xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

e95b7c4a4d32de04f316ef321c194f5dcc2591e2

186

py

Python

partnerships/admin.py

leonunesbs/aaafuria-rebon-backend

a969eab64b4968574f2d4ed0d746ca7cc63bf82b

[ "MIT" ]

1

2022-02-23T01:04:51.000Z

partnerships/admin.py

leonunesbs/aaafuria-rebon-backend

a969eab64b4968574f2d4ed0d746ca7cc63bf82b

[ "MIT" ]

65

2021-12-12T13:20:58.000Z

2022-03-29T17:03:43.000Z

partnerships/admin.py

leonunesbs/aaafuria-rebon-backend

a969eab64b4968574f2d4ed0d746ca7cc63bf82b

[ "MIT" ]

1

2022-03-06T17:50:49.000Z

from django.contrib import admin import partnerships.models as partnerships_models @admin.register(partnerships_models.Partnership) class PartnershipAdmin(admin.ModelAdmin): pass

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e9ae451dd2b75474ed4b70e68e92c5a9253d62d1

57,443

py

Python

data_loader/data_helper.py

JiaHe-yogurt/GNN

6b6dbc362591b4521e0b437d17ab09c1c879aa75

[ "Apache-2.0" ]

null

data_loader/data_helper.py

JiaHe-yogurt/GNN

6b6dbc362591b4521e0b437d17ab09c1c879aa75

[ "Apache-2.0" ]

null

data_loader/data_helper.py

JiaHe-yogurt/GNN

6b6dbc362591b4521e0b437d17ab09c1c879aa75

[ "Apache-2.0" ]

null

import networkx as nx from sklearn import preprocessing import numpy as np import os import collections import networkx as nx import matplotlib.pyplot as plt import random import numpy as np from itertools import permutations, combinations import tensorflow.compat.v1 as tf tf.disable_eager_execution() from numpy.linalg import matrix_power from scipy import sparse import pickle import copy tf.disable_eager_execution() NUM_LABELS = {'ENZYMES': 3, 'COLLAB': 0, 'IMDBBINARY': 0, 'IMDBMULTI': 0, 'MUTAG': 7, 'NCI1': 37, 'NCI109': 38, 'PROTEINS': 3, 'PTC': 22, 'DD': 89} BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) def normalize(graph): D_inv = np.diag(np.sum(graph, axis=0) ** -0.5) graph = np.matmul(np.matmul(D_inv, graph), D_inv) return graph def A_power(graph_adj): top = graph_adj.shape[0]-1 D_inv = np.diag(np.sum(graph_adj, axis=0) ** -0.5) graph_adj = np.matmul(np.matmul(D_inv, graph_adj), D_inv) adj_powers=[matrix_power(graph_adj,i+1) - matrix_power(graph_adj,i) for i in range(1, top+1)] adj_powers.insert(0,graph_adj) return np.array(adj_powers) #top = graph_adj.shape[0] #adj_powers, diffs = [],[] #adj_powers.append(graph_adj) #diffs.append(graph_adj) #for p in range(2,top+1): # power, diff = correct_A_power(p, graph_adj, adj_powers) # adj_powers.append(power), diffs.append(diff) return np.array(diffs) def correct_A_power(p,graph_adj,adj_powers): adj_power = matrix_power(graph_adj,p) + adj_powers[-1] np.fill_diagonal(adj_power, 0) adj_power[np.where(adj_power > 0)] = 1 diff = adj_power - adj_powers[-1] return adj_power, diff def load_dataset_ori(ds_name): """ construct graphs and labels from dataset text in data folder :param ds_name: name of data set you want to load :return: two numpy arrays of shape (num_of_graphs). the graphs array contains in each entry a ndarray represent adjacency matrix of a graph of shape (num_vertex, num_vertex, num_vertex_labels) the labels array in index i represent the class of graphs[i] """ directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name) graphs = [] labels = [] with open(directory, "r") as data: num_graphs = int(data.readline().rstrip().split(" ")[0]) for i in range(num_graphs): graph_meta = data.readline().rstrip().split(" ") num_vertex = int(graph_meta[0]) curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name]+1), dtype=np.float32) labels.append(int(graph_meta[1])) for j in range(num_vertex): vertex = data.readline().rstrip().split(" ") if NUM_LABELS[ds_name] != 0: curr_graph[j, j, int(vertex[0])+1] = 1. for k in range(2,len(vertex)): curr_graph[j, int(vertex[k]), 0] = 1. # curr_graph = noramlize_graph(curr_graph) graphs.append(curr_graph) graphs = np.array(graphs) for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2,0,1]) return graphs, np.array(labels) def load_dataset(ds_name): directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name) graphs = [] labels = [] with open(directory, "r") as data: num_graphs = int(data.readline().rstrip().split(" ")[0]) for i in range(num_graphs): graph_meta = data.readline().rstrip().split(" ") num_vertex = int(graph_meta[0]) curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name] + 1), dtype=np.float32) labels.append(int(graph_meta[1])) # ori for j in range(num_vertex): vertex = data.readline().rstrip().split(" ") if NUM_LABELS[ds_name] != 0: curr_graph[j, j, int(vertex[0]) + 1] = int(vertex[0]) + 1 for k in range(2, len(vertex)): curr_graph[j, int(vertex[k]), 0] = 1. # curr_graph = noramlize_graph(curr_graph) graphs.append(curr_graph) graphs = np.array(graphs) labels = np.array(labels) # ori # dim = [graph.shape[0] for graph in graphs] # sort = (sorted([(x, i) for (i, x) in enumerate(dim)], reverse=True)[:110]) # graphs = np.delete(graphs, ([sort[i][1] for i in range(len(sort))]), axis=0) # labels = np.delete(labels, ([sort[i][1] for i in range(len(sort))]), axis=0) for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2, 0, 1]) ## ori: use all features # edge_feature = Edge_Label(graphs[i]) # adj_powers = A_power(graphs[i][0]) # graphs[i] = np.concatenate((adj_powers, edge_feature), axis=0) adj_powers = A_power(graphs[i][0]) graphs[i] = np.concatenate((graphs[i], adj_powers[1:]), axis=0) # max_dim = max([graph.shape[0] for graph in graphs]) # for i in range(graphs.shape[0]): # padded = np.zeros((max_dim - graphs[i].shape[0], graphs[i].shape[1], graphs[i].shape[2])) # graphs[i] = np.concatenate((graphs[i], padded), axis=0) return graphs, labels def load_dataset2s(ds_name): graph_dict=dict(zip([5,6,9,12,15,16,25], [0.7,0.7,0.6,0.8,0.8,0.8,0.7])) num_rep=[100,100,100,200,200,200,200] # graph_dict=dict(zip([5,6,9,12,15,16], [0.7,0.7,0.6,0.8, 0.8,0.8])) # num_rep=[100,100,100,200,200,200] graphs = [] labels = [] for num, (k,v) in zip(num_rep, graph_dict.items()): G = nx.erdos_renyi_graph(k, v, seed=1, directed=False) #plt.subplot(121) #nx.draw(G,with_labels=True) label=nx.clique.graph_clique_number(G) A=nx.to_numpy_matrix(G,nodelist=list(range(len(G.nodes)))) graphs.append(A) labels.append(label) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) A_new=nx.to_numpy_matrix(G_new, nodelist=list(range(len(G_new.nodes)))) graphs.append(A_new) labels.append(label) graphs = np.array(graphs) labels = np.array(labels) for i in range(graphs.shape[0]): # graphs[i] = A_power(graphs[i]) graphs[i] = np.expand_dims(graphs[i], axis=0) # use only A # max_dim = max([graph.shape[0] for graph in graphs]) # for i in range(graphs.shape[0]): # padded = np.zeros((max_dim-graphs[i].shape[0], graphs[i].shape[1], graphs[i].shape[1])) # graphs[i] =np.concatenate([graphs[i], padded], axis=0) le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique return graphs, labels def load_dataset_2s_val(ds_name): """ construct graphs and labels from dataset text in data folder :param ds_name: name of data set you want to load :return: two numpy arrays of shape (num_of_graphs). the graphs array contains in each entry a ndarray represent adjacency matrix of a graph of shape (num_vertex, num_vertex, num_vertex_labels) the labels array in index i represent the class of graphs[i] """ graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) num_rep = [20, 20, 20, 30, 30, 30, 30] # graph_dict=dict(zip([5,6,9], [0.6,0.7,0.6])) # num_rep=[3,3,3] graphs = [] labels = [] for num, (k, v) in zip(num_rep, graph_dict.items()): G = nx.erdos_renyi_graph(k, v, seed=1, directed=False) # plt.subplot(121) # nx.draw(G,with_labels=True) label = nx.clique.graph_clique_number(G) A = nx.to_numpy_matrix(G, nodelist=list(range(len(G.nodes)))) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) u, v = random.sample(range(G_new.number_of_nodes() + 1), 2) G_new.add_edge(u, v) if G_new.number_of_edges() == G.number_of_edges() + 1: if nx.clique.graph_clique_number(G_new) == label: A_new = nx.to_numpy_matrix(G_new, nodelist=list(range(len(G_new.nodes)))) graphs.append(A_new) labels.append(label) graphs = np.array(graphs) labels = np.array(labels) for i in range(graphs.shape[0]): # graphs[i] = np.transpose(graphs[i], [2,0,1]) ## ori: use all features graphs[i] = np.expand_dims(np.expand_dims(graphs[i], axis=0), axis=0) # use only A le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique return graphs, labels def load_dataset2m(ds_name): graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) num_rep = [100, 100, 100, 200, 200, 200, 200] # graph_dict=dict(zip([5,6,9], [0.6,0.7,0.6])) # num_rep=[3,3,3] graphs = [] labels = [] for num, (k, v) in zip(num_rep, graph_dict.items()): G = nx.erdos_renyi_graph(k, v, seed=1, directed=False) # plt.subplot(121) # nx.draw(G,with_labels=True) label = nx.clique.graph_clique_number(G) A = nx.to_numpy_matrix(G, nodelist=list(range(len(G.nodes)))) graphs.append(A) labels.append(label) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) u, v = random.sample(range(G_new.number_of_nodes() + 1), 2) G_new.add_edge(u, v) if G_new.number_of_edges() == G.number_of_edges() + 1: if nx.clique.graph_clique_number(G_new) == label: A_new = nx.to_numpy_matrix(G_new, nodelist=list(range(len(G_new.nodes)))) graphs.append(A_new) labels.append(label) graphs = np.array(graphs) labels = np.array(labels) for i in range(graphs.shape[0]): # graphs[i] = np.transpose(graphs[i], [2,0,1]) ## ori: use all features graphs[i] = np.expand_dims(graphs[i], axis=0) # use only A le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique # idx = np.where(labels == 4)[0] # balance data # labels = np.delete(labels, idx[:700]) # labels = labels[:2000] # graphs = np.delete(graphs, idx[:700], axis=0) # graphs= graphs[:2000] return graphs, labels def get_train_val_indexes(num_val, ds_name): """ reads the indexes of a specific split to train and validation sets from data folder :param num_val: number of the split :param ds_name: name of data set :return: indexes of the train and test graphs """ directory = BASE_DIR + "/data/benchmark_graphs/{0}/10fold_idx".format(ds_name) train_file = "train_idx-{0}.txt".format(num_val) train_idx = [] with open(os.path.join(directory, train_file), 'r') as file: for line in file: train_idx.append(int(line.rstrip())) test_file = "test_idx-{0}.txt".format(num_val) test_idx = [] with open(os.path.join(directory, test_file), 'r') as file: for line in file: test_idx.append(int(line.rstrip())) return train_idx, test_idx def get_parameter_split(ds_name): """ reads the indexes of a specific split to train and validation sets from data folder :param ds_name: name of data set :return: indexes of the train and test graphs """ directory = BASE_DIR + "/data/benchmark_graphs/{0}/".format(ds_name) train_file = "tests_train_split.txt" train_idx = [] with open(os.path.join(directory, train_file), 'r') as file: for line in file: train_idx.append(int(line.rstrip())) test_file = "tests_val_split.txt" test_idx = [] with open(os.path.join(directory, test_file), 'r') as file: for line in file: test_idx.append(int(line.rstrip())) return train_idx, test_idx def group_same_size(graphs, labels, graphs3d): """ group graphs of same size to same array :param graphs: numpy array of shape (num_of_graphs) of numpy arrays of graphs adjacency matrix :param labels: numpy array of labels :return: two numpy arrays. graphs arrays in the shape (num of different size graphs) where each entry is a numpy array in the shape (number of graphs with this size, num vertex, num. vertex, num vertex labels) the second arrayy is labels with correspons shape """ sizes = list(map(lambda t: t.shape[1], graphs)) indexes = np.argsort(sizes) graphs = graphs[indexes] labels = labels[indexes] graphs3d = graphs3d[indexes] r_graphs = [] r_labels = [] r_graphs3d = [] one_size = [] one_size_node = [] start = 0 size = graphs[0].shape[1] for i in range(len(graphs)): if graphs[i].shape[1] == size: one_size.append(np.expand_dims(graphs[i], axis=0)) one_size_node.append(np.expand_dims(graphs3d[i], axis=0)) else: r_graphs.append(np.concatenate(one_size, axis=0)) r_graphs3d.append(np.concatenate(one_size_node, axis=0)) r_labels.append(np.array(labels[start:i])) start = i one_size = [] one_size_node = [] size = graphs[i].shape[1] one_size.append(np.expand_dims(graphs[i], axis=0)) one_size_node.append(np.expand_dims(graphs3d[i], axis=0)) r_graphs.append(np.concatenate(one_size, axis=0)) r_graphs3d.append(np.concatenate(one_size_node, axis=0)) r_labels.append(np.array(labels[start:])) return r_graphs, r_labels, r_graphs3d def QM9_group_same_size(graphs1d, graphs2d, graphs3d, labels): """ group graphs of same size to same array :param graphs: numpy array of shape (num_of_graphs) of numpy arrays of graphs adjacency matrix :param labels: numpy array of labels :return: two numpy arrays. graphs arrays in the shape (num of different size graphs) where each entry is a numpy array in the shape (number of graphs with this size, num vertex, num. vertex, num vertex labels) the second arrayy is labels with correspons shape """ sizes = list(map(lambda t: t.shape[1], graphs2d)) indexes = np.argsort(sizes) graphs1d = graphs1d[indexes] graphs2d = graphs2d[indexes] graphs3d = graphs3d[indexes] labels = labels[indexes] r_graphs1d, r_graphs2d ,r_graphs3d = [], [], [] r_labels = [] one_size1d, one_size2d, one_size3d = [],[],[] start = 0 size = graphs2d[0].shape[-1] for i in range(len(graphs2d)): if graphs2d[i].shape[-1] == size: one_size1d.append(np.expand_dims(graphs1d[i], axis=0)) one_size2d.append(np.expand_dims(graphs2d[i], axis=0)) one_size3d.append(np.expand_dims(graphs3d[i], axis=0)) else: r_graphs1d.append(np.concatenate(one_size1d, axis=0)) r_graphs2d.append(np.concatenate(one_size2d, axis=0)) r_graphs3d.append(np.concatenate(one_size3d, axis=0)) r_labels.append(np.array(labels[start:i])) start = i one_size1d ,one_size2d ,one_size3d = [], [], [] size = graphs2d[i].shape[-1] one_size1d.append(np.expand_dims(graphs1d[i], axis=0)) one_size2d.append(np.expand_dims(graphs2d[i], axis=0)) one_size3d.append(np.expand_dims(graphs3d[i], axis=0)) r_graphs1d.append(np.concatenate(one_size1d, axis=0)) r_graphs2d.append(np.concatenate(one_size2d, axis=0)) r_graphs3d.append(np.concatenate(one_size3d, axis=0)) r_labels.append(np.array(labels[start:])) return r_graphs1d, r_graphs2d, r_graphs3d, r_labels # helper method to shuffle each same size graphs array def shuffle_same_size(graphs, labels, graphs3d): r_graphs, r_labels, r_graphs3d = [], [], [] for i in range(len(labels)): curr_graph, curr_labels, curr_nodefeature = shuffle(graphs[i], labels[i], graphs3d[i]) r_graphs.append(curr_graph) r_graphs3d.append(curr_nodefeature ) r_labels.append(curr_labels) return r_graphs, r_labels, r_graphs3d def QM9_shuffle_same_size(graphs1d, graphs2d, graphs3d, labels): r_graphs1d, r_graphs2d, r_labels, r_graphs3d = [], [], [], [] for i in range(len(labels)): curr_graph1d, curr_graph2d,curr_graph3d, curr_labels = QM9_shuffle(graphs1d[i], graphs2d[i], graphs3d[i],labels[i]) r_graphs1d.append(curr_graph1d) r_graphs2d.append(curr_graph2d) r_graphs3d.append(curr_graph3d ) r_labels.append(curr_labels) return r_graphs1d, r_graphs2d, r_graphs3d, r_labels def split_to_batches(graphs, labels, graphs3d, size): """ split the same size graphs array to batches of specified size last batch is in size num_of_graphs_this_size % size :param graphs: array of arrays of same size graphs :param labels: the corresponding labels of the graphs :param size: batch size :return: two arrays. graphs array of arrays in size (batch, num vertex, num vertex. num vertex labels) corresponds labels """ r_graphs = [] r_labels = [] r_graphs3d = [] for k in range(len(graphs)): r_graphs = r_graphs + np.split(graphs[k], [j for j in range(size, graphs[k].shape[0], size)]) r_graphs3d = r_graphs3d + np.split(graphs3d[k], [j for j in range(size, graphs3d[k].shape[0], size)]) r_labels = r_labels + np.split(labels[k], [j for j in range(size, labels[k].shape[0], size)]) return np.array(r_graphs), np.array(r_labels), np.array(r_graphs3d) def QM9_split_to_batches(graphs1d, graphs2d, graphs3d, labels, size): """ split the same size graphs array to batches of specified size last batch is in size num_of_graphs_this_size % size :param graphs: array of arrays of same size graphs :param labels: the corresponding labels of the graphs :param size: batch size :return: two arrays. graphs array of arrays in size (batch, num vertex, num vertex. num vertex labels) corresponds labels """ r_graphs1d, r_graphs2d, r_graphs3d = [],[],[] r_labels = [] for k in range(len(graphs2d)): r_graphs1d = r_graphs1d + np.split(graphs1d[k], [j for j in range(size, graphs1d[k].shape[0], size)]) r_graphs2d = r_graphs2d + np.split(graphs2d[k], [j for j in range(size, graphs2d[k].shape[0], size)]) r_graphs3d = r_graphs3d + np.split(graphs3d[k], [j for j in range(size, graphs3d[k].shape[0], size)]) r_labels = r_labels + np.split(labels[k], [j for j in range(size, labels[k].shape[0], size)]) return np.array(r_graphs1d), np.array(r_graphs2d), np.array(r_graphs3d), np.array(r_labels) # helper method to shuffle the same way graphs and labels arrays def shuffle(graphs, labels, graphs3d): shf = np.arange(labels.shape[0], dtype=np.int32) #np.random.seed(1) np.random.shuffle(shf) return np.array(graphs)[shf], labels[shf], np.array(graphs3d)[shf] def QM9_shuffle(graphs1d,graphs2d,graphs3d, labels): shf = np.arange(labels.shape[0], dtype=np.int32) #np.random.seed(1) np.random.shuffle(shf) return np.array(graphs1d)[shf],np.array(graphs2d)[shf] , np.array(graphs3d)[shf], labels[shf] def noramlize_graph(curr_graph): split = np.split(curr_graph, [1], axis=2) adj = np.squeeze(split[0], axis=2) deg = np.sqrt(np.sum(adj, 0)) deg = np.divide(1., deg, out=np.zeros_like(deg), where=deg != 0) normal = np.diag(deg) norm_adj = np.expand_dims(np.matmul(np.matmul(normal, adj), normal), axis=2) ones = np.ones(shape=(curr_graph.shape[0], curr_graph.shape[1], curr_graph.shape[2]), dtype=np.float32) spred_adj = np.multiply(ones, norm_adj) labels = np.append(np.zeros(shape=(curr_graph.shape[0], curr_graph.shape[1], 1)), split[1], axis=2) return np.add(spred_adj, labels) def load_dataset3s(ds_name, upper=True): graphs, adj_powers, graphs3d = [], [], [] labels = [] if ds_name == 'syn': graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) # graph_dict=dict(zip([5,6,9,12], [0.7,0.7,0.6,0.8,0.8,0.8,0.7])) num_rep = [100, 100, 100, 200, 200, 200, 200] for num, (k, v) in zip(num_rep, graph_dict.items()): G = nx.erdos_renyi_graph(k, v, seed=1, directed=False) adj = nx.linalg.graphmatrix.adjacency_matrix(G).toarray() graphs.append(adj) label = nx.clique.graph_clique_number(G) if upper == False: A = construct_A3(G) adj_power = A_power(adj) else: A = construct_upperA3(G) adj_power = A_power(adj) graphs3d.append(A) adj_powers.append(adj_power) labels.append(label) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) adj_new = nx.linalg.graphmatrix.adjacency_matrix(G_new).toarray() if upper == False: A_new = construct_A3(G_new) adj_power = A_power(adj_new) else: A_new = construct_upperA3(G_new) adj_power = A_power(adj_new) graphs.append(adj) graphs3d.append(A_new) adj_powers.append(adj_power) labels.append(label) if k == list(graph_dict.keys())[-1]: zero = np.zeros((k + 1, k + 1, k + 1)) graphs.append(zero) adj_powers.append(zero) graphs3d.append(zero) graphs = np.array(graphs) labels = np.array(labels) graphs3d = np.array(graphs3d) adj_powers = np.array(adj_powers) for i in range(graphs.shape[0]): # graphs[i] = np.expand_dims(graphs[i], axis=0) graphs[i] = adj_powers[i] graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) graphs = tf.ragged.constant(graphs).to_tensor().eval(session=tf.Session()) graphs3d = tf.ragged.constant(graphs3d).to_tensor().eval(session=tf.Session()) graphs = np.delete(graphs, -1, axis=0) graphs3d = np.delete(graphs3d, -1, axis=0) # graphs = np.delete(graphs, -1, axis=0) le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique else: directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name) with open(directory, "r") as data: num_graphs = int(data.readline().rstrip().split(" ")[0]) for i in range(num_graphs): graph_meta = data.readline().rstrip().split(" ") num_vertex = int(graph_meta[0]) curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name] + 1), dtype=np.float32) labels.append(int(graph_meta[1])) # ori for j in range(num_vertex): vertex = data.readline().rstrip().split(" ") if NUM_LABELS[ds_name] != 0: curr_graph[j, j, int(vertex[0]) + 1] = 1. for k in range(2, len(vertex)): curr_graph[j, int(vertex[k]), 0] = 1. # curr_graph = noramlize_graph(curr_graph) graphs.append(curr_graph) graphs = np.array(graphs) for i in range(graphs.shape[0]): graphs[i] = np.expand_dims(np.transpose(graphs[i], [2, 0, 1])[0], axis=0) # use only A G = nx.from_numpy_array(graphs[i][0]) graphs[i] = construct_upperA3(G) graphs[i] = np.expand_dims(graphs[i], axis=0) labels = np.array(labels) return graphs, labels, graphs3d def load_dataset_3s_val(ds_name, upper): graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) # graph_dict=dict(zip([5,6,9,12], [0.7,0.7,0.6,0.8,0.8,0.8,0.7])) num_rep = [20, 20, 20, 30, 30, 30, 30] # graph_dict=dict(zip([5,6,9], [0.6,0.7,0.6])) # num_rep=[3,3,3] graphs, adj_powers, graphs3d = [], [], [] labels = [] for num, (k, v) in zip(num_rep, graph_dict.items()): G = nx.erdos_renyi_graph(k, v, seed=1, directed=False) label = nx.clique.graph_clique_number(G) if upper == False: A = construct_A3(G) else: A = construct_upperA3(G) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) u, v = random.sample(range(G_new.number_of_nodes() + 1), 2) G_new.add_edge(u, v) if G_new.number_of_edges() == G.number_of_edges() + 1: if nx.clique.graph_clique_number(G_new) == label: adj = nx.linalg.graphmatrix.adjacency_matrix(G_new).toarray() if upper == False: A_new = construct_A3(G_new) adj_power = A_power(adj) else: A_new = construct_upperA3(G_new) adj_power = A_power(adj) graphs3d.append(A_new) labels.append(label) graphs.append(adj_power) graphs = np.array(graphs) labels = np.array(labels) graphs3d = np.array(graphs3d) # graphs = tf.ragged.constant(graphs).to_tensor().eval(session=tf.Session()) for i in range(graphs.shape[0]): graphs[i] = np.expand_dims(graphs[i], axis=0) graphs3d[i] = np.expand_dims(np.expand_dims(graphs3d[i], axis=0), axis=0) graphs = tf.ragged.constant(graphs).to_tensor().eval(session=tf.Session()) graphs3d = tf.ragged.constant(graphs3d).to_tensor().eval(session=tf.Session()) # for i in range(graphs.shape[0]): # graphs[i] = np.expand_dims(np.expand_dims(graphs[i], axis=0), axis=0) # graphs3d[i] = np.expand_dims( np.expand_dims(graphs3d[i], axis=0), axis=0) le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique return graphs, labels, graphs3d def load_dataset3m(ds_name, upper): import tensorflow.compat.v1 as tf tf.disable_eager_execution graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) num_rep = [100, 100, 100, 200, 200, 200, 200] # graph_dict=dict(zip([5,6,9], [0.6,0.7,0.6])) # num_rep=[3,3,3] graphs = [] labels = [] for num, (k, v) in zip(num_rep, graph_dict.items()): G = nx.erdos_renyi_graph(k, v, seed=1, directed=False) label = nx.clique.graph_clique_number(G) if upper == False: A = construct_A3(G) else: A = construct_upperA3(G) graphs.append(A) labels.append(label) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) u, v = random.sample(range(G_new.number_of_nodes() + 1), 2) G_new.add_edge(u, v) if G_new.number_of_edges() == G.number_of_edges() + 1: if nx.clique.graph_clique_number(G_new) == label: if upper == False: A_new = construct_A3(G_new) else: A_new = construct_upperA3(G_new) graphs.append(A_new) labels.append(label) graphs = np.array(graphs) labels = np.array(labels) graphs = tf.ragged.constant(graphs).to_tensor().eval(session=tf.Session()) le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique # idx = np.where(labels == 4)[0] # balance data # labels = np.delete(labels, idx[:700]) # labels = labels[:2000] # graphs = np.delete(graphs, idx[:700], axis=0) # graphs= graphs[:2000] return graphs, labels def load_dataset3s_large(ds_name, upper): graph_dict = dict(zip([7, 8, 9], [1, 1, 1, 1, 1, 1, 1])) num_rep = [20, 20, 20, 50, 50, 200, 200] graphs = [] labels = [] for num, (k, v) in zip(num_rep, graph_dict.items()): G, label = construct_graph(k, v, sub_size=1) if upper == False: A = construct_A3(G) else: A = construct_upperA3(G) graphs.append(A) labels.append(label) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) if upper == False: A_new = construct_A3(G_new) else: A_new = construct_upperA3(G_new) graphs.append(A_new) labels.append(label) graphs = np.array(graphs) labels = np.array(labels) max_dim = max([graph.shape[0] for graph in graphs]) + 1 for i in range(graphs.shape[0]): padded = np.zeros((max_dim, max_dim, max_dim)) padded[:graphs[i].shape[0], :graphs[i].shape[1], :graphs[i].shape[2]] = graphs[i] graphs[i] = padded le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique return graphs, labels def load_dataset_3s_large_val(ds_name, upper): graph_dict = dict(zip([7, 8, 9], [1, 1, 1, 1, 1, 1, 1])) num_rep = [15, 15, 15, 50, 50, 200, 200] graphs = [] labels = [] for num, (k, v) in zip(num_rep, graph_dict.items()): G, label = construct_graph(k, v, sub_size=1) for graph in range(num): node_mapping = dict(zip(G.nodes(), sorted(G.nodes(), key=lambda k: random.random()))) G_new = nx.relabel_nodes(G, node_mapping) f, t = random.sample(range(G_new.number_of_nodes() + 1), 2) G_new.add_edge(f, t) f, t = random.sample(range(G_new.number_of_nodes() + 1), 2) G_new.add_edge(f, t) if G_new.number_of_edges() >= G.number_of_edges() + 1: if upper == False: A_new = construct_A3(G_new) else: A_new = construct_upperA3(G_new) graphs.append(A_new) labels.append(label) graphs = np.array(graphs) labels = np.array(labels) max_dim = max([graph.shape[0] for graph in graphs]) for i in range(graphs.shape[0]): padded = np.zeros((max_dim, max_dim, max_dim)) padded[:graphs[i].shape[0], :graphs[i].shape[1], :graphs[i].shape[2]] = graphs[i] graphs[i] = padded graphs = list(graphs) for i in range(len(graphs)): # graphs[i] = np.transpose(graphs[i], [2,0,1]) ## ori: use all features graphs[i] = np.expand_dims(graphs[i], axis=0) le = preprocessing.LabelEncoder() # to find clique le.fit(labels) # to find clique labels = le.transform(labels) # to find clique return graphs, labels def construct_graph(k, v, sub_size): G = nx.erdos_renyi_graph(k, v, directed=False) sub_k, sub_v = np.int(k * sub_size), 0.1 G2 = nx.erdos_renyi_graph(sub_k, sub_v, directed=False) G3 = nx.disjoint_union(G, G2) G3.add_edge(G.number_of_nodes() - 1, G.number_of_nodes()) label = nx.clique.graph_clique_number(G3) return G3, label def get_cliques_by_length(G, length_clique): """ Return the list of all cliques in an undirected graph G with length equal to length_clique. """ cliques = [] for c in nx.enumerate_all_cliques(G): if len(c) <= length_clique: if len(c) == length_clique: cliques.append(c) else: return cliques # return empty list if nothing is found return cliques def construct_A3(G, length_clique=3): tri = get_cliques_by_length(G, 3) # print(tri) nn = G.number_of_nodes() A3 = np.zeros((nn, nn, nn), dtype='float32') for i in tri: perm = permutations(i) for j in list(perm): A3[j] = 1 return A3 def construct_upperA3(G, length_clique=3): tri = get_cliques_by_length(G, 3) # print(tri) nn = G.number_of_nodes() A3 = np.zeros((nn, nn, nn), dtype='float32') for i in tri: A3[tuple(i)] = 1 return A3 def motif(shape): target = nx.Graph() if shape == 'tree': target.add_edge(1, 2) target.add_edge(2, 3) if shape == 'triangle': target.add_edge(1, 2) target.add_edge(2, 3) target.add_edge(1, 3) if shape == 'tail_triangle': target.add_edge(1, 2) target.add_edge(2, 3) target.add_edge(1, 3) target.add_edge(1, 4) if shape == 'star': target.add_edge(1, 2) target.add_edge(1, 3) target.add_edge(1, 4) if shape == 'chain': target.add_edge(1, 2) target.add_edge(2, 3) target.add_edge(3, 4) if shape == 'box': target.add_edge(1, 2) target.add_edge(2, 3) target.add_edge(3, 4) target.add_edge(1, 4) if shape == 'semi_clique': target.add_edge(1, 2) target.add_edge(2, 3) target.add_edge(3, 4) target.add_edge(1, 4) target.add_edge(1, 3) if shape == '4_clique': target.add_edge(1, 2) target.add_edge(2, 3) target.add_edge(3, 4) target.add_edge(1, 4) target.add_edge(1, 3) target.add_edge(2, 4) return target def high_order(g, target): nn = g.number_of_nodes() sub_node = [] if target.number_of_nodes() == 3: A = np.zeros((nn, nn, nn), dtype='float32') for sub_nodes in combinations(g.nodes(), len(target.nodes())): subg = g.subgraph(sub_nodes) if nx.is_connected(subg) and nx.is_isomorphic(subg, target): A[tuple(subg.nodes())] = 1 sub_node.append(tuple(subg.nodes())) if target.number_of_nodes() == 4: A = np.zeros((nn, nn, nn, nn), dtype='float32') for sub_nodes in combinations(g.nodes(), len(target.nodes())): subg = g.subgraph(sub_nodes) if nx.is_connected(subg) and nx.is_isomorphic(subg, target): A[tuple(subg.nodes())] = 1 sub_node.append(tuple(subg.nodes())) label = len(sub_node) return A, label, sub_node def high_order2(g, target): nn = g.number_of_nodes() sub_node = [] if target.number_of_nodes() == 3: A = np.zeros((nn, nn, nn), dtype='float32') for sub_nodes in combinations(g.nodes(), len(target.nodes())): subg = g.subgraph(sub_nodes) if nx.is_connected(subg) and nx.is_isomorphic(subg, target): center_node = list(set(list(subg.edges)[0]).intersection(set(list(subg.edges)[1]))) edge_nodes = list(set(tuple(subg.nodes())).difference(set((center_node)))) A[center_node[0], edge_nodes[0], edge_nodes[1]] = 1 A[center_node[0], edge_nodes[1], edge_nodes[0]] = 1 A[edge_nodes[0], center_node[0], edge_nodes[1]] = 1 A[edge_nodes[1], center_node[0], edge_nodes[0]] = 1 sub_node.append(tuple(subg.nodes())) if target.number_of_nodes() == 4: A = np.zeros((nn, nn, nn, nn), dtype='float32') for sub_nodes in combinations(g.nodes(), len(target.nodes())): subg = g.subgraph(sub_nodes) if nx.is_connected(subg) and nx.is_isomorphic(subg, target): A[tuple(subg.nodes())] = 1 sub_node.append(tuple(subg.nodes())) label = len(sub_node) return A, label, sub_node def high_order3(g, target): nn = g.number_of_nodes() sub_node = [] if target.number_of_nodes() == 3: A1, A2 = np.zeros((nn, nn, nn), dtype='float32'), np.zeros((nn, nn, nn), dtype='float32') for sub_nodes in combinations(g.nodes(), len(target.nodes())): subg = g.subgraph(sub_nodes) if nx.is_connected(subg) and nx.is_isomorphic(subg, target): center_node = list(set(list(subg.edges)[0]).intersection(set(list(subg.edges)[1]))) edge_nodes = list(set(tuple(subg.nodes())).difference(set((center_node)))) A1[center_node[0], edge_nodes[0], edge_nodes[1]] = 1 A1[center_node[0], edge_nodes[1], edge_nodes[0]] = 1 A2[edge_nodes[0], center_node[0], edge_nodes[1]] = 2 A2[edge_nodes[1], center_node[0], edge_nodes[0]] = 2 sub_node.append(tuple(subg.nodes())) if target.number_of_nodes() == 4: A = np.zeros((nn, nn, nn, nn), dtype='float32') for sub_nodes in combinations(g.nodes(), len(target.nodes())): subg = g.subgraph(sub_nodes) if nx.is_connected(subg) and nx.is_isomorphic(subg, target): A[tuple(subg.nodes())] = 1 sub_node.append(tuple(subg.nodes())) label = len(sub_node) return A1, A2, label, sub_node def multihead(ds_name, target_shape): graphs, graphs3d, labels = [], [], [] if ds_name == 'syn': target = motif(target_shape) # graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) # num_rep = [100, 100, 100, 200, 200, 200, 200] graph_dict = dict(zip([8, 9, 9, 10, 10, 11, 11, 12, 13], [0.3, 0.3, 0.3, 0.3, 0.4, 0.3, 0.4, 0.2, 0.2])) num_rep = [50, 50, 50, 50, 100, 100, 100, 100, 100, 100] for num, (k, v) in zip(num_rep, graph_dict.items()): for s in range(num): G = nx.erdos_renyi_graph(k, v, seed=s, directed=False) if nx.is_connected(G): graph3d, label, _ = high_order(G, target) # label = nx.clique.graph_clique_number(G) labels.append(label) graphs3d.append(graph3d) adj = nx.linalg.graphmatrix.adjacency_matrix(G).toarray() graphs.append(adj) graphs = np.array(graphs) graphs3d = np.array(graphs3d) for i in range(graphs.shape[0]): graphs[i] = np.expand_dims(graphs[i], axis=0) graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) # le = preprocessing.LabelEncoder() # to find clique # le.fit(labels) # to find clique # labels = le.transform(labels) # to find clique else: target = motif(target_shape) directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name) with open(directory, "r") as data: num_graphs = int(data.readline().rstrip().split(" ")[0]) for i in range(num_graphs): graph_meta = data.readline().rstrip().split(" ") num_vertex = int(graph_meta[0]) curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name] + 1), dtype=np.float32) labels.append(int(graph_meta[1])) # ori for j in range(num_vertex): vertex = data.readline().rstrip().split(" ") if NUM_LABELS[ds_name] != 0: curr_graph[j, j, int(vertex[0]) + 1] = 1. for k in range(2, len(vertex)): curr_graph[j, int(vertex[k]), 0] = 1. # curr_graph = noramlize_graph(curr_graph) graphs.append(curr_graph) graphs = np.array(graphs) labels = np.array(labels) # dim = [graph.shape[0] for graph in graphs] # sort = (sorted([(x, i) for (i, x) in enumerate(dim)], reverse=True)[:100]) # graphs = np.delete(graphs, ([sort[i][1] for i in range(len(sort))]), axis=0) # labels = np.delete(labels, ([sort[i][1] for i in range(len(sort))]), axis=0) for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2, 0, 1]) # use only A G = nx.from_numpy_array(graphs[i][0]) graph3d, _, _ = high_order(G, target) graphs3d.append(graph3d) adj_powers = A_power(graphs[i][0]) graphs[i] = np.concatenate((graphs[i], adj_powers[1:]), axis=0) graphs3d = np.array(graphs3d) for i in range(graphs3d.shape[0]): graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) return graphs, np.array(labels), graphs3d def gnn3(ds_name, target_shape): graphs, graphs3d, labels, adj_powers =[], [], [], [] if ds_name == 'syn': target = motif(target_shape) # graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) # num_rep = [100, 100, 100, 200, 200, 200, 200] graph_dict = dict(zip([8, 9, 9, 10, 10, 11, 11, 12, 13], [0.3, 0.3, 0.3, 0.3, 0.4, 0.3, 0.4, 0.2, 0.2])) num_rep = [50, 50, 50, 50, 100, 100, 100, 100, 100, 100] for num, (k, v) in zip(num_rep, graph_dict.items()): for s in range(num): G = nx.erdos_renyi_graph(k, v, seed=s, directed=False) if nx.is_connected(G): graph3d, label, _ = high_order(G, target) # label = nx.clique.graph_clique_number(G) labels.append(label) graphs3d.append(graph3d) adj = nx.linalg.graphmatrix.adjacency_matrix(G).toarray() graphs.append(adj) graphs = np.array(graphs) graphs3d = np.array(graphs3d) for i in range(graphs.shape[0]): graphs[i] = np.expand_dims(graphs[i], axis=0) graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) # le = preprocessing.LabelEncoder() # to find clique # le.fit(labels) # to find clique # labels = le.transform(labels) # to find clique else: target = motif(target_shape) directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name) with open(directory, "r") as data: num_graphs = int(data.readline().rstrip().split(" ")[0]) for i in range(num_graphs): graph_meta = data.readline().rstrip().split(" ") num_vertex = int(graph_meta[0]) curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name] + 1), dtype=np.float32) labels.append(int(graph_meta[1])) # ori for j in range(num_vertex): vertex = data.readline().rstrip().split(" ") if NUM_LABELS[ds_name] != 0: curr_graph[j, j, int(vertex[0]) + 1] = 1. for k in range(2, len(vertex)): curr_graph[j, int(vertex[k]), 0] = 1. curr_graph = noramlize_graph(curr_graph) graphs.append(curr_graph) graphs = np.array(graphs) labels = np.array(labels) # dim = [graph.shape[0] for graph in graphs] # sort = (sorted([(x, i) for (i, x) in enumerate(dim)], reverse=True)[:100]) # graphs = np.delete(graphs, ([sort[i][1] for i in range(len(sort))]), axis=0) # labels = np.delete(labels, ([sort[i][1] for i in range(len(sort))]), axis=0) for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2, 0, 1]) # use only A G = nx.from_numpy_array(graphs[i][0]) graph3d, _, _ = high_order(G, target) adj_power = A_power(graphs[i][0]) graphs3d.append(graph3d) adj_powers.append(adj_power) graphs3d = np.array(graphs3d) adj_powers = np.array(adj_powers) for i in range(graphs3d.shape[0]): graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) adj_powers[i] = np.expand_dims(adj_powers[i], axis=0) graphs3d[i] = np.concatenate((graphs3d[i], adj_powers[i]), axis=0) # graphs = tf.ragged.constant(graphs).to_tensor().eval(session=tf.Session()) # graphs3d = tf.ragged.constant(graphs3d).to_tensor().eval(session=tf.Session()) return graphs, np.array(labels), graphs3d def gnn4(ds_name, target_shape): graphs, graphs3d, labels, adj_powers =[], [], [], [] if ds_name == 'syn': target = motif(target_shape) # graph_dict = dict(zip([5, 6, 9, 12, 15, 16, 25], [0.7, 0.7, 0.6, 0.8, 0.8, 0.8, 0.7])) # num_rep = [100, 100, 100, 200, 200, 200, 200] graph_dict = dict(zip([8, 9, 9, 10, 10, 11, 11, 12, 13], [0.3, 0.3, 0.3, 0.3, 0.4, 0.3, 0.4, 0.2, 0.2])) num_rep = [50, 50, 50, 50, 100, 100, 100, 100, 100, 100] for num, (k, v) in zip(num_rep, graph_dict.items()): for s in range(num): G = nx.erdos_renyi_graph(k, v, seed=s, directed=False) if nx.is_connected(G): graph3d, label, _ = high_order(G, target) # label = nx.clique.graph_clique_number(G) labels.append(label) graphs3d.append(graph3d) adj = nx.linalg.graphmatrix.adjacency_matrix(G).toarray() graphs.append(adj) graphs = np.array(graphs) graphs3d = np.array(graphs3d) for i in range(graphs.shape[0]): graphs[i] = np.expand_dims(graphs[i], axis=0) graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) # le = preprocessing.LabelEncoder() # to find clique # le.fit(labels) # to find clique # labels = le.transform(labels) # to find clique else: target = motif(target_shape) directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name) with open(directory, "r") as data: num_graphs = int(data.readline().rstrip().split(" ")[0]) for i in range(num_graphs): graph_meta = data.readline().rstrip().split(" ") num_vertex = int(graph_meta[0]) curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name] + 1), dtype=np.float32) labels.append(int(graph_meta[1])) # ori for j in range(num_vertex): vertex = data.readline().rstrip().split(" ") if NUM_LABELS[ds_name] != 0: curr_graph[j, j, int(vertex[0]) + 1] = 1. for k in range(2, len(vertex)): curr_graph[j, int(vertex[k]), 0] = 1. #curr_graph = noramlize_graph(curr_graph) graphs.append(curr_graph) graphs = np.array(graphs) labels = np.array(labels) dim = [graph.shape[0] for graph in graphs] sort = (sorted([(x, i) for (i, x) in enumerate(dim)], reverse=True)[:100]) graphs = np.delete(graphs, ([sort[i][1] for i in range(len(sort))]), axis=0) labels = np.delete(labels, ([sort[i][1] for i in range(len(sort))]), axis=0) for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2, 0, 1]) # use only A G = nx.from_numpy_array(graphs[i][0]) graph3d, _, _ = high_order(G, target) adj_power = A_power(graphs[i][0]) graphs3d.append(graph3d) adj_powers.append(adj_power) graphs3d = np.array(graphs3d) adj_powers = np.array(adj_powers) for i in range(graphs3d.shape[0]): graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) adj_powers[i] = np.expand_dims(adj_powers[i], axis=0) graphs3d[i] = np.concatenate((graphs3d[i], adj_powers[i]), axis=0) graphs[i] = np.einsum('ijj->ij', graphs[i][1:]) # graphs = tf.ragged.constant(graphs).to_tensor().eval(session=tf.Session()) # graphs3d = tf.ragged.constant(graphs3d).to_tensor().eval(session=tf.Session()) return graphs, np.array(labels), graphs3d def load_qm9_aux(which_set, target_param,target_shape): target = motif(target_shape) base_path = BASE_DIR + "/data/QM9/QM9_{}.p".format(which_set) graphs, graphs1d, graphs2d, graphs3d, labels, adj_powers =[], [], [], [],[], [] counter = 0 with open(base_path, 'rb') as f: data = pickle.load(f) for instance in data: counter += 1 if counter == 100: break labels.append(instance['y']) nodes_num = instance['usable_features']['x'].shape[0] graph = np.empty((nodes_num, nodes_num, 19)) for i in range(13): # 13 features per node - for each, create a diag matrix of it as a feature graph[:, :, i] = np.diag(instance['usable_features']['x'][:, i]) graph[:, :, 13] = instance['usable_features']['distance_mat'] graph[:, :, 14] = instance['usable_features']['affinity'] graph[:, :, 15:] = instance['usable_features']['edge_features'] # shape n x n x 4 graphs.append(graph) graphs = np.array(graphs) graphs_copy = copy.deepcopy(graphs) labels = np.array(labels).squeeze() # shape N x 12 # if target_param is not False: # regression over a specific target, not all 12 elements # labels = labels[:, target_param].reshape(-1, 1) # shape N x 1 for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2, 0, 1]) # use only A G = nx.from_numpy_array(graphs[i][14]) graph3d, _, _ = high_order2(G, target) adj_power = A_power(graphs[i][14]) graphs3d.append(graph3d) adj_powers.append(adj_power) graph1d = graphs[i][:13] graph1d = np.einsum('ijj->ij', graph1d) graphs_copy[i] = graph1d # graphs[i] = graphs[i] graphs[i] = graphs[i][13:] # graphs[i][0] = normalize(graphs[i][0]) # graphs[i][1] = normalize(graphs[i][1]) graphs3d = np.array(graphs3d) adj_powers = np.array(adj_powers) for i in range(graphs3d.shape[0]): graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) adj_powers[i] = np.expand_dims(adj_powers[i], axis=0) graphs3d[i] = np.concatenate((graphs3d[i], adj_powers[i]), axis=0) return graphs_copy, graphs, graphs3d, labels def load_qm9(target_param,target_shape): """ Constructs the graphs and labels of QM9 data set, already split to train, val and test sets :return: 6 numpy arrays: train_graphs: N_train, train_labels: N_train x 12, (or Nx1 is target_param is not False) val_graphs: N_val, val_labels: N_train x 12, (or Nx1 is target_param is not False) test_graphs: N_test, test_labels: N_test x 12, (or Nx1 is target_param is not False) each graph of shape: 19 x Nodes x Nodes (CHW representation) """ train_graphs1d, train_graphs2d, train_graphs3d, train_labels = load_qm9_aux('train', target_param,target_shape) val_graphs1d, val_graphs2d, val_graphs3d, val_labels = load_qm9_aux('val', target_param,target_shape) test_graphs1d, test_graphs2d, test_graphs3d, test_labels = load_qm9_aux('test', target_param,target_shape) return train_graphs1d, train_graphs2d, train_graphs3d, train_labels, val_graphs1d, val_graphs2d, val_graphs3d, val_labels, test_graphs1d, test_graphs2d, test_graphs3d, test_labels def load_qm9_aux_gnn3(which_set, target_param, target_shape): target = motif(target_shape) base_path = BASE_DIR + "/data/QM9/QM9_{}.p".format(which_set) graphs, graphs3d, graphs3d2,labels, adj_powers =[], [], [], [],[] counter = 0 with open(base_path, 'rb') as f: data = pickle.load(f) for instance in data: #counter += 1 #if counter == 10000: # break labels.append(instance['y']) nodes_num = instance['usable_features']['x'].shape[0] graph = np.empty((nodes_num, nodes_num, 19)) for i in range(13): # 13 features per node - for each, create a diag matrix of it as a feature graph[:, :, i] = np.diag(instance['usable_features']['x'][:, i]) graph[:, :, 13] = instance['usable_features']['distance_mat'] graph[:, :, 14] = instance['usable_features']['affinity'] graph[:, :, 15:] = instance['usable_features']['edge_features'] # shape n x n x 4 #for i in range(4): # graph[:,:,i] += graph[:,:,i+15] #graphs.append(graph[:,:,:15]) graphs = np.array(graphs) labels = np.array(labels).squeeze() # shape N x 12 # if target_param is not False: # regression over a specific target, not all 12 elements # labels = labels[:, target_param].reshape(-1, 1) # shape N x 1 for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2, 0, 1]) # use only A G = nx.from_numpy_array(graphs[i][14]) # graph3d, graph3d2, _, _ = high_order3(G, target) graph3d, _, _ = high_order2(G, target) adj_power = A_power(graphs[i][14]) graphs3d.append(graph3d) # graphs3d2.append(graph3d2) adj_powers.append(adj_power) # graphs[i][13] = normalize(graphs[i][13]) # graphs[i][14] = normalize(graphs[i][14]) graphs3d = np.array(graphs3d) #graphs3d2 = np.array(graphs3d2) adj_powers = np.array(adj_powers) for i in range(graphs3d.shape[0]): graphs3d[i] = np.expand_dims(graphs3d[i], axis=0) adj_powers[i] = np.expand_dims(adj_powers[i], axis=0) # graphs3d2[i] = np.expand_dims(graphs3d2[i], axis=0) # graphs3d[i] = np.concatenate((graphs3d[i], graphs3d2[i], adj_powers[i]), axis=0) graphs3d[i] = np.concatenate((graphs3d[i], adj_powers[i]), axis=0) return graphs, labels, graphs3d def load_qm9_gnn3(target_param,target_shape): train_graphs2d, train_labels , train_graphs3d= load_qm9_aux_gnn3('train', target_param,target_shape) val_graphs2d, val_labels, val_graphs3d = load_qm9_aux_gnn3('val', target_param,target_shape) test_graphs2d, test_labels, test_graphs3d = load_qm9_aux_gnn3('test', target_param,target_shape) return train_graphs2d, train_labels, train_graphs3d, val_graphs2d,val_labels, val_graphs3d, test_graphs2d, test_labels, test_graphs3d def gnn1(ds_name, target_shape): graphs = [] labels = [] if ds_name == 'syn': target = motif(target_shape) # graph_dict=dict(zip([5,6,6, 6, 7,8, 9, 9, 10,10], [0.7,0.4,0.5, 0.6, 0.4,0.4,0.4, 0.3, 0.4, 0.3])) graph_dict = dict(zip([8, 9, 9, 10, 10, 11, 11, 12, 13], [0.3, 0.3, 0.3, 0.3, 0.4, 0.3, 0.4, 0.2, 0.2])) num_rep = [50, 50, 50, 50, 100, 100, 100, 100, 100, 100] for num, (k, v) in zip(num_rep, graph_dict.items()): for s in range(num): G = nx.erdos_renyi_graph(k, v, seed=s, directed=False) if nx.is_connected(G): graph, label, _ = high_order(G, target) graphs.append(graph) labels.append(label) graphs = np.array(graphs) labels = np.array(labels) graphs = tf.ragged.constant(graphs).to_tensor().eval(session=tf.Session()) else: target = motif(target_shape) directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name) with open(directory, "r") as data: num_graphs = int(data.readline().rstrip().split(" ")[0]) for i in range(num_graphs): graph_meta = data.readline().rstrip().split(" ") num_vertex = int(graph_meta[0]) curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name] + 1), dtype=np.float32) labels.append(int(graph_meta[1])) # ori for j in range(num_vertex): vertex = data.readline().rstrip().split(" ") if NUM_LABELS[ds_name] != 0: curr_graph[j, j, int(vertex[0]) + 1] = 1. for k in range(2, len(vertex)): curr_graph[j, int(vertex[k]), 0] = 1. # curr_graph = noramlize_graph(curr_graph) graphs.append(curr_graph) graphs = np.array(graphs) for i in range(graphs.shape[0]): graphs[i] = np.transpose(graphs[i], [2, 0, 1]) # use only A G = nx.from_numpy_array(graphs[i][0]) graph, _, _ = high_order(G, target) graphs[i] = np.expand_dims(graph, axis=0) return graphs, np.array(labels) if __name__ == '__main__': graphs, labels = load_dataset("MUTAG") a, b = get_train_val_indexes(1, "MUTAG") print(np.transpose(graphs[a[0]], [1, 2, 0])[0])

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Python

wilson/wcxf/converters/smeftsim.py

bednya/wilson

2cd803bc298c3f967401aed119f617fc5d7ba5c0

[ "MIT" ]

24

2018-04-16T15:01:39.000Z

2022-01-26T07:16:22.000Z

wilson/wcxf/converters/smeftsim.py

bednya/wilson

2cd803bc298c3f967401aed119f617fc5d7ba5c0

[ "MIT" ]

85

2018-04-27T08:17:00.000Z

2022-02-22T16:47:14.000Z

wilson/wcxf/converters/smeftsim.py

bednya/wilson

2cd803bc298c3f967401aed119f617fc5d7ba5c0

[ "MIT" ]

