xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

0394d77f7686ae81162fc08c23ef262c53dfe6b7

32

py

Python

matchzoo/datasets/cqa_ql_16/__init__.py

baajur/MatchZoo

fe0ccdd82500d116a7f945539ed05566fce90434

[ "Apache-2.0" ]

2,209

2018-10-15T08:31:35.000Z

2022-03-31T14:29:11.000Z

matchzoo/datasets/cqa_ql_16/__init__.py

baajur/MatchZoo

fe0ccdd82500d116a7f945539ed05566fce90434

[ "Apache-2.0" ]

398

2018-10-15T07:35:01.000Z

2022-03-13T21:31:26.000Z

matchzoo/datasets/cqa_ql_16/__init__.py

baajur/MatchZoo

fe0ccdd82500d116a7f945539ed05566fce90434

[ "Apache-2.0" ]

535

2018-10-16T09:29:02.000Z

2022-03-31T02:12:52.000Z

from .load_data import load_data

32

0.875

6

32

4.333333

0.666667

0.615385

0

0.09375

32

1

32

0.896552

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

03b5740d86f67787dc1db47fecaf44795633b670

66,015

py

Python

InterventionsMIP/reporting/plotting.py

haoxiangyang89/COVID_Staged_Alert

4c2cc5ef1d38c140875380a5f10a0fe1eaf8a47a

[ "MIT" ]

1

2021-06-24T19:27:01.000Z

InterventionsMIP/reporting/plotting.py

haoxiangyang89/COVID_Staged_Alert

4c2cc5ef1d38c140875380a5f10a0fe1eaf8a47a

[ "MIT" ]

null

InterventionsMIP/reporting/plotting.py

haoxiangyang89/COVID_Staged_Alert

4c2cc5ef1d38c140875380a5f10a0fe1eaf8a47a

[ "MIT" ]

3

2021-12-15T13:32:25.000Z

2022-02-24T13:57:07.000Z

''' Module for plotting function ''' import os import sys import numpy as np import pandas as pd import time import argparse import calendar as py_cal from pathlib import Path from matplotlib import pyplot as plt from matplotlib.ticker import FuncFormatter import matplotlib.dates as mdates import matplotlib.cbook as cbook from matplotlib import rc import matplotlib.patches as patches import matplotlib.colors as pltcolors from collections import defaultdict from utils import round_closest, roundup from InterventionsMIP import plots_path, instances_path import copy plt.rcParams['hatch.linewidth'] = 3.0 colors = {'S': 'b', 'E': 'y', 'IA': 'c', 'IY': 'm', 'IH': 'k', 'R': 'g', 'D': 'k', 'ToIHT': 'teal', 'ICU': 'k', 'ToICU': 'teal', 'IHT': 'k', 'ITot': 'k'} light_colors = {'IH':'silver','ToIHT':'paleturquoise', 'ICU':'silver', 'ToICU': 'paleturquoise', 'IHT': 'silver', 'ITot': 'silver'} l_styles = {'sim': '-', 'opt': '--'} compartment_names = { 'ITot': 'Total Infectious', 'IY': 'Symptomatic', 'IH': 'General Beds', 'ToIHT': 'COVID-19 Hospital Admissions\n(Seven-day Average)', 'D': 'Deaths', 'R': 'Recovered', 'S': 'Susceptible', 'ICU': 'COVID-19 ICU Patients', 'IHT': 'COVID-19 Hospitalizations', 'ToICU': 'Daily COVID-19 ICU Admissions' } def colorDecide(u,tier_by_tr): preCoded_color = ["blue","yellow","orange","red"] colorDict = {} for tKey in tier_by_tr.keys(): colorDict[tier_by_tr[tKey]["color"]] = tKey if u < colorDict["blue"]: return "white","" else: # if it is a color above blue, forced to be below red belowTier = -1 aboveTier = 2 for item in preCoded_color: if (u > colorDict[item])and(colorDict[item] >= belowTier): belowTier = colorDict[item] if (u < colorDict[item])and(colorDict[item] <= aboveTier): aboveTier = colorDict[item] aboveColor = pltcolors.to_rgb(tier_by_tr[aboveTier]["color"]) belowColor = pltcolors.to_rgb(tier_by_tr[belowTier]["color"]) ratio = (u - belowTier)/(aboveTier - belowTier) setcolor = ratio*np.array(aboveColor) + (1-ratio)*np.array(belowColor) return setcolor,tier_by_tr[aboveTier]["color"]+\ "_"+tier_by_tr[belowTier]["color"]+\ "_"+str(ratio) def find_central_path(city, states_to_plot_temp, states_ts_temp, real_hosp, real_icu, real_new_admission=None): ''' Obtains the central path id Args: TO DO ''' central_path_id = 0 weights_obs = 0.1 #0.005 weights = np.array(np.repeat((1 - weights_obs)/12, 12)) data_metrics = np.empty((300, 0), float) for v_t in states_to_plot_temp: data_metrics = np.append(data_metrics, np.max(states_ts_temp[v_t], axis = 1, keepdims = True), 1) data_metrics = np.append(data_metrics, np.argmax(states_ts_temp[v_t], axis = 1).reshape(len(states_ts_temp[v_t]), 1), 1) data_metrics = np.append(data_metrics, np.quantile(states_ts_temp[v_t], 0.5, axis = 1, keepdims = True), 1) data_metrics = np.append(data_metrics, np.sum(states_ts_temp[v_t], axis = 1, keepdims = True), 1) #Standardize std_data_metrics = (data_metrics - np.mean(data_metrics, axis=0)) / np.std(data_metrics, axis=0) errorlist1 = (np.square(std_data_metrics).dot(weights)).reshape(len(states_ts_temp['IHT']), 1) if city == 'austin': w = 7.3*(1 - 0.10896) + 9.9*0.10896 #Metric for deviations from the observed data if np.sum(real_hosp) > np.sum(real_icu): x_dev = np.mean(np.square((states_ts_temp['IHT'][:, 0:len(real_hosp)] - real_hosp[0:])), axis = 1, keepdims = True) z_dev = np.mean(np.square((states_ts_temp['ICU'][:, 0:len(real_icu)] - real_icu[0:])), axis = 1, keepdims = True) else: x_dev = np.mean(np.square((states_ts_temp['IHT'][:, 0:len(real_icu)] - real_icu[0:])), axis = 1, keepdims = True) z_dev = np.mean(np.square((states_ts_temp['ICU'][:, 0:len(real_hosp)] - real_hosp[0:])), axis = 1, keepdims = True) y_dev = np.mean(np.square((states_ts_temp['ToIHT'][:, 0:len(real_new_admission)] - real_new_admission[0:])), axis = 1, keepdims = True) errorlist2 = 1/(np.square(w))*x_dev + np.square(2.5)/(np.square(w))*z_dev + y_dev else: w = 7.3*(1 - 0.10896) + 9.9*0.10896 #Metric for deviations from the observed data if np.sum(real_hosp) > np.sum(real_icu): x_dev = np.mean(np.square((states_ts_temp['IHT'][:, 0:len(real_hosp)] - real_hosp[0:])), axis = 1, keepdims = True) z_dev = np.mean(np.square((states_ts_temp['ICU'][:, 0:len(real_icu)] - real_icu[0:])), axis = 1, keepdims = True) else: x_dev = np.mean(np.square((states_ts_temp['IHT'][:, 0:len(real_icu)] - real_icu[0:])), axis = 1, keepdims = True) z_dev = np.mean(np.square((states_ts_temp['ICU'][:, 0:len(real_hosp)] - real_hosp[0:])), axis = 1, keepdims = True) errorlist2 = 1/(np.square(w))*x_dev + np.square(2.5)/(np.square(w))*z_dev errorlist = (errorlist1 + weights_obs*errorlist2).tolist() central_path_id = errorlist.index(min(errorlist)) if central_path_id == 0: sorted_er = sorted(errorlist) central_path_id = errorlist.index(sorted_er[1]) print("central_path_id: ", central_path_id) return central_path_id def change_avg(all_st, min_st ,max_st, mean_st, nday_avg): # obtain the n-day average of the statistics all_st_copy = copy.deepcopy(all_st) min_st_copy = copy.deepcopy(min_st) max_st_copy = copy.deepcopy(max_st) mean_st_copy = copy.deepcopy(mean_st) # change all statistics to n-day average for v in all_st_copy.keys(): if v not in ['z', 'tier_history']: for i in range(len(all_st_copy[v])): for t in range(len(all_st_copy[v][i])): all_st_copy[v][i][t] = np.mean(all_st[v][i][np.maximum(t-nday_avg,0):t+1]) for t in range(len(min_st_copy[v])): min_st_copy[v][t] = np.mean(min_st[v][np.maximum(t-nday_avg,0):t+1]) for t in range(len(max_st_copy[v])): max_st_copy[v][t] = np.mean(max_st[v][np.maximum(t-nday_avg,0):t+1]) for t in range(len(mean_st_copy[v])): mean_st_copy[v][t] = np.mean(mean_st[v][np.maximum(t-nday_avg,0):t+1]) return all_st_copy,min_st_copy,max_st_copy,mean_st_copy def plot_multi_tier_sims(instance_name, instance, policy, profiles, profile_labels, real_hosp, plot_left_axis=['IH'], plot_right_axis=[], scale_plot=False, align_axes=True, show=True, plot_triggers=False, plot_trigger_annotations=False, plot_legend=False, y_lim=None, n_replicas=300, config=None, hosp_beds_list=None, real_new_admission=None, real_hosp_or_icu=None, bed_scale=1, is_representative_path=False, t_start = -1, central_path_id=0, cap_path_id=0, vertical_fill=True, nday_avg=None, **kwargs): ''' Plots a list of profiles in the same figure. Each profile corresponds to a stochastic replica for the given instance. Args: profiles (list of dict): a list of dictionaries that contain epi vars profiles profile_labels (list of str): name of each profile plot_only (list of str): list of variable names to be plot ''' plt.rcParams["font.size"] = "18" T = kwargs['T'] if "add_tiers" in kwargs.keys(): add_tiers = kwargs["add_tiers"] cal = instance.cal population = instance.N.sum() interventions = kwargs['interventions'] policy_params = kwargs['policy_params'] if hosp_beds_list is None: hosp_beds_list = [instance.hosp_beds] hosp_beds = hosp_beds_list[0] lb_band = 5 ub_band = 95 text_size = 28 fig, (ax1, actions_ax) = plt.subplots(2, 1, figsize=(17, 9), gridspec_kw={'height_ratios': [10, 1.1]}) # Main axis # ax1.set_xlabel('Time') ax2 = None # Policy axis policy_ax = ax1.twinx() #policy_ax.set_ylabel('Social Distance') # If there are plot to be on the right axis, move policy_ax # Second, show the right spine. if len(plot_right_axis) > 0: # Create second axis ax2 = ax1.twinx() # Fix policy axis policy_ax.spines["right"].set_position(("axes", 1.1)) make_patch_spines_invisible(policy_ax) policy_ax.spines["right"].set_visible(True) # Start plots max_y_lim_1 = population if 'S' in plot_left_axis or 'R' in plot_left_axis else 0 max_y_lim_2 = population if 'S' in plot_right_axis or 'R' in plot_right_axis else 0 plotted_lines = [] # Add IHT field if 'ICU' in profiles[0].keys(): for p in profiles: p['IHT'] = p['IH'] + p['ICU'] # Transform data of interest states_to_plot = plot_left_axis + plot_right_axis last_day_hosp_data = len(real_hosp) - 1 lb_hosp = real_hosp[-1] * (1 - config['div_filter_frac']) ub_hosp = real_hosp[-1] * (1 + config['div_filter_frac']) states_ts = {v: np.vstack(list(np.sum(p[v], axis=(1, 2))[:T] for p in profiles)) for v in states_to_plot} states_ts['z'] = np.vstack(list(p['z'][:T] for p in profiles)) states_ts['tier_history'] = np.vstack(list(p['tier_history'][:T] for p in profiles)) states_to_plot_temp = ['IHT','ToIHT', 'ICU'] states_ts_temp = {v: np.vstack(list(np.sum(p[v], axis=(1, 2))[:T] for p in profiles)) for v in states_to_plot_temp} central_path = 0 representative_path_id = 0 print("Printed seed is: ", profiles[0]["seed"]) if is_representative_path == False: central_path = central_path_id mean_st = {v: states_ts[v][central_path] if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts} else: representative_path_id = find_central_path(instance.city, states_to_plot_temp, states_ts_temp, real_hosp, real_hosp_or_icu, real_new_admission) mean_st = {v: states_ts[v][representative_path_id] if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts} central_path = representative_path_id cap_path_id = representative_path_id all_st = {v: states_ts[v][:] if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts} min_st = { v: np.percentile(states_ts[v], q=lb_band, axis=0) if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts } max_st = { v: np.percentile(states_ts[v], q=ub_band, axis=0) if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts } if nday_avg is not None: all_st, min_st ,max_st, mean_st = change_avg(all_st, min_st ,max_st, mean_st, nday_avg) # People that arrive above capacity # np.mean(np.sum(states_ts['IYIH']*(states_ts['IH']>=3239) , 1)) new_profiles = [mean_st, min_st, max_st] # Stats all_states = ['S', 'E', 'IH', 'IA', 'IY', 'R', 'D'] if 'ICU' in profiles[0].keys(): all_states.append('ICU') all_states.append('IHT') all_states.append('ToICU') all_states_ts = {v: np.vstack(list(np.sum(p[v], axis=(1, 2))[:T] for p in profiles)) for v in all_states} #assert len(all_states_ts['IH']) >= n_replicas for v in all_states_ts: all_states_ts[v] = all_states_ts[v][:n_replicas] #assert len(all_states_ts['IH']) == n_replicas # Hospitalizations Report # Probabilities of reaching x% of the capacity prob50 = np.sum(np.any(all_states_ts['IH'] >= 0.5 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob60 = np.sum(np.any(all_states_ts['IH'] >= 0.6 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob70 = np.sum(np.any(all_states_ts['IH'] >= 0.7 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob80 = np.sum(np.any(all_states_ts['IH'] >= 0.8 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob90 = np.sum(np.any(all_states_ts['IH'] >= 0.9 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob100 = np.sum(np.any(all_states_ts['IH'] >= 1 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob110 = np.sum(np.any(all_states_ts['IH'] >= 1.1 * hosp_beds, axis=1)) / len(all_states_ts['IH']) n_replicas_used = len(all_states_ts['IH']) print(f"{'P 50':10s}{'P 60':10s}{'P 70':10s}{'P 80':10s}{'P 90':10s}{'P 100':10s}{'P 110':10s}{'Scenarios':10s}") print( f"{prob50:<10.4f}{prob60:<10.4f}{prob70:<10.4f}{prob80:<10.4f}{prob90:<10.4f}{prob100:<10.4f}{prob110:<10.4f}{n_replicas_used}" ) # Min, Med, Max at the peak print('Hospitalization Peaks') peak_days = np.argmax(all_states_ts['IH'], axis=1) peak_vals = np.take_along_axis(all_states_ts['IH'], peak_days[:, None], axis=1) print(f'{"Percentile (%)":<15s} {"Peak IH":<15s} {"Date":15}') for q in [0, 5, 10, 50, 90, 100]: peak_day_percentile = int(np.percentile(peak_days, q)) peak_percentile = np.percentile(peak_vals, q) print(f'{q:<15} {peak_percentile:<15.0f} {str(cal.calendar[peak_day_percentile])}') # Deaths all_states_ts_ind = { v: np.array(list(p[v][:T, :, :] for p in profiles)) for v in all_states } #assert len(all_states_ts_ind['IH']) >= n_replicas for v in all_states_ts: all_states_ts_ind[v] = all_states_ts_ind[v][:n_replicas] #assert len(all_states_ts_ind['IH']) == n_replicas # Deaths data avg_deaths_by_group = np.round(np.mean(all_states_ts_ind['D'][:, -1, :, :], axis=0).reshape((10, 1)), 0) Median_deaths = np.round(np.percentile(np.sum(all_states_ts_ind['D'][:, -1, :, :], axis=(1, 2)), 50)) CI5_deaths = np.round(np.percentile(np.sum(all_states_ts_ind['D'][:, -1, :, :], axis=(1, 2)), lb_band)) CI95_deaths = np.round(np.percentile(np.sum(all_states_ts_ind['D'][:, -1, :, :], axis=(1, 2)), ub_band)) print('Deaths End Horizon') print(f'Point forecast {all_states_ts["D"][0][-1]}') print(f'Mean {avg_deaths_by_group.sum()} Median:{Median_deaths} CI_5_95:[{CI5_deaths}-{CI95_deaths}]') print('Fraction by Age and Risk Group (1-5, L-H)') print(100 * avg_deaths_by_group.reshape(5, 2) / avg_deaths_by_group.sum()) R_mean = np.mean(all_states_ts['R'][:, -1] / population) print(f'R End Horizon {R_mean}') # Policy lockdown_threshold = policy.lockdown_thresholds[0] # fdmi = policy_params['first_day_month_index'] # policy = {(m, y): lockdown_threshold[fdmi[m, y]] for (m, y) in fdmi if fdmi[m, y] < T} # print('Lockdown Threshold:') # print(policy) hide = 1 l_style = l_styles['sim'] for v in plot_left_axis: max_y_lim_1 = np.maximum(max_y_lim_1, np.max(max_st[v])) label_v = compartment_names[v] if v != 'IYIHa': v_a = ax1.plot(mean_st[v].T * bed_scale, c=colors[v], linestyle=l_style, linewidth=2, label=label_v, alpha=1 * hide, zorder = 50) plotted_lines.append(v_a[0]) v_aa = ax1.plot(all_st[v].T * bed_scale, c=light_colors[v], linestyle=l_style, linewidth=1, label=label_v, alpha=0.8 * hide) plotted_lines.append(v_aa[0]) #if central_path != 0: # ax1.fill_between(range(len(max_st[v])), # max_st[v], # min_st[v], # color=colors[v], # linestyle=l_style, # facecolor="none", # linewidth=0.0, # alpha=0.5 * hide) if v == 'IH' or v == 'ICU' or v == 'IHT' or v == 'ITot': real_h_plot = ax1.scatter(range(len(real_hosp_or_icu)), real_hosp_or_icu, color='maroon', label='Actual hospitalizations',zorder=100,s=15) max_y_lim_1 = np.maximum(roundup(np.max(hosp_beds_list), 100), max_y_lim_1) try: if v == 'IH' or v == 'IHT': ax1.plot(profiles[cap_path_id]['capacity'][:T], color='k', linestyle='-', linewidth=3) else: for hosp_beds_lines in hosp_beds_list: ax1.hlines(hosp_beds_lines, 0, T, color='k', linestyle='-', linewidth=3) except: for hosp_beds_lines in hosp_beds_list: ax1.hlines(hosp_beds_lines, 0, T, color='k', linestyle='-', linewidth=3) xpos = 30 #440 #200 # 440 if plot_trigger_annotations: ax1.annotate('Hospital capacity', (xpos, hosp_beds + 150), xycoords='data', color=colors[v], annotation_clip=True, fontsize=text_size + 2) # if plot_triggers: ax1.hlines(policy_params['hosp_beds'] * 0.6, 0, T, 'b', '-', linewidth=3) for tier_ix, tier in enumerate(policy.tiers): ax1.plot([policy.lockdown_thresholds[tier_ix][0]]*T, color=tier['color'], linewidth=5) xpos = np.minimum(405, int(T * 0.65)) #180 #405 xytext = (xpos, lockdown_threshold[xpos] - 20) if plot_trigger_annotations: ax1.annotate('Safety threshold', (xpos, policy_params['hosp_level_release'] - 250), xycoords='data', color='b', annotation_clip=True, fontsize=text_size + 2) if v == 'ToIHT' or v == 'ToICU': if v == 'ToIHT': if real_new_admission is not None: real_h_plot = ax1.scatter(range(len(real_new_admission)), real_new_admission, color='maroon', label='New hospital admission',zorder=100,s=15) if plot_triggers and vertical_fill: #if central_path > 0: # IYIH_mov_ave = [] # for t in range(T): # IYIH_mov_ave.append(np.mean(mean_st[v][np.maximum(0, t - 7):t])) # v_avg = ax1.plot(IYIH_mov_ave, c='black', linestyle=l_style, label=f'Moving Avg. {label_v}') # plotted_lines.append(v_avg[0]) for tier_ix, tier in enumerate(policy.tiers): ax1.plot([policy.lockdown_thresholds[tier_ix][0]]*T, color=tier['color'], linewidth=5) xpos = np.minimum(405, int(T * 0.65)) #180 #405 xytext = (xpos, lockdown_threshold[xpos] - 20) if plot_trigger_annotations: ax1.annotate('Lock-down threshold', xy=(120, lockdown_threshold[120]), xytext=xytext, xycoords='data', textcoords='data', color='b', annotation_clip=True, fontsize=text_size + 2) if "plot_ACS_triggers" in kwargs.keys(): if kwargs["plot_ACS_triggers"]: ax1.plot([policy.acs_thrs]*T, color='k', linewidth=5) for v in plot_right_axis: max_y_lim_2 = np.maximum(max_y_lim_2, np.max(max_st[v])) label_v = compartment_names[v] v_a = ax2.plot(mean_st[v].T, c=colors[v], linestyle=l_style, label=label_v) plotted_lines.append(v_a[0]) ax2.fill_between(range(T), min_st[v], max_st[v], color=colors[v], linestyle=l_style, alpha=0.5) if v == 'IH': max_y_lim_2 = np.maximum(roundup(hosp_beds, 100), max_y_lim_2) ax2.hlines(hosp_beds, 0, T, color='r', linestyle='--', label='N. of beds') if plot_triggers: ax2.hlines(policy_params['hosp_level_release'], 0, T, 'b', '--') ax2.annotate('Trigger - Current hospitalizations ', (0.05, 0.78 * policy_params['hosp_level_release'] / max_y_lim_1), xycoords='axes fraction', color='b', annotation_clip=True) if v == 'ToIHT': if plot_triggers: ax2.plot(lockdown_threshold[:T], 'b-') xytext = (160, lockdown_threshold[160] - 15) ax2.annotate('Trigger - Avg. Daily Hospitalization', xy=(120, lockdown_threshold[120]), xytext=xytext, xycoords='data', textcoords='data', color='b', annotation_clip=True) # ax2.annotate(' ', # xy=(85, lockdown_threshold[85]), # xytext=xytext, # xycoords='data', # textcoords='data', # arrowprops={'arrowstyle': '-|>'}, # color='b', # annotation_clip=True) # Plotting the policy # Plot school closure and cocooning tiers = policy.tiers z_ts = profiles[central_path]['z'][:T] tier_h = profiles[central_path]['tier_history'][:T] print('seed was', profiles[central_path]['seed']) sc_co = [interventions[k].school_closure for k in z_ts] unique_policies = set(sc_co) sd_lvl = [interventions[k].social_distance for k in z_ts] sd_levels = [tier['transmission_reduction'] for tier in tiers] + [0, 0.95] + sd_lvl unique_sd_policies = list(set(sd_levels)) unique_sd_policies.sort() intervals = {u: [False for t in range(len(z_ts) + 1)] for u in unique_policies} intervals_sd = {u: [False for t in range(len(z_ts) + 1)] for u in unique_sd_policies} for t in range(len(z_ts)): sc_co_t = interventions[z_ts[t]].school_closure for u in unique_policies: if u == sc_co_t: intervals[u][t] = True intervals[u][t + 1] = True for u_sd in unique_sd_policies: if u_sd == interventions[z_ts[t]].social_distance: intervals_sd[u_sd][t] = True intervals_sd[u_sd][t + 1] = True interval_color = {0: 'orange', 1: 'purple', 0.5: 'green'} interval_labels = {0: 'Schools Open', 1: 'Schools Closed', 0.5: 'Schools P. Open'} interval_alpha = {0: 0.3, 1: 0.3, 0.5: 0.3} for u in unique_policies: u_color = interval_color[u] u_label = interval_labels[u] actions_ax.fill_between( range(len(z_ts) + 1), 0, 1, where=intervals[u], color='white', #u_color, alpha=0, #interval_alpha[u], label=u_label, linewidth=0, hatch = '/', step='pre') # for kv in interval_labels: # kv_label = interval_labels[kv] # kv_color = interval_color[kv] # kv_alpha = interval_alpha[kv] # actions_ax.fill_between(range(len(z_ts) + 1), # 0, # 0.0001, # color=kv_color, # alpha=kv_alpha, # label=kv_label, # linewidth=0, # step='pre') sd_labels = { 0: '', 0.95: 'Initial lock-down', } sd_labels.update({tier['transmission_reduction']: tier['name'] for tier in tiers}) tier_by_tr = {tier['transmission_reduction']: tier for tier in tiers} tier_by_tr[0.746873309820472] = { "name": 'Ini Lockdown', "transmission_reduction": 0.95, "cocooning": 0.95, "school_closure": 1, "min_enforcing_time": 0, "daily_cost": 0, "color": 'darkgrey' } if "add_tiers" in kwargs.keys(): for add_t in add_tiers.keys(): tier_by_tr[add_t] = {"color": add_tiers[add_t], "name": "added stage"} if align_axes: max_y_lim_1 = np.maximum(max_y_lim_1, max_y_lim_2) max_y_lim_2 = max_y_lim_1 if y_lim is not None: max_y_lim_1 = y_lim else: max_y_lim_1 = roundup(max_y_lim_1, 100 if 'ToIHT' in plot_left_axis else 1000) if vertical_fill: for u in unique_sd_policies: try: if u in tier_by_tr.keys(): u_color = tier_by_tr[u]['color'] u_label = f'{tier_by_tr[u]["name"]}' if u > 0 else "" else: u_color,u_label = colorDecide(u,tier_by_tr) u_alpha1 = 0.6 u_alpha2 = 0.6 fill_1 = intervals_sd[u].copy() fill_2 = intervals_sd[u].copy() for i in range(len(intervals_sd[u])): if 'history_white' in kwargs.keys() and kwargs['history_white']: if i <= t_start: fill_2[i] = False fill_1[i] = False else: if i <= t_start: fill_2[i] = False else: fill_1[i] = False policy_ax.fill_between(range(len(z_ts) + 1), 0, 1, where=fill_1, color=u_color, alpha=u_alpha1, label=u_label, linewidth=0.0, step='pre') policy_ax.fill_between(range(len(z_ts) + 1), 0, 1, where=fill_2, color=u_color, alpha=u_alpha2, label=u_label, linewidth=0.0, step='pre') except Exception: print(f'WARNING: TR value {u} was not plotted') else: # fill the horizontal policy color for ti in range(len(tiers)): u = tiers[ti]['transmission_reduction'] if u in tier_by_tr.keys(): u_color = tier_by_tr[u]['color'] u_label = f'{tier_by_tr[u]["name"]}' if u > 0 else "" else: u_color,u_label = colorDecide(u,tier_by_tr) u_alpha = 0.6 u_lb = policy.lockdown_thresholds[ti][0] u_ub = policy.lockdown_thresholds_ub[ti][0] if u_ub == np.inf: u_ub = max_y_lim_1 if u_lb >= 0 and u_ub >= 0: policy_ax.fill_between(range(len(z_ts) + 1), u_lb/max_y_lim_1, u_ub/max_y_lim_1, color=u_color, alpha=u_alpha, label=u_label, linewidth=0.0, step='pre') if "acs_fill" in kwargs.keys(): # fill the ACS plot policy_ax.fill_between(range(len(z_ts) + 1), 0, 1, color='white', linewidth=0.0, step='pre') policy_ax.fill_between(range(len(z_ts) + 1), 0, hosp_beds/max_y_lim_1, color='lightgreen', alpha=0.6, linewidth=0.0, step='pre') fill_acs = [False]*(len(z_ts) + 1) acs_rec = -1 acs_date = [] for tind in range(T): if profiles[cap_path_id]['capacity'][tind] > hosp_beds: acs_date.append(tind) fill_acs[tind] = True acs_rec = profiles[cap_path_id]['capacity'][tind] ax1.plot(acs_date,[hosp_beds]*len(acs_date),color='gray', linestyle='-', linewidth=1) if acs_rec > 0: policy_ax.fill_between(range(len(z_ts) + 1), hosp_beds/max_y_lim_1, acs_rec/max_y_lim_1, where = fill_acs, color='forestgreen', alpha=0.6, linewidth=0.0, step='pre') # # Plot again for consolidated legend # for u in sd_alphas: # u_label = sd_labels[u] # policy_ax.fill_between(range(len(z_ts) + 1), # 0, # 0.0001, # color=u_color, # alpha=sd_alphas[u], # label=u_label, # linewidth=0, # step='pre') # Plot social distance social_distance = [interventions[k].social_distance for k in z_ts] #policy_ax.plot(social_distance, c='k', alpha=0.6 * hide) # marker='_', linestyle='None', hsd = np.sum(np.array(social_distance[:T]) >= 0.78) print(f'HIGH SOCIAL DISTANCE') print(f'Point Forecast: {hsd}') hsd_list = np.array( [np.sum(np.array([interventions[k].social_distance for k in z_ts]) >= 0.78) for z_ts in states_ts['z']]) count_lockdowns = defaultdict(int) for z_ts in states_ts['z']: n_lockdowns = 0 for ix_k in range(1, len(z_ts)): if interventions[z_ts[ix_k]].social_distance - interventions[z_ts[ix_k - 1]].social_distance > 0: n_lockdowns += 1 count_lockdowns[n_lockdowns] += 1 print( f'Mean: {np.mean(hsd_list):.2f} Median: {np.percentile(hsd_list,q=50)} - SD CI_5_95: {np.percentile(hsd_list,q=5)}-{np.percentile(hsd_list,q=95)}' ) for nlock in count_lockdowns: print(f'Prob of having exactly {nlock} lockdowns: {count_lockdowns[nlock]/len(states_ts["z"]):4f}') unique_social_distance = np.unique(social_distance) # for usd in unique_social_distance: # if usd > 0: # offset = {0.1: -0.03, 0.2: -0.03, 0.4: -0.03, 0.6: -0.03, 0.8: -0.03, 0.9: 0.02}[usd] # policy_ax.annotate(f'{int(usd*100)}% social distance', (0.07, usd + offset), # xycoords='axes fraction', # color='k', # annotation_clip=True) # # START PLOT STYLING # Axis limits ax1.set_ylim(0, max_y_lim_1) if ax2 is not None: ax2.set_ylim(0, roundup(max_y_lim_2, 1000)) policy_ax.set_ylim(0, 1) # plot a vertical line for the t_start plt.vlines(t_start, 0, max_y_lim_1, colors='k',linewidth = 3) # Axis format and names ax1.set_ylabel(" / ".join((compartment_names[v] for v in plot_left_axis)), fontsize=text_size) if ax2 is not None: ax2.set_ylabel(compartment_names[plot_right_axis[0]]) # Axis ticks ax1.xaxis.set_ticks([t for t, d in enumerate(cal.calendar) if (d.day == 1 and t < T)]) ax1.xaxis.set_ticklabels( [f' {py_cal.month_abbr[d.month]} ' for t, d in enumerate(cal.calendar) if (d.day == 1 and t < T)], rotation=0, fontsize=22) for tick in ax1.xaxis.get_major_ticks(): #tick.tick1line.set_markersize(0) #tick.tick2line.set_markersize(0) tick.label1.set_horizontalalignment('left') ax1.tick_params(axis='y', labelsize=text_size, length=5, width=2) ax1.tick_params(axis='x', length=5, width=2) # Policy axis span 0 - 1 #policy_ax.yaxis.set_ticks(np.arange(0, 1.001, 0.1)) policy_ax.tick_params( axis='both', # changes apply to the x-axis which='both', # both major and minor ticks are affected bottom=False, # ticks along the bottom edge are off right=False, # ticks along the top edge are off labelbottom=False, labelright=False) # labels along the bottom edge are off actions_ax.tick_params( axis='both', # changes apply to the x-axis which='both', # both major and minor ticks are affected bottom=False, # ticks along the bottom edge are off left=False, # ticks along the top edge are off labelbottom=False, labelleft=False) # labels along the bottom edge are off actions_ax.spines['top'].set_visible(False) actions_ax.spines['bottom'].set_visible(False) actions_ax.spines['left'].set_visible(False) actions_ax.spines['right'].set_visible(False) # if 321 <= T: # # line to separate years # actions_ax.axvline(321, 0, 1, color='k', alpha=0.3) if 140 <= T: actions_ax.annotate('2020', xy=(140, 0), xycoords='data', color='k', annotation_clip=True, fontsize=text_size - 2) if 425 <= T: actions_ax.annotate('2021', xy=(425, 0), xycoords='data', color='k', annotation_clip=True, fontsize=text_size - 2) # Order of layers ax1.set_zorder(policy_ax.get_zorder() + 10) # put ax in front of policy_ax ax1.patch.set_visible(False) # hide the 'canvas' if ax2 is not None: ax2.set_zorder(policy_ax.get_zorder() + 5) # put ax in front of policy_ax ax2.patch.set_visible(False) # hide the 'canvas' # Plot margins ax1.margins(0) actions_ax.margins(0) if ax2 is not None: ax2.margins(0) policy_ax.margins(0.) # Plot Grid #ax1.grid(True, which='both', color='grey', alpha=0.1, linewidth=0.5, zorder=0) # fig.delaxes(ax1[1, 2]) if plot_legend: handles_ax1, labels_ax1 = ax1.get_legend_handles_labels() handles_ax2, labels_ax2 = ax2.get_legend_handles_labels() if ax2 is not None else ([], []) handles_action_ax, labels_action_ax = actions_ax.get_legend_handles_labels() handles_policy_ax, labels_policy_ax = policy_ax.get_legend_handles_labels() plotted_labels = [pl.get_label() for pl in plotted_lines] if 'ToIHT' in plot_left_axis or True: fig_legend = ax1.legend( plotted_lines + handles_policy_ax + handles_action_ax, plotted_labels + labels_policy_ax + labels_action_ax, loc='upper right', fontsize=text_size + 2, #bbox_to_anchor=(0.90, 0.9), prop={'size': text_size}, framealpha=1) elif 'IH' in plot_left_axis: fig_legend = ax1.legend( handles_ax1, labels_ax1, loc='upper right', fontsize=text_size + 2, #bbox_to_anchor=(0.90, 0.9), prop={'size': text_size}, framealpha=1) fig_legend.set_zorder(4) plt.tight_layout() plt.subplots_adjust(hspace=0) plots_left_right = plot_left_axis + plot_right_axis plot_filename = plots_path / f'scratch_{instance_name}_{"".join(plots_left_right)}.pdf' plt.savefig(plot_filename) if show: plt.show() plt.close() return plot_filename def stack_plot(instance_name, instance, policy, profiles, profile_labels, real_hosp, plot_left_axis=['IH'], plot_right_axis=[], scale_plot=False, align_axes=True, show=True, plot_triggers=False, plot_trigger_annotations=False, plot_legend=False, y_lim=None, n_replicas=300, config=None, hosp_beds_list=None, real_new_admission=None, real_hosp_or_icu=None, bed_scale=1, is_representative_path=False, t_start = -1, central_path_id=0, cap_path_id=0, **kwargs): ''' Plots a list of profiles in the same figure. Each profile corresponds to a stochastic replica for the given instance. Args: profiles (list of dict): a list of dictionaries that contain epi vars profiles profile_labels (list of str): name of each profile plot_only (list of str): list of variable names to be plot ''' plt.rcParams["font.size"] = "18" T = kwargs['T'] if "add_tiers" in kwargs.keys(): add_tiers = kwargs["add_tiers"] cal = instance.cal population = instance.N.sum() interventions = kwargs['interventions'] policy_params = kwargs['policy_params'] if hosp_beds_list is None: hosp_beds_list = [instance.hosp_beds] hosp_beds = hosp_beds_list[0] lb_band = 5 ub_band = 95 text_size = 28 fig, (ax1, actions_ax) = plt.subplots(2, 1, figsize=(17, 9), gridspec_kw={'height_ratios': [10, 1.1]}) # Main axis # ax1.set_xlabel('Time') ax2 = None # Policy axis policy_ax = ax1.twinx() #policy_ax.set_ylabel('Social Distance') # If there are plot to be on the right axis, move policy_ax # Second, show the right spine. if len(plot_right_axis) > 0: # Create second axis ax2 = ax1.twinx() # Fix policy axis policy_ax.spines["right"].set_position(("axes", 1.1)) make_patch_spines_invisible(policy_ax) policy_ax.spines["right"].set_visible(True) # Start plots max_y_lim_1 = population if 'S' in plot_left_axis or 'R' in plot_left_axis else 0 max_y_lim_2 = population if 'S' in plot_right_axis or 'R' in plot_right_axis else 0 plotted_lines = [] # Add IHT field if 'ICU' in profiles[0].keys(): for p in profiles: p['IHT'] = p['IH'] + p['ICU'] # Transform data of interest states_to_plot = plot_left_axis + plot_right_axis last_day_hosp_data = len(real_hosp) - 1 lb_hosp = real_hosp[-1] * (1 - config['div_filter_frac']) ub_hosp = real_hosp[-1] * (1 + config['div_filter_frac']) states_ts = {v: np.vstack(list(np.sum(p[v], axis=(1, 2))[:T] for p in profiles)) for v in states_to_plot} states_ts['z'] = np.vstack(list(p['z'][:T] for p in profiles)) states_ts['tier_history'] = np.vstack(list(p['tier_history'][:T] for p in profiles)) if states_to_plot[0] == 'IH': states_to_plot_temp = ['ToIHT'] states_ts_temp = {v: np.vstack(list(np.sum(p[v], axis=(1, 2))[:T] for p in profiles)) for v in states_to_plot_temp} else: states_to_plot_temp = ['IH'] states_ts_temp = {v: np.vstack(list(np.sum(p[v], axis=(1, 2))[:T] for p in profiles)) for v in states_to_plot_temp} central_path = 0 representative_path_id = 0 print("Printed seed is: ", profiles[0]["seed"]) if is_representative_path == False: central_path = central_path_id mean_st = {v: states_ts[v][central_path] if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts} else: representative_path_id = find_central_path(instance.city, states_to_plot_temp, states_ts_temp, real_hosp, real_hosp_or_icu, real_new_admission) mean_st = {v: states_ts[v][representative_path_id] if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts} central_path = representative_path_id cap_path_id = representative_path_id all_st = {v: states_ts[v][:] if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts} min_st = { v: np.percentile(states_ts[v], q=lb_band, axis=0) if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts } max_st = { v: np.percentile(states_ts[v], q=ub_band, axis=0) if v not in ['z', 'tier_history'] else states_ts[v] for v in states_ts } # People that arrive above capacity # np.mean(np.sum(states_ts['IYIH']*(states_ts['IH']>=3239) , 1)) new_profiles = [mean_st, min_st, max_st] # Stats all_states = ['S', 'E', 'IH', 'IA', 'IY', 'R', 'D'] if 'ICU' in profiles[0].keys(): all_states.append('ICU') all_states.append('IHT') all_states.append('ToICU') all_states_ts = {v: np.vstack(list(np.sum(p[v], axis=(1, 2))[:T] for p in profiles)) for v in all_states} #assert len(all_states_ts['IH']) >= n_replicas for v in all_states_ts: all_states_ts[v] = all_states_ts[v][:n_replicas] #assert len(all_states_ts['IH']) == n_replicas # Hospitalizations Report # Probabilities of reaching x% of the capacity prob50 = np.sum(np.any(all_states_ts['IH'] >= 0.5 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob60 = np.sum(np.any(all_states_ts['IH'] >= 0.6 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob70 = np.sum(np.any(all_states_ts['IH'] >= 0.7 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob80 = np.sum(np.any(all_states_ts['IH'] >= 0.8 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob90 = np.sum(np.any(all_states_ts['IH'] >= 0.9 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob100 = np.sum(np.any(all_states_ts['IH'] >= 1 * hosp_beds, axis=1)) / len(all_states_ts['IH']) prob110 = np.sum(np.any(all_states_ts['IH'] >= 1.1 * hosp_beds, axis=1)) / len(all_states_ts['IH']) n_replicas_used = len(all_states_ts['IH']) print(f"{'P 50':10s}{'P 60':10s}{'P 70':10s}{'P 80':10s}{'P 90':10s}{'P 100':10s}{'P 110':10s}{'Scenarios':10s}") print( f"{prob50:<10.4f}{prob60:<10.4f}{prob70:<10.4f}{prob80:<10.4f}{prob90:<10.4f}{prob100:<10.4f}{prob110:<10.4f}{n_replicas_used}" ) # Min, Med, Max at the peak print('Hospitalization Peaks') peak_days = np.argmax(all_states_ts['IH'], axis=1) peak_vals = np.take_along_axis(all_states_ts['IH'], peak_days[:, None], axis=1) print(f'{"Percentile (%)":<15s} {"Peak IH":<15s} {"Date":15}') for q in [0, 5, 10, 50, 90, 100]: peak_day_percentile = int(np.percentile(peak_days, q)) peak_percentile = np.percentile(peak_vals, q) print(f'{q:<15} {peak_percentile:<15.0f} {str(cal.calendar[peak_day_percentile])}') # Deaths all_states_ts_ind = { v: np.array(list(p[v][:T, :, :] for p in profiles)) for v in all_states } #assert len(all_states_ts_ind['IH']) >= n_replicas for v in all_states_ts: all_states_ts_ind[v] = all_states_ts_ind[v][:n_replicas] #assert len(all_states_ts_ind['IH']) == n_replicas # Deaths data avg_deaths_by_group = np.round(np.mean(all_states_ts_ind['D'][:, -1, :, :], axis=0).reshape((10, 1)), 0) Median_deaths = np.round(np.percentile(np.sum(all_states_ts_ind['D'][:, -1, :, :], axis=(1, 2)), 50)) CI5_deaths = np.round(np.percentile(np.sum(all_states_ts_ind['D'][:, -1, :, :], axis=(1, 2)), lb_band)) CI95_deaths = np.round(np.percentile(np.sum(all_states_ts_ind['D'][:, -1, :, :], axis=(1, 2)), ub_band)) print('Deaths End Horizon') print(f'Point forecast {all_states_ts["D"][0][-1]}') print(f'Mean {avg_deaths_by_group.sum()} Median:{Median_deaths} CI_5_95:[{CI5_deaths}-{CI95_deaths}]') print('Fraction by Age and Risk Group (1-5, L-H)') print(100 * avg_deaths_by_group.reshape(5, 2) / avg_deaths_by_group.sum()) R_mean = np.mean(all_states_ts['R'][:, -1] / population) print(f'R End Horizon {R_mean}') # Policy lockdown_threshold = policy.lockdown_thresholds[0] # fdmi = policy_params['first_day_month_index'] # policy = {(m, y): lockdown_threshold[fdmi[m, y]] for (m, y) in fdmi if fdmi[m, y] < T} # print('Lockdown Threshold:') # print(policy) central_path = central_path_id hide = 1 l_style = l_styles['sim'] for v in plot_left_axis: max_y_lim_1 = np.maximum(max_y_lim_1, np.max(max_st[v])) label_v = compartment_names[v] if v != 'IYIHa': v_a = ax1.plot(mean_st[v].T * bed_scale, c=colors[v], linestyle=l_style, linewidth=2, label=label_v, alpha=1 * hide, zorder = 50) plotted_lines.append(v_a[0]) v_aa = ax1.plot(all_st[v].T * bed_scale, c=light_colors[v], linestyle=l_style, linewidth=1, label=label_v, alpha=0.8 * hide) plotted_lines.append(v_aa[0]) #if central_path != 0: # ax1.fill_between(range(len(max_st[v])), # max_st[v], # min_st[v], # color=colors[v], # linestyle=l_style, # facecolor="none", # linewidth=0.0, # alpha=0.5 * hide) if v == 'IH' or v == 'ICU' or v == 'IHT': real_h_plot = ax1.scatter(range(len(real_hosp_or_icu)), real_hosp_or_icu, color='maroon', label='Actual hospitalizations',zorder=100,s=15) max_y_lim_1 = np.maximum(roundup(np.max(hosp_beds_list), 100), max_y_lim_1) try: if v == 'IH' or v == 'IHT': ax1.plot(profiles[0]['capacity'][:T], color='k', linestyle='-', linewidth=3) else: for hosp_beds_lines in hosp_beds_list: ax1.hlines(hosp_beds_lines, 0, T, color='k', linestyle='-', linewidth=3) except: for hosp_beds_lines in hosp_beds_list: ax1.hlines(hosp_beds_lines, 0, T, color='k', linestyle='-', linewidth=3) xpos = 30 #440 #200 # 440 if plot_trigger_annotations: ax1.annotate('Hospital capacity', (xpos, hosp_beds + 150), xycoords='data', color=colors[v], annotation_clip=True, fontsize=text_size + 2) # if plot_triggers: ax1.hlines(policy_params['hosp_beds'] * 0.6, 0, T, 'b', '-', linewidth=3) if plot_trigger_annotations: ax1.annotate('Safety threshold', (xpos, policy_params['hosp_level_release'] - 250), xycoords='data', color='b', annotation_clip=True, fontsize=text_size + 2) if v == 'ToIHT' or v == 'ToICU': if v == 'ToIHT': if real_new_admission is not None: real_h_plot = ax1.scatter(range(len(real_new_admission)), real_new_admission, color='maroon', label='New hospital admission',zorder=100,s=15) if plot_triggers: #if central_path > 0: # IYIH_mov_ave = [] # for t in range(T): # IYIH_mov_ave.append(np.mean(mean_st[v][np.maximum(0, t - 7):t])) # v_avg = ax1.plot(IYIH_mov_ave, c='black', linestyle=l_style, label=f'Moving Avg. {label_v}') # plotted_lines.append(v_avg[0]) for tier_ix, tier in enumerate(policy.tiers): ax1.plot([policy.lockdown_thresholds[tier_ix][0]]*T, color=tier['color'], linewidth=5) xpos = np.minimum(405, int(T * 0.65)) #180 #405 xytext = (xpos, lockdown_threshold[xpos] - 20) if plot_trigger_annotations: ax1.annotate('Lock-down threshold', xy=(120, lockdown_threshold[120]), xytext=xytext, xycoords='data', textcoords='data', color='b', annotation_clip=True, fontsize=text_size + 2) if "plot_ACS_triggers" in kwargs.keys(): if kwargs["plot_ACS_triggers"]: ax1.plot([policy.acs_thrs]*T, color='k', linewidth=5) for v in plot_right_axis: max_y_lim_2 = np.maximum(max_y_lim_2, np.max(max_st[v])) label_v = compartment_names[v] v_a = ax2.plot(mean_st[v].T, c=colors[v], linestyle=l_style, label=label_v) plotted_lines.append(v_a[0]) ax2.fill_between(range(T), min_st[v], max_st[v], color=colors[v], linestyle=l_style, alpha=0.5) if v == 'IH': max_y_lim_2 = np.maximum(roundup(hosp_beds, 100), max_y_lim_2) ax2.hlines(hosp_beds, 0, T, color='r', linestyle='--', label='N. of beds') if plot_triggers: ax2.hlines(policy_params['hosp_level_release'], 0, T, 'b', '--') ax2.annotate('Trigger - Current hospitalizations ', (0.05, 0.78 * policy_params['hosp_level_release'] / max_y_lim_1), xycoords='axes fraction', color='b', annotation_clip=True) if v == 'ToIHT': if plot_triggers: ax2.plot(lockdown_threshold[:T], 'b-') xytext = (160, lockdown_threshold[160] - 15) ax2.annotate('Trigger - Avg. Daily Hospitalization', xy=(120, lockdown_threshold[120]), xytext=xytext, xycoords='data', textcoords='data', color='b', annotation_clip=True) # ax2.annotate(' ', # xy=(85, lockdown_threshold[85]), # xytext=xytext, # xycoords='data', # textcoords='data', # arrowprops={'arrowstyle': '-|>'}, # color='b', # annotation_clip=True) # Plotting the policy # Plot school closure and cocooning tiers = policy.tiers z_ts = profiles[central_path]['z'][:T] tier_h = profiles[central_path]['tier_history'][:T] print('seed was', profiles[central_path]['seed']) sc_co = [interventions[k].school_closure for k in z_ts] unique_policies = set(sc_co) sd_lvl = [interventions[k].social_distance for k in z_ts] sd_levels = [tier['transmission_reduction'] for tier in tiers] + [0, 0.95] + sd_lvl unique_sd_policies = list(set(sd_levels)) unique_sd_policies.sort() intervals = {u: [False for t in range(len(z_ts) + 1)] for u in unique_policies} intervals_sd = {u: [False for t in range(len(z_ts) + 1)] for u in unique_sd_policies} for t in range(len(z_ts)): sc_co_t = interventions[z_ts[t]].school_closure for u in unique_policies: if u == sc_co_t: intervals[u][t] = True intervals[u][t + 1] = True for u_sd in unique_sd_policies: if u_sd == interventions[z_ts[t]].social_distance: intervals_sd[u_sd][t] = True intervals_sd[u_sd][t + 1] = True interval_color = {0: 'orange', 1: 'purple', 0.5: 'green'} interval_labels = {0: 'Schools Open', 1: 'Schools Closed', 0.5: 'Schools P. Open'} interval_alpha = {0: 0.3, 1: 0.3, 0.5: 0.3} for u in unique_policies: u_color = interval_color[u] u_label = interval_labels[u] actions_ax.fill_between( range(len(z_ts) + 1), 0, 1, where=intervals[u], color='white', #u_color, alpha=0, #interval_alpha[u], label=u_label, linewidth=0, hatch = '/', step='pre') # for kv in interval_labels: # kv_label = interval_labels[kv] # kv_color = interval_color[kv] # kv_alpha = interval_alpha[kv] # actions_ax.fill_between(range(len(z_ts) + 1), # 0, # 0.0001, # color=kv_color, # alpha=kv_alpha, # label=kv_label, # linewidth=0, # step='pre') sd_labels = { 0: '', 0.95: 'Initial lock-down', } sd_labels.update({tier['transmission_reduction']: tier['name'] for tier in tiers}) tier_by_tr = {tier['transmission_reduction']: tier for tier in tiers} tier_by_tr[0.746873309820472] = { "name": 'Ini Lockdown', "transmission_reduction": 0.95, "cocooning": 0.95, "school_closure": 1, "min_enforcing_time": 0, "daily_cost": 0, "color": 'darkgrey' } if "add_tiers" in kwargs.keys(): for add_t in add_tiers.keys(): tier_by_tr[add_t] = {"color": add_tiers[add_t], "name": "added stage"} for u in unique_sd_policies: try: if u in tier_by_tr.keys(): u_color = tier_by_tr[u]['color'] u_label = f'{tier_by_tr[u]["name"]}' if u > 0 else "" else: u_color,u_label = colorDecide(u,tier_by_tr) u_alpha1 = 0.6 fill_1 = intervals_sd[u].copy() fill_2 = intervals_sd[u].copy() for i in range(len(intervals_sd[u])): if 'history_white' in kwargs.keys() and kwargs['history_white']: if i <= t_start: fill_2[i] = False fill_1[i] = False else: if i <= t_start: fill_2[i] = False else: fill_1[i] = False policy_ax.fill_between(range(len(z_ts) + 1), 0, 1, where=fill_1, color=u_color, alpha=u_alpha1, label=u_label, linewidth=0.0, step='pre') # policy_ax.fill_between(range(len(z_ts) + 1), # 0, # 1, # where=fill_2, # color=u_color, # alpha=u_alpha, # label=u_label, # linewidth=0.0, # step='pre') except Exception: print(f'WARNING: TR value {u} was not plotted') # Plot social distance social_distance = [interventions[k].social_distance for k in z_ts] #policy_ax.plot(social_distance, c='k', alpha=0.6 * hide) # marker='_', linestyle='None', hsd = np.sum(np.array(social_distance[:T]) >= 0.78) print(f'HIGH SOCIAL DISTANCE') print(f'Point Forecast: {hsd}') hsd_list = np.array( [np.sum(np.array([interventions[k].social_distance for k in z_ts]) >= 0.78) for z_ts in states_ts['z']]) count_lockdowns = defaultdict(int) for z_ts in states_ts['z']: n_lockdowns = 0 for ix_k in range(1, len(z_ts)): if interventions[z_ts[ix_k]].social_distance - interventions[z_ts[ix_k - 1]].social_distance > 0: n_lockdowns += 1 count_lockdowns[n_lockdowns] += 1 print( f'Mean: {np.mean(hsd_list):.2f} Median: {np.percentile(hsd_list,q=50)} - SD CI_5_95: {np.percentile(hsd_list,q=5)}-{np.percentile(hsd_list,q=95)}' ) for nlock in count_lockdowns: print(f'Prob of having exactly {nlock} lockdowns: {count_lockdowns[nlock]/len(states_ts["z"]):4f}') unique_social_distance = np.unique(social_distance) # START PLOT STYLING # Axis limits if align_axes: max_y_lim_1 = np.maximum(max_y_lim_1, max_y_lim_2) max_y_lim_2 = max_y_lim_1 if y_lim is not None: max_y_lim_1 = y_lim else: max_y_lim_1 = roundup(max_y_lim_1, 100 if 'ToIHT' in plot_left_axis else 1000) ax1.set_ylim(0, max_y_lim_1) policy_ax.set_ylim(0, 1) # plot the stacked part of the stage proportion ax3 = ax1.twinx() ax3.set_ylim(0, max_y_lim_1) data = states_ts['tier_history'].T tierColor = {} for tierInd in range(len(policy.tiers)): tierColor[tierInd] = (np.sum(data[(t_start+1):T,:] == tierInd, axis = 1)/len(data[0]))*max_y_lim_1 # #r = range(len(tier1)) r = range((t_start+1), T-1) bottomTier = 0 for tierInd in range(len(policy.tiers)): ax3.bar(r, tierColor[tierInd], color = policy.tiers[tierInd]['color'], bottom = bottomTier, label = 'tier{}'.format(tierInd), width = 1, alpha = 0.6, linewidth = 0) bottomTier += np.array(tierColor[tierInd]) # ax3.bar(r, tier2, color = 'blue', bottom = np.array(tier1), label = 'tier2', width = 1, alpha = 0.6, linewidth = 0) # ax3.bar(r, tier3, color = 'yellow', bottom = np.array(tier1) + np.array(tier2), label = 'tier3', width = 1, alpha = 0.6, linewidth = 0) # ax3.bar(r, tier4, color = 'orange', bottom = np.array(tier1) + np.array(tier2) + np.array(tier3), label = 'tier4', width = 1, alpha = 0.6, linewidth = 0) # ax3.bar(r, tier5, color = 'red', bottom = np.array(tier1) + np.array(tier2) + np.array(tier3) + np.array(tier4), label = 'tier5', width = 1, alpha = 0.6, linewidth = 0) ax3.set_yticks([]) if ax2 is not None: ax2.set_ylim(0, roundup(max_y_lim_2, 1000)) # plot a vertical line for the t_start plt.vlines(t_start, 0, max_y_lim_1, colors='k',linewidth = 3) # Axis format and names ax1.set_ylabel(" / ".join((compartment_names[v] for v in plot_left_axis)), fontsize=text_size) if ax2 is not None: ax2.set_ylabel(compartment_names[plot_right_axis[0]]) # Axis ticks ax1.xaxis.set_ticks([t for t, d in enumerate(cal.calendar) if (d.day == 1 and t < T)]) ax1.xaxis.set_ticklabels( [f' {py_cal.month_abbr[d.month]} ' for t, d in enumerate(cal.calendar) if (d.day == 1 and t < T)], rotation=0, fontsize=22) for tick in ax1.xaxis.get_major_ticks(): #tick.tick1line.set_markersize(0) #tick.tick2line.set_markersize(0) tick.label1.set_horizontalalignment('left') ax1.tick_params(axis='y', labelsize=text_size, length=5, width=2) ax1.tick_params(axis='x', length=5, width=2) # Policy axis span 0 - 1 #policy_ax.yaxis.set_ticks(np.arange(0, 1.001, 0.1)) policy_ax.tick_params( axis='both', # changes apply to the x-axis which='both', # both major and minor ticks are affected bottom=False, # ticks along the bottom edge are off right=False, # ticks along the top edge are off labelbottom=False, labelright=False) # labels along the bottom edge are off actions_ax.tick_params( axis='both', # changes apply to the x-axis which='both', # both major and minor ticks are affected bottom=False, # ticks along the bottom edge are off left=False, # ticks along the top edge are off labelbottom=False, labelleft=False) # labels along the bottom edge are off actions_ax.spines['top'].set_visible(False) actions_ax.spines['bottom'].set_visible(False) actions_ax.spines['left'].set_visible(False) actions_ax.spines['right'].set_visible(False) # if 321 <= T: # # line to separate years # actions_ax.axvline(321, 0, 1, color='k', alpha=0.3) if 140 <= T: actions_ax.annotate('2020', xy=(140, 0), xycoords='data', color='k', annotation_clip=True, fontsize=text_size - 2) if 425 <= T: actions_ax.annotate('2021', xy=(425, 0), xycoords='data', color='k', annotation_clip=True, fontsize=text_size - 2) # Order of layers ax1.set_zorder(policy_ax.get_zorder() + 10) # put ax in front of policy_ax ax1.patch.set_visible(False) # hide the 'canvas' if ax2 is not None: ax2.set_zorder(policy_ax.get_zorder() + 5) # put ax in front of policy_ax ax2.patch.set_visible(False) # hide the 'canvas' # Plot margins ax1.margins(0) actions_ax.margins(0) if ax2 is not None: ax2.margins(0) policy_ax.margins(0.) # Plot Grid #ax1.grid(True, which='both', color='grey', alpha=0.1, linewidth=0.5, zorder=0) # fig.delaxes(ax1[1, 2]) if plot_legend: handles_ax1, labels_ax1 = ax1.get_legend_handles_labels() handles_ax2, labels_ax2 = ax2.get_legend_handles_labels() if ax2 is not None else ([], []) handles_action_ax, labels_action_ax = actions_ax.get_legend_handles_labels() handles_policy_ax, labels_policy_ax = policy_ax.get_legend_handles_labels() plotted_labels = [pl.get_label() for pl in plotted_lines] if 'ToIHT' in plot_left_axis or True: fig_legend = ax1.legend( plotted_lines + handles_policy_ax + handles_action_ax, plotted_labels + labels_policy_ax + labels_action_ax, loc='upper right', fontsize=text_size + 2, #bbox_to_anchor=(0.90, 0.9), prop={'size': text_size}, framealpha=1) elif 'IH' in plot_left_axis: fig_legend = ax1.legend( handles_ax1, labels_ax1, loc='upper right', fontsize=text_size + 2, #bbox_to_anchor=(0.90, 0.9), prop={'size': text_size}, framealpha=1) fig_legend.set_zorder(4) plt.tight_layout() plt.subplots_adjust(hspace=0) plots_left_right = plot_left_axis + plot_right_axis plot_filename = plots_path / f'scratch_{instance_name}_{"".join(plots_left_right)}.pdf' plt.savefig(plot_filename) if show: plt.show() plt.close() return plot_filename def plot_pareto(cost_record, typePlt): # plot the pareto frontier with the cost record # take the mean of cost record plot_record_x = [] plot_record_y = [] for iKey in cost_record.keys(): # each item corresponds to a candidate item = cost_record[iKey] cost_record_ij = np.array(item) lockdown_cost = np.mean(cost_record_ij[:,0]) over_cap_cost = np.mean(cost_record_ij[:,1]) plot_record_x.append(lockdown_cost) plot_record_y.append(over_cap_cost) if typePlt == 's': # plot the scatter plot plt.scatter(plot_record_x,plot_record_y) elif typePlt == 'l': # calculate the pareto frontier and plot the line plot n_points = len(plot_record_x) xy = np.zeros([n_points,2]) xy[:,0] = np.array(plot_record_x) xy[:,1] = np.array(plot_record_y) xy_unique = np.unique(xy,axis = 0) xy_pareto = is_pareto_efficient_dumb(xy_unique) # plot the dots on the pareto frontier plt.scatter(xy_unique[xy_pareto][:,0],xy_unique[xy_pareto][:,1]) # plot the line on the pareto frontier xy_pareto_sort = xy_unique[xy_pareto][xy_unique[xy_pareto][:,0].argsort()] plt.plot(xy_pareto_sort[:,0],xy_pareto_sort[:,1]) plt.show() def is_pareto_efficient_dumb(costs): """ Find the pareto-efficient points :param costs: An (n_points, n_costs) array :return: A (n_points, ) boolean array, indicating whether each point is Pareto efficient """ is_efficient = np.ones(costs.shape[0], dtype = bool) for i, c in enumerate(costs): is_efficient[i] = np.all(np.any(costs[:i]>c, axis=1)) and np.all(np.any(costs[i+1:]>c, axis=1)) return is_efficient def make_patch_spines_invisible(ax): ax.set_frame_on(True) ax.patch.set_visible(False) for sp in ax.spines.values(): sp.set_visible(False)

46.391427

174

0.54421

8,941

66,015

3.784588

0.070909

0.032626

0.022755

0.014599

0.870648

0.858118

0.84807

0.836574

0.830752

0

0.0356

0.328547

66,015

1,423

175

46.391427

0.72779

0.149875

0

0.816744

0

0.009302

0.089565

0.025608

0

1

0.007442

false

0

0.017674

0

0.031628

0.034419

0

null

0

1

0

1

0

null

0

7

03d5d68331c42b26bfbffd2e7619b2acdab5aec7

232

py

Python

sample/example_module_to_import.py

GregHilston/example-ghilston-python-cookiecutter

47a13ee249f156815a6dd730e01e761e5055e4b6

[ "MIT" ]

null

sample/example_module_to_import.py

GregHilston/example-ghilston-python-cookiecutter

47a13ee249f156815a6dd730e01e761e5055e4b6

[ "MIT" ]

null

sample/example_module_to_import.py

GregHilston/example-ghilston-python-cookiecutter

47a13ee249f156815a6dd730e01e761e5055e4b6

[ "MIT" ]

null

"""Example function to import in the same package""" def example_function_to_import(): """Example function to import inside this package Returns: Hard coded message """ return "example_function_to_import"

21.090909

53

0.702586

29

232

5.413793

0.551724

0.382166

0.433121

0.585987

0

0.219828

232

10

54

23.2

0.867403

0.543103

0

0.317073

0

1

0.5

true

0

1

0

2

0

1

0

null

1

0

null

0

1

0

1

0

1

0

8

45760a29324e362299472492bfd7cc1a4cdc6bf1

39,738

py

Python

sourcecode/pathwaysearch/pwdfs_naive.py

CC-SXF/PyMiner

d103d54eeaa5653c8f8bc03f78fd4a96e0acefe7

[ "MIT" ]

2

2022-01-20T07:38:00.000Z

2022-01-20T07:56:39.000Z

sourcecode/pathwaysearch/pwdfs_naive.py

CC-SXF/PyMiner

d103d54eeaa5653c8f8bc03f78fd4a96e0acefe7

[ "MIT" ]

null

sourcecode/pathwaysearch/pwdfs_naive.py

CC-SXF/PyMiner

d103d54eeaa5653c8f8bc03f78fd4a96e0acefe7

[ "MIT" ]

1

2022-01-11T14:29:48.000Z

# -*- coding: utf-8 -*- """ Created on Tue Oct 27 10:13:28 2020 @author: CC-SXF """ # import re # import sys # import copy import psutil from datetime import datetime from PyQt5 import QtCore class PwNaDfs(QtCore.QObject): """ Pathway search tools using Depth-First Search algorithm. """ # Create one or more overloaded unbound signals as a class attribute. # PyQt5.QtCore.pyqtSignal(types[, name[, revision=0[, arguments=[]]]]) dfs_prompts_signal = QtCore.pyqtSignal(str) def __init__(self): """ """ super().__init__() def dfs_throw_prompts(self, prompts): """ """ self.dfs_prompts_signal.emit(prompts) def _lpSort(self, totalPathwayList, maxlength = 20): """ Sort the pathways by their length and string. ARGUMENTS: ... RETURNS: ... """ # lengthpathway_dict = dict() for length in range(1, maxlength+1): lengthpathway_dict[length] = set() # for lengthpathway in totalPathwayList: length = lengthpathway[0] pathway = lengthpathway[-1] lengthpathway_dict[length].add(pathway) # totalPathwayList = list() for length in range(1, maxlength+1): pathway_list = sorted(lengthpathway_dict[length]) lengthpathway_list = [(length, pathway) for pathway in pathway_list] totalPathwayList += lengthpathway_list # return totalPathwayList def _unifyPathway(self, pathwayList): """ ARGUMENTS: ... RETURNS: ... """ # # '0-Feasibility'; # '1-TotalLength'; '2-EndoLength'; '3-HeterLength'; '4-InfLength'; # '5-AtomUtilization'; '6-AtomConservation'; '7-Flux'; # '8-Pathway'; # '9-I-Details'; '10-C-Details'; # unifyPathwayList = list() for pathway_info in pathwayList: length = pathway_info[0] pathway = pathway_info[1] details_1 = [1 for idx in range(length)] details_2 = [list() for idx in range(length)] pathway_info = [True, length, length, 0, 0, None, None, None, pathway, details_1, details_2, ] unifyPathwayList.append(pathway_info) # return unifyPathwayList def _pwSource2Target(self, source, target, pathwaylength = 0, currentCompRxnList = list(), visitCompSetList = list(), totalPathwayList = list(), maxlength = 20, maxtime = 100, maxnumber = 1000000, isTotal = True, rxnDistInfoDict = dict(), compDistInfoDict = dict(), timer = {'start':0, "consume":0, "counter":0, "threshold":10000}, memorizer = {"used_memory_percent":0, "used_memory":0, "mempercent":85, "memgb":16}, exDir = 'forward', ): """ Depth-First Search. ARGUMENTS: ... rxnDistInfoDict: {rxnId: [Direction, Compound List, Compound Set, Compound Pairs], ..., } compDistInfoDict: {compId: [Name, Branching Factor, Reactions], ..., } ... RETURNS: ... """ # # The maximal value of the pathway length has been reached. if pathwaylength >= maxlength: return None # # The maximal searching time has been reached. if timer['consume'] >= maxtime: return None # # Deal with out of memory error. # # memory = psutil.virtual_memory() # # used_memory_percent = memory.percent # # used_memory = round(memory.used/1024/1024/1024, 2) if (memorizer["used_memory_percent"] > memorizer["mempercent"]) or(memorizer["used_memory"] > memorizer["memgb"]): return None # # The maximal number of the retrieved pathways has been reached. if len(totalPathwayList) > maxnumber: return None # # Update the counter and the running time. # Update the memory timer['counter'] += 1 if (timer['counter'] % timer['threshold']) == 0: interTime = datetime.now() timer['consume'] = (interTime - timer['start']).total_seconds() # memory = psutil.virtual_memory() used_memory_percent = memory.percent used_memory = round(memory.used/1024/1024/1024, 2) memorizer["used_memory_percent"] = used_memory_percent memorizer["used_memory"] = used_memory # comprxn_list = currentCompRxnList[:(2*pathwaylength+1)] comprxn_set = set(comprxn_list) lastVisitComp = comprxn_list[-1] # # Explicit/implicit visited compounds will be excluded. # comp1-->rxn1-->comp2-->rxn2-->comp3-->rxn3-->comp4-->rxn4-->comp5 # 0 1 2 3 4 5 6 7 8 visitCompSet = visitCompSetList[pathwaylength] """ visitCompSet = set() for idx, comprxn in enumerate(comprxn_list): if idx%2 == 0: continue rxnId = comprxn # # rxnCompList = rxnDistInfoDict[rxnId][1] rxnCompSet = rxnDistInfoDict[rxnId][2] visitCompSet |= rxnCompSet """ # # Continue the pathway search through the last visited compound compDistInfo = compDistInfoDict[lastVisitComp] # compName = compDistInfo[0] # compBf = compDistInfo[1] compRxnList = compDistInfo[2] compRxnSet = set(compRxnList) # Exclude the reactions have been visited by the current pathway. compRxnSet -= comprxn_set # Difference set # There are no new reactions to extend the current pathway. if compRxnSet == set(): return None # # Continue the pathway search through newly reached reactions. for rxnId in compRxnSet: rxnDistInfo = rxnDistInfoDict[rxnId] rxnDir = rxnDistInfo[0] # # rxnCompList = rxnDistInfo[1] rxnCompSet = rxnDistInfo[2] rxnCompPairList = rxnDistInfo[3][exDir] # # The information of this reaction's compound pairs doesn't exist. if rxnCompPairList is None: continue # if (rxnDir == '=>') or (rxnDir == '<=>'): try: genCompIdList = rxnCompPairList[0][lastVisitComp] genCompIdSet = set(genCompIdList) # # Every compound in this pathway must be different from the compounds # that belong to its direct/indirect predecessor reactions. # Exclude explicit/implicit visited compounds. genCompIdSet -= visitCompSet # Difference set # # There are no new compounds to extend the current pathway. if genCompIdSet == set(): continue # for genCompId in genCompIdSet: # Extend the current pathway. # comp1-->rxn1-->comp2-->rxn2-->comp3-->rxn3-->comp4-->rxn4-->comp5 # 0 1 2 3 4 5 6 7 8 currentCompRxnList[2*pathwaylength+1] = rxnId currentCompRxnList[2*pathwaylength+2] = genCompId newPl = pathwaylength + 1 # # The target compound has been reached, and the new complete pathway will be saved. if genCompId == target: newPathway = "-->".join(currentCompRxnList[:2*newPl+1]) if isTotal: # all pathways not longer than maximum length will be kept. totalPathwayList.append((newPl, newPathway)) elif newPl == maxlength: # pathway equal to maximum length will be kept totalPathwayList.append((newPl, newPathway)) else: # pathway shorter than maximum length will be discarded. pass continue # # The maximal value of the pathway length has been reached. if newPl >= maxlength: continue # # Continue the pathway search process by using recursive algorithm. visitCompSetList[newPl] = (visitCompSetList[newPl-1] | rxnCompSet) self._pwSource2Target(source, target, newPl, currentCompRxnList, visitCompSetList, totalPathwayList, maxlength, maxtime, maxnumber, isTotal, rxnDistInfoDict, compDistInfoDict, timer, memorizer, ) continue except KeyError: pass # if (rxnDir == "<=") or (rxnDir == '<=>'): try: genCompIdList = rxnCompPairList[1][lastVisitComp] genCompIdSet = set(genCompIdList) # # Every compound in this pathway must be different from the compounds # that belong to its direct/indirect predecessor reactions. # Exclude explicit/implicit visited compounds. genCompIdSet -= visitCompSet # Difference set # # There are no new compounds to extend the current pathway. if genCompIdSet == set(): continue # for genCompId in genCompIdSet: # Extend the current pathway. # comp1-->rxn1-->comp2-->rxn2-->comp3-->rxn3-->comp4-->rxn4-->comp5 # 0 1 2 3 4 5 6 7 8 currentCompRxnList[2*pathwaylength+1] = rxnId currentCompRxnList[2*pathwaylength+2] = genCompId newPl = pathwaylength + 1 # # The target compound has been reached, and the new complete pathway will be saved. if genCompId == target: newPathway = "-->".join(currentCompRxnList[:2*newPl+1]) if isTotal: # all pathways not longer than maximum length will be kept. totalPathwayList.append((newPl, newPathway)) elif newPl == maxlength: # pathway equal to maximum length will be kept totalPathwayList.append((newPl, newPathway)) else: # pathway shorter than maximum length will be discarded. pass continue # # The maximal value of the pathway length has been reached. if newPl >= maxlength: continue # # Continue the pathway search process by using recursive algorithm. visitCompSetList[newPl] = (visitCompSetList[newPl-1] | rxnCompSet) self._pwSource2Target(source, target, newPl, currentCompRxnList, visitCompSetList, totalPathwayList, maxlength, maxtime, maxnumber, isTotal, rxnDistInfoDict, compDistInfoDict, timer, memorizer, ) continue except KeyError: pass # return None def Source2Target(self, source, target, maxlength = 20, maxtime = 100, maxnumber = 1000000, isTotal = True, rxnDistInfoDict = dict(), compDistInfoDict = dict(), timer = {"start":0, "consume":0, "counter":0, "threshold":10000}, memorizer = {"used_memory_percent":0, "used_memory":0, "mempercent":85, "memgb":16}, isDebug = False, ): """ Search the pathways from source to target by using Depth-First Search algorithm. ARGUMENTS: ... rxnDistInfoDict: {rxnId: [Direction, Compound List, Compound Set, Compound Pairs], ..., } compDistInfoDict: {compId: [Name, Branching Factor, Reactions], ..., } ... RETURNS: ... """ # if isDebug: # # print("") print("Search the pathways from source to target (DFS):") else: # # self.dfs_throw_prompts("") self.dfs_throw_prompts("Search the pathways from source to target (DFS):") # if (not isinstance(source, str)) or (not isinstance(target, str)): if isDebug: print("Incorrect parameter type.") else: self.dfs_throw_prompts("Incorrect parameter type.") return list() # allCompSet = set(compDistInfoDict.keys()) if source not in allCompSet: if isDebug: print(f"The source({source}) does not exist in the Generalized Metabolic Space.") print("Please have a check on the source.") else: self.dfs_throw_prompts(f"The source({source}) does not exist in the Generalized Metabolic Space.") self.dfs_throw_prompts("Please have a check on the source.") return list() if target not in allCompSet: if isDebug: print(f"The target({target}) does not exist in the Generalized Metabolic Space.") print("Try to use de novo pathway design instead of pathway search.") else: self.dfs_throw_prompts(f"The target({target}) does not exist in the Generalized Metabolic Space.") self.dfs_throw_prompts("Try to use de novo pathway design instead of pathway search.") return list() # sourceName = compDistInfoDict[source][0] targetName = compDistInfoDict[target][0] if source == target: if isDebug: print(f"The source({source}, {sourceName}) is identical with the target({target}, {targetName}).") print("Please have a check on the source and the target.") else: self.dfs_throw_prompts(f"The source({source}, {sourceName}) is identical with the target({target}, {targetName}).") self.dfs_throw_prompts("Please have a check on the source and the target.") return list() # # Initialization pathwaylength = 0 currentCompRxnList = list() currentCompRxnList.append(source) for idx in range(1, 2*maxlength+1): currentCompRxnList.append("") visitCompSetList = list() for idx in range(maxlength+1): visitCompSetList.append(set()) visitCompSetList[0].add(source) totalPathwayList=list() startTime = datetime.now() # Resetting... timer = {'start':startTime, "consume":0, "counter":0, "threshold":10000} memorizer = {"used_memory_percent":0, "used_memory":0, "mempercent":85, "memgb":16} # self._pwSource2Target(source, target, pathwaylength, currentCompRxnList, visitCompSetList, totalPathwayList, maxlength, maxtime, maxnumber, isTotal, rxnDistInfoDict, compDistInfoDict, timer, memorizer, ) # # Calculate the running time. endTime = datetime.now() runTime = (endTime - startTime).total_seconds() if isDebug: print(''.join(['Search Time: ', str(round(runTime, 6)), 's'])) else: self.dfs_throw_prompts(''.join(['Search Time: ', str(round(runTime, 6)), 's'])) # # Deal with out of memory error. used_memory_percent = memorizer["used_memory_percent"] used_memory = memorizer["used_memory"] mempercent = memorizer["mempercent"] memgb = memorizer["memgb"] # if isDebug: print(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") else: self.dfs_throw_prompts(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") # # Sorting... # # totalPathwayList = self._lpSort(totalPathwayList) # # Unifying... totalPathwayList = self._unifyPathway(totalPathwayList) pathwayNum = len(totalPathwayList) # if pathwayNum == 0: if isDebug: print(f"The pathway from {source}({sourceName}) to {target}({targetName}) has not yet been found.") else: self.dfs_throw_prompts(f"The pathway from {source}({sourceName}) to {target}({targetName}) has not yet been found.") if runTime >= maxtime: if isDebug: print("Try to increase the maximal searching time of the potential pathway and repeat the search process.") else: self.dfs_throw_prompts("Try to increase the maximal searching time of the potential pathway and repeat the search process.") elif (used_memory_percent > mempercent) or (used_memory > memgb): if isDebug: # # print(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") print("The memory of this platform restricts the pathway search process.") pass else: # # self.dfs_throw_prompts(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") self.dfs_throw_prompts("The memory of this platform restricts the pathway search process.") pass else: if isTotal: if isDebug: print("Try to increase the maximal length of the potential pathway and repeat the search process.") else: self.dfs_throw_prompts("Try to increase the maximal length of the potential pathway and repeat the search process.") else: if isDebug: print("Try to decrease or increase the length of the potential pathway and repeat the search process.") else: self.dfs_throw_prompts("Try to decrease or increase the length of the potential pathway and repeat the search process.") else: if isDebug: print(f"The pathway from {source}({sourceName}) to {target}({targetName}) has been found.") print(f"The total number of the retrieved pathways is {pathwayNum}.\n") else: self.dfs_throw_prompts(f"The pathway from {source}({sourceName}) to {target}({targetName}) has been found.") self.dfs_throw_prompts(f"The total number of the retrieved pathways is {pathwayNum}.\n") # return totalPathwayList def _pwTarget2MultSource(self, multSourceSet, target, pathwaylength = 0, currentCompRxnList = list(), totalPathwayList = list(), maxlength = 20, maxtime = 100, maxnumber = 1000000, isTotal = True, rxnDistInfoDict = dict(), compDistInfoDict = dict(), timer = {'start':0, "consume":0, "counter":0, "threshold":10000}, memorizer = {"used_memory_percent":0, "used_memory":0, "mempercent":85, "memgb":16}, exDir='backward', ): """ Depth-First Search. ARGUMENTS: ... rxnDistInfoDict: {rxnId: [Direction, Compound List, Compound Set, Compound Pairs], ..., } compDistInfoDict: {compId: [Name, Branching Factor, Reactions], ..., } ... RETURNS: ... """ # # The maximal value of the pathway length has been reached. if pathwaylength >= maxlength: return None # # The maximal searching time has been reached. if timer['consume'] >= maxtime: return None # # Deal with out of memory error. # # memory = psutil.virtual_memory() # # used_memory_percent = memory.percent # # used_memory = round(memory.used/1024/1024/1024, 2) if (memorizer["used_memory_percent"] > memorizer["mempercent"]) or(memorizer["used_memory"] > memorizer["memgb"]): return None # # The maximal number of the retrieved pathways has been reached. if len(totalPathwayList) > maxnumber: return None # # Update the counter and the running time. # Update the memory timer['counter'] += 1 if (timer['counter'] % timer['threshold']) == 0: interTime = datetime.now() timer['consume'] = (interTime - timer['start']).total_seconds() # memory = psutil.virtual_memory() used_memory_percent = memory.percent used_memory = round(memory.used/1024/1024/1024, 2) memorizer["used_memory_percent"] = used_memory_percent memorizer["used_memory"] = used_memory # # comprxn_list = currentCompRxnList[:(2*pathwaylength+1)] comprxn_set = set(comprxn_list[:-1]) lastVisitComp = comprxn_list[-1] # # Continue the pathway search through the last visited compound compDistInfo = compDistInfoDict[lastVisitComp] # compName = compDistInfo[0] # compBf = compDistInfo[1] compRxnList = compDistInfo[2] compRxnSet = set(compRxnList) # Exclude the reactions have been visited by the current pathway. compRxnSet -= comprxn_set # Difference set # # There are no new reactions to extend the current pathway. if compRxnSet == set(): return None # # Continue the pathway search through newly reached reactions. for rxnId in compRxnSet: rxnDistInfo = rxnDistInfoDict[rxnId] rxnDir = rxnDistInfo[0] # rxnCompList = rxnDistInfo[1] rxnCompSet = rxnDistInfo[2] rxnCompPairList = rxnDistInfo[3][exDir] # # The information of this reaction's compound pairs doesn't exist. if rxnCompPairList is None: continue # # Explicit/implicit visited compounds will be excluded. # comp1-->rxn1-->comp2-->rxn2-->comp3-->rxn3-->comp4-->rxn4-->comp5 # 0 1 2 3 4 5 6 7 8 if len(rxnCompSet & comprxn_set) != 0: continue # if (rxnDir == '=>') or (rxnDir == '<=>'): try: # left-->right genCompIdList = rxnCompPairList[0][lastVisitComp] # # There are no new compounds to extend the current pathway. if len(genCompIdList) == 0: continue # for genCompId in genCompIdList: # Extend the current pathway. # comp1-->rxn1-->comp2-->rxn2-->comp3-->rxn3-->comp4-->rxn4-->comp5 # 0 1 2 3 4 5 6 7 8 currentCompRxnList[2*pathwaylength+1] = rxnId currentCompRxnList[2*pathwaylength+2] = genCompId newPl = pathwaylength + 1 # # The target compound has been reached, and the new complete pathway will be saved. if genCompId in multSourceSet: newPathway = "-->".join(currentCompRxnList[:2*newPl+1][::-1]) if isTotal: # all pathways not longer than maximum length will be kept. totalPathwayList.append((newPl, newPathway)) elif newPl == maxlength: # pathway equal to maximum length will be kept totalPathwayList.append((newPl, newPathway)) else: # pathway shorter than maximum length will be discarded. pass continue # # The maximal value of the pathway length has been reached. if newPl >= maxlength: continue # # Continue the pathway search process by using recursive algorithm. self._pwTarget2MultSource(multSourceSet, target, newPl, currentCompRxnList, totalPathwayList, maxlength, maxtime, maxnumber, isTotal, rxnDistInfoDict, compDistInfoDict, timer, memorizer, ) continue except KeyError: pass # if (rxnDir == "<=") or (rxnDir == '<=>'): try: # right-->left genCompIdList = rxnCompPairList[1][lastVisitComp] # # There are no new compounds to extend the current pathway. if len(genCompIdList) == 0: continue # for genCompId in genCompIdList: # Extend the current pathway. # comp1-->rxn1-->comp2-->rxn2-->comp3-->rxn3-->comp4-->rxn4-->comp5 # 0 1 2 3 4 5 6 7 8 currentCompRxnList[2*pathwaylength+1] = rxnId currentCompRxnList[2*pathwaylength+2] = genCompId newPl = pathwaylength + 1 # # The target compound has been reached, and the new complete pathway will be saved. if genCompId in multSourceSet: newPathway = "-->".join(currentCompRxnList[:2*newPl+1][::-1]) if isTotal: # all pathways not longer than maximum length will be kept. totalPathwayList.append((newPl, newPathway)) elif newPl == maxlength: # pathway equal to maximum length will be kept totalPathwayList.append((newPl, newPathway)) else: # pathway shorter than maximum length will be discarded. pass continue # # The maximal value of the pathway length has been reached. if newPl >= maxlength: continue # # Continue the pathway search process by using recursive algorithm. self._pwTarget2MultSource(multSourceSet, target, newPl, currentCompRxnList, totalPathwayList, maxlength, maxtime, maxnumber, isTotal, rxnDistInfoDict, compDistInfoDict, timer, memorizer, ) continue except KeyError: pass # return None def Target2MultSource(self, multSourceSet, target, maxlength = 20, maxtime = 100, maxnumber = 1000000, isTotal = True, rxnDistInfoDict = dict(), compDistInfoDict = dict(), timer = {'start':0, "consume":0, "counter":0, "threshold":10000}, memorizer = {"used_memory_percent":0, "used_memory":0, "mempercent":85, "memgb":16}, isDebug = False, ): """ Search the pathways from target to mult-sources by using Depth-First Search algorithm. ARGUMENTS: ... rxnDistInfoDict: {rxnId: [Direction, Compound List, Compound Set, Compound Pairs], ..., } compDistInfoDict: {compId: [Name, Branching Factor, Reactions], ..., } ... RETURNS: ... """ # if isDebug: # # print("") print("Search the pathways from target to mult-sources (DFS):") else: # # self.dfs_throw_prompts("") self.dfs_throw_prompts("Search the pathways from target to mult-sources (DFS):") # if (not isinstance(multSourceSet, set)) or (not isinstance(target, str)): # print("Incorrect parameter type.") self.dfs_throw_prompts("Incorrect parameter type.") return list() # allCompSet = set(compDistInfoDict.keys()) if target not in allCompSet: if isDebug: print(f"The target({target}) does not exist in the Generalized Metabolic Space.") print("Try to use de novo pathway design instead of pathway search.") else: self.dfs_throw_prompts(f"The target({target}) does not exist in the Generalized Metabolic Space.") self.dfs_throw_prompts("Try to use de novo pathway design instead of pathway search.") return list() # sourceEliSet = {target} for source in multSourceSet: if source not in allCompSet: sourceEliSet.add(source) # print(f"The source({source}) does not exist in the Generalized Metabolic Space.") # multSourceSet -= sourceEliSet # Difference Set # if multSourceSet == set(): if isDebug: print("The valid 'source set' in empty.") print("Please have a check on the 'source set'.") else: self.dfs_throw_prompts("The valid 'source set' in empty.") self.dfs_throw_prompts("Please have a check on the 'source set'.") return list() # multSourceIdNameSet = set() for source in list(multSourceSet)[:6]: sourceName = compDistInfoDict[source][0] sourceIdName = "".join([source, "(", sourceName, ")"]) multSourceIdNameSet.add(sourceIdName) if len(multSourceSet) > 6: multSourceIdNameSet.add('...') targetName = compDistInfoDict[target][0] # # Initialization pathwaylength = 0 currentCompRxnList = list() currentCompRxnList.append(target) for idx in range(1, 2*maxlength+1): currentCompRxnList.append("") totalPathwayList=list() startTime = datetime.now() # Resetting... timer = {'start':startTime, "consume":0, "counter":0, "threshold":10000} memorizer = {"used_memory_percent":0, "used_memory":0, "mempercent":85, "memgb":16} # self._pwTarget2MultSource(multSourceSet, target, pathwaylength, currentCompRxnList, totalPathwayList, maxlength, maxtime, maxnumber, isTotal, rxnDistInfoDict, compDistInfoDict, timer, memorizer, ) # # Calculate the running time. endTime = datetime.now() runTime = (endTime - startTime).total_seconds() if isDebug: print(''.join(['Search Time: ', str(round(runTime, 6)), 's'])) else: self.dfs_throw_prompts(''.join(['Search Time: ', str(round(runTime, 6)), 's'])) # # Deal with out of memory error. used_memory_percent = memorizer["used_memory_percent"] used_memory = memorizer["used_memory"] mempercent = memorizer["mempercent"] memgb = memorizer["memgb"] # if isDebug: print(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") else: self.dfs_throw_prompts(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") # # Sorting... # # totalPathwayList = self._lpSort(totalPathwayList) # # Unifying... totalPathwayList = self._unifyPathway(totalPathwayList) pathwayNum = len(totalPathwayList) # if pathwayNum == 0: if isDebug: print(f"The pathway from {multSourceIdNameSet} to {target}({targetName}) has not yet been found.") else: self.dfs_throw_prompts(f"The pathway from {multSourceIdNameSet} to {target}({targetName}) has not yet been found.") if runTime >= maxtime: if isDebug: print("Try to increase the maximal searching time of the potential pathway and repeat the search process.") else: self.dfs_throw_prompts("Try to increase the maximal searching time of the potential pathway and repeat the search process.") elif (used_memory_percent > mempercent) or (used_memory > memgb): if isDebug: # # print(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") print("The memory of this platform restricts the pathway search process.") pass else: # # self.dfs_throw_prompts(f"Memory: {used_memory}GB({used_memory_percent}%) of RAM of this platform has been used.") self.dfs_throw_prompts("The memory of this platform restricts the pathway search process.") pass else: if isTotal: if isDebug: print("Try to increase the maximal length of the potential pathway and repeat the search process.") else: self.dfs_throw_prompts("Try to increase the maximal length of the potential pathway and repeat the search process.") else: if isDebug: print("Try to decrease or increase the length of the potential pathway and repeat the search process.") else: self.dfs_throw_prompts("Try to decrease or increase the length of the potential pathway and repeat the search process.") return list() # multSourceSet = set() for pathway_info in totalPathwayList: # # pathway = pathway_info['8-Pathway'] pathway = pathway_info[8] source = pathway.split('-->')[0] multSourceSet.add(source) multSourceIdNameSet = set() for source in multSourceSet: sourceName = compDistInfoDict[source][0] sourceIdName = "".join([source, "(", sourceName, ")"]) multSourceIdNameSet.add(sourceIdName) targetName = compDistInfoDict[target][0] # if isDebug: print(f"The pathway from {multSourceIdNameSet} to {target}({targetName}) has been found.") print(f"The total number of the retrieved pathways is {pathwayNum}.\n") else: self.dfs_throw_prompts(f"The pathway from {multSourceIdNameSet} to {target}({targetName}) has been found.") self.dfs_throw_prompts(f"The total number of the retrieved pathways is {pathwayNum}.\n") # return totalPathwayList @classmethod def demoFunc(cls,): """ """ pass if __name__ == "__main__": """ """ pass

47.476703

145

0.488022

3,378

39,738

5.670515

0.095027

0.031323

0.028974

0.035709

0.868912

0.847716

0.843801

0.827878

0.82036

0.815557

0

0.019532

0.430545

39,738

836

146

47.533493

0.826948

0.185465

0

0.794059

0

0.163576

0.016601

0

1

0.017822

false

0.027723

0.005941

0

0.075248

0.061386

0

null

0

1

0

1

0

null

0

7

458885ba34826a6ae4c73e6e4bd8bfe052a63c89

145

py

Python

agentenc/encryptors/__init__.py

C4a15Wh/AgentEncryption

b0c878199db2898ea9d08c6a2e0b652971662bab

[ "Apache-2.0" ]

9

2021-11-09T12:31:25.000Z

2022-03-16T01:45:05.000Z

agentenc/encryptors/__init__.py

C4a15Wh/AgentEncryption

b0c878199db2898ea9d08c6a2e0b652971662bab

[ "Apache-2.0" ]

2

2021-11-04T05:36:23.000Z

2022-03-08T10:02:09.000Z

agentenc/encryptors/__init__.py

C4a15Wh/AgentEncryption

b0c878199db2898ea9d08c6a2e0b652971662bab

[ "Apache-2.0" ]

3

2021-11-05T16:12:08.000Z

2022-01-12T10:01:44.000Z

from agentenc.encryptors.base import Encryptor from agentenc.encryptors.rsa import RSAEncryptor from agentenc.encryptors.aes import AESEncryptor

36.25

48

0.875862

18

145

7.055556

0.555556

0.283465

0.519685

0

0.082759

145

3

49

48.333333

0.954887

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

b33951e96e1aa77a59510fa8ab219d3ff0b5a9dc

6,077

py

Python

tests/api-client/test_guest_media.py

bcurnow/rfid-security-svc

d3806cb74d3d0cc2623ea425230dc8781ba4d8b4

[ "Apache-2.0" ]

null

tests/api-client/test_guest_media.py

bcurnow/rfid-security-svc

d3806cb74d3d0cc2623ea425230dc8781ba4d8b4

[ "Apache-2.0" ]

null

tests/api-client/test_guest_media.py

bcurnow/rfid-security-svc

d3806cb74d3d0cc2623ea425230dc8781ba4d8b4

[ "Apache-2.0" ]

null

from unittest.mock import patch from rfidsecuritysvc.api import RECORD_COUNT_HEADER from rfidsecuritysvc.model.color import Color from rfidsecuritysvc.model.guest_media import GuestMedia as Model api = 'guest-media' def test_get(rh, guest_medias): rh.assert_response(rh.open('get', f'{api}/{guest_medias[0].id}'), 200, guest_medias[0]) def test_get_notfound(rh, guest_medias): rh.assert_response(rh.open('get', f'{api}/bogus'), 404) def test_search(rh, guest_medias): rh.assert_response(rh.open('get', f'{api}'), 200, guest_medias) def test_search_with_guest_id(rh, guest_medias): rh.assert_response(rh.open('get', f'{api}?guest_id={guest_medias[1].guest.id}'), 200, [guest_medias[1]]) @patch('rfidsecuritysvc.api.guest_media.model') def test_search_noresults(model, rh): """ The table is already populated so we need to patch instead """ model.list.return_value = [] rh.assert_response(rh.open('get', f'{api}'), 200, []) model.list.assert_called_once() def test_post(rh, creatable_guest_media): p = creatable_guest_media rh.assert_response(rh.open('post', f'{api}', p), 201) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200) rh.assert_response(rh.open('delete', f'{api}/{p.id}'), 200, headers={RECORD_COUNT_HEADER: '1'}) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 404) def test_post_duplicate(rh, guest_medias): rh.assert_response(rh.open('post', f'{api}', guest_medias[0]), 409) def test_post_guest_notfound(rh, creatable_guest_media, creatable_guest): m = Model(creatable_guest_media.id, creatable_guest, creatable_guest_media.media, creatable_guest_media.sound, creatable_guest_media.color) rh.assert_response(rh.open('post', f'{api}', m), 400) def test_post_media_notfound(rh, creatable_guest_media, creatable_media): m = Model(creatable_guest_media.id, creatable_guest_media.guest, creatable_media, creatable_guest_media.sound, creatable_guest_media.color) rh.assert_response(rh.open('post', f'{api}', m), 400) def test_post_sound_notfound(rh, creatable_guest_media, creatable_sound): m = Model(creatable_guest_media.id, creatable_guest_media.guest, creatable_guest_media.media, creatable_sound, creatable_guest_media.color) rh.assert_response(rh.open('post', f'{api}', m), 400) def test_delete(rh, creatable_guest_media): p = creatable_guest_media rh.assert_response(rh.open('post', f'{api}', p.test_create()), 201) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200) rh.assert_response(rh.open('delete', f'{api}/{p.id}'), 200, headers={RECORD_COUNT_HEADER: '1'}) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 404) def test_delete_notfound(rh, creatable_guest_media): rh.assert_response(rh.open('delete', f'{api}/{creatable_guest_media.id}'), 200, headers={RECORD_COUNT_HEADER: '0'}) def test_put(rh, creatable_guest_media): p = creatable_guest_media updated_p = Model(creatable_guest_media.id, creatable_guest_media.guest, creatable_guest_media.media, creatable_guest_media.sound, Color(0xFEDCBA)) rh.assert_response(rh.open('post', f'{api}', p.test_create()), 201) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200) rh.assert_response(rh.open('put', f'{api}/{p.id}', updated_p.test_update()), 200, headers={RECORD_COUNT_HEADER: '1'}) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200, updated_p) rh.assert_response(rh.open('delete', f'{api}/{p.id}'), 200, headers={RECORD_COUNT_HEADER: '1'}) def test_put_notfound(rh, creatable_guest_media): p = creatable_guest_media rh.assert_response(rh.open('put', f'{api}/{p.id}', p.test_update()), 201, headers={RECORD_COUNT_HEADER: '1'}) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200, p) rh.assert_response(rh.open('delete', f'{api}/{p.id}'), 200, headers={RECORD_COUNT_HEADER: '1'}) def test_put_guest_notfound(rh, creatable_guest_media, creatable_guest): p = creatable_guest_media updated_p = Model(creatable_guest_media.id, creatable_guest, creatable_guest_media.media, creatable_guest_media.sound, Color(0xFEDCBA)) rh.assert_response(rh.open('post', f'{api}', p.test_create()), 201) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200) rh.assert_response(rh.open('put', f'{api}/{p.id}', updated_p.test_update()), 400) rh.assert_response(rh.open('delete', f'{api}/{p.id}'), 200, headers={RECORD_COUNT_HEADER: '1'}) def test_put_media_notfound(rh, creatable_guest_media, creatable_media): p = creatable_guest_media updated_p = Model(creatable_guest_media.id, creatable_guest_media.guest, creatable_media, creatable_guest_media.sound, Color(0xFEDCBA)) rh.assert_response(rh.open('post', f'{api}', p.test_create()), 201) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200) rh.assert_response(rh.open('put', f'{api}/{p.id}', updated_p.test_update()), 400) rh.assert_response(rh.open('delete', f'{api}/{p.id}'), 200, headers={RECORD_COUNT_HEADER: '1'}) def test_put_sound_notfound(rh, creatable_guest_media, creatable_sound): p = creatable_guest_media updated_p = Model(creatable_guest_media.id, creatable_guest_media.guest, creatable_guest_media.media, creatable_sound, Color(0xFEDCBA)) rh.assert_response(rh.open('post', f'{api}', p.test_create()), 201) rh.assert_response(rh.open('get', f'{api}/{p.id}'), 200) rh.assert_response(rh.open('put', f'{api}/{p.id}', updated_p.test_update()), 400) rh.assert_response(rh.open('delete', f'{api}/{p.id}'), 200, headers={RECORD_COUNT_HEADER: '1'})

41.060811

121

0.659701

870

6,077

4.34023

0.075862

0.177966

0.221398

0.181144

0.846398

0.8366

0.828919

0.724576

0.715307

0

0.026734

0.181339

6,077

147

122

41.340136

0.732261

0.009544

0

0.647619

0

0.106471

0.022625

0

0.005324

0

0.371429

1

0.161905

false

0

0.038095

0

0.2

0

null

0

1

0

null

0

8

b35bf34536a72046cb0993cd30816081f9f69ed8

18,637

py

Python

bundle/deepracer_msgs/lib/python2.7/dist-packages/deepracer_msgs/srv/_SetVisualMeshes.py

larsll/deepracer-simapp

9251c32ff33d49955b63ccca4f38d01a0c721d4f

[ "MIT" ]

1

2022-02-23T20:34:00.000Z

bundle/deepracer_msgs/lib/python2.7/dist-packages/deepracer_msgs/srv/_SetVisualMeshes.py

Bandwidth/deepracer-simapp

9bf0a5f9c55e37ecef8e72b1b6dc15ecb0370bc1

[ "MIT" ]

null

bundle/deepracer_msgs/lib/python2.7/dist-packages/deepracer_msgs/srv/_SetVisualMeshes.py

Bandwidth/deepracer-simapp

9bf0a5f9c55e37ecef8e72b1b6dc15ecb0370bc1

[ "MIT" ]

null

# This Python file uses the following encoding: utf-8 """autogenerated by genpy from deepracer_msgs/SetVisualMeshesRequest.msg. Do not edit.""" import codecs import sys python3 = True if sys.hexversion > 0x03000000 else False import genpy import struct import geometry_msgs.msg class SetVisualMeshesRequest(genpy.Message): _md5sum = "0af63bba011714dcda7e22d917c9a308" _type = "deepracer_msgs/SetVisualMeshesRequest" _has_header = False # flag to mark the presence of a Header object _full_text = """string[] link_names string[] visual_names string[] filenames geometry_msgs/Vector3[] scales bool block ================================================================================ MSG: geometry_msgs/Vector3 # This represents a vector in free space. # It is only meant to represent a direction. Therefore, it does not # make sense to apply a translation to it (e.g., when applying a # generic rigid transformation to a Vector3, tf2 will only apply the # rotation). If you want your data to be translatable too, use the # geometry_msgs/Point message instead. float64 x float64 y float64 z""" __slots__ = ['link_names','visual_names','filenames','scales','block'] _slot_types = ['string[]','string[]','string[]','geometry_msgs/Vector3[]','bool'] def __init__(self, *args, **kwds): """ Constructor. Any message fields that are implicitly/explicitly set to None will be assigned a default value. The recommend use is keyword arguments as this is more robust to future message changes. You cannot mix in-order arguments and keyword arguments. The available fields are: link_names,visual_names,filenames,scales,block :param args: complete set of field values, in .msg order :param kwds: use keyword arguments corresponding to message field names to set specific fields. """ if args or kwds: super(SetVisualMeshesRequest, self).__init__(*args, **kwds) # message fields cannot be None, assign default values for those that are if self.link_names is None: self.link_names = [] if self.visual_names is None: self.visual_names = [] if self.filenames is None: self.filenames = [] if self.scales is None: self.scales = [] if self.block is None: self.block = False else: self.link_names = [] self.visual_names = [] self.filenames = [] self.scales = [] self.block = False def _get_types(self): """ internal API method """ return self._slot_types def serialize(self, buff): """ serialize message into buffer :param buff: buffer, ``StringIO`` """ try: length = len(self.link_names) buff.write(_struct_I.pack(length)) for val1 in self.link_names: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) length = len(self.visual_names) buff.write(_struct_I.pack(length)) for val1 in self.visual_names: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) length = len(self.filenames) buff.write(_struct_I.pack(length)) for val1 in self.filenames: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) length = len(self.scales) buff.write(_struct_I.pack(length)) for val1 in self.scales: _x = val1 buff.write(_get_struct_3d().pack(_x.x, _x.y, _x.z)) _x = self.block buff.write(_get_struct_B().pack(_x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize(self, str): """ unpack serialized message in str into this message instance :param str: byte array of serialized message, ``str`` """ if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: if self.scales is None: self.scales = None end = 0 start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.link_names = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.link_names.append(val1) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.visual_names = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.visual_names.append(val1) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.filenames = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.filenames.append(val1) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.scales = [] for i in range(0, length): val1 = geometry_msgs.msg.Vector3() _x = val1 start = end end += 24 (_x.x, _x.y, _x.z,) = _get_struct_3d().unpack(str[start:end]) self.scales.append(val1) start = end end += 1 (self.block,) = _get_struct_B().unpack(str[start:end]) self.block = bool(self.block) return self except struct.error as e: raise genpy.DeserializationError(e) # most likely buffer underfill def serialize_numpy(self, buff, numpy): """ serialize message with numpy array types into buffer :param buff: buffer, ``StringIO`` :param numpy: numpy python module """ try: length = len(self.link_names) buff.write(_struct_I.pack(length)) for val1 in self.link_names: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) length = len(self.visual_names) buff.write(_struct_I.pack(length)) for val1 in self.visual_names: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) length = len(self.filenames) buff.write(_struct_I.pack(length)) for val1 in self.filenames: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) length = len(self.scales) buff.write(_struct_I.pack(length)) for val1 in self.scales: _x = val1 buff.write(_get_struct_3d().pack(_x.x, _x.y, _x.z)) _x = self.block buff.write(_get_struct_B().pack(_x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize_numpy(self, str, numpy): """ unpack serialized message in str into this message instance using numpy for array types :param str: byte array of serialized message, ``str`` :param numpy: numpy python module """ if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: if self.scales is None: self.scales = None end = 0 start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.link_names = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.link_names.append(val1) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.visual_names = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.visual_names.append(val1) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.filenames = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.filenames.append(val1) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.scales = [] for i in range(0, length): val1 = geometry_msgs.msg.Vector3() _x = val1 start = end end += 24 (_x.x, _x.y, _x.z,) = _get_struct_3d().unpack(str[start:end]) self.scales.append(val1) start = end end += 1 (self.block,) = _get_struct_B().unpack(str[start:end]) self.block = bool(self.block) return self except struct.error as e: raise genpy.DeserializationError(e) # most likely buffer underfill _struct_I = genpy.struct_I def _get_struct_I(): global _struct_I return _struct_I _struct_3d = None def _get_struct_3d(): global _struct_3d if _struct_3d is None: _struct_3d = struct.Struct("<3d") return _struct_3d _struct_B = None def _get_struct_B(): global _struct_B if _struct_B is None: _struct_B = struct.Struct("<B") return _struct_B # This Python file uses the following encoding: utf-8 """autogenerated by genpy from deepracer_msgs/SetVisualMeshesResponse.msg. Do not edit.""" import codecs import sys python3 = True if sys.hexversion > 0x03000000 else False import genpy import struct class SetVisualMeshesResponse(genpy.Message): _md5sum = "a0af81bf1f7c2eacb2693173f999072a" _type = "deepracer_msgs/SetVisualMeshesResponse" _has_header = False # flag to mark the presence of a Header object _full_text = """bool success string status_message int8[] status # status of each request: true if succeeded otherwise false string[] messages """ __slots__ = ['success','status_message','status','messages'] _slot_types = ['bool','string','int8[]','string[]'] def __init__(self, *args, **kwds): """ Constructor. Any message fields that are implicitly/explicitly set to None will be assigned a default value. The recommend use is keyword arguments as this is more robust to future message changes. You cannot mix in-order arguments and keyword arguments. The available fields are: success,status_message,status,messages :param args: complete set of field values, in .msg order :param kwds: use keyword arguments corresponding to message field names to set specific fields. """ if args or kwds: super(SetVisualMeshesResponse, self).__init__(*args, **kwds) # message fields cannot be None, assign default values for those that are if self.success is None: self.success = False if self.status_message is None: self.status_message = '' if self.status is None: self.status = [] if self.messages is None: self.messages = [] else: self.success = False self.status_message = '' self.status = [] self.messages = [] def _get_types(self): """ internal API method """ return self._slot_types def serialize(self, buff): """ serialize message into buffer :param buff: buffer, ``StringIO`` """ try: _x = self.success buff.write(_get_struct_B().pack(_x)) _x = self.status_message length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) length = len(self.status) buff.write(_struct_I.pack(length)) pattern = '<%sb'%length buff.write(struct.Struct(pattern).pack(*self.status)) length = len(self.messages) buff.write(_struct_I.pack(length)) for val1 in self.messages: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize(self, str): """ unpack serialized message in str into this message instance :param str: byte array of serialized message, ``str`` """ if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: end = 0 start = end end += 1 (self.success,) = _get_struct_B().unpack(str[start:end]) self.success = bool(self.success) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status_message = str[start:end].decode('utf-8', 'rosmsg') else: self.status_message = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sb'%length start = end s = struct.Struct(pattern) end += s.size self.status = s.unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.messages = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.messages.append(val1) return self except struct.error as e: raise genpy.DeserializationError(e) # most likely buffer underfill def serialize_numpy(self, buff, numpy): """ serialize message with numpy array types into buffer :param buff: buffer, ``StringIO`` :param numpy: numpy python module """ try: _x = self.success buff.write(_get_struct_B().pack(_x)) _x = self.status_message length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) length = len(self.status) buff.write(_struct_I.pack(length)) pattern = '<%sb'%length buff.write(self.status.tostring()) length = len(self.messages) buff.write(_struct_I.pack(length)) for val1 in self.messages: length = len(val1) if python3 or type(val1) == unicode: val1 = val1.encode('utf-8') length = len(val1) buff.write(struct.Struct('<I%ss'%length).pack(length, val1)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize_numpy(self, str, numpy): """ unpack serialized message in str into this message instance using numpy for array types :param str: byte array of serialized message, ``str`` :param numpy: numpy python module """ if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: end = 0 start = end end += 1 (self.success,) = _get_struct_B().unpack(str[start:end]) self.success = bool(self.success) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status_message = str[start:end].decode('utf-8', 'rosmsg') else: self.status_message = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sb'%length start = end s = struct.Struct(pattern) end += s.size self.status = numpy.frombuffer(str[start:end], dtype=numpy.int8, count=length) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) self.messages = [] for i in range(0, length): start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: val1 = str[start:end].decode('utf-8', 'rosmsg') else: val1 = str[start:end] self.messages.append(val1) return self except struct.error as e: raise genpy.DeserializationError(e) # most likely buffer underfill _struct_I = genpy.struct_I def _get_struct_I(): global _struct_I return _struct_I _struct_B = None def _get_struct_B(): global _struct_B if _struct_B is None: _struct_B = struct.Struct("<B") return _struct_B class SetVisualMeshes(object): _type = 'deepracer_msgs/SetVisualMeshes' _md5sum = 'a09fb2814d823a8b3a634fc955be2d1a' _request_class = SetVisualMeshesRequest _response_class = SetVisualMeshesResponse

33.459605

145

0.607555

2,459

18,637

4.463603

0.090281

0.065598

0.050109

0.044916

0.847941

0.841746

0.831359

0

0.020886

0.262703

18,637

556

146

33.519784

0.777891

0.13382

0

0.876087

1

0

0.100216

0.022101

0

0.00127

0

1

0.036957

false

0

0.019565

0

0.121739

0

null

0

1

0

1

0

null

0

8

b370f8c696e4d36b5534754f72d32abbfde04180

140

py

Python

icedata/datasets/fridge/__init__.py

davanstrien/icedata

fdab4d47f68c75bc11b0a97599d46fa8107786f4

[ "Apache-2.0" ]

null

icedata/datasets/fridge/__init__.py

davanstrien/icedata

fdab4d47f68c75bc11b0a97599d46fa8107786f4

[ "Apache-2.0" ]

null

icedata/datasets/fridge/__init__.py

davanstrien/icedata

fdab4d47f68c75bc11b0a97599d46fa8107786f4

[ "Apache-2.0" ]

null

from icedata.datasets.fridge.data import * from icedata.datasets.fridge.parsers import * from icedata.datasets.fridge import trained_models

35

50

0.842857

19

140

6.157895

0.473684

0.282051

0.487179

0.641026

0.529915

0

0.085714

140

3

51

46.666667

0.914063

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

2ffa64ae20dc9f4aa56a00e9e34afd5742b32984

51,360

py

Python

frozen/imagedata.py

ayoy/micropython-waveshare-epd

58859f5d0158987c84fb20e3920af0962b37de61

[ "MIT" ]

45

2018-04-02T22:24:47.000Z

2022-03-27T14:34:06.000Z

frozen_modules/fonts/imagedata.py

lemariva/uPyEINK

8778239b9dfe32b0d4535db0045a7feb1c131d5c

[ "Apache-2.0" ]

2

2018-09-19T09:39:20.000Z

2019-05-23T09:56:29.000Z

frozen/imagedata.py

ayoy/micropython-waveshare-epd

58859f5d0158987c84fb20e3920af0962b37de61

[ "MIT" ]

16

2018-04-08T21:34:28.000Z

2022-03-18T16:00:38.000Z

IMAGE_BLACK = [ # 0X00,0X01,0XC8,0X00,0XC8,0X00, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF7,0XFF, 0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE1,0XFE,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XE3,0XFF,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XFF,0X9F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0X00,0X00,0X01, 0XFF,0XFF,0XE7,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0XFF,0XFF,0XE3,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFE,0XFF,0XFF,0XE3,0XFF,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XE1,0XFE,0X1F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XF0,0XFC,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XF0, 0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XF8,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF, 0XFF,0XFE,0X01,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X7E,0XFF,0XFF,0XFB,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0X3E,0XFF,0XFF,0XE0,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF, 0XFF,0XF0,0X3E,0XFF,0XFF,0XC6,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XE0,0XCE,0XFF,0XFF,0XCE,0X7F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF, 0XFF,0XFF,0XFF,0X81,0X86,0XFF,0XFF,0XCE,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0X02,0X06,0XFF,0XFF, 0XC6,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFE,0XFF,0XFF,0XFF,0XFE,0X0C,0X02,0XFF,0XFF,0XE0,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFE,0X18,0X02, 0XFF,0XFF,0XFB,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFE,0X20,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFE, 0XC0,0X02,0XFF,0XFF,0XFF,0X03,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0X00,0X02,0XFF,0XFF,0XF8,0X00,0X7F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF, 0XFF,0XFF,0X00,0X02,0XFF,0XFF,0XF0,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0X80,0X06,0XFF,0XFF,0XE0, 0XCC,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE, 0XFF,0XFF,0XFF,0XFF,0XC0,0X0E,0XFF,0XFF,0XE3,0XC7,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XC0,0X0E,0XFF, 0XFF,0XE7,0XE7,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0X00,0X1E,0XFF,0XFF,0XE7,0XE7,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFC,0X00, 0X3E,0XFF,0XFF,0XE3,0XC7,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFE,0XFF,0X83,0XFF,0XF0,0X00,0X7E,0XFF,0XFF,0XE0,0X07,0X1F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFC,0X01,0XFF, 0XE0,0X00,0XFE,0XFF,0XFF,0XF0,0X0F,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XF0,0X07,0XFF,0X80,0X01,0XFE,0XFF,0XFF,0XF8,0X1F, 0XBF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XC0, 0X18,0XFE,0X00,0X03,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XC0,0XE0,0XF8,0X00,0X0F,0XFE,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFE,0XC7,0X00,0XE0,0X00,0X1F,0XFE,0XFF,0XFF,0XFF,0XFF,0X9F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XDC,0X00,0XC0,0X00,0X3F,0XFE, 0XFF,0XFF,0XF8,0X3F,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFE,0XE0,0X00,0X00,0X00,0XFF,0XFE,0XFF,0XFF,0XF0,0X0F,0X1F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XC0,0X00,0X00,0X03, 0XFF,0XFE,0XFF,0XFF,0XE0,0X03,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFE,0XE0,0X00,0X00,0X07,0XFF,0XFE,0XFF,0XFF,0XE3,0XC1,0X9F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XE0,0X00, 0X00,0X1F,0XFF,0XFE,0XFF,0XFF,0XE7,0XE0,0X9F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XF0,0X00,0X00,0XFF,0XFF,0XFE,0XFF,0XFF,0XE7, 0XF8,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE, 0XF8,0X00,0X03,0XFF,0XFF,0XFE,0XFF,0XFF,0XE7,0XFC,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFC,0X00,0X3F,0XFF,0XFF,0XFE,0XFF, 0XFF,0XE3,0XFE,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFE,0XFF,0XB7,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XF1,0XFF,0X1F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFE,0XFF,0XFF,0XF3,0XFF,0X9F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XDF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF, 0XFF,0X87,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XC3,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE, 0XFF,0XFF,0XFF,0XE3,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFE,0X7F,0XFF,0XFF,0XFF,0XFF,0XFC,0XFF,0XFF,0XFF,0XF3,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X00,0X00,0X00,0X00, 0X00,0X01,0XFF,0XFF,0XFF,0XE3,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC3,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X87,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X1F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0X3F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X1F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X87,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XCF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X70,0X3F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFA,0XFF,0XFF,0XFF,0XFF,0XF0,0X20,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XE0,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X1F,0XFF,0XFF,0XFF,0XE0, 0X02,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X00,0X00,0X0F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X00,0X0F,0XFF,0XFF,0XFF,0XE3,0X87,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFC,0X00,0X00,0X03,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0X00,0X07,0XFF,0XFF, 0XFF,0XE7,0X8F,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X00,0X00,0X01,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFE,0X00,0X02,0X7F,0XFF,0XFF,0XE7,0XCF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XE0,0X00,0X00,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0X00,0X00, 0X7F,0XFF,0XFF,0XE7,0XCF,0X9F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0X00,0X00, 0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X00,0X00,0XFF,0XFF,0XFF,0XE3,0XFF,0X1F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X0F,0XFE,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8, 0X30,0X00,0XFF,0XFF,0XFF,0XF3,0XFE,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0XFF, 0XFF,0XE0,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X30,0X00,0XFF,0XFF,0XFF,0XF7,0XFF, 0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X81,0XFF,0XFF,0XF8,0X1F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF0,0X00,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X83,0XFF,0XFF,0XF8,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X00,0X00,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X83,0XFF,0XFF,0XFC,0X1F,0XFF,0XFF, 0XFF,0XFF,0XFF,0X90,0X00,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0X1F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X83,0XFF,0XFF,0XFC,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0X10,0X00,0X00,0XFF, 0XFF,0XFF,0XF8,0X1F,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X83,0XFF,0XFF,0XFC,0X1F, 0XFF,0XFF,0XFF,0XFF,0XFC,0X10,0X00,0X00,0XFF,0XFF,0XFF,0XF0,0X0F,0X1F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X81,0XFF,0XFF,0XF8,0X1F,0XFF,0XFF,0XFF,0XFF,0XF8,0X18,0X30, 0X00,0XFF,0XFF,0XFF,0XE0,0X03,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0XFF,0XFF, 0XF0,0X3F,0XFF,0XFF,0XFF,0XFF,0XF8,0X08,0X38,0X00,0XFF,0XFF,0XFF,0XE3,0XC1,0X9F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X1F,0XFF,0X80,0X3F,0XFF,0XFF,0XFF,0XFF,0XF0, 0X08,0X30,0X01,0XFF,0XFF,0XFF,0XE7,0XF0,0X9F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0, 0X00,0X00,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XE0,0X08,0X00,0X01,0XFF,0XFF,0XFF,0XE7, 0XF8,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0X00,0X00,0X7F,0XFF,0XFF,0XFF, 0XFF,0XE0,0XE4,0X00,0X01,0XFF,0XFF,0XFF,0XE7,0XFC,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF0,0X00,0X00,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0XE2,0X00,0X03,0XFF,0XFF, 0XFF,0XE3,0XFE,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X00,0X00,0X03,0XFF,0XFF, 0XFF,0XFF,0XFF,0XC0,0XE2,0X00,0X07,0XFF,0XFF,0XFF,0XF1,0XFF,0X1F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFE,0X00,0X00,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X41,0X00,0X0F, 0XFF,0XFF,0XFF,0XF3,0XFF,0X9F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0X7F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0XC0,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00, 0X30,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0X07,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XC0,0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0X00,0X7F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X03,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XC0,0X40,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X80,0X00,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0XE0,0X00,0X7F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0X00,0X00,0X07,0XFF, 0XFF,0XFF,0XFF,0XFF,0XE0,0XE0,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF8,0X00,0X00,0X01,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0XE0,0X00, 0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0X00, 0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0X00,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XF0, 0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0, 0X00,0X60,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XF8,0X00,0X01,0X1F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0X7F,0XFF,0XC0,0X3F,0XFF,0XFF,0XFF, 0XFF,0XF8,0X00,0X03,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X81,0XFF,0XFF,0XF0,0X1F,0XFF,0XFF,0XFF,0XFF,0XFC,0X00,0X07,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X83,0XFF,0XFF,0XF8,0X1F,0XFF, 0XFF,0XFF,0XFF,0XFF,0X00,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X83,0XFF,0XFF,0XFC,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0X3F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X83,0XFF,0XFF,0XFC, 0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X83,0XFF,0XFF,0XFC,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X83,0XFF, 0XFF,0XF8,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X81,0XFF,0XFF,0XF0,0X3F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X80,0X7F,0XFF,0XC0,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0X00,0X00,0X3F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XE0,0X00,0X00,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X00,0X00,0X00,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF8,0X00,0X00,0X01,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0X00,0X00, 0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFC,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0XFF,0XF0,0X7F,0XFF,0XFF,0XFF,0XFF,0X00,0X00, 0X00,0X01,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0, 0X7F,0XE0,0X3F,0XFF,0XFF,0XFF,0XFD,0X80,0X00,0X00,0X03,0X1F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X3F,0XE0,0X1F,0XFF,0XFF,0XFF,0XF8, 0X80,0X00,0X00,0X02,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X80,0X3F,0XC0,0X1F,0XFF,0XFF,0XFF,0XF0,0X40,0X00,0X00,0X04,0X0F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0X3F,0XC0,0X1F,0XFF,0XFF, 0XFF,0XF0,0X60,0X00,0X00,0X0C,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XC0,0X3F,0XE0,0X1F,0XFF,0XFF,0XFF,0XF0,0X20,0X00,0X00,0X08,0X07, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X7F,0XE0,0X3F, 0XFF,0XFF,0XFF,0XF0,0X30,0X00,0X00,0X10,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0XFF,0XF8,0X7F,0XFF,0XFF,0XFF,0XF0,0X10,0X00,0X00, 0X30,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X18,0X00,0X00,0X20,0X07,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X08, 0X00,0X00,0X60,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X04,0X00,0X00,0X40,0X07,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF0,0X06,0X00,0X00,0X80,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X02,0X00,0X01,0X80,0X07,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0X0F,0XFF,0XFF, 0XFF,0XFF,0XF0,0X03,0X00,0X01,0X00,0X07,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0X00,0X00, 0XFF,0XFF,0XFF,0XFF,0X3F,0XF8,0X03,0XFF,0XFF,0XFF,0XFF,0XF0,0X01,0X00,0X02,0X00, 0X07,0XFF,0XFF,0XFF,0XFF,0X00,0X00,0X00,0X00,0XFF,0XFF,0XFF,0XF8,0X07,0XF0,0X00, 0XFF,0XFF,0XFF,0XFF,0XF0,0X01,0X80,0X06,0X00,0X07,0XFF,0XFF,0XFF,0XFC,0X00,0X00, 0X00,0X00,0XFF,0XFF,0XFF,0XF0,0X01,0XE0,0X00,0X7F,0XFF,0XFF,0XFF,0XF0,0X00,0X80, 0X04,0X00,0X07,0XFF,0XFF,0XFF,0XF0,0X00,0X38,0X00,0X00,0XFF,0XFF,0XFF,0XE0,0X00, 0XC0,0X00,0X7F,0XFF,0XFF,0XFF,0XF0,0X00,0X40,0X08,0X00,0X07,0XFF,0XFF,0XFF,0XE0, 0X00,0XFE,0X00,0X00,0XFF,0XFF,0XFF,0XC0,0X00,0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XF0, 0X00,0X40,0X08,0X00,0X07,0XFF,0XFF,0XFF,0XC0,0X03,0XFF,0X80,0X00,0XFF,0XFF,0XFF, 0XC0,0X00,0X00,0XE0,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X20,0X10,0X00,0X07,0XFF,0XFF, 0XFF,0X80,0X0F,0XFF,0XF8,0X00,0XFF,0XFF,0XFF,0X81,0XF8,0X01,0XF8,0X3F,0XFF,0XFF, 0XFF,0XF0,0X00,0X30,0X30,0X00,0X07,0XFF,0XFF,0XFF,0X00,0X3F,0XFF,0XFC,0X00,0XFF, 0XFF,0XFF,0X83,0XFE,0X03,0XFC,0X1F,0XFF,0XFF,0XFF,0XF0,0X00,0X10,0X20,0X00,0X07, 0XFF,0XFF,0XFE,0X00,0XFF,0XE7,0XFE,0X00,0XFF,0XFF,0XFF,0X83,0XFE,0X07,0XFC,0X1F, 0XFF,0XFF,0XFF,0XF0,0X00,0X18,0X40,0X00,0X07,0XFF,0XFF,0XFC,0X01,0XFF,0X81,0XFF, 0X00,0XFF,0XFF,0XFF,0X87,0XFE,0X07,0XFC,0X1F,0XFF,0XFF,0XFF,0XF0,0X00,0X08,0XC0, 0X00,0X07,0XFF,0XFF,0XFC,0X01,0XFF,0X00,0X7F,0X00,0XFF,0XFF,0XFF,0X87,0XFC,0X0F, 0XFC,0X1F,0XFF,0XFF,0XFF,0XF0,0X00,0X04,0X80,0X00,0X07,0XFF,0XFF,0XF8,0X01,0XFF, 0XC0,0X7F,0X80,0XFF,0XFF,0XFF,0X87,0XFC,0X0F,0XFC,0X1F,0XFF,0XFF,0XFF,0XF0,0X00, 0X05,0X00,0X00,0X07,0XFF,0XFF,0XF8,0X00,0XFF,0XF8,0X00,0X00,0XFF,0XFF,0XFF,0X83, 0XF8,0X1F,0XFC,0X1F,0XFF,0XFF,0XFF,0XF0,0X00,0X03,0X00,0X00,0X07,0XFF,0XFF,0XF0, 0X00,0X1F,0XFE,0X00,0X00,0XFF,0XFF,0XFF,0X81,0XF0,0X0F,0XF8,0X1F,0XFF,0XFF,0XFF, 0XF0,0X00,0X03,0X00,0X00,0X07,0XFF,0XFF,0XF0,0X00,0X07,0XFF,0X80,0X00,0XFF,0XFF, 0XFF,0X80,0X00,0X07,0XF0,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X01,0X00,0X00,0X07,0XFF, 0XFF,0XF1,0XFF,0X81,0XFF,0X80,0X00,0XFF,0XFF,0XFF,0XC0,0X00,0X00,0XE0,0X3F,0XFF, 0XFF,0XFF,0XF0,0X00,0X01,0X80,0X00,0X07,0XFF,0XFF,0XE0,0XFF,0X00,0X7F,0X80,0X00, 0XFF,0XFF,0XFF,0XC0,0X00,0X40,0X00,0X3F,0XFF,0XFF,0XFF,0XF0,0X47,0X80,0X80,0X00, 0X07,0XFF,0XFF,0XE0,0X7F,0XC1,0X3F,0X80,0X00,0XFF,0XFF,0XFF,0XE0,0X00,0XE0,0X00, 0X7F,0XFF,0XFF,0XFF,0XF0,0X4F,0XC0,0X40,0X00,0X07,0XFF,0XFF,0XE0,0X3F,0XF9,0X4F, 0X00,0X00,0XFF,0XFF,0XFF,0XF0,0X03,0XE0,0X00,0XFF,0XFF,0XFF,0XFF,0XF0,0X4C,0X40, 0X40,0X00,0X07,0XFF,0XFF,0XE0,0X1F,0XFE,0X78,0X00,0X00,0XFF,0XFF,0XFF,0XFC,0X07, 0XF8,0X01,0XFF,0XFF,0XFF,0XFF,0XF0,0X64,0XC0,0X40,0X00,0X07,0XFF,0XFF,0XE0,0X0F, 0XFF,0X80,0X00,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0X03,0XFF,0XFF,0XFF,0XFF,0XF0, 0X7F,0XC0,0X40,0X00,0X07,0XFF,0XFF,0XE0,0X05,0XFF,0XF0,0X00,0X00,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X1F,0X00,0XC0,0X00,0X07,0XFF,0XFF, 0XE0,0X00,0X3F,0XFC,0X00,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF0,0X00,0X00,0X80,0X00,0X07,0XFF,0XFF,0XE0,0X00,0X0F,0XFF,0X00,0X00,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X00,0X01,0X00,0X00,0X07, 0XFF,0XFF,0XE0,0X00,0X03,0XFF,0X80,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF0,0X00,0X01,0X00,0X00,0X07,0XFF,0XFF,0XE0,0X00,0X07,0XFF,0X80, 0X01,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X00,0X02,0X00, 0X00,0X07,0XFF,0XFF,0XE0,0X00,0X3F,0XFF,0X00,0X01,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X06,0X00,0X00,0X07,0XFF,0XFF,0XE0,0X00,0XFF, 0XFC,0X00,0X01,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X00, 0X05,0X00,0X00,0X07,0XFF,0XFF,0XE0,0X01,0XFF,0XE0,0X00,0X01,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X0D,0X80,0X00,0X07,0XFF,0XFF,0XE0, 0X01,0XFF,0X00,0X00,0X03,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF, 0XF0,0X00,0X08,0X80,0X00,0X07,0XFF,0XFF,0XE0,0X01,0XFF,0X80,0X00,0X03,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X10,0X40,0X00,0X07,0XFF, 0XFF,0XE0,0X00,0XFF,0XF0,0X00,0X03,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X3F,0XFF, 0XFF,0XFF,0XF0,0X00,0X10,0X40,0X00,0X07,0XFF,0XFF,0XE0,0X00,0X1F,0XFE,0X00,0X07, 0XFF,0XFF,0XFF,0XC0,0X00,0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X20,0X20,0X00, 0X07,0XFF,0XFF,0XE0,0X00,0X03,0XFF,0X80,0X07,0XFF,0XFF,0XFF,0X80,0X00,0X00,0X00, 0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X60,0X30,0X00,0X07,0XFF,0XFF,0XE0,0X00,0X07,0XFF, 0X80,0X0F,0XFF,0XFF,0XFF,0X80,0X00,0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0X40, 0X10,0X00,0X07,0XFF,0XFF,0XE0,0X00,0X3F,0XFF,0X80,0X1F,0XFF,0XFF,0XFF,0X80,0X00, 0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XF0,0X00,0XC0,0X08,0X00,0X07,0XFF,0XFF,0XE0,0X01, 0XFF,0XFF,0X00,0X1F,0XFF,0XFF,0XFF,0X80,0X00,0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XF0, 0X00,0X80,0X0C,0X00,0X07,0XFF,0XFF,0XE0,0X01,0XFF,0XF8,0X00,0X3F,0XFF,0XFF,0XFF, 0X80,0X00,0X00,0X00,0X3F,0XFF,0XFF,0XFF,0XF0,0X01,0X80,0X04,0X00,0X07,0XFF,0XFF, 0XE0,0X01,0XFF,0XE0,0X00,0X7F,0XFF,0XFF,0XFF,0XC0,0X00,0X00,0X00,0X3F,0XFF,0XFF, 0XFF,0XF0,0X01,0X00,0X02,0X00,0X07,0XFF,0XFF,0XE0,0X01,0XFE,0X00,0X00,0XFF,0XFF, 0XFF,0XFF,0XC0,0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X02,0X00,0X03,0X00,0X07, 0XFF,0XFF,0XE0,0X01,0XF0,0X00,0X03,0XFF,0XFF,0XFF,0XFF,0XE0,0XFF,0XFF,0XF8,0X3F, 0XFF,0XFF,0XFF,0XF0,0X06,0X00,0X01,0X00,0X07,0XFF,0XFF,0XE0,0X01,0X80,0X00,0X07, 0XFF,0XFF,0XFF,0XFF,0XE0,0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X04,0X00,0X01, 0X80,0X07,0XFF,0XFF,0XE0,0X00,0X00,0X00,0X1F,0XFF,0XFF,0XFF,0XFF,0XE0,0XFF,0XFF, 0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X0C,0X00,0X00,0X80,0X07,0XFF,0XFF,0XE0,0X00,0X00, 0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X08, 0X00,0X00,0X40,0X07,0XFF,0XFF,0XE0,0X00,0X00,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0, 0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF,0XF0,0X18,0X00,0X00,0X60,0X07,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X3F,0XFF,0XFF,0XFF, 0XF0,0X10,0X00,0X00,0X20,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X20,0X00,0X00,0X10,0X07,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF0,0X60,0X00,0X00,0X18,0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X40,0X00,0X00,0X08, 0X07,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF8,0XC0,0X00,0X00,0X04,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X80,0X00, 0X00,0X04,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X00,0X00,0X00,0X02,0X3F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, ] IMAGE_RED = [ # 0X00,0X01,0XC8,0X00,0XC8,0X00, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFE,0X01,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XF8,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XF0,0X00, 0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XF0,0X00,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XE0,0X00,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XE1,0XE3,0X1F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XC3,0XF3,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XC3,0X3B,0X0F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XC3,0X0F,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XC3,0X0F,0X0F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XE3, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XC3,0X87,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XE0,0X7F,0XFF,0XFF,0XFF,0XFF,0XF1,0XC1, 0X03,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F, 0XFF,0XE0,0X0F,0XFF,0XFF,0XFF,0XFF,0XF1,0XE0,0X00,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFC,0X03,0XFF,0XFF,0XFF,0XFF, 0XF1,0XE0,0X00,0X1F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X8F,0XFF,0XFF,0X80,0X7F,0XFF,0XFF,0XFF,0XF1,0XF0,0X00,0X3F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XF0,0X1F,0XFF, 0XFF,0XFF,0XF1,0XF8,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0X00,0X1F,0XFF,0XFF,0XFF,0XF1,0XFE,0X00,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XF8,0X07, 0X8F,0XFF,0XFF,0XFF,0XF1,0XFF,0X87,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XE0,0X1F,0X8F,0XC0,0X07,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XE0,0XFF,0XCF,0X80,0X07,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XE3,0XFF,0XEF,0X00,0X07,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0X1F,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0X1F,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFE,0X01,0XFF,0X1F,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XF0,0X01,0XFF, 0X9F,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XE0,0X01,0XE0,0X80,0X0F,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE7,0XFF,0XFF,0X8F,0XFF,0XE0, 0X03,0XE0,0X00,0X07,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XE0,0XFF,0XFF,0X8F,0XFF,0XE2,0X71,0XE0,0X00,0X07,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X3F,0XFF,0X8F, 0XFF,0XE7,0X39,0XE0,0X00,0X0F,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X07,0XFF,0X8F,0XFF,0XE7,0X38,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0X01, 0XFF,0X8F,0XFF,0XE3,0X10,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X7F,0X8F,0XFF,0XE3,0X01,0XFF,0X1F, 0XC7,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF8,0X3F,0X8F,0XFF,0XF3,0X81,0XFF,0X1F,0XC7,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X1F,0X8F,0XFF,0XFF,0XC7, 0XFF,0X1F,0XC7,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFE,0X00,0X0F,0X8F,0XFF,0XFF,0XFF,0XF8,0X00,0X07,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X07,0X87,0X8F,0XFF, 0XFF,0XFF,0XF8,0X00,0X0F,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XE0,0X1F,0XC7,0X8F,0XFF,0XFF,0XFF,0XF8,0X00,0X0F,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0XFF,0XC7, 0X8F,0XFE,0X00,0X01,0XFF,0X1E,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XFF,0XC7,0X8F,0XFE,0X00,0X01,0XFF,0X1F,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XC7,0X8F,0XFE,0X00,0X01,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFE,0X03,0XFF,0XF8, 0X7F,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XC0,0X7F,0XF8,0X1F,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X00,0XFF,0X8F,0XFF,0XF8, 0X1F,0XF8,0X07,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF0,0X00,0XFF,0X8F,0XFF,0XFE,0X03,0XF8,0X01,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F, 0XFF,0XFF,0X83,0XF8,0XC0,0X7F,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFC,0X07,0XF8,0XF0,0X1F,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0X31, 0XFF,0X8F,0XFF,0XE0,0X3F,0XF8,0XFC,0X07,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0X38,0XFF,0X8F,0XFF,0X00,0XFF,0XF8,0XFF, 0X03,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XE3,0X38,0XFF,0X8F,0XFE,0X07,0XFF,0XF8,0XFF,0XC3,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0X18,0XFF,0X8F,0XFE,0X00,0X01, 0XF8,0XFF,0XF3,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XE3,0X00,0XFF,0X8F,0XFE,0X00,0X01,0XF8,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0X80,0XFF,0X8F,0XFE, 0X00,0X01,0XF8,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0X81,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC3,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0X00,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFC,0X00,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFC,0X00,0X00,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFC,0X00,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XF1,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XF9,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XF8, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XF8,0XFF,0X80,0X00,0X00,0X00,0X00,0X00, 0X00,0X00,0X01,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XE1,0XF0,0XFF,0X80,0X00,0X00,0X00,0X00,0X00,0X00,0X00,0X01,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF0,0X01,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0X01,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFE,0X07,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8, 0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XE3,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XFF,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XE3,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0XFF, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0, 0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE1,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF9,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF8,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XE0,0X01,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X03,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XBF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X3F,0XFF,0XFF,0XFF,0X87,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X3F,0XFF,0XFF,0X1E, 0X03,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFE,0XFF,0XBF,0XCF,0XFE,0X3E,0X01,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0X3F,0XFF,0X8F, 0XFE,0X3C,0X01,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X3C,0X0F,0X9F,0XFE,0X3C,0X30,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0, 0X03,0XFF,0XFE,0X3C,0X78,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0XFE,0X38,0X78,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XC0,0X00,0XFF,0XFE,0X18,0X78,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0X7F,0XFE,0X00,0XF8, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X80,0X00,0X3F,0XFF,0X00,0XF8,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0X00,0X3F,0XFF, 0X01,0XF0,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0X00,0X3F,0XFF,0XC3,0XF1,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0X00,0X00, 0X31,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0X00,0X00,0X31,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X80,0X00,0X3F,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X80,0X00,0X3F,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X80,0X00,0X7F,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XC0,0X00,0X7F,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XE0,0X00,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF0,0X01,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X78,0X03,0XDF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0X3F, 0X1F,0X8F,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFE,0X7F,0XFF,0XCF,0XFF,0XFF,0XFF,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFE,0XFF,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X3F,0XFF,0XFF,0XFF,0XFF, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X3F,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X00,0X00,0X00,0X00,0X00,0X00,0X00,0X00,0X0F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X00,0X00,0X00, 0X00,0X00,0X00,0X00,0X00,0X0F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0X8F,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XF1, 0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF,0XFF, ]

81.009464

81

0.78014

10,016

51,360

4.0002

0.008087

1.331403

1.744621

2.038237

0.964908

0.946638

0.922977

0.895023

0.885838

0.874457

0

0.260941

0.024766

51,360

633

82

81.137441

0.538971

0.001188

0

0.352381

0

0.789531

0

1

0

false

0

null

1

0

1

0

null

0

1

0

11

2ffd5c6a2278ccbe2bff8023a1cc79e38bce5aae

12,453

py

Python

SimpleCV/tests/DrawingTests.py

quantombone/SimpleCV

6b88d767fea155377cce2a4435272361c5d10b91

[ "BSD-3-Clause" ]

2

2018-04-09T09:50:49.000Z

2021-05-16T20:13:52.000Z

SimpleCV/tests/DrawingTests.py

quantombone/SimpleCV

6b88d767fea155377cce2a4435272361c5d10b91

[ "BSD-3-Clause" ]

null

SimpleCV/tests/DrawingTests.py

quantombone/SimpleCV

6b88d767fea155377cce2a4435272361c5d10b91

[ "BSD-3-Clause" ]

null

import os, sys from SimpleCV import * from nose.tools import with_setup fname = "../sampleimages/color.jpg" def diffImgs(left,right): retVal = False diff = left-right c = diff.meanColor() thresh=2.0 if( c[0]<thresh and c[1]<thresh and c[2]<thresh): retVal = True return retVal def test_line(): img = Image(fname) test = Image("../sampleimages/line.png") lineL = DrawingLayer((img.width,img.height)) a = (20,20) b = (20,100) c = (100,100) d = (100,20) lineL.line(a,b,alpha=128,width=5) lineL.line(b,c,alpha=128) lineL.line(c,d, antialias=True) lineL.line(d,a,color=Color.PUCE) lineL.line(a,c,color=Color.PLUM, alpha=52) lineL.line(b,d,width=5) img.addDrawingLayer(lineL) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_lines(): img = Image(fname) test = Image("../sampleimages/lines.png") linesL = DrawingLayer((img.width,img.height)) a = (20,20) b = (20,100) c = (100,100) d = (100,20) pts = (a,b,c,d,a) linesL.lines(pts,alpha=128) #translate over and down 10 pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) linesL.lines(pts,color=Color.BEIGE,width=10) #translate over and down 10 pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) linesL.lines(pts,antialias=True) img.addDrawingLayer(linesL) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_rect_center(): img = Image(fname) test = Image("../sampleimages/rectC.png") rectC = DrawingLayer((img.width,img.height)) cxy = (img.width/2,img.height/2) wh = (200,100) rectC.centeredRectangle(cxy,wh,color=Color.BLUE) wh = (180,80) rectC.centeredRectangle(cxy,wh,color=Color.PUCE, width=5) wh = (160,60) rectC.centeredRectangle(cxy,wh,color=Color.FORESTGREEN, alpha=128,filled=True) wh = (140,40) rectC.centeredRectangle(cxy,wh,color=Color.GREEN,filled=True) img.addDrawingLayer(rectC) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_rect(): img = Image(fname) test = Image("../sampleimages/rectTR.png") rectTR = DrawingLayer((img.width,img.height)) tr = (150,50) wh = (200,100) rectTR.rectangle(tr,wh,color=Color.BLUE) tr = (170,70) rectTR.rectangle(tr,wh,color=Color.PUCE, width=5) tr = (190,90) rectTR.rectangle(tr,wh,color=Color.FORESTGREEN, alpha=128,filled=True) tr = (210,110) rectTR.rectangle(tr,wh,color=Color.GREEN,filled=True) img.addDrawingLayer(rectTR) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_poly(): img = Image(fname) test = Image("../sampleimages/poly.png") polyL = DrawingLayer((img.width,img.height)) a = (50,img.height-50) b = (250,img.height-50) c = (150,50) pts = (a,b,c) polyL.polygon(pts,alpha=128) pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) polyL.polygon(pts,antialias=True,width=3,alpha=210,filled=True,color=Color.LIME) #translate over and down 10 pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) polyL.polygon(pts,color=Color.BEIGE,width=10) #translate over and down 10 pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) polyL.polygon(pts,antialias=True,width=3,alpha=210) img.addDrawingLayer(polyL) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_circle(): img = Image(fname) test = Image("../sampleimages/circle.png") circleL = DrawingLayer((img.width,img.height)) c = (img.width/2,img.height/2) r = 150 circleL.circle(c,r,color=Color.RED,filled=True) r = 130 circleL.circle(c,r,color=Color.ORANGE,alpha=128,filled=True) r = 110 circleL.circle(c,r,color=Color.YELLOW,alpha=128,width=10) r = 100 circleL.circle(c,r,color=Color.GREEN) r = 90 circleL.circle(c,r,color=Color.BLUE,alpha=172) img.addDrawingLayer(circleL) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_ellipse(): img = Image(fname) test = Image("../sampleimages/ellipse.png") ellipseL = DrawingLayer((img.width,img.height)) cxy = (img.width/2,img.height/2) wh = (200,100) ellipseL.ellipse(cxy,wh,color=Color.BLUE) wh = (180,80) ellipseL.ellipse(cxy,wh,color=Color.PUCE, width=5) wh = (160,60) ellipseL.ellipse(cxy,wh,color=Color.FORESTGREEN, alpha=128,filled=True) wh = (140,40) ellipseL.ellipse(cxy,wh,color=Color.GREEN,filled=True) img.addDrawingLayer(ellipseL) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_bezier(): img = Image(fname) test = Image("../sampleimages/bez.png") bez = DrawingLayer((img.width,img.height)) a = (20,20) b = (img.width-20,20) c = (img.height-20,img.width-20) d = (20,img.height-20) e = (img.width/2,img.height/2) pts = (a,b,c,d,e) bez.bezier(pts,30) img.addDrawingLayer(bez) #translate over and down 10 pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) bez.bezier(pts,5,color=Color.RED) img.addDrawingLayer(bez) pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) bez.bezier(pts,30,color=Color.GREEN, alpha=128) img.addDrawingLayer(bez) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_font(): img = Image(fname) test = Image("../sampleimages/words.png") words = DrawingLayer((img.width,img.height)) words.setDefaultColor(Color.RED) pos = (30,30) words.setFontSize(30) words.text("THIS IS BIG",pos) pos = (50,50) words.setFontSize(10) words.text("THIS IS SMALL",pos) pos = (70,70) words.setFontSize(20) words.text("THIS IS medium",pos) pos = (90,90) words.setFontBold(True) words.text("THIS IS bold",pos) pos = (110,110) words.setFontItalic(True) words.text("THIS IS italic",pos) pos = (130,130) words.setFontUnderline(True) words.text("THIS IS underline",pos) words.setFontBold(False) words.setFontItalic(False) words.setFontUnderline(False) pos = (150,150) words.text("THIS IS PUCE, YES PUCE",pos,color=Color.PUCE) pos = (170,170) words.text("This is magical text",pos,color=Color.PLUM,alpha=128) pos = (190,190) words.ezViewText("Can you read this better?",pos) img.addDrawingLayer(words) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_layers(): img = Image(fname) test = Image("../sampleimages/layers.png") lineL = DrawingLayer((img.width,img.height)) a = (20,20) b = (20,100) c = (100,100) d = (100,20) lineL.line(a,b,alpha=128,width=5) lineL.line(b,c,alpha=128) lineL.line(c,d, antialias=True) lineL.line(d,a,color=Color.PUCE) lineL.line(a,c,color=Color.PLUM, alpha=52) lineL.line(b,d,width=5) circleL = DrawingLayer((img.width,img.height)) c = (img.width/2,img.height/2) r = 150 circleL.circle(c,r,color=Color.RED,filled=True) r = 130 circleL.circle(c,r,color=Color.ORANGE,alpha=128,filled=True) r = 110 circleL.circle(c,r,color=Color.YELLOW,alpha=128,width=10) r = 100 circleL.circle(c,r,color=Color.GREEN) r = 90 circleL.circle(c,r,color=Color.BLUE,alpha=172) bez = DrawingLayer((img.width,img.height)) a = (20,20) b = (img.width-20,20) c = (img.height-20,img.width-20) d = (20,img.height-20) e = (img.width/2,img.height/2) pts = (a,b,c,d,e) bez.bezier(pts,30) #translate over and down 10 pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) bez.bezier(pts,5,color=Color.RED) pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) bez.bezier(pts,30,color=Color.GREEN, alpha=128) words = DrawingLayer((img.width,img.height)) words.setDefaultColor(Color.RED) pos = (30,30) words.setFontSize(30) words.text("THIS IS BIG",pos) pos = (50,50) words.setFontSize(10) words.text("THIS IS SMALL",pos) pos = (70,70) words.setFontSize(20) words.text("THIS IS medium",pos) pos = (90,90) words.setFontBold(True) words.text("THIS IS bold",pos) pos = (110,110) words.setFontItalic(True) words.text("THIS IS italic",pos) pos = (130,130) words.setFontUnderline(True) words.text("THIS IS underline",pos) words.setFontBold(False) words.setFontItalic(False) words.setFontUnderline(False) pos = (150,150) words.text("THIS IS PUCE, YES PUCE",pos,color=Color.PUCE) pos = (170,170) words.text("This is magical text",pos,color=Color.PLUM,alpha=128) pos = (190,190) words.ezViewText("Can you read this better?",pos) img.addDrawingLayer(lineL) img.addDrawingLayer(circleL) img.addDrawingLayer(bez) img.addDrawingLayer(words) temp = img.applyLayers([0,2,3]) if(diffImgs(temp,test)): pass else: assert False def test_alpha(): img = Image(fname) test = Image("../sampleimages/flatlayers.png") lineL = DrawingLayer((img.width,img.height)) a = (20,20) b = (20,100) c = (100,100) d = (100,20) lineL.line(a,b,alpha=128,width=5) lineL.line(b,c,alpha=128) lineL.line(c,d, antialias=True) lineL.line(d,a,color=Color.PUCE) lineL.line(a,c,color=Color.PLUM, alpha=52) lineL.line(b,d,width=5) circleL = DrawingLayer((img.width,img.height)) c = (img.width/2,img.height/2) r = 150 circleL.circle(c,r,color=Color.RED,filled=True) r = 130 circleL.circle(c,r,color=Color.ORANGE,alpha=128,filled=True) r = 110 circleL.circle(c,r,color=Color.YELLOW,alpha=128,width=10) r = 100 circleL.circle(c,r,color=Color.GREEN) r = 90 circleL.circle(c,r,color=Color.BLUE,alpha=172) bez = DrawingLayer((img.width,img.height)) a = (20,20) b = (img.width-20,20) c = (img.height-20,img.width-20) d = (20,img.height-20) e = (img.width/2,img.height/2) pts = (a,b,c,d,e) bez.bezier(pts,30) #translate over and down 10 pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) bez.bezier(pts,5,color=Color.RED) pts = map(lambda x: ((x[0]+10),(x[1]+10)),pts) bez.bezier(pts,30,color=Color.GREEN, alpha=128) words = DrawingLayer((img.width,img.height)) words.setDefaultColor(Color.RED) pos = (30,30) words.setFontSize(30) words.text("THIS IS BIG",pos) pos = (50,50) words.setFontSize(10) words.text("THIS IS SMALL",pos) pos = (70,70) words.setFontSize(20) words.text("THIS IS medium",pos) pos = (90,90) words.setFontBold(True) words.text("THIS IS bold",pos) pos = (110,110) words.setFontItalic(True) words.text("THIS IS italic",pos) pos = (130,130) words.setFontUnderline(True) words.text("THIS IS underline",pos) words.setFontBold(False) words.setFontItalic(False) words.setFontUnderline(False) pos = (150,150) words.text("THIS IS PUCE, YES PUCE",pos,color=Color.PUCE) pos = (170,170) words.text("This is magical text",pos,color=Color.PLUM,alpha=128) pos = (190,190) words.ezViewText("Can you read this better?",pos) lineL.setLayerAlpha(128) circleL.setLayerAlpha(128) bez.setLayerAlpha(128) words.setLayerAlpha(128) img.addDrawingLayer(lineL) img.addDrawingLayer(circleL) img.addDrawingLayer(bez) img.addDrawingLayer(words) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False def test_sprites(): img = Image(fname) test = Image("../sampleimages/sprites.png") sprites = DrawingLayer((img.width,img.height)) sprites.sprite("../sampleimages/logo.png",(0,0),alpha=128, rot=45,scale=1.5) mySprite = Image("../sampleimages/logo.png").toPygameSurface() sprites.sprite(mySprite,(100,100),alpha=128, rot=45,scale=1.5) sprites.sprite(mySprite,(200,0)) sprites.sprite(mySprite,(0,200), rot=45,scale=1) img.addDrawingLayer(sprites) temp = img.applyLayers() if(diffImgs(temp,test)): pass else: assert False

30.597052

84

0.622019

1,835

12,453

4.213624

0.082289

0.06208

0.040352

0.04656

0.867693

0.859286

0.770305

0.765132

0.747284

0.734868

0

0.069824

0.213362

12,453

407

85

30.597052

0.719477

0.014615

0

0.775457

0

0.067265

0.031064

0

0.031332

1

0.033943

false

0.031332

0.007833

0

0.044386

0

null

0

1

0

1

0

null

0

7

643f261b2da2b888be1b49b6ee50f311ff6cf58b

5,888

py

Python

CAAPR/CAAPR_AstroMagic/PTS/pts/modeling/basics/instruments.py

wdobbels/CAAPR

50d0b32642a61af614c22f1c6dc3c4a00a1e71a3

[ "MIT" ]

7

2016-05-20T21:56:39.000Z

2022-02-07T21:09:48.000Z

CAAPR/CAAPR_AstroMagic/PTS/pts/modeling/basics/instruments.py

wdobbels/CAAPR

50d0b32642a61af614c22f1c6dc3c4a00a1e71a3

[ "MIT" ]

1

2019-03-21T16:10:04.000Z

2019-03-22T17:21:56.000Z

CAAPR/CAAPR_AstroMagic/PTS/pts/modeling/basics/instruments.py

wdobbels/CAAPR

50d0b32642a61af614c22f1c6dc3c4a00a1e71a3

[ "MIT" ]

1

2020-05-19T16:17:17.000Z

#!/usr/bin/env python # -*- coding: utf8 -*- # ***************************************************************** # ** PTS -- Python Toolkit for working with SKIRT ** # ** © Astronomical Observatory, Ghent University ** # ***************************************************************** ## \package pts.modeling.basics.instruments Contains the SEDInstrument, FrameInstrument SimpleInstrument and FullInstruemnt classes. # ----------------------------------------------------------------- # Ensure Python 3 functionality from __future__ import absolute_import, division, print_function # ----------------------------------------------------------------- class SEDInstrument(object): """ This class ... """ def __init__(self, distance, inclination, azimuth, position_angle): """ This function ... :param distance: :param inclination: :param azimuth: :param position_angle: :return: """ self.distance = distance self.inclination = inclination self.azimuth = azimuth self.position_angle = position_angle # ----------------------------------------------------------------- @classmethod def from_projection(cls, projection): """ This function ... :param projection: :return: """ return cls(projection.distance, projection.inclination, projection.azimuth, projection.position_angle) # ----------------------------------------------------------------- class FrameInstrument(object): """ This class ... """ def __init__(self, distance, inclination, azimuth, position_angle, field_x, field_y, pixels_x, pixels_y, center_x, center_y): """ This function ... :param distance: :param inclination: :param azimuth: :param position_angle: :param field_x: :param field_y: :param pixels_x: :param pixels_y: :param center_x: :param center_y: """ self.distance = distance self.inclination = inclination self.azimuth = azimuth self.position_angle = position_angle self.field_x = field_x self.field_y = field_y self.pixels_x = pixels_x self.pixels_y = pixels_y self.center_x = center_x self.center_y = center_y # ----------------------------------------------------------------- @classmethod def from_projection(cls, projection): """ This function ... :param projection: :return: """ return cls(projection.distance, projection.inclination, projection.azimuth, projection.position_angle, projection.field_x_physical, projection.field_y_physical, projection.pixels_x, projection.pixels_y, projection.center_x, projection.center_y) # ----------------------------------------------------------------- class SimpleInstrument(object): """ This class ... """ def __init__(self, distance, inclination, azimuth, position_angle, field_x, field_y, pixels_x, pixels_y, center_x, center_y): """ This function ... :param distance: :param inclination: :param azimuth: :param position_angle: :param field_x: :param field_y: :param pixels_x: :param pixels_y: :param center_x: :param center_y: :return: """ self.distance = distance self.inclination = inclination self.azimuth = azimuth self.position_angle = position_angle self.field_x = field_x self.field_y = field_y self.pixels_x = pixels_x self.pixels_y = pixels_y self.center_x = center_x self.center_y = center_y # ----------------------------------------------------------------- @classmethod def from_projection(cls, projection): """ This function ... :param projection: :return: """ return cls(projection.distance, projection.inclination, projection.azimuth, projection.position_angle, projection.field_x_physical, projection.field_y_physical, projection.pixels_x, projection.pixels_y, projection.center_x, projection.center_y) # ----------------------------------------------------------------- class FullInstrument(object): """ This class ... """ def __init__(self, distance, inclination, azimuth, position_angle, field_x, field_y, pixels_x, pixels_y, center_x, center_y): """ This function ... :param distance: :param inclination: :param azimuth: :param position_angle: :param field_x: :param field_y: :param pixels_x: :param pixels_y: :param center_x: :param center_y: :return: """ self.distance = distance self.inclination = inclination self.azimuth = azimuth self.position_angle = position_angle self.field_x = field_x self.field_y = field_y self.pixels_x = pixels_x self.pixels_y = pixels_y self.center_x = center_x self.center_y = center_y # ----------------------------------------------------------------- @classmethod def from_projection(cls, projection): """ This function ... :param projection: :return: """ return cls(projection.distance, projection.inclination, projection.azimuth, projection.position_angle, projection.field_x_physical, projection.field_y_physical, projection.pixels_x, projection.pixels_y, projection.center_x, projection.center_y) # -----------------------------------------------------------------

29.004926

139

0.523947

526

5,888

5.596958

0.117871

0.088315

0.046196

0.024457

0.878397

0

0.000462

0.264436

5,888

202

140

29.148515

0.679058

0.351902

0

0.85

0

1

0.133333

false

0

0.016667

0

0.283333

0.016667

0

null

0

1

0

1

0

null

0

7

ff3c416979024eb946eaedb1ccd1a3e20ce5e777

23,127

py

Python

Jogo_da_forca.py

fabiobarreto-data-science/Data-Science---Let-s-Code

df60c8351141d3fcbd96589c4dd27e1054fed712

[ "MIT" ]

null

Jogo_da_forca.py

fabiobarreto-data-science/Data-Science---Let-s-Code

df60c8351141d3fcbd96589c4dd27e1054fed712

[ "MIT" ]

null

Jogo_da_forca.py

fabiobarreto-data-science/Data-Science---Let-s-Code

df60c8351141d3fcbd96589c4dd27e1054fed712

[ "MIT" ]

null

import random import time def venceu(): for c in range(0, 3): print(" \033[1;33mW\033[m\033[1;33mW\033[m \033[1;33mW\033[m\033[1;33mW\033[m") time.sleep(0.3) print(" \033[30;42mPARABÉNS, VOCÊ VENCEU!!\033[m") def fim(): # Função que finaliza o jogo. print() print() print("\033[1;33m WW\033[m") time.sleep(0.2) print("\033[1;33m ++++\033[m") time.sleep(0.2) print("\033[1;33m +++++++++\033[m") time.sleep(0.2) print("\033[1;33m ++++++++++++++++\033[m") time.sleep(0.2) print("\033[1;33m+++++++++++++++++++++++++\033[m") time.sleep(0.2) print("\033[1;31mOBRIGADO E VOLTE SEMPRE!!\033[m") time.sleep(0.2) print("\033[1;33m+++++++++++++++++++++++++\033[m") time.sleep(0.2) print("\033[1;33m ++++++++++++++++\033[m") time.sleep(0.2) print("\033[1;33m +++++++++\033[m") time.sleep(0.2) print("\033[1;33m ++++\033[m") time.sleep(0.2) print("\033[1;33m WW\033[m") def forca_vazia(): # Função que inicializa o jogo print("==================") print("|| ") print("|| JOGO DA FORCA ") print("|| BY Fábio Barreto ") print("|| ") print("|| ") print("\033[1;32mxxxxxxxxxxxxxxxxxxx\033[m") # Função quando erra a letra def erro_01(): print("==================") print("|| \033[7;30;41m(oo)\033[m ") print("|| ") print("|| ") print("|| ") print("|| ") print("\033[1;32mxxxxxxxxxxxxxxxxxxx\033[m") # Função quando erra a letra def erro_02(): print("==================") print("|| \033[7;30;41m(oo)\033[m ") print("|| \033[7;30;41m||\033[m ") print("|| \033[7;30;41m||\033[m ") print("|| \033[m") print("|| \033[m") print("\033[1;32mxxxxxxxxxxxxxxxxxxx\033[m") # Função do desenho quando erra a letra def erro_03(): print("==================") print("|| \033[7;30;41m(oo)\033[m ") print("|| \033[7;30;41m||===\033[m ") print("|| \033[7;30;41m||\033[m ") print("|| ") print("|| ") print("\033[1;32mxxxxxxxxxxxxxxxxxxx\033[m") # Função do desenho quando erra a letra def erro_04(): print("==================") print("|| \033[7;30;41m(oo)\033[m ") print("|| \033[7;30;41m====||====\033[m ") print("|| \033[7;30;41m||\033[m ") print("|| \033[7;30;41m||\033[m ") print("|| \033[m") print("|| \033[m") print("\033[1;32mxxxxxxxxxxxxxxxxxxx\033[m") # Função do desenho quando erra a letra def erro_05(): print("==================") print("|| \033[7;30;41m(oo)\033[m ") print("|| \033[7;30;41m====||====\033[m ") print("|| \033[7;30;41m||\033[m ") print("|| \033[7;30;41mMWWW\033[m ") print("|| \033[7;30;41mMW\033[m ") print("|| \033[7;30;41mMW\033[m ") print("\033[1;32mxxxxxxxxxxxxxxxxxxx\033[m") # Função do desenho quando erra a letra def erro_06(): print("==================") print("|| \033[7;30;41m(oo)\033[m ") print("|| \033[7;30;41m===||===\033[m ") print("|| \033[7;30;41m||\033[m ") print("|| \033[7;30;41mMWWW\033[m ") print("|| \033[7;30;41mMW\033[m \033[7;30;41mMW\033[m ") print("|| \033[7;30;41mMW\033[m \033[7;30;41mMW\033[m ") print("\033[1;32mxxxxxxxxxxxxxxxxxxx\033[m") print() print("\033[1;31;40mVOCÊ PERDEU!!\033[m") print(f"A palavra correta era \033[1;32;40m{escolha}!!\033[m") # Função quando erra a letra def erraLetraTexto(): print() print("\033[1;31;40m===============\033[m") print("\033[1;31;40mERROU A LETRA!!\033[m") print("\033[1;31;40m===============\033[m") print() def erro(erro): # Função que trabalha todos os erros e apresenta a forca e os desenhos if erro == 1: erro_01() for p in palavra: print(f"{p}", end=" ") elif erro == 2: erro_02() for p in palavra: print(f"{p}", end=" ") elif erro == 3: erro_03() for p in palavra: print(f"{p}", end=" ") elif erro == 4: erro_04() for p in palavra: print(f"{p}", end=" ") elif erro == 5: erro_05() for p in palavra: print(f"{p}", end=" ") elif erro == 6: erro_06() print() # Lista dos nomes lista_dos_nomes = ["TIBET", "NEUTRON", "URANO", "EINSTEIN", "ALECRIM", "BAHIA", "COQUEIRO"] # Lista para detectar se já foi digitada alguma letra lista_letras = [] # Escolhe um dos nomes na lista por sorteio escolha = random.choice(lista_dos_nomes).upper().strip() if escolha == "TIBET": forca_vazia() print("\033[7;31;40mDICA: País do centro asiático.\033[m") palavra = ["_", "_", "_", "_", "_"] print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() erroMsg = 0 while palavra != ["T", "I", "B", "E", "T"]: letra = str(input("\033[7;31;40mEscolha uma letra:\033[m ")).upper().strip() # Independente se o suário digitar maiúsculo ou minúsculos, o upper() deixa tudo em maiúsculo como na lista principal e o strip para tirar o espaços caso alguém digite um. print() if letra in lista_letras: # Avisa ao usuário que a letra já foi dita! print(f"\033[7;31;40mA letra {letra} já saiu, escolha novamente!!.\033[m") print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "T": palavra[0] = letra palavra[4] = letra lista_letras.append(letra) if palavra == ["T", "I", "B", "E", "T"]: venceu() break for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "I": palavra[1] = letra lista_letras.append(letra) if palavra == ["T", "I", "B", "E", "T"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "B": palavra[2] = letra lista_letras.append(letra) if palavra == ["T", "I", "B", "E", "T"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "E": palavra[3] = letra lista_letras.append(letra) if palavra == ["T", "I", "B", "E", "T"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra != "T" or letra != "I" or letra != "B" or letra != "E": # Caso as letras digitadas forem diferentes das contidas na palavra este bloco é ativado e aciona 2 funções erraLetraTexto() # Função para alertar que o usuário errou a letra erroMsg = erroMsg + 1 erro(erroMsg) # Função que trabalha todos os erros e apresenta a forca e os desenhos if erroMsg == 6: break elif escolha == "NEUTRON": forca_vazia() print("\033[7;31;40mDICA: Partícula subatômica.\033[m") palavra = ["_", "_", "_", "_", "_", "_", "_"] print() for p in palavra: print(f"{p}", end=" ") print() erroMsg = 0 while palavra != ["N", "E", "U", "T", "R", "O", "N"]: letra = str(input("\033[7;31;40mEscolha uma letra:\033[m ")).upper().strip() print() if letra in lista_letras: print(f"\033[7;31;40mA letra {letra} já saiu, escolha novamente!!\033[m") print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "N": palavra[0] = letra palavra[6] = letra lista_letras.append(letra) if palavra == ["N", "E", "U", "T", "R", "O", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "E": palavra[1] = letra lista_letras.append(letra) if palavra == ["N", "E", "U", "T", "R", "O", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "U": palavra[2] = letra lista_letras.append(letra) if palavra == ["N", "E", "U", "T", "R", "O", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "T": palavra[3] = letra lista_letras.append(letra) if palavra == ["N", "E", "U", "T", "R", "O", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "R": palavra[4] = letra lista_letras.append(letra) if palavra == ["N", "E", "U", "T", "R", "O", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "O": palavra[5] = letra lista_letras.append(letra) if palavra == ["N", "E", "U", "T", "R", "O", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra != "N" or letra != "E" or letra != "B" or letra != "E": erraLetraTexto() erroMsg = erroMsg + 1 erro(erroMsg) if erroMsg == 6: break elif escolha == "URANO": forca_vazia() print("\033[7;31;40mDICA: Planeta do Sistema Solar.\033[m") palavra = ["_", "_", "_", "_", "_"] print() for p in palavra: print(f"{p}", end=" ") print() erroMsg = 0 while palavra != ["U", "R", "A", "N", "O"]: letra = str(input("\033[7;31;40mEscolha uma letra:\033[m ")).upper().strip() print() if letra in lista_letras: print(f"\033[7;31;40mA letra {letra} já saiu, escolha novamente!!\033[m") print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "U": palavra[0] = letra lista_letras.append(letra) if palavra == ["U", "R", "A", "N", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "R": palavra[1] = letra lista_letras.append(letra) if palavra == ["U", "R", "A", "N", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "A": palavra[2] = letra lista_letras.append(letra) if palavra == ["U", "R", "A", "N", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "N": palavra[3] = letra lista_letras.append(letra) if palavra == ["U", "R", "A", "N", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "O": palavra[4] = letra lista_letras.append(letra) if palavra == ["U", "R", "A", "N", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra != "U" or letra != "R" or letra != "A" or letra != "N" or letra != "O": erraLetraTexto() erroMsg = erroMsg + 1 erro(erroMsg) if erroMsg == 6: break elif escolha == "EINSTEIN": forca_vazia() print("\033[7;31;40mDICA: Importante nome da física clássica.\033[m") palavra = ["_", "_", "_", "_", "_", "_", "_", "_"] print() for p in palavra: print(f"{p}", end=" ") print() erroMsg = 0 while palavra != ["E", "I", "N", "S", "T", "E", "I", "N"]: letra = str(input("\033[7;31;40mEscolha uma letra:\033[m ")).upper().strip() print() if letra in lista_letras: print(f"\033[7;31;40mA letra {letra} já saiu, escolha novamente!!\033[m") print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "E": palavra[0] = letra palavra[5] = letra lista_letras.append(letra) if palavra == ["E", "I", "N", "S", "T", "E", "I", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "I": palavra[1] = letra palavra[6] = letra lista_letras.append(letra) if palavra == ["E", "I", "N", "S", "T", "E", "I", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "N": palavra[2] = letra palavra[7] = letra lista_letras.append(letra) if palavra == ["E", "I", "N", "S", "T", "E", "I", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "T": palavra[4] = letra lista_letras.append(letra) if palavra == ["E", "I", "N", "S", "T", "E", "I", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "S": palavra[3] = letra lista_letras.append(letra) if palavra == ["E", "I", "N", "S", "T", "E", "I", "N"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra != "E" or letra != "I" or letra != "N" or letra != "S" or letra != "T": erraLetraTexto() erroMsg = erroMsg + 1 erro(erroMsg) if erroMsg == 6: break elif escolha == "ALECRIM": forca_vazia() print("\033[7;31;40mDICA: Erva aromática.\033[m") palavra = ["_", "_", "_", "_", "_", "_", "_"] print() for p in palavra: print(f"{p}", end=" ") print() erroMsg = 0 while palavra != ["A", "L", "E", "C", "R", "I", "M"]: letra = str(input("\033[7;31;40mEscolha uma letra:\033[m ")).upper().strip() print() if letra in lista_letras: print(f"\033[7;31;40mA letra {letra} já saiu, escolha novamente!!\033[m") print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "A": palavra[0] = letra lista_letras.append(letra) if palavra == ["A", "L", "E", "C", "R", "I", "M"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "L": palavra[1] = letra lista_letras.append(letra) if palavra == ["A", "L", "E", "C", "R", "I", "M"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "E": palavra[2] = letra lista_letras.append(letra) if palavra == ["A", "L", "E", "C", "R", "I", "M"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "C": palavra[3] = letra lista_letras.append(letra) if palavra == ["A", "L", "E", "C", "R", "I", "M"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "R": palavra[4] = letra lista_letras.append(letra) if palavra == ["A", "L", "E", "C", "R", "I", "M"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "I": palavra[5] = letra lista_letras.append(letra) if palavra == ["A", "L", "E", "C", "R", "I", "M"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "M": palavra[6] = letra lista_letras.append(letra) if palavra == ["A", "L", "E", "C", "R", "I", "M"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra != "A" or letra != "L" or letra != "E" or letra != "C" or letra != "R" or letra != "I" or letra != "M": erraLetraTexto() erroMsg = erroMsg + 1 erro(erroMsg) if erroMsg == 6: break elif escolha == "BAHIA": forca_vazia() print("\033[7;31;40mDICA: Time de futebol que já foi campeão Brasileiro.\033[m") palavra = ["_", "_", "_", "_", "_"] print() for p in palavra: print(f"{p}", end=" ") print() erroMsg = 0 while palavra != ["B", "A", "H", "I", "A"]: letra = str(input("\033[7;31;40mEscolha uma letra:\033[m ")).upper().strip() print() if letra in lista_letras: print(f"\033[7;31;40mA letra {letra} já saiu, escolha novamente!!\033[m") print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "B": palavra[0] = letra lista_letras.append(letra) if palavra == ["B", "A", "H", "I", "A"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "A": palavra[1] = letra palavra[4] = letra lista_letras.append(letra) if palavra == ["B", "A", "H", "I", "A"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "H": palavra[2] = letra lista_letras.append(letra) if palavra == ["B", "A", "H", "I", "A"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "I": palavra[3] = letra lista_letras.append(letra) if palavra == ["B", "A", "H", "I", "A"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra != "B" or letra != "A" or letra != "H" or letra != "I": erraLetraTexto() erroMsg = erroMsg + 1 erro(erroMsg) if erroMsg == 6: break elif escolha == "COQUEIRO": forca_vazia() print("\033[7;31;40mDICA: Árvore do litoral brasileiro de origem asiática.\033[m") palavra = ["_", "_", "_", "_", "_", "_", "_", "_"] print() for p in palavra: print(f"{p}", end=" ") print() erroMsg = 0 while palavra != ["C", "O", "Q", "U", "E", "I", "R", "O"]: letra = str(input("\033[7;31;40mEscolha uma letra:\033[m ")).upper().strip() print() if letra in lista_letras: print(f"\033[7;31;40mA letra {letra} já saiu, escolha novamente!!\033[m") print() for p in palavra: print(f"{p}", end=" ") # Uso o "for" para printar na tela apenas as letras, sem precisar dos colchetes em forma de lista print() elif letra == "C": palavra[0] = letra lista_letras.append(letra) if palavra == ["C", "O", "Q", "U", "E", "I", "R", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "O": palavra[1] = letra palavra[7] = letra lista_letras.append(letra) if palavra == ["C", "O", "Q", "U", "E", "I", "R", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "Q": palavra[2] = letra lista_letras.append(letra) if palavra == ["C", "O", "Q", "U", "E", "I", "R", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "U": palavra[3] = letra lista_letras.append(letra) if palavra == ["C", "O", "Q", "U", "E", "I", "R", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "E": palavra[4] = letra lista_letras.append(letra) if palavra == ["C", "O", "Q", "U", "E", "I", "R", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "I": palavra[5] = letra lista_letras.append(letra) if palavra == ["C", "O", "Q", "U", "E", "I", "R", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra == "R": palavra[6] = letra lista_letras.append(letra) if palavra == ["C", "O", "Q", "U", "E", "I", "R", "O"]: venceu() break for p in palavra: print(f"{p}", end=" ") print() elif letra != "C" or letra != "O" or letra != "Q" or letra != "U" or letra != "E" or letra != "I" or letra != "R": erraLetraTexto() erroMsg = erroMsg + 1 erro(erroMsg) if erroMsg == 6: break fim()

36.709524

257

0.437238

2,800

23,127

3.570357

0.070357

0.031209

0.03421

0.074122

0.882765

0.857957

0.846754

0.821346

0.812544

0.79874

0

0.062452

0.375492

23,127

629

258

36.767886

0.629717

0.076404

0

0.873311

0

0.018581

0.194928

0.051709

0

0.00159

0

1

0.018581

false

0

0.005068

0

0.023649

0.371622

0

null

0

1

0

1

0

null

0

7

ff547a1eb6fbb32e3e4bb0461112caf0160a3e7a

23,804

py

Python

deploy/clients/localtestclient.py

hwinther/lanot

f6700cacb3946535081624467b746fdfd38e021d

[ "Apache-2.0" ]

null

deploy/clients/localtestclient.py

hwinther/lanot

f6700cacb3946535081624467b746fdfd38e021d

[ "Apache-2.0" ]

null

deploy/clients/localtestclient.py

hwinther/lanot

f6700cacb3946535081624467b746fdfd38e021d

[ "Apache-2.0" ]

null

# coding=utf-8 # generated at 2018-10-12 21:38:39 import prometheus import socket import time import gc import json import prometheus.crypto import prometheus.misc import prometheus.psocket import prometheus.logging as logging gc.collect() # region LocalTestUdpClient class LocalTestUdpClientDigital0(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestUdpClientDigital0', 'tv', str) def value(self, **kwargs): self.send(b'tv', **kwargs) return self.recv() class LocalTestUdpClientRedLed(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestUdpClientRedLed', 'rv', str) def value(self, **kwargs): self.send(b'rv', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestUdpClientRedLed', 'r0') def off(self, **kwargs): self.send(b'r0', **kwargs) @prometheus.Registry.register('LocalTestUdpClientRedLed', 'r1') def on(self, **kwargs): self.send(b'r1', **kwargs) class LocalTestUdpClientBlueLed(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestUdpClientBlueLed', 'bv', str) def value(self, **kwargs): self.send(b'bv', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestUdpClientBlueLed', 'b0') def off(self, **kwargs): self.send(b'b0', **kwargs) @prometheus.Registry.register('LocalTestUdpClientBlueLed', 'b1') def on(self, **kwargs): self.send(b'b1', **kwargs) class LocalTestUdpClientHygrometer(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestUdpClientHygrometer', 'hr', str) def read(self, **kwargs): self.send(b'hr', **kwargs) return self.recv() class LocalTestUdpClientDht11(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestUdpClientDht11', 'dv', str) def value(self, **kwargs): self.send(b'dv', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestUdpClientDht11', 'dt', str) def temperature(self, **kwargs): self.send(b'dt', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestUdpClientDht11', 'dm') def measure(self, **kwargs): self.send(b'dm', **kwargs) @prometheus.Registry.register('LocalTestUdpClientDht11', 'dh', str) def humidity(self, **kwargs): self.send(b'dh', **kwargs) return self.recv() class LocalTestUdpClient(prometheus.misc.RemoteTemplate): def __init__(self, remote_host, remote_port=9195, bind_host='', bind_port=9195): prometheus.misc.RemoteTemplate.__init__(self) self.socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) self.socket.bind((bind_host, bind_port)) logging.info('listening on %s:%d' % (bind_host, bind_port)) self.socket.settimeout(0) self.remote_addr = (remote_host, remote_port) self.buffers = dict() self.splitChars = b'\n' self.endChars = b'\r' self.blue_led = LocalTestUdpClientBlueLed(self.send, self.recv) self.register(blue_led=self.blue_led) self.dht11 = LocalTestUdpClientDht11(self.send, self.recv) self.register(dht11=self.dht11) self.digital0 = LocalTestUdpClientDigital0(self.send, self.recv) self.register(digital0=self.digital0) self.hygrometer = LocalTestUdpClientHygrometer(self.send, self.recv) self.register(hygrometer=self.hygrometer) self.red_led = LocalTestUdpClientRedLed(self.send, self.recv) self.register(red_led=self.red_led) def send(self, data, **kwargs): if len(kwargs) is 0: args = b'' else: args = prometheus.args_to_bytes(kwargs) self.socket.sendto(data + self.endChars + args + self.splitChars, self.remote_addr) def try_recv(self, buffersize): try: return self.socket.recvfrom(buffersize) # data, addr except prometheus.psocket.socket_error: return None, None def recv_once(self, buffersize=10): data, addr = self.try_recv(buffersize) if data is None: return None if addr not in self.buffers: self.buffers[addr] = prometheus.Buffer(split_chars=self.splitChars, end_chars=self.endChars) self.buffers[addr].parse(data) bufferpacket = self.buffers[addr].pop() if bufferpacket is None: return None return bufferpacket.packet def recv(self, buffersize=20): return self.recv_timeout(buffersize, 0.5) def recv_timeout(self, buffersize, timeout): """ :param buffersize: int :param timeout: float :return: str """ timestamp = time.time() while (time.time() - timestamp) < timeout: data = self.recv_once(buffersize) if data is not None: return data return None @prometheus.Registry.register('LocalTestUdpClient', '1', str) def test1(self, **kwargs): self.send(b'1', **kwargs) return self.resolve_response(self.recv_timeout(20, 0.5)) @prometheus.Registry.register('LocalTestUdpClient', '3', str) def test3(self, **kwargs): self.send(b'3', **kwargs) return self.resolve_response(self.recv_timeout(20, 0.5)) @prometheus.Registry.register('LocalTestUdpClient', '2', str) def test2(self, **kwargs): self.send(b'2', **kwargs) return self.resolve_response(self.recv_timeout(20, 0.5)) @prometheus.Registry.register('LocalTestUdpClient', '5', str) def test5(self, **kwargs): self.send(b'5', **kwargs) return self.resolve_response(self.recv_timeout(20, 0.5)) @prometheus.Registry.register('LocalTestUdpClient', '4') def test4(self, **kwargs): self.send(b'4', **kwargs) @prometheus.Registry.register('LocalTestUdpClient', '7', str) def test7(self, **kwargs): self.send(b'7', **kwargs) return self.resolve_response(self.recv_timeout(20, 0.5)) @prometheus.Registry.register('LocalTestUdpClient', '6', str) def test6(self, **kwargs): self.send(b'6', **kwargs) return self.resolve_response(self.recv_timeout(20, 0.5)) @prometheus.Registry.register('LocalTestUdpClient', '8', str) def test8(self, **kwargs): self.send(b'8', **kwargs) return self.resolve_response(self.recv_timeout(20, 0.5)) # endregion # region LocalTestTcpClient class LocalTestTcpClientDigital0(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestTcpClientDigital0', 'tv', str) def value(self, **kwargs): self.send(b'tv', **kwargs) return self.recv() class LocalTestTcpClientRedLed(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestTcpClientRedLed', 'rv', str) def value(self, **kwargs): self.send(b'rv', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestTcpClientRedLed', 'r0') def off(self, **kwargs): self.send(b'r0', **kwargs) @prometheus.Registry.register('LocalTestTcpClientRedLed', 'r1') def on(self, **kwargs): self.send(b'r1', **kwargs) class LocalTestTcpClientBlueLed(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestTcpClientBlueLed', 'bv', str) def value(self, **kwargs): self.send(b'bv', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestTcpClientBlueLed', 'b0') def off(self, **kwargs): self.send(b'b0', **kwargs) @prometheus.Registry.register('LocalTestTcpClientBlueLed', 'b1') def on(self, **kwargs): self.send(b'b1', **kwargs) class LocalTestTcpClientHygrometer(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestTcpClientHygrometer', 'hr', str) def read(self, **kwargs): self.send(b'hr', **kwargs) return self.recv() class LocalTestTcpClientDht11(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestTcpClientDht11', 'dv', str) def value(self, **kwargs): self.send(b'dv', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestTcpClientDht11', 'dt', str) def temperature(self, **kwargs): self.send(b'dt', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestTcpClientDht11', 'dm') def measure(self, **kwargs): self.send(b'dm', **kwargs) @prometheus.Registry.register('LocalTestTcpClientDht11', 'dh', str) def humidity(self, **kwargs): self.send(b'dh', **kwargs) return self.recv() class LocalTestTcpClient(prometheus.misc.RemoteTemplate): def __init__(self, remote_host, remote_port=9195, bind_host=None, bind_port=9195): prometheus.misc.RemoteTemplate.__init__(self) self.socket = None # type: socket.socket self.bind_host = bind_host self.bind_port = bind_port self.remote_addr = (remote_host, remote_port) self.buffers = dict() self.split_chars = b'\n' self.end_chars = b'\r' self.blue_led = LocalTestTcpClientBlueLed(self.send, self.recv) self.register(blue_led=self.blue_led) self.dht11 = LocalTestTcpClientDht11(self.send, self.recv) self.register(dht11=self.dht11) self.digital0 = LocalTestTcpClientDigital0(self.send, self.recv) self.register(digital0=self.digital0) self.hygrometer = LocalTestTcpClientHygrometer(self.send, self.recv) self.register(hygrometer=self.hygrometer) self.red_led = LocalTestTcpClientRedLed(self.send, self.recv) self.register(red_led=self.red_led) def create_socket(self): self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) if self.bind_host is not None: logging.notice('bound to %s:%d' % (self.bind_host, self.bind_port)) self.socket.bind((self.bind_host, self.bind_port)) self.socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.socket.settimeout(5) logging.info('Connecting to %s' % repr(self.remote_addr)) self.socket.connect(self.remote_addr) def send_once(self, data, args): self.socket.send(data + self.end_chars + args + self.split_chars) def send(self, data, **kwargs): if len(kwargs) is 0: args = b'' else: args = prometheus.args_to_bytes(kwargs) if self.socket is None: self.create_socket() try: self.send_once(data, args) except prometheus.psocket.socket_error: self.create_socket() self.send_once(data, args) def try_recv(self, buffersize): try: return self.socket.recvfrom(buffersize) # data, addr except prometheus.psocket.socket_error: return None, None def recv(self, buffersize=10): data, addr = self.try_recv(buffersize) if data is None: return None if addr not in self.buffers: self.buffers[addr] = prometheus.Buffer(split_chars=self.split_chars, end_chars=self.end_chars) self.buffers[addr].parse(data) bufferpacket = self.buffers[addr].pop() if bufferpacket is None: return None return bufferpacket.packet @prometheus.Registry.register('LocalTestTcpClient', '1', str) def test1(self, **kwargs): self.send(b'1', **kwargs) return self.resolve_response(self.recv(50)) @prometheus.Registry.register('LocalTestTcpClient', '3', str) def test3(self, **kwargs): self.send(b'3', **kwargs) return self.resolve_response(self.recv(50)) @prometheus.Registry.register('LocalTestTcpClient', '2', str) def test2(self, **kwargs): self.send(b'2', **kwargs) return self.resolve_response(self.recv(50)) @prometheus.Registry.register('LocalTestTcpClient', '5', str) def test5(self, **kwargs): self.send(b'5', **kwargs) return self.resolve_response(self.recv(50)) @prometheus.Registry.register('LocalTestTcpClient', '4') def test4(self, **kwargs): self.send(b'4', **kwargs) @prometheus.Registry.register('LocalTestTcpClient', '7', str) def test7(self, **kwargs): self.send(b'7', **kwargs) return self.resolve_response(self.recv(50)) @prometheus.Registry.register('LocalTestTcpClient', '6', str) def test6(self, **kwargs): self.send(b'6', **kwargs) return self.resolve_response(self.recv(50)) @prometheus.Registry.register('LocalTestTcpClient', '8', str) def test8(self, **kwargs): self.send(b'8', **kwargs) return self.resolve_response(self.recv(50)) # endregion # region LocalTestJsonRestClient class LocalTestJsonRestClientDigital0(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestJsonRestClientDigital0', 'api/digital0/value', str) def value(self, **kwargs): self.send(b'api/digital0/value', **kwargs) return self.recv() class LocalTestJsonRestClientRedLed(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestJsonRestClientRedLed', 'api/red_led/value', str) def value(self, **kwargs): self.send(b'api/red_led/value', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestJsonRestClientRedLed', 'api/red_led/on') def on(self, **kwargs): self.send(b'api/red_led/on', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClientRedLed', 'api/red_led/off') def off(self, **kwargs): self.send(b'api/red_led/off', **kwargs) class LocalTestJsonRestClientBlueLed(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestJsonRestClientBlueLed', 'api/blue_led/value', str) def value(self, **kwargs): self.send(b'api/blue_led/value', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestJsonRestClientBlueLed', 'api/blue_led/on') def on(self, **kwargs): self.send(b'api/blue_led/on', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClientBlueLed', 'api/blue_led/off') def off(self, **kwargs): self.send(b'api/blue_led/off', **kwargs) class LocalTestJsonRestClientHygrometer(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestJsonRestClientHygrometer', 'api/hygrometer/read', str) def read(self, **kwargs): self.send(b'api/hygrometer/read', **kwargs) return self.recv() class LocalTestJsonRestClientDht11(prometheus.Prometheus): def __init__(self, send, recv): prometheus.Prometheus.__init__(self) self.send = send self.recv = recv @prometheus.Registry.register('LocalTestJsonRestClientDht11', 'api/dht11/measure') def measure(self, **kwargs): self.send(b'api/dht11/measure', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClientDht11', 'api/dht11/temperature', str) def temperature(self, **kwargs): self.send(b'api/dht11/temperature', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestJsonRestClientDht11', 'api/dht11/value', str) def value(self, **kwargs): self.send(b'api/dht11/value', **kwargs) return self.recv() @prometheus.Registry.register('LocalTestJsonRestClientDht11', 'api/dht11/humidity', str) def humidity(self, **kwargs): self.send(b'api/dht11/humidity', **kwargs) return self.recv() class LocalTestJsonRestClient(prometheus.misc.RemoteTemplate): def __init__(self, remote_host, remote_port=8080, bind_host=None, bind_port=9195): prometheus.misc.RemoteTemplate.__init__(self) self.socket = None # type: socket.socket self.bind_host = bind_host self.bind_port = bind_port self.remote_addr = (remote_host, remote_port) self.blue_led = LocalTestJsonRestClientBlueLed(self.send, self.recv) self.register(blue_led=self.blue_led) self.dht11 = LocalTestJsonRestClientDht11(self.send, self.recv) self.register(dht11=self.dht11) self.digital0 = LocalTestJsonRestClientDigital0(self.send, self.recv) self.register(digital0=self.digital0) self.hygrometer = LocalTestJsonRestClientHygrometer(self.send, self.recv) self.register(hygrometer=self.hygrometer) self.red_led = LocalTestJsonRestClientRedLed(self.send, self.recv) self.register(red_led=self.red_led) def create_socket(self): self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) if self.bind_host is not None: logging.notice('bound to %s:%d' % (self.bind_host, self.bind_port)) self.socket.bind((self.bind_host, self.bind_port)) self.socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.socket.settimeout(5) self.socket.connect(self.remote_addr) def send_once(self, data, args): if len(args) is not 0: args = b'?' + args request = b'GET /%s%s HTTP/1.1\r\nHost: %s\r\n' % (data, args, self.remote_addr[0].encode('utf-8')) self.socket.send(request) def send(self, data, **kwargs): if len(kwargs) is 0: args = b'' else: args = prometheus.args_to_bytes(kwargs) self.create_socket() self.send_once(data, args) def try_recv(self, buffersize): try: return self.socket.recvfrom(buffersize) # data, addr except prometheus.psocket.socket_error: return None, None def recv(self, buffersize=200): data, addr = self.try_recv(buffersize) self.socket.close() if data is None: return None # print('data: %s' % (repr(data))) head, body = data.split(b'\r\n\r\n', 1) json_body = json.loads(body) # print('json_body = %s' % repr(json_body)) value = json_body['value'] # print('value = %s' % repr(value)) # print(prometheus.is_py2) if type(value) is str or (prometheus.is_py2 and type(value) is unicode): value = value.encode('utf-8') # print('value = %s' % repr(value)) return value @prometheus.Registry.register('LocalTestJsonRestClient', 'v', str) def value(self, **kwargs): self.send(b'api/blue_led/value', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', 'v', str) def value(self, **kwargs): self.send(b'api/digital0/value', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '1') def on(self, **kwargs): self.send(b'api/blue_led/on', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClient', '2', str) def test2(self, **kwargs): self.send(b'api/test2', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', 'h', str) def humidity(self, **kwargs): self.send(b'api/dht11/humidity', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '8', str) def test8(self, **kwargs): self.send(b'api/test8', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', 'm') def measure(self, **kwargs): self.send(b'api/dht11/measure', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClient', 't', str) def temperature(self, **kwargs): self.send(b'api/dht11/temperature', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '6', str) def test6(self, **kwargs): self.send(b'api/test6', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', 'r', str) def read(self, **kwargs): self.send(b'api/hygrometer/read', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '4') def test4(self, **kwargs): self.send(b'api/test4', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClient', '5', str) def test5(self, **kwargs): self.send(b'api/test5', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '0') def off(self, **kwargs): self.send(b'api/red_led/off', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClient', '7', str) def test7(self, **kwargs): self.send(b'api/test7', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '1', str) def test1(self, **kwargs): self.send(b'api/test1', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', 'v', str) def value(self, **kwargs): self.send(b'api/dht11/value', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '3', str) def test3(self, **kwargs): self.send(b'api/test3', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', 'v', str) def value(self, **kwargs): self.send(b'api/red_led/value', **kwargs) return self.resolve_response(self.recv(200)) @prometheus.Registry.register('LocalTestJsonRestClient', '1') def on(self, **kwargs): self.send(b'api/red_led/on', **kwargs) @prometheus.Registry.register('LocalTestJsonRestClient', '0') def off(self, **kwargs): self.send(b'api/blue_led/off', **kwargs) # endregion

35.688156

107

0.653546

2,748

23,804

5.545124

0.068049

0.063

0.122851

0.085051

0.822024

0.788161

0.780877

0.77228

0.754823

0.736711

0

0.01819

0.210133

23,804

666

108

35.741742

0.792256

0.01924

0

0.700389

1

0.001946

0.11353

0.062776

0

1

0.20428

false

0

0.01751

0.001946

0.385214

0

null

0

1

0

1

0

null

0

1

0

9

ffb81bb078780b13f44c8ba2ea4227fae5a20327

538,242

py

Python

base.py

pauloacmelo/papelex_winthor

4993aba5c24c4ea7f203058f164c14bc19d64980

[ "MIT" ]

1

2020-06-14T04:59:42.000Z

base.py

pauloacmelo/papelex_winthor

4993aba5c24c4ea7f203058f164c14bc19d64980

[ "MIT" ]

null

base.py

pauloacmelo/papelex_winthor

4993aba5c24c4ea7f203058f164c14bc19d64980

[ "MIT" ]

null

#encoding=utf-8 import sys, time from PySide import QtGui, QtCore import cx_Oracle from collections import OrderedDict import urllib2 import json POPUP_WIDTH = 250 POPUP_HEIGHT = 60 POPUP_TITLE_HEIGHT = 10 POPUP_MESSAGE_HEIGHT = 20 POPUP_MARGIN = 15 POPUP_PADDING = 10 class MyPopup(QtGui.QWidget): def __init__(self, popups, title, message, timeout): QtGui.QWidget.__init__(self) self.popups = popups self.title = title self.message = message self.setWindowFlags(QtCore.Qt.WindowStaysOnTopHint | QtCore.Qt.FramelessWindowHint) self.toastThread = ToastThread(timeout) # start thread to remove display self.connect(self.toastThread, QtCore.SIGNAL("finished()"), self.toastDone) self.toastThread.start() def toastDone(self): self.close() self.popups.remove(self) self = None def paintEvent(self, event): dc = QtGui.QPainter(self) dc.setBrush(QtGui.QColor(197, 197, 197)) dc.drawRect(0, 0, POPUP_WIDTH-1, POPUP_HEIGHT-1) dc.setPen(QtGui.QColor(0, 0, 0)) dc.setFont(QtGui.QFont('Decorative', 11, QtGui.QFont.Bold)) dc.drawText( QtCore.QRect(POPUP_PADDING, POPUP_PADDING, POPUP_WIDTH - POPUP_PADDING, POPUP_TITLE_HEIGHT + POPUP_PADDING), QtCore.Qt.AlignLeft, self.title) dc.setFont(QtGui.QFont('Decorative', 10)) dc.drawText( QtCore.QRect(POPUP_PADDING, POPUP_HEIGHT - POPUP_MESSAGE_HEIGHT - POPUP_PADDING, POPUP_WIDTH - POPUP_PADDING, POPUP_HEIGHT - POPUP_PADDING), QtCore.Qt.AlignLeft, self.message) dc.end() class ToastThread(QtCore.QThread): def __init__(self, timeout): QtCore.QThread.__init__(self) self.timeout = timeout def run(self): time.sleep(self.timeout) # wait and die class PicButton(QtGui.QAbstractButton): DEFAULT = { "static/closeNormal.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAASCAYAAABb0P4QAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAACXBIWXMAAAsMAAALDAE/QCLIAAAAbElEQVQ4T63RQQ6AIAxEUe5/6UqT0ozyE6l1krfgQ9w4zOxXGDswdmDswDj5qC8+6vhBXfl+C0F30hPGoKMzwiho9C5hfNDR/Q1GQaN3CWPQ0RlhnHQnPVHUle+3EHzUFx/1159ShrED43c2LmZxaNDkNX4VAAAAAElFTkSuQmCC", "static/closeNormalx.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAASCAYAAABb0P4QAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAACXBIWXMAAAsMAAALDAE/QCLIAAAAU0lEQVQ4T+2MQQoAIAgE/f/d9xaBQYm2WXiJBoJc3aFPDsxc5GuC9hPtuD+JJtDexCt5+Ra6rOcjRsm1rJMmu5ZqiZ5DeGUvX4JKaG+CjkOy1yGq/ieRV3OQ3GAAAAAASUVORK5CYII=", "static/closeOver.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAASCAYAAABb0P4QAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAgY0hSTQAAeiYAAICEAAD6AAAAgOgAAHUwAADqYAAAOpgAABdwnLpRPAAAAAlwSFlzAAALDAAACwwBP0AiyAAAAG1JREFUOE9j+P//PwM1MVUNAzlsKBo4E+jqmUCHQ2hcGCKPJfwxBSGGwTA2AxHyRBoIcyE2Q1EtI8FAbIZiupxEA9ENxXQxGQbi8z7RkYIcEcjepNiF6GFGURjiSjpkxTLN0iGVcgqFxdngL20ATijABKRUynEAAAAASUVORK5CYII=", "static/colorNormal.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAAbElEQVR42mNgGAVUBb9+/TL59+/ff2IxUL05xQaCAIxNjAstiDWMKAN///5tA9OIDoDi+4GUPlSdNUUGIhsGA2QbiM0wsg3EZRhZBuIzjBQDHaAxiNcwUgz0hPpWn5BaYg10JyWnjJYtQwQAAJ3peBA+SssPAAAAAElFTkSuQmCC", "static/colorNormal.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAAbElEQVR42mNgGAVUBb9+/TL59+/ff2IxUL05xQaCAIxNjAstiDWMKAN///5tA9OIDoDi+4GUPlSdNUUGIhsGA2QbiM0wsg3EZRhZBuIzjBQDHaAxiNcwUgz0hPpWn5BaYg10JyWnjJYtQwQAAJ3peBA+SssPAAAAAElFTkSuQmCC", "static/colorNormalx.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAACeSURBVDhPrdCxDYNAFANQNsgILIEUCqRkldQp0rDDjcGo4I9y0uEz0j8+xRNgfbugSyndSoYRMoyQYQQHA6wNnnDYOHxA6yD3q8ERVPEM96vBCVSRff9P7l8a7MFu7Z37TYMLPCDfWlZ2dxycDf6Aby3nzDX4Ar4zrsE3lGP5fymuwQ/ksfJ/Ka7BGfKgB/erwTAZRsgwQoYRMrwudRv1c9XD7r05ggAAAABJRU5ErkJggg==", "static/colorOver.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAAgUlEQVR42mNgGAVUBR8ms5r8m8Hwn1j8bQqDOVUNJOjCj5NYLahq4KcJLDbEGPRrGkM21Qz8P4dBHqSWOAOn4jbw7wyG+f9nMvDD1FJk4P8ZDPnoask28P8sBntsaoky8PNkFgds4UW2gT+nMSTCDUMKL7IN/DGVqYSq6XAUDA4AAAfoB6boyLgNAAAAAElFTkSuQmCC", "static/maximizeNormal.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAACXBIWXMAAAsMAAALDAE/QCLIAAAAc0lEQVQ4T+WMQQqAQAwDfZSgoIg3//+imhw3zcFabw7MYWdppoj4VBs72tjRxo4aZlhhgcPG8IDVQb1PgyusoPdpcIdEu7pBkv40PB2kJHUNPxw8IdHuJKlrOCDR7iSpa7hgBb1Pg21t7GhjRxs72vjemG676+hWgWVyzgAAAABJRU5ErkJggg==", "static/maximizeNormalx.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAACXBIWXMAAAsMAAALDAE/QCLIAAAAU0lEQVQ4T2MYBdQF9fX1JkD8nwRsDtWKHQAVkGQgVBtuAFRkga4JH4Zqww2AimyIUQhUY01VA0Fg1EDsAKjIgdoG2lHbQHeQQmIxVNsoGNyAgQEA7q+mdUDshAYAAAAASUVORK5CYII=", "static/maximizeOver.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAgY0hSTQAAeiYAAICEAAD6AAAAgOgAAHUwAADqYAAAOpgAABdwnLpRPAAAAAlwSFlzAAALDAAACwwBP0AiyAAAAHtJREFUOE9j+P//PwM1MVUNAzlsiBn4bSq7yf+ZQEcTiX9NZzFHD38UL3+bRpqBQIsxggxF4Ps0dgtiXQdVh9/AH9PYbOAKQbbjwL9nMFtT1UCoRaCwJuDC6cS5cHgZ6EBMpJDiZTuqGvhtGqc7VdMhNYqxIVbaDEovAwD/TCC9Fqz9GwAAAABJRU5ErkJggg==", "static/minimizeNormal.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAACXBIWXMAAAsMAAALDAE/QCLIAAAASElEQVQ4T+3RMQrAMAwEQf//04pJPZCQdRnBNAtXac3MUYwFY8FYMBaMBWPBWDAWjNvTaXNj3N6cdv9TDmAsGAvGgrFg/G7WBcxEvHwWWVwUAAAAAElFTkSuQmCC", "static/minimizeNormalx.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAACXBIWXMAAAsMAAALDAE/QCLIAAAAJklEQVQ4T2MYBaNgxICpU6f+x4ehyogH2AxBx1Clo2AUjATAwAAAnlsun3vIzd4AAAAASUVORK5CYII=", "static/minimizeOver.Image.png": "iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAgY0hSTQAAeiYAAICEAAD6AAAAgOgAAHUwAADqYAAAOpgAABdwnLpRPAAAAAlwSFlzAAALDAAACwwBP0AiyAAAAEFJREFUOE9j+P//PwM1MVUNAzls1EDKI2g0DCFh+GM6m83/mUAmbowzqLBKEDLw9wxma1y5azRSRhM2GYXv4E82AOg5oRA88cLZAAAAAElFTkSuQmCC", "static/telaAzulFull.png": "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", "static/WinThor.ico": "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", # Tela Cinza: #A7A7A7 } def __init__(self, pixmap, pixmap_hover, pixmap_pressed, start_x, start_y, clicked_action, tootip_text, parent=None): super(PicButton, self).__init__(parent) self.pixmap = self.load_image(pixmap) self.pixmap_hover = self.load_image(pixmap_hover) self.pixmap_pressed = self.load_image(pixmap_pressed) self.pressed.connect(self.update) self.released.connect(self.update) self.move(start_x, start_y) self.resize(self.sizeHint()) self.setToolTip(tootip_text) self.clicked.connect(clicked_action) def load_image(self, key): # qp = QtGui.QPixmap(key) ba = QtCore.QByteArray.fromBase64(self.DEFAULT[key]) qimg = QtGui.QImage.fromData(ba, 'PNG') qp = QtGui.QPixmap.fromImage(qimg) return qp def paintEvent(self, event): pix = self.pixmap_hover if self.underMouse() else self.pixmap if self.isDown(): pix = self.pixmap_pressed painter = QtGui.QPainter(self) painter.drawPixmap(event.rect(), pix) def move(self, x, y): # print('Moving', self) super(PicButton, self).move(x, y) self.show() def enterEvent(self, event): self.update() def leaveEvent(self, event): self.update() def sizeHint(self): return QtCore.QSize(20, 20) class DatabaseAdapter: def __init__(self, user='PAPELEX', password='FG2HU3DV4T', alias='WINT'): try: # Tries to connect to database directly self.conn = cx_Oracle.connect(user, password, alias) self.cur = self.conn.cursor() self.mode = 'direct' except Exception, e: # If there's an error goes print 'Entering webserver mode...' self.user = user self.password = password self.alias = alias self.endpoint = 'http://192.168.24.45:8888/' self.mode = 'webserver' def query(self, query, **kwargs): if self.mode == 'direct': self.cur.execute(query.encode('utf-8'), kwargs) header = [desc[0].lower() for desc in self.cur.description] result = [OrderedDict(zip(header, [e.decode('utf-8', 'ignore') if isinstance(e, basestring) else e for e in row] )) for row in self.cur] return result else: data = { 'user': self.user, 'password': self.password, 'alias': self.alias, 'query': query, 'args': kwargs } req = urllib2.Request(self.endpoint + 'query', json.dumps(data)) req.add_header('Content-Type', 'application/json') res = urllib2.urlopen(req) return json.loads(res.read()) def execute(self, query, **kwargs): if self.mode == 'direct': self.cur.execute(query.encode('utf-8'), kwargs) self.conn.commit() return True else: data = { 'user': self.user, 'password': self.password, 'alias': self.alias, 'query': query, 'args': kwargs } req = urllib2.Request(self.endpoint + 'execute', json.dumps(data)) req.add_header('Content-Type', 'application/json') res = urllib2.urlopen(req) return json.loads(res.read()) def close(self): if self.mode == 'direct': self.cur.close() self.conn.close() class WinthorRoutine(QtGui.QMainWindow): def __init__(self, number, name, username, db_pass, db_alias, db_user, *args): super(WinthorRoutine, self).__init__() print(number, name, username, db_pass, db_alias, db_user) self.number = number self.name = str(number) + u' - ' + name self.username = username self.db_pass = db_pass self.db_alias = db_alias self.db_user = db_user self.is_maximized = False self.initUI() self.db = DatabaseAdapter() self.popups = [] def load_background(self): imageBitmap = "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" ba = QtCore.QByteArray.fromBase64(imageBitmap) qimg = QtGui.QImage.fromData(ba, 'PNG') return QtGui.QPixmap.fromImage(qimg) def initUI(self): palette = QtGui.QPalette() palette.setBrush(QtGui.QPalette.Background,QtGui.QBrush(self.load_background())) self.setPalette(palette) QtGui.QToolTip.setFont(QtGui.QFont('SansSerif', 10)) self.setWindowFlags(QtCore.Qt.FramelessWindowHint) self.minimizeButton = PicButton('static/minimizeNormal.Image.png', 'static/minimizeOver.Image.png', 'static/minimizeNormalx.Image.png', 710, 15, self.minimizeAction, u'Este botão minimiza a rotina.', self) self.maximizeButton = PicButton('static/maximizeNormal.Image.png', 'static/maximizeOver.Image.png', 'static/maximizeNormalx.Image.png', 740, 12, self.maximizeAction, u'Este botão maximiza a rotina.', self) self.closeButton = PicButton('static/closeNormal.Image.png', 'static/closeOver.Image.png', 'static/closeNormalx.Image.png', 770, 10, self.closeAction, u'Este botão fecha a rotina.', self) self.titleLabel = self.header_label(self.name, 20, (10, 5), 500) self.companyLabel = self.header_label('Winthor - Papelex', 10, (10, 25), 500) conntext = '%s(%s@%s)' % (self.username, self.db_alias, self.db_user) self.connectionLabel = self.header_label(conntext, 10, (500, 25), 150) self.routineLabel = self.header_label('PCPPL' + str(self.number), 10, (650, 25), 100) self.versionLabel = self.header_label('23.0.1', 10, (750, 25), 50) self.setGeometry(100, 100, 800, 600) self.setWindowTitle(' ') mainFrame = QtGui.QFrame(self) mainFrame.setFixedSize(794, 547) mainFrame.move(3, 50) mainFrame.setObjectName("myWidget") mainFrame.setStyleSheet("#myWidget {background-color:white; border: 1px solid black;}") self.mainwindow = QtGui.QVBoxLayout() mainFrame.setLayout(self.mainwindow) self.show() def toast(self, title, message, timeout=2): index = len(self.popups) new_popup = MyPopup(self.popups, title, message, timeout) availableGeometry = QtGui.QApplication.desktop().availableGeometry() new_popup.setGeometry(QtCore.QRect( availableGeometry.width() - POPUP_WIDTH - POPUP_MARGIN, availableGeometry.height() - (index + 1) * (POPUP_HEIGHT + POPUP_MARGIN), POPUP_WIDTH, POPUP_HEIGHT)) new_popup.show() self.popups.append(new_popup) def header_label(self, text, fontsize, position, width): label = QtGui.QLabel(text, self) label.move(*position) label.setFixedWidth(width) label.setStyleSheet(''' QLabel { font-family: Arial, Helvetica, sans-serif; color: rgb(255, 255, 255); font-size: %spx; width: %spx; } ''' % (fontsize, width)) eff = QtGui.QGraphicsDropShadowEffect(self) eff.setColor(QtGui.QColor("#000000")) eff.setBlurRadius(0) eff.setOffset(1, 1) label.setGraphicsEffect(eff) return label def closeAction(self): self.close() def minimizeAction(self): self.showNormal() self.showMinimized() def maximizeAction(self): if self.is_maximized: self.showNormal() self.is_maximized = False else: self.showMaximized() self.is_maximized = True print('Maximize!') def mousePressEvent(self, event): # print('[MOUSE PRESS]', event.pos()) self.offset = event.pos() def mouseMoveEvent(self, event): # print('[MOUSE MOVE]', event.globalX(), event.globalY()) x=event.globalX() y=event.globalY() x_w = self.offset.x() y_w = self.offset.y() self.move(x-x_w, y-y_w) def resizeEvent(self, resizeEvent): self.minimizeButton.move(self.geometry().width() - 90, 15) self.maximizeButton.move(self.geometry().width() - 60, 12) self.closeButton.move(self.geometry().width() - 30, 10) # print("Window has been resized...", self.geometry().left(), self.geometry().width(), self.geometry().height()) def closeEvent(self, event): self.db.close() event.accept() class QTableModel(QtCore.QAbstractTableModel): def __init__(self, parent, mylist, header, *args): QtCore.QAbstractTableModel.__init__(self, parent, *args) self.mylist = mylist self.header = header def rowCount(self, parent): return len(self.mylist) def columnCount(self, parent): return len(self.mylist[0]) def data(self, index, role): if not index.isValid(): return None elif role != QtCore.Qt.DisplayRole: return None return self.mylist[index.row()][index.column()] def headerData(self, col, orientation, role): if orientation == QtCore.Qt.Horizontal and role == QtCore.Qt.DisplayRole: return self.header[col] return None def sort(self, col, order): """sort table by given column number col""" self.emit(SIGNAL("layoutAboutToBeChanged()")) self.mylist = sorted(self.mylist, key=operator.itemgetter(col)) if order == QtCore.Qt.DescendingOrder: self.mylist.reverse() self.emit(SIGNAL("layoutChanged()")) def main(): app = QtGui.QApplication(sys.argv) ex = WinthorRoutine(sys.argv) sys.exit(app.exec_()) if __name__ == '__main__': main()

1,592.431953

253,326

0.954017

19,534

538,242

26.279769

0.45879

0.023282

0.033954

0.043978

0.952691

0.952085

0.951818

0.951376

0.950519

0.950375

0

0.158853

0.006204

538,242

338

253,327

1,592.431953

0.800852

0.000725

0

0.16726

0

0.010676

0.980281

0.978892

0

1

0

null

0.02847

0.021352

null

0.010676

0

1

null

0

1

0

1

0

1

null

1

0

1

0

13

4422dfa5b5e32e084661deb03b17b5e61c7fd8e3

20,181

py

Python

sdk/python/pulumi_aws/organizations/outputs.py

alexbowers/pulumi-aws

7dbdb03b1e4f7c0d51d5b5d17233ff4465c3eff5

[ "ECL-2.0", "Apache-2.0" ]

260

2018-06-18T14:57:00.000Z

2022-03-29T11:41:03.000Z

sdk/python/pulumi_aws/organizations/outputs.py

alexbowers/pulumi-aws

7dbdb03b1e4f7c0d51d5b5d17233ff4465c3eff5

[ "ECL-2.0", "Apache-2.0" ]

1,154

2018-06-19T20:38:20.000Z

2022-03-31T19:48:16.000Z

sdk/python/pulumi_aws/organizations/outputs.py

alexbowers/pulumi-aws

7dbdb03b1e4f7c0d51d5b5d17233ff4465c3eff5

[ "ECL-2.0", "Apache-2.0" ]

115

2018-06-28T03:20:27.000Z

2022-03-29T11:41:06.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs __all__ = [ 'OrganizationAccount', 'OrganizationNonMasterAccount', 'OrganizationRoot', 'OrganizationRootPolicyType', 'OrganizationalUnitAccount', 'GetDelegatedAdministratorsDelegatedAdministratorResult', 'GetDelegatedServicesDelegatedServiceResult', 'GetOrganizationAccountResult', 'GetOrganizationNonMasterAccountResult', 'GetOrganizationRootResult', 'GetOrganizationRootPolicyTypeResult', 'GetOrganizationalUnitsChildrenResult', ] @pulumi.output_type class OrganizationAccount(dict): def __init__(__self__, *, arn: Optional[str] = None, email: Optional[str] = None, id: Optional[str] = None, name: Optional[str] = None, status: Optional[str] = None): """ :param str arn: ARN of the root :param str email: Email of the account :param str id: Identifier of the root :param str name: The name of the policy type :param str status: The status of the policy type as it relates to the associated root """ if arn is not None: pulumi.set(__self__, "arn", arn) if email is not None: pulumi.set(__self__, "email", email) if id is not None: pulumi.set(__self__, "id", id) if name is not None: pulumi.set(__self__, "name", name) if status is not None: pulumi.set(__self__, "status", status) @property @pulumi.getter def arn(self) -> Optional[str]: """ ARN of the root """ return pulumi.get(self, "arn") @property @pulumi.getter def email(self) -> Optional[str]: """ Email of the account """ return pulumi.get(self, "email") @property @pulumi.getter def id(self) -> Optional[str]: """ Identifier of the root """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> Optional[str]: """ The name of the policy type """ return pulumi.get(self, "name") @property @pulumi.getter def status(self) -> Optional[str]: """ The status of the policy type as it relates to the associated root """ return pulumi.get(self, "status") @pulumi.output_type class OrganizationNonMasterAccount(dict): def __init__(__self__, *, arn: Optional[str] = None, email: Optional[str] = None, id: Optional[str] = None, name: Optional[str] = None, status: Optional[str] = None): """ :param str arn: ARN of the root :param str email: Email of the account :param str id: Identifier of the root :param str name: The name of the policy type :param str status: The status of the policy type as it relates to the associated root """ if arn is not None: pulumi.set(__self__, "arn", arn) if email is not None: pulumi.set(__self__, "email", email) if id is not None: pulumi.set(__self__, "id", id) if name is not None: pulumi.set(__self__, "name", name) if status is not None: pulumi.set(__self__, "status", status) @property @pulumi.getter def arn(self) -> Optional[str]: """ ARN of the root """ return pulumi.get(self, "arn") @property @pulumi.getter def email(self) -> Optional[str]: """ Email of the account """ return pulumi.get(self, "email") @property @pulumi.getter def id(self) -> Optional[str]: """ Identifier of the root """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> Optional[str]: """ The name of the policy type """ return pulumi.get(self, "name") @property @pulumi.getter def status(self) -> Optional[str]: """ The status of the policy type as it relates to the associated root """ return pulumi.get(self, "status") @pulumi.output_type class OrganizationRoot(dict): @staticmethod def __key_warning(key: str): suggest = None if key == "policyTypes": suggest = "policy_types" if suggest: pulumi.log.warn(f"Key '{key}' not found in OrganizationRoot. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: OrganizationRoot.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: OrganizationRoot.__key_warning(key) return super().get(key, default) def __init__(__self__, *, arn: Optional[str] = None, id: Optional[str] = None, name: Optional[str] = None, policy_types: Optional[Sequence['outputs.OrganizationRootPolicyType']] = None): """ :param str arn: ARN of the root :param str id: Identifier of the root :param str name: The name of the policy type :param Sequence['OrganizationRootPolicyTypeArgs'] policy_types: List of policy types enabled for this root. All elements have these attributes: """ if arn is not None: pulumi.set(__self__, "arn", arn) if id is not None: pulumi.set(__self__, "id", id) if name is not None: pulumi.set(__self__, "name", name) if policy_types is not None: pulumi.set(__self__, "policy_types", policy_types) @property @pulumi.getter def arn(self) -> Optional[str]: """ ARN of the root """ return pulumi.get(self, "arn") @property @pulumi.getter def id(self) -> Optional[str]: """ Identifier of the root """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> Optional[str]: """ The name of the policy type """ return pulumi.get(self, "name") @property @pulumi.getter(name="policyTypes") def policy_types(self) -> Optional[Sequence['outputs.OrganizationRootPolicyType']]: """ List of policy types enabled for this root. All elements have these attributes: """ return pulumi.get(self, "policy_types") @pulumi.output_type class OrganizationRootPolicyType(dict): def __init__(__self__, *, status: Optional[str] = None, type: Optional[str] = None): """ :param str status: The status of the policy type as it relates to the associated root """ if status is not None: pulumi.set(__self__, "status", status) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter def status(self) -> Optional[str]: """ The status of the policy type as it relates to the associated root """ return pulumi.get(self, "status") @property @pulumi.getter def type(self) -> Optional[str]: return pulumi.get(self, "type") @pulumi.output_type class OrganizationalUnitAccount(dict): def __init__(__self__, *, arn: Optional[str] = None, email: Optional[str] = None, id: Optional[str] = None, name: Optional[str] = None): """ :param str arn: ARN of the organizational unit :param str email: Email of the account :param str id: Identifier of the organization unit :param str name: The name for the organizational unit """ if arn is not None: pulumi.set(__self__, "arn", arn) if email is not None: pulumi.set(__self__, "email", email) if id is not None: pulumi.set(__self__, "id", id) if name is not None: pulumi.set(__self__, "name", name) @property @pulumi.getter def arn(self) -> Optional[str]: """ ARN of the organizational unit """ return pulumi.get(self, "arn") @property @pulumi.getter def email(self) -> Optional[str]: """ Email of the account """ return pulumi.get(self, "email") @property @pulumi.getter def id(self) -> Optional[str]: """ Identifier of the organization unit """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> Optional[str]: """ The name for the organizational unit """ return pulumi.get(self, "name") @pulumi.output_type class GetDelegatedAdministratorsDelegatedAdministratorResult(dict): def __init__(__self__, *, arn: str, delegation_enabled_date: str, email: str, id: str, joined_method: str, joined_timestamp: str, name: str, status: str): """ :param str arn: The Amazon Resource Name (ARN) of the delegated administrator's account. :param str delegation_enabled_date: The date when the account was made a delegated administrator. :param str email: The email address that is associated with the delegated administrator's AWS account. :param str id: The unique identifier (ID) of the delegated administrator's account. :param str joined_method: The method by which the delegated administrator's account joined the organization. :param str joined_timestamp: The date when the delegated administrator's account became a part of the organization. :param str name: The friendly name of the delegated administrator's account. :param str status: The status of the delegated administrator's account in the organization. """ pulumi.set(__self__, "arn", arn) pulumi.set(__self__, "delegation_enabled_date", delegation_enabled_date) pulumi.set(__self__, "email", email) pulumi.set(__self__, "id", id) pulumi.set(__self__, "joined_method", joined_method) pulumi.set(__self__, "joined_timestamp", joined_timestamp) pulumi.set(__self__, "name", name) pulumi.set(__self__, "status", status) @property @pulumi.getter def arn(self) -> str: """ The Amazon Resource Name (ARN) of the delegated administrator's account. """ return pulumi.get(self, "arn") @property @pulumi.getter(name="delegationEnabledDate") def delegation_enabled_date(self) -> str: """ The date when the account was made a delegated administrator. """ return pulumi.get(self, "delegation_enabled_date") @property @pulumi.getter def email(self) -> str: """ The email address that is associated with the delegated administrator's AWS account. """ return pulumi.get(self, "email") @property @pulumi.getter def id(self) -> str: """ The unique identifier (ID) of the delegated administrator's account. """ return pulumi.get(self, "id") @property @pulumi.getter(name="joinedMethod") def joined_method(self) -> str: """ The method by which the delegated administrator's account joined the organization. """ return pulumi.get(self, "joined_method") @property @pulumi.getter(name="joinedTimestamp") def joined_timestamp(self) -> str: """ The date when the delegated administrator's account became a part of the organization. """ return pulumi.get(self, "joined_timestamp") @property @pulumi.getter def name(self) -> str: """ The friendly name of the delegated administrator's account. """ return pulumi.get(self, "name") @property @pulumi.getter def status(self) -> str: """ The status of the delegated administrator's account in the organization. """ return pulumi.get(self, "status") @pulumi.output_type class GetDelegatedServicesDelegatedServiceResult(dict): def __init__(__self__, *, delegation_enabled_date: str, service_principal: str): """ :param str delegation_enabled_date: The date that the account became a delegated administrator for this service. :param str service_principal: The name of an AWS service that can request an operation for the specified service. """ pulumi.set(__self__, "delegation_enabled_date", delegation_enabled_date) pulumi.set(__self__, "service_principal", service_principal) @property @pulumi.getter(name="delegationEnabledDate") def delegation_enabled_date(self) -> str: """ The date that the account became a delegated administrator for this service. """ return pulumi.get(self, "delegation_enabled_date") @property @pulumi.getter(name="servicePrincipal") def service_principal(self) -> str: """ The name of an AWS service that can request an operation for the specified service. """ return pulumi.get(self, "service_principal") @pulumi.output_type class GetOrganizationAccountResult(dict): def __init__(__self__, *, arn: str, email: str, id: str, name: str, status: str): """ :param str arn: ARN of the root :param str email: Email of the account :param str id: Identifier of the root :param str name: The name of the policy type :param str status: The status of the policy type as it relates to the associated root """ pulumi.set(__self__, "arn", arn) pulumi.set(__self__, "email", email) pulumi.set(__self__, "id", id) pulumi.set(__self__, "name", name) pulumi.set(__self__, "status", status) @property @pulumi.getter def arn(self) -> str: """ ARN of the root """ return pulumi.get(self, "arn") @property @pulumi.getter def email(self) -> str: """ Email of the account """ return pulumi.get(self, "email") @property @pulumi.getter def id(self) -> str: """ Identifier of the root """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ The name of the policy type """ return pulumi.get(self, "name") @property @pulumi.getter def status(self) -> str: """ The status of the policy type as it relates to the associated root """ return pulumi.get(self, "status") @pulumi.output_type class GetOrganizationNonMasterAccountResult(dict): def __init__(__self__, *, arn: str, email: str, id: str, name: str, status: str): """ :param str arn: ARN of the root :param str email: Email of the account :param str id: Identifier of the root :param str name: The name of the policy type :param str status: The status of the policy type as it relates to the associated root """ pulumi.set(__self__, "arn", arn) pulumi.set(__self__, "email", email) pulumi.set(__self__, "id", id) pulumi.set(__self__, "name", name) pulumi.set(__self__, "status", status) @property @pulumi.getter def arn(self) -> str: """ ARN of the root """ return pulumi.get(self, "arn") @property @pulumi.getter def email(self) -> str: """ Email of the account """ return pulumi.get(self, "email") @property @pulumi.getter def id(self) -> str: """ Identifier of the root """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ The name of the policy type """ return pulumi.get(self, "name") @property @pulumi.getter def status(self) -> str: """ The status of the policy type as it relates to the associated root """ return pulumi.get(self, "status") @pulumi.output_type class GetOrganizationRootResult(dict): def __init__(__self__, *, arn: str, id: str, name: str, policy_types: Sequence['outputs.GetOrganizationRootPolicyTypeResult']): """ :param str arn: ARN of the root :param str id: Identifier of the root :param str name: The name of the policy type :param Sequence['GetOrganizationRootPolicyTypeArgs'] policy_types: List of policy types enabled for this root. All elements have these attributes: """ pulumi.set(__self__, "arn", arn) pulumi.set(__self__, "id", id) pulumi.set(__self__, "name", name) pulumi.set(__self__, "policy_types", policy_types) @property @pulumi.getter def arn(self) -> str: """ ARN of the root """ return pulumi.get(self, "arn") @property @pulumi.getter def id(self) -> str: """ Identifier of the root """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ The name of the policy type """ return pulumi.get(self, "name") @property @pulumi.getter(name="policyTypes") def policy_types(self) -> Sequence['outputs.GetOrganizationRootPolicyTypeResult']: """ List of policy types enabled for this root. All elements have these attributes: """ return pulumi.get(self, "policy_types") @pulumi.output_type class GetOrganizationRootPolicyTypeResult(dict): def __init__(__self__, *, status: str, type: str): """ :param str status: The status of the policy type as it relates to the associated root """ pulumi.set(__self__, "status", status) pulumi.set(__self__, "type", type) @property @pulumi.getter def status(self) -> str: """ The status of the policy type as it relates to the associated root """ return pulumi.get(self, "status") @property @pulumi.getter def type(self) -> str: return pulumi.get(self, "type") @pulumi.output_type class GetOrganizationalUnitsChildrenResult(dict): def __init__(__self__, *, arn: str, id: str, name: str): """ :param str arn: ARN of the organizational unit :param str id: Parent identifier of the organizational units. :param str name: Name of the organizational unit """ pulumi.set(__self__, "arn", arn) pulumi.set(__self__, "id", id) pulumi.set(__self__, "name", name) @property @pulumi.getter def arn(self) -> str: """ ARN of the organizational unit """ return pulumi.get(self, "arn") @property @pulumi.getter def id(self) -> str: """ Parent identifier of the organizational units. """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ Name of the organizational unit """ return pulumi.get(self, "name")

29.721649

154

0.580744

2,264

20,181

5.007951

0.065813

0.034398

0.056183

0.082113

0.811078

0.794673

0.780561

0.761069

0.741489

0.731699

0

0.000073

0.316932

20,181

678

155

29.765487

0.822416

0.258213

0

0.81201

1

0.002611

0.098514

0.046819

0

1

0.167102

false

0

0.015666

0.005222

0.347258

0

null

0

1

0

1

0

null

0

8

922fb6ea3179fab4b58986e606c7c705ad85cbfb

7,885

py

Python

pytorchrl/agent/algorithms/policy_loss_addons/kv_similarity.py

PyTorchRL/pytorchrl

055843ab58a06ba1f77da73082be6f23cf453ddd

[ "MIT" ]

20

2021-01-12T16:31:34.000Z

2022-03-18T00:31:29.000Z

pytorchrl/agent/algorithms/policy_loss_addons/kv_similarity.py

PyTorchRL/pytorchrl

055843ab58a06ba1f77da73082be6f23cf453ddd

[ "MIT" ]

4

2021-01-19T09:29:58.000Z

2021-09-29T12:21:08.000Z

pytorchrl/agent/algorithms/policy_loss_addons/kv_similarity.py

PyTorchRL/pytorchrl

055843ab58a06ba1f77da73082be6f23cf453ddd

[ "MIT" ]

2

2021-01-12T16:07:37.000Z

2021-02-01T21:09:14.000Z

import torch import numpy as np from torch.distributions.kl import kl_divergence import pytorchrl as prl from pytorchrl.agent.algorithms.policy_loss_addons import PolicyLossAddOn class AttractionKL(PolicyLossAddOn): def __init__(self, behavior_factories, behavior_weights, loss_term_weight=1.0, eps=1e-8): """ Class to enforce similarity of any algorithm policy to specified list of behaviors. We use the same loss term as in https://arxiv.org/pdf/2105.12196.pdf. Parameters ---------- behavior_factories : list List of methods creating the agent behaviors. behavior_weights : list List of floats giving relative weight to each agent behavior. All weights should be positive. Otherwise AssertionError will be raised. loss_term_weight : float Weight of the KL term in the algorithm policy loss. eps : float Lower bound for prob values, used to clip action probs. """ # Check sizes match assert len(behavior_factories) == len(behavior_weights) self.eps = eps self.behaviors = [] self.loss_term_weight = loss_term_weight self.behavior_factories = behavior_factories # Check all behavior weights are positive assert (np.array(behavior_weights) >= 0.0).all() # Normalize behavior_weights self.behavior_weights = behavior_weights self.behavior_weights /= np.sum(self.behavior_weights) def setup(self, device): """ Setup addon module by casting behavior weights to torch tensors and initializing agent behaviors. """ self.device = device # Cast behavior weights to torch tensors self.behavior_weights = [torch.tensor(w).to(device) for w in self.behavior_weights] # Create behavior instances for b in self.behavior_factories: self.behaviors.append(b(self.device)) def compute_loss_term(self, actor, actor_dist, data): """ Calculate and add KL Attraction loss term. 1. Calculate KL between actor policy and all behaviors. 2. Compute biased KL similarities and select minimum value. 3. Multiply the result by the loss_term_weight. 4. Change sign of the loss term so KL between behaviors is minimized. Parameters ---------- actor : Actor Training algorithm's Actor_critic class instance. actor_dist : torch.distributions.Distribution Actor action distribution for actions in data[prl.OBS] data : dict data batch containing all required tensors to compute loss term. Returns ------- attraction_kl_loss_term : torch.tensor KL loss term. """ o, rhs, a, d = data[prl.OBS], data[prl.RHS], data[prl.ACT], data[prl.DONE] if not isinstance(actor_dist, torch.distributions.Distribution): # If deterministic policy, use action as mean as fix scale to 1.0 actor_dist = torch.distributions.Normal(loc=a, scale=1.0) actor_dist.probs = torch.clamp(actor_dist.probs, self.eps, 1.0 - self.eps) kl_div = [] for behavior, weight in zip(self.behaviors, self.behavior_weights): with torch.no_grad(): _, _, dist_b = behavior.evaluate_actions(o, rhs, d, a) if not isinstance(dist_b, torch.distributions.Distribution): # If deterministic policy, use action as mean as fix scale to 1.0 dist_b = torch.distributions.Normal(loc=dist_b, scale=1.0) dist_b.probs = torch.clamp(dist_b.probs, self.eps, 1.0 - self.eps) div = (kl_divergence(dist_b, actor_dist) - torch.log(weight)) # div *= torch.exp(- 2 * dist_b.entropy()).detach() kl_div.append(div.mean()) kl_div = min(kl_div) return self.loss_term_weight * kl_div class RepulsionKL(PolicyLossAddOn): def __init__(self, behavior_factories, behavior_weights, loss_term_weight=1.0, eps=1e-8): """ Class to enforce dissimilarity of any algorithm policy to specified list of behaviors. Parameters ---------- behavior_factories : list List of methods creating the agent behaviors. behavior_weights : list List of floats giving relative weight to each agent behavior. All weights should be positive. Otherwise AssertionError will be raised. loss_term_weight : float Weight of the KL term in the algorithm policy loss. eps : float Lower bound for prob values, used to clip action probs. """ # Check sizes match assert len(behavior_factories) == len(behavior_weights) self.eps = eps self.behaviors = [] self.loss_term_weight = loss_term_weight self.behavior_factories = behavior_factories # Check all behavior weights are positive assert (np.array(behavior_weights) >= 0.0).all() # Normalize behavior_weights self.behavior_weights = behavior_weights self.behavior_weights /= np.sum(self.behavior_weights) def setup(self, device): """ Setup addon module by casting behavior weights to torch tensors and initializing agent behaviors. """ self.device = device # Cast behavior weights to torch tensors self.behavior_weights = [torch.tensor(w).to(device) for w in self.behavior_weights] # Create behavior instances for b in self.behavior_factories: self.behaviors.append(b(self.device)) def compute_loss_term(self, actor, actor_dist, data): """ Calculate and add KL Repulsion loss term. 1. Calculate KL between actor policy and all behaviors. 2. Compute weighted sum of KL similarities. 3. Multiply the result by the loss_term_weight. 4. Keep sign of the loss term so KL between behaviors is maximized. Parameters ---------- actor : Actor Training algorithm's Actor_critic class instance. actor_dist : torch.distributions.Distribution Actor action distribution for actions in data[prl.OBS] data : dict data batch containing all required tensors to compute loss term. Returns ------- attraction_kl_loss_term : torch.tensor KL loss term. """ o, rhs, a, d = data[prl.OBS], data[prl.RHS], data[prl.ACT], data[prl.DONE] if not isinstance(actor_dist, torch.distributions.Distribution): # If deterministic policy, use action as mean as fix scale to 1.0 actor_dist = torch.distributions.Normal(loc=a, scale=1.0) actor_dist.probs = torch.clamp(actor_dist.probs, self.eps, 1.0 - self.eps) kl_div = torch.tensor(0.0, dtype=torch.float32).to(self.device) for behavior, weight in zip(self.behaviors, self.behavior_weights): with torch.no_grad(): _, _, dist_b = behavior.evaluate_actions(o, rhs, d, a) if not isinstance(dist_b, torch.distributions.Distribution): # If deterministic policy, use action as mean as fix scale to 1.0 dist_b = torch.distributions.Normal(loc=dist_b, scale=1.0) dist_b.probs = torch.clamp(dist_b.probs, self.eps, 1.0 - self.eps) div = kl_divergence(dist_b, actor_dist) # div *= torch.exp(- 2 * dist_b.entropy()).detach() kl_div += div.mean() return -1 * self.loss_term_weight * kl_div

35.840909

95

0.622828

987

7,885

4.842958

0.175279

0.094142

0.035146

0.033891

0.9

0.890377

0.87113

0

0.010838

0.297907

7,885

219

96

36.004566

0.852601

0.405834

0

0.783784

0

0.054054

1

0.081081

false

0

0.067568

0

0.202703

0

null

0

1

0

1

0

null

0

7

92998bb798d63a0ab9ffb715572c15123f884b93

128

py

Python

gtorch_utils/utils/images/__init__.py

giussepi/gtorch_utils

8dfe502b2ef2d7c082354b9f546db5248815af09

[ "MIT" ]

null

gtorch_utils/utils/images/__init__.py

giussepi/gtorch_utils

8dfe502b2ef2d7c082354b9f546db5248815af09

[ "MIT" ]

null

gtorch_utils/utils/images/__init__.py

giussepi/gtorch_utils

8dfe502b2ef2d7c082354b9f546db5248815af09

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ gtorch_utils/utils/images/__init__ """ from gtorch_utils.utils.images.padding import apply_padding

25.6

59

0.734375

17

128

5.117647

0.647059

0.252874

0.367816

0.505747

0

0.008696

0.101563

128

4

60

32

0.747826

0.453125

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

2b7c4624a04f7ac2ef167aff3b6bfcfdae8eaa90

382

py

Python

analysis/models/__init__.py

SACGF/variantgrid

515195e2f03a0da3a3e5f2919d8e0431babfd9c9

[ "RSA-MD" ]

5

2021-01-14T03:34:42.000Z

2022-03-07T15:34:18.000Z

analysis/models/__init__.py

SACGF/variantgrid

515195e2f03a0da3a3e5f2919d8e0431babfd9c9

[ "RSA-MD" ]

551

2020-10-19T00:02:38.000Z

2022-03-30T02:18:22.000Z

analysis/models/__init__.py

SACGF/variantgrid

515195e2f03a0da3a3e5f2919d8e0431babfd9c9

[ "RSA-MD" ]

null

from analysis.models.models_analysis import * from analysis.models.models_karyomapping import * from analysis.models.models_variant_tag import * from analysis.models.mutational_signatures import * from analysis.models.nodes.analysis_node import * from analysis.models.nodes.filters import * from analysis.models.nodes.node_types import * from analysis.models.nodes.sources import *

42.444444

51

0.842932

51

382

6.176471

0.27451

0.304762

0.457143

0.533333

0.55873

0

0.08377

382

8

52

47.75

0.9

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

2bc34b6bd516260b35a883a77b819111344120bc

10,393

py

Python

tests/benchmarks.py

amashinchi-rc/enterpriseattack

a971b5fed8cdb3b9d58f5b7bb386195dfcbc56d5

[ "MIT" ]

null

tests/benchmarks.py

amashinchi-rc/enterpriseattack

a971b5fed8cdb3b9d58f5b7bb386195dfcbc56d5

[ "MIT" ]

null

tests/benchmarks.py

amashinchi-rc/enterpriseattack

a971b5fed8cdb3b9d58f5b7bb386195dfcbc56d5

[ "MIT" ]

null

#---------------------------------------------------------------------------------# # Imports: #---------------------------------------------------------------------------------# # Imports: import logging import time # Logger: logger = logging.getLogger() logger.setLevel(logging.DEBUG) #---------------------------------------------------------------------------------# # Import tests: #---------------------------------------------------------------------------------# start = time.time() import enterpriseattack end = time.time() print('Loading import took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Initialisation tests: #---------------------------------------------------------------------------------# t1 = time.time() attack = enterpriseattack.Attack( enterprise_json='enterpriseattack/data/enterprise-attack.json', url='https://raw.githubusercontent.com/mitre/cti/master/enterprise-attack/enterprise-attack.json', include_deprecated=False, update=True ) t11 = time.time() print('Initialise Attack object (fresh download json) took: {}'.format(t11 - t1)) start = time.time() attack = enterpriseattack.Attack( enterprise_json='enterpriseattack/data/enterprise-attack.json', url='https://raw.githubusercontent.com/mitre/cti/master/enterprise-attack/enterprise-attack.json', include_deprecated=False, update=False ) end = time.time() print('Initialise Attack object (saved json) took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Relationship tests: #---------------------------------------------------------------------------------# start = time.time() for source, target in attack.relationships.items(): pass end = time.time() print('Iterate over each relationship object took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Software tests: #---------------------------------------------------------------------------------# start = time.time() for software in attack.software: pass end = time.time() print('Iterate over each software object took: {}'.format(end - start)) start = time.time() for software in attack.software: software.to_json() end = time.time() print('Iterate over each software object and jsonify it took: {}'.format(end - start)) start = time.time() for software in attack.software: for group in software.groups: pass end = time.time() print('Iterate over each software object and assoc group object took: {}'.format(end - start)) start = time.time() for software in attack.software: for technique in software.techniques: pass end = time.time() print('Iterate over each software object and assoc technique object took: {}'.format(end - start)) start = time.time() for software in attack.software: for technique in software.techniques: for sub_technique in technique.sub_techniques: pass end = time.time() print('Iterate over every software/technique/sub_technique object took: {}'.format(end - start)) start = time.time() for software in attack.software: for group in software.groups: pass end = time.time() print('Iterate over each software group object took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Data Source tests: #---------------------------------------------------------------------------------# start = time.time() for datasource in attack.data_sources: pass end = time.time() print('Iterate over each data source object took: {}'.format(end - start)) start = time.time() for datasource in attack.data_sources: datasource.to_json() end = time.time() print('Iterate over every data source object and jsonify it: {}'.format(end - start)) start = time.time() for datasource in attack.data_sources: for technique in datasource.techniques: print(technique.name) end = time.time() print('Iterate over each data source object and the techniques it took: {}'.format(end - start)) start = time.time() for datasource in attack.data_sources: for technique in datasource.techniques: for sub_technique in technique.sub_techniques: pass end = time.time() print('Iterate over each data source/technique/subtechnique objects it took: {}'.format(end - start)) start = time.time() for datasource in attack.data_sources: for component in datasource.components: pass end = time.time() print('Iterate over each data source object and component took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Group tests: #---------------------------------------------------------------------------------# start = time.time() for group in attack.groups: pass end = time.time() print('Iterate over every group object took: {}'.format(end - start)) start = time.time() for group in attack.groups: group.to_json() end = time.time() print('Jsonify every group object took: {}'.format(end - start)) start = time.time() for group in attack.groups: for software in group.software: print(software.name) end = time.time() print('Iterate over every group software object took: {}'.format(end - start)) start = time.time() for group in attack.groups: for technique in group.techniques: pass end = time.time() print('Iterate over every group technique object took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Technique tests: #---------------------------------------------------------------------------------# start = time.time() for technique in attack.techniques: pass end = time.time() print('Iterate over each technique object took: {}'.format(end - start)) start = time.time() for technique in attack.techniques: for sub_technique in technique.sub_techniques: pass end = time.time() print('Iterate over each technique/sub_technique object took: {}'.format(end - start)) start = time.time() for technique in attack.techniques: for mitigation in technique.mitigations: pass end = time.time() print('Iterate over each technique/mitigation object took: {}'.format(end - start)) start = time.time() for technique in attack.techniques: for tactic in technique.tactics: pass end = time.time() print('Iterate over each technique/tactic object took: {}'.format(end - start)) start = time.time() for technique in attack.techniques: for datasource in technique.datasources: pass end = time.time() print('Iterate over each technique/data source object took: {}'.format(end - start)) start = time.time() for technique in attack.techniques: technique.to_json() end = time.time() print('Iterate over each technique object and jsonify it took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Tactic tests: #---------------------------------------------------------------------------------# start = time.time() for tactic in attack.tactics: pass end = time.time() print('Iterate over each tactic object took: {}'.format(end - start)) start = time.time() for tactic in attack.tactics: tactic.to_json() end = time.time() print('Iterate over each tactic object and jsonify it took: {}'.format(end - start)) start = time.time() for tactic in attack.tactics: for technique in tactic.techniques: pass end = time.time() print('Iterate over each tactic and technique object took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Sub Technique tests: #---------------------------------------------------------------------------------# start = time.time() for sub_technique in attack.sub_techniques: pass end = time.time() print('Iterate over each sub_technique object took: {}'.format(end - start)) start = time.time() for sub_technique in attack.sub_techniques: for datasource in sub_technique.datasources: pass end = time.time() print('Iterate over each sub_technique/data source object took: {}'.format(end - start)) start = time.time() for sub_technique in attack.sub_techniques: for tactic in sub_technique.tactics: pass end = time.time() print('Iterate over each sub_technique/tactic object took: {}'.format(end - start)) start = time.time() for sub_technique in attack.sub_techniques: for technique in sub_technique.techniques: print(technique.name) end = time.time() print('Iterate over each sub_technique/tactic object took: {}'.format(end - start)) start = time.time() for sub_technique in attack.sub_techniques: for mitigation in sub_technique.mitigations: print(mitigation.name) end = time.time() print('Iterate over each sub_technique/tactic object took: {}'.format(end - start)) start = time.time() for sub_technique in attack.sub_techniques: for group in sub_technique.groups: print(sub_technique.name, group.name) end = time.time() print('Iterate over each sub_technique/tactic object took: {}'.format(end - start)) start = time.time() for sub_technique in attack.sub_techniques: sub_technique.to_json() end = time.time() print('Iterate over each sub_technique object and jsonify took: {}'.format(end - start)) start = time.time() for sub_technique in attack.sub_techniques: for mitigation in sub_technique.mitigations: pass end = time.time() print('Iterate over each sub_technique/mitigation object took: {}'.format(end - start)) #---------------------------------------------------------------------------------# # Mitigation tests: #---------------------------------------------------------------------------------# start = time.time() for mitigation in attack.mitigations: pass end = time.time() print('Iterate over each mitigation object took: {}'.format(end - start)) start = time.time() for mitigation in attack.mitigations: mitigation.to_json() end = time.time() print('Iterate over each mitigation object and jsonify took: {}'.format(end - start)) start = time.time() for mitigation in attack.mitigations: for technique in mitigation.techniques: pass end = time.time() print('Iterate over each mitigation/technique object took: {}'.format(end - start))

32.889241

102

0.59136

1,176

10,393

5.178571

0.065476

0.102463

0.083251

0.099836

0.865681

0.854187

0.813465

0.806404

0.755993

0.682759

0

0.000667

0.134995

10,393

315

103

32.993651

0.676752

0.190705

0

0.69869

0

0.008734

0.277711

0.023462

0

1

0

false

0.104803

0.017467

0

0.017467

0.19214

0

null

0

1

0

null

0

1

0

7

a6221dd03cf38bbe794d9a09327ad49625a9bba1

574

py

Python

src/genie/libs/parser/nxos/tests/ShowUsers/cli/equal/golden_output_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

204

2018-06-27T00:55:27.000Z

2022-03-06T21:12:18.000Z

src/genie/libs/parser/nxos/tests/ShowUsers/cli/equal/golden_output_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

468

2018-06-19T00:33:18.000Z

2022-03-31T23:23:35.000Z

src/genie/libs/parser/nxos/tests/ShowUsers/cli/equal/golden_output_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

309

2019-01-16T20:21:07.000Z

2022-03-30T12:56:41.000Z

expected_output = { "line":{ "pts/0":{ "active":False, "name":"admin", "time":"Jan 28 13:44", "idle":".", "pid":"8096", "comment":"adding some comments" }, "pts/1":{ "active":False, "name":"admin", "time":"Jan 28 13:44", "idle":".", "pid":"8096" }, "pts/2":{ "active":True, "name":"admin", "time":"Jan 28 13:44", "idle":".", "pid":"8096", "comment":"adding some comments " } } }