17

2018-04-27T07:59:35.000Z

2022-02-09T22:46:05.000Z

"""Functions to convert WCxf files to MadGraph param_cards for SMEFTsim.""" from numpy import angle from collections import OrderedDict from wilson.wcxf.converters.SMEFTsim_param_card_elements import * from wilson.util import smeftutil def initialize_smeftsim_card(model_set): if model_set == 'A': # initialize card with empty blocks card = {'Block': OrderedDict()} card['Block']['FRBlock'] = OrderedDict() card['Block']['FRBlock10'] = OrderedDict() card['Block']['FRBlock11'] = OrderedDict() card['Block']['FRBlock12'] = OrderedDict() card['Block']['FRBlock13'] = OrderedDict() card['Block']['FRBlock14'] = OrderedDict() card['Block']['FRBlock15'] = OrderedDict() card['Block']['FRBlock16'] = OrderedDict() card['Block']['FRBlock17'] = OrderedDict() card['Block']['FRBlock18'] = OrderedDict() card['Block']['FRBlock19'] = OrderedDict() card['Block']['FRBlock2'] = OrderedDict() card['Block']['FRBlock20'] = OrderedDict() card['Block']['FRBlock21'] = OrderedDict() card['Block']['FRBlock25'] = OrderedDict() card['Block']['FRBlock26'] = OrderedDict() card['Block']['FRBlock27'] = OrderedDict() card['Block']['FRBlock28'] = OrderedDict() card['Block']['FRBlock29'] = OrderedDict() card['Block']['FRBlock3'] = OrderedDict() card['Block']['FRBlock30'] = OrderedDict() card['Block']['FRBlock31'] = OrderedDict() card['Block']['FRBlock32'] = OrderedDict() card['Block']['FRBlock4'] = OrderedDict() card['Block']['FRBlock48'] = OrderedDict() card['Block']['FRBlock5'] = OrderedDict() card['Block']['FRBlock6'] = OrderedDict() card['Block']['FRBlock7'] = OrderedDict() card['Block']['FRBlock70'] = OrderedDict() card['Block']['FRBlock71'] = OrderedDict() card['Block']['FRBlock72'] = OrderedDict() card['Block']['FRBlock73'] = OrderedDict() card['Block']['FRBlock74'] = OrderedDict() card['Block']['FRBlock8'] = OrderedDict() card['Block']['FRBlock9'] = OrderedDict() elif model_set == 'B': card = {'Block': OrderedDict()} card['Block']['FRBlock'] = OrderedDict() card['Block']['FRBlock10'] = OrderedDict() card['Block']['FRBlock11'] = OrderedDict() card['Block']['FRBlock15'] = OrderedDict() card['Block']['FRBlock16'] = OrderedDict() card['Block']['FRBlock18'] = OrderedDict() card['Block']['FRBlock19'] = OrderedDict() card['Block']['FRBlock21'] = OrderedDict() card['Block']['FRBlock22'] = OrderedDict() card['Block']['FRBlock24'] = OrderedDict() card['Block']['FRBlock25'] = OrderedDict() card['Block']['FRBlock27'] = OrderedDict() card['Block']['FRBlock28'] = OrderedDict() card['Block']['FRBlock30'] = OrderedDict() card['Block']['FRBlock31'] = OrderedDict() card['Block']['FRBlock33'] = OrderedDict() card['Block']['FRBlock34'] = OrderedDict() card['Block']['FRBlock36'] = OrderedDict() card['Block']['FRBlock37'] = OrderedDict() card['Block']['FRBlock45'] = OrderedDict() card['Block']['FRBlock46'] = OrderedDict() card['Block']['FRBlock6'] = OrderedDict() card['Block']['FRBlock69'] = OrderedDict() card['Block']['FRBlock7'] = OrderedDict() card['Block']['FRBlock70'] = OrderedDict() card['Block']['FRBlock72'] = OrderedDict() card['Block']['FRBlock73'] = OrderedDict() card['Block']['FRBlock75'] = OrderedDict() card['Block']['FRBlock76'] = OrderedDict() card['Block']['FRBlock78'] = OrderedDict() card['Block']['FRBlock79'] = OrderedDict() card['Block']['FRBlock8'] = OrderedDict() card['Block']['FRBlock81'] = OrderedDict() card['Block']['FRBlock82'] = OrderedDict() card['Block']['FRBlock9'] = OrderedDict() card['Block']['NEWCOUP'] = OrderedDict() return card def smeftsim_card_fill(card, wc, model_set, lambda_smeft_value, input_scheme_value): _symm_fac = smeftutil.arrays2wcxf(smeftutil._scale_dict) def scaled_wc(key): """Return the coefficient scaled by the appropriate symmetry factor to account for the change from the flavor-non-redundant WCxf convention to the symmetrized SMEFTsim convention.""" return wc[key] / _symm_fac[key] if model_set == 'A': # set block entries to WC values card['Block']['FRBlock'] = {'values': [ [1, format(angle(scaled_wc('phil1_12')),'.6e'), '# cHl1Ph12'], [2, format(angle(scaled_wc('phil1_13')),'.6e'), '# cHl1Ph13'], [3, format(angle(scaled_wc('phil1_23')),'.6e'), '# cHl1Ph23'], [4, format(angle(scaled_wc('phil3_12')),'.6e'), '# cHl3Ph12'], [5, format(angle(scaled_wc('phil3_13')),'.6e'), '# cHl3Ph13'], [6, format(angle(scaled_wc('phil3_23')),'.6e'), '# cHl3Ph23'], [7, format(angle(scaled_wc('phie_12')),'.6e'), '# cHePh12'], [8, format(angle(scaled_wc('phie_13')),'.6e'), '# cHePh13'], [9, format(angle(scaled_wc('phie_23')),'.6e'), '# cHePh23'], [10, format(angle(scaled_wc('phiq1_12')),'.6e'), '# cHq1Ph12'], [11, format(angle(scaled_wc('phiq1_13')),'.6e'), '# cHq1Ph13'], [12, format(angle(scaled_wc('phiq1_23')),'.6e'), '# cHq1Ph23'], [13, format(angle(scaled_wc('phiq3_12')),'.6e'), '# cHq3Ph12'], [14, format(angle(scaled_wc('phiq3_13')),'.6e'), '# cHq3Ph13'], [15, format(angle(scaled_wc('phiq3_23')),'.6e'), '# cHq3Ph23'], [16, format(angle(scaled_wc('phiu_12')),'.6e'), '# cHuPh12'], [17, format(angle(scaled_wc('phiu_13')),'.6e'), '# cHuPh13'], [18, format(angle(scaled_wc('phiu_23')),'.6e'), '# cHuPh23'], [19, format(angle(scaled_wc('phid_12')),'.6e'), '# cHdPh12'], [20, format(angle(scaled_wc('phid_13')),'.6e'), '# cHdPh13'], [21, format(angle(scaled_wc('phid_23')),'.6e'), '# cHdPh23'], [22, format(angle(scaled_wc('ll_1112')),'.6e'), '# cllPh1112'], [23, format(angle(scaled_wc('ll_1113')),'.6e'), '# cllPh1113'], [24, format(angle(scaled_wc('ll_1123')),'.6e'), '# cllPh1123'], [25, format(angle(scaled_wc('ll_1212')),'.6e'), '# cllPh1212'], [26, format(angle(scaled_wc('ll_1213')),'.6e'), '# cllPh1213'], [27, format(angle(scaled_wc('ll_1231')),'.6e'), '# cllPh1231'], [28, format(angle(scaled_wc('ll_1222')),'.6e'), '# cllPh1222'], [29, format(angle(scaled_wc('ll_1223')),'.6e'), '# cllPh1223'], [30, format(angle(scaled_wc('ll_1232')),'.6e'), '# cllPh1232'], [31, format(angle(scaled_wc('ll_1233')),'.6e'), '# cllPh1233'], [32, format(angle(scaled_wc('ll_1313')),'.6e'), '# cllPh1313'], [33, format(angle(scaled_wc('ll_1322')),'.6e'), '# cllPh1322'], [34, format(angle(scaled_wc('ll_1332')),'.6e'), '# cllPh1332'], [35, format(angle(scaled_wc('ll_1323')),'.6e'), '# cllPh1323'], [36, format(angle(scaled_wc('ll_1333')),'.6e'), '# cllPh1333'], [37, format(angle(scaled_wc('ll_2223')),'.6e'), '# cllPh2223'], [38, format(angle(scaled_wc('ll_2323')),'.6e'), '# cllPh2323'], [39, format(angle(scaled_wc('ll_2333')),'.6e'), '# cllPh3323'], [40, format(angle(scaled_wc('qq1_1112')),'.6e'), '# cqq1Ph1112'], [41, format(angle(scaled_wc('qq1_1113')),'.6e'), '# cqq1Ph1113'], [42, format(angle(scaled_wc('qq1_1123')),'.6e'), '# cqq1Ph1123'], [43, format(angle(scaled_wc('qq1_1212')),'.6e'), '# cqq1Ph1212'], [44, format(angle(scaled_wc('qq1_1213')),'.6e'), '# cqq1Ph1213'], [45, format(angle(scaled_wc('qq1_1231')),'.6e'), '# cqq1Ph1231'], [46, format(angle(scaled_wc('qq1_1222')),'.6e'), '# cqq1Ph1222'], [47, format(angle(scaled_wc('qq1_1223')),'.6e'), '# cqq1Ph1223'], [48, format(angle(scaled_wc('qq1_1232')),'.6e'), '# cqq1Ph1232'], [49, format(angle(scaled_wc('qq1_1233')),'.6e'), '# cqq1Ph1233'], [50, format(angle(scaled_wc('qq1_1313')),'.6e'), '# cqq1Ph1313'], [51, format(angle(scaled_wc('qq1_1322')),'.6e'), '# cqq1Ph1322'], [52, format(angle(scaled_wc('qq1_1332')),'.6e'), '# cqq1Ph1332'], [53, format(angle(scaled_wc('qq1_1323')),'.6e'), '# cqq1Ph1323'], [54, format(angle(scaled_wc('qq1_1333')),'.6e'), '# cqq1Ph1333'], [55, format(angle(scaled_wc('qq1_2223')),'.6e'), '# cqq1Ph2223'], [56, format(angle(scaled_wc('qq1_2323')),'.6e'), '# cqq1Ph2323'], [57, format(angle(scaled_wc('qq1_2333')),'.6e'), '# cqq1Ph3323'], [58, format(angle(scaled_wc('qq3_1112')),'.6e'), '# cqq3Ph1112'], [59, format(angle(scaled_wc('qq3_1113')),'.6e'), '# cqq3Ph1113'], [60, format(angle(scaled_wc('qq3_1123')),'.6e'), '# cqq3Ph1123'], [61, format(angle(scaled_wc('qq3_1212')),'.6e'), '# cqq3Ph1212'], [62, format(angle(scaled_wc('qq3_1213')),'.6e'), '# cqq3Ph1213'], [63, format(angle(scaled_wc('qq3_1231')),'.6e'), '# cqq3Ph1231'], [64, format(angle(scaled_wc('qq3_1222')),'.6e'), '# cqq3Ph1222'], [65, format(angle(scaled_wc('qq3_1223')),'.6e'), '# cqq3Ph1223'], [66, format(angle(scaled_wc('qq3_1232')),'.6e'), '# cqq3Ph1232'], [67, format(angle(scaled_wc('qq3_1233')),'.6e'), '# cqq3Ph1233'], [68, format(angle(scaled_wc('qq3_1313')),'.6e'), '# cqq3Ph1313'], [69, format(angle(scaled_wc('qq3_1322')),'.6e'), '# cqq3Ph1322'], [70, format(angle(scaled_wc('qq3_1332')),'.6e'), '# cqq3Ph1332'], [71, format(angle(scaled_wc('qq3_1323')),'.6e'), '# cqq3Ph1323'], [72, format(angle(scaled_wc('qq3_1333')),'.6e'), '# cqq3Ph1333'], [73, format(angle(scaled_wc('qq3_2223')),'.6e'), '# cqq3Ph2223'], [74, format(angle(scaled_wc('qq3_2323')),'.6e'), '# cqq3Ph2323'], [75, format(angle(scaled_wc('qq3_2333')),'.6e'), '# cqq3Ph3323'], [76, format(angle(scaled_wc('uu_1112')),'.6e'), '# cuuPh1112'], [77, format(angle(scaled_wc('uu_1113')),'.6e'), '# cuuPh1113'], [78, format(angle(scaled_wc('uu_1123')),'.6e'), '# cuuPh1123'], [79, format(angle(scaled_wc('uu_1212')),'.6e'), '# cuuPh1212'], [80, format(angle(scaled_wc('uu_1213')),'.6e'), '# cuuPh1213'], [81, format(angle(scaled_wc('uu_1231')),'.6e'), '# cuuPh1231'], [82, format(angle(scaled_wc('uu_1222')),'.6e'), '# cuuPh1222'], [83, format(angle(scaled_wc('uu_1223')),'.6e'), '# cuuPh1223'], [84, format(angle(scaled_wc('uu_1232')),'.6e'), '# cuuPh1232'], [85, format(angle(scaled_wc('uu_1233')),'.6e'), '# cuuPh1233'], [86, format(angle(scaled_wc('uu_1313')),'.6e'), '# cuuPh1313'], [87, format(angle(scaled_wc('uu_1322')),'.6e'), '# cuuPh1322'], [88, format(angle(scaled_wc('uu_1332')),'.6e'), '# cuuPh1332'], [89, format(angle(scaled_wc('uu_1323')),'.6e'), '# cuuPh1323'], [90, format(angle(scaled_wc('uu_1333')),'.6e'), '# cuuPh1333'], [91, format(angle(scaled_wc('uu_2223')),'.6e'), '# cuuPh2223'], [92, format(angle(scaled_wc('uu_2323')),'.6e'), '# cuuPh2323'], [93, format(angle(scaled_wc('uu_2333')),'.6e'), '# cuuPh3323'], [94, format(angle(scaled_wc('dd_1112')),'.6e'), '# cddPh1112'], [95, format(angle(scaled_wc('dd_1113')),'.6e'), '# cddPh1113'], [96, format(angle(scaled_wc('dd_1123')),'.6e'), '# cddPh1123'], [97, format(angle(scaled_wc('dd_1212')),'.6e'), '# cddPh1212'], [98, format(angle(scaled_wc('dd_1213')),'.6e'), '# cddPh1213'], [99, format(angle(scaled_wc('dd_1231')),'.6e'), '# cddPh1231'], [100, format(angle(scaled_wc('dd_1222')),'.6e'), '# cddPh1222'], [101, format(angle(scaled_wc('dd_1223')),'.6e'), '# cddPh1223'], [102, format(angle(scaled_wc('dd_1232')),'.6e'), '# cddPh1232'], [103, format(angle(scaled_wc('dd_1233')),'.6e'), '# cddPh1233'], [104, format(angle(scaled_wc('dd_1313')),'.6e'), '# cddPh1313'], [105, format(angle(scaled_wc('dd_1322')),'.6e'), '# cddPh1322'], [106, format(angle(scaled_wc('dd_1332')),'.6e'), '# cddPh1332'], [107, format(angle(scaled_wc('dd_1323')),'.6e'), '# cddPh1323'], [108, format(angle(scaled_wc('dd_1333')),'.6e'), '# cddPh1333'], [109, format(angle(scaled_wc('dd_2223')),'.6e'), '# cddPh2223'], [110, format(angle(scaled_wc('dd_2323')),'.6e'), '# cddPh2323'], [111, format(angle(scaled_wc('dd_2333')),'.6e'), '# cddPh3323'], [112, format(angle(scaled_wc('ee_1112')),'.6e'), '# ceePh1112'], [113, format(angle(scaled_wc('ee_1113')),'.6e'), '# ceePh1113'], [114, format(angle(scaled_wc('ee_1123')),'.6e'), '# ceePh1123'], [115, format(angle(scaled_wc('ee_1212')),'.6e'), '# ceePh1212'], [116, format(angle(scaled_wc('ee_1213')),'.6e'), '# ceePh1213'], [117, format(angle(scaled_wc('ee_1222')),'.6e'), '# ceePh1222'], [118, format(angle(scaled_wc('ee_1232')),'.6e'), '# ceePh1232'], [119, format(angle(scaled_wc('ee_1233')),'.6e'), '# ceePh1233'], [120, format(angle(scaled_wc('ee_1313')),'.6e'), '# ceePh1313'], [121, format(angle(scaled_wc('ee_1223')),'.6e'), '# ceePh1322'], # element 1322 replaced with 1223 in wcxf [122, format(angle(scaled_wc('ee_1323')),'.6e'), '# ceePh1323'], [123, format(angle(scaled_wc('ee_1333')),'.6e'), '# ceePh1333'], [124, format(angle(scaled_wc('ee_2223')),'.6e'), '# ceePh2223'], [125, format(angle(scaled_wc('ee_2323')),'.6e'), '# ceePh2323'], [126, format(angle(scaled_wc('ee_2333')),'.6e'), '# ceePh3323'], [127, format(angle(scaled_wc('lq1_1112')),'.6e'), '# clq1Ph1112'], [128, format(angle(scaled_wc('lq1_1113')),'.6e'), '# clq1Ph1113'], [129, format(angle(scaled_wc('lq1_1123')),'.6e'), '# clq1Ph1123'], [130, format(angle(scaled_wc('lq1_1211')),'.6e'), '# clq1Ph1211'], [131, format(angle(scaled_wc('lq1_1212')),'.6e'), '# clq1Ph1212'], [132, format(angle(scaled_wc('lq1_1221')),'.6e'), '# clq1Ph1221'], [133, format(angle(scaled_wc('lq1_1213')),'.6e'), '# clq1Ph1213'], [134, format(angle(scaled_wc('lq1_1231')),'.6e'), '# clq1Ph1231'], [135, format(angle(scaled_wc('lq1_1222')),'.6e'), '# clq1Ph1222'], [136, format(angle(scaled_wc('lq1_1223')),'.6e'), '# clq1Ph1223'], [137, format(angle(scaled_wc('lq1_1232')),'.6e'), '# clq1Ph1232'], [138, format(angle(scaled_wc('lq1_1233')),'.6e'), '# clq1Ph1233'], [139, format(angle(scaled_wc('lq1_1311')),'.6e'), '# clq1Ph1311'], [140, format(angle(scaled_wc('lq1_1312')),'.6e'), '# clq1Ph1312'], [141, format(angle(scaled_wc('lq1_1313')),'.6e'), '# clq1Ph1313'], [142, format(angle(scaled_wc('lq1_1331')),'.6e'), '# clq1Ph1331'], [143, format(angle(scaled_wc('lq1_1321')),'.6e'), '# clq1Ph1321'], [144, format(angle(scaled_wc('lq1_1322')),'.6e'), '# clq1Ph1322'], [145, format(angle(scaled_wc('lq1_1332')),'.6e'), '# clq1Ph1332'], [146, format(angle(scaled_wc('lq1_1323')),'.6e'), '# clq1Ph1323'], [147, format(angle(scaled_wc('lq1_1333')),'.6e'), '# clq1Ph1333'], [148, format(angle(scaled_wc('lq1_2212')),'.6e'), '# clq1Ph2212'], [149, format(angle(scaled_wc('lq1_2213')),'.6e'), '# clq1Ph2213'], [150, format(angle(scaled_wc('lq1_2223')),'.6e'), '# clq1Ph2223'], [151, format(angle(scaled_wc('lq1_2311')),'.6e'), '# clq1Ph2311'], [152, format(angle(scaled_wc('lq1_2312')),'.6e'), '# clq1Ph2312'], [153, format(angle(scaled_wc('lq1_2313')),'.6e'), '# clq1Ph2313'], [154, format(angle(scaled_wc('lq1_2321')),'.6e'), '# clq1Ph2321'], [155, format(angle(scaled_wc('lq1_2322')),'.6e'), '# clq1Ph2322'], [156, format(angle(scaled_wc('lq1_2323')),'.6e'), '# clq1Ph2323'], [157, format(angle(scaled_wc('lq1_2331')),'.6e'), '# clq1Ph2331'], [158, format(angle(scaled_wc('lq1_2332')),'.6e'), '# clq1Ph2332'], [159, format(angle(scaled_wc('lq1_2333')),'.6e'), '# clq1Ph2333'], [160, format(angle(scaled_wc('lq1_3312')),'.6e'), '# clq1Ph3312'], [161, format(angle(scaled_wc('lq1_3313')),'.6e'), '# clq1Ph3313'], [162, format(angle(scaled_wc('lq1_3323')),'.6e'), '# clq1Ph3323'], [163, format(angle(scaled_wc('lq3_1112')),'.6e'), '# clq3Ph1112'], [164, format(angle(scaled_wc('lq3_1113')),'.6e'), '# clq3Ph1113'], [165, format(angle(scaled_wc('lq3_1123')),'.6e'), '# clq3Ph1123'], [166, format(angle(scaled_wc('lq3_1211')),'.6e'), '# clq3Ph1211'], [167, format(angle(scaled_wc('lq3_1212')),'.6e'), '# clq3Ph1212'], [168, format(angle(scaled_wc('lq3_1221')),'.6e'), '# clq3Ph1221'], [169, format(angle(scaled_wc('lq3_1213')),'.6e'), '# clq3Ph1213'], [170, format(angle(scaled_wc('lq3_1231')),'.6e'), '# clq3Ph1231'], [171, format(angle(scaled_wc('lq3_1222')),'.6e'), '# clq3Ph1222'], [172, format(angle(scaled_wc('lq3_1223')),'.6e'), '# clq3Ph1223'], [173, format(angle(scaled_wc('lq3_1232')),'.6e'), '# clq3Ph1232'], [174, format(angle(scaled_wc('lq3_1233')),'.6e'), '# clq3Ph1233'], [175, format(angle(scaled_wc('lq3_1311')),'.6e'), '# clq3Ph1311'], [176, format(angle(scaled_wc('lq3_1312')),'.6e'), '# clq3Ph1312'], [177, format(angle(scaled_wc('lq3_1313')),'.6e'), '# clq3Ph1313'], [178, format(angle(scaled_wc('lq3_1331')),'.6e'), '# clq3Ph1331'], [179, format(angle(scaled_wc('lq3_1321')),'.6e'), '# clq3Ph1321'], [180, format(angle(scaled_wc('lq3_1322')),'.6e'), '# clq3Ph1322'], [181, format(angle(scaled_wc('lq3_1332')),'.6e'), '# clq3Ph1332'], [182, format(angle(scaled_wc('lq3_1323')),'.6e'), '# clq3Ph1323'], [183, format(angle(scaled_wc('lq3_1333')),'.6e'), '# clq3Ph1333'], [184, format(angle(scaled_wc('lq3_2212')),'.6e'), '# clq3Ph2212'], [185, format(angle(scaled_wc('lq3_2213')),'.6e'), '# clq3Ph2213'], [186, format(angle(scaled_wc('lq3_2223')),'.6e'), '# clq3Ph2223'], [187, format(angle(scaled_wc('lq3_2311')),'.6e'), '# clq3Ph2311'], [188, format(angle(scaled_wc('lq3_2312')),'.6e'), '# clq3Ph2312'], [189, format(angle(scaled_wc('lq3_2313')),'.6e'), '# clq3Ph2313'], [190, format(angle(scaled_wc('lq3_2321')),'.6e'), '# clq3Ph2321'], [191, format(angle(scaled_wc('lq3_2322')),'.6e'), '# clq3Ph2322'], [192, format(angle(scaled_wc('lq3_2323')),'.6e'), '# clq3Ph2323'], [193, format(angle(scaled_wc('lq3_2331')),'.6e'), '# clq3Ph2331'], [194, format(angle(scaled_wc('lq3_2332')),'.6e'), '# clq3Ph2332'], [195, format(angle(scaled_wc('lq3_2333')),'.6e'), '# clq3Ph2333'], [196, format(angle(scaled_wc('lq3_3312')),'.6e'), '# clq3Ph3312'], [197, format(angle(scaled_wc('lq3_3313')),'.6e'), '# clq3Ph3313'], [198, format(angle(scaled_wc('lq3_3323')),'.6e'), '# clq3Ph3323'], [199, format(angle(scaled_wc('eu_1112')),'.6e'), '# ceuPh1112'], [200, format(angle(scaled_wc('eu_1113')),'.6e'), '# ceuPh1113'], [201, format(angle(scaled_wc('eu_1123')),'.6e'), '# ceuPh1123'], [202, format(angle(scaled_wc('eu_1211')),'.6e'), '# ceuPh1211'], [203, format(angle(scaled_wc('eu_1212')),'.6e'), '# ceuPh1212'], [204, format(angle(scaled_wc('eu_1221')),'.6e'), '# ceuPh1221'], [205, format(angle(scaled_wc('eu_1213')),'.6e'), '# ceuPh1213'], [206, format(angle(scaled_wc('eu_1231')),'.6e'), '# ceuPh1231'], [207, format(angle(scaled_wc('eu_1222')),'.6e'), '# ceuPh1222'], [208, format(angle(scaled_wc('eu_1223')),'.6e'), '# ceuPh1223'], [209, format(angle(scaled_wc('eu_1232')),'.6e'), '# ceuPh1232'], [210, format(angle(scaled_wc('eu_1233')),'.6e'), '# ceuPh1233'], [211, format(angle(scaled_wc('eu_1311')),'.6e'), '# ceuPh1311'], [212, format(angle(scaled_wc('eu_1312')),'.6e'), '# ceuPh1312'], [213, format(angle(scaled_wc('eu_1313')),'.6e'), '# ceuPh1313'], [214, format(angle(scaled_wc('eu_1331')),'.6e'), '# ceuPh1331'], [215, format(angle(scaled_wc('eu_1321')),'.6e'), '# ceuPh1321'], [216, format(angle(scaled_wc('eu_1322')),'.6e'), '# ceuPh1322'], [217, format(angle(scaled_wc('eu_1332')),'.6e'), '# ceuPh1332'], [218, format(angle(scaled_wc('eu_1323')),'.6e'), '# ceuPh1323'], [219, format(angle(scaled_wc('eu_1333')),'.6e'), '# ceuPh1333'], [220, format(angle(scaled_wc('eu_2212')),'.6e'), '# ceuPh2212'], [221, format(angle(scaled_wc('eu_2213')),'.6e'), '# ceuPh2213'], [222, format(angle(scaled_wc('eu_2223')),'.6e'), '# ceuPh2223'], [223, format(angle(scaled_wc('eu_2311')),'.6e'), '# ceuPh2311'], [224, format(angle(scaled_wc('eu_2312')),'.6e'), '# ceuPh2312'], [225, format(angle(scaled_wc('eu_2313')),'.6e'), '# ceuPh2313'], [226, format(angle(scaled_wc('eu_2321')),'.6e'), '# ceuPh2321'], [227, format(angle(scaled_wc('eu_2322')),'.6e'), '# ceuPh2322'], [228, format(angle(scaled_wc('eu_2323')),'.6e'), '# ceuPh2323'], [229, format(angle(scaled_wc('eu_2331')),'.6e'), '# ceuPh2331'], [230, format(angle(scaled_wc('eu_2332')),'.6e'), '# ceuPh2332'], [231, format(angle(scaled_wc('eu_2333')),'.6e'), '# ceuPh2333'], [232, format(angle(scaled_wc('eu_3312')),'.6e'), '# ceuPh3312'], [233, format(angle(scaled_wc('eu_3313')),'.6e'), '# ceuPh3313'], [234, format(angle(scaled_wc('eu_3323')),'.6e'), '# ceuPh3323'], [235, format(angle(scaled_wc('ed_1112')),'.6e'), '# cedPh1112'], [236, format(angle(scaled_wc('ed_1113')),'.6e'), '# cedPh1113'], [237, format(angle(scaled_wc('ed_1123')),'.6e'), '# cedPh1123'], [238, format(angle(scaled_wc('ed_1211')),'.6e'), '# cedPh1211'], [239, format(angle(scaled_wc('ed_1212')),'.6e'), '# cedPh1212'], [240, format(angle(scaled_wc('ed_1221')),'.6e'), '# cedPh1221'], [241, format(angle(scaled_wc('ed_1213')),'.6e'), '# cedPh1213'], [242, format(angle(scaled_wc('ed_1231')),'.6e'), '# cedPh1231'], [243, format(angle(scaled_wc('ed_1222')),'.6e'), '# cedPh1222'], [244, format(angle(scaled_wc('ed_1223')),'.6e'), '# cedPh1223'], [245, format(angle(scaled_wc('ed_1232')),'.6e'), '# cedPh1232'], [246, format(angle(scaled_wc('ed_1233')),'.6e'), '# cedPh1233'], [247, format(angle(scaled_wc('ed_1311')),'.6e'), '# cedPh1311'], [248, format(angle(scaled_wc('ed_1312')),'.6e'), '# cedPh1312'], [249, format(angle(scaled_wc('ed_1313')),'.6e'), '# cedPh1313'], [250, format(angle(scaled_wc('ed_1331')),'.6e'), '# cedPh1331'], [251, format(angle(scaled_wc('ed_1321')),'.6e'), '# cedPh1321'], [252, format(angle(scaled_wc('ed_1322')),'.6e'), '# cedPh1322'], [253, format(angle(scaled_wc('ed_1332')),'.6e'), '# cedPh1332'], [254, format(angle(scaled_wc('ed_1323')),'.6e'), '# cedPh1323'], [255, format(angle(scaled_wc('ed_1333')),'.6e'), '# cedPh1333'], [256, format(angle(scaled_wc('ed_2212')),'.6e'), '# cedPh2212'], [257, format(angle(scaled_wc('ed_2213')),'.6e'), '# cedPh2213'], [258, format(angle(scaled_wc('ed_2223')),'.6e'), '# cedPh2223'], [259, format(angle(scaled_wc('ed_2311')),'.6e'), '# cedPh2311'], [260, format(angle(scaled_wc('ed_2312')),'.6e'), '# cedPh2312'], [261, format(angle(scaled_wc('ed_2313')),'.6e'), '# cedPh2313'], [262, format(angle(scaled_wc('ed_2321')),'.6e'), '# cedPh2321'], [263, format(angle(scaled_wc('ed_2322')),'.6e'), '# cedPh2322'], [264, format(angle(scaled_wc('ed_2323')),'.6e'), '# cedPh2323'], [265, format(angle(scaled_wc('ed_2331')),'.6e'), '# cedPh2331'], [266, format(angle(scaled_wc('ed_2332')),'.6e'), '# cedPh2332'], [267, format(angle(scaled_wc('ed_2333')),'.6e'), '# cedPh2333'], [268, format(angle(scaled_wc('ed_3312')),'.6e'), '# cedPh3312'], [269, format(angle(scaled_wc('ed_3313')),'.6e'), '# cedPh3313'], [270, format(angle(scaled_wc('ed_3323')),'.6e'), '# cedPh3323'], [271, 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lambda_smeft_value**2,'.6e'), '# cqq1Abs1223'], [733, format(abs(scaled_wc('qq1_1232')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs1232'], [734, format(abs(scaled_wc('qq1_1233')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs1233'], [735, format(abs(scaled_wc('qq1_1313')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs1313'], [736, format(abs(scaled_wc('qq1_1322')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs1322'], [737, format(abs(scaled_wc('qq1_1332')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs1332'], [738, format(abs(scaled_wc('qq1_1323')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs1323'], [739, format(abs(scaled_wc('qq1_1333')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs1333'], [740, format(abs(scaled_wc('qq1_2223')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs2223'], [741, format(abs(scaled_wc('qq1_2323')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs2323'], [742, format(abs(scaled_wc('qq1_2333')) * lambda_smeft_value**2,'.6e'), '# cqq1Abs3323'], [743, format(scaled_wc('qq3_1111') * lambda_smeft_value**2,'.6e'), '# cqq3Abs1111'], [744, format(scaled_wc('qq3_1122') * lambda_smeft_value**2,'.6e'), '# cqq3Abs1122'], [745, format(scaled_wc('qq3_1221') * lambda_smeft_value**2,'.6e'), '# cqq3Abs1221'], [746, format(scaled_wc('qq3_1133') * lambda_smeft_value**2,'.6e'), '# cqq3Abs1133'], [747, format(scaled_wc('qq3_1331') * lambda_smeft_value**2,'.6e'), '# cqq3Abs1331'], [748, format(scaled_wc('qq3_2222') * lambda_smeft_value**2,'.6e'), '# cqq3Abs2222'], [749, format(scaled_wc('qq3_2233') * lambda_smeft_value**2,'.6e'), '# cqq3Abs2233'], [750, format(scaled_wc('qq3_2332') * lambda_smeft_value**2,'.6e'), '# cqq3Abs2332'], [751, format(scaled_wc('qq3_3333') * lambda_smeft_value**2,'.6e'), '# cqq3Abs3333'], [752, format(abs(scaled_wc('qq3_1112')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1112'], [753, format(abs(scaled_wc('qq3_1113')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1113'], [754, format(abs(scaled_wc('qq3_1123')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1123'], [755, format(abs(scaled_wc('qq3_1212')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1212'], [756, format(abs(scaled_wc('qq3_1213')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1213'], [757, format(abs(scaled_wc('qq3_1231')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1231'], [758, format(abs(scaled_wc('qq3_1222')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1222'], [759, format(abs(scaled_wc('qq3_1223')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1223'], [760, format(abs(scaled_wc('qq3_1232')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1232'], [761, format(abs(scaled_wc('qq3_1233')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1233'], [762, format(abs(scaled_wc('qq3_1313')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1313'], [763, format(abs(scaled_wc('qq3_1322')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1322'], [764, format(abs(scaled_wc('qq3_1332')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1332'], [765, format(abs(scaled_wc('qq3_1323')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1323'], [766, format(abs(scaled_wc('qq3_1333')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs1333'], [767, format(abs(scaled_wc('qq3_2223')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs2223'], [768, format(abs(scaled_wc('qq3_2323')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs2323'], [769, format(abs(scaled_wc('qq3_2333')) * lambda_smeft_value**2,'.6e'), '# cqq3Abs3323'], [770, format(scaled_wc('lq1_1111') * lambda_smeft_value**2,'.6e'), '# clq1Abs1111'], [771, format(abs(scaled_wc('lq1_1112')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1112'], [772, format(abs(scaled_wc('lq1_1113')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1113'], [773, format(abs(scaled_wc('lq1_1123')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1123'], [774, format(scaled_wc('lq1_1122') * lambda_smeft_value**2,'.6e'), '# clq1Abs1122'], [775, format(scaled_wc('lq1_1133') * lambda_smeft_value**2,'.6e'), '# clq1Abs1133'], [776, format(abs(scaled_wc('lq1_1211')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1211'], [777, format(abs(scaled_wc('lq1_1212')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1212'], [778, format(abs(scaled_wc('lq1_1221')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1221'], [779, format(abs(scaled_wc('lq1_1213')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1213'], [780, format(abs(scaled_wc('lq1_1231')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1231'], [781, format(abs(scaled_wc('lq1_1222')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1222'], [782, format(abs(scaled_wc('lq1_1223')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1223'], [783, format(abs(scaled_wc('lq1_1232')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1232'], [784, format(abs(scaled_wc('lq1_1233')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1233'], [785, format(abs(scaled_wc('lq1_1311')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1311'], [786, format(abs(scaled_wc('lq1_1312')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1312'], [787, format(abs(scaled_wc('lq1_1313')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1313'], [788, format(abs(scaled_wc('lq1_1331')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1331'], [789, format(abs(scaled_wc('lq1_1321')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1321'], [790, format(abs(scaled_wc('lq1_1322')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1322'], [791, format(abs(scaled_wc('lq1_1332')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1332'], [792, format(abs(scaled_wc('lq1_1323')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1323'], [793, format(abs(scaled_wc('lq1_1333')) * lambda_smeft_value**2,'.6e'), '# clq1Abs1333'], [794, format(scaled_wc('lq1_2211') * lambda_smeft_value**2,'.6e'), '# clq1Abs2211'], [795, format(abs(scaled_wc('lq1_2212')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2212'], [796, format(abs(scaled_wc('lq1_2213')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2213'], [797, format(scaled_wc('lq1_2222') * lambda_smeft_value**2,'.6e'), '# clq1Abs2222'], [798, format(abs(scaled_wc('lq1_2223')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2223'], [799, format(scaled_wc('lq1_2233') * lambda_smeft_value**2,'.6e'), '# clq1Abs2233'], [800, format(abs(scaled_wc('lq1_2311')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2311'], [801, format(abs(scaled_wc('lq1_2312')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2312'], [802, format(abs(scaled_wc('lq1_2313')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2313'], [803, format(abs(scaled_wc('lq1_2321')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2321'], [804, format(abs(scaled_wc('lq1_2322')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2322'], [805, format(abs(scaled_wc('lq1_2323')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2323'], [806, format(abs(scaled_wc('lq1_2331')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2331'], [807, format(abs(scaled_wc('lq1_2332')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2332'], [808, format(abs(scaled_wc('lq1_2333')) * lambda_smeft_value**2,'.6e'), '# clq1Abs2333'], [809, format(scaled_wc('lq1_3311') * lambda_smeft_value**2,'.6e'), '# clq1Abs3311'], [810, format(abs(scaled_wc('lq1_3312')) * lambda_smeft_value**2,'.6e'), '# clq1Abs3312'], [811, format(abs(scaled_wc('lq1_3313')) * lambda_smeft_value**2,'.6e'), '# clq1Abs3313'], [812, format(scaled_wc('lq1_3322') * lambda_smeft_value**2,'.6e'), '# clq1Abs3322'], [813, format(scaled_wc('lq1_3333') * lambda_smeft_value**2,'.6e'), '# clq1Abs3333'], [814, format(abs(scaled_wc('lq1_3323')) * lambda_smeft_value**2,'.6e'), '# clq1Abs3323'], [815, format(scaled_wc('lq3_1111') * lambda_smeft_value**2,'.6e'), '# clq3Abs1111'], [816, format(abs(scaled_wc('lq3_1112')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1112'], [817, format(abs(scaled_wc('lq3_1113')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1113'], [818, format(abs(scaled_wc('lq3_1123')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1123'], [819, format(scaled_wc('lq3_1122') * lambda_smeft_value**2,'.6e'), '# clq3Abs1122'], [820, format(scaled_wc('lq3_1133') * lambda_smeft_value**2,'.6e'), '# clq3Abs1133'], [821, format(abs(scaled_wc('lq3_1211')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1211'], [822, format(abs(scaled_wc('lq3_1212')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1212'], [823, format(abs(scaled_wc('lq3_1221')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1221'], [824, format(abs(scaled_wc('lq3_1213')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1213'], [825, format(abs(scaled_wc('lq3_1231')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1231'], [826, format(abs(scaled_wc('lq3_1222')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1222'], [827, format(abs(scaled_wc('lq3_1223')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1223'], [828, format(abs(scaled_wc('lq3_1232')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1232'], [829, format(abs(scaled_wc('lq3_1233')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1233'], [830, format(abs(scaled_wc('lq3_1311')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1311'], [831, format(abs(scaled_wc('lq3_1312')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1312'], [832, format(abs(scaled_wc('lq3_1313')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1313'], [833, format(abs(scaled_wc('lq3_1331')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1331'], [834, format(abs(scaled_wc('lq3_1321')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1321'], [835, format(abs(scaled_wc('lq3_1322')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1322'], [836, format(abs(scaled_wc('lq3_1332')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1332'], [837, format(abs(scaled_wc('lq3_1323')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1323'], [838, format(abs(scaled_wc('lq3_1333')) * lambda_smeft_value**2,'.6e'), '# clq3Abs1333'], [839, format(scaled_wc('lq3_2211') * lambda_smeft_value**2,'.6e'), '# clq3Abs2211'], [840, format(abs(scaled_wc('lq3_2212')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2212'], [841, format(abs(scaled_wc('lq3_2213')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2213'], [842, format(scaled_wc('lq3_2222') * lambda_smeft_value**2,'.6e'), '# clq3Abs2222'], [843, format(abs(scaled_wc('lq3_2223')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2223'], [844, format(scaled_wc('lq3_2233') * lambda_smeft_value**2,'.6e'), '# clq3Abs2233'], [845, format(abs(scaled_wc('lq3_2311')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2311'], [846, format(abs(scaled_wc('lq3_2312')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2312'], [847, format(abs(scaled_wc('lq3_2313')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2313'], [848, format(abs(scaled_wc('lq3_2321')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2321'], [849, format(abs(scaled_wc('lq3_2322')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2322'], [850, format(abs(scaled_wc('lq3_2323')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2323'], [851, format(abs(scaled_wc('lq3_2331')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2331'], [852, format(abs(scaled_wc('lq3_2332')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2332'], [853, format(abs(scaled_wc('lq3_2333')) * lambda_smeft_value**2,'.6e'), '# clq3Abs2333'], [854, format(scaled_wc('lq3_3311') * lambda_smeft_value**2,'.6e'), '# clq3Abs3311'], [855, format(abs(scaled_wc('lq3_3312')) * lambda_smeft_value**2,'.6e'), '# clq3Abs3312'], [856, format(abs(scaled_wc('lq3_3313')) * lambda_smeft_value**2,'.6e'), '# clq3Abs3313'], [857, format(scaled_wc('lq3_3322') * lambda_smeft_value**2,'.6e'), '# clq3Abs3322'], [858, format(scaled_wc('lq3_3333') * lambda_smeft_value**2,'.6e'), '# clq3Abs3333'], [859, format(abs(scaled_wc('lq3_3323')) * lambda_smeft_value**2,'.6e'), '# clq3Abs3323'], [860, format(scaled_wc('ee_1111') * lambda_smeft_value**2,'.6e'), '# ceeAbs1111'], [861, format(scaled_wc('ee_1122') * lambda_smeft_value**2,'.6e'), '# ceeAbs1122'], [862, format(scaled_wc('ee_1133') * lambda_smeft_value**2,'.6e'), '# ceeAbs1133'], [863, format(scaled_wc('ee_2222') * lambda_smeft_value**2,'.6e'), '# ceeAbs2222'], [864, format(scaled_wc('ee_2233') * lambda_smeft_value**2,'.6e'), '# ceeAbs2233'], [865, format(abs(scaled_wc('ee_1112')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1112'], [866, format(abs(scaled_wc('ee_3333')) * lambda_smeft_value**2,'.6e'), '# ceeAbs3333'], [867, format(abs(scaled_wc('ee_1123')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1123'], [868, format(abs(scaled_wc('ee_1113')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1113'], [869, format(abs(scaled_wc('ee_1213')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1213'], [870, format(abs(scaled_wc('ee_1212')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1212'], [871, format(abs(scaled_wc('ee_1232')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1232'], [872, format(abs(scaled_wc('ee_1222')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1222'], [873, format(abs(scaled_wc('ee_1313')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1313'], [874, format(abs(scaled_wc('ee_1233')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1233'], [875, format(abs(scaled_wc('ee_1323')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1323'], [876, format(abs(scaled_wc('ee_1223')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1322'], # element 1322 replaced with 1223 in wcxf [877, format(abs(scaled_wc('ee_2223')) * lambda_smeft_value**2,'.6e'), '# ceeAbs2223'], [878, format(abs(scaled_wc('ee_1333')) * lambda_smeft_value**2,'.6e'), '# ceeAbs1333'], [879, format(abs(scaled_wc('ee_2333')) * lambda_smeft_value**2,'.6e'), '# ceeAbs3323'], # element 3323 replaced with 2223 in wcxf [880, format(abs(scaled_wc('ee_2323')) * lambda_smeft_value**2,'.6e'), '# ceeAbs2323'], [881, format(scaled_wc('uu_1111') * lambda_smeft_value**2,'.6e'), '# cuuAbs1111'], [882, format(scaled_wc('uu_1122') * lambda_smeft_value**2,'.6e'), '# cuuAbs1122'], [883, format(scaled_wc('uu_1221') * lambda_smeft_value**2,'.6e'), '# cuuAbs1221'], [884, format(scaled_wc('uu_1133') * lambda_smeft_value**2,'.6e'), '# cuuAbs1133'], [885, format(scaled_wc('uu_1331') * lambda_smeft_value**2,'.6e'), '# cuuAbs1331'], [886, format(scaled_wc('uu_2222') * lambda_smeft_value**2,'.6e'), '# cuuAbs2222'], [887, format(scaled_wc('uu_2233') * lambda_smeft_value**2,'.6e'), '# cuuAbs2233'], [888, format(scaled_wc('uu_2332') * lambda_smeft_value**2,'.6e'), '# cuuAbs2332'], [889, format(scaled_wc('uu_3333') * lambda_smeft_value**2,'.6e'), '# cuuAbs3333'], [890, format(abs(scaled_wc('uu_1112')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1112'], [891, format(abs(scaled_wc('uu_1113')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1113'], [892, format(abs(scaled_wc('uu_1123')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1123'], [893, format(abs(scaled_wc('uu_1212')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1212'], [894, format(abs(scaled_wc('uu_1213')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1213'], [895, format(abs(scaled_wc('uu_1231')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1231'], [896, format(abs(scaled_wc('uu_1222')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1222'], [897, format(abs(scaled_wc('uu_1223')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1223'], [898, format(abs(scaled_wc('uu_1232')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1232'], [899, format(abs(scaled_wc('uu_1233')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1233'], [900, format(abs(scaled_wc('uu_1313')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1313'], [901, format(abs(scaled_wc('uu_1322')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1322'], [902, format(abs(scaled_wc('uu_1332')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1332'], [903, format(abs(scaled_wc('uu_1323')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1323'], [904, format(abs(scaled_wc('uu_1333')) * lambda_smeft_value**2,'.6e'), '# cuuAbs1333'], [905, format(abs(scaled_wc('uu_2223')) * lambda_smeft_value**2,'.6e'), '# cuuAbs2223'], [906, format(abs(scaled_wc('uu_2323')) * lambda_smeft_value**2,'.6e'), '# cuuAbs2323'], [907, format(abs(scaled_wc('uu_2333')) * lambda_smeft_value**2,'.6e'), '# cuuAbs3323'], [908, format(scaled_wc('dd_1111') * lambda_smeft_value**2,'.6e'), '# cddAbs1111'], [909, format(scaled_wc('dd_1122') * lambda_smeft_value**2,'.6e'), '# cddAbs1122'], [910, format(scaled_wc('dd_1221') * lambda_smeft_value**2,'.6e'), '# cddAbs1221'], 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format(abs(scaled_wc('qd8_1211')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1211'], [1437, format(abs(scaled_wc('qd8_1212')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1212'], [1438, format(abs(scaled_wc('qd8_1221')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1221'], [1439, format(abs(scaled_wc('qd8_1213')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1213'], [1440, format(abs(scaled_wc('qd8_1231')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1231'], [1441, format(abs(scaled_wc('qd8_1222')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1222'], [1442, format(abs(scaled_wc('qd8_1223')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1223'], [1443, format(abs(scaled_wc('qd8_1232')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1232'], [1444, format(abs(scaled_wc('qd8_1233')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1233'], [1445, format(abs(scaled_wc('qd8_1311')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1311'], [1446, format(abs(scaled_wc('qd8_1312')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1312'], [1447, format(abs(scaled_wc('qd8_1313')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1313'], [1448, format(abs(scaled_wc('qd8_1331')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1331'], [1449, format(abs(scaled_wc('qd8_1321')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1321'], [1450, format(abs(scaled_wc('qd8_1322')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1322'], [1451, format(abs(scaled_wc('qd8_1332')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1332'], [1452, format(abs(scaled_wc('qd8_1323')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1323'], [1453, format(abs(scaled_wc('qd8_1333')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs1333'], [1454, format(scaled_wc('qd8_2211') * lambda_smeft_value**2,'.6e'), '# cqd8Abs2211'], [1455, format(abs(scaled_wc('qd8_2212')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2212'], [1456, format(abs(scaled_wc('qd8_2213')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2213'], [1457, format(scaled_wc('qd8_2222') * lambda_smeft_value**2,'.6e'), '# cqd8Abs2222'], [1458, format(abs(scaled_wc('qd8_2223')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2223'], [1459, format(scaled_wc('qd8_2233') * lambda_smeft_value**2,'.6e'), '# cqd8Abs2233'], [1460, format(abs(scaled_wc('qd8_2311')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2311'], [1461, format(abs(scaled_wc('qd8_2312')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2312'], [1462, format(abs(scaled_wc('qd8_2313')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2313'], [1463, format(abs(scaled_wc('qd8_2321')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2321'], [1464, format(abs(scaled_wc('qd8_2322')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2322'], [1465, format(abs(scaled_wc('qd8_2323')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2323'], [1466, format(abs(scaled_wc('qd8_2331')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2331'], [1467, format(abs(scaled_wc('qd8_2332')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2332'], [1468, format(abs(scaled_wc('qd8_2333')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs2333'], [1469, format(scaled_wc('qd8_3311') * lambda_smeft_value**2,'.6e'), '# cqd8Abs3311'], [1470, format(abs(scaled_wc('qd8_3312')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs3312'], [1471, format(abs(scaled_wc('qd8_3313')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs3313'], [1472, format(scaled_wc('qd8_3322') * lambda_smeft_value**2,'.6e'), '# cqd8Abs3322'], [1473, format(scaled_wc('qd8_3333') * lambda_smeft_value**2,'.6e'), '# cqd8Abs3333'], [1474, format(abs(scaled_wc('qd8_3323')) * lambda_smeft_value**2,'.6e'), '# cqd8Abs3323'] ]} card['Block']['FRBlock10'] = {'values': [ [1, 1, format(angle(scaled_wc('phiud_11')),'.6e'), '# cHudPh1x1'], [1, 2, format(angle(scaled_wc('phiud_12')),'.6e'), '# cHudPh1x2'], [1, 3, format(angle(scaled_wc('phiud_13')),'.6e'), '# cHudPh1x3'], [2, 1, format(angle(scaled_wc('phiud_21')),'.6e'), '# cHudPh2x1'], [2, 2, format(angle(scaled_wc('phiud_22')),'.6e'), '# cHudPh2x2'], [2, 3, format(angle(scaled_wc('phiud_23')),'.6e'), '# cHudPh2x3'], [3, 1, format(angle(scaled_wc('phiud_31')),'.6e'), '# cHudPh3x1'], [3, 2, format(angle(scaled_wc('phiud_32')),'.6e'), '# cHudPh3x2'], [3, 3, format(angle(scaled_wc('phiud_33')),'.6e'), '# cHudPh3x3'], ]} card['Block']['FRBlock11'] = {'values': [ [1, 1, format(angle(scaled_wc('ephi_11')),'.6e'), '# ceHPh1x1'], [1, 2, format(angle(scaled_wc('ephi_12')),'.6e'), '# ceHPh1x2'], [1, 3, format(angle(scaled_wc('ephi_13')),'.6e'), '# ceHPh1x3'], [2, 1, format(angle(scaled_wc('ephi_21')),'.6e'), '# ceHPh2x1'], [2, 2, format(angle(scaled_wc('ephi_22')),'.6e'), '# ceHPh2x2'], [2, 3, format(angle(scaled_wc('ephi_23')),'.6e'), '# ceHPh2x3'], [3, 1, format(angle(scaled_wc('ephi_31')),'.6e'), '# ceHPh3x1'], [3, 2, format(angle(scaled_wc('ephi_32')),'.6e'), '# ceHPh3x2'], [3, 3, format(angle(scaled_wc('ephi_33')),'.6e'), '# ceHPh3x3'], ]} card['Block']['FRBlock12'] = {'values': [ [1, 1, format(angle(scaled_wc('uphi_11')),'.6e'), '# cuHPh1x1'], [1, 2, format(angle(scaled_wc('uphi_12')),'.6e'), '# cuHPh1x2'], [1, 3, format(angle(scaled_wc('uphi_13')),'.6e'), '# cuHPh1x3'], [2, 1, format(angle(scaled_wc('uphi_21')),'.6e'), '# cuHPh2x1'], [2, 2, format(angle(scaled_wc('uphi_22')),'.6e'), '# cuHPh2x2'], [2, 3, format(angle(scaled_wc('uphi_23')),'.6e'), '# cuHPh2x3'], [3, 1, format(angle(scaled_wc('uphi_31')),'.6e'), '# cuHPh3x1'], [3, 2, format(angle(scaled_wc('uphi_32')),'.6e'), '# cuHPh3x2'], [3, 3, format(angle(scaled_wc('uphi_33')),'.6e'), '# cuHPh3x3'], ]} card['Block']['FRBlock13'] = {'values': [ [1, 1, format(angle(scaled_wc('dphi_11')),'.6e'), '# cdHPh1x1'], [1, 2, format(angle(scaled_wc('dphi_12')),'.6e'), '# cdHPh1x2'], [1, 3, format(angle(scaled_wc('dphi_13')),'.6e'), '# cdHPh1x3'], [2, 1, format(angle(scaled_wc('dphi_21')),'.6e'), '# cdHPh2x1'], [2, 2, format(angle(scaled_wc('dphi_22')),'.6e'), '# cdHPh2x2'], [2, 3, format(angle(scaled_wc('dphi_23')),'.6e'), '# cdHPh2x3'], [3, 1, format(angle(scaled_wc('dphi_31')),'.6e'), '# cdHPh3x1'], [3, 2, format(angle(scaled_wc('dphi_32')),'.6e'), '# cdHPh3x2'], [3, 3, format(angle(scaled_wc('dphi_33')),'.6e'), '# cdHPh3x3'], ]} card['Block']['FRBlock14'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('ledq_1111')),'.6e'), '# cledqPh1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('ledq_1112')),'.6e'), '# cledqPh1x1x1x2'], [1, 1, 1, 3, format(angle(scaled_wc('ledq_1113')),'.6e'), '# cledqPh1x1x1x3'], [1, 1, 2, 1, format(angle(scaled_wc('ledq_1121')),'.6e'), '# cledqPh1x1x2x1'], [1, 1, 2, 2, format(angle(scaled_wc('ledq_1122')),'.6e'), '# cledqPh1x1x2x2'], [1, 1, 2, 3, format(angle(scaled_wc('ledq_1123')),'.6e'), '# cledqPh1x1x2x3'], [1, 1, 3, 1, format(angle(scaled_wc('ledq_1131')),'.6e'), '# cledqPh1x1x3x1'], [1, 1, 3, 2, format(angle(scaled_wc('ledq_1132')),'.6e'), '# cledqPh1x1x3x2'], [1, 1, 3, 3, format(angle(scaled_wc('ledq_1133')),'.6e'), '# cledqPh1x1x3x3'], [1, 2, 1, 1, format(angle(scaled_wc('ledq_1211')),'.6e'), '# cledqPh1x2x1x1'], [1, 2, 1, 2, format(angle(scaled_wc('ledq_1212')),'.6e'), '# cledqPh1x2x1x2'], [1, 2, 1, 3, format(angle(scaled_wc('ledq_1213')),'.6e'), '# cledqPh1x2x1x3'], [1, 2, 2, 1, format(angle(scaled_wc('ledq_1221')),'.6e'), '# cledqPh1x2x2x1'], [1, 2, 2, 2, format(angle(scaled_wc('ledq_1222')),'.6e'), '# cledqPh1x2x2x2'], [1, 2, 2, 3, format(angle(scaled_wc('ledq_1223')),'.6e'), '# cledqPh1x2x2x3'], [1, 2, 3, 1, format(angle(scaled_wc('ledq_1231')),'.6e'), '# cledqPh1x2x3x1'], [1, 2, 3, 2, format(angle(scaled_wc('ledq_1232')),'.6e'), '# cledqPh1x2x3x2'], [1, 2, 3, 3, format(angle(scaled_wc('ledq_1233')),'.6e'), '# cledqPh1x2x3x3'], [1, 3, 1, 1, format(angle(scaled_wc('ledq_1311')),'.6e'), '# cledqPh1x3x1x1'], [1, 3, 1, 2, format(angle(scaled_wc('ledq_1312')),'.6e'), '# cledqPh1x3x1x2'], [1, 3, 1, 3, format(angle(scaled_wc('ledq_1313')),'.6e'), '# cledqPh1x3x1x3'], [1, 3, 2, 1, format(angle(scaled_wc('ledq_1321')),'.6e'), '# cledqPh1x3x2x1'], [1, 3, 2, 2, format(angle(scaled_wc('ledq_1322')),'.6e'), '# cledqPh1x3x2x2'], [1, 3, 2, 3, format(angle(scaled_wc('ledq_1323')),'.6e'), '# cledqPh1x3x2x3'], [1, 3, 3, 1, format(angle(scaled_wc('ledq_1331')),'.6e'), '# cledqPh1x3x3x1'], [1, 3, 3, 2, format(angle(scaled_wc('ledq_1332')),'.6e'), '# cledqPh1x3x3x2'], [1, 3, 3, 3, format(angle(scaled_wc('ledq_1333')),'.6e'), '# cledqPh1x3x3x3'], [2, 1, 1, 1, format(angle(scaled_wc('ledq_2111')),'.6e'), '# cledqPh2x1x1x1'], [2, 1, 1, 2, format(angle(scaled_wc('ledq_2112')),'.6e'), '# cledqPh2x1x1x2'], [2, 1, 1, 3, format(angle(scaled_wc('ledq_2113')),'.6e'), '# cledqPh2x1x1x3'], [2, 1, 2, 1, format(angle(scaled_wc('ledq_2121')),'.6e'), '# cledqPh2x1x2x1'], [2, 1, 2, 2, format(angle(scaled_wc('ledq_2122')),'.6e'), '# cledqPh2x1x2x2'], [2, 1, 2, 3, format(angle(scaled_wc('ledq_2123')),'.6e'), '# cledqPh2x1x2x3'], [2, 1, 3, 1, format(angle(scaled_wc('ledq_2131')),'.6e'), '# cledqPh2x1x3x1'], [2, 1, 3, 2, format(angle(scaled_wc('ledq_2132')),'.6e'), '# cledqPh2x1x3x2'], [2, 1, 3, 3, format(angle(scaled_wc('ledq_2133')),'.6e'), '# cledqPh2x1x3x3'], [2, 2, 1, 1, format(angle(scaled_wc('ledq_2211')),'.6e'), '# cledqPh2x2x1x1'], [2, 2, 1, 2, format(angle(scaled_wc('ledq_2212')),'.6e'), '# cledqPh2x2x1x2'], [2, 2, 1, 3, format(angle(scaled_wc('ledq_2213')),'.6e'), '# cledqPh2x2x1x3'], [2, 2, 2, 1, format(angle(scaled_wc('ledq_2221')),'.6e'), '# cledqPh2x2x2x1'], [2, 2, 2, 2, format(angle(scaled_wc('ledq_2222')),'.6e'), '# cledqPh2x2x2x2'], [2, 2, 2, 3, format(angle(scaled_wc('ledq_2223')),'.6e'), '# cledqPh2x2x2x3'], [2, 2, 3, 1, format(angle(scaled_wc('ledq_2231')),'.6e'), '# cledqPh2x2x3x1'], [2, 2, 3, 2, format(angle(scaled_wc('ledq_2232')),'.6e'), '# cledqPh2x2x3x2'], [2, 2, 3, 3, format(angle(scaled_wc('ledq_2233')),'.6e'), '# cledqPh2x2x3x3'], [2, 3, 1, 1, format(angle(scaled_wc('ledq_2311')),'.6e'), '# cledqPh2x3x1x1'], [2, 3, 1, 2, format(angle(scaled_wc('ledq_2312')),'.6e'), '# cledqPh2x3x1x2'], [2, 3, 1, 3, format(angle(scaled_wc('ledq_2313')),'.6e'), '# cledqPh2x3x1x3'], [2, 3, 2, 1, format(angle(scaled_wc('ledq_2321')),'.6e'), '# cledqPh2x3x2x1'], [2, 3, 2, 2, format(angle(scaled_wc('ledq_2322')),'.6e'), '# cledqPh2x3x2x2'], [2, 3, 2, 3, format(angle(scaled_wc('ledq_2323')),'.6e'), '# cledqPh2x3x2x3'], [2, 3, 3, 1, format(angle(scaled_wc('ledq_2331')),'.6e'), '# cledqPh2x3x3x1'], [2, 3, 3, 2, format(angle(scaled_wc('ledq_2332')),'.6e'), '# cledqPh2x3x3x2'], [2, 3, 3, 3, format(angle(scaled_wc('ledq_2333')),'.6e'), '# cledqPh2x3x3x3'], [3, 1, 1, 1, format(angle(scaled_wc('ledq_3111')),'.6e'), '# cledqPh3x1x1x1'], [3, 1, 1, 2, format(angle(scaled_wc('ledq_3112')),'.6e'), '# cledqPh3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('ledq_3113')),'.6e'), '# cledqPh3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('ledq_3121')),'.6e'), '# cledqPh3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('ledq_3122')),'.6e'), '# cledqPh3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('ledq_3123')),'.6e'), '# cledqPh3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('ledq_3131')),'.6e'), '# cledqPh3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('ledq_3132')),'.6e'), '# cledqPh3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('ledq_3133')),'.6e'), '# cledqPh3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('ledq_3211')),'.6e'), '# cledqPh3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('ledq_3212')),'.6e'), '# cledqPh3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('ledq_3213')),'.6e'), '# cledqPh3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('ledq_3221')),'.6e'), '# cledqPh3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('ledq_3222')),'.6e'), '# cledqPh3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('ledq_3223')),'.6e'), '# cledqPh3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('ledq_3231')),'.6e'), '# cledqPh3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('ledq_3232')),'.6e'), '# cledqPh3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('ledq_3233')),'.6e'), '# cledqPh3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('ledq_3311')),'.6e'), '# 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format(angle(scaled_wc('quqd8_3112')),'.6e'), '# cquqd8Ph3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('quqd8_3113')),'.6e'), '# cquqd8Ph3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('quqd8_3121')),'.6e'), '# cquqd8Ph3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('quqd8_3122')),'.6e'), '# cquqd8Ph3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('quqd8_3123')),'.6e'), '# cquqd8Ph3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('quqd8_3131')),'.6e'), '# cquqd8Ph3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('quqd8_3132')),'.6e'), '# cquqd8Ph3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('quqd8_3133')),'.6e'), '# cquqd8Ph3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('quqd8_3211')),'.6e'), '# cquqd8Ph3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('quqd8_3212')),'.6e'), '# cquqd8Ph3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('quqd8_3213')),'.6e'), '# cquqd8Ph3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('quqd8_3221')),'.6e'), '# cquqd8Ph3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('quqd8_3222')),'.6e'), '# cquqd8Ph3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('quqd8_3223')),'.6e'), '# cquqd8Ph3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('quqd8_3231')),'.6e'), '# cquqd8Ph3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('quqd8_3232')),'.6e'), '# cquqd8Ph3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('quqd8_3233')),'.6e'), '# cquqd8Ph3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('quqd8_3311')),'.6e'), '# cquqd8Ph3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('quqd8_3312')),'.6e'), '# cquqd8Ph3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('quqd8_3313')),'.6e'), '# cquqd8Ph3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('quqd8_3321')),'.6e'), '# cquqd8Ph3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('quqd8_3322')),'.6e'), '# cquqd8Ph3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('quqd8_3323')),'.6e'), '# cquqd8Ph3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('quqd8_3331')),'.6e'), '# cquqd8Ph3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('quqd8_3332')),'.6e'), '# cquqd8Ph3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('quqd8_3333')),'.6e'), '# cquqd8Ph3x3x3x3'], ]} card['Block']['FRBlock17'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('lequ1_1111')),'.6e'), '# clequ1Ph1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('lequ1_1112')),'.6e'), '# clequ1Ph1x1x1x2'], [1, 1, 1, 3, format(angle(scaled_wc('lequ1_1113')),'.6e'), '# clequ1Ph1x1x1x3'], [1, 1, 2, 1, format(angle(scaled_wc('lequ1_1121')),'.6e'), '# clequ1Ph1x1x2x1'], [1, 1, 2, 2, format(angle(scaled_wc('lequ1_1122')),'.6e'), '# clequ1Ph1x1x2x2'], [1, 1, 2, 3, format(angle(scaled_wc('lequ1_1123')),'.6e'), '# clequ1Ph1x1x2x3'], [1, 1, 3, 1, format(angle(scaled_wc('lequ1_1131')),'.6e'), '# clequ1Ph1x1x3x1'], [1, 1, 3, 2, format(angle(scaled_wc('lequ1_1132')),'.6e'), '# clequ1Ph1x1x3x2'], [1, 1, 3, 3, format(angle(scaled_wc('lequ1_1133')),'.6e'), '# clequ1Ph1x1x3x3'], [1, 2, 1, 1, format(angle(scaled_wc('lequ1_1211')),'.6e'), '# clequ1Ph1x2x1x1'], [1, 2, 1, 2, format(angle(scaled_wc('lequ1_1212')),'.6e'), '# clequ1Ph1x2x1x2'], [1, 2, 1, 3, format(angle(scaled_wc('lequ1_1213')),'.6e'), '# clequ1Ph1x2x1x3'], [1, 2, 2, 1, format(angle(scaled_wc('lequ1_1221')),'.6e'), '# clequ1Ph1x2x2x1'], [1, 2, 2, 2, format(angle(scaled_wc('lequ1_1222')),'.6e'), '# clequ1Ph1x2x2x2'], [1, 2, 2, 3, format(angle(scaled_wc('lequ1_1223')),'.6e'), '# clequ1Ph1x2x2x3'], [1, 2, 3, 1, format(angle(scaled_wc('lequ1_1231')),'.6e'), '# clequ1Ph1x2x3x1'], [1, 2, 3, 2, format(angle(scaled_wc('lequ1_1232')),'.6e'), '# clequ1Ph1x2x3x2'], [1, 2, 3, 3, format(angle(scaled_wc('lequ1_1233')),'.6e'), '# clequ1Ph1x2x3x3'], [1, 3, 1, 1, format(angle(scaled_wc('lequ1_1311')),'.6e'), '# clequ1Ph1x3x1x1'], [1, 3, 1, 2, format(angle(scaled_wc('lequ1_1312')),'.6e'), '# clequ1Ph1x3x1x2'], [1, 3, 1, 3, format(angle(scaled_wc('lequ1_1313')),'.6e'), '# clequ1Ph1x3x1x3'], [1, 3, 2, 1, format(angle(scaled_wc('lequ1_1321')),'.6e'), '# clequ1Ph1x3x2x1'], [1, 3, 2, 2, format(angle(scaled_wc('lequ1_1322')),'.6e'), '# clequ1Ph1x3x2x2'], [1, 3, 2, 3, format(angle(scaled_wc('lequ1_1323')),'.6e'), '# clequ1Ph1x3x2x3'], [1, 3, 3, 1, format(angle(scaled_wc('lequ1_1331')),'.6e'), '# clequ1Ph1x3x3x1'], [1, 3, 3, 2, format(angle(scaled_wc('lequ1_1332')),'.6e'), '# clequ1Ph1x3x3x2'], [1, 3, 3, 3, format(angle(scaled_wc('lequ1_1333')),'.6e'), '# clequ1Ph1x3x3x3'], [2, 1, 1, 1, format(angle(scaled_wc('lequ1_2111')),'.6e'), '# clequ1Ph2x1x1x1'], [2, 1, 1, 2, format(angle(scaled_wc('lequ1_2112')),'.6e'), '# clequ1Ph2x1x1x2'], [2, 1, 1, 3, format(angle(scaled_wc('lequ1_2113')),'.6e'), '# clequ1Ph2x1x1x3'], [2, 1, 2, 1, format(angle(scaled_wc('lequ1_2121')),'.6e'), '# clequ1Ph2x1x2x1'], [2, 1, 2, 2, format(angle(scaled_wc('lequ1_2122')),'.6e'), '# clequ1Ph2x1x2x2'], [2, 1, 2, 3, format(angle(scaled_wc('lequ1_2123')),'.6e'), '# clequ1Ph2x1x2x3'], [2, 1, 3, 1, format(angle(scaled_wc('lequ1_2131')),'.6e'), '# clequ1Ph2x1x3x1'], [2, 1, 3, 2, format(angle(scaled_wc('lequ1_2132')),'.6e'), '# clequ1Ph2x1x3x2'], [2, 1, 3, 3, format(angle(scaled_wc('lequ1_2133')),'.6e'), '# clequ1Ph2x1x3x3'], [2, 2, 1, 1, format(angle(scaled_wc('lequ1_2211')),'.6e'), '# clequ1Ph2x2x1x1'], [2, 2, 1, 2, format(angle(scaled_wc('lequ1_2212')),'.6e'), '# clequ1Ph2x2x1x2'], [2, 2, 1, 3, format(angle(scaled_wc('lequ1_2213')),'.6e'), '# clequ1Ph2x2x1x3'], [2, 2, 2, 1, format(angle(scaled_wc('lequ1_2221')),'.6e'), '# clequ1Ph2x2x2x1'], [2, 2, 2, 2, format(angle(scaled_wc('lequ1_2222')),'.6e'), '# clequ1Ph2x2x2x2'], [2, 2, 2, 3, format(angle(scaled_wc('lequ1_2223')),'.6e'), '# clequ1Ph2x2x2x3'], [2, 2, 3, 1, format(angle(scaled_wc('lequ1_2231')),'.6e'), '# clequ1Ph2x2x3x1'], [2, 2, 3, 2, format(angle(scaled_wc('lequ1_2232')),'.6e'), '# clequ1Ph2x2x3x2'], [2, 2, 3, 3, format(angle(scaled_wc('lequ1_2233')),'.6e'), '# clequ1Ph2x2x3x3'], [2, 3, 1, 1, format(angle(scaled_wc('lequ1_2311')),'.6e'), '# clequ1Ph2x3x1x1'], [2, 3, 1, 2, format(angle(scaled_wc('lequ1_2312')),'.6e'), '# clequ1Ph2x3x1x2'], [2, 3, 1, 3, format(angle(scaled_wc('lequ1_2313')),'.6e'), '# clequ1Ph2x3x1x3'], [2, 3, 2, 1, format(angle(scaled_wc('lequ1_2321')),'.6e'), '# clequ1Ph2x3x2x1'], [2, 3, 2, 2, format(angle(scaled_wc('lequ1_2322')),'.6e'), '# clequ1Ph2x3x2x2'], [2, 3, 2, 3, format(angle(scaled_wc('lequ1_2323')),'.6e'), '# clequ1Ph2x3x2x3'], [2, 3, 3, 1, format(angle(scaled_wc('lequ1_2331')),'.6e'), '# clequ1Ph2x3x3x1'], [2, 3, 3, 2, format(angle(scaled_wc('lequ1_2332')),'.6e'), '# clequ1Ph2x3x3x2'], [2, 3, 3, 3, format(angle(scaled_wc('lequ1_2333')),'.6e'), '# clequ1Ph2x3x3x3'], [3, 1, 1, 1, format(angle(scaled_wc('lequ1_3111')),'.6e'), '# clequ1Ph3x1x1x1'], [3, 1, 1, 2, format(angle(scaled_wc('lequ1_3112')),'.6e'), '# clequ1Ph3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('lequ1_3113')),'.6e'), '# clequ1Ph3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('lequ1_3121')),'.6e'), '# clequ1Ph3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('lequ1_3122')),'.6e'), '# clequ1Ph3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('lequ1_3123')),'.6e'), '# clequ1Ph3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('lequ1_3131')),'.6e'), '# clequ1Ph3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('lequ1_3132')),'.6e'), '# clequ1Ph3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('lequ1_3133')),'.6e'), '# clequ1Ph3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('lequ1_3211')),'.6e'), '# clequ1Ph3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('lequ1_3212')),'.6e'), '# clequ1Ph3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('lequ1_3213')),'.6e'), '# clequ1Ph3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('lequ1_3221')),'.6e'), '# clequ1Ph3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('lequ1_3222')),'.6e'), '# clequ1Ph3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('lequ1_3223')),'.6e'), '# clequ1Ph3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('lequ1_3231')),'.6e'), '# clequ1Ph3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('lequ1_3232')),'.6e'), '# clequ1Ph3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('lequ1_3233')),'.6e'), '# clequ1Ph3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('lequ1_3311')),'.6e'), '# clequ1Ph3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('lequ1_3312')),'.6e'), '# clequ1Ph3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('lequ1_3313')),'.6e'), '# clequ1Ph3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('lequ1_3321')),'.6e'), '# clequ1Ph3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('lequ1_3322')),'.6e'), '# clequ1Ph3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('lequ1_3323')),'.6e'), '# clequ1Ph3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('lequ1_3331')),'.6e'), '# clequ1Ph3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('lequ1_3332')),'.6e'), '# clequ1Ph3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('lequ1_3333')),'.6e'), '# clequ1Ph3x3x3x3'], ]} card['Block']['FRBlock18'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('lequ3_1111')),'.6e'), '# clequ3Ph1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('lequ3_1112')),'.6e'), '# clequ3Ph1x1x1x2'], [1, 1, 1, 3, format(angle(scaled_wc('lequ3_1113')),'.6e'), '# clequ3Ph1x1x1x3'], [1, 1, 2, 1, format(angle(scaled_wc('lequ3_1121')),'.6e'), '# clequ3Ph1x1x2x1'], [1, 1, 2, 2, format(angle(scaled_wc('lequ3_1122')),'.6e'), '# clequ3Ph1x1x2x2'], [1, 1, 2, 3, format(angle(scaled_wc('lequ3_1123')),'.6e'), '# clequ3Ph1x1x2x3'], [1, 1, 3, 1, format(angle(scaled_wc('lequ3_1131')),'.6e'), '# clequ3Ph1x1x3x1'], [1, 1, 3, 2, format(angle(scaled_wc('lequ3_1132')),'.6e'), '# clequ3Ph1x1x3x2'], [1, 1, 3, 3, format(angle(scaled_wc('lequ3_1133')),'.6e'), '# clequ3Ph1x1x3x3'], [1, 2, 1, 1, format(angle(scaled_wc('lequ3_1211')),'.6e'), '# clequ3Ph1x2x1x1'], [1, 2, 1, 2, format(angle(scaled_wc('lequ3_1212')),'.6e'), '# clequ3Ph1x2x1x2'], [1, 2, 1, 3, format(angle(scaled_wc('lequ3_1213')),'.6e'), '# clequ3Ph1x2x1x3'], [1, 2, 2, 1, format(angle(scaled_wc('lequ3_1221')),'.6e'), '# clequ3Ph1x2x2x1'], [1, 2, 2, 2, format(angle(scaled_wc('lequ3_1222')),'.6e'), '# clequ3Ph1x2x2x2'], [1, 2, 2, 3, format(angle(scaled_wc('lequ3_1223')),'.6e'), '# clequ3Ph1x2x2x3'], [1, 2, 3, 1, format(angle(scaled_wc('lequ3_1231')),'.6e'), '# clequ3Ph1x2x3x1'], [1, 2, 3, 2, format(angle(scaled_wc('lequ3_1232')),'.6e'), '# clequ3Ph1x2x3x2'], [1, 2, 3, 3, format(angle(scaled_wc('lequ3_1233')),'.6e'), '# clequ3Ph1x2x3x3'], [1, 3, 1, 1, format(angle(scaled_wc('lequ3_1311')),'.6e'), '# clequ3Ph1x3x1x1'], [1, 3, 1, 2, format(angle(scaled_wc('lequ3_1312')),'.6e'), '# clequ3Ph1x3x1x2'], [1, 3, 1, 3, format(angle(scaled_wc('lequ3_1313')),'.6e'), '# clequ3Ph1x3x1x3'], [1, 3, 2, 1, format(angle(scaled_wc('lequ3_1321')),'.6e'), '# clequ3Ph1x3x2x1'], [1, 3, 2, 2, format(angle(scaled_wc('lequ3_1322')),'.6e'), '# clequ3Ph1x3x2x2'], [1, 3, 2, 3, format(angle(scaled_wc('lequ3_1323')),'.6e'), '# clequ3Ph1x3x2x3'], [1, 3, 3, 1, format(angle(scaled_wc('lequ3_1331')),'.6e'), '# clequ3Ph1x3x3x1'], [1, 3, 3, 2, format(angle(scaled_wc('lequ3_1332')),'.6e'), '# clequ3Ph1x3x3x2'], [1, 3, 3, 3, format(angle(scaled_wc('lequ3_1333')),'.6e'), '# clequ3Ph1x3x3x3'], [2, 1, 1, 1, format(angle(scaled_wc('lequ3_2111')),'.6e'), '# clequ3Ph2x1x1x1'], [2, 1, 1, 2, format(angle(scaled_wc('lequ3_2112')),'.6e'), '# clequ3Ph2x1x1x2'], [2, 1, 1, 3, format(angle(scaled_wc('lequ3_2113')),'.6e'), '# clequ3Ph2x1x1x3'], [2, 1, 2, 1, format(angle(scaled_wc('lequ3_2121')),'.6e'), '# clequ3Ph2x1x2x1'], [2, 1, 2, 2, format(angle(scaled_wc('lequ3_2122')),'.6e'), '# clequ3Ph2x1x2x2'], [2, 1, 2, 3, format(angle(scaled_wc('lequ3_2123')),'.6e'), '# clequ3Ph2x1x2x3'], [2, 1, 3, 1, format(angle(scaled_wc('lequ3_2131')),'.6e'), '# clequ3Ph2x1x3x1'], [2, 1, 3, 2, format(angle(scaled_wc('lequ3_2132')),'.6e'), '# clequ3Ph2x1x3x2'], [2, 1, 3, 3, format(angle(scaled_wc('lequ3_2133')),'.6e'), '# clequ3Ph2x1x3x3'], [2, 2, 1, 1, format(angle(scaled_wc('lequ3_2211')),'.6e'), '# clequ3Ph2x2x1x1'], [2, 2, 1, 2, format(angle(scaled_wc('lequ3_2212')),'.6e'), '# clequ3Ph2x2x1x2'], [2, 2, 1, 3, format(angle(scaled_wc('lequ3_2213')),'.6e'), '# clequ3Ph2x2x1x3'], [2, 2, 2, 1, format(angle(scaled_wc('lequ3_2221')),'.6e'), '# clequ3Ph2x2x2x1'], [2, 2, 2, 2, format(angle(scaled_wc('lequ3_2222')),'.6e'), '# clequ3Ph2x2x2x2'], [2, 2, 2, 3, format(angle(scaled_wc('lequ3_2223')),'.6e'), '# clequ3Ph2x2x2x3'], [2, 2, 3, 1, format(angle(scaled_wc('lequ3_2231')),'.6e'), '# clequ3Ph2x2x3x1'], [2, 2, 3, 2, format(angle(scaled_wc('lequ3_2232')),'.6e'), '# clequ3Ph2x2x3x2'], [2, 2, 3, 3, format(angle(scaled_wc('lequ3_2233')),'.6e'), '# clequ3Ph2x2x3x3'], [2, 3, 1, 1, format(angle(scaled_wc('lequ3_2311')),'.6e'), '# clequ3Ph2x3x1x1'], [2, 3, 1, 2, format(angle(scaled_wc('lequ3_2312')),'.6e'), '# clequ3Ph2x3x1x2'], [2, 3, 1, 3, format(angle(scaled_wc('lequ3_2313')),'.6e'), '# clequ3Ph2x3x1x3'], [2, 3, 2, 1, format(angle(scaled_wc('lequ3_2321')),'.6e'), '# clequ3Ph2x3x2x1'], [2, 3, 2, 2, format(angle(scaled_wc('lequ3_2322')),'.6e'), '# clequ3Ph2x3x2x2'], [2, 3, 2, 3, format(angle(scaled_wc('lequ3_2323')),'.6e'), '# clequ3Ph2x3x2x3'], [2, 3, 3, 1, format(angle(scaled_wc('lequ3_2331')),'.6e'), '# clequ3Ph2x3x3x1'], [2, 3, 3, 2, format(angle(scaled_wc('lequ3_2332')),'.6e'), '# clequ3Ph2x3x3x2'], [2, 3, 3, 3, format(angle(scaled_wc('lequ3_2333')),'.6e'), '# clequ3Ph2x3x3x3'], [3, 1, 1, 1, format(angle(scaled_wc('lequ3_3111')),'.6e'), '# clequ3Ph3x1x1x1'], [3, 1, 1, 2, format(angle(scaled_wc('lequ3_3112')),'.6e'), '# clequ3Ph3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('lequ3_3113')),'.6e'), '# clequ3Ph3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('lequ3_3121')),'.6e'), '# clequ3Ph3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('lequ3_3122')),'.6e'), '# clequ3Ph3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('lequ3_3123')),'.6e'), '# clequ3Ph3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('lequ3_3131')),'.6e'), '# clequ3Ph3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('lequ3_3132')),'.6e'), '# clequ3Ph3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('lequ3_3133')),'.6e'), '# clequ3Ph3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('lequ3_3211')),'.6e'), '# clequ3Ph3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('lequ3_3212')),'.6e'), '# clequ3Ph3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('lequ3_3213')),'.6e'), '# clequ3Ph3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('lequ3_3221')),'.6e'), '# clequ3Ph3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('lequ3_3222')),'.6e'), '# clequ3Ph3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('lequ3_3223')),'.6e'), '# clequ3Ph3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('lequ3_3231')),'.6e'), '# clequ3Ph3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('lequ3_3232')),'.6e'), '# clequ3Ph3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('lequ3_3233')),'.6e'), '# clequ3Ph3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('lequ3_3311')),'.6e'), '# clequ3Ph3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('lequ3_3312')),'.6e'), '# clequ3Ph3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('lequ3_3313')),'.6e'), '# clequ3Ph3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('lequ3_3321')),'.6e'), '# clequ3Ph3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('lequ3_3322')),'.6e'), '# clequ3Ph3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('lequ3_3323')),'.6e'), '# clequ3Ph3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('lequ3_3331')),'.6e'), '# clequ3Ph3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('lequ3_3332')),'.6e'), '# clequ3Ph3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('lequ3_3333')),'.6e'), '# clequ3Ph3x3x3x3'], ]} card['Block']['FRBlock19'] = {'values': [ [1, 1, format(abs(scaled_wc('ephi_11')) * lambda_smeft_value**2,'.6e'), '# ceHAbs1x1'], [1, 2, format(abs(scaled_wc('ephi_12')) * lambda_smeft_value**2,'.6e'), '# ceHAbs1x2'], [1, 3, format(abs(scaled_wc('ephi_13')) * lambda_smeft_value**2,'.6e'), '# ceHAbs1x3'], [2, 1, format(abs(scaled_wc('ephi_21')) * lambda_smeft_value**2,'.6e'), '# ceHAbs2x1'], [2, 2, format(abs(scaled_wc('ephi_22')) * lambda_smeft_value**2,'.6e'), '# ceHAbs2x2'], [2, 3, format(abs(scaled_wc('ephi_23')) * lambda_smeft_value**2,'.6e'), '# ceHAbs2x3'], [3, 1, format(abs(scaled_wc('ephi_31')) * lambda_smeft_value**2,'.6e'), '# ceHAbs3x1'], [3, 2, format(abs(scaled_wc('ephi_32')) * lambda_smeft_value**2,'.6e'), '# ceHAbs3x2'], [3, 3, format(abs(scaled_wc('ephi_33')) * lambda_smeft_value**2,'.6e'), '# ceHAbs3x3'], ]} card['Block']['FRBlock2'] = {'values': [ [1, 1, format(angle(scaled_wc('eW_11')),'.6e'), '# ceWPh1x1'], [1, 2, format(angle(scaled_wc('eW_12')),'.6e'), '# ceWPh1x2'], [1, 3, format(angle(scaled_wc('eW_13')),'.6e'), '# ceWPh1x3'], [2, 1, format(angle(scaled_wc('eW_21')),'.6e'), '# ceWPh2x1'], [2, 2, format(angle(scaled_wc('eW_22')),'.6e'), '# ceWPh2x2'], [2, 3, format(angle(scaled_wc('eW_23')),'.6e'), '# ceWPh2x3'], [3, 1, format(angle(scaled_wc('eW_31')),'.6e'), '# ceWPh3x1'], [3, 2, format(angle(scaled_wc('eW_32')),'.6e'), '# ceWPh3x2'], [3, 3, format(angle(scaled_wc('eW_33')),'.6e'), '# ceWPh3x3'], ]} card['Block']['FRBlock20'] = {'values': [ [1, 1, format(abs(scaled_wc('uphi_11')) * lambda_smeft_value**2,'.6e'), '# cuHAbs1x1'], [1, 2, format(abs(scaled_wc('uphi_12')) * lambda_smeft_value**2,'.6e'), '# cuHAbs1x2'], [1, 3, format(abs(scaled_wc('uphi_13')) * lambda_smeft_value**2,'.6e'), '# cuHAbs1x3'], [2, 1, format(abs(scaled_wc('uphi_21')) * lambda_smeft_value**2,'.6e'), '# cuHAbs2x1'], [2, 2, format(abs(scaled_wc('uphi_22')) * lambda_smeft_value**2,'.6e'), '# cuHAbs2x2'], [2, 3, format(abs(scaled_wc('uphi_23')) * lambda_smeft_value**2,'.6e'), '# cuHAbs2x3'], [3, 1, format(abs(scaled_wc('uphi_31')) * lambda_smeft_value**2,'.6e'), '# cuHAbs3x1'], [3, 2, format(abs(scaled_wc('uphi_32')) * lambda_smeft_value**2,'.6e'), '# cuHAbs3x2'], [3, 3, format(abs(scaled_wc('uphi_33')) * lambda_smeft_value**2,'.6e'), '# cuHAbs3x3'], ]} card['Block']['FRBlock21'] = {'values': [ [1, 1, format(abs(scaled_wc('dphi_11')) * lambda_smeft_value**2,'.6e'), '# cdHAbs1x1'], [1, 2, format(abs(scaled_wc('dphi_12')) * lambda_smeft_value**2,'.6e'), '# cdHAbs1x2'], [1, 3, format(abs(scaled_wc('dphi_13')) * lambda_smeft_value**2,'.6e'), '# cdHAbs1x3'], [2, 1, format(abs(scaled_wc('dphi_21')) * lambda_smeft_value**2,'.6e'), '# cdHAbs2x1'], [2, 2, format(abs(scaled_wc('dphi_22')) * lambda_smeft_value**2,'.6e'), '# cdHAbs2x2'], [2, 3, format(abs(scaled_wc('dphi_23')) * lambda_smeft_value**2,'.6e'), '# cdHAbs2x3'], [3, 1, format(abs(scaled_wc('dphi_31')) * lambda_smeft_value**2,'.6e'), '# cdHAbs3x1'], [3, 2, format(abs(scaled_wc('dphi_32')) * lambda_smeft_value**2,'.6e'), '# cdHAbs3x2'], [3, 3, format(abs(scaled_wc('dphi_33')) * lambda_smeft_value**2,'.6e'), '# cdHAbs3x3'], ]} card['Block']['FRBlock25'] = {'values': [ [1, 1, format(abs(scaled_wc('eW_11')) * lambda_smeft_value**2,'.6e'), '# ceWAbs1x1'], [1, 2, format(abs(scaled_wc('eW_12')) * lambda_smeft_value**2,'.6e'), '# ceWAbs1x2'], [1, 3, format(abs(scaled_wc('eW_13')) * lambda_smeft_value**2,'.6e'), '# ceWAbs1x3'], [2, 1, format(abs(scaled_wc('eW_21')) * lambda_smeft_value**2,'.6e'), '# ceWAbs2x1'], [2, 2, format(abs(scaled_wc('eW_22')) * lambda_smeft_value**2,'.6e'), '# ceWAbs2x2'], [2, 3, format(abs(scaled_wc('eW_23')) * lambda_smeft_value**2,'.6e'), '# ceWAbs2x3'], [3, 1, format(abs(scaled_wc('eW_31')) * lambda_smeft_value**2,'.6e'), '# ceWAbs3x1'], [3, 2, format(abs(scaled_wc('eW_32')) * lambda_smeft_value**2,'.6e'), '# ceWAbs3x2'], [3, 3, format(abs(scaled_wc('eW_33')) * lambda_smeft_value**2,'.6e'), '# ceWAbs3x3'], ]} card['Block']['FRBlock26'] = {'values': [ [1, 1, format(abs(scaled_wc('eB_11')) * lambda_smeft_value**2,'.6e'), '# ceBAbs1x1'], [1, 2, format(abs(scaled_wc('eB_12')) * lambda_smeft_value**2,'.6e'), '# ceBAbs1x2'], [1, 3, format(abs(scaled_wc('eB_13')) * lambda_smeft_value**2,'.6e'), '# ceBAbs1x3'], [2, 1, format(abs(scaled_wc('eB_21')) * lambda_smeft_value**2,'.6e'), '# ceBAbs2x1'], [2, 2, format(abs(scaled_wc('eB_22')) * lambda_smeft_value**2,'.6e'), '# ceBAbs2x2'], [2, 3, format(abs(scaled_wc('eB_23')) * lambda_smeft_value**2,'.6e'), '# ceBAbs2x3'], [3, 1, format(abs(scaled_wc('eB_31')) * lambda_smeft_value**2,'.6e'), '# ceBAbs3x1'], [3, 2, format(abs(scaled_wc('eB_32')) * lambda_smeft_value**2,'.6e'), '# ceBAbs3x2'], [3, 3, format(abs(scaled_wc('eB_33')) * lambda_smeft_value**2,'.6e'), '# ceBAbs3x3'], ]} card['Block']['FRBlock27'] = {'values': [ [1, 1, format(abs(scaled_wc('uG_11')) * lambda_smeft_value**2,'.6e'), '# cuGAbs1x1'], [1, 2, format(abs(scaled_wc('uG_12')) * lambda_smeft_value**2,'.6e'), '# cuGAbs1x2'], [1, 3, format(abs(scaled_wc('uG_13')) * lambda_smeft_value**2,'.6e'), '# cuGAbs1x3'], [2, 1, format(abs(scaled_wc('uG_21')) * lambda_smeft_value**2,'.6e'), '# cuGAbs2x1'], [2, 2, format(abs(scaled_wc('uG_22')) * lambda_smeft_value**2,'.6e'), '# cuGAbs2x2'], [2, 3, format(abs(scaled_wc('uG_23')) * lambda_smeft_value**2,'.6e'), '# cuGAbs2x3'], [3, 1, format(abs(scaled_wc('uG_31')) * lambda_smeft_value**2,'.6e'), '# cuGAbs3x1'], [3, 2, format(abs(scaled_wc('uG_32')) * lambda_smeft_value**2,'.6e'), '# cuGAbs3x2'], [3, 3, format(abs(scaled_wc('uG_33')) * lambda_smeft_value**2,'.6e'), '# cuGAbs3x3'], ]} card['Block']['FRBlock28'] = {'values': [ [1, 1, format(abs(scaled_wc('uW_11')) * lambda_smeft_value**2,'.6e'), '# cuWAbs1x1'], [1, 2, format(abs(scaled_wc('uW_12')) * lambda_smeft_value**2,'.6e'), '# cuWAbs1x2'], [1, 3, format(abs(scaled_wc('uW_13')) * lambda_smeft_value**2,'.6e'), '# cuWAbs1x3'], [2, 1, format(abs(scaled_wc('uW_21')) * lambda_smeft_value**2,'.6e'), '# cuWAbs2x1'], [2, 2, format(abs(scaled_wc('uW_22')) * lambda_smeft_value**2,'.6e'), '# cuWAbs2x2'], [2, 3, format(abs(scaled_wc('uW_23')) * lambda_smeft_value**2,'.6e'), '# cuWAbs2x3'], [3, 1, format(abs(scaled_wc('uW_31')) * lambda_smeft_value**2,'.6e'), '# cuWAbs3x1'], [3, 2, format(abs(scaled_wc('uW_32')) * lambda_smeft_value**2,'.6e'), '# cuWAbs3x2'], [3, 3, format(abs(scaled_wc('uW_33')) * lambda_smeft_value**2,'.6e'), '# cuWAbs3x3'], ]} card['Block']['FRBlock29'] = {'values': [ [1, 1, format(abs(scaled_wc('uB_11')) * lambda_smeft_value**2,'.6e'), '# cuBAbs1x1'], [1, 2, format(abs(scaled_wc('uB_12')) * lambda_smeft_value**2,'.6e'), '# cuBAbs1x2'], [1, 3, format(abs(scaled_wc('uB_13')) * lambda_smeft_value**2,'.6e'), '# cuBAbs1x3'], [2, 1, format(abs(scaled_wc('uB_21')) * lambda_smeft_value**2,'.6e'), '# cuBAbs2x1'], [2, 2, format(abs(scaled_wc('uB_22')) * lambda_smeft_value**2,'.6e'), '# cuBAbs2x2'], [2, 3, format(abs(scaled_wc('uB_23')) * lambda_smeft_value**2,'.6e'), '# cuBAbs2x3'], [3, 1, format(abs(scaled_wc('uB_31')) * lambda_smeft_value**2,'.6e'), '# cuBAbs3x1'], [3, 2, format(abs(scaled_wc('uB_32')) * lambda_smeft_value**2,'.6e'), '# cuBAbs3x2'], [3, 3, format(abs(scaled_wc('uB_33')) * lambda_smeft_value**2,'.6e'), '# cuBAbs3x3'], ]} card['Block']['FRBlock3'] = {'values': [ [1, 1, format(angle(scaled_wc('eB_11')),'.6e'), '# ceBPh1x1'], [1, 2, format(angle(scaled_wc('eB_12')),'.6e'), '# ceBPh1x2'], [1, 3, format(angle(scaled_wc('eB_13')),'.6e'), '# ceBPh1x3'], [2, 1, format(angle(scaled_wc('eB_21')),'.6e'), '# ceBPh2x1'], [2, 2, format(angle(scaled_wc('eB_22')),'.6e'), '# ceBPh2x2'], [2, 3, format(angle(scaled_wc('eB_23')),'.6e'), '# ceBPh2x3'], [3, 1, format(angle(scaled_wc('eB_31')),'.6e'), '# ceBPh3x1'], [3, 2, format(angle(scaled_wc('eB_32')),'.6e'), '# ceBPh3x2'], [3, 3, format(angle(scaled_wc('eB_33')),'.6e'), '# ceBPh3x3'], ]} card['Block']['FRBlock30'] = {'values': [ [1, 1, format(abs(scaled_wc('dG_11')) * lambda_smeft_value**2,'.6e'), '# cdGAbs1x1'], [1, 2, format(abs(scaled_wc('dG_12')) * lambda_smeft_value**2,'.6e'), '# cdGAbs1x2'], [1, 3, format(abs(scaled_wc('dG_13')) * lambda_smeft_value**2,'.6e'), '# cdGAbs1x3'], [2, 1, format(abs(scaled_wc('dG_21')) * lambda_smeft_value**2,'.6e'), '# cdGAbs2x1'], [2, 2, format(abs(scaled_wc('dG_22')) * lambda_smeft_value**2,'.6e'), '# cdGAbs2x2'], [2, 3, format(abs(scaled_wc('dG_23')) * lambda_smeft_value**2,'.6e'), '# cdGAbs2x3'], [3, 1, format(abs(scaled_wc('dG_31')) * lambda_smeft_value**2,'.6e'), '# cdGAbs3x1'], [3, 2, format(abs(scaled_wc('dG_32')) * lambda_smeft_value**2,'.6e'), '# cdGAbs3x2'], [3, 3, format(abs(scaled_wc('dG_33')) * lambda_smeft_value**2,'.6e'), '# cdGAbs3x3'], ]} card['Block']['FRBlock31'] = {'values': [ [1, 1, format(abs(scaled_wc('dW_11')) * lambda_smeft_value**2,'.6e'), '# cdWAbs1x1'], [1, 2, format(abs(scaled_wc('dW_12')) * lambda_smeft_value**2,'.6e'), '# cdWAbs1x2'], [1, 3, format(abs(scaled_wc('dW_13')) * lambda_smeft_value**2,'.6e'), '# cdWAbs1x3'], [2, 1, format(abs(scaled_wc('dW_21')) * lambda_smeft_value**2,'.6e'), '# cdWAbs2x1'], [2, 2, format(abs(scaled_wc('dW_22')) * lambda_smeft_value**2,'.6e'), '# cdWAbs2x2'], [2, 3, format(abs(scaled_wc('dW_23')) * lambda_smeft_value**2,'.6e'), '# cdWAbs2x3'], [3, 1, format(abs(scaled_wc('dW_31')) * lambda_smeft_value**2,'.6e'), '# cdWAbs3x1'], [3, 2, format(abs(scaled_wc('dW_32')) * lambda_smeft_value**2,'.6e'), '# cdWAbs3x2'], [3, 3, format(abs(scaled_wc('dW_33')) * lambda_smeft_value**2,'.6e'), '# cdWAbs3x3'], ]} card['Block']['FRBlock32'] = {'values': [ [1, 1, format(abs(scaled_wc('dB_11')) * lambda_smeft_value**2,'.6e'), '# cdBAbs1x1'], [1, 2, format(abs(scaled_wc('dB_12')) * lambda_smeft_value**2,'.6e'), '# cdBAbs1x2'], [1, 3, format(abs(scaled_wc('dB_13')) * lambda_smeft_value**2,'.6e'), '# cdBAbs1x3'], [2, 1, format(abs(scaled_wc('dB_21')) * lambda_smeft_value**2,'.6e'), '# cdBAbs2x1'], [2, 2, format(abs(scaled_wc('dB_22')) * lambda_smeft_value**2,'.6e'), '# cdBAbs2x2'], [2, 3, format(abs(scaled_wc('dB_23')) * lambda_smeft_value**2,'.6e'), '# cdBAbs2x3'], [3, 1, format(abs(scaled_wc('dB_31')) * lambda_smeft_value**2,'.6e'), '# cdBAbs3x1'], [3, 2, format(abs(scaled_wc('dB_32')) * lambda_smeft_value**2,'.6e'), '# cdBAbs3x2'], [3, 3, format(abs(scaled_wc('dB_33')) * lambda_smeft_value**2,'.6e'), '# cdBAbs3x3'], ]} card['Block']['FRBlock4'] = {'values': [ [1, 1, format(angle(scaled_wc('uG_11')),'.6e'), '# cuGPh1x1'], [1, 2, format(angle(scaled_wc('uG_12')),'.6e'), '# cuGPh1x2'], [1, 3, format(angle(scaled_wc('uG_13')),'.6e'), '# cuGPh1x3'], [2, 1, format(angle(scaled_wc('uG_21')),'.6e'), '# cuGPh2x1'], [2, 2, format(angle(scaled_wc('uG_22')),'.6e'), '# cuGPh2x2'], [2, 3, format(angle(scaled_wc('uG_23')),'.6e'), '# cuGPh2x3'], [3, 1, format(angle(scaled_wc('uG_31')),'.6e'), '# cuGPh3x1'], [3, 2, format(angle(scaled_wc('uG_32')),'.6e'), '# cuGPh3x2'], [3, 3, format(angle(scaled_wc('uG_33')),'.6e'), '# cuGPh3x3'], ]} card['Block']['FRBlock48'] = {'values': [ [1, 1, format(abs(scaled_wc('phiud_11')) * lambda_smeft_value**2,'.6e'), '# cHudAbs1x1'], [1, 2, format(abs(scaled_wc('phiud_12')) * lambda_smeft_value**2,'.6e'), '# cHudAbs1x2'], [1, 3, format(abs(scaled_wc('phiud_13')) * lambda_smeft_value**2,'.6e'), '# cHudAbs1x3'], [2, 1, format(abs(scaled_wc('phiud_21')) * lambda_smeft_value**2,'.6e'), '# cHudAbs2x1'], [2, 2, format(abs(scaled_wc('phiud_22')) * lambda_smeft_value**2,'.6e'), '# cHudAbs2x2'], [2, 3, format(abs(scaled_wc('phiud_23')) * lambda_smeft_value**2,'.6e'), '# cHudAbs2x3'], [3, 1, format(abs(scaled_wc('phiud_31')) * lambda_smeft_value**2,'.6e'), '# cHudAbs3x1'], [3, 2, format(abs(scaled_wc('phiud_32')) * lambda_smeft_value**2,'.6e'), '# cHudAbs3x2'], [3, 3, format(abs(scaled_wc('phiud_33')) * lambda_smeft_value**2,'.6e'), '# cHudAbs3x3'], ]} card['Block']['FRBlock5'] = {'values': [ [1, 1, format(angle(scaled_wc('uW_11')),'.6e'), '# cuWPh1x1'], [1, 2, format(angle(scaled_wc('uW_12')),'.6e'), '# cuWPh1x2'], [1, 3, format(angle(scaled_wc('uW_13')),'.6e'), '# cuWPh1x3'], [2, 1, format(angle(scaled_wc('uW_21')),'.6e'), '# cuWPh2x1'], [2, 2, format(angle(scaled_wc('uW_22')),'.6e'), '# cuWPh2x2'], [2, 3, format(angle(scaled_wc('uW_23')),'.6e'), '# cuWPh2x3'], [3, 1, format(angle(scaled_wc('uW_31')),'.6e'), '# cuWPh3x1'], [3, 2, format(angle(scaled_wc('uW_32')),'.6e'), '# cuWPh3x2'], [3, 3, format(angle(scaled_wc('uW_33')),'.6e'), '# cuWPh3x3'], ]} card['Block']['FRBlock6'] = {'values': [ [1, 1, format(angle(scaled_wc('uB_11')),'.6e'), '# cuBPh1x1'], [1, 2, format(angle(scaled_wc('uB_12')),'.6e'), '# cuBPh1x2'], [1, 3, format(angle(scaled_wc('uB_13')),'.6e'), '# cuBPh1x3'], [2, 1, format(angle(scaled_wc('uB_21')),'.6e'), '# cuBPh2x1'], [2, 2, format(angle(scaled_wc('uB_22')),'.6e'), '# cuBPh2x2'], [2, 3, format(angle(scaled_wc('uB_23')),'.6e'), '# cuBPh2x3'], [3, 1, format(angle(scaled_wc('uB_31')),'.6e'), '# cuBPh3x1'], [3, 2, format(angle(scaled_wc('uB_32')),'.6e'), '# cuBPh3x2'], [3, 3, format(angle(scaled_wc('uB_33')),'.6e'), '# cuBPh3x3'], ]} card['Block']['FRBlock7'] = {'values': [ [1, 1, format(angle(scaled_wc('dG_11')),'.6e'), '# cdGPh1x1'], [1, 2, format(angle(scaled_wc('dG_12')),'.6e'), '# cdGPh1x2'], [1, 3, format(angle(scaled_wc('dG_13')),'.6e'), '# cdGPh1x3'], [2, 1, format(angle(scaled_wc('dG_21')),'.6e'), '# cdGPh2x1'], [2, 2, format(angle(scaled_wc('dG_22')),'.6e'), '# cdGPh2x2'], [2, 3, format(angle(scaled_wc('dG_23')),'.6e'), '# cdGPh2x3'], [3, 1, format(angle(scaled_wc('dG_31')),'.6e'), '# cdGPh3x1'], [3, 2, format(angle(scaled_wc('dG_32')),'.6e'), '# cdGPh3x2'], [3, 3, format(angle(scaled_wc('dG_33')),'.6e'), '# cdGPh3x3'], ]} card['Block']['FRBlock70'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('ledq_1111')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('ledq_1112')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('ledq_1113')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('ledq_1121')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('ledq_1122')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('ledq_1123')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('ledq_1131')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('ledq_1132')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('ledq_1133')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('ledq_1211')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('ledq_1212')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('ledq_1213')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('ledq_1221')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('ledq_1222')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('ledq_1223')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('ledq_1231')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('ledq_1232')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('ledq_1233')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('ledq_1311')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('ledq_1312')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('ledq_1313')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('ledq_1321')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('ledq_1322')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('ledq_1323')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('ledq_1331')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('ledq_1332')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('ledq_1333')) * lambda_smeft_value**2,'.6e'), '# cledqAbs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('ledq_2111')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('ledq_2112')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('ledq_2113')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('ledq_2121')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('ledq_2122')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('ledq_2123')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('ledq_2131')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('ledq_2132')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('ledq_2133')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('ledq_2211')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('ledq_2212')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('ledq_2213')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('ledq_2221')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('ledq_2222')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('ledq_2223')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('ledq_2231')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('ledq_2232')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('ledq_2233')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('ledq_2311')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('ledq_2312')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('ledq_2313')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('ledq_2321')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('ledq_2322')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('ledq_2323')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('ledq_2331')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('ledq_2332')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('ledq_2333')) * lambda_smeft_value**2,'.6e'), '# cledqAbs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('ledq_3111')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('ledq_3112')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('ledq_3113')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('ledq_3121')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('ledq_3122')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('ledq_3123')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('ledq_3131')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('ledq_3132')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('ledq_3133')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('ledq_3211')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('ledq_3212')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('ledq_3213')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('ledq_3221')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('ledq_3222')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('ledq_3223')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('ledq_3231')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('ledq_3232')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('ledq_3233')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('ledq_3311')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('ledq_3312')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('ledq_3313')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('ledq_3321')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('ledq_3322')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('ledq_3323')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('ledq_3331')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('ledq_3332')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('ledq_3333')) * lambda_smeft_value**2,'.6e'), '# cledqAbs3x3x3x3'], ]} card['Block']['FRBlock71'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('quqd1_1111')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('quqd1_1112')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('quqd1_1113')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('quqd1_1121')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('quqd1_1122')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('quqd1_1123')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('quqd1_1131')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('quqd1_1132')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('quqd1_1133')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('quqd1_1211')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('quqd1_1212')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('quqd1_1213')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('quqd1_1221')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('quqd1_1222')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('quqd1_1223')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('quqd1_1231')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('quqd1_1232')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('quqd1_1233')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('quqd1_1311')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('quqd1_1312')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('quqd1_1313')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('quqd1_1321')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('quqd1_1322')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('quqd1_1323')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('quqd1_1331')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('quqd1_1332')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('quqd1_1333')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('quqd1_2111')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('quqd1_2112')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('quqd1_2113')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('quqd1_2121')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('quqd1_2122')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('quqd1_2123')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('quqd1_2131')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('quqd1_2132')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('quqd1_2133')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('quqd1_2211')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('quqd1_2212')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('quqd1_2213')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('quqd1_2221')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('quqd1_2222')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('quqd1_2223')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('quqd1_2231')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('quqd1_2232')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('quqd1_2233')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('quqd1_2311')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('quqd1_2312')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('quqd1_2313')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('quqd1_2321')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('quqd1_2322')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('quqd1_2323')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('quqd1_2331')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('quqd1_2332')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('quqd1_2333')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('quqd1_3111')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('quqd1_3112')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('quqd1_3113')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('quqd1_3121')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('quqd1_3122')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('quqd1_3123')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('quqd1_3131')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('quqd1_3132')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('quqd1_3133')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('quqd1_3211')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('quqd1_3212')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('quqd1_3213')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('quqd1_3221')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('quqd1_3222')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('quqd1_3223')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('quqd1_3231')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('quqd1_3232')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('quqd1_3233')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('quqd1_3311')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('quqd1_3312')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('quqd1_3313')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('quqd1_3321')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('quqd1_3322')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('quqd1_3323')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('quqd1_3331')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('quqd1_3332')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('quqd1_3333')) * lambda_smeft_value**2,'.6e'), '# cquqd1Abs3x3x3x3'], ]} card['Block']['FRBlock72'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('quqd8_1111')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('quqd8_1112')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('quqd8_1113')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('quqd8_1121')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('quqd8_1122')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('quqd8_1123')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('quqd8_1131')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('quqd8_1132')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('quqd8_1133')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('quqd8_1211')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('quqd8_1212')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('quqd8_1213')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('quqd8_1221')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('quqd8_1222')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('quqd8_1223')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('quqd8_1231')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('quqd8_1232')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('quqd8_1233')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('quqd8_1311')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('quqd8_1312')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('quqd8_1313')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('quqd8_1321')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('quqd8_1322')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('quqd8_1323')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('quqd8_1331')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('quqd8_1332')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('quqd8_1333')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('quqd8_2111')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('quqd8_2112')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('quqd8_2113')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('quqd8_2121')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('quqd8_2122')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('quqd8_2123')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('quqd8_2131')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('quqd8_2132')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('quqd8_2133')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('quqd8_2211')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('quqd8_2212')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('quqd8_2213')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('quqd8_2221')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('quqd8_2222')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('quqd8_2223')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('quqd8_2231')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('quqd8_2232')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('quqd8_2233')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('quqd8_2311')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('quqd8_2312')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('quqd8_2313')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('quqd8_2321')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('quqd8_2322')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('quqd8_2323')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('quqd8_2331')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('quqd8_2332')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('quqd8_2333')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('quqd8_3111')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('quqd8_3112')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('quqd8_3113')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('quqd8_3121')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('quqd8_3122')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('quqd8_3123')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('quqd8_3131')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('quqd8_3132')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('quqd8_3133')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('quqd8_3211')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('quqd8_3212')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('quqd8_3213')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('quqd8_3221')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('quqd8_3222')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('quqd8_3223')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('quqd8_3231')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('quqd8_3232')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('quqd8_3233')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('quqd8_3311')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('quqd8_3312')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('quqd8_3313')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('quqd8_3321')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('quqd8_3322')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('quqd8_3323')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('quqd8_3331')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('quqd8_3332')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('quqd8_3333')) * lambda_smeft_value**2,'.6e'), '# cquqd8Abs3x3x3x3'], ]} card['Block']['FRBlock73'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('lequ1_1111')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('lequ1_1112')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('lequ1_1113')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('lequ1_1121')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('lequ1_1122')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('lequ1_1123')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('lequ1_1131')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('lequ1_1132')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('lequ1_1133')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('lequ1_1211')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('lequ1_1212')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('lequ1_1213')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('lequ1_1221')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('lequ1_1222')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('lequ1_1223')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('lequ1_1231')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('lequ1_1232')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('lequ1_1233')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('lequ1_1311')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('lequ1_1312')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('lequ1_1313')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('lequ1_1321')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('lequ1_1322')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('lequ1_1323')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('lequ1_1331')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('lequ1_1332')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('lequ1_1333')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('lequ1_2111')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('lequ1_2112')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('lequ1_2113')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('lequ1_2121')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('lequ1_2122')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('lequ1_2123')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('lequ1_2131')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('lequ1_2132')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('lequ1_2133')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('lequ1_2211')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('lequ1_2212')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('lequ1_2213')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('lequ1_2221')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('lequ1_2222')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('lequ1_2223')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('lequ1_2231')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('lequ1_2232')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('lequ1_2233')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('lequ1_2311')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('lequ1_2312')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('lequ1_2313')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('lequ1_2321')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('lequ1_2322')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('lequ1_2323')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('lequ1_2331')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('lequ1_2332')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('lequ1_2333')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('lequ1_3111')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('lequ1_3112')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('lequ1_3113')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('lequ1_3121')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('lequ1_3122')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('lequ1_3123')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('lequ1_3131')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('lequ1_3132')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('lequ1_3133')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('lequ1_3211')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('lequ1_3212')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('lequ1_3213')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('lequ1_3221')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('lequ1_3222')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('lequ1_3223')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('lequ1_3231')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('lequ1_3232')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('lequ1_3233')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('lequ1_3311')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('lequ1_3312')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('lequ1_3313')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('lequ1_3321')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('lequ1_3322')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('lequ1_3323')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('lequ1_3331')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('lequ1_3332')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('lequ1_3333')) * lambda_smeft_value**2,'.6e'), '# clequ1Abs3x3x3x3'], ]} card['Block']['FRBlock74'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('lequ3_1111')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('lequ3_1112')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('lequ3_1113')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('lequ3_1121')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('lequ3_1122')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('lequ3_1123')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('lequ3_1131')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('lequ3_1132')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('lequ3_1133')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('lequ3_1211')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('lequ3_1212')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('lequ3_1213')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('lequ3_1221')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('lequ3_1222')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('lequ3_1223')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('lequ3_1231')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('lequ3_1232')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('lequ3_1233')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('lequ3_1311')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('lequ3_1312')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('lequ3_1313')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('lequ3_1321')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('lequ3_1322')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('lequ3_1323')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('lequ3_1331')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('lequ3_1332')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('lequ3_1333')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('lequ3_2111')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('lequ3_2112')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('lequ3_2113')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('lequ3_2121')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('lequ3_2122')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('lequ3_2123')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('lequ3_2131')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('lequ3_2132')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('lequ3_2133')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('lequ3_2211')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('lequ3_2212')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('lequ3_2213')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('lequ3_2221')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('lequ3_2222')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('lequ3_2223')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('lequ3_2231')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('lequ3_2232')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('lequ3_2233')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('lequ3_2311')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('lequ3_2312')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('lequ3_2313')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('lequ3_2321')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('lequ3_2322')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('lequ3_2323')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('lequ3_2331')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('lequ3_2332')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('lequ3_2333')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('lequ3_3111')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('lequ3_3112')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('lequ3_3113')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('lequ3_3121')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('lequ3_3122')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('lequ3_3123')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('lequ3_3131')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('lequ3_3132')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('lequ3_3133')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('lequ3_3211')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('lequ3_3212')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('lequ3_3213')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('lequ3_3221')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('lequ3_3222')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('lequ3_3223')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('lequ3_3231')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('lequ3_3232')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('lequ3_3233')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('lequ3_3311')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('lequ3_3312')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('lequ3_3313')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('lequ3_3321')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('lequ3_3322')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('lequ3_3323')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('lequ3_3331')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('lequ3_3332')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('lequ3_3333')) * lambda_smeft_value**2,'.6e'), '# clequ3Abs3x3x3x3'], ]} card['Block']['FRBlock8'] = {'values': [ [1, 1, format(angle(scaled_wc('dW_11')),'.6e'), '# cdWPh1x1'], [1, 2, format(angle(scaled_wc('dW_12')),'.6e'), '# cdWPh1x2'], [1, 3, format(angle(scaled_wc('dW_13')),'.6e'), '# cdWPh1x3'], [2, 1, format(angle(scaled_wc('dW_21')),'.6e'), '# cdWPh2x1'], [2, 2, format(angle(scaled_wc('dW_22')),'.6e'), '# cdWPh2x2'], [2, 3, format(angle(scaled_wc('dW_23')),'.6e'), '# cdWPh2x3'], [3, 1, format(angle(scaled_wc('dW_31')),'.6e'), '# cdWPh3x1'], [3, 2, format(angle(scaled_wc('dW_32')),'.6e'), '# cdWPh3x2'], [3, 3, format(angle(scaled_wc('dW_33')),'.6e'), '# cdWPh3x3'], ]} card['Block']['FRBlock9'] = {'values': [ [1, 1, format(angle(scaled_wc('dB_11')),'.6e'), '# cdBPh1x1'], [1, 2, format(angle(scaled_wc('dB_12')),'.6e'), '# cdBPh1x2'], [1, 3, format(angle(scaled_wc('dB_13')),'.6e'), '# cdBPh1x3'], [2, 1, format(angle(scaled_wc('dB_21')),'.6e'), '# cdBPh2x1'], [2, 2, format(angle(scaled_wc('dB_22')),'.6e'), '# cdBPh2x2'], [2, 3, format(angle(scaled_wc('dB_23')),'.6e'), '# cdBPh2x3'], [3, 1, format(angle(scaled_wc('dB_31')),'.6e'), '# cdBPh3x1'], [3, 2, format(angle(scaled_wc('dB_32')),'.6e'), '# cdBPh3x2'], [3, 3, format(angle(scaled_wc('dB_33')),'.6e'), '# cdBPh3x3'], ]} if input_scheme_value == 'mw': card['Block']['FRBlock']['values'].insert(1474,[1475, format(80.387, '.6e'), '# MW0']) elif model_set == 'B': card['Block']['FRBlock'] = {'values': [ [1, format(abs(scaled_wc('phil1_11')* lambda_smeft_value**2), '.6e') , '# cHl1Abs11'], [2, format(abs(scaled_wc('phil1_12')* lambda_smeft_value**2), '.6e') , '# cHl1Abs12'], [3, format(abs(scaled_wc('phil1_13')* lambda_smeft_value**2), '.6e') , '# cHl1Abs13'], [4, format(abs(scaled_wc('phil1_22')* lambda_smeft_value**2), '.6e') , '# cHl1Abs22'], [5, format(abs(scaled_wc('phil1_23')* lambda_smeft_value**2), '.6e') , '# cHl1Abs23'], [6, format(abs(scaled_wc('phil1_33')* lambda_smeft_value**2), '.6e') , '# cHl1Abs33'], [7, format(angle(scaled_wc('phil1_12')), '.6e') , '# cHl1Ph12'], [8, format(angle(scaled_wc('phil1_13')), '.6e') , '# cHl1Ph13'], [9, format(angle(scaled_wc('phil1_23')), '.6e') , '# cHl1Ph23'], [10, format(abs(scaled_wc('phil3_11')* lambda_smeft_value**2), '.6e') ,'# cHL3Abs11'], [11, format(abs(scaled_wc('phil3_12')* lambda_smeft_value**2), '.6e') ,'# cHL3Abs12'], [12, format(abs(scaled_wc('phil3_13')* lambda_smeft_value**2), '.6e') ,'# cHL3Abs13'], [13, format(abs(scaled_wc('phil3_22')* lambda_smeft_value**2), '.6e') ,'# cHL3Abs22'], [14, format(abs(scaled_wc('phil3_23')* lambda_smeft_value**2), '.6e') ,'# cHL3Abs23'], [15, format(abs(scaled_wc('phil3_33')* lambda_smeft_value**2), '.6e') ,'# cHL3Abs33'], [16, format(angle(scaled_wc('phil3_12')), '.6e') ,'# cHL3Ph12'], [17, format(angle(scaled_wc('phil3_13')), '.6e') ,'# cHL3Ph13'], [18, format(angle(scaled_wc('phil3_23')), '.6e') ,'# cHL3Ph23'], [19, format(abs(scaled_wc('phiq1_11')* lambda_smeft_value**2), '.6e') ,'# cHq1Abs11'], [20, format(abs(scaled_wc('phiq1_12')* lambda_smeft_value**2), '.6e') ,'# cHq1Abs12'], [21, format(abs(scaled_wc('phiq1_13')* lambda_smeft_value**2), '.6e') ,'# cHq1Abs13'], [22, format(abs(scaled_wc('phiq1_22')* lambda_smeft_value**2), '.6e') ,'# cHq1Abs22'], [23, format(abs(scaled_wc('phiq1_23')* lambda_smeft_value**2), '.6e') ,'# cHq1Abs23'], [24, format(abs(scaled_wc('phiq1_33')* lambda_smeft_value**2), '.6e') ,'# cHq1Abs33'], [25, format(angle(scaled_wc('phiq1_12')), '.6e') ,'# cHq1Ph12'], [26, format(angle(scaled_wc('phiq1_13')), '.6e') ,'# cHq1Ph13'], [27, format(angle(scaled_wc('phiq1_23')), '.6e') ,'# cHq1Ph23'], [28, format(abs(scaled_wc('phiq3_11')* lambda_smeft_value**2), '.6e') ,'# cHQ3Abs11'], [29, format(abs(scaled_wc('phiq3_12')* lambda_smeft_value**2), '.6e') ,'# cHQ3Abs12'], [30, format(abs(scaled_wc('phiq3_13')* lambda_smeft_value**2), '.6e') ,'# cHQ3Abs13'], [31, format(abs(scaled_wc('phiq3_22')* lambda_smeft_value**2), '.6e') ,'# cHQ3Abs22'], [32, format(abs(scaled_wc('phiq3_23')* lambda_smeft_value**2), '.6e') ,'# cHQ3Abs23'], [33, format(abs(scaled_wc('phiq3_33')* lambda_smeft_value**2), '.6e') ,'# cHQ3Abs33'], [34, format(angle(scaled_wc('phiq3_12')), '.6e') ,'# cHQ3Ph12'], [35, format(angle(scaled_wc('phiq3_13')), '.6e') ,'# cHQ3Ph13'], [36, format(angle(scaled_wc('phiq3_23')), '.6e') ,'# cHQ3Ph23'], [37, format(abs(scaled_wc('phiu_11')* lambda_smeft_value**2), '.6e') ,'# cHuAbs11'], [38, format(abs(scaled_wc('phiu_12')* lambda_smeft_value**2), '.6e') ,'# cHuAbs12'], [39, format(abs(scaled_wc('phiu_13')* lambda_smeft_value**2), '.6e') ,'# cHuAbs13'], [40, format(abs(scaled_wc('phiu_22')* lambda_smeft_value**2), '.6e') ,'# cHuAbs22'], [41, format(abs(scaled_wc('phiu_23')* lambda_smeft_value**2), '.6e') ,'# cHuAbs23'], [42, format(abs(scaled_wc('phiu_33')* lambda_smeft_value**2), '.6e') ,'# cHuAbs33'], [43, format(angle(scaled_wc('phiu_12')), '.6e') ,'# cHuPh12'], [44, format(angle(scaled_wc('phiu_13')), '.6e') ,'# cHuPh13'], [45, format(angle(scaled_wc('phiu_23')), '.6e') ,'# cHuPh23'], [46, format(abs(scaled_wc('phid_11')* lambda_smeft_value**2), '.6e') ,'# cHdAbs11'], [47, format(abs(scaled_wc('phid_12')* lambda_smeft_value**2), '.6e') ,'# cHdAbs12'], [48, format(abs(scaled_wc('phid_13')* lambda_smeft_value**2), '.6e') ,'# cHdAbs13'], [49, format(abs(scaled_wc('phid_22')* lambda_smeft_value**2), '.6e') ,'# cHdAbs22'], [50, format(abs(scaled_wc('phid_23')* lambda_smeft_value**2), '.6e') ,'# cHdAbs23'], [51, format(abs(scaled_wc('phid_33')* lambda_smeft_value**2), '.6e') ,'# cHdAbs33'], [52, format(angle(scaled_wc('phid_12')), '.6e') ,'# cHdPh12'], [53, format(angle(scaled_wc('phid_13')), '.6e') ,'# cHdPh13'], [54, format(angle(scaled_wc('phid_23')), '.6e') ,'# cHdPh23'], [55, format(abs(scaled_wc('phie_11')* lambda_smeft_value**2), '.6e') ,'# cHeAbs11'], [56, format(abs(scaled_wc('phie_12')* lambda_smeft_value**2), '.6e') ,'# cHeAbs12'], [57, format(abs(scaled_wc('phie_13')* lambda_smeft_value**2), '.6e') ,'# cHeAbs13'], [58, format(abs(scaled_wc('phie_22')* lambda_smeft_value**2), '.6e') ,'# cHeAbs22'], [59, format(abs(scaled_wc('phie_23')* lambda_smeft_value**2), '.6e') ,'# cHeAbs23'], [60, format(abs(scaled_wc('phie_33')* lambda_smeft_value**2), '.6e') ,'# cHeAbs33'], [61, format(angle(scaled_wc('phie_12')), '.6e') ,'# cHePh12'], [62, format(angle(scaled_wc('phie_13')), '.6e') ,'# cHePh13'], [63, format(angle(scaled_wc('phie_23')), '.6e') ,'# cHePh23'], [64, format(scaled_wc('ll_1111')* lambda_smeft_value**2, '.6e') ,'# cllAbs1111'], [65, format(scaled_wc('ll_1122')* lambda_smeft_value**2, '.6e') ,'# cllAbs1122'], [66, format(scaled_wc('ll_1221')* lambda_smeft_value**2, '.6e') ,'# cllAbs1221'], [67, format(scaled_wc('ll_1133')* lambda_smeft_value**2, '.6e') ,'# cllAbs1133'], [68, format(scaled_wc('ll_1331')* lambda_smeft_value**2, '.6e') ,'# cllAbs1331'], [69, format(scaled_wc('ll_2222')* lambda_smeft_value**2, '.6e') ,'# cllAbs2222'], [70, format(scaled_wc('ll_2233')* lambda_smeft_value**2, '.6e') ,'# cllAbs2233'], [71, format(scaled_wc('ll_2332')* lambda_smeft_value**2, '.6e') ,'# cllAbs2332'], [72, format(scaled_wc('ll_3333')* lambda_smeft_value**2, '.6e') ,'# cllAbs3333'], [73, format(abs(scaled_wc('ll_1112'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1112'], [74, format(abs(scaled_wc('ll_1113'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1113'], [75, format(abs(scaled_wc('ll_1123'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1123'], [76, format(abs(scaled_wc('ll_1212'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1212'], [77, format(abs(scaled_wc('ll_1213'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1213'], [78, format(abs(scaled_wc('ll_1231'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1231'], [79, format(abs(scaled_wc('ll_1222'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1222'], [80, format(abs(scaled_wc('ll_1223'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1223'], [81, format(abs(scaled_wc('ll_1232'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1232'], [82, format(abs(scaled_wc('ll_1233'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1233'], [83, format(abs(scaled_wc('ll_1313'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1313'], [84, format(abs(scaled_wc('ll_1322'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1322'], [85, format(abs(scaled_wc('ll_1332'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1332'], [86, format(abs(scaled_wc('ll_1323'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1323'], [87, format(abs(scaled_wc('ll_1333'))* lambda_smeft_value**2, '.6e') ,'# cllAbs1333'], [88, format(abs(scaled_wc('ll_2223'))* lambda_smeft_value**2, '.6e') ,'# cllAbs2223'], [89, format(abs(scaled_wc('ll_2323'))* lambda_smeft_value**2, '.6e') ,'# cllAbs2323'], [90, format(abs(scaled_wc('ll_2333'))* lambda_smeft_value**2, '.6e') ,'# cllAbs3323'], [91, format(angle(scaled_wc('ll_1112')), '.6e') ,'# cllPh1112'], [92, format(angle(scaled_wc('ll_1113')), '.6e') ,'# cllPh1113'], [93, format(angle(scaled_wc('ll_1123')), '.6e') ,'# cllPh1123'], [94, format(angle(scaled_wc('ll_1212')), '.6e') ,'# cllPh1212'], [95, format(angle(scaled_wc('ll_1213')), '.6e') ,'# cllPh1213'], [96, format(angle(scaled_wc('ll_1231')), '.6e') ,'# cllPh1231'], [97, format(angle(scaled_wc('ll_1222')), '.6e') ,'# cllPh1222'], [98, format(angle(scaled_wc('ll_1223')), '.6e') ,'# cllPh1223'], [99, format(angle(scaled_wc('ll_1232')), '.6e') ,'# cllPh1232'], [100, format(angle(scaled_wc('ll_1233')), '.6e') ,'# cllPh1233'], [101, format(angle(scaled_wc('ll_1313')), '.6e') ,'# cllPh1313'], [102, format(angle(scaled_wc('ll_1322')), '.6e') ,'# cllPh1322'], [103, format(angle(scaled_wc('ll_1332')), '.6e') ,'# cllPh1332'], [104, format(angle(scaled_wc('ll_1323')), '.6e') ,'# cllPh1323'], [105, format(angle(scaled_wc('ll_1333')), '.6e') ,'# cllPh1333'], [106, format(angle(scaled_wc('ll_2223')), '.6e') ,'# cllPh2223'], [107, format(angle(scaled_wc('ll_2323')), '.6e') ,'# cllPh2323'], [108, format(angle(scaled_wc('ll_2333')), '.6e') ,'# cllPh3323'], [109, format(scaled_wc('qq1_1111')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1111'], [110, format(scaled_wc('qq1_1122')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1122'], [111, format(scaled_wc('qq1_1221')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1221'], [112, format(scaled_wc('qq1_1133')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1133'], [113, format(scaled_wc('qq1_1331')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1331'], [114, format(scaled_wc('qq1_2222')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs2222'], [115, format(scaled_wc('qq1_2233')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs2233'], [116, format(scaled_wc('qq1_2332')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs2332'], [117, format(scaled_wc('qq1_3333')* lambda_smeft_value**2, '.6e') ,'# cqq1Abs3333'], [118, format(abs(scaled_wc('qq1_1112'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1112'], [119, format(abs(scaled_wc('qq1_1113'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1113'], [120, format(abs(scaled_wc('qq1_1123'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1123'], [121, format(abs(scaled_wc('qq1_1212'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1212'], [122, format(abs(scaled_wc('qq1_1213'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1213'], [123, format(abs(scaled_wc('qq1_1231'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1231'], [124, format(abs(scaled_wc('qq1_1222'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1222'], [125, format(abs(scaled_wc('qq1_1223'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1223'], [126, format(abs(scaled_wc('qq1_1232'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1232'], [127, format(abs(scaled_wc('qq1_1233'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1233'], [128, format(abs(scaled_wc('qq1_1313'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1313'], [129, format(abs(scaled_wc('qq1_1322'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1322'], [130, format(abs(scaled_wc('qq1_1332'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1332'], [131, format(abs(scaled_wc('qq1_1323'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1323'], [132, format(abs(scaled_wc('qq1_1333'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs1333'], [133, format(abs(scaled_wc('qq1_2223'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs2223'], [134, format(abs(scaled_wc('qq1_2323'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs2323'], [135, format(abs(scaled_wc('qq1_2333'))* lambda_smeft_value**2, '.6e') ,'# cqq1Abs3323'], [136, format(angle(scaled_wc('qq1_1112')), '.6e') ,'# cqq1Ph1112'], [137, format(angle(scaled_wc('qq1_1113')), '.6e') ,'# cqq1Ph1113'], [138, format(angle(scaled_wc('qq1_1123')), '.6e') ,'# cqq1Ph1123'], [139, format(angle(scaled_wc('qq1_1212')), '.6e') ,'# cqq1Ph1212'], [140, format(angle(scaled_wc('qq1_1213')), '.6e') ,'# cqq1Ph1213'], [141, format(angle(scaled_wc('qq1_1231')), '.6e') ,'# cqq1Ph1231'], [142, format(angle(scaled_wc('qq1_1222')), '.6e') ,'# cqq1Ph1222'], [143, format(angle(scaled_wc('qq1_1223')), '.6e') ,'# cqq1Ph1223'], [144, format(angle(scaled_wc('qq1_1232')), '.6e') ,'# cqq1Ph1232'], [145, format(angle(scaled_wc('qq1_1233')), '.6e') ,'# cqq1Ph1233'], [146, format(angle(scaled_wc('qq1_1313')), '.6e') ,'# cqq1Ph1313'], [147, format(angle(scaled_wc('qq1_1322')), '.6e') ,'# cqq1Ph1322'], [148, format(angle(scaled_wc('qq1_1332')), '.6e') ,'# cqq1Ph1332'], [149, format(angle(scaled_wc('qq1_1323')), '.6e') ,'# cqq1Ph1323'], [150, format(angle(scaled_wc('qq1_1333')), '.6e') ,'# cqq1Ph1333'], [151, format(angle(scaled_wc('qq1_2223')), '.6e') ,'# cqq1Ph2223'], [152, format(angle(scaled_wc('qq1_2323')), '.6e') ,'# cqq1Ph2323'], [153, format(angle(scaled_wc('qq1_2333')), '.6e') ,'# cqq1Ph3323'], [154, format(scaled_wc('qq3_1111')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1111'], [155, format(scaled_wc('qq3_1122')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1122'], [156, format(scaled_wc('qq3_1221')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1221'], [157, format(scaled_wc('qq3_1133')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1133'], [158, format(scaled_wc('qq3_1331')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1331'], [159, format(scaled_wc('qq3_2222')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs2222'], [160, format(scaled_wc('qq3_2233')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs2233'], [161, format(scaled_wc('qq3_2332')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs2332'], [162, format(scaled_wc('qq3_3333')* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs3333'], [163, format(abs(scaled_wc('qq3_1112'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1112'], [164, format(abs(scaled_wc('qq3_1113'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1113'], [165, format(abs(scaled_wc('qq3_1123'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1123'], [166, format(abs(scaled_wc('qq3_1212'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1212'], [167, format(abs(scaled_wc('qq3_1213'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1213'], [168, format(abs(scaled_wc('qq3_1231'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1231'], [169, format(abs(scaled_wc('qq3_1222'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1222'], [170, format(abs(scaled_wc('qq3_1223'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1223'], [171, format(abs(scaled_wc('qq3_1232'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1232'], [172, format(abs(scaled_wc('qq3_1233'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1233'], [173, format(abs(scaled_wc('qq3_1313'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1313'], [174, format(abs(scaled_wc('qq3_1322'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1322'], [175, format(abs(scaled_wc('qq3_1332'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1332'], [176, format(abs(scaled_wc('qq3_1323'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1323'], [177, format(abs(scaled_wc('qq3_1333'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs1333'], [178, format(abs(scaled_wc('qq3_2223'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs2223'], [179, format(abs(scaled_wc('qq3_2323'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs2323'], [180, format(abs(scaled_wc('qq3_2333'))* lambda_smeft_value**2, '.6e') ,'# cQQ3Abs3323'], [181, format(angle(scaled_wc('qq3_1112')), '.6e') ,'# cQQ3Ph1112'], [182, format(angle(scaled_wc('qq3_1113')), '.6e') ,'# cQQ3Ph1113'], [183, format(angle(scaled_wc('qq3_1123')), '.6e') ,'# cQQ3Ph1123'], [184, format(angle(scaled_wc('qq3_1212')), '.6e') ,'# cQQ3Ph1212'], [185, format(angle(scaled_wc('qq3_1213')), '.6e') ,'# cQQ3Ph1213'], [186, format(angle(scaled_wc('qq3_1231')), '.6e') ,'# cQQ3Ph1231'], [187, format(angle(scaled_wc('qq3_1222')), '.6e') ,'# cQQ3Ph1222'], [188, format(angle(scaled_wc('qq3_1223')), '.6e') ,'# cQQ3Ph1223'], [189, format(angle(scaled_wc('qq3_1232')), '.6e') ,'# cQQ3Ph1232'], [190, format(angle(scaled_wc('qq3_1233')), '.6e') ,'# cQQ3Ph1233'], [191, format(angle(scaled_wc('qq3_1313')), '.6e') ,'# cQQ3Ph1313'], [192, format(angle(scaled_wc('qq3_1322')), '.6e') ,'# cQQ3Ph1322'], [193, format(angle(scaled_wc('qq3_1332')), '.6e') ,'# cQQ3Ph1332'], [194, format(angle(scaled_wc('qq3_1323')), '.6e') ,'# cQQ3Ph1323'], [195, format(angle(scaled_wc('qq3_1333')), '.6e') ,'# cQQ3Ph1333'], [196, format(angle(scaled_wc('qq3_2223')), '.6e') ,'# cQQ3Ph2223'], [197, format(angle(scaled_wc('qq3_2323')), '.6e') ,'# cQQ3Ph2323'], [198, format(angle(scaled_wc('qq3_2333')), '.6e') ,'# cQQ3Ph3323'], [199, format(scaled_wc('lq1_1111')* lambda_smeft_value**2, '.6e') ,'# clq1Abs1111'], [200, format(abs(scaled_wc('lq1_1112'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1112'], [201, format(abs(scaled_wc('lq1_1113'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1113'], [202, format(abs(scaled_wc('lq1_1123'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1123'], [203, format(scaled_wc('lq1_1122')* lambda_smeft_value**2, '.6e') ,'# clq1Abs1122'], [204, format(scaled_wc('lq1_1133')* lambda_smeft_value**2, '.6e') ,'# clq1Abs1133'], [205, format(abs(scaled_wc('lq1_1211'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1211'], [206, format(abs(scaled_wc('lq1_1212'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1212'], [207, format(abs(scaled_wc('lq1_1221'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1221'], [208, format(abs(scaled_wc('lq1_1213'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1213'], [209, format(abs(scaled_wc('lq1_1231'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1231'], [210, format(abs(scaled_wc('lq1_1222'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1222'], [211, format(abs(scaled_wc('lq1_1223'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1223'], [212, format(abs(scaled_wc('lq1_1232'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1232'], [213, format(abs(scaled_wc('lq1_1233'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1233'], [214, format(abs(scaled_wc('lq1_1311'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1311'], [215, format(abs(scaled_wc('lq1_1312'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1312'], [216, format(abs(scaled_wc('lq1_1313'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1313'], [217, format(abs(scaled_wc('lq1_1331'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1331'], [218, format(abs(scaled_wc('lq1_1321'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1321'], [219, format(abs(scaled_wc('lq1_1322'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1322'], [220, format(abs(scaled_wc('lq1_1332'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1332'], [221, format(abs(scaled_wc('lq1_1323'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1323'], [222, format(abs(scaled_wc('lq1_1333'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs1333'], [223, format(scaled_wc('lq1_2211')* lambda_smeft_value**2, '.6e') ,'# clq1Abs2211'], [224, format(abs(scaled_wc('lq1_2212'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2212'], [225, format(abs(scaled_wc('lq1_2213'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2213'], [226, format(scaled_wc('lq1_2222')* lambda_smeft_value**2, '.6e') ,'# clq1Abs2222'], [227, format(abs(scaled_wc('lq1_2223'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2223'], [228, format(scaled_wc('lq1_2233')* lambda_smeft_value**2, '.6e') ,'# clq1Abs2233'], [229, format(abs(scaled_wc('lq1_2311'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2311'], [230, format(abs(scaled_wc('lq1_2312'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2312'], [231, format(abs(scaled_wc('lq1_2313'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2313'], [232, format(abs(scaled_wc('lq1_2321'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2321'], [233, format(abs(scaled_wc('lq1_2322'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2322'], [234, format(abs(scaled_wc('lq1_2323'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2323'], [235, format(abs(scaled_wc('lq1_2331'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2331'], [236, format(abs(scaled_wc('lq1_2332'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2332'], [237, format(abs(scaled_wc('lq1_2333'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs2333'], [238, format(scaled_wc('lq1_3311')* lambda_smeft_value**2, '.6e') ,'# clq1Abs3311'], [239, format(abs(scaled_wc('lq1_3312'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs3312'], [240, format(abs(scaled_wc('lq1_3313'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs3313'], [241, format(scaled_wc('lq1_3322')* lambda_smeft_value**2, '.6e') ,'# clq1Abs3322'], [242, format(scaled_wc('lq1_3333')* lambda_smeft_value**2, '.6e') ,'# clq1Abs3333'], [243, format(abs(scaled_wc('lq1_3323'))* lambda_smeft_value**2, '.6e') ,'# clq1Abs3323'], [244, format(angle(scaled_wc('lq1_1112')), '.6e') ,'# clq1Ph1112'], [245, format(angle(scaled_wc('lq1_2212')), '.6e') ,'# clq1Ph2212'], [246, format(angle(scaled_wc('lq1_1113')), '.6e') ,'# clq1Ph1113'], [247, format(angle(scaled_wc('lq1_1123')), '.6e') ,'# clq1Ph1123'], [248, format(angle(scaled_wc('lq1_1211')), '.6e') ,'# clq1Ph1211'], [249, format(angle(scaled_wc('lq1_1212')), '.6e') ,'# clq1Ph1212'], [250, format(angle(scaled_wc('lq1_1221')), '.6e') ,'# clq1Ph1221'], [251, format(angle(scaled_wc('lq1_1213')), '.6e') ,'# clq1Ph1213'], [252, format(angle(scaled_wc('lq1_1231')), '.6e') ,'# clq1Ph1231'], [253, format(angle(scaled_wc('lq1_1222')), '.6e') ,'# clq1Ph1222'], [254, format(angle(scaled_wc('lq1_1223')), '.6e') ,'# clq1Ph1223'], [255, format(angle(scaled_wc('lq1_1232')), '.6e') ,'# clq1Ph1232'], [256, format(angle(scaled_wc('lq1_1233')), '.6e') ,'# clq1Ph1233'], [257, format(angle(scaled_wc('lq1_1311')), '.6e') ,'# clq1Ph1311'], [258, format(angle(scaled_wc('lq1_1312')), '.6e') ,'# clq1Ph1312'], [259, format(angle(scaled_wc('lq1_1313')), '.6e') ,'# clq1Ph1313'], [260, format(angle(scaled_wc('lq1_1331')), '.6e') ,'# clq1Ph1331'], [261, format(angle(scaled_wc('lq1_1321')), '.6e') ,'# clq1Ph1321'], [262, format(angle(scaled_wc('lq1_1322')), '.6e') ,'# clq1Ph1322'], [263, format(angle(scaled_wc('lq1_1332')), '.6e') ,'# clq1Ph1332'], [264, format(angle(scaled_wc('lq1_1323')), '.6e') ,'# clq1Ph1323'], [265, format(angle(scaled_wc('lq1_1333')), '.6e') ,'# clq1Ph1333'], [266, format(angle(scaled_wc('lq1_2213')), '.6e') ,'# clq1Ph2213'], [267, format(angle(scaled_wc('lq1_2223')), '.6e') ,'# clq1Ph2223'], [268, format(angle(scaled_wc('lq1_2311')), '.6e') ,'# clq1Ph2311'], [269, format(angle(scaled_wc('lq1_2312')), '.6e') ,'# clq1Ph2312'], [270, format(angle(scaled_wc('lq1_2313')), '.6e') ,'# clq1Ph2313'], [271, format(angle(scaled_wc('lq1_2321')), '.6e') ,'# clq1Ph2321'], [272, format(angle(scaled_wc('lq1_2322')), '.6e') ,'# clq1Ph2322'], [273, format(angle(scaled_wc('lq1_2323')), '.6e') ,'# clq1Ph2323'], [274, format(angle(scaled_wc('lq1_2331')), '.6e') ,'# clq1Ph2331'], [275, format(angle(scaled_wc('lq1_2332')), '.6e') ,'# clq1Ph2332'], [276, format(angle(scaled_wc('lq1_2333')), '.6e') ,'# clq1Ph2333'], [277, format(angle(scaled_wc('lq1_3323')), '.6e') ,'# clq1Ph3323'], [278, format(angle(scaled_wc('lq1_3312')), '.6e') ,'# clq1Ph3312'], [279, format(angle(scaled_wc('lq1_3313')), '.6e') ,'# clq1Ph3313'], [280, format(scaled_wc('lq3_1111')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1111'], [281, format(abs(scaled_wc('lq3_1112'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1112'], [282, format(abs(scaled_wc('lq3_1113'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1113'], [283, format(abs(scaled_wc('lq3_1123'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1123'], [284, format(scaled_wc('lq3_1122')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1122'], [285, format(scaled_wc('lq3_1133')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1133'], [286, format(abs(scaled_wc('lq3_1211'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1211'], [287, format(abs(scaled_wc('lq3_1212'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1212'], [288, format(abs(scaled_wc('lq3_1221'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1221'], [289, format(abs(scaled_wc('lq3_1213'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1213'], [290, format(abs(scaled_wc('lq3_1231'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1231'], [291, format(abs(scaled_wc('lq3_1222'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1222'], [292, format(abs(scaled_wc('lq3_1223'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1223'], [293, format(abs(scaled_wc('lq3_1232'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1232'], [294, format(abs(scaled_wc('lq3_1233'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1233'], [295, format(abs(scaled_wc('lq3_1311'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1311'], [296, format(abs(scaled_wc('lq3_1312'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1312'], [297, format(abs(scaled_wc('lq3_1313'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1313'], [298, format(abs(scaled_wc('lq3_1331'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1331'], [299, format(abs(scaled_wc('lq3_1321'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1321'], [300, format(abs(scaled_wc('lq3_1322'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1322'], [301, format(abs(scaled_wc('lq3_1332'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1332'], [302, format(abs(scaled_wc('lq3_1323'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1323'], [303, format(abs(scaled_wc('lq3_1333'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs1333'], [304, format(scaled_wc('lq3_2211')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2211'], [305, format(abs(scaled_wc('lq3_2212'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2212'], [306, format(abs(scaled_wc('lq3_2213'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2213'], [307, format(scaled_wc('lq3_2222')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2222'], [308, format(abs(scaled_wc('lq3_2223'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2223'], [309, format(scaled_wc('lq3_2233')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2233'], [310, format(abs(scaled_wc('lq3_2311'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2311'], [311, format(abs(scaled_wc('lq3_2312'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2312'], [312, format(abs(scaled_wc('lq3_2313'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2313'], [313, format(abs(scaled_wc('lq3_2321'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2321'], [314, format(abs(scaled_wc('lq3_2322'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2322'], [315, format(abs(scaled_wc('lq3_2323'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2323'], [316, format(abs(scaled_wc('lq3_2331'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2331'], [317, format(abs(scaled_wc('lq3_2332'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2332'], [318, format(abs(scaled_wc('lq3_2333'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs2333'], [319, format(scaled_wc('lq3_3311')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs3311'], [320, format(abs(scaled_wc('lq3_3312'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs3312'], [321, format(abs(scaled_wc('lq3_3313'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs3313'], [322, format(scaled_wc('lq3_3322')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs3322'], [323, format(scaled_wc('lq3_3333')* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs3333'], [324, format(abs(scaled_wc('lq3_3323'))* lambda_smeft_value**2, '.6e') ,'# cLQ3Abs3323'], [325, format(angle(scaled_wc('lq3_1112')), '.6e') ,'# cLQ3Ph1112'], [326, format(angle(scaled_wc('lq3_2212')), '.6e') ,'# cLQ3Ph2212'], [327, format(angle(scaled_wc('lq3_1113')), '.6e') ,'# cLQ3Ph1113'], [328, format(angle(scaled_wc('lq3_1123')), '.6e') ,'# cLQ3Ph1123'], [329, format(angle(scaled_wc('lq3_1211')), '.6e') ,'# cLQ3Ph1211'], [330, format(angle(scaled_wc('lq3_1212')), '.6e') ,'# cLQ3Ph1212'], [331, format(angle(scaled_wc('lq3_1221')), '.6e') ,'# cLQ3Ph1221'], [332, format(angle(scaled_wc('lq3_1213')), '.6e') ,'# cLQ3Ph1213'], [333, format(angle(scaled_wc('lq3_1231')), '.6e') ,'# cLQ3Ph1231'], [334, format(angle(scaled_wc('lq3_1222')), '.6e') ,'# cLQ3Ph1222'], [335, format(angle(scaled_wc('lq3_1223')), '.6e') ,'# cLQ3Ph1223'], [336, format(angle(scaled_wc('lq3_1232')), '.6e') ,'# cLQ3Ph1232'], [337, format(angle(scaled_wc('lq3_1233')), '.6e') ,'# cLQ3Ph1233'], [338, format(angle(scaled_wc('lq3_1311')), '.6e') ,'# cLQ3Ph1311'], [339, format(angle(scaled_wc('lq3_1312')), '.6e') ,'# cLQ3Ph1312'], [340, format(angle(scaled_wc('lq3_1313')), '.6e') ,'# cLQ3Ph1313'], [341, format(angle(scaled_wc('lq3_1331')), '.6e') ,'# cLQ3Ph1331'], [342, format(angle(scaled_wc('lq3_1321')), '.6e') ,'# cLQ3Ph1321'], [343, format(angle(scaled_wc('lq3_1322')), '.6e') ,'# cLQ3Ph1322'], [344, format(angle(scaled_wc('lq3_1332')), '.6e') ,'# cLQ3Ph1332'], [345, format(angle(scaled_wc('lq3_1323')), '.6e') ,'# cLQ3Ph1323'], [346, format(angle(scaled_wc('lq3_1333')), '.6e') ,'# cLQ3Ph1333'], [347, format(angle(scaled_wc('lq3_2213')), '.6e') ,'# cLQ3Ph2213'], [348, format(angle(scaled_wc('lq3_2223')), '.6e') ,'# cLQ3Ph2223'], [349, format(angle(scaled_wc('lq3_2311')), '.6e') ,'# cLQ3Ph2311'], [350, format(angle(scaled_wc('lq3_2312')), '.6e') ,'# cLQ3Ph2312'], [351, format(angle(scaled_wc('lq3_2313')), '.6e') ,'# cLQ3Ph2313'], [352, format(angle(scaled_wc('lq3_2321')), '.6e') ,'# cLQ3Ph2321'], [353, format(angle(scaled_wc('lq3_2322')), '.6e') ,'# cLQ3Ph2322'], [354, format(angle(scaled_wc('lq3_2323')), '.6e') ,'# cLQ3Ph2323'], [355, format(angle(scaled_wc('lq3_2331')), '.6e') ,'# cLQ3Ph2331'], [356, format(angle(scaled_wc('lq3_2332')), '.6e') ,'# cLQ3Ph2332'], [357, format(angle(scaled_wc('lq3_2333')), '.6e') ,'# cLQ3Ph2333'], [358, format(angle(scaled_wc('lq3_3323')), '.6e') ,'# cLQ3Ph3323'], [359, format(angle(scaled_wc('lq3_3312')), '.6e') ,'# cLQ3Ph3312'], [360, format(angle(scaled_wc('lq3_3313')), '.6e') ,'# cLQ3Ph3313'], [361, format(scaled_wc('uu_1111')* lambda_smeft_value**2, '.6e') ,'# cuuAbs1111'], [362, format(scaled_wc('uu_1122')* lambda_smeft_value**2, '.6e') ,'# cuuAbs1122'], [363, format(scaled_wc('uu_1221')* lambda_smeft_value**2, '.6e') ,'# cuuAbs1221'], [364, format(scaled_wc('uu_1133')* lambda_smeft_value**2, '.6e') ,'# cuuAbs1133'], [365, format(scaled_wc('uu_1331')* lambda_smeft_value**2, '.6e') ,'# cuuAbs1331'], [366, format(scaled_wc('uu_2222')* lambda_smeft_value**2, '.6e') ,'# cuuAbs2222'], [367, format(scaled_wc('uu_2233')* lambda_smeft_value**2, '.6e') ,'# cuuAbs2233'], [368, format(scaled_wc('uu_2332')* lambda_smeft_value**2, '.6e') ,'# cuuAbs2332'], [369, format(scaled_wc('uu_3333')* lambda_smeft_value**2, '.6e') ,'# cuuAbs3333'], [370, format(abs(scaled_wc('uu_1112'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1112'], [371, format(abs(scaled_wc('uu_1113'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1113'], [372, format(abs(scaled_wc('uu_1123'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1123'], [373, format(abs(scaled_wc('uu_1212'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1212'], [374, format(abs(scaled_wc('uu_1213'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1213'], [375, format(abs(scaled_wc('uu_1231'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1231'], [376, format(abs(scaled_wc('uu_1222'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1222'], [377, format(abs(scaled_wc('uu_1223'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1223'], [378, format(abs(scaled_wc('uu_1232'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1232'], [379, format(abs(scaled_wc('uu_1233'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1233'], [380, format(abs(scaled_wc('uu_1313'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1313'], [381, format(abs(scaled_wc('uu_1322'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1322'], [382, format(abs(scaled_wc('uu_1332'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1332'], [383, format(abs(scaled_wc('uu_1323'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1323'], [384, format(abs(scaled_wc('uu_1333'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs1333'], [385, format(abs(scaled_wc('uu_2223'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs2223'], [386, format(abs(scaled_wc('uu_2323'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs2323'], [387, format(abs(scaled_wc('uu_2333'))* lambda_smeft_value**2, '.6e') ,'# cuuAbs3323'], [388, format(angle(scaled_wc('uu_1112')), '.6e') ,'# cuuPh1112'], [389, format(angle(scaled_wc('uu_1113')), '.6e') ,'# cuuPh1113'], [390, format(angle(scaled_wc('uu_1123')), '.6e') ,'# cuuPh1123'], [391, format(angle(scaled_wc('uu_1212')), '.6e') ,'# cuuPh1212'], [392, format(angle(scaled_wc('uu_1213')), '.6e') ,'# cuuPh1213'], [393, format(angle(scaled_wc('uu_1231')), '.6e') ,'# cuuPh1231'], [394, format(angle(scaled_wc('uu_1222')), '.6e') ,'# cuuPh1222'], [395, format(angle(scaled_wc('uu_1223')), '.6e') ,'# cuuPh1223'], [396, format(angle(scaled_wc('uu_1232')), '.6e') ,'# cuuPh1232'], [397, format(angle(scaled_wc('uu_1233')), '.6e') ,'# cuuPh1233'], [398, format(angle(scaled_wc('uu_1313')), '.6e') ,'# cuuPh1313'], [399, format(angle(scaled_wc('uu_1322')), '.6e') ,'# cuuPh1322'], [400, format(angle(scaled_wc('uu_1332')), '.6e') ,'# cuuPh1332'], [401, format(angle(scaled_wc('uu_1323')), '.6e') ,'# cuuPh1323'], [402, format(angle(scaled_wc('uu_1333')), '.6e') ,'# cuuPh1333'], [403, format(angle(scaled_wc('uu_2223')), '.6e') ,'# cuuPh2223'], [404, format(angle(scaled_wc('uu_2323')), '.6e') ,'# cuuPh2323'], [405, format(angle(scaled_wc('uu_2333')), '.6e') ,'# cuuPh3323'], [406, format(scaled_wc('dd_1111')* lambda_smeft_value**2, '.6e') ,'# cddAbs1111'], [407, format(scaled_wc('dd_1122')* lambda_smeft_value**2, '.6e') ,'# cddAbs1122'], [408, format(scaled_wc('dd_1221')* lambda_smeft_value**2, '.6e') ,'# cddAbs1221'], [409, format(scaled_wc('dd_1133')* lambda_smeft_value**2, '.6e') ,'# cddAbs1133'], [410, format(scaled_wc('dd_1331')* lambda_smeft_value**2, '.6e') ,'# cddAbs1331'], [411, format(scaled_wc('dd_2222')* lambda_smeft_value**2, '.6e') ,'# cddAbs2222'], [412, format(scaled_wc('dd_2233')* lambda_smeft_value**2, '.6e') ,'# cddAbs2233'], [413, format(scaled_wc('dd_2332')* lambda_smeft_value**2, '.6e') ,'# cddAbs2332'], [414, format(scaled_wc('dd_3333')* lambda_smeft_value**2, '.6e') ,'# cddAbs3333'], [415, format(abs(scaled_wc('dd_1112'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1112'], [416, format(abs(scaled_wc('dd_1113'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1113'], [417, format(abs(scaled_wc('dd_1123'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1123'], [418, format(abs(scaled_wc('dd_1212'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1212'], [419, format(abs(scaled_wc('dd_1213'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1213'], [420, format(abs(scaled_wc('dd_1231'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1231'], [421, format(abs(scaled_wc('dd_1222'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1222'], [422, format(abs(scaled_wc('dd_1223'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1223'], [423, format(abs(scaled_wc('dd_1232'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1232'], [424, format(abs(scaled_wc('dd_1233'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1233'], [425, format(abs(scaled_wc('dd_1313'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1313'], [426, format(abs(scaled_wc('dd_1322'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1322'], [427, format(abs(scaled_wc('dd_1332'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1332'], [428, format(abs(scaled_wc('dd_1323'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1323'], [429, format(abs(scaled_wc('dd_1333'))* lambda_smeft_value**2, '.6e') ,'# cddAbs1333'], [430, format(abs(scaled_wc('dd_2223'))* lambda_smeft_value**2, '.6e') ,'# cddAbs2223'], [431, format(abs(scaled_wc('dd_2323'))* lambda_smeft_value**2, '.6e') ,'# cddAbs2323'], [432, format(abs(scaled_wc('dd_2333'))* lambda_smeft_value**2, '.6e') ,'# cddAbs3323'], [433, format(angle(scaled_wc('dd_1112')), '.6e') ,'# cddPh1112'], [434, format(angle(scaled_wc('dd_1113')), '.6e') ,'# cddPh1113'], [435, format(angle(scaled_wc('dd_1123')), '.6e') ,'# cddPh1123'], [436, format(angle(scaled_wc('dd_1212')), '.6e') ,'# cddPh1212'], [437, format(angle(scaled_wc('dd_1213')), '.6e') ,'# cddPh1213'], [438, format(angle(scaled_wc('dd_1231')), '.6e') ,'# cddPh1231'], [439, format(angle(scaled_wc('dd_1222')), '.6e') ,'# cddPh1222'], [440, format(angle(scaled_wc('dd_1223')), '.6e') ,'# cddPh1223'], [441, format(angle(scaled_wc('dd_1232')), '.6e') ,'# cddPh1232'], [442, format(angle(scaled_wc('dd_1233')), '.6e') ,'# cddPh1233'], [443, format(angle(scaled_wc('dd_1313')), '.6e') ,'# cddPh1313'], [444, format(angle(scaled_wc('dd_1322')), '.6e') ,'# cddPh1322'], [445, format(angle(scaled_wc('dd_1332')), '.6e') ,'# cddPh1332'], [446, format(angle(scaled_wc('dd_1323')), '.6e') ,'# cddPh1323'], [447, format(angle(scaled_wc('dd_1333')), '.6e') ,'# cddPh1333'], [448, format(angle(scaled_wc('dd_2223')), '.6e') ,'# cddPh2223'], [449, format(angle(scaled_wc('dd_2323')), '.6e') ,'# cddPh2323'], [450, format(angle(scaled_wc('dd_2333')), '.6e') ,'# cddPh3323'], [451, format(scaled_wc('ee_1111')* lambda_smeft_value**2, '.6e') ,'# ceeAbs1111'], [452, format(scaled_wc('ee_2222')* lambda_smeft_value**2, '.6e') ,'# ceeAbs2222'], [453, format(scaled_wc('ee_3333')* lambda_smeft_value**2, '.6e') ,'# ceeAbs3333'], [454, format(scaled_wc('ee_1122')* lambda_smeft_value**2, '.6e') ,'# ceeAbs1122'], [455, format(scaled_wc('ee_1133')* lambda_smeft_value**2, '.6e') ,'# ceeAbs1133'], [456, format(scaled_wc('ee_2233')* lambda_smeft_value**2, '.6e') ,'# ceeAbs2233'], [457, format(abs(scaled_wc('ee_1212'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1212'], [458, format(abs(scaled_wc('ee_1213'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1213'], [459, format(abs(scaled_wc('ee_1232'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1232'], [460, format(abs(scaled_wc('ee_1313'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1313'], [461, format(abs(scaled_wc('ee_1323'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1323'], [462, format(abs(scaled_wc('ee_2323'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs2323'], [463, format(abs(scaled_wc('ee_1112'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1112'], [464, format(abs(scaled_wc('ee_1222'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1222'], [465, format(abs(scaled_wc('ee_1233'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1233'], [466, format(abs(scaled_wc('ee_1113'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1113'], [467, format(abs(scaled_wc('ee_1223'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1322'], # element 1322 replaced with 1223 in wcxf [468, format(abs(scaled_wc('ee_1333'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1333'], [469, format(abs(scaled_wc('ee_1123'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs1123'], [470, format(abs(scaled_wc('ee_2223'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs2223'], [471, format(abs(scaled_wc('ee_2333'))* lambda_smeft_value**2, '.6e') ,'# ceeAbs3323'], [472, format(angle(scaled_wc('ee_1112')), '.6e') ,'# ceePh1112'], [473, format(angle(scaled_wc('ee_1113')), '.6e') ,'# ceePh1113'], [474, format(angle(scaled_wc('ee_1123')), '.6e') ,'# ceePh1123'], [475, format(angle(scaled_wc('ee_1212')), '.6e') ,'# ceePh1212'], [476, format(angle(scaled_wc('ee_1213')), '.6e') ,'# ceePh1213'], [477, format(angle(scaled_wc('ee_1323')), '.6e') ,'# ceePh1323'], [478, format(angle(scaled_wc('ee_1222')), '.6e') ,'# ceePh1222'], [479, format(angle(scaled_wc('ee_2333')), '.6e') ,'# ceePh3323'], [480, format(angle(scaled_wc('ee_1232')), '.6e') ,'# ceePh1232'], [481, format(angle(scaled_wc('ee_1233')), '.6e') ,'# ceePh1233'], [482, format(angle(scaled_wc('ee_1313')), '.6e') ,'# ceePh1313'], [483, format(angle(scaled_wc('ee_1223')), '.6e') ,'# ceePh1322'], # element 1322 replaced with 1223 in wcxf [484, format(angle(scaled_wc('ee_1333')), '.6e') ,'# ceePh1333'], [485, format(angle(scaled_wc('ee_2223')), '.6e') ,'# ceePh2223'], [486, format(angle(scaled_wc('ee_2323')), '.6e') ,'# ceePh2323'], [487, format(scaled_wc('ud1_1111')* lambda_smeft_value**2, '.6e') ,'# cud1Abs1111'], [488, format(abs(scaled_wc('ud1_1112'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1112'], [489, format(abs(scaled_wc('ud1_1113'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1113'], [490, format(abs(scaled_wc('ud1_1123'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1123'], [491, format(scaled_wc('ud1_1122')* lambda_smeft_value**2, '.6e') ,'# cud1Abs1122'], [492, format(scaled_wc('ud1_1133')* lambda_smeft_value**2, '.6e') ,'# cud1Abs1133'], [493, format(abs(scaled_wc('ud1_1211'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1211'], [494, format(abs(scaled_wc('ud1_1212'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1212'], [495, format(abs(scaled_wc('ud1_1221'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1221'], [496, format(abs(scaled_wc('ud1_1213'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1213'], [497, format(abs(scaled_wc('ud1_1231'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1231'], [498, format(abs(scaled_wc('ud1_1222'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1222'], [499, format(abs(scaled_wc('ud1_1223'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1223'], [500, format(abs(scaled_wc('ud1_1232'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1232'], [501, format(abs(scaled_wc('ud1_1233'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1233'], [502, format(abs(scaled_wc('ud1_1311'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1311'], [503, format(abs(scaled_wc('ud1_1312'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1312'], [504, format(abs(scaled_wc('ud1_1313'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1313'], [505, format(abs(scaled_wc('ud1_1331'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1331'], [506, format(abs(scaled_wc('ud1_1321'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1321'], [507, format(abs(scaled_wc('ud1_1322'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1322'], [508, format(abs(scaled_wc('ud1_1332'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1332'], [509, format(abs(scaled_wc('ud1_1323'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1323'], [510, format(abs(scaled_wc('ud1_1333'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs1333'], [511, format(scaled_wc('ud1_2211')* lambda_smeft_value**2, '.6e') ,'# cud1Abs2211'], [512, format(abs(scaled_wc('ud1_2212'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2212'], [513, format(abs(scaled_wc('ud1_2213'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2213'], [514, format(scaled_wc('ud1_2222')* lambda_smeft_value**2, '.6e') ,'# cud1Abs2222'], [515, format(abs(scaled_wc('ud1_2223'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2223'], [516, format(scaled_wc('ud1_2233')* lambda_smeft_value**2, '.6e') ,'# cud1Abs2233'], [517, format(abs(scaled_wc('ud1_2311'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2311'], [518, format(abs(scaled_wc('ud1_2312'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2312'], [519, format(abs(scaled_wc('ud1_2313'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2313'], [520, format(abs(scaled_wc('ud1_2321'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2321'], [521, format(abs(scaled_wc('ud1_2322'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2322'], [522, format(abs(scaled_wc('ud1_2323'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2323'], [523, format(abs(scaled_wc('ud1_2331'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2331'], [524, format(abs(scaled_wc('ud1_2332'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2332'], [525, format(abs(scaled_wc('ud1_2333'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs2333'], [526, format(scaled_wc('ud1_3311')* lambda_smeft_value**2, '.6e') ,'# cud1Abs3311'], [527, format(abs(scaled_wc('ud1_3312'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs3312'], [528, format(abs(scaled_wc('ud1_3313'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs3313'], [529, format(scaled_wc('ud1_3322')* lambda_smeft_value**2, '.6e') ,'# cud1Abs3322'], [530, format(scaled_wc('ud1_3333')* lambda_smeft_value**2, '.6e') ,'# cud1Abs3333'], [531, format(abs(scaled_wc('ud1_3323'))* lambda_smeft_value**2, '.6e') ,'# cud1Abs3323'], [532, format(angle(scaled_wc('ud1_1112')), '.6e') ,'# cud1Ph1112'], [533, format(angle(scaled_wc('ud1_2212')), '.6e') ,'# cud1Ph2212'], [534, format(angle(scaled_wc('ud1_1113')), '.6e') ,'# cud1Ph1113'], [535, format(angle(scaled_wc('ud1_1123')), '.6e') ,'# cud1Ph1123'], [536, format(angle(scaled_wc('ud1_1211')), '.6e') ,'# cud1Ph1211'], [537, format(angle(scaled_wc('ud1_1212')), '.6e') ,'# cud1Ph1212'], [538, format(angle(scaled_wc('ud1_1221')), '.6e') ,'# cud1Ph1221'], [539, format(angle(scaled_wc('ud1_1213')), '.6e') ,'# cud1Ph1213'], [540, format(angle(scaled_wc('ud1_1231')), '.6e') ,'# cud1Ph1231'], [541, format(angle(scaled_wc('ud1_1222')), '.6e') ,'# cud1Ph1222'], [542, format(angle(scaled_wc('ud1_1223')), '.6e') ,'# cud1Ph1223'], [543, format(angle(scaled_wc('ud1_1232')), '.6e') ,'# cud1Ph1232'], [544, format(angle(scaled_wc('ud1_1233')), '.6e') ,'# cud1Ph1233'], [545, format(angle(scaled_wc('ud1_1311')), '.6e') ,'# cud1Ph1311'], [546, format(angle(scaled_wc('ud1_1312')), '.6e') ,'# cud1Ph1312'], [547, format(angle(scaled_wc('ud1_1313')), '.6e') ,'# cud1Ph1313'], [548, format(angle(scaled_wc('ud1_1331')), '.6e') ,'# cud1Ph1331'], [549, format(angle(scaled_wc('ud1_1321')), '.6e') ,'# cud1Ph1321'], [550, format(angle(scaled_wc('ud1_1322')), '.6e') ,'# cud1Ph1322'], [551, format(angle(scaled_wc('ud1_1332')), '.6e') ,'# cud1Ph1332'], [552, format(angle(scaled_wc('ud1_1323')), '.6e') ,'# cud1Ph1323'], [553, format(angle(scaled_wc('ud1_1333')), '.6e') ,'# cud1Ph1333'], [554, format(angle(scaled_wc('ud1_2213')), '.6e') ,'# cud1Ph2213'], [555, format(angle(scaled_wc('ud1_2223')), '.6e') ,'# cud1Ph2223'], [556, format(angle(scaled_wc('ud1_2311')), '.6e') ,'# cud1Ph2311'], [557, format(angle(scaled_wc('ud1_2312')), '.6e') ,'# cud1Ph2312'], [558, format(angle(scaled_wc('ud1_2313')), '.6e') ,'# cud1Ph2313'], [559, format(angle(scaled_wc('ud1_2321')), '.6e') ,'# cud1Ph2321'], [560, format(angle(scaled_wc('ud1_2322')), '.6e') ,'# cud1Ph2322'], [561, format(angle(scaled_wc('ud1_2323')), '.6e') ,'# cud1Ph2323'], [562, format(angle(scaled_wc('ud1_2331')), '.6e') ,'# cud1Ph2331'], [563, format(angle(scaled_wc('ud1_2332')), '.6e') ,'# cud1Ph2332'], [564, format(angle(scaled_wc('ud1_2333')), '.6e') ,'# cud1Ph2333'], [565, format(angle(scaled_wc('ud1_3323')), '.6e') ,'# cud1Ph3323'], [566, format(angle(scaled_wc('ud1_3312')), '.6e') ,'# cud1Ph3312'], [567, format(angle(scaled_wc('ud1_3313')), '.6e') ,'# cud1Ph3313'], [568, format(scaled_wc('ud8_1111')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1111'], [569, format(abs(scaled_wc('ud8_1112'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1112'], [570, format(abs(scaled_wc('ud8_1113'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1113'], [571, format(abs(scaled_wc('ud8_1123'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1123'], [572, format(scaled_wc('ud8_1122')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1122'], [573, format(scaled_wc('ud8_1133')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1133'], [574, format(abs(scaled_wc('ud8_1211'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1211'], [575, format(abs(scaled_wc('ud8_1212'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1212'], [576, format(abs(scaled_wc('ud8_1221'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1221'], [577, format(abs(scaled_wc('ud8_1213'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1213'], [578, format(abs(scaled_wc('ud8_1231'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1231'], [579, format(abs(scaled_wc('ud8_1222'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1222'], [580, format(abs(scaled_wc('ud8_1223'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1223'], [581, format(abs(scaled_wc('ud8_1232'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1232'], [582, format(abs(scaled_wc('ud8_1233'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1233'], [583, format(abs(scaled_wc('ud8_1311'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1311'], [584, format(abs(scaled_wc('ud8_1312'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1312'], [585, format(abs(scaled_wc('ud8_1313'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1313'], [586, format(abs(scaled_wc('ud8_1331'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1331'], [587, format(abs(scaled_wc('ud8_1321'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1321'], [588, format(abs(scaled_wc('ud8_1322'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1322'], [589, format(abs(scaled_wc('ud8_1332'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1332'], [590, format(abs(scaled_wc('ud8_1323'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1323'], [591, format(abs(scaled_wc('ud8_1333'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs1333'], [592, format(scaled_wc('ud8_2211')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2211'], [593, format(abs(scaled_wc('ud8_2212'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2212'], [594, format(abs(scaled_wc('ud8_2213'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2213'], [595, format(scaled_wc('ud8_2222')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2222'], [596, format(abs(scaled_wc('ud8_2223'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2223'], [597, format(scaled_wc('ud8_2233')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2233'], [598, format(abs(scaled_wc('ud8_2311'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2311'], [599, format(abs(scaled_wc('ud8_2312'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2312'], [600, format(abs(scaled_wc('ud8_2313'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2313'], [601, format(abs(scaled_wc('ud8_2321'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2321'], [602, format(abs(scaled_wc('ud8_2322'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2322'], [603, format(abs(scaled_wc('ud8_2323'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2323'], [604, format(abs(scaled_wc('ud8_2331'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2331'], [605, format(abs(scaled_wc('ud8_2332'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2332'], [606, format(abs(scaled_wc('ud8_2333'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs2333'], [607, format(scaled_wc('ud8_3311')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs3311'], [608, format(abs(scaled_wc('ud8_3312'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs3312'], [609, format(abs(scaled_wc('ud8_3313'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs3313'], [610, format(scaled_wc('ud8_3322')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs3322'], [611, format(scaled_wc('ud8_3333')* lambda_smeft_value**2, '.6e') ,'# cUD8Abs3333'], [612, format(abs(scaled_wc('ud8_3323'))* lambda_smeft_value**2, '.6e') ,'# cUD8Abs3323'], [613, format(angle(scaled_wc('ud8_1112')), '.6e') ,'# cUD8Ph1112'], [614, format(angle(scaled_wc('ud8_2212')), '.6e') ,'# cUD8Ph2212'], [615, format(angle(scaled_wc('ud8_1113')), '.6e') ,'# cUD8Ph1113'], [616, format(angle(scaled_wc('ud8_1123')), '.6e') ,'# cUD8Ph1123'], [617, format(angle(scaled_wc('ud8_1211')), '.6e') ,'# cUD8Ph1211'], [618, format(angle(scaled_wc('ud8_1212')), '.6e') ,'# cUD8Ph1212'], [619, format(angle(scaled_wc('ud8_1221')), '.6e') ,'# cUD8Ph1221'], [620, format(angle(scaled_wc('ud8_1213')), '.6e') ,'# cUD8Ph1213'], [621, format(angle(scaled_wc('ud8_1231')), '.6e') ,'# cUD8Ph1231'], [622, format(angle(scaled_wc('ud8_1222')), '.6e') ,'# cUD8Ph1222'], [623, format(angle(scaled_wc('ud8_1223')), '.6e') ,'# cUD8Ph1223'], [624, format(angle(scaled_wc('ud8_1232')), '.6e') ,'# cUD8Ph1232'], [625, format(angle(scaled_wc('ud8_1233')), '.6e') ,'# cUD8Ph1233'], [626, format(angle(scaled_wc('ud8_1311')), '.6e') ,'# cUD8Ph1311'], [627, format(angle(scaled_wc('ud8_1312')), '.6e') ,'# cUD8Ph1312'], [628, format(angle(scaled_wc('ud8_1313')), '.6e') ,'# cUD8Ph1313'], [629, format(angle(scaled_wc('ud8_1331')), '.6e') ,'# cUD8Ph1331'], [630, format(angle(scaled_wc('ud8_1321')), '.6e') ,'# cUD8Ph1321'], [631, format(angle(scaled_wc('ud8_1322')), '.6e') ,'# cUD8Ph1322'], [632, format(angle(scaled_wc('ud8_1332')), '.6e') ,'# cUD8Ph1332'], [633, format(angle(scaled_wc('ud8_1323')), '.6e') ,'# cUD8Ph1323'], [634, format(angle(scaled_wc('ud8_1333')), '.6e') ,'# cUD8Ph1333'], [635, format(angle(scaled_wc('ud8_2213')), '.6e') ,'# cUD8Ph2213'], [636, format(angle(scaled_wc('ud8_2223')), '.6e') ,'# cUD8Ph2223'], [637, format(angle(scaled_wc('ud8_2311')), '.6e') ,'# cUD8Ph2311'], [638, format(angle(scaled_wc('ud8_2312')), '.6e') ,'# cUD8Ph2312'], [639, format(angle(scaled_wc('ud8_2313')), '.6e') ,'# cUD8Ph2313'], [640, format(angle(scaled_wc('ud8_2321')), '.6e') ,'# cUD8Ph2321'], [641, format(angle(scaled_wc('ud8_2322')), '.6e') ,'# cUD8Ph2322'], [642, format(angle(scaled_wc('ud8_2323')), '.6e') ,'# cUD8Ph2323'], [643, format(angle(scaled_wc('ud8_2331')), '.6e') ,'# cUD8Ph2331'], [644, format(angle(scaled_wc('ud8_2332')), '.6e') ,'# cUD8Ph2332'], [645, format(angle(scaled_wc('ud8_2333')), '.6e') ,'# cUD8Ph2333'], [646, format(angle(scaled_wc('ud8_3323')), '.6e') ,'# cUD8Ph3323'], [647, format(angle(scaled_wc('ud8_3312')), '.6e') ,'# cUD8Ph3312'], [648, format(angle(scaled_wc('ud8_3313')), '.6e') ,'# cUD8Ph3313'], [649, format(scaled_wc('eu_1111')* lambda_smeft_value**2, '.6e') ,'# ceuAbs1111'], [650, format(abs(scaled_wc('eu_1112'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1112'], [651, format(abs(scaled_wc('eu_1113'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1113'], [652, format(abs(scaled_wc('eu_1123'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1123'], [653, format(scaled_wc('eu_1122')* lambda_smeft_value**2, '.6e') ,'# ceuAbs1122'], [654, format(scaled_wc('eu_1133')* lambda_smeft_value**2, '.6e') ,'# ceuAbs1133'], [655, format(abs(scaled_wc('eu_1211'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1211'], [656, format(abs(scaled_wc('eu_1212'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1212'], [657, format(abs(scaled_wc('eu_1221'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1221'], [658, format(abs(scaled_wc('eu_1213'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1213'], [659, format(abs(scaled_wc('eu_1231'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1231'], [660, format(abs(scaled_wc('eu_1222'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1222'], [661, format(abs(scaled_wc('eu_1223'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1223'], [662, format(abs(scaled_wc('eu_1232'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1232'], [663, format(abs(scaled_wc('eu_1233'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1233'], [664, format(abs(scaled_wc('eu_1311'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1311'], [665, format(abs(scaled_wc('eu_1312'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1312'], [666, format(abs(scaled_wc('eu_1313'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1313'], [667, format(abs(scaled_wc('eu_1331'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1331'], [668, format(abs(scaled_wc('eu_1321'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1321'], [669, format(abs(scaled_wc('eu_1322'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1322'], [670, format(abs(scaled_wc('eu_1332'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1332'], [671, format(abs(scaled_wc('eu_1323'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1323'], [672, format(abs(scaled_wc('eu_1333'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs1333'], [673, format(scaled_wc('eu_2211')* lambda_smeft_value**2, '.6e') ,'# ceuAbs2211'], [674, format(abs(scaled_wc('eu_2212'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2212'], [675, format(abs(scaled_wc('eu_2213'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2213'], [676, format(scaled_wc('eu_2222')* lambda_smeft_value**2, '.6e') ,'# ceuAbs2222'], [677, format(abs(scaled_wc('eu_2223'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2223'], [678, format(scaled_wc('eu_2233')* lambda_smeft_value**2, '.6e') ,'# ceuAbs2233'], [679, format(abs(scaled_wc('eu_2311'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2311'], [680, format(abs(scaled_wc('eu_2312'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2312'], [681, format(abs(scaled_wc('eu_2313'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2313'], [682, format(abs(scaled_wc('eu_2321'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2321'], [683, format(abs(scaled_wc('eu_2322'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2322'], [684, format(abs(scaled_wc('eu_2323'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2323'], [685, format(abs(scaled_wc('eu_2331'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2331'], [686, format(abs(scaled_wc('eu_2332'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2332'], [687, format(abs(scaled_wc('eu_2333'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs2333'], [688, format(scaled_wc('eu_3311')* lambda_smeft_value**2, '.6e') ,'# ceuAbs3311'], [689, format(abs(scaled_wc('eu_3312'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs3312'], [690, format(abs(scaled_wc('eu_3313'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs3313'], [691, format(scaled_wc('eu_3322')* lambda_smeft_value**2, '.6e') ,'# ceuAbs3322'], [692, format(scaled_wc('eu_3333')* lambda_smeft_value**2, '.6e') ,'# ceuAbs3333'], [693, format(abs(scaled_wc('eu_3323'))* lambda_smeft_value**2, '.6e') ,'# ceuAbs3323'], [694, format(angle(scaled_wc('eu_1112')), '.6e') ,'# ceuPh1112'], [695, format(angle(scaled_wc('eu_2212')), '.6e') ,'# ceuPh2212'], [696, format(angle(scaled_wc('eu_1113')), '.6e') ,'# ceuPh1113'], [697, format(angle(scaled_wc('eu_1123')), '.6e') ,'# ceuPh1123'], [698, format(angle(scaled_wc('eu_1211')), '.6e') ,'# ceuPh1211'], [699, format(angle(scaled_wc('eu_1212')), '.6e') ,'# ceuPh1212'], [700, format(angle(scaled_wc('eu_1221')), '.6e') ,'# ceuPh1221'], [701, format(angle(scaled_wc('eu_1213')), '.6e') ,'# ceuPh1213'], [702, format(angle(scaled_wc('eu_1231')), '.6e') ,'# ceuPh1231'], [703, format(angle(scaled_wc('eu_1222')), '.6e') ,'# ceuPh1222'], [704, format(angle(scaled_wc('eu_1223')), '.6e') ,'# ceuPh1223'], [705, format(angle(scaled_wc('eu_1232')), '.6e') ,'# ceuPh1232'], [706, format(angle(scaled_wc('eu_1233')), '.6e') ,'# ceuPh1233'], [707, format(angle(scaled_wc('eu_1311')), '.6e') ,'# ceuPh1311'], [708, format(angle(scaled_wc('eu_1312')), '.6e') ,'# ceuPh1312'], [709, format(angle(scaled_wc('eu_1313')), '.6e') ,'# ceuPh1313'], [710, format(angle(scaled_wc('eu_1331')), '.6e') ,'# ceuPh1331'], [711, format(angle(scaled_wc('eu_1321')), '.6e') ,'# ceuPh1321'], [712, format(angle(scaled_wc('eu_1322')), '.6e') ,'# ceuPh1322'], [713, format(angle(scaled_wc('eu_1332')), '.6e') ,'# ceuPh1332'], [714, format(angle(scaled_wc('eu_1323')), '.6e') ,'# ceuPh1323'], [715, format(angle(scaled_wc('eu_1333')), '.6e') ,'# ceuPh1333'], [716, format(angle(scaled_wc('eu_2213')), '.6e') ,'# ceuPh2213'], [717, format(angle(scaled_wc('eu_2223')), '.6e') ,'# ceuPh2223'], [718, format(angle(scaled_wc('eu_2311')), '.6e') ,'# ceuPh2311'], [719, format(angle(scaled_wc('eu_2312')), '.6e') ,'# ceuPh2312'], [720, format(angle(scaled_wc('eu_2313')), '.6e') ,'# ceuPh2313'], [721, format(angle(scaled_wc('eu_2321')), '.6e') ,'# ceuPh2321'], [722, format(angle(scaled_wc('eu_2322')), '.6e') ,'# ceuPh2322'], [723, format(angle(scaled_wc('eu_2323')), '.6e') ,'# ceuPh2323'], [724, format(angle(scaled_wc('eu_2331')), '.6e') ,'# ceuPh2331'], [725, format(angle(scaled_wc('eu_2332')), '.6e') ,'# ceuPh2332'], [726, format(angle(scaled_wc('eu_2333')), '.6e') ,'# ceuPh2333'], [727, format(angle(scaled_wc('eu_3323')), '.6e') ,'# ceuPh3323'], [728, format(angle(scaled_wc('eu_3312')), '.6e') ,'# ceuPh3312'], [729, format(angle(scaled_wc('eu_3313')), '.6e') ,'# ceuPh3313'], [730, format(scaled_wc('ed_1111')* lambda_smeft_value**2, '.6e') ,'# cedAbs1111'], [731, format(abs(scaled_wc('ed_1112'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1112'], [732, format(abs(scaled_wc('ed_1113'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1113'], [733, format(abs(scaled_wc('ed_1123'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1123'], [734, format(scaled_wc('ed_1122')* lambda_smeft_value**2, '.6e') ,'# cedAbs1122'], [735, format(scaled_wc('ed_1133')* lambda_smeft_value**2, '.6e') ,'# cedAbs1133'], [736, format(abs(scaled_wc('ed_1211'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1211'], [737, format(abs(scaled_wc('ed_1212'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1212'], [738, format(abs(scaled_wc('ed_1221'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1221'], [739, format(abs(scaled_wc('ed_1213'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1213'], [740, format(abs(scaled_wc('ed_1231'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1231'], [741, format(abs(scaled_wc('ed_1222'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1222'], [742, format(abs(scaled_wc('ed_1223'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1223'], [743, format(abs(scaled_wc('ed_1232'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1232'], [744, format(abs(scaled_wc('ed_1233'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1233'], [745, format(abs(scaled_wc('ed_1311'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1311'], [746, format(abs(scaled_wc('ed_1312'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1312'], [747, format(abs(scaled_wc('ed_1313'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1313'], [748, format(abs(scaled_wc('ed_1331'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1331'], [749, format(abs(scaled_wc('ed_1321'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1321'], [750, format(abs(scaled_wc('ed_1322'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1322'], [751, format(abs(scaled_wc('ed_1332'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1332'], [752, format(abs(scaled_wc('ed_1323'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1323'], [753, format(abs(scaled_wc('ed_1333'))* lambda_smeft_value**2, '.6e') ,'# cedAbs1333'], [754, format(scaled_wc('ed_2211')* lambda_smeft_value**2, '.6e') ,'# cedAbs2211'], [755, format(abs(scaled_wc('ed_2212'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2212'], [756, format(abs(scaled_wc('ed_2213'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2213'], [757, format(scaled_wc('ed_2222')* lambda_smeft_value**2, '.6e') ,'# cedAbs2222'], [758, format(abs(scaled_wc('ed_2223'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2223'], [759, format(scaled_wc('ed_2233')* lambda_smeft_value**2, '.6e') ,'# cedAbs2233'], [760, format(abs(scaled_wc('ed_2311'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2311'], [761, format(abs(scaled_wc('ed_2312'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2312'], [762, format(abs(scaled_wc('ed_2313'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2313'], [763, format(abs(scaled_wc('ed_2321'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2321'], [764, format(abs(scaled_wc('ed_2322'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2322'], [765, format(abs(scaled_wc('ed_2323'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2323'], [766, format(abs(scaled_wc('ed_2331'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2331'], [767, format(abs(scaled_wc('ed_2332'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2332'], [768, format(abs(scaled_wc('ed_2333'))* lambda_smeft_value**2, '.6e') ,'# cedAbs2333'], [769, format(scaled_wc('ed_3311')* lambda_smeft_value**2, '.6e') ,'# cedAbs3311'], [770, format(abs(scaled_wc('ed_3312'))* lambda_smeft_value**2, '.6e') ,'# cedAbs3312'], [771, format(abs(scaled_wc('ed_3313'))* lambda_smeft_value**2, '.6e') ,'# cedAbs3313'], [772, format(scaled_wc('ed_3322')* lambda_smeft_value**2, '.6e') ,'# cedAbs3322'], [773, format(scaled_wc('ed_3333')* lambda_smeft_value**2, '.6e') ,'# cedAbs3333'], [774, format(abs(scaled_wc('ed_3323'))* lambda_smeft_value**2, '.6e') ,'# cedAbs3323'], [775, format(angle(scaled_wc('ed_1112')), '.6e') ,'# cedPh1112'], [776, format(angle(scaled_wc('ed_2212')), '.6e') ,'# cedPh2212'], [777, format(angle(scaled_wc('ed_1113')), '.6e') ,'# cedPh1113'], [778, format(angle(scaled_wc('ed_1123')), '.6e') ,'# cedPh1123'], [779, format(angle(scaled_wc('ed_1211')), '.6e') ,'# cedPh1211'], [780, format(angle(scaled_wc('ed_1212')), '.6e') ,'# cedPh1212'], [781, format(angle(scaled_wc('ed_1221')), '.6e') ,'# cedPh1221'], [782, format(angle(scaled_wc('ed_1213')), '.6e') ,'# cedPh1213'], [783, format(angle(scaled_wc('ed_1231')), '.6e') ,'# cedPh1231'], [784, format(angle(scaled_wc('ed_1222')), '.6e') ,'# cedPh1222'], [785, format(angle(scaled_wc('ed_1223')), '.6e') ,'# cedPh1223'], [786, format(angle(scaled_wc('ed_1232')), '.6e') ,'# cedPh1232'], [787, format(angle(scaled_wc('ed_1233')), '.6e') ,'# cedPh1233'], [788, format(angle(scaled_wc('ed_1311')), '.6e') ,'# cedPh1311'], [789, format(angle(scaled_wc('ed_1312')), '.6e') ,'# cedPh1312'], [790, format(angle(scaled_wc('ed_1313')), '.6e') ,'# cedPh1313'], [791, format(angle(scaled_wc('ed_1331')), '.6e') ,'# cedPh1331'], [792, format(angle(scaled_wc('ed_1321')), '.6e') ,'# cedPh1321'], [793, format(angle(scaled_wc('ed_1322')), '.6e') ,'# cedPh1322'], [794, format(angle(scaled_wc('ed_1332')), '.6e') ,'# cedPh1332'], [795, format(angle(scaled_wc('ed_1323')), '.6e') ,'# cedPh1323'], [796, format(angle(scaled_wc('ed_1333')), '.6e') ,'# cedPh1333'], [797, format(angle(scaled_wc('ed_2213')), '.6e') ,'# cedPh2213'], [798, format(angle(scaled_wc('ed_2223')), '.6e') ,'# cedPh2223'], [799, format(angle(scaled_wc('ed_2311')), '.6e') ,'# cedPh2311'], [800, format(angle(scaled_wc('ed_2312')), '.6e') ,'# cedPh2312'], [801, format(angle(scaled_wc('ed_2313')), '.6e') ,'# cedPh2313'], [802, format(angle(scaled_wc('ed_2321')), '.6e') ,'# cedPh2321'], [803, format(angle(scaled_wc('ed_2322')), '.6e') ,'# cedPh2322'], [804, format(angle(scaled_wc('ed_2323')), '.6e') ,'# cedPh2323'], [805, format(angle(scaled_wc('ed_2331')), '.6e') ,'# cedPh2331'], [806, format(angle(scaled_wc('ed_2332')), '.6e') ,'# cedPh2332'], [807, format(angle(scaled_wc('ed_2333')), '.6e') ,'# cedPh2333'], [808, format(angle(scaled_wc('ed_3323')), '.6e') ,'# cedPh3323'], [809, format(angle(scaled_wc('ed_3312')), '.6e') ,'# cedPh3312'], [810, format(angle(scaled_wc('ed_3313')), '.6e') ,'# cedPh3313'], [811, format(scaled_wc('qu1_1111')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1111'], [812, format(abs(scaled_wc('qu1_1112'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1112'], [813, format(abs(scaled_wc('qu1_1113'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1113'], [814, format(abs(scaled_wc('qu1_1123'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1123'], [815, format(scaled_wc('qu1_1122')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1122'], [816, format(scaled_wc('qu1_1133')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1133'], [817, format(abs(scaled_wc('qu1_1211'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1211'], [818, format(abs(scaled_wc('qu1_1212'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1212'], [819, format(abs(scaled_wc('qu1_1221'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1221'], [820, format(abs(scaled_wc('qu1_1213'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1213'], [821, format(abs(scaled_wc('qu1_1231'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1231'], [822, format(abs(scaled_wc('qu1_1222'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1222'], [823, format(abs(scaled_wc('qu1_1223'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1223'], [824, format(abs(scaled_wc('qu1_1232'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1232'], [825, format(abs(scaled_wc('qu1_1233'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1233'], [826, format(abs(scaled_wc('qu1_1311'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1311'], [827, format(abs(scaled_wc('qu1_1312'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1312'], [828, format(abs(scaled_wc('qu1_1313'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1313'], [829, format(abs(scaled_wc('qu1_1331'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1331'], [830, format(abs(scaled_wc('qu1_1321'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1321'], [831, format(abs(scaled_wc('qu1_1322'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1322'], [832, format(abs(scaled_wc('qu1_1332'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1332'], [833, format(abs(scaled_wc('qu1_1323'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1323'], [834, format(abs(scaled_wc('qu1_1333'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs1333'], [835, format(scaled_wc('qu1_2211')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2211'], [836, format(abs(scaled_wc('qu1_2212'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2212'], [837, format(abs(scaled_wc('qu1_2213'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2213'], [838, format(scaled_wc('qu1_2222')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2222'], [839, format(abs(scaled_wc('qu1_2223'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2223'], [840, format(scaled_wc('qu1_2233')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2233'], [841, format(abs(scaled_wc('qu1_2311'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2311'], [842, format(abs(scaled_wc('qu1_2312'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2312'], [843, format(abs(scaled_wc('qu1_2313'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2313'], [844, format(abs(scaled_wc('qu1_2321'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2321'], [845, format(abs(scaled_wc('qu1_2322'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2322'], [846, format(abs(scaled_wc('qu1_2323'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2323'], [847, format(abs(scaled_wc('qu1_2331'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2331'], [848, format(abs(scaled_wc('qu1_2332'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2332'], [849, format(abs(scaled_wc('qu1_2333'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs2333'], [850, format(scaled_wc('qu1_3311')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs3311'], [851, format(abs(scaled_wc('qu1_3312'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs3312'], [852, format(abs(scaled_wc('qu1_3313'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs3313'], [853, format(scaled_wc('qu1_3322')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs3322'], [854, format(scaled_wc('qu1_3333')* lambda_smeft_value**2, '.6e') ,'# cqu1Abs3333'], [855, format(abs(scaled_wc('qu1_3323'))* lambda_smeft_value**2, '.6e') ,'# cqu1Abs3323'], [856, format(angle(scaled_wc('qu1_1112')), '.6e') ,'# cqu1Ph1112'], [857, format(angle(scaled_wc('qu1_2212')), '.6e') ,'# cqu1Ph2212'], [858, format(angle(scaled_wc('qu1_1113')), '.6e') ,'# cqu1Ph1113'], [859, format(angle(scaled_wc('qu1_1123')), '.6e') ,'# cqu1Ph1123'], [860, format(angle(scaled_wc('qu1_1211')), '.6e') ,'# cqu1Ph1211'], [861, format(angle(scaled_wc('qu1_1212')), '.6e') ,'# cqu1Ph1212'], [862, format(angle(scaled_wc('qu1_1221')), '.6e') ,'# cqu1Ph1221'], [863, format(angle(scaled_wc('qu1_1213')), '.6e') ,'# cqu1Ph1213'], [864, format(angle(scaled_wc('qu1_1231')), '.6e') ,'# cqu1Ph1231'], [865, format(angle(scaled_wc('qu1_1222')), '.6e') ,'# cqu1Ph1222'], [866, format(angle(scaled_wc('qu1_1223')), '.6e') ,'# cqu1Ph1223'], [867, format(angle(scaled_wc('qu1_1232')), '.6e') ,'# cqu1Ph1232'], [868, format(angle(scaled_wc('qu1_1233')), '.6e') ,'# cqu1Ph1233'], [869, format(angle(scaled_wc('qu1_1311')), '.6e') ,'# cqu1Ph1311'], [870, format(angle(scaled_wc('qu1_1312')), '.6e') ,'# cqu1Ph1312'], [871, format(angle(scaled_wc('qu1_1313')), '.6e') ,'# cqu1Ph1313'], [872, format(angle(scaled_wc('qu1_1331')), '.6e') ,'# cqu1Ph1331'], [873, format(angle(scaled_wc('qu1_1321')), '.6e') ,'# cqu1Ph1321'], [874, format(angle(scaled_wc('qu1_1322')), '.6e') ,'# cqu1Ph1322'], [875, format(angle(scaled_wc('qu1_1332')), '.6e') ,'# cqu1Ph1332'], [876, format(angle(scaled_wc('qu1_1323')), '.6e') ,'# cqu1Ph1323'], [877, format(angle(scaled_wc('qu1_1333')), '.6e') ,'# cqu1Ph1333'], [878, format(angle(scaled_wc('qu1_2213')), '.6e') ,'# cqu1Ph2213'], [879, format(angle(scaled_wc('qu1_2223')), '.6e') ,'# cqu1Ph2223'], [880, format(angle(scaled_wc('qu1_2311')), '.6e') ,'# cqu1Ph2311'], [881, format(angle(scaled_wc('qu1_2312')), '.6e') ,'# cqu1Ph2312'], [882, format(angle(scaled_wc('qu1_2313')), '.6e') ,'# cqu1Ph2313'], [883, format(angle(scaled_wc('qu1_2321')), '.6e') ,'# cqu1Ph2321'], [884, format(angle(scaled_wc('qu1_2322')), '.6e') ,'# cqu1Ph2322'], [885, format(angle(scaled_wc('qu1_2323')), '.6e') ,'# cqu1Ph2323'], [886, format(angle(scaled_wc('qu1_2331')), '.6e') ,'# cqu1Ph2331'], [887, format(angle(scaled_wc('qu1_2332')), '.6e') ,'# cqu1Ph2332'], [888, format(angle(scaled_wc('qu1_2333')), '.6e') ,'# cqu1Ph2333'], [889, format(angle(scaled_wc('qu1_3323')), '.6e') ,'# cqu1Ph3323'], [890, format(angle(scaled_wc('qu1_3312')), '.6e') ,'# cqu1Ph3312'], [891, format(angle(scaled_wc('qu1_3313')), '.6e') ,'# cqu1Ph3313'], [892, format(scaled_wc('qu8_1111')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1111'], [893, format(abs(scaled_wc('qu8_1112'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1112'], [894, format(abs(scaled_wc('qu8_1113'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1113'], [895, format(abs(scaled_wc('qu8_1123'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1123'], [896, format(scaled_wc('qu8_1122')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1122'], [897, format(scaled_wc('qu8_1133')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1133'], [898, format(abs(scaled_wc('qu8_1211'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1211'], [899, format(abs(scaled_wc('qu8_1212'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1212'], [900, format(abs(scaled_wc('qu8_1221'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1221'], [901, format(abs(scaled_wc('qu8_1213'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1213'], [902, format(abs(scaled_wc('qu8_1231'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1231'], [903, format(abs(scaled_wc('qu8_1222'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1222'], [904, format(abs(scaled_wc('qu8_1223'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1223'], [905, format(abs(scaled_wc('qu8_1232'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1232'], [906, format(abs(scaled_wc('qu8_1233'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1233'], [907, format(abs(scaled_wc('qu8_1311'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1311'], [908, format(abs(scaled_wc('qu8_1312'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1312'], [909, format(abs(scaled_wc('qu8_1313'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1313'], [910, format(abs(scaled_wc('qu8_1331'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1331'], [911, format(abs(scaled_wc('qu8_1321'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1321'], [912, format(abs(scaled_wc('qu8_1322'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1322'], [913, format(abs(scaled_wc('qu8_1332'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1332'], [914, format(abs(scaled_wc('qu8_1323'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1323'], [915, format(abs(scaled_wc('qu8_1333'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs1333'], [916, format(scaled_wc('qu8_2211')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2211'], [917, format(abs(scaled_wc('qu8_2212'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2212'], [918, format(abs(scaled_wc('qu8_2213'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2213'], [919, format(scaled_wc('qu8_2222')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2222'], [920, format(abs(scaled_wc('qu8_2223'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2223'], [921, format(scaled_wc('qu8_2233')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2233'], [922, format(abs(scaled_wc('qu8_2311'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2311'], [923, format(abs(scaled_wc('qu8_2312'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2312'], [924, format(abs(scaled_wc('qu8_2313'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2313'], [925, format(abs(scaled_wc('qu8_2321'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2321'], [926, format(abs(scaled_wc('qu8_2322'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2322'], [927, format(abs(scaled_wc('qu8_2323'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2323'], [928, format(abs(scaled_wc('qu8_2331'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2331'], [929, format(abs(scaled_wc('qu8_2332'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2332'], [930, format(abs(scaled_wc('qu8_2333'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs2333'], [931, format(scaled_wc('qu8_3311')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs3311'], [932, format(abs(scaled_wc('qu8_3312'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs3312'], [933, format(abs(scaled_wc('qu8_3313'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs3313'], [934, format(scaled_wc('qu8_3322')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs3322'], [935, format(scaled_wc('qu8_3333')* lambda_smeft_value**2, '.6e') ,'# cQU8Abs3333'], [936, format(abs(scaled_wc('qu8_3323'))* lambda_smeft_value**2, '.6e') ,'# cQU8Abs3323'], [937, format(angle(scaled_wc('qu8_1112')), '.6e') ,'# cQU8Ph1112'], [938, format(angle(scaled_wc('qu8_2212')), '.6e') ,'# cQU8Ph2212'], [939, format(angle(scaled_wc('qu8_1113')), '.6e') ,'# cQU8Ph1113'], [940, format(angle(scaled_wc('qu8_1123')), '.6e') ,'# cQU8Ph1123'], [941, format(angle(scaled_wc('qu8_1211')), '.6e') ,'# cQU8Ph1211'], [942, format(angle(scaled_wc('qu8_1212')), '.6e') ,'# cQU8Ph1212'], [943, format(angle(scaled_wc('qu8_1221')), '.6e') ,'# cQU8Ph1221'], [944, format(angle(scaled_wc('qu8_1213')), '.6e') ,'# cQU8Ph1213'], [945, format(angle(scaled_wc('qu8_1231')), '.6e') ,'# cQU8Ph1231'], [946, format(angle(scaled_wc('qu8_1222')), '.6e') ,'# cQU8Ph1222'], [947, format(angle(scaled_wc('qu8_1223')), '.6e') ,'# cQU8Ph1223'], [948, format(angle(scaled_wc('qu8_1232')), '.6e') ,'# cQU8Ph1232'], [949, format(angle(scaled_wc('qu8_1233')), '.6e') ,'# cQU8Ph1233'], [950, format(angle(scaled_wc('qu8_1311')), '.6e') ,'# cQU8Ph1311'], [951, format(angle(scaled_wc('qu8_1312')), '.6e') ,'# cQU8Ph1312'], [952, format(angle(scaled_wc('qu8_1313')), '.6e') ,'# cQU8Ph1313'], [953, format(angle(scaled_wc('qu8_1331')), '.6e') ,'# cQU8Ph1331'], [954, format(angle(scaled_wc('qu8_1321')), '.6e') ,'# cQU8Ph1321'], [955, format(angle(scaled_wc('qu8_1322')), '.6e') ,'# cQU8Ph1322'], [956, format(angle(scaled_wc('qu8_1332')), '.6e') ,'# cQU8Ph1332'], [957, format(angle(scaled_wc('qu8_1323')), '.6e') ,'# cQU8Ph1323'], [958, format(angle(scaled_wc('qu8_1333')), '.6e') ,'# cQU8Ph1333'], [959, format(angle(scaled_wc('qu8_2213')), '.6e') ,'# cQU8Ph2213'], [960, format(angle(scaled_wc('qu8_2223')), '.6e') ,'# cQU8Ph2223'], [961, format(angle(scaled_wc('qu8_2311')), '.6e') ,'# cQU8Ph2311'], [962, format(angle(scaled_wc('qu8_2312')), '.6e') ,'# cQU8Ph2312'], [963, format(angle(scaled_wc('qu8_2313')), '.6e') ,'# cQU8Ph2313'], [964, format(angle(scaled_wc('qu8_2321')), '.6e') ,'# cQU8Ph2321'], [965, format(angle(scaled_wc('qu8_2322')), '.6e') ,'# cQU8Ph2322'], [966, format(angle(scaled_wc('qu8_2323')), '.6e') ,'# cQU8Ph2323'], [967, format(angle(scaled_wc('qu8_2331')), '.6e') ,'# cQU8Ph2331'], [968, format(angle(scaled_wc('qu8_2332')), '.6e') ,'# cQU8Ph2332'], [969, format(angle(scaled_wc('qu8_2333')), '.6e') ,'# cQU8Ph2333'], [970, format(angle(scaled_wc('qu8_3323')), '.6e') ,'# cQU8Ph3323'], [971, format(angle(scaled_wc('qu8_3312')), '.6e') ,'# cQU8Ph3312'], [972, format(angle(scaled_wc('qu8_3313')), '.6e') ,'# cQU8Ph3313'], [973, format(scaled_wc('qd1_1111')* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1111'], [974, format(abs(scaled_wc('qd1_1112'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1112'], [975, format(abs(scaled_wc('qd1_1113'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1113'], [976, format(abs(scaled_wc('qd1_1123'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1123'], [977, format(scaled_wc('qd1_1122')* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1122'], [978, format(scaled_wc('qd1_1133')* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1133'], [979, format(abs(scaled_wc('qd1_1211'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1211'], [980, format(abs(scaled_wc('qd1_1212'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1212'], [981, format(abs(scaled_wc('qd1_1221'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1221'], [982, format(abs(scaled_wc('qd1_1213'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1213'], [983, format(abs(scaled_wc('qd1_1231'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1231'], [984, format(abs(scaled_wc('qd1_1222'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1222'], [985, format(abs(scaled_wc('qd1_1223'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1223'], [986, format(abs(scaled_wc('qd1_1232'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1232'], [987, format(abs(scaled_wc('qd1_1233'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1233'], [988, format(abs(scaled_wc('qd1_1311'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1311'], [989, format(abs(scaled_wc('qd1_1312'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1312'], [990, format(abs(scaled_wc('qd1_1313'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1313'], [991, format(abs(scaled_wc('qd1_1331'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1331'], [992, format(abs(scaled_wc('qd1_1321'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1321'], [993, format(abs(scaled_wc('qd1_1322'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1322'], [994, format(abs(scaled_wc('qd1_1332'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1332'], [995, format(abs(scaled_wc('qd1_1323'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1323'], [996, format(abs(scaled_wc('qd1_1333'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs1333'], [997, format(scaled_wc('qd1_2211')* lambda_smeft_value**2, '.6e') ,'# cqd1Abs2211'], [998, format(abs(scaled_wc('qd1_2212'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs2212'], [999, format(abs(scaled_wc('qd1_2213'))* lambda_smeft_value**2, '.6e') ,'# cqd1Abs2213'], [1000, format(scaled_wc('qd1_2222')* lambda_smeft_value**2, '.6e'), '# cqd1Abs2222'], [1001, format(abs(scaled_wc('qd1_2223'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2223'], [1002, format(scaled_wc('qd1_2233')* lambda_smeft_value**2, '.6e'), '# cqd1Abs2233'], [1003, format(abs(scaled_wc('qd1_2311'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2311'], [1004, format(abs(scaled_wc('qd1_2312'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2312'], [1005, format(abs(scaled_wc('qd1_2313'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2313'], [1006, format(abs(scaled_wc('qd1_2321'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2321'], [1007, format(abs(scaled_wc('qd1_2322'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2322'], [1008, format(abs(scaled_wc('qd1_2323'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2323'], [1009, format(abs(scaled_wc('qd1_2331'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2331'], [1010, format(abs(scaled_wc('qd1_2332'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2332'], [1011, format(abs(scaled_wc('qd1_2333'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs2333'], [1012, format(scaled_wc('qd1_3311')* lambda_smeft_value**2, '.6e'), '# cqd1Abs3311'], [1013, format(abs(scaled_wc('qd1_3312'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs3312'], [1014, format(abs(scaled_wc('qd1_3313'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs3313'], [1015, format(scaled_wc('qd1_3322')* lambda_smeft_value**2, '.6e'), '# cqd1Abs3322'], [1016, format(scaled_wc('qd1_3333')* lambda_smeft_value**2, '.6e'), '# cqd1Abs3333'], [1017, format(abs(scaled_wc('qd1_3323'))* lambda_smeft_value**2, '.6e'), '# cqd1Abs3323'], [1018, format(angle(scaled_wc('qd1_1112')), '.6e'), '# cqd1Ph1112'], [1019, format(angle(scaled_wc('qd1_2212')), '.6e'), '# cqd1Ph2212'], [1020, format(angle(scaled_wc('qd1_1113')), '.6e'), '# cqd1Ph1113'], [1021, format(angle(scaled_wc('qd1_1123')), '.6e'), '# cqd1Ph1123'], [1022, format(angle(scaled_wc('qd1_1211')), '.6e'), '# cqd1Ph1211'], [1023, format(angle(scaled_wc('qd1_1212')), '.6e'), '# cqd1Ph1212'], [1024, format(angle(scaled_wc('qd1_1221')), '.6e'), '# cqd1Ph1221'], [1025, format(angle(scaled_wc('qd1_1213')), '.6e'), '# cqd1Ph1213'], [1026, format(angle(scaled_wc('qd1_1231')), '.6e'), '# cqd1Ph1231'], [1027, format(angle(scaled_wc('qd1_1222')), '.6e'), '# cqd1Ph1222'], [1028, format(angle(scaled_wc('qd1_1223')), '.6e'), '# cqd1Ph1223'], [1029, format(angle(scaled_wc('qd1_1232')), '.6e'), '# cqd1Ph1232'], [1030, format(angle(scaled_wc('qd1_1233')), '.6e'), '# cqd1Ph1233'], [1031, format(angle(scaled_wc('qd1_1311')), '.6e'), '# cqd1Ph1311'], [1032, format(angle(scaled_wc('qd1_1312')), '.6e'), '# cqd1Ph1312'], [1033, format(angle(scaled_wc('qd1_1313')), '.6e'), '# cqd1Ph1313'], [1034, format(angle(scaled_wc('qd1_1331')), '.6e'), '# cqd1Ph1331'], [1035, format(angle(scaled_wc('qd1_1321')), '.6e'), '# cqd1Ph1321'], [1036, format(angle(scaled_wc('qd1_1322')), '.6e'), '# cqd1Ph1322'], [1037, format(angle(scaled_wc('qd1_1332')), '.6e'), '# cqd1Ph1332'], [1038, format(angle(scaled_wc('qd1_1323')), '.6e'), '# cqd1Ph1323'], [1039, format(angle(scaled_wc('qd1_1333')), '.6e'), '# cqd1Ph1333'], [1040, format(angle(scaled_wc('qd1_2213')), '.6e'), '# cqd1Ph2213'], [1041, format(angle(scaled_wc('qd1_2223')), '.6e'), '# cqd1Ph2223'], [1042, format(angle(scaled_wc('qd1_2311')), '.6e'), '# cqd1Ph2311'], [1043, format(angle(scaled_wc('qd1_2312')), '.6e'), '# cqd1Ph2312'], [1044, format(angle(scaled_wc('qd1_2313')), '.6e'), '# cqd1Ph2313'], [1045, format(angle(scaled_wc('qd1_2321')), '.6e'), '# cqd1Ph2321'], [1046, format(angle(scaled_wc('qd1_2322')), '.6e'), '# cqd1Ph2322'], [1047, format(angle(scaled_wc('qd1_2323')), '.6e'), '# cqd1Ph2323'], [1048, format(angle(scaled_wc('qd1_2331')), '.6e'), '# cqd1Ph2331'], [1049, format(angle(scaled_wc('qd1_2332')), '.6e'), '# cqd1Ph2332'], [1050, format(angle(scaled_wc('qd1_2333')), '.6e'), '# cqd1Ph2333'], [1051, format(angle(scaled_wc('qd1_3323')), '.6e'), '# cqd1Ph3323'], [1052, format(angle(scaled_wc('qd1_3312')), '.6e'), '# cqd1Ph3312'], [1053, format(angle(scaled_wc('qd1_3313')), '.6e'), '# cqd1Ph3313'], [1054, format(scaled_wc('qd8_1111')* 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lambda_smeft_value**2, '.6e'), '# cqeAbs2322'], [1413, format(abs(scaled_wc('qe_2323'))* lambda_smeft_value**2, '.6e'), '# cqeAbs2323'], [1414, format(abs(scaled_wc('qe_2331'))* lambda_smeft_value**2, '.6e'), '# cqeAbs2331'], [1415, format(abs(scaled_wc('qe_2332'))* lambda_smeft_value**2, '.6e'), '# cqeAbs2332'], [1416, format(abs(scaled_wc('qe_2333'))* lambda_smeft_value**2, '.6e'), '# cqeAbs2333'], [1417, format(scaled_wc('qe_3311')* lambda_smeft_value**2, '.6e'), '# cqeAbs3311'], [1418, format(abs(scaled_wc('qe_3312'))* lambda_smeft_value**2, '.6e'), '# cqeAbs3312'], [1419, format(abs(scaled_wc('qe_3313'))* lambda_smeft_value**2, '.6e'), '# cqeAbs3313'], [1420, format(scaled_wc('qe_3322')* lambda_smeft_value**2, '.6e'), '# cqeAbs3322'], [1421, format(scaled_wc('qe_3333')* lambda_smeft_value**2, '.6e'), '# cqeAbs3333'], [1422, format(abs(scaled_wc('qe_3323'))* lambda_smeft_value**2, '.6e'), '# cqeAbs3323'], [1423, format(angle(scaled_wc('qe_1112')), '.6e'), '# cqePh1112'], [1424, format(angle(scaled_wc('qe_2212')), '.6e'), '# cqePh2212'], [1425, format(angle(scaled_wc('qe_1113')), '.6e'), '# cqePh1113'], [1426, format(angle(scaled_wc('qe_1123')), '.6e'), '# cqePh1123'], [1427, format(angle(scaled_wc('qe_1211')), '.6e'), '# cqePh1211'], [1428, format(angle(scaled_wc('qe_1212')), '.6e'), '# cqePh1212'], [1429, format(angle(scaled_wc('qe_1221')), '.6e'), '# cqePh1221'], [1430, format(angle(scaled_wc('qe_1213')), '.6e'), '# cqePh1213'], [1431, format(angle(scaled_wc('qe_1231')), '.6e'), '# cqePh1231'], [1432, format(angle(scaled_wc('qe_1222')), '.6e'), '# cqePh1222'], [1433, format(angle(scaled_wc('qe_1223')), '.6e'), '# cqePh1223'], [1434, format(angle(scaled_wc('qe_1232')), '.6e'), '# cqePh1232'], [1435, format(angle(scaled_wc('qe_1233')), '.6e'), '# cqePh1233'], [1436, format(angle(scaled_wc('qe_1311')), '.6e'), '# cqePh1311'], [1437, format(angle(scaled_wc('qe_1312')), '.6e'), '# cqePh1312'], [1438, format(angle(scaled_wc('qe_1313')), '.6e'), '# cqePh1313'], [1439, format(angle(scaled_wc('qe_1331')), '.6e'), '# cqePh1331'], [1440, format(angle(scaled_wc('qe_1321')), '.6e'), '# cqePh1321'], [1441, format(angle(scaled_wc('qe_1322')), '.6e'), '# cqePh1322'], [1442, format(angle(scaled_wc('qe_1332')), '.6e'), '# cqePh1332'], [1443, format(angle(scaled_wc('qe_1323')), '.6e'), '# cqePh1323'], [1444, format(angle(scaled_wc('qe_1333')), '.6e'), '# cqePh1333'], [1445, format(angle(scaled_wc('qe_2213')), '.6e'), '# cqePh2213'], [1446, format(angle(scaled_wc('qe_2223')), '.6e'), '# cqePh2223'], [1447, format(angle(scaled_wc('qe_2311')), '.6e'), '# cqePh2311'], [1448, format(angle(scaled_wc('qe_2312')), '.6e'), '# cqePh2312'], [1449, format(angle(scaled_wc('qe_2313')), '.6e'), '# cqePh2313'], [1450, format(angle(scaled_wc('qe_2321')), '.6e'), '# cqePh2321'], [1451, format(angle(scaled_wc('qe_2322')), '.6e'), '# cqePh2322'], [1452, format(angle(scaled_wc('qe_2323')), '.6e'), '# cqePh2323'], [1453, format(angle(scaled_wc('qe_2331')), '.6e'), '# cqePh2331'], [1454, format(angle(scaled_wc('qe_2332')), '.6e'), '# cqePh2332'], [1455, format(angle(scaled_wc('qe_2333')), '.6e'), '# cqePh2333'], [1456, format(angle(scaled_wc('qe_3323')), '.6e'), '# cqePh3323'], [1457, format(angle(scaled_wc('qe_3312')), '.6e'), '# cqePh3312'], [1458, format(angle(scaled_wc('qe_3313')), '.6e'), '# cqePh3313'], ]} card['Block']['FRBlock10'] = {'values': [ [1, 1, format(angle(scaled_wc('uphi_11')), '.6e'), '# cuHPh1x1'], [1, 2, format(angle(scaled_wc('uphi_12')), '.6e'), '# cuHPh1x2'], [1, 3, format(angle(scaled_wc('uphi_13')), '.6e'), '# cuHPh1x3'], [2, 1, format(angle(scaled_wc('uphi_21')), '.6e'), '# cuHPh2x1'], [2, 2, format(angle(scaled_wc('uphi_22')), '.6e'), '# cuHPh2x2'], [2, 3, format(angle(scaled_wc('uphi_23')), '.6e'), '# cuHPh2x3'], [3, 1, format(angle(scaled_wc('uphi_31')), '.6e'), '# cuHPh3x1'], [3, 2, format(angle(scaled_wc('uphi_32')), '.6e'), '# cuHPh3x2'], [3, 3, format(angle(scaled_wc('uphi_33')), '.6e'), '# cuHPh3x3'], ]} card['Block']['FRBlock11'] = {'values': [ [1, 1, format(angle(scaled_wc('dphi_11')), '.6e'), '# cdHPh1x1'], [1, 2, format(angle(scaled_wc('dphi_12')), '.6e'), '# cdHPh1x2'], [1, 3, format(angle(scaled_wc('dphi_13')), '.6e'), '# cdHPh1x3'], [2, 1, format(angle(scaled_wc('dphi_21')), '.6e'), '# cdHPh2x1'], [2, 2, format(angle(scaled_wc('dphi_22')), '.6e'), '# cdHPh2x2'], [2, 3, format(angle(scaled_wc('dphi_23')), '.6e'), '# cdHPh2x3'], [3, 1, format(angle(scaled_wc('dphi_31')), '.6e'), '# cdHPh3x1'], [3, 2, format(angle(scaled_wc('dphi_32')), '.6e'), '# cdHPh3x2'], [3, 3, format(angle(scaled_wc('dphi_33')), '.6e'), '# cdHPh3x3'], ]} card['Block']['FRBlock15'] = {'values': [ [1, 1, format(abs(scaled_wc('eW_11'))* lambda_smeft_value**2, '.6e'), '# ceWAbs1x1'], [1, 2, format(abs(scaled_wc('eW_12'))* lambda_smeft_value**2, '.6e'), '# ceWAbs1x2'], [1, 3, format(abs(scaled_wc('eW_13'))* lambda_smeft_value**2, '.6e'), '# ceWAbs1x3'], [2, 1, format(abs(scaled_wc('eW_21'))* lambda_smeft_value**2, '.6e'), '# ceWAbs2x1'], [2, 2, format(abs(scaled_wc('eW_22'))* lambda_smeft_value**2, '.6e'), '# ceWAbs2x2'], [2, 3, format(abs(scaled_wc('eW_23'))* lambda_smeft_value**2, '.6e'), '# ceWAbs2x3'], [3, 1, format(abs(scaled_wc('eW_31'))* lambda_smeft_value**2, '.6e'), '# ceWAbs3x1'], [3, 2, format(abs(scaled_wc('eW_32'))* lambda_smeft_value**2, '.6e'), '# ceWAbs3x2'], [3, 3, format(abs(scaled_wc('eW_33'))* lambda_smeft_value**2, '.6e'), '# ceWAbs3x3'], ]} card['Block']['FRBlock16'] = {'values': [ [1, 1, format(angle(scaled_wc('eW_11')), '.6e'), '# ceWPh1x1'], [1, 2, format(angle(scaled_wc('eW_12')), '.6e'), '# ceWPh1x2'], [1, 3, format(angle(scaled_wc('eW_13')), '.6e'), '# ceWPh1x3'], [2, 1, format(angle(scaled_wc('eW_21')), '.6e'), '# ceWPh2x1'], [2, 2, format(angle(scaled_wc('eW_22')), '.6e'), '# ceWPh2x2'], [2, 3, format(angle(scaled_wc('eW_23')), '.6e'), '# ceWPh2x3'], [3, 1, format(angle(scaled_wc('eW_31')), '.6e'), '# ceWPh3x1'], [3, 2, format(angle(scaled_wc('eW_32')), '.6e'), '# ceWPh3x2'], [3, 3, format(angle(scaled_wc('eW_33')), '.6e'), '# ceWPh3x3'], ]} card['Block']['FRBlock18'] = {'values': [ [1, 1, format(abs(scaled_wc('eB_11'))* lambda_smeft_value**2, '.6e'), '# ceBAbs1x1'], [1, 2, format(abs(scaled_wc('eB_12'))* lambda_smeft_value**2, '.6e'), '# ceBAbs1x2'], [1, 3, format(abs(scaled_wc('eB_13'))* lambda_smeft_value**2, '.6e'), '# ceBAbs1x3'], [2, 1, format(abs(scaled_wc('eB_21'))* lambda_smeft_value**2, '.6e'), '# ceBAbs2x1'], [2, 2, format(abs(scaled_wc('eB_22'))* lambda_smeft_value**2, '.6e'), '# ceBAbs2x2'], [2, 3, format(abs(scaled_wc('eB_23'))* lambda_smeft_value**2, '.6e'), '# ceBAbs2x3'], [3, 1, format(abs(scaled_wc('eB_31'))* lambda_smeft_value**2, '.6e'), '# ceBAbs3x1'], [3, 2, format(abs(scaled_wc('eB_32'))* lambda_smeft_value**2, '.6e'), '# ceBAbs3x2'], [3, 3, format(abs(scaled_wc('eB_33'))* lambda_smeft_value**2, '.6e'), '# ceBAbs3x3'], ]} card['Block']['FRBlock19'] = {'values': [ [1, 1, format(angle(scaled_wc('eB_11')), '.6e'), '# ceBPh1x1'], [1, 2, format(angle(scaled_wc('eB_12')), '.6e'), '# ceBPh1x2'], [1, 3, format(angle(scaled_wc('eB_13')), '.6e'), '# ceBPh1x3'], [2, 1, format(angle(scaled_wc('eB_21')), '.6e'), '# ceBPh2x1'], [2, 2, format(angle(scaled_wc('eB_22')), '.6e'), '# ceBPh2x2'], [2, 3, format(angle(scaled_wc('eB_23')), '.6e'), '# ceBPh2x3'], [3, 1, format(angle(scaled_wc('eB_31')), '.6e'), '# ceBPh3x1'], [3, 2, format(angle(scaled_wc('eB_32')), '.6e'), '# ceBPh3x2'], [3, 3, format(angle(scaled_wc('eB_33')), '.6e'), '# ceBPh3x3'], ]} card['Block']['FRBlock21'] = {'values': [ [1, 1, format(abs(scaled_wc('uG_11'))* lambda_smeft_value**2, '.6e'), '# cuGAbs1x1'], [1, 2, format(abs(scaled_wc('uG_12'))* lambda_smeft_value**2, '.6e'), '# cuGAbs1x2'], [1, 3, format(abs(scaled_wc('uG_13'))* lambda_smeft_value**2, '.6e'), '# cuGAbs1x3'], [2, 1, format(abs(scaled_wc('uG_21'))* lambda_smeft_value**2, '.6e'), '# cuGAbs2x1'], [2, 2, format(abs(scaled_wc('uG_22'))* lambda_smeft_value**2, '.6e'), '# cuGAbs2x2'], [2, 3, format(abs(scaled_wc('uG_23'))* lambda_smeft_value**2, '.6e'), '# cuGAbs2x3'], [3, 1, format(abs(scaled_wc('uG_31'))* lambda_smeft_value**2, '.6e'), '# cuGAbs3x1'], [3, 2, format(abs(scaled_wc('uG_32'))* lambda_smeft_value**2, '.6e'), '# cuGAbs3x2'], [3, 3, format(abs(scaled_wc('uG_33'))* lambda_smeft_value**2, '.6e'), '# cuGAbs3x3'], ]} card['Block']['FRBlock22'] = {'values': [ [1, 1, format(angle(scaled_wc('uG_11')), '.6e'), '# cuGPh1x1'], [1, 2, format(angle(scaled_wc('uG_12')), '.6e'), '# cuGPh1x2'], [1, 3, format(angle(scaled_wc('uG_13')), '.6e'), '# cuGPh1x3'], [2, 1, format(angle(scaled_wc('uG_21')), '.6e'), '# cuGPh2x1'], [2, 2, format(angle(scaled_wc('uG_22')), '.6e'), '# cuGPh2x2'], [2, 3, format(angle(scaled_wc('uG_23')), '.6e'), '# cuGPh2x3'], [3, 1, format(angle(scaled_wc('uG_31')), '.6e'), '# cuGPh3x1'], [3, 2, format(angle(scaled_wc('uG_32')), '.6e'), '# cuGPh3x2'], [3, 3, format(angle(scaled_wc('uG_33')), '.6e'), '# cuGPh3x3'], ]} card['Block']['FRBlock24'] = {'values': [ [1, 1, format(abs(scaled_wc('uW_11'))* lambda_smeft_value**2, '.6e'), '# cuWAbs1x1'], [1, 2, format(abs(scaled_wc('uW_12'))* lambda_smeft_value**2, '.6e'), '# cuWAbs1x2'], [1, 3, format(abs(scaled_wc('uW_13'))* lambda_smeft_value**2, '.6e'), '# cuWAbs1x3'], [2, 1, format(abs(scaled_wc('uW_21'))* lambda_smeft_value**2, '.6e'), '# cuWAbs2x1'], [2, 2, format(abs(scaled_wc('uW_22'))* lambda_smeft_value**2, '.6e'), '# cuWAbs2x2'], [2, 3, format(abs(scaled_wc('uW_23'))* lambda_smeft_value**2, '.6e'), '# cuWAbs2x3'], [3, 1, format(abs(scaled_wc('uW_31'))* lambda_smeft_value**2, '.6e'), '# cuWAbs3x1'], [3, 2, format(abs(scaled_wc('uW_32'))* lambda_smeft_value**2, '.6e'), '# cuWAbs3x2'], [3, 3, format(abs(scaled_wc('uW_33'))* lambda_smeft_value**2, '.6e'), '# cuWAbs3x3'], ]} card['Block']['FRBlock25'] = {'values': [ [1, 1, format(angle(scaled_wc('uW_11')), '.6e'), '# cuWPh1x1'], [1, 2, format(angle(scaled_wc('uW_12')), '.6e'), '# cuWPh1x2'], [1, 3, format(angle(scaled_wc('uW_13')), '.6e'), '# cuWPh1x3'], [2, 1, format(angle(scaled_wc('uW_21')), '.6e'), '# cuWPh2x1'], [2, 2, format(angle(scaled_wc('uW_22')), '.6e'), '# cuWPh2x2'], [2, 3, format(angle(scaled_wc('uW_23')), '.6e'), '# cuWPh2x3'], [3, 1, format(angle(scaled_wc('uW_31')), '.6e'), '# cuWPh3x1'], [3, 2, format(angle(scaled_wc('uW_32')), '.6e'), '# cuWPh3x2'], [3, 3, format(angle(scaled_wc('uW_33')), '.6e'), '# cuWPh3x3'], ]} card['Block']['FRBlock27'] = {'values': [ [1, 1, format(abs(scaled_wc('uB_11'))* lambda_smeft_value**2, '.6e'), '# cuBAbs1x1'], [1, 2, format(abs(scaled_wc('uB_12'))* lambda_smeft_value**2, '.6e'), '# cuBAbs1x2'], [1, 3, format(abs(scaled_wc('uB_13'))* lambda_smeft_value**2, '.6e'), '# cuBAbs1x3'], [2, 1, format(abs(scaled_wc('uB_21'))* lambda_smeft_value**2, '.6e'), '# cuBAbs2x1'], [2, 2, format(abs(scaled_wc('uB_22'))* lambda_smeft_value**2, '.6e'), '# cuBAbs2x2'], [2, 3, format(abs(scaled_wc('uB_23'))* lambda_smeft_value**2, '.6e'), '# cuBAbs2x3'], [3, 1, format(abs(scaled_wc('uB_31'))* lambda_smeft_value**2, '.6e'), '# cuBAbs3x1'], [3, 2, format(abs(scaled_wc('uB_32'))* lambda_smeft_value**2, '.6e'), '# cuBAbs3x2'], [3, 3, format(abs(scaled_wc('uB_33'))* lambda_smeft_value**2, '.6e'), '# cuBAbs3x3'], ]} card['Block']['FRBlock28'] = {'values': [ [1, 1, format(angle(scaled_wc('uB_11')), '.6e'), '# cuBPh1x1'], [1, 2, format(angle(scaled_wc('uB_12')), '.6e'), '# cuBPh1x2'], [1, 3, format(angle(scaled_wc('uB_13')), '.6e'), '# cuBPh1x3'], [2, 1, format(angle(scaled_wc('uB_21')), '.6e'), '# cuBPh2x1'], [2, 2, format(angle(scaled_wc('uB_22')), '.6e'), '# cuBPh2x2'], [2, 3, format(angle(scaled_wc('uB_23')), '.6e'), '# cuBPh2x3'], [3, 1, format(angle(scaled_wc('uB_31')), '.6e'), '# cuBPh3x1'], [3, 2, format(angle(scaled_wc('uB_32')), '.6e'), '# cuBPh3x2'], [3, 3, format(angle(scaled_wc('uB_33')), '.6e'), '# cuBPh3x3'], ]} card['Block']['FRBlock30'] = {'values': [ [1, 1, format(abs(scaled_wc('dG_11'))* lambda_smeft_value**2, '.6e'), '# cdGAbs1x1'], [1, 2, format(abs(scaled_wc('dG_12'))* lambda_smeft_value**2, '.6e'), '# cdGAbs1x2'], [1, 3, format(abs(scaled_wc('dG_13'))* lambda_smeft_value**2, '.6e'), '# cdGAbs1x3'], [2, 1, format(abs(scaled_wc('dG_21'))* lambda_smeft_value**2, '.6e'), '# cdGAbs2x1'], [2, 2, format(abs(scaled_wc('dG_22'))* lambda_smeft_value**2, '.6e'), '# cdGAbs2x2'], [2, 3, format(abs(scaled_wc('dG_23'))* lambda_smeft_value**2, '.6e'), '# cdGAbs2x3'], [3, 1, format(abs(scaled_wc('dG_31'))* lambda_smeft_value**2, '.6e'), '# cdGAbs3x1'], [3, 2, format(abs(scaled_wc('dG_32'))* lambda_smeft_value**2, '.6e'), '# cdGAbs3x2'], [3, 3, format(abs(scaled_wc('dG_33'))* lambda_smeft_value**2, '.6e'), '# cdGAbs3x3'], ]} card['Block']['FRBlock31'] = {'values': [ [1, 1, format(angle(scaled_wc('dG_11')), '.6e'), '# cdGPh1x1'], [1, 2, format(angle(scaled_wc('dG_12')), '.6e'), '# cdGPh1x2'], [1, 3, format(angle(scaled_wc('dG_13')), '.6e'), '# cdGPh1x3'], [2, 1, format(angle(scaled_wc('dG_21')), '.6e'), '# cdGPh2x1'], [2, 2, format(angle(scaled_wc('dG_22')), '.6e'), '# cdGPh2x2'], [2, 3, format(angle(scaled_wc('dG_23')), '.6e'), '# cdGPh2x3'], [3, 1, format(angle(scaled_wc('dG_31')), '.6e'), '# cdGPh3x1'], [3, 2, format(angle(scaled_wc('dG_32')), '.6e'), '# cdGPh3x2'], [3, 3, format(angle(scaled_wc('dG_33')), '.6e'), '# cdGPh3x3'], ]} card['Block']['FRBlock33'] = {'values': [ [1, 1, format(abs(scaled_wc('dW_11'))* lambda_smeft_value**2, '.6e'), '# cdWAbs1x1'], [1, 2, format(abs(scaled_wc('dW_12'))* lambda_smeft_value**2, '.6e'), '# cdWAbs1x2'], [1, 3, format(abs(scaled_wc('dW_13'))* lambda_smeft_value**2, '.6e'), '# cdWAbs1x3'], [2, 1, format(abs(scaled_wc('dW_21'))* lambda_smeft_value**2, '.6e'), '# cdWAbs2x1'], [2, 2, format(abs(scaled_wc('dW_22'))* lambda_smeft_value**2, '.6e'), '# cdWAbs2x2'], [2, 3, format(abs(scaled_wc('dW_23'))* lambda_smeft_value**2, '.6e'), '# cdWAbs2x3'], [3, 1, format(abs(scaled_wc('dW_31'))* lambda_smeft_value**2, '.6e'), '# cdWAbs3x1'], [3, 2, format(abs(scaled_wc('dW_32'))* lambda_smeft_value**2, '.6e'), '# cdWAbs3x2'], [3, 3, format(abs(scaled_wc('dW_33'))* lambda_smeft_value**2, '.6e'), '# cdWAbs3x3'], ]} card['Block']['FRBlock34'] = {'values': [ [1, 1, format(angle(scaled_wc('dW_11')), '.6e'), '# cdWPh1x1'], [1, 2, format(angle(scaled_wc('dW_12')), '.6e'), '# cdWPh1x2'], [1, 3, format(angle(scaled_wc('dW_13')), '.6e'), '# cdWPh1x3'], [2, 1, format(angle(scaled_wc('dW_21')), '.6e'), '# cdWPh2x1'], [2, 2, format(angle(scaled_wc('dW_22')), '.6e'), '# cdWPh2x2'], [2, 3, format(angle(scaled_wc('dW_23')), '.6e'), '# cdWPh2x3'], [3, 1, format(angle(scaled_wc('dW_31')), '.6e'), '# cdWPh3x1'], [3, 2, format(angle(scaled_wc('dW_32')), '.6e'), '# cdWPh3x2'], [3, 3, format(angle(scaled_wc('dW_33')), '.6e'), '# cdWPh3x3'], ]} card['Block']['FRBlock36'] = {'values': [ [1, 1, format(abs(scaled_wc('dB_11'))* lambda_smeft_value**2, '.6e'), '# cdBAbs1x1'], [1, 2, format(abs(scaled_wc('dB_12'))* lambda_smeft_value**2, '.6e'), '# cdBAbs1x2'], [1, 3, format(abs(scaled_wc('dB_13'))* lambda_smeft_value**2, '.6e'), '# cdBAbs1x3'], [2, 1, format(abs(scaled_wc('dB_21'))* lambda_smeft_value**2, '.6e'), '# cdBAbs2x1'], [2, 2, format(abs(scaled_wc('dB_22'))* lambda_smeft_value**2, '.6e'), '# cdBAbs2x2'], [2, 3, format(abs(scaled_wc('dB_23'))* lambda_smeft_value**2, '.6e'), '# cdBAbs2x3'], [3, 1, format(abs(scaled_wc('dB_31'))* lambda_smeft_value**2, '.6e'), '# cdBAbs3x1'], [3, 2, format(abs(scaled_wc('dB_32'))* lambda_smeft_value**2, '.6e'), '# cdBAbs3x2'], [3, 3, format(abs(scaled_wc('dB_33'))* lambda_smeft_value**2, '.6e'), '# cdBAbs3x3'], ]} card['Block']['FRBlock37'] = {'values': [ [1, 1, format(angle(scaled_wc('dB_11')), '.6e'), '# cdBPh1x1'], [1, 2, format(angle(scaled_wc('dB_12')), '.6e'), '# cdBPh1x2'], [1, 3, format(angle(scaled_wc('dB_13')), '.6e'), '# cdBPh1x3'], [2, 1, format(angle(scaled_wc('dB_21')), '.6e'), '# cdBPh2x1'], [2, 2, format(angle(scaled_wc('dB_22')), '.6e'), '# cdBPh2x2'], [2, 3, format(angle(scaled_wc('dB_23')), '.6e'), '# cdBPh2x3'], [3, 1, format(angle(scaled_wc('dB_31')), '.6e'), '# cdBPh3x1'], [3, 2, format(angle(scaled_wc('dB_32')), '.6e'), '# cdBPh3x2'], [3, 3, format(angle(scaled_wc('dB_33')), '.6e'), '# cdBPh3x3'], ]} card['Block']['FRBlock45'] = {'values': [ [1, 1, format(abs(scaled_wc('phiud_11'))* lambda_smeft_value**2, '.6e'), '# cHudAbs1x1'], [1, 2, format(abs(scaled_wc('phiud_12'))* lambda_smeft_value**2, '.6e'), '# cHudAbs1x2'], [1, 3, format(abs(scaled_wc('phiud_13'))* lambda_smeft_value**2, '.6e'), '# cHudAbs1x3'], [2, 1, format(abs(scaled_wc('phiud_21'))* lambda_smeft_value**2, '.6e'), '# cHudAbs2x1'], [2, 2, format(abs(scaled_wc('phiud_22'))* lambda_smeft_value**2, '.6e'), '# cHudAbs2x2'], [2, 3, format(abs(scaled_wc('phiud_23'))* lambda_smeft_value**2, '.6e'), '# cHudAbs2x3'], [3, 1, format(abs(scaled_wc('phiud_31'))* lambda_smeft_value**2, '.6e'), '# cHudAbs3x1'], [3, 2, format(abs(scaled_wc('phiud_32'))* lambda_smeft_value**2, '.6e'), '# cHudAbs3x2'], [3, 3, format(abs(scaled_wc('phiud_33'))* lambda_smeft_value**2, '.6e'), '# cHudAbs3x3'], ]} card['Block']['FRBlock46'] = {'values': [ [1, 1, format(angle(scaled_wc('phiud_11')), '.6e'), '# cHudPh1x1'], [1, 2, format(angle(scaled_wc('phiud_12')), '.6e'), '# cHudPh1x2'], [1, 3, format(angle(scaled_wc('phiud_13')), '.6e'), '# cHudPh1x3'], [2, 1, format(angle(scaled_wc('phiud_21')), '.6e'), '# cHudPh2x1'], [2, 2, format(angle(scaled_wc('phiud_22')), '.6e'), '# cHudPh2x2'], [2, 3, format(angle(scaled_wc('phiud_23')), '.6e'), '# cHudPh2x3'], [3, 1, format(angle(scaled_wc('phiud_31')), '.6e'), '# cHudPh3x1'], [3, 2, format(angle(scaled_wc('phiud_32')), '.6e'), '# cHudPh3x2'], [3, 3, format(angle(scaled_wc('phiud_33')), '.6e'), '# cHudPh3x3'], ]} card['Block']['FRBlock6'] = {'values': [ [1, 1, format(abs(scaled_wc('ephi_11'))* lambda_smeft_value**2, '.6e'), '# ceHAbs1x1'], [1, 2, format(abs(scaled_wc('ephi_12'))* lambda_smeft_value**2, '.6e'), '# ceHAbs1x2'], [1, 3, format(abs(scaled_wc('ephi_13'))* lambda_smeft_value**2, '.6e'), '# ceHAbs1x3'], [2, 1, format(abs(scaled_wc('ephi_21'))* lambda_smeft_value**2, '.6e'), '# ceHAbs2x1'], [2, 2, format(abs(scaled_wc('ephi_22'))* lambda_smeft_value**2, '.6e'), '# ceHAbs2x2'], [2, 3, format(abs(scaled_wc('ephi_23'))* lambda_smeft_value**2, '.6e'), '# ceHAbs2x3'], [3, 1, format(abs(scaled_wc('ephi_31'))* lambda_smeft_value**2, '.6e'), '# ceHAbs3x1'], [3, 2, format(abs(scaled_wc('ephi_32'))* lambda_smeft_value**2, '.6e'), '# ceHAbs3x2'], [3, 3, format(abs(scaled_wc('ephi_33'))* lambda_smeft_value**2, '.6e'), '# ceHAbs3x3'], ]} card['Block']['FRBlock69'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('ledq_1111'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('ledq_1112'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('ledq_1113'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('ledq_1121'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('ledq_1122'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('ledq_1123'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('ledq_1131'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('ledq_1132'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('ledq_1133'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('ledq_1211'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('ledq_1212'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('ledq_1213'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('ledq_1221'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('ledq_1222'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('ledq_1223'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('ledq_1231'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('ledq_1232'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('ledq_1233'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('ledq_1311'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('ledq_1312'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('ledq_1313'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('ledq_1321'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('ledq_1322'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('ledq_1323'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('ledq_1331'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('ledq_1332'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('ledq_1333'))* lambda_smeft_value**2, '.6e'), '# cledqAbs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('ledq_2111'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('ledq_2112'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('ledq_2113'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('ledq_2121'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('ledq_2122'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('ledq_2123'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('ledq_2131'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('ledq_2132'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('ledq_2133'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('ledq_2211'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('ledq_2212'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('ledq_2213'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('ledq_2221'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('ledq_2222'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('ledq_2223'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('ledq_2231'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('ledq_2232'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('ledq_2233'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('ledq_2311'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('ledq_2312'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('ledq_2313'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('ledq_2321'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('ledq_2322'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('ledq_2323'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('ledq_2331'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('ledq_2332'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('ledq_2333'))* lambda_smeft_value**2, '.6e'), '# cledqAbs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('ledq_3111'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('ledq_3112'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('ledq_3113'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('ledq_3121'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('ledq_3122'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('ledq_3123'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('ledq_3131'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('ledq_3132'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('ledq_3133'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('ledq_3211'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('ledq_3212'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('ledq_3213'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('ledq_3221'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('ledq_3222'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('ledq_3223'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('ledq_3231'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('ledq_3232'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('ledq_3233'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('ledq_3311'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('ledq_3312'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('ledq_3313'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('ledq_3321'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('ledq_3322'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('ledq_3323'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('ledq_3331'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('ledq_3332'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('ledq_3333'))* lambda_smeft_value**2, '.6e'), '# cledqAbs3x3x3x3'], ]} card['Block']['FRBlock7'] = {'values': [ [1, 1, format(abs(scaled_wc('uphi_11'))* lambda_smeft_value**2, '.6e'), '# cuHAbs1x1'], [1, 2, format(abs(scaled_wc('uphi_12'))* lambda_smeft_value**2, '.6e'), '# cuHAbs1x2'], [1, 3, format(abs(scaled_wc('uphi_13'))* lambda_smeft_value**2, '.6e'), '# cuHAbs1x3'], [2, 1, format(abs(scaled_wc('uphi_21'))* lambda_smeft_value**2, '.6e'), '# cuHAbs2x1'], [2, 2, format(abs(scaled_wc('uphi_22'))* lambda_smeft_value**2, '.6e'), '# cuHAbs2x2'], [2, 3, format(abs(scaled_wc('uphi_23'))* lambda_smeft_value**2, '.6e'), '# cuHAbs2x3'], [3, 1, format(abs(scaled_wc('uphi_31'))* lambda_smeft_value**2, '.6e'), '# cuHAbs3x1'], [3, 2, format(abs(scaled_wc('uphi_32'))* lambda_smeft_value**2, '.6e'), '# cuHAbs3x2'], [3, 3, format(abs(scaled_wc('uphi_33'))* lambda_smeft_value**2, '.6e'), '# cuHAbs3x3'], ]} card['Block']['FRBlock70'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('ledq_1111')), '.6e'), '# cledqPh1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('ledq_1112')), '.6e'), '# cledqPh1x1x1x2'], [1, 1, 1, 3, format(angle(scaled_wc('ledq_1113')), '.6e'), '# cledqPh1x1x1x3'], [1, 1, 2, 1, format(angle(scaled_wc('ledq_1121')), '.6e'), '# cledqPh1x1x2x1'], [1, 1, 2, 2, format(angle(scaled_wc('ledq_1122')), '.6e'), '# cledqPh1x1x2x2'], [1, 1, 2, 3, format(angle(scaled_wc('ledq_1123')), '.6e'), '# cledqPh1x1x2x3'], [1, 1, 3, 1, format(angle(scaled_wc('ledq_1131')), '.6e'), '# cledqPh1x1x3x1'], [1, 1, 3, 2, format(angle(scaled_wc('ledq_1132')), '.6e'), '# cledqPh1x1x3x2'], [1, 1, 3, 3, format(angle(scaled_wc('ledq_1133')), '.6e'), '# cledqPh1x1x3x3'], [1, 2, 1, 1, format(angle(scaled_wc('ledq_1211')), '.6e'), '# cledqPh1x2x1x1'], [1, 2, 1, 2, format(angle(scaled_wc('ledq_1212')), '.6e'), '# cledqPh1x2x1x2'], [1, 2, 1, 3, format(angle(scaled_wc('ledq_1213')), '.6e'), '# cledqPh1x2x1x3'], [1, 2, 2, 1, format(angle(scaled_wc('ledq_1221')), '.6e'), '# cledqPh1x2x2x1'], [1, 2, 2, 2, format(angle(scaled_wc('ledq_1222')), '.6e'), '# cledqPh1x2x2x2'], [1, 2, 2, 3, format(angle(scaled_wc('ledq_1223')), '.6e'), '# cledqPh1x2x2x3'], [1, 2, 3, 1, format(angle(scaled_wc('ledq_1231')), '.6e'), '# cledqPh1x2x3x1'], [1, 2, 3, 2, format(angle(scaled_wc('ledq_1232')), '.6e'), '# cledqPh1x2x3x2'], [1, 2, 3, 3, format(angle(scaled_wc('ledq_1233')), '.6e'), '# cledqPh1x2x3x3'], [1, 3, 1, 1, format(angle(scaled_wc('ledq_1311')), '.6e'), '# cledqPh1x3x1x1'], [1, 3, 1, 2, format(angle(scaled_wc('ledq_1312')), '.6e'), '# cledqPh1x3x1x2'], [1, 3, 1, 3, format(angle(scaled_wc('ledq_1313')), '.6e'), '# cledqPh1x3x1x3'], [1, 3, 2, 1, format(angle(scaled_wc('ledq_1321')), '.6e'), '# cledqPh1x3x2x1'], [1, 3, 2, 2, format(angle(scaled_wc('ledq_1322')), '.6e'), '# cledqPh1x3x2x2'], [1, 3, 2, 3, format(angle(scaled_wc('ledq_1323')), '.6e'), '# cledqPh1x3x2x3'], [1, 3, 3, 1, format(angle(scaled_wc('ledq_1331')), '.6e'), '# cledqPh1x3x3x1'], [1, 3, 3, 2, format(angle(scaled_wc('ledq_1332')), '.6e'), '# cledqPh1x3x3x2'], [1, 3, 3, 3, format(angle(scaled_wc('ledq_1333')), '.6e'), '# cledqPh1x3x3x3'], [2, 1, 1, 1, format(angle(scaled_wc('ledq_2111')), '.6e'), '# cledqPh2x1x1x1'], [2, 1, 1, 2, format(angle(scaled_wc('ledq_2112')), '.6e'), '# cledqPh2x1x1x2'], [2, 1, 1, 3, format(angle(scaled_wc('ledq_2113')), '.6e'), '# cledqPh2x1x1x3'], [2, 1, 2, 1, format(angle(scaled_wc('ledq_2121')), '.6e'), '# cledqPh2x1x2x1'], [2, 1, 2, 2, format(angle(scaled_wc('ledq_2122')), '.6e'), '# cledqPh2x1x2x2'], [2, 1, 2, 3, format(angle(scaled_wc('ledq_2123')), '.6e'), '# cledqPh2x1x2x3'], [2, 1, 3, 1, format(angle(scaled_wc('ledq_2131')), '.6e'), '# cledqPh2x1x3x1'], [2, 1, 3, 2, format(angle(scaled_wc('ledq_2132')), '.6e'), '# cledqPh2x1x3x2'], [2, 1, 3, 3, format(angle(scaled_wc('ledq_2133')), '.6e'), '# cledqPh2x1x3x3'], [2, 2, 1, 1, format(angle(scaled_wc('ledq_2211')), '.6e'), '# cledqPh2x2x1x1'], [2, 2, 1, 2, format(angle(scaled_wc('ledq_2212')), '.6e'), '# cledqPh2x2x1x2'], [2, 2, 1, 3, format(angle(scaled_wc('ledq_2213')), '.6e'), '# cledqPh2x2x1x3'], [2, 2, 2, 1, format(angle(scaled_wc('ledq_2221')), '.6e'), '# cledqPh2x2x2x1'], [2, 2, 2, 2, format(angle(scaled_wc('ledq_2222')), '.6e'), '# cledqPh2x2x2x2'], [2, 2, 2, 3, format(angle(scaled_wc('ledq_2223')), '.6e'), '# cledqPh2x2x2x3'], [2, 2, 3, 1, format(angle(scaled_wc('ledq_2231')), '.6e'), '# cledqPh2x2x3x1'], [2, 2, 3, 2, format(angle(scaled_wc('ledq_2232')), '.6e'), '# cledqPh2x2x3x2'], [2, 2, 3, 3, format(angle(scaled_wc('ledq_2233')), '.6e'), '# cledqPh2x2x3x3'], [2, 3, 1, 1, format(angle(scaled_wc('ledq_2311')), '.6e'), '# cledqPh2x3x1x1'], [2, 3, 1, 2, format(angle(scaled_wc('ledq_2312')), '.6e'), '# cledqPh2x3x1x2'], [2, 3, 1, 3, format(angle(scaled_wc('ledq_2313')), '.6e'), '# cledqPh2x3x1x3'], [2, 3, 2, 1, format(angle(scaled_wc('ledq_2321')), '.6e'), '# cledqPh2x3x2x1'], [2, 3, 2, 2, format(angle(scaled_wc('ledq_2322')), '.6e'), '# cledqPh2x3x2x2'], [2, 3, 2, 3, format(angle(scaled_wc('ledq_2323')), '.6e'), '# cledqPh2x3x2x3'], [2, 3, 3, 1, format(angle(scaled_wc('ledq_2331')), '.6e'), '# cledqPh2x3x3x1'], [2, 3, 3, 2, format(angle(scaled_wc('ledq_2332')), '.6e'), '# cledqPh2x3x3x2'], [2, 3, 3, 3, format(angle(scaled_wc('ledq_2333')), '.6e'), '# cledqPh2x3x3x3'], [3, 1, 1, 1, format(angle(scaled_wc('ledq_3111')), '.6e'), '# cledqPh3x1x1x1'], [3, 1, 1, 2, format(angle(scaled_wc('ledq_3112')), '.6e'), '# cledqPh3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('ledq_3113')), '.6e'), '# cledqPh3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('ledq_3121')), '.6e'), '# cledqPh3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('ledq_3122')), '.6e'), '# cledqPh3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('ledq_3123')), '.6e'), '# cledqPh3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('ledq_3131')), '.6e'), '# cledqPh3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('ledq_3132')), '.6e'), '# cledqPh3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('ledq_3133')), '.6e'), '# cledqPh3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('ledq_3211')), '.6e'), '# cledqPh3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('ledq_3212')), '.6e'), '# cledqPh3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('ledq_3213')), '.6e'), '# cledqPh3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('ledq_3221')), '.6e'), '# cledqPh3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('ledq_3222')), '.6e'), '# cledqPh3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('ledq_3223')), '.6e'), '# cledqPh3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('ledq_3231')), '.6e'), '# cledqPh3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('ledq_3232')), '.6e'), '# cledqPh3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('ledq_3233')), '.6e'), '# cledqPh3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('ledq_3311')), '.6e'), '# cledqPh3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('ledq_3312')), '.6e'), '# cledqPh3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('ledq_3313')), '.6e'), '# cledqPh3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('ledq_3321')), '.6e'), '# cledqPh3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('ledq_3322')), '.6e'), '# cledqPh3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('ledq_3323')), '.6e'), '# cledqPh3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('ledq_3331')), '.6e'), '# cledqPh3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('ledq_3332')), '.6e'), '# cledqPh3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('ledq_3333')), '.6e'), '# cledqPh3x3x3x3'], ]} card['Block']['FRBlock72'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('quqd1_1111'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('quqd1_1112'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('quqd1_1113'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('quqd1_1121'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('quqd1_1122'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('quqd1_1123'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('quqd1_1131'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('quqd1_1132'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('quqd1_1133'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('quqd1_1211'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('quqd1_1212'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('quqd1_1213'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('quqd1_1221'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('quqd1_1222'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('quqd1_1223'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('quqd1_1231'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('quqd1_1232'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('quqd1_1233'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('quqd1_1311'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('quqd1_1312'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('quqd1_1313'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('quqd1_1321'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('quqd1_1322'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('quqd1_1323'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('quqd1_1331'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('quqd1_1332'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('quqd1_1333'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('quqd1_2111'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('quqd1_2112'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('quqd1_2113'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('quqd1_2121'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('quqd1_2122'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('quqd1_2123'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('quqd1_2131'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('quqd1_2132'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('quqd1_2133'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('quqd1_2211'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('quqd1_2212'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('quqd1_2213'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('quqd1_2221'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('quqd1_2222'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('quqd1_2223'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('quqd1_2231'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('quqd1_2232'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('quqd1_2233'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('quqd1_2311'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('quqd1_2312'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('quqd1_2313'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('quqd1_2321'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('quqd1_2322'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('quqd1_2323'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('quqd1_2331'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('quqd1_2332'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('quqd1_2333'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('quqd1_3111'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('quqd1_3112'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('quqd1_3113'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('quqd1_3121'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('quqd1_3122'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('quqd1_3123'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('quqd1_3131'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('quqd1_3132'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('quqd1_3133'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('quqd1_3211'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('quqd1_3212'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('quqd1_3213'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('quqd1_3221'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('quqd1_3222'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('quqd1_3223'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('quqd1_3231'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('quqd1_3232'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('quqd1_3233'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('quqd1_3311'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('quqd1_3312'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('quqd1_3313'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('quqd1_3321'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('quqd1_3322'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('quqd1_3323'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('quqd1_3331'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('quqd1_3332'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('quqd1_3333'))* lambda_smeft_value**2, '.6e'), '# cquqd1Abs3x3x3x3'], ]} card['Block']['FRBlock73'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('quqd1_1111')), '.6e'), '# cquqd1Ph1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('quqd1_1112')), '.6e'), '# cquqd1Ph1x1x1x2'], [1, 1, 1, 3, format(angle(scaled_wc('quqd1_1113')), '.6e'), '# cquqd1Ph1x1x1x3'], [1, 1, 2, 1, format(angle(scaled_wc('quqd1_1121')), '.6e'), '# cquqd1Ph1x1x2x1'], [1, 1, 2, 2, format(angle(scaled_wc('quqd1_1122')), '.6e'), '# cquqd1Ph1x1x2x2'], [1, 1, 2, 3, format(angle(scaled_wc('quqd1_1123')), '.6e'), '# cquqd1Ph1x1x2x3'], [1, 1, 3, 1, format(angle(scaled_wc('quqd1_1131')), '.6e'), '# cquqd1Ph1x1x3x1'], [1, 1, 3, 2, format(angle(scaled_wc('quqd1_1132')), '.6e'), '# cquqd1Ph1x1x3x2'], [1, 1, 3, 3, format(angle(scaled_wc('quqd1_1133')), '.6e'), '# cquqd1Ph1x1x3x3'], [1, 2, 1, 1, format(angle(scaled_wc('quqd1_1211')), '.6e'), '# cquqd1Ph1x2x1x1'], [1, 2, 1, 2, format(angle(scaled_wc('quqd1_1212')), '.6e'), '# cquqd1Ph1x2x1x2'], [1, 2, 1, 3, format(angle(scaled_wc('quqd1_1213')), '.6e'), '# cquqd1Ph1x2x1x3'], [1, 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format(angle(scaled_wc('quqd1_2211')), '.6e'), '# cquqd1Ph2x2x1x1'], [2, 2, 1, 2, format(angle(scaled_wc('quqd1_2212')), '.6e'), '# cquqd1Ph2x2x1x2'], [2, 2, 1, 3, format(angle(scaled_wc('quqd1_2213')), '.6e'), '# cquqd1Ph2x2x1x3'], [2, 2, 2, 1, format(angle(scaled_wc('quqd1_2221')), '.6e'), '# cquqd1Ph2x2x2x1'], [2, 2, 2, 2, format(angle(scaled_wc('quqd1_2222')), '.6e'), '# cquqd1Ph2x2x2x2'], [2, 2, 2, 3, format(angle(scaled_wc('quqd1_2223')), '.6e'), '# cquqd1Ph2x2x2x3'], [2, 2, 3, 1, format(angle(scaled_wc('quqd1_2231')), '.6e'), '# cquqd1Ph2x2x3x1'], [2, 2, 3, 2, format(angle(scaled_wc('quqd1_2232')), '.6e'), '# cquqd1Ph2x2x3x2'], [2, 2, 3, 3, format(angle(scaled_wc('quqd1_2233')), '.6e'), '# cquqd1Ph2x2x3x3'], [2, 3, 1, 1, format(angle(scaled_wc('quqd1_2311')), '.6e'), '# cquqd1Ph2x3x1x1'], [2, 3, 1, 2, format(angle(scaled_wc('quqd1_2312')), '.6e'), '# cquqd1Ph2x3x1x2'], [2, 3, 1, 3, format(angle(scaled_wc('quqd1_2313')), '.6e'), '# cquqd1Ph2x3x1x3'], [2, 3, 2, 1, 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format(angle(scaled_wc('quqd1_3131')), '.6e'), '# cquqd1Ph3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('quqd1_3132')), '.6e'), '# cquqd1Ph3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('quqd1_3133')), '.6e'), '# cquqd1Ph3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('quqd1_3211')), '.6e'), '# cquqd1Ph3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('quqd1_3212')), '.6e'), '# cquqd1Ph3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('quqd1_3213')), '.6e'), '# cquqd1Ph3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('quqd1_3221')), '.6e'), '# cquqd1Ph3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('quqd1_3222')), '.6e'), '# cquqd1Ph3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('quqd1_3223')), '.6e'), '# cquqd1Ph3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('quqd1_3231')), '.6e'), '# cquqd1Ph3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('quqd1_3232')), '.6e'), '# cquqd1Ph3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('quqd1_3233')), '.6e'), '# cquqd1Ph3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('quqd1_3311')), '.6e'), '# cquqd1Ph3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('quqd1_3312')), '.6e'), '# cquqd1Ph3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('quqd1_3313')), '.6e'), '# cquqd1Ph3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('quqd1_3321')), '.6e'), '# cquqd1Ph3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('quqd1_3322')), '.6e'), '# cquqd1Ph3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('quqd1_3323')), '.6e'), '# cquqd1Ph3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('quqd1_3331')), '.6e'), '# cquqd1Ph3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('quqd1_3332')), '.6e'), '# cquqd1Ph3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('quqd1_3333')), '.6e'), '# cquqd1Ph3x3x3x3'], ]} card['Block']['FRBlock75'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('quqd8_1111'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('quqd8_1112'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs1x1x1x2'], [1, 1, 1, 3, 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'.6e'), '# cQUQD8Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('quqd8_2323'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('quqd8_2331'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('quqd8_2332'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('quqd8_2333'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('quqd8_3111'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('quqd8_3112'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('quqd8_3113'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('quqd8_3121'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('quqd8_3122'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('quqd8_3123'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('quqd8_3131'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('quqd8_3132'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('quqd8_3133'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('quqd8_3211'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('quqd8_3212'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('quqd8_3213'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('quqd8_3221'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('quqd8_3222'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('quqd8_3223'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('quqd8_3231'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('quqd8_3232'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('quqd8_3233'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('quqd8_3311'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('quqd8_3312'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('quqd8_3313'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('quqd8_3321'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('quqd8_3322'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('quqd8_3323'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('quqd8_3331'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('quqd8_3332'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('quqd8_3333'))* lambda_smeft_value**2, '.6e'), '# cQUQD8Abs3x3x3x3'], ]} card['Block']['FRBlock76'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('quqd8_1111')), '.6e'), '# cQUQD8Ph1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('quqd8_1112')), '.6e'), '# cQUQD8Ph1x1x1x2'], [1, 1, 1, 3, format(angle(scaled_wc('quqd8_1113')), '.6e'), '# cQUQD8Ph1x1x1x3'], [1, 1, 2, 1, format(angle(scaled_wc('quqd8_1121')), '.6e'), '# cQUQD8Ph1x1x2x1'], [1, 1, 2, 2, format(angle(scaled_wc('quqd8_1122')), '.6e'), '# cQUQD8Ph1x1x2x2'], [1, 1, 2, 3, format(angle(scaled_wc('quqd8_1123')), '.6e'), '# cQUQD8Ph1x1x2x3'], [1, 1, 3, 1, format(angle(scaled_wc('quqd8_1131')), '.6e'), '# cQUQD8Ph1x1x3x1'], [1, 1, 3, 2, format(angle(scaled_wc('quqd8_1132')), '.6e'), '# cQUQD8Ph1x1x3x2'], [1, 1, 3, 3, format(angle(scaled_wc('quqd8_1133')), '.6e'), '# cQUQD8Ph1x1x3x3'], [1, 2, 1, 1, format(angle(scaled_wc('quqd8_1211')), '.6e'), '# cQUQD8Ph1x2x1x1'], [1, 2, 1, 2, format(angle(scaled_wc('quqd8_1212')), '.6e'), '# cQUQD8Ph1x2x1x2'], [1, 2, 1, 3, format(angle(scaled_wc('quqd8_1213')), '.6e'), '# cQUQD8Ph1x2x1x3'], [1, 2, 2, 1, format(angle(scaled_wc('quqd8_1221')), '.6e'), '# cQUQD8Ph1x2x2x1'], [1, 2, 2, 2, format(angle(scaled_wc('quqd8_1222')), '.6e'), '# cQUQD8Ph1x2x2x2'], [1, 2, 2, 3, format(angle(scaled_wc('quqd8_1223')), '.6e'), '# cQUQD8Ph1x2x2x3'], [1, 2, 3, 1, format(angle(scaled_wc('quqd8_1231')), '.6e'), '# cQUQD8Ph1x2x3x1'], [1, 2, 3, 2, format(angle(scaled_wc('quqd8_1232')), '.6e'), '# cQUQD8Ph1x2x3x2'], [1, 2, 3, 3, format(angle(scaled_wc('quqd8_1233')), '.6e'), '# cQUQD8Ph1x2x3x3'], [1, 3, 1, 1, format(angle(scaled_wc('quqd8_1311')), '.6e'), '# cQUQD8Ph1x3x1x1'], [1, 3, 1, 2, format(angle(scaled_wc('quqd8_1312')), '.6e'), '# cQUQD8Ph1x3x1x2'], [1, 3, 1, 3, format(angle(scaled_wc('quqd8_1313')), '.6e'), '# cQUQD8Ph1x3x1x3'], [1, 3, 2, 1, format(angle(scaled_wc('quqd8_1321')), '.6e'), '# cQUQD8Ph1x3x2x1'], [1, 3, 2, 2, format(angle(scaled_wc('quqd8_1322')), '.6e'), '# cQUQD8Ph1x3x2x2'], [1, 3, 2, 3, format(angle(scaled_wc('quqd8_1323')), '.6e'), '# cQUQD8Ph1x3x2x3'], [1, 3, 3, 1, format(angle(scaled_wc('quqd8_1331')), '.6e'), '# cQUQD8Ph1x3x3x1'], [1, 3, 3, 2, format(angle(scaled_wc('quqd8_1332')), '.6e'), '# cQUQD8Ph1x3x3x2'], [1, 3, 3, 3, format(angle(scaled_wc('quqd8_1333')), '.6e'), '# cQUQD8Ph1x3x3x3'], [2, 1, 1, 1, format(angle(scaled_wc('quqd8_2111')), '.6e'), '# cQUQD8Ph2x1x1x1'], [2, 1, 1, 2, format(angle(scaled_wc('quqd8_2112')), '.6e'), '# cQUQD8Ph2x1x1x2'], [2, 1, 1, 3, format(angle(scaled_wc('quqd8_2113')), '.6e'), '# cQUQD8Ph2x1x1x3'], [2, 1, 2, 1, format(angle(scaled_wc('quqd8_2121')), '.6e'), '# cQUQD8Ph2x1x2x1'], [2, 1, 2, 2, format(angle(scaled_wc('quqd8_2122')), '.6e'), '# cQUQD8Ph2x1x2x2'], [2, 1, 2, 3, format(angle(scaled_wc('quqd8_2123')), '.6e'), '# cQUQD8Ph2x1x2x3'], [2, 1, 3, 1, format(angle(scaled_wc('quqd8_2131')), '.6e'), '# cQUQD8Ph2x1x3x1'], [2, 1, 3, 2, format(angle(scaled_wc('quqd8_2132')), '.6e'), '# cQUQD8Ph2x1x3x2'], [2, 1, 3, 3, format(angle(scaled_wc('quqd8_2133')), '.6e'), '# cQUQD8Ph2x1x3x3'], [2, 2, 1, 1, format(angle(scaled_wc('quqd8_2211')), '.6e'), '# cQUQD8Ph2x2x1x1'], [2, 2, 1, 2, format(angle(scaled_wc('quqd8_2212')), '.6e'), '# cQUQD8Ph2x2x1x2'], [2, 2, 1, 3, format(angle(scaled_wc('quqd8_2213')), '.6e'), '# cQUQD8Ph2x2x1x3'], [2, 2, 2, 1, format(angle(scaled_wc('quqd8_2221')), '.6e'), '# cQUQD8Ph2x2x2x1'], [2, 2, 2, 2, format(angle(scaled_wc('quqd8_2222')), '.6e'), '# cQUQD8Ph2x2x2x2'], [2, 2, 2, 3, format(angle(scaled_wc('quqd8_2223')), '.6e'), '# cQUQD8Ph2x2x2x3'], [2, 2, 3, 1, format(angle(scaled_wc('quqd8_2231')), '.6e'), '# cQUQD8Ph2x2x3x1'], [2, 2, 3, 2, format(angle(scaled_wc('quqd8_2232')), '.6e'), '# cQUQD8Ph2x2x3x2'], [2, 2, 3, 3, format(angle(scaled_wc('quqd8_2233')), '.6e'), '# cQUQD8Ph2x2x3x3'], [2, 3, 1, 1, format(angle(scaled_wc('quqd8_2311')), '.6e'), '# cQUQD8Ph2x3x1x1'], [2, 3, 1, 2, format(angle(scaled_wc('quqd8_2312')), '.6e'), '# cQUQD8Ph2x3x1x2'], [2, 3, 1, 3, format(angle(scaled_wc('quqd8_2313')), '.6e'), '# cQUQD8Ph2x3x1x3'], [2, 3, 2, 1, format(angle(scaled_wc('quqd8_2321')), '.6e'), '# cQUQD8Ph2x3x2x1'], [2, 3, 2, 2, format(angle(scaled_wc('quqd8_2322')), '.6e'), '# cQUQD8Ph2x3x2x2'], [2, 3, 2, 3, format(angle(scaled_wc('quqd8_2323')), '.6e'), '# cQUQD8Ph2x3x2x3'], [2, 3, 3, 1, format(angle(scaled_wc('quqd8_2331')), '.6e'), '# cQUQD8Ph2x3x3x1'], [2, 3, 3, 2, format(angle(scaled_wc('quqd8_2332')), '.6e'), '# cQUQD8Ph2x3x3x2'], [2, 3, 3, 3, format(angle(scaled_wc('quqd8_2333')), '.6e'), '# cQUQD8Ph2x3x3x3'], [3, 1, 1, 1, format(angle(scaled_wc('quqd8_3111')), '.6e'), '# cQUQD8Ph3x1x1x1'], [3, 1, 1, 2, format(angle(scaled_wc('quqd8_3112')), '.6e'), '# cQUQD8Ph3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('quqd8_3113')), '.6e'), '# cQUQD8Ph3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('quqd8_3121')), '.6e'), '# cQUQD8Ph3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('quqd8_3122')), '.6e'), '# cQUQD8Ph3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('quqd8_3123')), '.6e'), '# cQUQD8Ph3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('quqd8_3131')), '.6e'), '# cQUQD8Ph3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('quqd8_3132')), '.6e'), '# cQUQD8Ph3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('quqd8_3133')), '.6e'), '# cQUQD8Ph3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('quqd8_3211')), '.6e'), '# cQUQD8Ph3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('quqd8_3212')), '.6e'), '# cQUQD8Ph3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('quqd8_3213')), '.6e'), '# cQUQD8Ph3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('quqd8_3221')), '.6e'), '# cQUQD8Ph3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('quqd8_3222')), '.6e'), '# cQUQD8Ph3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('quqd8_3223')), '.6e'), '# cQUQD8Ph3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('quqd8_3231')), '.6e'), '# cQUQD8Ph3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('quqd8_3232')), '.6e'), '# cQUQD8Ph3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('quqd8_3233')), '.6e'), '# cQUQD8Ph3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('quqd8_3311')), '.6e'), '# cQUQD8Ph3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('quqd8_3312')), '.6e'), '# cQUQD8Ph3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('quqd8_3313')), '.6e'), '# cQUQD8Ph3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('quqd8_3321')), '.6e'), '# cQUQD8Ph3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('quqd8_3322')), '.6e'), '# cQUQD8Ph3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('quqd8_3323')), '.6e'), '# cQUQD8Ph3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('quqd8_3331')), '.6e'), '# cQUQD8Ph3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('quqd8_3332')), '.6e'), '# cQUQD8Ph3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('quqd8_3333')), '.6e'), '# cQUQD8Ph3x3x3x3'], ]} card['Block']['FRBlock78'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('lequ1_1111'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('lequ1_1112'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('lequ1_1113'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('lequ1_1121'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('lequ1_1122'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('lequ1_1123'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('lequ1_1131'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('lequ1_1132'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('lequ1_1133'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('lequ1_1211'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('lequ1_1212'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('lequ1_1213'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('lequ1_1221'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('lequ1_1222'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('lequ1_1223'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('lequ1_1231'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('lequ1_1232'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('lequ1_1233'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('lequ1_1311'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('lequ1_1312'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('lequ1_1313'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('lequ1_1321'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('lequ1_1322'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('lequ1_1323'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('lequ1_1331'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('lequ1_1332'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('lequ1_1333'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('lequ1_2111'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('lequ1_2112'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('lequ1_2113'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('lequ1_2121'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('lequ1_2122'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('lequ1_2123'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('lequ1_2131'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('lequ1_2132'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('lequ1_2133'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('lequ1_2211'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('lequ1_2212'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('lequ1_2213'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('lequ1_2221'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('lequ1_2222'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('lequ1_2223'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('lequ1_2231'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('lequ1_2232'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('lequ1_2233'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('lequ1_2311'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('lequ1_2312'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('lequ1_2313'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('lequ1_2321'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('lequ1_2322'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('lequ1_2323'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('lequ1_2331'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('lequ1_2332'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('lequ1_2333'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('lequ1_3111'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('lequ1_3112'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('lequ1_3113'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('lequ1_3121'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('lequ1_3122'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('lequ1_3123'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('lequ1_3131'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('lequ1_3132'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('lequ1_3133'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('lequ1_3211'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('lequ1_3212'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('lequ1_3213'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('lequ1_3221'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('lequ1_3222'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('lequ1_3223'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('lequ1_3231'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('lequ1_3232'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('lequ1_3233'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('lequ1_3311'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('lequ1_3312'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('lequ1_3313'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('lequ1_3321'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('lequ1_3322'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('lequ1_3323'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('lequ1_3331'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('lequ1_3332'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('lequ1_3333'))* lambda_smeft_value**2, '.6e'), '# clequ1Abs3x3x3x3'], ]} card['Block']['FRBlock79'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('lequ1_1111')), '.6e'), '# clequ1Ph1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('lequ1_1112')), '.6e'), '# clequ1Ph1x1x1x2'], [1, 1, 1, 3, format(angle(scaled_wc('lequ1_1113')), '.6e'), '# clequ1Ph1x1x1x3'], [1, 1, 2, 1, format(angle(scaled_wc('lequ1_1121')), '.6e'), '# clequ1Ph1x1x2x1'], [1, 1, 2, 2, format(angle(scaled_wc('lequ1_1122')), '.6e'), '# clequ1Ph1x1x2x2'], [1, 1, 2, 3, format(angle(scaled_wc('lequ1_1123')), '.6e'), '# clequ1Ph1x1x2x3'], [1, 1, 3, 1, format(angle(scaled_wc('lequ1_1131')), '.6e'), '# clequ1Ph1x1x3x1'], [1, 1, 3, 2, format(angle(scaled_wc('lequ1_1132')), '.6e'), '# clequ1Ph1x1x3x2'], [1, 1, 3, 3, format(angle(scaled_wc('lequ1_1133')), '.6e'), '# clequ1Ph1x1x3x3'], [1, 2, 1, 1, format(angle(scaled_wc('lequ1_1211')), '.6e'), '# clequ1Ph1x2x1x1'], [1, 2, 1, 2, format(angle(scaled_wc('lequ1_1212')), '.6e'), '# clequ1Ph1x2x1x2'], [1, 2, 1, 3, format(angle(scaled_wc('lequ1_1213')), '.6e'), '# clequ1Ph1x2x1x3'], [1, 2, 2, 1, format(angle(scaled_wc('lequ1_1221')), '.6e'), '# clequ1Ph1x2x2x1'], [1, 2, 2, 2, format(angle(scaled_wc('lequ1_1222')), '.6e'), '# clequ1Ph1x2x2x2'], [1, 2, 2, 3, format(angle(scaled_wc('lequ1_1223')), '.6e'), '# clequ1Ph1x2x2x3'], [1, 2, 3, 1, format(angle(scaled_wc('lequ1_1231')), '.6e'), '# clequ1Ph1x2x3x1'], [1, 2, 3, 2, format(angle(scaled_wc('lequ1_1232')), '.6e'), '# clequ1Ph1x2x3x2'], [1, 2, 3, 3, format(angle(scaled_wc('lequ1_1233')), '.6e'), '# clequ1Ph1x2x3x3'], [1, 3, 1, 1, format(angle(scaled_wc('lequ1_1311')), '.6e'), '# clequ1Ph1x3x1x1'], [1, 3, 1, 2, format(angle(scaled_wc('lequ1_1312')), '.6e'), '# clequ1Ph1x3x1x2'], [1, 3, 1, 3, format(angle(scaled_wc('lequ1_1313')), '.6e'), '# clequ1Ph1x3x1x3'], [1, 3, 2, 1, format(angle(scaled_wc('lequ1_1321')), '.6e'), '# clequ1Ph1x3x2x1'], [1, 3, 2, 2, format(angle(scaled_wc('lequ1_1322')), '.6e'), '# clequ1Ph1x3x2x2'], [1, 3, 2, 3, format(angle(scaled_wc('lequ1_1323')), '.6e'), '# clequ1Ph1x3x2x3'], [1, 3, 3, 1, format(angle(scaled_wc('lequ1_1331')), '.6e'), '# clequ1Ph1x3x3x1'], [1, 3, 3, 2, format(angle(scaled_wc('lequ1_1332')), '.6e'), '# clequ1Ph1x3x3x2'], [1, 3, 3, 3, format(angle(scaled_wc('lequ1_1333')), '.6e'), '# clequ1Ph1x3x3x3'], [2, 1, 1, 1, format(angle(scaled_wc('lequ1_2111')), '.6e'), '# clequ1Ph2x1x1x1'], [2, 1, 1, 2, format(angle(scaled_wc('lequ1_2112')), '.6e'), '# clequ1Ph2x1x1x2'], [2, 1, 1, 3, format(angle(scaled_wc('lequ1_2113')), '.6e'), '# clequ1Ph2x1x1x3'], [2, 1, 2, 1, format(angle(scaled_wc('lequ1_2121')), '.6e'), '# clequ1Ph2x1x2x1'], [2, 1, 2, 2, format(angle(scaled_wc('lequ1_2122')), '.6e'), '# clequ1Ph2x1x2x2'], [2, 1, 2, 3, format(angle(scaled_wc('lequ1_2123')), '.6e'), '# clequ1Ph2x1x2x3'], [2, 1, 3, 1, format(angle(scaled_wc('lequ1_2131')), '.6e'), '# clequ1Ph2x1x3x1'], [2, 1, 3, 2, format(angle(scaled_wc('lequ1_2132')), '.6e'), '# clequ1Ph2x1x3x2'], [2, 1, 3, 3, format(angle(scaled_wc('lequ1_2133')), '.6e'), '# clequ1Ph2x1x3x3'], [2, 2, 1, 1, format(angle(scaled_wc('lequ1_2211')), '.6e'), '# clequ1Ph2x2x1x1'], [2, 2, 1, 2, format(angle(scaled_wc('lequ1_2212')), '.6e'), '# clequ1Ph2x2x1x2'], [2, 2, 1, 3, format(angle(scaled_wc('lequ1_2213')), '.6e'), '# clequ1Ph2x2x1x3'], [2, 2, 2, 1, format(angle(scaled_wc('lequ1_2221')), '.6e'), '# clequ1Ph2x2x2x1'], [2, 2, 2, 2, format(angle(scaled_wc('lequ1_2222')), '.6e'), '# clequ1Ph2x2x2x2'], [2, 2, 2, 3, format(angle(scaled_wc('lequ1_2223')), '.6e'), '# clequ1Ph2x2x2x3'], [2, 2, 3, 1, format(angle(scaled_wc('lequ1_2231')), '.6e'), '# clequ1Ph2x2x3x1'], [2, 2, 3, 2, format(angle(scaled_wc('lequ1_2232')), '.6e'), '# clequ1Ph2x2x3x2'], [2, 2, 3, 3, format(angle(scaled_wc('lequ1_2233')), '.6e'), '# clequ1Ph2x2x3x3'], [2, 3, 1, 1, format(angle(scaled_wc('lequ1_2311')), '.6e'), '# clequ1Ph2x3x1x1'], [2, 3, 1, 2, format(angle(scaled_wc('lequ1_2312')), '.6e'), '# clequ1Ph2x3x1x2'], [2, 3, 1, 3, format(angle(scaled_wc('lequ1_2313')), '.6e'), '# clequ1Ph2x3x1x3'], [2, 3, 2, 1, format(angle(scaled_wc('lequ1_2321')), '.6e'), '# clequ1Ph2x3x2x1'], [2, 3, 2, 2, format(angle(scaled_wc('lequ1_2322')), '.6e'), '# clequ1Ph2x3x2x2'], [2, 3, 2, 3, format(angle(scaled_wc('lequ1_2323')), '.6e'), '# clequ1Ph2x3x2x3'], [2, 3, 3, 1, format(angle(scaled_wc('lequ1_2331')), '.6e'), '# clequ1Ph2x3x3x1'], [2, 3, 3, 2, format(angle(scaled_wc('lequ1_2332')), '.6e'), '# clequ1Ph2x3x3x2'], [2, 3, 3, 3, format(angle(scaled_wc('lequ1_2333')), '.6e'), '# clequ1Ph2x3x3x3'], [3, 1, 1, 1, format(angle(scaled_wc('lequ1_3111')), '.6e'), '# clequ1Ph3x1x1x1'], [3, 1, 1, 2, format(angle(scaled_wc('lequ1_3112')), '.6e'), '# clequ1Ph3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('lequ1_3113')), '.6e'), '# clequ1Ph3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('lequ1_3121')), '.6e'), '# clequ1Ph3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('lequ1_3122')), '.6e'), '# clequ1Ph3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('lequ1_3123')), '.6e'), '# clequ1Ph3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('lequ1_3131')), '.6e'), '# clequ1Ph3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('lequ1_3132')), '.6e'), '# clequ1Ph3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('lequ1_3133')), '.6e'), '# clequ1Ph3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('lequ1_3211')), '.6e'), '# clequ1Ph3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('lequ1_3212')), '.6e'), '# clequ1Ph3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('lequ1_3213')), '.6e'), '# clequ1Ph3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('lequ1_3221')), '.6e'), '# clequ1Ph3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('lequ1_3222')), '.6e'), '# clequ1Ph3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('lequ1_3223')), '.6e'), '# clequ1Ph3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('lequ1_3231')), '.6e'), '# clequ1Ph3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('lequ1_3232')), '.6e'), '# clequ1Ph3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('lequ1_3233')), '.6e'), '# clequ1Ph3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('lequ1_3311')), '.6e'), '# clequ1Ph3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('lequ1_3312')), '.6e'), '# clequ1Ph3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('lequ1_3313')), '.6e'), '# clequ1Ph3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('lequ1_3321')), '.6e'), '# clequ1Ph3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('lequ1_3322')), '.6e'), '# clequ1Ph3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('lequ1_3323')), '.6e'), '# clequ1Ph3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('lequ1_3331')), '.6e'), '# clequ1Ph3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('lequ1_3332')), '.6e'), '# clequ1Ph3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('lequ1_3333')), '.6e'), '# clequ1Ph3x3x3x3'], ]} card['Block']['FRBlock8'] = {'values': [ [1, 1, format(abs(scaled_wc('dphi_11'))* lambda_smeft_value**2, '.6e'), '# cdHAbs1x1'], [1, 2, format(abs(scaled_wc('dphi_12'))* lambda_smeft_value**2, '.6e'), '# cdHAbs1x2'], [1, 3, format(abs(scaled_wc('dphi_13'))* lambda_smeft_value**2, '.6e'), '# cdHAbs1x3'], [2, 1, format(abs(scaled_wc('dphi_21'))* lambda_smeft_value**2, '.6e'), '# cdHAbs2x1'], [2, 2, format(abs(scaled_wc('dphi_22'))* lambda_smeft_value**2, '.6e'), '# cdHAbs2x2'], [2, 3, format(abs(scaled_wc('dphi_23'))* lambda_smeft_value**2, '.6e'), '# cdHAbs2x3'], [3, 1, format(abs(scaled_wc('dphi_31'))* lambda_smeft_value**2, '.6e'), '# cdHAbs3x1'], [3, 2, format(abs(scaled_wc('dphi_32'))* lambda_smeft_value**2, '.6e'), '# cdHAbs3x2'], [3, 3, format(abs(scaled_wc('dphi_33'))* lambda_smeft_value**2, '.6e'), '# cdHAbs3x3'], ]} card['Block']['FRBlock81'] = {'values': [ [1, 1, 1, 1, format(abs(scaled_wc('lequ3_1111'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x1x1'], [1, 1, 1, 2, format(abs(scaled_wc('lequ3_1112'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x1x2'], [1, 1, 1, 3, format(abs(scaled_wc('lequ3_1113'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x1x3'], [1, 1, 2, 1, format(abs(scaled_wc('lequ3_1121'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x2x1'], [1, 1, 2, 2, format(abs(scaled_wc('lequ3_1122'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x2x2'], [1, 1, 2, 3, format(abs(scaled_wc('lequ3_1123'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x2x3'], [1, 1, 3, 1, format(abs(scaled_wc('lequ3_1131'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x3x1'], [1, 1, 3, 2, format(abs(scaled_wc('lequ3_1132'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x3x2'], [1, 1, 3, 3, format(abs(scaled_wc('lequ3_1133'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x1x3x3'], [1, 2, 1, 1, format(abs(scaled_wc('lequ3_1211'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x1x1'], [1, 2, 1, 2, format(abs(scaled_wc('lequ3_1212'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x1x2'], [1, 2, 1, 3, format(abs(scaled_wc('lequ3_1213'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x1x3'], [1, 2, 2, 1, format(abs(scaled_wc('lequ3_1221'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x2x1'], [1, 2, 2, 2, format(abs(scaled_wc('lequ3_1222'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x2x2'], [1, 2, 2, 3, format(abs(scaled_wc('lequ3_1223'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x2x3'], [1, 2, 3, 1, format(abs(scaled_wc('lequ3_1231'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x3x1'], [1, 2, 3, 2, format(abs(scaled_wc('lequ3_1232'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x3x2'], [1, 2, 3, 3, format(abs(scaled_wc('lequ3_1233'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x2x3x3'], [1, 3, 1, 1, format(abs(scaled_wc('lequ3_1311'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x1x1'], [1, 3, 1, 2, format(abs(scaled_wc('lequ3_1312'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x1x2'], [1, 3, 1, 3, format(abs(scaled_wc('lequ3_1313'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x1x3'], [1, 3, 2, 1, format(abs(scaled_wc('lequ3_1321'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x2x1'], [1, 3, 2, 2, format(abs(scaled_wc('lequ3_1322'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x2x2'], [1, 3, 2, 3, format(abs(scaled_wc('lequ3_1323'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x2x3'], [1, 3, 3, 1, format(abs(scaled_wc('lequ3_1331'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x3x1'], [1, 3, 3, 2, format(abs(scaled_wc('lequ3_1332'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x3x2'], [1, 3, 3, 3, format(abs(scaled_wc('lequ3_1333'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs1x3x3x3'], [2, 1, 1, 1, format(abs(scaled_wc('lequ3_2111'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x1x1'], [2, 1, 1, 2, format(abs(scaled_wc('lequ3_2112'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x1x2'], [2, 1, 1, 3, format(abs(scaled_wc('lequ3_2113'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x1x3'], [2, 1, 2, 1, format(abs(scaled_wc('lequ3_2121'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x2x1'], [2, 1, 2, 2, format(abs(scaled_wc('lequ3_2122'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x2x2'], [2, 1, 2, 3, format(abs(scaled_wc('lequ3_2123'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x2x3'], [2, 1, 3, 1, format(abs(scaled_wc('lequ3_2131'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x3x1'], [2, 1, 3, 2, format(abs(scaled_wc('lequ3_2132'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x3x2'], [2, 1, 3, 3, format(abs(scaled_wc('lequ3_2133'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x1x3x3'], [2, 2, 1, 1, format(abs(scaled_wc('lequ3_2211'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x1x1'], [2, 2, 1, 2, format(abs(scaled_wc('lequ3_2212'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x1x2'], [2, 2, 1, 3, format(abs(scaled_wc('lequ3_2213'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x1x3'], [2, 2, 2, 1, format(abs(scaled_wc('lequ3_2221'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x2x1'], [2, 2, 2, 2, format(abs(scaled_wc('lequ3_2222'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x2x2'], [2, 2, 2, 3, format(abs(scaled_wc('lequ3_2223'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x2x3'], [2, 2, 3, 1, format(abs(scaled_wc('lequ3_2231'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x3x1'], [2, 2, 3, 2, format(abs(scaled_wc('lequ3_2232'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x3x2'], [2, 2, 3, 3, format(abs(scaled_wc('lequ3_2233'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x2x3x3'], [2, 3, 1, 1, format(abs(scaled_wc('lequ3_2311'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x1x1'], [2, 3, 1, 2, format(abs(scaled_wc('lequ3_2312'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x1x2'], [2, 3, 1, 3, format(abs(scaled_wc('lequ3_2313'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x1x3'], [2, 3, 2, 1, format(abs(scaled_wc('lequ3_2321'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x2x1'], [2, 3, 2, 2, format(abs(scaled_wc('lequ3_2322'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x2x2'], [2, 3, 2, 3, format(abs(scaled_wc('lequ3_2323'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x2x3'], [2, 3, 3, 1, format(abs(scaled_wc('lequ3_2331'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x3x1'], [2, 3, 3, 2, format(abs(scaled_wc('lequ3_2332'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x3x2'], [2, 3, 3, 3, format(abs(scaled_wc('lequ3_2333'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs2x3x3x3'], [3, 1, 1, 1, format(abs(scaled_wc('lequ3_3111'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x1x1'], [3, 1, 1, 2, format(abs(scaled_wc('lequ3_3112'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x1x2'], [3, 1, 1, 3, format(abs(scaled_wc('lequ3_3113'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x1x3'], [3, 1, 2, 1, format(abs(scaled_wc('lequ3_3121'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x2x1'], [3, 1, 2, 2, format(abs(scaled_wc('lequ3_3122'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x2x2'], [3, 1, 2, 3, format(abs(scaled_wc('lequ3_3123'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x2x3'], [3, 1, 3, 1, format(abs(scaled_wc('lequ3_3131'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x3x1'], [3, 1, 3, 2, format(abs(scaled_wc('lequ3_3132'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x3x2'], [3, 1, 3, 3, format(abs(scaled_wc('lequ3_3133'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x1x3x3'], [3, 2, 1, 1, format(abs(scaled_wc('lequ3_3211'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x1x1'], [3, 2, 1, 2, format(abs(scaled_wc('lequ3_3212'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x1x2'], [3, 2, 1, 3, format(abs(scaled_wc('lequ3_3213'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x1x3'], [3, 2, 2, 1, format(abs(scaled_wc('lequ3_3221'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x2x1'], [3, 2, 2, 2, format(abs(scaled_wc('lequ3_3222'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x2x2'], [3, 2, 2, 3, format(abs(scaled_wc('lequ3_3223'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x2x3'], [3, 2, 3, 1, format(abs(scaled_wc('lequ3_3231'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x3x1'], [3, 2, 3, 2, format(abs(scaled_wc('lequ3_3232'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x3x2'], [3, 2, 3, 3, format(abs(scaled_wc('lequ3_3233'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x2x3x3'], [3, 3, 1, 1, format(abs(scaled_wc('lequ3_3311'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x1x1'], [3, 3, 1, 2, format(abs(scaled_wc('lequ3_3312'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x1x2'], [3, 3, 1, 3, format(abs(scaled_wc('lequ3_3313'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x1x3'], [3, 3, 2, 1, format(abs(scaled_wc('lequ3_3321'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x2x1'], [3, 3, 2, 2, format(abs(scaled_wc('lequ3_3322'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x2x2'], [3, 3, 2, 3, format(abs(scaled_wc('lequ3_3323'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x2x3'], [3, 3, 3, 1, format(abs(scaled_wc('lequ3_3331'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x3x1'], [3, 3, 3, 2, format(abs(scaled_wc('lequ3_3332'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x3x2'], [3, 3, 3, 3, format(abs(scaled_wc('lequ3_3333'))* lambda_smeft_value**2, '.6e'), '# cLeQu3Abs3x3x3x3'], ]} card['Block']['FRBlock82'] = {'values': [ [1, 1, 1, 1, format(angle(scaled_wc('lequ3_1111')), '.6e'), '# cLeQu3Ph1x1x1x1'], [1, 1, 1, 2, format(angle(scaled_wc('lequ3_1112')), 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cLeQu3Ph1x2x2x2'], [1, 2, 2, 3, format(angle(scaled_wc('lequ3_1223')), '.6e'), '# cLeQu3Ph1x2x2x3'], [1, 2, 3, 1, format(angle(scaled_wc('lequ3_1231')), '.6e'), '# cLeQu3Ph1x2x3x1'], [1, 2, 3, 2, format(angle(scaled_wc('lequ3_1232')), '.6e'), '# cLeQu3Ph1x2x3x2'], [1, 2, 3, 3, format(angle(scaled_wc('lequ3_1233')), '.6e'), '# cLeQu3Ph1x2x3x3'], [1, 3, 1, 1, format(angle(scaled_wc('lequ3_1311')), '.6e'), '# cLeQu3Ph1x3x1x1'], [1, 3, 1, 2, format(angle(scaled_wc('lequ3_1312')), '.6e'), '# cLeQu3Ph1x3x1x2'], [1, 3, 1, 3, format(angle(scaled_wc('lequ3_1313')), '.6e'), '# cLeQu3Ph1x3x1x3'], [1, 3, 2, 1, format(angle(scaled_wc('lequ3_1321')), '.6e'), '# cLeQu3Ph1x3x2x1'], [1, 3, 2, 2, format(angle(scaled_wc('lequ3_1322')), '.6e'), '# cLeQu3Ph1x3x2x2'], [1, 3, 2, 3, format(angle(scaled_wc('lequ3_1323')), '.6e'), '# cLeQu3Ph1x3x2x3'], [1, 3, 3, 1, format(angle(scaled_wc('lequ3_1331')), '.6e'), '# cLeQu3Ph1x3x3x1'], [1, 3, 3, 2, format(angle(scaled_wc('lequ3_1332')), '.6e'), '# 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cLeQu3Ph2x3x2x2'], [2, 3, 2, 3, format(angle(scaled_wc('lequ3_2323')), '.6e'), '# cLeQu3Ph2x3x2x3'], [2, 3, 3, 1, format(angle(scaled_wc('lequ3_2331')), '.6e'), '# cLeQu3Ph2x3x3x1'], [2, 3, 3, 2, format(angle(scaled_wc('lequ3_2332')), '.6e'), '# cLeQu3Ph2x3x3x2'], [2, 3, 3, 3, format(angle(scaled_wc('lequ3_2333')), '.6e'), '# cLeQu3Ph2x3x3x3'], [3, 1, 1, 1, format(angle(scaled_wc('lequ3_3111')), '.6e'), '# cLeQu3Ph3x1x1x1'], [3, 1, 1, 2, format(angle(scaled_wc('lequ3_3112')), '.6e'), '# cLeQu3Ph3x1x1x2'], [3, 1, 1, 3, format(angle(scaled_wc('lequ3_3113')), '.6e'), '# cLeQu3Ph3x1x1x3'], [3, 1, 2, 1, format(angle(scaled_wc('lequ3_3121')), '.6e'), '# cLeQu3Ph3x1x2x1'], [3, 1, 2, 2, format(angle(scaled_wc('lequ3_3122')), '.6e'), '# cLeQu3Ph3x1x2x2'], [3, 1, 2, 3, format(angle(scaled_wc('lequ3_3123')), '.6e'), '# cLeQu3Ph3x1x2x3'], [3, 1, 3, 1, format(angle(scaled_wc('lequ3_3131')), '.6e'), '# cLeQu3Ph3x1x3x1'], [3, 1, 3, 2, format(angle(scaled_wc('lequ3_3132')), '.6e'), '# cLeQu3Ph3x1x3x2'], [3, 1, 3, 3, format(angle(scaled_wc('lequ3_3133')), '.6e'), '# cLeQu3Ph3x1x3x3'], [3, 2, 1, 1, format(angle(scaled_wc('lequ3_3211')), '.6e'), '# cLeQu3Ph3x2x1x1'], [3, 2, 1, 2, format(angle(scaled_wc('lequ3_3212')), '.6e'), '# cLeQu3Ph3x2x1x2'], [3, 2, 1, 3, format(angle(scaled_wc('lequ3_3213')), '.6e'), '# cLeQu3Ph3x2x1x3'], [3, 2, 2, 1, format(angle(scaled_wc('lequ3_3221')), '.6e'), '# cLeQu3Ph3x2x2x1'], [3, 2, 2, 2, format(angle(scaled_wc('lequ3_3222')), '.6e'), '# cLeQu3Ph3x2x2x2'], [3, 2, 2, 3, format(angle(scaled_wc('lequ3_3223')), '.6e'), '# cLeQu3Ph3x2x2x3'], [3, 2, 3, 1, format(angle(scaled_wc('lequ3_3231')), '.6e'), '# cLeQu3Ph3x2x3x1'], [3, 2, 3, 2, format(angle(scaled_wc('lequ3_3232')), '.6e'), '# cLeQu3Ph3x2x3x2'], [3, 2, 3, 3, format(angle(scaled_wc('lequ3_3233')), '.6e'), '# cLeQu3Ph3x2x3x3'], [3, 3, 1, 1, format(angle(scaled_wc('lequ3_3311')), '.6e'), '# cLeQu3Ph3x3x1x1'], [3, 3, 1, 2, format(angle(scaled_wc('lequ3_3312')), '.6e'), '# cLeQu3Ph3x3x1x2'], [3, 3, 1, 3, format(angle(scaled_wc('lequ3_3313')), '.6e'), '# cLeQu3Ph3x3x1x3'], [3, 3, 2, 1, format(angle(scaled_wc('lequ3_3321')), '.6e'), '# cLeQu3Ph3x3x2x1'], [3, 3, 2, 2, format(angle(scaled_wc('lequ3_3322')), '.6e'), '# cLeQu3Ph3x3x2x2'], [3, 3, 2, 3, format(angle(scaled_wc('lequ3_3323')), '.6e'), '# cLeQu3Ph3x3x2x3'], [3, 3, 3, 1, format(angle(scaled_wc('lequ3_3331')), '.6e'), '# cLeQu3Ph3x3x3x1'], [3, 3, 3, 2, format(angle(scaled_wc('lequ3_3332')), '.6e'), '# cLeQu3Ph3x3x3x2'], [3, 3, 3, 3, format(angle(scaled_wc('lequ3_3333')), '.6e'), '# cLeQu3Ph3x3x3x3'], ]} card['Block']['FRBlock9'] = {'values': [ [1, 1, format(angle(scaled_wc('ephi_11')), '.6e'), '# ceHPh1x1'], [1, 2, format(angle(scaled_wc('ephi_12')), '.6e'), '# ceHPh1x2'], [1, 3, format(angle(scaled_wc('ephi_13')), '.6e'), '# ceHPh1x3'], [2, 1, format(angle(scaled_wc('ephi_21')), '.6e'), '# ceHPh2x1'], [2, 2, format(angle(scaled_wc('ephi_22')), '.6e'), '# ceHPh2x2'], [2, 3, format(angle(scaled_wc('ephi_23')), '.6e'), '# ceHPh2x3'], [3, 1, format(angle(scaled_wc('ephi_31')), '.6e'), '# ceHPh3x1'], [3, 2, format(angle(scaled_wc('ephi_32')), '.6e'), '# ceHPh3x2'], [3, 3, format(angle(scaled_wc('ephi_33')), '.6e'), '# ceHPh3x3'], ]} card['Block']['NEWCOUP'] = {'values': [ [0, format(lambda_smeft_value, '.6e'),'# Lambda'], [1, format(scaled_wc('phiBox')* lambda_smeft_value**2, '.6e'), '# cHBox'], [2, format(scaled_wc('phiD')* lambda_smeft_value**2, '.6e'), '# cHDD'], [3, format(scaled_wc('phi')* lambda_smeft_value**2, '.6e'), '# cH'], [4, format(scaled_wc('phiB')* lambda_smeft_value**2, '.6e'), '# cHB'], [5, format(scaled_wc('phiW')* lambda_smeft_value**2, '.6e'), '# cHW'], [6, format(scaled_wc('phiWB')* lambda_smeft_value**2, '.6e'), '# cHWB'], [7, format(scaled_wc('phiG')* lambda_smeft_value**2, '.6e'), '# cHG'], [8, format(scaled_wc('W')* lambda_smeft_value**2, '.6e'), '# cW'], [9, format(scaled_wc('G')* lambda_smeft_value**2, '.6e'), '# cG'], [10, format(scaled_wc('Wtilde')* lambda_smeft_value**2, '.6e'), '# cWtil'], [11, format(scaled_wc('Gtilde')* lambda_smeft_value**2, '.6e'), '# cGtil'], [12, format(scaled_wc('phiBtilde')* lambda_smeft_value**2, '.6e'), '# cHBtil'], [13, format(scaled_wc('phiWtilde')* lambda_smeft_value**2, '.6e'), '# cHWtil'], [14, format(scaled_wc('phiWtildeB')* lambda_smeft_value**2, '.6e'), '# cHWBtil'], [15, format(scaled_wc('phiGtilde')* lambda_smeft_value**2, '.6e'), '# cHGtil'], ]} return card def smeftsim_card_text(model_set, input_scheme_value): #corrections for mw input scheme if input_scheme_value == 'mw': if model_set == 'A': p_list = preamble_A.split('\n') del p_list[9] p_list[2]="## PARAM_CARD FOR SMEFTSIM SET A v2.0 - FLAVOR_GENERAL MW_INPUTS ########" p_list[32]="24 80.387000 # W+ : MW0" p_list[35]="9000003 80.387000 # ghWp : MW0" p_list[36]="9000004 80.387000 # ghWm : MW0" p_list[41]="251 80.387000 # G+ : MW0" preamble = '\n'.join(p_list) postamble = postamble_A elif model_set == 'B': p_list = preamble_B.split('\n') del p_list[9], p_list[32], p_list[34], p_list[34], p_list[38] p_list[2]="## PARAM_CARD FOR SMEFTSIM SET B - FLAVOR_GENERAL MW_INPUTS ########" p_list[10]=" 3 1.185000e-01 # aS" p_list.insert(26, " 24 8.038700e+01 # MW") p_list.insert(40, " 9000003 80.387000 # ghWp : MW" ) p_list.insert(41, " 9000004 80.387000 # ghWm : MW" ) p_list.insert(43, " 251 80.387000 # G+ : MW") preamble = '\n'.join(p_list) postamble = postamble_B elif input_scheme_value == 'alpha': if model_set == 'A': preamble = preamble_A postamble = postamble_A elif model_set == 'B': preamble = preamble_B postamble = postamble_B return preamble, postamble