20.5

42

0.369338

53

574

3.981132

0.45283

0.127962

0.184834

0.227488

0.810427

0

0.097345

0.409408

574

27

43

21.259259

0.525074

0

0.555556

0

0.353659

0

1

0

false

0

null

0

1

0

null

0

8

a627d7e45c1412d36cdfa8e5f5c8c97428ffec47

27,034

py

Python

tests/unit/pypyr/steps/pype_test.py

vlcinsky/pypyr

c386b86da7904e4bb23cbd555156ce011790a56f

[ "Apache-2.0" ]

null

tests/unit/pypyr/steps/pype_test.py

vlcinsky/pypyr

c386b86da7904e4bb23cbd555156ce011790a56f

[ "Apache-2.0" ]

null

tests/unit/pypyr/steps/pype_test.py

vlcinsky/pypyr

c386b86da7904e4bb23cbd555156ce011790a56f

[ "Apache-2.0" ]

null

"""pype.py unit tests.""" import logging import pytest from unittest.mock import call, patch from pypyr.context import Context from pypyr.errors import ( ContextError, Stop, KeyInContextHasNoValueError, KeyNotInContextError) import pypyr.steps.pype as pype from tests.common.utils import patch_logger # region get_arguments def test_pype_get_arguments_all(): """Parse all input from context.""" context = Context({ 'pype': { 'name': 'pipe name', 'args': {'a': 'b'}, 'out': 'out value', 'pipeArg': 'argument here', 'useParentContext': False, 'skipParse': 'skip parse', 'raiseError': 'raise err', 'loader': 'test loader', 'groups': ['gr'], 'success': 'sg', 'failure': 'fg' } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args == {'a': 'b'} assert out == 'out value' assert not use_parent_context assert skip_parse == 'skip parse' assert raise_error == 'raise err' assert loader == 'test loader' assert groups == ['gr'] assert success_group == 'sg' assert failure_group == 'fg' def test_pype_get_arguments_all_with_interpolation(): """Parse all input from context.""" context = Context({ 'pipeName': 'pipe name', 'argsHere': {'a': '{pipeName}'}, 'outHere': 'out here', 'argHere': 'argument here', 'parentContext': False, 'skipParse': 'skip parse', 'raiseErr': 'raise err', 'loaderHere': 'test loader', 'groups': ['gr'], 'success': 'sg', 'failure': 'fg', 'pype': { 'name': '{pipeName}', 'args': '{argsHere}', 'out': '{outHere}', 'pipeArg': '{argHere}', 'useParentContext': '{parentContext}', 'skipParse': '{skipParse}', 'raiseError': '{raiseErr}', 'loader': '{loaderHere}', 'groups': '{groups}', 'success': '{success}', 'failure': '{failure}', } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args == {'a': 'pipe name'} assert out == 'out here' assert not use_parent_context assert pipe_arg == ['argument', 'here'] assert skip_parse == 'skip parse' assert raise_error == 'raise err' assert loader == 'test loader' assert groups == ['gr'] assert success_group == 'sg' assert failure_group == 'fg' def test_pype_get_arguments_defaults(): """Parse all input from context and assign defaults where not specified.""" context = Context({ 'pype': { 'name': 'pipe name' } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args is None assert out is None assert use_parent_context assert isinstance(use_parent_context, bool) assert pipe_arg is None assert skip_parse assert isinstance(skip_parse, bool) assert raise_error assert isinstance(raise_error, bool) assert loader is None assert groups is None assert success_group is None assert failure_group is None def test_pype_get_arguments_missing_pype(): """Missing pype throw.""" context = Context() with pytest.raises(KeyNotInContextError) as err_info: pype.get_arguments(context) assert str(err_info.value) == ("context['pype'] " "doesn't exist. It must exist for " "pypyr.steps.pype.") def test_pype_get_args_not_a_dict(): """When args not a dict raise.""" context = Context({'pype': {'name': 'blah', 'args': 'arb'}}) with pytest.raises(ContextError) as err_info: pype.get_arguments(context) assert str(err_info.value) == ( "pypyr.steps.pype 'args' in the 'pype' context item " "must be a dict.") def test_pype_get_out_set_with_use_parent_context(): """When out is present useParentContext must be false.""" context = Context({'pype': {'name': 'blah', 'out': 'arb', 'useParentContext': True}}) with pytest.raises(ContextError) as err_info: pype.get_arguments(context) assert str(err_info.value) == ( "pypyr.steps.pype pype.out is only " "relevant if useParentContext = False. If you're using the parent " "context, no need to have out args since their values will already be " "in context. If you're NOT using parent context and you've specified " "pype.args, just leave off the useParentContext key and it'll default " "to False under the hood, or set it to False yourself if you keep it " "in.") def test_pype_get_arguments_missing_name(): """Missing pype name throw.""" context = Context({'pype': {}}) with pytest.raises(KeyNotInContextError) as err_info: pype.get_arguments(context) assert str(err_info.value) == ( "pypyr.steps.pype missing 'name' in the 'pype' " "context item. You need to specify the pipeline name to run another " "pipeline.") def test_pype_get_arguments_name_empty(): """Empty pype name throw.""" context = Context({'pype': {'name': None}}) with pytest.raises(KeyInContextHasNoValueError) as err_info: pype.get_arguments(context) assert str(err_info.value) == ("pypyr.steps.pype ['pype']['name'] exists " "but is empty.") def test_pype_get_arguments_group_str(): """Parse group as str input from context.""" context = Context({ 'pype': { 'name': 'pipe name', 'groups': 'gr', } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args is None assert out is None assert use_parent_context assert isinstance(use_parent_context, bool) assert pipe_arg is None assert skip_parse assert isinstance(skip_parse, bool) assert raise_error assert isinstance(raise_error, bool) assert loader is None assert groups == ['gr'] assert success_group is None assert failure_group is None def test_pype_get_arguments_group_str_interpolate(): """Parse group as interpolated str input from context.""" context = Context({ 'group': 'gr', 'pype': { 'name': 'pipe name', 'groups': '{group}', } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args is None assert out is None assert use_parent_context assert isinstance(use_parent_context, bool) assert pipe_arg is None assert skip_parse assert isinstance(skip_parse, bool) assert raise_error assert isinstance(raise_error, bool) assert loader is None assert groups == ['gr'] assert success_group is None assert failure_group is None def test_pype_get_args_no_parent_context(): """If args set use_parent_context should default False.""" context = Context({ 'pype': { 'name': 'pipe name', 'args': {'a': 'b'}, } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args == {'a': 'b'} assert out is None assert not use_parent_context assert pipe_arg is None assert skip_parse assert raise_error assert not loader assert not groups assert not success_group assert not failure_group def test_pype_get_pipeargs_no_skip_parse(): """If pipeArgs set skipParse should default False.""" context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'a b c', } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args is None assert out is None assert not use_parent_context assert pipe_arg == ['a', 'b', 'c'] assert not skip_parse assert raise_error assert not loader assert not groups assert not success_group assert not failure_group def test_pype_get_args_and_pipearg(): """Combine pipeArgs and args. Defaults useParentContext to False.""" context = Context({ 'pype': { 'name': 'pipe name', 'args': {'a': 'b'}, 'pipeArg': 'a b c', } }) (pipeline_name, args, out, use_parent_context, pipe_arg, skip_parse, raise_error, loader, groups, success_group, failure_group) = pype.get_arguments(context) assert pipeline_name == 'pipe name' assert args == {'a': 'b'} assert out is None assert not use_parent_context assert pipe_arg == ['a', 'b', 'c'] assert not skip_parse assert raise_error assert not loader assert not groups assert not success_group assert not failure_group # endregion get_arguments # region run_step def mocked_run_pipeline(*args, **kwargs): """Check pipeline name set on context in child pipeline.""" assert (kwargs['pipeline_name'] == kwargs['context'].pipeline_name == 'pipe name') @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_use_parent_context(mock_run_pipeline): """Input pype use_parent_context True.""" mock_run_pipeline.side_effect = mocked_run_pipeline context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'argument here', 'useParentContext': True, 'skipParse': True, 'raiseError': True, 'loader': 'test loader' } }) context.pipeline_name = 'og pipe name' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context=context, parse_input=False, loader='test loader', groups=None, success_group=None, failure_group=None ) assert context.pipeline_name == 'og pipe name' assert mock_logger_info.mock_calls == [ call('pyping pipe name, using parent context.'), call('pyped pipe name.')] @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_use_parent_context_with_args(mock_run_pipeline): """Input pype use_parent_context True with args.""" mock_run_pipeline.side_effect = mocked_run_pipeline context = Context({ 'k1': 'v1', 'pype': { 'name': 'pipe name', 'args': {'a': 'b'}, 'pipeArg': 'argument here', 'useParentContext': True, 'skipParse': True, 'raiseError': True, 'loader': 'test loader' } }) context.pipeline_name = 'og pipe name' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) merged_context = { 'a': 'b', 'k1': 'v1', 'pype': { 'name': 'pipe name', 'args': {'a': 'b'}, 'pipeArg': 'argument here', 'useParentContext': True, 'skipParse': True, 'raiseError': True, 'loader': 'test loader' } } mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context=merged_context, parse_input=False, loader='test loader', groups=None, success_group=None, failure_group=None ) assert context.pipeline_name == 'og pipe name' assert mock_logger_info.mock_calls == [ call('pyping pipe name, using parent context.'), call('pyped pipe name.')] @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_no_parent_context(mock_run_pipeline): """Input pype use_parent_context False.""" context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'argument here', 'useParentContext': False, 'skipParse': True, 'raiseError': True, 'loader': 'test loader', } }) context.working_dir = 'arb/dir' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context={}, parse_input=False, loader='test loader', groups=None, success_group=None, failure_group=None ) assert mock_logger_info.mock_calls == [ call('pyping pipe name, without parent context.'), call('pyped pipe name.')] @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_args(mock_run_pipeline): """Input pype args used as context.""" context = Context({ 'pype': { 'name': 'pipe name', 'args': {'a': 'b'} } }) context.working_dir = 'arb/dir' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=None, context={'a': 'b'}, parse_input=False, loader=None, groups=None, success_group=None, failure_group=None ) assert mock_logger_info.mock_calls == [ call('pyping pipe name, without parent context.'), call('pyped pipe name.')] @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_args_with_out(mock_run_pipeline): """Input pype args used as context with out.""" context = Context({ 'parentkey': 'parentvalue', 'pype': { 'name': 'pipe name', 'args': {'a': 'b'}, 'out': 'a' } }) context.working_dir = 'arb/dir' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=None, context={'a': 'b'}, parse_input=False, loader=None, groups=None, success_group=None, failure_group=None ) assert mock_logger_info.mock_calls == [ call('pyping pipe name, without parent context.'), call('pyped pipe name.')] assert context == {'parentkey': 'parentvalue', 'a': 'b', 'pype': { 'name': 'pipe name', 'args': {'a': 'b'}, 'out': 'a' } } @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_args_with_mapping_out(mock_run_pipeline): """Input pype args used as context with mapping out.""" context = Context({ 'parentkey': 'parentvalue', 'pype': { 'name': 'pipe name', 'args': {'a': 'av', 'b': 'bv', 'c': 'cv'}, 'out': {'new-a': 'a', 'new-c': 'c'} } }) context.working_dir = 'arb/dir' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=None, context={'a': 'av', 'b': 'bv', 'c': 'cv'}, parse_input=False, loader=None, groups=None, success_group=None, failure_group=None ) assert mock_logger_info.mock_calls == [ call('pyping pipe name, without parent context.'), call('pyped pipe name.')] assert context == {'parentkey': 'parentvalue', 'new-a': 'av', 'new-c': 'cv', 'pype': { 'name': 'pipe name', 'args': {'a': 'av', 'b': 'bv', 'c': 'cv'}, 'out': {'new-a': 'a', 'new-c': 'c'} } } @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_no_skip_parse(mock_run_pipeline): """Input pype use_parent_context False.""" context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'argument here', 'useParentContext': False, 'skipParse': False, 'raiseError': True } }) context.working_dir = 'arb/dir' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context={}, parse_input=True, loader=None, groups=None, success_group=None, failure_group=None ) assert mock_logger_info.mock_calls == [ call('pyping pipe name, without parent context.'), call('pyped pipe name.')] @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_no_pipe_arg(mock_run_pipeline): """Input pype use_parent_context False.""" context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': None, 'useParentContext': False, 'skipParse': False, 'raiseError': True, } }) context.working_dir = 'arb/dir' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=None, context={}, parse_input=True, loader=None, groups=None, success_group=None, failure_group=None ) assert mock_logger_info.mock_calls == [ call('pyping pipe name, without parent context.'), call('pyped pipe name.')] def mocked_run_pipeline_with_runtime_error(*args, **kwargs): """Check pipeline name set on context in child pipeline with arb err.""" assert (kwargs['pipeline_name'] == kwargs['context'].pipeline_name == 'pipe name') raise RuntimeError('whoops') @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_use_parent_context_no_swallow(mock_run_pipeline): """Input pype without swallowing error in child pipeline.""" mock_run_pipeline.side_effect = mocked_run_pipeline_with_runtime_error context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'argument here', 'useParentContext': True, 'skipParse': True, 'raiseError': True } }) context.pipeline_name = 'og pipe name' with patch_logger('pypyr.steps.pype', logging.ERROR) as mock_logger_error: with pytest.raises(RuntimeError) as err_info: pype.run_step(context) assert str(err_info.value) == "whoops" assert context.pipeline_name == 'og pipe name' mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context=context, parse_input=False, loader=None, groups=None, success_group=None, failure_group=None ) mock_logger_error.assert_called_once_with( 'Something went wrong pyping pipe name. RuntimeError: whoops') @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_use_parent_context_with_swallow(mock_run_pipeline): """Input pype swallowing error in child pipeline.""" mock_run_pipeline.side_effect = mocked_run_pipeline_with_runtime_error context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'argument here', 'useParentContext': True, 'skipParse': True, 'raiseError': False, 'loader': 'test loader' } }) context.pipeline_name = 'og pipe name' with patch_logger('pypyr.steps.pype', logging.ERROR) as mock_logger_error: pype.run_step(context) assert context.pipeline_name == 'og pipe name' mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context=context, parse_input=False, loader='test loader', groups=None, success_group=None, failure_group=None ) mock_logger_error.assert_called_once_with( 'Something went wrong pyping pipe name. RuntimeError: whoops') def mocked_run_pipeline_with_stop(*args, **kwargs): """Check pipeline name set on context in child pipeline with Stop.""" assert (kwargs['pipeline_name'] == kwargs['context'].pipeline_name == 'pipe name') raise Stop() @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_use_parent_context_swallow_stop_error(mock_run_pipeline): """Input pype doesn't swallow stop error in child pipeline.""" mock_run_pipeline.side_effect = mocked_run_pipeline_with_stop context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'argument here', 'useParentContext': True, 'skipParse': True, 'raiseError': False } }) context.pipeline_name = 'og pipe name' with patch_logger('pypyr.steps.pype', logging.ERROR) as mock_logger_error: with pytest.raises(Stop) as err_info: pype.run_step(context) assert isinstance(err_info.value, Stop) assert context.pipeline_name == 'og pipe name' mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context=context, parse_input=False, loader=None, groups=None, success_group=None, failure_group=None ) mock_logger_error.assert_not_called() @patch('pypyr.pipelinerunner.load_and_run_pipeline') def test_pype_set_groups(mock_run_pipeline): """Input pype use_parent_context True.""" mock_run_pipeline.side_effect = mocked_run_pipeline context = Context({ 'pype': { 'name': 'pipe name', 'pipeArg': 'argument here', 'useParentContext': True, 'skipParse': True, 'raiseError': True, 'loader': 'test loader', 'groups': 'testgroup', 'success': 'successgroup', 'failure': 'failuregroup' } }) context.pipeline_name = 'og pipe name' with patch_logger('pypyr.steps.pype', logging.INFO) as mock_logger_info: pype.run_step(context) mock_run_pipeline.assert_called_once_with( pipeline_name='pipe name', pipeline_context_input=['argument', 'here'], context=context, parse_input=False, loader='test loader', groups=['testgroup'], success_group='successgroup', failure_group='failuregroup' ) assert context.pipeline_name == 'og pipe name' assert mock_logger_info.mock_calls == [ call('pyping pipe name, using parent context.'), call('pyped pipe name.')] # endregion run_step # region write_child_context_to_parent def test_write_child_context_to_parent_wrong_type(): """When out not a str, list or dict raise.""" with pytest.raises(ContextError) as err_info: pype.write_child_context_to_parent(3, None, None) assert str(err_info.value) == ( "pypyr.steps.pype pype.out should be a string, or a list or a dict. " "Instead, it's a <class 'int'>") def test_write_child_context_to_parent_string(): """Single string writes single key to parent.""" parent = Context({'a': 'b'}) child = Context({'c': 'd', 'e': 'f'}) pype.write_child_context_to_parent('c', parent, child) assert parent == {'a': 'b', 'c': 'd'} def test_write_child_context_to_parent_list(): """Single string writes list of keys to parent.""" parent = Context({'a': 'b'}) child = Context({'c': 'd', 'e': 'f', 'g': 'h'}) pype.write_child_context_to_parent(['c', 'g'], parent, child) assert parent == {'a': 'b', 'c': 'd', 'g': 'h'} def test_write_child_context_to_parent_dict(): """Single string maps keys to parent.""" parent = Context({'a': 'b'}) child = Context({'c': 'd', 'e': 'f', 'g': 'h'}) pype.write_child_context_to_parent({'new-c': 'c', 'new-g': 'g'}, parent, child) assert parent == {'a': 'b', 'new-c': 'd', 'new-g': 'h'} def test_write_child_context_to_parent_dict_with_formatting(): """Single string maps keys to parent and formats child.""" parent = Context({'a': 'b'}) child = Context({'c': 'd', 'e': 'f', 'g': 'h and {e}'}) pype.write_child_context_to_parent({'new-c': 'c', 'new-g': 'g'}, parent, child) assert parent == {'a': 'b', 'new-c': 'd', 'new-g': 'h and f'} # endregion write_child_context_to_parent

28.456842

79

0.585966

3,064

27,034

4.931789

0.067232

0.041824

0.035736

0.030441

0.858977

0.83694

0.80405

0.789954

0.769572

0.753888

0

0.000262

0.295184

27,034

949

80

28.486828

0.792799

0.060073

0

0.770252

0

0.193826

0.019973

0

0.189907

1

0.043825

false

0

0.009296

0

0.053121

0

null

0

1

0

1

0

null

0

7

a6e5c86f27bf5493b83d247e17558e862b74a004

23,495

py

Python

CI-Python-master/qa327_test/frontend/test_registraion.py

lia-mason/SeetGeek

7be512c07af6fc42c57360f38db76f87825f3a44

[ "MIT" ]

null

CI-Python-master/qa327_test/frontend/test_registraion.py

lia-mason/SeetGeek

7be512c07af6fc42c57360f38db76f87825f3a44

[ "MIT" ]

6

2020-11-19T22:13:59.000Z

2020-12-17T03:58:03.000Z

CI-Python-master/qa327_test/frontend/test_registraion.py

lia-mason/SeetGeek

7be512c07af6fc42c57360f38db76f87825f3a44

[ "MIT" ]

null

''' import pytest from seleniumbase import BaseCase from qa327_test.conftest import base_url from unittest.mock import patch from qa327.models import db, User from werkzeug.security import generate_password_hash, check_password_hash """ This file defines all unit tests for the frontend homepage. The tests will only test the frontend portion of the program, by patching the backend to return specfic values. For example: @patch('qa327.backend.get_user', return_value=test_user) Will patch the backend get_user function (within the scope of the current test case) so that it return 'test_user' instance below rather than reading the user from the database. Annotate @patch before unit tests can mock backend methods (for that testing function) """ # Moch a sample user test_user = User( email='jivanji_adnan@test.com', name='test_frontend', password=generate_password_hash('test_frontend') ) # Moch some sample tickets test_tickets = [ {'name': 't1', 'price': '100'} ] class FrontEndHomePageTest(BaseCase): @patch('qa327.backend.get_user', return_value=test_user) def test_header(self, *_): """ This is a front end unit test to login to home page and verify if the welcome header is displayed correctly. """ # open login page self.open(base_url + '/login') # fill email and password self.type("#email", "test_frontend@test.com") self.type("#password", "test_frontend") # click enter button self.click('input[type="submit"]') # open home page self.open(base_url) # test if the page loads correctly self.assert_element("#welcome-header") # test for welcome header message ("Hi {username}") self.assert_text("Hi test_frontend", "#welcome-header") @patch('qa327.backend.get_user', return_value=test_user) def test_logout(self, *_): """ This is a front end unit test to login to home page and verify if the logout link is displayed correctly. """ # open login page self.open(base_url + '/login') # fill email and password self.type("#email", "test_frontend@test.com") self.type("#password", "test_frontend") # click enter button self.click('input[type="submit"]') # open home page self.open(base_url) # test if the page loads correctly # test for logout link self.assert_element("#welcome-header") self.assert_element("#logout") element = self.find_element("#logout") assert element.get_attribute("href") == base_url + "/logout" # test that logout redirects to '/' #URL = self.get_current_url(); #self.assert_equal(URL, base_url + '/'); @patch('qa327.backend.get_user', return_value=test_user) def test_login(self, *_): """ R3.1 This will test the login page and test if the user gets redirected to login page if not logged in """ self.open(base_url + '/logout') self.open(base_url + '/login') self.assert_element("#title") #self.assert_text("Log in", "#title") @patch('qa327.backend.get_user', return_value=test_user) @patch('qa327.backend.get_all_tickets', return_value=test_tickets) def test_show_user_balance(self, *_): """ R3.3 This will test whether the user balance displays """ self.open(base_url + '/login') self.type("#email", "test_frontend@test.com") self.type("#password", "test_frontend") self.click('input[type="submit"]') self.open(base_url) # test if the page loads correctly self.assert_element("#welcome-header") self.assert_element("#ubalance") @patch('qa327.backend.get_user', return_value=test_user) def test_sell_form(self, *_): """ This is a front end unit test to login to home page and verify if the sell form is displayed correctly. """ # open login page self.open(base_url + '/login') # fill email and password self.type("#email", "test_frontend@test.com") self.type("#password", "test_frontend") # click enter button self.click('input[type="submit"]') # open home page self.open(base_url) # test if the page loads correctly self.assert_element("#welcome-header") # test for sell form elements # enter name, quantity, price, expiration # click submit # verify that ?? self.assert_element("#tname") self.type("#tname", "ticket_name") self.assert_element("#tquantity") self.type("#tquantity", "1") self.assert_element("#tprice") self.type("#tprice", "50.00") self.assert_element("#texpiration") self.type("#texpiration", "02/03/21") self.click("#sell-btn-submit") self.assert_element("#welcome-header") @patch('qa327.backend.get_user', return_value=test_user) @patch('qa327.backend.get_all_tickets', return_value=test_tickets) def test_all_tickets(self, *_): """ R3.5 check to see if tickets displays """ # open login page self.open(base_url + '/login') # fill email and password self.type("#email", "test_frontend@test.com") self.type("#password", "test_frontend") # click enter button self.click('input[type="submit"]') # open home page self.open(base_url) self.assert_text("Hi test_frontend", "#welcome-header") self.assert_element("#tickets") self.assert_text("Here are all available tickets") @patch('qa327.backend.get_user', return_value=test_user) def test_update_form(self, *_): """ This is a front end unit test to login to home page and verify if the update form is displayed correctly. """ # open login page self.open(base_url + '/login') # fill email and password self.type("#email", "test_frontend@test.com") self.type("#password", "test_frontend") # click enter button self.click('input[type="submit"]') # open home page self.open(base_url) # test if the page loads correctly self.assert_element("#welcome-header") # test for update form elements # enter name, quantity, price, expiration # click submit # verify that ?? self.assert_element("#uname") self.type("#uname", "ticket_name") self.assert_element("#uquantity") self.type("#uquantity", "3") self.assert_element("#uprice") self.type("#uprice", "30.00") self.assert_element("#uexpiration") self.type("#uexpiration", "03/04/22") self.click("#update-btn-submit") self.assert_element("#welcome-header") @patch('qa327.backend.get_user', return_value=test_user) @patch('qa327.backend.get_all_tickets', return_value=test_tickets) def test_buy_form(self, *_): """ R3.7 This will test if buy form is displaying """ # open login page self.open(base_url + '/login') # fill email and password self.type("#email", "test_frontend@test.com") self.type("#password", "test_frontend") # click enter button self.click('input[type="submit"]') # open home page self.open(base_url) self.assert_element("#name") self.type("#name", "test_name") self.assert_element("#quantity") self.type("#quantity", "1") self.click("#buy-btn-submit") #self.assert_element("#welcome-header") # @patch('qa327.backend.get_user', return_value=test_user) # @patch('qa327.backend.get_all_tickets', return_value=test_tickets) # def test_login_success(self, *_): # """ # This is a sample front end unit test to login to home page # and verify if the tickets are correctly listed. # """ # # open login page # self.open(base_url + '/login') # # fill email and password # self.type("#email", "test_frontend@test.com") # self.type("#password", "test_frontend") # # click enter button # self.click('input[type="submit"]') # # # after clicking on the browser (the line above) # # the front-end code is activated # # and tries to call get_user function. # # The get_user function is supposed to read data from database # # and return the value. However, here we only want to test the # # front-end, without running the backend logics. # # so we patch the backend to return a specific user instance, # # rather than running that program. (see @ annotations above) # # # # open home page # self.open(base_url) # # test if the page loads correctly # self.assert_element("#welcome-header") # self.assert_text("Welcome test_frontend", "#welcome-header") # self.assert_element("#tickets div h4") # self.assert_text("t1 100", "#tickets div h4") # @patch('qa327.backend.get_user', return_value=test_user) # @patch('qa327.backend.get_all_tickets', return_value=test_tickets) # def test_login_password_failed(self, *_): # """ Login and verify if the tickets are correctly listed.""" # # open login page # self.open(base_url + '/login') # # fill wrong email and password # self.type("#email", "test_frontend@test.com") # self.type("#password", "wrong_password") # # click enter button # self.click('input[type="submit"]') # # make sure it shows proper error message # self.assert_element("#message") # self.assert_text("login failed", "#message") class RegistrationTest(BaseCase): #This function checks for an error message when password1 and password2 don't match def test_passwords_dont_match(self, *_): #open register page self.open(base_url + '/register') #fill email and passwords that don't match self.type("#email", "test_frontend@testing.com") self.type("#name", "test_frontend") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualAssura327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows correct error message self.assert_element("#message") self.assert_text("password1 and password2 don't match", "#message") #This function checks whether the registration was successful when both passwords match def test_passwords_match(self, *_): #open register page self.open(base_url + '/register') #fill email and passwords that match self.type("#email", "edinsoncavanie3@testing.com") self.type("#name", "test frontend") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and checks if no error message is displayed self.assert_element("#message") self.assert_text("Please login", "#message") #This function checks whether the registration fails when username field is empty def test_empty_username(self, *_): #open register page self.open(base_url + '/register') #leave username field as empty self.type("#email", "test_frooonten@testing.com") self.type("#name", "") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #Since the field username is required, page wont be redirected to login. #By checking if regsitration form is still being displayed through one of its elements, #we have verified that the form submission failed. self.assert_element('#name') #This function checks whether the registration fails when password field is empty def test_empty_password(self, *_): #open register page self.open(base_url + '/register') #leave password field as empty self.type("#email", "test_frrrronten@testing.com") self.type("#name", "AmaarJivanji") self.type("#password", "") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #Since the field username is required, page wont be redirected to login. #By checking if regsitration form is still being displayed through one of its elements, #we have verified that the form submission failed. self.assert_element('#name') #This function checks whether the registration fails when email field is empty def test_empty_email(self, *_): #open register page self.open(base_url + '/register') #leave email field as empty self.type("#email", "") self.type("#name", "AmaarJivanji") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #Since the field username is required, page wont be redirected to login. #By checking if regsitration form is still being displayed through one of its elements, #we have verified that the form submission failed. self.assert_element('#name') #This function checks whether the registration fails when username is lte 2 characters def test_short_username(self, *_): #open register page self.open(base_url + '/register') #fill email, passwords and username shorter than 3 characters self.type("#email", "test_frrronten@testing.com") self.type("#name", "ab") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows correct error message self.assert_element("#message") self.assert_text("username too short or too long", "#message") #This function checks whether the registration fails when username gte 20 characters def test_long_username(self, *_): #open register page self.open(base_url + '/register') #fill email, passwords and username greater than 19 characters self.type("#email", "test_frontend@testing.com") self.type("#name", "amaarmoizmohammedalijivanji") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows correct error message self.assert_element("#message") self.assert_text("username too short or too long", "#message") #This function checks whether registration fails when username has space at beginning def test_space_beginning(self, *_): #open register page self.open(base_url + '/register') #fill email, passwords and username with space at beginning self.type("#email", "test_frontend@testing.com") self.type("#name", " paulPogba") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("space at start/end", "#message") #This function checks whether registration fails when username has space at the end def test_space_end(self, *_): #open register page self.open(base_url + '/register') #fill email, passwords and username with space at end self.type("#email", "test_frontend@testing.com") self.type("#name", "paulPogba ") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("space at start/end", "#message") #This function checks whether registration fails when password doesn't have any special characters def test_password_without_specialcharacters(self, *_): #open register page self.open(base_url + '/register') #fill email, username and password with no special characters self.type("#email", "test_frontend@testing.com") self.type("#name", "AmaarJivanji") self.type("#password", "QualityAssurance327") self.type("#password2", "QualityAssurance327") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("password doesn't meet required complexity", "#message") #This function checks whether registration fails when password has no uppercase letter def test_password_without_uppercase(self, *_): #open register page self.open(base_url + '/register') #fill email, username and password with no uppercase letters self.type("#email", "test_frontend@testing.com") self.type("#name", "AmaarJivanji") self.type("#password", "qualityassurance327$") self.type("#password2", "qualityassurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("password doesn't meet required complexity", "#message") #This function checks whether registration fails when password has no lowercase letter def test_password_without_lowercase(self, *_): #open register page self.open(base_url + '/register') #fill email, username and password with no lowercase letters self.type("#email", "test_frontend@testing.com") self.type("#name", "AmaarJivanji") self.type("#password", "QUALITYASSURANCE327$") self.type("#password2", "QUALITYASSURANCE327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("password doesn't meet required complexity", "#message") #This functions checks whether registration fails when password is lt 6 characters def test_password_short(self, *_): #open register page self.open(base_url + '/register') #fill email, username and password with 5 characters self.type("#email", "test_frontend@testing.com") self.type("#name", "AmaarJivanjishort") self.type("#password", "Qua$3") self.type("#password2", "Qua$3") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("password doesn't meet required complexity", "#message") #This function checks whether registration succeeds when passwords inputted are valid def test_valid_password(self, *_): #open register page self.open(base_url + '/register') #fill email, passwords and username - all valid self.type("#email", "zebradonkey3@testing.com") self.type("#name", "AmaarJivanji") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and checks if no error message is displayed self.assert_element("#message") self.assert_text("Please login", "#message") #This function checks whether registration fails when email submitted is already taken @patch('qa327.backend.get_user', return_value=test_user) def test_email_already_used(self, *_): #open register page self.open(base_url + '/register') #fill passwords, username and email that has already been used self.type("#email", "jivanji_adnan@test.com") self.type("#name", "AmaariiiJivanji") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("this email has already been used", "#message") #This function checks whether the email follows the addr-spec defined in RFC 5322 def test_valid_email(self, *_): #open register page self.open(base_url + '/register') #fill invalid email self.type("#email", "jicom") self.type("#name", "AmaariiiJivanji") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("email not valid", "#message") #This function checks whether registrations fails when username is not alphanumeric def test_username_notalnum(self, *_): #open register page self.open(base_url + '/register') #fill invalid email self.type("#email", "amaarsmolsky@hotmail.com") self.type("#name", "Ama%4rJIVANJI") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened and check if message shows error message self.assert_element("#message") self.assert_text("name not alphanumeric", "#message") #This function confirms that the user balance is set to 5000 when new user is registered def test_registration_and_userbalance(self, *_): #open register page self.open(base_url + '/register') #fill invalid email self.type("#email", "LiaAmaar1239@gmail.com") self.type("#name", "Muhammad Ahmed") self.type("#password", "QualityAssurance327$") self.type("#password2", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') #login page is opened #fill email and password self.type("#email", "LiaAmaar1239@gmail.com") self.type("#password", "QualityAssurance327$") #click enter button self.click('input[type="submit"]') # #user profile page is opened #verify that user balance is set to 5000 self.assert_element("#ubalance") self.assert_text(5000, "#ubalance") '''

41.075175

110

0.638306

2,837

23,495

5.177652

0.111033

0.055552

0.049765

0.037783

0.764041

0.744639

0.722718

0.714208

0.692695

0.677854

0

0.014597

0.244818

23,495

571

111

41.14711

0.813278

0.999276

0

null

1

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

1

0

1

0

1

0

null

0

1

0

7

a6f48e42a98009279d2bdeed0cb5492320962463

63

py

Python

fs2conf/__init__.py

OmniTroid/mcconf

b248f0fce911b02e4cc8213c1b0e0ddc0105b6f8

[ "MIT" ]

1

2022-03-03T12:17:40.000Z

fs2conf/__init__.py

OmniTroid/mcconf

b248f0fce911b02e4cc8213c1b0e0ddc0105b6f8

[ "MIT" ]

null

fs2conf/__init__.py

OmniTroid/mcconf

b248f0fce911b02e4cc8213c1b0e0ddc0105b6f8

[ "MIT" ]

null

from .fs2conf import fs2conf from .fs2conf import combine_dirs

21

33

0.84127

9

63

5.777778

0.555556

0.423077

0.653846

0

0.054545

0.126984

63

2

34

31.5

0.890909

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

5b440a9c9a5a40531055c172bf4db066d8154ae6

26,387

py

Python

QuantumInformation/chap5_partial_quantumentanglement.py

pranay1990/QuantumInformation

6588e623c3c4839e2b484a5ce57bb9aac9bb458c

[ "Unlicense" ]

null

QuantumInformation/chap5_partial_quantumentanglement.py

pranay1990/QuantumInformation

6588e623c3c4839e2b484a5ce57bb9aac9bb458c

[ "Unlicense" ]

null

QuantumInformation/chap5_partial_quantumentanglement.py

pranay1990/QuantumInformation

6588e623c3c4839e2b484a5ce57bb9aac9bb458c

[ "Unlicense" ]

null

""" Created on Thu Aug 22 19:18:53 2019 @authors: Dr. M. S. Ramkarthik and Dr. Pranay Barkataki """ import numpy as np import math from QuantumInformation import RecurNum from QuantumInformation import LinearAlgebra as LA from QuantumInformation import QuantumMechanics as QM import scipy.linalg.lapack as la import re qobj=QM() class PartialTr: def __init__(self): """It is a class dealing with partial trace and transpose it primarily intrinsic functions of uses numpy, math, cmath. """ # partial trace operation subroutine for a real pure state #entry is in the column form def partial_trace_vec(self,state,sub_tr): """ Partial trace operation on a quantum state Input: state: real state vector sub_tr: details of the subsystems not to be traced out Output: red_den: reduced density matrix """ typestate=str(state.dtype) N=int(math.log2(state.shape[0])) length=len(sub_tr) # count=length, and count0= N-length assert set(sub_tr).issubset(set(np.arange(1,N+1))),\ "Invalid subsystems to be traced out" if re.findall("^complex",typestate): red_den=np.zeros([2**(length),2**(length)],dtype=np.complex_) vec=np.zeros([(N-length),1]) im=0 for ii in range(1,N+1): if ii not in sub_tr: vec[im]=2**(N-ii) im=im+1 mylist=[] icount=0 sum2=0 RecurNum.recur_comb_add(mylist,vec,icount,sum2) irow=np.zeros([N,1]) icol=np.zeros([N,1]) mylist=np.array(mylist) len_mylist=len(mylist) for i1 in range(0,2**length): col1=self.__dectobin(i1,length) for i2 in range(0,2**length): col2=self.__dectobin(i2,length) i3=0 for k in range(0,N): if k+1 not in sub_tr: irow[k]=0 else: irow[k]=col1[i3] i3=i3+1 ic=0 for k2 in range(0,N): if k2+1 not in sub_tr: icol[k2]=0 else: icol[k2]=col2[ic] ic=ic+1 icc=self.__bintodec(irow) jcc=self.__bintodec(icol) red_den[i1,i2]=red_den[i1,i2]+(state[icc]*\ np.conjugate(state[jcc])) for jj in range(0,len_mylist): icc2=icc+mylist[jj] jcc2=jcc+mylist[jj] red_den[i1,i2]=red_den[i1,i2]+(state[icc2]*\ np.conjugate(state[jcc2])) else: red_den=np.zeros([2**(length),2**(length)],dtype='float64') vec=np.zeros([(N-length),1]) im=0 for ii in range(1,N+1): if ii not in sub_tr: vec[im]=2**(N-ii) im=im+1 mylist=[] icount=0 sum2=0 RecurNum.recur_comb_add(mylist,vec,icount,sum2) irow=np.zeros([N,1]) icol=np.zeros([N,1]) mylist=np.array(mylist) len_mylist=len(mylist) for i1 in range(0,2**length): col1=self.__dectobin(i1,length) for i2 in range(0,2**length): col2=self.__dectobin(i2,length) i3=0 for k in range(0,N): if k+1 not in sub_tr: irow[k]=0 else: irow[k]=col1[i3] i3=i3+1 ic=0 for k2 in range(0,N): if k2+1 not in sub_tr: icol[k2]=0 else: icol[k2]=col2[ic] ic=ic+1 icc=self.__bintodec(irow) jcc=self.__bintodec(icol) red_den[i1,i2]=red_den[i1,i2]+(state[icc]*state[jcc]) for jj in range(0,len_mylist): icc2=icc+mylist[jj] jcc2=jcc+mylist[jj] red_den[i1,i2]=red_den[i1,i2]+(state[icc2]*state[jcc2]) return(red_den) # partial trace operation for a real state density matrix def partial_trace_den(self,state,sub_tr): """ Partial trace operation on a density matrix Input: state: input real density matrix sub_tr: details of the subsystem not to be traced out Output: red_den: reduced density matrix """ typestate=str(state.dtype) N=int(math.log2(state.shape[0])) length=len(sub_tr) # count=length, and count0= N-length assert set(sub_tr).issubset(set(np.arange(1,N+1))),\ "Invalid subsystems to be traced out" if re.findall("^complex",typestate): red_den=np.zeros([2**(length),2**(length)],dtype=np.complex_) vec=np.zeros([(N-length),1]) im=0 for ii in range(1,N+1): if ii not in sub_tr: vec[im]=2**(N-ii) im=im+1 mylist=[] icount=0 sum2=0 RecurNum.recur_comb_add(mylist,vec,icount,sum2) irow=np.zeros([N,1]) icol=np.zeros([N,1]) mylist=np.array(mylist) len_mylist=len(mylist) for i1 in range(0,2**length): col1=self.__dectobin(i1,length) for i2 in range(0,2**length): col2=self.__dectobin(i2,length) i3=0 for k in range(0,N): if k+1 not in sub_tr: irow[k]=0 else: irow[k]=col1[i3] i3=i3+1 ic=0 for k2 in range(0,N): if k2+1 not in sub_tr: icol[k2]=0 else: icol[k2]=col2[ic] ic=ic+1 icc=self.__bintodec(irow) jcc=self.__bintodec(icol) red_den[i1,i2]=red_den[i1,i2]+(state[icc,jcc]) for jj in range(0,len_mylist): icc2=icc+mylist[jj] jcc2=jcc+mylist[jj] red_den[i1,i2]=red_den[i1,i2]+(state[icc2,jcc2]) else: red_den=np.zeros([2**(length),2**(length)],dtype='float64') vec=np.zeros([(N-length),1]) im=0 for ii in range(1,N+1): if ii not in sub_tr: vec[im]=2**(N-ii) im=im+1 mylist=[] icount=0 sum2=0 RecurNum.recur_comb_add(mylist,vec,icount,sum2) irow=np.zeros([N,1]) icol=np.zeros([N,1]) mylist=np.array(mylist) len_mylist=len(mylist) for i1 in range(0,2**length): col1=self.__dectobin(i1,length) for i2 in range(0,2**length): col2=self.__dectobin(i2,length) i3=0 for k in range(0,N): if k+1 not in sub_tr: irow[k]=0 else: irow[k]=col1[i3] i3=i3+1 ic=0 for k2 in range(0,N): if k2+1 not in sub_tr: icol[k2]=0 else: icol[k2]=col2[ic] ic=ic+1 icc=self.__bintodec(irow) jcc=self.__bintodec(icol) red_den[i1,i2]=red_den[i1,i2]+(state[icc,jcc]) for jj in range(0,len_mylist): icc2=icc+mylist[jj] jcc2=jcc+mylist[jj] red_den[i1,i2]=red_den[i1,i2]+(state[icc2,jcc2]) return(red_den) # Partial Transpose of real pure state def ptranspose_vec(self,state,sub_tr): """ Partial transpose operation on a quantum state Parameters state : It is a real or complex state. sub_tr : List of number designating the subsystems to be partially transposed. Returns denc2: It is partially transposed density matrix """ N=int(math.log2(state.shape[0])) assert set(sub_tr).issubset(set(np.arange(1,N+1))),\ "Invalid subsystems to be traced out" typestate=str(state.dtype) if re.findall("^complex",typestate): denc2=np.zeros([2**N,2**N],dtype=np.complex_) for i in range(state.shape[0]): vec_row=qobj.decimal_binary(i,N) for j in range(state.shape[0]): vec_col=qobj.decimal_binary(j,N) vec_row2=vec_row.copy() for k in sub_tr: temp=vec_row2[k-1] vec_row2[k-1]=vec_col[k-1] vec_col[k-1]=temp row=qobj.binary_decimal(vec_row2) col=qobj.binary_decimal(vec_col) denc2[row,col]=state[i]*np.conjugate(state[j]) else: denc2=np.zeros([2**N,2**N],dtype='float64') for i in range(state.shape[0]): vec_row=qobj.decimal_binary(i,N) for j in range(state.shape[0]): vec_col=qobj.decimal_binary(j,N) vec_row2=vec_row.copy() for k in sub_tr: temp=vec_row2[k-1] vec_row2[k-1]=vec_col[k-1] vec_col[k-1]=temp row=qobj.binary_decimal(vec_row2) col=qobj.binary_decimal(vec_col) denc2[row,col]=state[i]*state[j] return(denc2) # Partial Transpose of real density matrix def ptranspose_den(self,denc,sub_tr): """ Partial transpose operation on density matrix Parameters denc : It is a real or complex density matrix. sub_tr : List of number designating the subsystems to be partially transposed. Returns denc2: It is partially transposed density matrix """ N=int(math.log2(denc.shape[0])) assert set(sub_tr).issubset(set(np.arange(1,N+1))),\ "Invalid subsystems to be traced out" typestate=str(denc.dtype) if re.findall("^complex",typestate): denc2=np.zeros([2**N,2**N],dtype=np.complex_) for i in range(denc.shape[0]): vec_row=qobj.decimal_binary(i,N) for j in range(denc.shape[1]): vec_col=qobj.decimal_binary(j,N) vec_row2=vec_row.copy() for k in sub_tr: temp=vec_row2[k-1] vec_row2[k-1]=vec_col[k-1] vec_col[k-1]=temp row=qobj.binary_decimal(vec_row2) col=qobj.binary_decimal(vec_col) denc2[row,col]=denc[i,j] else: denc2=np.zeros([2**N,2**N],dtype='float64') for i in range(denc.shape[0]): vec_row=qobj.decimal_binary(i,N) for j in range(denc.shape[1]): vec_col=qobj.decimal_binary(j,N) vec_row2=vec_row.copy() for k in sub_tr: temp=vec_row2[k-1] vec_row2[k-1]=vec_col[k-1] vec_col[k-1]=temp row=qobj.binary_decimal(vec_row2) col=qobj.binary_decimal(vec_col) denc2[row,col]=denc[i,j] return(denc2) def __dectobin(self,n,l): """It converts decimal to binary. Attributes: n: entry of the decimal number l: length of the binary output Returns: dtb: a numpy array containing the binary equivalent of number n """ import numpy as np p=n dtb=np.empty([l,1]) for i in range(0,l): dtb[l-1-i]=int(p % 2) p=int(p/2) #print(dtb) return(dtb) # Binary to decimal conversion def __bintodec(self,vec): """ It converts biinary to decimal Attributes: vec: entry of 1D array of binary numbers {0,1} Returns: t: decimal equivalent of the vec """ t=0 for i in range(0,len(vec)): t=t+vec[len(vec)-1-i]*(2**i) #print(dtb) return(int(t)) class Entanglement(PartialTr): # Concurrence calculation for a real pure state def concurrence_vec(self,state,i,j,eps=10**(-13)): """ Calculation of concurrence for a quantum state Parameters state : Real or complex state i : It stores the place values of the qubits. j : It stores the place values of the qubits. eps : Below the eps value the eigenvalues will be considered zero. The default is 10**(-13). Returns conc: concurrence value """ sigmay=np.zeros([4,4],dtype='float64') typestate=str(state.dtype) if re.findall("^complex",typestate): sigmay[0,3]=-1 sigmay[1,2]=1 sigmay[2,1]=1 sigmay[3,0]=-1 sub_tr=[i,j] rdm= self.partial_trace_vec(state,sub_tr) rhot3=rdm@sigmay@np.conjugate(rdm)@sigmay w,vl,vr,info =la.zgeev(rhot3) wc=[] for i in range(0,4): if abs(w.item(i))<eps: wc.append(0.000000000000000) else: wc.append(abs(w.item(i))) wc.sort(reverse=True) wc=np.array(wc,dtype='float64') conc=math.sqrt(wc.item(0))-math.sqrt(wc.item(1))-\ math.sqrt(wc.item(2))-math.sqrt(wc.item(3)) if conc<0: conc=0 else: sigmay[0,3]=-1 sigmay[1,2]=1 sigmay[2,1]=1 sigmay[3,0]=-1 sub_tr=[i,j] rdm= self.partial_trace_vec(state,sub_tr) rhot3=rdm@sigmay@rdm@sigmay wr,wi,vl,vr,info =la.dgeev(rhot3) w=[] for i in range(0,4): if wr[i] < eps: w.append(0.000000000000000) else: w.append(np.float64(wr.item(i))) w.sort(reverse=True) w=np.array(w,dtype='float64') conc=math.sqrt(w.item(0))-math.sqrt(w.item(1))-\ math.sqrt(w.item(2))-math.sqrt(w.item(3)) if conc<0: conc=0.0 return(np.float64(conc)) # Concurrence calculation for real state density matrix def concurrence_den(self,state,i,j,eps=10**(-13)): """ Calculation of concurrence for a density matrix Parameters state : Real or complex density matrix i : It stores the place values of the qubits. j : It stores the place values of the qubits. eps : Below the eps value the eigenvalues will be considered zero. The default is 10**(-13). Returns conc: concurrence value """ sigmay=np.zeros([4,4],dtype='float64') typestate=str(state.dtype) if re.findall("^complex",typestate): sigmay[0,3]=-1 sigmay[1,2]=1 sigmay[2,1]=1 sigmay[3,0]=-1 sub_tr=[i,j] rdm= self.partial_trace_den(state,sub_tr) rhot3=rdm@sigmay@np.conjugate(rdm)@sigmay w,vl,vr,info =la.zgeev(rhot3) wc=[] for i in range(0,4): if abs(w.item(i))<eps: wc.append(0.000000000000000) else: wc.append(abs(w.item(i))) wc.sort(reverse=True) wc=np.array(wc,dtype='float64') conc=math.sqrt(wc.item(0))-math.sqrt(wc.item(1))-\ math.sqrt(wc.item(2))-math.sqrt(wc.item(3)) if conc<0: conc=0 else: sigmay[0,3]=-1 sigmay[1,2]=1 sigmay[2,1]=1 sigmay[3,0]=-1 sub_tr=[i,j] rdm= self.partial_trace_den(state,sub_tr) rhot3=rdm@sigmay@rdm@sigmay wr,wi,vl,vr,info =la.dgeev(rhot3) w=[] for i in range(0,4): if wr[i] < eps: w.append(0.000000000000000) else: w.append(np.float64(wr.item(i))) w.sort(reverse=True) w=np.array(w,dtype='float64') conc=math.sqrt(w.item(0))-math.sqrt(w.item(1))-\ math.sqrt(w.item(2))-math.sqrt(w.item(3)) if conc<0: conc=0.0 return(np.float64(conc)) # Block entropy for a pure real state def block_entropy_vec(self,state,sub_tr,eps=10**(-13)): """ Calculation of block entropy for a quantum state Parameters state : Real or complex state sub_tr: List of numbers designating the particular subsystems not to be traced out. eps : Below the eps value the eigenvalues will be considered zero. The default is 10**(-13). Returns Bent: Block entropy value """ typestate=str(state.dtype) rdm= self.partial_trace_vec(state,sub_tr) if re.findall("^complex",typestate): w,v,info=la.zheev(rdm) else: w,v,info=la.dsyev(rdm) wlen=len(w) Bent=0.0 for x in range(0,wlen): if abs(w.item(x))<eps: w[x]=0.000000000000000 else: assert w.item(x) > 0.0,\ "The density matrix entered is not correct as the eigenvalues are negative" Bent=Bent-(w.item(x)*math.log(w.item(x),2)) return(Bent) # Block entropy for a pure real density matrix def block_entropy_den(self,state,sub_tr,eps=10**(-13)): """ Calculation of block entropy for a density matrix Parameters state : Real or complex density matrix sub_tr: List of numbers designating the particular subsystems not to be traced out. eps : Below the eps value the eigenvalues will be considered zero. The default is 10**(-13). Returns Bent: Block entropy value """ typestate=str(state.dtype) rdm= self.partial_trace_den(state,sub_tr) if re.findall("^complex",typestate): w,v,info=la.zheev(rdm) else: w,v,info=la.dsyev(rdm) wlen=len(w) Bent=0.0 for x in range(0,wlen): if abs(w.item(x))<eps: w[x]=0.000000000000000 else: assert w.item(x) > 0.0,\ "The density matrix entered is not correct as the eigenvalues are negative" Bent=Bent-(w.item(x)*math.log(w.item(x),2)) return(Bent) # Q measure for pure real state def QMeasure_vec(self,state): """ Calculation of Q measure for a quantum state Parameters state : Real or complex state Returns Qmeas: Q measure value """ NN=math.log2(state.shape[0])/math.log2(2) NN=int(NN) sub_tr=np.zeros([NN,1]) sum3=0.0 for x in range(0,NN): sub_tr=[] sub_tr.append(x+1) rho=self.partial_trace_vec(state,sub_tr) rho=np.matmul(rho,rho) tr2=np.trace(rho) sum3=sum3+tr2 Qmeas=2*(1-(sum3/NN)) return abs(Qmeas) # Q measure for real density matrix def QMeasure_den(self,den): """ Calculation of Q measure for a density matrix Parameters den : Real or complex density matrix Returns Qmeas: Q measure value """ NN=math.log2(den.shape[0])/math.log2(2) NN=int(NN) sub_tr=np.zeros([NN,1]) sum3=0.0 for x in range(0,NN): sub_tr=[] sub_tr.append(x+1) rho=self.partial_trace_den(den,sub_tr) rho=np.matmul(rho,rho) tr2=np.trace(rho) sum3=sum3+tr2 Qmeas=2*(1-(sum3/NN)) return abs(Qmeas) # Negativity of real pure state def negativity_log_vec(self,state,sub_tr,eps=10**(-13)): """ Calculation of negativity and logarithmic negativity for a quantum state Parameters state : Real or complex state sub_tr: List of numbers designating the particular subsystems to be transposed. eps : Below the eps value the eigenvalues will be considered zero. The default is 10**(-13). Returns negv,lognegv : negativity and log negativity values, respectively """ laobj=LA() typestate=str(state.dtype) rhoa=self.ptranspose_vec(state,sub_tr) if re.findall("^complex",typestate): negv=laobj.trace_norm_cmatrix(rhoa,precision=eps) else: negv=laobj.trace_norm_rmatrix(rhoa,precision=eps) assert negv > 0.0,\ "The density matrix entered is not correct as the negativity is negative" lognegv=math.log2(negv) negv=(negv-1)/2 return(negv,lognegv) # Negativity of real pure state def negativity_log_den(self,den,sub_tr,eps=10**(-13)): """ Calculation of negativity and logarithmic negativity for a density matrix Parameters state : Real or complex density matrix sub_tr: List of numbers designating the particular subsystems to be transposed. eps : Below the eps value the eigenvalues will be considered zero. The default is 10**(-13). Returns negv,lognegv : negativity and log negativity values, respectively """ laobj=LA() typestate=str(den.dtype) rhoa=self.ptranspose_den(den,sub_tr) if re.findall("^complex",typestate): negv=laobj.trace_norm_cmatrix(rhoa,precision=eps) else: negv=laobj.trace_norm_rmatrix(rhoa,precision=eps) assert negv > 0.0,\ "The density matrix entered is not correct as the negativity is negative" lognegv=math.log2(negv) negv=(negv-1)/2 return(negv,lognegv) def renyi_entropy(self,rho,alpha): """ Calculation of Renyi entropy Parameters rho : Real or complex density matrix alpha : It is the value of Renyi index Returns renyi : Renyi Entropy value """ assert alpha != 1.0, "alpha should not be equal to 1" typerho=str(rho.dtype) laobj=LA() if re.findall('^complex',typerho): renyi=math.log(abs(np.trace(laobj.power_hmatrix(rho,alpha))))/(1-alpha) else: renyi=math.log(np.trace(laobj.power_smatrix(rho,alpha)))/(1-alpha) return renyi def entanglement_spectrum(self,rho): """ Calculation of entanglement spectrum of a density matrix Parameters rho : Real or complex density matrix Returns eigenvalues : List containing the eigenvalues of rho logeigenvalues : List containing the negative logarithmic eigenvalues of rho """ typerho=str(rho.dtype) if re.findall('^complex',typerho): eigenvalues,eigenvectors,info=la.zheev(rho) else: eigenvalues,eigenvectors,info=la.dsyev(rho) logeigenvalues=np.zeros([eigenvalues.shape[0]],dtype='float64') for i in range(0,eigenvalues.shape[0]): assert eigenvalues[i]>0.0,\ "The eigenvalues of the matrix is coming less than equal to zero" logeigenvalues[i]=(-1)*math.log(eigenvalues[i]) return (eigenvalues,logeigenvalues) def residual_entanglement_vec(self,state): """ Calculation of residual entanglement for a three-qubit quantum state Parameters state : Real or complex 3-qubit state Returns res_tang : Residual entanglement value """ assert state.shape[0]==8,"It is not a three qubit quantum system" det=np.linalg.det(self.partial_trace_vec(state,[1])) det=4*det res_tang=det-(self.concurrence_vec(state,1,2)**2)-\ (self.concurrence_vec(state,1,3)**2) res_tang=abs(res_tang) return res_tang def residual_entanglement_den(self,den): """ Calculation of residual entanglement for a three-qubit density matrix Parameters den : Real or complex 3-qubit density matrix Returns res_tang : Residual entanglement value """ assert den.shape[0]==8,"It is not a three qubit quantum system" det=np.linalg.det(self.partial_trace_den(den,[1])) det=4*det res_tang=det-(self.concurrence_den(den,1,2)**2)-\ (self.concurrence_den(den,1,3)**2) res_tang=abs(res_tang) return res_tang

36.750696

98

0.497935

3,355

26,387

3.836364

0.080179

0.022531

0.019268

0.012431

0.821925

0.787041

0.768705

0.745474

0.72473

0.710434

0

0.043175

0.396976

26,387

717

99

36.801953

0.765711

0.201993

0

0.846626

0

0.038991

0

0.02454

1

0.038855

false

0

0.01636

0

0.071575

0

null

0

1

0

1

0

null

0

7

5bbc80849986a5e15c02563156c13327c939f1e4

19,357

py

Python

models/cdae.py

chenrz925/DiamondNet

d195dbd5fc6c8ffcf7485a5180f790532f068db9

[ "Apache-2.0" ]

null

models/cdae.py

chenrz925/DiamondNet

d195dbd5fc6c8ffcf7485a5180f790532f068db9

[ "Apache-2.0" ]

null

models/cdae.py

chenrz925/DiamondNet

d195dbd5fc6c8ffcf7485a5180f790532f068db9

[ "Apache-2.0" ]

null

from typing import Dict, Text, Any, Tuple, Union import torch from torch import nn class DenoiseL(nn.Module): def __init__(self, in_features: int, ratio: float): super(DenoiseL, self).__init__() assert in_features > 0 assert 0.0 <= ratio < 1.0 self.permutation = nn.Parameter(torch.randperm(in_features), requires_grad=False) self.ratio = ratio self.in_features = in_features def forward(self, *input: torch.Tensor, **kwargs: Any) -> torch.Tensor: return input[0].index_fill(-1, self.permutation[:int(self.ratio * self.in_features)], 0.0) def __repr__(self): return f'DenoiseL({self.in_features}, ratio={self.ratio})' class ConvAutoEncoder1LayerDeCoBnCotSi(nn.Module): def __init__(self, **kwargs): super(ConvAutoEncoder1LayerDeCoBnCotSi, self).__init__() self.add_module('encoder', nn.ModuleDict({ 'denoise': DenoiseL(kwargs['in_features'], kwargs['denoise']['ratio'] if 'denoise' in kwargs and 'ratio' in kwargs[ 'denoise'] else 0.2), 'conv': nn.Conv1d( in_channels=kwargs['conv1d']['in_channels'], out_channels=kwargs['conv1d']['out_channels'], kernel_size=kwargs['conv1d']['kernel_size'], stride=kwargs['conv1d']['stride'] if 'conv1d' in kwargs and 'stride' in kwargs['conv1d'] else 1, padding=kwargs['conv1d']['padding'] if 'conv1d' in kwargs and 'padding' in kwargs['conv1d'] else 0, dilation=kwargs['conv1d']['dilation'] if 'conv1d' in kwargs and 'dilation' in kwargs['conv1d'] else 1, groups=kwargs['conv1d']['groups'] if 'conv1d' in kwargs and 'groups' in kwargs['conv1d'] else 1, bias=kwargs['conv1d']['bias'] if 'conv1d' in kwargs and 'bias' in kwargs['conv1d'] else True, padding_mode=kwargs['padding_mode'] if 'conv1d' in kwargs and 'padding_mode' in kwargs[ 'conv1d'] else 'zeros', ), 'batchnorm': nn.BatchNorm1d( num_features=kwargs['conv1d']['out_channels'] ), })) self.add_module('decoder', nn.ModuleDict({ 'convtranspose': nn.ConvTranspose1d( in_channels=kwargs['conv1d']['out_channels'], out_channels=kwargs['conv1d']['in_channels'], kernel_size=kwargs['conv1d']['kernel_size'], stride=kwargs['conv1d']['stride'] if 'stride' in kwargs else 1, padding=kwargs['conv1d']['padding'] if 'padding' in kwargs else 0, dilation=kwargs['conv1d']['dilation'] if 'dilation' in kwargs else 1, groups=kwargs['conv1d']['groups'] if 'groups' in kwargs else 1, bias=kwargs['conv1d']['bias'] if 'bias' in kwargs else True, padding_mode=kwargs['padding_mode'] if 'padding_mode' in kwargs else 'zeros', ), 'sigmoid': nn.Sigmoid() })) def forward(self, *input: torch.Tensor, **kwargs: Dict[Text, torch.Tensor]) -> Union[ Tuple[torch.Tensor, torch.Tensor], torch.Tensor ]: return_features = kwargs['return_features'] if 'return_features' in kwargs else False childrens = dict(self.named_children()) features = childrens['encoder']['denoise'](input[0]) features = childrens['encoder']['conv'](features) features = childrens['encoder']['batchnorm'](features) output_features = features features = childrens['decoder']['convtranspose'](features) features = childrens['decoder']['sigmoid'](features) if return_features: return features, output_features else: return features class ConvAutoEncoder1LayerDeCoSeCotSi(nn.Module): def __init__(self, **kwargs: Dict[Text, Any]): super(ConvAutoEncoder1LayerDeCoSeCotSi, self).__init__() self.add_module('encoder', nn.ModuleDict({ 'denoise': DenoiseL(kwargs['in_features'], kwargs['denoise']['ratio'] if 'denoise' in kwargs and 'ratio' in kwargs[ 'denoise'] else 0.2), 'conv': nn.Conv1d( in_channels=kwargs['conv1d']['in_channels'], out_channels=kwargs['conv1d']['out_channels'], kernel_size=kwargs['conv1d']['kernel_size'], stride=kwargs['conv1d']['stride'] if 'conv1d' in kwargs and 'stride' in kwargs['conv1d'] else 1, padding=kwargs['conv1d']['padding'] if 'conv1d' in kwargs and 'padding' in kwargs['conv1d'] else 0, dilation=kwargs['conv1d']['dilation'] if 'conv1d' in kwargs and 'dilation' in kwargs['conv1d'] else 1, groups=kwargs['conv1d']['groups'] if 'conv1d' in kwargs and 'groups' in kwargs['conv1d'] else 1, bias=kwargs['conv1d']['bias'] if 'conv1d' in kwargs and 'bias' in kwargs['conv1d'] else True, padding_mode=kwargs['padding_mode'] if 'conv1d' in kwargs and 'padding_mode' in kwargs[ 'conv1d'] else 'zeros', ), 'selu': nn.SELU(), })) self.add_module('decoder', nn.ModuleDict({ 'convtranspose': nn.ConvTranspose1d( in_channels=kwargs['conv1d']['out_channels'], out_channels=kwargs['conv1d']['in_channels'], kernel_size=kwargs['conv1d']['kernel_size'], stride=kwargs['conv1d']['stride'] if 'stride' in kwargs else 1, padding=kwargs['conv1d']['padding'] if 'padding' in kwargs else 0, dilation=kwargs['conv1d']['dilation'] if 'dilation' in kwargs else 1, groups=kwargs['conv1d']['groups'] if 'groups' in kwargs else 1, bias=kwargs['conv1d']['bias'] if 'bias' in kwargs else True, padding_mode=kwargs['padding_mode'] if 'padding_mode' in kwargs else 'zeros', ), 'sigmoid': nn.Sigmoid() })) def forward(self, *input: torch.Tensor, **kwargs: Dict[Text, torch.Tensor]) -> Union[ Tuple[torch.Tensor, torch.Tensor], torch.Tensor ]: return_features = kwargs['return_features'] if 'return_features' in kwargs else False childrens = dict(self.named_children()) features = childrens['encoder']['denoise'](input[0]) features = childrens['encoder']['conv'](features) features = childrens['encoder']['selu'](features) output_features = features features = childrens['decoder']['convtranspose'](features) features = childrens['decoder']['sigmoid'](features) if return_features: return features, output_features else: return features class ConvAutoEncoder2LayerDeCoSeCoSeCotSeCotSi(nn.Module): def __init__(self, **kwargs): super(ConvAutoEncoder2LayerDeCoSeCoSeCotSeCotSi, self).__init__() self.add_module('encoder', nn.ModuleDict({ 'denoise': DenoiseL(kwargs['in_features'], kwargs['denoise']['ratio'] if 'denoise' in kwargs and 'ratio' in kwargs[ 'denoise'] else 0.2), 'conv1': nn.Conv1d( in_channels=kwargs['conv1d'][0]['in_channels'], out_channels=kwargs['conv1d'][0]['out_channels'], kernel_size=kwargs['conv1d'][0]['kernel_size'], stride=kwargs['conv1d'][0]['stride'] if 'conv1d' in kwargs and 'stride' in kwargs['conv1d'][0] else 1, padding=kwargs['conv1d'][0]['padding'] if 'conv1d' in kwargs and 'padding' in kwargs['conv1d'][ 0] else 0, dilation=kwargs['conv1d'][0]['dilation'] if 'conv1d' in kwargs and 'dilation' in kwargs[ 'conv1d'] else 1, groups=kwargs['conv1d'][0]['groups'] if 'conv1d' in kwargs and 'groups' in kwargs['conv1d'][0] else 1, bias=kwargs['conv1d'][0]['bias'] if 'conv1d' in kwargs and 'bias' in kwargs['conv1d'][0] else True, padding_mode=kwargs['padding_mode'] if 'conv1d' in kwargs and 'padding_mode' in kwargs[ 'conv1d'] else 'zeros', ), 'bn1': nn.BatchNorm1d(kwargs['conv1d'][0]['in_channels']), 'selu1': nn.SELU(), 'conv2': nn.Conv1d( in_channels=kwargs['conv1d'][1]['in_channels'], out_channels=kwargs['conv1d'][1]['out_channels'], kernel_size=kwargs['conv1d'][1]['kernel_size'], stride=kwargs['conv1d'][1]['stride'] if 'conv1d' in kwargs and 'stride' in kwargs['conv1d'][1] else 1, padding=kwargs['conv1d'][1]['padding'] if 'conv1d' in kwargs and 'padding' in kwargs['conv1d'][ 1] else 0, dilation=kwargs['conv1d'][1]['dilation'] if 'conv1d' in kwargs and 'dilation' in kwargs['conv1d'][ 1] else 1, groups=kwargs['conv1d'][1]['groups'] if 'conv1d' in kwargs and 'groups' in kwargs['conv1d'][1] else 1, bias=kwargs['conv1d'][1]['bias'] if 'conv1d' in kwargs and 'bias' in kwargs['conv1d'][1] else True, padding_mode=kwargs['padding_mode'] if 'conv1d' in kwargs and 'padding_mode' in kwargs[ 'conv1d'] else 'zeros', ), 'bn2': nn.BatchNorm1d(kwargs['conv1d'][1]['in_channels']), 'selu2': nn.SELU(), })) self.add_module('decoder', nn.ModuleDict({ 'convtranspose1': nn.ConvTranspose1d( in_channels=kwargs['conv1d'][1]['out_channels'], out_channels=kwargs['conv1d'][1]['in_channels'], kernel_size=kwargs['conv1d'][1]['kernel_size'], stride=kwargs['conv1d'][1]['stride'] if 'stride' in kwargs['conv1d'][1] else 1, padding=kwargs['conv1d'][1]['padding'] if 'padding' in kwargs['conv1d'][1] else 0, dilation=kwargs['conv1d'][1]['dilation'] if 'dilation' in kwargs['conv1d'][1] else 1, groups=kwargs['conv1d'][1]['groups'] if 'groups' in kwargs['conv1d'][1] else 1, bias=kwargs['conv1d'][1]['bias'] if 'bias' in kwargs['conv1d'][1] else True, padding_mode=kwargs['padding_mode'] if 'padding_mode' in kwargs['conv1d'][1] else 'zeros', ), 'selu': nn.SELU(), 'bn1': nn.BatchNorm1d(kwargs['conv1d'][1]['out_channels']), 'convtranspose2': nn.ConvTranspose1d( in_channels=kwargs['conv1d'][0]['out_channels'], out_channels=kwargs['conv1d'][0]['in_channels'], kernel_size=kwargs['conv1d'][0]['kernel_size'], stride=kwargs['conv1d'][0]['stride'] if 'stride' in kwargs['conv1d'][0] else 1, padding=kwargs['conv1d'][0]['padding'] if 'padding' in kwargs['conv1d'][0] else 0, dilation=kwargs['conv1d'][0]['dilation'] if 'dilation' in kwargs['conv1d'][0] else 1, groups=kwargs['conv1d'][0]['groups'] if 'groups' in kwargs['conv1d'][0] else 1, bias=kwargs['conv1d'][0]['bias'] if 'bias' in kwargs['conv1d'][0] else True, padding_mode=kwargs['padding_mode'] if 'padding_mode' in kwargs['conv1d'][0] else 'zeros', ), 'bn2': nn.BatchNorm1d(kwargs['conv1d'][0]['out_channels']), 'sigmoid': nn.Sigmoid() })) def forward(self, *input: torch.Tensor, **kwargs: Any) -> Union[ Tuple[torch.Tensor, torch.Tensor], torch.Tensor ]: return_features = kwargs['return_features'] if 'return_features' in kwargs else False childrens = dict(self.named_children()) features = childrens['encoder']['denoise'](input[0]) # features = childrens['encoder']['bn1'](features) features = childrens['encoder']['conv1'](features) # print(features.shape) features = childrens['encoder']['selu1'](features) # features = childrens['encoder']['bn2'](features) features = childrens['encoder']['conv2'](features) features = childrens['encoder']['selu2'](features) output_features = features # features = childrens['decoder']['bn1'](features) features = childrens['decoder']['convtranspose1'](features) features = childrens['decoder']['selu'](features) # features = childrens['decoder']['bn2'](features) features = childrens['decoder']['convtranspose2'](features) features = childrens['decoder']['sigmoid'](features) if return_features: return features, output_features else: return features class ConvAutoEncoder2LayerLiDeCoSeCoSeCotSeCotSi(nn.Module): def __init__(self, **kwargs): super(ConvAutoEncoder2LayerLiDeCoSeCoSeCotSeCotSi, self).__init__() self.add_module('encoder', nn.ModuleDict({ 'linear': nn.Linear( in_features=kwargs['in_features'], out_features=kwargs['linear_out_features'] ), 'selu0': nn.SELU(), 'denoise': DenoiseL(kwargs['linear_out_features'], kwargs['denoise']['ratio'] if 'denoise' in kwargs and 'ratio' in kwargs[ 'denoise'] else 0.2), 'conv1': nn.Conv1d( in_channels=kwargs['conv1d'][0]['in_channels'], out_channels=kwargs['conv1d'][0]['out_channels'], kernel_size=kwargs['conv1d'][0]['kernel_size'], stride=kwargs['conv1d'][0]['stride'] if 'conv1d' in kwargs and 'stride' in kwargs['conv1d'][0] else 1, padding=kwargs['conv1d'][0]['padding'] if 'conv1d' in kwargs and 'padding' in kwargs['conv1d'][ 0] else 0, dilation=kwargs['conv1d'][0]['dilation'] if 'conv1d' in kwargs and 'dilation' in kwargs[ 'conv1d'] else 1, groups=kwargs['conv1d'][0]['groups'] if 'conv1d' in kwargs and 'groups' in kwargs['conv1d'][0] else 1, bias=kwargs['conv1d'][0]['bias'] if 'conv1d' in kwargs and 'bias' in kwargs['conv1d'][0] else True, padding_mode=kwargs['padding_mode'] if 'conv1d' in kwargs and 'padding_mode' in kwargs[ 'conv1d'] else 'zeros', ), # 'bn1': nn.BatchNorm1d(config['conv1d'][0]['in_channels']), 'selu1': nn.SELU(), 'conv2': nn.Conv1d( in_channels=kwargs['conv1d'][1]['in_channels'], out_channels=kwargs['conv1d'][1]['out_channels'], kernel_size=kwargs['conv1d'][1]['kernel_size'], stride=kwargs['conv1d'][1]['stride'] if 'conv1d' in kwargs and 'stride' in kwargs['conv1d'][1] else 1, padding=kwargs['conv1d'][1]['padding'] if 'conv1d' in kwargs and 'padding' in kwargs['conv1d'][ 1] else 0, dilation=kwargs['conv1d'][1]['dilation'] if 'conv1d' in kwargs and 'dilation' in kwargs['conv1d'][ 1] else 1, groups=kwargs['conv1d'][1]['groups'] if 'conv1d' in kwargs and 'groups' in kwargs['conv1d'][1] else 1, bias=kwargs['conv1d'][1]['bias'] if 'conv1d' in kwargs and 'bias' in kwargs['conv1d'][1] else True, padding_mode=kwargs['padding_mode'] if 'conv1d' in kwargs and 'padding_mode' in kwargs[ 'conv1d'] else 'zeros', ), # 'bn2': nn.BatchNorm1d(config['conv1d'][1]['in_channels']), 'selu2': nn.SELU(), })) self.add_module('decoder', nn.ModuleDict({ 'convtranspose1': nn.ConvTranspose1d( in_channels=kwargs['conv1d'][1]['out_channels'], out_channels=kwargs['conv1d'][1]['in_channels'], kernel_size=kwargs['conv1d'][1]['kernel_size'], stride=kwargs['conv1d'][1]['stride'] if 'stride' in kwargs['conv1d'][1] else 1, padding=kwargs['conv1d'][1]['padding'] if 'padding' in kwargs['conv1d'][1] else 0, dilation=kwargs['conv1d'][1]['dilation'] if 'dilation' in kwargs['conv1d'][1] else 1, groups=kwargs['conv1d'][1]['groups'] if 'groups' in kwargs['conv1d'][1] else 1, bias=kwargs['conv1d'][1]['bias'] if 'bias' in kwargs['conv1d'][1] else True, padding_mode=kwargs['padding_mode'] if 'padding_mode' in kwargs['conv1d'][1] else 'zeros', ), 'selu1': nn.SELU(), # 'bn1': nn.BatchNorm1d(config['conv1d'][1]['out_channels']), 'convtranspose2': nn.ConvTranspose1d( in_channels=kwargs['conv1d'][0]['out_channels'], out_channels=kwargs['conv1d'][0]['in_channels'], kernel_size=kwargs['conv1d'][0]['kernel_size'], stride=kwargs['conv1d'][0]['stride'] if 'stride' in kwargs['conv1d'][0] else 1, padding=kwargs['conv1d'][0]['padding'] if 'padding' in kwargs['conv1d'][0] else 0, dilation=kwargs['conv1d'][0]['dilation'] if 'dilation' in kwargs['conv1d'][0] else 1, groups=kwargs['conv1d'][0]['groups'] if 'groups' in kwargs['conv1d'][0] else 1, bias=kwargs['conv1d'][0]['bias'] if 'bias' in kwargs['conv1d'][0] else True, padding_mode=kwargs['padding_mode'] if 'padding_mode' in kwargs['conv1d'][0] else 'zeros', ), # 'bn2': nn.BatchNorm1d(config['conv1d'][0]['out_channels']), 'selu2': nn.SELU(), 'linear': nn.Linear( in_features=kwargs['linear_out_features'], out_features=kwargs['in_features'], ), 'sigmoid': nn.Sigmoid() })) def forward(self, *input: torch.Tensor, **kwargs: Any) -> Union[ Tuple[torch.Tensor, torch.Tensor], torch.Tensor ]: return_features = kwargs['return_features'] if 'return_features' in kwargs else False childrens = dict(self.named_children()) features = childrens['encoder']['linear'](input[0]) features = childrens['encoder']['selu0'](features) features = childrens['encoder']['denoise'](features) # features = childrens['encoder']['bn1'](features) features = childrens['encoder']['conv1'](features) # print(features.shape) features = childrens['encoder']['selu1'](features) # features = childrens['encoder']['bn2'](features) features = childrens['encoder']['conv2'](features) features = childrens['encoder']['selu2'](features) output_features = features # features = childrens['decoder']['bn1'](features) features = childrens['decoder']['convtranspose1'](features) features = childrens['decoder']['selu1'](features) # features = childrens['decoder']['bn2'](features) features = childrens['decoder']['convtranspose2'](features) features = childrens['decoder']['selu2'](features) features = childrens['decoder']['linear'](features) features = childrens['decoder']['sigmoid'](features) if return_features: return features, output_features else: return features

58.129129

118

0.573384

2,123

19,357

5.12341

0.042864

0.177623

0.077227

0.052956

0.908798

0.891698

0.883883

0.872299

0.864485

0

0.03239

0.267913

19,357

332

119

58.304217

0.735163

0.034768

0

0.850498

0

0.208688

0.0015

0

0.006645

1

0.036545

false

0

0.009967

0.006645

0.096346

0

null

0

1

0

1

0

null

0

7

5bcfeb4eb092adc9e9f23c647caa207e1ff9074c

120

py

Python

lib/py/test/server/conftest.py

galbash/serverless-rpc

27a8ea2571220833fc1086417152a0c2ca95ca6d

[ "MIT" ]

null

lib/py/test/server/conftest.py

galbash/serverless-rpc

27a8ea2571220833fc1086417152a0c2ca95ca6d

[ "MIT" ]

10

2019-11-08T14:41:13.000Z

2022-01-22T09:18:27.000Z

lib/py/test/server/conftest.py

galbash/serverless-rpc

27a8ea2571220833fc1086417152a0c2ca95ca6d

[ "MIT" ]

null

import pytest import unittest.mock @pytest.fixture() def processor(): return unittest.mock.NonCallableMagicMock()

15

47

0.775

13

120

7.153846

0.692308

0.258065

0

0.125

120

7

48

17.142857

0.885714

0

1

0.2

true

0

0.4

0.2

0.8

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

5beedb6c40df2c44bff7db67b105e1b6883e09aa

139

py

Python

console/__init__.py

gorgeousbubble/Nightmare

b374b48877898b6193081b7a8a6d2fb571816c75

[ "Apache-2.0" ]

1

2019-10-24T15:47:18.000Z

console/__init__.py

gorgeousbubble/Nightmare

b374b48877898b6193081b7a8a6d2fb571816c75

[ "Apache-2.0" ]

null

console/__init__.py

gorgeousbubble/Nightmare

b374b48877898b6193081b7a8a6d2fb571816c75

[ "Apache-2.0" ]

3

2019-10-24T15:47:25.000Z

2020-11-01T01:26:41.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import console from console.console import Console from console.console import ConsoleLevel

23.166667

40

0.76259

19

139

5.578947

0.578947

0.245283

0.320755

0.45283

0.641509

0

0.016393

0.122302

139

5

41

27.8

0.852459

0.309353

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

f35d38175477d4bdbadb9fa23497849e76b2e262

9,846

py

Python

evaluation/bin/diff/word_diff_test.py

ckorzen/pdf-text-extraction-benchmark

47b456f7c5c445b5087200d2ce4051647a9cbbf6

[ "MIT" ]

34

2018-05-16T17:50:10.000Z

2021-09-12T19:40:40.000Z

evaluation/bin/diff/word_diff_test.py

e-sim/pdf-text-extraction-benchmark

42eede9867e5795a6fc040b0a7ce92da3ddd3120

[ "MIT" ]

1

2017-06-20T10:31:15.000Z

2017-08-08T20:10:16.000Z

evaluation/bin/diff/word_diff_test.py

e-sim/pdf-text-extraction-benchmark

42eede9867e5795a6fc040b0a7ce92da3ddd3120

[ "MIT" ]

10

2018-07-07T15:37:45.000Z

2021-01-28T07:06:27.000Z

import unittest import word_diff word_diff_tests = [ # (actual, target, expected output) (None, None, "[]"), ("", "", "[]"), ("", None, "[]"), (None, "A", "[[/ [], [A]]]"), ("A", None, "[[/ [A], []]]"), ("A", "", "[[/ [A], []]]"), ("", "A", "[[/ [], [A]]]"), ("A", "A", "[[= [A], [A]]]"), ("A", "A B C", "[[= [A], [A]], [/ [], [B, C]]]"), ("A B C", "A", "[[= [A], [A]], [/ [B, C], []]]"), ("A B C", "A B C", "[[= [A, B, C], [A, B, C]]]"), ("A B C", "A B D", "[[= [A, B], [A, B]], [/ [C], [D]]]"), ("A B C", "A D C", "[[= [A], [A]], [/ [B], [D]], [= [C], [C]]]"), ("A B C", "A D E", "[[= [A], [A]], [/ [B, C], [D, E]]]"), ("A B C", "D B C", "[[/ [A], [D]], [= [B, C], [B, C]]]"), ("A B C", "D B E", "[[/ [A], [D]], [= [B], [B]], [/ [C], [E]]]"), ("A B C", "D E C", "[[/ [A, B], [D, E]], [= [C], [C]]]"), ("A B C", "D E G", "[[/ [A, B, C], [D, E, G]]]") ] class WordDiffTest(unittest.TestCase): """ Tests for word_diff.""" def test_word_diff_from_string(self): """ Tests the method word_diff_from_strings().""" # Test all the given test cases. for test in word_diff_tests: out = word_diff.word_diff_from_strings(test[0], test[1]).phrases self.assertEqual(str(out), test[2], msg="Test: {0}".format(test)) def test_diff_phrases_and_diff_words(self): """ Tests some properties of DiffPhrase and DiffWord objects. """ # Test properties of a phrase. phrase = word_diff.word_diff_from_strings("A B C", "").phrases[0] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 3) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 0) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 0) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 0) self.assertEqual(str(phrase.first_word_actual), "A") self.assertEqual(str(phrase.last_word_actual), "C") self.assertEqual(str(phrase.first_word_target), "None") self.assertEqual(str(phrase.last_word_target), "None") self.assertEqual(phrase.num_words_actual, 3) self.assertEqual(phrase.num_words_target, 0) # Test properties of some words. word = phrase.words_actual[0] self.assertTrue(hasattr(word, "word")) self.assertEqual(word.word, "A") self.assertTrue(hasattr(word, "pos_actual")) self.assertEqual(word.pos_actual, 0) self.assertTrue(hasattr(word, "pos_target")) self.assertEqual(word.pos_target, 0) self.assertTrue(hasattr(word, "phrase")) self.assertTrue(word.phrase is not None) word = phrase.words_actual[2] self.assertTrue(hasattr(word, "word")) self.assertEqual(word.word, "C") self.assertTrue(hasattr(word, "pos_actual")) self.assertEqual(word.pos_actual, 2) self.assertTrue(hasattr(word, "pos_target")) self.assertEqual(word.pos_target, 0) self.assertTrue(hasattr(word, "phrase")) self.assertTrue(word.phrase is not None) # ---------------------------------------------------------------------- phrases = word_diff.word_diff_from_strings("A B C", "C").phrases phrase = phrases[0] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 2) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 0) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 0) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 0) self.assertEqual(str(phrase.first_word_actual), "A") self.assertEqual(str(phrase.last_word_actual), "B") self.assertEqual(str(phrase.first_word_target), "None") self.assertEqual(str(phrase.last_word_target), "None") self.assertEqual(phrase.num_words_actual, 2) self.assertEqual(phrase.num_words_target, 0) phrase = phrases[1] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 1) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 2) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 1) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 0) self.assertEqual(str(phrase.first_word_actual), "C") self.assertEqual(str(phrase.last_word_actual), "C") self.assertEqual(str(phrase.first_word_target), "C") self.assertEqual(str(phrase.last_word_target), "C") self.assertEqual(phrase.num_words_actual, 1) self.assertEqual(phrase.num_words_target, 1) # ---------------------------------------------------------------------- phrases = word_diff.word_diff_from_strings("C", "A B C").phrases phrase = phrases[0] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 0) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 0) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 2) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 0) self.assertEqual(str(phrase.first_word_actual), "None") self.assertEqual(str(phrase.last_word_actual), "None") self.assertEqual(str(phrase.first_word_target), "A") self.assertEqual(str(phrase.last_word_target), "B") self.assertEqual(phrase.num_words_actual, 0) self.assertEqual(phrase.num_words_target, 2) # Test a word. word = phrase.words_target[1] self.assertTrue(hasattr(word, "word")) self.assertEqual(word.word, "B") self.assertTrue(hasattr(word, "pos_actual")) self.assertEqual(word.pos_actual, 0) self.assertTrue(hasattr(word, "pos_target")) self.assertEqual(word.pos_target, 1) self.assertTrue(hasattr(word, "phrase")) self.assertTrue(word.phrase is not None) phrase = phrases[1] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 1) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 0) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 1) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 2) self.assertEqual(str(phrase.first_word_actual), "C") self.assertEqual(str(phrase.last_word_actual), "C") self.assertEqual(str(phrase.first_word_target), "C") self.assertEqual(str(phrase.last_word_target), "C") self.assertEqual(phrase.num_words_actual, 1) self.assertEqual(phrase.num_words_target, 1) # ---------------------------------------------------------------------- phrases = word_diff.word_diff_from_strings("A B C", "A D C").phrases phrase = phrases[0] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 1) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 0) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 1) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 0) self.assertEqual(str(phrase.first_word_actual), "A") self.assertEqual(str(phrase.last_word_actual), "A") self.assertEqual(str(phrase.first_word_target), "A") self.assertEqual(str(phrase.last_word_target), "A") self.assertEqual(phrase.num_words_actual, 1) self.assertEqual(phrase.num_words_target, 1) phrase = phrases[1] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 1) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 1) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 1) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 1) self.assertEqual(str(phrase.first_word_actual), "B") self.assertEqual(str(phrase.last_word_actual), "B") self.assertEqual(str(phrase.first_word_target), "D") self.assertEqual(str(phrase.last_word_target), "D") self.assertEqual(phrase.num_words_actual, 1) self.assertEqual(phrase.num_words_target, 1) phrase = phrases[2] self.assertTrue(hasattr(phrase, "words_actual")) self.assertEqual(len(phrase.words_actual), 1) self.assertTrue(hasattr(phrase, "pos_actual")) self.assertEqual(phrase.pos_actual, 2) self.assertTrue(hasattr(phrase, "words_target")) self.assertEqual(len(phrase.words_target), 1) self.assertTrue(hasattr(phrase, "pos_target")) self.assertEqual(phrase.pos_target, 2) self.assertEqual(str(phrase.first_word_actual), "C") self.assertEqual(str(phrase.last_word_actual), "C") self.assertEqual(str(phrase.first_word_target), "C") self.assertEqual(str(phrase.last_word_target), "C") self.assertEqual(phrase.num_words_actual, 1) self.assertEqual(phrase.num_words_target, 1) if __name__ == '__main__': unittest.main()

43.566372

80

0.612431

1,224

9,846

4.745915

0.051471

0.232398

0.159064

0.148735

0.912894

0.902221

0.880875

0.837321

0.835772

0.803753

0

0.008812

0.204753

9,846

225

81

43.76

0.733078

0.048141

0

0.661111

0

0.011111

0.111385

0

0.761111

1

0.011111

false

0

0.011111

0

0.027778

0

null

1

0

1

0

null

0

1

0

8

45e8790f2365355f37541abc07b61774fad8bd98

47,615

py

Python

examples/dynamic.py

faymek/compression

20c6745b741e266f7118e6b3fc88d22f6179cfdf

[ "Apache-2.0" ]

null

examples/dynamic.py

faymek/compression

20c6745b741e266f7118e6b3fc88d22f6179cfdf

[ "Apache-2.0" ]

null

examples/dynamic.py

faymek/compression

20c6745b741e266f7118e6b3fc88d22f6179cfdf

[ "Apache-2.0" ]

null

import tensorflow.compat.v1 as tf import tensorflow_compression as tfc from tensorflow_compression.python.layers import parameterizers from tensorflow_compression.python.ops import padding_ops from tensorflow_compression.python.ops import math_ops from tensorflow_compression.python.ops import range_coding_ops from tensorflow.python.keras.engine import input_spec import numpy as np class Intercept(tf.layers.Layer): def __init__(self, start, stop, step=1): super(Intercept, self).__init__() self.start = start self.stop = stop self.step = step self.const = tf.constant([1]*stop+[0]*(stop-start),dtype=tf.float32) def build(self, input_shape): #tf.set_random_seed(self.seed) super(Intercept, self).build(input_shape) def call(self, inputs): mask = tf.random_crop(self.const, [self.stop]) rate = tf.reduce_sum(mask) / self.stop output = inputs * mask / rate # broadcast (?,16,16,256) * (256,) return output class InterceptNorate(tf.layers.Layer): def __init__(self, start, stop, step=1): super(InterceptNorate, self).__init__() self.start = start self.stop = stop self.step = step self.const = tf.constant([1]*stop+[0]*(stop-start),dtype=tf.float32) def build(self, input_shape): #tf.set_random_seed(self.seed) super(InterceptNorate, self).build(input_shape) def call(self, inputs): mask = tf.random_crop(self.const, [self.stop]) rate = tf.reduce_sum(mask) / self.stop output = inputs * mask # broadcast (?,16,16,256) * (256,) return output class OneGDN(tfc.GDN): def __init__(self, *args, **kwargs): super(OneGDN, self).__init__(*args, **kwargs) def build(self, input_shape): # Create a trainable weight variable for this layer. super(OneGDN, self).build(input_shape) def call(self, inputs): inputs = tf.convert_to_tensor(inputs, dtype=self.dtype) ndim = self._input_rank if self.rectify: inputs = tf.nn.relu(inputs) # Compute normalization pool. if ndim == 2: norm_pool = tf.linalg.matmul(tf.math.abs(inputs), self.gamma) norm_pool = tf.nn.bias_add(norm_pool, self.beta) elif self.data_format == "channels_last" and ndim <= 4: # TODO(unassigned): This branch should also work for ndim == 5, but # currently triggers a bug in TF. shape = self.gamma.shape.as_list() gamma = tf.reshape(self.gamma, (ndim - 2) * [1] + shape) norm_pool = tf.nn.convolution(tf.math.abs(inputs), gamma, "VALID") norm_pool = tf.nn.bias_add(norm_pool, self.beta) else: # generic implementation # This puts channels in the last dimension regardless of input. norm_pool = tf.linalg.tensordot( tf.math.abs(inputs), self.gamma, [[self._channel_axis()], [0]]) norm_pool += self.beta if self.data_format == "channels_first": # Return to channels_first format if necessary. axes = list(range(ndim - 1)) axes.insert(1, ndim - 1) norm_pool = tf.transpose(norm_pool, axes) if self.inverse: pass else: norm_pool = tf.math.reciprocal(norm_pool) outputs = inputs * norm_pool if not tf.executing_eagerly(): outputs.set_shape(self.compute_output_shape(inputs.shape)) return outputs class DynamicCondSignalConv2D(tfc.SignalConv2D): def __init__(self, *args, **kwargs): super(DynamicCondSignalConv2D, self).__init__(*args, **kwargs) def build(self, input_shape): self.fc_u = tf.keras.layers.Dense(self.filters, activation=tf.nn.softplus, name="fc_u") self.fc_v = tf.keras.layers.Dense(self.filters, activation=None, name="fc_v") super(DynamicCondSignalConv2D, self).build(input_shape) self.input_spec = None def call(self, inputs, lmbda, active_out): inputs = tf.convert_to_tensor(inputs) active_in = tf.shape(inputs)[-1] self.active_out = active_out outputs = inputs # Not for all possible combinations of (`kernel_support`, `corr`, # `strides_up`, `strides_down`) TF ops exist. We implement some additional # combinations by manipulating the kernels and toggling `corr`. kernel = self.kernel corr = self.corr # If a convolution with no upsampling is desired, we flip the kernels and # use cross correlation to implement it, provided the kernels are odd-length # in every dimension (with even-length kernels, the boundary handling # would have to change). if (not corr and all(s == 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = True slices = self._rank * (slice(None, None, -1),) + 2 * (slice(None),) kernel = kernel[slices] # Similarly, we can implement a cross correlation using convolutions. # However, we do this only if upsampling is requested, as we are potentially # wasting computation in the boundaries whenever we call the transpose ops. elif (corr and any(s != 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = False slices = self._rank * (slice(None, None, -1),) + 2 * (slice(None),) kernel = kernel[slices] slices = self._rank * (slice(None),) + (slice(0, active_in), slice(0, active_out)) kernel = kernel[slices] # Compute amount of necessary padding, and determine whether to use built-in # padding or to pre-pad with a separate op. if self.padding == "valid": padding = prepadding = self._rank * ((0, 0),) else: # same_* padding = padding_ops.same_padding_for_kernel( self.kernel_support, corr, self.strides_up) if (self.padding == "same_zeros" and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): # Don't pre-pad and use built-in EXPLICIT mode. prepadding = self._rank * ((0, 0),) else: # Pre-pad and then use built-in valid padding mode. outputs = tf.pad( outputs, self._padded_tuple(padding, (0, 0)), self._pad_mode) prepadding = padding padding = self._rank * ((0, 0),) # Compute the convolution/correlation. Prefer EXPLICIT padding ops where # possible, but don't use them to implement VALID padding. if (corr and all(s == 1 for s in self.strides_up) and not self.channel_separable and 1 <= self._rank <= 2 and not all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_explicit(outputs, kernel, padding) elif (corr and all(s == 1 for s in self.strides_up) and all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_valid(outputs, kernel) elif (not corr and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): outputs = self._up_convolve_transpose_explicit( outputs, kernel, prepadding) elif not corr: outputs = self._up_convolve_transpose_valid( outputs, kernel, prepadding) else: self._raise_notimplemented() # Now, add bias if requested. if self.use_bias: bias = self.bias[slice(0, active_out)] if self.data_format == "channels_first": # As of Mar 2017, direct addition is significantly slower than # bias_add when computing gradients. if self._rank == 1: # tf.nn.bias_add does not accept a 1D input tensor. outputs = tf.expand_dims(outputs, 2) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.squeeze(outputs, [2]) elif self._rank == 2: outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") elif self._rank >= 3: shape = tf.shape(outputs) outputs = tf.reshape( outputs, tf.concat([shape[:3], [-1]], axis=0)) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.reshape(outputs, shape) else: outputs = tf.nn.bias_add(outputs, bias) s = self.fc_u(lmbda)[slice(None), slice(0, active_out)] b = self.fc_v(lmbda)[slice(None), slice(0, active_out)] outputs = outputs * s + b # Finally, pass through activation function if requested. if self.activation is not None: outputs = self.activation(outputs) # pylint:disable=not-callable # Aid shape inference, for some reason shape info is not always available. if not tf.executing_eagerly(): outputs.set_shape(self.compute_output_shape(inputs.shape)) #print(kernel) #print(outputs) return outputs def compute_output_shape(self, input_shape): input_shape = tf.TensorShape(input_shape) input_shape = input_shape.with_rank(self._rank + 2) batch = input_shape[0] if self.data_format == "channels_first": spatial = input_shape[2:].dims channels = input_shape[1] else: spatial = input_shape[1:-1].dims channels = input_shape[-1] for i, s in enumerate(spatial): if self.extra_pad_end: s *= self.strides_up[i] else: s = (s - 1) * self.strides_up[i] + 1 if self.padding == "valid": s -= self.kernel_support[i] - 1 s = (s - 1) // self.strides_down[i] + 1 spatial[i] = s if self.channel_separable: channels *= self.active_out else: channels = self.active_out if self.data_format == "channels_first": return tf.TensorShape([batch, None] + spatial) else: return tf.TensorShape([batch] + spatial + [None]) def _up_convolve_transpose_valid(self, inputs, kernel, prepadding): # Computes upsampling followed by convolution, via transpose convolution ops # in VALID mode. This is a relatively inefficient implementation of # upsampled convolutions, where we need to crop away a lot of the values # computed in the boundaries. # Transpose convolutions expect the output and input channels in reversed # order. We implement this by swapping those dimensions of the kernel. # For channel separable convolutions, we can't currently perform anything # other than one filter per channel, so the last dimension needs to be of # length one. Since this happens to be the format that the op expects it, # we can skip the transpose in that case. if not self.channel_separable: kernel = tf.transpose( kernel, list(range(self._rank)) + [self._rank + 1, self._rank]) # Compute shape of temporary. input_shape = tf.shape(inputs) temp_shape = [input_shape[0]] + (self._rank + 1) * [None] if self.data_format == "channels_last": spatial_axes = range(1, self._rank + 1) temp_shape[-1] = ( input_shape[-1] if self.channel_separable else self.active_out) else: spatial_axes = range(2, self._rank + 2) temp_shape[1] = input_shape[1] if self.channel_separable else self.active_out if self.extra_pad_end: get_length = lambda l, s, k: l * s + (k - 1) else: get_length = lambda l, s, k: l * s + ((k - 1) - (s - 1)) for i, a in enumerate(spatial_axes): temp_shape[a] = get_length( input_shape[a], self.strides_up[i], self.kernel_support[i]) data_format = self._op_data_format strides = self._padded_tuple(self.strides_up, 1) # Compute convolution. if self._rank == 1 and not self.channel_separable: # There's no 1D equivalent to conv2d_backprop_input, so we insert an # extra dimension and use the 2D op. extradim = {"channels_first": 2, "channels_last": 1}[self.data_format] data_format = data_format.replace("W", "HW") strides = strides[:extradim] + (strides[extradim],) + strides[extradim:] temp_shape = temp_shape[:extradim] + [1] + temp_shape[extradim:] kernel = tf.expand_dims(kernel, 0) inputs = tf.expand_dims(inputs, extradim) outputs = tf.nn.conv2d_backprop_input( temp_shape, kernel, inputs, strides=strides, padding="VALID", data_format=data_format) outputs = tf.squeeze(outputs, [extradim]) elif self._rank == 1 and self.channel_separable and self.filters == 1: # There's no 1D equivalent to depthwise_conv2d_native_backprop_input, so # we insert an extra dimension and use the 2D op. extradim = {"channels_first": 2, "channels_last": 1}[self.data_format] data_format = data_format.replace("W", "HW") strides = strides[:extradim] + (strides[extradim],) + strides[extradim:] temp_shape = temp_shape[:extradim] + [1] + temp_shape[extradim:] kernel = tf.expand_dims(kernel, 0) inputs = tf.expand_dims(inputs, extradim) outputs = tf.nn.depthwise_conv2d_native_backprop_input( temp_shape, kernel, inputs, strides=strides, padding="VALID", data_format=data_format) outputs = tf.squeeze(outputs, [extradim]) elif self._rank == 2 and not self.channel_separable: outputs = tf.nn.conv2d_backprop_input( temp_shape, kernel, inputs, strides=strides, padding="VALID", data_format=data_format) elif (self._rank == 2 and self.channel_separable and self.filters == 1 and self.strides_up[0] == self.strides_up[1]): outputs = tf.nn.depthwise_conv2d_native_backprop_input( temp_shape, kernel, inputs, strides=strides, padding="VALID", data_format=data_format) elif self._rank == 3 and not self.channel_separable: outputs = tf.nn.conv3d_transpose( inputs, kernel, temp_shape, strides=strides, padding="VALID", data_format=data_format) else: self._raise_notimplemented() # Perform crop, taking into account any pre-padding that was applied. slices = (self._rank + 2) * [slice(None)] for i, a in enumerate(spatial_axes): if self.padding == "valid": # Take `kernel_support - 1` samples away from both sides. This leaves # just samples computed without any padding. start = stop = self.kernel_support[i] - 1 else: # same # Take half of kernel sizes plus the pre-padding away from each side. start = prepadding[i][0] * self.strides_up[i] start += self.kernel_support[i] // 2 stop = prepadding[i][1] * self.strides_up[i] stop += (self.kernel_support[i] - 1) // 2 step = self.strides_down[i] start = start if start > 0 else None stop = -stop if stop > 0 else None step = step if step > 1 else None slices[a] = slice(start, stop, step) if not all(s.start is s.stop is s.step is None for s in slices): outputs = outputs[tuple(slices)] return outputs def _up_convolve_transpose_explicit(self, inputs, kernel, prepadding): # Computes upsampling followed by convolution, via transpose convolution ops # in EXPLICIT mode. This is an efficient implementation of upsampled # convolutions, where we only compute values that are necessary. do_cast = inputs.dtype.is_integer # conv2d_backprop_input expects the output and input channels in reversed # order. We implement this by swapping those dimensions of the kernel. kernel = tf.transpose( kernel, list(range(self._rank)) + [self._rank + 1, self._rank]) # Compute explicit padding corresponding to the equivalent conv2d call, # and the shape of the output, taking into account any pre-padding. input_shape = tf.shape(inputs) padding = (self._rank + 2) * [(0, 0)] output_shape = [input_shape[0]] + (self._rank + 1) * [None] if self.data_format == "channels_last": spatial_axes = range(1, self._rank + 1) output_shape[-1] = self.active_out else: spatial_axes = range(2, self._rank + 2) output_shape[1] = self.active_out if self.extra_pad_end: get_length = lambda l, s, k, p: l * s + ((k - 1) - p) else: get_length = lambda l, s, k, p: l * s + ((k - 1) - (s - 1) - p) for i, a in enumerate(spatial_axes): if self.padding == "valid": padding[a] = 2 * (self.kernel_support[i] - 1,) else: # same padding[a] = ( prepadding[i][0] * self.strides_up[i] + self.kernel_support[i] // 2, prepadding[i][1] * self.strides_up[i] + ( self.kernel_support[i] - 1) // 2, ) output_shape[a] = get_length( input_shape[a], self.strides_up[i], self.kernel_support[i], sum(padding[a])) data_format = self._op_data_format strides = self._padded_tuple(self.strides_up, 1) # Compute convolution. if self._rank == 1 and not self.channel_separable: # There's no 1D equivalent to conv2d_backprop_input, so we insert an # extra dimension and use the 2D op. extradim = {"channels_first": 2, "channels_last": 1}[self.data_format] data_format = data_format.replace("W", "HW") strides = strides[:extradim] + (strides[extradim],) + strides[extradim:] padding = padding[:extradim] + [(0, 0)] + padding[extradim:] output_shape = output_shape[:extradim] + [1] + output_shape[extradim:] kernel = tf.expand_dims(kernel, 0) inputs = tf.expand_dims(inputs, extradim) if do_cast: inputs = tf.cast(inputs, tf.float32) outputs = tf.nn.conv2d_backprop_input( output_shape, kernel, inputs, strides=strides, padding=padding, data_format=data_format) if do_cast: outputs = tf.cast(tf.math.round(outputs), self.accum_dtype) outputs = tf.squeeze(outputs, [extradim]) elif self._rank == 2 and not self.channel_separable: if do_cast: inputs = tf.cast(inputs, tf.float32) outputs = tf.nn.conv2d_backprop_input( output_shape, kernel, inputs, strides=strides, padding=padding, data_format=data_format) if do_cast: outputs = tf.cast(tf.math.round(outputs), self.accum_dtype) #print(outputs, kernel, inputs, sep='\n') #print() else: self._raise_notimplemented() # Perform downsampling if it is requested. if any(s > 1 for s in self.strides_down): slices = tuple(slice(None, None, s) for s in self.strides_down) slices = self._padded_tuple(slices, slice(None)) outputs = outputs[slices] return outputs class CondSignalConv2D(tfc.SignalConv2D): def __init__(self, *args, **kwargs): super(CondSignalConv2D, self).__init__(*args, **kwargs) def build(self, input_shape): self.fc_u = tf.keras.layers.Dense(self.filters, activation=tf.nn.softplus, name="fc_u") self.fc_v = tf.keras.layers.Dense(self.filters, activation=None, name="fc_v") super(CondSignalConv2D, self).build(input_shape) def call(self, inputs, lmbda): inputs = tf.convert_to_tensor(inputs) outputs = inputs # Not for all possible combinations of (`kernel_support`, `corr`, # `strides_up`, `strides_down`) TF ops exist. We implement some additional # combinations by manipulating the kernels and toggling `corr`. kernel = self.kernel corr = self.corr # If a convolution with no upsampling is desired, we flip the kernels and # use cross correlation to implement it, provided the kernels are odd-length # in every dimension (with even-length kernels, the boundary handling # would have to change). if (not corr and all(s == 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = True slices = self._rank * (slice(None, None, -1),) + 2 * (slice(None),) kernel = kernel[slices] # Similarly, we can implement a cross correlation using convolutions. # However, we do this only if upsampling is requested, as we are potentially # wasting computation in the boundaries whenever we call the transpose ops. elif (corr and any(s != 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = False slices = self._rank * (slice(None, None, -1),) + 2 * (slice(None),) kernel = kernel[slices] # Compute amount of necessary padding, and determine whether to use built-in # padding or to pre-pad with a separate op. if self.padding == "valid": padding = prepadding = self._rank * ((0, 0),) else: # same_* padding = padding_ops.same_padding_for_kernel( self.kernel_support, corr, self.strides_up) if (self.padding == "same_zeros" and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): # Don't pre-pad and use built-in EXPLICIT mode. prepadding = self._rank * ((0, 0),) else: # Pre-pad and then use built-in valid padding mode. outputs = tf.pad( outputs, self._padded_tuple(padding, (0, 0)), self._pad_mode) prepadding = padding padding = self._rank * ((0, 0),) # Compute the convolution/correlation. Prefer EXPLICIT padding ops where # possible, but don't use them to implement VALID padding. if (corr and all(s == 1 for s in self.strides_up) and not self.channel_separable and 1 <= self._rank <= 2 and not all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_explicit(outputs, kernel, padding) elif (corr and all(s == 1 for s in self.strides_up) and all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_valid(outputs, kernel) elif (not corr and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): outputs = self._up_convolve_transpose_explicit( outputs, kernel, prepadding) elif not corr: outputs = self._up_convolve_transpose_valid( outputs, kernel, prepadding) else: self._raise_notimplemented() # Now, add bias if requested. if self.use_bias: bias = self.bias if self.data_format == "channels_first": # As of Mar 2017, direct addition is significantly slower than # bias_add when computing gradients. if self._rank == 1: # tf.nn.bias_add does not accept a 1D input tensor. outputs = tf.expand_dims(outputs, 2) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.squeeze(outputs, [2]) elif self._rank == 2: outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") elif self._rank >= 3: shape = tf.shape(outputs) outputs = tf.reshape( outputs, tf.concat([shape[:3], [-1]], axis=0)) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.reshape(outputs, shape) else: outputs = tf.nn.bias_add(outputs, bias) s = self.fc_u(lmbda) b = self.fc_v(lmbda) outputs = outputs * s + b # Finally, pass through activation function if requested. if self.activation is not None: outputs = self.activation(outputs) # pylint:disable=not-callable # Aid shape inference, for some reason shape info is not always available. if not tf.executing_eagerly(): outputs.set_shape(self.compute_output_shape(inputs.shape)) return outputs class Cond1SignalConv2D(tfc.SignalConv2D): def __init__(self, *args, **kwargs): super(Cond1SignalConv2D, self).__init__(*args, **kwargs) def build(self, input_shape): self.fc1 = tf.keras.layers.Dense(16, activation=tf.nn.relu) self.fc2 = tf.keras.layers.Dense(self.filters, activation=tf.nn.softplus) self.fc3 = tf.keras.layers.Dense(self.filters, activation=None) super(Cond1SignalConv2D, self).build(input_shape) def call(self, inputs, lmbda): inputs = tf.convert_to_tensor(inputs) outputs = inputs # Not for all possible combinations of (`kernel_support`, `corr`, # `strides_up`, `strides_down`) TF ops exist. We implement some additional # combinations by manipulating the kernels and toggling `corr`. kernel = self.kernel corr = self.corr # If a convolution with no upsampling is desired, we flip the kernels and # use cross correlation to implement it, provided the kernels are odd-length # in every dimension (with even-length kernels, the boundary handling # would have to change). if (not corr and all(s == 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = True slices = self._rank * (slice(None, None, -1),) + 2 * (slice(None),) kernel = kernel[slices] # Similarly, we can implement a cross correlation using convolutions. # However, we do this only if upsampling is requested, as we are potentially # wasting computation in the boundaries whenever we call the transpose ops. elif (corr and any(s != 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = False slices = self._rank * (slice(None, None, -1),) + 2 * (slice(None),) kernel = kernel[slices] # Compute amount of necessary padding, and determine whether to use built-in # padding or to pre-pad with a separate op. if self.padding == "valid": padding = prepadding = self._rank * ((0, 0),) else: # same_* padding = padding_ops.same_padding_for_kernel( self.kernel_support, corr, self.strides_up) if (self.padding == "same_zeros" and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): # Don't pre-pad and use built-in EXPLICIT mode. prepadding = self._rank * ((0, 0),) else: # Pre-pad and then use built-in valid padding mode. outputs = tf.pad( outputs, self._padded_tuple(padding, (0, 0)), self._pad_mode) prepadding = padding padding = self._rank * ((0, 0),) # Compute the convolution/correlation. Prefer EXPLICIT padding ops where # possible, but don't use them to implement VALID padding. if (corr and all(s == 1 for s in self.strides_up) and not self.channel_separable and 1 <= self._rank <= 2 and not all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_explicit(outputs, kernel, padding) elif (corr and all(s == 1 for s in self.strides_up) and all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_valid(outputs, kernel) elif (not corr and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): outputs = self._up_convolve_transpose_explicit( outputs, kernel, prepadding) elif not corr: outputs = self._up_convolve_transpose_valid( outputs, kernel, prepadding) else: self._raise_notimplemented() # Now, add bias if requested. if self.use_bias: bias = self.bias if self.data_format == "channels_first": # As of Mar 2017, direct addition is significantly slower than # bias_add when computing gradients. if self._rank == 1: # tf.nn.bias_add does not accept a 1D input tensor. outputs = tf.expand_dims(outputs, 2) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.squeeze(outputs, [2]) elif self._rank == 2: outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") elif self._rank >= 3: shape = tf.shape(outputs) outputs = tf.reshape( outputs, tf.concat([shape[:3], [-1]], axis=0)) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.reshape(outputs, shape) else: outputs = tf.nn.bias_add(outputs, bias) oh = self.fc1(tf.reshape(lmbda, [1,1])) s = self.fc2(oh) b = self.fc3(oh) outputs = outputs * s + b # Finally, pass through activation function if requested. if self.activation is not None: outputs = self.activation(outputs) # pylint:disable=not-callable # Aid shape inference, for some reason shape info is not always available. if not tf.executing_eagerly(): outputs.set_shape(self.compute_output_shape(inputs.shape)) return outputs class Cond0SignalConv2D(tfc.SignalConv2D): def __init__(self, *args, **kwargs): super(Cond0SignalConv2D, self).__init__(*args, **kwargs) def build(self, input_shape): self.fc1 = tf.keras.layers.Dense(16, activation=tf.nn.relu) self.fc2 = tf.keras.layers.Dense(self.filters, activation=tf.nn.softplus) self.fc3 = tf.keras.layers.Dense(self.filters, activation=None) super(Cond0SignalConv2D, self).build(input_shape) def call(self, inputs, lmbda): wx = super(Cond0SignalConv2D, self).call(inputs) oh = self.fc1(tf.reshape(lmbda, [1,1])) s = self.fc2(oh) b = self.fc3(oh) return wx * s + b class DynamicSignalConv2D(tfc.SignalConv2D): def __init__(self, *args, **kwargs): super(DynamicSignalConv2D, self).__init__(*args, **kwargs) self.active_in_filters = None self.active_out_filters = self.filters def build(self, input_shape): # Create a trainable weight variable for this layer. super(DynamicSignalConv2D, self).build(input_shape) self.input_spec = None def call(self, inputs): inputs = tf.convert_to_tensor(inputs) outputs = inputs input_shape = inputs.shape channel_axis = {"channels_first": 1, "channels_last": -1}[self.data_format] self.active_in_filters = input_shape.as_list()[channel_axis] # effects 4 up/down conv methods, and compute_output_shape self._filters = self.active_out_filters # Not for all possible combinations of (`kernel_support`, `corr`, # `strides_up`, `strides_down`) TF ops exist. We implement some additional # combinations by manipulating the kernels and toggling `corr`. kernel = self.kernel corr = self.corr # If a convolution with no upsampling is desired, we flip the kernels and # use cross correlation to implement it, provided the kernels are odd-length # in every dimension (with even-length kernels, the boundary handling # would have to change). if (not corr and all(s == 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = True slices = self._rank * (slice(None, None, -1),) + (slice(0, self.active_in_filters), slice(0, self.active_out_filters)) kernel = kernel[slices] # Similarly, we can implement a cross correlation using convolutions. # However, we do this only if upsampling is requested, as we are potentially # wasting computation in the boundaries whenever we call the transpose ops. elif (corr and any(s != 1 for s in self.strides_up) and all(s % 2 == 1 for s in self.kernel_support)): corr = False slices = self._rank * (slice(None, None, -1),) + (slice(0, self.active_in_filters), slice(0, self.active_out_filters)) kernel = kernel[slices] else: slices = self._rank * (slice(None),) + (slice(0, self.active_in_filters), slice(0, self.active_out_filters)) kernel = kernel[slices] # Compute amount of necessary padding, and determine whether to use built-in # padding or to pre-pad with a separate op. if self.padding == "valid": padding = prepadding = self._rank * ((0, 0),) else: # same_* padding = padding_ops.same_padding_for_kernel( self.kernel_support, corr, self.strides_up) if (self.padding == "same_zeros" and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): # Don't pre-pad and use built-in EXPLICIT mode. prepadding = self._rank * ((0, 0),) else: # Pre-pad and then use built-in valid padding mode. outputs = tf.pad( outputs, self._padded_tuple(padding, (0, 0)), self._pad_mode) prepadding = padding padding = self._rank * ((0, 0),) # Compute the convolution/correlation. Prefer EXPLICIT padding ops where # possible, but don't use them to implement VALID padding. if (corr and all(s == 1 for s in self.strides_up) and not self.channel_separable and 1 <= self._rank <= 2 and not all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_explicit(outputs, kernel, padding) elif (corr and all(s == 1 for s in self.strides_up) and all(p[0] == p[1] == 0 for p in padding)): outputs = self._correlate_down_valid(outputs, kernel) elif (not corr and not self.channel_separable and 1 <= self._rank <= 2 and self.use_explicit): outputs = self._up_convolve_transpose_explicit( outputs, kernel, prepadding) elif not corr: outputs = self._up_convolve_transpose_valid( outputs, kernel, prepadding) else: self._raise_notimplemented() # Now, add bias if requested. if self.use_bias: bias = self.bias[slice(0,self.active_out_filters)] if self.data_format == "channels_first": # As of Mar 2017, direct addition is significantly slower than # bias_add when computing gradients. if self._rank == 1: # tf.nn.bias_add does not accept a 1D input tensor. outputs = tf.expand_dims(outputs, 2) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.squeeze(outputs, [2]) elif self._rank == 2: outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") elif self._rank >= 3: shape = tf.shape(outputs) outputs = tf.reshape( outputs, tf.concat([shape[:3], [-1]], axis=0)) outputs = tf.nn.bias_add(outputs, bias, data_format="NCHW") outputs = tf.reshape(outputs, shape) else: outputs = tf.nn.bias_add(outputs, bias) # Finally, pass through activation function if requested. if self.activation is not None: outputs = self.activation(outputs) # pylint:disable=not-callable # Aid shape inference, for some reason shape info is not always available. if not tf.executing_eagerly(): outputs.set_shape(self.compute_output_shape(inputs.shape)) return outputs def compute_output_shape(self, input_shape): input_shape = tf.TensorShape(input_shape) input_shape = input_shape.with_rank(self._rank + 2) batch = input_shape[0] if self.data_format == "channels_first": spatial = input_shape[2:].dims channels = input_shape[1] else: spatial = input_shape[1:-1].dims channels = input_shape[-1] for i, s in enumerate(spatial): if self.extra_pad_end: s *= self.strides_up[i] else: s = (s - 1) * self.strides_up[i] + 1 if self.padding == "valid": s -= self.kernel_support[i] - 1 s = (s - 1) // self.strides_down[i] + 1 spatial[i] = s if self.channel_separable: channels *= self.active_out_filters else: channels = self.active_out_filters if self.data_format == "channels_first": return tf.TensorShape([batch, channels] + spatial) else: return tf.TensorShape([batch] + spatial + [channels]) def sort_filter(self, sess, vst, sort_in=True, sort_out=True): # sort_in: idx/False # sort_out: idx/True/False # sort in_channel by input idx from input layer weights = self.weights update_ops = [] var_kernel = vst[weights[0].name] kernel = sess.run(var_kernel).reshape(self.kernel.shape) # to array, in case of rdft if sort_in is not False: kernel = kernel[:,:,sort_in,:] # axis=2 # sort out_channel by calulate L1 norm sorted_idx = None if sort_out is not False: if sort_out is True: importance = np.sum(np.abs(kernel), axis=(0,1,2)) importance[self.active_out_filters:] = np.arange(0, self.active_out_filters-kernel.shape[3], -1) sorted_idx = np.argsort(-importance) # descending else: sorted_idx = sort_out kernel = kernel[:,:,:,sorted_idx] # axis=3 if self.use_bias: var_bias = vst[weights[1].name] # variable op_bias = tf.assign(var_bias, tf.gather(var_bias, sorted_idx, axis=0)) update_ops.append(op_bias) if isinstance(self.activation, DynamicGDN): var_beta = vst[weights[2].name] var_gamma = vst[weights[3].name] op_beta = tf.assign(var_beta, tf.gather(var_beta, sorted_idx, axis=0)) op_gamma = tf.assign(var_gamma, tf.gather(tf.gather(var_gamma, sorted_idx, axis=0), sorted_idx, axis=1)) update_ops.extend([op_beta, op_gamma]) op_kernel = tf.assign(var_kernel, kernel.reshape(weights[0].shape)) update_ops.append(op_kernel) sess.run(update_ops) print(sorted_idx) return sorted_idx def sort_filter_graph(self, sort_in=True, sort_out=True): # set weights version of sort_filter, no graph # sort_in: idx/False # sort_out: idx/True/False # sort in_channel by input idx from input layer if sort_in is not False: self._kernel = tf.gather(self._kernel, sort_in, axis=2) # sort out_channel by calulate L1 norm sorted_idx = None if sort_out is not False: if sort_out is True: importance = tf.reduce_sum(tf.abs(self.kernel), axis=[0,1,2]) endpoint = self.kernel.shape.as_list()[3]-self.active_out_filters if endpoint > 0: protect = tf.range(0, -endpoint, -1.0) importance = tf.concat([importance[:self.active_out_filters], protect], axis=0) sorted_idx = tf.argsort(importance, direction='DESCENDING') else: sorted_idx = sort_out self._kernel = tf.gather(self._kernel, sorted_idx, axis=3) if self.use_bias: self._bias = tf.gather(self._bias, sorted_idx, axis=0) if isinstance(self.activation, DynamicGDN): self.activation.sort_weight_graph(sorted_idx) return sorted_idx class DynamicEntropyBottleneck(tfc.EntropyBottleneck): def __init__(self, *args, **kwargs): super(DynamicEntropyBottleneck, self).__init__(*args, **kwargs) self.active_out_filters = None def build(self, input_shape): # Create a trainable weight variable for this layer. super(DynamicEntropyBottleneck, self).build(input_shape) def _logits_cumulative(self, inputs, stop_gradient): logits = inputs _, _, channels, _ = self._get_input_dims() self.active_out_filters = channels slices = (slice(0, self.active_out_filters), slice(None), slice(None)) for i in range(len(self.filters) + 1): matrix = self._matrices[i][slices] if stop_gradient: matrix = tf.stop_gradient(matrix) logits = tf.linalg.matmul(matrix, logits) bias = self._biases[i][slices] if stop_gradient: bias = tf.stop_gradient(bias) logits += bias if i < len(self._factors): factor = self._factors[i][slices] if stop_gradient: factor = tf.stop_gradient(factor) logits += factor * tf.math.tanh(logits) return logits def _quantize(self, inputs, mode): # Add noise or quantize (and optionally dequantize in one step). half = tf.constant(.5, dtype=self.dtype) _, _, channels, input_slices = self._get_input_dims() self.active_out_filters = channels if mode == "noise": noise = tf.random.uniform(tf.shape(inputs), -half, half) return tf.math.add_n([inputs, noise]) medians = self._medians[:self.active_out_filters] medians = medians[input_slices] outputs = tf.math.floor(inputs + (half - medians)) if mode == "dequantize": outputs = tf.cast(outputs, self.dtype) return outputs + medians else: assert mode == "symbols", mode outputs = tf.cast(outputs, tf.int32) return outputs def _dequantize(self, inputs, mode): _, _, _, input_slices = self._get_input_dims() medians = self._medians[:self.active_out_filters] medians = medians[input_slices] outputs = tf.cast(inputs, self.dtype) return outputs + medians def compress(self, inputs): with tf.name_scope(self._name_scope()): inputs = tf.convert_to_tensor(inputs, dtype=self.dtype) if not self.built: # Check input assumptions set before layer building, e.g. input rank. input_spec.assert_input_compatibility( self.input_spec, inputs, self.name) if self.dtype is None: self._dtype = inputs.dtype.base_dtype.name self.build(inputs.shape) # Check input assumptions set after layer building, e.g. input shape. if not tf.executing_eagerly(): input_spec.assert_input_compatibility( self.input_spec, inputs, self.name) if inputs.dtype.is_integer: raise ValueError( "{} can't take integer inputs.".format(type(self).__name__)) symbols = self._quantize(inputs, "symbols") assert symbols.dtype == tf.int32 ndim = self.input_spec.ndim indexes = self._prepare_indexes(shape=tf.shape(symbols)[1:]) broadcast_indexes = (indexes.shape.ndims != ndim) if broadcast_indexes: # We can't currently broadcast over anything else but the batch axis. assert indexes.shape.ndims == ndim - 1 args = (symbols,) else: args = (symbols, indexes) def loop_body(args): string = range_coding_ops.unbounded_index_range_encode( args[0], indexes if broadcast_indexes else args[1], self._quantized_cdf[:self.active_out_filters,:], self._cdf_length[:self.active_out_filters], self._offset[:self.active_out_filters], precision=self.range_coder_precision, overflow_width=4, debug_level=0) return string strings = tf.map_fn( loop_body, args, dtype=tf.string, back_prop=False, name="compress") if not tf.executing_eagerly(): strings.set_shape(inputs.shape[:1]) return strings def sort_weight(self, sess, vst, sorted_idx): weights = self.weights update_ops = [] for i in range(len(weights)): var_weight = vst[weights[i].name] op_weight = tf.assign(var_weight, tf.gather(var_weight, sorted_idx, axis=0)) update_ops.append(op_weight) # matrix,bias,factor,11, quantiles,quantized_cdf,cdf_length sess.run(update_ops) def sort_weight_graph(self, sorted_idx): self._medians = tf.gather(self._medians, sorted_idx, axis=0) self._quantized_cdf = tf.gather(self._quantized_cdf, sorted_idx, axis=0) self._cdf_length = tf.gather(self._cdf_length, sorted_idx, axis=0) self._offset = tf.gather(self._offset, sorted_idx, axis=0) for i in range(len(self.filters) + 1): self._matrices[i] = tf.gather(self._matrices[i], sorted_idx, axis=0) self._biases[i] = tf.gather(self._biases[i], sorted_idx, axis=0) if i < len(self._factors): self._factors[i] = tf.gather(self._factors[i], sorted_idx, axis=0) class DynamicGaussianConditional(tfc.GaussianConditional): def __init__(self, *args, **kwargs): super(DynamicGaussianConditional, self).__init__(*args, **kwargs) self.active_out_filters = None def build(self, input_shape): # Create a trainable weight variable for this layer. super(DynamicGaussianConditional, self).build(input_shape) def compress(self, inputs): with tf.name_scope(self._name_scope()): inputs = tf.convert_to_tensor(inputs, dtype=self.dtype) if not self.built: # Check input assumptions set before layer building, e.g. input rank. input_spec.assert_input_compatibility( self.input_spec, inputs, self.name) if self.dtype is None: self._dtype = inputs.dtype.base_dtype.name self.build(inputs.shape) # Check input assumptions set after layer building, e.g. input shape. if not tf.executing_eagerly(): input_spec.assert_input_compatibility( self.input_spec, inputs, self.name) if inputs.dtype.is_integer: raise ValueError( "{} can't take integer inputs.".format(type(self).__name__)) symbols = self._quantize(inputs, "symbols") assert symbols.dtype == tf.int32 ndim = self.input_spec.ndim indexes = self._prepare_indexes(shape=tf.shape(symbols)[1:]) broadcast_indexes = (indexes.shape.ndims != ndim) if broadcast_indexes: # We can't currently broadcast over anything else but the batch axis. assert indexes.shape.ndims == ndim - 1 args = (symbols,) else: args = (symbols, indexes) def loop_body(args): string = range_coding_ops.unbounded_index_range_encode( args[0], indexes if broadcast_indexes else args[1], self._quantized_cdf, self._cdf_length, self._offset, precision=self.range_coder_precision, overflow_width=4, debug_level=0) return string #print(symbols, indexes, self._quantized_cdf, self._cdf_length, self._offset) strings = tf.map_fn( loop_body, args, dtype=tf.string, back_prop=False, name="compress") if not tf.executing_eagerly(): strings.set_shape(inputs.shape[:1]) return strings def sort_weight(self, sorted_idx): pass class DynamicGDN(tfc.GDN): def __init__(self, *args, **kwargs): super(DynamicGDN, self).__init__(*args, **kwargs) self.active_out = None def build(self, input_shape): # Create a trainable weight variable for this layer. super(DynamicGDN, self).build(input_shape) self.input_spec = None def call(self, inputs): inputs = tf.convert_to_tensor(inputs, dtype=self.dtype) ndim = self._input_rank self.active_out = tf.shape(inputs)[-1] gamma = self.gamma[(slice(0,self.active_out), slice(0, self.active_out))] beta = self.beta[slice(0, self.active_out)] if self.rectify: inputs = tf.nn.relu(inputs) # Compute normalization pool. if ndim == 2: norm_pool = tf.linalg.matmul(tf.math.square(inputs), gamma) norm_pool = tf.nn.bias_add(norm_pool, beta) elif self.data_format == "channels_last" and ndim <= 4: # TODO(unassigned): This branch should also work for ndim == 5, but # currently triggers a bug in TF. #shape = gamma.shape.as_list() shape = tf.shape(gamma) gamma = tf.reshape(gamma, [1,1, shape[0], shape[1]]) norm_pool = tf.nn.convolution(tf.math.square(inputs), gamma, "VALID") norm_pool = tf.nn.bias_add(norm_pool, beta) else: # generic implementation # This puts channels in the last dimension regardless of input. norm_pool = tf.linalg.tensordot( tf.math.square(inputs), gamma, [[self._channel_axis()], [0]]) norm_pool += beta if self.data_format == "channels_first": # Return to channels_first format if necessary. axes = list(range(ndim - 1)) axes.insert(1, ndim - 1) norm_pool = tf.transpose(norm_pool, axes) if self.inverse: norm_pool = tf.math.sqrt(norm_pool) else: norm_pool = tf.math.rsqrt(norm_pool) outputs = inputs * norm_pool if not tf.executing_eagerly(): outputs.set_shape(self.compute_output_shape(inputs.shape)) return outputs def compute_output_shape(self, input_shape): return tf.TensorShape(input_shape) def sort_weight_graph(self, sorted_idx): self.beta = tf.gather(self.beta, sorted_idx, axis=0) self.gamma = tf.gather(tf.gather(self.gamma, sorted_idx, axis=0), sorted_idx, axis=1)

39.580216

124

0.653513

6,586

47,615

4.556483

0.069693

0.018394

0.014729

0.008664

0.845813

0.808491

0.785064

0.764271

0.735013

0.724483

0

0.013369

0.236522

47,615

1,202

125

39.613145

0.81212

0.192355

0

0.748292

0

0.015885

0

0.000832

0.010251

1

0.055809

false

0.002278

0.015945

0.001139

0.115034

0.001139

0

null

0

1

0

1

0

null

0

7

45edb3d66ef5ecfec7c7f41ac2610fac2c2635bf

70

py

Python

deps/pyextensibletype/extensibletype/test/test_pstdint.py

liuzhenhai/numba

855a2b262ae3d82bd6ac1c3e1c0acb36ee2e2acf

[ "BSD-2-Clause" ]

1

2015-01-29T06:52:36.000Z

deps/pyextensibletype/extensibletype/test/test_pstdint.py

shiquanwang/numba

a41c85fdd7d6abf8ea1ebe9116939ddc2217193b

[ "BSD-2-Clause" ]

null

deps/pyextensibletype/extensibletype/test/test_pstdint.py

shiquanwang/numba

a41c85fdd7d6abf8ea1ebe9116939ddc2217193b

[ "BSD-2-Clause" ]

null

from . import pstdint def test_pstdint(): pstdint.test_pstdint()

14

26

0.728571

9

70

5.444444

0.555556

0.44898

0

0.171429

70

4

27

17.5

0.844828

0

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

caa9ba8efc80e4c2e5c7fd862617bbf16eb1dbdb

4,303

py

Python

ade25/contacts/browser/contact.py

ade25/ade25.contacts

60cb741e4c67e3ed059dacd3f2b0c5b2ced1dde2

[ "MIT" ]

null

ade25/contacts/browser/contact.py

ade25/ade25.contacts

60cb741e4c67e3ed059dacd3f2b0c5b2ced1dde2

[ "MIT" ]

null

ade25/contacts/browser/contact.py

ade25/ade25.contacts

60cb741e4c67e3ed059dacd3f2b0c5b2ced1dde2

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Module providing views for contact page type""" from Acquisition import aq_inner from Products.Five.browser import BrowserView from plone import api from zope.component import getUtility from ade25.contacts.interfaces import IContactImagesTool class ContactView(BrowserView): """ Folderish contact item default view """ def has_image(self): context = aq_inner(self.context) try: lead_img = context.image except AttributeError: lead_img = None if lead_img is not None: return True return False def has_address_info(self): context = aq_inner(self.context) if context.address or context.city: return True return False def has_position_info(self): context = aq_inner(self.context) if context.position or context.department: return True return False def get_image_data(self, uuid): tool = getUtility(IContactImagesTool) return tool.create(uuid) def render_contact_card(self): context = aq_inner(self.context) template = context.restrictedTraverse('@@contact-card-view')() return template class ContactCardView(BrowserView): """ Card view for contact objects """ def __call__(self, **kw): self.params = {} self.params.update(kw) return self.render() def render(self): return self.index() def has_image(self): context = aq_inner(self.context) try: lead_img = context.image except AttributeError: lead_img = None if lead_img is not None: return True return False def has_address_info(self): context = aq_inner(self.context) if context.address or context.city: return True return False def has_position_info(self): context = aq_inner(self.context) if context.position or context.department: return True return False def get_image_data(self, uuid): tool = getUtility(IContactImagesTool) return tool.create(uuid) def get_inquiry_form_link(self): context = aq_inner(self.context) assignment_context_uid = self.params.get('uuid', None) if assignment_context_uid: assignment_context = api.content.get(UID=assignment_context_uid) uri = '{0}/@@inquiry-form/{1}'.format( assignment_context.absolute_url(), context.UID() ) else: uri = '{0}/@@inquiry-form/{1}'.format( context.absolute_url(), context.UID() ) return uri class ContactElementView(BrowserView): """ Contact object element view usable below content main viewlet """ def __call__(self, **kw): self.params = {} self.params.update(kw) return self.render() def render(self): return self.index() def has_image(self): context = aq_inner(self.context) try: lead_img = context.image except AttributeError: lead_img = None if lead_img is not None: return True return False def has_address_info(self): context = aq_inner(self.context) if context.address or context.city: return True return False def has_position_info(self): context = aq_inner(self.context) if context.position or context.department: return True return False def get_image_data(self, uuid): tool = getUtility(IContactImagesTool) return tool.create(uuid) def get_inquiry_form_link(self): context = aq_inner(self.context) assignment_context_uid = self.params.get('uuid', None) if assignment_context_uid: assignment_context = api.content.get(UID=assignment_context_uid) uri = '{0}/@@inquiry-form/{1}'.format( assignment_context.absolute_url(), context.UID() ) else: uri = '{0}/@@inquiry-form/{1}'.format( context.absolute_url(), context.UID() ) return uri

28.309211

76

0.599117

482

4,303

5.184647

0.192946

0.105642

0.062425

0.086435

0.80072

0.789116

0

0.003725

0.313735

4,303

151

77

28.496689

0.842533

0.046014

0

0.875

0

0.028179

0.021563

0

1

0.158333

false

0

0.041667

0.016667

0.458333

0

null

0

1

0

1

0

null

0

7

1b0de86645d4cd051d09693d94960bddfd538eb9

4,066

py

Python

src/niweb/apps/noclook/tests/test_detail_ipaddr.py

emjemj/ni

a78e6d97d1e4610aad7698c4f0f459221c680b4f

[ "BSD-2-Clause-FreeBSD" ]

2

2018-12-21T09:35:27.000Z

2019-07-31T18:51:58.000Z

src/niweb/apps/noclook/tests/test_detail_ipaddr.py

emjemj/ni

a78e6d97d1e4610aad7698c4f0f459221c680b4f

[ "BSD-2-Clause-FreeBSD" ]

6

2019-07-25T07:10:23.000Z

2021-02-08T09:58:57.000Z

src/niweb/apps/noclook/tests/test_detail_ipaddr.py

emjemj/ni

a78e6d97d1e4610aad7698c4f0f459221c680b4f

[ "BSD-2-Clause-FreeBSD" ]

5

2019-02-06T12:00:26.000Z

2021-11-19T14:48:06.000Z

from .neo4j_base import NeoTestCase from django.urls import reverse class PeeringGroupDetailTest(NeoTestCase): def test_peering_group_detail(self): # Minimal unit = self.create_node('Unit1', 'unit', 'Logical') peering_group = self.create_node('TESTIX', 'peering-group', 'Logical') peering_partner = self.create_node('Awesome Co', 'peering-partner', 'Relation') group_node = peering_group.get_node() group_node.set_group_dependency(unit.handle_id, '172.16.0.0/12') group_node.set_group_dependency(unit.handle_id, 'fd00::/8') partner_node = peering_partner.get_node() partner_node.set_peering_group(peering_group.handle_id, '172.17.0.13') partner_node.set_peering_group(peering_group.handle_id, 'fd17:1234:abcd:1::1') resp = self.client.get(reverse('peering_group_detail', args=[peering_group.handle_id])) self.assertContains(resp, peering_group.node_name) self.assertContains(resp, peering_partner.node_name) self.assertContains(resp, unit.node_name) self.assertContains(resp, '172.16.0.0/12') self.assertContains(resp, '172.17.0.13') self.assertContains(resp, 'fd00::/8') self.assertContains(resp, 'fd17:1234:abcd:1::1') def test_peering_group_detail_dangling_network(self): unit = self.create_node('Unit1', 'unit', 'Logical') peering_group = self.create_node('TESTIX', 'peering-group', 'Logical') peering_partner = self.create_node('Awesome Co', 'peering-partner', 'Relation') # Add dependencies on unit with networks group_node = peering_group.get_node() group_node.set_group_dependency(unit.handle_id, '172.16.0.0/12') group_node.set_group_dependency(unit.handle_id, 'fd00::/8') # Set peering group for partner partner_node = peering_partner.get_node() partner_node.set_peering_group(peering_group.handle_id, '192.168.0.13') partner_node.set_peering_group(peering_group.handle_id, 'cd17:1234:abcd:1::1') resp = self.client.get(reverse('peering_group_detail', args=[peering_group.handle_id])) self.assertContains(resp, '172.16.0.0/12') self.assertContains(resp, 'fd00::/8') self.assertNotContains(resp, '192.168.0.13') self.assertNotContains(resp, 'cd17:1234:abcd:1::1') class PeeringPartnerDetailTest(NeoTestCase): def test_peering_partner_detail(self): router = self.create_node('route1.test.dev', 'router') port = self.create_node('ae0', 'port') unit = self.create_node('Unit1', 'unit', 'Logical') peering_group = self.create_node('TESTIX', 'peering-group', 'Logical') peering_partner = self.create_node('Awesome Co', 'peering-partner', 'Relation') # Router-[:Has]->(port)<-[:Part_of]-(unit) router.get_node().set_has(port.handle_id) port.get_node().set_part_of(unit.handle_id) # Add dependencies on unit with networks group_node = peering_group.get_node() group_node.set_group_dependency(unit.handle_id, '172.16.0.0/12') group_node.set_group_dependency(unit.handle_id, 'fd00::/8') # Set peering group for partner partner_node = peering_partner.get_node() partner_node.set_peering_group(peering_group.handle_id, '172.17.0.13') partner_node.set_peering_group(peering_group.handle_id, 'fd17:1234:abcd:1::1') resp = self.client.get(reverse('peering_partner_detail', args=[peering_partner.handle_id])) self.assertContains(resp, peering_partner.node_name) self.assertContains(resp, peering_group.node_name) self.assertContains(resp, unit.node_name) self.assertContains(resp, port.node_name) self.assertContains(resp, router.node_name) self.assertContains(resp, unit.node_name) self.assertContains(resp, '172.16.0.0/12') self.assertContains(resp, '172.17.0.13') self.assertContains(resp, 'fd00::/8') self.assertContains(resp, 'fd17:1234:abcd:1::1')

46.735632

99

0.689129

541

4,066

4.931608

0.12939

0.13943

0.156672

0.087706

0.832084

0.795352

0.788981

0

0.0526

0.177078

4,066

86

100

47.27907

0.74477

0.045745

0

0.709677

0

0.160857

0.00568

0

0.33871

1

0.048387

false

0

0.032258

0

0.112903

0

null

0

1

0

1

0

null

0

7

1b542fb5448d0fc0c6755f585cd19fe8733eb765

92,202

py

Python

src/pyrad_proc/pyrad/proc/process_calib.py

jfigui/pyrad

7811d593bb09a7f8a621c0e8ae3f32c2b85a0254

[ "BSD-3-Clause" ]

41

2016-12-01T08:46:06.000Z

2021-06-24T21:14:33.000Z

src/pyrad_proc/pyrad/proc/process_calib.py

jfigui/pyrad

7811d593bb09a7f8a621c0e8ae3f32c2b85a0254

[ "BSD-3-Clause" ]

42

2017-02-23T14:52:49.000Z

2021-02-01T10:43:52.000Z

src/pyrad_proc/pyrad/proc/process_calib.py

jfigui/pyrad

7811d593bb09a7f8a621c0e8ae3f32c2b85a0254

[ "BSD-3-Clause" ]

21

2016-08-25T15:02:12.000Z

2021-05-27T04:09:40.000Z

""" pyrad.proc.process_calib =========================== Functions for monitoring data quality and correct bias and noise effects .. autosummary:: :toctree: generated/ process_correct_bias process_correct_noise_rhohv process_gc_monitoring process_occurrence process_time_avg_std process_occurrence_period process_sun_hits *process_sunscan """ from copy import deepcopy from warnings import warn import numpy as np import sys from scipy.constants import c as c_speed from netCDF4 import num2date from datetime import datetime as dt try: import pysolar _PYSOLAR_AVAILABLE = True except ImportError: _PYSOLAR_AVAILABLE = False import pyart from ..io.io_aux import get_datatype_fields, get_fieldname_pyart from ..io.read_data_sun import read_sun_hits_multiple_days, read_solar_flux from ..io.read_data_other import read_excess_gates from ..io.read_data_radar import interpol_field from ..util.radar_utils import get_closest_solar_flux, get_histogram_bins from ..util.radar_utils import find_ray_index, find_rng_index def process_correct_bias(procstatus, dscfg, radar_list=None): """ Corrects a bias on the data Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: datatype : string. Dataset keyword The data type to correct for bias bias : float. Dataset keyword The bias to be corrected [dB]. Default 0 radar_list : list of Radar objects Optional. list of radar objects Returns ------- new_dataset : dict dictionary containing the output ind_rad : int radar index """ if procstatus != 1: return None, None for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) break field_name = get_fieldname_pyart(datatype) ind_rad = int(radarnr[5:8])-1 if radar_list[ind_rad] is None: warn('No valid radar') return None, None radar = radar_list[ind_rad] if field_name not in radar.fields: warn('Unable to correct for bias field ' + field_name + '. Field not available') return None, None bias = dscfg.get('bias', 0.) corrected_field = pyart.correct.correct_bias( radar, bias=bias, field_name=field_name) if field_name.startswith('corrected_'): new_field_name = field_name else: new_field_name = 'corrected_'+field_name # prepare for exit new_dataset = {'radar_out': deepcopy(radar)} new_dataset['radar_out'].fields = dict() new_dataset['radar_out'].add_field(new_field_name, corrected_field) return new_dataset, ind_rad def process_correct_noise_rhohv(procstatus, dscfg, radar_list=None): """ identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Precipitation Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: datatype : list of string. Dataset keyword The data types used in the correction radar_list : list of Radar objects Optional. list of radar objects Returns ------- new_dataset : dict dictionary containing the output ind_rad : int radar index """ if procstatus != 1: return None, None for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) if datatype == 'uRhoHV': urhohv = 'uncorrected_cross_correlation_ratio' if datatype == 'SNRh': snr = 'signal_to_noise_ratio_hh' if datatype == 'ZDR': zdr = 'differential_reflectivity' if datatype == 'ZDRc': zdr = 'corrected_differential_reflectivity' if datatype == 'Nh': nh = 'noisedBZ_hh' if datatype == 'Nv': nv = 'noisedBZ_vv' ind_rad = int(radarnr[5:8])-1 if radar_list[ind_rad] is None: warn('No valid radar') return None, None radar = radar_list[ind_rad] if ((urhohv not in radar.fields) or (snr not in radar.fields) or (zdr not in radar.fields) or (nh not in radar.fields) or (nv not in radar.fields)): warn('Unable to correct RhoHV field for noise. Missing fields') return None, None rhohv = pyart.correct.correct_noise_rhohv( radar, urhohv_field=urhohv, snr_field=snr, zdr_field=zdr, nh_field=nh, nv_field=nv, rhohv_field='cross_correlation_ratio') # prepare for exit new_dataset = {'radar_out': deepcopy(radar)} new_dataset['radar_out'].fields = dict() new_dataset['radar_out'].add_field('cross_correlation_ratio', rhohv) return new_dataset, ind_rad def process_gc_monitoring(procstatus, dscfg, radar_list=None): """ computes ground clutter monitoring statistics Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: excessgatespath : str. Config keyword The path to the gates in excess of quantile location excessgates_fname : str. Dataset keyword The name of the gates in excess of quantile file datatype : list of string. Dataset keyword The input data types step : float. Dataset keyword The width of the histogram bin. Default is None. In that case the default step in function get_histogram_bins is used regular_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False val_min : Float. Dataset keyword Minimum value to consider that the gate has signal. Default None filter_prec : str. Dataset keyword Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes. rmax_prec : float. Dataset keyword Maximum range to consider when looking for wet gates [m] percent_prec_max : float. Dataset keyword Maxim percentage of wet gates to consider the volume dry radar_list : list of Radar objects Optional. list of radar objects Returns ------- new_dataset : Radar radar object containing histogram data ind_rad : int radar index """ echoid_field = None for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) if datatype == 'echoID': echoid_field = get_fieldname_pyart(datatype) else: field_name = get_fieldname_pyart(datatype) ind_rad = int(radarnr[5:8])-1 if procstatus == 0: savedir = dscfg['excessgatespath'] fname = dscfg['excessgates_fname'] ray_ind, rng_ind, ele, azi, rng, nsamples, occurrence, freq_occu = ( read_excess_gates(savedir+fname)) dscfg['global_data'] = { 'ray_ind': ray_ind, 'rng_ind': rng_ind, 'ele': ele, 'azi': azi, 'rng': rng, 'nsamples': nsamples, 'occurrence': occurrence, 'freq_occu': freq_occu} return None, None if dscfg['global_data']['ray_ind'] is None: warn('Unable to get statistics of clutter') return None, None if procstatus == 1: if radar_list[ind_rad] is None: warn('No valid radar') return None, None radar = deepcopy(radar_list[ind_rad]) if field_name not in radar.fields: warn(field_name+' not available.') return None, None # filter out low values val_min = dscfg.get('val_min', None) mask = np.ma.getmaskarray(radar.fields[field_name]['data']) if val_min is not None: mask = np.logical_or( mask, radar.fields[field_name]['data'] < val_min) field = deepcopy(radar.fields[field_name]['data']) field[mask] = np.ma.masked # filter wet or dry volumes filter_prec = dscfg.get('filter_prec', 'None') if filter_prec in ('keep_wet', 'keep_dry'): if echoid_field not in radar.fields: warn('Unable to determine if there is precipitation ' + 'close to the radar. Missing echoID field.') return None, None # Put invalid values to noise echoid = deepcopy(radar.fields[echoid_field]['data']) echoid[mask] = 1 rmax_prec = dscfg.get('rmax_prec', 0.) percent_prec_max = dscfg.get('percent_prec_max', 10.) ngates = radar.ngates if rmax_prec > 0.: ngates = len( radar.range['data'][radar.range['data'] < rmax_prec]) ngates_total = ngates*radar.nrays prec_field = echoid[:, :ngates] ngates_prec = np.size(prec_field[prec_field == 3]) percent_prec = ngates_prec/ngates_total*100. warn('Percent gates with precipitation: '+str(percent_prec)+'\n') if percent_prec > percent_prec_max: if filter_prec == 'keep_dry': warn('Radar volume is precipitation contaminated.\n' + 'Maximum percentage allowed: '+str(percent_prec_max)) return None, None else: if filter_prec == 'keep_wet': warn('Radar volume has not enough precipitation.\n' + 'Minimum percentage required: ' + str(percent_prec_max)) return None, None step = dscfg.get('step', None) bin_edges = get_histogram_bins(field_name, step=step) nbins = len(bin_edges)-1 step = bin_edges[1]-bin_edges[0] bin_centers = bin_edges[:-1]+step/2. # create histogram object from radar object radar_aux = deepcopy(radar) radar_aux.fields = dict() radar_aux.range['data'] = bin_centers radar_aux.ngates = nbins radar_aux.nrays = 1 field_dict = pyart.config.get_metadata(field_name) field_dict['data'] = np.ma.zeros((1, nbins), dtype=int) # rays are indexed to regular grid regular_grid = dscfg.get('regular_grid', False) if regular_grid: ray_ind = dscfg['global_data']['ray_ind'] rng_ind = dscfg['global_data']['rng_ind'] field = field[ray_ind, rng_ind].compressed() else: azi_tol = dscfg.get('azi_tol', 0.5) ele_tol = dscfg.get('ele_tol', 0.5) rng_tol = dscfg.get('rng_tol', 50.) # get indexes of gates close to target ngc = np.size(dscfg['global_data']['ray_ind']) ray_ind = np.ma.masked_all(ngc, dtype=int) rng_ind = np.ma.masked_all(ngc, dtype=int) for i in range(ngc): ind_ray_rad = find_ray_index( radar.elevation['data'], radar.azimuth['data'], dscfg['global_data']['ele'][i], dscfg['global_data']['azi'][i], ele_tol=ele_tol, azi_tol=azi_tol) if ind_ray_rad is None: continue ind_rng_rad = find_rng_index( radar.range['data'], dscfg['global_data']['rng'][i], rng_tol=rng_tol) if ind_rng_rad is None: continue ray_ind[i] = ind_ray_rad rng_ind[i] = ind_rng_rad ray_ind = ray_ind.compressed() rng_ind = rng_ind.compressed() field = field[ray_ind, rng_ind].compressed() # put gates with values off limits to limit # and compute histogram field[field < bin_centers[0]] = bin_centers[0] field[field > bin_centers[-1]] = bin_centers[-1] field_dict['data'][0, :], bin_edges = np.histogram( field, bins=bin_edges) radar_aux.add_field(field_name, field_dict) start_time = pyart.graph.common.generate_radar_time_begin(radar_aux) # Put histogram in Memory or add to existing histogram if dscfg['initialized'] == 0: dscfg['global_data'].update({ 'hist_obj': radar_aux, 'timeinfo': start_time}) dscfg['initialized'] = 1 else: dscfg['global_data']['hist_obj'].fields[field_name]['data'] += ( field_dict['data'].filled(fill_value=0)).astype('int64') # dscfg['global_data']['timeinfo'] = dscfg['timeinfo'] dataset = dict() dataset.update({'hist_obj': radar_aux}) dataset.update({'hist_type': 'instant'}) dataset.update({'timeinfo': start_time}) return dataset, ind_rad if procstatus == 2: if dscfg['initialized'] == 0: return None, None dataset = dict() dataset.update({'hist_obj': dscfg['global_data']['hist_obj']}) dataset.update({'hist_type': 'cumulative'}) dataset.update({'timeinfo': dscfg['global_data']['timeinfo']}) return dataset, ind_rad def process_occurrence(procstatus, dscfg, radar_list=None): """ computes the frequency of occurrence of data. It looks only for gates where data is present. Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: datatype : list of string. Dataset keyword The input data types regular_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False rmin, rmax : float. Dataset keyword minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1 val_min : Float. Dataset keyword Minimum value to consider that the gate has signal. Default None filter_prec : str. Dataset keyword Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes. rmax_prec : float. Dataset keyword Maximum range to consider when looking for wet gates [m] percent_prec_max : float. Dataset keyword Maxim percentage of wet gates to consider the volume dry radar_list : list of Radar objects Optional. list of radar objects Returns ------- new_dataset : dict dictionary containing the output ind_rad : int radar index """ echoid_field = None for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) if datatype == 'echoID': echoid_field = get_fieldname_pyart(datatype) else: field_name = get_fieldname_pyart(datatype) ind_rad = int(radarnr[5:8])-1 if procstatus == 0: return None, None if procstatus == 1: if radar_list[ind_rad] is None: warn('No valid radar') return None, None radar = radar_list[ind_rad] if field_name not in radar.fields: warn(field_name+' not available.') return None, None # filter out low values val_min = dscfg.get('val_min', None) mask = np.ma.getmaskarray(radar.fields[field_name]['data']) if val_min is not None: mask = np.logical_or( mask, radar.fields[field_name]['data'] < val_min) filter_prec = dscfg.get('filter_prec', 'None') if filter_prec in ('keep_wet', 'keep_dry'): if echoid_field not in radar.fields: warn('Unable to determine if there is precipitation ' + 'close to the radar. Missing echoID field.') return None, None # Put invalid values to noise echoid = deepcopy(radar.fields[echoid_field]['data']) echoid[mask] = 1 rmax_prec = dscfg.get('rmax_prec', 0.) percent_prec_max = dscfg.get('percent_prec_max', 10.) ngates = radar.ngates if rmax_prec > 0.: ngates = len( radar.range['data'][radar.range['data'] < rmax_prec]) ngates_total = ngates*radar.nrays prec_field = echoid[:, :ngates] ngates_prec = np.size(prec_field[prec_field == 3]) percent_prec = ngates_prec/ngates_total*100. warn('Percent gates with precipitation: '+str(percent_prec)+'\n') if percent_prec > percent_prec_max: if filter_prec == 'keep_dry': warn('Radar volume is precipitation contaminated.\n' + 'Maximum percentage allowed: '+str(percent_prec_max)) return None, None else: if filter_prec == 'keep_wet': warn('Radar volume has not enough precipitation.\n' + 'Minimum percentage required: ' + str(percent_prec_max)) return None, None # prepare field number of samples and occurrence radar_aux = deepcopy(radar) radar_aux.fields = dict() npoints_dict = pyart.config.get_metadata('number_of_samples') npoints_dict['data'] = np.ma.ones( (radar.nrays, radar.ngates), dtype=int) radar_aux.add_field('number_of_samples', npoints_dict) occu_dict = pyart.config.get_metadata('occurrence') occu_dict['data'] = np.ma.zeros( (radar.nrays, radar.ngates), dtype=int) occu_dict['data'][np.logical_not(mask)] = 1 # filter out out of range data rmin = dscfg.get('rmin', -1.) rmax = dscfg.get('rmax', -1.) if rmin >= 0.: ind_min = np.where(radar_aux.range['data'] < rmin)[0] if ind_min: ind_min = ind_min[-1] occu_dict['data'][:, 0:ind_min+1] = 0 if rmax >= 0.: ind_max = np.where(radar_aux.range['data'] > rmax)[0] if ind_max: ind_max = ind_max[0] occu_dict['data'][:, ind_max:radar_aux.ngates] = 0 radar_aux.add_field('occurrence', occu_dict) # first volume: initialize radar object if dscfg['initialized'] == 0: new_dataset = { 'radar_out': radar_aux, 'starttime': dscfg['timeinfo'], 'endtime': dscfg['timeinfo'], 'occu_final': False} dscfg['global_data'] = new_dataset dscfg['initialized'] = 1 return new_dataset, ind_rad # accumulate data regular_grid = False if 'regular_grid' in dscfg: regular_grid = dscfg['regular_grid'] if not regular_grid: occu_interp = interpol_field( dscfg['global_data']['radar_out'], radar_aux, 'occurrence') npoints_interp = interpol_field( dscfg['global_data']['radar_out'], radar_aux, 'number_of_samples') else: if radar_aux.nrays != dscfg['global_data']['radar_out'].nrays: warn('Unable to accumulate radar object. ' + 'Number of rays of current radar different from ' + 'reference. nrays current: '+str(radar_aux.nrays) + ' nrays ref: ' + str(dscfg['global_data']['radar_out'].nrays)) return None, None occu_interp = radar_aux.fields['occurrence'] npoints_interp = radar_aux.fields['number_of_samples'] dscfg['global_data']['radar_out'].fields['occurrence']['data'] += ( np.ma.asarray( occu_interp['data'].filled(fill_value=0)).astype('int')) dscfg['global_data']['radar_out'].fields['number_of_samples'][ 'data'] += (np.ma.asarray( npoints_interp['data'].filled(fill_value=0)).astype('int')) dscfg['global_data']['endtime'] = dscfg['timeinfo'] new_dataset = { 'radar_out': dscfg['global_data']['radar_out'], 'starttime': dscfg['global_data']['starttime'], 'endtime': dscfg['global_data']['endtime'], 'occu_final': False} return new_dataset, ind_rad # no more files to process. Compute frequency of occurrence if procstatus == 2: if dscfg['initialized'] == 0: return None, None if 'radar_out' not in dscfg['global_data']: return None, None radar = dscfg['global_data']['radar_out'] freq_occu_dict = pyart.config.get_metadata('frequency_of_occurrence') freq_occu_dict['data'] = (100.*radar.fields['occurrence']['data'] / radar.fields['number_of_samples']['data']) radar.add_field('frequency_of_occurrence', freq_occu_dict) new_dataset = { 'radar_out': dscfg['global_data']['radar_out'], 'starttime': dscfg['global_data']['starttime'], 'endtime': dscfg['global_data']['endtime'], 'occu_final': True} return new_dataset, ind_rad def process_time_avg_std(procstatus, dscfg, radar_list=None): """ computes the average and standard deviation of data. It looks only for gates where data is present. Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: datatype : list of string. Dataset keyword The input data types regular_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False rmin, rmax : float. Dataset keyword minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1 val_min : Float. Dataset keyword Minimum reflectivity value to consider that the gate has signal. Default None filter_prec : str. Dataset keyword Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes. rmax_prec : float. Dataset keyword Maximum range to consider when looking for wet gates [m] percent_prec_max : float. Dataset keyword Maxim percentage of wet gates to consider the volume dry lin_trans : Boolean. Dataset keyword If True the data will be transformed into linear units. Default False radar_list : list of Radar objects Optional. list of radar objects Returns ------- new_dataset : dict dictionary containing the output ind_rad : int radar index """ echoid_field = None refl_field = None for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) if datatype == 'echoID': echoid_field = get_fieldname_pyart(datatype) elif (datatype in ('dBZ', 'dBZc', 'dBZv', 'dBZvc', 'dBuZ', 'dBuZc') and refl_field is None): refl_field = get_fieldname_pyart(datatype) else: field_name = get_fieldname_pyart(datatype) ind_rad = int(radarnr[5:8])-1 lin_trans = dscfg.get('lin_trans', 0) if procstatus == 0: return None, None if procstatus == 1: if radar_list[ind_rad] is None: warn('No valid radar') return None, None radar = radar_list[ind_rad] if field_name not in radar.fields: warn(field_name+' not available.') return None, None # filter out low reflectivity values val_min = dscfg.get('val_min', None) mask = np.ma.getmaskarray(radar.fields[field_name]['data']) if val_min is not None and refl_field is not None: mask = np.logical_or( mask, radar.fields[refl_field]['data'] < val_min) filter_prec = dscfg.get('filter_prec', 'None') if filter_prec in ('keep_wet', 'keep_dry'): if echoid_field not in radar.fields: warn('Unable to determine if there is precipitation ' + 'close to the radar. Missing echoID field.') return None, None # Put invalid values to noise echoid = deepcopy(radar.fields[echoid_field]['data']) echoid[mask] = 1 rmax_prec = dscfg.get('rmax_prec', 0.) percent_prec_max = dscfg.get('percent_prec_max', 10.) ngates = radar.ngates if rmax_prec > 0.: ngates = len( radar.range['data'][radar.range['data'] < rmax_prec]) ngates_total = ngates*radar.nrays prec_field = echoid[:, :ngates] ngates_prec = np.size(prec_field[prec_field == 3]) percent_prec = ngates_prec/ngates_total*100. warn('Percent gates with precipitation: '+str(percent_prec)+'\n') if percent_prec > percent_prec_max: if filter_prec == 'keep_dry': warn('Radar volume is precipitation contaminated.\n' + 'Maximum percentage allowed: '+str(percent_prec_max)) return None, None else: if filter_prec == 'keep_wet': warn('Radar volume has not enough precipitation.\n' + 'Minimum percentage required: ' + str(percent_prec_max)) return None, None # filter out out of range data rmin = dscfg.get('rmin', -1.) rmax = dscfg.get('rmax', -1.) if rmin >= 0.: ind_min = np.where(radar.range['data'] < rmin)[0] if ind_min: ind_min = ind_min[-1] mask[:, 0:ind_min+1] = 1 if rmax >= 0.: ind_max = np.where(radar.range['data'] > rmax)[0] if ind_max: ind_max = ind_max[0] mask[:, ind_max:radar.ngates] = 1 # prepare field number of samples and values sum field = deepcopy(radar.fields[field_name]['data']) if lin_trans: field = np.ma.power(10., 0.1*field) field = np.ma.masked_where(mask, field) field = np.ma.asarray(field) radar_aux = deepcopy(radar) radar_aux.fields = dict() sum_dict = pyart.config.get_metadata('sum') sum_dict['data'] = field radar_aux.add_field('sum', sum_dict) sum2_dict = pyart.config.get_metadata('sum_squared') sum2_dict['data'] = field*field radar_aux.add_field('sum_squared', sum2_dict) npoints_dict = pyart.config.get_metadata('number_of_samples') npoints_dict['data'] = np.ma.asarray(np.logical_not(mask), dtype=int) radar_aux.add_field('number_of_samples', npoints_dict) # first volume: initialize radar object if dscfg['initialized'] == 0: new_dataset = { 'radar_out': radar_aux, 'starttime': dscfg['timeinfo'], 'endtime': dscfg['timeinfo'], 'occu_final': False} dscfg['global_data'] = new_dataset dscfg['initialized'] = 1 return new_dataset, ind_rad # accumulate data regular_grid = False if 'regular_grid' in dscfg: regular_grid = dscfg['regular_grid'] if not regular_grid: sum_interp = interpol_field( dscfg['global_data']['radar_out'], radar_aux, 'sum') sum2_interp = interpol_field( dscfg['global_data']['radar_out'], radar_aux, 'sum_squared') npoints_interp = interpol_field( dscfg['global_data']['radar_out'], radar_aux, 'number_of_samples') else: if radar_aux.nrays != dscfg['global_data']['radar_out'].nrays: warn('Unable to accumulate radar object. ' + 'Number of rays of current radar different from ' + 'reference. nrays current: '+str(radar_aux.nrays) + ' nrays ref: ' + str(dscfg['global_data']['radar_out'].nrays)) return None, None sum_interp = radar_aux.fields['sum'] sum2_interp = radar_aux.fields['sum_squared'] npoints_interp = radar_aux.fields['number_of_samples'] valid = np.logical_not(np.ma.getmaskarray(sum_interp)) dscfg['global_data']['radar_out'].fields['sum']['data'][valid] += ( np.ma.asarray(sum_interp['data'][valid])) dscfg['global_data']['radar_out'].fields['sum_squared'][ 'data'][valid] += np.ma.asarray(sum2_interp['data'][valid]) dscfg['global_data']['radar_out'].fields['number_of_samples'][ 'data'][valid] += np.ma.asarray(npoints_interp['data'][valid]) dscfg['global_data']['endtime'] = dscfg['timeinfo'] new_dataset = { 'radar_out': dscfg['global_data']['radar_out'], 'starttime': dscfg['global_data']['starttime'], 'endtime': dscfg['global_data']['endtime'], 'occu_final': False} return new_dataset, ind_rad # no more files to process. Compute mean and standard deviation if procstatus == 2: if dscfg['initialized'] == 0: return None, None if 'radar_out' not in dscfg['global_data']: return None, None field_mean = ( dscfg['global_data']['radar_out'].fields['sum']['data'] / dscfg['global_data']['radar_out'].fields[ 'number_of_samples']['data']) field_std = np.ma.sqrt( dscfg['global_data']['radar_out'].fields['sum_squared']['data'] / dscfg['global_data']['radar_out'].fields[ 'number_of_samples']['data']-field_mean*field_mean) if lin_trans: field_mean = 10.*np.ma.log10(field_mean) field_std = 10.*np.ma.log10(field_std) radar = dscfg['global_data']['radar_out'] mean_dict = pyart.config.get_metadata(field_name) mean_dict['data'] = field_mean radar.add_field(field_name, mean_dict) std_dict = pyart.config.get_metadata('standard_deviation') std_dict['data'] = field_std radar.add_field('standard_deviation', std_dict) new_dataset = { 'radar_out': radar, 'starttime': dscfg['global_data']['starttime'], 'endtime': dscfg['global_data']['endtime'], 'occu_final': True} return new_dataset, ind_rad def process_occurrence_period(procstatus, dscfg, radar_list=None): """ computes the frequency of occurrence over a long period of time by adding together shorter periods Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: datatype : list of string. Dataset keyword The input data types regular_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False rmin, rmax : float. Dataset keyword minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1 radar_list : list of Radar objects Optional. list of radar objects Returns ------- new_dataset : dict dictionary containing the output ind_rad : int radar index """ for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) if datatype == 'occurrence': occu_field = get_fieldname_pyart(datatype) elif datatype == 'nsamples': nsamples_field = get_fieldname_pyart(datatype) ind_rad = int(radarnr[5:8])-1 if procstatus == 0: return None, None if procstatus == 1: if radar_list[ind_rad] is None: warn('No valid radar') return None, None radar = radar_list[ind_rad] if ((occu_field not in radar.fields) or (nsamples_field not in radar.fields)): warn('Unable to compute frequency of occurrence. Missing data') return None, None radar_aux = deepcopy(radar) radar_aux.fields = dict() radar_aux.add_field('occurrence', radar.fields['occurrence']) radar_aux.add_field( 'number_of_samples', radar.fields['number_of_samples']) # filter out out of range data rmin = dscfg.get('rmin', -1.) rmax = dscfg.get('rmax', -1.) if rmin >= 0.: ind_min = np.where(radar_aux.range['data'] < rmin)[0] if ind_min: ind_min = ind_min[-1] radar_aux.fields['occurrence']['data'][:, 0:ind_min+1] = 0 if rmax >= 0.: ind_max = np.where(radar_aux.range['data'] > rmax)[0] if ind_max: ind_max = ind_max[0] radar_aux.fields['occurrence']['data'][ :, ind_max:radar_aux.ngates] = 0 # first volume: initialize radar object if dscfg['initialized'] == 0: new_dataset = { 'radar_out': radar_aux, 'starttime': dscfg['timeinfo'], 'endtime': dscfg['timeinfo'], 'occu_final': False} dscfg['global_data'] = new_dataset dscfg['initialized'] = 1 return new_dataset, ind_rad # accumulate data regular_grid = False if 'regular_grid' in dscfg: regular_grid = dscfg['regular_grid'] if not regular_grid: occu_interp = interpol_field( dscfg['global_data']['radar_out'], radar_aux, 'occurrence') npoints_interp = interpol_field( dscfg['global_data']['radar_out'], radar_aux, 'number_of_samples') else: if radar_aux.nrays != dscfg['global_data']['radar_out'].nrays: warn('Unable to accumulate radar object. ' + 'Number of rays of current radar different from ' + 'reference. nrays current: '+str(radar_aux.nrays) + ' nrays ref: ' + str(dscfg['global_data']['radar_out'].nrays)) return None, None occu_interp = radar_aux.fields['occurrence'] npoints_interp = radar_aux.fields['number_of_samples'] dscfg['global_data']['radar_out'].fields['occurrence']['data'] += ( np.ma.asarray( occu_interp['data'].filled(fill_value=0)).astype('int')) dscfg['global_data']['radar_out'].fields['number_of_samples'][ 'data'] += np.ma.asarray( npoints_interp['data'].filled(fill_value=0)).astype('int') dscfg['global_data']['endtime'] = dscfg['timeinfo'] new_dataset = { 'radar_out': dscfg['global_data']['radar_out'], 'starttime': dscfg['global_data']['starttime'], 'endtime': dscfg['global_data']['endtime'], 'occu_final': False} return new_dataset, ind_rad # no more files to process. Compute frequency of occurrence if procstatus == 2: if dscfg['initialized'] == 0: return None, None if 'radar_out' not in dscfg['global_data']: return None, None radar = dscfg['global_data']['radar_out'] freq_occu_dict = pyart.config.get_metadata('frequency_of_occurrence') freq_occu_dict['data'] = (100.*radar.fields['occurrence']['data'] / radar.fields['number_of_samples']['data']) radar.add_field('frequency_of_occurrence', freq_occu_dict) new_dataset = { 'radar_out': dscfg['global_data']['radar_out'], 'starttime': dscfg['global_data']['starttime'], 'endtime': dscfg['global_data']['endtime'], 'occu_final': True} return new_dataset, ind_rad def process_sun_hits(procstatus, dscfg, radar_list=None): """ monitoring of the radar using sun hits Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: datatype : list of string. Dataset keyword The input data types delev_max : float. Dataset keyword maximum elevation distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 dazim_max : float. Dataset keyword maximum azimuth distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 elmin : float. Dataset keyword minimum radar elevation where to look for sun hits [deg]. Default 1. attg : float. Dataset keyword gaseous attenuation. Default None sun_position : string. Datset keyword The function to compute the sun position to use. Can be 'MF' or 'pysolar' sun_hit_method : str. Dataset keyword Method used to estimate the power of the sun hit. Can be HS (Hildebrand and Sekhon 1974) or Ivic (Ivic 2013) rmin : float. Dataset keyword minimum range where to look for a sun hit signal [m]. Used in HS method. Default 50000. hmin : float. Dataset keyword minimum altitude where to look for a sun hit signal [m MSL]. Default 10000. The actual range from which a sun hit signal will be search will be the minimum between rmin and the range from which the altitude is higher than hmin. Used in HS method. Default 10000. nbins_min : int. Dataset keyword. minimum number of range bins that have to contain signal to consider the ray a potential sun hit. Default 20 for HS and 8000 for Ivic. npulses_ray : int Default number of pulses used in the computation of the ray. If the number of pulses is not in radar.instrument_parameters this will be used instead. Used in Ivic method. Default 30 iterations: int number of iterations in step 7 of Ivic method. Default 10. max_std_pwr : float. Dataset keyword maximum standard deviation of the signal power to consider the data a sun hit [dB]. Default 2. Used in HS method max_std_zdr : float. Dataset keyword maximum standard deviation of the ZDR to consider the data a sun hit [dB]. Default 2. az_width_co : float. Dataset keyword co-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_co : float. Dataset keyword co-polar antenna elevation width (convoluted with sun width) [deg]. Default None az_width_cross : float. Dataset keyword cross-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_cross : float. Dataset keyword cross-polar antenna elevation width (convoluted with sun width) [deg]. Default None ndays : int. Dataset keyword number of days used in sun retrieval. Default 1 coeff_band : float. Dataset keyword multiplicate coefficient to transform pulse width into receiver bandwidth frequency : float. Dataset keyword the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present frequency dependent parameters will not be computed beamwidth : float. Dataset keyword the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth dependent parameters will not be computed pulse_width : float. Dataset keyword the pulse width [s]. If None that of the key pulse_width in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the pulse width dependent parameters will not be computed ray_angle_res : float. Dataset keyword the ray angle resolution [deg]. If None that of the key ray_angle_res in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed AntennaGainH, AntennaGainV : float. Dataset keyword the horizontal (vertical) polarization antenna gain [dB]. If None that of the attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed radar_list : list of Radar objects Optional. list of radar objects Returns ------- sun_hits_dict : dict dictionary containing a radar object, a sun_hits dict and a sun_retrieval dictionary ind_rad : int radar index """ if procstatus == 0: return None, None if procstatus == 1: for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) if datatype == 'dBm': pwrh_field = 'signal_power_hh' if datatype == 'dBmv': pwrv_field = 'signal_power_vv' if datatype == 'ZDRu': zdr_field = 'unfiltered_differential_reflectivity' if datatype == 'ZDRuc': zdr_field = 'corrected_unfiltered_differential_reflectivity' if datatype == 'ZDR': zdr_field = 'differential_reflectivity' ind_rad = int(radarnr[5:8])-1 if radar_list[ind_rad] is None: warn('No valid radar') return None, None radar = radar_list[ind_rad] if ((pwrh_field not in radar.fields) or (pwrv_field not in radar.fields) or (zdr_field not in radar.fields)): warn('Unable to get sun hits. Missing data') return None, None # initialize dataset if dscfg['initialized'] == 0: radar_par = dict() freq = dscfg.get('frequency', None) if freq is None: if (radar.instrument_parameters is not None and 'frequency' in radar.instrument_parameters): freq = radar.instrument_parameters['frequency']['data'][0] if freq is None: warn('Radar frequency unknown.') else: radar_par.update({'wavelen': 3e8/freq}) beamwidth = dscfg.get('beamwidth', None) if beamwidth is None: if radar.instrument_parameters is not None: if 'radar_beam_width_h' in radar.instrument_parameters: beamwidth = radar.instrument_parameters[ 'radar_beam_width_h']['data'][0] elif 'radar_beam_width_v' in radar.instrument_parameters: beamwidth = radar.instrument_parameters[ 'radar_beam_width_v']['data'][0] if beamwidth is None: warn('Antenna beam width unknown.') else: radar_par.update({'beamwidth': beamwidth}) pulse_width = dscfg.get('pulse_width', None) if pulse_width is None: if (radar.instrument_parameters is not None and 'pulse_width' in radar.instrument_parameters): pulse_width = radar.instrument_parameters['pulse_width'][ 'data'][0] if pulse_width is None: warn('Pulse width unknown.') else: radar_par.update({'pulse_width': pulse_width}) ray_angle_res = dscfg.get('ray_angle_res', None) if ray_angle_res is None: if radar.ray_angle_res is not None: ray_angle_res = radar.ray_angle_res['data'][0] if ray_angle_res is None: warn('Angular resolution unknown.') else: radar_par.update({'angle_step': ray_angle_res}) antenna_gain_h = dscfg.get('AntennaGainH', None) if antenna_gain_h is None: if (radar.instrument_parameters is not None and 'radar_antenna_gain_h' in radar.instrument_parameters): antenna_gain_h = ( radar.instrument_parameters['radar_antenna_gain_h'][ 'data'][0]) if antenna_gain_h is None: warn('Horizontal antenna gain unknown.') else: radar_par.update({'antenna_gain_h': antenna_gain_h}) antenna_gain_v = dscfg.get('AntennaGainV', None) if antenna_gain_v is None: if (radar.instrument_parameters is not None and 'radar_antenna_gain_v' in radar.instrument_parameters): antenna_gain_v = ( radar.instrument_parameters['radar_antenna_gain_v'][ 'data'][0]) if antenna_gain_v is None: warn('Vertical antenna gain unknown.') else: radar_par.update({'antenna_gain_v': antenna_gain_v}) radar_par.update({'timeinfo': dscfg['timeinfo']}) dscfg['global_data'] = radar_par dscfg['initialized'] = 1 dscfg['global_data']['timeinfo'] = dscfg['timeinfo'] # user values delev_max = dscfg.get('delev_max', 1.5) dazim_max = dscfg.get('dazim_max', 1.5) elmin = dscfg.get('elmin', 1.) attg = dscfg.get('attg', None) max_std_zdr = dscfg.get('max_std_zdr', 2.) sun_hit_method = dscfg.get('sun_hit_method', 'HS') sun_position = dscfg.get('sun_position', 'MF') if sun_hit_method == 'HS': rmin = dscfg.get('rmin', 50000.) hmin = dscfg.get('hmin', 10000.) nbins_min = dscfg.get('nbins_min', 20) max_std_pwr = dscfg.get('max_std_pwr', 2.) sun_hits, new_radar = pyart.correct.get_sun_hits( radar, delev_max=delev_max, dazim_max=dazim_max, elmin=elmin, rmin=rmin, hmin=hmin, nbins_min=nbins_min, max_std_pwr=max_std_pwr, max_std_zdr=max_std_zdr, attg=attg, sun_position=sun_position, pwrh_field=pwrh_field, pwrv_field=pwrv_field, zdr_field=zdr_field) else: npulses_ray = dscfg.get('npulses_ray', 30) nbins_min = dscfg.get('nbins_min', 800) iterations = dscfg.get('iterations', 10) sun_hits, new_radar = pyart.correct.get_sun_hits_ivic( radar, delev_max=delev_max, dazim_max=dazim_max, elmin=elmin, npulses_ray=npulses_ray, nbins_min=nbins_min, iterations=iterations, attg=attg, max_std_zdr=max_std_zdr, sun_position=sun_position, pwrh_field=pwrh_field, pwrv_field=pwrv_field, zdr_field=zdr_field) if sun_hits is None: return None, None sun_hits_dataset = dict() sun_hits_dataset.update({'sun_hits': sun_hits}) sun_hits_dataset.update({'radar_out': new_radar}) sun_hits_dataset.update({'timeinfo': dscfg['timeinfo']}) return sun_hits_dataset, ind_rad if procstatus == 2: for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) break ind_rad = int(radarnr[5:8])-1 # user values az_width_co = dscfg.get('az_width_co', None) el_width_co = dscfg.get('el_width_co', None) az_width_cross = dscfg.get('az_width_cross', None) el_width_cross = dscfg.get('el_width_cross', None) nfiles = dscfg.get('ndays', 1) sun_hits = read_sun_hits_multiple_days( dscfg, dscfg['global_data']['timeinfo'], nfiles=nfiles) if sun_hits[0] is None: return None, None sun_pwr_h = sun_hits[7] sun_pwr_v = sun_hits[11] # get DRAO reference sf_ref = np.ma.asarray(np.ma.masked) ref_time = None if 'wavelen' in dscfg['global_data']: flx_dt, flx_val = read_solar_flux( dscfg['solarfluxpath']+'fluxtable.txt') if flx_dt is not None: flx_dt_closest, flx_val_closest = get_closest_solar_flux( sun_hits[0], flx_dt, flx_val) # flux at radar wavelength sf_radar = pyart.correct.solar_flux_lookup( flx_val_closest, dscfg['global_data']['wavelen']) sf_ref = np.ma.asarray(sf_radar[-1]) ref_time = flx_dt_closest[-1] # scaling of the power to account for solar flux variations. # The last sun hit is the reference. The scale factor is in dB scale_factor = -10.*np.log10(sf_radar/sf_ref) sun_pwr_h += scale_factor sun_pwr_v += scale_factor else: warn('Unable to compute solar power reference. ' + 'Missing DRAO data') else: warn('Unable to compute solar power reference. ' + 'Missing radar wavelength') sun_retrieval_h = pyart.correct.sun_retrieval( sun_hits[4], sun_hits[6], sun_hits[3], sun_hits[5], sun_pwr_h, sun_hits[8], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) sun_retrieval_v = pyart.correct.sun_retrieval( sun_hits[4], sun_hits[6], sun_hits[3], sun_hits[5], sun_pwr_v, sun_hits[12], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) sun_retrieval_zdr = pyart.correct.sun_retrieval( sun_hits[4], sun_hits[6], sun_hits[3], sun_hits[5], sun_hits[15], sun_hits[16], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=True) sun_retrieval_dict = { 'first_hit_time': sun_hits[0][0], 'last_hit_time': sun_hits[0][-1], 'dBm_sun_est': np.ma.asarray(np.ma.masked), 'std(dBm_sun_est)': np.ma.asarray(np.ma.masked), 'sf_h': np.ma.asarray(np.ma.masked), 'az_bias_h': np.ma.asarray(np.ma.masked), 'el_bias_h': np.ma.asarray(np.ma.masked), 'az_width_h': np.ma.asarray(np.ma.masked), 'el_width_h': np.ma.asarray(np.ma.masked), 'nhits_h': 0, 'par_h': None, 'dBmv_sun_est': np.ma.asarray(np.ma.masked), 'std(dBmv_sun_est)': np.ma.asarray(np.ma.masked), 'sf_v': np.ma.asarray(np.ma.masked), 'az_bias_v': np.ma.asarray(np.ma.masked), 'el_bias_v': np.ma.asarray(np.ma.masked), 'az_width_v': np.ma.asarray(np.ma.masked), 'el_width_v': np.ma.asarray(np.ma.masked), 'nhits_v': 0, 'par_v': None, 'ZDR_sun_est': np.ma.asarray(np.ma.masked), 'std(ZDR_sun_est)': np.ma.asarray(np.ma.masked), 'az_bias_zdr': np.ma.asarray(np.ma.masked), 'el_bias_zdr': np.ma.asarray(np.ma.masked), 'nhits_zdr': 0, 'par_zdr': None, 'sf_ref': np.ma.asarray(sf_ref), 'ref_time': ref_time, 'lant': np.ma.asarray(np.ma.masked)} if sun_retrieval_h is not None: # correct for scanning losses and the polarization of the antenna if (('angle_step' in dscfg['global_data']) and ('beamwidth' in dscfg['global_data'])): lant = pyart.correct.scanning_losses( dscfg['global_data']['angle_step'], dscfg['global_data']['beamwidth']) else: warn('Unable to estimate scanning losses. ' + 'Missing radar parameters. ' + 'Antenna losses will be neglected') lant = 0. ptoa_h = sun_retrieval_h[0]+lant+3. # compute observed solar flux if (('pulse_width' in dscfg['global_data']) and ('wavelen' in dscfg['global_data']) and ('antenna_gain_h' in dscfg['global_data'])): sf_h = pyart.correct.ptoa_to_sf( ptoa_h, dscfg['global_data']['pulse_width'], dscfg['global_data']['wavelen'], dscfg['global_data']['antenna_gain_h']) else: warn('Unable to estimate observed solar flux. ' + 'Missing radar parameters') sf_h = np.ma.asarray(np.ma.masked) sun_retrieval_dict['dBm_sun_est'] = np.ma.asarray(ptoa_h) sun_retrieval_dict['std(dBm_sun_est)'] = np.ma.asarray( sun_retrieval_h[1]) sun_retrieval_dict['sf_h'] = np.ma.asarray(sf_h) sun_retrieval_dict['az_bias_h'] = np.ma.asarray( sun_retrieval_h[2]) sun_retrieval_dict['el_bias_h'] = np.ma.asarray( sun_retrieval_h[3]) sun_retrieval_dict['az_width_h'] = np.ma.asarray( sun_retrieval_h[4]) sun_retrieval_dict['el_width_h'] = np.ma.asarray( sun_retrieval_h[5]) sun_retrieval_dict['nhits_h'] = np.asarray(sun_retrieval_h[6]) sun_retrieval_dict['par_h'] = np.ma.asarray(sun_retrieval_h[7]) sun_retrieval_dict['lant'] = np.ma.asarray(lant) if sun_retrieval_v is not None: # correct for scanning losses and the polarization of the antenna if (('angle_step' in dscfg['global_data']) and ('beamwidth' in dscfg['global_data'])): lant = pyart.correct.scanning_losses( dscfg['global_data']['angle_step'], dscfg['global_data']['beamwidth']) else: lant = 0. warn('Unable to estimate scanning losses. ' + 'Missing radar parameters. ' + 'Antenna losses will be neglected') ptoa_v = sun_retrieval_v[0]+lant+3. # compute observed solar flux if (('pulse_width' in dscfg['global_data']) and ('wavelen' in dscfg['global_data']) and ('antenna_gain_v' in dscfg['global_data'])): sf_v = pyart.correct.ptoa_to_sf( ptoa_v, dscfg['global_data']['pulse_width'], dscfg['global_data']['wavelen'], dscfg['global_data']['antenna_gain_v']) else: warn('Unable to estimate observed solar flux. ' + 'Missing radar parameters') sf_v = np.ma.asarray(np.ma.masked) sun_retrieval_dict['dBmv_sun_est'] = np.ma.asarray(ptoa_v) sun_retrieval_dict['std(dBmv_sun_est)'] = np.ma.asarray( sun_retrieval_v[1]) sun_retrieval_dict['sf_v'] = np.ma.asarray(sf_v) sun_retrieval_dict['az_bias_v'] = np.ma.asarray( sun_retrieval_v[2]) sun_retrieval_dict['el_bias_v'] = np.ma.asarray( sun_retrieval_v[3]) sun_retrieval_dict['az_width_v'] = np.ma.asarray( sun_retrieval_v[4]) sun_retrieval_dict['el_width_v'] = np.ma.asarray( sun_retrieval_v[5]) sun_retrieval_dict['nhits_v'] = np.ma.asarray(sun_retrieval_v[6]) sun_retrieval_dict['par_v'] = np.ma.asarray(sun_retrieval_v[7]) sun_retrieval_dict['lant'] = np.ma.asarray(lant) if sun_retrieval_zdr is not None: sun_retrieval_dict['ZDR_sun_est'] = np.ma.asarray( sun_retrieval_zdr[0]) sun_retrieval_dict['std(ZDR_sun_est)'] = np.ma.asarray( sun_retrieval_zdr[1]) sun_retrieval_dict['az_bias_zdr'] = np.ma.asarray( sun_retrieval_zdr[2]) sun_retrieval_dict['el_bias_dzr'] = np.ma.asarray( sun_retrieval_zdr[3]) sun_retrieval_dict['nhits_zdr'] = np.asarray(sun_retrieval_zdr[6]) sun_retrieval_dict['par_zdr'] = np.asarray(sun_retrieval_zdr[7]) sun_hits_dict = { 'time': sun_hits[0], 'ray': sun_hits[1], 'NPrng': sun_hits[2], 'rad_el': sun_hits[3], 'rad_az': sun_hits[4], 'sun_el': sun_hits[5], 'sun_az': sun_hits[6], 'dBm_sun_hit': sun_hits[7], 'std(dBm_sun_hit)': sun_hits[8], 'NPh': sun_hits[9], 'NPhval': sun_hits[10], 'dBmv_sun_hit': sun_hits[11], 'std(dBmv_sun_hit)': sun_hits[12], 'NPv': sun_hits[13], 'NPvval': sun_hits[14], 'ZDR_sun_hit': sun_hits[15], 'std(ZDR_sun_hit)': sun_hits[16], 'NPzdr': sun_hits[17], 'NPzdrval': sun_hits[18]} sun_hits_dataset = dict() sun_hits_dataset.update({'sun_hits_final': sun_hits_dict}) sun_hits_dataset.update({'sun_retrieval': sun_retrieval_dict}) sun_hits_dataset.update( {'timeinfo': dscfg['global_data']['timeinfo']}) return sun_hits_dataset, ind_rad def process_sunscan(procstatus, dscfg, radar_list=None): """ Processing of automatic sun scans for monitoring purposes of the radar system. Parameters ---------- procstatus : int Processing status: 0 initializing, 1 processing volume, 2 post-processing dscfg : dictionary of dictionaries data set configuration. Accepted Configuration Keywords:: datatype : list of string. Dataset keyword The input data types delev_max : float. Dataset keyword maximum elevation distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 dazim_max : float. Dataset keyword maximum azimuth distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 elmin : float. Dataset keyword minimum radar elevation where to look for sun hits [deg]. Default 1. attg : float. Dataset keyword gaseous attenuation. Default None sun_position : string. Datset keyword The function to compute the sun position to use. Can be 'MF' or 'pysolar' sun_hit_method : str. Dataset keyword Method used to estimate the power of the sun hit. Should be PSR. HS (Hildebrand and Sekhon 1974) or Ivic (Ivic 2013) are implemented but not tested. n_noise_bins : int. Dataset keyword Number of bins to use for noise estimation noise_threshold : float. Dataset keyword Distance over the noise level in [dBm] min_num_samples : int. Dataset keyword Minimal number of samples above the noise level max_fit_stddev : float. Dataset keyword Maximal allowed standard deviation for a valid sun fit [dBm] do_second_noise_est : string ('Yes' or 'No'). Dataset keyword Used to trigger a second noise estimation based on the first fit Requires another dataset keyword: n_indfar_bins n_indfar_bins : int. Dataset keyword Number of samples most remote from the sun center az_width_co : float. Dataset keyword co-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_co : float. Dataset keyword co-polar antenna elevation width (convoluted with sun width) [deg]. Default None az_width_cross : float. Dataset keyword cross-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_cross : float. Dataset keyword cross-polar antenna elevation width (convoluted with sun width) [deg]. Default None rmin : float. Dataset keyword minimum range where to look for a sun hit signal [m]. Used in HS method. Default 50000. hmin : float. Dataset keyword minimum altitude where to look for a sun hit signal [m MSL]. Default 10000. The actual range from which a sun hit signal will be search will be the minimum between rmin and the range from which the altitude is higher than hmin. Used in HS method. Default 10000. nbins_min : int. Dataset keyword. minimum number of range bins that have to contain signal to consider the ray a potential sun hit. Default 20 for HS and 8000 for Ivic. npulses_ray : int Default number of pulses used in the computation of the ray. If the number of pulses is not in radar.instrument_parameters this will be used instead. Used in Ivic method. Default 30 flat_reg_wlen : int Length of the flat region window [m]. Used in Ivic method. Default 8000. iterations: int number of iterations in step 7 of Ivic method. Default 10. max_std_pwr : float. Dataset keyword maximum standard deviation of the signal power to consider the data a sun hit [dB]. Default 2. Used in HS method max_std_zdr : float. Dataset keyword maximum standard deviation of the ZDR to consider the data a sun hit [dB]. Default 2. ndays : int. Dataset keyword number of days used in sun retrieval. Default 1 coeff_band : float. Dataset keyword multiplicate coefficient to transform pulse width into receiver bandwidth frequency : float. Dataset keyword the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present frequency dependent parameters will not be computed beamwidth : float. Dataset keyword the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth dependent parameters will not be computed pulse_width : float. Dataset keyword the pulse width [s]. If None that of the key pulse_width in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the pulse width dependent parameters will not be computed ray_angle_res : float. Dataset keyword the ray angle resolution [deg]. If None that of the key ray_angle_res in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed AntennaGainH, AntennaGainV : float. Dataset keyword the horizontal (vertical) polarization antenna gain [dB]. If None that of the attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed radar_list : list of Radar objects Optional. list of radar objects Returns ------- sunscan_dataset : dict dictionary containing a radar object, a sun_hits dict, a sun_retrieval dictionary, field_name and timeinfo ind_rad : int radar index """ if procstatus != 1: return None, None pwrh_field = None pwrv_field = None zdr_field = None sun_hit_method = dscfg.get('sun_hit_method', 'PSR') sun_position = dscfg.get('sun_position', 'MF') n_noise_bins = dscfg.get('n_noise_bins', 8) noise_threshold = dscfg.get('noise_threshold', 1.5) min_num_samples = dscfg.get('min_num_samples', 60) max_fit_stddev = dscfg.get('max_fit_stddev', 0.8) do_second_noise_est = dscfg.get('do_second_noise_est', 'Yes') n_indfar_bins = dscfg.get('n_indfar_bins', 10) az_width_co = dscfg.get('az_width_co', None) el_width_co = dscfg.get('el_width_co', None) az_width_cross = dscfg.get('az_width_cross', None) el_width_cross = dscfg.get('el_width_cross', None) delev_max = dscfg.get('delev_max', 3.0) dazim_max = dscfg.get('dazim_max', 3.0) elmin = dscfg.get('elmin', 5.) attg = dscfg.get('attg', None) for datatypedescr in dscfg['datatype']: radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) if sun_hit_method == "PSR": if datatype == 'NdBmh': pwrh_field = get_fieldname_pyart(datatype) elif datatype == 'NdBmv': pwrv_field = get_fieldname_pyart(datatype) elif datatype == 'ZDR': zdr_field = get_fieldname_pyart(datatype) else: warn('ERROR: No valid datatype') else: if datatype == 'dBm': pwrh_field = 'signal_power_hh' if datatype == 'dBmv': pwrv_field = 'signal_power_vv' if datatype == 'ZDRu': zdr_field = 'unfiltered_differential_reflectivity' if datatype == 'ZDRuc': zdr_field = 'corrected_unfiltered_differential_reflectivity' if datatype == 'ZDR': zdr_field = 'differential_reflectivity' ind_rad = int(radarnr[5:8])-1 if (radar_list is None) or (radar_list[ind_rad] is None): warn('ERROR: No valid radar') return None, None radar = radar_list[ind_rad] if ((pwrh_field not in radar.fields) and (pwrv_field not in radar.fields) and (zdr_field not in radar.fields)): warn('Unable to process sunscan. Missing data') return None, None # initialize dataset if dscfg['initialized'] == 0: radar_par = dict() freq = dscfg.get('frequency', None) if freq is None: if (radar.instrument_parameters is not None and 'frequency' in radar.instrument_parameters): freq = radar.instrument_parameters['frequency']['data'][0] if freq is None: warn('Radar frequency unknown.') else: radar_par.update({'wavelen': 3e8/freq}) beamwidth = dscfg.get('beamwidth', None) if beamwidth is None: if radar.instrument_parameters is not None: if 'radar_beam_width_h' in radar.instrument_parameters: beamwidth = radar.instrument_parameters[ 'radar_beam_width_h']['data'][0] elif 'radar_beam_width_v' in radar.instrument_parameters: beamwidth = radar.instrument_parameters[ 'radar_beam_width_v']['data'][0] if beamwidth is None: warn('Antenna beam width unknown.') else: radar_par.update({'beamwidth': beamwidth}) pulse_width = dscfg.get('pulse_width', None) if pulse_width is None: if (radar.instrument_parameters is not None and 'pulse_width' in radar.instrument_parameters): pulse_width = radar.instrument_parameters['pulse_width'][ 'data'][0] if pulse_width is None: warn('Pulse width unknown.') else: radar_par.update({'pulse_width': pulse_width}) ray_angle_res = dscfg.get('ray_angle_res', None) if ray_angle_res is None: if radar.ray_angle_res is not None: ray_angle_res = radar.ray_angle_res['data'][0] if ray_angle_res is None: warn('Angular resolution unknown.') else: radar_par.update({'angle_step': ray_angle_res}) antenna_gain_h = dscfg.get('AntennaGainH', None) if antenna_gain_h is None: if (radar.instrument_parameters is not None and 'radar_antenna_gain_h' in radar.instrument_parameters): antenna_gain_h = ( radar.instrument_parameters['radar_antenna_gain_h'][ 'data'][0]) if antenna_gain_h is None: warn('Horizontal antenna gain unknown.') else: radar_par.update({'antenna_gain_h': antenna_gain_h}) antenna_gain_v = dscfg.get('AntennaGainV', None) if antenna_gain_v is None: if (radar.instrument_parameters is not None and 'radar_antenna_gain_v' in radar.instrument_parameters): antenna_gain_v = ( radar.instrument_parameters['radar_antenna_gain_v'][ 'data'][0]) if antenna_gain_v is None: warn('Vertical antenna gain unknown.') else: radar_par.update({'antenna_gain_v': antenna_gain_v}) radar_par.update({'timeinfo': dscfg['timeinfo']}) dscfg['global_data'] = radar_par dscfg['initialized'] = 1 dscfg['global_data']['timeinfo'] = dscfg['timeinfo'] # get time for sunscan time = num2date(radar.time['data'], radar.time['units'], radar.time['calendar']) center_index = int(len(time) / 2.) sunscan_time = time[center_index] if sun_hit_method == 'PSR': if datatype == 'NdBmh': sunvol = radar.fields[pwrh_field]['data'][:, 0] elif datatype == 'NdBmv': sunvol = radar.fields[pwrv_field]['data'][:, 0] else: warn('ERROR: No valid datatype') indsorted = np.ma.argsort(sunvol) valsorted = sunvol[indsorted] valmax = np.ma.max(valsorted) noise_level1 = np.mean(valsorted[0:n_noise_bins-1]) noise_thres = noise_level1 + noise_threshold indval = np.ma.where(sunvol > noise_thres) nval = np.ma.size(indval) if nval < min_num_samples: warn('WARNING: Sun scan processing failed! Not enough valid samples') return None, None sun_hits = pyart.correct.get_sun_hits_psr( radar, delev_max=delev_max, dazim_max=dazim_max, elmin=elmin, noise_thres=noise_thres, attg=attg, sun_position=sun_position, pwrh_field=pwrh_field, pwrv_field=pwrv_field) elif sun_hit_method == 'HS': rmin = dscfg.get('rmin', 50000.) hmin = dscfg.get('hmin', 10000.) nbins_min = dscfg.get('nbins_min', 20) max_std_zdr = dscfg.get('max_std_zdr', 2.) max_std_pwr = dscfg.get('max_std_pwr', 2.) sun_hits, new_radar = pyart.correct.get_sun_hits( radar, delev_max=delev_max, dazim_max=dazim_max, elmin=elmin, rmin=rmin, hmin=hmin, nbins_min=nbins_min, max_std_pwr=max_std_pwr, max_std_zdr=max_std_zdr, attg=attg, sun_position=sun_position, pwrh_field=pwrh_field, pwrv_field=pwrv_field, zdr_field=zdr_field) elif sun_hit_method == 'IVIC': npulses_ray = dscfg.get('npulses_ray', 30) flat_reg_wlen_rng = dscfg.get('flat_reg_wlen', 8000.) nbins_min = dscfg.get('nbins_min', 800) iterations = dscfg.get('iterations', 10) max_std_zdr = dscfg.get('max_std_zdr', 2.) r_res = radar.range['data'][1]-radar.range['data'][0] flat_reg_wlen = int(flat_reg_wlen_rng/r_res) sun_hits, new_radar = pyart.correct.get_sun_hits_ivic( radar, delev_max=delev_max, dazim_max=dazim_max, elmin=elmin, npulses_ray=npulses_ray, flat_reg_wlen=flat_reg_wlen, nbins_min=nbins_min, iterations=iterations, attg=attg, max_std_zdr=max_std_zdr, sun_position=sun_position, pwrh_field=pwrh_field, pwrv_field=pwrv_field, zdr_field=zdr_field) else: warn('Warning: No valid sun_hit_method specified.') if sun_hits is None: return None, None sun_pwr_h = sun_hits['dBm_sun_hit'] sun_pwr_v = sun_hits['dBmv_sun_hit'] #Substraction of noise vals_lin_h = 10. ** (sun_pwr_h / 10.) vals_lin_v = 10. ** (sun_pwr_v / 10.) noise_lin = 10. ** (noise_level1 / 10.) vals_nonoise_lin_h = vals_lin_h - noise_lin vals_nonoise_lin_v = vals_lin_v - noise_lin indnotval_h = np.ma.where(vals_nonoise_lin_h <= 1e-37) indnotval_v = np.ma.where(vals_nonoise_lin_v <= 1e-37) if np.ma.size(indnotval_h) > 0: warn('WARNING: SunScan: Too small linear values!') vals_nonoise_lin_h[indnotval_h] = np.ma.masked if np.ma.size(indnotval_v) > 0: warn('WARNING: SunScan: Too small linear values!') vals_nonoise_lin_v[indnotval_v] = np.ma.masked if pwrh_field is not None: vals_nonoise_db = 10. * np.ma.log10(vals_nonoise_lin_h) if pwrv_field is not None: vals_nonoise_db = 10. * np.ma.log10(vals_nonoise_lin_v) valmax_nonoise = np.ma.max(vals_nonoise_db) # get DRAO reference sf_ref = np.ma.asarray(np.ma.masked) ref_time = None if 'wavelen' in dscfg['global_data']: flx_dt, flx_val = read_solar_flux( dscfg['solarfluxpath']+'fluxtable.txt') if flx_dt is not None: flx_dt_closest, flx_val_closest = get_closest_solar_flux( sun_hits['time'], flx_dt, flx_val) # flux at radar wavelength sf_radar = pyart.correct.solar_flux_lookup( flx_val_closest, dscfg['global_data']['wavelen']) sf_ref = np.ma.asarray(sf_radar[-1]) ref_time = flx_dt_closest[-1] # scaling of the power to account for solar flux variations. # The last sun hit is the reference. The scale factor is in dB scale_factor = -10.*np.log10(sf_radar/sf_ref) if sun_hit_method == 'PSR': vals_nonoise_db += scale_factor else: sun_pwr_h += scale_factor sun_pwr_v += scale_factor else: warn('Unable to compute solar power reference. ' + 'Missing DRAO data') else: warn('Unable to compute solar power reference. ' + 'Missing radar wavelength') sun_retrieval_h = None sun_retrieval_v = None if sun_hit_method == 'PSR': if pwrh_field is not None: sun_retrieval_h = pyart.correct.sun_retrieval( sun_hits['rad_az'], sun_hits['sun_az'], sun_hits['rad_el'], sun_hits['sun_el'], vals_nonoise_db, sun_hits['std(dBm_sun_hit)'], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) azoff = np.ma.asarray(sun_retrieval_h[2]) eloff = np.ma.asarray(sun_retrieval_h[3]) par = np.ma.asarray(sun_retrieval_h[7]) fit_stddev = np.ma.asarray(sun_retrieval_h[1]) if fit_stddev >= max_fit_stddev: return None, None if pwrv_field is not None: sun_retrieval_v = pyart.correct.sun_retrieval( sun_hits['rad_az'], sun_hits['sun_az'], sun_hits['rad_el'], sun_hits['sun_el'], vals_nonoise_db, sun_hits['std(dBmv_sun_hit)'], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) azoff = np.ma.asarray(sun_retrieval_v[2]) eloff = np.ma.asarray(sun_retrieval_v[3]) par = np.ma.asarray(sun_retrieval_v[7]) fit_stddev = np.ma.asarray(sun_retrieval_v[1]) if fit_stddev >= max_fit_stddev: return None, None sundist = np.zeros_like(sunvol) sunpwrmat = np.zeros_like(sunvol) sunvalmat = np.zeros_like(sunvol) sunpos_el = np.zeros_like(sunvol) sunpos_az = np.zeros_like(sunvol) # get time at each ray time = num2date(radar.time['data'], radar.time['units'], radar.time['calendar']) for ray in range(radar.nrays): if _PYSOLAR_AVAILABLE and sun_position == 'pysolar': elev_sun, azim_sun = pyart.correct.sun_position_pysolar( time[ray], radar.latitude['data'][0], radar.longitude['data'][0]) else: elev_sun, azim_sun = pyart.correct.sun_position_mfr( time[ray], radar.latitude['data'][0], radar.longitude['data'][0], refraction=True) #azshift? delev = np.ma.abs(radar.elevation['data'][ray]-elev_sun) dazim = np.ma.abs( (radar.azimuth['data'][ray]-azim_sun) * np.ma.cos(elev_sun*np.pi/180.)) if dazim > 360.: dazim -= 360. sundist[ray] = np.sqrt((dazim - azoff)**2 + (delev - eloff)**2) sunpwrmat[ray] = (par[0] + par[1] * dazim + par[2] * delev + par[3] * dazim**2 + par[4] * delev**2) sunvalmat[ray] = sunvol[ray] sunpos_el[ray] = elev_sun sunpos_az[ray] = azim_sun #Second noise estimation: removal of sunpower influence if do_second_noise_est == 'Yes': #Find the samples most remote from the sun center inddistsorted = np.argsort(sundist)[::-1] indfar = inddistsorted[0:n_indfar_bins-1] noise_far_lin = 10. ** (sunvalmat[indfar] / 10.) - 10. ** (sunpwrmat[indfar] / 10.) noise_level2 = 10. * np.log10(np.mean(noise_far_lin)) noise_thres2 = noise_level2 + noise_threshold sun_hits = pyart.correct.get_sun_hits_psr( radar, delev_max=delev_max, dazim_max=dazim_max, elmin=elmin, noise_thres=noise_thres2, attg=attg, sun_position=sun_position, pwrh_field=pwrh_field, pwrv_field=pwrv_field) if sun_hits is None: return None sun_pwr_h = sun_hits['dBm_sun_hit'] sun_pwr_v = sun_hits['dBmv_sun_hit'] #Substraction of noise vals_lin_h = 10. ** (sun_pwr_h / 10.) vals_lin_v = 10. ** (sun_pwr_v / 10.) noise_lin = 10. ** (noise_level2 / 10.) vals_nonoise_lin_h = vals_lin_h - noise_lin vals_nonoise_lin_v = vals_lin_v - noise_lin indnotval_h = np.ma.where(vals_nonoise_lin_h <= 1e-37) indnotval_v = np.ma.where(vals_nonoise_lin_v <= 1e-37) if np.ma.size(indnotval_h) > 0: warn('WARNING: SunScan: Too small linear values!') vals_nonoise_lin_h[indnotval_h] = np.ma.masked if np.ma.size(indnotval_v) > 0: warn('WARNING: SunScan: Too small linear values!') vals_nonoise_lin_v[indnotval_v] = np.ma.masked if pwrh_field is not None: vals_nonoise_db = 10. * np.ma.log10(vals_nonoise_lin_h) if pwrv_field is not None: vals_nonoise_db = 10. * np.ma.log10(vals_nonoise_lin_v) valmax_nonoise = np.ma.max(vals_nonoise_db) # get DRAO reference sf_ref = np.ma.asarray(np.ma.masked) ref_time = None if 'wavelen' in dscfg['global_data']: flx_dt, flx_val = read_solar_flux( dscfg['solarfluxpath']+'fluxtable.txt') if flx_dt is not None: flx_dt_closest, flx_val_closest = get_closest_solar_flux( sun_hits['time'], flx_dt, flx_val) # flux at radar wavelength sf_radar = pyart.correct.solar_flux_lookup( flx_val_closest, dscfg['global_data']['wavelen']) sf_ref = np.ma.asarray(sf_radar[-1]) ref_time = flx_dt_closest[-1] # scaling of the power to account for solar flux variations. # The last sun hit is the reference. The scale factor is in dB scale_factor = -10.*np.log10(sf_radar/sf_ref) vals_nonoise_db += scale_factor else: warn('Unable to compute solar power reference. ' + 'Missing DRAO data') else: warn('Unable to compute solar power reference. ' + 'Missing radar wavelength') sun_retrieval_h = None sun_retrieval_v = None if pwrh_field is not None: sun_retrieval_h = pyart.correct.sun_retrieval( sun_hits['rad_az'], sun_hits['sun_az'], sun_hits['rad_el'], sun_hits['sun_el'], vals_nonoise_db, sun_hits['std(dBm_sun_hit)'], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) if pwrv_field is not None: sun_retrieval_v = pyart.correct.sun_retrieval( sun_hits['rad_az'], sun_hits['sun_az'], sun_hits['rad_el'], sun_hits['sun_el'], vals_nonoise_db, sun_hits['std(dBmv_sun_hit)'], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) else: sun_retrieval_h = pyart.correct.sun_retrieval( sun_hits[4], sun_hits[6], sun_hits[3], sun_hits[5], sun_pwr_h, sun_hits[8], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) sun_retrieval_v = pyart.correct.sun_retrieval( sun_hits[4], sun_hits[6], sun_hits[3], sun_hits[5], sun_pwr_v, sun_hits[12], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=False) sun_retrieval_zdr = pyart.correct.sun_retrieval( sun_hits[4], sun_hits[6], sun_hits[3], sun_hits[5], sun_hits[15], sun_hits[16], az_width_co=az_width_co, el_width_co=el_width_co, az_width_cross=az_width_cross, el_width_cross=el_width_cross, is_zdr=True) sun_retrieval_dict = { 'first_hit_time': sun_hits['time'][0], 'sunscan_time': sunscan_time, 'last_hit_time': sun_hits['time'][-1], 'sunpos_el': sunpos_el[center_index], 'sunpos_az': sunpos_az[center_index], 'sun_maxpwr_noise': np.ma.asarray(np.ma.masked), 'sun_maxpwr_nonoise': np.ma.asarray(np.ma.masked), 'noise_pwr': np.ma.asarray(np.ma.masked), 'dBm_sun_est': np.ma.asarray(np.ma.masked), 'dBm_sun_est_toa': np.ma.asarray(np.ma.masked), 'std(dBm_sun_est)': np.ma.asarray(np.ma.masked), 'sf_h': np.ma.asarray(np.ma.masked), 'az_bias_h': np.ma.asarray(np.ma.masked), 'el_bias_h': np.ma.asarray(np.ma.masked), 'az_width_h': np.ma.asarray(np.ma.masked), 'el_width_h': np.ma.asarray(np.ma.masked), 'nhits_h': 0, 'par_h': None, 'dBmv_sun_est': np.ma.asarray(np.ma.masked), 'dBmv_sun_est_toa': np.ma.asarray(np.ma.masked), 'std(dBmv_sun_est)': np.ma.asarray(np.ma.masked), 'sf_v': np.ma.asarray(np.ma.masked), 'az_bias_v': np.ma.asarray(np.ma.masked), 'el_bias_v': np.ma.asarray(np.ma.masked), 'az_width_v': np.ma.asarray(np.ma.masked), 'el_width_v': np.ma.asarray(np.ma.masked), 'nhits_v': 0, 'par_v': None, 'ZDR_sun_est': np.ma.asarray(np.ma.masked), 'std(ZDR_sun_est)': np.ma.asarray(np.ma.masked), 'az_bias_zdr': np.ma.asarray(np.ma.masked), 'el_bias_zdr': np.ma.asarray(np.ma.masked), 'nhits_zdr': 0, 'par_zdr': None, 'sf_ref': np.ma.asarray(sf_ref), 'ref_time': ref_time, 'lant': np.ma.asarray(np.ma.masked)} if sun_retrieval_h is not None: # correct for scanning losses and the aneotenna polarization if (('angle_step' in dscfg['global_data']) and ('beamwidth' in dscfg['global_data'])): lant = pyart.correct.scanning_losses( dscfg['global_data']['angle_step'], dscfg['global_data']['beamwidth']) else: warn('Unable to estimate scanning losses. ' + 'Missing radar parameters. ' + 'Antenna losses will be neglected') lant = 0. ptoa_h = sun_retrieval_h[0]+lant+3. # compute observed solar flux if (('pulse_width' in dscfg['global_data']) and ('wavelen' in dscfg['global_data']) and ('antenna_gain_h' in dscfg['global_data'])): sf_h = pyart.correct.ptoa_to_sf( ptoa_h, dscfg['global_data']['pulse_width'], dscfg['global_data']['wavelen'], dscfg['global_data']['antenna_gain_h']) else: warn('Unable to estimate observed solar flux. ' + 'Missing radar parameters') sf_h = np.ma.asarray(np.ma.masked) sun_retrieval_dict['sun_maxpwr_noise'] = np.ma.asarray(valmax) sun_retrieval_dict['sun_maxpwr_nonoise'] = np.ma.asarray(valmax_nonoise) if do_second_noise_est == 'Yes': sun_retrieval_dict['noise_pwr'] = np.ma.asarray(noise_level2) else: sun_retrieval_dict['noise_pwr'] = np.ma.asarray(noise_level1) sun_retrieval_dict['dBm_sun_est'] = np.ma.asarray(sun_retrieval_h[0]) sun_retrieval_dict['dBm_sun_est_toa'] = np.ma.asarray(ptoa_h) sun_retrieval_dict['std(dBm_sun_est)'] = np.ma.asarray( sun_retrieval_h[1]) sun_retrieval_dict['sf_h'] = np.ma.asarray(sf_h) sun_retrieval_dict['az_bias_h'] = np.ma.asarray( sun_retrieval_h[2]) sun_retrieval_dict['el_bias_h'] = np.ma.asarray( sun_retrieval_h[3]) sun_retrieval_dict['az_width_h'] = np.ma.asarray( sun_retrieval_h[4]) sun_retrieval_dict['el_width_h'] = np.ma.asarray( sun_retrieval_h[5]) sun_retrieval_dict['nhits_h'] = np.asarray(sun_retrieval_h[6]) sun_retrieval_dict['par_h'] = np.ma.asarray(sun_retrieval_h[7]) sun_retrieval_dict['lant'] = np.ma.asarray(lant) if sun_retrieval_v is not None: # correct for scanning losses and the polarization of the antenna if (('angle_step' in dscfg['global_data']) and ('beamwidth' in dscfg['global_data'])): lant = pyart.correct.scanning_losses( dscfg['global_data']['angle_step'], dscfg['global_data']['beamwidth']) else: lant = 0. warn('Unable to estimate scanning losses. ' + 'Missing radar parameters. ' + 'Antenna losses will be neglected') ptoa_v = sun_retrieval_v[0]+lant+3. # compute observed solar flux if (('pulse_width' in dscfg['global_data']) and ('wavelen' in dscfg['global_data']) and ('antenna_gain_v' in dscfg['global_data'])): sf_v = pyart.correct.ptoa_to_sf( ptoa_v, dscfg['global_data']['pulse_width'], dscfg['global_data']['wavelen'], dscfg['global_data']['antenna_gain_v']) else: warn('Unable to estimate observed solar flux. ' + 'Missing radar parameters') sf_v = np.ma.asarray(np.ma.masked) sun_retrieval_dict['sun_maxpwr_noise'] = np.ma.asarray(valmax) sun_retrieval_dict['sun_maxpwr_nonoise'] = np.ma.asarray(valmax_nonoise) if do_second_noise_est == 'Yes': sun_retrieval_dict['noise_pwr'] = np.ma.asarray(noise_level2) else: sun_retrieval_dict['noise_pwr'] = np.ma.asarray(noise_level1) sun_retrieval_dict['dBmv_sun_est'] = np.ma.asarray(sun_retrieval_v[0]) sun_retrieval_dict['dBmv_sun_est_toa'] = np.ma.asarray(ptoa_v) sun_retrieval_dict['std(dBmv_sun_est)'] = np.ma.asarray( sun_retrieval_v[1]) sun_retrieval_dict['sf_v'] = np.ma.asarray(sf_v) sun_retrieval_dict['az_bias_v'] = np.ma.asarray( sun_retrieval_v[2]) sun_retrieval_dict['el_bias_v'] = np.ma.asarray( sun_retrieval_v[3]) sun_retrieval_dict['az_width_v'] = np.ma.asarray( sun_retrieval_v[4]) sun_retrieval_dict['el_width_v'] = np.ma.asarray( sun_retrieval_v[5]) sun_retrieval_dict['nhits_v'] = np.ma.asarray(sun_retrieval_v[6]) sun_retrieval_dict['par_v'] = np.ma.asarray(sun_retrieval_v[7]) sun_retrieval_dict['lant'] = np.ma.asarray(lant) sun_hits_dict = { 'time': sun_hits['time'], 'ray': sun_hits['ray'], 'NPrng': sun_hits['NPrng'], 'nhits': sun_hits['nhits'], 'rad_el': sun_hits['rad_el'], 'rad_az': sun_hits['rad_az'], 'sun_el': sun_hits['sun_el'], 'sun_az': sun_hits['sun_az']} sunscan_dataset = dict() sunscan_dataset.update({'sun_hits': sun_hits_dict}) sunscan_dataset.update({'sun_retrieval': sun_retrieval_dict}) sunscan_dataset.update({'field_name': get_fieldname_pyart(datatype)}) sunscan_dataset.update({'radar_out': radar}) sunscan_dataset.update({'timeinfo': dscfg['global_data']['timeinfo']}) return sunscan_dataset, ind_rad

40.942274

99

0.591701

11,609

92,202

4.452321

0.051253

0.016561

0.02639

0.012827

0.858417

0.832569

0.805077

0.782905

0.767756

0.75549

0

0.010323

0.309744

92,202

2,251

100

40.960462

0.801816

0.215624

0

0.741891

1

0

0.163309

0.006673

0

1

0.005521

false

0

0.011042

0

0.062802

0

null

0

1

0

1

0

null

0

8

1b8768b911c190a2b2e1e153d2df5bfd5ab9af13

44,438

py

Python

learning_transforms/old/learning_fft_old.py

sfox14/butterfly

13cc15cee5bdb7adaf376219aaf20fab0459e9ef

[ "Apache-2.0" ]

52

2020-08-05T08:32:24.000Z

2022-03-27T21:56:34.000Z

learning_transforms/old/learning_fft_old.py

sfox14/butterfly

13cc15cee5bdb7adaf376219aaf20fab0459e9ef

[ "Apache-2.0" ]

13

2020-09-14T23:34:32.000Z

2022-02-15T10:51:03.000Z

learning_transforms/old/learning_fft_old.py

sfox14/butterfly

13cc15cee5bdb7adaf376219aaf20fab0459e9ef

[ "Apache-2.0" ]

11

2020-10-15T07:03:25.000Z

2022-03-25T12:03:49.000Z

import argparse import math import multiprocessing as mp import os from pathlib import Path import pickle import random import sys import numpy as np import torch from torch import nn from torch import optim from sacred import Experiment from sacred.observers import FileStorageObserver, SlackObserver import ray from ray.tune import Trainable, Experiment as RayExperiment, sample_from, run_experiments from ray.tune.schedulers import AsyncHyperBandScheduler from butterfly import Butterfly, ButterflyProduct, sinkhorn, Block2x2DiagProduct, BlockPermProduct from semantic_loss import semantic_loss_exactly_one from utils import PytorchTrainable, bitreversal_permutation from complex_utils import real_to_complex, complex_matmul N_LBFGS_STEPS = 300 N_LBFGS_STEPS_VALIDATION = 15 N_TRIALS_TO_POLISH = 60 def fft_test(): # DFT matrix for n = 4 size = 4 DFT = torch.fft(real_to_complex(torch.eye(size)), 1) P = torch.stack((torch.tensor([[1., 0., 0., 0.], [0., 0., 1., 0.], [0., 1., 0., 0.], [0., 0., 0., 1.]]), torch.zeros((size, size))), dim=-1) M0 = Butterfly(size, diagonal=2, complex=True, diag=torch.tensor([[1.0, 0.0], [1.0, 0.0], [-1.0, 0.0], [0.0, 1.0]], requires_grad=True), subdiag=torch.tensor([[1.0, 0.0], [1.0, 0.0]], requires_grad=True), superdiag=torch.tensor([[1.0, 0.0], [0.0, -1.0]], requires_grad=True)) M1 = Butterfly(size, diagonal=1, complex=True, diag=torch.tensor([[1.0, 0.0], [-1.0, 0.0], [1.0, 0.0], [-1.0, 0.0]], requires_grad=True), subdiag=torch.tensor([[1.0, 0.0], [0.0, 0.0], [1.0, 0.0]], requires_grad=True), superdiag=torch.tensor([[1.0, 0.0], [0.0, 0.0], [1.0, 0.0]], requires_grad=True)) assert torch.allclose(complex_matmul(M0.matrix(), complex_matmul(M1.matrix(), P)), DFT) br_perm = torch.tensor(bitreversal_permutation(size)) assert torch.allclose(complex_matmul(M0.matrix(), M1.matrix())[:, br_perm], DFT) D = complex_matmul(DFT, P.transpose(0, 1)) assert torch.allclose(complex_matmul(M0.matrix(), M1.matrix()), D) class TrainableFftFactorFixedOrder(PytorchTrainable): def _setup(self, config): size = config['size'] torch.manual_seed(config['seed']) self.model = ButterflyProduct(size=size, complex=True, fixed_order=True) self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size)), 1) self.br_perm = torch.tensor(bitreversal_permutation(size)) def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix()[:, self.br_perm] loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftFactorSoftmax(PytorchTrainable): def _setup(self, config): size = config['size'] torch.manual_seed(config['seed']) self.model = ButterflyProduct(size=size, complex=True, fixed_order=False) self.semantic_loss_weight = config['semantic_loss_weight'] self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size)), 1) self.br_perm = torch.tensor(bitreversal_permutation(size)) def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix()[:, self.br_perm] loss = nn.functional.mse_loss(y, self.target_matrix) semantic_loss = semantic_loss_exactly_one(nn.functional.log_softmax(self.model.logit, dim=-1)) total_loss = loss + self.semantic_loss_weight * semantic_loss.mean() total_loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftFactorSparsemax(TrainableFftFactorFixedOrder): def _setup(self, config): size = config['size'] torch.manual_seed(config['seed']) self.model = ButterflyProduct(size=size, complex=True, fixed_order=False, softmax_fn='sparsemax') self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size)), 1) self.br_perm = torch.tensor(bitreversal_permutation(size)) class TrainableFftFactorSparsemaxNoPerm(TrainableFftFactorSparsemax): def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix() loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftFactorSoftmaxNoPerm(TrainableFftFactorSoftmax): def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix() loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableRandnFactorSoftmaxNoPerm(PytorchTrainable): def _setup(self, config): size = config['size'] torch.manual_seed(config['seed']) self.model = ButterflyProduct(size=size, complex=False, fixed_order=False, softmax_fn='softmax') self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] self.target_matrix = torch.rand(size, size, requires_grad=False) def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix() loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftFactorSparsemaxPermFront(TrainableFftFactorSparsemax): def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix()[self.br_perm, :] loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} def fft_factorization_fixed_order(argv): parser = argparse.ArgumentParser(description='Learn to factor Fft matrix') parser.add_argument('--size', type=int, default=8, help='Size of matrix to factor, must be power of 2') parser.add_argument('--ntrials', type=int, default=20, help='Number of trials for hyperparameter tuning') parser.add_argument('--nsteps', type=int, default=200, help='Number of steps per epoch') parser.add_argument('--nmaxepochs', type=int, default=200, help='Maximum number of epochs') parser.add_argument('--result-dir', type=str, default='./results', help='Directory to store results') parser.add_argument('--nthreads', type=int, default=1, help='Number of CPU threads per job') parser.add_argument('--smoke-test', action='store_true', help='Finish quickly for testing') args = parser.parse_args(argv) experiment = RayExperiment( name=f'Fft_factorization_fixed_order_{args.size}', run=TrainableFftFactorFixedOrder, local_dir=args.result_dir, num_samples=args.ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': args.nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if args.smoke_test else 99999, 'negative_loss': -1e-8 }, config={ 'size': args.size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': args.nsteps, }, ) return experiment, args def fft_factorization_softmax(argv): parser = argparse.ArgumentParser(description='Learn to factor Fft matrix') parser.add_argument('--size', type=int, default=8, help='Size of matrix to factor, must be power of 2') parser.add_argument('--ntrials', type=int, default=20, help='Number of trials for hyperparameter tuning') parser.add_argument('--nsteps', type=int, default=200, help='Number of steps per epoch') parser.add_argument('--nmaxepochs', type=int, default=200, help='Maximum number of epochs') parser.add_argument('--result-dir', type=str, default='./results', help='Directory to store results') parser.add_argument('--nthreads', type=int, default=1, help='Number of CPU threads per job') parser.add_argument('--smoke-test', action='store_true', help='Finish quickly for testing') args = parser.parse_args(argv) experiment = RayExperiment( name=f'Fft_factorization_softmax_{args.size}', run=TrainableFftFactorSoftmax, local_dir=args.result_dir, num_samples=args.ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': args.nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if args.smoke_test else 99999, 'is_nan': True, 'negative_loss': -1e-8 }, config={ 'size': args.size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'semantic_loss_weight': sample_from(lambda spec: math.exp(random.uniform(math.log(5e-4), math.log(5e-1)))), 'n_steps_per_epoch': args.nsteps, }, ) return experiment, args def fft_factorization_sparsemax(argv): parser = argparse.ArgumentParser(description='Learn to factor Fft matrix') parser.add_argument('--size', type=int, default=8, help='Size of matrix to factor, must be power of 2') parser.add_argument('--ntrials', type=int, default=20, help='Number of trials for hyperparameter tuning') parser.add_argument('--nsteps', type=int, default=200, help='Number of steps per epoch') parser.add_argument('--nmaxepochs', type=int, default=200, help='Maximum number of epochs') parser.add_argument('--result-dir', type=str, default='./results', help='Directory to store results') parser.add_argument('--nthreads', type=int, default=1, help='Number of CPU threads per job') parser.add_argument('--smoke-test', action='store_true', help='Finish quickly for testing') args = parser.parse_args(argv) experiment = RayExperiment( name=f'Fft_factorization_sparsemax_{args.size}', run=TrainableFftFactorSparsemax, local_dir=args.result_dir, num_samples=args.ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': args.nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if args.smoke_test else 99999, 'negative_loss': -1e-8 }, config={ 'size': args.size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': args.nsteps, }, ) return experiment, args def fft_factorization_sparsemax_no_perm(argv): parser = argparse.ArgumentParser(description='Learn to factor Fft matrix') parser.add_argument('--size', type=int, default=8, help='Size of matrix to factor, must be power of 2') parser.add_argument('--ntrials', type=int, default=20, help='Number of trials for hyperparameter tuning') parser.add_argument('--nsteps', type=int, default=200, help='Number of steps per epoch') parser.add_argument('--nmaxepochs', type=int, default=200, help='Maximum number of epochs') parser.add_argument('--result-dir', type=str, default='./results', help='Directory to store results') parser.add_argument('--nthreads', type=int, default=1, help='Number of CPU threads per job') parser.add_argument('--smoke-test', action='store_true', help='Finish quickly for testing') args = parser.parse_args(argv) experiment = RayExperiment( name=f'Fft_factorization_sparsemax_no_perm_{args.size}', run=TrainableFftFactorSparsemaxNoPerm, local_dir=args.result_dir, num_samples=args.ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': args.nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if args.smoke_test else 99999, 'negative_loss': -1e-8 }, config={ 'size': args.size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': args.nsteps, }, ) return experiment, args def fft_factorization_softmax_no_perm(argv): parser = argparse.ArgumentParser(description='Learn to factor Fft matrix') parser.add_argument('--size', type=int, default=8, help='Size of matrix to factor, must be power of 2') parser.add_argument('--ntrials', type=int, default=20, help='Number of trials for hyperparameter tuning') parser.add_argument('--nsteps', type=int, default=200, help='Number of steps per epoch') parser.add_argument('--nmaxepochs', type=int, default=200, help='Maximum number of epochs') parser.add_argument('--result-dir', type=str, default='./results', help='Directory to store results') parser.add_argument('--nthreads', type=int, default=1, help='Number of CPU threads per job') parser.add_argument('--smoke-test', action='store_true', help='Finish quickly for testing') args = parser.parse_args(argv) experiment = RayExperiment( name=f'Fft_factorization_softmax_no_perm_{args.size}', run=TrainableFftFactorSoftmaxNoPerm, local_dir=args.result_dir, num_samples=args.ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': args.nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if args.smoke_test else 99999, 'negative_loss': -1e-8 }, config={ 'size': args.size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': args.nsteps, }, ) return experiment, args def randn_factorization_softmax_no_perm(argv): parser = argparse.ArgumentParser(description='Learn to factor Fft matrix') parser.add_argument('--size', type=int, default=8, help='Size of matrix to factor, must be power of 2') parser.add_argument('--ntrials', type=int, default=20, help='Number of trials for hyperparameter tuning') parser.add_argument('--nsteps', type=int, default=200, help='Number of steps per epoch') parser.add_argument('--nmaxepochs', type=int, default=200, help='Maximum number of epochs') parser.add_argument('--result-dir', type=str, default='./results', help='Directory to store results') parser.add_argument('--nthreads', type=int, default=1, help='Number of CPU threads per job') parser.add_argument('--smoke-test', action='store_true', help='Finish quickly for testing') args = parser.parse_args(argv) experiment = RayExperiment( name=f'Randn_factorization_softmax_no_perm_{args.size}', run=TrainableRandnFactorSoftmaxNoPerm, local_dir=args.result_dir, num_samples=args.ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': args.nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if args.smoke_test else 99999, 'negative_loss': -1e-8 }, config={ 'size': args.size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': args.nsteps, }, ) return experiment, args def fft_factorization_sparsemax_perm_front(argv): parser = argparse.ArgumentParser(description='Learn to factor Fft matrix') parser.add_argument('--size', type=int, default=8, help='Size of matrix to factor, must be power of 2') parser.add_argument('--ntrials', type=int, default=20, help='Number of trials for hyperparameter tuning') parser.add_argument('--nsteps', type=int, default=200, help='Number of steps per epoch') parser.add_argument('--nmaxepochs', type=int, default=200, help='Maximum number of epochs') parser.add_argument('--result-dir', type=str, default='./results', help='Directory to store results') parser.add_argument('--nthreads', type=int, default=1, help='Number of CPU threads per job') parser.add_argument('--smoke-test', action='store_true', help='Finish quickly for testing') args = parser.parse_args(argv) experiment = RayExperiment( name=f'Fft_factorization_sparsemax_perm_front_{args.size}', run=TrainableFftFactorSparsemaxPermFront, local_dir=args.result_dir, num_samples=args.ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': args.nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if args.smoke_test else 99999, 'negative_loss': -1e-8 }, config={ 'size': args.size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': args.nsteps, }, ) return experiment, args # if __name__ == '__main__': # # experiment, args = fft_factorization_fixed_order(sys.argv[1:]) # experiment, args = fft_factorization_softmax(sys.argv[1:]) # # experiment, args = fft_factorization_sparsemax(sys.argv[1:]) # # experiment, args = fft_factorization_sparsemax_no_perm(sys.argv[1:]) # # experiment, args = fft_factorization_softmax_no_perm(sys.argv[1:]) # # experiment, args = randn_factorization_softmax_no_perm(sys.argv[1:]) # # experiment, args = fft_factorization_sparsemax_perm_front(sys.argv[1:]) # # We'll use multiple processes so disable MKL multithreading # os.environ['MKL_NUM_THREADS'] = str(args.nthreads) # ray.init() # ahb = AsyncHyperBandScheduler(reward_attr='negative_loss', max_t=args.nmaxepochs) # trials = run_experiments(experiment, scheduler=ahb) # losses = [-trial.last_result['negative_loss'] for trial in trials] # print(np.array(losses)) # print(np.sort(losses)) # checkpoint_path = Path(args.result_dir) / experiment.name # checkpoint_path.mkdir(parents=True, exist_ok=True) # checkpoint_path /= 'trial.pkl' # with checkpoint_path.open('wb') as f: # pickle.dump(trials, f) class TrainableFft(PytorchTrainable): def _setup(self, config): torch.manual_seed(config['seed']) self.model = ButterflyProduct(size=config['size'], complex=True, fixed_order=config['fixed_order'], softmax_fn=config['softmax_fn']) if (not config['fixed_order']) and config['softmax_fn'] == 'softmax': self.semantic_loss_weight = config['semantic_loss_weight'] self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] size = config['size'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size)), 1) self.br_perm = torch.tensor(bitreversal_permutation(size)) # br_perm = bitreversal_permutation(size) # br_reverse = torch.tensor(list(br_perm[::-1])) # br_reverse = torch.cat((torch.tensor(list(br_perm[:size//2][::-1])), torch.tensor(list(br_perm[size//2:][::-1])))) # Same as [6, 2, 4, 0, 7, 3, 5, 1], which is [0, 1]^4 * [0, 2, 1, 3]^2 * [6, 4, 2, 0, 7, 5, 3, 1] # br_reverse = torch.cat((torch.tensor(list(br_perm[:size//4][::-1])), torch.tensor(list(br_perm[size//4:size//2][::-1])), torch.tensor(list(br_perm[size//2:3*size//4][::-1])), torch.tensor(list(br_perm[3*size//4:][::-1])))) # self.br_perm = br_reverse # self.br_perm = torch.tensor([0, 7, 4, 3, 2, 5, 6, 1]) # Doesn't work # self.br_perm = torch.tensor([7, 3, 0, 4, 2, 6, 5, 1]) # Doesn't work # self.br_perm = torch.tensor([4, 0, 6, 2, 5, 1, 7, 3]) # This works, [0, 1]^4 * [2, 0, 3, 1]^2 * [0, 2, 4, 6, 1, 3, 5, 7] or [1, 0]^4 * [0, 2, 1, 3]^2 * [0, 2, 4, 6, 1, 3, 5, 7] # self.br_perm = torch.tensor([4, 0, 2, 6, 5, 1, 3, 7]) # Doesn't work, [0, 1]^4 * [2, 0, 1, 3]^2 * [0, 2, 4, 6, 1, 3, 5, 7] # self.br_perm = torch.tensor([1, 5, 3, 7, 0, 4, 2, 6]) # This works, [0, 1]^4 * [4, 6, 5, 7, 0, 4, 2, 6] # self.br_perm = torch.tensor([4, 0, 6, 2, 5, 1, 3, 7]) # Doesn't work # self.br_perm = torch.tensor([4, 0, 6, 2, 1, 5, 3, 7]) # Doesn't work # self.br_perm = torch.tensor([0, 4, 6, 2, 1, 5, 7, 3]) # Doesn't work # self.br_perm = torch.tensor([4, 1, 6, 2, 5, 0, 7, 3]) # This works, since it's just swapping 0 and 1 # self.br_perm = torch.tensor([5, 1, 6, 2, 4, 0, 7, 3]) # This works, since it's swapping 4 and 5 def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix()[:, self.br_perm] loss = nn.functional.mse_loss(y, self.target_matrix) if (not self.model.fixed_order) and hasattr(self, 'semantic_loss_weight'): semantic_loss = semantic_loss_exactly_one(nn.functional.log_softmax(self.model.logit, dim=-1)) loss += self.semantic_loss_weight * semantic_loss.mean() loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftBlock2x2(PytorchTrainable): def _setup(self, config): torch.manual_seed(config['seed']) self.model = Block2x2DiagProduct(size=config['size'], complex=True) self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] size = config['size'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size)), 1) self.br_perm = torch.tensor(bitreversal_permutation(size)) self.input = real_to_complex(torch.eye(size))[:, self.br_perm] def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model(self.input) loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftBlockPerm(PytorchTrainable): def _setup(self, config): torch.manual_seed(config['seed']) self.model = nn.Sequential( BlockPermProduct(size=config['size'], complex=True, share_logit=False), Block2x2DiagProduct(size=config['size'], complex=True) ) self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] size = config['size'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size))) # self.target_matrix = size * torch.ifft(real_to_complex(torch.eye(size))) self.input = real_to_complex(torch.eye(size)) def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model(self.input) loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftBlockPermTranspose(TrainableFftBlockPerm): def _setup(self, config): torch.manual_seed(config['seed']) self.model = nn.Sequential( Block2x2DiagProduct(size=config['size'], complex=True, decreasing_size=False), BlockPermProduct(size=config['size'], complex=True, share_logit=False, increasing_size=True), ) self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] size = config['size'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size)), 1) self.input = real_to_complex(torch.eye(size)) def _train(self): for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model(self.input) loss = nn.functional.mse_loss(y, self.target_matrix) loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftTempAnnealing(TrainableFft): def _train(self): temperature = 1.0 / (0.1 * self._iteration + 1) for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix(temperature)[:, self.br_perm] loss = nn.functional.mse_loss(y, self.target_matrix) if (not self.model.fixed_order) and hasattr(self, 'semantic_loss_weight'): semantic_loss = semantic_loss_exactly_one(nn.functional.log_softmax(self.model.logit, dim=-1)) loss += self.semantic_loss_weight * semantic_loss.mean() loss.backward() self.optimizer.step() return {'negative_loss': -loss.item()} class TrainableFftLearnPerm(PytorchTrainable): def _setup(self, config): torch.manual_seed(config['seed']) self.model = ButterflyProduct(size=config['size'], complex=True, fixed_order=config['fixed_order'], softmax_fn=config['softmax_fn'], learn_perm=True) if (not config['fixed_order']) and config['softmax_fn'] == 'softmax': self.semantic_loss_weight = config['semantic_loss_weight'] self.optimizer = optim.Adam(self.model.parameters(), lr=config['lr']) self.n_steps_per_epoch = config['n_steps_per_epoch'] size = config['size'] self.target_matrix = torch.fft(real_to_complex(torch.eye(size)), 1) def _train(self): temperature = 1.0 / (0.3 * self._iteration + 1) for _ in range(self.n_steps_per_epoch): self.optimizer.zero_grad() y = self.model.matrix(temperature) loss = nn.functional.mse_loss(y, self.target_matrix) if (not self.model.fixed_order) and hasattr(self, 'semantic_loss_weight'): semantic_loss = semantic_loss_exactly_one(nn.functional.log_softmax(self.model.logit, dim=-1)) loss += self.semantic_loss_weight * semantic_loss.mean() loss.backward() self.optimizer.step() return {'negative_loss': -polished_loss_fft_learn_perm(self)} def polish_fft(trial): """Load model from checkpoint, then fix the order of the factor matrices (using the largest logits), and re-optimize using L-BFGS to find the nearest local optima. """ trainable = eval(trial.trainable_name)(trial.config) trainable.restore(str(Path(trial.logdir) / trial._checkpoint.value)) model = trainable.model config = trial.config polished_model = ButterflyProduct(size=config['size'], complex=model.complex, fixed_order=True) if not model.fixed_order: prob = model.softmax_fn(model.logit) maxes, argmaxes = torch.max(prob, dim=-1) polished_model.factors = nn.ModuleList([model.factors[argmax] for argmax in argmaxes]) else: polished_model.factors = model.factors optimizer = optim.LBFGS(polished_model.parameters()) def closure(): optimizer.zero_grad() loss = nn.functional.mse_loss(polished_model.matrix()[:, trainable.br_perm], trainable.target_matrix) loss.backward() return loss for i in range(N_LBFGS_STEPS): optimizer.step(closure) torch.save(polished_model.state_dict(), str((Path(trial.logdir) / trial._checkpoint.value).parent / 'polished_model.pth')) loss = nn.functional.mse_loss(polished_model.matrix()[:, trainable.br_perm], trainable.target_matrix) return loss.item() def polish_fft_learn_perm(trial): """Load model from checkpoint, then fix the order of the factor matrices (using the largest logits), and re-optimize using L-BFGS to find the nearest local optima. """ trainable = eval(trial.trainable_name)(trial.config) trainable.restore(str(Path(trial.logdir) / trial._checkpoint.value)) model = trainable.model config = trial.config polished_model = ButterflyProduct(size=config['size'], complex=model.complex, fixed_order=True) temperature = 1.0 / (0.3 * trainable._iteration + 1) trainable.perm = torch.argmax(sinkhorn(model.perm_logit / temperature), dim=1) if not model.fixed_order: prob = model.softmax_fn(model.logit) maxes, argmaxes = torch.max(prob, dim=-1) polished_model.factors = nn.ModuleList([model.factors[argmax] for argmax in argmaxes]) else: polished_model.factors = model.factors optimizer = optim.LBFGS(polished_model.parameters()) def closure(): optimizer.zero_grad() loss = nn.functional.mse_loss(polished_model.matrix()[:, trainable.perm], trainable.target_matrix) loss.backward() return loss for i in range(N_LBFGS_STEPS): optimizer.step(closure) torch.save(polished_model.state_dict(), str((Path(trial.logdir) / trial._checkpoint.value).parent / 'polished_model.pth')) loss = nn.functional.mse_loss(polished_model.matrix()[:, trainable.perm], trainable.target_matrix) return loss.item() def polished_loss_fft_learn_perm(trainable): model = trainable.model polished_model = ButterflyProduct(size=model.size, complex=model.complex, fixed_order=True) temperature = 1.0 / (0.3 * trainable._iteration + 1) trainable.perm = torch.argmax(sinkhorn(model.perm_logit / temperature), dim=1) if not model.fixed_order: prob = model.softmax_fn(model.logit) maxes, argmaxes = torch.max(prob, dim=-1) polished_model.factors = nn.ModuleList([model.factors[argmax] for argmax in argmaxes]) else: polished_model.factors = model.factors preopt_loss = nn.functional.mse_loss(polished_model.matrix()[:, trainable.perm], trainable.target_matrix) optimizer = optim.LBFGS(polished_model.parameters()) def closure(): optimizer.zero_grad() loss = nn.functional.mse_loss(polished_model.matrix()[:, trainable.perm], trainable.target_matrix) loss.backward() return loss for i in range(N_LBFGS_STEPS_VALIDATION): optimizer.step(closure) loss = nn.functional.mse_loss(polished_model.matrix()[:, trainable.perm], trainable.target_matrix) # return loss.item() if not torch.isnan(loss) else preopt_loss.item() if not torch.isnan(preopt_loss) else float('inf') return loss.item() if not torch.isnan(loss) else preopt_loss.item() if not torch.isnan(preopt_loss) else 9999.0 def polish_fft_block2x2(trial): """Load model from checkpoint, then fix the order of the factor matrices (using the largest logits), and re-optimize using L-BFGS to find the nearest local optima. """ trainable = eval(trial.trainable_name)(trial.config) trainable.restore(str(Path(trial.logdir) / trial._checkpoint.value)) model = trainable.model config = trial.config polished_model = Block2x2DiagProduct(size=config['size'], complex=model.complex) polished_model.factors = model.factors optimizer = optim.LBFGS(polished_model.parameters()) def closure(): optimizer.zero_grad() loss = nn.functional.mse_loss(polished_model(trainable.input), trainable.target_matrix) loss.backward() return loss for i in range(N_LBFGS_STEPS): optimizer.step(closure) torch.save(polished_model.state_dict(), str((Path(trial.logdir) / trial._checkpoint.value).parent / 'polished_model.pth')) loss = nn.functional.mse_loss(polished_model(trainable.input), trainable.target_matrix) return loss.item() def polish_fft_blockperm(trial): """Load model from checkpoint, then fix the order of the factor matrices (using the largest logits), and re-optimize using L-BFGS to find the nearest local optima. """ trainable = eval(trial.trainable_name)(trial.config) trainable.restore(str(Path(trial.logdir) / trial._checkpoint.value)) model = trainable.model config = trial.config perm = model[0].argmax() polished_model = Block2x2DiagProduct(size=config['size'], complex=True) polished_model.load_state_dict(model[1].state_dict()) optimizer = optim.LBFGS(polished_model.parameters()) def closure(): optimizer.zero_grad() loss = nn.functional.mse_loss(polished_model(trainable.input[:, perm]), trainable.target_matrix) loss.backward() return loss for i in range(N_LBFGS_STEPS): optimizer.step(closure) torch.save(polished_model.state_dict(), str((Path(trial.logdir) / trial._checkpoint.value).parent / 'polished_model.pth')) loss = nn.functional.mse_loss(polished_model(trainable.input[:, perm]), trainable.target_matrix) return loss.item() def polish_fft_blockperm_transpose(trial): """Load model from checkpoint, then fix the order of the factor matrices (using the largest logits), and re-optimize using L-BFGS to find the nearest local optima. """ trainable = eval(trial.trainable_name)(trial.config) trainable.restore(str(Path(trial.logdir) / trial._checkpoint.value)) model = trainable.model config = trial.config perm = model[1].argmax() polished_model = Block2x2DiagProduct(size=config['size'], complex=True, decreasing_size=False) polished_model.load_state_dict(model[0].state_dict()) optimizer = optim.LBFGS(polished_model.parameters()) def closure(): optimizer.zero_grad() loss = nn.functional.mse_loss(polished_model(trainable.input)[:, perm], trainable.target_matrix) loss.backward() return loss for i in range(N_LBFGS_STEPS): optimizer.step(closure) torch.save(polished_model.state_dict(), str((Path(trial.logdir) / trial._checkpoint.value).parent / 'polished_model.pth')) loss = nn.functional.mse_loss(polished_model(trainable.input)[:, perm], trainable.target_matrix) return loss.item() ex = Experiment('Fft_factorization') ex.observers.append(FileStorageObserver.create('logs')) slack_config_path = Path('config/slack.json') # Add webhook_url there for Slack notification if slack_config_path.exists(): ex.observers.append(SlackObserver.from_config(str(slack_config_path))) @ex.named_config def softmax_config(): fixed_order = False # Whether the order of the factors are fixed softmax_fn = 'softmax' # Whether to use softmax (+ semantic loss) or sparsemax @ex.named_config def sparsemax_config(): fixed_order = False # Whether the order of the factors are fixed softmax_fn = 'sparsemax' # Whether to use softmax (+ semantic loss) or sparsemax @ex.config def fixed_order_config(): fixed_order = True # Whether the order of the factors are fixed softmax_fn = 'softmax' # Whether to use softmax (+ semantic loss) or sparsemax size = 8 # Size of matrix to factor, must be power of 2 ntrials = 20 # Number of trials for hyperparameter tuning nsteps = 400 # Number of steps per epoch nmaxepochs = 200 # Maximum number of epochs result_dir = 'results' # Directory to store results nthreads = 1 # Number of CPU threads per job smoke_test = False # Finish quickly for testing @ex.capture def fft_experiment(fixed_order, softmax_fn, size, ntrials, nsteps, result_dir, nthreads, smoke_test): assert softmax_fn in ['softmax', 'sparsemax'] config={ 'fixed_order': fixed_order, 'softmax_fn': softmax_fn, 'size': size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': nsteps, } if (not fixed_order) and softmax_fn == 'softmax': config['semantic_loss_weight'] = sample_from(lambda spec: math.exp(random.uniform(math.log(5e-3), math.log(5e-1)))) experiment = RayExperiment( name=f'Fft_factorization_{fixed_order}_{softmax_fn}_{size}', run=TrainableFft, local_dir=result_dir, num_samples=ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if smoke_test else 99999, 'negative_loss': -1e-8 }, config=config, ) return experiment @ex.capture def fft_experiment_temp_annealing(fixed_order, softmax_fn, size, ntrials, nsteps, result_dir, nthreads, smoke_test): assert softmax_fn in ['softmax', 'sparsemax'] config={ 'fixed_order': fixed_order, 'softmax_fn': softmax_fn, 'size': size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': nsteps, } if (not fixed_order) and softmax_fn == 'softmax': config['semantic_loss_weight'] = sample_from(lambda spec: math.exp(random.uniform(math.log(5e-3), math.log(5e-1)))) experiment = RayExperiment( name=f'Fft_factorization_Temp_{fixed_order}_{softmax_fn}_{size}', run=TrainableFftTempAnnealing, local_dir=result_dir, num_samples=ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if smoke_test else 99999, 'negative_loss': -1e-8 }, config=config, ) return experiment @ex.capture def fft_experiment_learn_perm(fixed_order, softmax_fn, size, ntrials, nsteps, result_dir, nthreads, smoke_test): assert softmax_fn in ['softmax', 'sparsemax'] config={ 'fixed_order': fixed_order, 'softmax_fn': softmax_fn, 'size': size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': nsteps, } if (not fixed_order) and softmax_fn == 'softmax': config['semantic_loss_weight'] = sample_from(lambda spec: math.exp(random.uniform(math.log(5e-3), math.log(5e-1)))) experiment = RayExperiment( name=f'Fft_factorization_Learnperm_{fixed_order}_{softmax_fn}_{size}', run=TrainableFftLearnPerm, local_dir=result_dir, num_samples=ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if smoke_test else 99999, # 'negative_loss': -1e-8 }, config=config, ) return experiment @ex.capture def fft_experiment_block2x2(size, ntrials, nsteps, result_dir, nthreads, smoke_test): config={ 'size': size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': nsteps, } experiment = RayExperiment( name=f'Fft_factorization_block_{size}', run=TrainableFftBlock2x2, local_dir=result_dir, num_samples=ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if smoke_test else 99999, 'negative_loss': -1e-8 }, config=config, ) return experiment @ex.capture def fft_experiment_blockperm(size, ntrials, nsteps, result_dir, nthreads, smoke_test): config={ 'size': size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': nsteps, } experiment = RayExperiment( name=f'Fft_factorization_block_perm_{size}', run=TrainableFftBlockPerm, local_dir=result_dir, num_samples=ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if smoke_test else 99999, 'negative_loss': -1e-8 }, config=config, ) return experiment @ex.capture def fft_experiment_blockperm_transpose(size, ntrials, nsteps, result_dir, nthreads, smoke_test): config={ 'size': size, 'lr': sample_from(lambda spec: math.exp(random.uniform(math.log(1e-4), math.log(5e-1)))), 'seed': sample_from(lambda spec: random.randint(0, 1 << 16)), 'n_steps_per_epoch': nsteps, } experiment = RayExperiment( name=f'Fft_factorization_block_perm_transpose_{size}', run=TrainableFftBlockPermTranspose, local_dir=result_dir, num_samples=ntrials, checkpoint_at_end=True, resources_per_trial={'cpu': nthreads, 'gpu': 0}, stop={ 'training_iteration': 1 if smoke_test else 99999, 'negative_loss': -1e-8 }, config=config, ) return experiment @ex.automain def run(result_dir, nmaxepochs, nthreads): # experiment = fft_experiment() # experiment = fft_experiment_temp_annealing() # experiment = fft_experiment_learn_perm() # experiment = fft_experiment_block2x2() # experiment = fft_experiment_blockperm() experiment = fft_experiment_blockperm_transpose() # We'll use multiple processes so disable MKL multithreading os.environ['MKL_NUM_THREADS'] = str(nthreads) ray.init() ahb = AsyncHyperBandScheduler(reward_attr='negative_loss', max_t=nmaxepochs) trials = run_experiments(experiment, scheduler=ahb, raise_on_failed_trial=False) losses = [-trial.last_result['negative_loss'] for trial in trials] # Polish solutions with L-BFGS pool = mp.Pool() sorted_trials = sorted(trials, key=lambda trial: -trial.last_result['negative_loss']) # polished_losses = pool.map(polish_fft, sorted_trials[:N_TRIALS_TO_POLISH]) # polished_losses = pool.map(polish_fft_learn_perm, sorted_trials[:N_TRIALS_TO_POLISH]) # polished_losses = pool.map(polish_fft_block2x2, sorted_trials[:N_TRIALS_TO_POLISH]) # polished_losses = pool.map(polish_fft_blockperm, sorted_trials[:N_TRIALS_TO_POLISH]) polished_losses = pool.map(polish_fft_blockperm_transpose, sorted_trials[:N_TRIALS_TO_POLISH]) pool.close() pool.join() for i in range(min(N_TRIALS_TO_POLISH, len(trials))): sorted_trials[i].last_result['polished_negative_loss'] = -polished_losses[i] print(np.array(losses)) print(np.sort(losses)) # print(np.sort(losses)[:N_TRIALS_TO_POLISH]) print(np.sort(polished_losses)) checkpoint_path = Path(result_dir) / experiment.name checkpoint_path.mkdir(parents=True, exist_ok=True) checkpoint_path /= 'trial.pkl' with checkpoint_path.open('wb') as f: pickle.dump(trials, f) ex.add_artifact(str(checkpoint_path)) return min(losses + polished_losses) polished_losses = [-trial.last_result['polished_negative_loss'] for trial in sorted_trials[:N_TRIALS_TO_POLISH]]