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1

0

null

0

8

75acaa4092f55e02b29eea4f4c43c803fbd106f2

232

py

Python

src/models/person.py

eboliveira/Music-recommender

9d4cc15c694e628d1ffa29748a82f555d4b3e581

[ "MIT" ]

null

src/models/person.py

eboliveira/Music-recommender

9d4cc15c694e628d1ffa29748a82f555d4b3e581

[ "MIT" ]

null

src/models/person.py

eboliveira/Music-recommender

9d4cc15c694e628d1ffa29748a82f555d4b3e581

[ "MIT" ]

3

2020-12-08T20:32:07.000Z

2021-03-31T18:24:44.000Z

class Person: def __init__(self, params): self.name = params.get('name') self.birth_date = params.get('birth_date') def params_str(self): return "{{name: '{}', birth_date: '{}'}}".format(self.name, self.birth_date)

29

80

0.650862

32

232

4.4375

0.40625

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0.183099

0.239437

0

0.155172

232

7

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null

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1

0

1

0

7

75cb0458f761854e76201ffba18c687a89ce6a3a

157

py

Python

potc_torch/plugin/rules.py

potc-dev/potc-torch

a5eec2051b03271bdafc1389cb29a03aad729752

[ "Apache-2.0" ]

null

potc_torch/plugin/rules.py

potc-dev/potc-torch

a5eec2051b03271bdafc1389cb29a03aad729752

[ "Apache-2.0" ]

null

potc_torch/plugin/rules.py

potc-dev/potc-torch

a5eec2051b03271bdafc1389cb29a03aad729752

[ "Apache-2.0" ]

null

from .torch import torch_tensor, torch_dtype, torch_size, torch_device __rules__ = [ torch_tensor, torch_dtype, torch_size, torch_device, ]

17.444444

70

0.726115

20

157

5.1

0.4

0.215686

0.313725

0.411765

0.803922

0

0.203822

157

8

71

19.625

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0

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null

1

0

1

0

null

0

9

f981abdaf721055e8cc5e43edbec46fb754c9ecc

344

py

Python

irekua_permissions/annotations/tools.py

CONABIO-audio/irekua-permissions

563c558e59788054504c852a6a6017bce7469a12

[ "BSD-4-Clause" ]

null

irekua_permissions/annotations/tools.py

CONABIO-audio/irekua-permissions

563c558e59788054504c852a6a6017bce7469a12

[ "BSD-4-Clause" ]

2

2020-02-12T03:00:51.000Z

2020-04-26T23:27:52.000Z

irekua_permissions/annotations/tools.py

CONABIO-audio/irekua-permissions

563c558e59788054504c852a6a6017bce7469a12

[ "BSD-4-Clause" ]

null

def view(user, tool): return True def create(user, tool): if user.is_superuser: return True return user.is_developer def change(user, tool): if user.is_superuser: return True return user.is_developer def delete(user, tool): if user.is_superuser: return True return user.is_developer

14.333333

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344

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0.790909

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0.270349

344

23

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0

1

0

null

0

1

0

1

0

9

f9a28fa5db2b9f40b64a616077ba54ef455be5f9

137

py

Python

latent_gce/__init__.py

PhilipZRH/latent-gce

16eae22a2f8edb8965ba3623e1513ebdfb37e811

[ "MIT" ]

4

2021-04-02T18:31:33.000Z

2022-01-23T22:10:28.000Z

latent_gce/__init__.py

PhilipZRH/latent-gce

16eae22a2f8edb8965ba3623e1513ebdfb37e811

[ "MIT" ]

1

2021-05-20T04:28:41.000Z

latent_gce/__init__.py

PhilipZRH/latent-gce

16eae22a2f8edb8965ba3623e1513ebdfb37e811

[ "MIT" ]

2

2021-04-12T22:20:27.000Z

2021-05-19T04:21:48.000Z

from latent_gce.model import * from latent_gce.trajectory_utils import * from latent_gce.utils import * from latent_gce.gce_ppo import *

27.4

41

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22

137

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137

4

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null

0

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1

0

1

0

8

ddfb109cf4d4cf9239d4fd0bf4067d090f1870e9

18,776

py

Python

services/image-rec-master/test/test_tasks.py

uavaustin/orchestra

b2b60253723caa2f265139f89d4cd3f2d1ba805f

[ "MIT" ]

1

2020-10-08T14:37:36.000Z

services/image-rec-master/test/test_tasks.py

uavaustin/orchestra

b2b60253723caa2f265139f89d4cd3f2d1ba805f

[ "MIT" ]

33

2017-10-31T22:36:42.000Z

2021-01-10T22:15:54.000Z

services/image-rec-master/test/test_tasks.py

uavaustin/orchestra

b2b60253723caa2f265139f89d4cd3f2d1ba805f

[ "MIT" ]

3

2018-10-07T21:36:02.000Z

2020-02-07T01:13:53.000Z

from aiohttp import ClientSession, web from aioresponses import CallbackResult, aioresponses import pytest from messages.imagery_pb2 import AvailableImages from messages.interop_pb2 import Odlc import service.tasks from service.util import get_int_list, get_int_set @pytest.fixture async def app(aiohttp_client, redis): app = web.Application() app['redis'] = redis app['http_client'] = ClientSession() app['imagery_url'] = 'http://imagery:1234' app['interop_url'] = 'http://interop-proxy:1234' yield app await app['http_client'].close() @pytest.fixture def http_mock(): with aioresponses() as m: yield m async def test_queue_new_images_no_images(app, redis, http_mock): available_images = AvailableImages() available_images.id_list.extend([]) http_mock.get('http://imagery:1234/api/available', body=available_images.SerializeToString(), headers={'Content-Type': 'application/x-protobuf'}) await service.tasks.queue_new_images(app) assert await get_int_set(redis, 'all-images') == [] assert await get_int_list(redis, 'unprocessed-auto') == [] assert await get_int_list(redis, 'unprocessed-manual') == [] async def test_queue_new_images_with_images(app, redis, http_mock): available_images = AvailableImages() available_images.id_list.extend([1, 2]) http_mock.get('http://imagery:1234/api/available', body=available_images.SerializeToString(), headers={'Content-Type': 'application/x-protobuf'}) await service.tasks.queue_new_images(app) assert await get_int_set(redis, 'all-images') == [1, 2] assert await get_int_list(redis, 'unprocessed-auto') == [2, 1] assert await get_int_list(redis, 'unprocessed-manual') == [2, 1] async def test_queue_new_images_no_images_existing(app, redis, http_mock): await redis.sadd('all-images', 2) await redis.lpush('unprocessed-auto', 2) await redis.lpush('unprocessed-manual', 2) available_images = AvailableImages() available_images.id_list.extend([]) http_mock.get('http://imagery:1234/api/available', body=available_images.SerializeToString(), headers={'Content-Type': 'application/x-protobuf'}) await service.tasks.queue_new_images(app) assert await get_int_set(redis, 'all-images') == [2] assert await get_int_list(redis, 'unprocessed-auto') == [2] assert await get_int_list(redis, 'unprocessed-manual') == [2] async def test_queue_new_images_with_images_existing(app, redis, http_mock): await redis.sadd('all-images', 2) await redis.lpush('unprocessed-auto', 2) await redis.lpush('unprocessed-manual', 2) available_images = AvailableImages() available_images.id_list.extend([1, 2]) http_mock.get('http://imagery:1234/api/available', body=available_images.SerializeToString(), headers={'Content-Type': 'application/x-protobuf'}) await service.tasks.queue_new_images(app) assert await get_int_set(redis, 'all-images') == [1, 2] assert await get_int_list(redis, 'unprocessed-auto') == [1, 2] assert await get_int_list(redis, 'unprocessed-manual') == [1, 2] async def test_requeue_auto_images_no_error(app, redis): # Add image 2, and let it process without error, also add image # 3 later which shouldn't affect. await redis.lpush('processing-auto', 2) await service.tasks.requeue_auto_images(app) assert await get_int_list(redis, 'unprocessed-auto') == [] assert await get_int_list(redis, 'processing-auto') == [2] assert await get_int_set(redis, 'processed-auto') == [] assert await get_int_set(redis, 'retrying-auto') == [] assert await get_int_set(redis, 'errored-auto') == [] await redis.lrem('processing-auto', 0, 2) await redis.sadd('processed-auto', 2) await redis.lpush('processing-auto', 3) await service.tasks.requeue_auto_images(app) assert await get_int_list(redis, 'unprocessed-auto') == [] assert await get_int_list(redis, 'processing-auto') == [3] assert await get_int_set(redis, 'processed-auto') == [2] assert await get_int_set(redis, 'retrying-auto') == [] assert await get_int_set(redis, 'errored-auto') == [] async def test_requeue_auto_images_error_once_immediate(app, redis): # Add image 2, and let it stall, also add 3 which does not stall # and doesn't interfere. Image 2 works the second time. await redis.lpush('processing-auto', 2) await service.tasks.requeue_auto_images(app) await redis.lpush('processing-auto', 3) await service.tasks.requeue_auto_images(app) assert await get_int_list(redis, 'unprocessed-auto') == [2] assert await get_int_list(redis, 'processing-auto') == [3] assert await get_int_set(redis, 'processed-auto') == [] assert await get_int_set(redis, 'retrying-auto') == [2] assert await get_int_set(redis, 'errored-auto') == [] await redis.lrem('unprocessed-auto', 0, 2) await redis.lpush('processing-auto', 2) await redis.lrem('processing-auto', 0, 3) await redis.sadd('processed-auto', 3) await service.tasks.requeue_auto_images(app) assert await get_int_list(redis, 'unprocessed-auto') == [] assert await get_int_list(redis, 'processing-auto') == [2] assert await get_int_set(redis, 'processed-auto') == [3] assert await get_int_set(redis, 'retrying-auto') == [2] assert await get_int_set(redis, 'errored-auto') == [] await redis.lrem('processing-auto', 0, 2) await redis.sadd('processed-auto', 2) await service.tasks.requeue_auto_images(app) assert await get_int_list(redis, 'unprocessed-auto') == [] assert await get_int_list(redis, 'processing-auto') == [] assert await get_int_set(redis, 'processed-auto') == [2, 3] assert await get_int_set(redis, 'retrying-auto') == [2] assert await get_int_set(redis, 'errored-auto') == [] async def test_requeue_auto_images_error_once_delay(app, redis): # Add image 2, and let it stall. Run a couple iterations before # processing 2 again. await redis.lpush('processing-auto', 2) await service.tasks.requeue_auto_images(app) await service.tasks.requeue_auto_images(app) await service.tasks.requeue_auto_images(app) await redis.lrem('unprocessed-auto', 0, 2) await redis.lpush('processing-auto', 2) await service.tasks.requeue_auto_images(app) assert await get_int_list(redis, 'unprocessed-auto') == [] assert await get_int_list(redis, 'processing-auto') == [2] assert await get_int_set(redis, 'processed-auto') == [] assert await get_int_set(redis, 'retrying-auto') == [2] assert await get_int_set(redis, 'errored-auto') == [] await service.tasks.requeue_auto_images(app) async def test_requeue_auto_images_error_twice(app, redis): # Add image 2, and let it stall, also add 3 which does not stall # and doesn't interfere. Image 2 fails the second time. await redis.lpush('processing-auto', 2) await service.tasks.requeue_auto_images(app) await redis.lpush('processing-auto', 3) await service.tasks.requeue_auto_images(app) await redis.lrem('unprocessed-auto', 0, 2) await redis.lpush('processing-auto', 2) await redis.lrem('processing-auto', 0, 3) await redis.sadd('processed-auto', 3) await service.tasks.requeue_auto_images(app) await service.tasks.requeue_auto_images(app) assert await get_int_list(redis, 'unprocessed-auto') == [] assert await get_int_list(redis, 'processing-auto') == [] assert await get_int_set(redis, 'processed-auto') == [3] assert await get_int_set(redis, 'retrying-auto') == [] assert await get_int_set(redis, 'errored-auto') == [2] async def test_submit_targets(app, redis, http_mock): odlc = Odlc() odlc.type = Odlc.EMERGENT odlc.pos.lat = 12.01 odlc.pos.lon = -13.51 odlc.description = 'test test' odlc.image = b'test-image' target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 0, 'errored', 0, 'removed', 0) post_odlc = Odlc() post_odlc.type = Odlc.EMERGENT post_odlc.id = 2 post_odlc.pos.lat = 12.01 post_odlc.pos.lon = -13.51 post_odlc.description = 'test test' await redis.sadd('all-targets', 5) await redis.lpush('unsubmitted-targets', 5) await redis.hmset('target:5', *target) def post_cb(url, data, **kwargs): assert data == odlc.SerializeToString() return CallbackResult( status=201, body=post_odlc.SerializeToString(), headers={'Content-Type': 'application/x-protobuf'} ) http_mock.post('http://interop-proxy:1234/api/odlcs', callback=post_cb) await service.tasks.submit_targets(app) end_odlc = Odlc() end_odlc.type = Odlc.EMERGENT end_odlc.id = 2 end_odlc.pos.lat = 12.01 end_odlc.pos.lon = -13.51 end_odlc.description = 'test test' end_odlc.image = b'test-image' assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [5] assert await get_int_set(redis, 'errored-targets') == [] assert await get_int_set(redis, 'removed-targets') == [] assert await get_int_list(redis, 'unsubmitted-targets') == [] assert await get_int_list(redis, 'submitting-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': end_odlc.SerializeToString(), b'submitted': b'1', b'errored': b'0', b'removed': b'0' } async def test_submit_targets_server_error_once(app, redis, http_mock): odlc = Odlc() target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 0, 'errored', 0, 'removed', 0) post_odlc = Odlc() post_odlc.id = 2 await redis.sadd('all-targets', 5) await redis.lpush('unsubmitted-targets', 5) await redis.hmset('target:5', *target) http_mock.post('http://interop-proxy:1234/api/odlcs', status=500) http_mock.post('http://interop-proxy:1234/api/odlcs', body=post_odlc.SerializeToString(), headers={'Content-Type': 'application/x-protobuf'}) await service.tasks.submit_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [5] assert await get_int_set(redis, 'errored-targets') == [] assert await get_int_set(redis, 'removed-targets') == [] assert await get_int_list(redis, 'unsubmitted-targets') == [] assert await get_int_list(redis, 'submitting-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': post_odlc.SerializeToString(), b'submitted': b'1', b'errored': b'0', b'removed': b'0' } async def test_submit_targets_client_error(app, redis, http_mock): odlc = Odlc() target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 0, 'errored', 0, 'removed', 0) await redis.sadd('all-targets', 5) await redis.lpush('unsubmitted-targets', 5) await redis.hmset('target:5', *target) http_mock.post('http://interop-proxy:1234/api/odlcs', status=400) await service.tasks.submit_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [] assert await get_int_set(redis, 'errored-targets') == [5] assert await get_int_set(redis, 'removed-targets') == [] assert await get_int_list(redis, 'unsubmitted-targets') == [] assert await get_int_list(redis, 'submitting-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': odlc.SerializeToString(), b'submitted': b'0', b'errored': b'1', b'removed': b'0' } async def test_submit_targets_cancelled(app, redis, http_mock): odlc = Odlc() target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 0, 'errored', 0, 'removed', 0) await redis.sadd('all-targets', 5) await redis.lpush('unsubmitted-targets', 5) await redis.lpush('unremoved-targets', 5) await redis.hmset('target:5', *target) await service.tasks.submit_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [] assert await get_int_set(redis, 'errored-targets') == [] assert await get_int_set(redis, 'removed-targets') == [5] assert await get_int_list(redis, 'unsubmitted-targets') == [] assert await get_int_list(redis, 'unremoved-targets') == [] assert await get_int_list(redis, 'submitting-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': odlc.SerializeToString(), b'submitted': b'0', b'errored': b'0', b'removed': b'1' } async def test_remove_targets(app, redis, http_mock): odlc = Odlc() odlc.id = 2 odlc.type = Odlc.OFF_AXIS odlc.image = b'test-image' target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 1, 'errored', 0, 'removed', 0) await redis.sadd('all-targets', 5) await redis.sadd('submitted-targets', 5) await redis.lpush('unremoved-targets', 5) await redis.hmset('target:5', *target) http_mock.delete('http://interop-proxy:1234/api/odlcs/2') await service.tasks.remove_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [5] assert await get_int_set(redis, 'errored-targets') == [] assert await get_int_set(redis, 'removed-targets') == [5] assert await get_int_list(redis, 'unremoved-targets') == [] assert await get_int_list(redis, 'removing-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': odlc.SerializeToString(), b'submitted': b'1', b'errored': b'0', b'removed': b'1' } async def test_remove_targets_already_removed(app, redis, http_mock): odlc = Odlc() odlc.id = 2 odlc.type = Odlc.OFF_AXIS odlc.image = b'test-image' target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 1, 'errored', 0, 'removed', 1) await redis.sadd('all-targets', 5) await redis.sadd('submitted-targets', 5) await redis.sadd('removed-targets', 5) await redis.lpush('unremoved-targets', 5) await redis.hmset('target:5', *target) http_mock.delete('http://interop-proxy:1234/api/odlcs/2') await service.tasks.remove_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [5] assert await get_int_set(redis, 'errored-targets') == [] assert await get_int_set(redis, 'removed-targets') == [5] assert await get_int_list(redis, 'unremoved-targets') == [] assert await get_int_list(redis, 'removing-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': odlc.SerializeToString(), b'submitted': b'1', b'errored': b'0', b'removed': b'1' } async def test_remove_targets_no_exist(app, redis, http_mock): # If something doesn't exist it shouldn't be removed. odlc = Odlc() odlc.id = 2 odlc.type = Odlc.OFF_AXIS odlc.image = b'test-image' target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 0, 'errored', 1, 'removed', 0) await redis.sadd('all-targets', 5) await redis.sadd('errored-targets', 5) await redis.lpush('unremoved-targets', 5) await redis.hmset('target:5', *target) http_mock.delete('http://interop-proxy:1234/api/odlcs/2', status=404) await service.tasks.remove_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [] assert await get_int_set(redis, 'errored-targets') == [5] assert await get_int_set(redis, 'removed-targets') == [] assert await get_int_list(redis, 'unremoved-targets') == [] assert await get_int_list(redis, 'removing-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': odlc.SerializeToString(), b'submitted': b'0', b'errored': b'1', b'removed': b'0' } async def test_remove_targets_server_error(app, redis, http_mock): odlc = Odlc() odlc.id = 2 odlc.type = Odlc.OFF_AXIS odlc.image = b'test-image' target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 1, 'errored', 0, 'removed', 0) await redis.sadd('all-targets', 5) await redis.sadd('submitted-targets', 5) await redis.lpush('unremoved-targets', 5) await redis.hmset('target:5', *target) http_mock.delete('http://interop-proxy:1234/api/odlcs/2', status=500) http_mock.delete('http://interop-proxy:1234/api/odlcs/2') await service.tasks.remove_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [5] assert await get_int_set(redis, 'errored-targets') == [] assert await get_int_set(redis, 'removed-targets') == [5] assert await get_int_list(redis, 'unremoved-targets') == [] assert await get_int_list(redis, 'removing-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': odlc.SerializeToString(), b'submitted': b'1', b'errored': b'0', b'removed': b'1' } async def test_remove_targets_unsubmitted(app, redis, http_mock): odlc = Odlc() odlc.type = Odlc.OFF_AXIS odlc.image = b'test-image' target = ('id', 5, 'image_id', 6, 'odlc', odlc.SerializeToString(), 'submitted', 0, 'errored', 0, 'removed', 0) await redis.sadd('all-targets', 5) await redis.lpush('unsubmitted-targets', 5) await redis.lpush('unremoved-targets', 5) await redis.hmset('target:5', *target) await service.tasks.remove_targets(app) assert await get_int_set(redis, 'all-targets') == [5] assert await get_int_set(redis, 'submitted-targets') == [] assert await get_int_set(redis, 'errored-targets') == [] assert await get_int_set(redis, 'removed-targets') == [5] assert await get_int_list(redis, 'unremoved-targets') == [] assert await get_int_list(redis, 'removing-targets') == [] assert await redis.hgetall('target:5') == { b'id': b'5', b'image_id': b'6', b'odlc': odlc.SerializeToString(), b'submitted': b'0', b'errored': b'0', b'removed': b'1' }

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null

0

7

3498e8e58b3afddae35c73784f44aaa305c1c144

140

py

Python

src/lib/db/src/drop_all.py

arnulfojr/money-manager

8600f1ff258a89f5742ffad4d5f589fd1def5259

[ "MIT" ]

1

2020-08-18T08:03:44.000Z

src/lib/db/src/drop_all.py

arnulfojr/money-manager

8600f1ff258a89f5742ffad4d5f589fd1def5259

[ "MIT" ]

null

src/lib/db/src/drop_all.py

arnulfojr/money-manager

8600f1ff258a89f5742ffad4d5f589fd1def5259

[ "MIT" ]

null

from .. import Model from .. import engine def drop_all(): """Drops all the registered models""" Model.metadata.drop_all(engine)

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34e4451091be240e6791a5e6f455f30f15b21b6f

4,986

py

Python

surveys/models.py

inclusive-design/coop-map-directory-index

b215ea95677dc90fafe60eaa494a4fd6af0431fb

[ "BSD-3-Clause" ]

1

2020-01-28T16:16:49.000Z

surveys/models.py

inclusive-design/coop-map-directory-index

b215ea95677dc90fafe60eaa494a4fd6af0431fb

[ "BSD-3-Clause" ]

114

2020-02-12T20:22:07.000Z

2021-09-22T18:29:50.000Z

surveys/models.py

inclusive-design/coop-map-directory-index

b215ea95677dc90fafe60eaa494a4fd6af0431fb

[ "BSD-3-Clause" ]

4

2020-04-21T21:09:25.000Z

2021-01-08T14:18:58.000Z

from django.contrib.gis.db import models class Ecosystem2020Questions(models.Model): column_name = models.CharField(max_length=2) question = models.CharField(max_length=254, blank=True,) class Meta: managed = False db_table = 'surveys_ecosystem2020_questions' class Ecosystem2020(models.Model): a = models.DateTimeField(auto_now=True) b = models.CharField(max_length=254, blank=True,) c = models.CharField(max_length=254, blank=True,) d = models.CharField(max_length=254, blank=True,) e = models.CharField(max_length=254, blank=True,) f = models.CharField(max_length=254, blank=True,) g = models.CharField(max_length=254, blank=True,) h = models.CharField(max_length=254, blank=True,) i = models.CharField(max_length=254, blank=True,) j = models.CharField(max_length=254, blank=True,) k = models.CharField(max_length=254, blank=True,) l = models.CharField(max_length=254, blank=True,) m = models.CharField(max_length=254, blank=True,) n = models.CharField(max_length=254, blank=True,) o = models.CharField(max_length=254, blank=True,) p = models.CharField(max_length=254, blank=True,) q = models.CharField(max_length=254, blank=True,) r = models.CharField(max_length=254, blank=True,) s = models.CharField(max_length=254, blank=True,) t = models.CharField(max_length=254, blank=True,) u = models.CharField(max_length=254, blank=True,) v = models.CharField(max_length=254, blank=True,) w = models.CharField(max_length=254, blank=True,) x = models.CharField(max_length=254, blank=True,) y = models.CharField(max_length=254, blank=True,) z = models.CharField(max_length=254, blank=True,) aa = models.CharField(max_length=254, blank=True,) ab = models.CharField(max_length=254, blank=True,) ac = models.CharField(max_length=254, blank=True,) ad = models.CharField(max_length=254, blank=True,) ae = models.CharField(max_length=254, blank=True,) af = models.CharField(max_length=254, blank=True,) ag = models.CharField(max_length=254, blank=True,) ah = models.CharField(max_length=254, blank=True,) ai = models.CharField(max_length=254, blank=True,) aj = models.CharField(max_length=254, blank=True,) ak = models.CharField(max_length=254, blank=True,) al = models.CharField(max_length=254, blank=True,) am = models.CharField(max_length=254, blank=True,) an = models.CharField(max_length=254, blank=True,) ao = models.CharField(max_length=254, blank=True,) ap = models.CharField(max_length=254, blank=True,) aq = models.CharField(max_length=254, blank=True,) ar = models.CharField(max_length=254, blank=True,) as_field = models.CharField(max_length=254, blank=True,) # Field renamed because it was a Python reserved word. at = models.CharField(max_length=254, blank=True,) au = models.CharField(max_length=254, blank=True,) av = models.CharField(max_length=254, blank=True,) aw = models.CharField(max_length=254, blank=True,) ax = models.CharField(max_length=254, blank=True,) ay = models.CharField(max_length=254, blank=True,) az = models.CharField(max_length=254, blank=True,) ba = models.CharField(max_length=254, blank=True,) bb = models.CharField(max_length=254, blank=True,) bc = models.CharField(max_length=254, blank=True,) bd = models.CharField(max_length=254, blank=True,) be = models.CharField(max_length=254, blank=True,) bf = models.CharField(max_length=254, blank=True,) bg = models.TextField(blank=True,) bh = models.CharField(max_length=254, blank=True,) bi = models.CharField(max_length=254, blank=True,) bj = models.CharField(max_length=254, blank=True,) bk = models.CharField(max_length=254, blank=True,) bl = models.CharField(max_length=254, blank=True,) bm = models.CharField(max_length=254, blank=True,) bn = models.CharField(max_length=254, blank=True,) bo = models.CharField(max_length=254, blank=True,) bp = models.CharField(max_length=254, blank=True,) bq = models.CharField(max_length=254, blank=True,) br = models.CharField(max_length=254, blank=True,) bs = models.CharField(max_length=254, blank=True,) bt = models.CharField(max_length=254, blank=True,) bu = models.CharField(max_length=254, blank=True,) bv = models.CharField(max_length=254, blank=True,) bw = models.CharField(max_length=254, blank=True,) bx = models.CharField(max_length=254, blank=True,) by = models.CharField(max_length=254, blank=True,) bz = models.CharField(max_length=254, blank=True,) ca = models.CharField(max_length=254, blank=True,) cb = models.CharField(max_length=254, blank=True,) cc = models.CharField(max_length=254, blank=True,) cd = models.CharField(max_length=254, blank=True,) ce = models.CharField(max_length=254, blank=True,) class Meta: managed = True db_table = 'surveys_ecosystem2020'

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null

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34fd02b72809c479db0ff4c2ea0b86f1248ede6e

13,813

py

Python

calico/felix/test/test_endpoint.py

robbrockbank/felix

3429099d677bec0caa3dd9b8d69d1553304741ca

[ "Apache-2.0" ]

null

calico/felix/test/test_endpoint.py

robbrockbank/felix

3429099d677bec0caa3dd9b8d69d1553304741ca

[ "Apache-2.0" ]

null

calico/felix/test/test_endpoint.py

robbrockbank/felix

3429099d677bec0caa3dd9b8d69d1553304741ca

[ "Apache-2.0" ]

1

2016-12-02T12:08:32.000Z

# -*- coding: utf-8 -*- # Copyright 2014, 2015 Metaswitch Networks # # 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. """ felix.test.test_endpoint ~~~~~~~~~~~~~~~~~~~~~~~~ Tests of endpoint module. """ import gevent import logging import itertools from contextlib import nested from calico.felix.endpoint import EndpointManager from calico.felix.fiptables import IptablesUpdater from calico.felix.dispatch import DispatchChains from calico.felix.profilerules import RulesManager from gevent.event import AsyncResult import mock from mock import Mock, MagicMock, patch from calico.felix.actor import actor_message, ResultOrExc, SplitBatchAndRetry from calico.felix.test.base import BaseTestCase from calico.felix.test import stub_utils from calico.felix import config from calico.felix import devices from calico.felix import endpoint from calico.felix import futils from calico.datamodel_v1 import EndpointId _log = logging.getLogger(__name__) class TestLocalEndpoint(BaseTestCase): def setUp(self): super(TestLocalEndpoint, self).setUp() self.m_config = Mock(spec=config.Config) self.m_config.IFACE_PREFIX = "tap" self.m_iptables_updater = Mock(spec=IptablesUpdater) self.m_dispatch_chains = Mock(spec=DispatchChains) self.m_rules_mgr = Mock(spec=RulesManager) def get_local_endpoint(self, combined_id, ip_type): local_endpoint = endpoint.LocalEndpoint(self.m_config, combined_id, ip_type, self.m_iptables_updater, self.m_dispatch_chains, self.m_rules_mgr) # For purposes of our testing, we force things to happen in line. local_endpoint.greenlet = gevent.getcurrent() return local_endpoint def test_on_endpoint_update_v4(self): combined_id = EndpointId("host_id", "orchestrator_id", "workload_id", "endpoint_id") ip_type = futils.IPV4 retcode = futils.CommandOutput("", "") local_ep = self.get_local_endpoint(combined_id, ip_type) # Call with no data; should be ignored (no configuration to remove). local_ep.on_endpoint_update(None, async=False) ips = ["1.2.3.4"] iface = "tapabcdef" data = { 'endpoint': "endpoint_id", 'mac': stub_utils.get_mac(), 'name': iface, 'ipv4_nets': ips, 'profile_ids': []} # Report an initial update (endpoint creation) and check configured with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv4'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv4.assert_called_once_with(iface) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=True) # Send through an update with no changes - should redo without # resetting ARP. with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv4'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv4.assert_called_once_with(iface) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=False) # Change the MAC address and try again, leading to reset of ARP. data['mac'] = stub_utils.get_mac() with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv4'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv4.assert_called_once_with(iface) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=True) # Send empty data, which deletes the endpoint. with mock.patch('calico.felix.devices.set_routes'): local_ep.on_endpoint_update(None, async=False) devices.set_routes.assert_called_once_with(ip_type, set(), data["name"], None) def test_on_endpoint_update_v6(self): combined_id = EndpointId("host_id", "orchestrator_id", "workload_id", "endpoint_id") ip_type = futils.IPV6 retcode = futils.CommandOutput("", "") local_ep = self.get_local_endpoint(combined_id, ip_type) # Call with no data; should be ignored (no configuration to remove). local_ep.on_endpoint_update(None, async=False) ips = ["2001::abcd"] gway = "2020:ab::9876" iface = "tapabcdef" data = { 'endpoint': "endpoint_id", 'mac': stub_utils.get_mac(), 'name': iface, 'ipv6_nets': ips, 'ipv6_gateway': gway, 'profile_ids': []} # Report an initial update (endpoint creation) and check configured with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv6'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv6.assert_called_once_with(iface, gway) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=False) # Send through an update with no changes - should redo without # resetting ARP. with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv6'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv6.assert_called_once_with(iface, gway) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=False) # Send through an update with no changes - would reset ARP, but this is # IPv6 so it won't. data['mac'] = stub_utils.get_mac() with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv6'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv6.assert_called_once_with(iface, gway) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=False) # Send empty data, which deletes the endpoint. with mock.patch('calico.felix.devices.set_routes'): local_ep.on_endpoint_update(None, async=False) devices.set_routes.assert_called_once_with(ip_type, set(), data["name"], None) def test_on_interface_update_v4(self): combined_id = EndpointId("host_id", "orchestrator_id", "workload_id", "endpoint_id") ip_type = futils.IPV4 retcode = futils.CommandOutput("", "") local_ep = self.get_local_endpoint(combined_id, ip_type) ips = ["1.2.3.4"] iface = "tapabcdef" data = { 'endpoint': "endpoint_id", 'mac': stub_utils.get_mac(), 'name': iface, 'ipv4_nets': ips, 'profile_ids': []} # We can only get on_interface_update calls after the first # on_endpoint_update, so trigger that. with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv4'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv4.assert_called_once_with(iface) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=True) # Now pretend to get an interface update - does all the same work. with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv4'): local_ep.on_interface_update() devices.configure_interface_ipv4.assert_called_once_with(iface) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=True) def test_on_interface_update_v6(self): combined_id = EndpointId("host_id", "orchestrator_id", "workload_id", "endpoint_id") ip_type = futils.IPV6 retcode = futils.CommandOutput("", "") local_ep = self.get_local_endpoint(combined_id, ip_type) ips = ["1234::5678"] iface = "tapabcdef" data = { 'endpoint': "endpoint_id", 'mac': stub_utils.get_mac(), 'name': iface, 'ipv6_nets': ips, 'profile_ids': []} # We can only get on_interface_update calls after the first # on_endpoint_update, so trigger that. with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv6'): local_ep.on_endpoint_update(data, async=False) self.assertEqual(local_ep._mac, data['mac']) devices.configure_interface_ipv6.assert_called_once_with(iface, None) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=False) # Now pretend to get an interface update - does all the same work. with mock.patch('calico.felix.devices.set_routes'): with mock.patch('calico.felix.devices.configure_interface_ipv6'): local_ep.on_interface_update() devices.configure_interface_ipv6.assert_called_once_with(iface, None) devices.set_routes.assert_called_once_with(ip_type, set(ips), iface, data['mac'], reset_arp=False)

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9b605c23b365ec318b28d6a85713f7d6d8c039ff

88,666

py

Python

Lib/site-packages/OCC/BOPTools.py

JWerbrouck/RWTH_M1_Projekt

7ae63a2277361fa3273cf0677b297379482b8240

[ "bzip2-1.0.6" ]

null

Lib/site-packages/OCC/BOPTools.py

JWerbrouck/RWTH_M1_Projekt

7ae63a2277361fa3273cf0677b297379482b8240

[ "bzip2-1.0.6" ]

1

2022-03-17T16:46:04.000Z

Lib/site-packages/OCC/BOPTools.py

JWerbrouck/RWTH_M1_Projekt

7ae63a2277361fa3273cf0677b297379482b8240

[ "bzip2-1.0.6" ]

null

# This file was automatically generated by SWIG (http://www.swig.org). # Version 3.0.1 # # Do not make changes to this file unless you know what you are doing--modify # the SWIG interface file instead. from sys import version_info if version_info >= (3,0,0): new_instancemethod = lambda func, inst, cls: _BOPTools.SWIG_PyInstanceMethod_New(func) else: from new import instancemethod as new_instancemethod if version_info >= (2,6,0): def swig_import_helper(): from os.path import dirname import imp fp = None try: fp, pathname, description = imp.find_module('_BOPTools', [dirname(__file__)]) except ImportError: import _BOPTools return _BOPTools if fp is not None: try: _mod = imp.load_module('_BOPTools', fp, pathname, description) finally: fp.close() return _mod _BOPTools = swig_import_helper() del swig_import_helper else: import _BOPTools del version_info try: _swig_property = property except NameError: pass # Python < 2.2 doesn't have 'property'. def _swig_setattr_nondynamic(self,class_type,name,value,static=1): if (name == "thisown"): return self.this.own(value) if (name == "this"): if type(value).__name__ == 'SwigPyObject': self.__dict__[name] = value return method = class_type.__swig_setmethods__.get(name,None) if method: return method(self,value) if (not static): self.__dict__[name] = value else: raise AttributeError("You cannot add attributes to %s" % self) def _swig_setattr(self,class_type,name,value): return _swig_setattr_nondynamic(self,class_type,name,value,0) def _swig_getattr(self,class_type,name): if (name == "thisown"): return self.this.own() method = class_type.__swig_getmethods__.get(name,None) if method: return method(self) raise AttributeError(name) def _swig_repr(self): try: strthis = "proxy of " + self.this.__repr__() except: strthis = "" return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,) try: _object = object _newclass = 1 except AttributeError: class _object : pass _newclass = 0 def _swig_setattr_nondynamic_method(set): def set_attr(self,name,value): if (name == "thisown"): return self.this.own(value) if hasattr(self,name) or (name == "this"): set(self,name,value) else: raise AttributeError("You cannot add attributes to %s" % self) return set_attr class SwigPyIterator(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') def __init__(self, *args, **kwargs): raise AttributeError("No constructor defined - class is abstract") __repr__ = _swig_repr __swig_destroy__ = _BOPTools.delete_SwigPyIterator def __iter__(self): return self SwigPyIterator.value = new_instancemethod(_BOPTools.SwigPyIterator_value,None,SwigPyIterator) SwigPyIterator.incr = new_instancemethod(_BOPTools.SwigPyIterator_incr,None,SwigPyIterator) SwigPyIterator.decr = new_instancemethod(_BOPTools.SwigPyIterator_decr,None,SwigPyIterator) SwigPyIterator.distance = new_instancemethod(_BOPTools.SwigPyIterator_distance,None,SwigPyIterator) SwigPyIterator.equal = new_instancemethod(_BOPTools.SwigPyIterator_equal,None,SwigPyIterator) SwigPyIterator.copy = new_instancemethod(_BOPTools.SwigPyIterator_copy,None,SwigPyIterator) SwigPyIterator.next = new_instancemethod(_BOPTools.SwigPyIterator_next,None,SwigPyIterator) SwigPyIterator.__next__ = new_instancemethod(_BOPTools.SwigPyIterator___next__,None,SwigPyIterator) SwigPyIterator.previous = new_instancemethod(_BOPTools.SwigPyIterator_previous,None,SwigPyIterator) SwigPyIterator.advance = new_instancemethod(_BOPTools.SwigPyIterator_advance,None,SwigPyIterator) SwigPyIterator.__eq__ = new_instancemethod(_BOPTools.SwigPyIterator___eq__,None,SwigPyIterator) SwigPyIterator.__ne__ = new_instancemethod(_BOPTools.SwigPyIterator___ne__,None,SwigPyIterator) SwigPyIterator.__iadd__ = new_instancemethod(_BOPTools.SwigPyIterator___iadd__,None,SwigPyIterator) SwigPyIterator.__isub__ = new_instancemethod(_BOPTools.SwigPyIterator___isub__,None,SwigPyIterator) SwigPyIterator.__add__ = new_instancemethod(_BOPTools.SwigPyIterator___add__,None,SwigPyIterator) SwigPyIterator.__sub__ = new_instancemethod(_BOPTools.SwigPyIterator___sub__,None,SwigPyIterator) SwigPyIterator_swigregister = _BOPTools.SwigPyIterator_swigregister SwigPyIterator_swigregister(SwigPyIterator) import OCC.TopoDS import OCC.MMgt import OCC.Standard import OCC.TCollection import OCC.TopLoc import OCC.gp import OCC.TopAbs import OCC.BOPCol import OCC.IntTools import OCC.Geom import OCC.GeomAbs import OCC.TColgp import OCC.TColStd import OCC.BRepAdaptor import OCC.Adaptor3d import OCC.Adaptor2d import OCC.Geom2d import OCC.math import OCC.GeomAdaptor import OCC.Geom2dAdaptor import OCC.BOPInt import OCC.GeomAPI import OCC.Quantity import OCC.Extrema import OCC.Approx import OCC.AppCont import OCC.AppParCurves import OCC.BRepClass3d import OCC.IntCurveSurface import OCC.Intf import OCC.Bnd import OCC.IntSurf import OCC.IntCurvesFace import OCC.Geom2dHatch import OCC.IntRes2d import OCC.HatchGen import OCC.Geom2dInt import OCC.IntCurve import OCC.ProjLib import OCC.NCollection class boptools(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def MapShapes(*args): """ :param S: :type S: TopoDS_Shape & :param M: :type M: BOPCol_MapOfShape & :rtype: void :param S: :type S: TopoDS_Shape & :param M: :type M: BOPCol_IndexedMapOfShape & :rtype: void :param S: :type S: TopoDS_Shape & :param T: :type T: TopAbs_ShapeEnum :param M: :type M: BOPCol_IndexedMapOfShape & :rtype: void """ return _BOPTools.boptools_MapShapes(*args) MapShapes = staticmethod(MapShapes) def MapShapesAndAncestors(*args): """ :param S: :type S: TopoDS_Shape & :param TS: :type TS: TopAbs_ShapeEnum :param TA: :type TA: TopAbs_ShapeEnum :param M: :type M: BOPCol_IndexedDataMapOfShapeListOfShape & :rtype: void """ return _BOPTools.boptools_MapShapesAndAncestors(*args) MapShapesAndAncestors = staticmethod(MapShapesAndAncestors) def __init__(self): _BOPTools.boptools_swiginit(self,_BOPTools.new_boptools()) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass boptools._kill_pointed = new_instancemethod(_BOPTools.boptools__kill_pointed,None,boptools) boptools_swigregister = _BOPTools.boptools_swigregister boptools_swigregister(boptools) def boptools_MapShapes(*args): """ :param S: :type S: TopoDS_Shape & :param M: :type M: BOPCol_MapOfShape & :rtype: void :param S: :type S: TopoDS_Shape & :param M: :type M: BOPCol_IndexedMapOfShape & :rtype: void :param S: :type S: TopoDS_Shape & :param T: :type T: TopAbs_ShapeEnum :param M: :type M: BOPCol_IndexedMapOfShape & :rtype: void """ return _BOPTools.boptools_MapShapes(*args) def boptools_MapShapesAndAncestors(*args): """ :param S: :type S: TopoDS_Shape & :param TS: :type TS: TopAbs_ShapeEnum :param TA: :type TA: TopAbs_ShapeEnum :param M: :type M: BOPCol_IndexedDataMapOfShapeListOfShape & :rtype: void """ return _BOPTools.boptools_MapShapesAndAncestors(*args) class BOPTools_AlgoTools(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def ComputeVV(*args): """ :param aV1: :type aV1: TopoDS_Vertex & :param aP2: :type aP2: gp_Pnt :param aTolP2: :type aTolP2: float :rtype: int :param aV1: :type aV1: TopoDS_Vertex & :param aV2: :type aV2: TopoDS_Vertex & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_ComputeVV(*args) ComputeVV = staticmethod(ComputeVV) def MakeVertex(*args): """ :param aLV: :type aLV: BOPCol_ListOfShape & :param aV: :type aV: TopoDS_Vertex & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeVertex(*args) MakeVertex = staticmethod(MakeVertex) def MakeEdge(*args): """ :param theCurve: :type theCurve: IntTools_Curve & :param theV1: :type theV1: TopoDS_Vertex & :param theT1: :type theT1: float :param theV2: :type theV2: TopoDS_Vertex & :param theT2: :type theT2: float :param theTolR3D: :type theTolR3D: float :param theE: :type theE: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeEdge(*args) MakeEdge = staticmethod(MakeEdge) def MakePCurve(*args): """ :param theE: :type theE: TopoDS_Edge & :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :param theCurve: :type theCurve: IntTools_Curve & :param thePC1: :type thePC1: bool :param thePC2: :type thePC2: bool :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakePCurve(*args) MakePCurve = staticmethod(MakePCurve) def MakeContainer(*args): """ :param theType: :type theType: TopAbs_ShapeEnum :param theShape: :type theShape: TopoDS_Shape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeContainer(*args) MakeContainer = staticmethod(MakeContainer) def IsHole(*args): """ :param aW: :type aW: TopoDS_Shape & :param aF: :type aF: TopoDS_Shape & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsHole(*args) IsHole = staticmethod(IsHole) def IsSplitToReverse(*args): """ * Returns True if the shape theSplit has opposite direction than theShape theContext - cashed geometrical tools :param theSplit: :type theSplit: TopoDS_Shape & :param theShape: :type theShape: TopoDS_Shape & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool * Returns True if normal direction of the face theShape is not the same as for the face theSplit theContext - cashed geometrical tools :param theSplit: :type theSplit: TopoDS_Face & :param theShape: :type theShape: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool :param aE1: :type aE1: TopoDS_Edge & :param aE2: :type aE2: TopoDS_Edge & :param aContext: :type aContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsSplitToReverse(*args) IsSplitToReverse = staticmethod(IsSplitToReverse) def AreFacesSameDomain(*args): """ :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_AreFacesSameDomain(*args) AreFacesSameDomain = staticmethod(AreFacesSameDomain) def CheckSameGeom(*args): """ :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_CheckSameGeom(*args) CheckSameGeom = staticmethod(CheckSameGeom) def Sense(*args): """ :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_Sense(*args) Sense = staticmethod(Sense) def GetEdgeOff(*args): """ * Returns True if the face theFace contains the edge theEdge but with opposite orientation. If the method returns True theEdgeOff is the edge founded :param theEdge: :type theEdge: TopoDS_Edge & :param theFace: :type theFace: TopoDS_Face & :param theEdgeOff: :type theEdgeOff: TopoDS_Edge & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_GetEdgeOff(*args) GetEdgeOff = staticmethod(GetEdgeOff) def GetFaceOff(*args): """ * For the face theFace and its edge theEdge finds the face suitable to produce shell. theLCEF - set of faces to search. All faces from theLCEF must share edge theEdge :param theEdge: :type theEdge: TopoDS_Edge & :param theFace: :type theFace: TopoDS_Face & :param theLCEF: :type theLCEF: BOPTools_ListOfCoupleOfShape & :param theFaceOff: :type theFaceOff: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_GetFaceOff(*args) GetFaceOff = staticmethod(GetFaceOff) def IsInternalFace(*args): """ * Returns True if the face theFace is inside of the couple of faces theFace1, theFace2. The faces theFace, theFace1, theFace2 must share the edge theEdge :param theFace: :type theFace: TopoDS_Face & :param theEdge: :type theEdge: TopoDS_Edge & :param theFace1: :type theFace1: TopoDS_Face & :param theFace2: :type theFace2: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int * Returns True if the face theFace is inside of the appropriate couple of faces (from the set theLF) . The faces of the set theLF and theFace must share the edge theEdge :param theFace: :type theFace: TopoDS_Face & :param theEdge: :type theEdge: TopoDS_Edge & :param theLF: :type theLF: BOPCol_ListOfShape & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int * Returns True if the face theFace is inside the solid theSolid. theMEF - Map Edge/Faces for theSolid theTol - value of precision of computation theContext- cahed geometrical tools :param theFace: :type theFace: TopoDS_Face & :param theSolid: :type theSolid: TopoDS_Solid & :param theMEF: :type theMEF: BOPCol_IndexedDataMapOfShapeListOfShape & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_IsInternalFace(*args) IsInternalFace = staticmethod(IsInternalFace) def GetEdgeOnFace(*args): """ * For the face theFace gets the edge theEdgeOnF that is the same as theEdge Returns True if such edge exists Returns False if there is no such edge :param theEdge: :type theEdge: TopoDS_Edge & :param theFace: :type theFace: TopoDS_Face & :param theEdgeOnF: :type theEdgeOnF: TopoDS_Edge & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_GetEdgeOnFace(*args) GetEdgeOnFace = staticmethod(GetEdgeOnFace) def ComputeState(*args): """ * Computes the 3-D state of the point thePoint toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param thePoint: :type thePoint: gp_Pnt :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State * Computes the 3-D state of the vertex theVertex toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param theVertex: :type theVertex: TopoDS_Vertex & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State * Computes the 3-D state of the edge theEdge toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param theEdge: :type theEdge: TopoDS_Edge & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State * Computes the 3-D state of the face theFace toward solid theSolid. theTol - value of precision of computation theBounds - set of edges of theFace to avoid theContext- cahed geometrical tools Returns 3-D state. :param theFace: :type theFace: TopoDS_Face & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theBounds: :type theBounds: BOPCol_IndexedMapOfShape & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State """ return _BOPTools.BOPTools_AlgoTools_ComputeState(*args) ComputeState = staticmethod(ComputeState) def ComputeStateByOnePoint(*args): """ * Computes the 3-D state of the shape theShape toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param theShape: :type theShape: TopoDS_Shape & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State """ return _BOPTools.BOPTools_AlgoTools_ComputeStateByOnePoint(*args) ComputeStateByOnePoint = staticmethod(ComputeStateByOnePoint) def MakeConnexityBlock(*args): """ * For the list of faces theLS build block theLSCB in terms of connexity by edges theMapAvoid - set of edges to avoid for the treatment :param theLS: :type theLS: BOPCol_ListOfShape & :param theMapAvoid: :type theMapAvoid: BOPCol_IndexedMapOfShape & :param theLSCB: :type theLSCB: BOPCol_ListOfShape & :param theAllocator: :type theAllocator: BOPCol_BaseAllocator & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeConnexityBlock(*args) MakeConnexityBlock = staticmethod(MakeConnexityBlock) def MakeConnexityBlocks(*args): """ * For the compound theS build the blocks theLCB (as list of compounds) in terms of connexity by the shapes of theType :param theS: :type theS: TopoDS_Shape & :param theType1: :type theType1: TopAbs_ShapeEnum :param theType2: :type theType2: TopAbs_ShapeEnum :param theLCB: :type theLCB: BOPCol_ListOfShape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeConnexityBlocks(*args) MakeConnexityBlocks = staticmethod(MakeConnexityBlocks) def OrientFacesOnShell(*args): """ :param theS: :type theS: TopoDS_Shape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_OrientFacesOnShell(*args) OrientFacesOnShell = staticmethod(OrientFacesOnShell) def CorrectTolerances(*args): """ * Provides valid values of tolerances for the shape <theS> <theTolMax> is max value of the tolerance that can be accepted for correction. If real value of the tolerance will be greater than <aTolMax>, the correction does not perform. :param theS: :type theS: TopoDS_Shape & :param theTolMax: default value is 0.0001 :type theTolMax: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectTolerances(*args) CorrectTolerances = staticmethod(CorrectTolerances) def CorrectCurveOnSurface(*args): """ * Provides valid values of tolerances for the shape <theS> in terms of BRepCheck_InvalidCurveOnSurface. :param theS: :type theS: TopoDS_Shape & :param theTolMax: default value is 0.0001 :type theTolMax: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectCurveOnSurface(*args) CorrectCurveOnSurface = staticmethod(CorrectCurveOnSurface) def CorrectPointOnCurve(*args): """ * Provides valid values of tolerances for the shape <theS> in terms of BRepCheck_InvalidPointOnCurve. :param theS: :type theS: TopoDS_Shape & :param theTolMax: default value is 0.0001 :type theTolMax: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectPointOnCurve(*args) CorrectPointOnCurve = staticmethod(CorrectPointOnCurve) def MakeNewVertex(*args): """ * Make a vertex using 3D-point <aP1> and 3D-tolerance value <aTol> :param aP1: :type aP1: gp_Pnt :param aTol: :type aTol: float :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void * Make a vertex using couple of vertices <aV1, aV2> :param aV1: :type aV1: TopoDS_Vertex & :param aV2: :type aV2: TopoDS_Vertex & :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void * Make a vertex in place of intersection between two edges <aE1, aE2> with parameters <aP1, aP2> :param aE1: :type aE1: TopoDS_Edge & :param aP1: :type aP1: float :param aE2: :type aE2: TopoDS_Edge & :param aP2: :type aP2: float :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void * Make a vertex in place of intersection between the edge <aE1> with parameter <aP1> and the face <aF2> :param aE1: :type aE1: TopoDS_Edge & :param aP1: :type aP1: float :param aF2: :type aF2: TopoDS_Face & :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeNewVertex(*args) MakeNewVertex = staticmethod(MakeNewVertex) def PointOnEdge(*args): """ * Compute a 3D-point on the edge <aEdge> at parameter <aPrm> :param aEdge: :type aEdge: TopoDS_Edge & :param aPrm: :type aPrm: float :param aP: :type aP: gp_Pnt :rtype: void """ return _BOPTools.BOPTools_AlgoTools_PointOnEdge(*args) PointOnEdge = staticmethod(PointOnEdge) def MakeSplitEdge(*args): """ * Make the edge from base edge <aE1> and two vertices <aV1,aV2> at parameters <aP1,aP2> :param aE1: :type aE1: TopoDS_Edge & :param aV1: :type aV1: TopoDS_Vertex & :param aP1: :type aP1: float :param aV2: :type aV2: TopoDS_Vertex & :param aP2: :type aP2: float :param aNewEdge: :type aNewEdge: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeSplitEdge(*args) MakeSplitEdge = staticmethod(MakeSplitEdge) def MakeSectEdge(*args): """ * Make the edge from 3D-Curve <aIC> and two vertices <aV1,aV2> at parameters <aP1,aP2> :param aIC: :type aIC: IntTools_Curve & :param aV1: :type aV1: TopoDS_Vertex & :param aP1: :type aP1: float :param aV2: :type aV2: TopoDS_Vertex & :param aP2: :type aP2: float :param aNewEdge: :type aNewEdge: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeSectEdge(*args) MakeSectEdge = staticmethod(MakeSectEdge) def UpdateVertex(*args): """ * Update the tolerance value for vertex <aV> taking into account the fact that <aV> lays on the curve <aIC> :param aIC: :type aIC: IntTools_Curve & :param aT: :type aT: float :param aV: :type aV: TopoDS_Vertex & :rtype: void * Update the tolerance value for vertex <aV> taking into account the fact that <aV> lays on the edge <aE> :param aE: :type aE: TopoDS_Edge & :param aT: :type aT: float :param aV: :type aV: TopoDS_Vertex & :rtype: void * Update the tolerance value for vertex <aVN> taking into account the fact that <aVN> should cover tolerance zone of <aVF> :param aVF: :type aVF: TopoDS_Vertex & :param aVN: :type aVN: TopoDS_Vertex & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_UpdateVertex(*args) UpdateVertex = staticmethod(UpdateVertex) def CorrectRange(*args): """ * Correct shrunk range <aSR> taking into account 3D-curve resolution and corresp. tolerances' values of <aE1>, <aE2> :param aE1: :type aE1: TopoDS_Edge & :param aE2: :type aE2: TopoDS_Edge & :param aSR: :type aSR: IntTools_Range & :param aNewSR: :type aNewSR: IntTools_Range & :rtype: void * Correct shrunk range <aSR> taking into account 3D-curve resolution and corresp. tolerances' values of <aE>, <aF> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aSR: :type aSR: IntTools_Range & :param aNewSR: :type aNewSR: IntTools_Range & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectRange(*args) CorrectRange = staticmethod(CorrectRange) def IsBlockInOnFace(*args): """ * Returns True if PaveBlock <aPB> lays on the face <aF>, i.e the <PB> is IN or ON in 2D of <aF> :param aShR: :type aShR: IntTools_Range & :param aF: :type aF: TopoDS_Face & :param aE: :type aE: TopoDS_Edge & :param aContext: :type aContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsBlockInOnFace(*args) IsBlockInOnFace = staticmethod(IsBlockInOnFace) def IsMicroEdge(*args): """ * Checks if it is possible to compute shrunk range for the edge <aE>. :param theEdge: :type theEdge: TopoDS_Edge & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsMicroEdge(*args) IsMicroEdge = staticmethod(IsMicroEdge) def CorrectShapeTolerances(*args): """ * Corrects tolerance values of the sub-shapes of the shape <theS> if needed. :param theS: :type theS: TopoDS_Shape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectShapeTolerances(*args) CorrectShapeTolerances = staticmethod(CorrectShapeTolerances) def Dimension(*args): """ * Retutns dimension of the shape <theS>. :param theS: :type theS: TopoDS_Shape & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_Dimension(*args) Dimension = staticmethod(Dimension) def IsOpenShell(*args): """ * Returns true if the shell <theShell> is open :param theShell: :type theShell: TopoDS_Shell & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsOpenShell(*args) IsOpenShell = staticmethod(IsOpenShell) def IsInvertedSolid(*args): """ * Returns true if the solid <theSolid> is inverted :param theSolid: :type theSolid: TopoDS_Solid & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsInvertedSolid(*args) IsInvertedSolid = staticmethod(IsInvertedSolid) def __init__(self): _BOPTools.BOPTools_AlgoTools_swiginit(self,_BOPTools.new_BOPTools_AlgoTools()) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_AlgoTools._kill_pointed = new_instancemethod(_BOPTools.BOPTools_AlgoTools__kill_pointed,None,BOPTools_AlgoTools) BOPTools_AlgoTools_swigregister = _BOPTools.BOPTools_AlgoTools_swigregister BOPTools_AlgoTools_swigregister(BOPTools_AlgoTools) def BOPTools_AlgoTools_ComputeVV(*args): """ :param aV1: :type aV1: TopoDS_Vertex & :param aP2: :type aP2: gp_Pnt :param aTolP2: :type aTolP2: float :rtype: int :param aV1: :type aV1: TopoDS_Vertex & :param aV2: :type aV2: TopoDS_Vertex & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_ComputeVV(*args) def BOPTools_AlgoTools_MakeVertex(*args): """ :param aLV: :type aLV: BOPCol_ListOfShape & :param aV: :type aV: TopoDS_Vertex & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeVertex(*args) def BOPTools_AlgoTools_MakeEdge(*args): """ :param theCurve: :type theCurve: IntTools_Curve & :param theV1: :type theV1: TopoDS_Vertex & :param theT1: :type theT1: float :param theV2: :type theV2: TopoDS_Vertex & :param theT2: :type theT2: float :param theTolR3D: :type theTolR3D: float :param theE: :type theE: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeEdge(*args) def BOPTools_AlgoTools_MakePCurve(*args): """ :param theE: :type theE: TopoDS_Edge & :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :param theCurve: :type theCurve: IntTools_Curve & :param thePC1: :type thePC1: bool :param thePC2: :type thePC2: bool :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakePCurve(*args) def BOPTools_AlgoTools_MakeContainer(*args): """ :param theType: :type theType: TopAbs_ShapeEnum :param theShape: :type theShape: TopoDS_Shape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeContainer(*args) def BOPTools_AlgoTools_IsHole(*args): """ :param aW: :type aW: TopoDS_Shape & :param aF: :type aF: TopoDS_Shape & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsHole(*args) def BOPTools_AlgoTools_IsSplitToReverse(*args): """ * Returns True if the shape theSplit has opposite direction than theShape theContext - cashed geometrical tools :param theSplit: :type theSplit: TopoDS_Shape & :param theShape: :type theShape: TopoDS_Shape & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool * Returns True if normal direction of the face theShape is not the same as for the face theSplit theContext - cashed geometrical tools :param theSplit: :type theSplit: TopoDS_Face & :param theShape: :type theShape: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool :param aE1: :type aE1: TopoDS_Edge & :param aE2: :type aE2: TopoDS_Edge & :param aContext: :type aContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsSplitToReverse(*args) def BOPTools_AlgoTools_AreFacesSameDomain(*args): """ :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_AreFacesSameDomain(*args) def BOPTools_AlgoTools_CheckSameGeom(*args): """ :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_CheckSameGeom(*args) def BOPTools_AlgoTools_Sense(*args): """ :param theF1: :type theF1: TopoDS_Face & :param theF2: :type theF2: TopoDS_Face & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_Sense(*args) def BOPTools_AlgoTools_GetEdgeOff(*args): """ * Returns True if the face theFace contains the edge theEdge but with opposite orientation. If the method returns True theEdgeOff is the edge founded :param theEdge: :type theEdge: TopoDS_Edge & :param theFace: :type theFace: TopoDS_Face & :param theEdgeOff: :type theEdgeOff: TopoDS_Edge & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_GetEdgeOff(*args) def BOPTools_AlgoTools_GetFaceOff(*args): """ * For the face theFace and its edge theEdge finds the face suitable to produce shell. theLCEF - set of faces to search. All faces from theLCEF must share edge theEdge :param theEdge: :type theEdge: TopoDS_Edge & :param theFace: :type theFace: TopoDS_Face & :param theLCEF: :type theLCEF: BOPTools_ListOfCoupleOfShape & :param theFaceOff: :type theFaceOff: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_GetFaceOff(*args) def BOPTools_AlgoTools_IsInternalFace(*args): """ * Returns True if the face theFace is inside of the couple of faces theFace1, theFace2. The faces theFace, theFace1, theFace2 must share the edge theEdge :param theFace: :type theFace: TopoDS_Face & :param theEdge: :type theEdge: TopoDS_Edge & :param theFace1: :type theFace1: TopoDS_Face & :param theFace2: :type theFace2: TopoDS_Face & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int * Returns True if the face theFace is inside of the appropriate couple of faces (from the set theLF) . The faces of the set theLF and theFace must share the edge theEdge :param theFace: :type theFace: TopoDS_Face & :param theEdge: :type theEdge: TopoDS_Edge & :param theLF: :type theLF: BOPCol_ListOfShape & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int * Returns True if the face theFace is inside the solid theSolid. theMEF - Map Edge/Faces for theSolid theTol - value of precision of computation theContext- cahed geometrical tools :param theFace: :type theFace: TopoDS_Face & :param theSolid: :type theSolid: TopoDS_Solid & :param theMEF: :type theMEF: BOPCol_IndexedDataMapOfShapeListOfShape & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_IsInternalFace(*args) def BOPTools_AlgoTools_GetEdgeOnFace(*args): """ * For the face theFace gets the edge theEdgeOnF that is the same as theEdge Returns True if such edge exists Returns False if there is no such edge :param theEdge: :type theEdge: TopoDS_Edge & :param theFace: :type theFace: TopoDS_Face & :param theEdgeOnF: :type theEdgeOnF: TopoDS_Edge & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_GetEdgeOnFace(*args) def BOPTools_AlgoTools_ComputeState(*args): """ * Computes the 3-D state of the point thePoint toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param thePoint: :type thePoint: gp_Pnt :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State * Computes the 3-D state of the vertex theVertex toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param theVertex: :type theVertex: TopoDS_Vertex & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State * Computes the 3-D state of the edge theEdge toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param theEdge: :type theEdge: TopoDS_Edge & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State * Computes the 3-D state of the face theFace toward solid theSolid. theTol - value of precision of computation theBounds - set of edges of theFace to avoid theContext- cahed geometrical tools Returns 3-D state. :param theFace: :type theFace: TopoDS_Face & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theBounds: :type theBounds: BOPCol_IndexedMapOfShape & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State """ return _BOPTools.BOPTools_AlgoTools_ComputeState(*args) def BOPTools_AlgoTools_ComputeStateByOnePoint(*args): """ * Computes the 3-D state of the shape theShape toward solid theSolid. theTol - value of precision of computation theContext- cahed geometrical tools Returns 3-D state. :param theShape: :type theShape: TopoDS_Shape & :param theSolid: :type theSolid: TopoDS_Solid & :param theTol: :type theTol: float :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: TopAbs_State """ return _BOPTools.BOPTools_AlgoTools_ComputeStateByOnePoint(*args) def BOPTools_AlgoTools_MakeConnexityBlock(*args): """ * For the list of faces theLS build block theLSCB in terms of connexity by edges theMapAvoid - set of edges to avoid for the treatment :param theLS: :type theLS: BOPCol_ListOfShape & :param theMapAvoid: :type theMapAvoid: BOPCol_IndexedMapOfShape & :param theLSCB: :type theLSCB: BOPCol_ListOfShape & :param theAllocator: :type theAllocator: BOPCol_BaseAllocator & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeConnexityBlock(*args) def BOPTools_AlgoTools_MakeConnexityBlocks(*args): """ * For the compound theS build the blocks theLCB (as list of compounds) in terms of connexity by the shapes of theType :param theS: :type theS: TopoDS_Shape & :param theType1: :type theType1: TopAbs_ShapeEnum :param theType2: :type theType2: TopAbs_ShapeEnum :param theLCB: :type theLCB: BOPCol_ListOfShape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeConnexityBlocks(*args) def BOPTools_AlgoTools_OrientFacesOnShell(*args): """ :param theS: :type theS: TopoDS_Shape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_OrientFacesOnShell(*args) def BOPTools_AlgoTools_CorrectTolerances(*args): """ * Provides valid values of tolerances for the shape <theS> <theTolMax> is max value of the tolerance that can be accepted for correction. If real value of the tolerance will be greater than <aTolMax>, the correction does not perform. :param theS: :type theS: TopoDS_Shape & :param theTolMax: default value is 0.0001 :type theTolMax: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectTolerances(*args) def BOPTools_AlgoTools_CorrectCurveOnSurface(*args): """ * Provides valid values of tolerances for the shape <theS> in terms of BRepCheck_InvalidCurveOnSurface. :param theS: :type theS: TopoDS_Shape & :param theTolMax: default value is 0.0001 :type theTolMax: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectCurveOnSurface(*args) def BOPTools_AlgoTools_CorrectPointOnCurve(*args): """ * Provides valid values of tolerances for the shape <theS> in terms of BRepCheck_InvalidPointOnCurve. :param theS: :type theS: TopoDS_Shape & :param theTolMax: default value is 0.0001 :type theTolMax: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectPointOnCurve(*args) def BOPTools_AlgoTools_MakeNewVertex(*args): """ * Make a vertex using 3D-point <aP1> and 3D-tolerance value <aTol> :param aP1: :type aP1: gp_Pnt :param aTol: :type aTol: float :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void * Make a vertex using couple of vertices <aV1, aV2> :param aV1: :type aV1: TopoDS_Vertex & :param aV2: :type aV2: TopoDS_Vertex & :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void * Make a vertex in place of intersection between two edges <aE1, aE2> with parameters <aP1, aP2> :param aE1: :type aE1: TopoDS_Edge & :param aP1: :type aP1: float :param aE2: :type aE2: TopoDS_Edge & :param aP2: :type aP2: float :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void * Make a vertex in place of intersection between the edge <aE1> with parameter <aP1> and the face <aF2> :param aE1: :type aE1: TopoDS_Edge & :param aP1: :type aP1: float :param aF2: :type aF2: TopoDS_Face & :param aNewVertex: :type aNewVertex: TopoDS_Vertex & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeNewVertex(*args) def BOPTools_AlgoTools_PointOnEdge(*args): """ * Compute a 3D-point on the edge <aEdge> at parameter <aPrm> :param aEdge: :type aEdge: TopoDS_Edge & :param aPrm: :type aPrm: float :param aP: :type aP: gp_Pnt :rtype: void """ return _BOPTools.BOPTools_AlgoTools_PointOnEdge(*args) def BOPTools_AlgoTools_MakeSplitEdge(*args): """ * Make the edge from base edge <aE1> and two vertices <aV1,aV2> at parameters <aP1,aP2> :param aE1: :type aE1: TopoDS_Edge & :param aV1: :type aV1: TopoDS_Vertex & :param aP1: :type aP1: float :param aV2: :type aV2: TopoDS_Vertex & :param aP2: :type aP2: float :param aNewEdge: :type aNewEdge: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeSplitEdge(*args) def BOPTools_AlgoTools_MakeSectEdge(*args): """ * Make the edge from 3D-Curve <aIC> and two vertices <aV1,aV2> at parameters <aP1,aP2> :param aIC: :type aIC: IntTools_Curve & :param aV1: :type aV1: TopoDS_Vertex & :param aP1: :type aP1: float :param aV2: :type aV2: TopoDS_Vertex & :param aP2: :type aP2: float :param aNewEdge: :type aNewEdge: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_MakeSectEdge(*args) def BOPTools_AlgoTools_UpdateVertex(*args): """ * Update the tolerance value for vertex <aV> taking into account the fact that <aV> lays on the curve <aIC> :param aIC: :type aIC: IntTools_Curve & :param aT: :type aT: float :param aV: :type aV: TopoDS_Vertex & :rtype: void * Update the tolerance value for vertex <aV> taking into account the fact that <aV> lays on the edge <aE> :param aE: :type aE: TopoDS_Edge & :param aT: :type aT: float :param aV: :type aV: TopoDS_Vertex & :rtype: void * Update the tolerance value for vertex <aVN> taking into account the fact that <aVN> should cover tolerance zone of <aVF> :param aVF: :type aVF: TopoDS_Vertex & :param aVN: :type aVN: TopoDS_Vertex & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_UpdateVertex(*args) def BOPTools_AlgoTools_CorrectRange(*args): """ * Correct shrunk range <aSR> taking into account 3D-curve resolution and corresp. tolerances' values of <aE1>, <aE2> :param aE1: :type aE1: TopoDS_Edge & :param aE2: :type aE2: TopoDS_Edge & :param aSR: :type aSR: IntTools_Range & :param aNewSR: :type aNewSR: IntTools_Range & :rtype: void * Correct shrunk range <aSR> taking into account 3D-curve resolution and corresp. tolerances' values of <aE>, <aF> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aSR: :type aSR: IntTools_Range & :param aNewSR: :type aNewSR: IntTools_Range & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectRange(*args) def BOPTools_AlgoTools_IsBlockInOnFace(*args): """ * Returns True if PaveBlock <aPB> lays on the face <aF>, i.e the <PB> is IN or ON in 2D of <aF> :param aShR: :type aShR: IntTools_Range & :param aF: :type aF: TopoDS_Face & :param aE: :type aE: TopoDS_Edge & :param aContext: :type aContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsBlockInOnFace(*args) def BOPTools_AlgoTools_IsMicroEdge(*args): """ * Checks if it is possible to compute shrunk range for the edge <aE>. :param theEdge: :type theEdge: TopoDS_Edge & :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsMicroEdge(*args) def BOPTools_AlgoTools_CorrectShapeTolerances(*args): """ * Corrects tolerance values of the sub-shapes of the shape <theS> if needed. :param theS: :type theS: TopoDS_Shape & :rtype: void """ return _BOPTools.BOPTools_AlgoTools_CorrectShapeTolerances(*args) def BOPTools_AlgoTools_Dimension(*args): """ * Retutns dimension of the shape <theS>. :param theS: :type theS: TopoDS_Shape & :rtype: int """ return _BOPTools.BOPTools_AlgoTools_Dimension(*args) def BOPTools_AlgoTools_IsOpenShell(*args): """ * Returns true if the shell <theShell> is open :param theShell: :type theShell: TopoDS_Shell & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsOpenShell(*args) def BOPTools_AlgoTools_IsInvertedSolid(*args): """ * Returns true if the solid <theSolid> is inverted :param theSolid: :type theSolid: TopoDS_Solid & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools_IsInvertedSolid(*args) class BOPTools_AlgoTools2D(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def BuildPCurveForEdgeOnFace(*args): """ * Compute P-Curve for the edge <aE> on the face <aF> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_BuildPCurveForEdgeOnFace(*args) BuildPCurveForEdgeOnFace = staticmethod(BuildPCurveForEdgeOnFace) def EdgeTangent(*args): """ * Compute tangent for the edge <aE> [in 3D] at parameter <aT> :param anE: :type anE: TopoDS_Edge & :param aT: :type aT: float :param Tau: :type Tau: gp_Vec :rtype: bool """ return _BOPTools.BOPTools_AlgoTools2D_EdgeTangent(*args) EdgeTangent = staticmethod(EdgeTangent) def PointOnSurface(*args): """ * Compute surface parameters <U,V> of the face <aF> for the point from the edge <aE> at parameter <aT>. :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param U: :type U: float & :param V: :type V: float & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_PointOnSurface(*args) PointOnSurface = staticmethod(PointOnSurface) def HasCurveOnSurface(*args): """ * Returns True if the edge <aE> has P-Curve <aC> on surface <aF> . [aFirst, aLast] - range of the P-Curve [aToler] - reached tolerance If the P-Curve does not exist, aC.IsNull()=True. :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aC: :type aC: Handle_Geom2d_Curve & :param aFirst: :type aFirst: float & :param aLast: :type aLast: float & :param aToler: :type aToler: float & :rtype: bool * Returns True if the edge <aE> has P-Curve <aC> on surface <aF> . If the P-Curve does not exist, aC.IsNull()=True. :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools2D_HasCurveOnSurface(*args) HasCurveOnSurface = staticmethod(HasCurveOnSurface) def AdjustPCurveOnFace(*args): """ * Adjust P-Curve <aC2D> (3D-curve <C3D>) on surface <aF> . :param aF: :type aF: TopoDS_Face & :param C3D: :type C3D: Handle_Geom_Curve & :param aC2D: :type aC2D: Handle_Geom2d_Curve & :param aC2DA: :type aC2DA: Handle_Geom2d_Curve & :rtype: void * Adjust P-Curve <aC2D> (3D-curve <C3D>) on surface <aF> . [aT1, aT2] - range to adjust :param aF: :type aF: TopoDS_Face & :param aT1: :type aT1: float :param aT2: :type aT2: float :param aC2D: :type aC2D: Handle_Geom2d_Curve & :param aC2DA: :type aC2DA: Handle_Geom2d_Curve & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_AdjustPCurveOnFace(*args) AdjustPCurveOnFace = staticmethod(AdjustPCurveOnFace) def IntermediatePoint(*args): """ * Compute intermediate value in between [aFirst, aLast] . :param aFirst: :type aFirst: float :param aLast: :type aLast: float :rtype: float * Compute intermediate value of parameter for the edge <anE>. :param anE: :type anE: TopoDS_Edge & :rtype: float """ return _BOPTools.BOPTools_AlgoTools2D_IntermediatePoint(*args) IntermediatePoint = staticmethod(IntermediatePoint) def BuildPCurveForEdgeOnPlane(*args): """ :param theE: :type theE: TopoDS_Edge & :param theF: :type theF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_BuildPCurveForEdgeOnPlane(*args) BuildPCurveForEdgeOnPlane = staticmethod(BuildPCurveForEdgeOnPlane) def BuildPCurveForEdgesOnPlane(*args): """ :param theLE: :type theLE: BOPCol_ListOfShape & :param theF: :type theF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_BuildPCurveForEdgesOnPlane(*args) BuildPCurveForEdgesOnPlane = staticmethod(BuildPCurveForEdgesOnPlane) def Make2D(*args): """ * Make P-Curve <aC> for the edge <aE> on surface <aF> . [aFirst, aLast] - range of the P-Curve [aToler] - reached tolerance :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aC: :type aC: Handle_Geom2d_Curve & :param aFirst: :type aFirst: float & :param aLast: :type aLast: float & :param aToler: :type aToler: float & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_Make2D(*args) Make2D = staticmethod(Make2D) def MakePCurveOnFace(*args): """ * Make P-Curve <aC> for the 3D-curve <C3D> on surface <aF> . [aToler] - reached tolerance :param aF: :type aF: TopoDS_Face & :param C3D: :type C3D: Handle_Geom_Curve & :param aC: :type aC: Handle_Geom2d_Curve & :param aToler: :type aToler: float & :rtype: void * Make P-Curve <aC> for the 3D-curve <C3D> on surface <aF> . [aT1, aT2] - range to build [aToler] - reached tolerance :param aF: :type aF: TopoDS_Face & :param C3D: :type C3D: Handle_Geom_Curve & :param aT1: :type aT1: float :param aT2: :type aT2: float :param aC: :type aC: Handle_Geom2d_Curve & :param aToler: :type aToler: float & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_MakePCurveOnFace(*args) MakePCurveOnFace = staticmethod(MakePCurveOnFace) def MakePCurveOfType(*args): """ * Make empty P-Curve <aC> of relevant to <PC> type :param PC: :type PC: ProjLib_ProjectedCurve & :param aC: :type aC: Handle_Geom2d_Curve & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_MakePCurveOfType(*args) MakePCurveOfType = staticmethod(MakePCurveOfType) def __init__(self): _BOPTools.BOPTools_AlgoTools2D_swiginit(self,_BOPTools.new_BOPTools_AlgoTools2D()) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_AlgoTools2D._kill_pointed = new_instancemethod(_BOPTools.BOPTools_AlgoTools2D__kill_pointed,None,BOPTools_AlgoTools2D) BOPTools_AlgoTools2D_swigregister = _BOPTools.BOPTools_AlgoTools2D_swigregister BOPTools_AlgoTools2D_swigregister(BOPTools_AlgoTools2D) def BOPTools_AlgoTools2D_BuildPCurveForEdgeOnFace(*args): """ * Compute P-Curve for the edge <aE> on the face <aF> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_BuildPCurveForEdgeOnFace(*args) def BOPTools_AlgoTools2D_EdgeTangent(*args): """ * Compute tangent for the edge <aE> [in 3D] at parameter <aT> :param anE: :type anE: TopoDS_Edge & :param aT: :type aT: float :param Tau: :type Tau: gp_Vec :rtype: bool """ return _BOPTools.BOPTools_AlgoTools2D_EdgeTangent(*args) def BOPTools_AlgoTools2D_PointOnSurface(*args): """ * Compute surface parameters <U,V> of the face <aF> for the point from the edge <aE> at parameter <aT>. :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param U: :type U: float & :param V: :type V: float & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_PointOnSurface(*args) def BOPTools_AlgoTools2D_HasCurveOnSurface(*args): """ * Returns True if the edge <aE> has P-Curve <aC> on surface <aF> . [aFirst, aLast] - range of the P-Curve [aToler] - reached tolerance If the P-Curve does not exist, aC.IsNull()=True. :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aC: :type aC: Handle_Geom2d_Curve & :param aFirst: :type aFirst: float & :param aLast: :type aLast: float & :param aToler: :type aToler: float & :rtype: bool * Returns True if the edge <aE> has P-Curve <aC> on surface <aF> . If the P-Curve does not exist, aC.IsNull()=True. :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools2D_HasCurveOnSurface(*args) def BOPTools_AlgoTools2D_AdjustPCurveOnFace(*args): """ * Adjust P-Curve <aC2D> (3D-curve <C3D>) on surface <aF> . :param aF: :type aF: TopoDS_Face & :param C3D: :type C3D: Handle_Geom_Curve & :param aC2D: :type aC2D: Handle_Geom2d_Curve & :param aC2DA: :type aC2DA: Handle_Geom2d_Curve & :rtype: void * Adjust P-Curve <aC2D> (3D-curve <C3D>) on surface <aF> . [aT1, aT2] - range to adjust :param aF: :type aF: TopoDS_Face & :param aT1: :type aT1: float :param aT2: :type aT2: float :param aC2D: :type aC2D: Handle_Geom2d_Curve & :param aC2DA: :type aC2DA: Handle_Geom2d_Curve & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_AdjustPCurveOnFace(*args) def BOPTools_AlgoTools2D_IntermediatePoint(*args): """ * Compute intermediate value in between [aFirst, aLast] . :param aFirst: :type aFirst: float :param aLast: :type aLast: float :rtype: float * Compute intermediate value of parameter for the edge <anE>. :param anE: :type anE: TopoDS_Edge & :rtype: float """ return _BOPTools.BOPTools_AlgoTools2D_IntermediatePoint(*args) def BOPTools_AlgoTools2D_BuildPCurveForEdgeOnPlane(*args): """ :param theE: :type theE: TopoDS_Edge & :param theF: :type theF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_BuildPCurveForEdgeOnPlane(*args) def BOPTools_AlgoTools2D_BuildPCurveForEdgesOnPlane(*args): """ :param theLE: :type theLE: BOPCol_ListOfShape & :param theF: :type theF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_BuildPCurveForEdgesOnPlane(*args) def BOPTools_AlgoTools2D_Make2D(*args): """ * Make P-Curve <aC> for the edge <aE> on surface <aF> . [aFirst, aLast] - range of the P-Curve [aToler] - reached tolerance :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aC: :type aC: Handle_Geom2d_Curve & :param aFirst: :type aFirst: float & :param aLast: :type aLast: float & :param aToler: :type aToler: float & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_Make2D(*args) def BOPTools_AlgoTools2D_MakePCurveOnFace(*args): """ * Make P-Curve <aC> for the 3D-curve <C3D> on surface <aF> . [aToler] - reached tolerance :param aF: :type aF: TopoDS_Face & :param C3D: :type C3D: Handle_Geom_Curve & :param aC: :type aC: Handle_Geom2d_Curve & :param aToler: :type aToler: float & :rtype: void * Make P-Curve <aC> for the 3D-curve <C3D> on surface <aF> . [aT1, aT2] - range to build [aToler] - reached tolerance :param aF: :type aF: TopoDS_Face & :param C3D: :type C3D: Handle_Geom_Curve & :param aT1: :type aT1: float :param aT2: :type aT2: float :param aC: :type aC: Handle_Geom2d_Curve & :param aToler: :type aToler: float & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_MakePCurveOnFace(*args) def BOPTools_AlgoTools2D_MakePCurveOfType(*args): """ * Make empty P-Curve <aC> of relevant to <PC> type :param PC: :type PC: ProjLib_ProjectedCurve & :param aC: :type aC: Handle_Geom2d_Curve & :rtype: void """ return _BOPTools.BOPTools_AlgoTools2D_MakePCurveOfType(*args) class BOPTools_AlgoTools3D(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def DoSplitSEAMOnFace(*args): """ * Make the edge <aSp> seam edge for the face <aF> :param aSp: :type aSp: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_DoSplitSEAMOnFace(*args) DoSplitSEAMOnFace = staticmethod(DoSplitSEAMOnFace) def GetNormalToFaceOnEdge(*args): """ * Computes normal to the face <aF> for the point on the edge <aE> at parameter <aT> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aD: :type aD: gp_Dir :rtype: void * Computes normal to the face <aF> for the point on the edge <aE> at arbitrary intermediate parameter :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aD: :type aD: gp_Dir :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_GetNormalToFaceOnEdge(*args) GetNormalToFaceOnEdge = staticmethod(GetNormalToFaceOnEdge) def SenseFlag(*args): """ * Returns 1 if scalar product aNF1* aNF2>0. Returns 0 if directions aNF1 aNF2 coinside Returns -1 if scalar product aNF1* aNF2<0. :param aNF1: :type aNF1: gp_Dir :param aNF2: :type aNF2: gp_Dir :rtype: int """ return _BOPTools.BOPTools_AlgoTools3D_SenseFlag(*args) SenseFlag = staticmethod(SenseFlag) def GetNormalToSurface(*args): """ * Compute normal <aD> to surface <aS> in point (U,V) Returns True if directions aD1U, aD1V coinside :param aS: :type aS: Handle_Geom_Surface & :param U: :type U: float :param V: :type V: float :param aD: :type aD: gp_Dir :rtype: bool """ return _BOPTools.BOPTools_AlgoTools3D_GetNormalToSurface(*args) GetNormalToSurface = staticmethod(GetNormalToSurface) def GetApproxNormalToFaceOnEdge(*args): """ * Computes normal to the face <aF> for the 3D-point that belonds to the edge <aE> at parameter <aT>. Output: aPx - the 3D-point where the normal computed aD - the normal; Warning: The normal is computed not exactly in the point on the edge, but in point that is near to the edge towards to the face material (so, we'll have approx. normal) :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aPx: :type aPx: gp_Pnt :param aD: :type aD: gp_Dir :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: void :param theE: :type theE: TopoDS_Edge & :param theF: :type theF: TopoDS_Face & :param aT: :type aT: float :param aP: :type aP: gp_Pnt :param aDNF: :type aDNF: gp_Dir :param aDt2D: :type aDt2D: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_GetApproxNormalToFaceOnEdge(*args) GetApproxNormalToFaceOnEdge = staticmethod(GetApproxNormalToFaceOnEdge) def PointNearEdge(*args): """ * Compute the point <aPx>, (<aP2D>) that is near to the edge <aE> at parameter <aT> towards to the material of the face <aF>. The value of shifting in 2D is <aDt2D> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aDt2D: :type aDt2D: float :param aP2D: :type aP2D: gp_Pnt2d :param aPx: :type aPx: gp_Pnt :rtype: void * Computes the point <aPx>, (<aP2D>) that is near to the edge <aE> at parameter <aT> towards to the material of the face <aF>. The value of shifting in 2D is dt2D=BOPTools_AlgoTools3D::MinStepIn2d() :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aP2D: :type aP2D: gp_Pnt2d :param aPx: :type aPx: gp_Pnt :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: void * Compute the point <aPx>, (<aP2D>) that is near to the edge <aE> at arbitrary parameter towards to the material of the face <aF>. The value of shifting in 2D is dt2D=BOPTools_AlgoTools3D::MinStepIn2d() :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aP2D: :type aP2D: gp_Pnt2d :param aPx: :type aPx: gp_Pnt :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_PointNearEdge(*args) PointNearEdge = staticmethod(PointNearEdge) def MinStepIn2d(*args): """ * Returns simple step value that is used in 2D-computations = 1.e-5 :rtype: float """ return _BOPTools.BOPTools_AlgoTools3D_MinStepIn2d(*args) MinStepIn2d = staticmethod(MinStepIn2d) def IsEmptyShape(*args): """ * Returns True if the shape <aS> does not contain geometry information (e.g. empty compound) :param aS: :type aS: TopoDS_Shape & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools3D_IsEmptyShape(*args) IsEmptyShape = staticmethod(IsEmptyShape) def OrientEdgeOnFace(*args): """ * Get the edge <aER> from the face <aF> that is the same as the edge <aE> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aER: :type aER: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_OrientEdgeOnFace(*args) OrientEdgeOnFace = staticmethod(OrientEdgeOnFace) def PointInFace(*args): """ * Computes a point <theP> inside the face <theF>. <theP2D> - 2D representation of <theP> on the surface of <theF> Returns 0 in case of success. :param theF: :type theF: TopoDS_Face & :param theP: :type theP: gp_Pnt :param theP2D: :type theP2D: gp_Pnt2d :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int """ return _BOPTools.BOPTools_AlgoTools3D_PointInFace(*args) PointInFace = staticmethod(PointInFace) def __init__(self): _BOPTools.BOPTools_AlgoTools3D_swiginit(self,_BOPTools.new_BOPTools_AlgoTools3D()) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_AlgoTools3D._kill_pointed = new_instancemethod(_BOPTools.BOPTools_AlgoTools3D__kill_pointed,None,BOPTools_AlgoTools3D) BOPTools_AlgoTools3D_swigregister = _BOPTools.BOPTools_AlgoTools3D_swigregister BOPTools_AlgoTools3D_swigregister(BOPTools_AlgoTools3D) def BOPTools_AlgoTools3D_DoSplitSEAMOnFace(*args): """ * Make the edge <aSp> seam edge for the face <aF> :param aSp: :type aSp: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_DoSplitSEAMOnFace(*args) def BOPTools_AlgoTools3D_GetNormalToFaceOnEdge(*args): """ * Computes normal to the face <aF> for the point on the edge <aE> at parameter <aT> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aD: :type aD: gp_Dir :rtype: void * Computes normal to the face <aF> for the point on the edge <aE> at arbitrary intermediate parameter :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aD: :type aD: gp_Dir :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_GetNormalToFaceOnEdge(*args) def BOPTools_AlgoTools3D_SenseFlag(*args): """ * Returns 1 if scalar product aNF1* aNF2>0. Returns 0 if directions aNF1 aNF2 coinside Returns -1 if scalar product aNF1* aNF2<0. :param aNF1: :type aNF1: gp_Dir :param aNF2: :type aNF2: gp_Dir :rtype: int """ return _BOPTools.BOPTools_AlgoTools3D_SenseFlag(*args) def BOPTools_AlgoTools3D_GetNormalToSurface(*args): """ * Compute normal <aD> to surface <aS> in point (U,V) Returns True if directions aD1U, aD1V coinside :param aS: :type aS: Handle_Geom_Surface & :param U: :type U: float :param V: :type V: float :param aD: :type aD: gp_Dir :rtype: bool """ return _BOPTools.BOPTools_AlgoTools3D_GetNormalToSurface(*args) def BOPTools_AlgoTools3D_GetApproxNormalToFaceOnEdge(*args): """ * Computes normal to the face <aF> for the 3D-point that belonds to the edge <aE> at parameter <aT>. Output: aPx - the 3D-point where the normal computed aD - the normal; Warning: The normal is computed not exactly in the point on the edge, but in point that is near to the edge towards to the face material (so, we'll have approx. normal) :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aPx: :type aPx: gp_Pnt :param aD: :type aD: gp_Dir :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: void :param theE: :type theE: TopoDS_Edge & :param theF: :type theF: TopoDS_Face & :param aT: :type aT: float :param aP: :type aP: gp_Pnt :param aDNF: :type aDNF: gp_Dir :param aDt2D: :type aDt2D: float :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_GetApproxNormalToFaceOnEdge(*args) def BOPTools_AlgoTools3D_PointNearEdge(*args): """ * Compute the point <aPx>, (<aP2D>) that is near to the edge <aE> at parameter <aT> towards to the material of the face <aF>. The value of shifting in 2D is <aDt2D> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aDt2D: :type aDt2D: float :param aP2D: :type aP2D: gp_Pnt2d :param aPx: :type aPx: gp_Pnt :rtype: void * Computes the point <aPx>, (<aP2D>) that is near to the edge <aE> at parameter <aT> towards to the material of the face <aF>. The value of shifting in 2D is dt2D=BOPTools_AlgoTools3D::MinStepIn2d() :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aT: :type aT: float :param aP2D: :type aP2D: gp_Pnt2d :param aPx: :type aPx: gp_Pnt :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: void * Compute the point <aPx>, (<aP2D>) that is near to the edge <aE> at arbitrary parameter towards to the material of the face <aF>. The value of shifting in 2D is dt2D=BOPTools_AlgoTools3D::MinStepIn2d() :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aP2D: :type aP2D: gp_Pnt2d :param aPx: :type aPx: gp_Pnt :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_PointNearEdge(*args) def BOPTools_AlgoTools3D_MinStepIn2d(*args): """ * Returns simple step value that is used in 2D-computations = 1.e-5 :rtype: float """ return _BOPTools.BOPTools_AlgoTools3D_MinStepIn2d(*args) def BOPTools_AlgoTools3D_IsEmptyShape(*args): """ * Returns True if the shape <aS> does not contain geometry information (e.g. empty compound) :param aS: :type aS: TopoDS_Shape & :rtype: bool """ return _BOPTools.BOPTools_AlgoTools3D_IsEmptyShape(*args) def BOPTools_AlgoTools3D_OrientEdgeOnFace(*args): """ * Get the edge <aER> from the face <aF> that is the same as the edge <aE> :param aE: :type aE: TopoDS_Edge & :param aF: :type aF: TopoDS_Face & :param aER: :type aER: TopoDS_Edge & :rtype: void """ return _BOPTools.BOPTools_AlgoTools3D_OrientEdgeOnFace(*args) def BOPTools_AlgoTools3D_PointInFace(*args): """ * Computes a point <theP> inside the face <theF>. <theP2D> - 2D representation of <theP> on the surface of <theF> Returns 0 in case of success. :param theF: :type theF: TopoDS_Face & :param theP: :type theP: gp_Pnt :param theP2D: :type theP2D: gp_Pnt2d :param theContext: :type theContext: Handle_BOPInt_Context & :rtype: int """ return _BOPTools.BOPTools_AlgoTools3D_PointInFace(*args) class BOPTools_ConnexityBlock(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def __init__(self, *args): """ :rtype: None :param theAllocator: :type theAllocator: Handle_NCollection_BaseAllocator & :rtype: None """ _BOPTools.BOPTools_ConnexityBlock_swiginit(self,_BOPTools.new_BOPTools_ConnexityBlock(*args)) def Shapes(self, *args): """ :rtype: BOPCol_ListOfShape """ return _BOPTools.BOPTools_ConnexityBlock_Shapes(self, *args) def ChangeShapes(self, *args): """ :rtype: BOPCol_ListOfShape """ return _BOPTools.BOPTools_ConnexityBlock_ChangeShapes(self, *args) def SetRegular(self, *args): """ :param theFlag: :type theFlag: bool :rtype: None """ return _BOPTools.BOPTools_ConnexityBlock_SetRegular(self, *args) def IsRegular(self, *args): """ :rtype: bool """ return _BOPTools.BOPTools_ConnexityBlock_IsRegular(self, *args) def Loops(self, *args): """ :rtype: BOPCol_ListOfShape """ return _BOPTools.BOPTools_ConnexityBlock_Loops(self, *args) def ChangeLoops(self, *args): """ :rtype: BOPCol_ListOfShape """ return _BOPTools.BOPTools_ConnexityBlock_ChangeLoops(self, *args) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_ConnexityBlock.Shapes = new_instancemethod(_BOPTools.BOPTools_ConnexityBlock_Shapes,None,BOPTools_ConnexityBlock) BOPTools_ConnexityBlock.ChangeShapes = new_instancemethod(_BOPTools.BOPTools_ConnexityBlock_ChangeShapes,None,BOPTools_ConnexityBlock) BOPTools_ConnexityBlock.SetRegular = new_instancemethod(_BOPTools.BOPTools_ConnexityBlock_SetRegular,None,BOPTools_ConnexityBlock) BOPTools_ConnexityBlock.IsRegular = new_instancemethod(_BOPTools.BOPTools_ConnexityBlock_IsRegular,None,BOPTools_ConnexityBlock) BOPTools_ConnexityBlock.Loops = new_instancemethod(_BOPTools.BOPTools_ConnexityBlock_Loops,None,BOPTools_ConnexityBlock) BOPTools_ConnexityBlock.ChangeLoops = new_instancemethod(_BOPTools.BOPTools_ConnexityBlock_ChangeLoops,None,BOPTools_ConnexityBlock) BOPTools_ConnexityBlock._kill_pointed = new_instancemethod(_BOPTools.BOPTools_ConnexityBlock__kill_pointed,None,BOPTools_ConnexityBlock) BOPTools_ConnexityBlock_swigregister = _BOPTools.BOPTools_ConnexityBlock_swigregister BOPTools_ConnexityBlock_swigregister(BOPTools_ConnexityBlock) class BOPTools_CoupleOfShape(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def __init__(self, *args): """ :rtype: None """ _BOPTools.BOPTools_CoupleOfShape_swiginit(self,_BOPTools.new_BOPTools_CoupleOfShape(*args)) def SetShape1(self, *args): """ :param theShape: :type theShape: TopoDS_Shape & :rtype: None """ return _BOPTools.BOPTools_CoupleOfShape_SetShape1(self, *args) def Shape1(self, *args): """ :rtype: TopoDS_Shape """ return _BOPTools.BOPTools_CoupleOfShape_Shape1(self, *args) def SetShape2(self, *args): """ :param theShape: :type theShape: TopoDS_Shape & :rtype: None """ return _BOPTools.BOPTools_CoupleOfShape_SetShape2(self, *args) def Shape2(self, *args): """ :rtype: TopoDS_Shape """ return _BOPTools.BOPTools_CoupleOfShape_Shape2(self, *args) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_CoupleOfShape.SetShape1 = new_instancemethod(_BOPTools.BOPTools_CoupleOfShape_SetShape1,None,BOPTools_CoupleOfShape) BOPTools_CoupleOfShape.Shape1 = new_instancemethod(_BOPTools.BOPTools_CoupleOfShape_Shape1,None,BOPTools_CoupleOfShape) BOPTools_CoupleOfShape.SetShape2 = new_instancemethod(_BOPTools.BOPTools_CoupleOfShape_SetShape2,None,BOPTools_CoupleOfShape) BOPTools_CoupleOfShape.Shape2 = new_instancemethod(_BOPTools.BOPTools_CoupleOfShape_Shape2,None,BOPTools_CoupleOfShape) BOPTools_CoupleOfShape._kill_pointed = new_instancemethod(_BOPTools.BOPTools_CoupleOfShape__kill_pointed,None,BOPTools_CoupleOfShape) BOPTools_CoupleOfShape_swigregister = _BOPTools.BOPTools_CoupleOfShape_swigregister BOPTools_CoupleOfShape_swigregister(BOPTools_CoupleOfShape) class BOPTools_EdgeSet(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def __init__(self, *args): """ :rtype: None :param theAllocator: :type theAllocator: BOPCol_BaseAllocator & :rtype: None """ _BOPTools.BOPTools_EdgeSet_swiginit(self,_BOPTools.new_BOPTools_EdgeSet(*args)) def SetShape(self, *args): """ :param theS: :type theS: TopoDS_Shape & :rtype: None """ return _BOPTools.BOPTools_EdgeSet_SetShape(self, *args) def Shape(self, *args): """ :rtype: TopoDS_Shape """ return _BOPTools.BOPTools_EdgeSet_Shape(self, *args) def AddEdge(self, *args): """ :param theEdge: :type theEdge: TopoDS_Edge & :rtype: None """ return _BOPTools.BOPTools_EdgeSet_AddEdge(self, *args) def AddEdges(self, *args): """ :param theLS: :type theLS: BOPCol_ListOfShape & :rtype: None :param theFace: :type theFace: TopoDS_Shape & :rtype: None """ return _BOPTools.BOPTools_EdgeSet_AddEdges(self, *args) def Clear(self, *args): """ :rtype: None """ return _BOPTools.BOPTools_EdgeSet_Clear(self, *args) def Get(self, *args): """ :param theLS: :type theLS: BOPCol_ListOfShape & :rtype: None """ return _BOPTools.BOPTools_EdgeSet_Get(self, *args) def Contains(self, *args): """ :param theSet: :type theSet: BOPTools_EdgeSet & :rtype: bool """ return _BOPTools.BOPTools_EdgeSet_Contains(self, *args) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_EdgeSet.SetShape = new_instancemethod(_BOPTools.BOPTools_EdgeSet_SetShape,None,BOPTools_EdgeSet) BOPTools_EdgeSet.Shape = new_instancemethod(_BOPTools.BOPTools_EdgeSet_Shape,None,BOPTools_EdgeSet) BOPTools_EdgeSet.AddEdge = new_instancemethod(_BOPTools.BOPTools_EdgeSet_AddEdge,None,BOPTools_EdgeSet) BOPTools_EdgeSet.AddEdges = new_instancemethod(_BOPTools.BOPTools_EdgeSet_AddEdges,None,BOPTools_EdgeSet) BOPTools_EdgeSet.Clear = new_instancemethod(_BOPTools.BOPTools_EdgeSet_Clear,None,BOPTools_EdgeSet) BOPTools_EdgeSet.Get = new_instancemethod(_BOPTools.BOPTools_EdgeSet_Get,None,BOPTools_EdgeSet) BOPTools_EdgeSet.Contains = new_instancemethod(_BOPTools.BOPTools_EdgeSet_Contains,None,BOPTools_EdgeSet) BOPTools_EdgeSet._kill_pointed = new_instancemethod(_BOPTools.BOPTools_EdgeSet__kill_pointed,None,BOPTools_EdgeSet) BOPTools_EdgeSet_swigregister = _BOPTools.BOPTools_EdgeSet_swigregister BOPTools_EdgeSet_swigregister(BOPTools_EdgeSet) class BOPTools_Set(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def __init__(self, *args): """ :rtype: None :param theAllocator: :type theAllocator: BOPCol_BaseAllocator & :rtype: None """ _BOPTools.BOPTools_Set_swiginit(self,_BOPTools.new_BOPTools_Set(*args)) def Assign(self, *args): """ :param Other: :type Other: BOPTools_Set & :rtype: BOPTools_Set """ return _BOPTools.BOPTools_Set_Assign(self, *args) def Set(self, *args): """ :param Other: :type Other: BOPTools_Set & :rtype: BOPTools_Set """ return _BOPTools.BOPTools_Set_Set(self, *args) def Shape(self, *args): """ :rtype: TopoDS_Shape """ return _BOPTools.BOPTools_Set_Shape(self, *args) def Add(self, *args): """ :param theS: :type theS: TopoDS_Shape & :param theType: :type theType: TopAbs_ShapeEnum :rtype: None """ return _BOPTools.BOPTools_Set_Add(self, *args) def NbShapes(self, *args): """ :rtype: int """ return _BOPTools.BOPTools_Set_NbShapes(self, *args) def IsEqual(self, *args): """ :param aOther: :type aOther: BOPTools_Set & :rtype: bool """ return _BOPTools.BOPTools_Set_IsEqual(self, *args) def HashCode(self, *args): """ :param Upper: :type Upper: int :rtype: int """ return _BOPTools.BOPTools_Set_HashCode(self, *args) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_Set.Assign = new_instancemethod(_BOPTools.BOPTools_Set_Assign,None,BOPTools_Set) BOPTools_Set.Set = new_instancemethod(_BOPTools.BOPTools_Set_Set,None,BOPTools_Set) BOPTools_Set.Shape = new_instancemethod(_BOPTools.BOPTools_Set_Shape,None,BOPTools_Set) BOPTools_Set.Add = new_instancemethod(_BOPTools.BOPTools_Set_Add,None,BOPTools_Set) BOPTools_Set.NbShapes = new_instancemethod(_BOPTools.BOPTools_Set_NbShapes,None,BOPTools_Set) BOPTools_Set.IsEqual = new_instancemethod(_BOPTools.BOPTools_Set_IsEqual,None,BOPTools_Set) BOPTools_Set.HashCode = new_instancemethod(_BOPTools.BOPTools_Set_HashCode,None,BOPTools_Set) BOPTools_Set.__hash__ = new_instancemethod(_BOPTools.BOPTools_Set___hash__,None,BOPTools_Set) BOPTools_Set._kill_pointed = new_instancemethod(_BOPTools.BOPTools_Set__kill_pointed,None,BOPTools_Set) BOPTools_Set_swigregister = _BOPTools.BOPTools_Set_swigregister BOPTools_Set_swigregister(BOPTools_Set) class BOPTools_SetMapHasher(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def HashCode(*args): """ :param aSet: :type aSet: BOPTools_Set & :param Upper: :type Upper: int :rtype: int """ return _BOPTools.BOPTools_SetMapHasher_HashCode(*args) HashCode = staticmethod(HashCode) def IsEqual(*args): """ :param aSet1: :type aSet1: BOPTools_Set & :param aSet2: :type aSet2: BOPTools_Set & :rtype: bool """ return _BOPTools.BOPTools_SetMapHasher_IsEqual(*args) IsEqual = staticmethod(IsEqual) def __init__(self): _BOPTools.BOPTools_SetMapHasher_swiginit(self,_BOPTools.new_BOPTools_SetMapHasher()) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_SetMapHasher._kill_pointed = new_instancemethod(_BOPTools.BOPTools_SetMapHasher__kill_pointed,None,BOPTools_SetMapHasher) BOPTools_SetMapHasher_swigregister = _BOPTools.BOPTools_SetMapHasher_swigregister BOPTools_SetMapHasher_swigregister(BOPTools_SetMapHasher) def BOPTools_SetMapHasher_HashCode(*args): """ :param aSet: :type aSet: BOPTools_Set & :param Upper: :type Upper: int :rtype: int """ return _BOPTools.BOPTools_SetMapHasher_HashCode(*args) def BOPTools_SetMapHasher_IsEqual(*args): """ :param aSet1: :type aSet1: BOPTools_Set & :param aSet2: :type aSet2: BOPTools_Set & :rtype: bool """ return _BOPTools.BOPTools_SetMapHasher_IsEqual(*args) class BOPTools_ShapeSet(object): thisown = _swig_property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc='The membership flag') __repr__ = _swig_repr def __init__(self, *args): """ :rtype: None :param theAllocator: :type theAllocator: BOPCol_BaseAllocator & :rtype: None """ _BOPTools.BOPTools_ShapeSet_swiginit(self,_BOPTools.new_BOPTools_ShapeSet(*args)) def SetShape(self, *args): """ :param theS: :type theS: TopoDS_Shape & :rtype: None """ return _BOPTools.BOPTools_ShapeSet_SetShape(self, *args) def Shape(self, *args): """ :rtype: TopoDS_Shape """ return _BOPTools.BOPTools_ShapeSet_Shape(self, *args) def Add(self, *args): """ :param theLS: :type theLS: BOPCol_ListOfShape & :rtype: None :param theShape: :type theShape: TopoDS_Shape & :rtype: None :param theShape: :type theShape: TopoDS_Shape & :param theType: :type theType: TopAbs_ShapeEnum :rtype: None """ return _BOPTools.BOPTools_ShapeSet_Add(self, *args) def AddEdge(self, *args): """ :param theEdge: :type theEdge: TopoDS_Edge & :rtype: None """ return _BOPTools.BOPTools_ShapeSet_AddEdge(self, *args) def AddEdges(self, *args): """ :param theLS: :type theLS: BOPCol_ListOfShape & :rtype: None :param theFace: :type theFace: TopoDS_Shape & :rtype: None """ return _BOPTools.BOPTools_ShapeSet_AddEdges(self, *args) def Subtract(self, *args): """ :param theSet: :type theSet: BOPTools_ShapeSet & :rtype: None """ return _BOPTools.BOPTools_ShapeSet_Subtract(self, *args) def __isub__(self, *args): """ :param theSet: :type theSet: BOPTools_ShapeSet & :rtype: None """ return _BOPTools.BOPTools_ShapeSet___isub__(self, *args) def Clear(self, *args): """ :rtype: None """ return _BOPTools.BOPTools_ShapeSet_Clear(self, *args) def Get(self, *args): """ :param theLS: :type theLS: BOPCol_ListOfShape & :rtype: None """ return _BOPTools.BOPTools_ShapeSet_Get(self, *args) def Contains(self, *args): """ :param theSet: :type theSet: BOPTools_ShapeSet & :rtype: bool """ return _BOPTools.BOPTools_ShapeSet_Contains(self, *args) def __del__(self): try: self.thisown = False GarbageCollector.garbage.collect_object(self) except: pass BOPTools_ShapeSet.SetShape = new_instancemethod(_BOPTools.BOPTools_ShapeSet_SetShape,None,BOPTools_ShapeSet) BOPTools_ShapeSet.Shape = new_instancemethod(_BOPTools.BOPTools_ShapeSet_Shape,None,BOPTools_ShapeSet) BOPTools_ShapeSet.Add = new_instancemethod(_BOPTools.BOPTools_ShapeSet_Add,None,BOPTools_ShapeSet) BOPTools_ShapeSet.AddEdge = new_instancemethod(_BOPTools.BOPTools_ShapeSet_AddEdge,None,BOPTools_ShapeSet) BOPTools_ShapeSet.AddEdges = new_instancemethod(_BOPTools.BOPTools_ShapeSet_AddEdges,None,BOPTools_ShapeSet) BOPTools_ShapeSet.Subtract = new_instancemethod(_BOPTools.BOPTools_ShapeSet_Subtract,None,BOPTools_ShapeSet) BOPTools_ShapeSet.__isub__ = new_instancemethod(_BOPTools.BOPTools_ShapeSet___isub__,None,BOPTools_ShapeSet) BOPTools_ShapeSet.Clear = new_instancemethod(_BOPTools.BOPTools_ShapeSet_Clear,None,BOPTools_ShapeSet) BOPTools_ShapeSet.Get = new_instancemethod(_BOPTools.BOPTools_ShapeSet_Get,None,BOPTools_ShapeSet) BOPTools_ShapeSet.Contains = new_instancemethod(_BOPTools.BOPTools_ShapeSet_Contains,None,BOPTools_ShapeSet) BOPTools_ShapeSet._kill_pointed = new_instancemethod(_BOPTools.BOPTools_ShapeSet__kill_pointed,None,BOPTools_ShapeSet) BOPTools_ShapeSet_swigregister = _BOPTools.BOPTools_ShapeSet_swigregister BOPTools_ShapeSet_swigregister(BOPTools_ShapeSet)

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0.657197

9,983

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5.63518

0.056596

0.062002

0.059443

0.037472

0.838488

0.760701

0.751298

0.750018

0.744436

0.736099

0

0.009732

0.253705

88,666

3,030

348

29.262706

0.840429

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null

0

1

0

1

0

9

9b6c1d99746bf103a912346ed77157d7a12bec0a

49

py

Python

test_sundry/test/__main__.py

jamesabel/sundry

4f63bfa0624c88a3cd05adf2784e9e3e66e094f4

[ "MIT" ]

2

2019-10-02T06:30:27.000Z

2021-07-10T22:39:30.000Z

test_sundry/test/__main__.py

jamesabel/sundry

4f63bfa0624c88a3cd05adf2784e9e3e66e094f4

[ "MIT" ]

3

2019-03-13T17:15:58.000Z

2019-06-04T20:26:57.000Z

test_sundry/test/__main__.py

jamesabel/sundry

4f63bfa0624c88a3cd05adf2784e9e3e66e094f4

[ "MIT" ]

1

2019-03-08T21:37:29.000Z

from sundry import is_main assert not is_main()

12.25

26

0.795918

9

49

4.111111

0.777778

0.324324

0

0.163265

49

3

27

16.333333

0.902439

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0.5

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null

0

1

0

1

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1

0

7

9b8a26e9e9af044f0eedb1fd956665a5b8979d7a

3,010

py

Python

tests/terraform/checks/resource/azure/test_FunctionAppsEnableAuthentication.py

kylelaker/checkov

6eada26030a87f397a6bf1831827b3dc6c5dad2d

[ "Apache-2.0" ]

4,013

2019-12-09T13:16:54.000Z

2022-03-31T14:31:01.000Z

tests/terraform/checks/resource/azure/test_FunctionAppsEnableAuthentication.py

kylelaker/checkov

6eada26030a87f397a6bf1831827b3dc6c5dad2d

[ "Apache-2.0" ]

1,258

2019-12-17T09:55:51.000Z

2022-03-31T19:17:17.000Z

tests/terraform/checks/resource/azure/test_FunctionAppsEnableAuthentication.py

kylelaker/checkov

6eada26030a87f397a6bf1831827b3dc6c5dad2d

[ "Apache-2.0" ]

638

2019-12-19T08:57:38.000Z

2022-03-30T21:38:37.000Z

import unittest import hcl2 from checkov.terraform.checks.resource.azure.FunctionAppsEnableAuthentication import check from checkov.common.models.enums import CheckResult class TestFunctionAppsEnableAuthentication(unittest.TestCase): def test_failure_missing_authentication_block(self): hcl_res = hcl2.loads(""" resource "azurerm_function_app" "example" { name = "test-azure-functions" location = "azurerm_resource_group.example.location" resource_group_name = "azurerm_resource_group.example.name" app_service_plan_id = "azurerm_app_service_plan.example.id" storage_account_name = "azurerm_storage_account.example.name" storage_account_access_key = "azurerm_storage_account.example.primary_access_key" } """) resource_conf = hcl_res['resource'][0]['azurerm_function_app']['example'] scan_result = check.scan_resource_conf(conf=resource_conf) self.assertEqual(CheckResult.FAILED, scan_result) def test_success(self): hcl_res = hcl2.loads(""" resource "azurerm_function_app" "example" { name = "test-azure-functions" location = "azurerm_resource_group.example.location" resource_group_name = "azurerm_resource_group.example.name" app_service_plan_id = "azurerm_app_service_plan.example.id" storage_account_name = "azurerm_storage_account.example.name" storage_account_access_key = "azurerm_storage_account.example.primary_access_key" auth_settings { enabled = true } } """) resource_conf = hcl_res['resource'][0]['azurerm_function_app']['example'] scan_result = check.scan_resource_conf(conf=resource_conf) self.assertEqual(CheckResult.PASSED, scan_result) def test_failed(self): hcl_res = hcl2.loads(""" resource "azurerm_function_app" "example" { name = "test-azure-functions" location = "azurerm_resource_group.example.location" resource_group_name = "azurerm_resource_group.example.name" app_service_plan_id = "azurerm_app_service_plan.example.id" storage_account_name = "azurerm_storage_account.example.name" storage_account_access_key = "azurerm_storage_account.example.primary_access_key" auth_settings { enabled = false } } """) resource_conf = hcl_res['resource'][0]['azurerm_function_app']['example'] scan_result = check.scan_resource_conf(conf=resource_conf) self.assertEqual(CheckResult.FAILED, scan_result) if __name__ == '__main__': unittest.main()

46.307692

95

0.621927

295

3,010

5.935593

0.2

0.095945

0.061679

0.085665

0.816105

0

0.003302

0.295681

3,010

64

96

47.03125

0.822642

0

0.672727

0

0.660797

0.274086

0

0.054545

1

0.054545

false

0.018182

0.072727

0

0.145455

0

null

0

1

0

1

0

null

0

7

fd613517404f82acae209290b5971133e88ce8d3

1,476

py

Python

fastxtend/test_utils.py

warner-benjamin/fastxtend

be969749a0401acb28effad7c09c8f96f699cbcc

[ "MIT" ]

null

fastxtend/test_utils.py

warner-benjamin/fastxtend

be969749a0401acb28effad7c09c8f96f699cbcc

[ "MIT" ]

null

fastxtend/test_utils.py

warner-benjamin/fastxtend

be969749a0401acb28effad7c09c8f96f699cbcc

[ "MIT" ]

null

# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/test_utils.ipynb (unless otherwise specified). __all__ = ['test_fail', 'test', 'nequals', 'test_eq', 'test_eq_type', 'test_ne', 'is_close', 'test_close', 'test_is', 'test_shuffled', 'test_stdout', 'test_warns', 'TEST_IMAGE', 'test_fig_exists', 'ExceptionExpected', 'exception', 'synth_dbunch', 'RegModel', 'synth_learner', 'VerboseCallback', 'get_env', 'try_import', 'nvidia_smi', 'nvidia_mem', 'test_show_install', 'less_random', 'TEST_AUDIO'] # Cell from fastcore.test import (test_fail, test, nequals, test_eq, test_eq_type, test_ne, is_close, test_close, test_is, test_shuffled, test_stdout, test_warns, TEST_IMAGE, test_fig_exists, ExceptionExpected, exception) from fastai.test_utils import synth_dbunch, synth_learner, RegModel, VerboseCallback, get_env, try_import, nvidia_smi, nvidia_mem from fastai.test_utils import show_install as test_show_install from .utils import less_random # Cell #nbdev_comment _all_ = ['test_fail', 'test', 'nequals', 'test_eq', 'test_eq_type', 'test_ne', 'is_close', 'test_close', 'test_is', 'test_shuffled', 'test_stdout', 'test_warns', 'TEST_IMAGE', 'test_fig_exists', 'ExceptionExpected', 'exception', 'synth_dbunch', 'RegModel', 'synth_learner', 'VerboseCallback', 'get_env', 'try_import', 'nvidia_smi', 'nvidia_mem', 'test_show_install', 'less_random'] # Cell TEST_AUDIO = 'audio/whistle.mp3'

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195

1,476

4.994872

0.282051

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0.058522

0.7577

0.706366

0.657084

0

0.000791

0.142954

1,476

21

398

70.285714

0.76917

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0

1

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0.305785

0

1

0

false

0

0.454545

0

0.454545

0

null

0

1

0

1

0

null

0

1

0

7

bd2bf0e8287050b976aca247631e5e292bcf0670

60,424

py

Python

pybind/slxos/v16r_1_00b/spf_log_state/spf_log_levels/spf_log_events/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/spf_log_state/spf_log_levels/spf_log_events/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/spf_log_state/spf_log_levels/spf_log_events/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

1

2021-11-05T22:15:42.000Z

from operator import attrgetter import pyangbind.lib.xpathhelper as xpathhelper from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType from pyangbind.lib.base import PybindBase from decimal import Decimal from bitarray import bitarray import __builtin__ class spf_log_events(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module brocade-isis-operational - based on the path /spf-log-state/spf-log-levels/spf-log-events. Each member element of the container is represented as a class variable - with a specific YANG type. YANG Description: SPF Log event """ __slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__spf_log_index','__isis_spf_log_reason','__isis_lsp_name','__brief_reason','__event_count','__node_count','__time_stamp_ms','__duration_ms','__ipv4_routes','__ipv6_routes','__first_trigger_change','__first_trigger_time_stamp_ms','__first_trigger_detail_reason','__last_trigger_change','__last_trigger_time_stamp_ms','__last_trigger_detail_reason',) _yang_name = 'spf-log-events' _rest_name = 'spf-log-events' _pybind_generated_by = 'container' def __init__(self, *args, **kwargs): path_helper_ = kwargs.pop("path_helper", None) if path_helper_ is False: self._path_helper = False elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper): self._path_helper = path_helper_ elif hasattr(self, "_parent"): path_helper_ = getattr(self._parent, "_path_helper", False) self._path_helper = path_helper_ else: self._path_helper = False extmethods = kwargs.pop("extmethods", None) if extmethods is False: self._extmethods = False elif extmethods is not None and isinstance(extmethods, dict): self._extmethods = extmethods elif hasattr(self, "_parent"): extmethods = getattr(self._parent, "_extmethods", None) self._extmethods = extmethods else: self._extmethods = False self.__last_trigger_time_stamp_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="last-trigger-time-stamp-ms", rest_name="last-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) self.__time_stamp_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="time-stamp-ms", rest_name="time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) self.__event_count = YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="event-count", rest_name="event-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) self.__isis_spf_log_reason = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'isis-spf-reason-clear-route': {'value': 33}, u'isis-spf-reason-ispf': {'value': 41}, u'isis-spf-reason-multi-topo-config-change': {'value': 48}, u'isis-spf-reason-build-table': {'value': 2}, u'isis-spf-reason-isis-port-cfg': {'value': 37}, u'isis-spf-reason-redis-policy-change': {'value': 30}, u'isis-spf-reason-ipv4-bfd-down': {'value': 45}, u'isis-spf-reason-ipv4-alt': {'value': 3}, u'isis-spf-reason-ipv6-max-paths': {'value': 47}, u'isis-spf-reason-rtm-ecmp-change': {'value': 32}, u'isis-spf-reason-adj-state-chg': {'value': 12}, u'isis-spf-reason-overload-exit': {'value': 39}, u'isis-spf-reason-ipv6-traverse': {'value': 6}, u'isis-spf-reason-level-change': {'value': 21}, u'isis-spf-reason-ipv6-bfd-down': {'value': 46}, u'isis-spf-reason-none': {'value': 0}, u'isis-spf-reason-adj-change': {'value': 17}, u'isis-spf-reason-summary-addr-chg': {'value': 11}, u'isis-spf-reason-lsp-header': {'value': 15}, u'isis-spf-reason-kickall': {'value': 1}, u'isis-spf-reason-ipv6-alt': {'value': 5}, u'isis-spf-reason-nlpid-change': {'value': 35}, u'isis-spf-reason-build-plsp-nondis': {'value': 9}, u'isis-spf-reason-router-enable': {'value': 36}, u'isis-spf-reason-tlv-change': {'value': 24}, u'isis-spf-reason-recal-interlevel-route': {'value': 40}, u'isis-spf-reason-lsp-db-clear': {'value': 22}, u'isis-spf-reason-pspf-new-lsp': {'value': 8}, u'isis-spf-reason-ipv6addr-change': {'value': 20}, u'isis-spf-reason-attflag': {'value': 13}, u'isis-spf-reason-tlv-content-change': {'value': 25}, u'isis-spf-reason-ipaddr-change': {'value': 19}, u'isis-spf-reason-pspf-purge-lsp': {'value': 7}, u'isis-spf-reason-build-plsp': {'value': 10}, u'isis-spf-reason-tnl-state-chg': {'value': 42}, u'isis-spf-reason-clear-all-route': {'value': 34}, u'isis-spf-reason-ipaddr-cfg-change': {'value': 16}, u'isis-spf-reason-ip6metric-change': {'value': 43}, u'isis-spf-reason-redis-list-change': {'value': 29}, u'isis-spf-reason-istct-spf': {'value': 44}, u'isis-spf-reason-circ-change': {'value': 28}, u'isis-spf-reason-max-paths': {'value': 31}, u'isis-spf-reason-ipv4-traverse': {'value': 4}, u'isis-spf-reason-metric-change': {'value': 23}, u'isis-spf-reason-pspf-not-enable': {'value': 26}, u'isis-spf-reason-admin-dist': {'value': 14}, u'isis-spf-reason-user-trig': {'value': 38}, u'isis-spf-reason-overload': {'value': 27}, u'isis-spf-reason-area-change': {'value': 18}},), is_leaf=True, yang_name="isis-spf-log-reason", rest_name="isis-spf-log-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='isis-spf-log-reason-code', is_config=False) self.__spf_log_index = YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="spf-log-index", rest_name="spf-log-index", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) self.__ipv6_routes = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv6-routes", rest_name="ipv6-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) self.__brief_reason = YANGDynClass(base=unicode, is_leaf=True, yang_name="brief-reason", rest_name="brief-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) self.__first_trigger_time_stamp_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="first-trigger-time-stamp-ms", rest_name="first-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) self.__ipv4_routes = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv4-routes", rest_name="ipv4-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) self.__first_trigger_change = YANGDynClass(base=unicode, is_leaf=True, yang_name="first-trigger-change", rest_name="first-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) self.__first_trigger_detail_reason = YANGDynClass(base=unicode, is_leaf=True, yang_name="first-trigger-detail-reason", rest_name="first-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) self.__isis_lsp_name = YANGDynClass(base=unicode, is_leaf=True, yang_name="isis-lsp-name", rest_name="isis-lsp-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) self.__duration_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="duration-ms", rest_name="duration-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) self.__node_count = YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="node-count", rest_name="node-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) self.__last_trigger_detail_reason = YANGDynClass(base=unicode, is_leaf=True, yang_name="last-trigger-detail-reason", rest_name="last-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) self.__last_trigger_change = YANGDynClass(base=unicode, is_leaf=True, yang_name="last-trigger-change", rest_name="last-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) load = kwargs.pop("load", None) if args: if len(args) > 1: raise TypeError("cannot create a YANG container with >1 argument") all_attr = True for e in self._pyangbind_elements: if not hasattr(args[0], e): all_attr = False break if not all_attr: raise ValueError("Supplied object did not have the correct attributes") for e in self._pyangbind_elements: nobj = getattr(args[0], e) if nobj._changed() is False: continue setmethod = getattr(self, "_set_%s" % e) if load is None: setmethod(getattr(args[0], e)) else: setmethod(getattr(args[0], e), load=load) def _path(self): if hasattr(self, "_parent"): return self._parent._path()+[self._yang_name] else: return [u'spf-log-state', u'spf-log-levels', u'spf-log-events'] def _rest_path(self): if hasattr(self, "_parent"): if self._rest_name: return self._parent._rest_path()+[self._rest_name] else: return self._parent._rest_path() else: return [u'spf-log-state', u'spf-log-levels', u'spf-log-events'] def _get_spf_log_index(self): """ Getter method for spf_log_index, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/spf_log_index (uint16) YANG Description: SPF LOG event Index """ return self.__spf_log_index def _set_spf_log_index(self, v, load=False): """ Setter method for spf_log_index, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/spf_log_index (uint16) If this variable is read-only (config: false) in the source YANG file, then _set_spf_log_index is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_spf_log_index() directly. YANG Description: SPF LOG event Index """ parent = getattr(self, "_parent", None) if parent is not None and load is False: raise AttributeError("Cannot set keys directly when" + " within an instantiated list") if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="spf-log-index", rest_name="spf-log-index", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """spf_log_index must be of a type compatible with uint16""", 'defined-type': "uint16", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="spf-log-index", rest_name="spf-log-index", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False)""", }) self.__spf_log_index = t if hasattr(self, '_set'): self._set() def _unset_spf_log_index(self): self.__spf_log_index = YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="spf-log-index", rest_name="spf-log-index", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) def _get_isis_spf_log_reason(self): """ Getter method for isis_spf_log_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/isis_spf_log_reason (isis-spf-log-reason-code) YANG Description: ISIS SPF reason code for event """ return self.__isis_spf_log_reason def _set_isis_spf_log_reason(self, v, load=False): """ Setter method for isis_spf_log_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/isis_spf_log_reason (isis-spf-log-reason-code) If this variable is read-only (config: false) in the source YANG file, then _set_isis_spf_log_reason is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_isis_spf_log_reason() directly. YANG Description: ISIS SPF reason code for event """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'isis-spf-reason-clear-route': {'value': 33}, u'isis-spf-reason-ispf': {'value': 41}, u'isis-spf-reason-multi-topo-config-change': {'value': 48}, u'isis-spf-reason-build-table': {'value': 2}, u'isis-spf-reason-isis-port-cfg': {'value': 37}, u'isis-spf-reason-redis-policy-change': {'value': 30}, u'isis-spf-reason-ipv4-bfd-down': {'value': 45}, u'isis-spf-reason-ipv4-alt': {'value': 3}, u'isis-spf-reason-ipv6-max-paths': {'value': 47}, u'isis-spf-reason-rtm-ecmp-change': {'value': 32}, u'isis-spf-reason-adj-state-chg': {'value': 12}, u'isis-spf-reason-overload-exit': {'value': 39}, u'isis-spf-reason-ipv6-traverse': {'value': 6}, u'isis-spf-reason-level-change': {'value': 21}, u'isis-spf-reason-ipv6-bfd-down': {'value': 46}, u'isis-spf-reason-none': {'value': 0}, u'isis-spf-reason-adj-change': {'value': 17}, u'isis-spf-reason-summary-addr-chg': {'value': 11}, u'isis-spf-reason-lsp-header': {'value': 15}, u'isis-spf-reason-kickall': {'value': 1}, u'isis-spf-reason-ipv6-alt': {'value': 5}, u'isis-spf-reason-nlpid-change': {'value': 35}, u'isis-spf-reason-build-plsp-nondis': {'value': 9}, u'isis-spf-reason-router-enable': {'value': 36}, u'isis-spf-reason-tlv-change': {'value': 24}, u'isis-spf-reason-recal-interlevel-route': {'value': 40}, u'isis-spf-reason-lsp-db-clear': {'value': 22}, u'isis-spf-reason-pspf-new-lsp': {'value': 8}, u'isis-spf-reason-ipv6addr-change': {'value': 20}, u'isis-spf-reason-attflag': {'value': 13}, u'isis-spf-reason-tlv-content-change': {'value': 25}, u'isis-spf-reason-ipaddr-change': {'value': 19}, u'isis-spf-reason-pspf-purge-lsp': {'value': 7}, u'isis-spf-reason-build-plsp': {'value': 10}, u'isis-spf-reason-tnl-state-chg': {'value': 42}, u'isis-spf-reason-clear-all-route': {'value': 34}, u'isis-spf-reason-ipaddr-cfg-change': {'value': 16}, u'isis-spf-reason-ip6metric-change': {'value': 43}, u'isis-spf-reason-redis-list-change': {'value': 29}, u'isis-spf-reason-istct-spf': {'value': 44}, u'isis-spf-reason-circ-change': {'value': 28}, u'isis-spf-reason-max-paths': {'value': 31}, u'isis-spf-reason-ipv4-traverse': {'value': 4}, u'isis-spf-reason-metric-change': {'value': 23}, u'isis-spf-reason-pspf-not-enable': {'value': 26}, u'isis-spf-reason-admin-dist': {'value': 14}, u'isis-spf-reason-user-trig': {'value': 38}, u'isis-spf-reason-overload': {'value': 27}, u'isis-spf-reason-area-change': {'value': 18}},), is_leaf=True, yang_name="isis-spf-log-reason", rest_name="isis-spf-log-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='isis-spf-log-reason-code', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """isis_spf_log_reason must be of a type compatible with isis-spf-log-reason-code""", 'defined-type': "brocade-isis-operational:isis-spf-log-reason-code", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'isis-spf-reason-clear-route': {'value': 33}, u'isis-spf-reason-ispf': {'value': 41}, u'isis-spf-reason-multi-topo-config-change': {'value': 48}, u'isis-spf-reason-build-table': {'value': 2}, u'isis-spf-reason-isis-port-cfg': {'value': 37}, u'isis-spf-reason-redis-policy-change': {'value': 30}, u'isis-spf-reason-ipv4-bfd-down': {'value': 45}, u'isis-spf-reason-ipv4-alt': {'value': 3}, u'isis-spf-reason-ipv6-max-paths': {'value': 47}, u'isis-spf-reason-rtm-ecmp-change': {'value': 32}, u'isis-spf-reason-adj-state-chg': {'value': 12}, u'isis-spf-reason-overload-exit': {'value': 39}, u'isis-spf-reason-ipv6-traverse': {'value': 6}, u'isis-spf-reason-level-change': {'value': 21}, u'isis-spf-reason-ipv6-bfd-down': {'value': 46}, u'isis-spf-reason-none': {'value': 0}, u'isis-spf-reason-adj-change': {'value': 17}, u'isis-spf-reason-summary-addr-chg': {'value': 11}, u'isis-spf-reason-lsp-header': {'value': 15}, u'isis-spf-reason-kickall': {'value': 1}, u'isis-spf-reason-ipv6-alt': {'value': 5}, u'isis-spf-reason-nlpid-change': {'value': 35}, u'isis-spf-reason-build-plsp-nondis': {'value': 9}, u'isis-spf-reason-router-enable': {'value': 36}, u'isis-spf-reason-tlv-change': {'value': 24}, u'isis-spf-reason-recal-interlevel-route': {'value': 40}, u'isis-spf-reason-lsp-db-clear': {'value': 22}, u'isis-spf-reason-pspf-new-lsp': {'value': 8}, u'isis-spf-reason-ipv6addr-change': {'value': 20}, u'isis-spf-reason-attflag': {'value': 13}, u'isis-spf-reason-tlv-content-change': {'value': 25}, u'isis-spf-reason-ipaddr-change': {'value': 19}, u'isis-spf-reason-pspf-purge-lsp': {'value': 7}, u'isis-spf-reason-build-plsp': {'value': 10}, u'isis-spf-reason-tnl-state-chg': {'value': 42}, u'isis-spf-reason-clear-all-route': {'value': 34}, u'isis-spf-reason-ipaddr-cfg-change': {'value': 16}, u'isis-spf-reason-ip6metric-change': {'value': 43}, u'isis-spf-reason-redis-list-change': {'value': 29}, u'isis-spf-reason-istct-spf': {'value': 44}, u'isis-spf-reason-circ-change': {'value': 28}, u'isis-spf-reason-max-paths': {'value': 31}, u'isis-spf-reason-ipv4-traverse': {'value': 4}, u'isis-spf-reason-metric-change': {'value': 23}, u'isis-spf-reason-pspf-not-enable': {'value': 26}, u'isis-spf-reason-admin-dist': {'value': 14}, u'isis-spf-reason-user-trig': {'value': 38}, u'isis-spf-reason-overload': {'value': 27}, u'isis-spf-reason-area-change': {'value': 18}},), is_leaf=True, yang_name="isis-spf-log-reason", rest_name="isis-spf-log-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='isis-spf-log-reason-code', is_config=False)""", }) self.__isis_spf_log_reason = t if hasattr(self, '_set'): self._set() def _unset_isis_spf_log_reason(self): self.__isis_spf_log_reason = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'isis-spf-reason-clear-route': {'value': 33}, u'isis-spf-reason-ispf': {'value': 41}, u'isis-spf-reason-multi-topo-config-change': {'value': 48}, u'isis-spf-reason-build-table': {'value': 2}, u'isis-spf-reason-isis-port-cfg': {'value': 37}, u'isis-spf-reason-redis-policy-change': {'value': 30}, u'isis-spf-reason-ipv4-bfd-down': {'value': 45}, u'isis-spf-reason-ipv4-alt': {'value': 3}, u'isis-spf-reason-ipv6-max-paths': {'value': 47}, u'isis-spf-reason-rtm-ecmp-change': {'value': 32}, u'isis-spf-reason-adj-state-chg': {'value': 12}, u'isis-spf-reason-overload-exit': {'value': 39}, u'isis-spf-reason-ipv6-traverse': {'value': 6}, u'isis-spf-reason-level-change': {'value': 21}, u'isis-spf-reason-ipv6-bfd-down': {'value': 46}, u'isis-spf-reason-none': {'value': 0}, u'isis-spf-reason-adj-change': {'value': 17}, u'isis-spf-reason-summary-addr-chg': {'value': 11}, u'isis-spf-reason-lsp-header': {'value': 15}, u'isis-spf-reason-kickall': {'value': 1}, u'isis-spf-reason-ipv6-alt': {'value': 5}, u'isis-spf-reason-nlpid-change': {'value': 35}, u'isis-spf-reason-build-plsp-nondis': {'value': 9}, u'isis-spf-reason-router-enable': {'value': 36}, u'isis-spf-reason-tlv-change': {'value': 24}, u'isis-spf-reason-recal-interlevel-route': {'value': 40}, u'isis-spf-reason-lsp-db-clear': {'value': 22}, u'isis-spf-reason-pspf-new-lsp': {'value': 8}, u'isis-spf-reason-ipv6addr-change': {'value': 20}, u'isis-spf-reason-attflag': {'value': 13}, u'isis-spf-reason-tlv-content-change': {'value': 25}, u'isis-spf-reason-ipaddr-change': {'value': 19}, u'isis-spf-reason-pspf-purge-lsp': {'value': 7}, u'isis-spf-reason-build-plsp': {'value': 10}, u'isis-spf-reason-tnl-state-chg': {'value': 42}, u'isis-spf-reason-clear-all-route': {'value': 34}, u'isis-spf-reason-ipaddr-cfg-change': {'value': 16}, u'isis-spf-reason-ip6metric-change': {'value': 43}, u'isis-spf-reason-redis-list-change': {'value': 29}, u'isis-spf-reason-istct-spf': {'value': 44}, u'isis-spf-reason-circ-change': {'value': 28}, u'isis-spf-reason-max-paths': {'value': 31}, u'isis-spf-reason-ipv4-traverse': {'value': 4}, u'isis-spf-reason-metric-change': {'value': 23}, u'isis-spf-reason-pspf-not-enable': {'value': 26}, u'isis-spf-reason-admin-dist': {'value': 14}, u'isis-spf-reason-user-trig': {'value': 38}, u'isis-spf-reason-overload': {'value': 27}, u'isis-spf-reason-area-change': {'value': 18}},), is_leaf=True, yang_name="isis-spf-log-reason", rest_name="isis-spf-log-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='isis-spf-log-reason-code', is_config=False) def _get_isis_lsp_name(self): """ Getter method for isis_lsp_name, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/isis_lsp_name (string) YANG Description: ISIS SPF LSP Name """ return self.__isis_lsp_name def _set_isis_lsp_name(self, v, load=False): """ Setter method for isis_lsp_name, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/isis_lsp_name (string) If this variable is read-only (config: false) in the source YANG file, then _set_isis_lsp_name is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_isis_lsp_name() directly. YANG Description: ISIS SPF LSP Name """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=unicode, is_leaf=True, yang_name="isis-lsp-name", rest_name="isis-lsp-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """isis_lsp_name must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=unicode, is_leaf=True, yang_name="isis-lsp-name", rest_name="isis-lsp-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False)""", }) self.__isis_lsp_name = t if hasattr(self, '_set'): self._set() def _unset_isis_lsp_name(self): self.__isis_lsp_name = YANGDynClass(base=unicode, is_leaf=True, yang_name="isis-lsp-name", rest_name="isis-lsp-name", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) def _get_brief_reason(self): """ Getter method for brief_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/brief_reason (string) YANG Description: ISIS SPF reason """ return self.__brief_reason def _set_brief_reason(self, v, load=False): """ Setter method for brief_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/brief_reason (string) If this variable is read-only (config: false) in the source YANG file, then _set_brief_reason is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_brief_reason() directly. YANG Description: ISIS SPF reason """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=unicode, is_leaf=True, yang_name="brief-reason", rest_name="brief-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """brief_reason must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=unicode, is_leaf=True, yang_name="brief-reason", rest_name="brief-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False)""", }) self.__brief_reason = t if hasattr(self, '_set'): self._set() def _unset_brief_reason(self): self.__brief_reason = YANGDynClass(base=unicode, is_leaf=True, yang_name="brief-reason", rest_name="brief-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) def _get_event_count(self): """ Getter method for event_count, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/event_count (uint16) """ return self.__event_count def _set_event_count(self, v, load=False): """ Setter method for event_count, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/event_count (uint16) If this variable is read-only (config: false) in the source YANG file, then _set_event_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_event_count() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="event-count", rest_name="event-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """event_count must be of a type compatible with uint16""", 'defined-type': "uint16", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="event-count", rest_name="event-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False)""", }) self.__event_count = t if hasattr(self, '_set'): self._set() def _unset_event_count(self): self.__event_count = YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="event-count", rest_name="event-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) def _get_node_count(self): """ Getter method for node_count, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/node_count (uint16) """ return self.__node_count def _set_node_count(self, v, load=False): """ Setter method for node_count, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/node_count (uint16) If this variable is read-only (config: false) in the source YANG file, then _set_node_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_node_count() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="node-count", rest_name="node-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """node_count must be of a type compatible with uint16""", 'defined-type': "uint16", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="node-count", rest_name="node-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False)""", }) self.__node_count = t if hasattr(self, '_set'): self._set() def _unset_node_count(self): self.__node_count = YANGDynClass(base=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), is_leaf=True, yang_name="node-count", rest_name="node-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint16', is_config=False) def _get_time_stamp_ms(self): """ Getter method for time_stamp_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/time_stamp_ms (uint32) YANG Description: Time stamp in hundred millisecond """ return self.__time_stamp_ms def _set_time_stamp_ms(self, v, load=False): """ Setter method for time_stamp_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/time_stamp_ms (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_time_stamp_ms is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_time_stamp_ms() directly. YANG Description: Time stamp in hundred millisecond """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="time-stamp-ms", rest_name="time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """time_stamp_ms must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="time-stamp-ms", rest_name="time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False)""", }) self.__time_stamp_ms = t if hasattr(self, '_set'): self._set() def _unset_time_stamp_ms(self): self.__time_stamp_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="time-stamp-ms", rest_name="time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) def _get_duration_ms(self): """ Getter method for duration_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/duration_ms (uint32) YANG Description: SPF run time """ return self.__duration_ms def _set_duration_ms(self, v, load=False): """ Setter method for duration_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/duration_ms (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_duration_ms is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_duration_ms() directly. YANG Description: SPF run time """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="duration-ms", rest_name="duration-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """duration_ms must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="duration-ms", rest_name="duration-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False)""", }) self.__duration_ms = t if hasattr(self, '_set'): self._set() def _unset_duration_ms(self): self.__duration_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="duration-ms", rest_name="duration-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) def _get_ipv4_routes(self): """ Getter method for ipv4_routes, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/ipv4_routes (uint32) """ return self.__ipv4_routes def _set_ipv4_routes(self, v, load=False): """ Setter method for ipv4_routes, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/ipv4_routes (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_ipv4_routes is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_ipv4_routes() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv4-routes", rest_name="ipv4-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """ipv4_routes must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv4-routes", rest_name="ipv4-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False)""", }) self.__ipv4_routes = t if hasattr(self, '_set'): self._set() def _unset_ipv4_routes(self): self.__ipv4_routes = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv4-routes", rest_name="ipv4-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) def _get_ipv6_routes(self): """ Getter method for ipv6_routes, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/ipv6_routes (uint32) """ return self.__ipv6_routes def _set_ipv6_routes(self, v, load=False): """ Setter method for ipv6_routes, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/ipv6_routes (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_ipv6_routes is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_ipv6_routes() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv6-routes", rest_name="ipv6-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """ipv6_routes must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv6-routes", rest_name="ipv6-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False)""", }) self.__ipv6_routes = t if hasattr(self, '_set'): self._set() def _unset_ipv6_routes(self): self.__ipv6_routes = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="ipv6-routes", rest_name="ipv6-routes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) def _get_first_trigger_change(self): """ Getter method for first_trigger_change, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/first_trigger_change (string) YANG Description: Add, delete or modify event """ return self.__first_trigger_change def _set_first_trigger_change(self, v, load=False): """ Setter method for first_trigger_change, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/first_trigger_change (string) If this variable is read-only (config: false) in the source YANG file, then _set_first_trigger_change is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_first_trigger_change() directly. YANG Description: Add, delete or modify event """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=unicode, is_leaf=True, yang_name="first-trigger-change", rest_name="first-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """first_trigger_change must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=unicode, is_leaf=True, yang_name="first-trigger-change", rest_name="first-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False)""", }) self.__first_trigger_change = t if hasattr(self, '_set'): self._set() def _unset_first_trigger_change(self): self.__first_trigger_change = YANGDynClass(base=unicode, is_leaf=True, yang_name="first-trigger-change", rest_name="first-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) def _get_first_trigger_time_stamp_ms(self): """ Getter method for first_trigger_time_stamp_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/first_trigger_time_stamp_ms (uint32) YANG Description: Time stamp in hundred millisecond """ return self.__first_trigger_time_stamp_ms def _set_first_trigger_time_stamp_ms(self, v, load=False): """ Setter method for first_trigger_time_stamp_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/first_trigger_time_stamp_ms (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_first_trigger_time_stamp_ms is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_first_trigger_time_stamp_ms() directly. YANG Description: Time stamp in hundred millisecond """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="first-trigger-time-stamp-ms", rest_name="first-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """first_trigger_time_stamp_ms must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="first-trigger-time-stamp-ms", rest_name="first-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False)""", }) self.__first_trigger_time_stamp_ms = t if hasattr(self, '_set'): self._set() def _unset_first_trigger_time_stamp_ms(self): self.__first_trigger_time_stamp_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="first-trigger-time-stamp-ms", rest_name="first-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) def _get_first_trigger_detail_reason(self): """ Getter method for first_trigger_detail_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/first_trigger_detail_reason (string) YANG Description: Decoded reason for the event """ return self.__first_trigger_detail_reason def _set_first_trigger_detail_reason(self, v, load=False): """ Setter method for first_trigger_detail_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/first_trigger_detail_reason (string) If this variable is read-only (config: false) in the source YANG file, then _set_first_trigger_detail_reason is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_first_trigger_detail_reason() directly. YANG Description: Decoded reason for the event """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=unicode, is_leaf=True, yang_name="first-trigger-detail-reason", rest_name="first-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """first_trigger_detail_reason must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=unicode, is_leaf=True, yang_name="first-trigger-detail-reason", rest_name="first-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False)""", }) self.__first_trigger_detail_reason = t if hasattr(self, '_set'): self._set() def _unset_first_trigger_detail_reason(self): self.__first_trigger_detail_reason = YANGDynClass(base=unicode, is_leaf=True, yang_name="first-trigger-detail-reason", rest_name="first-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) def _get_last_trigger_change(self): """ Getter method for last_trigger_change, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/last_trigger_change (string) YANG Description: Add, delete or modify event """ return self.__last_trigger_change def _set_last_trigger_change(self, v, load=False): """ Setter method for last_trigger_change, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/last_trigger_change (string) If this variable is read-only (config: false) in the source YANG file, then _set_last_trigger_change is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_last_trigger_change() directly. YANG Description: Add, delete or modify event """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=unicode, is_leaf=True, yang_name="last-trigger-change", rest_name="last-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """last_trigger_change must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=unicode, is_leaf=True, yang_name="last-trigger-change", rest_name="last-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False)""", }) self.__last_trigger_change = t if hasattr(self, '_set'): self._set() def _unset_last_trigger_change(self): self.__last_trigger_change = YANGDynClass(base=unicode, is_leaf=True, yang_name="last-trigger-change", rest_name="last-trigger-change", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) def _get_last_trigger_time_stamp_ms(self): """ Getter method for last_trigger_time_stamp_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/last_trigger_time_stamp_ms (uint32) YANG Description: Time stamp in hundred millisecond """ return self.__last_trigger_time_stamp_ms def _set_last_trigger_time_stamp_ms(self, v, load=False): """ Setter method for last_trigger_time_stamp_ms, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/last_trigger_time_stamp_ms (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_last_trigger_time_stamp_ms is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_last_trigger_time_stamp_ms() directly. YANG Description: Time stamp in hundred millisecond """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="last-trigger-time-stamp-ms", rest_name="last-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """last_trigger_time_stamp_ms must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="last-trigger-time-stamp-ms", rest_name="last-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False)""", }) self.__last_trigger_time_stamp_ms = t if hasattr(self, '_set'): self._set() def _unset_last_trigger_time_stamp_ms(self): self.__last_trigger_time_stamp_ms = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="last-trigger-time-stamp-ms", rest_name="last-trigger-time-stamp-ms", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='uint32', is_config=False) def _get_last_trigger_detail_reason(self): """ Getter method for last_trigger_detail_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/last_trigger_detail_reason (string) YANG Description: Decoded reason for the event """ return self.__last_trigger_detail_reason def _set_last_trigger_detail_reason(self, v, load=False): """ Setter method for last_trigger_detail_reason, mapped from YANG variable /spf_log_state/spf_log_levels/spf_log_events/last_trigger_detail_reason (string) If this variable is read-only (config: false) in the source YANG file, then _set_last_trigger_detail_reason is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_last_trigger_detail_reason() directly. YANG Description: Decoded reason for the event """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=unicode, is_leaf=True, yang_name="last-trigger-detail-reason", rest_name="last-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """last_trigger_detail_reason must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=unicode, is_leaf=True, yang_name="last-trigger-detail-reason", rest_name="last-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False)""", }) self.__last_trigger_detail_reason = t if hasattr(self, '_set'): self._set() def _unset_last_trigger_detail_reason(self): self.__last_trigger_detail_reason = YANGDynClass(base=unicode, is_leaf=True, yang_name="last-trigger-detail-reason", rest_name="last-trigger-detail-reason", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-isis-operational', defining_module='brocade-isis-operational', yang_type='string', is_config=False) spf_log_index = __builtin__.property(_get_spf_log_index) isis_spf_log_reason = __builtin__.property(_get_isis_spf_log_reason) isis_lsp_name = __builtin__.property(_get_isis_lsp_name) brief_reason = __builtin__.property(_get_brief_reason) event_count = __builtin__.property(_get_event_count) node_count = __builtin__.property(_get_node_count) time_stamp_ms = __builtin__.property(_get_time_stamp_ms) duration_ms = __builtin__.property(_get_duration_ms) ipv4_routes = __builtin__.property(_get_ipv4_routes) ipv6_routes = __builtin__.property(_get_ipv6_routes) first_trigger_change = __builtin__.property(_get_first_trigger_change) first_trigger_time_stamp_ms = __builtin__.property(_get_first_trigger_time_stamp_ms) first_trigger_detail_reason = __builtin__.property(_get_first_trigger_detail_reason) last_trigger_change = __builtin__.property(_get_last_trigger_change) last_trigger_time_stamp_ms = __builtin__.property(_get_last_trigger_time_stamp_ms) last_trigger_detail_reason = __builtin__.property(_get_last_trigger_detail_reason) _pyangbind_elements = {'spf_log_index': spf_log_index, 'isis_spf_log_reason': isis_spf_log_reason, 'isis_lsp_name': isis_lsp_name, 'brief_reason': brief_reason, 'event_count': event_count, 'node_count': node_count, 'time_stamp_ms': time_stamp_ms, 'duration_ms': duration_ms, 'ipv4_routes': ipv4_routes, 'ipv6_routes': ipv6_routes, 'first_trigger_change': first_trigger_change, 'first_trigger_time_stamp_ms': first_trigger_time_stamp_ms, 'first_trigger_detail_reason': first_trigger_detail_reason, 'last_trigger_change': last_trigger_change, 'last_trigger_time_stamp_ms': last_trigger_time_stamp_ms, 'last_trigger_detail_reason': last_trigger_detail_reason, }

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bd49bdc678b87776168220a19eb9f9ced5cb2cfc

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py

Python

tests/distributions/test_combinators.py

ibab/tensorfit

53bbb324520f34335a272dc057c3ae6e9d2c575e

[ "MIT" ]

95

2016-02-29T08:25:07.000Z

2021-06-02T15:33:01.000Z

tests/distributions/test_combinators.py

tensorprob/tensorprob

53bbb324520f34335a272dc057c3ae6e9d2c575e

[ "MIT" ]

27

2016-02-29T14:49:16.000Z

2019-04-28T21:01:38.000Z

tests/distributions/test_combinators.py

ibab/tensorfit

53bbb324520f34335a272dc057c3ae6e9d2c575e

[ "MIT" ]

19

2016-02-29T00:14:34.000Z

2020-06-18T06:07:39.000Z

from __future__ import division import numpy as np import scipy.stats as st from numpy.testing import assert_array_almost_equal from tensorprob import ( Exponential, MigradOptimizer, Mix2, Mix3, MixN, Model, Normal, Parameter, Poisson ) def test_mix2_fit(): with Model() as model: mu = Parameter() sigma = Parameter(lower=1) a = Parameter(lower=0) f = Parameter(lower=0, upper=1) X1 = Normal(mu, sigma, bounds=[(-np.inf, 21), (22, np.inf)]) X2 = Exponential(a, bounds=[(-np.inf, 8), (10, np.inf)]) X12 = Mix2(f, X1, X2, bounds=[(6, 17), (18, 36)]) model.observed(X12) model.initialize({ mu: 23, sigma: 1.2, a: 0.2, f: 0.3, }) # Generate some data to fit np.random.seed(42) exp_data = np.random.exponential(10, 200000) exp_data = exp_data[(exp_data < 8) | (10 < exp_data)] # Include the data blinded by the Mix2 bounds as we use the len(norm_data) norm_data = np.random.normal(19, 2, 100000) norm_data = norm_data[ ((6 < norm_data) & (norm_data < 17)) | ((18 < norm_data) & (norm_data < 21)) | ((22 < norm_data) & (norm_data < 36)) ] data = np.concatenate([exp_data, norm_data]) data = data[((6 < data) & (data < 17)) | ((18 < data) & (data < 36))] result = model.fit(data) # Check the fit was successful assert result.success assert abs(model.state[mu] - 19) < 5e-3 assert abs(model.state[sigma] - 2) < 5e-3 assert abs(model.state[a] - 0.1) < 5e-4 assert abs(model.state[f] - (len(norm_data)/len(data))) < 5e-4 def test_mix2_fit_with_mix2_input(): with Model() as model: mu = Parameter() sigma = Parameter(lower=1, upper=4) a = Parameter(lower=0.06) b = Parameter(lower=0) f_1 = Parameter(lower=0, upper=1) f_2 = Parameter(lower=0, upper=1) X1 = Normal(mu, sigma, bounds=[(-np.inf, 21), (22, np.inf)]) X2 = Exponential(a, bounds=[(-np.inf, 8), (10, 27), (31, np.inf)]) X12 = Mix2(f_1, X1, X2, bounds=[(6, 17), (18, 36)]) X3 = Exponential(b) X123 = Mix2(f_2, X12, X3, bounds=[(6, 17), (18, 36)]) model.observed(X123) model.initialize({ mu: 23, sigma: 1.2, a: 0.2, b: 0.04, f_1: 0.3, f_2: 0.4 }) # Generate some data to fit np.random.seed(42) exp_1_data = np.random.exponential(10, 200000) exp_1_data = exp_1_data[ (6 < exp_1_data) & ((exp_1_data < 8) | (10 < exp_1_data)) & ((exp_1_data < 17) | (18 < exp_1_data)) & ((exp_1_data < 27) | (31 < exp_1_data)) & (exp_1_data < 36) ] exp_2_data = np.random.exponential(20, 200000) exp_2_data = exp_2_data[ (6 < exp_2_data) & ((exp_2_data < 17) | (18 < exp_2_data)) & (exp_2_data < 36) ] # Include the data blinded by the Mix2 bounds as we use the len(norm_data) norm_data = np.random.normal(19, 2, 100000) norm_data = norm_data[ ((6 < norm_data) & (norm_data < 17)) | ((18 < norm_data) & (norm_data < 21)) | ((22 < norm_data) & (norm_data < 36)) ] data = np.concatenate([exp_1_data, exp_2_data, norm_data]) data = data[((6 < data) & (data < 17)) | ((18 < data) & (data < 36))] result = model.fit(data) # Check the fit was successful assert result.success assert abs(model.state[mu] - 19) < 3e-2 assert abs(model.state[sigma] - 2) < 1e-3 assert abs(model.state[a] - 0.1) < 1e-3 assert abs(model.state[b] - 0.05) < 3e-4 assert abs(model.state[f_1] - (len(norm_data)/(len(exp_1_data)+len(norm_data)))) < 5e-3 assert abs(model.state[f_2] - ((len(exp_1_data)+len(norm_data))/len(data))) < 5e-4 # Check if we can access the individual components xs = np.linspace(0, 41, 1001) def allowed_point(x, bounds): @np.vectorize def allowed_point(x): for l, u in bounds: if l < x and x < u: return 1 return 0 return allowed_point(x) # Normal bounds = [(6, 17), (18, 21), (22, 36)] out1 = st.norm.pdf(xs, model.state[mu], model.state[sigma]) * allowed_point(xs, bounds) integral = sum( st.norm.cdf(u, model.state[mu], model.state[sigma]) - st.norm.cdf(l, model.state[mu], model.state[sigma]) for l, u in bounds ) out1 *= model.state[f_1] * model.state[f_2] / integral out2 = model[X1].pdf(xs) assert_array_almost_equal(out1, out2, 11) # Exponential 1 bounds = [(6, 8), (10, 17), (18, 27), (31, 36)] out1 = st.expon.pdf(xs, 0, 1/model.state[a]) * allowed_point(xs, bounds) integral = sum( st.expon.cdf(u, 0, 1/model.state[a]) - st.expon.cdf(l, 0, 1/model.state[a]) for l, u in bounds ) out1 *= (1-model.state[f_1]) * model.state[f_2] / integral out2 = model[X2].pdf(xs) assert_array_almost_equal(out1, out2, 11) # Exponential 2 bounds = [(6, 17), (18, 36)] out1 = st.expon.pdf(xs, 0, 1/model.state[b]) * allowed_point(xs, bounds) integral = sum( st.expon.cdf(u, 0, 1/model.state[b]) - st.expon.cdf(l, 0, 1/model.state[b]) for l, u in bounds ) out1 *= (1-model.state[f_2]) / integral out2 = model[X3].pdf(xs) assert_array_almost_equal(out1, out2, 11) def test_mix3_fit(): with Model() as model: mu = Parameter() sigma = Parameter(lower=1, upper=4) a = Parameter(lower=0.06) b = Parameter(lower=0) f_1 = Parameter(lower=0, upper=1) f_2 = Parameter(lower=0, upper=1) X1 = Normal(mu, sigma, bounds=[(-np.inf, 21), (22, np.inf)]) X2 = Exponential(a, bounds=[(-np.inf, 8), (10, 27), (31, np.inf)]) X3 = Exponential(b) X123 = Mix3(f_1, f_2, X1, X2, X3, bounds=[(6, 17), (18, 36)]) model.observed(X123) model.initialize({ mu: 23, sigma: 1.2, a: 0.2, b: 0.04, f_1: 0.3, f_2: 0.4 }) # Generate some data to fit np.random.seed(42) exp_1_data = np.random.exponential(10, 200000) exp_1_data = exp_1_data[ (6 < exp_1_data) & ((exp_1_data < 8) | (10 < exp_1_data)) & ((exp_1_data < 17) | (18 < exp_1_data)) & ((exp_1_data < 27) | (31 < exp_1_data)) & (exp_1_data < 36) ] exp_2_data = np.random.exponential(20, 200000) exp_2_data = exp_2_data[ (6 < exp_2_data) & ((exp_2_data < 17) | (18 < exp_2_data)) & (exp_2_data < 36) ] # Include the data blinded by the Mix2 bounds as we use the len(norm_data) norm_data = np.random.normal(19, 2, 100000) norm_data = norm_data[ ((6 < norm_data) & (norm_data < 17)) | ((18 < norm_data) & (norm_data < 21)) | ((22 < norm_data) & (norm_data < 36)) ] data = np.concatenate([exp_1_data, exp_2_data, norm_data]) data = data[((6 < data) & (data < 17)) | ((18 < data) & (data < 36))] result = model.fit(data) # Check the fit was successful assert result.success assert abs(model.state[mu] - 19) < 3e-2 assert abs(model.state[sigma] - 2) < 1e-3 assert abs(model.state[a] - 0.1) < 1e-3 assert abs(model.state[b] - 0.05) < 3e-4 assert abs(model.state[f_1] - (len(norm_data)/(len(exp_1_data)+len(norm_data)))) < 5e-3 assert abs(model.state[f_2] - ((len(exp_1_data)+len(norm_data))/len(data))) < 5e-4 # Check if we can access the individual components xs = np.linspace(0, 41, 1001) def allowed_point(x, bounds): @np.vectorize def allowed_point(x): for l, u in bounds: if l < x and x < u: return 1 return 0 return allowed_point(x) # Normal bounds = [(6, 17), (18, 21), (22, 36)] out1 = st.norm.pdf(xs, model.state[mu], model.state[sigma]) * allowed_point(xs, bounds) integral = sum( st.norm.cdf(u, model.state[mu], model.state[sigma]) - st.norm.cdf(l, model.state[mu], model.state[sigma]) for l, u in bounds ) out1 *= model.state[f_1] * model.state[f_2] / integral out2 = model[X1].pdf(xs) assert_array_almost_equal(out1, out2, 11) # Exponential 1 bounds = [(6, 8), (10, 17), (18, 27), (31, 36)] out1 = st.expon.pdf(xs, 0, 1/model.state[a]) * allowed_point(xs, bounds) integral = sum( st.expon.cdf(u, 0, 1/model.state[a]) - st.expon.cdf(l, 0, 1/model.state[a]) for l, u in bounds ) out1 *= (1-model.state[f_1]) * model.state[f_2] / integral out2 = model[X2].pdf(xs) assert_array_almost_equal(out1, out2, 11) # Exponential 2 bounds = [(6, 17), (18, 36)] out1 = st.expon.pdf(xs, 0, 1/model.state[b]) * allowed_point(xs, bounds) integral = sum( st.expon.cdf(u, 0, 1/model.state[b]) - st.expon.cdf(l, 0, 1/model.state[b]) for l, u in bounds ) out1 *= (1-model.state[f_2]) / integral out2 = model[X3].pdf(xs) assert_array_almost_equal(out1, out2, 11) def test_mixn_fit(): with Model() as model: mu = Parameter() sigma = Parameter(lower=1, upper=4) a = Parameter(lower=0.06) b = Parameter(lower=0) f_1 = Parameter(lower=0, upper=1) f_2 = Parameter(lower=0, upper=1) X1 = Normal(mu, sigma, bounds=[(-np.inf, 21), (22, np.inf)]) X2 = Exponential(a, bounds=[(-np.inf, 8), (10, 27), (31, np.inf)]) X3 = Exponential(b) X123 = MixN([f_1, f_2], [X1, X2, X3], bounds=[(6, 17), (18, 36)]) model.observed(X123) model.initialize({ mu: 23, sigma: 1.2, a: 0.2, b: 0.04, f_1: 0.3, f_2: 0.4 }) # Generate some data to fit np.random.seed(42) exp_1_data = np.random.exponential(10, 200000) exp_1_data = exp_1_data[ (6 < exp_1_data) & ((exp_1_data < 8) | (10 < exp_1_data)) & ((exp_1_data < 17) | (18 < exp_1_data)) & ((exp_1_data < 27) | (31 < exp_1_data)) & (exp_1_data < 36) ] exp_2_data = np.random.exponential(20, 200000) exp_2_data = exp_2_data[ (6 < exp_2_data) & ((exp_2_data < 17) | (18 < exp_2_data)) & (exp_2_data < 36) ] # Include the data blinded by the Mix2 bounds as we use the len(norm_data) norm_data = np.random.normal(19, 2, 100000) norm_data = norm_data[ ((6 < norm_data) & (norm_data < 17)) | ((18 < norm_data) & (norm_data < 21)) | ((22 < norm_data) & (norm_data < 36)) ] data = np.concatenate([exp_1_data, exp_2_data, norm_data]) data = data[((6 < data) & (data < 17)) | ((18 < data) & (data < 36))] result = model.fit(data) # Check the fit was successful assert result.success assert abs(model.state[mu] - 19) < 3e-2 assert abs(model.state[sigma] - 2) < 1e-3 assert abs(model.state[a] - 0.1) < 1e-3 assert abs(model.state[b] - 0.05) < 3e-4 assert abs(model.state[f_1] - (len(norm_data)/(len(exp_1_data)+len(norm_data)))) < 5e-3 assert abs(model.state[f_2] - ((len(exp_1_data)+len(norm_data))/len(data))) < 5e-4 # Check if we can access the individual components xs = np.linspace(0, 41, 1001) def allowed_point(x, bounds): @np.vectorize def allowed_point(x): for l, u in bounds: if l < x and x < u: return 1 return 0 return allowed_point(x) # Normal bounds = [(6, 17), (18, 21), (22, 36)] out1 = st.norm.pdf(xs, model.state[mu], model.state[sigma]) * allowed_point(xs, bounds) integral = sum( st.norm.cdf(u, model.state[mu], model.state[sigma]) - st.norm.cdf(l, model.state[mu], model.state[sigma]) for l, u in bounds ) out1 *= model.state[f_1] * model.state[f_2] / integral out2 = model[X1].pdf(xs) assert_array_almost_equal(out1, out2, 11) # Exponential 1 bounds = [(6, 8), (10, 17), (18, 27), (31, 36)] out1 = st.expon.pdf(xs, 0, 1/model.state[a]) * allowed_point(xs, bounds) integral = sum( st.expon.cdf(u, 0, 1/model.state[a]) - st.expon.cdf(l, 0, 1/model.state[a]) for l, u in bounds ) out1 *= (1-model.state[f_1]) * model.state[f_2] / integral out2 = model[X2].pdf(xs) assert_array_almost_equal(out1, out2, 11) # Exponential 2 bounds = [(6, 17), (18, 36)] out1 = st.expon.pdf(xs, 0, 1/model.state[b]) * allowed_point(xs, bounds) integral = sum( st.expon.cdf(u, 0, 1/model.state[b]) - st.expon.cdf(l, 0, 1/model.state[b]) for l, u in bounds ) out1 *= (1-model.state[f_2]) / integral out2 = model[X3].pdf(xs) assert_array_almost_equal(out1, out2, 11) def test_mix2_extended(): np.random.seed(0) exp_data = np.random.exponential(10, 20000) exp_data = exp_data[(6 < exp_data) & (exp_data < 36)] norm1_data = np.random.normal(19, 2, 10000) norm1_data = norm1_data[(6 < norm1_data) & (norm1_data < 36)] data = np.concatenate([exp_data, norm1_data]) data = data[((6 < data) & (data < 36))] with Model() as model: mu = Parameter() sigma = Parameter(lower=1) a = Parameter(lower=0) N1 = Parameter(lower=0) N2 = Parameter(lower=0) N = Poisson(N1+N2) X1 = Normal(mu, sigma) X2 = Exponential(a) X12 = Mix2(N1/(N1+N2), X1, X2, bounds=[(6, 36)]) model.observed(X12, N) model.initialize({ mu: 23, sigma: 1.2, a: 0.2, N1: len(data)/5, N2: len(data)*4/5 }) result = model.fit(data, np.ones_like(data)*len(data), optimizer=MigradOptimizer()) assert result.success assert abs(model.state[mu] - 19) < 3e-2 assert abs(model.state[sigma] - 2) < 3e-2 assert abs(model.state[a] - 0.1) < 1e-3 assert abs(model.state[N1] - len(norm1_data)) < np.sqrt(len(norm1_data)) assert abs(model.state[N2] - len(exp_data)) < np.sqrt(len(exp_data)) # Check if the pdf is correct xs = np.linspace(0, 41, 101) def allowed_point(x, bounds): @np.vectorize def allowed_point(x): for l, u in bounds: if l < x and x < u: return 1 return 0 return allowed_point(x) out1a = st.norm.pdf(xs, model.state[mu], model.state[sigma]) * allowed_point(xs, [(6, 36)]) integral = st.norm.cdf(36, model.state[mu], model.state[sigma]) integral -= st.norm.cdf(6, model.state[mu], model.state[sigma]) out1a *= model.state[N1] / (model.state[N1]+model.state[N2]) / integral out1b = st.expon.pdf(xs, 0, 1/model.state[a]) * allowed_point(xs, [(6, 36)]) integral = st.expon.cdf(36, 0, 1/model.state[a]) - st.expon.cdf(6, 0, 1/model.state[a]) out1b *= model.state[N2] / (model.state[N1]+model.state[N2]) / integral out1 = out1a + out1b out2 = model.pdf(xs, None) assert_array_almost_equal(out1, out2, 16)

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15,098

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null

0

1

0

1

0

null

0

7

950391e5a3c451418099d92041eb29e188f3a30d

106

py

Python

ControlFlow/5_1BoolProsirenoOR.py

Smajkan/PythonUcenjePonovo

00982fb4caacb35ed11748dcc471f26257c8e5ed

[ "CC0-1.0" ]

null

ControlFlow/5_1BoolProsirenoOR.py

Smajkan/PythonUcenjePonovo

00982fb4caacb35ed11748dcc471f26257c8e5ed

[ "CC0-1.0" ]

null

ControlFlow/5_1BoolProsirenoOR.py

Smajkan/PythonUcenjePonovo

00982fb4caacb35ed11748dcc471f26257c8e5ed

[ "CC0-1.0" ]

null

print( 1 == 1 or 2 == 2 ) print( 1 == 1 or 2 == 3 ) print( 1 != 1 or 2 == 2 ) print( 2 < 1 or 3 > 6 )

13.25

25

0.415094

24

106

1.833333

0.25

0.272727

0.477273

0.613636

0.840909

0.727273

0

0.242424

0.377358

106

7

26

15.142857

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true

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null

0

1

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1

0

13

1f28447ca26d6e3aff97e8c78f253da253ab1af2

6,968

py

Python

tests/plugins/modules/test_tripleo_shell_script.py

openstack/tripleo-operator-ansible

504216653d509ec7170640eff45c786085520e76

[ "Apache-2.0" ]

7

2020-02-05T20:44:04.000Z

2022-03-08T05:08:07.000Z

tests/plugins/modules/test_tripleo_shell_script.py

openstack/tripleo-operator-ansible

504216653d509ec7170640eff45c786085520e76

[ "Apache-2.0" ]

null

tests/plugins/modules/test_tripleo_shell_script.py

openstack/tripleo-operator-ansible

504216653d509ec7170640eff45c786085520e76

[ "Apache-2.0" ]

2

2020-05-20T15:16:17.000Z

2021-06-11T09:29:55.000Z

# Copyright 2019 Red Hat, Inc. # All Rights Reserved. # # 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. from unittest import mock from plugins.modules import tripleo_shell_script from tests import base as tests_base class TestTripleoShellScript(tests_base.TestCase): @mock.patch('os.chmod') def test_run(self, mock_chmod): mock_module = mock.Mock() mock_exit_json = mock.Mock() mock_open = mock.mock_open() mock_module.exit_json = mock_exit_json params = {'dest': '/tmo/foo.sh', 'shell_command': 'foo'} mock_module.params = params results = {} with mock.patch('plugins.modules.tripleo_shell_script.open', mock_open): tripleo_shell_script.TripleoShellScript(mock_module, results) mock_calls = [ mock.call().write(tripleo_shell_script._SHELL_HEADER), mock.call().write('foo'), mock.call().write("\n") ] mock_open.assert_has_calls(mock_calls) mock_chmod.assert_called_once_with('/tmo/foo.sh', 0o755) mock_exit_json.assert_called_once_with(changed=True) @mock.patch('os.chmod') def test_run_env(self, mock_chmod): mock_module = mock.Mock() mock_exit_json = mock.Mock() mock_open = mock.mock_open() mock_module.exit_json = mock_exit_json params = {'dest': '/tmo/foo.sh', 'shell_command': 'foo', 'shell_environment': { 'OS_CLOUD': 'undercloud'} } mock_module.params = params results = {} with mock.patch('plugins.modules.tripleo_shell_script.open', mock_open): tripleo_shell_script.TripleoShellScript(mock_module, results) mock_calls = [ mock.call().write(tripleo_shell_script._SHELL_HEADER), mock.call().write('export OS_CLOUD=undercloud\n'), mock.call().write('foo'), mock.call().write("\n") ] mock_open.assert_has_calls(mock_calls) mock_chmod.assert_called_once_with('/tmo/foo.sh', 0o755) mock_exit_json.assert_called_once_with(changed=True) @mock.patch('os.chmod') def test_run_env_avoid_none(self, mock_chmod): mock_module = mock.Mock() mock_exit_json = mock.Mock() mock_open = mock.mock_open() mock_module.exit_json = mock_exit_json params = {'dest': '/tmo/foo.sh', 'shell_command': 'foo', 'shell_environment': { 'OS_CLOUD': 'undercloud', 'FOO_BAR': None} } mock_module.params = params results = {} with mock.patch('plugins.modules.tripleo_shell_script.open', mock_open): tripleo_shell_script.TripleoShellScript(mock_module, results) mock_calls = [ mock.call().write(tripleo_shell_script._SHELL_HEADER), mock.call().write('export OS_CLOUD=undercloud\n'), mock.call().write('foo'), mock.call().write("\n") ] mock_open.assert_has_calls(mock_calls) mock_chmod.assert_called_once_with('/tmo/foo.sh', 0o755) mock_exit_json.assert_called_once_with(changed=True) @mock.patch('os.chmod') def test_run_env_quote_int(self, mock_chmod): mock_module = mock.Mock() mock_exit_json = mock.Mock() mock_open = mock.mock_open() mock_module.exit_json = mock_exit_json params = {'dest': '/tmo/foo.sh', 'shell_command': 'foo', 'shell_environment': { 'OS_CLOUD': 'undercloud', 'FOO_BAR': 1} } mock_module.params = params results = {} with mock.patch('plugins.modules.tripleo_shell_script.open', mock_open): tripleo_shell_script.TripleoShellScript(mock_module, results) mock_calls = [ mock.call().write(tripleo_shell_script._SHELL_HEADER), mock.call().write('export OS_CLOUD=undercloud\n'), mock.call().write('export FOO_BAR=1\n'), mock.call().write('foo'), mock.call().write("\n") ] mock_open.assert_has_calls(mock_calls) mock_chmod.assert_called_once_with('/tmo/foo.sh', 0o755) mock_exit_json.assert_called_once_with(changed=True) @mock.patch('os.chmod') def test_run_env_quoted(self, mock_chmod): mock_module = mock.Mock() mock_exit_json = mock.Mock() mock_open = mock.mock_open() mock_module.exit_json = mock_exit_json params = {'dest': '/tmo/foo.sh', 'shell_command': 'foo', 'shell_environment': { 'OS_CLOUD': 'undercloud', 'FILES': 'a.yaml b.yaml'} } mock_module.params = params results = {} with mock.patch('plugins.modules.tripleo_shell_script.open', mock_open): tripleo_shell_script.TripleoShellScript(mock_module, results) mock_calls = [ mock.call().write(tripleo_shell_script._SHELL_HEADER), mock.call().write('export OS_CLOUD=undercloud\n'), mock.call().write('export FILES=\'a.yaml b.yaml\'\n'), mock.call().write('foo'), mock.call().write("\n") ] mock_open.assert_has_calls(mock_calls) mock_chmod.assert_called_once_with('/tmo/foo.sh', 0o755) mock_exit_json.assert_called_once_with(changed=True) @mock.patch('os.chmod') def test_run_fail(self, mock_chmod): mock_module = mock.Mock() mock_exit_json = mock.Mock() mock_open = mock.mock_open() mock_open.side_effect = Exception('err') mock_module.exit_json = mock_exit_json params = {'dest': '/tmo/foo.sh', 'shell_command': 'foo'} mock_module.params = params results = {} with mock.patch('plugins.modules.tripleo_shell_script.open', mock_open): tripleo_shell_script.TripleoShellScript(mock_module, results) mock_exit_json.assert_called_once_with( error='err', failed=True, msg='Unable to output shell script /tmo/foo.sh: err')

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0

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0

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1

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null

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7

c80915e2d162e0a79ccae722af51d6e9d839a9d4

12,882

py

Python

integrations/sparse/test_lucenesearcher_check_irst.py

vjeronymo2/pyserini

441077bc3891a8db0e166382cf6c88ba051f289b

[ "Apache-2.0" ]

null

integrations/sparse/test_lucenesearcher_check_irst.py

vjeronymo2/pyserini

441077bc3891a8db0e166382cf6c88ba051f289b

[ "Apache-2.0" ]

null

integrations/sparse/test_lucenesearcher_check_irst.py

vjeronymo2/pyserini

441077bc3891a8db0e166382cf6c88ba051f289b

[ "Apache-2.0" ]

null

# # Pyserini: Reproducible IR research with sparse and dense representations # # 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. # import os import unittest from shutil import rmtree from random import randint from integrations.utils import run_command, parse_score class TestMsmarcoPassageIrst(unittest.TestCase): def setUp(self): curdir = os.getcwd() if curdir.endswith('sparse'): self.pyserini_root = '../..' else: self.pyserini_root = '.' self.tmp = f'tmp{randint(0, 10000)}' if(os.path.isdir(self.tmp)): rmtree(self.tmp) os.mkdir(self.tmp) self.dl19_pass = 'tools/topics-and-qrels/topics.dl19-passage.txt' self.dl20 = 'tools/topics-and-qrels/topics.dl20.txt' def test_sum_aggregation_dl19_passage(self): # dl19 passage sum topic = 'dl19-passage' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl19_pass} \ --index msmarco-v1-passage \ --output {self.tmp}/regression_test_sum.{topic}.txt \ --alpha 0.1 ') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -l 2 {topic} {self.tmp}/regression_test_sum.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3281) self.assertEqual(ndcg_score, 0.5260) def test_sum_aggregation_dl20_passage(self): # dl20 passage sum topic = 'dl20-passage' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl20} \ --index msmarco-v1-passage \ --output {self.tmp}/regression_test_sum.{topic}.txt \ --alpha 0.1 ') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -l 2 {topic} {self.tmp}/regression_test_sum.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3520) self.assertEqual(ndcg_score, 0.5578) def test_max_aggregation_dl19(self): # dl19 passage max topic = 'dl19-passage' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl19_pass} \ --index msmarco-v1-passage \ --output {self.tmp}/regression_test_max.{topic}.txt \ --alpha 0.3 \ --max-sim ') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -l 2 {topic} {self.tmp}/regression_test_max.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3286) self.assertEqual(ndcg_score, 0.5371) def test_max_aggregation_dl20_passage(self): # dl20 passage max topic = 'dl20-passage' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl20} \ --index msmarco-v1-passage \ --output {self.tmp}/regression_test_max.{topic}.txt \ --alpha 0.3 \ --max-sim') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -l 2 {topic} {self.tmp}/regression_test_max.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3357) self.assertEqual(ndcg_score, 0.5469) def tearDown(self): rmtree(self.tmp) class TestMsmarcoDocumentIrst(unittest.TestCase): def setUp(self): curdir = os.getcwd() if curdir.endswith('sparse'): self.pyserini_root = '../..' else: self.pyserini_root = '.' self.tmp = f'tmp{randint(0, 10000)}' if(os.path.isdir(self.tmp)): rmtree(self.tmp) os.mkdir(self.tmp) self.dl19_doc = 'tools/topics-and-qrels/topics.dl19-doc.txt' self.dl20 = 'tools/topics-and-qrels/topics.dl20.txt' def test_sum_aggregation_dl19_doc(self): # dl19-doc-sum topic = 'dl19-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl19_doc} \ --index msmarco-v1-doc \ --output {self.tmp}/regression_test_sum.{topic}.txt \ --alpha 0.3') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_sum.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.2524) self.assertEqual(ndcg_score, 0.5494) def test_sum_aggregation_dl20_doc(self): # dl20-doc-sum topic = 'dl20-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl20} \ --index msmarco-v1-doc \ --output {self.tmp}/regression_test_sum.{topic}.txt \ --alpha 0.3 ') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_sum.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3825) self.assertEqual(ndcg_score, 0.5559) def test_max_aggregation_dl19_doc(self): # dl19-doc-max topic = 'dl19-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl19_doc} \ --index msmarco-v1-doc \ --output {self.tmp}/regression_test_max.{topic}.txt \ --alpha 0.3 \ --max-sim') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_max.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.2204) self.assertEqual(ndcg_score, 0.4912) def test_max_aggregation_dl20_doc(self): # dl20-doc-max topic = 'dl20-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl20} \ --index msmarco-v1-doc \ --output {self.tmp}/regression_test_max.{topic}.txt \ --alpha 0.3 \ --max-sim') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_max.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3373) self.assertEqual(ndcg_score, 0.5015) def tearDown(self): rmtree(self.tmp) class TestMsmarcoDocumentSegIrst(unittest.TestCase): def setUp(self): curdir = os.getcwd() if curdir.endswith('sparse'): self.pyserini_root = '../..' else: self.pyserini_root = '.' self.tmp = f'tmp{randint(0, 10000)}' if(os.path.isdir(self.tmp)): rmtree(self.tmp) os.mkdir(self.tmp) self.dl19_doc = 'tools/topics-and-qrels/topics.dl19-doc.txt' self.dl20 = 'tools/topics-and-qrels/topics.dl20.txt' def test_sum_aggregation_dl19_doc_seg(self): # dl19-doc-seg-sum topic = 'dl19-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl19_doc} \ --index msmarco-v1-doc-segmented \ --output {self.tmp}/regression_test_sum.{topic}.txt \ --hits 10000 --segments \ --alpha 0.3') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_sum.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.2711) self.assertEqual(ndcg_score, 0.5596) def test_sum_aggregation_dl20_doc_seg(self): # dl20-doc-seg-sum topic = 'dl20-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl20} \ --index msmarco-v1-doc-segmented \ --output {self.tmp}/regression_test_sum.{topic}.txt \ --hits 10000 --segments \ --alpha 0.3 ') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_sum.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3759) self.assertEqual(ndcg_score, 0.5343) def test_max_aggregation_dl19_doc_seg(self): # dl19-doc-seg-max topic = 'dl19-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl19_doc} \ --index msmarco-v1-doc-segmented \ --output {self.tmp}/regression_test_max.{topic}.txt \ --alpha 0.3 \ --hits 10000 --segments \ --max-sim') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_max.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.2425) self.assertEqual(ndcg_score, 0.5195) def test_max_aggregation_dl20_doc_seg(self): # dl20-doc-seg-max topic = 'dl20-doc' os.system(f'python -m pyserini.search.lucene.irst \ --topics {self.dl20} \ --index msmarco-v1-doc-segmented \ --output {self.tmp}/regression_test_max.{topic}.txt \ --alpha 0.3 \ --hits 10000 --segments \ --max-sim') score_cmd = f'python -m pyserini.eval.trec_eval \ -c -m map -m ndcg_cut.10 -M 100 {topic} {self.tmp}/regression_test_max.{topic}.txt' status = os.system(score_cmd) stdout, stderr = run_command(score_cmd) map_score = parse_score(stdout, "map") ndcg_score = parse_score(stdout, "ndcg") self.assertEqual(status, 0) self.assertEqual(stderr, '') self.assertEqual(map_score, 0.3496) self.assertEqual(ndcg_score, 0.5089) def tearDown(self): rmtree(self.tmp) if __name__ == '__main__': unittest.main()

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c80ad5f8b1d06e95aaaa50a5acccb45173a79ea5

213

py

Python

api/infrastructure/ping_controller.py

testingthingsfordev/skeleton-py-flask-rest

19319f61eca1260dcd433528c99db9d8e83ca0e6

[ "MIT" ]

null

api/infrastructure/ping_controller.py

testingthingsfordev/skeleton-py-flask-rest

19319f61eca1260dcd433528c99db9d8e83ca0e6

[ "MIT" ]

3

2022-03-28T10:44:43.000Z

2022-03-28T11:27:23.000Z

api/infrastructure/ping_controller.py

Rviewer-Challenges/skeleton-py-flask-rest

7873cd08e778e03ef2f371a9974ccfb9f9d64f8a

[ "MIT" ]

null

from flask_restful import Resource class PingController(Resource): def __init__(self, ping_service): self.ping_service = ping_service def get(self): return self.ping_service.ping(), 200

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c82be628b8cac865cbe49dc6d56ffd80df925e88

13,723

py

Python

jetmontecarlo/tests/simple_tests/test_integrate2d.py

samcaf/JetMonteCarlo

71f50f3bb53a4f68ed927eaeaed5ee258da0dd34

[ "MIT" ]

null

jetmontecarlo/tests/simple_tests/test_integrate2d.py

samcaf/JetMonteCarlo

71f50f3bb53a4f68ed927eaeaed5ee258da0dd34

[ "MIT" ]

null

jetmontecarlo/tests/simple_tests/test_integrate2d.py

samcaf/JetMonteCarlo

71f50f3bb53a4f68ed927eaeaed5ee258da0dd34

[ "MIT" ]

null

import numpy as np import matplotlib.pyplot as plt from matplotlib import cm # Local imports from jetmontecarlo.tests.simple_tests.test_simpleSampler import * from jetmontecarlo.montecarlo.integrator import * from jetmontecarlo.utils.color_utils import * # Parameters NUM_SAMPLES = int(1e4) NUM_BINS = 10 EPSILON = 1e-5 showPlots = True savePlots = False def test_weight(x, y, n, m): weight = (n+1.)*x**n * (m+1.)*y**m return weight # ------------------------------------ # Linear Integrators: # ------------------------------------ def test_Simple2DLinIntegrator_firstbin(plot_2d=False): # Sampling testSampler_1 = simpleSampler('lin') testSampler_1.generateSamples(NUM_SAMPLES) samples_1 = testSampler_1.getSamples() testSampler_2 = simpleSampler('lin') testSampler_2.generateSamples(NUM_SAMPLES) samples_2 = testSampler_2.getSamples() # Setting up integrator testInt = integrator_2d() testInt.setFirstBinBndCondition(0.) testInt.setBins(NUM_BINS, [samples_1, samples_2], 'lin') for n in range(4): m = 1 # Weights, binned observables, and area weights = test_weight(samples_1, samples_2, n, m) jacs = (np.array(testSampler_1.jacobians) * np.array(testSampler_2.jacobians)) obs = [samples_1, samples_2] area = testSampler_1.area * testSampler_2.area testInt.setDensity(obs, weights * jacs, area) testInt.integrate() integral = testInt.integral int_err = testInt.integralErr xs = testInt.bins[0][1:] ys = testInt.bins[1][1:] testInt.makeInterpolatingFn() interp_mc = testInt.interpFn integral_interp = interp_mc(xs, ys) xs, ys = np.meshgrid(xs, ys) zs = [integral, integral_interp, xs**(n+1) * ys**(m+1)] zs.append(abs(zs[0] - zs[1])) zlims = [(0, 1), (0, 1), (0, 1), (0, .1)] titles = ['Monte Carlo', 'Interpolation', 'Analytic', '|Difference|'] projection = '3d' figsize = plt.figaspect(0.5) if plot_2d: projection = None figsize = (15, 4) fig = plt.figure(figsize=figsize) fig.suptitle('MC Integration to determine ' + 'x^{} y^{}'.format(n+1, m+1)) axes = [] for i in range(4): ax = fig.add_subplot(1, 4, i+1, projection=projection) ax.set_title(titles[i]) if plot_2d: axes.append(ax) im = ax.pcolormesh(xs, ys, zs[i], vmin=0, vmax=1) else: my_col = cm.coolwarm(zs[i]) ax.plot_surface(xs, ys, zs[i], rstride=1, cstride=1, facecolors=my_col, linewidth=0, antialiased=False) ax.set_zlim(zlims[i]) if i == 0 or i == 3: # Plotting errorbars fx = xs.flatten() fy = ys.flatten() fz = zs[i].flatten() fzerr = int_err.flatten() fcols = my_col.reshape(fx.shape[0], 4) for j in np.arange(0, len(fx)): ax.plot([fx[j], fx[j]], [fy[j], fy[j]], [fz[j]+fzerr[j], fz[j]-fzerr[j]], marker="|", color=fcols[j], zorder=5) if plot_2d: axes = np.array(axes) fig.colorbar(im, ax=axes.ravel().tolist()) fig.savefig('simple_2d_lin_firstbin_test_' + str(n+1) + '_' + str(m+1) + '.pdf', format='pdf') def test_Simple2DLinIntegrator_lastbin(plot_2d=False): # Sampling testSampler_1 = simpleSampler('lin') testSampler_1.generateSamples(NUM_SAMPLES) samples_1 = testSampler_1.getSamples() testSampler_2 = simpleSampler('lin') testSampler_2.generateSamples(NUM_SAMPLES) samples_2 = testSampler_2.getSamples() # Setting up integrator testInt = integrator_2d() testInt.setLastBinBndCondition([0., 'plus']) testInt.setBins(NUM_BINS, [samples_1, samples_2], 'lin') for n in range(4): m = 1 # Weights, binned observables, and area weights = test_weight(samples_1, samples_2, n, m) jacs = (np.array(testSampler_1.jacobians) * np.array(testSampler_2.jacobians)) obs = [samples_1, samples_2] area = testSampler_1.area * testSampler_2.area testInt.setDensity(obs, weights * jacs, area) testInt.integrate() integral = testInt.integral int_err = testInt.integralErr xs = testInt.bins[0][:-1] ys = testInt.bins[1][:-1] testInt.makeInterpolatingFn() interp_mc = testInt.interpFn integral_interp = interp_mc(xs, ys) xs, ys = np.meshgrid(xs, ys) zs = [integral, integral_interp, (1-xs**(n+1)) * (1-ys**(n+1))] zs.append(abs(zs[0] - zs[1])) zlims = [(0, 1), (0, 1), (0, 1), (0, .1)] titles = ['Monte Carlo', 'Interpolation', 'Analytic', '|Difference|'] projection = '3d' figsize = plt.figaspect(0.5) if plot_2d: projection = None figsize = (15, 4) fig = plt.figure(figsize=figsize) fig.suptitle('MC Integration to determine ' + '(1-x^{})(1-y^{})'.format(n+1, m+1)) axes = [] for i in range(4): ax = fig.add_subplot(1, 4, i+1, projection=projection) ax.set_title(titles[i]) if plot_2d: axes.append(ax) im = ax.pcolormesh(xs, ys, zs[i], vmin=0, vmax=1) else: my_col = cm.coolwarm(zs[i]) ax.plot_surface(xs, ys, zs[i], rstride=1, cstride=1, facecolors=my_col, linewidth=0, antialiased=False) ax.set_zlim(zlims[i]) if i == 0 or i == 3: # Plotting errorbars fx = xs.flatten() fy = ys.flatten() fz = zs[i].flatten() fzerr = int_err.flatten() fcols = my_col.reshape(fx.shape[0], 4) for j in np.arange(0, len(fx)): ax.plot([fx[j], fx[j]], [fy[j], fy[j]], [fz[j]+fzerr[j], fz[j]-fzerr[j]], marker="|", color=fcols[j], zorder=5) if plot_2d: axes = np.array(axes) fig.colorbar(im, ax=axes.ravel().tolist()) fig.savefig('simple_2d_lin_lastbin_test_' + str(n+1) + '_' + str(m+1) + '.pdf', format='pdf') # ------------------------------------ # Logarithmic Integrators: # ------------------------------------ def test_Simple2DLogIntegrator_firstbin(plot_2d=False): # Sampling testSampler_1 = simpleSampler('log', epsilon=EPSILON) testSampler_1.generateSamples(NUM_SAMPLES) samples_1 = testSampler_1.getSamples() testSampler_2 = simpleSampler('log', epsilon=EPSILON) testSampler_2.generateSamples(NUM_SAMPLES) samples_2 = testSampler_2.getSamples() # Setting up integrator testInt = integrator_2d() testInt.setFirstBinBndCondition(0.) testInt.setBins(NUM_BINS, [samples_1, samples_2], 'log') for n in range(4): m = 1 # Weights, binned observables, and area weights = test_weight(samples_1, samples_2, n, m) jacs = (np.array(testSampler_1.jacobians) * np.array(testSampler_2.jacobians)) obs = [samples_1, samples_2] area = testSampler_1.area * testSampler_2.area testInt.setDensity(obs, weights * jacs, area) testInt.integrate() integral = testInt.integral int_err = testInt.integralErr xs = testInt.bins[0][1:] ys = testInt.bins[1][1:] testInt.makeInterpolatingFn() interp_mc = testInt.interpFn integral_interp = interp_mc(xs, ys) xs, ys = np.meshgrid(xs, ys) zs = [integral, integral_interp, xs**(n+1) * ys**(m+1)] zs.append(abs(zs[0] - zs[1])) xs = np.log10(xs) ys = np.log10(ys) zlims = [(0, 1), (0, 1), (0, 1), (0, .1)] titles = ['Monte Carlo', 'Interpolation', 'Analytic', '|Difference|'] projection = '3d' figsize = plt.figaspect(0.5) if plot_2d: projection = None figsize = (15, 4) fig = plt.figure(figsize=figsize) fig.suptitle('MC Integration to determine ' + 'x^{} y^{}'.format(n+1, m+1)) axes = [] for i in range(4): ax = fig.add_subplot(1, 4, i+1, projection=projection) ax.set_title(titles[i]) if plot_2d: axes.append(ax) im = ax.pcolormesh(xs, ys, zs[i], vmin=0, vmax=1) else: my_col = cm.coolwarm(zs[i]) ax.plot_surface(xs, ys, zs[i], rstride=1, cstride=1, facecolors=my_col, linewidth=0, antialiased=False) ax.set_zlim(zlims[i]) if i == 0 or i == 3: # Plotting errorbars fx = xs.flatten() fy = ys.flatten() fz = zs[i].flatten() fzerr = int_err.flatten() fcols = my_col.reshape(fx.shape[0], 4) for j in np.arange(0, len(fx)): ax.plot([fx[j], fx[j]], [fy[j], fy[j]], [fz[j]+fzerr[j], fz[j]-fzerr[j]], marker="|", color=fcols[j], zorder=5) if plot_2d: axes = np.array(axes) fig.colorbar(im, ax=axes.ravel().tolist()) fig.savefig('simple_2d_log_firstbin_test_' + str(n+1) + '_' + str(m+1) + '.pdf', format='pdf') def test_Simple2DLogIntegrator_lastbin(plot_2d=False): # Sampling testSampler_1 = simpleSampler('log', epsilon=EPSILON) testSampler_1.generateSamples(NUM_SAMPLES) samples_1 = testSampler_1.getSamples() testSampler_2 = simpleSampler('log', epsilon=EPSILON) testSampler_2.generateSamples(NUM_SAMPLES) samples_2 = testSampler_2.getSamples() # Setting up integrator testInt = integrator_2d() testInt.setLastBinBndCondition([0., 'plus']) testInt.setBins(NUM_BINS, [samples_1, samples_2], 'log') for n in range(4): m = 1 # Weights, binned observables, and area weights = test_weight(samples_1, samples_2, n, m) jacs = (np.array(testSampler_1.jacobians) * np.array(testSampler_2.jacobians)) obs = [samples_1, samples_2] area = testSampler_1.area * testSampler_2.area testInt.setDensity(obs, weights * jacs, area) testInt.integrate() integral = testInt.integral int_err = testInt.integralErr xs = testInt.bins[0][:-1] ys = testInt.bins[1][:-1] testInt.makeInterpolatingFn() interp_mc = testInt.interpFn integral_interp = interp_mc(xs, ys) xs, ys = np.meshgrid(xs, ys) zs = [integral, integral_interp, (1-xs**(n+1)) * (1-ys**(m+1))] zs.append(abs(zs[0] - zs[1])) xs = np.log10(xs) ys = np.log10(ys) zlims = [(0, 1), (0, 1), (0, 1), (0, .1)] titles = ['Monte Carlo', 'Interpolation', 'Analytic', '|Difference|'] projection = '3d' figsize = plt.figaspect(0.5) if plot_2d: projection = None figsize = (15, 4) fig = plt.figure(figsize=figsize) fig.suptitle('MC Integration to determine ' + '(1-x^{})(1-y^{})'.format(n+1, m+1)) axes = [] for i in range(4): ax = fig.add_subplot(1, 4, i+1, projection=projection) ax.set_title(titles[i]) if plot_2d: axes.append(ax) im = ax.pcolormesh(xs, ys, zs[i], vmin=0, vmax=1) else: my_col = cm.coolwarm(zs[i]) ax.plot_surface(xs, ys, zs[i], rstride=1, cstride=1, facecolors=my_col, linewidth=0, antialiased=False) ax.set_zlim(zlims[i]) if i == 0 or i == 3: # Plotting errorbars fx = xs.flatten() fy = ys.flatten() fz = zs[i].flatten() fzerr = int_err.flatten() fcols = my_col.reshape(fx.shape[0], 4) for j in np.arange(0, len(fx)): ax.plot([fx[j], fx[j]], [fy[j], fy[j]], [fz[j]+fzerr[j], fz[j]-fzerr[j]], marker="|", color=fcols[j], zorder=5) if plot_2d: axes = np.array(axes) fig.colorbar(im, ax=axes.ravel().tolist()) fig.savefig('simple_2d_log_lastbin_test_' + str(n+1) + '_' + str(m+1) + '.pdf', format='pdf') # Implementing tests if __name__ == '__main__': test_Simple2DLinIntegrator_firstbin() test_Simple2DLinIntegrator_lastbin() test_Simple2DLogIntegrator_firstbin() test_Simple2DLogIntegrator_lastbin()

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c85ff33c3486bae317cad09b8bed64f15f92832e

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py

Python

office365api/model/__init__.py

swimlane/python-office365

42c0c0cad0d92e4cd7f18fcf3e75153045a9ea0f

[ "MIT" ]

21

2016-10-27T10:39:25.000Z

2021-06-15T01:03:06.000Z

office365api/model/__init__.py

swimlane/python-office365

42c0c0cad0d92e4cd7f18fcf3e75153045a9ea0f

[ "MIT" ]

6

2017-03-08T06:39:59.000Z

2021-07-12T01:35:05.000Z

office365api/model/__init__.py

swimlane/python-office365

42c0c0cad0d92e4cd7f18fcf3e75153045a9ea0f

[ "MIT" ]

15

2016-12-11T22:33:56.000Z

2021-09-13T17:44:11.000Z

from office365api.model.recipient import Recipient from office365api.model.email_address import EmailAddress from office365api.model.message import Message from office365api.model.item_body import ItemBody

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py

Python

plugins/typo_squatter/komand_typo_squatter/actions/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

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2019-06-05T20:47:58.000Z

2022-03-29T10:18:01.000Z

plugins/typo_squatter/komand_typo_squatter/actions/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

386

2019-06-07T20:20:39.000Z

2022-03-30T17:35:01.000Z

plugins/typo_squatter/komand_typo_squatter/actions/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

43

2019-07-09T14:13:58.000Z

2022-03-28T12:04:46.000Z

# GENERATED BY KOMAND SDK - DO NOT EDIT from .check_for_squatters.action import CheckForSquatters from .score_domain.action import ScoreDomain

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py

Python

let's-learn-python/nesting-functions-and-decorators/nesting-function-2.py

Valka7a/python-playground

f08d4374f2cec2e8b1afec3753854b1ec10ff480

[ "MIT" ]

null

let's-learn-python/nesting-functions-and-decorators/nesting-function-2.py

Valka7a/python-playground

f08d4374f2cec2e8b1afec3753854b1ec10ff480

[ "MIT" ]

null

let's-learn-python/nesting-functions-and-decorators/nesting-function-2.py

Valka7a/python-playground

f08d4374f2cec2e8b1afec3753854b1ec10ff480

[ "MIT" ]

null

def outside(): x = 5 def print_ham(): print x return print_ham myFunc = outside() myFunc() # other way def outside(x = 5): def print_ham(): print x return print_ham myFunc = outside(7) myFunc()

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Python

twitterproducer/tests/mock_tweets_provider.py

AppleteeYT/Iris

b60deb6575820253bad50b48b9b39023d6440fd4

[ "Apache-2.0" ]

null

twitterproducer/tests/mock_tweets_provider.py

AppleteeYT/Iris

b60deb6575820253bad50b48b9b39023d6440fd4

[ "Apache-2.0" ]

null

twitterproducer/tests/mock_tweets_provider.py

AppleteeYT/Iris

b60deb6575820253bad50b48b9b39023d6440fd4

[ "Apache-2.0" ]

null

import ast import json from datetime import datetime from tweepy import Status from twitterproducer.tweets.itweets_provider import ITweetsProvider status_json = "{'created_at': 'Wed Aug 26 03:22:48 +0000 2020', 'id': 1298460861900652545, 'id_str': " \ "'1298460861900652545', 'full_text': 'https://t.co/WjbNIvW96r', 'truncated': False, " \ "'display_text_range': [0, 23], 'entities': {'hashtags': [], 'symbols': [], 'user_mentions': [], " \ "'urls': [], 'media': [{'id': 1298458167211425795, 'id_str': '1298458167211425795', 'indices': [0, 23], " \ "'media_url': 'http://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img/Yf5i8sL2TJ9eOurH.jpg', " \ "'media_url_https': 'https://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img/Yf5i8sL2TJ9eOurH" \ ".jpg', 'url': 'https://t.co/WjbNIvW96r', 'display_url': 'pic.twitter.com/WjbNIvW96r', 'expanded_url': " \ "'https://twitter.com/TeamTrump/status/1298458366306660353/video/1', 'type': 'photo', 'sizes': {" \ "'thumb': {'w': 150, 'h': 150, 'resize': 'crop'}, 'medium': {'w': 1200, 'h': 675, 'resize': 'fit'}, " \ "'small': {'w': 680, 'h': 383, 'resize': 'fit'}, 'large': {'w': 1280, 'h': 720, 'resize': 'fit'}}, " \ "'source_status_id': 1298458366306660353, 'source_status_id_str': '1298458366306660353', " \ "'source_user_id': 729676086632656900, 'source_user_id_str': '729676086632656900'}]}, " \ "'extended_entities': {'media': [{'id': 1298458167211425795, 'id_str': '1298458167211425795', " \ "'indices': [0, 23], 'media_url': " \ "'http://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img/Yf5i8sL2TJ9eOurH.jpg', " \ "'media_url_https': 'https://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img/Yf5i8sL2TJ9eOurH" \ ".jpg', 'url': 'https://t.co/WjbNIvW96r', 'display_url': 'pic.twitter.com/WjbNIvW96r', 'expanded_url': " \ "'https://twitter.com/TeamTrump/status/1298458366306660353/video/1', 'type': 'video', 'sizes': {" \ "'thumb': {'w': 150, 'h': 150, 'resize': 'crop'}, 'medium': {'w': 1200, 'h': 675, 'resize': 'fit'}, " \ "'small': {'w': 680, 'h': 383, 'resize': 'fit'}, 'large': {'w': 1280, 'h': 720, 'resize': 'fit'}}, " \ "'source_status_id': 1298458366306660353, 'source_status_id_str': '1298458366306660353', " \ "'source_user_id': 729676086632656900, 'source_user_id_str': '729676086632656900', 'video_info': {" \ "'aspect_ratio': [16, 9], 'duration_millis': 54922, 'variants': [{'bitrate': 288000, 'content_type': " \ "'video/mp4', 'url': 'https://video.twimg.com/amplify_video/1298458167211425795/vid/480x270" \ "/sXwPBww7AzzE0l9Q.mp4?tag=13'}, {'bitrate': 2176000, 'content_type': 'video/mp4', " \ "'url': 'https://video.twimg.com/amplify_video/1298458167211425795/vid/1280x720/uNjTWvnP00FREqPM.mp4" \ "?tag=13'}, {'content_type': 'application/x-mpegURL', 'url': " \ "'https://video.twimg.com/amplify_video/1298458167211425795/pl/Zjm-_QsgnU-brl_G.m3u8?tag=13'}, " \ "{'bitrate': 832000, 'content_type': 'video/mp4', 'url': " \ "'https://video.twimg.com/amplify_video/1298458167211425795/vid/640x360/BBMmBNzsb75nsyC4.mp4?tag=13" \ "'}]}, 'additional_media_info': {'title': '', 'description': '', 'embeddable': True, 'monetizable': " \ "False, 'source_user': {'id': 729676086632656900, 'id_str': '729676086632656900', 'name': 'Team Trump (" \ "Text VOTE to 88022)', 'screen_name': 'TeamTrump', 'location': 'USA', 'description': 'The official " \ "Twitter account for the Trump Campaign. Together, we will KEEP AMERICA GREAT! 🇺🇸', " \ "'url': 'https://t.co/mZB2hymxC9', 'entities': {'url': {'urls': [{'url': 'https://t.co/mZB2hymxC9', " \ "'expanded_url': 'http://www.DonaldJTrump.com', 'display_url': 'DonaldJTrump.com', 'indices': [0, " \ "23]}]}, 'description': {'urls': []}}, 'protected': False, 'followers_count': 2123084, 'friends_count': " \ "127, 'listed_count': 4055, 'created_at': 'Mon May 09 14:15:10 +0000 2016', 'favourites_count': 3479, " \ "'utc_offset': None, 'time_zone': None, 'geo_enabled': True, 'verified': True, 'statuses_count': 25663, " \ "'lang': None, 'contributors_enabled': False, 'is_translator': False, 'is_translation_enabled': False, " \ "'profile_background_color': '000000', 'profile_background_image_url': " \ "'http://abs.twimg.com/images/themes/theme1/bg.png', 'profile_background_image_url_https': " \ "'https://abs.twimg.com/images/themes/theme1/bg.png', 'profile_background_tile': False, " \ "'profile_image_url': 'http://pbs.twimg.com/profile_images/745768799849308160/KrZhjkpH_normal.jpg', " \ "'profile_image_url_https': 'https://pbs.twimg.com/profile_images/745768799849308160/KrZhjkpH_normal" \ ".jpg', 'profile_banner_url': 'https://pbs.twimg.com/profile_banners/729676086632656900/1588979102', " \ "'profile_link_color': 'CB0606', 'profile_sidebar_border_color': '000000', " \ "'profile_sidebar_fill_color': '000000', 'profile_text_color': '000000', " \ "'profile_use_background_image': False, 'has_extended_profile': False, 'default_profile': False, " \ "'default_profile_image': False, 'following': False, 'follow_request_sent': False, 'notifications': " \ "False, 'translator_type': 'none'}}}]}, 'source': '<a href=\"http://twitter.com/download/iphone\" " \ "rel=\"nofollow\">Twitter for iPhone</a>', 'in_reply_to_status_id': None, 'in_reply_to_status_id_str': " \ "None, 'in_reply_to_user_id': None, 'in_reply_to_user_id_str': None, 'in_reply_to_screen_name': None, " \ "'user': {'id': 25073877, 'id_str': '25073877', 'name': 'Donald J. Trump', 'screen_name': " \ "'realDonaldTrump', 'location': 'Washington, DC', 'description': '45th President of the United States " \ "of America🇺🇸', 'url': 'https://t.co/OMxB0x7xC5', 'entities': {'url': {'urls': [{'url': " \ "'https://t.co/OMxB0x7xC5', 'expanded_url': 'http://www.Instagram.com/realDonaldTrump', 'display_url': " \ "'Instagram.com/realDonaldTrump', 'indices': [0, 23]}]}, 'description': {'urls': []}}, 'protected': " \ "False, 'followers_count': 85580226, 'friends_count': 50, 'listed_count': 118643, 'created_at': 'Wed " \ "Mar 18 13:46:38 +0000 2009', 'favourites_count': 4, 'utc_offset': None, 'time_zone': None, " \ "'geo_enabled': True, 'verified': True, 'statuses_count': 54945, 'lang': None, 'contributors_enabled': " \ "False, 'is_translator': False, 'is_translation_enabled': True, 'profile_background_color': '6D5C18', " \ "'profile_background_image_url': 'http://abs.twimg.com/images/themes/theme1/bg.png', " \ "'profile_background_image_url_https': 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'possibly_sensitive': False, 'lang': 'und'}, created_at=datetime.datetime(2020, 8, " \ "26, 3, 22, 48), id=1298460861900652545, id_str='1298460861900652545', " \ "full_text='https://t.co/WjbNIvW96r', truncated=False, display_text_range=[0, 23], entities={" \ "'hashtags': [], 'symbols': [], 'user_mentions': [], 'urls': [], 'media': [{'id': 1298458167211425795, " \ "'id_str': '1298458167211425795', 'indices': [0, 23], 'media_url': " \ "'http://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img/Yf5i8sL2TJ9eOurH.jpg', " \ "'media_url_https': 'https://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img/Yf5i8sL2TJ9eOurH" \ ".jpg', 'url': 'https://t.co/WjbNIvW96r', 'display_url': 'pic.twitter.com/WjbNIvW96r', 'expanded_url': " \ "'https://twitter.com/TeamTrump/status/1298458366306660353/video/1', 'type': 'photo', 'sizes': {" \ "'thumb': {'w': 150, 'h': 150, 'resize': 'crop'}, 'medium': {'w': 1200, 'h': 675, 'resize': 'fit'}, " \ "'small': {'w': 680, 'h': 383, 'resize': 'fit'}, 'large': {'w': 1280, 'h': 720, 'resize': 'fit'}}, " \ "'source_status_id': 1298458366306660353, 'source_status_id_str': '1298458366306660353', " \ "'source_user_id': 729676086632656900, 'source_user_id_str': '729676086632656900'}]}, " \ "extended_entities={'media': [{'id': 1298458167211425795, 'id_str': '1298458167211425795', 'indices': [" \ "0, 23], 'media_url': 'http://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img" \ "/Yf5i8sL2TJ9eOurH.jpg', 'media_url_https': " \ "'https://pbs.twimg.com/amplify_video_thumb/1298458167211425795/img/Yf5i8sL2TJ9eOurH.jpg', " \ "'url': 'https://t.co/WjbNIvW96r', 'display_url': 'pic.twitter.com/WjbNIvW96r', 'expanded_url': " \ "'https://twitter.com/TeamTrump/status/1298458366306660353/video/1', 'type': 'video', 'sizes': {" \ "'thumb': {'w': 150, 'h': 150, 'resize': 'crop'}, 'medium': {'w': 1200, 'h': 675, 'resize': 'fit'}, " \ "'small': {'w': 680, 'h': 383, 'resize': 'fit'}, 'large': {'w': 1280, 'h': 720, 'resize': 'fit'}}, " \ 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'monetizable': " \ "False, 'source_user': {'id': 729676086632656900, 'id_str': '729676086632656900', 'name': 'Team Trump (" \ "Text VOTE to 88022)', 'screen_name': 'TeamTrump', 'location': 'USA', 'description': 'The official " \ "Twitter account for the Trump Campaign. Together, we will KEEP AMERICA GREAT! 🇺🇸', " \ "'url': 'https://t.co/mZB2hymxC9', 'entities': {'url': {'urls': [{'url': 'https://t.co/mZB2hymxC9', " \ "'expanded_url': 'http://www.DonaldJTrump.com', 'display_url': 'DonaldJTrump.com', 'indices': [0, " \ "23]}]}, 'description': {'urls': []}}, 'protected': False, 'followers_count': 2123084, 'friends_count': " \ "127, 'listed_count': 4055, 'created_at': 'Mon May 09 14:15:10 +0000 2016', 'favourites_count': 3479, " \ "'utc_offset': None, 'time_zone': None, 'geo_enabled': True, 'verified': True, 'statuses_count': 25663, " \ "'lang': None, 'contributors_enabled': False, 'is_translator': False, 'is_translation_enabled': False, " \ "'profile_background_color': '000000', 'profile_background_image_url': " \ "'http://abs.twimg.com/images/themes/theme1/bg.png', 'profile_background_image_url_https': " \ "'https://abs.twimg.com/images/themes/theme1/bg.png', 'profile_background_tile': False, " \ "'profile_image_url': 'http://pbs.twimg.com/profile_images/745768799849308160/KrZhjkpH_normal.jpg', " \ "'profile_image_url_https': 'https://pbs.twimg.com/profile_images/745768799849308160/KrZhjkpH_normal" \ ".jpg', 'profile_banner_url': 'https://pbs.twimg.com/profile_banners/729676086632656900/1588979102', " \ "'profile_link_color': 'CB0606', 'profile_sidebar_border_color': '000000', " \ "'profile_sidebar_fill_color': '000000', 'profile_text_color': '000000', " \ "'profile_use_background_image': False, 'has_extended_profile': False, 'default_profile': False, " \ "'default_profile_image': False, 'following': False, 'follow_request_sent': False, 'notifications': " \ "False, 'translator_type': 'none'}}}]}, source='Twitter for iPhone', " \ "source_url='http://twitter.com/download/iphone', in_reply_to_status_id=None, " \ "in_reply_to_status_id_str=None, in_reply_to_user_id=None, in_reply_to_user_id_str=None, " \ "in_reply_to_screen_name=None, author=User(_api=<tweepy.api.API object at 0x0000023F470BA0B8>, " \ "_json={'id': 25073877, 'id_str': '25073877', 'name': 'Donald J. Trump', 'screen_name': " \ "'realDonaldTrump', 'location': 'Washington, DC', 'description': '45th President of the United States " \ "of America🇺🇸', 'url': 'https://t.co/OMxB0x7xC5', 'entities': {'url': {'urls': [{'url': " \ "'https://t.co/OMxB0x7xC5', 'expanded_url': 'http://www.Instagram.com/realDonaldTrump', 'display_url': " \ "'Instagram.com/realDonaldTrump', 'indices': [0, 23]}]}, 'description': {'urls': []}}, 'protected': " \ "False, 'followers_count': 85580226, 'friends_count': 50, 'listed_count': 118643, 'created_at': 'Wed " \ "Mar 18 13:46:38 +0000 2009', 'favourites_count': 4, 'utc_offset': None, 'time_zone': None, " \ "'geo_enabled': True, 'verified': True, 'statuses_count': 54945, 'lang': None, 'contributors_enabled': " \ "False, 'is_translator': False, 'is_translation_enabled': True, 'profile_background_color': '6D5C18', " \ "'profile_background_image_url': 'http://abs.twimg.com/images/themes/theme1/bg.png', " \ "'profile_background_image_url_https': 'https://abs.twimg.com/images/themes/theme1/bg.png', " \ "'profile_background_tile': True, 'profile_image_url': " \ "'http://pbs.twimg.com/profile_images/874276197357596672/kUuht00m_normal.jpg', " \ "'profile_image_url_https': 'https://pbs.twimg.com/profile_images/874276197357596672/kUuht00m_normal" \ ".jpg', 'profile_banner_url': 'https://pbs.twimg.com/profile_banners/25073877/1595058372', " \ "'profile_link_color': '1B95E0', 'profile_sidebar_border_color': 'BDDCAD', " \ "'profile_sidebar_fill_color': 'C5CEC0', 'profile_text_color': '333333', " \ "'profile_use_background_image': True, 'has_extended_profile': False, 'default_profile': False, " \ "'default_profile_image': False, 'following': True, 'follow_request_sent': False, 'notifications': " \ "False, 'translator_type': 'regular'}, id=25073877, id_str='25073877', name='Donald J. Trump', " \ "screen_name='realDonaldTrump', location='Washington, DC', description='45th President of the United " \ "States of America🇺🇸', url='https://t.co/OMxB0x7xC5', entities={'url': {'urls': [{'url': " \ "'https://t.co/OMxB0x7xC5', 'expanded_url': 'http://www.Instagram.com/realDonaldTrump', 'display_url': " \ "'Instagram.com/realDonaldTrump', 'indices': [0, 23]}]}, 'description': {'urls': []}}, protected=False, " \ "followers_count=85580226, friends_count=50, listed_count=118643, created_at=datetime.datetime(2009, 3, " \ "18, 13, 46, 38), favourites_count=4, utc_offset=None, time_zone=None, geo_enabled=True, verified=True, " \ "statuses_count=54945, lang=None, contributors_enabled=False, is_translator=False, " \ "is_translation_enabled=True, profile_background_color='6D5C18', " \ "profile_background_image_url='http://abs.twimg.com/images/themes/theme1/bg.png', " \ "profile_background_image_url_https='https://abs.twimg.com/images/themes/theme1/bg.png', " \ "profile_background_tile=True, " \ "profile_image_url='http://pbs.twimg.com/profile_images/874276197357596672/kUuht00m_normal.jpg', " \ "profile_image_url_https='https://pbs.twimg.com/profile_images/874276197357596672/kUuht00m_normal.jpg', " \ "profile_banner_url='https://pbs.twimg.com/profile_banners/25073877/1595058372', " \ "profile_link_color='1B95E0', profile_sidebar_border_color='BDDCAD', " \ "profile_sidebar_fill_color='C5CEC0', profile_text_color='333333', profile_use_background_image=True, " \ "has_extended_profile=False, default_profile=False, default_profile_image=False, following=True, " \ "follow_request_sent=False, notifications=False, translator_type='regular'), user=User(" \ "_api=<tweepy.api.API object at 0x0000023F470BA0B8>, _json={'id': 25073877, 'id_str': '25073877', " \ "'name': 'Donald J. Trump', 'screen_name': 'realDonaldTrump', 'location': 'Washington, DC', " \ "'description': '45th President of the United States of America🇺🇸', 'url': 'https://t.co/OMxB0x7xC5', " \ "'entities': {'url': {'urls': [{'url': 'https://t.co/OMxB0x7xC5', 'expanded_url': " \ "'http://www.Instagram.com/realDonaldTrump', 'display_url': 'Instagram.com/realDonaldTrump', " \ "'indices': [0, 23]}]}, 'description': {'urls': []}}, 'protected': False, 'followers_count': 85580226, " \ "'friends_count': 50, 'listed_count': 118643, 'created_at': 'Wed Mar 18 13:46:38 +0000 2009', " \ "'favourites_count': 4, 'utc_offset': None, 'time_zone': None, 'geo_enabled': True, 'verified': True, " \ "'statuses_count': 54945, 'lang': None, 'contributors_enabled': False, 'is_translator': False, " \ "'is_translation_enabled': True, 'profile_background_color': '6D5C18', 'profile_background_image_url': " \ "'http://abs.twimg.com/images/themes/theme1/bg.png', 'profile_background_image_url_https': " \ "'https://abs.twimg.com/images/themes/theme1/bg.png', 'profile_background_tile': True, " \ "'profile_image_url': 'http://pbs.twimg.com/profile_images/874276197357596672/kUuht00m_normal.jpg', " \ "'profile_image_url_https': 'https://pbs.twimg.com/profile_images/874276197357596672/kUuht00m_normal" \ ".jpg', 'profile_banner_url': 'https://pbs.twimg.com/profile_banners/25073877/1595058372', " \ "'profile_link_color': '1B95E0', 'profile_sidebar_border_color': 'BDDCAD', " \ "'profile_sidebar_fill_color': 'C5CEC0', 'profile_text_color': '333333', " \ "'profile_use_background_image': True, 'has_extended_profile': False, 'default_profile': False, " \ "'default_profile_image': False, 'following': True, 'follow_request_sent': False, 'notifications': " \ "False, 'translator_type': 'regular'}, id=25073877, id_str='25073877', name='Donald J. Trump', " \ "screen_name='realDonaldTrump', location='Washington, DC', description='45th President of the United " \ "States of America🇺🇸', url='https://t.co/OMxB0x7xC5', entities={'url': {'urls': [{'url': " \ "'https://t.co/OMxB0x7xC5', 'expanded_url': 'http://www.Instagram.com/realDonaldTrump', 'display_url': " \ "'Instagram.com/realDonaldTrump', 'indices': [0, 23]}]}, 'description': {'urls': []}} " class obj(object): def __init__(self, d): for a, b in d.items(): if type(b) == dict: if b.get('ignore'): setattr(self, a, b) continue if isinstance(b, (list, tuple)): setattr(self, a, [obj(x) if isinstance(x, dict) else x for x in b]) else: setattr(self, a, obj(b) if isinstance(b, dict) else b) class MockTweetsProvider(ITweetsProvider): def get_tweets(self, user_id): return [obj({ 'user': { 'screen_name': 'mockuser' }, 'full_text': 'Mock tweet', 'created_at': datetime.now(), 'id_str': '121212', 'entities': {'urls': [], 'ignore': True}, 'retweeted': False })]

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f1aeed06b6d6b53ce91a9842579ef006a4f7d657

103,340

py

Python

sdk/python/pulumi_gitlab/project.py

pulumi/pulumi-gitlab

5627240bf718fc765d3a2068acd20621383514c8

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

11

2019-09-17T20:41:23.000Z

2021-12-02T20:39:23.000Z

sdk/python/pulumi_gitlab/project.py

pulumi/pulumi-gitlab

5627240bf718fc765d3a2068acd20621383514c8

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

67

2019-06-21T18:30:30.000Z

2022-03-31T21:27:20.000Z

sdk/python/pulumi_gitlab/project.py

pulumi/pulumi-gitlab

5627240bf718fc765d3a2068acd20621383514c8

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

2

2019-10-05T10:36:36.000Z

2021-05-13T18:14:59.000Z

# 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 from ._inputs import * __all__ = ['ProjectArgs', 'Project'] @pulumi.input_type class ProjectArgs: def __init__(__self__, *, approvals_before_merge: Optional[pulumi.Input[int]] = None, archived: Optional[pulumi.Input[bool]] = None, build_coverage_regex: Optional[pulumi.Input[str]] = None, ci_config_path: Optional[pulumi.Input[str]] = None, container_registry_enabled: Optional[pulumi.Input[bool]] = None, default_branch: Optional[pulumi.Input[str]] = None, description: Optional[pulumi.Input[str]] = None, group_with_project_templates_id: Optional[pulumi.Input[int]] = None, import_url: Optional[pulumi.Input[str]] = None, initialize_with_readme: Optional[pulumi.Input[bool]] = None, issues_enabled: Optional[pulumi.Input[bool]] = None, lfs_enabled: Optional[pulumi.Input[bool]] = None, merge_method: Optional[pulumi.Input[str]] = None, merge_requests_enabled: Optional[pulumi.Input[bool]] = None, mirror: Optional[pulumi.Input[bool]] = None, mirror_overwrites_diverged_branches: Optional[pulumi.Input[bool]] = None, mirror_trigger_builds: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, namespace_id: Optional[pulumi.Input[int]] = None, only_allow_merge_if_all_discussions_are_resolved: Optional[pulumi.Input[bool]] = None, only_allow_merge_if_pipeline_succeeds: Optional[pulumi.Input[bool]] = None, only_mirror_protected_branches: Optional[pulumi.Input[bool]] = None, packages_enabled: Optional[pulumi.Input[bool]] = None, pages_access_level: Optional[pulumi.Input[str]] = None, path: Optional[pulumi.Input[str]] = None, pipelines_enabled: Optional[pulumi.Input[bool]] = None, push_rules: Optional[pulumi.Input['ProjectPushRulesArgs']] = None, remove_source_branch_after_merge: Optional[pulumi.Input[bool]] = None, request_access_enabled: Optional[pulumi.Input[bool]] = None, shared_runners_enabled: Optional[pulumi.Input[bool]] = None, snippets_enabled: Optional[pulumi.Input[bool]] = None, tags: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, template_name: Optional[pulumi.Input[str]] = None, template_project_id: Optional[pulumi.Input[int]] = None, use_custom_template: Optional[pulumi.Input[bool]] = None, visibility_level: Optional[pulumi.Input[str]] = None, wiki_enabled: Optional[pulumi.Input[bool]] = None): """ The set of arguments for constructing a Project resource. :param pulumi.Input[int] approvals_before_merge: Number of merge request approvals required for merging. Default is 0. :param pulumi.Input[bool] archived: Whether the project is in read-only mode (archived). Repositories can be archived/unarchived by toggling this parameter. :param pulumi.Input[str] build_coverage_regex: Test coverage parsing for the project. :param pulumi.Input[str] ci_config_path: Custom Path to CI config file. :param pulumi.Input[bool] container_registry_enabled: Enable container registry for the project. :param pulumi.Input[str] default_branch: The default branch for the project. :param pulumi.Input[str] description: A description of the project. :param pulumi.Input[int] group_with_project_templates_id: For group-level custom templates, specifies ID of group from which all the custom project templates are sourced. Leave empty for instance-level templates. Requires use_custom_template to be true (enterprise edition). :param pulumi.Input[str] import_url: Git URL to a repository to be imported. :param pulumi.Input[bool] initialize_with_readme: Create main branch with first commit containing a README.md file. :param pulumi.Input[bool] issues_enabled: Enable issue tracking for the project. :param pulumi.Input[bool] lfs_enabled: Enable LFS for the project. :param pulumi.Input[str] merge_method: Set to `ff` to create fast-forward merges Valid values are `merge`, `rebase_merge`, `ff` Repositories are created with `merge` by default :param pulumi.Input[bool] merge_requests_enabled: Enable merge requests for the project. :param pulumi.Input[bool] mirror: Enables pull mirroring in a project. Default is `false`. For further information on mirroring, consult the [gitlab documentation](https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#repository-mirroring). :param pulumi.Input[bool] mirror_overwrites_diverged_branches: Pull mirror overwrites diverged branches. :param pulumi.Input[bool] mirror_trigger_builds: Pull mirroring triggers builds. Default is `false`. :param pulumi.Input[str] name: The name of the project. :param pulumi.Input[int] namespace_id: The namespace (group or user) of the project. Defaults to your user. See `Group` for an example. :param pulumi.Input[bool] only_allow_merge_if_all_discussions_are_resolved: Set to true if you want allow merges only if all discussions are resolved. :param pulumi.Input[bool] only_allow_merge_if_pipeline_succeeds: Set to true if you want allow merges only if a pipeline succeeds. :param pulumi.Input[bool] only_mirror_protected_branches: Only mirror protected branches. :param pulumi.Input[bool] packages_enabled: Enable packages repository for the project. :param pulumi.Input[str] pages_access_level: Enable pages access control Valid values are `disabled`, `private`, `enabled`, `public`. `private` is the default. :param pulumi.Input[str] path: The path of the repository. :param pulumi.Input[bool] pipelines_enabled: Enable pipelines for the project. :param pulumi.Input['ProjectPushRulesArgs'] push_rules: Push rules for the project (documented below). :param pulumi.Input[bool] remove_source_branch_after_merge: Enable `Delete source branch` option by default for all new merge requests. :param pulumi.Input[bool] request_access_enabled: Allow users to request member access. :param pulumi.Input[bool] shared_runners_enabled: Enable shared runners for this project. :param pulumi.Input[bool] snippets_enabled: Enable snippets for the project. :param pulumi.Input[Sequence[pulumi.Input[str]]] tags: Tags (topics) of the project. :param pulumi.Input[str] template_name: When used without use_custom_template, name of a built-in project template. When used with use_custom_template, name of a custom project template. This option is mutually exclusive with `template_project_id`. :param pulumi.Input[int] template_project_id: When used with use_custom_template, project ID of a custom project template. This is preferable to using template_name since template_name may be ambiguous (enterprise edition). This option is mutually exclusive with `template_name`. :param pulumi.Input[bool] use_custom_template: Use either custom instance or group (with group_with_project_templates_id) project template (enterprise edition). :param pulumi.Input[str] visibility_level: Set to `public` to create a public project. Valid values are `private`, `internal`, `public`. Repositories are created as private by default. :param pulumi.Input[bool] wiki_enabled: Enable wiki for the project. """ if approvals_before_merge is not None: pulumi.set(__self__, "approvals_before_merge", approvals_before_merge) if archived is not None: pulumi.set(__self__, "archived", archived) if build_coverage_regex is not None: pulumi.set(__self__, "build_coverage_regex", build_coverage_regex) if ci_config_path is not None: pulumi.set(__self__, "ci_config_path", ci_config_path) if container_registry_enabled is not None: pulumi.set(__self__, "container_registry_enabled", container_registry_enabled) if default_branch is not None: pulumi.set(__self__, "default_branch", default_branch) if description is not None: pulumi.set(__self__, "description", description) if group_with_project_templates_id is not None: pulumi.set(__self__, "group_with_project_templates_id", group_with_project_templates_id) if import_url is not None: pulumi.set(__self__, "import_url", import_url) if initialize_with_readme is not None: pulumi.set(__self__, "initialize_with_readme", initialize_with_readme) if issues_enabled is not None: pulumi.set(__self__, "issues_enabled", issues_enabled) if lfs_enabled is not None: pulumi.set(__self__, "lfs_enabled", lfs_enabled) if merge_method is not None: pulumi.set(__self__, "merge_method", merge_method) if merge_requests_enabled is not None: pulumi.set(__self__, "merge_requests_enabled", merge_requests_enabled) if mirror is not None: pulumi.set(__self__, "mirror", mirror) if mirror_overwrites_diverged_branches is not None: pulumi.set(__self__, "mirror_overwrites_diverged_branches", mirror_overwrites_diverged_branches) if mirror_trigger_builds is not None: pulumi.set(__self__, "mirror_trigger_builds", mirror_trigger_builds) if name is not None: pulumi.set(__self__, "name", name) if namespace_id is not None: pulumi.set(__self__, "namespace_id", namespace_id) if only_allow_merge_if_all_discussions_are_resolved is not None: pulumi.set(__self__, "only_allow_merge_if_all_discussions_are_resolved", only_allow_merge_if_all_discussions_are_resolved) if only_allow_merge_if_pipeline_succeeds is not None: pulumi.set(__self__, "only_allow_merge_if_pipeline_succeeds", only_allow_merge_if_pipeline_succeeds) if only_mirror_protected_branches is not None: pulumi.set(__self__, "only_mirror_protected_branches", only_mirror_protected_branches) if packages_enabled is not None: pulumi.set(__self__, "packages_enabled", packages_enabled) if pages_access_level is not None: pulumi.set(__self__, "pages_access_level", pages_access_level) if path is not None: pulumi.set(__self__, "path", path) if pipelines_enabled is not None: pulumi.set(__self__, "pipelines_enabled", pipelines_enabled) if push_rules is not None: pulumi.set(__self__, "push_rules", push_rules) if remove_source_branch_after_merge is not None: pulumi.set(__self__, "remove_source_branch_after_merge", remove_source_branch_after_merge) if request_access_enabled is not None: pulumi.set(__self__, "request_access_enabled", request_access_enabled) if shared_runners_enabled is not None: pulumi.set(__self__, "shared_runners_enabled", shared_runners_enabled) if snippets_enabled is not None: pulumi.set(__self__, "snippets_enabled", snippets_enabled) if tags is not None: pulumi.set(__self__, "tags", tags) if template_name is not None: pulumi.set(__self__, "template_name", template_name) if template_project_id is not None: pulumi.set(__self__, "template_project_id", template_project_id) if use_custom_template is not None: pulumi.set(__self__, "use_custom_template", use_custom_template) if visibility_level is not None: pulumi.set(__self__, "visibility_level", visibility_level) if wiki_enabled is not None: pulumi.set(__self__, "wiki_enabled", wiki_enabled) @property @pulumi.getter(name="approvalsBeforeMerge") def approvals_before_merge(self) -> Optional[pulumi.Input[int]]: """ Number of merge request approvals required for merging. Default is 0. """ return pulumi.get(self, "approvals_before_merge") @approvals_before_merge.setter def approvals_before_merge(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "approvals_before_merge", value) @property @pulumi.getter def archived(self) -> Optional[pulumi.Input[bool]]: """ Whether the project is in read-only mode (archived). Repositories can be archived/unarchived by toggling this parameter. """ return pulumi.get(self, "archived") @archived.setter def archived(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "archived", value) @property @pulumi.getter(name="buildCoverageRegex") def build_coverage_regex(self) -> Optional[pulumi.Input[str]]: """ Test coverage parsing for the project. """ return pulumi.get(self, "build_coverage_regex") @build_coverage_regex.setter def build_coverage_regex(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "build_coverage_regex", value) @property @pulumi.getter(name="ciConfigPath") def ci_config_path(self) -> Optional[pulumi.Input[str]]: """ Custom Path to CI config file. """ return pulumi.get(self, "ci_config_path") @ci_config_path.setter def ci_config_path(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ci_config_path", value) @property @pulumi.getter(name="containerRegistryEnabled") def container_registry_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable container registry for the project. """ return pulumi.get(self, "container_registry_enabled") @container_registry_enabled.setter def container_registry_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "container_registry_enabled", value) @property @pulumi.getter(name="defaultBranch") def default_branch(self) -> Optional[pulumi.Input[str]]: """ The default branch for the project. """ return pulumi.get(self, "default_branch") @default_branch.setter def default_branch(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "default_branch", value) @property @pulumi.getter def description(self) -> Optional[pulumi.Input[str]]: """ A description of the project. """ return pulumi.get(self, "description") @description.setter def description(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "description", value) @property @pulumi.getter(name="groupWithProjectTemplatesId") def group_with_project_templates_id(self) -> Optional[pulumi.Input[int]]: """ For group-level custom templates, specifies ID of group from which all the custom project templates are sourced. Leave empty for instance-level templates. Requires use_custom_template to be true (enterprise edition). """ return pulumi.get(self, "group_with_project_templates_id") @group_with_project_templates_id.setter def group_with_project_templates_id(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "group_with_project_templates_id", value) @property @pulumi.getter(name="importUrl") def import_url(self) -> Optional[pulumi.Input[str]]: """ Git URL to a repository to be imported. """ return pulumi.get(self, "import_url") @import_url.setter def import_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "import_url", value) @property @pulumi.getter(name="initializeWithReadme") def initialize_with_readme(self) -> Optional[pulumi.Input[bool]]: """ Create main branch with first commit containing a README.md file. """ return pulumi.get(self, "initialize_with_readme") @initialize_with_readme.setter def initialize_with_readme(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "initialize_with_readme", value) @property @pulumi.getter(name="issuesEnabled") def issues_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable issue tracking for the project. """ return pulumi.get(self, "issues_enabled") @issues_enabled.setter def issues_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "issues_enabled", value) @property @pulumi.getter(name="lfsEnabled") def lfs_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable LFS for the project. """ return pulumi.get(self, "lfs_enabled") @lfs_enabled.setter def lfs_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "lfs_enabled", value) @property @pulumi.getter(name="mergeMethod") def merge_method(self) -> Optional[pulumi.Input[str]]: """ Set to `ff` to create fast-forward merges Valid values are `merge`, `rebase_merge`, `ff` Repositories are created with `merge` by default """ return pulumi.get(self, "merge_method") @merge_method.setter def merge_method(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "merge_method", value) @property @pulumi.getter(name="mergeRequestsEnabled") def merge_requests_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable merge requests for the project. """ return pulumi.get(self, "merge_requests_enabled") @merge_requests_enabled.setter def merge_requests_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "merge_requests_enabled", value) @property @pulumi.getter def mirror(self) -> Optional[pulumi.Input[bool]]: """ Enables pull mirroring in a project. Default is `false`. For further information on mirroring, consult the [gitlab documentation](https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#repository-mirroring). """ return pulumi.get(self, "mirror") @mirror.setter def mirror(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "mirror", value) @property @pulumi.getter(name="mirrorOverwritesDivergedBranches") def mirror_overwrites_diverged_branches(self) -> Optional[pulumi.Input[bool]]: """ Pull mirror overwrites diverged branches. """ return pulumi.get(self, "mirror_overwrites_diverged_branches") @mirror_overwrites_diverged_branches.setter def mirror_overwrites_diverged_branches(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "mirror_overwrites_diverged_branches", value) @property @pulumi.getter(name="mirrorTriggerBuilds") def mirror_trigger_builds(self) -> Optional[pulumi.Input[bool]]: """ Pull mirroring triggers builds. Default is `false`. """ return pulumi.get(self, "mirror_trigger_builds") @mirror_trigger_builds.setter def mirror_trigger_builds(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "mirror_trigger_builds", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the project. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="namespaceId") def namespace_id(self) -> Optional[pulumi.Input[int]]: """ The namespace (group or user) of the project. Defaults to your user. See `Group` for an example. """ return pulumi.get(self, "namespace_id") @namespace_id.setter def namespace_id(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "namespace_id", value) @property @pulumi.getter(name="onlyAllowMergeIfAllDiscussionsAreResolved") def only_allow_merge_if_all_discussions_are_resolved(self) -> Optional[pulumi.Input[bool]]: """ Set to true if you want allow merges only if all discussions are resolved. """ return pulumi.get(self, "only_allow_merge_if_all_discussions_are_resolved") @only_allow_merge_if_all_discussions_are_resolved.setter def only_allow_merge_if_all_discussions_are_resolved(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "only_allow_merge_if_all_discussions_are_resolved", value) @property @pulumi.getter(name="onlyAllowMergeIfPipelineSucceeds") def only_allow_merge_if_pipeline_succeeds(self) -> Optional[pulumi.Input[bool]]: """ Set to true if you want allow merges only if a pipeline succeeds. """ return pulumi.get(self, "only_allow_merge_if_pipeline_succeeds") @only_allow_merge_if_pipeline_succeeds.setter def only_allow_merge_if_pipeline_succeeds(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "only_allow_merge_if_pipeline_succeeds", value) @property @pulumi.getter(name="onlyMirrorProtectedBranches") def only_mirror_protected_branches(self) -> Optional[pulumi.Input[bool]]: """ Only mirror protected branches. """ return pulumi.get(self, "only_mirror_protected_branches") @only_mirror_protected_branches.setter def only_mirror_protected_branches(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "only_mirror_protected_branches", value) @property @pulumi.getter(name="packagesEnabled") def packages_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable packages repository for the project. """ return pulumi.get(self, "packages_enabled") @packages_enabled.setter def packages_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "packages_enabled", value) @property @pulumi.getter(name="pagesAccessLevel") def pages_access_level(self) -> Optional[pulumi.Input[str]]: """ Enable pages access control Valid values are `disabled`, `private`, `enabled`, `public`. `private` is the default. """ return pulumi.get(self, "pages_access_level") @pages_access_level.setter def pages_access_level(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "pages_access_level", value) @property @pulumi.getter def path(self) -> Optional[pulumi.Input[str]]: """ The path of the repository. """ return pulumi.get(self, "path") @path.setter def path(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "path", value) @property @pulumi.getter(name="pipelinesEnabled") def pipelines_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable pipelines for the project. """ return pulumi.get(self, "pipelines_enabled") @pipelines_enabled.setter def pipelines_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "pipelines_enabled", value) @property @pulumi.getter(name="pushRules") def push_rules(self) -> Optional[pulumi.Input['ProjectPushRulesArgs']]: """ Push rules for the project (documented below). """ return pulumi.get(self, "push_rules") @push_rules.setter def push_rules(self, value: Optional[pulumi.Input['ProjectPushRulesArgs']]): pulumi.set(self, "push_rules", value) @property @pulumi.getter(name="removeSourceBranchAfterMerge") def remove_source_branch_after_merge(self) -> Optional[pulumi.Input[bool]]: """ Enable `Delete source branch` option by default for all new merge requests. """ return pulumi.get(self, "remove_source_branch_after_merge") @remove_source_branch_after_merge.setter def remove_source_branch_after_merge(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "remove_source_branch_after_merge", value) @property @pulumi.getter(name="requestAccessEnabled") def request_access_enabled(self) -> Optional[pulumi.Input[bool]]: """ Allow users to request member access. """ return pulumi.get(self, "request_access_enabled") @request_access_enabled.setter def request_access_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "request_access_enabled", value) @property @pulumi.getter(name="sharedRunnersEnabled") def shared_runners_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable shared runners for this project. """ return pulumi.get(self, "shared_runners_enabled") @shared_runners_enabled.setter def shared_runners_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "shared_runners_enabled", value) @property @pulumi.getter(name="snippetsEnabled") def snippets_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable snippets for the project. """ return pulumi.get(self, "snippets_enabled") @snippets_enabled.setter def snippets_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "snippets_enabled", value) @property @pulumi.getter def tags(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Tags (topics) of the project. """ return pulumi.get(self, "tags") @tags.setter def tags(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "tags", value) @property @pulumi.getter(name="templateName") def template_name(self) -> Optional[pulumi.Input[str]]: """ When used without use_custom_template, name of a built-in project template. When used with use_custom_template, name of a custom project template. This option is mutually exclusive with `template_project_id`. """ return pulumi.get(self, "template_name") @template_name.setter def template_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "template_name", value) @property @pulumi.getter(name="templateProjectId") def template_project_id(self) -> Optional[pulumi.Input[int]]: """ When used with use_custom_template, project ID of a custom project template. This is preferable to using template_name since template_name may be ambiguous (enterprise edition). This option is mutually exclusive with `template_name`. """ return pulumi.get(self, "template_project_id") @template_project_id.setter def template_project_id(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "template_project_id", value) @property @pulumi.getter(name="useCustomTemplate") def use_custom_template(self) -> Optional[pulumi.Input[bool]]: """ Use either custom instance or group (with group_with_project_templates_id) project template (enterprise edition). """ return pulumi.get(self, "use_custom_template") @use_custom_template.setter def use_custom_template(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "use_custom_template", value) @property @pulumi.getter(name="visibilityLevel") def visibility_level(self) -> Optional[pulumi.Input[str]]: """ Set to `public` to create a public project. Valid values are `private`, `internal`, `public`. Repositories are created as private by default. """ return pulumi.get(self, "visibility_level") @visibility_level.setter def visibility_level(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "visibility_level", value) @property @pulumi.getter(name="wikiEnabled") def wiki_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable wiki for the project. """ return pulumi.get(self, "wiki_enabled") @wiki_enabled.setter def wiki_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "wiki_enabled", value) @pulumi.input_type class _ProjectState: def __init__(__self__, *, approvals_before_merge: Optional[pulumi.Input[int]] = None, archived: Optional[pulumi.Input[bool]] = None, build_coverage_regex: Optional[pulumi.Input[str]] = None, ci_config_path: Optional[pulumi.Input[str]] = None, container_registry_enabled: Optional[pulumi.Input[bool]] = None, default_branch: Optional[pulumi.Input[str]] = None, description: Optional[pulumi.Input[str]] = None, group_with_project_templates_id: Optional[pulumi.Input[int]] = None, http_url_to_repo: Optional[pulumi.Input[str]] = None, import_url: Optional[pulumi.Input[str]] = None, initialize_with_readme: Optional[pulumi.Input[bool]] = None, issues_enabled: Optional[pulumi.Input[bool]] = None, lfs_enabled: Optional[pulumi.Input[bool]] = None, merge_method: Optional[pulumi.Input[str]] = None, merge_requests_enabled: Optional[pulumi.Input[bool]] = None, mirror: Optional[pulumi.Input[bool]] = None, mirror_overwrites_diverged_branches: Optional[pulumi.Input[bool]] = None, mirror_trigger_builds: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, namespace_id: Optional[pulumi.Input[int]] = None, only_allow_merge_if_all_discussions_are_resolved: Optional[pulumi.Input[bool]] = None, only_allow_merge_if_pipeline_succeeds: Optional[pulumi.Input[bool]] = None, only_mirror_protected_branches: Optional[pulumi.Input[bool]] = None, packages_enabled: Optional[pulumi.Input[bool]] = None, pages_access_level: Optional[pulumi.Input[str]] = None, path: Optional[pulumi.Input[str]] = None, path_with_namespace: Optional[pulumi.Input[str]] = None, pipelines_enabled: Optional[pulumi.Input[bool]] = None, push_rules: Optional[pulumi.Input['ProjectPushRulesArgs']] = None, remove_source_branch_after_merge: Optional[pulumi.Input[bool]] = None, request_access_enabled: Optional[pulumi.Input[bool]] = None, runners_token: Optional[pulumi.Input[str]] = None, shared_runners_enabled: Optional[pulumi.Input[bool]] = None, snippets_enabled: Optional[pulumi.Input[bool]] = None, ssh_url_to_repo: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, template_name: Optional[pulumi.Input[str]] = None, template_project_id: Optional[pulumi.Input[int]] = None, use_custom_template: Optional[pulumi.Input[bool]] = None, visibility_level: Optional[pulumi.Input[str]] = None, web_url: Optional[pulumi.Input[str]] = None, wiki_enabled: Optional[pulumi.Input[bool]] = None): """ Input properties used for looking up and filtering Project resources. :param pulumi.Input[int] approvals_before_merge: Number of merge request approvals required for merging. Default is 0. :param pulumi.Input[bool] archived: Whether the project is in read-only mode (archived). Repositories can be archived/unarchived by toggling this parameter. :param pulumi.Input[str] build_coverage_regex: Test coverage parsing for the project. :param pulumi.Input[str] ci_config_path: Custom Path to CI config file. :param pulumi.Input[bool] container_registry_enabled: Enable container registry for the project. :param pulumi.Input[str] default_branch: The default branch for the project. :param pulumi.Input[str] description: A description of the project. :param pulumi.Input[int] group_with_project_templates_id: For group-level custom templates, specifies ID of group from which all the custom project templates are sourced. Leave empty for instance-level templates. Requires use_custom_template to be true (enterprise edition). :param pulumi.Input[str] http_url_to_repo: URL that can be provided to `git clone` to clone the repository via HTTP. :param pulumi.Input[str] import_url: Git URL to a repository to be imported. :param pulumi.Input[bool] initialize_with_readme: Create main branch with first commit containing a README.md file. :param pulumi.Input[bool] issues_enabled: Enable issue tracking for the project. :param pulumi.Input[bool] lfs_enabled: Enable LFS for the project. :param pulumi.Input[str] merge_method: Set to `ff` to create fast-forward merges Valid values are `merge`, `rebase_merge`, `ff` Repositories are created with `merge` by default :param pulumi.Input[bool] merge_requests_enabled: Enable merge requests for the project. :param pulumi.Input[bool] mirror: Enables pull mirroring in a project. Default is `false`. For further information on mirroring, consult the [gitlab documentation](https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#repository-mirroring). :param pulumi.Input[bool] mirror_overwrites_diverged_branches: Pull mirror overwrites diverged branches. :param pulumi.Input[bool] mirror_trigger_builds: Pull mirroring triggers builds. Default is `false`. :param pulumi.Input[str] name: The name of the project. :param pulumi.Input[int] namespace_id: The namespace (group or user) of the project. Defaults to your user. See `Group` for an example. :param pulumi.Input[bool] only_allow_merge_if_all_discussions_are_resolved: Set to true if you want allow merges only if all discussions are resolved. :param pulumi.Input[bool] only_allow_merge_if_pipeline_succeeds: Set to true if you want allow merges only if a pipeline succeeds. :param pulumi.Input[bool] only_mirror_protected_branches: Only mirror protected branches. :param pulumi.Input[bool] packages_enabled: Enable packages repository for the project. :param pulumi.Input[str] pages_access_level: Enable pages access control Valid values are `disabled`, `private`, `enabled`, `public`. `private` is the default. :param pulumi.Input[str] path: The path of the repository. :param pulumi.Input[str] path_with_namespace: The path of the repository with namespace. :param pulumi.Input[bool] pipelines_enabled: Enable pipelines for the project. :param pulumi.Input['ProjectPushRulesArgs'] push_rules: Push rules for the project (documented below). :param pulumi.Input[bool] remove_source_branch_after_merge: Enable `Delete source branch` option by default for all new merge requests. :param pulumi.Input[bool] request_access_enabled: Allow users to request member access. :param pulumi.Input[str] runners_token: Registration token to use during runner setup. :param pulumi.Input[bool] shared_runners_enabled: Enable shared runners for this project. :param pulumi.Input[bool] snippets_enabled: Enable snippets for the project. :param pulumi.Input[str] ssh_url_to_repo: URL that can be provided to `git clone` to clone the repository via SSH. :param pulumi.Input[Sequence[pulumi.Input[str]]] tags: Tags (topics) of the project. :param pulumi.Input[str] template_name: When used without use_custom_template, name of a built-in project template. When used with use_custom_template, name of a custom project template. This option is mutually exclusive with `template_project_id`. :param pulumi.Input[int] template_project_id: When used with use_custom_template, project ID of a custom project template. This is preferable to using template_name since template_name may be ambiguous (enterprise edition). This option is mutually exclusive with `template_name`. :param pulumi.Input[bool] use_custom_template: Use either custom instance or group (with group_with_project_templates_id) project template (enterprise edition). :param pulumi.Input[str] visibility_level: Set to `public` to create a public project. Valid values are `private`, `internal`, `public`. Repositories are created as private by default. :param pulumi.Input[str] web_url: URL that can be used to find the project in a browser. :param pulumi.Input[bool] wiki_enabled: Enable wiki for the project. """ if approvals_before_merge is not None: pulumi.set(__self__, "approvals_before_merge", approvals_before_merge) if archived is not None: pulumi.set(__self__, "archived", archived) if build_coverage_regex is not None: pulumi.set(__self__, "build_coverage_regex", build_coverage_regex) if ci_config_path is not None: pulumi.set(__self__, "ci_config_path", ci_config_path) if container_registry_enabled is not None: pulumi.set(__self__, "container_registry_enabled", container_registry_enabled) if default_branch is not None: pulumi.set(__self__, "default_branch", default_branch) if description is not None: pulumi.set(__self__, "description", description) if group_with_project_templates_id is not None: pulumi.set(__self__, "group_with_project_templates_id", group_with_project_templates_id) if http_url_to_repo is not None: pulumi.set(__self__, "http_url_to_repo", http_url_to_repo) if import_url is not None: pulumi.set(__self__, "import_url", import_url) if initialize_with_readme is not None: pulumi.set(__self__, "initialize_with_readme", initialize_with_readme) if issues_enabled is not None: pulumi.set(__self__, "issues_enabled", issues_enabled) if lfs_enabled is not None: pulumi.set(__self__, "lfs_enabled", lfs_enabled) if merge_method is not None: pulumi.set(__self__, "merge_method", merge_method) if merge_requests_enabled is not None: pulumi.set(__self__, "merge_requests_enabled", merge_requests_enabled) if mirror is not None: pulumi.set(__self__, "mirror", mirror) if mirror_overwrites_diverged_branches is not None: pulumi.set(__self__, "mirror_overwrites_diverged_branches", mirror_overwrites_diverged_branches) if mirror_trigger_builds is not None: pulumi.set(__self__, "mirror_trigger_builds", mirror_trigger_builds) if name is not None: pulumi.set(__self__, "name", name) if namespace_id is not None: pulumi.set(__self__, "namespace_id", namespace_id) if only_allow_merge_if_all_discussions_are_resolved is not None: pulumi.set(__self__, "only_allow_merge_if_all_discussions_are_resolved", only_allow_merge_if_all_discussions_are_resolved) if only_allow_merge_if_pipeline_succeeds is not None: pulumi.set(__self__, "only_allow_merge_if_pipeline_succeeds", only_allow_merge_if_pipeline_succeeds) if only_mirror_protected_branches is not None: pulumi.set(__self__, "only_mirror_protected_branches", only_mirror_protected_branches) if packages_enabled is not None: pulumi.set(__self__, "packages_enabled", packages_enabled) if pages_access_level is not None: pulumi.set(__self__, "pages_access_level", pages_access_level) if path is not None: pulumi.set(__self__, "path", path) if path_with_namespace is not None: pulumi.set(__self__, "path_with_namespace", path_with_namespace) if pipelines_enabled is not None: pulumi.set(__self__, "pipelines_enabled", pipelines_enabled) if push_rules is not None: pulumi.set(__self__, "push_rules", push_rules) if remove_source_branch_after_merge is not None: pulumi.set(__self__, "remove_source_branch_after_merge", remove_source_branch_after_merge) if request_access_enabled is not None: pulumi.set(__self__, "request_access_enabled", request_access_enabled) if runners_token is not None: pulumi.set(__self__, "runners_token", runners_token) if shared_runners_enabled is not None: pulumi.set(__self__, "shared_runners_enabled", shared_runners_enabled) if snippets_enabled is not None: pulumi.set(__self__, "snippets_enabled", snippets_enabled) if ssh_url_to_repo is not None: pulumi.set(__self__, "ssh_url_to_repo", ssh_url_to_repo) if tags is not None: pulumi.set(__self__, "tags", tags) if template_name is not None: pulumi.set(__self__, "template_name", template_name) if template_project_id is not None: pulumi.set(__self__, "template_project_id", template_project_id) if use_custom_template is not None: pulumi.set(__self__, "use_custom_template", use_custom_template) if visibility_level is not None: pulumi.set(__self__, "visibility_level", visibility_level) if web_url is not None: pulumi.set(__self__, "web_url", web_url) if wiki_enabled is not None: pulumi.set(__self__, "wiki_enabled", wiki_enabled) @property @pulumi.getter(name="approvalsBeforeMerge") def approvals_before_merge(self) -> Optional[pulumi.Input[int]]: """ Number of merge request approvals required for merging. Default is 0. """ return pulumi.get(self, "approvals_before_merge") @approvals_before_merge.setter def approvals_before_merge(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "approvals_before_merge", value) @property @pulumi.getter def archived(self) -> Optional[pulumi.Input[bool]]: """ Whether the project is in read-only mode (archived). Repositories can be archived/unarchived by toggling this parameter. """ return pulumi.get(self, "archived") @archived.setter def archived(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "archived", value) @property @pulumi.getter(name="buildCoverageRegex") def build_coverage_regex(self) -> Optional[pulumi.Input[str]]: """ Test coverage parsing for the project. """ return pulumi.get(self, "build_coverage_regex") @build_coverage_regex.setter def build_coverage_regex(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "build_coverage_regex", value) @property @pulumi.getter(name="ciConfigPath") def ci_config_path(self) -> Optional[pulumi.Input[str]]: """ Custom Path to CI config file. """ return pulumi.get(self, "ci_config_path") @ci_config_path.setter def ci_config_path(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ci_config_path", value) @property @pulumi.getter(name="containerRegistryEnabled") def container_registry_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable container registry for the project. """ return pulumi.get(self, "container_registry_enabled") @container_registry_enabled.setter def container_registry_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "container_registry_enabled", value) @property @pulumi.getter(name="defaultBranch") def default_branch(self) -> Optional[pulumi.Input[str]]: """ The default branch for the project. """ return pulumi.get(self, "default_branch") @default_branch.setter def default_branch(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "default_branch", value) @property @pulumi.getter def description(self) -> Optional[pulumi.Input[str]]: """ A description of the project. """ return pulumi.get(self, "description") @description.setter def description(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "description", value) @property @pulumi.getter(name="groupWithProjectTemplatesId") def group_with_project_templates_id(self) -> Optional[pulumi.Input[int]]: """ For group-level custom templates, specifies ID of group from which all the custom project templates are sourced. Leave empty for instance-level templates. Requires use_custom_template to be true (enterprise edition). """ return pulumi.get(self, "group_with_project_templates_id") @group_with_project_templates_id.setter def group_with_project_templates_id(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "group_with_project_templates_id", value) @property @pulumi.getter(name="httpUrlToRepo") def http_url_to_repo(self) -> Optional[pulumi.Input[str]]: """ URL that can be provided to `git clone` to clone the repository via HTTP. """ return pulumi.get(self, "http_url_to_repo") @http_url_to_repo.setter def http_url_to_repo(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "http_url_to_repo", value) @property @pulumi.getter(name="importUrl") def import_url(self) -> Optional[pulumi.Input[str]]: """ Git URL to a repository to be imported. """ return pulumi.get(self, "import_url") @import_url.setter def import_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "import_url", value) @property @pulumi.getter(name="initializeWithReadme") def initialize_with_readme(self) -> Optional[pulumi.Input[bool]]: """ Create main branch with first commit containing a README.md file. """ return pulumi.get(self, "initialize_with_readme") @initialize_with_readme.setter def initialize_with_readme(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "initialize_with_readme", value) @property @pulumi.getter(name="issuesEnabled") def issues_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable issue tracking for the project. """ return pulumi.get(self, "issues_enabled") @issues_enabled.setter def issues_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "issues_enabled", value) @property @pulumi.getter(name="lfsEnabled") def lfs_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable LFS for the project. """ return pulumi.get(self, "lfs_enabled") @lfs_enabled.setter def lfs_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "lfs_enabled", value) @property @pulumi.getter(name="mergeMethod") def merge_method(self) -> Optional[pulumi.Input[str]]: """ Set to `ff` to create fast-forward merges Valid values are `merge`, `rebase_merge`, `ff` Repositories are created with `merge` by default """ return pulumi.get(self, "merge_method") @merge_method.setter def merge_method(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "merge_method", value) @property @pulumi.getter(name="mergeRequestsEnabled") def merge_requests_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable merge requests for the project. """ return pulumi.get(self, "merge_requests_enabled") @merge_requests_enabled.setter def merge_requests_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "merge_requests_enabled", value) @property @pulumi.getter def mirror(self) -> Optional[pulumi.Input[bool]]: """ Enables pull mirroring in a project. Default is `false`. For further information on mirroring, consult the [gitlab documentation](https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#repository-mirroring). """ return pulumi.get(self, "mirror") @mirror.setter def mirror(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "mirror", value) @property @pulumi.getter(name="mirrorOverwritesDivergedBranches") def mirror_overwrites_diverged_branches(self) -> Optional[pulumi.Input[bool]]: """ Pull mirror overwrites diverged branches. """ return pulumi.get(self, "mirror_overwrites_diverged_branches") @mirror_overwrites_diverged_branches.setter def mirror_overwrites_diverged_branches(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "mirror_overwrites_diverged_branches", value) @property @pulumi.getter(name="mirrorTriggerBuilds") def mirror_trigger_builds(self) -> Optional[pulumi.Input[bool]]: """ Pull mirroring triggers builds. Default is `false`. """ return pulumi.get(self, "mirror_trigger_builds") @mirror_trigger_builds.setter def mirror_trigger_builds(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "mirror_trigger_builds", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the project. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="namespaceId") def namespace_id(self) -> Optional[pulumi.Input[int]]: """ The namespace (group or user) of the project. Defaults to your user. See `Group` for an example. """ return pulumi.get(self, "namespace_id") @namespace_id.setter def namespace_id(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "namespace_id", value) @property @pulumi.getter(name="onlyAllowMergeIfAllDiscussionsAreResolved") def only_allow_merge_if_all_discussions_are_resolved(self) -> Optional[pulumi.Input[bool]]: """ Set to true if you want allow merges only if all discussions are resolved. """ return pulumi.get(self, "only_allow_merge_if_all_discussions_are_resolved") @only_allow_merge_if_all_discussions_are_resolved.setter def only_allow_merge_if_all_discussions_are_resolved(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "only_allow_merge_if_all_discussions_are_resolved", value) @property @pulumi.getter(name="onlyAllowMergeIfPipelineSucceeds") def only_allow_merge_if_pipeline_succeeds(self) -> Optional[pulumi.Input[bool]]: """ Set to true if you want allow merges only if a pipeline succeeds. """ return pulumi.get(self, "only_allow_merge_if_pipeline_succeeds") @only_allow_merge_if_pipeline_succeeds.setter def only_allow_merge_if_pipeline_succeeds(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "only_allow_merge_if_pipeline_succeeds", value) @property @pulumi.getter(name="onlyMirrorProtectedBranches") def only_mirror_protected_branches(self) -> Optional[pulumi.Input[bool]]: """ Only mirror protected branches. """ return pulumi.get(self, "only_mirror_protected_branches") @only_mirror_protected_branches.setter def only_mirror_protected_branches(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "only_mirror_protected_branches", value) @property @pulumi.getter(name="packagesEnabled") def packages_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable packages repository for the project. """ return pulumi.get(self, "packages_enabled") @packages_enabled.setter def packages_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "packages_enabled", value) @property @pulumi.getter(name="pagesAccessLevel") def pages_access_level(self) -> Optional[pulumi.Input[str]]: """ Enable pages access control Valid values are `disabled`, `private`, `enabled`, `public`. `private` is the default. """ return pulumi.get(self, "pages_access_level") @pages_access_level.setter def pages_access_level(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "pages_access_level", value) @property @pulumi.getter def path(self) -> Optional[pulumi.Input[str]]: """ The path of the repository. """ return pulumi.get(self, "path") @path.setter def path(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "path", value) @property @pulumi.getter(name="pathWithNamespace") def path_with_namespace(self) -> Optional[pulumi.Input[str]]: """ The path of the repository with namespace. """ return pulumi.get(self, "path_with_namespace") @path_with_namespace.setter def path_with_namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "path_with_namespace", value) @property @pulumi.getter(name="pipelinesEnabled") def pipelines_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable pipelines for the project. """ return pulumi.get(self, "pipelines_enabled") @pipelines_enabled.setter def pipelines_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "pipelines_enabled", value) @property @pulumi.getter(name="pushRules") def push_rules(self) -> Optional[pulumi.Input['ProjectPushRulesArgs']]: """ Push rules for the project (documented below). """ return pulumi.get(self, "push_rules") @push_rules.setter def push_rules(self, value: Optional[pulumi.Input['ProjectPushRulesArgs']]): pulumi.set(self, "push_rules", value) @property @pulumi.getter(name="removeSourceBranchAfterMerge") def remove_source_branch_after_merge(self) -> Optional[pulumi.Input[bool]]: """ Enable `Delete source branch` option by default for all new merge requests. """ return pulumi.get(self, "remove_source_branch_after_merge") @remove_source_branch_after_merge.setter def remove_source_branch_after_merge(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "remove_source_branch_after_merge", value) @property @pulumi.getter(name="requestAccessEnabled") def request_access_enabled(self) -> Optional[pulumi.Input[bool]]: """ Allow users to request member access. """ return pulumi.get(self, "request_access_enabled") @request_access_enabled.setter def request_access_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "request_access_enabled", value) @property @pulumi.getter(name="runnersToken") def runners_token(self) -> Optional[pulumi.Input[str]]: """ Registration token to use during runner setup. """ return pulumi.get(self, "runners_token") @runners_token.setter def runners_token(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "runners_token", value) @property @pulumi.getter(name="sharedRunnersEnabled") def shared_runners_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable shared runners for this project. """ return pulumi.get(self, "shared_runners_enabled") @shared_runners_enabled.setter def shared_runners_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "shared_runners_enabled", value) @property @pulumi.getter(name="snippetsEnabled") def snippets_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable snippets for the project. """ return pulumi.get(self, "snippets_enabled") @snippets_enabled.setter def snippets_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "snippets_enabled", value) @property @pulumi.getter(name="sshUrlToRepo") def ssh_url_to_repo(self) -> Optional[pulumi.Input[str]]: """ URL that can be provided to `git clone` to clone the repository via SSH. """ return pulumi.get(self, "ssh_url_to_repo") @ssh_url_to_repo.setter def ssh_url_to_repo(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ssh_url_to_repo", value) @property @pulumi.getter def tags(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Tags (topics) of the project. """ return pulumi.get(self, "tags") @tags.setter def tags(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "tags", value) @property @pulumi.getter(name="templateName") def template_name(self) -> Optional[pulumi.Input[str]]: """ When used without use_custom_template, name of a built-in project template. When used with use_custom_template, name of a custom project template. This option is mutually exclusive with `template_project_id`. """ return pulumi.get(self, "template_name") @template_name.setter def template_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "template_name", value) @property @pulumi.getter(name="templateProjectId") def template_project_id(self) -> Optional[pulumi.Input[int]]: """ When used with use_custom_template, project ID of a custom project template. This is preferable to using template_name since template_name may be ambiguous (enterprise edition). This option is mutually exclusive with `template_name`. """ return pulumi.get(self, "template_project_id") @template_project_id.setter def template_project_id(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "template_project_id", value) @property @pulumi.getter(name="useCustomTemplate") def use_custom_template(self) -> Optional[pulumi.Input[bool]]: """ Use either custom instance or group (with group_with_project_templates_id) project template (enterprise edition). """ return pulumi.get(self, "use_custom_template") @use_custom_template.setter def use_custom_template(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "use_custom_template", value) @property @pulumi.getter(name="visibilityLevel") def visibility_level(self) -> Optional[pulumi.Input[str]]: """ Set to `public` to create a public project. Valid values are `private`, `internal`, `public`. Repositories are created as private by default. """ return pulumi.get(self, "visibility_level") @visibility_level.setter def visibility_level(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "visibility_level", value) @property @pulumi.getter(name="webUrl") def web_url(self) -> Optional[pulumi.Input[str]]: """ URL that can be used to find the project in a browser. """ return pulumi.get(self, "web_url") @web_url.setter def web_url(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "web_url", value) @property @pulumi.getter(name="wikiEnabled") def wiki_enabled(self) -> Optional[pulumi.Input[bool]]: """ Enable wiki for the project. """ return pulumi.get(self, "wiki_enabled") @wiki_enabled.setter def wiki_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "wiki_enabled", value) class Project(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, approvals_before_merge: Optional[pulumi.Input[int]] = None, archived: Optional[pulumi.Input[bool]] = None, build_coverage_regex: Optional[pulumi.Input[str]] = None, ci_config_path: Optional[pulumi.Input[str]] = None, container_registry_enabled: Optional[pulumi.Input[bool]] = None, default_branch: Optional[pulumi.Input[str]] = None, description: Optional[pulumi.Input[str]] = None, group_with_project_templates_id: Optional[pulumi.Input[int]] = None, import_url: Optional[pulumi.Input[str]] = None, initialize_with_readme: Optional[pulumi.Input[bool]] = None, issues_enabled: Optional[pulumi.Input[bool]] = None, lfs_enabled: Optional[pulumi.Input[bool]] = None, merge_method: Optional[pulumi.Input[str]] = None, merge_requests_enabled: Optional[pulumi.Input[bool]] = None, mirror: Optional[pulumi.Input[bool]] = None, mirror_overwrites_diverged_branches: Optional[pulumi.Input[bool]] = None, mirror_trigger_builds: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, namespace_id: Optional[pulumi.Input[int]] = None, only_allow_merge_if_all_discussions_are_resolved: Optional[pulumi.Input[bool]] = None, only_allow_merge_if_pipeline_succeeds: Optional[pulumi.Input[bool]] = None, only_mirror_protected_branches: Optional[pulumi.Input[bool]] = None, packages_enabled: Optional[pulumi.Input[bool]] = None, pages_access_level: Optional[pulumi.Input[str]] = None, path: Optional[pulumi.Input[str]] = None, pipelines_enabled: Optional[pulumi.Input[bool]] = None, push_rules: Optional[pulumi.Input[pulumi.InputType['ProjectPushRulesArgs']]] = None, remove_source_branch_after_merge: Optional[pulumi.Input[bool]] = None, request_access_enabled: Optional[pulumi.Input[bool]] = None, shared_runners_enabled: Optional[pulumi.Input[bool]] = None, snippets_enabled: Optional[pulumi.Input[bool]] = None, tags: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, template_name: Optional[pulumi.Input[str]] = None, template_project_id: Optional[pulumi.Input[int]] = None, use_custom_template: Optional[pulumi.Input[bool]] = None, visibility_level: Optional[pulumi.Input[str]] = None, wiki_enabled: Optional[pulumi.Input[bool]] = None, __props__=None): """ ## # gitlab\_project This resource allows you to create and manage projects within your GitLab group or within your user. ## Example Usage ```python import pulumi import pulumi_gitlab as gitlab example = gitlab.Project("example", description="My awesome codebase", visibility_level="public") # Project with custom push rules example_two = gitlab.Project("example-two", push_rules=gitlab.ProjectPushRulesArgs( author_email_regex="@example\\.com$", commit_committer_check=True, member_check=True, prevent_secrets=True, )) ``` ## Import ```sh $ pulumi import gitlab:index/project:Project You can import a project state using `<resource> <id>`. The ``` `id` can be whatever the [get single project api][get_single_project] takes for its `:id` value, so for example ```sh $ pulumi import gitlab:index/project:Project example richardc/example ``` [get_single_project]https://docs.gitlab.com/ee/api/projects.html#get-single-project [group_members_permissions]https://docs.gitlab.com/ce/user/permissions.html#group-members-permissions :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[int] approvals_before_merge: Number of merge request approvals required for merging. Default is 0. :param pulumi.Input[bool] archived: Whether the project is in read-only mode (archived). Repositories can be archived/unarchived by toggling this parameter. :param pulumi.Input[str] build_coverage_regex: Test coverage parsing for the project. :param pulumi.Input[str] ci_config_path: Custom Path to CI config file. :param pulumi.Input[bool] container_registry_enabled: Enable container registry for the project. :param pulumi.Input[str] default_branch: The default branch for the project. :param pulumi.Input[str] description: A description of the project. :param pulumi.Input[int] group_with_project_templates_id: For group-level custom templates, specifies ID of group from which all the custom project templates are sourced. Leave empty for instance-level templates. Requires use_custom_template to be true (enterprise edition). :param pulumi.Input[str] import_url: Git URL to a repository to be imported. :param pulumi.Input[bool] initialize_with_readme: Create main branch with first commit containing a README.md file. :param pulumi.Input[bool] issues_enabled: Enable issue tracking for the project. :param pulumi.Input[bool] lfs_enabled: Enable LFS for the project. :param pulumi.Input[str] merge_method: Set to `ff` to create fast-forward merges Valid values are `merge`, `rebase_merge`, `ff` Repositories are created with `merge` by default :param pulumi.Input[bool] merge_requests_enabled: Enable merge requests for the project. :param pulumi.Input[bool] mirror: Enables pull mirroring in a project. Default is `false`. For further information on mirroring, consult the [gitlab documentation](https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#repository-mirroring). :param pulumi.Input[bool] mirror_overwrites_diverged_branches: Pull mirror overwrites diverged branches. :param pulumi.Input[bool] mirror_trigger_builds: Pull mirroring triggers builds. Default is `false`. :param pulumi.Input[str] name: The name of the project. :param pulumi.Input[int] namespace_id: The namespace (group or user) of the project. Defaults to your user. See `Group` for an example. :param pulumi.Input[bool] only_allow_merge_if_all_discussions_are_resolved: Set to true if you want allow merges only if all discussions are resolved. :param pulumi.Input[bool] only_allow_merge_if_pipeline_succeeds: Set to true if you want allow merges only if a pipeline succeeds. :param pulumi.Input[bool] only_mirror_protected_branches: Only mirror protected branches. :param pulumi.Input[bool] packages_enabled: Enable packages repository for the project. :param pulumi.Input[str] pages_access_level: Enable pages access control Valid values are `disabled`, `private`, `enabled`, `public`. `private` is the default. :param pulumi.Input[str] path: The path of the repository. :param pulumi.Input[bool] pipelines_enabled: Enable pipelines for the project. :param pulumi.Input[pulumi.InputType['ProjectPushRulesArgs']] push_rules: Push rules for the project (documented below). :param pulumi.Input[bool] remove_source_branch_after_merge: Enable `Delete source branch` option by default for all new merge requests. :param pulumi.Input[bool] request_access_enabled: Allow users to request member access. :param pulumi.Input[bool] shared_runners_enabled: Enable shared runners for this project. :param pulumi.Input[bool] snippets_enabled: Enable snippets for the project. :param pulumi.Input[Sequence[pulumi.Input[str]]] tags: Tags (topics) of the project. :param pulumi.Input[str] template_name: When used without use_custom_template, name of a built-in project template. When used with use_custom_template, name of a custom project template. This option is mutually exclusive with `template_project_id`. :param pulumi.Input[int] template_project_id: When used with use_custom_template, project ID of a custom project template. This is preferable to using template_name since template_name may be ambiguous (enterprise edition). This option is mutually exclusive with `template_name`. :param pulumi.Input[bool] use_custom_template: Use either custom instance or group (with group_with_project_templates_id) project template (enterprise edition). :param pulumi.Input[str] visibility_level: Set to `public` to create a public project. Valid values are `private`, `internal`, `public`. Repositories are created as private by default. :param pulumi.Input[bool] wiki_enabled: Enable wiki for the project. """ ... @overload def __init__(__self__, resource_name: str, args: Optional[ProjectArgs] = None, opts: Optional[pulumi.ResourceOptions] = None): """ ## # gitlab\_project This resource allows you to create and manage projects within your GitLab group or within your user. ## Example Usage ```python import pulumi import pulumi_gitlab as gitlab example = gitlab.Project("example", description="My awesome codebase", visibility_level="public") # Project with custom push rules example_two = gitlab.Project("example-two", push_rules=gitlab.ProjectPushRulesArgs( author_email_regex="@example\\.com$", commit_committer_check=True, member_check=True, prevent_secrets=True, )) ``` ## Import ```sh $ pulumi import gitlab:index/project:Project You can import a project state using `<resource> <id>`. The ``` `id` can be whatever the [get single project api][get_single_project] takes for its `:id` value, so for example ```sh $ pulumi import gitlab:index/project:Project example richardc/example ``` [get_single_project]https://docs.gitlab.com/ee/api/projects.html#get-single-project [group_members_permissions]https://docs.gitlab.com/ce/user/permissions.html#group-members-permissions :param str resource_name: The name of the resource. :param ProjectArgs 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(ProjectArgs, 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, approvals_before_merge: Optional[pulumi.Input[int]] = None, archived: Optional[pulumi.Input[bool]] = None, build_coverage_regex: Optional[pulumi.Input[str]] = None, ci_config_path: Optional[pulumi.Input[str]] = None, container_registry_enabled: Optional[pulumi.Input[bool]] = None, default_branch: Optional[pulumi.Input[str]] = None, description: Optional[pulumi.Input[str]] = None, group_with_project_templates_id: Optional[pulumi.Input[int]] = None, import_url: Optional[pulumi.Input[str]] = None, initialize_with_readme: Optional[pulumi.Input[bool]] = None, issues_enabled: Optional[pulumi.Input[bool]] = None, lfs_enabled: Optional[pulumi.Input[bool]] = None, merge_method: Optional[pulumi.Input[str]] = None, merge_requests_enabled: Optional[pulumi.Input[bool]] = None, mirror: Optional[pulumi.Input[bool]] = None, mirror_overwrites_diverged_branches: Optional[pulumi.Input[bool]] = None, mirror_trigger_builds: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, namespace_id: Optional[pulumi.Input[int]] = None, only_allow_merge_if_all_discussions_are_resolved: Optional[pulumi.Input[bool]] = None, only_allow_merge_if_pipeline_succeeds: Optional[pulumi.Input[bool]] = None, only_mirror_protected_branches: Optional[pulumi.Input[bool]] = None, packages_enabled: Optional[pulumi.Input[bool]] = None, pages_access_level: Optional[pulumi.Input[str]] = None, path: Optional[pulumi.Input[str]] = None, pipelines_enabled: Optional[pulumi.Input[bool]] = None, push_rules: Optional[pulumi.Input[pulumi.InputType['ProjectPushRulesArgs']]] = None, remove_source_branch_after_merge: Optional[pulumi.Input[bool]] = None, request_access_enabled: Optional[pulumi.Input[bool]] = None, shared_runners_enabled: Optional[pulumi.Input[bool]] = None, snippets_enabled: Optional[pulumi.Input[bool]] = None, tags: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, template_name: Optional[pulumi.Input[str]] = None, template_project_id: Optional[pulumi.Input[int]] = None, use_custom_template: Optional[pulumi.Input[bool]] = None, visibility_level: Optional[pulumi.Input[str]] = None, wiki_enabled: Optional[pulumi.Input[bool]] = 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__ = ProjectArgs.__new__(ProjectArgs) __props__.__dict__["approvals_before_merge"] = approvals_before_merge __props__.__dict__["archived"] = archived __props__.__dict__["build_coverage_regex"] = build_coverage_regex __props__.__dict__["ci_config_path"] = ci_config_path __props__.__dict__["container_registry_enabled"] = container_registry_enabled __props__.__dict__["default_branch"] = default_branch __props__.__dict__["description"] = description __props__.__dict__["group_with_project_templates_id"] = group_with_project_templates_id __props__.__dict__["import_url"] = import_url __props__.__dict__["initialize_with_readme"] = initialize_with_readme __props__.__dict__["issues_enabled"] = issues_enabled __props__.__dict__["lfs_enabled"] = lfs_enabled __props__.__dict__["merge_method"] = merge_method __props__.__dict__["merge_requests_enabled"] = merge_requests_enabled __props__.__dict__["mirror"] = mirror __props__.__dict__["mirror_overwrites_diverged_branches"] = mirror_overwrites_diverged_branches __props__.__dict__["mirror_trigger_builds"] = mirror_trigger_builds __props__.__dict__["name"] = name __props__.__dict__["namespace_id"] = namespace_id __props__.__dict__["only_allow_merge_if_all_discussions_are_resolved"] = only_allow_merge_if_all_discussions_are_resolved __props__.__dict__["only_allow_merge_if_pipeline_succeeds"] = only_allow_merge_if_pipeline_succeeds __props__.__dict__["only_mirror_protected_branches"] = only_mirror_protected_branches __props__.__dict__["packages_enabled"] = packages_enabled __props__.__dict__["pages_access_level"] = pages_access_level __props__.__dict__["path"] = path __props__.__dict__["pipelines_enabled"] = pipelines_enabled __props__.__dict__["push_rules"] = push_rules __props__.__dict__["remove_source_branch_after_merge"] = remove_source_branch_after_merge __props__.__dict__["request_access_enabled"] = request_access_enabled __props__.__dict__["shared_runners_enabled"] = shared_runners_enabled __props__.__dict__["snippets_enabled"] = snippets_enabled __props__.__dict__["tags"] = tags __props__.__dict__["template_name"] = template_name __props__.__dict__["template_project_id"] = template_project_id __props__.__dict__["use_custom_template"] = use_custom_template __props__.__dict__["visibility_level"] = visibility_level __props__.__dict__["wiki_enabled"] = wiki_enabled __props__.__dict__["http_url_to_repo"] = None __props__.__dict__["path_with_namespace"] = None __props__.__dict__["runners_token"] = None __props__.__dict__["ssh_url_to_repo"] = None __props__.__dict__["web_url"] = None super(Project, __self__).__init__( 'gitlab:index/project:Project', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, approvals_before_merge: Optional[pulumi.Input[int]] = None, archived: Optional[pulumi.Input[bool]] = None, build_coverage_regex: Optional[pulumi.Input[str]] = None, ci_config_path: Optional[pulumi.Input[str]] = None, container_registry_enabled: Optional[pulumi.Input[bool]] = None, default_branch: Optional[pulumi.Input[str]] = None, description: Optional[pulumi.Input[str]] = None, group_with_project_templates_id: Optional[pulumi.Input[int]] = None, http_url_to_repo: Optional[pulumi.Input[str]] = None, import_url: Optional[pulumi.Input[str]] = None, initialize_with_readme: Optional[pulumi.Input[bool]] = None, issues_enabled: Optional[pulumi.Input[bool]] = None, lfs_enabled: Optional[pulumi.Input[bool]] = None, merge_method: Optional[pulumi.Input[str]] = None, merge_requests_enabled: Optional[pulumi.Input[bool]] = None, mirror: Optional[pulumi.Input[bool]] = None, mirror_overwrites_diverged_branches: Optional[pulumi.Input[bool]] = None, mirror_trigger_builds: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, namespace_id: Optional[pulumi.Input[int]] = None, only_allow_merge_if_all_discussions_are_resolved: Optional[pulumi.Input[bool]] = None, only_allow_merge_if_pipeline_succeeds: Optional[pulumi.Input[bool]] = None, only_mirror_protected_branches: Optional[pulumi.Input[bool]] = None, packages_enabled: Optional[pulumi.Input[bool]] = None, pages_access_level: Optional[pulumi.Input[str]] = None, path: Optional[pulumi.Input[str]] = None, path_with_namespace: Optional[pulumi.Input[str]] = None, pipelines_enabled: Optional[pulumi.Input[bool]] = None, push_rules: Optional[pulumi.Input[pulumi.InputType['ProjectPushRulesArgs']]] = None, remove_source_branch_after_merge: Optional[pulumi.Input[bool]] = None, request_access_enabled: Optional[pulumi.Input[bool]] = None, runners_token: Optional[pulumi.Input[str]] = None, shared_runners_enabled: Optional[pulumi.Input[bool]] = None, snippets_enabled: Optional[pulumi.Input[bool]] = None, ssh_url_to_repo: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, template_name: Optional[pulumi.Input[str]] = None, template_project_id: Optional[pulumi.Input[int]] = None, use_custom_template: Optional[pulumi.Input[bool]] = None, visibility_level: Optional[pulumi.Input[str]] = None, web_url: Optional[pulumi.Input[str]] = None, wiki_enabled: Optional[pulumi.Input[bool]] = None) -> 'Project': """ Get an existing Project 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[int] approvals_before_merge: Number of merge request approvals required for merging. Default is 0. :param pulumi.Input[bool] archived: Whether the project is in read-only mode (archived). Repositories can be archived/unarchived by toggling this parameter. :param pulumi.Input[str] build_coverage_regex: Test coverage parsing for the project. :param pulumi.Input[str] ci_config_path: Custom Path to CI config file. :param pulumi.Input[bool] container_registry_enabled: Enable container registry for the project. :param pulumi.Input[str] default_branch: The default branch for the project. :param pulumi.Input[str] description: A description of the project. :param pulumi.Input[int] group_with_project_templates_id: For group-level custom templates, specifies ID of group from which all the custom project templates are sourced. Leave empty for instance-level templates. Requires use_custom_template to be true (enterprise edition). :param pulumi.Input[str] http_url_to_repo: URL that can be provided to `git clone` to clone the repository via HTTP. :param pulumi.Input[str] import_url: Git URL to a repository to be imported. :param pulumi.Input[bool] initialize_with_readme: Create main branch with first commit containing a README.md file. :param pulumi.Input[bool] issues_enabled: Enable issue tracking for the project. :param pulumi.Input[bool] lfs_enabled: Enable LFS for the project. :param pulumi.Input[str] merge_method: Set to `ff` to create fast-forward merges Valid values are `merge`, `rebase_merge`, `ff` Repositories are created with `merge` by default :param pulumi.Input[bool] merge_requests_enabled: Enable merge requests for the project. :param pulumi.Input[bool] mirror: Enables pull mirroring in a project. Default is `false`. For further information on mirroring, consult the [gitlab documentation](https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#repository-mirroring). :param pulumi.Input[bool] mirror_overwrites_diverged_branches: Pull mirror overwrites diverged branches. :param pulumi.Input[bool] mirror_trigger_builds: Pull mirroring triggers builds. Default is `false`. :param pulumi.Input[str] name: The name of the project. :param pulumi.Input[int] namespace_id: The namespace (group or user) of the project. Defaults to your user. See `Group` for an example. :param pulumi.Input[bool] only_allow_merge_if_all_discussions_are_resolved: Set to true if you want allow merges only if all discussions are resolved. :param pulumi.Input[bool] only_allow_merge_if_pipeline_succeeds: Set to true if you want allow merges only if a pipeline succeeds. :param pulumi.Input[bool] only_mirror_protected_branches: Only mirror protected branches. :param pulumi.Input[bool] packages_enabled: Enable packages repository for the project. :param pulumi.Input[str] pages_access_level: Enable pages access control Valid values are `disabled`, `private`, `enabled`, `public`. `private` is the default. :param pulumi.Input[str] path: The path of the repository. :param pulumi.Input[str] path_with_namespace: The path of the repository with namespace. :param pulumi.Input[bool] pipelines_enabled: Enable pipelines for the project. :param pulumi.Input[pulumi.InputType['ProjectPushRulesArgs']] push_rules: Push rules for the project (documented below). :param pulumi.Input[bool] remove_source_branch_after_merge: Enable `Delete source branch` option by default for all new merge requests. :param pulumi.Input[bool] request_access_enabled: Allow users to request member access. :param pulumi.Input[str] runners_token: Registration token to use during runner setup. :param pulumi.Input[bool] shared_runners_enabled: Enable shared runners for this project. :param pulumi.Input[bool] snippets_enabled: Enable snippets for the project. :param pulumi.Input[str] ssh_url_to_repo: URL that can be provided to `git clone` to clone the repository via SSH. :param pulumi.Input[Sequence[pulumi.Input[str]]] tags: Tags (topics) of the project. :param pulumi.Input[str] template_name: When used without use_custom_template, name of a built-in project template. When used with use_custom_template, name of a custom project template. This option is mutually exclusive with `template_project_id`. :param pulumi.Input[int] template_project_id: When used with use_custom_template, project ID of a custom project template. This is preferable to using template_name since template_name may be ambiguous (enterprise edition). This option is mutually exclusive with `template_name`. :param pulumi.Input[bool] use_custom_template: Use either custom instance or group (with group_with_project_templates_id) project template (enterprise edition). :param pulumi.Input[str] visibility_level: Set to `public` to create a public project. Valid values are `private`, `internal`, `public`. Repositories are created as private by default. :param pulumi.Input[str] web_url: URL that can be used to find the project in a browser. :param pulumi.Input[bool] wiki_enabled: Enable wiki for the project. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _ProjectState.__new__(_ProjectState) __props__.__dict__["approvals_before_merge"] = approvals_before_merge __props__.__dict__["archived"] = archived __props__.__dict__["build_coverage_regex"] = build_coverage_regex __props__.__dict__["ci_config_path"] = ci_config_path __props__.__dict__["container_registry_enabled"] = container_registry_enabled __props__.__dict__["default_branch"] = default_branch __props__.__dict__["description"] = description __props__.__dict__["group_with_project_templates_id"] = group_with_project_templates_id __props__.__dict__["http_url_to_repo"] = http_url_to_repo __props__.__dict__["import_url"] = import_url __props__.__dict__["initialize_with_readme"] = initialize_with_readme __props__.__dict__["issues_enabled"] = issues_enabled __props__.__dict__["lfs_enabled"] = lfs_enabled __props__.__dict__["merge_method"] = merge_method __props__.__dict__["merge_requests_enabled"] = merge_requests_enabled __props__.__dict__["mirror"] = mirror __props__.__dict__["mirror_overwrites_diverged_branches"] = mirror_overwrites_diverged_branches __props__.__dict__["mirror_trigger_builds"] = mirror_trigger_builds __props__.__dict__["name"] = name __props__.__dict__["namespace_id"] = namespace_id __props__.__dict__["only_allow_merge_if_all_discussions_are_resolved"] = only_allow_merge_if_all_discussions_are_resolved __props__.__dict__["only_allow_merge_if_pipeline_succeeds"] = only_allow_merge_if_pipeline_succeeds __props__.__dict__["only_mirror_protected_branches"] = only_mirror_protected_branches __props__.__dict__["packages_enabled"] = packages_enabled __props__.__dict__["pages_access_level"] = pages_access_level __props__.__dict__["path"] = path __props__.__dict__["path_with_namespace"] = path_with_namespace __props__.__dict__["pipelines_enabled"] = pipelines_enabled __props__.__dict__["push_rules"] = push_rules __props__.__dict__["remove_source_branch_after_merge"] = remove_source_branch_after_merge __props__.__dict__["request_access_enabled"] = request_access_enabled __props__.__dict__["runners_token"] = runners_token __props__.__dict__["shared_runners_enabled"] = shared_runners_enabled __props__.__dict__["snippets_enabled"] = snippets_enabled __props__.__dict__["ssh_url_to_repo"] = ssh_url_to_repo __props__.__dict__["tags"] = tags __props__.__dict__["template_name"] = template_name __props__.__dict__["template_project_id"] = template_project_id __props__.__dict__["use_custom_template"] = use_custom_template __props__.__dict__["visibility_level"] = visibility_level __props__.__dict__["web_url"] = web_url __props__.__dict__["wiki_enabled"] = wiki_enabled return Project(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="approvalsBeforeMerge") def approvals_before_merge(self) -> pulumi.Output[Optional[int]]: """ Number of merge request approvals required for merging. Default is 0. """ return pulumi.get(self, "approvals_before_merge") @property @pulumi.getter def archived(self) -> pulumi.Output[Optional[bool]]: """ Whether the project is in read-only mode (archived). Repositories can be archived/unarchived by toggling this parameter. """ return pulumi.get(self, "archived") @property @pulumi.getter(name="buildCoverageRegex") def build_coverage_regex(self) -> pulumi.Output[Optional[str]]: """ Test coverage parsing for the project. """ return pulumi.get(self, "build_coverage_regex") @property @pulumi.getter(name="ciConfigPath") def ci_config_path(self) -> pulumi.Output[Optional[str]]: """ Custom Path to CI config file. """ return pulumi.get(self, "ci_config_path") @property @pulumi.getter(name="containerRegistryEnabled") def container_registry_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable container registry for the project. """ return pulumi.get(self, "container_registry_enabled") @property @pulumi.getter(name="defaultBranch") def default_branch(self) -> pulumi.Output[str]: """ The default branch for the project. """ return pulumi.get(self, "default_branch") @property @pulumi.getter def description(self) -> pulumi.Output[Optional[str]]: """ A description of the project. """ return pulumi.get(self, "description") @property @pulumi.getter(name="groupWithProjectTemplatesId") def group_with_project_templates_id(self) -> pulumi.Output[Optional[int]]: """ For group-level custom templates, specifies ID of group from which all the custom project templates are sourced. Leave empty for instance-level templates. Requires use_custom_template to be true (enterprise edition). """ return pulumi.get(self, "group_with_project_templates_id") @property @pulumi.getter(name="httpUrlToRepo") def http_url_to_repo(self) -> pulumi.Output[str]: """ URL that can be provided to `git clone` to clone the repository via HTTP. """ return pulumi.get(self, "http_url_to_repo") @property @pulumi.getter(name="importUrl") def import_url(self) -> pulumi.Output[Optional[str]]: """ Git URL to a repository to be imported. """ return pulumi.get(self, "import_url") @property @pulumi.getter(name="initializeWithReadme") def initialize_with_readme(self) -> pulumi.Output[Optional[bool]]: """ Create main branch with first commit containing a README.md file. """ return pulumi.get(self, "initialize_with_readme") @property @pulumi.getter(name="issuesEnabled") def issues_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable issue tracking for the project. """ return pulumi.get(self, "issues_enabled") @property @pulumi.getter(name="lfsEnabled") def lfs_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable LFS for the project. """ return pulumi.get(self, "lfs_enabled") @property @pulumi.getter(name="mergeMethod") def merge_method(self) -> pulumi.Output[Optional[str]]: """ Set to `ff` to create fast-forward merges Valid values are `merge`, `rebase_merge`, `ff` Repositories are created with `merge` by default """ return pulumi.get(self, "merge_method") @property @pulumi.getter(name="mergeRequestsEnabled") def merge_requests_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable merge requests for the project. """ return pulumi.get(self, "merge_requests_enabled") @property @pulumi.getter def mirror(self) -> pulumi.Output[Optional[bool]]: """ Enables pull mirroring in a project. Default is `false`. For further information on mirroring, consult the [gitlab documentation](https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#repository-mirroring). """ return pulumi.get(self, "mirror") @property @pulumi.getter(name="mirrorOverwritesDivergedBranches") def mirror_overwrites_diverged_branches(self) -> pulumi.Output[Optional[bool]]: """ Pull mirror overwrites diverged branches. """ return pulumi.get(self, "mirror_overwrites_diverged_branches") @property @pulumi.getter(name="mirrorTriggerBuilds") def mirror_trigger_builds(self) -> pulumi.Output[Optional[bool]]: """ Pull mirroring triggers builds. Default is `false`. """ return pulumi.get(self, "mirror_trigger_builds") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the project. """ return pulumi.get(self, "name") @property @pulumi.getter(name="namespaceId") def namespace_id(self) -> pulumi.Output[int]: """ The namespace (group or user) of the project. Defaults to your user. See `Group` for an example. """ return pulumi.get(self, "namespace_id") @property @pulumi.getter(name="onlyAllowMergeIfAllDiscussionsAreResolved") def only_allow_merge_if_all_discussions_are_resolved(self) -> pulumi.Output[Optional[bool]]: """ Set to true if you want allow merges only if all discussions are resolved. """ return pulumi.get(self, "only_allow_merge_if_all_discussions_are_resolved") @property @pulumi.getter(name="onlyAllowMergeIfPipelineSucceeds") def only_allow_merge_if_pipeline_succeeds(self) -> pulumi.Output[Optional[bool]]: """ Set to true if you want allow merges only if a pipeline succeeds. """ return pulumi.get(self, "only_allow_merge_if_pipeline_succeeds") @property @pulumi.getter(name="onlyMirrorProtectedBranches") def only_mirror_protected_branches(self) -> pulumi.Output[Optional[bool]]: """ Only mirror protected branches. """ return pulumi.get(self, "only_mirror_protected_branches") @property @pulumi.getter(name="packagesEnabled") def packages_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable packages repository for the project. """ return pulumi.get(self, "packages_enabled") @property @pulumi.getter(name="pagesAccessLevel") def pages_access_level(self) -> pulumi.Output[Optional[str]]: """ Enable pages access control Valid values are `disabled`, `private`, `enabled`, `public`. `private` is the default. """ return pulumi.get(self, "pages_access_level") @property @pulumi.getter def path(self) -> pulumi.Output[Optional[str]]: """ The path of the repository. """ return pulumi.get(self, "path") @property @pulumi.getter(name="pathWithNamespace") def path_with_namespace(self) -> pulumi.Output[str]: """ The path of the repository with namespace. """ return pulumi.get(self, "path_with_namespace") @property @pulumi.getter(name="pipelinesEnabled") def pipelines_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable pipelines for the project. """ return pulumi.get(self, "pipelines_enabled") @property @pulumi.getter(name="pushRules") def push_rules(self) -> pulumi.Output['outputs.ProjectPushRules']: """ Push rules for the project (documented below). """ return pulumi.get(self, "push_rules") @property @pulumi.getter(name="removeSourceBranchAfterMerge") def remove_source_branch_after_merge(self) -> pulumi.Output[Optional[bool]]: """ Enable `Delete source branch` option by default for all new merge requests. """ return pulumi.get(self, "remove_source_branch_after_merge") @property @pulumi.getter(name="requestAccessEnabled") def request_access_enabled(self) -> pulumi.Output[Optional[bool]]: """ Allow users to request member access. """ return pulumi.get(self, "request_access_enabled") @property @pulumi.getter(name="runnersToken") def runners_token(self) -> pulumi.Output[str]: """ Registration token to use during runner setup. """ return pulumi.get(self, "runners_token") @property @pulumi.getter(name="sharedRunnersEnabled") def shared_runners_enabled(self) -> pulumi.Output[bool]: """ Enable shared runners for this project. """ return pulumi.get(self, "shared_runners_enabled") @property @pulumi.getter(name="snippetsEnabled") def snippets_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable snippets for the project. """ return pulumi.get(self, "snippets_enabled") @property @pulumi.getter(name="sshUrlToRepo") def ssh_url_to_repo(self) -> pulumi.Output[str]: """ URL that can be provided to `git clone` to clone the repository via SSH. """ return pulumi.get(self, "ssh_url_to_repo") @property @pulumi.getter def tags(self) -> pulumi.Output[Optional[Sequence[str]]]: """ Tags (topics) of the project. """ return pulumi.get(self, "tags") @property @pulumi.getter(name="templateName") def template_name(self) -> pulumi.Output[Optional[str]]: """ When used without use_custom_template, name of a built-in project template. When used with use_custom_template, name of a custom project template. This option is mutually exclusive with `template_project_id`. """ return pulumi.get(self, "template_name") @property @pulumi.getter(name="templateProjectId") def template_project_id(self) -> pulumi.Output[Optional[int]]: """ When used with use_custom_template, project ID of a custom project template. This is preferable to using template_name since template_name may be ambiguous (enterprise edition). This option is mutually exclusive with `template_name`. """ return pulumi.get(self, "template_project_id") @property @pulumi.getter(name="useCustomTemplate") def use_custom_template(self) -> pulumi.Output[Optional[bool]]: """ Use either custom instance or group (with group_with_project_templates_id) project template (enterprise edition). """ return pulumi.get(self, "use_custom_template") @property @pulumi.getter(name="visibilityLevel") def visibility_level(self) -> pulumi.Output[Optional[str]]: """ Set to `public` to create a public project. Valid values are `private`, `internal`, `public`. Repositories are created as private by default. """ return pulumi.get(self, "visibility_level") @property @pulumi.getter(name="webUrl") def web_url(self) -> pulumi.Output[str]: """ URL that can be used to find the project in a browser. """ return pulumi.get(self, "web_url") @property @pulumi.getter(name="wikiEnabled") def wiki_enabled(self) -> pulumi.Output[Optional[bool]]: """ Enable wiki for the project. """ return pulumi.get(self, "wiki_enabled")

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Python

novautils/__init__.py

novasush/novautils

08ca6adf47cae4bf759ecd1cd3999b64807ed493

[ "MIT" ]

null

novautils/__init__.py

novasush/novautils

08ca6adf47cae4bf759ecd1cd3999b64807ed493

[ "MIT" ]

null

novautils/__init__.py

novasush/novautils

08ca6adf47cae4bf759ecd1cd3999b64807ed493

[ "MIT" ]

null

print("Importing novautils") print("Sample pip package imported successfully")

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py

Python

boto3_type_annotations_with_docs/boto3_type_annotations/elasticache/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

119

2018-12-01T18:20:57.000Z

2022-02-02T10:31:29.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/elasticache/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

15

2018-11-16T00:16:44.000Z

2021-11-13T03:44:18.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/elasticache/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