45.67112

232

0.658963

5,793

44,438

4.865527

0.06059

0.003761

0.023522

0.021358

0.880614

0.866423

0.854006

0.840417

0.827148

0.80022

0

0.019893

0.210428

44,438

972

233

45.718107

0.783424

0.110198

0

0.712834

0

0.123936

0.015952

0

0.007624

1

0.064803

false

0

0.026684

0

0.15629

0.003812

0

null

0

1

0

1

0

null

0

7

1baeb4e4f961bb326e4656baa42511752cafda93

474

py

Python

cm/app/helper.py

HotMaps/test_repo

3bb84386f08631af904b59f440611bf312082c7c

[ "Apache-2.0" ]

null

cm/app/helper.py

HotMaps/test_repo

3bb84386f08631af904b59f440611bf312082c7c

[ "Apache-2.0" ]

null

cm/app/helper.py

HotMaps/test_repo

3bb84386f08631af904b59f440611bf312082c7c

[ "Apache-2.0" ]

null

import uuid def generate_output_file_tif(output_directory): return generate_output_file_with_extension(output_directory,'.tif') def generate_output_file_shp(output_directory): return generate_output_file_with_extension(output_directory, '.shp') def generate_output_file_with_extension(output_directory,extension): filename = str(uuid.uuid4()) + extension output_raster_path = output_directory+'/'+filename # output raster return output_raster_path

31.6

72

0.814346

60

474

5.966667

0.283333

0.251397

0.175978

0.502793

0.374302

0

0.00237

0.109705

474

15

73

31.6

0.845972

0.027426

0

1

0

0.019565

0

1

0.333333

false

0

0.111111

0.222222

0.777778

0

null

1

0

1

0

null

0

1

0

1

0

7

1bbf246af1bbfa9dd3f13c4783ec59785c82ed17

61,514

py

Python

mmu/methods/prpoint.py

RUrlus/ModelMetricUncertainty

f401a25dd196d6e4edf4901fcfee4b56ebd7c10b

[ "Apache-2.0" ]

null

mmu/methods/prpoint.py

RUrlus/ModelMetricUncertainty

f401a25dd196d6e4edf4901fcfee4b56ebd7c10b

[ "Apache-2.0" ]

11

2021-12-08T10:34:17.000Z

2022-01-20T13:40:05.000Z

mmu/methods/prpoint.py

RUrlus/ModelMetricUncertainty

f401a25dd196d6e4edf4901fcfee4b56ebd7c10b

[ "Apache-2.0" ]

null

"""Module containing the API for the precision-recall uncertainty modelled through profile log likelihoods.""" import warnings from itertools import zip_longest from typing import Dict, List, Optional, Union import numpy as np import pandas as pd import scipy.stats as sts from mmu.commons import check_array from mmu.commons import _convert_to_int, _convert_to_float, _convert_to_ext_types from mmu.commons.checks import _check_n_threads from mmu.metrics.confmat import confusion_matrix from mmu.metrics.confmat import confusion_matrix_to_dataframe from mmu.metrics.confmat import confusion_matrices_to_dataframe from mmu.viz.ellipse import _plot_pr_ellipse from mmu.viz.contours import _plot_pr_contours from mmu.lib import _MMU_MT_SUPPORT import mmu.lib._mmu_core as _core class PrecisionRecallUncertainty: """Compute joint uncertainty Precision-Recall. The joint statistical uncertainty can be computed using: Multinomial method: Model's the uncertainty using profile log-likelihoods between the observed and most conservative confusion matrix for that precision-recall. Unlike the Bivariate-Normal/Elliptical approach, this approach is valid for relatively low statistic samples and at the edges of the curve. However, it does not allow one to add the training sample uncertainty to it. Bivariate Normal / Elliptical method: Model's the linearly propogated errors of the confusion matrix as a bivariate Normal distribution. Note that this method is not valid for low statistic sets or for precision/recall close to 1.0/0.0. In these scenarios the Multinomial method should be used. To incorporate the training uncertainty to the ``from_scores_with_train`` must be used which used the Bivariate/Elliptical approach. Attributes ---------- conf_mat : np.ndarray[int64] the confusion_matrix with layout [0, 0] = TN, [0, 1] = FP, [1, 0] = FN, [1, 1] = TP A DataFrame can be obtained by calling `get_conf_mat`. precision : float the Positive Predictive Value aka positive precision recall : float True Positive Rate aka Sensitivity aka positive recall threshold : float, optional the inclusive threshold used to determine the confusion matrix. Is None when the class is instantiated with `from_predictions` or `from_confusion_matrix`. cov_mat : np.ndarray[float64], optional the covariance matrix of precision and recall with layout [0, 0] = V[P], [0, 1] = COV[P, R], [1, 0] = COV[P, R], [1, 1] = V[R] A DataFrame can be obtained by calling `get_cov_mat`. **Only set when Bivariate/Elliptical method is used.** chi2_scores : np.ndarray[float64], optional the chi2 scores for the grid with shape (`n_bins`, `n_bins`) and bounds precision_bounds on the y-axis, recall_bounds on the x-axis **Only set when Multinomial method is used.** precision_bounds : np.ndarray[float64], optional the lower and upper bound for which precision was evaluated, equal to precision +- `n_sigmas` * sigma(precision) **Only set when Multinomial method is used.** recall_bounds : np.ndarray[float64], optional the lower and upper bound for which recall was evaluated, equal to recall +- `n_sigmas` * sigma(recall) **Only set when Multinomial method is used.** n_sigmas : int, float, optional the number of marginal standard deviations used to determine the bounds of the grid which is evaluated for each observed precision and recall. **Only set when Multinomial method is used.** epsilon : float, optional the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. **Only set when Multinomial method is used.** train_precisions : np.ndarray, optional precisions of the bootstrapped training runs **Only set when initialised with ``from_scores_with_train``.** train_recalls : np.ndarray, optional recalls of the bootstrapped training runs **Only set when initialised with ``from_scores_with_train``.** train_conf_mats : np.ndarray, optional the confusion matrices from the multiple training runs. A DataFrame can be obtained by calling `get_train_conf_mats` **Only set when initialised with ``from_scores_with_train``.** train_cov_mat : np.ndarray, optional the precision, recall covariance matrix from the multiple training runs. A DataFrame can be obtained by calling `get_train_cov_mat`. **Only set when initialised with ``from_scores_with_train``.** total_cov_mat : np.ndarray, optional the precision, recall covariance matrix that combines the test and training sampling uncertainty. **Only set when initialised with ``from_scores_with_train``.** """ def __init__(self): self.conf_mat = None self.precision = None self.recall = None self.cov_mat = None self.train_precisions = None self.train_recalls = None self.train_conf_mats = None self.train_cov_mat = None self.total_cov_mat = None self._bounds = None self.precision_bounds = None self.recall_bounds = None self.chi2_scores = None self.n_bins = None self.n_sigmas = None self.epsilon = None self._has_cov = False self._moptions = { 'mult': {'mult', 'multinomial'}, 'bvn': {'bvn', 'bivariate', 'elliptical'} } def _parse_threshold(self, threshold): if not isinstance(threshold, float) or not (0.0 < threshold < 1.0): raise TypeError("`threshold` must be a float in [0, 1]") self.threshold = threshold def _parse_method(self, method): if method in self._moptions['mult']: self.method = method self._compute_scores = self._compute_multn_scores elif method in self._moptions['bvn']: self._has_cov = True self.method = method self._compute_scores = self._compute_bvn_scores else: raise ValueError( "``method`` must be one of 'multinomial', 'mult', 'elliptical'" ", 'bivariate', 'bvn'" ) def _compute_multn_scores(self, n_bins, n_sigmas, epsilon, n_threads): # -- validate n_bins arg if n_bins is None: self.n_bins = 100 elif isinstance(n_bins, int): if n_bins < 1: raise ValueError("`n_bins` must be bigger than 0") self.n_bins = n_bins else: raise TypeError("`n_bins` must be an int") # -- validate n_sigmas arg if not isinstance(n_sigmas, (int, float)): raise TypeError("`n_sigmas` must be an int or float.") elif n_sigmas < 1.0: raise ValueError("`n_sigmas` must be greater than 1.") self.n_sigmas = n_sigmas # -- validate epsilon arg if not isinstance(epsilon, float): raise TypeError("`epsilon` must be a float") elif not (1e-15 <= epsilon <= 0.1): raise ValueError("`epsilon` must be in [1e-15, 0.1]") self.epsilon = epsilon self.precision, self.recall = _core.precision_recall(self.conf_mat) # compute scores n_threads = _check_n_threads(n_threads) if _MMU_MT_SUPPORT and n_threads > 1: self.chi2_scores, bounds = _core.pr_multn_error_mt( n_bins=self.n_bins, conf_mat=self.conf_mat, n_sigmas=self.n_sigmas, epsilon=self.epsilon, n_threads=n_threads ) else: if (n_threads > 1): warnings.warn( "mmu was not compiled with multi-threading enabled," " ignoring `n_threads`" ) self.chi2_scores, bounds = _core.pr_multn_error( n_bins=self.n_bins, conf_mat=self.conf_mat, n_sigmas=self.n_sigmas, epsilon=self.epsilon ) self.precision_bounds = bounds[0, :].copy() self.recall_bounds = bounds[1, :].copy() self._bounds = bounds.flatten() def _compute_bvn_scores(self, *args, **kwargs): out = _core.pr_bvn_cov(self.conf_mat) self.precision = out[0] self.recall = out[1] self.cov_mat = out[2:].reshape(2, 2) if self.precision < 1e-12: warnings.warn("`precision` is close to zero, COV[P, R] is not valid") elif (1 - self.precision) < 1e-12: warnings.warn("`precision` is close to one, COV[P, R] is not valid") if self.recall < 1e-12: warnings.warn("`recall` is close to zero, COV[P, R] is not valid") elif (1 - self.recall) < 1e-12: warnings.warn("`recall` is close to one, COV[P, R] is not valid") # check if we have enough power for binomial approximation # n * p * (1 - p) > 10 fcmat = self.conf_mat.flatten() # type: ignore # p = TP / P + N p = fcmat[3] / fcmat.sum() n = min(fcmat[1] + fcmat[3], fcmat[2] + fcmat[3]) min_val_score = n * p * (1 - p) if min_val_score <= 10.0: warnings.warn( "Low statistics, Normal approximation to Binomial may not be" f" robust for the observed confusion matrix probabilities" " and counts" ) @classmethod def from_scores(cls, y : np.ndarray, scores : np.ndarray, threshold : float = 0.5, method : str = 'multinomial', n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- y : np.ndarray true labels for observations, supported dtypes are [bool, int32, int64, float32, float64] scores : np.ndarray, default=None the classifier scores to be evaluated against the `threshold`, i.e. `yhat` = `scores` >= `threshold`. Supported dtypes are float32 and float64. threshold : float, default=0.5 the classification threshold to which the classifier scores are evaluated, is inclusive. method : str, default='multinomial', which method to use, options are the Multinomial approach {'multinomial', 'mult'} or the bivariate-normal/elliptical approach {'bvn', 'bivariate', 'elliptical'}. Default is 'multinomial'. n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation of multinomial. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() self._parse_method(method) self._parse_threshold(threshold) self.conf_mat = confusion_matrix(y=y, scores=scores, threshold=threshold) self._compute_scores(n_bins, n_sigmas, epsilon, n_threads) return self @classmethod def from_predictions(cls, y : np.ndarray, yhat : np.ndarray, method : str = 'multinomial', n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- y : np.ndarray[bool, int32, int64, float32, float64] true labels for observations, supported dtypes are yhat : yhat : np.ndarray[bool, int32, int64, float32, float64], default=None the predicted labels, the same dtypes are supported as y. method : str, default='multinomial', which method to use, options are the Multinomial approach {'multinomial', 'mult'} or the bivariate-normal/elliptical approach {'bvn', 'bivariate', 'elliptical'}. Default is 'multinomial'. n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation of multinomial. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() self._parse_method(method) self.conf_mat = confusion_matrix(y=y, yhat=yhat) self._compute_scores(n_bins, n_sigmas, epsilon, n_threads) return self @classmethod def from_confusion_matrix(cls, conf_mat : np.ndarray, method : str = 'multinomial', n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- conf_mat : np.ndarray[int64], confusion matrix as returned by mmu.confusion_matrix, i.e. with layout [0, 0] = TN, [0, 1] = FP, [1, 0] = FN, [1, 1] = TP or the flattened equivalent. Supported dtypes are int32, int64 method : str, default='multinomial', which method to use, options are the Multinomial approach {'multinomial', 'mult'} or the bivariate-normal/elliptical approach {'bvn', 'bivariate', 'elliptical'}. Default is 'multinomial'. n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation of multinomial. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() self._parse_method(method) if conf_mat.shape == (2, 2): conf_mat = conf_mat.ravel() self.conf_mat = check_array(conf_mat, max_dim=1, dtype_check=_convert_to_int) self._compute_scores(n_bins, n_sigmas, epsilon, n_threads) return self @classmethod def from_classifier(cls, clf, X : np.ndarray, y : np.ndarray, threshold : float = 0.5, method : str = 'multinomial', n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- clf : sklearn.Predictor a trained model with method `predict_proba`, used to compute the classifier scores X : np.ndarray the feature array to be used to compute the classifier scores y : np.ndarray[bool, int32, int64, float32, float64] true labels for observations threshold : float, default=0.5 the classification threshold to which the classifier score is evaluated, is inclusive. method : str, default='multinomial', which method to use, options are the Multinomial approach {'multinomial', 'mult'} or the bivariate-normal/elliptical approach {'bvn', 'bivariate', 'elliptical'}. Default is 'multinomial'. n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation of multinomial. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() self._parse_method(method) self._parse_threshold(threshold) if not hasattr(clf, 'predict_proba'): raise TypeError("`clf` must have a method `predict_proba`") scores = clf.predict_proba(X)[:, 1] self.conf_mat = confusion_matrix(y=y, scores=scores, threshold=threshold) self._compute_scores(n_bins, n_sigmas, epsilon, n_threads) return self @classmethod def from_scores_with_train(cls, y : np.ndarray, scores : np.ndarray, scores_bs : np.ndarray, threshold : float = 0.5, obs_axis : int = 0 ): """Compute joint-uncertainty on precision and recall from classifier scores with train uncertainty. Train uncertainty is only supported for the bivariate-normal/elliptical approach. ``method`` is set to `bvn`. Train uncertainty can be added by bootstrapping the train set, say 30, times, training the model each time on the bootstrapped train set and predicting on the fixed holdout set ``y_test`` each time. This should result in a array of classifier scores with shape (n_test_obs, n_bootstraps) Parameters ---------- y : np.ndarray true labels for observations, supported dtypes are [bool, int32, int64, float32, float64] scores : np.ndarray, default=None the classifier scores to be evaluated against the `threshold`, i.e. `yhat` = `scores` >= `threshold`. Supported dtypes are float32 and float64. scores_bs : np.ndarray[float32, float64] the classifier scores for each of the bootstrapped models on the test set y. threshold : float, default=0.5 the classification threshold to which the classifier scores are evaluated, is inclusive. obs_axis : int, default=0 the axis containing the observations for a single run for the scores_train, e.g. 0 when the labels and scores are stored as columns """ self = cls() self._has_cov = True self.method = 'bvn_with_train' self._parse_threshold(threshold) y = check_array( y, max_dim=1, dtype_check=_convert_to_ext_types ) scores = check_array( scores, max_dim=1, dtype_check=_convert_to_float, ) if scores.size != y.size: raise ValueError('`scores` and `y` must have equal size.') scores_bs = check_array( scores_bs, axis=obs_axis, target_axis=obs_axis, target_order=1-obs_axis, max_dim=2, dtype_check=_convert_to_float, ) n_runs = scores_bs.shape[1 - obs_axis] if n_runs < 3: raise ValueError( "Cannot compute covariance for less than three training bootstraps" ) y_bs = check_array( np.tile(y, n_runs).reshape(n_runs, y.size).T, axis=0, target_axis=obs_axis, target_order=1-obs_axis, max_dim=2, dtype_check=_convert_to_ext_types, check_finite=False ) self.conf_mat = _core.confusion_matrix_score(y, scores, self.threshold) self._compute_bvn_scores() self.train_conf_mats = _core.confusion_matrix_score_runs( y_bs, scores_bs, self.threshold, obs_axis=obs_axis ) out = _core.precision_recall_2d(self.train_conf_mats) self.train_precisions = out[:, 0] self.train_recalls = out[:, 1] self.train_cov_mat = np.cov(out, rowvar=False, ddof=1) self.total_cov_mat = self.cov_mat + self.train_cov_mat # type: ignore return self def _get_scaling_factor_alpha(self, alphas): """Compute critical value given a number alphas.""" # Get the scale for 2 degrees of freedom confidence interval # We use chi2 because the equation of an ellipse is a sum of squared variable, return np.sqrt(sts.chi2.ppf(alphas, 2)) def _get_scaling_factor_std(self, stds): alphas = 2. * (sts.norm.cdf(stds) - 0.5) return np.sqrt(sts.chi2.ppf(alphas, 2)) def _get_critical_values_std(self, n_std): """Compute the critical values for a chi2 with 2df using the continuity correction""" alphas = 2. * (sts.norm.cdf(n_std) - 0.5) # confidence limits in two dimensions return sts.chi2.ppf(alphas, 2) def _get_critical_values_alpha(self, alphas): """Compute the critical values for a chi2 with 2df.""" # confidence limits in two dimensions return sts.chi2.ppf(alphas, 2) def get_train_conf_mats(self) -> pd.DataFrame: """Obtain confusion matrices as a DataFrame. Returns ------- pd.DataFrame the confusion matrices of the training sets Raises ------ NotImplementedError when method is not Bivariate-Normal/Elliptical """ if self.train_conf_mats is None: raise NotImplementedError( "`train_conf_mats` are only compute when initialised " " with ``from_scores_with_train``" ) return confusion_matrices_to_dataframe(self.train_conf_mats) def get_cov_mat(self) -> pd.DataFrame: """Obtain covariance matrix of the test set. Returns ------- pd.DataFrame the covariance matrix Raises ------ NotImplementedError when method is not Bivariate-Normal/Elliptical """ if not self._has_cov: raise NotImplementedError( "`cov_mat` is not computed when method is not" " Bivariate-Normal/Elliptical." ) cov_cols = ['precision', 'recall'] return pd.DataFrame(self.cov_mat, index=cov_cols, columns=cov_cols) def get_train_cov_mat(self) -> pd.DataFrame: """Obtain covariance matrix of the train set. Returns ------- pd.DataFrame the covariance matrix Raises ------ NotImplementedError when method is not Bivariate-Normal/Elliptical """ if self.train_cov_mat is None: raise NotImplementedError( "`train_cov_mat` is only compute when initialised " " with ``from_scores_with_train``" ) cov_cols = ['precision', 'recall'] return pd.DataFrame(self.train_cov_mat, index=cov_cols, columns=cov_cols) def get_total_cov_mat(self) -> pd.DataFrame: """Obtain covariance matrix of the train and test set combined. Returns ------- pd.DataFrame the covariance matrix Raises ------ NotImplementedError when method is not Bivariate-Normal/Elliptical """ if self.total_cov_mat is None: raise NotImplementedError( "`total_cov_mat` is only compute when initialised " " with ``from_scores_with_train``" ) cov_cols = ['precision', 'recall'] return pd.DataFrame(self.total_cov_mat, index=cov_cols, columns=cov_cols) def compute_score_for(self, prec : Union[float, np.ndarray], rec : Union[float, np.ndarray], epsilon : float = 1e-12 ) -> float: """Compute score for a given precision(s) and recall(s). If method is `bvn` the sum of squared Z scores is computed, if method is 'mult' the profile loglikelihood is computed. Both follow a chi2 distribution with 2 degrees of freedom. Parameters ---------- prec : float, np.ndarray[float64, float32] the precision(s) to evaluate rec : float, np.ndarray[float64, float32] the recall(s) to evaluate epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Returns ------- chi2_score : float, np.ndarray[float64] the chi2_score(s) for the given precision(s) and recall(s). """ if self.conf_mat is None: raise RuntimeError("the class needs to be initialised with from_*") if not isinstance(epsilon, float): raise TypeError("`epsilon` must be a float") elif not (1e-15 <= epsilon <= 0.1): raise ValueError("`epsilon` must be in [1e-15, 0.1]") if ( isinstance(prec, float) and (0.0 <= prec <= 1.0) and isinstance(rec, float) and (0.0 <= rec <= 1.0) ): if self._has_cov: return _core.pr_bvn_chi2_score(prec, rec, self.conf_mat, epsilon) return _core.pr_multn_chi2_score(prec, rec, self.conf_mat, epsilon) elif ( isinstance(prec, np.ndarray) and isinstance(rec, np.ndarray) ): prec = check_array(prec, max_dim=1, dtype_check=_convert_to_float) rec = check_array(rec, max_dim=1, dtype_check=_convert_to_float) if self._has_cov: if _MMU_MT_SUPPORT: return _core.pr_bvn_chi2_scores_mt(prec, rec, self.conf_mat, epsilon) return _core.pr_bvn_chi2_scores(prec, rec, self.conf_mat, epsilon) if _MMU_MT_SUPPORT: return _core.pr_multn_chi2_scores_mt(prec, rec, self.conf_mat, epsilon) return _core.pr_multn_chi2_scores(prec, rec, self.conf_mat, epsilon) else: raise ValueError( "``prec`` and ``rec`` must bot be floats or np.ndarray's of" " floats in [0, 1]" ) def compute_pvalue_for(self, prec : Union[float, np.ndarray], rec : Union[float, np.ndarray], epsilon : float = 1e-12 ) -> float: """Compute p-value(s) for a given precision(s) and recall(s). If method is `bvn` the sum of squared Z scores is computed, if method is 'mult' the profile loglikelihood is computed. Both follow are chi2 distribution with 2 degrees of freedom. Parameters ---------- prec : float, np.ndarray[float64, float32] the precision(s) to evaluate rec : float, np.ndarray[float64, float32] the recall(s) to evaluate level : int, float epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. Returns ------- chi2_score : float, np.ndarray[float64] the chi2_score(s) for the given precision(s) and recall(s) """ chi2_score = self.compute_score_for(prec, rec, epsilon) return sts.chi2.sf(chi2_score, 2) def get_conf_mat(self) -> pd.DataFrame: """Obtain confusion matrix as a DataFrame. Returns ------- pd.DataFrame the confusion matrix of the test set """ return confusion_matrix_to_dataframe(self.conf_mat) def _add_point_to_plot(self, point, point_kwargs): if isinstance(point_kwargs, dict): if 'cmap' not in point_kwargs: point_kwargs['cmap'] = 'Reds' if 'ax' in point_kwargs: point_kwargs.pop('ax') elif point_kwargs is None: point_kwargs = {'cmap': 'Reds'} else: raise TypeError("`point_kwargs` must be a Dict or None") self._ax = point.plot(ax=self._ax, **point_kwargs) self._handles = self._handles + point._handles self._ax.legend(handles=self._handles, loc='lower left', fontsize=12) # type: ignore def _add_other_to_plot(self, other, other_kwargs): if ( isinstance(other, PrecisionRecallUncertainty) or isinstance(other, PrecisionRecallSimulatedUncertainty) ): self._add_point_to_plot(other, other_kwargs) elif isinstance(other, (list, tuple)): if other_kwargs is None: other_kwargs = {} elif isinstance(other_kwargs, dict): other_kwargs = [other_kwargs, ] * len(other) for point, kwargs in zip_longest(other, other_kwargs): self._add_point_to_plot(point, kwargs) else: raise TypeError( "`point_uncertainty` must be of type PrecisionRecallUncertainty" " , PrecisionRecallSimulatedUncertainty or a list of those" ) def _plot_ellipse( self, levels, uncertainties, ax, cmap, equal_aspect, limit_axis, legend_loc, alpha, other, other_kwargs ): """Plot elliptical confidence interval(s) for precision and recall.""" if self.cov_mat is None: raise RuntimeError("the class needs to be initialised with from_*") # -- parse uncertainties if uncertainties == 'test': cov_mat = self.cov_mat elif uncertainties == 'all': if self.total_cov_mat is not None: cov_mat = self.total_cov_mat else: raise RuntimeError( "`toal_cov_mat` is only compute when initialised " " with ``from_scores_with_train``" ) elif uncertainties == 'train': if self.train_cov_mat is not None: cov_mat = self.train_cov_mat else: raise RuntimeError( "`train_cov_mat` is only compute when initialised " " with ``from_scores_with_train``" ) else: raise ValueError( "`uncertainties` must be one of {'test', 'train', 'all'}" ) # quick catch for list and tuples if isinstance(levels, (list, tuple)): levels = np.asarray(levels) # transform levels into scaling factors for the ellipse if levels is None: scales = self._get_scaling_factor_std(np.array((1, 2, 3))) labels = [r'$1\sigma$ CI', r'$2\sigma$ CI', r'$3\sigma$ CI'] elif isinstance(levels, int): labels = [f'{levels}' + r'$\sigma$ CI'] scales = self._get_scaling_factor_std(np.array((levels,))) elif ( isinstance(levels, np.ndarray) and np.issubdtype(levels.dtype, np.integer) ): levels = np.sort(np.unique(levels)) labels = [f'{l}' + r'$\sigma$ CI' for l in levels] scales = self._get_scaling_factor_std(levels) elif isinstance(levels, float): labels = [f'{round(levels * 100, 3)}% CI'] scales = self._get_scaling_factor_alpha(np.array((levels,))) elif ( isinstance(levels, np.ndarray) and np.issubdtype(levels.dtype, np.floating) ): levels = np.sort(np.unique(levels)) labels = [f'{round(l * 100, 3)}% CI' for l in levels] scales = self._get_scaling_factor_alpha(levels) else: raise TypeError( "`levels` must be a int, float, array-like or None" ) self.critical_values_plot = levels self._ax, self._handles = _plot_pr_ellipse( precision=self.precision, recall=self.recall, cov_mat=cov_mat, scales=scales, labels=labels, cmap=cmap, ax=ax, alpha=alpha, equal_aspect=equal_aspect, limit_axis=limit_axis, legend_loc=legend_loc ) if other is not None: self._add_other_to_plot(other, other_kwargs) return self._ax def _plot_contour( self, levels, ax, cmap, equal_aspect, limit_axis, legend_loc, alpha, other, other_kwargs ): """Plot confidence interval(s) for precision and recall.""" if self.chi2_scores is None: raise RuntimeError("the class needs to be initialised with from_*") # quick catch for list and tuples if isinstance(levels, (list, tuple)): levels = np.asarray(levels) # transform levels into scaling factors for the ellipse if levels is None: levels = self._get_critical_values_std(np.array((1, 2, 3))) labels = [r'$1\sigma$ CI', r'$2\sigma$ CI', r'$3\sigma$ CI'] elif isinstance(levels, int): labels = [f'{levels}' + r'$\sigma$ CI'] levels = self._get_critical_values_std(np.array((levels,))) elif ( isinstance(levels, np.ndarray) and np.issubdtype(levels.dtype, np.integer) ): levels = np.sort(np.unique(levels)) labels = [f'{l}' + r'$\sigma$ CI' for l in levels] levels = self._get_critical_values_std(levels) elif isinstance(levels, float): labels = [f'{round(levels * 100, 3)}% CI'] levels = self._get_critical_values_alpha(np.array((levels,))) elif ( isinstance(levels, np.ndarray) and np.issubdtype(levels.dtype, np.floating) ): levels = np.sort(np.unique(levels)) labels = [f'{round(l * 100, 3)}% CI' for l in levels] levels = self._get_critical_values_alpha(levels) else: raise TypeError( "`levels` must be a int, float, array-like or None" ) self.critical_values_plot = levels self._ax, self._handles = _plot_pr_contours( n_bins=self.n_bins, precision=self.precision, recall=self.recall, scores=self.chi2_scores, bounds=self._bounds, levels=levels, labels=labels, cmap=cmap, ax=ax, alpha=alpha, equal_aspect=equal_aspect, limit_axis=limit_axis, legend_loc=legend_loc ) if other is not None: self._add_other_to_plot(other, other_kwargs) return self._ax def plot( self, levels : Union[int, float, np.ndarray, None] = None, source = 'test', ax=None, cmap : str = 'Blues', equal_aspect : bool = True, limit_axis : bool = True, legend_loc : Optional[str] = None, alpha : float = 0.8, other : Union['PrecisionRecallUncertainty', 'PrecisionRecallSimulatedUncertainty', List['PrecisionRecallUncertainty'], List['PrecisionRecallSimulatedUncertainty'], None ] = None, other_kwargs : Union[Dict, List[Dict], None] = None ): """Plot confidence interval(s) for precision and recall. Parameters ---------- levels : int, float np.ndarray, default=np.array((1, 2, 3,)) if int(s) levels is treated as the number of standard deviations for the confidence interval. If float(s) it is taken to be the density to be contained in the confidence interval By default we plot 1, 2 and 3 std deviations source : str, default='test' which source of uncertainty to plot, ignored when method is not Bivariate-Normal / Elliptical. 'test' indicates only the sampling uncertainty of the test set. 'train' only plots the sampling uncertainty of the train set. 'all' plots to toal uncertainty over both the train and test sets. Note that 'train' and 'all' require that the class was initialised with ``from_scores_with_train``. ax : matplotlib.axes.Axes, default=None Pre-existing axes for the plot cmap : str, default='Blues' matplotlib cmap name to use for CIs equal_aspect : bool, default=True ensure the same scaling for x and y axis limit_axis : bool, default=True allow ax to be limited for optimal CI plot legend_loc : str, default=None location of the legend, default is `lower left` alpha : float, defualt=0.8 opacity value of the contours other : PrecisionRecallUncertainty, PrecisionRecallSimulatedUncertainty, List, default=None Add other point uncertainty(ies) plot to the plot, by default the `Reds` cmap is used for the `other` plot(s). other_kwargs : dict, list[dict], default=None Keyword arguments passed to `other.plot()`, ignored if `other` is None. If `other` is a list and `other_kwargs` is a dict, the kwargs are used for all point others. Returns ------- ax : matplotlib.axes.Axes the axis with the ellipse added to it """ if self._has_cov is True: return self._plot_ellipse( levels=levels, uncertainties=source, ax=ax, cmap=cmap, equal_aspect=equal_aspect, limit_axis=limit_axis, legend_loc=legend_loc, alpha=alpha, other=other, other_kwargs=other_kwargs ) else: return self._plot_contour( levels=levels, ax=ax, cmap=cmap, equal_aspect=equal_aspect, limit_axis=limit_axis, legend_loc=legend_loc, alpha=alpha, other=other, other_kwargs=other_kwargs ) class PrecisionRecallSimulatedUncertainty: """Compute joint uncertainty Precision-Recall through simulation. Model's the uncertainty using profile log-likelihoods between the observed and most conservative confusion matrix for that precision-recall and checks how often random multinomial given the observed probabilities of the confusion matrix result in lower profile log-likelihoods. This approach is much slower than the PrecisionRecallUncertainty with Multinomial method, and is likely to give less well-defined contours unless the number of simulations is high enough. Attributes ---------- conf_mat : np.ndarray[int64] the confusion_matrix with layout [0, 0] = TN, [0, 1] = FP, [1, 0] = FN, [1, 1] = TP A DataFrame can be obtained by calling `get_conf_mat`. precision : float the Positive Predictive Value aka positive precision recall : float True Positive Rate aka Sensitivity aka positive recall threshold : float, optional the inclusive threshold used to determine the confusion matrix. Is None when the class is instantiated with `from_predictions` or `from_confusion_matrix`. coverage : np.ndarray[float64] the percentage of simulations with a lower profile loglikelihood for the grid with shape (`n_bins`, `n_bins`) and bounds precision_bounds on the y-axis, recall_bounds on the x-axis precision_bounds : np.ndarray[float64] the lower and upper bound for which precision was evaluated, equal to precision +- `n_sigmas` * sigma(precision) recall_bounds : np.ndarray[float64] the lower and upper bound for which recall was evaluated, equal to recall +- `n_sigmas` * sigma(recall) n_sigmas : int, float the number of marginal standard deviations used to determine the bounds of the grid which is evaluated for each observed precision and recall. epsilon : float the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. n_simulations : int the number of simulations performed per grid point """ def __init__(self): self.conf_mat = None self.precision = None self.recall = None self._bounds = None self.precision_bounds = None self.recall_bounds = None self.coverage = None self.n_bins = None self.n_sigmas = None self.epsilon = None def _parse_threshold(self, threshold): if not isinstance(threshold, float) or not (0.0 < threshold < 1.0): raise TypeError("`threshold` must be a float in [0, 1]") self.threshold = threshold def _simulate_multn_scores(self, n_simulations, n_bins, n_sigmas, epsilon, n_threads ): n_threads = _check_n_threads(n_threads) if isinstance(n_simulations, int): if n_simulations <= 29: raise ValueError( "``n_simulations`` must be at least 30." " The results will be unreliable for small number of simulations." ) self.n_simulations = n_simulations else: raise TypeError("``n_simulations`` must be an int") # -- validate n_bins arg if n_bins is None: self.n_bins = 100 elif isinstance(n_bins, int): if n_bins < 1: raise ValueError("`n_bins` must be bigger than 0") self.n_bins = n_bins else: raise TypeError("`n_bins` must be an int") # -- validate n_sigmas arg if not isinstance(n_sigmas, (int, float)): raise TypeError("`n_sigmas` must be an int or float.") elif n_sigmas < 1.0: raise ValueError("`n_sigmas` must be greater than 1.") self.n_sigmas = n_sigmas # -- validate epsilon arg if not isinstance(epsilon, float): raise TypeError("`epsilon` must be a float") elif not (1e-15 <= epsilon <= 0.1): raise ValueError("`epsilon` must be in [1e-15, 0.1]") self.epsilon = epsilon self.precision, self.recall = _core.precision_recall(self.conf_mat) # compute scores if _MMU_MT_SUPPORT and n_threads > 1: self.coverage, bounds = _core.pr_multn_sim_error_mt( n_sims=n_simulations, n_bins=self.n_bins, conf_mat=self.conf_mat, n_sigmas=self.n_sigmas, epsilon=self.epsilon, n_threads=n_threads, ) else: if (n_threads > 1): warnings.warn( "mmu was not compiled with multi-threading enabled," " ignoring `n_threads`" ) self.coverage, bounds = _core.pr_multn_sim_error_mt( n_sims=n_simulations, n_bins=self.n_bins, conf_mat=self.conf_mat, n_sigmas=self.n_sigmas, epsilon=self.epsilon, ) self.precision_bounds = bounds[0, :].copy() self.recall_bounds = bounds[1, :].copy() self._bounds = bounds.flatten() @classmethod def from_scores(cls, y : np.ndarray, scores : np.ndarray, threshold : float = 0.5, n_simulations : int = 10000, n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- y : np.ndarray true labels for observations, supported dtypes are [bool, int32, int64, float32, float64] scores : np.ndarray, default=None the classifier scores to be evaluated against the `threshold`, i.e. `yhat` = `scores` >= `threshold`. Supported dtypes are float32 and float64. threshold : float, default=0.5 the classification threshold to which the classifier scores are evaluated, is inclusive. n_simulations : int, default=10000 the number of simulations to perform per grid point, note that the total number of simulations is (n_bins ** 2 * n_simulations) It is advised ``n_simulations`` >= 10000 n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() self._parse_threshold(threshold) self.conf_mat = confusion_matrix(y=y, scores=scores, threshold=threshold) self._simulate_multn_scores(n_simulations, n_bins, n_sigmas, epsilon, n_threads) return self @classmethod def from_predictions(cls, y : np.ndarray, yhat : np.ndarray, n_simulations : int = 10000, n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- y : np.ndarray[bool, int32, int64, float32, float64] true labels for observations, supported dtypes are yhat : yhat : np.ndarray[bool, int32, int64, float32, float64], default=None the predicted labels, the same dtypes are supported as y. n_simulations : int, default=10000 the number of simulations to perform per grid point, note that the total number of simulations is (n_bins ** 2 * n_simulations) It is advised ``n_simulations`` >= 10000 n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() self.conf_mat = confusion_matrix(y=y, yhat=yhat) self._simulate_multn_scores( n_simulations, n_bins, n_sigmas, epsilon, n_threads ) return self @classmethod def from_confusion_matrix(cls, conf_mat : np.ndarray, n_simulations : int = 10000, n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- conf_mat : np.ndarray[int64], confusion matrix as returned by mmu.confusion_matrix, i.e. with layout [0, 0] = TN, [0, 1] = FP, [1, 0] = FN, [1, 1] = TP or the flattened equivalent. Supported dtypes are int32, int64 n_simulations : int, default=10000 the number of simulations to perform per grid point, note that the total number of simulations is (n_bins ** 2 * n_simulations) It is advised ``n_simulations`` >= 10000 n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() if conf_mat.shape == (2, 2): conf_mat = conf_mat.ravel() self.conf_mat = check_array(conf_mat, max_dim=1, dtype_check=_convert_to_int) self._simulate_multn_scores( n_simulations, n_bins, n_sigmas, epsilon, n_threads ) return self @classmethod def from_classifier(cls, clf, X : np.ndarray, y : np.ndarray, threshold : float = 0.5, n_simulations : int = 10000, n_bins : int = 100, n_sigmas : Union[int, float] = 6.0, epsilon : float = 1e-12, n_threads: Optional[int] = None ): """Compute joint-uncertainty on precision and recall. Parameters ---------- clf : sklearn.Predictor a trained model with method `predict_proba`, used to compute the classifier scores X : np.ndarray the feature array to be used to compute the classifier scores y : np.ndarray[bool, int32, int64, float32, float64] true labels for observations threshold : float, default=0.5 the classification threshold to which the classifier score is evaluated, is inclusive. n_simulations : int, default=10000 the number of simulations to perform per grid point, note that the total number of simulations is (n_bins ** 2 * n_simulations) It is advised ``n_simulations`` >= 10000 n_bins : int, default=100 the number of bins in the precision/recall grid for which the uncertainty is computed. `scores` will be a `n_bins` by `n_bins` array. Ignored when method is not the Multinomial approach. n_sigmas : int, float, default=6.0 the number of marginal standard deviations used to determine the bounds of the grid which is evaluated. Ignored when method is not the Multinomial approach. epsilon : float, default=1e-12 the value used to prevent the bounds from reaching precision/recall 1.0/0.0 which would result in NaNs. Ignored when method is not the Multinomial approach. n_threads : int, default=None number of threads to use in the computation. If mmu installed from a wheel it won't have multithreading support. If it was compiled with OpenMP support the default is 4, otherwise 1. """ self = cls() self._parse_threshold(threshold) if not hasattr(clf, 'predict_proba'): raise TypeError("`clf` must have a method `predict_proba`") scores = clf.predict_proba(X)[:, 1] self.conf_mat = confusion_matrix(y=y, scores=scores, threshold=threshold) self._simulate_multn_scores( n_simulations, n_bins, n_sigmas, epsilon, n_threads ) return self def _get_cdf_factor_std(self, stds): return 2. * (sts.norm.cdf(stds) - 0.5) def get_conf_mat(self) -> pd.DataFrame: """Obtain confusion matrix as a DataFrame. Returns ------- pd.DataFrame the confusion matrix of the test set """ return confusion_matrix_to_dataframe(self.conf_mat) def _add_point_to_plot(self, point, point_kwargs): if isinstance(point_kwargs, dict): if 'cmap' not in point_kwargs: point_kwargs['cmap'] = 'Reds' if 'ax' in point_kwargs: point_kwargs.pop('ax') elif point_kwargs is None: point_kwargs = {'cmap': 'Reds'} else: raise TypeError("`point_kwargs` must be a Dict or None") self._ax = point.plot(ax=self._ax, **point_kwargs) self._handles = self._handles + point._handles self._ax.legend(handles=self._handles, loc='lower left', fontsize=12) # type: ignore def _add_other_to_plot(self, other, other_kwargs): if ( isinstance(other, PrecisionRecallUncertainty) or isinstance(other, PrecisionRecallSimulatedUncertainty) ): self._add_point_to_plot(other, other_kwargs) elif isinstance(other, (list, tuple)): if other_kwargs is None: other_kwargs = {} elif isinstance(other_kwargs, dict): other_kwargs = [other_kwargs, ] * len(other) for point, kwargs in zip_longest(other, other_kwargs): self._add_point_to_plot(point, kwargs) else: raise TypeError( "`point_uncertainty` must be a subclass of PointUncertainty" " or a list of PointUncertainty's" ) def plot( self, levels : Union[int, float, np.ndarray, None] = None, ax=None, cmap : str = 'Blues', equal_aspect : bool = False, limit_axis : bool = True, legend_loc : Optional[str] = None, alpha : float = 0.8, other : Union['PrecisionRecallUncertainty', 'PrecisionRecallSimulatedUncertainty', List['PrecisionRecallUncertainty'], List['PrecisionRecallSimulatedUncertainty'], None ] = None, other_kwargs : Union[Dict, List[Dict], None] = None ): """Plot confidence interval(s) for precision and recall. Parameters ---------- levels : int, float np.ndarray, default=np.array((1, 2, 3,)) if int(s) levels is treated as the number of standard deviations for the confidence interval. If float(s) it is taken to be the density to be contained in the confidence interval By default we plot 1, 2 and 3 std deviations ax : matplotlib.axes.Axes, default=None Pre-existing axes for the plot cmap : str, default='Blues' matplotlib cmap name to use for CIs equal_aspect : bool, default=False enforce square axis limit_axis : bool, default=True allow ax to be limited for optimal CI plot legend_loc : str, default=None location of the legend, default is `lower left` alpha : float, defualt=0.8 opacity value of the contours other : PrecisionRecallUncertainty, PrecisionRecallSimulatedUncertainty, List, default=None Add other point uncertainty(ies) plot to the plot, by default the `Reds` cmap is used for the `other` plot(s). other_kwargs : dict, list[dict], default=None Keyword arguments passed to `other.plot()`, ignored if `other` is None. If `other` is a list and `other_kwargs` is a dict, the kwargs are used for all point others. Returns ------- ax : matplotlib.axes.Axes the axis with the ellipse added to it """ if self.coverage is None: raise RuntimeError("the class needs to be initialised with from_*") # quick catch for list and tuples if isinstance(levels, (list, tuple)): levels = np.asarray(levels) # transform levels into scaling factors for the ellipse if levels is None: levels = self._get_cdf_factor_std(np.array((1, 2, 3))) labels = [r'$1\sigma$ CI', r'$2\sigma$ CI', r'$3\sigma$ CI'] elif isinstance(levels, int): labels = [f'{levels}' + r'$\sigma$ CI'] levels = self._get_cdf_factor_std(np.array((levels,))) elif ( isinstance(levels, np.ndarray) and np.issubdtype(levels.dtype, np.integer) ): levels = np.sort(np.unique(levels)) labels = [f'{l}' + r'$\sigma$ CI' for l in levels] elif isinstance(levels, float): labels = [f'{round(levels * 100, 3)}% CI'] levels = np.array((levels,)) elif ( isinstance(levels, np.ndarray) and np.issubdtype(levels.dtype, np.floating) ): levels = np.sort(np.unique(levels)) labels = [f'{round(l * 100, 3)}% CI' for l in levels] else: raise TypeError( "`levels` must be a int, float, array-like or None" ) self.critical_values_plot = levels self._ax, self._handles = _plot_pr_contours( n_bins=self.n_bins, precision=self.precision, recall=self.recall, scores=self.coverage, bounds=self._bounds, levels=levels, labels=labels, cmap=cmap, ax=ax, alpha=alpha, equal_aspect=equal_aspect, limit_axis=limit_axis, legend_loc=legend_loc ) if other is not None: self._add_other_to_plot(other, other_kwargs) return self._ax

40.126549

110

0.597978

7,656

61,514

4.668365

0.064394

0.011471

0.009849

0.01301

0.836882

0.822753

0.811925

0.798551

0.778238

0.763325

0

0.017308

0.320935

61,514

1,532

111

40.152742

0.838313

0.418864

0

0.71161

0

0.109313

0.014636

0

1

0.047441

false

0

0.019975

0.001248

0.109863

0

null

0

1

0

1

0

null

0

7

941c0be4e5a4875ebdd506efdf62e8dee4528022

2,170

py

Python

TSSystem/apps/graduation_design/migrations/0002_auto_20180607_2143.py

LittleBai0606/TeachingSecretarySystem

c9067b83f8e1edaf06974db73b7cc47a5b49e0d4

[ "MIT" ]

null

TSSystem/apps/graduation_design/migrations/0002_auto_20180607_2143.py

LittleBai0606/TeachingSecretarySystem

c9067b83f8e1edaf06974db73b7cc47a5b49e0d4

[ "MIT" ]

5

2020-06-05T18:13:28.000Z

2022-02-11T03:39:14.000Z

TSSystem/apps/graduation_design/migrations/0002_auto_20180607_2143.py

WhiteBrownBottle/TeachingSecretarySystem

c9067b83f8e1edaf06974db73b7cc47a5b49e0d4

[ "MIT" ]

null

# Generated by Django 2.0.5 on 2018-06-07 21:43 from django.db import migrations, models import django.utils.timezone class Migration(migrations.Migration): dependencies = [ ('graduation_design', '0001_initial'), ] operations = [ migrations.AddField( model_name='dissertation', name='file_date', field=models.DateField(default=django.utils.timezone.now, verbose_name='上传日期'), ), migrations.AddField( model_name='midtermreport', name='file_date', field=models.DateField(default=django.utils.timezone.now, verbose_name='上传日期'), ), migrations.AddField( model_name='openingreport', name='file_date', field=models.DateField(default=django.utils.timezone.now, verbose_name='上传日期'), ), migrations.AlterField( model_name='dissertation', name='file_name', field=models.CharField(blank=True, default='暂未命名', max_length=100, null=True, verbose_name='文档名称'), ), migrations.AlterField( model_name='dissertation', name='file_url', field=models.CharField(blank=True, max_length=100, null=True, verbose_name='文件路径'), ), migrations.AlterField( model_name='midtermreport', name='file_name', field=models.CharField(blank=True, default='暂未命名', max_length=100, null=True, verbose_name='文档名称'), ), migrations.AlterField( model_name='midtermreport', name='file_url', field=models.CharField(blank=True, max_length=100, null=True, verbose_name='文件路径'), ), migrations.AlterField( model_name='modelfile', name='file_name', field=models.CharField(blank=True, default='暂未命名', max_length=100, null=True, verbose_name='文件名称'), ), migrations.AlterField( model_name='openingreport', name='file_name', field=models.CharField(blank=True, default='暂未命名', max_length=100, null=True, verbose_name='文件名称'), ), ]

36.166667

111

0.599539

223

2,170

5.67713

0.246637

0.063981

0.118483

0.137441

0.824645

0.770142

0.71564

0

0.023477

0.273733

2,170

59

112

36.779661

0.779822

0.020737

0

0.830189

1

0

0.127179

0

1

0

false

0

0.037736

0

0.09434

0

null

0

1

0

1

0

null

0

8

942085b0996e2010b1585183480b5ac76438f8fc

14,317

py

Python

countess/tests/test_selection_barcodevariant_lib_coding.py

VariantEffect/Enrich2-py3

5f8534c8c9259d90d99d70e5bd9140fd0fdc8ea4

[ "BSD-3-Clause" ]

4

2020-01-14T19:24:07.000Z

2020-01-16T18:11:35.000Z

countess/tests/test_selection_barcodevariant_lib_coding.py

VariantEffect/CountESS

5f8534c8c9259d90d99d70e5bd9140fd0fdc8ea4

[ "BSD-3-Clause" ]

3

2020-01-01T10:38:15.000Z

2020-01-03T09:45:41.000Z

countess/tests/test_selection_barcodevariant_lib_coding.py

VariantEffect/CountESS

5f8534c8c9259d90d99d70e5bd9140fd0fdc8ea4

[ "BSD-3-Clause" ]

1

2022-02-20T00:35:24.000Z

import unittest from copy import deepcopy from ..selection.selection import Selection from .methods import HDF5TestComponent from .utilities import DEFAULT_STORE_PARAMS from .utilities import load_config_data, update_cfg_file CFG_FILE = "barcodevariant_selection_coding.json" CFG_DIR = "data/config/selection/" READS_DIR = "data/reads/selection/" RESULT_DIR = "data/result/selection/" DRIVER = "runTest" LIBTYPE = "barcodevariant" CODING_STR = "c" FILE_EXT = "tsv" FILE_SEP = "\t" class TestSelectionBcvLibWLSScoringCompleteNormC(unittest.TestCase): def setUp(self): scoring = "WLS" logr = "complete" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibWLSScoringFullNormC(unittest.TestCase): def setUp(self): scoring = "WLS" logr = "full" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibWLSScoringWTNormC(unittest.TestCase): def setUp(self): scoring = "WLS" logr = "wt" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibOLSScoringCompleteNormC(unittest.TestCase): def setUp(self): scoring = "OLS" logr = "complete" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibOLSScoringFullNormC(unittest.TestCase): def setUp(self): scoring = "OLS" logr = "full" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibOLSScoringWTNormC(unittest.TestCase): def setUp(self): scoring = "OLS" logr = "wt" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibRatiosScoringCompleteNormC(unittest.TestCase): def setUp(self): scoring = "ratios" logr = "complete" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibRatiosScoringFullNormC(unittest.TestCase): def setUp(self): scoring = "ratios" logr = "full" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibRatiosScoringWTNormC(unittest.TestCase): def setUp(self): scoring = "ratios" logr = "wt" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibCountsScoringCompleteNormC(unittest.TestCase): def setUp(self): scoring = "counts" logr = "complete" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibCountsScoringFullNormC(unittest.TestCase): def setUp(self): scoring = "counts" logr = "full" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibCountsScoringWTNormC(unittest.TestCase): def setUp(self): scoring = "counts" logr = "wt" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibSimpleScoringCompleteNormC(unittest.TestCase): def setUp(self): scoring = "simple" logr = "complete" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibSimpleScoringFullNormC(unittest.TestCase): def setUp(self): scoring = "simple" logr = "full" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() class TestSelectionBcvLibSimpleScoringWTNormC(unittest.TestCase): def setUp(self): scoring = "simple" logr = "wt" cfg = load_config_data(CFG_FILE, CFG_DIR) cfg = update_cfg_file(cfg, scoring, logr) params = deepcopy(DEFAULT_STORE_PARAMS) self.general_test_component = HDF5TestComponent( store_constructor=Selection, cfg=cfg, result_dir=RESULT_DIR, file_ext=FILE_EXT, file_sep=FILE_SEP, save=False, params=params, verbose=False, libtype=LIBTYPE, scoring_method=scoring, logr_method=logr, coding="coding", ) self.general_test_component.setUp() def tearDown(self): self.general_test_component.tearDown() def test_all_hdf5_dataframes(self): self.general_test_component.runTest() if __name__ == "__main__": unittest.main()

29.338115

71

0.615702

1,464

14,317

5.718579

0.053279

0.078834

0.107501

0.172002

0.879957

0.808648

0

0.003112

0.304114

14,317

487

72

29.398357

0.837198

0

0.884521

0

0.025704

0.007055

0

1

0.110565

false

0

0.014742

0

0.162162

0

null

0

1

0

1

0

null

0

8

9441808d4598c923f29ca92dc95330efc8419457

5,556

py

Python

tests/integration/operators_test/reshape_test.py

gglin001/popart

3225214343f6d98550b6620e809a3544e8bcbfc6

[ "MIT" ]

61

2020-07-06T17:11:46.000Z

2022-03-12T14:42:51.000Z

tests/integration/operators_test/reshape_test.py

gglin001/popart

3225214343f6d98550b6620e809a3544e8bcbfc6

[ "MIT" ]

1

2021-02-25T01:30:29.000Z

2021-11-09T11:13:14.000Z

tests/integration/operators_test/reshape_test.py

gglin001/popart

3225214343f6d98550b6620e809a3544e8bcbfc6

[ "MIT" ]

6

2020-07-15T12:33:13.000Z

2021-11-07T06:55:00.000Z

# Copyright (c) 2019 Graphcore Ltd. All rights reserved. import numpy as np import pytest import popart import torch from op_tester import op_tester def test_reshape(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2 = np.array([4, 6]).astype(np.int64) def init_builder(builder): i1 = builder.addInputTensor(d1) c = builder.aiOnnx.constant(d2) o = builder.aiOnnx.reshape([i1, c]) builder.addOutputTensor(o) return [o] def reference(ref_data): out = np.reshape(d1, d2) return [out] op_tester.run(init_builder, reference, 'infer') def test_reshape_neg_one(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2 = np.array([-1, 6]).astype(np.int64) def init_builder(builder): i1 = builder.addInputTensor(d1) c = builder.aiOnnx.constant(d2) o = builder.aiOnnx.reshape([i1, c]) builder.addOutputTensor(o) return [o] def reference(ref_data): out = np.reshape(d1, d2) return [out] op_tester.run(init_builder, reference, 'infer') def test_reshape_neg_one_error(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2 = np.array([-1, -1, 0]).astype(np.int64) def init_builder(builder): i1 = builder.addInputTensor(d1) c = builder.aiOnnx.constant(d2) o = builder.aiOnnx.reshape([i1, c]) builder.addOutputTensor(o) return [o] with pytest.raises(popart.popart_exception) as e_info: op_tester.run(init_builder, None, 'infer') assert ('shape input to ReshapeOp can only use -1 to ' 'specify one unknown dimension') in str(e_info.value) def test_reshape_zeros(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2 = np.array([6, 0]).astype(np.int64) def init_builder(builder): i1 = builder.addInputTensor(d1) c = builder.aiOnnx.constant(d2) o = builder.aiOnnx.reshape([i1, c]) builder.addOutputTensor(o) return [o] def reference(ref_data): s = [i for i in d2] for i in range(0, len(s)): if s[i] == 0: s[i] = d1.shape[i] out = np.reshape(d1, s) return [out] op_tester.run(init_builder, reference, 'infer') def test_reshape_neg_one_and_zeros(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2 = np.array([-1, 0]).astype(np.int64) def init_builder(builder): i1 = builder.addInputTensor(d1) c = builder.aiOnnx.constant(d2) o = builder.aiOnnx.reshape([i1, c]) builder.addOutputTensor(o) return [o] def reference(ref_data): s = [i for i in d2] for i in range(0, len(s)): if s[i] == 0: s[i] = d1.shape[i] out = np.reshape(d1, s) return [out] op_tester.run(init_builder, reference, 'infer') def test_reshape_neg_one_and_zeros_grad(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2 = np.array([-1, 0]).astype(np.int64) def init_builder(builder): i1 = builder.addInputTensor(d1) c = builder.aiOnnx.constant(d2) o = builder.aiOnnx.reshape([i1, c]) builder.addOutputTensor(o) return [ o, popart.reservedGradientPrefix() + i1, popart.reservedGradientPrefix() + o ] def reference(ref_data): s = [i for i in d2] for i in range(0, len(s)): if s[i] == 0: s[i] = d1.shape[i] a = torch.tensor(d1, requires_grad=True) o = torch.reshape(a, s) d__o = ref_data.getOutputTensorGrad(0) o.backward(torch.tensor(d__o)) return [o, a.grad, None] op_tester.setPatterns(['PreUniRepl'], enableRuntimeAsserts=False) op_tester.run(init_builder, reference, 'train') def test_reshape_graphcore(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2a = [4, 6] d2 = np.array(d2a).astype(np.int64) def init_builder(builder): i1 = builder.addInputTensor(d1) o = builder.aiGraphcore.reshape(i1, shape=d2a) builder.addOutputTensor(o) return [o] def reference(ref_data): out = np.reshape(d1, d2) return [out] op_tester.run(init_builder, reference, 'infer') def test_reshape_neg_graphcore(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2a = [-1, 6] def init_builder(builder): i1 = builder.addInputTensor(d1) o = builder.aiGraphcore.reshape(i1, shape=d2a) builder.addOutputTensor(o) return [o] with pytest.raises(popart.popart_exception) as e_info: op_tester.run(init_builder, None, 'infer') assert ('Attribute shape has negative dimension.') in str(e_info.value) def test_reshape_graphcore_grad(op_tester): d1 = np.random.rand(2, 4, 3).astype(np.float32) d2a = [4, 6] d2b = (4, 6) def init_builder(builder): i1 = builder.addInputTensor(d1) o = builder.aiGraphcore.reshape(i1, shape=d2a) builder.addOutputTensor(o) return [ o, popart.reservedGradientPrefix() + i1, popart.reservedGradientPrefix() + o, ] def reference(ref_data): tx = torch.tensor(d1, requires_grad=True) out = torch.reshape(tx, d2b) d__o = ref_data.getOutputTensorGrad(0) out.backward(torch.tensor(d__o)) return [out, tx.grad, None] op_tester.run(init_builder, reference, 'train')

28.060606

75

0.608351

767

5,556

4.285528

0.132986

0.05111

0.024338

0.032857

0.885914

0.834195

0.812291

0.789169

0

0.041179

0.261339

5,556

197

76

28.203046

0.759747

0.009719

0

0.748299

0

0.030364

0

0.020408

1

0.170068

false

0

0.034014

0

0.312925

0

null

0

1

0

1

0

null

0

7

94574f25b51ec7956e672fda136814ac912d8c4d

15,090

py

Python

ingestion/functions/parsing/peru/peru_test.py

globaldothealth/list

26e63c83e0066aa57a341c1b2282c7f4d6bbd6f0

[ "MIT" ]

25

2020-09-01T23:03:21.000Z

2022-01-12T08:08:31.000Z

ingestion/functions/parsing/peru/peru_test.py

globaldothealth/list

26e63c83e0066aa57a341c1b2282c7f4d6bbd6f0

[ "MIT" ]

1,342

2020-07-27T09:51:00.000Z

2022-03-31T17:03:35.000Z

ingestion/functions/parsing/peru/peru_test.py

open-covid-data/healthmap-gdo-temp

5af5c9e2f7dcefa9039dc6b3a2e2c5094566fc2e

[ "MIT" ]

7

2020-08-31T00:15:17.000Z

2020-11-17T12:01:03.000Z

import os import unittest from peru import peru _SOURCE_ID = "placeholder_ID" _SOURCE_URL = "placeholder_URL" class PeruTest(unittest.TestCase): def setUp(self): self.maxDiff = 5000 def test_parse(self): ''' Includes a row where province and district are unspecified, where it should return just the department and country ''' current_dir = os.path.dirname(__file__) sample_data_file = os.path.join(current_dir, "sample_data.csv") result = peru.parse_cases(sample_data_file, _SOURCE_ID, _SOURCE_URL) self.assertCountEqual(list(result), [{'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'FERREÑAFE', 'administrativeAreaLevel2': 'FERREÑAFE', 'administrativeAreaLevel1': 'LAMBAYEQUE', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'FERREÑAFE, FERREÑAFE, LAMBAYEQUE, Peru', 'geometry': {'latitude': -6.62052434308725, 'longitude': -79.7911185840526}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/29/2020Z', 'end': '03/29/2020Z'}}], 'demographics': {'ageRange': {'start': 35.0, 'end': 35.0}, 'gender': 'Female'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'CHORRILLOS', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'CHORRILLOS, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.1926451966803, 'longitude': -77.0058884465196}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 36.0, 'end': 36.0}, 'gender': 'Male'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 1.0, 'end': 1.0}, 'gender': 'Female'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 65.0, 'end': 65.0}, 'gender': 'Female'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 32.0, 'end': 32.0}, 'gender': 'Female'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 44.0, 'end': 44.0}, 'gender': 'Male'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 29.0, 'end': 29.0}, 'gender': 'Female'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 44.0, 'end': 44.0}, 'gender': 'Female'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'name': 'LIMA, Peru', 'geoResolution': 'Admin1', 'geometry': {'latitude': -11.7855675478949, 'longitude': -76.6271728665078}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 41.0, 'end': 41.0}, 'gender': 'Male'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'EL AGUSTINO', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'EL AGUSTINO, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0400969138003, 'longitude': -76.9874046804472}}, 'events': [{'name': 'confirmed', 'value': 'Serological test', 'dateRange': {'start': '03/30/2020Z', 'end': '03/30/2020Z'}}], 'demographics': {'ageRange': {'start': 40.0, 'end': 40.0}, 'gender': 'Male'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'PCR test', 'dateRange': {'start': '01/05/2021Z', 'end': '01/05/2021Z'}}], 'demographics': {'gender': 'Male'}}, {'caseReference': {'sourceId': 'placeholder_ID', 'sourceUrl': 'placeholder_URL'}, 'location': {'administrativeAreaLevel3': 'LIMA', 'administrativeAreaLevel2': 'LIMA', 'administrativeAreaLevel1': 'LIMA', 'country': 'Peru', 'geoResolution': 'Admin3', 'name': 'LIMA, LIMA, LIMA, Peru', 'geometry': {'latitude': -12.0510318836147, 'longitude': -77.0488741340857}}, 'events': [{'name': 'confirmed', 'value': 'PCR test', 'dateRange': {'start': '01/19/2021Z', 'end': '01/19/2021Z'}}], 'demographics': {'gender': 'Male'}}])

75.829146

108

0.322068

722

15,090

6.666205

0.157895

0.029919

0.033659

0.08477

0.79493

0.787866

0.7754

0.708082

0

0.099698

0.561299

15,090

198

109

76.212121

0.627341

0.007555

0

0.756614

0

0.280112

0.054604

0

0.005291

1

0.010582

false

0

0.015873

0

0.031746

0

null

0

1

0

1

0

1

0

null

0

7

84a3f7f4b2d2c611746f6f788578142db75ee541

88

py

Python

app/views/__init__.py

accordeiro/flask-skeleton

71e2b6849a8dd95235bea8ffca274f844c069510

[ "MIT" ]

1

2015-06-24T14:04:40.000Z

app/views/__init__.py

accordeiro/flask-skeleton

71e2b6849a8dd95235bea8ffca274f844c069510

[ "MIT" ]

null

app/views/__init__.py

accordeiro/flask-skeleton

71e2b6849a8dd95235bea8ffca274f844c069510

[ "MIT" ]

null

from app.views.admin import * from app.views.api import * from app.views.auth import *

22

29

0.75

15

88

4.4

0.466667

0.318182

0.545455

0

0.147727

88

3

30

29.333333

0.88

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

84c2f2605cf00f9571d4c259eb6bc079af9b76d4

487

py

Python

pyresume/templators/__init__.py

JasonYao/resume

9402ae3a7a6e99d2d411f0446a6ee82d0404e1a1

[ "MIT" ]

1

2018-03-31T03:46:27.000Z

pyresume/templators/__init__.py

JasonYao/resume

9402ae3a7a6e99d2d411f0446a6ee82d0404e1a1

[ "MIT" ]

26

2017-05-23T03:16:11.000Z

2021-09-27T00:08:13.000Z

pyresume/templators/__init__.py

JasonYao/resume

9402ae3a7a6e99d2d411f0446a6ee82d0404e1a1

[ "MIT" ]

2

2017-04-28T21:27:27.000Z

2021-03-19T22:48:43.000Z

from .biography import load_templator from .templating import load_data, Templator from .json_raw import load_templator as json_raw_load_templator from .json_ld import load_templator as json_ld_load_templator from .latex_2_column_resume import load_templator as latex_2_column_load_templator # TODO: Replace manual module loading with dynamic loading templators: list[Templator] = [load_templator(), json_raw_load_templator(), json_ld_load_templator(), latex_2_column_load_templator()]

54.111111

134

0.858316

73

487

5.30137

0.328767

0.369509

0.196382

0.162791

0.258398

0

0.006772

0.090349

487

8

135

60.875

0.866817

0.11499

0

0.125

0

1

0

true

0

0.833333

0

0.833333

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

84c3a1a613fbdb2b6edbe007ce9a9babeb766aec

146

py

Python

2_sed/ex2_legacy_imports.py

dannysepler/refactoring-workshop

fd17342d36346a168eae6c08811b8d8e67f7f50b

[ "MIT" ]

null

2_sed/ex2_legacy_imports.py

dannysepler/refactoring-workshop

fd17342d36346a168eae6c08811b8d8e67f7f50b

[ "MIT" ]

null

2_sed/ex2_legacy_imports.py

dannysepler/refactoring-workshop

fd17342d36346a168eae6c08811b8d8e67f7f50b

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import print_function from __future__ import with_statement from a import b print("hi!")

18.25

38

0.835616

21

146

5.095238

0.52381

0.280374

0.448598

0

0.130137

146

7

39

20.857143

0.84252

0

0.020548

0

1

0

true

0

0.8

0

0.8

0.4

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

ca39d95f1448828edf3c16490769f91e83de7b17

203

py

Python

awesomeblog/core/decorators.py

tyrozz/awesome-blog

1bf6a2ae90e96e37fa4503bcb3834e77cfccf5c4

[ "MIT" ]

1

2021-04-07T23:19:52.000Z

awesomeblog/core/decorators.py

tyrozz/awesome-blog

1bf6a2ae90e96e37fa4503bcb3834e77cfccf5c4

[ "MIT" ]

null

awesomeblog/core/decorators.py

tyrozz/awesome-blog

1bf6a2ae90e96e37fa4503bcb3834e77cfccf5c4

[ "MIT" ]

null

from django.contrib.admin.views.decorators import ( staff_member_required as _staff_member_required, ) def staff_member_required(f): return _staff_member_required(f, login_url="account:login")

25.375

63

0.802956

28

203

5.428571

0.607143

0.289474

0.5

0.263158

0

0.1133

203

7

64

29

0.844444

0

0.064039

0

1

0.2

false

0

0.2

0.6

0

1

0

null

1

0

1

0

null

0

1

0

7

ca412113c44ad292a228a8fcd0cc044844aeed7b

16,128

py

Python

porousdrake/DPP/velocity_patch/solvers.py

volpatto/porousdrake

ffc2cadebc0415daa86fbeab130489d095b76193

[ "MIT" ]

1

2020-09-03T14:07:05.000Z

porousdrake/DPP/velocity_patch/solvers.py

volpatto/porousdrake

ffc2cadebc0415daa86fbeab130489d095b76193

[ "MIT" ]

null

porousdrake/DPP/velocity_patch/solvers.py

volpatto/porousdrake

ffc2cadebc0415daa86fbeab130489d095b76193

[ "MIT" ]

1

2020-11-15T18:05:43.000Z

from firedrake import * import numpy as np from firedrake.petsc import PETSc from firedrake import COMM_WORLD from porousdrake.DPP.velocity_patch.model_parameters import * try: import matplotlib.pyplot as plt plt.rcParams["contour.corner_mask"] = False plt.close("all") except: warning("Matplotlib not imported") def sdhm( mesh, degree, beta_0=Constant(1e-2), delta_0=Constant(1.0), delta_1=Constant(-0.5), delta_2=Constant(0.5), delta_3=Constant(0.5), mesh_parameter=True, solver_parameters={}, ): if not solver_parameters: solver_parameters = { "snes_type": "ksponly", "pmat_type": "matfree", # 'ksp_view': True, "ksp_type": "tfqmr", "ksp_monitor_true_residual": None, # 'snes_monitor': None, "ksp_rtol": 1e-12, "ksp_atol": 1e-12, # 'snes_rtol': 1e-5, # 'snes_atol': 1e-5, "pc_type": "fieldsplit", "pc_fieldsplit_0_fields": "0,1,2", "pc_fieldsplit_1_fields": "3,4,5", "fieldsplit_0": { "pmat_type": "matfree", "ksp_type": "preonly", "pc_type": "python", "pc_python_type": "firedrake.SCPC", "pc_sc_eliminate_fields": "0, 1", "condensed_field": { "ksp_type": "preonly", "pc_type": "lu", "pc_factor_mat_solver_type": "mumps", }, }, "fieldsplit_1": { "pmat_type": "matfree", "ksp_type": "preonly", "pc_type": "python", "pc_python_type": "firedrake.SCPC", "pc_sc_eliminate_fields": "0, 1", "condensed_field": { "ksp_type": "preonly", "pc_type": "lu", "pc_factor_mat_solver_type": "mumps", }, }, } # solver_parameters = { # 'snes_type': 'ksponly', # 'pmat_type': 'matfree', # # 'ksp_view': True, # 'ksp_type': 'tfqmr', # 'ksp_monitor_true_residual': None, # 'snes_monitor': None, # 'ksp_rtol': 1e-12, # 'ksp_atol': 1e-12, # 'pc_type': 'fieldsplit', # 'pc_fieldsplit_type': 'schur', # 'pc_fieldsplit_schur_fact_type': 'FULL', # 'pc_fieldsplit_0_fields': '0,1,2', # 'pc_fieldsplit_1_fields': '3,4,5', # 'fieldsplit_0': { # 'pmat_type': 'matfree', # 'ksp_type': 'preonly', # 'pc_type': 'python', # 'pc_python_type': 'firedrake.SCPC', # 'pc_sc_eliminate_fields': '0, 1', # 'condensed_field': { # 'ksp_type': 'preonly', # 'pc_type': 'lu', # 'pc_factor_mat_solver_type': 'mumps' # } # }, # 'fieldsplit_1': { # 'pmat_type': 'matfree', # 'ksp_type': 'preonly', # 'pc_type': 'python', # 'pc_python_type': 'firedrake.SCPC', # 'pc_sc_eliminate_fields': '0, 1', # 'condensed_field': { # 'ksp_type': 'preonly', # 'pc_type': 'lu', # 'pc_factor_mat_solver_type': 'mumps' # } # } # } pressure_family = "DG" velocity_family = "DG" trace_family = "HDiv Trace" U = VectorFunctionSpace(mesh, velocity_family, degree) V = FunctionSpace(mesh, pressure_family, degree) T = FunctionSpace(mesh, trace_family, degree) W = U * V * T * U * V * T # Trial and test functions DPP_solution = Function(W) u1, p1, lambda1, u2, p2, lambda2 = split(DPP_solution) v1, q1, mu1, v2, q2, mu2 = TestFunctions(W) # Mesh entities n = FacetNormal(mesh) h = CellDiameter(mesh) # Permeability kSpace = FunctionSpace(mesh, "DG", 0) k1 = interpolate(myk1(), kSpace) k2 = interpolate(myk2(), kSpace) def alpha1(): return mu0 / k1 def invalpha1(): return 1.0 / alpha1() def alpha2(): return mu0 / k2 def invalpha2(): return 1.0 / alpha2() # Flux BCs un1_1 = -k1 / mu0 un2_1 = -k2 / mu0 un1_2 = k1 / mu0 un2_2 = k2 / mu0 # Stabilizing parameter beta = beta_0 / h beta_avg = beta_0 / h("+") if mesh_parameter: delta_2 = delta_2 * h * h delta_3 = delta_3 * h * h # Mixed classical terms a = (dot(alpha1() * u1, v1) - div(v1) * p1 - delta_0 * q1 * div(u1)) * dx a += (dot(alpha2() * u2, v2) - div(v2) * p2 - delta_0 * q2 * div(u2)) * dx a += delta_0 * q1 * (b_factor * invalpha1() / k1) * (p2 - p1) * dx a += delta_0 * q2 * (b_factor * invalpha2() / k2) * (p1 - p2) * dx L = -delta_0 * dot(rhob1, v1) * dx L += -delta_0 * dot(rhob2, v2) * dx # Stabilizing terms ### a += ( delta_1 * inner(invalpha1() * (alpha1() * u1 + grad(p1)), delta_0 * alpha1() * v1 + grad(q1)) * dx ) a += ( delta_1 * inner(invalpha2() * (alpha2() * u2 + grad(p2)), delta_0 * alpha2() * v2 + grad(q2)) * dx ) ### a += delta_2 * alpha1() * div(u1) * div(v1) * dx a += delta_2 * alpha2() * div(u2) * div(v2) * dx L += delta_2 * alpha1() * (b_factor * invalpha1() / k1) * (p2 - p1) * div(v1) * dx L += delta_2 * alpha2() * (b_factor * invalpha2() / k2) * (p1 - p2) * div(v2) * dx ### a += delta_3 * inner(invalpha1() * curl(alpha1() * u1), curl(alpha1() * v1)) * dx a += delta_3 * inner(invalpha2() * curl(alpha2() * u2), curl(alpha2() * v2)) * dx # Hybridization terms ### a += lambda1("+") * jump(v1, n) * dS + mu1("+") * jump(u1, n) * dS a += lambda2("+") * jump(v2, n) * dS + mu2("+") * jump(u2, n) * dS ### a += beta_avg * invalpha1()("+") * (lambda1("+") - p1("+")) * (mu1("+") - q1("+")) * dS a += beta_avg * invalpha2()("+") * (lambda2("+") - p2("+")) * (mu2("+") - q2("+")) * dS # Weakly imposed BC from hybridization a += (lambda1 * dot(v1, n) + mu1 * (dot(u1, n) - un1_1)) * ds(1) a += (lambda2 * dot(v2, n) + mu2 * (dot(u2, n) - un2_1)) * ds(1) a += (lambda1 * dot(v1, n) + mu1 * (dot(u1, n) - un1_2)) * ds(2) a += (lambda2 * dot(v2, n) + mu2 * (dot(u2, n) - un2_2)) * ds(2) a += (lambda1 * dot(v1, n) + mu1 * (dot(u1, n))) * (ds(3) + ds(4)) a += (lambda2 * dot(v2, n) + mu2 * (dot(u2, n))) * (ds(3) + ds(4)) F = a - L # Solving SC below PETSc.Sys.Print( "*******************************************\nSolving using static condensation.\n" ) problem_flow = NonlinearVariationalProblem(F, DPP_solution) solver_flow = NonlinearVariationalSolver(problem_flow, solver_parameters=solver_parameters) solver_flow.solve() # Returning numerical and exact solutions p1_sol, v1_sol, p2_sol, v2_sol = _decompose_numerical_solution_hybrid(DPP_solution) return p1_sol, v1_sol, p2_sol, v2_sol def dgls( mesh, degree, delta_0=Constant(1.0), delta_1=Constant(-0.5), delta_2=Constant(0.5), delta_3=Constant(0.5), eta_p=Constant(0.0), eta_u=Constant(1.0), mesh_parameter=True, solver_parameters={}, ): if not solver_parameters: solver_parameters = { "ksp_type": "lgmres", "pc_type": "lu", "mat_type": "aij", "ksp_rtol": 1e-12, "ksp_atol": 1e-12, "ksp_monitor_true_residual": None, } pressure_family = "DG" velocity_family = "DG" U = VectorFunctionSpace(mesh, velocity_family, degree) V = FunctionSpace(mesh, pressure_family, degree) W = U * V * U * V # Trial and test functions DPP_solution = Function(W) u1, p1, u2, p2 = TrialFunctions(W) v1, q1, v2, q2 = TestFunctions(W) # Mesh entities n = FacetNormal(mesh) h = CellDiameter(mesh) # Permeability kSpace = FunctionSpace(mesh, "DG", 0) k1 = interpolate(myk1(), kSpace) k2 = interpolate(myk2(), kSpace) def alpha1(): return mu0 / k1 def invalpha1(): return 1.0 / alpha1() def alpha2(): return mu0 / k2 def invalpha2(): return 1.0 / alpha2() # Flux BCs un1_1 = -k1 / mu0 un2_1 = -k2 / mu0 un1_2 = k1 / mu0 un2_2 = k2 / mu0 # Average cell size and mesh dependent stabilization h_avg = (h("+") + h("-")) / 2.0 if mesh_parameter: delta_2 = delta_2 * h * h delta_3 = delta_3 * h * h # Mixed classical terms a = (dot(alpha1() * u1, v1) - div(v1) * p1 - delta_0 * q1 * div(u1)) * dx a += (dot(alpha2() * u2, v2) - div(v2) * p2 - delta_0 * q2 * div(u2)) * dx a += delta_0 * q1 * (b_factor * invalpha1() / k1) * (p2 - p1) * dx a += delta_0 * q2 * (b_factor * invalpha2() / k2) * (p1 - p2) * dx L = -delta_0 * dot(rhob1, v1) * dx L += -delta_0 * dot(rhob2, v2) * dx # DG terms a += ( jump(v1, n) * avg(p1) * dS + jump(v2, n) * avg(p2) * dS - avg(q1) * jump(u1, n) * dS - avg(q2) * jump(u2, n) * dS ) # Edge stabilizing terms a += ( (eta_u * h_avg) * avg(alpha1()) * (jump(u1, n) * jump(v1, n)) * dS + (eta_u * h_avg) * avg(alpha2()) * (jump(u2, n) * jump(v2, n)) * dS + (eta_p / h_avg) * avg(1.0 / alpha1()) * dot(jump(q1, n), jump(p1, n)) * dS + (eta_p / h_avg) * avg(1.0 / alpha2()) * dot(jump(q2, n), jump(p2, n)) * dS ) # Volume stabilizing terms ### a += ( delta_1 * inner(invalpha1() * (alpha1() * u1 + grad(p1)), delta_0 * alpha1() * v1 + grad(q1)) * dx ) a += ( delta_1 * inner(invalpha2() * (alpha2() * u2 + grad(p2)), delta_0 * alpha2() * v2 + grad(q2)) * dx ) L += -delta_1 * dot(delta_0 * alpha1() * v1 + grad(q1), invalpha1() * rhob1) * dx L += -delta_1 * dot(delta_0 * alpha2() * v2 + grad(q2), invalpha2() * rhob2) * dx ### a += delta_2 * alpha1() * div(u1) * div(v1) * dx a += delta_2 * alpha2() * div(u2) * div(v2) * dx a += -delta_2 * alpha1() * (b_factor * invalpha1() / k1) * (p2 - p1) * div(v1) * dx a += -delta_2 * alpha2() * (b_factor * invalpha2() / k2) * (p1 - p2) * div(v2) * dx ### a += delta_3 * inner(invalpha1() * curl(alpha1() * u1), curl(alpha1() * v1)) * dx a += delta_3 * inner(invalpha2() * curl(alpha2() * u2), curl(alpha2() * v2)) * dx # Weakly imposed BC by Nitsche's method a += dot(v1, n) * p1 * ds + dot(v2, n) * p2 * ds - q1 * dot(u1, n) * ds - q2 * dot(u2, n) * ds L += -q1 * un1_1 * ds(1) - q2 * un2_1 * ds(1) - q1 * un1_2 * ds(2) - q2 * un2_2 * ds(2) a += ( eta_u / h * inner(dot(v1, n), dot(u1, n)) * ds + eta_u / h * inner(dot(v2, n), dot(u2, n)) * ds ) L += ( eta_u / h * dot(v1, n) * un1_1 * ds(1) + eta_u / h * dot(v2, n) * un2_1 * ds(1) + eta_u / h * dot(v1, n) * un1_2 * ds(2) + eta_u / h * dot(v2, n) * un2_2 * ds(2) ) # Solving problem_flow = LinearVariationalProblem(a, L, DPP_solution, bcs=[], constant_jacobian=False) solver_flow = LinearVariationalSolver( problem_flow, options_prefix="dpp_flow", solver_parameters=solver_parameters ) solver_flow.solve() # Returning numerical and exact solutions p1_sol, v1_sol, p2_sol, v2_sol = _decompose_numerical_solution_mixed(DPP_solution) return p1_sol, v1_sol, p2_sol, v2_sol def cgls( mesh, degree, delta_0=Constant(1.0), delta_1=Constant(-0.5), delta_2=Constant(0.5), delta_3=Constant(0.5), eta_u=Constant(10), mesh_parameter=True, solver_parameters={}, ): if not solver_parameters: solver_parameters = { "ksp_type": "lgmres", "pc_type": "lu", "mat_type": "aij", "ksp_rtol": 1e-12, "ksp_atol": 1e-12, "ksp_monitor_true_residual": None, } pressure_family = "CG" velocity_family = "CG" U = VectorFunctionSpace(mesh, velocity_family, degree) V = FunctionSpace(mesh, pressure_family, degree) W = U * V * U * V # Trial and test functions DPP_solution = Function(W) u1, p1, u2, p2 = TrialFunctions(W) v1, q1, v2, q2 = TestFunctions(W) # Mesh entities n = FacetNormal(mesh) h = CellDiameter(mesh) # Permeability kSpace = FunctionSpace(mesh, "DG", 0) k1 = interpolate(myk1(), kSpace) k2 = interpolate(myk2(), kSpace) def alpha1(): return mu0 / k1 def invalpha1(): return 1.0 / alpha1() def alpha2(): return mu0 / k2 def invalpha2(): return 1.0 / alpha2() # Flux BCs un1_1 = -k1 / mu0 un2_1 = -k2 / mu0 un1_2 = k1 / mu0 un2_2 = k2 / mu0 # Mesh stabilizing parameter if mesh_parameter: delta_2 = delta_2 * h * h delta_3 = delta_3 * h * h # Mixed classical terms a = (dot(alpha1() * u1, v1) - div(v1) * p1 - delta_0 * q1 * div(u1)) * dx a += (dot(alpha2() * u2, v2) - div(v2) * p2 - delta_0 * q2 * div(u2)) * dx a += delta_0 * q1 * (b_factor * invalpha1() / k1) * (p2 - p1) * dx a += delta_0 * q2 * (b_factor * invalpha2() / k2) * (p1 - p2) * dx L = -delta_0 * dot(rhob1, v1) * dx L += -delta_0 * dot(rhob2, v2) * dx # Stabilizing terms ### a += ( delta_1 * inner(invalpha1() * (alpha1() * u1 + grad(p1)), delta_0 * alpha1() * v1 + grad(q1)) * dx ) a += ( delta_1 * inner(invalpha2() * (alpha2() * u2 + grad(p2)), delta_0 * alpha2() * v2 + grad(q2)) * dx ) ### a += delta_2 * alpha1() * div(u1) * div(v1) * dx a += delta_2 * alpha2() * div(u2) * div(v2) * dx a += -delta_2 * alpha1() * (b_factor * invalpha1() / k1) * (p2 - p1) * div(v1) * dx a += -delta_2 * alpha2() * (b_factor * invalpha2() / k2) * (p1 - p2) * div(v2) * dx ### a += delta_3 * inner(invalpha1() * curl(alpha1() * u1), curl(alpha1() * v1)) * dx a += delta_3 * inner(invalpha2() * curl(alpha2() * u2), curl(alpha2() * v2)) * dx # Weakly imposed BC by Nitsche's method a += dot(v1, n) * p1 * ds + dot(v2, n) * p2 * ds - q1 * dot(u1, n) * ds - q2 * dot(u2, n) * ds L += -q1 * un1_1 * ds(1) - q2 * un2_1 * ds(1) - q1 * un1_2 * ds(2) - q2 * un2_2 * ds(2) a += ( eta_u / h * inner(dot(v1, n), dot(u1, n)) * ds + eta_u / h * inner(dot(v2, n), dot(u2, n)) * ds ) L += ( eta_u / h * dot(v1, n) * un1_1 * ds(1) + eta_u / h * dot(v2, n) * un2_1 * ds(1) + eta_u / h * dot(v1, n) * un1_2 * ds(2) + eta_u / h * dot(v2, n) * un2_2 * ds(2) ) # Solving problem_flow = LinearVariationalProblem(a, L, DPP_solution, bcs=[], constant_jacobian=False) solver_flow = LinearVariationalSolver( problem_flow, options_prefix="dpp_flow", solver_parameters=solver_parameters ) solver_flow.solve() # Returning numerical and exact solutions p1_sol, v1_sol, p2_sol, v2_sol = _decompose_numerical_solution_mixed(DPP_solution) return p1_sol, v1_sol, p2_sol, v2_sol def _decompose_numerical_solution_hybrid(solution): v1_sol = solution.sub(0) v1_sol.rename("Macro velocity", "label") p1_sol = solution.sub(1) p1_sol.rename("Macro pressure", "label") v2_sol = solution.sub(3) v2_sol.rename("Micro velocity", "label") p2_sol = solution.sub(4) p2_sol.rename("Micro pressure", "label") return p1_sol, v1_sol, p2_sol, v2_sol def _decompose_numerical_solution_mixed(solution): v1_sol = solution.sub(0) v1_sol.rename("Macro velocity", "label") p1_sol = solution.sub(1) p1_sol.rename("Macro pressure", "label") v2_sol = solution.sub(2) v2_sol.rename("Micro velocity", "label") p2_sol = solution.sub(3) p2_sol.rename("Micro pressure", "label") return p1_sol, v1_sol, p2_sol, v2_sol

33.253608

98

0.520833

2,135

16,128

3.743326

0.096019

0.021772

0.025025

0.011261

0.852853

0.838839

0.829079

0.824825

0.815065

0

0.06754

0.313306

16,128

484

99

33.322314

0.654086

0.12097

0

0.736232

0

0.071378

0.01884

0

1

0.049275

false

0

0.02029

0.034783

0.118841

0

null

0

1

0

1

0

null

0

7

04893f7c9505f50980ba45ecfe9846717a545106

14,004

py

Python

accounts/calendar_views.py

saurabhpetkar/club_portal

4c0f68ca01f4e4ee7048b58d40226afb9f8ae876

[ "MIT" ]

2

2019-01-12T08:13:37.000Z

2019-01-17T19:18:51.000Z

accounts/calendar_views.py

saurabhpetkar/club_portal

4c0f68ca01f4e4ee7048b58d40226afb9f8ae876

[ "MIT" ]

57

2018-11-07T05:07:09.000Z

2022-01-13T01:02:43.000Z

accounts/calendar_views.py

saurabhpetkar/club_portal

4c0f68ca01f4e4ee7048b58d40226afb9f8ae876

[ "MIT" ]

12

2018-11-12T20:10:06.000Z

2019-10-15T16:33:23.000Z

from django.shortcuts import render from .models import Calendar import datetime import calendar from .forms import CalendarForm, ChooseMonthAndYearForm # from first_app.forms import calendar_data # Create your views here. next_m = 0 next_y = 0 back_m = 0 back_y = 0 def currentdate(): return datetime.date.today() # def index(request): # return render(request, 'put_calendar/index.html') def hello(request, select, show): x = currentdate() y = x.isoformat() year = int(y[:4]) month = int(y[5:7]) global next_m next_m = month global next_y next_y = year global back_m back_m = month global back_y back_y = year mandy = ChooseMonthAndYearForm() if select != '1': trig = select.split('m') year = int(trig[0]) month = int(trig[1]) if int(show) < 10: sdate = '0' + str(show) else: sdate = str(show) if int(month) < 10: smonth = '0' + str(month) else: smonth = str(month) final_date = str(year) + '-' + str(smonth) + '-' + str(sdate) if request.method == 'POST': form = CalendarForm(request.POST) if form.is_valid(): form_instance = form.save(commit=False) form_instance.user = request.user form_instance.date = final_date form_instance.save() form = CalendarForm() month_calendar = calendar.monthcalendar(year, month) month_name = calendar.month_name[month] year_name = str(month_name + ' , ' + str(year)) len_month = len(month_calendar) p = [] b = [] for i in range(len(month_calendar)): for j in range(len(month_calendar[i])): if month_calendar[i][j] > 0: if month_calendar[i][j] < 10: y = str('0' + str(month_calendar[i][j])) p.append(y) if month_calendar[i][j] >= 10: y = str(month_calendar[i][j]) p.append(y) q = [] for i in range(len(p)): if month < 10: c = str(str(year) + '-0' + str(month) + '-' + p[i]) else: c = str(str(year) + '-' + str(month) + '-' + p[i]) q.append(c) dates_with_works = [] work_on_date = [] for i in range(len_month): a = [0, 0, 0, 0, 0, 0, 0] b.append(a) dates_needed = [] query = Calendar.objects.filter(user=request.user, date=final_date).order_by('date') for i in range(len(query)): s = str(query[i].work_title) work_on_date.append(s) c = query[i].date d = c.isoformat() dates_needed.append(d) dates_with_works.append(int(d[8:10])) for m in range(len(q)): for i in range(len(b)): for j in range(len(b[i])): for k in range(len(dates_with_works)): if month_calendar[i][j] == dates_with_works[k] and q[m] == dates_needed[k]: b[i][j] = [dates_with_works[k], work_on_date[k]] print(b) return render(request, 'accounts/put_templates/date.html', {'year_no': str(year) + 'm' + str(month), 'month_cal': month_calendar, 'zipped_data': zip(month_calendar, b), 'present_year': year_name, 'form': form, 'final_date': final_date, 'events': query, 'mandy': mandy}) else: form = CalendarForm() month_calendar = calendar.monthcalendar(year, month) month_name = calendar.month_name[month] year_name = str(month_name + ' , ' + str(year)) len_month = len(month_calendar) p = [] b = [] for i in range(len(month_calendar)): for j in range(len(month_calendar[i])): if month_calendar[i][j] > 0: if month_calendar[i][j] < 10: y = str('0' + str(month_calendar[i][j])) p.append(y) if month_calendar[i][j] >= 10: y = str(month_calendar[i][j]) p.append(y) q = [] for i in range(len(p)): if month < 10: c = str(str(year) + '-0' + str(month) + '-' + p[i]) else: c = str(str(year) + '-' + str(month) + '-' + p[i]) q.append(c) dates_with_works = [] work_on_date = [] for i in range(len_month): a = [0, 0, 0, 0, 0, 0, 0] b.append(a) dates_needed = [] query = Calendar.objects.filter(user=request.user, date=final_date).order_by('date') for i in range(len(query)): s = str(query[i].work_title) work_on_date.append(s) c = query[i].date d = c.isoformat() dates_needed.append(d) dates_with_works.append(int(d[8:10])) for m in range(len(q)): for i in range(len(b)): for j in range(len(b[i])): for k in range(len(dates_with_works)): if month_calendar[i][j] == dates_with_works[k] and q[m] == dates_needed[k]: b[i][j] = [dates_with_works[k], work_on_date[k]] print(b) return render(request, 'accounts/put_templates/date.html', {'year_no': str(year) + 'm' + str(month), 'month_cal': month_calendar, 'zipped_data': zip(month_calendar, b), 'present_year': year_name, 'form': form, 'final_date': final_date, 'events': query, 'mandy': mandy}) else: month_calendar = calendar.monthcalendar(year, month) month_name = calendar.month_name[month] year_name = str(month_name + ' , ' + str(year)) len_month = len(month_calendar) p = [] b = [] for i in range(len(month_calendar)): for j in range(len(month_calendar[i])): if month_calendar[i][j] > 0: if month_calendar[i][j] < 10: y = str('0' + str(month_calendar[i][j])) p.append(y) if month_calendar[i][j] >= 10: y = str(month_calendar[i][j]) p.append(y) q = [] for i in range(len(p)): if month < 10: c = str(str(year) + '-0' + str(month) + '-' + p[i]) else: c = str(str(year) + '-' + str(month) + '-' + p[i]) q.append(c) dates_with_works = [] work_on_date = [] for i in range(len_month): a = [0, 0, 0, 0, 0, 0, 0] b.append(a) dates_needed = [] query = Calendar.objects.order_by('work_title') for i in range(len(query)): s = str(query[i].work_title) work_on_date.append(s) c = query[i].date d = c.isoformat() dates_needed.append(d) dates_with_works.append(int(d[8:10])) for m in range(len(q)): for i in range(len(b)): for j in range(len(b[i])): for k in range(len(dates_with_works)): if month_calendar[i][j] == dates_with_works[k] and q[m] == dates_needed[k]: b[i][j] = [dates_with_works[k], work_on_date[k]] print(b) return render(request, 'accounts/put_templates/date.html', {'year_no': str(year) + 'm' + str(month), 'month_cal': month_calendar, 'zipped_data': zip(month_calendar, b), 'present_year': year_name, 'mandy': mandy}) def date(request, select, show): global back_m global back_y global next_m global next_y if next_m < 12 and next_m >= 1: next_m = next_m + 1 next_y = next_y else: next_m = 1 next_y = next_y + 1 back_m = next_m back_y = next_y return grid(request, next_y, next_m) def date1(request, select, show): global back_m global back_y global next_m global next_y if back_m > 1 and back_m <= 12: back_m = back_m - 1 back_y = back_y else: back_m = 12 back_y = back_y - 1 next_m = back_m next_y = back_y return grid(request, back_y, back_m) def choose_event(request, select, show): if request.method == 'POST': form = ChooseMonthAndYearForm(request.POST) month = int(request.POST['month']) year = int(request.POST['year']) return grid(request, year, month) def grid(request, year, month): mandy = ChooseMonthAndYearForm() if request.method == 'POST': form = CalendarForm(request.POST) if form.is_valid(): form_instance = form.save(commit=False) form_instance.user = request.user form_instance.save() month_calendar = calendar.monthcalendar(year, month) month_name = calendar.month_name[month] year_name = str(month_name + ' , ' + str(year)) len_month = len(month_calendar) b = [] dates_with_works = [] dates_needed = [] p = [] for i in range(len(month_calendar)): for j in range(len(month_calendar[i])): if month_calendar[i][j] > 0: if month_calendar[i][j] < 10: y = str('0' + str(month_calendar[i][j])) p.append(y) if month_calendar[i][j] >= 10: y = str(month_calendar[i][j]) p.append(y) q = [] work_on_date = [] for i in range(len(p)): if month < 10: c = str(str(year) + '-0' + str(month) + '-' + p[i]) else: c = str(str(year) + '-' + str(month) + '-' + p[i]) q.append(c) for i in range(len_month): a = [0, 0, 0, 0, 0, 0, 0] b.append(a) query = Calendar.objects.all() for i in range(len(query)): s = str(query[i].work_title) work_on_date.append(s) c = query[i].date d = c.isoformat() dates_needed.append(d) dates_with_works.append(int(d[8:10])) for m in range(len(q)): for i in range(len(b)): for j in range(len(b[i])): for k in range(len(dates_with_works)): if month_calendar[i][j] == dates_with_works[k] and q[m] == dates_needed[k]: b[i][j] = [dates_with_works[k], work_on_date[k]] return render(request, 'accounts/put_templates/date.html', {'year_no': str(year) + 'm' + str(month), 'month_cal': month_calendar, 'zipped_data': zip(month_calendar, b), 'present_year': year_name, 'mandy': mandy}) else: form = CalendarForm() month_calendar = calendar.monthcalendar(year, month) month_name = calendar.month_name[month] year_name = str(month_name + ' , ' + str(year)) len_month = len(month_calendar) b = [] dates_with_works = [] dates_needed = [] p = [] for i in range(len(month_calendar)): for j in range(len(month_calendar[i])): if month_calendar[i][j] > 0: if month_calendar[i][j] < 10: y = str('0' + str(month_calendar[i][j])) p.append(y) if month_calendar[i][j] >= 10: y = str(month_calendar[i][j]) p.append(y) q = [] work_on_date = [] for i in range(len(p)): if month < 10: c = str(str(year) + '-0' + str(month) + '-' + p[i]) else: c = str(str(year) + '-' + str(month) + '-' + p[i]) q.append(c) for i in range(len_month): a = [0, 0, 0, 0, 0, 0, 0] b.append(a) query = Calendar.objects.all() for i in range(len(query)): s = str(query[i].work_title) work_on_date.append(s) c = query[i].date d = c.isoformat() dates_needed.append(d) dates_with_works.append(int(d[8:10])) for m in range(len(q)): for i in range(len(b)): for j in range(len(b[i])): for k in range(len(dates_with_works)): if month_calendar[i][j] == dates_with_works[k] and q[m] == dates_needed[k]: b[i][j] = [dates_with_works[k], work_on_date[k]] return render(request, 'accounts/put_templates/date.html', {'year_no': str(year) + 'm' + str(month), 'month_cal': month_calendar, 'zipped_data': zip(month_calendar, b), 'present_year': year_name, 'mandy': mandy}) def event_enter(request, date_selected): if request.method == 'POST': form = CalendarForm(request.POST) if form.is_valid(): form_instance = form.save(commit=False) form_instance.user = request.user form_instance.save() else: form = CalendarForm() return render(request, 'accounts/put_templates/date.html', {'form': form})

32.567442

106

0.480863

1,750

14,004

3.675429

0.064571

0.121269

0.069963

0.825093

0.821517

0.816542

0.809235

0

0.01462

0.38946

14,004

430

107

32.567442

0.737661

0.009926

0

0.822823

0

0.04004

0.013852

0

1

0.021021

false

0

0.015015

0.003003

0.066066

0.009009

0

null

0

1

0

1

0

null

0

7

04fc1c66f58707ba53257368e438c012b07d55d7

382,401

pyt

Python

eran/NNet/nnet/ACASXU_run2a_4_5_batch_2000_16bit.pyt

pauls658/ReluDiff-ICSE2020-Artifact

212854fe04f482183c239e5dfec70106a9a83df8

[ "Apache-2.0" ]

7

2020-01-27T21:25:49.000Z

2022-01-07T04:37:37.000Z

eran/NNet/nnet/ACASXU_run2a_4_5_batch_2000_16bit.pyt

yqtianust/ReluDiff-ICSE2020-Artifact

149f6efe4799602db749faa576980c36921a07c7

[ "Apache-2.0" ]

1

2022-01-25T17:41:54.000Z

2022-01-26T02:27:51.000Z

eran/NNet/nnet/ACASXU_run2a_4_5_batch_2000_16bit.pyt

yqtianust/ReluDiff-ICSE2020-Artifact

149f6efe4799602db749faa576980c36921a07c7

[ "Apache-2.0" ]

3

2020-03-14T17:12:17.000Z

2022-03-16T09:50:46.000Z

ReLU [[0.0553801, 0.190198, -0.0377036, -1.32009, -0.704992], [-0.010481, -0.118571, 0.153946, -0.736114, -1.00878], [0.482564, 0.0565022, 0.0443098, 0.0600691, 0.0020876], [-0.0778212, -0.0577902, -0.153575, 0.0605465, 0.450204], [0.0143941, -0.25066, -0.132743, 0.533158, -0.0781143], [-0.00869665, -0.447464, -0.0517125, -0.0990526, 0.204336], [0.010042, -0.00129605, -0.00514204, -0.0715019, -0.0436908], [-0.0696566, 0.215441, -0.00483027, 0.155244, -0.858598], [-0.0412334, 0.845604, 0.238394, 0.166022, -0.0812237], [0.386318, -0.0315554, 0.00926705, -0.369564, -0.731116], [-0.727862, -0.136911, 0.0147124, -0.76237, -0.181072], [0.00181044, -0.131803, 0.0962716, 0.175322, -0.863416], [0.0213996, 0.126362, 0.0304863, -1.13285, 1.17788], [-1.41449, -0.0028435, -0.0144381, -0.0132612, 0.00265051], [-0.126224, 0.115034, -0.124887, -0.754803, -0.478396], [0.00489443, -0.0621162, -0.442564, -0.325057, 0.29953], [0.0238864, -0.294626, 0.437456, 0.167242, -1.57446], [-0.0339431, 0.212746, 0.555427, 0.401026, -0.113187], [0.0534015, 0.505959, -0.695019, -0.597797, 0.757852], [0.0759885, 1.02061, -0.767079, 0.790857, -0.781343], [0.0280475, -0.0544412, 0.492328, -0.388467, 0.188625], [0.00126882, -0.00331824, 0.00365573, -0.0122686, 0.0154782], [0.378386, 2.2269, 0.117052, -0.224842, 0.335837], [0.150166, -2.23327, 0.0177583, 0.146265, -0.332893], [-0.0746921, -0.958603, 0.971528, 0.609819, -0.817018], [-0.00927227, -1.58696, 0.0165695, 0.00278922, 0.0574048], [-0.0132054, -0.849359, 0.548887, 0.310252, -1.48819], [0.0478079, -0.681258, -0.868954, 0.583286, -0.306058], [0.0828738, 0.440471, 0.630704, -0.0333658, 0.00772661], [-0.00806285, 0.0531106, -0.222073, 0.0686884, -1.50157], [-0.114841, 0.919164, 0.190187, 0.0437794, 0.00520963], [-1.76543, -0.0157442, -0.0315514, 0.00938973, -0.000685154], [-0.0530375, -0.450235, 1.76927, 0.5936, -0.6578], [0.0198095, -0.113013, -0.552609, -0.518049, 0.285155], [0.0214781, -1.74124, 1.73425, -0.0566436, 0.459649], [-0.649957, -0.0397138, -0.00584056, -0.00988717, 0.0166818], [0.00680587, 0.0170974, -0.0202533, -1.63096, -0.944574], [-0.116581, 1.9092, -2.42837, -0.107407, 0.248435], [-0.00247847, -0.00046304, 0.00565075, -0.000137539, 0.00251783], [-0.0357091, -0.166897, -0.00179253, -0.579197, -1.04002], [0.344397, -0.939464, 0.00142697, -0.18813, 0.190268], [0.0630945, 1.17492, -1.27231, 0.157916, -0.00482825], [-1.81425, -0.00623258, -0.0159597, 0.00737333, -0.00575161], [-0.00829891, -0.0115763, -0.00241857, 0.00255223, -0.0173112], [-0.077549, -0.28407, 0.00596384, -0.420798, 0.511508], [-0.00162356, -0.621229, 0.599885, -0.170725, 0.68297], [-0.196361, -0.909656, 0.158577, -0.606075, -0.199725], [0.0163317, 0.0189992, 0.00514905, -0.0639583, -0.0439335], [-0.0514028, -1.17772, -0.301449, 0.382633, -0.500615], [-0.936931, -0.203562, 0.279398, -0.20136, 0.320543], [0.0554, 0.1902, -0.0377, -1.32, -0.705], [-0.01048, -0.1186, 0.1539, -0.7363, -1.009], [0.4827, 0.0565, 0.0443, 0.06006, 0.002089], [-0.0778, -0.0578, -0.1536, 0.06055, 0.4502], [0.0144, -0.2507, -0.1327, 0.533, -0.0781], [-0.0087, -0.4475, -0.05173, -0.09906, 0.2043], [0.01004, -0.001296, -0.005142, -0.0715, -0.0437], [-0.06964, 0.2155, -0.00483, 0.1553, -0.8584], [-0.04123, 0.8457, 0.2384, 0.166, -0.08124], [0.3862, -0.03156, 0.00927, -0.3696, -0.731], [-0.728, -0.137, 0.01471, -0.762, -0.181], [0.00181, -0.1318, 0.09625, 0.1753, -0.8633], [0.0214, 0.1263, 0.03049, -1.133, 1.178], [-1.414, -0.002844, -0.014435, -0.01326, 0.002651], [-0.1262, 0.11505, -0.1249, -0.755, -0.4785], [0.004894, -0.0621, -0.4426, -0.325, 0.2996], [0.02388, -0.2947, 0.4375, 0.1672, -1.574], [-0.03394, 0.2128, 0.5557, 0.4011, -0.11316], [0.0534, 0.506, -0.695, -0.5977, 0.758], [0.076, 1.0205, -0.767, 0.791, -0.7812], [0.02805, -0.05444, 0.4924, -0.3884, 0.1886], [0.001268, -0.003319, 0.003656, -0.01227, 0.01548], [0.3784, 2.227, 0.11707, -0.2249, 0.336], [0.1501, -2.232, 0.01776, 0.1462, -0.333], [-0.0747, -0.9585, 0.9717, 0.61, -0.817], [-0.00927, -1.587, 0.01657, 0.002789, 0.0574], [-0.01321, -0.849, 0.549, 0.3103, -1.488], [0.04782, -0.681, -0.869, 0.5835, -0.3062], [0.0829, 0.4404, 0.631, -0.03336, 0.007725], [-0.008064, 0.0531, -0.222, 0.06866, -1.502], [-0.11487, 0.919, 0.1902, 0.0438, 0.00521], [-1.766, -0.01575, -0.03156, 0.00939, -0.000685], [-0.05304, -0.4502, 1.77, 0.5938, -0.6577], [0.0198, -0.11304, -0.5527, -0.518, 0.2852], [0.02148, -1.741, 1.734, -0.05664, 0.4597], [-0.65, -0.0397, -0.00584, -0.00989, 0.01668], [0.006805, 0.01709, -0.02025, -1.631, -0.9443], [-0.1166, 1.909, -2.428, -0.1074, 0.2484], [-0.002478, -0.000463, 0.00565, -0.0001376, 0.002518], [-0.0357, -0.1669, -0.001793, -0.579, -1.04], [0.3445, -0.9395, 0.001427, -0.1881, 0.1903], [0.0631, 1.175, -1.272, 0.158, -0.00483], [-1.814, -0.006233, -0.01596, 0.007374, -0.005753], [-0.0083, -0.01157, -0.002419, 0.002552, -0.01732], [-0.0776, -0.2842, 0.005962, -0.421, 0.5117], [-0.001623, -0.621, 0.6, -0.1708, 0.683], [-0.1964, -0.9097, 0.1586, -0.606, -0.1997], [0.01633, 0.019, 0.00515, -0.06396, -0.04395], [-0.0514, -1.178, -0.3015, 0.3826, -0.5005], [-0.937, -0.2036, 0.2793, -0.2014, 0.3206]] [-0.557027, -0.317043, 0.138104, 0.189978, 0.188149, 0.0552362, -0.06767, -0.260805, -0.267183, -0.348518, -0.614078, 0.217921, -0.156318, -0.191004, -0.563467, 0.198722, -0.642526, -0.0575729, 0.0511302, -0.187772, -0.0248378, -0.0206649, 0.259386, -0.183478, -0.149923, 0.0451136, -0.371688, -0.0188617, 0.0366777, -0.552902, 0.189979, -0.358897, 0.256364, 0.138195, -0.478434, 0.0133866, -0.133131, -0.349492, -0.0137361, -0.652247, 0.180223, -0.408499, -0.429542, -0.0201813, 0.0710165, 0.0685803, -0.303011, -0.0773268, 0.0294964, -0.20074, -0.557, -0.3171, 0.1381, 0.19, 0.1881, 0.05524, -0.0677, -0.2607, -0.267, -0.3486, -0.6143, 0.2179, -0.1564, -0.191, -0.5635, 0.1987, -0.6426, -0.0576, 0.05112, -0.1877, -0.02484, -0.02066, 0.2593, -0.1835, -0.1499, 0.0451, -0.3716, -0.01886, 0.03668, -0.5527, 0.19, -0.359, 0.2563, 0.1382, -0.4785, 0.01339, -0.1332, -0.3496, -0.01373, -0.6523, 0.1802, -0.4084, -0.4294, -0.02019, 0.07104, 0.0686, -0.303, -0.07733, 0.0295, -0.2007] ReLU [[0.0566575, -0.886943, 0.230586, 1.45451, 0.597745, 0.227455, 0.0324496, 0.0962953, 0.633446, -0.321703, 0.614659, 0.513456, -0.207988, -0.106215, 1.56553, 0.258868, -0.735231, -0.95162, -0.087422, 0.0441749, -0.860643, 0.0136313, -0.0763127, -0.0170699, -0.0763528, 0.13214, 0.523823, -0.112733, 0.335358, 1.00594, 0.568737, -1.39865, 0.204936, -0.148696, 0.173248, -0.0788495, 1.17112, 0.0316677, 0.0556427, -0.633747, 0.0171092, -0.0598277, -2.08626, -0.00464231, -0.140753, 0.127757, -0.200616, 0.0578406, -0.0620558, 0.675837, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0112267, -0.0286864, 0.0311223, 0.0419601, -0.0218081, -0.00774441, 0.0556754, -0.0286823, -0.0128888, 0.0377224, 0.0405741, -0.0155171, -0.0286421, -0.0437483, -0.0424458, -0.0465849, 0.0084671, 0.000231055, -0.0260211, -0.0409128, -0.00940972, -0.00526273, -0.0265895, 0.0142803, -0.0252259, -0.0143645, -0.0142295, 0.00947478, 0.0234896, -0.0573354, -0.0293224, -0.0523232, -0.00181744, -0.0131525, -0.0381496, -0.0503052, -0.0087803, -0.0247571, 0.00776736, 0.00488961, -0.00309288, 0.00886165, 0.0121621, 0.0369953, -0.0365977, -0.0112973, 0.043858, -0.00142178, -0.0204356, 0.0231885, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.00504374, -0.0464097, -0.0498462, -0.0304533, 0.00302208, 0.0322248, 0.0296794, 0.0367799, 0.0227954, -0.0383889, 0.0385381, -0.0367588, -0.00679786, -0.0504207, 0.0316609, -0.0427613, -0.0221433, -0.0257581, -0.0399118, -0.0340255, 0.0231971, 0.0224371, -0.0115063, 0.00552454, -0.0018375, 0.0149984, -0.0267956, -0.0538718, 0.034087, 0.035375, -0.0463983, -0.0160521, 0.0271612, -0.0050365, -0.0470514, 0.0291255, 0.0272604, -0.000217995, 0.0356944, -0.016358, 0.00891133, 0.0376687, -0.0475234, 0.0447155, 0.0285667, -0.0252544, 0.00285394, -0.00270473, -0.0268782, -0.00185817, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.377525, 0.112185, -1.1619, -0.444595, -1.71525, -1.61309, -0.0674231, 1.33914, 0.691602, 0.588673, 0.369135, -0.845436, -2.52656, 0.558474, 1.3696, 0.75013, 0.469634, -0.529725, -0.192167, 0.407051, 0.339037, 0.0397048, -0.0926856, -2.22371, -0.0412369, -1.76197, 0.748254, 0.00263616, -0.102593, 1.51041, 0.162677, -0.680222, 0.351902, 0.671622, 0.996997, 1.53587, -0.259994, -0.442276, 0.0293023, 1.78556, 1.01464, 0.156254, 1.66674, 0.0343558, 0.418668, -0.206413, 0.317031, -0.0610785, 0.501862, 0.445306, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.34908, 0.120792, 1.10705, 0.0681482, -0.261093, 0.123956, 0.0834657, -0.113424, -0.0934773, 1.37932, -2.36824, 0.338262, 0.306419, -0.699439, 0.706828, -0.00103402, -0.111298, -0.686809, 0.0104301, -0.0505599, -0.72632, -0.00985458, 0.334483, 1.1772, 0.206715, -0.0663537, -0.215016, 0.365249, 0.159313, 0.306795, -0.0242865, -0.191828, 0.379393, 0.278277, -0.689262, -0.169154, -0.478237, -0.0325523, -0.00222893, 0.919736, 0.482243, -0.4136, 0.336234, -0.0244682, -0.414824, -0.0276796, 0.141941, 0.0379019, -0.351966, 0.166649, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0423158, 0.706556, 0.149792, -0.816403, -0.193987, -1.45324, 0.0151341, -1.17154, -2.77325, 1.27635, 0.280781, -0.475095, -0.100811, -1.35603, -2.5568, -0.366193, -1.84443, -0.75066, -0.291455, -0.0185313, 0.213009, 0.0194092, -0.0131288, 0.277549, -2.31768, 0.250379, -0.489956, -1.5717, -0.286765, -2.53283, -0.340916, -2.60784, 1.23306, 0.133259, -2.19479, -0.471285, -0.973891, 1.09622, 0.0176062, 3.6785, -0.594739, 4.20202, -4.53677, 0.0539721, -0.945468, 1.64178, 3.29903, 0.0584497, 0.184615, -0.732787, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0375253, -0.0305356, -0.0262838, -0.0579221, 0.0266807, 0.0109767, -0.00704786, 0.00341256, 0.0125713, 0.038845, -0.0123605, 0.0308559, 0.0328326, -0.0040399, 0.0276922, 0.0190819, -0.0438157, -0.0106141, 0.0137063, 0.0125937, -0.00305571, -0.0364192, -0.0336753, -0.0405723, -0.0115847, 0.0111881, 0.0240347, -0.0158172, -0.0436974, -0.0131908, -0.000541112, 0.0256702, -0.0249343, -0.000638733, -0.031507, 0.0172331, -0.0283839, 0.00727735, -0.0228869, -0.0460157, -0.0196476, -0.0499876, -0.0245726, 0.0410408, -0.0516399, 0.0314717, 1.37251e-05, -0.0124679, -0.0442359, -0.0127343, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.000244819, -0.38248, 1.81978, 0.275369, 0.60334, 0.131322, 0.0501444, -0.0260271, -0.186852, 1.13628, 0.458005, 0.217254, -0.204227, -2.13189, 0.0632322, 0.0134891, 0.236612, 0.488996, 0.325143, 0.181775, 0.692817, -0.00133557, 0.345212, -0.0167631, -0.361024, 0.273217, 0.309543, -0.151751, 0.326382, 0.464742, -0.701932, -2.20269, -0.135494, 0.206295, 0.0356574, -0.948911, 0.0572745, -0.173056, -0.0240137, -1.0537, 0.629684, 0.88545, -9.51497, -0.0123121, -0.310005, 0.171877, -0.107679, 0.0628073, 0.183218, -0.72922, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.487687, -0.587927, 0.196683, 0.125844, -0.0696401, 0.890886, 0.0997762, -1.13694, 1.86193, 0.657471, -1.72525, 0.0387606, -0.358006, -0.0293386, 1.40958, -0.213652, 1.0917, 1.32941, 0.243467, -1.64478, 0.0974222, 0.0221039, 0.118198, 0.0745903, 0.347848, -0.186472, -0.162519, 0.640643, 1.58531, -0.328757, 0.222549, -0.0797493, -0.157845, -0.078084, -1.13974, -0.0735975, 0.390608, -1.33571, 0.0527736, -1.63188, 0.89929, -2.80574, 0.0505383, 0.0318459, 1.95704, 0.345222, -1.3532, 0.0906519, 0.574992, 0.529116, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.145943, 0.345862, 0.558316, -0.561703, -0.418964, -0.0601791, 0.0349879, 0.387201, -1.24267, -0.163624, -0.63582, -0.247941, 0.655903, -0.364268, 0.209071, -0.119284, 0.853323, 0.685325, -0.1906, 0.437243, -0.0151264, 0.0472489, 0.0351498, -0.0690239, -0.449261, -0.143982, -0.433861, 0.603212, -0.527496, -0.429884, -0.444871, -0.597174, 0.025364, -0.0329944, -0.348101, -0.0227748, 0.0817933, -0.383106, -0.0283425, -0.215912, -0.0593923, -0.0860069, -0.866936, 0.0387609, -0.229344, -0.190438, -0.406143, 0.0598102, 0.230038, -0.0236759, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.01911, 2.26028, -0.450729, -1.25282, -1.18248, 0.723411, -0.00752673, -1.17643, 2.23023, 0.481789, -0.0237311, -2.40671, 0.554721, 0.267296, 0.264926, 0.307094, -3.20595, -1.13599, 0.182035, 1.59532, 0.0963449, 0.0397644, 0.288633, -0.161414, 2.00226, -0.3859, 0.0109566, 0.0447989, 0.0359261, -2.7127, 0.301199, 0.271198, 0.0989276, 0.622195, 1.25379, 0.095005, -0.157387, 0.977858, 0.0250872, 0.303424, 0.599718, -1.0387, 0.672899, -0.00993041, 0.884717, 0.0453394, 0.169373, 0.00340578, 0.512466, 1.15533, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.181847, -0.461969, 0.597039, 0.401535, 0.67818, 1.11699, 0.0516457, 1.08401, -0.822757, -0.107817, -2.40868, 0.84119, -0.225539, -0.0895863, -0.431638, 0.212196, -0.415454, 0.417287, 0.0138937, -0.229277, 0.41048, 0.00552106, -0.206036, -0.0386024, 0.0174153, -1.33412, -0.285902, 0.148826, -0.201547, -0.493115, 0.379782, -0.337845, 0.122052, -0.26976, -0.141651, 0.292212, 0.0409835, 0.127332, -0.0515634, 1.18676, -0.503445, -0.361453, -0.39565, -0.0491936, -0.0936745, 0.28499, 0.0498659, 0.058024, -0.0293801, -0.132769, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.795252, 0.0759886, -0.598678, 0.341264, 0.152706, -0.0498407, 0.0982676, -0.768335, 0.578385, -0.238336, -1.46266, 0.537457, 0.685212, -0.0853625, 1.03508, 0.107274, 0.697614, -0.219276, 0.416518, -0.537134, -0.583389, -0.0217382, -0.397924, 0.480579, 0.369483, 0.276095, 0.520203, 0.712521, -0.0264957, 0.730464, 0.177435, 0.272815, -0.518256, -0.585156, -0.4811, 0.0879773, -0.468558, -0.407164, 0.0258813, 0.3788, 0.911367, 0.817278, 0.677622, -0.0322538, -2.14685, -0.255604, -0.0350247, 0.0743049, 0.167002, 0.771497, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0142154, 0.0608605, -0.343283, 0.284569, 0.572987, -0.574893, -0.0667932, -1.85959, 0.775011, -0.626682, -0.695703, -0.702999, 0.0872007, -0.00798904, 1.34966, 0.415809, 2.77823, -1.15716, 0.96962, -1.44698, -0.0857441, 0.0247745, -0.0282822, 0.291721, 1.19593, -0.939613, 0.749361, 1.37451, 0.0599326, -3.41684, -1.0667, -0.502515, -1.32919, 0.136194, -0.334965, 0.315904, 0.368124, -1.14446, 0.0129079, -0.867094, 0.265176, -2.55064, 0.779143, 0.0180276, 0.061928, -1.18224, -1.30092, -0.00174132, 1.51017, -0.345314, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.440923, -1.63207, 0.108396, 0.0246664, -1.66169, 0.145853, -0.0578173, -0.651022, -1.35602, -0.895698, -0.996828, 0.0797387, -0.218981, 0.260353, 1.4288, -0.0905217, -1.13167, -0.603433, -0.270705, -0.600027, 0.160398, 0.00968109, 0.0159161, 0.134747, -0.837106, -0.0430073, 1.49847, 0.0782186, -0.272802, 1.85381, 0.115658, -0.468968, 0.60554, 0.164905, -0.253429, 0.188269, -0.329754, 0.37062, -0.0500694, -2.9964, 0.150063, 0.114843, -0.0239656, -0.0199717, 0.000714967, -1.25558, 0.662538, -0.0786537, -0.0141523, 0.0948839, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.246229, -0.660003, -0.108316, -0.778707, -0.256514, 0.693604, -0.024098, -0.415239, 1.67271, -0.33721, 0.32824, -0.775435, 0.321869, 0.0886571, 1.49677, -0.834428, -0.94957, -0.300986, -1.20711, 0.338976, 0.310334, -0.0450165, -0.0625634, 0.141738, 0.569376, 0.595003, -0.310876, -0.635246, -0.257889, 2.25379, -0.679055, 0.679786, 0.802399, -0.590539, 0.170628, 0.315941, 0.265157, 0.511506, -0.0466546, -2.29527, 0.170894, -0.176633, 0.452344, 0.00282725, 0.695072, 0.585204, -0.0240918, 0.048591, 0.168488, 0.850836, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0648798, -0.713205, 0.184109, 0.263193, -1.17017, -0.27902, -0.0184611, 0.149203, 0.0625735, -1.47176, -0.544243, 0.253936, -0.232978, 0.554867, -0.492828, -0.793316, -0.628855, -0.553705, -0.269334, -0.517286, -0.227616, -0.0283357, 0.0847632, 1.08829, 0.745166, -1.18479, -0.636596, -5.98398, 0.691477, -1.08156, 0.379564, 0.267218, 0.0285503, -0.0327507, 0.413654, -0.652442, 0.457227, 0.0199745, 0.0233787, 2.36146, 0.21126, 0.152223, 0.515382, 0.0122972, -0.765941, -1.3653, -1.45485, 0.0278161, -0.499104, -0.752126, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0877714, 0.594682, -0.468329, 1.76406, -0.0831016, -0.4663, 0.0506801, 0.064633, -0.021765, -0.0174555, 0.282811, 0.706214, -0.0797849, -0.975125, -0.309657, -0.45979, 0.470287, -0.902108, 0.126915, -0.0244586, 0.141614, -0.0228444, -0.892338, 0.183324, -0.165465, 0.0315152, 0.415779, -0.811849, -0.140529, -0.669645, 0.0327296, -0.279654, -0.264833, -0.241752, -0.158728, 0.143443, -0.0138105, 0.139231, 0.04216, 0.463097, 0.0227689, 0.183031, 1.05698, 0.0246632, -0.442754, 0.212869, 0.477364, 0.0486496, 0.183229, -0.42994, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0345073, -0.023264, 0.000605256, -0.0717934, -0.0535752, 0.0206562, -0.0397345, -0.0456846, 0.0222671, 0.0455364, 0.00817602, -0.00981517, 0.0189005, 0.0150684, -0.058151, 0.0248626, 0.00578861, 0.0302838, 0.0425335, 0.00692726, 0.00643819, -0.0444926, 0.0334587, 0.0405654, -0.0240477, -0.0139168, -0.0202117, -0.022642, -0.0518317, 0.0271231, -0.0186023, -0.0303917, -0.0420824, -0.0080056, 0.0101854, 0.00783324, -0.0415649, -0.0556682, -0.00352495, 0.0234421, 0.0388969, -0.0556853, 0.00268545, 0.0278309, -0.0561288, -0.0480787, -0.033947, 0.039185, -0.0378302, -0.0304035, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.58633, 0.438732, 0.0200577, 1.1784, -0.0845582, 0.0986984, 0.0950237, -0.0982923, 1.06439, -0.582533, 0.381889, 0.417171, -0.0430939, 0.0346135, -1.3605, 0.11913, -0.982431, 0.700004, 0.362675, -0.821623, -0.478803, -0.0417712, 0.0420779, -0.256704, -0.0441338, 0.103111, 0.0597218, 0.568777, 1.17287, -3.74795, 0.66222, -0.141397, -0.536032, -0.0488814, -1.19941, -0.652637, 0.069944, -0.834254, -0.011009, -1.47332, 0.42554, -2.50711, -0.0251331, -0.0377687, 0.463134, -0.249951, 0.0651639, 0.0433228, 0.367277, 0.665172, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.104856, 0.213985, 0.500872, -1.60166, -0.498544, 0.217992, 0.0460801, -0.160995, -0.512666, 1.87008, 0.681351, -1.52953, -0.340704, 0.111278, -1.90133, -0.362015, -0.213668, 0.932387, -0.863125, 0.494217, -0.241433, -0.0391745, -0.326819, -0.0370894, -0.00995829, -0.263929, 0.355007, -0.324813, 1.36031, 0.818368, 0.549364, -0.322965, -0.350454, 0.705665, -1.41687, 0.0330546, -0.540712, 0.235485, 0.0163556, 0.07737, 0.649505, -1.81483, -0.0397011, -0.0184345, 1.00884, 0.121649, -0.631759, 0.0140766, 0.355955, 0.792969, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.190017, -0.176666, 0.862852, 0.267403, -0.100373, 0.567067, -0.00363644, -1.50895, 1.51627, 1.22398, 2.33617, -0.188437, -0.0516359, -0.344849, 2.01942, -0.311764, -0.717134, 0.320258, 0.418724, 0.763896, -1.34214, 0.00964182, -0.0433202, -0.205245, 0.35233, 0.305866, 0.461229, -0.157048, 0.225948, 0.239461, 0.495281, -0.129372, -0.017714, -0.600791, 0.150609, 0.502796, 0.0760881, 0.122303, -0.0141077, 1.19975, -0.798428, -0.0712829, -0.582187, 0.00588628, 0.27573, 0.397124, 0.210933, 0.0220056, 0.04037, -0.37138, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.186561, -0.170019, 0.234048, -0.299775, 0.656264, 0.00337622, 0.0329379, -0.180777, 0.634188, 0.537222, 0.206188, -0.240952, -0.0805749, 0.290026, 1.19055, -0.146819, -0.441834, 0.0557701, 0.0552614, -2.04872, 0.0692606, -0.0011736, 0.182394, -0.674005, -0.0636562, 0.165715, 1.89022, 0.627899, 0.731291, -1.76318, 1.03139, 0.472603, -1.18, 0.333642, 1.05844, 0.20359, 0.0712123, 0.475923, -0.00534451, 0.658245, 0.0985115, -1.00116, 0.000831981, -0.0175927, 0.431012, -0.471486, -0.343864, -0.0233023, 0.183987, 0.176769, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.556134, 0.295114, -0.307221, -0.12859, 0.162358, 0.287115, -0.0356249, 0.15974, 0.809326, 0.252038, 0.301994, 0.744063, 0.791187, 1.63988, 0.823666, -1.12408, -1.00023, 0.831528, 0.120488, -0.141429, -0.599594, -0.0373065, -1.60278, 1.1246, -0.45696, -0.634278, 0.408557, -0.0939014, 1.08571, 3.05493, -0.00844536, 1.13779, 0.425493, -0.64756, -1.73879, 0.34551, 0.286578, 0.0880463, 0.0242349, -1.06334, 0.515013, 1.45087, 1.05863, -0.0427058, -0.390423, 1.91765, -0.0786041, -0.0442716, -0.781786, 0.620425, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.350242, 0.0296617, -0.738328, 0.114678, -0.392205, 0.0970929, -0.0105927, 0.142615, -3.43232, 0.503728, 0.370657, -0.128545, -0.206008, 0.833324, 0.832859, 0.432469, -0.549753, 1.57585, 0.692997, 0.120008, 1.09042, -0.00285732, -0.551422, 0.902218, 1.41392, -0.829847, -0.56265, 1.61241, 1.3242, -1.74288, -0.552389, -1.51765, -0.286381, 0.613846, -0.105492, -0.799065, 0.438392, -0.258334, -0.0359138, 0.227812, -0.0454768, 1.80715, -3.48199, 0.00706228, 0.621769, 0.195971, 0.326618, -0.0479138, -0.00139742, -1.21838, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.13308, 0.0738553, -0.0655643, 0.346969, 0.143684, 0.590521, 0.0305996, -1.3155, -1.70751, 0.668998, -1.13258, 0.206683, -1.07457, -0.144142, 1.61217, 0.157876, -0.971489, 2.60186, -0.131549, 0.698813, -0.478913, 0.021539, -0.970298, 0.616065, -0.291093, 0.589562, 0.280511, 0.0425333, 1.44654, -0.185334, 0.237082, 0.411828, -0.155771, -0.0897715, -0.849426, 0.104194, -0.133887, 0.90485, -0.0228045, 2.28946, 0.19809, -0.675426, -0.401409, 0.0278287, 1.20885, 0.549968, 0.130972, -0.051972, -0.0609346, 0.291788, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.355877, 0.074585, 0.543993, 0.0094941, -0.488597, 0.800184, 0.0133344, 0.0873287, 0.484354, -0.137375, 0.0691673, 0.392801, 0.393054, 0.0273709, -0.344398, -0.345044, -1.45882, 0.105087, -0.119247, -0.387154, -0.0955563, 0.0128327, -0.107151, -0.0683734, -0.1342, 0.555954, -0.23078, -0.367461, 0.775111, 1.17014, 0.353249, -0.651854, 0.478701, -0.736876, -0.430849, 0.0867644, -0.144416, -0.249169, -0.0255341, -0.0348127, -0.45255, 0.0364509, 0.492345, 0.00233357, 0.0860406, 0.0982313, -0.400312, 0.0104205, -0.0481961, 0.176154, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.48934, -2.61871, 0.523867, -0.546705, -1.1973, -1.88871, 0.100343, -0.150907, -0.457815, 1.98869, 6.04372, 0.496071, -1.0815, -0.62071, 0.167771, -0.169979, 2.11485, -1.606, -0.138813, 0.0560474, -0.309248, 0.0125485, 0.127597, 0.990157, 0.5091, -1.69503, 1.14117, 0.608649, -0.94089, 0.626275, -0.246207, -1.30284, -0.196009, -0.996228, 0.995066, -1.02815, 1.02812, 0.755761, 0.0373495, -0.125095, -0.610197, 1.17382, -3.36472, -0.0291519, -0.463616, -1.8597, 1.85315, 0.0976282, -0.950093, -4.65116, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.875352, 0.299999, -0.558586, -1.01837, -1.09446, 0.0231376, -0.0156277, -5.44767, 0.670859, 0.190351, -0.449405, -1.91947, 0.154591, -0.0934756, 0.185571, 0.286901, -7.37806, -0.6377, -0.166756, -1.43411, 0.703947, -0.0146976, -0.12314, 0.261381, -0.889668, 0.150155, -0.555912, -0.0305427, 0.540046, -4.56203, -0.155935, -0.214393, -0.0184498, 0.960204, -0.603861, 0.145163, -0.196522, -0.650219, -0.0382655, -2.37421, 0.159874, -0.817143, -0.277655, -0.00288902, -0.0747411, -0.633264, 0.196235, -0.060413, 0.353046, 0.615464, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.00989925, 0.0408112, 0.0222571, -0.0192318, 0.0336411, 0.0437608, -0.0218266, 0.00654142, -0.0437913, -0.0390459, 0.0281461, -0.0168665, -0.0175365, 0.0306678, -0.0257691, -0.0209148, 0.0230185, -0.0330928, -0.0190128, 0.00577224, 0.0347872, -0.0399777, -0.0183539, -0.0389549, -0.0388145, 0.0178445, -0.00507923, -0.0186408, -0.0378365, -0.00609372, -0.0305898, -0.00688025, -0.048024, -0.024257, -0.058554, -0.0216803, -0.0304288, -0.0226648, -0.0171038, -0.0218681, 0.0155073, -0.0378867, -0.0382861, 0.00853588, 0.00775763, -0.022186, -0.0373835, 0.0228459, -0.0375108, -0.0287254, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0441219, 2.57145, -0.0540204, -0.0514344, 1.31714, 0.812391, 0.0161108, 0.125519, 0.109744, -2.75991, 0.00432638, 0.770327, 0.777566, -0.0513164, 0.0096526, -0.718816, -0.405026, 0.635844, -1.81719, -0.288166, 1.54955, 0.0138982, 0.201884, -0.290579, 0.240071, 0.646898, 0.0359214, -0.546447, -0.577472, 1.73588, 0.377061, -0.532835, -0.415209, 0.704112, -0.0138888, -0.460609, -3.76659, -0.157399, 0.0328416, 0.0277412, -0.413569, -0.177464, 0.398373, -0.0354396, 0.0932446, -0.155182, -1.95032, -0.0470554, 0.0587571, 0.184558, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.411289, -1.60569, 0.0629511, -0.806082, -0.770867, 0.246553, -0.00229392, 2.27837, -6.02591, -1.14218, 0.211296, 0.0399824, 0.0894669, 0.657961, -2.56337, -0.608787, 0.49211, -3.15043, -0.508961, -1.46554, 0.434984, 0.000888676, -0.050613, 0.0801453, 2.3042, 0.295424, -0.681567, -2.02956, -0.60352, 4.51445, -0.763578, 0.726418, -0.0778358, -1.42221, 2.42509, 0.156027, 0.468577, -0.114349, -0.0108623, 0.639681, 0.00871794, 0.0133278, 0.801101, 0.0297853, 0.150921, 0.600465, 0.3876, 0.0393227, -0.0138865, -0.159958, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.08961, 0.773649, -0.17191, 1.06054, 2.12036, 0.626866, 0.00785014, -0.905464, -0.65552, 0.63365, 0.578249, 0.392071, 0.187524, -0.147862, 1.99624, 0.0313428, 0.376379, 1.07581, 0.55606, -0.36071, 1.07612, -0.0285355, 0.0556019, -0.447871, -1.13925, 0.527802, -0.501332, -0.75093, -0.519414, -0.803971, -0.12349, -1.08738, -0.15951, 0.197769, -0.577044, -0.0160379, 0.610642, -0.824513, 0.0333632, 0.033283, 0.138315, 0.191128, -0.320059, -0.0174192, -0.0826227, -1.08845, -0.165392, 0.00999685, -0.516267, -0.489053, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.390032, 0.203215, -0.0704345, -0.576127, -0.118973, -0.0264338, 0.0821641, 1.60779, -2.16668, 0.10021, -0.993419, 0.5978, -0.950612, -0.668529, -1.92835, -0.214793, 1.42054, 0.317243, -0.13934, 1.05521, -0.856989, -0.0292194, 1.1198, 1.28942, 0.127685, 0.710626, 0.715554, -0.60714, -0.393182, 1.5645, 0.143547, -0.909254, -0.294504, -0.0127911, 0.612582, -1.59583, -0.214846, -0.000207184, -0.0149363, 3.79878, -0.779139, -0.835343, -1.3764, 0.00980285, -0.578353, 1.10859, -0.83294, 0.106501, -0.0273668, -0.649119, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.00154739, 0.290167, -1.6727, 0.280135, 0.223504, -0.117137, 0.0230853, 0.134865, 0.163097, 0.0322647, -1.25181, 0.147647, 0.15914, -0.275305, -0.503192, -0.178651, -0.111522, 0.396618, 0.246615, 0.428948, -0.419862, 0.0442446, -0.0930593, 0.103728, -0.317618, 0.639421, -0.299068, -0.210926, -0.198063, -0.128892, 0.18899, -2.17379, 0.29265, -0.167759, -0.473774, 0.240971, -0.107053, 0.156288, 0.0275476, 1.0984, -0.0852038, 0.410218, -5.34178, -0.0166803, -0.332746, 0.135087, 0.367799, 0.0686241, -0.133533, 0.394125, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0947261, -0.0253837, -0.0717219, -0.707829, 0.177132, 0.386833, 0.0353594, -1.43738, -0.717836, -0.373564, -0.510524, 0.046821, 0.648317, -0.400213, -3.25939, -0.374583, -0.590091, -0.727124, 0.00919414, 0.089166, 0.0560927, 0.00240063, -0.0253784, -0.113658, 0.0761041, 1.0583, 0.185559, 0.778679, -0.182294, -1.70124, 0.533055, -0.61823, -0.665185, -0.363279, -1.0502, 0.463417, -0.0234154, 0.183073, -0.03217, 1.4056, 0.801534, 1.17137, -1.79086, 0.0426667, 0.329774, 0.0141646, 0.283006, 0.0271014, 0.444215, 1.09721, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.198076, 0.533921, -0.125359, -0.260811, -0.024686, 0.325941, 0.0637398, -0.00359718, -1.21337, -0.221233, -0.607081, 0.467499, 0.213512, -0.0911222, -0.743891, 0.310424, 0.744339, -0.922364, 0.118881, 0.995886, 0.326093, -0.0099077, 0.0608646, 0.141621, 0.31068, -0.346364, -0.329684, -0.359319, -0.472189, -0.00074171, -0.107808, -0.0301606, -0.0641094, 0.0706103, -0.793633, 0.207059, -0.288765, 0.14521, -0.00391595, 0.142511, -0.0539983, -0.420556, -0.296284, -0.00724858, 1.05741, 1.40833, -0.247382, 0.0740253, -0.600497, -0.471993, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0535403, 0.554431, 0.0853417, 0.406319, 0.0145552, -1.39444, -0.00726305, 0.17759, 0.325076, 0.46329, -0.204918, 0.388982, -0.530363, 0.407425, -0.248122, 0.258163, 0.607674, -0.27644, 0.482927, 0.162894, 0.517553, 0.00318702, -0.233806, -0.602762, 0.16773, -1.88042, 0.394356, -0.168146, -0.398574, 0.0840358, -0.173725, -0.129058, -0.434925, 0.46756, 0.645383, 0.693387, -0.335332, -0.382333, -0.0390095, 0.370092, -0.273675, 0.842109, 0.309505, 0.0020546, -1.40963, -0.208951, 0.0534885, 0.0730893, 0.242664, -0.576013, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0470067, 0.0294559, -0.0492486, -0.0354673, 0.00769722, -0.0122949, 0.0386137, 0.0278825, -0.047217, -0.0198802, 0.0406254, -0.0138496, 0.0051009, -0.00300363, 0.044655, 0.00655871, -0.0420764, -0.015427, 0.0205839, -0.00803614, 0.014996, 0.0301648, -0.0367273, -0.0643906, 0.0178261, 0.0165806, 0.0153959, -0.0366424, -0.0335817, 0.0021255, 0.00349398, -0.0534741, 0.021362, 0.0066101, 0.0147461, 0.0151114, -0.0610155, -0.0159879, 0.0264758, 0.000476675, 0.0211, 0.0236464, -0.0457114, 0.0289232, 0.0210815, -0.0331501, 0.0120221, -0.032336, -0.0231229, -0.0252931, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.610716, -0.286072, -0.478817, 1.30707, 1.29565, 0.0288889, 0.0348883, -0.0306226, -0.0944289, -1.31996, -0.755699, -0.0837464, 0.210171, 1.08554, -1.79975, -0.169906, -0.106645, 0.130582, 0.371455, 0.0323318, -0.452259, 0.041392, -0.018725, -0.20193, -0.411756, 0.10752, -0.0390294, 0.56509, -0.347837, -0.374911, -0.195757, 0.566694, 0.501423, -0.735321, -0.0278603, 1.54466, 0.161582, 0.250226, -0.0302147, -1.06757, -0.292536, 0.0780629, 0.249524, -0.0217857, -0.34573, 0.374927, 0.298234, 0.00773501, -0.00772001, -0.12699, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.610755, -1.89742, -0.324779, 1.62153, 0.340517, 0.135322, 0.0466983, -1.16995, 0.221351, -1.54249, 0.134479, 0.859255, -0.508505, -0.057686, 1.31511, -0.262777, -1.34151, 0.756218, 0.682869, -1.02197, 1.16584, 0.0205732, 0.00963084, 1.15616, -1.0663, 0.655276, -0.0308994, -0.285051, 0.330204, 0.469937, -0.271884, 0.123566, 0.777452, -1.15024, -1.30671, -0.649395, 0.956551, -0.211537, -0.0346957, 0.289016, 0.531949, 1.49965, 0.850505, -0.0160587, 1.1857, -0.673036, -0.0862142, 0.0527193, -0.110452, 0.785696, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.837696, -0.584332, -0.0601505, -1.54587, 0.538069, 0.438474, -0.00590967, -4.42216, -0.882494, -0.329361, -2.9676, -0.978091, 1.25534, -1.61302, -0.672891, -1.27955, -1.01973, -1.48322, -1.20425, -0.448862, 0.272711, 0.00149033, -0.816033, 0.379119, 1.10142, 0.993195, 0.671343, -0.424983, -0.166358, 2.66109, -1.43311, -2.43087, 0.879333, -1.84155, 1.83216, -0.429725, 0.325415, 2.20149, 0.00135861, -2.10894, 0.483406, 0.549453, -3.58442, -0.0311826, -0.0865619, 0.141533, -1.11123, -0.0323794, 0.677098, -0.278038, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.863445, -1.57738, 0.232364, 1.22873, -0.0204112, 0.395961, -0.0576078, 1.33739, -0.955175, -1.03957, -4.42217, 1.10722, 0.00806377, 0.266313, -3.36331, 0.183604, 1.05824, -0.74048, 0.29395, -0.229056, -0.119455, -0.0443224, -0.207595, -0.448165, 0.167957, 0.150002, 0.833177, -0.902891, 0.263744, 3.13873, -0.471584, 0.799583, -0.238198, -0.768014, -0.845479, 0.0376902, 0.514212, -0.377451, -0.00735792, 0.78211, 0.177952, 1.75595, -1.52491, 0.0446172, 0.537249, 0.495552, -1.07117, -0.107169, -0.33982, 0.33822, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.473283, -0.450633, -0.478355, 0.13074, 0.330065, 0.273499, 0.0868823, 2.02395, -0.245901, -0.788462, 1.46611, -0.280558, -0.28561, -0.601743, -0.191123, 0.229672, -0.262144, 0.364152, 0.439885, 0.374948, 0.581021, 0.0123727, -0.232856, 0.122417, -0.393826, 0.38461, 0.490367, -0.131125, 0.616592, 1.88607, -0.811258, -0.925936, -0.0253196, 0.339918, -0.688223, -0.923048, 0.121045, -0.29676, -0.020222, -0.1561, -0.252263, -0.169618, -0.600861, -0.0315333, 0.606056, -0.457938, -0.26319, 0.082405, 0.185023, -1.06271, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.810242, 0.113636, -0.105592, -0.216382, -0.100001, 1.75269, 0.0104732, 2.46942, 1.48335, -0.526179, 0.400669, 1.03199, -0.00750793, -0.223137, 2.06099, -0.494627, -1.69585, 1.07157, 0.0906824, 0.848594, -1.13084, -0.0368065, 1.08498, -0.771697, -0.783785, 0.105314, -0.776347, -0.645035, 0.114237, 0.868518, 0.677247, -0.271629, 0.560876, -0.337047, -0.428959, 0.127251, 0.222131, -0.429953, 0.0378395, 0.905855, -0.261032, 3.92533, 0.419241, -0.0134357, 0.613707, 0.265602, -1.19286, 0.0305718, -1.32047, 0.352392, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.262288, 0.412957, -0.319933, 0.0245819, -0.631888, -0.272538, -0.0613503, -0.258094, -0.225997, -1.15533, -1.16448, 0.543625, -0.361905, 0.444386, -1.21589, 0.536699, 0.6819, 0.552473, 0.297685, 0.692084, 0.0452458, -0.00843163, -0.298482, -0.441979, -0.0143193, 0.411795, -0.0462187, -0.75885, 0.0884722, -0.0438499, -0.149006, 0.248442, -0.0540165, 0.305586, -0.375579, 0.478995, -0.539542, -0.0286828, 0.0100369, -2.67691, -0.26251, -0.380524, 1.82078, -0.016739, 0.374334, 0.214312, 0.1968, -0.065056, 0.363059, -0.342501, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0547023, -0.0694519, 0.435038, -0.0672935, 0.653476, -0.789705, -0.0103252, -0.153953, 1.96176, -0.704197, -1.06415, 1.31855, 0.370558, 0.224441, 1.44133, -0.0157389, 0.227919, -0.989558, 0.657929, -0.740702, 0.540559, -0.0131007, -0.107461, 0.176075, 0.437909, -0.246782, 0.222487, 0.160153, -1.11795, -3.15123, -0.261176, 0.220382, -0.155376, 0.468695, 0.805086, 0.031749, 0.0143038, 0.424842, -0.0379838, -1.78158, -0.391662, -1.43131, 0.313703, -0.0310593, -0.970225, 0.107721, -0.693167, 0.0554268, -0.165589, -0.380542, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.206101, -0.0502535, 0.0273176, -0.193413, -0.970976, 0.130296, -0.0228225, -1.26989, -1.40062, 1.04582, -1.75642, -0.0396868, 0.609338, 0.378339, 0.173156, -0.855559, -0.412995, 0.168602, -1.61331, -0.271556, 0.000181844, 0.00410194, -0.429278, -0.109792, 0.623493, 0.0485287, 0.336578, -0.186591, -0.464048, 1.50201, -0.674428, 0.230967, 0.597335, -0.996954, -0.568548, 0.388832, 0.26549, 0.835441, -0.00305616, 0.847817, 0.417681, 1.8836, 0.579625, 0.016492, 0.407276, 0.509091, -0.502841, -0.033443, 0.346993, -1.25621, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0430308, -0.0507441, -0.0340275, 0.0170621, -0.0212162, -0.0245178, 0.0316967, -0.0226182, 0.0209672, 0.00791943, 0.0128553, -0.0219924, -0.0321493, -0.0418026, -0.0325168, -0.0468227, 0.00876138, -0.0396294, -0.0347355, -0.0314302, -0.0340371, 0.00225405, -0.0226152, 0.0231806, -0.0145877, -0.0376479, -0.00199067, 0.0141855, 0.0085875, -0.063467, -0.0616177, -0.0516846, -0.0387743, -0.0307538, 0.0215187, -0.0368715, -0.0336392, 0.0374868, 0.00753022, -0.040917, -0.0330896, 0.00832754, 0.0326107, -0.0192944, 0.0187889, -0.0148533, -0.0153374, 0.021779, 0.0543209, 0.0106731, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.471027, -0.156611, -0.0429382, -0.772776, -1.17639, 0.231679, -0.0347801, -0.690192, -0.00113331, -0.284155, 0.0260061, 0.747238, -0.09524, -0.0366892, -0.320514, -0.269948, -0.312604, -0.578058, -0.309002, 0.621899, 0.065412, -0.0261291, 0.023213, -0.0594319, -0.0983378, -0.000430707, -0.782595, -0.693231, 0.534412, -0.390392, -0.480244, -0.0616526, 0.141112, 0.258903, -0.31267, 0.305553, -0.479098, -0.103666, 0.00859899, 0.173878, -0.221702, 0.583248, -0.477242, -0.0143994, 0.418996, -0.221456, 0.288104, -0.0173556, -0.0869253, -0.119048, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.05667, -0.8867, 0.2306, 1.454, 0.5977, 0.2274, 0.03244, 0.0963, 0.6333, -0.3218, 0.6147, 0.5137, -0.208, -0.1062, 1.565, 0.2588, -0.7354, -0.9517, -0.0874, 0.0442, -0.861, 0.01363, -0.0763, -0.01707, -0.07635, 0.1321, 0.524, -0.11273, 0.3354, 1.006, 0.569, -1.398, 0.205, -0.1487, 0.1732, -0.07886, 1.171, 0.03168, 0.05563, -0.634, 0.0171, -0.0598, -2.086, -0.004642, -0.1407, 0.1278, -0.2006, 0.05783, -0.06204, 0.676], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01123, -0.02869, 0.03113, 0.04196, -0.0218, -0.007744, 0.05566, -0.02869, -0.012886, 0.03772, 0.0406, -0.01552, -0.02864, -0.04376, -0.04245, -0.04657, 0.00847, 0.000231, -0.02602, -0.04092, -0.00941, -0.005264, -0.0266, 0.01428, -0.02522, -0.014366, -0.01423, 0.009476, 0.02348, -0.05734, -0.02933, -0.05234, -0.001818, -0.01315, -0.03815, -0.0503, -0.00878, -0.02475, 0.007767, 0.00489, -0.003094, 0.008865, 0.01216, 0.037, -0.0366, -0.0113, 0.04385, -0.001422, -0.02043, 0.0232], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005043, -0.04642, -0.04984, -0.03046, 0.003021, 0.03223, 0.02968, 0.03677, 0.0228, -0.0384, 0.03854, -0.03677, -0.006798, -0.0504, 0.03165, -0.04276, -0.02214, -0.02576, -0.03992, -0.03403, 0.0232, 0.02243, -0.011505, 0.005524, -0.001838, 0.015, -0.0268, -0.05386, 0.0341, 0.03537, -0.0464, -0.01605, 0.02716, -0.005035, -0.04706, 0.02913, 0.02727, -0.000218, 0.0357, -0.01636, 0.00891, 0.03766, -0.04752, 0.0447, 0.02856, -0.02525, 0.002853, -0.002705, -0.02687, -0.001858], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3774, 0.1122, -1.162, -0.4446, -1.715, -1.613, -0.06744, 1.339, 0.6914, 0.589, 0.3691, -0.845, -2.527, 0.5586, 1.369, 0.75, 0.4697, -0.53, -0.1921, 0.407, 0.339, 0.0397, -0.0927, -2.225, -0.04123, -1.762, 0.748, 0.002636, -0.1026, 1.511, 0.1627, -0.68, 0.3518, 0.6714, 0.997, 1.536, -0.26, -0.4424, 0.0293, 1.785, 1.015, 0.1562, 1.667, 0.03436, 0.4187, -0.2064, 0.3171, -0.06107, 0.502, 0.4453], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.349, 0.1208, 1.107, 0.0682, -0.261, 0.12396, 0.0835, -0.1134, -0.0935, 1.379, -2.37, 0.3384, 0.3064, -0.699, 0.707, -0.001034, -0.1113, -0.687, 0.01043, -0.05057, -0.7266, -0.00986, 0.3345, 1.177, 0.2067, -0.06635, -0.215, 0.3652, 0.1593, 0.307, -0.02429, -0.1918, 0.3794, 0.2783, -0.6895, -0.1692, -0.4783, -0.03256, -0.00223, 0.92, 0.4822, -0.4136, 0.3362, -0.02448, -0.4148, -0.02768, 0.142, 0.0379, -0.352, 0.1666], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.04233, 0.7065, 0.1498, -0.8164, -0.194, -1.453, 0.01514, -1.172, -2.773, 1.276, 0.2808, -0.475, -0.1008, -1.356, -2.557, -0.3662, -1.845, -0.7505, -0.2915, -0.01852, 0.213, 0.01941, -0.01313, 0.2776, -2.318, 0.2505, -0.49, -1.571, -0.2869, -2.533, -0.3408, -2.607, 1.233, 0.1333, -2.195, -0.4712, -0.974, 1.097, 0.01761, 3.678, -0.5947, 4.203, -4.535, 0.054, -0.9453, 1.642, 3.299, 0.05844, 0.1846, -0.733], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.03754, -0.03053, -0.02629, -0.05792, 0.02669, 0.01098, -0.00705, 0.003412, 0.01257, 0.03885, -0.01236, 0.03085, 0.03284, -0.00404, 0.0277, 0.01909, -0.04382, -0.01061, 0.01371, 0.012596, -0.003056, -0.0364, -0.03366, -0.04056, -0.01158, 0.011185, 0.02403, -0.01582, -0.0437, -0.01319, -0.000541, 0.02567, -0.02493, -0.000639, -0.0315, 0.01723, -0.02838, 0.00728, -0.02289, -0.04602, -0.01965, -0.05, -0.02457, 0.04105, -0.05164, 0.03146, 1.37e-05, -0.01247, -0.04425, -0.01273], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0002449, -0.3826, 1.819, 0.2754, 0.6035, 0.1313, 0.05014, -0.02603, -0.1869, 1.137, 0.458, 0.2173, -0.2042, -2.133, 0.06323, 0.01349, 0.2366, 0.489, 0.3252, 0.1818, 0.693, -0.001335, 0.3452, -0.01677, -0.361, 0.2732, 0.3096, -0.1517, 0.3264, 0.4648, -0.702, -2.203, -0.1355, 0.2063, 0.03564, -0.9487, 0.05728, -0.1731, -0.02402, -1.054, 0.63, 0.8853, -9.516, -0.012314, -0.31, 0.1719, -0.10767, 0.0628, 0.1832, -0.729], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4878, -0.588, 0.1967, 0.1259, -0.06964, 0.891, 0.0998, -1.137, 1.862, 0.6577, -1.726, 0.03876, -0.358, -0.02934, 1.409, -0.2136, 1.092, 1.329, 0.2434, -1.645, 0.0974, 0.02211, 0.1182, 0.0746, 0.348, -0.1865, -0.1625, 0.6406, 1.585, -0.3289, 0.2225, -0.0798, -0.1578, -0.07806, -1.14, -0.0736, 0.3906, -1.336, 0.05276, -1.632, 0.8994, -2.807, 0.05054, 0.03186, 1.957, 0.3452, -1.354, 0.09064, 0.575, 0.5293], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.146, 0.346, 0.558, -0.5615, -0.419, -0.06018, 0.03497, 0.3872, -1.242, -0.1636, -0.6357, -0.2479, 0.656, -0.3643, 0.2091, -0.11926, 0.8535, 0.6855, -0.1906, 0.4373, -0.01513, 0.04724, 0.03516, -0.06903, -0.4492, -0.144, -0.4338, 0.603, -0.5273, -0.43, -0.4448, -0.597, 0.02536, -0.033, -0.3481, -0.02278, 0.0818, -0.383, -0.02834, -0.216, -0.0594, -0.086, -0.8667, 0.03876, -0.2294, -0.1904, -0.4062, 0.0598, 0.23, -0.02368], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.02, 2.26, -0.4507, -1.253, -1.183, 0.7236, -0.007526, -1.177, 2.23, 0.4817, -0.02373, -2.406, 0.5547, 0.2673, 0.265, 0.3071, -3.205, -1.136, 0.182, 1.596, 0.0964, 0.03976, 0.2886, -0.1614, 2.002, -0.386, 0.010956, 0.0448, 0.03592, -2.713, 0.3013, 0.2712, 0.09894, 0.622, 1.254, 0.09503, -0.1573, 0.978, 0.02509, 0.3035, 0.5996, -1.039, 0.673, -0.00993, 0.885, 0.04535, 0.1694, 0.003407, 0.5127, 1.155], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1819, -0.462, 0.597, 0.4016, 0.678, 1.117, 0.05164, 1.084, -0.8228, -0.1078, -2.408, 0.8413, -0.2256, -0.0896, -0.4316, 0.2122, -0.4155, 0.4172, 0.01389, -0.2292, 0.4104, 0.00552, -0.206, -0.0386, 0.01741, -1.334, -0.286, 0.1488, -0.2015, -0.4932, 0.38, -0.338, 0.1221, -0.2698, -0.1416, 0.2922, 0.041, 0.1273, -0.05157, 1.187, -0.5034, -0.3616, -0.3958, -0.0492, -0.0937, 0.285, 0.04987, 0.058, -0.02937, -0.1328], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.7954, 0.076, -0.5986, 0.3413, 0.1527, -0.04984, 0.09827, -0.7686, 0.5786, -0.2383, -1.463, 0.5376, 0.685, -0.0854, 1.035, 0.1073, 0.6978, -0.2192, 0.4165, -0.537, -0.5835, -0.02174, -0.398, 0.4805, 0.3694, 0.2761, 0.52, 0.7124, -0.02649, 0.7305, 0.1775, 0.2727, -0.518, -0.585, -0.4812, 0.08795, -0.4685, -0.4072, 0.02588, 0.379, 0.911, 0.8174, 0.6777, -0.03226, -2.146, -0.2556, -0.03503, 0.0743, 0.167, 0.7715], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01421, 0.06085, -0.3433, 0.2847, 0.5728, -0.5747, -0.0668, -1.859, 0.775, -0.6265, -0.696, -0.703, 0.0872, -0.00799, 1.35, 0.4158, 2.777, -1.157, 0.9697, -1.447, -0.08575, 0.02478, -0.02829, 0.2917, 1.196, -0.9395, 0.7495, 1.374, 0.05994, -3.416, -1.066, -0.5024, -1.329, 0.1362, -0.335, 0.316, 0.3682, -1.145, 0.01291, -0.867, 0.2651, -2.55, 0.7793, 0.01802, 0.06192, -1.183, -1.301, -0.001741, 1.51, -0.3452], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.441, -1.632, 0.1084, 0.02467, -1.662, 0.1459, -0.05783, -0.651, -1.356, -0.8955, -0.997, 0.0797, -0.219, 0.2603, 1.429, -0.0905, -1.132, -0.6035, -0.2708, -0.6, 0.1604, 0.00968, 0.01591, 0.1348, -0.837, -0.043, 1.498, 0.07825, -0.2727, 1.854, 0.11566, -0.469, 0.6055, 0.1649, -0.2534, 0.1882, -0.3298, 0.3706, -0.05008, -2.996, 0.15, 0.11487, -0.02397, -0.01997, 0.000715, -1.256, 0.6626, -0.0787, -0.01415, 0.0949], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2462, -0.66, -0.10834, -0.779, -0.2566, 0.694, -0.0241, -0.4153, 1.673, -0.3372, 0.3281, -0.7754, 0.3218, 0.0887, 1.497, -0.8345, -0.9497, -0.301, -1.207, 0.3389, 0.3103, -0.045, -0.06256, 0.1417, 0.5693, 0.595, -0.3108, -0.6353, -0.2578, 2.254, -0.679, 0.6797, 0.8022, -0.5903, 0.1707, 0.316, 0.2651, 0.5117, -0.04666, -2.295, 0.1709, -0.1766, 0.4524, 0.002827, 0.6953, 0.585, -0.0241, 0.04858, 0.1685, 0.851], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0649, -0.7134, 0.1841, 0.2632, -1.17, -0.279, -0.01846, 0.1492, 0.06256, -1.472, -0.5444, 0.254, -0.233, 0.5547, -0.493, -0.7935, -0.629, -0.5537, -0.2693, -0.517, -0.2277, -0.02834, 0.0848, 1.088, 0.745, -1.185, -0.6367, -5.984, 0.6914, -1.082, 0.3796, 0.2673, 0.02855, -0.03275, 0.4136, -0.6523, 0.4573, 0.01997, 0.02338, 2.361, 0.2113, 0.1522, 0.5156, 0.0123, -0.766, -1.365, -1.455, 0.02782, -0.499, -0.752], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.08777, 0.5947, -0.4683, 1.764, -0.0831, -0.4663, 0.0507, 0.06464, -0.02176, -0.01746, 0.2827, 0.706, -0.0798, -0.975, -0.3096, -0.4597, 0.4702, -0.9023, 0.127, -0.02446, 0.1416, -0.02284, -0.8926, 0.1833, -0.1654, 0.03152, 0.4158, -0.812, -0.1405, -0.6694, 0.0327, -0.2795, -0.265, -0.2417, -0.1587, 0.1434, -0.01381, 0.1393, 0.04214, 0.4631, 0.02277, 0.183, 1.057, 0.02466, -0.4429, 0.2129, 0.4773, 0.04865, 0.1832, -0.43], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03452, -0.02327, 0.000605, -0.0718, -0.0536, 0.02066, -0.03973, -0.0457, 0.02226, 0.04553, 0.00818, -0.00981, 0.0189, 0.01507, -0.05814, 0.02486, 0.005787, 0.03029, 0.04254, 0.006927, 0.00644, -0.0445, 0.03345, 0.04056, -0.02405, -0.013916, -0.02022, -0.02264, -0.05182, 0.02713, -0.0186, -0.0304, -0.04208, -0.008, 0.010185, 0.007835, -0.04156, -0.05566, -0.003525, 0.02344, 0.0389, -0.0557, 0.002686, 0.02783, -0.05612, -0.04807, -0.03394, 0.03918, -0.03784, -0.03041], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5864, 0.4387, 0.02007, 1.179, -0.08453, 0.0987, 0.09503, -0.09827, 1.064, -0.5825, 0.3818, 0.4172, -0.0431, 0.0346, -1.36, 0.11914, -0.9824, 0.7, 0.3628, -0.822, -0.4788, -0.04178, 0.04208, -0.2566, -0.04413, 0.1031, 0.05972, 0.569, 1.173, -3.748, 0.662, -0.1414, -0.536, -0.0489, -1.199, -0.653, 0.06995, -0.8345, -0.01101, -1.474, 0.4255, -2.508, -0.02513, -0.03778, 0.4631, -0.25, 0.0652, 0.04333, 0.3672, 0.665], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.10486, 0.214, 0.501, -1.602, -0.4985, 0.218, 0.04608, -0.161, -0.5127, 1.87, 0.681, -1.529, -0.3408, 0.11127, -1.901, -0.362, -0.2136, 0.9326, -0.8633, 0.4941, -0.2415, -0.03918, -0.327, -0.03708, -0.00996, -0.264, 0.355, -0.3247, 1.36, 0.8184, 0.5493, -0.323, -0.3503, 0.7056, -1.417, 0.03305, -0.5405, 0.2355, 0.01636, 0.0774, 0.6494, -1.814, -0.0397, -0.01843, 1.009, 0.12164, -0.632, 0.01408, 0.356, 0.793], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1901, -0.1766, 0.863, 0.2673, -0.1004, 0.567, -0.003637, -1.509, 1.517, 1.224, 2.336, -0.1885, -0.05164, -0.345, 2.02, -0.3118, -0.7173, 0.3203, 0.4187, 0.7637, -1.342, 0.00964, -0.04333, -0.2052, 0.3523, 0.306, 0.4612, -0.1571, 0.226, 0.2395, 0.4954, -0.1294, -0.01772, -0.6006, 0.1506, 0.503, 0.0761, 0.1223, -0.01411, 1.2, -0.7983, -0.0713, -0.582, 0.005886, 0.2756, 0.3972, 0.2109, 0.022, 0.04037, -0.3713], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1865, -0.17, 0.234, -0.2998, 0.6562, 0.003376, 0.03293, -0.1808, 0.6343, 0.537, 0.2062, -0.241, -0.08057, 0.29, 1.19, -0.1469, -0.442, 0.05576, 0.05527, -2.049, 0.0693, -0.001174, 0.1824, -0.674, -0.06366, 0.1658, 1.891, 0.628, 0.7314, -1.763, 1.031, 0.4727, -1.18, 0.3337, 1.059, 0.2036, 0.0712, 0.4758, -0.005344, 0.658, 0.0985, -1.001, 0.000832, -0.0176, 0.431, -0.4714, -0.3438, -0.0233, 0.184, 0.1768], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.556, 0.2952, -0.3071, -0.1285, 0.1624, 0.287, -0.0356, 0.1598, 0.809, 0.252, 0.302, 0.744, 0.791, 1.64, 0.8237, -1.124, -1.0, 0.8315, 0.1205, -0.1415, -0.5996, -0.0373, -1.603, 1.125, -0.457, -0.6343, 0.4084, -0.0939, 1.086, 3.055, -0.008446, 1.138, 0.4255, -0.6475, -1.739, 0.3455, 0.2866, 0.0881, 0.02423, -1.063, 0.515, 1.451, 1.059, -0.0427, -0.3904, 1.918, -0.0786, -0.04428, -0.7817, 0.6206], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.3503, 0.02966, -0.7383, 0.1147, -0.392, 0.0971, -0.01059, 0.1426, -3.432, 0.504, 0.3706, -0.1285, -0.206, 0.8335, 0.833, 0.4324, -0.55, 1.576, 0.693, 0.12, 1.091, -0.002857, -0.5513, 0.9023, 1.414, -0.83, -0.5625, 1.612, 1.324, -1.743, -0.5522, -1.518, -0.2864, 0.614, -0.10547, -0.799, 0.4385, -0.2583, -0.03592, 0.2278, -0.04547, 1.808, -3.482, 0.00706, 0.6216, 0.1959, 0.3267, -0.0479, -0.001397, -1.219], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.133, 0.07385, -0.06555, 0.347, 0.1437, 0.5903, 0.0306, -1.315, -1.707, 0.669, -1.133, 0.2067, -1.074, -0.1442, 1.612, 0.1578, -0.9717, 2.602, -0.1316, 0.6987, -0.479, 0.02155, -0.97, 0.616, -0.291, 0.5894, 0.2805, 0.04254, 1.446, -0.1853, 0.237, 0.4119, -0.1558, -0.0898, -0.8496, 0.1042, -0.1339, 0.905, -0.02281, 2.29, 0.1981, -0.6753, -0.4014, 0.02783, 1.209, 0.55, 0.131, -0.05197, -0.06094, 0.2917], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.356, 0.0746, 0.544, 0.00949, -0.4885, 0.8003, 0.013336, 0.08734, 0.4844, -0.1373, 0.06915, 0.3928, 0.393, 0.02737, -0.3445, -0.345, -1.459, 0.1051, -0.11926, -0.3872, -0.0956, 0.01283, -0.1072, -0.06836, -0.1342, 0.556, -0.2308, -0.3674, 0.775, 1.17, 0.3533, -0.652, 0.4788, -0.737, -0.431, 0.0868, -0.1444, -0.2491, -0.02553, -0.03482, -0.4526, 0.03644, 0.4924, 0.002333, 0.08606, 0.0982, -0.4004, 0.01042, -0.0482, 0.1761], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4893, -2.62, 0.524, -0.547, -1.197, -1.889, 0.10034, -0.1509, -0.4578, 1.988, 6.043, 0.496, -1.081, -0.6206, 0.1677, -0.1699, 2.115, -1.606, -0.1388, 0.05606, -0.3093, 0.01255, 0.1276, 0.99, 0.5093, -1.695, 1.142, 0.609, -0.941, 0.6265, -0.2462, -1.303, -0.196, -0.996, 0.995, -1.028, 1.028, 0.756, 0.03735, -0.1251, -0.6104, 1.174, -3.365, -0.02914, -0.4636, -1.859, 1.854, 0.09766, -0.95, -4.652], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8755, 0.3, -0.5586, -1.019, -1.095, 0.02313, -0.01563, -5.45, 0.671, 0.1903, -0.4495, -1.92, 0.1545, -0.0935, 0.1855, 0.2869, -7.38, -0.6377, -0.1667, -1.435, 0.704, -0.014694, -0.12317, 0.2615, -0.8896, 0.1501, -0.556, -0.03055, 0.54, -4.562, -0.1559, -0.2144, -0.01845, 0.96, -0.604, 0.1451, -0.1965, -0.6504, -0.03827, -2.375, 0.1599, -0.8174, -0.2776, -0.00289, -0.07477, -0.6333, 0.1963, -0.06042, 0.353, 0.615], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0099, 0.0408, 0.02226, -0.01923, 0.03363, 0.04376, -0.02182, 0.006542, -0.0438, -0.03903, 0.02815, -0.01686, -0.01753, 0.03067, -0.02577, -0.02092, 0.02303, -0.03308, -0.01901, 0.00577, 0.0348, -0.03998, -0.01836, -0.03894, -0.03882, 0.01784, -0.005077, -0.01865, -0.03784, -0.006092, -0.0306, -0.00688, -0.04803, -0.02426, -0.05856, -0.02168, -0.03043, -0.02266, -0.0171, -0.02187, 0.01551, -0.03787, -0.0383, 0.00854, 0.00776, -0.02219, -0.03738, 0.02284, -0.0375, -0.02873], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.04413, 2.572, -0.05402, -0.05142, 1.317, 0.8125, 0.01611, 0.1255, 0.10974, -2.76, 0.004326, 0.7705, 0.7773, -0.05133, 0.00965, -0.7188, -0.405, 0.6357, -1.817, -0.288, 1.55, 0.0139, 0.2019, -0.2905, 0.2401, 0.647, 0.03592, -0.5464, -0.5776, 1.736, 0.377, -0.5327, -0.4153, 0.704, -0.013885, -0.4607, -3.766, -0.1573, 0.03284, 0.02774, -0.4136, -0.1775, 0.3984, -0.03543, 0.09326, -0.1552, -1.95, -0.04706, 0.05875, 0.1846], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4114, -1.605, 0.0629, -0.806, -0.771, 0.2466, -0.002295, 2.28, -6.027, -1.143, 0.2113, 0.03998, 0.0895, 0.658, -2.562, -0.609, 0.4922, -3.15, -0.509, -1.466, 0.435, 0.000889, -0.0506, 0.08014, 2.305, 0.2954, -0.6816, -2.03, -0.6035, 4.516, -0.7637, 0.7266, -0.0778, -1.422, 2.426, 0.156, 0.4685, -0.1143, -0.010864, 0.6396, 0.00872, 0.01333, 0.8013, 0.02979, 0.1509, 0.6006, 0.3877, 0.03934, -0.013885, -0.1599], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.09, 0.7734, -0.1719, 1.061, 2.121, 0.627, 0.00785, -0.9053, -0.656, 0.634, 0.578, 0.392, 0.1875, -0.1478, 1.996, 0.03134, 0.3765, 1.076, 0.556, -0.3606, 1.076, -0.02853, 0.0556, -0.4478, -1.14, 0.528, -0.5015, -0.751, -0.5195, -0.804, -0.1235, -1.087, -0.1595, 0.1978, -0.577, -0.01604, 0.611, -0.8247, 0.03336, 0.0333, 0.1383, 0.1912, -0.32, -0.01743, -0.08264, -1.089, -0.1654, 0.009995, -0.516, -0.489], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.3901, 0.2032, -0.07043, -0.576, -0.11896, -0.02643, 0.08215, 1.607, -2.166, 0.1002, -0.9937, 0.5977, -0.9507, -0.6685, -1.929, -0.2148, 1.421, 0.3171, -0.1393, 1.056, -0.857, -0.02922, 1.12, 1.289, 0.1277, 0.7104, 0.7153, -0.607, -0.393, 1.564, 0.1436, -0.909, -0.2944, -0.012794, 0.613, -1.596, -0.2148, -0.0002072, -0.01494, 3.799, -0.7793, -0.8354, -1.376, 0.0098, -0.578, 1.108, -0.833, 0.1065, -0.02737, -0.649], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.001548, 0.2903, -1.673, 0.28, 0.2235, -0.1171, 0.02309, 0.1349, 0.1631, 0.03226, -1.252, 0.1477, 0.1592, -0.2754, -0.5034, -0.1787, -0.1115, 0.3967, 0.2466, 0.429, -0.42, 0.04425, -0.0931, 0.1037, -0.3176, 0.6396, -0.299, -0.2109, -0.1981, -0.1289, 0.189, -2.174, 0.2927, -0.1677, -0.4739, 0.241, -0.10706, 0.1562, 0.02754, 1.099, -0.0852, 0.4102, -5.34, -0.01668, -0.3328, 0.1351, 0.368, 0.0686, -0.1335, 0.394], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0947, -0.02539, -0.0717, -0.708, 0.1771, 0.3867, 0.03537, -1.4375, -0.718, -0.3735, -0.5107, 0.0468, 0.6484, -0.4001, -3.26, -0.3745, -0.5903, -0.727, 0.00919, 0.0892, 0.0561, 0.002401, -0.02538, -0.11365, 0.0761, 1.059, 0.1855, 0.779, -0.1823, -1.701, 0.533, -0.618, -0.665, -0.3633, -1.05, 0.4634, -0.02342, 0.1831, -0.03217, 1.405, 0.802, 1.171, -1.791, 0.04266, 0.3298, 0.01417, 0.283, 0.0271, 0.4443, 1.098], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1981, 0.5337, -0.1254, -0.2607, -0.02469, 0.326, 0.0637, -0.003597, -1.213, -0.2212, -0.607, 0.4675, 0.2135, -0.0911, -0.7437, 0.3103, 0.744, -0.9224, 0.1189, 0.996, 0.3262, -0.00991, 0.06085, 0.1416, 0.3108, -0.3464, -0.3296, -0.3594, -0.4722, -0.0007415, -0.1078, -0.03017, -0.0641, 0.0706, -0.7935, 0.207, -0.2888, 0.1453, -0.003918, 0.1425, -0.054, -0.4207, -0.2964, -0.007248, 1.058, 1.408, -0.2474, 0.07404, -0.6006, -0.472], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.05353, 0.554, 0.0853, 0.4062, 0.01456, -1.395, -0.007263, 0.1776, 0.3252, 0.4634, -0.205, 0.389, -0.5303, 0.4075, -0.2482, 0.258, 0.608, -0.2764, 0.483, 0.1628, 0.5176, 0.003187, -0.2338, -0.6025, 0.1677, -1.881, 0.3943, -0.1681, -0.3987, 0.08405, -0.1737, -0.129, -0.4348, 0.4675, 0.6455, 0.6934, -0.3354, -0.3823, -0.039, 0.37, -0.2737, 0.8423, 0.3096, 0.002054, -1.409, -0.209, 0.0535, 0.07306, 0.2427, -0.576], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.047, 0.02945, -0.04926, -0.03546, 0.007698, -0.0123, 0.0386, 0.02788, -0.0472, -0.01988, 0.04062, -0.01385, 0.0051, -0.003004, 0.04465, 0.006557, -0.04208, -0.01543, 0.02058, -0.00803, 0.015, 0.03017, -0.0367, -0.0644, 0.01782, 0.01659, 0.015396, -0.03665, -0.03357, 0.002125, 0.003494, -0.05347, 0.02136, 0.00661, 0.01475, 0.015114, -0.061, -0.01599, 0.02647, 0.0004766, 0.0211, 0.02365, -0.04572, 0.02893, 0.02109, -0.03314, 0.012024, -0.03235, -0.02312, -0.0253], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.611, -0.2861, -0.4788, 1.307, 1.296, 0.02888, 0.03488, -0.03062, -0.0944, -1.32, -0.756, -0.08374, 0.2102, 1.086, -1.8, -0.1699, -0.1066, 0.1306, 0.3713, 0.03232, -0.4521, 0.04138, -0.01872, -0.2019, -0.4119, 0.10754, -0.03903, 0.565, -0.348, -0.375, -0.1958, 0.567, 0.5015, -0.7354, -0.02786, 1.545, 0.1616, 0.2502, -0.03021, -1.067, -0.2925, 0.07806, 0.2495, -0.02179, -0.3457, 0.375, 0.2983, 0.007736, -0.00772, -0.127], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.611, -1.897, -0.3247, 1.621, 0.3406, 0.1354, 0.0467, -1.17, 0.2213, -1.543, 0.1345, 0.8594, -0.5083, -0.05768, 1.315, -0.2627, -1.342, 0.7563, 0.683, -1.021, 1.166, 0.02057, 0.00963, 1.156, -1.066, 0.6553, -0.0309, -0.2852, 0.3303, 0.47, -0.272, 0.1236, 0.7773, -1.15, -1.307, -0.6494, 0.9565, -0.2115, -0.0347, 0.289, 0.5317, 1.5, 0.8506, -0.01605, 1.186, -0.673, -0.08624, 0.05273, -0.1105, 0.7856], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.838, -0.5845, -0.06015, -1.546, 0.538, 0.4385, -0.00591, -4.42, -0.8823, -0.3293, -2.967, -0.978, 1.255, -1.613, -0.673, -1.279, -1.02, -1.483, -1.204, -0.449, 0.2727, 0.001491, -0.816, 0.3792, 1.102, 0.993, 0.6714, -0.425, -0.1664, 2.66, -1.434, -2.432, 0.8794, -1.842, 1.832, -0.4297, 0.3254, 2.201, 0.001359, -2.11, 0.4834, 0.5493, -3.584, -0.03119, -0.08655, 0.1415, -1.111, -0.03238, 0.6772, -0.278], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.8633, -1.577, 0.2324, 1.229, -0.02042, 0.396, -0.05762, 1.337, -0.955, -1.04, -4.42, 1.107, 0.008064, 0.2664, -3.363, 0.1836, 1.059, -0.7407, 0.294, -0.229, -0.11945, -0.0443, -0.2076, -0.4482, 0.168, 0.15, 0.833, -0.903, 0.2637, 3.139, -0.4717, 0.8, -0.2382, -0.768, -0.8457, 0.0377, 0.514, -0.3774, -0.00736, 0.782, 0.178, 1.756, -1.525, 0.04462, 0.537, 0.4956, -1.071, -0.1072, -0.3398, 0.3381], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4734, -0.4507, -0.4783, 0.1307, 0.33, 0.2734, 0.08685, 2.023, -0.2458, -0.7886, 1.466, -0.2805, -0.2856, -0.6016, -0.1912, 0.2296, -0.2622, 0.3643, 0.44, 0.375, 0.581, 0.012375, -0.2329, 0.12244, -0.3938, 0.3845, 0.4905, -0.1311, 0.6167, 1.886, -0.811, -0.926, -0.02531, 0.3398, -0.688, -0.923, 0.12103, -0.2969, -0.02022, -0.1561, -0.2522, -0.1697, -0.601, -0.03152, 0.606, -0.458, -0.2632, 0.0824, 0.185, -1.0625], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.81, 0.11365, -0.1056, -0.2164, -0.1, 1.753, 0.010475, 2.469, 1.483, -0.5264, 0.4006, 1.032, -0.007507, -0.2231, 2.06, -0.4946, -1.696, 1.071, 0.0907, 0.8486, -1.131, -0.0368, 1.085, -0.7715, -0.7837, 0.1053, -0.7764, -0.645, 0.11426, 0.8687, 0.6772, -0.2717, 0.561, -0.3372, -0.429, 0.1272, 0.2222, -0.43, 0.03784, 0.906, -0.261, 3.926, 0.4192, -0.013435, 0.614, 0.2656, -1.192, 0.03058, -1.32, 0.3523], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2622, 0.4128, -0.3198, 0.02458, -0.632, -0.2725, -0.06134, -0.258, -0.226, -1.155, -1.164, 0.5435, -0.3618, 0.4443, -1.216, 0.5366, 0.682, 0.5522, 0.2976, 0.692, 0.04526, -0.00843, -0.2986, -0.442, -0.01432, 0.4119, -0.0462, -0.759, 0.0885, -0.04385, -0.149, 0.2484, -0.05402, 0.3057, -0.3755, 0.479, -0.5396, -0.02869, 0.01004, -2.678, -0.2625, -0.3806, 1.82, -0.01674, 0.3743, 0.2144, 0.1968, -0.06506, 0.363, -0.3425], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0547, -0.06946, 0.435, -0.0673, 0.6533, -0.7896, -0.01032, -0.1539, 1.962, -0.704, -1.064, 1.318, 0.3706, 0.2245, 1.441, -0.01573, 0.2279, -0.9897, 0.6577, -0.7407, 0.5405, -0.0131, -0.1075, 0.176, 0.438, -0.2468, 0.2225, 0.1602, -1.118, -3.15, -0.2612, 0.2203, -0.1554, 0.4688, 0.805, 0.03174, 0.014305, 0.4248, -0.038, -1.781, -0.3916, -1.432, 0.3137, -0.03107, -0.97, 0.1077, -0.6934, 0.05542, -0.1656, -0.3806], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.206, -0.05026, 0.02731, -0.1934, -0.971, 0.1302, -0.02283, -1.27, -1.4, 1.046, -1.757, -0.03967, 0.6094, 0.3784, 0.1731, -0.8555, -0.413, 0.1686, -1.613, -0.2715, 0.0001818, 0.0041, -0.4292, -0.1098, 0.6235, 0.04852, 0.3367, -0.1866, -0.464, 1.502, -0.6743, 0.231, 0.597, -0.997, -0.5684, 0.389, 0.2654, 0.8354, -0.003056, 0.8477, 0.4177, 1.884, 0.5796, 0.0165, 0.4072, 0.5093, -0.503, -0.03345, 0.347, -1.256], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.04303, -0.05075, -0.03403, 0.01706, -0.02121, -0.02452, 0.0317, -0.02261, 0.02097, 0.00792, 0.012856, -0.02199, -0.03214, -0.0418, -0.03253, -0.0468, 0.00876, -0.03964, -0.03473, -0.03143, -0.03403, 0.002254, -0.02261, 0.02318, -0.01459, -0.03766, -0.001991, 0.01418, 0.00859, -0.0635, -0.0616, -0.0517, -0.0388, -0.03075, 0.02151, -0.03687, -0.03363, 0.03748, 0.00753, -0.04092, -0.03308, 0.00833, 0.03262, -0.01929, 0.01878, -0.014854, -0.015335, 0.02177, 0.05432, 0.01067], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.471, -0.1566, -0.04294, -0.773, -1.177, 0.2317, -0.0348, -0.6904, -0.001133, -0.2842, 0.026, 0.747, -0.0952, -0.03668, -0.3206, -0.27, -0.3125, -0.578, -0.309, 0.622, 0.0654, -0.02612, 0.02321, -0.05942, -0.0983, -0.0004308, -0.7827, -0.6934, 0.534, -0.3904, -0.4802, -0.06165, 0.1411, 0.2588, -0.3127, 0.3057, -0.479, -0.10364, 0.0086, 0.1738, -0.2217, 0.583, -0.4773, -0.0144, 0.419, -0.2214, 0.288, -0.01735, -0.0869, -0.119]] [-0.725588, -0.00307708, -0.0214729, -1.02263, 0.0132117, 0.254539, -0.0161837, 1.00489, 0.366733, 0.576586, -1.12231, -0.101106, 0.234992, 0.497892, 0.380083, -0.106264, -0.00875837, -0.217394, -0.0338691, 0.174241, 0.94051, -0.446787, -0.432205, -0.672141, -0.847108, -1.28102, -0.0116062, -0.0695951, 0.763553, -0.00961155, -0.455887, -0.883115, -0.155809, -0.264165, 1.15232, -0.00141853, -0.189275, 0.00461055, -0.0335549, -0.0259916, -0.620393, -0.587556, 0.25641, 0.323012, -0.339327, 0.0850243, -0.0925355, 0.110709, -0.00651723, 0.75789, -0.7256, -0.003077, -0.02147, -1.022, 0.013214, 0.2546, -0.01619, 1.005, 0.3667, 0.5767, -1.122, -0.10114, 0.235, 0.4978, 0.3801, -0.10626, -0.00876, -0.2174, -0.03387, 0.1742, 0.9404, -0.4468, -0.4321, -0.6724, -0.847, -1.281, -0.011604, -0.0696, 0.7637, -0.00961, -0.4558, -0.8833, -0.1558, -0.2642, 1.152, -0.001418, -0.1893, 0.004612, -0.03357, -0.02599, -0.6206, -0.5874, 0.2563, 0.323, -0.3394, 0.085, -0.0925, 0.1107, -0.006516, 0.758] ReLU [[0.811313, -0.0177385, -0.0014636, 0.0133059, -0.388109, 0.213835, 0.00453104, -0.776802, -0.137644, -0.0462726, -0.247041, 0.412123, -0.485391, -0.409135, -0.471061, 0.980002, -0.496437, -0.153921, 0.0410588, 0.328544, -0.445126, -0.801411, 0.836187, 0.430518, -0.0168299, 1.88084, -0.105027, -0.364653, -0.507144, -0.0275504, -0.958071, 0.438539, -0.246737, 0.557851, 0.599184, 0.122409, -0.214961, 1.24402, -0.0346459, -0.322664, -0.0936644, -0.353644, -0.0610976, 0.163154, -0.388433, 0.254114, -0.119902, 0.462745, 0.044751, -0.310097, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.100491, 0.0188655, -0.00925881, -0.55625, -0.617853, 0.379207, 0.0101598, -0.374003, 0.0827988, 0.237098, -0.0919097, 0.0163179, 0.438138, 0.142748, -0.0381825, -0.590176, 0.0746897, 0.509264, -0.0493225, -0.279967, -0.294505, 0.6982, -0.152568, -0.00870336, 0.0377771, 0.62479, 0.425313, 0.0494753, -0.691234, 0.0144461, 0.263372, 0.114303, 0.103521, -0.404182, -0.0170254, -0.368765, 0.150453, 0.129839, 0.033546, -0.0173307, 0.0806632, 0.206317, 0.0715441, 0.406903, -0.088828, -0.0545317, 0.175563, 0.0194402, -0.0401978, 0.0208675, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.731301, -0.0109689, 0.00383127, -2.86657, -0.51331, 0.0050442, -0.0220147, 0.319144, 1.26684, -0.907023, -0.0375653, 0.80825, -0.724535, 1.22485, -0.0128222, -1.44214, 0.185645, -0.460607, 0.0113302, 1.4537, -0.226557, 0.822182, 0.73717, -0.362831, 0.613661, 4.63687, -0.476399, -0.396051, 1.10675, 0.011242, 0.700531, -0.517449, 0.39688, -0.430245, 0.0109719, 0.24185, 0.702614, 1.70956, -0.0282011, -0.504949, -0.310546, -1.39292, 0.352398, 0.100283, 0.45525, -0.285845, -1.01592, -0.88017, 0.0151465, 0.262648, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.963447, 0.0184756, 0.0524902, -3.39628, 0.201813, -0.586245, 0.00751359, 0.0629724, 1.02548, -1.18464, -1.52399, 0.353354, 0.634522, 2.49436, -1.10076, -2.10929, -0.155111, 1.20787, 0.040144, 0.3576, 0.317072, 0.160713, -1.90828, -1.18209, 0.456117, 1.83574, -0.188327, 0.719125, 1.55768, 0.038151, 0.673171, -3.72614, -0.631704, -0.787168, 0.0550641, 0.00567553, 1.62224, -0.272949, -0.0336407, -0.304505, 0.0651625, -1.23232, -0.177411, 0.206973, 0.858136, -0.179617, -0.390884, -1.42746, 0.00147773, 1.57758, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.519067, -0.0246169, -0.0110044, -0.425676, 1.16722, 2.1215, -0.00128834, 0.823633, -0.52011, -0.237305, 0.495048, 0.203697, 0.280611, 0.734181, 1.97413, 0.0370129, 0.746967, -0.024998, -0.0121088, -0.128827, 0.86027, 0.405586, 0.26779, -0.174814, -0.0518498, -0.0401906, 0.314804, 0.621194, -1.12817, -0.0184328, 0.308767, 2.49553, -1.04755, 1.06201, 0.036921, 0.0293827, 0.165621, 1.0866, -0.00971276, 0.744828, 0.0858684, 3.12814, -0.958666, 0.0508196, 0.739517, -0.516312, 0.47178, 0.403, 0.0451177, 0.306622, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.92815, 0.00107255, -0.0367574, -0.6403, 0.121902, -0.281761, 0.0137163, 0.287801, -0.523652, -0.651533, -0.38391, -0.46958, 0.251854, 1.52758, 0.713201, -0.904163, 1.29378, -3.50665, 0.0330222, -0.291146, 1.09246, -0.190694, -0.127036, 0.569781, 0.0717871, -1.08937, -0.356804, 0.964633, 2.14611, -0.00434954, 2.28744, 0.49767, -0.293071, -0.605983, 0.588775, -0.736287, -2.27631, 0.468967, -0.0131226, -0.615434, 0.288091, 1.29847, -0.357076, -1.0441, -0.233734, 0.159134, 0.260993, -0.774442, -0.0177385, 1.12959, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0600274, -0.0120029, -0.0498438, 1.05568, 0.774116, -0.648841, -0.0241602, 0.164155, 0.289611, 0.020502, -0.494944, -0.241698, 0.729365, -0.467453, -1.32305, -0.797542, -0.539319, 1.15863, -0.00385008, 0.276325, -0.0324962, 0.568388, -0.218214, 0.339411, -0.501625, -0.328049, -1.47908, 0.154547, -0.297043, -0.0335662, -0.783486, -0.553681, 0.983528, -0.586441, 0.336911, 0.668088, -0.647906, 0.147802, 0.0239194, -0.639321, -0.57444, 0.00224391, 0.488284, 0.709749, -1.3861, 0.855235, 0.894619, -0.112297, 0.0296955, 0.569047, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.05679, 0.0360732, -0.018255, -0.501725, 0.372611, 1.77157, -0.00233268, -0.665359, -0.484194, 1.53867, 0.329315, 0.0606779, 0.00841973, 0.0901827, 1.5512, -0.994703, 0.629109, 0.488129, -0.00941487, -0.250967, 0.57756, -0.679383, 0.0594881, 0.67746, -0.730104, 1.03187, 1.10984, 0.0440237, 1.50094, 0.0258131, 0.489309, 0.749803, 0.667329, -0.0625478, -0.270367, 0.479992, 1.45437, 0.676673, 0.0339755, -1.51184, 0.365476, 0.32379, -1.37074, 0.824769, -0.10203, -0.896035, 0.741514, 0.491357, 0.0470632, 1.42058, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.423759, 0.0327952, -0.0262193, 0.401625, -0.10105, -0.65266, 0.000826148, -0.367487, 0.065482, -0.112798, 0.141655, 1.54594, -0.245872, 0.119747, -0.16871, -0.391303, -0.586213, -0.419382, -0.00395657, -0.428122, 0.339796, -0.541126, 0.829188, 0.129571, 0.130355, -0.386772, 0.107073, 0.231393, 0.139191, 0.00754007, -0.930162, -0.0512804, -0.89883, -0.0243509, 0.127727, -0.60996, 0.519975, 1.98351, -0.0252601, 0.216293, -0.0450776, -0.33975, -0.0588554, -0.407454, -0.175702, -0.262883, 0.264357, 0.0980844, -0.00164302, 0.7835, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.944394, -0.0118286, 0.0379274, -0.975407, -0.882533, 0.23147, -0.00487467, -1.13582, -0.417686, -1.03966, 0.196868, 0.862121, -0.667767, 0.737998, 0.320091, 0.958194, -0.26246, -0.736852, -0.0349438, -0.736819, 0.340736, -1.99614, 1.38675, 0.216967, -0.520038, 0.861486, 1.22213, 0.31378, 1.09245, -0.0463766, 1.65492, 0.287583, -0.325148, 0.0386103, 0.41679, 0.509949, 0.324421, 0.985516, 0.0260347, 1.16103, -0.220176, -0.0530351, 0.0363344, 0.330143, -0.135412, 0.0897156, 0.262688, -0.546898, 0.0215727, 0.295673, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.480417, 0.0023628, 0.0191803, -4.21252, 0.14837, 0.235711, -0.014872, 0.0683013, 0.596003, -0.11004, -0.272752, 0.393611, -0.860328, 0.194785, 0.322214, -0.969178, -1.00953, 0.522625, 0.067974, -0.299107, 0.117989, -0.706314, -0.583905, 0.264493, -0.458266, -0.609456, -0.5081, -0.547752, 0.434698, 0.0162448, -1.81796, -0.0776603, -0.230507, -0.455915, 0.0262963, 0.0405859, 0.122288, -1.82978, 0.0304973, 0.528785, 0.380744, 0.581266, 0.144232, 0.1151, -0.0440856, -0.484297, 0.535517, -0.463081, 0.0419933, 0.152452, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0709426, -0.0220233, 0.0437604, -0.0377328, -0.0276735, -0.03095, 0.0448819, 0.00269211, -0.00276687, -0.013933, -0.0436612, 0.0123269, 0.0181843, 0.0330683, -0.0219515, -0.00875586, -0.0146836, 0.0110944, 0.0341042, -0.0456183, -0.0422696, 0.0031869, -0.0596941, -0.0619811, -0.0441751, -0.000359246, 0.000366565, 0.016629, -0.0561777, -0.0302759, -0.0615107, -0.0252622, 0.0251009, -0.00760954, 0.0218715, -0.044191, 0.0217868, -0.0194391, -0.0312541, 0.0116615, -0.0209742, 0.0295111, -0.0450674, -0.0534241, -0.0407367, -0.0222713, 0.012751, -0.0592856, 0.0233099, 0.0210626, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.416636, 0.0293729, -0.0408676, 0.695739, 0.151289, 0.186248, -0.033982, 0.139941, -0.540407, -0.896141, -0.817135, 0.304356, -0.0229578, 1.24958, -0.157918, -0.434146, -0.850146, -1.36292, -0.0160607, -0.476017, -0.2953, -3.08645, -0.484768, -0.210179, -0.255941, -0.711761, -1.52519, -0.675345, -2.71473, -0.0262139, -0.0939162, -0.234008, -0.868482, -0.575072, 0.274914, -0.657096, -1.55423, -1.80045, 0.0078778, 1.32894, 1.19559, 1.767, 1.71488, -0.986932, 1.03454, 0.0818, -0.33332, 0.0394363, -0.0463089, -1.69761, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.472704, -0.0549676, -0.0462262, 1.12857, 0.495042, 0.910451, 0.033872, -0.0410703, 1.68722, -2.25592, 0.290531, -1.17759, 0.768398, -1.74616, 0.301216, -0.0334781, -0.336298, 1.88785, 0.0516685, 0.468893, 0.0831304, 0.322957, -0.102377, -0.50031, 0.143344, -3.42848, -3.03966, 0.0271334, -1.67207, 0.0488801, -6.78944, -1.81339, 0.845122, -0.196997, -0.0245759, -0.211604, -1.85894, -0.413863, -0.0153718, 0.319465, -0.731697, -1.46461, -0.273598, -0.974207, -0.396761, 0.959444, 0.152172, -0.994118, 0.0341299, 1.06346, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0870665, -0.0280953, 0.00581883, -0.713621, 0.491815, -0.069658, 0.0373594, -0.167977, -0.339393, -0.366378, 0.141672, 0.796677, -0.168069, 0.530639, 0.103447, 0.0210827, 0.639248, -0.781566, -0.000127343, 0.82031, 0.253545, 0.300487, -0.731732, -0.141477, 0.0501823, -0.696686, -2.18552, 0.237496, -1.26255, -0.0302104, 0.432764, 0.105244, 0.404788, -0.522077, 0.111734, -0.0190685, -2.19868, 0.175925, 0.044751, 0.238753, 0.220069, 0.165326, 0.227408, -0.27047, -0.0956266, 0.0273602, 0.34837, -0.414545, -0.0154651, 0.739651, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.32633, -0.00315071, -0.0279219, 0.363292, -0.18123, -0.461338, 0.00617613, -0.0865601, 0.197894, 0.271282, -0.692837, -0.430785, 0.411287, -0.44508, 1.68649, 0.174796, -0.0981218, 0.804314, 0.0238822, 0.50641, 0.346504, 0.627337, -0.152987, -0.645282, 0.336946, -1.23276, 0.331588, -0.1036, -0.710769, -0.0474171, -0.0266687, -0.0126977, 1.18906, 0.29812, 0.170107, 0.0752392, 0.355517, 0.478257, 0.0213874, -0.204202, 0.159414, -0.171194, -0.0522834, 0.260891, 0.12019, -0.118133, -0.112283, -0.0133419, -0.0333671, 0.537877, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.931318, -0.026699, -0.0430233, -8.42089, -0.410075, 0.91444, 0.00952195, -0.154176, -0.174947, 1.6879, -0.156479, 2.36038, 0.482181, -0.0162155, 0.218536, 0.577321, 1.46868, -0.464432, 0.0243973, 0.42825, -0.212455, -3.43695, 0.0553139, 0.596314, -0.407266, 1.58391, 0.0783116, 0.498192, 0.761551, 0.0353754, 0.606812, -0.727815, 0.762773, 0.276725, -0.366828, 0.56751, -0.1076, 0.872082, 0.0414551, -0.259794, 0.309054, 0.782681, 0.164771, 0.0421481, -0.577316, 0.241195, 0.00839003, 0.0720553, 0.01759, 0.721887, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.289778, 0.0274126, -0.0417219, -0.210994, -1.34888, -0.291793, -0.0384598, 0.152613, 0.00105761, -0.635325, -0.170119, -0.103042, 0.0609201, 1.49043, 0.687075, -0.165078, -0.652347, 0.790193, -0.00690178, -0.724236, 0.878917, -0.8014, 0.0368651, 0.250999, 0.272471, -0.384182, 0.234907, 0.0025715, 0.533011, -0.0295137, -0.0354768, 0.23174, -0.335175, 0.172125, 0.284949, -0.313607, 0.799504, -2.90934, -0.012615, -0.0933058, 0.311329, 0.659862, -0.29829, -0.759124, 0.522255, -0.268992, 0.205252, 0.522689, 0.0453698, 0.4594, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.13464, 0.0295944, 0.0245011, -2.28134, 0.109568, 0.388786, 0.0221704, -0.222947, 0.498451, 0.777401, -0.311282, 0.655988, 0.195293, -1.37558, 0.779089, -0.494402, 0.811202, -6.15231, -0.0258152, -1.8634, -0.164982, 1.95545, 1.30954, -0.576282, 0.0397479, 1.10488, 0.629502, 0.362247, -0.116913, -0.00158784, -1.39841, 0.30631, -0.279171, -0.254166, 0.0340864, 0.593448, 0.0665205, 0.306127, -0.0286695, 0.231519, 0.0366756, 0.260175, 0.0257343, 0.376348, -0.502748, -0.0482275, 0.00171808, -0.168766, -0.0400816, 1.2199, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.200642, -0.0033009, 0.0135852, -1.40954, 0.138612, -0.255865, 0.0360685, -0.703289, 0.584976, 0.482819, -0.442671, 0.430992, 0.22227, -0.584405, 0.634876, -0.459898, -0.034332, -0.183143, 0.0425568, 0.746816, 0.183466, 0.160072, -0.687299, 0.3428, -0.579981, 2.20816, -0.26821, 0.104586, -0.642631, 0.00962135, -0.585949, 1.3089, 0.312346, 0.0187367, -0.0870731, -0.471523, 0.6808, -0.697106, 0.0405859, -0.196089, -0.0256506, 0.512637, -0.550852, 0.316118, 0.82512, -0.932918, 0.0548054, -0.0691433, 0.00938467, -0.188773, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.06778, 0.0344189, -0.00222405, 0.0686246, -0.380264, 0.235947, 0.0190772, -0.48517, 0.247254, 1.22134, -0.19597, 0.513269, 0.476122, -0.352711, -0.125376, -0.216972, 0.51427, -0.312375, -0.0328808, 0.522547, -0.405417, 0.957507, 0.328888, -0.531307, 0.516941, 2.88329, 0.00693158, -0.201371, -0.268054, 0.0461242, -0.567902, 1.1836, 1.07446, 0.251978, 0.0705809, -1.13579, -0.812332, 1.41842, -0.0289873, 0.0660811, -0.0587564, 0.474422, 0.318032, -0.488681, -0.171418, 0.180129, 0.946826, 1.02109, 0.0101449, 0.744694, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.655075, 0.0164387, 0.0366246, 0.177964, 0.366021, 0.44641, 0.00680532, 0.626608, -0.64574, -1.94299, 0.336492, 1.22928, -0.450805, 0.53112, 0.515462, -0.793327, 0.294587, 0.797357, 0.0122763, -1.10604, 0.0327199, -0.0828126, -0.261638, -0.377329, 0.0791103, 2.51438, -1.75784, 0.606115, 0.834736, 0.0249963, 1.31886, 1.13386, -0.985015, -0.460914, 0.200869, 0.284671, 0.137742, 0.331948, 0.00896249, -0.123893, 0.26379, 0.714411, -0.697799, -0.134967, 0.0257488, 0.535767, 0.193502, -0.0636542, 0.0436053, -0.820588, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.00859, 0.00964938, -0.0260507, -1.97109, -0.178861, -0.0872287, 0.0258517, -0.0575296, -0.566175, -0.984028, 0.12646, 0.324272, -0.262476, 1.72576, 0.885657, 0.843804, 0.917316, 1.29201, -0.0231202, 0.254617, 1.09331, 2.29212, 1.58205, -0.206142, -0.479806, 0.94813, -0.474594, 0.169825, 0.371081, 0.00629849, -2.8414, -0.292976, -0.853772, 0.610063, 0.103738, 0.353901, 0.627537, 0.33616, 0.0525245, -0.687595, 0.991269, 0.367813, -0.152504, -0.0359097, 0.132177, 0.121041, 0.0685087, -0.12109, -0.0366684, 0.265422, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0382411, -0.0454778, 0.0279679, -1.87688, 0.585872, -0.48284, -0.0331704, -0.432949, 0.661612, 0.589162, 0.368233, -0.760537, -0.211078, -1.41428, -2.65694, -0.810495, -0.381588, -0.0200679, 0.000522581, -0.264054, 0.0231162, -0.960968, -1.29865, -0.872881, 0.200225, -4.13963, 0.886618, -0.873222, 0.192742, -0.00786447, -0.211825, 0.372305, 0.287954, 0.428078, -0.278429, 0.00887717, -1.06172, 0.303869, -0.0335036, 0.716549, 0.281811, 0.157619, -1.28207, 0.632141, -0.608236, -2.09721, -0.351585, -0.17695, 0.014541, 0.584467, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.428972, 0.0283061, 0.023512, -4.32271, -0.555818, 0.501647, -0.0130971, 0.156082, 0.344418, 0.716639, -0.168123, -0.0771917, -1.68225, 0.73003, -0.58561, -1.24731, 0.0453372, -5.21461, -0.0357975, -0.795874, -0.205325, -0.0340176, -0.160822, -1.19482, -0.0697359, -5.7038, 1.2089, 0.137693, -0.369307, 0.0170458, 0.494073, 1.55403, 0.263624, 0.455938, 0.0482342, 0.00503275, 0.772527, -0.93065, -0.00207728, -0.085989, 0.564283, -0.726747, -0.13993, 0.186751, 0.0541882, 0.531235, -0.307814, -0.193084, 0.0301065, 0.0452925, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.420354, 0.011102, -0.0100949, -2.7855, 0.444735, -0.341821, -0.0336035, -0.196111, 0.00688367, 0.0121731, -0.871266, 0.340184, 0.417717, -0.12782, -0.787633, -0.216453, 0.088588, -0.31274, 0.00872857, 0.36717, -0.444221, -0.601963, 0.0119677, -0.190108, 0.151363, -0.643591, 0.843356, 0.0949585, 0.32265, 0.0203074, 0.424942, -1.19022, -0.327875, 0.427815, 0.303704, 0.288988, 1.27872, -1.45, -0.00580711, -0.160407, -0.250804, 1.13876, 0.439097, 0.374644, 0.448239, -0.510803, 0.321372, -0.716122, -0.0405768, -0.601686, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0230765, 0.0425039, 0.00604485, 0.00866214, -0.0112167, -0.0208478, -0.000221185, -0.00334536, -0.040503, -0.0698407, -0.00654019, -0.00810153, 0.00852389, 0.0428863, -0.0472654, 0.0302426, -0.024082, -0.010352, 0.0117341, 0.0111874, 0.0311825, 0.016727, -0.0214917, -0.0412443, 0.0318757, 0.0443425, -0.0496544, 0.044432, -0.0334993, 0.0425624, -0.0435212, -0.00718994, -0.0216302, -0.0151579, -0.0435055, -0.0448481, -0.0141563, -0.0126352, -0.027484, -0.0224617, 0.00742873, -0.018015, 0.0329805, -0.0120797, -0.0326914, -0.0419061, 0.0149964, -0.00970029, 0.0268344, 0.0509176, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.134675, -0.0283421, 0.0325593, 0.568914, 0.311424, 0.0252139, 0.041917, 0.0746309, 0.0583415, 0.591764, -0.155039, 0.0785674, -0.269412, -0.18379, -0.201881, 0.139437, -0.161931, -0.209872, 0.018233, 0.57487, 0.0430545, 0.643033, 0.24406, -0.179074, 0.208049, 1.58078, 0.233516, 0.282132, -0.23157, -0.0321117, -0.78181, -0.0927894, 0.333846, 0.0575534, 0.0570362, -0.0261611, -0.175828, 0.218298, -0.0531317, -0.306272, -0.351634, 0.0479559, 0.0908989, 0.189459, -0.16834, -0.50422, 0.199647, 0.023206, -0.0268954, 0.273896, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.089832, -0.0058392, -0.0476836, -0.468711, 0.197222, 0.496236, -0.0363833, -0.397042, 0.201457, -0.753343, -0.18867, 1.51596, -0.223412, 0.953162, 1.23865, -2.63986, 0.157286, -1.00065, -0.045119, -0.757357, 0.193874, -1.20186, -1.65953, 0.157915, -0.433512, -0.284269, 0.112124, 0.792522, 2.10487, 0.0418095, -1.98397, 1.31459, -0.290935, 0.89202, 0.199035, -0.00662774, 0.798099, -0.968541, 0.0314963, -0.239914, 1.12785, -1.30672, -0.384953, -0.59819, 0.810036, 0.771004, -1.23762, -0.972403, 0.0320565, -0.322074, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.533056, 0.0301338, 0.000450955, -0.0169449, 0.394584, -0.213158, 0.0143484, 0.0312714, -0.718086, -0.873308, -0.175898, 0.277615, 0.106061, 0.416285, 0.280482, -0.0522649, 0.310982, -2.72787, 0.0211982, 0.134969, -0.57014, 0.191996, 0.199784, -0.29206, 0.0975938, 1.42406, -0.332286, -0.283385, 0.0532732, 0.0185434, -0.122626, 0.149549, 0.355473, -0.124114, -0.147041, -0.129311, 0.411871, -0.155746, -0.00935963, 0.410151, -0.840325, 0.162905, -0.0907317, -0.197543, -0.0673483, 0.440741, -0.172629, -0.0456312, -0.0171342, -0.252047, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0357318, 0.0450605, 0.0421839, -11.242, 0.266213, -0.637663, 0.0128606, -0.0945967, 0.120034, -0.56783, 0.222139, -0.986788, -0.301952, 1.27303, 1.09125, 0.269037, 0.771456, 0.620312, -0.032509, 0.74973, -0.115995, 1.07366, 0.489576, 0.2579, 0.200169, 0.348922, 0.293085, -0.128882, 0.648135, 0.0483273, -1.00878, -0.165187, 0.276639, -0.0615758, -0.190746, -0.240532, 0.704171, -1.39398, -0.0377028, -0.0766554, -0.446226, 0.317941, -0.248637, -0.773776, -0.141562, -0.421989, -0.634853, -1.35103, -0.0186773, -0.117341, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.946593, -0.0221957, 0.040491, 0.663431, 0.0909302, -0.224121, -0.0164189, -6.54241, -0.291494, -1.58872, -0.0752477, -0.995423, 0.558704, -0.313282, -0.256967, -0.409046, -0.164638, 0.0581523, -0.0245705, 0.380206, -0.225828, -0.869062, -0.887467, 0.74313, -0.454857, 0.587341, -0.288038, 0.0138775, -0.0542681, 0.0213342, 0.0704731, 0.528576, -0.0626746, -0.0102671, -3.9644, 0.0289203, 0.249151, -1.08364, -0.0295513, 1.00314, 0.577083, -0.065843, -0.411268, -0.678594, 1.0507, 0.998842, -0.597288, -0.0422921, 0.0455505, -1.02148, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.954327, 0.0266772, 0.0514533, 0.912429, -1.40858, -5.07143, 0.0532594, 0.387059, 1.07796, -1.24973, 0.676278, -1.00554, 0.202103, 1.86571, 0.467356, 1.18874, -4.70104, 0.884367, -0.0167872, -1.1408, -2.1699, -2.89044, 0.275337, 0.821742, 0.168856, -4.42739, -1.1772, 0.797766, -1.49599, 0.0382018, -2.53474, 0.17043, -3.23519, -1.15359, 0.060815, -0.302005, -0.650991, 0.112945, 0.0432233, -1.98592, -0.315874, 1.85365, -1.24812, -0.981022, -1.88318, -1.05639, 1.4989, 0.574752, 0.0166933, -3.49196, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.293382, 0.0115303, -0.0300807, -0.0263515, 1.36849, 0.193781, 0.012379, 0.519362, 0.267711, -0.563979, -0.476246, 0.65127, 0.914733, 0.501536, -0.12347, -1.56523, -0.311342, -2.20743, -0.0297588, -0.019627, 0.370306, -1.00903, -1.05096, -0.809662, -0.327455, -0.200574, -0.471705, -0.0114714, -1.04089, 0.0455044, 1.10211, 1.38408, -0.746379, -0.851029, 0.471854, -0.4508, -0.948197, -0.450125, 0.00110652, 1.46533, -0.811419, 0.99341, 0.139629, 0.398199, 0.0631665, 1.76213, -0.877674, 0.932817, -0.0113307, -0.311199, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.12783, -0.00919593, -0.0118468, 0.258667, -0.796779, -1.50908, -0.0295466, 0.788156, -0.50425, 0.652038, 0.266319, 0.473053, 0.577638, 0.609001, 0.0158412, 0.0907692, 1.13289, 1.10197, -0.0370423, 0.619267, 0.268206, 0.364352, 0.858178, 0.2932, -0.0821838, -0.755331, 0.661365, -1.70616, 0.864812, 0.00661227, -1.32318, 0.248612, -0.836806, 0.0883328, -0.339644, -1.36073, 0.486052, 0.989986, -0.0150513, 0.677363, 0.807683, -0.356108, -0.75579, 0.230967, 0.254993, -0.482836, -1.89509, 0.0913143, -0.00626889, 1.10661, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.38777, -0.00454229, 0.0497012, 1.0708, 0.19254, -0.0168642, 0.0477453, 0.0945038, -0.0359894, -0.0143644, -0.266836, 0.731572, 0.749883, 0.287955, -0.907636, 0.252374, 1.60382, -0.320988, 0.00604048, 0.572453, 0.199183, -0.796982, 0.207896, -0.0805822, 0.0117118, 0.989924, -2.7971, -5.28685, -0.00108187, -0.038542, -4.51399, -0.389183, -0.223448, -0.0801296, 0.151563, -0.19787, 0.581115, -0.291507, -0.00345056, 0.140115, 0.0257655, -0.196248, 0.029021, -0.359916, -0.203331, -0.10043, -2.25303, 0.289592, 0.0212118, -0.083148, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.771759, -0.0273428, 0.0196889, -0.577189, 0.197653, -0.965995, -0.0445225, -0.465324, 1.15957, 2.05721, -1.83507, 1.71085, 1.64233, 3.71569, -3.21709, -2.07053, -0.474854, 0.965559, -0.00606317, 2.5586, -0.113371, 1.17649, -0.85835, 0.0957424, -0.774141, 1.1047, -0.877691, -0.389167, 1.48849, -0.0130864, 0.989019, 0.39172, 1.89508, 1.64114, 0.216997, -0.00802008, 0.163388, -1.08442, -0.0414038, -0.347834, -0.940318, -2.59058, -0.0108722, 0.505758, -0.178299, 0.022653, -0.500763, -0.241365, 0.010683, 2.33838, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.138102, 0.00058958, 0.0283761, 0.549986, 0.0661433, -2.50239, -0.0469932, 0.352679, 0.0536239, -0.72213, 0.19088, -0.30828, 0.132972, -0.792769, 0.615765, 1.02873, -1.20273, -0.718913, 0.0201991, 0.252917, -0.681534, -0.227472, -0.557596, 0.041073, -0.270742, -3.20957, 0.187343, -0.0763597, -0.925862, -0.0241887, -0.437578, 0.346965, -0.090142, 0.214796, 0.081482, -0.725359, -0.733793, -0.545751, -0.0508016, 0.0250382, -0.19436, 0.364135, 0.0899854, -0.651392, 0.0199875, -0.534086, 0.301668, 0.323576, 0.0405854, -1.22383, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.3401, 0.0121334, -0.00800883, 1.4257, -0.365099, 0.378571, -0.00822665, -0.752624, -0.65972, 1.2278, -0.813437, 0.800513, 0.0313067, 0.91839, -0.518418, 1.1642, 0.430446, 1.60216, 0.0371016, 0.936469, -0.484686, 1.79936, 1.94012, -0.390006, 0.627778, 2.14924, 1.16332, 0.713161, 0.0173174, -0.0200927, 0.703903, 0.528863, -0.693374, 0.0185382, -0.17631, -0.366435, 1.79156, 1.2386, -0.0240505, -0.245714, 0.023033, 0.00377718, 0.252785, -0.903414, -0.173591, 0.349916, 0.362114, -2.15148, 0.0187364, 1.58117, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.50539, -0.0228517, 0.0416224, -0.409626, -1.64663, 1.34598, 0.0391681, -3.20157, 0.146062, 2.75871, -0.61292, 3.31265, -0.284479, 2.25395, -0.349595, 0.229642, 0.514632, 1.11528, 0.0287406, 0.105885, 0.677524, -2.17179, 1.86918, 0.45549, 2.12121, -0.571983, 2.58791, 0.531397, 0.144061, -0.0499785, 0.101364, 0.619147, -0.519203, -0.367891, -2.58595, -0.36753, 1.45037, 0.0938842, -0.0046505, 0.929458, 0.532295, 1.48385, 0.44598, 1.11539, -0.178974, 0.91566, 1.53495, 0.839349, -0.027788, 1.0096, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0590705, -0.00141676, 0.0119914, -1.69375, -0.0912304, 0.361036, -0.0072981, 0.140386, 0.198019, -0.0106635, 0.082318, 1.80503, -0.578689, -0.721823, -0.642943, 0.193089, 1.11686, 0.784666, 0.0411706, 0.370692, -0.142972, 0.434239, -0.362538, 0.226803, -0.0129982, 1.34117, 0.25939, -0.382362, 0.616974, 0.029159, 0.722447, -0.135499, 0.665274, -0.198023, -0.0363179, 0.113355, -0.969876, 1.52277, 0.0179129, 0.314434, -0.0420985, -0.945403, 0.297125, 1.00822, -0.192946, -0.772635, -0.234391, 0.0826652, 0.021268, 0.23637, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.101113, 0.0371734, 0.0107315, -0.126968, 0.0879583, -0.103949, 0.00541737, -0.0174191, -0.0527177, 0.390562, -0.693967, 0.632487, -0.798097, -1.52745, -0.744492, -1.4058, -0.0318744, -0.959487, 0.0495543, 0.625676, -0.035864, 0.133041, -0.448174, 0.154083, -0.199376, 2.24276, 0.999903, 0.281325, 0.537587, -0.0430699, 0.717528, 0.274869, 0.555, 0.556308, -0.0496878, -0.196055, 0.610387, 0.0106062, -0.0312864, 0.200599, 0.500662, -0.76813, 0.263402, -0.346404, 0.428867, -0.282818, -0.922678, -0.381409, -0.0455021, 0.714733, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.577698, -0.0369215, 0.0420604, -0.941128, 0.598361, 0.946358, -0.0342668, 0.22664, -0.219987, -1.649, 0.31793, -0.247147, 0.249903, -0.296621, 1.06243, -0.00103298, 0.729814, -0.359346, 0.0512736, -1.55571, 0.240059, 0.734834, -1.8309, 0.272621, 0.532336, -0.20266, -1.85707, -0.257893, -1.06486, 0.0220649, 1.53337, 1.53814, -0.398166, -0.0372271, 0.0353231, -0.0217013, -0.602596, 0.375331, 8.19982e-05, 0.454131, 0.302616, 0.826888, 0.305387, -0.873342, 0.660712, 0.565666, -0.0101074, -0.128374, -0.0338887, -1.03434, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.318596, -0.00186571, -0.0103086, -3.2705, -0.0248819, 1.22261, 0.00851778, 0.214473, -0.517481, -0.0425092, 1.06182, 0.181073, -1.32658, -2.43973, 0.674561, -0.163404, -0.453589, 0.0705861, 0.0385594, -0.97232, 1.02621, 0.332805, 0.704735, -0.572719, 0.646487, -2.39839, -0.662164, 1.04722, -0.412747, 0.0270702, -3.00255, 0.172178, -0.186008, 0.873544, 0.246415, -1.0094, 0.42461, -2.05485, -0.0294378, -0.345762, 0.66472, 2.01011, 0.131973, -1.45575, 0.336525, -2.73153, -0.760404, -0.342198, -0.049847, -1.75913, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.760214, -0.0408706, -0.0238836, -0.864504, 0.921205, -1.13125, -0.0333821, 0.378875, -0.537462, 0.361761, -0.64344, -0.000991932, 0.81196, 0.369736, -0.0395649, 0.438179, -0.340571, 0.107002, 0.0239568, -1.04195, -1.06163, -1.93315, 1.36499, 0.563536, -0.431078, -1.95502, -0.279297, -0.747956, -0.0736405, -0.0269252, -1.32509, -0.0424449, -1.05083, 0.447899, 0.210248, -0.599615, -2.01585, -1.10091, -0.00274574, 0.0887036, -0.0351324, 0.170155, -0.682618, 0.461644, 0.119972, -0.211176, 0.188575, 1.58981, 0.00499148, 0.22042, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.394744, 0.0451598, 0.00843855, -8.64305, 0.0505721, -0.432928, -0.00859871, -0.0498626, 0.528403, -0.265346, -1.01206, -0.213485, -0.944121, 0.719174, 0.906518, -0.280656, 0.144464, 2.40525, -0.0295381, 0.0668099, -0.398973, -1.82482, 0.377089, 0.0510083, -0.00770424, -0.847453, -1.56677, -0.469241, -0.15669, 0.0254073, -1.02425, -0.170599, -0.145966, -0.0945348, 0.251025, -0.299561, -1.26246, -3.19726, -0.0079116, 0.193228, -0.0570418, 1.14751, 0.0846883, 0.902416, -0.0520648, -0.946247, -0.815166, -0.292744, -0.0195672, -0.27404, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.205752, 0.0141348, 0.0238186, 0.0110625, -0.0780668, 0.804991, -0.00951888, 0.448299, -0.270209, 0.298123, -0.616803, 0.985479, 0.347499, 0.500774, 0.369662, 0.999876, 3.03668, 1.95676, 0.0129209, 0.608689, -1.11193, 1.16694, 0.783586, -0.529808, 0.0481731, 2.45282, -0.430251, -1.76543, 0.989718, -0.00255428, 2.8861, 0.20497, -0.827829, -0.490284, 0.036098, -0.0438288, 1.03597, 0.914541, -0.0392478, -0.0238381, 0.0536982, 0.116662, -0.0981768, -0.308972, -0.275115, 0.433435, -1.08495, -0.55384, -0.0431464, -0.591706, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.469939, -0.00428575, 0.0296289, 1.00469, -0.691086, -0.44241, -0.0465452, -0.302511, -0.264858, 0.0029502, 0.497938, 0.927781, 0.313907, 0.458113, -0.373221, 0.10398, 1.49416, -0.607689, 0.0202021, -0.103681, 1.36373, 1.50017, 1.01748, 0.69377, 0.85286, -0.0611901, 0.309808, -1.90695, -1.0428, -0.0243154, 0.251268, 0.0938104, 1.15704, 0.234515, -0.514147, 0.43469, 0.33847, 0.155534, -0.00486815, 0.423134, 0.0339721, -0.176598, -0.685949, 1.39892, 0.0502985, -1.1338, 0.420408, 0.0102128, 0.00810712, -0.620907, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.258992, 0.0390925, 0.0320232, -1.23515, -0.109423, -0.0440749, -0.020977, -0.0884084, 0.317673, 0.351339, -0.117655, -0.737693, 0.582759, -0.679441, -0.161368, 0.291509, -1.0132, -0.00896867, 0.0162354, 0.365794, 0.941431, 0.270007, 0.0137858, 0.26657, 0.135451, 0.542227, -0.511692, -0.845924, -0.153877, -0.0414075, 0.410176, 0.527841, -0.0751344, 0.109117, 0.440351, -0.504515, -0.061346, -1.34662, 0.0229068, 1.85892, 0.437179, -0.70837, 0.313044, -0.376874, 0.182559, -0.263453, 0.345296, -0.0866746, 0.0222974, -0.256489, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.248176, 0.0204616, -0.01597, -9.3133, -0.387316, 0.164584, -0.0267274, 0.706071, 0.201752, -1.44278, -0.0868364, 0.42155, -0.435936, -0.344492, 0.0589144, -1.08495, 0.0988594, -0.400791, -0.0295115, 0.580631, 0.227182, -0.0795563, -0.617337, 0.0921778, -0.389105, -1.07696, -0.441818, -0.135874, 1.02422, -0.0423222, -1.25833, 0.975295, -0.324869, -0.309133, 0.57203, 0.157027, -0.0483925, -1.16063, -0.0406848, -0.0519587, -0.63219, 0.864009, -0.314508, -0.133759, 0.147187, -0.663738, 0.434568, -1.24045, -0.00455045, -0.0194011, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8115, -0.01775, -0.001464, 0.013306, -0.3882, 0.2139, 0.00453, -0.777, -0.1377, -0.04626, -0.2471, 0.412, -0.4854, -0.4092, -0.471, 0.98, -0.4963, -0.1539, 0.04105, 0.3286, -0.445, -0.8013, 0.8364, 0.4304, -0.01683, 1.881, -0.10504, -0.3647, -0.5073, -0.02756, -0.958, 0.4385, -0.2467, 0.5576, 0.599, 0.12244, -0.215, 1.244, -0.03464, -0.3228, -0.0937, -0.3538, -0.0611, 0.1632, -0.3884, 0.2542, -0.1199, 0.4626, 0.04474, -0.31], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.10046, 0.01886, -0.00926, -0.556, -0.6177, 0.3792, 0.01016, -0.374, 0.0828, 0.237, -0.0919, 0.01631, 0.4382, 0.1427, -0.03818, -0.5903, 0.0747, 0.5093, -0.04932, -0.28, -0.2944, 0.698, -0.1526, -0.008705, 0.03778, 0.625, 0.4253, 0.04947, -0.6914, 0.01444, 0.2634, 0.1143, 0.1035, -0.4043, -0.01703, -0.3687, 0.1505, 0.1299, 0.03354, -0.01733, 0.0807, 0.2063, 0.07153, 0.407, -0.0888, -0.05453, 0.1755, 0.01944, -0.0402, 0.02087], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.7314, -0.01097, 0.003832, -2.867, -0.513, 0.005043, -0.02202, 0.319, 1.267, -0.907, -0.03757, 0.808, -0.7246, 1.225, -0.012825, -1.442, 0.1857, -0.4607, 0.01133, 1.454, -0.2266, 0.8223, 0.7373, -0.3628, 0.614, 4.637, -0.4763, -0.396, 1.106, 0.011246, 0.7007, -0.5176, 0.397, -0.4302, 0.01097, 0.2418, 0.7026, 1.71, -0.0282, -0.505, -0.3105, -1.393, 0.3523, 0.1003, 0.4553, -0.286, -1.016, -0.8804, 0.015144, 0.2627], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9634, 0.01848, 0.0525, -3.396, 0.2018, -0.5864, 0.007515, 0.063, 1.025, -1.185, -1.524, 0.3533, 0.635, 2.494, -1.101, -2.11, -0.1552, 1.208, 0.04013, 0.3577, 0.3171, 0.1608, -1.908, -1.182, 0.456, 1.836, -0.1884, 0.719, 1.558, 0.03815, 0.6733, -3.727, -0.632, -0.787, 0.05505, 0.005676, 1.622, -0.273, -0.03363, -0.3044, 0.0652, -1.232, -0.1774, 0.207, 0.858, -0.1796, -0.3909, -1.428, 0.001478, 1.577], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.519, -0.02461, -0.011, -0.4258, 1.167, 2.121, -0.001288, 0.8237, -0.52, -0.2373, 0.495, 0.2037, 0.2805, 0.7344, 1.975, 0.03702, 0.747, -0.025, -0.01211, -0.1288, 0.8604, 0.4055, 0.2678, -0.1748, -0.05185, -0.0402, 0.3147, 0.621, -1.128, -0.01843, 0.3088, 2.496, -1.048, 1.062, 0.03693, 0.02939, 0.1656, 1.087, -0.00971, 0.7446, 0.0859, 3.129, -0.9585, 0.0508, 0.7397, -0.516, 0.4717, 0.403, 0.0451, 0.3066], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.928, 0.001073, -0.03674, -0.64, 0.1219, -0.2817, 0.01372, 0.2878, -0.5234, -0.6514, -0.3838, -0.4695, 0.252, 1.527, 0.7134, -0.9043, 1.294, -3.506, 0.03302, -0.2913, 1.093, -0.1907, -0.1271, 0.57, 0.0718, -1.09, -0.3567, 0.965, 2.146, -0.00435, 2.287, 0.4976, -0.293, -0.606, 0.589, -0.7363, -2.275, 0.469, -0.01312, -0.615, 0.288, 1.299, -0.3572, -1.044, -0.2338, 0.1592, 0.261, -0.7744, -0.01775, 1.13], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.06003, -0.012, -0.04984, 1.056, 0.774, -0.649, -0.02415, 0.1642, 0.2896, 0.02051, -0.4949, -0.2417, 0.7295, -0.4675, -1.323, -0.7974, -0.5396, 1.158, -0.00385, 0.2764, -0.0325, 0.5684, -0.2183, 0.3394, -0.5015, -0.3281, -1.4795, 0.1545, -0.297, -0.03357, -0.7837, -0.5537, 0.9834, -0.5864, 0.337, 0.668, -0.648, 0.1478, 0.02393, -0.639, -0.574, 0.002243, 0.4883, 0.71, -1.386, 0.8555, 0.8945, -0.1123, 0.0297, 0.569], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.057, 0.03607, -0.01825, -0.502, 0.3726, 1.771, -0.002333, -0.6655, -0.4841, 1.539, 0.3293, 0.06067, 0.00842, 0.0902, 1.551, -0.9946, 0.629, 0.488, -0.009415, -0.251, 0.5776, -0.679, 0.05948, 0.6772, -0.73, 1.032, 1.109, 0.04404, 1.501, 0.02582, 0.4893, 0.75, 0.6675, -0.06256, -0.2703, 0.48, 1.454, 0.677, 0.03397, -1.512, 0.3655, 0.3237, -1.371, 0.8247, -0.10205, -0.896, 0.7417, 0.4915, 0.04706, 1.421], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.4238, 0.0328, -0.02621, 0.4016, -0.1011, -0.653, 0.0008264, -0.3674, 0.0655, -0.1128, 0.1416, 1.546, -0.2458, 0.11975, -0.1687, -0.3914, -0.5864, -0.4194, -0.003956, -0.4282, 0.3398, -0.541, 0.829, 0.1295, 0.1304, -0.3867, 0.10706, 0.2314, 0.1392, 0.00754, -0.93, -0.05127, -0.899, -0.02435, 0.1277, -0.61, 0.52, 1.983, -0.02525, 0.2163, -0.04507, -0.3398, -0.05887, -0.4075, -0.1757, -0.263, 0.2644, 0.0981, -0.001643, 0.7837], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.9443, -0.011826, 0.03793, -0.9756, -0.8823, 0.2314, -0.004875, -1.136, -0.4177, -1.04, 0.1969, 0.8623, -0.668, 0.738, 0.32, 0.958, -0.2625, -0.737, -0.03494, -0.737, 0.3408, -1.996, 1.387, 0.2169, -0.52, 0.8613, 1.222, 0.3137, 1.093, -0.0464, 1.655, 0.2876, -0.3252, 0.0386, 0.4167, 0.51, 0.3245, 0.9854, 0.02603, 1.161, -0.2202, -0.05304, 0.03635, 0.33, -0.1354, 0.0897, 0.2627, -0.547, 0.02158, 0.2957], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4805, 0.002363, 0.01918, -4.21, 0.1483, 0.2357, -0.01487, 0.0683, 0.596, -0.11005, -0.2727, 0.3936, -0.8604, 0.1948, 0.3223, -0.969, -1.01, 0.5225, 0.068, -0.299, 0.118, -0.7065, -0.584, 0.2644, -0.4583, -0.6094, -0.5083, -0.548, 0.4348, 0.01625, -1.818, -0.07764, -0.2305, -0.4558, 0.02629, 0.0406, 0.1223, -1.83, 0.0305, 0.529, 0.3809, 0.581, 0.1443, 0.1151, -0.0441, -0.4844, 0.5356, -0.4631, 0.042, 0.1525], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0709, -0.02202, 0.04376, -0.03772, -0.02768, -0.03094, 0.0449, 0.002691, -0.002768, -0.01393, -0.04367, 0.01233, 0.01819, 0.03308, -0.02196, -0.00876, -0.01469, 0.01109, 0.03412, -0.04562, -0.04227, 0.003187, -0.0597, -0.06198, -0.0442, -0.0003593, 0.0003664, 0.01663, -0.05618, -0.03027, -0.06152, -0.02527, 0.0251, -0.00761, 0.02187, -0.0442, 0.02179, -0.01944, -0.03125, 0.01166, -0.02098, 0.02951, -0.04507, -0.05344, -0.04074, -0.02228, 0.01275, -0.0593, 0.02332, 0.02106], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4167, 0.02937, -0.04086, 0.696, 0.1512, 0.1863, -0.034, 0.1399, -0.5405, -0.896, -0.817, 0.3044, -0.02296, 1.25, -0.158, -0.434, -0.85, -1.363, -0.01607, -0.476, -0.2954, -3.086, -0.4849, -0.2102, -0.2559, -0.712, -1.525, -0.6753, -2.715, -0.02621, -0.09393, -0.234, -0.8687, -0.575, 0.275, -0.657, -1.555, -1.801, 0.00788, 1.329, 1.195, 1.767, 1.715, -0.987, 1.034, 0.0818, -0.3333, 0.03943, -0.0463, -1.697], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.4727, -0.05496, -0.04623, 1.129, 0.495, 0.9106, 0.03387, -0.04108, 1.6875, -2.256, 0.2905, -1.178, 0.7686, -1.746, 0.3013, -0.03348, -0.3362, 1.888, 0.05167, 0.469, 0.0831, 0.323, -0.10236, -0.5005, 0.1433, -3.428, -3.04, 0.02713, -1.672, 0.0489, -6.79, -1.813, 0.845, -0.197, -0.02458, -0.2115, -1.859, -0.4138, -0.01537, 0.3196, -0.732, -1.465, -0.2737, -0.974, -0.3967, 0.9595, 0.1522, -0.994, 0.03412, 1.063], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.08704, -0.02809, 0.005817, -0.7134, 0.4917, -0.06964, 0.03735, -0.168, -0.3394, -0.3665, 0.1417, 0.797, -0.1681, 0.531, 0.10345, 0.02109, 0.639, -0.7817, -0.0001273, 0.8203, 0.2537, 0.3005, -0.732, -0.1415, 0.05017, -0.697, -2.186, 0.2375, -1.263, -0.03021, 0.4329, 0.1052, 0.4048, -0.522, 0.11176, -0.01907, -2.2, 0.1759, 0.04474, 0.2388, 0.2201, 0.1653, 0.2274, -0.2705, -0.09564, 0.02736, 0.3484, -0.4146, -0.015465, 0.7397], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.326, -0.00315, -0.02792, 0.3633, -0.1813, -0.4614, 0.006176, -0.08655, 0.1979, 0.2712, -0.693, -0.4307, 0.4114, -0.445, 1.687, 0.1748, -0.09814, 0.804, 0.02388, 0.5063, 0.3464, 0.6274, -0.153, -0.6455, 0.337, -1.232, 0.3315, -0.1036, -0.711, -0.04742, -0.02667, -0.012695, 1.189, 0.298, 0.1702, 0.07526, 0.3555, 0.4783, 0.0214, -0.2042, 0.1594, -0.1711, -0.05228, 0.261, 0.1202, -0.1181, -0.1123, -0.01334, -0.03336, 0.538], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.931, -0.0267, -0.04303, -8.42, -0.4102, 0.9146, 0.00952, -0.1542, -0.1749, 1.6875, -0.1565, 2.361, 0.4822, -0.01622, 0.2185, 0.577, 1.469, -0.4644, 0.0244, 0.4282, -0.2124, -3.438, 0.05533, 0.596, -0.4072, 1.584, 0.0783, 0.4983, 0.7617, 0.03537, 0.607, -0.728, 0.7627, 0.2766, -0.367, 0.5674, -0.1076, 0.872, 0.04144, -0.2598, 0.309, 0.7827, 0.1648, 0.04214, -0.577, 0.2412, 0.00839, 0.0721, 0.0176, 0.7217], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2898, 0.02742, -0.04172, -0.2109, -1.349, -0.2917, -0.03845, 0.1526, 0.001058, -0.6353, -0.1702, -0.103, 0.0609, 1.49, 0.687, -0.165, -0.6523, 0.79, -0.0069, -0.724, 0.879, -0.8013, 0.03687, 0.251, 0.2725, -0.3843, 0.2349, 0.002571, 0.533, -0.02951, -0.0355, 0.2317, -0.3352, 0.1721, 0.285, -0.3137, 0.7993, -2.91, -0.01261, -0.0933, 0.3113, 0.6597, -0.2983, -0.7593, 0.5225, -0.269, 0.2052, 0.5225, 0.04538, 0.4595], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.135, 0.02959, 0.0245, -2.281, 0.10956, 0.3887, 0.02217, -0.2229, 0.4985, 0.7773, -0.3113, 0.656, 0.1953, -1.376, 0.7793, -0.4944, 0.811, -6.152, -0.02582, -1.863, -0.165, 1.955, 1.31, -0.576, 0.03973, 1.1045, 0.6294, 0.3623, -0.11694, -0.001588, -1.398, 0.3064, -0.279, -0.2542, 0.0341, 0.5933, 0.0665, 0.3062, -0.02867, 0.2316, 0.03668, 0.2603, 0.02574, 0.3765, -0.503, -0.04822, 0.0017185, -0.1688, -0.04007, 1.22], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.2007, -0.003302, 0.01359, -1.409, 0.1387, -0.2559, 0.03607, -0.703, 0.585, 0.483, -0.4426, 0.431, 0.2223, -0.5845, 0.635, -0.46, -0.03433, -0.1831, 0.04257, 0.7466, 0.1835, 0.16, -0.6875, 0.3428, -0.58, 2.209, -0.2683, 0.1046, -0.6426, 0.00962, -0.586, 1.309, 0.3123, 0.01874, -0.0871, -0.4714, 0.6807, -0.6973, 0.0406, -0.196, -0.02565, 0.5127, -0.551, 0.3162, 0.825, -0.933, 0.0548, -0.06915, 0.009384, -0.1887], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.067, 0.03442, -0.002224, 0.0686, -0.3804, 0.236, 0.01907, -0.485, 0.2473, 1.222, -0.1959, 0.513, 0.476, -0.3528, -0.1254, -0.2169, 0.514, -0.3123, -0.03287, 0.5225, -0.4055, 0.9575, 0.3289, -0.5312, 0.517, 2.883, 0.00693, -0.2014, -0.268, 0.0461, -0.568, 1.184, 1.074, 0.252, 0.07056, -1.136, -0.8125, 1.418, -0.02899, 0.0661, -0.05875, 0.4744, 0.318, -0.4888, -0.1714, 0.1802, 0.947, 1.021, 0.01015, 0.7446], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6553, 0.01643, 0.03662, 0.178, 0.366, 0.4463, 0.006805, 0.6265, -0.6455, -1.943, 0.3364, 1.2295, -0.4507, 0.5312, 0.5156, -0.7935, 0.2947, 0.7974, 0.012276, -1.106, 0.0327, -0.0828, -0.2617, -0.3774, 0.0791, 2.514, -1.758, 0.606, 0.835, 0.025, 1.319, 1.134, -0.985, -0.461, 0.2009, 0.2847, 0.1377, 0.332, 0.008965, -0.1239, 0.2637, 0.7144, -0.6978, -0.135, 0.02574, 0.5356, 0.1935, -0.06366, 0.0436, -0.821], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.009, 0.00965, -0.02605, -1.971, -0.1788, -0.0872, 0.02585, -0.05753, -0.5664, -0.984, 0.1265, 0.3242, -0.2625, 1.726, 0.8857, 0.8438, 0.9175, 1.292, -0.02312, 0.2546, 1.094, 2.293, 1.582, -0.2062, -0.4797, 0.948, -0.4746, 0.1698, 0.371, 0.006298, -2.842, -0.293, -0.854, 0.61, 0.10376, 0.354, 0.6274, 0.3362, 0.05252, -0.6875, 0.991, 0.368, -0.1525, -0.03592, 0.1322, 0.12103, 0.0685, -0.1211, -0.03668, 0.2654], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.03824, -0.04547, 0.02797, -1.877, 0.586, -0.483, -0.03317, -0.4329, 0.6616, 0.5894, 0.3682, -0.7607, -0.211, -1.414, -2.656, -0.8105, -0.3816, -0.02007, 0.0005226, -0.2642, 0.02312, -0.961, -1.299, -0.873, 0.2002, -4.14, 0.8867, -0.873, 0.1927, -0.007866, -0.2118, 0.3723, 0.2878, 0.428, -0.2783, 0.00888, -1.062, 0.304, -0.0335, 0.7163, 0.2817, 0.1576, -1.282, 0.6323, -0.6084, -2.098, -0.3516, -0.177, 0.01454, 0.5845], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.429, 0.0283, 0.02351, -4.324, -0.5557, 0.5015, -0.0131, 0.1561, 0.3445, 0.717, -0.1681, -0.0772, -1.683, 0.73, -0.5854, -1.247, 0.04535, -5.215, -0.0358, -0.796, -0.2053, -0.03403, -0.1608, -1.194, -0.06976, -5.703, 1.209, 0.1377, -0.3694, 0.01704, 0.4941, 1.554, 0.2637, 0.456, 0.04825, 0.00503, 0.7725, -0.9307, -0.002077, -0.086, 0.5645, -0.7266, -0.1399, 0.1868, 0.0542, 0.5312, -0.3079, -0.1931, 0.0301, 0.0453], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.4204, 0.0111, -0.01009, -2.785, 0.4448, -0.3418, -0.0336, -0.1962, 0.006886, 0.01218, -0.871, 0.34, 0.4177, -0.1278, -0.7876, -0.2164, 0.08856, -0.3127, 0.00873, 0.3672, -0.4443, -0.602, 0.01197, -0.1901, 0.1514, -0.6436, 0.8433, 0.095, 0.3228, 0.02031, 0.425, -1.19, -0.328, 0.4277, 0.3037, 0.289, 1.278, -1.45, -0.005806, -0.1604, -0.2507, 1.139, 0.4392, 0.3748, 0.4482, -0.5107, 0.3213, -0.7163, -0.0406, -0.6016], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.02307, 0.0425, 0.006046, 0.00866, -0.011215, -0.02084, -0.0002211, -0.003345, -0.0405, -0.0698, -0.00654, -0.0081, 0.00852, 0.04288, -0.04727, 0.03024, -0.02408, -0.01035, 0.011734, 0.011185, 0.03119, 0.01672, -0.02148, -0.04123, 0.0319, 0.04434, -0.04965, 0.04443, -0.0335, 0.04257, -0.04352, -0.00719, -0.02164, -0.01516, -0.04352, -0.04486, -0.01415, -0.012634, -0.02748, -0.02246, 0.007427, -0.01802, 0.033, -0.01208, -0.03268, -0.0419, 0.015, -0.0097, 0.02684, 0.0509], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1346, -0.02834, 0.03256, 0.569, 0.3115, 0.0252, 0.04193, 0.07465, 0.05835, 0.592, -0.155, 0.07855, -0.2695, -0.1838, -0.2019, 0.1394, -0.162, -0.2098, 0.01823, 0.5747, 0.04306, 0.643, 0.244, -0.1791, 0.208, 1.581, 0.2335, 0.2822, -0.2316, -0.0321, -0.7817, -0.0928, 0.3337, 0.05756, 0.05704, -0.02615, -0.1758, 0.2183, -0.05313, -0.3062, -0.3516, 0.04794, 0.0909, 0.1895, -0.1683, -0.5044, 0.1997, 0.02321, -0.0269, 0.274], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.08984, -0.00584, -0.04767, -0.4688, 0.1973, 0.4963, -0.03638, -0.397, 0.2014, -0.7534, -0.1887, 1.516, -0.2234, 0.953, 1.238, -2.64, 0.1572, -1.001, -0.0451, -0.7573, 0.1938, -1.202, -1.659, 0.158, -0.4336, -0.2842, 0.1121, 0.7925, 2.105, 0.0418, -1.984, 1.314, -0.291, 0.892, 0.199, -0.006626, 0.7983, -0.9688, 0.0315, -0.2399, 1.128, -1.307, -0.385, -0.598, 0.81, 0.771, -1.237, -0.972, 0.03204, -0.322], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.533, 0.03014, 0.0004508, -0.01695, 0.3945, -0.2131, 0.01435, 0.03128, -0.7183, -0.8735, -0.1759, 0.2776, 0.1061, 0.4163, 0.2805, -0.05228, 0.311, -2.729, 0.0212, 0.135, -0.5703, 0.192, 0.1998, -0.292, 0.0976, 1.424, -0.3323, -0.2834, 0.05328, 0.01854, -0.1226, 0.1495, 0.3555, -0.1241, -0.1471, -0.1293, 0.4119, -0.1558, -0.00936, 0.4102, -0.8403, 0.163, -0.09076, -0.1975, -0.0673, 0.4407, -0.1726, -0.04562, -0.01714, -0.252], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03574, 0.04507, 0.04218, -11.24, 0.266, -0.6377, 0.01286, -0.0946, 0.12006, -0.568, 0.2222, -0.987, -0.302, 1.273, 1.091, 0.269, 0.7715, 0.62, -0.0325, 0.7495, -0.11597, 1.073, 0.4895, 0.2578, 0.2002, 0.3489, 0.293, -0.1289, 0.648, 0.04834, -1.009, -0.1652, 0.2766, -0.06158, -0.1908, -0.2405, 0.704, -1.394, -0.0377, -0.07666, -0.4463, 0.3179, -0.2487, -0.774, -0.1416, -0.4219, -0.635, -1.351, -0.01868, -0.1174], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.947, -0.0222, 0.0405, 0.6636, 0.09094, -0.2241, -0.01642, -6.543, -0.2915, -1.589, -0.07526, -0.9956, 0.5586, -0.3132, -0.257, -0.409, -0.1647, 0.05817, -0.02457, 0.3801, -0.2258, -0.869, -0.8877, 0.743, -0.4548, 0.5874, -0.288, 0.01388, -0.05426, 0.02133, 0.0705, 0.529, -0.0627, -0.01027, -3.965, 0.02892, 0.2491, -1.084, -0.02956, 1.003, 0.577, -0.06586, -0.4114, -0.6787, 1.051, 0.999, -0.597, -0.0423, 0.04556, -1.021], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.954, 0.02667, 0.05145, 0.9126, -1.408, -5.07, 0.05325, 0.387, 1.078, -1.25, 0.6763, -1.006, 0.2021, 1.865, 0.4673, 1.188, -4.7, 0.8843, -0.01678, -1.141, -2.17, -2.89, 0.2754, 0.822, 0.1688, -4.426, -1.177, 0.798, -1.496, 0.0382, -2.535, 0.1704, -3.234, -1.153, 0.06082, -0.302, -0.651, 0.1129, 0.0432, -1.986, -0.316, 1.854, -1.248, -0.981, -1.883, -1.057, 1.499, 0.5747, 0.0167, -3.492], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2935, 0.01153, -0.03008, -0.02635, 1.368, 0.1937, 0.01238, 0.5195, 0.2678, -0.564, -0.4763, 0.6514, 0.9146, 0.5015, -0.1235, -1.565, -0.3113, -2.207, -0.02975, -0.01962, 0.3704, -1.009, -1.051, -0.8096, -0.3274, -0.2006, -0.4717, -0.011475, -1.041, 0.0455, 1.103, 1.384, -0.7466, -0.851, 0.472, -0.4507, -0.948, -0.4502, 0.001106, 1.465, -0.8115, 0.9937, 0.1396, 0.3982, 0.0632, 1.762, -0.8774, 0.9326, -0.01133, -0.3113], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.128, -0.00919, -0.01185, 0.2588, -0.797, -1.509, -0.02954, 0.788, -0.5044, 0.652, 0.2664, 0.4731, 0.5776, 0.609, 0.01584, 0.09076, 1.133, 1.102, -0.03705, 0.619, 0.2683, 0.3643, 0.8584, 0.2932, -0.08215, -0.7554, 0.661, -1.706, 0.8647, 0.00661, -1.323, 0.2487, -0.837, 0.0883, -0.3396, -1.36, 0.486, 0.9897, -0.01505, 0.6772, 0.8076, -0.3562, -0.756, 0.231, 0.255, -0.483, -1.8955, 0.0913, -0.006268, 1.106], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.3877, -0.004543, 0.0497, 1.07, 0.1925, -0.01686, 0.04776, 0.0945, -0.03598, -0.014366, -0.2668, 0.7314, 0.75, 0.2878, -0.9077, 0.2524, 1.604, -0.321, 0.00604, 0.5723, 0.1992, -0.797, 0.2079, -0.08057, 0.01171, 0.9897, -2.797, -5.285, -0.001081, -0.03854, -4.516, -0.3892, -0.2234, -0.08014, 0.1516, -0.1979, 0.581, -0.2915, -0.00345, 0.1401, 0.02577, -0.1963, 0.02902, -0.3599, -0.2034, -0.1004, -2.254, 0.2896, 0.02121, -0.0831], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.772, -0.02734, 0.01968, -0.577, 0.1976, -0.966, -0.04453, -0.4653, 1.159, 2.057, -1.835, 1.711, 1.643, 3.715, -3.217, -2.07, -0.4749, 0.9653, -0.00606, 2.559, -0.11334, 1.177, -0.8584, 0.09576, -0.774, 1.1045, -0.878, -0.3892, 1.488, -0.013084, 0.9893, 0.3916, 1.8955, 1.642, 0.217, -0.00802, 0.1633, -1.084, -0.0414, -0.348, -0.9404, -2.59, -0.01087, 0.506, -0.1783, 0.02266, -0.501, -0.2413, 0.01068, 2.338], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1381, 0.0005894, 0.02838, 0.55, 0.06616, -2.502, -0.047, 0.3528, 0.05362, -0.722, 0.1909, -0.3083, 0.1329, -0.793, 0.6157, 1.028, -1.203, -0.7188, 0.0202, 0.253, -0.6816, -0.2274, -0.5576, 0.04108, -0.2708, -3.209, 0.1874, -0.07635, -0.926, -0.02419, -0.4375, 0.347, -0.09015, 0.2148, 0.0815, -0.7256, -0.734, -0.546, -0.0508, 0.02504, -0.1943, 0.364, 0.08997, -0.6514, 0.01999, -0.534, 0.3018, 0.3235, 0.0406, -1.224], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.34, 0.01213, -0.00801, 1.426, -0.365, 0.3787, -0.008224, -0.7524, -0.6597, 1.228, -0.8135, 0.8003, 0.0313, 0.9185, -0.5186, 1.164, 0.4304, 1.603, 0.0371, 0.9365, -0.4846, 1.8, 1.94, -0.39, 0.628, 2.148, 1.163, 0.7134, 0.01732, -0.0201, 0.704, 0.529, -0.6934, 0.01854, -0.1763, -0.3665, 1.792, 1.238, -0.02405, -0.2457, 0.02303, 0.003777, 0.2527, -0.9033, -0.1736, 0.3499, 0.362, -2.152, 0.01874, 1.581], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.506, -0.02286, 0.04163, -0.4097, -1.646, 1.346, 0.03915, -3.201, 0.1461, 2.758, -0.613, 3.312, -0.2844, 2.254, -0.3496, 0.2296, 0.5146, 1.115, 0.02875, 0.1059, 0.6777, -2.172, 1.869, 0.4556, 2.121, -0.572, 2.588, 0.5312, 0.144, -0.05, 0.1014, 0.619, -0.519, -0.368, -2.586, -0.3674, 1.45, 0.0939, -0.00465, 0.9297, 0.532, 1.483, 0.446, 1.115, -0.179, 0.9155, 1.535, 0.8394, -0.02779, 1.01], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.05908, -0.001417, 0.01199, -1.693, -0.09125, 0.361, -0.007298, 0.1404, 0.198, -0.010666, 0.08234, 1.805, -0.5786, -0.7217, -0.643, 0.1931, 1.117, 0.7847, 0.04117, 0.3706, -0.143, 0.4343, -0.3625, 0.2268, -0.013, 1.341, 0.2593, -0.3823, 0.617, 0.02916, 0.7227, -0.1355, 0.665, -0.198, -0.03632, 0.11334, -0.9697, 1.522, 0.01791, 0.3145, -0.04208, -0.9453, 0.297, 1.008, -0.193, -0.7725, -0.2344, 0.08264, 0.02127, 0.2363], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.10114, 0.03717, 0.010735, -0.127, 0.08795, -0.10394, 0.005417, -0.01743, -0.0527, 0.3906, -0.694, 0.6323, -0.7983, -1.527, -0.7446, -1.406, -0.03186, -0.9595, 0.04956, 0.6255, -0.03586, 0.133, -0.4482, 0.154, -0.1993, 2.242, 1.0, 0.2812, 0.5376, -0.04306, 0.7173, 0.275, 0.555, 0.556, -0.04968, -0.196, 0.6104, 0.010605, -0.03128, 0.2006, 0.5005, -0.768, 0.2634, -0.3464, 0.429, -0.2827, -0.923, -0.3813, -0.0455, 0.715], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5776, -0.03693, 0.04205, -0.941, 0.598, 0.9463, -0.03427, 0.2267, -0.22, -1.649, 0.3179, -0.2472, 0.2499, -0.2966, 1.0625, -0.001033, 0.73, -0.3594, 0.05127, -1.556, 0.2401, 0.735, -1.831, 0.2727, 0.532, -0.2026, -1.857, -0.2578, -1.064, 0.02206, 1.533, 1.538, -0.3982, -0.03723, 0.0353, -0.0217, -0.6025, 0.3752, 8.2e-05, 0.454, 0.3027, 0.8267, 0.3054, -0.8735, 0.6606, 0.5654, -0.01011, -0.1284, -0.03387, -1.034], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3186, -0.001865, -0.01031, -3.27, -0.02489, 1.223, 0.008514, 0.2145, -0.5176, -0.0425, 1.062, 0.181, -1.326, -2.44, 0.675, -0.1635, -0.4536, 0.07056, 0.03857, -0.972, 1.026, 0.3328, 0.7046, -0.5728, 0.6465, -2.398, -0.662, 1.047, -0.4128, 0.02707, -3.002, 0.1721, -0.186, 0.8735, 0.2465, -1.01, 0.4246, -2.055, -0.02943, -0.3457, 0.6646, 2.01, 0.132, -1.456, 0.3364, -2.732, -0.7603, -0.3423, -0.04984, -1.759], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.7603, -0.04086, -0.02388, -0.8647, 0.9214, -1.131, -0.0334, 0.379, -0.5376, 0.3618, -0.6436, -0.000992, 0.812, 0.3696, -0.03955, 0.4382, -0.3406, 0.107, 0.02396, -1.042, -1.062, -1.934, 1.365, 0.5635, -0.4312, -1.955, -0.2793, -0.748, -0.07367, -0.02693, -1.325, -0.04245, -1.051, 0.448, 0.2102, -0.5996, -2.016, -1.101, -0.002747, 0.0887, -0.03513, 0.1702, -0.6826, 0.4617, 0.12, -0.2112, 0.1886, 1.59, 0.00499, 0.2205], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.3948, 0.04517, 0.00844, -8.64, 0.05057, -0.4329, -0.0086, -0.04987, 0.5283, -0.2654, -1.012, -0.2135, -0.9443, 0.719, 0.9067, -0.2808, 0.1444, 2.404, -0.02954, 0.06683, -0.399, -1.825, 0.3772, 0.051, -0.007706, -0.8477, -1.566, -0.4692, -0.1567, 0.0254, -1.024, -0.1707, -0.146, -0.09454, 0.251, -0.2996, -1.263, -3.197, -0.00791, 0.1932, -0.05704, 1.147, 0.0847, 0.9023, -0.05206, -0.9463, -0.815, -0.2927, -0.01956, -0.274], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2058, 0.01414, 0.02382, 0.01106, -0.07806, 0.805, -0.00952, 0.4482, -0.2703, 0.298, -0.6167, 0.9854, 0.3474, 0.501, 0.3696, 1.0, 3.037, 1.957, 0.012924, 0.609, -1.112, 1.167, 0.7837, -0.53, 0.0482, 2.453, -0.4302, -1.766, 0.9897, -0.002554, 2.887, 0.205, -0.8276, -0.4902, 0.0361, -0.04382, 1.036, 0.9146, -0.03925, -0.02383, 0.0537, 0.11664, -0.0982, -0.309, -0.2751, 0.4333, -1.085, -0.5537, -0.04315, -0.592], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.47, -0.004284, 0.02963, 1.005, -0.691, -0.4424, -0.04654, -0.3025, -0.265, 0.00295, 0.498, 0.9277, 0.314, 0.458, -0.3733, 0.104, 1.494, -0.608, 0.0202, -0.1037, 1.363, 1.5, 1.018, 0.694, 0.853, -0.0612, 0.3098, -1.907, -1.043, -0.02432, 0.2512, 0.0938, 1.157, 0.2345, -0.514, 0.4346, 0.3384, 0.1555, -0.004868, 0.423, 0.03397, -0.1766, -0.686, 1.398, 0.0503, -1.134, 0.4204, 0.010216, 0.00811, -0.621], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.259, 0.0391, 0.032, -1.235, -0.10944, -0.04407, -0.02098, -0.0884, 0.3176, 0.3513, -0.1177, -0.738, 0.5825, -0.679, -0.1614, 0.2915, -1.014, -0.00897, 0.01624, 0.3657, 0.9414, 0.27, 0.01379, 0.2666, 0.1355, 0.542, -0.5117, -0.8457, -0.1539, -0.0414, 0.4102, 0.528, -0.07513, 0.10913, 0.4404, -0.5044, -0.06134, -1.347, 0.0229, 1.859, 0.4373, -0.7085, 0.313, -0.377, 0.1826, -0.2634, 0.3452, -0.0867, 0.0223, -0.2566], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2482, 0.02046, -0.01598, -9.31, -0.3872, 0.1646, -0.02673, 0.706, 0.2018, -1.442, -0.08685, 0.4216, -0.436, -0.3445, 0.05893, -1.085, 0.0989, -0.401, -0.02951, 0.5806, 0.2272, -0.0795, -0.617, 0.09216, -0.3892, -1.077, -0.442, -0.1359, 1.024, -0.04233, -1.259, 0.975, -0.325, -0.309, 0.5723, 0.157, -0.0484, -1.16, -0.04068, -0.05197, -0.6323, 0.864, -0.3145, -0.1338, 0.1472, -0.6636, 0.4346, -1.24, -0.00455, -0.0194]] [1.21833, 0.375853, -0.499518, 0.229708, -0.230561, 0.604014, -0.126404, -1.15477, 0.925198, 0.391276, -0.392373, -0.0485303, 0.661184, -0.258817, -0.262143, -0.421345, -2.23233, -0.402541, -1.27036, 0.626348, -1.40018, -0.981155, -1.5832, 0.0644774, 0.26938, -0.363033, -0.00779845, -0.555079, 0.856432, 0.244071, -0.340949, 1.81262, 0.861881, 0.702678, -2.12008, -0.474719, 0.736491, -0.191585, -0.996563, -1.29823, -0.374973, 0.355833, 0.466743, 0.195897, -0.209863, 1.4417, -1.92691, -1.33186, -0.608108, -0.0552489, 1.219, 0.3757, -0.4995, 0.2297, -0.2306, 0.604, -0.1265, -1.154, 0.9253, 0.3914, -0.3923, -0.04852, 0.661, -0.2588, -0.2622, -0.4214, -2.232, -0.4026, -1.2705, 0.6265, -1.4, -0.981, -1.583, 0.06445, 0.2693, -0.363, -0.007797, -0.555, 0.8564, 0.244, -0.341, 1.8125, 0.862, 0.7026, -2.12, -0.4746, 0.7363, -0.1915, -0.9966, -1.298, -0.375, 0.3557, 0.4668, 0.1959, -0.2098, 1.441, -1.927, -1.332, -0.608, -0.05524] ReLU [[-0.284275, 1.26682, 0.227606, -0.430687, 0.175256, -2.90409, -0.354323, -0.105499, -0.065354, -0.0687478, 0.929486, -0.0042842, -0.268191, -0.0775385, -0.0606558, 0.358629, -0.485917, 0.80015, 1.47266, 0.535073, 0.276766, 0.180479, -0.379851, 0.839968, -0.145853, 0.0502979, -0.0383403, 0.747112, 0.162377, 1.13293, 0.529236, 0.0734345, 0.545077, -0.0099485, -1.18784, -0.334543, 0.172153, -0.183255, -0.288845, -0.299769, -0.558723, -0.12049, -0.570181, -0.179259, -0.918069, -0.563468, 0.986531, 0.613763, 0.652368, 0.261866, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.358022, 0.54326, -0.633674, -0.0359051, 0.0108844, 1.26203, 0.259117, -0.627013, 0.14828, -0.0526315, -0.343257, 0.00637939, -1.40376, 0.785337, -1.11938, -1.36114, 1.4982, -0.0355828, 0.25936, 0.328618, 1.26909, 1.43333, -0.253105, -0.929219, -1.39051, -0.793451, -0.0487595, -2.08604, -0.0650096, 1.00569, 0.380984, -0.5136, -2.82662, -0.333894, 1.88868, 2.62377, 0.217485, 0.553979, 1.27434, 0.54456, 1.02915, 0.280127, -2.99456, 0.192758, -1.0324, 0.62225, -0.803031, 0.827546, -0.31556, 1.48484, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0234489, -2.49712, 0.114682, -0.0691118, -0.167092, -0.789033, 0.618592, 0.536524, -0.0168831, -0.251218, -0.302744, 0.0406662, -0.129925, -0.14334, -0.41705, -0.00382989, 0.0486284, 0.640536, 0.862996, -0.0287041, -0.707495, -0.560642, -1.00281, -1.49474, -0.199561, -0.142404, 0.0264394, 0.79126, 0.446107, 0.311888, -0.131916, -0.249532, 0.309585, -0.0229734, -1.31602, -0.685365, 0.356939, 0.590178, -0.556481, -0.738531, 0.0429873, -0.386154, 0.227895, -0.0901392, -0.0226938, 0.418468, -0.017173, 0.127852, -0.270323, 0.716056, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.999008, -0.790326, 1.29958, 0.979057, 0.373025, 0.338804, -1.03814, 2.0916, -1.15365, 0.08589, -0.49122, -0.0200842, 0.13314, -1.29883, 0.70453, -2.16993, 1.12447, 1.67437, -1.50205, 0.792417, 0.380403, 1.86452, -2.14393, -0.173538, 0.999718, -0.343665, -0.00649479, -3.68844, 2.40128, -4.86179, 0.96024, 3.34568, 0.865946, -0.820488, -0.672079, -4.45719, 1.10764, 2.02691, 0.170413, 1.74066, -0.755223, -0.184888, 0.977805, 1.82849, 1.69045, 0.040112, -0.0915305, 2.3925, 0.643472, -1.14999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0989006, 0.636087, -0.109757, -0.363131, -0.405639, 0.225736, 0.0618267, 0.183641, -0.392262, 0.566138, 0.806953, -0.0366909, 0.0871751, -0.850149, 0.225613, -0.262845, 0.430769, 1.04423, 0.866763, -1.42558, -0.422137, 0.490498, -0.466843, 0.210958, 0.398031, 0.300621, -0.00867315, -0.222954, 0.867751, 1.28645, 0.289921, -0.249705, -0.155034, 0.0458982, 0.15685, -0.203462, 0.140095, 0.692386, 0.0357768, 0.101185, -0.790539, -0.607616, 0.859083, 0.0816745, -0.0577447, -0.3711, 0.700928, 0.556247, -0.105712, 0.064958, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0968768, 0.197811, -0.593796, 0.263431, 0.205889, 0.0438197, -0.34953, -0.26315, 0.115324, -0.733997, -0.069615, 0.0311429, -0.0165353, -0.257602, -0.439022, -0.0481829, -0.505084, -0.0825689, -0.673385, -0.136646, 0.395274, -0.066023, -0.0319243, -1.21569, -0.228519, 0.680479, -0.0407958, 0.436588, 0.297282, -1.17586, 1.08094, -0.609057, -0.377546, -0.127441, -0.942879, -0.202809, 0.00364328, -0.739644, -1.49826, -0.418332, -0.214507, 1.06285, 0.50224, -0.234087, 0.321819, 0.0761167, -0.79505, 0.451784, 0.00834747, -0.150586, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.17728, 0.636085, -0.31551, -0.526668, -0.2318, 0.389489, 0.130099, 0.816966, -0.498103, -0.0886652, 0.460415, -0.0459181, 0.544465, 0.4648, -1.22266, -0.114208, -0.504829, -0.0293829, 0.0404724, 0.352464, 0.183928, -0.225708, 0.27759, -0.800456, 0.286067, 0.469946, 0.0456233, 0.545792, -0.130885, 1.45746, 0.650535, 0.0299198, 0.104971, 0.21923, 1.24524, -0.180106, -0.10135, 0.41107, 0.836492, -0.384781, 0.269002, -0.0295044, 0.128104, -0.0357706, -0.305127, -0.0325722, 0.884248, -0.320268, 0.0681919, 0.0784178, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.331806, -1.47116, 2.26557, 2.13391, 2.1977, 0.191304, 1.89413, 1.98131, -0.338592, 0.52804, 2.32016, 0.0136311, 1.43462, 0.819731, -2.64089, 0.482388, 0.369577, 1.29431, 2.0276, -0.061871, 0.182129, 0.568901, -0.0377707, 3.74893, 3.54831, 3.0322, 0.0302618, 3.75942, 0.453959, 0.897862, 2.9929, 0.0743171, 0.00879006, 0.37894, 0.900206, -1.80212, 0.810043, 3.0446, 1.15883, 0.44744, 1.31883, 1.93384, 1.35284, 1.19071, 2.06927, 0.938871, 0.90322, 1.66429, 2.07684, 1.28258, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.170405, 0.757803, -0.863912, 0.533469, -0.457795, 0.794137, 0.154619, 0.749436, 0.478885, 0.0874074, 0.518791, 0.0302184, 0.281403, 0.290648, -0.75424, 0.298071, -0.606848, -0.809644, 2.30369, -0.424082, -0.543999, 1.12735, 1.35418, 1.67151, 0.344811, -0.383678, -0.0418203, 1.39311, -0.630503, 0.901349, 0.187012, -0.0236141, -0.736971, -0.0638097, 1.14611, 1.89217, -0.159583, -1.55756, -4.41633, -0.112932, -0.364376, 0.704721, 0.121647, -0.79191, 0.545391, 0.577472, -0.566425, 0.64269, 0.0666288, 0.274511, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.379563, 0.734132, -0.687718, -0.103808, -0.0923686, 0.406493, 0.354254, 0.770176, -0.275157, -0.35677, -0.295576, -0.0454949, 0.133424, 0.103903, 1.14149, 0.949794, 1.04933, -0.224756, 0.311279, -0.442522, 0.797567, -0.442438, -0.427441, 0.32383, 0.136742, 0.619006, -0.0134779, -1.7229, -0.417007, 1.24927, 1.65082, -0.200069, 0.101421, 0.275574, 1.05537, 2.20239, -0.0301719, 1.32931, 0.34738, -0.0842973, 0.441186, -1.19089, -0.817613, -0.313352, 0.285404, 0.120433, 0.76657, -0.0445124, -0.0960039, 0.344398, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.145773, 1.25871, 0.171849, -0.0309215, -0.222246, 0.231912, 0.115675, 0.387131, -0.281555, -0.346492, 0.281663, 0.0139388, -0.0684206, 0.108411, -1.06896, 0.516769, -0.105826, 0.0190393, 0.415898, -0.249917, 0.148061, -0.202719, 0.13185, -0.687329, 0.1984, 0.342041, 0.0281302, -0.229348, 0.243042, 0.505675, -0.0135984, -0.101475, -0.0593905, 0.422999, 0.0221473, -0.042166, -0.186206, 0.507236, 0.541827, -0.482505, 0.0665278, -0.0198526, -0.460283, -0.865302, -0.579521, 0.156849, -0.0493468, -0.0690224, -0.192243, -0.187144, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.254234, -0.0759313, -0.21641, 0.0328228, 0.145663, 0.225521, -0.831283, 1.23902, 0.667077, -0.0542318, 0.337806, -0.0362097, -0.322588, 0.550372, -2.15276, -0.113621, 0.887147, 0.510452, -1.24905, -1.58582, -0.198863, 0.222578, -0.0766427, 0.184219, 1.06669, -0.980706, 0.0306799, 1.56745, -0.266377, 0.529986, -0.109913, 3.34233, -0.202272, -0.00740836, 1.41592, 0.519171, 0.0180143, 0.766378, 0.899749, 0.275515, 0.941362, -0.118229, 0.00180934, -0.208087, -0.20434, 0.176194, -0.819042, -0.19917, -0.0872376, 1.09437, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.328399, -0.806561, -0.233259, 0.199122, 0.0449956, -0.0516724, -0.868875, -0.545921, -0.186834, -0.37872, -2.50364, 0.0398915, -0.552926, 0.912888, -1.75948, -3.48989, 0.988646, -0.75722, -3.03757, -1.04781, -1.05044, 1.26576, 0.295852, -1.05146, 1.93959, 0.225418, -0.0694098, -0.864691, 0.542975, 0.444565, -1.32108, 2.29713, -0.191647, 0.244704, 0.312488, -1.37784, 0.00346581, 0.284705, 0.941921, 1.14781, 0.784581, -0.398951, 0.676804, -0.614706, -0.294457, -0.249609, -0.278088, -0.182958, 0.22915, -1.69271, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.162578, 1.76015, -0.810007, -3.75192, 0.577104, -0.0096827, -2.33598, -2.63967, -0.716967, 1.09646, -0.252697, 0.0378908, -1.34643, 1.2857, -0.592113, 0.140995, -3.23995, -1.47998, -5.03117, 1.1152, -0.556227, 0.0160079, 0.0194186, -1.75963, -0.74427, -0.636786, 0.0086819, -2.11797, -1.79077, -6.27138, -7.8958, 0.464458, -0.37865, 0.322548, -1.84493, -4.51041, -0.172198, 0.286625, -0.0687048, -0.0550956, -2.12365, -2.3063, -0.0208289, 0.563104, 0.582748, 1.69888, -1.17363, -1.20752, 0.406209, 0.0471435, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.650169, 2.05707, -0.198745, -0.210305, -0.154496, -0.427423, 0.0675001, 1.24475, 1.26031, 0.642608, 0.214276, 0.02566, -0.337905, 0.485601, 0.0864803, -0.661595, -0.249406, 0.7232, -0.538731, 0.206816, 0.495378, 0.722987, 0.799123, -0.418978, -0.535888, -0.144878, 0.0240383, 0.182735, -0.264767, -1.14296, 0.188878, 0.0446619, -0.140152, 0.425719, 0.674493, -0.337529, -0.277865, -0.820357, 0.781545, -0.275523, 0.434514, -0.549617, -0.308188, -0.406416, -0.340522, 0.140798, -0.00634322, 0.0281688, 0.338502, -0.332175, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.31412, 1.95941, -1.12863, -0.278226, -0.819963, 0.207142, -1.01198, 1.44693, 0.798008, -0.153769, -0.885878, -0.0489694, 0.775227, 0.115457, 0.734768, 2.02726, 0.469568, -0.221043, 1.29198, -0.311321, 1.26446, 0.127162, 2.04824, 0.126897, -0.301804, 0.468216, -0.00413409, 2.462, -0.180891, 0.324568, 2.00382, 0.503514, 0.749987, 0.984184, -0.344942, -1.80611, -0.158834, -0.163554, -0.378898, 0.36995, 0.135367, 0.459618, -0.863998, 0.34127, -0.692251, -0.841918, 1.2, 0.0700292, -0.840236, -0.402418, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.00377343, 1.49689, -2.0712, 1.50132, 0.232392, -0.871307, -1.90945, -0.0195531, -1.88687, -0.667356, 0.22901, 0.00299684, -0.20972, -1.77553, -1.08054, 1.5485, 1.39181, -0.0435803, -2.37731, -1.07081, -0.224445, -0.819183, -3.52851, -0.395608, 1.15439, -0.498944, -0.000630277, -1.94409, 3.15953, 0.0451801, 0.182467, -0.0349953, 0.458244, 0.328345, 0.104601, 1.34702, 0.165526, 0.129263, 0.0622065, -0.213281, -0.341571, 0.142802, 0.855909, 0.0818853, 0.900619, -0.4285, 0.371865, 0.848814, 0.286174, 0.221217, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.268186, 1.24137, -0.0312714, 0.435598, 0.177536, -0.326452, -0.946285, -0.281469, -0.227357, 0.151322, -0.269015, 0.00785447, 0.0910949, 0.0930259, -0.971911, -0.580382, -0.736818, 0.521062, 0.290421, 0.256289, -0.138516, -0.272388, -0.310447, 0.0340162, 0.384415, 0.48963, -0.0214476, 1.76603, 0.28767, -1.49288, 0.948355, -0.925331, 0.0546952, -0.411163, -0.891105, -0.885179, 0.165505, -0.348402, -0.335606, 0.0695606, -0.222304, 0.470472, 0.608533, -0.342523, -0.118527, 0.0832469, -0.291898, -0.0663922, 0.391779, 0.0113011, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.332611, 1.52356, 0.0904958, 1.06989, -0.255592, 1.19391, 1.20917, 0.59269, -0.887591, -0.306957, 0.193141, -0.0133169, 0.583804, 1.44802, -0.0323222, -0.69325, 3.04729, 0.737624, -3.51079, 1.08586, -0.00746613, -0.089289, 1.21751, 2.90606, 1.23159, -0.57073, -0.0250933, -0.889267, 0.389452, 2.52855, 0.16386, 0.0176434, 0.431767, -1.05188, 0.101002, 0.219061, -0.564139, 3.01826, 1.79934, -0.416807, -0.076716, -0.605331, 0.747534, 0.328707, -0.927759, -0.304006, 0.472812, 0.0830999, 0.215846, -0.594885, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0562114, -0.48633, 0.675919, 0.726934, 0.100005, -0.688669, -1.07123, 0.533984, -0.598761, 0.308611, 0.735271, 0.0124962, 0.0664155, 1.18192, -6.78514, -0.230588, 0.329212, -1.18258, -2.17538, -0.0115188, -4.61563, 0.168153, 0.0338641, 0.434331, -0.0131463, 0.101472, 0.00271732, -0.332126, -1.22241, 0.135337, 0.537247, 0.0610676, 1.01261, -0.601829, 2.16877, 1.65994, 0.188487, -2.2646, -0.870499, 0.172487, 0.115779, 1.12822, -0.10302, -1.99338, -0.385347, 0.0636825, 0.459609, 0.402605, -0.0932862, 0.631031, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.012778, -0.0272505, -0.0352487, -0.0295281, -0.0253257, 0.0191541, -0.00621281, -0.0415315, -0.00945223, 0.0358585, 0.0287837, -0.0497906, 0.00349082, -0.0112679, 0.0129249, -0.00668162, -0.0149547, 0.0237895, -0.0448949, 0.00539067, 0.037409, 0.0377003, -0.00466664, -0.00604354, -0.0360271, 0.0225744, -0.0307482, -0.0236538, -0.0347687, -0.0305213, -0.0130423, 0.0120021, -0.0488348, 0.0165546, -0.0327422, 0.0155539, -0.0178501, 0.0161265, -0.0216025, -0.0125374, -0.0432994, 0.00172066, -0.0178518, 0.00435269, -0.028389, -0.0455606, -0.0271542, -0.0339995, -0.0493311, -0.0138799, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.13098, -2.41854, -1.43525, -1.06749, 1.15255, 1.56461, -4.07561, -3.80718, 0.224617, -1.56527, -2.38962, 0.0291377, 0.449633, -5.35687, -1.98628, -9.2135, -1.49784, 1.27404, -1.18072, -1.01527, -0.620695, -1.07378, -1.73776, -1.76963, -2.22717, -1.24896, 0.0482713, -4.21331, 0.457737, -1.95539, -4.6641, -1.07585, 0.295743, -0.95307, -1.60651, -3.56269, -0.898775, -1.77992, 3.97808, 0.244878, -1.07307, -0.451742, 1.22102, 1.70229, -0.613326, 0.448902, -1.93906, 1.03113, -1.07723, 1.14332, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.313883, 0.169055, 0.0693451, 0.646804, 0.145751, -0.0962563, -1.63167, -0.488794, 0.474343, 0.0367232, -0.679209, 0.0369163, 0.212365, 0.969158, 0.0583536, -0.0952241, -1.23294, -0.418228, -0.339132, -0.14558, -0.0553567, 0.973366, -0.716211, -1.96829, 0.638094, -0.239422, -0.0677582, 0.416926, 0.212179, -1.34756, -0.528417, 0.0408894, 0.216852, -0.209786, -0.277045, -0.00699132, 0.430529, -0.367817, -0.102752, -0.195002, -0.220348, 0.786963, 0.502953, -0.499865, -1.05651, -0.328473, -1.02438, 0.355192, -0.333116, 0.279846, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.184484, 0.262424, 0.488954, -0.314003, -0.0804898, 0.00754351, 1.55459, 0.203896, 0.256019, 1.24919, -0.160849, -0.0130543, 0.331459, -0.778835, -0.884474, -0.0982978, 1.2265, 1.21316, -0.963929, 0.0525874, 0.252194, -0.369714, 0.347875, -0.855459, -0.330919, -0.344962, 0.0355463, -0.298102, 1.18565, 2.96705, -0.626469, 1.28156, -0.162213, 0.0852958, -0.28715, 1.58073, -0.215764, 0.860316, 1.54086, -0.164125, 0.220463, -0.687521, -0.357919, 0.541786, 0.700625, -0.652462, 0.319895, -0.656363, 0.228626, -0.012567, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.114098, 1.69226, 0.0411432, 0.640336, 0.454028, -0.371369, 1.56985, 1.80124, -0.687147, 0.0362648, 2.51554, 0.0175732, 0.0244624, 0.579202, -1.08378, 0.748737, -0.49071, 0.34689, 0.0328943, 0.244265, -1.03868, -0.18534, -0.203502, -0.192562, 0.0783449, 0.290319, -0.0224043, -0.145377, 0.19808, -0.0369191, 0.954906, 0.450173, 0.608103, -0.141527, 1.79435, -0.169488, 0.34406, 0.124211, 0.551751, 0.00287159, -0.105683, -0.684328, -0.346716, 0.26342, 0.349299, 0.243327, 0.51744, -0.0786158, -0.246908, -0.852789, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.306984, -2.88885, 0.820868, -1.1691, -0.645425, 0.659574, 0.620928, 0.914789, -0.380586, 0.653304, -1.30222, -0.0138448, 0.672416, 2.13761, 0.722731, 0.595021, 3.00366, 1.63084, 0.386863, 0.61162, 0.226447, 0.403856, 1.12581, 1.48901, 1.11141, 0.887769, -0.0388975, 2.4718, 0.0878332, 2.48974, -1.0884, 0.487133, 1.03251, -0.366449, 2.3258, 3.98911, -0.938098, 0.367399, 0.737401, -0.671277, 0.170576, 0.788092, 0.397106, 0.393602, 0.993614, -0.406408, 1.16868, -1.8853, -0.949831, 0.190619, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.0532, 0.812997, -0.0525606, -0.235053, -1.04217, -0.261044, 0.662683, 0.649432, 0.118334, -1.06859, 0.257147, 0.0229514, 0.577841, 1.17237, 1.44452, -0.0333943, 0.758348, 0.750978, 0.106588, -0.144782, 1.26728, -2.13705, -0.617745, -0.272711, -0.180695, -0.730183, -0.0393454, 0.749283, 0.412666, 2.08826, 2.16505, 0.811117, 0.0209224, 0.0619245, 1.16128, 4.05457, 0.27127, 1.34022, 1.31923, -0.480744, -0.553332, -0.39955, 1.69846, 2.30849, 1.06255, 0.0351151, -2.67225, 1.38479, -1.2118, -1.98709, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.322331, -1.53862, 0.789563, -0.527051, -0.253044, -0.119786, 0.531984, -0.610566, 0.354823, -0.749754, 1.77799, 0.0159274, 1.25937, 1.25386, 1.91068, 0.63536, -0.264885, 1.6047, 1.76722, 1.07923, -0.962823, 2.58385, -1.06186, 1.25926, 0.632296, 0.26415, 0.0399243, 1.93756, -0.836932, 2.73931, 0.0175712, -0.11787, -0.76016, -1.40027, 0.71932, 0.761819, 0.124984, 2.69124, 1.03144, 0.30401, 0.708613, 0.0308694, -0.471297, 0.376353, 1.31747, -1.68635, 0.212399, 0.894313, -0.34297, -0.339031, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.699171, 2.00548, -0.411671, 0.149516, -0.441447, 1.54196, 0.694866, 0.630184, 0.404716, 0.25343, -0.494987, 0.0229202, -1.50392, 1.7854, 0.967333, -0.268374, 2.98121, 1.25746, 1.08943, 0.740836, 0.967602, -0.0788312, 1.17115, 2.2943, 0.496295, 0.567636, 0.0398041, -0.671812, 0.376256, 1.84502, 0.918443, 0.107981, -0.296414, -0.837359, 1.66907, 1.92712, -0.347531, 2.1598, 0.0241494, -0.806388, -0.85464, 0.274417, 0.222605, -0.154209, 1.03067, 0.808865, 1.55303, 0.816903, -0.511125, 0.268956, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0192611, 1.79656, 0.551384, 0.159408, -0.0687317, -0.12259, 0.49486, -0.557924, -0.266792, 0.56198, 0.154324, -0.0187898, 0.261679, 0.0928194, 0.221043, -0.555954, 0.641607, 0.559963, 0.944821, 0.0973636, -1.30986, -1.48869, 0.813371, -0.899002, 0.250217, -0.57487, -0.0267058, -0.857023, 0.220931, 1.39376, -2.01034, -0.275653, 0.286628, -0.165247, -0.608814, -0.868963, 0.288176, 1.09796, 0.284953, -0.272322, 0.104043, -1.84853, -0.110347, 0.252881, 0.166985, 0.154492, 0.41363, -0.459985, -0.116676, 0.183026, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.403155, 3.58094, -0.0684845, 0.312943, 0.121371, -0.586346, -0.252782, -0.714082, 0.469945, 1.11993, 0.630787, 0.0172489, -0.703879, 0.154944, 2.67781, -0.0067704, 1.20004, -0.169173, 1.47658, -0.496227, 0.9496, -1.67541, -0.42254, 1.40841, 0.442921, -0.257257, -0.037838, 2.53684, 0.0574775, -2.21297, 1.58881, 0.506287, -1.23114, -0.649889, -0.0978173, 3.01143, -0.554836, -5.23069, 2.67389, -0.491398, -0.529609, -0.451351, 0.086119, 0.970209, 0.578646, 0.441398, 1.307, 0.967332, 0.697648, 0.23256, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.816338, -0.974669, 0.141914, -0.457434, 0.451895, 0.585282, -2.63146, -0.0527888, 0.228212, 0.567048, 0.583511, 0.0235531, -0.0661345, -0.282686, 2.91354, -0.47136, 0.0289292, 1.42143, -0.623908, -0.0960318, -0.313375, 0.557292, -0.379237, -0.0762243, 0.65277, 0.278464, -0.0276976, -1.23381, -1.36198, 0.162014, -3.42446, 0.00705659, -1.55472, 0.454882, -1.76812, -2.47277, -0.699334, -0.402984, 0.289787, 0.396324, -1.55657, 1.58907, -0.0908736, 0.122109, -1.72773, -0.536403, 0.671964, 0.262161, -0.110674, 0.164407, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0659705, 0.489986, -0.351049, 0.494412, -0.611202, -0.112238, 0.423225, 0.100006, 0.318215, -0.0163176, 1.21514, -0.00330576, 0.0560548, 0.920715, -0.880536, -0.303963, -0.236743, 0.813473, 0.976658, -0.210659, 0.333913, 1.22307, -0.21073, 0.715377, 1.38374, -0.609727, 0.0362775, 1.94526, -0.194261, 0.921757, 1.61522, -0.25421, 0.296928, 0.122845, 1.28446, -0.854302, -0.274163, 0.776896, 0.354005, 0.180336, 0.0951353, 0.486428, 0.575516, 0.00132232, 0.10317, 0.82646, 1.09443, 0.269363, -0.179425, -1.84294, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.900838, 2.57703, -0.69438, -0.736769, -1.00233, 0.0123685, -0.580937, 0.434144, 1.39883, 0.404135, 0.18097, -0.0365661, -0.491884, -1.25644, 0.857004, 0.146387, 0.895446, -0.0373804, -0.0994301, -0.804365, 0.745899, -0.011521, 1.46374, 3.24868, -1.01716, -0.196318, -0.0285723, 1.76171, -0.295487, 1.93959, 0.390272, 0.269372, -0.505943, 0.32369, 0.795021, -0.471801, -0.750619, 0.326403, -0.313848, 0.30256, 0.53201, -0.713615, -0.703975, -0.765731, -0.639235, -0.383566, 0.801341, -0.314607, 0.471662, -0.00616915, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.16323, 0.639406, 0.467339, -0.217598, -0.0924136, 0.22057, 0.740826, 0.426803, -0.974908, 0.214078, 1.10627, -0.0307786, -0.129054, 0.222244, 1.07914, 0.290719, 0.378242, 0.212707, 0.00320677, -0.255423, 0.0197094, -0.549325, 0.308789, 1.17322, 0.102338, -0.647064, -0.0208384, 1.85923, 0.00174391, 0.211018, -1.05418, 0.0584622, 0.192502, 0.723319, 0.180405, 1.35758, -0.214581, 0.0465302, 0.76632, -0.223966, 0.0427998, -0.339725, -0.778413, 0.453984, 0.697748, -0.558328, 0.345718, -0.0880078, -0.468329, -0.266022, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0528794, -0.0590655, 0.0304756, 0.213052, -0.0490519, 0.174651, 0.554494, -0.247633, 0.541209, -0.49833, 0.530083, -0.0415282, -0.301584, -1.17886, -3.57353, -0.673111, -0.552272, -0.357391, -0.142143, 0.365101, -0.165831, -0.798298, 0.527799, 0.342829, -0.0651988, -0.231023, 0.0511668, 1.8323, -0.00117606, 0.824258, -0.031021, 0.0634864, 0.347937, -0.389773, -0.571805, -1.05956, -0.0903921, -0.628903, 0.343957, -0.369439, -0.121596, 0.304264, 0.129098, 0.280402, 0.23922, 0.0732357, 1.41502, -0.0482111, 0.252375, -0.240341, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.48439, -0.46696, 0.537086, 0.0474083, 0.123195, 0.446715, -0.373878, 0.555024, -0.322277, -1.14056, -0.15141, 0.0276609, 0.391802, -0.128161, 0.0458416, 0.0400307, 0.10564, 0.763896, -0.47619, 0.483539, -0.16839, -0.01803, 0.0819146, 1.65726, 0.984789, 1.25194, 0.00399742, -1.59733, -0.184337, 1.1679, -1.16908, 0.612382, -0.193892, -0.440123, -0.0111288, -0.5446, -0.154512, -0.82155, 0.336127, -0.220392, -0.55122, -0.901624, -0.527955, -0.124108, 0.41872, -0.0141801, 0.437667, 1.0107, -0.517759, 0.670925, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.579823, 2.71946, -0.623132, 0.240218, -0.562435, 0.0747131, -0.11062, -1.95323, 0.405431, -0.296137, 1.41539, -0.0135745, -0.275769, 0.466078, 1.20972, 0.047969, 1.58726, 0.438355, -0.0530462, -0.340863, 0.711998, -0.271177, -0.346202, 2.22079, 1.84675, -0.771861, 0.0190983, 1.0816, -0.262031, 0.829304, -0.696025, -0.338908, 0.772854, -0.479626, -0.924252, 1.64185, -0.105003, -1.33625, 0.498782, 0.497039, -1.87295, 1.23388, 0.982982, -0.335519, 0.688252, 0.528904, -1.15255, 1.30328, -1.07958, 1.4042, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.755867, -2.53303, 0.690429, -0.253648, 0.11748, -0.529559, -0.407754, -2.20808, -0.0775436, 0.649543, 0.739101, 0.00485108, -0.471483, 0.350401, -1.3485, -0.481856, -1.5941, -1.05749, 1.26743, 1.68422, 0.152759, -2.06597, -0.234037, 0.642807, -0.0558574, -1.0353, 0.00759321, -0.510127, -0.156694, -1.85019, 2.34259, 0.139293, 0.453054, 0.426664, 0.444405, -1.75199, -0.231615, -1.21987, -1.7393, 0.0866174, 1.14908, 0.87026, 0.432537, -1.11913, -1.17699, -0.0786995, -0.733229, -1.19072, -0.37595, 0.350341, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0063073, -0.158148, -0.0833554, -0.0669555, -0.149701, -0.105554, 0.0129294, -0.0758146, -0.0287561, -0.0159452, 0.0370317, -0.00852738, 0.0701864, 0.0218395, -0.0250278, -0.0918062, -0.0167299, -0.141578, -0.0305547, 0.0894717, -0.265901, -0.00535277, 0.0598256, 0.0738661, -0.0956868, -0.0357707, 0.00793329, 0.00571656, 0.0747351, 0.0618329, 0.0111991, 0.178964, 0.026524, 0.036347, -0.251097, 0.0554032, 0.00741218, -0.0368947, -0.0707146, -0.0306597, -0.0214918, 0.117009, 0.077938, -0.155216, -0.0924666, 0.0591293, -0.0704943, -0.124119, 0.0410801, 0.0276152, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.00829052, 0.815607, 0.201056, -0.535283, -0.267006, 0.0332216, 0.622024, 0.731398, 0.285498, -0.322606, -0.238372, 0.0113493, -0.369413, 1.03725, -1.83024, -1.02129, -0.886929, 0.712246, -0.682769, -0.566121, 0.346827, 0.283019, -0.103928, 0.180462, 0.636335, 0.192885, -0.0485103, 1.43154, 0.342994, 1.51508, 0.263403, 0.126477, -0.0670699, -0.414532, 0.966859, 1.09097, -0.738341, 0.765486, 0.31896, 0.14129, 0.603468, 0.355562, -0.0997661, 0.114375, -0.315162, 0.638402, 0.55027, -0.573287, -0.184097, 0.0206618, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.106844, -3.71086, -0.552019, -0.612014, 0.99349, -0.443409, -2.6565, -1.25468, -1.94897, 0.0468946, -1.43641, 0.0384962, -0.488, -1.18082, 0.298491, -13.4291, 3.33805, -0.0885898, -1.78852, -2.68771, -4.02096, 1.39928, -0.342676, -2.84981, 0.223106, -0.547787, 0.00425122, -4.10294, 0.640137, 1.73471, 2.10137, -0.268978, 0.454505, -2.46765, -4.59062, -8.36669, 0.331325, -1.42121, -2.9716, -0.836467, -1.58039, -1.79906, 1.20955, 0.394612, -0.543273, -0.660232, -2.55132, 0.329211, -0.656977, 1.05109, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0723871, 0.580505, 0.29645, 0.21891, -0.258054, -0.0174203, -0.394323, -1.65597, 0.0302437, 0.0130167, -3.54187, -0.0359448, 0.428615, -0.010924, -0.190289, 1.23068, 1.09834, -0.11198, 0.918908, -0.265518, 0.343377, 0.96992, 0.503064, 1.03536, -0.348981, 0.272094, 0.0092088, 2.98221, 0.736067, 1.13716, 0.505523, 0.202451, 0.349912, -0.218073, 0.650273, -2.44091, -0.169996, 0.78373, -0.838336, -0.383846, -0.442223, -0.505687, -0.136395, -0.142265, 0.972397, -0.29331, -3.17109, -0.759627, 0.279491, -0.500538, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.12236, 0.426088, -0.316444, -0.434342, -0.494173, 0.73156, -0.440819, 0.029812, 0.78854, -0.252462, 0.678571, -0.0411198, -0.539202, -0.701557, 1.14747, -0.482863, 1.65548, 0.268428, -0.833923, -0.872314, 0.161458, -0.666464, 0.743855, 2.51191, 0.324225, -0.621616, 0.0167678, -0.0916108, 0.0212643, 2.67912, -0.391477, 0.419872, -0.525817, -0.126785, 0.231581, 0.201953, -0.513373, 0.0985635, 0.537365, 0.413361, 0.580884, -0.107579, 0.0914069, 0.140279, 0.0291187, 0.205933, 0.588687, -0.23258, 0.281435, 1.1293, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0586664, -0.806584, -0.0765156, 0.182652, 0.0983031, -0.131669, 0.096281, -0.0310456, 0.52573, 0.759204, -0.542016, 0.0197133, 0.419307, -0.759262, -1.23573, 0.0689432, 0.335936, 0.00699886, 0.0644176, -0.160764, -0.00317411, -0.386552, 0.285078, -0.284247, 0.0554896, 0.0101737, -0.0271135, -0.0709641, 0.00449068, 0.449197, 0.0479091, 0.162362, -0.341255, 0.0758764, -0.254116, -1.78187, 0.241849, 0.511203, 0.0122546, 0.189284, 0.583504, -0.189127, -0.0894164, 0.38615, 0.091116, 0.035632, 0.0126621, -0.245792, 0.384396, 0.214631, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.240622, -2.21794, 0.253197, 0.100278, -0.23129, -0.723861, -0.128824, 0.457958, 0.243213, 0.325193, 0.511448, -0.00771262, -0.923622, 0.181761, 1.3402, 0.623447, 0.783559, -0.222595, 0.0427555, -0.0487431, -0.208418, -0.179052, 0.219971, 0.667823, 0.271573, 0.0818551, 0.0105107, 0.693074, 0.0419809, 0.805912, -0.0689762, -0.0682103, -0.529693, 0.0908128, 0.232833, 0.443013, -0.621185, 0.898635, -0.826145, -0.0430814, -0.0355935, 0.171585, 0.252858, 0.212211, 0.448188, 0.122546, 0.0302043, 1.14366, 0.237843, 0.361547, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.35751, -3.88019, -0.613062, -0.942671, 0.301746, 0.106906, 0.984956, -3.66305, 0.0188413, 0.854888, -1.40868, -0.0442855, -0.69085, -0.137974, 1.80443, -0.610102, 0.0283075, -1.30331, -0.411488, 1.72937, 0.521437, -0.830002, -1.16802, -4.2889, -1.5794, -2.78957, -0.00818726, -1.73344, 0.270378, -6.00068, 1.61027, 2.9489, 0.767939, 0.518549, 0.712006, -3.37045, 0.241456, -3.6613, 2.58931, -0.309675, -2.00334, -0.3577, 0.00207665, -0.20407, 0.0560358, 0.653713, -1.41749, -0.282993, 0.425683, -1.80554, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.105657, -1.2411, 0.097486, -0.0732571, 0.135073, 0.697984, -0.31206, 0.338973, 0.160884, -0.308835, -0.15801, -0.0199675, -0.237758, 0.531561, 0.122127, -0.069766, 0.552214, -1.16987, -0.557575, 0.342957, -0.282554, 0.0966528, 0.202975, 0.578097, 0.394102, 0.00282032, 0.00721883, -0.109211, -0.100114, 0.17035, -0.686516, -0.530799, -0.316579, 0.0779676, -1.26615, -0.0880863, 0.103119, -0.190706, -1.12426, 0.221176, 0.00238201, -0.721319, 0.405173, -0.173616, 0.0936056, 0.0124885, -0.318126, -1.39959, 0.126646, -0.229249, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0544387, 0.0318407, -0.00494751, -0.0453473, 0.00486177, 0.0273195, -0.00308243, 0.0315614, 0.0195515, -0.0497246, 0.0232228, 0.0297023, 0.000146404, -0.00510103, 0.0201175, -0.0101679, -0.0336553, 0.022804, -0.00202287, -0.0491653, -0.0155629, -0.0472109, 0.0116035, 0.0184606, -0.0554498, -0.0466292, -0.0265829, -0.0145717, -0.0625577, 0.0213534, 0.0305276, -0.00148679, -0.045615, 0.000178186, 0.0431409, -0.0256723, -0.0522248, 0.0225956, 0.0218752, -0.00685589, 0.0153951, 0.0158764, 0.000904041, -0.0560237, -0.0658094, -0.0484432, -0.0203288, -0.0437119, -0.00964187, -0.0312889, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.24653, -1.90103, 0.518482, 0.638194, 0.936413, -0.981042, -0.182626, -0.423077, -0.890909, -0.233012, -0.725546, 0.0127101, 0.36068, 0.617299, -0.283685, 0.430569, -0.650614, 0.722261, -0.70136, -0.317811, -0.290717, 0.0144176, -0.916125, -0.473655, 0.658821, -0.127603, 0.021195, -3.74292, 0.352904, -3.05259, -0.250116, 1.01783, 0.364797, -0.200665, -0.764628, -0.50688, 0.455734, -0.527596, -0.197679, -0.65848, -0.591984, 0.409957, 0.059913, 0.547452, 0.0361255, 0.313067, -1.11724, 0.517463, 0.23901, 0.93731, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.2842, 1.267, 0.2277, -0.4307, 0.1753, -2.904, -0.3542, -0.10547, -0.06537, -0.0687, 0.9297, -0.004284, -0.2683, -0.0775, -0.06067, 0.3586, -0.4858, 0.8003, 1.473, 0.535, 0.2769, 0.1804, -0.38, 0.84, -0.1459, 0.0503, -0.03833, 0.747, 0.1624, 1.133, 0.5293, 0.0734, 0.545, -0.00995, -1.1875, -0.3345, 0.1721, -0.1832, -0.2888, -0.2998, -0.5586, -0.1205, -0.5703, -0.1792, -0.918, -0.5635, 0.9863, 0.614, 0.6523, 0.262], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.358, 0.5435, -0.634, -0.03592, 0.01089, 1.262, 0.259, -0.627, 0.1483, -0.05264, -0.3433, 0.00638, -1.403, 0.785, -1.119, -1.361, 1.498, -0.03558, 0.2593, 0.3286, 1.27, 1.434, -0.2532, -0.929, -1.391, -0.7935, -0.04877, -2.086, -0.065, 1.006, 0.381, -0.5137, -2.826, -0.334, 1.889, 2.623, 0.2175, 0.554, 1.274, 0.5444, 1.029, 0.28, -2.994, 0.1927, -1.032, 0.622, -0.803, 0.8276, -0.3157, 1.484], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.02345, -2.498, 0.1147, -0.0691, -0.1671, -0.789, 0.6187, 0.5366, -0.01688, -0.2512, -0.3027, 0.04068, -0.1299, -0.1433, -0.417, -0.00383, 0.0486, 0.6406, 0.863, -0.0287, -0.7075, -0.5605, -1.003, -1.495, -0.1996, -0.1425, 0.02644, 0.7915, 0.446, 0.3118, -0.132, -0.2495, 0.3096, -0.02298, -1.316, -0.6855, 0.357, 0.5903, -0.5566, -0.739, 0.043, -0.3862, 0.2279, -0.09015, -0.02269, 0.4185, -0.01717, 0.1278, -0.2703, 0.716], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.999, -0.7905, 1.3, 0.979, 0.373, 0.3389, -1.038, 2.092, -1.153, 0.0859, -0.4912, -0.02008, 0.1332, -1.299, 0.7046, -2.17, 1.124, 1.675, -1.502, 0.7925, 0.3804, 1.864, -2.145, -0.1736, 0.9995, -0.3438, -0.006496, -3.688, 2.4, -4.863, 0.9604, 3.346, 0.8657, -0.8203, -0.672, -4.457, 1.107, 2.027, 0.1704, 1.74, -0.7554, -0.1849, 0.978, 1.828, 1.69, 0.0401, -0.09155, 2.393, 0.6436, -1.15], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0989, 0.636, -0.10974, -0.363, -0.4055, 0.2257, 0.06183, 0.1836, -0.3923, 0.566, 0.807, -0.03668, 0.08716, -0.85, 0.2256, -0.263, 0.4307, 1.044, 0.8667, -1.426, -0.422, 0.4905, -0.4668, 0.2109, 0.398, 0.3005, -0.008675, -0.2229, 0.8677, 1.286, 0.29, -0.2498, -0.155, 0.0459, 0.1569, -0.2035, 0.1401, 0.6924, 0.03577, 0.1012, -0.7905, -0.6074, 0.859, 0.08167, -0.05774, -0.371, 0.701, 0.556, -0.1057, 0.06494], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.09686, 0.1978, -0.5938, 0.2634, 0.2059, 0.04382, -0.3496, -0.2632, 0.1153, -0.734, -0.06964, 0.03114, -0.01654, -0.2576, -0.439, -0.0482, -0.505, -0.0826, -0.6733, -0.1366, 0.3953, -0.06604, -0.03192, -1.216, -0.2285, 0.6807, -0.0408, 0.4365, 0.2974, -1.176, 1.081, -0.609, -0.3774, -0.1274, -0.943, -0.2028, 0.003643, -0.7397, -1.498, -0.4182, -0.2145, 1.0625, 0.5024, -0.2341, 0.3218, 0.0761, -0.795, 0.452, 0.00835, -0.1506], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1772, 0.636, -0.3154, -0.527, -0.2318, 0.3894, 0.1301, 0.817, -0.498, -0.0887, 0.4604, -0.04593, 0.5444, 0.4648, -1.223, -0.1142, -0.505, -0.02939, 0.04047, 0.3525, 0.184, -0.2257, 0.2776, -0.8003, 0.2861, 0.47, 0.04562, 0.546, -0.1309, 1.457, 0.6504, 0.02992, 0.105, 0.2192, 1.245, -0.18, -0.1014, 0.4111, 0.8364, -0.3848, 0.269, -0.02951, 0.128, -0.03577, -0.3052, -0.03256, 0.8843, -0.3203, 0.0682, 0.0784], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3318, -1.471, 2.266, 2.135, 2.197, 0.1913, 1.895, 1.981, -0.3386, 0.528, 2.32, 0.01363, 1.435, 0.82, -2.64, 0.4824, 0.3696, 1.294, 2.027, -0.06186, 0.1821, 0.569, -0.03778, 3.748, 3.549, 3.031, 0.03026, 3.76, 0.4539, 0.898, 2.992, 0.07434, 0.00879, 0.379, 0.9004, -1.802, 0.81, 3.045, 1.159, 0.4475, 1.318, 1.934, 1.353, 1.19, 2.068, 0.939, 0.9033, 1.664, 2.076, 1.282], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1704, 0.758, -0.864, 0.5337, -0.4578, 0.794, 0.1547, 0.7495, 0.479, 0.0874, 0.5186, 0.03021, 0.2815, 0.2905, -0.7544, 0.298, -0.607, -0.8096, 2.303, -0.424, -0.544, 1.127, 1.3545, 1.672, 0.3447, -0.3838, -0.0418, 1.394, -0.6304, 0.9014, 0.187, -0.02362, -0.737, -0.0638, 1.146, 1.893, -0.1595, -1.558, -4.418, -0.1129, -0.3643, 0.7046, 0.12164, -0.792, 0.5454, 0.5776, -0.5664, 0.6426, 0.06665, 0.2744], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3796, 0.7344, -0.6875, -0.1038, -0.09235, 0.4065, 0.3542, 0.77, -0.2751, -0.3567, -0.2957, -0.0455, 0.1334, 0.1039, 1.142, 0.9497, 1.05, -0.2247, 0.3113, -0.4426, 0.7974, -0.4424, -0.4275, 0.3237, 0.1367, 0.619, -0.01348, -1.723, -0.417, 1.249, 1.65, -0.2001, 0.10144, 0.2756, 1.056, 2.203, -0.03017, 1.329, 0.3474, -0.0843, 0.4412, -1.19, -0.8174, -0.3132, 0.2854, 0.1204, 0.7666, -0.04453, -0.096, 0.3445], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1458, 1.259, 0.1719, -0.03091, -0.2223, 0.2319, 0.11566, 0.3872, -0.2815, -0.3464, 0.2817, 0.01394, -0.0684, 0.1084, -1.069, 0.5166, -0.10583, 0.01904, 0.416, -0.2499, 0.1481, -0.2028, 0.1318, -0.6875, 0.1984, 0.342, 0.02814, -0.2294, 0.243, 0.506, -0.013596, -0.1015, -0.0594, 0.423, 0.02214, -0.04218, -0.1862, 0.5073, 0.542, -0.4824, 0.0665, -0.01985, -0.4602, -0.865, -0.5796, 0.1569, -0.04935, -0.06903, -0.1923, -0.1871], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.2542, -0.0759, -0.2164, 0.03284, 0.1456, 0.2255, -0.831, 1.239, 0.667, -0.05423, 0.338, -0.03622, -0.3225, 0.5503, -2.152, -0.11365, 0.887, 0.5103, -1.249, -1.586, -0.1989, 0.2225, -0.07666, 0.1842, 1.066, -0.9805, 0.03069, 1.567, -0.2664, 0.53, -0.1099, 3.342, -0.2023, -0.00741, 1.416, 0.519, 0.01802, 0.7666, 0.9, 0.2756, 0.9414, -0.1182, 0.001809, -0.2081, -0.2043, 0.1761, -0.819, -0.1992, -0.0872, 1.095], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3284, -0.8066, -0.2333, 0.1991, 0.04498, -0.05167, -0.8687, -0.546, -0.1869, -0.3787, -2.504, 0.0399, -0.5527, 0.913, -1.76, -3.49, 0.989, -0.7573, -3.037, -1.048, -1.051, 1.266, 0.296, -1.052, 1.939, 0.2255, -0.0694, -0.8647, 0.543, 0.4446, -1.321, 2.297, -0.1917, 0.2448, 0.3125, -1.378, 0.003466, 0.2847, 0.942, 1.147, 0.7847, -0.399, 0.677, -0.6147, -0.2944, -0.2496, -0.278, -0.183, 0.2291, -1.692], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1626, 1.76, -0.81, -3.752, 0.577, -0.00968, -2.336, -2.64, -0.717, 1.097, -0.2527, 0.0379, -1.347, 1.286, -0.5923, 0.141, -3.24, -1.4795, -5.03, 1.115, -0.556, 0.016, 0.01942, -1.76, -0.744, -0.6367, 0.00868, -2.117, -1.791, -6.27, -7.895, 0.4644, -0.3787, 0.3225, -1.845, -4.51, -0.1722, 0.2866, -0.0687, -0.05508, -2.123, -2.307, -0.02083, 0.563, 0.5825, 1.699, -1.174, -1.208, 0.4062, 0.04715], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6504, 2.057, -0.1987, -0.2103, -0.1545, -0.4275, 0.0675, 1.245, 1.261, 0.6426, 0.2142, 0.02567, -0.338, 0.4856, 0.0865, -0.6616, -0.2494, 0.723, -0.5386, 0.2068, 0.4954, 0.723, 0.7993, -0.419, -0.5356, -0.1449, 0.02403, 0.1827, -0.2646, -1.143, 0.1888, 0.04465, -0.1401, 0.4258, 0.6743, -0.3376, -0.2778, -0.8203, 0.7817, -0.2756, 0.4346, -0.55, -0.308, -0.4065, -0.3406, 0.1407, -0.006344, 0.02817, 0.3386, -0.3323], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.314, 1.959, -1.129, -0.2783, -0.82, 0.2072, -1.012, 1.447, 0.798, -0.1538, -0.8857, -0.04898, 0.7754, 0.1155, 0.735, 2.027, 0.4695, -0.2211, 1.292, -0.3113, 1.265, 0.1272, 2.049, 0.127, -0.3018, 0.4683, -0.004135, 2.463, -0.1809, 0.3245, 2.004, 0.5034, 0.75, 0.9844, -0.345, -1.806, -0.1588, -0.1636, -0.379, 0.3699, 0.1354, 0.4597, -0.864, 0.3413, -0.6924, -0.842, 1.2, 0.07, -0.8403, -0.4023], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.003773, 1.497, -2.07, 1.501, 0.2324, -0.871, -1.909, -0.01955, -1.887, -0.6675, 0.229, 0.002996, -0.2097, -1.775, -1.08, 1.549, 1.392, -0.04358, -2.377, -1.071, -0.2245, -0.8193, -3.53, -0.3955, 1.154, -0.499, -0.0006304, -1.944, 3.16, 0.04517, 0.1825, -0.035, 0.4583, 0.3284, 0.1046, 1.347, 0.1655, 0.1293, 0.0622, -0.2133, -0.3416, 0.1428, 0.856, 0.0819, 0.9004, -0.4285, 0.3718, 0.8486, 0.2861, 0.2212], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.268, 1.241, -0.03128, 0.4355, 0.1775, -0.3264, -0.9463, -0.2815, -0.2274, 0.1514, -0.269, 0.00786, 0.09106, 0.093, -0.9717, -0.5806, -0.737, 0.521, 0.2905, 0.2563, -0.1385, -0.2725, -0.3105, 0.03403, 0.3845, 0.4897, -0.02145, 1.766, 0.2876, -1.493, 0.948, -0.9253, 0.0547, -0.4111, -0.891, -0.8853, 0.1655, -0.3484, -0.3357, 0.0696, -0.2223, 0.4705, 0.6084, -0.3425, -0.1185, 0.08325, -0.292, -0.0664, 0.3918, 0.0113], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.3325, 1.523, 0.0905, 1.07, -0.2556, 1.194, 1.209, 0.593, -0.8877, -0.307, 0.1931, -0.01331, 0.584, 1.448, -0.03232, -0.6934, 3.047, 0.738, -3.512, 1.086, -0.007465, -0.0893, 1.218, 2.906, 1.231, -0.571, -0.0251, -0.889, 0.3894, 2.53, 0.1638, 0.01764, 0.432, -1.052, 0.101, 0.2191, -0.564, 3.018, 1.8, -0.4167, -0.0767, -0.6055, 0.7476, 0.3286, -0.9277, -0.304, 0.473, 0.0831, 0.2158, -0.5947], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0562, -0.4863, 0.676, 0.727, 0.1, -0.6885, -1.071, 0.534, -0.5986, 0.3086, 0.7354, 0.0125, 0.0664, 1.182, -6.785, -0.2306, 0.329, -1.183, -2.176, -0.01152, -4.617, 0.1682, 0.03387, 0.4343, -0.013145, 0.1015, 0.002718, -0.332, -1.223, 0.1354, 0.537, 0.06107, 1.013, -0.602, 2.168, 1.66, 0.1885, -2.264, -0.8706, 0.1725, 0.1158, 1.128, -0.103, -1.993, -0.3853, 0.06366, 0.4597, 0.4026, -0.09326, 0.631], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.01278, -0.02725, -0.03525, -0.02953, -0.02533, 0.01915, -0.006214, -0.04153, -0.00945, 0.03586, 0.02878, -0.0498, 0.00349, -0.01127, 0.012924, -0.006683, -0.01495, 0.02379, -0.0449, 0.00539, 0.0374, 0.0377, -0.004665, -0.006042, -0.03604, 0.02257, -0.03075, -0.02365, -0.03476, -0.03052, -0.01304, 0.012, -0.04883, 0.01656, -0.03275, 0.01556, -0.01785, 0.01613, -0.0216, -0.012535, -0.0433, 0.00172, -0.01785, 0.004353, -0.0284, -0.04556, -0.02716, -0.034, -0.04932, -0.01388], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.131, -2.418, -1.436, -1.067, 1.152, 1.564, -4.074, -3.807, 0.2246, -1.565, -2.389, 0.02914, 0.4497, -5.355, -1.986, -9.21, -1.498, 1.274, -1.181, -1.016, -0.6206, -1.074, -1.737, -1.77, -2.227, -1.249, 0.04828, -4.215, 0.4578, -1.955, -4.664, -1.076, 0.2957, -0.953, -1.606, -3.562, -0.899, -1.78, 3.979, 0.2449, -1.073, -0.4517, 1.221, 1.702, -0.6133, 0.449, -1.939, 1.031, -1.077, 1.144], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.314, 0.1691, 0.06934, 0.647, 0.1458, -0.09625, -1.632, -0.4888, 0.4744, 0.0367, -0.679, 0.03693, 0.2124, 0.969, 0.05835, -0.0952, -1.233, -0.4182, -0.339, -0.1456, -0.05536, 0.973, -0.7163, -1.969, 0.638, -0.2394, -0.06775, 0.417, 0.2122, -1.348, -0.5283, 0.0409, 0.2168, -0.2098, -0.277, -0.006992, 0.4304, -0.368, -0.1027, -0.195, -0.2203, 0.787, 0.503, -0.4998, -1.057, -0.3284, -1.024, 0.3552, -0.333, 0.2798], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1844, 0.2625, 0.489, -0.314, -0.0805, 0.00754, 1.555, 0.2039, 0.256, 1.249, -0.1609, -0.013054, 0.3315, -0.779, -0.8843, -0.0983, 1.227, 1.213, -0.964, 0.05258, 0.2522, -0.3696, 0.348, -0.8555, -0.3308, -0.345, 0.03555, -0.298, 1.186, 2.967, -0.6265, 1.281, -0.1622, 0.08527, -0.287, 1.581, -0.2158, 0.8604, 1.541, -0.1642, 0.2205, -0.6875, -0.358, 0.542, 0.7007, -0.6523, 0.3198, -0.6562, 0.2286, -0.012566], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1141, 1.692, 0.04114, 0.64, 0.454, -0.3713, 1.57, 1.801, -0.687, 0.03625, 2.516, 0.01758, 0.02446, 0.579, -1.084, 0.7485, -0.4907, 0.347, 0.0329, 0.2443, -1.039, -0.1853, -0.2035, -0.1925, 0.07837, 0.2903, -0.0224, -0.1454, 0.1981, -0.03693, 0.955, 0.4502, 0.608, -0.1415, 1.794, -0.1694, 0.344, 0.1242, 0.552, 0.002872, -0.1057, -0.6846, -0.3467, 0.2634, 0.3494, 0.2433, 0.5176, -0.0786, -0.247, -0.853], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.307, -2.889, 0.821, -1.169, -0.6455, 0.6597, 0.621, 0.9146, -0.3806, 0.6533, -1.302, -0.01385, 0.6724, 2.137, 0.7227, 0.595, 3.004, 1.631, 0.387, 0.612, 0.2264, 0.4038, 1.126, 1.489, 1.111, 0.8877, -0.0389, 2.473, 0.0878, 2.49, -1.089, 0.487, 1.032, -0.3665, 2.326, 3.988, -0.938, 0.3674, 0.7373, -0.6714, 0.1705, 0.788, 0.3972, 0.3936, 0.9937, -0.4065, 1.169, -1.886, -0.9497, 0.1907], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.053, 0.813, -0.05255, -0.2351, -1.042, -0.261, 0.6626, 0.6494, 0.11835, -1.068, 0.257, 0.02295, 0.5776, 1.173, 1.444, -0.0334, 0.7583, 0.751, 0.10657, -0.1448, 1.268, -2.137, -0.6177, -0.2727, -0.1807, -0.73, -0.03934, 0.7495, 0.4126, 2.088, 2.166, 0.811, 0.02092, 0.06192, 1.161, 4.055, 0.2712, 1.34, 1.319, -0.4807, -0.553, -0.3997, 1.698, 2.309, 1.0625, 0.03513, -2.672, 1.385, -1.212, -1.987], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3223, -1.539, 0.7896, -0.527, -0.253, -0.1198, 0.532, -0.6104, 0.3547, -0.7495, 1.778, 0.01593, 1.26, 1.254, 1.911, 0.6353, -0.265, 1.6045, 1.768, 1.079, -0.963, 2.584, -1.062, 1.259, 0.6323, 0.2642, 0.03992, 1.9375, -0.837, 2.74, 0.01758, -0.11786, -0.7603, -1.4, 0.719, 0.7617, 0.125, 2.691, 1.031, 0.304, 0.7085, 0.03087, -0.4712, 0.3765, 1.317, -1.687, 0.2124, 0.8945, -0.343, -0.339], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.699, 2.006, -0.4116, 0.1495, -0.4414, 1.542, 0.695, 0.6304, 0.4048, 0.2534, -0.4949, 0.02292, -1.504, 1.785, 0.9673, -0.2683, 2.98, 1.258, 1.09, 0.7407, 0.968, -0.07886, 1.171, 2.295, 0.4963, 0.568, 0.0398, -0.672, 0.3762, 1.845, 0.9185, 0.108, -0.2964, -0.8374, 1.669, 1.927, -0.3474, 2.16, 0.02415, -0.806, -0.8545, 0.2744, 0.2227, -0.1542, 1.03, 0.809, 1.553, 0.817, -0.511, 0.269], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.01926, 1.797, 0.5513, 0.1594, -0.0687, -0.1226, 0.4949, -0.558, -0.2668, 0.562, 0.1543, -0.01878, 0.2617, 0.09283, 0.2211, -0.556, 0.6416, 0.56, 0.945, 0.09735, -1.31, -1.488, 0.8135, -0.899, 0.2502, -0.5747, -0.0267, -0.857, 0.221, 1.394, -2.01, -0.2756, 0.2866, -0.1653, -0.609, -0.869, 0.288, 1.098, 0.285, -0.2722, 0.10406, -1.849, -0.11035, 0.253, 0.167, 0.1545, 0.4136, -0.46, -0.1167, 0.183], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.403, 3.58, -0.0685, 0.313, 0.1214, -0.5864, -0.2527, -0.714, 0.47, 1.12, 0.631, 0.01724, -0.704, 0.1549, 2.678, -0.00677, 1.2, -0.1692, 1.477, -0.4963, 0.9497, -1.676, -0.4226, 1.408, 0.4429, -0.2573, -0.03784, 2.537, 0.05746, -2.213, 1.589, 0.5063, -1.231, -0.65, -0.09784, 3.012, -0.5547, -5.23, 2.674, -0.4915, -0.53, -0.4514, 0.0861, 0.97, 0.5786, 0.4414, 1.307, 0.9673, 0.6978, 0.2325], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8164, -0.9746, 0.142, -0.4575, 0.452, 0.5854, -2.63, -0.0528, 0.2283, 0.567, 0.5835, 0.02356, -0.06616, -0.2827, 2.914, -0.4714, 0.02893, 1.422, -0.624, -0.096, -0.3135, 0.557, -0.3792, -0.07623, 0.653, 0.2786, -0.0277, -1.233, -1.362, 0.162, -3.424, 0.007057, -1.555, 0.4548, -1.769, -2.473, -0.699, -0.403, 0.2898, 0.3962, -1.557, 1.589, -0.0909, 0.12213, -1.728, -0.5366, 0.672, 0.2622, -0.11066, 0.1644], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.066, 0.49, -0.351, 0.4944, -0.6113, -0.11224, 0.4233, 0.1, 0.318, -0.01631, 1.215, -0.003305, 0.05606, 0.921, -0.8804, -0.304, -0.2367, 0.8135, 0.9766, -0.2107, 0.334, 1.223, -0.2107, 0.7153, 1.384, -0.61, 0.0363, 1.945, -0.1942, 0.922, 1.615, -0.2542, 0.2969, 0.12286, 1.284, -0.8545, -0.2742, 0.777, 0.354, 0.1803, 0.09515, 0.4863, 0.5757, 0.001323, 0.10315, 0.8267, 1.095, 0.2693, -0.1794, -1.843], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.901, 2.576, -0.6943, -0.737, -1.002, 0.01237, -0.581, 0.434, 1.398, 0.404, 0.181, -0.03656, -0.492, -1.257, 0.857, 0.1464, 0.8955, -0.03738, -0.0994, -0.804, 0.746, -0.01152, 1.464, 3.248, -1.018, -0.1963, -0.02858, 1.762, -0.2954, 1.939, 0.3904, 0.2693, -0.506, 0.3237, 0.795, -0.4717, -0.7505, 0.3264, -0.314, 0.3025, 0.532, -0.7134, -0.704, -0.7656, -0.639, -0.3835, 0.8013, -0.3147, 0.4717, -0.00617], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1632, 0.6396, 0.4673, -0.2177, -0.0924, 0.2206, 0.7407, 0.4268, -0.975, 0.2141, 1.106, -0.03078, -0.129, 0.2223, 1.079, 0.2908, 0.3782, 0.2126, 0.003206, -0.2554, 0.01971, -0.5493, 0.3088, 1.173, 0.10236, -0.647, -0.02084, 1.859, 0.001744, 0.211, -1.054, 0.05847, 0.1925, 0.723, 0.1804, 1.357, -0.2146, 0.04654, 0.766, -0.224, 0.0428, -0.3398, -0.7783, 0.454, 0.6978, -0.558, 0.3457, -0.088, -0.4683, -0.266], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0529, -0.05905, 0.03047, 0.213, -0.04904, 0.1747, 0.5547, -0.2477, 0.541, -0.4983, 0.5303, -0.04153, -0.3015, -1.179, -3.574, -0.6733, -0.5522, -0.3574, -0.1421, 0.365, -0.1658, -0.7983, 0.528, 0.3428, -0.0652, -0.2311, 0.05118, 1.832, -0.001176, 0.824, -0.03102, 0.0635, 0.348, -0.39, -0.572, -1.06, -0.0904, -0.629, 0.344, -0.3694, -0.1216, 0.3042, 0.1292, 0.2805, 0.2393, 0.07324, 1.415, -0.04822, 0.2524, -0.2404], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.484, -0.467, 0.537, 0.0474, 0.12317, 0.4468, -0.3738, 0.555, -0.3223, -1.141, -0.1514, 0.02766, 0.3918, -0.1282, 0.04584, 0.04004, 0.10565, 0.7637, -0.476, 0.4836, -0.1683, -0.01804, 0.0819, 1.657, 0.985, 1.252, 0.003998, -1.598, -0.1843, 1.168, -1.169, 0.6123, -0.1938, -0.4402, -0.01113, -0.5444, -0.1545, -0.822, 0.3362, -0.2203, -0.5513, -0.902, -0.528, -0.1241, 0.4187, -0.01418, 0.4377, 1.011, -0.5176, 0.671], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5796, 2.719, -0.623, 0.2402, -0.5625, 0.0747, -0.1106, -1.953, 0.4055, -0.2961, 1.415, -0.01357, -0.276, 0.466, 1.21, 0.04797, 1.587, 0.4385, -0.05304, -0.3408, 0.712, -0.2712, -0.3462, 2.22, 1.847, -0.772, 0.0191, 1.082, -0.262, 0.829, -0.696, -0.3389, 0.773, -0.4797, -0.9243, 1.642, -0.105, -1.336, 0.4988, 0.497, -1.873, 1.233, 0.983, -0.3354, 0.6885, 0.529, -1.152, 1.304, -1.079, 1.404], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.756, -2.533, 0.6904, -0.2537, 0.1175, -0.53, -0.4077, -2.209, -0.0775, 0.6494, 0.7393, 0.004852, -0.4714, 0.3503, -1.349, -0.482, -1.594, -1.058, 1.268, 1.685, 0.1527, -2.066, -0.234, 0.6426, -0.05585, -1.035, 0.007595, -0.5103, -0.1567, -1.851, 2.342, 0.1393, 0.4531, 0.4268, 0.4443, -1.752, -0.2316, -1.22, -1.739, 0.0866, 1.149, 0.87, 0.4326, -1.119, -1.177, -0.0787, -0.7334, -1.19, -0.376, 0.3503], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.006306, -0.1582, -0.0834, -0.06696, -0.1497, -0.1055, 0.01293, -0.0758, -0.02876, -0.01595, 0.03702, -0.00853, 0.0702, 0.02184, -0.02502, -0.0918, -0.01672, -0.1416, -0.03055, 0.0895, -0.2659, -0.005352, 0.0598, 0.07385, -0.0957, -0.03577, 0.007935, 0.00572, 0.0747, 0.06183, 0.0112, 0.179, 0.02652, 0.03635, -0.251, 0.0554, 0.007412, -0.0369, -0.07074, -0.03065, -0.02148, 0.117, 0.07794, -0.1553, -0.09247, 0.05914, -0.0705, -0.12415, 0.04108, 0.02762], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.00829, 0.8154, 0.201, -0.535, -0.267, 0.03323, 0.622, 0.7314, 0.2854, -0.3225, -0.2384, 0.01135, -0.3694, 1.037, -1.83, -1.021, -0.8867, 0.7124, -0.6826, -0.566, 0.347, 0.283, -0.10394, 0.1804, 0.636, 0.1929, -0.04852, 1.432, 0.343, 1.515, 0.2634, 0.1265, -0.0671, -0.4146, 0.967, 1.091, -0.7383, 0.7656, 0.3188, 0.1412, 0.6035, 0.3555, -0.0998, 0.1144, -0.3152, 0.638, 0.5503, -0.573, -0.1841, 0.02066], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1069, -3.71, -0.5522, -0.612, 0.9937, -0.4434, -2.656, -1.255, -1.949, 0.0469, -1.437, 0.03848, -0.488, -1.181, 0.2986, -13.43, 3.338, -0.08856, -1.788, -2.688, -4.02, 1.399, -0.3428, -2.85, 0.2231, -0.548, 0.00425, -4.1, 0.64, 1.734, 2.102, -0.269, 0.4546, -2.467, -4.59, -8.37, 0.3313, -1.421, -2.97, -0.8364, -1.58, -1.799, 1.21, 0.3945, -0.5435, -0.66, -2.55, 0.329, -0.6567, 1.051], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0724, 0.5806, 0.2964, 0.2189, -0.258, -0.01743, -0.3943, -1.656, 0.03024, 0.013016, -3.541, -0.03595, 0.4287, -0.010925, -0.1903, 1.23, 1.099, -0.112, 0.919, -0.2656, 0.3433, 0.9697, 0.503, 1.035, -0.3489, 0.272, 0.00921, 2.982, 0.736, 1.137, 0.5054, 0.2024, 0.3499, -0.218, 0.6504, -2.441, -0.17, 0.7837, -0.8384, -0.3838, -0.4421, -0.506, -0.1364, -0.1422, 0.972, -0.2932, -3.172, -0.76, 0.2795, -0.5005], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.122, 0.426, -0.3164, -0.4343, -0.4941, 0.7314, -0.441, 0.02982, 0.7886, -0.2524, 0.6787, -0.0411, -0.539, -0.7017, 1.147, -0.483, 1.655, 0.2683, -0.834, -0.872, 0.1615, -0.6665, 0.7437, 2.512, 0.3242, -0.6216, 0.01677, -0.0916, 0.02127, 2.68, -0.3914, 0.42, -0.526, -0.1268, 0.2316, 0.2019, -0.513, 0.0986, 0.5376, 0.4133, 0.581, -0.1076, 0.09143, 0.1403, 0.02911, 0.2059, 0.589, -0.2325, 0.2815, 1.129], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.05865, -0.8066, -0.07654, 0.1826, 0.0983, -0.1317, 0.09625, -0.03105, 0.526, 0.7593, -0.542, 0.01971, 0.4192, -0.7593, -1.235, 0.069, 0.336, 0.007, 0.0644, -0.1608, -0.003174, -0.3865, 0.2852, -0.2842, 0.05548, 0.01017, -0.02711, -0.071, 0.00449, 0.4492, 0.0479, 0.1624, -0.3413, 0.07587, -0.2542, -1.782, 0.2418, 0.511, 0.01225, 0.1893, 0.5835, -0.1891, -0.0894, 0.3862, 0.0911, 0.03564, 0.012665, -0.2458, 0.3843, 0.2146], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.2406, -2.219, 0.2532, 0.1003, -0.2313, -0.7236, -0.1288, 0.458, 0.2432, 0.3252, 0.511, -0.007713, -0.924, 0.1818, 1.34, 0.6235, 0.7837, -0.2225, 0.04276, -0.04874, -0.2084, -0.1791, 0.22, 0.668, 0.2715, 0.08185, 0.01051, 0.693, 0.042, 0.806, -0.069, -0.06824, -0.53, 0.0908, 0.2328, 0.443, -0.621, 0.8984, -0.826, -0.0431, -0.03558, 0.1716, 0.253, 0.2122, 0.4482, 0.12256, 0.0302, 1.144, 0.2378, 0.3616], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.357, -3.88, -0.6133, -0.943, 0.3018, 0.10693, 0.985, -3.662, 0.01884, 0.855, -1.408, -0.04428, -0.691, -0.138, 1.805, -0.61, 0.0283, -1.304, -0.4114, 1.7295, 0.5215, -0.83, -1.168, -4.29, -1.579, -2.79, -0.00819, -1.733, 0.2703, -6.0, 1.61, 2.95, 0.768, 0.5186, 0.712, -3.371, 0.2415, -3.662, 2.59, -0.3096, -2.004, -0.3577, 0.002077, -0.2041, 0.05603, 0.654, -1.418, -0.283, 0.4258, -1.806], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.10565, -1.241, 0.0975, -0.07324, 0.1351, 0.6978, -0.312, 0.3389, 0.1609, -0.3088, -0.158, -0.01997, -0.2378, 0.5317, 0.12213, -0.06976, 0.5522, -1.17, -0.5576, 0.343, -0.2825, 0.0967, 0.203, 0.578, 0.394, 0.002821, 0.007217, -0.1092, -0.1001, 0.1704, -0.6865, -0.531, -0.3167, 0.07794, -1.267, -0.0881, 0.10315, -0.1907, -1.124, 0.2212, 0.002382, -0.721, 0.4053, -0.1736, 0.0936, 0.01249, -0.318, -1.399, 0.1266, -0.2292], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.05444, 0.03183, -0.004948, -0.04535, 0.00486, 0.02731, -0.003082, 0.03156, 0.01955, -0.0497, 0.02322, 0.02971, 0.0001464, -0.0051, 0.02011, -0.01017, -0.03366, 0.0228, -0.002024, -0.04916, -0.015564, -0.0472, 0.011604, 0.01846, -0.05545, -0.04663, -0.02658, -0.01457, -0.06256, 0.02135, 0.03053, -0.001487, -0.04562, 0.0001782, 0.04315, -0.02567, -0.05222, 0.0226, 0.02188, -0.006855, 0.015396, 0.01587, 0.000904, -0.05603, -0.0658, -0.04843, -0.02032, -0.0437, -0.00964, -0.03128], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.246, -1.901, 0.5186, 0.638, 0.9365, -0.981, -0.1826, -0.423, -0.891, -0.233, -0.7256, 0.01271, 0.3606, 0.617, -0.2837, 0.4307, -0.6504, 0.722, -0.701, -0.3179, -0.2908, 0.01442, -0.916, -0.4736, 0.6587, -0.1276, 0.0212, -3.742, 0.3528, -3.053, -0.25, 1.018, 0.3647, -0.2007, -0.7646, -0.507, 0.4558, -0.528, -0.1976, -0.6587, -0.592, 0.41, 0.0599, 0.5474, 0.03613, 0.313, -1.117, 0.5176, 0.239, 0.9375]] [-1.13694, -1.44306, -0.460143, -0.0907356, 0.241528, -0.192749, -0.630641, 0.83967, -1.39985, 0.082259, 0.644486, 0.346046, -1.37318, 1.91771, 1.3785, 1.09443, 1.95282, 0.144738, -2.01362, 0.333593, -0.0129631, 1.17558, 0.0723718, -1.05965, -0.980818, -3.80623, -2.06844, -3.40776, -1.97707, 0.542041, -2.08537, -2.55494, -1.27271, 1.88521, 0.417992, -1.00457, 4.05678, -1.40696, -1.27322, 0.00521946, -0.0646865, -0.114161, -0.786448, 1.2535, -1.50742, -0.242032, 1.32623, 0.192411, -0.0200379, -1.84077, -1.137, -1.443, -0.4602, -0.09076, 0.2416, -0.1927, -0.631, 0.84, -1.399, 0.0823, 0.6445, 0.346, -1.373, 1.918, 1.379, 1.095, 1.953, 0.1448, -2.014, 0.3335, -0.01296, 1.176, 0.0724, -1.06, -0.981, -3.807, -2.068, -3.408, -1.978, 0.542, -2.086, -2.555, -1.272, 1.885, 0.418, -1.005, 4.06, -1.407, -1.273, 0.00522, -0.0647, -0.11414, -0.7866, 1.254, -1.508, -0.2421, 1.326, 0.1924, -0.02003, -1.841] ReLU [[1.91712, 1.71162, -0.865643, -0.675245, 0.115941, 2.32312, 3.05575, -0.747302, 1.67603, 0.975563, 0.564508, -0.0432727, 0.183743, 1.14732, -0.697722, 0.0304389, 0.23617, 2.28116, 0.292969, 1.0325, 0.0052107, 0.150817, -0.296688, -0.734047, -0.970466, -1.02466, -1.95234, -0.302053, 2.16229, -0.413084, -0.191811, 1.05415, -0.877535, -0.535528, 1.53689, 3.56275, 1.68807, -0.663738, -1.15793, 0.0718926, 2.29661, 0.441948, 1.89711, 0.283074, 0.579396, 1.91301, 1.43407, 2.17167, -0.0212174, -0.132761, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.511885, -0.0767139, 0.491689, -0.0108316, 0.0897383, 0.974227, 0.378149, 0.0534572, 0.557518, 0.0204455, -0.180858, -0.110056, 0.193279, -0.0232134, -0.0913468, 0.0269763, -0.180257, -0.0521417, -0.566472, -0.702262, -0.021886, 0.0725328, -0.393673, -0.816566, -0.237276, 1.32254, -0.63123, 0.0403561, 0.537984, -0.307434, -0.345897, 0.178237, -0.247145, -0.0277611, 0.520469, 0.592441, -0.158881, 0.158281, 0.0784012, 0.198765, 1.08976, -0.205987, -0.394705, 0.0155505, -0.307528, 0.18805, -0.365387, -0.0860726, -0.000783143, -0.106214, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [2.15809, 1.43388, -1.70614, 0.490871, 0.619629, -0.761357, 3.0245, -0.460518, 0.471794, 0.811151, 2.80187, -0.716187, -0.709324, 0.831012, 1.55071, 0.309172, 0.414338, 1.88793, 0.0976581, 0.0923488, -0.0283241, 1.09326, 0.546906, 0.224145, 0.14408, 0.905952, 0.569351, 0.0685678, -0.0426106, 0.455127, -1.24424, -0.318337, 0.612047, -1.6823, -0.582092, 0.525577, -0.158654, -1.00207, 0.293126, 0.0275447, 1.13869, 0.113317, 0.837703, -0.128874, -0.0143548, 1.94327, 0.919907, -1.36505, -0.0302694, -3.55898, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-10.7355, -2.7117, 1.80391, 0.704075, -1.51594, 0.414581, -5.72295, 0.269293, -2.23951, 0.698959, -4.19903, 0.498813, -0.880595, 1.76379, -3.53834, -2.90121, -0.653859, -5.0771, -6.43003, 2.18339, -0.0239953, -1.00178, -4.36339, 0.622437, -1.0414, 0.835835, -0.984032, -5.48161, 0.464009, 2.22127, -4.91612, -5.92431, -0.549394, -8.9769, 1.6629, -3.34649, 0.477715, -7.60442, -3.68671, -0.0460745, -7.38571, -6.35704, -1.17726, -0.848007, -1.71212, -0.843698, 0.179575, -2.11558, 0.0436363, -1.45966, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.552737, 0.13978, -0.259721, 0.0640417, 0.126201, -0.631158, 1.07787, -0.162214, 0.953216, -0.413434, -0.376972, 0.369627, -0.521863, 0.330081, 0.284313, 0.302964, 0.115025, 0.520219, -0.0332342, 0.19487, 0.00844482, 0.0918271, -0.135156, 0.0598809, -0.141126, 0.393872, 0.16736, -0.399845, 0.188245, 0.169207, -0.177598, -0.106557, 0.0283852, -0.259799, 0.291491, 0.701346, -0.110449, -0.583393, -0.0382966, -0.0871158, 0.0184207, -0.140817, -0.370554, 0.171824, 0.504698, 1.7089, -0.0915694, 0.408827, 0.0348522, -0.684088, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.678645, 0.320827, -0.0329934, 0.0206529, -0.800709, -0.3005, 0.297557, 0.000602132, 0.209416, 0.11998, -0.0518605, 0.104073, -0.11021, -0.109815, 0.137246, 0.342793, 0.0420746, -0.689631, -0.065184, 0.0591423, 0.0188984, -0.138839, -0.32296, 0.131949, -0.286667, 0.482397, -0.2337, 0.200393, 0.257033, 0.393775, -0.345341, 0.103059, 0.179499, -0.517728, -0.346749, -0.219303, -0.0748764, 0.37663, -0.764253, 0.326106, -0.097163, -0.460619, -0.163553, 0.126914, -0.60604, -0.0083236, 0.161305, -0.0711626, 0.0258663, -0.176122, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.154423, -0.184876, 0.676482, -0.518649, -0.226214, 1.6974, 2.14903, -0.115889, 1.34666, -0.311675, -0.325693, -0.0259666, -2.60941, 0.118797, 0.00855245, 0.0539266, -0.143575, -0.68242, -1.79669, -0.365907, 0.0345975, 0.0534712, 0.222552, -0.973017, 0.946482, 1.80979, -0.675757, 0.683928, 0.908395, -0.763, 1.24009, -1.04741, 0.37122, -0.265263, 0.28091, 0.707673, 0.204208, 0.0842126, 0.0359913, 0.0578004, 1.57185, 0.361434, 2.13398, -0.205666, -0.850041, 0.971494, 0.165585, 0.376338, 0.0274625, 0.484636, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.421618, -0.577935, -2.57969, 0.159878, -1.72743, -1.18363, -0.0528655, 0.184875, -0.105082, -1.44534, -1.27054, 0.147633, -0.187499, 0.472118, 0.153236, -0.581519, 0.2734, -0.533803, 0.356548, 0.935337, -0.0434167, -0.0924407, 0.504217, -0.149616, -1.26756, 0.796002, -0.894053, -1.56002, -0.57756, -0.271953, 0.934183, -0.536031, -2.15551, 1.745, -0.14105, -2.20062, 0.215269, -1.48737, 0.0649911, 0.00285381, -1.27889, -0.715458, 1.46693, -1.19699, 0.408613, -5.31594, -0.0418879, -2.87653, 0.0250052, 0.0617122, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.514072, 0.327233, -0.00981564, -0.116392, 0.504435, -0.745757, -0.162663, -0.133179, -0.534504, -0.349923, -0.0624029, -0.26671, -1.12464, 0.212271, 0.522141, 0.333069, 0.269884, 0.411604, 0.295257, 0.15998, -0.0434317, 0.0522157, -0.101218, -0.16441, -0.110891, 0.507246, 0.0949839, -0.497723, 0.586129, 0.128865, 0.0895804, -0.244465, 0.4655, -1.96421, 0.740496, -0.389826, -0.0521907, -0.536302, 0.187216, 0.0376125, -0.251669, 0.0645537, 0.496586, 0.447798, 0.825577, 0.961549, -0.437757, 0.168252, 0.015049, -0.062453, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.25903, -4.35994, -0.0242797, 0.00122929, -0.988552, 0.0179451, 2.04668, 0.165142, -1.30936, 0.237697, -1.74057, -0.47532, -0.193784, -0.634988, -0.149848, -1.04578, 0.54523, -1.72987, 0.420936, -0.328957, 0.0389816, -0.239948, -0.268676, -0.534677, -0.893524, -1.18489, -1.21558, -0.907032, 1.29602, 0.0977193, 0.228051, -0.062076, 0.382351, 0.244349, -0.43492, -1.02728, -0.514502, -0.167342, -0.12987, 0.00945495, -0.827564, -1.84606, -1.83094, -0.294193, 1.37959, -2.63303, 0.590345, -0.784309, -0.037683, -0.418117, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0127623, 1.05367, -0.224202, 0.0880751, -0.985404, -0.692736, -0.558033, 0.199422, -0.237565, -0.959567, 0.554293, 0.834746, -1.06609, -0.0854266, -0.0574848, -0.674232, 0.179759, -0.95015, 0.0426577, 0.328533, 0.0419038, -0.110795, 0.15657, 0.317776, -0.113263, -2.78285, -0.983517, -0.23402, -1.02372, 0.304592, -3.4675, 0.440216, -0.211656, 0.553338, -0.283765, -1.84443, 0.499184, -1.00219, -1.33203, 0.00675693, -3.51345, 0.368218, 0.395715, -1.11827, -3.00483, -1.17875, 0.301781, -1.74068, -0.0281057, -0.454104, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.333629, -0.134096, 0.0510493, -0.110478, -0.2409, 0.291257, -0.295583, -0.0124777, 1.06057, 0.121604, 0.413187, -0.0575497, -0.128701, -0.300497, 0.278075, -0.0867591, 0.208179, 0.0960076, -0.655412, 0.0516505, 0.0340488, 0.188721, -0.908219, 0.0378959, -0.345057, 0.703942, -0.33609, 0.810449, 0.631295, -0.174017, -0.839905, -0.342376, 0.499504, -0.764807, -0.39025, 0.303579, 0.127894, -0.0856524, 0.131001, 0.0797702, -0.166391, 0.0551976, -0.802472, 0.105714, 0.0393627, 1.45538, 0.324215, -0.200576, 0.0050708, -0.0582809, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.633388, 1.18574, -0.536048, -0.0367929, 0.825529, 0.731993, -0.165754, -0.261811, -0.919853, -0.368611, 0.626913, 0.186512, -0.473765, -0.144225, -0.156459, 0.246941, -0.0566372, 0.266293, -0.655531, -0.10602, 0.0360664, 0.0810416, -0.412147, 0.421756, 0.0205085, 0.821387, 0.193235, -0.538725, -0.00545372, -0.448016, -0.116526, 0.31939, 0.602741, -0.563266, 0.312381, -0.173902, 0.659759, -0.735931, 0.403339, 0.0813476, 0.432647, -0.278227, -0.955094, -0.027798, -0.122885, 0.58645, -0.0611259, 0.614879, -0.0069432, 0.52531, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.501689, 0.428264, -1.8517, 0.0790751, -1.59471, -4.73294, -0.995209, -0.195087, -2.58104, 0.151301, -0.861892, -0.41962, 0.0884628, -0.0834321, 0.115524, 0.0419715, -1.4353, -4.64687, 0.402835, 0.467766, 0.0198912, -2.18622, -1.41894, 0.269951, -0.00511751, -0.9988, -2.89426, 0.0991447, -2.45378, 0.101561, 0.228963, -1.21439, -4.13197, 0.0623575, -0.403075, -0.086739, 0.334211, -0.355396, -0.501651, 0.0572387, -0.334952, -2.63386, -4.44855, -0.0725033, -2.63508, -1.36703, 0.190635, -0.415348, -0.020003, -0.959318, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.06666, -0.00138137, 0.259013, 0.185393, 0.42114, 0.735207, 1.56337, -0.317628, 0.157875, -0.140705, -0.0264516, -0.0405823, -0.483974, 0.0262971, 0.166615, 0.171001, -0.22016, -0.0492614, 0.179707, -0.114736, -0.0137644, 0.100879, 0.642598, -0.0649007, 0.716152, 0.0432913, 0.102389, 0.474268, 0.129447, -0.387093, -0.409192, -0.336681, 0.243377, -0.247517, -0.314925, 1.59852, 0.52025, 0.0548716, 0.234407, -0.0491135, -1.00914, -0.4633, -0.631077, 0.662509, -0.550906, -1.5312, 0.114553, 1.07295, -0.0354227, -0.106565, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-3.42461, 0.145398, -0.166352, -0.479109, 0.58619, -4.26314, -6.22248, 0.197141, -1.62099, -1.50533, -6.12655, -0.929334, -0.121396, 0.318499, 1.53963, -0.476752, -1.02618, -2.13584, 0.204332, -0.618249, 0.0299843, 0.402251, 0.329847, -0.658481, 0.00739732, -1.72248, -1.54722, -0.537421, -2.39717, 0.228401, -2.13451, -2.74056, 0.465607, -0.274214, 0.310293, -5.72711, -0.596145, 0.15236, -1.54746, -0.0444491, 1.43683, -2.99107, -5.32851, 1.14701, -3.11924, -7.29255, 2.14531, -0.181313, 0.00976695, -0.735231, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0312858, -0.189998, 0.206731, -0.0168996, -0.314712, -0.60103, 0.363858, -0.117104, 0.566539, 0.0853194, -0.564412, -0.110615, -0.0196459, -0.0166243, -0.0587605, 0.117953, -0.115682, -0.315487, 0.800873, -0.106791, -0.00110899, -0.0159747, 0.424374, -0.421534, -0.110642, -0.448161, -0.49785, 0.26553, -0.395676, 0.0492655, 0.35118, 0.0168678, -0.648119, -0.0653526, -0.218361, 0.978838, 0.289934, 0.223694, -0.18991, -0.0614019, 0.241294, 0.012051, 0.0411264, 0.0763655, -0.14855, 0.798905, 0.199827, -0.40519, -0.0153657, 0.0585707, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.20229, 0.150965, 0.393742, -0.157481, 0.703598, 0.061929, -0.0958538, -0.16509, 2.1833, 0.269137, -2.05737, -1.29966, 0.969014, 0.469707, -0.707684, 0.118814, -0.440834, 0.130534, 0.426366, 0.227163, 0.0192284, -0.0634732, 1.25228, 0.617602, -0.954509, -0.891125, 0.353045, -0.364344, 0.669082, -0.022483, -0.219272, -0.284838, 2.04686, -3.18259, 0.368327, 2.0564, 0.331647, -0.0454942, -0.510217, 0.0746629, 0.722942, -0.21508, 1.2932, 0.00892973, 0.33864, 1.49436, 0.0705549, 0.505335, 0.0164396, 1.02629, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.332287, -0.0535548, -0.321523, -0.0272509, -0.310716, -0.370799, -0.423994, -0.0973717, -0.359633, -0.138224, 0.322568, -0.217488, 0.157781, 0.132792, 0.0517267, 0.0544634, 0.056331, -0.0885758, 0.252928, -0.218829, 0.0343139, -0.00647533, -0.226071, 0.00280077, -0.0309699, -0.231365, 0.317673, 0.00763083, 0.189551, 0.0268982, -0.0498405, -0.0973081, 0.238955, -0.13083, -0.0750735, 0.292524, 0.4104, 0.128405, 0.0761928, 0.251511, 0.480047, -0.184331, 0.0374049, 0.369565, -0.382634, -0.142326, 0.010095, -0.302128, -0.0275802, 0.175322, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.826842, 2.98769, 1.74675, -0.398763, 0.889264, 2.3168, 3.81331, -0.672105, 2.05499, -0.61313, 2.87353, -0.042223, 1.16475, 2.30289, 0.537443, 1.31919, 0.260084, -4.7967, 1.35878, 2.69035, -0.0224819, 1.35689, 3.35947, -1.21891, -1.16432, 2.55645, 1.79308, 2.96198, -1.53845, 2.11829, 1.36533, 4.31415, 0.421217, -1.76249, 2.14783, 4.33867, 0.120958, -1.19661, -1.04992, 0.00262566, 4.66828, 1.04306, -0.619637, -1.53328, 1.40752, 0.958499, -0.0566043, 0.0954647, -0.0293897, -1.40567, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.132304, 0.242379, -0.620396, -0.483752, 1.70543, 2.33056, 3.42543, -0.54799, 2.33107, 0.00386605, -3.36514, 0.0596789, 0.485138, -0.862918, -0.642043, -0.930825, 0.586046, 0.288891, -0.334595, 0.77451, 0.0239161, 0.762076, -0.592911, 0.00114896, 0.179033, -0.0159361, -0.193175, 0.803423, 0.366085, 1.02254, 0.240719, -0.250938, -1.14406, -1.50733, 1.80845, -0.266419, 0.608748, 2.36271, 2.19127, 0.0665568, 1.50208, 0.564936, 1.31454, -0.2381, 1.99219, 3.59141, -0.0171759, 1.8582, -0.0346115, -0.115635, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.024051, 0.118412, -0.560764, 0.0723003, -0.0991343, 0.14212, 0.109928, -0.182503, 0.103564, 0.416107, 0.736439, 0.438152, 0.0420692, 0.32384, -0.0934079, 0.080456, -0.0517526, -0.0967182, 0.0388146, -0.0441661, 0.0257788, -0.12309, 0.312738, 0.3013, 0.161526, 0.0834254, -0.0938487, 0.232697, 0.0974572, -0.184441, -0.106618, 0.350473, 0.276201, -0.0599967, 0.0722878, 1.11315, 0.290759, 0.151777, 0.125921, -0.0568421, 0.731155, 0.026802, 0.13536, -1.15777, 0.00302849, 0.043818, 0.115833, -0.0218743, -0.0314066, 0.210947, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.235692, 0.0996545, 0.0648054, -0.102595, -0.277918, -0.2415, -0.0144835, 0.0075418, 0.377218, 0.0200296, 0.60864, -0.311493, 0.0961392, -0.974341, -0.0771421, 0.0707816, -0.0314403, -0.316013, -0.208247, -0.0717996, -0.00610772, -0.189746, 0.205266, -0.0201452, 0.136382, 0.507522, 0.289519, -0.552322, 0.0890912, 0.0129174, 0.100449, -0.87412, 0.0490558, -0.666659, -0.186977, -0.255366, 0.214103, -0.0207163, 0.227192, 0.0276348, 0.236468, -0.273472, 0.837772, -0.0557081, -0.211265, 0.000850257, -0.242358, -0.0364585, -0.0199523, -0.113188, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.438543, 0.379397, 0.358304, -0.0773801, -0.366158, 0.0490463, 0.686302, 0.0225138, 0.340097, -0.530462, 0.173969, -0.0348445, -0.013868, 0.215796, 0.156245, 0.26339, 0.103678, -0.557911, -0.602355, 0.19108, -0.0319093, 0.034938, -0.119517, -0.496942, -0.486192, 0.403654, -0.222121, 0.282228, 0.59265, 0.0654504, 0.170625, -0.723298, 0.293512, 0.103814, -0.362937, 0.38495, 0.0220563, -0.165686, -0.304847, 0.00335465, 0.830609, 0.148706, -0.179289, -0.223589, -0.199016, 0.725526, 0.0766948, 0.0418838, -0.0131586, -0.221591, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.02514, -0.00147425, 0.819559, -0.188289, 0.251381, -1.40641, -0.134107, 0.0197203, 0.18866, -0.0377162, -1.36462, -0.049471, -0.0124661, 0.408771, -0.448087, 0.0150934, -0.503457, 0.632273, -0.0855894, -0.834034, -0.00577917, -0.150065, 1.01127, -0.256626, -0.0641272, -0.238138, -1.55339, 0.264853, -0.903478, -0.67357, 0.471612, -0.364006, 0.39642, 0.162383, -0.332569, 0.507864, 0.303014, -0.134571, -0.0622213, 0.0388267, -2.01987, 0.122426, 0.64298, 0.0499628, 0.144692, -2.33893, 0.291967, 0.248189, -0.0424526, 0.183213, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.19524, 1.25074, -1.60454, 0.167853, 2.47896, 1.75434, -1.10612, -0.0898483, 0.0267287, -3.56518, 2.06019, 0.27837, -0.889831, 0.783546, 0.684408, 0.275141, -0.134263, -1.58225, 0.723689, 0.258237, 0.0358474, -0.389908, 0.0452969, -1.61825, -1.26175, -2.56158, -5.83188, -0.234059, -0.45978, -0.948524, -0.503194, -0.740925, 1.79708, -0.802708, -1.55122, 2.88848, 0.0855585, -0.203855, 0.16253, -0.0173154, -1.24526, 0.00333169, -0.347336, 0.646906, -0.0661931, -0.87145, 0.430522, 0.0615745, -0.0462951, 0.813804, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.396811, -0.224406, -0.899274, -0.195209, 0.802173, -2.1913, -2.03764, 0.104574, -1.69013, 0.261342, -0.976442, -0.121631, 0.927417, -0.864794, -0.981916, -0.335791, 0.0871111, -0.588874, 0.261057, -0.120918, 0.01083, -0.252138, -0.33334, 0.83345, -0.245787, -0.768666, 0.190394, -0.0126325, 0.0374215, 1.09515, -0.548997, 0.802324, 1.77733, -0.0253681, -0.191419, -1.21135, -0.530847, 1.03401, -0.788644, -0.017306, -0.448833, -0.0494631, 0.400144, -0.317647, -0.578369, 1.20942, 0.166916, -0.435287, -0.0364604, 0.063089, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.0861, 1.31345, -0.688635, -0.222775, 1.36332, -1.30729, 0.358346, -0.0501927, 0.157224, -0.344743, 0.328955, -0.163658, 0.561576, -0.560357, 1.93429, 0.667374, 0.0705984, -1.25166, 1.11659, 0.0947537, 0.00102608, -0.819772, -1.67931, -1.1809, -1.12206, -0.523163, -0.236623, 1.04603, 1.34674, -0.242429, -0.0460118, -0.798652, 0.398762, -2.53205, -0.523379, 0.782301, 0.290683, 1.93613, -0.243884, -0.00341457, -0.0865853, -0.797451, -0.28323, 0.663569, 0.483375, 1.59037, 0.0689928, -0.468233, 0.0109797, -0.402003, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.00617666, -0.00626907, -0.0364087, -0.033766, -0.0420393, -0.0173827, -0.0251857, -0.0265295, 0.00369311, 0.0205826, -0.00826092, -0.0405211, -0.0296416, 0.0037617, -0.0222573, -0.0215694, -0.0364583, -0.0430819, 0.0204683, 0.0181259, 0.0482162, 0.00835882, -0.016463, 0.0143153, -0.0109554, -0.015299, -0.0394956, -0.0128708, 0.0372357, 0.0161543, -0.0171729, -0.00234245, 0.0262538, 0.0375109, -0.0364627, 0.0170497, -0.0342193, -0.0145733, 0.0014113, -0.00196946, -0.0290391, 0.0186284, 0.00284599, -0.0316734, -0.0449425, -0.0139637, -0.0165479, 0.00591352, 0.0413902, -0.0100204, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-3.8171, -8.82756, -3.47401, 0.159373, 1.82747, -3.54952, 0.905804, 0.734157, -8.94325, -2.97076, -13.0414, -4.75728, 1.65942, -1.76639, -2.23584, 0.510225, -0.895899, -0.864878, -1.6592, 1.06701, 0.0237621, -0.721575, -1.89576, -1.70837, -1.61175, -8.8923, -6.83752, -4.18233, -4.74016, -0.672735, -5.52467, 1.11037, -3.79067, -4.61597, 0.318559, -8.57426, -1.43702, -10.499, -2.38969, -0.0639587, -0.0288864, -5.83034, -4.57014, -0.491869, 1.03637, -13.0836, -4.07073, -0.858079, -0.044583, -0.953208, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.336489, 0.470317, 1.12115, -0.110559, 0.172742, 0.663962, 0.717662, 0.00207668, 1.87062, 0.0966886, 0.927672, 0.147204, -0.180531, 0.628024, -0.382055, -0.0942685, 0.171731, 0.550981, 0.293362, 0.41302, 0.0432035, 0.670419, 1.00073, 0.168903, 0.105111, 0.992534, 0.158492, 0.498977, 0.39512, 0.484066, 0.149968, 1.10138, 0.436477, 0.259648, 0.757776, 2.38998, 0.531197, 0.204843, 0.889504, 0.0559832, -0.0524716, 0.78483, 0.9652, -0.612299, 0.00635633, 0.445725, 0.5117, 1.09911, -0.0324919, 0.430204, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.664628, 0.508629, -0.399036, -0.265941, -0.383114, 0.329273, 0.597569, -0.122218, -0.0317256, -0.0888315, 0.00982428, 0.438555, -0.60241, 0.164894, 0.0454583, -0.313243, -0.238712, 0.630362, 0.320989, -0.0497018, -0.00770173, -0.222201, 0.00806423, -0.274415, -0.669787, 0.86598, -0.191612, 0.657269, 0.0662044, 0.0362145, 0.626445, 0.54692, 0.908383, -0.598341, 0.46131, 0.924829, 0.421478, 0.450122, -0.547269, 0.0461089, 0.0360318, -0.518128, -0.765577, -0.0670621, 0.540337, -0.16555, 0.3016, 1.34515, 0.0356433, 0.491279, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.650161, 0.181347, 0.0271655, -0.054744, -0.124775, -0.175194, 0.934573, -0.22091, 1.04258, -0.154343, 0.306732, 0.0565732, -0.20738, 0.115912, 0.114182, 0.200939, 0.193945, -0.170099, -0.475163, 0.169361, 0.0354498, -0.0728376, -0.274711, -0.407099, -0.123224, 0.106888, -0.237148, 0.495832, 0.353033, 0.110958, 0.150733, 0.177381, -0.203811, -0.231482, -0.0913728, 1.36505, 0.497377, 0.232687, 0.147419, -0.057873, 0.976346, 0.146604, -0.464932, 0.13809, -0.0995222, 0.389619, -0.0439576, -0.383882, 0.0130817, 0.478197, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.71966, 0.437323, 1.5435, 0.234833, 0.606325, 0.382558, 3.209, -0.484546, 0.88344, -1.64797, 1.1776, 0.730343, -0.0620317, 0.981793, 0.754917, 0.754142, 0.358443, -1.92046, 0.0262496, 1.02511, -0.00655277, -0.323363, 1.11758, -0.308324, -0.369623, 0.64024, 1.36653, 2.30861, 1.3116, 0.420355, 0.907235, 0.195808, 0.226531, -2.60767, 1.36523, 3.78456, -0.0955614, 1.123, 0.388804, -0.0171665, 0.94292, 0.336499, 1.26241, 0.192017, 1.73986, -0.289057, 0.392934, 0.0972322, -0.0229843, -1.52806, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.12822, -4.61335, 0.334411, -0.223552, -0.533639, 0.237696, -4.22561, -0.0369685, 1.31524, -2.80042, 1.77855, 0.539336, -1.20894, -0.130237, 0.0369446, -0.237485, -0.134144, 1.40924, -6.05523, -0.423303, 0.00637672, 0.912645, -2.09701, -1.71502, -0.363672, -7.25835, 1.88759, 0.346979, -4.63624, -0.10238, -0.994474, -0.345391, -0.819466, -0.622513, 0.550018, -0.0685538, 0.539643, 1.80407, -0.51752, 0.00786489, 1.18734, -0.0389075, 0.611614, -0.821523, 2.18883, -0.655104, 0.562751, 0.0965078, -0.0294369, -0.0252464, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.541082, -0.0574228, -0.498636, -0.271276, 0.0412878, -1.30808, 1.99276, 0.0258941, -0.274217, -0.0340979, 0.20175, 0.514585, -0.404963, 0.033708, 0.026217, -0.0490579, 0.462941, -0.76646, 1.05147, 0.739627, 0.0128172, -0.0508563, -0.37103, -0.477017, -0.408518, -1.05894, 0.0636573, 1.32278, 0.462368, 0.636759, -0.178947, 0.564367, -0.681844, -0.270084, -1.17195, -1.5698, 0.649325, 0.81723, -1.99037, -0.0162347, -2.70606, -0.343818, -1.02138, -0.740587, 0.484682, -0.0801058, 0.265655, -0.485425, -0.0195206, -0.426221, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.508212, 1.1464, 2.32947, -0.473903, 2.19511, 1.40564, 1.69702, -0.224658, 1.80718, -0.268146, -1.89817, -0.935125, 0.590961, 0.821486, -0.911711, 0.62626, 0.149034, -1.14198, 1.21882, 0.68591, 0.0480892, -0.289662, 0.492446, -0.598976, 0.278667, -2.15104, 0.175778, 0.797284, 1.02212, -1.14863, -0.199179, -0.464598, -0.294116, 0.37971, -0.943043, 1.38938, 0.478286, 0.41418, 0.10092, -0.0516024, 2.17457, 0.724207, 0.331201, 0.14082, -0.182164, 0.760291, 1.09014, 0.64034, -0.0318314, 0.245731, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.93351, -0.26478, -1.50677, -0.0762895, 1.48221, -0.471432, -1.7039, 0.186494, -0.631412, -2.56819, -0.0150673, 1.02278, -0.463305, 0.462328, 0.179834, 0.865842, -0.0159018, 0.846736, -2.01613, 0.0741399, -0.0313217, -0.220396, -0.364432, -1.20149, 0.520672, -0.957294, -1.5062, 0.320809, 0.0531439, -0.459631, -0.788573, -1.23157, 0.631036, -0.72682, -1.76117, 0.198421, -0.406299, -0.285017, 0.642325, -0.0537078, -1.05429, -0.103756, 0.43556, 1.53806, -0.430252, -1.58501, -0.361288, -0.644875, 0.0335687, 0.296034, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.143234, 0.805157, -3.43675, -0.256007, -0.684648, 0.322951, -6.63001, 0.0994218, -2.03302, -2.22722, -3.27212, 0.63611, -0.427303, 0.338124, 0.583842, -0.209801, 0.585102, -1.46159, -0.364896, 0.79232, -0.0365294, 0.223671, 0.868018, 0.259206, -1.92537, -5.25459, -0.870115, 0.885208, 1.62484, -3.04068, -2.93796, -0.796098, -0.873136, 0.465928, -1.93092, -3.7572, 0.0448381, 0.3741, -0.371281, 0.0347686, -0.693255, -2.47542, -6.09506, -0.473078, -1.6278, -1.01258, 0.269942, -0.989684, -0.0107711, 1.01346, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [2.56769, 0.744101, 0.989803, 0.0707506, -0.520404, 2.94337, 1.52542, -0.436462, -0.152241, 0.473186, 2.30593, 0.601026, -0.294752, 1.6882, -1.80861, 0.12187, 1.06868, 1.03169, -0.521453, 2.39687, 0.0271559, 0.591481, 1.39257, -0.114476, 0.949464, 0.619214, 1.1171, 0.777771, 1.02623, 0.878573, 0.700519, 1.49759, 0.803343, -5.67363, -0.919278, 4.59986, -3.4536, 3.80278, 1.14795, 0.08343, 1.9374, 1.92968, 1.3674, -0.324621, 1.08074, 1.82274, 0.230967, 4.50858, 0.00230818, -4.87846, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-2.62122, -1.67697, -2.86036, 0.480993, -3.23796, -0.774589, -8.37259, -0.129986, -1.82142, -0.0607685, 0.300123, -0.187689, 0.233994, -0.0528228, -1.91802, -1.24263, -0.539895, -0.261955, -0.104127, -0.381465, -0.00168384, 0.439824, 0.271703, 0.796839, 0.665268, -1.10783, 1.13961, 0.839985, 0.257796, -0.906412, -0.411282, -1.36393, -1.26215, 2.22821, -0.111279, 1.32085, 1.26886, -1.11578, -0.284895, -0.00708048, 0.782819, -0.47918, 0.605261, -0.484601, -8.74234, -0.223438, -0.654625, 0.332457, -0.0114348, -0.268094, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.737548, -0.369773, -0.434994, -0.00732519, 0.892852, -0.79207, -2.6346, 0.361574, -0.253152, -1.8007, 0.774046, 0.316907, -0.0881974, -0.0740688, 1.53028, 0.552037, 0.116041, -0.377559, 0.439152, 0.21733, -0.0150386, -1.00063, -1.1742, -1.71331, -2.05431, -5.49996, 0.86411, -0.273745, -0.97708, -0.69289, -0.167838, -1.07094, -2.27169, -0.247436, -2.86493, -2.41488, 0.0187518, 0.448256, -0.385792, -0.119733, -1.60489, -2.48982, -5.22746, -1.08503, -0.939354, 0.643298, -0.238835, -2.48517, 0.00434891, -0.745752, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.887993, 1.35304, -2.0372, -0.351248, -1.89712, -2.27889, -1.00346, 0.338931, -6.4065, 1.81178, -4.82734, -2.89919, 4.31782, -0.523837, -0.490207, -2.10909, 0.249502, 0.742935, -5.27501, 0.0152689, -0.0383177, -0.213618, -1.51338, -1.10458, 0.33724, -4.00357, -0.500083, -4.26617, -5.47747, -0.31178, -8.51335, -5.16476, -4.23693, 1.11972, 1.02968, -7.32771, -0.25778, -3.72624, -4.78895, -0.0334224, 1.29404, 1.33438, -1.8207, -0.35076, 1.10421, -5.20823, 0.912287, -0.664811, 0.0241254, -2.19034, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.2159, -0.497496, -2.77635, -0.100781, 1.24434, -0.882615, 0.319811, 0.241552, -2.13253, -2.44541, -1.57685, 0.0476498, 0.124343, 0.353094, 0.381108, 0.645647, 0.230561, -0.206339, -0.3218, -0.0740437, -0.00212909, -0.344081, -0.737089, -1.23983, -0.536651, -1.61429, -1.63248, -1.34848, -0.444604, -1.38086, 0.288191, -0.34087, -1.97843, 0.000137315, -1.9814, 0.0793025, 0.200219, -0.808826, 0.206289, -0.0540589, -0.191055, 0.14805, 0.76055, -0.0341562, -2.34695, -0.447044, 0.248762, -0.595182, -0.0441508, -0.286075, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.399186, 2.69237, 3.90135, 0.0765419, -1.6987, 0.0298567, 1.47378, -1.24091, 3.73473, 0.748788, 3.13239, -1.59199, 0.760351, 0.458254, 2.00967, -0.476311, 0.641691, 2.58396, 0.253238, 2.14008, -0.00557312, 0.480056, -0.489584, 0.241186, -0.556425, 4.13503, 0.560299, 0.936778, 0.406733, 2.65752, 2.33011, 2.98882, 3.016, -2.92358, -2.32449, -1.775, 2.3066, -3.86118, 1.75869, -0.0417082, 1.58795, 2.29032, 0.892855, -0.340113, 0.440077, 1.53466, 1.47796, -0.435286, 0.00234656, -0.352568, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.05023, -0.580693, 0.766014, -0.782152, 3.3483, 1.04234, 1.01239, -0.429834, 0.176673, -0.152083, 2.54015, -0.25205, 0.105111, -1.1695, 1.51777, -0.0411696, -0.591313, 1.80215, 0.371952, 0.0718412, -0.0417704, 0.0322501, 0.303579, -1.30516, -0.0795092, 1.8509, 0.187329, 0.0233616, -0.156261, -0.863168, -1.13653, 2.02608, -0.0883863, -3.79393, 1.03553, 4.00753, 0.5675, 3.06878, -1.1049, 0.122296, -1.07553, -0.818809, 0.15298, 1.06571, -2.05583, 1.15742, 1.38218, 1.26986, 0.036645, 1.98061, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.481297, 0.133977, -0.497157, 0.0299331, -0.364031, -0.620503, -1.93325, -0.0349921, 1.21408, -0.849517, -1.59409, -0.146117, 0.160829, -0.0778031, -0.172807, -0.0379369, 0.0176435, -0.187005, 0.197025, -0.157459, 0.0356228, -0.069798, 0.069154, 0.0517078, 0.252481, 0.315408, -0.183811, -0.488509, -0.673494, -0.144855, 0.13437, -0.303346, -0.237923, 0.181182, -0.66149, 0.655801, 0.863319, -0.227904, 0.22541, -0.0840926, -0.203309, 0.05607, -0.49629, -0.524626, -1.2011, -0.405481, -0.0595285, -1.38604, 0.0146923, -0.421471, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.807671, -0.965712, 0.576834, -0.538454, 0.508279, 0.207324, -0.265654, -0.291125, 0.546935, 0.490871, 0.830914, -0.203819, 1.50337, 0.101228, 0.664359, -0.252667, 0.263581, -0.171374, 0.266583, 0.733759, 0.0175978, 0.224798, 0.232579, -0.643046, 0.476411, -1.00198, -1.60174, 0.667806, 1.54203, 0.195639, 0.276368, -0.850228, 1.05409, -0.687725, 0.45548, 0.121774, -0.11682, 0.508349, 0.115207, 0.055741, -0.832324, 0.086683, -0.262984, 0.568829, 0.692504, 1.34025, -0.761174, 1.26134, -0.0157362, 1.05428, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-2.22863, -2.68154, -9.4645, 1.99582, -2.60804, -3.80318, -3.75667, 0.361697, -0.642802, -4.501, -3.21963, -1.70966, -1.82915, -3.76644, -5.70789, -4.36876, -0.723356, -1.78269, 1.04735, -1.77779, -0.0127646, -3.21105, -1.24122, 1.14503, -0.0864939, -0.513903, 1.57612, -3.75914, -1.87035, -2.60641, 0.943033, -8.34706, -3.16288, 4.32521, -3.57267, -0.307046, -1.63156, -3.28743, -2.81827, -0.0260408, -0.451872, -10.8739, -1.25341, -3.77436, -0.235106, -7.36822, -0.406326, -3.42473, 0.0329931, -0.733651, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.876422, -1.5178, 0.947764, -0.189072, -0.170776, -1.7697, 1.17711, -0.214164, 2.07722, -0.213864, 2.30325, -0.0470967, 0.170056, 0.279734, -0.0108658, 0.272024, -0.243922, 0.809523, -0.532046, 0.163675, 0.0166525, 0.271867, 0.639669, -0.126689, -0.253285, 1.08108, -3.01555, 0.623307, -1.57968, -0.180409, -0.27128, 0.161183, 0.190635, -0.875921, -0.539196, 2.53405, 0.0526957, -2.45461, -0.202574, -0.0419357, 0.523818, 0.0463655, -1.03312, 0.238402, 1.36291, 0.942575, -0.582631, -0.00566493, 0.0121031, 0.894566, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.917, 1.712, -0.8657, -0.6753, 0.11597, 2.322, 3.057, -0.747, 1.676, 0.9756, 0.5645, -0.04327, 0.1837, 1.147, -0.6978, 0.03044, 0.2362, 2.281, 0.293, 1.032, 0.00521, 0.1508, -0.2966, -0.734, -0.9707, -1.024, -1.952, -0.302, 2.162, -0.413, -0.1918, 1.054, -0.8774, -0.5356, 1.537, 3.562, 1.688, -0.6636, -1.158, 0.0719, 2.297, 0.442, 1.897, 0.283, 0.5796, 1.913, 1.434, 2.172, -0.02122, -0.1328], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5117, -0.0767, 0.4917, -0.01083, 0.0897, 0.974, 0.3782, 0.05347, 0.5576, 0.02045, -0.1809, -0.11005, 0.1932, -0.02321, -0.0914, 0.02698, -0.1803, -0.05215, -0.5664, -0.702, -0.02188, 0.0725, -0.3936, -0.8164, -0.2373, 1.322, -0.6313, 0.04034, 0.538, -0.3074, -0.346, 0.1782, -0.2472, -0.02776, 0.5205, 0.5923, -0.1589, 0.1583, 0.0784, 0.1987, 1.09, -0.2059, -0.3948, 0.01555, -0.3076, 0.1881, -0.3655, -0.08606, -0.000783, -0.1062], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.158, 1.434, -1.706, 0.491, 0.6196, -0.761, 3.025, -0.4604, 0.4717, 0.811, 2.803, -0.7163, -0.7095, 0.831, 1.551, 0.309, 0.4143, 1.888, 0.09766, 0.09235, -0.02832, 1.093, 0.547, 0.2241, 0.144, 0.906, 0.5693, 0.06854, -0.0426, 0.455, -1.244, -0.3184, 0.612, -1.683, -0.582, 0.5254, -0.1587, -1.002, 0.2932, 0.02754, 1.139, 0.11334, 0.838, -0.1289, -0.01436, 1.943, 0.92, -1.365, -0.03027, -3.559], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -10.734, -2.71, 1.804, 0.704, -1.516, 0.4146, -5.723, 0.2693, -2.24, 0.6987, -4.2, 0.4988, -0.8804, 1.764, -3.54, -2.9, -0.654, -5.08, -6.43, 2.184, -0.024, -1.002, -4.363, 0.6226, -1.041, 0.836, -0.984, -5.48, 0.464, 2.22, -4.918, -5.926, -0.5493, -8.98, 1.663, -3.346, 0.4778, -7.605, -3.688, -0.04608, -7.387, -6.355, -1.178, -0.848, -1.712, -0.8438, 0.1796, -2.115, 0.04364, -1.46], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5527, 0.1398, -0.2598, 0.064, 0.1262, -0.6313, 1.078, -0.1622, 0.953, -0.4133, -0.377, 0.3696, -0.522, 0.33, 0.2844, 0.303, 0.11505, 0.52, -0.03323, 0.1948, 0.008446, 0.0918, -0.1351, 0.05988, -0.1411, 0.3938, 0.1674, -0.4, 0.1882, 0.1692, -0.1776, -0.10657, 0.02838, -0.2598, 0.2915, 0.701, -0.1105, -0.5835, -0.0383, -0.0871, 0.01842, -0.1409, -0.3706, 0.1719, 0.505, 1.709, -0.09155, 0.409, 0.03485, -0.684], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6787, 0.3208, -0.033, 0.02066, -0.801, -0.3005, 0.2976, 0.0006022, 0.2095, 0.12, -0.05185, 0.10406, -0.1102, -0.1098, 0.1372, 0.3428, 0.04208, -0.6895, -0.0652, 0.05914, 0.0189, -0.1388, -0.323, 0.132, -0.2866, 0.4824, -0.2336, 0.2004, 0.257, 0.3938, -0.3455, 0.1031, 0.1794, -0.5176, -0.3467, -0.2194, -0.0749, 0.3767, -0.764, 0.3262, -0.09717, -0.4607, -0.1636, 0.127, -0.606, -0.00832, 0.1613, -0.07117, 0.02586, -0.1761], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1544, -0.1849, 0.6763, -0.5186, -0.2262, 1.697, 2.148, -0.1159, 1.347, -0.3118, -0.3257, -0.02597, -2.61, 0.1188, 0.00855, 0.05392, -0.1436, -0.6826, -1.797, -0.366, 0.0346, 0.05347, 0.2225, -0.973, 0.9463, 1.81, -0.676, 0.684, 0.908, -0.763, 1.24, -1.048, 0.3713, -0.2654, 0.281, 0.7075, 0.2042, 0.0842, 0.03598, 0.0578, 1.572, 0.3613, 2.135, -0.2057, -0.85, 0.9717, 0.1655, 0.3762, 0.02747, 0.4846], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.4216, -0.578, -2.58, 0.1599, -1.728, -1.184, -0.05286, 0.1848, -0.1051, -1.445, -1.2705, 0.1476, -0.1875, 0.4722, 0.1532, -0.5815, 0.2734, -0.5337, 0.3564, 0.9355, -0.04343, -0.09247, 0.5044, -0.1497, -1.268, 0.796, -0.894, -1.56, -0.5776, -0.272, 0.934, -0.536, -2.156, 1.745, -0.141, -2.201, 0.2152, -1.487, 0.065, 0.002853, -1.279, -0.7153, 1.467, -1.197, 0.4087, -5.316, -0.0419, -2.877, 0.02501, 0.0617], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.514, 0.3271, -0.00982, -0.1164, 0.5044, -0.7456, -0.1627, -0.1332, -0.5347, -0.3499, -0.0624, -0.2666, -1.125, 0.2123, 0.522, 0.333, 0.2698, 0.4116, 0.2952, 0.16, -0.04343, 0.05222, -0.1012, -0.1644, -0.1109, 0.5073, 0.095, -0.4978, 0.586, 0.1289, 0.0896, -0.2445, 0.4656, -1.964, 0.7407, -0.39, -0.0522, -0.536, 0.1873, 0.0376, -0.2517, 0.0646, 0.4966, 0.4478, 0.8257, 0.9614, -0.4377, 0.1682, 0.01505, -0.06244], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.259, -4.36, -0.02428, 0.001229, -0.989, 0.01794, 2.047, 0.1652, -1.31, 0.2377, -1.74, -0.4753, -0.1937, -0.635, -0.1499, -1.046, 0.5454, -1.7295, 0.421, -0.3289, 0.03897, -0.24, -0.2686, -0.5347, -0.8936, -1.185, -1.216, -0.907, 1.296, 0.0977, 0.228, -0.06207, 0.3823, 0.2444, -0.4348, -1.027, -0.5146, -0.1674, -0.1299, 0.00945, -0.8276, -1.846, -1.831, -0.2942, 1.38, -2.633, 0.5903, -0.784, -0.0377, -0.4182], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.012764, 1.054, -0.2242, 0.0881, -0.9854, -0.693, -0.558, 0.1995, -0.2375, -0.9595, 0.554, 0.835, -1.066, -0.08545, -0.0575, -0.6743, 0.1798, -0.95, 0.04266, 0.3286, 0.0419, -0.1108, 0.1566, 0.3179, -0.1133, -2.783, -0.9834, -0.234, -1.023, 0.3047, -3.467, 0.4402, -0.2117, 0.553, -0.2837, -1.845, 0.4993, -1.002, -1.332, 0.006756, -3.514, 0.3682, 0.3958, -1.118, -3.004, -1.179, 0.3018, -1.74, -0.0281, -0.454], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3337, -0.1342, 0.05106, -0.1105, -0.2408, 0.2913, -0.2957, -0.012474, 1.061, 0.1216, 0.413, -0.05756, -0.1287, -0.3005, 0.278, -0.08673, 0.2081, 0.096, -0.6553, 0.05164, 0.03406, 0.1887, -0.908, 0.0379, -0.345, 0.704, -0.3362, 0.8105, 0.6313, -0.1741, -0.84, -0.3423, 0.4995, -0.7646, -0.3901, 0.3035, 0.1279, -0.08563, 0.131, 0.0798, -0.1664, 0.0552, -0.8022, 0.1057, 0.03937, 1.455, 0.3242, -0.2006, 0.00507, -0.0583], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6333, 1.186, -0.536, -0.0368, 0.8257, 0.732, -0.1658, -0.2617, -0.92, -0.3687, 0.627, 0.1865, -0.4739, -0.1442, -0.1565, 0.247, -0.05664, 0.2664, -0.656, -0.106, 0.03607, 0.08105, -0.412, 0.4219, 0.02051, 0.8213, 0.1932, -0.5386, -0.005455, -0.448, -0.1165, 0.3193, 0.6025, -0.5635, 0.3125, -0.174, 0.6597, -0.736, 0.4033, 0.08136, 0.4326, -0.2783, -0.955, -0.0278, -0.12286, 0.5864, -0.06113, 0.6147, -0.006943, 0.5254], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5015, 0.4282, -1.852, 0.0791, -1.595, -4.734, -0.995, -0.1951, -2.58, 0.1512, -0.862, -0.4197, 0.08844, -0.08344, 0.11554, 0.04196, -1.436, -4.65, 0.4028, 0.4678, 0.0199, -2.186, -1.419, 0.27, -0.00512, -0.999, -2.895, 0.0991, -2.453, 0.10156, 0.229, -1.215, -4.133, 0.06235, -0.403, -0.08673, 0.3342, -0.3555, -0.5015, 0.05725, -0.335, -2.635, -4.45, -0.0725, -2.635, -1.367, 0.1907, -0.4153, -0.02, -0.9595], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.066, -0.001381, 0.259, 0.1854, 0.4211, 0.7354, 1.563, -0.3176, 0.1578, -0.1407, -0.02646, -0.0406, -0.484, 0.02629, 0.1666, 0.171, -0.2202, -0.04926, 0.1797, -0.11475, -0.01376, 0.1009, 0.6426, -0.0649, 0.7163, 0.0433, 0.1024, 0.4744, 0.1294, -0.3872, -0.4092, -0.3367, 0.2434, -0.2476, -0.315, 1.599, 0.52, 0.05487, 0.2344, -0.0491, -1.009, -0.4634, -0.631, 0.6626, -0.551, -1.531, 0.11456, 1.073, -0.03543, -0.10657], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -3.424, 0.1454, -0.1664, -0.479, 0.5864, -4.26, -6.223, 0.1971, -1.621, -1.505, -6.125, -0.929, -0.1214, 0.3186, 1.54, -0.4768, -1.026, -2.137, 0.2043, -0.618, 0.02998, 0.4023, 0.3298, -0.6587, 0.007397, -1.723, -1.547, -0.5376, -2.396, 0.2284, -2.135, -2.74, 0.4656, -0.2742, 0.3103, -5.727, -0.596, 0.1523, -1.548, -0.04446, 1.437, -2.99, -5.33, 1.147, -3.12, -7.293, 2.145, -0.1813, 0.009766, -0.7354], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03128, -0.19, 0.2068, -0.0169, -0.3147, -0.601, 0.3638, -0.1171, 0.5664, 0.0853, -0.5645, -0.1106, -0.01965, -0.01662, -0.05875, 0.118, -0.11566, -0.3154, 0.801, -0.1068, -0.001109, -0.01598, 0.4243, -0.4216, -0.11066, -0.4482, -0.4978, 0.2656, -0.3958, 0.04926, 0.351, 0.01686, -0.648, -0.06537, -0.2184, 0.979, 0.29, 0.2238, -0.19, -0.0614, 0.2413, 0.012054, 0.04114, 0.07635, -0.1486, 0.799, 0.1998, -0.4053, -0.015366, 0.05856], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.202, 0.151, 0.3938, -0.1575, 0.7036, 0.06192, -0.0958, -0.165, 2.184, 0.269, -2.057, -1.3, 0.969, 0.4697, -0.7075, 0.11884, -0.441, 0.1305, 0.4263, 0.2272, 0.01923, -0.0635, 1.252, 0.6177, -0.9546, -0.891, 0.353, -0.3643, 0.669, -0.02248, -0.2192, -0.285, 2.047, -3.182, 0.3684, 2.057, 0.3315, -0.0455, -0.5103, 0.07465, 0.723, -0.2151, 1.293, 0.00893, 0.3386, 1.494, 0.07056, 0.5054, 0.01643, 1.026], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3323, -0.05356, -0.3215, -0.02725, -0.3108, -0.3708, -0.424, -0.09735, -0.3596, -0.1382, 0.3225, -0.2175, 0.1578, 0.1328, 0.05173, 0.05447, 0.05634, -0.08856, 0.253, -0.2189, 0.0343, -0.006474, -0.2261, 0.0028, -0.03098, -0.2313, 0.3176, 0.00763, 0.1896, 0.0269, -0.04984, -0.0973, 0.239, -0.1309, -0.0751, 0.2925, 0.4104, 0.1284, 0.0762, 0.2515, 0.48, -0.1843, 0.0374, 0.3696, -0.3826, -0.1423, 0.01009, -0.3022, -0.02757, 0.1753], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8267, 2.988, 1.747, -0.3987, 0.889, 2.316, 3.812, -0.672, 2.055, -0.6133, 2.873, -0.04224, 1.165, 2.303, 0.5376, 1.319, 0.26, -4.797, 1.358, 2.69, -0.02248, 1.356, 3.36, -1.219, -1.164, 2.557, 1.793, 2.963, -1.538, 2.12, 1.365, 4.312, 0.4211, -1.763, 2.148, 4.34, 0.121, -1.196, -1.05, 0.002626, 4.668, 1.043, -0.6196, -1.533, 1.407, 0.9585, -0.0566, 0.09546, -0.02939, -1.405], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1323, 0.2424, -0.6206, -0.4836, 1.705, 2.33, 3.426, -0.548, 2.332, 0.003866, -3.365, 0.0597, 0.485, -0.863, -0.642, -0.9307, 0.586, 0.2888, -0.3347, 0.7744, 0.02391, 0.762, -0.593, 0.001149, 0.1791, -0.01593, -0.1931, 0.803, 0.366, 1.022, 0.2407, -0.251, -1.145, -1.508, 1.809, -0.2664, 0.609, 2.363, 2.191, 0.0665, 1.502, 0.565, 1.314, -0.2382, 1.992, 3.592, -0.01718, 1.858, -0.0346, -0.11566], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.02405, 0.1184, -0.5605, 0.0723, -0.0991, 0.1421, 0.1099, -0.1825, 0.1036, 0.416, 0.7363, 0.4382, 0.04208, 0.3237, -0.0934, 0.08044, -0.05176, -0.09674, 0.03882, -0.04416, 0.02577, -0.1231, 0.3127, 0.3013, 0.1615, 0.08344, -0.0939, 0.2327, 0.0975, -0.1844, -0.1066, 0.3506, 0.2761, -0.06, 0.07227, 1.113, 0.2908, 0.1517, 0.126, -0.05685, 0.731, 0.0268, 0.1354, -1.158, 0.003029, 0.04382, 0.11584, -0.02188, -0.0314, 0.2109], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.2357, 0.0997, 0.0648, -0.1026, -0.2778, -0.2415, -0.01448, 0.00754, 0.3772, 0.02003, 0.6084, -0.3115, 0.0961, -0.974, -0.07715, 0.0708, -0.03143, -0.316, -0.2083, -0.0718, -0.006107, -0.1897, 0.2053, -0.02014, 0.1364, 0.5073, 0.2896, -0.5522, 0.0891, 0.01292, 0.10046, -0.874, 0.04904, -0.6665, -0.187, -0.2554, 0.2141, -0.02072, 0.2272, 0.02763, 0.2365, -0.2734, 0.838, -0.0557, -0.2113, 0.00085, -0.2423, -0.03647, -0.01996, -0.11316], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4385, 0.3794, 0.3584, -0.0774, -0.3662, 0.04904, 0.6865, 0.0225, 0.34, -0.5303, 0.174, -0.03485, -0.01387, 0.2158, 0.1562, 0.2634, 0.1037, -0.558, -0.6025, 0.191, -0.03192, 0.03494, -0.1195, -0.4968, -0.486, 0.4036, -0.2222, 0.2822, 0.593, 0.0654, 0.1707, -0.723, 0.2935, 0.1038, -0.363, 0.385, 0.02205, -0.1656, -0.305, 0.003355, 0.8306, 0.1487, -0.1793, -0.2236, -0.199, 0.7256, 0.0767, 0.04187, -0.01316, -0.2216], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.025, -0.001474, 0.8193, -0.1882, 0.2515, -1.406, -0.1342, 0.01971, 0.1887, -0.03772, -1.364, -0.04947, -0.01247, 0.4087, -0.448, 0.01509, -0.5034, 0.6323, -0.0856, -0.834, -0.00578, -0.15, 1.012, -0.2566, -0.06415, -0.2382, -1.554, 0.265, -0.9033, -0.6733, 0.4717, -0.364, 0.3965, 0.1624, -0.3325, 0.508, 0.303, -0.1345, -0.06223, 0.03882, -2.02, 0.12244, 0.643, 0.04996, 0.1447, -2.34, 0.292, 0.2482, -0.04245, 0.1832], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.195, 1.251, -1.6045, 0.1678, 2.479, 1.754, -1.106, -0.08984, 0.02673, -3.564, 2.06, 0.2783, -0.8896, 0.7837, 0.6846, 0.2751, -0.1343, -1.582, 0.7236, 0.2583, 0.03586, -0.39, 0.0453, -1.618, -1.262, -2.562, -5.832, -0.234, -0.4597, -0.9487, -0.5034, -0.7407, 1.797, -0.8027, -1.551, 2.889, 0.0856, -0.2039, 0.1625, -0.01732, -1.245, 0.003332, -0.3474, 0.647, -0.0662, -0.8716, 0.4304, 0.06158, -0.0463, 0.814], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3967, -0.2244, -0.8994, -0.1952, 0.8022, -2.191, -2.037, 0.10455, -1.69, 0.2612, -0.9766, -0.12164, 0.9272, -0.8647, -0.982, -0.3357, 0.0871, -0.589, 0.261, -0.1209, 0.01083, -0.2522, -0.3333, 0.8335, -0.2457, -0.7686, 0.1904, -0.012634, 0.0374, 1.095, -0.549, 0.8022, 1.777, -0.02538, -0.1914, -1.211, -0.531, 1.034, -0.7886, -0.0173, -0.4487, -0.04947, 0.4001, -0.3176, -0.578, 1.209, 0.1669, -0.4353, -0.03647, 0.0631], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.086, 1.313, -0.6885, -0.2228, 1.363, -1.308, 0.3584, -0.0502, 0.1572, -0.3447, 0.3289, -0.1637, 0.5615, -0.5605, 1.935, 0.6675, 0.0706, -1.252, 1.116, 0.0947, 0.001026, -0.82, -1.68, -1.181, -1.122, -0.523, -0.2366, 1.046, 1.347, -0.2424, -0.04602, -0.799, 0.3987, -2.531, -0.5234, 0.782, 0.2908, 1.937, -0.2439, -0.003414, -0.0866, -0.7974, -0.2832, 0.6636, 0.4834, 1.591, 0.069, -0.4683, 0.01098, -0.402], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.006176, -0.006268, -0.0364, -0.03375, -0.04205, -0.01738, -0.02519, -0.02654, 0.003693, 0.02058, -0.00826, -0.04053, -0.02965, 0.003761, -0.02226, -0.02158, -0.03647, -0.0431, 0.02046, 0.01813, 0.04822, 0.00836, -0.01646, 0.01431, -0.010956, -0.0153, -0.0395, -0.01287, 0.03723, 0.01616, -0.01717, -0.002342, 0.02626, 0.0375, -0.03647, 0.01704, -0.0342, -0.01457, 0.001411, -0.00197, -0.02904, 0.01863, 0.002846, -0.03168, -0.04495, -0.01396, -0.01654, 0.005913, 0.04138, -0.01002], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -3.816, -8.83, -3.475, 0.1594, 1.827, -3.549, 0.906, 0.7344, -8.945, -2.97, -13.04, -4.758, 1.659, -1.767, -2.236, 0.5103, -0.896, -0.8647, -1.659, 1.067, 0.02376, -0.7217, -1.8955, -1.708, -1.611, -8.89, -6.836, -4.184, -4.74, -0.673, -5.523, 1.11, -3.791, -4.617, 0.3186, -8.58, -1.4375, -10.5, -2.39, -0.06396, -0.02888, -5.832, -4.57, -0.492, 1.036, -13.086, -4.07, -0.858, -0.0446, -0.953], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3364, 0.4702, 1.121, -0.11053, 0.1727, 0.664, 0.718, 0.002077, 1.871, 0.0967, 0.9277, 0.1472, -0.1805, 0.628, -0.382, -0.09424, 0.1718, 0.551, 0.2935, 0.413, 0.0432, 0.6704, 1.001, 0.169, 0.1051, 0.9927, 0.1584, 0.499, 0.395, 0.4841, 0.15, 1.102, 0.4365, 0.2598, 0.758, 2.39, 0.5312, 0.2048, 0.8896, 0.05597, -0.05246, 0.7847, 0.9653, -0.6123, 0.006355, 0.4458, 0.5117, 1.099, -0.0325, 0.4302], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6646, 0.509, -0.399, -0.2659, -0.383, 0.3293, 0.5977, -0.1222, -0.03174, -0.0888, 0.00983, 0.4385, -0.6025, 0.1649, 0.04547, -0.3132, -0.2388, 0.6304, 0.321, -0.0497, -0.0077, -0.2222, 0.008064, -0.2744, -0.67, 0.866, -0.1917, 0.657, 0.0662, 0.03622, 0.6265, 0.547, 0.908, -0.598, 0.4614, 0.925, 0.4214, 0.4502, -0.5474, 0.0461, 0.03604, -0.518, -0.7656, -0.0671, 0.5405, -0.1655, 0.3015, 1.345, 0.03564, 0.4912], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6504, 0.1814, 0.02716, -0.05475, -0.12476, -0.1752, 0.9346, -0.221, 1.043, -0.1543, 0.3066, 0.05658, -0.2074, 0.1159, 0.1142, 0.2009, 0.194, -0.17, -0.475, 0.1693, 0.03546, -0.0728, -0.2747, -0.407, -0.1232, 0.1069, -0.2372, 0.4958, 0.353, 0.11096, 0.1508, 0.1774, -0.2039, -0.2314, -0.0914, 1.365, 0.4973, 0.2327, 0.1475, -0.05786, 0.9766, 0.1466, -0.4648, 0.1381, -0.09955, 0.3896, -0.04395, -0.3838, 0.013084, 0.4783], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.72, 0.4373, 1.544, 0.2349, 0.6064, 0.3826, 3.209, -0.4846, 0.8833, -1.648, 1.178, 0.7305, -0.06204, 0.982, 0.755, 0.754, 0.3584, -1.921, 0.02625, 1.025, -0.006554, -0.3232, 1.117, -0.3083, -0.3696, 0.64, 1.366, 2.309, 1.312, 0.4204, 0.907, 0.1958, 0.2266, -2.607, 1.365, 3.785, -0.0956, 1.123, 0.389, -0.01717, 0.943, 0.3364, 1.263, 0.192, 1.74, -0.289, 0.3928, 0.0972, -0.02298, -1.528], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.128, -4.613, 0.3345, -0.2235, -0.5337, 0.2377, -4.227, -0.03696, 1.315, -2.8, 1.778, 0.5396, -1.209, -0.1302, 0.03696, -0.2374, -0.1342, 1.409, -6.055, -0.4233, 0.00638, 0.9126, -2.098, -1.715, -0.3638, -7.258, 1.888, 0.347, -4.637, -0.10236, -0.9946, -0.3455, -0.8193, -0.6226, 0.55, -0.06854, 0.5396, 1.804, -0.5176, 0.007866, 1.1875, -0.0389, 0.612, -0.8213, 2.19, -0.6553, 0.563, 0.0965, -0.02943, -0.02525], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.541, -0.05743, -0.4985, -0.2712, 0.0413, -1.308, 1.993, 0.0259, -0.2742, -0.0341, 0.2018, 0.5146, -0.405, 0.03372, 0.02621, -0.04907, 0.463, -0.7666, 1.052, 0.7397, 0.01282, -0.05084, -0.371, -0.477, -0.4084, -1.059, 0.06366, 1.323, 0.4624, 0.6367, -0.179, 0.5645, -0.6816, -0.27, -1.172, -1.569, 0.6494, 0.8174, -1.99, -0.01624, -2.707, -0.3438, -1.021, -0.7407, 0.4846, -0.0801, 0.2656, -0.4854, -0.01952, -0.4263], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5083, 1.146, 2.33, -0.4739, 2.195, 1.405, 1.697, -0.2246, 1.808, -0.268, -1.898, -0.935, 0.591, 0.8213, -0.9116, 0.6265, 0.149, -1.142, 1.219, 0.686, 0.0481, -0.2896, 0.4924, -0.599, 0.2786, -2.15, 0.1758, 0.7974, 1.022, -1.148, -0.1992, -0.4646, -0.2942, 0.3796, -0.943, 1.39, 0.4783, 0.414, 0.1009, -0.0516, 2.174, 0.724, 0.3313, 0.1409, -0.1821, 0.7603, 1.09, 0.64, -0.03183, 0.2457], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.934, -0.265, -1.507, -0.0763, 1.482, -0.4714, -1.704, 0.1865, -0.6313, -2.568, -0.01507, 1.022, -0.4634, 0.4624, 0.1798, 0.8657, -0.0159, 0.8467, -2.016, 0.07416, -0.0313, -0.2203, -0.3645, -1.201, 0.5205, -0.9575, -1.506, 0.3208, 0.05313, -0.4597, -0.7886, -1.231, 0.631, -0.727, -1.761, 0.1984, -0.4062, -0.285, 0.642, -0.0537, -1.055, -0.10376, 0.4355, 1.538, -0.4302, -1.585, -0.3613, -0.645, 0.03357, 0.2961], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1432, 0.805, -3.438, -0.256, -0.6846, 0.323, -6.63, 0.0994, -2.033, -2.227, -3.271, 0.636, -0.4272, 0.3381, 0.584, -0.2098, 0.585, -1.462, -0.365, 0.7925, -0.03653, 0.2236, 0.868, 0.2593, -1.926, -5.254, -0.87, 0.8853, 1.625, -3.041, -2.938, -0.796, -0.873, 0.4658, -1.931, -3.758, 0.04483, 0.374, -0.3713, 0.03476, -0.6934, -2.475, -6.094, -0.4731, -1.628, -1.013, 0.27, -0.9897, -0.01077, 1.014], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.568, 0.744, 0.9897, 0.07074, -0.5205, 2.943, 1.525, -0.4365, -0.1522, 0.4731, 2.307, 0.601, -0.2947, 1.688, -1.809, 0.1219, 1.068, 1.031, -0.5215, 2.396, 0.02716, 0.5913, 1.393, -0.1145, 0.9497, 0.619, 1.117, 0.778, 1.026, 0.8784, 0.7007, 1.498, 0.803, -5.67, -0.9194, 4.6, -3.453, 3.803, 1.148, 0.08344, 1.9375, 1.93, 1.367, -0.3247, 1.081, 1.822, 0.231, 4.508, 0.002308, -4.88], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -2.621, -1.677, -2.861, 0.481, -3.238, -0.7744, -8.375, -0.13, -1.821, -0.06076, 0.3, -0.1877, 0.234, -0.05283, -1.918, -1.242, -0.54, -0.262, -0.1041, -0.3813, -0.001684, 0.44, 0.2717, 0.797, 0.665, -1.107, 1.14, 0.84, 0.2578, -0.9062, -0.4114, -1.364, -1.262, 2.229, -0.11127, 1.321, 1.269, -1.116, -0.285, -0.00708, 0.7827, -0.4792, 0.6055, -0.4846, -8.74, -0.2234, -0.655, 0.3325, -0.01144, -0.268], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.7373, -0.3699, -0.435, -0.007324, 0.893, -0.792, -2.635, 0.3616, -0.2532, -1.801, 0.774, 0.317, -0.0882, -0.0741, 1.53, 0.5522, 0.116, -0.3774, 0.4392, 0.2173, -0.01504, -1.001, -1.174, -1.713, -2.055, -5.5, 0.8643, -0.2737, -0.977, -0.693, -0.1678, -1.071, -2.271, -0.2474, -2.865, -2.414, 0.01875, 0.4482, -0.3857, -0.11975, -1.6045, -2.49, -5.227, -1.085, -0.9395, 0.643, -0.2389, -2.484, 0.00435, -0.7456], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.888, 1.354, -2.037, -0.3513, -1.897, -2.28, -1.004, 0.3389, -6.406, 1.812, -4.83, -2.898, 4.316, -0.524, -0.4902, -2.11, 0.2495, 0.743, -5.273, 0.01527, -0.03833, -0.2136, -1.514, -1.1045, 0.3372, -4.004, -0.5, -4.266, -5.477, -0.3118, -8.516, -5.164, -4.24, 1.12, 1.029, -7.33, -0.2578, -3.727, -4.79, -0.03342, 1.294, 1.334, -1.82, -0.3508, 1.1045, -5.207, 0.912, -0.665, 0.02412, -2.19], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.216, -0.4976, -2.775, -0.10077, 1.244, -0.883, 0.3198, 0.2416, -2.133, -2.445, -1.577, 0.04764, 0.1243, 0.353, 0.381, 0.6455, 0.2306, -0.2063, -0.3218, -0.07404, -0.002129, -0.344, -0.7373, -1.24, -0.5366, -1.614, -1.633, -1.349, -0.4446, -1.381, 0.288, -0.3408, -1.979, 0.0001373, -1.981, 0.0793, 0.2002, -0.8086, 0.2063, -0.05405, -0.191, 0.1481, 0.7607, -0.03415, -2.348, -0.447, 0.2488, -0.595, -0.04416, -0.2861], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3992, 2.691, 3.9, 0.07654, -1.698, 0.02986, 1.474, -1.241, 3.734, 0.749, 3.133, -1.592, 0.7603, 0.4583, 2.01, -0.4763, 0.6416, 2.584, 0.2532, 2.14, -0.005573, 0.48, -0.4895, 0.2412, -0.5566, 4.137, 0.56, 0.937, 0.4067, 2.658, 2.33, 2.988, 3.016, -2.924, -2.324, -1.775, 2.307, -3.861, 1.759, -0.04172, 1.588, 2.291, 0.893, -0.34, 0.4402, 1.534, 1.478, -0.4353, 0.002346, -0.3525], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.05, -0.5806, 0.766, -0.782, 3.348, 1.042, 1.013, -0.43, 0.1766, -0.1521, 2.541, -0.252, 0.1051, -1.17, 1.518, -0.04117, -0.5913, 1.802, 0.372, 0.07184, -0.04178, 0.03226, 0.3035, -1.305, -0.0795, 1.851, 0.1874, 0.02336, -0.1562, -0.8633, -1.137, 2.025, -0.0884, -3.793, 1.035, 4.008, 0.5674, 3.068, -1.1045, 0.1223, -1.075, -0.819, 0.153, 1.065, -2.057, 1.157, 1.382, 1.27, 0.03665, 1.98], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.4812, 0.134, -0.497, 0.02994, -0.364, -0.6206, -1.934, -0.035, 1.214, -0.8496, -1.594, -0.1461, 0.1609, -0.0778, -0.1729, -0.03793, 0.01764, -0.187, 0.197, -0.1575, 0.0356, -0.0698, 0.06915, 0.0517, 0.2524, 0.3154, -0.1838, -0.4885, -0.6733, -0.1449, 0.1344, -0.3035, -0.2379, 0.1812, -0.6616, 0.656, 0.8633, -0.2279, 0.2255, -0.0841, -0.2034, 0.05606, -0.4963, -0.5244, -1.201, -0.4055, -0.05954, -1.386, 0.014694, -0.4214], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8076, -0.966, 0.5767, -0.5386, 0.5083, 0.2073, -0.2656, -0.291, 0.547, 0.491, 0.831, -0.2039, 1.503, 0.10126, 0.6646, -0.2527, 0.2637, -0.1714, 0.2666, 0.734, 0.0176, 0.2249, 0.2325, -0.643, 0.4763, -1.002, -1.602, 0.668, 1.542, 0.1957, 0.2764, -0.85, 1.054, -0.6875, 0.4556, 0.12177, -0.1168, 0.5083, 0.11523, 0.05576, -0.8325, 0.0867, -0.263, 0.569, 0.6924, 1.34, -0.761, 1.262, -0.01573, 1.055], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -2.229, -2.682, -9.46, 1.996, -2.607, -3.803, -3.756, 0.3618, -0.6426, -4.5, -3.219, -1.71, -1.829, -3.766, -5.707, -4.367, -0.723, -1.782, 1.047, -1.777, -0.012764, -3.21, -1.241, 1.1455, -0.0865, -0.5137, 1.576, -3.76, -1.87, -2.605, 0.943, -8.34, -3.162, 4.324, -3.572, -0.3071, -1.632, -3.287, -2.818, -0.02605, -0.452, -10.875, -1.253, -3.773, -0.2351, -7.367, -0.4062, -3.424, 0.033, -0.734], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8765, -1.518, 0.9478, -0.1891, -0.1708, -1.77, 1.177, -0.2141, 2.078, -0.2139, 2.303, -0.0471, 0.17, 0.2798, -0.010864, 0.272, -0.2439, 0.8096, -0.532, 0.1637, 0.01665, 0.272, 0.6396, -0.1267, -0.2532, 1.081, -3.016, 0.6235, -1.58, -0.1804, -0.2712, 0.1611, 0.1907, -0.876, -0.539, 2.533, 0.0527, -2.455, -0.2025, -0.04193, 0.524, 0.04636, -1.033, 0.2384, 1.363, 0.9424, -0.5825, -0.005665, 0.0121, 0.8945]] [-0.00531489, 1.09042, 2.14067, 1.00862, 2.09616, 2.17111, 0.608048, -0.45753, 2.19102, -1.64808, -0.499766, 0.853452, 2.00846, -0.0260503, 2.18324, 0.265655, 0.952091, 0.539105, 3.45282, 0.661719, -0.812026, -0.662646, -0.0381569, 3.08199, 0.259077, 0.567328, 0.115133, 4.59682, 0.0, -1.00437, -2.51176, 0.59332, 1.17463, 0.49534, -1.84365, 2.80205, -0.397106, -0.168564, 1.71175, 1.19615, 1.29271, 2.49076, -0.33568, 1.20101, 0.984225, 0.926552, 3.37819, 1.09261, -1.20169, 0.121169, -0.005314, 1.091, 2.14, 1.009, 2.096, 2.172, 0.608, -0.4575, 2.191, -1.648, -0.4998, 0.8535, 2.008, -0.02605, 2.184, 0.2656, 0.952, 0.539, 3.453, 0.6616, -0.812, -0.6626, -0.03815, 3.082, 0.259, 0.5674, 0.1151, 4.598, 0.0, -1.004, -2.512, 0.5933, 1.175, 0.4954, -1.844, 2.803, -0.3972, -0.1686, 1.712, 1.196, 1.293, 2.49, -0.3357, 1.201, 0.9844, 0.927, 3.379, 1.093, -1.202, 0.12115] ReLU [[0.0309351, 0.018066, -0.015908, -0.0050587, 0.110306, 0.00142164, -0.104527, 0.0157008, -0.123083, 0.025456, 0.0125262, 0.0278131, 0.00571411, 1.6049, -0.0105878, 0.0220079, 0.128387, -0.0105834, 0.0853231, -4.99155e-05, 0.00558305, 0.22781, -0.0874578, 0.0191829, -0.0369042, 0.0194176, 0.010549, 0.0125647, 0.0440927, -0.0427327, -0.034355, 0.0570962, 0.15388, 0.0205593, -0.075037, -0.0156852, -0.0446344, -0.00381369, -0.0130292, 0.00590512, 0.0206849, -0.0125329, -0.0207889, -0.0478776, 0.00670024, -0.00510712, -0.00411626, 0.026292, -0.000404464, -0.00930195, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0947937, 0.0378741, 0.0376514, -0.0172005, 0.0129996, -0.0312773, 0.0513173, 0.00963456, 0.0507877, -0.0204445, 0.00777349, 0.0393754, 0.058835, -1.07172, 0.0212838, -0.0223187, -0.0826702, 0.0548555, 0.0433634, 0.0214364, 0.0226821, 0.0112825, -0.0783626, 0.0107729, 0.0556142, 0.0153335, 0.0147153, 0.0327069, 0.0319434, -0.0168213, -0.0901462, 0.0912605, 0.0487227, -0.0176531, -0.0144453, 0.0113559, 0.0801996, -0.0130964, -0.0253788, 0.0238591, -0.00273918, -0.0274435, -0.0268253, -0.0155129, 0.0188467, 0.0283852, 0.00381021, -0.0060986, -0.0157776, 0.0151329, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.236667, 0.0217327, 0.0961016, -0.0860911, -0.0538118, -0.0940888, 0.0118218, -0.0158617, -0.167394, -0.458569, -0.00165716, 0.0787979, -0.105609, -0.0498574, 0.198722, 0.0830129, -0.404822, 0.0507795, 0.0145466, 0.00343944, 0.0718483, 0.155001, -0.0757487, -0.218226, 0.175006, 0.0501895, 0.0599304, -0.0864215, 0.000209375, -0.0585608, -0.283413, 0.124071, -0.139772, -0.0324328, -2.49922, 0.381085, -0.0812795, -0.00127184, -0.131931, -0.167437, -0.0952938, 0.00102788, -0.0629529, 0.0526138, -0.431546, -0.0469713, 0.192164, -0.108329, 0.05167, 0.10709, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.912842, -1.93439, -0.755438, -1.18454, -0.899518, -1.44267, 0.0763976, -0.29454, -0.899745, -0.582776, 0.462914, -0.0989079, -4.12109, 0.448558, 0.120589, 0.605945, 1.76974, -3.12317, -0.811643, 0.307298, -0.391524, 0.0475524, -0.603239, -0.0660639, -1.46889, -1.18127, -2.56329, -0.289555, -0.0366659, 0.234657, -0.832153, 0.689344, 1.77372, -0.548878, -0.589327, 0.635358, -1.69571, 0.133208, -2.1331, -1.88766, -0.488661, -1.018, -0.798981, 0.471432, 0.140066, -3.63333, 0.419544, -2.30035, -0.0963147, -1.34624, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0244775, -0.0187852, -0.00413599, -0.00393064, -0.0112805, 0.0511191, -0.00409766, -0.00828047, -0.00509975, 0.00258534, 0.00570281, 0.0272436, 0.0255486, -0.158767, 0.0832071, -0.000476821, -0.0605735, -0.00226249, 0.0958247, 0.00916384, 0.00264474, 0.0338204, -0.0523577, 0.0495072, -0.000348247, -0.00144428, -0.0154884, 0.00767292, 0.0148814, -0.0132412, -0.0157956, -0.0225658, 0.158025, -0.00248878, 0.00692398, 0.00679627, -0.0268579, -0.00465732, 0.000176073, -0.00352727, 0.000611897, 0.000756007, -0.00685694, 0.00045702, 0.00276794, 0.0123411, 0.0604515, 0.00587464, -0.00309287, 0.000387732, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0153319, -0.0761142, 0.0153552, -0.0705958, 0.000382962, 0.283185, -0.0808563, 0.16745, -0.0669273, -0.33577, 0.00123483, 0.456922, 0.174457, -1.12356, -0.266133, 0.0480015, 0.981271, 0.164536, 0.195804, 0.145682, 0.178577, -0.0691009, -0.031794, -0.15365, 0.0816411, 0.113618, -0.397702, -0.237545, -0.0169165, -0.0624405, -0.176585, 0.322811, -0.116773, -0.107211, 0.0323974, 0.252949, 0.184957, 0.0645982, 0.00692965, 0.0256673, 0.191273, -0.0999088, 0.00129849, 0.109724, -0.118934, 0.0182882, 0.0126665, -0.248069, -0.39128, -0.167833, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.311409, 1.21654, -1.56223, -0.779191, -0.319205, -1.81302, 0.490326, -1.14337, 0.93568, 1.05753, -0.728093, 0.0831378, 0.618117, -0.0458155, 0.790801, -1.99609, -0.389011, 0.378418, -0.264313, 0.268159, 0.668754, -0.404622, 0.287599, -0.556831, 1.54464, -2.00819, -2.55612, -2.6061, 0.0220928, -0.285784, -1.31475, 0.941117, 2.59923, 0.386473, 0.711182, -0.328683, 0.846011, -1.24178, 0.822046, 0.570562, 0.899135, 0.0358904, -0.933297, -0.109469, 0.221186, -0.81945, 0.0878435, 1.41974, -0.762075, 0.741666, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.164016, -0.218194, 0.0044117, 0.0350279, -0.055459, 0.138164, -0.218066, 0.0154572, 0.0829462, 0.0293349, 0.0589587, -0.00404776, 0.031788, -1.76091, 0.0865706, -1.24957, -0.45736, -0.142706, -0.252384, -0.0677601, 0.0492024, -0.040515, 0.195312, 0.22967, 0.0164208, -0.128295, -0.0288299, -0.032432, -0.0185707, 0.00646946, -0.0303664, -0.12358, 0.552547, -0.0283874, 0.150632, 0.0250886, -0.38092, 0.04155, -0.060001, -0.00441836, 0.0841029, -0.0472774, 2.33923e-06, -0.053133, -0.0394548, 0.0509593, -0.0376707, -0.0959278, 0.0209807, 0.0810693, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0340645, 0.129567, -0.254698, -0.0360564, -0.0232624, -0.116346, 0.0484182, -0.108228, 0.0843986, 0.0711714, -0.0377304, 0.0332786, 0.055055, 1.63855, 0.032545, -0.119091, 0.00352319, 0.0430024, -0.0154465, 0.0391224, 0.0611402, 0.0827748, 0.012589, -0.00675787, 0.137884, -0.0789687, -0.20825, -0.280488, 0.0132607, -0.0312786, -0.153903, 0.0894347, 0.224941, 0.0303358, 0.018816, -0.062106, 0.116807, -0.066618, 0.0426308, 0.043809, 0.0535386, -0.0786438, -0.0793168, 0.00985263, 0.0326819, -0.0106666, 0.00537743, 0.115842, -0.634412, 0.0865105, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.134169, -0.131721, -0.127073, -0.0183548, -0.806306, 0.577847, 0.453213, 0.0146746, -0.192321, -0.963922, -0.900389, -0.306895, -0.884472, -1.23919, 0.454021, 0.0605787, -4.5777, 0.527298, -0.375371, 0.257885, -0.0701051, -0.306694, -0.0822203, 0.27757, 0.139682, 0.3198, 0.161103, -0.481797, -0.00984522, 0.054756, -0.503911, 0.828075, 1.09586, -0.823629, 0.546283, 0.209662, 0.0813088, -0.356954, -0.234332, 0.264416, 0.373524, 0.138263, -0.196298, -0.0862998, -1.18769, 0.143746, 0.354115, 0.3471, -0.0315256, -0.408445, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0333344, -0.142113, 0.0545333, -0.054725, -0.100239, -0.235062, 0.0114255, -0.0140442, -0.0831892, -0.333998, 0.0398908, 0.137394, 0.211497, -0.147731, -0.0205809, -0.0071075, 0.362035, 0.0837296, 0.102061, -0.0181184, -0.0573538, 0.222999, 0.0356619, 0.143972, 0.0272016, -0.0353422, -0.154718, 0.0339213, 0.00597503, 0.00379215, -0.0693494, 0.0523165, 0.0277668, -0.517671, -0.0973582, 0.0776056, 0.0149324, -0.014229, -0.0269256, -0.535525, -0.0270749, -0.0114139, 0.0419661, -0.0336658, 0.0138358, -0.0180215, -0.153756, 0.0176288, -1.40741, 0.0569768, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-4.36414, 0.232655, -0.933917, -0.336884, -0.241696, -0.0511536, 0.199848, 0.000140902, 1.06298, -0.426417, 0.619423, 1.24314, 0.75808, -0.190621, -0.550444, 1.15712, -7.44772, 1.79592, 0.490897, -0.395391, -2.10494, 1.02347, 0.25312, 0.630596, -0.48113, 0.647416, -0.703596, -0.977305, 0.0411539, 0.134335, -0.980724, 1.55857, -8.57259, 0.706988, 0.684759, 0.387611, -2.60371, -0.663775, -0.444831, 0.0149362, 0.928222, 0.533671, -0.113454, 0.258219, -7.48532, 0.177657, -4.71002, 0.951732, -0.52047, -0.0863061, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0154108, 0.0781994, -0.0110771, 0.0351249, -0.0566218, 0.0216918, -0.123121, -0.0179859, -0.176101, 0.0561789, 0.00279031, 0.157558, 0.0557174, 0.968038, 0.105367, 0.0521196, 0.3252, -0.0107507, 0.153844, 0.0697811, 0.0682607, 0.271895, 0.0245924, 0.0394035, -0.128342, 0.0357865, -0.0942249, -0.0175665, -0.0261822, 0.0301137, -0.0595658, 0.0780462, 0.166889, -0.0687616, -0.165216, 0.0351968, 0.0301228, 0.0713989, -0.0158115, -0.00166718, -0.0625997, 0.0508779, -0.130264, -0.0396914, 0.00648072, -0.0232784, 0.167893, 0.0257187, -0.0224845, 0.155146, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.00543683, -0.279402, -0.0149697, 0.00660854, -0.0959905, -0.00956715, -0.064029, 0.0105886, 0.104578, -0.0430467, 0.0210722, -0.0252195, 0.13722, -0.250355, 0.191811, 0.0286778, -0.0254097, 0.0441613, 0.0346253, -0.0112783, -0.0303964, 0.037594, 0.00958984, 0.134612, -0.0698438, -0.115054, -0.00953476, -0.019705, 0.0156583, -1.90453, -0.0443359, -0.0772139, 0.107798, 0.0300511, 0.00359712, 0.0271675, -0.0373775, -0.0232039, -0.0624459, 0.00527232, 0.00503453, -0.0254295, 0.0316107, 0.0356706, -0.0101497, -0.0138443, 0.161677, -0.044059, 0.00168178, 0.152129, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.670166, 1.12357, -0.378797, -0.171346, 0.481274, -1.19534, 0.894133, -0.682925, 0.869895, 1.83885, 1.44477, 1.97564, 0.363368, -0.382683, 0.989072, 0.233388, -4.9559, 1.5792, -1.06955, 1.19496, 2.05282, -0.623286, 0.784238, -2.09322, 1.72642, -0.24295, -0.42756, -1.59541, -0.0122853, 0.601019, -2.02735, 2.59981, 3.34246, -6.18645, 0.250166, -0.66818, 1.9778, 0.258024, 0.657789, -0.686895, 0.667627, -0.441963, -0.137112, 1.20824, -1.89438, 0.300553, -0.917798, 1.4502, 0.520096, 0.518662, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0948205, -0.441589, -0.0500001, 0.0211725, -0.597599, 0.13788, -0.0297396, 0.0388057, -0.14679, 0.0772723, 0.0638456, -0.0971806, -0.146301, 1.65785, -0.107101, 0.0283756, -1.07285, -0.0778035, 0.0363209, -0.0796365, 0.175635, 0.13938, -0.389816, 0.385684, 0.012902, 0.00694645, -0.203212, -0.140741, -0.000219947, -0.0021842, -0.0615142, -0.116907, 0.0308523, 0.0439695, 0.198099, -0.077479, 0.0859085, -0.0061486, 0.0170556, -0.0230142, 0.0415396, 0.067818, 0.0324175, -0.141866, -0.00333263, 0.0608921, 0.0702907, -0.0636471, -0.182517, 0.12709, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0584585, 0.104036, 0.0688731, -0.0266464, 0.0441542, 0.0125827, 0.0941346, 0.0277657, 0.0708956, -0.0203524, -0.0522283, 0.0934733, 0.160782, -0.312079, -0.00820623, -0.047884, 0.23385, 0.107443, 0.0193554, 0.0489908, 0.0371176, 0.0443423, -0.00793252, -0.00961495, 0.118854, 0.0590874, 0.0309531, 0.0724503, 0.0332306, -0.0330579, -0.18493, 0.112929, 0.0429623, 0.0412911, -0.0772363, 0.0334547, 0.0535856, -0.0362087, -0.0652333, 0.0520815, -0.122204, -0.0552548, -0.0453773, -0.0323922, 0.0453782, 0.0620116, 0.0575762, 0.0490232, -0.0354093, 0.0666633, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.272064, 0.0050209, 0.12547, 0.0545317, -0.115638, 0.123417, -2.35972, -0.10114, -0.274696, 0.177977, 0.161416, -0.0508446, 0.00954908, -1.73837, 0.00829101, -0.015852, -0.00511574, 0.474278, 0.352744, -0.0675566, 0.181888, 0.336612, -0.0423793, 0.181862, -0.0124973, -0.042285, -0.147827, -0.0526162, -0.0459354, -0.455611, -0.233299, -0.187242, -0.416631, 0.0119479, -0.0653088, 0.117289, 0.0242018, 0.0676456, 0.06114, -0.0225303, -0.490337, 0.201653, -0.173913, 0.0482663, -0.0255633, 0.0305105, -0.13838, 0.368778, -1.48773, 0.324353, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.182821, 0.348526, -0.0618761, -0.145008, -0.0247096, 0.223244, -0.0530427, -0.295013, 0.0685783, 0.0425703, 0.0302481, -0.0140249, 0.110783, 0.91447, 0.0805797, 0.00548485, -0.731067, 0.137952, 0.113618, 0.0461002, 0.1465, 0.0409918, -1.10832, 0.258314, -0.401459, 0.113778, -0.0627072, -0.105111, -0.0438661, -0.0465584, -0.276299, 0.500353, 0.132738, 0.0687608, -0.0590173, -0.0502332, -0.205429, -0.0806843, -0.0992292, -0.576503, -0.0292142, -0.101149, -0.0461852, -0.070056, -0.234652, -0.00712008, 0.175677, 0.0340669, 0.01039, -0.955353, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.00574534, 0.0174505, 0.00823736, -0.0205825, -0.025444, -0.0636697, 0.0135763, -0.0162142, -0.00920626, 0.021179, -0.0355348, -0.0221683, -0.0186349, -0.0260795, -0.0273032, 0.019215, 0.0155749, -0.0458928, -0.0123694, -0.0476085, -0.0427274, -0.0603579, 0.0432385, -0.0500227, 0.0120433, 0.0150069, -0.00575103, -0.0505779, -0.00538401, -0.0211709, -0.0835034, -0.0210836, -0.00579467, -0.010618, 0.00691491, -0.0582471, -0.0321992, -0.0463144, 0.0166432, -0.0106154, -0.0494861, 0.00707492, -0.00164387, -0.0361766, -0.0273302, -0.000779469, -0.0179518, -0.0925022, 0.012932, -0.0095603, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.36531, 0.501902, -0.245464, -0.121591, -0.922377, -0.270389, 0.277503, -0.526656, 0.263144, -0.705467, 0.774439, 0.14827, 0.839278, -0.0393303, 0.56872, -2.33639, -3.20442, 2.19548, -0.490325, 0.177987, 0.724249, -3.01126, -0.0648737, -0.450932, -0.248917, -0.448852, -3.93942, -0.481624, -0.0317077, -1.15767, -1.51555, 0.473277, 2.40339, -2.84543, -0.34916, 0.90346, -2.17828, 0.47529, 0.35041, -1.29863, -0.335606, -0.252818, 0.389997, 0.173538, -1.58891, -0.271877, -1.18747, -0.787887, -0.0487669, 1.12385, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0466498, -0.0790913, 0.00322579, -0.0192459, -0.0701031, 0.140652, -0.00777316, -0.00164592, 0.0129095, -0.0200882, -0.045406, 0.0513314, 0.0258271, 0.592618, 0.0213045, 0.000583976, 0.0299037, 0.0570453, 0.124826, 0.0216232, 0.00754163, -0.0399979, 0.0915789, -0.0551116, -0.217124, 0.0304989, -0.0699134, -0.0425094, 0.00438888, -0.0340779, -0.042548, -0.025483, 0.00746704, -0.0159298, -0.0470671, 0.0293712, -0.123123, -0.0289644, -0.0905544, 0.00364703, -0.0411031, -0.0693569, 0.0145095, -0.0891062, 0.00155143, 0.00651407, 0.00484864, 0.0825966, -2.4424, 0.057812, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.73714, -0.294682, -0.079328, -0.0294241, -1.43671, 0.00239785, -0.592491, -0.0845896, 0.232373, 0.0279705, -0.0215978, -0.370185, -0.318121, 0.201554, -0.239868, -0.808664, -6.01583, -0.341997, 0.207962, 0.0167317, 0.0620036, 0.0764778, 0.30327, 0.0169994, 0.030579, 0.037268, -0.0966652, -0.435034, -0.0237068, -0.0907104, -0.0525368, 0.053248, 0.395733, -0.373671, 0.195629, 0.0116096, 0.137841, -0.0875781, 0.0347446, -0.00601306, -0.0723557, -0.21912, -0.0472595, -0.0332816, -0.049932, -0.190827, 0.234995, -0.414175, 0.0215693, -0.0300216, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.57971, -0.141799, 0.122533, -0.266208, -3.55728, -2.229, 0.217454, -0.475642, -0.611795, -0.222564, 0.114433, 0.38599, -5.05669, -0.0197712, -2.20136, -1.40236, 0.0472978, -0.684547, 1.99329, -2.42195, -3.53269, -1.43803, 0.334979, -0.0176636, -0.659068, -0.597323, -1.73066, -0.929035, -0.0285235, -0.0374966, -0.494183, 1.31442, -0.798022, -0.778086, 0.63873, 0.438119, 0.326959, -0.169519, 0.258997, 0.428836, -0.636027, -0.0311057, -0.33552, 0.0271565, -2.10682, -2.04409, -2.15375, -0.604533, -1.02672, -0.0158975, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.105565, -0.20163, 0.0367913, -0.186291, -0.119046, -0.189649, -0.427981, -0.070253, -0.125724, -0.884951, -0.00475639, 0.133016, 0.0578366, 0.0843263, 0.168571, -0.00353073, -0.0343956, 0.147231, 0.0103426, 0.00247469, 0.0421845, 0.102744, 0.176968, 0.332263, 0.00109935, 0.0523672, -0.770292, -0.0363813, -0.0166153, -0.275199, -0.21096, 0.266486, -0.250248, 0.0447803, -0.0732872, 0.0436498, 0.224171, -0.0255253, -0.0533559, 0.0415497, -0.0793143, 0.0955697, -0.302971, 0.130419, -0.0375034, 0.0704915, 0.0875236, -0.0143581, -0.568048, -0.384479, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.104783, 0.0551895, 0.0183107, -0.237466, -0.13146, -0.0889406, -0.0824353, 0.00712216, -0.067343, -0.114315, -0.019112, 0.0569511, 0.139005, -0.488838, 0.161824, -0.0514162, -2.26975, -0.010342, 0.0679362, 0.026138, -0.071463, -0.84675, 0.0693023, 0.233992, 0.0458268, 0.0394858, -0.830281, 0.00161283, 0.00475367, -2.49622, -0.020545, -0.0619091, -1.10106, 0.0283019, -0.136847, 0.027672, -0.0299334, 0.0270566, -0.0033933, 0.0222381, -0.0287313, 0.0234348, -0.876697, -0.00803294, -0.0193395, -0.0312091, -0.037166, -0.130647, -0.635582, 0.0388194, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0177645, 0.119796, 0.0506167, 0.00391343, -0.0928419, -0.150754, 0.07399, 0.0160851, 0.000451114, -1.61242, -0.0091665, 0.0159249, 0.164908, 0.0626971, -0.0656443, 0.0537075, 0.271716, -0.0663914, 0.249078, 0.0227344, 0.0791285, 0.214198, -0.265653, 0.0650767, -0.145491, -0.0652902, -0.0900602, 0.0178419, 0.00854897, 0.0651934, -0.0660416, 0.039284, 0.183361, -0.0525257, -0.1138, 0.136156, -0.397772, 0.0258236, 0.0744765, -0.691637, -0.150065, -0.055096, -1.41295, -0.0989956, -0.0258025, -0.00438213, 0.093249, 0.129894, -0.068694, 0.0279002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.145194, 0.267471, 0.177856, -0.066636, 0.114681, 0.0398737, 0.228763, 0.0748215, 0.182467, -0.0458531, -0.144412, 0.235518, 0.407207, -0.0405057, -0.0143461, -0.125645, 0.667515, 0.27151, 0.0625998, 0.127747, 0.0986974, 0.097163, 0.0420122, -0.0193354, 0.283089, 0.151582, 0.0782278, 0.189919, 0.0317566, -0.0816408, -0.478307, 0.2603, 0.15232, 0.116898, -0.225699, 0.0900437, 0.110918, -0.0920472, -0.169074, 0.138655, -0.372722, -0.144585, -0.112974, -0.0989958, 0.118094, 0.154203, 0.197078, 0.130284, -0.110066, 0.187751, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1.91803, -0.291365, -0.0287233, -2.2854, -0.447402, -0.549387, 0.121527, -0.128481, -0.0620184, 0.278666, -0.0556456, -0.352386, 0.386545, 2.05106, 0.0764744, -0.338989, 0.812821, 0.099188, -0.250088, -0.246655, -0.135953, 0.181045, -0.16561, 0.154134, 0.0893089, -0.225041, -0.541031, -0.0657395, 0.00224399, -0.0425039, -0.12099, -0.285287, -1.58296, 0.00972699, -0.533882, -0.197989, -0.116033, 0.0051144, 0.0938912, -2.78848, 0.0661115, -0.133502, -1.08657, 0.124644, 0.00923678, 0.0297015, 0.123444, -0.416493, -3.26088, 0.26748, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.197836, 0.737045, -4.3746, -0.452796, 0.534183, -1.18605, 0.708202, -0.610886, -0.105039, 0.92585, 0.937828, -1.21831, 2.01152, -1.44793, -1.63183, 1.31674, -9.29117, 1.83469, 1.15199, 0.310973, 1.07918, 3.37113, 0.611127, -0.150202, -0.772395, 0.225136, -1.12697, -1.50766, -0.0275733, 0.308928, -1.70322, 1.70757, 0.283941, -3.81543, 0.0177448, 0.663176, -0.444753, -0.26624, 0.103405, 0.377903, 0.184203, 0.647216, -0.324064, -0.838146, 0.33503, -0.974943, -0.0491812, 1.08616, -0.546284, 0.23297, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0978169, 0.081665, 0.00859469, -0.13403, -0.0311976, -0.024116, -0.151476, -0.0872239, 0.00662188, -0.184653, -0.0543021, 0.128318, 0.12193, 0.373107, 0.0269641, 0.00824512, 0.0744901, 0.227296, 0.0309162, 0.0352381, -0.0137325, -0.18835, 0.303082, -0.0129443, -0.0354542, -0.0842245, -0.202739, -0.0603496, 0.0405794, -0.503064, -0.0936106, -0.0574276, 0.398186, 0.0105767, -0.00119496, -0.0557166, 0.0492075, 0.0420602, -0.100275, -2.19383, 0.0421416, -0.0332658, -2.22122, -0.0113205, -0.0379569, -0.0195882, 0.0141159, -0.111314, -0.840987, -0.0404652, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0332601, -0.215001, -0.0502811, -0.044491, 0.0919335, 0.0929356, -0.312031, -0.0430778, -0.144701, -0.254587, 0.00684034, 0.0118517, 0.132503, -0.182531, 0.141691, 0.0216497, 0.328844, 0.0017829, 0.118445, -0.030153, 0.077549, 0.293852, -0.124419, -0.122, -0.307025, -0.0826321, -0.276638, -0.0131884, 0.00718599, -0.0613894, -0.0351163, -0.161896, 0.210465, 0.00254536, 0.180567, 0.069311, 0.0450809, -0.0575776, 0.0605707, 0.00110596, 0.0411386, 0.103275, 0.120026, -0.00409792, -0.00622104, 0.00462257, 0.0631818, -0.0461031, -0.0596653, -1.22522, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-3.30339, 0.583762, -1.10553, 0.0297347, -0.544593, -1.10016, 1.40809, -0.970653, 1.05416, 1.88998, 1.38357, -0.860655, -0.153546, -0.535423, -1.76496, 0.423575, -2.38337, -0.562742, 0.0433839, 1.1559, -1.26841, -5.70335, 0.793956, -0.238739, 0.185553, 0.705871, 0.154658, -1.41127, -0.00208014, -0.476258, -2.37085, 0.870228, 2.92451, 0.204499, -0.553834, 0.0599711, 0.785814, 0.00824317, -0.157475, 0.0840446, 0.679572, 1.06451, -0.110567, 0.5669, -2.14796, 0.118534, 1.30551, 2.08083, -0.0383141, 0.14121, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0668234, -0.237088, 0.0359558, 0.0905643, -0.812542, -0.255138, -0.508653, -0.0564773, -0.305087, -0.0880428, -0.0201616, 0.220241, 0.031309, 0.0142881, 0.141246, 0.169191, -4.41984, -0.176963, -0.152251, 0.0395917, -0.0444679, -0.430282, 0.197598, 0.556579, -0.189045, 0.0416484, -1.15496, -0.205892, 0.0113956, -1.15997, -0.0338692, 0.181409, 0.21014, -0.0212761, -0.127548, 0.0622072, 0.105738, 0.0633277, -0.00768166, 0.0164492, -0.184875, 0.10833, -1.28848, 0.0422734, -0.172085, 0.0358351, 0.244614, -0.0101336, -0.115372, -0.307832, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0469681, -0.0482588, -0.00622907, 0.00897092, -0.177337, -0.0364372, -0.0596747, -0.0429863, 0.0375607, 0.015212, -0.0556293, 0.0717938, 0.0209079, -1.8904, 0.108925, -0.0449854, -0.541152, 0.0547433, -0.0172261, 0.0323758, 0.0586542, -0.0479659, 0.0890952, 0.196503, 0.0237353, 0.00611113, -0.0519805, -0.00612833, 0.00479463, -0.00151377, -0.106623, 0.0811336, -0.111309, 0.00236022, -0.0370781, 0.00883038, 0.0203212, -0.0227826, -0.01635, 0.0257681, -0.144318, -0.00370385, -0.0294718, -0.0149897, 0.0137506, 0.0412701, 0.086646, 0.0517121, -0.533206, 0.0259859, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0131071, -0.0977562, -0.00472974, -0.00347089, -0.0773172, 0.0325706, -0.030344, -0.0640302, -0.025346, 0.0393096, -0.037748, -0.0806879, 0.0347824, -0.0667865, 0.0326808, -0.00451392, -0.1511, -0.023217, 0.166083, 0.0159795, 0.0044698, -0.0866026, -0.142498, 0.111886, -0.171382, -0.0535259, -0.0330108, 0.00280808, -0.0341349, -0.00671037, -0.0250026, 0.0230989, 0.0880759, -0.0171817, 0.0325878, 0.0132058, 0.0678575, 0.0196903, -0.0170916, -0.00269929, -0.0477977, -0.0453852, 0.00179979, -0.0556421, -0.00967321, 0.000713364, 0.134009, 0.0173581, -1.0055, -0.363184, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.17131, -0.08458, -0.0418596, -0.0352089, 0.0780991, 0.0298368, -0.00174063, -0.0259883, -0.0581726, -0.0334867, -0.0417741, -0.011197, 0.0588903, -0.0475893, 0.144323, -0.00538225, 0.17206, -0.0411194, -0.0105379, -0.0354084, 0.0322185, -0.172957, -0.115803, 0.110878, 0.0821978, -0.0494375, -0.0380648, 0.0420068, 0.00784141, 0.00489288, -0.0468657, 0.0805272, -0.28738, 0.0026959, 0.0316654, 0.0160083, -0.116599, -0.0302253, -0.0731876, -0.0198668, -0.0557603, 0.00521864, -0.0260671, 0.0528269, -0.00355989, -0.0126928, -0.0337587, 0.0147573, -1.16125, -0.0355815, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.29968, 1.61381, -5.61527, 0.169657, 0.0572476, -0.55676, 0.136106, -1.11525, 0.682704, 0.749697, 0.657964, 0.503884, -0.354155, -0.965878, -1.011, -0.464147, 0.537073, -0.0161356, -0.449256, 0.832111, 0.445588, 0.296039, 0.352398, 0.627724, 1.27756, -2.00556, -1.19676, -3.4114, -0.0412708, -0.248279, -1.47082, 0.516119, 2.60467, 0.207507, 0.312017, -2.43294, 1.48706, 0.073449, 0.439093, 0.228571, 0.60875, -2.08336, -0.57264, 0.10202, 0.489493, 0.516368, 0.152291, 0.793884, -0.163586, 1.47555, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.00553502, -0.0245234, 0.0141801, -0.0165301, 0.0448721, 0.101895, -0.12619, -0.00570562, -0.0722891, 0.0457881, 0.0185793, 0.0179171, 0.0623294, 0.336159, -0.00732771, 0.0124065, 0.249372, 0.139755, 0.165522, 0.0157896, -0.0166547, -0.0424483, 0.0993118, 0.065964, 0.0885008, 0.0397192, -0.0792015, -0.0309825, 0.0145761, -0.0028326, -0.0658539, 0.0198885, 0.12359, 0.0138702, 0.0216207, 0.0193196, -0.0325875, -0.0130412, -0.0123963, -0.0534388, -0.0836718, 0.0459641, 0.0175946, 0.0268082, 0.0160494, 0.0157401, 0.0158919, 0.105273, -0.541376, -0.0217315, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.2075, -0.375012, -0.0343038, -0.00157732, 0.148836, 0.0493773, -0.583362, -0.0257827, -0.215347, -0.0101018, -0.143252, 0.101234, 0.0418974, 0.164639, -0.0417583, 0.0254606, -0.305052, 0.0125695, 0.0588049, -0.00918611, 0.0377718, -0.0168373, 0.456512, 0.0995877, -0.121592, -0.0048513, -0.0304011, 0.0451062, -0.0135199, 0.0151827, -0.106533, 0.158518, 0.0982386, 0.0248091, -0.977317, 0.00585554, -0.375783, -0.0384439, -0.07957, 0.0400931, -0.283112, -0.028536, -0.0604227, -0.0226889, 0.0190849, -0.0953438, -0.0941874, 0.0339419, -0.170713, -0.0692725, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0556457, -0.130285, 0.0410483, -0.010125, -0.0695211, -0.137962, -0.0668256, -0.0251664, 0.0243701, -0.0107999, -0.0290782, 0.0347083, 0.0568238, 1.23306, 0.0394104, -0.0308587, 0.146249, 0.027713, 0.0561028, -0.0210745, 0.0493129, -0.0626726, -0.136062, 0.171223, 0.0984693, 0.00586778, -0.13606, -0.0347207, -6.67597e-05, -0.0566174, -0.0436823, 0.0968129, -0.0301952, 0.0221049, -0.0482821, 0.027801, 0.0830409, 0.0284331, 0.0105205, 0.000862171, -0.0461196, 0.033594, 0.00510617, 0.0499842, -0.0208329, 0.0226163, 0.100216, -0.021521, -1.43353, -0.0096646, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.069031, 0.179743, -0.015564, -0.0144464, 0.106863, -0.0466807, -0.531641, 0.02039, -0.0278886, 0.0781126, 0.0134981, -0.0312746, -0.0315292, 1.17197, -0.0452076, 0.0137876, 0.450858, -0.00422906, -0.0186547, 0.00928347, -0.0184217, 0.248236, -0.0229766, 0.00395466, 0.0157622, 0.0349091, 0.0149215, 0.0137575, -0.0428298, -0.0345099, -0.0398913, -0.10934, 0.0674287, 0.0248883, -0.156223, -0.0310667, -0.245621, 0.0082392, -0.0221347, 0.010755, -0.0278086, 0.0122943, -0.0362756, -0.0023555, 0.0056806, -0.0392459, -0.0589829, -0.0485623, -0.00153612, 0.108168, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0380369, -0.580266, 0.011483, -0.0143166, 0.0290425, -0.00566892, -0.544955, 0.0107963, -0.0902663, 0.000936195, -0.340911, 0.0505111, -0.0105287, -0.0433341, -0.0896619, -0.0234929, -0.605726, 0.0317302, 0.0242908, 0.0146868, 0.0386746, -0.0211301, -0.0538678, 0.0563051, -0.0420617, 0.00420177, 0.0071399, 0.0135405, 0.0499374, -0.0292703, -0.0456727, 0.0194885, 0.261688, -0.00394304, -1.97821, -0.00341347, 0.0560567, 0.0105465, 0.000465311, 0.0165253, -0.0450004, -0.0360439, -0.0242854, -0.022221, 0.0101647, 0.0169255, -0.0488017, -0.0881409, -0.00344577, 0.049271, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.478399, 1.11213, 0.0555435, -0.247925, -0.317403, -0.4399, -0.113443, 0.163131, 0.435437, -2.40153, -0.085367, 0.238746, -0.43988, -1.57704, -0.528578, 1.09933, -2.10832, 0.709644, -0.908777, 0.172288, 0.012581, 1.36782, 0.0609381, -0.0516084, -1.14676, -0.221348, 0.357058, -0.952722, -0.00321124, 0.042836, -0.937659, 0.480657, 1.62654, -0.699657, 0.628552, 1.43311, 0.586832, -0.156685, -0.448598, -2.13141, 0.729117, -0.303936, -0.0355377, 0.372791, 0.144561, 0.103603, 0.786449, 0.807925, -2.07225, 0.230852, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0371963, 0.660953, -0.42978, -0.0241507, -0.100381, -0.0968207, -0.264351, -0.14703, 0.563504, 0.0742931, 0.0939806, 1.04325, 0.36283, -4.19494, -0.66932, 0.153644, 0.0598868, 0.567599, 0.313719, -0.431178, -0.41652, 1.58172, -0.118457, -0.278152, 0.570539, -0.69249, -0.0426958, -0.895395, 0.0332382, 0.176845, -0.850942, -1.24184, 1.39626, -0.0289744, 0.149766, 0.400705, 0.976197, -0.174827, -0.0649834, -0.828533, -0.166292, 0.167116, -0.0350803, 0.465406, -0.0439736, -0.177513, 0.36893, 0.925106, 0.0673907, 0.439352, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0186377, -0.996702, 0.064135, 0.0409475, -0.983195, 0.44996, 0.691132, 0.17436, 0.439962, -0.913194, -0.107193, 0.513493, 0.606698, 0.940793, -0.0909874, 0.279058, -0.3825, 0.793571, -0.0682184, 0.0348774, 0.272343, -0.0688781, 0.291176, 0.472839, 0.0774415, -0.204483, 0.172016, -0.449679, 0.0224675, -1.15251, -0.69154, 0.505536, 0.619775, 0.0358183, 0.523416, -0.26602, -0.374945, -0.0267528, -0.505425, -1.66025, 0.426467, 0.00182986, -2.2084, 0.341686, 0.104655, -0.465889, 0.324731, 0.690344, -0.169488, 0.335948, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0558881, -0.195573, -0.0212637, 0.00418723, -0.0155424, -0.0598023, -0.191016, 0.0233098, -0.12664, -2.45246, 0.109031, 0.296543, 0.117737, 2.27797, 0.0959276, 0.0859297, 0.543081, 0.181389, 0.260317, 0.0842646, -0.124854, 0.290568, 0.179738, 0.0267668, -2.28973, -1.44629, -0.00538957, -0.0476232, -0.0408108, -2.5635, -0.121463, 0.00281452, 0.316743, -0.0449353, -0.216359, 0.029123, 0.17077, -0.0404921, -0.26613, -3.00846, -0.0879433, 0.0122444, -0.097148, -1.46536, 0.0176542, -0.0239015, 0.0417313, 0.010873, 0.00340917, -0.00784347, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0247632, -0.106122, -0.0346297, -0.342825, -0.41731, -0.427519, -0.334916, -0.130929, 0.131995, -1.27981, 0.118321, -0.0456248, 0.364887, 1.70257, 0.0679688, -0.00716185, 0.43781, -0.134613, -0.0282014, -0.0735231, 0.0173761, 0.431666, 0.0126955, 0.569945, -0.0103389, -0.171156, 0.0590178, 0.00283023, -0.0288109, -0.0958176, -0.161364, 0.36612, 0.329281, 0.0449298, -0.121514, 0.00193557, 0.317925, 0.121165, -0.116266, -1.05946, -0.0193103, -0.00693385, -0.0130499, 0.0197165, 0.0180292, 0.0580752, -0.100067, 0.0193245, -0.492618, -0.314515, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.0239041, 0.00795744, 0.00209678, -0.0113519, -0.0416126, 0.0599743, 0.00394191, -0.0211539, 0.000619299, 0.00779789, -0.00346354, 0.0294715, -0.000978749, 0.268564, 0.0422202, 0.000435541, -0.137534, 0.00595717, 0.0271909, 0.00730356, 0.0024782, 0.0265516, -0.0271277, 0.0329048, -0.0113405, -0.0887782, -0.00641681, 0.012123, 0.0443226, -0.00185712, -0.0246771, 0.00991751, -0.0242694, -0.00427057, 0.012446, 0.00376881, 0.00462286, -0.0321166, -0.0614338, -0.00501834, -0.0243886, -0.0322684, -0.00739006, -0.119823, 0.00256954, 0.0115151, -0.00459238, 0.00686865, 0.00174597, -0.0144685, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-2.98325, -0.327786, -0.385298, 0.504421, -0.0536664, -0.465205, 1.80169, -1.52517, 1.68196, -0.276319, 0.608534, 0.435637, -2.64781, -0.390487, -2.93494, -0.0715481, -5.78253, 1.00365, 0.985976, 0.730504, 1.11946, -1.22295, 0.542494, 0.187622, 0.695906, 0.540859, 0.028504, -0.718279, 0.0113387, 0.00439653, -1.94349, 0.622207, -3.23432, -1.11367, 1.13216, -1.28693, 2.44503, 0.488007, 0.946854, -2.18063, 1.5155, 0.262788, 0.182595, -0.531642, -4.5861, 0.978881, -0.589485, 0.152665, 0.0901683, 2.65604, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03093, 0.01807, -0.01591, -0.00506, 0.1103, 0.001422, -0.10455, 0.0157, -0.1231, 0.02545, 0.01253, 0.02782, 0.005714, 1.6045, -0.01059, 0.022, 0.1284, -0.01058, 0.0853, -4.99e-05, 0.005585, 0.2278, -0.08746, 0.01918, -0.0369, 0.01942, 0.01055, 0.012566, 0.0441, -0.04272, -0.03436, 0.0571, 0.1539, 0.02055, -0.075, -0.01569, -0.04465, -0.003813, -0.01303, 0.005905, 0.02069, -0.012535, -0.02078, -0.04788, 0.0067, -0.005108, -0.004116, 0.02629, -0.0004044, -0.0093], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0948, 0.03787, 0.03766, -0.0172, 0.013, -0.03128, 0.05133, 0.009636, 0.05078, -0.02045, 0.007774, 0.03937, 0.05884, -1.071, 0.02129, -0.02232, -0.08264, 0.05487, 0.04337, 0.02144, 0.02267, 0.011284, -0.07837, 0.01077, 0.0556, 0.015335, 0.01472, 0.0327, 0.03195, -0.01682, -0.09015, 0.09125, 0.04874, -0.01765, -0.01444, 0.01135, 0.0802, -0.0131, -0.02538, 0.02386, -0.002739, -0.02745, -0.02682, -0.01551, 0.01884, 0.02838, 0.00381, -0.0061, -0.01578, 0.01513], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2367, 0.02173, 0.0961, -0.0861, -0.0538, -0.0941, 0.011826, -0.01587, -0.1674, -0.4585, -0.0016575, 0.0788, -0.1056, -0.04987, 0.1987, 0.083, -0.4048, 0.05078, 0.01455, 0.003439, 0.07184, 0.155, -0.07574, -0.2183, 0.175, 0.0502, 0.05994, -0.0864, 0.0002093, -0.05856, -0.2834, 0.1241, -0.1398, -0.03244, -2.5, 0.381, -0.0813, -0.001272, -0.132, -0.1675, -0.0953, 0.001028, -0.0629, 0.0526, -0.4316, -0.04697, 0.1921, -0.10834, 0.05167, 0.1071], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.913, -1.935, -0.7554, -1.185, -0.8994, -1.442, 0.0764, -0.2944, -0.9, -0.583, 0.463, -0.09894, -4.12, 0.4485, 0.1206, 0.606, 1.77, -3.123, -0.8115, 0.3074, -0.3916, 0.04755, -0.603, -0.06604, -1.469, -1.182, -2.562, -0.2896, -0.03665, 0.2346, -0.832, 0.6895, 1.773, -0.549, -0.5894, 0.6353, -1.695, 0.1332, -2.133, -1.888, -0.4888, -1.018, -0.799, 0.4714, 0.14, -3.633, 0.4194, -2.3, -0.0963, -1.347], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.02448, -0.01878, -0.004135, -0.00393, -0.011284, 0.05112, -0.004097, -0.00828, -0.0051, 0.002584, 0.005703, 0.02724, 0.02554, -0.1588, 0.0832, -0.0004768, -0.06058, -0.002262, 0.0958, 0.00916, 0.002645, 0.0338, -0.05237, 0.0495, -0.0003483, -0.001444, -0.01549, 0.00767, 0.014885, -0.013245, -0.0158, -0.02257, 0.1581, -0.00249, 0.006924, 0.006798, -0.02686, -0.004658, 0.0001761, -0.003527, 0.000612, 0.000756, -0.00686, 0.000457, 0.002768, 0.012344, 0.06046, 0.005875, -0.003094, 0.0003877], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.015335, -0.0761, 0.01536, -0.0706, 0.000383, 0.2832, -0.0809, 0.1675, -0.06696, -0.3357, 0.001235, 0.457, 0.1744, -1.124, -0.266, 0.048, 0.9814, 0.1646, 0.1958, 0.1456, 0.1786, -0.0691, -0.0318, -0.1537, 0.08167, 0.11365, -0.3977, -0.2375, -0.01692, -0.06244, -0.1766, 0.3228, -0.11676, -0.10724, 0.0324, 0.253, 0.1849, 0.0646, 0.00693, 0.02567, 0.1913, -0.0999, 0.001299, 0.10974, -0.11896, 0.0183, 0.012665, -0.248, -0.3914, -0.1678], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.3115, 1.217, -1.5625, -0.7793, -0.319, -1.813, 0.4902, -1.144, 0.9355, 1.058, -0.728, 0.0831, 0.618, -0.0458, 0.791, -1.996, -0.389, 0.3784, -0.2644, 0.268, 0.669, -0.4045, 0.2876, -0.5566, 1.545, -2.008, -2.557, -2.605, 0.0221, -0.286, -1.314, 0.941, 2.6, 0.3865, 0.7114, -0.3286, 0.846, -1.242, 0.8223, 0.571, 0.899, 0.0359, -0.933, -0.1095, 0.2212, -0.8193, 0.0878, 1.42, -0.762, 0.7417], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.1641, -0.2181, 0.004414, 0.03503, -0.05545, 0.1382, -0.218, 0.01546, 0.08295, 0.02933, 0.05896, -0.004047, 0.0318, -1.761, 0.08655, -1.25, -0.4573, -0.1427, -0.2524, -0.06775, 0.0492, -0.04053, 0.1953, 0.2296, 0.01642, -0.1283, -0.02882, -0.03244, -0.01857, 0.00647, -0.03036, -0.1236, 0.5527, -0.02838, 0.1506, 0.02509, -0.3809, 0.04156, -0.06, -0.004417, 0.0841, -0.04727, 2.3e-06, -0.05313, -0.03946, 0.05096, -0.03766, -0.09595, 0.02098, 0.08105], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03406, 0.1295, -0.2546, -0.03604, -0.02327, -0.11633, 0.04843, -0.1082, 0.0844, 0.07117, -0.03772, 0.03326, 0.05505, 1.639, 0.03253, -0.1191, 0.003523, 0.043, -0.01545, 0.03912, 0.06113, 0.08276, 0.01259, -0.00676, 0.138, -0.079, -0.2083, -0.2805, 0.01326, -0.03128, -0.1539, 0.0894, 0.225, 0.03033, 0.01881, -0.0621, 0.1168, -0.0666, 0.04263, 0.04382, 0.05353, -0.0787, -0.07935, 0.00985, 0.03268, -0.010666, 0.00538, 0.11584, -0.6343, 0.0865], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1342, -0.1317, -0.1271, -0.01836, -0.806, 0.5776, 0.4531, 0.01467, -0.1923, -0.964, -0.9004, -0.307, -0.8843, -1.239, 0.454, 0.06058, -4.58, 0.5273, -0.3755, 0.2578, -0.0701, -0.3066, -0.0822, 0.2776, 0.1396, 0.3198, 0.1611, -0.4817, -0.00984, 0.05475, -0.504, 0.828, 1.096, -0.8237, 0.5464, 0.2097, 0.0813, -0.357, -0.2344, 0.2644, 0.3735, 0.1383, -0.1963, -0.0863, -1.1875, 0.1438, 0.354, 0.3472, -0.03152, -0.4084], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.03333, -0.1421, 0.05453, -0.05472, -0.1002, -0.2351, 0.01143, -0.014046, -0.0832, -0.334, 0.0399, 0.1375, 0.2115, -0.1477, -0.02058, -0.007107, 0.362, 0.08374, 0.10205, -0.01811, -0.05734, 0.223, 0.03568, 0.1439, 0.0272, -0.03534, -0.1547, 0.03394, 0.005974, 0.003792, -0.06934, 0.0523, 0.02777, -0.5176, -0.09735, 0.0776, 0.01493, -0.01423, -0.02693, -0.5356, -0.02707, -0.01141, 0.04196, -0.03366, 0.01383, -0.01802, -0.1538, 0.01762, -1.407, 0.05698], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -4.363, 0.2327, -0.934, -0.337, -0.2417, -0.05115, 0.1998, 0.0001409, 1.0625, -0.4265, 0.6196, 1.243, 0.7583, -0.1907, -0.5503, 1.157, -7.45, 1.796, 0.491, -0.3955, -2.105, 1.023, 0.2532, 0.6304, -0.4812, 0.6475, -0.7036, -0.9775, 0.04117, 0.1343, -0.981, 1.559, -8.57, 0.707, 0.6846, 0.3877, -2.604, -0.6636, -0.4448, 0.01494, 0.928, 0.5337, -0.11346, 0.2583, -7.484, 0.1776, -4.71, 0.9517, -0.5205, -0.0863], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01541, 0.0782, -0.01108, 0.03513, -0.0566, 0.0217, -0.1231, -0.01799, -0.1761, 0.05618, 0.00279, 0.1576, 0.05573, 0.9683, 0.10535, 0.05212, 0.3252, -0.01075, 0.1538, 0.06976, 0.06824, 0.272, 0.0246, 0.0394, -0.1283, 0.0358, -0.09424, -0.01756, -0.02618, 0.03012, -0.05957, 0.07806, 0.1669, -0.0688, -0.1652, 0.0352, 0.03012, 0.0714, -0.01581, -0.001667, -0.0626, 0.05087, -0.1302, -0.0397, 0.00648, -0.02328, 0.1678, 0.02573, -0.02249, 0.1552], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005436, -0.2793, -0.01497, 0.006607, -0.096, -0.00957, -0.064, 0.01059, 0.10455, -0.04306, 0.02107, -0.02522, 0.1372, -0.2502, 0.1918, 0.02867, -0.0254, 0.04416, 0.03464, -0.01128, -0.0304, 0.0376, 0.00959, 0.1346, -0.0698, -0.11505, -0.00954, -0.0197, 0.01566, -1.904, -0.04434, -0.0772, 0.1078, 0.03004, 0.003597, 0.02716, -0.03738, -0.02321, -0.06244, 0.005272, 0.005035, -0.02544, 0.03162, 0.03568, -0.01015, -0.01385, 0.1616, -0.04407, 0.001681, 0.1521], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.67, 1.124, -0.379, -0.1714, 0.4812, -1.195, 0.894, -0.683, 0.87, 1.839, 1.444, 1.976, 0.3633, -0.3826, 0.9893, 0.2334, -4.957, 1.579, -1.069, 1.195, 2.053, -0.623, 0.784, -2.094, 1.727, -0.2429, -0.4275, -1.596, -0.01228, 0.601, -2.027, 2.6, 3.342, -6.188, 0.2502, -0.668, 1.978, 0.258, 0.6577, -0.687, 0.6675, -0.442, -0.1371, 1.208, -1.895, 0.3005, -0.918, 1.45, 0.52, 0.5186], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.09485, -0.4417, -0.05, 0.02118, -0.5977, 0.138, -0.02974, 0.03882, -0.1469, 0.0773, 0.06384, -0.09717, -0.1462, 1.658, -0.1071, 0.02838, -1.073, -0.0778, 0.03632, -0.07965, 0.1757, 0.1394, -0.39, 0.3857, 0.0129, 0.006947, -0.2032, -0.1407, -0.00022, -0.002184, -0.06152, -0.1169, 0.03085, 0.04398, 0.1981, -0.07745, 0.08594, -0.00615, 0.01706, -0.02301, 0.04153, 0.0678, 0.0324, -0.1418, -0.003332, 0.06088, 0.0703, -0.06366, -0.1825, 0.1271], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.05847, 0.10406, 0.06885, -0.02664, 0.04416, 0.01258, 0.0941, 0.02777, 0.0709, -0.02036, -0.05222, 0.09344, 0.1608, -0.312, -0.00821, -0.04788, 0.2339, 0.1074, 0.01935, 0.04898, 0.0371, 0.04434, -0.007935, -0.00961, 0.11884, 0.05908, 0.03096, 0.07245, 0.03323, -0.03305, -0.1849, 0.1129, 0.04297, 0.0413, -0.0772, 0.03345, 0.0536, -0.0362, -0.06525, 0.0521, -0.1222, -0.05527, -0.04538, -0.03238, 0.04538, 0.062, 0.0576, 0.049, -0.0354, 0.06665], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.272, 0.00502, 0.1255, 0.05453, -0.11566, 0.1234, -2.36, -0.10114, -0.2747, 0.178, 0.1614, -0.05084, 0.00955, -1.738, 0.00829, -0.01585, -0.005116, 0.4744, 0.3528, -0.06757, 0.1819, 0.3367, -0.0424, 0.1819, -0.0125, -0.0423, -0.1478, -0.0526, -0.04593, -0.4556, -0.2333, -0.1873, -0.4167, 0.01195, -0.0653, 0.1173, 0.0242, 0.0676, 0.06113, -0.02254, -0.4902, 0.2017, -0.174, 0.04828, -0.02556, 0.03052, -0.1384, 0.369, -1.487, 0.3245], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1829, 0.3486, -0.0619, -0.145, -0.0247, 0.2233, -0.05304, -0.295, 0.0686, 0.04257, 0.03024, -0.01402, 0.1108, 0.9146, 0.08057, 0.005486, -0.731, 0.138, 0.11365, 0.0461, 0.1465, 0.041, -1.108, 0.2583, -0.4014, 0.1138, -0.0627, -0.1051, -0.04385, -0.04657, -0.2764, 0.5005, 0.1327, 0.0688, -0.05902, -0.05023, -0.2054, -0.0807, -0.09924, -0.5767, -0.02922, -0.10114, -0.04617, -0.07007, -0.2346, -0.00712, 0.1757, 0.03406, 0.01039, -0.9556], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005745, 0.01746, 0.00824, -0.02058, -0.02544, -0.06366, 0.01357, -0.01622, -0.00921, 0.02118, -0.03552, -0.02217, -0.01863, -0.02608, -0.0273, 0.01921, 0.01557, -0.0459, -0.01237, -0.0476, -0.04272, -0.06036, 0.04324, -0.05002, 0.01205, 0.01501, -0.005753, -0.05057, -0.005383, -0.02116, -0.0835, -0.02109, -0.005795, -0.01062, 0.006916, -0.05826, -0.0322, -0.04633, 0.01665, -0.01061, -0.0495, 0.007076, -0.001644, -0.03616, -0.02733, -0.0007796, -0.01794, -0.0925, 0.01293, -0.00956], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3652, 0.502, -0.2455, -0.1216, -0.9224, -0.2705, 0.2776, -0.527, 0.2632, -0.7056, 0.7744, 0.1483, 0.8394, -0.03934, 0.569, -2.336, -3.205, 2.195, -0.4902, 0.178, 0.724, -3.012, -0.0649, -0.451, -0.2489, -0.4487, -3.94, -0.4817, -0.0317, -1.157, -1.516, 0.4734, 2.404, -2.846, -0.349, 0.9033, -2.178, 0.4753, 0.3503, -1.299, -0.3357, -0.253, 0.39, 0.1736, -1.589, -0.272, -1.1875, -0.788, -0.04877, 1.124], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04666, -0.0791, 0.003225, -0.01924, -0.0701, 0.1406, -0.007774, -0.001646, 0.01291, -0.0201, -0.0454, 0.05133, 0.02583, 0.593, 0.0213, 0.000584, 0.0299, 0.05704, 0.1248, 0.02162, 0.00754, -0.04, 0.09155, -0.0551, -0.2172, 0.0305, -0.0699, -0.0425, 0.00439, -0.0341, -0.04254, -0.02548, 0.007465, -0.01593, -0.04706, 0.02937, -0.1231, -0.02896, -0.0906, 0.003647, -0.0411, -0.06934, 0.01451, -0.0891, 0.001552, 0.006516, 0.00485, 0.0826, -2.443, 0.0578], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.737, -0.2947, -0.07935, -0.02942, -1.437, 0.002398, -0.5923, -0.0846, 0.2324, 0.02797, -0.02159, -0.37, -0.318, 0.2015, -0.2399, -0.8086, -6.016, -0.342, 0.208, 0.01674, 0.062, 0.0765, 0.3032, 0.017, 0.03058, 0.03726, -0.0967, -0.435, -0.02371, -0.0907, -0.05255, 0.05325, 0.3958, -0.3738, 0.1957, 0.01161, 0.1378, -0.0876, 0.03476, -0.006012, -0.0723, -0.2191, -0.04727, -0.0333, -0.04993, -0.1908, 0.235, -0.414, 0.02158, -0.03001], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.58, -0.1418, 0.12256, -0.266, -3.557, -2.229, 0.2174, -0.4756, -0.612, -0.2225, 0.11444, 0.386, -5.06, -0.01978, -2.201, -1.402, 0.0473, -0.6846, 1.993, -2.422, -3.533, -1.438, 0.335, -0.01767, -0.659, -0.597, -1.73, -0.929, -0.02852, -0.0375, -0.4941, 1.314, -0.798, -0.7783, 0.6387, 0.4382, 0.327, -0.1696, 0.259, 0.429, -0.636, -0.03111, -0.3354, 0.02716, -2.107, -2.045, -2.154, -0.6045, -1.026, -0.0159], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1056, -0.2017, 0.0368, -0.1863, -0.119, -0.1897, -0.428, -0.07025, -0.1257, -0.885, -0.004757, 0.133, 0.05783, 0.08435, 0.1686, -0.00353, -0.0344, 0.1472, 0.010345, 0.002474, 0.04218, 0.1027, 0.177, 0.3323, 0.0011, 0.05237, -0.7705, -0.03638, -0.01662, -0.2751, -0.2109, 0.2666, -0.2502, 0.04477, -0.0733, 0.04364, 0.2241, -0.02553, -0.05334, 0.04156, -0.0793, 0.0956, -0.303, 0.1304, -0.0375, 0.0705, 0.0875, -0.01436, -0.568, -0.3845], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1048, 0.05518, 0.01831, -0.2374, -0.1315, -0.0889, -0.08246, 0.007122, -0.0673, -0.1143, -0.01912, 0.05695, 0.139, -0.4888, 0.1619, -0.05142, -2.27, -0.010345, 0.06793, 0.02614, -0.0715, -0.8467, 0.0693, 0.234, 0.04584, 0.0395, -0.83, 0.001613, 0.004753, -2.496, -0.02054, -0.06192, -1.101, 0.0283, -0.1368, 0.02768, -0.02994, 0.02705, -0.003393, 0.02223, -0.02873, 0.02344, -0.8765, -0.00803, -0.01933, -0.0312, -0.03717, -0.1306, -0.6357, 0.03882], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.01776, 0.1198, 0.05063, 0.003914, -0.09283, -0.1508, 0.074, 0.01608, 0.000451, -1.612, -0.00916, 0.01593, 0.1649, 0.0627, -0.0657, 0.0537, 0.2717, -0.0664, 0.249, 0.02274, 0.0791, 0.2142, -0.2656, 0.06506, -0.1455, -0.0653, -0.0901, 0.01784, 0.00855, 0.0652, -0.06604, 0.03928, 0.1833, -0.05252, -0.1138, 0.1361, -0.3977, 0.02582, 0.07446, -0.6914, -0.15, -0.05508, -1.413, -0.099, -0.0258, -0.004383, 0.09326, 0.1299, -0.06866, 0.0279], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1451, 0.2676, 0.1779, -0.06665, 0.1147, 0.0399, 0.2288, 0.0748, 0.1825, -0.04587, -0.1444, 0.2355, 0.4072, -0.0405, -0.01434, -0.1256, 0.6675, 0.2715, 0.0626, 0.1278, 0.0987, 0.09717, 0.04202, -0.01933, 0.2832, 0.1516, 0.07825, 0.19, 0.03177, -0.08167, -0.4783, 0.2603, 0.1523, 0.1169, -0.2257, 0.09, 0.1109, -0.09204, -0.1691, 0.1387, -0.3728, -0.1445, -0.113, -0.099, 0.1181, 0.1542, 0.197, 0.1302, -0.11005, 0.1877], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.918, -0.2913, -0.02872, -2.285, -0.4475, -0.5493, 0.1215, -0.1285, -0.062, 0.2786, -0.05563, -0.3523, 0.3865, 2.05, 0.0765, -0.3389, 0.813, 0.0992, -0.25, -0.2467, -0.136, 0.181, -0.1656, 0.1542, 0.0893, -0.2251, -0.541, -0.06573, 0.002243, -0.0425, -0.121, -0.2854, -1.583, 0.00973, -0.5337, -0.198, -0.116, 0.005116, 0.0939, -2.79, 0.0661, -0.1335, -1.087, 0.12463, 0.00924, 0.02971, 0.1235, -0.4165, -3.262, 0.2676], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1979, 0.737, -4.375, -0.453, 0.534, -1.187, 0.708, -0.611, -0.10504, 0.926, 0.938, -1.219, 2.012, -1.448, -1.632, 1.316, -9.29, 1.835, 1.152, 0.311, 1.079, 3.371, 0.6113, -0.1501, -0.7725, 0.2251, -1.127, -1.508, -0.02757, 0.3088, -1.703, 1.708, 0.284, -3.816, 0.01775, 0.663, -0.4448, -0.2664, 0.1034, 0.378, 0.1842, 0.647, -0.324, -0.8384, 0.335, -0.975, -0.0492, 1.086, -0.5464, 0.2329], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.09784, 0.08167, 0.0086, -0.134, -0.0312, -0.02411, -0.1515, -0.0872, 0.006622, -0.1847, -0.0543, 0.1283, 0.12195, 0.373, 0.02696, 0.00825, 0.07446, 0.2273, 0.03091, 0.03525, -0.01373, -0.1884, 0.303, -0.01295, -0.03546, -0.0842, -0.2028, -0.06036, 0.0406, -0.503, -0.0936, -0.05743, 0.3982, 0.010574, -0.001195, -0.05573, 0.0492, 0.04205, -0.1003, -2.193, 0.04214, -0.03326, -2.22, -0.01132, -0.03796, -0.01959, 0.014114, -0.1113, -0.841, -0.04047], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03326, -0.215, -0.0503, -0.0445, 0.0919, 0.09296, -0.312, -0.0431, -0.1447, -0.2546, 0.00684, 0.01185, 0.1324, -0.1825, 0.1417, 0.02165, 0.3289, 0.001783, 0.11847, -0.03015, 0.0776, 0.294, -0.1244, -0.122, -0.3071, -0.08264, -0.2766, -0.01319, 0.007187, -0.0614, -0.03513, -0.1619, 0.2104, 0.002546, 0.1805, 0.06934, 0.04507, -0.0576, 0.06058, 0.001106, 0.04114, 0.1033, 0.12006, -0.004097, -0.00622, 0.004623, 0.0632, -0.0461, -0.05966, -1.226], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -3.303, 0.584, -1.105, 0.02974, -0.5444, -1.101, 1.408, -0.9707, 1.054, 1.89, 1.384, -0.861, -0.1536, -0.5356, -1.765, 0.4236, -2.383, -0.5625, 0.0434, 1.156, -1.269, -5.703, 0.794, -0.2388, 0.1855, 0.706, 0.1547, -1.411, -0.00208, -0.4763, -2.371, 0.87, 2.924, 0.2045, -0.5537, 0.05997, 0.7856, 0.00824, -0.1575, 0.08405, 0.6797, 1.064, -0.1106, 0.567, -2.148, 0.1185, 1.306, 2.08, -0.0383, 0.1412], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.06683, -0.237, 0.03595, 0.0906, -0.8125, -0.2551, -0.509, -0.0565, -0.3052, -0.088, -0.02016, 0.2202, 0.0313, 0.01429, 0.1412, 0.1692, -4.418, -0.177, -0.1522, 0.03958, -0.04446, -0.4302, 0.1976, 0.5566, -0.1891, 0.04166, -1.155, -0.2059, 0.0114, -1.16, -0.03387, 0.1814, 0.2101, -0.02127, -0.1276, 0.0622, 0.1057, 0.06335, -0.007683, 0.01645, -0.1848, 0.10834, -1.288, 0.04227, -0.1721, 0.03583, 0.2446, -0.01013, -0.11536, -0.3079], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.04697, -0.04825, -0.00623, 0.00897, -0.1774, -0.03644, -0.05966, -0.043, 0.03757, 0.01521, -0.05563, 0.0718, 0.0209, -1.891, 0.10895, -0.04498, -0.541, 0.05475, -0.01723, 0.03238, 0.05865, -0.04797, 0.0891, 0.1965, 0.02374, 0.00611, -0.05197, -0.00613, 0.004795, -0.0015135, -0.1066, 0.0811, -0.1113, 0.00236, -0.03708, 0.00883, 0.02032, -0.02278, -0.01636, 0.02577, -0.1443, -0.003704, -0.02946, -0.01499, 0.01375, 0.04126, 0.0867, 0.05173, -0.533, 0.02599], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.01311, -0.0978, -0.00473, -0.003471, -0.07733, 0.03256, -0.03035, -0.064, -0.02534, 0.0393, -0.03775, -0.0807, 0.0348, -0.0668, 0.03268, -0.004513, -0.1511, -0.02322, 0.1661, 0.01598, 0.00447, -0.0866, -0.1425, 0.1119, -0.1714, -0.05353, -0.03302, 0.002808, -0.03415, -0.00671, -0.02501, 0.0231, 0.0881, -0.01718, 0.0326, 0.01321, 0.0679, 0.01968, -0.01709, -0.002699, -0.0478, -0.04538, 0.0018, -0.05563, -0.009674, 0.0007133, 0.134, 0.01736, -1.006, -0.3633], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1713, -0.0846, -0.04187, -0.03522, 0.0781, 0.02983, -0.00174, -0.02599, -0.05817, -0.03348, -0.04178, -0.0112, 0.0589, -0.04758, 0.1443, -0.005383, 0.1721, -0.0411, -0.01054, -0.0354, 0.03223, -0.173, -0.1158, 0.1109, 0.0822, -0.04944, -0.03806, 0.042, 0.00784, 0.004894, -0.04688, 0.0805, -0.2874, 0.002695, 0.03168, 0.016, -0.1166, -0.03023, -0.0732, -0.01987, -0.05576, 0.00522, -0.02606, 0.05283, -0.00356, -0.012695, -0.03375, 0.014755, -1.161, -0.03558], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.3, 1.614, -5.617, 0.1697, 0.05725, -0.5566, 0.1361, -1.115, 0.6826, 0.7495, 0.658, 0.504, -0.3542, -0.966, -1.011, -0.464, 0.537, -0.01613, -0.4492, 0.832, 0.4456, 0.2961, 0.3523, 0.628, 1.277, -2.006, -1.196, -3.412, -0.04126, -0.2483, -1.471, 0.516, 2.605, 0.2075, 0.312, -2.434, 1.487, 0.0734, 0.4392, 0.2285, 0.609, -2.084, -0.5728, 0.102, 0.4895, 0.5166, 0.1523, 0.794, -0.1636, 1.476], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005535, -0.02452, 0.01418, -0.01653, 0.04486, 0.10187, -0.1262, -0.005707, -0.07227, 0.04578, 0.01859, 0.01791, 0.06232, 0.3362, -0.007328, 0.012405, 0.2494, 0.1398, 0.1655, 0.0158, -0.01665, -0.04245, 0.0993, 0.066, 0.0885, 0.03973, -0.0792, -0.03098, 0.01458, -0.002832, -0.06586, 0.01988, 0.1236, 0.01387, 0.02162, 0.01932, -0.0326, -0.01304, -0.0124, -0.05344, -0.0837, 0.04596, 0.0176, 0.02681, 0.01605, 0.01575, 0.01588, 0.1053, -0.5415, -0.02173], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2075, -0.375, -0.0343, -0.001577, 0.1488, 0.04938, -0.5835, -0.02579, -0.2153, -0.0101, -0.1433, 0.10126, 0.0419, 0.1647, -0.04175, 0.02547, -0.305, 0.01257, 0.0588, -0.009186, 0.03778, -0.01683, 0.4565, 0.0996, -0.1216, -0.004852, -0.0304, 0.0451, -0.01352, 0.01518, -0.1065, 0.1586, 0.09827, 0.02481, -0.9775, 0.005856, -0.3757, -0.03845, -0.0796, 0.0401, -0.2832, -0.02853, -0.06042, -0.02269, 0.01909, -0.09534, -0.0942, 0.03394, -0.1707, -0.0693], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.05563, -0.1302, 0.04105, -0.010124, -0.0695, -0.138, -0.06683, -0.02516, 0.02437, -0.0108, -0.02908, 0.0347, 0.05682, 1.233, 0.0394, -0.03085, 0.1462, 0.02771, 0.0561, -0.02107, 0.04932, -0.0627, -0.1361, 0.1713, 0.09845, 0.005867, -0.1361, -0.03473, -6.676e-05, -0.0566, -0.04367, 0.0968, -0.0302, 0.02211, -0.04828, 0.0278, 0.08307, 0.02843, 0.01052, 0.000862, -0.0461, 0.0336, 0.005108, 0.05, -0.02083, 0.02261, 0.1002, -0.02151, -1.434, -0.00967], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.06903, 0.1797, -0.015564, -0.01445, 0.1069, -0.0467, -0.5317, 0.02039, -0.0279, 0.0781, 0.0135, -0.03128, -0.03152, 1.172, -0.0452, 0.01379, 0.451, -0.00423, -0.01866, 0.009285, -0.01842, 0.2483, -0.02298, 0.003956, 0.01576, 0.0349, 0.01492, 0.013756, -0.04282, -0.03452, -0.0399, -0.1093, 0.06744, 0.02489, -0.1562, -0.03107, -0.2456, 0.00824, -0.02214, 0.01076, -0.0278, 0.01229, -0.0363, -0.002356, 0.00568, -0.03925, -0.059, -0.04855, -0.001536, 0.10815], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03802, -0.58, 0.01148, -0.01432, 0.02904, -0.00567, -0.545, 0.010796, -0.0903, 0.000936, -0.3408, 0.0505, -0.01053, -0.04333, -0.08966, -0.0235, -0.606, 0.03174, 0.02429, 0.01469, 0.03867, -0.02113, -0.05386, 0.0563, -0.04205, 0.0042, 0.00714, 0.01354, 0.04993, -0.02927, -0.0457, 0.01949, 0.2617, -0.003944, -1.979, -0.003414, 0.05606, 0.010544, 0.0004654, 0.01653, -0.045, -0.03604, -0.02429, -0.02222, 0.01016, 0.01692, -0.0488, -0.08813, -0.003447, 0.0493], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.4785, 1.112, 0.05554, -0.2479, -0.3174, -0.44, -0.11346, 0.1631, 0.4355, -2.402, -0.0854, 0.2388, -0.44, -1.577, -0.529, 1.1, -2.107, 0.7095, -0.9087, 0.1722, 0.01258, 1.368, 0.06094, -0.0516, -1.146, -0.2213, 0.3572, -0.9526, -0.003212, 0.04285, -0.9375, 0.4807, 1.627, -0.6997, 0.6284, 1.434, 0.587, -0.1567, -0.4485, -2.13, 0.729, -0.304, -0.03552, 0.3728, 0.1445, 0.1036, 0.7866, 0.808, -2.072, 0.2308], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0372, 0.661, -0.4297, -0.02415, -0.1004, -0.0968, -0.2644, -0.147, 0.5635, 0.0743, 0.094, 1.043, 0.3628, -4.195, -0.6694, 0.1537, 0.05988, 0.5674, 0.3137, -0.4312, -0.4165, 1.582, -0.11847, -0.278, 0.5703, -0.6924, -0.0427, -0.8955, 0.03323, 0.1769, -0.851, -1.242, 1.396, -0.02898, 0.1498, 0.4006, 0.976, -0.1748, -0.065, -0.8286, -0.1663, 0.1671, -0.0351, 0.4653, -0.04398, -0.1775, 0.369, 0.9253, 0.0674, 0.4395], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.01863, -0.9966, 0.06415, 0.04095, -0.9834, 0.45, 0.691, 0.1743, 0.44, -0.913, -0.1072, 0.5137, 0.607, 0.941, -0.091, 0.279, -0.3826, 0.7935, -0.06824, 0.03488, 0.2725, -0.06885, 0.2913, 0.473, 0.07745, -0.2045, 0.172, -0.4497, 0.02246, -1.152, -0.6914, 0.5054, 0.6196, 0.03583, 0.5234, -0.266, -0.375, -0.02675, -0.5054, -1.66, 0.4265, 0.00183, -2.209, 0.3418, 0.1047, -0.4658, 0.3247, 0.6904, -0.1694, 0.336], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.05588, -0.1956, -0.02127, 0.00419, -0.01554, -0.0598, -0.191, 0.02332, -0.1266, -2.453, 0.109, 0.2966, 0.11774, 2.277, 0.09595, 0.08594, 0.543, 0.1814, 0.2603, 0.0843, -0.1249, 0.2905, 0.1797, 0.02676, -2.29, -1.446, -0.00539, -0.04764, -0.0408, -2.564, -0.12146, 0.002815, 0.3167, -0.04492, -0.2163, 0.02913, 0.1708, -0.0405, -0.266, -3.008, -0.08795, 0.012245, -0.09717, -1.466, 0.01765, -0.0239, 0.04172, 0.01087, 0.003408, -0.00784], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.02477, -0.10614, -0.03464, -0.3428, -0.4172, -0.4275, -0.335, -0.131, 0.132, -1.28, 0.11835, -0.04562, 0.365, 1.702, 0.068, -0.00716, 0.4377, -0.1346, -0.0282, -0.07355, 0.01738, 0.4316, 0.012695, 0.57, -0.01034, -0.1711, 0.05902, 0.00283, -0.02881, -0.0958, -0.1614, 0.3662, 0.3293, 0.04492, -0.1215, 0.001936, 0.3179, 0.12115, -0.1163, -1.06, -0.01932, -0.006935, -0.01305, 0.01971, 0.01804, 0.05807, -0.10004, 0.01932, -0.4927, -0.3145], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.02391, 0.00796, 0.002096, -0.01135, -0.04163, 0.05997, 0.00394, -0.02115, 0.0006194, 0.007797, -0.003464, 0.02946, -0.000978, 0.2686, 0.0422, 0.0004356, -0.1376, 0.00596, 0.02719, 0.007305, 0.002478, 0.02655, -0.02713, 0.0329, -0.01134, -0.0888, -0.006416, 0.01212, 0.0443, -0.001857, -0.02467, 0.00992, -0.02428, -0.004272, 0.01244, 0.003769, 0.004623, -0.0321, -0.06143, -0.00502, -0.02438, -0.03226, -0.00739, -0.1198, 0.00257, 0.01151, -0.004593, 0.00687, 0.001746, -0.014465], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -2.982, -0.328, -0.3853, 0.5044, -0.05368, -0.465, 1.802, -1.525, 1.682, -0.2764, 0.6084, 0.4355, -2.648, -0.3904, -2.936, -0.07153, -5.78, 1.004, 0.986, 0.7305, 1.119, -1.223, 0.5425, 0.1876, 0.696, 0.541, 0.0285, -0.7183, 0.01134, 0.0044, -1.943, 0.622, -3.234, -1.113, 1.132, -1.287, 2.445, 0.488, 0.947, -2.18, 1.516, 0.2627, 0.1826, -0.5317, -4.586, 0.979, -0.5894, 0.1527, 0.09015, 2.656]] [0.225979, 0.641137, -1.12203, -0.258403, 0.279404, -3.15813, 3.81989, -0.838817, 0.337129, 1.48143, -0.387311, -4.85249, -1.46318, -0.622097, -5.73916, -0.539505, 0.355817, -3.20894, -0.669792, -0.0532718, -1.07259, 0.233222, 0.540133, 0.0347038, -1.80848, -1.00167, -1.97158, 1.99375, 0.667326, -2.41988, -0.262248, -2.32239, -6.11991, -2.56012, 0.243932, -0.225704, -0.123976, 1.85484, -0.492205, -0.572575, -0.530786, -0.593049, 0.0029525, -3.16795, -0.806849, -3.26406, -0.874765, -2.21406, 0.29674, -5.66597, 0.226, 0.641, -1.122, -0.2583, 0.2793, -3.158, 3.82, -0.839, 0.3372, 1.481, -0.3872, -4.85, -1.463, -0.622, -5.74, -0.5396, 0.3557, -3.209, -0.67, -0.05328, -1.072, 0.2333, 0.54, 0.0347, -1.809, -1.002, -1.972, 1.994, 0.6675, -2.42, -0.2622, -2.322, -6.12, -2.56, 0.2439, -0.2257, -0.12396, 1.8545, -0.4922, -0.5728, -0.531, -0.5933, 0.002953, -3.168, -0.8066, -3.264, -0.875, -2.215, 0.2966, -5.664] Affine [[0.0122767, 0.011308, 0.00802413, -0.0218188, 0.00319675, 0.0125322, 0.0114257, -0.00255323, -0.19602, 0.00588624, 0.0146445, 0.00852873, 0.0055578, 0.016655, 0.00837751, -0.00579741, -0.0923604, 0.000827512, -0.00723109, -0.0148582, 0.00993681, 0.0029669, -0.00786654, -0.00905188, -0.00637787, 0.000188001, 0.029826, 0.0348445, -0.0105056, 0.0074786, 0.0299888, 0.0272654, 0.00631335, -0.00640395, 0.0034457, 0.0128381, 0.00504764, 0.00753466, 0.00460818, -0.00852125, -0.000186634, -0.00705426, -0.00513893, 0.0143603, 0.00520082, 0.00872262, 0.00605885, 0.00447079, 0.00265729, 0.00543699, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0137882, -0.00240659, 0.0177903, 9.71692e-05, 0.0130397, 0.0161613, 0.000524016, 0.0158962, 0.00381941, -0.00114972, 0.0159186, 0.000975197, 0.0143296, 0.0128481, 0.000375721, 0.0085622, 0.00389359, 0.00386216, -0.00843075, -0.0210459, -0.00070852, -0.00328687, 0.000999868, 0.000684317, -0.0272917, 0.0206021, 0.00664966, -0.00121418, 0.00564371, 0.000300641, 0.0159826, 0.0235862, -0.000208657, -0.0149683, 0.0144311, 0.013267, 0.0152384, 0.000171705, 0.019005, -0.0149771, 0.00489971, -0.0116472, 0.00766545, 0.000158434, 0.00067949, 0.00173288, 0.00474157, 0.00660135, -0.00545564, -0.000239328, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0110372, 0.00325833, 0.00660415, -0.00219831, 0.0134385, -0.000334552, 0.000347947, 0.0136776, -0.0107638, 0.000426412, 0.0159823, 0.00114102, 0.0108758, 0.0144529, -0.000471512, -0.0013555, -0.000176958, -0.00353982, -0.0117788, -0.0143221, 0.00372341, 0.0382456, -0.000723518, -0.000346702, 0.00178803, -0.00408429, 0.0250151, -0.000140875, -0.000234128, 0.00134603, 0.0193501, 0.022014, 0.000635926, 0.00649425, -0.00514869, 0.01712, 0.00346974, -0.000444044, -0.00269448, -0.00523957, -0.00385362, -0.00908819, -0.00306574, 0.00141819, 0.00506691, 0.0105807, 0.00550354, 0.000320443, 0.0138631, 0.000129755, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.000427794, 0.00247098, 0.00318599, -0.000931611, 0.0187611, 0.0262813, -0.000246228, 0.000796719, 0.00444284, -0.000487216, -0.000408966, -0.000453513, 0.021514, 0.0113723, 0.000618181, 0.00972581, -5.62241e-05, 0.0137408, 0.00469408, 0.0203374, -0.00636208, -0.00314665, -0.000494459, -6.86316e-05, -0.0289031, 0.0087665, 0.0191301, -0.000599625, 0.00975496, -0.000393373, 0.0178813, 0.0216552, -0.00198573, -0.0172266, -0.0052339, 0.0100204, -0.00216445, -0.000529878, 0.00426757, -0.00261175, 0.0227263, 0.000517605, -0.00684216, 5.97784e-05, -0.000151559, 0.0126098, -0.0109503, 0.0197202, -0.0130717, -0.000811515, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.00589371, 0.0030568, 0.00255281, -0.00229315, 0.0151719, -0.00273326, 0.000961601, 0.0124695, -0.0116233, 0.00251327, 0.00636245, -0.000334227, -0.00662235, 0.0122744, 0.000325531, -0.000874993, 0.000850324, -0.00292568, -0.00776242, -0.00608874, 0.00444306, 0.04261, 0.000312545, -0.000660786, 0.00672582, 0.00305449, 0.0344578, -8.23427e-05, 0.00252333, 0.00147089, 0.0331118, 0.0295184, -0.000225769, 0.00357071, -0.00942575, 0.0151026, -0.00040097, -0.000141207, -0.00308233, -0.00190664, -0.00485058, -0.00449136, -0.00714107, 0.00235382, 0.00533209, 0.00984751, 0.0165893, -0.00793129, 0.00953482, 0.00126345, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.012276, 0.01131, 0.008026, -0.02182, 0.003197, 0.012535, 0.01143, -0.002554, -0.196, 0.005886, 0.01464, 0.00853, 0.005558, 0.01666, 0.00838, -0.0058, -0.09235, 0.0008273, -0.007233, -0.014854, 0.00993, 0.002968, -0.007866, -0.00905, -0.00638, 0.000188, 0.02983, 0.03485, -0.010506, 0.007477, 0.02998, 0.02727, 0.006313, -0.006405, 0.003447, 0.01284, 0.005047, 0.007534, 0.00461, -0.00852, -0.0001867, -0.007053, -0.00514, 0.01436, 0.0052, 0.00872, 0.006058, 0.00447, 0.002657, 0.005436], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01379, -0.002407, 0.01779, 9.716e-05, 0.01304, 0.01616, 0.000524, 0.0159, 0.003819, -0.00115, 0.01591, 0.000975, 0.01433, 0.01285, 0.0003757, 0.00856, 0.003893, 0.003862, -0.00843, -0.02104, -0.0007086, -0.003286, 0.000999, 0.0006843, -0.0273, 0.0206, 0.00665, -0.001214, 0.005642, 0.0003006, 0.01598, 0.02359, -0.0002086, -0.01497, 0.014435, 0.01327, 0.015236, 0.0001717, 0.01901, -0.01498, 0.004898, -0.01165, 0.007664, 0.0001584, 0.0006795, 0.001733, 0.00474, 0.006603, -0.005455, -0.0002394], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01104, 0.003258, 0.006603, -0.0022, 0.013435, -0.0003345, 0.0003479, 0.01368, -0.010765, 0.0004265, 0.01598, 0.001141, 0.01088, 0.01445, -0.0004716, -0.001355, -0.0001769, -0.00354, -0.01178, -0.01432, 0.003723, 0.03824, -0.0007234, -0.0003467, 0.001788, -0.004086, 0.02501, -0.0001409, -0.0002341, 0.001346, 0.01935, 0.02202, 0.000636, 0.006493, -0.00515, 0.01712, 0.00347, -0.000444, -0.002695, -0.00524, -0.003853, -0.00909, -0.003065, 0.001418, 0.005066, 0.01058, 0.005505, 0.0003204, 0.01386, 0.0001297], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0004277, 0.002472, 0.003185, -0.0009317, 0.01877, 0.02628, -0.0002463, 0.000797, 0.004444, -0.0004873, -0.000409, -0.0004535, 0.02151, 0.011375, 0.000618, 0.00973, -5.62e-05, 0.01374, 0.004696, 0.02034, -0.006363, -0.003147, -0.0004945, -6.86e-05, -0.0289, 0.008766, 0.01913, -0.0006, 0.00976, -0.0003934, 0.01788, 0.02165, -0.001986, -0.01723, -0.005234, 0.01002, -0.002165, -0.00053, 0.00427, -0.002611, 0.02272, 0.0005174, -0.006844, 5.98e-05, -0.0001515, 0.01261, -0.01095, 0.01971, -0.01307, -0.0008116], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005894, 0.003057, 0.002552, -0.002293, 0.015175, -0.002733, 0.000962, 0.01247, -0.01162, 0.002514, 0.006363, -0.0003343, -0.006622, 0.012276, 0.0003254, -0.000875, 0.00085, -0.002926, -0.007763, -0.00609, 0.004444, 0.0426, 0.0003126, -0.000661, 0.006725, 0.003054, 0.03445, -8.23e-05, 0.002523, 0.001471, 0.0331, 0.02953, -0.0002258, 0.00357, -0.00942, 0.01511, -0.000401, -0.0001413, -0.003082, -0.001906, -0.004852, -0.00449, -0.00714, 0.002354, 0.005333, 0.00985, 0.01659, -0.007935, 0.00954, 0.001264]] [-0.0206515, -0.0190316, 0.0181379, -0.0184323, 0.018364, -0.02065, -0.01903, 0.01814, -0.01843, 0.01837]