11

2019-05-06T05:26:51.000Z

2021-09-28T15:27:59.000Z

from typing import Optional from botocore.client import BaseClient from typing import Dict from botocore.paginate import Paginator from datetime import datetime from botocore.waiter import Waiter from typing import Union from typing import List class Client(BaseClient): def add_tags_to_resource(self, ResourceName: str, Tags: List) -> Dict: """ Adds up to 50 cost allocation tags to the named resource. A cost allocation tag is a key-value pair where the key and value are case-sensitive. You can use cost allocation tags to categorize and track your AWS costs. When you apply tags to your ElastiCache resources, AWS generates a cost allocation report as a comma-separated value (CSV) file with your usage and costs aggregated by your tags. You can apply tags that represent business categories (such as cost centers, application names, or owners) to organize your costs across multiple services. For more information, see `Using Cost Allocation Tags in Amazon ElastiCache <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Tagging.html>`__ in the *ElastiCache User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/AddTagsToResource>`_ **Request Syntax** :: response = client.add_tags_to_resource( ResourceName='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) **Response Syntax** :: { 'TagList': [ { 'Key': 'string', 'Value': 'string' }, ] } **Response Structure** - *(dict) --* Represents the output from the ``AddTagsToResource`` , ``ListTagsForResource`` , and ``RemoveTagsFromResource`` operations. - **TagList** *(list) --* A list of cost allocation tags as key-value pairs. - *(dict) --* A cost allocation Tag that can be added to an ElastiCache cluster or replication group. Tags are composed of a Key/Value pair. A tag with a null Value is permitted. - **Key** *(string) --* The key for the tag. May not be null. - **Value** *(string) --* The tag's value. May be null. :type ResourceName: string :param ResourceName: **[REQUIRED]** The Amazon Resource Name (ARN) of the resource to which the tags are to be added, for example ``arn:aws:elasticache:us-west-2:0123456789:cluster:myCluster`` or ``arn:aws:elasticache:us-west-2:0123456789:snapshot:mySnapshot`` . ElastiCache resources are *cluster* and *snapshot* . For more information about ARNs, see `Amazon Resource Names (ARNs) and AWS Service Namespaces <http://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html>`__ . :type Tags: list :param Tags: **[REQUIRED]** A list of cost allocation tags to be added to this resource. A tag is a key-value pair. A tag key must be accompanied by a tag value. - *(dict) --* A cost allocation Tag that can be added to an ElastiCache cluster or replication group. Tags are composed of a Key/Value pair. A tag with a null Value is permitted. - **Key** *(string) --* The key for the tag. May not be null. - **Value** *(string) --* The tag\'s value. May be null. :rtype: dict :returns: """ pass def authorize_cache_security_group_ingress(self, CacheSecurityGroupName: str, EC2SecurityGroupName: str, EC2SecurityGroupOwnerId: str) -> Dict: """ Allows network ingress to a cache security group. Applications using ElastiCache must be running on Amazon EC2, and Amazon EC2 security groups are used as the authorization mechanism. .. note:: You cannot authorize ingress from an Amazon EC2 security group in one region to an ElastiCache cluster in another region. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/AuthorizeCacheSecurityGroupIngress>`_ **Request Syntax** :: response = client.authorize_cache_security_group_ingress( CacheSecurityGroupName='string', EC2SecurityGroupName='string', EC2SecurityGroupOwnerId='string' ) **Response Syntax** :: { 'CacheSecurityGroup': { 'OwnerId': 'string', 'CacheSecurityGroupName': 'string', 'Description': 'string', 'EC2SecurityGroups': [ { 'Status': 'string', 'EC2SecurityGroupName': 'string', 'EC2SecurityGroupOwnerId': 'string' }, ] } } **Response Structure** - *(dict) --* - **CacheSecurityGroup** *(dict) --* Represents the output of one of the following operations: * ``AuthorizeCacheSecurityGroupIngress`` * ``CreateCacheSecurityGroup`` * ``RevokeCacheSecurityGroupIngress`` - **OwnerId** *(string) --* The AWS account ID of the cache security group owner. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Description** *(string) --* The description of the cache security group. - **EC2SecurityGroups** *(list) --* A list of Amazon EC2 security groups that are associated with this cache security group. - *(dict) --* Provides ownership and status information for an Amazon EC2 security group. - **Status** *(string) --* The status of the Amazon EC2 security group. - **EC2SecurityGroupName** *(string) --* The name of the Amazon EC2 security group. - **EC2SecurityGroupOwnerId** *(string) --* The AWS account ID of the Amazon EC2 security group owner. :type CacheSecurityGroupName: string :param CacheSecurityGroupName: **[REQUIRED]** The cache security group that allows network ingress. :type EC2SecurityGroupName: string :param EC2SecurityGroupName: **[REQUIRED]** The Amazon EC2 security group to be authorized for ingress to the cache security group. :type EC2SecurityGroupOwnerId: string :param EC2SecurityGroupOwnerId: **[REQUIRED]** The AWS account number of the Amazon EC2 security group owner. Note that this is not the same thing as an AWS access key ID - you must provide a valid AWS account number for this parameter. :rtype: dict :returns: """ pass def can_paginate(self, operation_name: str = None): """ Check if an operation can be paginated. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :return: ``True`` if the operation can be paginated, ``False`` otherwise. """ pass def copy_snapshot(self, SourceSnapshotName: str, TargetSnapshotName: str, TargetBucket: str = None) -> Dict: """ Makes a copy of an existing snapshot. .. note:: This operation is valid for Redis only. .. warning:: Users or groups that have permissions to use the ``CopySnapshot`` operation can create their own Amazon S3 buckets and copy snapshots to it. To control access to your snapshots, use an IAM policy to control who has the ability to use the ``CopySnapshot`` operation. For more information about using IAM to control the use of ElastiCache operations, see `Exporting Snapshots <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html>`__ and `Authentication & Access Control <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/IAM.html>`__ . You could receive the following error messages. **Error Messages** * **Error Message:** The S3 bucket %s is outside of the region. **Solution:** Create an Amazon S3 bucket in the same region as your snapshot. For more information, see `Step 1\: Create an Amazon S3 Bucket <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html#Snapshots.Exporting.CreateBucket>`__ in the ElastiCache User Guide. * **Error Message:** The S3 bucket %s does not exist. **Solution:** Create an Amazon S3 bucket in the same region as your snapshot. For more information, see `Step 1\: Create an Amazon S3 Bucket <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html#Snapshots.Exporting.CreateBucket>`__ in the ElastiCache User Guide. * **Error Message:** The S3 bucket %s is not owned by the authenticated user. **Solution:** Create an Amazon S3 bucket in the same region as your snapshot. For more information, see `Step 1\: Create an Amazon S3 Bucket <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html#Snapshots.Exporting.CreateBucket>`__ in the ElastiCache User Guide. * **Error Message:** The authenticated user does not have sufficient permissions to perform the desired activity. **Solution:** Contact your system administrator to get the needed permissions. * **Error Message:** The S3 bucket %s already contains an object with key %s. **Solution:** Give the ``TargetSnapshotName`` a new and unique value. If exporting a snapshot, you could alternatively create a new Amazon S3 bucket and use this same value for ``TargetSnapshotName`` . * **Error Message:** ElastiCache has not been granted READ permissions %s on the S3 Bucket. **Solution:** Add List and Read permissions on the bucket. For more information, see `Step 2\: Grant ElastiCache Access to Your Amazon S3 Bucket <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html#Snapshots.Exporting.GrantAccess>`__ in the ElastiCache User Guide. * **Error Message:** ElastiCache has not been granted WRITE permissions %s on the S3 Bucket. **Solution:** Add Upload/Delete permissions on the bucket. For more information, see `Step 2\: Grant ElastiCache Access to Your Amazon S3 Bucket <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html#Snapshots.Exporting.GrantAccess>`__ in the ElastiCache User Guide. * **Error Message:** ElastiCache has not been granted READ_ACP permissions %s on the S3 Bucket. **Solution:** Add View Permissions on the bucket. For more information, see `Step 2\: Grant ElastiCache Access to Your Amazon S3 Bucket <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html#Snapshots.Exporting.GrantAccess>`__ in the ElastiCache User Guide. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/CopySnapshot>`_ **Request Syntax** :: response = client.copy_snapshot( SourceSnapshotName='string', TargetSnapshotName='string', TargetBucket='string' ) **Response Syntax** :: { 'Snapshot': { 'SnapshotName': 'string', 'ReplicationGroupId': 'string', 'ReplicationGroupDescription': 'string', 'CacheClusterId': 'string', 'SnapshotStatus': 'string', 'SnapshotSource': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'TopicArn': 'string', 'Port': 123, 'CacheParameterGroupName': 'string', 'CacheSubnetGroupName': 'string', 'VpcId': 'string', 'AutoMinorVersionUpgrade': True|False, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'NumNodeGroups': 123, 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'NodeSnapshots': [ { 'CacheClusterId': 'string', 'NodeGroupId': 'string', 'CacheNodeId': 'string', 'NodeGroupConfiguration': { 'NodeGroupId': 'string', 'Slots': 'string', 'ReplicaCount': 123, 'PrimaryAvailabilityZone': 'string', 'ReplicaAvailabilityZones': [ 'string', ] }, 'CacheSize': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'SnapshotCreateTime': datetime(2015, 1, 1) }, ] } } **Response Structure** - *(dict) --* - **Snapshot** *(dict) --* Represents a copy of an entire Redis cluster as of the time when the snapshot was taken. - **SnapshotName** *(string) --* The name of a snapshot. For an automatic snapshot, the name is system-generated. For a manual snapshot, this is the user-provided name. - **ReplicationGroupId** *(string) --* The unique identifier of the source replication group. - **ReplicationGroupDescription** *(string) --* A description of the source replication group. - **CacheClusterId** *(string) --* The user-supplied identifier of the source cluster. - **SnapshotStatus** *(string) --* The status of the snapshot. Valid values: ``creating`` | ``available`` | ``restoring`` | ``copying`` | ``deleting`` . - **SnapshotSource** *(string) --* Indicates whether the snapshot is from an automatic backup (``automated`` ) or was created manually (``manual`` ). - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the source cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) used by the source cluster. - **EngineVersion** *(string) --* The version of the cache engine version that is used by the source cluster. - **NumCacheNodes** *(integer) --* The number of cache nodes in the source cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the source cluster is located. - **CacheClusterCreateTime** *(datetime) --* The date and time when the source cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **TopicArn** *(string) --* The Amazon Resource Name (ARN) for the topic used by the source cluster for publishing notifications. - **Port** *(integer) --* The port number used by each cache nodes in the source cluster. - **CacheParameterGroupName** *(string) --* The cache parameter group that is associated with the source cluster. - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the source cluster. - **VpcId** *(string) --* The Amazon Virtual Private Cloud identifier (VPC ID) of the cache subnet group for the source cluster. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SnapshotRetentionLimit** *(integer) --* For an automatic snapshot, the number of days for which ElastiCache retains the snapshot before deleting it. For manual snapshots, this field reflects the ``SnapshotRetentionLimit`` for the source cluster when the snapshot was created. This field is otherwise ignored: Manual snapshots do not expire, and can only be deleted using the ``DeleteSnapshot`` operation. **Important** If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range during which ElastiCache takes daily snapshots of the source cluster. - **NumNodeGroups** *(integer) --* The number of node groups (shards) in this snapshot. When restoring from a snapshot, the number of node groups (shards) in the snapshot and in the restored replication group must be the same. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for the source Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **NodeSnapshots** *(list) --* A list of the cache nodes in the source cluster. - *(dict) --* Represents an individual cache node in a snapshot of a cluster. - **CacheClusterId** *(string) --* A unique identifier for the source cluster. - **NodeGroupId** *(string) --* A unique identifier for the source node group (shard). - **CacheNodeId** *(string) --* The cache node identifier for the node in the source cluster. - **NodeGroupConfiguration** *(dict) --* The configuration for the source node group (shard). - **NodeGroupId** *(string) --* The 4-digit id for the node group these configuration values apply to. - **Slots** *(string) --* A string that specifies the keyspace for a particular node group. Keyspaces range from 0 to 16,383. The string is in the format ``startkey-endkey`` . Example: ``"0-3999"`` - **ReplicaCount** *(integer) --* The number of read replica nodes in this node group (shard). - **PrimaryAvailabilityZone** *(string) --* The Availability Zone where the primary node of this node group (shard) is launched. - **ReplicaAvailabilityZones** *(list) --* A list of Availability Zones to be used for the read replicas. The number of Availability Zones in this list must match the value of ``ReplicaCount`` or ``ReplicasPerNodeGroup`` if not specified. - *(string) --* - **CacheSize** *(string) --* The size of the cache on the source cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created in the source cluster. - **SnapshotCreateTime** *(datetime) --* The date and time when the source node's metadata and cache data set was obtained for the snapshot. :type SourceSnapshotName: string :param SourceSnapshotName: **[REQUIRED]** The name of an existing snapshot from which to make a copy. :type TargetSnapshotName: string :param TargetSnapshotName: **[REQUIRED]** A name for the snapshot copy. ElastiCache does not permit overwriting a snapshot, therefore this name must be unique within its context - ElastiCache or an Amazon S3 bucket if exporting. :type TargetBucket: string :param TargetBucket: The Amazon S3 bucket to which the snapshot is exported. This parameter is used only when exporting a snapshot for external access. When using this parameter to export a snapshot, be sure Amazon ElastiCache has the needed permissions to this S3 bucket. For more information, see `Step 2\: Grant ElastiCache Access to Your Amazon S3 Bucket <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html#Snapshots.Exporting.GrantAccess>`__ in the *Amazon ElastiCache User Guide* . For more information, see `Exporting a Snapshot <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Snapshots.Exporting.html>`__ in the *Amazon ElastiCache User Guide* . :rtype: dict :returns: """ pass def create_cache_cluster(self, CacheClusterId: str, ReplicationGroupId: str = None, AZMode: str = None, PreferredAvailabilityZone: str = None, PreferredAvailabilityZones: List = None, NumCacheNodes: int = None, CacheNodeType: str = None, Engine: str = None, EngineVersion: str = None, CacheParameterGroupName: str = None, CacheSubnetGroupName: str = None, CacheSecurityGroupNames: List = None, SecurityGroupIds: List = None, Tags: List = None, SnapshotArns: List = None, SnapshotName: str = None, PreferredMaintenanceWindow: str = None, Port: int = None, NotificationTopicArn: str = None, AutoMinorVersionUpgrade: bool = None, SnapshotRetentionLimit: int = None, SnapshotWindow: str = None, AuthToken: str = None) -> Dict: """ Creates a cluster. All nodes in the cluster run the same protocol-compliant cache engine software, either Memcached or Redis. This operation is not supported for Redis (cluster mode enabled) clusters. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/CreateCacheCluster>`_ **Request Syntax** :: response = client.create_cache_cluster( CacheClusterId='string', ReplicationGroupId='string', AZMode='single-az'|'cross-az', PreferredAvailabilityZone='string', PreferredAvailabilityZones=[ 'string', ], NumCacheNodes=123, CacheNodeType='string', Engine='string', EngineVersion='string', CacheParameterGroupName='string', CacheSubnetGroupName='string', CacheSecurityGroupNames=[ 'string', ], SecurityGroupIds=[ 'string', ], Tags=[ { 'Key': 'string', 'Value': 'string' }, ], SnapshotArns=[ 'string', ], SnapshotName='string', PreferredMaintenanceWindow='string', Port=123, NotificationTopicArn='string', AutoMinorVersionUpgrade=True|False, SnapshotRetentionLimit=123, SnapshotWindow='string', AuthToken='string' ) **Response Syntax** :: { 'CacheCluster': { 'CacheClusterId': 'string', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'ClientDownloadLandingPage': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'CacheClusterStatus': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'PendingModifiedValues': { 'NumCacheNodes': 123, 'CacheNodeIdsToRemove': [ 'string', ], 'EngineVersion': 'string', 'CacheNodeType': 'string' }, 'NotificationConfiguration': { 'TopicArn': 'string', 'TopicStatus': 'string' }, 'CacheSecurityGroups': [ { 'CacheSecurityGroupName': 'string', 'Status': 'string' }, ], 'CacheParameterGroup': { 'CacheParameterGroupName': 'string', 'ParameterApplyStatus': 'string', 'CacheNodeIdsToReboot': [ 'string', ] }, 'CacheSubnetGroupName': 'string', 'CacheNodes': [ { 'CacheNodeId': 'string', 'CacheNodeStatus': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'Endpoint': { 'Address': 'string', 'Port': 123 }, 'ParameterGroupStatus': 'string', 'SourceCacheNodeId': 'string', 'CustomerAvailabilityZone': 'string' }, ], 'AutoMinorVersionUpgrade': True|False, 'SecurityGroups': [ { 'SecurityGroupId': 'string', 'Status': 'string' }, ], 'ReplicationGroupId': 'string', 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **CacheCluster** *(dict) --* Contains all of the attributes of a specific cluster. - **CacheClusterId** *(string) --* The user-supplied identifier of the cluster. This identifier is a unique key that identifies a cluster. - **ConfigurationEndpoint** *(dict) --* Represents a Memcached cluster endpoint which, if Automatic Discovery is enabled on the cluster, can be used by an application to connect to any node in the cluster. The configuration endpoint will always have ``.cfg`` in it. Example: ``mem-3.9dvc4r.cfg.usw2.cache.amazonaws.com:11211`` - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ClientDownloadLandingPage** *(string) --* The URL of the web page where you can download the latest ElastiCache client library. - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) to be used for this cluster. - **EngineVersion** *(string) --* The version of the cache engine that is used in this cluster. - **CacheClusterStatus** *(string) --* The current state of this cluster, one of the following values: ``available`` , ``creating`` , ``deleted`` , ``deleting`` , ``incompatible-network`` , ``modifying`` , ``rebooting cluster nodes`` , ``restore-failed`` , or ``snapshotting`` . - **NumCacheNodes** *(integer) --* The number of cache nodes in the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the cluster is located or "Multiple" if the cache nodes are located in different Availability Zones. - **CacheClusterCreateTime** *(datetime) --* The date and time when the cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **PendingModifiedValues** *(dict) --* A group of settings that are applied to the cluster in the future, or that are currently being applied. - **NumCacheNodes** *(integer) --* The new number of cache nodes for the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **CacheNodeIdsToRemove** *(list) --* A list of cache node IDs that are being removed (or will be removed) from the cluster. A node ID is a 4-digit numeric identifier (0001, 0002, etc.). - *(string) --* - **EngineVersion** *(string) --* The new cache engine version that the cluster runs. - **CacheNodeType** *(string) --* The cache node type that this cluster or replication group is scaled to. - **NotificationConfiguration** *(dict) --* Describes a notification topic and its status. Notification topics are used for publishing ElastiCache events to subscribers using Amazon Simple Notification Service (SNS). - **TopicArn** *(string) --* The Amazon Resource Name (ARN) that identifies the topic. - **TopicStatus** *(string) --* The current state of the topic. - **CacheSecurityGroups** *(list) --* A list of cache security group elements, composed of name and status sub-elements. - *(dict) --* Represents a cluster's status within a particular cache security group. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Status** *(string) --* The membership status in the cache security group. The status changes when a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **CacheParameterGroup** *(dict) --* Status of the cache parameter group. - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. - **ParameterApplyStatus** *(string) --* The status of parameter updates. - **CacheNodeIdsToReboot** *(list) --* A list of the cache node IDs which need to be rebooted for parameter changes to be applied. A node ID is a numeric identifier (0001, 0002, etc.). - *(string) --* - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the cluster. - **CacheNodes** *(list) --* A list of cache nodes that are members of the cluster. - *(dict) --* Represents an individual cache node within a cluster. Each cache node runs its own instance of the cluster's protocol-compliant caching software - either Memcached or Redis. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **CacheNodeId** *(string) --* The cache node identifier. A node ID is a numeric identifier (0001, 0002, etc.). The combination of cluster ID and node ID uniquely identifies every cache node used in a customer's AWS account. - **CacheNodeStatus** *(string) --* The current state of this cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created. - **Endpoint** *(dict) --* The hostname for connecting to this cache node. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ParameterGroupStatus** *(string) --* The status of the parameter group applied to this cache node. - **SourceCacheNodeId** *(string) --* The ID of the primary node to which this read replica node is synchronized. If this field is empty, this node is not associated with a primary cluster. - **CustomerAvailabilityZone** *(string) --* The Availability Zone where this node was created and now resides. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SecurityGroups** *(list) --* A list of VPC Security Groups associated with the cluster. - *(dict) --* Represents a single cache security group and its status. - **SecurityGroupId** *(string) --* The identifier of the cache security group. - **Status** *(string) --* The status of the cache security group membership. The status changes whenever a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **ReplicationGroupId** *(string) --* The replication group to which this cluster belongs. If this field is empty, the cluster is not associated with any replication group. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your cluster. Example: ``05:00-09:00`` - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable at-rest encryption on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type CacheClusterId: string :param CacheClusterId: **[REQUIRED]** The node group (shard) identifier. This parameter is stored as a lowercase string. **Constraints:** * A name must contain from 1 to 20 alphanumeric characters or hyphens. * The first character must be a letter. * A name cannot end with a hyphen or contain two consecutive hyphens. :type ReplicationGroupId: string :param ReplicationGroupId: The ID of the replication group to which this cluster should belong. If this parameter is specified, the cluster is added to the specified replication group as a read replica; otherwise, the cluster is a standalone primary that is not part of any replication group. If the specified replication group is Multi-AZ enabled and the Availability Zone is not specified, the cluster is created in Availability Zones that provide the best spread of read replicas across Availability Zones. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . :type AZMode: string :param AZMode: Specifies whether the nodes in this Memcached cluster are created in a single Availability Zone or created across multiple Availability Zones in the cluster\'s region. This parameter is only supported for Memcached clusters. If the ``AZMode`` and ``PreferredAvailabilityZones`` are not specified, ElastiCache assumes ``single-az`` mode. :type PreferredAvailabilityZone: string :param PreferredAvailabilityZone: The EC2 Availability Zone in which the cluster is created. All nodes belonging to this Memcached cluster are placed in the preferred Availability Zone. If you want to create your nodes across multiple Availability Zones, use ``PreferredAvailabilityZones`` . Default: System chosen Availability Zone. :type PreferredAvailabilityZones: list :param PreferredAvailabilityZones: A list of the Availability Zones in which cache nodes are created. The order of the zones in the list is not important. This option is only supported on Memcached. .. note:: If you are creating your cluster in an Amazon VPC (recommended) you can only locate nodes in Availability Zones that are associated with the subnets in the selected subnet group. The number of Availability Zones listed must equal the value of ``NumCacheNodes`` . If you want all the nodes in the same Availability Zone, use ``PreferredAvailabilityZone`` instead, or repeat the Availability Zone multiple times in the list. Default: System chosen Availability Zones. - *(string) --* :type NumCacheNodes: integer :param NumCacheNodes: The initial number of cache nodes that the cluster has. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. If you need more than 20 nodes for your Memcached cluster, please fill out the ElastiCache Limit Increase Request form at `http\://aws.amazon.com/contact-us/elasticache-node-limit-request/ <http://aws.amazon.com/contact-us/elasticache-node-limit-request/>`__ . :type CacheNodeType: string :param CacheNodeType: The compute and memory capacity of the nodes in the node group (shard). The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ :type Engine: string :param Engine: The name of the cache engine to be used for this cluster. Valid values for this parameter are: ``memcached`` | ``redis`` :type EngineVersion: string :param EngineVersion: The version number of the cache engine to be used for this cluster. To view the supported cache engine versions, use the DescribeCacheEngineVersions operation. **Important:** You can upgrade to a newer engine version (see `Selecting a Cache Engine and Version <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/SelectEngine.html#VersionManagement>`__ ), but you cannot downgrade to an earlier engine version. If you want to use an earlier engine version, you must delete the existing cluster or replication group and create it anew with the earlier engine version. :type CacheParameterGroupName: string :param CacheParameterGroupName: The name of the parameter group to associate with this cluster. If this argument is omitted, the default parameter group for the specified engine is used. You cannot use any parameter group which has ``cluster-enabled=\'yes\'`` when creating a cluster. :type CacheSubnetGroupName: string :param CacheSubnetGroupName: The name of the subnet group to be used for the cluster. Use this parameter only when you are creating a cluster in an Amazon Virtual Private Cloud (Amazon VPC). .. warning:: If you\'re going to launch your cluster in an Amazon VPC, you need to create a subnet group before you start creating a cluster. For more information, see `Subnets and Subnet Groups <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/SubnetGroups.html>`__ . :type CacheSecurityGroupNames: list :param CacheSecurityGroupNames: A list of security group names to associate with this cluster. Use this parameter only when you are creating a cluster outside of an Amazon Virtual Private Cloud (Amazon VPC). - *(string) --* :type SecurityGroupIds: list :param SecurityGroupIds: One or more VPC security groups associated with the cluster. Use this parameter only when you are creating a cluster in an Amazon Virtual Private Cloud (Amazon VPC). - *(string) --* :type Tags: list :param Tags: A list of cost allocation tags to be added to this resource. - *(dict) --* A cost allocation Tag that can be added to an ElastiCache cluster or replication group. Tags are composed of a Key/Value pair. A tag with a null Value is permitted. - **Key** *(string) --* The key for the tag. May not be null. - **Value** *(string) --* The tag\'s value. May be null. :type SnapshotArns: list :param SnapshotArns: A single-element string list containing an Amazon Resource Name (ARN) that uniquely identifies a Redis RDB snapshot file stored in Amazon S3. The snapshot file is used to populate the node group (shard). The Amazon S3 object name in the ARN cannot contain any commas. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . Example of an Amazon S3 ARN: ``arn:aws:s3:::my_bucket/snapshot1.rdb`` - *(string) --* :type SnapshotName: string :param SnapshotName: The name of a Redis snapshot from which to restore data into the new node group (shard). The snapshot status changes to ``restoring`` while the new node group (shard) is being created. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . :type PreferredMaintenanceWindow: string :param PreferredMaintenanceWindow: Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` :type Port: integer :param Port: The port number on which each of the cache nodes accepts connections. :type NotificationTopicArn: string :param NotificationTopicArn: The Amazon Resource Name (ARN) of the Amazon Simple Notification Service (SNS) topic to which notifications are sent. .. note:: The Amazon SNS topic owner must be the same as the cluster owner. :type AutoMinorVersionUpgrade: boolean :param AutoMinorVersionUpgrade: This parameter is currently disabled. :type SnapshotRetentionLimit: integer :param SnapshotRetentionLimit: The number of days for which ElastiCache retains automatic snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot taken today is retained for 5 days before being deleted. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . Default: 0 (i.e., automatic backups are disabled for this cache cluster). :type SnapshotWindow: string :param SnapshotWindow: The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . :type AuthToken: string :param AuthToken: **Reserved parameter.** The password used to access a password protected server. Password constraints: * Must be only printable ASCII characters. * Must be at least 16 characters and no more than 128 characters in length. * Cannot contain any of the following characters: \'/\', \'\"\', or \'@\'. For more information, see `AUTH password <http://redis.io/commands/AUTH>`__ at http://redis.io/commands/AUTH. :rtype: dict :returns: """ pass def create_cache_parameter_group(self, CacheParameterGroupName: str, CacheParameterGroupFamily: str, Description: str) -> Dict: """ Creates a new Amazon ElastiCache cache parameter group. An ElastiCache cache parameter group is a collection of parameters and their values that are applied to all of the nodes in any cluster or replication group using the CacheParameterGroup. A newly created CacheParameterGroup is an exact duplicate of the default parameter group for the CacheParameterGroupFamily. To customize the newly created CacheParameterGroup you can change the values of specific parameters. For more information, see: * `ModifyCacheParameterGroup <http://docs.aws.amazon.com/AmazonElastiCache/latest/APIReference/API_ModifyCacheParameterGroup.html>`__ in the ElastiCache API Reference. * `Parameters and Parameter Groups <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.html>`__ in the ElastiCache User Guide. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/CreateCacheParameterGroup>`_ **Request Syntax** :: response = client.create_cache_parameter_group( CacheParameterGroupName='string', CacheParameterGroupFamily='string', Description='string' ) **Response Syntax** :: { 'CacheParameterGroup': { 'CacheParameterGroupName': 'string', 'CacheParameterGroupFamily': 'string', 'Description': 'string' } } **Response Structure** - *(dict) --* - **CacheParameterGroup** *(dict) --* Represents the output of a ``CreateCacheParameterGroup`` operation. - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. - **CacheParameterGroupFamily** *(string) --* The name of the cache parameter group family that this cache parameter group is compatible with. Valid values are: ``memcached1.4`` | ``redis2.6`` | ``redis2.8`` | ``redis3.2`` | ``redis4.0`` - **Description** *(string) --* The description for this cache parameter group. :type CacheParameterGroupName: string :param CacheParameterGroupName: **[REQUIRED]** A user-specified name for the cache parameter group. :type CacheParameterGroupFamily: string :param CacheParameterGroupFamily: **[REQUIRED]** The name of the cache parameter group family that the cache parameter group can be used with. Valid values are: ``memcached1.4`` | ``redis2.6`` | ``redis2.8`` | ``redis3.2`` | ``redis4.0`` :type Description: string :param Description: **[REQUIRED]** A user-specified description for the cache parameter group. :rtype: dict :returns: """ pass def create_cache_security_group(self, CacheSecurityGroupName: str, Description: str) -> Dict: """ Creates a new cache security group. Use a cache security group to control access to one or more clusters. Cache security groups are only used when you are creating a cluster outside of an Amazon Virtual Private Cloud (Amazon VPC). If you are creating a cluster inside of a VPC, use a cache subnet group instead. For more information, see `CreateCacheSubnetGroup <http://docs.aws.amazon.com/AmazonElastiCache/latest/APIReference/API_CreateCacheSubnetGroup.html>`__ . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/CreateCacheSecurityGroup>`_ **Request Syntax** :: response = client.create_cache_security_group( CacheSecurityGroupName='string', Description='string' ) **Response Syntax** :: { 'CacheSecurityGroup': { 'OwnerId': 'string', 'CacheSecurityGroupName': 'string', 'Description': 'string', 'EC2SecurityGroups': [ { 'Status': 'string', 'EC2SecurityGroupName': 'string', 'EC2SecurityGroupOwnerId': 'string' }, ] } } **Response Structure** - *(dict) --* - **CacheSecurityGroup** *(dict) --* Represents the output of one of the following operations: * ``AuthorizeCacheSecurityGroupIngress`` * ``CreateCacheSecurityGroup`` * ``RevokeCacheSecurityGroupIngress`` - **OwnerId** *(string) --* The AWS account ID of the cache security group owner. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Description** *(string) --* The description of the cache security group. - **EC2SecurityGroups** *(list) --* A list of Amazon EC2 security groups that are associated with this cache security group. - *(dict) --* Provides ownership and status information for an Amazon EC2 security group. - **Status** *(string) --* The status of the Amazon EC2 security group. - **EC2SecurityGroupName** *(string) --* The name of the Amazon EC2 security group. - **EC2SecurityGroupOwnerId** *(string) --* The AWS account ID of the Amazon EC2 security group owner. :type CacheSecurityGroupName: string :param CacheSecurityGroupName: **[REQUIRED]** A name for the cache security group. This value is stored as a lowercase string. Constraints: Must contain no more than 255 alphanumeric characters. Cannot be the word \"Default\". Example: ``mysecuritygroup`` :type Description: string :param Description: **[REQUIRED]** A description for the cache security group. :rtype: dict :returns: """ pass def create_cache_subnet_group(self, CacheSubnetGroupName: str, CacheSubnetGroupDescription: str, SubnetIds: List) -> Dict: """ Creates a new cache subnet group. Use this parameter only when you are creating a cluster in an Amazon Virtual Private Cloud (Amazon VPC). See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/CreateCacheSubnetGroup>`_ **Request Syntax** :: response = client.create_cache_subnet_group( CacheSubnetGroupName='string', CacheSubnetGroupDescription='string', SubnetIds=[ 'string', ] ) **Response Syntax** :: { 'CacheSubnetGroup': { 'CacheSubnetGroupName': 'string', 'CacheSubnetGroupDescription': 'string', 'VpcId': 'string', 'Subnets': [ { 'SubnetIdentifier': 'string', 'SubnetAvailabilityZone': { 'Name': 'string' } }, ] } } **Response Structure** - *(dict) --* - **CacheSubnetGroup** *(dict) --* Represents the output of one of the following operations: * ``CreateCacheSubnetGroup`` * ``ModifyCacheSubnetGroup`` - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group. - **CacheSubnetGroupDescription** *(string) --* The description of the cache subnet group. - **VpcId** *(string) --* The Amazon Virtual Private Cloud identifier (VPC ID) of the cache subnet group. - **Subnets** *(list) --* A list of subnets associated with the cache subnet group. - *(dict) --* Represents the subnet associated with a cluster. This parameter refers to subnets defined in Amazon Virtual Private Cloud (Amazon VPC) and used with ElastiCache. - **SubnetIdentifier** *(string) --* The unique identifier for the subnet. - **SubnetAvailabilityZone** *(dict) --* The Availability Zone associated with the subnet. - **Name** *(string) --* The name of the Availability Zone. :type CacheSubnetGroupName: string :param CacheSubnetGroupName: **[REQUIRED]** A name for the cache subnet group. This value is stored as a lowercase string. Constraints: Must contain no more than 255 alphanumeric characters or hyphens. Example: ``mysubnetgroup`` :type CacheSubnetGroupDescription: string :param CacheSubnetGroupDescription: **[REQUIRED]** A description for the cache subnet group. :type SubnetIds: list :param SubnetIds: **[REQUIRED]** A list of VPC subnet IDs for the cache subnet group. - *(string) --* :rtype: dict :returns: """ pass def create_replication_group(self, ReplicationGroupId: str, ReplicationGroupDescription: str, PrimaryClusterId: str = None, AutomaticFailoverEnabled: bool = None, NumCacheClusters: int = None, PreferredCacheClusterAZs: List = None, NumNodeGroups: int = None, ReplicasPerNodeGroup: int = None, NodeGroupConfiguration: List = None, CacheNodeType: str = None, Engine: str = None, EngineVersion: str = None, CacheParameterGroupName: str = None, CacheSubnetGroupName: str = None, CacheSecurityGroupNames: List = None, SecurityGroupIds: List = None, Tags: List = None, SnapshotArns: List = None, SnapshotName: str = None, PreferredMaintenanceWindow: str = None, Port: int = None, NotificationTopicArn: str = None, AutoMinorVersionUpgrade: bool = None, SnapshotRetentionLimit: int = None, SnapshotWindow: str = None, AuthToken: str = None, TransitEncryptionEnabled: bool = None, AtRestEncryptionEnabled: bool = None) -> Dict: """ Creates a Redis (cluster mode disabled) or a Redis (cluster mode enabled) replication group. A Redis (cluster mode disabled) replication group is a collection of clusters, where one of the clusters is a read/write primary and the others are read-only replicas. Writes to the primary are asynchronously propagated to the replicas. A Redis (cluster mode enabled) replication group is a collection of 1 to 15 node groups (shards). Each node group (shard) has one read/write primary node and up to 5 read-only replica nodes. Writes to the primary are asynchronously propagated to the replicas. Redis (cluster mode enabled) replication groups partition the data across node groups (shards). When a Redis (cluster mode disabled) replication group has been successfully created, you can add one or more read replicas to it, up to a total of 5 read replicas. You cannot alter a Redis (cluster mode enabled) replication group after it has been created. However, if you need to increase or decrease the number of node groups (console: shards), you can avail yourself of ElastiCache for Redis' enhanced backup and restore. For more information, see `Restoring From a Backup with Cluster Resizing <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/backups-restoring.html>`__ in the *ElastiCache User Guide* . .. note:: This operation is valid for Redis only. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/CreateReplicationGroup>`_ **Request Syntax** :: response = client.create_replication_group( ReplicationGroupId='string', ReplicationGroupDescription='string', PrimaryClusterId='string', AutomaticFailoverEnabled=True|False, NumCacheClusters=123, PreferredCacheClusterAZs=[ 'string', ], NumNodeGroups=123, ReplicasPerNodeGroup=123, NodeGroupConfiguration=[ { 'NodeGroupId': 'string', 'Slots': 'string', 'ReplicaCount': 123, 'PrimaryAvailabilityZone': 'string', 'ReplicaAvailabilityZones': [ 'string', ] }, ], CacheNodeType='string', Engine='string', EngineVersion='string', CacheParameterGroupName='string', CacheSubnetGroupName='string', CacheSecurityGroupNames=[ 'string', ], SecurityGroupIds=[ 'string', ], Tags=[ { 'Key': 'string', 'Value': 'string' }, ], SnapshotArns=[ 'string', ], SnapshotName='string', PreferredMaintenanceWindow='string', Port=123, NotificationTopicArn='string', AutoMinorVersionUpgrade=True|False, SnapshotRetentionLimit=123, SnapshotWindow='string', AuthToken='string', TransitEncryptionEnabled=True|False, AtRestEncryptionEnabled=True|False ) **Response Syntax** :: { 'ReplicationGroup': { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **ReplicationGroup** *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: **[REQUIRED]** The replication group identifier. This parameter is stored as a lowercase string. Constraints: * A name must contain from 1 to 20 alphanumeric characters or hyphens. * The first character must be a letter. * A name cannot end with a hyphen or contain two consecutive hyphens. :type ReplicationGroupDescription: string :param ReplicationGroupDescription: **[REQUIRED]** A user-created description for the replication group. :type PrimaryClusterId: string :param PrimaryClusterId: The identifier of the cluster that serves as the primary for this replication group. This cluster must already exist and have a status of ``available`` . This parameter is not required if ``NumCacheClusters`` , ``NumNodeGroups`` , or ``ReplicasPerNodeGroup`` is specified. :type AutomaticFailoverEnabled: boolean :param AutomaticFailoverEnabled: Specifies whether a read-only replica is automatically promoted to read/write primary if the existing primary fails. If ``true`` , Multi-AZ is enabled for this replication group. If ``false`` , Multi-AZ is disabled for this replication group. ``AutomaticFailoverEnabled`` must be enabled for Redis (cluster mode enabled) replication groups. Default: false Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. :type NumCacheClusters: integer :param NumCacheClusters: The number of clusters this replication group initially has. This parameter is not used if there is more than one node group (shard). You should use ``ReplicasPerNodeGroup`` instead. If ``AutomaticFailoverEnabled`` is ``true`` , the value of this parameter must be at least 2. If ``AutomaticFailoverEnabled`` is ``false`` you can omit this parameter (it will default to 1), or you can explicitly set it to a value between 2 and 6. The maximum permitted value for ``NumCacheClusters`` is 6 (1 primary plus 5 replicas). :type PreferredCacheClusterAZs: list :param PreferredCacheClusterAZs: A list of EC2 Availability Zones in which the replication group\'s clusters are created. The order of the Availability Zones in the list is the order in which clusters are allocated. The primary cluster is created in the first AZ in the list. This parameter is not used if there is more than one node group (shard). You should use ``NodeGroupConfiguration`` instead. .. note:: If you are creating your replication group in an Amazon VPC (recommended), you can only locate clusters in Availability Zones associated with the subnets in the selected subnet group. The number of Availability Zones listed must equal the value of ``NumCacheClusters`` . Default: system chosen Availability Zones. - *(string) --* :type NumNodeGroups: integer :param NumNodeGroups: An optional parameter that specifies the number of node groups (shards) for this Redis (cluster mode enabled) replication group. For Redis (cluster mode disabled) either omit this parameter or set it to 1. Default: 1 :type ReplicasPerNodeGroup: integer :param ReplicasPerNodeGroup: An optional parameter that specifies the number of replica nodes in each node group (shard). Valid values are 0 to 5. :type NodeGroupConfiguration: list :param NodeGroupConfiguration: A list of node group (shard) configuration options. Each node group (shard) configuration has the following members: ``PrimaryAvailabilityZone`` , ``ReplicaAvailabilityZones`` , ``ReplicaCount`` , and ``Slots`` . If you\'re creating a Redis (cluster mode disabled) or a Redis (cluster mode enabled) replication group, you can use this parameter to individually configure each node group (shard), or you can omit this parameter. However, when seeding a Redis (cluster mode enabled) cluster from a S3 rdb file, you must configure each node group (shard) using this parameter because you must specify the slots for each node group. - *(dict) --* Node group (shard) configuration options. Each node group (shard) configuration has the following: ``Slots`` , ``PrimaryAvailabilityZone`` , ``ReplicaAvailabilityZones`` , ``ReplicaCount`` . - **NodeGroupId** *(string) --* The 4-digit id for the node group these configuration values apply to. - **Slots** *(string) --* A string that specifies the keyspace for a particular node group. Keyspaces range from 0 to 16,383. The string is in the format ``startkey-endkey`` . Example: ``\"0-3999\"`` - **ReplicaCount** *(integer) --* The number of read replica nodes in this node group (shard). - **PrimaryAvailabilityZone** *(string) --* The Availability Zone where the primary node of this node group (shard) is launched. - **ReplicaAvailabilityZones** *(list) --* A list of Availability Zones to be used for the read replicas. The number of Availability Zones in this list must match the value of ``ReplicaCount`` or ``ReplicasPerNodeGroup`` if not specified. - *(string) --* :type CacheNodeType: string :param CacheNodeType: The compute and memory capacity of the nodes in the node group (shard). The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ :type Engine: string :param Engine: The name of the cache engine to be used for the clusters in this replication group. :type EngineVersion: string :param EngineVersion: The version number of the cache engine to be used for the clusters in this replication group. To view the supported cache engine versions, use the ``DescribeCacheEngineVersions`` operation. **Important:** You can upgrade to a newer engine version (see `Selecting a Cache Engine and Version <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/SelectEngine.html#VersionManagement>`__ ) in the *ElastiCache User Guide* , but you cannot downgrade to an earlier engine version. If you want to use an earlier engine version, you must delete the existing cluster or replication group and create it anew with the earlier engine version. :type CacheParameterGroupName: string :param CacheParameterGroupName: The name of the parameter group to associate with this replication group. If this argument is omitted, the default cache parameter group for the specified engine is used. If you are running Redis version 3.2.4 or later, only one node group (shard), and want to use a default parameter group, we recommend that you specify the parameter group by name. * To create a Redis (cluster mode disabled) replication group, use ``CacheParameterGroupName=default.redis3.2`` . * To create a Redis (cluster mode enabled) replication group, use ``CacheParameterGroupName=default.redis3.2.cluster.on`` . :type CacheSubnetGroupName: string :param CacheSubnetGroupName: The name of the cache subnet group to be used for the replication group. .. warning:: If you\'re going to launch your cluster in an Amazon VPC, you need to create a subnet group before you start creating a cluster. For more information, see `Subnets and Subnet Groups <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/SubnetGroups.html>`__ . :type CacheSecurityGroupNames: list :param CacheSecurityGroupNames: A list of cache security group names to associate with this replication group. - *(string) --* :type SecurityGroupIds: list :param SecurityGroupIds: One or more Amazon VPC security groups associated with this replication group. Use this parameter only when you are creating a replication group in an Amazon Virtual Private Cloud (Amazon VPC). - *(string) --* :type Tags: list :param Tags: A list of cost allocation tags to be added to this resource. A tag is a key-value pair. - *(dict) --* A cost allocation Tag that can be added to an ElastiCache cluster or replication group. Tags are composed of a Key/Value pair. A tag with a null Value is permitted. - **Key** *(string) --* The key for the tag. May not be null. - **Value** *(string) --* The tag\'s value. May be null. :type SnapshotArns: list :param SnapshotArns: A list of Amazon Resource Names (ARN) that uniquely identify the Redis RDB snapshot files stored in Amazon S3. The snapshot files are used to populate the new replication group. The Amazon S3 object name in the ARN cannot contain any commas. The new replication group will have the number of node groups (console: shards) specified by the parameter *NumNodeGroups* or the number of node groups configured by *NodeGroupConfiguration* regardless of the number of ARNs specified here. Example of an Amazon S3 ARN: ``arn:aws:s3:::my_bucket/snapshot1.rdb`` - *(string) --* :type SnapshotName: string :param SnapshotName: The name of a snapshot from which to restore data into the new replication group. The snapshot status changes to ``restoring`` while the new replication group is being created. :type PreferredMaintenanceWindow: string :param PreferredMaintenanceWindow: Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` :type Port: integer :param Port: The port number on which each member of the replication group accepts connections. :type NotificationTopicArn: string :param NotificationTopicArn: The Amazon Resource Name (ARN) of the Amazon Simple Notification Service (SNS) topic to which notifications are sent. .. note:: The Amazon SNS topic owner must be the same as the cluster owner. :type AutoMinorVersionUpgrade: boolean :param AutoMinorVersionUpgrade: This parameter is currently disabled. :type SnapshotRetentionLimit: integer :param SnapshotRetentionLimit: The number of days for which ElastiCache retains automatic snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. Default: 0 (i.e., automatic backups are disabled for this cluster). :type SnapshotWindow: string :param SnapshotWindow: The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. :type AuthToken: string :param AuthToken: **Reserved parameter.** The password used to access a password protected server. ``AuthToken`` can be specified only on replication groups where ``TransitEncryptionEnabled`` is ``true`` . .. warning:: For HIPAA compliance, you must specify ``TransitEncryptionEnabled`` as ``true`` , an ``AuthToken`` , and a ``CacheSubnetGroup`` . Password constraints: * Must be only printable ASCII characters. * Must be at least 16 characters and no more than 128 characters in length. * Cannot contain any of the following characters: \'/\', \'\"\', or \'@\'. For more information, see `AUTH password <http://redis.io/commands/AUTH>`__ at http://redis.io/commands/AUTH. :type TransitEncryptionEnabled: boolean :param TransitEncryptionEnabled: A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. This parameter is valid only if the ``Engine`` parameter is ``redis`` , the ``EngineVersion`` parameter is ``3.2.6`` or ``4.x`` , and the cluster is being created in an Amazon VPC. If you enable in-transit encryption, you must also specify a value for ``CacheSubnetGroup`` . **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` .. warning:: For HIPAA compliance, you must specify ``TransitEncryptionEnabled`` as ``true`` , an ``AuthToken`` , and a ``CacheSubnetGroup`` . :type AtRestEncryptionEnabled: boolean :param AtRestEncryptionEnabled: A flag that enables encryption at rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the replication group is created. To enable encryption at rest on a replication group you must set ``AtRestEncryptionEnabled`` to ``true`` when you create the replication group. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :rtype: dict :returns: """ pass def create_snapshot(self, SnapshotName: str, ReplicationGroupId: str = None, CacheClusterId: str = None) -> Dict: """ Creates a copy of an entire cluster or replication group at a specific moment in time. .. note:: This operation is valid for Redis only. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/CreateSnapshot>`_ **Request Syntax** :: response = client.create_snapshot( ReplicationGroupId='string', CacheClusterId='string', SnapshotName='string' ) **Response Syntax** :: { 'Snapshot': { 'SnapshotName': 'string', 'ReplicationGroupId': 'string', 'ReplicationGroupDescription': 'string', 'CacheClusterId': 'string', 'SnapshotStatus': 'string', 'SnapshotSource': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'TopicArn': 'string', 'Port': 123, 'CacheParameterGroupName': 'string', 'CacheSubnetGroupName': 'string', 'VpcId': 'string', 'AutoMinorVersionUpgrade': True|False, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'NumNodeGroups': 123, 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'NodeSnapshots': [ { 'CacheClusterId': 'string', 'NodeGroupId': 'string', 'CacheNodeId': 'string', 'NodeGroupConfiguration': { 'NodeGroupId': 'string', 'Slots': 'string', 'ReplicaCount': 123, 'PrimaryAvailabilityZone': 'string', 'ReplicaAvailabilityZones': [ 'string', ] }, 'CacheSize': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'SnapshotCreateTime': datetime(2015, 1, 1) }, ] } } **Response Structure** - *(dict) --* - **Snapshot** *(dict) --* Represents a copy of an entire Redis cluster as of the time when the snapshot was taken. - **SnapshotName** *(string) --* The name of a snapshot. For an automatic snapshot, the name is system-generated. For a manual snapshot, this is the user-provided name. - **ReplicationGroupId** *(string) --* The unique identifier of the source replication group. - **ReplicationGroupDescription** *(string) --* A description of the source replication group. - **CacheClusterId** *(string) --* The user-supplied identifier of the source cluster. - **SnapshotStatus** *(string) --* The status of the snapshot. Valid values: ``creating`` | ``available`` | ``restoring`` | ``copying`` | ``deleting`` . - **SnapshotSource** *(string) --* Indicates whether the snapshot is from an automatic backup (``automated`` ) or was created manually (``manual`` ). - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the source cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) used by the source cluster. - **EngineVersion** *(string) --* The version of the cache engine version that is used by the source cluster. - **NumCacheNodes** *(integer) --* The number of cache nodes in the source cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the source cluster is located. - **CacheClusterCreateTime** *(datetime) --* The date and time when the source cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **TopicArn** *(string) --* The Amazon Resource Name (ARN) for the topic used by the source cluster for publishing notifications. - **Port** *(integer) --* The port number used by each cache nodes in the source cluster. - **CacheParameterGroupName** *(string) --* The cache parameter group that is associated with the source cluster. - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the source cluster. - **VpcId** *(string) --* The Amazon Virtual Private Cloud identifier (VPC ID) of the cache subnet group for the source cluster. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SnapshotRetentionLimit** *(integer) --* For an automatic snapshot, the number of days for which ElastiCache retains the snapshot before deleting it. For manual snapshots, this field reflects the ``SnapshotRetentionLimit`` for the source cluster when the snapshot was created. This field is otherwise ignored: Manual snapshots do not expire, and can only be deleted using the ``DeleteSnapshot`` operation. **Important** If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range during which ElastiCache takes daily snapshots of the source cluster. - **NumNodeGroups** *(integer) --* The number of node groups (shards) in this snapshot. When restoring from a snapshot, the number of node groups (shards) in the snapshot and in the restored replication group must be the same. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for the source Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **NodeSnapshots** *(list) --* A list of the cache nodes in the source cluster. - *(dict) --* Represents an individual cache node in a snapshot of a cluster. - **CacheClusterId** *(string) --* A unique identifier for the source cluster. - **NodeGroupId** *(string) --* A unique identifier for the source node group (shard). - **CacheNodeId** *(string) --* The cache node identifier for the node in the source cluster. - **NodeGroupConfiguration** *(dict) --* The configuration for the source node group (shard). - **NodeGroupId** *(string) --* The 4-digit id for the node group these configuration values apply to. - **Slots** *(string) --* A string that specifies the keyspace for a particular node group. Keyspaces range from 0 to 16,383. The string is in the format ``startkey-endkey`` . Example: ``"0-3999"`` - **ReplicaCount** *(integer) --* The number of read replica nodes in this node group (shard). - **PrimaryAvailabilityZone** *(string) --* The Availability Zone where the primary node of this node group (shard) is launched. - **ReplicaAvailabilityZones** *(list) --* A list of Availability Zones to be used for the read replicas. The number of Availability Zones in this list must match the value of ``ReplicaCount`` or ``ReplicasPerNodeGroup`` if not specified. - *(string) --* - **CacheSize** *(string) --* The size of the cache on the source cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created in the source cluster. - **SnapshotCreateTime** *(datetime) --* The date and time when the source node's metadata and cache data set was obtained for the snapshot. :type ReplicationGroupId: string :param ReplicationGroupId: The identifier of an existing replication group. The snapshot is created from this replication group. :type CacheClusterId: string :param CacheClusterId: The identifier of an existing cluster. The snapshot is created from this cluster. :type SnapshotName: string :param SnapshotName: **[REQUIRED]** A name for the snapshot being created. :rtype: dict :returns: """ pass def decrease_replica_count(self, ReplicationGroupId: str, ApplyImmediately: bool, NewReplicaCount: int = None, ReplicaConfiguration: List = None, ReplicasToRemove: List = None) -> Dict: """ Dynamically decreases the number of replics in a Redis (cluster mode disabled) replication group or the number of replica nodes in one or more node groups (shards) of a Redis (cluster mode enabled) replication group. This operation is performed with no cluster down time. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DecreaseReplicaCount>`_ **Request Syntax** :: response = client.decrease_replica_count( ReplicationGroupId='string', NewReplicaCount=123, ReplicaConfiguration=[ { 'NodeGroupId': 'string', 'NewReplicaCount': 123, 'PreferredAvailabilityZones': [ 'string', ] }, ], ReplicasToRemove=[ 'string', ], ApplyImmediately=True|False ) **Response Syntax** :: { 'ReplicationGroup': { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **ReplicationGroup** *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: **[REQUIRED]** The id of the replication group from which you want to remove replica nodes. :type NewReplicaCount: integer :param NewReplicaCount: The number of read replica nodes you want at the completion of this operation. For Redis (cluster mode disabled) replication groups, this is the number of replica nodes in the replication group. For Redis (cluster mode enabled) replication groups, this is the number of replica nodes in each of the replication group\'s node groups. The minimum number of replicas in a shard or replication group is: * Redis (cluster mode disabled) * If Multi-AZ with Automatic Failover is enabled: 1 * If Multi-AZ with Automatic Failover is not enabled: 0 * Redis (cluster mode enabled): 0 (though you will not be able to failover to a replica if your primary node fails) :type ReplicaConfiguration: list :param ReplicaConfiguration: A list of ``ConfigureShard`` objects that can be used to configure each shard in a Redis (cluster mode enabled) replication group. The ``ConfigureShard`` has three members: ``NewReplicaCount`` , ``NodeGroupId`` , and ``PreferredAvailabilityZones`` . - *(dict) --* Node group (shard) configuration options when adding or removing replicas. Each node group (shard) configuration has the following members: NodeGroupId, NewReplicaCount, and PreferredAvailabilityZones. - **NodeGroupId** *(string) --* **[REQUIRED]** The 4-digit id for the node group you are configuring. For Redis (cluster mode disabled) replication groups, the node group id is always 0001. To find a Redis (cluster mode enabled)\'s node group\'s (shard\'s) id, see `Finding a Shard\'s Id <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/shard-find-id.html>`__ . - **NewReplicaCount** *(integer) --* **[REQUIRED]** The number of replicas you want in this node group at the end of this operation. The maximum value for ``NewReplicaCount`` is 5. The minimum value depends upon the type of Redis replication group you are working with. The minimum number of replicas in a shard or replication group is: * Redis (cluster mode disabled) * If Multi-AZ with Automatic Failover is enabled: 1 * If Multi-AZ with Automatic Failover is not enable: 0 * Redis (cluster mode enabled): 0 (though you will not be able to failover to a replica if your primary node fails) - **PreferredAvailabilityZones** *(list) --* A list of ``PreferredAvailabilityZone`` strings that specify which availability zones the replication group\'s nodes are to be in. The nummber of ``PreferredAvailabilityZone`` values must equal the value of ``NewReplicaCount`` plus 1 to account for the primary node. If this member of ``ReplicaConfiguration`` is omitted, ElastiCache for Redis selects the availability zone for each of the replicas. - *(string) --* :type ReplicasToRemove: list :param ReplicasToRemove: A list of the node ids to remove from the replication group or node group (shard). - *(string) --* :type ApplyImmediately: boolean :param ApplyImmediately: **[REQUIRED]** If ``True`` , the number of replica nodes is decreased immediately. If ``False`` , the number of replica nodes is decreased during the next maintenance window. :rtype: dict :returns: """ pass def delete_cache_cluster(self, CacheClusterId: str, FinalSnapshotIdentifier: str = None) -> Dict: """ Deletes a previously provisioned cluster. ``DeleteCacheCluster`` deletes all associated cache nodes, node endpoints and the cluster itself. When you receive a successful response from this operation, Amazon ElastiCache immediately begins deleting the cluster; you cannot cancel or revert this operation. This operation cannot be used to delete a cluster that is the last read replica of a replication group or node group (shard) that has Multi-AZ mode enabled or a cluster from a Redis (cluster mode enabled) replication group. This operation is not valid for Redis (cluster mode enabled) clusters. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DeleteCacheCluster>`_ **Request Syntax** :: response = client.delete_cache_cluster( CacheClusterId='string', FinalSnapshotIdentifier='string' ) **Response Syntax** :: { 'CacheCluster': { 'CacheClusterId': 'string', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'ClientDownloadLandingPage': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'CacheClusterStatus': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'PendingModifiedValues': { 'NumCacheNodes': 123, 'CacheNodeIdsToRemove': [ 'string', ], 'EngineVersion': 'string', 'CacheNodeType': 'string' }, 'NotificationConfiguration': { 'TopicArn': 'string', 'TopicStatus': 'string' }, 'CacheSecurityGroups': [ { 'CacheSecurityGroupName': 'string', 'Status': 'string' }, ], 'CacheParameterGroup': { 'CacheParameterGroupName': 'string', 'ParameterApplyStatus': 'string', 'CacheNodeIdsToReboot': [ 'string', ] }, 'CacheSubnetGroupName': 'string', 'CacheNodes': [ { 'CacheNodeId': 'string', 'CacheNodeStatus': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'Endpoint': { 'Address': 'string', 'Port': 123 }, 'ParameterGroupStatus': 'string', 'SourceCacheNodeId': 'string', 'CustomerAvailabilityZone': 'string' }, ], 'AutoMinorVersionUpgrade': True|False, 'SecurityGroups': [ { 'SecurityGroupId': 'string', 'Status': 'string' }, ], 'ReplicationGroupId': 'string', 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **CacheCluster** *(dict) --* Contains all of the attributes of a specific cluster. - **CacheClusterId** *(string) --* The user-supplied identifier of the cluster. This identifier is a unique key that identifies a cluster. - **ConfigurationEndpoint** *(dict) --* Represents a Memcached cluster endpoint which, if Automatic Discovery is enabled on the cluster, can be used by an application to connect to any node in the cluster. The configuration endpoint will always have ``.cfg`` in it. Example: ``mem-3.9dvc4r.cfg.usw2.cache.amazonaws.com:11211`` - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ClientDownloadLandingPage** *(string) --* The URL of the web page where you can download the latest ElastiCache client library. - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) to be used for this cluster. - **EngineVersion** *(string) --* The version of the cache engine that is used in this cluster. - **CacheClusterStatus** *(string) --* The current state of this cluster, one of the following values: ``available`` , ``creating`` , ``deleted`` , ``deleting`` , ``incompatible-network`` , ``modifying`` , ``rebooting cluster nodes`` , ``restore-failed`` , or ``snapshotting`` . - **NumCacheNodes** *(integer) --* The number of cache nodes in the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the cluster is located or "Multiple" if the cache nodes are located in different Availability Zones. - **CacheClusterCreateTime** *(datetime) --* The date and time when the cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **PendingModifiedValues** *(dict) --* A group of settings that are applied to the cluster in the future, or that are currently being applied. - **NumCacheNodes** *(integer) --* The new number of cache nodes for the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **CacheNodeIdsToRemove** *(list) --* A list of cache node IDs that are being removed (or will be removed) from the cluster. A node ID is a 4-digit numeric identifier (0001, 0002, etc.). - *(string) --* - **EngineVersion** *(string) --* The new cache engine version that the cluster runs. - **CacheNodeType** *(string) --* The cache node type that this cluster or replication group is scaled to. - **NotificationConfiguration** *(dict) --* Describes a notification topic and its status. Notification topics are used for publishing ElastiCache events to subscribers using Amazon Simple Notification Service (SNS). - **TopicArn** *(string) --* The Amazon Resource Name (ARN) that identifies the topic. - **TopicStatus** *(string) --* The current state of the topic. - **CacheSecurityGroups** *(list) --* A list of cache security group elements, composed of name and status sub-elements. - *(dict) --* Represents a cluster's status within a particular cache security group. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Status** *(string) --* The membership status in the cache security group. The status changes when a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **CacheParameterGroup** *(dict) --* Status of the cache parameter group. - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. - **ParameterApplyStatus** *(string) --* The status of parameter updates. - **CacheNodeIdsToReboot** *(list) --* A list of the cache node IDs which need to be rebooted for parameter changes to be applied. A node ID is a numeric identifier (0001, 0002, etc.). - *(string) --* - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the cluster. - **CacheNodes** *(list) --* A list of cache nodes that are members of the cluster. - *(dict) --* Represents an individual cache node within a cluster. Each cache node runs its own instance of the cluster's protocol-compliant caching software - either Memcached or Redis. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **CacheNodeId** *(string) --* The cache node identifier. A node ID is a numeric identifier (0001, 0002, etc.). The combination of cluster ID and node ID uniquely identifies every cache node used in a customer's AWS account. - **CacheNodeStatus** *(string) --* The current state of this cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created. - **Endpoint** *(dict) --* The hostname for connecting to this cache node. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ParameterGroupStatus** *(string) --* The status of the parameter group applied to this cache node. - **SourceCacheNodeId** *(string) --* The ID of the primary node to which this read replica node is synchronized. If this field is empty, this node is not associated with a primary cluster. - **CustomerAvailabilityZone** *(string) --* The Availability Zone where this node was created and now resides. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SecurityGroups** *(list) --* A list of VPC Security Groups associated with the cluster. - *(dict) --* Represents a single cache security group and its status. - **SecurityGroupId** *(string) --* The identifier of the cache security group. - **Status** *(string) --* The status of the cache security group membership. The status changes whenever a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **ReplicationGroupId** *(string) --* The replication group to which this cluster belongs. If this field is empty, the cluster is not associated with any replication group. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your cluster. Example: ``05:00-09:00`` - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable at-rest encryption on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type CacheClusterId: string :param CacheClusterId: **[REQUIRED]** The cluster identifier for the cluster to be deleted. This parameter is not case sensitive. :type FinalSnapshotIdentifier: string :param FinalSnapshotIdentifier: The user-supplied name of a final cluster snapshot. This is the unique name that identifies the snapshot. ElastiCache creates the snapshot, and then deletes the cluster immediately afterward. :rtype: dict :returns: """ pass def delete_cache_parameter_group(self, CacheParameterGroupName: str): """ Deletes the specified cache parameter group. You cannot delete a cache parameter group if it is associated with any cache clusters. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DeleteCacheParameterGroup>`_ **Request Syntax** :: response = client.delete_cache_parameter_group( CacheParameterGroupName='string' ) :type CacheParameterGroupName: string :param CacheParameterGroupName: **[REQUIRED]** The name of the cache parameter group to delete. .. note:: The specified cache security group must not be associated with any clusters. :returns: None """ pass def delete_cache_security_group(self, CacheSecurityGroupName: str): """ Deletes a cache security group. .. note:: You cannot delete a cache security group if it is associated with any clusters. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DeleteCacheSecurityGroup>`_ **Request Syntax** :: response = client.delete_cache_security_group( CacheSecurityGroupName='string' ) :type CacheSecurityGroupName: string :param CacheSecurityGroupName: **[REQUIRED]** The name of the cache security group to delete. .. note:: You cannot delete the default security group. :returns: None """ pass def delete_cache_subnet_group(self, CacheSubnetGroupName: str): """ Deletes a cache subnet group. .. note:: You cannot delete a cache subnet group if it is associated with any clusters. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DeleteCacheSubnetGroup>`_ **Request Syntax** :: response = client.delete_cache_subnet_group( CacheSubnetGroupName='string' ) :type CacheSubnetGroupName: string :param CacheSubnetGroupName: **[REQUIRED]** The name of the cache subnet group to delete. Constraints: Must contain no more than 255 alphanumeric characters or hyphens. :returns: None """ pass def delete_replication_group(self, ReplicationGroupId: str, RetainPrimaryCluster: bool = None, FinalSnapshotIdentifier: str = None) -> Dict: """ Deletes an existing replication group. By default, this operation deletes the entire replication group, including the primary/primaries and all of the read replicas. If the replication group has only one primary, you can optionally delete only the read replicas, while retaining the primary by setting ``RetainPrimaryCluster=true`` . When you receive a successful response from this operation, Amazon ElastiCache immediately begins deleting the selected resources; you cannot cancel or revert this operation. .. note:: This operation is valid for Redis only. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DeleteReplicationGroup>`_ **Request Syntax** :: response = client.delete_replication_group( ReplicationGroupId='string', RetainPrimaryCluster=True|False, FinalSnapshotIdentifier='string' ) **Response Syntax** :: { 'ReplicationGroup': { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **ReplicationGroup** *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: **[REQUIRED]** The identifier for the cluster to be deleted. This parameter is not case sensitive. :type RetainPrimaryCluster: boolean :param RetainPrimaryCluster: If set to ``true`` , all of the read replicas are deleted, but the primary node is retained. :type FinalSnapshotIdentifier: string :param FinalSnapshotIdentifier: The name of a final node group (shard) snapshot. ElastiCache creates the snapshot from the primary node in the cluster, rather than one of the replicas; this is to ensure that it captures the freshest data. After the final snapshot is taken, the replication group is immediately deleted. :rtype: dict :returns: """ pass def delete_snapshot(self, SnapshotName: str) -> Dict: """ Deletes an existing snapshot. When you receive a successful response from this operation, ElastiCache immediately begins deleting the snapshot; you cannot cancel or revert this operation. .. note:: This operation is valid for Redis only. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DeleteSnapshot>`_ **Request Syntax** :: response = client.delete_snapshot( SnapshotName='string' ) **Response Syntax** :: { 'Snapshot': { 'SnapshotName': 'string', 'ReplicationGroupId': 'string', 'ReplicationGroupDescription': 'string', 'CacheClusterId': 'string', 'SnapshotStatus': 'string', 'SnapshotSource': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'TopicArn': 'string', 'Port': 123, 'CacheParameterGroupName': 'string', 'CacheSubnetGroupName': 'string', 'VpcId': 'string', 'AutoMinorVersionUpgrade': True|False, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'NumNodeGroups': 123, 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'NodeSnapshots': [ { 'CacheClusterId': 'string', 'NodeGroupId': 'string', 'CacheNodeId': 'string', 'NodeGroupConfiguration': { 'NodeGroupId': 'string', 'Slots': 'string', 'ReplicaCount': 123, 'PrimaryAvailabilityZone': 'string', 'ReplicaAvailabilityZones': [ 'string', ] }, 'CacheSize': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'SnapshotCreateTime': datetime(2015, 1, 1) }, ] } } **Response Structure** - *(dict) --* - **Snapshot** *(dict) --* Represents a copy of an entire Redis cluster as of the time when the snapshot was taken. - **SnapshotName** *(string) --* The name of a snapshot. For an automatic snapshot, the name is system-generated. For a manual snapshot, this is the user-provided name. - **ReplicationGroupId** *(string) --* The unique identifier of the source replication group. - **ReplicationGroupDescription** *(string) --* A description of the source replication group. - **CacheClusterId** *(string) --* The user-supplied identifier of the source cluster. - **SnapshotStatus** *(string) --* The status of the snapshot. Valid values: ``creating`` | ``available`` | ``restoring`` | ``copying`` | ``deleting`` . - **SnapshotSource** *(string) --* Indicates whether the snapshot is from an automatic backup (``automated`` ) or was created manually (``manual`` ). - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the source cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) used by the source cluster. - **EngineVersion** *(string) --* The version of the cache engine version that is used by the source cluster. - **NumCacheNodes** *(integer) --* The number of cache nodes in the source cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the source cluster is located. - **CacheClusterCreateTime** *(datetime) --* The date and time when the source cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **TopicArn** *(string) --* The Amazon Resource Name (ARN) for the topic used by the source cluster for publishing notifications. - **Port** *(integer) --* The port number used by each cache nodes in the source cluster. - **CacheParameterGroupName** *(string) --* The cache parameter group that is associated with the source cluster. - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the source cluster. - **VpcId** *(string) --* The Amazon Virtual Private Cloud identifier (VPC ID) of the cache subnet group for the source cluster. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SnapshotRetentionLimit** *(integer) --* For an automatic snapshot, the number of days for which ElastiCache retains the snapshot before deleting it. For manual snapshots, this field reflects the ``SnapshotRetentionLimit`` for the source cluster when the snapshot was created. This field is otherwise ignored: Manual snapshots do not expire, and can only be deleted using the ``DeleteSnapshot`` operation. **Important** If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range during which ElastiCache takes daily snapshots of the source cluster. - **NumNodeGroups** *(integer) --* The number of node groups (shards) in this snapshot. When restoring from a snapshot, the number of node groups (shards) in the snapshot and in the restored replication group must be the same. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for the source Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **NodeSnapshots** *(list) --* A list of the cache nodes in the source cluster. - *(dict) --* Represents an individual cache node in a snapshot of a cluster. - **CacheClusterId** *(string) --* A unique identifier for the source cluster. - **NodeGroupId** *(string) --* A unique identifier for the source node group (shard). - **CacheNodeId** *(string) --* The cache node identifier for the node in the source cluster. - **NodeGroupConfiguration** *(dict) --* The configuration for the source node group (shard). - **NodeGroupId** *(string) --* The 4-digit id for the node group these configuration values apply to. - **Slots** *(string) --* A string that specifies the keyspace for a particular node group. Keyspaces range from 0 to 16,383. The string is in the format ``startkey-endkey`` . Example: ``"0-3999"`` - **ReplicaCount** *(integer) --* The number of read replica nodes in this node group (shard). - **PrimaryAvailabilityZone** *(string) --* The Availability Zone where the primary node of this node group (shard) is launched. - **ReplicaAvailabilityZones** *(list) --* A list of Availability Zones to be used for the read replicas. The number of Availability Zones in this list must match the value of ``ReplicaCount`` or ``ReplicasPerNodeGroup`` if not specified. - *(string) --* - **CacheSize** *(string) --* The size of the cache on the source cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created in the source cluster. - **SnapshotCreateTime** *(datetime) --* The date and time when the source node's metadata and cache data set was obtained for the snapshot. :type SnapshotName: string :param SnapshotName: **[REQUIRED]** The name of the snapshot to be deleted. :rtype: dict :returns: """ pass def describe_cache_clusters(self, CacheClusterId: str = None, MaxRecords: int = None, Marker: str = None, ShowCacheNodeInfo: bool = None, ShowCacheClustersNotInReplicationGroups: bool = None) -> Dict: """ Returns information about all provisioned clusters if no cluster identifier is specified, or about a specific cache cluster if a cluster identifier is supplied. By default, abbreviated information about the clusters is returned. You can use the optional *ShowCacheNodeInfo* flag to retrieve detailed information about the cache nodes associated with the clusters. These details include the DNS address and port for the cache node endpoint. If the cluster is in the *creating* state, only cluster-level information is displayed until all of the nodes are successfully provisioned. If the cluster is in the *deleting* state, only cluster-level information is displayed. If cache nodes are currently being added to the cluster, node endpoint information and creation time for the additional nodes are not displayed until they are completely provisioned. When the cluster state is *available* , the cluster is ready for use. If cache nodes are currently being removed from the cluster, no endpoint information for the removed nodes is displayed. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeCacheClusters>`_ **Request Syntax** :: response = client.describe_cache_clusters( CacheClusterId='string', MaxRecords=123, Marker='string', ShowCacheNodeInfo=True|False, ShowCacheClustersNotInReplicationGroups=True|False ) **Response Syntax** :: { 'Marker': 'string', 'CacheClusters': [ { 'CacheClusterId': 'string', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'ClientDownloadLandingPage': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'CacheClusterStatus': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'PendingModifiedValues': { 'NumCacheNodes': 123, 'CacheNodeIdsToRemove': [ 'string', ], 'EngineVersion': 'string', 'CacheNodeType': 'string' }, 'NotificationConfiguration': { 'TopicArn': 'string', 'TopicStatus': 'string' }, 'CacheSecurityGroups': [ { 'CacheSecurityGroupName': 'string', 'Status': 'string' }, ], 'CacheParameterGroup': { 'CacheParameterGroupName': 'string', 'ParameterApplyStatus': 'string', 'CacheNodeIdsToReboot': [ 'string', ] }, 'CacheSubnetGroupName': 'string', 'CacheNodes': [ { 'CacheNodeId': 'string', 'CacheNodeStatus': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'Endpoint': { 'Address': 'string', 'Port': 123 }, 'ParameterGroupStatus': 'string', 'SourceCacheNodeId': 'string', 'CustomerAvailabilityZone': 'string' }, ], 'AutoMinorVersionUpgrade': True|False, 'SecurityGroups': [ { 'SecurityGroupId': 'string', 'Status': 'string' }, ], 'ReplicationGroupId': 'string', 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeCacheClusters`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **CacheClusters** *(list) --* A list of clusters. Each item in the list contains detailed information about one cluster. - *(dict) --* Contains all of the attributes of a specific cluster. - **CacheClusterId** *(string) --* The user-supplied identifier of the cluster. This identifier is a unique key that identifies a cluster. - **ConfigurationEndpoint** *(dict) --* Represents a Memcached cluster endpoint which, if Automatic Discovery is enabled on the cluster, can be used by an application to connect to any node in the cluster. The configuration endpoint will always have ``.cfg`` in it. Example: ``mem-3.9dvc4r.cfg.usw2.cache.amazonaws.com:11211`` - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ClientDownloadLandingPage** *(string) --* The URL of the web page where you can download the latest ElastiCache client library. - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) to be used for this cluster. - **EngineVersion** *(string) --* The version of the cache engine that is used in this cluster. - **CacheClusterStatus** *(string) --* The current state of this cluster, one of the following values: ``available`` , ``creating`` , ``deleted`` , ``deleting`` , ``incompatible-network`` , ``modifying`` , ``rebooting cluster nodes`` , ``restore-failed`` , or ``snapshotting`` . - **NumCacheNodes** *(integer) --* The number of cache nodes in the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the cluster is located or "Multiple" if the cache nodes are located in different Availability Zones. - **CacheClusterCreateTime** *(datetime) --* The date and time when the cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **PendingModifiedValues** *(dict) --* A group of settings that are applied to the cluster in the future, or that are currently being applied. - **NumCacheNodes** *(integer) --* The new number of cache nodes for the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **CacheNodeIdsToRemove** *(list) --* A list of cache node IDs that are being removed (or will be removed) from the cluster. A node ID is a 4-digit numeric identifier (0001, 0002, etc.). - *(string) --* - **EngineVersion** *(string) --* The new cache engine version that the cluster runs. - **CacheNodeType** *(string) --* The cache node type that this cluster or replication group is scaled to. - **NotificationConfiguration** *(dict) --* Describes a notification topic and its status. Notification topics are used for publishing ElastiCache events to subscribers using Amazon Simple Notification Service (SNS). - **TopicArn** *(string) --* The Amazon Resource Name (ARN) that identifies the topic. - **TopicStatus** *(string) --* The current state of the topic. - **CacheSecurityGroups** *(list) --* A list of cache security group elements, composed of name and status sub-elements. - *(dict) --* Represents a cluster's status within a particular cache security group. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Status** *(string) --* The membership status in the cache security group. The status changes when a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **CacheParameterGroup** *(dict) --* Status of the cache parameter group. - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. - **ParameterApplyStatus** *(string) --* The status of parameter updates. - **CacheNodeIdsToReboot** *(list) --* A list of the cache node IDs which need to be rebooted for parameter changes to be applied. A node ID is a numeric identifier (0001, 0002, etc.). - *(string) --* - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the cluster. - **CacheNodes** *(list) --* A list of cache nodes that are members of the cluster. - *(dict) --* Represents an individual cache node within a cluster. Each cache node runs its own instance of the cluster's protocol-compliant caching software - either Memcached or Redis. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **CacheNodeId** *(string) --* The cache node identifier. A node ID is a numeric identifier (0001, 0002, etc.). The combination of cluster ID and node ID uniquely identifies every cache node used in a customer's AWS account. - **CacheNodeStatus** *(string) --* The current state of this cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created. - **Endpoint** *(dict) --* The hostname for connecting to this cache node. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ParameterGroupStatus** *(string) --* The status of the parameter group applied to this cache node. - **SourceCacheNodeId** *(string) --* The ID of the primary node to which this read replica node is synchronized. If this field is empty, this node is not associated with a primary cluster. - **CustomerAvailabilityZone** *(string) --* The Availability Zone where this node was created and now resides. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SecurityGroups** *(list) --* A list of VPC Security Groups associated with the cluster. - *(dict) --* Represents a single cache security group and its status. - **SecurityGroupId** *(string) --* The identifier of the cache security group. - **Status** *(string) --* The status of the cache security group membership. The status changes whenever a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **ReplicationGroupId** *(string) --* The replication group to which this cluster belongs. If this field is empty, the cluster is not associated with any replication group. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your cluster. Example: ``05:00-09:00`` - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable at-rest encryption on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type CacheClusterId: string :param CacheClusterId: The user-supplied cluster identifier. If this parameter is specified, only information about that specific cluster is returned. This parameter isn\'t case sensitive. :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :type ShowCacheNodeInfo: boolean :param ShowCacheNodeInfo: An optional flag that can be included in the ``DescribeCacheCluster`` request to retrieve information about the individual cache nodes. :type ShowCacheClustersNotInReplicationGroups: boolean :param ShowCacheClustersNotInReplicationGroups: An optional flag that can be included in the ``DescribeCacheCluster`` request to show only nodes (API/CLI: clusters) that are not members of a replication group. In practice, this mean Memcached and single node Redis clusters. :rtype: dict :returns: """ pass def describe_cache_engine_versions(self, Engine: str = None, EngineVersion: str = None, CacheParameterGroupFamily: str = None, MaxRecords: int = None, Marker: str = None, DefaultOnly: bool = None) -> Dict: """ Returns a list of the available cache engines and their versions. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeCacheEngineVersions>`_ **Request Syntax** :: response = client.describe_cache_engine_versions( Engine='string', EngineVersion='string', CacheParameterGroupFamily='string', MaxRecords=123, Marker='string', DefaultOnly=True|False ) **Response Syntax** :: { 'Marker': 'string', 'CacheEngineVersions': [ { 'Engine': 'string', 'EngineVersion': 'string', 'CacheParameterGroupFamily': 'string', 'CacheEngineDescription': 'string', 'CacheEngineVersionDescription': 'string' }, ] } **Response Structure** - *(dict) --* Represents the output of a DescribeCacheEngineVersions operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **CacheEngineVersions** *(list) --* A list of cache engine version details. Each element in the list contains detailed information about one cache engine version. - *(dict) --* Provides all of the details about a particular cache engine version. - **Engine** *(string) --* The name of the cache engine. - **EngineVersion** *(string) --* The version number of the cache engine. - **CacheParameterGroupFamily** *(string) --* The name of the cache parameter group family associated with this cache engine. Valid values are: ``memcached1.4`` | ``redis2.6`` | ``redis2.8`` | ``redis3.2`` | ``redis4.0`` - **CacheEngineDescription** *(string) --* The description of the cache engine. - **CacheEngineVersionDescription** *(string) --* The description of the cache engine version. :type Engine: string :param Engine: The cache engine to return. Valid values: ``memcached`` | ``redis`` :type EngineVersion: string :param EngineVersion: The cache engine version to return. Example: ``1.4.14`` :type CacheParameterGroupFamily: string :param CacheParameterGroupFamily: The name of a specific cache parameter group family to return details for. Valid values are: ``memcached1.4`` | ``redis2.6`` | ``redis2.8`` | ``redis3.2`` | ``redis4.0`` Constraints: * Must be 1 to 255 alphanumeric characters * First character must be a letter * Cannot end with a hyphen or contain two consecutive hyphens :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :type DefaultOnly: boolean :param DefaultOnly: If ``true`` , specifies that only the default version of the specified engine or engine and major version combination is to be returned. :rtype: dict :returns: """ pass def describe_cache_parameter_groups(self, CacheParameterGroupName: str = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns a list of cache parameter group descriptions. If a cache parameter group name is specified, the list contains only the descriptions for that group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeCacheParameterGroups>`_ **Request Syntax** :: response = client.describe_cache_parameter_groups( CacheParameterGroupName='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'CacheParameterGroups': [ { 'CacheParameterGroupName': 'string', 'CacheParameterGroupFamily': 'string', 'Description': 'string' }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeCacheParameterGroups`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **CacheParameterGroups** *(list) --* A list of cache parameter groups. Each element in the list contains detailed information about one cache parameter group. - *(dict) --* Represents the output of a ``CreateCacheParameterGroup`` operation. - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. - **CacheParameterGroupFamily** *(string) --* The name of the cache parameter group family that this cache parameter group is compatible with. Valid values are: ``memcached1.4`` | ``redis2.6`` | ``redis2.8`` | ``redis3.2`` | ``redis4.0`` - **Description** *(string) --* The description for this cache parameter group. :type CacheParameterGroupName: string :param CacheParameterGroupName: The name of a specific cache parameter group to return details for. :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_cache_parameters(self, CacheParameterGroupName: str, Source: str = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns the detailed parameter list for a particular cache parameter group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeCacheParameters>`_ **Request Syntax** :: response = client.describe_cache_parameters( CacheParameterGroupName='string', Source='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'Parameters': [ { 'ParameterName': 'string', 'ParameterValue': 'string', 'Description': 'string', 'Source': 'string', 'DataType': 'string', 'AllowedValues': 'string', 'IsModifiable': True|False, 'MinimumEngineVersion': 'string', 'ChangeType': 'immediate'|'requires-reboot' }, ], 'CacheNodeTypeSpecificParameters': [ { 'ParameterName': 'string', 'Description': 'string', 'Source': 'string', 'DataType': 'string', 'AllowedValues': 'string', 'IsModifiable': True|False, 'MinimumEngineVersion': 'string', 'CacheNodeTypeSpecificValues': [ { 'CacheNodeType': 'string', 'Value': 'string' }, ], 'ChangeType': 'immediate'|'requires-reboot' }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeCacheParameters`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **Parameters** *(list) --* A list of Parameter instances. - *(dict) --* Describes an individual setting that controls some aspect of ElastiCache behavior. - **ParameterName** *(string) --* The name of the parameter. - **ParameterValue** *(string) --* The value of the parameter. - **Description** *(string) --* A description of the parameter. - **Source** *(string) --* The source of the parameter. - **DataType** *(string) --* The valid data type for the parameter. - **AllowedValues** *(string) --* The valid range of values for the parameter. - **IsModifiable** *(boolean) --* Indicates whether (``true`` ) or not (``false`` ) the parameter can be modified. Some parameters have security or operational implications that prevent them from being changed. - **MinimumEngineVersion** *(string) --* The earliest cache engine version to which the parameter can apply. - **ChangeType** *(string) --* Indicates whether a change to the parameter is applied immediately or requires a reboot for the change to be applied. You can force a reboot or wait until the next maintenance window's reboot. For more information, see `Rebooting a Cluster <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Clusters.Rebooting.html>`__ . - **CacheNodeTypeSpecificParameters** *(list) --* A list of parameters specific to a particular cache node type. Each element in the list contains detailed information about one parameter. - *(dict) --* A parameter that has a different value for each cache node type it is applied to. For example, in a Redis cluster, a ``cache.m1.large`` cache node type would have a larger ``maxmemory`` value than a ``cache.m1.small`` type. - **ParameterName** *(string) --* The name of the parameter. - **Description** *(string) --* A description of the parameter. - **Source** *(string) --* The source of the parameter value. - **DataType** *(string) --* The valid data type for the parameter. - **AllowedValues** *(string) --* The valid range of values for the parameter. - **IsModifiable** *(boolean) --* Indicates whether (``true`` ) or not (``false`` ) the parameter can be modified. Some parameters have security or operational implications that prevent them from being changed. - **MinimumEngineVersion** *(string) --* The earliest cache engine version to which the parameter can apply. - **CacheNodeTypeSpecificValues** *(list) --* A list of cache node types and their corresponding values for this parameter. - *(dict) --* A value that applies only to a certain cache node type. - **CacheNodeType** *(string) --* The cache node type for which this value applies. - **Value** *(string) --* The value for the cache node type. - **ChangeType** *(string) --* Indicates whether a change to the parameter is applied immediately or requires a reboot for the change to be applied. You can force a reboot or wait until the next maintenance window's reboot. For more information, see `Rebooting a Cluster <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Clusters.Rebooting.html>`__ . :type CacheParameterGroupName: string :param CacheParameterGroupName: **[REQUIRED]** The name of a specific cache parameter group to return details for. :type Source: string :param Source: The parameter types to return. Valid values: ``user`` | ``system`` | ``engine-default`` :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_cache_security_groups(self, CacheSecurityGroupName: str = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns a list of cache security group descriptions. If a cache security group name is specified, the list contains only the description of that group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeCacheSecurityGroups>`_ **Request Syntax** :: response = client.describe_cache_security_groups( CacheSecurityGroupName='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'CacheSecurityGroups': [ { 'OwnerId': 'string', 'CacheSecurityGroupName': 'string', 'Description': 'string', 'EC2SecurityGroups': [ { 'Status': 'string', 'EC2SecurityGroupName': 'string', 'EC2SecurityGroupOwnerId': 'string' }, ] }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeCacheSecurityGroups`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **CacheSecurityGroups** *(list) --* A list of cache security groups. Each element in the list contains detailed information about one group. - *(dict) --* Represents the output of one of the following operations: * ``AuthorizeCacheSecurityGroupIngress`` * ``CreateCacheSecurityGroup`` * ``RevokeCacheSecurityGroupIngress`` - **OwnerId** *(string) --* The AWS account ID of the cache security group owner. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Description** *(string) --* The description of the cache security group. - **EC2SecurityGroups** *(list) --* A list of Amazon EC2 security groups that are associated with this cache security group. - *(dict) --* Provides ownership and status information for an Amazon EC2 security group. - **Status** *(string) --* The status of the Amazon EC2 security group. - **EC2SecurityGroupName** *(string) --* The name of the Amazon EC2 security group. - **EC2SecurityGroupOwnerId** *(string) --* The AWS account ID of the Amazon EC2 security group owner. :type CacheSecurityGroupName: string :param CacheSecurityGroupName: The name of the cache security group to return details for. :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_cache_subnet_groups(self, CacheSubnetGroupName: str = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns a list of cache subnet group descriptions. If a subnet group name is specified, the list contains only the description of that group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeCacheSubnetGroups>`_ **Request Syntax** :: response = client.describe_cache_subnet_groups( CacheSubnetGroupName='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'CacheSubnetGroups': [ { 'CacheSubnetGroupName': 'string', 'CacheSubnetGroupDescription': 'string', 'VpcId': 'string', 'Subnets': [ { 'SubnetIdentifier': 'string', 'SubnetAvailabilityZone': { 'Name': 'string' } }, ] }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeCacheSubnetGroups`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **CacheSubnetGroups** *(list) --* A list of cache subnet groups. Each element in the list contains detailed information about one group. - *(dict) --* Represents the output of one of the following operations: * ``CreateCacheSubnetGroup`` * ``ModifyCacheSubnetGroup`` - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group. - **CacheSubnetGroupDescription** *(string) --* The description of the cache subnet group. - **VpcId** *(string) --* The Amazon Virtual Private Cloud identifier (VPC ID) of the cache subnet group. - **Subnets** *(list) --* A list of subnets associated with the cache subnet group. - *(dict) --* Represents the subnet associated with a cluster. This parameter refers to subnets defined in Amazon Virtual Private Cloud (Amazon VPC) and used with ElastiCache. - **SubnetIdentifier** *(string) --* The unique identifier for the subnet. - **SubnetAvailabilityZone** *(dict) --* The Availability Zone associated with the subnet. - **Name** *(string) --* The name of the Availability Zone. :type CacheSubnetGroupName: string :param CacheSubnetGroupName: The name of the cache subnet group to return details for. :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_engine_default_parameters(self, CacheParameterGroupFamily: str, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns the default engine and system parameter information for the specified cache engine. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeEngineDefaultParameters>`_ **Request Syntax** :: response = client.describe_engine_default_parameters( CacheParameterGroupFamily='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'EngineDefaults': { 'CacheParameterGroupFamily': 'string', 'Marker': 'string', 'Parameters': [ { 'ParameterName': 'string', 'ParameterValue': 'string', 'Description': 'string', 'Source': 'string', 'DataType': 'string', 'AllowedValues': 'string', 'IsModifiable': True|False, 'MinimumEngineVersion': 'string', 'ChangeType': 'immediate'|'requires-reboot' }, ], 'CacheNodeTypeSpecificParameters': [ { 'ParameterName': 'string', 'Description': 'string', 'Source': 'string', 'DataType': 'string', 'AllowedValues': 'string', 'IsModifiable': True|False, 'MinimumEngineVersion': 'string', 'CacheNodeTypeSpecificValues': [ { 'CacheNodeType': 'string', 'Value': 'string' }, ], 'ChangeType': 'immediate'|'requires-reboot' }, ] } } **Response Structure** - *(dict) --* - **EngineDefaults** *(dict) --* Represents the output of a ``DescribeEngineDefaultParameters`` operation. - **CacheParameterGroupFamily** *(string) --* Specifies the name of the cache parameter group family to which the engine default parameters apply. Valid values are: ``memcached1.4`` | ``redis2.6`` | ``redis2.8`` | ``redis3.2`` | ``redis4.0`` - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **Parameters** *(list) --* Contains a list of engine default parameters. - *(dict) --* Describes an individual setting that controls some aspect of ElastiCache behavior. - **ParameterName** *(string) --* The name of the parameter. - **ParameterValue** *(string) --* The value of the parameter. - **Description** *(string) --* A description of the parameter. - **Source** *(string) --* The source of the parameter. - **DataType** *(string) --* The valid data type for the parameter. - **AllowedValues** *(string) --* The valid range of values for the parameter. - **IsModifiable** *(boolean) --* Indicates whether (``true`` ) or not (``false`` ) the parameter can be modified. Some parameters have security or operational implications that prevent them from being changed. - **MinimumEngineVersion** *(string) --* The earliest cache engine version to which the parameter can apply. - **ChangeType** *(string) --* Indicates whether a change to the parameter is applied immediately or requires a reboot for the change to be applied. You can force a reboot or wait until the next maintenance window's reboot. For more information, see `Rebooting a Cluster <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Clusters.Rebooting.html>`__ . - **CacheNodeTypeSpecificParameters** *(list) --* A list of parameters specific to a particular cache node type. Each element in the list contains detailed information about one parameter. - *(dict) --* A parameter that has a different value for each cache node type it is applied to. For example, in a Redis cluster, a ``cache.m1.large`` cache node type would have a larger ``maxmemory`` value than a ``cache.m1.small`` type. - **ParameterName** *(string) --* The name of the parameter. - **Description** *(string) --* A description of the parameter. - **Source** *(string) --* The source of the parameter value. - **DataType** *(string) --* The valid data type for the parameter. - **AllowedValues** *(string) --* The valid range of values for the parameter. - **IsModifiable** *(boolean) --* Indicates whether (``true`` ) or not (``false`` ) the parameter can be modified. Some parameters have security or operational implications that prevent them from being changed. - **MinimumEngineVersion** *(string) --* The earliest cache engine version to which the parameter can apply. - **CacheNodeTypeSpecificValues** *(list) --* A list of cache node types and their corresponding values for this parameter. - *(dict) --* A value that applies only to a certain cache node type. - **CacheNodeType** *(string) --* The cache node type for which this value applies. - **Value** *(string) --* The value for the cache node type. - **ChangeType** *(string) --* Indicates whether a change to the parameter is applied immediately or requires a reboot for the change to be applied. You can force a reboot or wait until the next maintenance window's reboot. For more information, see `Rebooting a Cluster <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Clusters.Rebooting.html>`__ . :type CacheParameterGroupFamily: string :param CacheParameterGroupFamily: **[REQUIRED]** The name of the cache parameter group family. Valid values are: ``memcached1.4`` | ``redis2.6`` | ``redis2.8`` | ``redis3.2`` | ``redis4.0`` :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_events(self, SourceIdentifier: str = None, SourceType: str = None, StartTime: datetime = None, EndTime: datetime = None, Duration: int = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns events related to clusters, cache security groups, and cache parameter groups. You can obtain events specific to a particular cluster, cache security group, or cache parameter group by providing the name as a parameter. By default, only the events occurring within the last hour are returned; however, you can retrieve up to 14 days' worth of events if necessary. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeEvents>`_ **Request Syntax** :: response = client.describe_events( SourceIdentifier='string', SourceType='cache-cluster'|'cache-parameter-group'|'cache-security-group'|'cache-subnet-group'|'replication-group', StartTime=datetime(2015, 1, 1), EndTime=datetime(2015, 1, 1), Duration=123, MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'Events': [ { 'SourceIdentifier': 'string', 'SourceType': 'cache-cluster'|'cache-parameter-group'|'cache-security-group'|'cache-subnet-group'|'replication-group', 'Message': 'string', 'Date': datetime(2015, 1, 1) }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeEvents`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **Events** *(list) --* A list of events. Each element in the list contains detailed information about one event. - *(dict) --* Represents a single occurrence of something interesting within the system. Some examples of events are creating a cluster, adding or removing a cache node, or rebooting a node. - **SourceIdentifier** *(string) --* The identifier for the source of the event. For example, if the event occurred at the cluster level, the identifier would be the name of the cluster. - **SourceType** *(string) --* Specifies the origin of this event - a cluster, a parameter group, a security group, etc. - **Message** *(string) --* The text of the event. - **Date** *(datetime) --* The date and time when the event occurred. :type SourceIdentifier: string :param SourceIdentifier: The identifier of the event source for which events are returned. If not specified, all sources are included in the response. :type SourceType: string :param SourceType: The event source to retrieve events for. If no value is specified, all events are returned. :type StartTime: datetime :param StartTime: The beginning of the time interval to retrieve events for, specified in ISO 8601 format. **Example:** 2017-03-30T07:03:49.555Z :type EndTime: datetime :param EndTime: The end of the time interval for which to retrieve events, specified in ISO 8601 format. **Example:** 2017-03-30T07:03:49.555Z :type Duration: integer :param Duration: The number of minutes worth of events to retrieve. :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_replication_groups(self, ReplicationGroupId: str = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns information about a particular replication group. If no identifier is specified, ``DescribeReplicationGroups`` returns information about all replication groups. .. note:: This operation is valid for Redis only. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeReplicationGroups>`_ **Request Syntax** :: response = client.describe_replication_groups( ReplicationGroupId='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'ReplicationGroups': [ { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeReplicationGroups`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **ReplicationGroups** *(list) --* A list of replication groups. Each item in the list contains detailed information about one replication group. - *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: The identifier for the replication group to be described. This parameter is not case sensitive. If you do not specify this parameter, information about all replication groups is returned. :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_reserved_cache_nodes(self, ReservedCacheNodeId: str = None, ReservedCacheNodesOfferingId: str = None, CacheNodeType: str = None, Duration: str = None, ProductDescription: str = None, OfferingType: str = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Returns information about reserved cache nodes for this account, or about a specified reserved cache node. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeReservedCacheNodes>`_ **Request Syntax** :: response = client.describe_reserved_cache_nodes( ReservedCacheNodeId='string', ReservedCacheNodesOfferingId='string', CacheNodeType='string', Duration='string', ProductDescription='string', OfferingType='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'ReservedCacheNodes': [ { 'ReservedCacheNodeId': 'string', 'ReservedCacheNodesOfferingId': 'string', 'CacheNodeType': 'string', 'StartTime': datetime(2015, 1, 1), 'Duration': 123, 'FixedPrice': 123.0, 'UsagePrice': 123.0, 'CacheNodeCount': 123, 'ProductDescription': 'string', 'OfferingType': 'string', 'State': 'string', 'RecurringCharges': [ { 'RecurringChargeAmount': 123.0, 'RecurringChargeFrequency': 'string' }, ], 'ReservationARN': 'string' }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeReservedCacheNodes`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **ReservedCacheNodes** *(list) --* A list of reserved cache nodes. Each element in the list contains detailed information about one node. - *(dict) --* Represents the output of a ``PurchaseReservedCacheNodesOffering`` operation. - **ReservedCacheNodeId** *(string) --* The unique identifier for the reservation. - **ReservedCacheNodesOfferingId** *(string) --* The offering identifier. - **CacheNodeType** *(string) --* The cache node type for the reserved cache nodes. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **StartTime** *(datetime) --* The time the reservation started. - **Duration** *(integer) --* The duration of the reservation in seconds. - **FixedPrice** *(float) --* The fixed price charged for this reserved cache node. - **UsagePrice** *(float) --* The hourly price charged for this reserved cache node. - **CacheNodeCount** *(integer) --* The number of cache nodes that have been reserved. - **ProductDescription** *(string) --* The description of the reserved cache node. - **OfferingType** *(string) --* The offering type of this reserved cache node. - **State** *(string) --* The state of the reserved cache node. - **RecurringCharges** *(list) --* The recurring price charged to run this reserved cache node. - *(dict) --* Contains the specific price and frequency of a recurring charges for a reserved cache node, or for a reserved cache node offering. - **RecurringChargeAmount** *(float) --* The monetary amount of the recurring charge. - **RecurringChargeFrequency** *(string) --* The frequency of the recurring charge. - **ReservationARN** *(string) --* The Amazon Resource Name (ARN) of the reserved cache node. Example: ``arn:aws:elasticache:us-east-1:123456789012:reserved-instance:ri-2017-03-27-08-33-25-582`` :type ReservedCacheNodeId: string :param ReservedCacheNodeId: The reserved cache node identifier filter value. Use this parameter to show only the reservation that matches the specified reservation ID. :type ReservedCacheNodesOfferingId: string :param ReservedCacheNodesOfferingId: The offering identifier filter value. Use this parameter to show only purchased reservations matching the specified offering identifier. :type CacheNodeType: string :param CacheNodeType: The cache node type filter value. Use this parameter to show only those reservations matching the specified cache node type. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ :type Duration: string :param Duration: The duration filter value, specified in years or seconds. Use this parameter to show only reservations for this duration. Valid Values: ``1 | 3 | 31536000 | 94608000`` :type ProductDescription: string :param ProductDescription: The product description filter value. Use this parameter to show only those reservations matching the specified product description. :type OfferingType: string :param OfferingType: The offering type filter value. Use this parameter to show only the available offerings matching the specified offering type. Valid values: ``\"Light Utilization\"|\"Medium Utilization\"|\"Heavy Utilization\"`` :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_reserved_cache_nodes_offerings(self, ReservedCacheNodesOfferingId: str = None, CacheNodeType: str = None, Duration: str = None, ProductDescription: str = None, OfferingType: str = None, MaxRecords: int = None, Marker: str = None) -> Dict: """ Lists available reserved cache node offerings. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeReservedCacheNodesOfferings>`_ **Request Syntax** :: response = client.describe_reserved_cache_nodes_offerings( ReservedCacheNodesOfferingId='string', CacheNodeType='string', Duration='string', ProductDescription='string', OfferingType='string', MaxRecords=123, Marker='string' ) **Response Syntax** :: { 'Marker': 'string', 'ReservedCacheNodesOfferings': [ { 'ReservedCacheNodesOfferingId': 'string', 'CacheNodeType': 'string', 'Duration': 123, 'FixedPrice': 123.0, 'UsagePrice': 123.0, 'ProductDescription': 'string', 'OfferingType': 'string', 'RecurringCharges': [ { 'RecurringChargeAmount': 123.0, 'RecurringChargeFrequency': 'string' }, ] }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeReservedCacheNodesOfferings`` operation. - **Marker** *(string) --* Provides an identifier to allow retrieval of paginated results. - **ReservedCacheNodesOfferings** *(list) --* A list of reserved cache node offerings. Each element in the list contains detailed information about one offering. - *(dict) --* Describes all of the attributes of a reserved cache node offering. - **ReservedCacheNodesOfferingId** *(string) --* A unique identifier for the reserved cache node offering. - **CacheNodeType** *(string) --* The cache node type for the reserved cache node. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Duration** *(integer) --* The duration of the offering. in seconds. - **FixedPrice** *(float) --* The fixed price charged for this offering. - **UsagePrice** *(float) --* The hourly price charged for this offering. - **ProductDescription** *(string) --* The cache engine used by the offering. - **OfferingType** *(string) --* The offering type. - **RecurringCharges** *(list) --* The recurring price charged to run this reserved cache node. - *(dict) --* Contains the specific price and frequency of a recurring charges for a reserved cache node, or for a reserved cache node offering. - **RecurringChargeAmount** *(float) --* The monetary amount of the recurring charge. - **RecurringChargeFrequency** *(string) --* The frequency of the recurring charge. :type ReservedCacheNodesOfferingId: string :param ReservedCacheNodesOfferingId: The offering identifier filter value. Use this parameter to show only the available offering that matches the specified reservation identifier. Example: ``438012d3-4052-4cc7-b2e3-8d3372e0e706`` :type CacheNodeType: string :param CacheNodeType: The cache node type filter value. Use this parameter to show only the available offerings matching the specified cache node type. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ :type Duration: string :param Duration: Duration filter value, specified in years or seconds. Use this parameter to show only reservations for a given duration. Valid Values: ``1 | 3 | 31536000 | 94608000`` :type ProductDescription: string :param ProductDescription: The product description filter value. Use this parameter to show only the available offerings matching the specified product description. :type OfferingType: string :param OfferingType: The offering type filter value. Use this parameter to show only the available offerings matching the specified offering type. Valid Values: ``\"Light Utilization\"|\"Medium Utilization\"|\"Heavy Utilization\"`` :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 100 Constraints: minimum 20; maximum 100. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :rtype: dict :returns: """ pass def describe_snapshots(self, ReplicationGroupId: str = None, CacheClusterId: str = None, SnapshotName: str = None, SnapshotSource: str = None, Marker: str = None, MaxRecords: int = None, ShowNodeGroupConfig: bool = None) -> Dict: """ Returns information about cluster or replication group snapshots. By default, ``DescribeSnapshots`` lists all of your snapshots; it can optionally describe a single snapshot, or just the snapshots associated with a particular cache cluster. .. note:: This operation is valid for Redis only. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/DescribeSnapshots>`_ **Request Syntax** :: response = client.describe_snapshots( ReplicationGroupId='string', CacheClusterId='string', SnapshotName='string', SnapshotSource='string', Marker='string', MaxRecords=123, ShowNodeGroupConfig=True|False ) **Response Syntax** :: { 'Marker': 'string', 'Snapshots': [ { 'SnapshotName': 'string', 'ReplicationGroupId': 'string', 'ReplicationGroupDescription': 'string', 'CacheClusterId': 'string', 'SnapshotStatus': 'string', 'SnapshotSource': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'TopicArn': 'string', 'Port': 123, 'CacheParameterGroupName': 'string', 'CacheSubnetGroupName': 'string', 'VpcId': 'string', 'AutoMinorVersionUpgrade': True|False, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'NumNodeGroups': 123, 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'NodeSnapshots': [ { 'CacheClusterId': 'string', 'NodeGroupId': 'string', 'CacheNodeId': 'string', 'NodeGroupConfiguration': { 'NodeGroupId': 'string', 'Slots': 'string', 'ReplicaCount': 123, 'PrimaryAvailabilityZone': 'string', 'ReplicaAvailabilityZones': [ 'string', ] }, 'CacheSize': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'SnapshotCreateTime': datetime(2015, 1, 1) }, ] }, ] } **Response Structure** - *(dict) --* Represents the output of a ``DescribeSnapshots`` operation. - **Marker** *(string) --* An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . - **Snapshots** *(list) --* A list of snapshots. Each item in the list contains detailed information about one snapshot. - *(dict) --* Represents a copy of an entire Redis cluster as of the time when the snapshot was taken. - **SnapshotName** *(string) --* The name of a snapshot. For an automatic snapshot, the name is system-generated. For a manual snapshot, this is the user-provided name. - **ReplicationGroupId** *(string) --* The unique identifier of the source replication group. - **ReplicationGroupDescription** *(string) --* A description of the source replication group. - **CacheClusterId** *(string) --* The user-supplied identifier of the source cluster. - **SnapshotStatus** *(string) --* The status of the snapshot. Valid values: ``creating`` | ``available`` | ``restoring`` | ``copying`` | ``deleting`` . - **SnapshotSource** *(string) --* Indicates whether the snapshot is from an automatic backup (``automated`` ) or was created manually (``manual`` ). - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the source cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) used by the source cluster. - **EngineVersion** *(string) --* The version of the cache engine version that is used by the source cluster. - **NumCacheNodes** *(integer) --* The number of cache nodes in the source cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the source cluster is located. - **CacheClusterCreateTime** *(datetime) --* The date and time when the source cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **TopicArn** *(string) --* The Amazon Resource Name (ARN) for the topic used by the source cluster for publishing notifications. - **Port** *(integer) --* The port number used by each cache nodes in the source cluster. - **CacheParameterGroupName** *(string) --* The cache parameter group that is associated with the source cluster. - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the source cluster. - **VpcId** *(string) --* The Amazon Virtual Private Cloud identifier (VPC ID) of the cache subnet group for the source cluster. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SnapshotRetentionLimit** *(integer) --* For an automatic snapshot, the number of days for which ElastiCache retains the snapshot before deleting it. For manual snapshots, this field reflects the ``SnapshotRetentionLimit`` for the source cluster when the snapshot was created. This field is otherwise ignored: Manual snapshots do not expire, and can only be deleted using the ``DeleteSnapshot`` operation. **Important** If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range during which ElastiCache takes daily snapshots of the source cluster. - **NumNodeGroups** *(integer) --* The number of node groups (shards) in this snapshot. When restoring from a snapshot, the number of node groups (shards) in the snapshot and in the restored replication group must be the same. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for the source Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **NodeSnapshots** *(list) --* A list of the cache nodes in the source cluster. - *(dict) --* Represents an individual cache node in a snapshot of a cluster. - **CacheClusterId** *(string) --* A unique identifier for the source cluster. - **NodeGroupId** *(string) --* A unique identifier for the source node group (shard). - **CacheNodeId** *(string) --* The cache node identifier for the node in the source cluster. - **NodeGroupConfiguration** *(dict) --* The configuration for the source node group (shard). - **NodeGroupId** *(string) --* The 4-digit id for the node group these configuration values apply to. - **Slots** *(string) --* A string that specifies the keyspace for a particular node group. Keyspaces range from 0 to 16,383. The string is in the format ``startkey-endkey`` . Example: ``"0-3999"`` - **ReplicaCount** *(integer) --* The number of read replica nodes in this node group (shard). - **PrimaryAvailabilityZone** *(string) --* The Availability Zone where the primary node of this node group (shard) is launched. - **ReplicaAvailabilityZones** *(list) --* A list of Availability Zones to be used for the read replicas. The number of Availability Zones in this list must match the value of ``ReplicaCount`` or ``ReplicasPerNodeGroup`` if not specified. - *(string) --* - **CacheSize** *(string) --* The size of the cache on the source cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created in the source cluster. - **SnapshotCreateTime** *(datetime) --* The date and time when the source node's metadata and cache data set was obtained for the snapshot. :type ReplicationGroupId: string :param ReplicationGroupId: A user-supplied replication group identifier. If this parameter is specified, only snapshots associated with that specific replication group are described. :type CacheClusterId: string :param CacheClusterId: A user-supplied cluster identifier. If this parameter is specified, only snapshots associated with that specific cluster are described. :type SnapshotName: string :param SnapshotName: A user-supplied name of the snapshot. If this parameter is specified, only this snapshot are described. :type SnapshotSource: string :param SnapshotSource: If set to ``system`` , the output shows snapshots that were automatically created by ElastiCache. If set to ``user`` the output shows snapshots that were manually created. If omitted, the output shows both automatically and manually created snapshots. :type Marker: string :param Marker: An optional marker returned from a prior request. Use this marker for pagination of results from this operation. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by ``MaxRecords`` . :type MaxRecords: integer :param MaxRecords: The maximum number of records to include in the response. If more records exist than the specified ``MaxRecords`` value, a marker is included in the response so that the remaining results can be retrieved. Default: 50 Constraints: minimum 20; maximum 50. :type ShowNodeGroupConfig: boolean :param ShowNodeGroupConfig: A Boolean value which if true, the node group (shard) configuration is included in the snapshot description. :rtype: dict :returns: """ pass def generate_presigned_url(self, ClientMethod: str = None, Params: Dict = None, ExpiresIn: int = None, HttpMethod: str = 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 ``ClientMethod``. :type ExpiresIn: int :param ExpiresIn: The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds) :type HttpMethod: string :param HttpMethod: The http method to use on the generated url. By default, the http method is whatever is used in the method\'s model. :returns: The presigned url """ pass def get_paginator(self, operation_name: str = None) -> Paginator: """ Create a paginator for an operation. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :raise OperationNotPageableError: Raised if the operation is not pageable. You can use the ``client.can_paginate`` method to check if an operation is pageable. :rtype: L{botocore.paginate.Paginator} :return: A paginator object. """ pass def get_waiter(self, waiter_name: str = None) -> Waiter: """ 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 section of the service docs for a list of available waiters. :returns: The specified waiter object. :rtype: botocore.waiter.Waiter """ pass def increase_replica_count(self, ReplicationGroupId: str, ApplyImmediately: bool, NewReplicaCount: int = None, ReplicaConfiguration: List = None) -> Dict: """ Dynamically increases the number of replics in a Redis (cluster mode disabled) replication group or the number of replica nodes in one or more node groups (shards) of a Redis (cluster mode enabled) replication group. This operation is performed with no cluster down time. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/IncreaseReplicaCount>`_ **Request Syntax** :: response = client.increase_replica_count( ReplicationGroupId='string', NewReplicaCount=123, ReplicaConfiguration=[ { 'NodeGroupId': 'string', 'NewReplicaCount': 123, 'PreferredAvailabilityZones': [ 'string', ] }, ], ApplyImmediately=True|False ) **Response Syntax** :: { 'ReplicationGroup': { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **ReplicationGroup** *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: **[REQUIRED]** The id of the replication group to which you want to add replica nodes. :type NewReplicaCount: integer :param NewReplicaCount: The number of read replica nodes you want at the completion of this operation. For Redis (cluster mode disabled) replication groups, this is the number of replica nodes in the replication group. For Redis (cluster mode enabled) replication groups, this is the number of replica nodes in each of the replication group\'s node groups. :type ReplicaConfiguration: list :param ReplicaConfiguration: A list of ``ConfigureShard`` objects that can be used to configure each shard in a Redis (cluster mode enabled) replication group. The ``ConfigureShard`` has three members: ``NewReplicaCount`` , ``NodeGroupId`` , and ``PreferredAvailabilityZones`` . - *(dict) --* Node group (shard) configuration options when adding or removing replicas. Each node group (shard) configuration has the following members: NodeGroupId, NewReplicaCount, and PreferredAvailabilityZones. - **NodeGroupId** *(string) --* **[REQUIRED]** The 4-digit id for the node group you are configuring. For Redis (cluster mode disabled) replication groups, the node group id is always 0001. To find a Redis (cluster mode enabled)\'s node group\'s (shard\'s) id, see `Finding a Shard\'s Id <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/shard-find-id.html>`__ . - **NewReplicaCount** *(integer) --* **[REQUIRED]** The number of replicas you want in this node group at the end of this operation. The maximum value for ``NewReplicaCount`` is 5. The minimum value depends upon the type of Redis replication group you are working with. The minimum number of replicas in a shard or replication group is: * Redis (cluster mode disabled) * If Multi-AZ with Automatic Failover is enabled: 1 * If Multi-AZ with Automatic Failover is not enable: 0 * Redis (cluster mode enabled): 0 (though you will not be able to failover to a replica if your primary node fails) - **PreferredAvailabilityZones** *(list) --* A list of ``PreferredAvailabilityZone`` strings that specify which availability zones the replication group\'s nodes are to be in. The nummber of ``PreferredAvailabilityZone`` values must equal the value of ``NewReplicaCount`` plus 1 to account for the primary node. If this member of ``ReplicaConfiguration`` is omitted, ElastiCache for Redis selects the availability zone for each of the replicas. - *(string) --* :type ApplyImmediately: boolean :param ApplyImmediately: **[REQUIRED]** If ``True`` , the number of replica nodes is increased immediately. If ``False`` , the number of replica nodes is increased during the next maintenance window. :rtype: dict :returns: """ pass def list_allowed_node_type_modifications(self, CacheClusterId: str = None, ReplicationGroupId: str = None) -> Dict: """ Lists all available node types that you can scale your Redis cluster's or replication group's current node type up to. When you use the ``ModifyCacheCluster`` or ``ModifyReplicationGroup`` operations to scale up your cluster or replication group, the value of the ``CacheNodeType`` parameter must be one of the node types returned by this operation. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ListAllowedNodeTypeModifications>`_ **Request Syntax** :: response = client.list_allowed_node_type_modifications( CacheClusterId='string', ReplicationGroupId='string' ) **Response Syntax** :: { 'ScaleUpModifications': [ 'string', ] } **Response Structure** - *(dict) --* Represents the allowed node types you can use to modify your cluster or replication group. - **ScaleUpModifications** *(list) --* A string list, each element of which specifies a cache node type which you can use to scale your cluster or replication group. When scaling up a Redis cluster or replication group using ``ModifyCacheCluster`` or ``ModifyReplicationGroup`` , use a value from this list for the ``CacheNodeType`` parameter. - *(string) --* :type CacheClusterId: string :param CacheClusterId: The name of the cluster you want to scale up to a larger node instanced type. ElastiCache uses the cluster id to identify the current node type of this cluster and from that to create a list of node types you can scale up to. .. warning:: You must provide a value for either the ``CacheClusterId`` or the ``ReplicationGroupId`` . :type ReplicationGroupId: string :param ReplicationGroupId: The name of the replication group want to scale up to a larger node type. ElastiCache uses the replication group id to identify the current node type being used by this replication group, and from that to create a list of node types you can scale up to. .. warning:: You must provide a value for either the ``CacheClusterId`` or the ``ReplicationGroupId`` . :rtype: dict :returns: """ pass def list_tags_for_resource(self, ResourceName: str) -> Dict: """ Lists all cost allocation tags currently on the named resource. A ``cost allocation tag`` is a key-value pair where the key is case-sensitive and the value is optional. You can use cost allocation tags to categorize and track your AWS costs. If the cluster is not in the *available* state, ``ListTagsForResource`` returns an error. You can have a maximum of 50 cost allocation tags on an ElastiCache resource. For more information, see `Monitoring Costs with Tags <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Tagging.html>`__ . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ListTagsForResource>`_ **Request Syntax** :: response = client.list_tags_for_resource( ResourceName='string' ) **Response Syntax** :: { 'TagList': [ { 'Key': 'string', 'Value': 'string' }, ] } **Response Structure** - *(dict) --* Represents the output from the ``AddTagsToResource`` , ``ListTagsForResource`` , and ``RemoveTagsFromResource`` operations. - **TagList** *(list) --* A list of cost allocation tags as key-value pairs. - *(dict) --* A cost allocation Tag that can be added to an ElastiCache cluster or replication group. Tags are composed of a Key/Value pair. A tag with a null Value is permitted. - **Key** *(string) --* The key for the tag. May not be null. - **Value** *(string) --* The tag's value. May be null. :type ResourceName: string :param ResourceName: **[REQUIRED]** The Amazon Resource Name (ARN) of the resource for which you want the list of tags, for example ``arn:aws:elasticache:us-west-2:0123456789:cluster:myCluster`` or ``arn:aws:elasticache:us-west-2:0123456789:snapshot:mySnapshot`` . For more information about ARNs, see `Amazon Resource Names (ARNs) and AWS Service Namespaces <http://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html>`__ . :rtype: dict :returns: """ pass def modify_cache_cluster(self, CacheClusterId: str, NumCacheNodes: int = None, CacheNodeIdsToRemove: List = None, AZMode: str = None, NewAvailabilityZones: List = None, CacheSecurityGroupNames: List = None, SecurityGroupIds: List = None, PreferredMaintenanceWindow: str = None, NotificationTopicArn: str = None, CacheParameterGroupName: str = None, NotificationTopicStatus: str = None, ApplyImmediately: bool = None, EngineVersion: str = None, AutoMinorVersionUpgrade: bool = None, SnapshotRetentionLimit: int = None, SnapshotWindow: str = None, CacheNodeType: str = None) -> Dict: """ Modifies the settings for a cluster. You can use this operation to change one or more cluster configuration parameters by specifying the parameters and the new values. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ModifyCacheCluster>`_ **Request Syntax** :: response = client.modify_cache_cluster( CacheClusterId='string', NumCacheNodes=123, CacheNodeIdsToRemove=[ 'string', ], AZMode='single-az'|'cross-az', NewAvailabilityZones=[ 'string', ], CacheSecurityGroupNames=[ 'string', ], SecurityGroupIds=[ 'string', ], PreferredMaintenanceWindow='string', NotificationTopicArn='string', CacheParameterGroupName='string', NotificationTopicStatus='string', ApplyImmediately=True|False, EngineVersion='string', AutoMinorVersionUpgrade=True|False, SnapshotRetentionLimit=123, SnapshotWindow='string', CacheNodeType='string' ) **Response Syntax** :: { 'CacheCluster': { 'CacheClusterId': 'string', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'ClientDownloadLandingPage': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'CacheClusterStatus': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'PendingModifiedValues': { 'NumCacheNodes': 123, 'CacheNodeIdsToRemove': [ 'string', ], 'EngineVersion': 'string', 'CacheNodeType': 'string' }, 'NotificationConfiguration': { 'TopicArn': 'string', 'TopicStatus': 'string' }, 'CacheSecurityGroups': [ { 'CacheSecurityGroupName': 'string', 'Status': 'string' }, ], 'CacheParameterGroup': { 'CacheParameterGroupName': 'string', 'ParameterApplyStatus': 'string', 'CacheNodeIdsToReboot': [ 'string', ] }, 'CacheSubnetGroupName': 'string', 'CacheNodes': [ { 'CacheNodeId': 'string', 'CacheNodeStatus': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'Endpoint': { 'Address': 'string', 'Port': 123 }, 'ParameterGroupStatus': 'string', 'SourceCacheNodeId': 'string', 'CustomerAvailabilityZone': 'string' }, ], 'AutoMinorVersionUpgrade': True|False, 'SecurityGroups': [ { 'SecurityGroupId': 'string', 'Status': 'string' }, ], 'ReplicationGroupId': 'string', 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **CacheCluster** *(dict) --* Contains all of the attributes of a specific cluster. - **CacheClusterId** *(string) --* The user-supplied identifier of the cluster. This identifier is a unique key that identifies a cluster. - **ConfigurationEndpoint** *(dict) --* Represents a Memcached cluster endpoint which, if Automatic Discovery is enabled on the cluster, can be used by an application to connect to any node in the cluster. The configuration endpoint will always have ``.cfg`` in it. Example: ``mem-3.9dvc4r.cfg.usw2.cache.amazonaws.com:11211`` - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ClientDownloadLandingPage** *(string) --* The URL of the web page where you can download the latest ElastiCache client library. - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) to be used for this cluster. - **EngineVersion** *(string) --* The version of the cache engine that is used in this cluster. - **CacheClusterStatus** *(string) --* The current state of this cluster, one of the following values: ``available`` , ``creating`` , ``deleted`` , ``deleting`` , ``incompatible-network`` , ``modifying`` , ``rebooting cluster nodes`` , ``restore-failed`` , or ``snapshotting`` . - **NumCacheNodes** *(integer) --* The number of cache nodes in the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the cluster is located or "Multiple" if the cache nodes are located in different Availability Zones. - **CacheClusterCreateTime** *(datetime) --* The date and time when the cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **PendingModifiedValues** *(dict) --* A group of settings that are applied to the cluster in the future, or that are currently being applied. - **NumCacheNodes** *(integer) --* The new number of cache nodes for the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **CacheNodeIdsToRemove** *(list) --* A list of cache node IDs that are being removed (or will be removed) from the cluster. A node ID is a 4-digit numeric identifier (0001, 0002, etc.). - *(string) --* - **EngineVersion** *(string) --* The new cache engine version that the cluster runs. - **CacheNodeType** *(string) --* The cache node type that this cluster or replication group is scaled to. - **NotificationConfiguration** *(dict) --* Describes a notification topic and its status. Notification topics are used for publishing ElastiCache events to subscribers using Amazon Simple Notification Service (SNS). - **TopicArn** *(string) --* The Amazon Resource Name (ARN) that identifies the topic. - **TopicStatus** *(string) --* The current state of the topic. - **CacheSecurityGroups** *(list) --* A list of cache security group elements, composed of name and status sub-elements. - *(dict) --* Represents a cluster's status within a particular cache security group. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Status** *(string) --* The membership status in the cache security group. The status changes when a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **CacheParameterGroup** *(dict) --* Status of the cache parameter group. - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. - **ParameterApplyStatus** *(string) --* The status of parameter updates. - **CacheNodeIdsToReboot** *(list) --* A list of the cache node IDs which need to be rebooted for parameter changes to be applied. A node ID is a numeric identifier (0001, 0002, etc.). - *(string) --* - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the cluster. - **CacheNodes** *(list) --* A list of cache nodes that are members of the cluster. - *(dict) --* Represents an individual cache node within a cluster. Each cache node runs its own instance of the cluster's protocol-compliant caching software - either Memcached or Redis. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **CacheNodeId** *(string) --* The cache node identifier. A node ID is a numeric identifier (0001, 0002, etc.). The combination of cluster ID and node ID uniquely identifies every cache node used in a customer's AWS account. - **CacheNodeStatus** *(string) --* The current state of this cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created. - **Endpoint** *(dict) --* The hostname for connecting to this cache node. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ParameterGroupStatus** *(string) --* The status of the parameter group applied to this cache node. - **SourceCacheNodeId** *(string) --* The ID of the primary node to which this read replica node is synchronized. If this field is empty, this node is not associated with a primary cluster. - **CustomerAvailabilityZone** *(string) --* The Availability Zone where this node was created and now resides. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SecurityGroups** *(list) --* A list of VPC Security Groups associated with the cluster. - *(dict) --* Represents a single cache security group and its status. - **SecurityGroupId** *(string) --* The identifier of the cache security group. - **Status** *(string) --* The status of the cache security group membership. The status changes whenever a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **ReplicationGroupId** *(string) --* The replication group to which this cluster belongs. If this field is empty, the cluster is not associated with any replication group. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your cluster. Example: ``05:00-09:00`` - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable at-rest encryption on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type CacheClusterId: string :param CacheClusterId: **[REQUIRED]** The cluster identifier. This value is stored as a lowercase string. :type NumCacheNodes: integer :param NumCacheNodes: The number of cache nodes that the cluster should have. If the value for ``NumCacheNodes`` is greater than the sum of the number of current cache nodes and the number of cache nodes pending creation (which may be zero), more nodes are added. If the value is less than the number of existing cache nodes, nodes are removed. If the value is equal to the number of current cache nodes, any pending add or remove requests are canceled. If you are removing cache nodes, you must use the ``CacheNodeIdsToRemove`` parameter to provide the IDs of the specific cache nodes to remove. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. .. note:: Adding or removing Memcached cache nodes can be applied immediately or as a pending operation (see ``ApplyImmediately`` ). A pending operation to modify the number of cache nodes in a cluster during its maintenance window, whether by adding or removing nodes in accordance with the scale out architecture, is not queued. The customer\'s latest request to add or remove nodes to the cluster overrides any previous pending operations to modify the number of cache nodes in the cluster. For example, a request to remove 2 nodes would override a previous pending operation to remove 3 nodes. Similarly, a request to add 2 nodes would override a previous pending operation to remove 3 nodes and vice versa. As Memcached cache nodes may now be provisioned in different Availability Zones with flexible cache node placement, a request to add nodes does not automatically override a previous pending operation to add nodes. The customer can modify the previous pending operation to add more nodes or explicitly cancel the pending request and retry the new request. To cancel pending operations to modify the number of cache nodes in a cluster, use the ``ModifyCacheCluster`` request and set ``NumCacheNodes`` equal to the number of cache nodes currently in the cluster. :type CacheNodeIdsToRemove: list :param CacheNodeIdsToRemove: A list of cache node IDs to be removed. A node ID is a numeric identifier (0001, 0002, etc.). This parameter is only valid when ``NumCacheNodes`` is less than the existing number of cache nodes. The number of cache node IDs supplied in this parameter must match the difference between the existing number of cache nodes in the cluster or pending cache nodes, whichever is greater, and the value of ``NumCacheNodes`` in the request. For example: If you have 3 active cache nodes, 7 pending cache nodes, and the number of cache nodes in this ``ModifyCacheCluster`` call is 5, you must list 2 (7 - 5) cache node IDs to remove. - *(string) --* :type AZMode: string :param AZMode: Specifies whether the new nodes in this Memcached cluster are all created in a single Availability Zone or created across multiple Availability Zones. Valid values: ``single-az`` | ``cross-az`` . This option is only supported for Memcached clusters. .. note:: You cannot specify ``single-az`` if the Memcached cluster already has cache nodes in different Availability Zones. If ``cross-az`` is specified, existing Memcached nodes remain in their current Availability Zone. Only newly created nodes are located in different Availability Zones. For instructions on how to move existing Memcached nodes to different Availability Zones, see the **Availability Zone Considerations** section of `Cache Node Considerations for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/CacheNode.Memcached.html>`__ . :type NewAvailabilityZones: list :param NewAvailabilityZones: The list of Availability Zones where the new Memcached cache nodes are created. This parameter is only valid when ``NumCacheNodes`` in the request is greater than the sum of the number of active cache nodes and the number of cache nodes pending creation (which may be zero). The number of Availability Zones supplied in this list must match the cache nodes being added in this request. This option is only supported on Memcached clusters. Scenarios: * **Scenario 1:** You have 3 active nodes and wish to add 2 nodes. Specify ``NumCacheNodes=5`` (3 + 2) and optionally specify two Availability Zones for the two new nodes. * **Scenario 2:** You have 3 active nodes and 2 nodes pending creation (from the scenario 1 call) and want to add 1 more node. Specify ``NumCacheNodes=6`` ((3 + 2) + 1) and optionally specify an Availability Zone for the new node. * **Scenario 3:** You want to cancel all pending operations. Specify ``NumCacheNodes=3`` to cancel all pending operations. The Availability Zone placement of nodes pending creation cannot be modified. If you wish to cancel any nodes pending creation, add 0 nodes by setting ``NumCacheNodes`` to the number of current nodes. If ``cross-az`` is specified, existing Memcached nodes remain in their current Availability Zone. Only newly created nodes can be located in different Availability Zones. For guidance on how to move existing Memcached nodes to different Availability Zones, see the **Availability Zone Considerations** section of `Cache Node Considerations for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/CacheNode.Memcached.html>`__ . **Impact of new add/remove requests upon pending requests** * Scenario-1 * Pending Action: Delete * New Request: Delete * Result: The new delete, pending or immediate, replaces the pending delete. * Scenario-2 * Pending Action: Delete * New Request: Create * Result: The new create, pending or immediate, replaces the pending delete. * Scenario-3 * Pending Action: Create * New Request: Delete * Result: The new delete, pending or immediate, replaces the pending create. * Scenario-4 * Pending Action: Create * New Request: Create * Result: The new create is added to the pending create. .. warning:: **Important:** If the new create request is **Apply Immediately - Yes** , all creates are performed immediately. If the new create request is **Apply Immediately - No** , all creates are pending. - *(string) --* :type CacheSecurityGroupNames: list :param CacheSecurityGroupNames: A list of cache security group names to authorize on this cluster. This change is asynchronously applied as soon as possible. You can use this parameter only with clusters that are created outside of an Amazon Virtual Private Cloud (Amazon VPC). Constraints: Must contain no more than 255 alphanumeric characters. Must not be \"Default\". - *(string) --* :type SecurityGroupIds: list :param SecurityGroupIds: Specifies the VPC Security Groups associated with the cluster. This parameter can be used only with clusters that are created in an Amazon Virtual Private Cloud (Amazon VPC). - *(string) --* :type PreferredMaintenanceWindow: string :param PreferredMaintenanceWindow: Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` :type NotificationTopicArn: string :param NotificationTopicArn: The Amazon Resource Name (ARN) of the Amazon SNS topic to which notifications are sent. .. note:: The Amazon SNS topic owner must be same as the cluster owner. :type CacheParameterGroupName: string :param CacheParameterGroupName: The name of the cache parameter group to apply to this cluster. This change is asynchronously applied as soon as possible for parameters when the ``ApplyImmediately`` parameter is specified as ``true`` for this request. :type NotificationTopicStatus: string :param NotificationTopicStatus: The status of the Amazon SNS notification topic. Notifications are sent only if the status is ``active`` . Valid values: ``active`` | ``inactive`` :type ApplyImmediately: boolean :param ApplyImmediately: If ``true`` , this parameter causes the modifications in this request and any pending modifications to be applied, asynchronously and as soon as possible, regardless of the ``PreferredMaintenanceWindow`` setting for the cluster. If ``false`` , changes to the cluster are applied on the next maintenance reboot, or the next failure reboot, whichever occurs first. .. warning:: If you perform a ``ModifyCacheCluster`` before a pending modification is applied, the pending modification is replaced by the newer modification. Valid values: ``true`` | ``false`` Default: ``false`` :type EngineVersion: string :param EngineVersion: The upgraded version of the cache engine to be run on the cache nodes. **Important:** You can upgrade to a newer engine version (see `Selecting a Cache Engine and Version <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/SelectEngine.html#VersionManagement>`__ ), but you cannot downgrade to an earlier engine version. If you want to use an earlier engine version, you must delete the existing cluster and create it anew with the earlier engine version. :type AutoMinorVersionUpgrade: boolean :param AutoMinorVersionUpgrade: This parameter is currently disabled. :type SnapshotRetentionLimit: integer :param SnapshotRetentionLimit: The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. note:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. :type SnapshotWindow: string :param SnapshotWindow: The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your cluster. :type CacheNodeType: string :param CacheNodeType: A valid cache node type that you want to scale this cluster up to. :rtype: dict :returns: """ pass def modify_cache_parameter_group(self, CacheParameterGroupName: str, ParameterNameValues: List) -> Dict: """ Modifies the parameters of a cache parameter group. You can modify up to 20 parameters in a single request by submitting a list parameter name and value pairs. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ModifyCacheParameterGroup>`_ **Request Syntax** :: response = client.modify_cache_parameter_group( CacheParameterGroupName='string', ParameterNameValues=[ { 'ParameterName': 'string', 'ParameterValue': 'string' }, ] ) **Response Syntax** :: { 'CacheParameterGroupName': 'string' } **Response Structure** - *(dict) --* Represents the output of one of the following operations: * ``ModifyCacheParameterGroup`` * ``ResetCacheParameterGroup`` - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. :type CacheParameterGroupName: string :param CacheParameterGroupName: **[REQUIRED]** The name of the cache parameter group to modify. :type ParameterNameValues: list :param ParameterNameValues: **[REQUIRED]** An array of parameter names and values for the parameter update. You must supply at least one parameter name and value; subsequent arguments are optional. A maximum of 20 parameters may be modified per request. - *(dict) --* Describes a name-value pair that is used to update the value of a parameter. - **ParameterName** *(string) --* The name of the parameter. - **ParameterValue** *(string) --* The value of the parameter. :rtype: dict :returns: """ pass def modify_cache_subnet_group(self, CacheSubnetGroupName: str, CacheSubnetGroupDescription: str = None, SubnetIds: List = None) -> Dict: """ Modifies an existing cache subnet group. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ModifyCacheSubnetGroup>`_ **Request Syntax** :: response = client.modify_cache_subnet_group( CacheSubnetGroupName='string', CacheSubnetGroupDescription='string', SubnetIds=[ 'string', ] ) **Response Syntax** :: { 'CacheSubnetGroup': { 'CacheSubnetGroupName': 'string', 'CacheSubnetGroupDescription': 'string', 'VpcId': 'string', 'Subnets': [ { 'SubnetIdentifier': 'string', 'SubnetAvailabilityZone': { 'Name': 'string' } }, ] } } **Response Structure** - *(dict) --* - **CacheSubnetGroup** *(dict) --* Represents the output of one of the following operations: * ``CreateCacheSubnetGroup`` * ``ModifyCacheSubnetGroup`` - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group. - **CacheSubnetGroupDescription** *(string) --* The description of the cache subnet group. - **VpcId** *(string) --* The Amazon Virtual Private Cloud identifier (VPC ID) of the cache subnet group. - **Subnets** *(list) --* A list of subnets associated with the cache subnet group. - *(dict) --* Represents the subnet associated with a cluster. This parameter refers to subnets defined in Amazon Virtual Private Cloud (Amazon VPC) and used with ElastiCache. - **SubnetIdentifier** *(string) --* The unique identifier for the subnet. - **SubnetAvailabilityZone** *(dict) --* The Availability Zone associated with the subnet. - **Name** *(string) --* The name of the Availability Zone. :type CacheSubnetGroupName: string :param CacheSubnetGroupName: **[REQUIRED]** The name for the cache subnet group. This value is stored as a lowercase string. Constraints: Must contain no more than 255 alphanumeric characters or hyphens. Example: ``mysubnetgroup`` :type CacheSubnetGroupDescription: string :param CacheSubnetGroupDescription: A description of the cache subnet group. :type SubnetIds: list :param SubnetIds: The EC2 subnet IDs for the cache subnet group. - *(string) --* :rtype: dict :returns: """ pass def modify_replication_group(self, ReplicationGroupId: str, ReplicationGroupDescription: str = None, PrimaryClusterId: str = None, SnapshottingClusterId: str = None, AutomaticFailoverEnabled: bool = None, CacheSecurityGroupNames: List = None, SecurityGroupIds: List = None, PreferredMaintenanceWindow: str = None, NotificationTopicArn: str = None, CacheParameterGroupName: str = None, NotificationTopicStatus: str = None, ApplyImmediately: bool = None, EngineVersion: str = None, AutoMinorVersionUpgrade: bool = None, SnapshotRetentionLimit: int = None, SnapshotWindow: str = None, CacheNodeType: str = None, NodeGroupId: str = None) -> Dict: """ Modifies the settings for a replication group. For Redis (cluster mode enabled) clusters, this operation cannot be used to change a cluster's node type or engine version. For more information, see: * `Scaling for Amazon ElastiCache for Redis—Redis (cluster mode enabled) <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/scaling-redis-cluster-mode-enabled.html>`__ in the ElastiCache User Guide * `ModifyReplicationGroupShardConfiguration <http://docs.aws.amazon.com/AmazonElastiCache/latest/APIReference/API_ModifyReplicationGroupShardConfiguration.html>`__ in the ElastiCache API Reference .. note:: This operation is valid for Redis only. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ModifyReplicationGroup>`_ **Request Syntax** :: response = client.modify_replication_group( ReplicationGroupId='string', ReplicationGroupDescription='string', PrimaryClusterId='string', SnapshottingClusterId='string', AutomaticFailoverEnabled=True|False, CacheSecurityGroupNames=[ 'string', ], SecurityGroupIds=[ 'string', ], PreferredMaintenanceWindow='string', NotificationTopicArn='string', CacheParameterGroupName='string', NotificationTopicStatus='string', ApplyImmediately=True|False, EngineVersion='string', AutoMinorVersionUpgrade=True|False, SnapshotRetentionLimit=123, SnapshotWindow='string', CacheNodeType='string', NodeGroupId='string' ) **Response Syntax** :: { 'ReplicationGroup': { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **ReplicationGroup** *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: **[REQUIRED]** The identifier of the replication group to modify. :type ReplicationGroupDescription: string :param ReplicationGroupDescription: A description for the replication group. Maximum length is 255 characters. :type PrimaryClusterId: string :param PrimaryClusterId: For replication groups with a single primary, if this parameter is specified, ElastiCache promotes the specified cluster in the specified replication group to the primary role. The nodes of all other clusters in the replication group are read replicas. :type SnapshottingClusterId: string :param SnapshottingClusterId: The cluster ID that is used as the daily snapshot source for the replication group. This parameter cannot be set for Redis (cluster mode enabled) replication groups. :type AutomaticFailoverEnabled: boolean :param AutomaticFailoverEnabled: Determines whether a read replica is automatically promoted to read/write primary if the existing primary encounters a failure. Valid values: ``true`` | ``false`` Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. :type CacheSecurityGroupNames: list :param CacheSecurityGroupNames: A list of cache security group names to authorize for the clusters in this replication group. This change is asynchronously applied as soon as possible. This parameter can be used only with replication group containing clusters running outside of an Amazon Virtual Private Cloud (Amazon VPC). Constraints: Must contain no more than 255 alphanumeric characters. Must not be ``Default`` . - *(string) --* :type SecurityGroupIds: list :param SecurityGroupIds: Specifies the VPC Security Groups associated with the clusters in the replication group. This parameter can be used only with replication group containing clusters running in an Amazon Virtual Private Cloud (Amazon VPC). - *(string) --* :type PreferredMaintenanceWindow: string :param PreferredMaintenanceWindow: Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` :type NotificationTopicArn: string :param NotificationTopicArn: The Amazon Resource Name (ARN) of the Amazon SNS topic to which notifications are sent. .. note:: The Amazon SNS topic owner must be same as the replication group owner. :type CacheParameterGroupName: string :param CacheParameterGroupName: The name of the cache parameter group to apply to all of the clusters in this replication group. This change is asynchronously applied as soon as possible for parameters when the ``ApplyImmediately`` parameter is specified as ``true`` for this request. :type NotificationTopicStatus: string :param NotificationTopicStatus: The status of the Amazon SNS notification topic for the replication group. Notifications are sent only if the status is ``active`` . Valid values: ``active`` | ``inactive`` :type ApplyImmediately: boolean :param ApplyImmediately: If ``true`` , this parameter causes the modifications in this request and any pending modifications to be applied, asynchronously and as soon as possible, regardless of the ``PreferredMaintenanceWindow`` setting for the replication group. If ``false`` , changes to the nodes in the replication group are applied on the next maintenance reboot, or the next failure reboot, whichever occurs first. Valid values: ``true`` | ``false`` Default: ``false`` :type EngineVersion: string :param EngineVersion: The upgraded version of the cache engine to be run on the clusters in the replication group. **Important:** You can upgrade to a newer engine version (see `Selecting a Cache Engine and Version <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/SelectEngine.html#VersionManagement>`__ ), but you cannot downgrade to an earlier engine version. If you want to use an earlier engine version, you must delete the existing replication group and create it anew with the earlier engine version. :type AutoMinorVersionUpgrade: boolean :param AutoMinorVersionUpgrade: This parameter is currently disabled. :type SnapshotRetentionLimit: integer :param SnapshotRetentionLimit: The number of days for which ElastiCache retains automatic node group (shard) snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. **Important** If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. :type SnapshotWindow: string :param SnapshotWindow: The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of the node group (shard) specified by ``SnapshottingClusterId`` . Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. :type CacheNodeType: string :param CacheNodeType: A valid cache node type that you want to scale this replication group to. :type NodeGroupId: string :param NodeGroupId: Deprecated. This parameter is not used. :rtype: dict :returns: """ pass def modify_replication_group_shard_configuration(self, ReplicationGroupId: str, NodeGroupCount: int, ApplyImmediately: bool, ReshardingConfiguration: List = None, NodeGroupsToRemove: List = None, NodeGroupsToRetain: List = None) -> Dict: """ Modifies a replication group's shards (node groups) by allowing you to add shards, remove shards, or rebalance the keyspaces among exisiting shards. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ModifyReplicationGroupShardConfiguration>`_ **Request Syntax** :: response = client.modify_replication_group_shard_configuration( ReplicationGroupId='string', NodeGroupCount=123, ApplyImmediately=True|False, ReshardingConfiguration=[ { 'NodeGroupId': 'string', 'PreferredAvailabilityZones': [ 'string', ] }, ], NodeGroupsToRemove=[ 'string', ], NodeGroupsToRetain=[ 'string', ] ) **Response Syntax** :: { 'ReplicationGroup': { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **ReplicationGroup** *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: **[REQUIRED]** The name of the Redis (cluster mode enabled) cluster (replication group) on which the shards are to be configured. :type NodeGroupCount: integer :param NodeGroupCount: **[REQUIRED]** The number of node groups (shards) that results from the modification of the shard configuration. :type ApplyImmediately: boolean :param ApplyImmediately: **[REQUIRED]** Indicates that the shard reconfiguration process begins immediately. At present, the only permitted value for this parameter is ``true`` . Value: true :type ReshardingConfiguration: list :param ReshardingConfiguration: Specifies the preferred availability zones for each node group in the cluster. If the value of ``NodeGroupCount`` is greater than the current number of node groups (shards), you can use this parameter to specify the preferred availability zones of the cluster\'s shards. If you omit this parameter ElastiCache selects availability zones for you. You can specify this parameter only if the value of ``NodeGroupCount`` is greater than the current number of node groups (shards). - *(dict) --* A list of ``PreferredAvailabilityZones`` objects that specifies the configuration of a node group in the resharded cluster. - **NodeGroupId** *(string) --* The 4-digit id for the node group these configuration values apply to. - **PreferredAvailabilityZones** *(list) --* A list of preferred availability zones for the nodes in this cluster. - *(string) --* :type NodeGroupsToRemove: list :param NodeGroupsToRemove: If the value of ``NodeGroupCount`` is less than the current number of node groups (shards), the ``NodeGroupsToRemove`` or ``NodeGroupsToRetain`` is a required list of node group ids to remove from or retain in the cluster. ElastiCache for Redis will attempt to remove all node groups listed by ``NodeGroupsToRemove`` from the cluster. - *(string) --* :type NodeGroupsToRetain: list :param NodeGroupsToRetain: If the value of ``NodeGroupCount`` is less than the current number of node groups (shards), the ``NodeGroupsToRemove`` or ``NodeGroupsToRetain`` is a required list of node group ids to remove from or retain in the cluster. ElastiCache for Redis will attempt to remove all node groups except those listed by ``NodeGroupsToRetain`` from the cluster. - *(string) --* :rtype: dict :returns: """ pass def purchase_reserved_cache_nodes_offering(self, ReservedCacheNodesOfferingId: str, ReservedCacheNodeId: str = None, CacheNodeCount: int = None) -> Dict: """ Allows you to purchase a reserved cache node offering. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/PurchaseReservedCacheNodesOffering>`_ **Request Syntax** :: response = client.purchase_reserved_cache_nodes_offering( ReservedCacheNodesOfferingId='string', ReservedCacheNodeId='string', CacheNodeCount=123 ) **Response Syntax** :: { 'ReservedCacheNode': { 'ReservedCacheNodeId': 'string', 'ReservedCacheNodesOfferingId': 'string', 'CacheNodeType': 'string', 'StartTime': datetime(2015, 1, 1), 'Duration': 123, 'FixedPrice': 123.0, 'UsagePrice': 123.0, 'CacheNodeCount': 123, 'ProductDescription': 'string', 'OfferingType': 'string', 'State': 'string', 'RecurringCharges': [ { 'RecurringChargeAmount': 123.0, 'RecurringChargeFrequency': 'string' }, ], 'ReservationARN': 'string' } } **Response Structure** - *(dict) --* - **ReservedCacheNode** *(dict) --* Represents the output of a ``PurchaseReservedCacheNodesOffering`` operation. - **ReservedCacheNodeId** *(string) --* The unique identifier for the reservation. - **ReservedCacheNodesOfferingId** *(string) --* The offering identifier. - **CacheNodeType** *(string) --* The cache node type for the reserved cache nodes. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **StartTime** *(datetime) --* The time the reservation started. - **Duration** *(integer) --* The duration of the reservation in seconds. - **FixedPrice** *(float) --* The fixed price charged for this reserved cache node. - **UsagePrice** *(float) --* The hourly price charged for this reserved cache node. - **CacheNodeCount** *(integer) --* The number of cache nodes that have been reserved. - **ProductDescription** *(string) --* The description of the reserved cache node. - **OfferingType** *(string) --* The offering type of this reserved cache node. - **State** *(string) --* The state of the reserved cache node. - **RecurringCharges** *(list) --* The recurring price charged to run this reserved cache node. - *(dict) --* Contains the specific price and frequency of a recurring charges for a reserved cache node, or for a reserved cache node offering. - **RecurringChargeAmount** *(float) --* The monetary amount of the recurring charge. - **RecurringChargeFrequency** *(string) --* The frequency of the recurring charge. - **ReservationARN** *(string) --* The Amazon Resource Name (ARN) of the reserved cache node. Example: ``arn:aws:elasticache:us-east-1:123456789012:reserved-instance:ri-2017-03-27-08-33-25-582`` :type ReservedCacheNodesOfferingId: string :param ReservedCacheNodesOfferingId: **[REQUIRED]** The ID of the reserved cache node offering to purchase. Example: ``438012d3-4052-4cc7-b2e3-8d3372e0e706`` :type ReservedCacheNodeId: string :param ReservedCacheNodeId: A customer-specified identifier to track this reservation. .. note:: The Reserved Cache Node ID is an unique customer-specified identifier to track this reservation. If this parameter is not specified, ElastiCache automatically generates an identifier for the reservation. Example: myreservationID :type CacheNodeCount: integer :param CacheNodeCount: The number of cache node instances to reserve. Default: ``1`` :rtype: dict :returns: """ pass def reboot_cache_cluster(self, CacheClusterId: str, CacheNodeIdsToReboot: List) -> Dict: """ Reboots some, or all, of the cache nodes within a provisioned cluster. This operation applies any modified cache parameter groups to the cluster. The reboot operation takes place as soon as possible, and results in a momentary outage to the cluster. During the reboot, the cluster status is set to REBOOTING. The reboot causes the contents of the cache (for each cache node being rebooted) to be lost. When the reboot is complete, a cluster event is created. Rebooting a cluster is currently supported on Memcached and Redis (cluster mode disabled) clusters. Rebooting is not supported on Redis (cluster mode enabled) clusters. If you make changes to parameters that require a Redis (cluster mode enabled) cluster reboot for the changes to be applied, see `Rebooting a Cluster <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Clusters.Rebooting.html>`__ for an alternate process. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/RebootCacheCluster>`_ **Request Syntax** :: response = client.reboot_cache_cluster( CacheClusterId='string', CacheNodeIdsToReboot=[ 'string', ] ) **Response Syntax** :: { 'CacheCluster': { 'CacheClusterId': 'string', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'ClientDownloadLandingPage': 'string', 'CacheNodeType': 'string', 'Engine': 'string', 'EngineVersion': 'string', 'CacheClusterStatus': 'string', 'NumCacheNodes': 123, 'PreferredAvailabilityZone': 'string', 'CacheClusterCreateTime': datetime(2015, 1, 1), 'PreferredMaintenanceWindow': 'string', 'PendingModifiedValues': { 'NumCacheNodes': 123, 'CacheNodeIdsToRemove': [ 'string', ], 'EngineVersion': 'string', 'CacheNodeType': 'string' }, 'NotificationConfiguration': { 'TopicArn': 'string', 'TopicStatus': 'string' }, 'CacheSecurityGroups': [ { 'CacheSecurityGroupName': 'string', 'Status': 'string' }, ], 'CacheParameterGroup': { 'CacheParameterGroupName': 'string', 'ParameterApplyStatus': 'string', 'CacheNodeIdsToReboot': [ 'string', ] }, 'CacheSubnetGroupName': 'string', 'CacheNodes': [ { 'CacheNodeId': 'string', 'CacheNodeStatus': 'string', 'CacheNodeCreateTime': datetime(2015, 1, 1), 'Endpoint': { 'Address': 'string', 'Port': 123 }, 'ParameterGroupStatus': 'string', 'SourceCacheNodeId': 'string', 'CustomerAvailabilityZone': 'string' }, ], 'AutoMinorVersionUpgrade': True|False, 'SecurityGroups': [ { 'SecurityGroupId': 'string', 'Status': 'string' }, ], 'ReplicationGroupId': 'string', 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **CacheCluster** *(dict) --* Contains all of the attributes of a specific cluster. - **CacheClusterId** *(string) --* The user-supplied identifier of the cluster. This identifier is a unique key that identifies a cluster. - **ConfigurationEndpoint** *(dict) --* Represents a Memcached cluster endpoint which, if Automatic Discovery is enabled on the cluster, can be used by an application to connect to any node in the cluster. The configuration endpoint will always have ``.cfg`` in it. Example: ``mem-3.9dvc4r.cfg.usw2.cache.amazonaws.com:11211`` - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ClientDownloadLandingPage** *(string) --* The URL of the web page where you can download the latest ElastiCache client library. - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for the cluster. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **Engine** *(string) --* The name of the cache engine (``memcached`` or ``redis`` ) to be used for this cluster. - **EngineVersion** *(string) --* The version of the cache engine that is used in this cluster. - **CacheClusterStatus** *(string) --* The current state of this cluster, one of the following values: ``available`` , ``creating`` , ``deleted`` , ``deleting`` , ``incompatible-network`` , ``modifying`` , ``rebooting cluster nodes`` , ``restore-failed`` , or ``snapshotting`` . - **NumCacheNodes** *(integer) --* The number of cache nodes in the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the cluster is located or "Multiple" if the cache nodes are located in different Availability Zones. - **CacheClusterCreateTime** *(datetime) --* The date and time when the cluster was created. - **PreferredMaintenanceWindow** *(string) --* Specifies the weekly time range during which maintenance on the cluster is performed. It is specified as a range in the format ddd:hh24:mi-ddd:hh24:mi (24H Clock UTC). The minimum maintenance window is a 60 minute period. Valid values for ``ddd`` are: * ``sun`` * ``mon`` * ``tue`` * ``wed`` * ``thu`` * ``fri`` * ``sat`` Example: ``sun:23:00-mon:01:30`` - **PendingModifiedValues** *(dict) --* A group of settings that are applied to the cluster in the future, or that are currently being applied. - **NumCacheNodes** *(integer) --* The new number of cache nodes for the cluster. For clusters running Redis, this value must be 1. For clusters running Memcached, this value must be between 1 and 20. - **CacheNodeIdsToRemove** *(list) --* A list of cache node IDs that are being removed (or will be removed) from the cluster. A node ID is a 4-digit numeric identifier (0001, 0002, etc.). - *(string) --* - **EngineVersion** *(string) --* The new cache engine version that the cluster runs. - **CacheNodeType** *(string) --* The cache node type that this cluster or replication group is scaled to. - **NotificationConfiguration** *(dict) --* Describes a notification topic and its status. Notification topics are used for publishing ElastiCache events to subscribers using Amazon Simple Notification Service (SNS). - **TopicArn** *(string) --* The Amazon Resource Name (ARN) that identifies the topic. - **TopicStatus** *(string) --* The current state of the topic. - **CacheSecurityGroups** *(list) --* A list of cache security group elements, composed of name and status sub-elements. - *(dict) --* Represents a cluster's status within a particular cache security group. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Status** *(string) --* The membership status in the cache security group. The status changes when a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **CacheParameterGroup** *(dict) --* Status of the cache parameter group. - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. - **ParameterApplyStatus** *(string) --* The status of parameter updates. - **CacheNodeIdsToReboot** *(list) --* A list of the cache node IDs which need to be rebooted for parameter changes to be applied. A node ID is a numeric identifier (0001, 0002, etc.). - *(string) --* - **CacheSubnetGroupName** *(string) --* The name of the cache subnet group associated with the cluster. - **CacheNodes** *(list) --* A list of cache nodes that are members of the cluster. - *(dict) --* Represents an individual cache node within a cluster. Each cache node runs its own instance of the cluster's protocol-compliant caching software - either Memcached or Redis. The following node types are supported by ElastiCache. Generally speaking, the current generation types provide more memory and computational power at lower cost when compared to their equivalent previous generation counterparts. * General purpose: * Current generation: **T2 node types:** ``cache.t2.micro`` , ``cache.t2.small`` , ``cache.t2.medium`` **M3 node types:** ``cache.m3.medium`` , ``cache.m3.large`` , ``cache.m3.xlarge`` , ``cache.m3.2xlarge`` **M4 node types:** ``cache.m4.large`` , ``cache.m4.xlarge`` , ``cache.m4.2xlarge`` , ``cache.m4.4xlarge`` , ``cache.m4.10xlarge`` * Previous generation: (not recommended) **T1 node types:** ``cache.t1.micro`` **M1 node types:** ``cache.m1.small`` , ``cache.m1.medium`` , ``cache.m1.large`` , ``cache.m1.xlarge`` * Compute optimized: * Previous generation: (not recommended) **C1 node types:** ``cache.c1.xlarge`` * Memory optimized: * Current generation: **R3 node types:** ``cache.r3.large`` , ``cache.r3.xlarge`` , ``cache.r3.2xlarge`` , ``cache.r3.4xlarge`` , ``cache.r3.8xlarge`` **R4 node types;** ``cache.r4.large`` , ``cache.r4.xlarge`` , ``cache.r4.2xlarge`` , ``cache.r4.4xlarge`` , ``cache.r4.8xlarge`` , ``cache.r4.16xlarge`` * Previous generation: (not recommended) **M2 node types:** ``cache.m2.xlarge`` , ``cache.m2.2xlarge`` , ``cache.m2.4xlarge`` **Notes:** * All T2 instances are created in an Amazon Virtual Private Cloud (Amazon VPC). * Redis (cluster mode disabled): Redis backup/restore is not supported on T1 and T2 instances. * Redis (cluster mode enabled): Backup/restore is not supported on T1 instances. * Redis Append-only files (AOF) functionality is not supported for T1 or T2 instances. For a complete listing of node types and specifications, see: * `Amazon ElastiCache Product Features and Details <http://aws.amazon.com/elasticache/details>`__ * `Cache Node Type-Specific Parameters for Memcached <http://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/ParameterGroups.Memcached.html#ParameterGroups.Memcached.NodeSpecific>`__ * `Cache Node Type-Specific Parameters for Redis <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ParameterGroups.Redis.html#ParameterGroups.Redis.NodeSpecific>`__ - **CacheNodeId** *(string) --* The cache node identifier. A node ID is a numeric identifier (0001, 0002, etc.). The combination of cluster ID and node ID uniquely identifies every cache node used in a customer's AWS account. - **CacheNodeStatus** *(string) --* The current state of this cache node. - **CacheNodeCreateTime** *(datetime) --* The date and time when the cache node was created. - **Endpoint** *(dict) --* The hostname for connecting to this cache node. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **ParameterGroupStatus** *(string) --* The status of the parameter group applied to this cache node. - **SourceCacheNodeId** *(string) --* The ID of the primary node to which this read replica node is synchronized. If this field is empty, this node is not associated with a primary cluster. - **CustomerAvailabilityZone** *(string) --* The Availability Zone where this node was created and now resides. - **AutoMinorVersionUpgrade** *(boolean) --* This parameter is currently disabled. - **SecurityGroups** *(list) --* A list of VPC Security Groups associated with the cluster. - *(dict) --* Represents a single cache security group and its status. - **SecurityGroupId** *(string) --* The identifier of the cache security group. - **Status** *(string) --* The status of the cache security group membership. The status changes whenever a cache security group is modified, or when the cache security groups assigned to a cluster are modified. - **ReplicationGroupId** *(string) --* The replication group to which this cluster belongs. If this field is empty, the cluster is not associated with any replication group. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of SnapshotRetentionLimit is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your cluster. Example: ``05:00-09:00`` - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable at-rest encryption on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type CacheClusterId: string :param CacheClusterId: **[REQUIRED]** The cluster identifier. This parameter is stored as a lowercase string. :type CacheNodeIdsToReboot: list :param CacheNodeIdsToReboot: **[REQUIRED]** A list of cache node IDs to reboot. A node ID is a numeric identifier (0001, 0002, etc.). To reboot an entire cluster, specify all of the cache node IDs. - *(string) --* :rtype: dict :returns: """ pass def remove_tags_from_resource(self, ResourceName: str, TagKeys: List) -> Dict: """ Removes the tags identified by the ``TagKeys`` list from the named resource. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/RemoveTagsFromResource>`_ **Request Syntax** :: response = client.remove_tags_from_resource( ResourceName='string', TagKeys=[ 'string', ] ) **Response Syntax** :: { 'TagList': [ { 'Key': 'string', 'Value': 'string' }, ] } **Response Structure** - *(dict) --* Represents the output from the ``AddTagsToResource`` , ``ListTagsForResource`` , and ``RemoveTagsFromResource`` operations. - **TagList** *(list) --* A list of cost allocation tags as key-value pairs. - *(dict) --* A cost allocation Tag that can be added to an ElastiCache cluster or replication group. Tags are composed of a Key/Value pair. A tag with a null Value is permitted. - **Key** *(string) --* The key for the tag. May not be null. - **Value** *(string) --* The tag's value. May be null. :type ResourceName: string :param ResourceName: **[REQUIRED]** The Amazon Resource Name (ARN) of the resource from which you want the tags removed, for example ``arn:aws:elasticache:us-west-2:0123456789:cluster:myCluster`` or ``arn:aws:elasticache:us-west-2:0123456789:snapshot:mySnapshot`` . For more information about ARNs, see `Amazon Resource Names (ARNs) and AWS Service Namespaces <http://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html>`__ . :type TagKeys: list :param TagKeys: **[REQUIRED]** A list of ``TagKeys`` identifying the tags you want removed from the named resource. - *(string) --* :rtype: dict :returns: """ pass def reset_cache_parameter_group(self, CacheParameterGroupName: str, ResetAllParameters: bool = None, ParameterNameValues: List = None) -> Dict: """ Modifies the parameters of a cache parameter group to the engine or system default value. You can reset specific parameters by submitting a list of parameter names. To reset the entire cache parameter group, specify the ``ResetAllParameters`` and ``CacheParameterGroupName`` parameters. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/ResetCacheParameterGroup>`_ **Request Syntax** :: response = client.reset_cache_parameter_group( CacheParameterGroupName='string', ResetAllParameters=True|False, ParameterNameValues=[ { 'ParameterName': 'string', 'ParameterValue': 'string' }, ] ) **Response Syntax** :: { 'CacheParameterGroupName': 'string' } **Response Structure** - *(dict) --* Represents the output of one of the following operations: * ``ModifyCacheParameterGroup`` * ``ResetCacheParameterGroup`` - **CacheParameterGroupName** *(string) --* The name of the cache parameter group. :type CacheParameterGroupName: string :param CacheParameterGroupName: **[REQUIRED]** The name of the cache parameter group to reset. :type ResetAllParameters: boolean :param ResetAllParameters: If ``true`` , all parameters in the cache parameter group are reset to their default values. If ``false`` , only the parameters listed by ``ParameterNameValues`` are reset to their default values. Valid values: ``true`` | ``false`` :type ParameterNameValues: list :param ParameterNameValues: An array of parameter names to reset to their default values. If ``ResetAllParameters`` is ``true`` , do not use ``ParameterNameValues`` . If ``ResetAllParameters`` is ``false`` , you must specify the name of at least one parameter to reset. - *(dict) --* Describes a name-value pair that is used to update the value of a parameter. - **ParameterName** *(string) --* The name of the parameter. - **ParameterValue** *(string) --* The value of the parameter. :rtype: dict :returns: """ pass def revoke_cache_security_group_ingress(self, CacheSecurityGroupName: str, EC2SecurityGroupName: str, EC2SecurityGroupOwnerId: str) -> Dict: """ Revokes ingress from a cache security group. Use this operation to disallow access from an Amazon EC2 security group that had been previously authorized. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/RevokeCacheSecurityGroupIngress>`_ **Request Syntax** :: response = client.revoke_cache_security_group_ingress( CacheSecurityGroupName='string', EC2SecurityGroupName='string', EC2SecurityGroupOwnerId='string' ) **Response Syntax** :: { 'CacheSecurityGroup': { 'OwnerId': 'string', 'CacheSecurityGroupName': 'string', 'Description': 'string', 'EC2SecurityGroups': [ { 'Status': 'string', 'EC2SecurityGroupName': 'string', 'EC2SecurityGroupOwnerId': 'string' }, ] } } **Response Structure** - *(dict) --* - **CacheSecurityGroup** *(dict) --* Represents the output of one of the following operations: * ``AuthorizeCacheSecurityGroupIngress`` * ``CreateCacheSecurityGroup`` * ``RevokeCacheSecurityGroupIngress`` - **OwnerId** *(string) --* The AWS account ID of the cache security group owner. - **CacheSecurityGroupName** *(string) --* The name of the cache security group. - **Description** *(string) --* The description of the cache security group. - **EC2SecurityGroups** *(list) --* A list of Amazon EC2 security groups that are associated with this cache security group. - *(dict) --* Provides ownership and status information for an Amazon EC2 security group. - **Status** *(string) --* The status of the Amazon EC2 security group. - **EC2SecurityGroupName** *(string) --* The name of the Amazon EC2 security group. - **EC2SecurityGroupOwnerId** *(string) --* The AWS account ID of the Amazon EC2 security group owner. :type CacheSecurityGroupName: string :param CacheSecurityGroupName: **[REQUIRED]** The name of the cache security group to revoke ingress from. :type EC2SecurityGroupName: string :param EC2SecurityGroupName: **[REQUIRED]** The name of the Amazon EC2 security group to revoke access from. :type EC2SecurityGroupOwnerId: string :param EC2SecurityGroupOwnerId: **[REQUIRED]** The AWS account number of the Amazon EC2 security group owner. Note that this is not the same thing as an AWS access key ID - you must provide a valid AWS account number for this parameter. :rtype: dict :returns: """ pass def test_failover(self, ReplicationGroupId: str, NodeGroupId: str) -> Dict: """ Represents the input of a ``TestFailover`` operation which test automatic failover on a specified node group (called shard in the console) in a replication group (called cluster in the console). **Note the following** * A customer can use this operation to test automatic failover on up to 5 shards (called node groups in the ElastiCache API and AWS CLI) in any rolling 24-hour period. * If calling this operation on shards in different clusters (called replication groups in the API and CLI), the calls can be made concurrently. * If calling this operation multiple times on different shards in the same Redis (cluster mode enabled) replication group, the first node replacement must complete before a subsequent call can be made. * To determine whether the node replacement is complete you can check Events using the Amazon ElastiCache console, the AWS CLI, or the ElastiCache API. Look for the following automatic failover related events, listed here in order of occurrance: * Replication group message: ``Test Failover API called for node group <node-group-id>`` * Cache cluster message: ``Failover from master node <primary-node-id> to replica node <node-id> completed`` * Replication group message: ``Failover from master node <primary-node-id> to replica node <node-id> completed`` * Cache cluster message: ``Recovering cache nodes <node-id>`` * Cache cluster message: ``Finished recovery for cache nodes <node-id>`` For more information see: * `Viewing ElastiCache Events <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/ECEvents.Viewing.html>`__ in the *ElastiCache User Guide* * `DescribeEvents <http://docs.aws.amazon.com/AmazonElastiCache/latest/APIReference/API_DescribeEvents.html>`__ in the ElastiCache API Reference Also see, `Testing Multi-AZ with Automatic Failover <http://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/AutoFailover.html#auto-failover-test>`__ in the *ElastiCache User Guide* . See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/elasticache-2015-02-02/TestFailover>`_ **Request Syntax** :: response = client.test_failover( ReplicationGroupId='string', NodeGroupId='string' ) **Response Syntax** :: { 'ReplicationGroup': { 'ReplicationGroupId': 'string', 'Description': 'string', 'Status': 'string', 'PendingModifiedValues': { 'PrimaryClusterId': 'string', 'AutomaticFailoverStatus': 'enabled'|'disabled', 'Resharding': { 'SlotMigration': { 'ProgressPercentage': 123.0 } } }, 'MemberClusters': [ 'string', ], 'NodeGroups': [ { 'NodeGroupId': 'string', 'Status': 'string', 'PrimaryEndpoint': { 'Address': 'string', 'Port': 123 }, 'Slots': 'string', 'NodeGroupMembers': [ { 'CacheClusterId': 'string', 'CacheNodeId': 'string', 'ReadEndpoint': { 'Address': 'string', 'Port': 123 }, 'PreferredAvailabilityZone': 'string', 'CurrentRole': 'string' }, ] }, ], 'SnapshottingClusterId': 'string', 'AutomaticFailover': 'enabled'|'disabled'|'enabling'|'disabling', 'ConfigurationEndpoint': { 'Address': 'string', 'Port': 123 }, 'SnapshotRetentionLimit': 123, 'SnapshotWindow': 'string', 'ClusterEnabled': True|False, 'CacheNodeType': 'string', 'AuthTokenEnabled': True|False, 'TransitEncryptionEnabled': True|False, 'AtRestEncryptionEnabled': True|False } } **Response Structure** - *(dict) --* - **ReplicationGroup** *(dict) --* Contains all of the attributes of a specific Redis replication group. - **ReplicationGroupId** *(string) --* The identifier for the replication group. - **Description** *(string) --* The user supplied description of the replication group. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , ``modifying`` , ``deleting`` , ``create-failed`` , ``snapshotting`` . - **PendingModifiedValues** *(dict) --* A group of settings to be applied to the replication group, either immediately or during the next maintenance window. - **PrimaryClusterId** *(string) --* The primary cluster ID that is applied immediately (if ``--apply-immediately`` was specified), or during the next maintenance window. - **AutomaticFailoverStatus** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **Resharding** *(dict) --* The status of an online resharding operation. - **SlotMigration** *(dict) --* Represents the progress of an online resharding operation. - **ProgressPercentage** *(float) --* The percentage of the slot migration that is complete. - **MemberClusters** *(list) --* The names of all the cache clusters that are part of this replication group. - *(string) --* - **NodeGroups** *(list) --* A list of node groups in this replication group. For Redis (cluster mode disabled) replication groups, this is a single-element list. For Redis (cluster mode enabled) replication groups, the list contains an entry for each node group (shard). - *(dict) --* Represents a collection of cache nodes in a replication group. One node in the node group is the read/write primary node. All the other nodes are read-only Replica nodes. - **NodeGroupId** *(string) --* The identifier for the node group (shard). A Redis (cluster mode disabled) replication group contains only 1 node group; therefore, the node group ID is 0001. A Redis (cluster mode enabled) replication group contains 1 to 15 node groups numbered 0001 to 0015. - **Status** *(string) --* The current state of this replication group - ``creating`` , ``available`` , etc. - **PrimaryEndpoint** *(dict) --* The endpoint of the primary node in this node group (shard). - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **Slots** *(string) --* The keyspace for this node group (shard). - **NodeGroupMembers** *(list) --* A list containing information about individual nodes within the node group (shard). - *(dict) --* Represents a single node within a node group (shard). - **CacheClusterId** *(string) --* The ID of the cluster to which the node belongs. - **CacheNodeId** *(string) --* The ID of the node within its cluster. A node ID is a numeric identifier (0001, 0002, etc.). - **ReadEndpoint** *(dict) --* The information required for client programs to connect to a node for read operations. The read endpoint is only applicable on Redis (cluster mode disabled) clusters. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **PreferredAvailabilityZone** *(string) --* The name of the Availability Zone in which the node is located. - **CurrentRole** *(string) --* The role that is currently assigned to the node - ``primary`` or ``replica`` . This member is only applicable for Redis (cluster mode disabled) replication groups. - **SnapshottingClusterId** *(string) --* The cluster ID that is used as the daily snapshot source for the replication group. - **AutomaticFailover** *(string) --* Indicates the status of Multi-AZ with automatic failover for this Redis replication group. Amazon ElastiCache for Redis does not support Multi-AZ with automatic failover on: * Redis versions earlier than 2.8.6. * Redis (cluster mode disabled): T1 and T2 cache node types. * Redis (cluster mode enabled): T1 node types. - **ConfigurationEndpoint** *(dict) --* The configuration endpoint for this replication group. Use the configuration endpoint to connect to this replication group. - **Address** *(string) --* The DNS hostname of the cache node. - **Port** *(integer) --* The port number that the cache engine is listening on. - **SnapshotRetentionLimit** *(integer) --* The number of days for which ElastiCache retains automatic cluster snapshots before deleting them. For example, if you set ``SnapshotRetentionLimit`` to 5, a snapshot that was taken today is retained for 5 days before being deleted. .. warning:: If the value of ``SnapshotRetentionLimit`` is set to zero (0), backups are turned off. - **SnapshotWindow** *(string) --* The daily time range (in UTC) during which ElastiCache begins taking a daily snapshot of your node group (shard). Example: ``05:00-09:00`` If you do not specify this parameter, ElastiCache automatically chooses an appropriate time range. .. note:: This parameter is only valid if the ``Engine`` parameter is ``redis`` . - **ClusterEnabled** *(boolean) --* A flag indicating whether or not this replication group is cluster enabled; i.e., whether its data can be partitioned across multiple shards (API/CLI: node groups). Valid values: ``true`` | ``false`` - **CacheNodeType** *(string) --* The name of the compute and memory capacity node type for each node in the replication group. - **AuthTokenEnabled** *(boolean) --* A flag that enables using an ``AuthToken`` (password) when issuing Redis commands. Default: ``false`` - **TransitEncryptionEnabled** *(boolean) --* A flag that enables in-transit encryption when set to ``true`` . You cannot modify the value of ``TransitEncryptionEnabled`` after the cluster is created. To enable in-transit encryption on a cluster you must set ``TransitEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` - **AtRestEncryptionEnabled** *(boolean) --* A flag that enables encryption at-rest when set to ``true`` . You cannot modify the value of ``AtRestEncryptionEnabled`` after the cluster is created. To enable encryption at-rest on a cluster you must set ``AtRestEncryptionEnabled`` to ``true`` when you create a cluster. **Required:** Only available when creating a replication group in an Amazon VPC using redis version ``3.2.6`` or ``4.x`` . Default: ``false`` :type ReplicationGroupId: string :param ReplicationGroupId: **[REQUIRED]** The name of the replication group (console: cluster) whose automatic failover is being tested by this operation. :type NodeGroupId: string :param NodeGroupId: **[REQUIRED]** The name of the node group (called shard in the console) in this replication group on which automatic failover is to be tested. You may test automatic failover on up to 5 node groups in any rolling 24-hour period. :rtype: dict :returns: """ pass