17,381.863636

74,457

0.553184

104,247

382,401

2.0292

0.181262

0.481417

0.714921

0.943698

0.243966

0.243758

0

0.640322

0.136289

382,401

21

74,458

18,209.571429

0.000151

0

0.285714

0

1

0

true

0

null

1

0

1

0

1

0

null

0

1

0

8

b6cf3581fafaf568158df310530605422758047c

10,047

py

Python

src/genie/libs/parser/iosxe/c9300/tests/ShowSystemIntegrityAllMeasurementNonce/cli/equal/golden_output1_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/c9300/tests/ShowSystemIntegrityAllMeasurementNonce/cli/equal/golden_output1_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/c9300/tests/ShowSystemIntegrityAllMeasurementNonce/cli/equal/golden_output1_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

expected_output = { "bay": "0", "chassis": { 1: { "boot_hashes": { "17.9.0.3r": "CD187702DD2CB79BC1B8E62BF8EF596E9227F76254E19BE0F5A0AB9E9D9A3F1FF643FA1AE9354037355119E974B62903FBD045C152EB66C19412FA78FB13AE17", "MA0081R06.1307262016": "80F5629CB70F2B4ABD89F118BF402A105E82E0A8A0AE5E7CD9E4D21F898CEFF5", }, "os": { "hashes": { "cat9k-cc_srdriver.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "EEB0F9960AF3450B8F49B91C400CF91AE3C76C46B1CA1092E5312969507C6580783BF3E8CC333C805C1B843864150D16C56E9B0B513F53D8707555CFCF061383", "cat9k-espbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "70F46A04D0A267D4441AD536FB3664FA0A88A6E54AADDC14E4408CA0AA156C6799E04D9E782D5DAB39A59FE9BBED69B8061B6061A41D590DFD209AAB8DD4C953", "cat9k-guestshell.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "A98215AEE09183E88D46F9BAF454E40B8E226FDA321ABFE66F27DDB834FA6941024314FE1EFE6FD09E456E5076B6D8971841F6E2CD03583A96A89D4E800F1FB7", "cat9k-rpbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "8120F1275A4838D69B38B0FD99E874D215536A9434511AE4D9AFC65791DBD498D6CE03AB737A213A4749D9FEB5ADC97AA0CE634A6A1450EA2F961B49FF0F8CF2", "cat9k-sipbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "05E581DCC6F9A11F8220B17302C912ECFF8D1A1C814D8108F269754204477414A1B3C117C1E7E9983252E9573DEE61C3BA622372F374827FB65CD9D08340B33B", "cat9k-sipspa.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "514281D7CD755DA2DBA709C13D0A8853CCF6826BB4D6C77F23CE65668DAD7BC85FB57FB626ED4E1267B68932FE097CCDB157D9803BF5C947DB2B1EDB51E19309", "cat9k-srdriver.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "49B5BC58094BBAB7C388AA915C40AAF79DC4FBA0C6B4D80F0FDE28689AE893FEE61E66467C9A7CB20377AD9900250BD1625D0931A275BF3331A0D43561DCAEE1", "cat9k-webui.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "A7EF61F6EA1690DE96735FD7ED804A8E6D52A5A27826B4B219B5CCB6F455FC0B885C96C836FDDDB60AE51C1CD7315699536B9369D84C30677E604FCD5A862165", "cat9k-wlc.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "6A1BFFDE02EF9E9EC6D0A9DAEC01E65ED4B4A20A04EA1C360279BFC693E1E2E1857A7A92122BCB589FD751C517DE51843767D2BBE4909AFAC94805449FA3DC63", }, "version": "BLD_POLARIS_DEV_LATEST_20220302_153046", }, "platform": "C9300-48UXM", "registers": { "PCR0": "7AE45909A7AD1255CE9FE4E4278837C05EC0C7B7DC0F89B9BA8FD7F361AF4E34", "PCR8": "30A6A0DF43D757CF620F2ECE10BE7FA55162FEDA0982F1A7CEF70F03C6C4B8CD", }, "signature": { "value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version": 1, }, }, 2: { "boot_hashes": { "17.9.0.3r": "CD187702DD2CB79BC1B8E62BF8EF596E9227F76254E19BE0F5A0AB9E9D9A3F1FF643FA1AE9354037355119E974B62903FBD045C152EB66C19412FA78FB13AE17", "MA0081R06.1307262016": "80F5629CB70F2B4ABD89F118BF402A105E82E0A8A0AE5E7CD9E4D21F898CEFF5", }, "os": { "hashes": { "cat9k-cc_srdriver.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "EEB0F9960AF3450B8F49B91C400CF91AE3C76C46B1CA1092E5312969507C6580783BF3E8CC333C805C1B843864150D16C56E9B0B513F53D8707555CFCF061383", "cat9k-espbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "70F46A04D0A267D4441AD536FB3664FA0A88A6E54AADDC14E4408CA0AA156C6799E04D9E782D5DAB39A59FE9BBED69B8061B6061A41D590DFD209AAB8DD4C953", "cat9k-guestshell.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "A98215AEE09183E88D46F9BAF454E40B8E226FDA321ABFE66F27DDB834FA6941024314FE1EFE6FD09E456E5076B6D8971841F6E2CD03583A96A89D4E800F1FB7", "cat9k-rpbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "8120F1275A4838D69B38B0FD99E874D215536A9434511AE4D9AFC65791DBD498D6CE03AB737A213A4749D9FEB5ADC97AA0CE634A6A1450EA2F961B49FF0F8CF2", "cat9k-sipbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "05E581DCC6F9A11F8220B17302C912ECFF8D1A1C814D8108F269754204477414A1B3C117C1E7E9983252E9573DEE61C3BA622372F374827FB65CD9D08340B33B", "cat9k-sipspa.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "514281D7CD755DA2DBA709C13D0A8853CCF6826BB4D6C77F23CE65668DAD7BC85FB57FB626ED4E1267B68932FE097CCDB157D9803BF5C947DB2B1EDB51E19309", "cat9k-srdriver.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "49B5BC58094BBAB7C388AA915C40AAF79DC4FBA0C6B4D80F0FDE28689AE893FEE61E66467C9A7CB20377AD9900250BD1625D0931A275BF3331A0D43561DCAEE1", "cat9k-webui.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "A7EF61F6EA1690DE96735FD7ED804A8E6D52A5A27826B4B219B5CCB6F455FC0B885C96C836FDDDB60AE51C1CD7315699536B9369D84C30677E604FCD5A862165", "cat9k-wlc.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "6A1BFFDE02EF9E9EC6D0A9DAEC01E65ED4B4A20A04EA1C360279BFC693E1E2E1857A7A92122BCB589FD751C517DE51843767D2BBE4909AFAC94805449FA3DC63", }, "version": "BLD_POLARIS_DEV_LATEST_20220302_153046", }, "platform": "C9300-48UXM", "registers": { "PCR0": "7AE45909A7AD1255CE9FE4E4278837C05EC0C7B7DC0F89B9BA8FD7F361AF4E34", "PCR8": "30A6A0DF43D757CF620F2ECE10BE7FA55162FEDA0982F1A7CEF70F03C6C4B8CD", }, "signature": { "value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version": 1, }, }, 3: { "boot_hashes": { "17.9.0.3r": "CD187702DD2CB79BC1B8E62BF8EF596E9227F76254E19BE0F5A0AB9E9D9A3F1FF643FA1AE9354037355119E974B62903FBD045C152EB66C19412FA78FB13AE17", "MA0081R06.1307262016": "80F5629CB70F2B4ABD89F118BF402A105E82E0A8A0AE5E7CD9E4D21F898CEFF5", }, "os": { "hashes": { "cat9k-cc_srdriver.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "EEB0F9960AF3450B8F49B91C400CF91AE3C76C46B1CA1092E5312969507C6580783BF3E8CC333C805C1B843864150D16C56E9B0B513F53D8707555CFCF061383", "cat9k-espbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "70F46A04D0A267D4441AD536FB3664FA0A88A6E54AADDC14E4408CA0AA156C6799E04D9E782D5DAB39A59FE9BBED69B8061B6061A41D590DFD209AAB8DD4C953", "cat9k-guestshell.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "A98215AEE09183E88D46F9BAF454E40B8E226FDA321ABFE66F27DDB834FA6941024314FE1EFE6FD09E456E5076B6D8971841F6E2CD03583A96A89D4E800F1FB7", "cat9k-rpbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "8120F1275A4838D69B38B0FD99E874D215536A9434511AE4D9AFC65791DBD498D6CE03AB737A213A4749D9FEB5ADC97AA0CE634A6A1450EA2F961B49FF0F8CF2", "cat9k-sipbase.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "05E581DCC6F9A11F8220B17302C912ECFF8D1A1C814D8108F269754204477414A1B3C117C1E7E9983252E9573DEE61C3BA622372F374827FB65CD9D08340B33B", "cat9k-sipspa.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "514281D7CD755DA2DBA709C13D0A8853CCF6826BB4D6C77F23CE65668DAD7BC85FB57FB626ED4E1267B68932FE097CCDB157D9803BF5C947DB2B1EDB51E19309", "cat9k-srdriver.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "49B5BC58094BBAB7C388AA915C40AAF79DC4FBA0C6B4D80F0FDE28689AE893FEE61E66467C9A7CB20377AD9900250BD1625D0931A275BF3331A0D43561DCAEE1", "cat9k-webui.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "A7EF61F6EA1690DE96735FD7ED804A8E6D52A5A27826B4B219B5CCB6F455FC0B885C96C836FDDDB60AE51C1CD7315699536B9369D84C30677E604FCD5A862165", "cat9k-wlc.BLD_POLARIS_DEV_LATEST_20220302_153046.SSA.pkg": "6A1BFFDE02EF9E9EC6D0A9DAEC01E65ED4B4A20A04EA1C360279BFC693E1E2E1857A7A92122BCB589FD751C517DE51843767D2BBE4909AFAC94805449FA3DC63", }, "version": "BLD_POLARIS_DEV_LATEST_20220302_153046", }, "platform": "C9300-48UXM", "registers": { "PCR0": "7AE45909A7AD1255CE9FE4E4278837C05EC0C7B7DC0F89B9BA8FD7F361AF4E34", "PCR8": "30A6A0DF43D757CF620F2ECE10BE7FA55162FEDA0982F1A7CEF70F03C6C4B8CD", }, "signature": { "value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version": 1, }, }, }, "fru": "fru-rp", "node": "0", "slot": "0", }

104.65625

540

0.791181

411

10,047

18.958637

0.153285

0.038501

0.050051

0.073152

0.793891

0

0.49953

0.15318

10,047

95

541

105.757895

0.416314

0

0.663158

0

0.801433

0.765004

0

1

0

1

0

false

0

1

null

0

1

0

1

0

1

0

1

null

1

0

12

b6f13cb2b6d222678cbd28364cab57b746b2549d

52,122

py

Python

standard_neural_network_architectures.py

AntreasAntoniou/FewShotContinualLearning

819b9cc26ef9d2360a040c51f17958e1b8dba8fd

[ "MIT" ]

34

2020-04-16T06:19:45.000Z

2022-02-10T02:02:59.000Z

standard_neural_network_architectures.py

AntreasAntoniou/FewShotContinualLearning

819b9cc26ef9d2360a040c51f17958e1b8dba8fd

[ "MIT" ]

3

2020-08-13T03:41:43.000Z

2020-08-25T11:24:33.000Z

standard_neural_network_architectures.py

AntreasAntoniou/FewShotContinualLearning

819b9cc26ef9d2360a040c51f17958e1b8dba8fd

[ "MIT" ]

4

2020-06-23T02:50:59.000Z

2021-07-12T01:47:06.000Z

from collections import OrderedDict import numpy as np import torch import torch.nn as nn import torch.nn.functional as F class Conv2dNormLeakyReLU(nn.Module): def __init__(self, input_shape, num_filters, kernel_size, dilation=1, stride=1, groups=1, padding=0, use_bias=False, normalization=True, weight_attention=False): super(Conv2dNormLeakyReLU, self).__init__() self.input_shape = list(input_shape) self.num_filters = num_filters self.kernel_size = kernel_size self.stride = stride self.padding = padding self.use_bias = use_bias self.normalization = normalization self.dilation = dilation self.weight_attention = weight_attention self.groups = groups self.num_mac = None self.layer_dict = nn.ModuleDict() self.build_network() def build_network(self): x = torch.ones(self.input_shape) out = x self.layer_dict['conv'] = nn.Conv2d(in_channels=out.shape[1], out_channels=self.num_filters, kernel_size=self.kernel_size, stride=self.stride, padding=self.padding, dilation=self.dilation, groups=self.groups, bias=self.use_bias) out = self.layer_dict['conv'].forward(out) if self.normalization: self.layer_dict['norm_layer'] = nn.BatchNorm2d(num_features=out.shape[1]) out = self.layer_dict['norm_layer'](out) self.layer_dict['relu'] = nn.LeakyReLU() out = self.layer_dict['relu'](out) print(out.shape) def forward(self, x): out = x out = self.layer_dict['conv'].forward(out) if self.normalization: out = self.layer_dict['norm_layer'](out) out = self.layer_dict['relu'](out) return out class DenseNetActivationNormNetwork(nn.Module): def __init__(self, im_shape, num_filters, num_stages, num_blocks_per_stage, dropout_rate, average_pool_output, reduction_rate, conv_type): """ Builds a multilayer convolutional network. It also provides functionality for passing external parameters to be used at inference time. Enables inner loop optimization readily. :param im_shape: The input image batch shape. :param num_output_classes: The number of output classes of the network. :param args: A named tuple containing the system's hyperparameters. :param device: The device to run this on. :param meta_classifier: A flag indicating whether the system's meta-learning (inner-loop) functionalities should be enabled. """ super(DenseNetActivationNormNetwork, self).__init__() self.input_shape = list(im_shape) self.num_filters = num_filters self.num_stages = num_stages self.dropout_rate = dropout_rate self.reduction_rate = reduction_rate self.average_pool_output = average_pool_output self.conv_type = conv_type # self.num_output_classes = num_output_classes self.num_blocks_per_stage = num_blocks_per_stage self.layer_dict = nn.ModuleDict() self.build_network() def build_network(self): """ Builds the network before inference is required by creating some dummy inputs with the same input as the self.im_shape tuple. Then passes that through the network and dynamically computes input shapes and sets output shapes for each layer. """ x = torch.zeros(self.input_shape) out = x self.layer_dict['stem_conv'] = self.conv_type(input_shape=out.shape, num_filters=64, kernel_size=3, padding=1) out = self.layer_dict['stem_conv'](out) for i in range(self.num_stages): for j in range(self.num_blocks_per_stage): self.layer_dict['conv_bottleneck_{}_{}'.format(i, j)] = self.conv_type(input_shape=out.shape, num_filters=self.num_filters, kernel_size=1, padding=0) cur = self.layer_dict['conv_bottleneck_{}_{}'.format(i, j)](out) self.layer_dict['conv_{}_{}'.format(i, j)] = self.conv_type(input_shape=cur.shape, num_filters=self.num_filters, kernel_size=3, padding=1) cur = self.layer_dict['conv_{}_{}'.format(i, j)](cur) cur = F.dropout(cur, p=self.dropout_rate, training=True) out = torch.cat([out, cur], dim=1) out = F.avg_pool2d(out, 2) print(out.shape) self.layer_dict['transition_layer_{}'.format(i)] = self.conv_type(input_shape=out.shape, num_filters=int(out.shape[ 1] * self.reduction_rate), kernel_size=1, padding=0) out = self.layer_dict['transition_layer_{}'.format(i)](out) if self.average_pool_output: out = F.avg_pool2d(out, out.shape[2]) out = out.view(out.shape[0], -1) else: out = F.adaptive_avg_pool2d(out, output_size=(5, 5)) # self.layer_dict['adaptor_layer'] = Conv2dNormLeakyReLU(input_shape=out.shape, # num_filters=64, # kernel_size=1, padding=0) # out = self.layer_dict['adaptor_layer'].forward(out) print(out.shape) def forward(self, x, dropout_training): """ Forward propages through the network. If any params are passed then they are used instead of stored params. :param x: Input image batch. :param num_step: The current inner loop step number :param params: If params are None then internal parameters are used. If params are a dictionary with keys the same as the layer names then they will be used instead. :param training: Whether this is training (True) or eval time. :param backup_running_statistics: Whether to backup the running statistics in their backup store. Which is then used to reset the stats back to a previous state (usually after an eval loop, when we want to throw away stored statistics) :return: Logits of shape b, num_output_classes. """ out = x out = self.layer_dict['stem_conv'](out) for i in range(self.num_stages): for j in range(self.num_blocks_per_stage): cur = self.layer_dict['conv_bottleneck_{}_{}'.format(i, j)](out) cur = self.layer_dict['conv_{}_{}'.format(i, j)](cur) cur = F.dropout(cur, p=self.dropout_rate, training=dropout_training) out = torch.cat([out, cur], dim=1) out = F.avg_pool2d(out, 2) out = self.layer_dict['transition_layer_{}'.format(i)](out) if self.average_pool_output: out = F.avg_pool2d(out, out.shape[2]) out = out.view(out.shape[0], -1) else: out = F.adaptive_avg_pool2d(out, output_size=(5, 5)) # out = self.layer_dict['adaptor_layer'].forward(out) return out class SqueezeExciteDenseNet(nn.Module): def __init__(self, im_shape, num_filters, num_stages, num_blocks_per_stage, dropout_rate, average_pool_output, reduction_rate, output_spatial_dim, use_channel_wise_attention): """ Builds a multilayer convolutional network. It also provides functionality for passing external parameters to be used at inference time. Enables inner loop optimization readily. :param im_shape: The input image batch shape. :param num_output_classes: The number of output classes of the network. :param args: A named tuple containing the system's hyperparameters. :param device: The device to run this on. :param meta_classifier: A flag indicating whether the system's meta-learning (inner-loop) functionalities should be enabled. """ super(SqueezeExciteDenseNet, self).__init__() self.input_shape = list(im_shape) self.num_filters = num_filters self.num_stages = num_stages self.dropout_rate = dropout_rate self.reduction_rate = reduction_rate self.average_pool_output = average_pool_output # self.num_output_classes = num_output_classes self.num_blocks_per_stage = num_blocks_per_stage self.output_spatial_dim = output_spatial_dim self.conv_type = Conv2dNormLeakyReLU self.layer_dict = nn.ModuleDict() self.use_channel_wise_attention = use_channel_wise_attention self.build_network() def build_network(self): """ Builds the network before inference is required by creating some dummy inputs with the same input as the self.im_shape tuple. Then passes that through the network and dynamically computes input shapes and sets output shapes for each layer. """ x = torch.zeros(self.input_shape) out = x self.layer_dict['stem_conv'] = Conv2dNormLeakyReLU(input_shape=out.shape, num_filters=64, kernel_size=3, padding=1, groups=1) out = self.layer_dict['stem_conv'](out) for i in range(self.num_stages): for j in range(self.num_blocks_per_stage): if self.use_channel_wise_attention: attention_network_out = F.avg_pool2d(out, out.shape[-1]).squeeze() self.layer_dict['channel_wise_attention_output_fcc_{}_{}'.format(j, i)] = nn.Linear( in_features=attention_network_out.shape[1], out_features=out.shape[1], bias=True) channel_wise_attention_regions = self.layer_dict[ 'channel_wise_attention_output_fcc_{}_{}'.format(j, i)].forward(attention_network_out) channel_wise_attention_regions = F.sigmoid(channel_wise_attention_regions) out = out * channel_wise_attention_regions.unsqueeze(2).unsqueeze(2) self.layer_dict['conv_bottleneck_{}_{}'.format(i, j)] = self.conv_type(input_shape=out.shape, num_filters=self.num_filters, kernel_size=1, padding=0) cur = self.layer_dict['conv_bottleneck_{}_{}'.format(i, j)](out) self.layer_dict['conv_{}_{}'.format(i, j)] = self.conv_type(input_shape=cur.shape, num_filters=self.num_filters, kernel_size=3, padding=1, groups=1) cur = self.layer_dict['conv_{}_{}'.format(i, j)](cur) cur = F.dropout(cur, p=self.dropout_rate, training=True) out = torch.cat([out, cur], dim=1) out = F.avg_pool2d(out, 2) print(out.shape) self.layer_dict['transition_layer_{}'.format(i)] = Conv2dNormLeakyReLU(input_shape=out.shape, num_filters=int(out.shape[ 1] * self.reduction_rate), kernel_size=1, padding=0) out = self.layer_dict['transition_layer_{}'.format(i)](out) if self.average_pool_output: out = F.avg_pool2d(out, out.shape[2]) out = out.view(out.shape[0], -1) else: out = F.adaptive_avg_pool2d(out, output_size=(self.output_spatial_dim, self.output_spatial_dim)) print(out.shape) def forward(self, x, dropout_training): """ Forward propages through the network. If any params are passed then they are used instead of stored params. :param x: Input image batch. :param num_step: The current inner loop step number :param params: If params are None then internal parameters are used. If params are a dictionary with keys the same as the layer names then they will be used instead. :param training: Whether this is training (True) or eval time. :param backup_running_statistics: Whether to backup the running statistics in their backup store. Which is then used to reset the stats back to a previous state (usually after an eval loop, when we want to throw away stored statistics) :return: Logits of shape b, num_output_classes. """ out = x out = self.layer_dict['stem_conv'](out) for i in range(self.num_stages): for j in range(self.num_blocks_per_stage): # out_channels = F.avg_pool2d(out, out.shape[-1]).squeeze() if self.use_channel_wise_attention: out_channels = F.avg_pool2d(out, out.shape[-1]).squeeze() channel_wise_attention_regions = self.layer_dict[ 'channel_wise_attention_output_fcc_{}_{}'.format(j, i)].forward(out_channels) channel_wise_attention_regions = F.sigmoid(channel_wise_attention_regions) out = out * channel_wise_attention_regions.unsqueeze(2).unsqueeze(2) cur = self.layer_dict['conv_bottleneck_{}_{}'.format(i, j)](out) cur = self.layer_dict['conv_{}_{}'.format(i, j)](cur) cur = F.dropout(cur, p=self.dropout_rate, training=dropout_training) out = torch.cat([out, cur], dim=1) out = F.avg_pool2d(out, 2) out = self.layer_dict['transition_layer_{}'.format(i)](out) if self.average_pool_output: out = F.avg_pool2d(out, out.shape[2]) out = out.view(out.shape[0], -1) else: out = F.adaptive_avg_pool2d(out, output_size=(self.output_spatial_dim, self.output_spatial_dim)) return out class Conv1dNormLeakyReLU(nn.Module): def __init__(self, input_shape, num_filters, kernel_size, dilation=1, stride=1, groups=1, padding=0, use_bias=False, normalization=True): super(Conv1dNormLeakyReLU, self).__init__() self.input_shape = list(input_shape) self.num_filters = num_filters self.kernel_size = kernel_size self.stride = stride self.padding = padding self.use_bias = use_bias self.normalization = normalization self.dilation = dilation self.groups = groups self.layer_dict = nn.ModuleDict() self.build_network() def build_network(self): x = torch.ones(self.input_shape) out = x self.layer_dict['conv'] = nn.Conv1d(in_channels=out.shape[1], out_channels=self.num_filters, kernel_size=self.kernel_size, stride=self.stride, padding=self.padding, dilation=self.dilation, groups=self.groups, bias=self.use_bias) out = self.layer_dict['conv'](out) if self.normalization: self.layer_dict['norm_layer'] = nn.BatchNorm1d(num_features=out.shape[1]) out = self.layer_dict['norm_layer'](out) self.layer_dict['relu'] = nn.LeakyReLU() out = self.layer_dict['relu'](out) print(out.shape) def forward(self, x): out = x out = self.layer_dict['conv'](out) if self.normalization: out = self.layer_dict['norm_layer'](out) out = self.layer_dict['relu'](out) return out class DilatedDenseNetActivationNormNetwork(nn.Module): def __init__(self, im_shape, num_filters, num_stages, num_blocks_per_stage, per_param_biases=False): """ Builds a multilayer convolutional network. It also provides functionality for passing external parameters to be used at inference time. Enables inner loop optimization readily. :param im_shape: The input image batch shape. :param num_output_classes: The number of output classes of the network. :param args: A named tuple containing the system's hyperparameters. :param device: The device to run this on. :param meta_classifier: A flag indicating whether the system's meta-learning (inner-loop) functionalities should be enabled. """ super(DilatedDenseNetActivationNormNetwork, self).__init__() self.input_shape = list(im_shape) self.num_filters = num_filters self.num_stages = num_stages # self.num_output_classes = num_output_classes self.num_blocks_per_stage = num_blocks_per_stage self.use_per_param_biases = per_param_biases self.layer_dict = nn.ModuleDict() self.build_network() def build_network(self): """ Builds the network before inference is required by creating some dummy inputs with the same input as the self.im_shape tuple. Then passes that through the network and dynamically computes input shapes and sets output shapes for each layer. """ x = torch.zeros(self.input_shape) out = x self.layer_dict['stem_conv'] = Conv2dNormLeakyReLU(input_shape=out.shape, num_filters=self.num_filters, kernel_size=3, padding=1) out = self.layer_dict['stem_conv'](out) for i in range(2): for j in range(8): dilation = 2 ** j self.layer_dict['conv_{}_{}'.format(i, j)] = Conv2dNormLeakyReLU(input_shape=out.shape, num_filters=8, kernel_size=3, padding=dilation, dilation=dilation) cur = self.layer_dict['conv_{}_{}'.format(i, j)](out) out = torch.cat([out, cur], dim=1) self.layer_dict['out_conv'] = nn.Conv2d(in_channels=out.shape[1], out_channels=self.input_shape[1], bias=True, kernel_size=3, padding=1) out = self.layer_dict['out_conv'](out) if self.use_per_param_biases: biases = torch.zeros(out.shape) self.bias_params = nn.Parameter(biases, requires_grad=True) out = out + self.bias_params def forward(self, x): """ Forward propages through the network. If any params are passed then they are used instead of stored params. :param x: Input image batch. :param num_step: The current inner loop step number :param params: If params are None then internal parameters are used. If params are a dictionary with keys the same as the layer names then they will be used instead. :param training: Whether this is training (True) or eval time. :param backup_running_statistics: Whether to backup the running statistics in their backup store. Which is then used to reset the stats back to a previous state (usually after an eval loop, when we want to throw away stored statistics) :return: Logits of shape b, num_output_classes. """ out = x out = self.layer_dict['stem_conv'](out) for i in range(2): for j in range(8): dilation = 2 ** j cur = self.layer_dict['conv_{}_{}'.format(i, j)](out) out = torch.cat([out, cur], dim=1) out = self.layer_dict['out_conv'](out) if self.use_per_param_biases: out = out + self.bias_params return out class Dilated1dDenseNetActivationNormNetwork(nn.Module): def __init__(self, im_shape, num_filters, num_stages, num_blocks_per_stage): """ Builds a multilayer convolutional network. It also provides functionality for passing external parameters to be used at inference time. Enables inner loop optimization readily. :param im_shape: The input image batch shape. :param num_output_classes: The number of output classes of the network. :param args: A named tuple containing the system's hyperparameters. :param device: The device to run this on. :param meta_classifier: A flag indicating whether the system's meta-learning (inner-loop) functionalities should be enabled. """ super(Dilated1dDenseNetActivationNormNetwork, self).__init__() self.input_shape = list(im_shape) self.num_filters = num_filters self.num_stages = num_stages # self.num_output_classes = num_output_classes self.num_blocks_per_stage = num_blocks_per_stage self.layer_dict = nn.ModuleDict() self.build_network() def build_network(self): """ Builds the network before inference is required by creating some dummy inputs with the same input as the self.im_shape tuple. Then passes that through the network and dynamically computes input shapes and sets output shapes for each layer. """ x = torch.zeros(self.input_shape) out = x self.layer_dict['stem_conv'] = Conv1dNormLeakyReLU(input_shape=out.shape, num_filters=self.num_filters, kernel_size=3, padding=1) out = self.layer_dict['stem_conv'](out) for i in range(1): for j in range(11): dilation = 2 ** j self.layer_dict['conv_{}_{}'.format(i, j)] = Conv1dNormLeakyReLU(input_shape=out.shape, num_filters=self.num_filters, kernel_size=3, padding=dilation, dilation=dilation) cur = self.layer_dict['conv_{}_{}'.format(i, j)](out) out = torch.cat([out, cur], dim=1) self.layer_dict['out_conv'] = nn.Conv1d(in_channels=out.shape[1], out_channels=self.input_shape[1], bias=True, kernel_size=3, padding=1) out = self.layer_dict['out_conv'](out) def forward(self, x): """ Forward propages through the network. If any params are passed then they are used instead of stored params. :param x: Input image batch. :param num_step: The current inner loop step number :param params: If params are None then internal parameters are used. If params are a dictionary with keys the same as the layer names then they will be used instead. :param training: Whether this is training (True) or eval time. :param backup_running_statistics: Whether to backup the running statistics in their backup store. Which is then used to reset the stats back to a previous state (usually after an eval loop, when we want to throw away stored statistics) :return: Logits of shape b, num_output_classes. """ out = x out = self.layer_dict['stem_conv'](out) for i in range(1): for j in range(11): dilation = 2 ** j cur = self.layer_dict['conv_{}_{}'.format(i, j)](out) out = torch.cat([out, cur], dim=1) out = self.layer_dict['out_conv'](out) return out class CriticNetwork(nn.Module): def __init__(self, task_embedding_shape, logit_shape, support_set_feature_shape, target_set_feature_shape, support_set_classifier_pre_last_features, target_set_classifier_pre_last_features, support_set_label_shape, num_classes_per_set, num_support_samples, num_target_samples, conditional_information): """ Builds a multilayer convolutional network. It also provides functionality for passing external parameters to be used at inference time. Enables inner loop optimization readily. :param im_shape: The input image batch shape. :param num_output_classes: The number of output classes of the network. :param args: A named tuple containing the system's hyperparameters. :param device: The device to run this on. :param meta_classifier: A flag indicating whether the system's meta-learning (inner-loop) functionalities should be enabled. """ super(CriticNetwork, self).__init__() self.layer_dict = nn.ModuleDict() self.num_target_samples = num_target_samples self.num_samples_per_class = num_support_samples self.num_classes_per_set = num_classes_per_set self.logit_shape = logit_shape self.task_embedding_shape = task_embedding_shape self.conditional_information = conditional_information self.support_set_feature_shape = support_set_feature_shape self.target_set_feature_shape = target_set_feature_shape self.support_set_classifier_pre_last_features = support_set_classifier_pre_last_features self.target_set_classifier_pre_last_features = target_set_classifier_pre_last_features self.support_set_label_shape = support_set_label_shape self.build_network() def build_network(self): """ Builds the network before inference is required by creating some dummy inputs with the same input as the self.im_shape tuple. Then passes that through the network and dynamically computes input shapes and sets output shapes for each layer. """ processed_feature_list = [] if 'preds' in self.conditional_information: logits = torch.ones(self.logit_shape) logits_abs_diff_targets = torch.abs(logits) logits_square_diff_targets = logits ** 2 sign_logits = torch.sign(logits) logit_targets_features = torch.cat( [logits, logits_abs_diff_targets, logits_square_diff_targets, sign_logits], dim=1) logit_targets_features = logit_targets_features.view(logit_targets_features.shape[0], 1, logit_targets_features.shape[1]) processed_feature_list.append(logit_targets_features) if 'task_embedding' in self.conditional_information: task_embedding = torch.zeros(self.task_embedding_shape) task_embed_batched = task_embedding.view(1, 1, -1) if 'preds' in self.conditional_information: task_embed_batched = task_embed_batched.repeat(processed_feature_list[0].shape[0], 1, 1) processed_feature_list.append(task_embed_batched) # print(param_features_batched.shape, logit_targets_features.shape) for item in processed_feature_list: print('this one', item.shape) mixed_features = torch.cat(processed_feature_list, dim=2) feature_sets = [mixed_features] out = torch.cat(feature_sets, dim=1) out = out.view(out.shape[0], -1) self.layer_dict['linear_0'] = nn.Linear(in_features=out.shape[1], out_features=16, bias=False) out = self.layer_dict['linear_0'](out) out = F.leaky_relu(out) self.layer_dict['linear_1'] = nn.Linear(in_features=out.shape[1], out_features=16, bias=False) out = self.layer_dict['linear_1'](out) out = F.leaky_relu(out) self.layer_dict['linear_preds'] = nn.Linear(in_features=out.shape[1], out_features=1, bias=False) out = self.layer_dict['linear_preds'](out) out = out.sum() print("VGGNetwork build", out.shape) def forward(self, logits, task_embedding, return_sum=True): """ Forward propages through the network. If any params are passed then they are used instead of stored params. :param x: Input image batch. :param num_step: The current inner loop step number :param params: If params are None then internal parameters are used. If params are a dictionary with keys the same as the layer names then they will be used instead. :param training: Whether this is training (True) or eval time. :param backup_running_statistics: Whether to backup the running statistics in their backup store. Which is then used to reset the stats back to a previous state (usually after an eval loop, when we want to throw away stored statistics) :return: Logits of shape b, num_output_classes. """ # print(logits.shape, task_embedding.shape, support_set_features.shape, target_set_features.shape, # support_set_classifier_pre_last_layer.shape, target_set_classifier_pre_last_layer.shape, # support_set_labels.shape) processed_feature_list = [] if 'preds' in self.conditional_information: logits_abs_diff_targets = torch.abs(logits) logits_square_diff_targets = logits ** 2 sign_logits = torch.sign(logits) logit_targets_features = torch.cat( [logits, logits_abs_diff_targets, logits_square_diff_targets, sign_logits], dim=1) logit_targets_features = logit_targets_features.view(logit_targets_features.shape[0], 1, logit_targets_features.shape[1]) processed_feature_list.append(logit_targets_features) if 'task_embedding' in self.conditional_information: task_embed_batched = task_embedding.view(1, 1, -1) if 'preds' in self.conditional_information: task_embed_batched = task_embed_batched.repeat(processed_feature_list[0].shape[0], 1, 1) processed_feature_list.append(task_embed_batched) mixed_features = torch.cat(processed_feature_list, dim=2) feature_sets = [mixed_features] out = torch.cat(feature_sets, dim=1) out = out.view(out.shape[0], -1) out = self.layer_dict['linear_0'](out) out = F.leaky_relu(out) print(out.shape) out = self.layer_dict['linear_1'](out) out = F.leaky_relu(out) print(out.shape) out = self.layer_dict['linear_preds'](out) print(out.shape) if return_sum: out = out.sum() return out class TaskRelationalEmbedding(nn.Module): def __init__(self, input_shape, num_samples_per_support_class, num_classes_per_set): super(TaskRelationalEmbedding, self).__init__() self.input_shape = input_shape self.block_dict = nn.ModuleDict() self.num_samples_per_class = num_samples_per_support_class self.num_classes_per_set = num_classes_per_set self.first_time = True self.build_block() def build_block(self): out_img = torch.zeros(self.input_shape) """g""" b, f = out_img.shape print(out_img.shape) out_img = out_img.view(b, f) print(out_img.shape) # x_flat = (64 x 25 x 24) self.coord_tensor = [] for i in range(b): self.coord_tensor.append(torch.Tensor(np.array([i]))) self.coord_tensor = torch.stack(self.coord_tensor, dim=0) out_img = torch.cat([out_img, self.coord_tensor], dim=1) x_i = torch.unsqueeze(out_img, 0) # (1xh*wxc) x_i = x_i.repeat(b, 1, 1) # (h*wxh*wxc) x_j = torch.unsqueeze(out_img, 1) # (h*wx1xc) x_j = x_j.repeat(1, b, 1) # (h*wxh*wxc) # concatenate all together out = torch.cat([x_i, x_j], 2) # (h*wxh*wx2*c) prev_shape = out.shape out = out.view(out.shape[0] * out.shape[1], out.shape[-1]) for idx_layer in range(3): self.block_dict['g_fcc_{}'.format(idx_layer)] = nn.Linear(out.shape[1], out_features=32) out = F.relu(self.block_dict['g_fcc_{}'.format(idx_layer)].forward(out)) # reshape again and sum out = out.view(prev_shape[0], prev_shape[1], out.shape[-1]) out = out.sum(1) out = out.view(self.num_classes_per_set, self.num_samples_per_class, -1) out = out.mean(1).view(1, -1) print('Task Relational Network Block built with output volume shape', out.shape) def forward(self, x_img): out_img = x_img # print("input", out_img.shape) """g""" b, f = out_img.shape out_img = out_img.view(b, f) out_img = torch.cat([out_img, self.coord_tensor.to(x_img.device)], dim=1) # x_flat = (64 x 25 x 24) # print('out_img', out_img.shape) x_i = torch.unsqueeze(out_img, 0) # (1xh*wxc) x_i = x_i.repeat(b, 1, 1) # (h*wxh*wxc) x_j = torch.unsqueeze(out_img, 1) # (h*wx1xc) x_j = x_j.repeat(1, b, 1) # (h*wxh*wxc) # concatenate all together out = torch.cat([x_i, x_j], 2) # (h*wxh*wx2*c) prev_shape = out.shape out = out.view(out.shape[0] * out.shape[1], out.shape[-1]) for idx_layer in range(3): print(idx_layer, out.shape) out = F.relu(self.block_dict['g_fcc_{}'.format(idx_layer)].forward(out)) # reshape again and sum # print(out.shape) out = out.view(prev_shape[0], prev_shape[1], out.shape[-1]) out = out.sum(1) out = out.view(self.num_classes_per_set, self.num_samples_per_class, -1) out = out.mean(1).view(1, -1) # """f""" # out = self.post_processing_layer.forward(out) # out = F.relu(out) # out = self.output_layer.forward(out) # # print('Block built with output volume shape', out.shape) return out class RelationalModule(nn.Module): def __init__(self, input_shape): super(RelationalModule, self).__init__() self.input_shape = input_shape self.block_dict = nn.ModuleDict() self.first_time = True self.build_block() def build_block(self): out_img = torch.zeros(self.input_shape) """g""" c, h, w = out_img.shape print(out_img.shape) out_img = out_img.view(c, h * w) out_img = out_img.permute([1, 0]) # h*w, c print(out_img.shape) # x_flat = (64 x 25 x 24) self.coord_tensor = [] for i in range(h * w): self.coord_tensor.append(torch.Tensor(np.array([i]))) self.coord_tensor = torch.stack(self.coord_tensor, dim=0) out_img = torch.cat([out_img, self.coord_tensor], dim=1) x_i = torch.unsqueeze(out_img, 0) # (1xh*wxc) x_i = x_i.repeat(h * w, 1, 1) # (h*wxh*wxc) x_j = torch.unsqueeze(out_img, 1) # (h*wx1xc) x_j = x_j.repeat(1, h * w, 1) # (h*wxh*wxc) # concatenate all together out = torch.cat([x_i, x_j], 2) # (h*wxh*wx2*c) out = out.view(out.shape[0] * out.shape[1], out.shape[2]) for idx_layer in range(2): self.block_dict['g_fcc_{}'.format(idx_layer)] = nn.Linear(out.shape[1], out_features=32) out = F.leaky_relu(self.block_dict['g_fcc_{}'.format(idx_layer)].forward(out)) # reshape again and sum print(out.shape) out = out.sum(0).view(1, -1) """f""" self.post_processing_layer = nn.Linear(in_features=out.shape[1], out_features=32) out = self.post_processing_layer.forward(out) out = F.relu(out) self.output_layer = nn.Linear(in_features=out.shape[1], out_features=32) out = self.output_layer.forward(out) print('Block built with output volume shape', out.shape) def forward(self, x_img): out_img = x_img # print("input", out_img.shape) """g""" c, h, w = out_img.shape out_img = out_img.view(c, h * w) out_img = out_img.permute([1, 0]) # h*w, c out_img = torch.cat([out_img, self.coord_tensor.to(x_img.device)], dim=1) # x_flat = (64 x 25 x 24) # print('out_img', out_img.shape) x_i = torch.unsqueeze(out_img, 0) # (1xh*wxc) x_i = x_i.repeat(h * w, 1, 1) # (h*wxh*wxc) x_j = torch.unsqueeze(out_img, 1) # (h*wx1xc) x_j = x_j.repeat(1, h * w, 1) # (h*wxh*wxc) # concatenate all together out = torch.cat([x_i, x_j], 2) # (h*wxh*wx2*c) out = out.view(out.shape[0] * out.shape[1], out.shape[2]) for idx_layer in range(2): out = F.leaky_relu(self.block_dict['g_fcc_{}'.format(idx_layer)].forward(out)) # reshape again and sum # print(out.shape) out = out.sum(0).view(1, -1) """f""" out = self.post_processing_layer.forward(out) out = F.relu(out) out = self.output_layer.forward(out) # print('Block built with output volume shape', out.shape) return out class BatchRelationalModule(nn.Module): def __init__(self, input_shape, use_coordinates=True, num_layers=2, num_units=64): super(BatchRelationalModule, self).__init__() self.input_shape = input_shape self.block_dict = nn.ModuleDict() self.first_time = True self.use_coordinates = use_coordinates self.num_layers = num_layers self.num_units = num_units self.build_block() def build_block(self): out_img = torch.zeros(self.input_shape) """g""" if len(out_img.shape) > 3: b, c, h, w = out_img.shape print(out_img.shape) out_img = out_img.view(b, c, h * w) out_img = out_img.permute([0, 2, 1]) # h*w, c b, length, c = out_img.shape print(out_img.shape) # x_flat = (64 x 25 x 24) if self.use_coordinates: self.coord_tensor = [] for i in range(length): self.coord_tensor.append(torch.Tensor(np.array([i]))) self.coord_tensor = torch.stack(self.coord_tensor, dim=0).unsqueeze(0) if self.coord_tensor.shape[0] != out_img.shape[0]: self.coord_tensor = self.coord_tensor[0].unsqueeze(0).repeat([out_img.shape[0], 1, 1]) out_img = torch.cat([out_img, self.coord_tensor], dim=2) x_i = torch.unsqueeze(out_img, 1) # (1xh*wxc) x_i = x_i.repeat(1, length, 1, 1) # (h*wxh*wxc) x_j = torch.unsqueeze(out_img, 2) # (h*wx1xc) x_j = x_j.repeat(1, 1, length, 1) # (h*wxh*wxc) # concatenate all together per_location_feature = torch.cat([x_i, x_j], 3) # (h*wxh*wx2*c) out = per_location_feature.view( per_location_feature.shape[0] * per_location_feature.shape[1] * per_location_feature.shape[2], per_location_feature.shape[3]) print(out.shape) for idx_layer in range(self.num_layers): self.block_dict['g_fcc_{}'.format(idx_layer)] = nn.Linear(out.shape[1], out_features=self.num_units, bias=True) out = self.block_dict['g_fcc_{}'.format(idx_layer)].forward(out) self.block_dict['LeakyReLU_{}'.format(idx_layer)] = nn.LeakyReLU() out = self.block_dict['LeakyReLU_{}'.format(idx_layer)].forward(out) # reshape again and sum print(out.shape) out = out.view(per_location_feature.shape[0], per_location_feature.shape[1], per_location_feature.shape[2], -1) out = out.sum(1).sum(1) print('here', out.shape) """f""" self.post_processing_layer = nn.Linear(in_features=out.shape[1], out_features=self.num_units) out = self.post_processing_layer.forward(out) self.block_dict['LeakyReLU_post_processing'] = nn.LeakyReLU() out = self.block_dict['LeakyReLU_post_processing'].forward(out) self.output_layer = nn.Linear(in_features=out.shape[1], out_features=self.num_units) out = self.output_layer.forward(out) self.block_dict['LeakyReLU_output'] = nn.LeakyReLU() out = self.block_dict['LeakyReLU_output'].forward(out) print('Block built with output volume shape', out.shape) def forward(self, x_img): out_img = x_img # print("input", out_img.shape) """g""" if len(out_img.shape) > 3: b, c, h, w = out_img.shape out_img = out_img.view(b, c, h * w) out_img = out_img.permute([0, 2, 1]) # h*w, c b, length, c = out_img.shape if self.use_coordinates: if self.coord_tensor.shape[0] != out_img.shape[0]: self.coord_tensor = self.coord_tensor[0].unsqueeze(0).repeat([out_img.shape[0], 1, 1]) out_img = torch.cat([out_img, self.coord_tensor.to(x_img.device)], dim=2) # x_flat = (64 x 25 x 24) # print('out_img', out_img.shape) x_i = torch.unsqueeze(out_img, 1) # (1xh*wxc) x_i = x_i.repeat(1, length, 1, 1) # (h*wxh*wxc) x_j = torch.unsqueeze(out_img, 2) # (h*wx1xc) x_j = x_j.repeat(1, 1, length, 1) # (h*wxh*wxc) # concatenate all together per_location_feature = torch.cat([x_i, x_j], 3) # (h*wxh*wx2*c) out = per_location_feature.view( per_location_feature.shape[0] * per_location_feature.shape[1] * per_location_feature.shape[2], per_location_feature.shape[3]) for idx_layer in range(2): out = self.block_dict['g_fcc_{}'.format(idx_layer)].forward(out) out = self.block_dict['LeakyReLU_{}'.format(idx_layer)].forward(out) # reshape again and sum # print(out.shape) out = out.view(per_location_feature.shape[0], per_location_feature.shape[1], per_location_feature.shape[2], -1) out = out.sum(1).sum(1) """f""" out = self.post_processing_layer.forward(out) out = self.block_dict['LeakyReLU_post_processing'].forward(out) out = self.output_layer.forward(out) out = self.block_dict['LeakyReLU_output'].forward(out) # print('Block built with output volume shape', out.shape) return out class DenseEmbeddingSmallNetwork(nn.Module): def __init__(self, im_shape, num_filters, num_blocks_per_stage, num_stages, dropout_rate, output_spatial_dimensionality, average_pool_outputs=True, use_vgg_features=False): super(DenseEmbeddingSmallNetwork, self).__init__() b, c, self.h, self.w = im_shape self.total_layers = 0 self.input_shape = list(im_shape) self.num_filters = num_filters self.num_blocks_per_stage = num_blocks_per_stage self.num_stages = num_stages self.average_pool_outputs = average_pool_outputs self.use_vgg_features = use_vgg_features self.output_spatial_dimensionality = output_spatial_dimensionality self.dropout_rate = dropout_rate self.layer_dict = nn.ModuleDict() self.build_block() def build_block(self): x = torch.ones(self.input_shape) out = x self.layer_dict['dense_net_features'] = DenseNetActivationNormNetwork(im_shape=x.shape, num_filters=self.num_filters, num_stages=self.num_stages, num_blocks_per_stage=self.num_blocks_per_stage, dropout_rate=self.dropout_rate, reduction_rate=1.0, average_pool_output=self.average_pool_outputs) out = self.layer_dict['dense_net_features'].forward(out, dropout_training=False) print("DenseEmbeddingSmallNetwork output shape", out.shape) return out def forward(self, x, dropout_training): out = x # print("inputs", x.shape) out = self.layer_dict['dense_net_features'].forward(out, dropout_training=dropout_training) # out = out.view(out.shape[0], out.shape[1], 1, 1) # b, c, h, w = out.shape return out def reinitialize(self): for name, module in self.named_modules(): if type(module) == nn.Conv2d: module.reset_parameters() class SqueezeExciteDenseNetEmbeddingSmallNetwork(nn.Module): def __init__(self, im_shape, num_filters, num_blocks_per_stage, num_stages, dropout_rate, output_spatial_dimensionality, use_channel_wise_attention, average_pool_outputs=True, use_vgg_features=False, conv_type=Conv2dNormLeakyReLU): super(SqueezeExciteDenseNetEmbeddingSmallNetwork, self).__init__() b, c, self.h, self.w = im_shape self.total_layers = 0 self.input_shape = list(im_shape) self.num_filters = num_filters self.num_blocks_per_stage = num_blocks_per_stage self.num_stages = num_stages self.average_pool_outputs = average_pool_outputs self.use_vgg_features = use_vgg_features self.output_spatial_dimensionality = output_spatial_dimensionality self.use_channel_wise_attention = use_channel_wise_attention self.dropout_rate = dropout_rate self.conv_type = conv_type self.layer_dict = nn.ModuleDict() self.build_block() def build_block(self): x = torch.ones(self.input_shape) out = x self.layer_dict['dense_net_features'] = SqueezeExciteDenseNet(im_shape=x.shape, num_filters=self.num_filters, num_stages=self.num_stages, num_blocks_per_stage=self.num_blocks_per_stage, dropout_rate=self.dropout_rate, reduction_rate=1.0, average_pool_output=self.average_pool_outputs, output_spatial_dim=self.output_spatial_dimensionality, use_channel_wise_attention=self.use_channel_wise_attention) out = self.layer_dict['dense_net_features'].forward(out, dropout_training=False) print("DenseEmbeddingSmallNetwork output shape", out.shape) return out def forward(self, x, dropout_training): out = x # print("inputs", x.shape) out = self.layer_dict['dense_net_features'].forward(out, dropout_training=dropout_training) # out = out.view(out.shape[0], out.shape[1], 1, 1) # b, c, h, w = out.shape return out def reinitialize(self): for name, module in self.named_modules(): if type(module) == nn.Conv2d: module.reset_parameters() class TaskRelationalNetwork(nn.Module): def __init__(self, im_shape): super(TaskRelationalNetwork, self).__init__() self.total_layers = 0 self.input_shape = list(im_shape) self.layer_dict = nn.ModuleDict() self.build_block() def build_block(self): x = torch.ones(self.input_shape) out = x out = out.unbind(dim=0) out = torch.stack(out, dim=1) out = out.view(out.shape[0], -1, out.shape[-1]) self.layer_dict['relational_net'] = RelationalModule(input_shape=out.shape) out = self.layer_dict['relational_net'](out) print(out.shape) def forward(self, x): out = x out = out.unbind(dim=0) out = torch.stack(out, dim=1) out = out.view(out.shape[0], -1, out.shape[-1]) out = self.layer_dict['relational_net'](out) return out def reinitialize(self): for name, module in self.named_modules(): if type(module) == nn.Conv2d: module.reset_parameters() class ConvReLUBatchNorm(nn.Module): def __init__(self, input_shape, num_filters, kernel_size, stride, padding, bias, batch_norm=True): super(ConvReLUBatchNorm, self).__init__() self.input_shape = input_shape self.batch_norm = batch_norm self.num_filters = num_filters self.padding = padding self.bias = bias self.kernel_size = kernel_size self.stride = stride self.layer_dict = nn.ModuleDict() self.build_block() def build_block(self): x = torch.zeros(self.input_shape) out = x self.layer_dict['conv'] = nn.Conv2d(in_channels=out.shape[1], out_channels=self.num_filters, kernel_size=self.kernel_size, stride=self.stride, padding=self.padding, bias=self.bias) out = self.layer_dict['conv'].forward(out) out = F.leaky_relu(out) if self.batch_norm: self.layer_dict['bn'] = nn.BatchNorm2d(out.shape[1], track_running_stats=True) out = self.layer_dict['bn'].forward(out) print("ConvBatchNormReLU output volume", out.shape) def forward(self, x): out = x out = self.layer_dict['conv'].forward(out) out = F.leaky_relu(out) if self.batch_norm: out = self.layer_dict['bn'].forward(out) return out class VGGEmbeddingNetwork(nn.Module): def __init__(self, im_shape): super(VGGEmbeddingNetwork, self).__init__() b, c, self.h, self.w = im_shape self.total_layers = 0 self.layers = OrderedDict() self.input_shape = list(im_shape) self.layer_dict = nn.ModuleDict() self.build_block() def build_block(self): x = torch.ones(self.input_shape) out = x for i in range(4): self.layer_dict['conv_relu_bn_{}'.format(i)] = ConvReLUBatchNorm(input_shape=out.shape, num_filters=64, stride=1, padding=1, bias=False, batch_norm=True, kernel_size=3) out = self.layer_dict['conv_relu_bn_{}'.format(i)](out) out = F.max_pool2d(input=out, kernel_size=(2, 2), stride=2, padding=0) print(out.shape) def forward(self, x): out = x for i in range(4): out = self.layer_dict['conv_relu_bn_{}'.format(i)](out) out = F.max_pool2d(input=out, kernel_size=(2, 2), stride=2, padding=0) # print(out.shape) features = out out = out.view(out.size(0), -1) return out, features def reinitialize(self): for name, module in self.named_modules(): if type(module) == nn.Conv2d or type(module) == nn.BatchNorm2d: module.reset_parameters()

44.586826

136

0.596639

6,657

52,122

4.429323

0.048671

0.032049

0.046293

0.029302

0.90816

0.894357

0.87862

0.853286

0.839788

0.831717

0

0.012574

0.305763

52,122

1,168

137

44.625

0.802294

0.187445

0

0.804

0

0.038527

0.008988

0

1

0.065333

false

0

0.006667

0

0.114667

0.04

0

null

0

1

0

1

0

null

0

7

8e1b97378b4ff987b23b0a2251622ba5c6e0472a

6,841

py

Python

glharvest/tests/test_scenarios.py

ec-geolink/glharvest

a08258d17391067c4136ee569f9a38e6df37c0d2

[ "Apache-2.0" ]

1

2021-03-30T00:24:33.000Z

glharvest/tests/test_scenarios.py

ec-geolink/glharvest

a08258d17391067c4136ee569f9a38e6df37c0d2

[ "Apache-2.0" ]

21

2015-10-21T21:47:10.000Z

2018-01-11T19:18:23.000Z

glharvest/tests/test_scenarios.py

ec-geolink/glharvest

a08258d17391067c4136ee569f9a38e6df37c0d2

[ "Apache-2.0" ]

null

"""test_scenarios.py End-end-end tests for the Harvester. """ import sys import os import RDF from glharvest import jobs, registry, void def test_can_update_a_provider_with_a_new_resource(repository): """This test tests the case where a provider gives informationa about one resource at time t0 then, at time t1, their data dump no longer contains information about the old resource. In this case, we keep the previous knowledge and add the new knowledge because we don't allow providers to completely remove a resource. """ # Setup repository.clear() provider = 'test' infile_fmt = 'turtle' base_uri = 'http://example.org/test/' parser = RDF.TurtleParser() state_t0 = """ @prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:A a test:Thing ; test:someProperty 'some property' . """ state_t1 = """@prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:B a test:Thing ; test:someProperty 'some other property' . """ # State t0 for statement in parser.parse_string_as_stream(state_t0, base_uri=base_uri): print statement.subject repository.delete_triples_about(statement.subject, context=provider) repository.import_from_string(state_t0, context=provider, fmt=infile_fmt) assert repository.size() == 2 # State t1 for statement in parser.parse_string_as_stream(state_t1, base_uri=base_uri): print statement.subject repository.delete_triples_about(statement.subject, context=provider) repository.import_from_string(state_t1, context=provider, fmt=infile_fmt) assert repository.size() == 4 def test_provide_can_change_knowledge_about_a_previous_resource(repository): """This test tests the case where a provider wishes to change the knowledge about a resource. They do this by making an update datadump with at least one statement about that resource. """ # Setup repository.clear() provider = 'test' infile_fmt = 'turtle' base_uri = 'http://example.org/test/' parser = RDF.TurtleParser() state_t0 = """ @prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:A a test:Thing ; test:someProperty 'some property' ; test:anotherProperty 'just another thing' . """ state_t1 = """@prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:A a test:Thing ; test:someProperty 'some other property' . """ # State t0 for statement in parser.parse_string_as_stream(state_t0, base_uri=base_uri): repository.delete_triples_about(statement.subject, context=provider) repository.import_from_string(state_t0, context=provider, fmt=infile_fmt) assert repository.size() == 3 # State t1 for statement in parser.parse_string_as_stream(state_t1, base_uri=base_uri): repository.delete_triples_about(statement.subject, context=provider) assert repository.size() == 0 repository.import_from_string(state_t1, context=provider, fmt=infile_fmt) assert repository.size() == 2 def test_can_handle_multiple_duplicate_updates(repository): """This tests the case where a provider's datadump is updated but contains the same information as the datadump at a previous time. We'd assume the result would be that all statements would be first removed then just added again so the size would go from N to 0 back to N. """ # Setup repository.clear() provider = 'test' infile_fmt = 'turtle' base_uri = 'http://example.org/test/' parser = RDF.TurtleParser() state_t0 = """ @prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:A a test:Thing ; test:someProperty 'some property' ; test:anotherProperty 'just another thing' . """ state_t1 = """ @prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:A a test:Thing ; test:someProperty 'some property' ; test:anotherProperty 'just another thing' . """ # State t0 for statement in parser.parse_string_as_stream(state_t0, base_uri=base_uri): repository.delete_triples_about(statement.subject, context=provider) repository.import_from_string(state_t0, context=provider, fmt=infile_fmt) assert repository.size() == 3 # State t1 for statement in parser.parse_string_as_stream(state_t1, base_uri=base_uri): repository.delete_triples_about(statement.subject, context=provider) assert repository.size() == 0 repository.import_from_string(state_t1, context=provider, fmt=infile_fmt) assert repository.size() == 3 def test_can_handle_multiple_providers(repository): """This test tests the case where there are two registered providers. Each provider should have triples in their respective named graph. """ # Setup repository.clear() infile_fmt = 'turtle' base_uri = 'http://example.org/test/' parser = RDF.TurtleParser() state_t0 = """ @prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:A a test:Thing ; test:someProperty 'some property' ; test:anotherProperty 'just another thing' . """ state_t1 = """ @prefix void: <http://rdfs.org/ns/void#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix test: <http://example.org/test/> . test:A a test:Thing ; test:someProperty 'some property' ; test:anotherProperty 'just another thing' . """ # State t0 provider = 'providerA' for statement in parser.parse_string_as_stream(state_t0, base_uri=base_uri): repository.delete_triples_about(statement.subject, context=provider) repository.import_from_string(state_t0, context=provider, fmt=infile_fmt) assert repository.size() == 3 # State t1 provider = 'providerB' for statement in parser.parse_string_as_stream(state_t1, base_uri=base_uri): repository.delete_triples_about(statement.subject, context=provider) assert repository.size() == 3 repository.import_from_string(state_t1, context=provider, fmt=infile_fmt) assert repository.size() == 6

31.525346

80

0.684403

935

6,841

4.859893

0.166845

0.03081

0.036972

0.047535

0.807879

0.797315

0.791593

0.783891

0.783231

0

0.021423

0.194855

6,841

216

81

31.671296

0.803558

0.013887

0

0.888

0

0.064

0.398383

0

0.088

0

null

0

0.096

null

0.016

0

null

0

1

0

1

0

null

0

1

0

8

f3db39db2e1bc9f977eb755bee6e8351fda5a9ca

31,010

py

Python

sdk/python/pulumi_hcp/aws_transit_gateway_attachment.py

stack72/pulumi-hcp

df3eae86ddfd6648221eca8b1d1fa5619b1b490e

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_hcp/aws_transit_gateway_attachment.py

stack72/pulumi-hcp

df3eae86ddfd6648221eca8b1d1fa5619b1b490e

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_hcp/aws_transit_gateway_attachment.py

stack72/pulumi-hcp

df3eae86ddfd6648221eca8b1d1fa5619b1b490e

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from . import _utilities __all__ = ['AwsTransitGatewayAttachmentArgs', 'AwsTransitGatewayAttachment'] @pulumi.input_type class AwsTransitGatewayAttachmentArgs: def __init__(__self__, *, hvn_id: pulumi.Input[str], resource_share_arn: pulumi.Input[str], transit_gateway_attachment_id: pulumi.Input[str], transit_gateway_id: pulumi.Input[str]): """ The set of arguments for constructing a AwsTransitGatewayAttachment resource. :param pulumi.Input[str] hvn_id: The ID of the HashiCorp Virtual Network (HVN). :param pulumi.Input[str] resource_share_arn: The Amazon Resource Name (ARN) of the Resource Share that is needed to grant HCP access to the transit gateway in AWS. The Resource Share should be associated with the HCP AWS account principal (see [aws_ram_principal_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_principal_association)) and the transit gateway resource (see [aws_ram_resource_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_resource_association)) :param pulumi.Input[str] transit_gateway_attachment_id: The user-settable name of the transit gateway attachment in HCP. :param pulumi.Input[str] transit_gateway_id: The ID of the user-owned transit gateway in AWS. The AWS region of the transit gateway must match the HVN. """ pulumi.set(__self__, "hvn_id", hvn_id) pulumi.set(__self__, "resource_share_arn", resource_share_arn) pulumi.set(__self__, "transit_gateway_attachment_id", transit_gateway_attachment_id) pulumi.set(__self__, "transit_gateway_id", transit_gateway_id) @property @pulumi.getter(name="hvnId") def hvn_id(self) -> pulumi.Input[str]: """ The ID of the HashiCorp Virtual Network (HVN). """ return pulumi.get(self, "hvn_id") @hvn_id.setter def hvn_id(self, value: pulumi.Input[str]): pulumi.set(self, "hvn_id", value) @property @pulumi.getter(name="resourceShareArn") def resource_share_arn(self) -> pulumi.Input[str]: """ The Amazon Resource Name (ARN) of the Resource Share that is needed to grant HCP access to the transit gateway in AWS. The Resource Share should be associated with the HCP AWS account principal (see [aws_ram_principal_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_principal_association)) and the transit gateway resource (see [aws_ram_resource_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_resource_association)) """ return pulumi.get(self, "resource_share_arn") @resource_share_arn.setter def resource_share_arn(self, value: pulumi.Input[str]): pulumi.set(self, "resource_share_arn", value) @property @pulumi.getter(name="transitGatewayAttachmentId") def transit_gateway_attachment_id(self) -> pulumi.Input[str]: """ The user-settable name of the transit gateway attachment in HCP. """ return pulumi.get(self, "transit_gateway_attachment_id") @transit_gateway_attachment_id.setter def transit_gateway_attachment_id(self, value: pulumi.Input[str]): pulumi.set(self, "transit_gateway_attachment_id", value) @property @pulumi.getter(name="transitGatewayId") def transit_gateway_id(self) -> pulumi.Input[str]: """ The ID of the user-owned transit gateway in AWS. The AWS region of the transit gateway must match the HVN. """ return pulumi.get(self, "transit_gateway_id") @transit_gateway_id.setter def transit_gateway_id(self, value: pulumi.Input[str]): pulumi.set(self, "transit_gateway_id", value) @pulumi.input_type class _AwsTransitGatewayAttachmentState: def __init__(__self__, *, created_at: Optional[pulumi.Input[str]] = None, expires_at: Optional[pulumi.Input[str]] = None, hvn_id: Optional[pulumi.Input[str]] = None, organization_id: Optional[pulumi.Input[str]] = None, project_id: Optional[pulumi.Input[str]] = None, provider_transit_gateway_attachment_id: Optional[pulumi.Input[str]] = None, resource_share_arn: Optional[pulumi.Input[str]] = None, self_link: Optional[pulumi.Input[str]] = None, state: Optional[pulumi.Input[str]] = None, transit_gateway_attachment_id: Optional[pulumi.Input[str]] = None, transit_gateway_id: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering AwsTransitGatewayAttachment resources. :param pulumi.Input[str] created_at: The time that the transit gateway attachment was created. :param pulumi.Input[str] expires_at: The time after which the transit gateway attachment will be considered expired if it hasn't transitioned into `ACCEPTED` or `ACTIVE` state. :param pulumi.Input[str] hvn_id: The ID of the HashiCorp Virtual Network (HVN). :param pulumi.Input[str] organization_id: The ID of the HCP organization where the transit gateway attachment is located. Always matches the HVN's organization. :param pulumi.Input[str] project_id: The ID of the HCP project where the transit gateway attachment is located. Always matches the HVN's project. :param pulumi.Input[str] provider_transit_gateway_attachment_id: The transit gateway attachment ID used by AWS. :param pulumi.Input[str] resource_share_arn: The Amazon Resource Name (ARN) of the Resource Share that is needed to grant HCP access to the transit gateway in AWS. The Resource Share should be associated with the HCP AWS account principal (see [aws_ram_principal_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_principal_association)) and the transit gateway resource (see [aws_ram_resource_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_resource_association)) :param pulumi.Input[str] self_link: A unique URL identifying the transit gateway attachment. :param pulumi.Input[str] state: The state of the transit gateway attachment. :param pulumi.Input[str] transit_gateway_attachment_id: The user-settable name of the transit gateway attachment in HCP. :param pulumi.Input[str] transit_gateway_id: The ID of the user-owned transit gateway in AWS. The AWS region of the transit gateway must match the HVN. """ if created_at is not None: pulumi.set(__self__, "created_at", created_at) if expires_at is not None: pulumi.set(__self__, "expires_at", expires_at) if hvn_id is not None: pulumi.set(__self__, "hvn_id", hvn_id) if organization_id is not None: pulumi.set(__self__, "organization_id", organization_id) if project_id is not None: pulumi.set(__self__, "project_id", project_id) if provider_transit_gateway_attachment_id is not None: pulumi.set(__self__, "provider_transit_gateway_attachment_id", provider_transit_gateway_attachment_id) if resource_share_arn is not None: pulumi.set(__self__, "resource_share_arn", resource_share_arn) if self_link is not None: pulumi.set(__self__, "self_link", self_link) if state is not None: pulumi.set(__self__, "state", state) if transit_gateway_attachment_id is not None: pulumi.set(__self__, "transit_gateway_attachment_id", transit_gateway_attachment_id) if transit_gateway_id is not None: pulumi.set(__self__, "transit_gateway_id", transit_gateway_id) @property @pulumi.getter(name="createdAt") def created_at(self) -> Optional[pulumi.Input[str]]: """ The time that the transit gateway attachment was created. """ return pulumi.get(self, "created_at") @created_at.setter def created_at(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "created_at", value) @property @pulumi.getter(name="expiresAt") def expires_at(self) -> Optional[pulumi.Input[str]]: """ The time after which the transit gateway attachment will be considered expired if it hasn't transitioned into `ACCEPTED` or `ACTIVE` state. """ return pulumi.get(self, "expires_at") @expires_at.setter def expires_at(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "expires_at", value) @property @pulumi.getter(name="hvnId") def hvn_id(self) -> Optional[pulumi.Input[str]]: """ The ID of the HashiCorp Virtual Network (HVN). """ return pulumi.get(self, "hvn_id") @hvn_id.setter def hvn_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "hvn_id", value) @property @pulumi.getter(name="organizationId") def organization_id(self) -> Optional[pulumi.Input[str]]: """ The ID of the HCP organization where the transit gateway attachment is located. Always matches the HVN's organization. """ return pulumi.get(self, "organization_id") @organization_id.setter def organization_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "organization_id", value) @property @pulumi.getter(name="projectId") def project_id(self) -> Optional[pulumi.Input[str]]: """ The ID of the HCP project where the transit gateway attachment is located. Always matches the HVN's project. """ return pulumi.get(self, "project_id") @project_id.setter def project_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "project_id", value) @property @pulumi.getter(name="providerTransitGatewayAttachmentId") def provider_transit_gateway_attachment_id(self) -> Optional[pulumi.Input[str]]: """ The transit gateway attachment ID used by AWS. """ return pulumi.get(self, "provider_transit_gateway_attachment_id") @provider_transit_gateway_attachment_id.setter def provider_transit_gateway_attachment_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "provider_transit_gateway_attachment_id", value) @property @pulumi.getter(name="resourceShareArn") def resource_share_arn(self) -> Optional[pulumi.Input[str]]: """ The Amazon Resource Name (ARN) of the Resource Share that is needed to grant HCP access to the transit gateway in AWS. The Resource Share should be associated with the HCP AWS account principal (see [aws_ram_principal_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_principal_association)) and the transit gateway resource (see [aws_ram_resource_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_resource_association)) """ return pulumi.get(self, "resource_share_arn") @resource_share_arn.setter def resource_share_arn(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "resource_share_arn", value) @property @pulumi.getter(name="selfLink") def self_link(self) -> Optional[pulumi.Input[str]]: """ A unique URL identifying the transit gateway attachment. """ return pulumi.get(self, "self_link") @self_link.setter def self_link(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "self_link", value) @property @pulumi.getter def state(self) -> Optional[pulumi.Input[str]]: """ The state of the transit gateway attachment. """ return pulumi.get(self, "state") @state.setter def state(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "state", value) @property @pulumi.getter(name="transitGatewayAttachmentId") def transit_gateway_attachment_id(self) -> Optional[pulumi.Input[str]]: """ The user-settable name of the transit gateway attachment in HCP. """ return pulumi.get(self, "transit_gateway_attachment_id") @transit_gateway_attachment_id.setter def transit_gateway_attachment_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "transit_gateway_attachment_id", value) @property @pulumi.getter(name="transitGatewayId") def transit_gateway_id(self) -> Optional[pulumi.Input[str]]: """ The ID of the user-owned transit gateway in AWS. The AWS region of the transit gateway must match the HVN. """ return pulumi.get(self, "transit_gateway_id") @transit_gateway_id.setter def transit_gateway_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "transit_gateway_id", value) class AwsTransitGatewayAttachment(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, hvn_id: Optional[pulumi.Input[str]] = None, resource_share_arn: Optional[pulumi.Input[str]] = None, transit_gateway_attachment_id: Optional[pulumi.Input[str]] = None, transit_gateway_id: Optional[pulumi.Input[str]] = None, __props__=None): """ ## Example Usage ```python import pulumi import pulumi_aws as aws import pulumi_hcp as hcp main = hcp.Hvn("main", hvn_id="main-hvn", cloud_provider="aws", region="us-west-2", cidr_block="172.25.16.0/20") example_vpc = aws.ec2.Vpc("exampleVpc", cidr_block="172.31.0.0/16") example_transit_gateway = aws.ec2transitgateway.TransitGateway("exampleTransitGateway", tags={ "Name": "example-tgw", }) example_resource_share = aws.ram.ResourceShare("exampleResourceShare", allow_external_principals=True) example_principal_association = aws.ram.PrincipalAssociation("examplePrincipalAssociation", resource_share_arn=example_resource_share.arn, principal=main.provider_account_id) example_resource_association = aws.ram.ResourceAssociation("exampleResourceAssociation", resource_share_arn=example_resource_share.arn, resource_arn=example_transit_gateway.arn) example_aws_transit_gateway_attachment = hcp.AwsTransitGatewayAttachment("exampleAwsTransitGatewayAttachment", hvn_id=main.hvn_id, transit_gateway_attachment_id="example-tgw-attachment", transit_gateway_id=example_transit_gateway.id, resource_share_arn=example_resource_share.arn, opts=pulumi.ResourceOptions(depends_on=[ example_principal_association, example_resource_association, ])) route = hcp.HvnRoute("route", hvn_link=main.self_link, hvn_route_id="hvn-to-tgw-attachment", destination_cidr=example_vpc.cidr_block, target_link=example_aws_transit_gateway_attachment.self_link) example_vpc_attachment_accepter = aws.ec2transitgateway.VpcAttachmentAccepter("exampleVpcAttachmentAccepter", transit_gateway_attachment_id=example_aws_transit_gateway_attachment.provider_transit_gateway_attachment_id) ``` ## Import # The import ID is {hvn_id}:{transit_gateway_attachment_id} ```sh $ pulumi import hcp:index/awsTransitGatewayAttachment:AwsTransitGatewayAttachment example main-hvn:example-tgw-attachment ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] hvn_id: The ID of the HashiCorp Virtual Network (HVN). :param pulumi.Input[str] resource_share_arn: The Amazon Resource Name (ARN) of the Resource Share that is needed to grant HCP access to the transit gateway in AWS. The Resource Share should be associated with the HCP AWS account principal (see [aws_ram_principal_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_principal_association)) and the transit gateway resource (see [aws_ram_resource_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_resource_association)) :param pulumi.Input[str] transit_gateway_attachment_id: The user-settable name of the transit gateway attachment in HCP. :param pulumi.Input[str] transit_gateway_id: The ID of the user-owned transit gateway in AWS. The AWS region of the transit gateway must match the HVN. """ ... @overload def __init__(__self__, resource_name: str, args: AwsTransitGatewayAttachmentArgs, opts: Optional[pulumi.ResourceOptions] = None): """ ## Example Usage ```python import pulumi import pulumi_aws as aws import pulumi_hcp as hcp main = hcp.Hvn("main", hvn_id="main-hvn", cloud_provider="aws", region="us-west-2", cidr_block="172.25.16.0/20") example_vpc = aws.ec2.Vpc("exampleVpc", cidr_block="172.31.0.0/16") example_transit_gateway = aws.ec2transitgateway.TransitGateway("exampleTransitGateway", tags={ "Name": "example-tgw", }) example_resource_share = aws.ram.ResourceShare("exampleResourceShare", allow_external_principals=True) example_principal_association = aws.ram.PrincipalAssociation("examplePrincipalAssociation", resource_share_arn=example_resource_share.arn, principal=main.provider_account_id) example_resource_association = aws.ram.ResourceAssociation("exampleResourceAssociation", resource_share_arn=example_resource_share.arn, resource_arn=example_transit_gateway.arn) example_aws_transit_gateway_attachment = hcp.AwsTransitGatewayAttachment("exampleAwsTransitGatewayAttachment", hvn_id=main.hvn_id, transit_gateway_attachment_id="example-tgw-attachment", transit_gateway_id=example_transit_gateway.id, resource_share_arn=example_resource_share.arn, opts=pulumi.ResourceOptions(depends_on=[ example_principal_association, example_resource_association, ])) route = hcp.HvnRoute("route", hvn_link=main.self_link, hvn_route_id="hvn-to-tgw-attachment", destination_cidr=example_vpc.cidr_block, target_link=example_aws_transit_gateway_attachment.self_link) example_vpc_attachment_accepter = aws.ec2transitgateway.VpcAttachmentAccepter("exampleVpcAttachmentAccepter", transit_gateway_attachment_id=example_aws_transit_gateway_attachment.provider_transit_gateway_attachment_id) ``` ## Import # The import ID is {hvn_id}:{transit_gateway_attachment_id} ```sh $ pulumi import hcp:index/awsTransitGatewayAttachment:AwsTransitGatewayAttachment example main-hvn:example-tgw-attachment ``` :param str resource_name: The name of the resource. :param AwsTransitGatewayAttachmentArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(AwsTransitGatewayAttachmentArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, hvn_id: Optional[pulumi.Input[str]] = None, resource_share_arn: Optional[pulumi.Input[str]] = None, transit_gateway_attachment_id: Optional[pulumi.Input[str]] = None, transit_gateway_id: Optional[pulumi.Input[str]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.plugin_download_url is None: opts.plugin_download_url = _utilities.get_plugin_download_url() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = AwsTransitGatewayAttachmentArgs.__new__(AwsTransitGatewayAttachmentArgs) if hvn_id is None and not opts.urn: raise TypeError("Missing required property 'hvn_id'") __props__.__dict__["hvn_id"] = hvn_id if resource_share_arn is None and not opts.urn: raise TypeError("Missing required property 'resource_share_arn'") __props__.__dict__["resource_share_arn"] = resource_share_arn if transit_gateway_attachment_id is None and not opts.urn: raise TypeError("Missing required property 'transit_gateway_attachment_id'") __props__.__dict__["transit_gateway_attachment_id"] = transit_gateway_attachment_id if transit_gateway_id is None and not opts.urn: raise TypeError("Missing required property 'transit_gateway_id'") __props__.__dict__["transit_gateway_id"] = transit_gateway_id __props__.__dict__["created_at"] = None __props__.__dict__["expires_at"] = None __props__.__dict__["organization_id"] = None __props__.__dict__["project_id"] = None __props__.__dict__["provider_transit_gateway_attachment_id"] = None __props__.__dict__["self_link"] = None __props__.__dict__["state"] = None super(AwsTransitGatewayAttachment, __self__).__init__( 'hcp:index/awsTransitGatewayAttachment:AwsTransitGatewayAttachment', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, created_at: Optional[pulumi.Input[str]] = None, expires_at: Optional[pulumi.Input[str]] = None, hvn_id: Optional[pulumi.Input[str]] = None, organization_id: Optional[pulumi.Input[str]] = None, project_id: Optional[pulumi.Input[str]] = None, provider_transit_gateway_attachment_id: Optional[pulumi.Input[str]] = None, resource_share_arn: Optional[pulumi.Input[str]] = None, self_link: Optional[pulumi.Input[str]] = None, state: Optional[pulumi.Input[str]] = None, transit_gateway_attachment_id: Optional[pulumi.Input[str]] = None, transit_gateway_id: Optional[pulumi.Input[str]] = None) -> 'AwsTransitGatewayAttachment': """ Get an existing AwsTransitGatewayAttachment resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] created_at: The time that the transit gateway attachment was created. :param pulumi.Input[str] expires_at: The time after which the transit gateway attachment will be considered expired if it hasn't transitioned into `ACCEPTED` or `ACTIVE` state. :param pulumi.Input[str] hvn_id: The ID of the HashiCorp Virtual Network (HVN). :param pulumi.Input[str] organization_id: The ID of the HCP organization where the transit gateway attachment is located. Always matches the HVN's organization. :param pulumi.Input[str] project_id: The ID of the HCP project where the transit gateway attachment is located. Always matches the HVN's project. :param pulumi.Input[str] provider_transit_gateway_attachment_id: The transit gateway attachment ID used by AWS. :param pulumi.Input[str] resource_share_arn: The Amazon Resource Name (ARN) of the Resource Share that is needed to grant HCP access to the transit gateway in AWS. The Resource Share should be associated with the HCP AWS account principal (see [aws_ram_principal_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_principal_association)) and the transit gateway resource (see [aws_ram_resource_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_resource_association)) :param pulumi.Input[str] self_link: A unique URL identifying the transit gateway attachment. :param pulumi.Input[str] state: The state of the transit gateway attachment. :param pulumi.Input[str] transit_gateway_attachment_id: The user-settable name of the transit gateway attachment in HCP. :param pulumi.Input[str] transit_gateway_id: The ID of the user-owned transit gateway in AWS. The AWS region of the transit gateway must match the HVN. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _AwsTransitGatewayAttachmentState.__new__(_AwsTransitGatewayAttachmentState) __props__.__dict__["created_at"] = created_at __props__.__dict__["expires_at"] = expires_at __props__.__dict__["hvn_id"] = hvn_id __props__.__dict__["organization_id"] = organization_id __props__.__dict__["project_id"] = project_id __props__.__dict__["provider_transit_gateway_attachment_id"] = provider_transit_gateway_attachment_id __props__.__dict__["resource_share_arn"] = resource_share_arn __props__.__dict__["self_link"] = self_link __props__.__dict__["state"] = state __props__.__dict__["transit_gateway_attachment_id"] = transit_gateway_attachment_id __props__.__dict__["transit_gateway_id"] = transit_gateway_id return AwsTransitGatewayAttachment(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="createdAt") def created_at(self) -> pulumi.Output[str]: """ The time that the transit gateway attachment was created. """ return pulumi.get(self, "created_at") @property @pulumi.getter(name="expiresAt") def expires_at(self) -> pulumi.Output[str]: """ The time after which the transit gateway attachment will be considered expired if it hasn't transitioned into `ACCEPTED` or `ACTIVE` state. """ return pulumi.get(self, "expires_at") @property @pulumi.getter(name="hvnId") def hvn_id(self) -> pulumi.Output[str]: """ The ID of the HashiCorp Virtual Network (HVN). """ return pulumi.get(self, "hvn_id") @property @pulumi.getter(name="organizationId") def organization_id(self) -> pulumi.Output[str]: """ The ID of the HCP organization where the transit gateway attachment is located. Always matches the HVN's organization. """ return pulumi.get(self, "organization_id") @property @pulumi.getter(name="projectId") def project_id(self) -> pulumi.Output[str]: """ The ID of the HCP project where the transit gateway attachment is located. Always matches the HVN's project. """ return pulumi.get(self, "project_id") @property @pulumi.getter(name="providerTransitGatewayAttachmentId") def provider_transit_gateway_attachment_id(self) -> pulumi.Output[str]: """ The transit gateway attachment ID used by AWS. """ return pulumi.get(self, "provider_transit_gateway_attachment_id") @property @pulumi.getter(name="resourceShareArn") def resource_share_arn(self) -> pulumi.Output[str]: """ The Amazon Resource Name (ARN) of the Resource Share that is needed to grant HCP access to the transit gateway in AWS. The Resource Share should be associated with the HCP AWS account principal (see [aws_ram_principal_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_principal_association)) and the transit gateway resource (see [aws_ram_resource_association](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/ram_resource_association)) """ return pulumi.get(self, "resource_share_arn") @property @pulumi.getter(name="selfLink") def self_link(self) -> pulumi.Output[str]: """ A unique URL identifying the transit gateway attachment. """ return pulumi.get(self, "self_link") @property @pulumi.getter def state(self) -> pulumi.Output[str]: """ The state of the transit gateway attachment. """ return pulumi.get(self, "state") @property @pulumi.getter(name="transitGatewayAttachmentId") def transit_gateway_attachment_id(self) -> pulumi.Output[str]: """ The user-settable name of the transit gateway attachment in HCP. """ return pulumi.get(self, "transit_gateway_attachment_id") @property @pulumi.getter(name="transitGatewayId") def transit_gateway_id(self) -> pulumi.Output[str]: """ The ID of the user-owned transit gateway in AWS. The AWS region of the transit gateway must match the HVN. """ return pulumi.get(self, "transit_gateway_id")

50.752864

226

0.68594

3,722

31,010

5.437131

0.065019

0.114839

0.116223

0.078371

0.878243

0.858082

0.839403

0.821466

0.812027

0.773682

0

0.001954

0.224218

31,010

610

227

50.836066

0.839257

0.443502

0

0.52349

1

0

0.13461

0.053167

0

1

0.161074

false

0.003356

0.016779

0

0.278523

0

null

0

1

0

1

0

null

0

7

f3f3e8e8922515c66dcbf75092b13f022472898c

2,864

py

Python

pytorch/network/regnet/blocks.py

psm9733/backbone

b891c859f667f52127af50cb60d08081f40032fe

[ "BSD-2-Clause" ]

11

2021-08-15T20:00:35.000Z

2022-01-22T12:25:07.000Z

pytorch/network/regnet/blocks.py

psm9733/backbone

b891c859f667f52127af50cb60d08081f40032fe

[ "BSD-2-Clause" ]

null

pytorch/network/regnet/blocks.py

psm9733/backbone

b891c859f667f52127af50cb60d08081f40032fe

[ "BSD-2-Clause" ]

null

from network.common.layers import Conv2D_BN from network.common.blocks import SEBlock import torch.nn as nn class XBlock(nn.Module): #based ResidualBlock + group convolution def __init__(self, activation, in_channels, block_width, bottleneck_ratio, stride, padding='same', groups=1, dilation=1, bias=True): super().__init__() self.conv2d_bn_1 = Conv2D_BN(in_channels, activation, int(block_width / bottleneck_ratio), kernel_size=(1, 1), stride=1, padding=padding, dilation=dilation, bias=bias) self.conv2d_bn_2 = Conv2D_BN(int(block_width / bottleneck_ratio), activation, int(block_width / bottleneck_ratio), kernel_size=(3, 3), stride=stride, padding=padding, groups=groups, dilation=dilation, bias=bias) self.conv2d_bn_3 = Conv2D_BN(int(block_width / bottleneck_ratio), activation, block_width, kernel_size=(1, 1), stride=1, padding=padding, dilation=dilation, bias=bias) self.identity = Conv2D_BN(in_channels, activation, block_width, kernel_size=(1, 1), stride=stride, padding=padding, dilation=dilation, bias=bias) def forward(self, input): output = self.conv2d_bn_1(input) output = self.conv2d_bn_2(output) output = self.conv2d_bn_3(output) if output.shape[2:4] == input.shape[2:4]: identity = input else: identity = self.identity(input) output += identity return output class YBlock(nn.Module): # based ResidualBlock + group convolution + SEBlock def __init__(self, activation, in_channels, block_width, bottleneck_ratio, stride, padding='same', groups=1, dilation=1, bias=True): super().__init__() self.conv2d_bn_1 = Conv2D_BN(in_channels, activation, int(block_width / bottleneck_ratio), kernel_size=(1, 1), stride=1, padding=padding, dilation=dilation, bias=bias) self.conv2d_bn_2 = Conv2D_BN(int(block_width / bottleneck_ratio), activation, int(block_width / bottleneck_ratio), kernel_size=(3, 3), stride=stride, padding=padding, groups=groups, dilation=dilation, bias=bias) self.seblock = SEBlock(int(block_width / bottleneck_ratio), bottleneck_ratio=4, bias=bias) self.conv2d_bn_3 = Conv2D_BN(int(block_width / bottleneck_ratio), activation, block_width, kernel_size=(1, 1), stride=1, padding=padding, dilation=dilation, bias=bias) self.identity = Conv2D_BN(in_channels, activation, block_width, kernel_size=(1, 1), stride=stride, padding=padding, dilation=dilation, bias=bias) def forward(self, input): output = self.conv2d_bn_1(input) output = self.conv2d_bn_2(output) output = self.seblock(output) output = self.conv2d_bn_3(output) if output.shape[2:4] == input.shape[2:4]: identity = input else: identity = self.identity(input) output += identity return output

66.604651

219

0.706704

386

2,864

5.010363

0.137306

0.086867

0.074457

0.142192

0.919338

0.90486

0.861427

0

0.028049

0.178422

2,864

43

220

66.604651

0.79388

0.031075

0

0.820513

0

0.002884

0

1

0.102564

false

0

0.076923

0

0.282051

0

null

0

1

0

1

0

null

0

7

6d03a80dd2f5041111d1755e966dd38d4d4a6b96

27,853

py

Python

multiple-languages/python/ros-cdk-vs-1.0.3/src/ros_cdk_vs/__init__.py

aliyun/Resource-Orchestration-Service-Cloud-Development-K

2b81e135002ed81cb72f7d07be7ff497ea39e2e1

[ "Apache-2.0" ]

15

2020-11-10T02:00:28.000Z

2022-02-07T19:28:10.000Z

multiple-languages/python/ros-cdk-vs-1.0.3/src/ros_cdk_vs/__init__.py

aliyun/Resource-Orchestration-Service-Cloud-Development-K

2b81e135002ed81cb72f7d07be7ff497ea39e2e1

[ "Apache-2.0" ]

23

2021-02-02T04:37:02.000Z

2022-03-31T06:41:06.000Z

multiple-languages/python/ros-cdk-vs-1.0.3/src/ros_cdk_vs/__init__.py

aliyun/Resource-Orchestration-Service-Cloud-Development-K

2b81e135002ed81cb72f7d07be7ff497ea39e2e1

[ "Apache-2.0" ]

4

2021-01-13T05:48:43.000Z

2022-03-15T11:26:48.000Z

''' ## Aliyun ROS VS Construct Library This module is part of the AliCloud ROS Cloud Development Kit (ROS CDK) project. ```python # Example automatically generated from non-compiling source. May contain errors. import * as VS from '@alicloud/ros-cdk-vs'; ``` ''' import abc import builtins import datetime import enum import typing import jsii import publication import typing_extensions from ._jsii import * import ros_cdk_core class Group( ros_cdk_core.Resource, metaclass=jsii.JSIIMeta, jsii_type="@alicloud/ros-cdk-vs.Group", ): '''A ROS resource type: ``ALIYUN::VS::Group``.''' def __init__( self, scope: ros_cdk_core.Construct, id: builtins.str, props: "GroupProps", enable_resource_property_constraint: typing.Optional[builtins.bool] = None, ) -> None: '''Create a new ``ALIYUN::VS::Group``. Param scope - scope in which this resource is defined Param id - scoped id of the resource Param props - resource properties :param scope: - :param id: - :param props: - :param enable_resource_property_constraint: - ''' jsii.create(self.__class__, self, [scope, id, props, enable_resource_property_constraint]) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrGbId") def attr_gb_id(self) -> ros_cdk_core.IResolvable: '''Attribute GbId: GB ID space provided. (Applies only to access the space marked States) ''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrGbId")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrGbIp") def attr_gb_ip(self) -> ros_cdk_core.IResolvable: '''Attribute GbIp: GB signaling server address space provided. (Applies only to access the space marked States) ''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrGbIp")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrGbPort") def attr_gb_port(self) -> ros_cdk_core.IResolvable: '''Attribute GbPort: GB Port space provided. (Applies only to access the space marked States) ''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrGbPort")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrId") def attr_id(self) -> ros_cdk_core.IResolvable: '''Attribute Id: Space ID.''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrId")) @jsii.data_type( jsii_type="@alicloud/ros-cdk-vs.GroupProps", jsii_struct_bases=[], name_mapping={ "in_protocol": "inProtocol", "name": "name", "out_protocol": "outProtocol", "play_domain": "playDomain", "push_domain": "pushDomain", "region": "region", "app": "app", "callback": "callback", "description": "description", "enabled": "enabled", "lazy_pull": "lazyPull", }, ) class GroupProps: def __init__( self, *, in_protocol: typing.Union[builtins.str, ros_cdk_core.IResolvable], name: typing.Union[builtins.str, ros_cdk_core.IResolvable], out_protocol: typing.Union[builtins.str, ros_cdk_core.IResolvable], play_domain: typing.Union[builtins.str, ros_cdk_core.IResolvable], push_domain: typing.Union[builtins.str, ros_cdk_core.IResolvable], region: typing.Union[builtins.str, ros_cdk_core.IResolvable], app: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]] = None, callback: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]] = None, description: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]] = None, enabled: typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]] = None, lazy_pull: typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]] = None, ) -> None: '''Properties for defining a ``ALIYUN::VS::Group``. :param in_protocol: Property inProtocol: Access protocol used by the space. Value: gb28181, rtmp :param name: Property name: Space name. :param out_protocol: Property outProtocol: Play protocol used by the space, multivalued separated by commas. Value: flv, hls, rtmp :param play_domain: Property playDomain: Use of the domain name space broadcast stream. :param push_domain: Property pushDomain: Plug flow domain name space to use. (Only access to the space rtmp) :param region: Property region: Space belongs to the region, as a service center. :param app: Property app: Application name space used, the default live. :param callback: Property callback: Updating the space callback device / flow state. :param description: Property description: Space description. :param enabled: Property enabled: Space is enabled. :param lazy_pull: Property lazyPull: Whether to enable on-demand pull flow, default false. ''' self._values: typing.Dict[str, typing.Any] = { "in_protocol": in_protocol, "name": name, "out_protocol": out_protocol, "play_domain": play_domain, "push_domain": push_domain, "region": region, } if app is not None: self._values["app"] = app if callback is not None: self._values["callback"] = callback if description is not None: self._values["description"] = description if enabled is not None: self._values["enabled"] = enabled if lazy_pull is not None: self._values["lazy_pull"] = lazy_pull @builtins.property def in_protocol(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: '''Property inProtocol: Access protocol used by the space. Value: gb28181, rtmp ''' result = self._values.get("in_protocol") assert result is not None, "Required property 'in_protocol' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def name(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: '''Property name: Space name.''' result = self._values.get("name") assert result is not None, "Required property 'name' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def out_protocol(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: '''Property outProtocol: Play protocol used by the space, multivalued separated by commas. Value: flv, hls, rtmp ''' result = self._values.get("out_protocol") assert result is not None, "Required property 'out_protocol' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def play_domain(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: '''Property playDomain: Use of the domain name space broadcast stream.''' result = self._values.get("play_domain") assert result is not None, "Required property 'play_domain' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def push_domain(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: '''Property pushDomain: Plug flow domain name space to use. (Only access to the space rtmp) ''' result = self._values.get("push_domain") assert result is not None, "Required property 'push_domain' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def region(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: '''Property region: Space belongs to the region, as a service center.''' result = self._values.get("region") assert result is not None, "Required property 'region' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def app( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: '''Property app: Application name space used, the default live.''' result = self._values.get("app") return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], result) @builtins.property def callback( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: '''Property callback: Updating the space callback device / flow state.''' result = self._values.get("callback") return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], result) @builtins.property def description( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: '''Property description: Space description.''' result = self._values.get("description") return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], result) @builtins.property def enabled( self, ) -> typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]]: '''Property enabled: Space is enabled.''' result = self._values.get("enabled") return typing.cast(typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], result) @builtins.property def lazy_pull( self, ) -> typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]]: '''Property lazyPull: Whether to enable on-demand pull flow, default false.''' result = self._values.get("lazy_pull") return typing.cast(typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], result) def __eq__(self, rhs: typing.Any) -> builtins.bool: return isinstance(rhs, self.__class__) and rhs._values == self._values def __ne__(self, rhs: typing.Any) -> builtins.bool: return not (rhs == self) def __repr__(self) -> str: return "GroupProps(%s)" % ", ".join( k + "=" + repr(v) for k, v in self._values.items() ) class RosGroup( ros_cdk_core.RosResource, metaclass=jsii.JSIIMeta, jsii_type="@alicloud/ros-cdk-vs.RosGroup", ): '''A ROS template type: ``ALIYUN::VS::Group``.''' def __init__( self, scope: ros_cdk_core.Construct, id: builtins.str, props: "RosGroupProps", enable_resource_property_constraint: builtins.bool, ) -> None: '''Create a new ``ALIYUN::VS::Group``. :param scope: - scope in which this resource is defined. :param id: - scoped id of the resource. :param props: - resource properties. :param enable_resource_property_constraint: - ''' jsii.create(self.__class__, self, [scope, id, props, enable_resource_property_constraint]) @jsii.member(jsii_name="renderProperties") def _render_properties( self, props: typing.Mapping[builtins.str, typing.Any], ) -> typing.Mapping[builtins.str, typing.Any]: ''' :param props: - ''' return typing.cast(typing.Mapping[builtins.str, typing.Any], jsii.invoke(self, "renderProperties", [props])) @jsii.python.classproperty # type: ignore[misc] @jsii.member(jsii_name="ROS_RESOURCE_TYPE_NAME") def ROS_RESOURCE_TYPE_NAME(cls) -> builtins.str: '''The resource type name for this resource class.''' return typing.cast(builtins.str, jsii.sget(cls, "ROS_RESOURCE_TYPE_NAME")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrGbId") def attr_gb_id(self) -> ros_cdk_core.IResolvable: ''' :Attribute: GbId: GB ID space provided. (Applies only to access the space marked States) ''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrGbId")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrGbIp") def attr_gb_ip(self) -> ros_cdk_core.IResolvable: ''' :Attribute: GbIp: GB signaling server address space provided. (Applies only to access the space marked States) ''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrGbIp")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrGbPort") def attr_gb_port(self) -> ros_cdk_core.IResolvable: ''' :Attribute: GbPort: GB Port space provided. (Applies only to access the space marked States) ''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrGbPort")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="attrId") def attr_id(self) -> ros_cdk_core.IResolvable: ''' :Attribute: Id: Space ID. ''' return typing.cast(ros_cdk_core.IResolvable, jsii.get(self, "attrId")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="rosProperties") def _ros_properties(self) -> typing.Mapping[builtins.str, typing.Any]: return typing.cast(typing.Mapping[builtins.str, typing.Any], jsii.get(self, "rosProperties")) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="enableResourcePropertyConstraint") def enable_resource_property_constraint(self) -> builtins.bool: return typing.cast(builtins.bool, jsii.get(self, "enableResourcePropertyConstraint")) @enable_resource_property_constraint.setter def enable_resource_property_constraint(self, value: builtins.bool) -> None: jsii.set(self, "enableResourcePropertyConstraint", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="inProtocol") def in_protocol(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: inProtocol: Access protocol used by the space. Value: gb28181, rtmp ''' return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], jsii.get(self, "inProtocol")) @in_protocol.setter def in_protocol( self, value: typing.Union[builtins.str, ros_cdk_core.IResolvable], ) -> None: jsii.set(self, "inProtocol", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="name") def name(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: name: Space name. ''' return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], jsii.get(self, "name")) @name.setter def name(self, value: typing.Union[builtins.str, ros_cdk_core.IResolvable]) -> None: jsii.set(self, "name", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="outProtocol") def out_protocol(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: outProtocol: Play protocol used by the space, multivalued separated by commas. Value: flv, hls, rtmp ''' return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], jsii.get(self, "outProtocol")) @out_protocol.setter def out_protocol( self, value: typing.Union[builtins.str, ros_cdk_core.IResolvable], ) -> None: jsii.set(self, "outProtocol", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="playDomain") def play_domain(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: playDomain: Use of the domain name space broadcast stream. ''' return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], jsii.get(self, "playDomain")) @play_domain.setter def play_domain( self, value: typing.Union[builtins.str, ros_cdk_core.IResolvable], ) -> None: jsii.set(self, "playDomain", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="pushDomain") def push_domain(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: pushDomain: Plug flow domain name space to use. (Only access to the space rtmp) ''' return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], jsii.get(self, "pushDomain")) @push_domain.setter def push_domain( self, value: typing.Union[builtins.str, ros_cdk_core.IResolvable], ) -> None: jsii.set(self, "pushDomain", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="region") def region(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: region: Space belongs to the region, as a service center. ''' return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], jsii.get(self, "region")) @region.setter def region( self, value: typing.Union[builtins.str, ros_cdk_core.IResolvable], ) -> None: jsii.set(self, "region", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="app") def app( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: ''' :Property: app: Application name space used, the default live. ''' return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], jsii.get(self, "app")) @app.setter def app( self, value: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], ) -> None: jsii.set(self, "app", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="callback") def callback( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: ''' :Property: callback: Updating the space callback device / flow state ''' return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], jsii.get(self, "callback")) @callback.setter def callback( self, value: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], ) -> None: jsii.set(self, "callback", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="description") def description( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: ''' :Property: description: Space description. ''' return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], jsii.get(self, "description")) @description.setter def description( self, value: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], ) -> None: jsii.set(self, "description", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="enabled") def enabled( self, ) -> typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]]: ''' :Property: enabled: Space is enabled. ''' return typing.cast(typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], jsii.get(self, "enabled")) @enabled.setter def enabled( self, value: typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], ) -> None: jsii.set(self, "enabled", value) @builtins.property # type: ignore[misc] @jsii.member(jsii_name="lazyPull") def lazy_pull( self, ) -> typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]]: ''' :Property: lazyPull: Whether to enable on-demand pull flow, default false ''' return typing.cast(typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], jsii.get(self, "lazyPull")) @lazy_pull.setter def lazy_pull( self, value: typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], ) -> None: jsii.set(self, "lazyPull", value) @jsii.data_type( jsii_type="@alicloud/ros-cdk-vs.RosGroupProps", jsii_struct_bases=[], name_mapping={ "in_protocol": "inProtocol", "name": "name", "out_protocol": "outProtocol", "play_domain": "playDomain", "push_domain": "pushDomain", "region": "region", "app": "app", "callback": "callback", "description": "description", "enabled": "enabled", "lazy_pull": "lazyPull", }, ) class RosGroupProps: def __init__( self, *, in_protocol: typing.Union[builtins.str, ros_cdk_core.IResolvable], name: typing.Union[builtins.str, ros_cdk_core.IResolvable], out_protocol: typing.Union[builtins.str, ros_cdk_core.IResolvable], play_domain: typing.Union[builtins.str, ros_cdk_core.IResolvable], push_domain: typing.Union[builtins.str, ros_cdk_core.IResolvable], region: typing.Union[builtins.str, ros_cdk_core.IResolvable], app: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]] = None, callback: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]] = None, description: typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]] = None, enabled: typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]] = None, lazy_pull: typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]] = None, ) -> None: '''Properties for defining a ``ALIYUN::VS::Group``. :param in_protocol: :param name: :param out_protocol: :param play_domain: :param push_domain: :param region: :param app: :param callback: :param description: :param enabled: :param lazy_pull: ''' self._values: typing.Dict[str, typing.Any] = { "in_protocol": in_protocol, "name": name, "out_protocol": out_protocol, "play_domain": play_domain, "push_domain": push_domain, "region": region, } if app is not None: self._values["app"] = app if callback is not None: self._values["callback"] = callback if description is not None: self._values["description"] = description if enabled is not None: self._values["enabled"] = enabled if lazy_pull is not None: self._values["lazy_pull"] = lazy_pull @builtins.property def in_protocol(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: inProtocol: Access protocol used by the space. Value: gb28181, rtmp ''' result = self._values.get("in_protocol") assert result is not None, "Required property 'in_protocol' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def name(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: name: Space name. ''' result = self._values.get("name") assert result is not None, "Required property 'name' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def out_protocol(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: outProtocol: Play protocol used by the space, multivalued separated by commas. Value: flv, hls, rtmp ''' result = self._values.get("out_protocol") assert result is not None, "Required property 'out_protocol' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def play_domain(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: playDomain: Use of the domain name space broadcast stream. ''' result = self._values.get("play_domain") assert result is not None, "Required property 'play_domain' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def push_domain(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: pushDomain: Plug flow domain name space to use. (Only access to the space rtmp) ''' result = self._values.get("push_domain") assert result is not None, "Required property 'push_domain' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def region(self) -> typing.Union[builtins.str, ros_cdk_core.IResolvable]: ''' :Property: region: Space belongs to the region, as a service center. ''' result = self._values.get("region") assert result is not None, "Required property 'region' is missing" return typing.cast(typing.Union[builtins.str, ros_cdk_core.IResolvable], result) @builtins.property def app( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: ''' :Property: app: Application name space used, the default live. ''' result = self._values.get("app") return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], result) @builtins.property def callback( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: ''' :Property: callback: Updating the space callback device / flow state ''' result = self._values.get("callback") return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], result) @builtins.property def description( self, ) -> typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]]: ''' :Property: description: Space description. ''' result = self._values.get("description") return typing.cast(typing.Optional[typing.Union[builtins.str, ros_cdk_core.IResolvable]], result) @builtins.property def enabled( self, ) -> typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]]: ''' :Property: enabled: Space is enabled. ''' result = self._values.get("enabled") return typing.cast(typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], result) @builtins.property def lazy_pull( self, ) -> typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]]: ''' :Property: lazyPull: Whether to enable on-demand pull flow, default false ''' result = self._values.get("lazy_pull") return typing.cast(typing.Optional[typing.Union[builtins.bool, ros_cdk_core.IResolvable]], result) def __eq__(self, rhs: typing.Any) -> builtins.bool: return isinstance(rhs, self.__class__) and rhs._values == self._values def __ne__(self, rhs: typing.Any) -> builtins.bool: return not (rhs == self) def __repr__(self) -> str: return "RosGroupProps(%s)" % ", ".join( k + "=" + repr(v) for k, v in self._values.items() ) __all__ = [ "Group", "GroupProps", "RosGroup", "RosGroupProps", ] publication.publish()

38.900838

138

0.653682

3,321

27,853

5.323999

0.056308

0.042758

0.067869

0.136587

0.884678

0.88055

0.870539

0.868729

0.848255

0

0.000926

0.224572

27,853

715

139

38.955245

0.817715

0.191936

0

0.758315

1

0

0.095014

0.012217

0

0.026608

1

0.148559

false

0

0.022173

0.017738

0.292683

0

null

0

1

0

1

0

null

0

8

6d2470084ad5959dc06af1c7b80c8954e7726e7c

459

py

Python

models.py

maciejszewczyk/zlobki-warszawa-rekrutacja

f266e31a72f79d7b17e6a95439f97a89777ca59b

[ "Apache-2.0" ]

null

models.py

maciejszewczyk/zlobki-warszawa-rekrutacja

f266e31a72f79d7b17e6a95439f97a89777ca59b

[ "Apache-2.0" ]

null

models.py

maciejszewczyk/zlobki-warszawa-rekrutacja

f266e31a72f79d7b17e6a95439f97a89777ca59b

[ "Apache-2.0" ]

null

from google.appengine.ext import ndb class TestNote(ndb.Model): date_created = ndb.DateProperty(auto_now_add=True) db_nursery_no1 = ndb.IntegerProperty() db_nursery_no2 = ndb.IntegerProperty() db_nursery_no3 = ndb.IntegerProperty() class Note(ndb.Model): date_created = ndb.DateProperty(auto_now_add=True) db_nursery_no1 = ndb.IntegerProperty() db_nursery_no2 = ndb.IntegerProperty() db_nursery_no3 = ndb.IntegerProperty()

28.6875

54

0.755991

60

459

5.483333

0.383333

0.164134

0.243161

0.328267

0.838906

0

0.015345

0.148148

459

15

55

30.6

0.826087

0

0.727273

0

1

0

false

0

0.090909

0

1

0

null

0

1

0

1

0

null

0

1

0

10

edc5f652c3f03c6cdb42c94b2dab44ce39e35eb2

5,586

py

Python

edbdeploy/spec/gcloud.py

vincentp7212/postgres-deployment

ea0ed0e06a4eb99cc28600398eddcf2320778113

[ "BSD-3-Clause" ]

58

2020-02-24T21:02:50.000Z

2022-03-28T14:51:56.000Z

edbdeploy/spec/gcloud.py

vincentp7212/postgres-deployment

ea0ed0e06a4eb99cc28600398eddcf2320778113

[ "BSD-3-Clause" ]

108

2020-09-18T12:53:44.000Z

2022-02-02T09:02:31.000Z

edbdeploy/spec/gcloud.py

vincentp7212/postgres-deployment

ea0ed0e06a4eb99cc28600398eddcf2320778113

[ "BSD-3-Clause" ]

47

2020-03-04T15:51:01.000Z

2022-02-27T13:48:05.000Z

from . import DefaultGcloudSpec from . import SpecValidator GCVMSpec = { 'postgres_server': { 'instance_type': SpecValidator( type='choice', choices=[ 'e2-standard-2', 'e2-standard-4', 'e2-standard-8', 'e2-standard-16', 'e2-standard-32', 'e2-highmem-2', 'e2-highmem-4', 'e2-highmem-8', 'e2-highmem-16', 'n2-highmem-4', 'n2-highmem-8', 'n2-highmem-16', 'n2-highmem-32' ], default='e2-standard-4' ), 'volume': { 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-standard' ), 'size': SpecValidator( type='integer', min=10, max=16000, default=50 ) }, 'additional_volumes': { 'count': SpecValidator( type='integer', min=0, max=5, default=2 ), 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-ssd' ), 'size': SpecValidator( type='integer', min=10, max=65536, default=100 ) } }, 'bdr_server': { 'instance_type': SpecValidator( type='choice', choices=[ 'e2-standard-2', 'e2-standard-4', 'e2-standard-8', 'e2-standard-16', 'e2-standard-32', 'e2-highmem-2', 'e2-highmem-4', 'e2-highmem-8', 'e2-highmem-16', 'n2-highmem-4', 'n2-highmem-8', 'n2-highmem-16', 'n2-highmem-32' ], default='e2-standard-4' ), 'volume': { 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-standard' ), 'size': SpecValidator( type='integer', min=10, max=16000, default=50 ) }, 'additional_volumes': { 'count': SpecValidator( type='integer', min=0, max=5, default=2 ), 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-ssd' ), 'size': SpecValidator( type='integer', min=10, max=65536, default=100 ) } }, 'bdr_witness_server': { 'instance_type': SpecValidator( type='choice', choices=[ 'e2-standard-2', 'e2-standard-4', 'e2-standard-8', 'e2-standard-16', 'e2-standard-32', 'e2-highmem-2', 'e2-highmem-4', 'e2-highmem-8', 'e2-highmem-16' ], default='e2-standard-2' ), 'volume': { 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-standard' ), 'size': SpecValidator( type='integer', min=10, max=65536, default=50 ) } }, 'pooler_server': { 'instance_type': SpecValidator( type='choice', choices=[ 'e2-standard-2', 'e2-standard-4', 'e2-standard-8', 'e2-standard-16', 'e2-standard-32', 'e2-highmem-2', 'e2-highmem-4', 'e2-highmem-8', 'e2-highmem-16' ], default='e2-standard-2' ), 'volume': { 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-standard' ), 'size': SpecValidator( type='integer', min=10, max=65536, default=50 ) } }, 'barman_server': { 'instance_type': SpecValidator( type='choice', choices=[ 'e2-standard-2', 'e2-standard-4', 'e2-standard-8', 'e2-standard-16', 'e2-standard-32', 'e2-highmem-2', 'e2-highmem-4', 'e2-highmem-8', 'e2-highmem-16' ], default='e2-standard-2' ), 'volume': { 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-standard' ), 'size': SpecValidator( type='integer', min=10, max=65536, default=50 ) }, 'additional_volumes': { 'count': SpecValidator( type='integer', min=0, max=1, default=1 ), 'type': SpecValidator( type='choice', choices=['pd-standard', 'pd-ssd'], default='pd-ssd' ), 'size': SpecValidator( type='integer', min=10, max=65536, default=300 ) } } } GCloudSpec = {**DefaultGcloudSpec, **GCVMSpec}

29.712766

67

0.389545

447

5,586

4.836689

0.100671

0.13876

0.126272

0.16235

0.938945

0

0.073663

0.467777

5,586

188

68

29.712766

0.653549

0

0.817204

0

0.251656

0

1

0

false

0

0.010753

0

0.010753

0

null

0

1

0

1

0

null

0

8

edcd781249f301c21c8684eab7444859ee5fddf3

858

py

Python

tests/test_number.py

silverag-corgi/python-lib-for-me

ed30c7b879396ca6af53c762d7c919b0ea44bea7

[ "MIT" ]

null

tests/test_number.py

silverag-corgi/python-lib-for-me

ed30c7b879396ca6af53c762d7c919b0ea44bea7

[ "MIT" ]

1

2022-02-06T08:21:56.000Z

2022-02-06T15:48:26.000Z

tests/test_number.py

silverag-corgi/python-lib-for-me

ed30c7b879396ca6af53c762d7c919b0ea44bea7

[ "MIT" ]

null

from decimal import Decimal import python_lib_for_me as pyl def test_round_half_up_01() -> None: actual_values: Decimal = pyl.round_half_up(1.234, 2) expected_values: Decimal = Decimal('1.23') assert actual_values == expected_values def test_round_half_up_02() -> None: actual_values: Decimal = pyl.round_half_up(1.235, 2) expected_values: Decimal = Decimal('1.24') assert actual_values == expected_values def test_round_half_up_03() -> None: actual_values: Decimal = pyl.round_half_up(Decimal('1.234'), 2) expected_values: Decimal = Decimal('1.23') assert actual_values == expected_values def test_round_half_up_04() -> None: actual_values: Decimal = pyl.round_half_up(Decimal('1.235'), 2) expected_values: Decimal = Decimal('1.24') assert actual_values == expected_values

30.642857

68

0.706294

125

858

4.504

0.232

0.127886

0.156306

0.113677

0.898757

0.866785

0.735346

0

0.057307

0.18648

858

27

69

31.777778

0.749284

0

0.444444

0

0.031288

0

0.222222

1

0.222222

true

0

0.111111

0

0.333333

0

null

0

1

0

null

0

1

0

8

ede1ff49675ed35f09af4904757c33ac1504706b

33

py

Python

function_20373684.py

YJoJ/Study-16

4d2b6d0d50185a904be856b7bb69e310dbe7df0f

[ "MIT" ]

1

2022-03-19T08:09:36.000Z

function_20373684.py

YJoJ/Study-16

4d2b6d0d50185a904be856b7bb69e310dbe7df0f

[ "MIT" ]

null

function_20373684.py

YJoJ/Study-16

4d2b6d0d50185a904be856b7bb69e310dbe7df0f

[ "MIT" ]

1

2022-03-19T08:09:48.000Z

print('My student_id: 20373684')

16.5

32

0.757576

5

33

4.8

1

0

0.266667

0.090909

33

1

33

0.533333

0

0.69697

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

7

610c3175273a256ab79cdd44cf16d82dd26e8101

21,918

py

Python

tests/platforms/macOS/app/test_package.py

pybee/briefcase

d7e9aa7bf15aa2abbc71e97aef9bea287129fdaa

[ "BSD-3-Clause" ]

522

2015-07-28T16:06:18.000Z

2019-03-25T17:16:55.000Z

tests/platforms/macOS/app/test_package.py

pybee/briefcase

d7e9aa7bf15aa2abbc71e97aef9bea287129fdaa

[ "BSD-3-Clause" ]

154

2015-09-17T02:50:55.000Z

2019-03-22T07:10:34.000Z

tests/platforms/macOS/app/test_package.py

pybee/briefcase

d7e9aa7bf15aa2abbc71e97aef9bea287129fdaa

[ "BSD-3-Clause" ]

105

2015-09-25T08:43:26.000Z

2019-03-25T15:59:27.000Z

import os from unittest import mock import pytest from briefcase.exceptions import BriefcaseCommandError from briefcase.platforms.macOS.app import macOSAppPackageCommand @pytest.fixture def package_command(tmp_path): command = macOSAppPackageCommand(base_path=tmp_path) command.select_identity = mock.MagicMock() command.sign_app = mock.MagicMock() command.sign_file = mock.MagicMock() command.notarize = mock.MagicMock() command.dmgbuild = mock.MagicMock() return command def test_package_app(package_command, first_app_with_binaries, tmp_path, capsys): """A macOS App can be packaged.""" # Select a codesigning identity package_command.select_identity.return_value = ( "CAFEBEEF", "Sekrit identity (DEADBEEF)", ) # Package the app. Sign and notarize by default package_command.package_app(first_app_with_binaries) # A request has been made to sign the app package_command.sign_app.assert_called_once_with( app=first_app_with_binaries, identity="CAFEBEEF" ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, }, ) # A request was made to sign the DMG as well. # This ignores the calls that would have been made transitively # by calling sign_app() package_command.sign_file.assert_called_once_with( tmp_path / "macOS" / "First App-0.0.1.dmg", identity="CAFEBEEF", ) # A request was made to notarize the DMG package_command.notarize.assert_called_once_with( tmp_path / "macOS" / "First App-0.0.1.dmg", team_id="DEADBEEF", ) # The app doesn't specify an app icon or installer icon, so there's no # mention about the DMG installer icon in the console log. assert "DMG installer icon" not in capsys.readouterr().out def test_package_app_no_notarization( package_command, first_app_with_binaries, tmp_path, capsys ): """A macOS App can be packaged without notarization.""" # Select a codesigning identity package_command.select_identity.return_value = ( "CAFEBEEF", "Sekrit identity (DEADBEEF)", ) # Package the app; sign by default, but disable notarization package_command.package_app(first_app_with_binaries, notarize_app=False) # A request has been made to sign the app package_command.sign_app.assert_called_once_with( app=first_app_with_binaries, identity="CAFEBEEF" ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, }, ) # A request was made to sign the DMG as well. # This ignores the calls that would have been made transitively # by calling sign_app() package_command.sign_file.assert_called_once_with( tmp_path / "macOS" / "First App-0.0.1.dmg", identity="CAFEBEEF", ) # A request was made to notarize the DMG package_command.notarize.assert_not_called() # The app doesn't specify an app icon or installer icon, so there's no # mention about the DMG installer icon in the console log. assert "DMG installer icon" not in capsys.readouterr().out def test_package_app_sign_failure(package_command, first_app_with_binaries, tmp_path): """If the signing process can't be completed, an error is raised.""" # Select a codesigning identity package_command.select_identity.return_value = ( "CAFEBEEF", "Sekrit identity (DEADBEEF)", ) # Raise an error when attempting to sign the app package_command.sign_app.side_effect = BriefcaseCommandError("Unable to code sign") # Attempt to package the app; it should raise an error with pytest.raises(BriefcaseCommandError, match=r"Unable to code sign"): package_command.package_app(first_app_with_binaries) # A request has been made to sign the app package_command.sign_app.assert_called_once_with( app=first_app_with_binaries, identity="CAFEBEEF" ) # dmgbuild has not been called package_command.dmgbuild.build_dmg.assert_not_called() # No attempt was made to sign the dmg either # This ignores the calls that would have been made transitively # by calling sign_app() package_command.sign_file.assert_not_called() def test_package_app_no_sign(package_command, first_app_with_binaries): """A macOS App can be packaged without signing or notarization.""" # Package the app without code signing or notarization package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=False, ) # No code signing or notarization has been performed. assert package_command.select_identity.call_count == 0 assert package_command.sign_app.call_count == 0 assert package_command.sign_file.call_count == 0 assert package_command.notarize.call_count == 0 def test_package_app_notarize_without_sign(package_command, first_app_with_binaries): """A macOS App cannot be notarized if it wasn't signed.""" # Package the app without code signing with pytest.raises( BriefcaseCommandError, match=r"Can't notarize an app that hasn't been signed", ): package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=True, ) # No code signing or notarization has been performed. assert package_command.select_identity.call_count == 0 assert package_command.sign_app.call_count == 0 assert package_command.sign_file.call_count == 0 assert package_command.notarize.call_count == 0 def test_package_app_notarize_without_sign_default_notariztion( package_command, first_app_with_binaries ): """A macOS App will default to no notarization if it wasn't signed.""" # Package the app without code signing; notarization will be disabled # even though it isn't specified package_command.package_app( first_app_with_binaries, sign_app=False, ) # No code signing or notarization has been performed. assert package_command.select_identity.call_count == 0 assert package_command.sign_app.call_count == 0 assert package_command.sign_file.call_count == 0 assert package_command.notarize.call_count == 0 def test_package_app_adhoc_sign(package_command, first_app_with_binaries, tmp_path): """A macOS App can be packaged and signed with adhoc identity.""" # Package the app with an adhoc identity. # Explicitly disable notarization (can't adhoc notarize an app) package_command.package_app( first_app_with_binaries, adhoc_sign=True, notarize_app=False, ) # A request has been made to sign the app package_command.sign_app.assert_called_once_with( app=first_app_with_binaries, identity="-" ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, }, ) # A request was made to sign the DMG as well. # This ignores the calls that would have been made transitively # by calling sign_app() package_command.sign_file.assert_called_once_with( tmp_path / "macOS" / "First App-0.0.1.dmg", identity="-", ) # No request was made to notarize package_command.notarize.assert_not_called() def test_package_app_adhoc_sign_default_notarization( package_command, first_app_with_binaries, tmp_path ): """An adhoc signed app is not notarized by default.""" # Package the app with an adhoc identity; notarization will # be disabled as a default package_command.package_app( first_app_with_binaries, adhoc_sign=True, ) # A request has been made to sign the app package_command.sign_app.assert_called_once_with( app=first_app_with_binaries, identity="-" ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, }, ) # A request was made to sign the DMG as well. # This ignores the calls that would have been made transitively # by calling sign_app() package_command.sign_file.assert_called_once_with( tmp_path / "macOS" / "First App-0.0.1.dmg", identity="-", ) # No request was made to notarize package_command.notarize.assert_not_called() def test_package_bare_app(package_command, first_app_with_binaries, tmp_path): """A macOS App can be packaged without building dmg.""" # Select a code signing identity package_command.select_identity.return_value = ( "CAFEBEEF", "Sekrit identity (DEADBEEF)", ) # Package the app in app (not DMG) format package_command.package_app(first_app_with_binaries, packaging_format="app") # A request has been made to sign the app package_command.sign_app.assert_called_once_with( app=first_app_with_binaries, identity="CAFEBEEF" ) # A request has been made to notarize the app package_command.notarize.assert_called_once_with( tmp_path / "macOS" / "app" / "First App" / "First App.app", team_id="DEADBEEF", ) # No dmg was built. assert package_command.dmgbuild.build_dmg.call_count == 0 # If the DMG doesn't exist, it can't be signed either. # This ignores the calls that would have been made transitively # by calling sign_app() assert package_command.sign_file.call_count == 0 def test_package_bare_app_no_sign(package_command, first_app_with_binaries): """A macOS App can be packaged without building dmg, and without signing.""" # Select a code signing identity package_command.select_identity.return_value = ( "CAFEBEEF", "Sekrit identity (DEADBEEF)", ) # Package the app in app (not DMG) format, disabling signing and notarization package_command.package_app( first_app_with_binaries, packaging_format="app", sign_app=False, notarize_app=False, ) # No request has been made to sign the app package_command.sign_app.assert_not_called() # No request has been made to notarize the app package_command.notarize.assert_not_called() # No dmg was built. assert package_command.dmgbuild.build_dmg.call_count == 0 # If the DMG doesn't exist, it can't be signed either. # This ignores the calls that would have been made transitively # by calling sign_app() assert package_command.sign_file.call_count == 0 def test_package_bare_app_no_notarization(package_command, first_app_with_binaries): """A macOS App can be packaged without building dmg, and without notarization.""" # Select a code signing identity package_command.select_identity.return_value = ( "CAFEBEEF", "Sekrit identity (DEADBEEF)", ) # Package the app in app (not DMG) format, disabling notarization package_command.package_app( first_app_with_binaries, packaging_format="app", notarize_app=False, ) # A request has been made to sign the app package_command.sign_app.assert_called_once_with( app=first_app_with_binaries, identity="CAFEBEEF" ) # No request has been made to notarize the app package_command.notarize.assert_not_called() # No dmg was built. assert package_command.dmgbuild.build_dmg.call_count == 0 # If the DMG doesn't exist, it can't be signed either. # This ignores the calls that would have been made transitively # by calling sign_app() assert package_command.sign_file.call_count == 0 def test_dmg_with_installer_icon(package_command, first_app_with_binaries, tmp_path): """An installer icon can be specified for a DMG.""" # Specify an installer icon, and create the matching file. first_app_with_binaries.installer_icon = "pretty" with open(tmp_path / "pretty.icns", "wb") as f: f.write(b"A pretty installer icon") # Package the app without signing or notarization package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=False, ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, "icon": os.fsdecode(tmp_path / "pretty.icns"), }, ) def test_dmg_with_missing_installer_icon( package_command, first_app_with_binaries, tmp_path, capsys ): """If an installer icon is specified, but the specific file is missing, there is a warning.""" # Specify an installer icon, but don't create the matching file. first_app_with_binaries.installer_icon = "pretty" # Package the app without signing or notarization package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=False, ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, }, ) # The warning about a missing icon was output assert ( "Can't find pretty.icns to use as DMG installer icon\n" in capsys.readouterr().out ) def test_dmg_with_app_installer_icon( package_command, first_app_with_binaries, tmp_path ): """An installer will fall back to an app icon for a DMG.""" # Specify an app icon, and create the matching file. first_app_with_binaries.icon = "pretty_app" with open(tmp_path / "pretty_app.icns", "wb") as f: f.write(b"A pretty app icon") # Package the app without signing or notarization package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=False, ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, "icon": os.fsdecode(tmp_path / "pretty_app.icns"), }, ) def test_dmg_with_missing_app_installer_icon( package_command, first_app_with_binaries, tmp_path, capsys ): """If an app icon is specified, but the specific file is missing, there is a warning.""" # Specify an app icon, but don't create the matching file. first_app_with_binaries.icon = "pretty_app" # Package the app without signing or notarization package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=False, ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, }, ) # The warning about a missing icon was output assert ( "Can't find pretty_app.icns to use as fallback DMG installer icon\n" in capsys.readouterr().out ) def test_dmg_with_installer_background( package_command, first_app_with_binaries, tmp_path ): """An installer can be built with an installer background.""" # Specify an installer background, and create the matching file. first_app_with_binaries.installer_background = "pretty_background" with open(tmp_path / "pretty_background.png", "wb") as f: f.write(b"A pretty background") # Package the app without signing or notarization package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=False, ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, "background": os.fsdecode(tmp_path / "pretty_background.png"), }, ) def test_dmg_with_missing_installer_background( package_command, first_app_with_binaries, tmp_path, capsys ): """If an installer image is specified, but the specific file is missing, there is a warning.""" # Specify an installer background, but don't create the matching file. first_app_with_binaries.installer_background = "pretty_background" # Package the app without signing or notarization package_command.package_app( first_app_with_binaries, sign_app=False, notarize_app=False, ) # The DMG has been built as expected package_command.dmgbuild.build_dmg.assert_called_once_with( filename=os.fsdecode(tmp_path / "macOS" / "First App-0.0.1.dmg"), volume_name="First App 0.0.1", settings={ "files": [ os.fsdecode(tmp_path / "macOS" / "app" / "First App" / "First App.app") ], "symlinks": {"Applications": "/Applications"}, "icon_locations": { "First App.app": (75, 75), "Applications": (225, 75), }, "window_rect": ((600, 600), (350, 150)), "icon_size": 64, "text_size": 12, }, ) # The warning about a missing background was output assert ( "Can't find pretty_background.png to use as DMG background\n" in capsys.readouterr().out )

34.354232

87

0.641482

2,828

21,918

4.747525

0.066124

0.061969

0.042008

0.070013

0.904365

0.88917

0.869805

0.857888

0.851408

0.830106

0

0.021151

0.260106

21,918

637

88

34.408163

0.806746

0.240031

0

0.708434

0

0.165836

0.003828

0

0.13012

1

0.043373

false

0

0.012048

0

0.057831

0

null

0

1

0

1

0

null

0

7

b61d4bcb58f9024e0557bb6897cf107a16734f5b

159

py

Python

src/dataset/__init__.py

eclipsesource/squeezeDet

77a9f03f52a5d6c99998a4dbcfb20d45d6b7a8d7

[ "BSD-2-Clause" ]

null

src/dataset/__init__.py

eclipsesource/squeezeDet

77a9f03f52a5d6c99998a4dbcfb20d45d6b7a8d7

[ "BSD-2-Clause" ]

null

src/dataset/__init__.py

eclipsesource/squeezeDet

77a9f03f52a5d6c99998a4dbcfb20d45d6b7a8d7

[ "BSD-2-Clause" ]

2

2020-06-13T22:40:45.000Z

2020-06-13T22:44:03.000Z

#from kitti import kitti #from pascal_voc import pascal_voc from __future__ import absolute_import from .kitti import kitti from .pascal_voc import pascal_voc

26.5

38

0.849057

25

159

5.04

0.28

0.285714

0.238095

0.31746

0.761905

0

0.125786

159

6

39

26.5

0.906475

0.352201

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

1

0

13

b65abca1ddb89cf25243e36dc95fc69e1064e38a

4,321

py

Python

tests/unit/test_SkipList_hypothesis.py

paulross/skiplist

324b5706b1beca589612c1da496ad5c12014686d

[ "MIT" ]

32

2017-10-03T15:35:30.000Z

2022-03-07T06:46:57.000Z

tests/unit/test_SkipList_hypothesis.py

paulross/skiplist

324b5706b1beca589612c1da496ad5c12014686d

[ "MIT" ]

6

2017-08-18T17:06:37.000Z

2022-03-25T15:03:11.000Z

tests/unit/test_SkipList_hypothesis.py

paulross/skiplist

324b5706b1beca589612c1da496ad5c12014686d

[ "MIT" ]

6

2019-08-07T03:23:45.000Z

2022-01-03T09:05:56.000Z

import sys import hypothesis import hypothesis.strategies as hst import pytest import orderedstructs from .compat_23 import int_type @hypothesis.given(hst.lists(hst.integers(min_value=orderedstructs.min_long(), max_value=orderedstructs.max_long()))) def test_hypothesis_insert_integers(lst): sl = orderedstructs.SkipList(int_type) for v in lst: sl.insert(int_type(v)) result = [sl.at(i) for i in range(sl.size())] assert result == sorted(lst) @hypothesis.given(hst.lists(hst.floats(allow_nan=False))) def test_hypothesis_insert_floats_no_nan(lst): sl = orderedstructs.SkipList(float) for v in lst: sl.insert(v) result = [sl.at(i) for i in range(sl.size())] assert result == sorted(lst) @hypothesis.given(hst.lists(hst.floats(allow_nan=False, allow_infinity=True))) def test_hypothesis_insert_floats_no_nan_with_infinity(lst): sl = orderedstructs.SkipList(float) for v in lst: sl.insert(v) result = [sl.at(i) for i in range(sl.size())] assert result == sorted(lst) @hypothesis.given(hst.lists(hst.binary())) def test_hypothesis_insert_bytes(lst): sl = orderedstructs.SkipList(bytes) for v in lst: sl.insert(v) result = [sl.at(i) for i in range(sl.size())] assert result == sorted(lst) @hypothesis.given(hst.lists(hst.integers(min_value=orderedstructs.min_long(), max_value=orderedstructs.max_long()))) def test_hypothesis_insert_remove_integers(lst): sl = orderedstructs.SkipList(int_type) for v in lst: sl.insert(int_type(v)) for v in lst: sl.remove(int_type(v)) assert sl.size() == 0 @hypothesis.given(hst.lists(hst.floats(allow_nan=False))) def test_hypothesis_insert_remove_floats_no_nan(lst): sl = orderedstructs.SkipList(float) for v in lst: sl.insert(v) for v in lst: sl.remove(v) assert sl.size() == 0 @hypothesis.given(hst.lists(hst.floats(allow_nan=False, allow_infinity=True))) def test_hypothesis_insert_remove_floats_no_nan_with_infinity(lst): sl = orderedstructs.SkipList(float) for v in lst: sl.insert(v) for v in lst: sl.remove(v) assert sl.size() == 0 @hypothesis.given(hst.lists(hst.binary())) def test_hypothesis_insert_remove_bytes(lst): sl = orderedstructs.SkipList(bytes) for v in lst: sl.insert(v) for v in lst: sl.remove(v) assert sl.size() == 0 @hypothesis.given(hst.lists(hst.integers(min_value=orderedstructs.min_long(), max_value=orderedstructs.max_long()))) def test_hypothesis_index_integers(lst): sl = orderedstructs.SkipList(int_type) for v in lst: sl.insert(int_type(v)) reference = sorted(lst) for v in lst: assert reference.index(v) == sl.index(int_type(v)) @hypothesis.given(hst.lists(hst.floats(allow_nan=False, allow_infinity=True))) def test_hypothesis_index_floats(lst): sl = orderedstructs.SkipList(float) for v in lst: sl.insert(v) reference = sorted(lst) for v in lst: assert reference.index(v) == sl.index(v) @hypothesis.given(hst.lists(hst.binary())) def test_hypothesis_index_bytes(lst): sl = orderedstructs.SkipList(bytes) for v in lst: sl.insert(v) reference = sorted(lst) for v in lst: assert reference.index(v) == sl.index(v) @hypothesis.given(hst.lists(hst.integers(min_value=orderedstructs.min_long(), max_value=orderedstructs.max_long()))) def test_hypothesis_index_matches_at_integers(lst): sl = orderedstructs.SkipList(int_type) for v in lst: sl.insert(int_type(v)) for v in lst: assert sl.at(sl.index(int_type(v))) == v @hypothesis.given(hst.lists(hst.floats(allow_nan=False, allow_infinity=True))) def test_hypothesis_index_matches_at_floats(lst): sl = orderedstructs.SkipList(float) for v in lst: sl.insert(v) for v in lst: assert sl.at(sl.index(v)) == v @hypothesis.given(hst.lists(hst.binary())) def test_hypothesis_index_matches_at_bytes(lst): sl = orderedstructs.SkipList(bytes) for v in lst: sl.insert(v) for v in lst: assert sl.at(sl.index(v)) == v

32.488722

79

0.66605

626

4,321

4.432907

0.083067

0.057658

0.051892

0.077838

0.956757

0.947387

0.937658

0.934414

0.93009

0

0.001766

0.213839

4,321

132

80

32.734848

0.815131

0

0.8

0

0.121739

1

0.121739

false

0

0.052174

0

0.173913

0

null

0

1

0

1

0

null

0

7

b66b9b720d0626ff6f5004a042a966d9c0bc13fd

34,087

py

Python

sdk/finbourne_insights/api/vendor_logs_api.py

finbourne/finbourne-insights-sdk-python

33ea49f0157def867405725013218d6f29cc2ee0

[ "MIT" ]

null

sdk/finbourne_insights/api/vendor_logs_api.py

finbourne/finbourne-insights-sdk-python

33ea49f0157def867405725013218d6f29cc2ee0

[ "MIT" ]

null

sdk/finbourne_insights/api/vendor_logs_api.py

finbourne/finbourne-insights-sdk-python

33ea49f0157def867405725013218d6f29cc2ee0

[ "MIT" ]

null

# coding: utf-8 """ FINBOURNE Insights API FINBOURNE Technology # noqa: E501 The version of the OpenAPI document: 0.0.238 Contact: info@finbourne.com Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from finbourne_insights.api_client import ApiClient from finbourne_insights.exceptions import ( # noqa: F401 ApiTypeError, ApiValueError ) class VendorLogsApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def get_vendor_log(self, id, **kwargs): # noqa: E501 """[EXPERIMENTAL] GetVendorLog: Get the log for a specific vendor request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_vendor_log(id, async_req=True) >>> result = thread.get() :param id: The identifier of the request to obtain the log for. (required) :type id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: VendorLog """ kwargs['_return_http_data_only'] = True return self.get_vendor_log_with_http_info(id, **kwargs) # noqa: E501 def get_vendor_log_with_http_info(self, id, **kwargs): # noqa: E501 """[EXPERIMENTAL] GetVendorLog: Get the log for a specific vendor request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_vendor_log_with_http_info(id, async_req=True) >>> result = thread.get() :param id: The identifier of the request to obtain the log for. (required) :type id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(VendorLog, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_vendor_log" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501 local_var_params['id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `id` when calling `get_vendor_log`") # noqa: E501 if self.api_client.client_side_validation and ('id' in local_var_params and # noqa: E501 len(local_var_params['id']) > 64): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_log`, length must be less than or equal to `64`") # noqa: E501 if self.api_client.client_side_validation and ('id' in local_var_params and # noqa: E501 len(local_var_params['id']) < 1): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_log`, length must be greater than or equal to `1`") # noqa: E501 if self.api_client.client_side_validation and 'id' in local_var_params and not re.search(r'^[a-zA-Z0-9\-_:\+]+$', local_var_params['id']): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_log`, must conform to the pattern `/^[a-zA-Z0-9\-_:\+]+$/`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in local_var_params: path_params['id'] = local_var_params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['text/plain', 'application/json', 'text/json']) # noqa: E501 header_params['Accept-Encoding'] = "gzip, deflate, br" # Authentication setting auth_settings = ['oauth2'] # noqa: E501 response_types_map = { 200: "VendorLog", 400: "LusidValidationProblemDetails", } return self.api_client.call_api( '/api/vendor/{id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def get_vendor_request(self, id, **kwargs): # noqa: E501 """[EXPERIMENTAL] GetVendorRequest: Get the request body for a vendor request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_vendor_request(id, async_req=True) >>> result = thread.get() :param id: The identifier of the request to obtain the content for. (required) :type id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: VendorRequest """ kwargs['_return_http_data_only'] = True return self.get_vendor_request_with_http_info(id, **kwargs) # noqa: E501 def get_vendor_request_with_http_info(self, id, **kwargs): # noqa: E501 """[EXPERIMENTAL] GetVendorRequest: Get the request body for a vendor request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_vendor_request_with_http_info(id, async_req=True) >>> result = thread.get() :param id: The identifier of the request to obtain the content for. (required) :type id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(VendorRequest, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_vendor_request" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501 local_var_params['id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `id` when calling `get_vendor_request`") # noqa: E501 if self.api_client.client_side_validation and ('id' in local_var_params and # noqa: E501 len(local_var_params['id']) > 64): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_request`, length must be less than or equal to `64`") # noqa: E501 if self.api_client.client_side_validation and ('id' in local_var_params and # noqa: E501 len(local_var_params['id']) < 1): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_request`, length must be greater than or equal to `1`") # noqa: E501 if self.api_client.client_side_validation and 'id' in local_var_params and not re.search(r'^[a-zA-Z0-9\-_:\+]+$', local_var_params['id']): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_request`, must conform to the pattern `/^[a-zA-Z0-9\-_:\+]+$/`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in local_var_params: path_params['id'] = local_var_params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['text/plain', 'application/json', 'text/json']) # noqa: E501 header_params['Accept-Encoding'] = "gzip, deflate, br" # Authentication setting auth_settings = ['oauth2'] # noqa: E501 response_types_map = { 200: "VendorRequest", 400: "LusidValidationProblemDetails", } return self.api_client.call_api( '/api/vendor/{id}/request', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def get_vendor_response(self, id, **kwargs): # noqa: E501 """[EXPERIMENTAL] GetVendorResponse: Get the response from a vendor request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_vendor_response(id, async_req=True) >>> result = thread.get() :param id: The identifier of the request to obtain the response for. (required) :type id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: VendorResponse """ kwargs['_return_http_data_only'] = True return self.get_vendor_response_with_http_info(id, **kwargs) # noqa: E501 def get_vendor_response_with_http_info(self, id, **kwargs): # noqa: E501 """[EXPERIMENTAL] GetVendorResponse: Get the response from a vendor request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_vendor_response_with_http_info(id, async_req=True) >>> result = thread.get() :param id: The identifier of the request to obtain the response for. (required) :type id: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(VendorResponse, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_vendor_response" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'id' is set if self.api_client.client_side_validation and ('id' not in local_var_params or # noqa: E501 local_var_params['id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `id` when calling `get_vendor_response`") # noqa: E501 if self.api_client.client_side_validation and ('id' in local_var_params and # noqa: E501 len(local_var_params['id']) > 64): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_response`, length must be less than or equal to `64`") # noqa: E501 if self.api_client.client_side_validation and ('id' in local_var_params and # noqa: E501 len(local_var_params['id']) < 1): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_response`, length must be greater than or equal to `1`") # noqa: E501 if self.api_client.client_side_validation and 'id' in local_var_params and not re.search(r'^[a-zA-Z0-9\-_:\+]+$', local_var_params['id']): # noqa: E501 raise ApiValueError("Invalid value for parameter `id` when calling `get_vendor_response`, must conform to the pattern `/^[a-zA-Z0-9\-_:\+]+$/`") # noqa: E501 collection_formats = {} path_params = {} if 'id' in local_var_params: path_params['id'] = local_var_params['id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['text/plain', 'application/json', 'text/json']) # noqa: E501 header_params['Accept-Encoding'] = "gzip, deflate, br" # Authentication setting auth_settings = ['oauth2'] # noqa: E501 response_types_map = { 200: "VendorResponse", 400: "LusidValidationProblemDetails", } return self.api_client.call_api( '/api/vendor/{id}/response', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth')) def list_vendor_logs(self, **kwargs): # noqa: E501 """[EXPERIMENTAL] ListVendorLogs: List the logs for vendor requests. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_vendor_logs(async_req=True) >>> result = thread.get() :param filter: Expression to filter the result set. Read more about <see href=\"https://support.lusid.com/filtering-results-from-lusid\"> filtering results from LUSID</see>. :type filter: str :param sort_by: Order the results by these fields. Use the '-' sign to denote descending order e.g. -MyFieldName. Multiple fields can be denoted by a comma e.g. -MyFieldName,AnotherFieldName,-AFurtherFieldName :type sort_by: str :param limit: When paginating, only return this number of records. The minimum value is 0 and the maximum is 10000. :type limit: int :param page: Encoded page string returned from a previous search result that will retrieve the next page of data. When this field is supplied, filter and sortby fields should not be supplied. :type page: str :param histogram_interval: Optional interval to use in a histogram of the returned values. If not provided, no histogram will be generated. :type histogram_interval: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: ResourceListWithHistogramOfVendorLog """ kwargs['_return_http_data_only'] = True return self.list_vendor_logs_with_http_info(**kwargs) # noqa: E501 def list_vendor_logs_with_http_info(self, **kwargs): # noqa: E501 """[EXPERIMENTAL] ListVendorLogs: List the logs for vendor requests. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_vendor_logs_with_http_info(async_req=True) >>> result = thread.get() :param filter: Expression to filter the result set. Read more about <see href=\"https://support.lusid.com/filtering-results-from-lusid\"> filtering results from LUSID</see>. :type filter: str :param sort_by: Order the results by these fields. Use the '-' sign to denote descending order e.g. -MyFieldName. Multiple fields can be denoted by a comma e.g. -MyFieldName,AnotherFieldName,-AFurtherFieldName :type sort_by: str :param limit: When paginating, only return this number of records. The minimum value is 0 and the maximum is 10000. :type limit: int :param page: Encoded page string returned from a previous search result that will retrieve the next page of data. When this field is supplied, filter and sortby fields should not be supplied. :type page: str :param histogram_interval: Optional interval to use in a histogram of the returned values. If not provided, no histogram will be generated. :type histogram_interval: str :param async_req: Whether to execute the request asynchronously. :type async_req: bool, optional :param _return_http_data_only: response data without head status code and headers :type _return_http_data_only: bool, optional :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :type _preload_content: bool, optional :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :param _request_auth: set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request. :type _request_auth: dict, optional :return: Returns the result object. If the method is called asynchronously, returns the request thread. :rtype: tuple(ResourceListWithHistogramOfVendorLog, status_code(int), headers(HTTPHeaderDict)) """ local_var_params = locals() all_params = [ 'filter', 'sort_by', 'limit', 'page', 'histogram_interval' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout', '_request_auth' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method list_vendor_logs" % key ) local_var_params[key] = val del local_var_params['kwargs'] if self.api_client.client_side_validation and ('filter' in local_var_params and # noqa: E501 len(local_var_params['filter']) > 16384): # noqa: E501 raise ApiValueError("Invalid value for parameter `filter` when calling `list_vendor_logs`, length must be less than or equal to `16384`") # noqa: E501 if self.api_client.client_side_validation and ('filter' in local_var_params and # noqa: E501 len(local_var_params['filter']) < 0): # noqa: E501 raise ApiValueError("Invalid value for parameter `filter` when calling `list_vendor_logs`, length must be greater than or equal to `0`") # noqa: E501 if self.api_client.client_side_validation and 'filter' in local_var_params and not re.search(r'^[\s\S]*$', local_var_params['filter']): # noqa: E501 raise ApiValueError("Invalid value for parameter `filter` when calling `list_vendor_logs`, must conform to the pattern `/^[\s\S]*$/`") # noqa: E501 if self.api_client.client_side_validation and ('sort_by' in local_var_params and # noqa: E501 len(local_var_params['sort_by']) > 16384): # noqa: E501 raise ApiValueError("Invalid value for parameter `sort_by` when calling `list_vendor_logs`, length must be less than or equal to `16384`") # noqa: E501 if self.api_client.client_side_validation and ('sort_by' in local_var_params and # noqa: E501 len(local_var_params['sort_by']) < 1): # noqa: E501 raise ApiValueError("Invalid value for parameter `sort_by` when calling `list_vendor_logs`, length must be greater than or equal to `1`") # noqa: E501 if self.api_client.client_side_validation and 'sort_by' in local_var_params and not re.search(r'^[\s\S]*$', local_var_params['sort_by']): # noqa: E501 raise ApiValueError("Invalid value for parameter `sort_by` when calling `list_vendor_logs`, must conform to the pattern `/^[\s\S]*$/`") # noqa: E501 if self.api_client.client_side_validation and 'limit' in local_var_params and local_var_params['limit'] > 10000: # noqa: E501 raise ApiValueError("Invalid value for parameter `limit` when calling `list_vendor_logs`, must be a value less than or equal to `10000`") # noqa: E501 if self.api_client.client_side_validation and 'limit' in local_var_params and local_var_params['limit'] < 0: # noqa: E501 raise ApiValueError("Invalid value for parameter `limit` when calling `list_vendor_logs`, must be a value greater than or equal to `0`") # noqa: E501 if self.api_client.client_side_validation and ('page' in local_var_params and # noqa: E501 len(local_var_params['page']) > 500): # noqa: E501 raise ApiValueError("Invalid value for parameter `page` when calling `list_vendor_logs`, length must be less than or equal to `500`") # noqa: E501 if self.api_client.client_side_validation and ('page' in local_var_params and # noqa: E501 len(local_var_params['page']) < 1): # noqa: E501 raise ApiValueError("Invalid value for parameter `page` when calling `list_vendor_logs`, length must be greater than or equal to `1`") # noqa: E501 if self.api_client.client_side_validation and 'page' in local_var_params and not re.search(r'^[a-zA-Z0-9\+\/]*={0,3}$', local_var_params['page']): # noqa: E501 raise ApiValueError("Invalid value for parameter `page` when calling `list_vendor_logs`, must conform to the pattern `/^[a-zA-Z0-9\+\/]*={0,3}$/`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] if 'filter' in local_var_params and local_var_params['filter'] is not None: # noqa: E501 query_params.append(('filter', local_var_params['filter'])) # noqa: E501 if 'sort_by' in local_var_params and local_var_params['sort_by'] is not None: # noqa: E501 query_params.append(('sortBy', local_var_params['sort_by'])) # noqa: E501 if 'limit' in local_var_params and local_var_params['limit'] is not None: # noqa: E501 query_params.append(('limit', local_var_params['limit'])) # noqa: E501 if 'page' in local_var_params and local_var_params['page'] is not None: # noqa: E501 query_params.append(('page', local_var_params['page'])) # noqa: E501 if 'histogram_interval' in local_var_params and local_var_params['histogram_interval'] is not None: # noqa: E501 query_params.append(('histogramInterval', local_var_params['histogram_interval'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['text/plain', 'application/json', 'text/json']) # noqa: E501 header_params['Accept-Encoding'] = "gzip, deflate, br" # Authentication setting auth_settings = ['oauth2'] # noqa: E501 response_types_map = { 200: "ResourceListWithHistogramOfVendorLog", 400: "LusidValidationProblemDetails", } return self.api_client.call_api( '/api/vendor', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_types_map=response_types_map, auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats, _request_auth=local_var_params.get('_request_auth'))

51.725341

217

0.607152

4,035

34,087

4.907807

0.068401

0.044842

0.072817

0.025047

0.946422

0.942837

0.932283

0.928445

0.911276

0.908448

0

0.019843

0.312524

34,087

658

218

51.803951

0.825211

0.416258

0

0.654088

1

0.062893

0.253613

0.041074

0

1

0.028302

false

0

0.015723

0

0.072327

0

null

0

1

0

1

0

null

0

7

b6b401ee8d1c30c6473d93894d5c6868bfa11d79

162

py

Python

torchlib/spl/__init__.py

antsfamily/torchtool

fd0d6e6fe6701206b15f95af145d6178a87233f9

[ "MIT" ]

1

2019-08-15T15:32:36.000Z

torchlib/spl/__init__.py

antsfamily/torchtool

fd0d6e6fe6701206b15f95af145d6178a87233f9

[ "MIT" ]

null

torchlib/spl/__init__.py

antsfamily/torchtool

fd0d6e6fe6701206b15f95af145d6178a87233f9

[ "MIT" ]

null

from __future__ import absolute_import from .voptimizer import Binary, Linear, Logarithmic, Mixture from .spfunction import Binary, Linear, Logarithmic, Mixture

32.4

60

0.833333

19

162

6.842105

0.526316

0.184615

0.276923

0.446154

0.553846

0

0.117284

162

4

61

40.5

0.909091

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

7

1e00a085ce49d26ccc67c3b386587993217d386b

43

py

Python

gcvb/dashboard/__init__.py

felsocim/gcvb

48c5b694f005cdcb1ccec81d44232d6488a31b3b

[ "MIT" ]

5

2019-10-10T11:55:12.000Z

2021-08-18T08:46:22.000Z

gcvb/dashboard/__init__.py

felsocim/gcvb

48c5b694f005cdcb1ccec81d44232d6488a31b3b

[ "MIT" ]

29

2020-02-21T14:52:12.000Z

2020-11-25T17:57:48.000Z

gcvb/dashboard/__init__.py

felsocim/gcvb

48c5b694f005cdcb1ccec81d44232d6488a31b3b

[ "MIT" ]

2

2020-08-06T14:17:05.000Z

2020-10-04T10:15:15.000Z

from .index import run_server as run_server

43

0.860465

8

43

4.375

0.75

0.514286

0

0.116279

43

1

43

0.921053

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

1e932f43ffe260a2835abb37e5593f0f0c886c6b

241

py

Python

src/safer_prompt_toolkit/__init__.py

LiorAvrahami/safer-prompt-toolkit

976136d8a63f42c9cec48d2e027877acac49f1cf

[ "MIT" ]

2

2021-09-12T09:42:50.000Z

2021-09-23T07:20:48.000Z

src/safer_prompt_toolkit/__init__.py

LiorAvrahami/safer-prompt-toolkit

976136d8a63f42c9cec48d2e027877acac49f1cf

[ "MIT" ]

null

src/safer_prompt_toolkit/__init__.py

LiorAvrahami/safer-prompt-toolkit

976136d8a63f42c9cec48d2e027877acac49f1cf

[ "MIT" ]

null

from ._safer_prompt_toolkit import prompt from ._extra_prompt_toolkit_utilities import make_ConstantOptions_Completer_and_Validator,make_ConstantOptions_Completer_and_Validator__return_kwargs,ConstantOptionsCompleter,ConstantOptionsValidator

120.5

199

0.950207

26

241

8.115385

0.615385

0.123223

0.265403

0.293839

0.379147

0

0.029046

241

2

199

120.5

0.901709

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

1

0

8

1eb6c56f47b073916f4fc33c98453ddcec2bbfd7

166

py

Python

Osnove/7_1_1Eksponencijalnost.py

Smajkan/PythonUcenjePonovo

00982fb4caacb35ed11748dcc471f26257c8e5ed

[ "CC0-1.0" ]

null

Osnove/7_1_1Eksponencijalnost.py

Smajkan/PythonUcenjePonovo

00982fb4caacb35ed11748dcc471f26257c8e5ed

[ "CC0-1.0" ]

null

Osnove/7_1_1Eksponencijalnost.py

Smajkan/PythonUcenjePonovo

00982fb4caacb35ed11748dcc471f26257c8e5ed

[ "CC0-1.0" ]

null

print("2 ** 5 = ",2**5) # je u suštini isto kao i:(((2 * 2) * 2) * 2) * 2 print("(((2 * 2) * 2) * 2) * 2 =", (((2 * 2) * 2) * 2) * 2) print("5 ** 2 ** 2 =", 5**2**2)

41.5

73

0.349398

34

166

1.705882

0.264706

0.517241

0.568966

0.62069

0.431034

0.172414

0

0.208333

0.277108

166

3

74

55.333333

0.275

0.283133

0

0.401709

0

1

0

true

0

1

0

1

null

1

0

1

0

1

0

1

0

null

0

1

0

1

0

9

94c4123269940c27f7f0ba7e97bcc5a10a52d286

97

py

Python

avg_numbers.py

EliasPapachristos/Python_Snippets

ea7ed9c2baded690b320bfce5567d306b10b5a62

[ "MIT" ]

1

2020-05-01T10:29:02.000Z

avg_numbers.py

EliasPapachristos/Python_Snippets

ea7ed9c2baded690b320bfce5567d306b10b5a62

[ "MIT" ]

null

avg_numbers.py

EliasPapachristos/Python_Snippets

ea7ed9c2baded690b320bfce5567d306b10b5a62

[ "MIT" ]

null

def average_number(*args): return sum(args, 0.0) / len(args) average_number(6, 9, 10)

16.166667

38

0.628866

16

97

3.6875

0.6875

0.440678

0

0.078947

0.216495

97

5

39

19.4

0.697368

0

1

0.333333

true

0

0.333333

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

bf9f181abd1a94b4adcd72e9e06156a25575cb5f

545

py

Python

train_covid20cases_timm-regnetx_002_flip.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

train_covid20cases_timm-regnetx_002_flip.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

train_covid20cases_timm-regnetx_002_flip.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

import os ls=["python main.py --configs configs/train_covid20cases_unetplusplus_timm-regnetx_002_fold0_flip.yml", "python main.py --configs configs/train_covid20cases_unetplusplus_timm-regnetx_002_fold1_flip.yml", "python main.py --configs configs/train_covid20cases_unetplusplus_timm-regnetx_002_fold2_flip.yml", "python main.py --configs configs/train_covid20cases_unetplusplus_timm-regnetx_002_fold3_flip.yml", "python main.py --configs configs/train_covid20cases_unetplusplus_timm-regnetx_002_fold4_flip.yml", ] for l in ls: os.system(l)

49.545455

103

0.847706

80

545

5.4

0.3

0.115741

0.138889

0.219907

0.863426

0

0.058366

0.056881

545

11

104

49.545455

0.782101

0

0.879121

0.650183

0

1

0

false

0

0.111111

0

0.111111

0

null

0

1

0

1

null

0

9

bfd9b8f108e00efdd9acff49d597c64226ac1c42

63,807

py

Python

parser/testing/intermediate_expression_tests.py

zhangshyue/regex-library

69a26b580bcc94f95dda3536cd790fb59c81a31b

[ "MIT" ]

null

parser/testing/intermediate_expression_tests.py

zhangshyue/regex-library

69a26b580bcc94f95dda3536cd790fb59c81a31b

[ "MIT" ]

null

parser/testing/intermediate_expression_tests.py

zhangshyue/regex-library

69a26b580bcc94f95dda3536cd790fb59c81a31b

[ "MIT" ]

null

# Builtin imports import unittest import logging # Internal imports import root_pb2 from testing.test_utils import PatternTest import logconf class IntermediateSubexpressionTests(unittest.TestCase, PatternTest): patterns = { r"\b[A-Z]{1}\b": PatternTest.gen_root(root_pb2.Expression( raw=r'\b[A-Z]{1}\b', tokens=[ # Add tokens here root_pb2.Token( token=r"\b", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.WordBoundry ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="A-Z", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.RangeSet ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="{1}", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.SpecifiedQuantifier ), root_pb2.Token( token=r"\b", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.WordBoundry ), ], expressions=[ root_pb2.Expression( raw=r"\b", tokens=[ root_pb2.Token( token=r"\b", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.WordBoundry ), ] ), root_pb2.Expression( raw="[A-Z]{1}", tokens=[ root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="A-Z", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.RangeSet ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="{1}", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.SpecifiedQuantifier ), ] ), root_pb2.Expression( raw=r"\b", tokens=[ root_pb2.Token( token=r"\b", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.WordBoundry ), ] ), ] )), r"/^(?:0x[a-f\d]+|0b[01]+|(?:\d+\.?\d*|\.\d+)(?:e[-+]?\d+)?)(u|ll?|l|f)?/i": PatternTest.gen_root(root_pb2.Expression( raw=r"/^(?:0x[a-f\d]+|0b[01]+|(?:\d+\.?\d*|\.\d+)(?:e[-+]?\d+)?)(u|ll?|l|f)?/i", tokens=[ # Add tokens here root_pb2.Token( token=r"/", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token="^", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.SetNegation ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token=r"?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="x", type=root_pb2.TokenType.Character, character="x" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="a-f", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.RangeSet ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="b", type=root_pb2.TokenType.Character, character="b" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="1", type=root_pb2.TokenType.Character, character="1" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="\.", type=root_pb2.TokenType.Escape, escape=root_pb2.EscapeType.Reserved ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="*", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Star ), root_pb2.Token( token=r"\.", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.CloseCapture ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token="e", type=root_pb2.TokenType.Character, character="e" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="-", type=root_pb2.TokenType.Character, character="-" ), root_pb2.Token( token="+", type=root_pb2.TokenType.Character, character="+" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="u", type=root_pb2.TokenType.Character, character="u" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="f", type=root_pb2.TokenType.Character, character="f" ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token="/", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token="i", type=root_pb2.TokenType.Flag, flag=root_pb2.FlagType.Ignore ), ], expressions=[ root_pb2.Expression( raw='/', tokens=[ root_pb2.Token( token=r"/", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), ] ), root_pb2.Expression( raw=r'/^(?:0x[a-f\d]+|0b[01]+|(?:\d+\.?\d*|\.\d+)(?:e[-+]?\d+)?)(u|ll?|l|f)?/i', tokens=[ root_pb2.Token( token=r"/", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token="^", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.SetNegation ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token=r"?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="x", type=root_pb2.TokenType.Character, character="x" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="a-f", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.RangeSet ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="b", type=root_pb2.TokenType.Character, character="b" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="1", type=root_pb2.TokenType.Character, character="1" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="\.", type=root_pb2.TokenType.Escape, escape=root_pb2.EscapeType.Reserved ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="*", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Star ), root_pb2.Token( token=r"\.", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.CloseCapture ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token="e", type=root_pb2.TokenType.Character, character="e" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="-", type=root_pb2.TokenType.Character, character="-" ), root_pb2.Token( token="+", type=root_pb2.TokenType.Character, character="+" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="u", type=root_pb2.TokenType.Character, character="u" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="f", type=root_pb2.TokenType.Character, character="f" ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token="/", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token="i", type=root_pb2.TokenType.Flag, flag=root_pb2.FlagType.Ignore ), ] ), root_pb2.Expression( raw='[a-f\d]+', tokens=[ root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="a-f", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.RangeSet ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), ] ), root_pb2.Expression( raw='0x', tokens=[ root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="x", type=root_pb2.TokenType.Character, character="x" ), ] ), root_pb2.Expression( raw='0b', tokens=[ root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="b", type=root_pb2.TokenType.Character, character="b" ), ] ), root_pb2.Expression( raw='"', tokens=[ root_pb2.Token( token='"', type=root_pb2.TokenType.Character, character='"' ), ] ), root_pb2.Expression( raw='[a-f\d]+|0b', tokens=[ root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="a-f", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.RangeSet ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="b", type=root_pb2.TokenType.Character, character="b" ), ] ), root_pb2.Expression( raw='[01]+|(?:\d+\.?\d*|\.\d+)', tokens=[ root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="0", type=root_pb2.TokenType.Character, character="0" ), root_pb2.Token( token="1", type=root_pb2.TokenType.Character, character="1" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="\.", type=root_pb2.TokenType.Escape, escape=root_pb2.EscapeType.Reserved ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="*", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Star ), root_pb2.Token( token=r"\.", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.CloseCapture ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token="e", type=root_pb2.TokenType.Character, character="e" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="-", type=root_pb2.TokenType.Character, character="-" ), root_pb2.Token( token="+", type=root_pb2.TokenType.Character, character="+" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=r")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.CloseCapture ), ] ), root_pb2.Expression( raw='(?:e[-+]?\d+)?)(u | ll? | l | f)?', tokens=[ root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token="e", type=root_pb2.TokenType.Character, character="e" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="-", type=root_pb2.TokenType.Character, character="-" ), root_pb2.Token( token="+", type=root_pb2.TokenType.Character, character="+" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="u", type=root_pb2.TokenType.Character, character="u" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="f", type=root_pb2.TokenType.Character, character="f" ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), ] ), root_pb2.Expression( raw='(?:e[-+]?\d+)?)', tokens=[ root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token="e", type=root_pb2.TokenType.Character, character="e" ), root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="-", type=root_pb2.TokenType.Character, character="-" ), root_pb2.Token( token="+", type=root_pb2.TokenType.Character, character="+" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.ClosedCapture ), ] ), root_pb2.Expression( raw='(?:\d+\.?\d * | \.\d+)', tokens=[ root_pb2.Token( token=r"(", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.OpenCapture ), root_pb2.Token( token="?:", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.NonCapturing ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token="\.", type=root_pb2.TokenType.Escape, escape=root_pb2.EscapeType.Reserved ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="*", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Star ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token=r"\.", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), root_pb2.Token( token=")", type=root_pb2.TokenType.GroupReference, groupref=root_pb2.GroupReferenceType.CloseCapture ), ] ), root_pb2.Expression( raw='[-+]?', tokens=[ root_pb2.Token( token="[", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.OpenSet ), root_pb2.Token( token="-", type=root_pb2.TokenType.Character, character="-" ), root_pb2.Token( token="+", type=root_pb2.TokenType.Character, character="+" ), root_pb2.Token( token="]", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.CloseSet ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), ] ), root_pb2.Expression( raw='\d+', tokens=[ root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="+", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Plus ), ] ), root_pb2.Expression( raw='\.?', tokens=[ root_pb2.Token( token="\.", type=root_pb2.TokenType.Escape, escape=root_pb2.EscapeType.Reserved ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), ] ), root_pb2.Expression( raw='\d*|\.', tokens=[ root_pb2.Token( token=r"\d", type=root_pb2.TokenType.CharacterClass, characterclass=root_pb2.CharacterClassType.Digit ), root_pb2.Token( token="*", type=root_pb2.TokenType.QuantifierModifider, quantifiermodifier=root_pb2.QuantifierModifierType.Star ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token=r"\.", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), ] ), root_pb2.Expression( raw='l?|l', tokens=[ root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="?", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.Optional ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), ] ), root_pb2.Expression( raw='u|l', tokens=[ root_pb2.Token( token="u", type=root_pb2.TokenType.Character, character="u" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), ] ), root_pb2.Expression( raw='l|f', tokens=[ root_pb2.Token( token="l", type=root_pb2.TokenType.Character, character="l" ), root_pb2.Token( token="|", type=root_pb2.TokenType.QuantifierModifier, quantifiermodifier=root_pb2.QuantifierModifierType.AlternationPipe ), root_pb2.Token( token="f", type=root_pb2.TokenType.Character, character="f" ), ] ), root_pb2.Expression( raw='/', tokens=[ root_pb2.Token( token="/", type=root_pb2.TokenType.Anchor, anchor=root_pb2.AnchorType.ForwardSlash ), ] ) ] )) }

45.189093

126

0.384989

3,768

63,807

6.325372

0.020701

0.213812

0.127885

0.18117

0.991231

0.989133

0.987916

0.986154

0.983595

0.981413

0

0.026584

0.542511

63,807

1,412

127

45.189093

0.789901

0.001003

0

0.956522

0

0.002138

0.012191

0.003781

0

1

0

false

0

0.003564

0

0.004989

0

null

1

0

1

0

1

0

1

0

null

0

10

ec918bdde572143ba05bd4c1748a2907fb78c59b

27,564

py

Python

init.py

alesanz237/usabilityProject

5f48d388ec487203147e546562076a2643afaf44

[ "Apache-2.0" ]

null

init.py

alesanz237/usabilityProject

5f48d388ec487203147e546562076a2643afaf44

[ "Apache-2.0" ]

null

init.py

alesanz237/usabilityProject

5f48d388ec487203147e546562076a2643afaf44

[ "Apache-2.0" ]

null

from flask import Flask, jsonify, render_template, request from db import readDB, writeDB, updateDB import random import time app = Flask(__name__) @app.route('/_validateUser') def getUsers(): email = request.args['email'] password = request.args['password'] users = readDB("data/users.json")["users"] user_type = {"type":-1} for user in users: if user["email"] == email and user["password"] == password: user_type = {"type":user["type"]} return jsonify(user_type) @app.route('/_getStudentDocuments') def get_StudentDocuments(): documents = readDB('data/student_documents.json') return jsonify(documents) @app.route('/_getProfessorDocuments') def get_ProfessorDocuments(): documents = readDB('data/professor_documents.json') return jsonify(documents) @app.route('/_getAssistantDocuments') def get_AssistantDocuments(): documents = readDB('data/assistant_documents.json') return jsonify(documents) @app.route('/_getDirectorDocuments') def get_DirectorDocuments(): documents = readDB('data/director_documents.json') return jsonify(documents) @app.route('/_newAssistantship') def newAssistantship(): # documents = readDB('data/student_documents.json') return render_template("new_assistantship") @app.route('/_getDocument') def getDocument(): print "Entre a Get Document" doc_id = request.args["doc_id"] user_type = request.args["user_type"] print "doc_id",doc_id print "user_type",user_type if int(user_type) == 0: documents = readDB('data/student_documents.json')["documents"] if int(user_type) == 1: documents = readDB('data/professor_documents.json')["documents"] if int(user_type) == 2: documents = readDB('data/assistant_documents.json')["documents"] if int(user_type) == 3: documents = readDB('data/director_documents.json')["documents"] print "documents",documents for document in documents: if int(document["id"]) == int(doc_id): doc = document return jsonify(doc) @app.route('/_insertAssistantship') def insertAssistantship(): user_type = request.args['user_type'] advisor = request.args['advisor'] project = request.args['project'] task = request.args['task'] assistantship_type = request.args['a_type'] student = request.args['student'] print "user_type", user_type print "advisor", advisor print "project", project print "task", task print "assistantship_type", assistantship_type print "student", student # student: student inserted = {'status':-1} # Setting values for document to be inserted doc_id = random.randint(1, 999999999) if assistantship_type == "Research": name = "2016 Research Assistantship Request" else: name = "2016 TA Assistantship Request" # If document is being sent by student if int(user_type) == 0: document = {} document["id"] = doc_id document["name"] = name document["type"] = "Assistantship Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = advisor document["project"] = project document["task"] = task document["student"] = student document["requester"] = "Student: Jessica Cotrina" document["sent_status"] = "" document["last_edited"] = "Student: Jessica Cotrina" document["student_number"] = "502-15-6168" print document writeDB('data/student_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':name} if int(user_type) == 1: document = {} document["id"] = doc_id document["name"] = name document["type"] = "Assistantship Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = "Nestor Rodriguez" document["project"] = project document["task"] = task document["student"] = student document["requester"] = "Professor: Nestor Rodriguez" document["sent_status"] = "" document["last_edited"] = "Professor: Nestor Rodriguez" print document writeDB('data/professor_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':name} if int(user_type) == 2: document = {} document["id"] = doc_id document["name"] = name document["type"] = "Assistantship Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = advisor document["project"] = project document["task"] = task document["student"] = student document["requester"] = "Assistant: Alida Minguela" document["sent_status"] = "" document["last_edited"] = "Assistant: Alida Minguela" print document writeDB('data/assistant_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':name} if int(user_type) == 3: document = {} document["id"] = doc_id document["name"] = name document["type"] = "Assistantship Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = advisor document["project"] = project document["task"] = task document["student"] = student document["requester"] = "Director: Jose Colom" document["sent_status"] = "" docucment["last_edited"] = "Director Jose Colom" print document writeDB('data/director_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':name} return jsonify(inserted) @app.route('/_insertAssistantAssistantship') def insertAssistantAssistantship(): user_type = request.args['user_type'] advisor = request.args['advisor'] project = request.args['project'] task = request.args['task'] assistantship_type = request.args['a_type'] student = request.args['student'] student_number = request.args['student_number'] department = request.args['department'] major = request.args['major'] print "user_type", user_type print "advisor", advisor print "project", project print "task", task print "assistantship_type", assistantship_type print "student", student print "student_number", student_number print "department", department print "major", major # student: student inserted = {'status':-1} # Setting values for document to be inserted doc_id = random.randint(1, 999999999) if assistantship_type == "Research": name = "2016 Research Assistantship Request" else: name = "2016 TA Assistantship Request" # If document is being sent by student document = {} document["id"] = doc_id document["name"] = name document["type"] = "Assistantship Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = department document["major"] = major document["progress"] = 0 document["advisor"] = advisor document["project"] = project document["task"] = task document["student"] = student document["requester"] = "Assistant: Alida Minguela" document["sent_status"] = "" document["last_edited"] = "Assistant: Alida Minguela" document["student number"] = student_number print document writeDB('data/assistant_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':name} return jsonify(inserted) @app.route('/_insertTravelRequest') def insertTravelRequest(): user_type = request.args['user_type'] conference_name = request.args['conference_name'] travel_location = request.args['travel_location'] departure_date = request.args['departure_date'] return_date = request.args['return_date'] advisor = request.args['advisor'] purpose= request.args['purpose'] requester = request.args['requester'] print "user_type",user_type inserted = {'status':-1} # Setting values for document to be inserted doc_id = random.randint(1, 999999999) # If document is being sent by student if int(user_type) == 0: document = {} document["id"] = doc_id document["name"] = conference_name + " Travel Request" document["type"] = "Travel Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = advisor document["travel_location"] = travel_location document["departure_date"] = departure_date document["return_date"] = return_date document["purpose"] = purpose document["requester"] = "Student: Jessica Cotrina" document["sent_status"] = "" document["last_edited"] = "Student: Jessica Cotrina" print document writeDB('data/student_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':conference_name} # If document is being sent by professor if int(user_type) == 1: document = {} document["id"] = doc_id document["name"] = conference_name + " Travel Request" document["type"] = "Travel Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = advisor document["travel_location"] = travel_location document["departure_date"] = departure_date document["return_date"] = return_date document["purpose"] = purpose document["requester"] = "Professor: Nestor Rodriguez" document["sent_status"] = "" document["last_edited"] = "Professor: Nestor Rodriguez" print document writeDB('data/professor_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':conference_name} if int(user_type) == 2: document = {} document["id"] = doc_id document["name"] = conference_name + " Travel Request" document["type"] = "Travel Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = "Assistant: Alida Minguela" document["travel_location"] = travel_location document["departure_date"] = departure_date document["return_date"] = return_date document["purpose"] = purpose document["requester"] = advisor document["sent_status"] = "" document["last_edited"] = "Assistant: Alida Minguela" print document writeDB('data/assistant_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':conference_name} if int(user_type) == 3: document = {} document["id"] = doc_id document["name"] = conference_name + " Travel Request" document["type"] = "Travel Request" document["date"] = (time.strftime("%d/%m/%Y %H:%M:%S")) document["status"] = "Created" document["faculty"] = "Electrical Engineering" document["major"] = "computer Engineering" document["progress"] = 0 document["advisor"] = advisor document["travel_location"] = travel_location document["departure_date"] = departure_date document["return_date"] = return_date document["purpose"] = purpose document["requester"] = "Director: Jose Colom" document["sent_status"] = "" document["last_edited"] = "Director: Jose Colom" print document writeDB('data/director_documents.json',document) writeDB('data/document_history.json',document) inserted = {'status':0,'id':doc_id,'name':conference_name} return jsonify(inserted) @app.route('/_saveAssistantship') def saveAssistantship(): user_type = request.args['user_type'] doc_id = request.args['doc_id'] project = request.args['project'] advisor = request.args['advisor'] student = request.args['student'] task = request.args['task'] saved = {'status':-1} if int(user_type) == 0: documents = readDB('data/student_documents.json')["documents"] for document in documents: if int(document["id"]) == int(doc_id): doc = document doc["project"] = project doc["advisor"] = advisor doc["student"] = student doc["task"] = task doc["last_edited"] = "Student: Jessica Cotrina" print "doc", doc updateDB('data/student_documents.json',doc) writeDB('data/document_history.json',doc) saved = {'status':0,'doc_id':doc_id} if int(user_type) == 1: documents = readDB('data/professor_documents.json')["documents"] for document in documents: if int(document["id"]) == int(doc_id): doc = document doc["project"] = project doc["advisor"] = advisor doc["student"] = student doc["task"] = task doc["last_edited"] = "Professor: Nestor Rodriguez" updateDB('data/profssor_documents.json',doc) writeDB('data/document_history.json',doc) saved = {'status':0,'doc_id':doc_id} if int(user_type) == 2: documents = readDB('data/assistant_documents.json')["documents"] for document in documents: if int(document["id"]) == int(doc_id): doc = document doc["project"] = project doc["advisor"] = advisor doc["student"] = student doc["task"] = task doc["last_edited"] = "Assistant: Alida Minguela" updateDB('data/assistant_documents.json',doc) writeDB('data/document_history.json',doc) saved = {'status':0,'doc_id':doc_id} if int(user_type) == 3: documents = readDB('data/director_documents.json')["documents"] for document in documents: if int(document["id"]) == int(doc_id): doc = document doc["project"] = project doc["advisor"] = advisor doc["student"] = student doc["task"] = task doc["last_edited"] = "Director: Jessica Cotrina" updateDB('data/director_documents.json',doc) writeDB('data/document_history.json',doc) saved = {'status':0,'doc_id':doc_id} return jsonify(saved) @app.route('/_getStudentAssistantships') def get_StudentAssistantships(): print "Entre" documents = readDB('data/student_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Assistantship Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route('/_getProfessorAssistantships') def get_ProfessorAssistantships(): print "Entre" documents = readDB('data/professor_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Assistantship Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route('/_getStudentTravelRequests') def get_StudentTravelRequests(): print "Entre" documents = readDB('data/student_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Travel Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route('/_getProfessorTravelRequests') def get_ProfessorTravelRequests(): print "Entre" documents = readDB('data/professor_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Travel Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route('/_getAssistantAssistantships') def get_AssistantAssistantships(): print "Entre" documents = readDB('data/assistant_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Assistantship Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route('/_getDirectorAssistantships') def get_DirectorAssistantships(): print "Entre" documents = readDB('data/director_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Assistantship Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route('/_getAssistantTravelRequests') def get_AssistantTravelRequests(): print "Entre" documents = readDB('data/assistant_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Travel Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route('/_getDirectorTravelRequests') def get_DirectorTravelRequests(): print "Entre" documents = readDB('data/director_documents.json')["documents"] new_documents = {"documents":[]} # print documents for document in documents: print document if document["type"] == "Travel Request": new_documents["documents"].append(document) # print "\n",new_documents return jsonify(new_documents) @app.route("/") def init(): return render_template("login.html") @app.route("/student") def getStudents(): return render_template("student.html") @app.route("/professor") def getProfessors(): return render_template("professor.html") @app.route("/assistant") def getAssistant(): return render_template("assistant.html") @app.route("/director") def getDirector(): return render_template("director.html") @app.route('/_sendDocument') def sendAndSaveDocument(): print "Entre" doc_id = request.args['doc_id'] user_type = request.args['user_type'] sent_to = request.args['sent_to'] message = request.args['message'] action = request.args['action'] if request.args['action'] else "Sent" if action == "Authorize": action_title = "Waiting for authorization" if action == "Sign": action_title = "Waiting for signature" if action == "Verify": action_title = "Waiting for verification" if action == "Endose": action_title = "Waiting for endorsement" if action == "Sent": action_title = "Sent" # status = request.args['status'] ? request.args['status'] else "Sent" sent = {'status':-1} print doc_id, user_type, sent_to, sent, action # If document is being sent by student if int(user_type) == 0: print "Soy estudiante" documents = readDB('data/student_documents.json')["documents"] print "documents",documents # Getting documment for doc in documents: # print "Entre al doc" print doc["id"], doc_id if int(doc["id"]) == int(doc_id): document = doc # elif doc["name"] == doc_name + " Travel Request": # document = doc document["status"] = action_title document["sent_status"] = "sent" document["last_edited"] = "Student: Jessica Cotrina" document["message"] = message document["action"] = action document["sent_to"] = sent_to # document[""] updateDB('data/student_documents.json',document) # If document is being sent by professor if int(user_type) == 1: print "Soy profesor" documents = readDB('data/professor_documents.json')["documents"] # Getting documment for doc in documents: # print "Entre al doc" print doc["id"], doc_id if int(doc["id"]) == int(doc_id): # print "True" document = doc # elif doc["name"] == doc_name + " Travel Request": # document = doc document["status"] = action document["sent_status"] = "sent" document["last_edited"] = "Professor: Nestor Rodriguez" document["message"] = message document["action"] = action document["sent_to"] = sent_to updateDB('data/professor_documents.json',document) # If document is being sent by assistant if int(user_type) == 2: print "Soy Asistente" documents = readDB('data/assistant_documents.json')["documents"] # Getting documment for doc in documents: # print "Entre al doc" print doc["id"], doc_id if int(doc["id"]) == int(doc_id): # print "True" document = doc # elif doc["name"] == doc_name + " Travel Request": # document = doc document["status"] = action document["sent_status"] = "sent" document["last_edited"] = "Assistant: Alida Minguela" document["message"] = message document["action"] = action document["sent_to"] = sent_to updateDB('data/assistant_documents.json',document) # If document is being sent by director if int(user_type) == 3: print "Soy director" documents = readDB('data/director_documents.json')["documents"] # Getting documment for doc in documents: # print "Entre al doc" print doc["id"], doc_id if int(doc["id"]) == int(doc_id): # print "True" document = doc # elif doc["name"] == doc_name + " Travel Request": # document = doc document["status"] = action document["sent_status"] = "sent" document["last_edited"] = "Director: Jose Colom" document["message"] = message document["action"] = action document["sent_to"] = sent_to updateDB('data/director_documents.json',document) # If document being sent to professor if sent_to == "nestor.rodriguez@upr.edu": document["sent_status"] = "received" documents = readDB('data/professor_documents.json')["documents"] print "Professor Documents",documents document_exists = False for d in documents: if int(d["id"]) == int(doc_id): document_exists = True print "Document Exists? ", document_exists if document_exists == True: updateDB('data/professor_documents.json',document) else: writeDB('data/professor_documents.json',document) writeDB('data/document_history.json',document) sent = {'status':0} # If document being set to assistant if sent_to == "alida.minguela@upr.edu": document["sent_status"] = "received" documents = readDB('data/assistant_documents.json')["documents"] document_exists = False for d in documents: if int(d["id"]) == int(doc_id): document_exists = True print "Document Exists? ", document_exists if document_exists == True: updateDB('data/assistant_documents.json',document) else: writeDB('data/assistant_documents.json',document) writeDB('data/document_history.json',document) sent = {'status':0} # If document being sent to director if sent_to == "jose.colom@upr.edu": document["sent_status"] = "received" documents = readDB('data/director_documents.json')["documents"] document_exists = False for d in documents: if int(d["id"]) == int(doc_id): document_exists = True print "Document Exists? ", document_exists if document_exists == True: updateDB('data/director_documents.json',document) else: writeDB('data/director_documents.json',document) writeDB('data/document_history.json',document) sent = {'status':0} # If document being sent to student if sent_to == "jessica.cotrina@upr.edu": document["sent_status"] = "received" documents = readDB('data/student_documents.json')["documents"] document_exists = False for d in documents: if int(d["id"]) == int(doc_id): document_exists = True print "Document Exists? ", document_exists if document_exists == True: updateDB('data/student_documents.json',document) else: writeDB('data/student_documents.json',document) writeDB('data/document_history.json',document) sent = {'status':0} return jsonify(sent) @app.route("/doc_info",methods=['GET']) def getDocumentInfo(): doc_id = request.args['id'] documents = readDB('data/document_history.json')['documents'] for document in documents: if int(document["id"]) == int(doc_id): doc = document return render_template("doc_info.html",document_id=doc["id"]) @app.route("/_getDocumentHistory",methods=['GET']) def getInfo(): document_id = request.args['document_id'] documents = readDB('data/document_history.json')['documents'] document_history = {"history":[]} for document in documents: if int(document["id"]) == int(document_id): document_history["history"].append(document) return jsonify(document_history) if __name__ == "__main__": app.run()

36.557029

74

0.622878

2,930

27,564

5.723208

0.062799

0.019679

0.035124

0.015505

0.810245

0.794204

0.765043

0.733556

0.724313

0.703262

0

0.005111

0.240422

27,564

754

75

36.557029

0.795816

0.056088

0

0.762058

0

0.285291

0.093941

0

null

0.003215

0.006431

null

0.099678

0

null

0

1

0

1

0

null

0

1

0

8

ec97de57611627a4aabd8f8d73cc3debe32f3552

53,125

py

Python

src/ralph_assets/migrations/0015_auto__add_supporttype__add_assetlasthostname__add_unique_assetlasthost.py

xliiv/ralph_assets

73e5e46db380c9a8dafb9ca1bd5abe47d5733385

[ "Apache-2.0" ]

null

src/ralph_assets/migrations/0015_auto__add_supporttype__add_assetlasthostname__add_unique_assetlasthost.py

xliiv/ralph_assets

73e5e46db380c9a8dafb9ca1bd5abe47d5733385

[ "Apache-2.0" ]

null

src/ralph_assets/migrations/0015_auto__add_supporttype__add_assetlasthostname__add_unique_assetlasthost.py

xliiv/ralph_assets

73e5e46db380c9a8dafb9ca1bd5abe47d5733385

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding model 'SupportType' db.create_table('ralph_assets_supporttype', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('name', self.gf('django.db.models.fields.CharField')(unique=True, max_length=75, db_index=True)), )) db.send_create_signal('ralph_assets', ['SupportType']) # Adding model 'AssetLastHostname' db.create_table('ralph_assets_assetlasthostname', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('prefix', self.gf('django.db.models.fields.CharField')(max_length=8, db_index=True)), ('counter', self.gf('django.db.models.fields.PositiveSmallIntegerField')(default=1)), ('postfix', self.gf('django.db.models.fields.CharField')(max_length=8, db_index=True)), )) db.send_create_signal('ralph_assets', ['AssetLastHostname']) # Adding unique constraint on 'AssetLastHostname', fields ['prefix', 'postfix'] db.create_unique('ralph_assets_assetlasthostname', ['prefix', 'postfix']) # Adding model 'BudgetInfo' db.create_table('ralph_assets_budgetinfo', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('name', self.gf('django.db.models.fields.CharField')(unique=True, max_length=75, db_index=True)), ('created', self.gf('django.db.models.fields.DateTimeField')(default=datetime.datetime.now)), ('modified', self.gf('django.db.models.fields.DateTimeField')(default=datetime.datetime.now)), ('cache_version', self.gf('django.db.models.fields.PositiveIntegerField')(default=0)), ('created_by', self.gf('django.db.models.fields.related.ForeignKey')(related_name=u'+', on_delete=models.SET_NULL, default=None, to=orm['account.Profile'], blank=True, null=True)), ('modified_by', self.gf('django.db.models.fields.related.ForeignKey')(related_name=u'+', on_delete=models.SET_NULL, default=None, to=orm['account.Profile'], blank=True, null=True)), )) db.send_create_signal('ralph_assets', ['BudgetInfo']) # Adding model 'Support' db.create_table('ralph_assets_support', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('name', self.gf('django.db.models.fields.CharField')(max_length=75)), ('created', self.gf('django.db.models.fields.DateTimeField')(default=datetime.datetime.now)), ('modified', self.gf('django.db.models.fields.DateTimeField')(default=datetime.datetime.now)), ('cache_version', self.gf('django.db.models.fields.PositiveIntegerField')(default=0)), ('created_by', self.gf('django.db.models.fields.related.ForeignKey')(related_name=u'+', on_delete=models.SET_NULL, default=None, to=orm['account.Profile'], blank=True, null=True)), ('modified_by', self.gf('django.db.models.fields.related.ForeignKey')(related_name=u'+', on_delete=models.SET_NULL, default=None, to=orm['account.Profile'], blank=True, null=True)), ('deleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_index=True)), ('contract_id', self.gf('django.db.models.fields.CharField')(max_length=50)), ('description', self.gf('django.db.models.fields.CharField')(max_length=100, blank=True)), ('price', self.gf('django.db.models.fields.DecimalField')(default=0, null=True, max_digits=10, decimal_places=2, blank=True)), ('date_from', self.gf('django.db.models.fields.DateField')(null=True, blank=True)), ('date_to', self.gf('django.db.models.fields.DateField')()), ('escalation_path', self.gf('django.db.models.fields.CharField')(max_length=200, blank=True)), ('contract_terms', self.gf('django.db.models.fields.CharField')(max_length=200, blank=True)), ('additional_notes', self.gf('django.db.models.fields.CharField')(max_length=200, blank=True)), ('sla_type', self.gf('django.db.models.fields.CharField')(max_length=200, blank=True)), ('asset_type', self.gf('django.db.models.fields.PositiveSmallIntegerField')()), ('status', self.gf('django.db.models.fields.PositiveSmallIntegerField')(default=1)), ('producer', self.gf('django.db.models.fields.CharField')(max_length=100, blank=True)), ('supplier', self.gf('django.db.models.fields.CharField')(max_length=100, blank=True)), ('serial_no', self.gf('django.db.models.fields.CharField')(max_length=100, blank=True)), ('invoice_no', self.gf('django.db.models.fields.CharField')(db_index=True, max_length=100, blank=True)), ('invoice_date', self.gf('django.db.models.fields.DateField')(null=True, blank=True)), ('period_in_months', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True)), ('property_of', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['ralph_assets.AssetOwner'], null=True, on_delete=models.PROTECT, blank=True)), ('support_type', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['ralph_assets.SupportType'], on_delete=models.PROTECT)), )) db.send_create_signal('ralph_assets', ['Support']) # Adding M2M table for field attachments on 'Support' db.create_table('ralph_assets_support_attachments', ( ('id', models.AutoField(verbose_name='ID', primary_key=True, auto_created=True)), ('support', models.ForeignKey(orm['ralph_assets.support'], null=False)), ('attachment', models.ForeignKey(orm['ralph_assets.attachment'], null=False)) )) db.create_unique('ralph_assets_support_attachments', ['support_id', 'attachment_id']) # Adding M2M table for field assets on 'Support' db.create_table('ralph_assets_support_assets', ( ('id', models.AutoField(verbose_name='ID', primary_key=True, auto_created=True)), ('support', models.ForeignKey(orm['ralph_assets.support'], null=False)), ('asset', models.ForeignKey(orm['ralph_assets.asset'], null=False)) )) db.create_unique('ralph_assets_support_assets', ['support_id', 'asset_id']) # Adding model 'SupportHistoryChange' db.create_table('ralph_assets_supporthistorychange', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('date', self.gf('django.db.models.fields.DateTimeField')(default=datetime.datetime.now)), ('support', self.gf('django.db.models.fields.related.ForeignKey')(default=None, to=orm['ralph_assets.Support'], null=True, on_delete=models.SET_NULL, blank=True)), ('user', self.gf('django.db.models.fields.related.ForeignKey')(default=None, to=orm['auth.User'], null=True, on_delete=models.SET_NULL, blank=True)), ('field_name', self.gf('django.db.models.fields.CharField')(default=u'', max_length=64)), ('old_value', self.gf('django.db.models.fields.CharField')(default=u'', max_length=255)), ('new_value', self.gf('django.db.models.fields.CharField')(default=u'', max_length=255)), )) db.send_create_signal('ralph_assets', ['SupportHistoryChange']) # Adding field 'Licence.license_details' db.add_column('ralph_assets_licence', 'license_details', self.gf('django.db.models.fields.CharField')(default=u'', max_length=1024, blank=True), keep_default=False) # Adding field 'Licence.budget_info' db.add_column('ralph_assets_licence', 'budget_info', self.gf('django.db.models.fields.related.ForeignKey')(default=None, to=orm['ralph_assets.BudgetInfo'], null=True, on_delete=models.PROTECT, blank=True), keep_default=False) # Adding field 'Asset.budget_info' db.add_column('ralph_assets_asset', 'budget_info', self.gf('django.db.models.fields.related.ForeignKey')(default=None, to=orm['ralph_assets.BudgetInfo'], null=True, on_delete=models.PROTECT, blank=True), keep_default=False) # Adding field 'Asset.hostname' db.add_column('ralph_assets_asset', 'hostname', self.gf('django.db.models.fields.CharField')(default=None, max_length=16, unique=True, null=True, blank=True), keep_default=False) # Adding field 'Asset.required_support' db.add_column('ralph_assets_asset', 'required_support', self.gf('django.db.models.fields.BooleanField')(default=False), keep_default=False) # Adding field 'AssetCategory.code' db.add_column('ralph_assets_assetcategory', 'code', self.gf('django.db.models.fields.CharField')(default=u'', max_length=4, blank=True), keep_default=False) def backwards(self, orm): # Removing unique constraint on 'AssetLastHostname', fields ['prefix', 'postfix'] db.delete_unique('ralph_assets_assetlasthostname', ['prefix', 'postfix']) # Deleting model 'SupportType' db.delete_table('ralph_assets_supporttype') # Deleting model 'AssetLastHostname' db.delete_table('ralph_assets_assetlasthostname') # Deleting model 'BudgetInfo' db.delete_table('ralph_assets_budgetinfo') # Deleting model 'Support' db.delete_table('ralph_assets_support') # Removing M2M table for field attachments on 'Support' db.delete_table('ralph_assets_support_attachments') # Removing M2M table for field assets on 'Support' db.delete_table('ralph_assets_support_assets') # Deleting model 'SupportHistoryChange' db.delete_table('ralph_assets_supporthistorychange') # Deleting field 'Licence.license_details' db.delete_column('ralph_assets_licence', 'license_details') # Deleting field 'Licence.budget_info' db.delete_column('ralph_assets_licence', 'budget_info_id') # Deleting field 'Asset.budget_info' db.delete_column('ralph_assets_asset', 'budget_info_id') # Deleting field 'Asset.hostname' db.delete_column('ralph_assets_asset', 'hostname') # Deleting field 'Asset.required_support' db.delete_column('ralph_assets_asset', 'required_support') # Deleting field 'AssetCategory.code' db.delete_column('ralph_assets_assetcategory', 'code') models = { 'account.profile': { 'Meta': {'object_name': 'Profile'}, 'activation_token': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '40', 'blank': 'True'}), 'birth_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'city': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'company': ('django.db.models.fields.CharField', [], {'max_length': '64', 'blank': 'True'}), 'cost_center': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'blank': 'True'}), 'country': ('django.db.models.fields.PositiveIntegerField', [], {'default': '153'}), 'department': ('django.db.models.fields.CharField', [], {'max_length': '64', 'blank': 'True'}), 'employee_id': ('django.db.models.fields.CharField', [], {'max_length': '64', 'blank': 'True'}), 'gender': ('django.db.models.fields.PositiveIntegerField', [], {'default': '2'}), 'home_page': (u'dj.choices.fields.ChoiceField', [], {'unique': 'False', 'primary_key': 'False', 'db_column': 'None', 'blank': 'False', u'default': '1', 'null': 'False', '_in_south': 'True', 'db_index': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'last_active': ('django.db.models.fields.DateTimeField', [], {'default': 'None', 'null': 'True', 'blank': 'True'}), 'location': ('django.db.models.fields.CharField', [], {'max_length': '128', 'blank': 'True'}), 'manager': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'blank': 'True'}), 'nick': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '30', 'blank': 'True'}), 'profit_center': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'blank': 'True'}), 'time_zone': ('django.db.models.fields.FloatField', [], {'default': '1.0'}), 'user': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['auth.User']", 'unique': 'True'}) }, 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'ralph_assets.action': { 'Meta': {'object_name': 'Action'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.asset': { 'Meta': {'object_name': 'Asset'}, 'attachments': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['ralph_assets.Attachment']", 'null': 'True', 'blank': 'True'}), 'barcode': ('django.db.models.fields.CharField', [], {'default': 'None', 'max_length': '200', 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'budget_info': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.BudgetInfo']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'deleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'delivery_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'deprecation_end_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'deprecation_rate': ('django.db.models.fields.DecimalField', [], {'default': '25', 'max_digits': '5', 'decimal_places': '2', 'blank': 'True'}), 'device_info': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['ralph_assets.DeviceInfo']", 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'force_deprecation': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'hostname': ('django.db.models.fields.CharField', [], {'default': 'None', 'max_length': '16', 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'invoice_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'invoice_no': ('django.db.models.fields.CharField', [], {'db_index': 'True', 'max_length': '128', 'null': 'True', 'blank': 'True'}), 'loan_end_date': ('django.db.models.fields.DateField', [], {'default': 'None', 'null': 'True', 'blank': 'True'}), 'location': ('django.db.models.fields.CharField', [], {'max_length': '128', 'null': 'True', 'blank': 'True'}), 'model': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.AssetModel']", 'on_delete': 'models.PROTECT'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'niw': ('django.db.models.fields.CharField', [], {'default': 'None', 'max_length': '200', 'null': 'True', 'blank': 'True'}), 'note': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'blank': 'True'}), 'office_info': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['ralph_assets.OfficeInfo']", 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'order_no': ('django.db.models.fields.CharField', [], {'max_length': '50', 'null': 'True', 'blank': 'True'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "u'owner'", 'null': 'True', 'to': "orm['auth.User']"}), 'part_info': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['ralph_assets.PartInfo']", 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'price': ('django.db.models.fields.DecimalField', [], {'default': '0', 'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'production_use_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'production_year': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'blank': 'True'}), 'property_of': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.AssetOwner']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'provider': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'provider_order_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'remarks': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'blank': 'True'}), 'request_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'required_support': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'service_name': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.Service']", 'null': 'True', 'blank': 'True'}), 'slots': ('django.db.models.fields.FloatField', [], {'default': '0', 'max_length': '64'}), 'sn': ('django.db.models.fields.CharField', [], {'max_length': '200', 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'source': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True', 'null': 'True', 'blank': 'True'}), 'status': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1', 'null': 'True', 'blank': 'True'}), 'support_period': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '0', 'null': 'True', 'blank': 'True'}), 'support_price': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'support_type': ('django.db.models.fields.CharField', [], {'max_length': '150', 'blank': 'True'}), 'support_void_reporting': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}), 'task_url': ('django.db.models.fields.URLField', [], {'max_length': '2048', 'null': 'True', 'blank': 'True'}), 'type': ('django.db.models.fields.PositiveSmallIntegerField', [], {}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "u'user'", 'null': 'True', 'to': "orm['auth.User']"}), 'warehouse': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.Warehouse']", 'on_delete': 'models.PROTECT'}) }, 'ralph_assets.assetcategory': { 'Meta': {'object_name': 'AssetCategory'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'code': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '4', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'is_blade': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'level': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'lft': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}), 'parent': ('mptt.fields.TreeForeignKey', [], {'blank': 'True', 'related_name': "u'children'", 'null': 'True', 'to': "orm['ralph_assets.AssetCategory']"}), 'rght': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100', 'primary_key': 'True'}), 'tree_id': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'type': ('django.db.models.fields.PositiveIntegerField', [], {}) }, 'ralph_assets.assethistorychange': { 'Meta': {'object_name': 'AssetHistoryChange'}, 'asset': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.Asset']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}), 'comment': ('django.db.models.fields.TextField', [], {'null': 'True'}), 'date': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'device_info': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.DeviceInfo']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}), 'field_name': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '64'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'new_value': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '255'}), 'office_info': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.OfficeInfo']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}), 'old_value': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '255'}), 'part_info': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.PartInfo']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['auth.User']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}) }, 'ralph_assets.assetlasthostname': { 'Meta': {'unique_together': "((u'prefix', u'postfix'),)", 'object_name': 'AssetLastHostname'}, 'counter': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'postfix': ('django.db.models.fields.CharField', [], {'max_length': '8', 'db_index': 'True'}), 'prefix': ('django.db.models.fields.CharField', [], {'max_length': '8', 'db_index': 'True'}) }, 'ralph_assets.assetmanufacturer': { 'Meta': {'object_name': 'AssetManufacturer'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.assetmodel': { 'Meta': {'object_name': 'AssetModel'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'category': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.AssetCategory']", 'null': 'True', 'blank': 'True'}), 'cores_count': ('django.db.models.fields.IntegerField', [], {'default': '0', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'height_of_device': ('django.db.models.fields.FloatField', [], {'default': '0', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'manufacturer': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.AssetManufacturer']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '75'}), 'power_consumption': ('django.db.models.fields.IntegerField', [], {'default': '0', 'blank': 'True'}), 'type': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True'}) }, 'ralph_assets.assetowner': { 'Meta': {'object_name': 'AssetOwner'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.attachment': { 'Meta': {'object_name': 'Attachment'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'file': ('django.db.models.fields.files.FileField', [], {'max_length': '100', 'null': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'original_filename': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'uploaded_by': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']", 'null': 'True', 'blank': 'True'}) }, 'ralph_assets.budgetinfo': { 'Meta': {'object_name': 'BudgetInfo'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.coaoemos': { 'Meta': {'object_name': 'CoaOemOs'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.deviceinfo': { 'Meta': {'object_name': 'DeviceInfo'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'deleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'rack': ('django.db.models.fields.CharField', [], {'max_length': '10', 'null': 'True', 'blank': 'True'}), 'ralph_device_id': ('django.db.models.fields.IntegerField', [], {'default': 'None', 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'u_height': ('django.db.models.fields.CharField', [], {'max_length': '10', 'null': 'True', 'blank': 'True'}), 'u_level': ('django.db.models.fields.CharField', [], {'max_length': '10', 'null': 'True', 'blank': 'True'}) }, 'ralph_assets.importproblem': { 'Meta': {'object_name': 'ImportProblem'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'message': ('django.db.models.fields.TextField', [], {}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {}), 'severity': ('django.db.models.fields.PositiveSmallIntegerField', [], {}) }, 'ralph_assets.licence': { 'Meta': {'object_name': 'Licence'}, 'accounting_id': ('django.db.models.fields.CharField', [], {'max_length': '200', 'null': 'True', 'blank': 'True'}), 'asset_type': ('django.db.models.fields.PositiveSmallIntegerField', [], {}), 'assets': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['ralph_assets.Asset']", 'symmetrical': 'False'}), 'attachments': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['ralph_assets.Attachment']", 'null': 'True', 'blank': 'True'}), 'budget_info': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.BudgetInfo']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'invoice_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'invoice_no': ('django.db.models.fields.CharField', [], {'db_index': 'True', 'max_length': '128', 'null': 'True', 'blank': 'True'}), 'level': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'lft': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'licence_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.LicenceType']", 'on_delete': 'models.PROTECT'}), 'license_details': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '1024', 'blank': 'True'}), 'manufacturer': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.AssetManufacturer']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'niw': ('django.db.models.fields.CharField', [], {'default': "u'N/A'", 'unique': 'True', 'max_length': '200'}), 'number_bought': ('django.db.models.fields.IntegerField', [], {}), 'order_no': ('django.db.models.fields.CharField', [], {'max_length': '50', 'null': 'True', 'blank': 'True'}), 'parent': ('mptt.fields.TreeForeignKey', [], {'blank': 'True', 'related_name': "u'children'", 'null': 'True', 'to': "orm['ralph_assets.Licence']"}), 'price': ('django.db.models.fields.DecimalField', [], {'default': '0', 'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'property_of': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.AssetOwner']", 'null': 'True', 'on_delete': 'models.PROTECT'}), 'provider': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'remarks': ('django.db.models.fields.CharField', [], {'default': 'None', 'max_length': '1024', 'null': 'True', 'blank': 'True'}), 'rght': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'service_name': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.Service']", 'null': 'True', 'blank': 'True'}), 'sn': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'software_category': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.SoftwareCategory']", 'on_delete': 'models.PROTECT'}), 'tree_id': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'users': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.User']", 'symmetrical': 'False'}), 'valid_thru': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}) }, 'ralph_assets.licencehistorychange': { 'Meta': {'object_name': 'LicenceHistoryChange'}, 'date': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'field_name': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '64'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'licence': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.Licence']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}), 'new_value': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '255'}), 'old_value': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '255'}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['auth.User']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}) }, 'ralph_assets.licencetype': { 'Meta': {'object_name': 'LicenceType'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.officeinfo': { 'Meta': {'object_name': 'OfficeInfo'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'coa_number': ('django.db.models.fields.CharField', [], {'max_length': '256', 'null': 'True', 'blank': 'True'}), 'coa_oem_os': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.CoaOemOs']", 'null': 'True', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'deleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'imei': ('django.db.models.fields.CharField', [], {'max_length': '18', 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'license_key': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'purpose': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': 'None', 'null': 'True', 'blank': 'True'}) }, 'ralph_assets.partinfo': { 'Meta': {'object_name': 'PartInfo'}, 'barcode_salvaged': ('django.db.models.fields.CharField', [], {'max_length': '200', 'null': 'True', 'blank': 'True'}), 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'deleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'device': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "u'device'", 'null': 'True', 'to': "orm['ralph_assets.Asset']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'source_device': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "u'source_device'", 'null': 'True', 'to': "orm['ralph_assets.Asset']"}) }, 'ralph_assets.reportodtsource': { 'Meta': {'object_name': 'ReportOdtSource'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100'}), 'template': ('django.db.models.fields.files.FileField', [], {'max_length': '100'}) }, 'ralph_assets.service': { 'Meta': {'object_name': 'Service'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'cost_center': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}), 'profit_center': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'blank': 'True'}) }, 'ralph_assets.softwarecategory': { 'Meta': {'object_name': 'SoftwareCategory'}, 'asset_type': ('django.db.models.fields.PositiveSmallIntegerField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.support': { 'Meta': {'object_name': 'Support'}, 'additional_notes': ('django.db.models.fields.CharField', [], {'max_length': '200', 'blank': 'True'}), 'asset_type': ('django.db.models.fields.PositiveSmallIntegerField', [], {}), 'assets': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "u'supports'", 'symmetrical': 'False', 'to': "orm['ralph_assets.Asset']"}), 'attachments': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['ralph_assets.Attachment']", 'null': 'True', 'blank': 'True'}), 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'contract_id': ('django.db.models.fields.CharField', [], {'max_length': '50'}), 'contract_terms': ('django.db.models.fields.CharField', [], {'max_length': '200', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'date_from': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'date_to': ('django.db.models.fields.DateField', [], {}), 'deleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'description': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'escalation_path': ('django.db.models.fields.CharField', [], {'max_length': '200', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'invoice_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'invoice_no': ('django.db.models.fields.CharField', [], {'db_index': 'True', 'max_length': '100', 'blank': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '75'}), 'period_in_months': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'price': ('django.db.models.fields.DecimalField', [], {'default': '0', 'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'producer': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'property_of': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.AssetOwner']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'serial_no': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'sla_type': ('django.db.models.fields.CharField', [], {'max_length': '200', 'blank': 'True'}), 'status': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'supplier': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'support_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.SupportType']", 'on_delete': 'models.PROTECT'}) }, 'ralph_assets.supporthistorychange': { 'Meta': {'object_name': 'SupportHistoryChange'}, 'date': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'field_name': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '64'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'new_value': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '255'}), 'old_value': ('django.db.models.fields.CharField', [], {'default': "u''", 'max_length': '255'}), 'support': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['ralph_assets.Support']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'to': "orm['auth.User']", 'null': 'True', 'on_delete': 'models.SET_NULL', 'blank': 'True'}) }, 'ralph_assets.supporttype': { 'Meta': {'object_name': 'SupportType'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, 'ralph_assets.transition': { 'Meta': {'object_name': 'Transition'}, 'actions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['ralph_assets.Action']", 'symmetrical': 'False'}), 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'from_status': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100'}), 'to_status': ('django.db.models.fields.PositiveSmallIntegerField', [], {}) }, 'ralph_assets.transitionshistory': { 'Meta': {'ordering': "[u'-created']", 'object_name': 'TransitionsHistory'}, 'affected_user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'affected user'", 'to': "orm['auth.User']"}), 'assets': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['ralph_assets.Asset']", 'symmetrical': 'False'}), 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'logged_user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'logged user'", 'to': "orm['auth.User']"}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'report_file': ('django.db.models.fields.files.FileField', [], {'max_length': '100'}), 'report_filename': ('django.db.models.fields.CharField', [], {'max_length': '256', 'null': 'True', 'blank': 'True'}), 'transition': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['ralph_assets.Transition']"}), 'uid': ('django.db.models.fields.CharField', [], {'max_length': '36'}) }, 'ralph_assets.warehouse': { 'Meta': {'object_name': 'Warehouse'}, 'cache_version': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'created_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'modified_by': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "u'+'", 'on_delete': 'models.SET_NULL', 'default': 'None', 'to': "orm['account.Profile']", 'blank': 'True', 'null': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) } } complete_apps = ['ralph_assets']

89.436027

224

0.589816

5,625

53,125

5.437333

0.0544

0.096518

0.168449

0.240641

0.876116

0.844237

0.801929

0.757038

0.72068

0.663757

0

0.008342

0.17408

53,125

594

225

89.436027

0.688721

0.020913

0

0.391714

0

0.573704

0.336289

0

1

0.003766

false

0.001883

0.011299

0

0.020716

0

null

0

1

0

null

0

7

ecee687df04f7bc7d7fcd6f1189845893b40357b

13,506

py

Python

aggregatres.py

ressourceplanning/StochasticMRP

fe433986d22a4126769b9d3ae25c6ace11b8c1c4

[ "BSL-1.0" ]

3

2020-06-17T06:17:31.000Z

2021-07-19T07:53:40.000Z

aggregatres.py

ressourceplanning/StochasticMRP

fe433986d22a4126769b9d3ae25c6ace11b8c1c4

[ "BSL-1.0" ]

null

aggregatres.py

ressourceplanning/StochasticMRP

fe433986d22a4126769b9d3ae25c6ace11b8c1c4

[ "BSL-1.0" ]

2

2021-07-18T05:01:42.000Z

2021-09-03T02:16:43.000Z

#This script aggregates all the csv file in the folder Test. import openpyxl as opxl import pandas as pd import glob as glob columnname = ["Instance name", "Distribution", "Model", "Method", "Scenario Generation", "NrInSampleScenario", "Seed", "Policy generation", "NrOutSampleScenario", "Cplex solution value", "Solution cost", "Cplex_status", "Build time", "Solve time", "Cplex gap", "Cplex Nr iteration", "Cplex Nr nodes", "Cplex best node nr", "Cplex Nr Variable", "Cplex Nr constraint", "Inventory Cost", "BackOrder cost", "Setup cost", "In sample Average", "In Sample Standard deviation", "Nr level", "Nr product", "Nr time Period", "Demand Tree Seed", "Nr Scenario", "Max lead time", "BranchingStrategy", "Demand Distribuion", "UseNonAnticipativity", "Model", "UseSlowMoving", "ScenarioSeed" ] all_data = pd.DataFrame( columns = columnname ) #Add the content of each csv file at the end of the dataframe for f in glob.glob("./Test/SolveInfo/*.csv"): df = pd.read_csv( f, names= columnname ) df.columns = columnname all_data = all_data.append(df, ignore_index = True) writer = pd.ExcelWriter( "./Test/SolveInfo/TestResultSolveInfo.xlsx", engine='openpyxl' ) all_data.to_excel( writer, "Res" ) writer.save( ) # columnname = ["Instance name", # "Distribution", # "Model", # "Method", # "Scenario Generation", # "NrInSampleScenario", # "Seed", # "Policy generation", # "NrOutSampleScenario", # "Identificator", # "Mean", # "Variance", # "Covariance", # "LB", # "UB", # "Min Average", # "Max Average", # "Error" # ] # # all_data = pd.DataFrame(columns=columnname) # # Add the content of each csv file at the end of the dataframe # for f in glob.glob("./Test/Bounds/*.csv"): # df = pd.read_csv(f, names=columnname) # df.columns = columnname # all_data = all_data.append(df, ignore_index=True) # # # writer = pd.ExcelWriter("./Test/Bounds/TestResultBounds.xlsx", engine='openpyxl') # all_data.to_excel(writer, "Res") # writer.save() columnname = ["Instance name", "Model", "Scenario from YQFix", "Policy generation", "Distribution", "NrInSampleScenario", "Scenario Geeration Method", "Whatever ", "Nr Scenario", "KPI On Time", "KPI Backorder", "KPI Lost sales", "Stock level 1", "Stock level 2", "Stock level 3", "Stock level 4", "Stock level 5", "BackOrder For 1 Period", "BackOrder For 2 Period", "BackOrder For 3 Period", "BackOrder For 4 Period", "BackOrder For 5 Period", "BackOrder For 6 Period", "BackOrder For 7 Period", "BackOrder For 8 Period", "BackOrder For 9 Period", "BackOrder For 10 Period", "Lost Sale" ] all_data = pd.DataFrame(columns=columnname) # Add the content of each csv file at the end of the dataframe for f in glob.glob("./Test/Statistic/*.csv"): df = pd.read_csv(f, names=columnname) df.columns = columnname all_data = all_data.append(df, ignore_index=True) writer = pd.ExcelWriter("./Test/Statistic/TestResultStatistic.xlsx", engine='openpyxl') all_data.to_excel(writer, "Res") writer.save() columnname = ["Instance name", "Model", "Method", "Scenario Generation Method", "NrInSampleScenario", "Seed", "EVPI", "Policy generation", "Policy generation2", "NrOutSampleScenario", "TimeHorizonRH", "GenerateAllPossibleScenarios", "Expected In Sample", "CPLEX Time", "CPLEX Gap", "CPLEX NrVariable", "CPLEX NrConstraints", "totaltime", "SetupCost", "Inventory", "In Sample KPI On Time", "Backorder cost", "Lost sales cost", "variable cost", "Inventory cost stochastic period ", "Setup cost stochastic period ", "Backorder cost stochastic period ", "Nr Setups", "Nr period Coverage ", "Evaluation Duration", "In Sample Stock level 1", "In Sample Stock level 2", "In Sample Stock level 3", "In Sample Stock level 4", "In Sample Stock level 5", "In Sample BackOrder For 1 Period", "In Sample BackOrder For 2 Period", "In Sample BackOrder For 3 Period", "In Sample BackOrder For 4 Period", "In Sample BackOrder For 5 Period", "In Sample BackOrder For 6 Period", "In Sample BackOrder For 7 Period", "In Sample BackOrder For 8 Period", "In Sample BackOrder For 9 Period", "In Sample BackOrder For 10 Period", "In Sample BackOrder For 11 Period", "In Sample BackOrder For 12 Period", "In Sample BackOrder For 13 Period", "In Sample BackOrder For 14 Period", "In Sample BackOrder For 15 Period", "In Sample BackOrder For 16 Period", "In Sample BackOrder For 17 Period", "In Sample BackOrder For 18 Period", "In Sample BackOrder For 19 Period", "In Sample BackOrder For 20 Period", "In Sample BackOrder For 21 Period", "In Sample BackOrder For 22 Period", "In Sample BackOrder For 23 Period", "In Sample BackOrder For 24 Period", "In Sample BackOrder For 25 Period", "In Sample BackOrder For 26 Period", "In Sample BackOrder For 27 Period", "In Sample BackOrder For 28 Period", "In Sample BackOrder For 29 Period", "In Sample BackOrder For 30 Period", "In Sample BackOrder For 31 Period", "In Sample BackOrder For 32 Period", "In Sample BackOrder For 33 Period", "In Sample BackOrder For 34 Period", "In Sample BackOrder For 35 Period", "In Sample BackOrder For 36 Period", "In Sample BackOrder For 37 Period", "In Sample BackOrder For 38 Period", "In Sample BackOrder For 39 Period", "In Sample BackOrder For 40 Period", "In Sample BackOrder For 41 Period", "In Sample BackOrder For 42 Period", "In Sample BackOrder For 43 Period", "In Sample BackOrder For 44 Period", "In Sample BackOrder For 45 Period", "In Sample BackOrder For 46 Period", "In Sample BackOrder For 47 Period", "In Sample BackOrder For 48 Period", "In Sample BackOrder For 49 Period", "In Sample Lost Sale", "Expected Out Sample", "LB", "UB", "Min Average", "Max Average", "Error", "SetupCost", "Inventory", "Out Sample KPI On Time", "backorder cost", "lostsales cost", "variable cost", "Inventory cost stochastic period ", "Setup cost stochastic period ", "Backorder cost stochastic period ", "Nr Setups", "Nr period Coverage ", "Evaluation Duration", "Out Sample Stock level 1", "Out Sample Stock level 2", "Out Sample Stock level 3", "Out Sample Stock level 4", "Out Sample Stock level 5", "In Sample BackOrder For 1 Period", "In Sample BackOrder For 2 Period", "In Sample BackOrder For 3 Period", "In Sample BackOrder For 4 Period", "In Sample BackOrder For 5 Period", "In Sample BackOrder For 6 Period", "In Sample BackOrder For 7 Period", "In Sample BackOrder For 8 Period", "In Sample BackOrder For 9 Period", "In Sample BackOrder For 10 Period", "In Sample BackOrder For 11 Period", "In Sample BackOrder For 12 Period", "In Sample BackOrder For 13 Period", "In Sample BackOrder For 14 Period", "In Sample BackOrder For 15 Period", "In Sample BackOrder For 16 Period", "In Sample BackOrder For 17 Period", "In Sample BackOrder For 18 Period", "In Sample BackOrder For 19 Period", "In Sample BackOrder For 20 Period", "In Sample BackOrder For 21 Period", "In Sample BackOrder For 22 Period", "In Sample BackOrder For 23 Period", "In Sample BackOrder For 24 Period", "In Sample BackOrder For 25 Period", "In Sample BackOrder For 26 Period", "In Sample BackOrder For 27 Period", "In Sample BackOrder For 28 Period", "In Sample BackOrder For 29 Period", "In Sample BackOrder For 30 Period", "In Sample BackOrder For 31 Period", "In Sample BackOrder For 32 Period", "In Sample BackOrder For 33 Period", "In Sample BackOrder For 34 Period", "In Sample BackOrder For 35 Period", "In Sample BackOrder For 36 Period", "In Sample BackOrder For 37 Period", "In Sample BackOrder For 38 Period", "In Sample BackOrder For 39 Period", "In Sample BackOrder For 40 Period", "In Sample BackOrder For 41 Period", "In Sample BackOrder For 42 Period", "In Sample BackOrder For 43 Period", "In Sample BackOrder For 44 Period", "In Sample BackOrder For 45 Period", "In Sample BackOrder For 46 Period", "In Sample BackOrder For 47 Period", "In Sample BackOrder For 48 Period", "In Sample BackOrder For 49 Period", "Out Sample Lost Sale" ] all_data = pd.DataFrame(columns=columnname) # Add the content of each csv file at the end of the dataframe for f in glob.glob("./Test/*.csv"): df = pd.read_csv(f, names=columnname) df.columns = columnname all_data = all_data.append(df, ignore_index=True) #all_data.sort_values(by=["Instance name", # "Distribution", # "Model", # "Scenario Generation Method", # "NrInSampleScenario", # "Seed", # "Policy generation", # "NrOutSampleScenario"]) writer = pd.ExcelWriter("./Test/TestResult.xlsx", engine='openpyxl') all_data.to_excel(writer, "Res") writer.save() columnname = ["Instance name", "Distribution", "Model", "Method", "Scenario Generation", "NrInSampleScenario", "Seed", "Policy generation", "NrOutSampleScenario", "Cplex solution value", "Solution cost", "Cplex_status", "Build time", "Solve time", "Cplex gap", "Cplex Nr iteration", "Cplex Nr nodes", "Cplex best node nr", "Cplex Nr Variable", "Cplex Nr constraint", "Inventory Cost", "BackOrder cost", "Setup cost", "In sample Average", "In Sample Standard deviation", "Nr level", "Nr product", "Nr time Period", "Demand Tree Seed", "Nr Scenario", "Max lead time", "BranchingStrategy", "Demand Distribuion", "UseNonAnticipativity", "Model", "UseSlowMoving", "ScenarioSeed" ] all_data = pd.DataFrame(columns=columnname) # Add the content of each csv file at the end of the dataframe for f in glob.glob("./Test/VSS/*.csv"): df = pd.read_csv(f, names=columnname) df.columns = columnname all_data = all_data.append(df, ignore_index=True) writer = pd.ExcelWriter("./Test/VSS/VSS.xlsx", engine='openpyxl') all_data.to_excel(writer, "Res") writer.save()

37.62117

89

0.511773

1,364

13,506

5.038856

0.134897

0.128037

0.242398

0.285174

0.832679

0.8142

0.806053

0.797614

0

0.025296

0.39997

13,506

359

90

37.62117

0.822804

0.113505

0

0.759197

0

0.500545

0.014754

0

1

0

false

0

0.010033

0

0.010033

0

null

0

1

0

1

0

null

0

9

ecf50379002914b9a7c456cb5283ade0e97cf57d

20,857

py

Python

addons/stock_picking_batch/tests/test_batch_picking.py

SHIVJITH/Odoo_Machine_Test

310497a9872db7844b521e6dab5f7a9f61d365a4

[ "Apache-2.0" ]

null

addons/stock_picking_batch/tests/test_batch_picking.py

SHIVJITH/Odoo_Machine_Test

310497a9872db7844b521e6dab5f7a9f61d365a4

[ "Apache-2.0" ]

null

addons/stock_picking_batch/tests/test_batch_picking.py

SHIVJITH/Odoo_Machine_Test

310497a9872db7844b521e6dab5f7a9f61d365a4

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Part of Odoo. See LICENSE file for full copyright and licensing details. from datetime import datetime, timedelta from odoo.tests import Form from odoo.tests.common import TransactionCase class TestBatchPicking(TransactionCase): def setUp(self): """ Create a picking batch with two pickings from stock to customer """ super(TestBatchPicking, self).setUp() self.stock_location = self.env.ref('stock.stock_location_stock') self.customer_location = self.env.ref('stock.stock_location_customers') self.picking_type_out = self.env['ir.model.data'].xmlid_to_res_id('stock.picking_type_out') self.productA = self.env['product.product'].create({ 'name': 'Product A', 'type': 'product', 'categ_id': self.env.ref('product.product_category_all').id, }) self.productB = self.env['product.product'].create({ 'name': 'Product B', 'type': 'product', 'categ_id': self.env.ref('product.product_category_all').id, }) self.picking_client_1 = self.env['stock.picking'].create({ 'location_id': self.stock_location.id, 'location_dest_id': self.customer_location.id, 'picking_type_id': self.picking_type_out, 'company_id': self.env.company.id, }) self.env['stock.move'].create({ 'name': self.productA.name, 'product_id': self.productA.id, 'product_uom_qty': 10, 'product_uom': self.productA.uom_id.id, 'picking_id': self.picking_client_1.id, 'location_id': self.stock_location.id, 'location_dest_id': self.customer_location.id, }) self.picking_client_2 = self.env['stock.picking'].create({ 'location_id': self.stock_location.id, 'location_dest_id': self.customer_location.id, 'picking_type_id': self.picking_type_out, 'company_id': self.env.company.id, }) self.env['stock.move'].create({ 'name': self.productB.name, 'product_id': self.productB.id, 'product_uom_qty': 10, 'product_uom': self.productA.uom_id.id, 'picking_id': self.picking_client_2.id, 'location_id': self.stock_location.id, 'location_dest_id': self.customer_location.id, }) self.picking_client_3 = self.env['stock.picking'].create({ 'location_id': self.stock_location.id, 'location_dest_id': self.customer_location.id, 'picking_type_id': self.picking_type_out, 'company_id': self.env.company.id, }) self.env['stock.move'].create({ 'name': self.productB.name, 'product_id': self.productB.id, 'product_uom_qty': 10, 'product_uom': self.productA.uom_id.id, 'picking_id': self.picking_client_3.id, 'location_id': self.stock_location.id, 'location_dest_id': self.customer_location.id, }) self.batch = self.env['stock.picking.batch'].create({ 'name': 'Batch 1', 'company_id': self.env.company.id, 'picking_ids': [(4, self.picking_client_1.id), (4, self.picking_client_2.id)] }) def test_batch_scheduled_date(self): """ Test to make sure the correct scheduled date is set for both a batch and its pickings. Setting a batch's scheduled date manually has different behavior from when it is automatically set/updated via compute. """ now = datetime.now().replace(microsecond=0) self.batch.scheduled_date = now # TODO: this test cannot currently handle the onchange scheduled_date logic because of test form # view not handling the M2M widget assigned to picking_ids (O2M). Hopefully if this changes then # commented parts of this test can be used later. # manually set batch scheduled date => picking's scheduled dates auto update to match (onchange logic test) # with Form(self.batch) as batch_form: # batch_form.scheduled_date = now - timedelta(days=1) # batch_form.save() # self.assertEqual(self.batch.scheduled_date, self.picking_client_1.scheduled_date) # self.assertEqual(self.batch.scheduled_date, self.picking_client_2.scheduled_date) picking1_scheduled_date = now - timedelta(days=2) picking2_scheduled_date = now - timedelta(days=3) picking3_scheduled_date = now - timedelta(days=4) # manually update picking scheduled dates => batch's scheduled date auto update to match lowest value self.picking_client_1.scheduled_date = picking1_scheduled_date self.picking_client_2.scheduled_date = picking2_scheduled_date self.assertEqual(self.batch.scheduled_date, self.picking_client_2.scheduled_date) # but individual pickings keep original scheduled dates self.assertEqual(self.picking_client_1.scheduled_date, picking1_scheduled_date) self.assertEqual(self.picking_client_2.scheduled_date, picking2_scheduled_date) # add a new picking with an earlier scheduled date => batch's scheduled date should auto-update self.picking_client_3.scheduled_date = picking3_scheduled_date self.batch.write({'picking_ids': [(4, self.picking_client_3.id)]}) self.assertEqual(self.batch.scheduled_date, self.picking_client_3.scheduled_date) # remove that picking and batch scheduled date should auto-update to next min date self.batch.write({'picking_ids': [(3, self.picking_client_3.id)]}) self.assertEqual(self.batch.scheduled_date, self.picking_client_2.scheduled_date) # directly add new picking with an earlier scheduled date => batch's scheduled date auto updates to match, # but existing pickings do not (onchange logic test) # with Form(self.batch) as batch_form: # batch_form.picking_ids.add(self.picking_client_3) # batch_form.save() # # individual pickings keep original scheduled dates self.assertEqual(self.picking_client_1.scheduled_date, picking1_scheduled_date) self.assertEqual(self.picking_client_2.scheduled_date, picking2_scheduled_date) # self.assertEqual(self.batch.scheduled_date, self.picking_client_3.scheduled_date) # self.batch.write({'picking_ids': [(3, self.picking_client_3.id)]}) # remove all pickings and batch scheduled date should default to none self.batch.write({'picking_ids': [(3, self.picking_client_1.id)]}) self.batch.write({'picking_ids': [(3, self.picking_client_2.id)]}) self.assertEqual(self.batch.scheduled_date, False) def test_simple_batch_with_manual_qty_done(self): """ Test a simple batch picking with all quantity for picking available. The user set all the quantity_done on picking manually and no wizard are used. """ self.env['stock.quant']._update_available_quantity(self.productA, self.stock_location, 10.0) self.env['stock.quant']._update_available_quantity(self.productB, self.stock_location, 10.0) # Confirm batch, pickings should not be automatically assigned. self.batch.action_confirm() self.assertEqual(self.picking_client_1.state, 'confirmed', 'Picking 1 should be confirmed') self.assertEqual(self.picking_client_2.state, 'confirmed', 'Picking 2 should be confirmed') # Ask to assign, so pickings should be assigned now. self.batch.action_assign() self.assertEqual(self.picking_client_1.state, 'assigned', 'Picking 1 should be ready') self.assertEqual(self.picking_client_2.state, 'assigned', 'Picking 2 should be ready') self.picking_client_1.move_lines.quantity_done = 10 self.picking_client_2.move_lines.quantity_done = 10 self.batch.action_done() self.assertEqual(self.picking_client_1.state, 'done', 'Picking 1 should be done') self.assertEqual(self.picking_client_2.state, 'done', 'Picking 2 should be done') quant_A = self.env['stock.quant']._gather(self.productA, self.stock_location) quant_B = self.env['stock.quant']._gather(self.productB, self.stock_location) # ensure that quantity for picking has been moved self.assertFalse(sum(quant_A.mapped('quantity'))) self.assertFalse(sum(quant_B.mapped('quantity'))) def test_simple_batch_with_wizard(self): """ Test a simple batch picking with all quantity for picking available. The user use the wizard in order to complete automatically the quantity_done to the initial demand (or reserved quantity in this test). """ self.env['stock.quant']._update_available_quantity(self.productA, self.stock_location, 10.0) self.env['stock.quant']._update_available_quantity(self.productB, self.stock_location, 10.0) # Confirm batch, pickings should not be automatically assigned. self.batch.action_confirm() self.assertEqual(self.picking_client_1.state, 'confirmed', 'Picking 1 should be confirmed') self.assertEqual(self.picking_client_2.state, 'confirmed', 'Picking 2 should be confirmed') # Ask to assign, so pickings should be assigned now. self.batch.action_assign() self.assertEqual(self.picking_client_1.state, 'assigned', 'Picking 1 should be ready') self.assertEqual(self.picking_client_2.state, 'assigned', 'Picking 2 should be ready') # There should be a wizard asking to process picking without quantity done immediate_transfer_wizard_dict = self.batch.action_done() self.assertTrue(immediate_transfer_wizard_dict) immediate_transfer_wizard = Form(self.env[(immediate_transfer_wizard_dict.get('res_model'))].with_context(immediate_transfer_wizard_dict['context'])).save() self.assertEqual(len(immediate_transfer_wizard.pick_ids), 2) immediate_transfer_wizard.process() self.assertEqual(self.picking_client_1.state, 'done', 'Picking 1 should be done') self.assertEqual(self.picking_client_2.state, 'done', 'Picking 2 should be done') quant_A = self.env['stock.quant']._gather(self.productA, self.stock_location) quant_B = self.env['stock.quant']._gather(self.productB, self.stock_location) # ensure that quantity for picking has been moved self.assertFalse(sum(quant_A.mapped('quantity'))) self.assertFalse(sum(quant_B.mapped('quantity'))) def test_batch_with_backorder_wizard(self): """ Test a simple batch picking with only one quantity fully available. The user will set by himself the quantity reserved for each picking and run the picking batch. There should be a wizard asking for a backorder. """ self.env['stock.quant']._update_available_quantity(self.productA, self.stock_location, 5.0) self.env['stock.quant']._update_available_quantity(self.productB, self.stock_location, 10.0) # Confirm batch, pickings should not be automatically assigned. self.batch.action_confirm() self.assertEqual(self.picking_client_1.state, 'confirmed', 'Picking 1 should be confirmed') self.assertEqual(self.picking_client_2.state, 'confirmed', 'Picking 2 should be confirmed') # Ask to assign, so pickings should be assigned now. self.batch.action_assign() self.assertEqual(self.picking_client_1.state, 'assigned', 'Picking 1 should be ready') self.assertEqual(self.picking_client_2.state, 'assigned', 'Picking 2 should be ready') self.picking_client_1.move_lines.quantity_done = 5 self.picking_client_2.move_lines.quantity_done = 10 # There should be a wizard asking to process picking without quantity done back_order_wizard_dict = self.batch.action_done() self.assertTrue(back_order_wizard_dict) back_order_wizard = Form(self.env[(back_order_wizard_dict.get('res_model'))].with_context(back_order_wizard_dict['context'])).save() self.assertEqual(len(back_order_wizard.pick_ids), 1) back_order_wizard.process() self.assertEqual(self.picking_client_2.state, 'done', 'Picking 2 should be done') self.assertEqual(self.picking_client_1.state, 'done', 'Picking 1 should be done') self.assertEqual(self.picking_client_1.move_lines.product_uom_qty, 5, 'initial demand should be 5 after picking split') self.assertTrue(self.env['stock.picking'].search([('backorder_id', '=', self.picking_client_1.id)]), 'no back order created') quant_A = self.env['stock.quant']._gather(self.productA, self.stock_location) quant_B = self.env['stock.quant']._gather(self.productB, self.stock_location) # ensure that quantity for picking has been moved self.assertFalse(sum(quant_A.mapped('quantity'))) self.assertFalse(sum(quant_B.mapped('quantity'))) def test_batch_with_immediate_transfer_and_backorder_wizard(self): """ Test a simple batch picking with only one product fully available. Everything should be automatically. First one backorder in order to set quantity_done to reserved quantity. After a second wizard asking for a backorder for the quantity that has not been fully transfered. """ self.env['stock.quant']._update_available_quantity(self.productA, self.stock_location, 5.0) self.env['stock.quant']._update_available_quantity(self.productB, self.stock_location, 10.0) # Confirm batch, pickings should not be automatically assigned. self.batch.action_confirm() self.assertEqual(self.picking_client_1.state, 'confirmed', 'Picking 1 should be confirmed') self.assertEqual(self.picking_client_2.state, 'confirmed', 'Picking 2 should be confirmed') # Ask to assign, so pickings should be assigned now. self.batch.action_assign() self.assertEqual(self.picking_client_1.state, 'assigned', 'Picking 1 should be ready') self.assertEqual(self.picking_client_2.state, 'assigned', 'Picking 2 should be ready') # There should be a wizard asking to process picking without quantity done immediate_transfer_wizard_dict = self.batch.action_done() self.assertTrue(immediate_transfer_wizard_dict) immediate_transfer_wizard = Form(self.env[(immediate_transfer_wizard_dict.get('res_model'))].with_context(immediate_transfer_wizard_dict['context'])).save() self.assertEqual(len(immediate_transfer_wizard.pick_ids), 2) back_order_wizard_dict = immediate_transfer_wizard.process() self.assertTrue(back_order_wizard_dict) back_order_wizard = Form(self.env[(back_order_wizard_dict.get('res_model'))].with_context(back_order_wizard_dict['context'])).save() self.assertEqual(len(back_order_wizard.pick_ids), 1) back_order_wizard.process() self.assertEqual(self.picking_client_1.state, 'done', 'Picking 1 should be done') self.assertEqual(self.picking_client_1.move_lines.product_uom_qty, 5, 'initial demand should be 5 after picking split') self.assertTrue(self.env['stock.picking'].search([('backorder_id', '=', self.picking_client_1.id)]), 'no back order created') quant_A = self.env['stock.quant']._gather(self.productA, self.stock_location) quant_B = self.env['stock.quant']._gather(self.productB, self.stock_location) # ensure that quantity for picking has been moved self.assertFalse(sum(quant_A.mapped('quantity'))) self.assertFalse(sum(quant_B.mapped('quantity'))) def test_batch_with_immediate_transfer_and_backorder_wizard_with_manual_operations(self): """ Test a simple batch picking with only one quantity fully available. The user set the quantity done only for the partially available picking. The test should run the immediate transfer for the first picking and then the backorder wizard for the second picking. """ self.env['stock.quant']._update_available_quantity(self.productA, self.stock_location, 5.0) self.env['stock.quant']._update_available_quantity(self.productB, self.stock_location, 10.0) # Confirm batch, pickings should not be automatically assigned. self.batch.action_confirm() self.assertEqual(self.picking_client_1.state, 'confirmed', 'Picking 1 should be confirmed') self.assertEqual(self.picking_client_2.state, 'confirmed', 'Picking 2 should be confirmed') # Ask to assign, so pickings should be assigned now. self.batch.action_assign() self.assertEqual(self.picking_client_1.state, 'assigned', 'Picking 1 should be ready') self.assertEqual(self.picking_client_2.state, 'assigned', 'Picking 2 should be ready') self.picking_client_1.move_lines.quantity_done = 5 # There should be a wizard asking to process picking without quantity done immediate_transfer_wizard_dict = self.batch.action_done() self.assertTrue(immediate_transfer_wizard_dict) immediate_transfer_wizard = Form(self.env[(immediate_transfer_wizard_dict.get('res_model'))].with_context(immediate_transfer_wizard_dict['context'])).save() self.assertEqual(len(immediate_transfer_wizard.pick_ids), 1) back_order_wizard_dict = immediate_transfer_wizard.process() self.assertTrue(back_order_wizard_dict) back_order_wizard = Form(self.env[(back_order_wizard_dict.get('res_model'))].with_context(back_order_wizard_dict['context'])).save() self.assertEqual(len(back_order_wizard.pick_ids), 1) back_order_wizard.process() self.assertEqual(self.picking_client_1.state, 'done', 'Picking 1 should be done') self.assertEqual(self.picking_client_1.move_lines.product_uom_qty, 5, 'initial demand should be 5 after picking split') self.assertTrue(self.env['stock.picking'].search([('backorder_id', '=', self.picking_client_1.id)]), 'no back order created') quant_A = self.env['stock.quant']._gather(self.productA, self.stock_location) quant_B = self.env['stock.quant']._gather(self.productB, self.stock_location) # ensure that quantity for picking has been moved self.assertFalse(sum(quant_A.mapped('quantity'))) self.assertFalse(sum(quant_B.mapped('quantity'))) def test_put_in_pack(self): self.env['stock.quant']._update_available_quantity(self.productA, self.stock_location, 10.0) self.env['stock.quant']._update_available_quantity(self.productB, self.stock_location, 10.0) # Confirm batch, pickings should not be automatically assigned. self.batch.action_confirm() self.assertEqual(self.picking_client_1.state, 'confirmed', 'Picking 1 should be confirmed') self.assertEqual(self.picking_client_2.state, 'confirmed', 'Picking 2 should be confirmed') # Ask to assign, so pickings should be assigned now. self.batch.action_assign() self.assertEqual(self.picking_client_1.state, 'assigned', 'Picking 1 should be ready') self.assertEqual(self.picking_client_2.state, 'assigned', 'Picking 2 should be ready') # only do part of pickings + assign different destinations + try to pack (should get wizard to correct destination) self.batch.move_line_ids.qty_done = 5 self.batch.move_line_ids[0].location_dest_id = self.stock_location.id wizard_values = self.batch.action_put_in_pack() wizard = self.env[(wizard_values.get('res_model'))].browse(wizard_values.get('res_id')) wizard.location_dest_id = self.customer_location.id package = wizard.action_done() # a new package is made and done quantities should be in same package self.assertTrue(package) done_qty_move_lines = self.batch.move_line_ids.filtered(lambda ml: ml.qty_done == 5) self.assertEqual(done_qty_move_lines[0].result_package_id.id, package.id) self.assertEqual(done_qty_move_lines[1].result_package_id.id, package.id) # not done quantities should be split into separate lines self.assertEqual(len(self.batch.move_line_ids), 4) # confirm w/ backorder back_order_wizard_dict = self.batch.action_done() self.assertTrue(back_order_wizard_dict) back_order_wizard = Form(self.env[(back_order_wizard_dict.get('res_model'))].with_context(back_order_wizard_dict['context'])).save() self.assertEqual(len(back_order_wizard.pick_ids), 2) back_order_wizard.process() # final package location should be correctly set based on wizard self.assertEqual(package.location_id.id, self.customer_location.id)

56.67663

164

0.703073

2,780

20,857

5.046403

0.088849

0.058023

0.084824

0.072279

0.828569

0.792644

0.776035

0.756291

0.755863

0.740181

0

0.011535

0.193652

20,857

367

165

56.831063

0.822631

0.2147

0

0.729258

0

0.160962

0.008309

0

0.002725

0.327511

1

0.034935

false

0

0.0131

0

0.052402

0

null

0

1

0

1

0

null

0

7

01c895788e425a871a9d1583b6f60cfb41ece1d1

163

py

Python

src/tensorflow_jr/__init__.py

mvsusp/tensorflow_jr

bbf72884d0cba083c24ae1bc4d7f07b77a6210e4

[ "Apache-2.0" ]

null

src/tensorflow_jr/__init__.py

mvsusp/tensorflow_jr

bbf72884d0cba083c24ae1bc4d7f07b77a6210e4

[ "Apache-2.0" ]

null

src/tensorflow_jr/__init__.py

mvsusp/tensorflow_jr

bbf72884d0cba083c24ae1bc4d7f07b77a6210e4

[ "Apache-2.0" ]

null

from src.tensorflow_jr.operations import * from src.tensorflow_jr.core import * from src.tensorflow_jr.session import * from train import GradientDescentOptimizer

32.6

42

0.846626

22

163

6.136364

0.454545

0.155556

0.377778

0.422222

0.37037

0

0.09816

163

4

43

40.75

0.918367

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

7

01e31c770e45dd21250442b1398dc582bdf538f6

17,424

py

Python

sdk/python/pulumi_gandi/domain/domain.py

vincentbernat/pulumi-gandi

8eb3610d62e626c9ef75b8fbf393f5aab0e147a6

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_gandi/domain/domain.py

vincentbernat/pulumi-gandi

8eb3610d62e626c9ef75b8fbf393f5aab0e147a6

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_gandi/domain/domain.py

vincentbernat/pulumi-gandi

8eb3610d62e626c9ef75b8fbf393f5aab0e147a6

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities from . import outputs from ._inputs import * __all__ = ['DomainArgs', 'Domain'] @pulumi.input_type class DomainArgs: def __init__(__self__, *, owners: pulumi.Input[Sequence[pulumi.Input['DomainOwnerArgs']]], admins: Optional[pulumi.Input[Sequence[pulumi.Input['DomainAdminArgs']]]] = None, autorenew: Optional[pulumi.Input[bool]] = None, billings: Optional[pulumi.Input[Sequence[pulumi.Input['DomainBillingArgs']]]] = None, name: Optional[pulumi.Input[str]] = None, nameservers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, teches: Optional[pulumi.Input[Sequence[pulumi.Input['DomainTechArgs']]]] = None): """ The set of arguments for constructing a Domain resource. :param pulumi.Input[bool] autorenew: Should the domain autorenew :param pulumi.Input[str] name: The FQDN of the domain :param pulumi.Input[Sequence[pulumi.Input[str]]] nameservers: A list of nameservers for the domain """ pulumi.set(__self__, "owners", owners) if admins is not None: pulumi.set(__self__, "admins", admins) if autorenew is not None: pulumi.set(__self__, "autorenew", autorenew) if billings is not None: pulumi.set(__self__, "billings", billings) if name is not None: pulumi.set(__self__, "name", name) if nameservers is not None: warnings.warn("""This nameservers attribute will be removed on next major release: the nameservers resource has to be used instead. See https://github.com/go-gandi/terraform-provider-gandi/issues/88 for details.""", DeprecationWarning) pulumi.log.warn("""nameservers is deprecated: This nameservers attribute will be removed on next major release: the nameservers resource has to be used instead. See https://github.com/go-gandi/terraform-provider-gandi/issues/88 for details.""") if nameservers is not None: pulumi.set(__self__, "nameservers", nameservers) if teches is not None: pulumi.set(__self__, "teches", teches) @property @pulumi.getter def owners(self) -> pulumi.Input[Sequence[pulumi.Input['DomainOwnerArgs']]]: return pulumi.get(self, "owners") @owners.setter def owners(self, value: pulumi.Input[Sequence[pulumi.Input['DomainOwnerArgs']]]): pulumi.set(self, "owners", value) @property @pulumi.getter def admins(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['DomainAdminArgs']]]]: return pulumi.get(self, "admins") @admins.setter def admins(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['DomainAdminArgs']]]]): pulumi.set(self, "admins", value) @property @pulumi.getter def autorenew(self) -> Optional[pulumi.Input[bool]]: """ Should the domain autorenew """ return pulumi.get(self, "autorenew") @autorenew.setter def autorenew(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "autorenew", value) @property @pulumi.getter def billings(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['DomainBillingArgs']]]]: return pulumi.get(self, "billings") @billings.setter def billings(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['DomainBillingArgs']]]]): pulumi.set(self, "billings", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The FQDN of the domain """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def nameservers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ A list of nameservers for the domain """ return pulumi.get(self, "nameservers") @nameservers.setter def nameservers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "nameservers", value) @property @pulumi.getter def teches(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['DomainTechArgs']]]]: return pulumi.get(self, "teches") @teches.setter def teches(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['DomainTechArgs']]]]): pulumi.set(self, "teches", value) @pulumi.input_type class _DomainState: def __init__(__self__, *, admins: Optional[pulumi.Input[Sequence[pulumi.Input['DomainAdminArgs']]]] = None, autorenew: Optional[pulumi.Input[bool]] = None, billings: Optional[pulumi.Input[Sequence[pulumi.Input['DomainBillingArgs']]]] = None, name: Optional[pulumi.Input[str]] = None, nameservers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, owners: Optional[pulumi.Input[Sequence[pulumi.Input['DomainOwnerArgs']]]] = None, teches: Optional[pulumi.Input[Sequence[pulumi.Input['DomainTechArgs']]]] = None): """ Input properties used for looking up and filtering Domain resources. :param pulumi.Input[bool] autorenew: Should the domain autorenew :param pulumi.Input[str] name: The FQDN of the domain :param pulumi.Input[Sequence[pulumi.Input[str]]] nameservers: A list of nameservers for the domain """ if admins is not None: pulumi.set(__self__, "admins", admins) if autorenew is not None: pulumi.set(__self__, "autorenew", autorenew) if billings is not None: pulumi.set(__self__, "billings", billings) if name is not None: pulumi.set(__self__, "name", name) if nameservers is not None: warnings.warn("""This nameservers attribute will be removed on next major release: the nameservers resource has to be used instead. See https://github.com/go-gandi/terraform-provider-gandi/issues/88 for details.""", DeprecationWarning) pulumi.log.warn("""nameservers is deprecated: This nameservers attribute will be removed on next major release: the nameservers resource has to be used instead. See https://github.com/go-gandi/terraform-provider-gandi/issues/88 for details.""") if nameservers is not None: pulumi.set(__self__, "nameservers", nameservers) if owners is not None: pulumi.set(__self__, "owners", owners) if teches is not None: pulumi.set(__self__, "teches", teches) @property @pulumi.getter def admins(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['DomainAdminArgs']]]]: return pulumi.get(self, "admins") @admins.setter def admins(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['DomainAdminArgs']]]]): pulumi.set(self, "admins", value) @property @pulumi.getter def autorenew(self) -> Optional[pulumi.Input[bool]]: """ Should the domain autorenew """ return pulumi.get(self, "autorenew") @autorenew.setter def autorenew(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "autorenew", value) @property @pulumi.getter def billings(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['DomainBillingArgs']]]]: return pulumi.get(self, "billings") @billings.setter def billings(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['DomainBillingArgs']]]]): pulumi.set(self, "billings", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The FQDN of the domain """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def nameservers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ A list of nameservers for the domain """ return pulumi.get(self, "nameservers") @nameservers.setter def nameservers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "nameservers", value) @property @pulumi.getter def owners(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['DomainOwnerArgs']]]]: return pulumi.get(self, "owners") @owners.setter def owners(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['DomainOwnerArgs']]]]): pulumi.set(self, "owners", value) @property @pulumi.getter def teches(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['DomainTechArgs']]]]: return pulumi.get(self, "teches") @teches.setter def teches(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['DomainTechArgs']]]]): pulumi.set(self, "teches", value) class Domain(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, admins: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainAdminArgs']]]]] = None, autorenew: Optional[pulumi.Input[bool]] = None, billings: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainBillingArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, nameservers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, owners: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainOwnerArgs']]]]] = None, teches: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainTechArgs']]]]] = None, __props__=None): """ Create a Domain resource with the given unique name, props, and options. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[bool] autorenew: Should the domain autorenew :param pulumi.Input[str] name: The FQDN of the domain :param pulumi.Input[Sequence[pulumi.Input[str]]] nameservers: A list of nameservers for the domain """ ... @overload def __init__(__self__, resource_name: str, args: DomainArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Create a Domain resource with the given unique name, props, and options. :param str resource_name: The name of the resource. :param DomainArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(DomainArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, admins: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainAdminArgs']]]]] = None, autorenew: Optional[pulumi.Input[bool]] = None, billings: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainBillingArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, nameservers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, owners: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainOwnerArgs']]]]] = None, teches: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainTechArgs']]]]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = DomainArgs.__new__(DomainArgs) __props__.__dict__["admins"] = admins __props__.__dict__["autorenew"] = autorenew __props__.__dict__["billings"] = billings __props__.__dict__["name"] = name if nameservers is not None and not opts.urn: warnings.warn("""This nameservers attribute will be removed on next major release: the nameservers resource has to be used instead. See https://github.com/go-gandi/terraform-provider-gandi/issues/88 for details.""", DeprecationWarning) pulumi.log.warn("""nameservers is deprecated: This nameservers attribute will be removed on next major release: the nameservers resource has to be used instead. See https://github.com/go-gandi/terraform-provider-gandi/issues/88 for details.""") __props__.__dict__["nameservers"] = nameservers if owners is None and not opts.urn: raise TypeError("Missing required property 'owners'") __props__.__dict__["owners"] = owners __props__.__dict__["teches"] = teches super(Domain, __self__).__init__( 'gandi:domain/domain:Domain', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, admins: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainAdminArgs']]]]] = None, autorenew: Optional[pulumi.Input[bool]] = None, billings: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainBillingArgs']]]]] = None, name: Optional[pulumi.Input[str]] = None, nameservers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, owners: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainOwnerArgs']]]]] = None, teches: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['DomainTechArgs']]]]] = None) -> 'Domain': """ Get an existing Domain resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[bool] autorenew: Should the domain autorenew :param pulumi.Input[str] name: The FQDN of the domain :param pulumi.Input[Sequence[pulumi.Input[str]]] nameservers: A list of nameservers for the domain """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _DomainState.__new__(_DomainState) __props__.__dict__["admins"] = admins __props__.__dict__["autorenew"] = autorenew __props__.__dict__["billings"] = billings __props__.__dict__["name"] = name __props__.__dict__["nameservers"] = nameservers __props__.__dict__["owners"] = owners __props__.__dict__["teches"] = teches return Domain(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter def admins(self) -> pulumi.Output[Optional[Sequence['outputs.DomainAdmin']]]: return pulumi.get(self, "admins") @property @pulumi.getter def autorenew(self) -> pulumi.Output[Optional[bool]]: """ Should the domain autorenew """ return pulumi.get(self, "autorenew") @property @pulumi.getter def billings(self) -> pulumi.Output[Optional[Sequence['outputs.DomainBilling']]]: return pulumi.get(self, "billings") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The FQDN of the domain """ return pulumi.get(self, "name") @property @pulumi.getter def nameservers(self) -> pulumi.Output[Optional[Sequence[str]]]: """ A list of nameservers for the domain """ return pulumi.get(self, "nameservers") @property @pulumi.getter def owners(self) -> pulumi.Output[Sequence['outputs.DomainOwner']]: return pulumi.get(self, "owners") @property @pulumi.getter def teches(self) -> pulumi.Output[Optional[Sequence['outputs.DomainTech']]]: return pulumi.get(self, "teches")

44.22335

176

0.647039

1,942

17,424

5.643666

0.085479

0.128467

0.104015

0.11177

0.844161

0.815876

0.777464

0.762682

0.749635

0.748266

0

0.000973

0.233242

17,424

393

177

44.335878

0.819386

0.128157

0

0.78777

1

0.032374

0.174185

0.003198

0

1

0.151079

false

0.003597

0.02518

0.043165

0.266187

0

null

0

1

0

1

0

null

0

8

01f146e0aa9d8cce76dcf4fadb963ca6814f4017

110,449

py

Python

o3seespy/command/element/bearing.py

o3seespy/o3seespy

4fdd942370df1ac8d454e361f651405717b8584c

[ "MIT", "BSD-3-Clause" ]

16

2019-10-24T17:58:46.000Z

2022-03-01T19:48:06.000Z

o3seespy/command/element/bearing.py

o3seespy/o3seespy

4fdd942370df1ac8d454e361f651405717b8584c

[ "MIT", "BSD-3-Clause" ]

5

2020-04-17T01:39:27.000Z

2020-12-18T05:07:58.000Z

o3seespy/command/element/bearing.py

o3seespy/o3seespy

4fdd942370df1ac8d454e361f651405717b8584c

[ "MIT", "BSD-3-Clause" ]

6

2020-02-20T02:13:11.000Z

2021-11-01T19:08:41.000Z

from o3seespy.command.element.base_element import ElementBase class ElastomericBearingPlasticity2D(ElementBase): """ The ElastomericBearingPlasticity2D Element Class This command is used to construct an elastomericBearing element object, which is defined by two nodes. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) plasticity properties for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. By default (sDratio = 0.5) P-Delta moments are equally distributed to the two end-nodes. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a two-dimensional problem """ op_type = 'elastomericBearingPlasticity' def __init__(self, osi, ele_nodes, k_init, qd, alpha1, alpha2, mu, p_mat=None, mz_mat=None, do_rayleigh=False, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for ElastomericBearingPlasticity2D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes k_init: float Initial elastic stiffness in local shear direction qd: float Characteristic strength alpha1: float Post yield stiffness ratio of linear hardening component alpha2: float Post yield stiffness ratio of non-linear hardening component mu: float Exponent of non-linear hardening component p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.5) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [0, 1]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> o3.element.ElastomericBearingPlasticity2D(osi, ele_nodes=ele_nodes, k_init=1.0, qd=1.0, alpha1=1.0, alpha2=1.0, >>> mu=1.0, p_mat=p_mat, mz_mat=mz_mat) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.k_init = float(k_init) self.qd = float(qd) self.alpha1 = float(alpha1) self.alpha2 = float(alpha2) self.mu = float(mu) self.p_mat = p_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.k_init, self.qd, self.alpha1, self.alpha2, self.mu] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class ElastomericBearingPlasticity3D(ElementBase): """ The ElastomericBearingPlasticity3D Element Class This command is used to construct an elastomericBearing element object, which is defined by two nodes. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) plasticity properties for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. By default (sDratio = 0.5) P-Delta moments are equally distributed to the two end-nodes. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a three-dimensional problem """ op_type = 'elastomericBearingPlasticity' def __init__(self, osi, ele_nodes, k_init, qd, alpha1, alpha2, mu, p_mat=None, t_mat=None, my_mat=None, mz_mat=None, do_rayleigh=False, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for ElastomericBearingPlasticity3D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes k_init: float Initial elastic stiffness in local shear direction qd: float Characteristic strength alpha1: float Post yield stiffness ratio of linear hardening component alpha2: float Post yield stiffness ratio of non-linear hardening component mu: float Exponent of non-linear hardening component p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction t_mat: obj, optional Object associated with previously-defined uniaxial_material in torsional direction my_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local y-axis mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.5) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=3, ndf=6) >>> coords = [[0, 0, 0], [0, 1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> t_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> my_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> orient_vals = [1, 0, 0] >>> o3.element.ElastomericBearingPlasticity3D(osi, ele_nodes=ele_nodes, k_init=1.0, qd=1.0, alpha1=1.0, alpha2=1.0, >>> mu=1.0, p_mat=p_mat, t_mat=t_mat, my_mat=my_mat, mz_mat=mz_mat, >>> orient=orient_vals) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.k_init = float(k_init) self.qd = float(qd) self.alpha1 = float(alpha1) self.alpha2 = float(alpha2) self.mu = float(mu) self.p_mat = p_mat self.t_mat = t_mat self.my_mat = my_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.k_init, self.qd, self.alpha1, self.alpha2, self.mu] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 't_mat') is not None: self._parameters += ['-T', self.t_mat.tag] if getattr(self, 'my_mat') is not None: self._parameters += ['-My', self.my_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class ElastomericBearingBoucWen2D(ElementBase): """ The ElastomericBearingBoucWen2D Element Class This command is used to construct an elastomericBearing element object, which is defined by two nodes. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) plasticity properties for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. By default (sDratio = 0.5) P-Delta moments are equally distributed to the two end-nodes. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a two-dimensional problem """ op_type = 'elastomericBearingBoucWen' def __init__(self, osi, ele_nodes, k_init, qd, alpha1, alpha2, mu, eta, beta, gamma, p_mat=None, mz_mat=None, orient_vals: list = None, shear_dist: float = None, do_rayleigh=False, mass: float = None): """ Initial method for ElastomericBearingBoucWen2D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes k_init: float Initial elastic stiffness in local shear direction qd: float Characteristic strength alpha1: float Post yield stiffness ratio of linear hardening component alpha2: float Post yield stiffness ratio of non-linear hardening component mu: float Exponent of non-linear hardening component eta: float Yielding exponent (sharpness of hysteresis loop corners) (default = 1.0) beta: float First hysteretic shape parameter (default = 0.5) gamma: float Second hysteretic shape parameter (default = 0.5) p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis orient_vals: list, optional Vector components in global coordinates defining local x-axis , vector components in global coordinates defining local y-axis shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.5) do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) mass: float, optional Element mass (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> orient_vals = [1, 0, 0, 1, 0, 1] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> o3.element.ElastomericBearingBoucWen2D(osi, ele_nodes=ele_nodes, k_init=1.0, qd=1.0, alpha1=1.0, alpha2=1.0, >>> mu=1.0, eta=1.0, beta=1.0, gamma=1.0, p_mat=p_mat, mz_mat=mz_mat, >>> orient_vals=orient_vals, shear_dist=1.0, do_rayleigh=False, mass=1.0) """ self.osi = osi self.ele_nodes = [x.tag for x in ele_nodes] self.k_init = float(k_init) self.qd = float(qd) self.alpha1 = float(alpha1) self.alpha2 = float(alpha2) self.mu = float(mu) self.eta = float(eta) self.beta = float(beta) self.gamma = float(gamma) self.p_mat = p_mat self.mz_mat = mz_mat self.orient_vals = orient_vals if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) self.do_rayleigh = do_rayleigh if mass is None: self.mass = None else: self.mass = float(mass) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_nodes, self.k_init, self.qd, self.alpha1, self.alpha2, self.mu, self.eta, self.beta, self.gamma] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'orient_vals') is not None: self._parameters += ['-orient', *self.orient_vals] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] try: self.to_process(osi) except ValueError: self._parameters[0] = 'ElastomericBearingBoucWen' self.to_process(osi) class ElastomericBearingBoucWen3D(ElementBase): """ The ElastomericBearingBoucWen3D Element Class This command is used to construct an elastomericBearing element object, which is defined by two nodes. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) plasticity properties for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. By default (sDratio = 0.5) P-Delta moments are equally distributed to the two end-nodes. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a three-dimensional problem """ op_type = 'elastomericBearingBoucWen' def __init__(self, osi, ele_nodes, k_init, qd, alpha1, alpha2, mu, eta, beta, gamma, p_mat=None, t_mat=None, my_mat=None, mz_mat=None, orient_vals: list = None, shear_dist: float = None, do_rayleigh=False, mass: float = None): """ Initial method for ElastomericBearingBoucWen3D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes k_init: float Initial elastic stiffness in local shear direction qd: float Characteristic strength alpha1: float Post yield stiffness ratio of linear hardening component alpha2: float Post yield stiffness ratio of non-linear hardening component mu: float Exponent of non-linear hardening component eta: float Yielding exponent (sharpness of hysteresis loop corners) (default = 1.0) beta: float First hysteretic shape parameter (default = 0.5) gamma: float Second hysteretic shape parameter (default = 0.5) p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction t_mat: obj, optional Object associated with previously-defined uniaxial_material in torsional direction my_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local y-axis mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis orient_vals: list, optional Vector components in global coordinates defining local x-axis , vector components in global coordinates defining local y-axis shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.5) do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) mass: float, optional Element mass (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=3, ndf=6) >>> coords = [[0, 0, 0], [0, 1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> orient_vals = [1, 0, 0] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> t_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> my_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> o3.element.ElastomericBearingBoucWen3D(osi, ele_nodes=ele_nodes, k_init=1.0, qd=1.0, alpha1=1.0, alpha2=1.0, >>> mu=1.0, eta=1.0, beta=1.0, gamma=1.0, p_mat=p_mat, t_mat=t_mat, >>> my_mat=my_mat, mz_mat=mz_mat, orient_vals=orient_vals, >>> shear_dist=1.0, do_rayleigh=False, mass=1.0) """ self.osi = osi self.ele_nodes = [x.tag for x in ele_nodes] self.k_init = float(k_init) self.qd = float(qd) self.alpha1 = float(alpha1) self.alpha2 = float(alpha2) self.mu = float(mu) self.eta = float(eta) self.beta = float(beta) self.gamma = float(gamma) self.p_mat = p_mat self.t_mat = t_mat self.my_mat = my_mat self.mz_mat = mz_mat self.orient_vals = orient_vals if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) self.do_rayleigh = do_rayleigh if mass is None: self.mass = None else: self.mass = float(mass) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_nodes, self.k_init, self.qd, self.alpha1, self.alpha2, self.mu, self.eta, self.beta, self.gamma] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 't_mat') is not None: self._parameters += ['-T', self.t_mat.tag] if getattr(self, 'my_mat') is not None: self._parameters += ['-My', self.my_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'orient_vals') is not None: self._parameters += ['-orient', *self.orient_vals] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] try: self.to_process(osi) except ValueError: self._parameters[0] = 'ElastomericBearingBoucWen' self.to_process(osi) class FlatSliderBearing2D(ElementBase): """ The FlatSliderBearing2D Element Class This command is used to construct a flatSliderBearing element object, which is defined by two nodes. The iNode represents the flat sliding surface and the jNode represents the slider. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) friction properties for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. To capture the uplift behavior of the bearing, the user-specified UniaxialMaterial in the axial direction is modified for no-tension behavior. By default (sDratio = 0.0) P-Delta moments are entirely transferred to the flat sliding surface (iNode). It is important to note that rotations of the flat sliding surface (rotations at the iNode) affect the shear behavior of the bearing. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a two-dimensional problem """ op_type = 'flatSliderBearing' def __init__(self, osi, ele_nodes, frn_mdl, k_init, p_mat=None, mz_mat=None, do_rayleigh=False, max_iter: int=None, tol: float=None, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for FlatSliderBearing2D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes frn_mdl: obj Object associated with previously-defined frictionmodel k_init: float Initial elastic stiffness in local shear direction p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) max_iter: int, optional Maximum number of iterations to undertake to satisfy element equilibrium (optional, default = 20) tol: float, optional Convergence tolerance to satisfy element equilibrium (optional, default = 1e-8) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> frn1 = o3.friction_model.Coulomb(osi, mu=1.0) >>> o3.element.FlatSliderBearing2D(osi, ele_nodes=ele_nodes, frn_mdl=frn1, k_init=1.0, p_mat=p_mat, mz_mat=mz_mat, >>> do_rayleigh=False, max_iter=1, tol=1.0, orient=None, mass=1.0, shear_dist=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.frn_mdl = frn_mdl self.k_init = float(k_init) self.p_mat = p_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh if max_iter is None: self.max_iter = None else: self.max_iter = int(max_iter) if tol is None: self.tol = None else: self.tol = float(tol) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.frn_mdl.tag, self.k_init] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'max_iter') is not None: self._parameters += ['-iter', self.max_iter] if getattr(self, 'tol') is not None: if getattr(self, 'max_iter') is None: raise ValueError('Cannot set: tol and not: max_iter') self._parameters += [self.tol] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class FlatSliderBearing3D(ElementBase): """ The FlatSliderBearing3D Element Class This command is used to construct a flatSliderBearing element object, which is defined by two nodes. The iNode represents the flat sliding surface and the jNode represents the slider. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) friction properties for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. To capture the uplift behavior of the bearing, the user-specified UniaxialMaterial in the axial direction is modified for no-tension behavior. By default (sDratio = 0.0) P-Delta moments are entirely transferred to the flat sliding surface (iNode). It is important to note that rotations of the flat sliding surface (rotations at the iNode) affect the shear behavior of the bearing. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a three-dimensional problem """ op_type = 'flatSliderBearing' def __init__(self, osi, ele_nodes, frn_mdl, k_init, p_mat=None, t_mat=None, my_mat=None, mz_mat=None, do_rayleigh=False, max_iter=None, tol: float=None, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for FlatSliderBearing3D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes frn_mdl: obj Object associated with previously-defined frictionmodel k_init: float Initial elastic stiffness in local shear direction p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction t_mat: obj, optional Object associated with previously-defined uniaxial_material in torsional direction my_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local y-axis mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) max_iter: None, optional tol: float, optional Convergence tolerance to satisfy element equilibrium (optional, default = 1e-8) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=3, ndf=6) >>> coords = [[0, 0, 0], [0, 1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> t_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> my_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> frn1 = o3.friction_model.Coulomb(osi, mu=1.0) >>> orient_vals = [1, 0, 0] >>> o3.element.FlatSliderBearing3D(osi, ele_nodes=ele_nodes, frn_mdl=frn1, k_init=1.0, p_mat=p_mat, t_mat=t_mat, >>> my_mat=my_mat, mz_mat=mz_mat, do_rayleigh=False, max_iter=None, tol=None, >>> mass=1.0, shear_dist=1.0, orient=orient_vals) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.frn_mdl = frn_mdl self.k_init = float(k_init) self.p_mat = p_mat self.t_mat = t_mat self.my_mat = my_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh self.max_iter = max_iter if tol is None: self.tol = None else: self.tol = float(tol) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.frn_mdl.tag, self.k_init] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 't_mat') is not None: self._parameters += ['-T', self.t_mat.tag] if getattr(self, 'my_mat') is not None: self._parameters += ['-My', self.my_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'max_iter') is not None: self._parameters += ['-iter', self.max_iter] if getattr(self, 'tol') is not None: if getattr(self, 'max_iter') is None: raise ValueError('Cannot set: tol and not: max_iter') self._parameters += [self.tol] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class SingleFPBearing2D(ElementBase): """ The SingleFPBearing2D Element Class This command is used to construct a singleFPBearing element object, which is defined by two nodes. The iNode represents the concave sliding surface and the jNode represents the articulated slider. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) friction properties (with post-yield stiffening due to the concave sliding surface) for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. To capture the uplift behavior of the bearing, the user-specified UniaxialMaterial in the axial direction is modified for no-tension behavior. By default (sDratio = 0.0) P-Delta moments are entirely transferred to the concave sliding surface (iNode). It is important to note that rotations of the concave sliding surface (rotations at the iNode) affect the shear behavior of the bearing. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a two-dimensional problem """ op_type = 'singleFPBearing' def __init__(self, osi, ele_nodes, frn_mdl, reff, k_init, p_mat=None, mz_mat=None, do_rayleigh=False, max_iter: int=None, tol: float=None, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for SingleFPBearing2D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes frn_mdl: obj Object associated with previously-defined frictionmodel reff: float Effective radius of concave sliding surface k_init: float Initial elastic stiffness in local shear direction p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) max_iter: int, optional Maximum number of iterations to undertake to satisfy element equilibrium (optional, default = 20) tol: float, optional Convergence tolerance to satisfy element equilibrium (optional, default = 1e-8) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> frn1 = o3.friction_model.Coulomb(osi, mu=1.0) >>> o3.element.SingleFPBearing2D(osi, ele_nodes=ele_nodes, frn_mdl=frn1, reff=1.0, k_init=1.0, p_mat=p_mat, >>> mz_mat=mz_mat, do_rayleigh=False, max_iter=1, tol=1.0, orient=None, >>> mass=1.0, shear_dist=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.frn_mdl = frn_mdl self.reff = float(reff) self.k_init = float(k_init) self.p_mat = p_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh if max_iter is None: self.max_iter = None else: self.max_iter = int(max_iter) if tol is None: self.tol = None else: self.tol = float(tol) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.frn_mdl.tag, self.reff, self.k_init] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'max_iter') is not None: self._parameters += ['-iter', self.max_iter] if getattr(self, 'tol') is not None: if getattr(self, 'max_iter') is None: raise ValueError('Cannot set: tol and not: max_iter') self._parameters += [self.tol] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class SingleFPBearing3D(ElementBase): """ The SingleFPBearing3D Element Class This command is used to construct a singleFPBearing element object, which is defined by two nodes. The iNode represents the concave sliding surface and the jNode represents the articulated slider. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) friction properties (with post-yield stiffening due to the concave sliding surface) for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. To capture the uplift behavior of the bearing, the user-specified UniaxialMaterial in the axial direction is modified for no-tension behavior. By default (sDratio = 0.0) P-Delta moments are entirely transferred to the concave sliding surface (iNode). It is important to note that rotations of the concave sliding surface (rotations at the iNode) affect the shear behavior of the bearing. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a three-dimensional problem """ op_type = 'singleFPBearing' def __init__(self, osi, ele_nodes, frn_mdl, reff, k_init, p_mat=None, t_mat=None, my_mat=None, mz_mat=None, do_rayleigh=False, max_iter: int=None, tol: float=None, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for SingleFPBearing3D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes frn_mdl: obj Object associated with previously-defined frictionmodel reff: float Effective radius of concave sliding surface k_init: float Initial elastic stiffness in local shear direction p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction t_mat: obj, optional Object associated with previously-defined uniaxial_material in torsional direction my_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local y axis mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) max_iter: int, optional Maximum number of iterations to undertake to satisfy element equilibrium (optional, default = 20) tol: float, optional Convergence tolerance to satisfy element equilibrium (optional, default = 1e-8) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=3, ndf=6) >>> coords = [[0, 0, 0], [0, 1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> p_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mz_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> t_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> my_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> frn1 = o3.friction_model.Coulomb(osi, mu=1.0) >>> orient_vals = [1, 0, 0] >>> o3.element.SingleFPBearing3D(osi, ele_nodes=ele_nodes, frn_mdl=frn1, reff=1.0, k_init=1.0, p_mat=p_mat, t_mat=t_mat, >>> my_mat=my_mat, mz_mat=mz_mat, do_rayleigh=False, max_iter=None, tol=None, >>> orient=orient_vals, mass=1.0, shear_dist=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.frn_mdl = frn_mdl self.reff = float(reff) self.k_init = float(k_init) self.p_mat = p_mat self.t_mat = t_mat self.my_mat = my_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh if max_iter is None: self.max_iter = None else: self.max_iter = int(max_iter) if tol is None: self.tol = None else: self.tol = float(tol) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.frn_mdl.tag, self.reff, self.k_init] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 't_mat') is not None: self._parameters += ['-T', self.t_mat.tag] if getattr(self, 'my_mat') is not None: self._parameters += ['-My', self.my_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'max_iter') is not None: self._parameters += ['-iter', self.max_iter] if getattr(self, 'tol') is not None: if getattr(self, 'max_iter') is None: raise ValueError('Cannot set: tol and not: max_iter') self._parameters += [self.tol] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class TFP(ElementBase): """ The TFP Element Class This command is used to construct a Triple Friction Pendulum Bearing element object, which is defined by two nodes. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) friction properties (with post-yield stiffening due to the concave sliding surface) for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. To capture the uplift behavior of the bearing, the user-specified UniaxialMaterial in the axial direction is modified for no-tension behavior. P-Delta moments are entirely transferred to the concave sliding surface (iNode). It is important to note that rotations of the concave sliding surface (rotations at the iNode) affect the shear behavior of the bearing. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. """ op_type = 'TFP' def __init__(self, osi, ele_nodes, r1, r2, r3, r4, db1, db2, db3, db4, d1, d2, d3, d4, mu1, mu2, mu3, mu4, h1, h2, h3, h4, h0, col_load, big_k=None): """ Initial method for TFP Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes r1: float Radius of inner bottom sliding surface r2: float Radius of inner top sliding surface r3: float Radius of outer bottom sliding surface r4: float Radius of outer top sliding surface db1: float Diameter of inner bottom sliding surface db2: float Diameter of inner top sliding surface db3: float Diameter of outer bottom sliding surface db4: float Diameter of outer top sliding surface d1: float Diameter of inner slider d2: float Diameter of inner slider d3: float Diameter of outer bottom slider d4: float Diameter of outer top slider mu1: float Friction coefficient of inner bottom sliding surface mu2: float Friction coefficient of inner top sliding surface mu3: float Friction coefficient of outer bottom sliding surface mu4: float Friction coefficient of outer top sliding surface h1: float Height from inner bottom sliding surface to center of bearing h2: float Height from inner top sliding surface to center of bearing h3: float Height from outer bottom sliding surface to center of bearing h4: float Height from inner top sliding surface to center of bearing h0: float Total height of bearing col_load: float Initial axial load on bearing (only used for first time step then load come from model) big_k: float Optional, stiffness of spring in vertical dirn (dof 2 if ndm= 2, dof 3 if ndm = 3) (default=1.0e15) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> o3.element.TFP(osi, ele_nodes=ele_nodes, >>> r1=1.0, r2=1.0, r3=1.0, r4=1.0, >>> db1=1.0, db2=1.0, db3=1.0, db4=1.0, >>> d1=1.0, d2=1.0, d3=1.0, d4=1.0, >>> mu1=0.3, mu2=0.4, mu3=0.5, mu4=0.5, >>> h1=1.0, h2=1.0, h3=1.0, h4=1.0, >>> h0=1.0, col_load=1.0, big_k=None) """ self.osi = osi self.ele_nodes = [x.tag for x in ele_nodes] self.r1 = float(r1) self.r2 = float(r2) self.r3 = float(r3) self.r4 = float(r4) self.db1 = float(db1) self.db2 = float(db2) self.db3 = float(db3) self.db4 = float(db4) self.d1 = float(d1) self.d2 = float(d2) self.d3 = float(d3) self.d4 = float(d4) self.mu1 = float(mu1) self.mu2 = float(mu2) self.mu3 = float(mu3) self.mu4 = float(mu4) self.h1 = float(h1) self.h2 = float(h2) self.h3 = float(h3) self.h4 = float(h4) self.h0 = float(h0) self.col_load = float(col_load) if big_k is not None: self.big_k = float(big_k) else: self.big_k = None osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_nodes, self.r1, self.r2, self.r3, self.r4, self.db1, self.db2, self.db3, self.db4, self.d1, self.d2, self.d3, self.d4, self.mu1, self.mu2, self.mu3, self.mu4, self.h1, self.h2, self.h3, self.h4, self.h0, self.col_load] if getattr(self, 'big_k') is not None: self._parameters += [self.big_k] self.to_process(osi) class TripleFrictionPendulum(ElementBase): """ The TripleFrictionPendulum Element Class """ op_type = 'TripleFrictionPendulum' def __init__(self, osi, ele_nodes, frn1, frn2, frn3, vert_mat, rot_z_mat, rot_x_mat, rot_y_mat, l1, l2, l3, d1, d2, d3, big_w, uy, kvt, min_fv, tol): """ Initial method for TripleFrictionPendulum Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes frn1: obj = objects associated with previously-defined frictionmodels at the three sliding interfaces frn2: obj = objects associated with previously-defined frictionmodels at the three sliding interfaces frn3: obj = objects associated with previously-defined frictionmodels at the three sliding interfaces vert_mat: obj = pre-defined material object for compression behavior of the bearing rot_z_mat: obj = pre-defined material objects for rotational behavior about 3-axis, 1-axis and 2-axis, respectively. rot_x_mat: obj = pre-defined material objects for rotational behavior about 3-axis, 1-axis and 2-axis, respectively. rot_y_mat: obj = pre-defined material objects for rotational behavior about 3-axis, 1-axis and 2-axis, respectively. l1: float = effective radii. li = r_i - h_i (see figure 1) l2: float = effective radii. li = r_i - h_i (see figure 1) l3: float = effective radii. li = r_i - h_i (see figure 1) d1: float = displacement limits of pendulums (figure 1). displacement limit of the bearing is 2 ``d1`` + ``d2`` + ``d3`` + ``l1``. ``d3``/ ``l3`` - ``l1``. ``d2``/ ``l2`` d2: float = displacement limits of pendulums (figure 1). displacement limit of the bearing is 2 ``d1`` + ``d2`` + ``d3`` + ``l1``. ``d3``/ ``l3`` - ``l1``. ``d2``/ ``l2`` d3: float = displacement limits of pendulums (figure 1). displacement limit of the bearing is 2 ``d1`` + ``d2`` + ``d3`` + ``l1``. ``d3``/ ``l3`` - ``l1``. ``d2``/ ``l2`` big_w: float = axial force used for the first trial of the first analysis step. uy: float = lateral displacement where sliding of the bearing starts. recommended value = 0.25 to 1 mm. a smaller value may cause convergence problem. kvt: float = tension stiffness k_vt of the bearing. min_fv: None tol: float = relative tolerance for checking the convergence of the element. recommended value = 1.e-10 to 1.e-3. Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> frn1 = o3.friction_model.Coulomb(osi, mu=1.0) >>> frn2 = o3.friction_model.Coulomb(osi, mu=1.0) >>> frn3 = o3.friction_model.Coulomb(osi, mu=1.0) >>> vert_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> rot_z_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> rot_x_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> rot_y_mat = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> o3.element.TripleFrictionPendulum(osi, ele_nodes=ele_nodes, frn1=frn1, frn2=frn2, frn3=frn3, vert_mat=vert_mat, >>> rot_z_mat=rot_z_mat, rot_x_mat=rot_x_mat, rot_y_mat=rot_y_mat, l1=1.0, l2=1.0, >>> l3=1.0, d1=1.0, d2=1.0, d3=1.0, big_w=1.0, uy=1.0, kvt=1.0, min_fv=None, tol=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.frn1 = frn1 self.frn2 = frn2 self.frn3 = frn3 self.vert_mat = vert_mat self.rot_z_mat = rot_z_mat self.rot_x_mat = rot_x_mat self.rot_y_mat = rot_y_mat self.l1 = float(l1) self.l2 = float(l2) self.l3 = float(l3) self.d1 = float(d1) self.d2 = float(d2) self.d3 = float(d3) self.big_w = float(big_w) self.uy = float(uy) self.kvt = float(kvt) self.min_fv = min_fv self.tol = float(tol) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.frn1.tag, self.frn2.tag, self.frn3.tag, self.vert_mat.tag, self.rot_z_mat.tag, self.rot_x_mat.tag, self.rot_y_mat.tag, self.l1, self.l2, self.l3, self.d1, self.d2, self.d3, self.big_w, self.uy, self.kvt, self.min_fv, self.tol] self.to_process(osi) class MultipleShearSpring(ElementBase): """ The MultipleShearSpring Element Class This command is used to construct a multipleShearSpring (MSS) element object, which is defined by two nodes. This element consists of a series of identical shear springs arranged radially to represent the isotropic behavior in the local y-z plane. """ op_type = 'multipleShearSpring' def __init__(self, osi, ele_nodes, n_spring, mat=None, lim: float=None, mass: float=None, orient=None): """ Initial method for MultipleShearSpring Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes n_spring: int Number of springs mat: obj, optional Object associated with previously-defined uniaxial_material object lim: float, optional Minimum deformation to calculate equivalent coefficient (see note 1) mass: float, optional Element mass orient: None, optional Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=3, ndf=6) >>> coords = [[0, 0, 0], [1, 0, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> mat = o3.uniaxial_material.Elastic(osi, 1.0) >>> o3.element.MultipleShearSpring(osi, ele_nodes=ele_nodes, n_spring=1, mat=mat, lim=1.0, mass=1.0, orient=None) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.n_spring = int(n_spring) self.mat = mat if lim is None: self.lim = None else: self.lim = float(lim) if mass is None: self.mass = None else: self.mass = float(mass) self.orient = orient osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.n_spring] if getattr(self, 'mat') is not None: self._parameters += ['-mat', self.mat.tag] if getattr(self, 'lim') is not None: self._parameters += ['-lim', self.lim] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] self.to_process(osi) class KikuchiBearingadjustPDOutput(ElementBase): """ The KikuchiBearingadjustPDOutput Element Class This command is used to construct a KikuchiBearing element object, which is defined by two nodes. This element consists of multiple shear spring model (MSS) and multiple normal spring model (MNS). """ op_type = 'KikuchiBearing' def __init__(self, osi, ele_nodes, total_rubber, ci, cj, shape: float=None, size: float=None, total_height: float=None, n_mss: int=None, mat_mss=None, lim_disp: float=None, n_mns: int=None, mat_mns=None, lamb: float=None, no_pd_input=False, no_tilt=False, orient=None, mass: float=None): """ Initial method for KikuchiBearingadjustPDOutput Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes total_rubber: float Total rubber thickness ci: float P-delta moment adjustment for reaction force (default: ``ci`` =0.5, ``cj`` =0.5) cj: float P-delta moment adjustment for reaction force (default: ``ci`` =0.5, ``cj`` =0.5) shape: float, optional Following shapes are available: round, square size: float, optional Diameter (round shape), length of edge (square shape) total_height: float, optional Total height of the bearing (defaulut: distance between inode and jnode) n_mss: int, optional Number of springs in mss = nmss mat_mss: obj, optional Matobject for mss lim_disp: float, optional Minimum deformation to calculate equivalent coefficient of mss (see note 1) n_mns: int, optional Number of springs in mns = nmns*nmns (for round and square shape) mat_mns: obj, optional Matobject for mns lamb: float, optional Parameter to calculate compression modulus distribution on mns (see note 2) no_pd_input: bool Not consider p-delta moment no_tilt: bool Not consider tilt of rigid link orient: None, optional mass: float, optional Element mass Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> mat_mss = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mat_mns = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> o3.element.KikuchiBearingadjustPDOutput(osi, ele_nodes=ele_nodes, shape=1.0, size=1.0, total_rubber=1.0, total_height=1.0, n_mss=1, mat_mss=mat_mss, lim_disp=1.0, n_mns=1, mat_mns=mat_mns, lamb=1.0, no_pd_input="string", no_tilt="string", ci=1.0, cj=1.0, orient=[0.0, 0.0], mass=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes if shape is None: self.shape = None else: self.shape = float(shape) if size is None: self.size = None else: self.size = float(size) self.total_rubber = float(total_rubber) if total_height is None: self.total_height = None else: self.total_height = float(total_height) if n_mss is None: self.n_mss = None else: self.n_mss = int(n_mss) self.mat_mss = mat_mss if lim_disp is None: self.lim_disp = None else: self.lim_disp = float(lim_disp) if n_mns is None: self.n_mns = None else: self.n_mns = int(n_mns) self.mat_mns = mat_mns if lamb is None: self.lamb = None else: self.lamb = float(lamb) self.no_pd_input = no_pd_input self.no_tilt = no_tilt self.ci = float(ci) self.cj = float(cj) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.total_rubber, '-adjustPDOutput', self.ci, self.cj] if getattr(self, 'shape') is not None: self._parameters += ['-shape', self.shape] if getattr(self, 'size') is not None: self._parameters += ['-size', self.size] if getattr(self, 'total_height') is not None: self._parameters += ['-totalHeight', self.total_height] if getattr(self, 'n_mss') is not None: self._parameters += ['-nMSS', self.n_mss] if getattr(self, 'mat_mss') is not None: self._parameters += ['-matMSS', self.mat_mss.tag] if getattr(self, 'lim_disp') is not None: self._parameters += ['-limDisp', self.lim_disp] if getattr(self, 'n_mns') is not None: self._parameters += ['-nMNS', self.n_mns] if getattr(self, 'mat_mns') is not None: self._parameters += ['-matMNS', self.mat_mns.tag] if getattr(self, 'lamb') is not None: self._parameters += ['-lambda', self.lamb] if getattr(self, 'no_pd_input'): self._parameters += ['-noPDInput'] if getattr(self, 'no_tilt'): self._parameters += ['-noTilt'] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] self.to_process(osi) class KikuchiBearingdoBalance(ElementBase): """ The KikuchiBearingdoBalance Element Class This command is used to construct a KikuchiBearing element object, which is defined by two nodes. This element consists of multiple shear spring model (MSS) and multiple normal spring model (MNS). """ op_type = 'KikuchiBearing' def __init__(self, osi, ele_nodes, total_rubber, lim_fo, lim_fi, n_iter, shape: float=None, size: float=None, total_height: float=None, n_mss: int=None, mat_mss=None, lim_disp: float=None, n_mns: int=None, mat_mns=None, lamb: float=None, no_pd_input=False, no_tilt=False, orient=None, mass: float=None): """ Initial method for KikuchiBearingdoBalance Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes total_rubber: float Total rubber thickness lim_fo: float Tolerance of external unbalanced force ( ``limfo``), tolorance of internal unbalanced force ( ``limfi``), number of iterations to get rid of internal unbalanced force ( ``niter``) lim_fi: float Tolerance of external unbalanced force ( ``limfo``), tolorance of internal unbalanced force ( ``limfi``), number of iterations to get rid of internal unbalanced force ( ``niter``) n_iter: float Tolerance of external unbalanced force ( ``limfo``), tolorance of internal unbalanced force ( ``limfi``), number of iterations to get rid of internal unbalanced force ( ``niter``) shape: float, optional Following shapes are available: round, square size: float, optional Diameter (round shape), length of edge (square shape) total_height: float, optional Total height of the bearing (defaulut: distance between inode and jnode) n_mss: int, optional Number of springs in mss = nmss mat_mss: obj, optional Matobject for mss lim_disp: float, optional Minimum deformation to calculate equivalent coefficient of mss (see note 1) n_mns: int, optional Number of springs in mns = nmns*nmns (for round and square shape) mat_mns: obj, optional Matobject for mns lamb: float, optional Parameter to calculate compression modulus distribution on mns (see note 2) no_pd_input: bool Not consider p-delta moment no_tilt: bool Not consider tilt of rigid link orient: None, optional mass: float, optional Element mass Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> mat_mss = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> mat_mns = o3.uniaxial_material.Elastic(osi, e_mod=1.0, eta=0.0, eneg=None) >>> o3.element.KikuchiBearingdoBalance(osi, ele_nodes=ele_nodes, shape=1.0, size=1.0, total_rubber=1.0, total_height=1.0, n_mss=1, mat_mss=mat_mss, lim_disp=1.0, n_mns=1, mat_mns=mat_mns, lamb=1.0, no_pd_input="string", no_tilt="string", lim_fo=1.0, lim_fi=1.0, n_iter=1.0, orient=[0.0, 0.0], mass=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes if shape is None: self.shape = None else: self.shape = float(shape) if size is None: self.size = None else: self.size = float(size) self.total_rubber = float(total_rubber) if total_height is None: self.total_height = None else: self.total_height = float(total_height) if n_mss is None: self.n_mss = None else: self.n_mss = int(n_mss) self.mat_mss = mat_mss if lim_disp is None: self.lim_disp = None else: self.lim_disp = float(lim_disp) if n_mns is None: self.n_mns = None else: self.n_mns = int(n_mns) self.mat_mns = mat_mns if lamb is None: self.lamb = None else: self.lamb = float(lamb) self.no_pd_input = no_pd_input self.no_tilt = no_tilt self.lim_fo = float(lim_fo) self.lim_fi = float(lim_fi) self.n_iter = float(n_iter) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.total_rubber, '-doBalance', self.lim_fo, self.lim_fi, self.n_iter] if getattr(self, 'shape') is not None: self._parameters += ['-shape', self.shape] if getattr(self, 'size') is not None: self._parameters += ['-size', self.size] if getattr(self, 'total_height') is not None: self._parameters += ['-totalHeight', self.total_height] if getattr(self, 'n_mss') is not None: self._parameters += ['-nMSS', self.n_mss] if getattr(self, 'mat_mss') is not None: self._parameters += ['-matMSS', self.mat_mss.tag] if getattr(self, 'lim_disp') is not None: self._parameters += ['-limDisp', self.lim_disp] if getattr(self, 'n_mns') is not None: self._parameters += ['-nMNS', self.n_mns] if getattr(self, 'mat_mns') is not None: self._parameters += ['-matMNS', self.mat_mns.tag] if getattr(self, 'lamb') is not None: self._parameters += ['-lambda', self.lamb] if getattr(self, 'no_pd_input'): self._parameters += ['-noPDInput'] if getattr(self, 'no_tilt'): self._parameters += ['-noTilt'] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] self.to_process(osi) class YamamotoBiaxialHDRcoRS(ElementBase): """ The YamamotoBiaxialHDRcoRS Element Class This command is used to construct a YamamotoBiaxialHDR element object, which is defined by two nodes. This element can be used to represent the isotropic behavior of high-damping rubber bearing in the local y-z plane. """ op_type = 'YamamotoBiaxialHDR' def __init__(self, osi, ele_nodes, tp, d_do, d_di, hr, cr, cs, orient: list=None, mass: float=None): """ Initial method for YamamotoBiaxialHDRcoRS Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes tp: int Compound type = 1 : x0.6r manufactured by bridgestone corporation. d_do: float Outer diameter [m] d_di: float Bore diameter [m] hr: float Total thickness of rubber layer [m] optional data cr: float Coefficients for shear stress components of tau_r and tau_s cs: float Coefficients for shear stress components of tau_r and tau_s orient: list, optional mass: float, optional Element mass [kg] Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> o3.element.YamamotoBiaxialHDRcoRS(osi, ele_nodes=ele_nodes, tp=1, d_do=1.0, d_di=1.0, hr=1.0, cr=1.0, cs=1.0, orient=[0.0, 0.0], mass=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.tp = int(tp) self.d_do = float(d_do) self.d_di = float(d_di) self.hr = float(hr) self.cr = float(cr) self.cs = float(cs) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.tp, self.d_do, self.d_di, self.hr, '-coRS', self.cr, self.cs] if getattr(self, 'orient') is not None: self._parameters += ['--orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] self.to_process(osi) class ElastomericX(ElementBase): """ The ElastomericX Element Class This command is used to construct an ElastomericX bearing element object in three-dimension. The 3D continuum geometry of an elastomeric bearing is modeled as a 2-node, 12 DOF discrete element. This elements extends the formulation of Elastomeric_Bearing_(Bouc-Wen)_Element element. However, instead of the user providing material models as input arguments, it only requires geometric and material properties of an elastomeric bearing as arguments. The material models in six direction are formulated within the element from input arguments. The time-dependent values of mechanical properties (e.g., shear stiffness, buckling load capacity) can also be recorded using the "parameters" recorder. For 3D problem """ op_type = 'ElastomericX' def __init__(self, osi, ele_nodes, fy, alpha, gr, kbulk, d1, d2, ts, tr, n, x1, x2, x3, y1, y2, y3, kc, phi_m, ac, s_dratio, m, cd, tc, tag1, tag2, tag3, tag4): """ Initial method for ElastomericX Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes fy: float Yield strength alpha: float Post-yield stiffness ratio gr: float Shear modulus of elastomeric bearing kbulk: float Bulk modulus of rubber d1: float Internal diameter d2: float Outer diameter (excluding cover thickness) ts: float Single steel shim layer thickness tr: float Single rubber layer thickness n: int Number of rubber layers x1: float Vector components in global coordinates defining local x-axis x2: float Vector components in global coordinates defining local x-axis x3: float Vector components in global coordinates defining local x-axis y1: float Vector components in global coordinates defining local y-axis y2: float Vector components in global coordinates defining local y-axis y3: float Vector components in global coordinates defining local y-axis kc: float Cavitation parameter (optional, default = 10.0) phi_m: float Damage parameter (optional, default = 0.5) ac: float Strength reduction parameter (optional, default = 1.0) s_dratio: float Shear distance from inode as a fraction of the element length (optional, default = 0.5) m: float Element mass (optional, default = 0.0) cd: float Viscous damping parameter (optional, default = 0.0) tc: float Cover thickness (optional, default = 0.0) tag1: float Object to include cavitation and post-cavitation (optional, default = 0) tag2: float Object to include buckling load variation (optional, default = 0) tag3: float Object to include horizontal stiffness variation (optional, default = 0) tag4: float Object to include vertical stiffness variation (optional, default = 0) Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> o3.element.ElastomericX(osi, ele_nodes=ele_nodes, fy=1.0, alpha=1.0, gr=1.0, kbulk=1.0, d1=1.0, d2=1.0, ts=1.0, >>> tr=1.0, n=1, x1=1.0, x2=1.0, x3=1.0, y1=1.0, y2=1.0, y3=1.0, kc=1.0, phi_m=1.0, ac=1.0, >>> s_dratio=1.0, m=1.0, cd=1.0, tc=1.0, tag1=0, tag2=0, tag3=0, tag4=0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.fy = float(fy) self.alpha = float(alpha) self.gr = float(gr) self.kbulk = float(kbulk) self.d1 = float(d1) self.d2 = float(d2) self.ts = float(ts) self.tr = float(tr) self.n = int(n) self.x1 = float(x1) self.x2 = float(x2) self.x3 = float(x3) self.y1 = float(y1) self.y2 = float(y2) self.y3 = float(y3) self.kc = float(kc) self.phi_m = float(phi_m) self.ac = float(ac) self.s_dratio = float(s_dratio) self.m = float(m) self.cd = float(cd) self.tc = float(tc) self.tag1 = float(tag1) self.tag2 = float(tag2) self.tag3 = float(tag3) self.tag4 = float(tag4) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.fy, self.alpha, self.gr, self.kbulk, self.d1, self.d2, self.ts, self.tr, self.n, self.x1, self.x2, self.x3, self.y1, self.y2, self.y3, self.kc, self.phi_m, self.ac, self.s_dratio, self.m, self.cd, self.tc, self.tag1, self.tag2, self.tag3, self.tag4] self.to_process(osi) class LeadRubberX(ElementBase): """ The LeadRubberX Element Class This command is used to construct a LeadRubberX bearing element object in three-dimension. The 3D continuum geometry of a lead rubber bearing is modeled as a 2-node, 12 DOF discrete element. It extends the formulation of ElastomericX by including strength degradation in lead rubber bearing due to heating of the lead-core. The LeadRubberX element requires only the geometric and material properties of an elastomeric bearing as arguments. The material models in six direction are formulated within the element from input arguments. The time-dependent values of mechanical properties (e.g., shear stiffness, buckling load capacity, temperature in the lead-core, yield strength) can also be recorded using the "parameters" recorder. """ op_type = 'LeadRubberX' def __init__(self, osi, ele_nodes, fy, alpha, gr, kbulk, d1, d2, ts, tr, n, x1, x2, x3, y1, y2, y3, kc, phi_m, ac, s_dratio, m, cd, tc, q_l, c_l, k_s, a_s, tag1, tag2, tag3, tag4, tag5): """ Initial method for LeadRubberX Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes fy: float Yield strength alpha: float Post-yield stiffness ratio gr: float Shear modulus of elastomeric bearing kbulk: float Bulk modulus of rubber d1: float Internal diameter d2: float Outer diameter (excluding cover thickness) ts: float Single steel shim layer thickness tr: float Single rubber layer thickness n: int Number of rubber layers x1: float Vector components in global coordinates defining local x-axis x2: float Vector components in global coordinates defining local x-axis x3: float Vector components in global coordinates defining local x-axis y1: float Vector components in global coordinates defining local y-axis y2: float Vector components in global coordinates defining local y-axis y3: float Vector components in global coordinates defining local y-axis kc: float Cavitation parameter (optional, default = 10.0) phi_m: float Damage parameter (optional, default = 0.5) ac: float Strength reduction parameter (optional, default = 1.0) s_dratio: float Shear distance from inode as a fraction of the element length (optional, default = 0.5) m: float Element mass (optional, default = 0.0) cd: float Viscous damping parameter (optional, default = 0.0) tc: float Cover thickness (optional, default = 0.0) q_l: float Density of lead (optional, default = 11200 kg/m3) c_l: float Specific heat of lead (optional, default = 130 n-m/kg oc) k_s: float Thermal conductivity of steel (optional, default = 50 w/m oc) a_s: float Thermal diffusivity of steel (optional, default = 1.41e-05 m2/s) tag1: int Object to include cavitation and post-cavitation (optional, default = 0) tag2: int Object to include buckling load variation (optional, default = 0) tag3: int Object to include horizontal stiffness variation (optional, default = 0) tag4: int Object to include vertical stiffness variation (optional, default = 0) tag5: int Object to include strength degradation in shear due to heating of lead core (optional, default = 0) Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> o3.element.LeadRubberX(osi, ele_nodes=ele_nodes, fy=1.0, alpha=1.0, gr=1.0, kbulk=1.0, d1=1.0, d2=1.0, ts=1.0, >>> tr=1.0, n=1, x1=1.0, x2=1.0, x3=1.0, y1=1.0, y2=1.0, y3=1.0, kc=1.0, phi_m=1.0, ac=1.0, >>> s_dratio=1.0, m=1.0, cd=1.0, tc=1.0, q_l=1.0, c_l=1.0, k_s=1.0, a_s=1.0, >>> tag1=1, tag2=1, tag3=1, tag4=1, tag5=1) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.fy = float(fy) self.alpha = float(alpha) self.gr = float(gr) self.kbulk = float(kbulk) self.d1 = float(d1) self.d2 = float(d2) self.ts = float(ts) self.tr = float(tr) self.n = int(n) self.x1 = float(x1) self.x2 = float(x2) self.x3 = float(x3) self.y1 = float(y1) self.y2 = float(y2) self.y3 = float(y3) self.kc = float(kc) self.phi_m = float(phi_m) self.ac = float(ac) self.s_dratio = float(s_dratio) self.m = float(m) self.cd = float(cd) self.tc = float(tc) self.q_l = float(q_l) self.c_l = float(c_l) self.k_s = float(k_s) self.a_s = float(a_s) self.tag1 = int(tag1) self.tag2 = int(tag2) self.tag3 = int(tag3) self.tag4 = int(tag4) self.tag5 = int(tag5) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.fy, self.alpha, self.gr, self.kbulk, self.d1, self.d2, self.ts, self.tr, self.n, self.x1, self.x2, self.x3, self.y1, self.y2, self.y3, self.kc, self.phi_m, self.ac, self.s_dratio, self.m, self.cd, self.tc, self.q_l, self.c_l, self.k_s, self.a_s, self.tag1, self.tag2, self.tag3, self.tag4, self.tag5] self.to_process(osi) class HDR(ElementBase): """ The HDR Element Class For 3D problem """ op_type = 'HDR' def __init__(self, osi, ele_nodes, gr, kbulk, d1, d2, ts, tr, n, a1, a2, a3, b1, b2, b3, c1, c2, c3, c4, x1, x2, x3, y1, y2, y3, kc, phi_m, ac, s_dratio, m, tc): """ Initial method for HDR Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes gr: float Shear modulus of elastomeric bearing kbulk: float Bulk modulus of rubber d1: float Internal diameter d2: float Outer diameter (excluding cover thickness) ts: float Single steel shim layer thickness tr: float Single rubber layer thickness n: int Number of rubber layers a1: float Parameters of the grant model a2: float Parameters of the grant model a3: float Parameters of the grant model b1: float Parameters of the grant model b2: float Parameters of the grant model b3: float Parameters of the grant model c1: float Parameters of the grant model c2: float Parameters of the grant model c3: float Parameters of the grant model c4: float Parameters of the grant model x1: float Vector components in global coordinates defining local x-axis x2: float Vector components in global coordinates defining local x-axis x3: float Vector components in global coordinates defining local x-axis y1: float Vector components in global coordinates defining local y-axis y2: float Vector components in global coordinates defining local y-axis y3: float Vector components in global coordinates defining local y-axis kc: float Cavitation parameter (optional, default = 10.0) phi_m: float Damage parameter (optional, default = 0.5) ac: float Strength reduction parameter (optional, default = 1.0) s_dratio: float Shear distance from inode as a fraction of the element length (optional, default = 0.5) m: float Element mass (optional, default = 0.0) tc: float Cover thickness (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> o3.element.HDR(osi, ele_nodes=ele_nodes, gr=1.0, kbulk=1.0, d1=1.0, d2=1.0, ts=1.0, tr=1.0, n=1, a1=1.0, a2=1.0, a3=1.0, b1=1.0, b2=1.0, b3=1.0, c1=1.0, c2=1.0, c3=1.0, c4=1.0, x1=1.0, x2=1.0, x3=1.0, y1=1.0, y2=1.0, y3=1.0, kc=1.0, phi_m=1.0, ac=1.0, s_dratio=1.0, m=1.0, tc=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.gr = float(gr) self.kbulk = float(kbulk) self.d1 = float(d1) self.d2 = float(d2) self.ts = float(ts) self.tr = float(tr) self.n = int(n) self.a1 = float(a1) self.a2 = float(a2) self.a3 = float(a3) self.b1 = float(b1) self.b2 = float(b2) self.b3 = float(b3) self.c1 = float(c1) self.c2 = float(c2) self.c3 = float(c3) self.c4 = float(c4) self.x1 = float(x1) self.x2 = float(x2) self.x3 = float(x3) self.y1 = float(y1) self.y2 = float(y2) self.y3 = float(y3) self.kc = float(kc) self.phi_m = float(phi_m) self.ac = float(ac) self.s_dratio = float(s_dratio) self.m = float(m) self.tc = float(tc) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.gr, self.kbulk, self.d1, self.d2, self.ts, self.tr, self.n, self.a1, self.a2, self.a3, self.b1, self.b2, self.b3, self.c1, self.c2, self.c3, self.c4, self.x1, self.x2, self.x3, self.y1, self.y2, self.y3, self.kc, self.phi_m, self.ac, self.s_dratio, self.m, self.tc] self.to_process(osi) class RJWatsonEqsBearing2D(ElementBase): """ The RJWatsonEqsBearing2D Element Class This command is used to construct a RJWatsonEqsBearing element object, which is defined by two nodes. The iNode represents the masonry plate and the jNode represents the sliding surface plate. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) friction properties (with post-yield stiffening due to the mass-energy-regulator (MER) springs) for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. To capture the uplift behavior of the bearing, the user-specified UniaxialMaterial in the axial direction is modified for no-tension behavior. By default (sDratio = 1.0) P-Delta moments are entirely transferred to the sliding surface (jNode). It is important to note that rotations of the sliding surface (rotations at the jNode) affect the shear behavior of the bearing. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a two-dimensional problem """ op_type = 'RJWatsonEqsBearing' def __init__(self, osi, ele_nodes, frn_mdl, k_init, p_mat=None, vy_mat=None, mz_mat=None, do_rayleigh=False, max_iter: int=None, tol: float=None, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for RJWatsonEqsBearing2D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes frn_mdl: obj Object associated with previously-defined frictionmodel k_init: float Initial stiffness of sliding friction component in local shear direction p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction vy_mat: obj, optional Object associated with previously-defined uniaxial_material in shear direction along local y-axis (mer spring behavior not including friction) mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) max_iter: int, optional Maximum number of iterations to undertake to satisfy element equilibrium (optional, default = 20) tol: float, optional Convergence tolerance to satisfy element equilibrium (optional, default = 1e-8) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [0, 1]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> p_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> vy_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> mz_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> frn_mdl = o3.friction_model.Coulomb(osi, mu=1.0) >>> o3.element.RJWatsonEqsBearing2D(osi, ele_nodes=ele_nodes, frn_mdl=frn_mdl, k_init=1.0, p_mat=p_mat, vy_mat=vy_mat, >>> mz_mat=mz_mat, do_rayleigh=False, max_iter=1, tol=1.0, orient=None, mass=1.0, >>> shear_dist=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.frn_mdl = frn_mdl self.k_init = float(k_init) self.p_mat = p_mat self.vy_mat = vy_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh if max_iter is None: self.max_iter = None else: self.max_iter = int(max_iter) if tol is None: self.tol = None else: self.tol = float(tol) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.frn_mdl.tag, self.k_init] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 'vy_mat') is not None: self._parameters += ['-Vy', self.vy_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'max_iter') is not None: self._parameters += ['-iter', self.max_iter] if getattr(self, 'tol') is not None: if getattr(self, 'max_iter') is None: raise ValueError('Cannot set: tol and not: max_iter') self._parameters += [self.tol] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class RJWatsonEqsBearing3D(ElementBase): """ The RJWatsonEqsBearing3D Element Class This command is used to construct a RJWatsonEqsBearing element object, which is defined by two nodes. The iNode represents the masonry plate and the jNode represents the sliding surface plate. The element can have zero length or the appropriate bearing height. The bearing has unidirectional (2D) or coupled (3D) friction properties (with post-yield stiffening due to the mass-energy-regulator (MER) springs) for the shear deformations, and force-deformation behaviors defined by UniaxialMaterials in the remaining two (2D) or four (3D) directions. To capture the uplift behavior of the bearing, the user-specified UniaxialMaterial in the axial direction is modified for no-tension behavior. By default (sDratio = 1.0) P-Delta moments are entirely transferred to the sliding surface (jNode). It is important to note that rotations of the sliding surface (rotations at the jNode) affect the shear behavior of the bearing. To avoid the introduction of artificial viscous damping in the isolation system (sometimes referred to as "damping leakage in the isolation system"), the bearing element does not contribute to the Rayleigh damping by default. If the element has non-zero length, the local x-axis is determined from the nodal geometry unless the optional x-axis vector is specified in which case the nodal geometry is ignored and the user-defined orientation is utilized. For a three-dimensional problem """ op_type = 'RJWatsonEqsBearing' def __init__(self, osi, ele_nodes, frn_mdl, k_init, p_mat=None, vy_mat=None, vz_mat=None, t_mat=None, my_mat=None, mz_mat=None, do_rayleigh=False, max_iter: int=None, tol: float=None, orient=None, mass: float=None, shear_dist: float=None): """ Initial method for RJWatsonEqsBearing3D Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes frn_mdl: obj Object associated with previously-defined frictionmodel k_init: float Initial stiffness of sliding friction component in local shear direction p_mat: obj, optional Object associated with previously-defined uniaxial_material in axial direction vy_mat: obj, optional Object associated with previously-defined uniaxial_material in shear direction along local y-axis (mer spring behavior not including friction) vz_mat: obj, optional Object associated with previously-defined uniaxial_material in shear direction along local z-axis (mer spring behavior not including friction) t_mat: obj, optional Object associated with previously-defined uniaxial_material in torsional direction my_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local y-axis mz_mat: obj, optional Object associated with previously-defined uniaxial_material in moment direction around local z-axis do_rayleigh: bool To include rayleigh damping from the bearing (optional, default = no rayleigh damping contribution) max_iter: int, optional Maximum number of iterations to undertake to satisfy element equilibrium (optional, default = 20) tol: float, optional Convergence tolerance to satisfy element equilibrium (optional, default = 1e-8) orient: None, optional mass: float, optional Element mass (optional, default = 0.0) shear_dist: float, optional Shear distance from inode as a fraction of the element length (optional, default = 0.0) Examples -------- >>> import o3seespy as o3 >>> osi = o3.OpenSeesInstance(ndm=3, ndf=6) >>> coords = [[0, 0, 0], [0, 1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(2)] >>> p_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> vy_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> vz_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> t_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> my_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> mz_mat = o3.uniaxial_material.Elastic(osi, 1, 1) >>> orient_vals = [1, 0, 0] >>> frn_mdl = o3.friction_model.Coulomb(osi, mu=1.0) >>> o3.element.RJWatsonEqsBearing3D(osi, ele_nodes=ele_nodes, frn_mdl=frn_mdl, k_init=1.0, p_mat=p_mat, >>> vy_mat=vy_mat, vz_mat=vz_mat, t_mat=t_mat, my_mat=my_mat, mz_mat=mz_mat, >>> do_rayleigh=False, max_iter=1, tol=1.0, orient=orient_vals, mass=1.0, shear_dist=1.0) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.frn_mdl = frn_mdl self.k_init = float(k_init) self.p_mat = p_mat self.vy_mat = vy_mat self.vz_mat = vz_mat self.t_mat = t_mat self.my_mat = my_mat self.mz_mat = mz_mat self.do_rayleigh = do_rayleigh if max_iter is None: self.max_iter = None else: self.max_iter = int(max_iter) if tol is None: self.tol = None else: self.tol = float(tol) self.orient = orient if mass is None: self.mass = None else: self.mass = float(mass) if shear_dist is None: self.shear_dist = None else: self.shear_dist = float(shear_dist) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.frn_mdl.tag, self.k_init] if getattr(self, 'p_mat') is not None: self._parameters += ['-P', self.p_mat.tag] if getattr(self, 'vy_mat') is not None: self._parameters += ['-Vy', self.vy_mat.tag] if getattr(self, 'vz_mat') is not None: self._parameters += ['-Vz', self.vz_mat.tag] if getattr(self, 't_mat') is not None: self._parameters += ['-T', self.t_mat.tag] if getattr(self, 'my_mat') is not None: self._parameters += ['-My', self.my_mat.tag] if getattr(self, 'mz_mat') is not None: self._parameters += ['-Mz', self.mz_mat.tag] if getattr(self, 'do_rayleigh'): self._parameters += ['-doRayleigh'] if getattr(self, 'max_iter') is not None: self._parameters += ['-iter', self.max_iter] if getattr(self, 'tol') is not None: if getattr(self, 'max_iter') is None: raise ValueError('Cannot set: tol and not: max_iter') self._parameters += [self.tol] if getattr(self, 'orient') is not None: self._parameters += ['-orient', *self.orient] if getattr(self, 'mass') is not None: self._parameters += ['-mass', self.mass] if getattr(self, 'shear_dist') is not None: self._parameters += ['-shearDist', self.shear_dist] self.to_process(osi) class FPBearingPTV(ElementBase): """ The FPBearingPTV Element Class The FPBearingPTV command creates a single Friction Pendulum bearing element, which is capable of accounting for the changes in the coefficient of friction at the sliding surface with instantaneous values of the sliding velocity, axial pressure and temperature at the sliding surface. The constitutive modelling is similar to the existing singleFPBearing element, otherwise. The FPBearingPTV element has been verified and validated in accordance with the ASME guidelines, details of which are presented in Chapter 4 of Kumar et al. (2015a). """ op_type = 'FPBearingPTV' def __init__(self, osi, ele_nodes, mu_ref, is_pressure_dependent, p_ref, is_temperature_dependent, diffusivity, conductivity, is_velocity_dependent, rate_parameter, reffective_fp, radius__contact, k_initial, the_material_a, the_material_b, the_material_c, the_material_d, x1, x2, x3, y1, y2, y3, shear_dist, do_rayleigh, mass, max_iter, tol, unit): """ Initial method for FPBearingPTV Parameters ---------- osi: o3seespy.OpenSeesInstance ele_nodes: list A list of two element nodes mu_ref: float Reference coefficient of friction is_pressure_dependent: int 1 if the coefficient of friction is a function of instantaneous axial pressure p_ref: float Reference axial pressure (the bearing pressure under static loads) is_temperature_dependent: int 1 if the coefficient of friction is a function of instantaneous temperature at the sliding surface diffusivity: float Thermal diffusivity of steel conductivity: float Thermal conductivity of steel is_velocity_dependent: int 1 if the coefficient of friction is a function of instantaneous velocity at the sliding surface rate_parameter: float The exponent that determines the shape of the coefficient of friction vs. sliding velocity curve reffective_fp: float Effective radius of curvature of the sliding surface of the fpbearing radius__contact: float Radius of contact area at the sliding surface k_initial: float Lateral stiffness of the sliding bearing before sliding begins the_material_a: int Object for the uniaxial material in the axial direction the_material_b: int Object for the uniaxial material in the torsional direction the_material_c: int Object for the uniaxial material for rocking about local y axis the_material_d: int Object for the uniaxial material for rocking about local z axis x1: float Vector components to define local x axis x2: float Vector components to define local x axis x3: float Vector components to define local x axis y1: float Vector components to define local y axis y2: float Vector components to define local y axis y3: float Vector components to define local y axis shear_dist: float Shear distance from inode as a fraction of the length of the element do_rayleigh: int To include rayleigh damping from the bearing mass: float Element mass max_iter: int Maximum number of iterations to satisfy the equilibrium of element tol: float Convergence tolerance to satisfy the equilibrium of the element unit: int Object to identify the unit from the list below. * ``1``: n, m, s, c * ``2``: kn, m, s, c * ``3``: n, mm, s, c * ``4``: kn, mm, s, c * ``5``: lb, in, s, c * ``6``: kip, in, s, c * ``7``: lb, ft, s, c * ``8``: kip, ft, s, c Examples -------- >>> import o3seespy as o3 >>> # Example is currently not working >>> osi = o3.OpenSeesInstance(ndm=2) >>> coords = [[0, 0], [1, 0]] >>> ele_nodes = [o3.node.Node(osi, *coords[x]) for x in range(len(coords))] >>> o3.element.FPBearingPTV(osi, ele_nodes=ele_nodes, mu_ref=1.0, is_pressure_dependent=1, p_ref=1.0, is_temperature_dependent=1, diffusivity=1.0, conductivity=1.0, is_velocity_dependent=1, rate_parameter=1.0, reffective_fp=1.0, radius__contact=1.0, k_initial=1.0, the_material_a=1, the_material_b=1, the_material_c=1, the_material_d=1, x1=1.0, x2=1.0, x3=1.0, y1=1.0, y2=1.0, y3=1.0, shear_dist=1.0, do_rayleigh=1, mass=1.0, max_iter=1, tol=1.0, unit=1) """ self.osi = osi self.ele_node_tags = [x.tag for x in ele_nodes] self.ele_nodes = ele_nodes self.mu_ref = float(mu_ref) self.is_pressure_dependent = int(is_pressure_dependent) self.p_ref = float(p_ref) self.is_temperature_dependent = int(is_temperature_dependent) self.diffusivity = float(diffusivity) self.conductivity = float(conductivity) self.is_velocity_dependent = int(is_velocity_dependent) self.rate_parameter = float(rate_parameter) self.reffective_fp = float(reffective_fp) self.radius__contact = float(radius__contact) self.k_initial = float(k_initial) self.the_material_a = int(the_material_a) self.the_material_b = int(the_material_b) self.the_material_c = int(the_material_c) self.the_material_d = int(the_material_d) self.x1 = float(x1) self.x2 = float(x2) self.x3 = float(x3) self.y1 = float(y1) self.y2 = float(y2) self.y3 = float(y3) self.shear_dist = float(shear_dist) self.do_rayleigh = int(do_rayleigh) self.mass = float(mass) self.max_iter = int(max_iter) self.tol = float(tol) self.unit = int(unit) osi.n_ele += 1 self._tag = osi.n_ele self._parameters = [self.op_type, self._tag, *self.ele_node_tags, self.mu_ref, self.is_pressure_dependent, self.p_ref, self.is_temperature_dependent, self.diffusivity, self.conductivity, self.is_velocity_dependent, self.rate_parameter, self.reffective_fp, self.radius__contact, self.k_initial, self.the_material_a, self.the_material_b, self.the_material_c, self.the_material_d, self.x1, self.x2, self.x3, self.y1, self.y2, self.y3, self.shear_dist, self.do_rayleigh, self.mass, self.max_iter, self.tol, self.unit] self.to_process(osi)

45.677833

521

0.614492

15,078

110,449

4.379626

0.04165

0.008299

0.024411

0.019489

0.881353

0.8562

0.841708

0.834605

0.824278

0.817584

0

0.023503

0.291583

110,449

2,417

522

45.696731

0.820472

0.538158

0

0.821277

0

0.05058

0.00431

0

1

0.021277

false

0

0.001064

0

0.064894

0

null

0

1

0

1

0

null

0

7

172e5a33710eedfb1d0a22b208cf0c050b392544

1,757

py

Python

src/nostradamus/metrics.py

nostradamus-ai/nostradamus

691f433d31a125d5363bb061cac43cc097080ae0

[ "MIT" ]

9

2019-11-08T20:19:53.000Z

2022-03-25T21:55:19.000Z

src/nostradamus/metrics.py

nostradamus-ai/nostradamus

691f433d31a125d5363bb061cac43cc097080ae0

[ "MIT" ]

null

src/nostradamus/metrics.py

nostradamus-ai/nostradamus

691f433d31a125d5363bb061cac43cc097080ae0

[ "MIT" ]

1

2020-09-29T16:18:04.000Z

import logging import tornado.web from prometheus_client import generate_latest from prometheus_client.core import (REGISTRY, GaugeMetricFamily, CounterMetricFamily) class HealthzUpHandler(tornado.web.RequestHandler): """ Tornado Handler for /healthz/metrics endpoint """ def __init__(self, application, request, **kwargs): super().__init__(application, request, **kwargs) self.logger = logging.getLogger(type(self).__name__) self.logger.setLevel(logging.DEBUG) def initialize(self, ref_object): self.obj = ref_object def get(self): value = self.obj.ping() self.write(value) def on_finish(self): self.obj = None class HealthzReadyHandler(tornado.web.RequestHandler): """ Tornado Handler for /healthz/metrics endpoint """ def __init__(self, application, request, **kwargs): super().__init__(application, request, **kwargs) self.logger = logging.getLogger(type(self).__name__) self.logger.setLevel(logging.DEBUG) def initialize(self, ref_object): self.obj = ref_object def get(self): value = self.obj.ping() self.write(value) def on_finish(self): self.obj = None class HealthzMetricHandler(tornado.web.RequestHandler): """ Tornado Handler for /healthz/metrics endpoint """ def __init__(self, application, request, **kwargs): super().__init__(application, request, **kwargs) self.logger = logging.getLogger(type(self).__name__) self.logger.setLevel(logging.DEBUG) def initialize(self, ref_object): self.obj = ref_object def get(self): value = self.obj.ping() self.write(value) def on_finish(self): self.obj = None

29.779661

64

0.672738

199

1,757

5.698492

0.236181

0.055556

0.126984

0.082011

0.820988

0

0.212863

1,757

59

65

29.779661

0.819957

0.079112

0

0.804878

1

0

1

0.292683

false

0

0.097561

0

0.463415

0

null

0

1

0

1

0

null

0

1

0

9

176c7314899bc55a28262cc152e512492fb7a1ee

153

py

Python

ai-engineer/course0_20190911/basic_syntax/1_Import.py

linksdl/meta-project-artificial_intelligence_projects

3abe0dc59aa891717a661b3ad1e987c14536bd62

[ "Apache-2.0" ]

null

ai-engineer/course0_20190911/basic_syntax/1_Import.py

linksdl/meta-project-artificial_intelligence_projects

3abe0dc59aa891717a661b3ad1e987c14536bd62

[ "Apache-2.0" ]

null

ai-engineer/course0_20190911/basic_syntax/1_Import.py

linksdl/meta-project-artificial_intelligence_projects

3abe0dc59aa891717a661b3ad1e987c14536bd62

[ "Apache-2.0" ]

null

import time print(time.localtime()) import time as t print(t.localtime()) from time import time print(time()) from time import * print(localtime())

10.928571

23

0.72549

23

153

4.826087

0.304348

0.27027

0.342342

0

0.150327

153

13

24

11.769231

0.853846

0

1

0

true

0

0.5

0

0.5

1

0

null

1

0

null

0

1

0

1

0

1

0

7

178ac4d4df20b19a75f846ec4af786faa396a73a

744,474

py

Python

pyboto3/ssm.py

gehad-shaat/pyboto3

4a0c2851a8bc04fb1c71c36086f7bb257e48181d

[ "MIT" ]

91

2016-12-31T11:38:37.000Z

2021-09-16T19:33:23.000Z

pyboto3/ssm.py

gehad-shaat/pyboto3

4a0c2851a8bc04fb1c71c36086f7bb257e48181d

[ "MIT" ]

7

2017-01-02T18:54:23.000Z

2020-08-11T13:54:02.000Z

pyboto3/ssm.py

gehad-shaat/pyboto3

4a0c2851a8bc04fb1c71c36086f7bb257e48181d

[ "MIT" ]