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7b206fb93c23a3af801abae48971228081341211

8,553

py

Python

h2o-py/h2o/demo.py

ChristosChristofidis/h2o-3

2a926c0950a98eff5a4c06aeaf0373e17176ecd8

[ "Apache-2.0" ]

null

h2o-py/h2o/demo.py

ChristosChristofidis/h2o-3

2a926c0950a98eff5a4c06aeaf0373e17176ecd8

[ "Apache-2.0" ]

null

h2o-py/h2o/demo.py

ChristosChristofidis/h2o-3

2a926c0950a98eff5a4c06aeaf0373e17176ecd8

[ "Apache-2.0" ]

1

2020-12-18T19:20:02.000Z

import h2o import sys, os def demo(func=None, interactive=True, echo=True, test=False): """ H2O built-in demo facility :param func: A string that identifies the h2o python function to demonstrate. :param interactive: If True, the user will be prompted to continue the demonstration after every segment. :param echo: If True, the python commands that are executed will be displayed. :param test: Used for pyunit testing. h2o.init() will not be called if set to True. :return: Example: >>> h2o.demo("gbm") """ if func == "gbm": gbm_demo(interactive, echo, test) elif func == "deeplearning": deeplearning_demo(interactive, echo, test) else: print "Demo for {0} has not been implemented.".format(func) def gbm_demo(interactive, echo, test): demo_description = ['\n-----------------------------------------------------------------', 'This is a demo of H2O\'s GBM function.', 'It uploads a dataset to h2o, parses it, and shows a description.', 'Then, it divides the dataset into training and test sets, ', 'builds a GBM from the training set, and predicts on the test set.', 'Finally, default performance metrics are displayed.', '-----------------------------------------------------------------'] demo_commands = ['# Connect to h2o', '>>> h2o.init()\n', '\n# Upload the prostate dataset that comes included in the h2o python package', '>>> prostate = h2o.upload_file(path = os.path.join(sys.prefix, "h2o_data/prostate.csv"))\n', '\n# Print a description of the prostate data', '>>> prostate.describe()\n', '\n# Randomly split the dataset into ~70/30, training/test sets', '>>> r = prostate[0].runif()', '>>> train = prostate[r < 0.70]', '>>> valid = prostate[r >= 0.30]\n', '\n# Convert the response columns to factors (for binary classification problems)', '>>> train["CAPSULE"] = train["CAPSULE"].asfactor()', '>>> test["CAPSULE"] = test["CAPSULE"].asfactor()\n', '\n# Build a (classification) GBM', '>>> prostate_gbm = h2o.gbm(x=train[["AGE", "RACE", "PSA", "VOL", "GLEASON"]], ' 'y=train["CAPSULE"], distribution="bernoulli", ntrees=10, max_depth=8, min_rows=10, ' 'learn_rate=0.2)\n', '\n# Show the model', '>>> prostate_gbm.show()\n', '\n# Predict on the test set and show the first ten predictions', '>>> predictions = prostate_gbm.predict(test)', '>>> predictions.show()\n', '\n# Show default performance metrics', '>>> performance = prostate_gbm.model_performance(test)', '>>> performance.show()\n'] for line in demo_description: print line print echo_and_interact(demo_commands, interactive, echo) if not test: h2o.init() echo_and_interact(demo_commands, interactive, echo) if not test: prostate = h2o.upload_file(path = os.path.join(sys.prefix, 'h2o_data/prostate.csv')) else: prostate = h2o.upload_file(path = h2o.locate('smalldata/prostate/prostate.csv')) echo_and_interact(demo_commands, interactive, echo) prostate.describe() echo_and_interact(demo_commands, interactive, echo, npop=4) r = prostate[0].runif() train = prostate[r < 0.70] test = prostate[r >= 0.30] echo_and_interact(demo_commands, interactive, echo, npop=3) train["CAPSULE"] = train["CAPSULE"].asfactor() test["CAPSULE"] = test["CAPSULE"].asfactor() echo_and_interact(demo_commands, interactive, echo) prostate_gbm = h2o.gbm(x=train[["AGE", "RACE", "PSA", "VOL", "GLEASON"]], y=train["CAPSULE"], distribution="bernoulli", ntrees=10, max_depth=8, min_rows=10, learn_rate=0.2) echo_and_interact(demo_commands, interactive, echo) prostate_gbm.show() echo_and_interact(demo_commands, interactive, echo, npop=3) predictions = prostate_gbm.predict(test) predictions.show() echo_and_interact(demo_commands, interactive, echo, npop=3) performance = prostate_gbm.model_performance(test) performance.show() def deeplearning_demo(interactive, echo, test): demo_description = ['\n-----------------------------------------------------------------', 'This is a demo of H2O\'s Deeplearning function.', 'It uploads a dataset to h2o, parses it, and shows a description.', 'Then, it divides the dataset into training and test sets, ', 'builds a model from the training set, and predicts on the test set.', 'Finally, default performance metrics are displayed.', '-----------------------------------------------------------------'] demo_commands = ['# Connect to h2o', '>>> h2o.init()\n', '\n# Upload the prostate dataset that comes included in the h2o python package', '>>> prostate = h2o.upload_file(path = os.path.join(sys.prefix, "h2o_data/prostate.csv"))\n', '\n# Print a description of the prostate data', '>>> prostate.describe()\n', '\n# Randomly split the dataset into ~70/30, training/test sets', '>>> r = prostate[0].runif()', '>>> train = prostate[r < 0.70]', '>>> valid = prostate[r >= 0.30]\n', '\n# Convert the response columns to factors (for binary classification problems)', '>>> train["CAPSULE"] = train["CAPSULE"].asfactor()', '>>> test["CAPSULE"] = test["CAPSULE"].asfactor()\n', '\n# Build a (classification) Deeplearning model', '>>> prostate_dl = h2o.deeplearning(x=train[list(set(prostate.col_names())-set(["ID","CAPSULE"]))]' ', y=train["CAPSULE"], activation="Tanh", hidden=[10, 10, 10], epochs=10000)\n', '\n# Show the model', '>>> prostate_dl.show()\n', '\n# Predict on the test set and show the first ten predictions', '>>> predictions = prostate_dl.predict(test)', '>>> predictions.show()\n', '\n# Show default performance metrics', '>>> performance = prostate_dl.model_performance(test)', '>>> performance.show()\n'] for line in demo_description: print line print echo_and_interact(demo_commands, interactive, echo) if not test: h2o.init() echo_and_interact(demo_commands, interactive, echo) if not test: prostate = h2o.upload_file(path = os.path.join(sys.prefix, 'h2o_data/prostate.csv')) else: prostate = h2o.upload_file(path = h2o.locate('smalldata/prostate/prostate.csv')) echo_and_interact(demo_commands, interactive, echo) prostate.describe() echo_and_interact(demo_commands, interactive, echo, npop=4) r = prostate[0].runif() train = prostate[r < 0.70] test = prostate[r >= 0.30] echo_and_interact(demo_commands, interactive, echo, npop=3) train["CAPSULE"] = train["CAPSULE"].asfactor() test["CAPSULE"] = test["CAPSULE"].asfactor() echo_and_interact(demo_commands, interactive, echo) prostate_dl = h2o.deeplearning(x=train[list(set(prostate.col_names())-set(["ID","CAPSULE"]))], y=train["CAPSULE"], activation="Tanh", hidden=[10, 10, 10], epochs=10000) echo_and_interact(demo_commands, interactive, echo) prostate_dl.show() echo_and_interact(demo_commands, interactive, echo, npop=3) predictions = prostate_dl.predict(test) predictions.show() echo_and_interact(demo_commands, interactive, echo, npop=3) performance = prostate_dl.model_performance(test) performance.show() def echo_and_interact(demo_commands, interactive, echo, npop=2): if demo_commands: if echo: for p in range(npop): print demo_commands.pop(0) if interactive: raw_input('Press ENTER...\n')

50.609467

120

0.562259

966

8,553

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0.170807

0.073389

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8,553

169

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null

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1

0

null

0

1

0

7

9e3c3d8c514a9640c4c392e49c45e75ff1093176

2,050

py

Python

tests/test_delete.py

noqqe/rvo

423e1ea1aea0a2dc849ceae838e18896a13e7771

[ "MIT" ]

14

2016-05-04T13:56:10.000Z

2019-08-01T14:31:33.000Z

tests/test_delete.py

noqqe/rvo

423e1ea1aea0a2dc849ceae838e18896a13e7771

[ "MIT" ]

12

2016-08-01T12:42:53.000Z

2022-02-16T09:37:47.000Z

tests/test_delete.py

noqqe/rvo

423e1ea1aea0a2dc849ceae838e18896a13e7771

[ "MIT" ]

null

from conftest import rvo_output, rvo_err from click.testing import CliRunner from rvo import cli def test_delete_yes(): options = ['delete', '569e5eed6815b47ce7bdb583', '--yes'] output = ["Removed"] rvo_output(options,output) def test_delete_input_yes(): runner = CliRunner() result = runner.invoke(cli.cli, ['delete', '569e5eed6815b47ce7bdb583'], input="y\n") assert not result.exception assert result.output.strip().endswith('Removed Nutella, Coffee, ninja') def test_delete_input_no(): runner = CliRunner() result = runner.invoke(cli.cli, ['delete', '569e5eed6815b47ce7bdb583'], input="n\n") assert not result.exception assert not result.output.strip().endswith('Removed Nutella, Coffee, ninja') def test_delete_input_default(): runner = CliRunner() result = runner.invoke(cli.cli, ['delete', '569e5eed6815b47ce7bdb583'], input="\n") assert not result.exception assert not result.output.strip().endswith('Removed Nutella, Coffee, ninja') def test_delete_nonexistent(): options = ['delete', '769e5eed6815b47ce7bdb583'] rvo_err(options) def test_delete_shortid_yes(): options = ['delete', '2', '--yes'] output = ["Removed"] rvo_output(options,output) def test_delete_shortid_input_yes(): runner = CliRunner() result = runner.invoke(cli.cli, ['delete', '1'], input="y\n") assert not result.exception assert result.output.strip().endswith('Removed Nutella, Coffee, ninja') def test_delete_shortid_input_no(): runner = CliRunner() result = runner.invoke(cli.cli, ['delete', '1'], input="n\n") assert not result.exception assert not result.output.strip().endswith('Removed Nutella, Coffee, ninja') def test_delete_shortid_input_default(): runner = CliRunner() result = runner.invoke(cli.cli, ['delete', '1'], input="\n") assert not result.exception assert not result.output.strip().endswith('Removed Nutella, Coffee, ninja') def test_delete_shortid_nonexistent(): options = ['delete', '7'] rvo_err(options)

35.344828

88

0.704878

251

2,050

5.609562

0.155378

0.049716

0.09233

0.115057

0.808949

0.803977

0

0.043178

0.152683

2,050

57

89

35.964912

0.767415

0

0.510638

0

0.197561

0.058537

0

0.255319

1

0.212766

false

0

0.06383

0

0.276596

0

null

0

1

0

null

0

1

0

7

9e686718e623f5301edcf2f5b0b84cf1ded950d8

293,164

py

Python

install/app_store/tk-framework-qtwidgets/v2.6.5/python/activity_stream/ui/resources_rc.py

JoanAzpeitia/lp_sg

e0ee79555e419dd2ae3a5f31e5515b3f40b22a62

[ "MIT" ]

null

install/app_store/tk-framework-qtwidgets/v2.6.5/python/activity_stream/ui/resources_rc.py

JoanAzpeitia/lp_sg

e0ee79555e419dd2ae3a5f31e5515b3f40b22a62

[ "MIT" ]

null

install/app_store/tk-framework-qtwidgets/v2.6.5/python/activity_stream/ui/resources_rc.py

JoanAzpeitia/lp_sg

e0ee79555e419dd2ae3a5f31e5515b3f40b22a62

[ "MIT" ]

1

2020-02-15T10:42:56.000Z

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13,960.190476

291,486

0.740401

67,274

293,164

3.218926

0.122677

0.006373

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0.001521

293,164

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291,487

14,658.2

0.508438

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0.333333

0.998734

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false

0

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0

1

null

1

0

1

0

8

9e700c2acd8e1412905a1f56a5b90c92a31935e8

1,329

py

Python

images.py

tikurahul/Inkplate-6-micropython

184eaa1228fcd02b75abaa878f9b7b3229a93410

[ "MIT" ]

21

2020-12-28T20:09:27.000Z

2021-10-04T07:07:33.000Z

images.py

tikurahul/Inkplate-6-micropython

184eaa1228fcd02b75abaa878f9b7b3229a93410

[ "MIT" ]

null

images.py

tikurahul/Inkplate-6-micropython

184eaa1228fcd02b75abaa878f9b7b3229a93410

[ "MIT" ]

3

2021-01-06T05:55:52.000Z

2021-02-06T00:31:36.000Z

# https://javl.github.io/image2cpp/ # 40x40 CALENDAR_40_40 = bytearray([ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x38, 0x00, 0x1c, 0x00, 0x00, 0x38, 0x00, 0x1c, 0x00, 0x00, 0x3c, 0x00, 0x1c, 0x00, 0x01, 0xff, 0xff, 0xff, 0x80, 0x03, 0xff, 0xff, 0xff, 0xc0, 0x07, 0xff, 0xff, 0xff, 0xe0, 0x07, 0xff, 0xff, 0xff, 0xe0, 0x07, 0xff, 0xff, 0xff, 0xe0, 0x07, 0xff, 0xff, 0xff, 0xe0, 0x07, 0xff, 0xff, 0xff, 0xe0, 0x07, 0xff, 0xff, 0xff, 0xe0, 0x07, 0x80, 0x00, 0x01, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x0f, 0xf0, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x00, 0x00, 0x00, 0xe0, 0x07, 0x80, 0x00, 0x01, 0xe0, 0x07, 0xff, 0xff, 0xff, 0xe0, 0x03, 0xff, 0xff, 0xff, 0xc0, 0x01, 0xff, 0xff, 0xff, 0x80, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 ])

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99

0.642588

210

1,329

4.057143

0.104762

0.507042

0.577465

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1

0

1

0

1

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null

0

1

0

12

9ea65d81297b45ec6a398fcc04a162922c4ac4d5

119

py

Python

pokemon/status/__init__.py

Rix565/PygaMone

58879a01b5427328824ab4558f6ea3916f1b844a

[ "MIT" ]

null

pokemon/status/__init__.py

Rix565/PygaMone

58879a01b5427328824ab4558f6ea3916f1b844a

[ "MIT" ]

null

pokemon/status/__init__.py

Rix565/PygaMone

58879a01b5427328824ab4558f6ea3916f1b844a

[ "MIT" ]

null

from . import pokemon_status from . import pokemon_stats_modifier from . import status_animations from . import status

23.8

36

0.831933

16

119

5.9375

0.4375

0.421053

0.357895

0

0.134454

119

4

37

29.75

0.92233

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

7b562920603f9c7c1586fe010e39f972e07e4d1e

295

py

Python

hivemind/client/__init__.py

Vsevolod-pl/hivemind

0300cfd91adeb14d91d9659a98221628f9b775b9

[ "MIT" ]

11

2021-06-21T19:56:01.000Z

2021-12-22T09:06:09.000Z

hivemind/client/__init__.py

Vsevolod-pl/hivemind

0300cfd91adeb14d91d9659a98221628f9b775b9

[ "MIT" ]

null

hivemind/client/__init__.py

Vsevolod-pl/hivemind

0300cfd91adeb14d91d9659a98221628f9b775b9

[ "MIT" ]

null

from hivemind.client.expert import RemoteExpert from hivemind.client.moe import RemoteMixtureOfExperts from hivemind.client.switch_moe import RemoteSwitchMixtureOfExperts from hivemind.client.averaging import DecentralizedAverager from hivemind.client.averaging.training import TrainingAverager

49.166667

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32

295

8.21875

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0.342205

0.205323

0

0.067797

295

5

68

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true

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1

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null

1

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1

0

null

0

1

0

1

0

1

0

7

7b5f108eb1ce335f83209dbe9be032e2e701f074

52,888

py

Python

src/pgr_corpus.py

santiagonasar/PDR

2485be9abf92b2785cb3c8524a01783a8fd60f84

[ "Apache-2.0" ]

7

2019-04-01T15:00:09.000Z

2022-01-04T04:14:53.000Z

src/pgr_corpus.py

santiagonasar/PDR

2485be9abf92b2785cb3c8524a01783a8fd60f84

[ "Apache-2.0" ]

null

src/pgr_corpus.py

santiagonasar/PDR

2485be9abf92b2785cb3c8524a01783a8fd60f84

[ "Apache-2.0" ]

4

2019-03-27T19:54:12.000Z

2021-02-05T01:04:37.000Z

import os import collections import sys import re import relations #### GENE - GO DICTIONARY: GENE ID - (GO ID, EVIDENCE CODE, GO NAME, CATEGORY), (...) #### def dict_g2go(file_g2go): """Creates a dictionary of type {gene1:[(GO_ID, Evidence, GO_name, category), (GO_ID, Evidence, GO_name, category), ...], } :param file_g2go: file with relations gene to GO :return: dict of type {gene1:[(GO_ID, Evidence, GO_name, category), (GO_ID, Evidence, GO_name, category), ...], } """ os.system('gunzip -k ' + file_g2go + '.gz') gene2go = open(file_g2go, 'r', encoding = 'utf-8') gene2go.readline() # skip header relations_g2go = gene2go.readlines() gene2go.close() relations_g2go.pop() dict_gene_go = {} for line in relations_g2go: line = line.split('\t') gene_id = line[1] go = line[2] evidence = line[3] name = line[5] category = line[7][:-1] if gene_id not in dict_gene_go: dict_gene_go[gene_id] = [] dict_gene_go[gene_id].append((go, evidence, name, category)) else: dict_gene_go[gene_id].append((go, evidence, name, category)) os.system('rm ' + file_g2go) return dict_gene_go #### REPLACEMENT OF GENE ANNOTATIONS IN DIVIDED BY SENTENCES ANNOTATIONS FOR THEIR MOST REPRESENTATIVE GO ANNOTATION TO DIVIDED BY SENTENCES GO ANNOTATIONS #### def go_annotations(annotations_path, file_g2go, destination_path): """Generates a file for each abstract with the correspondent phenotype and GO annotations, creates a dictionary of type {gene_id:go_id, gene_id2:go_id, } and a dictionary of type {gene_name:go_name, gene_name:go_name, } :param annotations_path: divided by sentences annotations path :param file_g2go: file with relations gene to GO :param destination_path: destination path :return: file for each abstract with the correspondent phenotype and GO annotations, creates a dictionary of type {gene_id:go_id, gene_id2:go_id, } and a dictionary of type {gene_name:go_name, gene_name:go_name, } annotation file example: 26 29 negative regulation of cell proliferation GO_0008285 279 288 bilateral HP_0012832 313 323 unilateral HP_0012833 """ dict_gene_id_go = dict_g2go(file_g2go) dict_gene_go_id = {} dict_gene_go_name = {} for (dir_path, dir_names, file_names) in os.walk(annotations_path): for filename in file_names: annotation_file = open(annotations_path + filename, 'r', encoding = 'utf-8') contents = annotation_file.readlines() annotation_file.close() annotation_file_go = open(destination_path + filename, 'w', encoding = 'utf-8') save = 0 for line in contents: line = line.split('\t') start = int(line[0]) end = int(line[1]) if save != 0: start = start + save end = end + save if line[3].startswith('HP'): annotation_file_go.write(str(start) + '\t' + str(end) + '\t' + line[2] + '\t' + line[3]) else: value = False for key_g, value_tup in dict_gene_id_go.items(): if line[3][:-1] == key_g: list_evidence = ['EXP', 'IDA', 'IPI', 'IMP', 'IGI', 'IEP', 'HTP', 'HDA', 'HMP', 'HGI', 'HEP', 'ISS', 'ISO', 'ISA', 'ISM', 'IGC', 'IBA', 'IBD', 'IKR', 'IRD', 'RCA', 'TAS', 'NAS', 'IC', 'ND', 'IEA'] # order criteria bins = collections.defaultdict(list) for pair in value_tup: bins[pair[1]].append(pair) value_tup = [pair for i in list_evidence for pair in bins[i]] for v_tup in value_tup: if v_tup[3] == 'Process': # Biological Process value = True end = int(line[1]) + len(v_tup[2]) - len(line[2]) + save save = save + len(v_tup[2]) - len(line[2]) dict_gene_go_id[line[3][:-1]] = v_tup[0].replace(':', '_') dict_gene_go_name[line[2]] = v_tup[2] annotation_file_go.write(str(start) + '\t' + str(end) + '\t' + \ v_tup[2] + '\t' + v_tup[0].replace(':', '_') + '\n') break if not value: # genes with no associated GO terms or no associated GO terms from Biological Processes end = int(line[1]) + len('biological_process') - len(line[2]) + save save = save + len('biological_process') - len(line[2]) dict_gene_go_id[line[3][:-1]] = 'GO_0008150' dict_gene_go_name[line[2]] = 'biological_process' annotation_file_go.write(str(start) + '\t' + str(end) + '\t' + \ 'biological_process' + '\t' + 'GO_0008150' + '\n') annotation_file_go.close() return dict_gene_go_id, dict_gene_go_name #### XML FORMAT GENE AND PHENOTYPE CORPUS #### def pgr_gene(verify_file, destination_path, type = None): """Generates a .xml file for each abstract with sentences with relations in corpus with the correspondent phenotype and gene annotations :param verify_file: file with sentences with relations verified (for test corpus) or file with sentences with relations not verified (for train corpus) or file with all the relations (for corpus without curator correction) :param destination_path: destination path :param type: type (optional) if pretended file is a test corpus file :return: .xml file for each abstract with sentences with relations in corpus with the correspondent phenotype and gene annotations of type: <sentence id="s0" text="In addition, the coexistence of high MACC1 and low NM23-H1 expression and tumor budding was associated with short OS (p AAAA 0.001)."> <entity id="s0.e1" charOffset="51-55" type="GENE" text="NM23" ontology_id="4830"/> <entity id="s0.e2" charOffset="74-79" type="HP" text="tumor" ontology_id="HP_0002664"/> <pair id="s0.p1" e1="s0.e1" e2="s0.e2" pgr="true"/> </sentence> """ verify = open(verify_file, 'r', encoding = 'utf-8') verify.readline() # skip header verify_relations = [line.split('\t') for line in verify] verify.close() verify_relations.sort(key=lambda x: int(x[0])) # sort by abstract identifier iterator = 1 sentence_number = 1 entity_number = 1 pair_number = 1 dict_entities = {} dict_pairs = {} for line in verify_relations: abstract = line[0] sentence = line[1] gene = line[2] phenotype = line[3] gene_id = line[4] phenotype_id = line[5] gene_start_position = line[6] gene_end_position = line[7] phenotype_start_position = line[8] phenotype_end_position = line[9] if type: relation = line[10] else: relation = line[10][:-1] if verify_relations[iterator - 2][0] == abstract: # same abstract if verify_relations[iterator - 2][1] == sentence: # same sentence if int(gene_start_position) < int(phenotype_start_position): dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + gene_start_position + '-' + \ gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ + gene + '" ontology_id="' + gene_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 else: dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + gene_start_position + '-' + \ gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ + gene + '" ontology_id="' + gene_id + '"/>' + '\n')) entity_number += 1 dict_pairs[pair_number] = [] dict_pairs[pair_number].append(((entity_number - 2, entity_number - 1),'\t\t' + '<pair id="s' + str(sentence_number) + '.p' + str(pair_number) + '" e1="s' + str(sentence_number) + \ '.e' + str(entity_number - 2) + '"\n\t\t ' + 'e2="s' + str(sentence_number) + '.e' + str(entity_number - 1) + '" pgr="' + relation.lower() + '"/>' + '\n')) pair_number += 1 else: # different sentence pair_number = 1 entity_number = 1 list_entities = sorted(dict_entities.items()) used_entities_list = [] used_numbers_list = [] to_write_entities = [] right_number = 1 save_alterations = {} for element in range(1, len(list_entities) + 1): if list_entities[element - 1][1][0][0] not in used_entities_list: to_write_entities.append(str(list_entities[element - 1][1][0][1]).replace('e' + str(list_entities[element - 1][0]), 'e' + str(right_number))) used_entities_list.append(list_entities[element - 1][1][0][0]) used_numbers_list.append((list_entities[element - 1][1][0][0], element)) save_alterations['e' + str(list_entities[element - 1][0])] = 'e' + str(right_number) right_number += 1 else: for used_number in used_numbers_list: if used_number[0] == list_entities[element - 1][1][0][0]: save_alterations['e' + str(element)] = 'e' + str(used_number[1]) organized_writing = [] for line_to_write in to_write_entities: first_offset = int(line_to_write.split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[0]) organized_writing.append((first_offset, line_to_write)) organized_writing = sorted(organized_writing, key=lambda tup: tup[0]) new_entity_number = 1 used_keys = [] for organized_tuple in organized_writing: original_entity_number = int(organized_tuple[1].split('.e')[1].split('" charOffset="')[0]) writer.write(re.sub(r'.e[0-9]+', '.e' + str(new_entity_number), organized_tuple[1])) for key, value in save_alterations.items(): if value == 'e' + str(original_entity_number) and key not in used_keys: save_alterations[key] = 'e' + str(new_entity_number) used_keys.append(key) new_entity_number += 1 dict_entities = {} list_pairs = sorted(dict_pairs.items()) for pair in list_pairs: writer.write(str(pair[1][0][1].replace('.e' + str(pair[1][0][0][0]), '.' + save_alterations['e' + str(pair[1][0][0][0])]).replace('.e' + str(pair[1][0][0][1]), '.' + save_alterations['e' + str(pair[1][0][0][1])]))) dict_pairs = {} writer.write('\t' + '</sentence>' + '\n') sentence_number += 1 sentence = sentence.replace(' <', ' l').replace('(<', '(l').replace('(p<', '(pl').replace(' < ', ' l ').replace('.&quot', '.AAAAA').replace('>', 'AAAA').replace('"', 'AAAAAA').replace('<','AAAA').replace('&', 'AAAAA').split('\n')[0] # avoid invalid (bad/not well-formed) XML writer.write('\t' + '<sentence id="s' + str(sentence_number) + '" text="' + sentence + '">' + '\n') if int(gene_start_position) < int(phenotype_start_position): dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + gene_start_position + '-' + \ gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ + gene + '" ontology_id="' + gene_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 else: dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + gene_start_position + '-' + \ gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ + gene + '" ontology_id="' + gene_id + '"/>' + '\n')) entity_number += 1 dict_pairs[pair_number] = [] dict_pairs[pair_number].append(((entity_number - 2, entity_number - 1),'\t\t' + '<pair id="s' + str(sentence_number) + '.p' + str(pair_number) + '" e1="s' + str(sentence_number) + \ '.e' + str(entity_number - 2) + '"\n\t\t ' + 'e2="s' + str(sentence_number) + '.e' + str(entity_number - 1) + '" pgr="' + relation.lower() + '"/>' + '\n')) pair_number += 1 else: # different abstract if iterator != 1: # different for first one pair_number = 1 entity_number = 1 sentence_number = 1 list_entities = sorted(dict_entities.items()) used_entities_list = [] used_numbers_list = [] to_write_entities = [] right_number = 1 save_alterations = {} for element in range(1, len(list_entities) + 1): if list_entities[element - 1][1][0][0] not in used_entities_list: to_write_entities.append(str(list_entities[element - 1][1][0][1]).replace('e' + str(list_entities[element - 1][0]), 'e' + str(right_number))) used_entities_list.append(list_entities[element - 1][1][0][0]) used_numbers_list.append((list_entities[element - 1][1][0][0], element)) save_alterations['e' + str(list_entities[element - 1][0])] = 'e' + str(right_number) right_number += 1 else: for used_number in used_numbers_list: if used_number[0] == list_entities[element - 1][1][0][0]: save_alterations['e' + str(element)] = 'e' + str(used_number[1]) organized_writing = [] for line_to_write in to_write_entities: first_offset = int(line_to_write.split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[0]) organized_writing.append((first_offset, line_to_write)) organized_writing = sorted(organized_writing, key=lambda tup: tup[0]) new_entity_number = 1 used_keys = [] for organized_tuple in organized_writing: original_entity_number = int(organized_tuple[1].split('.e')[1].split('" charOffset="')[0]) writer.write(re.sub(r'.e[0-9]+', '.e' + str(new_entity_number), organized_tuple[1])) for key, value in save_alterations.items(): if value == 'e' + str(original_entity_number) and key not in used_keys: save_alterations[key] = 'e' + str(new_entity_number) used_keys.append(key) new_entity_number += 1 dict_entities = {} list_pairs = sorted(dict_pairs.items()) for pair in list_pairs: writer.write(str(pair[1][0][1].replace('.e' + str(pair[1][0][0][0]), '.' + save_alterations['e' + str(pair[1][0][0][0])]).replace('.e' + str(pair[1][0][0][1]), '.' + save_alterations['e' + str(pair[1][0][0][1])]))) dict_pairs = {} writer.write('\t' + '</sentence>' + '\n') writer.write('</document>' + '\n') writer.close() writer = open(destination_path + abstract + '.xml', 'w', encoding = 'utf-8') writer.write('<?xml version="1.0" encoding="UTF-8"?>' + '\n') writer.write('<document id="' + abstract + '">' + '\n') sentence = sentence.replace(' <', ' l').replace('(<', '(l').replace('(p<', '(pl').replace(' < ', ' l ').replace('.&quot', '.AAAAA').replace('>', 'AAAA').replace('"', 'AAAAAA').replace('<', 'AAAA').replace('&', 'AAAAA').split('\n')[0] # avoid invalid (bad/not well-formed) XML writer.write('\t' + '<sentence id="s' + str(sentence_number) + '" text="' + sentence + '">' + '\n') if int(gene_start_position) < int(phenotype_start_position): dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + gene_start_position + '-' + \ gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ + gene + '" ontology_id="' + gene_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 else: dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + gene_start_position + '-' + \ gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ + gene + '" ontology_id="' + gene_id + '"/>' + '\n')) entity_number += 1 dict_pairs[pair_number] = [] dict_pairs[pair_number].append(((entity_number - 2, entity_number - 1),'\t\t' + '<pair id="s' + str(sentence_number) + '.p' + str(pair_number) + '" e1="s' + str(sentence_number) + \ '.e' + str(entity_number - 2) + '"\n\t\t ' + 'e2="s' + str(sentence_number) + '.e' + str(entity_number - 1) + '" pgr="' + relation.lower() + '"/>' + '\n')) pair_number += 1 iterator += 1 return #### XML FORMAT GO AND PHENOTYPE CORPUS #### def pgr_go(file_g2go, go_annotations_path, annotations_path, verify_file, destination_path, type = None): """Generates a .xml file for each abstract with sentences with relations in corpus with the correspondent phenotype and GO annotations :param file_g2go: file with relations gene to GO :param go_annotations_path: divided by sentences go annotations path :param annotations_path: final annotations path :param verify_file: file with sentences with relations verified (for test corpus) or file with sentences with relations not verified (for train corpus) or file with all the relations (for corpus without curator correction) :param destination_path: destination path :param type: type (optional) if pretended file is a test corpus file :return: .xml file for each abstract with sentences with relations in corpus with the correspondent phenotype and GO annotations of type: <sentence id="s0" text="In addition, the coexistence of high MACC1 and low positive regulation of DNA binding-H1 expression and tumor budding was associated with short OS (p AAAA 0.001)."> <entity id="s0.e1" charOffset="51-85" type="GO" text="positive regulation of DNA binding" ontology_id="GO_0043388"/> <entity id="s0.e2" charOffset="104-109" type="HP" text="tumor" ontology_id="HP_0002664"/> <pair id="s0.p1" e1="s0.e1" e2="s0.e2" pgr="true"/> </sentence> """ dict_g2go_id, dict_g2go_name = go_annotations(annotations_path, file_g2go, go_annotations_path) verify = open(verify_file, 'r', encoding = 'utf-8') verify.readline() # skip header verify_relations = [line.split('\t') for line in verify] verify.close() verify_relations.sort(key=lambda x: int(x[0])) # sort by abstract identifier iterator = 1 sentence_number = 1 entity_number = 1 pair_number = 1 dict_entities = {} dict_pairs = {} save_sentence = '' for line in verify_relations: abstract = line[0] sentence = line[1] gene = line[2] phenotype = line[3] gene_id = line[4] phenotype_id = line[5] gene_start_position = line[6] gene_end_position = line[7] phenotype_start_position = line[8] phenotype_end_position = line[9] if type: relation = line[10] else: relation = line[10][:-1] if verify_relations[iterator - 2][0] == abstract: # same abstract if verify_relations[iterator - 2][1] == sentence: # same sentence go_start_position = gene_start_position go_end_position = str(int(gene_start_position) + len(dict_g2go_name[gene])) if int(gene_start_position) < int(phenotype_start_position): phenotype_start_position = str(int(phenotype_start_position) + len(dict_g2go_name[gene]) - len(gene)) phenotype_end_position = str(int(phenotype_end_position) + len(dict_g2go_name[gene]) - len(gene)) dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + go_start_position + '-' + \ go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 else: dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + go_start_position + '-' + \ go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n')) entity_number += 1 dict_pairs[pair_number] = [] dict_pairs[pair_number].append(((entity_number - 2, entity_number - 1),'\t\t' + '<pair id="s' + str(sentence_number) + '.p' + str(pair_number) + '" e1="s' + str(sentence_number) + \ '.e' + str(entity_number - 2) + '"\n\t\t ' + 'e2="s' + str(sentence_number) + '.e' + str(entity_number - 1) + '" pgr="' + relation.lower() + '"/>' + '\n')) pair_number += 1 else: # different sentence pair_number = 1 entity_number = 1 for entity_n, info_tuple in dict_entities.items(): first_offset = info_tuple[0][1].split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[0] second_offset = info_tuple[0][1].split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[1] if 'GO' in info_tuple[0][1]: go_start_position = str(len(save_sentence.split(info_tuple[0][0], 1)[0])) go_end_position = str(int(go_start_position) + len(dict_g2go_name[info_tuple[0][0]])) dict_entities[entity_n] = [(info_tuple[0][0], info_tuple[0][1].replace(first_offset, go_start_position).replace( second_offset, go_end_position))] save_sentence = save_sentence.replace(info_tuple[0][0], dict_g2go_name[info_tuple[0][0]], 1) writer.write('\t' + '<sentence id="s' + str(sentence_number) + '" text="' + save_sentence + '">' + '\n') list_entities = sorted(dict_entities.items()) used_entities_list = [] used_numbers_list = [] to_write_entities = [] right_number = 1 save_alterations = {} for element in range(1, len(list_entities) + 1): if list_entities[element - 1][1][0][0] not in used_entities_list: to_write_entities.append(str(list_entities[element - 1][1][0][1]).replace('e' + str(list_entities[element - 1][0]), 'e' + str(right_number))) used_entities_list.append(list_entities[element - 1][1][0][0]) used_numbers_list.append((list_entities[element - 1][1][0][0], element)) save_alterations['e' + str(list_entities[element - 1][0])] = 'e' + str(right_number) right_number += 1 else: for used_number in used_numbers_list: if used_number[0] == list_entities[element - 1][1][0][0]: save_alterations['e' + str(element)] = 'e' + str(used_number[1]) organized_writing = [] for line_to_write in to_write_entities: first_offset = int(line_to_write.split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[0]) organized_writing.append((first_offset, line_to_write)) organized_writing = sorted(organized_writing, key=lambda tup: tup[0]) new_entity_number = 1 used_keys = [] for organized_tuple in organized_writing: original_entity_number = int(organized_tuple[1].split('.e')[1].split('" charOffset="')[0]) writer.write(re.sub(r'.e[0-9]+', '.e' + str(new_entity_number), organized_tuple[1])) for key, value in save_alterations.items(): if value == 'e' + str(original_entity_number) and key not in used_keys: save_alterations[key] = 'e' + str(new_entity_number) used_keys.append(key) new_entity_number += 1 dict_entities = {} list_pairs = sorted(dict_pairs.items()) for pair in list_pairs: writer.write(str(pair[1][0][1].replace('.e' + str(pair[1][0][0][0]), '.' + save_alterations['e' + str(pair[1][0][0][0])]).replace('.e' + str(pair[1][0][0][1]), '.' + save_alterations['e' + str(pair[1][0][0][1])]))) dict_pairs = {} save_sentence = '' writer.write('\t' + '</sentence>' + '\n') sentence_number += 1 sentence = sentence.replace(' <', ' l').replace('(<', '(l').replace('(p<', '(pl').replace(' < ', ' l ').replace('.&quot', '.AAAAA').replace('>', 'AAAA').replace('"', 'AAAAAA').replace('<','AAAA').replace('&', 'AAAAA').split('\n')[0] # avoid invalid (bad/not well-formed) XML save_sentence = sentence go_start_position = gene_start_position go_end_position = str(int(gene_start_position) + len(dict_g2go_name[gene])) if int(gene_start_position) < int(phenotype_start_position): phenotype_start_position = str(int(phenotype_start_position) + len(dict_g2go_name[gene]) - len(gene)) phenotype_end_position = str(int(phenotype_end_position) + len(dict_g2go_name[gene]) - len(gene)) dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + go_start_position + '-' + \ go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 else: dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + go_start_position + '-' + \ go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n')) entity_number += 1 dict_pairs[pair_number] = [] dict_pairs[pair_number].append(((entity_number - 2, entity_number - 1),'\t\t' + '<pair id="s' + str(sentence_number) + '.p' + str(pair_number) + '" e1="s' + str(sentence_number) + \ '.e' + str(entity_number - 2) + '"\n\t\t ' + 'e2="s' + str(sentence_number) + '.e' + str(entity_number - 1) + '" pgr="' + relation.lower() + '"/>' + '\n')) pair_number += 1 else: # different abstract if iterator != 1: # different for first one pair_number = 1 entity_number = 1 for entity_n, info_tuple in dict_entities.items(): first_offset = info_tuple[0][1].split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[0] second_offset = info_tuple[0][1].split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[1] if 'GO' in info_tuple[0][1]: go_start_position = str(len(save_sentence.split(info_tuple[0][0], 1)[0])) go_end_position = str(int(go_start_position) + len(dict_g2go_name[info_tuple[0][0]])) dict_entities[entity_n] = [(info_tuple[0][0], info_tuple[0][1].replace(first_offset, go_start_position).replace(second_offset, go_end_position))] save_sentence = save_sentence.replace(info_tuple[0][0], dict_g2go_name[info_tuple[0][0]], 1) writer.write('\t' + '<sentence id="s' + str(sentence_number) + '" text="' + save_sentence + '">' + '\n') sentence_number = 1 list_entities = sorted(dict_entities.items()) used_entities_list = [] used_numbers_list = [] to_write_entities = [] right_number = 1 save_alterations = {} for element in range(1, len(list_entities) + 1): if list_entities[element - 1][1][0][0] not in used_entities_list: to_write_entities.append(str(list_entities[element - 1][1][0][1]).replace('e' + str(list_entities[element - 1][0]), 'e' + str(right_number))) used_entities_list.append(list_entities[element - 1][1][0][0]) used_numbers_list.append((list_entities[element - 1][1][0][0], element)) save_alterations['e' + str(list_entities[element - 1][0])] = 'e' + str(right_number) right_number += 1 else: for used_number in used_numbers_list: if used_number[0] == list_entities[element - 1][1][0][0]: save_alterations['e' + str(element)] = 'e' + str(used_number[1]) organized_writing = [] for line_to_write in to_write_entities: first_offset = int(line_to_write.split('charOffset="')[1].split('"\n\t\t\t')[0].split('-')[0]) organized_writing.append((first_offset, line_to_write)) organized_writing = sorted(organized_writing, key=lambda tup: tup[0]) new_entity_number = 1 used_keys = [] for organized_tuple in organized_writing: original_entity_number = int(organized_tuple[1].split('.e')[1].split('" charOffset="')[0]) writer.write(re.sub(r'.e[0-9]+', '.e' + str(new_entity_number), organized_tuple[1])) for key, value in save_alterations.items(): if value == 'e' + str(original_entity_number) and key not in used_keys: save_alterations[key] = 'e' + str(new_entity_number) used_keys.append(key) new_entity_number += 1 dict_entities = {} list_pairs = sorted(dict_pairs.items()) for pair in list_pairs: writer.write(str(pair[1][0][1].replace('.e' + str(pair[1][0][0][0]), '.' + save_alterations['e' + str(pair[1][0][0][0])]).replace('.e' + str(pair[1][0][0][1]), '.' + save_alterations['e' + str(pair[1][0][0][1])]))) dict_pairs = {} save_sentence = '' writer.write('\t' + '</sentence>' + '\n') writer.write('</document>' + '\n') writer.close() writer = open(destination_path + abstract + '.xml', 'w', encoding = 'utf-8') writer.write('<?xml version="1.0" encoding="UTF-8"?>' + '\n') writer.write('<document id="' + abstract + '">' + '\n') sentence = sentence.replace(' <', ' l').replace('(<', '(l').replace('(p<', '(pl').replace(' < ', ' l ').replace('.&quot', '.AAAAA').replace('>', 'AAAA').replace('"', 'AAAAAA').replace('<', 'AAAA').replace('&', 'AAAAA').split('\n')[0] # avoid invalid (bad/not well-formed) XML save_sentence = sentence go_start_position = gene_start_position go_end_position = str(int(gene_start_position) + len(dict_g2go_name[gene])) if int(gene_start_position) < int(phenotype_start_position): phenotype_start_position = str(int(phenotype_start_position) + len(dict_g2go_name[gene]) - len(gene)) phenotype_end_position = str(int(phenotype_end_position) + len(dict_g2go_name[gene]) - len(gene)) dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + go_start_position + '-' + \ go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 else: dict_entities[entity_number] = [] dict_entities[entity_number].append((phenotype, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + phenotype_start_position + '-' + \ phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n')) entity_number += 1 dict_entities[entity_number] = [] dict_entities[entity_number].append((gene, '\t\t' + '<entity id="s' + str(sentence_number) + '.e' + str(entity_number) + '" charOffset="' + go_start_position + '-' + \ go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n')) entity_number += 1 dict_pairs[pair_number] = [] dict_pairs[pair_number].append(((entity_number - 2, entity_number - 1),'\t\t' + '<pair id="s' + str(sentence_number) + '.p' + str(pair_number) + '" e1="s' + str(sentence_number) + \ '.e' + str(entity_number - 2) + '"\n\t\t ' + 'e2="s' + str(sentence_number) + '.e' + str(entity_number - 1) + '" pgr="' + relation.lower() + '"/>' + '\n')) pair_number += 1 iterator += 1 return #### OBSOLETE (ONE FILE CORPUS) - XML FORMAT GO AND PHENOTYPE CORPUS (ONE FILE) #### # def pgr_go(file_g2go, go_annotations_path, annotations_path, verify_file, destination_file, type = None): # """Generates a .xml file for all sentences with relations in corpus with the correspondent phenotype and GO annotations # # :param file_g2go: file with relations gene to GO # :param go_annotations_path: divided by sentences go annotations path # :param annotations_path: final annotations path # :param verify_file: file with sentences with relations verified (for test corpus) # or file with sentences with relations not verified (for train corpus) # :param destination_file: test corpus file or train corpus file # :param type: type (optional) if pretended file is a test corpus file # :return: .xml file for all sentences with relations in corpus with the correspondent phenotype and GO annotations of type: # # <sentence id="s0" text="In addition, the coexistence of high MACC1 and low positive regulation of DNA binding-H1 # expression and tumor budding was associated with short OS (p AAAA 0.001)."> # <entity id="s0.e1" charOffset="51-85" # type="GO" text="positive regulation of DNA binding" ontology_id="GO_0043388"/> # <entity id="s0.e2" charOffset="104-109" # type="HP" text="tumor" ontology_id="HP_0002664"/> # <pair id="s0.p1" e1="s0.e1" # e2="s0.e2" pgr="true"/> # </sentence> # # """ # # dict_g2go_id, dict_g2go_name = go_annotations(annotations_path, file_g2go, go_annotations_path) # # verify = open(verify_file, 'r', encoding = 'utf-8') # # verify.readline() # skip header # # verify_relations = verify.readlines() # verify.close() # # writer = open(destination_file + '.xml', 'w', encoding = 'utf-8') # writer.write('<?xml version="1.0" encoding="UTF-8"?>' + '\n') # writer.write('<document id="' + destination_file.split('/')[-1] + '">' + '\n') # # count = 0 # number of sentence # # for line in verify_relations: # # sentence = line.split('\t')[1] # gene = line.split('\t')[2] # phenotype = line.split('\t')[3] # gene_id = line.split('\t')[4] # phenotype_id = line.split('\t')[5] # gene_start_position = line.split('\t')[6] # gene_end_position = line.split('\t')[7] # phenotype_start_position = line.split('\t')[8] # phenotype_end_position = line.split('\t')[9] # # if type: # relation = line.split('\t')[10] # # else: # relation = line.split('\t')[10][:-1] # # sentence = sentence.replace(' <', ' l').replace('(<', '(l').replace('(p<', '(pl').replace(' < ', ' l ').replace('.&quot', '.AAAAA').replace('>', 'AAAA').replace('"', 'AAAAAA').replace('<', 'AAAA').replace('&', 'AAAAA').split('\n')[0] # avoid invalid (bad/not well-formed) XML # # sentence = sentence[:int(gene_start_position)] + dict_g2go_name[gene] + sentence[int(gene_end_position):] # # writer.write('\t' + '<sentence id="s' + str(count) + '" text="' + sentence + '">' + '\n') # # go_start_position = gene_start_position # go_end_position = str(int(gene_start_position) + len(dict_g2go_name[gene])) # # if int(gene_start_position) < int(phenotype_start_position): # # phenotype_start_position = str(int(phenotype_start_position) + len(dict_g2go_name[gene]) - len(gene)) # phenotype_end_position = str(int(phenotype_end_position) + len(dict_g2go_name[gene]) - len(gene)) # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e1" charOffset="' + go_start_position + '-' + \ # go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ # + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n') # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e2" charOffset="' + phenotype_start_position + '-' + \ # phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ # + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n') # # else: # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e1" charOffset="' + phenotype_start_position + '-' + \ # phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ # + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n') # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e2" charOffset="' + go_start_position + '-' + \ # go_end_position + '"\n\t\t\t' + 'type="' + 'GO' + '" text="' \ # + dict_g2go_name[gene] + '" ontology_id="' + dict_g2go_id[gene_id] + '"/>' + '\n') # # writer.write('\t\t' + '<pair id="s' + str(count) + '.p1" e1="s' + str(count) + \ # '.e1"\n\t\t ' + 'e2="s' + str(count) + '.e2" pgr="' + relation.lower() + '"/>' + '\n') # # writer.write('\t' + '</sentence>' + '\n') # # count += 1 # # writer.write('</document>' + '\n') # writer.close() # # return #### OBSOLETE (ONE FILE CORPUS) - XML FORMAT GENE AND PHENOTYPE CORPUS (ONE FILE) #### # def pgr_gene(verify_file, destination_file, type = None): # """Generates a .xml file for all sentences with relations in corpus with the correspondent phenotype and gene annotations # # :param verify_file: file with sentences with relations verified (for test corpus) # or file with sentences with relations not verified (for train corpus) # :param destination_file: test corpus file or train corpus file # :param type: type (optional) if pretended file is a test corpus file # :return: .xml file for all sentences with relations in corpus with the correspondent phenotype and gene annotations of type: # # <sentence id="s0" text="In addition, the coexistence of high MACC1 and low NM23-H1 expression and tumor budding # was associated with short OS (p AAAA 0.001)."> # <entity id="s0.e1" charOffset="51-55" # type="GENE" text="NM23" ontology_id="4830"/> # <entity id="s0.e2" charOffset="74-79" # type="HP" text="tumor" ontology_id="HP_0002664"/> # <pair id="s0.p1" e1="s0.e1" # e2="s0.e2" pgr="true"/> # </sentence> # # """ # # verify = open(verify_file, 'r', encoding = 'utf-8') # # verify.readline() # skip header # # verify_relations = verify.readlines() # verify.close() # # writer = open(destination_file + '.xml', 'w', encoding = 'utf-8') # writer.write('<?xml version="1.0" encoding="UTF-8"?>' + '\n') # writer.write('<document id="' + destination_file.split('/')[-1] + '">' + '\n') # # count = 0 # number of sentence # # for line in verify_relations: # # sentence = line.split('\t')[1] # gene = line.split('\t')[2] # phenotype = line.split('\t')[3] # gene_id = line.split('\t')[4] # phenotype_id = line.split('\t')[5] # gene_start_position = line.split('\t')[6] # gene_end_position = line.split('\t')[7] # phenotype_start_position = line.split('\t')[8] # phenotype_end_position = line.split('\t')[9] # # if type: # relation = line.split('\t')[10] # # else: # relation = line.split('\t')[10][:-1] # # sentence = sentence.replace(' <', ' l').replace('(<', '(l').replace('(p<', '(pl').replace(' < ', ' l ').replace('.&quot', '.AAAAA').replace('>', 'AAAA').replace('"', 'AAAAAA').replace('<', 'AAAA').replace('&', 'AAAAA').split('\n')[0] # avoid invalid (bad/not well-formed) XML # # writer.write('\t' + '<sentence id="s' + str(count) + '" text="' + sentence + '">' + '\n') # # if int(gene_start_position) < int(phenotype_start_position): # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e1" charOffset="' + gene_start_position + '-' + \ # gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ # + gene + '" ontology_id="' + gene_id + '"/>' + '\n') # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e2" charOffset="' + phenotype_start_position + '-' + \ # phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ # + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n') # # else: # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e1" charOffset="' + phenotype_start_position + '-' + \ # phenotype_end_position + '"\n\t\t\t' + 'type="' + 'HP' + '" text="' \ # + phenotype + '" ontology_id="' + phenotype_id + '"/>' + '\n') # # writer.write('\t\t' + '<entity id="s' + str(count) + '.e2" charOffset="' + gene_start_position + '-' + \ # gene_end_position + '"\n\t\t\t' + 'type="' + 'GENE' + '" text="' \ # + gene + '" ontology_id="' + gene_id + '"/>' + '\n') # # writer.write('\t\t' + '<pair id="s' + str(count) + '.p1" e1="s' + str(count) + \ # '.e1"\n\t\t ' + 'e2="s' + str(count) + '.e2" pgr="' + relation.lower() + '"/>' + '\n') # # writer.write('\t' + '</sentence>' + '\n') # # count += 1 # # writer.write('</document>' + '\n') # writer.close() # # return #### RUN #### def main(): """Creates a directory with a file for all retrieved abstracts with the respective gene and human phenotype annotations per sentence in XML format :return: directory with a file for all retrieved abstracts with the respective gene and human phenotype annotations per sentence in XML format """ type_gene_or_go = sys.argv[1] if type_gene_or_go == 'gene': os.system('mkdir -p corpora/pgr_gene/ || true') pgr_gene('corpora/relations.tsv', 'corpora/pgr_gene/') elif type_gene_or_go == 'go': os.system('mkdir -p corpora/pgr_go/ || true') os.system('mkdir -p corpora/go_phenotype_annotations/ || true') pgr_go('data/gene2go', 'corpora/go_phenotype_annotations/', 'corpora/gene_phenotype_annotations/', 'corpora/relations.tsv', 'corpora/pgr_go/') else: print('Invalid argument. Argument options: gene or go.') return if __name__ == "__main__": main()

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0

7

7b96b5fa886cd9d651fb4ee9f51b8779c3507bb4

1,674

py

Python

covid19/data/fetch_ncbi_data.py

kingspp/covid19_research

f932f56a38b906cd58477be4e0fabf5c4f372c77

[ "MIT" ]

null

covid19/data/fetch_ncbi_data.py

kingspp/covid19_research

f932f56a38b906cd58477be4e0fabf5c4f372c77

[ "MIT" ]

null

covid19/data/fetch_ncbi_data.py

kingspp/covid19_research

f932f56a38b906cd58477be4e0fabf5c4f372c77

[ "MIT" ]

null

import requests from covid19 import COVID19_MODULE_PATH def fetch_data_and_save(url, file_path): response = requests.get(url) with open(COVID19_MODULE_PATH + f'/data/{file_path}', 'wb') as f: f.write(response.content) url_protein = "https://www.ncbi.nlm.nih.gov/genomes/VirusVariation/vvsearch2/?q=*:*&fq=%7B!tag=SeqType_s%7DSeqType_s:(%22Protein%22)&fq=VirusLineageId_ss:(2697049)&cmd=download&sort=SourceDB_s%20desc,CreateDate_dt%20desc&dlfmt=csv&fl=Accession:id,Release_Date:CreateDate_dt,Species:VirusSpecies_s,Genus:VirusGenus_s,Family:VirusFamily_s,Length:SLen_i,Sequence_Type:SourceDB_s,Nuc_Completeness:Completeness_s,Genotype:Serotype_s,Segment:Segment_s,Authors:Authors_csv,Publications:PubMed_csv,Geo_Location:CountryFull_s,Host:Host_s,Isolation_Source:Isolation_csv,Collection_Date:CollectionDate_s,BioSample:BioSample_s,GenBank_Title:Definition_s" url_nucleotide = "https://www.ncbi.nlm.nih.gov/genomes/VirusVariation/vvsearch2/?q=*:*&fq=%7B!tag=SeqType_s%7DSeqType_s:(%22Nucleotide%22)&fq=VirusLineageId_ss:(2697049)&cmd=download&sort=SourceDB_s%20desc,CreateDate_dt%20desc&dlfmt=csv&fl=Accession:id,Release_Date:CreateDate_dt,Species:VirusSpecies_s,Genus:VirusGenus_s,Family:VirusFamily_s,Length:SLen_i,Sequence_Type:SourceDB_s,Nuc_Completeness:Completeness_s,Genotype:Serotype_s,Segment:Segment_s,Authors:Authors_csv,Publications:PubMed_csv,Geo_Location:CountryFull_s,Host:Host_s,Isolation_Source:Isolation_csv,Collection_Date:CollectionDate_s,BioSample:BioSample_s,GenBank_Title:Definition_s" fetch_data_and_save(url=url_protein, file_path='protein_latest.csv') fetch_data_and_save(url=url_nucleotide, file_path='nucleotide_latest.csv')

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0

0.025862

0.029869

1,674

15

649

111.6

0.799261

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0.2

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0

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0.1

false

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1

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1

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1

0

null

0

8

7bab87ae1112e6f7aece02327e62261c8f498e8a

14,608

py

Python

nova/tests/unit/scheduler/test_client.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

null

nova/tests/unit/scheduler/test_client.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

null

nova/tests/unit/scheduler/test_client.py

bopopescu/nova-token

ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2

[ "Apache-2.0" ]

2

2017-07-20T17:31:34.000Z

2020-07-24T02:42:19.000Z

begin_unit comment|'# Copyright (c) 2014 Red Hat, Inc.' nl|'\n' comment|'# All Rights Reserved.' nl|'\n' comment|'#' nl|'\n' comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may' nl|'\n' comment|'# not use this file except in compliance with the License. You may obtain' nl|'\n' comment|'# a copy of the License at' nl|'\n' comment|'#' nl|'\n' comment|'# http://www.apache.org/licenses/LICENSE-2.0' nl|'\n' comment|'#' nl|'\n' comment|'# Unless required by applicable law or agreed to in writing, software' nl|'\n' comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT' nl|'\n' comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the' nl|'\n' comment|'# License for the specific language governing permissions and limitations' nl|'\n' comment|'# under the License.' nl|'\n' nl|'\n' name|'import' name|'mock' newline|'\n' name|'import' name|'oslo_messaging' name|'as' name|'messaging' newline|'\n' nl|'\n' name|'from' name|'nova' name|'import' name|'context' newline|'\n' name|'from' name|'nova' name|'import' name|'objects' newline|'\n' name|'from' name|'nova' op|'.' name|'objects' name|'import' name|'pci_device_pool' newline|'\n' name|'from' name|'nova' op|'.' name|'scheduler' name|'import' name|'client' name|'as' name|'scheduler_client' newline|'\n' name|'from' name|'nova' op|'.' name|'scheduler' op|'.' name|'client' name|'import' name|'query' name|'as' name|'scheduler_query_client' newline|'\n' name|'from' name|'nova' op|'.' name|'scheduler' op|'.' name|'client' name|'import' name|'report' name|'as' name|'scheduler_report_client' newline|'\n' name|'from' name|'nova' op|'.' name|'scheduler' name|'import' name|'rpcapi' name|'as' name|'scheduler_rpcapi' newline|'\n' name|'from' name|'nova' name|'import' name|'test' newline|'\n' string|'"""Tests for Scheduler Client."""' newline|'\n' nl|'\n' nl|'\n' DECL|class|SchedulerReportClientTestCase name|'class' name|'SchedulerReportClientTestCase' op|'(' name|'test' op|'.' name|'NoDBTestCase' op|')' op|':' newline|'\n' nl|'\n' DECL|member|setUp indent|' ' name|'def' name|'setUp' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'super' op|'(' name|'SchedulerReportClientTestCase' op|',' name|'self' op|')' op|'.' name|'setUp' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'context' op|'=' name|'context' op|'.' name|'get_admin_context' op|'(' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'flags' op|'(' name|'use_local' op|'=' name|'True' op|',' name|'group' op|'=' string|"'conductor'" op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'client' op|'=' name|'scheduler_report_client' op|'.' name|'SchedulerReportClient' op|'(' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'objects' op|'.' name|'ComputeNode' op|',' string|"'save'" op|')' newline|'\n' DECL|member|test_update_resource_stats_saves name|'def' name|'test_update_resource_stats_saves' op|'(' name|'self' op|',' name|'mock_save' op|')' op|':' newline|'\n' indent|' ' name|'cn' op|'=' name|'objects' op|'.' name|'ComputeNode' op|'(' op|')' newline|'\n' name|'cn' op|'.' name|'host' op|'=' string|"'fakehost'" newline|'\n' name|'cn' op|'.' name|'hypervisor_hostname' op|'=' string|"'fakenode'" newline|'\n' name|'cn' op|'.' name|'pci_device_pools' op|'=' name|'pci_device_pool' op|'.' name|'from_pci_stats' op|'(' nl|'\n' op|'[' op|'{' string|'"vendor_id"' op|':' string|'"foo"' op|',' nl|'\n' string|'"product_id"' op|':' string|'"foo"' op|',' nl|'\n' string|'"count"' op|':' number|'1' op|',' nl|'\n' string|'"a"' op|':' string|'"b"' op|'}' op|']' op|')' newline|'\n' name|'self' op|'.' name|'client' op|'.' name|'update_resource_stats' op|'(' name|'cn' op|')' newline|'\n' name|'mock_save' op|'.' name|'assert_called_once_with' op|'(' op|')' newline|'\n' nl|'\n' nl|'\n' DECL|class|SchedulerQueryClientTestCase dedent|'' dedent|'' name|'class' name|'SchedulerQueryClientTestCase' op|'(' name|'test' op|'.' name|'NoDBTestCase' op|')' op|':' newline|'\n' nl|'\n' DECL|member|setUp indent|' ' name|'def' name|'setUp' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'super' op|'(' name|'SchedulerQueryClientTestCase' op|',' name|'self' op|')' op|'.' name|'setUp' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'context' op|'=' name|'context' op|'.' name|'get_admin_context' op|'(' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'client' op|'=' name|'scheduler_query_client' op|'.' name|'SchedulerQueryClient' op|'(' op|')' newline|'\n' nl|'\n' DECL|member|test_constructor dedent|'' name|'def' name|'test_constructor' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'assertIsNotNone' op|'(' name|'self' op|'.' name|'client' op|'.' name|'scheduler_rpcapi' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_rpcapi' op|'.' name|'SchedulerAPI' op|',' string|"'select_destinations'" op|')' newline|'\n' DECL|member|test_select_destinations name|'def' name|'test_select_destinations' op|'(' name|'self' op|',' name|'mock_select_destinations' op|')' op|':' newline|'\n' indent|' ' name|'fake_spec' op|'=' name|'objects' op|'.' name|'RequestSpec' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'client' op|'.' name|'select_destinations' op|'(' nl|'\n' name|'context' op|'=' name|'self' op|'.' name|'context' op|',' nl|'\n' name|'spec_obj' op|'=' name|'fake_spec' nl|'\n' op|')' newline|'\n' name|'mock_select_destinations' op|'.' name|'assert_called_once_with' op|'(' nl|'\n' name|'self' op|'.' name|'context' op|',' name|'fake_spec' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_rpcapi' op|'.' name|'SchedulerAPI' op|',' string|"'update_aggregates'" op|')' newline|'\n' DECL|member|test_update_aggregates name|'def' name|'test_update_aggregates' op|'(' name|'self' op|',' name|'mock_update_aggs' op|')' op|':' newline|'\n' indent|' ' name|'aggregates' op|'=' op|'[' name|'objects' op|'.' name|'Aggregate' op|'(' name|'id' op|'=' number|'1' op|')' op|']' newline|'\n' name|'self' op|'.' name|'client' op|'.' name|'update_aggregates' op|'(' nl|'\n' name|'context' op|'=' name|'self' op|'.' name|'context' op|',' nl|'\n' name|'aggregates' op|'=' name|'aggregates' op|')' newline|'\n' name|'mock_update_aggs' op|'.' name|'assert_called_once_with' op|'(' nl|'\n' name|'self' op|'.' name|'context' op|',' name|'aggregates' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_rpcapi' op|'.' name|'SchedulerAPI' op|',' string|"'delete_aggregate'" op|')' newline|'\n' DECL|member|test_delete_aggregate name|'def' name|'test_delete_aggregate' op|'(' name|'self' op|',' name|'mock_delete_agg' op|')' op|':' newline|'\n' indent|' ' name|'aggregate' op|'=' name|'objects' op|'.' name|'Aggregate' op|'(' name|'id' op|'=' number|'1' op|')' newline|'\n' name|'self' op|'.' name|'client' op|'.' name|'delete_aggregate' op|'(' nl|'\n' name|'context' op|'=' name|'self' op|'.' name|'context' op|',' nl|'\n' name|'aggregate' op|'=' name|'aggregate' op|')' newline|'\n' name|'mock_delete_agg' op|'.' name|'assert_called_once_with' op|'(' nl|'\n' name|'self' op|'.' name|'context' op|',' name|'aggregate' op|')' newline|'\n' nl|'\n' nl|'\n' DECL|class|SchedulerClientTestCase dedent|'' dedent|'' name|'class' name|'SchedulerClientTestCase' op|'(' name|'test' op|'.' name|'NoDBTestCase' op|')' op|':' newline|'\n' nl|'\n' DECL|member|setUp indent|' ' name|'def' name|'setUp' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'super' op|'(' name|'SchedulerClientTestCase' op|',' name|'self' op|')' op|'.' name|'setUp' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'client' op|'=' name|'scheduler_client' op|'.' name|'SchedulerClient' op|'(' op|')' newline|'\n' nl|'\n' DECL|member|test_constructor dedent|'' name|'def' name|'test_constructor' op|'(' name|'self' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'assertIsNotNone' op|'(' name|'self' op|'.' name|'client' op|'.' name|'queryclient' op|')' newline|'\n' name|'self' op|'.' name|'assertIsNotNone' op|'(' name|'self' op|'.' name|'client' op|'.' name|'reportclient' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_query_client' op|'.' name|'SchedulerQueryClient' op|',' nl|'\n' string|"'select_destinations'" op|')' newline|'\n' DECL|member|test_select_destinations name|'def' name|'test_select_destinations' op|'(' name|'self' op|',' name|'mock_select_destinations' op|')' op|':' newline|'\n' indent|' ' name|'fake_spec' op|'=' name|'objects' op|'.' name|'RequestSpec' op|'(' op|')' newline|'\n' name|'self' op|'.' name|'assertIsNone' op|'(' name|'self' op|'.' name|'client' op|'.' name|'queryclient' op|'.' name|'instance' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'client' op|'.' name|'select_destinations' op|'(' string|"'ctxt'" op|',' name|'fake_spec' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'assertIsNotNone' op|'(' name|'self' op|'.' name|'client' op|'.' name|'queryclient' op|'.' name|'instance' op|')' newline|'\n' name|'mock_select_destinations' op|'.' name|'assert_called_once_with' op|'(' string|"'ctxt'" op|',' name|'fake_spec' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_query_client' op|'.' name|'SchedulerQueryClient' op|',' nl|'\n' string|"'select_destinations'" op|',' nl|'\n' name|'side_effect' op|'=' name|'messaging' op|'.' name|'MessagingTimeout' op|'(' op|')' op|')' newline|'\n' DECL|member|test_select_destinations_timeout name|'def' name|'test_select_destinations_timeout' op|'(' name|'self' op|',' name|'mock_select_destinations' op|')' op|':' newline|'\n' comment|'# check if the scheduler service times out properly' nl|'\n' indent|' ' name|'fake_spec' op|'=' name|'objects' op|'.' name|'RequestSpec' op|'(' op|')' newline|'\n' name|'fake_args' op|'=' op|'[' string|"'ctxt'" op|',' name|'fake_spec' op|']' newline|'\n' name|'self' op|'.' name|'assertRaises' op|'(' name|'messaging' op|'.' name|'MessagingTimeout' op|',' nl|'\n' name|'self' op|'.' name|'client' op|'.' name|'select_destinations' op|',' op|'*' name|'fake_args' op|')' newline|'\n' name|'mock_select_destinations' op|'.' name|'assert_has_calls' op|'(' op|'[' name|'mock' op|'.' name|'call' op|'(' op|'*' name|'fake_args' op|')' op|']' op|'*' number|'2' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_query_client' op|'.' name|'SchedulerQueryClient' op|',' nl|'\n' string|"'select_destinations'" op|',' name|'side_effect' op|'=' op|'[' nl|'\n' name|'messaging' op|'.' name|'MessagingTimeout' op|'(' op|')' op|',' name|'mock' op|'.' name|'DEFAULT' op|']' op|')' newline|'\n' DECL|member|test_select_destinations_timeout_once name|'def' name|'test_select_destinations_timeout_once' op|'(' name|'self' op|',' name|'mock_select_destinations' op|')' op|':' newline|'\n' comment|'# scenario: the scheduler service times out & recovers after failure' nl|'\n' indent|' ' name|'fake_spec' op|'=' name|'objects' op|'.' name|'RequestSpec' op|'(' op|')' newline|'\n' name|'fake_args' op|'=' op|'[' string|"'ctxt'" op|',' name|'fake_spec' op|']' newline|'\n' name|'self' op|'.' name|'client' op|'.' name|'select_destinations' op|'(' op|'*' name|'fake_args' op|')' newline|'\n' name|'mock_select_destinations' op|'.' name|'assert_has_calls' op|'(' op|'[' name|'mock' op|'.' name|'call' op|'(' op|'*' name|'fake_args' op|')' op|']' op|'*' number|'2' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_query_client' op|'.' name|'SchedulerQueryClient' op|',' nl|'\n' string|"'update_aggregates'" op|')' newline|'\n' DECL|member|test_update_aggregates name|'def' name|'test_update_aggregates' op|'(' name|'self' op|',' name|'mock_update_aggs' op|')' op|':' newline|'\n' indent|' ' name|'aggregates' op|'=' op|'[' name|'objects' op|'.' name|'Aggregate' op|'(' name|'id' op|'=' number|'1' op|')' op|']' newline|'\n' name|'self' op|'.' name|'client' op|'.' name|'update_aggregates' op|'(' nl|'\n' name|'context' op|'=' string|"'context'" op|',' nl|'\n' name|'aggregates' op|'=' name|'aggregates' op|')' newline|'\n' name|'mock_update_aggs' op|'.' name|'assert_called_once_with' op|'(' nl|'\n' string|"'context'" op|',' name|'aggregates' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_query_client' op|'.' name|'SchedulerQueryClient' op|',' nl|'\n' string|"'delete_aggregate'" op|')' newline|'\n' DECL|member|test_delete_aggregate name|'def' name|'test_delete_aggregate' op|'(' name|'self' op|',' name|'mock_delete_agg' op|')' op|':' newline|'\n' indent|' ' name|'aggregate' op|'=' name|'objects' op|'.' name|'Aggregate' op|'(' name|'id' op|'=' number|'1' op|')' newline|'\n' name|'self' op|'.' name|'client' op|'.' name|'delete_aggregate' op|'(' nl|'\n' name|'context' op|'=' string|"'context'" op|',' nl|'\n' name|'aggregate' op|'=' name|'aggregate' op|')' newline|'\n' name|'mock_delete_agg' op|'.' name|'assert_called_once_with' op|'(' nl|'\n' string|"'context'" op|',' name|'aggregate' op|')' newline|'\n' nl|'\n' dedent|'' op|'@' name|'mock' op|'.' name|'patch' op|'.' name|'object' op|'(' name|'scheduler_report_client' op|'.' name|'SchedulerReportClient' op|',' nl|'\n' string|"'update_resource_stats'" op|')' newline|'\n' DECL|member|test_update_resource_stats name|'def' name|'test_update_resource_stats' op|'(' name|'self' op|',' name|'mock_update_resource_stats' op|')' op|':' newline|'\n' indent|' ' name|'self' op|'.' name|'assertIsNone' op|'(' name|'self' op|'.' name|'client' op|'.' name|'reportclient' op|'.' name|'instance' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'client' op|'.' name|'update_resource_stats' op|'(' name|'mock' op|'.' name|'sentinel' op|'.' name|'cn' op|')' newline|'\n' nl|'\n' name|'self' op|'.' name|'assertIsNotNone' op|'(' name|'self' op|'.' name|'client' op|'.' name|'reportclient' op|'.' name|'instance' op|')' newline|'\n' name|'mock_update_resource_stats' op|'.' name|'assert_called_once_with' op|'(' name|'mock' op|'.' name|'sentinel' op|'.' name|'cn' op|')' newline|'\n' dedent|'' dedent|'' endmarker|'' end_unit

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null

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8

c884804fd450c27dcbf93a0cdccfe58eee499b84

84

py

Python

testability/__init__.py

m-zakeri/ADAFEST

d13f73682aecded34b4e8fa203435e56dd7a280a

[ "MIT" ]

2

2022-01-04T14:47:35.000Z

2022-02-23T07:14:11.000Z

testability/__init__.py

m-zakeri/ADAFEST

d13f73682aecded34b4e8fa203435e56dd7a280a

[ "MIT" ]

1

2021-03-20T07:25:30.000Z

testability/__init__.py

m-zakeri/ADAFEST

d13f73682aecded34b4e8fa203435e56dd7a280a

[ "MIT" ]

1

2022-02-23T07:14:13.000Z

from testability import ml_models from testability import descriptive_statistics

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c89ebc8113c406b19077dabd1a06696ba911b0d2

831

py

Python

amt_tools/datasets/__init__.py

cwitkowitz/transcription-models

e8697d6969b074926ac55986bc02fa1aad04b471

[ "MIT" ]

4

2021-06-15T19:45:26.000Z

2022-03-31T20:42:26.000Z

amt_tools/datasets/__init__.py

cwitkowitz/transcription-models

e8697d6969b074926ac55986bc02fa1aad04b471

[ "MIT" ]

null

amt_tools/datasets/__init__.py

cwitkowitz/transcription-models

e8697d6969b074926ac55986bc02fa1aad04b471

[ "MIT" ]

1

2021-11-08T02:13:02.000Z

""" Should be able to use the following import patterns (e.g.): ------------------------------------------------------------ import amt_tools amt_tools.datasets.GuitarSet() ------------------------------------------------------------ import amt_tools.datasets as dt dt.GuitarSet() ------------------------------------------------------------ from amt_tools import datasets datasets.MAESTRO_V3() ------------------------------------------------------------ from amt_tools.datasets import * MAESTRO_V3() ------------------------------------------------------------ from amt_tools.datasets import MAPS MAPS() ------------------------------------------------------------ from amt_tools.datasets.MAPS import MAPS MAPS() """ from .combo import * from .common import * from .GuitarSet import * from .MAESTRO import * from .MAPS import *

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true

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null

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1

0

1

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1

0

7

c8a6cc55f5f3c8ba923fef4bb877ec9e0cb58a92

147

py

Python

virtualscreening/vina/spark/pbox_description.py

rodrigofaccioli/drugdesign

de15880af361a010729b1f4fbc8a75a2b36688a6

[ "Apache-2.0" ]

3

2015-01-19T20:12:59.000Z

2019-02-21T18:43:04.000Z

virtualscreening/vina/spark/pbox_description.py

rodrigofaccioli/drugdesign

de15880af361a010729b1f4fbc8a75a2b36688a6

[ "Apache-2.0" ]

22

2015-01-05T16:48:54.000Z

2017-01-21T16:36:10.000Z

virtualscreening/vina/spark/pbox_description.py

rodrigofaccioli/drugdesign

de15880af361a010729b1f4fbc8a75a2b36688a6

[ "Apache-2.0" ]

11

2015-03-03T13:32:24.000Z

2020-04-03T11:22:24.000Z

class pbox_description: def __init__(self, pdb_id): self.pdb_id = pdb_id def get_pdb_id(self): return self.pdb_id

18.375

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0.619048

22

147

3.636364

0.454545

0.3125

0.3375

0

0.306122

147

7

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0.784314

0

1

0.4

false

0

0.2

0.8

0

1

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null

1

0

1

0

null

0

1

0

1

0

7

c8f77c04624c00af574ca38fa54c57d6e6625079

67,173

py

Python

pystatsm/pylmm/lmm.py

lukepinkel/pystatsm

baa9078a73ab32ec21347aea65555a3f81f10149

[ "MIT" ]

1

2021-03-21T08:07:40.000Z

pystatsm/pylmm/lmm.py

lukepinkel/pystats

8e8d7588a63c9ca39b6b7ca1e4a6e92f5a1c0c22

[ "MIT" ]

null

pystatsm/pylmm/lmm.py

lukepinkel/pystats

8e8d7588a63c9ca39b6b7ca1e4a6e92f5a1c0c22

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Wed Feb 10 00:01:29 2021 @author: lukepinkel """ import tqdm import numpy as np import scipy as sp import pandas as pd import matplotlib as mpl import scipy.sparse as sps import matplotlib.pyplot as plt from .model_matrices import (construct_model_matrices, make_theta, make_gcov, get_jacmats, transform_theta, get_d2_chol, lndet_gmat, inverse_transform_theta, vcrepara_grad, VarCorrReparam, RestrictedModel) from ..utilities.data_utils import _check_shape from ..utilities.linalg_operations import invech_chol, invech from ..utilities.special_mats import lmat, nmat from ..utilities.numerical_derivs import so_gc_cd, so_fc_cd, fo_fc_cd from ..pyglm.families import (Binomial, ExponentialFamily, Poisson, NegativeBinomial) from ..utilities.output import get_param_table from sksparse.cholmod import cholesky class LMM: def __init__(self, formula, data, weights=None, rcov=None): """ Parameters ---------- formula : string lme4 style formula with random effects specified by terms in parentheses with a bar data : dataframe Dataframe containing data. Missing values should be dropped manually before passing the dataframe. weights : ndarray, optional Array of model weights. The default is None, which sets the weights to one internally. Returns ------- None. """ indices = {} X, Z, y, dims, levels, fe_vars = construct_model_matrices(formula, data, return_fe=True) theta, theta_indices = make_theta(dims) indices['theta'] = theta_indices G, g_indices = make_gcov(theta, indices, dims) indices['g'] = g_indices XZ, Xty, Zty, yty = np.hstack([X, Z]), X.T.dot(y), Z.T.dot(y), y.T.dot(y) XZ = sp.sparse.csc_matrix(XZ) C, m = sps.csc_matrix(XZ.T.dot(XZ)), sps.csc_matrix(np.vstack([Xty, Zty])) M = sps.bmat([[C, m], [m.T, yty]]) M = M.tocsc() self.fe_vars = fe_vars self.X, self.Z, self.y, self.dims, self.levels = X, Z, y, dims, levels self.XZ, self.Xty, self.Zty, self.yty = XZ, Xty, Zty, yty self.C, self.m, self.M = C, m, M self.theta, self.theta_chol = theta, transform_theta(theta, dims, indices) self.G = G self.indices = indices self.R = sps.eye(Z.shape[0]) self.Zs = sps.csc_matrix(Z) self.g_derivs, self.jac_inds = get_jacmats(self.Zs, self.dims, self.indices['theta'], self.indices['g'], self.theta) self.t_indices = list(zip(*np.triu_indices(len(theta)))) self.elim_mats, self.symm_mats, self.iden_mats = {}, {}, {} self.d2g_dchol = {} for key in self.levels: p = self.dims[key]['n_vars'] self.elim_mats[key] = lmat(p).A self.symm_mats[key] = nmat(p).A self.iden_mats[key] = np.eye(p) self.d2g_dchol[key] = get_d2_chol(self.dims[key]) self.bounds = [(0, None) if x==1 else (None, None) for x in self.theta[:-1]]+[(None, None)] self.bounds_2 = [(1e-6, None) if x==1 else (None, None) for x in self.theta[:-1]]+[(None, None)] self.zero_mat = sp.sparse.eye(self.X.shape[1])*0.0 self.zero_mat2 = sp.sparse.eye(1)*0.0 self.rcov = rcov if rcov is None: self.XtX = self.X.T.dot(self.X) self.ZtZ = self.Zs.T.dot(self.Zs) self.ZtX = self.Zs.T.dot(self.X) def update_mme(self, Ginv, Rinv): """ Parameters ---------- Ginv: sparse matrix scipy sparse matrix with inverse covariance block diagonal s: float resid covariance Returns ------- M: sparse matrix updated mixed model matrix """ if type(Rinv) in [float, int, np.float64, np.float32, np.float16, np.int, np.int16, np.int32, np.int64]: M = self.M.copy()/Rinv else: RZX = Rinv.dot(self.XZ) C = sps.csc_matrix(RZX.T.dot(self.XZ)) Ry = Rinv.dot(self.y) m = sps.csc_matrix(np.vstack([self.X.T.dot(Ry), self.Zs.T.dot(Ry)])) M = sps.bmat([[C, m], [m.T, self.y.T.dot(Ry)]]).tocsc() Omega = sp.sparse.block_diag([self.zero_mat, Ginv, self.zero_mat2]) M+=Omega return M def update_gmat(self, theta, inverse=False): """ Parameters ---------- theta: ndarray covariance parameters on the original scale inverse: bool whether or not to inverse G Returns ------- G: sparse matrix updated random effects covariance """ G = self.G for key in self.levels: ng = self.dims[key]['n_groups'] theta_i = theta[self.indices['theta'][key]] if inverse: theta_i = np.linalg.inv(invech(theta_i)).reshape(-1, order='F') else: theta_i = invech(theta_i).reshape(-1, order='F') G.data[self.indices['g'][key]] = np.tile(theta_i, ng) return G def loglike(self, theta, reml=True, use_sw=False, use_sparse=True): """ Parameters ---------- theta: array_like The original parameterization of the model parameters Returns ------- loglike: scalar Log likelihood of the model """ Ginv = self.update_gmat(theta, inverse=True) M = self.update_mme(Ginv, theta[-1]) if (M.nnz / np.product(M.shape) < 0.05) and use_sparse: L = cholesky(M.tocsc()).L().A else: L = np.linalg.cholesky(M.A) ytPy = np.diag(L)[-1]**2 logdetG = lndet_gmat(theta, self.dims, self.indices) logdetR = np.log(theta[-1]) * self.Z.shape[0] if reml: logdetC = np.sum(2*np.log(np.diag(L))[:-1]) ll = logdetR + logdetC + logdetG + ytPy else: Rinv = self.R / theta[-1] RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) _, logdetV = cholesky(Q).slogdet() ll = logdetR + logdetV + logdetG + ytPy return ll def vinvcrossprod(self, A, B, theta): """ Parameters ---------- X : ndarray Array with first dimension equal to number of observations. theta : ndarray covariance parameters. Returns ------- XtVX : ndarray X' V^{-1} X. """ Rinv = self.R / theta[-1] Ginv = self.update_gmat(theta, inverse=True) RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) M = cholesky(Q).inv() AtRB = ((Rinv.dot(B)).T.dot(A)).T AtRZ = (RZ.T.dot(A)).T ZtRB = RZ.T.dot(B) AtVB = AtRB - (M.dot(ZtRB)).T.dot(AtRZ.T).T return AtVB def gradient(self, theta, reml=True, use_sw=False): """ Parameters ---------- theta: array_like The original parameterization of the components Returns ------- gradient: array_like The gradient of the log likelihood with respect to the covariance parameterization Notes ----- """ s = theta[-1] Rinv = self.R / s Ginv = self.update_gmat(theta, inverse=True) if self.rcov is None: RZ = self.Zs / s RX = self.X / s Ry = self.y / s ZtRZ = self.ZtZ / s XtRX = self.XtX / s ZtRX = self.ZtX / s ZtRy = self.Zty / s else: RZ = Rinv.dot(self.Zs) RX = Rinv.dot(self.X) Ry = Rinv.dot(self.y) ZtRZ = RZ.T.dot(self.Zs) XtRX = self.X.T.dot(RX) ZtRX = RZ.T.dot(self.X) ZtRy = RZ.T.dot(self.y) Q = Ginv + ZtRZ M = cholesky(Q).inv() ZtWZ = ZtRZ - ZtRZ.dot(M).dot(ZtRZ) MZtRX = M.dot(ZtRX) XtWX = XtRX - ZtRX.T.dot(MZtRX) XtWX_inv = np.linalg.inv(XtWX) ZtWX = ZtRX - ZtRZ.dot(MZtRX) WX = RX - RZ.dot(MZtRX) U = XtWX_inv.dot(WX.T) Vy = Ry - RZ.dot(M.dot(ZtRy)) Py = Vy - WX.dot(U.dot(self.y)) ZtPy = self.Zs.T.dot(Py) grad = [] for key in (self.levels): ind = self.jac_inds[key] ZtWZi = ZtWZ[ind][:, ind] ZtWXi = ZtWX[ind] ZtPyi = ZtPy[ind] for dGdi in self.g_derivs[key]: g1 = dGdi.dot(ZtWZi).diagonal().sum() g2 = ZtPyi.T.dot(dGdi.dot(ZtPyi)) if reml: g3 = np.trace(XtWX_inv.dot(ZtWXi.T.dot(dGdi.dot(ZtWXi)))) else: g3 = 0 gi = g1 - g2 - g3 grad.append(gi) for dR in self.g_derivs['resid']: g1 = Rinv.diagonal().sum() - (M.dot((RZ.T).dot(dR).dot(RZ))).diagonal().sum() g2 = Py.T.dot(Py) if reml: g3 = np.trace(XtWX_inv.dot(WX.T.dot(WX))) else: g3 = 0 gi = g1 - g2 - g3 grad.append(gi) grad = np.concatenate(grad) grad = _check_shape(np.array(grad)) return grad def hessian(self, theta, reml=True, use_sw=False): """ Parameters ---------- theta: array_like The original parameterization of the components Returns ------- H: array_like The hessian of the log likelihood with respect to the covariance parameterization Notes ----- This function has the infrastructure to support more complex residual covariances that are yet to be implemented. """ Ginv = self.update_gmat(theta, inverse=True) Rinv = self.R / theta[-1] RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) M = cholesky(Q).inv() W = Rinv - RZ.dot(M).dot(RZ.T) WZ = W.dot(self.Zs) WX = W.dot(self.X) XtWX = WX.T.dot(self.X) ZtWX = self.Zs.T.dot(WX) U = np.linalg.solve(XtWX, WX.T) ZtP = WZ.T - ZtWX.dot(np.linalg.solve(XtWX, WX.T)) ZtPZ = self.Zs.T.dot(ZtP.T) Py = W.dot(self.y) - WX.dot(U.dot(self.y)) ZtPy = self.Zs.T.dot(Py) PPy = W.dot(Py) - WX.dot(U.dot(Py)) ZtPPy = self.Zs.T.dot(PPy) H = np.zeros((len(self.theta), len(self.theta))) PJ, yPZJ, ZPJ = [], [], [] ix = [] for key in (self.levels): ind = self.jac_inds[key] ZtPZi = ZtPZ[ind] ZtPyi = ZtPy[ind] ZtPi = ZtP[ind] for i in range(len(self.g_derivs[key])): Gi = self.g_derivs[key][i] PJ.append(Gi.dot(ZtPZi)) yPZJ.append(Gi.dot(ZtPyi)) ZPJ.append((Gi.dot(ZtPi)).T) ix.append(ind) t_indices = list(zip(*np.triu_indices(len(self.theta)-1))) for i, j in t_indices: ZtPZij = ZtPZ[ix[i]][:, ix[j]] PJi, PJj = PJ[i][:, ix[j]], PJ[j][:, ix[i]] yPZJi, JjZPy = yPZJ[i], yPZJ[j] Hij = -np.einsum('ij,ji->', PJi, PJj)\ + (2 * (yPZJi.T.dot(ZtPZij)).dot(JjZPy))[0] H[i, j] = H[j, i] = Hij dR = self.g_derivs['resid'][0] dRZtP = (dR.dot(ZtP.T)) for i in range(len(self.theta)-1): yPZJi = yPZJ[i] ZPJi = ZPJ[i] ZtPPyi = ZtPPy[ix[i]] H[i, -1] = H[-1, i] = 2*yPZJi.T.dot(ZtPPyi) - np.einsum('ij,ji->', ZPJi.T, dRZtP[:, ix[i]]) P = W - WX.dot(U) H[-1, -1] = Py.T.dot(PPy)*2 - np.einsum("ij,ji->", P, P) return H def update_chol(self, theta, inverse=False): """ Parameters ---------- theta: array_like array containing the lower triangular components of the cholesky for each random effect covariance inverse: bool Returns ------- L_dict: dict of array_like Dictionary whose keys and values correspond to level names and the corresponding cholesky of the level's random effects covariance """ L_dict = {} for key in self.levels: theta_i = theta[self.indices['theta'][key]] L_i = invech_chol(theta_i) L_dict[key] = L_i return L_dict def dg_dchol(self, L_dict): """ Parameters ---------- L_dict: dict of array_like Dictionary whose keys and values correspond to level names and the corresponding cholesky of the level's random effects covariance Returns ------- Jf: dict of array_like For each level contains the derivative of the cholesky parameters with respect to the covariance Notes ----- Function evaluates the derivative of the cholesky parameterization with respect to the lower triangular components of the covariance """ Jf = {} for key in self.levels: L = L_dict[key] E = self.elim_mats[key] N = self.symm_mats[key] I = self.iden_mats[key] Jf[key] = E.dot(N.dot(np.kron(L, I))).dot(E.T) return Jf def loglike_c(self, theta_chol, reml=True, use_sw=False): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- loglike: scalar Log likelihood of the model """ theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return self.loglike(theta, reml, use_sw) def gradient_c(self, theta_chol, reml=True, use_sw=False): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- gradient: array_like The gradient of the log likelihood with respect to the covariance parameterization """ theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return self.gradient(theta, reml, use_sw) def hessian_c(self, theta_chol, reml=True): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- hessian: array_like The hessian of the log likelihood with respect to the covariance parameterization """ theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return self.hessian(theta, reml) def gradient_chol(self, theta_chol, reml=True, use_sw=False): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- gradient: array_like The gradient of the log likelihood with respect to the cholesky parameterization """ L_dict = self.update_chol(theta_chol) Jf_dict = self.dg_dchol(L_dict) Jg = self.gradient_c(theta_chol, reml, use_sw) Jf = sp.linalg.block_diag(*Jf_dict.values()) Jf = np.pad(Jf, [[0, 1]]) Jf[-1, -1] = np.exp(theta_chol[-1]) return Jg.dot(Jf) def hessian_chol(self, theta_chol, reml=True): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- hessian: array_like The hessian of the log likelihood with respect to the cholesky parameterization """ L_dict = self.update_chol(theta_chol) Jf_dict = self.dg_dchol(L_dict) Hq = self.hessian_c(theta_chol, reml) Jg = self.gradient_c(theta_chol, reml) Hf = self.d2g_dchol Jf = sp.linalg.block_diag(*Jf_dict.values()) Jf = np.pad(Jf, [[0, 1]]) Jf[-1, -1] = np.exp(theta_chol[-1]) A = Jf.T.dot(Hq).dot(Jf) B = np.zeros_like(Hq) for key in self.levels: ix = self.indices['theta'][key] Jg_i = Jg[ix] Hf_i = Hf[key] C = np.einsum('i,ijk->jk', Jg_i, Hf_i) B[ix, ix[:, None]] += C B[-1, -1] = Jg[-1] * np.exp(theta_chol[-1]) H = A + B return H def _compute_effects(self, theta=None): """ Parameters ---------- theta : ndarray, optional Model parameters in the covariance form Returns ------- beta : ndarray Fixed effects estimated at theta. XtViX_inv : ndarray Fixed effects covariance matrix. u : ndarray Random effect estimate at theta. G : csc_matrix Random effects covariance matrix. R : dia_matrix Matrix of residual covariance. V : csc_matrix Model covariance matrix given fixed effects. """ theta = self.theta if theta is None else theta Ginv = self.update_gmat(theta, inverse=True) M = self.update_mme(Ginv, theta[-1]) XZy = self.XZ.T.dot(self.y) / theta[-1] chol_fac = cholesky(M[:-1, :-1].tocsc()) betau = chol_fac.solve_A(XZy) u = betau[self.X.shape[1]:].reshape(-1) beta = betau[:self.X.shape[1]].reshape(-1) Rinv = self.R / theta[-1] RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) M = cholesky(Q).inv() XtRinvX = self.X.T.dot(Rinv.dot(self.X)) XtRinvZ = self.X.T.dot(Rinv.dot(self.Z)) XtVinvX = XtRinvX - XtRinvZ.dot(M.dot(XtRinvZ.T)) XtVinvX_inv = np.linalg.inv(XtVinvX) return beta, XtVinvX_inv, u def _optimize(self, reml=True, use_grad=True, use_hess=False, approx_hess=False, opt_kws={}): """ Parameters ---------- use_grad : bool, optional If true, the analytic gradient is used during optimization. The default is True. use_hess : bool, optional If true, the analytic hessian is used during optimization. The default is False. approx_hess: bool, optional If true, uses the gradient to approximate the hessian opt_kws : dict, optional Dictionary of options to use in scipy.optimize.minimize. The default is {}. Returns ------- None. """ default_opt_kws = dict(verbose=0, gtol=1e-6, xtol=1e-6) for key, value in default_opt_kws.items(): if key not in opt_kws.keys(): opt_kws[key] = value if use_grad: if use_hess: hess = self.hessian_chol elif approx_hess: hess = lambda x, reml: so_gc_cd(self.gradient_chol, x, args=(reml,)) else: hess = None optimizer = sp.optimize.minimize(self.loglike_c, self.theta, args=(reml,), jac=self.gradient_chol, hess=hess, options=opt_kws, bounds=self.bounds, method='trust-constr') else: jac = lambda x, reml: fo_fc_cd(self.loglike_c, x, args=(reml,)) hess = lambda x, reml: so_fc_cd(self.loglike_c, x, args=(reml,)) optimizer = sp.optimize.minimize(self.loglike_c, self.theta, args=(reml,), jac=jac, hess=hess, bounds=self.bounds, method='trust-constr', options=opt_kws) theta_chol = optimizer.x theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return theta, theta_chol, optimizer def _post_fit(self, theta, theta_chol, optimizer, reml=True, use_grad=True, analytic_se=False): """ Parameters ---------- use_grad : bool, optional If true and analytic_se is False, the gradient is used in the numerical approximation of the hessian. The default is True. analytic_se : bool, optional If true, then the hessian is used to compute standard errors. The default is False. Returns ------- None. """ beta, XtWX_inv, u = self._compute_effects(theta) params = np.concatenate([beta, theta]) re_covs, re_corrs = {}, {} for key, value in self.dims.items(): re_covs[key] = invech(theta[self.indices['theta'][key]].copy()) C = re_covs[key] v = np.diag(np.sqrt(1/np.diag(C))) re_corrs[key] = v.dot(C).dot(v) if analytic_se: Htheta = self.hessian(theta) elif use_grad: Htheta = so_gc_cd(self.gradient, theta) else: Htheta = so_fc_cd(self.loglike, theta) self.theta, self.beta, self.u, self.params = theta, beta, u, params self.Hinv_beta = XtWX_inv self.Hinv_theta = np.linalg.pinv(Htheta/2.0) self.se_beta = np.sqrt(np.diag(XtWX_inv)) self.se_theta = np.sqrt(np.diag(self.Hinv_theta)) self.se_params = np.concatenate([self.se_beta, self.se_theta]) self.optimizer = optimizer self.theta_chol = theta_chol if reml: self.llconst = (self.X.shape[0] - self.X.shape[1])*np.log(2*np.pi) else: self.llconst = self.X.shape[0] * np.log(2*np.pi) self.lltheta = self.optimizer.fun self.ll = (self.llconst + self.lltheta) self.llf = self.ll / -2.0 self.re_covs = re_covs self.re_corrs = re_corrs if reml: n = self.X.shape[0] - self.X.shape[1] d = len(self.theta) else: n = self.X.shape[0] d = self.X.shape[1] + len(self.theta) self.AIC = self.ll + 2.0 * d self.AICC = self.ll + 2 * d * n / (n-d-1) self.BIC = self.ll + d * np.log(n) self.CAIC = self.ll + d * (np.log(n) + 1) sumstats = np.array([self.ll, self.llf, self.AIC, self.AICC, self.BIC, self.CAIC]) self.sumstats = pd.DataFrame(sumstats, index=['ll', 'llf', 'AIC', 'AICC', 'BIC', 'CAIC'], columns=['value']) def predict(self, X=None, Z=None): """ Parameters ---------- X : ndarray, optional Model matrix for fixed effects. The default is None. Z : ndarray, optional Model matrix from random effects. The default is None. Returns ------- yhat : ndarray Model predictions evaluated at X and Z. """ if X is None: X = self.X if Z is None: Z = self.Z yhat = X.dot(self.beta)+Z.dot(self.u) return yhat def fit(self, reml=True, use_grad=True, use_hess=False, approx_hess=False, analytic_se=False, adjusted_pvals=True, opt_kws={}): """ Parameters ---------- use_grad : bool, optional If true, the analytic gradient is used during optimization. The default is True. use_hess : bool, optional If true, the analytic hessian is used during optimization. The default is False. approx_hess: bool, optional If true, uses the gradient to approximate the hessian analytic_se : bool, optional If true, then the hessian is used to compute standard errors. The default is False. opt_kws : dict, optional Dictionary of options to use in scipy.optimize.minimize. The default is {}. Returns ------- None. """ theta, theta_chol, optimizer = self._optimize(reml, use_grad, use_hess, approx_hess, opt_kws) self._post_fit(theta, theta_chol, optimizer, reml, use_grad, analytic_se) param_names = list(self.fe_vars) for level in self.levels: for i, j in list(zip(*np.triu_indices(self.dims[level]['n_vars']))): param_names.append(f"{level}:G[{i}][{j}]") param_names.append("resid_cov") self.param_names = param_names res = np.vstack((self.params, self.se_params)).T res = pd.DataFrame(res, index=param_names, columns=['estimate', 'SE']) res['t'] = res['estimate'] / res['SE'] res['p'] = sp.stats.t(self.X.shape[0]-self.X.shape[1]).sf(np.abs(res['t'])) res['degfree'] = self.X.shape[0] - self.X.shape[1] if adjusted_pvals: L = np.eye(self.X.shape[1]) L_list = [L[[i]] for i in range(self.X.shape[1])] adj_table = pd.DataFrame(self.approx_degfree(L_list), index=self.fe_vars) res.loc[self.fe_vars, 't'] = adj_table['F']**0.5 res.loc[self.fe_vars, 'degfree'] = adj_table['df2'] res.loc[self.fe_vars, 'p'] = adj_table['p'] self.res = res def _restricted_ll_grad(self, theta_chol_f, free_ix, theta_chol_r, reml=True): theta_chol_r[free_ix] = theta_chol_f ll = self.loglike_c(theta_chol_r.copy(), reml) g = self.gradient_chol(theta_chol_r.copy(), reml)[free_ix] return ll, g def profile(self, n_points=40, tb=3): theta = self.theta.copy() free_ix = np.ones_like(theta).astype(bool) reparam = VarCorrReparam(self.dims, self.indices) rmodel = RestrictedModel(self, reparam) tau = reparam.transform(theta) n_theta = len(theta) llmax = self.loglike(self.theta.copy()) H = so_gc_cd(vcrepara_grad, tau, args=(self.gradient, reparam,)) se = np.diag(np.linalg.inv(H/2.0))**0.5 thetas, zetas = np.zeros((n_theta*n_points, n_theta)), np.zeros(n_theta*n_points) k = 0 pbar = tqdm.tqdm(total=n_theta*n_points, smoothing=0.001) for i in range(n_theta): free_ix[i] = False t_mle = tau[i] tau_r = tau.copy() if self.bounds[i][0]==0: lb = np.maximum(0.01, t_mle-tb*se[i]) else: lb = t_mle - tb * se[i] ub = t_mle + tb * se[i] tspace = np.linspace(lb, ub, n_points) for t0 in tspace: x = tau[free_ix] func = lambda x: rmodel.llgrad(x, free_ix, t0) bounds = rmodel.get_bounds(free_ix) opt = sp.optimize.minimize(func, x, jac=True, bounds=bounds, method='trust-constr', options=dict(initial_tr_radius=0.5)) tau_r[free_ix] = opt.x tau_r[~free_ix] = t0 LR = (opt.fun - llmax) zeta = np.sqrt(LR) * np.sign(t0 - tau[~free_ix]) zetas[k] = zeta thetas[k] = reparam.inverse_transform(tau_r) k+=1 pbar.update(1) free_ix[i] = True pbar.close() ix = np.repeat(np.arange(n_theta), n_points) return thetas, zetas, ix def plot_profile(self, thetas, zetas, ix, quantiles=None, figsize=(16, 8)): if quantiles is None: quantiles = np.array([60, 70, 80, 90, 95, 99, 99.9]) quantiles = np.concatenate([(100-quantiles[::-1])/2, 100-(100-quantiles)/2]) theta = self.theta.copy() se_theta = self.se_theta.copy() n_thetas = thetas.shape[1] q = sp.stats.norm(0, 1).ppf(np.array(quantiles)/100) fig, axes = plt.subplots(figsize=(14, 4), ncols=n_thetas, sharey=True) plt.subplots_adjust(wspace=0.05, left=0.05, right=0.95) for i in range(n_thetas): ax = axes[i] x = thetas[ix==i, i] y = zetas[ix==i] trunc = (y>-5)&(y<5) x, y = x[trunc], y[trunc] f_interp = sp.interpolate.interp1d(y, x, fill_value="extrapolate") xq = f_interp(q) ax.plot(x,y) ax.set_xlim(x.min(), x.max()) ax.axhline(0, color='k') sgs = np.zeros((len(q), 2, 2)) sgs[:, 0, 0] = sgs[:, 1, 0] = xq sgs[:, 1, 1] = q xqt = theta[i] + q * se_theta[i] ax.axvline(theta[i], color='k') norm = mpl.colors.TwoSlopeNorm(vcenter=0, vmin=q.min(), vmax=q.max()) lc = mpl.collections.LineCollection(sgs, cmap=plt.cm.bwr, norm=norm) lc.set_array(q) lc.set_linewidth(2) ax.add_collection(lc) ax.scatter(xqt, np.zeros_like(xqt), c=q, cmap=plt.cm.bwr, norm=norm, s=20) ax.set_xlabel(f"$\\theta$[{i}]") ax.set_ylim(-5, 5) fig.suptitle("Profile Zeta Plots") return fig, axes def approx_degfree(self, L_list=None, theta=None, beta=None, method='satterthwaite'): L_list = [np.eye(self.X.shape[1])] if L_list is None else L_list theta = self.theta if theta is None else theta beta = self.beta if beta is None else beta C = np.linalg.inv(self.vinvcrossprod(self.X, self.X, theta)) Vtheta = np.linalg.inv(so_gc_cd(self.gradient, theta)) J = [] for key in self.levels: ind = self.jac_inds[key] XtVZ = self.vinvcrossprod(self.X, self.Z[:, ind], theta) CXtVZ = C.dot(XtVZ) for dGdi in self.g_derivs[key]: dC = CXtVZ.dot(dGdi.dot(CXtVZ.T)) J.append(dC) XtVi = self.vinvcrossprod(self.X, self.R.copy(), theta) CXtVi = C.dot(XtVi) J.append(CXtVi.dot(CXtVi.T)) res = [] for L in L_list: u, Q = np.linalg.eigh(L.dot(C).dot(L.T)) order = np.argsort(u)[::-1] u, Q = u[order], Q[:, order] q = np.linalg.matrix_rank(L) P = Q.T.dot(L) t2 = (P.dot(beta))**2 / u f = np.sum(t2) / q D = [] for i in range(q): x = P[i] D.append([np.dot(x, Ji).dot(x) for Ji in J]) D = np.asarray(D) nu_d = np.array([D[i].T.dot(Vtheta).dot(D[i]) for i in range(q)]) nu_m = u**2 / nu_d E = np.sum(nu_m[nu_m>2] / (nu_m[nu_m>2] - 2.0)) nu = 2.0 * E / (E - q) res.append(dict(F=f, df1=q, df2=nu, p=sp.stats.f(q, nu).sf(f))) return res class WLMM: def __init__(self, formula, data, weights=None, fixed_resid_cov=False): """ Parameters ---------- formula : string lme4 style formula with random effects specified by terms in parentheses with a bar data : dataframe Dataframe containing data. Missing values should be dropped manually before passing the dataframe. weights : ndarray, optional Array of model weights. The default is None, which sets the weights to one internally. Returns ------- None. """ if weights is None: weights = np.eye(len(data)) self.weights = sps.csc_matrix(weights) self.weights_inv = sps.csc_matrix(np.linalg.inv(weights)) indices = {} X, Z, y, dims, levels, fe_vars = construct_model_matrices(formula, data, return_fe=True) theta, theta_indices = make_theta(dims) indices['theta'] = theta_indices G, g_indices = make_gcov(theta, indices, dims) indices['g'] = g_indices XZ, Xty, Zty, yty = np.hstack([X, Z]), X.T.dot(y), Z.T.dot(y), y.T.dot(y) XZ = sp.sparse.csc_matrix(XZ) C, m = sps.csc_matrix(XZ.T.dot(XZ)), sps.csc_matrix(np.vstack([Xty, Zty])) M = sps.bmat([[C, m], [m.T, yty]]) M = M.tocsc() self.fe_vars = fe_vars self.X, self.Z, self.y, self.dims, self.levels = X, Z, y, dims, levels self.XZ, self.Xty, self.Zty, self.yty = XZ, Xty, Zty, yty self.C, self.m, self.M = C, m, M self.theta, self.theta_chol = theta, transform_theta(theta, dims, indices) self.G = G self.indices = indices self.R = sps.eye(Z.shape[0]) self.Zs = sps.csc_matrix(Z) self.g_derivs, self.jac_inds = get_jacmats(self.Zs, self.dims, self.indices['theta'], self.indices['g'], self.theta) self.t_indices = list(zip(*np.triu_indices(len(theta)))) self.elim_mats, self.symm_mats, self.iden_mats = {}, {}, {} self.d2g_dchol = {} for key in self.levels: p = self.dims[key]['n_vars'] self.elim_mats[key] = lmat(p).A self.symm_mats[key] = nmat(p).A self.iden_mats[key] = np.eye(p) self.d2g_dchol[key] = get_d2_chol(self.dims[key]) self.bounds = [(0, None) if x==1 else (None, None) for x in self.theta[:-1]]+[(None, None)] self.bounds_2 = [(1e-6, None) if x==1 else (None, None) for x in self.theta[:-1]]+[(None, None)] self.zero_mat = sp.sparse.eye(self.X.shape[1])*0.0 self.zero_mat2 = sp.sparse.eye(1)*0.0 self.rcov = self.weights self.fixed_resid_cov = fixed_resid_cov def update_mme(self, Ginv, Rinv): """ Parameters ---------- Ginv: sparse matrix scipy sparse matrix with inverse covariance block diagonal s: float resid covariance Returns ------- M: sparse matrix updated mixed model matrix """ if type(Rinv) in [float, int, np.float64, np.float32, np.float16, np.int, np.int16, np.int32, np.int64]: M = self.M.copy()/Rinv else: RZX = Rinv.dot(self.XZ) C = sps.csc_matrix(RZX.T.dot(self.XZ)) Ry = Rinv.dot(self.y) m = sps.csc_matrix(np.vstack([self.X.T.dot(Ry), self.Zs.T.dot(Ry)])) M = sps.bmat([[C, m], [m.T, self.y.T.dot(Ry)]]).tocsc() Omega = sp.sparse.block_diag([self.zero_mat, Ginv, self.zero_mat2]) M+=Omega return M def update_gmat(self, theta, inverse=False): """ Parameters ---------- theta: ndarray covariance parameters on the original scale inverse: bool whether or not to inverse G Returns ------- G: sparse matrix updated random effects covariance """ G = self.G for key in self.levels: ng = self.dims[key]['n_groups'] theta_i = theta[self.indices['theta'][key]] if inverse: theta_i = np.linalg.inv(invech(theta_i)).reshape(-1, order='F') else: theta_i = invech(theta_i).reshape(-1, order='F') G.data[self.indices['g'][key]] = np.tile(theta_i, ng) return G def loglike(self, theta, reml=True, use_sw=False, use_sparse=True): """ Parameters ---------- theta: array_like The original parameterization of the model parameters Returns ------- loglike: scalar Log likelihood of the model """ s = 1.0 if self.fixed_resid_cov else theta[-1] Rinv = self.weights_inv.dot(self.R / s).dot(self.weights_inv) Ginv = self.update_gmat(theta, inverse=True) M = self.update_mme(Ginv, Rinv) if (M.nnz / np.product(M.shape) < 0.05) and use_sparse: L = cholesky(M.tocsc()).L().A else: L = np.linalg.cholesky(M.A) ytPy = np.diag(L)[-1]**2 logdetG = lndet_gmat(theta, self.dims, self.indices) logdetR = np.log(theta[-1]) * self.Z.shape[0] if reml: logdetC = np.sum(2*np.log(np.diag(L))[:-1]) ll = logdetR + logdetC + logdetG + ytPy else: Rinv = self.R / theta[-1] RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) _, logdetV = cholesky(Q).slogdet() ll = logdetR + logdetV + logdetG + ytPy return ll def vinvcrossprod(self, X, theta): """ Parameters ---------- X : ndarray Array with first dimension equal to number of observations. theta : ndarray covariance parameters. Returns ------- XtVX : ndarray X' V^{-1} X. """ s = 1.0 if self.fixed_resid_cov else theta[-1] Rinv = self.weights_inv.dot(self.R / s).dot(self.weights_inv) Ginv = self.update_gmat(theta, inverse=True) RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) M = cholesky(Q).inv() XtRX = X.T.dot(Rinv.dot(X)) XtRZ = X.T.dot(Rinv.dot(self.Z)) XtVX = XtRX - XtRZ.dot(M.dot(XtRZ.T)) return XtVX def gradient(self, theta, reml=True, use_sw=False): """ Parameters ---------- theta: array_like The original parameterization of the components Returns ------- gradient: array_like The gradient of the log likelihood with respect to the covariance parameterization Notes ----- """ s = 1.0 if self.fixed_resid_cov else theta[-1] Rinv = self.weights_inv.dot(self.R / s).dot(self.weights_inv) Ginv = self.update_gmat(theta, inverse=True) RZ = Rinv.dot(self.Zs) RX = Rinv.dot(self.X) Ry = Rinv.dot(self.y) ZtRZ = RZ.T.dot(self.Zs) XtRX = self.X.T.dot(RX) ZtRX = RZ.T.dot(self.X) ZtRy = RZ.T.dot(self.y) Q = Ginv + ZtRZ M = cholesky(Q).inv() ZtWZ = ZtRZ - ZtRZ.dot(M).dot(ZtRZ) MZtRX = M.dot(ZtRX) XtWX = XtRX - ZtRX.T.dot(MZtRX) XtWX_inv = np.linalg.inv(XtWX) ZtWX = ZtRX - ZtRZ.dot(MZtRX) WX = RX - RZ.dot(MZtRX) U = XtWX_inv.dot(WX.T) Vy = Ry - RZ.dot(M.dot(ZtRy)) Py = Vy - WX.dot(U.dot(self.y)) ZtPy = self.Zs.T.dot(Py) grad = [] for key in (self.levels): ind = self.jac_inds[key] ZtWZi = ZtWZ[ind][:, ind] ZtWXi = ZtWX[ind] ZtPyi = ZtPy[ind] for dGdi in self.g_derivs[key]: g1 = dGdi.dot(ZtWZi).diagonal().sum() g2 = ZtPyi.T.dot(dGdi.dot(ZtPyi)) if reml: g3 = np.trace(XtWX_inv.dot(ZtWXi.T.dot(dGdi.dot(ZtWXi)))) else: g3 = 0 gi = g1 - g2 - g3 grad.append(gi) for dR in self.g_derivs['resid']: g1 = Rinv.diagonal().sum() - (M.dot((RZ.T).dot(dR).dot(RZ))).diagonal().sum() g2 = Py.T.dot(Py) if reml: g3 = np.trace(XtWX_inv.dot(WX.T.dot(WX))) else: g3 = 0 gi = g1 - g2 - g3 grad.append(gi) grad = np.concatenate(grad) grad = _check_shape(np.array(grad)) return grad def hessian(self, theta, reml=True, use_sw=False): """ Parameters ---------- theta: array_like The original parameterization of the components Returns ------- H: array_like The hessian of the log likelihood with respect to the covariance parameterization Notes ----- This function has the infrastructure to support more complex residual covariances that are yet to be implemented. """ s = 1.0 if self.fixed_resid_cov else theta[-1] Rinv = self.weights_inv.dot(self.R / s).dot(self.weights_inv) Ginv = self.update_gmat(theta, inverse=True) RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) M = cholesky(Q).inv() W = Rinv - RZ.dot(M).dot(RZ.T) WZ = W.dot(self.Zs) WX = W.dot(self.X) XtWX = WX.T.dot(self.X) ZtWX = self.Zs.T.dot(WX) U = np.linalg.solve(XtWX, WX.T) ZtP = WZ.T - ZtWX.dot(np.linalg.solve(XtWX, WX.T)) ZtPZ = self.Zs.T.dot(ZtP.T) Py = W.dot(self.y) - WX.dot(U.dot(self.y)) ZtPy = self.Zs.T.dot(Py) PPy = W.dot(Py) - WX.dot(U.dot(Py)) ZtPPy = self.Zs.T.dot(PPy) H = np.zeros((len(self.theta), len(self.theta))) PJ, yPZJ, ZPJ = [], [], [] ix = [] for key in (self.levels): ind = self.jac_inds[key] ZtPZi = ZtPZ[ind] ZtPyi = ZtPy[ind] ZtPi = ZtP[ind] for i in range(len(self.g_derivs[key])): Gi = self.g_derivs[key][i] PJ.append(Gi.dot(ZtPZi)) yPZJ.append(Gi.dot(ZtPyi)) ZPJ.append((Gi.dot(ZtPi)).T) ix.append(ind) t_indices = list(zip(*np.triu_indices(len(self.theta)-1))) for i, j in t_indices: ZtPZij = ZtPZ[ix[i]][:, ix[j]] PJi, PJj = PJ[i][:, ix[j]], PJ[j][:, ix[i]] yPZJi, JjZPy = yPZJ[i], yPZJ[j] Hij = -np.einsum('ij,ji->', PJi, PJj)\ + (2 * (yPZJi.T.dot(ZtPZij)).dot(JjZPy))[0] H[i, j] = H[j, i] = Hij dR = self.g_derivs['resid'][0] dRZtP = (dR.dot(ZtP.T)) for i in range(len(self.theta)-1): yPZJi = yPZJ[i] ZPJi = ZPJ[i] ZtPPyi = ZtPPy[ix[i]] H[i, -1] = H[-1, i] = 2*yPZJi.T.dot(ZtPPyi) - np.einsum('ij,ji->', ZPJi.T, dRZtP[:, ix[i]]) P = W - WX.dot(U) H[-1, -1] = Py.T.dot(PPy)*2 - np.einsum("ij,ji->", P, P) return H def update_chol(self, theta, inverse=False): """ Parameters ---------- theta: array_like array containing the lower triangular components of the cholesky for each random effect covariance inverse: bool Returns ------- L_dict: dict of array_like Dictionary whose keys and values correspond to level names and the corresponding cholesky of the level's random effects covariance """ L_dict = {} for key in self.levels: theta_i = theta[self.indices['theta'][key]] L_i = invech_chol(theta_i) L_dict[key] = L_i return L_dict def dg_dchol(self, L_dict): """ Parameters ---------- L_dict: dict of array_like Dictionary whose keys and values correspond to level names and the corresponding cholesky of the level's random effects covariance Returns ------- Jf: dict of array_like For each level contains the derivative of the cholesky parameters with respect to the covariance Notes ----- Function evaluates the derivative of the cholesky parameterization with respect to the lower triangular components of the covariance """ Jf = {} for key in self.levels: L = L_dict[key] E = self.elim_mats[key] N = self.symm_mats[key] I = self.iden_mats[key] Jf[key] = E.dot(N.dot(np.kron(L, I))).dot(E.T) return Jf def loglike_c(self, theta_chol, reml=True, use_sw=False): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- loglike: scalar Log likelihood of the model """ theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return self.loglike(theta, reml, use_sw) def gradient_c(self, theta_chol, reml=True, use_sw=False): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- gradient: array_like The gradient of the log likelihood with respect to the covariance parameterization """ theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return self.gradient(theta, reml, use_sw) def hessian_c(self, theta_chol, reml=True): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- hessian: array_like The hessian of the log likelihood with respect to the covariance parameterization """ theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return self.hessian(theta, reml) def gradient_chol(self, theta_chol, reml=True, use_sw=False): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- gradient: array_like The gradient of the log likelihood with respect to the cholesky parameterization """ L_dict = self.update_chol(theta_chol) Jf_dict = self.dg_dchol(L_dict) Jg = self.gradient_c(theta_chol, reml, use_sw) Jf = sp.linalg.block_diag(*Jf_dict.values()) Jf = np.pad(Jf, [[0, 1]]) Jf[-1, -1] = np.exp(theta_chol[-1]) return Jg.dot(Jf) def hessian_chol(self, theta_chol, reml=True): """ Parameters ---------- theta_chol: array_like The cholesky parameterization of the components Returns ------- hessian: array_like The hessian of the log likelihood with respect to the cholesky parameterization """ L_dict = self.update_chol(theta_chol) Jf_dict = self.dg_dchol(L_dict) Hq = self.hessian_c(theta_chol, reml) Jg = self.gradient_c(theta_chol, reml) Hf = self.d2g_dchol Jf = sp.linalg.block_diag(*Jf_dict.values()) Jf = np.pad(Jf, [[0, 1]]) Jf[-1, -1] = np.exp(theta_chol[-1]) A = Jf.T.dot(Hq).dot(Jf) B = np.zeros_like(Hq) for key in self.levels: ix = self.indices['theta'][key] Jg_i = Jg[ix] Hf_i = Hf[key] C = np.einsum('i,ijk->jk', Jg_i, Hf_i) B[ix, ix[:, None]] += C B[-1, -1] = Jg[-1] * np.exp(theta_chol[-1]) H = A + B return H def _compute_effects(self, theta=None): """ Parameters ---------- theta : ndarray, optional Model parameters in the covariance form Returns ------- beta : ndarray Fixed effects estimated at theta. XtViX_inv : ndarray Fixed effects covariance matrix. u : ndarray Random effect estimate at theta. G : csc_matrix Random effects covariance matrix. R : dia_matrix Matrix of residual covariance. V : csc_matrix Model covariance matrix given fixed effects. """ s = 1.0 if self.fixed_resid_cov else theta[-1] Rinv = self.weights_inv.dot(self.R / s).dot(self.weights_inv) theta = self.theta if theta is None else theta Ginv = self.update_gmat(theta, inverse=True) M = self.update_mme(Ginv, Rinv) XZy = self.XZ.T.dot(Rinv.dot(self.y)) chol_fac = cholesky(M[:-1, :-1].tocsc()) betau = chol_fac.solve_A(XZy) u = betau[self.X.shape[1]:].reshape(-1) beta = betau[:self.X.shape[1]].reshape(-1) RZ = Rinv.dot(self.Zs) Q = Ginv + self.Zs.T.dot(RZ) M = cholesky(Q).inv() XtRinvX = self.X.T.dot(Rinv.dot(self.X)) XtRinvZ = self.X.T.dot(Rinv.dot(self.Z)) XtVinvX = XtRinvX - XtRinvZ.dot(M.dot(XtRinvZ.T)) XtVinvX_inv = np.linalg.inv(XtVinvX) return beta, XtVinvX_inv, u def _optimize(self, reml=True, use_grad=True, use_hess=False, approx_hess=False, opt_kws={}): """ Parameters ---------- use_grad : bool, optional If true, the analytic gradient is used during optimization. The default is True. use_hess : bool, optional If true, the analytic hessian is used during optimization. The default is False. approx_hess: bool, optional If true, uses the gradient to approximate the hessian opt_kws : dict, optional Dictionary of options to use in scipy.optimize.minimize. The default is {}. Returns ------- None. """ default_opt_kws = dict(verbose=0, gtol=1e-6, xtol=1e-6) for key, value in default_opt_kws.items(): if key not in opt_kws.keys(): opt_kws[key] = value if use_grad: if use_hess: hess = self.hessian_chol elif approx_hess: hess = lambda x, reml: so_gc_cd(self.gradient_chol, x, args=(reml,)) else: hess = None optimizer = sp.optimize.minimize(self.loglike_c, self.theta, args=(reml,), jac=self.gradient_chol, hess=hess, options=opt_kws, bounds=self.bounds, method='trust-constr') else: jac = lambda x, reml: fo_fc_cd(self.loglike_c, x, args=(reml,)) hess = lambda x, reml: so_fc_cd(self.loglike_c, x, args=(reml,)) optimizer = sp.optimize.minimize(self.loglike_c, self.theta, args=(reml,), jac=jac, hess=hess, bounds=self.bounds, method='trust-constr', options=opt_kws) theta_chol = optimizer.x theta = inverse_transform_theta(theta_chol.copy(), self.dims, self.indices) return theta, theta_chol, optimizer def _post_fit(self, theta, theta_chol, optimizer, reml=True, use_grad=True, analytic_se=False): """ Parameters ---------- use_grad : bool, optional If true and analytic_se is False, the gradient is used in the numerical approximation of the hessian. The default is True. analytic_se : bool, optional If true, then the hessian is used to compute standard errors. The default is False. Returns ------- None. """ beta, XtWX_inv, u = self._compute_effects(theta) params = np.concatenate([beta, theta]) re_covs, re_corrs = {}, {} for key, value in self.dims.items(): re_covs[key] = invech(theta[self.indices['theta'][key]].copy()) C = re_covs[key] v = np.diag(np.sqrt(1/np.diag(C))) re_corrs[key] = v.dot(C).dot(v) if analytic_se: Htheta = self.hessian(theta) elif use_grad: Htheta = so_gc_cd(self.gradient, theta) else: Htheta = so_fc_cd(self.loglike, theta) self.theta, self.beta, self.u, self.params = theta, beta, u, params self.Hinv_beta = XtWX_inv self.Hinv_theta = np.linalg.pinv(Htheta/2.0) self.se_beta = np.sqrt(np.diag(XtWX_inv)) self.se_theta = np.sqrt(np.diag(self.Hinv_theta)) self.se_params = np.concatenate([self.se_beta, self.se_theta]) self.optimizer = optimizer self.theta_chol = theta_chol if reml: self.llconst = (self.X.shape[0] - self.X.shape[1])*np.log(2*np.pi) else: self.llconst = self.X.shape[0] * np.log(2*np.pi) self.lltheta = self.optimizer.fun self.ll = (self.llconst + self.lltheta) self.llf = self.ll / -2.0 self.re_covs = re_covs self.re_corrs = re_corrs if reml: n = self.X.shape[0] - self.X.shape[1] d = len(self.theta) else: n = self.X.shape[0] d = self.X.shape[1] + len(self.theta) self.AIC = self.ll + 2.0 * d self.AICC = self.ll + 2 * d * n / (n-d-1) self.BIC = self.ll + d * np.log(n) self.CAIC = self.ll + d * (np.log(n) + 1) sumstats = np.array([self.ll, self.llf, self.AIC, self.AICC, self.BIC, self.CAIC]) self.sumstats = pd.DataFrame(sumstats, index=['ll', 'llf', 'AIC', 'AICC', 'BIC', 'CAIC'], columns=['value']) def predict(self, X=None, Z=None): """ Parameters ---------- X : ndarray, optional Model matrix for fixed effects. The default is None. Z : ndarray, optional Model matrix from random effects. The default is None. Returns ------- yhat : ndarray Model predictions evaluated at X and Z. """ if X is None: X = self.X if Z is None: Z = self.Z yhat = X.dot(self.beta)+Z.dot(self.u) return yhat def fit(self, reml=True, use_grad=True, use_hess=False, approx_hess=False, analytic_se=False, opt_kws={}): """ Parameters ---------- use_grad : bool, optional If true, the analytic gradient is used during optimization. The default is True. use_hess : bool, optional If true, the analytic hessian is used during optimization. The default is False. approx_hess: bool, optional If true, uses the gradient to approximate the hessian analytic_se : bool, optional If true, then the hessian is used to compute standard errors. The default is False. opt_kws : dict, optional Dictionary of options to use in scipy.optimize.minimize. The default is {}. Returns ------- None. """ theta, theta_chol, optimizer = self._optimize(reml, use_grad, use_hess, approx_hess, opt_kws) self._post_fit(theta, theta_chol, optimizer, reml, use_grad, analytic_se) param_names = list(self.fe_vars) for level in self.levels: for i, j in list(zip(*np.triu_indices(self.dims[level]['n_vars']))): param_names.append(f"{level}:G[{i}][{j}]") param_names.append("resid_cov") self.param_names = param_names res = np.vstack((self.params, self.se_params)).T res = pd.DataFrame(res, index=param_names, columns=['estimate', 'SE']) res['t'] = res['estimate'] / res['SE'] res['p'] = sp.stats.t(self.X.shape[0]-self.X.shape[1]).sf(np.abs(res['t'])) self.res = res def _restricted_ll_grad(self, theta_chol_f, free_ix, theta_chol_r, reml=True): theta_chol_r[free_ix] = theta_chol_f ll = self.loglike_c(theta_chol_r.copy(), reml) g = self.gradient_chol(theta_chol_r.copy(), reml)[free_ix] return ll, g def profile(self, n_points=40, par_ind=None, reml=True): par_ind = np.ones_like(self.theta_chol) if par_ind is None else par_ind theta_chol = self.theta_chol.copy() n_theta = len(theta_chol) llmax = self.loglike(self.theta.copy()) free_ix = np.ones_like(theta_chol, dtype=bool) Hchol = so_gc_cd(self.gradient_chol, theta_chol, args=(reml,)) se_chol = np.diag(np.linalg.inv(Hchol/2.0))**0.5 thetas, zetas = np.zeros((n_theta*n_points, n_theta)), np.zeros(n_theta*n_points) k = 0 pbar = tqdm.tqdm(total=n_theta*n_points, smoothing=0.001) for i in range(n_theta): free_ix[i] = False t_mle = theta_chol[i] theta_chol_r = theta_chol.copy() if self.bounds[i][0]==0: lb = np.maximum(0.01, t_mle-4.5*se_chol[i]) else: lb = t_mle - 4.5 * se_chol[i] ub = t_mle + 4.5 * se_chol[i] tspace = np.linspace(lb, ub, n_points) for t0 in tspace: theta_chol_r = theta_chol.copy() theta_chol_r[~free_ix] = t0 theta_chol_f = theta_chol[free_ix] func = lambda x : self._restricted_ll_grad(x, free_ix, theta_chol_r, reml) bounds = np.array(self.bounds)[free_ix].tolist() opt = sp.optimize.minimize(func, theta_chol_f, jac=True, bounds=bounds, method='trust-constr') theta_chol_f = opt.x theta_chol_r[free_ix] = theta_chol_f LR = 2.0 * (opt.fun - llmax) zeta = np.sqrt(LR) * np.sign(t0 - theta_chol[~free_ix]) zetas[k] = zeta thetas[k] = theta_chol_r k+=1 pbar.update(1) free_ix[i] = True pbar.close() ix = np.repeat(np.arange(n_theta), n_points) return thetas, zetas, ix def plot_profile(self, n_points=40, par_ind=None, reml=True, quantiles=None): if quantiles is None: quantiles = [0.001, 0.05, 1, 5, 10, 20, 50, 80, 90, 95, 99, 99.5, 99.999] thetas, zetas, ix = self.profile(n_points, par_ind, reml) n_thetas = thetas.shape[1] q = sp.stats.norm(0, 1).ppf(np.array(quantiles)/100) fig, axes = plt.subplots(figsize=(14, 4), ncols=n_thetas, sharey=True) plt.subplots_adjust(wspace=0.05, left=0.05, right=0.95) for i in range(n_thetas): ax = axes[i] x = thetas[ix==i, i] y = zetas[ix==i] trunc = (y>-5)&(y<5) x, y = x[trunc], y[trunc] f_interp = sp.interpolate.interp1d(y, x, fill_value="extrapolate") xq = f_interp(q) ax.plot(x,y) ax.set_xlim(x.min(), x.max()) ax.axhline(0, color='k') for a, b in list(zip(xq, q)): ax.plot((a, a), (0, b), color='k') ax.set_ylim(-5, 5) return thetas, zetas, ix, fig, ax class GLMM(WLMM): ''' Currently an ineffecient implementation of a GLMM, mostly done for fun. A variety of implementations for GLMMs have been proposed in the literature, and a variety of names have been used to refer to each model; the implementation here is based of off linearization using a taylor approximation of the error (assumed to be gaussian) around the current estimates of fixed and random effects. This type of approach may be referred to as penalized quasi-likelihood, or pseudo-likelihood, and may be abbreviated PQL, REPL, RPL, or RQL. ''' def __init__(self, formula, data, weights=None, fam=None): super().__init__(formula=formula, data=data, weights=weights) if isinstance(fam, ExponentialFamily) == False: fam = fam() self.f = fam self.theta_init = self.theta.copy() self.y_original = self.y.copy() self.non_continuous = [isinstance(self.f, Binomial), isinstance(self.f, NegativeBinomial), isinstance(self.f, Poisson)] if np.any(self.non_continuous): self.bounds = self.bounds[:-1]+[(0, 0)] self.fix_resid_cov=True self.theta, self.theta_chol, self.optimizer = self._optimize() self.beta, _, self.u = self._compute_effects(self.theta) if isinstance(self.f, Binomial): self.u /= np.linalg.norm(self.u) self._nfixed_params = self.X.shape[1] self._n_obs = self.X.shape[0] self._n_cov_params = len(self.bounds) self._df1 = self._n_obs - self._nfixed_params self._df2 = self._n_obs - self._nfixed_params - self._n_cov_params - 1 self._ll_const = self._df1 / 2 * np.log(2*np.pi) def _update_model(self, W, nu): nu = _check_shape(nu, 2) self.weights = sps.csc_matrix(W) self.weights_inv = sps.csc_matrix(np.diag(1.0/np.diag((W)))) self.y = nu self.Xty = self.X.T.dot(nu) self.Zty = self.Z.T.dot(nu) self.theta = self.theta_init self.yty = nu.T.dot(nu) def _get_pseudovar(self): eta = self.predict() mu = self.f.inv_link(eta) var_mu = _check_shape(self.f.var_func(mu=mu), 1) gp = self.f.dlink(mu) nu = eta + gp * (_check_shape(self.y_original, 1) - mu) W = np.diag(np.sqrt(var_mu * (self.f.dlink(mu)**2))) return W, nu def fit(self, n_iters=200, tol=1e-3, optimizer_kwargs={}, verbose_outer=True): theta, theta_chol, optimizer = self.theta, self.theta_chol, self.optimizer fit_hist = {} for i in range(n_iters): W, nu = self._get_pseudovar() self._update_model(W, nu) theta_new, theta_chol_new, optimizer_new = self._optimize(**optimizer_kwargs) tvar = (np.linalg.norm(theta)+np.linalg.norm(theta_new)) eps = np.linalg.norm(theta - theta_new) / tvar fit_hist[i] = dict(param_change=eps, theta=theta_new, nu=nu) if verbose_outer: print(eps) if eps < tol: break theta, theta_chol, optimizer = theta_new, theta_chol_new, optimizer_new self.beta, _, self.u = self._compute_effects(theta) self._post_fit(theta, theta_chol, optimizer) self.res = get_param_table(self.params, self.se_params, self.X.shape[0]-len(self.params)) eta_fe = self.X.dot(self.beta) eta = self.X.dot(self.beta)+self.Z.dot(self.u) mu = self.f.inv_link(eta) gp = self.f.dlink(mu) var_mu = _check_shape(self.f.var_func(mu=mu), 1) r_eta_fe = _check_shape(self.y, 1) - eta_fe generalized_chi2 = self.vinvcrossprod(r_eta_fe, theta) resids_raw_linear = _check_shape(self.y, 1) - eta resids_raw_mean = _check_shape(self.y_original, 1) - mu s = 1.0 if self.fixed_resid_cov else theta[-1] R = self.weights.dot(self.R * s).dot(self.weights) var_pearson_linear = R.diagonal() / gp**2 var_pearson_mean = var_mu resids_pearson_linear = resids_raw_linear / np.sqrt(var_pearson_linear) resids_pearson_mean = resids_raw_mean / np.sqrt(var_pearson_mean) pll = self.loglike(self.theta) / -2.0 - self._ll_const aicc = -2 * pll + 2 * self._n_cov_params * self._df1 / self._df2 bic = -2 * pll + self._n_cov_params * np.log(self._df1) self.sumstats = dict(generalized_chi2=generalized_chi2, pseudo_loglike=pll, AICC=aicc, BIC=bic) self.resids = dict(resids_raw_linear=resids_raw_linear, resids_raw_mean=resids_raw_mean, resids_pearson_linear=resids_pearson_linear, resids_pearson_mean=resids_pearson_mean) param_names = list(self.fe_vars) for level in self.levels: for i, j in list(zip(*np.triu_indices(self.dims[level]['n_vars']))): param_names.append(f"{level}:G[{i}][{j}]") param_names.append("resid_cov") self.param_names = param_names self.res.index = param_names """ from pystats.utilities.random_corr import vine_corr from pystats.tests.test_data import generate_data from pylmm.pylmm.lmm import LME from pylmm.pylmm.glmm import WLME, GLMM from pystats.utilities import numerical_derivs np.set_printoptions(precision=3, suppress=True, linewidth=200) formula = "y~1+x1+x2+(1+x3|id1)+(1+x4|id2)" model_dict = {} model_dict['gcov'] = {'id1':invech(np.array([2., 0.4, 2.])), 'id2':invech(np.array([2.,-0.4, 2.]))} model_dict['ginfo'] = {'id1':dict(n_grp=200, n_per=10), 'id2':dict(n_grp=400, n_per=5)} model_dict['mu'] = np.zeros(4) model_dict['vcov'] = vine_corr(4, 20) model_dict['beta'] = np.array([1, -1, 1]) model_dict['n_obs'] = 2000 data, formula = generate_data(formula, model_dict, r=0.6**0.5) model_original = LME(formula, data) model_cholesky = LME3(formula, data) model_original._fit() model_cholesky._fit(opt_kws=dict(verbose=3)) model_cholesky._post_fit() model_original.se_params model_cholesky.se_params """

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Python

evalne/methods/similarity.py

Dru-Mara/EvalNE

b30c894d8db530137b7d2345436ffea7b6ec521f

[ "MIT" ]

92

2019-01-17T15:50:11.000Z

2022-03-19T12:07:12.000Z

evalne/methods/similarity.py

Dru-Mara/EvalNE

b30c894d8db530137b7d2345436ffea7b6ec521f

[ "MIT" ]

12

2019-05-14T09:05:21.000Z

2022-01-05T17:16:35.000Z

evalne/methods/similarity.py

Dru-Mara/EvalNE

b30c894d8db530137b7d2345436ffea7b6ec521f

[ "MIT" ]

23

2019-01-16T03:48:47.000Z

2022-03-19T10:45:39.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- # Author: Mara Alexandru Cristian # Contact: alexandru.mara@ugent.be # Date: 18/12/2018 # This file provides implementations of a variety heuristics for computing node-pair similarities. These heuristics are # commonly used as baselines for network embedding evaluation. All functions of the networkx.link_prediction module are # reimplemented here and extended to directed graphs (following https://surface.syr.edu/etd/355/). # MultiGraphs and weighted graphs are not supported. # TODO: the apply_prediction method should probably return a numpy array (like edge_embeddings does) rather than a list. from __future__ import division import math import random import networkx as nx import numpy as np __all__ = ['common_neighbours', 'jaccard_coefficient', 'cosine_similarity', 'lhn_index', 'topological_overlap', 'adamic_adar_index', 'resource_allocation_index', 'preferential_attachment', 'random_prediction', 'all_baselines'] def _apply_prediction(G, func, ebunch=None): r""" Applies the given function to each node-pair in ebunch, if this is provided, otherwise, it applies the function to all edges in G. Parameters ---------- G : graph A NetworkX graph or digraph. func : func A function on two inputs each being a node in the graph. Can return anything, but it should return a value representing the likelihood of a "link" between the two nodes. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. """ if ebunch is None: ebunch = list(G.edges) return list(map(lambda e: func(e[0], e[1]), ebunch)) def common_neighbours(G, ebunch=None, neighbourhood='in'): r""" Computes the common neighbours similarity between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the common neighbours similarity of nodes 'u' and 'v' is defined as: .. math:: |\Gamma(u) \cap \Gamma(v)| For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: |\Gamma_i(u) \cap \Gamma_i(v)| |\Gamma_o(u) \cap \Gamma_o(v)| """ def predict(u, v): return len(set(G[u]) & set(G[v])) def predict_in(u, v): su = set(map(lambda e: e[0], G.in_edges(u))) sv = set(map(lambda e: e[0], G.in_edges(v))) return len(su & sv) def predict_out(u, v): su = set(map(lambda e: e[1], G.out_edges(u))) sv = set(map(lambda e: e[1], G.out_edges(v))) return len(su & sv) # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def jaccard_coefficient(G, ebunch=None, neighbourhood='in'): r""" Computes the Jaccard coefficient between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the Jaccard coefficient of nodes 'u' and 'v' is defined as: .. math:: |\Gamma(u) \cap \Gamma(v)| / |\Gamma(u) \cup \Gamma(v)| For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: \frac{|\Gamma_i(u) \cap \Gamma_i(v)|}{|\Gamma_i(u) \cup \Gamma_i(v)|} \frac{|\Gamma_o(u) \cap \Gamma_o(v)|}{|\Gamma_o(u) \cup \Gamma_o(v)|} """ def predict(u, v): union_size = len(set(G[u]) | set(G[v])) if union_size == 0: return 0 return len(list(nx.common_neighbors(G, u, v))) / union_size def predict_in(u, v): su = set(map(lambda e: e[0], G.in_edges(u))) sv = set(map(lambda e: e[0], G.in_edges(v))) union_size = len(su | sv) if union_size == 0: return 0 return len(su & sv) / union_size def predict_out(u, v): su = set(map(lambda e: e[1], G.out_edges(u))) sv = set(map(lambda e: e[1], G.out_edges(v))) union_size = len(su | sv) if union_size == 0: return 0 return len(su & sv) / union_size # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def cosine_similarity(G, ebunch=None, neighbourhood='in'): r""" Computes the cosine similarity between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the cosine similarity of nodes 'u' and 'v' is defined as: .. math:: \frac{|\Gamma(u) \cap \Gamma(v)|}{\sqrt{|\Gamma(u)| |\Gamma(v)|}} For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: \frac{|\Gamma_i(u) \cap \Gamma_i(v)|}{\sqrt{|\Gamma_i(u)| |\Gamma_i(v)|}} \frac{|\Gamma_o(u) \cap \Gamma_o(v)|}{\sqrt{|\Gamma_o(u)| |\Gamma_o(v)|}} """ def predict(u, v): den = math.sqrt(len(set(G[u])) * len(set(G[v]))) if den == 0: return 0 return len(list(nx.common_neighbors(G, u, v))) / den def predict_in(u, v): su = set(map(lambda e: e[0], G.in_edges(u))) sv = set(map(lambda e: e[0], G.in_edges(v))) den = math.sqrt(len(su) * len(sv)) if den == 0: return 0 return len(su & sv) / den def predict_out(u, v): su = set(map(lambda e: e[1], G.out_edges(u))) sv = set(map(lambda e: e[1], G.out_edges(v))) den = math.sqrt(len(su) * len(sv)) if den == 0: return 0 return len(su & sv) / den # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def lhn_index(G, ebunch=None, neighbourhood='in'): r""" Computes the Leicht-Holme-Newman index [1]_ between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the Leicht-Holme-Newman index of nodes 'u' and 'v' is defined as: .. math:: \frac{|\Gamma(u) \cap \Gamma(v)|}{|\Gamma(u)| |\Gamma(v)|} For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: \frac{|\Gamma_i(u) \cap \Gamma_i(v)|}{|\Gamma_i(u)| |\Gamma_i(v)|} \frac{|\Gamma_o(u) \cap \Gamma_o(v)|}{|\Gamma_o(u)| |\Gamma_o(v)|} References ---------- .. [1] Leicht, E. A. and Holme, Petter and Newman, M. E. J. (2006). "Vertex similarity in networks.", Phys. Rev. E, 73, 10.1103/PhysRevE.73.026120. """ def predict(u, v): den = G.degree(u) * G.degree(v) if den == 0: return 0 return len(list(nx.common_neighbors(G, u, v))) / den def predict_in(u, v): su = set(map(lambda e: e[0], G.in_edges(u))) sv = set(map(lambda e: e[0], G.in_edges(v))) den = len(su) * len(sv) if den == 0: return 0 return len(su & sv) / den def predict_out(u, v): su = set(map(lambda e: e[1], G.out_edges(u))) sv = set(map(lambda e: e[1], G.out_edges(v))) den = len(su) * len(sv) if den == 0: return 0 return len(su & sv) / den # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def topological_overlap(G, ebunch=None, neighbourhood='in'): r""" Computes the topological overlap [2]_ between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the topological overlap of nodes 'u' and 'v' is defined as: .. math:: \frac{|\Gamma(u) \cap \Gamma(v)|}{min(|\Gamma(u)|,|\Gamma(v)|)} For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: \frac{|\Gamma_i(u) \cap \Gamma_i(v)|}{min(|\Gamma_i(u)|,|\Gamma_i(v)|)} \frac{|\Gamma_o(u) \cap \Gamma_o(v)|}{min(|\Gamma_o(u)|,|\Gamma_o(v)|)} References ---------- .. [2] Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A. L. (2002). "Hierarchical organization of modularity in metabolic networks." Science, 297(5586), 1551-1555. """ def predict(u, v): den = min(G.degree(u), G.degree(v)) if den == 0: return 0 return len(list(nx.common_neighbors(G, u, v))) / den def predict_in(u, v): su = set(map(lambda e: e[0], G.in_edges(u))) sv = set(map(lambda e: e[0], G.in_edges(v))) den = min(len(su), len(sv)) if den == 0: return 0 return len(su & sv) / den def predict_out(u, v): su = set(map(lambda e: e[1], G.out_edges(u))) sv = set(map(lambda e: e[1], G.out_edges(v))) den = min(len(su), len(sv)) if den == 0: return 0 return len(su & sv) / den # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def adamic_adar_index(G, ebunch=None, neighbourhood='in'): r""" Computes the Adamic-Adar index between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the Adamic-Adar index of nodes 'u' and 'v' is defined as: .. math:: \sum_{w \in \Gamma(u) \cap \Gamma(v)} \frac{1}{\log |\Gamma(w)|} For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: \sum_{w \in \Gamma_i(u) \cap \Gamma_i(v)} \frac{1}{\log |\Gamma_i(w)|} \sum_{w \in \Gamma_o(u) \cap \Gamma_o(v)} \frac{1}{\log |\Gamma_o(w)|} """ def predict(u, v): return sum(1 / math.log(G.degree(w)) for w in nx.common_neighbors(G, u, v)) def predict_in(u, v): su = set(map(lambda e: e[0], G.in_edges(u))) sv = set(map(lambda e: e[0], G.in_edges(v))) inters = su & sv res = 0 for w in inters: l = len(G.in_edges(w)) if l > 1: res += 1 / math.log(l) return res def predict_out(u, v): su = set(map(lambda e: e[1], G.out_edges(u))) sv = set(map(lambda e: e[1], G.out_edges(v))) inters = su & sv res = 0 for w in inters: l = len(G.out_edges(w)) if l > 1: res += 1 / math.log(l) return res # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def resource_allocation_index(G, ebunch=None, neighbourhood='in'): r""" Computes the resource allocation index between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the resource allocation index of nodes 'u' and 'v' is defined as: .. math:: \sum_{w \in \Gamma(u) \cap \Gamma(v)} \frac{1}{| \Gamma(w) |} For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: \sum_{w \in \Gamma_i(u) \cap \Gamma_i(v)} \frac{1}{|\Gamma_i(w)|} \sum_{w \in \Gamma_o(u) \cap \Gamma_o(v)} \frac{1}{|\Gamma_o(w)|} """ def predict(u, v): return sum(1 / G.degree(w) for w in nx.common_neighbors(G, u, v)) def predict_in(u, v): su = set(map(lambda e: e[0], G.in_edges(u))) sv = set(map(lambda e: e[0], G.in_edges(v))) inters = su & sv res = 0 for w in inters: l = len(G.in_edges(w)) if l > 1: res += 1 / l return res def predict_out(u, v): su = set(map(lambda e: e[1], G.out_edges(u))) sv = set(map(lambda e: e[1], G.out_edges(v))) inters = su & sv res = 0 for w in inters: l = len(G.out_edges(w)) if l > 1: res += 1 / l return res # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def preferential_attachment(G, ebunch=None, neighbourhood='in'): r""" Computes the preferential attachment score between all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs (see Notes for exact definitions). Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. Notes ----- For undirected graphs the preferential attachment score of nodes 'u' and 'v' is defined as: .. math:: |\Gamma(u)| |\Gamma(v)| For directed graphs we can consider either the in or the out-neighbourhoods, respectively: .. math:: |\Gamma_i(u)| |\Gamma_i(v)| |\Gamma_o(u)| |\Gamma_o(v)| """ def predict(u, v): return G.degree(u) * G.degree(v) def predict_in(u, v): return len(G.in_edges(u)) * len(G.in_edges(v)) def predict_out(u, v): return len(G.out_edges(u)) * len(G.out_edges(v)) # Select the appropriate function and return the results if G.is_directed(): if neighbourhood == 'in': return _apply_prediction(G, predict_in, ebunch) elif neighbourhood == 'out': return _apply_prediction(G, predict_out, ebunch) else: raise ValueError("Unknown parameter value.") return _apply_prediction(G, predict, ebunch) def random_prediction(G, ebunch=None, neighbourhood='in'): r""" Returns a float drawn uniformly at random from the interval (0.0, 1.0] for all node pairs in ebunch; or all nodes in G, if ebunch is None. Can be computed for directed and undirected graphs. Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional Not used. Returns ------- sim : list A list of node-pair similarities in the same order as ebunch. """ def predict(u, v): return 1 if random.random() > 0.5 else 0 return _apply_prediction(G, predict, ebunch) def all_baselines(G, ebunch=None, neighbourhood='in'): r""" Computes a 5-dimensional embedding for all node pairs in ebunch; or all nodes in G, if ebunch is None. Each of the 5 dimensions correspond to the similarity between the nodes as computed by a different function (i.e. CN, JC, AA, RAI and PA). Can be computed for directed and undirected graphs. Parameters ---------- G : graph A NetworkX graph or digraph. ebunch : iterable, optional An iterable of node pairs. If None, all edges in G will be used. Default is None. neighbourhood : string, optional For directed graphs only. Determines if the in or the out-neighbourhood of nodes should be used. Default is 'in'. Returns ------- emb : ndarray Column vector containing node-pair embeddings as rows. Raises ------ ValueError If G is directed and neighbourhood is not one of 'in' or 'out'. """ if ebunch is None: ebunch = list(G.edges) emb = np.zeros((len(ebunch), 5)) for i in range(len(ebunch)): emb[i][0] = common_neighbours(G, [ebunch[i]], neighbourhood)[0] emb[i][1] = jaccard_coefficient(G, [ebunch[i]], neighbourhood)[0] emb[i][2] = adamic_adar_index(G, [ebunch[i]], neighbourhood)[0] emb[i][3] = resource_allocation_index(G, [ebunch[i]], neighbourhood)[0] emb[i][4] = preferential_attachment(G, [ebunch[i]], neighbourhood)[0] return emb

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a811aaef151d5f57dccf25c1f966cb6e9975c7b1

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py

Python

quantum/plugins/nicira/nicira_nvp_plugin/tests/test_config.py

r-mibu/neutron

7aebe2468bdcc1befef7d09136fdedafcb0049ec

[ "Apache-2.0" ]

null

quantum/plugins/nicira/nicira_nvp_plugin/tests/test_config.py

r-mibu/neutron

7aebe2468bdcc1befef7d09136fdedafcb0049ec

[ "Apache-2.0" ]

null

quantum/plugins/nicira/nicira_nvp_plugin/tests/test_config.py

r-mibu/neutron

7aebe2468bdcc1befef7d09136fdedafcb0049ec

[ "Apache-2.0" ]

null

# Copyright 2012 Nicira Networks, Inc. # # 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. import ConfigParser import StringIO import unittest from quantum.plugins.nicira.nicira_nvp_plugin.QuantumPlugin import ( NVPCluster, parse_config, ) class ConfigParserTest(unittest.TestCase): def setUp(self): pass def tearDown(self): pass def test_nvp_config_000(self): nvpc = NVPCluster('cluster1') for f in [ ( 'default_tz_id1', 'ip1', 'port1', 'user1', 'passwd1', 42, 43, 44, 45), ( 'default_tz_id1', 'ip2', 'port2', 'user2', 'passwd2', 42, 43, 44, 45), ( 'default_tz_id1', 'ip3', 'port3', 'user3', 'passwd3', 42, 43, 44, 45), ]: nvpc.add_controller(*f) self.assertTrue(nvpc.name == 'cluster1') self.assertTrue(len(nvpc.controllers) == 3) def test_old_config_parser_old_style(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_IP = <controller ip> PORT = <port> USER = <user> PASSWORD = <pass> """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(cluster1.name == 'cluster1') self.assertTrue( cluster1.controllers[0]['default_tz_uuid'] == '<default uuid>') self.assertTrue( cluster1.controllers[0]['port'] == '<port>') self.assertTrue( cluster1.controllers[0]['user'] == '<user>') self.assertTrue( cluster1.controllers[0]['password'] == '<pass>') self.assertTrue( cluster1.controllers[0]['request_timeout'] == 30) self.assertTrue( cluster1.controllers[0]['http_timeout'] == 10) self.assertTrue( cluster1.controllers[0]['retries'] == 2) self.assertTrue( cluster1.controllers[0]['redirects'] == 2) def test_old_config_parser_new_style(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_CONNECTIONS = CONNECTION1 CONNECTION1 = 10.0.0.1:4242:admin:admin:42:43:44:45 """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(cluster1.name == 'cluster1') self.assertTrue( cluster1.controllers[0]['default_tz_uuid'] == '<default uuid>') self.assertTrue( cluster1.controllers[0]['port'] == '4242') self.assertTrue( cluster1.controllers[0]['user'] == 'admin') self.assertTrue( cluster1.controllers[0]['password'] == 'admin') self.assertTrue( cluster1.controllers[0]['request_timeout'] == 42) self.assertTrue( cluster1.controllers[0]['http_timeout'] == 43) self.assertTrue( cluster1.controllers[0]['retries'] == 44) self.assertTrue( cluster1.controllers[0]['redirects'] == 45) def test_old_config_parser_both_styles(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] NVP_CONTROLLER_IP = <controller ip> PORT = <port> USER = <user> PASSWORD = <pass> DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_CONNECTIONS = CONNECTION1 CONNECTION1 = 10.0.0.1:4242:admin:admin:42:43:44:45 """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(cluster1.name == 'cluster1') self.assertTrue( cluster1.controllers[0]['default_tz_uuid'] == '<default uuid>') self.assertTrue( cluster1.controllers[0]['port'] == '4242') self.assertTrue( cluster1.controllers[0]['user'] == 'admin') self.assertTrue( cluster1.controllers[0]['password'] == 'admin') self.assertTrue( cluster1.controllers[0]['request_timeout'] == 42) self.assertTrue( cluster1.controllers[0]['http_timeout'] == 43) self.assertTrue( cluster1.controllers[0]['retries'] == 44) self.assertTrue( cluster1.controllers[0]['redirects'] == 45) def test_old_config_parser_both_styles(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] NVP_CONTROLLER_IP = <controller ip> PORT = <port> USER = <user> PASSWORD = <pass> DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_CONNECTIONS = CONNECTION1 CONNECTION1 = 10.0.0.1:4242:admin:admin:42:43:44:45 """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(cluster1.name == 'cluster1') self.assertTrue( cluster1.controllers[0]['default_tz_uuid'] == '<default uuid>') self.assertTrue( cluster1.controllers[0]['port'] == '4242') self.assertTrue( cluster1.controllers[0]['user'] == 'admin') self.assertTrue( cluster1.controllers[0]['password'] == 'admin') self.assertTrue( cluster1.controllers[0]['request_timeout'] == 42) self.assertTrue( cluster1.controllers[0]['http_timeout'] == 43) self.assertTrue( cluster1.controllers[0]['retries'] == 44) self.assertTrue( cluster1.controllers[0]['redirects'] == 45) def test_failover_time(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_IP = <controller ip> PORT = 443 USER = admin PASSWORD = admin FAILOVER_TIME = 10 """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(plugin_config['failover_time'] == '10') def test_failover_time_new_style(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_CONNECTIONS = CONNECTION1 CONNECTION1 = 10.0.0.1:4242:admin:admin:42:43:44:45 FAILOVER_TIME = 10 """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(plugin_config['failover_time'] == '10') def test_concurrent_connections_time(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_IP = <controller ip> PORT = 443 USER = admin PASSWORD = admin CONCURRENT_CONNECTIONS = 5 """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(plugin_config['concurrent_connections'] == '5') def test_concurrent_connections_time_new_style(self): config = StringIO.StringIO(""" [DEFAULT] [NVP] DEFAULT_TZ_UUID = <default uuid> NVP_CONTROLLER_CONNECTIONS = CONNECTION1 CONNECTION1 = 10.0.0.1:4242:admin:admin:42:43:44:45 CONCURRENT_CONNECTIONS = 5 """) cp = ConfigParser.ConfigParser() cp.readfp(config) cluster1, plugin_config = parse_config(cp) self.assertTrue(plugin_config['concurrent_connections'] == '5') if __name__ == '__main__': unittest.main()