26

2016-12-31T13:11:00.000Z

2022-03-03T21:01:12.000Z

''' The MIT License (MIT) Copyright (c) 2016 WavyCloud Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ''' def add_tags_to_resource(ResourceType=None, ResourceId=None, Tags=None): """ Adds or overwrites one or more tags for the specified resource. Tags are metadata that you can assign to your documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. Each tag consists of a key and an optional value, both of which you define. For example, you could define a set of tags for your account\'s managed instances that helps you track each instance\'s owner and stack level. For example: Key=Owner and Value=DbAdmin, SysAdmin, or Dev. Or Key=Stack and Value=Production, Pre-Production, or Test. Each resource can have a maximum of 50 tags. We recommend that you devise a set of tag keys that meets your needs for each resource type. Using a consistent set of tag keys makes it easier for you to manage your resources. You can search and filter the resources based on the tags you add. Tags don\'t have any semantic meaning to and are interpreted strictly as a string of characters. For more information about using tags with EC2 instances, see Tagging your Amazon EC2 resources in the Amazon EC2 User Guide . See also: AWS API Documentation Exceptions :example: response = client.add_tags_to_resource( ResourceType='Document'|'ManagedInstance'|'MaintenanceWindow'|'Parameter'|'PatchBaseline'|'OpsItem', ResourceId='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type ResourceType: string :param ResourceType: [REQUIRED]\nSpecifies the type of resource you are tagging.\n\nNote\nThe ManagedInstance type for this API action is for on-premises managed instances. You must specify the name of the managed instance in the following format: mi-ID_number. For example, mi-1a2b3c4d5e6f.\n\n :type ResourceId: string :param ResourceId: [REQUIRED]\nThe resource ID you want to tag.\nUse the ID of the resource. Here are some examples:\nManagedInstance: mi-012345abcde\nMaintenanceWindow: mw-012345abcde\nPatchBaseline: pb-012345abcde\nFor the Document and Parameter values, use the name of the resource.\n\nNote\nThe ManagedInstance type for this API action is only for on-premises managed instances. You must specify the name of the managed instance in the following format: mi-ID_number. For example, mi-1a2b3c4d5e6f.\n\n :type Tags: list :param Tags: [REQUIRED]\nOne or more tags. The value parameter is required, but if you don\'t want the tag to have a value, specify the parameter with no value, and we set the value to an empty string.\n\nWarning\nDo not enter personally identifiable information in this field.\n\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InvalidResourceType SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.TooManyTagsError SSM.Client.exceptions.TooManyUpdates :return: {} :returns: (dict) -- """ pass def can_paginate(operation_name=None): """ Check if an operation can be paginated. :type operation_name: string :param operation_name: The operation name. This is the same name\nas the method name on the client. For example, if the\nmethod name is create_foo, and you\'d normally invoke the\noperation as client.create_foo(**kwargs), if the\ncreate_foo operation can be paginated, you can use the\ncall client.get_paginator('create_foo'). """ pass def cancel_command(CommandId=None, InstanceIds=None): """ Attempts to cancel the command specified by the Command ID. There is no guarantee that the command will be terminated and the underlying process stopped. See also: AWS API Documentation Exceptions :example: response = client.cancel_command( CommandId='string', InstanceIds=[ 'string', ] ) :type CommandId: string :param CommandId: [REQUIRED]\nThe ID of the command you want to cancel.\n :type InstanceIds: list :param InstanceIds: (Optional) A list of instance IDs on which you want to cancel the command. If not provided, the command is canceled on every instance on which it was requested.\n\n(string) --\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Whether or not the command was successfully canceled. There is no guarantee that a request can be canceled. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidCommandId SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.DuplicateInstanceId :return: {} :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidCommandId SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.DuplicateInstanceId """ pass def cancel_maintenance_window_execution(WindowExecutionId=None): """ Stops a maintenance window execution that is already in progress and cancels any tasks in the window that have not already starting running. (Tasks already in progress will continue to completion.) See also: AWS API Documentation Exceptions :example: response = client.cancel_maintenance_window_execution( WindowExecutionId='string' ) :type WindowExecutionId: string :param WindowExecutionId: [REQUIRED]\nThe ID of the maintenance window execution to stop.\n :rtype: dict ReturnsResponse Syntax{ 'WindowExecutionId': 'string' } Response Structure (dict) -- WindowExecutionId (string) --The ID of the maintenance window execution that has been stopped. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.DoesNotExistException :return: { 'WindowExecutionId': 'string' } """ pass def create_activation(Description=None, DefaultInstanceName=None, IamRole=None, RegistrationLimit=None, ExpirationDate=None, Tags=None): """ Generates an activation code and activation ID you can use to register your on-premises server or virtual machine (VM) with Systems Manager. Registering these machines with Systems Manager makes it possible to manage them using Systems Manager capabilities. You use the activation code and ID when installing SSM Agent on machines in your hybrid environment. For more information about requirements for managing on-premises instances and VMs using Systems Manager, see Setting up AWS Systems Manager for hybrid environments in the AWS Systems Manager User Guide . See also: AWS API Documentation Exceptions :example: response = client.create_activation( Description='string', DefaultInstanceName='string', IamRole='string', RegistrationLimit=123, ExpirationDate=datetime(2015, 1, 1), Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type Description: string :param Description: A user-defined description of the resource that you want to register with Systems Manager.\n\nWarning\nDo not enter personally identifiable information in this field.\n\n :type DefaultInstanceName: string :param DefaultInstanceName: The name of the registered, managed instance as it will appear in the Systems Manager console or when you use the AWS command line tools to list Systems Manager resources.\n\nWarning\nDo not enter personally identifiable information in this field.\n\n :type IamRole: string :param IamRole: [REQUIRED]\nThe Amazon Identity and Access Management (IAM) role that you want to assign to the managed instance. This IAM role must provide AssumeRole permissions for the Systems Manager service principal ssm.amazonaws.com . For more information, see Create an IAM service role for a hybrid environment in the AWS Systems Manager User Guide .\n :type RegistrationLimit: integer :param RegistrationLimit: Specify the maximum number of managed instances you want to register. The default value is 1 instance. :type ExpirationDate: datetime :param ExpirationDate: The date by which this activation request should expire. The default value is 24 hours. :type Tags: list :param Tags: Optional metadata that you assign to a resource. Tags enable you to categorize a resource in different ways, such as by purpose, owner, or environment. For example, you might want to tag an activation to identify which servers or virtual machines (VMs) in your on-premises environment you intend to activate. In this case, you could specify the following key name/value pairs:\n\nKey=OS,Value=Windows\nKey=Environment,Value=Production\n\n\nWarning\nWhen you install SSM Agent on your on-premises servers and VMs, you specify an activation ID and code. When you specify the activation ID and code, tags assigned to the activation are automatically applied to the on-premises servers or VMs.\n\nYou can\'t add tags to or delete tags from an existing activation. You can tag your on-premises servers and VMs after they connect to Systems Manager for the first time and are assigned a managed instance ID. This means they are listed in the AWS Systems Manager console with an ID that is prefixed with 'mi-'. For information about how to add tags to your managed instances, see AddTagsToResource . For information about how to remove tags from your managed instances, see RemoveTagsFromResource .\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'ActivationId': 'string', 'ActivationCode': 'string' } Response Structure (dict) -- ActivationId (string) -- The ID number generated by the system when it processed the activation. The activation ID functions like a user name. ActivationCode (string) -- The code the system generates when it processes the activation. The activation code functions like a password to validate the activation ID. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'ActivationId': 'string', 'ActivationCode': 'string' } :returns: SSM.Client.exceptions.InternalServerError """ pass def create_association(Name=None, DocumentVersion=None, InstanceId=None, Parameters=None, Targets=None, ScheduleExpression=None, OutputLocation=None, AssociationName=None, AutomationTargetParameterName=None, MaxErrors=None, MaxConcurrency=None, ComplianceSeverity=None, SyncCompliance=None): """ Associates the specified Systems Manager document with the specified instances or targets. When you associate a document with one or more instances, SSM Agent running on the instance processes the document and configures the instance as specified. If you associate a document with an instance that already has an associated document, the system returns the AssociationAlreadyExists exception. See also: AWS API Documentation Exceptions :example: response = client.create_association( Name='string', DocumentVersion='string', InstanceId='string', Parameters={ 'string': [ 'string', ] }, Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], ScheduleExpression='string', OutputLocation={ 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, AssociationName='string', AutomationTargetParameterName='string', MaxErrors='string', MaxConcurrency='string', ComplianceSeverity='CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', SyncCompliance='AUTO'|'MANUAL' ) :type Name: string :param Name: [REQUIRED]\nThe name of the SSM document that contains the configuration information for the instance. You can specify Command or Automation documents.\nYou can specify AWS-predefined documents, documents you created, or a document that is shared with you from another account.\nFor SSM documents that are shared with you from other AWS accounts, you must specify the complete SSM document ARN, in the following format:\n\n``arn:partition :ssm:region :account-id :document/document-name ``\nFor example:\n\narn:aws:ssm:us-east-2:12345678912:document/My-Shared-Document\nFor AWS-predefined documents and SSM documents you created in your account, you only need to specify the document name. For example, AWS-ApplyPatchBaseline or My-Document .\n :type DocumentVersion: string :param DocumentVersion: The document version you want to associate with the target(s). Can be a specific version or the default version. :type InstanceId: string :param InstanceId: The instance ID.\n\nNote\nInstanceId has been deprecated. To specify an instance ID for an association, use the Targets parameter. Requests that include the parameter InstanceID with SSM documents that use schema version 2.0 or later will fail. In addition, if you use the parameter InstanceId , you cannot use the parameters AssociationName , DocumentVersion , MaxErrors , MaxConcurrency , OutputLocation , or ScheduleExpression . To use these parameters, you must use the Targets parameter.\n\n :type Parameters: dict :param Parameters: The parameters for the runtime configuration of the document.\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n :type Targets: list :param Targets: The targets for the association. You can target instances by using tags, AWS Resource Groups, all instances in an AWS account, or individual instance IDs. For more information about choosing targets for an association, see Using targets and rate controls with State Manager associations in the AWS Systems Manager User Guide .\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type ScheduleExpression: string :param ScheduleExpression: A cron expression when the association will be applied to the target(s). :type OutputLocation: dict :param OutputLocation: An S3 bucket where you want to store the output details of the request.\n\nS3Location (dict) --An S3 bucket where you want to store the results of this request.\n\nOutputS3Region (string) --(Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket.\n\nOutputS3BucketName (string) --The name of the S3 bucket.\n\nOutputS3KeyPrefix (string) --The S3 bucket subfolder.\n\n\n\n\n :type AssociationName: string :param AssociationName: Specify a descriptive name for the association. :type AutomationTargetParameterName: string :param AutomationTargetParameterName: Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. :type MaxErrors: string :param MaxErrors: The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received.\nExecutions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time.\n :type MaxConcurrency: string :param MaxConcurrency: The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time.\nIf a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency.\n :type ComplianceSeverity: string :param ComplianceSeverity: The severity level to assign to the association. :type SyncCompliance: string :param SyncCompliance: The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT .\nIn MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action.\nBy default, all associations use AUTO mode.\n :rtype: dict ReturnsResponse Syntax { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } Response Structure (dict) -- AssociationDescription (dict) -- Information about the association. Name (string) -- The name of the Systems Manager document. InstanceId (string) -- The ID of the instance. AssociationVersion (string) -- The association version. Date (datetime) -- The date when the association was made. LastUpdateAssociationDate (datetime) -- The date when the association was last updated. Status (dict) -- The association status. Date (datetime) -- The date when the status changed. Name (string) -- The status. Message (string) -- The reason for the status. AdditionalInfo (string) -- A user-defined string. Overview (dict) -- Information about the association. Status (string) -- The status of the association. Status can be: Pending, Success, or Failed. DetailedStatus (string) -- A detailed status of the association. AssociationStatusAggregatedCount (dict) -- Returns the number of targets for the association status. For example, if you created an association with two instances, and one of them was successful, this would return the count of instances by status. (string) -- (integer) -- DocumentVersion (string) -- The document version. AutomationTargetParameterName (string) -- Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. Parameters (dict) -- A description of the parameters for a document. (string) -- (list) -- (string) -- AssociationId (string) -- The association ID. Targets (list) -- The instances targeted by the request. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- ScheduleExpression (string) -- A cron expression that specifies a schedule when the association runs. OutputLocation (dict) -- An S3 bucket where you want to store the output details of the request. S3Location (dict) -- An S3 bucket where you want to store the results of this request. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) -- The name of the S3 bucket. OutputS3KeyPrefix (string) -- The S3 bucket subfolder. LastExecutionDate (datetime) -- The date on which the association was last run. LastSuccessfulExecutionDate (datetime) -- The last date on which the association was successfully run. AssociationName (string) -- The association name. MaxErrors (string) -- The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received. Executions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time. MaxConcurrency (string) -- The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time. If a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency. ComplianceSeverity (string) -- The severity level that is assigned to the association. SyncCompliance (string) -- The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT . In MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action. By default, all associations use AUTO mode. Exceptions SSM.Client.exceptions.AssociationAlreadyExists SSM.Client.exceptions.AssociationLimitExceeded SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.UnsupportedPlatformType SSM.Client.exceptions.InvalidOutputLocation SSM.Client.exceptions.InvalidParameters SSM.Client.exceptions.InvalidTarget SSM.Client.exceptions.InvalidSchedule :return: { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } :returns: (string) -- (integer) -- """ pass def create_association_batch(Entries=None): """ Associates the specified Systems Manager document with the specified instances or targets. When you associate a document with one or more instances using instance IDs or tags, SSM Agent running on the instance processes the document and configures the instance as specified. If you associate a document with an instance that already has an associated document, the system returns the AssociationAlreadyExists exception. See also: AWS API Documentation Exceptions :example: response = client.create_association_batch( Entries=[ { 'Name': 'string', 'InstanceId': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AutomationTargetParameterName': 'string', 'DocumentVersion': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' }, ] ) :type Entries: list :param Entries: [REQUIRED]\nOne or more associations.\n\n(dict) --Describes the association of a Systems Manager SSM document and an instance.\n\nName (string) -- [REQUIRED]The name of the SSM document that contains the configuration information for the instance. You can specify Command or Automation documents.\nYou can specify AWS-predefined documents, documents you created, or a document that is shared with you from another account.\nFor SSM documents that are shared with you from other AWS accounts, you must specify the complete SSM document ARN, in the following format:\n\n``arn:aws:ssm:region :account-id :document/document-name ``\nFor example:\n\narn:aws:ssm:us-east-2:12345678912:document/My-Shared-Document\nFor AWS-predefined documents and SSM documents you created in your account, you only need to specify the document name. For example, AWS-ApplyPatchBaseline or My-Document .\n\nInstanceId (string) --The ID of the instance.\n\nParameters (dict) --A description of the parameters for a document.\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n\nAutomationTargetParameterName (string) --Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls.\n\nDocumentVersion (string) --The document version.\n\nTargets (list) --The instances targeted by the request.\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n\nScheduleExpression (string) --A cron expression that specifies a schedule when the association runs.\n\nOutputLocation (dict) --An S3 bucket where you want to store the results of this request.\n\nS3Location (dict) --An S3 bucket where you want to store the results of this request.\n\nOutputS3Region (string) --(Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket.\n\nOutputS3BucketName (string) --The name of the S3 bucket.\n\nOutputS3KeyPrefix (string) --The S3 bucket subfolder.\n\n\n\n\n\nAssociationName (string) --Specify a descriptive name for the association.\n\nMaxErrors (string) --The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received.\nExecutions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time.\n\nMaxConcurrency (string) --The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time.\nIf a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency.\n\nComplianceSeverity (string) --The severity level to assign to the association.\n\nSyncCompliance (string) --The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT .\nIn MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action.\nBy default, all associations use AUTO mode.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax{ 'Successful': [ { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' }, ], 'Failed': [ { 'Entry': { 'Name': 'string', 'InstanceId': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AutomationTargetParameterName': 'string', 'DocumentVersion': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' }, 'Message': 'string', 'Fault': 'Client'|'Server'|'Unknown' }, ] } Response Structure (dict) -- Successful (list) --Information about the associations that succeeded. (dict) --Describes the parameters for a document. Name (string) --The name of the Systems Manager document. InstanceId (string) --The ID of the instance. AssociationVersion (string) --The association version. Date (datetime) --The date when the association was made. LastUpdateAssociationDate (datetime) --The date when the association was last updated. Status (dict) --The association status. Date (datetime) --The date when the status changed. Name (string) --The status. Message (string) --The reason for the status. AdditionalInfo (string) --A user-defined string. Overview (dict) --Information about the association. Status (string) --The status of the association. Status can be: Pending, Success, or Failed. DetailedStatus (string) --A detailed status of the association. AssociationStatusAggregatedCount (dict) --Returns the number of targets for the association status. For example, if you created an association with two instances, and one of them was successful, this would return the count of instances by status. (string) -- (integer) -- DocumentVersion (string) --The document version. AutomationTargetParameterName (string) --Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. Parameters (dict) --A description of the parameters for a document. (string) -- (list) -- (string) -- AssociationId (string) --The association ID. Targets (list) --The instances targeted by the request. (dict) --An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) --User-defined criteria for sending commands that target instances that meet the criteria. Values (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- ScheduleExpression (string) --A cron expression that specifies a schedule when the association runs. OutputLocation (dict) --An S3 bucket where you want to store the output details of the request. S3Location (dict) --An S3 bucket where you want to store the results of this request. OutputS3Region (string) --(Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) --The name of the S3 bucket. OutputS3KeyPrefix (string) --The S3 bucket subfolder. LastExecutionDate (datetime) --The date on which the association was last run. LastSuccessfulExecutionDate (datetime) --The last date on which the association was successfully run. AssociationName (string) --The association name. MaxErrors (string) --The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received. Executions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time. MaxConcurrency (string) --The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time. If a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency. ComplianceSeverity (string) --The severity level that is assigned to the association. SyncCompliance (string) --The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT . In MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action. By default, all associations use AUTO mode. Failed (list) --Information about the associations that failed. (dict) --Describes a failed association. Entry (dict) --The association. Name (string) --The name of the SSM document that contains the configuration information for the instance. You can specify Command or Automation documents. You can specify AWS-predefined documents, documents you created, or a document that is shared with you from another account. For SSM documents that are shared with you from other AWS accounts, you must specify the complete SSM document ARN, in the following format: ``arn:aws:ssm:region :account-id :document/document-name `` For example: arn:aws:ssm:us-east-2:12345678912:document/My-Shared-Document For AWS-predefined documents and SSM documents you created in your account, you only need to specify the document name. For example, AWS-ApplyPatchBaseline or My-Document . InstanceId (string) --The ID of the instance. Parameters (dict) --A description of the parameters for a document. (string) -- (list) -- (string) -- AutomationTargetParameterName (string) --Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. DocumentVersion (string) --The document version. Targets (list) --The instances targeted by the request. (dict) --An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) --User-defined criteria for sending commands that target instances that meet the criteria. Values (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- ScheduleExpression (string) --A cron expression that specifies a schedule when the association runs. OutputLocation (dict) --An S3 bucket where you want to store the results of this request. S3Location (dict) --An S3 bucket where you want to store the results of this request. OutputS3Region (string) --(Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) --The name of the S3 bucket. OutputS3KeyPrefix (string) --The S3 bucket subfolder. AssociationName (string) --Specify a descriptive name for the association. MaxErrors (string) --The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received. Executions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time. MaxConcurrency (string) --The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time. If a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency. ComplianceSeverity (string) --The severity level to assign to the association. SyncCompliance (string) --The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT . In MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action. By default, all associations use AUTO mode. Message (string) --A description of the failure. Fault (string) --The source of the failure. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidParameters SSM.Client.exceptions.DuplicateInstanceId SSM.Client.exceptions.AssociationLimitExceeded SSM.Client.exceptions.UnsupportedPlatformType SSM.Client.exceptions.InvalidOutputLocation SSM.Client.exceptions.InvalidTarget SSM.Client.exceptions.InvalidSchedule :return: { 'Successful': [ { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' }, ], 'Failed': [ { 'Entry': { 'Name': 'string', 'InstanceId': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AutomationTargetParameterName': 'string', 'DocumentVersion': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' }, 'Message': 'string', 'Fault': 'Client'|'Server'|'Unknown' }, ] } :returns: ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` """ pass def create_document(Content=None, Requires=None, Attachments=None, Name=None, VersionName=None, DocumentType=None, DocumentFormat=None, TargetType=None, Tags=None): """ Creates a Systems Manager (SSM) document. An SSM document defines the actions that Systems Manager performs on your managed instances. For more information about SSM documents, including information about supported schemas, features, and syntax, see AWS Systems Manager Documents in the AWS Systems Manager User Guide . See also: AWS API Documentation Exceptions :example: response = client.create_document( Content='string', Requires=[ { 'Name': 'string', 'Version': 'string' }, ], Attachments=[ { 'Key': 'SourceUrl'|'S3FileUrl'|'AttachmentReference', 'Values': [ 'string', ], 'Name': 'string' }, ], Name='string', VersionName='string', DocumentType='Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', DocumentFormat='YAML'|'JSON'|'TEXT', TargetType='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type Content: string :param Content: [REQUIRED]\nThe content for the new SSM document in JSON or YAML format. We recommend storing the contents for your new document in an external JSON or YAML file and referencing the file in a command.\nFor examples, see the following topics in the AWS Systems Manager User Guide .\n\nCreate an SSM document (AWS API)\nCreate an SSM document (AWS CLI)\nCreate an SSM document (API)\n\n :type Requires: list :param Requires: A list of SSM documents required by a document. This parameter is used exclusively by AWS AppConfig. When a user creates an AppConfig configuration in an SSM document, the user must also specify a required document for validation purposes. In this case, an ApplicationConfiguration document requires an ApplicationConfigurationSchema document for validation purposes. For more information, see AWS AppConfig in the AWS Systems Manager User Guide .\n\n(dict) --An SSM document required by the current document.\n\nName (string) -- [REQUIRED]The name of the required SSM document. The name can be an Amazon Resource Name (ARN).\n\nVersion (string) --The document version required by the current document.\n\n\n\n\n :type Attachments: list :param Attachments: A list of key and value pairs that describe attachments to a version of a document.\n\n(dict) --Identifying information about a document attachment, including the file name and a key-value pair that identifies the location of an attachment to a document.\n\nKey (string) --The key of a key-value pair that identifies the location of an attachment to a document.\n\nValues (list) --The value of a key-value pair that identifies the location of an attachment to a document. The format for Value depends on the type of key you specify.\n\nFor the key SourceUrl , the value is an S3 bucket location. For example: 'Values': [ 's3://my-bucket/my-folder' ]\nFor the key S3FileUrl , the value is a file in an S3 bucket. For example: 'Values': [ 's3://my-bucket/my-folder/my-file.py' ]\nFor the key AttachmentReference , the value is constructed from the name of another SSM document in your account, a version number of that document, and a file attached to that document version that you want to reuse. For example: 'Values': [ 'MyOtherDocument/3/my-other-file.py' ] However, if the SSM document is shared with you from another account, the full SSM document ARN must be specified instead of the document name only. For example: 'Values': [ 'arn:aws:ssm:us-east-2:111122223333:document/OtherAccountDocument/3/their-file.py' ]\n\n\n(string) --\n\n\nName (string) --The name of the document attachment file.\n\n\n\n\n :type Name: string :param Name: [REQUIRED]\nA name for the Systems Manager document.\n\nWarning\nYou can\'t use the following strings as document name prefixes. These are reserved by AWS for use as document name prefixes:\n\naws-\namazon\namzn\n\n\n :type VersionName: string :param VersionName: An optional field specifying the version of the artifact you are creating with the document. For example, 'Release 12, Update 6'. This value is unique across all versions of a document, and cannot be changed. :type DocumentType: string :param DocumentType: The type of document to create. :type DocumentFormat: string :param DocumentFormat: Specify the document format for the request. The document format can be JSON, YAML, or TEXT. JSON is the default format. :type TargetType: string :param TargetType: Specify a target type to define the kinds of resources the document can run on. For example, to run a document on EC2 instances, specify the following value: /AWS::EC2::Instance. If you specify a value of \'/\' the document can run on all types of resources. If you don\'t specify a value, the document can\'t run on any resources. For a list of valid resource types, see AWS resource and property types reference in the AWS CloudFormation User Guide . :type Tags: list :param Tags: Optional metadata that you assign to a resource. Tags enable you to categorize a resource in different ways, such as by purpose, owner, or environment. For example, you might want to tag an SSM document to identify the types of targets or the environment where it will run. In this case, you could specify the following key name/value pairs:\n\nKey=OS,Value=Windows\nKey=Environment,Value=Production\n\n\nNote\nTo add tags to an existing SSM document, use the AddTagsToResource action.\n\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'DocumentDescription': { 'Sha1': 'string', 'Hash': 'string', 'HashType': 'Sha256'|'Sha1', 'Name': 'string', 'VersionName': 'string', 'Owner': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'DocumentVersion': 'string', 'Description': 'string', 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList', 'Description': 'string', 'DefaultValue': 'string' }, ], 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'LatestVersion': 'string', 'DefaultVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'AttachmentsInformation': [ { 'Name': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] } } Response Structure (dict) -- DocumentDescription (dict) -- Information about the Systems Manager document. Sha1 (string) -- The SHA1 hash of the document, which you can use for verification. Hash (string) -- The Sha256 or Sha1 hash created by the system when the document was created. Note Sha1 hashes have been deprecated. HashType (string) -- The hash type of the document. Valid values include Sha256 or Sha1 . Note Sha1 hashes have been deprecated. Name (string) -- The name of the Systems Manager document. VersionName (string) -- The version of the artifact associated with the document. Owner (string) -- The AWS user account that created the document. CreatedDate (datetime) -- The date when the document was created. Status (string) -- The status of the Systems Manager document. StatusInformation (string) -- A message returned by AWS Systems Manager that explains the Status value. For example, a Failed status might be explained by the StatusInformation message, "The specified S3 bucket does not exist. Verify that the URL of the S3 bucket is correct." DocumentVersion (string) -- The document version. Description (string) -- A description of the document. Parameters (list) -- A description of the parameters for a document. (dict) -- Parameters specified in a System Manager document that run on the server when the command is run. Name (string) -- The name of the parameter. Type (string) -- The type of parameter. The type can be either String or StringList. Description (string) -- A description of what the parameter does, how to use it, the default value, and whether or not the parameter is optional. DefaultValue (string) -- If specified, the default values for the parameters. Parameters without a default value are required. Parameters with a default value are optional. PlatformTypes (list) -- The list of OS platforms compatible with this Systems Manager document. (string) -- DocumentType (string) -- The type of document. SchemaVersion (string) -- The schema version. LatestVersion (string) -- The latest version of the document. DefaultVersion (string) -- The default version. DocumentFormat (string) -- The document format, either JSON or YAML. TargetType (string) -- The target type which defines the kinds of resources the document can run on. For example, /AWS::EC2::Instance. For a list of valid resource types, see AWS resource and property types reference in the AWS CloudFormation User Guide . Tags (list) -- The tags, or metadata, that have been applied to the document. (dict) -- Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines. Key (string) -- The name of the tag. Value (string) -- The value of the tag. AttachmentsInformation (list) -- Details about the document attachments, including names, locations, sizes, and so on. (dict) -- An attribute of an attachment, such as the attachment name. Name (string) -- The name of the attachment. Requires (list) -- A list of SSM documents required by a document. For example, an ApplicationConfiguration document requires an ApplicationConfigurationSchema document. (dict) -- An SSM document required by the current document. Name (string) -- The name of the required SSM document. The name can be an Amazon Resource Name (ARN). Version (string) -- The document version required by the current document. Exceptions SSM.Client.exceptions.DocumentAlreadyExists SSM.Client.exceptions.MaxDocumentSizeExceeded SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocumentContent SSM.Client.exceptions.DocumentLimitExceeded SSM.Client.exceptions.InvalidDocumentSchemaVersion :return: { 'DocumentDescription': { 'Sha1': 'string', 'Hash': 'string', 'HashType': 'Sha256'|'Sha1', 'Name': 'string', 'VersionName': 'string', 'Owner': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'DocumentVersion': 'string', 'Description': 'string', 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList', 'Description': 'string', 'DefaultValue': 'string' }, ], 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'LatestVersion': 'string', 'DefaultVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'AttachmentsInformation': [ { 'Name': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] } } :returns: (string) -- """ pass def create_maintenance_window(Name=None, Description=None, StartDate=None, EndDate=None, Schedule=None, ScheduleTimezone=None, Duration=None, Cutoff=None, AllowUnassociatedTargets=None, ClientToken=None, Tags=None): """ Creates a new maintenance window. See also: AWS API Documentation Exceptions :example: response = client.create_maintenance_window( Name='string', Description='string', StartDate='string', EndDate='string', Schedule='string', ScheduleTimezone='string', Duration=123, Cutoff=123, AllowUnassociatedTargets=True|False, ClientToken='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type Name: string :param Name: [REQUIRED]\nThe name of the maintenance window.\n :type Description: string :param Description: An optional description for the maintenance window. We recommend specifying a description to help you organize your maintenance windows. :type StartDate: string :param StartDate: The date and time, in ISO-8601 Extended format, for when you want the maintenance window to become active. StartDate allows you to delay activation of the maintenance window until the specified future date. :type EndDate: string :param EndDate: The date and time, in ISO-8601 Extended format, for when you want the maintenance window to become inactive. EndDate allows you to set a date and time in the future when the maintenance window will no longer run. :type Schedule: string :param Schedule: [REQUIRED]\nThe schedule of the maintenance window in the form of a cron or rate expression.\n :type ScheduleTimezone: string :param ScheduleTimezone: The time zone that the scheduled maintenance window executions are based on, in Internet Assigned Numbers Authority (IANA) format. For example: 'America/Los_Angeles', 'etc/UTC', or 'Asia/Seoul'. For more information, see the Time Zone Database on the IANA website. :type Duration: integer :param Duration: [REQUIRED]\nThe duration of the maintenance window in hours.\n :type Cutoff: integer :param Cutoff: [REQUIRED]\nThe number of hours before the end of the maintenance window that Systems Manager stops scheduling new tasks for execution.\n :type AllowUnassociatedTargets: boolean :param AllowUnassociatedTargets: [REQUIRED]\nEnables a maintenance window task to run on managed instances, even if you have not registered those instances as targets. If enabled, then you must specify the unregistered instances (by instance ID) when you register a task with the maintenance window.\nIf you don\'t enable this option, then you must specify previously-registered targets when you register a task with the maintenance window.\n :type ClientToken: string :param ClientToken: User-provided idempotency token.\nThis field is autopopulated if not provided.\n :type Tags: list :param Tags: Optional metadata that you assign to a resource. Tags enable you to categorize a resource in different ways, such as by purpose, owner, or environment. For example, you might want to tag a maintenance window to identify the type of tasks it will run, the types of targets, and the environment it will run in. In this case, you could specify the following key name/value pairs:\n\nKey=TaskType,Value=AgentUpdate\nKey=OS,Value=Windows\nKey=Environment,Value=Production\n\n\nNote\nTo add tags to an existing maintenance window, use the AddTagsToResource action.\n\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'WindowId': 'string' } Response Structure (dict) -- WindowId (string) -- The ID of the created maintenance window. Exceptions SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string' } :returns: SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError """ pass def create_ops_item(Description=None, OperationalData=None, Notifications=None, Priority=None, RelatedOpsItems=None, Source=None, Title=None, Tags=None, Category=None, Severity=None): """ Creates a new OpsItem. You must have permission in AWS Identity and Access Management (IAM) to create a new OpsItem. For more information, see Getting started with OpsCenter in the AWS Systems Manager User Guide . Operations engineers and IT professionals use OpsCenter to view, investigate, and remediate operational issues impacting the performance and health of their AWS resources. For more information, see AWS Systems Manager OpsCenter in the AWS Systems Manager User Guide . See also: AWS API Documentation Exceptions :example: response = client.create_ops_item( Description='string', OperationalData={ 'string': { 'Value': 'string', 'Type': 'SearchableString'|'String' } }, Notifications=[ { 'Arn': 'string' }, ], Priority=123, RelatedOpsItems=[ { 'OpsItemId': 'string' }, ], Source='string', Title='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ], Category='string', Severity='string' ) :type Description: string :param Description: [REQUIRED]\nInformation about the OpsItem.\n :type OperationalData: dict :param OperationalData: Operational data is custom data that provides useful reference details about the OpsItem. For example, you can specify log files, error strings, license keys, troubleshooting tips, or other relevant data. You enter operational data as key-value pairs. The key has a maximum length of 128 characters. The value has a maximum size of 20 KB.\n\nWarning\nOperational data keys can\'t begin with the following: amazon, aws, amzn, ssm, /amazon, /aws, /amzn, /ssm.\n\nYou can choose to make the data searchable by other users in the account or you can restrict search access. Searchable data means that all users with access to the OpsItem Overview page (as provided by the DescribeOpsItems API action) can view and search on the specified data. Operational data that is not searchable is only viewable by users who have access to the OpsItem (as provided by the GetOpsItem API action).\nUse the /aws/resources key in OperationalData to specify a related resource in the request. Use the /aws/automations key in OperationalData to associate an Automation runbook with the OpsItem. To view AWS CLI example commands that use these keys, see Creating OpsItems manually in the AWS Systems Manager User Guide .\n\n(string) --\n(dict) --An object that defines the value of the key and its type in the OperationalData map.\n\nValue (string) --The value of the OperationalData key.\n\nType (string) --The type of key-value pair. Valid types include SearchableString and String .\n\n\n\n\n\n\n :type Notifications: list :param Notifications: The Amazon Resource Name (ARN) of an SNS topic where notifications are sent when this OpsItem is edited or changed.\n\n(dict) --A notification about the OpsItem.\n\nArn (string) --The Amazon Resource Name (ARN) of an SNS topic where notifications are sent when this OpsItem is edited or changed.\n\n\n\n\n :type Priority: integer :param Priority: The importance of this OpsItem in relation to other OpsItems in the system. :type RelatedOpsItems: list :param RelatedOpsItems: One or more OpsItems that share something in common with the current OpsItems. For example, related OpsItems can include OpsItems with similar error messages, impacted resources, or statuses for the impacted resource.\n\n(dict) --An OpsItems that shares something in common with the current OpsItem. For example, related OpsItems can include OpsItems with similar error messages, impacted resources, or statuses for the impacted resource.\n\nOpsItemId (string) -- [REQUIRED]The ID of an OpsItem related to the current OpsItem.\n\n\n\n\n :type Source: string :param Source: [REQUIRED]\nThe origin of the OpsItem, such as Amazon EC2 or Systems Manager.\n\nNote\nThe source name can\'t contain the following strings: aws, amazon, and amzn.\n\n :type Title: string :param Title: [REQUIRED]\nA short heading that describes the nature of the OpsItem and the impacted resource.\n :type Tags: list :param Tags: Optional metadata that you assign to a resource. You can restrict access to OpsItems by using an inline IAM policy that specifies tags. For more information, see Getting started with OpsCenter in the AWS Systems Manager User Guide .\nTags use a key-value pair. For example:\n\nKey=Department,Value=Finance\n\nNote\nTo add tags to an existing OpsItem, use the AddTagsToResource action.\n\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :type Category: string :param Category: Specify a category to assign to an OpsItem. :type Severity: string :param Severity: Specify a severity to assign to an OpsItem. :rtype: dict ReturnsResponse Syntax { 'OpsItemId': 'string' } Response Structure (dict) -- OpsItemId (string) -- The ID of the OpsItem. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.OpsItemAlreadyExistsException SSM.Client.exceptions.OpsItemLimitExceededException SSM.Client.exceptions.OpsItemInvalidParameterException :return: { 'OpsItemId': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.OpsItemAlreadyExistsException SSM.Client.exceptions.OpsItemLimitExceededException SSM.Client.exceptions.OpsItemInvalidParameterException """ pass def create_patch_baseline(OperatingSystem=None, Name=None, GlobalFilters=None, ApprovalRules=None, ApprovedPatches=None, ApprovedPatchesComplianceLevel=None, ApprovedPatchesEnableNonSecurity=None, RejectedPatches=None, RejectedPatchesAction=None, Description=None, Sources=None, ClientToken=None, Tags=None): """ Creates a patch baseline. See also: AWS API Documentation Exceptions :example: response = client.create_patch_baseline( OperatingSystem='WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', Name='string', GlobalFilters={ 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, ApprovalRules={ 'PatchRules': [ { 'PatchFilterGroup': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApproveAfterDays': 123, 'ApproveUntilDate': 'string', 'EnableNonSecurity': True|False }, ] }, ApprovedPatches=[ 'string', ], ApprovedPatchesComplianceLevel='CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', ApprovedPatchesEnableNonSecurity=True|False, RejectedPatches=[ 'string', ], RejectedPatchesAction='ALLOW_AS_DEPENDENCY'|'BLOCK', Description='string', Sources=[ { 'Name': 'string', 'Products': [ 'string', ], 'Configuration': 'string' }, ], ClientToken='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type OperatingSystem: string :param OperatingSystem: Defines the operating system the patch baseline applies to. The Default value is WINDOWS. :type Name: string :param Name: [REQUIRED]\nThe name of the patch baseline.\n :type GlobalFilters: dict :param GlobalFilters: A set of global filters used to include patches in the baseline.\n\nPatchFilters (list) -- [REQUIRED]The set of patch filters that make up the group.\n\n(dict) --Defines which patches should be included in a patch baseline.\nA patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ['Office 2013', 'Office 2016'], then the filter accepts all patches where product name is either 'Office 2013' or 'Office 2016'. The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values.\nYou can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties .\n\nKey (string) -- [REQUIRED]The key for the filter.\nRun the DescribePatchProperties command to view lists of valid keys for each operating system type.\n\nValues (list) -- [REQUIRED]The value for the filter key.\nRun the DescribePatchProperties command to view lists of valid values for each key based on operating system type.\n\n(string) --\n\n\n\n\n\n\n\n :type ApprovalRules: dict :param ApprovalRules: A set of rules used to include patches in the baseline.\n\nPatchRules (list) -- [REQUIRED]The rules that make up the rule group.\n\n(dict) --Defines an approval rule for a patch baseline.\n\nPatchFilterGroup (dict) -- [REQUIRED]The patch filter group that defines the criteria for the rule.\n\nPatchFilters (list) -- [REQUIRED]The set of patch filters that make up the group.\n\n(dict) --Defines which patches should be included in a patch baseline.\nA patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ['Office 2013', 'Office 2016'], then the filter accepts all patches where product name is either 'Office 2013' or 'Office 2016'. The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values.\nYou can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties .\n\nKey (string) -- [REQUIRED]The key for the filter.\nRun the DescribePatchProperties command to view lists of valid keys for each operating system type.\n\nValues (list) -- [REQUIRED]The value for the filter key.\nRun the DescribePatchProperties command to view lists of valid values for each key based on operating system type.\n\n(string) --\n\n\n\n\n\n\n\n\nComplianceLevel (string) --A compliance severity level for all approved patches in a patch baseline.\n\nApproveAfterDays (integer) --The number of days after the release date of each patch matched by the rule that the patch is marked as approved in the patch baseline. For example, a value of 7 means that patches are approved seven days after they are released. Not supported on Ubuntu Server.\n\nApproveUntilDate (string) --The cutoff date for auto approval of released patches. Any patches released on or before this date are installed automatically. Not supported on Ubuntu Server.\nEnter dates in the format YYYY-MM-DD . For example, 2020-12-31 .\n\nEnableNonSecurity (boolean) --For instances identified by the approval rule filters, enables a patch baseline to apply non-security updates available in the specified repository. The default value is \'false\'. Applies to Linux instances only.\n\n\n\n\n\n\n :type ApprovedPatches: list :param ApprovedPatches: A list of explicitly approved patches for the baseline.\nFor information about accepted formats for lists of approved patches and rejected patches, see About package name formats for approved and rejected patch lists in the AWS Systems Manager User Guide .\n\n(string) --\n\n :type ApprovedPatchesComplianceLevel: string :param ApprovedPatchesComplianceLevel: Defines the compliance level for approved patches. This means that if an approved patch is reported as missing, this is the severity of the compliance violation. The default value is UNSPECIFIED. :type ApprovedPatchesEnableNonSecurity: boolean :param ApprovedPatchesEnableNonSecurity: Indicates whether the list of approved patches includes non-security updates that should be applied to the instances. The default value is \'false\'. Applies to Linux instances only. :type RejectedPatches: list :param RejectedPatches: A list of explicitly rejected patches for the baseline.\nFor information about accepted formats for lists of approved patches and rejected patches, see About package name formats for approved and rejected patch lists in the AWS Systems Manager User Guide .\n\n(string) --\n\n :type RejectedPatchesAction: string :param RejectedPatchesAction: The action for Patch Manager to take on patches included in the RejectedPackages list.\n\nALLOW_AS_DEPENDENCY : A package in the Rejected patches list is installed only if it is a dependency of another package. It is considered compliant with the patch baseline, and its status is reported as InstalledOther . This is the default action if no option is specified.\nBLOCK : Packages in the RejectedPatches list, and packages that include them as dependencies, are not installed under any circumstances. If a package was installed before it was added to the Rejected patches list, it is considered non-compliant with the patch baseline, and its status is reported as InstalledRejected .\n\n :type Description: string :param Description: A description of the patch baseline. :type Sources: list :param Sources: Information about the patches to use to update the instances, including target operating systems and source repositories. Applies to Linux instances only.\n\n(dict) --Information about the patches to use to update the instances, including target operating systems and source repository. Applies to Linux instances only.\n\nName (string) -- [REQUIRED]The name specified to identify the patch source.\n\nProducts (list) -- [REQUIRED]The specific operating system versions a patch repository applies to, such as 'Ubuntu16.04', 'AmazonLinux2016.09', 'RedhatEnterpriseLinux7.2' or 'Suse12.7'. For lists of supported product values, see PatchFilter .\n\n(string) --\n\n\nConfiguration (string) -- [REQUIRED]The value of the yum repo configuration. For example:\n\n[main]cachedir=/var/cache/yum/$basesearch$releasever\nkeepcache=0\ndebuglevel=2\n\n\n\n\n\n :type ClientToken: string :param ClientToken: User-provided idempotency token.\nThis field is autopopulated if not provided.\n :type Tags: list :param Tags: Optional metadata that you assign to a resource. Tags enable you to categorize a resource in different ways, such as by purpose, owner, or environment. For example, you might want to tag a patch baseline to identify the severity level of patches it specifies and the operating system family it applies to. In this case, you could specify the following key name/value pairs:\n\nKey=PatchSeverity,Value=Critical\nKey=OS,Value=Windows\n\n\nNote\nTo add tags to an existing patch baseline, use the AddTagsToResource action.\n\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'BaselineId': 'string' } Response Structure (dict) -- BaselineId (string) -- The ID of the created patch baseline. Exceptions SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string' } :returns: SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError """ pass def create_resource_data_sync(SyncName=None, S3Destination=None, SyncType=None, SyncSource=None): """ A resource data sync helps you view data from multiple sources in a single location. Systems Manager offers two types of resource data sync: SyncToDestination and SyncFromSource . You can configure Systems Manager Inventory to use the SyncToDestination type to synchronize Inventory data from multiple AWS Regions to a single S3 bucket. For more information, see Configuring Resource Data Sync for Inventory in the AWS Systems Manager User Guide . You can configure Systems Manager Explorer to use the SyncFromSource type to synchronize operational work items (OpsItems) and operational data (OpsData) from multiple AWS Regions to a single S3 bucket. This type can synchronize OpsItems and OpsData from multiple AWS accounts and Regions or EntireOrganization by using AWS Organizations. For more information, see Setting up Systems Manager Explorer to display data from multiple accounts and Regions in the AWS Systems Manager User Guide . A resource data sync is an asynchronous operation that returns immediately. After a successful initial sync is completed, the system continuously syncs data. To check the status of a sync, use the ListResourceDataSync . See also: AWS API Documentation Exceptions :example: response = client.create_resource_data_sync( SyncName='string', S3Destination={ 'BucketName': 'string', 'Prefix': 'string', 'SyncFormat': 'JsonSerDe', 'Region': 'string', 'AWSKMSKeyARN': 'string', 'DestinationDataSharing': { 'DestinationDataSharingType': 'string' } }, SyncType='string', SyncSource={ 'SourceType': 'string', 'AwsOrganizationsSource': { 'OrganizationSourceType': 'string', 'OrganizationalUnits': [ { 'OrganizationalUnitId': 'string' }, ] }, 'SourceRegions': [ 'string', ], 'IncludeFutureRegions': True|False } ) :type SyncName: string :param SyncName: [REQUIRED]\nA name for the configuration.\n :type S3Destination: dict :param S3Destination: Amazon S3 configuration details for the sync. This parameter is required if the SyncType value is SyncToDestination.\n\nBucketName (string) -- [REQUIRED]The name of the S3 bucket where the aggregated data is stored.\n\nPrefix (string) --An Amazon S3 prefix for the bucket.\n\nSyncFormat (string) -- [REQUIRED]A supported sync format. The following format is currently supported: JsonSerDe\n\nRegion (string) -- [REQUIRED]The AWS Region with the S3 bucket targeted by the Resource Data Sync.\n\nAWSKMSKeyARN (string) --The ARN of an encryption key for a destination in Amazon S3. Must belong to the same Region as the destination S3 bucket.\n\nDestinationDataSharing (dict) --Enables destination data sharing. By default, this field is null .\n\nDestinationDataSharingType (string) --The sharing data type. Only Organization is supported.\n\n\n\n\n :type SyncType: string :param SyncType: Specify SyncToDestination to create a resource data sync that synchronizes data to an S3 bucket for Inventory. If you specify SyncToDestination , you must provide a value for S3Destination . Specify SyncFromSource to synchronize data from a single account and multiple Regions, or multiple AWS accounts and Regions, as listed in AWS Organizations for Explorer. If you specify SyncFromSource , you must provide a value for SyncSource . The default value is SyncToDestination . :type SyncSource: dict :param SyncSource: Specify information about the data sources to synchronize. This parameter is required if the SyncType value is SyncFromSource.\n\nSourceType (string) -- [REQUIRED]The type of data source for the resource data sync. SourceType is either AwsOrganizations (if an organization is present in AWS Organizations) or singleAccountMultiRegions .\n\nAwsOrganizationsSource (dict) --Information about the AwsOrganizationsSource resource data sync source. A sync source of this type can synchronize data from AWS Organizations.\n\nOrganizationSourceType (string) -- [REQUIRED]If an AWS Organization is present, this is either OrganizationalUnits or EntireOrganization . For OrganizationalUnits , the data is aggregated from a set of organization units. For EntireOrganization , the data is aggregated from the entire AWS Organization.\n\nOrganizationalUnits (list) --The AWS Organizations organization units included in the sync.\n\n(dict) --The AWS Organizations organizational unit data source for the sync.\n\nOrganizationalUnitId (string) --The AWS Organization unit ID data source for the sync.\n\n\n\n\n\n\n\nSourceRegions (list) -- [REQUIRED]The SyncSource AWS Regions included in the resource data sync.\n\n(string) --\n\n\nIncludeFutureRegions (boolean) --Whether to automatically synchronize and aggregate data from new AWS Regions when those Regions come online.\n\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ResourceDataSyncCountExceededException SSM.Client.exceptions.ResourceDataSyncAlreadyExistsException SSM.Client.exceptions.ResourceDataSyncInvalidConfigurationException :return: {} :returns: (dict) -- """ pass def delete_activation(ActivationId=None): """ Deletes an activation. You are not required to delete an activation. If you delete an activation, you can no longer use it to register additional managed instances. Deleting an activation does not de-register managed instances. You must manually de-register managed instances. See also: AWS API Documentation Exceptions :example: response = client.delete_activation( ActivationId='string' ) :type ActivationId: string :param ActivationId: [REQUIRED]\nThe ID of the activation that you want to delete.\n :rtype: dict ReturnsResponse Syntax{} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InvalidActivationId SSM.Client.exceptions.InvalidActivation SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.TooManyUpdates :return: {} :returns: SSM.Client.exceptions.InvalidActivationId SSM.Client.exceptions.InvalidActivation SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.TooManyUpdates """ pass def delete_association(Name=None, InstanceId=None, AssociationId=None): """ Disassociates the specified Systems Manager document from the specified instance. When you disassociate a document from an instance, it does not change the configuration of the instance. To change the configuration state of an instance after you disassociate a document, you must create a new document with the desired configuration and associate it with the instance. See also: AWS API Documentation Exceptions :example: response = client.delete_association( Name='string', InstanceId='string', AssociationId='string' ) :type Name: string :param Name: The name of the Systems Manager document. :type InstanceId: string :param InstanceId: The ID of the instance. :type AssociationId: string :param AssociationId: The association ID that you want to delete. :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.TooManyUpdates :return: {} :returns: (dict) -- """ pass def delete_document(Name=None, DocumentVersion=None, VersionName=None, Force=None): """ Deletes the Systems Manager document and all instance associations to the document. Before you delete the document, we recommend that you use DeleteAssociation to disassociate all instances that are associated with the document. See also: AWS API Documentation Exceptions :example: response = client.delete_document( Name='string', DocumentVersion='string', VersionName='string', Force=True|False ) :type Name: string :param Name: [REQUIRED]\nThe name of the document.\n :type DocumentVersion: string :param DocumentVersion: The version of the document that you want to delete. If not provided, all versions of the document are deleted. :type VersionName: string :param VersionName: The version name of the document that you want to delete. If not provided, all versions of the document are deleted. :type Force: boolean :param Force: Some SSM document types require that you specify a Force flag before you can delete the document. For example, you must specify a Force flag to delete a document of type ApplicationConfigurationSchema . You can restrict access to the Force flag in an AWS Identity and Access Management (IAM) policy. :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentOperation SSM.Client.exceptions.AssociatedInstances :return: {} :returns: (dict) -- """ pass def delete_inventory(TypeName=None, SchemaDeleteOption=None, DryRun=None, ClientToken=None): """ Delete a custom inventory type, or the data associated with a custom Inventory type. Deleting a custom inventory type is also referred to as deleting a custom inventory schema. See also: AWS API Documentation Exceptions :example: response = client.delete_inventory( TypeName='string', SchemaDeleteOption='DisableSchema'|'DeleteSchema', DryRun=True|False, ClientToken='string' ) :type TypeName: string :param TypeName: [REQUIRED]\nThe name of the custom inventory type for which you want to delete either all previously collected data, or the inventory type itself.\n :type SchemaDeleteOption: string :param SchemaDeleteOption: Use the SchemaDeleteOption to delete a custom inventory type (schema). If you don\'t choose this option, the system only deletes existing inventory data associated with the custom inventory type. Choose one of the following options:\nDisableSchema: If you choose this option, the system ignores all inventory data for the specified version, and any earlier versions. To enable this schema again, you must call the PutInventory action for a version greater than the disabled version.\nDeleteSchema: This option deletes the specified custom type from the Inventory service. You can recreate the schema later, if you want.\n :type DryRun: boolean :param DryRun: Use this option to view a summary of the deletion request without deleting any data or the data type. This option is useful when you only want to understand what will be deleted. Once you validate that the data to be deleted is what you intend to delete, you can run the same command without specifying the DryRun option. :type ClientToken: string :param ClientToken: User-provided idempotency token.\nThis field is autopopulated if not provided.\n :rtype: dict ReturnsResponse Syntax { 'DeletionId': 'string', 'TypeName': 'string', 'DeletionSummary': { 'TotalCount': 123, 'RemainingCount': 123, 'SummaryItems': [ { 'Version': 'string', 'Count': 123, 'RemainingCount': 123 }, ] } } Response Structure (dict) -- DeletionId (string) -- Every DeleteInventory action is assigned a unique ID. This option returns a unique ID. You can use this ID to query the status of a delete operation. This option is useful for ensuring that a delete operation has completed before you begin other actions. TypeName (string) -- The name of the inventory data type specified in the request. DeletionSummary (dict) -- A summary of the delete operation. For more information about this summary, see Deleting custom inventory in the AWS Systems Manager User Guide . TotalCount (integer) -- The total number of items to delete. This count does not change during the delete operation. RemainingCount (integer) -- Remaining number of items to delete. SummaryItems (list) -- A list of counts and versions for deleted items. (dict) -- Either a count, remaining count, or a version number in a delete inventory summary. Version (string) -- The inventory type version. Count (integer) -- A count of the number of deleted items. RemainingCount (integer) -- The remaining number of items to delete. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidOptionException SSM.Client.exceptions.InvalidDeleteInventoryParametersException SSM.Client.exceptions.InvalidInventoryRequestException :return: { 'DeletionId': 'string', 'TypeName': 'string', 'DeletionSummary': { 'TotalCount': 123, 'RemainingCount': 123, 'SummaryItems': [ { 'Version': 'string', 'Count': 123, 'RemainingCount': 123 }, ] } } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidOptionException SSM.Client.exceptions.InvalidDeleteInventoryParametersException SSM.Client.exceptions.InvalidInventoryRequestException """ pass def delete_maintenance_window(WindowId=None): """ Deletes a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.delete_maintenance_window( WindowId='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window to delete.\n :rtype: dict ReturnsResponse Syntax{ 'WindowId': 'string' } Response Structure (dict) -- WindowId (string) --The ID of the deleted maintenance window. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string' } """ pass def delete_parameter(Name=None): """ Delete a parameter from the system. See also: AWS API Documentation Exceptions :example: response = client.delete_parameter( Name='string' ) :type Name: string :param Name: [REQUIRED]\nThe name of the parameter to delete.\n :rtype: dict ReturnsResponse Syntax{} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ParameterNotFound :return: {} :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ParameterNotFound """ pass def delete_parameters(Names=None): """ Delete a list of parameters. See also: AWS API Documentation Exceptions :example: response = client.delete_parameters( Names=[ 'string', ] ) :type Names: list :param Names: [REQUIRED]\nThe names of the parameters to delete.\n\n(string) --\n\n :rtype: dict ReturnsResponse Syntax{ 'DeletedParameters': [ 'string', ], 'InvalidParameters': [ 'string', ] } Response Structure (dict) -- DeletedParameters (list) --The names of the deleted parameters. (string) -- InvalidParameters (list) --The names of parameters that weren\'t deleted because the parameters are not valid. (string) -- Exceptions SSM.Client.exceptions.InternalServerError :return: { 'DeletedParameters': [ 'string', ], 'InvalidParameters': [ 'string', ] } :returns: (string) -- """ pass def delete_patch_baseline(BaselineId=None): """ Deletes a patch baseline. See also: AWS API Documentation Exceptions :example: response = client.delete_patch_baseline( BaselineId='string' ) :type BaselineId: string :param BaselineId: [REQUIRED]\nThe ID of the patch baseline to delete.\n :rtype: dict ReturnsResponse Syntax{ 'BaselineId': 'string' } Response Structure (dict) -- BaselineId (string) --The ID of the deleted patch baseline. Exceptions SSM.Client.exceptions.ResourceInUseException SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string' } """ pass def delete_resource_data_sync(SyncName=None, SyncType=None): """ Deletes a Resource Data Sync configuration. After the configuration is deleted, changes to data on managed instances are no longer synced to or from the target. Deleting a sync configuration does not delete data. See also: AWS API Documentation Exceptions :example: response = client.delete_resource_data_sync( SyncName='string', SyncType='string' ) :type SyncName: string :param SyncName: [REQUIRED]\nThe name of the configuration to delete.\n :type SyncType: string :param SyncType: Specify the type of resource data sync to delete. :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ResourceDataSyncNotFoundException SSM.Client.exceptions.ResourceDataSyncInvalidConfigurationException :return: {} :returns: (dict) -- """ pass def deregister_managed_instance(InstanceId=None): """ Removes the server or virtual machine from the list of registered servers. You can reregister the instance again at any time. If you don\'t plan to use Run Command on the server, we suggest uninstalling SSM Agent first. See also: AWS API Documentation Exceptions :example: response = client.deregister_managed_instance( InstanceId='string' ) :type InstanceId: string :param InstanceId: [REQUIRED]\nThe ID assigned to the managed instance when you registered it using the activation process.\n :rtype: dict ReturnsResponse Syntax{} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InternalServerError :return: {} :returns: SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InternalServerError """ pass def deregister_patch_baseline_for_patch_group(BaselineId=None, PatchGroup=None): """ Removes a patch group from a patch baseline. See also: AWS API Documentation Exceptions :example: response = client.deregister_patch_baseline_for_patch_group( BaselineId='string', PatchGroup='string' ) :type BaselineId: string :param BaselineId: [REQUIRED]\nThe ID of the patch baseline to deregister the patch group from.\n :type PatchGroup: string :param PatchGroup: [REQUIRED]\nThe name of the patch group that should be deregistered from the patch baseline.\n :rtype: dict ReturnsResponse Syntax { 'BaselineId': 'string', 'PatchGroup': 'string' } Response Structure (dict) -- BaselineId (string) -- The ID of the patch baseline the patch group was deregistered from. PatchGroup (string) -- The name of the patch group deregistered from the patch baseline. Exceptions SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string', 'PatchGroup': 'string' } :returns: SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError """ pass def deregister_target_from_maintenance_window(WindowId=None, WindowTargetId=None, Safe=None): """ Removes a target from a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.deregister_target_from_maintenance_window( WindowId='string', WindowTargetId='string', Safe=True|False ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window the target should be removed from.\n :type WindowTargetId: string :param WindowTargetId: [REQUIRED]\nThe ID of the target definition to remove.\n :type Safe: boolean :param Safe: The system checks if the target is being referenced by a task. If the target is being referenced, the system returns an error and does not deregister the target from the maintenance window. :rtype: dict ReturnsResponse Syntax { 'WindowId': 'string', 'WindowTargetId': 'string' } Response Structure (dict) -- WindowId (string) -- The ID of the maintenance window the target was removed from. WindowTargetId (string) -- The ID of the removed target definition. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.TargetInUseException :return: { 'WindowId': 'string', 'WindowTargetId': 'string' } :returns: SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.TargetInUseException """ pass def deregister_task_from_maintenance_window(WindowId=None, WindowTaskId=None): """ Removes a task from a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.deregister_task_from_maintenance_window( WindowId='string', WindowTaskId='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window the task should be removed from.\n :type WindowTaskId: string :param WindowTaskId: [REQUIRED]\nThe ID of the task to remove from the maintenance window.\n :rtype: dict ReturnsResponse Syntax { 'WindowId': 'string', 'WindowTaskId': 'string' } Response Structure (dict) -- WindowId (string) -- The ID of the maintenance window the task was removed from. WindowTaskId (string) -- The ID of the task removed from the maintenance window. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string', 'WindowTaskId': 'string' } :returns: SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError """ pass def describe_activations(Filters=None, MaxResults=None, NextToken=None): """ Describes details about the activation, such as the date and time the activation was created, its expiration date, the IAM role assigned to the instances in the activation, and the number of instances registered by using this activation. See also: AWS API Documentation Exceptions :example: response = client.describe_activations( Filters=[ { 'FilterKey': 'ActivationIds'|'DefaultInstanceName'|'IamRole', 'FilterValues': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type Filters: list :param Filters: A filter to view information about your activations.\n\n(dict) --Filter for the DescribeActivation API.\n\nFilterKey (string) --The name of the filter.\n\nFilterValues (list) --The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'ActivationList': [ { 'ActivationId': 'string', 'Description': 'string', 'DefaultInstanceName': 'string', 'IamRole': 'string', 'RegistrationLimit': 123, 'RegistrationsCount': 123, 'ExpirationDate': datetime(2015, 1, 1), 'Expired': True|False, 'CreatedDate': datetime(2015, 1, 1), 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } Response Structure (dict) -- ActivationList (list) -- A list of activations for your AWS account. (dict) -- An activation registers one or more on-premises servers or virtual machines (VMs) with AWS so that you can configure those servers or VMs using Run Command. A server or VM that has been registered with AWS is called a managed instance. ActivationId (string) -- The ID created by Systems Manager when you submitted the activation. Description (string) -- A user defined description of the activation. DefaultInstanceName (string) -- A name for the managed instance when it is created. IamRole (string) -- The Amazon Identity and Access Management (IAM) role to assign to the managed instance. RegistrationLimit (integer) -- The maximum number of managed instances that can be registered using this activation. RegistrationsCount (integer) -- The number of managed instances already registered with this activation. ExpirationDate (datetime) -- The date when this activation can no longer be used to register managed instances. Expired (boolean) -- Whether or not the activation is expired. CreatedDate (datetime) -- The date the activation was created. Tags (list) -- Tags assigned to the activation. (dict) -- Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines. Key (string) -- The name of the tag. Value (string) -- The value of the tag. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InternalServerError :return: { 'ActivationList': [ { 'ActivationId': 'string', 'Description': 'string', 'DefaultInstanceName': 'string', 'IamRole': 'string', 'RegistrationLimit': 123, 'RegistrationsCount': 123, 'ExpirationDate': datetime(2015, 1, 1), 'Expired': True|False, 'CreatedDate': datetime(2015, 1, 1), 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InternalServerError """ pass def describe_association(Name=None, InstanceId=None, AssociationId=None, AssociationVersion=None): """ Describes the association for the specified target or instance. If you created the association by using the Targets parameter, then you must retrieve the association by using the association ID. If you created the association by specifying an instance ID and a Systems Manager document, then you retrieve the association by specifying the document name and the instance ID. See also: AWS API Documentation Exceptions :example: response = client.describe_association( Name='string', InstanceId='string', AssociationId='string', AssociationVersion='string' ) :type Name: string :param Name: The name of the Systems Manager document. :type InstanceId: string :param InstanceId: The instance ID. :type AssociationId: string :param AssociationId: The association ID for which you want information. :type AssociationVersion: string :param AssociationVersion: Specify the association version to retrieve. To view the latest version, either specify $LATEST for this parameter, or omit this parameter. To view a list of all associations for an instance, use ListAssociations . To get a list of versions for a specific association, use ListAssociationVersions . :rtype: dict ReturnsResponse Syntax { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } Response Structure (dict) -- AssociationDescription (dict) -- Information about the association. Name (string) -- The name of the Systems Manager document. InstanceId (string) -- The ID of the instance. AssociationVersion (string) -- The association version. Date (datetime) -- The date when the association was made. LastUpdateAssociationDate (datetime) -- The date when the association was last updated. Status (dict) -- The association status. Date (datetime) -- The date when the status changed. Name (string) -- The status. Message (string) -- The reason for the status. AdditionalInfo (string) -- A user-defined string. Overview (dict) -- Information about the association. Status (string) -- The status of the association. Status can be: Pending, Success, or Failed. DetailedStatus (string) -- A detailed status of the association. AssociationStatusAggregatedCount (dict) -- Returns the number of targets for the association status. For example, if you created an association with two instances, and one of them was successful, this would return the count of instances by status. (string) -- (integer) -- DocumentVersion (string) -- The document version. AutomationTargetParameterName (string) -- Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. Parameters (dict) -- A description of the parameters for a document. (string) -- (list) -- (string) -- AssociationId (string) -- The association ID. Targets (list) -- The instances targeted by the request. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- ScheduleExpression (string) -- A cron expression that specifies a schedule when the association runs. OutputLocation (dict) -- An S3 bucket where you want to store the output details of the request. S3Location (dict) -- An S3 bucket where you want to store the results of this request. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) -- The name of the S3 bucket. OutputS3KeyPrefix (string) -- The S3 bucket subfolder. LastExecutionDate (datetime) -- The date on which the association was last run. LastSuccessfulExecutionDate (datetime) -- The last date on which the association was successfully run. AssociationName (string) -- The association name. MaxErrors (string) -- The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received. Executions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time. MaxConcurrency (string) -- The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time. If a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency. ComplianceSeverity (string) -- The severity level that is assigned to the association. SyncCompliance (string) -- The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT . In MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action. By default, all associations use AUTO mode. Exceptions SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.InvalidAssociationVersion SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidInstanceId :return: { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } :returns: (string) -- (integer) -- """ pass def describe_association_execution_targets(AssociationId=None, ExecutionId=None, Filters=None, MaxResults=None, NextToken=None): """ Use this API action to view information about a specific execution of a specific association. See also: AWS API Documentation Exceptions :example: response = client.describe_association_execution_targets( AssociationId='string', ExecutionId='string', Filters=[ { 'Key': 'Status'|'ResourceId'|'ResourceType', 'Value': 'string' }, ], MaxResults=123, NextToken='string' ) :type AssociationId: string :param AssociationId: [REQUIRED]\nThe association ID that includes the execution for which you want to view details.\n :type ExecutionId: string :param ExecutionId: [REQUIRED]\nThe execution ID for which you want to view details.\n :type Filters: list :param Filters: Filters for the request. You can specify the following filters and values.\nStatus (EQUAL)\nResourceId (EQUAL)\nResourceType (EQUAL)\n\n(dict) --Filters for the association execution.\n\nKey (string) -- [REQUIRED]The key value used in the request.\n\nValue (string) -- [REQUIRED]The value specified for the key.\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'AssociationExecutionTargets': [ { 'AssociationId': 'string', 'AssociationVersion': 'string', 'ExecutionId': 'string', 'ResourceId': 'string', 'ResourceType': 'string', 'Status': 'string', 'DetailedStatus': 'string', 'LastExecutionDate': datetime(2015, 1, 1), 'OutputSource': { 'OutputSourceId': 'string', 'OutputSourceType': 'string' } }, ], 'NextToken': 'string' } Response Structure (dict) -- AssociationExecutionTargets (list) -- Information about the execution. (dict) -- Includes information about the specified association execution. AssociationId (string) -- The association ID. AssociationVersion (string) -- The association version. ExecutionId (string) -- The execution ID. ResourceId (string) -- The resource ID, for example, the instance ID where the association ran. ResourceType (string) -- The resource type, for example, instance. Status (string) -- The association execution status. DetailedStatus (string) -- Detailed information about the execution status. LastExecutionDate (datetime) -- The date of the last execution. OutputSource (dict) -- The location where the association details are saved. OutputSourceId (string) -- The ID of the output source, for example the URL of an S3 bucket. OutputSourceType (string) -- The type of source where the association execution details are stored, for example, Amazon S3. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.AssociationExecutionDoesNotExist :return: { 'AssociationExecutionTargets': [ { 'AssociationId': 'string', 'AssociationVersion': 'string', 'ExecutionId': 'string', 'ResourceId': 'string', 'ResourceType': 'string', 'Status': 'string', 'DetailedStatus': 'string', 'LastExecutionDate': datetime(2015, 1, 1), 'OutputSource': { 'OutputSourceId': 'string', 'OutputSourceType': 'string' } }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.AssociationExecutionDoesNotExist """ pass def describe_association_executions(AssociationId=None, Filters=None, MaxResults=None, NextToken=None): """ Use this API action to view all executions for a specific association ID. See also: AWS API Documentation Exceptions :example: response = client.describe_association_executions( AssociationId='string', Filters=[ { 'Key': 'ExecutionId'|'Status'|'CreatedTime', 'Value': 'string', 'Type': 'EQUAL'|'LESS_THAN'|'GREATER_THAN' }, ], MaxResults=123, NextToken='string' ) :type AssociationId: string :param AssociationId: [REQUIRED]\nThe association ID for which you want to view execution history details.\n :type Filters: list :param Filters: Filters for the request. You can specify the following filters and values.\nExecutionId (EQUAL)\nStatus (EQUAL)\nCreatedTime (EQUAL, GREATER_THAN, LESS_THAN)\n\n(dict) --Filters used in the request.\n\nKey (string) -- [REQUIRED]The key value used in the request.\n\nValue (string) -- [REQUIRED]The value specified for the key.\n\nType (string) -- [REQUIRED]The filter type specified in the request.\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'AssociationExecutions': [ { 'AssociationId': 'string', 'AssociationVersion': 'string', 'ExecutionId': 'string', 'Status': 'string', 'DetailedStatus': 'string', 'CreatedTime': datetime(2015, 1, 1), 'LastExecutionDate': datetime(2015, 1, 1), 'ResourceCountByStatus': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- AssociationExecutions (list) -- A list of the executions for the specified association ID. (dict) -- Includes information about the specified association. AssociationId (string) -- The association ID. AssociationVersion (string) -- The association version. ExecutionId (string) -- The execution ID for the association. Status (string) -- The status of the association execution. DetailedStatus (string) -- Detailed status information about the execution. CreatedTime (datetime) -- The time the execution started. LastExecutionDate (datetime) -- The date of the last execution. ResourceCountByStatus (string) -- An aggregate status of the resources in the execution based on the status type. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.InvalidNextToken :return: { 'AssociationExecutions': [ { 'AssociationId': 'string', 'AssociationVersion': 'string', 'ExecutionId': 'string', 'Status': 'string', 'DetailedStatus': 'string', 'CreatedTime': datetime(2015, 1, 1), 'LastExecutionDate': datetime(2015, 1, 1), 'ResourceCountByStatus': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.InvalidNextToken """ pass def describe_automation_executions(Filters=None, MaxResults=None, NextToken=None): """ Provides details about all active and terminated Automation executions. See also: AWS API Documentation Exceptions :example: response = client.describe_automation_executions( Filters=[ { 'Key': 'DocumentNamePrefix'|'ExecutionStatus'|'ExecutionId'|'ParentExecutionId'|'CurrentAction'|'StartTimeBefore'|'StartTimeAfter'|'AutomationType'|'TagKey', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type Filters: list :param Filters: Filters used to limit the scope of executions that are requested.\n\n(dict) --A filter used to match specific automation executions. This is used to limit the scope of Automation execution information returned.\n\nKey (string) -- [REQUIRED]One or more keys to limit the results. Valid filter keys include the following: DocumentNamePrefix, ExecutionStatus, ExecutionId, ParentExecutionId, CurrentAction, StartTimeBefore, StartTimeAfter.\n\nValues (list) -- [REQUIRED]The values used to limit the execution information associated with the filter\'s key.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'AutomationExecutionMetadataList': [ { 'AutomationExecutionId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'AutomationExecutionStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'ExecutedBy': 'string', 'LogFile': 'string', 'Outputs': { 'string': [ 'string', ] }, 'Mode': 'Auto'|'Interactive', 'ParentAutomationExecutionId': 'string', 'CurrentStepName': 'string', 'CurrentAction': 'string', 'FailureMessage': 'string', 'TargetParameterName': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetMaps': [ { 'string': [ 'string', ] }, ], 'ResolvedTargets': { 'ParameterValues': [ 'string', ], 'Truncated': True|False }, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Target': 'string', 'AutomationType': 'CrossAccount'|'Local' }, ], 'NextToken': 'string' } Response Structure (dict) -- AutomationExecutionMetadataList (list) -- The list of details about each automation execution which has occurred which matches the filter specification, if any. (dict) -- Details about a specific Automation execution. AutomationExecutionId (string) -- The execution ID. DocumentName (string) -- The name of the Automation document used during execution. DocumentVersion (string) -- The document version used during the execution. AutomationExecutionStatus (string) -- The status of the execution. ExecutionStartTime (datetime) -- The time the execution started. ExecutionEndTime (datetime) -- The time the execution finished. This is not populated if the execution is still in progress. ExecutedBy (string) -- The IAM role ARN of the user who ran the Automation. LogFile (string) -- An S3 bucket where execution information is stored. Outputs (dict) -- The list of execution outputs as defined in the Automation document. (string) -- (list) -- (string) -- Mode (string) -- The Automation execution mode. ParentAutomationExecutionId (string) -- The ExecutionId of the parent Automation. CurrentStepName (string) -- The name of the step that is currently running. CurrentAction (string) -- The action of the step that is currently running. FailureMessage (string) -- The list of execution outputs as defined in the Automation document. TargetParameterName (string) -- The list of execution outputs as defined in the Automation document. Targets (list) -- The targets defined by the user when starting the Automation. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TargetMaps (list) -- The specified key-value mapping of document parameters to target resources. (dict) -- (string) -- (list) -- (string) -- ResolvedTargets (dict) -- A list of targets that resolved during the execution. ParameterValues (list) -- A list of parameter values sent to targets that resolved during the Automation execution. (string) -- Truncated (boolean) -- A boolean value indicating whether the resolved target list is truncated. MaxConcurrency (string) -- The MaxConcurrency value specified by the user when starting the Automation. MaxErrors (string) -- The MaxErrors value specified by the user when starting the Automation. Target (string) -- The list of execution outputs as defined in the Automation document. AutomationType (string) -- Use this filter with DescribeAutomationExecutions . Specify either Local or CrossAccount. CrossAccount is an Automation that runs in multiple AWS Regions and accounts. For more information, see Running Automation workflows in multiple AWS Regions and accounts in the AWS Systems Manager User Guide . NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidFilterValue SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InternalServerError :return: { 'AutomationExecutionMetadataList': [ { 'AutomationExecutionId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'AutomationExecutionStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'ExecutedBy': 'string', 'LogFile': 'string', 'Outputs': { 'string': [ 'string', ] }, 'Mode': 'Auto'|'Interactive', 'ParentAutomationExecutionId': 'string', 'CurrentStepName': 'string', 'CurrentAction': 'string', 'FailureMessage': 'string', 'TargetParameterName': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetMaps': [ { 'string': [ 'string', ] }, ], 'ResolvedTargets': { 'ParameterValues': [ 'string', ], 'Truncated': True|False }, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Target': 'string', 'AutomationType': 'CrossAccount'|'Local' }, ], 'NextToken': 'string' } :returns: (string) -- (list) -- (string) -- """ pass def describe_automation_step_executions(AutomationExecutionId=None, Filters=None, NextToken=None, MaxResults=None, ReverseOrder=None): """ Information about all active and terminated step executions in an Automation workflow. See also: AWS API Documentation Exceptions :example: response = client.describe_automation_step_executions( AutomationExecutionId='string', Filters=[ { 'Key': 'StartTimeBefore'|'StartTimeAfter'|'StepExecutionStatus'|'StepExecutionId'|'StepName'|'Action', 'Values': [ 'string', ] }, ], NextToken='string', MaxResults=123, ReverseOrder=True|False ) :type AutomationExecutionId: string :param AutomationExecutionId: [REQUIRED]\nThe Automation execution ID for which you want step execution descriptions.\n :type Filters: list :param Filters: One or more filters to limit the number of step executions returned by the request.\n\n(dict) --A filter to limit the amount of step execution information returned by the call.\n\nKey (string) -- [REQUIRED]One or more keys to limit the results. Valid filter keys include the following: StepName, Action, StepExecutionId, StepExecutionStatus, StartTimeBefore, StartTimeAfter.\n\nValues (list) -- [REQUIRED]The values of the filter key.\n\n(string) --\n\n\n\n\n\n :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type ReverseOrder: boolean :param ReverseOrder: A boolean that indicates whether to list step executions in reverse order by start time. The default value is false. :rtype: dict ReturnsResponse Syntax { 'StepExecutions': [ { 'StepName': 'string', 'Action': 'string', 'TimeoutSeconds': 123, 'OnFailure': 'string', 'MaxAttempts': 123, 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'StepStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'ResponseCode': 'string', 'Inputs': { 'string': 'string' }, 'Outputs': { 'string': [ 'string', ] }, 'Response': 'string', 'FailureMessage': 'string', 'FailureDetails': { 'FailureStage': 'string', 'FailureType': 'string', 'Details': { 'string': [ 'string', ] } }, 'StepExecutionId': 'string', 'OverriddenParameters': { 'string': [ 'string', ] }, 'IsEnd': True|False, 'NextStep': 'string', 'IsCritical': True|False, 'ValidNextSteps': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetLocation': { 'Accounts': [ 'string', ], 'Regions': [ 'string', ], 'TargetLocationMaxConcurrency': 'string', 'TargetLocationMaxErrors': 'string', 'ExecutionRoleName': 'string' } }, ], 'NextToken': 'string' } Response Structure (dict) -- StepExecutions (list) -- A list of details about the current state of all steps that make up an execution. (dict) -- Detailed information about an the execution state of an Automation step. StepName (string) -- The name of this execution step. Action (string) -- The action this step performs. The action determines the behavior of the step. TimeoutSeconds (integer) -- The timeout seconds of the step. OnFailure (string) -- The action to take if the step fails. The default value is Abort. MaxAttempts (integer) -- The maximum number of tries to run the action of the step. The default value is 1. ExecutionStartTime (datetime) -- If a step has begun execution, this contains the time the step started. If the step is in Pending status, this field is not populated. ExecutionEndTime (datetime) -- If a step has finished execution, this contains the time the execution ended. If the step has not yet concluded, this field is not populated. StepStatus (string) -- The execution status for this step. ResponseCode (string) -- The response code returned by the execution of the step. Inputs (dict) -- Fully-resolved values passed into the step before execution. (string) -- (string) -- Outputs (dict) -- Returned values from the execution of the step. (string) -- (list) -- (string) -- Response (string) -- A message associated with the response code for an execution. FailureMessage (string) -- If a step failed, this message explains why the execution failed. FailureDetails (dict) -- Information about the Automation failure. FailureStage (string) -- The stage of the Automation execution when the failure occurred. The stages include the following: InputValidation, PreVerification, Invocation, PostVerification. FailureType (string) -- The type of Automation failure. Failure types include the following: Action, Permission, Throttling, Verification, Internal. Details (dict) -- Detailed information about the Automation step failure. (string) -- (list) -- (string) -- StepExecutionId (string) -- The unique ID of a step execution. OverriddenParameters (dict) -- A user-specified list of parameters to override when running a step. (string) -- (list) -- (string) -- IsEnd (boolean) -- The flag which can be used to end automation no matter whether the step succeeds or fails. NextStep (string) -- The next step after the step succeeds. IsCritical (boolean) -- The flag which can be used to help decide whether the failure of current step leads to the Automation failure. ValidNextSteps (list) -- Strategies used when step fails, we support Continue and Abort. Abort will fail the automation when the step fails. Continue will ignore the failure of current step and allow automation to run the next step. With conditional branching, we add step:stepName to support the automation to go to another specific step. (string) -- Targets (list) -- The targets for the step execution. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TargetLocation (dict) -- The combination of AWS Regions and accounts targeted by the current Automation execution. Accounts (list) -- The AWS accounts targeted by the current Automation execution. (string) -- Regions (list) -- The AWS Regions targeted by the current Automation execution. (string) -- TargetLocationMaxConcurrency (string) -- The maximum number of AWS accounts and AWS regions allowed to run the Automation concurrently TargetLocationMaxErrors (string) -- The maximum number of errors allowed before the system stops queueing additional Automation executions for the currently running Automation. ExecutionRoleName (string) -- The Automation execution role used by the currently running Automation. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.AutomationExecutionNotFoundException SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidFilterValue SSM.Client.exceptions.InternalServerError :return: { 'StepExecutions': [ { 'StepName': 'string', 'Action': 'string', 'TimeoutSeconds': 123, 'OnFailure': 'string', 'MaxAttempts': 123, 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'StepStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'ResponseCode': 'string', 'Inputs': { 'string': 'string' }, 'Outputs': { 'string': [ 'string', ] }, 'Response': 'string', 'FailureMessage': 'string', 'FailureDetails': { 'FailureStage': 'string', 'FailureType': 'string', 'Details': { 'string': [ 'string', ] } }, 'StepExecutionId': 'string', 'OverriddenParameters': { 'string': [ 'string', ] }, 'IsEnd': True|False, 'NextStep': 'string', 'IsCritical': True|False, 'ValidNextSteps': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetLocation': { 'Accounts': [ 'string', ], 'Regions': [ 'string', ], 'TargetLocationMaxConcurrency': 'string', 'TargetLocationMaxErrors': 'string', 'ExecutionRoleName': 'string' } }, ], 'NextToken': 'string' } :returns: (string) -- (string) -- """ pass def describe_available_patches(Filters=None, MaxResults=None, NextToken=None): """ Lists all patches eligible to be included in a patch baseline. See also: AWS API Documentation Exceptions :example: response = client.describe_available_patches( Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type Filters: list :param Filters: Filters used to scope down the returned patches.\n\n(dict) --Defines a filter used in Patch Manager APIs.\n\nKey (string) --The key for the filter.\n\nValues (list) --The value for the filter.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of patches to return (per page). :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Patches': [ { 'Id': 'string', 'ReleaseDate': datetime(2015, 1, 1), 'Title': 'string', 'Description': 'string', 'ContentUrl': 'string', 'Vendor': 'string', 'ProductFamily': 'string', 'Product': 'string', 'Classification': 'string', 'MsrcSeverity': 'string', 'KbNumber': 'string', 'MsrcNumber': 'string', 'Language': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Patches (list) -- An array of patches. Each entry in the array is a patch structure. (dict) -- Represents metadata about a patch. Id (string) -- The ID of the patch (this is different than the Microsoft Knowledge Base ID). ReleaseDate (datetime) -- The date the patch was released. Title (string) -- The title of the patch. Description (string) -- The description of the patch. ContentUrl (string) -- The URL where more information can be obtained about the patch. Vendor (string) -- The name of the vendor providing the patch. ProductFamily (string) -- The product family the patch is applicable for (for example, Windows). Product (string) -- The specific product the patch is applicable for (for example, WindowsServer2016). Classification (string) -- The classification of the patch (for example, SecurityUpdates, Updates, CriticalUpdates). MsrcSeverity (string) -- The severity of the patch (for example Critical, Important, Moderate). KbNumber (string) -- The Microsoft Knowledge Base ID of the patch. MsrcNumber (string) -- The ID of the MSRC bulletin the patch is related to. Language (string) -- The language of the patch if it\'s language-specific. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'Patches': [ { 'Id': 'string', 'ReleaseDate': datetime(2015, 1, 1), 'Title': 'string', 'Description': 'string', 'ContentUrl': 'string', 'Vendor': 'string', 'ProductFamily': 'string', 'Product': 'string', 'Classification': 'string', 'MsrcSeverity': 'string', 'KbNumber': 'string', 'MsrcNumber': 'string', 'Language': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError """ pass def describe_document(Name=None, DocumentVersion=None, VersionName=None): """ Describes the specified Systems Manager document. See also: AWS API Documentation Exceptions :example: response = client.describe_document( Name='string', DocumentVersion='string', VersionName='string' ) :type Name: string :param Name: [REQUIRED]\nThe name of the Systems Manager document.\n :type DocumentVersion: string :param DocumentVersion: The document version for which you want information. Can be a specific version or the default version. :type VersionName: string :param VersionName: An optional field specifying the version of the artifact associated with the document. For example, 'Release 12, Update 6'. This value is unique across all versions of a document, and cannot be changed. :rtype: dict ReturnsResponse Syntax { 'Document': { 'Sha1': 'string', 'Hash': 'string', 'HashType': 'Sha256'|'Sha1', 'Name': 'string', 'VersionName': 'string', 'Owner': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'DocumentVersion': 'string', 'Description': 'string', 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList', 'Description': 'string', 'DefaultValue': 'string' }, ], 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'LatestVersion': 'string', 'DefaultVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'AttachmentsInformation': [ { 'Name': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] } } Response Structure (dict) -- Document (dict) -- Information about the Systems Manager document. Sha1 (string) -- The SHA1 hash of the document, which you can use for verification. Hash (string) -- The Sha256 or Sha1 hash created by the system when the document was created. Note Sha1 hashes have been deprecated. HashType (string) -- The hash type of the document. Valid values include Sha256 or Sha1 . Note Sha1 hashes have been deprecated. Name (string) -- The name of the Systems Manager document. VersionName (string) -- The version of the artifact associated with the document. Owner (string) -- The AWS user account that created the document. CreatedDate (datetime) -- The date when the document was created. Status (string) -- The status of the Systems Manager document. StatusInformation (string) -- A message returned by AWS Systems Manager that explains the Status value. For example, a Failed status might be explained by the StatusInformation message, "The specified S3 bucket does not exist. Verify that the URL of the S3 bucket is correct." DocumentVersion (string) -- The document version. Description (string) -- A description of the document. Parameters (list) -- A description of the parameters for a document. (dict) -- Parameters specified in a System Manager document that run on the server when the command is run. Name (string) -- The name of the parameter. Type (string) -- The type of parameter. The type can be either String or StringList. Description (string) -- A description of what the parameter does, how to use it, the default value, and whether or not the parameter is optional. DefaultValue (string) -- If specified, the default values for the parameters. Parameters without a default value are required. Parameters with a default value are optional. PlatformTypes (list) -- The list of OS platforms compatible with this Systems Manager document. (string) -- DocumentType (string) -- The type of document. SchemaVersion (string) -- The schema version. LatestVersion (string) -- The latest version of the document. DefaultVersion (string) -- The default version. DocumentFormat (string) -- The document format, either JSON or YAML. TargetType (string) -- The target type which defines the kinds of resources the document can run on. For example, /AWS::EC2::Instance. For a list of valid resource types, see AWS resource and property types reference in the AWS CloudFormation User Guide . Tags (list) -- The tags, or metadata, that have been applied to the document. (dict) -- Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines. Key (string) -- The name of the tag. Value (string) -- The value of the tag. AttachmentsInformation (list) -- Details about the document attachments, including names, locations, sizes, and so on. (dict) -- An attribute of an attachment, such as the attachment name. Name (string) -- The name of the attachment. Requires (list) -- A list of SSM documents required by a document. For example, an ApplicationConfiguration document requires an ApplicationConfigurationSchema document. (dict) -- An SSM document required by the current document. Name (string) -- The name of the required SSM document. The name can be an Amazon Resource Name (ARN). Version (string) -- The document version required by the current document. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion :return: { 'Document': { 'Sha1': 'string', 'Hash': 'string', 'HashType': 'Sha256'|'Sha1', 'Name': 'string', 'VersionName': 'string', 'Owner': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'DocumentVersion': 'string', 'Description': 'string', 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList', 'Description': 'string', 'DefaultValue': 'string' }, ], 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'LatestVersion': 'string', 'DefaultVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'AttachmentsInformation': [ { 'Name': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] } } :returns: (string) -- """ pass def describe_document_permission(Name=None, PermissionType=None): """ Describes the permissions for a Systems Manager document. If you created the document, you are the owner. If a document is shared, it can either be shared privately (by specifying a user\'s AWS account ID) or publicly (All ). See also: AWS API Documentation Exceptions :example: response = client.describe_document_permission( Name='string', PermissionType='Share' ) :type Name: string :param Name: [REQUIRED]\nThe name of the document for which you are the owner.\n :type PermissionType: string :param PermissionType: [REQUIRED]\nThe permission type for the document. The permission type can be Share .\n :rtype: dict ReturnsResponse Syntax { 'AccountIds': [ 'string', ], 'AccountSharingInfoList': [ { 'AccountId': 'string', 'SharedDocumentVersion': 'string' }, ] } Response Structure (dict) -- AccountIds (list) -- The account IDs that have permission to use this document. The ID can be either an AWS account or All . (string) -- AccountSharingInfoList (list) -- A list of AWS accounts where the current document is shared and the version shared with each account. (dict) -- Information includes the AWS account ID where the current document is shared and the version shared with that account. AccountId (string) -- The AWS account ID where the current document is shared. SharedDocumentVersion (string) -- The version of the current document shared with the account. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidPermissionType :return: { 'AccountIds': [ 'string', ], 'AccountSharingInfoList': [ { 'AccountId': 'string', 'SharedDocumentVersion': 'string' }, ] } :returns: (string) -- """ pass def describe_effective_instance_associations(InstanceId=None, MaxResults=None, NextToken=None): """ All associations for the instance(s). See also: AWS API Documentation Exceptions :example: response = client.describe_effective_instance_associations( InstanceId='string', MaxResults=123, NextToken='string' ) :type InstanceId: string :param InstanceId: [REQUIRED]\nThe instance ID for which you want to view all associations.\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Associations': [ { 'AssociationId': 'string', 'InstanceId': 'string', 'Content': 'string', 'AssociationVersion': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Associations (list) -- The associations for the requested instance. (dict) -- One or more association documents on the instance. AssociationId (string) -- The association ID. InstanceId (string) -- The instance ID. Content (string) -- The content of the association document for the instance(s). AssociationVersion (string) -- Version information for the association on the instance. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidNextToken :return: { 'Associations': [ { 'AssociationId': 'string', 'InstanceId': 'string', 'Content': 'string', 'AssociationVersion': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidNextToken """ pass def describe_effective_patches_for_patch_baseline(BaselineId=None, MaxResults=None, NextToken=None): """ Retrieves the current effective patches (the patch and the approval state) for the specified patch baseline. Note that this API applies only to Windows patch baselines. See also: AWS API Documentation Exceptions :example: response = client.describe_effective_patches_for_patch_baseline( BaselineId='string', MaxResults=123, NextToken='string' ) :type BaselineId: string :param BaselineId: [REQUIRED]\nThe ID of the patch baseline to retrieve the effective patches for.\n :type MaxResults: integer :param MaxResults: The maximum number of patches to return (per page). :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'EffectivePatches': [ { 'Patch': { 'Id': 'string', 'ReleaseDate': datetime(2015, 1, 1), 'Title': 'string', 'Description': 'string', 'ContentUrl': 'string', 'Vendor': 'string', 'ProductFamily': 'string', 'Product': 'string', 'Classification': 'string', 'MsrcSeverity': 'string', 'KbNumber': 'string', 'MsrcNumber': 'string', 'Language': 'string' }, 'PatchStatus': { 'DeploymentStatus': 'APPROVED'|'PENDING_APPROVAL'|'EXPLICIT_APPROVED'|'EXPLICIT_REJECTED', 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApprovalDate': datetime(2015, 1, 1) } }, ], 'NextToken': 'string' } Response Structure (dict) -- EffectivePatches (list) -- An array of patches and patch status. (dict) -- The EffectivePatch structure defines metadata about a patch along with the approval state of the patch in a particular patch baseline. The approval state includes information about whether the patch is currently approved, due to be approved by a rule, explicitly approved, or explicitly rejected and the date the patch was or will be approved. Patch (dict) -- Provides metadata for a patch, including information such as the KB ID, severity, classification and a URL for where more information can be obtained about the patch. Id (string) -- The ID of the patch (this is different than the Microsoft Knowledge Base ID). ReleaseDate (datetime) -- The date the patch was released. Title (string) -- The title of the patch. Description (string) -- The description of the patch. ContentUrl (string) -- The URL where more information can be obtained about the patch. Vendor (string) -- The name of the vendor providing the patch. ProductFamily (string) -- The product family the patch is applicable for (for example, Windows). Product (string) -- The specific product the patch is applicable for (for example, WindowsServer2016). Classification (string) -- The classification of the patch (for example, SecurityUpdates, Updates, CriticalUpdates). MsrcSeverity (string) -- The severity of the patch (for example Critical, Important, Moderate). KbNumber (string) -- The Microsoft Knowledge Base ID of the patch. MsrcNumber (string) -- The ID of the MSRC bulletin the patch is related to. Language (string) -- The language of the patch if it\'s language-specific. PatchStatus (dict) -- The status of the patch in a patch baseline. This includes information about whether the patch is currently approved, due to be approved by a rule, explicitly approved, or explicitly rejected and the date the patch was or will be approved. DeploymentStatus (string) -- The approval status of a patch (APPROVED, PENDING_APPROVAL, EXPLICIT_APPROVED, EXPLICIT_REJECTED). ComplianceLevel (string) -- The compliance severity level for a patch. ApprovalDate (datetime) -- The date the patch was approved (or will be approved if the status is PENDING_APPROVAL). NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.UnsupportedOperatingSystem SSM.Client.exceptions.InternalServerError :return: { 'EffectivePatches': [ { 'Patch': { 'Id': 'string', 'ReleaseDate': datetime(2015, 1, 1), 'Title': 'string', 'Description': 'string', 'ContentUrl': 'string', 'Vendor': 'string', 'ProductFamily': 'string', 'Product': 'string', 'Classification': 'string', 'MsrcSeverity': 'string', 'KbNumber': 'string', 'MsrcNumber': 'string', 'Language': 'string' }, 'PatchStatus': { 'DeploymentStatus': 'APPROVED'|'PENDING_APPROVAL'|'EXPLICIT_APPROVED'|'EXPLICIT_REJECTED', 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApprovalDate': datetime(2015, 1, 1) } }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.UnsupportedOperatingSystem SSM.Client.exceptions.InternalServerError """ pass def describe_instance_associations_status(InstanceId=None, MaxResults=None, NextToken=None): """ The status of the associations for the instance(s). See also: AWS API Documentation Exceptions :example: response = client.describe_instance_associations_status( InstanceId='string', MaxResults=123, NextToken='string' ) :type InstanceId: string :param InstanceId: [REQUIRED]\nThe instance IDs for which you want association status information.\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'InstanceAssociationStatusInfos': [ { 'AssociationId': 'string', 'Name': 'string', 'DocumentVersion': 'string', 'AssociationVersion': 'string', 'InstanceId': 'string', 'ExecutionDate': datetime(2015, 1, 1), 'Status': 'string', 'DetailedStatus': 'string', 'ExecutionSummary': 'string', 'ErrorCode': 'string', 'OutputUrl': { 'S3OutputUrl': { 'OutputUrl': 'string' } }, 'AssociationName': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- InstanceAssociationStatusInfos (list) -- Status information about the association. (dict) -- Status information about the instance association. AssociationId (string) -- The association ID. Name (string) -- The name of the association. DocumentVersion (string) -- The association document versions. AssociationVersion (string) -- The version of the association applied to the instance. InstanceId (string) -- The instance ID where the association was created. ExecutionDate (datetime) -- The date the instance association ran. Status (string) -- Status information about the instance association. DetailedStatus (string) -- Detailed status information about the instance association. ExecutionSummary (string) -- Summary information about association execution. ErrorCode (string) -- An error code returned by the request to create the association. OutputUrl (dict) -- A URL for an S3 bucket where you want to store the results of this request. S3OutputUrl (dict) -- The URL of S3 bucket where you want to store the results of this request. OutputUrl (string) -- A URL for an S3 bucket where you want to store the results of this request. AssociationName (string) -- The name of the association applied to the instance. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidNextToken :return: { 'InstanceAssociationStatusInfos': [ { 'AssociationId': 'string', 'Name': 'string', 'DocumentVersion': 'string', 'AssociationVersion': 'string', 'InstanceId': 'string', 'ExecutionDate': datetime(2015, 1, 1), 'Status': 'string', 'DetailedStatus': 'string', 'ExecutionSummary': 'string', 'ErrorCode': 'string', 'OutputUrl': { 'S3OutputUrl': { 'OutputUrl': 'string' } }, 'AssociationName': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidNextToken """ pass def describe_instance_information(InstanceInformationFilterList=None, Filters=None, MaxResults=None, NextToken=None): """ Describes one or more of your instances, including information about the operating system platform, the version of SSM Agent installed on the instance, instance status, and so on. If you specify one or more instance IDs, it returns information for those instances. If you do not specify instance IDs, it returns information for all your instances. If you specify an instance ID that is not valid or an instance that you do not own, you receive an error. See also: AWS API Documentation Exceptions :example: response = client.describe_instance_information( InstanceInformationFilterList=[ { 'key': 'InstanceIds'|'AgentVersion'|'PingStatus'|'PlatformTypes'|'ActivationIds'|'IamRole'|'ResourceType'|'AssociationStatus', 'valueSet': [ 'string', ] }, ], Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type InstanceInformationFilterList: list :param InstanceInformationFilterList: This is a legacy method. We recommend that you don\'t use this method. Instead, use the Filters data type. Filters enables you to return instance information by filtering based on tags applied to managed instances.\n\nNote\nAttempting to use InstanceInformationFilterList and Filters leads to an exception error.\n\n\n(dict) --Describes a filter for a specific list of instances. You can filter instances information by using tags. You specify tags by using a key-value mapping.\nUse this action instead of the DescribeInstanceInformationRequest$InstanceInformationFilterList method. The InstanceInformationFilterList method is a legacy method and does not support tags.\n\nkey (string) -- [REQUIRED]The name of the filter.\n\nvalueSet (list) -- [REQUIRED]The filter values.\n\n(string) --\n\n\n\n\n\n :type Filters: list :param Filters: One or more filters. Use a filter to return a more specific list of instances. You can filter based on tags applied to EC2 instances. Use this Filters data type instead of InstanceInformationFilterList , which is deprecated.\n\n(dict) --The filters to describe or get information about your managed instances.\n\nKey (string) -- [REQUIRED]The filter key name to describe your instances. For example:\n'InstanceIds'|'AgentVersion'|'PingStatus'|'PlatformTypes'|'ActivationIds'|'IamRole'|'ResourceType'|'AssociationStatus'|'Tag Key'\n\nValues (list) -- [REQUIRED]The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'InstanceInformationList': [ { 'InstanceId': 'string', 'PingStatus': 'Online'|'ConnectionLost'|'Inactive', 'LastPingDateTime': datetime(2015, 1, 1), 'AgentVersion': 'string', 'IsLatestVersion': True|False, 'PlatformType': 'Windows'|'Linux', 'PlatformName': 'string', 'PlatformVersion': 'string', 'ActivationId': 'string', 'IamRole': 'string', 'RegistrationDate': datetime(2015, 1, 1), 'ResourceType': 'ManagedInstance'|'Document'|'EC2Instance', 'Name': 'string', 'IPAddress': 'string', 'ComputerName': 'string', 'AssociationStatus': 'string', 'LastAssociationExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulAssociationExecutionDate': datetime(2015, 1, 1), 'AssociationOverview': { 'DetailedStatus': 'string', 'InstanceAssociationStatusAggregatedCount': { 'string': 123 } } }, ], 'NextToken': 'string' } Response Structure (dict) -- InstanceInformationList (list) -- The instance information list. (dict) -- Describes a filter for a specific list of instances. InstanceId (string) -- The instance ID. PingStatus (string) -- Connection status of SSM Agent. LastPingDateTime (datetime) -- The date and time when agent last pinged Systems Manager service. AgentVersion (string) -- The version of SSM Agent running on your Linux instance. IsLatestVersion (boolean) -- Indicates whether the latest version of SSM Agent is running on your Linux Managed Instance. This field does not indicate whether or not the latest version is installed on Windows managed instances, because some older versions of Windows Server use the EC2Config service to process SSM requests. PlatformType (string) -- The operating system platform type. PlatformName (string) -- The name of the operating system platform running on your instance. PlatformVersion (string) -- The version of the OS platform running on your instance. ActivationId (string) -- The activation ID created by Systems Manager when the server or VM was registered. IamRole (string) -- The Amazon Identity and Access Management (IAM) role assigned to the on-premises Systems Manager managed instances. This call does not return the IAM role for EC2 instances. RegistrationDate (datetime) -- The date the server or VM was registered with AWS as a managed instance. ResourceType (string) -- The type of instance. Instances are either EC2 instances or managed instances. Name (string) -- The name of the managed instance. IPAddress (string) -- The IP address of the managed instance. ComputerName (string) -- The fully qualified host name of the managed instance. AssociationStatus (string) -- The status of the association. LastAssociationExecutionDate (datetime) -- The date the association was last run. LastSuccessfulAssociationExecutionDate (datetime) -- The last date the association was successfully run. AssociationOverview (dict) -- Information about the association. DetailedStatus (string) -- Detailed status information about the aggregated associations. InstanceAssociationStatusAggregatedCount (dict) -- The number of associations for the instance(s). (string) -- (integer) -- NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidInstanceInformationFilterValue SSM.Client.exceptions.InvalidFilterKey :return: { 'InstanceInformationList': [ { 'InstanceId': 'string', 'PingStatus': 'Online'|'ConnectionLost'|'Inactive', 'LastPingDateTime': datetime(2015, 1, 1), 'AgentVersion': 'string', 'IsLatestVersion': True|False, 'PlatformType': 'Windows'|'Linux', 'PlatformName': 'string', 'PlatformVersion': 'string', 'ActivationId': 'string', 'IamRole': 'string', 'RegistrationDate': datetime(2015, 1, 1), 'ResourceType': 'ManagedInstance'|'Document'|'EC2Instance', 'Name': 'string', 'IPAddress': 'string', 'ComputerName': 'string', 'AssociationStatus': 'string', 'LastAssociationExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulAssociationExecutionDate': datetime(2015, 1, 1), 'AssociationOverview': { 'DetailedStatus': 'string', 'InstanceAssociationStatusAggregatedCount': { 'string': 123 } } }, ], 'NextToken': 'string' } :returns: (string) -- (integer) -- """ pass def describe_instance_patch_states(InstanceIds=None, NextToken=None, MaxResults=None): """ Retrieves the high-level patch state of one or more instances. See also: AWS API Documentation Exceptions :example: response = client.describe_instance_patch_states( InstanceIds=[ 'string', ], NextToken='string', MaxResults=123 ) :type InstanceIds: list :param InstanceIds: [REQUIRED]\nThe ID of the instance whose patch state information should be retrieved.\n\n(string) --\n\n :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxResults: integer :param MaxResults: The maximum number of instances to return (per page). :rtype: dict ReturnsResponse Syntax { 'InstancePatchStates': [ { 'InstanceId': 'string', 'PatchGroup': 'string', 'BaselineId': 'string', 'SnapshotId': 'string', 'InstallOverrideList': 'string', 'OwnerInformation': 'string', 'InstalledCount': 123, 'InstalledOtherCount': 123, 'InstalledPendingRebootCount': 123, 'InstalledRejectedCount': 123, 'MissingCount': 123, 'FailedCount': 123, 'UnreportedNotApplicableCount': 123, 'NotApplicableCount': 123, 'OperationStartTime': datetime(2015, 1, 1), 'OperationEndTime': datetime(2015, 1, 1), 'Operation': 'Scan'|'Install', 'LastNoRebootInstallOperationTime': datetime(2015, 1, 1), 'RebootOption': 'RebootIfNeeded'|'NoReboot' }, ], 'NextToken': 'string' } Response Structure (dict) -- InstancePatchStates (list) -- The high-level patch state for the requested instances. (dict) -- Defines the high-level patch compliance state for a managed instance, providing information about the number of installed, missing, not applicable, and failed patches along with metadata about the operation when this information was gathered for the instance. InstanceId (string) -- The ID of the managed instance the high-level patch compliance information was collected for. PatchGroup (string) -- The name of the patch group the managed instance belongs to. BaselineId (string) -- The ID of the patch baseline used to patch the instance. SnapshotId (string) -- The ID of the patch baseline snapshot used during the patching operation when this compliance data was collected. InstallOverrideList (string) -- An https URL or an Amazon S3 path-style URL to a list of patches to be installed. This patch installation list, which you maintain in an S3 bucket in YAML format and specify in the SSM document AWS-RunPatchBaseline , overrides the patches specified by the default patch baseline. For more information about the InstallOverrideList parameter, see About the SSM document AWS-RunPatchBaseline in the AWS Systems Manager User Guide . OwnerInformation (string) -- Placeholder information. This field will always be empty in the current release of the service. InstalledCount (integer) -- The number of patches from the patch baseline that are installed on the instance. InstalledOtherCount (integer) -- The number of patches not specified in the patch baseline that are installed on the instance. InstalledPendingRebootCount (integer) -- The number of patches installed by Patch Manager since the last time the instance was rebooted. InstalledRejectedCount (integer) -- The number of instances with patches installed that are specified in a RejectedPatches list. Patches with a status of InstalledRejected were typically installed before they were added to a RejectedPatches list. Note If ALLOW_AS_DEPENDENCY is the specified option for RejectedPatchesAction, the value of InstalledRejectedCount will always be 0 (zero). MissingCount (integer) -- The number of patches from the patch baseline that are applicable for the instance but aren\'t currently installed. FailedCount (integer) -- The number of patches from the patch baseline that were attempted to be installed during the last patching operation, but failed to install. UnreportedNotApplicableCount (integer) -- The number of patches beyond the supported limit of NotApplicableCount that are not reported by name to Systems Manager Inventory. NotApplicableCount (integer) -- The number of patches from the patch baseline that aren\'t applicable for the instance and therefore aren\'t installed on the instance. This number may be truncated if the list of patch names is very large. The number of patches beyond this limit are reported in UnreportedNotApplicableCount . OperationStartTime (datetime) -- The time the most recent patching operation was started on the instance. OperationEndTime (datetime) -- The time the most recent patching operation completed on the instance. Operation (string) -- The type of patching operation that was performed: SCAN (assess patch compliance state) or INSTALL (install missing patches). LastNoRebootInstallOperationTime (datetime) -- The time of the last attempt to patch the instance with NoReboot specified as the reboot option. RebootOption (string) -- Indicates the reboot option specified in the patch baseline. Note Reboot options apply to Install operations only. Reboots are not attempted for Patch Manager Scan operations. RebootIfNeeded : Patch Manager tries to reboot the instance if it installed any patches, or if any patches are detected with a status of InstalledPendingReboot . NoReboot : Patch Manager attempts to install missing packages without trying to reboot the system. Patches installed with this option are assigned a status of InstalledPendingReboot . These patches might not be in effect until a reboot is performed. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken :return: { 'InstancePatchStates': [ { 'InstanceId': 'string', 'PatchGroup': 'string', 'BaselineId': 'string', 'SnapshotId': 'string', 'InstallOverrideList': 'string', 'OwnerInformation': 'string', 'InstalledCount': 123, 'InstalledOtherCount': 123, 'InstalledPendingRebootCount': 123, 'InstalledRejectedCount': 123, 'MissingCount': 123, 'FailedCount': 123, 'UnreportedNotApplicableCount': 123, 'NotApplicableCount': 123, 'OperationStartTime': datetime(2015, 1, 1), 'OperationEndTime': datetime(2015, 1, 1), 'Operation': 'Scan'|'Install', 'LastNoRebootInstallOperationTime': datetime(2015, 1, 1), 'RebootOption': 'RebootIfNeeded'|'NoReboot' }, ], 'NextToken': 'string' } :returns: RebootIfNeeded : Patch Manager tries to reboot the instance if it installed any patches, or if any patches are detected with a status of InstalledPendingReboot . NoReboot : Patch Manager attempts to install missing packages without trying to reboot the system. Patches installed with this option are assigned a status of InstalledPendingReboot . These patches might not be in effect until a reboot is performed. """ pass def describe_instance_patch_states_for_patch_group(PatchGroup=None, Filters=None, NextToken=None, MaxResults=None): """ Retrieves the high-level patch state for the instances in the specified patch group. See also: AWS API Documentation Exceptions :example: response = client.describe_instance_patch_states_for_patch_group( PatchGroup='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'Equal'|'NotEqual'|'LessThan'|'GreaterThan' }, ], NextToken='string', MaxResults=123 ) :type PatchGroup: string :param PatchGroup: [REQUIRED]\nThe name of the patch group for which the patch state information should be retrieved.\n :type Filters: list :param Filters: Each entry in the array is a structure containing:\nKey (string between 1 and 200 characters)\nValues (array containing a single string)\nType (string 'Equal', 'NotEqual', 'LessThan', 'GreaterThan')\n\n(dict) --Defines a filter used in DescribeInstancePatchStatesForPatchGroup used to scope down the information returned by the API.\n\nKey (string) -- [REQUIRED]The key for the filter. Supported values are FailedCount, InstalledCount, InstalledOtherCount, MissingCount and NotApplicableCount.\n\nValues (list) -- [REQUIRED]The value for the filter, must be an integer greater than or equal to 0.\n\n(string) --\n\n\nType (string) -- [REQUIRED]The type of comparison that should be performed for the value: Equal, NotEqual, LessThan or GreaterThan.\n\n\n\n\n :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxResults: integer :param MaxResults: The maximum number of patches to return (per page). :rtype: dict ReturnsResponse Syntax { 'InstancePatchStates': [ { 'InstanceId': 'string', 'PatchGroup': 'string', 'BaselineId': 'string', 'SnapshotId': 'string', 'InstallOverrideList': 'string', 'OwnerInformation': 'string', 'InstalledCount': 123, 'InstalledOtherCount': 123, 'InstalledPendingRebootCount': 123, 'InstalledRejectedCount': 123, 'MissingCount': 123, 'FailedCount': 123, 'UnreportedNotApplicableCount': 123, 'NotApplicableCount': 123, 'OperationStartTime': datetime(2015, 1, 1), 'OperationEndTime': datetime(2015, 1, 1), 'Operation': 'Scan'|'Install', 'LastNoRebootInstallOperationTime': datetime(2015, 1, 1), 'RebootOption': 'RebootIfNeeded'|'NoReboot' }, ], 'NextToken': 'string' } Response Structure (dict) -- InstancePatchStates (list) -- The high-level patch state for the requested instances. (dict) -- Defines the high-level patch compliance state for a managed instance, providing information about the number of installed, missing, not applicable, and failed patches along with metadata about the operation when this information was gathered for the instance. InstanceId (string) -- The ID of the managed instance the high-level patch compliance information was collected for. PatchGroup (string) -- The name of the patch group the managed instance belongs to. BaselineId (string) -- The ID of the patch baseline used to patch the instance. SnapshotId (string) -- The ID of the patch baseline snapshot used during the patching operation when this compliance data was collected. InstallOverrideList (string) -- An https URL or an Amazon S3 path-style URL to a list of patches to be installed. This patch installation list, which you maintain in an S3 bucket in YAML format and specify in the SSM document AWS-RunPatchBaseline , overrides the patches specified by the default patch baseline. For more information about the InstallOverrideList parameter, see About the SSM document AWS-RunPatchBaseline in the AWS Systems Manager User Guide . OwnerInformation (string) -- Placeholder information. This field will always be empty in the current release of the service. InstalledCount (integer) -- The number of patches from the patch baseline that are installed on the instance. InstalledOtherCount (integer) -- The number of patches not specified in the patch baseline that are installed on the instance. InstalledPendingRebootCount (integer) -- The number of patches installed by Patch Manager since the last time the instance was rebooted. InstalledRejectedCount (integer) -- The number of instances with patches installed that are specified in a RejectedPatches list. Patches with a status of InstalledRejected were typically installed before they were added to a RejectedPatches list. Note If ALLOW_AS_DEPENDENCY is the specified option for RejectedPatchesAction, the value of InstalledRejectedCount will always be 0 (zero). MissingCount (integer) -- The number of patches from the patch baseline that are applicable for the instance but aren\'t currently installed. FailedCount (integer) -- The number of patches from the patch baseline that were attempted to be installed during the last patching operation, but failed to install. UnreportedNotApplicableCount (integer) -- The number of patches beyond the supported limit of NotApplicableCount that are not reported by name to Systems Manager Inventory. NotApplicableCount (integer) -- The number of patches from the patch baseline that aren\'t applicable for the instance and therefore aren\'t installed on the instance. This number may be truncated if the list of patch names is very large. The number of patches beyond this limit are reported in UnreportedNotApplicableCount . OperationStartTime (datetime) -- The time the most recent patching operation was started on the instance. OperationEndTime (datetime) -- The time the most recent patching operation completed on the instance. Operation (string) -- The type of patching operation that was performed: SCAN (assess patch compliance state) or INSTALL (install missing patches). LastNoRebootInstallOperationTime (datetime) -- The time of the last attempt to patch the instance with NoReboot specified as the reboot option. RebootOption (string) -- Indicates the reboot option specified in the patch baseline. Note Reboot options apply to Install operations only. Reboots are not attempted for Patch Manager Scan operations. RebootIfNeeded : Patch Manager tries to reboot the instance if it installed any patches, or if any patches are detected with a status of InstalledPendingReboot . NoReboot : Patch Manager attempts to install missing packages without trying to reboot the system. Patches installed with this option are assigned a status of InstalledPendingReboot . These patches might not be in effect until a reboot is performed. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken :return: { 'InstancePatchStates': [ { 'InstanceId': 'string', 'PatchGroup': 'string', 'BaselineId': 'string', 'SnapshotId': 'string', 'InstallOverrideList': 'string', 'OwnerInformation': 'string', 'InstalledCount': 123, 'InstalledOtherCount': 123, 'InstalledPendingRebootCount': 123, 'InstalledRejectedCount': 123, 'MissingCount': 123, 'FailedCount': 123, 'UnreportedNotApplicableCount': 123, 'NotApplicableCount': 123, 'OperationStartTime': datetime(2015, 1, 1), 'OperationEndTime': datetime(2015, 1, 1), 'Operation': 'Scan'|'Install', 'LastNoRebootInstallOperationTime': datetime(2015, 1, 1), 'RebootOption': 'RebootIfNeeded'|'NoReboot' }, ], 'NextToken': 'string' } :returns: RebootIfNeeded : Patch Manager tries to reboot the instance if it installed any patches, or if any patches are detected with a status of InstalledPendingReboot . NoReboot : Patch Manager attempts to install missing packages without trying to reboot the system. Patches installed with this option are assigned a status of InstalledPendingReboot . These patches might not be in effect until a reboot is performed. """ pass def describe_instance_patches(InstanceId=None, Filters=None, NextToken=None, MaxResults=None): """ Retrieves information about the patches on the specified instance and their state relative to the patch baseline being used for the instance. See also: AWS API Documentation Exceptions :example: response = client.describe_instance_patches( InstanceId='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], NextToken='string', MaxResults=123 ) :type InstanceId: string :param InstanceId: [REQUIRED]\nThe ID of the instance whose patch state information should be retrieved.\n :type Filters: list :param Filters: An array of structures. Each entry in the array is a structure containing a Key, Value combination. Valid values for Key are Classification | KBId | Severity | State .\n\n(dict) --Defines a filter used in Patch Manager APIs.\n\nKey (string) --The key for the filter.\n\nValues (list) --The value for the filter.\n\n(string) --\n\n\n\n\n\n :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxResults: integer :param MaxResults: The maximum number of patches to return (per page). :rtype: dict ReturnsResponse Syntax { 'Patches': [ { 'Title': 'string', 'KBId': 'string', 'Classification': 'string', 'Severity': 'string', 'State': 'INSTALLED'|'INSTALLED_OTHER'|'INSTALLED_PENDING_REBOOT'|'INSTALLED_REJECTED'|'MISSING'|'NOT_APPLICABLE'|'FAILED', 'InstalledTime': datetime(2015, 1, 1) }, ], 'NextToken': 'string' } Response Structure (dict) -- Patches (list) -- Each entry in the array is a structure containing: Title (string) KBId (string) Classification (string) Severity (string) State (string, such as "INSTALLED" or "FAILED") InstalledTime (DateTime) InstalledBy (string) (dict) -- Information about the state of a patch on a particular instance as it relates to the patch baseline used to patch the instance. Title (string) -- The title of the patch. KBId (string) -- The operating system-specific ID of the patch. Classification (string) -- The classification of the patch (for example, SecurityUpdates, Updates, CriticalUpdates). Severity (string) -- The severity of the patch (for example, Critical, Important, Moderate). State (string) -- The state of the patch on the instance, such as INSTALLED or FAILED. For descriptions of each patch state, see About patch compliance in the AWS Systems Manager User Guide . InstalledTime (datetime) -- The date/time the patch was installed on the instance. Note that not all operating systems provide this level of information. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken :return: { 'Patches': [ { 'Title': 'string', 'KBId': 'string', 'Classification': 'string', 'Severity': 'string', 'State': 'INSTALLED'|'INSTALLED_OTHER'|'INSTALLED_PENDING_REBOOT'|'INSTALLED_REJECTED'|'MISSING'|'NOT_APPLICABLE'|'FAILED', 'InstalledTime': datetime(2015, 1, 1) }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken """ pass def describe_inventory_deletions(DeletionId=None, NextToken=None, MaxResults=None): """ Describes a specific delete inventory operation. See also: AWS API Documentation Exceptions :example: response = client.describe_inventory_deletions( DeletionId='string', NextToken='string', MaxResults=123 ) :type DeletionId: string :param DeletionId: Specify the delete inventory ID for which you want information. This ID was returned by the DeleteInventory action. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'InventoryDeletions': [ { 'DeletionId': 'string', 'TypeName': 'string', 'DeletionStartTime': datetime(2015, 1, 1), 'LastStatus': 'InProgress'|'Complete', 'LastStatusMessage': 'string', 'DeletionSummary': { 'TotalCount': 123, 'RemainingCount': 123, 'SummaryItems': [ { 'Version': 'string', 'Count': 123, 'RemainingCount': 123 }, ] }, 'LastStatusUpdateTime': datetime(2015, 1, 1) }, ], 'NextToken': 'string' } Response Structure (dict) -- InventoryDeletions (list) -- A list of status items for deleted inventory. (dict) -- Status information returned by the DeleteInventory action. DeletionId (string) -- The deletion ID returned by the DeleteInventory action. TypeName (string) -- The name of the inventory data type. DeletionStartTime (datetime) -- The UTC timestamp when the delete operation started. LastStatus (string) -- The status of the operation. Possible values are InProgress and Complete. LastStatusMessage (string) -- Information about the status. DeletionSummary (dict) -- Information about the delete operation. For more information about this summary, see Understanding the delete inventory summary in the AWS Systems Manager User Guide . TotalCount (integer) -- The total number of items to delete. This count does not change during the delete operation. RemainingCount (integer) -- Remaining number of items to delete. SummaryItems (list) -- A list of counts and versions for deleted items. (dict) -- Either a count, remaining count, or a version number in a delete inventory summary. Version (string) -- The inventory type version. Count (integer) -- A count of the number of deleted items. RemainingCount (integer) -- The remaining number of items to delete. LastStatusUpdateTime (datetime) -- The UTC timestamp of when the last status report. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDeletionIdException SSM.Client.exceptions.InvalidNextToken :return: { 'InventoryDeletions': [ { 'DeletionId': 'string', 'TypeName': 'string', 'DeletionStartTime': datetime(2015, 1, 1), 'LastStatus': 'InProgress'|'Complete', 'LastStatusMessage': 'string', 'DeletionSummary': { 'TotalCount': 123, 'RemainingCount': 123, 'SummaryItems': [ { 'Version': 'string', 'Count': 123, 'RemainingCount': 123 }, ] }, 'LastStatusUpdateTime': datetime(2015, 1, 1) }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDeletionIdException SSM.Client.exceptions.InvalidNextToken """ pass def describe_maintenance_window_execution_task_invocations(WindowExecutionId=None, TaskId=None, Filters=None, MaxResults=None, NextToken=None): """ Retrieves the individual task executions (one per target) for a particular task run as part of a maintenance window execution. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_window_execution_task_invocations( WindowExecutionId='string', TaskId='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type WindowExecutionId: string :param WindowExecutionId: [REQUIRED]\nThe ID of the maintenance window execution the task is part of.\n :type TaskId: string :param TaskId: [REQUIRED]\nThe ID of the specific task in the maintenance window task that should be retrieved.\n :type Filters: list :param Filters: Optional filters used to scope down the returned task invocations. The supported filter key is STATUS with the corresponding values PENDING, IN_PROGRESS, SUCCESS, FAILED, TIMED_OUT, CANCELLING, and CANCELLED.\n\n(dict) --Filter used in the request. Supported filter keys are Name and Enabled.\n\nKey (string) --The name of the filter.\n\nValues (list) --The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'WindowExecutionTaskInvocationIdentities': [ { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'InvocationId': 'string', 'ExecutionId': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'Parameters': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'OwnerInformation': 'string', 'WindowTargetId': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- WindowExecutionTaskInvocationIdentities (list) -- Information about the task invocation results per invocation. (dict) -- Describes the information about a task invocation for a particular target as part of a task execution performed as part of a maintenance window execution. WindowExecutionId (string) -- The ID of the maintenance window execution that ran the task. TaskExecutionId (string) -- The ID of the specific task execution in the maintenance window execution. InvocationId (string) -- The ID of the task invocation. ExecutionId (string) -- The ID of the action performed in the service that actually handled the task invocation. If the task type is RUN_COMMAND, this value is the command ID. TaskType (string) -- The task type. Parameters (string) -- The parameters that were provided for the invocation when it was run. Status (string) -- The status of the task invocation. StatusDetails (string) -- The details explaining the status of the task invocation. Only available for certain Status values. StartTime (datetime) -- The time the invocation started. EndTime (datetime) -- The time the invocation finished. OwnerInformation (string) -- User-provided value that was specified when the target was registered with the maintenance window. This was also included in any CloudWatch events raised during the task invocation. WindowTargetId (string) -- The ID of the target definition in this maintenance window the invocation was performed for. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowExecutionTaskInvocationIdentities': [ { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'InvocationId': 'string', 'ExecutionId': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'Parameters': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'OwnerInformation': 'string', 'WindowTargetId': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError """ pass def describe_maintenance_window_execution_tasks(WindowExecutionId=None, Filters=None, MaxResults=None, NextToken=None): """ For a given maintenance window execution, lists the tasks that were run. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_window_execution_tasks( WindowExecutionId='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type WindowExecutionId: string :param WindowExecutionId: [REQUIRED]\nThe ID of the maintenance window execution whose task executions should be retrieved.\n :type Filters: list :param Filters: Optional filters used to scope down the returned tasks. The supported filter key is STATUS with the corresponding values PENDING, IN_PROGRESS, SUCCESS, FAILED, TIMED_OUT, CANCELLING, and CANCELLED.\n\n(dict) --Filter used in the request. Supported filter keys are Name and Enabled.\n\nKey (string) --The name of the filter.\n\nValues (list) --The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'WindowExecutionTaskIdentities': [ { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'TaskArn': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA' }, ], 'NextToken': 'string' } Response Structure (dict) -- WindowExecutionTaskIdentities (list) -- Information about the task executions. (dict) -- Information about a task execution performed as part of a maintenance window execution. WindowExecutionId (string) -- The ID of the maintenance window execution that ran the task. TaskExecutionId (string) -- The ID of the specific task execution in the maintenance window execution. Status (string) -- The status of the task execution. StatusDetails (string) -- The details explaining the status of the task execution. Only available for certain status values. StartTime (datetime) -- The time the task execution started. EndTime (datetime) -- The time the task execution finished. TaskArn (string) -- The ARN of the task that ran. TaskType (string) -- The type of task that ran. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowExecutionTaskIdentities': [ { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'TaskArn': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError """ pass def describe_maintenance_window_executions(WindowId=None, Filters=None, MaxResults=None, NextToken=None): """ Lists the executions of a maintenance window. This includes information about when the maintenance window was scheduled to be active, and information about tasks registered and run with the maintenance window. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_window_executions( WindowId='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window whose executions should be retrieved.\n :type Filters: list :param Filters: Each entry in the array is a structure containing:\nKey (string, between 1 and 128 characters)\nValues (array of strings, each string is between 1 and 256 characters)\nThe supported Keys are ExecutedBefore and ExecutedAfter with the value being a date/time string such as 2016-11-04T05:00:00Z.\n\n(dict) --Filter used in the request. Supported filter keys are Name and Enabled.\n\nKey (string) --The name of the filter.\n\nValues (list) --The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'WindowExecutions': [ { 'WindowId': 'string', 'WindowExecutionId': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1) }, ], 'NextToken': 'string' } Response Structure (dict) -- WindowExecutions (list) -- Information about the maintenance window executions. (dict) -- Describes the information about an execution of a maintenance window. WindowId (string) -- The ID of the maintenance window. WindowExecutionId (string) -- The ID of the maintenance window execution. Status (string) -- The status of the execution. StatusDetails (string) -- The details explaining the Status. Only available for certain status values. StartTime (datetime) -- The time the execution started. EndTime (datetime) -- The time the execution finished. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'WindowExecutions': [ { 'WindowId': 'string', 'WindowExecutionId': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1) }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError """ pass def describe_maintenance_window_schedule(WindowId=None, Targets=None, ResourceType=None, Filters=None, MaxResults=None, NextToken=None): """ Retrieves information about upcoming executions of a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_window_schedule( WindowId='string', Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], ResourceType='INSTANCE'|'RESOURCE_GROUP', Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type WindowId: string :param WindowId: The ID of the maintenance window to retrieve information about. :type Targets: list :param Targets: The instance ID or key/value pair to retrieve information about.\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type ResourceType: string :param ResourceType: The type of resource you want to retrieve information about. For example, 'INSTANCE'. :type Filters: list :param Filters: Filters used to limit the range of results. For example, you can limit maintenance window executions to only those scheduled before or after a certain date and time.\n\n(dict) --Defines a filter used in Patch Manager APIs.\n\nKey (string) --The key for the filter.\n\nValues (list) --The value for the filter.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'ScheduledWindowExecutions': [ { 'WindowId': 'string', 'Name': 'string', 'ExecutionTime': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- ScheduledWindowExecutions (list) -- Information about maintenance window executions scheduled for the specified time range. (dict) -- Information about a scheduled execution for a maintenance window. WindowId (string) -- The ID of the maintenance window to be run. Name (string) -- The name of the maintenance window to be run. ExecutionTime (string) -- The time, in ISO-8601 Extended format, that the maintenance window is scheduled to be run. NextToken (string) -- The token for the next set of items to return. (You use this token in the next call.) Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.DoesNotExistException :return: { 'ScheduledWindowExecutions': [ { 'WindowId': 'string', 'Name': 'string', 'ExecutionTime': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.DoesNotExistException """ pass def describe_maintenance_window_targets(WindowId=None, Filters=None, MaxResults=None, NextToken=None): """ Lists the targets registered with the maintenance window. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_window_targets( WindowId='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window whose targets should be retrieved.\n :type Filters: list :param Filters: Optional filters that can be used to narrow down the scope of the returned window targets. The supported filter keys are Type, WindowTargetId and OwnerInformation.\n\n(dict) --Filter used in the request. Supported filter keys are Name and Enabled.\n\nKey (string) --The name of the filter.\n\nValues (list) --The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Targets': [ { 'WindowId': 'string', 'WindowTargetId': 'string', 'ResourceType': 'INSTANCE'|'RESOURCE_GROUP', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'OwnerInformation': 'string', 'Name': 'string', 'Description': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Targets (list) -- Information about the targets in the maintenance window. (dict) -- The target registered with the maintenance window. WindowId (string) -- The ID of the maintenance window to register the target with. WindowTargetId (string) -- The ID of the target. ResourceType (string) -- The type of target that is being registered with the maintenance window. Targets (list) -- The targets, either instances or tags. Specify instances using the following format: Key=instanceids,Values=<instanceid1>,<instanceid2> Tags are specified using the following format: Key=<tag name>,Values=<tag value> . (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- OwnerInformation (string) -- A user-provided value that will be included in any CloudWatch events that are raised while running tasks for these targets in this maintenance window. Name (string) -- The name for the maintenance window target. Description (string) -- A description for the target. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'Targets': [ { 'WindowId': 'string', 'WindowTargetId': 'string', 'ResourceType': 'INSTANCE'|'RESOURCE_GROUP', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'OwnerInformation': 'string', 'Name': 'string', 'Description': 'string' }, ], 'NextToken': 'string' } :returns: ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` """ pass def describe_maintenance_window_tasks(WindowId=None, Filters=None, MaxResults=None, NextToken=None): """ Lists the tasks in a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_window_tasks( WindowId='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window whose tasks should be retrieved.\n :type Filters: list :param Filters: Optional filters used to narrow down the scope of the returned tasks. The supported filter keys are WindowTaskId, TaskArn, Priority, and TaskType.\n\n(dict) --Filter used in the request. Supported filter keys are Name and Enabled.\n\nKey (string) --The name of the filter.\n\nValues (list) --The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Tasks': [ { 'WindowId': 'string', 'WindowTaskId': 'string', 'TaskArn': 'string', 'Type': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TaskParameters': { 'string': { 'Values': [ 'string', ] } }, 'Priority': 123, 'LoggingInfo': { 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, 'ServiceRoleArn': 'string', 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Name': 'string', 'Description': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Tasks (list) -- Information about the tasks in the maintenance window. (dict) -- Information about a task defined for a maintenance window. WindowId (string) -- The ID of the maintenance window where the task is registered. WindowTaskId (string) -- The task ID. TaskArn (string) -- The resource that the task uses during execution. For RUN_COMMAND and AUTOMATION task types, TaskArn is the Systems Manager document name or ARN. For LAMBDA tasks, it\'s the function name or ARN. For STEP_FUNCTIONS tasks, it\'s the state machine ARN. Type (string) -- The type of task. The type can be one of the following: RUN_COMMAND, AUTOMATION, LAMBDA, or STEP_FUNCTIONS. Targets (list) -- The targets (either instances or tags). Instances are specified using Key=instanceids,Values=<instanceid1>,<instanceid2>. Tags are specified using Key=<tag name>,Values=<tag value>. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TaskParameters (dict) -- The parameters that should be passed to the task when it is run. Note TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . (string) -- (dict) -- Defines the values for a task parameter. Values (list) -- This field contains an array of 0 or more strings, each 1 to 255 characters in length. (string) -- Priority (integer) -- The priority of the task in the maintenance window. The lower the number, the higher the priority. Tasks that have the same priority are scheduled in parallel. LoggingInfo (dict) -- Information about an S3 bucket to write task-level logs to. Note LoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . S3BucketName (string) -- The name of an S3 bucket where execution logs are stored . S3KeyPrefix (string) -- (Optional) The S3 bucket subfolder. S3Region (string) -- The Region where the S3 bucket is located. ServiceRoleArn (string) -- The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks. MaxConcurrency (string) -- The maximum number of targets this task can be run for, in parallel. MaxErrors (string) -- The maximum number of errors allowed before this task stops being scheduled. Name (string) -- The task name. Description (string) -- A description of the task. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'Tasks': [ { 'WindowId': 'string', 'WindowTaskId': 'string', 'TaskArn': 'string', 'Type': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TaskParameters': { 'string': { 'Values': [ 'string', ] } }, 'Priority': 123, 'LoggingInfo': { 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, 'ServiceRoleArn': 'string', 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Name': 'string', 'Description': 'string' }, ], 'NextToken': 'string' } :returns: ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` """ pass def describe_maintenance_windows(Filters=None, MaxResults=None, NextToken=None): """ Retrieves the maintenance windows in an AWS account. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_windows( Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type Filters: list :param Filters: Optional filters used to narrow down the scope of the returned maintenance windows. Supported filter keys are Name and Enabled .\n\n(dict) --Filter used in the request. Supported filter keys are Name and Enabled.\n\nKey (string) --The name of the filter.\n\nValues (list) --The filter values.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'WindowIdentities': [ { 'WindowId': 'string', 'Name': 'string', 'Description': 'string', 'Enabled': True|False, 'Duration': 123, 'Cutoff': 123, 'Schedule': 'string', 'ScheduleTimezone': 'string', 'EndDate': 'string', 'StartDate': 'string', 'NextExecutionTime': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- WindowIdentities (list) -- Information about the maintenance windows. (dict) -- Information about the maintenance window. WindowId (string) -- The ID of the maintenance window. Name (string) -- The name of the maintenance window. Description (string) -- A description of the maintenance window. Enabled (boolean) -- Indicates whether the maintenance window is enabled. Duration (integer) -- The duration of the maintenance window in hours. Cutoff (integer) -- The number of hours before the end of the maintenance window that Systems Manager stops scheduling new tasks for execution. Schedule (string) -- The schedule of the maintenance window in the form of a cron or rate expression. ScheduleTimezone (string) -- The time zone that the scheduled maintenance window executions are based on, in Internet Assigned Numbers Authority (IANA) format. EndDate (string) -- The date and time, in ISO-8601 Extended format, for when the maintenance window is scheduled to become inactive. StartDate (string) -- The date and time, in ISO-8601 Extended format, for when the maintenance window is scheduled to become active. NextExecutionTime (string) -- The next time the maintenance window will actually run, taking into account any specified times for the maintenance window to become active or inactive. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'WindowIdentities': [ { 'WindowId': 'string', 'Name': 'string', 'Description': 'string', 'Enabled': True|False, 'Duration': 123, 'Cutoff': 123, 'Schedule': 'string', 'ScheduleTimezone': 'string', 'EndDate': 'string', 'StartDate': 'string', 'NextExecutionTime': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError """ pass def describe_maintenance_windows_for_target(Targets=None, ResourceType=None, MaxResults=None, NextToken=None): """ Retrieves information about the maintenance window targets or tasks that an instance is associated with. See also: AWS API Documentation Exceptions :example: response = client.describe_maintenance_windows_for_target( Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], ResourceType='INSTANCE'|'RESOURCE_GROUP', MaxResults=123, NextToken='string' ) :type Targets: list :param Targets: [REQUIRED]\nThe instance ID or key/value pair to retrieve information about.\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type ResourceType: string :param ResourceType: [REQUIRED]\nThe type of resource you want to retrieve information about. For example, 'INSTANCE'.\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'WindowIdentities': [ { 'WindowId': 'string', 'Name': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- WindowIdentities (list) -- Information about the maintenance window targets and tasks an instance is associated with. (dict) -- The maintenance window to which the specified target belongs. WindowId (string) -- The ID of the maintenance window. Name (string) -- The name of the maintenance window. NextToken (string) -- The token for the next set of items to return. (You use this token in the next call.) Exceptions SSM.Client.exceptions.InternalServerError :return: { 'WindowIdentities': [ { 'WindowId': 'string', 'Name': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError """ pass def describe_ops_items(OpsItemFilters=None, MaxResults=None, NextToken=None): """ Query a set of OpsItems. You must have permission in AWS Identity and Access Management (IAM) to query a list of OpsItems. For more information, see Getting started with OpsCenter in the AWS Systems Manager User Guide . Operations engineers and IT professionals use OpsCenter to view, investigate, and remediate operational issues impacting the performance and health of their AWS resources. For more information, see AWS Systems Manager OpsCenter in the AWS Systems Manager User Guide . See also: AWS API Documentation Exceptions :example: response = client.describe_ops_items( OpsItemFilters=[ { 'Key': 'Status'|'CreatedBy'|'Source'|'Priority'|'Title'|'OpsItemId'|'CreatedTime'|'LastModifiedTime'|'OperationalData'|'OperationalDataKey'|'OperationalDataValue'|'ResourceId'|'AutomationId'|'Category'|'Severity', 'Values': [ 'string', ], 'Operator': 'Equal'|'Contains'|'GreaterThan'|'LessThan' }, ], MaxResults=123, NextToken='string' ) :type OpsItemFilters: list :param OpsItemFilters: One or more filters to limit the response.\n\nKey: CreatedTime Operations: GreaterThan, LessThan\nKey: LastModifiedBy Operations: Contains, Equals\nKey: LastModifiedTime Operations: GreaterThan, LessThan\nKey: Priority Operations: Equals\nKey: Source Operations: Contains, Equals\nKey: Status Operations: Equals\nKey: Title Operations: Contains\nKey: OperationalData* Operations: Equals\nKey: OperationalDataKey Operations: Equals\nKey: OperationalDataValue Operations: Equals, Contains\nKey: OpsItemId Operations: Equals\nKey: ResourceId Operations: Contains\nKey: AutomationId Operations: Equals\n\n*If you filter the response by using the OperationalData operator, specify a key-value pair by using the following JSON format: {'key':'key_name','value':'a_value'}\n\n(dict) --Describes an OpsItem filter.\n\nKey (string) -- [REQUIRED]The name of the filter.\n\nValues (list) -- [REQUIRED]The filter value.\n\n(string) --\n\n\nOperator (string) -- [REQUIRED]The operator used by the filter call.\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'NextToken': 'string', 'OpsItemSummaries': [ { 'CreatedBy': 'string', 'CreatedTime': datetime(2015, 1, 1), 'LastModifiedBy': 'string', 'LastModifiedTime': datetime(2015, 1, 1), 'Priority': 123, 'Source': 'string', 'Status': 'Open'|'InProgress'|'Resolved', 'OpsItemId': 'string', 'Title': 'string', 'OperationalData': { 'string': { 'Value': 'string', 'Type': 'SearchableString'|'String' } }, 'Category': 'string', 'Severity': 'string' }, ] } Response Structure (dict) -- NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. OpsItemSummaries (list) -- A list of OpsItems. (dict) -- A count of OpsItems. CreatedBy (string) -- The Amazon Resource Name (ARN) of the IAM entity that created the OpsItem. CreatedTime (datetime) -- The date and time the OpsItem was created. LastModifiedBy (string) -- The Amazon Resource Name (ARN) of the IAM entity that created the OpsItem. LastModifiedTime (datetime) -- The date and time the OpsItem was last updated. Priority (integer) -- The importance of this OpsItem in relation to other OpsItems in the system. Source (string) -- The impacted AWS resource. Status (string) -- The OpsItem status. Status can be Open , In Progress , or Resolved . OpsItemId (string) -- The ID of the OpsItem. Title (string) -- A short heading that describes the nature of the OpsItem and the impacted resource. OperationalData (dict) -- Operational data is custom data that provides useful reference details about the OpsItem. (string) -- (dict) -- An object that defines the value of the key and its type in the OperationalData map. Value (string) -- The value of the OperationalData key. Type (string) -- The type of key-value pair. Valid types include SearchableString and String . Category (string) -- A list of OpsItems by category. Severity (string) -- A list of OpsItems by severity. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'NextToken': 'string', 'OpsItemSummaries': [ { 'CreatedBy': 'string', 'CreatedTime': datetime(2015, 1, 1), 'LastModifiedBy': 'string', 'LastModifiedTime': datetime(2015, 1, 1), 'Priority': 123, 'Source': 'string', 'Status': 'Open'|'InProgress'|'Resolved', 'OpsItemId': 'string', 'Title': 'string', 'OperationalData': { 'string': { 'Value': 'string', 'Type': 'SearchableString'|'String' } }, 'Category': 'string', 'Severity': 'string' }, ] } :returns: SSM.Client.exceptions.InternalServerError """ pass def describe_parameters(Filters=None, ParameterFilters=None, MaxResults=None, NextToken=None): """ Get information about a parameter. See also: AWS API Documentation Exceptions :example: response = client.describe_parameters( Filters=[ { 'Key': 'Name'|'Type'|'KeyId', 'Values': [ 'string', ] }, ], ParameterFilters=[ { 'Key': 'string', 'Option': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type Filters: list :param Filters: This data type is deprecated. Instead, use ParameterFilters .\n\n(dict) --This data type is deprecated. Instead, use ParameterStringFilter .\n\nKey (string) -- [REQUIRED]The name of the filter.\n\nValues (list) -- [REQUIRED]The filter values.\n\n(string) --\n\n\n\n\n\n :type ParameterFilters: list :param ParameterFilters: Filters to limit the request results.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nWarning\nThe ParameterStringFilter object is used by the DescribeParameters and GetParametersByPath API actions. However, not all of the pattern values listed for Key can be used with both actions.\nFor DescribeActions , all of the listed patterns are valid, with the exception of Label .\nFor GetParametersByPath , the following patterns listed for Key are not valid: Name , Path , and Tier .\nFor examples of CLI commands demonstrating valid parameter filter constructions, see Searching for Systems Manager parameters in the AWS Systems Manager User Guide .\n\n\nKey (string) -- [REQUIRED]The name of the filter.\n\nOption (string) --For all filters used with DescribeParameters , valid options include Equals and BeginsWith . The Name filter additionally supports the Contains option. (Exception: For filters using the key Path , valid options include Recursive and OneLevel .)\nFor filters used with GetParametersByPath , valid options include Equals and BeginsWith . (Exception: For filters using the key Label , the only valid option is Equals .)\n\nValues (list) --The value you want to search for.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'KeyId': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'Description': 'string', 'AllowedPattern': 'string', 'Version': 123, 'Tier': 'Standard'|'Advanced'|'Intelligent-Tiering', 'Policies': [ { 'PolicyText': 'string', 'PolicyType': 'string', 'PolicyStatus': 'string' }, ], 'DataType': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Parameters (list) -- Parameters returned by the request. (dict) -- Metadata includes information like the ARN of the last user and the date/time the parameter was last used. Name (string) -- The parameter name. Type (string) -- The type of parameter. Valid parameter types include the following: String , StringList , and SecureString . KeyId (string) -- The ID of the query key used for this parameter. LastModifiedDate (datetime) -- Date the parameter was last changed or updated. LastModifiedUser (string) -- Amazon Resource Name (ARN) of the AWS user who last changed the parameter. Description (string) -- Description of the parameter actions. AllowedPattern (string) -- A parameter name can include only the following letters and symbols. a-zA-Z0-9_.- Version (integer) -- The parameter version. Tier (string) -- The parameter tier. Policies (list) -- A list of policies associated with a parameter. (dict) -- One or more policies assigned to a parameter. PolicyText (string) -- The JSON text of the policy. PolicyType (string) -- The type of policy. Parameter Store supports the following policy types: Expiration, ExpirationNotification, and NoChangeNotification. PolicyStatus (string) -- The status of the policy. Policies report the following statuses: Pending (the policy has not been enforced or applied yet), Finished (the policy was applied), Failed (the policy was not applied), or InProgress (the policy is being applied now). DataType (string) -- The data type of the parameter, such as text or aws:ec2:image . The default is text . NextToken (string) -- The token to use when requesting the next set of items. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidFilterOption SSM.Client.exceptions.InvalidFilterValue SSM.Client.exceptions.InvalidNextToken :return: { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'KeyId': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'Description': 'string', 'AllowedPattern': 'string', 'Version': 123, 'Tier': 'Standard'|'Advanced'|'Intelligent-Tiering', 'Policies': [ { 'PolicyText': 'string', 'PolicyType': 'string', 'PolicyStatus': 'string' }, ], 'DataType': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidFilterOption SSM.Client.exceptions.InvalidFilterValue SSM.Client.exceptions.InvalidNextToken """ pass def describe_patch_baselines(Filters=None, MaxResults=None, NextToken=None): """ Lists the patch baselines in your AWS account. See also: AWS API Documentation Exceptions :example: response = client.describe_patch_baselines( Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type Filters: list :param Filters: Each element in the array is a structure containing:\nKey: (string, 'NAME_PREFIX' or 'OWNER')\nValue: (array of strings, exactly 1 entry, between 1 and 255 characters)\n\n(dict) --Defines a filter used in Patch Manager APIs.\n\nKey (string) --The key for the filter.\n\nValues (list) --The value for the filter.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of patch baselines to return (per page). :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'BaselineIdentities': [ { 'BaselineId': 'string', 'BaselineName': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'BaselineDescription': 'string', 'DefaultBaseline': True|False }, ], 'NextToken': 'string' } Response Structure (dict) -- BaselineIdentities (list) -- An array of PatchBaselineIdentity elements. (dict) -- Defines the basic information about a patch baseline. BaselineId (string) -- The ID of the patch baseline. BaselineName (string) -- The name of the patch baseline. OperatingSystem (string) -- Defines the operating system the patch baseline applies to. The Default value is WINDOWS. BaselineDescription (string) -- The description of the patch baseline. DefaultBaseline (boolean) -- Whether this is the default baseline. Note that Systems Manager supports creating multiple default patch baselines. For example, you can create a default patch baseline for each operating system. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'BaselineIdentities': [ { 'BaselineId': 'string', 'BaselineName': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'BaselineDescription': 'string', 'DefaultBaseline': True|False }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError """ pass def describe_patch_group_state(PatchGroup=None): """ Returns high-level aggregated patch compliance state for a patch group. See also: AWS API Documentation Exceptions :example: response = client.describe_patch_group_state( PatchGroup='string' ) :type PatchGroup: string :param PatchGroup: [REQUIRED]\nThe name of the patch group whose patch snapshot should be retrieved.\n :rtype: dict ReturnsResponse Syntax{ 'Instances': 123, 'InstancesWithInstalledPatches': 123, 'InstancesWithInstalledOtherPatches': 123, 'InstancesWithInstalledPendingRebootPatches': 123, 'InstancesWithInstalledRejectedPatches': 123, 'InstancesWithMissingPatches': 123, 'InstancesWithFailedPatches': 123, 'InstancesWithNotApplicablePatches': 123, 'InstancesWithUnreportedNotApplicablePatches': 123 } Response Structure (dict) -- Instances (integer) --The number of instances in the patch group. InstancesWithInstalledPatches (integer) --The number of instances with installed patches. InstancesWithInstalledOtherPatches (integer) --The number of instances with patches installed that aren\'t defined in the patch baseline. InstancesWithInstalledPendingRebootPatches (integer) --The number of instances with patches installed by Patch Manager that have not been rebooted after the patch installation. The status of these instances is NON_COMPLIANT. InstancesWithInstalledRejectedPatches (integer) --The number of instances with patches installed that are specified in a RejectedPatches list. Patches with a status of INSTALLED_REJECTED were typically installed before they were added to a RejectedPatches list. Note If ALLOW_AS_DEPENDENCY is the specified option for RejectedPatchesAction, the value of InstancesWithInstalledRejectedPatches will always be 0 (zero). InstancesWithMissingPatches (integer) --The number of instances with missing patches from the patch baseline. InstancesWithFailedPatches (integer) --The number of instances with patches from the patch baseline that failed to install. InstancesWithNotApplicablePatches (integer) --The number of instances with patches that aren\'t applicable. InstancesWithUnreportedNotApplicablePatches (integer) --The number of instances with NotApplicable patches beyond the supported limit, which are not reported by name to Systems Manager Inventory. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken :return: { 'Instances': 123, 'InstancesWithInstalledPatches': 123, 'InstancesWithInstalledOtherPatches': 123, 'InstancesWithInstalledPendingRebootPatches': 123, 'InstancesWithInstalledRejectedPatches': 123, 'InstancesWithMissingPatches': 123, 'InstancesWithFailedPatches': 123, 'InstancesWithNotApplicablePatches': 123, 'InstancesWithUnreportedNotApplicablePatches': 123 } """ pass def describe_patch_groups(MaxResults=None, Filters=None, NextToken=None): """ Lists all patch groups that have been registered with patch baselines. See also: AWS API Documentation Exceptions :example: response = client.describe_patch_groups( MaxResults=123, Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], NextToken='string' ) :type MaxResults: integer :param MaxResults: The maximum number of patch groups to return (per page). :type Filters: list :param Filters: One or more filters. Use a filter to return a more specific list of results.\n\n(dict) --Defines a filter used in Patch Manager APIs.\n\nKey (string) --The key for the filter.\n\nValues (list) --The value for the filter.\n\n(string) --\n\n\n\n\n\n :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Mappings': [ { 'PatchGroup': 'string', 'BaselineIdentity': { 'BaselineId': 'string', 'BaselineName': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'BaselineDescription': 'string', 'DefaultBaseline': True|False } }, ], 'NextToken': 'string' } Response Structure (dict) -- Mappings (list) -- Each entry in the array contains: PatchGroup: string (between 1 and 256 characters, Regex: ^([p{L}p{Z}p{N}_.:/=+-@]*)$) PatchBaselineIdentity: A PatchBaselineIdentity element. (dict) -- The mapping between a patch group and the patch baseline the patch group is registered with. PatchGroup (string) -- The name of the patch group registered with the patch baseline. BaselineIdentity (dict) -- The patch baseline the patch group is registered with. BaselineId (string) -- The ID of the patch baseline. BaselineName (string) -- The name of the patch baseline. OperatingSystem (string) -- Defines the operating system the patch baseline applies to. The Default value is WINDOWS. BaselineDescription (string) -- The description of the patch baseline. DefaultBaseline (boolean) -- Whether this is the default baseline. Note that Systems Manager supports creating multiple default patch baselines. For example, you can create a default patch baseline for each operating system. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'Mappings': [ { 'PatchGroup': 'string', 'BaselineIdentity': { 'BaselineId': 'string', 'BaselineName': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'BaselineDescription': 'string', 'DefaultBaseline': True|False } }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError """ pass def describe_patch_properties(OperatingSystem=None, Property=None, PatchSet=None, MaxResults=None, NextToken=None): """ Lists the properties of available patches organized by product, product family, classification, severity, and other properties of available patches. You can use the reported properties in the filters you specify in requests for actions such as CreatePatchBaseline , UpdatePatchBaseline , DescribeAvailablePatches , and DescribePatchBaselines . The following section lists the properties that can be used in filters for each major operating system type: Valid properties: PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, MSRC_SEVERITY Valid properties: PRODUCT, CLASSIFICATION, SEVERITY Valid properties: PRODUCT, CLASSIFICATION, SEVERITY Valid properties: PRODUCT, PRIORITY Valid properties: PRODUCT, CLASSIFICATION, SEVERITY Valid properties: PRODUCT, CLASSIFICATION, SEVERITY Valid properties: PRODUCT, CLASSIFICATION, SEVERITY See also: AWS API Documentation Exceptions :example: response = client.describe_patch_properties( OperatingSystem='WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', Property='PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PRIORITY'|'SEVERITY', PatchSet='OS'|'APPLICATION', MaxResults=123, NextToken='string' ) :type OperatingSystem: string :param OperatingSystem: [REQUIRED]\nThe operating system type for which to list patches.\n :type Property: string :param Property: [REQUIRED]\nThe patch property for which you want to view patch details.\n :type PatchSet: string :param PatchSet: Indicates whether to list patches for the Windows operating system or for Microsoft applications. Not applicable for Linux operating systems. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Properties': [ { 'string': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Properties (list) -- A list of the properties for patches matching the filter request parameters. (dict) -- (string) -- (string) -- NextToken (string) -- The token for the next set of items to return. (You use this token in the next call.) Exceptions SSM.Client.exceptions.InternalServerError :return: { 'Properties': [ { 'string': 'string' }, ], 'NextToken': 'string' } :returns: (dict) -- (string) -- (string) -- """ pass def describe_sessions(State=None, MaxResults=None, NextToken=None, Filters=None): """ Retrieves a list of all active sessions (both connected and disconnected) or terminated sessions from the past 30 days. See also: AWS API Documentation Exceptions :example: response = client.describe_sessions( State='Active'|'History', MaxResults=123, NextToken='string', Filters=[ { 'key': 'InvokedAfter'|'InvokedBefore'|'Target'|'Owner'|'Status', 'value': 'string' }, ] ) :type State: string :param State: [REQUIRED]\nThe session status to retrieve a list of sessions for. For example, 'Active'.\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type Filters: list :param Filters: One or more filters to limit the type of sessions returned by the request.\n\n(dict) --Describes a filter for Session Manager information.\n\nkey (string) -- [REQUIRED]The name of the filter.\n\nvalue (string) -- [REQUIRED]The filter value. Valid values for each filter key are as follows:\n\nInvokedAfter: Specify a timestamp to limit your results. For example, specify 2018-08-29T00:00:00Z to see sessions that started August 29, 2018, and later.\nInvokedBefore: Specify a timestamp to limit your results. For example, specify 2018-08-29T00:00:00Z to see sessions that started before August 29, 2018.\nTarget: Specify an instance to which session connections have been made.\nOwner: Specify an AWS user account to see a list of sessions started by that user.\nStatus: Specify a valid session status to see a list of all sessions with that status. Status values you can specify include:\nConnected\nConnecting\nDisconnected\nTerminated\nTerminating\nFailed\n\n\n\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'Sessions': [ { 'SessionId': 'string', 'Target': 'string', 'Status': 'Connected'|'Connecting'|'Disconnected'|'Terminated'|'Terminating'|'Failed', 'StartDate': datetime(2015, 1, 1), 'EndDate': datetime(2015, 1, 1), 'DocumentName': 'string', 'Owner': 'string', 'Details': 'string', 'OutputUrl': { 'S3OutputUrl': 'string', 'CloudWatchOutputUrl': 'string' } }, ], 'NextToken': 'string' } Response Structure (dict) -- Sessions (list) -- A list of sessions meeting the request parameters. (dict) -- Information about a Session Manager connection to an instance. SessionId (string) -- The ID of the session. Target (string) -- The instance that the Session Manager session connected to. Status (string) -- The status of the session. For example, "Connected" or "Terminated". StartDate (datetime) -- The date and time, in ISO-8601 Extended format, when the session began. EndDate (datetime) -- The date and time, in ISO-8601 Extended format, when the session was terminated. DocumentName (string) -- The name of the Session Manager SSM document used to define the parameters and plugin settings for the session. For example, SSM-SessionManagerRunShell . Owner (string) -- The ID of the AWS user account that started the session. Details (string) -- Reserved for future use. OutputUrl (dict) -- Reserved for future use. S3OutputUrl (string) -- Reserved for future use. CloudWatchOutputUrl (string) -- Reserved for future use. NextToken (string) -- The token for the next set of items to return. (You received this token from a previous call.) Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidNextToken :return: { 'Sessions': [ { 'SessionId': 'string', 'Target': 'string', 'Status': 'Connected'|'Connecting'|'Disconnected'|'Terminated'|'Terminating'|'Failed', 'StartDate': datetime(2015, 1, 1), 'EndDate': datetime(2015, 1, 1), 'DocumentName': 'string', 'Owner': 'string', 'Details': 'string', 'OutputUrl': { 'S3OutputUrl': 'string', 'CloudWatchOutputUrl': 'string' } }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidNextToken """ pass def generate_presigned_url(ClientMethod=None, Params=None, ExpiresIn=None, HttpMethod=None): """ Generate a presigned url given a client, its method, and arguments :type ClientMethod: string :param ClientMethod: The client method to presign for :type Params: dict :param Params: The parameters normally passed to\nClientMethod. :type ExpiresIn: int :param ExpiresIn: The number of seconds the presigned url is valid\nfor. By default it expires in an hour (3600 seconds) :type HttpMethod: string :param HttpMethod: The http method to use on the generated url. By\ndefault, the http method is whatever is used in the method\'s model. """ pass def get_automation_execution(AutomationExecutionId=None): """ Get detailed information about a particular Automation execution. See also: AWS API Documentation Exceptions :example: response = client.get_automation_execution( AutomationExecutionId='string' ) :type AutomationExecutionId: string :param AutomationExecutionId: [REQUIRED]\nThe unique identifier for an existing automation execution to examine. The execution ID is returned by StartAutomationExecution when the execution of an Automation document is initiated.\n :rtype: dict ReturnsResponse Syntax{ 'AutomationExecution': { 'AutomationExecutionId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'AutomationExecutionStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'StepExecutions': [ { 'StepName': 'string', 'Action': 'string', 'TimeoutSeconds': 123, 'OnFailure': 'string', 'MaxAttempts': 123, 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'StepStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'ResponseCode': 'string', 'Inputs': { 'string': 'string' }, 'Outputs': { 'string': [ 'string', ] }, 'Response': 'string', 'FailureMessage': 'string', 'FailureDetails': { 'FailureStage': 'string', 'FailureType': 'string', 'Details': { 'string': [ 'string', ] } }, 'StepExecutionId': 'string', 'OverriddenParameters': { 'string': [ 'string', ] }, 'IsEnd': True|False, 'NextStep': 'string', 'IsCritical': True|False, 'ValidNextSteps': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetLocation': { 'Accounts': [ 'string', ], 'Regions': [ 'string', ], 'TargetLocationMaxConcurrency': 'string', 'TargetLocationMaxErrors': 'string', 'ExecutionRoleName': 'string' } }, ], 'StepExecutionsTruncated': True|False, 'Parameters': { 'string': [ 'string', ] }, 'Outputs': { 'string': [ 'string', ] }, 'FailureMessage': 'string', 'Mode': 'Auto'|'Interactive', 'ParentAutomationExecutionId': 'string', 'ExecutedBy': 'string', 'CurrentStepName': 'string', 'CurrentAction': 'string', 'TargetParameterName': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetMaps': [ { 'string': [ 'string', ] }, ], 'ResolvedTargets': { 'ParameterValues': [ 'string', ], 'Truncated': True|False }, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Target': 'string', 'TargetLocations': [ { 'Accounts': [ 'string', ], 'Regions': [ 'string', ], 'TargetLocationMaxConcurrency': 'string', 'TargetLocationMaxErrors': 'string', 'ExecutionRoleName': 'string' }, ], 'ProgressCounters': { 'TotalSteps': 123, 'SuccessSteps': 123, 'FailedSteps': 123, 'CancelledSteps': 123, 'TimedOutSteps': 123 } } } Response Structure (dict) -- AutomationExecution (dict) --Detailed information about the current state of an automation execution. AutomationExecutionId (string) --The execution ID. DocumentName (string) --The name of the Automation document used during the execution. DocumentVersion (string) --The version of the document to use during execution. ExecutionStartTime (datetime) --The time the execution started. ExecutionEndTime (datetime) --The time the execution finished. AutomationExecutionStatus (string) --The execution status of the Automation. StepExecutions (list) --A list of details about the current state of all steps that comprise an execution. An Automation document contains a list of steps that are run in order. (dict) --Detailed information about an the execution state of an Automation step. StepName (string) --The name of this execution step. Action (string) --The action this step performs. The action determines the behavior of the step. TimeoutSeconds (integer) --The timeout seconds of the step. OnFailure (string) --The action to take if the step fails. The default value is Abort. MaxAttempts (integer) --The maximum number of tries to run the action of the step. The default value is 1. ExecutionStartTime (datetime) --If a step has begun execution, this contains the time the step started. If the step is in Pending status, this field is not populated. ExecutionEndTime (datetime) --If a step has finished execution, this contains the time the execution ended. If the step has not yet concluded, this field is not populated. StepStatus (string) --The execution status for this step. ResponseCode (string) --The response code returned by the execution of the step. Inputs (dict) --Fully-resolved values passed into the step before execution. (string) -- (string) -- Outputs (dict) --Returned values from the execution of the step. (string) -- (list) -- (string) -- Response (string) --A message associated with the response code for an execution. FailureMessage (string) --If a step failed, this message explains why the execution failed. FailureDetails (dict) --Information about the Automation failure. FailureStage (string) --The stage of the Automation execution when the failure occurred. The stages include the following: InputValidation, PreVerification, Invocation, PostVerification. FailureType (string) --The type of Automation failure. Failure types include the following: Action, Permission, Throttling, Verification, Internal. Details (dict) --Detailed information about the Automation step failure. (string) -- (list) -- (string) -- StepExecutionId (string) --The unique ID of a step execution. OverriddenParameters (dict) --A user-specified list of parameters to override when running a step. (string) -- (list) -- (string) -- IsEnd (boolean) --The flag which can be used to end automation no matter whether the step succeeds or fails. NextStep (string) --The next step after the step succeeds. IsCritical (boolean) --The flag which can be used to help decide whether the failure of current step leads to the Automation failure. ValidNextSteps (list) --Strategies used when step fails, we support Continue and Abort. Abort will fail the automation when the step fails. Continue will ignore the failure of current step and allow automation to run the next step. With conditional branching, we add step:stepName to support the automation to go to another specific step. (string) -- Targets (list) --The targets for the step execution. (dict) --An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) --User-defined criteria for sending commands that target instances that meet the criteria. Values (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TargetLocation (dict) --The combination of AWS Regions and accounts targeted by the current Automation execution. Accounts (list) --The AWS accounts targeted by the current Automation execution. (string) -- Regions (list) --The AWS Regions targeted by the current Automation execution. (string) -- TargetLocationMaxConcurrency (string) --The maximum number of AWS accounts and AWS regions allowed to run the Automation concurrently TargetLocationMaxErrors (string) --The maximum number of errors allowed before the system stops queueing additional Automation executions for the currently running Automation. ExecutionRoleName (string) --The Automation execution role used by the currently running Automation. StepExecutionsTruncated (boolean) --A boolean value that indicates if the response contains the full list of the Automation step executions. If true, use the DescribeAutomationStepExecutions API action to get the full list of step executions. Parameters (dict) --The key-value map of execution parameters, which were supplied when calling StartAutomationExecution. (string) -- (list) -- (string) -- Outputs (dict) --The list of execution outputs as defined in the automation document. (string) -- (list) -- (string) -- FailureMessage (string) --A message describing why an execution has failed, if the status is set to Failed. Mode (string) --The automation execution mode. ParentAutomationExecutionId (string) --The AutomationExecutionId of the parent automation. ExecutedBy (string) --The Amazon Resource Name (ARN) of the user who ran the automation. CurrentStepName (string) --The name of the step that is currently running. CurrentAction (string) --The action of the step that is currently running. TargetParameterName (string) --The parameter name. Targets (list) --The specified targets. (dict) --An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) --User-defined criteria for sending commands that target instances that meet the criteria. Values (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TargetMaps (list) --The specified key-value mapping of document parameters to target resources. (dict) -- (string) -- (list) -- (string) -- ResolvedTargets (dict) --A list of resolved targets in the rate control execution. ParameterValues (list) --A list of parameter values sent to targets that resolved during the Automation execution. (string) -- Truncated (boolean) --A boolean value indicating whether the resolved target list is truncated. MaxConcurrency (string) --The MaxConcurrency value specified by the user when the execution started. MaxErrors (string) --The MaxErrors value specified by the user when the execution started. Target (string) --The target of the execution. TargetLocations (list) --The combination of AWS Regions and/or AWS accounts where you want to run the Automation. (dict) --The combination of AWS Regions and accounts targeted by the current Automation execution. Accounts (list) --The AWS accounts targeted by the current Automation execution. (string) -- Regions (list) --The AWS Regions targeted by the current Automation execution. (string) -- TargetLocationMaxConcurrency (string) --The maximum number of AWS accounts and AWS regions allowed to run the Automation concurrently TargetLocationMaxErrors (string) --The maximum number of errors allowed before the system stops queueing additional Automation executions for the currently running Automation. ExecutionRoleName (string) --The Automation execution role used by the currently running Automation. ProgressCounters (dict) --An aggregate of step execution statuses displayed in the AWS Console for a multi-Region and multi-account Automation execution. TotalSteps (integer) --The total number of steps run in all specified AWS Regions and accounts for the current Automation execution. SuccessSteps (integer) --The total number of steps that successfully completed in all specified AWS Regions and accounts for the current Automation execution. FailedSteps (integer) --The total number of steps that failed to run in all specified AWS Regions and accounts for the current Automation execution. CancelledSteps (integer) --The total number of steps that the system cancelled in all specified AWS Regions and accounts for the current Automation execution. TimedOutSteps (integer) --The total number of steps that timed out in all specified AWS Regions and accounts for the current Automation execution. Exceptions SSM.Client.exceptions.AutomationExecutionNotFoundException SSM.Client.exceptions.InternalServerError :return: { 'AutomationExecution': { 'AutomationExecutionId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'AutomationExecutionStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'StepExecutions': [ { 'StepName': 'string', 'Action': 'string', 'TimeoutSeconds': 123, 'OnFailure': 'string', 'MaxAttempts': 123, 'ExecutionStartTime': datetime(2015, 1, 1), 'ExecutionEndTime': datetime(2015, 1, 1), 'StepStatus': 'Pending'|'InProgress'|'Waiting'|'Success'|'TimedOut'|'Cancelling'|'Cancelled'|'Failed', 'ResponseCode': 'string', 'Inputs': { 'string': 'string' }, 'Outputs': { 'string': [ 'string', ] }, 'Response': 'string', 'FailureMessage': 'string', 'FailureDetails': { 'FailureStage': 'string', 'FailureType': 'string', 'Details': { 'string': [ 'string', ] } }, 'StepExecutionId': 'string', 'OverriddenParameters': { 'string': [ 'string', ] }, 'IsEnd': True|False, 'NextStep': 'string', 'IsCritical': True|False, 'ValidNextSteps': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetLocation': { 'Accounts': [ 'string', ], 'Regions': [ 'string', ], 'TargetLocationMaxConcurrency': 'string', 'TargetLocationMaxErrors': 'string', 'ExecutionRoleName': 'string' } }, ], 'StepExecutionsTruncated': True|False, 'Parameters': { 'string': [ 'string', ] }, 'Outputs': { 'string': [ 'string', ] }, 'FailureMessage': 'string', 'Mode': 'Auto'|'Interactive', 'ParentAutomationExecutionId': 'string', 'ExecutedBy': 'string', 'CurrentStepName': 'string', 'CurrentAction': 'string', 'TargetParameterName': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TargetMaps': [ { 'string': [ 'string', ] }, ], 'ResolvedTargets': { 'ParameterValues': [ 'string', ], 'Truncated': True|False }, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Target': 'string', 'TargetLocations': [ { 'Accounts': [ 'string', ], 'Regions': [ 'string', ], 'TargetLocationMaxConcurrency': 'string', 'TargetLocationMaxErrors': 'string', 'ExecutionRoleName': 'string' }, ], 'ProgressCounters': { 'TotalSteps': 123, 'SuccessSteps': 123, 'FailedSteps': 123, 'CancelledSteps': 123, 'TimedOutSteps': 123 } } } :returns: (string) -- (list) -- (string) -- """ pass def get_calendar_state(CalendarNames=None, AtTime=None): """ Gets the state of the AWS Systems Manager Change Calendar at an optional, specified time. If you specify a time, GetCalendarState returns the state of the calendar at a specific time, and returns the next time that the Change Calendar state will transition. If you do not specify a time, GetCalendarState assumes the current time. Change Calendar entries have two possible states: OPEN or CLOSED . For more information about Systems Manager Change Calendar, see AWS Systems Manager Change Calendar in the AWS Systems Manager User Guide . See also: AWS API Documentation Exceptions :example: response = client.get_calendar_state( CalendarNames=[ 'string', ], AtTime='string' ) :type CalendarNames: list :param CalendarNames: [REQUIRED]\nThe names or Amazon Resource Names (ARNs) of the Systems Manager documents that represent the calendar entries for which you want to get the state.\n\n(string) --\n\n :type AtTime: string :param AtTime: (Optional) The specific time for which you want to get calendar state information, in ISO 8601 format. If you do not add AtTime , the current time is assumed. :rtype: dict ReturnsResponse Syntax { 'State': 'OPEN'|'CLOSED', 'AtTime': 'string', 'NextTransitionTime': 'string' } Response Structure (dict) -- State (string) -- The state of the calendar. An OPEN calendar indicates that actions are allowed to proceed, and a CLOSED calendar indicates that actions are not allowed to proceed. AtTime (string) -- The time, as an ISO 8601 string, that you specified in your command. If you did not specify a time, GetCalendarState uses the current time. NextTransitionTime (string) -- The time, as an ISO 8601 string, that the calendar state will change. If the current calendar state is OPEN , NextTransitionTime indicates when the calendar state changes to CLOSED , and vice-versa. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentType SSM.Client.exceptions.UnsupportedCalendarException :return: { 'State': 'OPEN'|'CLOSED', 'AtTime': 'string', 'NextTransitionTime': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentType SSM.Client.exceptions.UnsupportedCalendarException """ pass def get_command_invocation(CommandId=None, InstanceId=None, PluginName=None): """ Returns detailed information about command execution for an invocation or plugin. See also: AWS API Documentation Exceptions :example: response = client.get_command_invocation( CommandId='string', InstanceId='string', PluginName='string' ) :type CommandId: string :param CommandId: [REQUIRED]\n(Required) The parent command ID of the invocation plugin.\n :type InstanceId: string :param InstanceId: [REQUIRED]\n(Required) The ID of the managed instance targeted by the command. A managed instance can be an EC2 instance or an instance in your hybrid environment that is configured for Systems Manager.\n :type PluginName: string :param PluginName: (Optional) The name of the plugin for which you want detailed results. If the document contains only one plugin, the name can be omitted and the details will be returned. :rtype: dict ReturnsResponse Syntax { 'CommandId': 'string', 'InstanceId': 'string', 'Comment': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'PluginName': 'string', 'ResponseCode': 123, 'ExecutionStartDateTime': 'string', 'ExecutionElapsedTime': 'string', 'ExecutionEndDateTime': 'string', 'Status': 'Pending'|'InProgress'|'Delayed'|'Success'|'Cancelled'|'TimedOut'|'Failed'|'Cancelling', 'StatusDetails': 'string', 'StandardOutputContent': 'string', 'StandardOutputUrl': 'string', 'StandardErrorContent': 'string', 'StandardErrorUrl': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False } } Response Structure (dict) -- CommandId (string) -- The parent command ID of the invocation plugin. InstanceId (string) -- The ID of the managed instance targeted by the command. A managed instance can be an EC2 instance or an instance in your hybrid environment that is configured for Systems Manager. Comment (string) -- The comment text for the command. DocumentName (string) -- The name of the document that was run. For example, AWS-RunShellScript. DocumentVersion (string) -- The SSM document version used in the request. PluginName (string) -- The name of the plugin for which you want detailed results. For example, aws:RunShellScript is a plugin. ResponseCode (integer) -- The error level response code for the plugin script. If the response code is -1, then the command has not started running on the instance, or it was not received by the instance. ExecutionStartDateTime (string) -- The date and time the plugin started running. Date and time are written in ISO 8601 format. For example, June 7, 2017 is represented as 2017-06-7. The following sample AWS CLI command uses the InvokedBefore filter. aws ssm list-commands --filters key=InvokedBefore,value=2017-06-07T00:00:00Z If the plugin has not started to run, the string is empty. ExecutionElapsedTime (string) -- Duration since ExecutionStartDateTime. ExecutionEndDateTime (string) -- The date and time the plugin was finished running. Date and time are written in ISO 8601 format. For example, June 7, 2017 is represented as 2017-06-7. The following sample AWS CLI command uses the InvokedAfter filter. aws ssm list-commands --filters key=InvokedAfter,value=2017-06-07T00:00:00Z If the plugin has not started to run, the string is empty. Status (string) -- The status of this invocation plugin. This status can be different than StatusDetails. StatusDetails (string) -- A detailed status of the command execution for an invocation. StatusDetails includes more information than Status because it includes states resulting from error and concurrency control parameters. StatusDetails can show different results than Status. For more information about these statuses, see Understanding command statuses in the AWS Systems Manager User Guide . StatusDetails can be one of the following values: Pending: The command has not been sent to the instance. In Progress: The command has been sent to the instance but has not reached a terminal state. Delayed: The system attempted to send the command to the target, but the target was not available. The instance might not be available because of network issues, because the instance was stopped, or for similar reasons. The system will try to send the command again. Success: The command or plugin ran successfully. This is a terminal state. Delivery Timed Out: The command was not delivered to the instance before the delivery timeout expired. Delivery timeouts do not count against the parent command\'s MaxErrors limit, but they do contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Execution Timed Out: The command started to run on the instance, but the execution was not complete before the timeout expired. Execution timeouts count against the MaxErrors limit of the parent command. This is a terminal state. Failed: The command wasn\'t run successfully on the instance. For a plugin, this indicates that the result code was not zero. For a command invocation, this indicates that the result code for one or more plugins was not zero. Invocation failures count against the MaxErrors limit of the parent command. This is a terminal state. Canceled: The command was terminated before it was completed. This is a terminal state. Undeliverable: The command can\'t be delivered to the instance. The instance might not exist or might not be responding. Undeliverable invocations don\'t count against the parent command\'s MaxErrors limit and don\'t contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Terminated: The parent command exceeded its MaxErrors limit and subsequent command invocations were canceled by the system. This is a terminal state. StandardOutputContent (string) -- The first 24,000 characters written by the plugin to stdout. If the command has not finished running, if ExecutionStatus is neither Succeeded nor Failed, then this string is empty. StandardOutputUrl (string) -- The URL for the complete text written by the plugin to stdout in Amazon S3. If an S3 bucket was not specified, then this string is empty. StandardErrorContent (string) -- The first 8,000 characters written by the plugin to stderr. If the command has not finished running, then this string is empty. StandardErrorUrl (string) -- The URL for the complete text written by the plugin to stderr. If the command has not finished running, then this string is empty. CloudWatchOutputConfig (dict) -- CloudWatch Logs information where Systems Manager sent the command output. CloudWatchLogGroupName (string) -- The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName . CloudWatchOutputEnabled (boolean) -- Enables Systems Manager to send command output to CloudWatch Logs. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidCommandId SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidPluginName SSM.Client.exceptions.InvocationDoesNotExist :return: { 'CommandId': 'string', 'InstanceId': 'string', 'Comment': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'PluginName': 'string', 'ResponseCode': 123, 'ExecutionStartDateTime': 'string', 'ExecutionElapsedTime': 'string', 'ExecutionEndDateTime': 'string', 'Status': 'Pending'|'InProgress'|'Delayed'|'Success'|'Cancelled'|'TimedOut'|'Failed'|'Cancelling', 'StatusDetails': 'string', 'StandardOutputContent': 'string', 'StandardOutputUrl': 'string', 'StandardErrorContent': 'string', 'StandardErrorUrl': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False } } :returns: Pending: The command has not been sent to the instance. In Progress: The command has been sent to the instance but has not reached a terminal state. Delayed: The system attempted to send the command to the target, but the target was not available. The instance might not be available because of network issues, because the instance was stopped, or for similar reasons. The system will try to send the command again. Success: The command or plugin ran successfully. This is a terminal state. Delivery Timed Out: The command was not delivered to the instance before the delivery timeout expired. Delivery timeouts do not count against the parent command\'s MaxErrors limit, but they do contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Execution Timed Out: The command started to run on the instance, but the execution was not complete before the timeout expired. Execution timeouts count against the MaxErrors limit of the parent command. This is a terminal state. Failed: The command wasn\'t run successfully on the instance. For a plugin, this indicates that the result code was not zero. For a command invocation, this indicates that the result code for one or more plugins was not zero. Invocation failures count against the MaxErrors limit of the parent command. This is a terminal state. Canceled: The command was terminated before it was completed. This is a terminal state. Undeliverable: The command can\'t be delivered to the instance. The instance might not exist or might not be responding. Undeliverable invocations don\'t count against the parent command\'s MaxErrors limit and don\'t contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Terminated: The parent command exceeded its MaxErrors limit and subsequent command invocations were canceled by the system. This is a terminal state. """ pass def get_connection_status(Target=None): """ Retrieves the Session Manager connection status for an instance to determine whether it is running and ready to receive Session Manager connections. See also: AWS API Documentation Exceptions :example: response = client.get_connection_status( Target='string' ) :type Target: string :param Target: [REQUIRED]\nThe ID of the instance.\n :rtype: dict ReturnsResponse Syntax{ 'Target': 'string', 'Status': 'Connected'|'NotConnected' } Response Structure (dict) -- Target (string) --The ID of the instance to check connection status. Status (string) --The status of the connection to the instance. For example, \'Connected\' or \'Not Connected\'. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'Target': 'string', 'Status': 'Connected'|'NotConnected' } """ pass def get_default_patch_baseline(OperatingSystem=None): """ Retrieves the default patch baseline. Note that Systems Manager supports creating multiple default patch baselines. For example, you can create a default patch baseline for each operating system. If you do not specify an operating system value, the default patch baseline for Windows is returned. See also: AWS API Documentation Exceptions :example: response = client.get_default_patch_baseline( OperatingSystem='WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN' ) :type OperatingSystem: string :param OperatingSystem: Returns the default patch baseline for the specified operating system. :rtype: dict ReturnsResponse Syntax{ 'BaselineId': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN' } Response Structure (dict) -- BaselineId (string) --The ID of the default patch baseline. OperatingSystem (string) --The operating system for the returned patch baseline. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN' } """ pass def get_deployable_patch_snapshot_for_instance(InstanceId=None, SnapshotId=None): """ Retrieves the current snapshot for the patch baseline the instance uses. This API is primarily used by the AWS-RunPatchBaseline Systems Manager document. See also: AWS API Documentation Exceptions :example: response = client.get_deployable_patch_snapshot_for_instance( InstanceId='string', SnapshotId='string' ) :type InstanceId: string :param InstanceId: [REQUIRED]\nThe ID of the instance for which the appropriate patch snapshot should be retrieved.\n :type SnapshotId: string :param SnapshotId: [REQUIRED]\nThe user-defined snapshot ID.\n :rtype: dict ReturnsResponse Syntax { 'InstanceId': 'string', 'SnapshotId': 'string', 'SnapshotDownloadUrl': 'string', 'Product': 'string' } Response Structure (dict) -- InstanceId (string) -- The ID of the instance. SnapshotId (string) -- The user-defined snapshot ID. SnapshotDownloadUrl (string) -- A pre-signed Amazon S3 URL that can be used to download the patch snapshot. Product (string) -- Returns the specific operating system (for example Windows Server 2012 or Amazon Linux 2015.09) on the instance for the specified patch snapshot. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.UnsupportedOperatingSystem SSM.Client.exceptions.UnsupportedFeatureRequiredException :return: { 'InstanceId': 'string', 'SnapshotId': 'string', 'SnapshotDownloadUrl': 'string', 'Product': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.UnsupportedOperatingSystem SSM.Client.exceptions.UnsupportedFeatureRequiredException """ pass def get_document(Name=None, VersionName=None, DocumentVersion=None, DocumentFormat=None): """ Gets the contents of the specified Systems Manager document. See also: AWS API Documentation Exceptions :example: response = client.get_document( Name='string', VersionName='string', DocumentVersion='string', DocumentFormat='YAML'|'JSON'|'TEXT' ) :type Name: string :param Name: [REQUIRED]\nThe name of the Systems Manager document.\n :type VersionName: string :param VersionName: An optional field specifying the version of the artifact associated with the document. For example, 'Release 12, Update 6'. This value is unique across all versions of a document and can\'t be changed. :type DocumentVersion: string :param DocumentVersion: The document version for which you want information. :type DocumentFormat: string :param DocumentFormat: Returns the document in the specified format. The document format can be either JSON or YAML. JSON is the default format. :rtype: dict ReturnsResponse Syntax { 'Name': 'string', 'VersionName': 'string', 'DocumentVersion': 'string', 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'Content': 'string', 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ], 'AttachmentsContent': [ { 'Name': 'string', 'Size': 123, 'Hash': 'string', 'HashType': 'Sha256', 'Url': 'string' }, ] } Response Structure (dict) -- Name (string) -- The name of the Systems Manager document. VersionName (string) -- The version of the artifact associated with the document. For example, "Release 12, Update 6". This value is unique across all versions of a document, and cannot be changed. DocumentVersion (string) -- The document version. Status (string) -- The status of the Systems Manager document, such as Creating , Active , Updating , Failed , and Deleting . StatusInformation (string) -- A message returned by AWS Systems Manager that explains the Status value. For example, a Failed status might be explained by the StatusInformation message, "The specified S3 bucket does not exist. Verify that the URL of the S3 bucket is correct." Content (string) -- The contents of the Systems Manager document. DocumentType (string) -- The document type. DocumentFormat (string) -- The document format, either JSON or YAML. Requires (list) -- A list of SSM documents required by a document. For example, an ApplicationConfiguration document requires an ApplicationConfigurationSchema document. (dict) -- An SSM document required by the current document. Name (string) -- The name of the required SSM document. The name can be an Amazon Resource Name (ARN). Version (string) -- The document version required by the current document. AttachmentsContent (list) -- A description of the document attachments, including names, locations, sizes, and so on. (dict) -- A structure that includes attributes that describe a document attachment. Name (string) -- The name of an attachment. Size (integer) -- The size of an attachment in bytes. Hash (string) -- The cryptographic hash value of the document content. HashType (string) -- The hash algorithm used to calculate the hash value. Url (string) -- The URL location of the attachment content. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion :return: { 'Name': 'string', 'VersionName': 'string', 'DocumentVersion': 'string', 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'Content': 'string', 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ], 'AttachmentsContent': [ { 'Name': 'string', 'Size': 123, 'Hash': 'string', 'HashType': 'Sha256', 'Url': 'string' }, ] } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion """ pass def get_inventory(Filters=None, Aggregators=None, ResultAttributes=None, NextToken=None, MaxResults=None): """ Query inventory information. See also: AWS API Documentation Exceptions :example: response = client.get_inventory( Filters=[ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'Equal'|'NotEqual'|'BeginWith'|'LessThan'|'GreaterThan'|'Exists' }, ], Aggregators=[ { 'Expression': 'string', 'Aggregators': {'... recursive ...'}, 'Groups': [ { 'Name': 'string', 'Filters': [ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'Equal'|'NotEqual'|'BeginWith'|'LessThan'|'GreaterThan'|'Exists' }, ] }, ] }, ], ResultAttributes=[ { 'TypeName': 'string' }, ], NextToken='string', MaxResults=123 ) :type Filters: list :param Filters: One or more filters. Use a filter to return a more specific list of results.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nKey (string) -- [REQUIRED]The name of the filter key.\n\nValues (list) -- [REQUIRED]Inventory filter values. Example: inventory filter where instance IDs are specified as values Key=AWS:InstanceInformation.InstanceId,Values= i-a12b3c4d5e6g, i-1a2b3c4d5e6,Type=Equal\n\n(string) --\n\n\nType (string) --The type of filter.\n\nNote\nThe Exists filter must be used with aggregators. For more information, see Aggregating inventory data in the AWS Systems Manager User Guide .\n\n\n\n\n\n :type Aggregators: list :param Aggregators: Returns counts of inventory types based on one or more expressions. For example, if you aggregate by using an expression that uses the AWS:InstanceInformation.PlatformType type, you can see a count of how many Windows and Linux instances exist in your inventoried fleet.\n\n(dict) --Specifies the inventory type and attribute for the aggregation execution.\n\nExpression (string) --The inventory type and attribute name for aggregation.\n\nAggregators (list) --Nested aggregators to further refine aggregation for an inventory type.\n\nGroups (list) --A user-defined set of one or more filters on which to aggregate inventory data. Groups return a count of resources that match and don\'t match the specified criteria.\n\n(dict) --A user-defined set of one or more filters on which to aggregate inventory data. Groups return a count of resources that match and don\'t match the specified criteria.\n\nName (string) -- [REQUIRED]The name of the group.\n\nFilters (list) -- [REQUIRED]Filters define the criteria for the group. The matchingCount field displays the number of resources that match the criteria. The notMatchingCount field displays the number of resources that don\'t match the criteria.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nKey (string) -- [REQUIRED]The name of the filter key.\n\nValues (list) -- [REQUIRED]Inventory filter values. Example: inventory filter where instance IDs are specified as values Key=AWS:InstanceInformation.InstanceId,Values= i-a12b3c4d5e6g, i-1a2b3c4d5e6,Type=Equal\n\n(string) --\n\n\nType (string) --The type of filter.\n\nNote\nThe Exists filter must be used with aggregators. For more information, see Aggregating inventory data in the AWS Systems Manager User Guide .\n\n\n\n\n\n\n\n\n\n\n\n\n\n :type ResultAttributes: list :param ResultAttributes: The list of inventory item types to return.\n\n(dict) --The inventory item result attribute.\n\nTypeName (string) -- [REQUIRED]Name of the inventory item type. Valid value: AWS:InstanceInformation. Default Value: AWS:InstanceInformation.\n\n\n\n\n :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'Entities': [ { 'Id': 'string', 'Data': { 'string': { 'TypeName': 'string', 'SchemaVersion': 'string', 'CaptureTime': 'string', 'ContentHash': 'string', 'Content': [ { 'string': 'string' }, ] } } }, ], 'NextToken': 'string' } Response Structure (dict) -- Entities (list) -- Collection of inventory entities such as a collection of instance inventory. (dict) -- Inventory query results. Id (string) -- ID of the inventory result entity. For example, for managed instance inventory the result will be the managed instance ID. For EC2 instance inventory, the result will be the instance ID. Data (dict) -- The data section in the inventory result entity JSON. (string) -- (dict) -- The inventory result item. TypeName (string) -- The name of the inventory result item type. SchemaVersion (string) -- The schema version for the inventory result item/ CaptureTime (string) -- The time inventory item data was captured. ContentHash (string) -- MD5 hash of the inventory item type contents. The content hash is used to determine whether to update inventory information. The PutInventory API does not update the inventory item type contents if the MD5 hash has not changed since last update. Content (list) -- Contains all the inventory data of the item type. Results include attribute names and values. (dict) -- (string) -- (string) -- NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidInventoryGroupException SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidAggregatorException SSM.Client.exceptions.InvalidResultAttributeException :return: { 'Entities': [ { 'Id': 'string', 'Data': { 'string': { 'TypeName': 'string', 'SchemaVersion': 'string', 'CaptureTime': 'string', 'ContentHash': 'string', 'Content': [ { 'string': 'string' }, ] } } }, ], 'NextToken': 'string' } :returns: (dict) -- (string) -- (string) -- """ pass def get_inventory_schema(TypeName=None, NextToken=None, MaxResults=None, Aggregator=None, SubType=None): """ Return a list of inventory type names for the account, or return a list of attribute names for a specific Inventory item type. See also: AWS API Documentation Exceptions :example: response = client.get_inventory_schema( TypeName='string', NextToken='string', MaxResults=123, Aggregator=True|False, SubType=True|False ) :type TypeName: string :param TypeName: The type of inventory item to return. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type Aggregator: boolean :param Aggregator: Returns inventory schemas that support aggregation. For example, this call returns the AWS:InstanceInformation type, because it supports aggregation based on the PlatformName , PlatformType , and PlatformVersion attributes. :type SubType: boolean :param SubType: Returns the sub-type schema for a specified inventory type. :rtype: dict ReturnsResponse Syntax { 'Schemas': [ { 'TypeName': 'string', 'Version': 'string', 'Attributes': [ { 'Name': 'string', 'DataType': 'string'|'number' }, ], 'DisplayName': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Schemas (list) -- Inventory schemas returned by the request. (dict) -- The inventory item schema definition. Users can use this to compose inventory query filters. TypeName (string) -- The name of the inventory type. Default inventory item type names start with AWS. Custom inventory type names will start with Custom. Default inventory item types include the following: AWS:AWSComponent, AWS:Application, AWS:InstanceInformation, AWS:Network, and AWS:WindowsUpdate. Version (string) -- The schema version for the inventory item. Attributes (list) -- The schema attributes for inventory. This contains data type and attribute name. (dict) -- Attributes are the entries within the inventory item content. It contains name and value. Name (string) -- Name of the inventory item attribute. DataType (string) -- The data type of the inventory item attribute. DisplayName (string) -- The alias name of the inventory type. The alias name is used for display purposes. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidNextToken :return: { 'Schemas': [ { 'TypeName': 'string', 'Version': 'string', 'Attributes': [ { 'Name': 'string', 'DataType': 'string'|'number' }, ], 'DisplayName': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidNextToken """ pass def get_maintenance_window(WindowId=None): """ Retrieves a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.get_maintenance_window( WindowId='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window for which you want to retrieve information.\n :rtype: dict ReturnsResponse Syntax{ 'WindowId': 'string', 'Name': 'string', 'Description': 'string', 'StartDate': 'string', 'EndDate': 'string', 'Schedule': 'string', 'ScheduleTimezone': 'string', 'NextExecutionTime': 'string', 'Duration': 123, 'Cutoff': 123, 'AllowUnassociatedTargets': True|False, 'Enabled': True|False, 'CreatedDate': datetime(2015, 1, 1), 'ModifiedDate': datetime(2015, 1, 1) } Response Structure (dict) -- WindowId (string) --The ID of the created maintenance window. Name (string) --The name of the maintenance window. Description (string) --The description of the maintenance window. StartDate (string) --The date and time, in ISO-8601 Extended format, for when the maintenance window is scheduled to become active. The maintenance window will not run before this specified time. EndDate (string) --The date and time, in ISO-8601 Extended format, for when the maintenance window is scheduled to become inactive. The maintenance window will not run after this specified time. Schedule (string) --The schedule of the maintenance window in the form of a cron or rate expression. ScheduleTimezone (string) --The time zone that the scheduled maintenance window executions are based on, in Internet Assigned Numbers Authority (IANA) format. For example: "America/Los_Angeles", "etc/UTC", or "Asia/Seoul". For more information, see the Time Zone Database on the IANA website. NextExecutionTime (string) --The next time the maintenance window will actually run, taking into account any specified times for the maintenance window to become active or inactive. Duration (integer) --The duration of the maintenance window in hours. Cutoff (integer) --The number of hours before the end of the maintenance window that Systems Manager stops scheduling new tasks for execution. AllowUnassociatedTargets (boolean) --Whether targets must be registered with the maintenance window before tasks can be defined for those targets. Enabled (boolean) --Indicates whether the maintenance window is enabled. CreatedDate (datetime) --The date the maintenance window was created. ModifiedDate (datetime) --The date the maintenance window was last modified. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string', 'Name': 'string', 'Description': 'string', 'StartDate': 'string', 'EndDate': 'string', 'Schedule': 'string', 'ScheduleTimezone': 'string', 'NextExecutionTime': 'string', 'Duration': 123, 'Cutoff': 123, 'AllowUnassociatedTargets': True|False, 'Enabled': True|False, 'CreatedDate': datetime(2015, 1, 1), 'ModifiedDate': datetime(2015, 1, 1) } """ pass def get_maintenance_window_execution(WindowExecutionId=None): """ Retrieves details about a specific a maintenance window execution. See also: AWS API Documentation Exceptions :example: response = client.get_maintenance_window_execution( WindowExecutionId='string' ) :type WindowExecutionId: string :param WindowExecutionId: [REQUIRED]\nThe ID of the maintenance window execution that includes the task.\n :rtype: dict ReturnsResponse Syntax{ 'WindowExecutionId': 'string', 'TaskIds': [ 'string', ], 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1) } Response Structure (dict) -- WindowExecutionId (string) --The ID of the maintenance window execution. TaskIds (list) --The ID of the task executions from the maintenance window execution. (string) -- Status (string) --The status of the maintenance window execution. StatusDetails (string) --The details explaining the Status. Only available for certain status values. StartTime (datetime) --The time the maintenance window started running. EndTime (datetime) --The time the maintenance window finished running. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowExecutionId': 'string', 'TaskIds': [ 'string', ], 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1) } :returns: SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError """ pass def get_maintenance_window_execution_task(WindowExecutionId=None, TaskId=None): """ Retrieves the details about a specific task run as part of a maintenance window execution. See also: AWS API Documentation Exceptions :example: response = client.get_maintenance_window_execution_task( WindowExecutionId='string', TaskId='string' ) :type WindowExecutionId: string :param WindowExecutionId: [REQUIRED]\nThe ID of the maintenance window execution that includes the task.\n :type TaskId: string :param TaskId: [REQUIRED]\nThe ID of the specific task execution in the maintenance window task that should be retrieved.\n :rtype: dict ReturnsResponse Syntax { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'TaskArn': 'string', 'ServiceRole': 'string', 'Type': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'TaskParameters': [ { 'string': { 'Values': [ 'string', ] } }, ], 'Priority': 123, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1) } Response Structure (dict) -- WindowExecutionId (string) -- The ID of the maintenance window execution that includes the task. TaskExecutionId (string) -- The ID of the specific task execution in the maintenance window task that was retrieved. TaskArn (string) -- The ARN of the task that ran. ServiceRole (string) -- The role that was assumed when running the task. Type (string) -- The type of task that was run. TaskParameters (list) -- The parameters passed to the task when it was run. Note TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . The map has the following format: Key: string, between 1 and 255 characters Value: an array of strings, each string is between 1 and 255 characters (dict) -- (string) -- (dict) -- Defines the values for a task parameter. Values (list) -- This field contains an array of 0 or more strings, each 1 to 255 characters in length. (string) -- Priority (integer) -- The priority of the task. MaxConcurrency (string) -- The defined maximum number of task executions that could be run in parallel. MaxErrors (string) -- The defined maximum number of task execution errors allowed before scheduling of the task execution would have been stopped. Status (string) -- The status of the task. StatusDetails (string) -- The details explaining the Status. Only available for certain status values. StartTime (datetime) -- The time the task execution started. EndTime (datetime) -- The time the task execution completed. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'TaskArn': 'string', 'ServiceRole': 'string', 'Type': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'TaskParameters': [ { 'string': { 'Values': [ 'string', ] } }, ], 'Priority': 123, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1) } :returns: (string) -- """ pass def get_maintenance_window_execution_task_invocation(WindowExecutionId=None, TaskId=None, InvocationId=None): """ Retrieves information about a specific task running on a specific target. See also: AWS API Documentation Exceptions :example: response = client.get_maintenance_window_execution_task_invocation( WindowExecutionId='string', TaskId='string', InvocationId='string' ) :type WindowExecutionId: string :param WindowExecutionId: [REQUIRED]\nThe ID of the maintenance window execution for which the task is a part.\n :type TaskId: string :param TaskId: [REQUIRED]\nThe ID of the specific task in the maintenance window task that should be retrieved.\n :type InvocationId: string :param InvocationId: [REQUIRED]\nThe invocation ID to retrieve.\n :rtype: dict ReturnsResponse Syntax { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'InvocationId': 'string', 'ExecutionId': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'Parameters': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'OwnerInformation': 'string', 'WindowTargetId': 'string' } Response Structure (dict) -- WindowExecutionId (string) -- The maintenance window execution ID. TaskExecutionId (string) -- The task execution ID. InvocationId (string) -- The invocation ID. ExecutionId (string) -- The execution ID. TaskType (string) -- Retrieves the task type for a maintenance window. Task types include the following: LAMBDA, STEP_FUNCTIONS, AUTOMATION, RUN_COMMAND. Parameters (string) -- The parameters used at the time that the task ran. Status (string) -- The task status for an invocation. StatusDetails (string) -- The details explaining the status. Details are only available for certain status values. StartTime (datetime) -- The time that the task started running on the target. EndTime (datetime) -- The time that the task finished running on the target. OwnerInformation (string) -- User-provided value to be included in any CloudWatch events raised while running tasks for these targets in this maintenance window. WindowTargetId (string) -- The maintenance window target ID. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowExecutionId': 'string', 'TaskExecutionId': 'string', 'InvocationId': 'string', 'ExecutionId': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'Parameters': 'string', 'Status': 'PENDING'|'IN_PROGRESS'|'SUCCESS'|'FAILED'|'TIMED_OUT'|'CANCELLING'|'CANCELLED'|'SKIPPED_OVERLAPPING', 'StatusDetails': 'string', 'StartTime': datetime(2015, 1, 1), 'EndTime': datetime(2015, 1, 1), 'OwnerInformation': 'string', 'WindowTargetId': 'string' } :returns: SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError """ pass def get_maintenance_window_task(WindowId=None, WindowTaskId=None): """ Lists the tasks in a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.get_maintenance_window_task( WindowId='string', WindowTaskId='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe maintenance window ID that includes the task to retrieve.\n :type WindowTaskId: string :param WindowTaskId: [REQUIRED]\nThe maintenance window task ID to retrieve.\n :rtype: dict ReturnsResponse Syntax { 'WindowId': 'string', 'WindowTaskId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TaskArn': 'string', 'ServiceRoleArn': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'TaskParameters': { 'string': { 'Values': [ 'string', ] } }, 'TaskInvocationParameters': { 'RunCommand': { 'Comment': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'DocumentHash': 'string', 'DocumentHashType': 'Sha256'|'Sha1', 'DocumentVersion': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'Parameters': { 'string': [ 'string', ] }, 'ServiceRoleArn': 'string', 'TimeoutSeconds': 123 }, 'Automation': { 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] } }, 'StepFunctions': { 'Input': 'string', 'Name': 'string' }, 'Lambda': { 'ClientContext': 'string', 'Qualifier': 'string', 'Payload': b'bytes' } }, 'Priority': 123, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'LoggingInfo': { 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, 'Name': 'string', 'Description': 'string' } Response Structure (dict) -- WindowId (string) -- The retrieved maintenance window ID. WindowTaskId (string) -- The retrieved maintenance window task ID. Targets (list) -- The targets where the task should run. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TaskArn (string) -- The resource that the task used during execution. For RUN_COMMAND and AUTOMATION task types, the TaskArn is the Systems Manager Document name/ARN. For LAMBDA tasks, the value is the function name/ARN. For STEP_FUNCTIONS tasks, the value is the state machine ARN. ServiceRoleArn (string) -- The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks. TaskType (string) -- The type of task to run. TaskParameters (dict) -- The parameters to pass to the task when it runs. Note TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . (string) -- (dict) -- Defines the values for a task parameter. Values (list) -- This field contains an array of 0 or more strings, each 1 to 255 characters in length. (string) -- TaskInvocationParameters (dict) -- The parameters to pass to the task when it runs. RunCommand (dict) -- The parameters for a RUN_COMMAND task type. Comment (string) -- Information about the commands to run. CloudWatchOutputConfig (dict) -- Configuration options for sending command output to CloudWatch Logs. CloudWatchLogGroupName (string) -- The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName . CloudWatchOutputEnabled (boolean) -- Enables Systems Manager to send command output to CloudWatch Logs. DocumentHash (string) -- The SHA-256 or SHA-1 hash created by the system when the document was created. SHA-1 hashes have been deprecated. DocumentHashType (string) -- SHA-256 or SHA-1. SHA-1 hashes have been deprecated. DocumentVersion (string) -- The SSM document version to use in the request. You can specify $DEFAULT, $LATEST, or a specific version number. If you run commands by using the AWS CLI, then you must escape the first two options by using a backslash. If you specify a version number, then you don\'t need to use the backslash. For example: --document-version "$DEFAULT" --document-version "$LATEST" --document-version "3" NotificationConfig (dict) -- Configurations for sending notifications about command status changes on a per-instance basis. NotificationArn (string) -- An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic. NotificationEvents (list) -- The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide . (string) -- NotificationType (string) -- Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes. OutputS3BucketName (string) -- The name of the S3 bucket. OutputS3KeyPrefix (string) -- The S3 bucket subfolder. Parameters (dict) -- The parameters for the RUN_COMMAND task execution. (string) -- (list) -- (string) -- ServiceRoleArn (string) -- The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks. TimeoutSeconds (integer) -- If this time is reached and the command has not already started running, it doesn\'t run. Automation (dict) -- The parameters for an AUTOMATION task type. DocumentVersion (string) -- The version of an Automation document to use during task execution. Parameters (dict) -- The parameters for the AUTOMATION task. For information about specifying and updating task parameters, see RegisterTaskWithMaintenanceWindow and UpdateMaintenanceWindowTask . Note LoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . For AUTOMATION task types, Systems Manager ignores any values specified for these parameters. (string) -- (list) -- (string) -- StepFunctions (dict) -- The parameters for a STEP_FUNCTIONS task type. Input (string) -- The inputs for the STEP_FUNCTIONS task. Name (string) -- The name of the STEP_FUNCTIONS task. Lambda (dict) -- The parameters for a LAMBDA task type. ClientContext (string) -- Pass client-specific information to the Lambda function that you are invoking. You can then process the client information in your Lambda function as you choose through the context variable. Qualifier (string) -- (Optional) Specify a Lambda function version or alias name. If you specify a function version, the action uses the qualified function ARN to invoke a specific Lambda function. If you specify an alias name, the action uses the alias ARN to invoke the Lambda function version to which the alias points. Payload (bytes) -- JSON to provide to your Lambda function as input. Priority (integer) -- The priority of the task when it runs. The lower the number, the higher the priority. Tasks that have the same priority are scheduled in parallel. MaxConcurrency (string) -- The maximum number of targets allowed to run this task in parallel. MaxErrors (string) -- The maximum number of errors allowed before the task stops being scheduled. LoggingInfo (dict) -- The location in Amazon S3 where the task results are logged. Note LoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . S3BucketName (string) -- The name of an S3 bucket where execution logs are stored . S3KeyPrefix (string) -- (Optional) The S3 bucket subfolder. S3Region (string) -- The Region where the S3 bucket is located. Name (string) -- The retrieved task name. Description (string) -- The retrieved task description. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string', 'WindowTaskId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TaskArn': 'string', 'ServiceRoleArn': 'string', 'TaskType': 'RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', 'TaskParameters': { 'string': { 'Values': [ 'string', ] } }, 'TaskInvocationParameters': { 'RunCommand': { 'Comment': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'DocumentHash': 'string', 'DocumentHashType': 'Sha256'|'Sha1', 'DocumentVersion': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'Parameters': { 'string': [ 'string', ] }, 'ServiceRoleArn': 'string', 'TimeoutSeconds': 123 }, 'Automation': { 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] } }, 'StepFunctions': { 'Input': 'string', 'Name': 'string' }, 'Lambda': { 'ClientContext': 'string', 'Qualifier': 'string', 'Payload': b'bytes' } }, 'Priority': 123, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'LoggingInfo': { 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, 'Name': 'string', 'Description': 'string' } :returns: ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` """ pass def get_ops_item(OpsItemId=None): """ Get information about an OpsItem by using the ID. You must have permission in AWS Identity and Access Management (IAM) to view information about an OpsItem. For more information, see Getting started with OpsCenter in the AWS Systems Manager User Guide . Operations engineers and IT professionals use OpsCenter to view, investigate, and remediate operational issues impacting the performance and health of their AWS resources. For more information, see AWS Systems Manager OpsCenter in the AWS Systems Manager User Guide . See also: AWS API Documentation Exceptions :example: response = client.get_ops_item( OpsItemId='string' ) :type OpsItemId: string :param OpsItemId: [REQUIRED]\nThe ID of the OpsItem that you want to get.\n :rtype: dict ReturnsResponse Syntax{ 'OpsItem': { 'CreatedBy': 'string', 'CreatedTime': datetime(2015, 1, 1), 'Description': 'string', 'LastModifiedBy': 'string', 'LastModifiedTime': datetime(2015, 1, 1), 'Notifications': [ { 'Arn': 'string' }, ], 'Priority': 123, 'RelatedOpsItems': [ { 'OpsItemId': 'string' }, ], 'Status': 'Open'|'InProgress'|'Resolved', 'OpsItemId': 'string', 'Version': 'string', 'Title': 'string', 'Source': 'string', 'OperationalData': { 'string': { 'Value': 'string', 'Type': 'SearchableString'|'String' } }, 'Category': 'string', 'Severity': 'string' } } Response Structure (dict) -- OpsItem (dict) --The OpsItem. CreatedBy (string) --The ARN of the AWS account that created the OpsItem. CreatedTime (datetime) --The date and time the OpsItem was created. Description (string) --The OpsItem description. LastModifiedBy (string) --The ARN of the AWS account that last updated the OpsItem. LastModifiedTime (datetime) --The date and time the OpsItem was last updated. Notifications (list) --The Amazon Resource Name (ARN) of an SNS topic where notifications are sent when this OpsItem is edited or changed. (dict) --A notification about the OpsItem. Arn (string) --The Amazon Resource Name (ARN) of an SNS topic where notifications are sent when this OpsItem is edited or changed. Priority (integer) --The importance of this OpsItem in relation to other OpsItems in the system. RelatedOpsItems (list) --One or more OpsItems that share something in common with the current OpsItem. For example, related OpsItems can include OpsItems with similar error messages, impacted resources, or statuses for the impacted resource. (dict) --An OpsItems that shares something in common with the current OpsItem. For example, related OpsItems can include OpsItems with similar error messages, impacted resources, or statuses for the impacted resource. OpsItemId (string) --The ID of an OpsItem related to the current OpsItem. Status (string) --The OpsItem status. Status can be Open , In Progress , or Resolved . For more information, see Editing OpsItem details in the AWS Systems Manager User Guide . OpsItemId (string) --The ID of the OpsItem. Version (string) --The version of this OpsItem. Each time the OpsItem is edited the version number increments by one. Title (string) --A short heading that describes the nature of the OpsItem and the impacted resource. Source (string) --The origin of the OpsItem, such as Amazon EC2 or Systems Manager. The impacted resource is a subset of source. OperationalData (dict) --Operational data is custom data that provides useful reference details about the OpsItem. For example, you can specify log files, error strings, license keys, troubleshooting tips, or other relevant data. You enter operational data as key-value pairs. The key has a maximum length of 128 characters. The value has a maximum size of 20 KB. Warning Operational data keys can\'t begin with the following: amazon, aws, amzn, ssm, /amazon, /aws, /amzn, /ssm. You can choose to make the data searchable by other users in the account or you can restrict search access. Searchable data means that all users with access to the OpsItem Overview page (as provided by the DescribeOpsItems API action) can view and search on the specified data. Operational data that is not searchable is only viewable by users who have access to the OpsItem (as provided by the GetOpsItem API action). Use the /aws/resources key in OperationalData to specify a related resource in the request. Use the /aws/automations key in OperationalData to associate an Automation runbook with the OpsItem. To view AWS CLI example commands that use these keys, see Creating OpsItems manually in the AWS Systems Manager User Guide . (string) -- (dict) --An object that defines the value of the key and its type in the OperationalData map. Value (string) --The value of the OperationalData key. Type (string) --The type of key-value pair. Valid types include SearchableString and String . Category (string) --An OpsItem category. Category options include: Availability, Cost, Performance, Recovery, Security. Severity (string) --The severity of the OpsItem. Severity options range from 1 to 4. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.OpsItemNotFoundException :return: { 'OpsItem': { 'CreatedBy': 'string', 'CreatedTime': datetime(2015, 1, 1), 'Description': 'string', 'LastModifiedBy': 'string', 'LastModifiedTime': datetime(2015, 1, 1), 'Notifications': [ { 'Arn': 'string' }, ], 'Priority': 123, 'RelatedOpsItems': [ { 'OpsItemId': 'string' }, ], 'Status': 'Open'|'InProgress'|'Resolved', 'OpsItemId': 'string', 'Version': 'string', 'Title': 'string', 'Source': 'string', 'OperationalData': { 'string': { 'Value': 'string', 'Type': 'SearchableString'|'String' } }, 'Category': 'string', 'Severity': 'string' } } """ pass def get_ops_summary(SyncName=None, Filters=None, Aggregators=None, ResultAttributes=None, NextToken=None, MaxResults=None): """ View a summary of OpsItems based on specified filters and aggregators. See also: AWS API Documentation Exceptions :example: response = client.get_ops_summary( SyncName='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'Equal'|'NotEqual'|'BeginWith'|'LessThan'|'GreaterThan'|'Exists' }, ], Aggregators=[ { 'AggregatorType': 'string', 'TypeName': 'string', 'AttributeName': 'string', 'Values': { 'string': 'string' }, 'Filters': [ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'Equal'|'NotEqual'|'BeginWith'|'LessThan'|'GreaterThan'|'Exists' }, ], 'Aggregators': {'... recursive ...'} }, ], ResultAttributes=[ { 'TypeName': 'string' }, ], NextToken='string', MaxResults=123 ) :type SyncName: string :param SyncName: Specify the name of a resource data sync to get. :type Filters: list :param Filters: Optional filters used to scope down the returned OpsItems.\n\n(dict) --A filter for viewing OpsItem summaries.\n\nKey (string) -- [REQUIRED]The name of the filter.\n\nValues (list) -- [REQUIRED]The filter value.\n\n(string) --\n\n\nType (string) --The type of filter.\n\n\n\n\n :type Aggregators: list :param Aggregators: Optional aggregators that return counts of OpsItems based on one or more expressions.\n\n(dict) --One or more aggregators for viewing counts of OpsItems using different dimensions such as Source , CreatedTime , or Source and CreatedTime , to name a few.\n\nAggregatorType (string) --Either a Range or Count aggregator for limiting an OpsItem summary.\n\nTypeName (string) --The data type name to use for viewing counts of OpsItems.\n\nAttributeName (string) --The name of an OpsItem attribute on which to limit the count of OpsItems.\n\nValues (dict) --The aggregator value.\n\n(string) --\n(string) --\n\n\n\n\nFilters (list) --The aggregator filters.\n\n(dict) --A filter for viewing OpsItem summaries.\n\nKey (string) -- [REQUIRED]The name of the filter.\n\nValues (list) -- [REQUIRED]The filter value.\n\n(string) --\n\n\nType (string) --The type of filter.\n\n\n\n\n\nAggregators (list) --A nested aggregator for viewing counts of OpsItems.\n\n\n\n\n :type ResultAttributes: list :param ResultAttributes: The OpsItem data type to return.\n\n(dict) --The OpsItem data type to return.\n\nTypeName (string) -- [REQUIRED]Name of the data type. Valid value: AWS:OpsItem, AWS:EC2InstanceInformation, AWS:OpsItemTrendline, or AWS:ComplianceSummary.\n\n\n\n\n :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'Entities': [ { 'Id': 'string', 'Data': { 'string': { 'CaptureTime': 'string', 'Content': [ { 'string': 'string' }, ] } } }, ], 'NextToken': 'string' } Response Structure (dict) -- Entities (list) -- The list of aggregated and filtered OpsItems. (dict) -- The result of the query. Id (string) -- The query ID. Data (dict) -- The data returned by the query. (string) -- (dict) -- The OpsItem summaries result item. CaptureTime (string) -- The time OpsItem data was captured. Content (list) -- The detailed data content for an OpsItem summaries result item. (dict) -- (string) -- (string) -- NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ResourceDataSyncNotFoundException SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidAggregatorException :return: { 'Entities': [ { 'Id': 'string', 'Data': { 'string': { 'CaptureTime': 'string', 'Content': [ { 'string': 'string' }, ] } } }, ], 'NextToken': 'string' } :returns: (dict) -- (string) -- (string) -- """ pass def get_paginator(operation_name=None): """ Create a paginator for an operation. :type operation_name: string :param operation_name: The operation name. This is the same name\nas the method name on the client. For example, if the\nmethod name is create_foo, and you\'d normally invoke the\noperation as client.create_foo(**kwargs), if the\ncreate_foo operation can be paginated, you can use the\ncall client.get_paginator('create_foo'). :rtype: L{botocore.paginate.Paginator} ReturnsA paginator object. """ pass def get_parameter(Name=None, WithDecryption=None): """ Get information about a parameter by using the parameter name. Don\'t confuse this API action with the GetParameters API action. See also: AWS API Documentation Exceptions :example: response = client.get_parameter( Name='string', WithDecryption=True|False ) :type Name: string :param Name: [REQUIRED]\nThe name of the parameter you want to query.\n :type WithDecryption: boolean :param WithDecryption: Return decrypted values for secure string parameters. This flag is ignored for String and StringList parameter types. :rtype: dict ReturnsResponse Syntax { 'Parameter': { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'Value': 'string', 'Version': 123, 'Selector': 'string', 'SourceResult': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'ARN': 'string', 'DataType': 'string' } } Response Structure (dict) -- Parameter (dict) -- Information about a parameter. Name (string) -- The name of the parameter. Type (string) -- The type of parameter. Valid values include the following: String , StringList , and SecureString . Value (string) -- The parameter value. Version (integer) -- The parameter version. Selector (string) -- Either the version number or the label used to retrieve the parameter value. Specify selectors by using one of the following formats: parameter_name:version parameter_name:label SourceResult (string) -- Applies to parameters that reference information in other AWS services. SourceResult is the raw result or response from the source. LastModifiedDate (datetime) -- Date the parameter was last changed or updated and the parameter version was created. ARN (string) -- The Amazon Resource Name (ARN) of the parameter. DataType (string) -- The data type of the parameter, such as text or aws:ec2:image . The default is text . Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidKeyId SSM.Client.exceptions.ParameterNotFound SSM.Client.exceptions.ParameterVersionNotFound :return: { 'Parameter': { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'Value': 'string', 'Version': 123, 'Selector': 'string', 'SourceResult': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'ARN': 'string', 'DataType': 'string' } } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidKeyId SSM.Client.exceptions.ParameterNotFound SSM.Client.exceptions.ParameterVersionNotFound """ pass def get_parameter_history(Name=None, WithDecryption=None, MaxResults=None, NextToken=None): """ Query a list of all parameters used by the AWS account. See also: AWS API Documentation Exceptions :example: response = client.get_parameter_history( Name='string', WithDecryption=True|False, MaxResults=123, NextToken='string' ) :type Name: string :param Name: [REQUIRED]\nThe name of a parameter you want to query.\n :type WithDecryption: boolean :param WithDecryption: Return decrypted values for secure string parameters. This flag is ignored for String and StringList parameter types. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'KeyId': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'Description': 'string', 'Value': 'string', 'AllowedPattern': 'string', 'Version': 123, 'Labels': [ 'string', ], 'Tier': 'Standard'|'Advanced'|'Intelligent-Tiering', 'Policies': [ { 'PolicyText': 'string', 'PolicyType': 'string', 'PolicyStatus': 'string' }, ], 'DataType': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Parameters (list) -- A list of parameters returned by the request. (dict) -- Information about parameter usage. Name (string) -- The name of the parameter. Type (string) -- The type of parameter used. KeyId (string) -- The ID of the query key used for this parameter. LastModifiedDate (datetime) -- Date the parameter was last changed or updated. LastModifiedUser (string) -- Amazon Resource Name (ARN) of the AWS user who last changed the parameter. Description (string) -- Information about the parameter. Value (string) -- The parameter value. AllowedPattern (string) -- Parameter names can include the following letters and symbols. a-zA-Z0-9_.- Version (integer) -- The parameter version. Labels (list) -- Labels assigned to the parameter version. (string) -- Tier (string) -- The parameter tier. Policies (list) -- Information about the policies assigned to a parameter. Assigning parameter policies in the AWS Systems Manager User Guide . (dict) -- One or more policies assigned to a parameter. PolicyText (string) -- The JSON text of the policy. PolicyType (string) -- The type of policy. Parameter Store supports the following policy types: Expiration, ExpirationNotification, and NoChangeNotification. PolicyStatus (string) -- The status of the policy. Policies report the following statuses: Pending (the policy has not been enforced or applied yet), Finished (the policy was applied), Failed (the policy was not applied), or InProgress (the policy is being applied now). DataType (string) -- The data type of the parameter, such as text or aws:ec2:image . The default is text . NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ParameterNotFound SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidKeyId :return: { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'KeyId': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'Description': 'string', 'Value': 'string', 'AllowedPattern': 'string', 'Version': 123, 'Labels': [ 'string', ], 'Tier': 'Standard'|'Advanced'|'Intelligent-Tiering', 'Policies': [ { 'PolicyText': 'string', 'PolicyType': 'string', 'PolicyStatus': 'string' }, ], 'DataType': 'string' }, ], 'NextToken': 'string' } :returns: (string) -- """ pass def get_parameters(Names=None, WithDecryption=None): """ Get details of a parameter. Don\'t confuse this API action with the GetParameter API action. See also: AWS API Documentation Exceptions :example: response = client.get_parameters( Names=[ 'string', ], WithDecryption=True|False ) :type Names: list :param Names: [REQUIRED]\nNames of the parameters for which you want to query information.\n\n(string) --\n\n :type WithDecryption: boolean :param WithDecryption: Return decrypted secure string value. Return decrypted values for secure string parameters. This flag is ignored for String and StringList parameter types. :rtype: dict ReturnsResponse Syntax { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'Value': 'string', 'Version': 123, 'Selector': 'string', 'SourceResult': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'ARN': 'string', 'DataType': 'string' }, ], 'InvalidParameters': [ 'string', ] } Response Structure (dict) -- Parameters (list) -- A list of details for a parameter. (dict) -- An Systems Manager parameter in Parameter Store. Name (string) -- The name of the parameter. Type (string) -- The type of parameter. Valid values include the following: String , StringList , and SecureString . Value (string) -- The parameter value. Version (integer) -- The parameter version. Selector (string) -- Either the version number or the label used to retrieve the parameter value. Specify selectors by using one of the following formats: parameter_name:version parameter_name:label SourceResult (string) -- Applies to parameters that reference information in other AWS services. SourceResult is the raw result or response from the source. LastModifiedDate (datetime) -- Date the parameter was last changed or updated and the parameter version was created. ARN (string) -- The Amazon Resource Name (ARN) of the parameter. DataType (string) -- The data type of the parameter, such as text or aws:ec2:image . The default is text . InvalidParameters (list) -- A list of parameters that are not formatted correctly or do not run during an execution. (string) -- Exceptions SSM.Client.exceptions.InvalidKeyId SSM.Client.exceptions.InternalServerError :return: { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'Value': 'string', 'Version': 123, 'Selector': 'string', 'SourceResult': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'ARN': 'string', 'DataType': 'string' }, ], 'InvalidParameters': [ 'string', ] } :returns: (string) -- """ pass def get_parameters_by_path(Path=None, Recursive=None, ParameterFilters=None, WithDecryption=None, MaxResults=None, NextToken=None): """ Retrieve information about one or more parameters in a specific hierarchy. See also: AWS API Documentation Exceptions :example: response = client.get_parameters_by_path( Path='string', Recursive=True|False, ParameterFilters=[ { 'Key': 'string', 'Option': 'string', 'Values': [ 'string', ] }, ], WithDecryption=True|False, MaxResults=123, NextToken='string' ) :type Path: string :param Path: [REQUIRED]\nThe hierarchy for the parameter. Hierarchies start with a forward slash (/) and end with the parameter name. A parameter name hierarchy can have a maximum of 15 levels. Here is an example of a hierarchy: /Finance/Prod/IAD/WinServ2016/license33\n :type Recursive: boolean :param Recursive: Retrieve all parameters within a hierarchy.\n\nWarning\nIf a user has access to a path, then the user can access all levels of that path. For example, if a user has permission to access path /a , then the user can also access /a/b . Even if a user has explicitly been denied access in IAM for parameter /a/b , they can still call the GetParametersByPath API action recursively for /a and view /a/b .\n\n :type ParameterFilters: list :param ParameterFilters: Filters to limit the request results.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nWarning\nThe ParameterStringFilter object is used by the DescribeParameters and GetParametersByPath API actions. However, not all of the pattern values listed for Key can be used with both actions.\nFor DescribeActions , all of the listed patterns are valid, with the exception of Label .\nFor GetParametersByPath , the following patterns listed for Key are not valid: Name , Path , and Tier .\nFor examples of CLI commands demonstrating valid parameter filter constructions, see Searching for Systems Manager parameters in the AWS Systems Manager User Guide .\n\n\nKey (string) -- [REQUIRED]The name of the filter.\n\nOption (string) --For all filters used with DescribeParameters , valid options include Equals and BeginsWith . The Name filter additionally supports the Contains option. (Exception: For filters using the key Path , valid options include Recursive and OneLevel .)\nFor filters used with GetParametersByPath , valid options include Equals and BeginsWith . (Exception: For filters using the key Label , the only valid option is Equals .)\n\nValues (list) --The value you want to search for.\n\n(string) --\n\n\n\n\n\n :type WithDecryption: boolean :param WithDecryption: Retrieve all parameters in a hierarchy with their value decrypted. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'Value': 'string', 'Version': 123, 'Selector': 'string', 'SourceResult': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'ARN': 'string', 'DataType': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Parameters (list) -- A list of parameters found in the specified hierarchy. (dict) -- An Systems Manager parameter in Parameter Store. Name (string) -- The name of the parameter. Type (string) -- The type of parameter. Valid values include the following: String , StringList , and SecureString . Value (string) -- The parameter value. Version (integer) -- The parameter version. Selector (string) -- Either the version number or the label used to retrieve the parameter value. Specify selectors by using one of the following formats: parameter_name:version parameter_name:label SourceResult (string) -- Applies to parameters that reference information in other AWS services. SourceResult is the raw result or response from the source. LastModifiedDate (datetime) -- Date the parameter was last changed or updated and the parameter version was created. ARN (string) -- The Amazon Resource Name (ARN) of the parameter. DataType (string) -- The data type of the parameter, such as text or aws:ec2:image . The default is text . NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidFilterOption SSM.Client.exceptions.InvalidFilterValue SSM.Client.exceptions.InvalidKeyId SSM.Client.exceptions.InvalidNextToken :return: { 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList'|'SecureString', 'Value': 'string', 'Version': 123, 'Selector': 'string', 'SourceResult': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'ARN': 'string', 'DataType': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidFilterOption SSM.Client.exceptions.InvalidFilterValue SSM.Client.exceptions.InvalidKeyId SSM.Client.exceptions.InvalidNextToken """ pass def get_patch_baseline(BaselineId=None): """ Retrieves information about a patch baseline. See also: AWS API Documentation Exceptions :example: response = client.get_patch_baseline( BaselineId='string' ) :type BaselineId: string :param BaselineId: [REQUIRED]\nThe ID of the patch baseline to retrieve.\n :rtype: dict ReturnsResponse Syntax{ 'BaselineId': 'string', 'Name': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'GlobalFilters': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ApprovalRules': { 'PatchRules': [ { 'PatchFilterGroup': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApproveAfterDays': 123, 'ApproveUntilDate': 'string', 'EnableNonSecurity': True|False }, ] }, 'ApprovedPatches': [ 'string', ], 'ApprovedPatchesComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApprovedPatchesEnableNonSecurity': True|False, 'RejectedPatches': [ 'string', ], 'RejectedPatchesAction': 'ALLOW_AS_DEPENDENCY'|'BLOCK', 'PatchGroups': [ 'string', ], 'CreatedDate': datetime(2015, 1, 1), 'ModifiedDate': datetime(2015, 1, 1), 'Description': 'string', 'Sources': [ { 'Name': 'string', 'Products': [ 'string', ], 'Configuration': 'string' }, ] } Response Structure (dict) -- BaselineId (string) --The ID of the retrieved patch baseline. Name (string) --The name of the patch baseline. OperatingSystem (string) --Returns the operating system specified for the patch baseline. GlobalFilters (dict) --A set of global filters used to exclude patches from the baseline. PatchFilters (list) --The set of patch filters that make up the group. (dict) --Defines which patches should be included in a patch baseline. A patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ["Office 2013", "Office 2016"], then the filter accepts all patches where product name is either "Office 2013" or "Office 2016". The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values. You can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties . Key (string) --The key for the filter. Run the DescribePatchProperties command to view lists of valid keys for each operating system type. Values (list) --The value for the filter key. Run the DescribePatchProperties command to view lists of valid values for each key based on operating system type. (string) -- ApprovalRules (dict) --A set of rules used to include patches in the baseline. PatchRules (list) --The rules that make up the rule group. (dict) --Defines an approval rule for a patch baseline. PatchFilterGroup (dict) --The patch filter group that defines the criteria for the rule. PatchFilters (list) --The set of patch filters that make up the group. (dict) --Defines which patches should be included in a patch baseline. A patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ["Office 2013", "Office 2016"], then the filter accepts all patches where product name is either "Office 2013" or "Office 2016". The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values. You can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties . Key (string) --The key for the filter. Run the DescribePatchProperties command to view lists of valid keys for each operating system type. Values (list) --The value for the filter key. Run the DescribePatchProperties command to view lists of valid values for each key based on operating system type. (string) -- ComplianceLevel (string) --A compliance severity level for all approved patches in a patch baseline. ApproveAfterDays (integer) --The number of days after the release date of each patch matched by the rule that the patch is marked as approved in the patch baseline. For example, a value of 7 means that patches are approved seven days after they are released. Not supported on Ubuntu Server. ApproveUntilDate (string) --The cutoff date for auto approval of released patches. Any patches released on or before this date are installed automatically. Not supported on Ubuntu Server. Enter dates in the format YYYY-MM-DD . For example, 2020-12-31 . EnableNonSecurity (boolean) --For instances identified by the approval rule filters, enables a patch baseline to apply non-security updates available in the specified repository. The default value is \'false\'. Applies to Linux instances only. ApprovedPatches (list) --A list of explicitly approved patches for the baseline. (string) -- ApprovedPatchesComplianceLevel (string) --Returns the specified compliance severity level for approved patches in the patch baseline. ApprovedPatchesEnableNonSecurity (boolean) --Indicates whether the list of approved patches includes non-security updates that should be applied to the instances. The default value is \'false\'. Applies to Linux instances only. RejectedPatches (list) --A list of explicitly rejected patches for the baseline. (string) -- RejectedPatchesAction (string) --The action specified to take on patches included in the RejectedPatches list. A patch can be allowed only if it is a dependency of another package, or blocked entirely along with packages that include it as a dependency. PatchGroups (list) --Patch groups included in the patch baseline. (string) -- CreatedDate (datetime) --The date the patch baseline was created. ModifiedDate (datetime) --The date the patch baseline was last modified. Description (string) --A description of the patch baseline. Sources (list) --Information about the patches to use to update the instances, including target operating systems and source repositories. Applies to Linux instances only. (dict) --Information about the patches to use to update the instances, including target operating systems and source repository. Applies to Linux instances only. Name (string) --The name specified to identify the patch source. Products (list) --The specific operating system versions a patch repository applies to, such as "Ubuntu16.04", "AmazonLinux2016.09", "RedhatEnterpriseLinux7.2" or "Suse12.7". For lists of supported product values, see PatchFilter . (string) -- Configuration (string) --The value of the yum repo configuration. For example: [main]cachedir=/var/cache/yum/$basesearch$releasever keepcache=0 debuglevel=2 Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string', 'Name': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'GlobalFilters': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ApprovalRules': { 'PatchRules': [ { 'PatchFilterGroup': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApproveAfterDays': 123, 'ApproveUntilDate': 'string', 'EnableNonSecurity': True|False }, ] }, 'ApprovedPatches': [ 'string', ], 'ApprovedPatchesComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApprovedPatchesEnableNonSecurity': True|False, 'RejectedPatches': [ 'string', ], 'RejectedPatchesAction': 'ALLOW_AS_DEPENDENCY'|'BLOCK', 'PatchGroups': [ 'string', ], 'CreatedDate': datetime(2015, 1, 1), 'ModifiedDate': datetime(2015, 1, 1), 'Description': 'string', 'Sources': [ { 'Name': 'string', 'Products': [ 'string', ], 'Configuration': 'string' }, ] } :returns: (string) -- """ pass def get_patch_baseline_for_patch_group(PatchGroup=None, OperatingSystem=None): """ Retrieves the patch baseline that should be used for the specified patch group. See also: AWS API Documentation Exceptions :example: response = client.get_patch_baseline_for_patch_group( PatchGroup='string', OperatingSystem='WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN' ) :type PatchGroup: string :param PatchGroup: [REQUIRED]\nThe name of the patch group whose patch baseline should be retrieved.\n :type OperatingSystem: string :param OperatingSystem: Returns he operating system rule specified for patch groups using the patch baseline. :rtype: dict ReturnsResponse Syntax { 'BaselineId': 'string', 'PatchGroup': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN' } Response Structure (dict) -- BaselineId (string) -- The ID of the patch baseline that should be used for the patch group. PatchGroup (string) -- The name of the patch group. OperatingSystem (string) -- The operating system rule specified for patch groups using the patch baseline. Exceptions SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string', 'PatchGroup': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN' } :returns: SSM.Client.exceptions.InternalServerError """ pass def get_service_setting(SettingId=None): """ Services map a SettingId object to a setting value. AWS services teams define the default value for a SettingId . You can\'t create a new SettingId , but you can overwrite the default value if you have the ssm:UpdateServiceSetting permission for the setting. Use the UpdateServiceSetting API action to change the default setting. Or use the ResetServiceSetting to change the value back to the original value defined by the AWS service team. Query the current service setting for the account. See also: AWS API Documentation Exceptions :example: response = client.get_service_setting( SettingId='string' ) :type SettingId: string :param SettingId: [REQUIRED]\nThe ID of the service setting to get. The setting ID can be /ssm/parameter-store/default-parameter-tier , /ssm/parameter-store/high-throughput-enabled , or /ssm/managed-instance/activation-tier .\n :rtype: dict ReturnsResponse Syntax{ 'ServiceSetting': { 'SettingId': 'string', 'SettingValue': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'ARN': 'string', 'Status': 'string' } } Response Structure (dict) --The query result body of the GetServiceSetting API action. ServiceSetting (dict) --The query result of the current service setting. SettingId (string) --The ID of the service setting. SettingValue (string) --The value of the service setting. LastModifiedDate (datetime) --The last time the service setting was modified. LastModifiedUser (string) --The ARN of the last modified user. This field is populated only if the setting value was overwritten. ARN (string) --The ARN of the service setting. Status (string) --The status of the service setting. The value can be Default, Customized or PendingUpdate. Default: The current setting uses a default value provisioned by the AWS service team. Customized: The current setting use a custom value specified by the customer. PendingUpdate: The current setting uses a default or custom value, but a setting change request is pending approval. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ServiceSettingNotFound :return: { 'ServiceSetting': { 'SettingId': 'string', 'SettingValue': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'ARN': 'string', 'Status': 'string' } } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ServiceSettingNotFound """ pass def get_waiter(waiter_name=None): """ Returns an object that can wait for some condition. :type waiter_name: str :param waiter_name: The name of the waiter to get. See the waiters\nsection of the service docs for a list of available waiters. :rtype: botocore.waiter.Waiter """ pass def label_parameter_version(Name=None, ParameterVersion=None, Labels=None): """ A parameter label is a user-defined alias to help you manage different versions of a parameter. When you modify a parameter, Systems Manager automatically saves a new version and increments the version number by one. A label can help you remember the purpose of a parameter when there are multiple versions. Parameter labels have the following requirements and restrictions. See also: AWS API Documentation Exceptions :example: response = client.label_parameter_version( Name='string', ParameterVersion=123, Labels=[ 'string', ] ) :type Name: string :param Name: [REQUIRED]\nThe parameter name on which you want to attach one or more labels.\n :type ParameterVersion: integer :param ParameterVersion: The specific version of the parameter on which you want to attach one or more labels. If no version is specified, the system attaches the label to the latest version. :type Labels: list :param Labels: [REQUIRED]\nOne or more labels to attach to the specified parameter version.\n\n(string) --\n\n :rtype: dict ReturnsResponse Syntax { 'InvalidLabels': [ 'string', ], 'ParameterVersion': 123 } Response Structure (dict) -- InvalidLabels (list) -- The label does not meet the requirements. For information about parameter label requirements, see Labeling parameters in the AWS Systems Manager User Guide . (string) -- ParameterVersion (integer) -- The version of the parameter that has been labeled. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.TooManyUpdates SSM.Client.exceptions.ParameterNotFound SSM.Client.exceptions.ParameterVersionNotFound SSM.Client.exceptions.ParameterVersionLabelLimitExceeded :return: { 'InvalidLabels': [ 'string', ], 'ParameterVersion': 123 } :returns: Name (string) -- [REQUIRED] The parameter name on which you want to attach one or more labels. ParameterVersion (integer) -- The specific version of the parameter on which you want to attach one or more labels. If no version is specified, the system attaches the label to the latest version. Labels (list) -- [REQUIRED] One or more labels to attach to the specified parameter version. (string) -- """ pass def list_association_versions(AssociationId=None, MaxResults=None, NextToken=None): """ Retrieves all versions of an association for a specific association ID. See also: AWS API Documentation Exceptions :example: response = client.list_association_versions( AssociationId='string', MaxResults=123, NextToken='string' ) :type AssociationId: string :param AssociationId: [REQUIRED]\nThe association ID for which you want to view all versions.\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'AssociationVersions': [ { 'AssociationId': 'string', 'AssociationVersion': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Name': 'string', 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] }, 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' }, ], 'NextToken': 'string' } Response Structure (dict) -- AssociationVersions (list) -- Information about all versions of the association for the specified association ID. (dict) -- Information about the association version. AssociationId (string) -- The ID created by the system when the association was created. AssociationVersion (string) -- The association version. CreatedDate (datetime) -- The date the association version was created. Name (string) -- The name specified when the association was created. DocumentVersion (string) -- The version of a Systems Manager document used when the association version was created. Parameters (dict) -- Parameters specified when the association version was created. (string) -- (list) -- (string) -- Targets (list) -- The targets specified for the association when the association version was created. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- ScheduleExpression (string) -- The cron or rate schedule specified for the association when the association version was created. OutputLocation (dict) -- The location in Amazon S3 specified for the association when the association version was created. S3Location (dict) -- An S3 bucket where you want to store the results of this request. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) -- The name of the S3 bucket. OutputS3KeyPrefix (string) -- The S3 bucket subfolder. AssociationName (string) -- The name specified for the association version when the association version was created. MaxErrors (string) -- The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received. Executions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time. MaxConcurrency (string) -- The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time. If a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency. ComplianceSeverity (string) -- The severity level that is assigned to the association. SyncCompliance (string) -- The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT . In MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action. By default, all associations use AUTO mode. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.AssociationDoesNotExist :return: { 'AssociationVersions': [ { 'AssociationId': 'string', 'AssociationVersion': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Name': 'string', 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] }, 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' }, ], 'NextToken': 'string' } :returns: (string) -- (list) -- (string) -- """ pass def list_associations(AssociationFilterList=None, MaxResults=None, NextToken=None): """ Returns all State Manager associations in the current AWS account and Region. You can limit the results to a specific State Manager association document or instance by specifying a filter. See also: AWS API Documentation Exceptions :example: response = client.list_associations( AssociationFilterList=[ { 'key': 'InstanceId'|'Name'|'AssociationId'|'AssociationStatusName'|'LastExecutedBefore'|'LastExecutedAfter'|'AssociationName'|'ResourceGroupName', 'value': 'string' }, ], MaxResults=123, NextToken='string' ) :type AssociationFilterList: list :param AssociationFilterList: One or more filters. Use a filter to return a more specific list of results.\n\n(dict) --Describes a filter.\n\nkey (string) -- [REQUIRED]The name of the filter.\n\nvalue (string) -- [REQUIRED]The filter value.\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'Associations': [ { 'Name': 'string', 'InstanceId': 'string', 'AssociationId': 'string', 'AssociationVersion': 'string', 'DocumentVersion': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'LastExecutionDate': datetime(2015, 1, 1), 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'ScheduleExpression': 'string', 'AssociationName': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- Associations (list) -- The associations. (dict) -- Describes an association of a Systems Manager document and an instance. Name (string) -- The name of the Systems Manager document. InstanceId (string) -- The ID of the instance. AssociationId (string) -- The ID created by the system when you create an association. An association is a binding between a document and a set of targets with a schedule. AssociationVersion (string) -- The association version. DocumentVersion (string) -- The version of the document used in the association. Targets (list) -- The instances targeted by the request to create an association. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- LastExecutionDate (datetime) -- The date on which the association was last run. Overview (dict) -- Information about the association. Status (string) -- The status of the association. Status can be: Pending, Success, or Failed. DetailedStatus (string) -- A detailed status of the association. AssociationStatusAggregatedCount (dict) -- Returns the number of targets for the association status. For example, if you created an association with two instances, and one of them was successful, this would return the count of instances by status. (string) -- (integer) -- ScheduleExpression (string) -- A cron expression that specifies a schedule when the association runs. AssociationName (string) -- The association name. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken :return: { 'Associations': [ { 'Name': 'string', 'InstanceId': 'string', 'AssociationId': 'string', 'AssociationVersion': 'string', 'DocumentVersion': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'LastExecutionDate': datetime(2015, 1, 1), 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'ScheduleExpression': 'string', 'AssociationName': 'string' }, ], 'NextToken': 'string' } :returns: ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` """ pass def list_command_invocations(CommandId=None, InstanceId=None, MaxResults=None, NextToken=None, Filters=None, Details=None): """ An invocation is copy of a command sent to a specific instance. A command can apply to one or more instances. A command invocation applies to one instance. For example, if a user runs SendCommand against three instances, then a command invocation is created for each requested instance ID. ListCommandInvocations provide status about command execution. See also: AWS API Documentation Exceptions :example: response = client.list_command_invocations( CommandId='string', InstanceId='string', MaxResults=123, NextToken='string', Filters=[ { 'key': 'InvokedAfter'|'InvokedBefore'|'Status'|'ExecutionStage'|'DocumentName', 'value': 'string' }, ], Details=True|False ) :type CommandId: string :param CommandId: (Optional) The invocations for a specific command ID. :type InstanceId: string :param InstanceId: (Optional) The command execution details for a specific instance ID. :type MaxResults: integer :param MaxResults: (Optional) The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: (Optional) The token for the next set of items to return. (You received this token from a previous call.) :type Filters: list :param Filters: (Optional) One or more filters. Use a filter to return a more specific list of results.\n\n(dict) --Describes a command filter.\n\nkey (string) -- [REQUIRED]The name of the filter.\n\nvalue (string) -- [REQUIRED]The filter value. Valid values for each filter key are as follows:\n\nInvokedAfter : Specify a timestamp to limit your results. For example, specify 2018-07-07T00:00:00Z to see a list of command executions occurring July 7, 2018, and later.\nInvokedBefore : Specify a timestamp to limit your results. For example, specify 2018-07-07T00:00:00Z to see a list of command executions from before July 7, 2018.\nStatus : Specify a valid command status to see a list of all command executions with that status. Status values you can specify include:\nPending\nInProgress\nSuccess\nCancelled\nFailed\nTimedOut\nCancelling\n\n\nDocumentName : Specify name of the SSM document for which you want to see command execution results. For example, specify AWS-RunPatchBaseline to see command executions that used this SSM document to perform security patching operations on instances.\nExecutionStage : Specify one of the following values:\nExecuting : Returns a list of command executions that are currently still running.\nComplete : Returns a list of command executions that have already completed.\n\n\n\n\n\n\n\n :type Details: boolean :param Details: (Optional) If set this returns the response of the command executions and any command output. By default this is set to False. :rtype: dict ReturnsResponse Syntax { 'CommandInvocations': [ { 'CommandId': 'string', 'InstanceId': 'string', 'InstanceName': 'string', 'Comment': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'RequestedDateTime': datetime(2015, 1, 1), 'Status': 'Pending'|'InProgress'|'Delayed'|'Success'|'Cancelled'|'TimedOut'|'Failed'|'Cancelling', 'StatusDetails': 'string', 'TraceOutput': 'string', 'StandardOutputUrl': 'string', 'StandardErrorUrl': 'string', 'CommandPlugins': [ { 'Name': 'string', 'Status': 'Pending'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', 'StatusDetails': 'string', 'ResponseCode': 123, 'ResponseStartDateTime': datetime(2015, 1, 1), 'ResponseFinishDateTime': datetime(2015, 1, 1), 'Output': 'string', 'StandardOutputUrl': 'string', 'StandardErrorUrl': 'string', 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' }, ], 'ServiceRole': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False } }, ], 'NextToken': 'string' } Response Structure (dict) -- CommandInvocations (list) -- (Optional) A list of all invocations. (dict) -- An invocation is copy of a command sent to a specific instance. A command can apply to one or more instances. A command invocation applies to one instance. For example, if a user runs SendCommand against three instances, then a command invocation is created for each requested instance ID. A command invocation returns status and detail information about a command you ran. CommandId (string) -- The command against which this invocation was requested. InstanceId (string) -- The instance ID in which this invocation was requested. InstanceName (string) -- The name of the invocation target. For EC2 instances this is the value for the aws:Name tag. For on-premises instances, this is the name of the instance. Comment (string) -- User-specified information about the command, such as a brief description of what the command should do. DocumentName (string) -- The document name that was requested for execution. DocumentVersion (string) -- The SSM document version. RequestedDateTime (datetime) -- The time and date the request was sent to this instance. Status (string) -- Whether or not the invocation succeeded, failed, or is pending. StatusDetails (string) -- A detailed status of the command execution for each invocation (each instance targeted by the command). StatusDetails includes more information than Status because it includes states resulting from error and concurrency control parameters. StatusDetails can show different results than Status. For more information about these statuses, see Understanding command statuses in the AWS Systems Manager User Guide . StatusDetails can be one of the following values: Pending: The command has not been sent to the instance. In Progress: The command has been sent to the instance but has not reached a terminal state. Success: The execution of the command or plugin was successfully completed. This is a terminal state. Delivery Timed Out: The command was not delivered to the instance before the delivery timeout expired. Delivery timeouts do not count against the parent command\'s MaxErrors limit, but they do contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Execution Timed Out: Command execution started on the instance, but the execution was not complete before the execution timeout expired. Execution timeouts count against the MaxErrors limit of the parent command. This is a terminal state. Failed: The command was not successful on the instance. For a plugin, this indicates that the result code was not zero. For a command invocation, this indicates that the result code for one or more plugins was not zero. Invocation failures count against the MaxErrors limit of the parent command. This is a terminal state. Canceled: The command was terminated before it was completed. This is a terminal state. Undeliverable: The command can\'t be delivered to the instance. The instance might not exist or might not be responding. Undeliverable invocations don\'t count against the parent command\'s MaxErrors limit and don\'t contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Terminated: The parent command exceeded its MaxErrors limit and subsequent command invocations were canceled by the system. This is a terminal state. TraceOutput (string) -- Gets the trace output sent by the agent. StandardOutputUrl (string) -- The URL to the plugin\'s StdOut file in Amazon S3, if the S3 bucket was defined for the parent command. For an invocation, StandardOutputUrl is populated if there is just one plugin defined for the command, and the S3 bucket was defined for the command. StandardErrorUrl (string) -- The URL to the plugin\'s StdErr file in Amazon S3, if the S3 bucket was defined for the parent command. For an invocation, StandardErrorUrl is populated if there is just one plugin defined for the command, and the S3 bucket was defined for the command. CommandPlugins (list) -- (dict) -- Describes plugin details. Name (string) -- The name of the plugin. Must be one of the following: aws:updateAgent, aws:domainjoin, aws:applications, aws:runPowerShellScript, aws:psmodule, aws:cloudWatch, aws:runShellScript, or aws:updateSSMAgent. Status (string) -- The status of this plugin. You can run a document with multiple plugins. StatusDetails (string) -- A detailed status of the plugin execution. StatusDetails includes more information than Status because it includes states resulting from error and concurrency control parameters. StatusDetails can show different results than Status. For more information about these statuses, see Understanding command statuses in the AWS Systems Manager User Guide . StatusDetails can be one of the following values: Pending: The command has not been sent to the instance. In Progress: The command has been sent to the instance but has not reached a terminal state. Success: The execution of the command or plugin was successfully completed. This is a terminal state. Delivery Timed Out: The command was not delivered to the instance before the delivery timeout expired. Delivery timeouts do not count against the parent command\'s MaxErrors limit, but they do contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Execution Timed Out: Command execution started on the instance, but the execution was not complete before the execution timeout expired. Execution timeouts count against the MaxErrors limit of the parent command. This is a terminal state. Failed: The command was not successful on the instance. For a plugin, this indicates that the result code was not zero. For a command invocation, this indicates that the result code for one or more plugins was not zero. Invocation failures count against the MaxErrors limit of the parent command. This is a terminal state. Canceled: The command was terminated before it was completed. This is a terminal state. Undeliverable: The command can\'t be delivered to the instance. The instance might not exist, or it might not be responding. Undeliverable invocations don\'t count against the parent command\'s MaxErrors limit, and they don\'t contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Terminated: The parent command exceeded its MaxErrors limit and subsequent command invocations were canceled by the system. This is a terminal state. ResponseCode (integer) -- A numeric response code generated after running the plugin. ResponseStartDateTime (datetime) -- The time the plugin started running. ResponseFinishDateTime (datetime) -- The time the plugin stopped running. Could stop prematurely if, for example, a cancel command was sent. Output (string) -- Output of the plugin execution. StandardOutputUrl (string) -- The URL for the complete text written by the plugin to stdout in Amazon S3. If the S3 bucket for the command was not specified, then this string is empty. StandardErrorUrl (string) -- The URL for the complete text written by the plugin to stderr. If execution is not yet complete, then this string is empty. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the S3 bucket region. OutputS3BucketName (string) -- The S3 bucket where the responses to the command executions should be stored. This was requested when issuing the command. For example, in the following response: test_folder/ab19cb99-a030-46dd-9dfc-8eSAMPLEPre-Fix/i-1234567876543/awsrunShellScript test_folder is the name of the S3 bucket; ab19cb99-a030-46dd-9dfc-8eSAMPLEPre-Fix is the name of the S3 prefix; i-1234567876543 is the instance ID; awsrunShellScript is the name of the plugin. OutputS3KeyPrefix (string) -- The S3 directory path inside the bucket where the responses to the command executions should be stored. This was requested when issuing the command. For example, in the following response: test_folder/ab19cb99-a030-46dd-9dfc-8eSAMPLEPre-Fix/i-1234567876543/awsrunShellScript test_folder is the name of the S3 bucket; ab19cb99-a030-46dd-9dfc-8eSAMPLEPre-Fix is the name of the S3 prefix; i-1234567876543 is the instance ID; awsrunShellScript is the name of the plugin. ServiceRole (string) -- The IAM service role that Run Command uses to act on your behalf when sending notifications about command status changes on a per instance basis. NotificationConfig (dict) -- Configurations for sending notifications about command status changes on a per instance basis. NotificationArn (string) -- An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic. NotificationEvents (list) -- The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide . (string) -- NotificationType (string) -- Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes. CloudWatchOutputConfig (dict) -- CloudWatch Logs information where you want Systems Manager to send the command output. CloudWatchLogGroupName (string) -- The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName . CloudWatchOutputEnabled (boolean) -- Enables Systems Manager to send command output to CloudWatch Logs. NextToken (string) -- (Optional) The token for the next set of items to return. (You received this token from a previous call.) Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidCommandId SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidNextToken :return: { 'CommandInvocations': [ { 'CommandId': 'string', 'InstanceId': 'string', 'InstanceName': 'string', 'Comment': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'RequestedDateTime': datetime(2015, 1, 1), 'Status': 'Pending'|'InProgress'|'Delayed'|'Success'|'Cancelled'|'TimedOut'|'Failed'|'Cancelling', 'StatusDetails': 'string', 'TraceOutput': 'string', 'StandardOutputUrl': 'string', 'StandardErrorUrl': 'string', 'CommandPlugins': [ { 'Name': 'string', 'Status': 'Pending'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', 'StatusDetails': 'string', 'ResponseCode': 123, 'ResponseStartDateTime': datetime(2015, 1, 1), 'ResponseFinishDateTime': datetime(2015, 1, 1), 'Output': 'string', 'StandardOutputUrl': 'string', 'StandardErrorUrl': 'string', 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' }, ], 'ServiceRole': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False } }, ], 'NextToken': 'string' } :returns: Pending: The command has not been sent to the instance. In Progress: The command has been sent to the instance but has not reached a terminal state. Success: The execution of the command or plugin was successfully completed. This is a terminal state. Delivery Timed Out: The command was not delivered to the instance before the delivery timeout expired. Delivery timeouts do not count against the parent command\'s MaxErrors limit, but they do contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Execution Timed Out: Command execution started on the instance, but the execution was not complete before the execution timeout expired. Execution timeouts count against the MaxErrors limit of the parent command. This is a terminal state. Failed: The command was not successful on the instance. For a plugin, this indicates that the result code was not zero. For a command invocation, this indicates that the result code for one or more plugins was not zero. Invocation failures count against the MaxErrors limit of the parent command. This is a terminal state. Canceled: The command was terminated before it was completed. This is a terminal state. Undeliverable: The command can\'t be delivered to the instance. The instance might not exist or might not be responding. Undeliverable invocations don\'t count against the parent command\'s MaxErrors limit and don\'t contribute to whether the parent command status is Success or Incomplete. This is a terminal state. Terminated: The parent command exceeded its MaxErrors limit and subsequent command invocations were canceled by the system. This is a terminal state. """ pass def list_commands(CommandId=None, InstanceId=None, MaxResults=None, NextToken=None, Filters=None): """ Lists the commands requested by users of the AWS account. See also: AWS API Documentation Exceptions :example: response = client.list_commands( CommandId='string', InstanceId='string', MaxResults=123, NextToken='string', Filters=[ { 'key': 'InvokedAfter'|'InvokedBefore'|'Status'|'ExecutionStage'|'DocumentName', 'value': 'string' }, ] ) :type CommandId: string :param CommandId: (Optional) If provided, lists only the specified command. :type InstanceId: string :param InstanceId: (Optional) Lists commands issued against this instance ID. :type MaxResults: integer :param MaxResults: (Optional) The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: (Optional) The token for the next set of items to return. (You received this token from a previous call.) :type Filters: list :param Filters: (Optional) One or more filters. Use a filter to return a more specific list of results.\n\n(dict) --Describes a command filter.\n\nkey (string) -- [REQUIRED]The name of the filter.\n\nvalue (string) -- [REQUIRED]The filter value. Valid values for each filter key are as follows:\n\nInvokedAfter : Specify a timestamp to limit your results. For example, specify 2018-07-07T00:00:00Z to see a list of command executions occurring July 7, 2018, and later.\nInvokedBefore : Specify a timestamp to limit your results. For example, specify 2018-07-07T00:00:00Z to see a list of command executions from before July 7, 2018.\nStatus : Specify a valid command status to see a list of all command executions with that status. Status values you can specify include:\nPending\nInProgress\nSuccess\nCancelled\nFailed\nTimedOut\nCancelling\n\n\nDocumentName : Specify name of the SSM document for which you want to see command execution results. For example, specify AWS-RunPatchBaseline to see command executions that used this SSM document to perform security patching operations on instances.\nExecutionStage : Specify one of the following values:\nExecuting : Returns a list of command executions that are currently still running.\nComplete : Returns a list of command executions that have already completed.\n\n\n\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'Commands': [ { 'CommandId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'Comment': 'string', 'ExpiresAfter': datetime(2015, 1, 1), 'Parameters': { 'string': [ 'string', ] }, 'InstanceIds': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'RequestedDateTime': datetime(2015, 1, 1), 'Status': 'Pending'|'InProgress'|'Success'|'Cancelled'|'Failed'|'TimedOut'|'Cancelling', 'StatusDetails': 'string', 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'TargetCount': 123, 'CompletedCount': 123, 'ErrorCount': 123, 'DeliveryTimedOutCount': 123, 'ServiceRole': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'TimeoutSeconds': 123 }, ], 'NextToken': 'string' } Response Structure (dict) -- Commands (list) -- (Optional) The list of commands requested by the user. (dict) -- Describes a command request. CommandId (string) -- A unique identifier for this command. DocumentName (string) -- The name of the document requested for execution. DocumentVersion (string) -- The SSM document version. Comment (string) -- User-specified information about the command, such as a brief description of what the command should do. ExpiresAfter (datetime) -- If this time is reached and the command has not already started running, it will not run. Calculated based on the ExpiresAfter user input provided as part of the SendCommand API. Parameters (dict) -- The parameter values to be inserted in the document when running the command. (string) -- (list) -- (string) -- InstanceIds (list) -- The instance IDs against which this command was requested. (string) -- Targets (list) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Targets is required if you don\'t provide one or more instance IDs in the call. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- RequestedDateTime (datetime) -- The date and time the command was requested. Status (string) -- The status of the command. StatusDetails (string) -- A detailed status of the command execution. StatusDetails includes more information than Status because it includes states resulting from error and concurrency control parameters. StatusDetails can show different results than Status. For more information about these statuses, see Understanding command statuses in the AWS Systems Manager User Guide . StatusDetails can be one of the following values: Pending: The command has not been sent to any instances. In Progress: The command has been sent to at least one instance but has not reached a final state on all instances. Success: The command successfully ran on all invocations. This is a terminal state. Delivery Timed Out: The value of MaxErrors or more command invocations shows a status of Delivery Timed Out. This is a terminal state. Execution Timed Out: The value of MaxErrors or more command invocations shows a status of Execution Timed Out. This is a terminal state. Failed: The value of MaxErrors or more command invocations shows a status of Failed. This is a terminal state. Incomplete: The command was attempted on all instances and one or more invocations does not have a value of Success but not enough invocations failed for the status to be Failed. This is a terminal state. Canceled: The command was terminated before it was completed. This is a terminal state. Rate Exceeded: The number of instances targeted by the command exceeded the account limit for pending invocations. The system has canceled the command before running it on any instance. This is a terminal state. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) -- The S3 bucket where the responses to the command executions should be stored. This was requested when issuing the command. OutputS3KeyPrefix (string) -- The S3 directory path inside the bucket where the responses to the command executions should be stored. This was requested when issuing the command. MaxConcurrency (string) -- The maximum number of instances that are allowed to run the command at the same time. You can specify a number of instances, such as 10, or a percentage of instances, such as 10%. The default value is 50. For more information about how to use MaxConcurrency, see Running commands using Systems Manager Run Command in the AWS Systems Manager User Guide . MaxErrors (string) -- The maximum number of errors allowed before the system stops sending the command to additional targets. You can specify a number of errors, such as 10, or a percentage or errors, such as 10%. The default value is 0. For more information about how to use MaxErrors, see Running commands using Systems Manager Run Command in the AWS Systems Manager User Guide . TargetCount (integer) -- The number of targets for the command. CompletedCount (integer) -- The number of targets for which the command invocation reached a terminal state. Terminal states include the following: Success, Failed, Execution Timed Out, Delivery Timed Out, Canceled, Terminated, or Undeliverable. ErrorCount (integer) -- The number of targets for which the status is Failed or Execution Timed Out. DeliveryTimedOutCount (integer) -- The number of targets for which the status is Delivery Timed Out. ServiceRole (string) -- The IAM service role that Run Command uses to act on your behalf when sending notifications about command status changes. NotificationConfig (dict) -- Configurations for sending notifications about command status changes. NotificationArn (string) -- An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic. NotificationEvents (list) -- The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide . (string) -- NotificationType (string) -- Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes. CloudWatchOutputConfig (dict) -- CloudWatch Logs information where you want Systems Manager to send the command output. CloudWatchLogGroupName (string) -- The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName . CloudWatchOutputEnabled (boolean) -- Enables Systems Manager to send command output to CloudWatch Logs. TimeoutSeconds (integer) -- The TimeoutSeconds value specified for a command. NextToken (string) -- (Optional) The token for the next set of items to return. (You received this token from a previous call.) Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidCommandId SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidFilterKey SSM.Client.exceptions.InvalidNextToken :return: { 'Commands': [ { 'CommandId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'Comment': 'string', 'ExpiresAfter': datetime(2015, 1, 1), 'Parameters': { 'string': [ 'string', ] }, 'InstanceIds': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'RequestedDateTime': datetime(2015, 1, 1), 'Status': 'Pending'|'InProgress'|'Success'|'Cancelled'|'Failed'|'TimedOut'|'Cancelling', 'StatusDetails': 'string', 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'TargetCount': 123, 'CompletedCount': 123, 'ErrorCount': 123, 'DeliveryTimedOutCount': 123, 'ServiceRole': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'TimeoutSeconds': 123 }, ], 'NextToken': 'string' } :returns: (string) -- (list) -- (string) -- """ pass def list_compliance_items(Filters=None, ResourceIds=None, ResourceTypes=None, NextToken=None, MaxResults=None): """ For a specified resource ID, this API action returns a list of compliance statuses for different resource types. Currently, you can only specify one resource ID per call. List results depend on the criteria specified in the filter. See also: AWS API Documentation Exceptions :example: response = client.list_compliance_items( Filters=[ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'EQUAL'|'NOT_EQUAL'|'BEGIN_WITH'|'LESS_THAN'|'GREATER_THAN' }, ], ResourceIds=[ 'string', ], ResourceTypes=[ 'string', ], NextToken='string', MaxResults=123 ) :type Filters: list :param Filters: One or more compliance filters. Use a filter to return a more specific list of results.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nKey (string) --The name of the filter.\n\nValues (list) --The value for which to search.\n\n(string) --\n\n\nType (string) --The type of comparison that should be performed for the value: Equal, NotEqual, BeginWith, LessThan, or GreaterThan.\n\n\n\n\n :type ResourceIds: list :param ResourceIds: The ID for the resources from which to get compliance information. Currently, you can only specify one resource ID.\n\n(string) --\n\n :type ResourceTypes: list :param ResourceTypes: The type of resource from which to get compliance information. Currently, the only supported resource type is ManagedInstance .\n\n(string) --\n\n :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'ComplianceItems': [ { 'ComplianceType': 'string', 'ResourceType': 'string', 'ResourceId': 'string', 'Id': 'string', 'Title': 'string', 'Status': 'COMPLIANT'|'NON_COMPLIANT', 'Severity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ExecutionSummary': { 'ExecutionTime': datetime(2015, 1, 1), 'ExecutionId': 'string', 'ExecutionType': 'string' }, 'Details': { 'string': 'string' } }, ], 'NextToken': 'string' } Response Structure (dict) -- ComplianceItems (list) -- A list of compliance information for the specified resource ID. (dict) -- Information about the compliance as defined by the resource type. For example, for a patch resource type, Items includes information about the PatchSeverity, Classification, and so on. ComplianceType (string) -- The compliance type. For example, Association (for a State Manager association), Patch, or Custom:string are all valid compliance types. ResourceType (string) -- The type of resource. ManagedInstance is currently the only supported resource type. ResourceId (string) -- An ID for the resource. For a managed instance, this is the instance ID. Id (string) -- An ID for the compliance item. For example, if the compliance item is a Windows patch, the ID could be the number of the KB article; for example: KB4010320. Title (string) -- A title for the compliance item. For example, if the compliance item is a Windows patch, the title could be the title of the KB article for the patch; for example: Security Update for Active Directory Federation Services. Status (string) -- The status of the compliance item. An item is either COMPLIANT or NON_COMPLIANT. Severity (string) -- The severity of the compliance status. Severity can be one of the following: Critical, High, Medium, Low, Informational, Unspecified. ExecutionSummary (dict) -- A summary for the compliance item. The summary includes an execution ID, the execution type (for example, command), and the execution time. ExecutionTime (datetime) -- The time the execution ran as a datetime object that is saved in the following format: yyyy-MM-dd\'T\'HH:mm:ss\'Z\'. ExecutionId (string) -- An ID created by the system when PutComplianceItems was called. For example, CommandID is a valid execution ID. You can use this ID in subsequent calls. ExecutionType (string) -- The type of execution. For example, Command is a valid execution type. Details (dict) -- A "Key": "Value" tag combination for the compliance item. (string) -- (string) -- NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InvalidResourceType SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken :return: { 'ComplianceItems': [ { 'ComplianceType': 'string', 'ResourceType': 'string', 'ResourceId': 'string', 'Id': 'string', 'Title': 'string', 'Status': 'COMPLIANT'|'NON_COMPLIANT', 'Severity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ExecutionSummary': { 'ExecutionTime': datetime(2015, 1, 1), 'ExecutionId': 'string', 'ExecutionType': 'string' }, 'Details': { 'string': 'string' } }, ], 'NextToken': 'string' } :returns: (string) -- (string) -- """ pass def list_compliance_summaries(Filters=None, NextToken=None, MaxResults=None): """ Returns a summary count of compliant and non-compliant resources for a compliance type. For example, this call can return State Manager associations, patches, or custom compliance types according to the filter criteria that you specify. See also: AWS API Documentation Exceptions :example: response = client.list_compliance_summaries( Filters=[ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'EQUAL'|'NOT_EQUAL'|'BEGIN_WITH'|'LESS_THAN'|'GREATER_THAN' }, ], NextToken='string', MaxResults=123 ) :type Filters: list :param Filters: One or more compliance or inventory filters. Use a filter to return a more specific list of results.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nKey (string) --The name of the filter.\n\nValues (list) --The value for which to search.\n\n(string) --\n\n\nType (string) --The type of comparison that should be performed for the value: Equal, NotEqual, BeginWith, LessThan, or GreaterThan.\n\n\n\n\n :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. Currently, you can specify null or 50. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'ComplianceSummaryItems': [ { 'ComplianceType': 'string', 'CompliantSummary': { 'CompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } }, 'NonCompliantSummary': { 'NonCompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } } }, ], 'NextToken': 'string' } Response Structure (dict) -- ComplianceSummaryItems (list) -- A list of compliant and non-compliant summary counts based on compliance types. For example, this call returns State Manager associations, patches, or custom compliance types according to the filter criteria that you specified. (dict) -- A summary of compliance information by compliance type. ComplianceType (string) -- The type of compliance item. For example, the compliance type can be Association, Patch, or Custom:string. CompliantSummary (dict) -- A list of COMPLIANT items for the specified compliance type. CompliantCount (integer) -- The total number of resources that are compliant. SeveritySummary (dict) -- A summary of the compliance severity by compliance type. CriticalCount (integer) -- The total number of resources or compliance items that have a severity level of critical. Critical severity is determined by the organization that published the compliance items. HighCount (integer) -- The total number of resources or compliance items that have a severity level of high. High severity is determined by the organization that published the compliance items. MediumCount (integer) -- The total number of resources or compliance items that have a severity level of medium. Medium severity is determined by the organization that published the compliance items. LowCount (integer) -- The total number of resources or compliance items that have a severity level of low. Low severity is determined by the organization that published the compliance items. InformationalCount (integer) -- The total number of resources or compliance items that have a severity level of informational. Informational severity is determined by the organization that published the compliance items. UnspecifiedCount (integer) -- The total number of resources or compliance items that have a severity level of unspecified. Unspecified severity is determined by the organization that published the compliance items. NonCompliantSummary (dict) -- A list of NON_COMPLIANT items for the specified compliance type. NonCompliantCount (integer) -- The total number of compliance items that are not compliant. SeveritySummary (dict) -- A summary of the non-compliance severity by compliance type CriticalCount (integer) -- The total number of resources or compliance items that have a severity level of critical. Critical severity is determined by the organization that published the compliance items. HighCount (integer) -- The total number of resources or compliance items that have a severity level of high. High severity is determined by the organization that published the compliance items. MediumCount (integer) -- The total number of resources or compliance items that have a severity level of medium. Medium severity is determined by the organization that published the compliance items. LowCount (integer) -- The total number of resources or compliance items that have a severity level of low. Low severity is determined by the organization that published the compliance items. InformationalCount (integer) -- The total number of resources or compliance items that have a severity level of informational. Informational severity is determined by the organization that published the compliance items. UnspecifiedCount (integer) -- The total number of resources or compliance items that have a severity level of unspecified. Unspecified severity is determined by the organization that published the compliance items. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InternalServerError :return: { 'ComplianceSummaryItems': [ { 'ComplianceType': 'string', 'CompliantSummary': { 'CompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } }, 'NonCompliantSummary': { 'NonCompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } } }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InternalServerError """ pass def list_document_versions(Name=None, MaxResults=None, NextToken=None): """ List all versions for a document. See also: AWS API Documentation Exceptions :example: response = client.list_document_versions( Name='string', MaxResults=123, NextToken='string' ) :type Name: string :param Name: [REQUIRED]\nThe name of the document. You can specify an Amazon Resource Name (ARN).\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'DocumentVersions': [ { 'Name': 'string', 'DocumentVersion': 'string', 'VersionName': 'string', 'CreatedDate': datetime(2015, 1, 1), 'IsDefaultVersion': True|False, 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- DocumentVersions (list) -- The document versions. (dict) -- Version information about the document. Name (string) -- The document name. DocumentVersion (string) -- The document version. VersionName (string) -- The version of the artifact associated with the document. For example, "Release 12, Update 6". This value is unique across all versions of a document, and cannot be changed. CreatedDate (datetime) -- The date the document was created. IsDefaultVersion (boolean) -- An identifier for the default version of the document. DocumentFormat (string) -- The document format, either JSON or YAML. Status (string) -- The status of the Systems Manager document, such as Creating , Active , Failed , and Deleting . StatusInformation (string) -- A message returned by AWS Systems Manager that explains the Status value. For example, a Failed status might be explained by the StatusInformation message, "The specified S3 bucket does not exist. Verify that the URL of the S3 bucket is correct." NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidDocument :return: { 'DocumentVersions': [ { 'Name': 'string', 'DocumentVersion': 'string', 'VersionName': 'string', 'CreatedDate': datetime(2015, 1, 1), 'IsDefaultVersion': True|False, 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string' }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidDocument """ pass def list_documents(DocumentFilterList=None, Filters=None, MaxResults=None, NextToken=None): """ Returns all Systems Manager (SSM) documents in the current AWS account and Region. You can limit the results of this request by using a filter. See also: AWS API Documentation Exceptions :example: response = client.list_documents( DocumentFilterList=[ { 'key': 'Name'|'Owner'|'PlatformTypes'|'DocumentType', 'value': 'string' }, ], Filters=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], MaxResults=123, NextToken='string' ) :type DocumentFilterList: list :param DocumentFilterList: This data type is deprecated. Instead, use Filters .\n\n(dict) --This data type is deprecated. Instead, use DocumentKeyValuesFilter .\n\nkey (string) -- [REQUIRED]The name of the filter.\n\nvalue (string) -- [REQUIRED]The value of the filter.\n\n\n\n\n :type Filters: list :param Filters: One or more DocumentKeyValuesFilter objects. Use a filter to return a more specific list of results. For keys, you can specify one or more key-value pair tags that have been applied to a document. Other valid keys include Owner , Name , PlatformTypes , DocumentType , and TargetType . For example, to return documents you own use Key=Owner,Values=Self . To specify a custom key-value pair, use the format Key=tag:tagName,Values=valueName .\n\n(dict) --One or more filters. Use a filter to return a more specific list of documents.\nFor keys, you can specify one or more tags that have been applied to a document.\nOther valid values include Owner , Name , PlatformTypes , DocumentType , and TargetType .\nNote that only one Owner can be specified in a request. For example: Key=Owner,Values=Self .\nIf you use Name as a key, you can use a name prefix to return a list of documents. For example, in the AWS CLI, to return a list of all documents that begin with Te , run the following command:\n\naws ssm list-documents --filters Key=Name,Values=Te\nIf you specify more than two keys, only documents that are identified by all the tags are returned in the results. If you specify more than two values for a key, documents that are identified by any of the values are returned in the results.\nTo specify a custom key and value pair, use the format Key=tag:tagName,Values=valueName .\nFor example, if you created a Key called region and are using the AWS CLI to call the list-documents command:\n\naws ssm list-documents --filters Key=tag:region,Values=east,west Key=Owner,Values=Self\n\nKey (string) --The name of the filter key.\n\nValues (list) --The value for the filter key.\n\n(string) --\n\n\n\n\n\n :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :rtype: dict ReturnsResponse Syntax { 'DocumentIdentifiers': [ { 'Name': 'string', 'Owner': 'string', 'VersionName': 'string', 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentVersion': 'string', 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] }, ], 'NextToken': 'string' } Response Structure (dict) -- DocumentIdentifiers (list) -- The names of the Systems Manager documents. (dict) -- Describes the name of a Systems Manager document. Name (string) -- The name of the Systems Manager document. Owner (string) -- The AWS user account that created the document. VersionName (string) -- An optional field specifying the version of the artifact associated with the document. For example, "Release 12, Update 6". This value is unique across all versions of a document, and cannot be changed. PlatformTypes (list) -- The operating system platform. (string) -- DocumentVersion (string) -- The document version. DocumentType (string) -- The document type. SchemaVersion (string) -- The schema version. DocumentFormat (string) -- The document format, either JSON or YAML. TargetType (string) -- The target type which defines the kinds of resources the document can run on. For example, /AWS::EC2::Instance. For a list of valid resource types, see AWS resource and property types reference in the AWS CloudFormation User Guide . Tags (list) -- The tags, or metadata, that have been applied to the document. (dict) -- Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines. Key (string) -- The name of the tag. Value (string) -- The value of the tag. Requires (list) -- A list of SSM documents required by a document. For example, an ApplicationConfiguration document requires an ApplicationConfigurationSchema document. (dict) -- An SSM document required by the current document. Name (string) -- The name of the required SSM document. The name can be an Amazon Resource Name (ARN). Version (string) -- The document version required by the current document. NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InvalidFilterKey :return: { 'DocumentIdentifiers': [ { 'Name': 'string', 'Owner': 'string', 'VersionName': 'string', 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentVersion': 'string', 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] }, ], 'NextToken': 'string' } :returns: (string) -- """ pass def list_inventory_entries(InstanceId=None, TypeName=None, Filters=None, NextToken=None, MaxResults=None): """ A list of inventory items returned by the request. See also: AWS API Documentation Exceptions :example: response = client.list_inventory_entries( InstanceId='string', TypeName='string', Filters=[ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'Equal'|'NotEqual'|'BeginWith'|'LessThan'|'GreaterThan'|'Exists' }, ], NextToken='string', MaxResults=123 ) :type InstanceId: string :param InstanceId: [REQUIRED]\nThe instance ID for which you want inventory information.\n :type TypeName: string :param TypeName: [REQUIRED]\nThe type of inventory item for which you want information.\n :type Filters: list :param Filters: One or more filters. Use a filter to return a more specific list of results.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nKey (string) -- [REQUIRED]The name of the filter key.\n\nValues (list) -- [REQUIRED]Inventory filter values. Example: inventory filter where instance IDs are specified as values Key=AWS:InstanceInformation.InstanceId,Values= i-a12b3c4d5e6g, i-1a2b3c4d5e6,Type=Equal\n\n(string) --\n\n\nType (string) --The type of filter.\n\nNote\nThe Exists filter must be used with aggregators. For more information, see Aggregating inventory data in the AWS Systems Manager User Guide .\n\n\n\n\n\n :type NextToken: string :param NextToken: The token for the next set of items to return. (You received this token from a previous call.) :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'TypeName': 'string', 'InstanceId': 'string', 'SchemaVersion': 'string', 'CaptureTime': 'string', 'Entries': [ { 'string': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- TypeName (string) -- The type of inventory item returned by the request. InstanceId (string) -- The instance ID targeted by the request to query inventory information. SchemaVersion (string) -- The inventory schema version used by the instance(s). CaptureTime (string) -- The time that inventory information was collected for the instance(s). Entries (list) -- A list of inventory items on the instance(s). (dict) -- (string) -- (string) -- NextToken (string) -- The token to use when requesting the next set of items. If there are no additional items to return, the string is empty. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken :return: { 'TypeName': 'string', 'InstanceId': 'string', 'SchemaVersion': 'string', 'CaptureTime': 'string', 'Entries': [ { 'string': 'string' }, ], 'NextToken': 'string' } :returns: (dict) -- (string) -- (string) -- """ pass def list_resource_compliance_summaries(Filters=None, NextToken=None, MaxResults=None): """ Returns a resource-level summary count. The summary includes information about compliant and non-compliant statuses and detailed compliance-item severity counts, according to the filter criteria you specify. See also: AWS API Documentation Exceptions :example: response = client.list_resource_compliance_summaries( Filters=[ { 'Key': 'string', 'Values': [ 'string', ], 'Type': 'EQUAL'|'NOT_EQUAL'|'BEGIN_WITH'|'LESS_THAN'|'GREATER_THAN' }, ], NextToken='string', MaxResults=123 ) :type Filters: list :param Filters: One or more filters. Use a filter to return a more specific list of results.\n\n(dict) --One or more filters. Use a filter to return a more specific list of results.\n\nKey (string) --The name of the filter.\n\nValues (list) --The value for which to search.\n\n(string) --\n\n\nType (string) --The type of comparison that should be performed for the value: Equal, NotEqual, BeginWith, LessThan, or GreaterThan.\n\n\n\n\n :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'ResourceComplianceSummaryItems': [ { 'ComplianceType': 'string', 'ResourceType': 'string', 'ResourceId': 'string', 'Status': 'COMPLIANT'|'NON_COMPLIANT', 'OverallSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ExecutionSummary': { 'ExecutionTime': datetime(2015, 1, 1), 'ExecutionId': 'string', 'ExecutionType': 'string' }, 'CompliantSummary': { 'CompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } }, 'NonCompliantSummary': { 'NonCompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } } }, ], 'NextToken': 'string' } Response Structure (dict) -- ResourceComplianceSummaryItems (list) -- A summary count for specified or targeted managed instances. Summary count includes information about compliant and non-compliant State Manager associations, patch status, or custom items according to the filter criteria that you specify. (dict) -- Compliance summary information for a specific resource. ComplianceType (string) -- The compliance type. ResourceType (string) -- The resource type. ResourceId (string) -- The resource ID. Status (string) -- The compliance status for the resource. OverallSeverity (string) -- The highest severity item found for the resource. The resource is compliant for this item. ExecutionSummary (dict) -- Information about the execution. ExecutionTime (datetime) -- The time the execution ran as a datetime object that is saved in the following format: yyyy-MM-dd\'T\'HH:mm:ss\'Z\'. ExecutionId (string) -- An ID created by the system when PutComplianceItems was called. For example, CommandID is a valid execution ID. You can use this ID in subsequent calls. ExecutionType (string) -- The type of execution. For example, Command is a valid execution type. CompliantSummary (dict) -- A list of items that are compliant for the resource. CompliantCount (integer) -- The total number of resources that are compliant. SeveritySummary (dict) -- A summary of the compliance severity by compliance type. CriticalCount (integer) -- The total number of resources or compliance items that have a severity level of critical. Critical severity is determined by the organization that published the compliance items. HighCount (integer) -- The total number of resources or compliance items that have a severity level of high. High severity is determined by the organization that published the compliance items. MediumCount (integer) -- The total number of resources or compliance items that have a severity level of medium. Medium severity is determined by the organization that published the compliance items. LowCount (integer) -- The total number of resources or compliance items that have a severity level of low. Low severity is determined by the organization that published the compliance items. InformationalCount (integer) -- The total number of resources or compliance items that have a severity level of informational. Informational severity is determined by the organization that published the compliance items. UnspecifiedCount (integer) -- The total number of resources or compliance items that have a severity level of unspecified. Unspecified severity is determined by the organization that published the compliance items. NonCompliantSummary (dict) -- A list of items that aren\'t compliant for the resource. NonCompliantCount (integer) -- The total number of compliance items that are not compliant. SeveritySummary (dict) -- A summary of the non-compliance severity by compliance type CriticalCount (integer) -- The total number of resources or compliance items that have a severity level of critical. Critical severity is determined by the organization that published the compliance items. HighCount (integer) -- The total number of resources or compliance items that have a severity level of high. High severity is determined by the organization that published the compliance items. MediumCount (integer) -- The total number of resources or compliance items that have a severity level of medium. Medium severity is determined by the organization that published the compliance items. LowCount (integer) -- The total number of resources or compliance items that have a severity level of low. Low severity is determined by the organization that published the compliance items. InformationalCount (integer) -- The total number of resources or compliance items that have a severity level of informational. Informational severity is determined by the organization that published the compliance items. UnspecifiedCount (integer) -- The total number of resources or compliance items that have a severity level of unspecified. Unspecified severity is determined by the organization that published the compliance items. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InternalServerError :return: { 'ResourceComplianceSummaryItems': [ { 'ComplianceType': 'string', 'ResourceType': 'string', 'ResourceId': 'string', 'Status': 'COMPLIANT'|'NON_COMPLIANT', 'OverallSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ExecutionSummary': { 'ExecutionTime': datetime(2015, 1, 1), 'ExecutionId': 'string', 'ExecutionType': 'string' }, 'CompliantSummary': { 'CompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } }, 'NonCompliantSummary': { 'NonCompliantCount': 123, 'SeveritySummary': { 'CriticalCount': 123, 'HighCount': 123, 'MediumCount': 123, 'LowCount': 123, 'InformationalCount': 123, 'UnspecifiedCount': 123 } } }, ], 'NextToken': 'string' } :returns: SSM.Client.exceptions.InvalidFilter SSM.Client.exceptions.InvalidNextToken SSM.Client.exceptions.InternalServerError """ pass def list_resource_data_sync(SyncType=None, NextToken=None, MaxResults=None): """ Lists your resource data sync configurations. Includes information about the last time a sync attempted to start, the last sync status, and the last time a sync successfully completed. The number of sync configurations might be too large to return using a single call to ListResourceDataSync . You can limit the number of sync configurations returned by using the MaxResults parameter. To determine whether there are more sync configurations to list, check the value of NextToken in the output. If there are more sync configurations to list, you can request them by specifying the NextToken returned in the call to the parameter of a subsequent call. See also: AWS API Documentation Exceptions :example: response = client.list_resource_data_sync( SyncType='string', NextToken='string', MaxResults=123 ) :type SyncType: string :param SyncType: View a list of resource data syncs according to the sync type. Specify SyncToDestination to view resource data syncs that synchronize data to an Amazon S3 buckets. Specify SyncFromSource to view resource data syncs from AWS Organizations or from multiple AWS Regions. :type NextToken: string :param NextToken: A token to start the list. Use this token to get the next set of results. :type MaxResults: integer :param MaxResults: The maximum number of items to return for this call. The call also returns a token that you can specify in a subsequent call to get the next set of results. :rtype: dict ReturnsResponse Syntax { 'ResourceDataSyncItems': [ { 'SyncName': 'string', 'SyncType': 'string', 'SyncSource': { 'SourceType': 'string', 'AwsOrganizationsSource': { 'OrganizationSourceType': 'string', 'OrganizationalUnits': [ { 'OrganizationalUnitId': 'string' }, ] }, 'SourceRegions': [ 'string', ], 'IncludeFutureRegions': True|False, 'State': 'string' }, 'S3Destination': { 'BucketName': 'string', 'Prefix': 'string', 'SyncFormat': 'JsonSerDe', 'Region': 'string', 'AWSKMSKeyARN': 'string', 'DestinationDataSharing': { 'DestinationDataSharingType': 'string' } }, 'LastSyncTime': datetime(2015, 1, 1), 'LastSuccessfulSyncTime': datetime(2015, 1, 1), 'SyncLastModifiedTime': datetime(2015, 1, 1), 'LastStatus': 'Successful'|'Failed'|'InProgress', 'SyncCreatedTime': datetime(2015, 1, 1), 'LastSyncStatusMessage': 'string' }, ], 'NextToken': 'string' } Response Structure (dict) -- ResourceDataSyncItems (list) -- A list of your current Resource Data Sync configurations and their statuses. (dict) -- Information about a Resource Data Sync configuration, including its current status and last successful sync. SyncName (string) -- The name of the Resource Data Sync. SyncType (string) -- The type of resource data sync. If SyncType is SyncToDestination , then the resource data sync synchronizes data to an S3 bucket. If the SyncType is SyncFromSource then the resource data sync synchronizes data from AWS Organizations or from multiple AWS Regions. SyncSource (dict) -- Information about the source where the data was synchronized. SourceType (string) -- The type of data source for the resource data sync. SourceType is either AwsOrganizations (if an organization is present in AWS Organizations) or singleAccountMultiRegions . AwsOrganizationsSource (dict) -- The field name in SyncSource for the ResourceDataSyncAwsOrganizationsSource type. OrganizationSourceType (string) -- If an AWS Organization is present, this is either OrganizationalUnits or EntireOrganization . For OrganizationalUnits , the data is aggregated from a set of organization units. For EntireOrganization , the data is aggregated from the entire AWS Organization. OrganizationalUnits (list) -- The AWS Organizations organization units included in the sync. (dict) -- The AWS Organizations organizational unit data source for the sync. OrganizationalUnitId (string) -- The AWS Organization unit ID data source for the sync. SourceRegions (list) -- The SyncSource AWS Regions included in the resource data sync. (string) -- IncludeFutureRegions (boolean) -- Whether to automatically synchronize and aggregate data from new AWS Regions when those Regions come online. State (string) -- The data type name for including resource data sync state. There are four sync states: OrganizationNotExists : Your organization doesn\'t exist. NoPermissions : The system can\'t locate the service-linked role. This role is automatically created when a user creates a resource data sync in Explorer. InvalidOrganizationalUnit : You specified or selected an invalid unit in the resource data sync configuration. TrustedAccessDisabled : You disabled Systems Manager access in the organization in AWS Organizations. S3Destination (dict) -- Configuration information for the target S3 bucket. BucketName (string) -- The name of the S3 bucket where the aggregated data is stored. Prefix (string) -- An Amazon S3 prefix for the bucket. SyncFormat (string) -- A supported sync format. The following format is currently supported: JsonSerDe Region (string) -- The AWS Region with the S3 bucket targeted by the Resource Data Sync. AWSKMSKeyARN (string) -- The ARN of an encryption key for a destination in Amazon S3. Must belong to the same Region as the destination S3 bucket. DestinationDataSharing (dict) -- Enables destination data sharing. By default, this field is null . DestinationDataSharingType (string) -- The sharing data type. Only Organization is supported. LastSyncTime (datetime) -- The last time the configuration attempted to sync (UTC). LastSuccessfulSyncTime (datetime) -- The last time the sync operations returned a status of SUCCESSFUL (UTC). SyncLastModifiedTime (datetime) -- The date and time the resource data sync was changed. LastStatus (string) -- The status reported by the last sync. SyncCreatedTime (datetime) -- The date and time the configuration was created (UTC). LastSyncStatusMessage (string) -- The status message details reported by the last sync. NextToken (string) -- The token for the next set of items to return. Use this token to get the next set of results. Exceptions SSM.Client.exceptions.ResourceDataSyncInvalidConfigurationException SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidNextToken :return: { 'ResourceDataSyncItems': [ { 'SyncName': 'string', 'SyncType': 'string', 'SyncSource': { 'SourceType': 'string', 'AwsOrganizationsSource': { 'OrganizationSourceType': 'string', 'OrganizationalUnits': [ { 'OrganizationalUnitId': 'string' }, ] }, 'SourceRegions': [ 'string', ], 'IncludeFutureRegions': True|False, 'State': 'string' }, 'S3Destination': { 'BucketName': 'string', 'Prefix': 'string', 'SyncFormat': 'JsonSerDe', 'Region': 'string', 'AWSKMSKeyARN': 'string', 'DestinationDataSharing': { 'DestinationDataSharingType': 'string' } }, 'LastSyncTime': datetime(2015, 1, 1), 'LastSuccessfulSyncTime': datetime(2015, 1, 1), 'SyncLastModifiedTime': datetime(2015, 1, 1), 'LastStatus': 'Successful'|'Failed'|'InProgress', 'SyncCreatedTime': datetime(2015, 1, 1), 'LastSyncStatusMessage': 'string' }, ], 'NextToken': 'string' } :returns: (string) -- """ pass def list_tags_for_resource(ResourceType=None, ResourceId=None): """ Returns a list of the tags assigned to the specified resource. See also: AWS API Documentation Exceptions :example: response = client.list_tags_for_resource( ResourceType='Document'|'ManagedInstance'|'MaintenanceWindow'|'Parameter'|'PatchBaseline'|'OpsItem', ResourceId='string' ) :type ResourceType: string :param ResourceType: [REQUIRED]\nReturns a list of tags for a specific resource type.\n :type ResourceId: string :param ResourceId: [REQUIRED]\nThe resource ID for which you want to see a list of tags.\n :rtype: dict ReturnsResponse Syntax { 'TagList': [ { 'Key': 'string', 'Value': 'string' }, ] } Response Structure (dict) -- TagList (list) -- A list of tags. (dict) -- Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines. Key (string) -- The name of the tag. Value (string) -- The value of the tag. Exceptions SSM.Client.exceptions.InvalidResourceType SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError :return: { 'TagList': [ { 'Key': 'string', 'Value': 'string' }, ] } :returns: SSM.Client.exceptions.InvalidResourceType SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError """ pass def modify_document_permission(Name=None, PermissionType=None, AccountIdsToAdd=None, AccountIdsToRemove=None, SharedDocumentVersion=None): """ Shares a Systems Manager document publicly or privately. If you share a document privately, you must specify the AWS user account IDs for those people who can use the document. If you share a document publicly, you must specify All as the account ID. See also: AWS API Documentation Exceptions :example: response = client.modify_document_permission( Name='string', PermissionType='Share', AccountIdsToAdd=[ 'string', ], AccountIdsToRemove=[ 'string', ], SharedDocumentVersion='string' ) :type Name: string :param Name: [REQUIRED]\nThe name of the document that you want to share.\n :type PermissionType: string :param PermissionType: [REQUIRED]\nThe permission type for the document. The permission type can be Share .\n :type AccountIdsToAdd: list :param AccountIdsToAdd: The AWS user accounts that should have access to the document. The account IDs can either be a group of account IDs or All .\n\n(string) --\n\n :type AccountIdsToRemove: list :param AccountIdsToRemove: The AWS user accounts that should no longer have access to the document. The AWS user account can either be a group of account IDs or All . This action has a higher priority than AccountIdsToAdd . If you specify an account ID to add and the same ID to remove, the system removes access to the document.\n\n(string) --\n\n :type SharedDocumentVersion: string :param SharedDocumentVersion: (Optional) The version of the document to share. If it\'s not specified, the system choose the Default version to share. :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidPermissionType SSM.Client.exceptions.DocumentPermissionLimit SSM.Client.exceptions.DocumentLimitExceeded :return: {} :returns: (dict) -- """ pass def put_compliance_items(ResourceId=None, ResourceType=None, ComplianceType=None, ExecutionSummary=None, Items=None, ItemContentHash=None, UploadType=None): """ Registers a compliance type and other compliance details on a designated resource. This action lets you register custom compliance details with a resource. This call overwrites existing compliance information on the resource, so you must provide a full list of compliance items each time that you send the request. ComplianceType can be one of the following: See also: AWS API Documentation Exceptions :example: response = client.put_compliance_items( ResourceId='string', ResourceType='string', ComplianceType='string', ExecutionSummary={ 'ExecutionTime': datetime(2015, 1, 1), 'ExecutionId': 'string', 'ExecutionType': 'string' }, Items=[ { 'Id': 'string', 'Title': 'string', 'Severity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'Status': 'COMPLIANT'|'NON_COMPLIANT', 'Details': { 'string': 'string' } }, ], ItemContentHash='string', UploadType='COMPLETE'|'PARTIAL' ) :type ResourceId: string :param ResourceId: [REQUIRED]\nSpecify an ID for this resource. For a managed instance, this is the instance ID.\n :type ResourceType: string :param ResourceType: [REQUIRED]\nSpecify the type of resource. ManagedInstance is currently the only supported resource type.\n :type ComplianceType: string :param ComplianceType: [REQUIRED]\nSpecify the compliance type. For example, specify Association (for a State Manager association), Patch, or Custom:string .\n :type ExecutionSummary: dict :param ExecutionSummary: [REQUIRED]\nA summary of the call execution that includes an execution ID, the type of execution (for example, Command ), and the date/time of the execution using a datetime object that is saved in the following format: yyyy-MM-dd\'T\'HH:mm:ss\'Z\'.\n\nExecutionTime (datetime) -- [REQUIRED]The time the execution ran as a datetime object that is saved in the following format: yyyy-MM-dd\'T\'HH:mm:ss\'Z\'.\n\nExecutionId (string) --An ID created by the system when PutComplianceItems was called. For example, CommandID is a valid execution ID. You can use this ID in subsequent calls.\n\nExecutionType (string) --The type of execution. For example, Command is a valid execution type.\n\n\n :type Items: list :param Items: [REQUIRED]\nInformation about the compliance as defined by the resource type. For example, for a patch compliance type, Items includes information about the PatchSeverity, Classification, and so on.\n\n(dict) --Information about a compliance item.\n\nId (string) --The compliance item ID. For example, if the compliance item is a Windows patch, the ID could be the number of the KB article.\n\nTitle (string) --The title of the compliance item. For example, if the compliance item is a Windows patch, the title could be the title of the KB article for the patch; for example: Security Update for Active Directory Federation Services.\n\nSeverity (string) -- [REQUIRED]The severity of the compliance status. Severity can be one of the following: Critical, High, Medium, Low, Informational, Unspecified.\n\nStatus (string) -- [REQUIRED]The status of the compliance item. An item is either COMPLIANT or NON_COMPLIANT.\n\nDetails (dict) --A 'Key': 'Value' tag combination for the compliance item.\n\n(string) --\n(string) --\n\n\n\n\n\n\n\n :type ItemContentHash: string :param ItemContentHash: MD5 or SHA-256 content hash. The content hash is used to determine if existing information should be overwritten or ignored. If the content hashes match, the request to put compliance information is ignored. :type UploadType: string :param UploadType: The mode for uploading compliance items. You can specify COMPLETE or PARTIAL . In COMPLETE mode, the system overwrites all existing compliance information for the resource. You must provide a full list of compliance items each time you send the request.\nIn PARTIAL mode, the system overwrites compliance information for a specific association. The association must be configured with SyncCompliance set to MANUAL . By default, all requests use COMPLETE mode.\n\nNote\nThis attribute is only valid for association compliance.\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidItemContentException SSM.Client.exceptions.TotalSizeLimitExceededException SSM.Client.exceptions.ItemSizeLimitExceededException SSM.Client.exceptions.ComplianceTypeCountLimitExceededException SSM.Client.exceptions.InvalidResourceType SSM.Client.exceptions.InvalidResourceId :return: {} :returns: ResourceId (string) -- [REQUIRED] Specify an ID for this resource. For a managed instance, this is the instance ID. ResourceType (string) -- [REQUIRED] Specify the type of resource. ManagedInstance is currently the only supported resource type. ComplianceType (string) -- [REQUIRED] Specify the compliance type. For example, specify Association (for a State Manager association), Patch, or Custom:string . ExecutionSummary (dict) -- [REQUIRED] A summary of the call execution that includes an execution ID, the type of execution (for example, Command ), and the date/time of the execution using a datetime object that is saved in the following format: yyyy-MM-dd\'T\'HH:mm:ss\'Z\'. ExecutionTime (datetime) -- [REQUIRED]The time the execution ran as a datetime object that is saved in the following format: yyyy-MM-dd\'T\'HH:mm:ss\'Z\'. ExecutionId (string) --An ID created by the system when PutComplianceItems was called. For example, CommandID is a valid execution ID. You can use this ID in subsequent calls. ExecutionType (string) --The type of execution. For example, Command is a valid execution type. Items (list) -- [REQUIRED] Information about the compliance as defined by the resource type. For example, for a patch compliance type, Items includes information about the PatchSeverity, Classification, and so on. (dict) --Information about a compliance item. Id (string) --The compliance item ID. For example, if the compliance item is a Windows patch, the ID could be the number of the KB article. Title (string) --The title of the compliance item. For example, if the compliance item is a Windows patch, the title could be the title of the KB article for the patch; for example: Security Update for Active Directory Federation Services. Severity (string) -- [REQUIRED]The severity of the compliance status. Severity can be one of the following: Critical, High, Medium, Low, Informational, Unspecified. Status (string) -- [REQUIRED]The status of the compliance item. An item is either COMPLIANT or NON_COMPLIANT. Details (dict) --A "Key": "Value" tag combination for the compliance item. (string) -- (string) -- ItemContentHash (string) -- MD5 or SHA-256 content hash. The content hash is used to determine if existing information should be overwritten or ignored. If the content hashes match, the request to put compliance information is ignored. UploadType (string) -- The mode for uploading compliance items. You can specify COMPLETE or PARTIAL . In COMPLETE mode, the system overwrites all existing compliance information for the resource. You must provide a full list of compliance items each time you send the request. In PARTIAL mode, the system overwrites compliance information for a specific association. The association must be configured with SyncCompliance set to MANUAL . By default, all requests use COMPLETE mode. Note This attribute is only valid for association compliance. """ pass def put_inventory(InstanceId=None, Items=None): """ Bulk update custom inventory items on one more instance. The request adds an inventory item, if it doesn\'t already exist, or updates an inventory item, if it does exist. See also: AWS API Documentation Exceptions :example: response = client.put_inventory( InstanceId='string', Items=[ { 'TypeName': 'string', 'SchemaVersion': 'string', 'CaptureTime': 'string', 'ContentHash': 'string', 'Content': [ { 'string': 'string' }, ], 'Context': { 'string': 'string' } }, ] ) :type InstanceId: string :param InstanceId: [REQUIRED]\nAn instance ID where you want to add or update inventory items.\n :type Items: list :param Items: [REQUIRED]\nThe inventory items that you want to add or update on instances.\n\n(dict) --Information collected from managed instances based on your inventory policy document\n\nTypeName (string) -- [REQUIRED]The name of the inventory type. Default inventory item type names start with AWS. Custom inventory type names will start with Custom. Default inventory item types include the following: AWS:AWSComponent, AWS:Application, AWS:InstanceInformation, AWS:Network, and AWS:WindowsUpdate.\n\nSchemaVersion (string) -- [REQUIRED]The schema version for the inventory item.\n\nCaptureTime (string) -- [REQUIRED]The time the inventory information was collected.\n\nContentHash (string) --MD5 hash of the inventory item type contents. The content hash is used to determine whether to update inventory information. The PutInventory API does not update the inventory item type contents if the MD5 hash has not changed since last update.\n\nContent (list) --The inventory data of the inventory type.\n\n(dict) --\n(string) --\n(string) --\n\n\n\n\n\n\nContext (dict) --A map of associated properties for a specified inventory type. For example, with this attribute, you can specify the ExecutionId , ExecutionType , ComplianceType properties of the AWS:ComplianceItem type.\n\n(string) --\n(string) --\n\n\n\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'Message': 'string' } Response Structure (dict) -- Message (string) -- Information about the request. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidItemContentException SSM.Client.exceptions.TotalSizeLimitExceededException SSM.Client.exceptions.ItemSizeLimitExceededException SSM.Client.exceptions.ItemContentMismatchException SSM.Client.exceptions.CustomSchemaCountLimitExceededException SSM.Client.exceptions.UnsupportedInventorySchemaVersionException SSM.Client.exceptions.UnsupportedInventoryItemContextException SSM.Client.exceptions.InvalidInventoryItemContextException SSM.Client.exceptions.SubTypeCountLimitExceededException :return: { 'Message': 'string' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidTypeNameException SSM.Client.exceptions.InvalidItemContentException SSM.Client.exceptions.TotalSizeLimitExceededException SSM.Client.exceptions.ItemSizeLimitExceededException SSM.Client.exceptions.ItemContentMismatchException SSM.Client.exceptions.CustomSchemaCountLimitExceededException SSM.Client.exceptions.UnsupportedInventorySchemaVersionException SSM.Client.exceptions.UnsupportedInventoryItemContextException SSM.Client.exceptions.InvalidInventoryItemContextException SSM.Client.exceptions.SubTypeCountLimitExceededException """ pass def put_parameter(Name=None, Description=None, Value=None, Type=None, KeyId=None, Overwrite=None, AllowedPattern=None, Tags=None, Tier=None, Policies=None, DataType=None): """ Add a parameter to the system. See also: AWS API Documentation Exceptions :example: response = client.put_parameter( Name='string', Description='string', Value='string', Type='String'|'StringList'|'SecureString', KeyId='string', Overwrite=True|False, AllowedPattern='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ], Tier='Standard'|'Advanced'|'Intelligent-Tiering', Policies='string', DataType='string' ) :type Name: string :param Name: [REQUIRED]\nThe fully qualified name of the parameter that you want to add to the system. The fully qualified name includes the complete hierarchy of the parameter path and name. For parameters in a hierarchy, you must include a leading forward slash character (/) when you create or reference a parameter. For example: /Dev/DBServer/MySQL/db-string13\nNaming Constraints:\n\nParameter names are case sensitive.\nA parameter name must be unique within an AWS Region\nA parameter name can\'t be prefixed with 'aws' or 'ssm' (case-insensitive).\nParameter names can include only the following symbols and letters: a-zA-Z0-9_.-/\nA parameter name can\'t include spaces.\nParameter hierarchies are limited to a maximum depth of fifteen levels.\n\nFor additional information about valid values for parameter names, see About requirements and constraints for parameter names in the AWS Systems Manager User Guide .\n\nNote\nThe maximum length constraint listed below includes capacity for additional system attributes that are not part of the name. The maximum length for a parameter name, including the full length of the parameter ARN, is 1011 characters. For example, the length of the following parameter name is 65 characters, not 20 characters:\n\narn:aws:ssm:us-east-2:111122223333:parameter/ExampleParameterName\n\n :type Description: string :param Description: Information about the parameter that you want to add to the system. Optional but recommended.\n\nWarning\nDo not enter personally identifiable information in this field.\n\n :type Value: string :param Value: [REQUIRED]\nThe parameter value that you want to add to the system. Standard parameters have a value limit of 4 KB. Advanced parameters have a value limit of 8 KB.\n :type Type: string :param Type: The type of parameter that you want to add to the system.\nItems in a StringList must be separated by a comma (,). You can\'t use other punctuation or special character to escape items in the list. If you have a parameter value that requires a comma, then use the String data type.\n\nNote\nSecureString is not currently supported for AWS CloudFormation templates or in the China Regions.\n\n :type KeyId: string :param KeyId: The KMS Key ID that you want to use to encrypt a parameter. Either the default AWS Key Management Service (AWS KMS) key automatically assigned to your AWS account or a custom key. Required for parameters that use the SecureString data type.\nIf you don\'t specify a key ID, the system uses the default key associated with your AWS account.\n\nTo use your default AWS KMS key, choose the SecureString data type, and do not specify the Key ID when you create the parameter. The system automatically populates Key ID with your default KMS key.\nTo use a custom KMS key, choose the SecureString data type with the Key ID parameter.\n\n :type Overwrite: boolean :param Overwrite: Overwrite an existing parameter. If not specified, will default to 'false'. :type AllowedPattern: string :param AllowedPattern: A regular expression used to validate the parameter value. For example, for String types with values restricted to numbers, you can specify the following: AllowedPattern=^d+$ :type Tags: list :param Tags: Optional metadata that you assign to a resource. Tags enable you to categorize a resource in different ways, such as by purpose, owner, or environment. For example, you might want to tag a Systems Manager parameter to identify the type of resource to which it applies, the environment, or the type of configuration data referenced by the parameter. In this case, you could specify the following key name/value pairs:\n\nKey=Resource,Value=S3bucket\nKey=OS,Value=Windows\nKey=ParameterType,Value=LicenseKey\n\n\nNote\nTo add tags to an existing Systems Manager parameter, use the AddTagsToResource action.\n\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :type Tier: string :param Tier: The parameter tier to assign to a parameter.\nParameter Store offers a standard tier and an advanced tier for parameters. Standard parameters have a content size limit of 4 KB and can\'t be configured to use parameter policies. You can create a maximum of 10,000 standard parameters for each Region in an AWS account. Standard parameters are offered at no additional cost.\nAdvanced parameters have a content size limit of 8 KB and can be configured to use parameter policies. You can create a maximum of 100,000 advanced parameters for each Region in an AWS account. Advanced parameters incur a charge. For more information, see Standard and advanced parameter tiers in the AWS Systems Manager User Guide .\nYou can change a standard parameter to an advanced parameter any time. But you can\'t revert an advanced parameter to a standard parameter. Reverting an advanced parameter to a standard parameter would result in data loss because the system would truncate the size of the parameter from 8 KB to 4 KB. Reverting would also remove any policies attached to the parameter. Lastly, advanced parameters use a different form of encryption than standard parameters.\nIf you no longer need an advanced parameter, or if you no longer want to incur charges for an advanced parameter, you must delete it and recreate it as a new standard parameter.\n\nUsing the Default Tier Configuration\nIn PutParameter requests, you can specify the tier to create the parameter in. Whenever you specify a tier in the request, Parameter Store creates or updates the parameter according to that request. However, if you do not specify a tier in a request, Parameter Store assigns the tier based on the current Parameter Store default tier configuration.\nThe default tier when you begin using Parameter Store is the standard-parameter tier. If you use the advanced-parameter tier, you can specify one of the following as the default:\n\nAdvanced : With this option, Parameter Store evaluates all requests as advanced parameters.\nIntelligent-Tiering : With this option, Parameter Store evaluates each request to determine if the parameter is standard or advanced. If the request doesn\'t include any options that require an advanced parameter, the parameter is created in the standard-parameter tier. If one or more options requiring an advanced parameter are included in the request, Parameter Store create a parameter in the advanced-parameter tier. This approach helps control your parameter-related costs by always creating standard parameters unless an advanced parameter is necessary.\n\nOptions that require an advanced parameter include the following:\n\nThe content size of the parameter is more than 4 KB.\nThe parameter uses a parameter policy.\nMore than 10,000 parameters already exist in your AWS account in the current Region.\n\nFor more information about configuring the default tier option, see Specifying a default parameter tier in the AWS Systems Manager User Guide .\n :type Policies: string :param Policies: One or more policies to apply to a parameter. This action takes a JSON array. Parameter Store supports the following policy types:\nExpiration: This policy deletes the parameter after it expires. When you create the policy, you specify the expiration date. You can update the expiration date and time by updating the policy. Updating the parameter does not affect the expiration date and time. When the expiration time is reached, Parameter Store deletes the parameter.\nExpirationNotification: This policy triggers an event in Amazon CloudWatch Events that notifies you about the expiration. By using this policy, you can receive notification before or after the expiration time is reached, in units of days or hours.\nNoChangeNotification: This policy triggers a CloudWatch event if a parameter has not been modified for a specified period of time. This policy type is useful when, for example, a secret needs to be changed within a period of time, but it has not been changed.\nAll existing policies are preserved until you send new policies or an empty policy. For more information about parameter policies, see Assigning parameter policies .\n :type DataType: string :param DataType: The data type for a String parameter. Supported data types include plain text and Amazon Machine Image IDs.\n\nThe following data type values are supported.\n\ntext\naws:ec2:image\n\nWhen you create a String parameter and specify aws:ec2:image , Systems Manager validates the parameter value is in the required format, such as ami-12345abcdeEXAMPLE , and that the specified AMI is available in your AWS account. For more information, see Native parameter support for Amazon Machine Image IDs in the AWS Systems Manager User Guide .\n :rtype: dict ReturnsResponse Syntax { 'Version': 123, 'Tier': 'Standard'|'Advanced'|'Intelligent-Tiering' } Response Structure (dict) -- Version (integer) -- The new version number of a parameter. If you edit a parameter value, Parameter Store automatically creates a new version and assigns this new version a unique ID. You can reference a parameter version ID in API actions or in Systems Manager documents (SSM documents). By default, if you don\'t specify a specific version, the system returns the latest parameter value when a parameter is called. Tier (string) -- The tier assigned to the parameter. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidKeyId SSM.Client.exceptions.ParameterLimitExceeded SSM.Client.exceptions.TooManyUpdates SSM.Client.exceptions.ParameterAlreadyExists SSM.Client.exceptions.HierarchyLevelLimitExceededException SSM.Client.exceptions.HierarchyTypeMismatchException SSM.Client.exceptions.InvalidAllowedPatternException SSM.Client.exceptions.ParameterMaxVersionLimitExceeded SSM.Client.exceptions.ParameterPatternMismatchException SSM.Client.exceptions.UnsupportedParameterType SSM.Client.exceptions.PoliciesLimitExceededException SSM.Client.exceptions.InvalidPolicyTypeException SSM.Client.exceptions.InvalidPolicyAttributeException SSM.Client.exceptions.IncompatiblePolicyException :return: { 'Version': 123, 'Tier': 'Standard'|'Advanced'|'Intelligent-Tiering' } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidKeyId SSM.Client.exceptions.ParameterLimitExceeded SSM.Client.exceptions.TooManyUpdates SSM.Client.exceptions.ParameterAlreadyExists SSM.Client.exceptions.HierarchyLevelLimitExceededException SSM.Client.exceptions.HierarchyTypeMismatchException SSM.Client.exceptions.InvalidAllowedPatternException SSM.Client.exceptions.ParameterMaxVersionLimitExceeded SSM.Client.exceptions.ParameterPatternMismatchException SSM.Client.exceptions.UnsupportedParameterType SSM.Client.exceptions.PoliciesLimitExceededException SSM.Client.exceptions.InvalidPolicyTypeException SSM.Client.exceptions.InvalidPolicyAttributeException SSM.Client.exceptions.IncompatiblePolicyException """ pass def register_default_patch_baseline(BaselineId=None): """ Defines the default patch baseline for the relevant operating system. To reset the AWS predefined patch baseline as the default, specify the full patch baseline ARN as the baseline ID value. For example, for CentOS, specify arn:aws:ssm:us-east-2:733109147000:patchbaseline/pb-0574b43a65ea646ed instead of pb-0574b43a65ea646ed . See also: AWS API Documentation Exceptions :example: response = client.register_default_patch_baseline( BaselineId='string' ) :type BaselineId: string :param BaselineId: [REQUIRED]\nThe ID of the patch baseline that should be the default patch baseline.\n :rtype: dict ReturnsResponse Syntax{ 'BaselineId': 'string' } Response Structure (dict) -- BaselineId (string) --The ID of the default patch baseline. Exceptions SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string' } """ pass def register_patch_baseline_for_patch_group(BaselineId=None, PatchGroup=None): """ Registers a patch baseline for a patch group. See also: AWS API Documentation Exceptions :example: response = client.register_patch_baseline_for_patch_group( BaselineId='string', PatchGroup='string' ) :type BaselineId: string :param BaselineId: [REQUIRED]\nThe ID of the patch baseline to register the patch group with.\n :type PatchGroup: string :param PatchGroup: [REQUIRED]\nThe name of the patch group that should be registered with the patch baseline.\n :rtype: dict ReturnsResponse Syntax { 'BaselineId': 'string', 'PatchGroup': 'string' } Response Structure (dict) -- BaselineId (string) -- The ID of the patch baseline the patch group was registered with. PatchGroup (string) -- The name of the patch group registered with the patch baseline. Exceptions SSM.Client.exceptions.AlreadyExistsException SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string', 'PatchGroup': 'string' } :returns: SSM.Client.exceptions.AlreadyExistsException SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError """ pass def register_target_with_maintenance_window(WindowId=None, ResourceType=None, Targets=None, OwnerInformation=None, Name=None, Description=None, ClientToken=None): """ Registers a target with a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.register_target_with_maintenance_window( WindowId='string', ResourceType='INSTANCE'|'RESOURCE_GROUP', Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], OwnerInformation='string', Name='string', Description='string', ClientToken='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window the target should be registered with.\n :type ResourceType: string :param ResourceType: [REQUIRED]\nThe type of target being registered with the maintenance window.\n :type Targets: list :param Targets: [REQUIRED]\nThe targets to register with the maintenance window. In other words, the instances to run commands on when the maintenance window runs.\nYou can specify targets using instance IDs, resource group names, or tags that have been applied to instances.\n\nExample 1 : Specify instance IDs``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\nExample 2 : Use tag key-pairs applied to instances\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\nExample 3 : Use tag-keys applied to instances\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\nExample 4 : Use resource group names\n``Key=resource-groups:Name,Values=*resource-group-name* ``\nExample 5 : Use filters for resource group types\n``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\n\nNote\nFor Key=resource-groups:ResourceTypeFilters , specify resource types in the following format\n\n``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* ``\n\nFor more information about these examples formats, including the best use case for each one, see Examples: Register targets with a maintenance window in the AWS Systems Manager User Guide .\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type OwnerInformation: string :param OwnerInformation: User-provided value that will be included in any CloudWatch events raised while running tasks for these targets in this maintenance window. :type Name: string :param Name: An optional name for the target. :type Description: string :param Description: An optional description for the target. :type ClientToken: string :param ClientToken: User-provided idempotency token.\nThis field is autopopulated if not provided.\n :rtype: dict ReturnsResponse Syntax { 'WindowTargetId': 'string' } Response Structure (dict) -- WindowTargetId (string) -- The ID of the target definition in this maintenance window. Exceptions SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError :return: { 'WindowTargetId': 'string' } :returns: SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.InternalServerError """ pass def register_task_with_maintenance_window(WindowId=None, Targets=None, TaskArn=None, ServiceRoleArn=None, TaskType=None, TaskParameters=None, TaskInvocationParameters=None, Priority=None, MaxConcurrency=None, MaxErrors=None, LoggingInfo=None, Name=None, Description=None, ClientToken=None): """ Adds a new task to a maintenance window. See also: AWS API Documentation Exceptions :example: response = client.register_task_with_maintenance_window( WindowId='string', Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], TaskArn='string', ServiceRoleArn='string', TaskType='RUN_COMMAND'|'AUTOMATION'|'STEP_FUNCTIONS'|'LAMBDA', TaskParameters={ 'string': { 'Values': [ 'string', ] } }, TaskInvocationParameters={ 'RunCommand': { 'Comment': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'DocumentHash': 'string', 'DocumentHashType': 'Sha256'|'Sha1', 'DocumentVersion': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'Parameters': { 'string': [ 'string', ] }, 'ServiceRoleArn': 'string', 'TimeoutSeconds': 123 }, 'Automation': { 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] } }, 'StepFunctions': { 'Input': 'string', 'Name': 'string' }, 'Lambda': { 'ClientContext': 'string', 'Qualifier': 'string', 'Payload': b'bytes' } }, Priority=123, MaxConcurrency='string', MaxErrors='string', LoggingInfo={ 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, Name='string', Description='string', ClientToken='string' ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window the task should be added to.\n :type Targets: list :param Targets: [REQUIRED]\nThe targets (either instances or maintenance window targets).\nSpecify instances using the following format:\n\nKey=InstanceIds,Values=<instance-id-1>,<instance-id-2>\nSpecify maintenance window targets using the following format:\n\nKey=WindowTargetIds;,Values=<window-target-id-1>,<window-target-id-2>\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type TaskArn: string :param TaskArn: [REQUIRED]\nThe ARN of the task to run.\n :type ServiceRoleArn: string :param ServiceRoleArn: The ARN of the IAM service role for Systems Manager to assume when running a maintenance window task. If you do not specify a service role ARN, Systems Manager uses your account\'s service-linked role. If no service-linked role for Systems Manager exists in your account, it is created when you run RegisterTaskWithMaintenanceWindow .\nFor more information, see the following topics in the in the AWS Systems Manager User Guide :\n\nUsing service-linked roles for Systems Manager\nShould I use a service-linked role or a custom service role to run maintenance window tasks?\n\n :type TaskType: string :param TaskType: [REQUIRED]\nThe type of task being registered.\n :type TaskParameters: dict :param TaskParameters: The parameters that should be passed to the task when it is run.\n\nNote\nTaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .\n\n\n(string) --\n(dict) --Defines the values for a task parameter.\n\nValues (list) --This field contains an array of 0 or more strings, each 1 to 255 characters in length.\n\n(string) --\n\n\n\n\n\n\n\n :type TaskInvocationParameters: dict :param TaskInvocationParameters: The parameters that the task should use during execution. Populate only the fields that match the task type. All other fields should be empty.\n\nRunCommand (dict) --The parameters for a RUN_COMMAND task type.\n\nComment (string) --Information about the commands to run.\n\nCloudWatchOutputConfig (dict) --Configuration options for sending command output to CloudWatch Logs.\n\nCloudWatchLogGroupName (string) --The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName .\n\nCloudWatchOutputEnabled (boolean) --Enables Systems Manager to send command output to CloudWatch Logs.\n\n\n\nDocumentHash (string) --The SHA-256 or SHA-1 hash created by the system when the document was created. SHA-1 hashes have been deprecated.\n\nDocumentHashType (string) --SHA-256 or SHA-1. SHA-1 hashes have been deprecated.\n\nDocumentVersion (string) --The SSM document version to use in the request. You can specify $DEFAULT, $LATEST, or a specific version number. If you run commands by using the AWS CLI, then you must escape the first two options by using a backslash. If you specify a version number, then you don\'t need to use the backslash. For example:\n--document-version '$DEFAULT'\n--document-version '$LATEST'\n--document-version '3'\n\nNotificationConfig (dict) --Configurations for sending notifications about command status changes on a per-instance basis.\n\nNotificationArn (string) --An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic.\n\nNotificationEvents (list) --The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide .\n\n(string) --\n\n\nNotificationType (string) --Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes.\n\n\n\nOutputS3BucketName (string) --The name of the S3 bucket.\n\nOutputS3KeyPrefix (string) --The S3 bucket subfolder.\n\nParameters (dict) --The parameters for the RUN_COMMAND task execution.\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n\nServiceRoleArn (string) --The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks.\n\nTimeoutSeconds (integer) --If this time is reached and the command has not already started running, it doesn\'t run.\n\n\n\nAutomation (dict) --The parameters for an AUTOMATION task type.\n\nDocumentVersion (string) --The version of an Automation document to use during task execution.\n\nParameters (dict) --The parameters for the AUTOMATION task.\nFor information about specifying and updating task parameters, see RegisterTaskWithMaintenanceWindow and UpdateMaintenanceWindowTask .\n\nNote\n\nLoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .\n\nFor AUTOMATION task types, Systems Manager ignores any values specified for these parameters.\n\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n\n\n\nStepFunctions (dict) --The parameters for a STEP_FUNCTIONS task type.\n\nInput (string) --The inputs for the STEP_FUNCTIONS task.\n\nName (string) --The name of the STEP_FUNCTIONS task.\n\n\n\nLambda (dict) --The parameters for a LAMBDA task type.\n\nClientContext (string) --Pass client-specific information to the Lambda function that you are invoking. You can then process the client information in your Lambda function as you choose through the context variable.\n\nQualifier (string) --(Optional) Specify a Lambda function version or alias name. If you specify a function version, the action uses the qualified function ARN to invoke a specific Lambda function. If you specify an alias name, the action uses the alias ARN to invoke the Lambda function version to which the alias points.\n\nPayload (bytes) --JSON to provide to your Lambda function as input.\n\n\n\n\n :type Priority: integer :param Priority: The priority of the task in the maintenance window, the lower the number the higher the priority. Tasks in a maintenance window are scheduled in priority order with tasks that have the same priority scheduled in parallel. :type MaxConcurrency: string :param MaxConcurrency: [REQUIRED]\nThe maximum number of targets this task can be run for in parallel.\n :type MaxErrors: string :param MaxErrors: [REQUIRED]\nThe maximum number of errors allowed before this task stops being scheduled.\n :type LoggingInfo: dict :param LoggingInfo: A structure containing information about an S3 bucket to write instance-level logs to.\n\nNote\nLoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .\n\n\nS3BucketName (string) -- [REQUIRED]The name of an S3 bucket where execution logs are stored .\n\nS3KeyPrefix (string) --(Optional) The S3 bucket subfolder.\n\nS3Region (string) -- [REQUIRED]The Region where the S3 bucket is located.\n\n\n :type Name: string :param Name: An optional name for the task. :type Description: string :param Description: An optional description for the task. :type ClientToken: string :param ClientToken: User-provided idempotency token.\nThis field is autopopulated if not provided.\n :rtype: dict ReturnsResponse Syntax { 'WindowTaskId': 'string' } Response Structure (dict) -- WindowTaskId (string) -- The ID of the task in the maintenance window. Exceptions SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.FeatureNotAvailableException SSM.Client.exceptions.InternalServerError :return: { 'WindowTaskId': 'string' } :returns: SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.ResourceLimitExceededException SSM.Client.exceptions.FeatureNotAvailableException SSM.Client.exceptions.InternalServerError """ pass def remove_tags_from_resource(ResourceType=None, ResourceId=None, TagKeys=None): """ Removes tag keys from the specified resource. See also: AWS API Documentation Exceptions :example: response = client.remove_tags_from_resource( ResourceType='Document'|'ManagedInstance'|'MaintenanceWindow'|'Parameter'|'PatchBaseline'|'OpsItem', ResourceId='string', TagKeys=[ 'string', ] ) :type ResourceType: string :param ResourceType: [REQUIRED]\nThe type of resource from which you want to remove a tag.\n\nNote\nThe ManagedInstance type for this API action is only for on-premises managed instances. Specify the name of the managed instance in the following format: mi-ID_number. For example, mi-1a2b3c4d5e6f.\n\n :type ResourceId: string :param ResourceId: [REQUIRED]\nThe ID of the resource from which you want to remove tags. For example:\nManagedInstance: mi-012345abcde\nMaintenanceWindow: mw-012345abcde\nPatchBaseline: pb-012345abcde\nFor the Document and Parameter values, use the name of the resource.\n\nNote\nThe ManagedInstance type for this API action is only for on-premises managed instances. Specify the name of the managed instance in the following format: mi-ID_number. For example, mi-1a2b3c4d5e6f.\n\n :type TagKeys: list :param TagKeys: [REQUIRED]\nTag keys that you want to remove from the specified resource.\n\n(string) --\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InvalidResourceType SSM.Client.exceptions.InvalidResourceId SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.TooManyUpdates :return: {} :returns: (dict) -- """ pass def reset_service_setting(SettingId=None): """ Services map a SettingId object to a setting value. AWS services teams define the default value for a SettingId . You can\'t create a new SettingId , but you can overwrite the default value if you have the ssm:UpdateServiceSetting permission for the setting. Use the GetServiceSetting API action to view the current value. Use the UpdateServiceSetting API action to change the default setting. Reset the service setting for the account to the default value as provisioned by the AWS service team. See also: AWS API Documentation Exceptions :example: response = client.reset_service_setting( SettingId='string' ) :type SettingId: string :param SettingId: [REQUIRED]\nThe Amazon Resource Name (ARN) of the service setting to reset. The setting ID can be /ssm/parameter-store/default-parameter-tier , /ssm/parameter-store/high-throughput-enabled , or /ssm/managed-instance/activation-tier . For example, arn:aws:ssm:us-east-1:111122223333:servicesetting/ssm/parameter-store/high-throughput-enabled .\n :rtype: dict ReturnsResponse Syntax{ 'ServiceSetting': { 'SettingId': 'string', 'SettingValue': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'ARN': 'string', 'Status': 'string' } } Response Structure (dict) --The result body of the ResetServiceSetting API action. ServiceSetting (dict) --The current, effective service setting after calling the ResetServiceSetting API action. SettingId (string) --The ID of the service setting. SettingValue (string) --The value of the service setting. LastModifiedDate (datetime) --The last time the service setting was modified. LastModifiedUser (string) --The ARN of the last modified user. This field is populated only if the setting value was overwritten. ARN (string) --The ARN of the service setting. Status (string) --The status of the service setting. The value can be Default, Customized or PendingUpdate. Default: The current setting uses a default value provisioned by the AWS service team. Customized: The current setting use a custom value specified by the customer. PendingUpdate: The current setting uses a default or custom value, but a setting change request is pending approval. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ServiceSettingNotFound SSM.Client.exceptions.TooManyUpdates :return: { 'ServiceSetting': { 'SettingId': 'string', 'SettingValue': 'string', 'LastModifiedDate': datetime(2015, 1, 1), 'LastModifiedUser': 'string', 'ARN': 'string', 'Status': 'string' } } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ServiceSettingNotFound SSM.Client.exceptions.TooManyUpdates """ pass def resume_session(SessionId=None): """ Reconnects a session to an instance after it has been disconnected. Connections can be resumed for disconnected sessions, but not terminated sessions. See also: AWS API Documentation Exceptions :example: response = client.resume_session( SessionId='string' ) :type SessionId: string :param SessionId: [REQUIRED]\nThe ID of the disconnected session to resume.\n :rtype: dict ReturnsResponse Syntax{ 'SessionId': 'string', 'TokenValue': 'string', 'StreamUrl': 'string' } Response Structure (dict) -- SessionId (string) --The ID of the session. TokenValue (string) --An encrypted token value containing session and caller information. Used to authenticate the connection to the instance. StreamUrl (string) --A URL back to SSM Agent on the instance that the Session Manager client uses to send commands and receive output from the instance. Format: wss://ssmmessages.**region** .amazonaws.com/v1/data-channel/**session-id** ?stream=(input|output) . region represents the Region identifier for an AWS Region supported by AWS Systems Manager, such as us-east-2 for the US East (Ohio) Region. For a list of supported region values, see the Region column in Systems Manager service endpoints in the AWS General Reference .session-id represents the ID of a Session Manager session, such as 1a2b3c4dEXAMPLE . Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'SessionId': 'string', 'TokenValue': 'string', 'StreamUrl': 'string' } """ pass def send_automation_signal(AutomationExecutionId=None, SignalType=None, Payload=None): """ Sends a signal to an Automation execution to change the current behavior or status of the execution. See also: AWS API Documentation Exceptions :example: response = client.send_automation_signal( AutomationExecutionId='string', SignalType='Approve'|'Reject'|'StartStep'|'StopStep'|'Resume', Payload={ 'string': [ 'string', ] } ) :type AutomationExecutionId: string :param AutomationExecutionId: [REQUIRED]\nThe unique identifier for an existing Automation execution that you want to send the signal to.\n :type SignalType: string :param SignalType: [REQUIRED]\nThe type of signal to send to an Automation execution.\n :type Payload: dict :param Payload: The data sent with the signal. The data schema depends on the type of signal used in the request.\nFor Approve and Reject signal types, the payload is an optional comment that you can send with the signal type. For example:\n\nComment='Looks good'\nFor StartStep and Resume signal types, you must send the name of the Automation step to start or resume as the payload. For example:\n\nStepName='step1'\nFor the StopStep signal type, you must send the step execution ID as the payload. For example:\n\nStepExecutionId='97fff367-fc5a-4299-aed8-0123456789ab'\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.AutomationExecutionNotFoundException SSM.Client.exceptions.AutomationStepNotFoundException SSM.Client.exceptions.InvalidAutomationSignalException SSM.Client.exceptions.InternalServerError :return: {} :returns: (dict) -- """ pass def send_command(InstanceIds=None, Targets=None, DocumentName=None, DocumentVersion=None, DocumentHash=None, DocumentHashType=None, TimeoutSeconds=None, Comment=None, Parameters=None, OutputS3Region=None, OutputS3BucketName=None, OutputS3KeyPrefix=None, MaxConcurrency=None, MaxErrors=None, ServiceRoleArn=None, NotificationConfig=None, CloudWatchOutputConfig=None): """ Runs commands on one or more managed instances. See also: AWS API Documentation Exceptions :example: response = client.send_command( InstanceIds=[ 'string', ], Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], DocumentName='string', DocumentVersion='string', DocumentHash='string', DocumentHashType='Sha256'|'Sha1', TimeoutSeconds=123, Comment='string', Parameters={ 'string': [ 'string', ] }, OutputS3Region='string', OutputS3BucketName='string', OutputS3KeyPrefix='string', MaxConcurrency='string', MaxErrors='string', ServiceRoleArn='string', NotificationConfig={ 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, CloudWatchOutputConfig={ 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False } ) :type InstanceIds: list :param InstanceIds: The instance IDs where the command should run. You can specify a maximum of 50 IDs. If you prefer not to list individual instance IDs, you can instead send commands to a fleet of instances using the Targets parameter, which accepts EC2 tags. For more information about how to use targets, see Using targets and rate controls to send commands to a fleet in the AWS Systems Manager User Guide .\n\n(string) --\n\n :type Targets: list :param Targets: (Optional) An array of search criteria that targets instances using a Key,Value combination that you specify. Targets is required if you don\'t provide one or more instance IDs in the call. For more information about how to use targets, see Sending commands to a fleet in the AWS Systems Manager User Guide .\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type DocumentName: string :param DocumentName: [REQUIRED]\nRequired. The name of the Systems Manager document to run. This can be a public document or a custom document.\n :type DocumentVersion: string :param DocumentVersion: The SSM document version to use in the request. You can specify $DEFAULT, $LATEST, or a specific version number. If you run commands by using the AWS CLI, then you must escape the first two options by using a backslash. If you specify a version number, then you don\'t need to use the backslash. For example:\n--document-version '$DEFAULT'\n--document-version '$LATEST'\n--document-version '3'\n :type DocumentHash: string :param DocumentHash: The Sha256 or Sha1 hash created by the system when the document was created.\n\nNote\nSha1 hashes have been deprecated.\n\n :type DocumentHashType: string :param DocumentHashType: Sha256 or Sha1.\n\nNote\nSha1 hashes have been deprecated.\n\n :type TimeoutSeconds: integer :param TimeoutSeconds: If this time is reached and the command has not already started running, it will not run. :type Comment: string :param Comment: User-specified information about the command, such as a brief description of what the command should do. :type Parameters: dict :param Parameters: The required and optional parameters specified in the document being run.\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n :type OutputS3Region: string :param OutputS3Region: (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. :type OutputS3BucketName: string :param OutputS3BucketName: The name of the S3 bucket where command execution responses should be stored. :type OutputS3KeyPrefix: string :param OutputS3KeyPrefix: The directory structure within the S3 bucket where the responses should be stored. :type MaxConcurrency: string :param MaxConcurrency: (Optional) The maximum number of instances that are allowed to run the command at the same time. You can specify a number such as 10 or a percentage such as 10%. The default value is 50. For more information about how to use MaxConcurrency, see Using concurrency controls in the AWS Systems Manager User Guide . :type MaxErrors: string :param MaxErrors: The maximum number of errors allowed without the command failing. When the command fails one more time beyond the value of MaxErrors, the systems stops sending the command to additional targets. You can specify a number like 10 or a percentage like 10%. The default value is 0. For more information about how to use MaxErrors, see Using error controls in the AWS Systems Manager User Guide . :type ServiceRoleArn: string :param ServiceRoleArn: The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for Run Command commands. :type NotificationConfig: dict :param NotificationConfig: Configurations for sending notifications.\n\nNotificationArn (string) --An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic.\n\nNotificationEvents (list) --The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide .\n\n(string) --\n\n\nNotificationType (string) --Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes.\n\n\n :type CloudWatchOutputConfig: dict :param CloudWatchOutputConfig: Enables Systems Manager to send Run Command output to Amazon CloudWatch Logs.\n\nCloudWatchLogGroupName (string) --The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName .\n\nCloudWatchOutputEnabled (boolean) --Enables Systems Manager to send command output to CloudWatch Logs.\n\n\n :rtype: dict ReturnsResponse Syntax { 'Command': { 'CommandId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'Comment': 'string', 'ExpiresAfter': datetime(2015, 1, 1), 'Parameters': { 'string': [ 'string', ] }, 'InstanceIds': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'RequestedDateTime': datetime(2015, 1, 1), 'Status': 'Pending'|'InProgress'|'Success'|'Cancelled'|'Failed'|'TimedOut'|'Cancelling', 'StatusDetails': 'string', 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'TargetCount': 123, 'CompletedCount': 123, 'ErrorCount': 123, 'DeliveryTimedOutCount': 123, 'ServiceRole': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'TimeoutSeconds': 123 } } Response Structure (dict) -- Command (dict) -- The request as it was received by Systems Manager. Also provides the command ID which can be used future references to this request. CommandId (string) -- A unique identifier for this command. DocumentName (string) -- The name of the document requested for execution. DocumentVersion (string) -- The SSM document version. Comment (string) -- User-specified information about the command, such as a brief description of what the command should do. ExpiresAfter (datetime) -- If this time is reached and the command has not already started running, it will not run. Calculated based on the ExpiresAfter user input provided as part of the SendCommand API. Parameters (dict) -- The parameter values to be inserted in the document when running the command. (string) -- (list) -- (string) -- InstanceIds (list) -- The instance IDs against which this command was requested. (string) -- Targets (list) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Targets is required if you don\'t provide one or more instance IDs in the call. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- RequestedDateTime (datetime) -- The date and time the command was requested. Status (string) -- The status of the command. StatusDetails (string) -- A detailed status of the command execution. StatusDetails includes more information than Status because it includes states resulting from error and concurrency control parameters. StatusDetails can show different results than Status. For more information about these statuses, see Understanding command statuses in the AWS Systems Manager User Guide . StatusDetails can be one of the following values: Pending: The command has not been sent to any instances. In Progress: The command has been sent to at least one instance but has not reached a final state on all instances. Success: The command successfully ran on all invocations. This is a terminal state. Delivery Timed Out: The value of MaxErrors or more command invocations shows a status of Delivery Timed Out. This is a terminal state. Execution Timed Out: The value of MaxErrors or more command invocations shows a status of Execution Timed Out. This is a terminal state. Failed: The value of MaxErrors or more command invocations shows a status of Failed. This is a terminal state. Incomplete: The command was attempted on all instances and one or more invocations does not have a value of Success but not enough invocations failed for the status to be Failed. This is a terminal state. Canceled: The command was terminated before it was completed. This is a terminal state. Rate Exceeded: The number of instances targeted by the command exceeded the account limit for pending invocations. The system has canceled the command before running it on any instance. This is a terminal state. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) -- The S3 bucket where the responses to the command executions should be stored. This was requested when issuing the command. OutputS3KeyPrefix (string) -- The S3 directory path inside the bucket where the responses to the command executions should be stored. This was requested when issuing the command. MaxConcurrency (string) -- The maximum number of instances that are allowed to run the command at the same time. You can specify a number of instances, such as 10, or a percentage of instances, such as 10%. The default value is 50. For more information about how to use MaxConcurrency, see Running commands using Systems Manager Run Command in the AWS Systems Manager User Guide . MaxErrors (string) -- The maximum number of errors allowed before the system stops sending the command to additional targets. You can specify a number of errors, such as 10, or a percentage or errors, such as 10%. The default value is 0. For more information about how to use MaxErrors, see Running commands using Systems Manager Run Command in the AWS Systems Manager User Guide . TargetCount (integer) -- The number of targets for the command. CompletedCount (integer) -- The number of targets for which the command invocation reached a terminal state. Terminal states include the following: Success, Failed, Execution Timed Out, Delivery Timed Out, Canceled, Terminated, or Undeliverable. ErrorCount (integer) -- The number of targets for which the status is Failed or Execution Timed Out. DeliveryTimedOutCount (integer) -- The number of targets for which the status is Delivery Timed Out. ServiceRole (string) -- The IAM service role that Run Command uses to act on your behalf when sending notifications about command status changes. NotificationConfig (dict) -- Configurations for sending notifications about command status changes. NotificationArn (string) -- An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic. NotificationEvents (list) -- The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide . (string) -- NotificationType (string) -- Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes. CloudWatchOutputConfig (dict) -- CloudWatch Logs information where you want Systems Manager to send the command output. CloudWatchLogGroupName (string) -- The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName . CloudWatchOutputEnabled (boolean) -- Enables Systems Manager to send command output to CloudWatch Logs. TimeoutSeconds (integer) -- The TimeoutSeconds value specified for a command. Exceptions SSM.Client.exceptions.DuplicateInstanceId SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion SSM.Client.exceptions.InvalidOutputFolder SSM.Client.exceptions.InvalidParameters SSM.Client.exceptions.UnsupportedPlatformType SSM.Client.exceptions.MaxDocumentSizeExceeded SSM.Client.exceptions.InvalidRole SSM.Client.exceptions.InvalidNotificationConfig :return: { 'Command': { 'CommandId': 'string', 'DocumentName': 'string', 'DocumentVersion': 'string', 'Comment': 'string', 'ExpiresAfter': datetime(2015, 1, 1), 'Parameters': { 'string': [ 'string', ] }, 'InstanceIds': [ 'string', ], 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'RequestedDateTime': datetime(2015, 1, 1), 'Status': 'Pending'|'InProgress'|'Success'|'Cancelled'|'Failed'|'TimedOut'|'Cancelling', 'StatusDetails': 'string', 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'TargetCount': 123, 'CompletedCount': 123, 'ErrorCount': 123, 'DeliveryTimedOutCount': 123, 'ServiceRole': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'TimeoutSeconds': 123 } } :returns: (string) -- (list) -- (string) -- """ pass def start_associations_once(AssociationIds=None): """ Use this API action to run an association immediately and only one time. This action can be helpful when troubleshooting associations. See also: AWS API Documentation Exceptions :example: response = client.start_associations_once( AssociationIds=[ 'string', ] ) :type AssociationIds: list :param AssociationIds: [REQUIRED]\nThe association IDs that you want to run immediately and only one time.\n\n(string) --\n\n :rtype: dict ReturnsResponse Syntax{} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InvalidAssociation SSM.Client.exceptions.AssociationDoesNotExist :return: {} :returns: (dict) -- """ pass def start_automation_execution(DocumentName=None, DocumentVersion=None, Parameters=None, ClientToken=None, Mode=None, TargetParameterName=None, Targets=None, TargetMaps=None, MaxConcurrency=None, MaxErrors=None, TargetLocations=None, Tags=None): """ Initiates execution of an Automation document. See also: AWS API Documentation Exceptions :example: response = client.start_automation_execution( DocumentName='string', DocumentVersion='string', Parameters={ 'string': [ 'string', ] }, ClientToken='string', Mode='Auto'|'Interactive', TargetParameterName='string', Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], TargetMaps=[ { 'string': [ 'string', ] }, ], MaxConcurrency='string', MaxErrors='string', TargetLocations=[ { 'Accounts': [ 'string', ], 'Regions': [ 'string', ], 'TargetLocationMaxConcurrency': 'string', 'TargetLocationMaxErrors': 'string', 'ExecutionRoleName': 'string' }, ], Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type DocumentName: string :param DocumentName: [REQUIRED]\nThe name of the Automation document to use for this execution.\n :type DocumentVersion: string :param DocumentVersion: The version of the Automation document to use for this execution. :type Parameters: dict :param Parameters: A key-value map of execution parameters, which match the declared parameters in the Automation document.\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n :type ClientToken: string :param ClientToken: User-provided idempotency token. The token must be unique, is case insensitive, enforces the UUID format, and can\'t be reused. :type Mode: string :param Mode: The execution mode of the automation. Valid modes include the following: Auto and Interactive. The default mode is Auto. :type TargetParameterName: string :param TargetParameterName: The name of the parameter used as the target resource for the rate-controlled execution. Required if you specify targets. :type Targets: list :param Targets: A key-value mapping to target resources. Required if you specify TargetParameterName.\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type TargetMaps: list :param TargetMaps: A key-value mapping of document parameters to target resources. Both Targets and TargetMaps cannot be specified together.\n\n(dict) --\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n\n\n :type MaxConcurrency: string :param MaxConcurrency: The maximum number of targets allowed to run this task in parallel. You can specify a number, such as 10, or a percentage, such as 10%. The default value is 10. :type MaxErrors: string :param MaxErrors: The number of errors that are allowed before the system stops running the automation on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops running the automation when the fourth error is received. If you specify 0, then the system stops running the automation on additional targets after the first error result is returned. If you run an automation on 50 resources and set max-errors to 10%, then the system stops running the automation on additional targets when the sixth error is received.\nExecutions that are already running an automation when max-errors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set max-concurrency to 1 so the executions proceed one at a time.\n :type TargetLocations: list :param TargetLocations: A location is a combination of AWS Regions and/or AWS accounts where you want to run the Automation. Use this action to start an Automation in multiple Regions and multiple accounts. For more information, see Running Automation workflows in multiple AWS Regions and accounts in the AWS Systems Manager User Guide .\n\n(dict) --The combination of AWS Regions and accounts targeted by the current Automation execution.\n\nAccounts (list) --The AWS accounts targeted by the current Automation execution.\n\n(string) --\n\n\nRegions (list) --The AWS Regions targeted by the current Automation execution.\n\n(string) --\n\n\nTargetLocationMaxConcurrency (string) --The maximum number of AWS accounts and AWS regions allowed to run the Automation concurrently\n\nTargetLocationMaxErrors (string) --The maximum number of errors allowed before the system stops queueing additional Automation executions for the currently running Automation.\n\nExecutionRoleName (string) --The Automation execution role used by the currently running Automation.\n\n\n\n\n :type Tags: list :param Tags: Optional metadata that you assign to a resource. You can specify a maximum of five tags for an automation. Tags enable you to categorize a resource in different ways, such as by purpose, owner, or environment. For example, you might want to tag an automation to identify an environment or operating system. In this case, you could specify the following key name/value pairs:\n\nKey=environment,Value=test\nKey=OS,Value=Windows\n\n\nNote\nTo add tags to an existing patch baseline, use the AddTagsToResource action.\n\n\n(dict) --Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines.\n\nKey (string) -- [REQUIRED]The name of the tag.\n\nValue (string) -- [REQUIRED]The value of the tag.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'AutomationExecutionId': 'string' } Response Structure (dict) -- AutomationExecutionId (string) -- The unique ID of a newly scheduled automation execution. Exceptions SSM.Client.exceptions.AutomationDefinitionNotFoundException SSM.Client.exceptions.InvalidAutomationExecutionParametersException SSM.Client.exceptions.AutomationExecutionLimitExceededException SSM.Client.exceptions.AutomationDefinitionVersionNotFoundException SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.InvalidTarget SSM.Client.exceptions.InternalServerError :return: { 'AutomationExecutionId': 'string' } :returns: SSM.Client.exceptions.AutomationDefinitionNotFoundException SSM.Client.exceptions.InvalidAutomationExecutionParametersException SSM.Client.exceptions.AutomationExecutionLimitExceededException SSM.Client.exceptions.AutomationDefinitionVersionNotFoundException SSM.Client.exceptions.IdempotentParameterMismatch SSM.Client.exceptions.InvalidTarget SSM.Client.exceptions.InternalServerError """ pass def start_session(Target=None, DocumentName=None, Parameters=None): """ Initiates a connection to a target (for example, an instance) for a Session Manager session. Returns a URL and token that can be used to open a WebSocket connection for sending input and receiving outputs. See also: AWS API Documentation Exceptions :example: response = client.start_session( Target='string', DocumentName='string', Parameters={ 'string': [ 'string', ] } ) :type Target: string :param Target: [REQUIRED]\nThe instance to connect to for the session.\n :type DocumentName: string :param DocumentName: The name of the SSM document to define the parameters and plugin settings for the session. For example, SSM-SessionManagerRunShell . If no document name is provided, a shell to the instance is launched by default. :type Parameters: dict :param Parameters: Reserved for future use.\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'SessionId': 'string', 'TokenValue': 'string', 'StreamUrl': 'string' } Response Structure (dict) -- SessionId (string) -- The ID of the session. TokenValue (string) -- An encrypted token value containing session and caller information. Used to authenticate the connection to the instance. StreamUrl (string) -- A URL back to SSM Agent on the instance that the Session Manager client uses to send commands and receive output from the instance. Format: wss://ssmmessages.**region** .amazonaws.com/v1/data-channel/**session-id** ?stream=(input|output) region represents the Region identifier for an AWS Region supported by AWS Systems Manager, such as us-east-2 for the US East (Ohio) Region. For a list of supported region values, see the Region column in Systems Manager service endpoints in the AWS General Reference . session-id represents the ID of a Session Manager session, such as 1a2b3c4dEXAMPLE . Exceptions SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.TargetNotConnected SSM.Client.exceptions.InternalServerError :return: { 'SessionId': 'string', 'TokenValue': 'string', 'StreamUrl': 'string' } :returns: SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.TargetNotConnected SSM.Client.exceptions.InternalServerError """ pass def stop_automation_execution(AutomationExecutionId=None, Type=None): """ Stop an Automation that is currently running. See also: AWS API Documentation Exceptions :example: response = client.stop_automation_execution( AutomationExecutionId='string', Type='Complete'|'Cancel' ) :type AutomationExecutionId: string :param AutomationExecutionId: [REQUIRED]\nThe execution ID of the Automation to stop.\n :type Type: string :param Type: The stop request type. Valid types include the following: Cancel and Complete. The default type is Cancel. :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.AutomationExecutionNotFoundException SSM.Client.exceptions.InvalidAutomationStatusUpdateException SSM.Client.exceptions.InternalServerError :return: {} :returns: (dict) -- """ pass def terminate_session(SessionId=None): """ Permanently ends a session and closes the data connection between the Session Manager client and SSM Agent on the instance. A terminated session cannot be resumed. See also: AWS API Documentation Exceptions :example: response = client.terminate_session( SessionId='string' ) :type SessionId: string :param SessionId: [REQUIRED]\nThe ID of the session to terminate.\n :rtype: dict ReturnsResponse Syntax{ 'SessionId': 'string' } Response Structure (dict) -- SessionId (string) --The ID of the session that has been terminated. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'SessionId': 'string' } """ pass def update_association(AssociationId=None, Parameters=None, DocumentVersion=None, ScheduleExpression=None, OutputLocation=None, Name=None, Targets=None, AssociationName=None, AssociationVersion=None, AutomationTargetParameterName=None, MaxErrors=None, MaxConcurrency=None, ComplianceSeverity=None, SyncCompliance=None): """ Updates an association. You can update the association name and version, the document version, schedule, parameters, and Amazon S3 output. In order to call this API action, your IAM user account, group, or role must be configured with permission to call the DescribeAssociation API action. If you don\'t have permission to call DescribeAssociation, then you receive the following error: An error occurred (AccessDeniedException) when calling the UpdateAssociation operation: User: <user_arn> is not authorized to perform: ssm:DescribeAssociation on resource: <resource_arn> See also: AWS API Documentation Exceptions :example: response = client.update_association( AssociationId='string', Parameters={ 'string': [ 'string', ] }, DocumentVersion='string', ScheduleExpression='string', OutputLocation={ 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, Name='string', Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], AssociationName='string', AssociationVersion='string', AutomationTargetParameterName='string', MaxErrors='string', MaxConcurrency='string', ComplianceSeverity='CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', SyncCompliance='AUTO'|'MANUAL' ) :type AssociationId: string :param AssociationId: [REQUIRED]\nThe ID of the association you want to update.\n :type Parameters: dict :param Parameters: The parameters you want to update for the association. If you create a parameter using Parameter Store, you can reference the parameter using {{ssm:parameter-name}}\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n :type DocumentVersion: string :param DocumentVersion: The document version you want update for the association. :type ScheduleExpression: string :param ScheduleExpression: The cron expression used to schedule the association that you want to update. :type OutputLocation: dict :param OutputLocation: An S3 bucket where you want to store the results of this request.\n\nS3Location (dict) --An S3 bucket where you want to store the results of this request.\n\nOutputS3Region (string) --(Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket.\n\nOutputS3BucketName (string) --The name of the S3 bucket.\n\nOutputS3KeyPrefix (string) --The S3 bucket subfolder.\n\n\n\n\n :type Name: string :param Name: The name of the SSM document that contains the configuration information for the instance. You can specify Command or Automation documents.\nYou can specify AWS-predefined documents, documents you created, or a document that is shared with you from another account.\nFor SSM documents that are shared with you from other AWS accounts, you must specify the complete SSM document ARN, in the following format:\n\n``arn:aws:ssm:region :account-id :document/document-name ``\nFor example:\n\narn:aws:ssm:us-east-2:12345678912:document/My-Shared-Document\nFor AWS-predefined documents and SSM documents you created in your account, you only need to specify the document name. For example, AWS-ApplyPatchBaseline or My-Document .\n :type Targets: list :param Targets: The targets of the association.\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type AssociationName: string :param AssociationName: The name of the association that you want to update. :type AssociationVersion: string :param AssociationVersion: This parameter is provided for concurrency control purposes. You must specify the latest association version in the service. If you want to ensure that this request succeeds, either specify $LATEST , or omit this parameter. :type AutomationTargetParameterName: string :param AutomationTargetParameterName: Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. :type MaxErrors: string :param MaxErrors: The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received.\nExecutions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time.\n :type MaxConcurrency: string :param MaxConcurrency: The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time.\nIf a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency.\n :type ComplianceSeverity: string :param ComplianceSeverity: The severity level to assign to the association. :type SyncCompliance: string :param SyncCompliance: The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT .\nIn MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action.\nBy default, all associations use AUTO mode.\n :rtype: dict ReturnsResponse Syntax { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } Response Structure (dict) -- AssociationDescription (dict) -- The description of the association that was updated. Name (string) -- The name of the Systems Manager document. InstanceId (string) -- The ID of the instance. AssociationVersion (string) -- The association version. Date (datetime) -- The date when the association was made. LastUpdateAssociationDate (datetime) -- The date when the association was last updated. Status (dict) -- The association status. Date (datetime) -- The date when the status changed. Name (string) -- The status. Message (string) -- The reason for the status. AdditionalInfo (string) -- A user-defined string. Overview (dict) -- Information about the association. Status (string) -- The status of the association. Status can be: Pending, Success, or Failed. DetailedStatus (string) -- A detailed status of the association. AssociationStatusAggregatedCount (dict) -- Returns the number of targets for the association status. For example, if you created an association with two instances, and one of them was successful, this would return the count of instances by status. (string) -- (integer) -- DocumentVersion (string) -- The document version. AutomationTargetParameterName (string) -- Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. Parameters (dict) -- A description of the parameters for a document. (string) -- (list) -- (string) -- AssociationId (string) -- The association ID. Targets (list) -- The instances targeted by the request. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- ScheduleExpression (string) -- A cron expression that specifies a schedule when the association runs. OutputLocation (dict) -- An S3 bucket where you want to store the output details of the request. S3Location (dict) -- An S3 bucket where you want to store the results of this request. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) -- The name of the S3 bucket. OutputS3KeyPrefix (string) -- The S3 bucket subfolder. LastExecutionDate (datetime) -- The date on which the association was last run. LastSuccessfulExecutionDate (datetime) -- The last date on which the association was successfully run. AssociationName (string) -- The association name. MaxErrors (string) -- The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received. Executions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time. MaxConcurrency (string) -- The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time. If a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency. ComplianceSeverity (string) -- The severity level that is assigned to the association. SyncCompliance (string) -- The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT . In MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action. By default, all associations use AUTO mode. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidSchedule SSM.Client.exceptions.InvalidParameters SSM.Client.exceptions.InvalidOutputLocation SSM.Client.exceptions.InvalidDocumentVersion SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.InvalidUpdate SSM.Client.exceptions.TooManyUpdates SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidTarget SSM.Client.exceptions.InvalidAssociationVersion SSM.Client.exceptions.AssociationVersionLimitExceeded :return: { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } :returns: (string) -- (integer) -- """ pass def update_association_status(Name=None, InstanceId=None, AssociationStatus=None): """ Updates the status of the Systems Manager document associated with the specified instance. See also: AWS API Documentation Exceptions :example: response = client.update_association_status( Name='string', InstanceId='string', AssociationStatus={ 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' } ) :type Name: string :param Name: [REQUIRED]\nThe name of the Systems Manager document.\n :type InstanceId: string :param InstanceId: [REQUIRED]\nThe ID of the instance.\n :type AssociationStatus: dict :param AssociationStatus: [REQUIRED]\nThe association status.\n\nDate (datetime) -- [REQUIRED]The date when the status changed.\n\nName (string) -- [REQUIRED]The status.\n\nMessage (string) -- [REQUIRED]The reason for the status.\n\nAdditionalInfo (string) --A user-defined string.\n\n\n :rtype: dict ReturnsResponse Syntax { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } Response Structure (dict) -- AssociationDescription (dict) -- Information about the association. Name (string) -- The name of the Systems Manager document. InstanceId (string) -- The ID of the instance. AssociationVersion (string) -- The association version. Date (datetime) -- The date when the association was made. LastUpdateAssociationDate (datetime) -- The date when the association was last updated. Status (dict) -- The association status. Date (datetime) -- The date when the status changed. Name (string) -- The status. Message (string) -- The reason for the status. AdditionalInfo (string) -- A user-defined string. Overview (dict) -- Information about the association. Status (string) -- The status of the association. Status can be: Pending, Success, or Failed. DetailedStatus (string) -- A detailed status of the association. AssociationStatusAggregatedCount (dict) -- Returns the number of targets for the association status. For example, if you created an association with two instances, and one of them was successful, this would return the count of instances by status. (string) -- (integer) -- DocumentVersion (string) -- The document version. AutomationTargetParameterName (string) -- Specify the target for the association. This target is required for associations that use an Automation document and target resources by using rate controls. Parameters (dict) -- A description of the parameters for a document. (string) -- (list) -- (string) -- AssociationId (string) -- The association ID. Targets (list) -- The instances targeted by the request. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- ScheduleExpression (string) -- A cron expression that specifies a schedule when the association runs. OutputLocation (dict) -- An S3 bucket where you want to store the output details of the request. S3Location (dict) -- An S3 bucket where you want to store the results of this request. OutputS3Region (string) -- (Deprecated) You can no longer specify this parameter. The system ignores it. Instead, Systems Manager automatically determines the Region of the S3 bucket. OutputS3BucketName (string) -- The name of the S3 bucket. OutputS3KeyPrefix (string) -- The S3 bucket subfolder. LastExecutionDate (datetime) -- The date on which the association was last run. LastSuccessfulExecutionDate (datetime) -- The last date on which the association was successfully run. AssociationName (string) -- The association name. MaxErrors (string) -- The number of errors that are allowed before the system stops sending requests to run the association on additional targets. You can specify either an absolute number of errors, for example 10, or a percentage of the target set, for example 10%. If you specify 3, for example, the system stops sending requests when the fourth error is received. If you specify 0, then the system stops sending requests after the first error is returned. If you run an association on 50 instances and set MaxError to 10%, then the system stops sending the request when the sixth error is received. Executions that are already running an association when MaxErrors is reached are allowed to complete, but some of these executions may fail as well. If you need to ensure that there won\'t be more than max-errors failed executions, set MaxConcurrency to 1 so that executions proceed one at a time. MaxConcurrency (string) -- The maximum number of targets allowed to run the association at the same time. You can specify a number, for example 10, or a percentage of the target set, for example 10%. The default value is 100%, which means all targets run the association at the same time. If a new instance starts and attempts to run an association while Systems Manager is running MaxConcurrency associations, the association is allowed to run. During the next association interval, the new instance will process its association within the limit specified for MaxConcurrency. ComplianceSeverity (string) -- The severity level that is assigned to the association. SyncCompliance (string) -- The mode for generating association compliance. You can specify AUTO or MANUAL . In AUTO mode, the system uses the status of the association execution to determine the compliance status. If the association execution runs successfully, then the association is COMPLIANT . If the association execution doesn\'t run successfully, the association is NON-COMPLIANT . In MANUAL mode, you must specify the AssociationId as a parameter for the PutComplianceItems API action. In this case, compliance data is not managed by State Manager. It is managed by your direct call to the PutComplianceItems API action. By default, all associations use AUTO mode. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.AssociationDoesNotExist SSM.Client.exceptions.StatusUnchanged SSM.Client.exceptions.TooManyUpdates :return: { 'AssociationDescription': { 'Name': 'string', 'InstanceId': 'string', 'AssociationVersion': 'string', 'Date': datetime(2015, 1, 1), 'LastUpdateAssociationDate': datetime(2015, 1, 1), 'Status': { 'Date': datetime(2015, 1, 1), 'Name': 'Pending'|'Success'|'Failed', 'Message': 'string', 'AdditionalInfo': 'string' }, 'Overview': { 'Status': 'string', 'DetailedStatus': 'string', 'AssociationStatusAggregatedCount': { 'string': 123 } }, 'DocumentVersion': 'string', 'AutomationTargetParameterName': 'string', 'Parameters': { 'string': [ 'string', ] }, 'AssociationId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'ScheduleExpression': 'string', 'OutputLocation': { 'S3Location': { 'OutputS3Region': 'string', 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string' } }, 'LastExecutionDate': datetime(2015, 1, 1), 'LastSuccessfulExecutionDate': datetime(2015, 1, 1), 'AssociationName': 'string', 'MaxErrors': 'string', 'MaxConcurrency': 'string', 'ComplianceSeverity': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'UNSPECIFIED', 'SyncCompliance': 'AUTO'|'MANUAL' } } :returns: (string) -- (integer) -- """ pass def update_document(Content=None, Attachments=None, Name=None, VersionName=None, DocumentVersion=None, DocumentFormat=None, TargetType=None): """ Updates one or more values for an SSM document. See also: AWS API Documentation Exceptions :example: response = client.update_document( Content='string', Attachments=[ { 'Key': 'SourceUrl'|'S3FileUrl'|'AttachmentReference', 'Values': [ 'string', ], 'Name': 'string' }, ], Name='string', VersionName='string', DocumentVersion='string', DocumentFormat='YAML'|'JSON'|'TEXT', TargetType='string' ) :type Content: string :param Content: [REQUIRED]\nA valid JSON or YAML string.\n :type Attachments: list :param Attachments: A list of key and value pairs that describe attachments to a version of a document.\n\n(dict) --Identifying information about a document attachment, including the file name and a key-value pair that identifies the location of an attachment to a document.\n\nKey (string) --The key of a key-value pair that identifies the location of an attachment to a document.\n\nValues (list) --The value of a key-value pair that identifies the location of an attachment to a document. The format for Value depends on the type of key you specify.\n\nFor the key SourceUrl , the value is an S3 bucket location. For example: 'Values': [ 's3://my-bucket/my-folder' ]\nFor the key S3FileUrl , the value is a file in an S3 bucket. For example: 'Values': [ 's3://my-bucket/my-folder/my-file.py' ]\nFor the key AttachmentReference , the value is constructed from the name of another SSM document in your account, a version number of that document, and a file attached to that document version that you want to reuse. For example: 'Values': [ 'MyOtherDocument/3/my-other-file.py' ] However, if the SSM document is shared with you from another account, the full SSM document ARN must be specified instead of the document name only. For example: 'Values': [ 'arn:aws:ssm:us-east-2:111122223333:document/OtherAccountDocument/3/their-file.py' ]\n\n\n(string) --\n\n\nName (string) --The name of the document attachment file.\n\n\n\n\n :type Name: string :param Name: [REQUIRED]\nThe name of the document that you want to update.\n :type VersionName: string :param VersionName: An optional field specifying the version of the artifact you are updating with the document. For example, 'Release 12, Update 6'. This value is unique across all versions of a document, and cannot be changed. :type DocumentVersion: string :param DocumentVersion: (Required) The latest version of the document that you want to update. The latest document version can be specified using the $LATEST variable or by the version number. Updating a previous version of a document is not supported. :type DocumentFormat: string :param DocumentFormat: Specify the document format for the new document version. Systems Manager supports JSON and YAML documents. JSON is the default format. :type TargetType: string :param TargetType: Specify a new target type for the document. :rtype: dict ReturnsResponse Syntax { 'DocumentDescription': { 'Sha1': 'string', 'Hash': 'string', 'HashType': 'Sha256'|'Sha1', 'Name': 'string', 'VersionName': 'string', 'Owner': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'DocumentVersion': 'string', 'Description': 'string', 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList', 'Description': 'string', 'DefaultValue': 'string' }, ], 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'LatestVersion': 'string', 'DefaultVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'AttachmentsInformation': [ { 'Name': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] } } Response Structure (dict) -- DocumentDescription (dict) -- A description of the document that was updated. Sha1 (string) -- The SHA1 hash of the document, which you can use for verification. Hash (string) -- The Sha256 or Sha1 hash created by the system when the document was created. Note Sha1 hashes have been deprecated. HashType (string) -- The hash type of the document. Valid values include Sha256 or Sha1 . Note Sha1 hashes have been deprecated. Name (string) -- The name of the Systems Manager document. VersionName (string) -- The version of the artifact associated with the document. Owner (string) -- The AWS user account that created the document. CreatedDate (datetime) -- The date when the document was created. Status (string) -- The status of the Systems Manager document. StatusInformation (string) -- A message returned by AWS Systems Manager that explains the Status value. For example, a Failed status might be explained by the StatusInformation message, "The specified S3 bucket does not exist. Verify that the URL of the S3 bucket is correct." DocumentVersion (string) -- The document version. Description (string) -- A description of the document. Parameters (list) -- A description of the parameters for a document. (dict) -- Parameters specified in a System Manager document that run on the server when the command is run. Name (string) -- The name of the parameter. Type (string) -- The type of parameter. The type can be either String or StringList. Description (string) -- A description of what the parameter does, how to use it, the default value, and whether or not the parameter is optional. DefaultValue (string) -- If specified, the default values for the parameters. Parameters without a default value are required. Parameters with a default value are optional. PlatformTypes (list) -- The list of OS platforms compatible with this Systems Manager document. (string) -- DocumentType (string) -- The type of document. SchemaVersion (string) -- The schema version. LatestVersion (string) -- The latest version of the document. DefaultVersion (string) -- The default version. DocumentFormat (string) -- The document format, either JSON or YAML. TargetType (string) -- The target type which defines the kinds of resources the document can run on. For example, /AWS::EC2::Instance. For a list of valid resource types, see AWS resource and property types reference in the AWS CloudFormation User Guide . Tags (list) -- The tags, or metadata, that have been applied to the document. (dict) -- Metadata that you assign to your AWS resources. Tags enable you to categorize your resources in different ways, for example, by purpose, owner, or environment. In Systems Manager, you can apply tags to documents, managed instances, maintenance windows, Parameter Store parameters, and patch baselines. Key (string) -- The name of the tag. Value (string) -- The value of the tag. AttachmentsInformation (list) -- Details about the document attachments, including names, locations, sizes, and so on. (dict) -- An attribute of an attachment, such as the attachment name. Name (string) -- The name of the attachment. Requires (list) -- A list of SSM documents required by a document. For example, an ApplicationConfiguration document requires an ApplicationConfigurationSchema document. (dict) -- An SSM document required by the current document. Name (string) -- The name of the required SSM document. The name can be an Amazon Resource Name (ARN). Version (string) -- The document version required by the current document. Exceptions SSM.Client.exceptions.MaxDocumentSizeExceeded SSM.Client.exceptions.DocumentVersionLimitExceeded SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.DuplicateDocumentContent SSM.Client.exceptions.DuplicateDocumentVersionName SSM.Client.exceptions.InvalidDocumentContent SSM.Client.exceptions.InvalidDocumentVersion SSM.Client.exceptions.InvalidDocumentSchemaVersion SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentOperation :return: { 'DocumentDescription': { 'Sha1': 'string', 'Hash': 'string', 'HashType': 'Sha256'|'Sha1', 'Name': 'string', 'VersionName': 'string', 'Owner': 'string', 'CreatedDate': datetime(2015, 1, 1), 'Status': 'Creating'|'Active'|'Updating'|'Deleting'|'Failed', 'StatusInformation': 'string', 'DocumentVersion': 'string', 'Description': 'string', 'Parameters': [ { 'Name': 'string', 'Type': 'String'|'StringList', 'Description': 'string', 'DefaultValue': 'string' }, ], 'PlatformTypes': [ 'Windows'|'Linux', ], 'DocumentType': 'Command'|'Policy'|'Automation'|'Session'|'Package'|'ApplicationConfiguration'|'ApplicationConfigurationSchema'|'DeploymentStrategy'|'ChangeCalendar', 'SchemaVersion': 'string', 'LatestVersion': 'string', 'DefaultVersion': 'string', 'DocumentFormat': 'YAML'|'JSON'|'TEXT', 'TargetType': 'string', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ], 'AttachmentsInformation': [ { 'Name': 'string' }, ], 'Requires': [ { 'Name': 'string', 'Version': 'string' }, ] } } :returns: (string) -- """ pass def update_document_default_version(Name=None, DocumentVersion=None): """ Set the default version of a document. See also: AWS API Documentation Exceptions :example: response = client.update_document_default_version( Name='string', DocumentVersion='string' ) :type Name: string :param Name: [REQUIRED]\nThe name of a custom document that you want to set as the default version.\n :type DocumentVersion: string :param DocumentVersion: [REQUIRED]\nThe version of a custom document that you want to set as the default version.\n :rtype: dict ReturnsResponse Syntax { 'Description': { 'Name': 'string', 'DefaultVersion': 'string', 'DefaultVersionName': 'string' } } Response Structure (dict) -- Description (dict) -- The description of a custom document that you want to set as the default version. Name (string) -- The name of the document. DefaultVersion (string) -- The default version of the document. DefaultVersionName (string) -- The default version of the artifact associated with the document. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion SSM.Client.exceptions.InvalidDocumentSchemaVersion :return: { 'Description': { 'Name': 'string', 'DefaultVersion': 'string', 'DefaultVersionName': 'string' } } :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.InvalidDocument SSM.Client.exceptions.InvalidDocumentVersion SSM.Client.exceptions.InvalidDocumentSchemaVersion """ pass def update_maintenance_window(WindowId=None, Name=None, Description=None, StartDate=None, EndDate=None, Schedule=None, ScheduleTimezone=None, Duration=None, Cutoff=None, AllowUnassociatedTargets=None, Enabled=None, Replace=None): """ Updates an existing maintenance window. Only specified parameters are modified. See also: AWS API Documentation Exceptions :example: response = client.update_maintenance_window( WindowId='string', Name='string', Description='string', StartDate='string', EndDate='string', Schedule='string', ScheduleTimezone='string', Duration=123, Cutoff=123, AllowUnassociatedTargets=True|False, Enabled=True|False, Replace=True|False ) :type WindowId: string :param WindowId: [REQUIRED]\nThe ID of the maintenance window to update.\n :type Name: string :param Name: The name of the maintenance window. :type Description: string :param Description: An optional description for the update request. :type StartDate: string :param StartDate: The time zone that the scheduled maintenance window executions are based on, in Internet Assigned Numbers Authority (IANA) format. For example: 'America/Los_Angeles', 'etc/UTC', or 'Asia/Seoul'. For more information, see the Time Zone Database on the IANA website. :type EndDate: string :param EndDate: The date and time, in ISO-8601 Extended format, for when you want the maintenance window to become inactive. EndDate allows you to set a date and time in the future when the maintenance window will no longer run. :type Schedule: string :param Schedule: The schedule of the maintenance window in the form of a cron or rate expression. :type ScheduleTimezone: string :param ScheduleTimezone: The time zone that the scheduled maintenance window executions are based on, in Internet Assigned Numbers Authority (IANA) format. For example: 'America/Los_Angeles', 'etc/UTC', or 'Asia/Seoul'. For more information, see the Time Zone Database on the IANA website. :type Duration: integer :param Duration: The duration of the maintenance window in hours. :type Cutoff: integer :param Cutoff: The number of hours before the end of the maintenance window that Systems Manager stops scheduling new tasks for execution. :type AllowUnassociatedTargets: boolean :param AllowUnassociatedTargets: Whether targets must be registered with the maintenance window before tasks can be defined for those targets. :type Enabled: boolean :param Enabled: Whether the maintenance window is enabled. :type Replace: boolean :param Replace: If True, then all fields that are required by the CreateMaintenanceWindow action are also required for this API request. Optional fields that are not specified are set to null. :rtype: dict ReturnsResponse Syntax { 'WindowId': 'string', 'Name': 'string', 'Description': 'string', 'StartDate': 'string', 'EndDate': 'string', 'Schedule': 'string', 'ScheduleTimezone': 'string', 'Duration': 123, 'Cutoff': 123, 'AllowUnassociatedTargets': True|False, 'Enabled': True|False } Response Structure (dict) -- WindowId (string) -- The ID of the created maintenance window. Name (string) -- The name of the maintenance window. Description (string) -- An optional description of the update. StartDate (string) -- The date and time, in ISO-8601 Extended format, for when the maintenance window is scheduled to become active. The maintenance window will not run before this specified time. EndDate (string) -- The date and time, in ISO-8601 Extended format, for when the maintenance window is scheduled to become inactive. The maintenance window will not run after this specified time. Schedule (string) -- The schedule of the maintenance window in the form of a cron or rate expression. ScheduleTimezone (string) -- The time zone that the scheduled maintenance window executions are based on, in Internet Assigned Numbers Authority (IANA) format. For example: "America/Los_Angeles", "etc/UTC", or "Asia/Seoul". For more information, see the Time Zone Database on the IANA website. Duration (integer) -- The duration of the maintenance window in hours. Cutoff (integer) -- The number of hours before the end of the maintenance window that Systems Manager stops scheduling new tasks for execution. AllowUnassociatedTargets (boolean) -- Whether targets must be registered with the maintenance window before tasks can be defined for those targets. Enabled (boolean) -- Whether the maintenance window is enabled. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string', 'Name': 'string', 'Description': 'string', 'StartDate': 'string', 'EndDate': 'string', 'Schedule': 'string', 'ScheduleTimezone': 'string', 'Duration': 123, 'Cutoff': 123, 'AllowUnassociatedTargets': True|False, 'Enabled': True|False } :returns: SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError """ pass def update_maintenance_window_target(WindowId=None, WindowTargetId=None, Targets=None, OwnerInformation=None, Name=None, Description=None, Replace=None): """ Modifies the target of an existing maintenance window. You can change the following: See also: AWS API Documentation Exceptions :example: response = client.update_maintenance_window_target( WindowId='string', WindowTargetId='string', Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], OwnerInformation='string', Name='string', Description='string', Replace=True|False ) :type WindowId: string :param WindowId: [REQUIRED]\nThe maintenance window ID with which to modify the target.\n :type WindowTargetId: string :param WindowTargetId: [REQUIRED]\nThe target ID to modify.\n :type Targets: list :param Targets: The targets to add or replace.\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type OwnerInformation: string :param OwnerInformation: User-provided value that will be included in any CloudWatch events raised while running tasks for these targets in this maintenance window. :type Name: string :param Name: A name for the update. :type Description: string :param Description: An optional description for the update. :type Replace: boolean :param Replace: If True, then all fields that are required by the RegisterTargetWithMaintenanceWindow action are also required for this API request. Optional fields that are not specified are set to null. :rtype: dict ReturnsResponse Syntax { 'WindowId': 'string', 'WindowTargetId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'OwnerInformation': 'string', 'Name': 'string', 'Description': 'string' } Response Structure (dict) -- WindowId (string) -- The maintenance window ID specified in the update request. WindowTargetId (string) -- The target ID specified in the update request. Targets (list) -- The updated targets. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- OwnerInformation (string) -- The updated owner. Name (string) -- The updated name. Description (string) -- The updated description. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string', 'WindowTargetId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'OwnerInformation': 'string', 'Name': 'string', 'Description': 'string' } :returns: WindowId (string) -- [REQUIRED] The maintenance window ID with which to modify the target. WindowTargetId (string) -- [REQUIRED] The target ID to modify. Targets (list) -- The targets to add or replace. (dict) --An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) --User-defined criteria for sending commands that target instances that meet the criteria. Values (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- OwnerInformation (string) -- User-provided value that will be included in any CloudWatch events raised while running tasks for these targets in this maintenance window. Name (string) -- A name for the update. Description (string) -- An optional description for the update. Replace (boolean) -- If True, then all fields that are required by the RegisterTargetWithMaintenanceWindow action are also required for this API request. Optional fields that are not specified are set to null. """ pass def update_maintenance_window_task(WindowId=None, WindowTaskId=None, Targets=None, TaskArn=None, ServiceRoleArn=None, TaskParameters=None, TaskInvocationParameters=None, Priority=None, MaxConcurrency=None, MaxErrors=None, LoggingInfo=None, Name=None, Description=None, Replace=None): """ Modifies a task assigned to a maintenance window. You can\'t change the task type, but you can change the following values: If a parameter is null, then the corresponding field is not modified. Also, if you set Replace to true, then all fields required by the RegisterTaskWithMaintenanceWindow action are required for this request. Optional fields that aren\'t specified are set to null. See also: AWS API Documentation Exceptions :example: response = client.update_maintenance_window_task( WindowId='string', WindowTaskId='string', Targets=[ { 'Key': 'string', 'Values': [ 'string', ] }, ], TaskArn='string', ServiceRoleArn='string', TaskParameters={ 'string': { 'Values': [ 'string', ] } }, TaskInvocationParameters={ 'RunCommand': { 'Comment': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'DocumentHash': 'string', 'DocumentHashType': 'Sha256'|'Sha1', 'DocumentVersion': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'Parameters': { 'string': [ 'string', ] }, 'ServiceRoleArn': 'string', 'TimeoutSeconds': 123 }, 'Automation': { 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] } }, 'StepFunctions': { 'Input': 'string', 'Name': 'string' }, 'Lambda': { 'ClientContext': 'string', 'Qualifier': 'string', 'Payload': b'bytes' } }, Priority=123, MaxConcurrency='string', MaxErrors='string', LoggingInfo={ 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, Name='string', Description='string', Replace=True|False ) :type WindowId: string :param WindowId: [REQUIRED]\nThe maintenance window ID that contains the task to modify.\n :type WindowTaskId: string :param WindowTaskId: [REQUIRED]\nThe task ID to modify.\n :type Targets: list :param Targets: The targets (either instances or tags) to modify. Instances are specified using Key=instanceids,Values=instanceID_1,instanceID_2. Tags are specified using Key=tag_name,Values=tag_value.\n\n(dict) --An array of search criteria that targets instances using a Key,Value combination that you specify.\nSupported formats include the following.\n\n``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* ``\n``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* ``\n``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* ``\n(Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* ``\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* ``\n\nFor example:\n\nKey=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE\nKey=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3\nKey=tag-key,Values=Name,Instance-Type,CostCenter\n(Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window.\n(Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window.\n(State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created.\n\nFor information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide .\n\nKey (string) --User-defined criteria for sending commands that target instances that meet the criteria.\n\nValues (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer .\n\n(string) --\n\n\n\n\n\n :type TaskArn: string :param TaskArn: The task ARN to modify. :type ServiceRoleArn: string :param ServiceRoleArn: The ARN of the IAM service role for Systems Manager to assume when running a maintenance window task. If you do not specify a service role ARN, Systems Manager uses your account\'s service-linked role. If no service-linked role for Systems Manager exists in your account, it is created when you run RegisterTaskWithMaintenanceWindow .\nFor more information, see the following topics in the in the AWS Systems Manager User Guide :\n\nUsing service-linked roles for Systems Manager\nShould I use a service-linked role or a custom service role to run maintenance window tasks?\n\n :type TaskParameters: dict :param TaskParameters: The parameters to modify.\n\nNote\nTaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .\n\nThe map has the following format:\nKey: string, between 1 and 255 characters\nValue: an array of strings, each string is between 1 and 255 characters\n\n(string) --\n(dict) --Defines the values for a task parameter.\n\nValues (list) --This field contains an array of 0 or more strings, each 1 to 255 characters in length.\n\n(string) --\n\n\n\n\n\n\n\n :type TaskInvocationParameters: dict :param TaskInvocationParameters: The parameters that the task should use during execution. Populate only the fields that match the task type. All other fields should be empty.\n\nRunCommand (dict) --The parameters for a RUN_COMMAND task type.\n\nComment (string) --Information about the commands to run.\n\nCloudWatchOutputConfig (dict) --Configuration options for sending command output to CloudWatch Logs.\n\nCloudWatchLogGroupName (string) --The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName .\n\nCloudWatchOutputEnabled (boolean) --Enables Systems Manager to send command output to CloudWatch Logs.\n\n\n\nDocumentHash (string) --The SHA-256 or SHA-1 hash created by the system when the document was created. SHA-1 hashes have been deprecated.\n\nDocumentHashType (string) --SHA-256 or SHA-1. SHA-1 hashes have been deprecated.\n\nDocumentVersion (string) --The SSM document version to use in the request. You can specify $DEFAULT, $LATEST, or a specific version number. If you run commands by using the AWS CLI, then you must escape the first two options by using a backslash. If you specify a version number, then you don\'t need to use the backslash. For example:\n--document-version '$DEFAULT'\n--document-version '$LATEST'\n--document-version '3'\n\nNotificationConfig (dict) --Configurations for sending notifications about command status changes on a per-instance basis.\n\nNotificationArn (string) --An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic.\n\nNotificationEvents (list) --The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide .\n\n(string) --\n\n\nNotificationType (string) --Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes.\n\n\n\nOutputS3BucketName (string) --The name of the S3 bucket.\n\nOutputS3KeyPrefix (string) --The S3 bucket subfolder.\n\nParameters (dict) --The parameters for the RUN_COMMAND task execution.\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n\nServiceRoleArn (string) --The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks.\n\nTimeoutSeconds (integer) --If this time is reached and the command has not already started running, it doesn\'t run.\n\n\n\nAutomation (dict) --The parameters for an AUTOMATION task type.\n\nDocumentVersion (string) --The version of an Automation document to use during task execution.\n\nParameters (dict) --The parameters for the AUTOMATION task.\nFor information about specifying and updating task parameters, see RegisterTaskWithMaintenanceWindow and UpdateMaintenanceWindowTask .\n\nNote\n\nLoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .\n\nFor AUTOMATION task types, Systems Manager ignores any values specified for these parameters.\n\n\n(string) --\n(list) --\n(string) --\n\n\n\n\n\n\n\n\nStepFunctions (dict) --The parameters for a STEP_FUNCTIONS task type.\n\nInput (string) --The inputs for the STEP_FUNCTIONS task.\n\nName (string) --The name of the STEP_FUNCTIONS task.\n\n\n\nLambda (dict) --The parameters for a LAMBDA task type.\n\nClientContext (string) --Pass client-specific information to the Lambda function that you are invoking. You can then process the client information in your Lambda function as you choose through the context variable.\n\nQualifier (string) --(Optional) Specify a Lambda function version or alias name. If you specify a function version, the action uses the qualified function ARN to invoke a specific Lambda function. If you specify an alias name, the action uses the alias ARN to invoke the Lambda function version to which the alias points.\n\nPayload (bytes) --JSON to provide to your Lambda function as input.\n\n\n\n\n :type Priority: integer :param Priority: The new task priority to specify. The lower the number, the higher the priority. Tasks that have the same priority are scheduled in parallel. :type MaxConcurrency: string :param MaxConcurrency: The new MaxConcurrency value you want to specify. MaxConcurrency is the number of targets that are allowed to run this task in parallel. :type MaxErrors: string :param MaxErrors: The new MaxErrors value to specify. MaxErrors is the maximum number of errors that are allowed before the task stops being scheduled. :type LoggingInfo: dict :param LoggingInfo: The new logging location in Amazon S3 to specify.\n\nNote\nLoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .\n\n\nS3BucketName (string) -- [REQUIRED]The name of an S3 bucket where execution logs are stored .\n\nS3KeyPrefix (string) --(Optional) The S3 bucket subfolder.\n\nS3Region (string) -- [REQUIRED]The Region where the S3 bucket is located.\n\n\n :type Name: string :param Name: The new task name to specify. :type Description: string :param Description: The new task description to specify. :type Replace: boolean :param Replace: If True, then all fields that are required by the RegisterTaskWithMaintenanceWndow action are also required for this API request. Optional fields that are not specified are set to null. :rtype: dict ReturnsResponse Syntax { 'WindowId': 'string', 'WindowTaskId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TaskArn': 'string', 'ServiceRoleArn': 'string', 'TaskParameters': { 'string': { 'Values': [ 'string', ] } }, 'TaskInvocationParameters': { 'RunCommand': { 'Comment': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'DocumentHash': 'string', 'DocumentHashType': 'Sha256'|'Sha1', 'DocumentVersion': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'Parameters': { 'string': [ 'string', ] }, 'ServiceRoleArn': 'string', 'TimeoutSeconds': 123 }, 'Automation': { 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] } }, 'StepFunctions': { 'Input': 'string', 'Name': 'string' }, 'Lambda': { 'ClientContext': 'string', 'Qualifier': 'string', 'Payload': b'bytes' } }, 'Priority': 123, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'LoggingInfo': { 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, 'Name': 'string', 'Description': 'string' } Response Structure (dict) -- WindowId (string) -- The ID of the maintenance window that was updated. WindowTaskId (string) -- The task ID of the maintenance window that was updated. Targets (list) -- The updated target values. (dict) -- An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) -- User-defined criteria for sending commands that target instances that meet the criteria. Values (list) -- User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TaskArn (string) -- The updated task ARN value. ServiceRoleArn (string) -- The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks. TaskParameters (dict) -- The updated parameter values. Note TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . (string) -- (dict) -- Defines the values for a task parameter. Values (list) -- This field contains an array of 0 or more strings, each 1 to 255 characters in length. (string) -- TaskInvocationParameters (dict) -- The updated parameter values. RunCommand (dict) -- The parameters for a RUN_COMMAND task type. Comment (string) -- Information about the commands to run. CloudWatchOutputConfig (dict) -- Configuration options for sending command output to CloudWatch Logs. CloudWatchLogGroupName (string) -- The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName . CloudWatchOutputEnabled (boolean) -- Enables Systems Manager to send command output to CloudWatch Logs. DocumentHash (string) -- The SHA-256 or SHA-1 hash created by the system when the document was created. SHA-1 hashes have been deprecated. DocumentHashType (string) -- SHA-256 or SHA-1. SHA-1 hashes have been deprecated. DocumentVersion (string) -- The SSM document version to use in the request. You can specify $DEFAULT, $LATEST, or a specific version number. If you run commands by using the AWS CLI, then you must escape the first two options by using a backslash. If you specify a version number, then you don\'t need to use the backslash. For example: --document-version "$DEFAULT" --document-version "$LATEST" --document-version "3" NotificationConfig (dict) -- Configurations for sending notifications about command status changes on a per-instance basis. NotificationArn (string) -- An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic. NotificationEvents (list) -- The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide . (string) -- NotificationType (string) -- Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes. OutputS3BucketName (string) -- The name of the S3 bucket. OutputS3KeyPrefix (string) -- The S3 bucket subfolder. Parameters (dict) -- The parameters for the RUN_COMMAND task execution. (string) -- (list) -- (string) -- ServiceRoleArn (string) -- The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks. TimeoutSeconds (integer) -- If this time is reached and the command has not already started running, it doesn\'t run. Automation (dict) -- The parameters for an AUTOMATION task type. DocumentVersion (string) -- The version of an Automation document to use during task execution. Parameters (dict) -- The parameters for the AUTOMATION task. For information about specifying and updating task parameters, see RegisterTaskWithMaintenanceWindow and UpdateMaintenanceWindowTask . Note LoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . For AUTOMATION task types, Systems Manager ignores any values specified for these parameters. (string) -- (list) -- (string) -- StepFunctions (dict) -- The parameters for a STEP_FUNCTIONS task type. Input (string) -- The inputs for the STEP_FUNCTIONS task. Name (string) -- The name of the STEP_FUNCTIONS task. Lambda (dict) -- The parameters for a LAMBDA task type. ClientContext (string) -- Pass client-specific information to the Lambda function that you are invoking. You can then process the client information in your Lambda function as you choose through the context variable. Qualifier (string) -- (Optional) Specify a Lambda function version or alias name. If you specify a function version, the action uses the qualified function ARN to invoke a specific Lambda function. If you specify an alias name, the action uses the alias ARN to invoke the Lambda function version to which the alias points. Payload (bytes) -- JSON to provide to your Lambda function as input. Priority (integer) -- The updated priority value. MaxConcurrency (string) -- The updated MaxConcurrency value. MaxErrors (string) -- The updated MaxErrors value. LoggingInfo (dict) -- The updated logging information in Amazon S3. Note LoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . S3BucketName (string) -- The name of an S3 bucket where execution logs are stored . S3KeyPrefix (string) -- (Optional) The S3 bucket subfolder. S3Region (string) -- The Region where the S3 bucket is located. Name (string) -- The updated task name. Description (string) -- The updated task description. Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'WindowId': 'string', 'WindowTaskId': 'string', 'Targets': [ { 'Key': 'string', 'Values': [ 'string', ] }, ], 'TaskArn': 'string', 'ServiceRoleArn': 'string', 'TaskParameters': { 'string': { 'Values': [ 'string', ] } }, 'TaskInvocationParameters': { 'RunCommand': { 'Comment': 'string', 'CloudWatchOutputConfig': { 'CloudWatchLogGroupName': 'string', 'CloudWatchOutputEnabled': True|False }, 'DocumentHash': 'string', 'DocumentHashType': 'Sha256'|'Sha1', 'DocumentVersion': 'string', 'NotificationConfig': { 'NotificationArn': 'string', 'NotificationEvents': [ 'All'|'InProgress'|'Success'|'TimedOut'|'Cancelled'|'Failed', ], 'NotificationType': 'Command'|'Invocation' }, 'OutputS3BucketName': 'string', 'OutputS3KeyPrefix': 'string', 'Parameters': { 'string': [ 'string', ] }, 'ServiceRoleArn': 'string', 'TimeoutSeconds': 123 }, 'Automation': { 'DocumentVersion': 'string', 'Parameters': { 'string': [ 'string', ] } }, 'StepFunctions': { 'Input': 'string', 'Name': 'string' }, 'Lambda': { 'ClientContext': 'string', 'Qualifier': 'string', 'Payload': b'bytes' } }, 'Priority': 123, 'MaxConcurrency': 'string', 'MaxErrors': 'string', 'LoggingInfo': { 'S3BucketName': 'string', 'S3KeyPrefix': 'string', 'S3Region': 'string' }, 'Name': 'string', 'Description': 'string' } :returns: WindowId (string) -- [REQUIRED] The maintenance window ID that contains the task to modify. WindowTaskId (string) -- [REQUIRED] The task ID to modify. Targets (list) -- The targets (either instances or tags) to modify. Instances are specified using Key=instanceids,Values=instanceID_1,instanceID_2. Tags are specified using Key=tag_name,Values=tag_value. (dict) --An array of search criteria that targets instances using a Key,Value combination that you specify. Supported formats include the following. ``Key=InstanceIds,Values=*instance-id-1* ,*instance-id-2* ,*instance-id-3* `` ``Key=tag:my-tag-key ,Values=*my-tag-value-1* ,*my-tag-value-2* `` ``Key=tag-key,Values=*my-tag-key-1* ,*my-tag-key-2* `` (Maintenance window targets only) ``Key=resource-groups:Name,Values=*resource-group-name* `` (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*resource-type-1* ,*resource-type-2* `` For example: Key=InstanceIds,Values=i-02573cafcfEXAMPLE,i-0471e04240EXAMPLE,i-07782c72faEXAMPLE Key=tag:CostCenter,Values=CostCenter1,CostCenter2,CostCenter3 Key=tag-key,Values=Name,Instance-Type,CostCenter (Maintenance window targets only) Key=resource-groups:Name,Values=ProductionResourceGroup This example demonstrates how to target all resources in the resource group ProductionResourceGroup in your maintenance window. (Maintenance window targets only) ``Key=resource-groups:ResourceTypeFilters,Values=*AWS::EC2::INSTANCE* ,*AWS::EC2::VPC* `` This example demonstrates how to target only EC2 instances and VPCs in your maintenance window. (State Manager association targets only) Key=InstanceIds,Values=* This example demonstrates how to target all managed instances in the AWS Region where the association was created. For information about how to send commands that target instances using Key,Value parameters, see Targeting multiple instances in the AWS Systems Manager User Guide . Key (string) --User-defined criteria for sending commands that target instances that meet the criteria. Values (list) --User-defined criteria that maps to Key . For example, if you specified tag:ServerRole , you could specify value:WebServer to run a command on instances that include EC2 tags of ServerRole,WebServer . (string) -- TaskArn (string) -- The task ARN to modify. ServiceRoleArn (string) -- The ARN of the IAM service role for Systems Manager to assume when running a maintenance window task. If you do not specify a service role ARN, Systems Manager uses your account\'s service-linked role. If no service-linked role for Systems Manager exists in your account, it is created when you run RegisterTaskWithMaintenanceWindow . For more information, see the following topics in the in the AWS Systems Manager User Guide : Using service-linked roles for Systems Manager Should I use a service-linked role or a custom service role to run maintenance window tasks? TaskParameters (dict) -- The parameters to modify. Note TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . The map has the following format: Key: string, between 1 and 255 characters Value: an array of strings, each string is between 1 and 255 characters (string) -- (dict) --Defines the values for a task parameter. Values (list) --This field contains an array of 0 or more strings, each 1 to 255 characters in length. (string) -- TaskInvocationParameters (dict) -- The parameters that the task should use during execution. Populate only the fields that match the task type. All other fields should be empty. RunCommand (dict) --The parameters for a RUN_COMMAND task type. Comment (string) --Information about the commands to run. CloudWatchOutputConfig (dict) --Configuration options for sending command output to CloudWatch Logs. CloudWatchLogGroupName (string) --The name of the CloudWatch log group where you want to send command output. If you don\'t specify a group name, Systems Manager automatically creates a log group for you. The log group uses the following naming format: aws/ssm/SystemsManagerDocumentName . CloudWatchOutputEnabled (boolean) --Enables Systems Manager to send command output to CloudWatch Logs. DocumentHash (string) --The SHA-256 or SHA-1 hash created by the system when the document was created. SHA-1 hashes have been deprecated. DocumentHashType (string) --SHA-256 or SHA-1. SHA-1 hashes have been deprecated. DocumentVersion (string) --The SSM document version to use in the request. You can specify $DEFAULT, $LATEST, or a specific version number. If you run commands by using the AWS CLI, then you must escape the first two options by using a backslash. If you specify a version number, then you don\'t need to use the backslash. For example: --document-version "$DEFAULT" --document-version "$LATEST" --document-version "3" NotificationConfig (dict) --Configurations for sending notifications about command status changes on a per-instance basis. NotificationArn (string) --An Amazon Resource Name (ARN) for an Amazon Simple Notification Service (Amazon SNS) topic. Run Command pushes notifications about command status changes to this topic. NotificationEvents (list) --The different events for which you can receive notifications. These events include the following: All (events), InProgress, Success, TimedOut, Cancelled, Failed. To learn more about these events, see Monitoring Systems Manager status changes using Amazon SNS notifications in the AWS Systems Manager User Guide . (string) -- NotificationType (string) --Command: Receive notification when the status of a command changes. Invocation: For commands sent to multiple instances, receive notification on a per-instance basis when the status of a command changes. OutputS3BucketName (string) --The name of the S3 bucket. OutputS3KeyPrefix (string) --The S3 bucket subfolder. Parameters (dict) --The parameters for the RUN_COMMAND task execution. (string) -- (list) -- (string) -- ServiceRoleArn (string) --The ARN of the IAM service role to use to publish Amazon Simple Notification Service (Amazon SNS) notifications for maintenance window Run Command tasks. TimeoutSeconds (integer) --If this time is reached and the command has not already started running, it doesn\'t run. Automation (dict) --The parameters for an AUTOMATION task type. DocumentVersion (string) --The version of an Automation document to use during task execution. Parameters (dict) --The parameters for the AUTOMATION task. For information about specifying and updating task parameters, see RegisterTaskWithMaintenanceWindow and UpdateMaintenanceWindowTask . Note LoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters .TaskParameters has been deprecated. To specify parameters to pass to a task when it runs, instead use the Parameters option in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . For AUTOMATION task types, Systems Manager ignores any values specified for these parameters. (string) -- (list) -- (string) -- StepFunctions (dict) --The parameters for a STEP_FUNCTIONS task type. Input (string) --The inputs for the STEP_FUNCTIONS task. Name (string) --The name of the STEP_FUNCTIONS task. Lambda (dict) --The parameters for a LAMBDA task type. ClientContext (string) --Pass client-specific information to the Lambda function that you are invoking. You can then process the client information in your Lambda function as you choose through the context variable. Qualifier (string) --(Optional) Specify a Lambda function version or alias name. If you specify a function version, the action uses the qualified function ARN to invoke a specific Lambda function. If you specify an alias name, the action uses the alias ARN to invoke the Lambda function version to which the alias points. Payload (bytes) --JSON to provide to your Lambda function as input. Priority (integer) -- The new task priority to specify. The lower the number, the higher the priority. Tasks that have the same priority are scheduled in parallel. MaxConcurrency (string) -- The new MaxConcurrency value you want to specify. MaxConcurrency is the number of targets that are allowed to run this task in parallel. MaxErrors (string) -- The new MaxErrors value to specify. MaxErrors is the maximum number of errors that are allowed before the task stops being scheduled. LoggingInfo (dict) -- The new logging location in Amazon S3 to specify. Note LoggingInfo has been deprecated. To specify an S3 bucket to contain logs, instead use the OutputS3BucketName and OutputS3KeyPrefix options in the TaskInvocationParameters structure. For information about how Systems Manager handles these options for the supported maintenance window task types, see MaintenanceWindowTaskInvocationParameters . S3BucketName (string) -- [REQUIRED]The name of an S3 bucket where execution logs are stored . S3KeyPrefix (string) --(Optional) The S3 bucket subfolder. S3Region (string) -- [REQUIRED]The Region where the S3 bucket is located. Name (string) -- The new task name to specify. Description (string) -- The new task description to specify. Replace (boolean) -- If True, then all fields that are required by the RegisterTaskWithMaintenanceWndow action are also required for this API request. Optional fields that are not specified are set to null. """ pass def update_managed_instance_role(InstanceId=None, IamRole=None): """ Changes the Amazon Identity and Access Management (IAM) role that is assigned to the on-premises instance or virtual machines (VM). IAM roles are first assigned to these hybrid instances during the activation process. For more information, see CreateActivation . See also: AWS API Documentation Exceptions :example: response = client.update_managed_instance_role( InstanceId='string', IamRole='string' ) :type InstanceId: string :param InstanceId: [REQUIRED]\nThe ID of the managed instance where you want to update the role.\n :type IamRole: string :param IamRole: [REQUIRED]\nThe IAM role you want to assign or change.\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InvalidInstanceId SSM.Client.exceptions.InternalServerError :return: {} :returns: (dict) -- """ pass def update_ops_item(Description=None, OperationalData=None, OperationalDataToDelete=None, Notifications=None, Priority=None, RelatedOpsItems=None, Status=None, OpsItemId=None, Title=None, Category=None, Severity=None): """ Edit or change an OpsItem. You must have permission in AWS Identity and Access Management (IAM) to update an OpsItem. For more information, see Getting started with OpsCenter in the AWS Systems Manager User Guide . Operations engineers and IT professionals use OpsCenter to view, investigate, and remediate operational issues impacting the performance and health of their AWS resources. For more information, see AWS Systems Manager OpsCenter in the AWS Systems Manager User Guide . See also: AWS API Documentation Exceptions :example: response = client.update_ops_item( Description='string', OperationalData={ 'string': { 'Value': 'string', 'Type': 'SearchableString'|'String' } }, OperationalDataToDelete=[ 'string', ], Notifications=[ { 'Arn': 'string' }, ], Priority=123, RelatedOpsItems=[ { 'OpsItemId': 'string' }, ], Status='Open'|'InProgress'|'Resolved', OpsItemId='string', Title='string', Category='string', Severity='string' ) :type Description: string :param Description: Update the information about the OpsItem. Provide enough information so that users reading this OpsItem for the first time understand the issue. :type OperationalData: dict :param OperationalData: Add new keys or edit existing key-value pairs of the OperationalData map in the OpsItem object.\nOperational data is custom data that provides useful reference details about the OpsItem. For example, you can specify log files, error strings, license keys, troubleshooting tips, or other relevant data. You enter operational data as key-value pairs. The key has a maximum length of 128 characters. The value has a maximum size of 20 KB.\n\nWarning\nOperational data keys can\'t begin with the following: amazon, aws, amzn, ssm, /amazon, /aws, /amzn, /ssm.\n\nYou can choose to make the data searchable by other users in the account or you can restrict search access. Searchable data means that all users with access to the OpsItem Overview page (as provided by the DescribeOpsItems API action) can view and search on the specified data. Operational data that is not searchable is only viewable by users who have access to the OpsItem (as provided by the GetOpsItem API action).\nUse the /aws/resources key in OperationalData to specify a related resource in the request. Use the /aws/automations key in OperationalData to associate an Automation runbook with the OpsItem. To view AWS CLI example commands that use these keys, see Creating OpsItems manually in the AWS Systems Manager User Guide .\n\n(string) --\n(dict) --An object that defines the value of the key and its type in the OperationalData map.\n\nValue (string) --The value of the OperationalData key.\n\nType (string) --The type of key-value pair. Valid types include SearchableString and String .\n\n\n\n\n\n\n :type OperationalDataToDelete: list :param OperationalDataToDelete: Keys that you want to remove from the OperationalData map.\n\n(string) --\n\n :type Notifications: list :param Notifications: The Amazon Resource Name (ARN) of an SNS topic where notifications are sent when this OpsItem is edited or changed.\n\n(dict) --A notification about the OpsItem.\n\nArn (string) --The Amazon Resource Name (ARN) of an SNS topic where notifications are sent when this OpsItem is edited or changed.\n\n\n\n\n :type Priority: integer :param Priority: The importance of this OpsItem in relation to other OpsItems in the system. :type RelatedOpsItems: list :param RelatedOpsItems: One or more OpsItems that share something in common with the current OpsItems. For example, related OpsItems can include OpsItems with similar error messages, impacted resources, or statuses for the impacted resource.\n\n(dict) --An OpsItems that shares something in common with the current OpsItem. For example, related OpsItems can include OpsItems with similar error messages, impacted resources, or statuses for the impacted resource.\n\nOpsItemId (string) -- [REQUIRED]The ID of an OpsItem related to the current OpsItem.\n\n\n\n\n :type Status: string :param Status: The OpsItem status. Status can be Open , In Progress , or Resolved . For more information, see Editing OpsItem details in the AWS Systems Manager User Guide . :type OpsItemId: string :param OpsItemId: [REQUIRED]\nThe ID of the OpsItem.\n :type Title: string :param Title: A short heading that describes the nature of the OpsItem and the impacted resource. :type Category: string :param Category: Specify a new category for an OpsItem. :type Severity: string :param Severity: Specify a new severity for an OpsItem. :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.OpsItemNotFoundException SSM.Client.exceptions.OpsItemAlreadyExistsException SSM.Client.exceptions.OpsItemLimitExceededException SSM.Client.exceptions.OpsItemInvalidParameterException :return: {} :returns: (dict) -- """ pass def update_patch_baseline(BaselineId=None, Name=None, GlobalFilters=None, ApprovalRules=None, ApprovedPatches=None, ApprovedPatchesComplianceLevel=None, ApprovedPatchesEnableNonSecurity=None, RejectedPatches=None, RejectedPatchesAction=None, Description=None, Sources=None, Replace=None): """ Modifies an existing patch baseline. Fields not specified in the request are left unchanged. See also: AWS API Documentation Exceptions :example: response = client.update_patch_baseline( BaselineId='string', Name='string', GlobalFilters={ 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, ApprovalRules={ 'PatchRules': [ { 'PatchFilterGroup': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApproveAfterDays': 123, 'ApproveUntilDate': 'string', 'EnableNonSecurity': True|False }, ] }, ApprovedPatches=[ 'string', ], ApprovedPatchesComplianceLevel='CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', ApprovedPatchesEnableNonSecurity=True|False, RejectedPatches=[ 'string', ], RejectedPatchesAction='ALLOW_AS_DEPENDENCY'|'BLOCK', Description='string', Sources=[ { 'Name': 'string', 'Products': [ 'string', ], 'Configuration': 'string' }, ], Replace=True|False ) :type BaselineId: string :param BaselineId: [REQUIRED]\nThe ID of the patch baseline to update.\n :type Name: string :param Name: The name of the patch baseline. :type GlobalFilters: dict :param GlobalFilters: A set of global filters used to include patches in the baseline.\n\nPatchFilters (list) -- [REQUIRED]The set of patch filters that make up the group.\n\n(dict) --Defines which patches should be included in a patch baseline.\nA patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ['Office 2013', 'Office 2016'], then the filter accepts all patches where product name is either 'Office 2013' or 'Office 2016'. The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values.\nYou can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties .\n\nKey (string) -- [REQUIRED]The key for the filter.\nRun the DescribePatchProperties command to view lists of valid keys for each operating system type.\n\nValues (list) -- [REQUIRED]The value for the filter key.\nRun the DescribePatchProperties command to view lists of valid values for each key based on operating system type.\n\n(string) --\n\n\n\n\n\n\n\n :type ApprovalRules: dict :param ApprovalRules: A set of rules used to include patches in the baseline.\n\nPatchRules (list) -- [REQUIRED]The rules that make up the rule group.\n\n(dict) --Defines an approval rule for a patch baseline.\n\nPatchFilterGroup (dict) -- [REQUIRED]The patch filter group that defines the criteria for the rule.\n\nPatchFilters (list) -- [REQUIRED]The set of patch filters that make up the group.\n\n(dict) --Defines which patches should be included in a patch baseline.\nA patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ['Office 2013', 'Office 2016'], then the filter accepts all patches where product name is either 'Office 2013' or 'Office 2016'. The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values.\nYou can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties .\n\nKey (string) -- [REQUIRED]The key for the filter.\nRun the DescribePatchProperties command to view lists of valid keys for each operating system type.\n\nValues (list) -- [REQUIRED]The value for the filter key.\nRun the DescribePatchProperties command to view lists of valid values for each key based on operating system type.\n\n(string) --\n\n\n\n\n\n\n\n\nComplianceLevel (string) --A compliance severity level for all approved patches in a patch baseline.\n\nApproveAfterDays (integer) --The number of days after the release date of each patch matched by the rule that the patch is marked as approved in the patch baseline. For example, a value of 7 means that patches are approved seven days after they are released. Not supported on Ubuntu Server.\n\nApproveUntilDate (string) --The cutoff date for auto approval of released patches. Any patches released on or before this date are installed automatically. Not supported on Ubuntu Server.\nEnter dates in the format YYYY-MM-DD . For example, 2020-12-31 .\n\nEnableNonSecurity (boolean) --For instances identified by the approval rule filters, enables a patch baseline to apply non-security updates available in the specified repository. The default value is \'false\'. Applies to Linux instances only.\n\n\n\n\n\n\n :type ApprovedPatches: list :param ApprovedPatches: A list of explicitly approved patches for the baseline.\nFor information about accepted formats for lists of approved patches and rejected patches, see About package name formats for approved and rejected patch lists in the AWS Systems Manager User Guide .\n\n(string) --\n\n :type ApprovedPatchesComplianceLevel: string :param ApprovedPatchesComplianceLevel: Assigns a new compliance severity level to an existing patch baseline. :type ApprovedPatchesEnableNonSecurity: boolean :param ApprovedPatchesEnableNonSecurity: Indicates whether the list of approved patches includes non-security updates that should be applied to the instances. The default value is \'false\'. Applies to Linux instances only. :type RejectedPatches: list :param RejectedPatches: A list of explicitly rejected patches for the baseline.\nFor information about accepted formats for lists of approved patches and rejected patches, see About package name formats for approved and rejected patch lists in the AWS Systems Manager User Guide .\n\n(string) --\n\n :type RejectedPatchesAction: string :param RejectedPatchesAction: The action for Patch Manager to take on patches included in the RejectedPackages list.\n\nALLOW_AS_DEPENDENCY : A package in the Rejected patches list is installed only if it is a dependency of another package. It is considered compliant with the patch baseline, and its status is reported as InstalledOther . This is the default action if no option is specified.\nBLOCK : Packages in the RejectedPatches list, and packages that include them as dependencies, are not installed under any circumstances. If a package was installed before it was added to the Rejected patches list, it is considered non-compliant with the patch baseline, and its status is reported as InstalledRejected .\n\n :type Description: string :param Description: A description of the patch baseline. :type Sources: list :param Sources: Information about the patches to use to update the instances, including target operating systems and source repositories. Applies to Linux instances only.\n\n(dict) --Information about the patches to use to update the instances, including target operating systems and source repository. Applies to Linux instances only.\n\nName (string) -- [REQUIRED]The name specified to identify the patch source.\n\nProducts (list) -- [REQUIRED]The specific operating system versions a patch repository applies to, such as 'Ubuntu16.04', 'AmazonLinux2016.09', 'RedhatEnterpriseLinux7.2' or 'Suse12.7'. For lists of supported product values, see PatchFilter .\n\n(string) --\n\n\nConfiguration (string) -- [REQUIRED]The value of the yum repo configuration. For example:\n\n[main]cachedir=/var/cache/yum/$basesearch$releasever\nkeepcache=0\ndebuglevel=2\n\n\n\n\n\n :type Replace: boolean :param Replace: If True, then all fields that are required by the CreatePatchBaseline action are also required for this API request. Optional fields that are not specified are set to null. :rtype: dict ReturnsResponse Syntax { 'BaselineId': 'string', 'Name': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'GlobalFilters': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ApprovalRules': { 'PatchRules': [ { 'PatchFilterGroup': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApproveAfterDays': 123, 'ApproveUntilDate': 'string', 'EnableNonSecurity': True|False }, ] }, 'ApprovedPatches': [ 'string', ], 'ApprovedPatchesComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApprovedPatchesEnableNonSecurity': True|False, 'RejectedPatches': [ 'string', ], 'RejectedPatchesAction': 'ALLOW_AS_DEPENDENCY'|'BLOCK', 'CreatedDate': datetime(2015, 1, 1), 'ModifiedDate': datetime(2015, 1, 1), 'Description': 'string', 'Sources': [ { 'Name': 'string', 'Products': [ 'string', ], 'Configuration': 'string' }, ] } Response Structure (dict) -- BaselineId (string) -- The ID of the deleted patch baseline. Name (string) -- The name of the patch baseline. OperatingSystem (string) -- The operating system rule used by the updated patch baseline. GlobalFilters (dict) -- A set of global filters used to exclude patches from the baseline. PatchFilters (list) -- The set of patch filters that make up the group. (dict) -- Defines which patches should be included in a patch baseline. A patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ["Office 2013", "Office 2016"], then the filter accepts all patches where product name is either "Office 2013" or "Office 2016". The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values. You can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties . Key (string) -- The key for the filter. Run the DescribePatchProperties command to view lists of valid keys for each operating system type. Values (list) -- The value for the filter key. Run the DescribePatchProperties command to view lists of valid values for each key based on operating system type. (string) -- ApprovalRules (dict) -- A set of rules used to include patches in the baseline. PatchRules (list) -- The rules that make up the rule group. (dict) -- Defines an approval rule for a patch baseline. PatchFilterGroup (dict) -- The patch filter group that defines the criteria for the rule. PatchFilters (list) -- The set of patch filters that make up the group. (dict) -- Defines which patches should be included in a patch baseline. A patch filter consists of a key and a set of values. The filter key is a patch property. For example, the available filter keys for WINDOWS are PATCH_SET, PRODUCT, PRODUCT_FAMILY, CLASSIFICATION, and MSRC_SEVERITY. The filter values define a matching criterion for the patch property indicated by the key. For example, if the filter key is PRODUCT and the filter values are ["Office 2013", "Office 2016"], then the filter accepts all patches where product name is either "Office 2013" or "Office 2016". The filter values can be exact values for the patch property given as a key, or a wildcard (*), which matches all values. You can view lists of valid values for the patch properties by running the DescribePatchProperties command. For information about which patch properties can be used with each major operating system, see DescribePatchProperties . Key (string) -- The key for the filter. Run the DescribePatchProperties command to view lists of valid keys for each operating system type. Values (list) -- The value for the filter key. Run the DescribePatchProperties command to view lists of valid values for each key based on operating system type. (string) -- ComplianceLevel (string) -- A compliance severity level for all approved patches in a patch baseline. ApproveAfterDays (integer) -- The number of days after the release date of each patch matched by the rule that the patch is marked as approved in the patch baseline. For example, a value of 7 means that patches are approved seven days after they are released. Not supported on Ubuntu Server. ApproveUntilDate (string) -- The cutoff date for auto approval of released patches. Any patches released on or before this date are installed automatically. Not supported on Ubuntu Server. Enter dates in the format YYYY-MM-DD . For example, 2020-12-31 . EnableNonSecurity (boolean) -- For instances identified by the approval rule filters, enables a patch baseline to apply non-security updates available in the specified repository. The default value is \'false\'. Applies to Linux instances only. ApprovedPatches (list) -- A list of explicitly approved patches for the baseline. (string) -- ApprovedPatchesComplianceLevel (string) -- The compliance severity level assigned to the patch baseline after the update completed. ApprovedPatchesEnableNonSecurity (boolean) -- Indicates whether the list of approved patches includes non-security updates that should be applied to the instances. The default value is \'false\'. Applies to Linux instances only. RejectedPatches (list) -- A list of explicitly rejected patches for the baseline. (string) -- RejectedPatchesAction (string) -- The action specified to take on patches included in the RejectedPatches list. A patch can be allowed only if it is a dependency of another package, or blocked entirely along with packages that include it as a dependency. CreatedDate (datetime) -- The date when the patch baseline was created. ModifiedDate (datetime) -- The date when the patch baseline was last modified. Description (string) -- A description of the Patch Baseline. Sources (list) -- Information about the patches to use to update the instances, including target operating systems and source repositories. Applies to Linux instances only. (dict) -- Information about the patches to use to update the instances, including target operating systems and source repository. Applies to Linux instances only. Name (string) -- The name specified to identify the patch source. Products (list) -- The specific operating system versions a patch repository applies to, such as "Ubuntu16.04", "AmazonLinux2016.09", "RedhatEnterpriseLinux7.2" or "Suse12.7". For lists of supported product values, see PatchFilter . (string) -- Configuration (string) -- The value of the yum repo configuration. For example: [main] cachedir=/var/cache/yum/$basesearch$releasever keepcache=0 debuglevel=2 Exceptions SSM.Client.exceptions.DoesNotExistException SSM.Client.exceptions.InternalServerError :return: { 'BaselineId': 'string', 'Name': 'string', 'OperatingSystem': 'WINDOWS'|'AMAZON_LINUX'|'AMAZON_LINUX_2'|'UBUNTU'|'REDHAT_ENTERPRISE_LINUX'|'SUSE'|'CENTOS'|'ORACLE_LINUX'|'DEBIAN', 'GlobalFilters': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ApprovalRules': { 'PatchRules': [ { 'PatchFilterGroup': { 'PatchFilters': [ { 'Key': 'PATCH_SET'|'PRODUCT'|'PRODUCT_FAMILY'|'CLASSIFICATION'|'MSRC_SEVERITY'|'PATCH_ID'|'SECTION'|'PRIORITY'|'SEVERITY', 'Values': [ 'string', ] }, ] }, 'ComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApproveAfterDays': 123, 'ApproveUntilDate': 'string', 'EnableNonSecurity': True|False }, ] }, 'ApprovedPatches': [ 'string', ], 'ApprovedPatchesComplianceLevel': 'CRITICAL'|'HIGH'|'MEDIUM'|'LOW'|'INFORMATIONAL'|'UNSPECIFIED', 'ApprovedPatchesEnableNonSecurity': True|False, 'RejectedPatches': [ 'string', ], 'RejectedPatchesAction': 'ALLOW_AS_DEPENDENCY'|'BLOCK', 'CreatedDate': datetime(2015, 1, 1), 'ModifiedDate': datetime(2015, 1, 1), 'Description': 'string', 'Sources': [ { 'Name': 'string', 'Products': [ 'string', ], 'Configuration': 'string' }, ] } :returns: (string) -- """ pass def update_resource_data_sync(SyncName=None, SyncType=None, SyncSource=None): """ Update a resource data sync. After you create a resource data sync for a Region, you can\'t change the account options for that sync. For example, if you create a sync in the us-east-2 (Ohio) Region and you choose the Include only the current account option, you can\'t edit that sync later and choose the Include all accounts from my AWS Organizations configuration option. Instead, you must delete the first resource data sync, and create a new one. See also: AWS API Documentation Exceptions :example: response = client.update_resource_data_sync( SyncName='string', SyncType='string', SyncSource={ 'SourceType': 'string', 'AwsOrganizationsSource': { 'OrganizationSourceType': 'string', 'OrganizationalUnits': [ { 'OrganizationalUnitId': 'string' }, ] }, 'SourceRegions': [ 'string', ], 'IncludeFutureRegions': True|False } ) :type SyncName: string :param SyncName: [REQUIRED]\nThe name of the resource data sync you want to update.\n :type SyncType: string :param SyncType: [REQUIRED]\nThe type of resource data sync. The supported SyncType is SyncFromSource.\n :type SyncSource: dict :param SyncSource: [REQUIRED]\nSpecify information about the data sources to synchronize.\n\nSourceType (string) -- [REQUIRED]The type of data source for the resource data sync. SourceType is either AwsOrganizations (if an organization is present in AWS Organizations) or singleAccountMultiRegions .\n\nAwsOrganizationsSource (dict) --Information about the AwsOrganizationsSource resource data sync source. A sync source of this type can synchronize data from AWS Organizations.\n\nOrganizationSourceType (string) -- [REQUIRED]If an AWS Organization is present, this is either OrganizationalUnits or EntireOrganization . For OrganizationalUnits , the data is aggregated from a set of organization units. For EntireOrganization , the data is aggregated from the entire AWS Organization.\n\nOrganizationalUnits (list) --The AWS Organizations organization units included in the sync.\n\n(dict) --The AWS Organizations organizational unit data source for the sync.\n\nOrganizationalUnitId (string) --The AWS Organization unit ID data source for the sync.\n\n\n\n\n\n\n\nSourceRegions (list) -- [REQUIRED]The SyncSource AWS Regions included in the resource data sync.\n\n(string) --\n\n\nIncludeFutureRegions (boolean) --Whether to automatically synchronize and aggregate data from new AWS Regions when those Regions come online.\n\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions SSM.Client.exceptions.ResourceDataSyncNotFoundException SSM.Client.exceptions.ResourceDataSyncInvalidConfigurationException SSM.Client.exceptions.ResourceDataSyncConflictException SSM.Client.exceptions.InternalServerError :return: {} :returns: (dict) -- """ pass def update_service_setting(SettingId=None, SettingValue=None): """ Services map a SettingId object to a setting value. AWS services teams define the default value for a SettingId . You can\'t create a new SettingId , but you can overwrite the default value if you have the ssm:UpdateServiceSetting permission for the setting. Use the GetServiceSetting API action to view the current value. Or, use the ResetServiceSetting to change the value back to the original value defined by the AWS service team. Update the service setting for the account. See also: AWS API Documentation Exceptions :example: response = client.update_service_setting( SettingId='string', SettingValue='string' ) :type SettingId: string :param SettingId: [REQUIRED]\nThe Amazon Resource Name (ARN) of the service setting to reset. For example, arn:aws:ssm:us-east-1:111122223333:servicesetting/ssm/parameter-store/high-throughput-enabled . The setting ID can be one of the following.\n\n/ssm/parameter-store/default-parameter-tier\n/ssm/parameter-store/high-throughput-enabled\n/ssm/managed-instance/activation-tier\n\n :type SettingValue: string :param SettingValue: [REQUIRED]\nThe new value to specify for the service setting. For the /ssm/parameter-store/default-parameter-tier setting ID, the setting value can be one of the following.\n\nStandard\nAdvanced\nIntelligent-Tiering\n\nFor the /ssm/parameter-store/high-throughput-enabled , and /ssm/managed-instance/activation-tier setting IDs, the setting value can be true or false.\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- The result body of the UpdateServiceSetting API action. Exceptions SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ServiceSettingNotFound SSM.Client.exceptions.TooManyUpdates :return: {} :returns: SSM.Client.exceptions.InternalServerError SSM.Client.exceptions.ServiceSettingNotFound SSM.Client.exceptions.TooManyUpdates """ pass

38.266461

6,246

0.678366

87,304

744,474

5.773596

0.02757

0.003337

0.023785

0.0025

0.865508

0.838719

0.820779

0.799348

0.786207

0.774097

0

0.009443

0.236249

744,474

19,454

6,247

38.268428

0.877058

0.975258

0

0.5

0

1

0.5

false

0.5

0

0.5

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

10

bdc9b9bef4ffc3e299cc20cc43ee68302c69f33c

937

py

Python

tests/unit_tests/test_fade.py

Robpol86/sphinx-carousel

df7cd8240fa61c7f27bbf1a6b37a522acd3f250f

[ "BSD-2-Clause" ]

1

2022-03-17T18:01:58.000Z

tests/unit_tests/test_fade.py

Robpol86/sphinx-carousel

df7cd8240fa61c7f27bbf1a6b37a522acd3f250f

[ "BSD-2-Clause" ]

54

2022-03-12T22:56:20.000Z

2022-03-31T17:44:43.000Z

tests/unit_tests/test_fade.py

Robpol86/sphinx-carousel

df7cd8240fa61c7f27bbf1a6b37a522acd3f250f

[ "BSD-2-Clause" ]

null

"""Tests.""" from typing import List import pytest from bs4 import element @pytest.mark.sphinx("html", testroot="fade/default") def test_default(carousels: List[element.Tag]): """Test.""" carousel = carousels[0] assert carousel["class"] == ["scbs-carousel", "scbs-slide", "scbs-carousel-fade"] carousel = carousels[1] assert carousel["class"] == ["scbs-carousel", "scbs-slide"] carousel = carousels[2] assert carousel["class"] == ["scbs-carousel", "scbs-slide"] @pytest.mark.sphinx("html", testroot="fade/sphinx-conf") def test_conf(carousels: List[element.Tag]): """Test.""" carousel = carousels[0] assert carousel["class"] == ["scbs-carousel", "scbs-slide", "scbs-carousel-fade"] carousel = carousels[1] assert carousel["class"] == ["scbs-carousel", "scbs-slide"] carousel = carousels[2] assert carousel["class"] == ["scbs-carousel", "scbs-slide", "scbs-carousel-fade"]

29.28125

85

0.65635

111

937

5.522523

0.243243

0.176183

0.185971

0.225122

0.838499

0.734095

0

0.008772

0.148346

937

31

86

30.225806

0.759399

0.01921

0

0.631579

0

0.285714

0

0.315789

1

0.105263

false

0

0.157895

0

0.263158

0

null

0

1

0

null

0

8

da6babac65c41200866236e1fe9874be5588f7ff

12,981

py

Python

test/test_numba_wrapper.py

Hasenpfote/fpq

3154ed1b1d5eca08255e8359b5027439af43691c

[ "MIT" ]

null

test/test_numba_wrapper.py

Hasenpfote/fpq

3154ed1b1d5eca08255e8359b5027439af43691c

[ "MIT" ]

1

2021-01-09T07:56:22.000Z

test/test_numba_wrapper.py

Hasenpfote/fpq

3154ed1b1d5eca08255e8359b5027439af43691c

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import types import unittest from unittest import TestCase import numpy as np import sys sys.path.append('../') from fpq import numba_wrapper def _identity_decorator(*args, **kwargs): if (len(args) == 1) and isinstance(args[0], types.FunctionType): return args[0] def wrapper(fn): return fn return wrapper class TestNumbaWrapperWithoutNumba(TestCase): '''Tests numba_wrapper without the numba.''' @classmethod def setUpClass(cls): cls._old = (numba_wrapper.IS_ENABLED_NUMBA, numba_wrapper.jit) numba_wrapper.IS_ENABLED_NUMBA = False numba_wrapper.jit = _identity_decorator @classmethod def tearDownClass(cls): numba_wrapper.IS_ENABLED_NUMBA = cls._old[0] numba_wrapper.jit = cls._old[1] def test_IS_ENABLED_NUMBA(self): self.assertFalse(numba_wrapper.IS_ENABLED_NUMBA) def test_jit(self): @numba_wrapper.jit def func(x): pass self.assertTrue(isinstance(func, types.FunctionType)) def test_avoid_non_supported_types(self): with self.assertRaises(Exception): try: @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(Exception): try: @numba_wrapper.avoid_non_supported_types() @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(TypeError): @numba_wrapper.avoid_non_supported_types(0) @numba_wrapper.jit def func(x): pass with self.assertRaises(ValueError): @numba_wrapper.avoid_non_supported_types('y') @numba_wrapper.jit def func(x): pass @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): return x self.assertTrue(isinstance(func, types.FunctionType)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float16) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float32) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float64) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) def test_avoid_mapping_to_py_types(self): with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types() @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(TypeError): @numba_wrapper.avoid_mapping_to_py_types(0) @numba_wrapper.jit def func(x): pass with self.assertRaises(ValueError): @numba_wrapper.avoid_mapping_to_py_types('y') @numba_wrapper.jit def func(x): pass @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.jit def func(x): return x self.assertTrue(isinstance(func, types.FunctionType)) dataset = np.float16(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float16)) dataset = np.float32(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float32)) dataset = np.float64(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float64)) def test_chain_of_decorators(self): with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types() @numba_wrapper.avoid_non_supported_types() @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(TypeError): @numba_wrapper.avoid_mapping_to_py_types(0) @numba_wrapper.avoid_non_supported_types(0) @numba_wrapper.jit def func(x): pass with self.assertRaises(ValueError): @numba_wrapper.avoid_mapping_to_py_types('y') @numba_wrapper.avoid_non_supported_types('y') @numba_wrapper.jit def func(x): pass @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): return x self.assertTrue(isinstance(func, types.FunctionType)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float16) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float32) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float64) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.float16(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float16)) dataset = np.float32(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float32)) dataset = np.float64(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float64)) @unittest.skipIf(not numba_wrapper.IS_ENABLED_NUMBA, 'Numba is not installed.') class TestNumbaWrapperWithNumba(TestCase): '''Tests numba_wrapper with the numba.''' def test_IS_ENABLED_NUMBA(self): self.assertTrue(numba_wrapper.IS_ENABLED_NUMBA) def test_jit(self): @numba_wrapper.jit def func(x): pass self.assertTrue(isinstance(func, numba_wrapper.CPUDispatcher)) def test_avoid_non_supported_types(self): with self.assertRaises(Exception): try: @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(Exception): try: @numba_wrapper.avoid_non_supported_types() @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(TypeError): @numba_wrapper.avoid_non_supported_types(0) @numba_wrapper.jit def func(x): pass with self.assertRaises(ValueError): @numba_wrapper.avoid_non_supported_types('y') @numba_wrapper.jit def func(x): pass with self.assertRaises(Exception): try: @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit(nopython=True) def func(x): return x func(np.float16(1)) except: pass else: raise Exception @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): return x self.assertTrue(isinstance(func, types.FunctionType)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float16) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float32) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float64) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) def test_avoid_mapping_to_py_types(self): with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types() @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(TypeError): @numba_wrapper.avoid_mapping_to_py_types(0) @numba_wrapper.jit def func(x): pass with self.assertRaises(ValueError): @numba_wrapper.avoid_mapping_to_py_types('y') @numba_wrapper.jit def func(x): pass @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.jit def func(x): return x self.assertTrue(isinstance(func, types.FunctionType)) dataset = np.float16(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float16)) dataset = np.float32(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float32)) dataset = np.float64(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float64)) def test_chain_of_decorators(self): with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(Exception): try: @numba_wrapper.avoid_mapping_to_py_types() @numba_wrapper.avoid_non_supported_types() @numba_wrapper.jit def func(x): pass except: pass else: raise Exception with self.assertRaises(TypeError): @numba_wrapper.avoid_mapping_to_py_types(0) @numba_wrapper.avoid_non_supported_types(0) @numba_wrapper.jit def func(x): pass with self.assertRaises(ValueError): @numba_wrapper.avoid_mapping_to_py_types('y') @numba_wrapper.avoid_non_supported_types('y') @numba_wrapper.jit def func(x): pass @numba_wrapper.avoid_mapping_to_py_types @numba_wrapper.avoid_non_supported_types @numba_wrapper.jit def func(x): return x self.assertTrue(isinstance(func, types.FunctionType)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float16) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float32) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.random.uniform(low=-1., high=1., size=10).astype(np.float64) actual = func(dataset) self.assertTrue(isinstance(actual, np.ndarray)) dataset = np.float16(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float16)) dataset = np.float32(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float32)) dataset = np.float64(1) actual = func(dataset) self.assertTrue(isinstance(actual, np.float64))

30.258741

81

0.563131

1,376

12,981

5.108285

0.069041

0.148528

0.099161

0.081946

0.908949

0.895433

0.884194

0.875943

0

0.017731

0.348278

12,981

428

82

30.329439

0.813121

0.00909

0

0.91954

0

0.002646

0

0.16954

1

0.135057

false

0.112069

0.017241

0.022989

0.186782

0

null

0

1

0

1

0

null

0

1

0

8

e56f161e89e50854a3c08a4cadd27916b5e2ff6b

167

py

Python

app/utils/url_maker.py

yogeshwaran01/Book-Store

7b4caa37b4132d8e969798eface3fd56c9721395

[ "MIT" ]

null

app/utils/url_maker.py

yogeshwaran01/Book-Store

7b4caa37b4132d8e969798eface3fd56c9721395

[ "MIT" ]

null

app/utils/url_maker.py

yogeshwaran01/Book-Store

7b4caa37b4132d8e969798eface3fd56c9721395

[ "MIT" ]

null

def make_url_from_title(string: str) -> str: return "-".join(string.split()) def make_title_from_url(string: str) -> str: return " ".join(string.split("-"))

23.857143

44

0.658683

24

167

4.333333

0.416667

0.134615

0.230769

0.346154

0.634615

0

0.149701

167

6

45

27.833333

0.732394

0

0.017964

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

7

e584a29e2ae2e668616f1b3da9de9c639fa418f6

13,992

py

Python

appengine/findit/services/flake_failure/test/flakiness_util_test.py

allaparthi/monorail

e18645fc1b952a5a6ff5f06e0c740d75f1904473

[ "BSD-3-Clause" ]

2

2021-04-13T21:22:18.000Z

2021-09-07T02:11:57.000Z

appengine/findit/services/flake_failure/test/flakiness_util_test.py

allaparthi/monorail

e18645fc1b952a5a6ff5f06e0c740d75f1904473

[ "BSD-3-Clause" ]

21

2020-09-06T02:41:05.000Z

2022-03-02T04:40:01.000Z

appengine/findit/services/flake_failure/test/flakiness_util_test.py

allaparthi/monorail

e18645fc1b952a5a6ff5f06e0c740d75f1904473

[ "BSD-3-Clause" ]

null

# Copyright 2018 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from datetime import datetime import mock from dto.flake_swarming_task_output import FlakeSwarmingTaskOutput from dto.flakiness import Flakiness from dto.swarming_task_error import SwarmingTaskError from libs.list_of_basestring import ListOfBasestring from services.flake_failure import flake_analysis_util from services.flake_failure import flake_constants from services.flake_failure import flakiness_util from waterfall.test import wf_testcase class FlakinessUtilTest(wf_testcase.WaterfallTestCase): def testGetMaximumIterationsToRun(self): self.assertEqual(flake_constants.DEFAULT_MAX_ITERATIONS_TO_RERUN, flakiness_util._GetMaximumIterationsToRun()) def testGetMaximumSwarmingTaskRetries(self): self.assertEqual( flake_constants.DEFAULT_MAX_SWARMING_TASK_RETRIES_PER_DATA_POINT, flakiness_util._GetMaximumSwarmingTaskRetries()) @mock.patch.object( flakiness_util, '_GetMaximumSwarmingTaskRetries', return_value=3) def testMaximumSwarmingTaskRetriesReached(self, _): flakiness = Flakiness(failed_swarming_task_attempts=4) self.assertTrue(flakiness_util.MaximumSwarmingTaskRetriesReached(flakiness)) @mock.patch.object( flakiness_util, '_GetMaximumIterationsToRun', return_value=100) def testMaximumIterationsReached(self, _): flakiness = Flakiness(iterations=150) self.assertTrue(flakiness_util.MaximumIterationsReached(flakiness)) def testUpdateFlakiness(self): flakiness = Flakiness( build_number=None, build_url='url', commit_position=1000, total_test_run_seconds=0, error=None, failed_swarming_task_attempts=0, iterations=0, pass_rate=None, revision='r1000', try_job_url=None, task_ids=ListOfBasestring.FromSerializable([])) self.assertEqual(flakiness, flakiness_util.UpdateFlakiness(flakiness, None)) @mock.patch.object( flake_analysis_util, 'CanFailedSwarmingTaskBeSalvaged', return_value=False) def testUpdateFlakinessWithErrorUnsalvagable(self, _): commit_position = 1000 completed_time = datetime(2018, 1, 1, 1, 0, 0) error = SwarmingTaskError(code=1, message='message') iterations = None pass_count = None revision = 'r1000' started_time = datetime(2018, 1, 1, 0, 0, 0) task_id = 'task_id' build_url = 'url' try_job_url = None swarming_task_output = FlakeSwarmingTaskOutput( completed_time=completed_time, error=error, iterations=iterations, pass_count=pass_count, started_time=started_time, task_id=task_id) flakiness_to_update = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=0, error=None, failed_swarming_task_attempts=0, iterations=0, pass_rate=None, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([])) expected_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=0, error=None, failed_swarming_task_attempts=1, iterations=0, pass_rate=None, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id])) resulting_flakiness = flakiness_util.UpdateFlakiness( flakiness_to_update, swarming_task_output) self.assertEqual(expected_flakiness, resulting_flakiness) def testUpdateFlakinessNewFlakinessWithErrorButSalvagable(self): commit_position = 1000 completed_time = datetime(2018, 1, 1, 0, 1, 0) error = SwarmingTaskError(code=1, message='message') iterations = 100 pass_count = 50 revision = 'r1000' started_time = datetime(2018, 1, 1, 0, 0, 0) task_id = 'task_id' build_url = None try_job_url = 'url' swarming_task_output = FlakeSwarmingTaskOutput( completed_time=completed_time, error=error, iterations=iterations, pass_count=pass_count, started_time=started_time, task_id=task_id) initial_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=None, error=None, failed_swarming_task_attempts=0, iterations=None, pass_rate=None, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([])) expected_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=60, error=None, failed_swarming_task_attempts=0, iterations=iterations, pass_rate=0.5, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id])) resulting_flakiness = flakiness_util.UpdateFlakiness( initial_flakiness, swarming_task_output) self.assertEqual(expected_flakiness, resulting_flakiness) def testUpdateFlakinessNewFlakinessNoError(self): commit_position = 1000 completed_time = datetime(2018, 1, 1, 0, 1, 0) error = None iterations = 100 pass_count = 50 revision = 'r1000' started_time = datetime(2018, 1, 1, 0, 0, 0) task_id = 'task_id' build_url = None try_job_url = 'url' swarming_task_output = FlakeSwarmingTaskOutput( completed_time=completed_time, error=error, iterations=iterations, pass_count=pass_count, started_time=started_time, task_id=task_id) initial_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=None, error=None, failed_swarming_task_attempts=0, iterations=None, pass_rate=None, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([])) expected_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=60, error=None, failed_swarming_task_attempts=0, iterations=iterations, pass_rate=0.5, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id])) resulting_flakiness = flakiness_util.UpdateFlakiness( initial_flakiness, swarming_task_output) self.assertEqual(expected_flakiness, resulting_flakiness) @mock.patch.object( flake_analysis_util, 'CanFailedSwarmingTaskBeSalvaged', return_value=False) def testUpdateExistingFlakinessWithErrorUnsalvagable(self, _): commit_position = 1000 revision = 'r1000' iterations = 100 pass_count = None completed_time = datetime(2018, 1, 1, 0, 1, 0) error = SwarmingTaskError(code=1, message='m') started_time = datetime(2018, 1, 1, 0, 0, 0) task_id_1 = 'task_1' task_id_2 = 'task_2' build_url = 'url' try_job_url = None swarming_task_output = FlakeSwarmingTaskOutput( completed_time=completed_time, error=error, iterations=iterations, pass_count=pass_count, started_time=started_time, task_id=task_id_2) initial_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=60, error=None, failed_swarming_task_attempts=0, iterations=None, pass_rate=0.5, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id_1])) expected_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=60, # No change due to unrecoverable error. error=None, # Only set error if no more retries. failed_swarming_task_attempts=1, iterations=None, # No change to iterations. pass_rate=0.5, # No change to pass rate. revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id_1, task_id_2])) resulting_flakiness = flakiness_util.UpdateFlakiness( initial_flakiness, swarming_task_output) self.assertEqual(expected_flakiness, resulting_flakiness) @mock.patch.object( flake_analysis_util, 'CanFailedSwarmingTaskBeSalvaged', return_value=True) def testUpdateExistingFlakinessWithErrorWithSuccessfulRun(self, _): commit_position = 1000 revision = 'r1000' iterations = 10 pass_count = 5 completed_time = datetime(2018, 1, 1, 0, 1, 0) started_time = datetime(2018, 1, 1, 0, 0, 0) task_id_1 = 'task_1' task_id_2 = 'task_2' build_url = 'url' try_job_url = None swarming_task_output = FlakeSwarmingTaskOutput( completed_time=completed_time, error=None, iterations=iterations, pass_count=pass_count, started_time=started_time, task_id=task_id_2) # Simulate first run failing. initial_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=60, error=None, failed_swarming_task_attempts=1, iterations=0, pass_rate=None, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id_1])) expected_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=120, # No change due to unrecoverable error. error=None, failed_swarming_task_attempts=1, iterations=10, pass_rate=0.5, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id_1, task_id_2])) resulting_flakiness = flakiness_util.UpdateFlakiness( initial_flakiness, swarming_task_output) self.assertEqual(expected_flakiness, resulting_flakiness) @mock.patch.object( flake_analysis_util, 'CanFailedSwarmingTaskBeSalvaged', return_value=True) def testUpdateAnalysisDataPointsExistingDataPointWithErrorSalvagable(self, _): commit_position = 1000 revision = 'r1000' iterations = 100 pass_count = 50 completed_time = datetime(2018, 1, 1, 0, 1, 0) error = SwarmingTaskError(code=1, message='m') started_time = datetime(2018, 1, 1, 0, 0, 0) task_id_1 = 'task_1' task_id_2 = 'task_2' build_url = 'url' try_job_url = None swarming_task_output = FlakeSwarmingTaskOutput( completed_time=completed_time, error=error, iterations=iterations, pass_count=pass_count, started_time=started_time, task_id=task_id_2) initial_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=60, error=None, failed_swarming_task_attempts=0, iterations=50, pass_rate=0.5, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id_1])) expected_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=120, error=None, # Only set error if no more retries. failed_swarming_task_attempts=0, # Task was salvaged. iterations=150, pass_rate=0.5, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable([task_id_1, task_id_2])) resulting_flakiness = flakiness_util.UpdateFlakiness( initial_flakiness, swarming_task_output) self.assertEqual(expected_flakiness, resulting_flakiness) def testUpdateAnalysisDataPointsExistingDataPointNoError(self): commit_position = 1000 revision = 'r1000' iterations = 100 pass_count = 60 failed_swarming_task_attempts = 2 completed_time = datetime(2018, 1, 1, 1, 0, 0) error = None started_time = datetime(2018, 1, 1, 0, 0, 0) task_id = 'task_2' build_url = None try_job_url = 'url' initial_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=1800, error=None, failed_swarming_task_attempts=failed_swarming_task_attempts, iterations=iterations, pass_rate=0.5, revision=revision, try_job_url=try_job_url, task_ids=ListOfBasestring.FromSerializable(['task_1'])) swarming_task_output = FlakeSwarmingTaskOutput( completed_time=completed_time, error=error, iterations=iterations, pass_count=pass_count, started_time=started_time, task_id=task_id) resulting_flakiness = flakiness_util.UpdateFlakiness( initial_flakiness, swarming_task_output) expected_flakiness = Flakiness( build_number=None, build_url=build_url, commit_position=commit_position, total_test_run_seconds=5400, error=None, failed_swarming_task_attempts=failed_swarming_task_attempts, iterations=200, pass_rate=0.55, revision=revision, task_ids=ListOfBasestring.FromSerializable(['task_1', 'task_2']), try_job_url=try_job_url) self.assertEqual(expected_flakiness, resulting_flakiness)

32.615385

80

0.697827

1,591

13,992

5.785041

0.095537

0.025424

0.035202

0.053672

0.813016

0.795198

0.77412

0.752825

0.735332

0.732073

0

0.031079

0.227344

13,992

428

81

32.691589

0.820276

0.028373

0

0.844086

0

0.025105

0.013252

0

0.032258

1

0.032258

false

0.077957

0.026882

0

0.061828

0

null

0

1

0

1

0

null

0

1

0

8

e5881e7d272ad99eac30d34796f1d7b3fea1af7e

5,975

py

Python

phanterpwa/components/left_bar.py

PhanterJR/phanterpwa

6daff40845b3a853cd08d319c4ce148f8deebed7

[ "MIT" ]

2

2019-06-06T10:37:01.000Z

2021-10-16T03:36:28.000Z

phanterpwa/components/left_bar.py

PhanterJR/phanterpwa

6daff40845b3a853cd08d319c4ce148f8deebed7

[ "MIT" ]

null

phanterpwa/components/left_bar.py

PhanterJR/phanterpwa

6daff40845b3a853cd08d319c4ce148f8deebed7

[ "MIT" ]

null

from ..helpers import DIV, I, IMG from ..xmlconstructor import XmlConstructor class LeftBarSubMenu(XmlConstructor): def __init__(self, _id, label, **attributes): self._id = _id self.label = label self.initial_class = "phanterpwa-component-left_bar-submenu-button link" attributes["_id"] = "phanterpwa-component-left_bar-submenu-button-%s" % _id if "_class" in attributes: self.initial_class = " ".join( [attributes['_class'].strip(), "phanterpwa-component-left_bar-submenu-button link"]) attributes['_class'] = self.initial_class content = [ DIV(I(_class="fas fa-angle-right"), _class="phanterpwa-component-left_bar-submenu-icon-container"), DIV(self.label, _class="phanterpwa-component-left_bar-submenu-label"), ] XmlConstructor.__init__(self, 'div', False, *content, **attributes) class LeftBarMenu(XmlConstructor): def __init__(self, _id, label, icon_class, **attributes): self._id = _id self.label = label self.icon_class = icon_class self.submenus = [] self.componentSubmenu = LeftBarSubMenu initial_class = "phanterpwa-component-left_bar" initial_id = "phanterpwa-component-left_bar-%s" % _id self.button_attributes = attributes if "_class" in self.button_attributes: self.button_attributes["_class"] = " ".join([ self.button_attributes['_class'].strip(), "phanterpwa-component-left_bar-menu link"]) else: self.button_attributes["_class"] = "phanterpwa-component-left_bar-menu link" XmlConstructor.__init__(self, 'div', False, _id=initial_id, _class=initial_class) self._update_content() def addSubmenu(self, _id, label, **attributes): self.submenus.append(self.componentSubmenu(_id=_id, label=label, **attributes)) self._update_content() def _update_content(self): html_submenus = "" attributes = self.button_attributes if self.submenus: attributes["_target_submenu"] = "phanterpwa-component-left_bar-submenu-from-%s" % self._id html_submenus = DIV( *self.submenus, _id=attributes["_target_submenu"], _class="phanterpwa-component-left_bar-submenu-container") self.content = [ DIV( DIV(I(_class=self.icon_class), _class="phanterpwa-component-left_bar-icon-container"), DIV(self.label, _class="phanterpwa-component-left_bar-label"), **attributes), html_submenus ] class LeftBarButton(XmlConstructor): def __init__(self, _id, label, icon_class, **attributes): self._id = _id self.label = label self.icon_class = icon_class self.submenus = [] initial_class = "phanterpwa-component-left_bar" initial_id = "phanterpwa-component-left_bar-%s" % _id self.button_attributes = attributes if "_class" in self.button_attributes: self.button_attributes["_class"] = " ".join([ self.button_attributes['_class'].strip(), "phanterpwa-component-left_bar-button link"]) else: self.button_attributes["_class"] = "phanterpwa-component-left_bar-button link" XmlConstructor.__init__(self, 'div', False, _id=initial_id, _class=initial_class) self.content = [ DIV( DIV(I(_class=self.icon_class), _class="phanterpwa-component-left_bar-icon-container"), DIV(self.label, _class="phanterpwa-component-left_bar-label"), **self.button_attributes) ] class LeftBarUserMenu(XmlConstructor): def __init__(self, _id, name_user="Nome usuário", url_image_user="/static/images/user.png", **attributes): self._id = _id self.name_user = name_user self.url_image_user = url_image_user self.submenus = [] self._image = IMG(_id="phanterpwa-component-left_bar-url-imagem-user", _src=url_image_user, _alt="user avatar") self.componentSubmenu = LeftBarSubMenu initial_class = "phanterpwa-component-left_bar" initial_id = "phanterpwa-component-left_bar-%s" % _id self.button_attributes = attributes if "_class" in self.button_attributes: self.button_attributes["_class"] = " ".join([ self.button_attributes['_class'].strip(), "phanterpwa-component-left_bar-button-user cmp-bar-user-img link"]) else: self.button_attributes["_class"] = "phanterpwa-component-left_bar-menu link" XmlConstructor.__init__(self, 'div', False, _id=initial_id, _class=initial_class) self._update_content() def addSubmenu(self, _id, label, **attributes): self.submenus.append(self.componentSubmenu(_id=_id, label=label, **attributes)) self._update_content() def _update_content(self): html_submenus = "" attributes = self.button_attributes if self.submenus: attributes["_target_submenu"] = "phanterpwa-component-left_bar-submenu-from-%s" % self._id html_submenus = DIV( *self.submenus, _id=attributes["_target_submenu"], _class="phanterpwa-component-left_bar-submenu-container") self.content = [ DIV( DIV( DIV(self._image, _class="phanterpwa-component-left_bar-image-user"), _class="phanterpwa-component-left_bar-image-user-container"), DIV(self.name_user, _id="phanterpwa-component-left_bar-name-user", _class="phanterpwa-component-left_bar-label"), **attributes), html_submenus ]

43.933824

111

0.61841

624

5,975

5.586538

0.099359

0.163511

0.197935

0.223752

0.860298

0.820998

0.780264

0.751578

0.710843

0.687894

0

0.265607

5,975

136

112

43.933824

0.794439

0

0.691057

0

0.245858

0.201172

0

1

0.065041

false

0

0.01626

0

0.113821

0

null

0

1

0

null

0

8

e5d40def419a0a0950b9751046c76e5a7da7810c

9,901

py

Python

tests/perf/test_perf.py

yaal-coop/sheraf

774e3781bc6ff2e16c6cc39f268d475b5e64fcea

[ "MIT" ]

null

tests/perf/test_perf.py

yaal-coop/sheraf

774e3781bc6ff2e16c6cc39f268d475b5e64fcea

[ "MIT" ]

null

tests/perf/test_perf.py

yaal-coop/sheraf

774e3781bc6ff2e16c6cc39f268d475b5e64fcea

[ "MIT" ]

null

import random import time import persistent import sheraf.types import transaction OBJECTS_NUMBERS = 10000 class Test_tel(persistent.Persistent): number = "" class Test_tel_3(persistent.Persistent): number = "" msisdn = "" msisdn2 = "" class Test_sheraf_tel(tests.UUIDAutoModel): number = sheraf.SimpleAttribute() class Test_sheraf_tel_in(sheraf.InlineModel): number = sheraf.SimpleAttribute() class Test_sheraf_tel_in_3(sheraf.InlineModel): number = sheraf.SimpleAttribute() msisdn = sheraf.SimpleAttribute() msisdn2 = sheraf.SimpleAttribute() class Test_sheraf_rep(tests.UUIDAutoModel): tels = sheraf.LargeDictAttribute(sheraf.InlineModelAttribute(Test_sheraf_tel_in)) class Test_sheraf_rep_3(tests.UUIDAutoModel): tels = sheraf.LargeDictAttribute(sheraf.InlineModelAttribute(Test_sheraf_tel_in_3)) # cela pourrait être un chargement de contact dans rich-sms class PerfSherafCaseHugeWrite: def sheraf_perf(self, sheraf_database): start_time = time.time() with sheraf.connection(): for i in range(0, OBJECTS_NUMBERS): tel_obj = Test_sheraf_tel.create() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel transaction.commit() print("--- Ecriture sheraf en %s secondes ---" % (time.time() - start_time)) def sheraf_perf_as_inline(self, sheraf_database): start_time = time.time() with sheraf.connection(): rep = Test_sheraf_rep.create() for i in range(0, OBJECTS_NUMBERS): tel_obj = Test_sheraf_tel_in.create() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel rep.tels[i] = tel_obj transaction.commit() print( "--- Ecriture sheraf inline en %s secondes ---" % (time.time() - start_time) ) def zodb_perfmapping_mapping(self, sheraf_database): start_time = time.time() with sheraf.connection() as c: c.root()["parents"] = sheraf.types.LargeDict() for i in range(0, OBJECTS_NUMBERS): tel_obj = persistent.mapping.PersistentMapping() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel c.root()["parents"][i] = tel_obj transaction.commit() print( "--- Ecriture zodb persistent mapping en %s secondes ---" % (time.time() - start_time) ) def zodb_perfmapping(self, sheraf_database): start_time = time.time() with sheraf.connection() as c: c.root()["parents"] = sheraf.types.LargeDict() for i in range(0, OBJECTS_NUMBERS): tel_obj = Test_tel() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel c.root()["parents"][i] = tel_obj transaction.commit() print( "--- Ecriture zodb persistent object en %s secondes ---" % (time.time() - start_time) ) def zodb_perfmapping_with_one(self, sheraf_database): for num_object in [1, 2, 10, 100, 1000, 10000, 100000]: start_time = time.time() with sheraf.connection() as c: c.root()["parents"] = sheraf.types.LargeDict() for i in range(0, num_object): tel_obj = Test_tel() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel c.root()["parents"][i] = tel_obj transaction.commit() print( "--- Ecriture zodb persistent object en %s secondes pour %s objects---" % (time.time() - start_time, num_object) ) def zodb_perfmapping_mapping_read_time(self, sheraf_database): start_time = time.time() with sheraf.connection() as c: c.root()["parents"] = sheraf.types.LargeDict() for i in range(0, OBJECTS_NUMBERS): tel_obj = persistent.mapping.PersistentMapping() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel tel_obj.msisdn = tel + str(i) tel_obj.msisdn2 = tel + str(i * 2) c.root()["parents"][i] = tel_obj transaction.commit() print( "--- Ecriture zodb persistent mapping en %s secondes ---" % (time.time() - start_time) ) data = [] start_time = time.time() with sheraf.connection() as c: for i in range(0, OBJECTS_NUMBERS): tel_obj = c.root()["parents"][i] data.append(tel_obj.number) print( "--- Lecture zodb persistent mapping 1 attr en %s secondes ---" % (time.time() - start_time) ) data = [] start_time = time.time() with sheraf.connection() as c: for i in range(0, OBJECTS_NUMBERS): tel_obj = c.root()["parents"][i] data.append(tel_obj.number) data.append(tel_obj.msisdn) data.append(tel_obj.msisdn2) print( "--- Lecture zodb persistent mapping 3 attr en %s secondes ---" % (time.time() - start_time) ) def zodb_perfmapping_read_time(self, sheraf_database): start_time = time.time() with sheraf.connection() as c: c.root()["parents"] = sheraf.types.LargeDict() for i in range(0, OBJECTS_NUMBERS): tel_obj = Test_tel_3() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel tel_obj.msisdn = tel + str(i) tel_obj.msisdn2 = tel + str(i * 2) c.root()["parents"][i] = tel_obj transaction.commit() print( "--- Ecriture zodb persistent en %s secondes ---" % (time.time() - start_time) ) data = [] start_time = time.time() with sheraf.connection() as c: for i in range(0, OBJECTS_NUMBERS): tel_obj = c.root()["parents"][i] data.append(tel_obj.number) print( "--- Lecture zodb persistent 1 attr en %s secondes ---" % (time.time() - start_time) ) data = [] start_time = time.time() with sheraf.connection() as c: for i in range(0, OBJECTS_NUMBERS): tel_obj = c.root()["parents"][i] data.append(tel_obj.number) data.append(tel_obj.msisdn) data.append(tel_obj.msisdn2) print( "--- Lecture zodb persistent 3 attr en %s secondes ---" % (time.time() - start_time) ) def sheraf_perf_inlinemode_read_time(self, sheraf_database): start_time = time.time() with sheraf.connection(): rep = Test_sheraf_rep_3.create() for i in range(0, OBJECTS_NUMBERS): tel_obj = Test_sheraf_tel_in_3.create() tel = "33" for _ in range(9): tel = tel + str(random.randint(0, 9)) tel = tel + ";\n" tel_obj.number = tel tel_obj.msisdn = tel + str(i) tel_obj.msisdn2 = tel + str(i * 2) rep.tels[i] = tel_obj transaction.commit() print( "--- Ecriture sheraf inline en %s secondes ---" % (time.time() - start_time) ) data = [] sheraf.models.count = 0 start_time = time.time() with sheraf.connection(): rep = next(Test_sheraf_rep_3.all()) for index, tel_obj in rep.tels: # data.append(tel_obj.number) data.append(tel_obj.mapping["number"]) print( "--- Lecture sheraf inline 1 attr en %s secondes ---" % (time.time() - start_time) ) data = [] sheraf.models.count = 0 start_time = time.time() with sheraf.connection(): rep = next(Test_sheraf_rep_3.all()) for index, tel_obj in rep.tels: data.append(tel_obj.number) print( "--- Lecture sheraf bypass inline 1 attr en %s secondes ---" % (time.time() - start_time) ) data = [] sheraf.models.count = 0 start_time = time.time() with sheraf.connection(): rep = next(Test_sheraf_rep_3.all()) for index, tel_obj in rep.tels: data.append(tel_obj.mapping["number"]) data.append(tel_obj.mapping["msisdn"]) data.append(tel_obj.mapping["msisdn2"]) # data.append(tel_obj.number) # data.append(tel_obj.msisdn) # data.append(tel_obj.msisdn2) print("Temps cummulé création instances %s " % (sheraf.models.count)) print( "--- Lecture sheraf inline 3 attr en %s secondes ---" % (time.time() - start_time) )

36.003636

88

0.515301

1,101

9,901

4.465032

0.088102

0.064687

0.044955

0.05533

0.871847

0.835435

0.825468

0.823027

0.803906

0.793938

0

0.017769

0.369054

9,901

274

89

36.135037

0.769169

0.01717

0

0.73029

0

0.102622

0

1

0.033195

false

0.004149

0.020747

0

0.13278

0.06639

0

null

0

1

0

1

0

null

0

7

0057a8e4199ce8d65af5776ff061c960f26a89f4

4,888

py

Python

stag.py

yuanqing-wang/stag

ba887352d2649c4d78bad75a1d3a9fbb6ee873a3

[ "MIT" ]

5

2021-02-26T10:08:42.000Z

2021-04-24T05:01:11.000Z

stag.py

yuanqing-wang/stag

ba887352d2649c4d78bad75a1d3a9fbb6ee873a3

[ "MIT" ]

1

2021-04-23T18:22:04.000Z

2021-05-15T17:47:56.000Z

stag.py

yuanqing-wang/stag

ba887352d2649c4d78bad75a1d3a9fbb6ee873a3

[ "MIT" ]

1

2021-04-24T05:01:28.000Z

import torch from dataset import Dataset def stag_copy_src_vi(src="h", out="m"): def message_fun(edges): if "a" in edges.data: return {out: edges.src[src] * edges.data["a"]} return {out: edges.src[src]} return message_fun def stag_copy_src_normal(src='h', out='m', alpha=0.1): def message_fun(edges): h = edges.src[src] mask = torch.distributions.normal.Normal( loc=torch.tensor(1.0, device=h.device), scale=torch.tensor(alpha, device=h.device), ).sample(h.shape) return {out: (mask * h)} return message_fun def stag_sum_dropout(msg='m', out='h', alpha=0.1): def reduce_func(nodes): m = nodes.mailbox[msg] if nodes._ntype == "_N": mask = torch.distributions.Bernoulli( torch.tensor(1.0-alpha, device=m.device), ).sample((1, 1, m.shape[-1])) return {out: (mask * m).sum(dim=1)} else: return {out: m.sum(dim=1)} return reduce_func def stag_sum_bernoulli_shared(msg='m', out='h', alpha=0.1): def reduce_func(nodes): m = nodes.mailbox[msg] if nodes._ntype == "_N": mask = torch.distributions.Bernoulli( torch.tensor(1.0-alpha, device=m.device), ).sample((m.shape[0], m.shape[1], 1)) mask = torch.where( torch.gt(mask, 0.0), mask / mask.sum(dim=1, keepdims=True) * mask.shape[1], mask ) return {out: (mask * m).sum(dim=1)} else: return {out: m.sum(dim=1)} return reduce_func def stag_sum_bernoulli(msg='m', out='h', alpha=0.1): def reduce_func(nodes): m = nodes.mailbox[msg] if nodes._ntype == "_N": mask = torch.distributions.Bernoulli( torch.tensor(1.0-alpha, device=m.device), ).sample(m.shape) mask = torch.where( torch.gt(mask, 0.0), mask / mask.sum(dim=1, keepdims=True) * mask.shape[1], mask ) return {out: (mask * m).sum(dim=1)} else: return {out: m.sum(dim=1)} return reduce_func def stag_sum_normal(msg='m', out='h', alpha=0.1): def reduce_func(nodes): m = nodes.mailbox[msg] mask = torch.distributions.normal.Normal( loc=torch.tensor(1.0, device=m.device), scale=torch.tensor(alpha, device=m.device), ).sample(m.shape) mask = torch.where( torch.gt(mask, 0.0), mask / mask.sum(dim=1, keepdims=True), mask ) return {out: (mask * m).sum(dim=1)} return reduce_func def stag_copy_src_uniform(src='h', out='m', alpha=0.1): if isinstance(alpha, float): def message_fun(edges): h = edges.src[src] mask = torch.distributions.uniform.Uniform( low=torch.tensor(1.0-alpha, device=h.device), high=torch.tensor(1.0+alpha, device=h.device), ).sample(h.shape) return {out: (mask * h)} return message_fun def stag_copy_src_bernoulli(src='h', out='m', alpha=0.1): if isinstance(alpha, float): def message_fun(edges): h = edges.src[src] mask = torch.distributions.bernoulli.Bernoulli( probs=torch.tensor(1.0-alpha, device=h.device), ).sample(h.shape) return {out: (mask * h)} return message_fun def stag_copy_src_normal_shared(src='h', out='m', alpha=0.1): def message_fun(edges): h = edges.src[src] if "mask" not in edges.data: mask = torch.distributions.normal.Normal( loc=torch.tensor(1.0, device=h.device), scale=torch.tensor(alpha, device=h.device), ).sample(h.shape) edges.data["mask"] = mask return {out: (edges.data["mask"] * h)} return message_fun def stag_copy_src_uniform_shared(src='h', out='m', alpha=0.1): def message_fun(edges): h = edges.src[src] if "mask" not in edges.data: mask = torch.distributions.uniform.Uniform( high=torch.tensor(1.0+alpha, device=h.device), low=torch.tensor(1.0-alpha, device=h.device), ).sample(h.shape) edges.data["mask"] = mask return {out: (edges.data["mask"] * h)} return message_fun def stag_copy_src_bernoulli_shared(src='h', out='m', alpha=0.1): def message_fun(edges): h = edges.src[src] if "mask" not in edges.data: mask = torch.distributions.bernoulli.Bernoulli( torch.tensor(1.0-alpha, device=h.device), ).sample(h.shape) edges.data["mask"] = mask return {out: (edges.data["mask"] * h)} return message_fun

32.370861

70

0.548077

660

4,888

3.966667

0.084848

0.051566

0.055004

0.059587

0.94385

0.899542

0.891138

0.887701

0.866692

0.825821

0

0.020018

0.305033

4,888

150

71

32.586667

0.750662

0

0.792

0

0.013502

0

1

0.176

false

0

0.016

0

0.4

0

null

0

1

0

1

0

null

0

7

978177120c3a151e9b77b2c450d0a9492c35d15c

90,856

py

Python

tests/fixtures/filters_3_0.py

Jack-Sun-007/pymsfilereader

e59fee9c2403768e187c62fed0d85b9a5dc8c74e

[ "MIT" ]

29

2019-07-27T09:01:09.000Z

2022-03-31T11:26:27.000Z

tests/fixtures/filters_3_0.py

Jack-Sun-007/pymsfilereader

e59fee9c2403768e187c62fed0d85b9a5dc8c74e

[ "MIT" ]

5

2019-07-19T15:35:41.000Z

2020-05-01T15:22:23.000Z

tests/fixtures/filters_3_0.py

Jack-Sun-007/pymsfilereader

e59fee9c2403768e187c62fed0d85b9a5dc8c74e

[ "MIT" ]

11

2017-03-14T02:03:17.000Z

2019-07-09T20:20:17.000Z

filters = \ ('+ c ESI Full ms [300.00-2000.00]', '+ c ESI Full ms [400.00-2000.00]', '+ c d Full ms2 400.31@cid45.00 [100.00-815.00]', '+ c d Full ms2 401.39@cid45.00 [100.00-815.00]', '+ c d Full ms2 406.73@cid45.00 [100.00-825.00]', '+ c d Full ms2 408.00@cid45.00 [100.00-830.00]', '+ c d Full ms2 412.90@cid45.00 [100.00-840.00]', '+ c d Full ms2 415.06@cid45.00 [100.00-845.00]', '+ c d Full ms2 416.05@cid45.00 [100.00-845.00]', '+ c d Full ms2 418.81@cid45.00 [105.00-850.00]', '+ c d Full ms2 420.63@cid45.00 [105.00-855.00]', '+ c d Full ms2 421.87@cid45.00 [105.00-855.00]', '+ c d Full ms2 426.02@cid45.00 [105.00-865.00]', '+ c d Full ms2 428.43@cid45.00 [105.00-870.00]', '+ c d Full ms2 431.93@cid45.00 [105.00-875.00]', '+ c d Full ms2 433.34@cid45.00 [105.00-880.00]', '+ c d Full ms2 435.86@cid45.00 [110.00-885.00]', '+ c d Full ms2 437.65@cid45.00 [110.00-890.00]', '+ c d Full ms2 440.08@cid45.00 [110.00-895.00]', '+ c d Full ms2 440.47@cid45.00 [110.00-895.00]', '+ c d Full ms2 441.47@cid45.00 [110.00-895.00]', '+ c d Full ms2 444.32@cid45.00 [110.00-900.00]', '+ c d Full ms2 450.22@cid45.00 [110.00-915.00]', '+ c d Full ms2 450.53@cid45.00 [110.00-915.00]', '+ c d Full ms2 451.01@cid45.00 [110.00-915.00]', '+ c d Full ms2 451.75@cid45.00 [110.00-915.00]', '+ c d Full ms2 454.12@cid45.00 [115.00-920.00]', '+ c d Full ms2 457.86@cid45.00 [115.00-930.00]', '+ c d Full ms2 458.18@cid45.00 [115.00-930.00]', '+ c d Full ms2 461.43@cid45.00 [115.00-935.00]', '+ c d Full ms2 462.49@cid45.00 [115.00-935.00]', '+ c d Full ms2 462.50@cid45.00 [115.00-940.00]', '+ c d Full ms2 470.47@cid45.00 [115.00-955.00]', '+ c d Full ms2 475.87@cid45.00 [120.00-965.00]', '+ c d Full ms2 476.27@cid45.00 [120.00-965.00]', '+ c d Full ms2 479.45@cid45.00 [120.00-970.00]', '+ c d Full ms2 480.12@cid45.00 [120.00-975.00]', '+ c d Full ms2 484.53@cid45.00 [120.00-980.00]', '+ c d Full ms2 485.31@cid45.00 [120.00-985.00]', '+ c d Full ms2 491.11@cid45.00 [125.00-995.00]', '+ c d Full ms2 493.40@cid45.00 [125.00-1000.00]', '+ c d Full ms2 493.92@cid45.00 [125.00-1000.00]', '+ c d Full ms2 495.99@cid45.00 [125.00-1005.00]', '+ c d Full ms2 502.39@cid45.00 [125.00-1015.00]', '+ c d Full ms2 504.00@cid45.00 [125.00-1020.00]', '+ c d Full ms2 506.28@cid45.00 [125.00-1025.00]', '+ c d Full ms2 507.01@cid45.00 [125.00-1025.00]', '+ c d Full ms2 510.83@cid45.00 [130.00-1035.00]', '+ c d Full ms2 515.37@cid45.00 [130.00-1045.00]', '+ c d Full ms2 523.83@cid45.00 [130.00-1060.00]', '+ c d Full ms2 529.27@cid45.00 [135.00-1070.00]', '+ c d Full ms2 530.70@cid45.00 [135.00-1075.00]', '+ c d Full ms2 533.63@cid45.00 [135.00-1080.00]', '+ c d Full ms2 537.62@cid45.00 [135.00-1090.00]', '+ c d Full ms2 540.32@cid45.00 [135.00-1095.00]', '+ c d Full ms2 541.33@cid45.00 [135.00-1095.00]', '+ c d Full ms2 545.32@cid45.00 [140.00-1105.00]', '+ c d Full ms2 546.18@cid45.00 [140.00-1105.00]', '+ c d Full ms2 549.30@cid45.00 [140.00-1110.00]', '+ c d Full ms2 559.23@cid45.00 [140.00-1130.00]', '+ c d Full ms2 562.08@cid45.00 [140.00-1135.00]', '+ c d Full ms2 571.30@cid45.00 [145.00-1155.00]', '+ c d Full ms2 572.33@cid45.00 [145.00-1155.00]', '+ c d Full ms2 573.88@cid45.00 [145.00-1160.00]', '+ c d Full ms2 574.31@cid45.00 [145.00-1160.00]', '+ c d Full ms2 575.33@cid45.00 [145.00-1165.00]', '+ c d Full ms2 584.27@cid45.00 [150.00-1180.00]', '+ c d Full ms2 591.99@cid45.00 [150.00-1195.00]', '+ c d Full ms2 594.20@cid45.00 [150.00-1200.00]', '+ c d Full ms2 594.90@cid45.00 [150.00-1200.00]', '+ c d Full ms2 595.76@cid45.00 [150.00-1205.00]', '+ c d Full ms2 596.55@cid45.00 [150.00-1205.00]', '+ c d Full ms2 599.35@cid45.00 [155.00-1210.00]', '+ c d Full ms2 600.32@cid45.00 [155.00-1215.00]', '+ c d Full ms2 601.42@cid45.00 [155.00-1215.00]', '+ c d Full ms2 602.31@cid45.00 [155.00-1215.00]', '+ c d Full ms2 602.59@cid45.00 [155.00-1220.00]', '+ c d Full ms2 606.32@cid45.00 [155.00-1225.00]', '+ c d Full ms2 607.35@cid45.00 [155.00-1225.00]', '+ c d Full ms2 612.36@cid45.00 [155.00-1235.00]', '+ c d Full ms2 614.33@cid45.00 [155.00-1240.00]', '+ c d Full ms2 616.40@cid45.00 [155.00-1245.00]', '+ c d Full ms2 620.38@cid45.00 [160.00-1255.00]', '+ c d Full ms2 624.71@cid45.00 [160.00-1260.00]', '+ c d Full ms2 629.41@cid45.00 [160.00-1270.00]', '+ c d Full ms2 631.37@cid45.00 [160.00-1275.00]', '+ c d Full ms2 631.93@cid45.00 [160.00-1275.00]', '+ c d Full ms2 633.62@cid45.00 [160.00-1280.00]', '+ c d Full ms2 634.07@cid45.00 [160.00-1280.00]', '+ c d Full ms2 637.77@cid45.00 [165.00-1290.00]', '+ c d Full ms2 639.72@cid45.00 [165.00-1290.00]', '+ c d Full ms2 640.57@cid45.00 [165.00-1295.00]', '+ c d Full ms2 641.38@cid45.00 [165.00-1295.00]', '+ c d Full ms2 642.12@cid45.00 [165.00-1295.00]', '+ c d Full ms2 643.33@cid45.00 [165.00-1300.00]', '+ c d Full ms2 646.37@cid45.00 [165.00-1305.00]', '+ c d Full ms2 648.41@cid45.00 [165.00-1310.00]', '+ c d Full ms2 653.16@cid45.00 [165.00-1320.00]', '+ c d Full ms2 654.91@cid45.00 [170.00-1320.00]', '+ c d Full ms2 655.08@cid45.00 [170.00-1325.00]', '+ c d Full ms2 656.14@cid45.00 [170.00-1325.00]', '+ c d Full ms2 658.62@cid45.00 [170.00-1330.00]', '+ c d Full ms2 662.25@cid45.00 [170.00-1335.00]', '+ c d Full ms2 663.40@cid45.00 [170.00-1340.00]', '+ c d Full ms2 664.30@cid45.00 [170.00-1340.00]', '+ c d Full ms2 665.58@cid45.00 [170.00-1345.00]', '+ c d Full ms2 667.35@cid45.00 [170.00-1345.00]', '+ c d Full ms2 668.58@cid45.00 [170.00-1350.00]', '+ c d Full ms2 669.35@cid45.00 [170.00-1350.00]', '+ c d Full ms2 671.52@cid45.00 [170.00-1355.00]', '+ c d Full ms2 672.38@cid45.00 [175.00-1355.00]', '+ c d Full ms2 675.21@cid45.00 [175.00-1365.00]', '+ c d Full ms2 676.56@cid45.00 [175.00-1365.00]', '+ c d Full ms2 677.96@cid45.00 [175.00-1370.00]', '+ c d Full ms2 679.26@cid45.00 [175.00-1370.00]', '+ c d Full ms2 679.59@cid45.00 [175.00-1370.00]', '+ c d Full ms2 680.83@cid45.00 [175.00-1375.00]', '+ c d Full ms2 683.84@cid45.00 [175.00-1380.00]', '+ c d Full ms2 684.27@cid45.00 [175.00-1380.00]', '+ c d Full ms2 686.29@cid45.00 [175.00-1385.00]', '+ c d Full ms2 687.40@cid45.00 [175.00-1385.00]', '+ c d Full ms2 688.24@cid45.00 [175.00-1390.00]', '+ c d Full ms2 689.38@cid45.00 [175.00-1390.00]', '+ c d Full ms2 691.77@cid45.00 [180.00-1395.00]', '+ c d Full ms2 693.42@cid45.00 [180.00-1400.00]', '+ c d Full ms2 695.41@cid45.00 [180.00-1405.00]', '+ c d Full ms2 698.33@cid45.00 [180.00-1410.00]', '+ c d Full ms2 698.88@cid45.00 [180.00-1410.00]', '+ c d Full ms2 700.37@cid45.00 [180.00-1415.00]', '+ c d Full ms2 703.33@cid45.00 [180.00-1420.00]', '+ c d Full ms2 706.10@cid45.00 [180.00-1425.00]', '+ c d Full ms2 708.37@cid45.00 [185.00-1430.00]', '+ c d Full ms2 712.24@cid45.00 [185.00-1435.00]', '+ c d Full ms2 714.45@cid45.00 [185.00-1440.00]', '+ c d Full ms2 715.38@cid45.00 [185.00-1445.00]', '+ c d Full ms2 719.12@cid45.00 [185.00-1450.00]', '+ c d Full ms2 723.37@cid45.00 [185.00-1460.00]', '+ c d Full ms2 723.88@cid45.00 [185.00-1460.00]', '+ c d Full ms2 728.21@cid45.00 [190.00-1470.00]', '+ c d Full ms2 729.27@cid45.00 [190.00-1470.00]', '+ c d Full ms2 730.41@cid45.00 [190.00-1475.00]', '+ c d Full ms2 731.88@cid45.00 [190.00-1475.00]', '+ c d Full ms2 733.56@cid45.00 [190.00-1480.00]', '+ c d Full ms2 739.66@cid45.00 [190.00-1490.00]', '+ c d Full ms2 740.16@cid45.00 [190.00-1495.00]', '+ c d Full ms2 741.56@cid45.00 [190.00-1495.00]', '+ c d Full ms2 742.30@cid45.00 [190.00-1495.00]', '+ c d Full ms2 743.35@cid45.00 [190.00-1500.00]', '+ c d Full ms2 744.46@cid45.00 [190.00-1500.00]', '+ c d Full ms2 745.45@cid45.00 [195.00-1505.00]', '+ c d Full ms2 745.97@cid45.00 [195.00-1505.00]', '+ c d Full ms2 750.03@cid45.00 [195.00-1515.00]', '+ c d Full ms2 751.19@cid45.00 [195.00-1515.00]', '+ c d Full ms2 751.42@cid45.00 [195.00-1515.00]', '+ c d Full ms2 752.37@cid45.00 [195.00-1515.00]', '+ c d Full ms2 753.04@cid45.00 [195.00-1520.00]', '+ c d Full ms2 754.38@cid45.00 [195.00-1520.00]', '+ c d Full ms2 756.35@cid45.00 [195.00-1525.00]', '+ c d Full ms2 757.39@cid45.00 [195.00-1525.00]', '+ c d Full ms2 758.35@cid45.00 [195.00-1530.00]', '+ c d Full ms2 759.11@cid45.00 [195.00-1530.00]', '+ c d Full ms2 760.68@cid45.00 [195.00-1535.00]', '+ c d Full ms2 761.47@cid45.00 [195.00-1535.00]', '+ c d Full ms2 762.38@cid45.00 [195.00-1535.00]', '+ c d Full ms2 763.41@cid45.00 [200.00-1540.00]', '+ c d Full ms2 766.53@cid45.00 [200.00-1545.00]', '+ c d Full ms2 767.03@cid45.00 [200.00-1545.00]', '+ c d Full ms2 768.43@cid45.00 [200.00-1550.00]', '+ c d Full ms2 768.72@cid45.00 [200.00-1550.00]', '+ c d Full ms2 769.48@cid45.00 [200.00-1550.00]', '+ c d Full ms2 772.29@cid45.00 [200.00-1555.00]', '+ c d Full ms2 772.55@cid45.00 [200.00-1560.00]', '+ c d Full ms2 773.18@cid45.00 [200.00-1560.00]', '+ c d Full ms2 773.59@cid45.00 [200.00-1560.00]', '+ c d Full ms2 774.44@cid45.00 [200.00-1560.00]', '+ c d Full ms2 776.39@cid45.00 [200.00-1565.00]', '+ c d Full ms2 777.24@cid45.00 [200.00-1565.00]', '+ c d Full ms2 778.38@cid45.00 [200.00-1570.00]', '+ c d Full ms2 779.02@cid45.00 [200.00-1570.00]', '+ c d Full ms2 779.42@cid45.00 [200.00-1570.00]', '+ c d Full ms2 781.25@cid45.00 [205.00-1575.00]', '+ c d Full ms2 783.46@cid45.00 [205.00-1580.00]', '+ c d Full ms2 785.09@cid45.00 [205.00-1585.00]', '+ c d Full ms2 786.41@cid45.00 [205.00-1585.00]', '+ c d Full ms2 787.37@cid45.00 [205.00-1585.00]', '+ c d Full ms2 787.86@cid45.00 [205.00-1590.00]', '+ c d Full ms2 790.32@cid45.00 [205.00-1595.00]', '+ c d Full ms2 790.99@cid45.00 [205.00-1595.00]', '+ c d Full ms2 792.30@cid45.00 [205.00-1595.00]', '+ c d Full ms2 793.57@cid45.00 [205.00-1600.00]', '+ c d Full ms2 794.82@cid45.00 [205.00-1600.00]', '+ c d Full ms2 795.31@cid45.00 [205.00-1605.00]', '+ c d Full ms2 796.38@cid45.00 [205.00-1605.00]', '+ c d Full ms2 796.98@cid45.00 [205.00-1605.00]', '+ c d Full ms2 798.67@cid45.00 [205.00-1610.00]', '+ c d Full ms2 799.09@cid45.00 [210.00-1610.00]', '+ c d Full ms2 801.33@cid45.00 [210.00-1615.00]', '+ c d Full ms2 802.25@cid45.00 [210.00-1615.00]', '+ c d Full ms2 802.99@cid45.00 [210.00-1620.00]', '+ c d Full ms2 803.39@cid45.00 [210.00-1620.00]', '+ c d Full ms2 804.66@cid45.00 [210.00-1620.00]', '+ c d Full ms2 805.35@cid45.00 [210.00-1625.00]', '+ c d Full ms2 806.24@cid45.00 [210.00-1625.00]', '+ c d Full ms2 807.41@cid45.00 [210.00-1625.00]', '+ c d Full ms2 807.80@cid45.00 [210.00-1630.00]', '+ c d Full ms2 808.42@cid45.00 [210.00-1630.00]', '+ c d Full ms2 809.38@cid45.00 [210.00-1630.00]', '+ c d Full ms2 809.59@cid45.00 [210.00-1630.00]', '+ c d Full ms2 810.39@cid45.00 [210.00-1635.00]', '+ c d Full ms2 811.34@cid45.00 [210.00-1635.00]', '+ c d Full ms2 811.61@cid45.00 [210.00-1635.00]', '+ c d Full ms2 812.20@cid45.00 [210.00-1635.00]', '+ c d Full ms2 812.49@cid45.00 [210.00-1635.00]', '+ c d Full ms2 814.31@cid45.00 [210.00-1640.00]', '+ c d Full ms2 815.32@cid45.00 [210.00-1645.00]', '+ c d Full ms2 815.92@cid45.00 [210.00-1645.00]', '+ c d Full ms2 816.26@cid45.00 [210.00-1645.00]', '+ c d Full ms2 816.51@cid45.00 [210.00-1645.00]', '+ c d Full ms2 817.43@cid45.00 [215.00-1645.00]', '+ c d Full ms2 817.78@cid45.00 [215.00-1650.00]', '+ c d Full ms2 818.41@cid45.00 [215.00-1650.00]', '+ c d Full ms2 819.38@cid45.00 [215.00-1650.00]', '+ c d Full ms2 822.30@cid45.00 [215.00-1655.00]', '+ c d Full ms2 822.57@cid45.00 [215.00-1660.00]', '+ c d Full ms2 823.22@cid45.00 [215.00-1660.00]', '+ c d Full ms2 823.85@cid45.00 [215.00-1660.00]', '+ c d Full ms2 824.44@cid45.00 [215.00-1660.00]', '+ c d Full ms2 824.96@cid45.00 [215.00-1660.00]', '+ c d Full ms2 826.38@cid45.00 [215.00-1665.00]', '+ c d Full ms2 827.31@cid45.00 [215.00-1665.00]', '+ c d Full ms2 828.41@cid45.00 [215.00-1670.00]', '+ c d Full ms2 829.41@cid45.00 [215.00-1670.00]', '+ c d Full ms2 829.83@cid45.00 [215.00-1670.00]', '+ c d Full ms2 830.10@cid45.00 [215.00-1675.00]', '+ c d Full ms2 830.83@cid45.00 [215.00-1675.00]', '+ c d Full ms2 831.41@cid45.00 [215.00-1675.00]', '+ c d Full ms2 832.41@cid45.00 [215.00-1675.00]', '+ c d Full ms2 834.32@cid45.00 [215.00-1680.00]', '+ c d Full ms2 834.77@cid45.00 [215.00-1680.00]', '+ c d Full ms2 836.43@cid45.00 [220.00-1685.00]', '+ c d Full ms2 837.95@cid45.00 [220.00-1690.00]', '+ c d Full ms2 838.48@cid45.00 [220.00-1690.00]', '+ c d Full ms2 839.40@cid45.00 [220.00-1690.00]', '+ c d Full ms2 842.34@cid45.00 [220.00-1695.00]', '+ c d Full ms2 843.86@cid45.00 [220.00-1700.00]', '+ c d Full ms2 844.20@cid45.00 [220.00-1700.00]', '+ c d Full ms2 844.48@cid45.00 [220.00-1700.00]', '+ c d Full ms2 845.24@cid45.00 [220.00-1705.00]', '+ c d Full ms2 847.69@cid45.00 [220.00-1710.00]', '+ c d Full ms2 848.05@cid45.00 [220.00-1710.00]', '+ c d Full ms2 848.45@cid45.00 [220.00-1710.00]', '+ c d Full ms2 849.37@cid45.00 [220.00-1710.00]', '+ c d Full ms2 849.58@cid45.00 [220.00-1710.00]', '+ c d Full ms2 850.94@cid45.00 [220.00-1715.00]', '+ c d Full ms2 851.34@cid45.00 [220.00-1715.00]', '+ c d Full ms2 852.11@cid45.00 [220.00-1715.00]', '+ c d Full ms2 853.27@cid45.00 [220.00-1720.00]', '+ c d Full ms2 854.04@cid45.00 [225.00-1720.00]', '+ c d Full ms2 854.43@cid45.00 [225.00-1720.00]', '+ c d Full ms2 855.33@cid45.00 [225.00-1725.00]', '+ c d Full ms2 857.32@cid45.00 [225.00-1725.00]', '+ c d Full ms2 858.28@cid45.00 [225.00-1730.00]', '+ c d Full ms2 858.95@cid45.00 [225.00-1730.00]', '+ c d Full ms2 859.35@cid45.00 [225.00-1730.00]', '+ c d Full ms2 860.53@cid45.00 [225.00-1735.00]', '+ c d Full ms2 861.33@cid45.00 [225.00-1735.00]', '+ c d Full ms2 861.93@cid45.00 [225.00-1735.00]', '+ c d Full ms2 862.22@cid45.00 [225.00-1735.00]', '+ c d Full ms2 863.50@cid45.00 [225.00-1740.00]', '+ c d Full ms2 864.06@cid45.00 [225.00-1740.00]', '+ c d Full ms2 864.40@cid45.00 [225.00-1740.00]', '+ c d Full ms2 866.15@cid45.00 [225.00-1745.00]', '+ c d Full ms2 868.39@cid45.00 [225.00-1750.00]', '+ c d Full ms2 868.96@cid45.00 [225.00-1750.00]', '+ c d Full ms2 871.16@cid45.00 [225.00-1755.00]', '+ c d Full ms2 871.67@cid45.00 [225.00-1755.00]', '+ c d Full ms2 872.36@cid45.00 [230.00-1755.00]', '+ c d Full ms2 874.10@cid45.00 [230.00-1760.00]', '+ c d Full ms2 874.39@cid45.00 [230.00-1760.00]', '+ c d Full ms2 875.69@cid45.00 [230.00-1765.00]', '+ c d Full ms2 877.42@cid45.00 [230.00-1765.00]', '+ c d Full ms2 877.53@cid45.00 [230.00-1770.00]', '+ c d Full ms2 880.17@cid45.00 [230.00-1775.00]', '+ c d Full ms2 880.62@cid45.00 [230.00-1775.00]', '+ c d Full ms2 881.11@cid45.00 [230.00-1775.00]', '+ c d Full ms2 881.42@cid45.00 [230.00-1775.00]', '+ c d Full ms2 881.83@cid45.00 [230.00-1775.00]', '+ c d Full ms2 884.41@cid45.00 [230.00-1780.00]', '+ c d Full ms2 885.52@cid45.00 [230.00-1785.00]', '+ c d Full ms2 885.82@cid45.00 [230.00-1785.00]', '+ c d Full ms2 888.12@cid45.00 [230.00-1790.00]', '+ c d Full ms2 889.17@cid45.00 [230.00-1790.00]', '+ c d Full ms2 889.78@cid45.00 [230.00-1790.00]', '+ c d Full ms2 890.33@cid45.00 [235.00-1795.00]', '+ c d Full ms2 891.38@cid45.00 [235.00-1795.00]', '+ c d Full ms2 891.70@cid45.00 [235.00-1795.00]', '+ c d Full ms2 892.68@cid45.00 [235.00-1800.00]', '+ c d Full ms2 894.59@cid45.00 [235.00-1800.00]', '+ c d Full ms2 894.89@cid45.00 [235.00-1800.00]', '+ c d Full ms2 895.20@cid45.00 [235.00-1805.00]', '+ c d Full ms2 895.45@cid45.00 [235.00-1805.00]', '+ c d Full ms2 896.19@cid45.00 [235.00-1805.00]', '+ c d Full ms2 896.71@cid45.00 [235.00-1805.00]', '+ c d Full ms2 899.26@cid45.00 [235.00-1810.00]', '+ c d Full ms2 899.51@cid45.00 [235.00-1810.00]', '+ c d Full ms2 899.94@cid45.00 [235.00-1810.00]', '+ c d Full ms2 900.15@cid45.00 [235.00-1815.00]', '+ c d Full ms2 900.86@cid45.00 [235.00-1815.00]', '+ c d Full ms2 901.06@cid45.00 [235.00-1815.00]', '+ c d Full ms2 901.40@cid45.00 [235.00-1815.00]', '+ c d Full ms2 902.55@cid45.00 [235.00-1820.00]', '+ c d Full ms2 902.80@cid45.00 [235.00-1820.00]', '+ c d Full ms2 904.25@cid45.00 [235.00-1820.00]', '+ c d Full ms2 904.63@cid45.00 [235.00-1820.00]', '+ c d Full ms2 905.13@cid45.00 [235.00-1825.00]', '+ c d Full ms2 905.38@cid45.00 [235.00-1825.00]', '+ c d Full ms2 905.59@cid45.00 [235.00-1825.00]', '+ c d Full ms2 906.01@cid45.00 [235.00-1825.00]', '+ c d Full ms2 906.48@cid45.00 [235.00-1825.00]', '+ c d Full ms2 906.87@cid45.00 [235.00-1825.00]', '+ c d Full ms2 907.11@cid45.00 [235.00-1825.00]', '+ c d Full ms2 907.97@cid45.00 [235.00-1830.00]', '+ c d Full ms2 908.40@cid45.00 [240.00-1830.00]', '+ c d Full ms2 909.43@cid45.00 [240.00-1830.00]', '+ c d Full ms2 910.07@cid45.00 [240.00-1835.00]', '+ c d Full ms2 910.74@cid45.00 [240.00-1835.00]', '+ c d Full ms2 911.04@cid45.00 [240.00-1835.00]', '+ c d Full ms2 911.42@cid45.00 [240.00-1835.00]', '+ c d Full ms2 911.83@cid45.00 [240.00-1835.00]', '+ c d Full ms2 912.10@cid45.00 [240.00-1835.00]', '+ c d Full ms2 912.46@cid45.00 [240.00-1835.00]', '+ c d Full ms2 912.56@cid45.00 [240.00-1840.00]', '+ c d Full ms2 913.88@cid45.00 [240.00-1840.00]', '+ c d Full ms2 914.39@cid45.00 [240.00-1840.00]', '+ c d Full ms2 914.93@cid45.00 [240.00-1840.00]', '+ c d Full ms2 915.89@cid45.00 [240.00-1845.00]', '+ c d Full ms2 916.33@cid45.00 [240.00-1845.00]', '+ c d Full ms2 917.65@cid45.00 [240.00-1850.00]', '+ c d Full ms2 918.07@cid45.00 [240.00-1850.00]', '+ c d Full ms2 918.29@cid45.00 [240.00-1850.00]', '+ c d Full ms2 918.76@cid45.00 [240.00-1850.00]', '+ c d Full ms2 919.63@cid45.00 [240.00-1850.00]', '+ c d Full ms2 920.02@cid45.00 [240.00-1855.00]', '+ c d Full ms2 921.31@cid45.00 [240.00-1855.00]', '+ c d Full ms2 921.59@cid45.00 [240.00-1855.00]', '+ c d Full ms2 923.39@cid45.00 [240.00-1860.00]', '+ c d Full ms2 923.80@cid45.00 [240.00-1860.00]', '+ c d Full ms2 924.41@cid45.00 [240.00-1860.00]', '+ c d Full ms2 924.66@cid45.00 [240.00-1860.00]', '+ c d Full ms2 925.38@cid45.00 [240.00-1865.00]', '+ c d Full ms2 925.78@cid45.00 [240.00-1865.00]', '+ c d Full ms2 926.96@cid45.00 [245.00-1865.00]', '+ c d Full ms2 927.27@cid45.00 [245.00-1865.00]', '+ c d Full ms2 927.54@cid45.00 [245.00-1870.00]', '+ c d Full ms2 928.26@cid45.00 [245.00-1870.00]', '+ c d Full ms2 928.84@cid45.00 [245.00-1870.00]', '+ c d Full ms2 929.24@cid45.00 [245.00-1870.00]', '+ c d Full ms2 929.48@cid45.00 [245.00-1870.00]', '+ c d Full ms2 930.67@cid45.00 [245.00-1875.00]', '+ c d Full ms2 931.41@cid45.00 [245.00-1875.00]', '+ c d Full ms2 932.60@cid45.00 [245.00-1880.00]', '+ c d Full ms2 933.16@cid45.00 [245.00-1880.00]', '+ c d Full ms2 933.47@cid45.00 [245.00-1880.00]', '+ c d Full ms2 933.69@cid45.00 [245.00-1880.00]', '+ c d Full ms2 935.15@cid45.00 [245.00-1885.00]', '+ c d Full ms2 936.08@cid45.00 [245.00-1885.00]', '+ c d Full ms2 936.38@cid45.00 [245.00-1885.00]', '+ c d Full ms2 937.44@cid45.00 [245.00-1885.00]', '+ c d Full ms2 937.84@cid45.00 [245.00-1890.00]', '+ c d Full ms2 938.13@cid45.00 [245.00-1890.00]', '+ c d Full ms2 938.36@cid45.00 [245.00-1890.00]', '+ c d Full ms2 939.80@cid45.00 [245.00-1890.00]', '+ c d Full ms2 940.24@cid45.00 [245.00-1895.00]', '+ c d Full ms2 940.44@cid45.00 [245.00-1895.00]', '+ c d Full ms2 941.62@cid45.00 [245.00-1895.00]', '+ c d Full ms2 942.72@cid45.00 [245.00-1900.00]', '+ c d Full ms2 943.05@cid45.00 [245.00-1900.00]', '+ c d Full ms2 943.47@cid45.00 [245.00-1900.00]', '+ c d Full ms2 944.40@cid45.00 [250.00-1900.00]', '+ c d Full ms2 944.97@cid45.00 [250.00-1900.00]', '+ c d Full ms2 945.37@cid45.00 [250.00-1905.00]', '+ c d Full ms2 945.91@cid45.00 [250.00-1905.00]', '+ c d Full ms2 946.43@cid45.00 [250.00-1905.00]', '+ c d Full ms2 947.74@cid45.00 [250.00-1910.00]', '+ c d Full ms2 949.47@cid45.00 [250.00-1910.00]', '+ c d Full ms2 950.47@cid45.00 [250.00-1915.00]', '+ c d Full ms2 950.94@cid45.00 [250.00-1915.00]', '+ c d Full ms2 951.32@cid45.00 [250.00-1915.00]', '+ c d Full ms2 952.53@cid45.00 [250.00-1920.00]', '+ c d Full ms2 953.41@cid45.00 [250.00-1920.00]', '+ c d Full ms2 953.71@cid45.00 [250.00-1920.00]', '+ c d Full ms2 954.96@cid45.00 [250.00-1920.00]', '+ c d Full ms2 955.59@cid45.00 [250.00-1925.00]', '+ c d Full ms2 957.40@cid45.00 [250.00-1925.00]', '+ c d Full ms2 957.52@cid45.00 [250.00-1930.00]', '+ c d Full ms2 957.87@cid45.00 [250.00-1930.00]', '+ c d Full ms2 958.27@cid45.00 [250.00-1930.00]', '+ c d Full ms2 959.14@cid45.00 [250.00-1930.00]', '+ c d Full ms2 959.37@cid45.00 [250.00-1930.00]', '+ c d Full ms2 959.72@cid45.00 [250.00-1930.00]', '+ c d Full ms2 960.41@cid45.00 [250.00-1935.00]', '+ c d Full ms2 960.63@cid45.00 [250.00-1935.00]', '+ c d Full ms2 961.10@cid45.00 [250.00-1935.00]', '+ c d Full ms2 961.41@cid45.00 [250.00-1935.00]', '+ c d Full ms2 961.62@cid45.00 [250.00-1935.00]', '+ c d Full ms2 962.85@cid45.00 [255.00-1940.00]', '+ c d Full ms2 963.39@cid45.00 [255.00-1940.00]', '+ c d Full ms2 963.88@cid45.00 [255.00-1940.00]', '+ c d Full ms2 964.72@cid45.00 [255.00-1940.00]', '+ c d Full ms2 966.25@cid45.00 [255.00-1945.00]', '+ c d Full ms2 966.49@cid45.00 [255.00-1945.00]', '+ c d Full ms2 967.28@cid45.00 [255.00-1945.00]', '+ c d Full ms2 967.52@cid45.00 [255.00-1950.00]', '+ c d Full ms2 968.08@cid45.00 [255.00-1950.00]', '+ c d Full ms2 968.34@cid45.00 [255.00-1950.00]', '+ c d Full ms2 968.57@cid45.00 [255.00-1950.00]', '+ c d Full ms2 969.52@cid45.00 [255.00-1950.00]', '+ c d Full ms2 970.16@cid45.00 [255.00-1955.00]', '+ c d Full ms2 970.68@cid45.00 [255.00-1955.00]', '+ c d Full ms2 971.01@cid45.00 [255.00-1955.00]', '+ c d Full ms2 971.61@cid45.00 [255.00-1955.00]', '+ c d Full ms2 972.29@cid45.00 [255.00-1955.00]', '+ c d Full ms2 972.81@cid45.00 [255.00-1960.00]', '+ c d Full ms2 973.12@cid45.00 [255.00-1960.00]', '+ c d Full ms2 973.40@cid45.00 [255.00-1960.00]', '+ c d Full ms2 974.29@cid45.00 [255.00-1960.00]', '+ c d Full ms2 974.78@cid45.00 [255.00-1960.00]', '+ c d Full ms2 975.58@cid45.00 [255.00-1965.00]', '+ c d Full ms2 976.62@cid45.00 [255.00-1965.00]', '+ c d Full ms2 977.65@cid45.00 [255.00-1970.00]', '+ c d Full ms2 978.57@cid45.00 [255.00-1970.00]', '+ c d Full ms2 979.30@cid45.00 [255.00-1970.00]', '+ c d Full ms2 979.59@cid45.00 [255.00-1970.00]', '+ c d Full ms2 980.18@cid45.00 [255.00-1975.00]', '+ c d Full ms2 980.40@cid45.00 [255.00-1975.00]', '+ c d Full ms2 980.63@cid45.00 [255.00-1975.00]', '+ c d Full ms2 981.06@cid45.00 [260.00-1975.00]', '+ c d Full ms2 981.61@cid45.00 [260.00-1975.00]', '+ c d Full ms2 981.95@cid45.00 [260.00-1975.00]', '+ c d Full ms2 983.47@cid45.00 [260.00-1980.00]', '+ c d Full ms2 984.00@cid45.00 [260.00-1980.00]', '+ c d Full ms2 984.44@cid45.00 [260.00-1980.00]', '+ c d Full ms2 985.39@cid45.00 [260.00-1985.00]', '+ c d Full ms2 985.72@cid45.00 [260.00-1985.00]', '+ c d Full ms2 986.31@cid45.00 [260.00-1985.00]', '+ c d Full ms2 986.63@cid45.00 [260.00-1985.00]', '+ c d Full ms2 987.41@cid45.00 [260.00-1985.00]', '+ c d Full ms2 988.69@cid45.00 [260.00-1990.00]', '+ c d Full ms2 989.35@cid45.00 [260.00-1990.00]', '+ c d Full ms2 990.43@cid45.00 [260.00-1995.00]', '+ c d Full ms2 991.27@cid45.00 [260.00-1995.00]', '+ c d Full ms2 991.56@cid45.00 [260.00-1995.00]', '+ c d Full ms2 993.08@cid45.00 [260.00-2000.00]', '+ c d Full ms2 993.41@cid45.00 [260.00-2000.00]', '+ c d Full ms2 993.96@cid45.00 [260.00-2000.00]', '+ c d Full ms2 994.22@cid45.00 [260.00-2000.00]', '+ c d Full ms2 994.80@cid45.00 [260.00-2000.00]', '+ c d Full ms2 995.06@cid45.00 [260.00-2000.00]', '+ c d Full ms2 996.25@cid45.00 [260.00-2000.00]', '+ c d Full ms2 997.38@cid45.00 [260.00-2000.00]', '+ c d Full ms2 998.27@cid45.00 [260.00-2000.00]', '+ c d Full ms2 998.52@cid45.00 [260.00-2000.00]', '+ c d Full ms2 998.96@cid45.00 [265.00-2000.00]', '+ c d Full ms2 999.55@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1000.25@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1001.01@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1001.35@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1001.95@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1002.42@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1002.87@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1004.08@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1004.45@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1005.47@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1006.25@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1006.51@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1007.01@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1007.26@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1007.91@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1008.44@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1008.86@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1009.09@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1009.30@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1009.75@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1010.13@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1010.62@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1011.22@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1011.43@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1011.75@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1012.56@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1012.84@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1013.70@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1014.12@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1014.93@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1015.18@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1015.49@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1015.77@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1016.20@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1016.66@cid45.00 [265.00-2000.00]', '+ c d Full ms2 1017.51@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1018.19@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1018.55@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1018.80@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1019.95@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1020.39@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1020.68@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1020.97@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1021.26@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1021.77@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1022.47@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1022.75@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1023.14@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1023.35@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1024.71@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1024.99@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1025.58@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1026.89@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1027.19@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1027.44@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1027.70@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1029.41@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1029.64@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1030.50@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1031.04@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1031.70@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1032.71@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1033.07@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1033.82@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1034.38@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1034.87@cid45.00 [270.00-2000.00]', '+ c d Full ms2 1035.62@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1036.45@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1036.77@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1037.18@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1037.41@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1038.50@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1041.84@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1042.75@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1043.90@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1044.24@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1044.67@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1045.25@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1046.43@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1046.98@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1047.65@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1048.43@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1048.94@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1050.59@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1051.41@cid45.00 [275.00-2000.00]', '+ c d Full ms2 1054.08@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1054.41@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1054.62@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1054.98@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1055.28@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1055.88@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1056.12@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1056.48@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1056.79@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1057.15@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1057.47@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1057.83@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1058.05@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1058.59@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1059.30@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1059.56@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1059.82@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1060.14@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1060.39@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1060.72@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1061.09@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1061.54@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1062.15@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1062.80@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1063.83@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1064.40@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1065.47@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1067.25@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1067.57@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1068.17@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1068.42@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1068.66@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1069.23@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1070.10@cid45.00 [280.00-2000.00]', '+ c d Full ms2 1071.46@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1072.28@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1073.35@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1073.59@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1074.02@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1074.43@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1074.89@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1075.40@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1077.00@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1077.85@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1078.07@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1078.30@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1078.74@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1079.00@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1079.57@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1080.21@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1080.71@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1081.47@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1081.85@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1082.42@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1082.84@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1083.33@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1083.91@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1084.39@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1084.66@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1085.02@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1085.29@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1085.69@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1086.39@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1087.02@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1087.51@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1088.67@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1089.29@cid45.00 [285.00-2000.00]', '+ c d Full ms2 1089.81@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1090.03@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1090.26@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1090.73@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1091.02@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1091.34@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1092.35@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1092.72@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1093.42@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1094.32@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1094.68@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1095.12@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1095.35@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1095.75@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1096.07@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1096.44@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1096.91@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1097.48@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1097.81@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1098.33@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1098.98@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1099.26@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1099.47@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1100.24@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1101.06@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1101.40@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1101.72@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1102.20@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1102.66@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1103.11@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1103.47@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1104.23@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1104.49@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1105.22@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1105.49@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1106.09@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1106.60@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1106.84@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1107.09@cid45.00 [290.00-2000.00]', '+ c d Full ms2 1107.87@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1108.14@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1108.35@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1108.78@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1110.17@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1110.39@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1111.11@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1112.47@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1112.92@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1113.29@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1113.71@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1114.10@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1114.37@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1114.69@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1115.44@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1116.28@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1116.87@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1117.14@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1118.29@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1118.50@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1119.32@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1119.70@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1120.73@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1121.24@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1121.70@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1122.20@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1123.35@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1124.20@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1124.50@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1124.82@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1125.56@cid45.00 [295.00-2000.00]', '+ c d Full ms2 1125.99@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1126.45@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1127.51@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1127.73@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1128.26@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1128.86@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1129.18@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1129.79@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1130.50@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1131.65@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1132.30@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1132.75@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1133.12@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1133.47@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1133.92@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1134.30@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1134.56@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1134.79@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1135.14@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1135.47@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1135.80@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1136.69@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1136.91@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1137.32@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1138.01@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1138.68@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1139.00@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1139.47@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1140.12@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1140.39@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1141.30@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1141.99@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1142.61@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1143.15@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1143.57@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1144.04@cid45.00 [300.00-2000.00]', '+ c d Full ms2 1144.28@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1144.70@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1145.82@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1146.04@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1146.43@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1147.03@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1147.36@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1147.67@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1148.34@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1148.56@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1148.84@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1151.55@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1151.75@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1152.55@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1152.80@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1153.07@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1153.53@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1153.92@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1154.35@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1155.06@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1155.29@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1155.50@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1156.28@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1156.54@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1156.76@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1157.03@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1157.25@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1157.91@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1158.18@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1158.54@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1160.86@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1161.43@cid45.00 [305.00-2000.00]', '+ c d Full ms2 1162.67@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1163.21@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1163.42@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1163.80@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1165.94@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1166.17@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1166.71@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1167.32@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1167.79@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1168.12@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1168.45@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1168.78@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1169.17@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1169.84@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1170.13@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1170.53@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1170.91@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1171.23@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1171.54@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1172.03@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1172.24@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1172.66@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1173.19@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1173.52@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1173.81@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1174.07@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1174.38@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1174.99@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1175.29@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1175.57@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1176.00@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1176.65@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1176.86@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1177.27@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1178.16@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1179.94@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1180.24@cid45.00 [310.00-2000.00]', '+ c d Full ms2 1180.49@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1180.76@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1180.98@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1181.45@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1181.89@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1182.20@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1182.49@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1183.36@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1185.39@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1185.61@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1186.62@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1187.45@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1187.83@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1188.39@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1188.63@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1189.41@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1190.32@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1190.52@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1190.74@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1191.20@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1191.84@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1192.25@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1192.60@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1193.22@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1193.45@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1193.74@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1194.50@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1194.78@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1196.48@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1197.12@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1197.75@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1198.28@cid45.00 [315.00-2000.00]', '+ c d Full ms2 1198.73@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1199.00@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1199.39@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1200.39@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1201.28@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1201.59@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1202.54@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1202.89@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1203.29@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1203.83@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1204.12@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1204.37@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1204.65@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1205.07@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1205.61@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1206.31@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1206.89@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1207.11@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1208.02@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1208.33@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1208.70@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1209.72@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1210.00@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1210.23@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1210.58@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1211.29@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1212.35@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1212.86@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1213.29@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1213.64@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1213.92@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1214.21@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1214.56@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1215.03@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1215.58@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1216.30@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1216.59@cid45.00 [320.00-2000.00]', '+ c d Full ms2 1217.65@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1218.19@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1218.66@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1218.86@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1220.87@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1221.49@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1222.00@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1223.12@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1223.40@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1223.61@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1224.13@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1224.50@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1224.96@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1225.20@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1225.41@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1226.17@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1226.41@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1226.63@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1227.12@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1227.36@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1227.77@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1228.09@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1228.38@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1228.62@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1230.05@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1230.35@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1230.61@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1230.86@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1231.10@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1231.37@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1231.93@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1232.75@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1233.36@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1234.07@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1234.42@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1234.67@cid45.00 [325.00-2000.00]', '+ c d Full ms2 1234.93@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1235.52@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1235.73@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1235.99@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1236.30@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1236.76@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1237.14@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1237.37@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1237.78@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1238.83@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1239.12@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1239.38@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1239.91@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1240.22@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1240.67@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1241.34@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1241.56@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1242.47@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1242.82@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1243.28@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1243.90@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1244.23@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1244.65@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1244.92@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1245.29@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1245.83@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1246.05@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1246.35@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1246.68@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1246.93@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1247.58@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1247.86@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1248.24@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1248.67@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1249.26@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1250.34@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1251.56@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1251.76@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1252.31@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1252.76@cid45.00 [330.00-2000.00]', '+ c d Full ms2 1253.64@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1254.24@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1254.45@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1255.05@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1255.49@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1256.62@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1257.46@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1258.58@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1259.45@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1260.52@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1261.08@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1261.50@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1261.81@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1262.19@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1262.55@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1262.80@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1263.25@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1263.54@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1264.09@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1264.47@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1264.98@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1265.77@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1266.07@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1266.38@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1266.73@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1267.36@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1267.58@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1267.88@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1268.14@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1270.59@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1270.81@cid45.00 [335.00-2000.00]', '+ c d Full ms2 1271.40@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1272.27@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1272.94@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1273.73@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1274.08@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1274.36@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1275.42@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1276.44@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1276.93@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1277.16@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1277.61@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1278.78@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1279.03@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1279.53@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1280.60@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1281.27@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1281.83@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1282.33@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1282.74@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1282.97@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1283.30@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1284.12@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1284.78@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1285.21@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1285.44@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1285.69@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1286.05@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1286.46@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1286.88@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1287.34@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1287.80@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1288.07@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1288.97@cid45.00 [340.00-2000.00]', '+ c d Full ms2 1290.42@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1290.65@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1291.10@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1291.64@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1292.97@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1293.49@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1293.93@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1294.83@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1295.24@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1295.61@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1295.94@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1296.69@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1297.01@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1297.68@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1298.05@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1299.23@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1300.22@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1300.51@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1300.73@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1301.46@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1302.36@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1302.71@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1302.97@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1304.04@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1304.53@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1305.66@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1305.97@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1306.31@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1306.58@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1306.86@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1307.31@cid45.00 [345.00-2000.00]', '+ c d Full ms2 1307.77@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1308.12@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1308.41@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1308.65@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1309.23@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1309.45@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1309.77@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1310.15@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1310.65@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1311.05@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1311.44@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1311.87@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1312.20@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1312.72@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1314.60@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1314.84@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1317.11@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1317.51@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1317.95@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1318.36@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1319.03@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1319.44@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1319.86@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1320.14@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1320.41@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1320.93@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1321.15@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1321.42@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1322.17@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1322.74@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1323.14@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1323.45@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1323.83@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1324.05@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1324.29@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1324.84@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1325.08@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1325.46@cid45.00 [350.00-2000.00]', '+ c d Full ms2 1325.82@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1326.18@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1326.54@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1327.18@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1327.64@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1328.13@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1328.42@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1328.82@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1329.61@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1329.83@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1330.08@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1330.51@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1330.74@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1331.12@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1332.79@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1333.02@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1334.25@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1334.67@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1334.98@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1335.38@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1335.84@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1336.31@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1336.74@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1337.12@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1337.83@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1338.08@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1338.42@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1339.64@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1341.24@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1342.18@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1342.62@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1342.97@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1343.62@cid45.00 [355.00-2000.00]', '+ c d Full ms2 1343.98@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1344.75@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1345.79@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1346.06@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1346.69@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1347.54@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1348.21@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1349.06@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1349.44@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1350.65@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1351.56@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1353.17@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1353.46@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1354.26@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1354.55@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1354.75@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1355.26@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1355.83@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1356.39@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1357.27@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1357.87@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1358.31@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1358.81@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1359.11@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1359.40@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1359.73@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1360.49@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1361.20@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1361.46@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1361.67@cid45.00 [360.00-2000.00]', '+ c d Full ms2 1362.04@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1362.27@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1362.48@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1362.72@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1363.34@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1364.21@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1365.97@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1366.55@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1367.12@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1367.35@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1367.82@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1368.08@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1368.80@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1370.16@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1370.36@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1371.30@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1371.73@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1372.28@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1372.66@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1373.38@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1373.98@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1374.39@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1374.84@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1375.35@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1375.61@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1376.23@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1376.56@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1377.09@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1377.46@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1378.79@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1379.48@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1380.14@cid45.00 [365.00-2000.00]', '+ c d Full ms2 1380.38@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1380.65@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1381.89@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1382.58@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1383.46@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1383.84@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1384.39@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1385.17@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1385.54@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1386.28@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1386.50@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1386.80@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1387.25@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1387.49@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1387.82@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1388.89@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1390.17@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1390.77@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1391.02@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1391.31@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1391.73@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1392.30@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1392.51@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1393.31@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1393.52@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1394.48@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1394.76@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1395.99@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1396.55@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1397.84@cid45.00 [370.00-2000.00]', '+ c d Full ms2 1398.59@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1402.18@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1402.47@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1404.40@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1405.00@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1405.30@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1406.30@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1406.66@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1408.27@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1409.03@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1409.48@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1409.75@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1410.07@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1410.29@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1410.55@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1411.75@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1412.08@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1412.49@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1413.12@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1413.60@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1413.84@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1414.16@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1415.51@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1415.98@cid45.00 [375.00-2000.00]', '+ c d Full ms2 1416.85@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1418.04@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1418.27@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1419.24@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1420.18@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1420.97@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1421.21@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1421.74@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1422.15@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1422.40@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1423.47@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1423.76@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1424.28@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1424.80@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1425.36@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1425.80@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1426.23@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1426.56@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1427.23@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1427.57@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1428.18@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1429.93@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1431.09@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1431.33@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1434.59@cid45.00 [380.00-2000.00]', '+ c d Full ms2 1435.30@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1435.81@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1436.55@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1438.42@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1438.62@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1439.33@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1440.17@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1440.77@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1441.16@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1441.44@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1442.61@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1443.12@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1443.47@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1443.92@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1444.46@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1445.53@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1446.72@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1447.22@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1447.53@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1448.12@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1448.42@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1448.92@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1449.40@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1449.66@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1450.57@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1451.32@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1451.96@cid45.00 [385.00-2000.00]', '+ c d Full ms2 1453.03@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1453.69@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1453.99@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1455.12@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1455.82@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1456.19@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1456.65@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1456.87@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1457.36@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1457.68@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1458.17@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1458.57@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1459.12@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1460.04@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1460.68@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1461.25@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1461.54@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1461.79@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1463.28@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1464.01@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1464.44@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1465.71@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1467.27@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1469.86@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1470.24@cid45.00 [390.00-2000.00]', '+ c d Full ms2 1470.98@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1471.87@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1472.75@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1473.08@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1473.61@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1474.05@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1475.78@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1476.67@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1478.23@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1478.78@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1480.73@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1480.94@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1481.18@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1481.69@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1483.68@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1484.16@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1485.03@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1485.56@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1486.16@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1486.68@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1487.22@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1488.95@cid45.00 [395.00-2000.00]', '+ c d Full ms2 1489.16@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1489.60@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1490.51@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1491.64@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1492.19@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1492.51@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1492.90@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1493.60@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1493.98@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1494.28@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1495.28@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1495.80@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1496.26@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1497.46@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1497.97@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1498.68@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1499.23@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1499.66@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1501.32@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1501.93@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1504.87@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1505.39@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1505.70@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1506.53@cid45.00 [400.00-2000.00]', '+ c d Full ms2 1507.59@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1508.64@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1509.00@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1509.34@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1509.83@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1510.37@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1511.93@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1512.57@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1513.31@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1513.89@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1514.12@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1515.71@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1516.48@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1516.89@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1518.14@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1519.06@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1520.53@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1521.33@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1521.56@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1522.25@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1522.70@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1523.83@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1524.64@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1525.14@cid45.00 [405.00-2000.00]', '+ c d Full ms2 1525.71@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1526.39@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1527.35@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1527.89@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1530.51@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1531.26@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1531.79@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1532.11@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1533.10@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1533.49@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1533.95@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1534.83@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1535.28@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1535.55@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1536.16@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1536.62@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1539.44@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1540.18@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1540.43@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1540.98@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1541.43@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1542.33@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1542.87@cid45.00 [410.00-2000.00]', '+ c d Full ms2 1544.34@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1546.55@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1547.23@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1547.59@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1548.33@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1548.59@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1548.99@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1549.96@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1550.56@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1550.78@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1551.14@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1551.42@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1551.67@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1552.36@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1553.50@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1553.85@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1555.23@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1555.47@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1555.76@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1557.34@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1557.80@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1558.03@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1558.85@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1559.67@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1559.93@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1560.67@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1561.46@cid45.00 [415.00-2000.00]', '+ c d Full ms2 1562.85@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1563.38@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1564.01@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1565.13@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1566.08@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1567.21@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1568.19@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1568.44@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1568.97@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1569.38@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1570.17@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1570.87@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1571.28@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1575.42@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1576.01@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1576.26@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1578.12@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1578.87@cid45.00 [420.00-2000.00]', '+ c d Full ms2 1580.11@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1580.75@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1581.76@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1582.34@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1582.73@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1583.71@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1583.95@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1584.17@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1584.78@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1585.39@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1585.67@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1586.38@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1586.96@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1587.46@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1587.91@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1588.67@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1589.52@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1590.04@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1590.89@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1591.99@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1592.20@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1592.69@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1592.96@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1593.68@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1593.90@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1595.56@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1596.08@cid45.00 [425.00-2000.00]', '+ c d Full ms2 1598.36@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1601.14@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1602.04@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1602.60@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1602.81@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1603.16@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1603.53@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1604.29@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1604.97@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1605.32@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1607.12@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1607.55@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1613.38@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1614.10@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1614.48@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1616.13@cid45.00 [430.00-2000.00]', '+ c d Full ms2 1616.48@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1616.94@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1617.58@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1617.86@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1619.41@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1620.32@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1621.06@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1622.22@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1623.74@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1624.51@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1625.15@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1625.83@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1627.44@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1627.81@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1628.13@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1629.79@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1630.55@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1631.44@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1633.48@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1633.69@cid45.00 [435.00-2000.00]', '+ c d Full ms2 1634.63@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1635.17@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1636.10@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1637.87@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1638.76@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1639.58@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1639.79@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1640.84@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1641.39@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1643.49@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1644.01@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1644.48@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1644.71@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1645.46@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1645.70@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1646.28@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1646.50@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1647.00@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1647.86@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1648.82@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1649.32@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1651.44@cid45.00 [440.00-2000.00]', '+ c d Full ms2 1654.03@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1654.84@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1656.22@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1656.44@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1657.78@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1658.43@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1661.11@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1662.57@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1663.04@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1663.38@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1663.93@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1665.77@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1666.84@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1667.41@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1668.84@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1669.45@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1670.71@cid45.00 [445.00-2000.00]', '+ c d Full ms2 1671.10@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1671.66@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1672.68@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1673.45@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1675.08@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1676.34@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1677.02@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1678.75@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1679.09@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1680.29@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1680.90@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1682.73@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1683.69@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1685.85@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1686.51@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1686.98@cid45.00 [450.00-2000.00]', '+ c d Full ms2 1690.60@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1692.08@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1692.93@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1694.48@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1694.84@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1695.84@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1697.48@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1697.96@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1698.50@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1700.60@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1702.26@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1704.41@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1704.62@cid45.00 [455.00-2000.00]', '+ c d Full ms2 1707.18@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1708.64@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1709.58@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1710.76@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1711.39@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1712.65@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1712.94@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1713.82@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1714.05@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1714.71@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1714.93@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1715.53@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1716.97@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1717.35@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1718.09@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1718.36@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1721.44@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1721.85@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1723.93@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1724.35@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1724.65@cid45.00 [460.00-2000.00]', '+ c d Full ms2 1725.45@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1726.45@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1726.83@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1727.30@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1727.88@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1731.49@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1731.99@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1733.02@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1734.70@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1735.52@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1736.21@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1737.08@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1738.18@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1742.66@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1743.28@cid45.00 [465.00-2000.00]', '+ c d Full ms2 1745.21@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1748.11@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1748.43@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1749.37@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1750.27@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1751.49@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1752.35@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1753.85@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1754.72@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1755.60@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1756.45@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1757.59@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1757.98@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1759.96@cid45.00 [470.00-2000.00]', '+ c d Full ms2 1764.69@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1764.99@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1767.04@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1769.91@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1771.06@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1772.64@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1774.50@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1777.30@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1779.16@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1779.56@cid45.00 [475.00-2000.00]', '+ c d Full ms2 1781.25@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1781.86@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1783.48@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1783.88@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1784.91@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1785.16@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1785.70@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1786.05@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1787.98@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1792.09@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1792.54@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1793.58@cid45.00 [480.00-2000.00]', '+ c d Full ms2 1798.47@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1802.44@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1803.49@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1804.55@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1805.51@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1806.75@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1807.44@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1808.21@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1811.97@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1813.78@cid45.00 [485.00-2000.00]', '+ c d Full ms2 1817.10@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1819.44@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1821.79@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1826.20@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1828.42@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1829.13@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1829.42@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1831.26@cid45.00 [490.00-2000.00]', '+ c d Full ms2 1835.72@cid45.00 [495.00-2000.00]', '+ c d Full ms2 1836.84@cid45.00 [495.00-2000.00]', '+ c d Full ms2 1841.06@cid45.00 [495.00-2000.00]', '+ c d Full ms2 1842.28@cid45.00 [495.00-2000.00]', '+ c d Full ms2 1847.28@cid45.00 [495.00-2000.00]', '+ c d Full ms2 1848.36@cid45.00 [495.00-2000.00]', '+ c d Full ms2 1849.21@cid45.00 [495.00-2000.00]', '+ c d Full ms2 1854.90@cid45.00 [500.00-2000.00]', '+ c d Full ms2 1855.53@cid45.00 [500.00-2000.00]', '+ c d Full ms2 1860.02@cid45.00 [500.00-2000.00]', '+ c d Full ms2 1861.93@cid45.00 [500.00-2000.00]', '+ c d Full ms2 1862.13@cid45.00 [500.00-2000.00]', '+ c d Full ms2 1865.29@cid45.00 [500.00-2000.00]', '+ c d Full ms2 1869.54@cid45.00 [500.00-2000.00]', '+ c d Full ms2 1871.64@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1872.62@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1873.22@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1878.72@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1880.77@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1881.71@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1882.62@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1884.41@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1886.10@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1886.76@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1887.78@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1888.03@cid45.00 [505.00-2000.00]', '+ c d Full ms2 1890.18@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1892.65@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1895.17@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1896.10@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1898.14@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1900.50@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1902.20@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1902.41@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1903.86@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1905.46@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1905.98@cid45.00 [510.00-2000.00]', '+ c d Full ms2 1911.29@cid45.00 [515.00-2000.00]', '+ c d Full ms2 1914.09@cid45.00 [515.00-2000.00]', '+ c d Full ms2 1914.91@cid45.00 [515.00-2000.00]', '+ c d Full ms2 1917.57@cid45.00 [515.00-2000.00]', '+ c d Full ms2 1921.83@cid45.00 [515.00-2000.00]', '+ c d Full ms2 1924.58@cid45.00 [515.00-2000.00]', '+ c d Full ms2 1926.45@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1931.41@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1931.94@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1933.56@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1935.11@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1939.01@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1940.43@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1942.28@cid45.00 [520.00-2000.00]', '+ c d Full ms2 1943.85@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1946.86@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1950.70@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1951.34@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1953.11@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1953.72@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1957.90@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1959.53@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1959.90@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1960.18@cid45.00 [525.00-2000.00]', '+ c d Full ms2 1962.24@cid45.00 [530.00-2000.00]', '+ c d Full ms2 1969.87@cid45.00 [530.00-2000.00]', '+ c d Full ms2 1971.23@cid45.00 [530.00-2000.00]', '+ c d Full ms2 1971.51@cid45.00 [530.00-2000.00]', '+ c d Full ms2 1971.79@cid45.00 [530.00-2000.00]', '+ c d Full ms2 1972.78@cid45.00 [530.00-2000.00]', '+ c d Full ms2 1976.08@cid45.00 [530.00-2000.00]', '+ c d Full ms2 1986.43@cid45.00 [535.00-2000.00]', '+ c d Full ms2 1988.63@cid45.00 [535.00-2000.00]', '+ c d Full ms2 1994.49@cid45.00 [535.00-2000.00]')

52.639629

52

0.620487

20,681

90,856

2.725932

0.063778

0.09169

0.122182

0.244364

0.894297

0.877605

0.87067

0.868257

0.865366

0

0.485414

0.151845

90,856

1,726

53

52.639629

0.246159

0

0.998261

0.904939

0

1

0

false

0

null

0

1

0

1

0

1

0

1

0

null

0

11

97ad9bf5e23676efffa0610db7c195640be3e7ef

32,426

py

Python

server/route_test.py

TDDD96-Kandidatgrupp-1-2020/Visual1ze

84579b7d05343e8be9123e92fc606a967d5714c8

[ "MIT" ]

6

2020-05-25T13:30:55.000Z

2021-11-08T13:00:01.000Z

server/route_test.py

matheus-bernat/Visual1ze

84579b7d05343e8be9123e92fc606a967d5714c8

[ "MIT" ]

null

server/route_test.py

matheus-bernat/Visual1ze

84579b7d05343e8be9123e92fc606a967d5714c8

[ "MIT" ]

1

2021-03-30T14:38:40.000Z

""" This module is used to test the routes for the reader on the server. """ from flask import url_for from flask_jwt_extended import create_access_token from flask_testing import TestCase import json from script.create_db_data import populate_db from visualize import create_app, db from visualize.models import Reader, Approver, Admin app = create_app() app.app_context().push() # make all test use this context db.drop_all() app.config["ENV"] = "testing" i = 0 # index of test Emails class BaseTestCase(TestCase): """ Base class for unittest. """ # Oklart ifall vi behöver dessa... SQLALCHEMY_DATABASE_URI = "sqlite://" TESTING = True def get_new_random_email(self): global i """creates a new user email""" i += 1 string = "test{}@test.com".format(i) return string def get_old_email(self): string = "test{}@test.com".format(i) return string def login(self, email, pas="abcABC123"): """logs in a user""" with app.test_client() as client: sent = json.dumps({"email": email, "password": pas}) result = client.post( '/login', data=sent, content_type='application/json', ) access_token = json.loads(result.data.decode("utf-8"))["access_token"] headers = { 'Authorization': 'Bearer {}'.format(access_token) } return headers def populate_reader(self, email, pas="abcABC123"): """ populates the test db with a reader :param pas: :param email: users email :return: tuple with message from create_reader() and the send message """ admin_headers = self.login("c@c.c") with app.test_client() as client: sent = json.dumps({"email": email, "password": pas, "name": "test", "surname": "testson"}) result = client.post( 'admin/reader', data=sent, headers=admin_headers, content_type='application/json', ) access_token = create_access_token(identity=email) headers = { 'Authorization': 'Bearer {}'.format(access_token) } res = (result, sent, access_token, headers) # skriv om till dict return res def populate_approver(self, email, pas="abcABC123"): """ populates the test db with a reader :param pas: :param email: users email :return: tuple with message from create_reader() and the send message """ admin_headers = self.login("c@c.c") with app.test_client() as client: sent = json.dumps({"email": email, "password": pas, "name": "test", "surname": "testson"}) result = client.post( 'admin/approver', data=sent, headers=admin_headers, content_type='application/json', ) access_token = create_access_token(identity=email) headers = { 'Authorization': 'Bearer {}'.format(access_token) } res = (result, sent, access_token, headers) # skriv om till dict return res def populate_admin(self, email, pas="abcABC123"): """ populates the test db with a reader :param pas: :param email: users email :return: tuple with message from create_reader() and the send message """ admin_headers = self.login("c@c.c") with app.test_client() as client: sent = json.dumps({"email": email, "password": pas, "name": "test", "surname": "testson"}) result = client.post( 'admin/admin', data=sent, headers=admin_headers, content_type='application/json', ) access_token = create_access_token(identity=email) headers = { 'Authorization': 'Bearer {}'.format(access_token) } res = (result, sent, access_token, headers) # skriv om till dict return res def create_app(self): # app.run() return create_app() def setUp(self): db.create_all() populate_db() def tearDown(self): db.session.remove() db.drop_all() class ReaderRouteTest(BaseTestCase): """class for unittests for reader routes.""" def test_get_empty_reader(self): """testing get_current_reader if there is no user with that email.""" email = self.get_new_random_email() access_token = create_access_token(email) headers = { 'Authorization': 'Bearer {}'.format(access_token) } response = self.client.get('reader/self', headers=headers) self.assert400(response, "400 if there are no readers ") def test_get_reader(self): """testing get_current_reader and create_reader()""" email = self.get_new_random_email() self.populate_reader(email) headers = self.login(email) response = self.client.get('/reader/self', headers=headers) self.assertStatus(response, 200, "check if the reader request is ok ") response_data = json.loads(response.data) self.assertEqual(response_data['email'], email, "Check if sent email user is created with is the same as returned") def test_order_room(self): """test get_reader_rooms with a good request for the room isy1. """ room = "isy1" with app.test_client() as client: sent = json.dumps({"room_text_id": room, "justification": "Because i can"}) email = self.get_new_random_email() res = self.populate_reader(email) headers = res[3] response = client.post('/reader/room', data=sent, headers=headers, content_type='application/json') self.assert200(response, "check if the request is ok") self.assertEqual(response.data.decode("utf-8"), "Request for room {} has been sent.".format(room), "Check if the right room is returned. ") def test_order_bad_room(self): """test get_reader_rooms with bad room requests""" room = "isy1" with app.test_client() as client: sent = json.dumps({"room_text_id": room, "justification": "Because i can"}) email = self.get_new_random_email() res = self.populate_reader(email) headers = res[3] # test to send duplicate of room res = client.post('/reader/room', data=sent, headers=headers, content_type='application/json') self.assert200(res, "check if the request is ok") response = client.post('/reader/room', data=sent, headers=headers, content_type='application/json') self.assert400(response, "Check so we cant create a duplicate request with the same room") # test to send room that does not exist sent2 = json.dumps({"room_text_id": room + "abcd", "justification": "Because i can"}) response2 = client.post('/reader/room', data=sent2, headers=headers, content_type='application/json') self.assert400(response2, "Check so we cant request a room that dont exist") def test_order_ag(self): """test order_ag with a good request for the group 1.""" ag = 1 with app.test_client() as client: sent = json.dumps({"ag_id": ag, "justification": "Because i can"}) email = self.get_new_random_email() res = self.populate_reader(email) headers = res[3] response = client.post('/reader/ag', data=sent, headers=headers, content_type='application/json') self.assert200(response, "check if the request is ok") self.assertEqual(response.data.decode("utf-8"), "Request for access group {} has been sent.".format(ag), "Check if the right room is returned. ") def test_get_orders(self): """ test get_order, needs to add rooms and ag to check returns""" room = "isy1" with app.test_client() as client: email = self.get_new_random_email() res = self.populate_reader(email) headers = res[3] sent = json.dumps({"room_text_id": room, "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=headers, content_type='application/json') response = client.get('/reader/orders', headers=headers, content_type='application/json') self.assert200(response, "check if the request is ok") def test_get_all_access(self): """ test get_all_access, needs to add ag the user is in to check returns """ with app.test_client() as client: email = self.get_new_random_email() res = self.populate_reader(email) headers = res[3] response = client.get('/reader/access', headers=headers, content_type='application/json') self.assert200(response, "check if the request is ok") class ApproverRouteTest(BaseTestCase): """class for unittests for approver routes""" def test_get_readers_for_room(self): """testing get_readers_for_room if there is no user with that email.""" room = "isy1" with app.test_client() as client: sent = json.dumps({"room_text_id": room}) approver_email = "b@b.b" approver_headers = self.login(approver_email) response = client.post('/approver/readers_for_room', data=sent, headers=approver_headers, content_type='application/json') self.assert200(response, "The request was from an approver/admin") self.assert200(response, "We get some data") def test_approve_room_request(self): """ Test if its possible to approve room request.""" reader_email = self.get_new_random_email() res_r = self.populate_reader(reader_email) reader_headers = res_r[3] approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: sent = json.dumps({"room_text_id": "isy1", "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=reader_headers, content_type='application/json') response = client.get('approver/orders', headers=approver_headers) self.assert200(response, "The request was from an approver/admin") response_data = json.loads(response.data.decode("utf-8")) for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: request_id = y['request_id'] sent2 = json.dumps({"request_id": request_id, "type": "Room", "is_access_granted": True}) response2 = client.post('approver/access', data=sent2, headers=approver_headers, content_type='application/json') self.assert200(response2, "We get some data") def test_approve_multiple_room_request(self): """ Test if its possible to approve multiple room request.""" reader_email = self.get_new_random_email() res_r = self.populate_reader(reader_email) reader_headers = res_r[3] approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: sent = json.dumps({"room_text_id": "isy1", "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=reader_headers, content_type='application/json') sent3 = json.dumps({"room_text_id": "isy2", "justification": "Because i can"}) client.post('/reader/room', data=sent3, headers=reader_headers, content_type='application/json') response = client.get('approver/orders', headers=approver_headers) self.assert200(response, "The request was from an approver/admin") response_data = json.loads(response.data.decode("utf-8")) for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: request_id = y['request_id'] sent2 = json.dumps({"request_id": request_id, "type": "Room", "is_access_granted": True}) response2 = client.post('approver/access', data=sent2, headers=approver_headers, content_type='application/json') self.assert200(response2, "We get some data") def test_approve_ag_request(self): """ Test if its possible to approve ag request.""" reader_email = self.get_new_random_email() res_r = self.populate_reader(reader_email) reader_headers = res_r[3] approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: sent = json.dumps({"ag_id": 1, "justification": "Because i can"}) client.post('/reader/ag', data=sent, headers=reader_headers, content_type='application/json') response = client.get('approver/orders', headers=approver_headers) self.assert200(response, "The request was from an approver/admin") response_data = json.loads(response.data.decode("utf-8")) for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: request_id = y['request_id'] sent2 = json.dumps({"request_id": request_id, "type": "AG", "is_access_granted": True}) response2 = client.post('approver/access', data=sent2, headers=approver_headers, content_type='application/json') self.assert200(response2, "We get some data") def test_get_all_orders_for_logged_in(self): """ Test to see all orders for current approver.""" reader_email = self.get_new_random_email() res_r = self.populate_reader(reader_email) reader_headers = res_r[3] approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: sent = json.dumps({"room_text_id": "isy1", "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=reader_headers, content_type='application/json') sent = json.dumps({"room_text_id": "isy2", "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=reader_headers, content_type='application/json') sent = json.dumps({"room_text_id": "isy3", "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=reader_headers, content_type='application/json') response = client.get('approver/orders', headers=approver_headers) self.assert200(response, "The request was from an approver/admin") response_data = json.loads(response.data.decode("utf-8")) nr = 0 for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: nr += 1 self.assertEqual(nr, 3, "Check that we get 3 request to the email") def test_get_responsibilities(self): """ Tests the route to get all responsibilities, might need to att check for return value""" approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: response = client.get('/approver/responsibilities', headers=approver_headers, content_type='application/json') self.assert200(response, "The request was from an approver/admin") def test_get_all_readers(self): """ Test to get all readers for a room""" approver_email = "b@b.b" approver_headers = self.login(approver_email) sent = json.dumps({"room_text_id": "isy2"}) with app.test_client() as client: response = client.post('/approver/readers_for_room', headers=approver_headers, data=sent, content_type='application/json') self.assert200(response, "The request was from an approver/admin") def test_reject_room_request(self): """ Test if its possible to reject room request.""" reader_email = self.get_new_random_email() res_r = self.populate_reader(reader_email) reader_headers = res_r[3] approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: sent = json.dumps({"room_text_id": "isy1", "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=reader_headers, content_type='application/json') response = client.get('approver/orders', headers=approver_headers) self.assert200(response, "The request was from an approver/admin") response_data = json.loads(response.data.decode("utf-8")) for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: request_id = y['request_id'] sent2 = json.dumps({"request_id": request_id, "type": "Room", "is_access_granted": False}) response2 = client.post('approver/access', data=sent2, headers=approver_headers, content_type='application/json') self.assert200(response2, "We get some data") def test_reject_ag_request(self): """ Test if its possible to reject ag request.""" reader_email = self.get_new_random_email() res_r = self.populate_reader(reader_email) reader_headers = res_r[3] approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: sent = json.dumps({"ag_id": 1, "justification": "Because i can"}) client.post('/reader/ag', data=sent, headers=reader_headers, content_type='application/json') response = client.get('approver/orders', headers=approver_headers) self.assert200(response, "The request was from an approver/admin") response_data = json.loads(response.data.decode("utf-8")) for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: request_id = y['request_id'] sent2 = json.dumps({"request_id": request_id, "type": "AG", "is_access_granted": False}) response2 = client.post('approver/access', data=sent2, headers=approver_headers, content_type='application/json') self.assert200(response2, "We get some data") def test_revoke_ag_access(self): """tests to remove a ag from reader""" # skapa läsare reader_email = self.get_new_random_email() self.populate_reader(reader_email) ag_id = 2 reder_header = self.login(reader_email) # skapa ag req with app.test_client() as client: sent = json.dumps({"ag_id": ag_id, "justification": "Because i can"}) client.post('/reader/ag', data=sent, headers=reder_header, content_type='application/json') # approva ag req med approver approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: response = client.get('approver/orders', headers=approver_headers) response_data = json.loads(response.data.decode("utf-8")) for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: request_id = y['request_id'] sent2 = json.dumps({"request_id": request_id, "type": "AG", "is_access_granted": True}) client.post('approver/access', data=sent2, headers=approver_headers, content_type='application/json') with app.test_client() as client: url = url_for("approver.get_all_access_for_reader", email=reader_email) response = client.get(url, headers=approver_headers) x = json.loads(response.data.decode("utf-8")) i = 0 for y in x: try: self.assertEqual(x[y]['ag_id'], ag_id, "check that we have rooms with the ag we requested") self.assertEqual(x[y]['access'], True, "check that we access to that room") i += 1 except KeyError: pass self.assertNotEqual(i, 0, "check so we got some access") # skapa ag req with app.test_client() as client: sent = json.dumps({"ag_id": ag_id, "email": reader_email}) respone = client.post('approver/revoke/ag', data=sent, headers=approver_headers, content_type='application/json') self.assert200(response, "check that request for revoke ag is ok") response = client.get('approver/access_for_reader/{}'.format(reader_email), headers=approver_headers) x = json.loads(response.data.decode("utf-8")) i = 0 for y in x: try: self.assertEqual(x[y]['ag_id'], ag_id, "check that we have rooms with the ag we requested") self.assertEqual(x[y]['access'], True, "check that we access to that room") i += 1 except KeyError: pass self.assertEqual(i, 0, "check so dont have any access any more") def test_revoke_room_access(self): """tests to remove a room from a reader""" # skapa läsare reader_email = self.get_new_random_email() self.populate_reader(reader_email) room_id = "ing27" reader_header = self.login(reader_email) # skapa ag req with app.test_client() as client: sent = json.dumps({"room_text_id": room_id, "justification": "Because i can"}) client.post('/reader/room', data=sent, headers=reader_header, content_type='application/json') # approva ag req med approver approver_email = "b@b.b" approver_headers = self.login(approver_email) with app.test_client() as client: response = client.get('approver/orders', headers=approver_headers) response_data = json.loads(response.data.decode("utf-8")) for x in response_data: res_data = response_data[x] for y in res_data: if y['reader']['email'] == reader_email: request_id = y['request_id'] sent2 = json.dumps({"request_id": request_id, "type": "Room", "is_access_granted": True}) res = client.post('approver/access', data=sent2, headers=approver_headers, content_type='application/json') with app.test_client() as client: url = url_for("approver.get_all_access_for_reader", email=reader_email) response = client.get(url, headers=approver_headers) x = json.loads(response.data.decode("utf-8")) i = 0 for y in x: print(x[y]) try: if x[y]['name'] == "Korridor": self.assertEqual(x[y]['access'], True, "check if we have access to that room") i += 1 except KeyError: pass self.assertNotEqual(i, 0, "check so we got some access") # skapa ag req with app.test_client() as client: sent = json.dumps({"room_text_id": room_id, "email": reader_email}) respone = client.post('approver/revoke/room', data=sent, headers=approver_headers, content_type='application/json') self.assert200(response, "check that request for revoke room is ok") response = client.get('approver/access_for_reader/{}'.format(reader_email), headers=approver_headers) x = json.loads(response.data.decode("utf-8")) for y in x: try: if x[y]['name'] == "Korridor": self.assertEqual(x[y]['access'], False, "check if we dont got access to that room") except KeyError: pass class AdminRouteTest(BaseTestCase): """class for unittests for approver routes""" def test_get_all_readers_roles(self): """get all reader and their roles""" admin_headers = self.login("c@c.c") known_users = ["a@a.a", "b@b.b", "c@c.c"] with app.test_client() as client: result = client.get( 'admin/readers', headers=admin_headers, content_type='application/json', ) lenght_of_expected_list = 0 for x in json.loads(result.data.decode("utf-8")): for y in json.loads(result.data.decode("utf-8"))[x]: if y['email'] in known_users: lenght_of_expected_list += 1 self.assertEqual(len(known_users), lenght_of_expected_list, "Checks that we find the 3 users always expected") def test_upgrade_to_approver(self): """ tests uppgrade to approver with a new reader""" admin_headers = self.login("c@c.c") reader_email = self.get_new_random_email() self.populate_reader(reader_email) reader_header = self.login(reader_email) reader = Reader.query.filter_by(email=reader_email).first() self.assertNotEqual(reader, None, "check that reader exist") reader = Approver.query.filter_by(email=reader_email).first() self.assertEqual(reader, None, "check that reader is not an approver yet") with app.test_client() as client: sent = json.dumps({ "email": reader_email}) request = client.post( 'admin/upgrade_to_approver', data=sent, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") reader = Approver.query.filter_by(email=reader_email).first() self.assertNotEqual(reader, None, "check that reader now is approver") def test_upgrade_to_admin(self): """tests upgrade to admin with a reader and a approver.""" admin_headers = self.login("c@c.c") # Reader -> admin reader_email = self.get_new_random_email() self.populate_reader(reader_email) reader_header = self.login(reader_email) reader = Reader.query.filter_by(email=reader_email).first() self.assertNotEqual(reader, None, "check that reader exist") reader = Admin.query.filter_by(email=reader_email).first() self.assertEqual(reader, None, "check that reader is not an admin yet") with app.test_client() as client: sent = json.dumps({"email": reader_email}) request = client.post( 'admin/upgrade_to_admin', data=sent, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") reader = Admin.query.filter_by(email=reader_email).first() self.assertNotEqual(reader, None, "check that reader now is admin") # approver -> admin approver_email = self.get_new_random_email() self.populate_approver(approver_email) approver_header = self.login(approver_email) approver = Reader.query.filter_by(email=approver_email).first() self.assertNotEqual(approver, None, "check that reader exist") approver = Admin.query.filter_by(email=approver_email).first() self.assertEqual(approver, None, "check that reader is not an admin yet") with app.test_client() as client: sent = json.dumps({"email": approver_email}) request = client.post( 'admin/upgrade_to_admin', data=sent, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") approver = Admin.query.filter_by(email=approver_email).first() self.assertNotEqual(approver, None, "check that reader now is admin") def test_create_ag(self): """test to create an ag.""" # utökning: # requesta den nya innan och efter # testa skicka in dålig data # testa skapa dubblett av rum admin_headers = self.login("c@c.c") with app.test_client() as client: sent = json.dumps({"ag_name": "test_ag", "approvers": ["b@b.b"], "room_text_ids": ["isy1", "isy2", "isy"] }) request = client.post( 'admin/ag', data=sent, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") def test_get_reader(self): """test to get a reader with get_reader""" admin_headers = self.login("c@c.c") with app.test_client() as client: url = url_for("admin.get_reader", reader_id=46) #46 is a@a.a request = client.get( url, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") print(request.data) def test_get_all_approvers(self): """test to get all approvers with get_all_approvers""" admin_headers = self.login("c@c.c") with app.test_client() as client: request = client.get( "admin/approvers/", headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") def test_get_all_admins(self): """test to get all admins with get_all_admins""" admin_headers = self.login("c@c.c") with app.test_client() as client: request = client.get( "admin/admins/", headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") def test_get_all_rooms(self): """test to get all rooms with get_all_rooms""" admin_headers = self.login("c@c.c") with app.test_client() as client: request = client.get( "admin/rooms", headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") def test_delete_user(self): """test to remove a user""" # create and get new user reader_email = self.get_new_random_email() self.populate_reader(reader_email) reader_header = self.login(reader_email) reader = Reader.query.filter_by(email=reader_email).first() self.assertNotEqual(reader, None, "check that reader email is a user") # remove user admin_headers = self.login("c@c.c") with app.test_client() as client: url = url_for("admin.delete_user", reader_email=reader_email) request = client.delete( url, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") # try to get user again reader = Reader.query.filter_by(email=reader_email).first() self.assertEqual(reader, None, "check that reader email is a user") def test_remove_card(self): """test to block card""" admin_headers = self.login("c@c.c") with app.test_client() as client: url = url_for("admin.remove_card", email="a@a.a") request = client.delete( url, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") def test_create_reader_approver_admin(self): """test to create reader""" # reader email = self.get_new_random_email() res = self.populate_reader(email) result = res[0] self.assertStatus(result, 201) self.assertEqual(result.data, b'Reader successfully created!', "check that we created a reader") # approver email = self.get_new_random_email() res = self.populate_approver(email) result = res[0] self.assertStatus(result, 201) self.assertEqual(result.data, b'Approver successfully created!', "check that we created a Approver") # admin email = self.get_new_random_email() res = self.populate_admin(email) result = res[0] self.assertStatus(result, 201) self.assertEqual(result.data, b'Admin successfully created!', "check that we created a Admin") def test_create_duplicate_reader_approver_admin(self): """testing create_reader() with already existing email""" # reader email = self.get_new_random_email() res = self.populate_reader(email) result = res[0] self.assertStatus(result, 201) self.assertEqual(result.data, b'Reader successfully created!', "check that we created a reader") res2 = self.populate_reader(email) result2 = res2[0] self.assert400(result2, "Check so we cant create a duplicate reader with the same email as another one") # approver email = self.get_new_random_email() res = self.populate_approver(email) result = res[0] self.assertStatus(result, 201) self.assertEqual(result.data, b'Approver successfully created!', "check that we created a Approver") res2 = self.populate_approver(email) result2 = res2[0] self.assert400(result2, "Check so we cant create a duplicate reader with the same email as another one") # admin email = self.get_new_random_email() res = self.populate_admin(email) result = res[0] self.assertStatus(result, 201) self.assertEqual(result.data, b'Admin successfully created!', "check that we created a Admin") res2 = self.populate_admin(email) result2 = res2[0] self.assert400(result2, "Check so we cant create a duplicate reader with the same email as another one") def test_create_reader_approver_admin_with_bad_pass(self): """ testing create_reader() with bad passwords """ pas_lst = ["", "ABab1", "abcd1234", "ABCD123", "ABCDabcd", "aBDcµ123"] # reader for pas in pas_lst: email = self.get_new_random_email() res = self.populate_reader(email, pas) result = res[0] self.assertStatus(result, 400) # approver for pas in pas_lst: email = self.get_new_random_email() res = self.populate_approver(email, pas) result = res[0] self.assertStatus(result, 400) # admin for pas in pas_lst: email = self.get_new_random_email() res = self.populate_admin(email, pas) result = res[0] self.assertStatus(result, 400) def test_get_all_orders(self): """test to get all orders with test_get_all_orders""" admin_headers = self.login("c@c.c") with app.test_client() as client: request = client.get( "admin/orders", headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") def test_remove_ag(self): """ test to remove ag from approvers approval area with ermove_ag""" # utökning: kolla approvers yta innan och efter admin_headers = self.login("c@c.c") with app.test_client() as client: sent = json.dumps({"ag": 1, "approver": 47 # 47 is b@b.b }) request = client.post( 'admin/remove_for_approver/ag', data=sent, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok") def test_remove_room(self): """ test to remove ag from approvers approval area with ermove_ag""" # utökning: kolla approvers yta innan och efter admin_headers = self.login("c@c.c") with app.test_client() as client: sent = json.dumps({"room": "isy1", "approver": 47 # 47 is b@b.b }) request = client.post( 'admin/remove_for_approver/room', data=sent, headers=admin_headers, content_type='application/json', ) self.assert200(request, "check that request returns ok")

32.753535

118

0.696972

4,585

32,426

4.761178

0.063468

0.039304

0.049382

0.05836

0.85126

0.832203

0.810399

0.792442

0.771003

0.743976

0

0.011773

0.174829

32,426

989

119

32.786653

0.804089

0.092025

0

0.7178

0

0.219557

0.011373

0

0.118669

1

0.062229

false

0.013025

0.01013

0.001447

0.091172

0.002894

0

null

0

1

0

1

0

null

0

7

c1109e174e3865f869121103a4c5dc09b983c9f3

1,804

py

Python

src/main_floquetinit.py

gsinuco/OPENMMF

2cc0d0f2a4ded895c189050c38dbf2e8985e2d55

[ "CC-BY-4.0" ]

4

2020-05-12T19:28:12.000Z

2022-03-06T05:37:17.000Z

src/main_floquetinit.py

gsinuco/OPENMMF

2cc0d0f2a4ded895c189050c38dbf2e8985e2d55

[ "CC-BY-4.0" ]

null

src/main_floquetinit.py

gsinuco/OPENMMF

2cc0d0f2a4ded895c189050c38dbf2e8985e2d55

[ "CC-BY-4.0" ]

3

2020-05-12T19:28:13.000Z

2020-11-16T21:09:32.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Sep 7 11:03:08 2020 @author: german """ import numpy as np import openmmf as openmmf import matplotlib.pyplot as plt # INITIALISE THE DATA TYPE id = openmmf.atom_c_T() info = 0 openmmf.floquetinit(id,'qubit',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'87Rb','U',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'87Rb','L',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'87Rb','B',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'123Cs','U',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'123Cs','L',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'123Cs','B',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'41K','U',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'41K','L',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'41K','B',info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'spin',4.0,info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id) openmmf.floquetinit(id,'lattice',40.0,info=info) d_bare = id.d_bare print(d_bare) # DEALLOCATE ALL ARRAYS openmmf.deallocateall(id)

18.989474

48

0.756652

295

1,804

4.498305

0.186441

0.135644

0.180859

0.117558

0.843255

0

0.024707

0.10255

1,804

94

49

19.191489

0.794935

0.213415

0

0.679245

0

0.043665

0

1

0

false

0

0.056604

0

0.056604

0.226415

0

null

0

1

0

1

0

null

0

7

c17c35ee5c4c9d8263071fd03ba65ddd5accfa63

30,743

py

Python

examples/coevolution/plots.py

aadeshnpn/swarm

873e5d90de4a3b3f69d4edc8de55eb9311226c2e

[ "MIT" ]

9

2018-03-26T22:22:08.000Z

2021-08-30T20:45:27.000Z

examples/coevolution/plots.py

aadeshnpn/swarm

873e5d90de4a3b3f69d4edc8de55eb9311226c2e

[ "MIT" ]

1

2021-05-06T12:45:11.000Z

2021-05-12T07:21:53.000Z

examples/coevolution/plots.py

aadeshnpn/swarm

873e5d90de4a3b3f69d4edc8de55eb9311226c2e

[ "MIT" ]

1

2019-04-22T00:27:09.000Z

import os import numpy as np import scipy.stats as stats import matplotlib # If there is $DISPLAY, display the plot if os.name == 'posix' and "DISPLAY" not in os.environ: matplotlib.use('Agg') import matplotlib.pyplot as plt # noqa: E402 import glob import pathlib def read_npy(fname='all.npy'): # /tmp/olddata/ data = np.load('/tmp/olddata/' + fname) return data[:, -1] def read_data_fitness(n=100, maindir='/tmp/div/diversity_withdecay'): # maindir = '/tmp/results_site_distance/experiments/' # maindir = '/home/aadeshnpn/Desktop/evolved_ppa/experiments/' # nadir = os.path.join(maindir, str(n), agent, str(site)) folders = pathlib.Path(maindir).glob("*EvoSForgeNew*") flist = [] dataf = [] datad = [] print(maindir) for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] try: _, _, f, d = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') dataf.append(f) datad.append(d) # print(flist[0], f.shape) except IndexError: pass # print(data) dataf = np.array(dataf) datad = np.array(datad) # print(dataf.shape, datad.shape, n) return dataf # def read_data_n_agent(n=100, filename='/tmp/old.txt'): # maindir = '/tmp/swarm/data/experiments/' # files = np.genfromtxt(filename, unpack=True, autostrip=True, dtype=np.str) # data = [] # for f in files: # # print(f) # _, _, d = np.genfromtxt(str(f), autostrip=True, unpack=True, delimiter='|') # data.append(d) # data = np.array(data) # # print(data.shape) # return data def read_data_n_agent(n=100, iter=12000): maindir = '/tmp/swarm/data/experiments/EvoCoevolutionPPA/' nadir = os.path.join(maindir, str(n), str(iter)) folders = pathlib.Path(nadir).glob("*EvoCoevolutionPPA") flist = [] fdata = [] mdata = [] for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] _, _, f, m = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') fdata.append(f) mdata.append(m) fdata = np.array(fdata) mdata = np.array(mdata) print(fdata.shape, mdata.shape) return fdata, mdata def read_data_n_agent_lt(n=100, iter=12000, lt='lt'): maindir = '/tmp/swarm/data/experiments/' nadir = os.path.join(maindir, str(n), str(iter), lt) # print(nadir) folders = pathlib.Path(nadir).glob("*EvoSForgeNewPPA1") flist = [] fdata = [] mdata = [] for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] _, _, f, _ = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') fdata.append(f) fdata = np.array(fdata) return fdata def read_data_n_agent_threshold(n=100, iter=12000, threshold=10): maindir = '/tmp/swarm/data/experiments/EvoCoevolutionPPA/' nadir = os.path.join(maindir, str(n), str(iter), str(threshold)) print(nadir) folders = pathlib.Path(nadir).glob("*EvoCoevolutionPPA") flist = [] fdata = [] mdata = [] for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] _, _, f, _ = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') # print(f.shape, flist[0]) fdata.append(f) fdata = np.array(fdata) # print(fdata.shape) return fdata def read_data_n_agent_threshold_new(n=100, iter=12000, threshold=10, gstep=200, expp=2): maindir = '/tmp/swarm/data/experiments/EvoCoevolutionPPA/' nadir = os.path.join(maindir, str(n), str(iter), str(threshold), str(gstep), str(expp)) print(nadir) folders = pathlib.Path(nadir).glob("*EvoCoevolutionPPA") flist = [] fdata = [] mdata = [] for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] _, _, f, _ = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') # print(f.shape, flist[0]) fdata.append(f) fdata = np.array(fdata) # print(fdata.shape) return fdata def read_data_n_agent_perturbations( n=100, iter=12000, threshold=10, gstep=200, expp=2, addobject=None, removeobject=None, no_objects=1, radius=5, time=13000): maindir = '/tmp/swarm/data/experiments/EvoCoevolutionPPA/' nadir = os.path.join( '/tmp', 'swarm', 'data', 'experiments', 'EvoCoevolutionPPA', str(n), str(iter), str(threshold), str(gstep), str(expp), str(addobject), str(removeobject), str(no_objects), str(radius), str(time) ) print(nadir) folders = pathlib.Path(nadir).glob("*EvoCoevolutionPPA") flist = [] fdata = [] mdata = [] for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] _, _, f, _ = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') # print(f.shape, flist[0]) fdata.append(f) fdata = np.array(fdata) # print(fdata.shape) return fdata def plot_none_obstacles_trap(): fig = plt.figure(figsize=(8,6), dpi=200) none = read_data_n_agent_perturbations() obstacles = read_data_n_agent_perturbations(addobject='Obstacles', radius=10, time=2) # traps = read_data_n_agent_perturbations(addobject='Traps', radius=10, time=2) ax1 = fig.add_subplot(1, 1, 1) colordict = { 0: 'gold', 1: 'peru', 2: 'orchid', 3: 'olivedrab', 4: 'linen', 5: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] # labels = [str(a) for a in agent_sizes] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') none_mean = np.median(none, axis=0) none_q1 = np.quantile(none, q =0.25, axis=0) none_q3 = np.quantile(none, q =0.75, axis=0) obstacles_mean = np.median(obstacles, axis=0) obs_q1 = np.quantile(obstacles, q =0.25, axis=0) obs_q3 = np.quantile(obstacles, q =0.75, axis=0) print(none_q3.shape) # traps_mean = np.mean(traps, axis=1) xvalues = range(12002) ax1.plot(xvalues, none_mean, label="None", color='blue') ax1.fill_between( xvalues, none_q1, none_q3, color='DodgerBlue', alpha=0.3) ax1.plot(xvalues, obstacles_mean, label="Obstacles", color='red') ax1.fill_between( xvalues, obs_q1, obs_q3, color='tomato', alpha=0.3) # ax1.plot(range(12001), traps_mean, labels="Traps") ax1.legend(fontsize="small", loc="upper right", title='Objects') # ax1.set_xticklabels(['Foraging', 'Maintenance']) ax1.set_xlabel('Evolution Steps') ax1.set_ylabel('Foraing (%)') ax1.set_yticks(range(0, 105, 20)) plt.tight_layout() maindir = '/tmp/swarm/data/experiments/' # fname = 'agentsitecomp' + agent nadir = os.path.join(maindir, str(50)) fig.savefig( nadir + 'coevolutionobjects' + '.png') plt.close(fig) def plot_obstacles_time(): fig = plt.figure(figsize=(8,6), dpi=200) time = [1000, 2000, 3000, 4000, 5000, 6000, 7000] obstaclestime = [read_data_n_agent_perturbations(addobject='Obstacles', no_objects=5, radius=10, time=t) for t in time] ax1 = fig.add_subplot(1, 1, 1) median = [ np.median(obstaclestime[i], axis=0) for i in range(len(time))] q1 = [ np.quantile(obstaclestime[i], q=0.25, axis=0) for i in range(len(time))] q3 = [ np.quantile(obstaclestime[i], q=0.75, axis=0) for i in range(len(time))] # traps_mean = np.mean(traps, axis=1) xvalues = range(12002) for i in range(len(time)): ax1.plot(xvalues, median[i], label=str(time[i])) # ax1.fill_between( # xvalues, q1[i], q3[i], alpha=0.3) # ax1.plot(range(12001), traps_mean, labels="Traps") ax1.legend(fontsize="small", loc="upper left", title='Perturbation Timestep') # ax1.set_xticklabels(['Foraging', 'Maintenance']) ax1.set_xlabel('Evolution Steps') ax1.set_ylabel('Foraing (%)') ax1.set_yticks(range(0, 105, 20)) plt.tight_layout() maindir = '/tmp/swarm/data/experiments/' # fname = 'agentsitecomp' + agent nadir = os.path.join(maindir, str(50)) fig.savefig( nadir + 'coevolutionobstaclestime' + '.png') plt.close(fig) def read_data_n_agent_site(n=100, agent='ExecutingAgent', site='20'): maindir = '/tmp/results_site_distance/experiments/' # maindir = '/home/aadeshnpn/Desktop/evolved_ppa/experiments/' nadir = os.path.join(maindir, str(n), agent, str(site)) folders = pathlib.Path(nadir).glob("*ForagingSim*") flist = [] dataf = [] datad = [] for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file()] try: # print(flist) _, _, f, d = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') dataf.append(f) datad.append(d) except IndexError: pass # print(data) dataf = np.array(dataf) datad = np.array(datad) print(dataf.shape, datad.shape, n) return dataf, datad def read_data_time(n=100): maindir = '/home/aadeshnpn/Desktop/experiments/' # nadir = os.path.join(maindir, str(n), str(iter)) # folders = pathlib.Path(nadir).glob("*EvoSForgeNew*") data = np.genfromtxt(maindir + str(n) +'.txt', autostrip=True, unpack=True) data = np.array(data) print(data.shape) return data def read_data_n_agent_6000(n=100, iter=6000): maindir = '/home/aadeshnpn/Desktop/experiments/' nadir = os.path.join(maindir, str(n), str(iter)) folders = pathlib.Path(nadir).glob("*EvoSForgeNew*") flist = [] data = [] for f in folders: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] # print(flist) _, _, d, _ = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') # print(d.shape) data.append(d) data = np.array(data) print(data.shape) return data def plot_evolution_algo_performance(): # plt.style.use('fivethirtyeight') agent_sizes = [50, 100, 150, 200] # dataf = [read_data_n_agent_6000(n=a)[:,-1] for a in agent_sizes] # datat = [read_data_time(n=a) for a in agent_sizes] fig = plt.figure(figsize=(8,6), dpi=200) ax1 = fig.add_subplot(1, 1, 1) colordict = { 0: 'gold', 1: 'linen', 2: 'orchid', 3: 'peru', 4: 'olivedrab', 5: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] labels = [str(a) for a in agent_sizes] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') # data = [data[:, i] for i in range(4)] positions = [ [1], [4], [7], [10] ] # print(len(values_data), len(runtime_data)) datas = [ [dataf[0]], [dataf[1]], [dataf[2]], [dataf[3]], ] for j in range(len(positions)): bp1 = ax1.boxplot( datas[j], 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops, positions=positions[j], widths=0.8) for patch, color in zip(bp1['boxes'], colordict.values()): patch.set_facecolor('gold') # plt.xlim(0, len(mean)) ax2 = ax1.twinx() positions = [ [2], [5], [8], [11] ] datas = [ [datat[0]], [datat[1]], [datat[2]], [datat[3]], ] for j in range(len(positions)): bp2 = ax2.boxplot( datas[j], 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops, positions=positions[j], widths=0.8) for patch, color in zip(bp2['boxes'], colordict.values()): patch.set_facecolor('deepskyblue') ax1.legend([bp1['boxes'][0], bp2['boxes'][0]], ['Foraing (%)', 'Runtime (secs)'], fontsize="small", loc="upper left", title='Performance Metric') # ax2.legend(zip(bp2['boxes']), ['Runtime (secs)'], fontsize="small", loc="lower right", title='Performance Measures') ax1.set_xticks( [1.5, 4.5, 7.5, 10.5 ]) ax1.set_xticklabels(labels) ax1.set_xlabel('Agent size', fontsize="large") ax1.set_ylabel('Foraing (%)', fontsize="large") ax1.set_yticks(range(0, 105, 20)) ax2.set_ylabel('Runtime (Secs)', fontsize="large") ax2.set_yticks(range(0, 10000, 2000)) plt.tight_layout() maindir = '/tmp/swarm/data/experiments/' # fname = 'agentsitecomp' + agent nadir = os.path.join(maindir, str(50)) fig.savefig( nadir + 'evolutionperform2axes' + '.png') plt.close(fig) def plot_evolution_algo_performance_boxplot(): fig = plt.figure(figsize=(8,6), dpi=200) fdata, mdata = read_data_n_agent() # fdata = fdata[:, -1] # mdata = mdata[:, -1] fdata = np.max(fdata[:,1:], axis=1) mdata = np.max(mdata[:,1:], axis=1) print(fdata.shape, mdata.shape) print(fdata, mdata) ax1 = fig.add_subplot(1, 1, 1) colordict = { 0: 'gold', 1: 'peru', 2: 'orchid', 3: 'olivedrab', 4: 'linen', 5: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] # labels = [str(a) for a in agent_sizes] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') bp1 = ax1.boxplot( [fdata, mdata], 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops) for patch, color in zip(bp1['boxes'], colordict.values()): patch.set_facecolor(color) # plt.xlim(0, len(mean)) ax1.legend(zip(bp1['boxes']), ['Foraing (%)', 'Maintenance (%)'], fontsize="small", loc="upper right", title='Performance Measures') # ax1.set_xticks( # [1.5, 4.5, 7.5, 10.5 # ]) ax1.set_xticklabels(['Foraging', 'Maintenance']) ax1.set_xlabel('Evolution Efficiency') ax1.set_ylabel('Foraing (%) / Maintenace (%)') ax1.set_yticks(range(0, 105, 20)) plt.tight_layout() maindir = '/tmp/swarm/data/experiments/' # fname = 'agentsitecomp' + agent nadir = os.path.join(maindir, str(50)) fig.savefig( nadir + 'coevolutionperform' + '.png') plt.close(fig) def read_data_sample_ratio(ratio=0.1): # maindir = '/tmp/swarm/data/experiments/behavior_sampling' maindir = '/tmp/bsample/' ## Experiment ID for the plots/results in the paper # maindir = '/tmp/16244729911974EvoSForgeNewPPA1/' # maindir = '/tmp/experiments/100/12000/16243666378807EvoSForgeNewPPA1' # nadir = os.path.join(maindir, str(n), agent) # maindir = '/tmp/bsampling/' # New sampling behaviors folders = pathlib.Path(maindir).glob("*_" + str(ratio) + "_ValidateSForgeNewPPA1") flist = [] data = [] for f in folders: # print(f) try: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] _, _, d = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') # print(d.shape) data.append(d[-1]) except: pass data = np.array(data) # print(ratio, data.shape) return data def read_data_sample_ratio_ijcai(ratio=0.1): # maindir = '/tmp/swarm/data/experiments/behavior_sampling' maindir = '/tmp/ratioijcai/' ## Experiment ID for the plots/results in the paper # maindir = '/tmp/16244729911974EvoSForgeNewPPA1/' # maindir = '/tmp/experiments/100/12000/16243666378807EvoSForgeNewPPA1' # nadir = os.path.join(maindir, str(n), agent) # maindir = '/tmp/bsampling/' # New sampling behaviors folders = pathlib.Path(maindir).glob("*[0-9]*-" + str(ratio)) flist = [] data = [] for f in folders: # print(f) try: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] _, _, d = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') # print(d.shape) data.append(d[-1]) except: pass data = np.array(data) # print(ratio, data.shape) return data def read_data_n(n=100, comm=True): maindir = '/tmp/swarm/data/experiments/' if comm: folders = pathlib.Path(maindir + 'comm').glob('*SForgeNewPPAComm1') else: folders = pathlib.Path(maindir + 'withoutcomm').glob('*ForagingSimulation') flist = [] dataf = [] datad = [] for f in folders: try: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] # print(flist) _, _, f, d = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') dataf.append(f) datad.append(d) except: pass dataf = np.array(dataf) datad = np.array(datad) return dataf, datad def read_data_exp_3(width=100, height=100, trap=5, obs=5, exp_no=3, site=30, no_trap=1, no_obs=1, agent=100, grid=None, no_site=1): maindir = '/tmp/betrgeese0-4/' if grid is None: ndir = os.path.join(maindir, str(agent), 'ExecutingAgent', str(exp_no), str(site), str(trap)+'_'+str(obs), str(no_trap)+'_'+str(no_obs), str(width) +'_'+str(height), str(no_site)) else: ndir = os.path.join(maindir, str(agent), 'ExecutingAgent', str(exp_no), str(site), str(trap)+'_'+str(obs), str(no_trap)+'_'+str(no_obs), str(width) +'_'+str(height), str(no_site), str(grid)) print(ndir) folders = pathlib.Path(ndir).glob('*ForagingSimulation') flist = [] dataf = [] datad = [] for f in folders: try: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] # print(flist) _, _, f, d = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') dataf.append(f) datad.append(d) except: pass dataf = np.array(dataf) datad = np.array(datad) return dataf, datad def read_data_exp_3_bt(width=100, height=100, trap=0, obs=0, exp_no=3, site=30, no_trap=0, no_obs=0, agent=100, grid=None, no_site=1): maindir = '/tmp/geesebt0-4/' if grid is None: ndir = os.path.join(maindir, str(agent), 'ExecutingAgent', str(exp_no), str(site), str(trap)+'_'+str(obs), str(no_trap)+'_'+str(no_obs), str(width) +'_'+str(height), str(no_site)) else: ndir = os.path.join(maindir, str(agent), 'ExecutingAgent', str(exp_no), str(site), str(trap)+'_'+str(obs), str(no_trap)+'_'+str(no_obs), str(width) +'_'+str(height), str(no_site), str(grid)) print(ndir) folders = pathlib.Path(ndir).glob('*ForagingSimulationOld') flist = [] dataf = [] # datad = [] for f in folders: try: flist = [p for p in pathlib.Path(f).iterdir() if p.is_file() and p.match('simulation.csv')] # print(flist) _, _, forgingp = np.genfromtxt(flist[0], autostrip=True, unpack=True, delimiter='|') # print(f, forgingp.shape) dataf.append(forgingp) # datad.append(d) except: pass dataf = np.array(dataf) # datad = np.array(datad) return dataf ## Command to count the occurance of PPA sub-tree in each evolved behavior # find $PWD -type f -name "*.json" | xargs cat | awk -F ',' '{for(i=1;i<=NF;i++){print $i;}}' # | awk -F'<Act>' 'NF{print NF-1}' | awk '{a[$1]++}END{for(x in a)print a[x]"="x}' def withWithoutLt(): fig = plt.figure(figsize=(8,6), dpi=200) ltdata = read_data_n_agent_lt(n=50, iter=12000, lt='lt') noltdata = read_data_n_agent_lt(n=50, iter=12000, lt='nolt') # print(ltdata) ltdata = ltdata[:, -1] noltdata = noltdata[:, -1] # fdata = np.max(fdata[:,1:], axis=1) # mdata = np.max(mdata[:,1:], axis=1) # print(ltdata, noltdata) ax1 = fig.add_subplot(1, 1, 1) colordict = { 5: 'gold', 1: 'peru', 2: 'orchid', 3: 'olivedrab', 4: 'linen', 0: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] # labels = [str(a) for a in agent_sizes] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') bp1 = ax1.boxplot( [noltdata, ltdata], 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops) for patch, color in zip(bp1['boxes'], colordict.values()): patch.set_facecolor(color) # plt.xlim(0, len(mean)) ax1.legend(zip(bp1['boxes']), ['Disabled', 'Enabled'], fontsize="small", loc="upper right", title='Lateral Transfer') # ax1.set_xticks( # [1.5, 4.5, 7.5, 10.5 # ]) ax1.set_xticklabels(['Disabled', 'Enabled']) ax1.set_xlabel('Lateral Transfer') ax1.set_ylabel('Foraing (%)') ax1.set_yticks(range(0, 105, 20)) plt.tight_layout() maindir = '/tmp/swarm/data/experiments/' # fname = 'agentsitecomp' + agent nadir = os.path.join(maindir, str(50)) fig.savefig( nadir + 'lateraltransferperform' + '.png') plt.close(fig) def storage_threshold_new(): thresholds = [5, 7, 11, 13, 17] data50 = [read_data_n_agent_threshold_new(n=50, iter=12000, threshold=t, gstep=200, expp=2)[:,-1] for t in thresholds] # data100 = [read_data_n_agent_threshold(n=100, iter=12000, threshold=t)[:,-1] for t in thresholds] fig = plt.figure(figsize=(8,6), dpi=200) ax1 = fig.add_subplot(1, 1, 1) colordict = { 0: 'gold', 1: 'linen', 2: 'orchid', 3: 'peru', 4: 'olivedrab', 5: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] # labels = [ "> n/"+str(a) for a in thresholds] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') positions = [ [1, 2], [4, 5], [7, 8], [10, 11], [13, 14] ] # datas = [ # [data50[0], data100[0]], # [data50[1], data100[1]], # [data50[2], data100[2]], # [data50[3], data100[3]], # [data50[4], data100[4]], # # [np.zeros(np.shape(datas50[4])), data100[5]], # ] # for j in range(len(positions)): bp1 = ax1.boxplot( data50, 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops, widths=0.8) for patch, color in zip(bp1['boxes'], colordict.values()): patch.set_facecolor(color) # ax1.legend(zip(bp1['boxes']), ['50', '100'], fontsize="small", loc="upper left", title='Agent Population (n)') ax1.legend(zip(bp1['boxes']), thresholds, fontsize="small", loc="upper right", title='Storage Threshold') # ax1.set_xticks([1.5, 4.5, 7.5, 10.5, 13.5]) ax1.set_xticklabels(thresholds) ax1.set_yticks(range(0, 105, 20)) ax1.set_xlabel('Storage Threshold', fontsize="large") ax1.set_ylabel('Foraging (%)', fontsize="large") plt.tight_layout() maindir = '/tmp/swarm/data/experiments' fname = 'thresholdboxplotnew' fig.savefig( maindir + '/' + fname + '.png') # pylint: disable = E1101 plt.close(fig) def exploration_parameter(): exploration = [1, 2, 3, 4, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 47, 50, 60, 70, 80] data50 = [read_data_n_agent_threshold_new(n=50, iter=12000, threshold=5, gstep=200, expp=e)[:,-1] for e in exploration] # data100 = [read_data_n_agent_threshold(n=100, iter=12000, threshold=t)[:,-1] for t in thresholds] fig = plt.figure(figsize=(8,6), dpi=200) ax1 = fig.add_subplot(1, 1, 1) colordict = { 0: 'gold', 1: 'linen', 2: 'orchid', 3: 'peru', 4: 'olivedrab', 5: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] # labels = [ "> n/"+str(a) for a in thresholds] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') positions = [ [1, 2], [4, 5], [7, 8], [10, 11], [13, 14] ] # datas = [ # [data50[0], data100[0]], # [data50[1], data100[1]], # [data50[2], data100[2]], # [data50[3], data100[3]], # [data50[4], data100[4]], # # [np.zeros(np.shape(datas50[4])), data100[5]], # ] # for j in range(len(positions)): bp1 = ax1.boxplot( data50, 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops, widths=0.8) for patch, color in zip(bp1['boxes'], colordict.values()): patch.set_facecolor(color) # ax1.legend(zip(bp1['boxes']), ['50', '100'], fontsize="small", loc="upper left", title='Agent Population (n)') ax1.legend(zip(bp1['boxes']), exploration, fontsize="small", loc="upper right", title='Exploration') # ax1.set_xticks([1.5, 4.5, 7.5, 10.5, 13.5]) ax1.set_xticklabels(exploration) ax1.set_yticks(range(0, 105, 20)) ax1.set_xlabel('Exploration', fontsize="large") ax1.set_ylabel('Foraging (%)', fontsize="large") plt.tight_layout() maindir = '/tmp/swarm/data/experiments' fname = 'explorationboxplotnew' fig.savefig( maindir + '/' + fname + '.png') # pylint: disable = E1101 plt.close(fig) def generationstep_parameter(): gsteps = [25, 50, 75, 100, 150, 200, 250, 300, 400, 500] data50 = [read_data_n_agent_threshold_new(n=50, iter=12000, threshold=5, gstep=g, expp=2)[:,-1] for g in gsteps] # data100 = [read_data_n_agent_threshold(n=100, iter=12000, threshold=t)[:,-1] for t in thresholds] fig = plt.figure(figsize=(8,6), dpi=200) ax1 = fig.add_subplot(1, 1, 1) colordict = { 0: 'gold', 1: 'linen', 2: 'orchid', 3: 'peru', 4: 'olivedrab', 5: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] # labels = [ "> n/"+str(a) for a in thresholds] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') positions = [ [1, 2], [4, 5], [7, 8], [10, 11], [13, 14] ] # datas = [ # [data50[0], data100[0]], # [data50[1], data100[1]], # [data50[2], data100[2]], # [data50[3], data100[3]], # [data50[4], data100[4]], # # [np.zeros(np.shape(datas50[4])), data100[5]], # ] # for j in range(len(positions)): bp1 = ax1.boxplot( data50, 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops, widths=0.8) for patch, color in zip(bp1['boxes'], colordict.values()): patch.set_facecolor(color) # ax1.legend(zip(bp1['boxes']), ['50', '100'], fontsize="small", loc="upper left", title='Agent Population (n)') ax1.legend(zip(bp1['boxes']), gsteps, fontsize="small", loc="upper right", title='GenerationSteps') # ax1.set_xticks([1.5, 4.5, 7.5, 10.5, 13.5]) ax1.set_xticklabels(gsteps) ax1.set_yticks(range(0, 105, 20)) ax1.set_xlabel('Generation Steps', fontsize="large") ax1.set_ylabel('Foraging (%)', fontsize="large") plt.tight_layout() maindir = '/tmp/swarm/data/experiments' fname = 'generationstepboxplotnew' fig.savefig( maindir + '/' + fname + '.png') # pylint: disable = E1101 plt.close(fig) def storage_threshold(): thresholds = [5, 7, 11, 13, 17] data50 = [read_data_n_agent_threshold(n=50, iter=12000, threshold=t)[:,-1] for t in thresholds] # data100 = [read_data_n_agent_threshold(n=100, iter=12000, threshold=t)[:,-1] for t in thresholds] fig = plt.figure(figsize=(8,6), dpi=200) ax1 = fig.add_subplot(1, 1, 1) colordict = { 0: 'gold', 1: 'linen', 2: 'orchid', 3: 'peru', 4: 'olivedrab', 5: 'indianred', 6: 'tomato'} colorshade = [ 'springgreen', 'lightcoral', 'khaki', 'lightsalmon', 'deepskyblue'] # labels = [ "> n/"+str(a) for a in thresholds] medianprops = dict(linewidth=2.5, color='firebrick') meanprops = dict(linewidth=2.5, color='#ff7f0e') positions = [ [1, 2], [4, 5], [7, 8], [10, 11], [13, 14] ] # datas = [ # [data50[0], data100[0]], # [data50[1], data100[1]], # [data50[2], data100[2]], # [data50[3], data100[3]], # [data50[4], data100[4]], # # [np.zeros(np.shape(datas50[4])), data100[5]], # ] # for j in range(len(positions)): bp1 = ax1.boxplot( data50, 0, 'gD', showmeans=True, meanline=True, patch_artist=True, medianprops=medianprops, meanprops=meanprops, widths=0.8) for patch, color in zip(bp1['boxes'], colordict.values()): patch.set_facecolor(color) # ax1.legend(zip(bp1['boxes']), ['50', '100'], fontsize="small", loc="upper left", title='Agent Population (n)') ax1.legend(zip(bp1['boxes']), thresholds, fontsize="small", loc="upper right", title='Storage Threshold') # ax1.set_xticks([1.5, 4.5, 7.5, 10.5, 13.5]) ax1.set_xticklabels(thresholds) ax1.set_yticks(range(0, 105, 20)) ax1.set_xlabel('Storage Threshold', fontsize="large") ax1.set_ylabel('Foraging (%)', fontsize="large") plt.tight_layout() maindir = '/tmp/swarm/data/experiments' fname = 'thresholdboxplot' fig.savefig( maindir + '/' + fname + '.png') # pylint: disable = E1101 plt.close(fig) def main(): # plot_evolution_algo_performance_boxplot() # plot_evolution_algo_performance() # withWithoutLt() # storage_threshold_new() # exploration_parameter() # generationstep_parameter() # plot_none_obstacles_trap() plot_obstacles_time() if __name__ == '__main__': main()

34.895573

149

0.592753

4,008

30,743

4.455589

0.090818

0.014447

0.012599

0.018815

0.82428

0.787994

0.760947

0.741908

0.729085

0.71867

0

0.05596

0.235631

30,743

881

150

34.895573

0.703987

0.194418

0

0.705491

0

0.132563

0.03184

0

1

0.041597

false

0.011647

0

0.078203

0.021631

0

null

0

1

0

1

0

null

0

7

c1911f4b48d5cc9de88e37f03fbf92bdddc7e127

531

py

Python

python/testData/refactoring/inlinelocal/operatorPrecedence/power.after.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/refactoring/inlinelocal/operatorPrecedence/power.after.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/refactoring/inlinelocal/operatorPrecedence/power.after.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

(10 ** 2)[::-5] (10 ** 2)[5] (10 ** 2)(5) (10 ** 2).foo -(10 ** 2) +(10 ** 2) ~(10 ** 2) 5 ** 10 ** 2 (10 ** 2) ** 5 5 * 10 ** 2 10 ** 2 * 5 5 / 10 ** 2 10 ** 2 / 5 5 // 10 ** 2 10 ** 2 // 5 5 + 10 ** 2 10 ** 2 + 5 10 ** 2 - 5 5 - 10 ** 2 5 >> 10 ** 2 10 ** 2 << 5 5 & 10 ** 2 10 ** 2 & 5 5 ^ 10 ** 2 10 ** 2 ^ 5 5 | 10 ** 2 10 ** 2 | 5 () in 10 ** 2 10 ** 2 in () 5 is 10 ** 2 10 ** 2 is 5 5 < 10 ** 2 10 ** 2 < 5 not 10 ** 2 5 and 10 ** 2 10 ** 2 and 5 5 or 10 ** 2 10 ** 2 or 5 10 ** 2 if 10 ** 2 else 10 ** 2

9.155172

31

0.346516

125

531

1.472

0.088

0.668478

0.369565

0.521739

0.597826

0.586957

0.505435

0.423913

0

0.470948

0.384181

531

57

32

9.315789

0.091743

0

1

0

true

0

1

null

1

0

1

0

1

0

null

0

1

0

7

a9c94e499332d60ec3ecca15bbcb160ef660cf84

55,333

py

Python

tschartslib/dentalstate/dentalstate.py

DaleProctor/tscharts

5447395e0aef0b949bef8426febdec2093cf37ef

[ "Apache-2.0" ]

16

2016-08-17T21:39:10.000Z

2021-11-24T12:14:28.000Z

tschartslib/dentalstate/dentalstate.py

DaleProctor/tscharts

5447395e0aef0b949bef8426febdec2093cf37ef

[ "Apache-2.0" ]

55

2017-04-23T18:12:04.000Z

2021-08-08T08:25:18.000Z

tschartslib/dentalstate/dentalstate.py

DaleProctor/tscharts

5447395e0aef0b949bef8426febdec2093cf37ef

[ "Apache-2.0" ]

8

2017-08-11T02:11:46.000Z

2021-07-06T22:58:42.000Z

#(C) Copyright Syd Logan 2020 #(C) Copyright Thousand Smiles Foundation 2020 # #Licensed under the Apache License, Version 2.0 (the "License"); #you may not use this file except in compliance with the License. # #You may obtain a copy of the License at #http://www.apache.org/licenses/LICENSE-2.0 # #Unless required by applicable law or agreed to in writing, software #distributed under the License is distributed on an "AS IS" BASIS, #WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #See the License for the specific language governing permissions and #limitations under the License. ''' unit tests for dental state application. Assumes django server is up and running on the specified host and port ''' import unittest import getopt, sys import json from tschartslib.service.serviceapi import ServiceAPI from tschartslib.tscharts.tscharts import Login, Logout from tschartslib.patient.patient import CreatePatient, DeletePatient from tschartslib.clinic.clinic import CreateClinic, DeleteClinic from tschartslib.dentalcdt.dentalcdt import CreateDentalCDT, DeleteDentalCDT import random import string import itertools def breakout(csv): #print("breakout csv {}".format(csv)) ret = [] x = csv.split(",") #print("breakout x {}".format(x)) for y in x: ret.append(y.strip()) #print("breakout ret {}".format(ret)) ret.sort() #print("breakout sorted ret {}".format(ret)) return ret def permuteAsCSV(strs): #print("permuteAsCSV strs {}".format(strs)) l = list(itertools.permutations(strs)) #print("permuteAsCSV l {}".format(l)) csvs = [] for x in l: y = list(x) ret = "" for z in y: if len(ret): ret += "," ret += z csvs.append(ret) #print("permuteAsCSV csvs {}".format(csvs)) return csvs def equalSurfaces(a, b): return a == b class DentalStateGenerator(): integerFields = [ "tooth", ] booleanFields = [ ] textFields = [ "username", "comment", ] stateFields = [ "state", ] surfaceFields = [ "surface", ] locationFields = [ "location", ] booleanStrings = ["true", "false"] locationStrings = ["top", "bottom"] stateStrings = ["missing", "none", "untreated", "treated", "other"] surfaceStrings = ["none", "buccal", "lingual", "mesial", "occlusal", "labial", "incisal", "other"] junkKeys = ["jadda", "fooboo", "yeehad"] junkStateStrings = ["sdfsdf", "9999", "UnTrEaTeD", "TrEaTeD", "noNe"] junkSurfaceStrings = junkStateStrings junkLocationStrings = junkStateStrings junkBooleanStrings = ["True", "trUe", "FAlse", "faLSE", "", None] junkTextStrings = [2654, 3.141592654] def getRandomJunkKey(self): i = random.randrange(len(self.junkKeys)) return self.junkKeys[i] def getRandomJunkBoolean(self): i = random.randrange(len(self.junkBooleanStrings)) return self.junkBooleanStrings[i] def getRandomJunkText(self, size): i = random.randrange(len(self.junkTextStrings)) return self.junkTextStrings[i] def getRandomJunkState(self): i = random.randrange(len(self.junkStateStrings)) return self.junkStateStrings[i] def getRandomJunkSurface(self): i = random.randrange(len(self.junkSurfaceStrings)) return self.junkSurfaceStrings[i] def getRandomJunkLocation(self): i = random.randrange(len(self.junkLocationStrings)) return self.junkLocationStrings[i] def getRandomBoolean(self): i = random.randrange(len(self.booleanStrings)) return self.booleanStrings[i] def getRandomText(self, size): return ''.join([random.choice(string.ascii_letters + string.digits) for n in xrange(size)]) def getRandomState(self): i = random.randrange(len(self.stateStrings)) return self.stateStrings[i] def getRandomSurface(self): i = random.randrange(len(self.surfaceStrings)) return self.surfaceStrings[i] def getRandomLocation(self): i = random.randrange(len(self.locationStrings)) return self.locationStrings[i] def getRandomInteger(self): i = random.randint(-999, 999) return i def createPayloadBody(self, full): # full True if POST, False for random PUT payload = {} for x in self.integerFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomInteger() for x in self.stateFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomState() for x in self.surfaceFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomSurface() for x in self.locationFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomLocation() for x in self.booleanFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomBoolean() count = 0 # len 0, 1, 2, 3, ... for x in self.textFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomText(count) if x == "username" and len(payload[x]) == 0: payload[x] = "username" count += 1 return payload def createJunkPayloadBody(self, full, junkKeys): payload = {} if junkKeys: for x in range(0, 100): payload[self.getRandomText(10)] = self.getRandomJunkState() for x in range(0, 100): payload[self.getRandomText(10)] = self.getRandomJunkSurface() for x in range(0, 100): payload[self.getRandomText(10)] = self.getRandomJunkBoolean() else: for x in self.integerFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomInteger() for x in self.stateFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomJunkState() for x in self.booleanFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomJunkBoolean() count = 0 # len 0, 1, 2, 3, ... for x in self.textFields: if full or (not full and self.getRandomBoolean()): payload[x] = self.getRandomJunkText(count) count += 1 return payload class CreateDentalState(ServiceAPI): def __init__(self, host, port, token): super(CreateDentalState, self).__init__() self.setHttpMethod("POST") self.setHost(host) self.setPort(port) self.setToken(token) self._payload = {} self.setPayload(self._payload) self.setURL("tscharts/v1/dentalstate/") def setClinic(self, val): self._payload["clinic"] = val self.setPayload(self._payload) def setPatient(self, val): self._payload["patient"] = val self.setPayload(self._payload) def setUsername(self, val): self._payload["username"] = val self.setPayload(self._payload) def setTooth(self, val): self._payload["tooth"] = val self.setPayload(self._payload) def setLocation(self, val): self._payload["location"] = val self.setPayload(self._payload) def setCode(self, val): self._payload["code"] = val self.setPayload(self._payload) def setState(self, val): self._payload["state"] = val self.setPayload(self._payload) def setSurface(self, val): self._payload["surface"] = val self.setPayload(self._payload) def setComment(self, val): self._payload["comment"] = val self.setPayload(self._payload) def createPayloadBody(self): generator = DentalStateGenerator() body = generator.createPayloadBody(True) self._payload = body self.setPayload(self._payload) return body def createJunkPayloadBody(self, junkKeys): generator = DentalStateGenerator() body = generator.createJunkPayloadBody(True, junkKeys) self._payload = body self.setPayload(self._payload) return body class GetDentalState(ServiceAPI): def makeURL(self): hasQArgs = False if not self._id == None: base = "tscharts/v1/dentalstate/{}/".format(self._id) else: base = "tscharts/v1/dentalstate/" if not self._clinic == None: if not hasQArgs: base += "?" else: base += "&" base += "clinic={}".format(self._clinic) hasQArgs = True if not self._patient == None: if not hasQArgs: base += "?" else: base += "&" base += "patient={}".format(self._patient) hasQArgs = True if not self._username == None: if not hasQArgs: base += "?" else: base += "&" base += "username={}".format(self._username) hasQArgs = True if not self._tooth == None: if not hasQArgs: base += "?" else: base += "&" base += "tooth={}".format(self._tooth) hasQArgs = True if not self._location == None: if not hasQArgs: base += "?" else: base += "&" base += "location={}".format(self._location) hasQArgs = True if not self._code == None: if not hasQArgs: base += "?" else: base += "&" base += "code={}".format(self._code) hasQArgs = True if not self._state == None: if not hasQArgs: base += "?" else: base += "&" base += "state={}".format(self._state) hasQArgs = True if not self._surface == None: if not hasQArgs: base += "?" else: base += "&" base += "surface={}".format(self._surface) hasQArgs = True if not self._comment == None: if not hasQArgs: base += "?" else: base += "&" base += "comment={}".format(self._comment) hasQArgs = True self.setURL(base) def __init__(self, host, port, token): super(GetDentalState, self).__init__() self.setHttpMethod("GET") self.setHost(host) self.setPort(port) self.setToken(token) self._clinic = None self._patient = None self._username = None self._location = None self._tooth = None self._code = None self._state = None self._surface = None self._comment = None self._id = None self.makeURL() def setId(self, id): self._id = id; self.makeURL() def setClinic(self, val): self._clinic = val self.makeURL() def setPatient(self, val): self._patient = val self.makeURL() def setUsername(self, val): self._username = val self.makeURL() def setTooth(self, val): self._tooth = val self.makeURL() def setLocation(self, val): self._location = val self.makeURL() def setCode(self, val): self._code = val self.makeURL() def setState(self, val): self._state = val self.makeURL() def setSurface(self, val): self._surface = val self.makeURL() def setComment(self, val): self._comment = val self.makeURL() class UpdateDentalState(ServiceAPI): def __init__(self, host, port, token, id): super(UpdateDentalState, self).__init__() self.setHttpMethod("PUT") self.setHost(host) self.setPort(port) self.setToken(token) self._payload = {} self.setPayload(self._payload) self.setURL("tscharts/v1/dentalstate/{}/".format(id)) def setClinic(self, val): self._payload["clinic"] = val self.setPayload(self._payload) def setPatient(self, val): self._payload["patient"] = val self.setPayload(self._payload) def setUsername(self, val): self._payload["username"] = val self.setPayload(self._payload) def setTooth(self, val): self._payload["tooth"] = val self.setPayload(self._payload) def setLocation(self, val): self._payload["location"] = val self.setPayload(self._payload) def setCode(self, val): self._payload["code"] = val self.setPayload(self._payload) def setState(self, val): self._payload["state"] = val self.setPayload(self._payload) def setSurface(self, val): self._payload["surface"] = val self.setPayload(self._payload) def setComment(self, val): self._payload["comment"] = val self.setPayload(self._payload) def createPayloadBody(self): generator = DentalStateGenerator() body = generator.createPayloadBody(False) self._payload = body self.setPayload(self._payload) return body def createJunkPayloadBody(self, junkKeys): generator = DentalStateGenerator() body = generator.createJunkPayloadBody(False, junkKeys) self._payload = body self.setPayload(self._payload) return body class DeleteDentalState(ServiceAPI): def __init__(self, host, port, token, id): super(DeleteDentalState, self).__init__() self.setHttpMethod("DELETE") self.setHost(host) self.setPort(port) self.setToken(token) self.setURL("tscharts/v1/dentalstate/{}/".format(id)) class TestTSDentalState(unittest.TestCase): def setUp(self): login = Login(host, port, username, password) ret = login.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("token" in ret[1]) global token token = ret[1]["token"] def testCreateDentalState(self): x = CreateClinic(host, port, token, "Ensenada", "02/05/2016", "02/06/2016") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("id" in ret[1]) clinicid = int(ret[1]["id"]) data = {} data["paternal_last"] = "abcd1234" data["maternal_last"] = "yyyyyy" data["first"] = "zzzzzzz" data["middle"] = "" data["suffix"] = "Jr." data["prefix"] = "" data["dob"] = "04/01/1962" data["gender"] = "Female" data["street1"] = "1234 First Ave" data["street2"] = "" data["city"] = "Ensenada" data["colonia"] = "" data["state"] = u"Baja California" data["phone1"] = "1-111-111-1111" data["phone2"] = "" data["email"] = "patient@example.com" data["emergencyfullname"] = "Maria Sanchez" data["emergencyphone"] = "1-222-222-2222" data["emergencyemail"] = "maria.sanchez@example.com" x = CreatePatient(host, port, token, data) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) patientid = int(ret[1]["id"]) x = CreateDentalCDT(host, port, token) x.setCode("D1234") x.setCategory("Some category") x.setDesc("Some description") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) codeid = int(ret[1]["id"]) x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setPatient(patientid) x.setClinic(clinicid) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("clinic" in ret[1]) clinicId = int(ret[1]["clinic"]) self.assertTrue(clinicId == clinicid) self.assertTrue("patient" in ret[1]) patientId = int(ret[1]["patient"]) self.assertTrue(patientId == patientid) self.assertTrue("code" in ret[1]) codeId = int(ret[1]["code"]) self.assertTrue(codeId == codeid) data = ret[1] for x in body: self.assertTrue(x in data) self.assertTrue(body[x] == data[x]) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 404) # not found # non-existent clinic param x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(9999) x.setPatient(patientid) x.setCode(codeid) x.setLocation("top") ret = x.send(timeout=30) self.assertEqual(ret[0], 404) # non-existent patient param x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(9999) x.setCode(codeid) x.setLocation("top") ret = x.send(timeout=30) self.assertEqual(ret[0], 404) # non-existent code param x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setLocation("top") x.setCode(9999) ret = x.send(timeout=30) self.assertEqual(ret[0], 404) # no data x = CreateDentalState(host, port, token) x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) # invalid data x = CreateDentalState(host, port, token) body = x.createJunkPayloadBody(False) x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) body = x.createJunkPayloadBody(True) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) # missing username x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) x.setUsername(None) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) # test each setter # tooth x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) x.setTooth(15) x.setLocation("top") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["tooth"], 15) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # code x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["code"], codeid) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # state states = DentalStateGenerator.stateStrings for state in states: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setSurface("none") x.setState(state) x.setLocation("top") x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["state"], state) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # location locations = DentalStateGenerator.locationStrings for location in locations: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setSurface("none") x.setState("none") x.setLocation(location) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["location"], location) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # surface surfaces = permuteAsCSV(DentalStateGenerator.surfaceStrings) for surface in surfaces: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setState("none") x.setSurface(surface) x.setLocation("top") sf1 = breakout(surface) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) sf2 = breakout(ret[1]["surface"]) self.assertTrue(equalSurfaces(sf1, sf2)) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # comment x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) x.setComment("a comment here") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["comment"], "a comment here") x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # test each search # tooth x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) x.setTooth(15) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setTooth(15) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["id"], id) self.assertEqual(ret[1][0]["tooth"], 15) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # code x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["id"], id) self.assertEqual(ret[1][0]["code"], codeid) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # state states = ["missing", "none", "treated", "untreated", "other"] badstates = ["yabba", "dabba", "doo"] for state in states: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setState(state) x.setSurface("none") x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setState(state) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["state"], state) self.assertEqual(ret[1][0]["id"], id) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) for state in states: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setSurface("none") x.setState(state) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) for badstate in badstates: x = GetDentalState(host, port, token) x.setState(badstate) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # location locations = DentalStateGenerator.locationStrings badlocations = DentalStateGenerator.junkLocationStrings for location in locations: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setState("none") x.setLocation(location) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setLocation(location) ret = x.send(timeout=30) #print("ret {}".format(ret)) #print("len of ret[1] {}".format(len(ret[1]))) #print("ret[1] {}".format(ret[1])) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["location"], location) self.assertEqual(ret[1][0]["id"], id) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) for location in locations: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setState("none") x.setLocation(location) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) for badlocation in badlocations: x = GetDentalState(host, port, token) x.setLocation(badlocation) #print("getting badsurface {}".format(badsurface)) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # surface surfaces = DentalStateGenerator.surfaceStrings badsurfaces = DentalStateGenerator.junkSurfaceStrings for surface in surfaces: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setState("none") x.setSurface(surface) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setSurface(surface) ret = x.send(timeout=30) #print("ret {}".format(ret)) #print("len of ret[1] {}".format(len(ret[1]))) #print("ret[1] {}".format(ret[1])) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["state"], "none") self.assertEqual(ret[1][0]["id"], id) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) for surface in surfaces: x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setState("none") x.setSurface(surface) x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) for badsurface in badsurfaces: x = GetDentalState(host, port, token) x.setSurface(badsurface) #print("getting badsurface {}".format(badsurface)) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) # comment x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setClinic(clinicid) x.setPatient(patientid) x.setCode(codeid) x.setComment("a comment here") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setComment("a comment here") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["comment"], "a comment here") self.assertEqual(ret[1][0]["id"], id) x = GetDentalState(host, port, token) x.setComment("a ") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["comment"], "a comment here") self.assertEqual(ret[1][0]["id"], id) x = GetDentalState(host, port, token) x.setComment("comment") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["comment"], "a comment here") self.assertEqual(ret[1][0]["id"], id) x = GetDentalState(host, port, token) x.setComment("here") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["comment"], "a comment here") self.assertEqual(ret[1][0]["id"], id) x = GetDentalState(host, port, token) x.setComment("com") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["comment"], "a comment here") self.assertEqual(ret[1][0]["id"], id) x = GetDentalState(host, port, token) x.setComment(" ") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1][0]["comment"], "a comment here") self.assertEqual(ret[1][0]["id"], id) x = GetDentalState(host, port, token) x.setComment("fooboo") ret = x.send(timeout=30) self.assertEqual(ret[0], 404) # cleanup x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteClinic(host, port, token, clinicid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeletePatient(host, port, token, patientid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteDentalCDT(host, port, token, codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) def testDeleteDentalState(self): x = CreateClinic(host, port, token, "Ensenada", "02/05/2016", "02/06/2016") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("id" in ret[1]) clinicid = int(ret[1]["id"]) data = {} data["paternal_last"] = "abcd1234" data["maternal_last"] = "yyyyyy" data["first"] = "zzzzzzz" data["middle"] = "" data["suffix"] = "Jr." data["prefix"] = "" data["dob"] = "04/01/1962" data["gender"] = "Female" data["street1"] = "1234 First Ave" data["street2"] = "" data["city"] = "Ensenada" data["colonia"] = "" data["state"] = u"Baja California" data["phone1"] = "1-111-111-1111" data["phone2"] = "" data["email"] = "patient@example.com" data["emergencyfullname"] = "Maria Sanchez" data["emergencyphone"] = "1-222-222-2222" data["emergencyemail"] = "maria.sanchez@example.com" x = CreatePatient(host, port, token, data) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) patientid = int(ret[1]["id"]) x = CreateDentalCDT(host, port, token) x.setCode("D4321") x.setCategory("Another category") x.setDesc("Another description") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) codeid = int(ret[1]["id"]) x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setPatient(patientid) x.setClinic(clinicid) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 404) # not found x = DeleteDentalState(host, port, token, 9999) ret = x.send(timeout=30) self.assertEqual(ret[0], 404) x = DeleteDentalState(host, port, token, None) ret = x.send(timeout=30) self.assertEqual(ret[0], 404) x = DeleteDentalState(host, port, token, "") ret = x.send(timeout=30) self.assertEqual(ret[0], 400) x = DeleteDentalState(host, port, token, "Hello") ret = x.send(timeout=30) self.assertEqual(ret[0], 404) x = DeleteDentalCDT(host, port, token, codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteClinic(host, port, token, clinicid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeletePatient(host, port, token, patientid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) def testUpdateDentalState(self): x = CreateClinic(host, port, token, "Ensenada", "02/05/2016", "02/06/2016") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("id" in ret[1]) clinicid = int(ret[1]["id"]) data = {} data["paternal_last"] = "abcd1234" data["maternal_last"] = "yyyyyy" data["first"] = "zzzzzzz" data["middle"] = "" data["suffix"] = "Jr." data["prefix"] = "" data["dob"] = "04/01/1962" data["gender"] = "Female" data["street1"] = "1234 First Ave" data["street2"] = "" data["city"] = "Ensenada" data["colonia"] = "" data["state"] = u"Baja California" data["phone1"] = "1-111-111-1111" data["phone2"] = "" data["email"] = "patient@example.com" data["emergencyfullname"] = "Maria Sanchez" data["emergencyphone"] = "1-222-222-2222" data["emergencyemail"] = "maria.sanchez@example.com" x = CreatePatient(host, port, token, data) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) patientid = int(ret[1]["id"]) x = CreateDentalCDT(host, port, token) x.setCode("D6655") x.setCategory("Yet another category") x.setDesc("Yet another description") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) codeid = int(ret[1]["id"]) x = CreateDentalState(host, port, token) body = x.createPayloadBody() x.setPatient(patientid) x.setClinic(clinicid) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) id = int(ret[1]["id"]) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("clinic" in ret[1]) clinicId = int(ret[1]["clinic"]) self.assertTrue(clinicId == clinicid) self.assertTrue("patient" in ret[1]) patientId = int(ret[1]["patient"]) self.assertTrue(patientId == patientid) self.assertTrue("code" in ret[1]) codeId = int(ret[1]["code"]) self.assertTrue(codeId == codeid) x = UpdateDentalState(host, port, token, id) body = x.createPayloadBody() ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("clinic" in ret[1]) clinicId = int(ret[1]["clinic"]) self.assertTrue(clinicId == clinicid) self.assertTrue("patient" in ret[1]) patientId = int(ret[1]["patient"]) self.assertTrue(patientId == patientid) self.assertTrue("code" in ret[1]) codeId = int(ret[1]["code"]) self.assertTrue(codeId == codeid) for x in body: self.assertTrue(x in ret[1]) self.assertTrue(body[x] == ret[1][x]) for i in xrange(0, 500): x = UpdateDentalState(host, port, token, id) body = x.createPayloadBody() ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("clinic" in ret[1]) clinicId = int(ret[1]["clinic"]) self.assertTrue(clinicId == clinicid) self.assertTrue("patient" in ret[1]) patientId = int(ret[1]["patient"]) self.assertTrue(patientId == patientid) self.assertTrue("code" in ret[1]) codeId = int(ret[1]["code"]) self.assertTrue(codeId == codeid) for x in body: self.assertTrue(x in ret[1]) self.assertTrue(body[x] == ret[1][x]) for i in xrange(0, 500): x = UpdateDentalState(host, port, token, id) body = x.createJunkPayloadBody(True) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) for i in xrange(0, 500): x = UpdateDentalState(host, port, token, id) body = x.createJunkPayloadBody(False) ret = x.send(timeout=30) self.assertEqual(ret[0], 400) for i in xrange(0, 500): x = UpdateDentalState(host, port, token, id) body = x.createPayloadBody() ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("clinic" in ret[1]) clinicId = int(ret[1]["clinic"]) self.assertTrue(clinicId == clinicid) self.assertTrue("patient" in ret[1]) patientId = int(ret[1]["patient"]) self.assertTrue(patientId == patientid) self.assertTrue("code" in ret[1]) codeId = int(ret[1]["code"]) self.assertTrue(codeId == codeid) for x in body: self.assertTrue(x in ret[1]) self.assertTrue(body[x] == ret[1][x]) # test each setter # tooth x = UpdateDentalState(host, port, token, id) x.setTooth(23) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["tooth"], 23) # code x = CreateDentalCDT(host, port, token) x.setCode("D8888") x.setCategory("cat") x.setDesc("desc") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) newcodeid = int(ret[1]["id"]) x = UpdateDentalState(host, port, token, id) x.setCode(newcodeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["code"], newcodeid) # location locations = ["top", "bottom"] for location in locations: x = UpdateDentalState(host, port, token, id) x.setLocation(location) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["location"], location) # state states = ["missing", "none", "treated", "untreated", "other"] for state in states: x = UpdateDentalState(host, port, token, id) x.setState(state) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["state"], state) # surfaces surfaces = permuteAsCSV(DentalStateGenerator.surfaceStrings) for surface in surfaces: x = UpdateDentalState(host, port, token, id) x.setSurface(surface) sf1 = breakout(surface) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) sf2 = breakout(ret[1]["surface"]) self.assertTrue(equalSurfaces(sf1, sf2)) # comment x = UpdateDentalState(host, port, token, id) x.setComment("booya") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setId(id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertEqual(ret[1]["comment"], "booya") # cleanup x = DeleteDentalState(host, port, token, id) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteClinic(host, port, token, clinicid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeletePatient(host, port, token, patientid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteDentalCDT(host, port, token, codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteDentalCDT(host, port, token, newcodeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) def testGetAllDentalStates(self): x = CreateClinic(host, port, token, "Ensenada", "02/05/2016", "02/06/2016") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("id" in ret[1]) clinicid1 = int(ret[1]["id"]) x = CreateClinic(host, port, token, "Ensenada", "05/05/2016", "05/06/2016") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("id" in ret[1]) clinicid2 = int(ret[1]["id"]) x = CreateClinic(host, port, token, "Ensenada", "08/05/2016", "08/06/2016") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) self.assertTrue("id" in ret[1]) clinicid3 = int(ret[1]["id"]) data = {} data["paternal_last"] = "3abcd1234" data["maternal_last"] = "yyyyyy" data["first"] = "zzzzzzz" data["middle"] = "" data["suffix"] = "Jr." data["prefix"] = "" data["dob"] = "04/01/1962" data["gender"] = "Female" data["street1"] = "1234 First Ave" data["street2"] = "" data["city"] = "Ensenada" data["colonia"] = "" data["state"] = u"Baja California" data["phone1"] = "1-111-111-1111" data["phone2"] = "" data["email"] = "patient@example.com" data["emergencyfullname"] = "Maria Sanchez" data["emergencyphone"] = "1-222-222-2222" data["emergencyemail"] = "maria.sanchez@example.com" x = CreatePatient(host, port, token, data) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) patientid1 = int(ret[1]["id"]) data = {} data["paternal_last"] = "1abcd1234" data["maternal_last"] = "yyyyyy" data["first"] = "zzzzzzz" data["middle"] = "" data["suffix"] = "Jr." data["prefix"] = "" data["dob"] = "04/01/1962" data["gender"] = "Female" data["street1"] = "1234 First Ave" data["street2"] = "" data["city"] = "Ensenada" data["colonia"] = "" data["state"] = u"Baja California" data["phone1"] = "1-111-111-1111" data["phone2"] = "" data["email"] = "patient@example.com" data["emergencyfullname"] = "Maria Sanchez" data["emergencyphone"] = "1-222-222-2222" data["emergencyemail"] = "maria.sanchez@example.com" x = CreatePatient(host, port, token, data) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) patientid2 = int(ret[1]["id"]) data = {} data["paternal_last"] = "2abcd1234" data["maternal_last"] = "yyyyyy" data["first"] = "zzzzzzz" data["middle"] = "" data["suffix"] = "Jr." data["prefix"] = "" data["dob"] = "04/01/1962" data["gender"] = "Female" data["street1"] = "1234 First Ave" data["street2"] = "" data["city"] = "Ensenada" data["colonia"] = "" data["state"] = u"Baja California" data["phone1"] = "1-111-111-1111" data["phone2"] = "" data["email"] = "patient@example.com" data["emergencyfullname"] = "Maria Sanchez" data["emergencyphone"] = "1-222-222-2222" data["emergencyemail"] = "maria.sanchez@example.com" x = CreatePatient(host, port, token, data) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) patientid3 = int(ret[1]["id"]) x = CreateDentalCDT(host, port, token) x.setCode("D2244") x.setCategory("category") x.setDesc("description") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) codeid = int(ret[1]["id"]) delids = [] x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid1) x.setClinic(clinicid1) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid2) x.setClinic(clinicid1) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid3) x.setClinic(clinicid1) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid1) x.setClinic(clinicid2) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid2) x.setClinic(clinicid2) x.setCode(codeid) x.setUsername("Gomez") ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid3) x.setClinic(clinicid2) x.setUsername("Gomez") x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid1) x.setClinic(clinicid3) x.setUsername("Gomez") x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid2) x.setClinic(clinicid3) x.setUsername("Gomez") x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = CreateDentalState(host, port, token) x.createPayloadBody() x.setPatient(patientid3) x.setClinic(clinicid3) x.setUsername("Gomez") x.setCode(codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) delids.append(ret[1]["id"]) x = GetDentalState(host, port, token) x.setClinic(clinicid1) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) rtcs = ret[1] self.assertTrue(len(rtcs) == 3) x = GetDentalState(host, port, token) x.setClinic(clinicid2) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) rtcs = ret[1] self.assertTrue(len(rtcs) == 3) x = GetDentalState(host, port, token) x.setClinic(clinicid3) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) rtcs = ret[1] self.assertTrue(len(rtcs) == 3) x = GetDentalState(host, port, token) x.setPatient(patientid1) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) rtcs = ret[1] self.assertTrue(len(rtcs) == 3) x = GetDentalState(host, port, token) x.setPatient(patientid2) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) rtcs = ret[1] self.assertTrue(len(rtcs) == 3) x = GetDentalState(host, port, token) x.setPatient(patientid3) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) rtcs = ret[1] self.assertTrue(len(rtcs) == 3) for x in delids: y = DeleteDentalState(host, port, token, x) ret = y.send(timeout=30) self.assertEqual(ret[0], 200) x = GetDentalState(host, port, token) x.setClinic(clinicid1) ret = x.send(timeout=30) self.assertEqual(ret[0], 404) rtcs = ret[1] self.assertTrue(len(rtcs) == 0) x = DeleteClinic(host, port, token, clinicid1) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteClinic(host, port, token, clinicid2) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteClinic(host, port, token, clinicid3) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeletePatient(host, port, token, patientid1) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeletePatient(host, port, token, patientid2) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeletePatient(host, port, token, patientid3) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) x = DeleteDentalCDT(host, port, token, codeid) ret = x.send(timeout=30) self.assertEqual(ret[0], 200) def usage(): print("dentalstate [-h host] [-p port] [-u username] [-w password]") def main(): try: opts, args = getopt.getopt(sys.argv[1:], "h:p:u:w:") except getopt.GetoptError as err: print(str(err)) usage() sys.exit(2) global host host = "127.0.0.1" global port port = 8000 global username username = None global password password = None for o, a in opts: if o == "-h": host = a elif o == "-p": port = int(a) elif o == "-u": username = a elif o == "-w": password = a else: assert False, "unhandled option" unittest.main(argv=[sys.argv[0]]) if __name__ == "__main__": main()

30.92957

102

0.549654

6,145

55,333

4.926444

0.06428

0.088197

0.105837

0.091633

0.813266

0.792753

0.782975

0.761999

0.747134

0.740396

0

0.041882

0.313899

55,333

1,788

103

30.946868

0.755532

0.03038

0

0.786581

0

0.069445

0.005207

0

0.16631

1

0.04354

false

0.003569

0.007852

0.001428

0.082084

0.001428

0

null

0

1

0

1

0

null

0

7

e7717ba0dba348c1e83e151b72f7a350d2accdbd

3,433

py

Python

tests/integration/renderer/test_title.py

jbampton/dashR

edbcc040ffabb7956eeb4774e922794c53c557ce

[ "MIT" ]

null

tests/integration/renderer/test_title.py

jbampton/dashR

edbcc040ffabb7956eeb4774e922794c53c557ce

[ "MIT" ]

null

tests/integration/renderer/test_title.py

jbampton/dashR

edbcc040ffabb7956eeb4774e922794c53c557ce

[ "MIT" ]

null

import pdb app_test_updating = """ library(dash) library(dashHtmlComponents) app <- Dash$new() app$layout(htmlDiv(list(htmlH3("Press button see document title updating"), htmlDiv(id="output", children="Awaiting output"), htmlButton("Update", id="button", n_clicks=0), htmlButton("Update Page", id="page", n_clicks=0), htmlDiv(id="dummy")) ) ) app$callback(output(id = 'output', property = 'children'), list(input(id = 'page', property = 'n_clicks')), function(n) { Sys.sleep(5) return(paste0("Page ", n)) }) app$run_server() """ app_test_no_update_title1 = """ library(dash) library(dashHtmlComponents) app <- Dash$new(update_title=NULL) app$layout(htmlDiv(list(htmlH3("Press button see document title updating"), htmlDiv(id="output", children="Awaiting output"), htmlButton("Update", id="button", n_clicks=0), htmlButton("Update Page", id="page", n_clicks=0), htmlDiv(id="dummy")) ) ) app$run_server() """ app_test_no_update_title2 = """ library(dash) library(dashHtmlComponents) app <- Dash$new(update_title="") app$layout(htmlDiv(list(htmlH3("Press button see document title updating"), htmlDiv(id="output", children="Awaiting output"), htmlButton("Update", id="button", n_clicks=0), htmlButton("Update Page", id="page", n_clicks=0), htmlDiv(id="dummy")) ) ) app$run_server() """ app_clientside_title1 = """ library(dash) library(dashHtmlComponents) app <- Dash$new(update_title=NULL) app$layout(htmlDiv(list(htmlH3("Press button see document title updating"), htmlDiv(id="output", children="Awaiting output"), htmlButton("Update", id="button", n_clicks=0), htmlButton("Update Page", id="page", n_clicks=0), htmlDiv(id="dummy")) ) ) app$callback( output('dummy', 'children'), params=list(input('page', 'n_clicks')), " function(n_clicks) { document.title = 'Page ' + n_clicks; return 'Page ' + n_clicks; }" ) app$run_server() """ app_clientside_title2 = """ library(dash) library(dashHtmlComponents) app <- Dash$new(update_title="") app$layout(htmlDiv(list(htmlH3("Press button see document title updating"), htmlDiv(id="output", children="Awaiting output"), htmlButton("Update", id="button", n_clicks=0), htmlButton("Update Page", id="page", n_clicks=0), htmlDiv(id="dummy")) ) ) app$callback( output('dummy', 'children'), params=list(input('page', 'n_clicks')), " function(n_clicks) { document.title = 'Page ' + n_clicks; return 'Page ' + n_clicks; }" ) app$run_server() """ def test_rstt001_update_title(dashr): dashr.start_server(app_test_updating) dashr.find_element("#page").click() assert dashr.driver.title == "Updating..." def test_rstt002_update_title(dashr): dashr.start_server(app_test_no_update_title1) assert dashr.driver.title == "Dash" def test_rstt003_update_title(dashr): dashr.start_server(app_test_no_update_title2) assert dashr.driver.title == "Dash" def test_rstt004_update_title(dashr): dashr.start_server(app_clientside_title1) dashr.find_element("#page").click() dashr.wait_for_text_to_equal("#dummy", "Page 1") assert dashr.driver.title == "Page 1" def test_rstt005_update_title(dashr): dashr.start_server(app_clientside_title2) dashr.find_element("#page").click() dashr.wait_for_text_to_equal("#dummy", "Page 1") assert dashr.driver.title == "Page 1"

25.42963

75

0.685989

449

3,433

5.051225

0.144766

0.058642

0.053351

0.079365

0.903439

0.882275

0.876984

0.810406

0.753527

0

0.015038

0.147684

3,433

134

76

25.619403

0.760082

0

0.654545

0

0.715701

0.14448

0

0.045455

1

0.045455

false

0

0.009091

0

0.072727

0

null

0

1

0

1

0

null

0

7

823632fec14881e345a96ed05d7fa15f372c70e0

1,486

py

Python

examples/example.py

mrbloozman/Python_NetPBM

cea78ca7d803d80ba10be498e5325db7b60137fb

[ "MIT" ]

null

examples/example.py

mrbloozman/Python_NetPBM

cea78ca7d803d80ba10be498e5325db7b60137fb

[ "MIT" ]

1

2018-02-21T06:42:51.000Z

examples/example.py

mrbloozman/Python_NetPBM

cea78ca7d803d80ba10be498e5325db7b60137fb

[ "MIT" ]

null

# import sys # sys.path.append('../netpbm') # from __init__ import * from netpbm import * print('Begin test...') print('Load P1...') img = NetPBM() img.load('P1.pbm') print('Height: ' + str(img.height())) print('Width: ' + str(img.width())) print('Comment: ' + str(img.comment())) for color in img.export(ColorMap.b24): print(hex(color)) print('Load P2...') img = NetPBM() img.load('P2.pgm') print('Height: ' + str(img.height())) print('Width: ' + str(img.width())) print('Comment: ' + str(img.comment())) for color in img.export(ColorMap.b24): print(hex(color)) print('Load P3...') img = NetPBM() img.load('P3.ppm') print('Height: ' + str(img.height())) print('Width: ' + str(img.width())) print('Comment: ' + str(img.comment())) for color in img.export(ColorMap.b24): print(hex(color)) print('Load P4...') img = NetPBM() img.load('P4.pbm') print('Height: ' + str(img.height())) print('Width: ' + str(img.width())) print('Comment: ' + str(img.comment())) for color in img.export(ColorMap.b24): print(hex(color)) print('Load P5...') img = NetPBM() img.load('P5.pgm') print('Height: ' + str(img.height())) print('Width: ' + str(img.width())) print('Comment: ' + str(img.comment())) for color in img.export(ColorMap.b24): print(hex(color)) print('Load P6...') img = NetPBM() img.load('P6.ppm') print('Height: ' + str(img.height())) print('Width: ' + str(img.width())) print('Comment: ' + str(img.comment())) for color in img.export(ColorMap.b24): print(hex(color))

20.929577

39

0.632571

219

1,486

4.273973

0.146119

0.115385

0.076923

0.102564

0.785256

0

0.018335

0.119112

1,486

71

40

20.929577

0.696715

0.041723

0

0.72

0

0.178044

0

1

0

false

0

0.02

0

0.02

0.62

0

null

0

1

0

1

0

null

0

1

0

7

413854ed144b1faadd17e9f186dda88045b911db

1,349

py

Python

backend/campusmedius/campusmedius/information/migrations/0022_auto_20181225_2104.py

campusmedius/campusmedius

9fb48b8aa869c3ce45003fff5144db1d5aaafa67

[ "MIT" ]

null

backend/campusmedius/campusmedius/information/migrations/0022_auto_20181225_2104.py

campusmedius/campusmedius

9fb48b8aa869c3ce45003fff5144db1d5aaafa67

[ "MIT" ]

205

2018-11-07T00:50:20.000Z

2022-03-11T23:37:47.000Z

backend/campusmedius/campusmedius/information/migrations/0022_auto_20181225_2104.py

campusmedius/campusmedius

9fb48b8aa869c3ce45003fff5144db1d5aaafa67

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.16 on 2018-12-25 20:04 from __future__ import unicode_literals from django.db import migrations import tinymce.models class Migration(migrations.Migration): dependencies = [ ('information', '0021_auto_20181225_1944'), ] operations = [ migrations.AlterField( model_name='audio', name='caption_de', field=tinymce.models.HTMLField(blank=True, null=True), ), migrations.AlterField( model_name='audio', name='caption_en', field=tinymce.models.HTMLField(blank=True, null=True), ), migrations.AlterField( model_name='image', name='caption_de', field=tinymce.models.HTMLField(blank=True, null=True), ), migrations.AlterField( model_name='image', name='caption_en', field=tinymce.models.HTMLField(blank=True, null=True), ), migrations.AlterField( model_name='video', name='caption_de', field=tinymce.models.HTMLField(blank=True, null=True), ), migrations.AlterField( model_name='video', name='caption_en', field=tinymce.models.HTMLField(blank=True, null=True), ), ]

28.702128

66

0.575241

135

1,349

5.6

0.348148

0.12037

0.198413

0.230159

0.722222

0.670635

0

0.036286

0.305411

1,349

46

67

29.326087

0.770544

0.051149

0

0.769231

1

0

0.097103

0.018011

0

1

0

false

0

0.076923

0

0.153846

0

null

0

1

0

1

0

1

0

1

0

null

0

7

41828045600739a71cd8543dabd4d5c88e34379f

10,365

py

Python

tests/excerptexport/views/test_order_excerpt_views.py

tyrasd/osmaxx

da4454083d17b2ef8b0623cad62e39992b6bd52a

[ "MIT" ]

27

2015-03-30T14:17:26.000Z

2022-02-19T17:30:44.000Z

tests/excerptexport/views/test_order_excerpt_views.py

tyrasd/osmaxx

da4454083d17b2ef8b0623cad62e39992b6bd52a

[ "MIT" ]

483

2015-03-09T16:58:03.000Z

2022-03-14T09:29:06.000Z

tests/excerptexport/views/test_order_excerpt_views.py

tyrasd/osmaxx

da4454083d17b2ef8b0623cad62e39992b6bd52a

[ "MIT" ]

6

2015-04-07T07:38:30.000Z

2020-04-01T12:45:53.000Z

from django.contrib.auth.models import User from django.core.urlresolvers import reverse from django.test import TestCase from hamcrest import assert_that, contains_inanyorder as contains_in_any_order from osmaxx.conversion.converters.converter_gis.detail_levels import DETAIL_LEVEL_ALL from osmaxx.excerptexport.models import ExtractionOrder, Excerpt from tests.excerptexport.permission_test_helper import PermissionHelperMixin from tests.test_helpers import vcr_explicit_path as vcr class ExcerptExportViewTests(TestCase, PermissionHelperMixin): def setUp(self): from django.contrib.gis import geos # FIXME: use the bounding_geometry fixture for this multi_polygon = geos.GEOSGeometry('{"type":"MultiPolygon","coordinates":[[[[8.815935552120209,47.222220486817676],[8.815935552120209,47.22402752311505],[8.818982541561127,47.22402752311505],[8.818982541561127,47.222220486817676],[8.815935552120209,47.222220486817676]]]]}') self.user = User.objects.create_user('user', 'user@example.com', 'pw') other_user = User.objects.create_user('other_user', 'o_u@example.com', 'o_pw') self.coordinate_reference_system = 4326 self.detail_level = DETAIL_LEVEL_ALL self.new_excerpt_post_data = { 'name': 'A very interesting region', 'bounding_geometry': '{"type":"Polygon","coordinates":[[[8.815935552120209,47.222220486817676],[8.815935552120209,47.22402752311505],[8.818982541561127,47.22402752311505],[8.818982541561127,47.222220486817676],[8.815935552120209,47.222220486817676]]]}', 'formats': ['fgdb'], 'coordinate_reference_system': self.coordinate_reference_system, 'detail_level': self.detail_level, } self.existing_own_excerpt = Excerpt.objects.create( name='Some old Excerpt', is_active=True, is_public=False, owner=self.user, bounding_geometry=multi_polygon ) self.existing_public_foreign_excerpt = Excerpt.objects.create( name='Public Excerpt by someone else', is_active=True, is_public=True, owner=other_user, bounding_geometry=multi_polygon ) self.existing_private_foreign_excerpt = Excerpt.objects.create( name='Private Excerpt by someone else', is_active=True, is_public=False, owner=other_user, bounding_geometry=multi_polygon ) self.existing_excerpt_post_data = { 'existing_excerpts': self.existing_own_excerpt.id, 'formats': ['fgdb'], 'coordinate_reference_system': self.coordinate_reference_system, 'detail_level': self.detail_level, } def test_new_when_not_logged_in(self): """ When not logged in, we get redirected. """ response = self.client.get(reverse('excerptexport:order_new_excerpt')) self.assertEqual(response.status_code, 302) @vcr.use_cassette('fixtures/vcr/views-test_test_new.yml') def test_new(self): """ When logged in, we get the excerpt choice form. """ self.add_valid_email() self.client.login(username='user', password='pw') response = self.client.get(reverse('excerptexport:order_new_excerpt')) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Order New Excerpt') @vcr.use_cassette('fixtures/vcr/views-test_test_new_offers_existing_own_excerpt.yml') def test_new_offers_existing_own_excerpt(self): self.add_valid_email() self.client.login(username='user', password='pw') response = self.client.get(reverse('excerptexport:order_existing_excerpt')) self.assertIn( ('Personal excerpts (user) [1]', ((self.existing_own_excerpt.id, 'Some old Excerpt'),)), response.context['form'].fields['existing_excerpts'].choices ) self.assertIn(self.existing_own_excerpt.name, response.context['form'].form_html) @vcr.use_cassette('fixtures/vcr/views-test_test_new_offers_existing_public_foreign_excerpt.yml') def test_new_offers_existing_public_foreign_excerpt(self): self.add_valid_email() self.client.login(username='user', password='pw') response = self.client.get(reverse('excerptexport:order_existing_excerpt')) self.assertIn( ('Public excerpts [1]', ((self.existing_public_foreign_excerpt.id, 'Public Excerpt by someone else'),)), response.context['form'].fields['existing_excerpts'].choices ) self.assertIn(self.existing_public_foreign_excerpt.name, response.context['form'].form_html) @vcr.use_cassette('fixtures/vcr/views-test_new_doesnt_offer_existing_private_foreign_excerpt.yml') def test_new_doesnt_offer_existing_private_foreign_excerpt(self): self.add_valid_email() self.client.login(username='user', password='pw') response = self.client.get(reverse('excerptexport:order_existing_excerpt')) self.assertNotContains(response, self.existing_private_foreign_excerpt.name) def test_create_when_not_logged_in(self): """ When not logged in, we get redirected. """ response = self.client.post(reverse('excerptexport:order_new_excerpt'), self.new_excerpt_post_data) self.assertEqual(response.status_code, 302) @vcr.use_cassette('fixtures/vcr/views-test_create_with_new_excerpt.yml') def test_create_with_new_excerpt(self): """ When logged in, POSTing an export request with a new excerpt is successful. """ self.add_valid_email() self.client.login(username='user', password='pw') response = self.client.post( reverse('excerptexport:order_new_excerpt'), self.new_excerpt_post_data, HTTP_HOST='thehost.example.com' ) self.assertEqual(response.status_code, 302) self.assertEqual( Excerpt.objects.filter(name='A very interesting region', is_active=True, is_public=False).count(), 1 ) @vcr.use_cassette('fixtures/vcr/views-test_create_with_new_excerpt.yml') def test_create_with_new_excerpt_ignores_ispublic(self): """ When logged in, POSTing an export request with a new excerpt is successful. """ self.add_valid_email() self.client.login(username='user', password='pw') self.new_excerpt_post_data['is_public'] = True response = self.client.post( reverse('excerptexport:order_new_excerpt'), self.new_excerpt_post_data, HTTP_HOST='thehost.example.com' ) self.assertEqual(response.status_code, 302) self.assertEqual( Excerpt.objects.filter(name='A very interesting region', is_active=True, is_public=False).count(), 1 ) self.assertEqual( Excerpt.objects.filter(name='A very interesting region', is_public=True).count(), 0 ) @vcr.use_cassette('fixtures/vcr/views-test_create_with_existing_excerpt.yml') def test_create_with_existing_excerpt(self): """ When logged in, POSTing an export request using an existing excerpt is successful. """ self.add_valid_email() self.client.login(username='user', password='pw') response = self.client.post( reverse('excerptexport:order_existing_excerpt'), self.existing_excerpt_post_data, HTTP_HOST='thehost.example.com' ) self.assertEqual(response.status_code, 302) # this should be a redirect when successful self.assertEqual(ExtractionOrder.objects.filter( excerpt_id=self.existing_excerpt_post_data['existing_excerpts'] ).count(), 1) # only reproducible because there is only 1 @vcr.use_cassette('fixtures/vcr/views-test_create_with_new_excerpt_persists_a_new_order.yml') def test_create_with_new_excerpt_persists_a_new_order(self): """ When logged in, POSTing an export request with a new excerpt persists a new ExtractionOrder. """ self.add_valid_email() self.assertEqual(ExtractionOrder.objects.count(), 0) self.client.login(username='user', password='pw') self.client.post(reverse('excerptexport:order_new_excerpt'), self.new_excerpt_post_data, HTTP_HOST='thehost.example.com') self.assertEqual(ExtractionOrder.objects.count(), 1) newly_created_order = ExtractionOrder.objects.first() # only reproducible because there is only 1 self.assertEqual(newly_created_order.coordinate_reference_system, self.coordinate_reference_system) self.assertEqual(newly_created_order.detail_level, self.detail_level) assert_that(newly_created_order.extraction_formats, contains_in_any_order('fgdb')) self.assertEqual(newly_created_order.orderer, self.user) self.assertEqual(newly_created_order.excerpt.name, 'A very interesting region') @vcr.use_cassette('fixtures/vcr/views-test_create_with_existing_excerpt_persists_a_new_order.yml') def test_create_with_existing_excerpt_persists_a_new_order(self): """ When logged in, POSTing an export request using an existing excerpt persists a new ExtractionOrder. """ self.add_valid_email() self.assertEqual(ExtractionOrder.objects.count(), 0) self.client.login(username='user', password='pw') self.client.post( reverse('excerptexport:order_existing_excerpt'), self.existing_excerpt_post_data, HTTP_HOST='thehost.example.com' ) self.assertEqual(ExtractionOrder.objects.count(), 1) newly_created_order = ExtractionOrder.objects.first() # only reproducible because there is only 1 self.assertEqual(newly_created_order.coordinate_reference_system, self.coordinate_reference_system) self.assertEqual(newly_created_order.detail_level, self.detail_level) assert_that(newly_created_order.extraction_formats, contains_in_any_order('fgdb')) self.assertEqual(newly_created_order.orderer, self.user) self.assertEqual(newly_created_order.excerpt.name, 'Some old Excerpt')

49.123223

281

0.695128

1,225

10,365

5.608163

0.139592

0.032023

0.029694

0.028821

0.834061

0.784571

0.771761

0.727802

0.716157

0.685153

0

0.043694

0.202894

10,365

210

282

49.357143

0.787824

0.074481

0

0.506024

0

0.012048

0.227563

0.153552

0

0.004762

0.186747

1

0.072289

false

0.054217

0

0.13253

0

null

0

1

0

null

0

1

0

7

41a427d5082514897c914e2eb2a6e80e1d9e2aa0

5,421

py

Python

skroute/datasets/_datasets.py

arubiales/scikit-route

83262d9d41ff700c911927f5bb6c93feb0c595e4

[ "MIT" ]

2

2020-12-30T19:01:08.000Z

2022-01-17T09:50:59.000Z

skroute/datasets/_datasets.py

arubiales/scikit-route

83262d9d41ff700c911927f5bb6c93feb0c595e4

[ "MIT" ]

39

2020-12-30T14:58:45.000Z

2021-06-21T20:50:02.000Z

skroute/datasets/_datasets.py

arubiales/scikit-route

83262d9d41ff700c911927f5bb6c93feb0c595e4

[ "MIT" ]

1

2020-12-31T00:41:10.000Z

""" Datasets Authors ------- 2020: Alberto Rubiales <al.rubiales.b@gmail.com> """ import pandas as pd from ._utils_datasets import _read_tsp, _read_txt, _loader, _docstring_decorator import os, sys _path = os.path.join(os.path.dirname(__file__) + "/", ) # #Borrar esto, es para jupyter # sys.path.append(_path) # from _utils_datasets import _read_tsp, _read_txt, _loader, _docstring_decorator @_docstring_decorator("cost") def load_alicante_murcia(): return { "DataFrame":pd.read_pickle(_path + "_data/_money_cost/Alicante-Murcia_places.pkl"), "DESCR": _read_txt(_path + "/DESCR.txt"), "feature_names": _read_txt(_path + "/columns_costs.txt") } @_docstring_decorator("cost") def load_barcelona(): return { "DataFrame":pd.read_pickle(_path + "_data/_money_cost/Barcelona_places.pkl"), "DESCR": _read_txt(_path + "/DESCR.txt"), "feature_names": _read_txt(_path +"/columns_costs.txt") } @_docstring_decorator("cost") def load_madrid(): return { "DataFrame":pd.read_pickle(_path + "_data/_money_cost/Madrid_places.pkl"), "DESCR": _read_txt(_path + "/DESCR.txt"), "feature_names": _read_txt(_path + "/columns_costs.txt") } @_docstring_decorator("cost") def load_valencia(): return { "DataFrame":pd.read_pickle(_path + "_data/_money_cost/Valencia.pkl"), "DESCR": _read_txt(_path + "/DESCR.txt"), "feature_names": _read_txt(_path + "/columns_costs.txt") } @_docstring_decorator("cost") def load_costs_qatar(): return{ "DataFrame":pd.read_pickle(_path + "_data/_money_cost/Valencia.pkl"), "DESCR": _read_txt(_path + "/DESCR.txt"), "feature_names": _read_txt(_path + "/columns_costs.txt") } @_docstring_decorator("latlon") def load_argentina(mode="big"): return _loader(_path + "_data/_latitude_longitude/ar9152.tsp", mode) @_docstring_decorator("latlon") def load_burma(mode="big"): return _loader(_path + "_data/_latitude_longitude/bm33708.tsp", mode) @_docstring_decorator("latlon") def load_china(mode="big"): return _loader(_path + "_data/_latitude_longitude/ch71009.tsp", mode) @_docstring_decorator("latlon") def load_canada(mode="big"): return _loader(_path + "_data/_latitude_longitude/ca4663.tsp", mode) @_docstring_decorator("latlon") def load_djibouti(mode="big"): return _loader(_path + "_data/_latitude_longitude/dj38.tsp", mode) @_docstring_decorator("latlon") def load_egypt(mode="big"): return _loader(_path + "_data/_latitude_longitude/eg7146.tsp", mode) @_docstring_decorator("latlon") def load_ireland(mode="big"): return _loader(_path + "_data/_latitude_longitude/ei8246.tsp", mode) @_docstring_decorator("latlon") def load_finland(mode="big"): return _loader(_path + "_data/_latitude_longitude/fi10639.tsp", mode) @_docstring_decorator("latlon") def load_greece(mode="big"): return _loader(_path + "_data/_latitude_longitude/gr9882.tsp", mode) @_docstring_decorator("latlon") def load_honduras(mode="big"): return _loader(_path + "_data/_latitude_longitude/ho14473.tsp", mode) @_docstring_decorator("latlon") def load_italy(mode="big"): return _loader(_path + "_data/_latitude_longitude/it16862.tsp", mode) @_docstring_decorator("latlon") def load_japan(mode="big"): return _loader(_path + "_data/_latitude_longitude/ja9847.tsp", mode) @_docstring_decorator("latlon") def load_kazakhstan(mode="big"): return _loader(_path + "_data/_latitude_longitude/kz9976.tsp", mode) @_docstring_decorator("latlon") def load_luxembourg(mode="big"): return _loader(_path + "_data/_latitude_longitude/lu980.tsp", mode) @_docstring_decorator("latlon") def load_morocco(mode="big"): return _loader(_path + "_data/_latitude_longitude/mo14185.tsp", mode) @_docstring_decorator("latlon") def load_oman(mode="big"): return _loader(_path + "_data/_latitude_longitude/mu1979.tsp", mode) @_docstring_decorator("latlon") def load_nicaragua(mode="big"): return _loader(_path + "_data/_latitude_longitude/nu3496.tsp", mode) @_docstring_decorator("latlon") def load_panama(mode="big"): return _loader(_path + "_data/_latitude_longitude/pm8079.tsp", mode) @_docstring_decorator("latlon") def load_qatar(mode="big"): return _loader(_path + "_data/_latitude_longitude/qa194.tsp", mode) @_docstring_decorator("latlon") def load_rwanda(mode="big"): return _loader(_path + "_data/_latitude_longitude/rw1621.tsp", mode) @_docstring_decorator("latlon") def load_sweden(mode="big"): return _loader(_path + "_data/_latitude_longitude/sw24978.tsp", mode) @_docstring_decorator("latlon") def load_tanzania(mode="big"): return _loader(_path + "_data/_latitude_longitude/tz6117.tsp", mode) @_docstring_decorator("latlon") def load_uruguay(mode="big"): return _loader(_path + "_data/_latitude_longitude/uy734.tsp", mode) @_docstring_decorator("latlon") def load_vietnam(mode="big"): return _loader(_path + "_data/_latitude_longitude/vm22775.tsp", mode) @_docstring_decorator("latlon") def load_sahara(mode="big"): return _loader(_path + "_data/_latitude_longitude/wi29.tsp", mode) @_docstring_decorator("latlon") def load_yemen(mode="big"): return _loader(_path + "_data/_latitude_longitude/ym7663.tsp", mode) @_docstring_decorator("latlon") def load_zimbabwe(mode="big"): return _loader(_path + "_data/_latitude_longitude/zi929.tsp", mode)

31.701754

91

0.729386

676

5,421

5.368343

0.16568

0.168642

0.178562

0.200882

0.841279

0.829705

0.557454

0.230091

0.193717

0

0.0235

0.120826

5,421

170

92

31.888235

0.737935

0.038185

0

0.408333

0

0.324491

0.220877

0

1

0.266667

false

0

0.025

0.266667

0.55

0

null

0

1

0

null

0

1

0

1

0

7

41a866d2f361c9851f5eb0bad6904d84d88f3b18

20,216

py

Python

sdk/python/pulumi_ucloud/uhost/instance.py

yufeiminds/pulumi-ucloud

e7899b4e92f60edec47369001530039acd945f7a

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_ucloud/uhost/instance.py

yufeiminds/pulumi-ucloud

e7899b4e92f60edec47369001530039acd945f7a

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_ucloud/uhost/instance.py

yufeiminds/pulumi-ucloud

e7899b4e92f60edec47369001530039acd945f7a

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import json import warnings import pulumi import pulumi.runtime from typing import Union from .. import utilities, tables class Instance(pulumi.CustomResource): allow_stopping_for_update: pulumi.Output[bool] auto_renew: pulumi.Output[bool] """ Whether to renew an instance automatically or not. """ availability_zone: pulumi.Output[str] """ Availability zone where instance is located. such as: `cn-bj2-02`. You may refer to [list of availability zone](https://docs.ucloud.cn/api/summary/regionlist) """ boot_disk_size: pulumi.Output[float] """ The size of the boot disk, measured in GB (GigaByte). Range: 20-100. The value set of disk size must be larger or equal to `20`(default: `20`) for Linux and `40` (default: `40`) for Windows. The responsive time is a bit longer if the value set is larger than default for local boot disk, and further settings may be required on host instance if the value set is larger than default for cloud boot disk. The disk volume adjustment must be a multiple of 10 GB. In addition, any reduction of boot disk size is not supported. """ boot_disk_type: pulumi.Output[str] """ The type of boot disk. Possible values are: `local_normal` and `local_ssd` for local boot disk, `cloud_ssd` for cloud SSD boot disk. (Default: `local_normal`). The `local_ssd` and `cloud_ssd` are not fully support by all regions as boot disk type, please proceed to UCloud console for more details. """ charge_type: pulumi.Output[str] """ The charge type of instance, possible values are: `year`, `month` and `dynamic` as pay by hour (specific permission required). (Default: `month`). """ cpu: pulumi.Output[float] """ The number of cores of virtual CPU, measured in core. """ create_time: pulumi.Output[str] """ The time of creation for instance, formatted in RFC3339 time string. """ data_disk_size: pulumi.Output[float] """ The size of local data disk, measured in GB (GigaByte), range: 0-8000 (Default: `20`), 0-8000 for cloud disk, 0-2000 for local sata disk and 100-1000 for local ssd disk (all the GPU type instances are included). The volume adjustment must be a multiple of 10 GB. In addition, any reduction of data disk size is not supported. """ data_disk_type: pulumi.Output[str] """ The type of local data disk. Possible values are: `local_normal` and `local_ssd` for local data disk. (Default: `local_normal`). The `local_ssd` is not fully support by all regions as data disk type, please proceed to UCloud console for more details. In addition, the `data_disk_type` must be same as `boot_disk_type` if specified. """ disk_sets: pulumi.Output[list] """ It is a nested type which documented below. * `id` (`str`) - The ID of disk. * `isBoot` (`bool`) - Specifies whether boot disk or not. * `size` (`float`) - The size of disk, measured in GB (Gigabyte). * `type` (`str`) - The type of disk. """ duration: pulumi.Output[float] """ The duration that you will buy the instance (Default: `1`). The value is `0` when pay by month and the instance will be valid till the last day of that month. It is not required when `dynamic` (pay by hour). """ expire_time: pulumi.Output[str] """ The expiration time for instance, formatted in RFC3339 time string. """ image_id: pulumi.Output[str] """ The ID for the image to use for the instance. """ instance_type: pulumi.Output[str] ip_sets: pulumi.Output[list] """ It is a nested type which documented below. * `internetType` (`str`) - Type of Elastic IP routes. Possible values are: `International` as international BGP IP, `BGP` as china BGP IP and `Private` as private IP. * `ip` (`str`) - Elastic IP address. """ isolation_group: pulumi.Output[str] """ The ID of the associated isolation group. """ memory: pulumi.Output[float] """ The size of memory, measured in GB(Gigabyte). """ name: pulumi.Output[str] private_ip: pulumi.Output[str] """ The private IP address assigned to the instance. """ remark: pulumi.Output[str] """ The remarks of instance. (Default: `""`). """ root_password: pulumi.Output[str] security_group: pulumi.Output[str] """ The ID of the associated security group. """ status: pulumi.Output[str] """ Instance current status. Possible values are `Initializing`, `Starting`, `Running`, `Stopping`, `Stopped`, `Install Fail`, `ResizeFail` and `Rebooting`. """ subnet_id: pulumi.Output[str] """ The ID of subnet. If defined `vpc_id`, the `subnet_id` is Required. If not defined `vpc_id` and `subnet_id`, the instance will use the default subnet in the current region. """ tag: pulumi.Output[str] """ A tag assigned to instance, which contains at most 63 characters and only support Chinese, English, numbers, '-', '_', and '.'. If it is not filled in or a empty string is filled in, then default tag will be assigned. (Default: `Default`). """ vpc_id: pulumi.Output[str] """ The ID of VPC linked to the instance. If not defined `vpc_id`, the instance will use the default VPC in the current region. """ def __init__(__self__, resource_name, opts=None, allow_stopping_for_update=None, availability_zone=None, boot_disk_size=None, boot_disk_type=None, charge_type=None, data_disk_size=None, data_disk_type=None, duration=None, image_id=None, instance_type=None, isolation_group=None, name=None, private_ip=None, remark=None, root_password=None, security_group=None, subnet_id=None, tag=None, vpc_id=None, __props__=None, __name__=None, __opts__=None): """ Create a Instance resource with the given unique name, props, and options. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] availability_zone: Availability zone where instance is located. such as: `cn-bj2-02`. You may refer to [list of availability zone](https://docs.ucloud.cn/api/summary/regionlist) :param pulumi.Input[float] boot_disk_size: The size of the boot disk, measured in GB (GigaByte). Range: 20-100. The value set of disk size must be larger or equal to `20`(default: `20`) for Linux and `40` (default: `40`) for Windows. The responsive time is a bit longer if the value set is larger than default for local boot disk, and further settings may be required on host instance if the value set is larger than default for cloud boot disk. The disk volume adjustment must be a multiple of 10 GB. In addition, any reduction of boot disk size is not supported. :param pulumi.Input[str] boot_disk_type: The type of boot disk. Possible values are: `local_normal` and `local_ssd` for local boot disk, `cloud_ssd` for cloud SSD boot disk. (Default: `local_normal`). The `local_ssd` and `cloud_ssd` are not fully support by all regions as boot disk type, please proceed to UCloud console for more details. :param pulumi.Input[str] charge_type: The charge type of instance, possible values are: `year`, `month` and `dynamic` as pay by hour (specific permission required). (Default: `month`). :param pulumi.Input[float] data_disk_size: The size of local data disk, measured in GB (GigaByte), range: 0-8000 (Default: `20`), 0-8000 for cloud disk, 0-2000 for local sata disk and 100-1000 for local ssd disk (all the GPU type instances are included). The volume adjustment must be a multiple of 10 GB. In addition, any reduction of data disk size is not supported. :param pulumi.Input[str] data_disk_type: The type of local data disk. Possible values are: `local_normal` and `local_ssd` for local data disk. (Default: `local_normal`). The `local_ssd` is not fully support by all regions as data disk type, please proceed to UCloud console for more details. In addition, the `data_disk_type` must be same as `boot_disk_type` if specified. :param pulumi.Input[float] duration: The duration that you will buy the instance (Default: `1`). The value is `0` when pay by month and the instance will be valid till the last day of that month. It is not required when `dynamic` (pay by hour). :param pulumi.Input[str] image_id: The ID for the image to use for the instance. :param pulumi.Input[str] isolation_group: The ID of the associated isolation group. :param pulumi.Input[str] private_ip: The private IP address assigned to the instance. :param pulumi.Input[str] remark: The remarks of instance. (Default: `""`). :param pulumi.Input[str] security_group: The ID of the associated security group. :param pulumi.Input[str] subnet_id: The ID of subnet. If defined `vpc_id`, the `subnet_id` is Required. If not defined `vpc_id` and `subnet_id`, the instance will use the default subnet in the current region. :param pulumi.Input[str] tag: A tag assigned to instance, which contains at most 63 characters and only support Chinese, English, numbers, '-', '_', and '.'. If it is not filled in or a empty string is filled in, then default tag will be assigned. (Default: `Default`). :param pulumi.Input[str] vpc_id: The ID of VPC linked to the instance. If not defined `vpc_id`, the instance will use the default VPC in the current region. > This content is derived from https://github.com/terraform-providers/terraform-provider-ucloud/blob/master/website/docs/r/instance.html.markdown. """ if __name__ is not None: warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning) resource_name = __name__ if __opts__ is not None: warnings.warn("explicit use of __opts__ is deprecated, use 'opts' instead", DeprecationWarning) opts = __opts__ if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = dict() __props__['allow_stopping_for_update'] = allow_stopping_for_update if availability_zone is None: raise TypeError("Missing required property 'availability_zone'") __props__['availability_zone'] = availability_zone __props__['boot_disk_size'] = boot_disk_size __props__['boot_disk_type'] = boot_disk_type __props__['charge_type'] = charge_type __props__['data_disk_size'] = data_disk_size __props__['data_disk_type'] = data_disk_type __props__['duration'] = duration if image_id is None: raise TypeError("Missing required property 'image_id'") __props__['image_id'] = image_id if instance_type is None: raise TypeError("Missing required property 'instance_type'") __props__['instance_type'] = instance_type __props__['isolation_group'] = isolation_group __props__['name'] = name __props__['private_ip'] = private_ip __props__['remark'] = remark __props__['root_password'] = root_password __props__['security_group'] = security_group __props__['subnet_id'] = subnet_id __props__['tag'] = tag __props__['vpc_id'] = vpc_id __props__['auto_renew'] = None __props__['cpu'] = None __props__['create_time'] = None __props__['disk_sets'] = None __props__['expire_time'] = None __props__['ip_sets'] = None __props__['memory'] = None __props__['status'] = None super(Instance, __self__).__init__( 'ucloud:uhost/instance:Instance', resource_name, __props__, opts) @staticmethod def get(resource_name, id, opts=None, allow_stopping_for_update=None, auto_renew=None, availability_zone=None, boot_disk_size=None, boot_disk_type=None, charge_type=None, cpu=None, create_time=None, data_disk_size=None, data_disk_type=None, disk_sets=None, duration=None, expire_time=None, image_id=None, instance_type=None, ip_sets=None, isolation_group=None, memory=None, name=None, private_ip=None, remark=None, root_password=None, security_group=None, status=None, subnet_id=None, tag=None, vpc_id=None): """ Get an existing Instance resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param str id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[bool] auto_renew: Whether to renew an instance automatically or not. :param pulumi.Input[str] availability_zone: Availability zone where instance is located. such as: `cn-bj2-02`. You may refer to [list of availability zone](https://docs.ucloud.cn/api/summary/regionlist) :param pulumi.Input[float] boot_disk_size: The size of the boot disk, measured in GB (GigaByte). Range: 20-100. The value set of disk size must be larger or equal to `20`(default: `20`) for Linux and `40` (default: `40`) for Windows. The responsive time is a bit longer if the value set is larger than default for local boot disk, and further settings may be required on host instance if the value set is larger than default for cloud boot disk. The disk volume adjustment must be a multiple of 10 GB. In addition, any reduction of boot disk size is not supported. :param pulumi.Input[str] boot_disk_type: The type of boot disk. Possible values are: `local_normal` and `local_ssd` for local boot disk, `cloud_ssd` for cloud SSD boot disk. (Default: `local_normal`). The `local_ssd` and `cloud_ssd` are not fully support by all regions as boot disk type, please proceed to UCloud console for more details. :param pulumi.Input[str] charge_type: The charge type of instance, possible values are: `year`, `month` and `dynamic` as pay by hour (specific permission required). (Default: `month`). :param pulumi.Input[float] cpu: The number of cores of virtual CPU, measured in core. :param pulumi.Input[str] create_time: The time of creation for instance, formatted in RFC3339 time string. :param pulumi.Input[float] data_disk_size: The size of local data disk, measured in GB (GigaByte), range: 0-8000 (Default: `20`), 0-8000 for cloud disk, 0-2000 for local sata disk and 100-1000 for local ssd disk (all the GPU type instances are included). The volume adjustment must be a multiple of 10 GB. In addition, any reduction of data disk size is not supported. :param pulumi.Input[str] data_disk_type: The type of local data disk. Possible values are: `local_normal` and `local_ssd` for local data disk. (Default: `local_normal`). The `local_ssd` is not fully support by all regions as data disk type, please proceed to UCloud console for more details. In addition, the `data_disk_type` must be same as `boot_disk_type` if specified. :param pulumi.Input[list] disk_sets: It is a nested type which documented below. :param pulumi.Input[float] duration: The duration that you will buy the instance (Default: `1`). The value is `0` when pay by month and the instance will be valid till the last day of that month. It is not required when `dynamic` (pay by hour). :param pulumi.Input[str] expire_time: The expiration time for instance, formatted in RFC3339 time string. :param pulumi.Input[str] image_id: The ID for the image to use for the instance. :param pulumi.Input[list] ip_sets: It is a nested type which documented below. :param pulumi.Input[str] isolation_group: The ID of the associated isolation group. :param pulumi.Input[float] memory: The size of memory, measured in GB(Gigabyte). :param pulumi.Input[str] private_ip: The private IP address assigned to the instance. :param pulumi.Input[str] remark: The remarks of instance. (Default: `""`). :param pulumi.Input[str] security_group: The ID of the associated security group. :param pulumi.Input[str] status: Instance current status. Possible values are `Initializing`, `Starting`, `Running`, `Stopping`, `Stopped`, `Install Fail`, `ResizeFail` and `Rebooting`. :param pulumi.Input[str] subnet_id: The ID of subnet. If defined `vpc_id`, the `subnet_id` is Required. If not defined `vpc_id` and `subnet_id`, the instance will use the default subnet in the current region. :param pulumi.Input[str] tag: A tag assigned to instance, which contains at most 63 characters and only support Chinese, English, numbers, '-', '_', and '.'. If it is not filled in or a empty string is filled in, then default tag will be assigned. (Default: `Default`). :param pulumi.Input[str] vpc_id: The ID of VPC linked to the instance. If not defined `vpc_id`, the instance will use the default VPC in the current region. The **disk_sets** object supports the following: * `id` (`pulumi.Input[str]`) - The ID of disk. * `isBoot` (`pulumi.Input[bool]`) - Specifies whether boot disk or not. * `size` (`pulumi.Input[float]`) - The size of disk, measured in GB (Gigabyte). * `type` (`pulumi.Input[str]`) - The type of disk. The **ip_sets** object supports the following: * `internetType` (`pulumi.Input[str]`) - Type of Elastic IP routes. Possible values are: `International` as international BGP IP, `BGP` as china BGP IP and `Private` as private IP. * `ip` (`pulumi.Input[str]`) - Elastic IP address. > This content is derived from https://github.com/terraform-providers/terraform-provider-ucloud/blob/master/website/docs/r/instance.html.markdown. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() __props__["allow_stopping_for_update"] = allow_stopping_for_update __props__["auto_renew"] = auto_renew __props__["availability_zone"] = availability_zone __props__["boot_disk_size"] = boot_disk_size __props__["boot_disk_type"] = boot_disk_type __props__["charge_type"] = charge_type __props__["cpu"] = cpu __props__["create_time"] = create_time __props__["data_disk_size"] = data_disk_size __props__["data_disk_type"] = data_disk_type __props__["disk_sets"] = disk_sets __props__["duration"] = duration __props__["expire_time"] = expire_time __props__["image_id"] = image_id __props__["instance_type"] = instance_type __props__["ip_sets"] = ip_sets __props__["isolation_group"] = isolation_group __props__["memory"] = memory __props__["name"] = name __props__["private_ip"] = private_ip __props__["remark"] = remark __props__["root_password"] = root_password __props__["security_group"] = security_group __props__["status"] = status __props__["subnet_id"] = subnet_id __props__["tag"] = tag __props__["vpc_id"] = vpc_id return Instance(resource_name, opts=opts, __props__=__props__) def translate_output_property(self, prop): return tables._CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop def translate_input_property(self, prop): return tables._SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop

71.94306

572

0.693856

2,926

20,216

4.590567

0.101504

0.027993

0.045265

0.038192

0.824151

0.800625

0.781864

0.758338

0.726176

0.710691

0

0.010125

0.213445

20,216

280

573

72.2

0.834602

0.447418

0

0.016

1

0

0.147139

0.012173

0

1

0.032

false

0.048

0.016

0.328

0

null

0

1

0

1

0

null

0

7

68ba180b4c6482a3dc6864ec52890b23465059b5

4,746

py

Python

tests/test_onboarding.py

alexko371/Python-Selenium-AofL

53a988fdfa06fae95a2f29fa677b46698336ef11

[ "Apache-2.0" ]

null

tests/test_onboarding.py

alexko371/Python-Selenium-AofL

53a988fdfa06fae95a2f29fa677b46698336ef11

[ "Apache-2.0" ]

null

tests/test_onboarding.py

alexko371/Python-Selenium-AofL

53a988fdfa06fae95a2f29fa677b46698336ef11

[ "Apache-2.0" ]

null

from selenium.webdriver.support.ui import WebDriverWait # Import at top of file from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.common.by import By def test_onboarding_process_gilr(app): app.onboarding.open_login_page("https://dk.qtest.abcmouse.com/login") app.login.to_abcmouse(email="camp2@bm.test", password="test123") # app.sign_up.click_submit_continue_registration_button() app.onboarding.welcome_page_click_get_started_button() app.onboarding.survey_click_continue_buttons() app.onboarding.input_parent_name(parent_first_name="AK Test", parent_family_name="Ko Test") ##### (grade Levels' IDs: [toddler-time] [preschool] [pre-k] [kindergarten] [first-grade] [second-grade] app.onboarding.create_child_profile(child_name="Lilly (bm2)", gender="F", academic_level="preschool") app.onboarding.choose_avatar(avatar="girl_avatar09") ##### | boy_avatar03 | girl_avatar03 #### | hamster-1 | hamster-2 ##### | fish-1 | fish-2 app.onboarding.choose_hamster_and_fish(hamster="hamster-3", fish="fish-3", hamster_name="My Ham-StAr") app.onboarding.skip_video() app.onboarding.go_to_shp() def test_onboarding_process_boy(app): app.onboarding.open_login_page("https://dk.qtest.abcmouse.com/login") app.login.to_abcmouse(email="ak3@dk.test", password="test123") # app.sign_up.click_submit_continue_registration_button() app.onboarding.welcome_page_click_get_started_button() app.onboarding.survey_click_continue_buttons() app.onboarding.input_parent_name(parent_first_name="AK Test", parent_family_name="Ko Test") ##### (grade Levels' IDs: [toddler-time] [preschool] [pre-k] [kindergarten] [first-grade] [second-grade] app.onboarding.create_child_profile(child_name="Alex (be-2)", gender="M", academic_level="second-grade") app.onboarding.choose_avatar(avatar="boy_avatar09") ##### | boy_avatar07 #### | hamster-1 | hamster-2 ##### | fish-1 | fish-2 app.onboarding.choose_hamster_and_fish(hamster="hamster-1", fish="fish-2", hamster_name="My Ham-StAr") app.onboarding.skip_video() app.onboarding.go_to_shp() def test_onboarding_process_gilr(app): app.onboarding.open_login_page("https://dk.qtest.abcmouse.com/login") app.login.to_abcmouse(email="ak001@dk.test", password="test123") app.sign_up.click_submit_continue_registration_button() ###### ON-BOARDING PAGE app.onboarding.welcome_page_click_get_started_button() app.onboarding.survey_click_continue_buttons() app.onboarding.input_parent_name(parent_first_name="AK Test", parent_family_name="Ko Test") ###### (grade Levels' IDs: [toddler-time] [preschool] [pre-k] [kindergarten] [first-grade] [second-grade] app.onboarding.create_child_profile(child_name="Tim", gender="F", academic_level="first-grade") app.onboarding.choose_avatar(avatar="girl_avatar7") ##### girl_avatar01 | girl_avatar16 app.onboarding.choose_hamster_and_fish(hamster="hamster-1", fish="fish-2", hamster_name="My Ham-StAr") app.onboarding.skip_video() app.onboarding.add_child() ##### (grade Levels' IDs: [toddler-time] [preschool] [pre-k] [kindergarten] [first-grade] [second-grade] app.onboarding.create_child_profile(child_name="Sansa", gender="M", academic_level="preschool") app.onboarding.choose_avatar(avatar="boy_avatar7") ##### | boy_avatar03 | boy_avatar03 app.onboarding.choose_hamster_and_fish(hamster="hamster-3", fish="fish-4", hamster_name="My Ham-StAr") app.onboarding.go_to_shp() # assert app.onboarding.mouse_pop_up() # def test_onb_live(app): # app.onboarding.open_login_page("https://www.abcmouse.com/login") # app.login.to_abcmouse(email="sitetimer@live.test", password="test123") # # ###### ON-BOARDING PAGE # app.sign_up.click_submit_continue_registration_button() # app.onboarding.welcome_page_click_get_started_button() # app.onboarding.survey_click_continue_buttons() # app.onboarding.input_parent_name(parent_first_name="AK Test", parent_family_name="Ko Test") # ##### (grade Levels' IDs: [toddler-time] [preschool] [pre-k] [kindergarten] [first-grade] [second-grade] # app.onboarding.create_child_profile(child_name="B_1", gender="M", academic_level="first-grade") # app.onboarding.choose_avatar(avatar="boy_avatar03") ##### | boy_avatar03 | girl_avatar03 # app.onboarding.choose_hamster_and_fish(hamster="hamster-3", fish="fish-3", hamster_name="My Ham-StAr") # app.onboarding.skip_video() # app.onboarding.go_to_shp() # assert app.onboarding.mouse_pop_up() # assert app.driver.current_url == "https://www.abcmouse.com/html5#abc/student_home"

50.489362

110

0.733249

644

4,746

5.125776

0.192547

0.165404

0.057558

0.043623

0.839443

0.83611

0.807028

0.763102

0.730385

0

0.015535

0.118416

4,746

94

111

50.489362

0.773423

0.394437

0

0.536585

0

0.1559

0

1

0.073171

false

0.073171

0

0.146341

0

null

0

1

0

null

0

1

0

7

68cb63cf818939578b7ad63069a26ef47bd86659

9,530

py

Python

tests/test_superuser.py

appukuttan-shailesh/hbp-validation-client

893ae3ecb7dc74420408abcd79610c7499ef9e84

[ "BSD-3-Clause" ]

3

2020-12-20T16:14:09.000Z

2021-05-07T15:33:35.000Z

tests/test_superuser.py

appukuttan-shailesh/hbp-validation-client

893ae3ecb7dc74420408abcd79610c7499ef9e84

[ "BSD-3-Clause" ]

42

2018-01-18T12:29:11.000Z

2021-02-01T14:07:42.000Z

tests/test_superuser.py

appukuttan-shailesh/hbp-validation-client

893ae3ecb7dc74420408abcd79610c7499ef9e84

[ "BSD-3-Clause" ]

6

2018-04-18T14:33:42.000Z

2020-07-23T10:22:42.000Z

import os import platform from datetime import datetime from time import sleep from hbp_validation_framework import ModelCatalog, TestLibrary, sample import pytest HBP_USERNAME = os.environ.get('HBP_USER') HBP_PASSWORD = os.environ.get('HBP_PASS') TOKEN = os.environ.get("HBP_AUTH_TOKEN") HBP_USERNAME_NORMAL_USER = os.environ.get('HBP_USER_NORMAL') HBP_PASSWORD_NORMAL_USER = os.environ.get('HBP_PASS_NORMAL') TOKEN_NORMAL_USER = os.environ.get("HBP_AUTH_TOKEN_NORMAL") """ 1. Verify superuser delete privileges """ #1.1) Super user - Delete model, model_instance, model_image, test, test_instance and result def test_delete_superUser(request): ENVIRONMENT = request.config.getoption("--environment") if HBP_USERNAME and HBP_PASSWORD: model_catalog = ModelCatalog(username=HBP_USERNAME, password=HBP_PASSWORD, environment=ENVIRONMENT) elif TOKEN: model_catalog = ModelCatalog(token=TOKEN, environment=ENVIRONMENT) else: raise Exception("Credentials not provided. Please define environment variables (HBP_AUTH_TOKEN or HBP_USER and HBP_PASS") model_name = "Model_{}_{}_py{}_superuser1".format(datetime.now().strftime("%Y-%m-%d_%H:%M:%S"), model_catalog.environment, platform.python_version()) model = model_catalog.register_model(collab_id="model-validation", name="IGNORE - Test Model - " + model_name, alias=model_name, author={"family_name": "Tester", "given_name": "Validation"}, organization="HBP-SP6", private=False, cell_type="granule cell", model_scope="single cell", abstraction_level="spiking neurons", brain_region="basal ganglia", species="Mus musculus", owner={"family_name": "Tester", "given_name": "Validation"}, license="BSD 3-Clause", description="This is a test entry! Please ignore.", instances=[{"source":"https://www.abcde.com", "version":"1.0", "parameters":""}], images=[{"url":"http://www.neuron.yale.edu/neuron/sites/default/themes/xchameleon/logo.png", "caption":"NEURON Logo"}]) model_instance_id = model["instances"][0]["id"] #model_image_id = model["images"][0]["id"] model_obj = sample.SampleModel(model_uuid=model["id"], model_version=model["instances"][0]["version"]) test_library = TestLibrary.from_existing(model_catalog) test_name = "Test_{}_{}_py{}_superuser2".format(datetime.now().strftime("%Y-%m-%d_%H:%M:%S"), test_library.environment, platform.python_version()) test = test_library.add_test(name="IGNORE - Test Test - " + test_name, alias=test_name, author={"family_name": "Tester", "given_name": "Validation"}, species="Mus musculus", age="", brain_region="basal ganglia", cell_type="granule cell", recording_modality="electron microscopy", test_type="network structure", score_type="Other", description="Later", data_location="https://object.cscs.ch/v1/AUTH_c0a333ecf7c045809321ce9d9ecdfdea/sp6_validation_data/test.txt", data_type="Mean, SD", publication="Testing et al., 2019", instances=[{"version":"1.0", "repository":"https://github.com/HumanBrainProject/hbp-validation-client.git", "path":"hbp_validation_framework.sample.SampleTest"}]) test_instance_id = test["instances"][0]["id"] sleep(20) test_obj = test_library.get_validation_test(test_id=test["id"]) score = test_obj.judge(model_obj) timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") folder_name = "results_{}_{}_{}".format(model_obj.name, model_obj.model_uuid[:8], timestamp) result = test_library.register_result(score, collab_id = "model-validation") # Collab ID = model-validation test_library.delete_result(result_id=result["id"]) sleep(20) with pytest.raises(Exception) as excinfo: result = test_library.get_result(result_id=result["id"]) assert "not found" in str(excinfo.value) model_catalog.delete_model_instance(instance_id=model_instance_id) sleep(20) with pytest.raises(Exception) as excinfo: model_instance = model_catalog.get_model_instance(instance_id=model_instance_id) assert "Error in retrieving model instance." in str(excinfo.value) model_catalog.delete_model(model_id=model["id"]) sleep(20) with pytest.raises(Exception) as excinfo: model = model_catalog.get_model(model_id=model["id"]) assert "Error in retrieving model." in str(excinfo.value) test_library.delete_test_instance(instance_id=test_instance_id) sleep(20) with pytest.raises(Exception) as excinfo: test_instance = test_library.get_test_instance(instance_id=test_instance_id) assert "Error in retrieving test instance." in str(excinfo.value) test_library.delete_test(test_id=test["id"]) sleep(20) with pytest.raises(Exception) as excinfo: test = test_library.get_test_definition(test_id=test["id"]) assert "Error in retrieving test" in str(excinfo.value) #1.2) Normal user - Delete model, model_instance, model_image, test, test_instance and result # @pytest.mark.xfail(reason="delete for normal users not handled properly yet?!") def test_delete_normalUser(request): ENVIRONMENT = request.config.getoption("--environment") if HBP_USERNAME_NORMAL_USER and HBP_PASSWORD_NORMAL_USER: model_catalog = ModelCatalog(username=HBP_USERNAME_NORMAL_USER, password=HBP_PASSWORD_NORMAL_USER, environment=ENVIRONMENT) elif TOKEN: model_catalog = ModelCatalog(token=TOKEN_NORMAL_USER, environment=ENVIRONMENT) else: raise Exception("Credentials not provided. Please define environment variables (HBP_AUTH_TOKEN or HBP_USER and HBP_PASS") model_name = "Model_{}_{}_py{}_normaluser1".format(datetime.now().strftime("%Y-%m-%d_%H:%M:%S"), model_catalog.environment, platform.python_version()) model = model_catalog.register_model(collab_id="validation-tester", name="IGNORE - Test Model - " + model_name, alias=model_name, author={"family_name": "Tester", "given_name": "Validation"}, organization="HBP-SP6", private=False, cell_type="granule cell", model_scope="single cell", abstraction_level="spiking neurons", brain_region="basal ganglia", species="Mus musculus", owner={"family_name": "Tester", "given_name": "Validation"}, license="BSD 3-Clause", description="This is a test entry! Please ignore.", instances=[{"source":"https://www.abcde.com", "version":"1.0", "parameters":""}], images=[{"url":"http://www.neuron.yale.edu/neuron/sites/default/themes/xchameleon/logo.png", "caption":"NEURON Logo"}]) model_instance_id = model["instances"][0]["id"] #model_image_id = model["images"][0]["id"] model_obj = sample.SampleModel(model_uuid=model["id"], model_version=model["instances"][0]["version"]) test_library = TestLibrary.from_existing(model_catalog) test_name = "Test_{}_{}_py{}_normaluser2".format(datetime.now().strftime("%Y-%m-%d_%H:%M:%S"), test_library.environment, platform.python_version()) test = test_library.add_test(name="IGNORE - Test Test - " + test_name, alias=test_name, author={"family_name": "Tester", "given_name": "Validation"}, species="Mus musculus", age="", brain_region="basal ganglia", cell_type="granule cell", recording_modality="electron microscopy", test_type="network structure", score_type="Other", description="Later", data_location="https://object.cscs.ch/v1/AUTH_c0a333ecf7c045809321ce9d9ecdfdea/sp6_validation_data/test.txt", data_type="Mean, SD", publication="Testing et al., 2019", instances=[{"version":"1.0", "repository":"https://github.com/HumanBrainProject/hbp-validation-client.git", "path":"hbp_validation_framework.sample.SampleTest"}]) test_instance_id = test["instances"][0]["id"] sleep(20) test_obj = test_library.get_validation_test(test_id=test["id"]) score = test_obj.judge(model_obj) timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") folder_name = "results_{}_{}_{}".format(model_obj.name, model_obj.model_uuid[:8], timestamp) result = test_library.register_result(score, collab_id="validation-tester") # Collab ID = validation-tester # normal users cannot delete results with pytest.raises(Exception) as excinfo: test_library.delete_result(result_id=result["id"]) assert "Only SuperUser accounts can delete data." in str(excinfo.value) # normal users can delete model instances that they have write access to model_catalog.delete_model_instance(instance_id=model_instance_id) # normal users can delete models that they have write access to model_catalog.delete_model(model_id=model["id"]) # normal users cannot delete test instances with pytest.raises(Exception) as excinfo: test_library.delete_test_instance(instance_id=test_instance_id) assert "Only SuperUser accounts can delete data." in str(excinfo.value) # normal users cannot delete tests with pytest.raises(Exception) as excinfo: test_library.delete_test(test_id=test["id"]) assert "Only SuperUser accounts can delete data." in str(excinfo.value)

57.409639

182

0.69276

1,201

9,530

5.263114

0.172356

0.021041

0.02025

0.031641

0.857934

0.843854

0.791647

0.785635

0.744977

0.68929

0

0.011329

0.175656

9,530

165

183

57.757576

0.793279

0.067891

0

0.682927

0

0.01626

0.277702

0.024133

0

0.065041

1

0.01626

false

0.065041

0.04878

0

0.065041

0

null

0

1

0

null

0

1

0

7

ec1f5279a3722bd20c779e11b525090b9fcd8a15

13,357

py

Python

src/PowerGraphPartitioning.py

YifanLi/SGVCut

8fde53d17876fade2bc561dd04c9acea35334a24

[ "Apache-2.0" ]

null

src/PowerGraphPartitioning.py

YifanLi/SGVCut

8fde53d17876fade2bc561dd04c9acea35334a24

[ "Apache-2.0" ]

null

src/PowerGraphPartitioning.py

YifanLi/SGVCut

8fde53d17876fade2bc561dd04c9acea35334a24

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- ''' Usage: PowerGraphPartitioning.py [edges_dataset] [numOfPartitions] Notice: this program is used to partition a graph with proper size, whose vertices table can be kept in memory, in PowerGraph way. Thus, we need a distributed version to handle that too large graph. ''' import sys import random from os import listdir from os.path import isfile, join #from sets import Set def PowerGraphPar(edgesFile, numOfPar): # the file to be partitioned(edges file) partitionedFile = edgesFile # the number of partitions requested numOfPartitions = numOfPar # build a table to store the current number of edges in each partition parInfoTable = {} for i in range(1, numOfPartitions+1): parInfoTable[i] = 0 # the number of edges(number of lines in partitionedFile) numEdges = 0 # the number of vertices numOfVertices = 0 # a dict to store the vertices in each partition vdic = {} # the partitioning results to display parRs = "" # build a table to store number of edges from each vertex and its machines assigned later, e.g. A(v) # {vertexId:(edgesNum, (machines))} verticesDict = {} with open(partitionedFile, 'r') as f: for line in f: # if line.startswith("#"): # break numEdges = numEdges + 1 srcTar = line.strip().split() # a -> b => a follows b ?? srcV = long(srcTar[0]) # src = long(srcTar[1]) tarV = long(srcTar[1]) if srcV in verticesDict: verticesDict[srcV] = (verticesDict[srcV][0] + 1, set()) else: # emptySet = set() verticesDict[srcV] = (1, set()) if tarV not in verticesDict: verticesDict[tarV] = (0, set()) # the max number of edges in each partition(file) obtained from partitioning edgesInEachFile = numEdges / numOfPartitions + numEdges % numOfPartitions # the files of partitions # sub_files = [open(partitionedFile + 'Sub_%i.txt' % i, 'w') for i in range(0, numOfPartitions)] # a list to store the edges and their partition id # [(1, 10, {"partition": 2}), ...] partitions = [] count = 0 with open(partitionedFile, 'r') as input: for line in input: # if line.startswith("#"): # break count = count + 1 print count srcTar = line.strip().split() # a -> b => a follows b ?? srcV = long(srcTar[0]) # src = long(srcTar[1]) tarV = long(srcTar[1]) srcUnassigned = verticesDict[srcV][0] srcMachines = verticesDict[srcV][1] tarUnassigned = verticesDict[tarV][0] tarMachines = verticesDict[tarV][1] parId = -1 #dic1 = {} #dic1["partition"] = parId #partitions.append((src, tar, dic1)) if (not srcMachines) and (not tarMachines): # choose the 1st partition with min edges parId = min(parInfoTable, key=parInfoTable.get) dic1 = {} dic1["partition"] = parId partitions.append((srcV, tarV, dic1)) parInfoTable[parId] = parInfoTable[parId] + 1 # print srcMachines # print srcV srcMachines.add(parId) tarMachines.add(parId) else: if len(srcMachines) != 0 and len(tarMachines) != 0: intersection = srcMachines & tarMachines if (len(intersection) == 0): tmp = set() tmp2 = set() if srcUnassigned > tarUnassigned: tmp = srcMachines tmp2 = tarMachines else: tmp = tarMachines tmp2 = srcMachines for t in tmp: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: for t in tmp2: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: parId = min(parInfoTable, key=parInfoTable.get) #sub_files[parId].write(line) dic1 = {} dic1["partition"] = parId partitions.append((srcV, tarV, dic1)) parInfoTable[parId] = parInfoTable[parId] + 1 srcMachines.add(parId) tarMachines.add(parId) else: for t in intersection: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: for t in (srcMachines | tarMachines) - intersection: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: parId = min(parInfoTable, key=parInfoTable.get) #sub_files[parId].write(line) dic1 = {} dic1["partition"] = parId partitions.append((srcV, tarV, dic1)) parInfoTable[parId] = parInfoTable[parId] + 1 srcMachines.add(parId) tarMachines.add(parId) else: if (len(srcMachines) == 0 or len(tarMachines) == 0) and (len(srcMachines) + len(tarMachines)) > 0: tmp = set() if len(srcMachines) == 0: tmp = tarMachines else: tmp = srcMachines for t in tmp: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: parId = min(parInfoTable, key=parInfoTable.get) #sub_files[parId].write(line) dic1 = {} dic1["partition"] = parId partitions.append((srcV, tarV, dic1)) parInfoTable[parId] = parInfoTable[parId] + 1 srcMachines.add(parId) tarMachines.add(parId) verticesDict[srcV] = (verticesDict[srcV][0] - 1, verticesDict[srcV][1]) if vdic.has_key(parId): vdic[parId].add(srcV) vdic[parId].add(tarV) else: vs = set() vs.add(srcV) vs.add(tarV) vdic[parId] = vs overall = 0L for id, vs in vdic.iteritems(): overall += len(vs) vs = vdic[1] for i in range(2, int(numOfPar) + 1): vs.update(vdic[i]) numOfVertices = len(vs) vrf = overall / float(numOfVertices) # to store/print the size of each partition sizeStr = "" for id, en in parInfoTable.iteritems(): sizeStr += str(en) + "\n" # the partitioning result(string) parRs = "*PowerGraph Partitioning*\n" + "Vertices: " + str(numOfVertices) + "\n" + "Edges: " + str(numEdges) + "\n" + \ "Size of Each Partition: \n" + sizeStr + "Vertex Replica Factor: \n" + str(vrf) return partitions, [], parRs # *************************************************** ''' # the file to be partitioned(edges file) partitionedFile = sys.argv[1] # the number of partitions requested numOfPartitions = int(sys.argv[2]) # build a table to store the current number of edges in each partition parInfoTable = {} for i in range(0,numOfPartitions): parInfoTable[i] = 0 # the number of edges(number of lines in partitionedFile) numEdges = 0 # build a table to store number of edges from each vertex and its machines assigned later, e.g. A(v) # {vertexId:(edgesNum, (machines))} verticesDict = {} with open(partitionedFile, 'r') as f: for line in f: #if line.startswith("#"): # break numEdges = numEdges + 1 srcV, tarV = line.strip().split() if srcV in verticesDict: verticesDict[srcV] = (verticesDict[srcV][0]+1, set()) else: #emptySet = set() verticesDict[srcV] = (1, set()) if tarV not in verticesDict: verticesDict[tarV] = (0, set()) print 'the number of edges: '+str(numEdges) print verticesDict['1'] # the max number of edges in each partition(file) obtained from partitioning edgesInEachFile = numEdges/numOfPartitions + numEdges%numOfPartitions # the files of partitions sub_files = [open(partitionedFile+'Sub_%i.txt' %i, 'w') for i in range(0,numOfPartitions)] count = 0 with open(partitionedFile, 'r') as input: for line in input: #if line.startswith("#"): # break count = count + 1 print count srcV, tarV = line.strip().split() srcUnassigned = verticesDict[srcV][0] srcMachines = verticesDict[srcV][1] tarUnassigned = verticesDict[tarV][0] tarMachines = verticesDict[tarV][1] parId = -1 if (not srcMachines) and (not tarMachines): # choose the 1st partition with min edges parId = min(parInfoTable, key=parInfoTable.get) sub_files[parId].write(line) parInfoTable[parId] = parInfoTable[parId]+1 #print srcMachines #print srcV srcMachines.add(parId) tarMachines.add(parId) else: if len(srcMachines)!=0 and len(tarMachines)!=0: intersection = srcMachines & tarMachines if(len(intersection)==0): tmp = set() tmp2 = set() if srcUnassigned > tarUnassigned: tmp = srcMachines tmp2 = tarMachines else: tmp = tarMachines tmp2 = srcMachines for t in tmp: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: for t in tmp2: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: parId = min(parInfoTable, key=parInfoTable.get) sub_files[parId].write(line) parInfoTable[parId] = parInfoTable[parId]+1 srcMachines.add(parId) tarMachines.add(parId) else: for t in intersection: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: for t in (srcMachines|tarMachines)-intersection: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: parId = min(parInfoTable, key=parInfoTable.get) sub_files[parId].write(line) parInfoTable[parId] = parInfoTable[parId]+1 srcMachines.add(parId) tarMachines.add(parId) else: if (len(srcMachines)==0 or len(tarMachines)==0) and (len(srcMachines)+len(tarMachines))>0: tmp = set() if len(srcMachines)==0: tmp = tarMachines else: tmp = srcMachines for t in tmp: if parInfoTable[t] < edgesInEachFile: parId = t break if parId == -1: parId = min(parInfoTable, key=parInfoTable.get) sub_files[parId].write(line) parInfoTable[parId] = parInfoTable[parId]+1 srcMachines.add(parId) tarMachines.add(parId) verticesDict[srcV] = (verticesDict[srcV][0]-1, verticesDict[srcV][1]) for f in sub_files: f.close() '''

34.514212

123

0.463877

1,206

13,357

5.126036

0.144279

0.019411

0.009706

0.048528

0.816241

0.809123

0.78583

0.770948

0

0.01552

0.445235

13,357

386

124

34.603627

0.818758

0.097552

0

0.496403

0

0.021668

0

0.007194

0

null

0

0.028777

null

0.007194

0

null

0

1

0

null

0

1

0

7