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9

b521b83f903c70dbbca411e8be96e9500d701c18

100

py

Python

juno/server/http/handler/base/ws_handler.py

DSciLab/juno

1d572c8d3fd06a6c1fcc51b42a6539dd3ae0927e

[ "MIT" ]

null

juno/server/http/handler/base/ws_handler.py

DSciLab/juno

1d572c8d3fd06a6c1fcc51b42a6539dd3ae0927e

[ "MIT" ]

null

juno/server/http/handler/base/ws_handler.py

DSciLab/juno

1d572c8d3fd06a6c1fcc51b42a6539dd3ae0927e

[ "MIT" ]

null

import tornado.websocket class WebSocketBaseHandler(tornado.websocket.WebSocketHandler): pass

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null

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1

0

1

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7

b534ca4d6b9063c02aecc17b4e2e61749ada4c91

5,601

py

Python

test_ssterm.py

Alexander3XL/ssterm

339c2426beeef015a96b2ac8a2552f3d79c5b013

[ "MIT" ]

30

2016-02-25T12:42:21.000Z

2022-03-16T17:18:15.000Z

test_ssterm.py

Alexander3XL/ssterm

339c2426beeef015a96b2ac8a2552f3d79c5b013

[ "MIT" ]

1

2015-02-06T19:48:45.000Z

test_ssterm.py

Alexander3XL/ssterm

339c2426beeef015a96b2ac8a2552f3d79c5b013

[ "MIT" ]

7

2015-12-10T22:03:05.000Z

2021-12-10T13:27:28.000Z

import os import unittest import ssterm class TestInputProcessors(unittest.TestCase): def test_processor_newline(self): f = ssterm.input_processor_newline(b"abc") self.assertEqual(f(b""), b"") self.assertEqual(f(os.linesep.encode()), b"abc") self.assertEqual(f(b"foo" + os.linesep.encode() + b"bar"), b"fooabcbar") def test_processor_hexadecimal(self): f = ssterm.input_processor_hexadecimal() self.assertEqual(f(b""), b"") self.assertEqual(f(b"q"), b"") self.assertEqual(f(b"aa,bb,cc"), b"\xaa\xbb\xcc") self.assertEqual(f(b"aa bb cc"), b"\xaa\xbb\xcc") self.assertEqual(f(b"0xaa,0xbb,0xcc"), b"\xaa\xbb\xcc") self.assertEqual(f(b"0xaa,foo,0xbb,0xcc"), b"\xaa\xbb\xcc") self.assertEqual(f(b"0xaa,foo,0xbb,gar,0xcc"), b"\xaa\xbb\xcc") self.assertEqual(f(b"axb"), b"") self.assertEqual(f(b"a"), b"\xba") self.assertEqual(f(b"012"), b"\x01") self.assertEqual(f(b" "), b"") self.assertEqual(f(b"45"), b"\x45") class TestOutputProcessors(unittest.TestCase): def test_processor_newline(self): f = ssterm.output_processor_newline(b"ab") self.assertEqual(f(b""), b"") self.assertEqual(f(b"ab"), os.linesep.encode()) self.assertEqual(f(b"helloabworld"), b"hello" + os.linesep.encode() + b"world") self.assertEqual(f(b"abababa"), os.linesep.encode() + os.linesep.encode() + os.linesep.encode()) self.assertEqual(f(b"f"), b"af") self.assertEqual(f(b"fooa"), b"foo") self.assertEqual(f(b"bar"), os.linesep.encode() + b"ar") self.assertEqual(f(b"a"), b"") self.assertEqual(f(b""), b"") self.assertEqual(f(b""), b"") self.assertEqual(f(b"b"), os.linesep.encode()) self.assertEqual(f(b"a"), b"") self.assertEqual(f(b""), b"") self.assertEqual(f(b""), b"") self.assertEqual(f(b"r"), b"ar") def test_processor_raw(self): f = ssterm.output_processor_raw() self.assertEqual(f(b""), b"") self.assertEqual(f(b"hello world"), b"hello world") self.assertEqual(f(b"hello" + os.linesep.encode() + b"world"), b"hello" + os.linesep.encode() + b"world") f = ssterm.output_processor_raw(b"AB") self.assertEqual(f(b""), b"") self.assertEqual(f(b"hello world"), b"hello world") self.assertEqual(f(b"hello" + os.linesep.encode() + b"world"), b"hello" + os.linesep.encode() + b"world") self.assertEqual(f(b"helABlo"), b"hel" + ssterm.Color_Codes[0] + b"A" + ssterm.Color_Code_Reset + ssterm.Color_Codes[1] + b"B" + ssterm.Color_Code_Reset + b"lo") def test_processor_hexadecimal(self): f = ssterm.output_processor_hexadecimal() self.assertEqual(f(b""), b"") self.assertEqual(f(b"\xaa\xbb\xcc\xdd"), b"aa bb cc dd ") self.assertEqual(f(b"\xee\xff\x00\x11"), b"ee ff 00 11 ") self.assertEqual(f(b"\xaa\xbb\xcc\xdd"), b"aa bb cc dd ") self.assertEqual(f(b"\xee\xff\x00\x11"), b"ee ff 00 11" + os.linesep.encode()) self.assertEqual(f(b"\x0a\x0a\x0a\x0a"), b"0a 0a 0a 0a ") if len(os.linesep.encode()) == 1: f = ssterm.output_processor_hexadecimal(interpret_newlines=True) self.assertEqual(f(b""), b"") self.assertEqual(f(b"\xaa" + os.linesep.encode() + b"\xbb"), b"aa " + ("%02x " % ord(os.linesep.encode())).encode() + os.linesep.encode() + b"bb ") f = ssterm.output_processor_hexadecimal(b"AB") self.assertEqual(f(b""), b"") self.assertEqual(f(b"\xaa\xbb\xcc\xdd"), b"aa bb cc dd ") self.assertEqual(f(b"AB\xee\xff"), ssterm.Color_Codes[0] + b"41" + ssterm.Color_Code_Reset + b" " + ssterm.Color_Codes[1] + b"42" + ssterm.Color_Code_Reset + b" ee ff ") self.assertEqual(f(b"\xee\xff\x00\x11\xee\xff\x00\x11"), b"ee ff 00 11 ee ff 00 11" + os.linesep.encode()) def test_processor_split(self): f = ssterm.output_processor_split(partial_lines=True) self.assertEqual(f(b""), b"") self.assertEqual(f(b"ABCD"), b"\r41 42 43 44 |ABCD |") self.assertEqual(f(b"EFGH"), b"\r41 42 43 44 45 46 47 48 |ABCDEFGH |") self.assertEqual(f(b""), b"") self.assertEqual(f(b"IJKL"), b"\r41 42 43 44 45 46 47 48 49 4a 4b 4c |ABCDEFGHIJKL |") self.assertEqual(f(b"MNOP"), b"\r41 42 43 44 45 46 47 48 49 4a 4b 4c 4d 4e 4f 50 |ABCDEFGHIJKLMNOP|" + os.linesep.encode()) self.assertEqual(f(b"ABCD"), b"\r41 42 43 44 |ABCD |") f = ssterm.output_processor_split(partial_lines=False) self.assertEqual(f(b""), b"") self.assertEqual(f(b"ABCD"), b"") self.assertEqual(f(b"EFGH"), b"") self.assertEqual(f(b""), b"") self.assertEqual(f(b"IJKL"), b"") self.assertEqual(f(b"MNOP"), b"41 42 43 44 45 46 47 48 49 4a 4b 4c 4d 4e 4f 50 |ABCDEFGHIJKLMNOP|" + os.linesep.encode()) f = ssterm.output_processor_split(b"AB", True) self.assertEqual(f(b""), b"") self.assertEqual(f(b"0ABC"), b"\r30 " + ssterm.Color_Codes[0] + b"41" + ssterm.Color_Code_Reset + b" " + ssterm.Color_Codes[1] + b"42" + ssterm.Color_Code_Reset + b" 43 |0" + ssterm.Color_Codes[0] + b"A" + ssterm.Color_Code_Reset + ssterm.Color_Codes[1] + b"B" + ssterm.Color_Code_Reset + b"C" + b" |") if __name__ == '__main__': unittest.main()

49.131579

359

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3.830144

0.135167

0.299813

0.3198

0.334478

0.835103

0.773579

0.723923

0.633979

0.614304

0.549032

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0.043619

0.230495

5,601

113

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49.566372

0.699304

0

0.370787

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0.202285

0.009641

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0.006427

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null

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b53bfbb84c2955b02d968ee4d5e1ba027800ff27

343,479

py

Python

configs/spec2006/spec_fs.py

farzadfch/gem5

d237637b3c581d53847d8ccca38ffb59b968f073

[ "BSD-3-Clause" ]

1

2019-04-17T23:09:07.000Z

configs/spec2006/spec_fs.py

farzadfch/gem5

d237637b3c581d53847d8ccca38ffb59b968f073

[ "BSD-3-Clause" ]

null

configs/spec2006/spec_fs.py

farzadfch/gem5

d237637b3c581d53847d8ccca38ffb59b968f073

[ "BSD-3-Clause" ]

2

2018-08-24T15:02:16.000Z

2019-01-15T14:58:26.000Z

#spec_fs.py import sys class fsBench: def __init__(self, cmd): self.cmd = cmd self.cwd = "/root" self.simpoint = 1 def setCwd(self, cwd): self.cwd = cwd def setSimpoint(self, simpoint): self.simpoint = simpoint def setStartInst(self, inst): self.start_inst = inst def setName(self, name): self.name = name def getCmd(self): return self.cmd def getCwd(self): return self.cwd def getSimpoint(self): return self.simpoint def getStartInst(self): return self.start_inst def getName(self): return self.name spec_fs_cmd = {} # Set benchmark command line spec_fs_cmd["perlbench"] = fsBench("/cpu2006/bin/spec.perlbench_base.x86-gcc -I/cpu2006/400.perlbench/data/all/input/splitmail.pl /cpu2006/400.perlbench/data/all/input/splitmail.pl 1600 12 26 16 4500") spec_fs_cmd["bzip2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/bzip2 /root/spec/dryer.jpg 280") spec_fs_cmd["milc"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/milc < /root/spec/su3imp.in") spec_fs_cmd["astar"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/astar /root/spec/lake.cfg") spec_fs_cmd["hmmer"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/hmmer /root/spec/nph3.hmm /root/spec/swiss41") spec_fs_cmd["cactusADM"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part7/tasks;taskset -c 2 /root/spec/cactusADM /root/spec/benchADM.par") spec_fs_cmd["hrt1"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;/root/hrt_dump -m 2048 -i 7 -c 0 -o fifo -I 20") spec_fs_cmd["hrt2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part2/tasks;/root/hrt -m 2048 -i 0 -c 1 -o fifo -I 30") spec_fs_cmd["hrt3"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part3/tasks;/root/hrt -m 2048 -i 0 -c 2 -o fifo -I 40") spec_fs_cmd["hrt4"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part4/tasks;/root/hrt -m 2048 -i 0 -c 3 -o fifo -I 60") spec_fs_cmd["leslie3d"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/leslie3d < /root/spec/leslie3d.in") spec_fs_cmd["omnetpp"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/omnetpp /root/spec/omnetpp.ini") #spec_fs_cmd["disparity"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part5/tasks;taskset -c 0 /root/disparity /root") spec_fs_cmd["libquantum"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/libquantum 1397 8") spec_fs_cmd["lbm1"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part2/tasks;taskset -c 1 /root/spec/lbm 3000 reference.dat 0 0 /root/spec/100_100_130_ldc.of") spec_fs_cmd["lbm2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part3/tasks;taskset -c 2 /root/spec/lbm 3000 reference.dat 0 0 /root/spec/100_100_130_ldc.of") spec_fs_cmd["lbm3"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part4/tasks;taskset -c 3 /root/spec/lbm 3000 reference.dat 0 0 /root/spec/100_100_130_ldc.of") spec_fs_cmd["omnetpp1"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part2/tasks;taskset -c 1 /root/spec/omnetpp /root/spec/omnetpp.ini") spec_fs_cmd["omnetpp2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part3/tasks;taskset -c 2 /root/spec/omnetpp /root/spec/omnetpp.ini") spec_fs_cmd["omnetpp3"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part4/tasks;taskset -c 3 /root/spec/omnetpp /root/spec/omnetpp.ini") spec_fs_cmd["libquantum1"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part5/tasks;taskset -c 0 /root/spec/libquantum 1397 8") spec_fs_cmd["libquantum2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part6/tasks;taskset -c 1 /root/spec/libquantum 1397 8") spec_fs_cmd["libquantum3"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part7/tasks;taskset -c 2 /root/spec/libquantum 1397 8") spec_fs_cmd["libquantum4"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part8/tasks;taskset -c 3 /root/spec/libquantum 1397 8") spec_fs_cmd["mcf1"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part5/tasks;taskset -c 0 /root/spec/mcf /root/spec/inp.in") spec_fs_cmd["mcf2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part2/tasks;taskset -c 1 /root/spec/mcf /root/spec/inp.in") spec_fs_cmd["mcf3"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part3/tasks;taskset -c 2 /root/spec/mcf /root/spec/inp.in") spec_fs_cmd["mcf4"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part4/tasks;taskset -c 3 /root/spec/mcf /root/spec/inp.in") spec_fs_cmd["soplex"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part5/tasks;taskset -c 0 /root/spec/soplex -s1 -e -m45000 /root/spec/pds-50.mps") spec_fs_cmd["mcf"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/mcf /root/spec/inp.in") spec_fs_cmd["lbm"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/lbm 3000 reference.dat 0 0 /root/spec/100_100_130_ldc.of") #spec_fs_cmd["soplex"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part5/tasks;taskset -c 0 /root/spec/soplex -s1 -e -m45000 /root/spec/pds-50.mps &;/bin/echo $$ > /sys/fs/cgroup/part1/tasks;/root/hrt -m 2048 -i 0 -c 0 -o fifo -I 20") spec_fs_cmd["gamess"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part7/tasks;taskset -c 2 /root/spec/gamess < /root/spec/cytosine.2.config ") spec_fs_cmd["namd"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/namd --input /root/spec/namd.input") spec_fs_cmd["h264ref"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/h264ref -d /root/spec/foreman_ref_encoder_baseline.cfg") #spec_fs_cmd["bandwidth1"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part2/tasks;/root/bandwidth -m 2048 -t 0 -c 1") #spec_fs_cmd["bandwidth2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part3/tasks;/root/bandwidth -m 2048 -t 0 -c 2") #spec_fs_cmd["bandwidth3"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part4/tasks;/root/bandwidth -m 2048 -t 0 -c 3") spec_fs_cmd["liblinear"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/liblinear-tlarge /root/kdda") spec_fs_cmd["bandwidth1"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;/root/bandwidth -m 4096 -a write -t 0 -c 0&") spec_fs_cmd["bandwidth2"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part3/tasks;/root/bandwidth -m 2048 -a write -t 0 -c 2") spec_fs_cmd["bandwidth3"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part4/tasks;/root/bandwidth -m 2048 -a write -t 0 -c 3") spec_fs_cmd["bandwidth4"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part8/tasks;/root/bandwidth -m 2048 -a write -t 0 -c 3") spec_fs_cmd["bwrite"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;/root/bandwidth -m 4096 -a write -t 0 -c 0") #spec_fs_cmd["bzip2"] = fsBench("/root/latency -m 2048 -i 5") #spec_fs_cmd["bzip2"] = fsBench("/home/prathap/WorkSpace/gem5/util/m5/cpu2006/cpu2006/benchspec/CPU2006/401.bzip2/exe/bzip2_base.gcc43-64bit /home/prathap/WorkSpace/gem5/util/m5/cpu2006/cpu2006/benchspec/CPU2006/401.bzip2/exe/dryer.jpg 280") spec_fs_cmd["gcc"] = fsBench("/cpu2006/bin/spec.gcc_base.x86-gcc /cpu2006/403.gcc/data/ref/input/200.i -o gcc_403.gcc_200.s") spec_fs_cmd["bwaves"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/bwaves /root/spec/bwaves.in") spec_fs_cmd["zeusmp"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/zeusmp") spec_fs_cmd["gromacs"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/gromacs -silent -deffnm /root/spec/gromacs.tpr -name 0") spec_fs_cmd["gobmk"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/gobmk --quiet --mode gtp < /root/spec/nngs.tst") spec_fs_cmd["dealII"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/deal 23") spec_fs_cmd["povray"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/povray /root/spec/SPEC-benchmark-ref.ini") spec_fs_cmd["calculix"] = fsBench("/cpu2006/bin/spec.calculix_base.x86-gcc -i /cpu2006/454.calculix/data/ref/input/hyperviscoplastic") spec_fs_cmd["sjeng"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/sjeng /root/spec/ref.txt") spec_fs_cmd["GemsFDTD"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/GemsFDTD") spec_fs_cmd["tonto"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/tonto_base") spec_fs_cmd["wrf"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/wrf /root/spec/namelist.input") spec_fs_cmd["sphinx"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/spec/sphinx /root/spec/model/lm/an4/an4.ctl . /root/spec/args.an4") spec_fs_cmd["xalancbmk"] = fsBench("/cpu2006/bin/spec.Xalan_base.x86-gcc -v /cpu2006/483.xalancbmk/data/ref/input/t5.xml /cpu2006/483.xalancbmk/data/ref/input/xalanc.xsl") spec_fs_cmd["specrand_i"] = fsBench("/cpu2006/bin/spec.specrand_base.x86-gcc 324342 24239") spec_fs_cmd["specrand_f"] = fsBench("/cpu2006/bin/spec.specrand_base.x86-gcc 324342 24239") #FF spec_fs_cmd["mcf-my"] = fsBench("/root/spec/mcf /root/spec/inp.in") spec_fs_cmd["lbm-my"] = fsBench("/root/spec/lbm 3000 reference.dat 0 0 /root/spec/100_100_130_ldc.of") #solo spec_fs_cmd["a2time01"] = fsBench("/root/eem.sh a2time01") spec_fs_cmd["aifftr01"] = fsBench("/root/eem.sh aifftr01") spec_fs_cmd["aifirf01"] = fsBench("/root/eem.sh aifirf01") spec_fs_cmd["aiifft01"] = fsBench("/root/eem.sh aiifft01") spec_fs_cmd["basefp01"] = fsBench("/root/eem.sh basefp01") spec_fs_cmd["bitmnp01"] = fsBench("/root/eem.sh bitmnp01") spec_fs_cmd["cacheb01"] = fsBench("/root/eem.sh cacheb01") spec_fs_cmd["canrdr01"] = fsBench("/root/eem.sh canrdr01") spec_fs_cmd["idctrn01"] = fsBench("/root/eem.sh idctrn01") spec_fs_cmd["iirflt01"] = fsBench("/root/eem.sh iirflt01") spec_fs_cmd["matrix01"] = fsBench("/root/eem.sh matrix01") spec_fs_cmd["pntrch01"] = fsBench("/root/eem.sh pntrch01") spec_fs_cmd["puwmod01"] = fsBench("/root/eem.sh puwmod01") spec_fs_cmd["rspeed01"] = fsBench("/root/eem.sh rspeed01") spec_fs_cmd["tblook01"] = fsBench("/root/eem.sh tblook01") spec_fs_cmd["ttsprk01"] = fsBench("/root/eem.sh ttsprk01") spec_fs_cmd["cjpeg"] = fsBench("/root/eem.sh cjpeg") spec_fs_cmd["djpeg"] = fsBench("/root/eem.sh djpeg") spec_fs_cmd["rgbcmy01"] = fsBench("/root/eem.sh rgbcmy01") spec_fs_cmd["rgbhpg01"] = fsBench("/root/eem.sh rgbhpg01") spec_fs_cmd["rgbyiq01"] = fsBench("/root/eem.sh rgbyiq01") spec_fs_cmd["latency"] = fsBench("/root/latency.sh 128 21") spec_fs_cmd["bwr"] = fsBench("/root/bw.sh 128 101 read") #Deterministic spec_fs_cmd["Dlatency"] = fsBench("/root/latency-dt -m 2048 -i 6 -c 0 -o fifo") spec_fs_cmd["Dlatencyd"] = fsBench("/root/latency-dt -m 2048 -i 6 -c 0 -o fifo -d deterministic") spec_fs_cmd["Dl-D3bwr"] = fsBench("/root/cr3.sh 2048 read;ls /;/root/latency-dt -m 2048 -i 6 -c 0 -o fifo") spec_fs_cmd["Dl-D3bwrd"] = fsBench("/root/cr3.sh 2048 read;/root/latency-dt -m 2048 -i 6 -c 0 -o fifo -d deterministic") spec_fs_cmd["Da2time01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/a2time01") spec_fs_cmd["Daifftr01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/aifftr01") spec_fs_cmd["Daifirf01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/aifirf01") spec_fs_cmd["Daiifft01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/aiifft01") spec_fs_cmd["Dbasefp01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/basefp01") spec_fs_cmd["Dbitmnp01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/bitmnp01") spec_fs_cmd["Dcacheb01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/cacheb01") spec_fs_cmd["Dcanrdr01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/canrdr01") spec_fs_cmd["Didctrn01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/idctrn01") spec_fs_cmd["Diirflt01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/iirflt01") spec_fs_cmd["Dmatrix01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/matrix01") spec_fs_cmd["Dpntrch01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/pntrch01") spec_fs_cmd["Dpuwmod01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/puwmod01") spec_fs_cmd["Drspeed01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/rspeed01") spec_fs_cmd["Dtblook01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/tblook01") spec_fs_cmd["Dttsprk01"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/ttsprk01") spec_fs_cmd["Daifftr01-mlock"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/mlock/aifftr01") spec_fs_cmd["Daiifft01-mlock"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/mlock/aiifft01") spec_fs_cmd["Dcacheb01-mlock"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/mlock/cacheb01") spec_fs_cmd["Dmatrix01-mlock"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/mlock/matrix01") spec_fs_cmd["Dpntrch01-mlock"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/mlock/pntrch01") spec_fs_cmd["Dttsprk01-mlock"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/mlock/ttsprk01") spec_fs_cmd["a2time01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01") spec_fs_cmd["aifftr01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01") spec_fs_cmd["aifirf01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01") spec_fs_cmd["aiifft01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01") spec_fs_cmd["basefp01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01") spec_fs_cmd["bitmnp01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01") spec_fs_cmd["cacheb01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01") spec_fs_cmd["canrdr01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01") spec_fs_cmd["idctrn01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01") spec_fs_cmd["iirflt01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01") spec_fs_cmd["matrix01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01") spec_fs_cmd["pntrch01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01") spec_fs_cmd["puwmod01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01") spec_fs_cmd["rspeed01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01") spec_fs_cmd["tblook01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01") spec_fs_cmd["ttsprk01-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01") spec_fs_cmd["aifftr01-mlock-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01") spec_fs_cmd["aiifft01-mlock-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01") spec_fs_cmd["cacheb01-mlock-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/cacheb01") spec_fs_cmd["matrix01-mlock-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01") spec_fs_cmd["pntrch01-mlock-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/pntrch01") spec_fs_cmd["ttsprk01-mlock-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/ttsprk01") spec_fs_cmd["a2time01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01") spec_fs_cmd["aifftr01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01") spec_fs_cmd["aifirf01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01") spec_fs_cmd["aiifft01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01") spec_fs_cmd["basefp01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01") spec_fs_cmd["bitmnp01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01") spec_fs_cmd["cacheb01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01") spec_fs_cmd["canrdr01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01") spec_fs_cmd["idctrn01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01") spec_fs_cmd["iirflt01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01") spec_fs_cmd["matrix01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01") spec_fs_cmd["pntrch01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01") spec_fs_cmd["puwmod01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01") spec_fs_cmd["rspeed01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01") spec_fs_cmd["tblook01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01") spec_fs_cmd["ttsprk01-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01") spec_fs_cmd["a2time01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01") spec_fs_cmd["aifftr01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01") spec_fs_cmd["aifirf01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01") spec_fs_cmd["aiifft01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01") spec_fs_cmd["basefp01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01") spec_fs_cmd["bitmnp01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01") spec_fs_cmd["cacheb01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01") spec_fs_cmd["canrdr01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01") spec_fs_cmd["idctrn01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01") spec_fs_cmd["iirflt01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01") spec_fs_cmd["matrix01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01") spec_fs_cmd["pntrch01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01") spec_fs_cmd["puwmod01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01") spec_fs_cmd["rspeed01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01") spec_fs_cmd["tblook01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01") spec_fs_cmd["ttsprk01-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01") spec_fs_cmd["aifftr01-mlock-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01") spec_fs_cmd["aiifft01-mlock-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01") spec_fs_cmd["cacheb01-mlock-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/cacheb01") spec_fs_cmd["matrix01-mlock-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01") spec_fs_cmd["pntrch01-mlock-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/pntrch01") spec_fs_cmd["ttsprk01-mlock-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/ttsprk01") spec_fs_cmd["a2time01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01") spec_fs_cmd["aifftr01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01") spec_fs_cmd["aifirf01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01") spec_fs_cmd["aiifft01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01") spec_fs_cmd["basefp01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01") spec_fs_cmd["bitmnp01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01") spec_fs_cmd["cacheb01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01") spec_fs_cmd["canrdr01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01") spec_fs_cmd["idctrn01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01") spec_fs_cmd["iirflt01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01") spec_fs_cmd["matrix01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01") spec_fs_cmd["pntrch01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01") spec_fs_cmd["puwmod01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01") spec_fs_cmd["rspeed01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01") spec_fs_cmd["tblook01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01") spec_fs_cmd["ttsprk01-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01") spec_fs_cmd["a2time01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01 -d") spec_fs_cmd["aifftr01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01 -d") spec_fs_cmd["aifirf01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01 -d") spec_fs_cmd["aiifft01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01 -d") spec_fs_cmd["basefp01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01 -d") spec_fs_cmd["bitmnp01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01 -d") spec_fs_cmd["cacheb01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01 -d") spec_fs_cmd["canrdr01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01 -d") spec_fs_cmd["idctrn01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01 -d") spec_fs_cmd["iirflt01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01 -d") spec_fs_cmd["matrix01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01 -d") spec_fs_cmd["pntrch01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01 -d") spec_fs_cmd["puwmod01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01 -d") spec_fs_cmd["rspeed01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01 -d") spec_fs_cmd["tblook01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01 -d") spec_fs_cmd["ttsprk01-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01 -d") spec_fs_cmd["aifftr01-mlock-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01 -d") spec_fs_cmd["aiifft01-mlock-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01 -d") spec_fs_cmd["cacheb01-mlock-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/cacheb01 -d") spec_fs_cmd["matrix01-mlock-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01 -d") spec_fs_cmd["pntrch01-mlock-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/pntrch01 -d") spec_fs_cmd["ttsprk01-mlock-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/ttsprk01 -d") spec_fs_cmd["a2time01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01 -d") spec_fs_cmd["aifftr01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01 -d") spec_fs_cmd["aifirf01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01 -d") spec_fs_cmd["aiifft01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01 -d") spec_fs_cmd["basefp01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01 -d") spec_fs_cmd["bitmnp01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01 -d") spec_fs_cmd["cacheb01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01 -d") spec_fs_cmd["canrdr01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01 -d") spec_fs_cmd["idctrn01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01 -d") spec_fs_cmd["iirflt01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01 -d") spec_fs_cmd["matrix01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01 -d") spec_fs_cmd["pntrch01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01 -d") spec_fs_cmd["puwmod01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01 -d") spec_fs_cmd["rspeed01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01 -d") spec_fs_cmd["tblook01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01 -d") spec_fs_cmd["ttsprk01-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01 -d") spec_fs_cmd["a2time01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01_deterministic -d") spec_fs_cmd["aifftr01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01_deterministic -d") spec_fs_cmd["aifirf01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01_deterministic -d") spec_fs_cmd["aiifft01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01_deterministic -d") spec_fs_cmd["basefp01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01_deterministic -d") spec_fs_cmd["bitmnp01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01_deterministic -d") spec_fs_cmd["cacheb01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01_deterministic -d") spec_fs_cmd["canrdr01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01_deterministic -d") spec_fs_cmd["idctrn01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01_deterministic -d") spec_fs_cmd["iirflt01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01_deterministic -d") spec_fs_cmd["matrix01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01_deterministic -d") spec_fs_cmd["pntrch01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01_deterministic -d") spec_fs_cmd["puwmod01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01_deterministic -d") spec_fs_cmd["rspeed01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01_deterministic -d") spec_fs_cmd["tblook01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01_deterministic -d") spec_fs_cmd["ttsprk01-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01_deterministic -d") spec_fs_cmd["aifftr01-mlock-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01_deterministic -d") spec_fs_cmd["aiifft01-mlock-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01_deterministic -d") spec_fs_cmd["cacheb01-mlock-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/cacheb01_deterministic -d") spec_fs_cmd["matrix01-mlock-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01_deterministic -d") spec_fs_cmd["pntrch01-mlock-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/pntrch01_deterministic -d") spec_fs_cmd["ttsprk01-mlock-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/ttsprk01_deterministic -d") spec_fs_cmd["a2time01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/a2time01_deterministic -d") spec_fs_cmd["aifftr01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifftr01_deterministic -d") spec_fs_cmd["aifirf01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aifirf01_deterministic -d") spec_fs_cmd["aiifft01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/aiifft01_deterministic -d") spec_fs_cmd["basefp01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/basefp01_deterministic -d") spec_fs_cmd["bitmnp01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/bitmnp01_deterministic -d") spec_fs_cmd["cacheb01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/cacheb01_deterministic -d") spec_fs_cmd["canrdr01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/canrdr01_deterministic -d") spec_fs_cmd["idctrn01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/idctrn01_deterministic -d") spec_fs_cmd["iirflt01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/iirflt01_deterministic -d") spec_fs_cmd["matrix01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/matrix01_deterministic -d") spec_fs_cmd["pntrch01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/pntrch01_deterministic -d") spec_fs_cmd["puwmod01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/puwmod01_deterministic -d") spec_fs_cmd["rspeed01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/rspeed01_deterministic -d") spec_fs_cmd["tblook01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/tblook01_deterministic -d") spec_fs_cmd["ttsprk01-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/ttsprk01_deterministic -d") spec_fs_cmd["Da2time01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/a2time01") spec_fs_cmd["Daifftr01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/aifftr01") spec_fs_cmd["Daifirf01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/aifirf01") spec_fs_cmd["Daiifft01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/aiifft01") spec_fs_cmd["Dbasefp01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/basefp01") spec_fs_cmd["Dbitmnp01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/bitmnp01") spec_fs_cmd["Dcacheb01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/cacheb01") spec_fs_cmd["Dcanrdr01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/canrdr01") spec_fs_cmd["Didctrn01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/idctrn01") spec_fs_cmd["Diirflt01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/iirflt01") spec_fs_cmd["Dmatrix01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/matrix01") spec_fs_cmd["Dpntrch01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/pntrch01") spec_fs_cmd["Dpuwmod01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/puwmod01") spec_fs_cmd["Drspeed01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/rspeed01") spec_fs_cmd["Dtblook01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/tblook01") spec_fs_cmd["Dttsprk01-cld"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-cold/ttsprk01") spec_fs_cmd["a2time01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/a2time01") spec_fs_cmd["aifftr01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifftr01") spec_fs_cmd["aifirf01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifirf01") spec_fs_cmd["aiifft01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aiifft01") spec_fs_cmd["basefp01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/basefp01") spec_fs_cmd["bitmnp01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/bitmnp01") spec_fs_cmd["cacheb01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/cacheb01") spec_fs_cmd["canrdr01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/canrdr01") spec_fs_cmd["idctrn01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/idctrn01") spec_fs_cmd["iirflt01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/iirflt01") spec_fs_cmd["matrix01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/matrix01") spec_fs_cmd["pntrch01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/pntrch01") spec_fs_cmd["puwmod01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/puwmod01") spec_fs_cmd["rspeed01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/rspeed01") spec_fs_cmd["tblook01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/tblook01") spec_fs_cmd["ttsprk01-cld-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/ttsprk01") spec_fs_cmd["a2time01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/a2time01") spec_fs_cmd["aifftr01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifftr01") spec_fs_cmd["aifirf01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifirf01") spec_fs_cmd["aiifft01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aiifft01") spec_fs_cmd["basefp01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/basefp01") spec_fs_cmd["bitmnp01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/bitmnp01") spec_fs_cmd["cacheb01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/cacheb01") spec_fs_cmd["canrdr01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/canrdr01") spec_fs_cmd["idctrn01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/idctrn01") spec_fs_cmd["iirflt01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/iirflt01") spec_fs_cmd["matrix01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/matrix01") spec_fs_cmd["pntrch01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/pntrch01") spec_fs_cmd["puwmod01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/puwmod01") spec_fs_cmd["rspeed01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/rspeed01") spec_fs_cmd["tblook01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/tblook01") spec_fs_cmd["ttsprk01-cld-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/ttsprk01") spec_fs_cmd["a2time01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/a2time01 -d") spec_fs_cmd["aifftr01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifftr01 -d") spec_fs_cmd["aifirf01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifirf01 -d") spec_fs_cmd["aiifft01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aiifft01 -d") spec_fs_cmd["basefp01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/basefp01 -d") spec_fs_cmd["bitmnp01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/bitmnp01 -d") spec_fs_cmd["cacheb01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/cacheb01 -d") spec_fs_cmd["canrdr01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/canrdr01 -d") spec_fs_cmd["idctrn01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/idctrn01 -d") spec_fs_cmd["iirflt01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/iirflt01 -d") spec_fs_cmd["matrix01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/matrix01 -d") spec_fs_cmd["pntrch01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/pntrch01 -d") spec_fs_cmd["puwmod01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/puwmod01 -d") spec_fs_cmd["rspeed01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/rspeed01 -d") spec_fs_cmd["tblook01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/tblook01 -d") spec_fs_cmd["ttsprk01-cld-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/ttsprk01 -d") spec_fs_cmd["a2time01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/a2time01_deterministic -d") spec_fs_cmd["aifftr01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifftr01_deterministic -d") spec_fs_cmd["aifirf01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aifirf01_deterministic -d") spec_fs_cmd["aiifft01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/aiifft01_deterministic -d") spec_fs_cmd["basefp01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/basefp01_deterministic -d") spec_fs_cmd["bitmnp01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/bitmnp01_deterministic -d") spec_fs_cmd["cacheb01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/cacheb01_deterministic -d") spec_fs_cmd["canrdr01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/canrdr01_deterministic -d") spec_fs_cmd["idctrn01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/idctrn01_deterministic -d") spec_fs_cmd["iirflt01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/iirflt01_deterministic -d") spec_fs_cmd["matrix01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/matrix01_deterministic -d") spec_fs_cmd["pntrch01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/pntrch01_deterministic -d") spec_fs_cmd["puwmod01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/puwmod01_deterministic -d") spec_fs_cmd["rspeed01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/rspeed01_deterministic -d") spec_fs_cmd["tblook01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/tblook01_deterministic -d") spec_fs_cmd["ttsprk01-cld-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-cold/ttsprk01_deterministic -d") spec_fs_cmd["Ddisparity-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/disparity/data/sim_fast/disparity ./sd-vbs/sim/disparity/data/sim_fast") spec_fs_cmd["Dlocalization-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/localization/data/sim_fast/localization ./sd-vbs/sim/localization/data/sim_fast") spec_fs_cmd["Dmser-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/mser/data/sim_fast/mser ./sd-vbs/sim/mser/data/sim_fast") spec_fs_cmd["Dmulti_ncut-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim_fast/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim_fast") spec_fs_cmd["Dsift-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/sift/data/sim_fast/sift ./sd-vbs/sim/sift/data/sim_fast") spec_fs_cmd["Dstitch-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/stitch/data/sim_fast/stitch ./sd-vbs/sim/stitch/data/sim_fast") spec_fs_cmd["Dsvm-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/svm/data/sim_fast/svm ./sd-vbs/sim/svm/data/sim_fast") spec_fs_cmd["Dtexture_synthesis-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim_fast/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim_fast") spec_fs_cmd["Dtracking-sim_fast"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/tracking/data/sim_fast/tracking ./sd-vbs/sim/tracking/data/sim_fast") spec_fs_cmd["disparity-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim_fast/disparity ./sd-vbs/sim/disparity/data/sim_fast") spec_fs_cmd["localization-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim_fast/localization ./sd-vbs/sim/localization/data/sim_fast") spec_fs_cmd["mser-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim_fast/mser ./sd-vbs/sim/mser/data/sim_fast") spec_fs_cmd["multi_ncut-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim_fast/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim_fast") spec_fs_cmd["sift-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim_fast/sift ./sd-vbs/sim/sift/data/sim_fast") spec_fs_cmd["stitch-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim_fast/stitch ./sd-vbs/sim/stitch/data/sim_fast") spec_fs_cmd["svm-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim_fast/svm ./sd-vbs/sim/svm/data/sim_fast") spec_fs_cmd["texture_synthesis-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim_fast/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim_fast") spec_fs_cmd["tracking-sim_fast-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim_fast/tracking ./sd-vbs/sim/tracking/data/sim_fast") spec_fs_cmd["disparity-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim_fast/disparity ./sd-vbs/sim/disparity/data/sim_fast") spec_fs_cmd["localization-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim_fast/localization ./sd-vbs/sim/localization/data/sim_fast") spec_fs_cmd["mser-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim_fast/mser ./sd-vbs/sim/mser/data/sim_fast") spec_fs_cmd["multi_ncut-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim_fast/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim_fast") spec_fs_cmd["sift-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim_fast/sift ./sd-vbs/sim/sift/data/sim_fast") spec_fs_cmd["stitch-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim_fast/stitch ./sd-vbs/sim/stitch/data/sim_fast") spec_fs_cmd["svm-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim_fast/svm ./sd-vbs/sim/svm/data/sim_fast") spec_fs_cmd["texture_synthesis-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim_fast/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim_fast") spec_fs_cmd["tracking-sim_fast-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim_fast/tracking ./sd-vbs/sim/tracking/data/sim_fast") spec_fs_cmd["disparity-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim_fast/disparity ./sd-vbs/sim/disparity/data/sim_fast -d") spec_fs_cmd["localization-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim_fast/localization ./sd-vbs/sim/localization/data/sim_fast -d") spec_fs_cmd["mser-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim_fast/mser ./sd-vbs/sim/mser/data/sim_fast -d") spec_fs_cmd["multi_ncut-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim_fast/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim_fast -d") spec_fs_cmd["sift-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim_fast/sift ./sd-vbs/sim/sift/data/sim_fast -d") spec_fs_cmd["stitch-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim_fast/stitch ./sd-vbs/sim/stitch/data/sim_fast -d") spec_fs_cmd["svm-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim_fast/svm ./sd-vbs/sim/svm/data/sim_fast -d") spec_fs_cmd["texture_synthesis-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim_fast/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim_fast -d") spec_fs_cmd["tracking-sim_fast-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim_fast/tracking ./sd-vbs/sim/tracking/data/sim_fast -d") spec_fs_cmd["disparity-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim_fast/disparity_deterministic ./sd-vbs/sim/disparity/data/sim_fast -d") spec_fs_cmd["localization-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim_fast/localization_deterministic ./sd-vbs/sim/localization/data/sim_fast -d") spec_fs_cmd["mser-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim_fast/mser_deterministic ./sd-vbs/sim/mser/data/sim_fast -d") spec_fs_cmd["multi_ncut-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim_fast/multi_ncut_deterministic ./sd-vbs/sim/multi_ncut/data/sim_fast -d") spec_fs_cmd["sift-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim_fast/sift_deterministic ./sd-vbs/sim/sift/data/sim_fast -d") spec_fs_cmd["stitch-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim_fast/stitch_deterministic ./sd-vbs/sim/stitch/data/sim_fast -d") spec_fs_cmd["svm-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim_fast/svm_deterministic ./sd-vbs/sim/svm/data/sim_fast -d") spec_fs_cmd["texture_synthesis-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim_fast/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim_fast -d") spec_fs_cmd["tracking-sim_fast-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim_fast/tracking_deterministic ./sd-vbs/sim/tracking/data/sim_fast -d") spec_fs_cmd["Ddisparity-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/disparity/data/sim/disparity ./sd-vbs/sim/disparity/data/sim") spec_fs_cmd["Dlocalization-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/localization/data/sim/localization ./sd-vbs/sim/localization/data/sim") spec_fs_cmd["Dmser-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/mser/data/sim/mser ./sd-vbs/sim/mser/data/sim") spec_fs_cmd["Dmulti_ncut-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim") spec_fs_cmd["Dsift-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/sift/data/sim/sift ./sd-vbs/sim/sift/data/sim") spec_fs_cmd["Dstitch-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/stitch/data/sim/stitch ./sd-vbs/sim/stitch/data/sim") spec_fs_cmd["Dsvm-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/svm/data/sim/svm ./sd-vbs/sim/svm/data/sim") spec_fs_cmd["Dtexture_synthesis-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim") spec_fs_cmd["Dtracking-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sim/tracking/data/sim/tracking ./sd-vbs/sim/tracking/data/sim") spec_fs_cmd["disparity-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim/disparity ./sd-vbs/sim/disparity/data/sim") spec_fs_cmd["localization-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim/localization ./sd-vbs/sim/localization/data/sim") spec_fs_cmd["mser-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim/mser ./sd-vbs/sim/mser/data/sim") spec_fs_cmd["multi_ncut-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim") spec_fs_cmd["sift-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim/sift ./sd-vbs/sim/sift/data/sim") spec_fs_cmd["stitch-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim/stitch ./sd-vbs/sim/stitch/data/sim") spec_fs_cmd["svm-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim/svm ./sd-vbs/sim/svm/data/sim") spec_fs_cmd["texture_synthesis-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim") spec_fs_cmd["tracking-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim/tracking ./sd-vbs/sim/tracking/data/sim") spec_fs_cmd["disparity-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim/disparity ./sd-vbs/sim/disparity/data/sim") spec_fs_cmd["localization-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim/localization ./sd-vbs/sim/localization/data/sim") spec_fs_cmd["mser-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim/mser ./sd-vbs/sim/mser/data/sim") spec_fs_cmd["multi_ncut-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim") spec_fs_cmd["sift-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim/sift ./sd-vbs/sim/sift/data/sim") spec_fs_cmd["stitch-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim/stitch ./sd-vbs/sim/stitch/data/sim") spec_fs_cmd["svm-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim/svm ./sd-vbs/sim/svm/data/sim") spec_fs_cmd["texture_synthesis-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim") spec_fs_cmd["tracking-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim/tracking ./sd-vbs/sim/tracking/data/sim") spec_fs_cmd["disparity-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim/disparity ./sd-vbs/sim/disparity/data/sim -d") spec_fs_cmd["localization-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim/localization ./sd-vbs/sim/localization/data/sim -d") spec_fs_cmd["mser-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim/mser ./sd-vbs/sim/mser/data/sim -d") spec_fs_cmd["multi_ncut-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim/multi_ncut ./sd-vbs/sim/multi_ncut/data/sim -d") spec_fs_cmd["sift-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim/sift ./sd-vbs/sim/sift/data/sim -d") spec_fs_cmd["stitch-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim/stitch ./sd-vbs/sim/stitch/data/sim -d") spec_fs_cmd["svm-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim/svm ./sd-vbs/sim/svm/data/sim -d") spec_fs_cmd["texture_synthesis-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -d") spec_fs_cmd["tracking-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim/tracking ./sd-vbs/sim/tracking/data/sim -d") spec_fs_cmd["disparity-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/disparity/data/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d") spec_fs_cmd["localization-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/localization/data/sim/localization_deterministic ./sd-vbs/sim/localization/data/sim -d") spec_fs_cmd["mser-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/mser/data/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d") spec_fs_cmd["multi_ncut-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/multi_ncut/data/sim/multi_ncut_deterministic ./sd-vbs/sim/multi_ncut/data/sim -d") spec_fs_cmd["sift-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/sift/data/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d") spec_fs_cmd["stitch-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/stitch/data/sim/stitch_deterministic ./sd-vbs/sim/stitch/data/sim -d") spec_fs_cmd["svm-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/svm/data/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d") spec_fs_cmd["texture_synthesis-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/texture_synthesis/data/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d") spec_fs_cmd["tracking-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sim/tracking/data/sim/tracking_deterministic ./sd-vbs/sim/tracking/data/sim -d") #sqcif spec_fs_cmd["Ddisparity-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/disparity/sqcif/disparity ./sd-vbs/disparity/sqcif") spec_fs_cmd["Dlocalization-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/localization/sqcif/localization ./sd-vbs/localization/sqcif") spec_fs_cmd["Dmser-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/mser/sqcif/mser ./sd-vbs/mser/sqcif") spec_fs_cmd["Dmulti_ncut-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/multi_ncut/sqcif/multi_ncut ./sd-vbs/multi_ncut/sqcif") spec_fs_cmd["Dsift-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/sift/sqcif/sift ./sd-vbs/sift/sqcif") spec_fs_cmd["Dstitch-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/stitch/sqcif/stitch ./sd-vbs/stitch/sqcif") spec_fs_cmd["Dsvm-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/svm/sqcif/svm ./sd-vbs/svm/sqcif") spec_fs_cmd["Dtexture_synthesis-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/texture_synthesis/sqcif/texture_synthesis ./sd-vbs/texture_synthesis/sqcif") spec_fs_cmd["Dtracking-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/tracking/sqcif/tracking ./sd-vbs/tracking/sqcif") spec_fs_cmd["disparity-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/disparity/sqcif/disparity ./sd-vbs/disparity/sqcif") spec_fs_cmd["localization-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/localization/sqcif/localization ./sd-vbs/localization/sqcif") spec_fs_cmd["mser-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mser/sqcif/mser ./sd-vbs/mser/sqcif") spec_fs_cmd["multi_ncut-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/multi_ncut/sqcif/multi_ncut ./sd-vbs/multi_ncut/sqcif") spec_fs_cmd["sift-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sift/sqcif/sift ./sd-vbs/sift/sqcif") spec_fs_cmd["stitch-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/stitch/sqcif/stitch ./sd-vbs/stitch/sqcif") spec_fs_cmd["svm-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/svm/sqcif/svm ./sd-vbs/svm/sqcif") spec_fs_cmd["texture_synthesis-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/texture_synthesis/sqcif/texture_synthesis ./sd-vbs/texture_synthesis/sqcif") spec_fs_cmd["tracking-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/tracking/sqcif/tracking ./sd-vbs/tracking/sqcif") spec_fs_cmd["disparity-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/disparity/sqcif/disparity ./sd-vbs/disparity/sqcif") spec_fs_cmd["localization-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/localization/sqcif/localization ./sd-vbs/localization/sqcif") spec_fs_cmd["mser-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mser/sqcif/mser ./sd-vbs/mser/sqcif") spec_fs_cmd["multi_ncut-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/multi_ncut/sqcif/multi_ncut ./sd-vbs/multi_ncut/sqcif") spec_fs_cmd["sift-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sift/sqcif/sift ./sd-vbs/sift/sqcif") spec_fs_cmd["stitch-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/stitch/sqcif/stitch ./sd-vbs/stitch/sqcif") spec_fs_cmd["svm-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/svm/sqcif/svm ./sd-vbs/svm/sqcif") spec_fs_cmd["texture_synthesis-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/texture_synthesis/sqcif/texture_synthesis ./sd-vbs/texture_synthesis/sqcif") spec_fs_cmd["tracking-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/tracking/sqcif/tracking ./sd-vbs/tracking/sqcif") spec_fs_cmd["disparity-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/disparity/sqcif/disparity ./sd-vbs/disparity/sqcif -d") spec_fs_cmd["localization-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/localization/sqcif/localization ./sd-vbs/localization/sqcif -d") spec_fs_cmd["mser-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mser/sqcif/mser ./sd-vbs/mser/sqcif -d") spec_fs_cmd["multi_ncut-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/multi_ncut/sqcif/multi_ncut ./sd-vbs/multi_ncut/sqcif -d") spec_fs_cmd["sift-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sift/sqcif/sift ./sd-vbs/sift/sqcif -d") spec_fs_cmd["stitch-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/stitch/sqcif/stitch ./sd-vbs/stitch/sqcif -d") spec_fs_cmd["svm-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/svm/sqcif/svm ./sd-vbs/svm/sqcif -d") spec_fs_cmd["texture_synthesis-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/texture_synthesis/sqcif/texture_synthesis ./sd-vbs/texture_synthesis/sqcif -d") spec_fs_cmd["tracking-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/tracking/sqcif/tracking ./sd-vbs/tracking/sqcif -d") spec_fs_cmd["disparity-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/disparity/sqcif/disparity_deterministic ./sd-vbs/disparity/sqcif -d") spec_fs_cmd["localization-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/localization/sqcif/localization_deterministic ./sd-vbs/localization/sqcif -d") spec_fs_cmd["mser-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mser/sqcif/mser_deterministic ./sd-vbs/mser/sqcif -d") spec_fs_cmd["multi_ncut-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/multi_ncut/sqcif/multi_ncut_deterministic ./sd-vbs/multi_ncut/sqcif -d") spec_fs_cmd["sift-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/sift/sqcif/sift_deterministic ./sd-vbs/sift/sqcif -d") spec_fs_cmd["stitch-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/stitch/sqcif/stitch_deterministic ./sd-vbs/stitch/sqcif -d") spec_fs_cmd["svm-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/svm/sqcif/svm_deterministic ./sd-vbs/svm/sqcif -d") spec_fs_cmd["texture_synthesis-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/texture_synthesis/sqcif/texture_synthesis_deterministic ./sd-vbs/texture_synthesis/sqcif -d") spec_fs_cmd["tracking-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/tracking/sqcif/tracking_deterministic ./sd-vbs/tracking/sqcif -d") spec_fs_cmd["Ddisparity-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim 2") spec_fs_cmd["Dlocalization-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization ./sd-vbs/itr/localization/data/sim 2") spec_fs_cmd["Dmser-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim 2") spec_fs_cmd["Dmulti_ncut-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut ./sd-vbs/itr/multi_ncut/data/sim 2") spec_fs_cmd["Dsift-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim 2") spec_fs_cmd["Dstitch-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch ./sd-vbs/itr/stitch/data/sim 2") spec_fs_cmd["Dsvm-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim 2") spec_fs_cmd["Dtexture_synthesis-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim 2") spec_fs_cmd["Dtracking-itr2-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking ./sd-vbs/itr/tracking/data/sim 2") spec_fs_cmd["disparity-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim 2") spec_fs_cmd["localization-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization ./sd-vbs/itr/localization/data/sim 2") spec_fs_cmd["mser-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim 2") spec_fs_cmd["multi_ncut-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut ./sd-vbs/itr/multi_ncut/data/sim 2") spec_fs_cmd["sift-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim 2") spec_fs_cmd["stitch-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch ./sd-vbs/itr/stitch/data/sim 2") spec_fs_cmd["svm-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim 2") spec_fs_cmd["tracking-itr2-sim-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking ./sd-vbs/itr/tracking/data/sim 2") spec_fs_cmd["disparity-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim 2") spec_fs_cmd["localization-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization ./sd-vbs/itr/localization/data/sim 2") spec_fs_cmd["mser-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim 2") spec_fs_cmd["multi_ncut-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut ./sd-vbs/itr/multi_ncut/data/sim 2") spec_fs_cmd["sift-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim 2") spec_fs_cmd["stitch-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch ./sd-vbs/itr/stitch/data/sim 2") spec_fs_cmd["svm-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim 2") spec_fs_cmd["tracking-itr2-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking ./sd-vbs/itr/tracking/data/sim 2") spec_fs_cmd["disparity-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim -d 2") spec_fs_cmd["localization-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization ./sd-vbs/itr/localization/data/sim -d 2") spec_fs_cmd["mser-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim -d 2") spec_fs_cmd["multi_ncut-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut ./sd-vbs/itr/multi_ncut/data/sim -d 2") spec_fs_cmd["sift-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim -d 2") spec_fs_cmd["stitch-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch ./sd-vbs/itr/stitch/data/sim -d 2") spec_fs_cmd["svm-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim -d 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim -d 2") spec_fs_cmd["tracking-itr2-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking ./sd-vbs/itr/tracking/data/sim -d 2") spec_fs_cmd["disparity-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity_deterministic ./sd-vbs/itr/disparity/data/sim -d 2") spec_fs_cmd["localization-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization_deterministic ./sd-vbs/itr/localization/data/sim -d 2") spec_fs_cmd["mser-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser_deterministic ./sd-vbs/itr/mser/data/sim -d 2") spec_fs_cmd["multi_ncut-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut_deterministic ./sd-vbs/itr/multi_ncut/data/sim -d 2") spec_fs_cmd["sift-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift_deterministic ./sd-vbs/itr/sift/data/sim -d 2") spec_fs_cmd["stitch-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch_deterministic ./sd-vbs/itr/stitch/data/sim -d 2") spec_fs_cmd["svm-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm_deterministic ./sd-vbs/itr/svm/data/sim -d 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis_deterministic ./sd-vbs/itr/texture_synthesis/data/sim -d 2") spec_fs_cmd["tracking-itr2-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking_deterministic ./sd-vbs/itr/tracking/data/sim -d 2") spec_fs_cmd["disparity-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim 2") spec_fs_cmd["localization-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization ./sd-vbs/itr/localization/data/sim 2") spec_fs_cmd["mser-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim 2") spec_fs_cmd["multi_ncut-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut ./sd-vbs/itr/multi_ncut/data/sim 2") spec_fs_cmd["sift-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim 2") spec_fs_cmd["stitch-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch ./sd-vbs/itr/stitch/data/sim 2") spec_fs_cmd["svm-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim 2") spec_fs_cmd["tracking-itr2-sim-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking ./sd-vbs/itr/tracking/data/sim 2") spec_fs_cmd["disparity-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim 2") spec_fs_cmd["localization-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization ./sd-vbs/itr/localization/data/sim 2") spec_fs_cmd["mser-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim 2") spec_fs_cmd["multi_ncut-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut ./sd-vbs/itr/multi_ncut/data/sim 2") spec_fs_cmd["sift-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim 2") spec_fs_cmd["stitch-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch ./sd-vbs/itr/stitch/data/sim 2") spec_fs_cmd["svm-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim 2") spec_fs_cmd["tracking-itr2-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking ./sd-vbs/itr/tracking/data/sim 2") spec_fs_cmd["disparity-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim -d 2") spec_fs_cmd["localization-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization ./sd-vbs/itr/localization/data/sim -d 2") spec_fs_cmd["mser-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim -d 2") spec_fs_cmd["multi_ncut-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut ./sd-vbs/itr/multi_ncut/data/sim -d 2") spec_fs_cmd["sift-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim -d 2") spec_fs_cmd["stitch-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch ./sd-vbs/itr/stitch/data/sim -d 2") spec_fs_cmd["svm-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim -d 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim -d 2") spec_fs_cmd["tracking-itr2-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking ./sd-vbs/itr/tracking/data/sim -d 2") spec_fs_cmd["disparity-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity_deterministic ./sd-vbs/itr/disparity/data/sim -d 2") spec_fs_cmd["localization-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sim/localization_deterministic ./sd-vbs/itr/localization/data/sim -d 2") spec_fs_cmd["mser-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser_deterministic ./sd-vbs/itr/mser/data/sim -d 2") spec_fs_cmd["multi_ncut-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sim/multi_ncut_deterministic ./sd-vbs/itr/multi_ncut/data/sim -d 2") spec_fs_cmd["sift-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift_deterministic ./sd-vbs/itr/sift/data/sim -d 2") spec_fs_cmd["stitch-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sim/stitch_deterministic ./sd-vbs/itr/stitch/data/sim -d 2") spec_fs_cmd["svm-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm_deterministic ./sd-vbs/itr/svm/data/sim -d 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis_deterministic ./sd-vbs/itr/texture_synthesis/data/sim -d 2") spec_fs_cmd["tracking-itr2-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sim/tracking_deterministic ./sd-vbs/itr/tracking/data/sim -d 2") spec_fs_cmd["Ddisparity-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif 2") spec_fs_cmd["Dlocalization-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif 2") spec_fs_cmd["Dmser-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif 2") spec_fs_cmd["Dmulti_ncut-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut ./sd-vbs/itr/multi_ncut/data/sqcif 2") spec_fs_cmd["Dsift-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif 2") spec_fs_cmd["Dstitch-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch ./sd-vbs/itr/stitch/data/sqcif 2") spec_fs_cmd["Dsvm-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif 2") spec_fs_cmd["Dtexture_synthesis-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif 2") spec_fs_cmd["Dtracking-itr2-sqcif"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking ./sd-vbs/itr/tracking/data/sqcif 2") spec_fs_cmd["disparity-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif 2") spec_fs_cmd["localization-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif 2") spec_fs_cmd["mser-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut ./sd-vbs/itr/multi_ncut/data/sqcif 2") spec_fs_cmd["sift-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif 2") spec_fs_cmd["stitch-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch ./sd-vbs/itr/stitch/data/sqcif 2") spec_fs_cmd["svm-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif 2") spec_fs_cmd["tracking-itr2-sqcif-3b683"] = fsBench("./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking ./sd-vbs/itr/tracking/data/sqcif 2") spec_fs_cmd["disparity-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif 2") spec_fs_cmd["localization-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif 2") spec_fs_cmd["mser-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut ./sd-vbs/itr/multi_ncut/data/sqcif 2") spec_fs_cmd["sift-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif 2") spec_fs_cmd["stitch-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch ./sd-vbs/itr/stitch/data/sqcif 2") spec_fs_cmd["svm-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif 2") spec_fs_cmd["tracking-itr2-sqcif-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking ./sd-vbs/itr/tracking/data/sqcif 2") spec_fs_cmd["disparity-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif -d 2") spec_fs_cmd["localization-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif -d 2") spec_fs_cmd["mser-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif -d 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut ./sd-vbs/itr/multi_ncut/data/sqcif -d 2") spec_fs_cmd["sift-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif -d 2") spec_fs_cmd["stitch-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch ./sd-vbs/itr/stitch/data/sqcif -d 2") spec_fs_cmd["svm-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif -d 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif -d 2") spec_fs_cmd["tracking-itr2-sqcif-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking ./sd-vbs/itr/tracking/data/sqcif -d 2") spec_fs_cmd["disparity-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity_deterministic ./sd-vbs/itr/disparity/data/sqcif -d 2") spec_fs_cmd["localization-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization_deterministic ./sd-vbs/itr/localization/data/sqcif -d 2") spec_fs_cmd["mser-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser_deterministic ./sd-vbs/itr/mser/data/sqcif -d 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut_deterministic ./sd-vbs/itr/multi_ncut/data/sqcif -d 2") spec_fs_cmd["sift-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift_deterministic ./sd-vbs/itr/sift/data/sqcif -d 2") spec_fs_cmd["stitch-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch_deterministic ./sd-vbs/itr/stitch/data/sqcif -d 2") spec_fs_cmd["svm-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm_deterministic ./sd-vbs/itr/svm/data/sqcif -d 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis_deterministic ./sd-vbs/itr/texture_synthesis/data/sqcif -d 2") spec_fs_cmd["tracking-itr2-sqcif-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking_deterministic ./sd-vbs/itr/tracking/data/sqcif -d 2") spec_fs_cmd["disparity-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif 2") spec_fs_cmd["localization-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif 2") spec_fs_cmd["mser-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut ./sd-vbs/itr/multi_ncut/data/sqcif 2") spec_fs_cmd["sift-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif 2") spec_fs_cmd["stitch-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch ./sd-vbs/itr/stitch/data/sqcif 2") spec_fs_cmd["svm-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif 2") spec_fs_cmd["tracking-itr2-sqcif-3b1365"] = fsBench("./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking ./sd-vbs/itr/tracking/data/sqcif 2") spec_fs_cmd["disparity-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif 2") spec_fs_cmd["localization-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif 2") spec_fs_cmd["mser-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut ./sd-vbs/itr/multi_ncut/data/sqcif 2") spec_fs_cmd["sift-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif 2") spec_fs_cmd["stitch-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch ./sd-vbs/itr/stitch/data/sqcif 2") spec_fs_cmd["svm-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif 2") spec_fs_cmd["tracking-itr2-sqcif-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking ./sd-vbs/itr/tracking/data/sqcif 2") spec_fs_cmd["disparity-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif -d 2") spec_fs_cmd["localization-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif -d 2") spec_fs_cmd["mser-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif -d 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut ./sd-vbs/itr/multi_ncut/data/sqcif -d 2") spec_fs_cmd["sift-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif -d 2") spec_fs_cmd["stitch-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch ./sd-vbs/itr/stitch/data/sqcif -d 2") spec_fs_cmd["svm-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif -d 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif -d 2") spec_fs_cmd["tracking-itr2-sqcif-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking ./sd-vbs/itr/tracking/data/sqcif -d 2") spec_fs_cmd["disparity-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/disparity/data/sqcif/disparity_deterministic ./sd-vbs/itr/disparity/data/sqcif -d 2") spec_fs_cmd["localization-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/localization/data/sqcif/localization_deterministic ./sd-vbs/itr/localization/data/sqcif -d 2") spec_fs_cmd["mser-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/mser/data/sqcif/mser_deterministic ./sd-vbs/itr/mser/data/sqcif -d 2") spec_fs_cmd["multi_ncut-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/multi_ncut/data/sqcif/multi_ncut_deterministic ./sd-vbs/itr/multi_ncut/data/sqcif -d 2") spec_fs_cmd["sift-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/sift/data/sqcif/sift_deterministic ./sd-vbs/itr/sift/data/sqcif -d 2") spec_fs_cmd["stitch-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/stitch/data/sqcif/stitch_deterministic ./sd-vbs/itr/stitch/data/sqcif -d 2") spec_fs_cmd["svm-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/svm/data/sqcif/svm_deterministic ./sd-vbs/itr/svm/data/sqcif -d 2") spec_fs_cmd["texture_synthesis-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis_deterministic ./sd-vbs/itr/texture_synthesis/data/sqcif -d 2") spec_fs_cmd["tracking-itr2-sqcif-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/itr/tracking/data/sqcif/tracking_deterministic ./sd-vbs/itr/tracking/data/sqcif -d 2") spec_fs_cmd["disparity-itr2-sim-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./sd-vbs/itr/disparity/data/sqcif/disparity ./sd-vbs/itr/disparity/data/sqcif 2") spec_fs_cmd["localization-itr2-sim-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./sd-vbs/itr/localization/data/sqcif/localization ./sd-vbs/itr/localization/data/sqcif 2") spec_fs_cmd["mser-itr2-sim-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./sd-vbs/itr/mser/data/sqcif/mser ./sd-vbs/itr/mser/data/sqcif 2") spec_fs_cmd["sift-itr2-sim-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./sd-vbs/itr/sift/data/sqcif/sift ./sd-vbs/itr/sift/data/sqcif 2") spec_fs_cmd["svm-itr2-sim-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./sd-vbs/itr/svm/data/sqcif/svm ./sd-vbs/itr/svm/data/sqcif 2") spec_fs_cmd["texture_synthesis-itr2-sim-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./sd-vbs/itr/texture_synthesis/data/sqcif/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sqcif 2") spec_fs_cmd["aifftr01-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./eembc-dm/aifftr01") spec_fs_cmd["aiifft01-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./eembc-dm/aiifft01") spec_fs_cmd["cacheb01-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./eembc-dm/cacheb01") spec_fs_cmd["matrix01-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./eembc-dm/matrix01") spec_fs_cmd["ttsprk01-vma"] = fsBench("taskset -c 0 ./vma.sh 0.003 ./eembc-dm/ttsprk01") spec_fs_cmd["disparity-itr2-core3-sim-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-core3-sim-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-core3-sim-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-core3-sim-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-core3-sim-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-core3-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./eembc-dm/stat-opt/aifftr01") spec_fs_cmd["aiifft01-core3-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./eembc-dm/stat-opt/aiifft01") spec_fs_cmd["matrix01-core3-vma"] = fsBench("taskset -c 3 ./vma.sh 0 ./eembc-dm/stat-opt/matrix01") spec_fs_cmd["disparity-itr2-sim"] = fsBench("taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim 2") spec_fs_cmd["mser-itr2-sim"] = fsBench("taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim 2") spec_fs_cmd["sift-itr2-sim"] = fsBench("taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim 2") spec_fs_cmd["svm-itr2-sim"] = fsBench("taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim 2") spec_fs_cmd["texture_synthesis-itr2-sim"] = fsBench("taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim 2") spec_fs_cmd["aifftr01"] = fsBench("taskset -c 0 /root/eembc-dm/aifftr01") spec_fs_cmd["aiifft01"] = fsBench("taskset -c 0 /root/eembc-dm/aiifft01") spec_fs_cmd["matrix01"] = fsBench("taskset -c 0 /root/eembc-dm/matrix01") spec_fs_cmd["disparity-itr2-sim-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity ./sd-vbs/itr/disparity/data/sim -d 2") spec_fs_cmd["mser-itr2-sim-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser ./sd-vbs/itr/mser/data/sim -d 2") spec_fs_cmd["sift-itr2-sim-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift ./sd-vbs/itr/sift/data/sim -d 2") spec_fs_cmd["svm-itr2-sim-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm ./sd-vbs/itr/svm/data/sim -d 2") spec_fs_cmd["texture_synthesis-itr2-sim-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis ./sd-vbs/itr/texture_synthesis/data/sim -d 2") spec_fs_cmd["aifftr01-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 /root/eembc-dm/aifftr01 -d") spec_fs_cmd["aiifft01-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 /root/eembc-dm/aiifft01 -d") spec_fs_cmd["matrix01-dm"] = fsBench("./set_wp_mode 2;taskset -c 0 /root/eembc-dm/matrix01 -d") spec_fs_cmd["disparity-itr2-sim-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/disparity/data/sim/disparity_deterministic ./sd-vbs/itr/disparity/data/sim -d 2") spec_fs_cmd["mser-itr2-sim-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/mser/data/sim/mser_deterministic ./sd-vbs/itr/mser/data/sim -d 2") spec_fs_cmd["sift-itr2-sim-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/sift/data/sim/sift_deterministic ./sd-vbs/itr/sift/data/sim -d 2") spec_fs_cmd["svm-itr2-sim-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/svm/data/sim/svm_deterministic ./sd-vbs/itr/svm/data/sim -d 2") spec_fs_cmd["texture_synthesis-itr2-sim-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 ./sd-vbs/itr/texture_synthesis/data/sim/texture_synthesis_deterministic ./sd-vbs/itr/texture_synthesis/data/sim -d 2") spec_fs_cmd["aifftr01-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 /root/eembc-dm/aifftr01_deterministic -d") spec_fs_cmd["aiifft01-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 /root/eembc-dm/aiifft01_deterministic -d") spec_fs_cmd["matrix01-dm-all"] = fsBench("./set_wp_mode 2;taskset -c 0 /root/eembc-dm/matrix01_deterministic -d") spec_fs_cmd["en-wp"] = fsBench("./set_wp_mode 1") spec_fs_cmd["en-dm"] = fsBench("./set_wp_mode 2") spec_fs_cmd["bw683"] = fsBench("/root/bandwidth -m 683 -a write -t 0") spec_fs_cmd["ps-el"] = fsBench("ps -el") # mlock spec_fs_cmd["Ddisparity-itr2-mlock-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["Dlocalization-itr2-mlock-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/mlock/sim/localization ./sd-vbs/sim/localization/data/sim -m 2") spec_fs_cmd["Dmser-itr2-mlock-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["Dsift-itr2-mlock-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["Dsvm-itr2-mlock-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["Dtexture_synthesis-itr2-mlock-sim"] = fsBench("/root/set_wp_mode 1;taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["disparity-itr2-mlock-sim-3b683"] = fsBench("./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["localization-itr2-mlock-sim-3b683"] = fsBench("./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/localization ./sd-vbs/sim/localization/data/sim -m 2") spec_fs_cmd["mser-itr2-mlock-sim-3b683"] = fsBench("./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-mlock-sim-3b683"] = fsBench("./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-mlock-sim-3b683"] = fsBench("./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b683"] = fsBench("./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["disparity-itr2-mlock-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["localization-itr2-mlock-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/localization ./sd-vbs/sim/localization/data/sim -m 2") spec_fs_cmd["mser-itr2-mlock-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-mlock-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-mlock-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b683-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["disparity-itr2-mlock-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["localization-itr2-mlock-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/localization ./sd-vbs/sim/localization/data/sim -m -d 2") spec_fs_cmd["mser-itr2-mlock-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-mlock-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-mlock-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b683-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["disparity-itr2-mlock-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["localization-itr2-mlock-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/localization_deterministic ./sd-vbs/sim/localization/data/sim -m -d 2") spec_fs_cmd["mser-itr2-mlock-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-mlock-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-mlock-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b683-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") # mlock for 4mb spec_fs_cmd["disparity-itr2-mlock-sim-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-mlock-sim-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-mlock-sim-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-mlock-sim-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-mlock-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01") spec_fs_cmd["aiifft01-mlock-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01") spec_fs_cmd["matrix01-mlock-3b1365"] = fsBench("./set_wp_mode 0;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01") spec_fs_cmd["disparity-itr2-mlock-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-mlock-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-mlock-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-mlock-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-mlock-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01") spec_fs_cmd["aiifft01-mlock-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01") spec_fs_cmd["matrix01-mlock-3b1365-wp"] = fsBench("./set_wp_mode 1;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01") spec_fs_cmd["disparity-itr2-mlock-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["mser-itr2-mlock-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-mlock-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-mlock-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["aifftr01-mlock-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01 -d") spec_fs_cmd["aiifft01-mlock-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01 -d") spec_fs_cmd["matrix01-mlock-3b1365-dm"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01 -d") spec_fs_cmd["disparity-itr2-mlock-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["mser-itr2-mlock-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-mlock-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-mlock-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["aifftr01-mlock-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01_deterministic -d") spec_fs_cmd["aiifft01-mlock-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01_deterministic -d") spec_fs_cmd["matrix01-mlock-3b1365-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth -m 1365 -a write -t 0 -c 1 &./bandwidth -m 1365 -a write -t 0 -c 2 &./bandwidth -m 1365 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01_deterministic -d") # 3-real-time spec_fs_cmd["Daifftr01-aiifft01-matrix01-itr"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000 &taskset -c 2 /root/eembc-dm/itr/matrix01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-matrix01-itr-1b2048"] = fsBench("./bandwidth -m 2048 -a write -t 0 -c 3 &taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000 &taskset -c 2 /root/eembc-dm/itr/matrix01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-matrix01-itr-1b2048-wp"] = fsBench("/root/set_wp_mode 1;./bandwidth -m 2048 -a write -t 0 -c 3 &taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000 &taskset -c 2 /root/eembc-dm/itr/matrix01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-matrix01-itr-1b2048-dm-all"] = fsBench("/root/set_wp_mode 2;./bandwidth -m 2048 -a write -t 0 -c 3 &taskset -c 0 /root/eembc-dm/itr/aifftr01_deterministic -d -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01_deterministic -d -i 2000 &taskset -c 2 /root/eembc-dm/itr/matrix01_deterministic -d -i 2000") spec_fs_cmd["aifftr01-aiifft01-matrix01-itr"] = fsBench("taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000 &taskset -c 2 /root/eembc-dm/itr/matrix01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-matrix01-itr-wp"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000 &taskset -c 2 /root/eembc-dm/itr/matrix01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-matrix01-itr-dm-all"] = fsBench("/root/set_wp_mode 2;taskset -c 0 /root/eembc-dm/itr/aifftr01_deterministic -d -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01_deterministic -d -i 2000 &taskset -c 2 /root/eembc-dm/itr/matrix01_deterministic -d -i 2000") # 2-real-time spec_fs_cmd["Daifftr01-aiifft01-itr"] = fsBench("/root/set_wp_mode 1;taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-itr-2b1024"] = fsBench("./bandwidth -m 1024 -a write -t 0 -c 2 &./bandwidth -m 1024 -a write -t 0 -c 3 &taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-itr-2b1024-wp"] = fsBench("/root/set_wp_mode 1;./bandwidth -m 1024 -a write -t 0 -c 2 &./bandwidth -m 1024 -a write -t 0 -c 3 &taskset -c 0 /root/eembc-dm/itr/aifftr01 -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01 -i 2000") spec_fs_cmd["aifftr01-aiifft01-itr-2b1024-dm-all"] = fsBench("/root/set_wp_mode 2;./bandwidth -m 1024 -a write -t 0 -c 2 &./bandwidth -m 1024 -a write -t 0 -c 3 &taskset -c 0 /root/eembc-dm/itr/aifftr01_deterministic -d -i 2000 &taskset -c 1 /root/eembc-dm/itr/aiifft01_deterministic -d -i 2000") # bandwidth rand spec_fs_cmd["disparity-itr2-mlock-sim-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-mlock-sim-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-mlock-sim-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-mlock-sim-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-mlock-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01") spec_fs_cmd["aiifft01-mlock-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01") spec_fs_cmd["matrix01-mlock-3brnd"] = fsBench("./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01") spec_fs_cmd["disparity-itr2-mlock-sim-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-mlock-sim-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-mlock-sim-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-mlock-sim-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-mlock-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01") spec_fs_cmd["aiifft01-mlock-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01") spec_fs_cmd["matrix01-mlock-3brnd-wp"] = fsBench("./set_wp_mode 1;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01") spec_fs_cmd["disparity-itr2-mlock-sim-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["mser-itr2-mlock-sim-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-mlock-sim-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-mlock-sim-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["aifftr01-mlock-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01 -d") spec_fs_cmd["aiifft01-mlock-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01 -d") spec_fs_cmd["matrix01-mlock-3brnd-dm"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01 -d") spec_fs_cmd["disparity-itr2-mlock-sim-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["mser-itr2-mlock-sim-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-mlock-sim-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-mlock-sim-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["aifftr01-mlock-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01_deterministic -d") spec_fs_cmd["aiifft01-mlock-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01_deterministic -d") spec_fs_cmd["matrix01-mlock-3brnd-dm-all"] = fsBench("./set_wp_mode 2;./bandwidth-rand -t 0 -c 1 &./bandwidth-rand -t 0 -c 2 &./bandwidth-rand -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01_deterministic -d") #dmh spec_fs_cmd["disparity-itr2-mlock-sim-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["localization-itr2-mlock-sim-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/localization_determ_heap ./sd-vbs/sim/localization/data/sim -m -d 2") spec_fs_cmd["mser-itr2-mlock-sim-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-mlock-sim-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-mlock-sim-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-mlock-sim-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./sd-vbs/mlock/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["aifftr01-mlock-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aifftr01_determ_heap -d") spec_fs_cmd["aiifft01-mlock-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/aiifft01_determ_heap -d") spec_fs_cmd["cacheb01-mlock-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/cacheb01_determ_heap -d") spec_fs_cmd["matrix01-mlock-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/matrix01_determ_heap -d") spec_fs_cmd["pntrch01-mlock-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/pntrch01_determ_heap -d") spec_fs_cmd["ttsprk01-mlock-3b683-dm-h"] = fsBench("./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &./bandwidth -m 683 -a write -t 0 -c 3 &taskset -c 0 ./eembc-dm/mlock/ttsprk01_determ_heap -d") # with mcf spec_fs_cmd["aifftr01-inf-1mcf"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &") spec_fs_cmd["aiifft01-inf-1mcf"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &") spec_fs_cmd["matrix01-inf-1mcf"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &") spec_fs_cmd["aifftr01-inf-1mcf-dm-all"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &") spec_fs_cmd["aiifft01-inf-1mcf-dm-all"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &") spec_fs_cmd["matrix01-inf-1mcf-dm-all"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &") # with mcf dump and reset stat spec_fs_cmd["disparity-inf-1mcf-ds"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["mser-inf-1mcf-ds"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["sift-inf-1mcf-ds"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["svm-inf-1mcf-ds"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["texture_synthesis-inf-1mcf-ds"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["aifftr01-inf-1mcf-ds"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["aiifft01-inf-1mcf-ds"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["matrix01-inf-1mcf-ds"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["disparity-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["mser-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["sift-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["svm-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["texture_synthesis-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["aifftr01-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["aiifft01-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") spec_fs_cmd["matrix01-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 1 ./spec/dmp_stat/mcf ./spec/inp.in &") # 3 real-time benches with mcf dump and reset stat spec_fs_cmd["3disparity-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") spec_fs_cmd["3disparity-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["3mser-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["3sift-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["3svm-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &") spec_fs_cmd["3disparity-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["3mser-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["3sift-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["3svm-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &") # 1 real-time with 3 mcf dump and reset stat spec_fs_cmd["disparity-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["mser-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["sift-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["svm-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["texture_synthesis-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["aifftr01-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["aiifft01-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["matrix01-inf-3mcf-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") spec_fs_cmd["disparity-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["mser-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["sift-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["svm-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["texture_synthesis-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["aifftr01-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &") spec_fs_cmd["aiifft01-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &") spec_fs_cmd["matrix01-inf-3mcf-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &") spec_fs_cmd["disparity-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["mser-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["sift-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["svm-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["texture_synthesis-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["aifftr01-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &") spec_fs_cmd["aiifft01-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &") spec_fs_cmd["matrix01-inf-3mcf-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/dmp_stat/mcf ./spec/inp.in &taskset -c 1 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 2 ./spec/loop_msg/mcf ./spec/inp.in &taskset -c 3 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &") # 3 real-time benches with bzip2 dump and reset stat spec_fs_cmd["3disparity-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") spec_fs_cmd["3disparity-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &") spec_fs_cmd["3disparity-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &") # 1 real-time with 3 bzip2 dump and reset stat spec_fs_cmd["disparity-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["mser-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["sift-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["svm-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["texture_synthesis-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["aifftr01-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["aiifft01-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["matrix01-inf-3bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") spec_fs_cmd["disparity-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["mser-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["sift-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["svm-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["texture_synthesis-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["aifftr01-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &") spec_fs_cmd["aiifft01-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &") spec_fs_cmd["matrix01-inf-3bzip2-ds-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &") spec_fs_cmd["disparity-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["mser-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["sift-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["svm-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["texture_synthesis-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["aifftr01-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &") spec_fs_cmd["aiifft01-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &") spec_fs_cmd["matrix01-inf-3bzip2-ds-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 2 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg &taskset -c 3 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &") spec_fs_cmd["bzip2-ds-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &") # real-time on core 3 spec_fs_cmd["Ddisparity-itr2-core3-sim"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["Dmser-itr2-core3-sim"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["Dsift-itr2-core3-sim"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["Dsvm-itr2-core3-sim"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["Dtexture_synthesis-itr2-core3-sim"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["Daifftr01-core3"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./eembc-dm/stat-opt/aifftr01") spec_fs_cmd["Daiifft01-core3"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./eembc-dm/stat-opt/aiifft01") spec_fs_cmd["Dmatrix01-core3"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./eembc-dm/stat-opt/matrix01") spec_fs_cmd["disparity-itr2-core3-sim-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-core3-sim-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-core3-sim-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-core3-sim-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-core3-sim-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-core3-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01") spec_fs_cmd["aiifft01-core3-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01") spec_fs_cmd["matrix01-core3-3b683"] = fsBench("taskset -c 0 ./set_wp_mode 0;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/matrix01") spec_fs_cmd["disparity-itr2-core3-sim-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-core3-sim-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-core3-sim-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-core3-sim-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-core3-sim-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-core3-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01") spec_fs_cmd["aiifft01-core3-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01") spec_fs_cmd["matrix01-core3-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/matrix01") spec_fs_cmd["disparity-itr2-core3-sim-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["mser-itr2-core3-sim-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-core3-sim-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-core3-sim-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-core3-sim-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["aifftr01-core3-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_determ_heap -d") spec_fs_cmd["aiifft01-core3-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_determ_heap -d") spec_fs_cmd["matrix01-core3-3b683-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_determ_heap -d") spec_fs_cmd["disparity-itr2-core3-sim-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -m -d 2") spec_fs_cmd["mser-itr2-core3-sim-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -m -d 2") spec_fs_cmd["sift-itr2-core3-sim-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -m -d 2") spec_fs_cmd["svm-itr2-core3-sim-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -m -d 2") spec_fs_cmd["texture_synthesis-itr2-core3-sim-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -m -d 2") spec_fs_cmd["aifftr01-core3-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_deterministic -d") spec_fs_cmd["aiifft01-core3-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_deterministic -d") spec_fs_cmd["matrix01-core3-3b683-dm-all"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_deterministic -d") # sift itr4 spec_fs_cmd["Dsift-itr4-core3-sim"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 4") spec_fs_cmd["sift-itr4-core3-sim-3b683-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 4") # PALLOC tests spec_fs_cmd["l4m11-3bw4m"] = fsBench("taskset -c 0 ./set_wp_mode 0;./cr3-shared.sh 4096 write;./latency-nosleep.sh 4096 11") spec_fs_cmd["l4m11"] = fsBench("taskset -c 0 ./set_wp_mode 0;./latency-nosleep.sh 4096 11") spec_fs_cmd["l4m2-p4"] = fsBench("taskset -c 0 ./set_wp_mode 0;./latency-nosleep-pconfig.sh 4096 2 part4 3") spec_fs_cmd["aifftr01-palloc-p4-dm-h"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 3 ./eembc-dm/stat-opt/aifftr01-dmh-p.sh part4") # SD-VBS CIF spec_fs_cmd["disparity-cif-solo"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity -m 2") spec_fs_cmd["mser-cif-solo"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/mser/mser ./sd-vbs/stat-opt/cif/mser -m 2") spec_fs_cmd["sift-cif-solo"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/sift/sift ./sd-vbs/stat-opt/cif/sift -m 2") spec_fs_cmd["svm-cif-solo"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/svm/svm ./sd-vbs/stat-opt/cif/svm -m 2") spec_fs_cmd["texture_synthesis-cif-solo"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/texture_synthesis/texture_synthesis ./sd-vbs/stat-opt/cif/texture_synthesis -m 2") # BW 4 MB spec_fs_cmd["disparity-cif-3b4096-sbfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./palloc-assign.sh part8 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part9 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part10 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part11 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity -m 2") spec_fs_cmd["mser-cif-3b4096-sbfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./palloc-assign.sh part8 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part9 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part10 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part11 ./sd-vbs/stat-opt/cif/mser/mser ./sd-vbs/stat-opt/cif/mser -m 2") spec_fs_cmd["sift-cif-3b4096-sbfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./palloc-assign.sh part8 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part9 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part10 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part11 ./sd-vbs/stat-opt/cif/sift/sift ./sd-vbs/stat-opt/cif/sift -m 2") spec_fs_cmd["svm-cif-3b4096-sbfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./palloc-assign.sh part8 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part9 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part10 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part11 ./sd-vbs/stat-opt/cif/svm/svm ./sd-vbs/stat-opt/cif/svm -m 2") spec_fs_cmd["texture_synthesis-cif-3b4096-sbfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./palloc-assign.sh part8 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part9 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part10 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part11 ./sd-vbs/stat-opt/cif/texture_synthesis/texture_synthesis ./sd-vbs/stat-opt/cif/texture_synthesis -m 2") spec_fs_cmd["disparity-cif-3b4096-budfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity -m 2") spec_fs_cmd["mser-cif-3b4096-budfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/cif/mser/mser ./sd-vbs/stat-opt/cif/mser -m 2") spec_fs_cmd["sift-cif-3b4096-budfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/cif/sift/sift ./sd-vbs/stat-opt/cif/sift -m 2") spec_fs_cmd["svm-cif-3b4096-budfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/cif/svm/svm ./sd-vbs/stat-opt/cif/svm -m 2") spec_fs_cmd["texture_synthesis-cif-3b4096-budfr"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/cif/texture_synthesis/texture_synthesis ./sd-vbs/stat-opt/cif/texture_synthesis -m 2") spec_fs_cmd["disparity-cif-3b4096-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity -m 2") spec_fs_cmd["mser-cif-3b4096-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/mser/mser ./sd-vbs/stat-opt/cif/mser -m 2") spec_fs_cmd["sift-cif-3b4096-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/sift/sift ./sd-vbs/stat-opt/cif/sift -m 2") spec_fs_cmd["svm-cif-3b4096-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/svm/svm ./sd-vbs/stat-opt/cif/svm -m 2") spec_fs_cmd["texture_synthesis-cif-3b4096-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/cif/texture_synthesis/texture_synthesis ./sd-vbs/stat-opt/cif/texture_synthesis -m 2") spec_fs_cmd["disparity-cif-3b4096-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/disparity/disparity_deterministic ./sd-vbs/stat-opt/cif/disparity -m -d 2") spec_fs_cmd["mser-cif-3b4096-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/mser/mser_deterministic ./sd-vbs/stat-opt/cif/mser -m -d 2") spec_fs_cmd["sift-cif-3b4096-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/sift/sift_deterministic ./sd-vbs/stat-opt/cif/sift -m -d 2") spec_fs_cmd["svm-cif-3b4096-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/svm/svm_deterministic ./sd-vbs/stat-opt/cif/svm -m -d 2") spec_fs_cmd["texture_synthesis-cif-3b4096-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/texture_synthesis/texture_synthesis_deterministic ./sd-vbs/stat-opt/cif/texture_synthesis -m -d 2") spec_fs_cmd["disparity-cif-3b4096-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/disparity/disparity_cif_determ_top ./sd-vbs/stat-opt/cif/disparity -m 2 --ndmpgs 692") spec_fs_cmd["mser-cif-3b4096-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/mser/mser_cif_determ_top ./sd-vbs/stat-opt/cif/mser -m 2 --ndmpgs 883") spec_fs_cmd["sift-cif-3b4096-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/sift/sift_cif_determ_top ./sd-vbs/stat-opt/cif/sift -m 2 --ndmpgs 7360") spec_fs_cmd["svm-cif-3b4096-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/svm/svm_cif_determ_top ./sd-vbs/stat-opt/cif/svm -m 2 --ndmpgs 65") spec_fs_cmd["texture_synthesis-cif-3b4096-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/texture_synthesis/texture_synthesis_cif_determ_top ./sd-vbs/stat-opt/cif/texture_synthesis -m 2 --ndmpgs 343") spec_fs_cmd["disparity-cif-3b4096-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/disparity/disparity_cif_determ_top ./sd-vbs/stat-opt/cif/disparity -m 2 --ndmpgs 555") spec_fs_cmd["mser-cif-3b4096-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/mser/mser_cif_determ_top ./sd-vbs/stat-opt/cif/mser -m 2 --ndmpgs 683") spec_fs_cmd["sift-cif-3b4096-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/sift/sift_cif_determ_top ./sd-vbs/stat-opt/cif/sift -m 2 --ndmpgs 5626") spec_fs_cmd["svm-cif-3b4096-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/svm/svm_cif_determ_top ./sd-vbs/stat-opt/cif/svm -m 2 --ndmpgs 36") spec_fs_cmd["texture_synthesis-cif-3b4096-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 4096 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 4096 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 4096 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/cif/texture_synthesis/texture_synthesis_cif_determ_top ./sd-vbs/stat-opt/cif/texture_synthesis -m 2 --ndmpgs 283") # top pages spec_fs_cmd["disparity-itr2-core3-sim-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-core3-sim-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-core3-sim-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-core3-sim-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-core3-sim-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-core3-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_determ_top") spec_fs_cmd["aiifft01-core3-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_determ_top") spec_fs_cmd["matrix01-core3-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_determ_top") spec_fs_cmd["3disparity-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ds-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 &") # balanced coloring spec_fs_cmd["sift-itr2-core3-sim-3b683-dmt"] = fsBench("taskset -c 0 ./set_wp_mode 2;./bandwidth -m 683 -a write -t 0 -c 0 &./bandwidth -m 683 -a write -t 0 -c 1 &./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -m 2") # with medusa spec_fs_cmd["disparity-itr2-core3-sim-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-core3-sim-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-core3-sim-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-core3-sim-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-core3-sim-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-core3-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aifftr01_determ_top") spec_fs_cmd["aiifft01-core3-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aiifft01_determ_top") spec_fs_cmd["matrix01-core3-3b683-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part5 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part6 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/matrix01_determ_top") spec_fs_cmd["3disparity-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 &taskset -c 2 ./palloc-assign.sh part6 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 &taskset -c 2 ./palloc-assign.sh part6 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ds-dmt-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./palloc-assign.sh part4 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./palloc-assign.sh part5 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 &taskset -c 2 ./palloc-assign.sh part6 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 &") # 1 bzip2, NoP spec_fs_cmd["3disparity-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ds-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./spec/init_exit/bzip2 ./spec/data/chicken.jpg -s &taskset -c 1 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") # bzip2 exit inst spec_fs_cmd["3disparity-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 35 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 35 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 35 &") spec_fs_cmd["3mser-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 65 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 65 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 65 &") spec_fs_cmd["3sift-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 95 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 95 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 95 &") spec_fs_cmd["3svm-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 26 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 26 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 26 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 41 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 41 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 41 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 13 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 13 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 13 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 14 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 14 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 14 &") spec_fs_cmd["3matrix01-inf-1bzip2-ei-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 16 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 16 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 16 &") spec_fs_cmd["3disparity-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 25 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 25 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 25 &") spec_fs_cmd["3mser-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 48 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 48 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 48 &") spec_fs_cmd["3sift-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 75 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 75 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 75 &") spec_fs_cmd["3svm-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 16 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 16 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 16 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 33 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 33 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 33 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 10 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 10 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 10 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 12 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 12 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 12 &") spec_fs_cmd["3matrix01-inf-1bzip2-ei-dmt90"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 12 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 12 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 12 &") spec_fs_cmd["3disparity-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_determ_heap ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_determ_heap ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_determ_heap ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_determ_heap ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_heap ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_determ_heap -d -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_determ_heap -d -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ei-dmh"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_determ_heap -d -s -i 200000 &") spec_fs_cmd["3disparity-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_deterministic -d -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_deterministic -d -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ei-dma"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_deterministic -d -s -i 200000 &") spec_fs_cmd["3disparity-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./palloc-assign.sh part6 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 2 ./palloc-assign.sh part6 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 2 ./palloc-assign.sh part6 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ei-wp"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./palloc-assign.sh part5 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 2 ./palloc-assign.sh part6 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") spec_fs_cmd["3disparity-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1bzip2-ei-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./spec/exit_inst/bzip2 ./spec/data/chicken.jpg -s -e 200 &taskset -c 1 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") # new setup: medusa, and top pages support spec_fs_cmd["disparity-itr2-sim-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -m 2 --ndmpgs 35") spec_fs_cmd["mser-itr2-sim-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -m 2 --ndmpgs 65") spec_fs_cmd["sift-itr2-sim-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -m 2 --ndmpgs 95") spec_fs_cmd["svm-itr2-sim-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -m 2 --ndmpgs 26") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -m 2 --ndmpgs 41") spec_fs_cmd["aifftr01-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_determ_top --ndmpgs 13") spec_fs_cmd["aiifft01-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_determ_top --ndmpgs 14") spec_fs_cmd["matrix01-3b683-dmt98-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_determ_top --ndmpgs 16") spec_fs_cmd["disparity-itr2-sim-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -m 2 --ndmpgs 25") spec_fs_cmd["mser-itr2-sim-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -m 2 --ndmpgs 48") spec_fs_cmd["sift-itr2-sim-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -m 2 --ndmpgs 75") spec_fs_cmd["svm-itr2-sim-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -m 2 --ndmpgs 16") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -m 2 --ndmpgs 33") spec_fs_cmd["aifftr01-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_determ_top --ndmpgs 10") spec_fs_cmd["aiifft01-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_determ_top --ndmpgs 12") spec_fs_cmd["matrix01-3b683-dmt90-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_determ_top --ndmpgs 12") spec_fs_cmd["disparity-itr2-sim-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_deterministic ./sd-vbs/sim/disparity/data/sim -d -m 2") spec_fs_cmd["mser-itr2-sim-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_deterministic ./sd-vbs/sim/mser/data/sim -d -m 2") spec_fs_cmd["sift-itr2-sim-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_deterministic ./sd-vbs/sim/sift/data/sim -d -m 2") spec_fs_cmd["svm-itr2-sim-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_deterministic ./sd-vbs/sim/svm/data/sim -d -m 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_deterministic ./sd-vbs/sim/texture_synthesis/data/sim -d -m 2") spec_fs_cmd["aifftr01-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_deterministic -d") spec_fs_cmd["aiifft01-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_deterministic -d") spec_fs_cmd["matrix01-3b683-dma-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_deterministic -d") spec_fs_cmd["disparity-itr2-sim-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-sim-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-sim-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-sim-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aifftr01") spec_fs_cmd["aiifft01-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aiifft01") spec_fs_cmd["matrix01-3b683-wp-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./palloc-assign.sh part1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./palloc-assign.sh part2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/matrix01") spec_fs_cmd["disparity-itr2-sim-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-sim-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-sim-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-sim-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aifftr01") spec_fs_cmd["aiifft01-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/aiifft01") spec_fs_cmd["matrix01-3b683-solo-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 1;taskset -c 0 ./set_medusa_mode 4;taskset -c 3 ./palloc-assign.sh part7 ./eembc-dm/stat-opt/matrix01") spec_fs_cmd["disparity-itr2-sim-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -m 2") spec_fs_cmd["mser-itr2-sim-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -m 2") spec_fs_cmd["sift-itr2-sim-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -m 2") spec_fs_cmd["svm-itr2-sim-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -m 2") spec_fs_cmd["texture_synthesis-itr2-sim-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -m 2") spec_fs_cmd["aifftr01-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01") spec_fs_cmd["aiifft01-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01") spec_fs_cmd["matrix01-3b683-nop-mdu"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./bandwidth -m 683 -a write -t 0 -c 0 &taskset -c 1 ./bandwidth -m 683 -a write -t 0 -c 1 &taskset -c 2 ./bandwidth -m 683 -a write -t 0 -c 2 &taskset -c 3 ./eembc-dm/stat-opt/matrix01") # disparity-cif co-runner spec_fs_cmd["3disparity-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/disparity ./sd-vbs/sim/disparity/data/sim -s -m 20000 &") spec_fs_cmd["3mser-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/mser ./sd-vbs/sim/mser/data/sim -s -m 20000 &") spec_fs_cmd["3sift-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/sift ./sd-vbs/sim/sift/data/sim -s -m 20000 &") spec_fs_cmd["3svm-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/svm ./sd-vbs/sim/svm/data/sim -s -m 20000 &") spec_fs_cmd["3texture_synthesis-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 2 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &taskset -c 3 ./sd-vbs/stat-opt/sim/texture_synthesis ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 &") spec_fs_cmd["3aifftr01-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aifftr01 -s -i 200000 &") spec_fs_cmd["3aiifft01-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/aiifft01 -s -i 200000 &") spec_fs_cmd["3matrix01-inf-1disparity-cif-nop"] = fsBench("taskset -c 0 ./set_wp_mode 0;taskset -c 0 ./set_medusa_mode 0;taskset -c 0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 2 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &taskset -c 3 ./eembc-dm/stat-opt/matrix01 -s -i 200000 &") spec_fs_cmd["3disparity-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 35 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 35 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/disparity_determ_top ./sd-vbs/sim/disparity/data/sim -s -m 20000 --ndmpgs 35 &") spec_fs_cmd["3mser-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 65 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 65 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/mser_determ_top ./sd-vbs/sim/mser/data/sim -s -m 20000 --ndmpgs 65 &") spec_fs_cmd["3sift-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 95 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 95 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/sift_determ_top ./sd-vbs/sim/sift/data/sim -s -m 20000 --ndmpgs 95 &") spec_fs_cmd["3svm-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 26 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 26 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/svm_determ_top ./sd-vbs/sim/svm/data/sim -s -m 20000 --ndmpgs 26 &") spec_fs_cmd["3texture_synthesis-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 41 &taskset -c 2 ./palloc-assign.sh part2 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 41 &taskset -c 3 ./palloc-assign.sh part3 ./sd-vbs/stat-opt/sim/texture_synthesis_determ_top ./sd-vbs/sim/texture_synthesis/data/sim -s -m 20000 --ndmpgs 41 &") spec_fs_cmd["3aifftr01-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 13 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 13 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aifftr01_determ_top -s -i 200000 --ndmpgs 13 &") spec_fs_cmd["3aiifft01-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 14 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 14 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/aiifft01_determ_top -s -i 200000 --ndmpgs 14 &") spec_fs_cmd["3matrix01-inf-1disparity-cif-dmt98"] = fsBench("taskset -c 0 ./set_wp_mode 2;taskset -c 0 ./set_medusa_mode 4;taskset -c 0 ./palloc-assign.sh part0 ./sd-vbs/stat-opt/cif/disparity/disparity ./sd-vbs/stat-opt/cif/disparity 2 &taskset -c 1 ./palloc-assign.sh part1 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 16 &taskset -c 2 ./palloc-assign.sh part2 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 16 &taskset -c 3 ./palloc-assign.sh part3 ./eembc-dm/stat-opt/matrix01_determ_top -s -i 200000 --ndmpgs 16 &") #vision spec_fs_cmd["disparity"] = fsBench("/root/vision.sh disparity-sqcif") #spec_fs_cmd["disparity"] = fsBench("/root/vision/disparity-sqcif/disparity /root/vision/disparity-sqcif") spec_fs_cmd["localization"] = fsBench("/root/vision.sh localization-sqcif") spec_fs_cmd["mser"] = fsBench("/root/vision.sh mser-sqcif") spec_fs_cmd["multi_ncut"] = fsBench("/root/vision.sh multi_ncut-sqcif") spec_fs_cmd["sift"] = fsBench("/root/vision.sh sift-sqcif") spec_fs_cmd["stitch"] = fsBench("/root/vision.sh stitch-sqcif") spec_fs_cmd["svm"] = fsBench("/root/vision.sh svm-sqcif") spec_fs_cmd["texture_synthesis"] = fsBench("/root/vision.sh texture_synthesis-sqcif") spec_fs_cmd["tracking"] = fsBench("/root/vision.sh tracking-sqcif") spec_fs_cmd["l-D1bwr"] = fsBench("/root/cr1.sh 4096 read;/root/latency.sh 128 21") spec_fs_cmd["l-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/latency.sh 128 21") spec_fs_cmd["bwr-D1bwr"] = fsBench("/root/cr1.sh 4096 read;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-L1bwr"] = fsBench("/root/cr1.sh 128 read;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-L1bww"] = fsBench("/root/cr1.sh 128 write;/root/bw.sh 128 101 read") spec_fs_cmd["l-D2bwr"] = fsBench("/root/cr2.sh 4096 read;/root/latency.sh 128 21") spec_fs_cmd["l-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/latency.sh 128 21") spec_fs_cmd["bwr-D2bwr"] = fsBench("/root/cr2.sh 4096 read;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-L2bwr"] = fsBench("/root/cr2.sh 128 read;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-L2bww"] = fsBench("/root/cr2.sh 128 write;/root/bw.sh 128 101 read") spec_fs_cmd["l-D3bwr"] = fsBench("/root/cr3.sh 4096 read;/root/latency.sh 128 21") spec_fs_cmd["l-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/latency.sh 128 21") spec_fs_cmd["bwr-D3bwr"] = fsBench("/root/cr3.sh 4096 read;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-L3bwr"] = fsBench("/root/cr3.sh 128 read;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/bw.sh 128 101 read") spec_fs_cmd["bwr-L3bww"] = fsBench("/root/cr3.sh 128 write;/root/bw.sh 128 101 read") #spec_fs_cmd["nmpc"] = fsBench("/root/nmpc.sh 1000") spec_fs_cmd["aifftr01-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/eem.sh aifftr01") spec_fs_cmd["aiifft01-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/eem.sh aiifft01") spec_fs_cmd["cacheb01-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/eem.sh cacheb01") spec_fs_cmd["rgbhpg01-D3bww"] = fsBench("/root/cr3.sh 4096 write;ls;/root/eem.sh rgbhpg01") spec_fs_cmd["rgbyiq01-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/eem.sh rgbyiq01") spec_fs_cmd["disparity-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/vision.sh disparity-sqcif") spec_fs_cmd["mser-D3bww"] = fsBench("/root/cr3.sh 4096 write;ls;/root/vision.sh mser-sqcif") spec_fs_cmd["sift-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/vision.sh sift-sqcif") spec_fs_cmd["localization-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/vision.sh localization-sqcif") spec_fs_cmd["svm-D3bww"] = fsBench("/root/cr3.sh 4096 write;/root/vision.sh svm-sqcif") spec_fs_cmd["aifftr01-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/eem.sh aifftr01") spec_fs_cmd["aiifft01-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/eem.sh aiifft01") spec_fs_cmd["cacheb01-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/eem.sh cacheb01") spec_fs_cmd["rgbhpg01-D2bww"] = fsBench("/root/cr2.sh 4096 write;ls;/root/eem.sh rgbhpg01") spec_fs_cmd["rgbyiq01-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/eem.sh rgbyiq01") spec_fs_cmd["disparity-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/vision.sh disparity-sqcif") spec_fs_cmd["mser-D2bww"] = fsBench("/root/cr2.sh 4096 write;ls;/root/vision.sh mser-sqcif") spec_fs_cmd["svm-D2bww"] = fsBench("/root/cr2.sh 4096 write;/root/vision.sh svm-sqcif") spec_fs_cmd["aifftr01-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/eem.sh aifftr01") spec_fs_cmd["aiifft01-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/eem.sh aiifft01") spec_fs_cmd["cacheb01-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/eem.sh cacheb01") spec_fs_cmd["rgbhpg01-D1bww"] = fsBench("/root/cr1.sh 4096 write;ls;/root/eem.sh rgbhpg01") spec_fs_cmd["rgbyiq01-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/eem.sh rgbyiq01") spec_fs_cmd["disparity-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/vision.sh disparity-sqcif") spec_fs_cmd["mser-D1bww"] = fsBench("/root/cr1.sh 4096 write;ls;/root/vision.sh mser-sqcif") spec_fs_cmd["svm-D1bww"] = fsBench("/root/cr1.sh 4096 write;/root/vision.sh svm-sqcif") spec_fs_cmd["aifftr01-3lbm"] = fsBench("/root/eem.sh aifftr01") spec_fs_cmd["aiifft01-3lbm"] = fsBench("/root/eem.sh aiifft01") spec_fs_cmd["cacheb01-3lbm"] = fsBench("/root/eem.sh cacheb01") spec_fs_cmd["rgbhpg01-3lbm"] = fsBench("/root/eem.sh rgbhpg01") spec_fs_cmd["rgbyiq01-3lbm"] = fsBench("/root/eem.sh rgbyiq01") spec_fs_cmd["disparity-3lbm"] = fsBench("/root/vision.sh disparity-sqcif") spec_fs_cmd["mser-3lbm"] = fsBench("/root/vision.sh mser-sqcif") spec_fs_cmd["svm-3lbm"] = fsBench("/root/vision.sh svm-sqcif") spec_fs_cmd["aifftr01-3opp"] = fsBench("/root/eem.sh aifftr01") spec_fs_cmd["aiifft01-3opp"] = fsBench("/root/eem.sh aiifft01") spec_fs_cmd["cacheb01-3opp"] = fsBench("/root/eem.sh cacheb01") spec_fs_cmd["rgbhpg01-3opp"] = fsBench("/root/eem.sh rgbhpg01") spec_fs_cmd["rgbyiq01-3opp"] = fsBench("/root/eem.sh rgbyiq01") spec_fs_cmd["disparity-3opp"] = fsBench("/root/vision.sh disparity-sqcif") spec_fs_cmd["mser-3opp"] = fsBench("/root/vision.sh mser-sqcif") spec_fs_cmd["svm-3opp"] = fsBench("/root/vision.sh svm-sqcif") #multi threaded - For renatos experiment spec_fs_cmd["cohebench"] = fsBench("/root/cohebench -t 0") spec_fs_cmd["cohebench3"] = fsBench("/root/cohebench -t 3") spec_fs_cmd["cohebench-o"] = fsBench("/root/cohebench -t 0 -c outer") spec_fs_cmd["cohebench3-o"] = fsBench("/root/cohebench -t 3 -c outer") spec_fs_cmd["bt"] = fsBench("/root/bt -m 32 -c 0 -b 1024") spec_fs_cmd["bt-64"] = fsBench("/root/bandwidth-test -m 64 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-128"] = fsBench("/root/bandwidth-test -m 128 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-256"] = fsBench("/root/bandwidth-test -m 256 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-512"] = fsBench("/root/bandwidth-test -m 512 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-1K"] = fsBench("/root/bandwidth-test -m 1024 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-2K"] = fsBench("/root/bandwidth-test -m 2048 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-4K"] = fsBench("/root/bandwidth-test -m 4096 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-8K"] = fsBench("/root/bandwidth-test -m 8192 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-16K"] = fsBench("/root/bandwidth-test -m 16384 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bt-32K"] = fsBench("/root/bandwidth-test -m 32768 -b 1024 -a read -d 0 -c 0") spec_fs_cmd["bwr-solo-1K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 0 -i 1000 -m 1 -t 0") spec_fs_cmd["bwr-solo-2K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 0 -i 1000 -m 2 -t 0") spec_fs_cmd["bwr-solo-4K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 0 -i 1000 -m 4 -t 0") spec_fs_cmd["bwr-solo-8K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 0 -i 1000 -m 8 -t 0") spec_fs_cmd["bwr-solo-16K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 0 -i 1000 -m 16 -t 0") spec_fs_cmd["bwr-solo-32K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 0 -i 1000 -m 32 -t 0") spec_fs_cmd["bwr-solo-2048K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 0 -i 1000 -m 2048 -t 0") spec_fs_cmd["bwr-1T-1K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 1 -i 1000 -m 1 -t 0") spec_fs_cmd["bwr-1T-2K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 1 -i 1000 -m 2 -t 0") spec_fs_cmd["bwr-1T-4K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 1 -i 1000 -m 4 -t 0") spec_fs_cmd["bwr-1T-8K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 1 -i 1000 -m 8 -t 0") spec_fs_cmd["bwr-1T-16K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 1 -i 1000 -m 16 -t 0") spec_fs_cmd["bwr-1T-32K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 1 -i 1000 -m 32 -t 0") spec_fs_cmd["bwr-2T-1K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 2 -i 1000 -m 1 -t 0") spec_fs_cmd["bwr-2T-2K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 2 -i 1000 -m 2 -t 0") spec_fs_cmd["bwr-2T-4K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 2 -i 1000 -m 4 -t 0") spec_fs_cmd["bwr-2T-8K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 2 -i 1000 -m 8 -t 0") spec_fs_cmd["bwr-2T-16K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 2 -i 1000 -m 16 -t 0") spec_fs_cmd["bwr-2T-32K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 2 -i 1000 -m 32 -t 0") spec_fs_cmd["bwr-3T-1K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 3 -i 1000 -m 1 -t 0") spec_fs_cmd["bwr-3T-2K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 3 -i 1000 -m 2 -t 0") spec_fs_cmd["bwr-3T-4K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 3 -i 1000 -m 4 -t 0") spec_fs_cmd["bwr-3T-8K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 3 -i 1000 -m 8 -t 0") spec_fs_cmd["bwr-3T-16K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 3 -i 1000 -m 16 -t 0") spec_fs_cmd["bwr-3T-32K"] = fsBench("/root/bandwidth-thread -a read -c 0 -d 3 -i 1000 -m 32 -t 0") spec_fs_cmd["bwr-1K"] = fsBench("/root/bw.sh 1 1000 read") spec_fs_cmd["bwr-2K"] = fsBench("/root/bw.sh 2 1000 read") spec_fs_cmd["bwr-4K"] = fsBench("/root/bw.sh 4 1000 read") spec_fs_cmd["bwr-8K"] = fsBench("/root/bw.sh 8 1000 read") spec_fs_cmd["bwr-16K"] = fsBench("/root/bw.sh 16 1000 read") spec_fs_cmd["bwr-32K"] = fsBench("/root/bw.sh 32 1000 read") spec_fs_cmd["bwr-1P-1K"] = fsBench("/root/cr1.sh 1 write;/root/bw.sh 1 1000 read") spec_fs_cmd["bwr-1P-2K"] = fsBench("/root/cr1.sh 2 write;/root/bw.sh 2 1000 read") spec_fs_cmd["bwr-1P-4K"] = fsBench("/root/cr1.sh 4 write;/root/bw.sh 4 1000 read") spec_fs_cmd["bwr-1P-8K"] = fsBench("/root/cr1.sh 8 write;/root/bw.sh 8 1000 read") spec_fs_cmd["bwr-1P-16K"] = fsBench("/root/cr1.sh 16 write;/root/bw.sh 16 1000 read") spec_fs_cmd["bwr-1P-32K"] = fsBench("/root/cr1.sh 32 write;/root/bw.sh 32 1000 read") spec_fs_cmd["bwr-2P-1K"] = fsBench("/root/cr2.sh 1 write;/root/bw.sh 1 1000 read") spec_fs_cmd["bwr-2P-2K"] = fsBench("/root/cr2.sh 2 write;/root/bw.sh 2 1000 read") spec_fs_cmd["bwr-2P-4K"] = fsBench("/root/cr2.sh 4 write;/root/bw.sh 4 1000 read") spec_fs_cmd["bwr-2P-8K"] = fsBench("/root/cr2.sh 8 write;/root/bw.sh 8 1000 read") spec_fs_cmd["bwr-2P-16K"] = fsBench("/root/cr2.sh 16 write;/root/bw.sh 16 1000 read") spec_fs_cmd["bwr-2P-32K"] = fsBench("/root/cr2.sh 32 write;/root/bw.sh 32 1000 read") spec_fs_cmd["bwr-3P-1K"] = fsBench("/root/cr3.sh 1 write;/root/bw.sh 1 1000 read") spec_fs_cmd["bwr-3P-2K"] = fsBench("/root/cr3.sh 2 write;/root/bw.sh 2 1000 read") spec_fs_cmd["bwr-3P-4K"] = fsBench("/root/cr3.sh 4 write;/root/bw.sh 4 1000 read") spec_fs_cmd["bwr-3P-8K"] = fsBench("/root/cr3.sh 8 write;/root/bw.sh 8 1000 read") spec_fs_cmd["bwr-3P-16K"] = fsBench("/root/cr3.sh 16 write;/root/bw.sh 16 1000 read") spec_fs_cmd["bwr-3P-32K"] = fsBench("/root/cr3.sh 32 write;/root/bw.sh 32 1000 read") #periodic spec_fs_cmd["aifftr01P"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/eembc_periodic/aifftr01 -o -r 7 -c 0 -p 20 &") spec_fs_cmd["aiifft01P"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/eembc_periodic/aiifft01 -o -r 7 -c 0 -p 20 &") spec_fs_cmd["cacheb01P"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/eembc_periodic/cacheb01 -o -r 7 -c 0 -p 20 &") spec_fs_cmd["rgbhpg01P"] = fsBench("/bin/echo $$ > /sys/fs/cgroup/part1/tasks;taskset -c 0 /root/eembc_periodic/rgbhpg01") spec_fs_cmd["rt4"] = fsBench("/root/eem_p.sh") spec_fs_cmd["rt4-cr4"] = fsBench("/root/cr4-part.sh 4096 write;/root/eem_p.sh") spec_fs_cmd["hrt"] = fsBench("/root/hrtS.sh 2048 7") spec_fs_cmd["hrt4-cr4"] = fsBench("/root/cr4.sh 2048 write;/root/hrt.sh 2048 7") spec_fs_cmd["hrt4-cr0"] = fsBench("/root/hrt.sh 2048 7") spec_fs_cmd["nmpc"] = fsBench("/root/nmpc.sh 6") spec_fs_cmd["nmpc4-cr4"] = fsBench("/root/cr4.sh 2048 write;/root/nmpc4.sh 6") spec_fs_cmd["nmpc4"] = fsBench("/root/nmpc4.sh 6") spec_fs_cmd["eembc"] = fsBench("/root/eembc.sh 7") spec_fs_cmd["eembc4-cr4"] = fsBench("/root/cr4.sh 2048 write;/root/eembc4.sh 7") spec_fs_cmd["eembc4"] = fsBench("/root/eembc4.sh 7") spec_fs_cmd["aiifft01-iter"] = fsBench("/root/eem-iter.sh aiifft01 3") spec_fs_cmd["mg"] = fsBench("/root/budget.sh 1000 2000 5000 10000;/root/m5 enablememguard 1;/root/bwmg.sh 2048 1 read") spec_fs_cmd["mg-solo"] = fsBench("/root/m5 setmembudget 0 1000;/root/m5 enablememguard 1;/bin/echo $$ > /sys/fs/cgroup/part1/tasks;/root/bandwidth -c 0 -t 0 -m 2048 -a read -i 10&") #1RT spec_fs_cmd["a2time01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh a2time01") spec_fs_cmd["aifftr01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aifftr01") spec_fs_cmd["aifirf01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aifirf01") spec_fs_cmd["aiifft01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aiifft01") spec_fs_cmd["basefp01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh basefp01") spec_fs_cmd["bitmnp01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh bitmnp01") spec_fs_cmd["cacheb01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh cacheb01") spec_fs_cmd["canrdr01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh canrdr01") spec_fs_cmd["idctrn01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh idctrn01") spec_fs_cmd["iirflt01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh iirflt01") spec_fs_cmd["matrix01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh matrix01") spec_fs_cmd["pntrch01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh pntrch01") spec_fs_cmd["puwmod01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh puwmod01") spec_fs_cmd["rspeed01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh rspeed01") spec_fs_cmd["tblook01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh tblook01") spec_fs_cmd["ttsprk01-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh ttsprk01") spec_fs_cmd["nmpc-1RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/nmpc.sh 1000") #2RT spec_fs_cmd["a2time01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh a2time01") spec_fs_cmd["aifftr01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aifftr01") spec_fs_cmd["aifirf01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aifirf01") spec_fs_cmd["aiifft01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aiifft01") spec_fs_cmd["basefp01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh basefp01") spec_fs_cmd["bitmnp01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh bitmnp01") spec_fs_cmd["cacheb01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh cacheb01") spec_fs_cmd["canrdr01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh canrdr01") spec_fs_cmd["idctrn01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh idctrn01") spec_fs_cmd["iirflt01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh iirflt01") spec_fs_cmd["matrix01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh matrix01") spec_fs_cmd["pntrch01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh pntrch01") spec_fs_cmd["puwmod01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh puwmod01") spec_fs_cmd["rspeed01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh rspeed01") spec_fs_cmd["tblook01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh tblook01") spec_fs_cmd["ttsprk01-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh ttsprk01") spec_fs_cmd["nmpc-2RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/nmpc.sh 1000") #3RT spec_fs_cmd["a2time01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh a2time01") spec_fs_cmd["aifftr01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aifftr01") spec_fs_cmd["aifirf01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aifirf01") spec_fs_cmd["aiifft01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh aiifft01") spec_fs_cmd["basefp01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh basefp01") spec_fs_cmd["bitmnp01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh bitmnp01") spec_fs_cmd["cacheb01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh cacheb01") spec_fs_cmd["canrdr01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh canrdr01") spec_fs_cmd["idctrn01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh idctrn01") spec_fs_cmd["iirflt01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh iirflt01") spec_fs_cmd["matrix01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh matrix01") spec_fs_cmd["pntrch01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh pntrch01") spec_fs_cmd["puwmod01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh puwmod01") spec_fs_cmd["rspeed01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh rspeed01") spec_fs_cmd["tblook01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh tblook01") spec_fs_cmd["ttsprk01-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/eem.sh ttsprk01") spec_fs_cmd["nmpc-3RT"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth write;/root/nmpc.sh 1000") #2RT #spec_fs_cmd["a2time01-2RT"] = fsBench("/root/crM.sh a2time01 bandwidth bandwidth;/root/eem.sh a2time01") #spec_fs_cmd["aifftr01-2RT"] = fsBench("/root/crM.sh aifftr01 bandwidth bandwidth;/root/eem.sh aifftr01") #spec_fs_cmd["aifirf01-2RT"] = fsBench("/root/crM.sh aifirf01 bandwidth bandwidth;/root/eem.sh aifirf01") #spec_fs_cmd["aiifft01-2RT"] = fsBench("/root/crM.sh aiifft01 bandwidth bandwidth;/root/eem.sh aiifft01") #spec_fs_cmd["basefp01-2RT"] = fsBench("/root/crM.sh basefp01 bandwidth bandwidth;/root/eem.sh basefp01") #spec_fs_cmd["bitmnp01-2RT"] = fsBench("/root/crM.sh bitmnp01 bandwidth bandwidth;/root/eem.sh bitmnp01") #spec_fs_cmd["cacheb01-2RT"] = fsBench("/root/crM.sh cacheb01 bandwidth bandwidth;/root/eem.sh cacheb01") #spec_fs_cmd["canrdr01-2RT"] = fsBench("/root/crM.sh canrdr01 bandwidth bandwidth;/root/eem.sh canrdr01") #spec_fs_cmd["idctrn01-2RT"] = fsBench("/root/crM.sh idctrn01 bandwidth bandwidth;/root/eem.sh idctrn01") #spec_fs_cmd["iirflt01-2RT"] = fsBench("/root/crM.sh iirflt01 bandwidth bandwidth;/root/eem.sh iirflt01") #spec_fs_cmd["matrix01-2RT"] = fsBench("/root/crM.sh matrix01 bandwidth bandwidth;/root/eem.sh matrix01") #spec_fs_cmd["pntrch01-2RT"] = fsBench("/root/crM.sh pntrch01 bandwidth bandwidth;/root/eem.sh pntrch01") #spec_fs_cmd["puwmod01-2RT"] = fsBench("/root/crM.sh puwmod01 bandwidth bandwidth;/root/eem.sh puwmod01") #spec_fs_cmd["rspeed01-2RT"] = fsBench("/root/crM.sh rspeed01 bandwidth bandwidth;/root/eem.sh rspeed01") #spec_fs_cmd["tblook01-2RT"] = fsBench("/root/crM.sh tblook01 bandwidth bandwidth;/root/eem.sh tblook01") #spec_fs_cmd["ttsprk01-2RT"] = fsBench("/root/crM.sh ttsprk01 bandwidth bandwidth;/root/eem.sh ttsprk01") #spec_fs_cmd["nmpc-2RT"] = fsBench("/root/crM.sh nmpc bandwidth bandwidth;/root/nmpc.sh 1000") #3RT #spec_fs_cmd["a2time01-3RT"] = fsBench("/root/crM.sh a2time01 a2time01 bandwidth;/root/eem.sh a2time01") #spec_fs_cmd["aifftr01-3RT"] = fsBench("/root/crM.sh aifftr01 aifftr01 bandwidth;/root/eem.sh aifftr01") #spec_fs_cmd["aifirf01-3RT"] = fsBench("/root/crM.sh aifirf01 aifirf01 bandwidth;/root/eem.sh aifirf01") #spec_fs_cmd["aiifft01-3RT"] = fsBench("/root/crM.sh aiifft01 aiifft01 bandwidth;/root/eem.sh aiifft01") #spec_fs_cmd["basefp01-3RT"] = fsBench("/root/crM.sh basefp01 basefp01 bandwidth;/root/eem.sh basefp01") #spec_fs_cmd["bitmnp01-3RT"] = fsBench("/root/crM.sh bitmnp01 bitmnp01 bandwidth;/root/eem.sh bitmnp01") #spec_fs_cmd["cacheb01-3RT"] = fsBench("/root/crM.sh cacheb01 cacheb01 bandwidth;/root/eem.sh cacheb01") #spec_fs_cmd["canrdr01-3RT"] = fsBench("/root/crM.sh canrdr01 canrdr01 bandwidth;/root/eem.sh canrdr01") #spec_fs_cmd["idctrn01-3RT"] = fsBench("/root/crM.sh idctrn01 idctrn01 bandwidth;/root/eem.sh idctrn01") #spec_fs_cmd["iirflt01-3RT"] = fsBench("/root/crM.sh iirflt01 iirflt01 bandwidth;/root/eem.sh iirflt01") #spec_fs_cmd["matrix01-3RT"] = fsBench("/root/crM.sh matrix01 matrix01 bandwidth;/root/eem.sh matrix01") #spec_fs_cmd["pntrch01-3RT"] = fsBench("/root/crM.sh pntrch01 pntrch01 bandwidth;/root/eem.sh pntrch01") #spec_fs_cmd["puwmod01-3RT"] = fsBench("/root/crM.sh puwmod01 puwmod01 bandwidth;/root/eem.sh puwmod01") #spec_fs_cmd["rspeed01-3RT"] = fsBench("/root/crM.sh rspeed01 rspeed01 bandwidth;/root/eem.sh rspeed01") #spec_fs_cmd["tblook01-3RT"] = fsBench("/root/crM.sh tblook01 tblook01 bandwidth;/root/eem.sh tblook01") #spec_fs_cmd["ttsprk01-3RT"] = fsBench("/root/crM.sh ttsprk01 ttsprk01 bandwidth;/root/eem.sh ttsprk01") #spec_fs_cmd["nmpc-3RT"] = fsBench("/root/crM.sh nmpc nmpc bandwidth;/root/nmpc.sh 1000") #spec_fs_cmd["aifirf01"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth;/root/eem.sh aifirf01") #spec_fs_cmd["aifftr01"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth;/root/eem.sh aifftr01") #spec_fs_cmd["aiifft01"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth;/root/eem.sh aiifft01.exe") #spec_fs_cmd["cacheb01"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth;/root/eem.sh cacheb01") #spec_fs_cmd["matrix01"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth;/root/eem.sh matrix01") #spec_fs_cmd["pntrch01"] = fsBench("/root/crM.sh bandwidth bandwidth bandwidth;/root/eem.sh pntrch01") # # Benchmarks to test pyterm -- These program output test at the beginning # # test1 -- hmmer spec_fs_cmd["test1"] = fsBench("/cpu2006/bin/spec.hmmer_base.x86-gcc --fixed 0 --mean 500 --num 500000 --sd 350 --seed 0 /cpu2006/456.hmmer/data/ref/input/retro.hmm") # test2 -- gobmk spec_fs_cmd["test2"] = fsBench("/cpu2006/bin/spec.gobmk_base.x86-gcc --mode gtp < /cpu2006/445.gobmk/data/ref/input/nngs.tst") # test3 -- mcf spec_fs_cmd["test3"] = fsBench("/cpu2006/bin/spec.mcf_base.x86-gcc /cpu2006/429.mcf/data/ref/input/inp.in") # test4 -- libquantum spec_fs_cmd["test4"] = fsBench("/cpu2006/bin/spec.libquantum_base.x86-gcc 1397 8") # Set the benchmark's working directory #spec_fs_cmd["bwaves"].setCwd("/cpu2006/410.bwaves/data/ref/input") #spec_fs_cmd["gamess"].setCwd("/cpu2006/416.gamess/data/ref/input") #spec_fs_cmd["zeusmp"].setCwd("/cpu2006/434.zeusmp/data/ref/input") #spec_fs_cmd["gobmk"].setCwd("/cpu2006/445.gobmk/data/all/input") #spec_fs_cmd["povray"].setCwd("/cpu2006/453.povray/data/all/input") #spec_fs_cmd["GemsFDTD"].setCwd("/cpu2006/459.GemsFDTD/data/ref/input") #spec_fs_cmd["h264ref"].setCwd("/cpu2006/464.h264ref/data/all/input") #spec_fs_cmd["tonto"].setCwd("/cpu2006/465.tonto/data/ref/input") #spec_fs_cmd["omnetpp"].setCwd("/cpu2006/471.omnetpp/data/ref/input") #spec_fs_cmd["astar"].setCwd("/cpu2006/473.astar/data/ref/input") #spec_fs_cmd["wrf"].setCwd("/cpu2006/481.wrf/data/all/input") #spec_fs_cmd["sphinx"].setCwd("/cpu2006/482.sphinx3/data/all/input") spec_fs_cmd["test2"].setCwd("/cpu2006/445.gobmk/data/all/input") # Set simpoint start #spec_fs_cmd["astar"].setSimpoint(400000000) spec_fs_cmd["astar"].setSimpoint(10000) spec_fs_cmd["bwaves"].setSimpoint(7800000000) spec_fs_cmd["GemsFDTD"].setSimpoint(6100000000) spec_fs_cmd["gobmk"].setSimpoint(20000) spec_fs_cmd["lbm"].setSimpoint(3000000000) spec_fs_cmd["lbm1"].setSimpoint(3000000000) spec_fs_cmd["lbm2"].setSimpoint(3000000000) spec_fs_cmd["lbm3"].setSimpoint(3000000000) spec_fs_cmd["omnetpp1"].setSimpoint(9000000000) spec_fs_cmd["omnetpp2"].setSimpoint(9000000000) spec_fs_cmd["omnetpp3"].setSimpoint(9000000000) spec_fs_cmd["leslie3d"].setSimpoint(61200000000) #spec_fs_cmd["libquantum"].setSimpoint(29100000000) spec_fs_cmd["libquantum"].setSimpoint(9400000000) spec_fs_cmd["libquantum1"].setSimpoint(9400000000) spec_fs_cmd["libquantum2"].setSimpoint(9400000000) spec_fs_cmd["libquantum3"].setSimpoint(9400000000) spec_fs_cmd["libquantum4"].setSimpoint(9400000000) spec_fs_cmd["disparity"].setSimpoint(90000000000) spec_fs_cmd["liblinear"].setSimpoint(1900000000) spec_fs_cmd["soplex"].setSimpoint(1800000000) spec_fs_cmd["mcf"].setSimpoint(3400000000) spec_fs_cmd["mcf1"].setSimpoint(3400000000) spec_fs_cmd["mcf2"].setSimpoint(3400000000) spec_fs_cmd["mcf3"].setSimpoint(3400000000) spec_fs_cmd["mcf4"].setSimpoint(3400000000) spec_fs_cmd["milc"].setSimpoint(7800000000) spec_fs_cmd["zeusmp"].setSimpoint(24100000000) # Low memory usage benchmarks #spec_fs_cmd["bzip2"].setSimpoint(4000000000) spec_fs_cmd["bzip2"].setSimpoint(2800000000) spec_fs_cmd["bwrite"].setSimpoint(100000000) spec_fs_cmd["bandwidth1"].setSimpoint(100000) spec_fs_cmd["bandwidth2"].setSimpoint(100000) spec_fs_cmd["bandwidth3"].setSimpoint(100000) spec_fs_cmd["bandwidth4"].setSimpoint(10000) spec_fs_cmd["hrt1"].setSimpoint(0) spec_fs_cmd["hrt2"].setSimpoint(1000) spec_fs_cmd["hrt3"].setSimpoint(1000) spec_fs_cmd["hrt4"].setSimpoint(1000) spec_fs_cmd["latency"].setSimpoint(0) spec_fs_cmd["cactusADM"].setSimpoint(200000000) spec_fs_cmd["gamess"].setSimpoint(200000000) spec_fs_cmd["gcc"].setSimpoint(600000000) spec_fs_cmd["gromacs"].setSimpoint(3000000000) spec_fs_cmd["dealII"].setSimpoint(1100000000) #spec_fs_cmd["wrf"].setSimpoint(3000000000) spec_fs_cmd["wrf"].setSimpoint(100000000) spec_fs_cmd["h264ref"].setSimpoint(5400000000) spec_fs_cmd["hmmer"].setSimpoint(300000000) spec_fs_cmd["namd"].setSimpoint(800000000) spec_fs_cmd["omnetpp"].setSimpoint(9000000000) #spec_fs_cmd["povray"].setSimpoint(4000000000) spec_fs_cmd["povray"].setSimpoint(100000000) spec_fs_cmd["sjeng"].setSimpoint(1400000000) spec_fs_cmd["sphinx"].setSimpoint(20000) spec_fs_cmd["tonto"].setSimpoint(600000000) # Tests -- start in a short time for testing spec_fs_cmd["test1"].setSimpoint(30000000) spec_fs_cmd["test2"].setSimpoint(20000000) spec_fs_cmd["test3"].setSimpoint(10000000) spec_fs_cmd["test4"].setSimpoint(40000000) #FF spec_fs_cmd["mcf-my"].setSimpoint(3400000000) spec_fs_cmd["lbm-my"].setSimpoint(3000000000) spec_fs_cmd["bw683"].setSimpoint(3000000000) def getSPECFSBench(bench): if not bench in spec_fs_cmd: print "Benchmark %s not found!" % bench sys.exit(1) spec_fs_cmd[bench].setName(bench) return spec_fs_cmd[bench] def getSPECCmd(bench, cpu): #return "cd %s; taskset -c %d %s &\n" % (bench.cwd, cpu, bench.cmd) #return "cd %s; ./set_wp_mode 2; taskset -c %d %s &\n" % (bench.cwd, cpu, bench.cmd) #return "cd %s; %s &\n" % (bench.cwd, bench.cmd) return "cd %s; %s \n" % ("/root", spec_fs_cmd[bench].cmd)

195.269471

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0.974287

0.959992

0.952162

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0.924029

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0.136445

343,479

1,758

713

195.380546

0.675233

0.021355

0

0.762922

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null

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1

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null

0

1

0

10

b54cea52e6d5fcfe2182cb17b3edd869e0200af7

18,303

py

Python

src/hapPyTango/CosNotifyComm_skel/__init__.py

mguijarr/hapPyTango

2506c8e83d93fbd2c0a0115983489d59c74caa2f

[ "MIT" ]

1

2020-10-28T16:57:36.000Z

src/hapPyTango/CosNotifyComm_skel/__init__.py

mguijarr/hapPyTango

2506c8e83d93fbd2c0a0115983489d59c74caa2f

[ "MIT" ]

null

src/hapPyTango/CosNotifyComm_skel/__init__.py

mguijarr/hapPyTango

2506c8e83d93fbd2c0a0115983489d59c74caa2f

[ "MIT" ]

null

""" Module: IDL:omg.org/CosNotifyComm:1.0 Automagically generated by:- The ORB called Fnorb v1.1.Return.of.Fnorb """ _FNORB_ID = "IDL:omg.org/CosNotifyComm:1.0" # Fnorb modules. import Fnorb.orb.CORBA import Fnorb.orb.TypeManager import Fnorb.orb.Util class NotifyPublish_skel(Fnorb.orb.CORBA.Object_skel): """ Interface: IDL:omg.org/CosNotifyComm/NotifyPublish:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/NotifyPublish:1.0" def _skel_offer_change(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/NotifyPublish/offer_change:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] inputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/EventTypeSeq:1.0")) inputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/EventTypeSeq:1.0")) # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotifyComm/InvalidEventType:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # Unmarshal the arguments to the request. arguments = server_request.arguments() # Invoke the implementation. results = apply(self.offer_change, arguments) # Create the reply. server_request.results(results) return class NotifySubscribe_skel(Fnorb.orb.CORBA.Object_skel): """ Interface: IDL:omg.org/CosNotifyComm/NotifySubscribe:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/NotifySubscribe:1.0" def _skel_subscription_change(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/NotifySubscribe/subscription_change:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] inputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/EventTypeSeq:1.0")) inputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/EventTypeSeq:1.0")) # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotifyComm/InvalidEventType:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # Unmarshal the arguments to the request. arguments = server_request.arguments() # Invoke the implementation. results = apply(self.subscription_change, arguments) # Create the reply. server_request.results(results) return # Import base interface packages. import CosEventComm_skel class PushConsumer_skel(Fnorb.orb.CORBA.Object_skel, NotifyPublish_skel, CosEventComm_skel.PushConsumer_skel): """ Interface: IDL:omg.org/CosNotifyComm/PushConsumer:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/PushConsumer:1.0" pass # Import base interface packages. import CosEventComm_skel class PullConsumer_skel(Fnorb.orb.CORBA.Object_skel, NotifyPublish_skel, CosEventComm_skel.PullConsumer_skel): """ Interface: IDL:omg.org/CosNotifyComm/PullConsumer:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/PullConsumer:1.0" pass # Import base interface packages. import CosEventComm_skel class PullSupplier_skel(Fnorb.orb.CORBA.Object_skel, NotifySubscribe_skel, CosEventComm_skel.PullSupplier_skel): """ Interface: IDL:omg.org/CosNotifyComm/PullSupplier:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/PullSupplier:1.0" pass # Import base interface packages. import CosEventComm_skel class PushSupplier_skel(Fnorb.orb.CORBA.Object_skel, NotifySubscribe_skel, CosEventComm_skel.PushSupplier_skel): """ Interface: IDL:omg.org/CosNotifyComm/PushSupplier:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/PushSupplier:1.0" pass class StructuredPushConsumer_skel(Fnorb.orb.CORBA.Object_skel, NotifyPublish_skel): """ Interface: IDL:omg.org/CosNotifyComm/StructuredPushConsumer:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/StructuredPushConsumer:1.0" def _skel_push_structured_event(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/StructuredPushConsumer/push_structured_event:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] inputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/StructuredEvent:1.0")) # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosEventComm/Disconnected:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # Unmarshal the arguments to the request. arguments = server_request.arguments() # Invoke the implementation. results = apply(self.push_structured_event, arguments) # Create the reply. server_request.results(results) return def _skel_disconnect_structured_push_consumer(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/StructuredPushConsumer/disconnect_structured_push_consumer:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_structured_push_consumer, arguments) # Create the reply. server_request.results(results) return class StructuredPullConsumer_skel(Fnorb.orb.CORBA.Object_skel, NotifyPublish_skel): """ Interface: IDL:omg.org/CosNotifyComm/StructuredPullConsumer:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/StructuredPullConsumer:1.0" def _skel_disconnect_structured_pull_consumer(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/StructuredPullConsumer/disconnect_structured_pull_consumer:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_structured_pull_consumer, arguments) # Create the reply. server_request.results(results) return class StructuredPullSupplier_skel(Fnorb.orb.CORBA.Object_skel, NotifySubscribe_skel): """ Interface: IDL:omg.org/CosNotifyComm/StructuredPullSupplier:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/StructuredPullSupplier:1.0" def _skel_pull_structured_event(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/StructuredPullSupplier/pull_structured_event:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] outputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/StructuredEvent:1.0")) # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosEventComm/Disconnected:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.pull_structured_event, arguments) # Create the reply. server_request.results(results) return def _skel_try_pull_structured_event(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/StructuredPullSupplier/try_pull_structured_event:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] outputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/StructuredEvent:1.0")) outputs.append(Fnorb.orb.CORBA.TC_boolean) # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosEventComm/Disconnected:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.try_pull_structured_event, arguments) # Create the reply. server_request.results(results) return def _skel_disconnect_structured_pull_supplier(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/StructuredPullSupplier/disconnect_structured_pull_supplier:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_structured_pull_supplier, arguments) # Create the reply. server_request.results(results) return class StructuredPushSupplier_skel(Fnorb.orb.CORBA.Object_skel, NotifySubscribe_skel): """ Interface: IDL:omg.org/CosNotifyComm/StructuredPushSupplier:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/StructuredPushSupplier:1.0" def _skel_disconnect_structured_push_supplier(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/StructuredPushSupplier/disconnect_structured_push_supplier:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_structured_push_supplier, arguments) # Create the reply. server_request.results(results) return class SequencePushConsumer_skel(Fnorb.orb.CORBA.Object_skel, NotifyPublish_skel): """ Interface: IDL:omg.org/CosNotifyComm/SequencePushConsumer:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/SequencePushConsumer:1.0" def _skel_push_structured_events(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/SequencePushConsumer/push_structured_events:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] inputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/EventBatch:1.0")) # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosEventComm/Disconnected:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # Unmarshal the arguments to the request. arguments = server_request.arguments() # Invoke the implementation. results = apply(self.push_structured_events, arguments) # Create the reply. server_request.results(results) return def _skel_disconnect_sequence_push_consumer(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/SequencePushConsumer/disconnect_sequence_push_consumer:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_sequence_push_consumer, arguments) # Create the reply. server_request.results(results) return class SequencePullConsumer_skel(Fnorb.orb.CORBA.Object_skel, NotifyPublish_skel): """ Interface: IDL:omg.org/CosNotifyComm/SequencePullConsumer:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/SequencePullConsumer:1.0" def _skel_disconnect_sequence_pull_consumer(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/SequencePullConsumer/disconnect_sequence_pull_consumer:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_sequence_pull_consumer, arguments) # Create the reply. server_request.results(results) return class SequencePullSupplier_skel(Fnorb.orb.CORBA.Object_skel, NotifySubscribe_skel): """ Interface: IDL:omg.org/CosNotifyComm/SequencePullSupplier:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/SequencePullSupplier:1.0" def _skel_pull_structured_events(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/SequencePullSupplier/pull_structured_events:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] inputs.append(Fnorb.orb.CORBA.TC_long) # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] outputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/EventBatch:1.0")) # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosEventComm/Disconnected:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # Unmarshal the arguments to the request. arguments = server_request.arguments() # Invoke the implementation. results = apply(self.pull_structured_events, arguments) # Create the reply. server_request.results(results) return def _skel_try_pull_structured_events(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/SequencePullSupplier/try_pull_structured_events:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] inputs.append(Fnorb.orb.CORBA.TC_long) # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] outputs.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosNotification/EventBatch:1.0")) outputs.append(Fnorb.orb.CORBA.TC_boolean) # Typecodes for user exceptions. exceptions = [] exceptions.append(Fnorb.orb.CORBA.typecode("IDL:omg.org/CosEventComm/Disconnected:1.0")) # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # Unmarshal the arguments to the request. arguments = server_request.arguments() # Invoke the implementation. results = apply(self.try_pull_structured_events, arguments) # Create the reply. server_request.results(results) return def _skel_disconnect_sequence_pull_supplier(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/SequencePullSupplier/disconnect_sequence_pull_supplier:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_sequence_pull_supplier, arguments) # Create the reply. server_request.results(results) return class SequencePushSupplier_skel(Fnorb.orb.CORBA.Object_skel, NotifySubscribe_skel): """ Interface: IDL:omg.org/CosNotifyComm/SequencePushSupplier:1.0 """ _FNORB_ID = "IDL:omg.org/CosNotifyComm/SequencePushSupplier:1.0" def _skel_disconnect_sequence_push_supplier(self, server_request): """ Operation: IDL:omg.org/CosNotifyComm/SequencePushSupplier/disconnect_sequence_push_supplier:1.0 """ # Typecodes for 'in' and 'inout' parameters. inputs = [] # Typecodes for the result, 'inout' and 'out' parameters. outputs = [] # Typecodes for user exceptions. exceptions = [] # Initialise the server request object. server_request.initialise(inputs, outputs, exceptions) # This operation has no arguments. arguments = () # Invoke the implementation. results = apply(self.disconnect_sequence_push_supplier, arguments) # Create the reply. server_request.results(results) return #############################################################################

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null

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null

0

7

a5c90bb0690c6dd80c0996d5ede23e8dc406c6d0

988

py

Python

biobb_analysis/test/unitests/test_ambertools/test_cpptraj_rgyr_container.py

bioexcel/biobb_analysis

794683daf65eb13ddaaaf6cf3c19da6d1322a949

[ "Apache-2.0" ]

3

2019-05-18T14:52:30.000Z

2020-10-18T06:20:00.000Z

biobb_analysis/test/unitests/test_ambertools/test_cpptraj_rgyr_container.py

bioexcel/biobb_analysis

794683daf65eb13ddaaaf6cf3c19da6d1322a949

[ "Apache-2.0" ]

7

2019-03-04T15:04:28.000Z

2021-06-17T10:57:25.000Z

biobb_analysis/test/unitests/test_ambertools/test_cpptraj_rgyr_container.py

bioexcel/biobb_analysis

794683daf65eb13ddaaaf6cf3c19da6d1322a949

[ "Apache-2.0" ]

null

from biobb_common.tools import test_fixtures as fx from biobb_analysis.ambertools.cpptraj_rgyr import cpptraj_rgyr class TestCpptrajRgyrDocker(): def setUp(self): fx.test_setup(self,'cpptraj_rgyr_docker') def tearDown(self): fx.test_teardown(self) pass def test_rgyr_docker(self): cpptraj_rgyr(properties=self.properties, **self.paths) assert fx.not_empty(self.paths['output_cpptraj_path']) assert fx.equal(self.paths['output_cpptraj_path'], self.paths['ref_output_cpptraj_path']) class TestCpptrajRgyrSingularity(): def setUp(self): fx.test_setup(self,'cpptraj_rgyr_singularity') def tearDown(self): fx.test_teardown(self) pass def test_rgyr_singularity(self): cpptraj_rgyr(properties=self.properties, **self.paths) assert fx.not_empty(self.paths['output_cpptraj_path']) assert fx.equal(self.paths['output_cpptraj_path'], self.paths['ref_output_cpptraj_path'])

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988

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0.130178

0.721893

0.609467

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0.174089

988

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98

34.068966

0.828431

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0.636364

0

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0.272727

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0.090909

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null

0

1

0

null

0

1

0

1

0

7

93a6235162b5004a5144d43f4707c3c76aebbf3c

43

py

Python

charq/__main__.py

EmidioLP/CharQ

7fb857c4481458ce5d09741d78bf0513d44af130

[ "MIT" ]

null

charq/__main__.py

EmidioLP/CharQ

7fb857c4481458ce5d09741d78bf0513d44af130

[ "MIT" ]

1

2021-03-16T19:11:36.000Z

2021-03-16T19:12:18.000Z

charq/__main__.py

EmidioLP/CharQ

7fb857c4481458ce5d09741d78bf0513d44af130

[ "MIT" ]

2

2021-03-16T19:03:43.000Z

2021-03-16T20:10:11.000Z

from charq import CharAscii, WordGenerate

14.333333

41

0.837209

5

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2

42

21.5

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0

1

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1

0

1

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null

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1

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1

0

null

0

1

0

1

0

1

0

7

93eb2298a89b79cf6afb9b78aa015b0edbdefdd3

2,526

py

Python

tests/test_network.py

vQuadX/pytest_network

a16a7b2f4a2ccd4365abf6c6797aa3d6572af2e7

[ "MIT" ]

9

2020-01-23T13:30:20.000Z

2021-09-03T11:14:22.000Z

tests/test_network.py

vQuadX/pytest_network

a16a7b2f4a2ccd4365abf6c6797aa3d6572af2e7

[ "MIT" ]

8

2020-05-07T05:35:06.000Z

2020-10-01T10:26:27.000Z

tests/test_network.py

vQuadX/pytest_network

a16a7b2f4a2ccd4365abf6c6797aa3d6572af2e7

[ "MIT" ]

3

2020-05-11T12:41:32.000Z

2021-01-12T09:06:32.000Z

import pytest from pytest_network import patched_connect, NetworkUsageException def test_disable_network_fixture_raiese_exception(testdir): testdir.makepyfile( """ import urllib.request import pytest def test_hello_default(disable_network): with pytest.raises(Exception): urllib.request.urlopen('http://httpbin.org/robots.txt') """ ) result = testdir.runpytest('--verbose') assert result.parseoutcomes() == {'passed': 1} @pytest.mark.usefixtures('disable_network_addopt') def test_disable_network_addopt_raises_exception(testdir): testdir.makepyfile( """ import urllib.request import pytest def test_hello_default(): with pytest.raises(Exception): urllib.request.urlopen('http://httpbin.org/robots.txt') """ ) result = testdir.runpytest('--verbose') assert result.parseoutcomes() == {'passed': 1} @pytest.mark.usefixtures('disable_network_addopt') def test_enable_network_fixture_enables_connect(testdir): testdir.makepyfile( """ import urllib.request import pytest def test_hello_default(enable_network): response = urllib.request.urlopen('http://httpbin.org/robots.txt') assert response.status == 200 """ ) result = testdir.runpytest('--verbose') assert result.parseoutcomes() == {'passed': 1} def test_disable_pytest_mark_workds(testdir): testdir.makepyfile( """ import urllib.request import pytest @pytest.mark.disable_network def test_hello_default(): with pytest.raises(Exception): urllib.request.urlopen('http://httpbin.org/robots.txt') """ ) result = testdir.runpytest('--verbose') assert result.parseoutcomes() == {'passed': 1} @pytest.mark.usefixtures('disable_network_addopt') def test_enable_pytest_mark_workds(testdir): testdir.makepyfile( """ import urllib.request import pytest @pytest.mark.enable_network def test_hello_default(): response = urllib.request.urlopen('http://httpbin.org/robots.txt') assert response.status == 200 """ ) result = testdir.runpytest('--verbose') assert result.parseoutcomes() == {'passed': 1} def test_patched_connect_always_raises_error(): with pytest.raises(NetworkUsageException): patched_connect()

22.756757

78

0.640934

252

2,526

6.222222

0.178571

0.049107

0.076531

0.095663

0.816964

0.795918

0

0.005771

0.245447

2,526

110

79

22.963636

0.816894

0

0.545455

0

0.107306

0.050228

0

0.151515

1

0.181818

false

0.151515

0.060606

0

0.242424

0

null

0

1

0

null

0

1

0

7

f50e9693f3bd423bb374bf0432c032f694cbb476

84

py

Python

examples/rotate_four.py

igfish/toyvm

bb1ab371a8c71ba01522556235fc9f017c9b6b8f

[ "MIT" ]

null

examples/rotate_four.py

igfish/toyvm

bb1ab371a8c71ba01522556235fc9f017c9b6b8f

[ "MIT" ]

null

examples/rotate_four.py

igfish/toyvm

bb1ab371a8c71ba01522556235fc9f017c9b6b8f

[ "MIT" ]

null

a, b, c, d = 1, 2, 3, 4 print(a, b, c, d) a, b, c, d = d, c, b, a print(a, b, c, d)

16.8

23

0.404762

26

84

1.307692

0.346154

0.235294

0.352941

0.470588

0.529412

0

0.068966

0.309524

84

4

24

21

0.517241

0

0.5

0

1

0

true

0

0.5

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1

null

1

0

1

0

null

0

1

0

1

0

8

f5860e9bafdaad426155b3f5615b64d9c7c2b4b4

157

py

Python

touchtechnology/common/backends/__init__.py

goodtune/vitriolic

d135eecf7acbc229a872585ebafb8bbefca52df4

[ "BSD-3-Clause" ]

null

touchtechnology/common/backends/__init__.py

goodtune/vitriolic

d135eecf7acbc229a872585ebafb8bbefca52df4

[ "BSD-3-Clause" ]

28

2016-12-09T21:14:19.000Z

2022-01-11T07:17:16.000Z

touchtechnology/common/backends/__init__.py

goodtune/vitriolic

d135eecf7acbc229a872585ebafb8bbefca52df4

[ "BSD-3-Clause" ]

null

""" Should specifically use: touchtechnology.common.backends.auth.UserSubclassBackend touchtechnology.common.backends.auth.EmailUserSubclassBackend """

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1

0

null

0

1

0

7

1956d52f2729b7ab1455e84d8c62841ccd7bb9c5

16,220

py

Python

VSC/model.py

Ali-Sahili/Background-Subtraction-Unsupervised-Learning

445b2cf8736a4a28cff2b074a32afe8fe6986d53

[ "MIT" ]

5

2021-05-17T06:52:28.000Z

2022-02-20T15:35:51.000Z

VSC/model.py

WN1695173791/Background-Subtraction-Unsupervised-Learning

445b2cf8736a4a28cff2b074a32afe8fe6986d53

[ "MIT" ]

null

VSC/model.py

WN1695173791/Background-Subtraction-Unsupervised-Learning

445b2cf8736a4a28cff2b074a32afe8fe6986d53

[ "MIT" ]

1

2021-05-17T06:52:33.000Z

import torch from torch import nn from torch.autograd import Variable import torch.nn.functional as F from Param import * class VSC512(nn.Module): def __init__(self,nz=nz,ngf=8,nef=8,nc=3): super(VSC512, self).__init__() self.nz=nz self.nc=nc self.encode = nn.Sequential( # input is (nc) x 512 x 512 nn.Conv2d(nc, nef, 4, 2, 1, bias=False), nn.BatchNorm2d(nef), nn.LeakyReLU(0.2, inplace=True), # state size is (nef) x 256 x 256 nn.Conv2d(nef, nef * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 2), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*2) x 128 x 128 nn.Conv2d(nef*2, nef * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 4), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*4) x 64 x 64 nn.Conv2d(nef * 4, nef * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 8), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*8) x 32 x 32 nn.Conv2d(nef*8, nef * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 16), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*16) x 16 x 16 nn.Conv2d(nef * 16, nef * 32, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 32), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*32) x 8 x 8 nn.Conv2d(nef * 32, nef * 64, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 64), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*64) x 4 x 4 nn.Conv2d(nef * 64, nef * 128, 4, 1, 0, bias=False), nn.BatchNorm2d(nef * 128), nn.LeakyReLU(0.2, inplace=True), nn.Conv2d(nef * 128, nz, 1, 1, 0, bias=True), nn.Sigmoid() ) self.decode = nn.Sequential( nn.ConvTranspose2d(nz, ngf *128 , 2, 1, 0, bias=False), nn.BatchNorm2d(ngf * 128), nn.ReLU(True), # size ngf*128 x2 x2 nn.ConvTranspose2d(ngf * 128, ngf * 64, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 64), nn.ReLU(True), # size ngf*64 x4 x4 nn.ConvTranspose2d(ngf * 64, ngf * 32, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 32), nn.ReLU(True), # size ngf*32 x8 x8 nn.ConvTranspose2d(ngf*32, ngf * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 16), nn.ReLU(True), # state size. (ngf*16) x 16 x16 nn.ConvTranspose2d(ngf * 16, ngf * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 8), nn.ReLU(True), # state size. (ngf*8) x 32 x 32 nn.ConvTranspose2d(ngf * 8, ngf * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 4), nn.ReLU(True), # state size. (ngf*4) x 64 x 64 nn.ConvTranspose2d(ngf * 4, ngf * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 2), nn.ReLU(True), # state size. (ngf*2) x 128 x 128 nn.ConvTranspose2d(ngf * 2, ngf, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf), nn.ReLU(True), # state size. (ngf) x 256 x 256 nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False), nn.Tanh() #nn.Sigmoid() # for VAE ) self.fc1 = nn.Linear(nz, 64) self.fc2 = nn.Linear(nz, 64) self.fc_logspike = nn.linear(nz, 64) self.fc3 = nn.Linear(64, nz) self.c = 50.0 def reparameterize(self, mu, logvar, logspike): std = torch.exp(0.5*logvar) eps = torch.randn_like(std) gaussian = eps.mul(std).add_(mu) eta = torch.rand_like(std) selection = nn.Sigmoid()(self.c*(eta + logspike.exp() - 1)) return selection.mul(gaussian) def forward(self, input): b_size = input.shape[0] x = self.encode(input).view(b_size, nz) mu = self.fc1(x) #fc1 logvar = self.fc2(x) #fc2 logspike = -F.relu(-self.fc_logspike(x)) z = self.reparameterize(mu, logvar, logspike) z = self.fc3(z).reshape(-1, self.nz, 1, 1) #fc3 #del x return self.decode(z), mu, logvar, logspike class VSC256(nn.Module): def __init__(self,nz=nz,ngf=16,nef=16,nc=3): super(VSC256, self).__init__() self.nz=nz self.nc=nc self.encode = nn.Sequential( # input is (nc) x 258 x 256 nn.Conv2d(nc, nef, 4, 2, 1, bias=False), nn.BatchNorm2d(nef), nn.LeakyReLU(0.2, inplace=True), # state size. (nef) x 128 x 128 nn.Conv2d(nef, nef * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 2), nn.LeakyReLU(0.2, inplace=True), # state size. (nef) x 64 x 64 nn.Conv2d(nef * 2, nef * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 4), nn.LeakyReLU(0.2, inplace=True), # state size. (nef) x 32 x 32 nn.Conv2d(nef*4, nef * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 8), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*2) x 16 x 16 nn.Conv2d(nef * 8, nef * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 16), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*4) x 8 x 8 nn.Conv2d(nef * 16, nef * 32, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 32), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*8) x 4 x 4 nn.Conv2d(nef * 32, nef * 64, 4, 1, 0, bias=False), nn.BatchNorm2d(nef * 64), nn.LeakyReLU(0.2, inplace=True), nn.Conv2d(nef * 64, nz, 1, 1, 0, bias=True), nn.Sigmoid() ) self.decode = nn.Sequential( nn.ConvTranspose2d(nz, ngf *64 , 2, 1, 0, bias=False), nn.BatchNorm2d(ngf * 64), nn.ReLU(True), # size ngf*64 x2 x2 nn.ConvTranspose2d(ngf * 64, ngf * 32, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 32), nn.ReLU(True), # size ngf*32 x4 x4 nn.ConvTranspose2d(ngf*32, ngf * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 16), nn.ReLU(True), # state size. (ngf*8) x 8 x 8 nn.ConvTranspose2d(ngf * 16, ngf * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 8), nn.ReLU(True), # state size. (ngf*4) x 16 x16 nn.ConvTranspose2d(ngf * 8, ngf * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 4), nn.ReLU(True), # state size. (ngf*2) x 32 x 32 nn.ConvTranspose2d(ngf * 4, ngf * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 2), nn.ReLU(True), # state size. (ngf) x 64 x 64 nn.ConvTranspose2d(ngf * 2, ngf, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf), nn.ReLU(True), # state size. (nc) x 128 x 128 nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False), nn.Tanh() #nn.Sigmoid() # for VAE # state size. (nc) x 256 x 256 ) self.fc1 = nn.Linear(nz, 64) self.fc2 = nn.Linear(nz, 64) self.fc_logspike = nn.Linear(nz, 64) self.fc3 = nn.Linear(64, nz) self.c = 50.0 def reparameterize(self, mu, logvar, logspike): std = torch.exp(0.5*logvar) eps = torch.randn_like(std) gaussian = eps.mul(std).add_(mu) eta = torch.rand_like(std) selection = nn.Sigmoid()(self.c*(eta + logspike.exp() - 1)) return selection.mul(gaussian) def forward(self, input): b_size = input.shape[0] x = self.encode(input).view(b_size, nz) mu = self.fc1(x) #fc1 logvar = self.fc2(x) #fc2 logspike = -F.relu(-self.fc_logspike(x)) z = self.reparameterize(mu, logvar, logspike) z = self.fc3(z).reshape(-1, self.nz, 1, 1) #fc3 #del x return self.decode(z), mu, logvar, logspike class VSC128(nn.Module): def __init__(self,nz=nz,ngf=32,nef=32,nc=3): super(VSC128, self).__init__() self.nz=nz self.nc=nc self.encode = nn.Sequential( # input is (nc) x 128 x 128 nn.Conv2d(nc, nef, 4, 2, 1, bias=False), nn.BatchNorm2d(nef), nn.LeakyReLU(0.2, inplace=True), # state size. (nef) x 64 x 64 nn.Conv2d(nef, nef * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 2), nn.LeakyReLU(0.2, inplace=True), # state size. (nef) x 32 x 32 nn.Conv2d(nef*2, nef * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 4), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*2) x 16 x 16 nn.Conv2d(nef * 4, nef * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 8), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*4) x 8 x 8 nn.Conv2d(nef * 8, nef * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 16), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*8) x 4 x 4 nn.Conv2d(nef * 16, nef * 32, 4, 1, 0, bias=False), nn.BatchNorm2d(nef * 32), nn.LeakyReLU(0.2, inplace=True), nn.Conv2d(nef * 32, nz, 1, 1, 0, bias=True), nn.Sigmoid() ) self.decode = nn.Sequential( nn.ConvTranspose2d(nz, ngf *32 , 2, 1, 0, bias=False), nn.BatchNorm2d(ngf * 32), nn.ReLU(True), # size ngf*32 x2 x2 nn.ConvTranspose2d(ngf*32, ngf * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 16), nn.ReLU(True), # size ngf*16 x4 x4 nn.ConvTranspose2d(ngf * 16, ngf * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 8), nn.ReLU(True), # state size. (ngf*8) x 8 x 8 nn.ConvTranspose2d(ngf * 8, ngf * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 4), nn.ReLU(True), # state size. (ngf*4) x 16 x16 nn.ConvTranspose2d(ngf * 4, ngf * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 2), nn.ReLU(True), # state size. (ngf*2) x 32 x 32 nn.ConvTranspose2d(ngf * 2, ngf, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf), nn.ReLU(True), # state size. (ngf) x 64 x 64 nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False), nn.Tanh() # for GAN #nn.Sigmoid() # for VAE # state size. (nc) x 128 x 128 ) self.fc1 = nn.Linear(nz, 64) self.fc2 = nn.Linear(nz, 64) self.fc_logspike = nn.linear(nz, 64) self.fc3 = nn.Linear(64, nz) self.c = 50.0 def reparameterize(self, mu, logvar, logspike): std = torch.exp(0.5*logvar) eps = torch.randn_like(std) gaussian = eps.mul(std).add_(mu) eta = torch.rand_like(std) selection = nn.Sigmoid()(self.c*(eta + logspike.exp() - 1)) return selection.mul(gaussian) def forward(self, input): b_size = input.shape[0] x = self.encode(input).view(b_size, nz) mu = self.fc1(x) #fc1 logvar = self.fc2(x) #fc2 logspike = -F.relu(-self.fc_logspike(x)) z = self.reparameterize(mu, logvar, logspike) z = self.fc3(z).reshape(-1, self.nz, 1, 1) #fc3 #del x return self.decode(z), mu, logvar, logspike class VSC_Encoder(nn.Module): def __init__(self,nz=nz,nef=8,nc=3): super(VSC_Encoder, self).__init__() self.nz=nz self.nc=nc self.main = nn.Sequential( # input is (nc) x 512 x 512 nn.Conv2d(nc, nef, 4, 2, 1, bias=False), nn.BatchNorm2d(nef), nn.LeakyReLU(0.2, inplace=True), # state size is (nef) x 256 x 256 nn.Conv2d(nef, nef * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 2), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*2) x 128 x 128 nn.Conv2d(nef*2, nef * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 4), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*4) x 64 x 64 nn.Conv2d(nef * 4, nef * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 8), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*8) x 32 x 32 nn.Conv2d(nef*8, nef * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 16), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*16) x 16 x 16 nn.Conv2d(nef * 16, nef * 32, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 32), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*32) x 8 x 8 nn.Conv2d(nef * 32, nef * 64, 4, 2, 1, bias=False), nn.BatchNorm2d(nef * 64), nn.LeakyReLU(0.2, inplace=True), # state size. (nef*64) x 4 x 4 nn.Conv2d(nef * 64, nef * 128, 4, 1, 0, bias=False), nn.BatchNorm2d(nef * 128), nn.LeakyReLU(0.2, inplace=True), nn.Conv2d(nef * 128, nz, 1, 1, 0, bias=True), nn.Sigmoid() ) self.fc1 = nn.Linear(nz, 1024) self.fc2 = nn.Linear(nz, 1024) self.fc_logspike = nn.Linear(nz, 1024) def forward(self, x): b_size = x.shape[0] x = self.main(x).view(b_size, nz) mu = self.fc1(x) logvar = self.fc2(x) logspike = -F.relu(-self.fc_logspike(x)) return mu, logvar, logspike class VSC_Decoder(nn.Module): def __init__(self,nz=nz,ngf=8,nc=3): super(VSC_Decoder, self).__init__() self.nz=nz self.nc=nc self.main = nn.Sequential( nn.ConvTranspose2d(nz, ngf *128 , 2, 1, 0, bias=False), nn.BatchNorm2d(ngf * 128), nn.ReLU(True), # size ngf*128 x2 x2 nn.ConvTranspose2d(ngf * 128, ngf * 64, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 64), nn.ReLU(True), # size ngf*64 x4 x4 nn.ConvTranspose2d(ngf * 64, ngf * 32, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 32), nn.ReLU(True), # size ngf*32 x8 x8 nn.ConvTranspose2d(ngf*32, ngf * 16, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 16), nn.ReLU(True), # state size. (ngf*16) x 16 x16 nn.ConvTranspose2d(ngf * 16, ngf * 8, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 8), nn.ReLU(True), # state size. (ngf*8) x 32 x 32 nn.ConvTranspose2d(ngf * 8, ngf * 4, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 4), nn.ReLU(True), # state size. (ngf*4) x 64 x 64 nn.ConvTranspose2d(ngf * 4, ngf * 2, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf * 2), nn.ReLU(True), # state size. (ngf*2) x 128 x 128 nn.ConvTranspose2d(ngf * 2, ngf, 4, 2, 1, bias=False), nn.BatchNorm2d(ngf), nn.ReLU(True), # state size. (ngf) x 256 x 256 nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False), nn.Tanh() ) self.fc = nn.Linear(1024, nz) self.c = 50.0 def reparameterize(self, mu, logvar, logspike): std = torch.exp(0.5*logvar) eps = torch.randn_like(std) gaussian = eps.mul(std).add_(mu) eta = torch.rand_like(std) selection = nn.Sigmoid()(self.c*(eta + logspike.exp() - 1)) return selection.mul(gaussian) def forward(self, mu, logvar, logspike): z = self.reparameterize(mu, logvar, logspike) z = z.view(-1, 1024) z = self.fc(z).reshape(-1, self.nz, 1, 1) return self.main(z)

36.044444

73

0.498089

2,343

16,220

3.417414

0.041827

0.069689

0.085175

0.159361

0.957537

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0.893218

0

0.102109

0.356967

16,220

449

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36.124722

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0.102167

0

null

0

1

0

1

0

null

0

7

1960bf26c2be27092e1d206f6ba5acc0c7607d57

4,236

py

Python

read_dataset.py

xiongxiaochu/neural-network

59fdd400d3b3977e29aad5354577a5f315a57809

[ "Apache-2.0" ]

null

read_dataset.py

xiongxiaochu/neural-network

59fdd400d3b3977e29aad5354577a5f315a57809

[ "Apache-2.0" ]

null

read_dataset.py

xiongxiaochu/neural-network

59fdd400d3b3977e29aad5354577a5f315a57809

[ "Apache-2.0" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- def read_gowalla_data(file_path): train_file = open(file_path, 'r') x_data = {} for i in open(file_path): line = train_file.readline() # line = line.strip('\n') if len(line) == 0: continue items = line.split("\t") user_id = items[0] if len(user_id) == 0: continue user_id = int(user_id) if user_id not in x_data.keys(): x_data[user_id] = list() poi_id = items[4] if len(poi_id) == 0: continue else: poi_id = int(poi_id) x_data[user_id].append(poi_id) train_file.close() return x_data def read_foursquare_data(file_path): train_file = open(file_path, 'r') x_data = {} while 1: line = train_file.readline() if not line: break if len(line) == 0: continue items = line.split("\t") user_id = items[0].split("_")[1] if len(user_id) == 0: continue user_id = int(user_id) if user_id not in x_data.keys(): x_data[user_id] = list() poi_id = items[1].split("_")[1] if len(poi_id) == 0: continue else: poi_id = int(poi_id) x_data[user_id].append(poi_id) train_file.close() return x_data def read_gtd_data(file_path): train_file = open(file_path, 'r') x_data = {} while 1: line = train_file.readline() if not line: break if len(line) == 0: continue items = line.split("\t") user_id = items[6] if len(user_id) == 0: continue user_id = int(user_id) if user_id not in x_data.keys(): x_data[user_id] = list() poi_id = items[2] if len(poi_id) == 0: continue else: poi_id = int(poi_id) x_data[user_id].append(poi_id) train_file.close() return x_data def read_foursquare_users(): users = set() t_file = open('../foursquare/foursquare_records.txt', 'r') for i in open('../foursquare/foursquare_records.txt'): line = t_file.readline() items = line.split("\t") user_id = int(items[0].split("_")[1]) users.add(user_id) t_file.close() num_users = len(users) return num_users def read_foursquare_pois(): pois = set() t_file = open('../foursquare/foursquare_records.txt', 'r') for i in open('../foursquare/foursquare_records.txt'): line = t_file.readline() items = line.split("\t") poi_id = int(items[1].split("_")[1]) pois.add(poi_id) t_file.close() num_pois = len(pois) return num_pois def read_gtd_users(): users = set() t_file = open('../GTD/old_GTD-1335/indexed_GTD.txt', 'r') for i in open('../GTD/old_GTD-1335/indexed_GTD.txt'): line = t_file.readline() items = line.split("\t") user_id = int(items[6]) users.add(user_id) t_file.close() num_users = len(users) return num_users def read_gtd_pois(): pois = set() t_file = open('../GTD/old_GTD-1335/indexed_GTD.txt', 'r') for i in open('../GTD/old_GTD-1335/indexed_GTD.txt'): line = t_file.readline() items = line.split("\t") poi_id = int(items[2]) pois.add(poi_id) t_file.close() num_pois = len(pois) return num_pois def read_gowalla_users(): users = set() t_file = open('../gowalla/sorted_indexed_final_gowalla.txt', 'r') for i in open('../gowalla/sorted_indexed_final_gowalla.txt'): line = t_file.readline() items = line.split("\t") user_id = int(items[0]) users.add(user_id) t_file.close() num_users = len(users) return num_users def read_gowalla_pois(): pois = set() t_file = open('../gowalla/sorted_indexed_final_gowalla.txt', 'r') for i in open('../gowalla/sorted_indexed_final_gowalla.txt'): line = t_file.readline() items = line.split("\t") poi_id = int(items[4]) pois.add(poi_id) t_file.close() num_pois = len(pois) return num_pois

25.672727

69

0.555477

602

4,236

3.651163

0.101329

0.073703

0.057325

0.061419

0.929936

0.905369

0

0.014936

0.304533

4,236

164

70

25.829268

0.731161

0.014636

0

0.838235

0

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0.109326

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false

0

0.132353

0

null

0

1

0

1

0

null

0

7

5ff99401aaa92b1fb567410697bc6b95ad9cb429

694

py

Python

python/hetu/layers/pooling.py

zpxbjdx/Hetu

e84b6436b668e56b4e97a5fcc2ced08780f2a3c3

[ "Apache-2.0" ]

82

2021-07-20T02:45:54.000Z

2022-03-14T07:08:45.000Z

python/hetu/layers/pooling.py

zpxbjdx/Hetu

e84b6436b668e56b4e97a5fcc2ced08780f2a3c3

[ "Apache-2.0" ]

4

2021-11-25T13:39:21.000Z

2022-03-13T04:14:14.000Z

python/hetu/layers/pooling.py

zpxbjdx/Hetu

e84b6436b668e56b4e97a5fcc2ced08780f2a3c3

[ "Apache-2.0" ]

13

2021-07-18T14:40:56.000Z

2022-03-09T06:37:42.000Z

from .base import BaseLayer import hetu as ht class MaxPool2d(BaseLayer): def __init__(self, kernel_size, stride, padding=0): self.kernel_size = kernel_size self.stride = stride self.padding = padding def __call__(self, x): return ht.max_pool2d_op( x, self.kernel_size, self.kernel_size, self.padding, self.stride) class AvgPool2d(BaseLayer): def __init__(self, kernel_size, stride, padding=0): self.kernel_size = kernel_size self.stride = stride self.padding = padding def __call__(self, x): return ht.avg_pool2d_op( x, self.kernel_size, self.kernel_size, self.padding, self.stride)

27.76

77

0.664265

92

694

4.684783

0.271739

0.232019

0.259861

0.167053

0.835267

0

0.01145

0.244957

694

24

78

28.916667

0.811069

0

0.666667

0

1

0.222222

false

0

0.111111

0.555556

0

null

1

0

null

0

1

0

1

0

11

2728135df587c97e48aea85f5ac8bc50898d85b3

35,723

py

Python

examples/panopticlick.py

JarbasAl/pybrowser

61a6f96e601bb5bfb5085f90a7a7b1da03051878

[ "Apache-2.0" ]

null

examples/panopticlick.py

JarbasAl/pybrowser

61a6f96e601bb5bfb5085f90a7a7b1da03051878

[ "Apache-2.0" ]

null

examples/panopticlick.py

JarbasAl/pybrowser

61a6f96e601bb5bfb5085f90a7a7b1da03051878

[ "Apache-2.0" ]

null

from os.path import join, dirname from time import sleep from pombo_correio import FirefoxBrowser, PrivacyFoxBrowser, TorBrowser # https://github.com/mozilla/geckodriver/releases geckodriver = join(dirname(__file__), "geckodriver") def panopticlick(browser, name="test"): browser.find_and_click_css_selector("#kcarterlink") full_results_link = browser.wait_for_css_selector( "#showFingerprintLink2", timeout=60) sleep(6) # loading time (TODO add an implicit wait for some element) browser.scroll_down(5) sleep(1) browser.save_screenshot("panopticlick_{name}.png".format(name=name)) browser.click_element(full_results_link) browser.wait_for_xpath('//*[@id="results"]') # scroll for screenshot browser.scroll_down(5) sleep(1) browser.save_screenshot("panopticlick_full_{name}.png".format(name=name)) with FirefoxBrowser(geckodriver, headless=True, homepage="https://panopticlick.eff.org/") as browser: panopticlick(browser, name="firefox") with PrivacyFoxBrowser(geckodriver, headless=True, homepage="https://panopticlick.eff.org/") as browser: panopticlick(browser, name="privacyfox") with TorBrowser(geckodriver, headless=True, homepage="https://panopticlick.eff.org/") as browser: panopticlick(browser, name="tor") """ BrowserEvents.BROWSER_OPEN {'open_tabs': ['15'], 'tab_id': '15', 'homepage': 'https://panopticlick.eff.org/'} BrowserEvents.WAIT_FOR_CSS {'css_selector': '#kcarterlink', 'timeout': 10, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/'} BrowserEvents.CSS_FOUND {'css_selector': '#kcarterlink', 'timeout': 10, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/', 'element_text': 'TEST ME', 'href': 'https://panopticlick.eff.org/kcarter?aat=1', 'element_id': '412b8e29-83df-46e5-affb-4a3c02952d5a'} BrowserEvents.ELEMENT_CLICKED {'css_selector': '#kcarterlink', 'element_text': 'TEST ME', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/', 'href': 'https://panopticlick.eff.org/kcarter?aat=1'} BrowserEvents.WAIT_FOR_CSS {'css_selector': '#showFingerprintLink2', 'timeout': 60, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/kcarter?aat=1'} BrowserEvents.CSS_FOUND {'css_selector': '#showFingerprintLink2', 'timeout': 60, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/kcarter?aat=1', 'element_text': 'Show full results for fingerprinting', 'href': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'element_id': '445ff485-a2a4-4335-810c-3194f8e3a9ee'} BrowserEvents.ELEMENT_SEND_KEYS {'keys': ['\ue015', '\ue015', '\ue015', '\ue015', '\ue015'], 'element_text': "A RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nDONATE\nIs your browser safe against tracking?\nHow well are you protected against non-consensual Web tracking? After analyzing your browser and add-ons, the answer is ...\nMixed results: you have some protection against Web tracking, but it has some gaps. We suggest re-configuring your protection software, or consider installing EFF's Privacy Badger.\nINSTALL PRIVACY BADGER\nAND ENABLE DO NOT TRACK\nClick here for Chrome version\nClick here for Opera version\nTest Result\nIs your browser blocking tracking ads? ⚠ partial protection\nIs your browser blocking invisible trackers? ⚠ partial protection\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✗ no\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ✗\nyour browser has a nearly-unique fingerprint\nShow full results for fingerprinting\nNote: because tracking techniques are complex, subtle, and constantly evolving, Panopticlick does not measure all forms of tracking and protection.\n\nRE-TEST YOUR BROWSER\nThanks to Fingerprint2 for various fingerprinting tests, Aloodo for portions of the tracker test, browserspy.dk for the font detection code, and to breadcrumbs for supercookie help. Send questions or comments to panopticlick@eff.org.\nSHARE ON FACEBOOK SHARE ON TWITTER SHARE ON GOOGLE+\nA RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nABOUT PANOPTICLICK DONATE TO EFF CONTACT PRIVACY CC-LICENSE PAPER", 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D', 'href': None} BrowserEvents.SCREENSHOT {'image': 'panopticlick_firefox.png', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D'} BrowserEvents.ELEMENT_CLICKED {'element_text': 'Show full results for fingerprinting', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D', 'href': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.WAIT_FOR_XPATH {'xpath': '//*[@id="results"]', 'timeout': 30, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.XPATH_FOUND {'xpath': '//*[@id="results"]', 'timeout': 30, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'element_text': 'Test Result\nIs your browser blocking tracking ads? ⚠ partial protection\nIs your browser blocking invisible trackers? ⚠ partial protection\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✗ no\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ✗\nyour browser has a nearly-unique fingerprint', 'href': None, 'element_id': 'a2c37ffb-fd02-4ec1-9170-81e35f83aa19'} BrowserEvents.ELEMENT_SEND_KEYS {'keys': ['\ue015', '\ue015', '\ue015', '\ue015', '\ue015'], 'element_text': "A RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nDONATE\nIs your browser safe against tracking?\nHow well are you protected against non-consensual Web tracking? After analyzing your browser and add-ons, the answer is ...\nMixed results: you have some protection against Web tracking, but it has some gaps. We suggest re-configuring your protection software, or consider installing EFF's Privacy Badger.\nINSTALL PRIVACY BADGER\nAND ENABLE DO NOT TRACK\nClick here for Chrome version\nClick here for Opera version\nTest Result\nIs your browser blocking tracking ads? ⚠ partial protection\nIs your browser blocking invisible trackers? ⚠ partial protection\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✗ no\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ✗\nyour browser has a nearly-unique fingerprint\nNote: because tracking techniques are complex, subtle, and constantly evolving, Panopticlick does not measure all forms of tracking and protection.\n\nWithin our dataset of several hundred thousand visitors tested in the past 45 days, only one in 77086.0 browsers have the same fingerprint as yours.\nCurrently, we estimate that your browser has a fingerprint that conveys 16.23 bits of identifying information.\nThe measurements we used to obtain this result are listed below. You can read more about our methodology, statistical results, and some defenses against fingerprinting here.\nBrowser Characteristic bits of identifying information one in x browsers have this value value\nUser Agent\n7.03\n131.1\nMozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:81.0) Gecko/20100101 Firefox/81.0\nHTTP_ACCEPT Headers\n1.95\n3.86\ntext/html, */*; q=0.01 gzip, deflate, br en-US,en;q=0.5\nBrowser Plugin Details\n1.13\n2.19\nundefined\nTime Zone Offset\n4.04\n16.5\n-60\nTime Zone\n8.2\n294.6\nEurope/Lisbon\nScreen Size and Color Depth\n3.76\n13.54\n1366x768x24\nSystem Fonts\n9.86\n928.75\nArial, Arial Narrow, Bitstream Vera Sans Mono, Bookman Old Style, Calibri, Cambria, Century Schoolbook, Courier, Courier New, Helvetica, MS Gothic, MS PGothic, Palatino, Palatino Linotype, Times, Times New Roman (via javascript)\nAre Cookies Enabled?\n0.18\n1.13\nYes\nLimited supercookie test\n1.04\n2.06\nDOM localStorage: Yes, DOM sessionStorage: Yes, IE userData: No, openDatabase: false, indexed db: true\nHash of canvas fingerprint\n6.38\n83.55\nf139fb61b2b20249d81082f9012141dc\nHash of WebGL fingerprint\n3.47\n11.05\n13ae805231fcd00154a46b5a992143ec\nWebGL Vendor & Renderer\n2.37\n5.19\nno javascript\nDNT Header Enabled?\n0.96\n1.95\nFalse\nLanguage\n0.98\n1.97\nen-US\nPlatform\n2.92\n7.56\nLinux x86_64\nTouch Support\n0.73\n1.66\nMax touchpoints: 0; TouchEvent supported: false; onTouchStart supported: false\nAd Blocker Used\n0.37\n1.3\nFalse\nAudioContext fingerprint\n4.05\n16.55\n35.73833402246237\nCPU Class\n0.15\n1.11\nN/A\nHardware Concurrency\n4.68\n25.58\n12\nDevice Memory (GB)\n0.73\n1.66\nN/A\nRE-TEST YOUR BROWSER\nThanks to Fingerprint2 for various fingerprinting tests, Aloodo for portions of the tracker test, browserspy.dk for the font detection code, and to breadcrumbs for supercookie help. Send questions or comments to panopticlick@eff.org.\nSHARE ON FACEBOOK SHARE ON TWITTER SHARE ON GOOGLE+\nA RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nABOUT PANOPTICLICK DONATE TO EFF CONTACT PRIVACY CC-LICENSE PAPER", 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'href': None} BrowserEvents.SCREENSHOT {'image': 'panopticlick_full_firefox.png', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.BROWSER_CLOSED {'open_tabs': ['15'], 'tab_id': '15', 'current_url': 'https://panopticlick.eff.org/results?aat=1&a=111&t=111&dnt=111&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'tab2url': {'15': 'https://panopticlick.eff.org/'}} BrowserEvents.EXTENSION_LOADED {'extension': 'jid1-BoFifL9Vbdl2zQ@jetpack.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': 'uMatrix@raymondhill.net.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': 'CookieAutoDelete@kennydo.com.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': 'uBlock0@raymondhill.net.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': '{c607c8df-14a7-4f28-894f-29e8722976af}.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': '{74145f27-f039-47ce-a470-a662b129930a}.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': 'https-everywhere@eff.org.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': 'jid1-MnnxcxisBPnSXQ@jetpack.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': '@testpilot-containers.xpi'} BrowserEvents.EXTENSION_LOADED {'extension': 'CanvasBlocker@kkapsner.de.xpi'} BrowserEvents.EXTENSIONS_ALL_LOADED {'extensions': ['jid1-BoFifL9Vbdl2zQ@jetpack.xpi', 'uMatrix@raymondhill.net.xpi', 'CookieAutoDelete@kennydo.com.xpi', 'uBlock0@raymondhill.net.xpi', '{c607c8df-14a7-4f28-894f-29e8722976af}.xpi', '{74145f27-f039-47ce-a470-a662b129930a}.xpi', 'https-everywhere@eff.org.xpi', 'jid1-MnnxcxisBPnSXQ@jetpack.xpi', '@testpilot-containers.xpi', 'CanvasBlocker@kkapsner.de.xpi']} BrowserEvents.BROWSER_OPEN {'open_tabs': ['15', '53', '64', '70'], 'tab_id': '15', 'homepage': 'https://panopticlick.eff.org/'} BrowserEvents.SWITCH_TAB {'open_tabs': ['15', '53', '64', '70'], 'old_tab': '15', 'old_url': 'https://panopticlick.eff.org/', 'tab_id': '53'} BrowserEvents.SWITCH_TAB {'open_tabs': ['15', '53', '64', '70'], 'old_tab': '53', 'old_url': 'moz-extension://e69a567a-bcb5-4af9-bd19-7115d6009d72/options.html?installed', 'tab_id': '64'} BrowserEvents.SWITCH_TAB {'open_tabs': ['15', '53', '64', '70'], 'old_tab': '64', 'old_url': 'moz-extension://75c0d9ba-f849-4765-a80c-6a7ab6838c9b/skin/firstRun.html', 'tab_id': '70'} BrowserEvents.SWITCH_TAB {'open_tabs': ['15', '53', '64', '70'], 'old_tab': '70', 'old_url': 'moz-extension://41a1b386-d9d4-4674-8c7b-996bccb787eb/options/presets.html?notice=install', 'tab_id': '15'} BrowserEvents.WAIT_FOR_CSS {'css_selector': '#kcarterlink', 'timeout': 10, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/'} BrowserEvents.CSS_FOUND {'css_selector': '#kcarterlink', 'timeout': 10, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/', 'element_text': 'TEST ME', 'href': 'https://panopticlick.eff.org/kcarter?aat=1', 'element_id': 'e2af97c3-d541-4ffc-b38f-232e800b5e21'} BrowserEvents.ELEMENT_CLICKED {'css_selector': '#kcarterlink', 'element_text': 'TEST ME', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/', 'href': 'https://panopticlick.eff.org/kcarter?aat=1'} BrowserEvents.WAIT_FOR_CSS {'css_selector': '#showFingerprintLink2', 'timeout': 60, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/kcarter?aat=1'} BrowserEvents.CSS_FOUND {'css_selector': '#showFingerprintLink2', 'timeout': 60, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/kcarter?aat=1', 'element_text': 'Show full results for fingerprinting', 'href': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'element_id': 'c6802d71-3b1b-459a-b88c-6173e3e5ed3d'} BrowserEvents.ELEMENT_SEND_KEYS {'keys': ['\ue015', '\ue015', '\ue015', '\ue015', '\ue015'], 'element_text': 'A RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nDONATE\nIs your browser safe against tracking?\nHow well are you protected against non-consensual Web tracking? After analyzing your browser and add-ons, the answer is ...\nYes! You have strong protection against Web tracking, though your software isn’t checking for Do Not Track policies.\nHelp us defend the Web against tracking:\nTest Result\nIs your browser blocking tracking ads? ✓ yes\nIs your browser blocking invisible trackers? ✓ yes\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✓ yes\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ⚠ partial protection\nShow full results for fingerprinting\nNote: because tracking techniques are complex, subtle, and constantly evolving, Panopticlick does not measure all forms of tracking and protection.\n\nRE-TEST YOUR BROWSER\nThanks to Fingerprint2 for various fingerprinting tests, Aloodo for portions of the tracker test, browserspy.dk for the font detection code, and to breadcrumbs for supercookie help. Send questions or comments to panopticlick@eff.org.\nSHARE ON FACEBOOK SHARE ON TWITTER SHARE ON GOOGLE+\nA RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nABOUT PANOPTICLICK DONATE TO EFF CONTACT PRIVACY CC-LICENSE PAPER', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D', 'href': None} BrowserEvents.SCREENSHOT {'image': 'panopticlick_privacyfox.png', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D'} BrowserEvents.ELEMENT_CLICKED {'element_text': 'Show full results for fingerprinting', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D', 'href': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.WAIT_FOR_XPATH {'xpath': '//*[@id="results"]', 'timeout': 30, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.XPATH_FOUND {'xpath': '//*[@id="results"]', 'timeout': 30, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'element_text': 'Test Result\nIs your browser blocking tracking ads? ✓ yes\nIs your browser blocking invisible trackers? ✓ yes\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✓ yes\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ⚠ partial protection', 'href': None, 'element_id': '6707bc5d-fa03-4f83-b0fa-9f28ee877337'} BrowserEvents.ELEMENT_SEND_KEYS {'keys': ['\ue015', '\ue015', '\ue015', '\ue015', '\ue015'], 'element_text': 'A RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nDONATE\nIs your browser safe against tracking?\nHow well are you protected against non-consensual Web tracking? After analyzing your browser and add-ons, the answer is ...\nYes! You have strong protection against Web tracking, though your software isn’t checking for Do Not Track policies.\nHelp us defend the Web against tracking:\nTest Result\nIs your browser blocking tracking ads? ✓ yes\nIs your browser blocking invisible trackers? ✓ yes\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✓ yes\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ⚠ partial protection\nNote: because tracking techniques are complex, subtle, and constantly evolving, Panopticlick does not measure all forms of tracking and protection.\n\nWithin our dataset of several hundred thousand visitors tested in the past 45 days, only one in 17789.23 browsers have the same fingerprint as yours.\nCurrently, we estimate that your browser has a fingerprint that conveys 14.12 bits of identifying information.\nThe measurements we used to obtain this result are listed below. You can read more about our methodology, statistical results, and some defenses against fingerprinting here.\nBrowser Characteristic bits of identifying information one in x browsers have this value value\nUser Agent\n7.03\n131.03\nMozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:81.0) Gecko/20100101 Firefox/81.0\nHTTP_ACCEPT Headers\n1.95\n3.86\ntext/html, */*; q=0.01 gzip, deflate, br en-US,en;q=0.5\nBrowser Plugin Details\n1.13\n2.19\nundefined\nTime Zone Offset\n4.04\n16.5\n-60\nTime Zone\n8.2\n294.22\nEurope/Lisbon\nScreen Size and Color Depth\n3.76\n13.54\n1366x768x24\nSystem Fonts\n9.85\n925.04\nArial, Arial Narrow, Bitstream Vera Sans Mono, Bookman Old Style, Calibri, Cambria, Century Schoolbook, Courier, Courier New, Helvetica, MS Gothic, MS PGothic, Palatino, Palatino Linotype, Times, Times New Roman (via javascript)\nAre Cookies Enabled?\n0.18\n1.13\nYes\nLimited supercookie test\n1.04\n2.06\nDOM localStorage: Yes, DOM sessionStorage: Yes, IE userData: No, openDatabase: false, indexed db: true\nHash of canvas fingerprint\n2.55\n5.87\nrandomized by first party domain\nHash of WebGL fingerprint\n3.47\n11.05\n13ae805231fcd00154a46b5a992143ec\nWebGL Vendor & Renderer\n2.37\n5.19\nno javascript\nDNT Header Enabled?\n1.04\n2.05\nTrue\nLanguage\n0.98\n1.97\nen-US\nPlatform\n2.92\n7.56\nLinux x86_64\nTouch Support\n0.73\n1.66\nMax touchpoints: 0; TouchEvent supported: false; onTouchStart supported: false\nAd Blocker Used\n0.37\n1.3\nFalse\nAudioContext fingerprint\n3.63\n12.37\nnot available\nCPU Class\n0.15\n1.11\nN/A\nHardware Concurrency\n4.68\n25.57\n12\nDevice Memory (GB)\n0.73\n1.66\nN/A\nRE-TEST YOUR BROWSER\nThanks to Fingerprint2 for various fingerprinting tests, Aloodo for portions of the tracker test, browserspy.dk for the font detection code, and to breadcrumbs for supercookie help. Send questions or comments to panopticlick@eff.org.\nSHARE ON FACEBOOK SHARE ON TWITTER SHARE ON GOOGLE+\nA RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nABOUT PANOPTICLICK DONATE TO EFF CONTACT PRIVACY CC-LICENSE PAPER', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'href': None} BrowserEvents.SCREENSHOT {'image': 'panopticlick_full_privacyfox.png', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.BROWSER_CLOSED {'open_tabs': ['15', '53', '64', '70'], 'tab_id': '15', 'current_url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%22not+available%22%2C%22canvas_hash_v2%22%3A%22e05964b9ad20338b6c3d28bb68a2e89a%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'tab2url': {'15': 'https://panopticlick.eff.org/', '53': 'moz-extension://e69a567a-bcb5-4af9-bd19-7115d6009d72/options.html?installed', '64': 'moz-extension://75c0d9ba-f849-4765-a80c-6a7ab6838c9b/skin/firstRun.html', '70': 'moz-extension://41a1b386-d9d4-4674-8c7b-996bccb787eb/options/presets.html?notice=install'}} BrowserEvents.BROWSER_OPEN {'open_tabs': ['15'], 'tab_id': '15', 'homepage': 'https://panopticlick.eff.org/'} BrowserEvents.WAIT_FOR_CSS {'css_selector': '#kcarterlink', 'timeout': 10, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/'} BrowserEvents.CSS_FOUND {'css_selector': '#kcarterlink', 'timeout': 10, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/', 'element_text': 'TEST ME', 'href': 'https://panopticlick.eff.org/kcarter?aat=1', 'element_id': '063aba69-85c4-4749-a70d-e3eb62136461'} BrowserEvents.ELEMENT_CLICKED {'css_selector': '#kcarterlink', 'element_text': 'TEST ME', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/', 'href': 'https://panopticlick.eff.org/kcarter?aat=1'} BrowserEvents.WAIT_FOR_CSS {'css_selector': '#showFingerprintLink2', 'timeout': 60, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/kcarter?aat=1'} BrowserEvents.CSS_FOUND {'css_selector': '#showFingerprintLink2', 'timeout': 60, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/kcarter?aat=1', 'element_text': 'Show full results for fingerprinting', 'href': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'element_id': '259a76c2-a010-4035-b81c-df928b1894d6'} BrowserEvents.ELEMENT_SEND_KEYS {'keys': ['\ue015', '\ue015', '\ue015', '\ue015', '\ue015'], 'element_text': 'A RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nDONATE\nIs your browser safe against tracking?\nHow well are you protected against non-consensual Web tracking? After analyzing your browser and add-ons, the answer is ...\nYes! You have strong protection against Web tracking, though your software isn’t checking for Do Not Track policies.\nHelp us defend the Web against tracking:\nTest Result\nIs your browser blocking tracking ads? ✓ yes\nIs your browser blocking invisible trackers? ✓ yes\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✓ yes\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ✗\nyour browser has a nearly-unique fingerprint\nShow full results for fingerprinting\nNote: because tracking techniques are complex, subtle, and constantly evolving, Panopticlick does not measure all forms of tracking and protection.\n\nRE-TEST YOUR BROWSER\nThanks to Fingerprint2 for various fingerprinting tests, Aloodo for portions of the tracker test, browserspy.dk for the font detection code, and to breadcrumbs for supercookie help. Send questions or comments to panopticlick@eff.org.\nSHARE ON FACEBOOK SHARE ON TWITTER SHARE ON GOOGLE+\nA RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nABOUT PANOPTICLICK DONATE TO EFF CONTACT PRIVACY CC-LICENSE PAPER', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D', 'href': None} BrowserEvents.SCREENSHOT {'image': 'panopticlick_tor.png', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D'} BrowserEvents.ELEMENT_CLICKED {'element_text': 'Show full results for fingerprinting', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D', 'href': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.WAIT_FOR_XPATH {'xpath': '//*[@id="results"]', 'timeout': 30, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.XPATH_FOUND {'xpath': '//*[@id="results"]', 'timeout': 30, 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'element_text': 'Test Result\nIs your browser blocking tracking ads? ✓ yes\nIs your browser blocking invisible trackers? ✓ yes\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✓ yes\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ✗\nyour browser has a nearly-unique fingerprint', 'href': None, 'element_id': '7d530cd9-fdc9-43f5-9851-f27dcce4b0c7'} BrowserEvents.ELEMENT_SEND_KEYS {'keys': ['\ue015', '\ue015', '\ue015', '\ue015', '\ue015'], 'element_text': 'A RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nDONATE\nIs your browser safe against tracking?\nHow well are you protected against non-consensual Web tracking? After analyzing your browser and add-ons, the answer is ...\nYes! You have strong protection against Web tracking, though your software isn’t checking for Do Not Track policies.\nHelp us defend the Web against tracking:\nTest Result\nIs your browser blocking tracking ads? ✓ yes\nIs your browser blocking invisible trackers? ✓ yes\nDoes your blocker stop trackers that are included in the so-called “acceptable ads” whitelist? ✓ yes\nDoes your browser unblock 3rd parties that promise to honor Do Not Track? ✗ no\nDoes your browser protect from fingerprinting? ✗\nyour browser has a nearly-unique fingerprint\nNote: because tracking techniques are complex, subtle, and constantly evolving, Panopticlick does not measure all forms of tracking and protection.\n\nWithin our dataset of several hundred thousand visitors tested in the past 45 days, only one in 57816.75 browsers have the same fingerprint as yours.\nCurrently, we estimate that your browser has a fingerprint that conveys 15.82 bits of identifying information.\nThe measurements we used to obtain this result are listed below. You can read more about our methodology, statistical results, and some defenses against fingerprinting here.\nBrowser Characteristic bits of identifying information one in x browsers have this value value\nUser Agent\n7.03\n130.96\nMozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:81.0) Gecko/20100101 Firefox/81.0\nHTTP_ACCEPT Headers\n1.95\n3.86\ntext/html, */*; q=0.01 gzip, deflate, br en-US,en;q=0.5\nBrowser Plugin Details\n1.13\n2.19\nundefined\nTime Zone Offset\n4.04\n16.5\n-60\nTime Zone\n8.2\n293.86\nEurope/Lisbon\nScreen Size and Color Depth\n3.76\n13.53\n1366x768x24\nSystem Fonts\n9.85\n921.38\nArial, Arial Narrow, Bitstream Vera Sans Mono, Bookman Old Style, Calibri, Cambria, Century Schoolbook, Courier, Courier New, Helvetica, MS Gothic, MS PGothic, Palatino, Palatino Linotype, Times, Times New Roman (via javascript)\nAre Cookies Enabled?\n0.18\n1.13\nYes\nLimited supercookie test\n1.04\n2.06\nDOM localStorage: Yes, DOM sessionStorage: Yes, IE userData: No, openDatabase: false, indexed db: true\nHash of canvas fingerprint\n6.38\n83.52\nf139fb61b2b20249d81082f9012141dc\nHash of WebGL fingerprint\n3.47\n11.05\n13ae805231fcd00154a46b5a992143ec\nWebGL Vendor & Renderer\n2.37\n5.19\nno javascript\nDNT Header Enabled?\n0.96\n1.95\nFalse\nLanguage\n0.98\n1.97\nen-US\nPlatform\n2.92\n7.56\nLinux x86_64\nTouch Support\n0.73\n1.66\nMax touchpoints: 0; TouchEvent supported: false; onTouchStart supported: false\nAd Blocker Used\n0.37\n1.3\nFalse\nAudioContext fingerprint\n4.05\n16.55\n35.73833402246237\nCPU Class\n0.15\n1.11\nN/A\nHardware Concurrency\n4.68\n25.57\n12\nDevice Memory (GB)\n0.73\n1.66\nN/A\nRE-TEST YOUR BROWSER\nThanks to Fingerprint2 for various fingerprinting tests, Aloodo for portions of the tracker test, browserspy.dk for the font detection code, and to breadcrumbs for supercookie help. Send questions or comments to panopticlick@eff.org.\nSHARE ON FACEBOOK SHARE ON TWITTER SHARE ON GOOGLE+\nA RESEARCH PROJECT OF THE ELECTRONIC FRONTIER FOUNDATION\nABOUT PANOPTICLICK DONATE TO EFF CONTACT PRIVACY CC-LICENSE PAPER', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'href': None} BrowserEvents.SCREENSHOT {'image': 'panopticlick_full_tor.png', 'tab_id': '15', 'url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable'} BrowserEvents.BROWSER_CLOSED {'open_tabs': ['15'], 'tab_id': '15', 'current_url': 'https://panopticlick.eff.org/results?aat=1&fpi_whorls=%7B%22v2%22%3A%7B%22plugins%22%3A%22permission+denied%22%2C%22hardware_concurrency%22%3A12%2C%22audio%22%3A%2235.73833402246237%22%2C%22canvas_hash_v2%22%3A%22f139fb61b2b20249d81082f9012141dc%22%2C%22webgl_hash_v2%22%3A%2213ae805231fcd00154a46b5a992143ec%22%7D%7D#fingerprintTable', 'tab2url': {'15': 'https://panopticlick.eff.org/'}} """

368.278351

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5.230568

0.110133

0.021485

0.043186

0.05024

0.956062

0.938624

0.927308

0.923441

0.921292

0

0.150948

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35,723

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368.278351

0.692117

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274cfa31c37b8f48facb84c9ddff1df96cec9073

12,536

py

Python

auto_process_ngs/test/commands/test_clone_cmd.py

fls-bioinformatics-core/auto_process_ngs

1f07a08e14f118e6a61d3f37130515efc6049dd7

[ "AFL-3.0" ]

5

2017-01-31T21:37:09.000Z

2022-03-17T19:26:29.000Z

auto_process_ngs/test/commands/test_clone_cmd.py

fls-bioinformatics-core/auto_process_ngs

1f07a08e14f118e6a61d3f37130515efc6049dd7

[ "AFL-3.0" ]

294

2015-08-14T09:00:30.000Z

2022-03-18T10:17:05.000Z

auto_process_ngs/test/commands/test_clone_cmd.py

fls-bioinformatics-core/auto_process_ngs

1f07a08e14f118e6a61d3f37130515efc6049dd7

[ "AFL-3.0" ]

7

2017-11-23T07:52:21.000Z

2020-07-15T10:12:05.000Z

####################################################################### # Tests for clone_cmd.py module ####################################################################### import unittest import tempfile import shutil import os from auto_process_ngs.auto_processor import AutoProcess from auto_process_ngs.mock import MockAnalysisDirFactory from auto_process_ngs.mock import UpdateAnalysisDir from auto_process_ngs.metadata import AnalysisDirParameters from auto_process_ngs.commands.clone_cmd import clone # Set to False to keep test output dirs REMOVE_TEST_OUTPUTS = True class TestAutoProcessClone(unittest.TestCase): """ Tests for AutoProcess.clone """ def setUp(self): # Create a temp working dir self.dirn = tempfile.mkdtemp(suffix='TestAutoProcessClone') # Store original location so we can get back at the end self.pwd = os.getcwd() # Move to working dir os.chdir(self.dirn) # Placeholders for test objects self.ap = None def tearDown(self): # Delete autoprocessor object if self.ap is not None: del(self.ap) # Return to original dir os.chdir(self.pwd) # Remove the temporary test directory if REMOVE_TEST_OUTPUTS: shutil.rmtree(self.dirn) def test_clone_analysis_dir(self): """ clone: copies an analysis directory using symlinks """ # Make a source analysis dir analysis_dir = MockAnalysisDirFactory.bcl2fastq2( "190116_M01234_0002_AXYZ123", platform="miseq", paired_end=True, no_lane_splitting=False, include_stats_files=True, top_dir=self.dirn) analysis_dir.create() ap = AutoProcess(analysis_dir.dirn) UpdateAnalysisDir(ap).add_processing_report() ap.add_directory("primary_data/190116_M01234_0002_AXYZ123") # Make a copy clone_dir = os.path.join(self.dirn,"190116_M01234_0002_AXYZ123_copy") self.assertFalse(os.path.exists(clone_dir)) clone(ap,clone_dir) self.assertTrue(os.path.isdir(clone_dir)) # Check contents for subdir in ('logs','ScriptCode'): d = os.path.join(clone_dir,subdir) self.assertTrue(os.path.isdir(d),"Missing '%s'" % subdir) for filen in ('SampleSheet.orig.csv', 'custom_SampleSheet.csv', 'auto_process.info', 'metadata.info', 'statistics.info', 'statistics_full.info', 'per_lane_statistics.info', 'per_lane_sample_stats.info', 'processing_qc.html',): f = os.path.join(clone_dir,filen) self.assertTrue(os.path.isfile(f),"Missing '%s'" % filen) # Check unaligned unaligned = os.path.join(clone_dir,'bcl2fastq') self.assertTrue(os.path.islink(unaligned)) # Check primary data primary_data = os.path.join(clone_dir, 'primary_data', '190116_M01234_0002_AXYZ123') self.assertTrue(os.path.islink(primary_data)) # Check projects for proj in ('AB','CDE','undetermined'): d = os.path.join(clone_dir,proj) self.assertTrue(os.path.isdir(d),"Missing '%s'" % proj) # Check parameters params = AnalysisDirParameters(filen=os.path.join( clone_dir, 'auto_process.info')) self.assertEqual(params.sample_sheet, os.path.join(clone_dir,"custom_SampleSheet.csv")) self.assertEqual(params.primary_data_dir, os.path.join(clone_dir,"primary_data")) def test_clone_analysis_dir_copy_fastqs(self): """ clone: copies an analysis directory """ # Make a source analysis dir analysis_dir = MockAnalysisDirFactory.bcl2fastq2( "190116_M01234_0002_AXYZ123", platform="miseq", paired_end=True, no_lane_splitting=False, include_stats_files=True, top_dir=self.dirn) analysis_dir.create() ap = AutoProcess(analysis_dir.dirn) UpdateAnalysisDir(ap).add_processing_report() ap.add_directory("primary_data/190116_M01234_0002_AXYZ123") # Make a copy clone_dir = os.path.join(self.dirn,"190116_M01234_0002_AXYZ123_copy") self.assertFalse(os.path.exists(clone_dir)) clone(ap,clone_dir,copy_fastqs=True) self.assertTrue(os.path.isdir(clone_dir)) # Check contents for subdir in ('logs','ScriptCode'): d = os.path.join(clone_dir,subdir) self.assertTrue(os.path.isdir(d),"Missing '%s'" % subdir) for filen in ('SampleSheet.orig.csv', 'custom_SampleSheet.csv', 'auto_process.info', 'metadata.info', 'statistics.info', 'statistics_full.info', 'per_lane_statistics.info', 'per_lane_sample_stats.info', 'processing_qc.html',): f = os.path.join(clone_dir,filen) self.assertTrue(os.path.isfile(f),"Missing '%s'" % filen) # Check unaligned unaligned = os.path.join(clone_dir,'bcl2fastq') self.assertTrue(os.path.isdir(unaligned)) # Check primary data primary_data = os.path.join(clone_dir, 'primary_data', '190116_M01234_0002_AXYZ123') self.assertTrue(os.path.islink(primary_data)) # Check projects for proj in ('AB','CDE','undetermined'): d = os.path.join(clone_dir,proj) self.assertTrue(os.path.isdir(d),"Missing '%s'" % proj) # Check parameters params = AnalysisDirParameters(filen=os.path.join( clone_dir, 'auto_process.info')) self.assertEqual(params.sample_sheet, os.path.join(clone_dir,"custom_SampleSheet.csv")) self.assertEqual(params.primary_data_dir, os.path.join(clone_dir,"primary_data")) def test_clone_analysis_dir_no_projects(self): """ clone: copies an analysis directory excluding projects """ # Make a source analysis dir analysis_dir = MockAnalysisDirFactory.bcl2fastq2( "190116_M01234_0002_AXYZ123", platform="miseq", paired_end=True, no_lane_splitting=False, include_stats_files=True, top_dir=self.dirn) analysis_dir.create() ap = AutoProcess(analysis_dir.dirn) UpdateAnalysisDir(ap).add_processing_report() ap.add_directory("primary_data/190116_M01234_0002_AXYZ123") # Make a copy clone_dir = os.path.join(self.dirn,"190116_M01234_0002_AXYZ123_copy") self.assertFalse(os.path.exists(clone_dir)) clone(ap,clone_dir,exclude_projects=True) self.assertTrue(os.path.isdir(clone_dir)) # Check contents for subdir in ('logs','ScriptCode'): d = os.path.join(clone_dir,subdir) self.assertTrue(os.path.isdir(d),"Missing '%s'" % subdir) for filen in ('SampleSheet.orig.csv', 'custom_SampleSheet.csv', 'auto_process.info', 'metadata.info', 'statistics.info', 'statistics_full.info', 'per_lane_statistics.info', 'per_lane_sample_stats.info', 'processing_qc.html',): f = os.path.join(clone_dir,filen) self.assertTrue(os.path.isfile(f),"Missing '%s'" % filen) # Check unaligned unaligned = os.path.join(clone_dir,'bcl2fastq') self.assertTrue(os.path.islink(unaligned)) # Check primary data primary_data = os.path.join(clone_dir, 'primary_data', '190116_M01234_0002_AXYZ123') self.assertTrue(os.path.islink(primary_data)) # Check projects for proj in ('AB','CDE','undetermined'): d = os.path.join(clone_dir,proj) self.assertFalse(os.path.exists(d),"Found '%s'" % proj) # Check parameters params = AnalysisDirParameters(filen=os.path.join( clone_dir, 'auto_process.info')) self.assertEqual(params.sample_sheet, os.path.join(clone_dir,"custom_SampleSheet.csv")) self.assertEqual(params.primary_data_dir, os.path.join(clone_dir,"primary_data")) def test_clone_analysis_dir_empty_params(self): """ clone: copies an analysis directory when parameter file is empty """ # Make a source analysis dir analysis_dir = MockAnalysisDirFactory.bcl2fastq2( "190116_M01234_0002_AXYZ123", platform="miseq", paired_end=True, no_lane_splitting=False, include_stats_files=True, top_dir=self.dirn) analysis_dir.create() ap = AutoProcess(analysis_dir.dirn) UpdateAnalysisDir(ap).add_processing_report() ap.add_directory("primary_data/190116_M01234_0002_AXYZ123") # Remove data from parameter file parameter_file = ap.parameter_file tmp_parameter_file = os.path.join(self.dirn,'new_params.tmp') del(ap) with open(parameter_file,'r') as fp: with open(tmp_parameter_file,'w') as fpp: for line in fp: line = "%s\t." % line.split('\t')[0] fpp.write(line) os.remove(parameter_file) os.rename(tmp_parameter_file,parameter_file) ap = AutoProcess(analysis_dir.dirn) # Make a copy clone_dir = os.path.join(self.dirn,"190116_M01234_0002_AXYZ123_copy") self.assertFalse(os.path.exists(clone_dir)) clone(ap,clone_dir,exclude_projects=False) self.assertTrue(os.path.isdir(clone_dir)) # Check contents for subdir in ('logs','ScriptCode'): d = os.path.join(clone_dir,subdir) self.assertTrue(os.path.isdir(d),"Missing '%s'" % subdir) for filen in ('SampleSheet.orig.csv', 'custom_SampleSheet.csv', 'auto_process.info', 'metadata.info', 'statistics.info', 'statistics_full.info', 'per_lane_statistics.info', 'per_lane_sample_stats.info', 'processing_qc.html',): f = os.path.join(clone_dir,filen) self.assertTrue(os.path.isfile(f),"Missing '%s'" % filen) # Check unaligned unaligned = os.path.join(clone_dir,'bcl2fastq') self.assertTrue(os.path.islink(unaligned)) # Check primary data primary_data = os.path.join(clone_dir, 'primary_data', '190116_M01234_0002_AXYZ123') self.assertFalse(os.path.exists(primary_data)) # Check projects for proj in ('AB','CDE','undetermined'): d = os.path.join(clone_dir,proj) self.assertTrue(os.path.exists(d),"Missing '%s'" % proj) def test_clone_fails_if_target_dir_exists(self): """ clone: raises an exception if target dir already exists """ # Make a source analysis dir analysis_dir = MockAnalysisDirFactory.bcl2fastq2( "190116_M01234_0002_AXYZ123", platform="miseq", paired_end=True, no_lane_splitting=False, include_stats_files=True, top_dir=self.dirn) analysis_dir.create() ap = AutoProcess(analysis_dir.dirn) UpdateAnalysisDir(ap).add_processing_report() ap.add_directory("primary_data/190116_M01234_0002_AXYZ123") # Make target dir clone_dir = os.path.join(self.dirn,"190116_M01234_0002_AXYZ123_copy") os.mkdir(clone_dir) # Try to copy source dir self.assertRaises(Exception, clone, ap,clone_dir)

41.926421

77

0.577457

1,374

12,536

5.051674

0.129549

0.054459

0.050425

0.062671

0.82308

0.798012

0.77035

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0.31262

12,536

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0.091098

0

0.784141

0

0.167389

0.084642

0

0.154185

1

0.030837

false

0

0.039648

0

0.07489

0

null

0

1

0

1

0

null

0

7

278f247468d68c031c3b222e914bec2124f18d6a

1,600

py

Python

metrics/my_scorer.py

MarcoFavorito/supervised-morphological-segmentation-using-CRFs

99934e4a40baf9886cefce8050e3d8329125eed0

[ "MIT" ]

null

metrics/my_scorer.py

MarcoFavorito/supervised-morphological-segmentation-using-CRFs

99934e4a40baf9886cefce8050e3d8329125eed0

[ "MIT" ]

null

metrics/my_scorer.py

MarcoFavorito/supervised-morphological-segmentation-using-CRFs

99934e4a40baf9886cefce8050e3d8329125eed0

[ "MIT" ]

null

import metrics.evaluation as e import metrics.evaluation def get_evaluation(y_test, y_pred): flat_y_test = [i for subl in y_test for i in subl] flat_y_pred = [i for subl in y_pred for i in subl] H,I,D = e.compute_HID(flat_y_test, flat_y_pred) Precision, Recall, FScore = e.compute_PRF(H,I,D) evaluation = {} evaluation["E-count_test"] = flat_y_test.count('E-SEG') evaluation["S-count_test"] = flat_y_test.count('S-SEG') evaluation["E-count_pred"] = flat_y_pred.count('E-SEG') evaluation["S-count_pred"] = flat_y_pred.count('S-SEG') evaluation["H"]=H evaluation["I"]=I evaluation["D"]=D evaluation["Precision"] = Precision evaluation["Recall"] = Recall evaluation["F-score"] = FScore return FScore def get_evaluation_BM(y_test, y_pred): flat_y_test = [i for subl in y_test for i in subl] flat_y_pred = [i for subl in y_pred for i in subl] flat_y_test = metrics.evaluation.fromBM2BMES(flat_y_test) flat_y_pred = metrics.evaluation.fromBM2BMES(flat_y_pred) H,I,D = e.compute_HID(flat_y_test, flat_y_pred) Precision, Recall, FScore = e.compute_PRF(H,I,D) evaluation = {} evaluation["E-count_test"] = flat_y_test.count('E-SEG') evaluation["S-count_test"] = flat_y_test.count('S-SEG') evaluation["E-count_pred"] = flat_y_pred.count('E-SEG') evaluation["S-count_pred"] = flat_y_pred.count('S-SEG') evaluation["H"]=H evaluation["I"]=I evaluation["D"]=D evaluation["Precision"] = Precision evaluation["Recall"] = Recall evaluation["F-score"] = FScore return FScore

34.042553

61

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259

1,600

3.972973

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0.097182

0.087464

0.038873

0.911565

0.852284

0.829932

0

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0.17625

1,600

47

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34.042553

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0

1

0

1

0

null

0

7

27a6e7f103a0621e62f651dbaeb2dbf59d41b6ea

13,427

py

Python

tckdb/backend/app/tests/schemas/test_encorr.py

TCKDB/TCKDB

2ac60e47e178aa05bebdf41394344a7e5428eb86

[ "MIT" ]

2

2019-04-24T15:34:12.000Z

2020-04-06T15:29:50.000Z

tckdb/backend/app/tests/schemas/test_encorr.py

TCKDB/TCKDB

2ac60e47e178aa05bebdf41394344a7e5428eb86

[ "MIT" ]

8

2020-05-19T19:01:22.000Z

2021-01-12T08:15:54.000Z

tckdb/backend/app/tests/schemas/test_encorr.py

tckdb/TCKDB

2ac60e47e178aa05bebdf41394344a7e5428eb86

[ "MIT" ]

1

2019-11-03T20:03:08.000Z

""" TCKDB backend app tests schemas test_encorr module """ import pytest from pydantic import ValidationError from tckdb.backend.app.schemas.encorr import EnCorrBase def test_encorr_schema(): """Test creating an instance of EnCorr""" supported_elements = ['H', 'C', 'N', 'O', 'S', 'P'] aec = {'H': -0.502155915123, 'C': -37.8574709934, 'N': -54.6007233609, 'O': -75.0909131284, 'P': -341.281730319, 'S': -398.134489850} bac = {'C-H': 0.25, 'C-C': -1.89, 'C=C': -0.40, 'C#C': -1.50, 'O-H': -1.09, 'C-O': -1.18, 'C=O': -0.01, 'N-H': 1.36, 'C-N': -0.44, 'C#N': 0.22, 'C-S': -2.35, 'O=S': -5.19, 'S-H': -0.52} encorr_1 = EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec, bac=bac) assert encorr_1.level_id == 1 assert encorr_1.supported_elements == supported_elements assert encorr_1.energy_unit == 'hartree' assert encorr_1.aec == aec assert encorr_1.bac == bac assert encorr_1.isodesmic_reactions is None assert encorr_1.isodesmic_high_level_id is None assert encorr_1.reviewer_flags == dict() isodesmic_reactions = [{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 16.809}, {'reactants': ['InChI=1S/C5H11/c1-3-5-4-2/h1,3-5H2,2H3', '[CH3]'], 'products': ['CCCC', 'InChI=1S/C2H4/c1-2/h1H,2H3'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 15.409}, ] encorr_2 = EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=isodesmic_reactions, isodesmic_high_level_id=3) assert encorr_2.level_id == 1 assert encorr_2.supported_elements == supported_elements assert encorr_2.energy_unit == 'kcal/mol' assert encorr_2.aec is None assert encorr_2.bac is None assert encorr_2.isodesmic_reactions == isodesmic_reactions assert encorr_2.isodesmic_high_level_id == 3 with pytest.raises(ValidationError): # invalid element in supported_elements EnCorrBase(level_id=1, supported_elements=['M', 'C', 'N', 'O', 'S', 'P'], energy_unit='hartree', aec=aec, bac=bac) with pytest.raises(ValidationError): # invalid energy units EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='wrong', aec=aec, bac=bac) with pytest.raises(ValidationError): # aec element not in supported_elements EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec={'Si': -0.502155915123, 'C': -37.8574709934, 'N': -54.6007233609, 'O': -75.0909131284, 'P': -341.281730319, 'S': -398.134489850}, bac=bac) with pytest.raises(ValidationError): # aec and supported_elements have different lengths EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec={'H': -0.502155915123, 'C': -37.8574709934, 'N': -54.6007233609, 'O': -75.0909131284, 'P': -341.281730319}, bac=bac) with pytest.raises(ValidationError): # space in bac EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec, bac={'C- H': 0.25, 'C-C': -1.89}) with pytest.raises(ValidationError): # no bond descriptor in bac EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec, bac={'CH': 0.25, 'C-C': -1.89}) with pytest.raises(ValidationError): # two bond descriptors in bac EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec, bac={'C-=H': 0.25, 'C-C': -1.89}) with pytest.raises(ValidationError): # bac element not in supported_elements EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec, bac={'C-Cl': 0.25, 'C-C': -1.89}) with pytest.raises(ValidationError): # no bac nor isodesmic EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec) with pytest.raises(ValidationError): # no aec nor isodesmic EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', bac=bac) with pytest.raises(ValidationError): # both isodesmic and aec EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec, isodesmic_reactions=isodesmic_reactions, isodesmic_high_level_id=3) with pytest.raises(ValidationError): # both isodesmic and bac EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', bac=bac, isodesmic_reactions=isodesmic_reactions, isodesmic_high_level_id=3) with pytest.raises(ValidationError): # both isodesmic and aec/bac EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='hartree', aec=aec, bac=bac, isodesmic_reactions=isodesmic_reactions, isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic 'reactant' not a list EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': '[CH2]CCCC+[CH]', 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic 'product' not a list EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': '[C]C+[CH2]C(C)C', 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic 'product' has an invalid identifier EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C++++f151_invalid', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic 'stoichiometry' is not a list EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': '*1 *1 *1 *1', 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic 'stoichiometry' coefficient is not an integer EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': ['one', 1, 1, 1], 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic 'stoichiometry' DHrxn298 is not a float EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': (16.809, 'kJ/mol')}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic reaction has a wrong key EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'enthalpy_chane_of_reaction': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic reaction is missing a key EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic reaction is missing a key EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic reaction is missing a key EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic reaction is missing a key EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1]}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic reaction has an extra key EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'index': 152, 'DHrxn298': 16.809}], isodesmic_high_level_id=3) with pytest.raises(ValidationError): # isodesmic reaction with no isodesmic_high_level_id EnCorrBase(level_id=1, supported_elements=supported_elements, energy_unit='kcal/mol', isodesmic_reactions=[{'reactants': ['[CH2]CCCC', '[CH]'], 'products': ['[C]C', '[CH2]C(C)C'], 'stoichiometry': [1, 1, 1, 1], 'DHrxn298': 16.809}])

48.472924

107

0.487749

1,302

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0.172206

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1

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null

0

7

27b5ba9ae60bcf49b8295e3162287544d8a1d185

149

py

Python

tests/parser/functions.safety.finiteness.1.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/functions.safety.finiteness.1.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/functions.safety.finiteness.1.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

input = """ q(X) :- p(f(X)). p(f(X)) :- r(X), q(X). q(a). r(a). """ output = """ q(X) :- p(f(X)). p(f(X)) :- r(X), q(X). q(a). r(a). """

9.933333

23

0.288591

34

149

1.264706

0.235294

0.186047

0.27907

0.372093

0.744186

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0.255034

149

14

24

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1

0

1

0

null

0

11

27ed9808d992bc4d07cb76fe1c4124dd94f65968

524

py

Python

isimip_qc/exceptions.py

rouxter/isimip-qc

c90b027d8014ea0f267c9b6cd1ac7e097e89195d

[ "MIT" ]

4

2020-08-05T13:27:19.000Z

2021-12-21T09:10:42.000Z

isimip_qc/exceptions.py

rouxter/isimip-qc

c90b027d8014ea0f267c9b6cd1ac7e097e89195d

[ "MIT" ]

4

2020-09-10T11:30:35.000Z

2021-04-06T08:45:16.000Z

isimip_qc/exceptions.py

rouxter/isimip-qc

c90b027d8014ea0f267c9b6cd1ac7e097e89195d

[ "MIT" ]

1

2021-01-21T14:05:16.000Z

class FileWarning(Exception): def __init__(self, file, message, *args, **kwargs): file.warn(message, *args, **kwargs) super().__init__(message % args) class FileError(Exception): def __init__(self, file, message, *args, **kwargs): file.error(message, *args, **kwargs) super().__init__(message % args) class FileCritical(Exception): def __init__(self, file, message, *args, **kwargs): file.critical(message, *args, **kwargs) super().__init__(message % args)

26.2

55

0.637405

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524

5.438596

0.280702

0.319355

0.329032

0.193548

0.825806

0.706452

0.435484

0

0.208015

524

19

56

27.578947

0.746988

0

0.5

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0.25

false

0

0.5

0

null

1

0

null

0

1

0

8

7e0dba308f32c0fc289cefef214f6996d5d839a0

86

py

Python

lib/config/__init__.py

Waterbearbear/BBN

85b5ee48387ded0d67db3edf907a9b6bba3dc57a

[ "MIT" ]

null

lib/config/__init__.py

Waterbearbear/BBN

85b5ee48387ded0d67db3edf907a9b6bba3dc57a

[ "MIT" ]

null

lib/config/__init__.py

Waterbearbear/BBN

85b5ee48387ded0d67db3edf907a9b6bba3dc57a

[ "MIT" ]

null

from lib.config.default import _C as cfg from lib.config.default import update_config

28.666667

44

0.837209

15

86

4.666667

0.6

0.2

0.371429

0.571429

0.742857

0

0.116279

86

2

45

43

0.921053

0

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null

0

1

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1

0

null

0

1

0

1

0

1

0

7

fd902534a36bfea86eebd8c200aad4aa9b5529e1

22,323

py

Python

sdks/python/bjr4py/api/users_api.py

barryw/bjr

de56f22198b34a9d303ee43ac01134b5cf1ce863

[ "BSD-3-Clause" ]

2

2020-06-04T03:04:15.000Z

2020-06-13T12:53:58.000Z

sdks/python/bjr4py/api/users_api.py

barryw/bjr

de56f22198b34a9d303ee43ac01134b5cf1ce863

[ "BSD-3-Clause" ]

6

2020-05-24T12:56:25.000Z

2022-02-26T07:13:17.000Z

sdks/python/bjr4py/api/users_api.py

barryw/bjr

de56f22198b34a9d303ee43ac01134b5cf1ce863

[ "BSD-3-Clause" ]

null

""" BJR API V1 API specification for the BJR job server. # noqa: E501 The version of the OpenAPI document: v1 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from bjr4py.api_client import ApiClient, Endpoint as _Endpoint from bjr4py.model_utils import ( # noqa: F401 check_allowed_values, check_validations, date, datetime, file_type, none_type, validate_and_convert_types ) from bjr4py.model.single_user_message import SingleUserMessage from bjr4py.model.user_array_message import UserArrayMessage from bjr4py.model.user_new_in import UserNewIn from bjr4py.model.user_update_in import UserUpdateIn class UsersApi(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 __create_user( self, **kwargs ): """Creates a user # noqa: E501 Create a new user. Only root users are allowed to create new users. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_user(async_req=True) >>> result = thread.get() Keyword Args: user_new_in (UserNewIn): [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): 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. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: SingleUserMessage If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') return self.call_with_http_info(**kwargs) self.create_user = _Endpoint( settings={ 'response_type': (SingleUserMessage,), 'auth': [ 'bearerAuth' ], 'endpoint_path': '/user_api', 'operation_id': 'create_user', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'user_new_in', ], 'required': [], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'user_new_in': (UserNewIn,), }, 'attribute_map': { }, 'location_map': { 'user_new_in': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client, callable=__create_user ) def __delete_user( self, id, **kwargs ): """Deletes a user # noqa: E501 Deletes a user. Only root users can delete other users. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_user(id, async_req=True) >>> result = thread.get() Args: id (int): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): 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. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: SingleUserMessage If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.call_with_http_info(**kwargs) self.delete_user = _Endpoint( settings={ 'response_type': (SingleUserMessage,), 'auth': [ 'bearerAuth' ], 'endpoint_path': '/user_api/{id}', 'operation_id': 'delete_user', 'http_method': 'DELETE', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (int,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client, callable=__delete_user ) def __get_user( self, id, **kwargs ): """Retrieve a single user # noqa: E501 Retrieve a single user. If you're a non-root user, then you can only retrieve your own user. # 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_user(id, async_req=True) >>> result = thread.get() Args: id (int): Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): 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. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: SingleUserMessage If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.call_with_http_info(**kwargs) self.get_user = _Endpoint( settings={ 'response_type': (SingleUserMessage,), 'auth': [ 'bearerAuth' ], 'endpoint_path': '/user_api/{id}', 'operation_id': 'get_user', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'id', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (int,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client, callable=__get_user ) def __get_users( self, **kwargs ): """Retrieves users # noqa: E501 Get a list of users # 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_users(async_req=True) >>> result = thread.get() Keyword Args: per_page (int): [optional] page (int): [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): 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. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: UserArrayMessage If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') return self.call_with_http_info(**kwargs) self.get_users = _Endpoint( settings={ 'response_type': (UserArrayMessage,), 'auth': [ 'bearerAuth' ], 'endpoint_path': '/user_api', 'operation_id': 'get_users', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'per_page', 'page', ], 'required': [], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'per_page': (int,), 'page': (int,), }, 'attribute_map': { 'per_page': 'per_page', 'page': 'page', }, 'location_map': { 'per_page': 'query', 'page': 'query', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client, callable=__get_users ) def __update_user( self, id, **kwargs ): """Update a single user # noqa: E501 Update a single user. If you're a non-root users, then you can only update your own user. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_user(id, async_req=True) >>> result = thread.get() Args: id (int): Keyword Args: user_update_in (UserUpdateIn): [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (float/tuple): 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. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: SingleUserMessage If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['id'] = \ id return self.call_with_http_info(**kwargs) self.update_user = _Endpoint( settings={ 'response_type': (SingleUserMessage,), 'auth': [ 'bearerAuth' ], 'endpoint_path': '/user_api/{id}', 'operation_id': 'update_user', 'http_method': 'PUT', 'servers': None, }, params_map={ 'all': [ 'id', 'user_update_in', ], 'required': [ 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'id': (int,), 'user_update_in': (UserUpdateIn,), }, 'attribute_map': { 'id': 'id', }, 'location_map': { 'id': 'path', 'user_update_in': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client, callable=__update_user )

34.989028

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0.80544

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0

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0

null

0

1

0

1

0

null

0

7

fdaf97a32ea84b75ca3da9961d9758c42308886e

52,646

py

Python

test/features/test_open_close.py

loic-simon/lg-rez

c5eb8af7b2146fca110ee50a9209529f0ecfca1a

[ "MIT" ]

4

2020-08-13T17:07:51.000Z

2021-04-21T00:29:33.000Z

test/features/test_open_close.py

loic-simon/lg-rez

c5eb8af7b2146fca110ee50a9209529f0ecfca1a

[ "MIT" ]

9

2021-03-22T00:52:18.000Z

2021-10-05T23:46:38.000Z

test/features/test_open_close.py

loic-simon/lg-rez

c5eb8af7b2146fca110ee50a9209529f0ecfca1a

[ "MIT" ]

1

2020-10-17T15:04:23.000Z

import datetime import unittest from unittest import mock from lgrez import config, bdd from lgrez.features import open_close from test import mock_discord, mock_bdd, mock_env class TestOpenCloseFunctions(unittest.IsolatedAsyncioTestCase): """Unit tests for lgrez.features.open_close utility functions.""" def setUp(self): mock_discord.mock_config() def tearDown(self): mock_discord.unmock_config() @unittest.SkipTest @mock_bdd.patch_db # Empty database for this method @mock.patch("lgrez.features.gestion_actions.get_actions") async def test_recup_joueurs(self, getact_patch): """Unit tests for open_close.recup_joueurs function.""" # async def recup_joueurs(quoi, qui, heure=None) recup_joueurs = open_close.recup_joueurs mock_bdd.add_campsroles() i = 0 joueurs = [] for vote_condamne_ in [None, "non défini", "oh"]: for vote_maire_ in [None, "non défini", "ah"]: for vote_loups_ in [None, "non défini", "eh"]: for votant_village in [True, False]: for votant_loups in [True, False]: for role_actif in [True, False]: j = bdd.Joueur( discord_id=i, chan_id_=i, nom=f"Joueur{i}", vote_condamne_=vote_condamne_, vote_maire_=vote_maire_, vote_loups_=vote_loups_, votant_village=votant_village, votant_loups=votant_loups, role_actif=role_actif ) joueurs.append(j) i += 1 bdd.Joueur.add(*joueurs) # bad quoi with self.assertRaises(ValueError): await recup_joueurs("bloup", "cond") getact_patch.assert_not_called() # bad qui with self.assertRaises(ValueError): await recup_joueurs("open", "bzzt") getact_patch.assert_not_called() with self.assertRaises(ValueError): await recup_joueurs("open", "19") # non-existing action getact_patch.assert_not_called() # qui = "cond" results = await recup_joueurs("open", "cond") getact_patch.assert_not_called() for joueur in joueurs: if joueur.votant_village and joueur.vote_condamne_ is None: self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) results = await recup_joueurs("remind", "cond") getact_patch.assert_not_called() for joueur in joueurs: if joueur.vote_condamne_ == "non défini": self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) results = await recup_joueurs("close", "cond") getact_patch.assert_not_called() for joueur in joueurs: if joueur.vote_condamne_ is not None: self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) # qui = "maire" results = await recup_joueurs("open", "maire") getact_patch.assert_not_called() for joueur in joueurs: if joueur.votant_village and joueur.vote_maire_ is None: self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) results = await recup_joueurs("remind", "maire") getact_patch.assert_not_called() for joueur in joueurs: if joueur.vote_maire_ == "non défini": self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) results = await recup_joueurs("close", "maire") getact_patch.assert_not_called() for joueur in joueurs: if joueur.vote_maire_ is not None: self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) # qui = "loups" results = await recup_joueurs("open", "loups") getact_patch.assert_not_called() for joueur in joueurs: if joueur.votant_loups and joueur.vote_loups_ is None: self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) results = await recup_joueurs("remind", "loups") getact_patch.assert_not_called() for joueur in joueurs: if joueur.vote_loups_ == "non défini": self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) results = await recup_joueurs("close", "loups") getact_patch.assert_not_called() for joueur in joueurs: if joueur.vote_loups_ is not None: self.assertIn(joueur, results) else: self.assertNotIn(joueur, results) # qui = "action" with self.assertRaises(ValueError): await recup_joueurs("open", "action") getact_patch.assert_not_called() with self.assertRaises(ValueError): await recup_joueurs("open", "action", 15) getact_patch.assert_not_called() bdd.BaseAction(slug="ouiZ").add() bdd.BaseAction(slug="nonZ").add() bdd.BaseAction(slug="lalaZ").add() action1 = bdd.Action(id=1, joueur=joueurs[0], _base_slug="ouiZ") action2 = bdd.Action(id=23, joueur=joueurs[0], _base_slug="nonZ") action3 = bdd.Action(id=72, joueur=joueurs[1], _base_slug="lalaZ") bdd.Action.add(action1, action2, action3) getact_patch.return_value = [action1, action2, action3] results = await recup_joueurs("open", "action", "15h23") self.assertEqual(results, {joueurs[0]: [action1, action2], joueurs[1]: [action3]}) getact_patch.assert_called_once_with( "open", bdd.ActionTrigger.temporel, datetime.time(15, 23) ) getact_patch.reset_mock() results = await recup_joueurs("close", "action", "7h") self.assertEqual(results, {joueurs[0]: [action1, action2], joueurs[1]: [action3]}) getact_patch.assert_called_once_with( "close", bdd.ActionTrigger.temporel, datetime.time(7, 0) ) getact_patch.reset_mock() results = await recup_joueurs("remind", "action", "23h12") self.assertEqual(results, {joueurs[0]: [action1, action2], joueurs[1]: [action3]}) getact_patch.assert_called_once_with( "remind", bdd.ActionTrigger.temporel, datetime.time(23, 12) ) getact_patch.reset_mock() # qui = id with self.assertRaises(ValueError): await recup_joueurs("open", "3") # Non-existing action getact_patch.assert_not_called() action3.decision_ = None action3.base.trigger_debut = bdd.ActionTrigger.perma action3.update() results = await recup_joueurs("open", "72") self.assertEqual(results, {joueurs[1]: [action3]}) getact_patch.assert_not_called() action3.decision_ = "blabla" action3.update() results = await recup_joueurs("open", "72") self.assertEqual(results, {joueurs[1]: [action3]}) getact_patch.assert_not_called() action3.decision_ = None action3.base.trigger_debut = bdd.ActionTrigger.mot_mjs action3.update() results = await recup_joueurs("open", "72") self.assertEqual(results, {joueurs[1]: [action3]}) getact_patch.assert_not_called() action3.decision_ = "blabla" action3.update() results = await recup_joueurs("open", "72") self.assertEqual(results, {}) getact_patch.assert_not_called() results = await recup_joueurs("remind", "72") self.assertEqual(results, {}) getact_patch.assert_not_called() action3.decision_ = "rien" action3.update() results = await recup_joueurs("remind", "72") self.assertEqual(results, {joueurs[1]: [action3]}) getact_patch.assert_not_called() results = await recup_joueurs("close", "72") self.assertEqual(results, {joueurs[1]: [action3]}) getact_patch.assert_not_called() action3.decision_ = "blabla" action3.update() results = await recup_joueurs("close", "72") self.assertEqual(results, {joueurs[1]: [action3]}) getact_patch.assert_not_called() action3.decision_ = None action3.update() results = await recup_joueurs("close", "72") self.assertEqual(results, {}) getact_patch.assert_not_called() @mock_bdd.patch_db # Empty database for this method async def test__do_refill(self): """Unit tests for open_close._do_refill function.""" # async def _do_refill(motif, actions) _do_refill = open_close._do_refill config.refills_full = ["uikz"] config.refills_one = ["forgebonk", "rebootax", "divvvvvvin"] config.refills_divins = ["divvvvvvin"] mock_bdd.add_campsroles() joueur1 = bdd.Joueur(discord_id=1, chan_id_=11, nom="Joueur1") joueur2 = bdd.Joueur(discord_id=2, chan_id_=21, nom="Joueur2") joueurs = [joueur1, joueur2] bdd.Joueur.add(*joueurs) actions = {} i = 0 for kw in [*config.refills_full, *config.refills_one]: base = f"baz_{kw}" bdd.BaseAction(slug=base, refill=kw, base_charges=5 + i).add() i += 1 actions[kw] = [ bdd.Action(joueur=joueur1, _base_slug=base, charges=3), bdd.Action(joueur=joueur2, _base_slug=base, charges=3), ] action_none = bdd.Action(joueur=joueur1, _base_slug=base, charges=None) all_actions = {ac for acs in actions.values() for ac in acs} bdd.Action.add(*all_actions, action_none) # motif = full with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await _do_refill("uikz", list(all_actions)) for action in all_actions: chan = chan1 if action.joueur == joueur1 else chan2 sent = "\n".join(call.args[0] for call in chan.send.call_args_list) self.assertEqual(action.charges, action.base.base_charges) self.assertIn(str(action.base.slug), sent) self.assertIn(str(action.base.base_charges), sent) # motif = not full for action in all_actions: action.charges = 3 config.session.commit() with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await _do_refill("forgebonk", list(all_actions)) for action in all_actions: chan = chan1 if action.joueur == joueur1 else chan2 sent = "\n".join(call.args[0] for call in chan.send.call_args_list) self.assertEqual(action.charges, 4) self.assertIn(str(action.base.slug), sent) self.assertIn("4", sent) # motif = full, already full action bdd.BaseAction(slug="oui", base_charges=7).add() fa = bdd.Action(joueur=joueur1, _base_slug="oui", charges=7) fa.add() with mock_discord.mock_members_and_chans(joueur1): chan1 = joueur1.private_chan await _do_refill("uikz", [fa]) self.assertEqual(fa.charges, 7) chan1.send.assert_not_called() # motif = not full, already full action with mock_discord.mock_members_and_chans(joueur1): chan1 = joueur1.private_chan await _do_refill("forgebonk", [fa]) self.assertEqual(fa.charges, 8) chan1.send.assert_called_once() # perma action with no charges bdd.BaseAction(slug="non", trigger_debut=bdd.ActionTrigger.perma, base_charges=7).add() pa = bdd.Action(id=13, joueur=joueur1, _base_slug="non", charges=0) pa.add() with mock_discord.mock_members_and_chans(joueur1): await _do_refill("forgebonk", [pa]) taches = bdd.Tache.query.all() self.assertEqual(len(taches), 1) self.assertEqual(taches[0].commande, "!open 13") self.assertEqual(taches[0].action, pa) @unittest.SkipTest class TestOpenClose(unittest.IsolatedAsyncioTestCase): """Unit tests for lgrez.features.open_close commands.""" def setUp(self): mock_discord.mock_config() self.cog = open_close.OpenClose(config.bot) def tearDown(self): mock_discord.unmock_config() @mock_bdd.patch_db # Empty database for this method @mock_discord.interact() @mock.patch("lgrez.features.open_close.recup_joueurs") # tested before @mock.patch("lgrez.features.gestion_actions.open_action") async def test_open(self, oa_patch, rj_patch): """Unit tests for !open command.""" # async def open(self, ctx, qui, heure=None, heure_chain=None) open = self.cog.open mock_bdd.add_campsroles() joueur1 = bdd.Joueur(discord_id=1, chan_id_=11, nom="Joueur1", votant_village=True, votant_loups=True) joueur2 = bdd.Joueur(discord_id=2, chan_id_=21, nom="Joueur2", votant_village=True, votant_loups=True) joueur3 = bdd.Joueur(discord_id=3, chan_id_=31, nom="Joueur3") joueurs = [joueur1, joueur2, joueur3] bdd.Joueur.add(*joueurs) haros = [bdd.CandidHaro(joueur=joueur2, type=bdd.CandidHaroType.haro), bdd.CandidHaro(joueur=joueur3, type=bdd.CandidHaroType.haro)] candids = [bdd.CandidHaro(joueur=joueur1, type=bdd.CandidHaroType.candidature), bdd.CandidHaro(joueur=joueur3, type=bdd.CandidHaroType.candidature)] bdd.CandidHaro.add(*haros, *candids) bases = [bdd.BaseAction(slug=trigger.name, trigger_debut=trigger) for trigger in bdd.ActionTrigger] ac_oc = [bdd.Action(joueur=joueur1, base=base) for joueur in joueurs for base in bases] # bad qui ctx = mock_discord.get_ctx(open, "bzeepzopsl") rj_patch.side_effect = ValueError with self.assertRaises(ValueError): await ctx.invoke() rj_patch.assert_called_once_with("open", "bzeepzopsl", None) rj_patch.reset_mock(side_effect=True) oa_patch.assert_not_called() # qui = "cond", heure = None, heure_chain = None ctx = mock_discord.get_ctx(open, "cond") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("open", "cond", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Ouverture vote self.assertEqual(joueur1.vote_condamne_, "non défini") self.assertEqual(joueur2.vote_condamne_, "non défini") self.assertIsNone(joueur3.vote_condamne_) # Information joueurs chan1.send.assert_called_once() self.assertIn("vote pour le condamné du jour est ouvert", chan1.send.call_args.args[0]) (await chan1.send()).add_reaction.assert_called_once_with( config.Emoji.bucher) chan2.send.assert_called_once() self.assertIn("vote pour le condamné du jour est ouvert", chan2.send.call_args.args[0]) (await chan2.send()).add_reaction.assert_called_once_with( config.Emoji.bucher) # Ouverture open_cond actions self.assertEqual(oa_patch.call_count, 3) self.assertEqual( [ac for ac in ac_oc if ac.base.trigger_debut == bdd.ActionTrigger.open_cond], [call.args[0] for call in oa_patch.call_args_list]) oa_patch.reset_mock() # Réinitialisation haros self.assertFalse(bdd.CandidHaro.query.filter_by( type=bdd.CandidHaroType.haro ).all()) self.assertEqual(bdd.CandidHaro.query.filter_by( type=bdd.CandidHaroType.candidature ).all(), candids) config.Channel.haros.send.assert_called_once self.assertIn("Nouveau vote", config.Channel.haros.send.call_args.args[0]) config.Channel.haros.send.reset_mock() # heure / heure_chain self.assertFalse(bdd.Tache.query.all()) # qui = "cond", heure = 15h12, heure_chain = None ctx = mock_discord.get_ctx(open, "cond", heure="15h12") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) oa_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 2) self.assertEqual({tache.commande for tache in taches}, {"!remind cond", "!close cond"}) bdd.Tache.delete(*taches) # qui = "cond", heure = 15h12, heure_chain = 7h ctx = mock_discord.get_ctx(open, "cond", heure="15h12", heure_chain="7h") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) oa_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 2) self.assertEqual({tache.commande for tache in taches}, {"!remind cond", "!close cond 7h 15h12"}) bdd.Tache.delete(*taches) # ---- maire ---- bdd.CandidHaro.delete(*haros, *candids) haros = [bdd.CandidHaro(joueur=joueur2, type=bdd.CandidHaroType.haro), bdd.CandidHaro(joueur=joueur3, type=bdd.CandidHaroType.haro)] candids = [bdd.CandidHaro(joueur=joueur1, type=bdd.CandidHaroType.candidature), bdd.CandidHaro(joueur=joueur3, type=bdd.CandidHaroType.candidature)] bdd.CandidHaro.add(*haros, *candids) # qui = "maire", heure = None, heure_chain = None ctx = mock_discord.get_ctx(open, "maire") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("open", "maire", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Ouverture vote self.assertEqual(joueur1.vote_maire_, "non défini") self.assertEqual(joueur2.vote_maire_, "non défini") self.assertIsNone(joueur3.vote_maire_) # Information joueurs chan1.send.assert_called_once() self.assertIn("vote pour l'élection du maire est ouvert", chan1.send.call_args.args[0]) (await chan1.send()).add_reaction.assert_called_once_with( config.Emoji.maire) chan2.send.assert_called_once() self.assertIn("vote pour l'élection du maire est ouvert", chan2.send.call_args.args[0]) (await chan2.send()).add_reaction.assert_called_once_with( config.Emoji.maire) # Ouverture open_maire actions self.assertEqual(oa_patch.call_count, 3) self.assertEqual( [ac for ac in ac_oc if ac.base.trigger_debut == bdd.ActionTrigger.open_maire], [call.args[0] for call in oa_patch.call_args_list]) oa_patch.reset_mock() # Réinitialisation haros self.assertFalse(bdd.CandidHaro.query.filter_by( type=bdd.CandidHaroType.candidature ).all()) self.assertEqual(bdd.CandidHaro.query.filter_by( type=bdd.CandidHaroType.haro ).all(), haros) config.Channel.haros.send.assert_called_once self.assertIn("Nouveau vote", config.Channel.haros.send.call_args.args[0]) config.Channel.haros.send.reset_mock() # heure / heure_chain self.assertFalse(bdd.Tache.query.all()) # qui = "maire", heure = 15h12, heure_chain = None ctx = mock_discord.get_ctx(open, "maire", heure="15h12") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) oa_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 2) self.assertEqual({tache.commande for tache in taches}, {"!remind maire", "!close maire"}) bdd.Tache.delete(*taches) # qui = "maire", heure = 15h12, heure_chain = 7h ctx = mock_discord.get_ctx(open, "maire", heure="15h12", heure_chain="7h") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) oa_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 2) self.assertEqual({tache.commande for tache in taches}, {"!remind maire", "!close maire 7h 15h12"}) bdd.Tache.delete(*taches) # ---- loups ---- bdd.CandidHaro.delete(*haros, *candids) haros = [bdd.CandidHaro(joueur=joueur2, type=bdd.CandidHaroType.haro), bdd.CandidHaro(joueur=joueur3, type=bdd.CandidHaroType.haro)] candids = [bdd.CandidHaro(joueur=joueur1, type=bdd.CandidHaroType.candidature), bdd.CandidHaro(joueur=joueur3, type=bdd.CandidHaroType.candidature)] bdd.CandidHaro.add(*haros, *candids) # qui = "loups", heure = None, heure_chain = None ctx = mock_discord.get_ctx(open, "loups") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("open", "loups", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Ouverture vote self.assertEqual(joueur1.vote_loups_, "non défini") self.assertEqual(joueur2.vote_loups_, "non défini") self.assertIsNone(joueur3.vote_loups_) # Information joueurs chan1.send.assert_called_once() self.assertIn("vote pour la victime de cette nuit est ouvert", chan1.send.call_args.args[0]) (await chan1.send()).add_reaction.assert_called_once_with( config.Emoji.lune) chan2.send.assert_called_once() self.assertIn("vote pour la victime de cette nuit est ouvert", chan2.send.call_args.args[0]) (await chan2.send()).add_reaction.assert_called_once_with( config.Emoji.lune) # Ouverture open_loups actions self.assertEqual(oa_patch.call_count, 3) self.assertEqual( [ac for ac in ac_oc if ac.base.trigger_debut == bdd.ActionTrigger.open_loups], [call.args[0] for call in oa_patch.call_args_list]) oa_patch.reset_mock() # Non-réinitialisation haros self.assertEqual(len(bdd.CandidHaro.query.all()), 4) config.Channel.haros.send.assert_not_called() # heure / heure_chain self.assertFalse(bdd.Tache.query.all()) # qui = "loups", heure = 15h12, heure_chain = None ctx = mock_discord.get_ctx(open, "loups", heure="15h12") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) oa_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 2) self.assertEqual({tache.commande for tache in taches}, {"!remind loups", "!close loups"}) bdd.Tache.delete(*taches) # qui = "loups", heure = 15h12, heure_chain = 7h ctx = mock_discord.get_ctx(open, "loups", heure="15h12", heure_chain="7h") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) oa_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 2) self.assertEqual({tache.commande for tache in taches}, {"!remind loups", "!close loups 7h 15h12"}) # ---- action ---- bdd.BaseAction(slug="ouiz", trigger_debut=bdd.ActionTrigger.temporel, heure_debut=datetime.time(15, 12)).add() action1 = bdd.Action(_base_slug="ouiz", joueur=joueur1) action2 = bdd.Action(_base_slug="ouiz", joueur=joueur1) action3 = bdd.Action(_base_slug="ouiz", joueur=joueur2) bdd.Action.add(action1, action2, action3) # qui = "action", heure = "15h12" ctx = mock_discord.get_ctx(open, "action", "15h12") rj_patch.return_value = {joueur1: [action1, action2], joueur2: [action3]} with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("open", "action", "15h12") rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Ouverture actions self.assertEqual(oa_patch.call_count, 3) self.assertEqual( [action1, action2, action3], [call.args[0] for call in oa_patch.call_args_list]) oa_patch.reset_mock() @mock_bdd.patch_db # Empty database for this method @mock_discord.interact() @mock.patch("lgrez.features.open_close.recup_joueurs") # tested before @mock.patch("lgrez.features.gestion_actions.close_action") async def test_close(self, ca_patch, rj_patch): """Unit tests for !close command.""" # async def close(self, ctx, qui, heure=None, heure_chain=None) close = self.cog.close mock_bdd.add_campsroles() joueur1 = bdd.Joueur(discord_id=1, chan_id_=11, nom="Joueur1", votant_village=True, votant_loups=True, vote_condamne_="zeret", vote_maire_="goo", vote_loups_="kowwwia") joueur2 = bdd.Joueur(discord_id=2, chan_id_=21, nom="Joueur2", votant_village=True, votant_loups=True, vote_condamne_="zeret", vote_maire_="goo", vote_loups_="kowwwia") joueur3 = bdd.Joueur(discord_id=3, chan_id_=31, nom="Joueur3", vote_condamne_="zeret", vote_maire_="goo", vote_loups_="kowwwia") joueurs = [joueur1, joueur2, joueur3] bdd.Joueur.add(*joueurs) bases = [bdd.BaseAction(slug=trigger.name, trigger_debut=trigger) for trigger in bdd.ActionTrigger] ac_oc = [bdd.Action(joueur=joueur1, base=base) for joueur in joueurs for base in bases] # bad qui ctx = mock_discord.get_ctx(close, "bzeepzopsl") rj_patch.side_effect = ValueError with self.assertRaises(ValueError): await ctx.invoke() rj_patch.assert_called_once_with("close", "bzeepzopsl", None) rj_patch.reset_mock(side_effect=True) ca_patch.assert_not_called() # qui = "cond", heure = None, heure_chain = None ctx = mock_discord.get_ctx(close, "cond") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("close", "cond", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Fermeture vote self.assertIsNone(joueur1.vote_condamne_) self.assertIsNone(joueur2.vote_condamne_) self.assertEqual(joueur3.vote_condamne_, "zeret") # Information joueurs chan1.send.assert_called_once() self.assertIn("Fin du vote pour le condamné", chan1.send.call_args.args[0]) chan2.send.assert_called_once() self.assertIn("Fin du vote pour le condamné", chan2.send.call_args.args[0]) # Fermeture close_cond actions self.assertEqual(ca_patch.call_count, 3) self.assertEqual( [ac for ac in ac_oc if ac.base.trigger_debut == bdd.ActionTrigger.close_cond], [call.args[0] for call in ca_patch.call_args_list]) ca_patch.reset_mock() # heure / heure_chain self.assertFalse(bdd.Tache.query.all()) # qui = "cond", heure = 15h12, heure_chain = None ctx = mock_discord.get_ctx(close, "cond", heure="15h12") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) ca_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 1) self.assertEqual(taches[0].commande, "!open cond") bdd.Tache.delete(*taches) # qui = "cond", heure = 15h12, heure_chain = 7h ctx = mock_discord.get_ctx(close, "cond", heure="15h12", heure_chain="7h") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) ca_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 1) self.assertEqual(taches[0].commande, "!open cond 7h 15h12") bdd.Tache.delete(*taches) # ---- maire ---- # qui = "maire", heure = None, heure_chain = None ctx = mock_discord.get_ctx(close, "maire") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("close", "maire", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Fermeture vote self.assertIsNone(joueur1.vote_maire_) self.assertIsNone(joueur2.vote_maire_) self.assertEqual(joueur3.vote_maire_, "goo") # Information joueurs chan1.send.assert_called_once() self.assertIn("Fin du vote pour le maire", chan1.send.call_args.args[0]) chan2.send.assert_called_once() self.assertIn("Fin du vote pour le maire", chan2.send.call_args.args[0]) # Fermeture close_maire actions self.assertEqual(ca_patch.call_count, 3) self.assertEqual( [ac for ac in ac_oc if ac.base.trigger_debut == bdd.ActionTrigger.close_maire], [call.args[0] for call in ca_patch.call_args_list]) ca_patch.reset_mock() # heure / heure_chain self.assertFalse(bdd.Tache.query.all()) # qui = "maire", heure = 15h12, heure_chain = None ctx = mock_discord.get_ctx(close, "maire", heure="15h12") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) ca_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 1) self.assertEqual(taches[0].commande, "!open maire") bdd.Tache.delete(*taches) # qui = "maire", heure = 15h12, heure_chain = 7h ctx = mock_discord.get_ctx(close, "maire", heure="15h12", heure_chain="7h") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) ca_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 1) self.assertEqual(taches[0].commande, "!open maire 7h 15h12") bdd.Tache.delete(*taches) # ---- loups ---- # qui = "loups", heure = None, heure_chain = None ctx = mock_discord.get_ctx(close, "loups") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("close", "loups", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Fermeture vote self.assertIsNone(joueur1.vote_loups_) self.assertIsNone(joueur2.vote_loups_) self.assertEqual(joueur3.vote_loups_, "kowwwia") # Information joueurs chan1.send.assert_called_once() self.assertIn("Fin du vote pour la victime", chan1.send.call_args.args[0]) chan2.send.assert_called_once() self.assertIn("Fin du vote pour la victime", chan2.send.call_args.args[0]) # Fermeture close_loups actions self.assertEqual(ca_patch.call_count, 3) self.assertEqual( [ac for ac in ac_oc if ac.base.trigger_debut == bdd.ActionTrigger.close_loups], [call.args[0] for call in ca_patch.call_args_list]) ca_patch.reset_mock() # heure / heure_chain self.assertFalse(bdd.Tache.query.all()) # qui = "loups", heure = 15h12, heure_chain = None ctx = mock_discord.get_ctx(close, "loups", heure="15h12") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) ca_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 1) self.assertEqual(taches[0].commande, "!open loups") bdd.Tache.delete(*taches) # qui = "loups", heure = 15h12, heure_chain = 7h ctx = mock_discord.get_ctx(close, "loups", heure="15h12", heure_chain="7h") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.reset_mock(return_value=True) ca_patch.reset_mock() taches = bdd.Tache.query.all() self.assertEqual(len(taches), 1) self.assertEqual(taches[0].commande, "!open loups 7h 15h12") bdd.Tache.delete(*taches) # ---- action ---- bdd.BaseAction(slug="ouiz", trigger_debut=bdd.ActionTrigger.temporel, heure_debut=datetime.time(15, 12)).add() action1 = bdd.Action(_base_slug="ouiz", joueur=joueur1) action2 = bdd.Action(_base_slug="ouiz", joueur=joueur1) action3 = bdd.Action(_base_slug="ouiz", joueur=joueur2) bdd.Action.add(action1, action2, action3) # qui = "action", heure = "15h12" ctx = mock_discord.get_ctx(close, "action", "15h12") rj_patch.return_value = {joueur1: [action1, action2], joueur2: [action3]} with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("close", "action", "15h12") rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Fermeture actions self.assertEqual(ca_patch.call_count, 3) self.assertEqual( [action1, action2, action3], [call.args[0] for call in ca_patch.call_args_list]) ca_patch.reset_mock() @mock_bdd.patch_db # Empty database for this method @mock_discord.interact() @mock.patch("lgrez.features.open_close.recup_joueurs") # tested before async def test_remind(self, rj_patch): """Unit tests for !remind command.""" # async def remind(self, ctx, qui, heure=None) remind = self.cog.remind mock_bdd.add_campsroles() joueur1 = bdd.Joueur(discord_id=1, chan_id_=11, nom="Joueur1", votant_village=True, votant_loups=True, vote_condamne_="non défini", vote_maire_="non défini", vote_loups_="non défini") joueur2 = bdd.Joueur(discord_id=2, chan_id_=21, nom="Joueur2", votant_village=True, votant_loups=True, vote_condamne_="non défini", vote_maire_="non défini", vote_loups_="non défini") joueur3 = bdd.Joueur(discord_id=3, chan_id_=31, nom="Joueur3") joueurs = [joueur1, joueur2, joueur3] bdd.Joueur.add(*joueurs) bases = [bdd.BaseAction(slug=trigger.name, trigger_debut=trigger) for trigger in bdd.ActionTrigger] ac_oc = [bdd.Action(joueur=joueur1, base=base) for joueur in joueurs for base in bases] # bad qui ctx = mock_discord.get_ctx(remind, "bzeepzopsl") rj_patch.side_effect = ValueError with self.assertRaises(ValueError): await ctx.invoke() rj_patch.assert_called_once_with("remind", "bzeepzopsl", None) rj_patch.reset_mock(side_effect=True) # qui = "cond", heure = None ctx = mock_discord.get_ctx(remind, "cond") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("remind", "cond", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Information joueurs chan1.send.assert_called_once() self.assertIn("pour voter pour le condamné", chan1.send.call_args.args[0]) chan2.send.assert_called_once() self.assertIn("pour voter pour le condamné", chan2.send.call_args.args[0]) # ---- maire ---- # qui = "maire", heure = None ctx = mock_discord.get_ctx(remind, "maire") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("remind", "maire", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Information joueurs chan1.send.assert_called_once() self.assertIn("pour élire le nouveau maire", chan1.send.call_args.args[0]) chan2.send.assert_called_once() self.assertIn("pour élire le nouveau maire", chan2.send.call_args.args[0]) # ---- loups ---- # qui = "loups", heure = None ctx = mock_discord.get_ctx(remind, "loups") rj_patch.return_value = [joueur1, joueur2] with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("remind", "loups", None) rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Information joueurs chan1.send.assert_called_once() self.assertIn("pour voter pour la victime", chan1.send.call_args.args[0]) chan2.send.assert_called_once() self.assertIn("pour voter pour la victime", chan2.send.call_args.args[0]) # ---- action ---- bdd.BaseAction(slug="ouiz", trigger_debut=bdd.ActionTrigger.temporel, heure_debut=datetime.time(15, 12)).add() action1 = bdd.Action(_base_slug="ouiz", joueur=joueur1) action2 = bdd.Action(_base_slug="ouiz", joueur=joueur1) action3 = bdd.Action(_base_slug="ouiz", joueur=joueur2) bdd.Action.add(action1, action2, action3) # qui = "action", heure = "15h12" ctx = mock_discord.get_ctx(remind, "action", "15h12") rj_patch.return_value = {joueur1: [action1, action2], joueur2: [action3]} with mock_discord.mock_members_and_chans(joueur1, joueur2): chan1, chan2 = joueur1.private_chan, joueur2.private_chan await ctx.invoke() rj_patch.assert_called_once_with("remind", "action", "15h12") rj_patch.reset_mock(return_value=True) # Liste joueurs concernés ctx.send.assert_called_once() self.assertIn("Joueur1", ctx.send.call_args.args[0]) self.assertIn("Joueur2", ctx.send.call_args.args[0]) self.assertNotIn("Joueur3", ctx.send.call_args.args[0]) # Information joueurs self.assertEqual(chan1.send.call_count, 2) self.assertIn("pour utiliser ton action", chan1.send.call_args.args[0]) chan2.send.assert_called_once() self.assertIn("pour utiliser ton action", chan2.send.call_args.args[0]) @mock_bdd.patch_db # Empty database for this method @mock_discord.interact() @mock.patch("lgrez.features.open_close._do_refill") # tested before async def test_refill(self, dr_patch): """Unit tests for !refill command.""" # async def refill(self, ctx, motif, *, cible=None) refill = self.cog.refill config.refills_full = ["uikz"] config.refills_one = ["forgebonk", "rebootax", "divvvvvvin"] config.refills_divins = ["divvvvvvin"] mock_bdd.add_campsroles() joueur1 = bdd.Joueur(discord_id=1, chan_id_=11, nom="Joueur1") joueur2 = bdd.Joueur(discord_id=2, chan_id_=21, nom="Joueur2") joueurs = [joueur1, joueur2] bdd.Joueur.add(*joueurs) nondivin = set(config.refills_full + config.refills_one) ^ set(config.refills_divins) bdd.BaseAction(slug="baz_all", refill=", ".join(nondivin)).add() act_all_refs = bdd.Action(joueur=joueur1, _base_slug="baz_all", charges=3) actions = {} for kw in [*config.refills_full, *config.refills_one]: base = f"baz_{kw}" bdd.BaseAction(slug=base, refill=kw).add() actions[kw] = [ bdd.Action(joueur=joueur1, _base_slug=base, charges=3), bdd.Action(joueur=joueur2, _base_slug=base, charges=3), act_all_refs, ] action_none = bdd.Action(joueur=joueur1, _base_slug=base, charges=None) all_actions = {ac for acs in actions.values() for ac in acs} bdd.Action.add(*all_actions, action_none) # bad motif ctx = mock_discord.get_ctx(refill, "bzeepzopsl") await ctx.invoke() ctx.send.assert_called_once() self.assertIn("pas un motif valide", ctx.send.call_args.args[0]) dr_patch.assert_not_called() # motif = divin, cible = "all", abort ctx = mock_discord.get_ctx(refill, "divvvvvvin", cible="all") with mock_discord.interact(("yes_no", False)): await ctx.invoke() ctx.assert_sent( "es-tu sûr ?", "Mission aborted", ) dr_patch.assert_not_called() # motif = divin, cible = "all", proceed ctx = mock_discord.get_ctx(refill, "divvvvvvin", cible="all") with mock_discord.interact(("yes_no", True)): await ctx.invoke() ctx.assert_sent( "es-tu sûr ?", "répondant aux critères", ) dr_patch.assert_called_once() motif, refilled = dr_patch.call_args.args self.assertEqual("divvvvvvin", motif) self.assertEqual(set(all_actions), set(refilled)) dr_patch.reset_mock() # motif = divin, cible = Joueur1 ctx = mock_discord.get_ctx(refill, "divvvvvvin", cible="Joueur1") await ctx.invoke() ctx.assert_sent("répondant aux critères") dr_patch.assert_called_once() motif, refilled = dr_patch.call_args.args self.assertEqual("divvvvvvin", motif) self.assertEqual(set(ac for ac in all_actions if ac.joueur == joueur1), set(refilled)) dr_patch.reset_mock() # motif = autre, cible = "all" for motif in ["uikz", "forgebonk", "rebootax"]: ctx = mock_discord.get_ctx(refill, motif, cible="all") await ctx.invoke() ctx.assert_sent("répondant aux critères") dr_patch.assert_called_once() motifc, refilled = dr_patch.call_args.args self.assertEqual(motif, motifc) self.assertEqual(set(actions[motif]), set(refilled)) dr_patch.reset_mock() # motif = autre, cible = Joueur1 for motif in ["uikz", "forgebonk", "rebootax"]: ctx = mock_discord.get_ctx(refill, motif, cible="Joueur1") await ctx.invoke() ctx.assert_sent("répondant aux critères") dr_patch.assert_called_once() motifc, refilled = dr_patch.call_args.args self.assertEqual(motif, motifc) self.assertEqual(set(ac for ac in actions[motif] if ac.joueur == joueur1), set(refilled)) dr_patch.reset_mock() @mock_bdd.patch_db # Empty database for this method @mock_discord.interact() async def test_cparti(self): """Unit tests for !cparti command.""" # async def cparti(self, ctx) cparti = self.cog.cparti mock_bdd.add_campsroles() joueur1 = bdd.Joueur(discord_id=1, chan_id_=11, nom="Joueur1") joueur2 = bdd.Joueur(discord_id=2, chan_id_=21, nom="Joueur2") joueurs = [joueur1, joueur2] bdd.Joueur.add(*joueurs) bas = [ bdd.BaseAction(slug="baz_strt", trigger_debut="start"), bdd.BaseAction(slug="baz_prm", trigger_debut="perma"), bdd.BaseAction(slug="baz_aut", trigger_debut="temporel") ] bdd.BaseAction.add(*bas) actions = [*[bdd.Action(base=base, joueur=joueur1) for base in bas], *[bdd.Action(base=base, joueur=joueur2) for base in bas]] bdd.Action.add(*actions) # abort 1 ctx = mock_discord.get_ctx(cparti) with mock_discord.interact(("yes_no", False)): await ctx.invoke() ctx.assert_sent( "", "Mission aborted", ) # abort 2 ctx = mock_discord.get_ctx(cparti) with mock_discord.interact(("yes_no", True), ("yes_no", False)): await ctx.invoke() ctx.assert_sent( "", "", "Mission aborted", ) # proceed ctx = mock_discord.get_ctx(cparti) with mock_discord.interact(("yes_no", True), ("yes_no", True)): await ctx.invoke() ctx.assert_sent( "", "", "tout bon", ) taches = bdd.Tache.query.all() self.assertEqual(len(taches), 8) commands_debuts = { " ".join(tache.commande.split(maxsplit=2)[:2]) for tache in taches } expected = { "!open cond", "!open maire", "!open loups", "!send all", *{f"!open {action.id}" for action in actions if action.base.slug in ("baz_strt", "baz_prm")} } self.assertEqual(commands_debuts, expected)

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0

null

0

7

fdbda0dbe260fdd4fc43cc1618d8692074ea1079

272

py

Python

config.py

gonzageraci/dydx-bot

d2cd3526c1eb7fbe5d07610510c74a2d428d3c4d

[ "Apache-2.0" ]

1

2021-11-13T20:38:29.000Z

config.py

gonzageraci/dydx-bot

d2cd3526c1eb7fbe5d07610510c74a2d428d3c4d

[ "Apache-2.0" ]

null

config.py

gonzageraci/dydx-bot

d2cd3526c1eb7fbe5d07610510c74a2d428d3c4d

[ "Apache-2.0" ]

1

2021-12-13T09:22:15.000Z

API_ENDPOINT = "https://api.dydx.exchange" StarkPrivateKey = "0x6d6300ffa9a563f84fc628251a3499459903354e33c965d83a613d56f1bdd8d" eth_private_key = "48d5c67094243f36207f0dc21967e005dccca0756d63e77d4e680adf7e4b66fe" eth_address = "0xb6eDcE2198cC2063906169fD4339B0F15EC558ea"

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fdd535875253a6a8c0c380d7b7a8bb6438d30217

39,963

py

Python

Base-code/measure_offsets.py

FPAVANO81/Tectonics

bda657b74cf920f40524421cdb5174d4ce865280

[ "MIT" ]

null

Base-code/measure_offsets.py

FPAVANO81/Tectonics

bda657b74cf920f40524421cdb5174d4ce865280

[ "MIT" ]

null

Base-code/measure_offsets.py

FPAVANO81/Tectonics

bda657b74cf920f40524421cdb5174d4ce865280

[ "MIT" ]

4

2021-06-14T20:58:51.000Z

2021-06-14T21:00:05.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Mar 18 23:58:03 2019 function to measure offsets from strike-slip model output topography dependencies: numpy, matplotlib, rasterio, scipy, scikit-image, slip function included in this archive author: nadine g reitman email: nadine.reitman@colorado.edu """ #%% import modules import numpy as np import matplotlib.pyplot as plt from sklearn.metrics import mean_squared_error from scipy.stats import norm from skimage import measure import pickle import rasterio as rio #import yaml import warnings warnings.filterwarnings('ignore') # figure settings plt.rcParams['axes.facecolor'] =(1,1,1,1) # white plot backgrounds plt.rcParams['figure.facecolor']=(1,1,1,0) # clear figure backgrounds plt.rcParams['xtick.top']=True # plot ticks on top plt.rcParams['ytick.right']=True # plot ticks on right side plt.rcParams['ytick.direction']='in' # tick marks face in plt.rcParams['xtick.direction']='in' # tick marks face in plt.rcParams["errorbar.capsize"] = 3 #%% define functions def measure_offsets(da_ascii,fzw,dxy,real_max_slip,name,save_loc,years=10000, channel_cutoff=1000,clean=False,left=False,plot=True,): ''' function to measure offsets given an ascii file of drainage area. saves output as pngs, thalwags.p (thalwag indices), offsets.p (offset msrmts & locations) INPUTS: da_ascii = filename ending in .asc (ESRI ASCII format) fzw = fault zone width dxy = grid pixel size real_max_slip = imposed total slip in model to evaluate how well auto method does name = string to name output data and figures years = years of simulation channel_cutoff = value of drainage area above which is a channel clean = whether or not to recalculate offset stats and pdf with outlier removed. left = is this a left-lateral fault? default=False for: no, it's right-lateral plot=True or False for plot & save figures or not save_loc = directory to save output in ''' ########################################### ### open drainage area and get channels ### ########################################### da = rio.open(da_ascii) da = da.read(1) ymax = np.shape(da)[0] fault_loc = np.int(ymax/2) # channels are da>1000 channels = np.copy(da) channels[channels<channel_cutoff] = np.nan channels[channels>=channel_cutoff] = 1000 ############################################# ### calc connected components on channels ### ############################################# conncomps = measure.label(channels, background=0, connectivity=2) conncomps_above = conncomps[fault_loc-(fzw),:] conncomps_below = conncomps[fault_loc+fzw,:] ############################################# ### extract subset from above/below fault ### ############################################# ### NOTICE SWITCH IN ABOVE BELOW +- B/C WEIRD INDEXING subset_above = channels[fault_loc-(fzw),:] subset_below = channels[fault_loc+fzw,:] # do binary thalwags arrays for yes/no thalwag/not thals_above = np.zeros_like(subset_above) thals_below = np.zeros_like(subset_below) for i,v in enumerate(subset_above): if subset_above[i]>=1000: thals_above[i] = 1 for i,v in enumerate(subset_below): if subset_below[i]>=1000: thals_below[i] = 1 # initiate offset array offsets = np.zeros_like(thals_above) # get a list of index,value for thals_below and above, then compare intervals = list(map(list, enumerate(thals_below))) # get list of [index,value] for item in intervals: item[0], item[1] = item[1], item[0] # swap index with value intervals = np.asarray(sorted(intervals),dtype=float) # sort by thalwag value low to high events = intervals[:][intervals[:,0]>0] # find indexs of thalwags/events thal_index_below = events[:,1] # get rid of events, keep only index column intervals = list(map(list, enumerate(thals_above))) # get list of [index,value] for item in intervals: item[0], item[1] = item[1], item[0] # swap index with value intervals = np.asarray(sorted(intervals),dtype=float) # sort by thalwag value low to high events = intervals[:][intervals[:,0]>0] # find indexs of thalwags/events thal_index_above = events[:,1] # get rid of events, keep only index column ### clean up thal_index to get rid of connected indices ### # could update this using connected components now # thal_index_above for i,v in enumerate(thal_index_above[:-1]): if v+1 == thal_index_above[i+1]: thal_index_above[i+1] = np.nan for i,v in enumerate(thal_index_above[:-2]): if v+2 == thal_index_above[i+2]: thal_index_above[i+2] = np.nan for i,v in enumerate(thal_index_above[:-3]): if v+3 == thal_index_above[i+3]: thal_index_above[i+3] = np.nan for i,v in enumerate(thal_index_above[:-4]): if v+4 == thal_index_above[i+4]: thal_index_above[i+4] = np.nan for i,v in enumerate(thal_index_above[:-5]): if v+5 == thal_index_above[i+5]: thal_index_above[i+5] = np.nan # thal_index_below for i,v in enumerate(thal_index_below[:-1]): if v+1 == thal_index_below[i+1]: thal_index_below[i+1] = np.nan for i,v in enumerate(thal_index_below[:-2]): if v+2 == thal_index_below[i+2]: thal_index_below[i+2] = np.nan for i,v in enumerate(thal_index_below[:-3]): if v+3 == thal_index_below[i+3]: thal_index_below[i+3] = np.nan for i,v in enumerate(thal_index_below[:-4]): if v+4 == thal_index_below[i+4]: thal_index_below[i+5] = np.nan for i,v in enumerate(thal_index_below[:-5]): if v+5 == thal_index_below[i+5]: thal_index_below[i+5] = np.nan # remove any nan entries thal_index_above = thal_index_above[thal_index_above>0] thal_index_below = thal_index_below[thal_index_below>0] # remove any thalwegs in the below array that are part of the same channel system and close by thal_index_below = np.flip(thal_index_below) # flip to reverse order for i,v in enumerate(thal_index_below[:-1]): if conncomps_below[np.int(thal_index_below[i])] == conncomps_below[np.int(thal_index_below[i+1])]: if thal_index_below[i] <= thal_index_below[i+1]+10: thal_index_below[i] = 0 thal_index_below = thal_index_below[thal_index_below>0] thal_index_below = np.flip(thal_index_below) # save thalweg data pickle.dump([thal_index_above,thal_index_below],open('%s/thalwags_%s_%s.p' %(save_loc,name,years),'wb')) # make offsets length of above array (implicit assumption that it is longer) offsets = np.zeros_like(thal_index_above) # plot conncomps and thal_indexes if plot: y_above = np.zeros_like(thal_index_above) y_below = np.zeros_like(thal_index_below) y_above[:] = fault_loc-fzw y_below[:] = fault_loc+fzw plt.figure(figsize=(12,8)) plt.imshow(conncomps,cmap='nipy_spectral_r') plt.axhline(fault_loc+fzw,0,1000,color='k',linestyle='--',linewidth=1) plt.axhline(fault_loc-fzw,0,1000,color='k',linestyle='--',linewidth=1) plt.plot(thal_index_above,y_above,'k*',markersize=5) plt.plot(thal_index_below,y_below,'k*',markersize=5) plt.colorbar(shrink=0.62) plt.title('channel connected components') plt.savefig('%s/connected_channels_%s_%s.png' %(save_loc,name,years),dpi=600,transparent=True) #plt.show() plt.clf() ################################## ### calc offsets from channels ### ################################## # initialize array to store offset locs offset_locs = np.zeros(shape=(len(offsets),2)) # set up iterator for below array j = 0 # iterate through the above/longer dataset # THIS IS FOR LEFT LATERAL: if left: print('left-lateral implementation needs to be updated') # THIS IS FOR RIGHT LATERAL: else: # iterate through the above-fault thalwag index array for i,v in enumerate(thal_index_above): # if above is right of below AND above is same connected channel system if (thal_index_above[i] > thal_index_below[j]) & (conncomps_above[np.int(v)] == conncomps_below[np.int(thal_index_below[j])]): # record an offset measurement and it's location # offset is above index - below index (corrected for dx later) offsets[i] = thal_index_above[i] - thal_index_below[j] # offset location is above index, below index offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j] # then move the below iterator forward # check that we won't exceed the length of the below dataset when move iterator forward if (j+1) < len(thal_index_below): # move iterator forward for below dataset j+=1 # don't move below iterator forward at end of below array else: j=j # else if above is right of below AND above is NOT same connected channel system elif (thal_index_above[i] > thal_index_below[j]) & (conncomps_above[np.int(v)] != conncomps_below[np.int(thal_index_below[j])]): # don't record an offset # move below iterator forward b/c this is a beheaded/orphaned channel # check that we won't exceed the length of the below dataset when move iterator forward if (j+1) < len(thal_index_below): # move iterator forward for below dataset j=j+1 # check that we satisfy requirements for recording an offset with new J: if (thal_index_above[i] > thal_index_below[j]) & (conncomps_above[np.int(v)] == conncomps_below[np.int(thal_index_below[j])]): # record an offset measurement for i and just updated j and it's location # offset is above index - below index (corrected for dx later) offsets[i] = thal_index_above[i] - thal_index_below[j] # offset location is above index, below index offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j] # if we don't satisfy reqiurements for an offset with new J, move J up again and try again: elif (thal_index_above[i] > thal_index_below[j]) & (conncomps_above[np.int(v)] != conncomps_below[np.int(thal_index_below[j])]): j=j+1 # check satisfy requirements for offset with 2nd new J if (thal_index_above[i] > thal_index_below[j]) & (conncomps_above[np.int(v)] == conncomps_below[np.int(thal_index_below[j])]): # record an offset measurement for i and just updated j and it's location # offset is above index - below index (corrected for dx later) offsets[i] = thal_index_above[i] - thal_index_below[j] # offset location is above index, below index offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j] # don't move below iterator forward at end of below array else: j=j # else if above is left of below AND it's part of the same connected channel system as the previous below thalwag, then it's a valid offest (stream capture) elif (thal_index_above[i] < thal_index_below[j]) & (conncomps_above[np.int(v)] == conncomps_below[np.int(thal_index_below[j-1])]): # record an offset here with previous below index (this is a stream capture) # SOMEHOW FLAG THIS OFFSET AS A CAPTURE, MAYBE DON"T INCLUDE IN SOME ANALYSIS B/C LIKELY TO BE LARGE! offsets[i] = thal_index_above[i] - thal_index_below[j-1] # offset location is above index, previous below index offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j-1] # don't move below iterator forward b/c it's already on the channel system ahead(right) of the current above thalwag j=j # else if above is left of below AND it's NOT part of the same connected channel system as previous, it's an apparent left offset elif (thal_index_above[i] < thal_index_below[j]) & (conncomps_above[np.int(v)] != conncomps_below[np.int(thal_index_below[j-1])]): # record a negative offset to signify left lateral? then need to figure out how to deal with that in processing later on # don't move the below iterator forward b/c this is apparent left offset j=j print(offsets[i],offset_locs[i]) # print for debugging # remove zeros/nans # this captures and removes negative numbers offset_locs = offset_locs[offsets>0] # this turns it into 1 long array offset_locs = offset_locs.reshape(np.int(np.sum(offset_locs>0)/2),2) # reshape back to 2-column array offsets = offsets[offsets>0] # scale offsets by grid size offsets = offsets * dxy ######################## ### save offset data ### ######################## pickle.dump([offsets,offset_locs],open('%s/offsets_%s_%s.p' %(save_loc,name,years),'wb')) ################################ ### plot channels w/ offsets ### ################################ if plot: y_above = np.zeros_like(offsets) y_below = np.zeros_like(offsets) y_above[:] = fault_loc-fzw y_below[:] = fault_loc+fzw fig = plt.subplots(figsize=(12,8)) plt.imshow(da,cmap='Greys',vmin=0,vmax=1000) plt.imshow(channels,cmap='winter') # rainbow gives purple, raibow_r gives red plt.axhline(fault_loc+fzw,0,1000,color='r',linestyle='--') plt.axhline(fault_loc-fzw,0,1000,color='r',linestyle='--') plt.scatter(offset_locs[:,0],y_above)#c=offsets) plt.scatter(offset_locs[:,1],y_below)#c=offsets) plt.savefig('%s/channels_%s_%s.png' %(save_loc,name,years),dpi=600,facecolor=(1,1,1,0)) plt.show() plt.clf() ####################### ### calculate stats ### ####################### # calculate mean mean = np.round(np.mean(offsets),2) #print('mean: %s' %mean) # calculate rmse real_offsets = np.zeros_like(offsets) real_offsets[:]=real_max_slip rmse = np.round(np.sqrt(mean_squared_error(real_offsets, offsets)),2) #print('RMSE: %s' %rmse) # calculate standard deviation std = np.round(np.std(offsets),2) #print('StDev: %s' %std) # make PDFs offsets_sorted = np.sort(offsets) pdf = norm.pdf(offsets_sorted, mean, std) ####################### ### clean offsets?? ### ####################### if clean: # throw out outliers = any >or< than 2*std offsets_clean = np.copy(offsets) offsets_clean[offsets>(mean+2*std)] = np.nan offsets_clean[offsets_clean<(mean-2*std)] = np.nan # also save locations of the clean set of offsets --> ugh do later offset_locs_clean = np.copy(offset_locs) offset_locs_clean = offset_locs_clean[offsets_clean>0] # remove nan entries offsets_clean = offsets_clean[offsets_clean>0] # then recalculate stats # calculate mean mean_clean = np.round(np.mean(offsets_clean),2) #print('mean: %s' %mean) # calculate rmse real_offsets_clean = np.zeros_like(offsets_clean) real_offsets_clean[:]=real_max_slip rmse_clean = np.round(np.sqrt(mean_squared_error(real_offsets_clean, offsets_clean)),2) #print('RMSE: %s' %rmse) # calculate standard deviation std_clean = np.round(np.std(offsets_clean),2) #print('StDev: %s' %std) # make PDFs offsets_sorted_clean = np.sort(offsets_clean) pdf_clean = norm.pdf(offsets_sorted_clean, mean_clean, std_clean) ######################## ### plot offset data ### ######################## if plot: ########################### ### displacement vs fzw ### ########################### x = np.zeros_like(offsets) x[:] = fzw fig,ax = plt.subplots(figsize=(8,6)) plt.axhline(real_offsets[0],color='indianred',linestyle='--') plt.errorbar(x,offsets,yerr=std,lw=1,marker='o',linestyle=None,color='royalblue')#mfc='k', mec='black',ecolor='k' )#ms=4, mew=2) plt.plot(pdf+fzw, offsets_sorted,'-',color='royalblue') plt.fill_betweenx(offsets_sorted,fzw,pdf+fzw,alpha=.3,color='royalblue') plt.text(0.02,.95,'mean: %s'%mean,transform=ax.transAxes,color='royalblue') plt.text(0.02,.90,'RMSE: %s'%rmse,transform=ax.transAxes,color='royalblue') plt.text(0.02,.85,'std: %s'%std,transform=ax.transAxes,color='royalblue') if clean: x_clean = np.zeros_like(offsets_clean) x_clean[:] = fzw plt.errorbar(x_clean,offsets_clean,yerr=std_clean,lw=1,marker='o',linestyle=None,color='k')#mfc='k', mec='black',ecolor='k' )#ms=4, mew=2) plt.plot(pdf_clean+fzw, offsets_sorted_clean,ls='--',color='k') plt.fill_betweenx(offsets_sorted_clean,fzw,pdf_clean+fzw,linestyle='--',alpha=.3,color='k') plt.text(0.2,.95,'mean clean: %s'%mean_clean,transform=ax.transAxes) plt.text(0.2,.90,'RMSE clean: %s'%rmse_clean,transform=ax.transAxes) plt.text(0.2,.85,'std clean: %s'%std_clean,transform=ax.transAxes) plt.text(fzw-.45,real_max_slip+1,'actual offset',color='indianred') plt.xlim(fzw-.5,fzw+.5) plt.ylabel('apparent offset measurement (m)') plt.xlabel('fault zone width (m)') plt.savefig('%s/offsets_%s_%s.png'%(save_loc,name,years),dpi=450,facecolor=(1,1,1,0)) #plt.show() plt.clf() ################################# ### displacement along strike ### ################################# # x location of each offset is mean of above and below thalwag indices x = np.zeros_like(offsets) for i in range(len(offset_locs)): x[i] = (offset_locs[i,0]+offset_locs[i,1]) / 2. fig,ax = plt.subplots(figsize=(6,4)) plt.fill_between((0,1000),mean+std,mean-std,alpha=0.1,color='k') plt.axhline(real_offsets[0],color='indianred',linestyle='--',linewidth=1,label='real') plt.axhline(mean,color='k',linestyle='-.',linewidth=1,label='mean') plt.plot(x,offsets,'.') if clean: # this part isn't working all the way # x_clean = np.zeros_like(offsets_clean) # for i in range(len(offsets_clean)): # x_clean[i] = (offset_locs_clean[i,0]+offset_locs_clean[i,1]) / 2. # plt.fill_between(x,mean_clean+std_clean,mean_clean-std_clean,alpha=0.3,color='royalblue') plt.axhline(mean_clean,linestyle='-',linewidth=1,label='clean') plt.xticks((0,100,200,300,400,500,600,700,800,900,1000)) plt.yticks((0,5,10,15,20,25,30,35,40,45,50,55,60)) plt.xlabel('distance along strike (m)') plt.ylabel('apparent offset (m)') #plt.grid(which='both',color='lightgray',linewidth=.5,linestyle='--') plt.xlim(0,1000) plt.ylim(-3,60) plt.legend(loc='upper right',fontsize=10) plt.savefig('%s/offsets_along_strike_%s_%s.png' %(save_loc,name,years),dpi=300,facecolor=(1,1,1,0)) plt.show() return offsets, offset_locs, thal_index_above, thal_index_below #%% def for small offsets def measure_small_offsets(da_ascii,fzw,dxy,real_max_slip,name,save_loc,years=10000,channel_cutoff=1000,clean=False,left=False,plot=True): ''' function to measure offsets given an ascii file of drainage area. saves output as pngs, thalwags.p (thalwag indices), offsets.p (offset msrmts & locations) INPUTS: da_ascii = filename ending in .asc (ESCRI ASCII format) fzw = fault zone width dxy = grid pixel size real_max_slip = imposed total slip in model to evaluate how well auto method does name = string to name output data and figures years = years of simulation channel_cutoff = value of drainage area above which is a channel clean = whether or not to recalculate offset stats and pdf with outlier removed. not working right yet? left = is this a left-lateral fault? default=False for: no, it's right-lateral plot=True or False for plot & save figures or not save_loc = directory to save output in ''' ########################################### ### open drainage area and get channels ### ########################################### da = rio.open(da_ascii) da = da.read(1) ymax = np.shape(da)[0] fault_loc = np.int(ymax/2) # channels are da>1000 channels = np.copy(da) channels[channels<channel_cutoff] = np.nan channels[channels>=channel_cutoff] = 1000 ############################################# ### calc connected components on channels ### ############################################# conncomps = measure.label(channels, background=0, connectivity=2) conncomps_above = conncomps[fault_loc-(fzw),:] conncomps_below = conncomps[fault_loc+fzw,:] ############################################# ### extract subset from above/below fault ### ############################################# ### NOTICE SWITCH IN ABOVE BELOW +- B/C WEIRD INDEXING subset_above = channels[fault_loc-(fzw),:] subset_below = channels[fault_loc+fzw,:] # do binary thalwags arrays for yes/no thalwag/not thals_above = np.zeros_like(subset_above) thals_below = np.zeros_like(subset_below) for i,v in enumerate(subset_above): if subset_above[i]>=1000: thals_above[i] = 1 for i,v in enumerate(subset_below): if subset_below[i]>=1000: thals_below[i] = 1 # initiate offset array offsets = np.zeros_like(thals_above) # get a list of index,value for thals_below and above, then compare intervals = list(map(list, enumerate(thals_below))) # get list of [index,value] for item in intervals: item[0], item[1] = item[1], item[0] # swap index with value intervals = np.asarray(sorted(intervals),dtype=float) # sort by thalwag value low to high events = intervals[:][intervals[:,0]>0] # find indexs of thalwags/events thal_index_below = events[:,1] # get rid of events, keep only index column intervals = list(map(list, enumerate(thals_above))) # get list of [index,value] for item in intervals: item[0], item[1] = item[1], item[0] # swap index with value intervals = np.asarray(sorted(intervals),dtype=float) # sort by thalwag value low to high events = intervals[:][intervals[:,0]>0] # find indexs of thalwags/events thal_index_above = events[:,1] # get rid of events, keep only index column ### clean up thal_index to get rid of connected indices ### # could update this using connected components now # thal_index_above for i,v in enumerate(thal_index_above[:-1]): if v+1 == thal_index_above[i+1]: thal_index_above[i+1] = np.nan for i,v in enumerate(thal_index_above[:-2]): if v+2 == thal_index_above[i+2]: thal_index_above[i+2] = np.nan for i,v in enumerate(thal_index_above[:-3]): if v+3 == thal_index_above[i+3]: thal_index_above[i+3] = np.nan for i,v in enumerate(thal_index_above[:-4]): if v+4 == thal_index_above[i+4]: thal_index_above[i+4] = np.nan for i,v in enumerate(thal_index_above[:-5]): if v+5 == thal_index_above[i+5]: thal_index_above[i+5] = np.nan # thal_index_below for i,v in enumerate(thal_index_below[:-1]): if v+1 == thal_index_below[i+1]: thal_index_below[i+1] = np.nan for i,v in enumerate(thal_index_below[:-2]): if v+2 == thal_index_below[i+2]: thal_index_below[i+2] = np.nan for i,v in enumerate(thal_index_below[:-3]): if v+3 == thal_index_below[i+3]: thal_index_below[i+3] = np.nan for i,v in enumerate(thal_index_below[:-4]): if v+4 == thal_index_below[i+4]: thal_index_below[i+5] = np.nan for i,v in enumerate(thal_index_below[:-5]): if v+5 == thal_index_below[i+5]: thal_index_below[i+5] = np.nan # remove any nan entries thal_index_above = thal_index_above[thal_index_above>0] thal_index_below = thal_index_below[thal_index_below>0] # remove any thals in the below array that are part of the same channel system and close by thal_index_below = np.flip(thal_index_below) # flip to reverse order for i,v in enumerate(thal_index_below[:-1]): if conncomps_below[np.int(thal_index_below[i])] == conncomps_below[np.int(thal_index_below[i+1])]: if thal_index_below[i] <= thal_index_below[i+1]+10: thal_index_below[i] = 0 thal_index_below = thal_index_below[thal_index_below>0] thal_index_below = np.flip(thal_index_below) # save thalwag data pickle.dump([thal_index_above,thal_index_below],open('%s/thalwags_%s_%s.p' %(save_loc,name,years),'wb')) # make offsets length of above array (implicit assumption that it is longer) offsets = np.zeros_like(thal_index_above) # plot conncomps and thal_indexes if plot: y_above = np.zeros_like(thal_index_above) y_below = np.zeros_like(thal_index_below) y_above[:] = fault_loc-fzw y_below[:] = fault_loc+fzw plt.figure(figsize=(12,8)) plt.imshow(conncomps,cmap='nipy_spectral_r') plt.axhline(fault_loc+fzw,0,1000,color='k',linestyle='--',linewidth=1) plt.axhline(fault_loc-fzw,0,1000,color='k',linestyle='--',linewidth=1) plt.plot(thal_index_above,y_above,'k*',markersize=5) plt.plot(thal_index_below,y_below,'k*',markersize=5) plt.colorbar(shrink=0.62) plt.title('channel connected components') plt.savefig('%s/connected_channels_%s_%s.png' %(save_loc,name,years),dpi=600,transparent=True) #plt.show() plt.clf() ################################## ### calc offsets from channels ### ################################## # initialize array to store offset locs offset_locs = np.zeros(shape=(len(offsets),2)) # set up iterator for below array j = 0 # iterate through the above/longer dataset # iterate through the above-fault thalwag index array for i,v in enumerate(thal_index_above): # print(i,j) # print for debugging # if above and below are same connected channel system if conncomps_above[np.int(v)] == conncomps_below[np.int(thal_index_below[j])]: # print(i,j) # print for debug # record an offset measurement and it's location # offset is above index - below index (corrected for dx and right vs left lateral later) offsets[i] = thal_index_above[i] - thal_index_below[j] # offset location is above index, below index offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j] # then move the below iterator forward # check that we won't exceed the length of the below dataset when move iterator forward if (j+1) < len(thal_index_below): # move iterator forward for below dataset j=j+1 # don't move below iterator forward at end of below array else: j=j # if above and below are NOT same connected channel system elif conncomps_above[np.int(v)] != conncomps_below[np.int(thal_index_below[j])]: # check if above is same channel system as j-1 below: if (conncomps_above[np.int(v)] == conncomps_below[np.int(thal_index_below[j-1])]): # if so, record an offset # print(i,j-1) # print for debug offsets[i] = thal_index_above[i] - thal_index_below[j-1] offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j-1] j=j # if above is not same channel system as j-1, elif conncomps_above[np.int(v)] != conncomps_below[np.int(thal_index_below[j-1])] : # don't record an offset # move below iterator forward b/c it's beheaded channel # check that we won't exceed the length of the below dataset when move iterator forward if (j+1) < len(thal_index_below): j=j+1 if conncomps_above[np.int(v)] == conncomps_below[np.int(thal_index_below[j])]: # print(i,j) # print for debug offsets[i] = thal_index_above[i] - thal_index_below[j] offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j] elif conncomps_above[np.int(v)] != conncomps_below[np.int(thal_index_below[j])]: if (j+1) < len(thal_index_below): j=j+1 # print(i,j) # print for debug offsets[i] = thal_index_above[i] - thal_index_below[j] offset_locs[i,0],offset_locs[i,1] = thal_index_above[i], thal_index_below[j] # don't move iterator forward at end of below dataset else: j=j print(offsets[i],offset_locs[i]) # print for debugging # remove zeros/nans and implement left/right for positive/negative # THIS IS FOR LEFT LATERAL: if left: if slip == 0: offset_locs = offset_locs[offsets<=0] # this turns it into 1 long array offset_locs = offset_locs.reshape(np.int(np.sum(offset_locs>0)/2),2) # reshape back to 2-column array offsets = offsets[offsets<=0] else: offset_locs = offset_locs[offsets<0] # this turns it into 1 long array offset_locs = offset_locs.reshape(np.int(np.sum(offset_locs>0)/2),2) # reshape back to 2-column array offsets = offsets[offsets<0] offsets *= -1 # make them all positive # THIS IS FOR RIGHT LATERAL: else: if slip == 0: offset_locs = offset_locs[offsets>=0] # this turns it into 1 long array offset_locs = offset_locs.reshape(np.int(np.sum(offset_locs>0)/2),2) # reshape back to 2-column array offsets = offsets[offsets>=0] else: offset_locs = offset_locs[offsets>0] # this turns it into 1 long array offset_locs = offset_locs.reshape(np.int(np.sum(offset_locs>0)/2),2) # reshape back to 2-column array offsets = offsets[offsets>0] # scale offsets by grid size offsets = offsets * dxy ######################## ### save offset data ### ######################## pickle.dump([offsets,offset_locs],open('%s/offsets_%s_%s.p' %(save_loc,name,years),'wb')) ################################ ### plot channels w/ offsets ### ################################ if plot: y_above = np.zeros_like(offsets) y_below = np.zeros_like(offsets) y_above[:] = fault_loc-fzw y_below[:] = fault_loc+fzw fig = plt.subplots(figsize=(12,8)) plt.imshow(da,cmap='Greys',vmin=0,vmax=1000) plt.imshow(channels,cmap='winter') # rainbow gives purple, raibow_r gives red plt.axhline(fault_loc+fzw,0,1000,color='r',linestyle='--') plt.axhline(fault_loc-fzw,0,1000,color='r',linestyle='--') plt.scatter(offset_locs[:,0],y_above)#c=offsets) plt.scatter(offset_locs[:,1],y_below)#c=offsets) plt.savefig('%s/channels_%s_%s.png' %(save_loc,name,years),dpi=600,facecolor=(1,1,1,0)) plt.show() plt.clf() ####################### ### calculate stats ### ####################### # calculate mean mean = np.round(np.mean(offsets),2) #print('mean: %s' %mean) # calculate rmse real_offsets = np.zeros_like(offsets) real_offsets[:]=real_max_slip rmse = np.round(np.sqrt(mean_squared_error(real_offsets, offsets)),2) #print('RMSE: %s' %rmse) # calculate standard deviation std = np.round(np.std(offsets),2) #print('StDev: %s' %std) # make PDFs offsets_sorted = np.sort(offsets) pdf = norm.pdf(offsets_sorted, mean, std) ####################### ### clean offsets?? ### ####################### if clean: # throw out outliers = any >or< than 2*std offsets_clean = np.copy(offsets) offsets_clean[offsets>(mean+2*std)] = np.nan offsets_clean[offsets_clean<(mean-2*std)] = np.nan # also save locations of the clean set of offsets --> ugh do later offset_locs_clean = np.copy(offset_locs) offset_locs_clean = offset_locs_clean[offsets_clean>0] # remove nan entries offsets_clean = offsets_clean[offsets_clean>0] # then recalculate stats # calculate mean mean_clean = np.round(np.mean(offsets_clean),2) #print('mean: %s' %mean) # calculate rmse real_offsets_clean = np.zeros_like(offsets_clean) real_offsets_clean[:]=real_max_slip rmse_clean = np.round(np.sqrt(mean_squared_error(real_offsets_clean, offsets_clean)),2) #print('RMSE: %s' %rmse) # calculate standard deviation std_clean = np.round(np.std(offsets_clean),2) #print('StDev: %s' %std) # make PDFs offsets_sorted_clean = np.sort(offsets_clean) pdf_clean = norm.pdf(offsets_sorted_clean, mean_clean, std_clean) ######################## ### plot offset data ### ######################## if plot: ########################### ### displacement vs fzw ### ########################### x = np.zeros_like(offsets) x[:] = fzw fig,ax = plt.subplots(figsize=(8,6)) plt.axhline(real_offsets[0],color='indianred',linestyle='--') plt.errorbar(x,offsets,yerr=std,lw=1,marker='o',linestyle=None,color='royalblue')#mfc='k', mec='black',ecolor='k' )#ms=4, mew=2) plt.plot(pdf+fzw, offsets_sorted,'-',color='royalblue') plt.fill_betweenx(offsets_sorted,fzw,pdf+fzw,alpha=.3,color='royalblue') plt.text(0.02,.95,'mean: %s'%mean,transform=ax.transAxes,color='royalblue') plt.text(0.02,.90,'RMSE: %s'%rmse,transform=ax.transAxes,color='royalblue') plt.text(0.02,.85,'std: %s'%std,transform=ax.transAxes,color='royalblue') if clean: x_clean = np.zeros_like(offsets_clean) x_clean[:] = fzw #plt.plot(x_clean,offsets_clean,'o',color='seagreen') plt.errorbar(x_clean,offsets_clean,yerr=std_clean,lw=1,marker='o',linestyle=None,color='k')#mfc='k', mec='black',ecolor='k' )#ms=4, mew=2) plt.plot(pdf_clean+fzw, offsets_sorted_clean,ls='--',color='k') plt.fill_betweenx(offsets_sorted_clean,fzw,pdf_clean+fzw,linestyle='--',alpha=.3,color='k') plt.text(0.2,.95,'mean clean: %s'%mean_clean,transform=ax.transAxes) plt.text(0.2,.90,'RMSE clean: %s'%rmse_clean,transform=ax.transAxes) plt.text(0.2,.85,'std clean: %s'%std_clean,transform=ax.transAxes) plt.text(fzw-.45,real_max_slip+1,'actual offset',color='indianred') plt.xlim(fzw-.5,fzw+.5) plt.ylabel('apparent offset measurement (m)') plt.xlabel('fault zone width (m)') plt.savefig('%s/offsets_%s_%s.png'%(save_loc,name,years),dpi=450,facecolor=(1,1,1,0)) #plt.show() plt.clf() ################################# ### displacement along strike ### ################################# # x location of each offset is mean of above and below thalwag indices x = np.zeros_like(offsets) for i in range(len(offset_locs)): x[i] = (offset_locs[i,0]+offset_locs[i,1]) / 2. fig,ax = plt.subplots(figsize=(6,4)) plt.fill_between((0,1000),mean+std,mean-std,alpha=0.1,color='k') plt.axhline(real_offsets[0],color='indianred',linestyle='--',linewidth=1,label='real') plt.axhline(mean,color='k',linestyle='-.',linewidth=1,label='mean') plt.plot(x,offsets,'.') if clean: plt.axhline(mean_clean,linestyle='-',linewidth=1,label='clean') plt.xticks((0,100,200,300,400,500,600,700,800,900,1000)) plt.yticks((0,5,10,15,20,25,30,35,40,45,50,55,60)) plt.xlabel('distance along strike (m)') plt.ylabel('apparent offset (m)') #plt.grid(which='both',color='lightgray',linewidth=.5,linestyle='--') plt.xlim(0,1000) plt.ylim(-3,60) plt.legend(loc='upper right',fontsize=10) plt.savefig('%s/offsets_along_strike_%s_%s.png' %(save_loc,name,years),dpi=300,facecolor=(1,1,1,0)) plt.show() return offsets, offset_locs, thal_index_above, thal_index_below #%% run for 1 model - measure_offsets # load parameter configuration from config.yaml file - yaml not playing nice with gdal #config = yaml.load(open('config_files/config.yaml','r')) # use this to run fron config/here #config = yaml.load(open(sys.argv[1],'r')) # use this line to read file from command line #model_name = config['saving']['model_name'] # model name for naming outputs - ztopo, avgZ, displacement, movie #dxy = config['grid']['dxy'] # grid step in meters #total_slip = config['strike-slip']['total_slip'] # total slip for entire model time [meters] #tmax = config['time']['tmax'] # total time in years model_name = 'fzw0' dxy = 1 total_slip = 30 tmax = 10000 output_loc = 'model_output/%s' %model_name # location to save output da_ascii = '%s/da_%s.asc' %(output_loc,model_name) profile_distance = 10 # number of meters away from fault on either side to measure thalweg offset distances cutoff = 1000 # drainage area threshold plot=True clean=True # this is for plotting purposes only! offsets, offset_locs, thal_index_above, thal_index_below = measure_offsets(da_ascii,profile_distance,dxy,total_slip,model_name,save_loc=output_loc,years=tmax,channel_cutoff=cutoff,clean=clean,plot=plot)

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fddb1a0516bca51c609914c26662e08ea5fc1cbe

31,907

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Python

20201129-pyconchina/typeschema_parser.py

thautwarm/Slides

f88832c1dcc38b9a7afdbb2986515c9a58d2b077

[ "MIT" ]

1

2019-08-26T22:50:19.000Z

20201129-pyconchina/typeschema_parser.py

thautwarm/Slides

f88832c1dcc38b9a7afdbb2986515c9a58d2b077

[ "MIT" ]

1

2019-08-26T04:44:54.000Z

2019-08-26T07:28:53.000Z

20201129-pyconchina/typeschema_parser.py

thautwarm/Slides

f88832c1dcc38b9a7afdbb2986515c9a58d2b077

[ "MIT" ]

null

""" Copyright thautwarm (c) 2019 All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of thautwarm nor the names of other contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ from typeschema import * from typing import Generic, TypeVar T = TypeVar('T') class Tokens(): __slots__ = ['array', 'offset'] def __init__(self, array): self.array = array self.offset = 0 class State(): def __init__(self): pass class AST(Generic[T]): __slots__ = ['tag', 'contents'] def __init__(self, tag: str, contents: T): self.tag = tag self.contents = contents class Nil(): nil = None __slots__ = [] def __init__(self): if (Nil.nil is None): Nil.nil = self return raise ValueError('Nil cannot get instantiated twice.') def __len__(self): return 0 def __getitem__(self, n): raise IndexError('Out of bounds') @property def head(self): raise IndexError('Out of bounds') @property def tail(self): raise IndexError('Out of bounds') def __repr__(self): return '[]' _nil = Nil() class Cons(): __slots__ = ['head', 'tail'] def __init__(self, _head, _tail): self.head = _head self.tail = _tail def __len__(self): nil = _nil l = 0 while (self is not nil): l += 1 self = self.tail return l def __iter__(self): nil = _nil while (self is not nil): (yield self.head) self = self.tail def __getitem__(self, n): while (n != 0): self = self.tail n -= 1 return self.head def __repr__(self): return repr(list(self)) try: def mk_pretty(): from prettyprinter import register_pretty, pretty_call, pprint @register_pretty(Tokens) def pretty_tokens(value, ctx): return pretty_call(ctx, Tokens, offset=value.offset, array=value.array) @register_pretty(AST) def pretty_ast(value, ctx): return pretty_call(ctx, AST, tag=value.tag, contents=value.contents) mk_pretty() del mk_pretty except ImportError: pass del T, Generic, TypeVar builtin_cons = Cons builtin_nil = _nil builtin_mk_ast = AST def mk_parser(): pass def rbnf_named_lr_step_rbnfmacro_0(rbnf_tmp_0, builtin_state, builtin_tokens): lcl_0 = rbnf_named_parse_classdef(builtin_state, builtin_tokens) rbnf_named__check_1 = lcl_0 lcl_0 = rbnf_named__check_1[0] lcl_0 = (lcl_0 == False) if lcl_0: lcl_0 = rbnf_named__check_1 else: lcl_1 = rbnf_named__check_1[1] rbnf_tmp_1 = lcl_1 lcl_1 = rbnf_tmp_0.append lcl_1 = lcl_1(rbnf_tmp_1) rbnf_tmp_1_ = rbnf_tmp_0 lcl_2 = (True, rbnf_tmp_1_) lcl_0 = lcl_2 return lcl_0 def rbnf_named_lr_loop_rbnfmacro_0(rbnf_tmp_0, builtin_state, builtin_tokens): rbnf_named_lr_rbnfmacro_0_reduce = rbnf_tmp_0 lcl_0 = builtin_tokens.offset rbnf_named__off_0 = lcl_0 lcl_0 = rbnf_named_lr_step_rbnfmacro_0(rbnf_named_lr_rbnfmacro_0_reduce, builtin_state, builtin_tokens) rbnf_named_lr_rbnfmacro_0_try = lcl_0 lcl_0 = rbnf_named_lr_rbnfmacro_0_try[0] lcl_0 = (lcl_0 is not False) while lcl_0: lcl_1 = builtin_tokens.offset rbnf_named__off_0 = lcl_1 lcl_1 = rbnf_named_lr_rbnfmacro_0_try[1] rbnf_named_lr_rbnfmacro_0_reduce = lcl_1 lcl_1 = rbnf_named_lr_step_rbnfmacro_0(rbnf_named_lr_rbnfmacro_0_reduce, builtin_state, builtin_tokens) rbnf_named_lr_rbnfmacro_0_try = lcl_1 lcl_1 = rbnf_named_lr_rbnfmacro_0_try[0] lcl_1 = (lcl_1 is not False) lcl_0 = lcl_1 lcl_0 = builtin_tokens.offset lcl_0 = (lcl_0 == rbnf_named__off_0) if lcl_0: lcl_1 = (True, rbnf_named_lr_rbnfmacro_0_reduce) lcl_0 = lcl_1 else: lcl_0 = rbnf_named_lr_rbnfmacro_0_try return lcl_0 def rbnf_named_lr_step_rbnfmacro_1(rbnf_tmp_0, builtin_state, builtin_tokens): try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 6): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_0 = _rbnf_cur_token rbnf_tmp_1 = lcl_0 lcl_0 = (rbnf_tmp_1 is None) if lcl_0: lcl_1 = builtin_tokens.offset lcl_1 = (lcl_1, 'quote , not match') lcl_1 = builtin_cons(lcl_1, builtin_nil) lcl_1 = (False, lcl_1) lcl_0 = lcl_1 else: lcl_1 = rbnf_named_parse_fieldef(builtin_state, builtin_tokens) rbnf_named__check_2 = lcl_1 lcl_1 = rbnf_named__check_2[0] lcl_1 = (lcl_1 == False) if lcl_1: lcl_1 = rbnf_named__check_2 else: lcl_2 = rbnf_named__check_2[1] rbnf_tmp_2 = lcl_2 lcl_2 = rbnf_tmp_0.append lcl_2 = lcl_2(rbnf_tmp_2) rbnf_tmp_1_ = rbnf_tmp_0 lcl_3 = (True, rbnf_tmp_1_) lcl_1 = lcl_3 lcl_0 = lcl_1 return lcl_0 def rbnf_named_lr_loop_rbnfmacro_1(rbnf_tmp_0, builtin_state, builtin_tokens): rbnf_named_lr_rbnfmacro_1_reduce = rbnf_tmp_0 lcl_0 = builtin_tokens.offset rbnf_named__off_0 = lcl_0 lcl_0 = rbnf_named_lr_step_rbnfmacro_1(rbnf_named_lr_rbnfmacro_1_reduce, builtin_state, builtin_tokens) rbnf_named_lr_rbnfmacro_1_try = lcl_0 lcl_0 = rbnf_named_lr_rbnfmacro_1_try[0] lcl_0 = (lcl_0 is not False) while lcl_0: lcl_1 = builtin_tokens.offset rbnf_named__off_0 = lcl_1 lcl_1 = rbnf_named_lr_rbnfmacro_1_try[1] rbnf_named_lr_rbnfmacro_1_reduce = lcl_1 lcl_1 = rbnf_named_lr_step_rbnfmacro_1(rbnf_named_lr_rbnfmacro_1_reduce, builtin_state, builtin_tokens) rbnf_named_lr_rbnfmacro_1_try = lcl_1 lcl_1 = rbnf_named_lr_rbnfmacro_1_try[0] lcl_1 = (lcl_1 is not False) lcl_0 = lcl_1 lcl_0 = builtin_tokens.offset lcl_0 = (lcl_0 == rbnf_named__off_0) if lcl_0: lcl_1 = (True, rbnf_named_lr_rbnfmacro_1_reduce) lcl_0 = lcl_1 else: lcl_0 = rbnf_named_lr_rbnfmacro_1_try return lcl_0 def rbnf_named_lr_step_rbnfmacro_2(rbnf_tmp_0, builtin_state, builtin_tokens): try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 6): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_0 = _rbnf_cur_token rbnf_tmp_1 = lcl_0 lcl_0 = (rbnf_tmp_1 is None) if lcl_0: lcl_1 = builtin_tokens.offset lcl_1 = (lcl_1, 'quote , not match') lcl_1 = builtin_cons(lcl_1, builtin_nil) lcl_1 = (False, lcl_1) lcl_0 = lcl_1 else: lcl_1 = rbnf_named_parse_type(builtin_state, builtin_tokens) rbnf_named__check_2 = lcl_1 lcl_1 = rbnf_named__check_2[0] lcl_1 = (lcl_1 == False) if lcl_1: lcl_1 = rbnf_named__check_2 else: lcl_2 = rbnf_named__check_2[1] rbnf_tmp_2 = lcl_2 lcl_2 = rbnf_tmp_0.append lcl_2 = lcl_2(rbnf_tmp_2) rbnf_tmp_1_ = rbnf_tmp_0 lcl_3 = (True, rbnf_tmp_1_) lcl_1 = lcl_3 lcl_0 = lcl_1 return lcl_0 def rbnf_named_lr_loop_rbnfmacro_2(rbnf_tmp_0, builtin_state, builtin_tokens): rbnf_named_lr_rbnfmacro_2_reduce = rbnf_tmp_0 lcl_0 = builtin_tokens.offset rbnf_named__off_0 = lcl_0 lcl_0 = rbnf_named_lr_step_rbnfmacro_2(rbnf_named_lr_rbnfmacro_2_reduce, builtin_state, builtin_tokens) rbnf_named_lr_rbnfmacro_2_try = lcl_0 lcl_0 = rbnf_named_lr_rbnfmacro_2_try[0] lcl_0 = (lcl_0 is not False) while lcl_0: lcl_1 = builtin_tokens.offset rbnf_named__off_0 = lcl_1 lcl_1 = rbnf_named_lr_rbnfmacro_2_try[1] rbnf_named_lr_rbnfmacro_2_reduce = lcl_1 lcl_1 = rbnf_named_lr_step_rbnfmacro_2(rbnf_named_lr_rbnfmacro_2_reduce, builtin_state, builtin_tokens) rbnf_named_lr_rbnfmacro_2_try = lcl_1 lcl_1 = rbnf_named_lr_rbnfmacro_2_try[0] lcl_1 = (lcl_1 is not False) lcl_0 = lcl_1 lcl_0 = builtin_tokens.offset lcl_0 = (lcl_0 == rbnf_named__off_0) if lcl_0: lcl_1 = (True, rbnf_named_lr_rbnfmacro_2_reduce) lcl_0 = lcl_1 else: lcl_0 = rbnf_named_lr_rbnfmacro_2_try return lcl_0 def rbnf_named_parse_START(builtin_state, builtin_tokens): try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 0): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_0 = _rbnf_cur_token rbnf_tmp_0 = lcl_0 lcl_0 = (rbnf_tmp_0 is None) if lcl_0: lcl_1 = builtin_tokens.offset lcl_1 = (lcl_1, 'BOF not match') lcl_1 = builtin_cons(lcl_1, builtin_nil) lcl_1 = (False, lcl_1) lcl_0 = lcl_1 else: try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 1): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_1 = _rbnf_cur_token rbnf_tmp_1 = lcl_1 lcl_1 = (rbnf_tmp_1 is None) if lcl_1: lcl_2 = builtin_tokens.offset lcl_2 = (lcl_2, 'quote backend not match') lcl_2 = builtin_cons(lcl_2, builtin_nil) lcl_2 = (False, lcl_2) lcl_1 = lcl_2 else: try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 2): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_2 = _rbnf_cur_token rbnf_tmp_2 = lcl_2 lcl_2 = (rbnf_tmp_2 is None) if lcl_2: lcl_3 = builtin_tokens.offset lcl_3 = (lcl_3, 'Ident not match') lcl_3 = builtin_cons(lcl_3, builtin_nil) lcl_3 = (False, lcl_3) lcl_2 = lcl_3 else: lcl_3 = rbnf_named_parse_typeschema(builtin_state, builtin_tokens) rbnf_named__check_3 = lcl_3 lcl_3 = rbnf_named__check_3[0] lcl_3 = (lcl_3 == False) if lcl_3: lcl_3 = rbnf_named__check_3 else: lcl_4 = rbnf_named__check_3[1] rbnf_tmp_3 = lcl_4 try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 3): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_4 = _rbnf_cur_token rbnf_tmp_4 = lcl_4 lcl_4 = (rbnf_tmp_4 is None) if lcl_4: lcl_5 = builtin_tokens.offset lcl_5 = (lcl_5, 'EOF not match') lcl_5 = builtin_cons(lcl_5, builtin_nil) lcl_5 = (False, lcl_5) lcl_4 = lcl_5 else: lcl_5 = rbnf_tmp_2.value lcl_5 = (lcl_5, rbnf_tmp_3) rbnf_tmp_1_ = lcl_5 lcl_5 = (True, rbnf_tmp_1_) lcl_4 = lcl_5 lcl_3 = lcl_4 lcl_2 = lcl_3 lcl_1 = lcl_2 lcl_0 = lcl_1 return lcl_0 def rbnf_named_parse_classdef(builtin_state, builtin_tokens): try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 7): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_0 = _rbnf_cur_token rbnf_tmp_0 = lcl_0 lcl_0 = (rbnf_tmp_0 is None) if lcl_0: lcl_1 = builtin_tokens.offset lcl_1 = (lcl_1, 'quote | not match') lcl_1 = builtin_cons(lcl_1, builtin_nil) lcl_1 = (False, lcl_1) lcl_0 = lcl_1 else: try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 2): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_1 = _rbnf_cur_token rbnf_tmp_1 = lcl_1 lcl_1 = (rbnf_tmp_1 is None) if lcl_1: lcl_2 = builtin_tokens.offset lcl_2 = (lcl_2, 'Ident not match') lcl_2 = builtin_cons(lcl_2, builtin_nil) lcl_2 = (False, lcl_2) lcl_1 = lcl_2 else: try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 8): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_2 = _rbnf_cur_token rbnf_tmp_2 = lcl_2 lcl_2 = (rbnf_tmp_2 is None) if lcl_2: lcl_3 = builtin_tokens.offset lcl_3 = (lcl_3, 'quote ( not match') lcl_3 = builtin_cons(lcl_3, builtin_nil) lcl_3 = (False, lcl_3) lcl_2 = lcl_3 else: lcl_3 = rbnf_named_parse_rbnfmacro_1(builtin_state, builtin_tokens) rbnf_named__check_3 = lcl_3 lcl_3 = rbnf_named__check_3[0] lcl_3 = (lcl_3 == False) if lcl_3: lcl_3 = rbnf_named__check_3 else: lcl_4 = rbnf_named__check_3[1] rbnf_tmp_3 = lcl_4 try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 9): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_4 = _rbnf_cur_token rbnf_tmp_4 = lcl_4 lcl_4 = (rbnf_tmp_4 is None) if lcl_4: lcl_5 = builtin_tokens.offset lcl_5 = (lcl_5, 'quote ) not match') lcl_5 = builtin_cons(lcl_5, builtin_nil) lcl_5 = (False, lcl_5) lcl_4 = lcl_5 else: lcl_5 = rbnf_tmp_1.value lcl_5 = CaseTypeDef(lcl_5, rbnf_tmp_3) rbnf_tmp_1_ = lcl_5 lcl_5 = (True, rbnf_tmp_1_) lcl_4 = lcl_5 lcl_3 = lcl_4 lcl_2 = lcl_3 lcl_1 = lcl_2 lcl_0 = lcl_1 return lcl_0 def rbnf_named_parse_fieldef(builtin_state, builtin_tokens): lcl_0 = builtin_tokens.offset rbnf_named__off_0 = lcl_0 try: builtin_tokens.array[(builtin_tokens.offset + 0)] _rbnf_peek_tmp = True except IndexError: _rbnf_peek_tmp = False lcl_0 = _rbnf_peek_tmp if lcl_0: lcl_2 = builtin_tokens.array[(builtin_tokens.offset + 0)] lcl_2 = lcl_2.idint if (lcl_2 == 2): lcl_3 = builtin_tokens.offset rbnf_named__off_1 = lcl_3 try: builtin_tokens.array[(builtin_tokens.offset + 1)] _rbnf_peek_tmp = True except IndexError: _rbnf_peek_tmp = False lcl_3 = _rbnf_peek_tmp if lcl_3: lcl_5 = builtin_tokens.array[(builtin_tokens.offset + 1)] lcl_5 = lcl_5.idint if (lcl_5 == 11): lcl_6 = rbnf_named_parse_type(builtin_state, builtin_tokens) rbnf_named__check_0 = lcl_6 lcl_6 = rbnf_named__check_0[0] lcl_6 = (lcl_6 == False) if lcl_6: lcl_6 = rbnf_named__check_0 else: lcl_7 = rbnf_named__check_0[1] rbnf_tmp_0 = lcl_7 lcl_7 = FieldDef(None, rbnf_tmp_0) rbnf_tmp_1_ = lcl_7 lcl_7 = (True, rbnf_tmp_1_) lcl_6 = lcl_7 lcl_4 = lcl_6 elif (lcl_5 == 10): _rbnf_old_offset = builtin_tokens.offset _rbnf_cur_token = builtin_tokens.array[_rbnf_old_offset] builtin_tokens.offset = (_rbnf_old_offset + 1) lcl_6 = _rbnf_cur_token rbnf_tmp_0 = lcl_6 _rbnf_old_offset = builtin_tokens.offset _rbnf_cur_token = builtin_tokens.array[_rbnf_old_offset] builtin_tokens.offset = (_rbnf_old_offset + 1) lcl_6 = _rbnf_cur_token rbnf_tmp_1 = lcl_6 lcl_6 = rbnf_named_parse_type(builtin_state, builtin_tokens) rbnf_named__check_2 = lcl_6 lcl_6 = rbnf_named__check_2[0] lcl_6 = (lcl_6 == False) if lcl_6: lcl_6 = rbnf_named__check_2 else: lcl_7 = rbnf_named__check_2[1] rbnf_tmp_2 = lcl_7 lcl_7 = rbnf_tmp_0.value lcl_7 = FieldDef(lcl_7, rbnf_tmp_2) rbnf_tmp_1_ = lcl_7 lcl_7 = (True, rbnf_tmp_1_) lcl_6 = lcl_7 lcl_4 = lcl_6 else: lcl_6 = rbnf_named_parse_type(builtin_state, builtin_tokens) rbnf_named__check_0 = lcl_6 lcl_6 = rbnf_named__check_0[0] lcl_6 = (lcl_6 == False) if lcl_6: lcl_6 = rbnf_named__check_0 else: lcl_7 = rbnf_named__check_0[1] rbnf_tmp_0 = lcl_7 lcl_7 = FieldDef(None, rbnf_tmp_0) rbnf_tmp_1_ = lcl_7 lcl_7 = (True, rbnf_tmp_1_) lcl_6 = lcl_7 lcl_4 = lcl_6 lcl_3 = lcl_4 else: lcl_4 = (rbnf_named__off_1, 'fieldef got EOF') lcl_4 = builtin_cons(lcl_4, builtin_nil) lcl_4 = (False, lcl_4) lcl_3 = lcl_4 lcl_1 = lcl_3 else: lcl_3 = (rbnf_named__off_0, 'fieldef lookahead failed') lcl_3 = builtin_cons(lcl_3, builtin_nil) lcl_3 = (False, lcl_3) lcl_1 = lcl_3 lcl_0 = lcl_1 else: lcl_1 = (rbnf_named__off_0, 'fieldef got EOF') lcl_1 = builtin_cons(lcl_1, builtin_nil) lcl_1 = (False, lcl_1) lcl_0 = lcl_1 return lcl_0 def rbnf_named_parse_rbnfmacro_0(builtin_state, builtin_tokens): lcl_0 = rbnf_named_parse_classdef(builtin_state, builtin_tokens) rbnf_named__check_0 = lcl_0 lcl_0 = rbnf_named__check_0[0] lcl_0 = (lcl_0 == False) if lcl_0: lcl_0 = rbnf_named__check_0 else: lcl_1 = rbnf_named__check_0[1] rbnf_tmp_0 = lcl_1 lcl_1 = [] _rbnf_immediate_lst = lcl_1 _rbnf_immediate_lst.append(rbnf_tmp_0) lcl_1 = _rbnf_immediate_lst rbnf_tmp_1_ = lcl_1 lcl_1 = rbnf_named_lr_loop_rbnfmacro_0(rbnf_tmp_1_, builtin_state, builtin_tokens) lcl_0 = lcl_1 return lcl_0 def rbnf_named_parse_rbnfmacro_1(builtin_state, builtin_tokens): lcl_0 = rbnf_named_parse_fieldef(builtin_state, builtin_tokens) rbnf_named__check_0 = lcl_0 lcl_0 = rbnf_named__check_0[0] lcl_0 = (lcl_0 == False) if lcl_0: lcl_0 = rbnf_named__check_0 else: lcl_1 = rbnf_named__check_0[1] rbnf_tmp_0 = lcl_1 lcl_1 = [] _rbnf_immediate_lst = lcl_1 _rbnf_immediate_lst.append(rbnf_tmp_0) lcl_1 = _rbnf_immediate_lst rbnf_tmp_1_ = lcl_1 lcl_1 = rbnf_named_lr_loop_rbnfmacro_1(rbnf_tmp_1_, builtin_state, builtin_tokens) lcl_0 = lcl_1 return lcl_0 def rbnf_named_parse_rbnfmacro_2(builtin_state, builtin_tokens): lcl_0 = rbnf_named_parse_type(builtin_state, builtin_tokens) rbnf_named__check_0 = lcl_0 lcl_0 = rbnf_named__check_0[0] lcl_0 = (lcl_0 == False) if lcl_0: lcl_0 = rbnf_named__check_0 else: lcl_1 = rbnf_named__check_0[1] rbnf_tmp_0 = lcl_1 lcl_1 = [] _rbnf_immediate_lst = lcl_1 _rbnf_immediate_lst.append(rbnf_tmp_0) lcl_1 = _rbnf_immediate_lst rbnf_tmp_1_ = lcl_1 lcl_1 = rbnf_named_lr_loop_rbnfmacro_2(rbnf_tmp_1_, builtin_state, builtin_tokens) lcl_0 = lcl_1 return lcl_0 def rbnf_named_parse_type(builtin_state, builtin_tokens): try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 2): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_0 = _rbnf_cur_token rbnf_tmp_0 = lcl_0 lcl_0 = (rbnf_tmp_0 is None) if lcl_0: lcl_1 = builtin_tokens.offset lcl_1 = (lcl_1, 'Ident not match') lcl_1 = builtin_cons(lcl_1, builtin_nil) lcl_1 = (False, lcl_1) lcl_0 = lcl_1 else: lcl_1 = builtin_tokens.offset rbnf_named__off_1 = lcl_1 try: builtin_tokens.array[(builtin_tokens.offset + 0)] _rbnf_peek_tmp = True except IndexError: _rbnf_peek_tmp = False lcl_1 = _rbnf_peek_tmp if lcl_1: lcl_3 = builtin_tokens.array[(builtin_tokens.offset + 0)] lcl_3 = lcl_3.idint if (lcl_3 == 11): _rbnf_old_offset = builtin_tokens.offset _rbnf_cur_token = builtin_tokens.array[_rbnf_old_offset] builtin_tokens.offset = (_rbnf_old_offset + 1) lcl_4 = _rbnf_cur_token rbnf_tmp_1 = lcl_4 lcl_4 = rbnf_named_parse_rbnfmacro_2(builtin_state, builtin_tokens) rbnf_named__check_2 = lcl_4 lcl_4 = rbnf_named__check_2[0] lcl_4 = (lcl_4 == False) if lcl_4: lcl_4 = rbnf_named__check_2 else: lcl_5 = rbnf_named__check_2[1] rbnf_tmp_2 = lcl_5 try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 12): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_5 = _rbnf_cur_token rbnf_tmp_3 = lcl_5 lcl_5 = (rbnf_tmp_3 is None) if lcl_5: lcl_6 = builtin_tokens.offset lcl_6 = (lcl_6, 'quote ] not match') lcl_6 = builtin_cons(lcl_6, builtin_nil) lcl_6 = (False, lcl_6) lcl_5 = lcl_6 else: lcl_6 = rbnf_tmp_0.value lcl_6 = Typ(lcl_6, rbnf_tmp_2) rbnf_tmp_1_ = lcl_6 lcl_6 = (True, rbnf_tmp_1_) lcl_5 = lcl_6 lcl_4 = lcl_5 lcl_2 = lcl_4 else: lcl_4 = rbnf_tmp_0.value lcl_5 = [] lcl_4 = Typ(lcl_4, lcl_5) rbnf_tmp_1_ = lcl_4 lcl_4 = (True, rbnf_tmp_1_) lcl_2 = lcl_4 lcl_1 = lcl_2 else: lcl_2 = (rbnf_named__off_1, 'type got EOF') lcl_2 = builtin_cons(lcl_2, builtin_nil) lcl_2 = (False, lcl_2) lcl_1 = lcl_2 lcl_0 = lcl_1 return lcl_0 def rbnf_named_parse_typeschema(builtin_state, builtin_tokens): try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 4): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_0 = _rbnf_cur_token rbnf_tmp_0 = lcl_0 lcl_0 = (rbnf_tmp_0 is None) if lcl_0: lcl_1 = builtin_tokens.offset lcl_1 = (lcl_1, 'quote type not match') lcl_1 = builtin_cons(lcl_1, builtin_nil) lcl_1 = (False, lcl_1) lcl_0 = lcl_1 else: try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 2): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_1 = _rbnf_cur_token rbnf_tmp_1 = lcl_1 lcl_1 = (rbnf_tmp_1 is None) if lcl_1: lcl_2 = builtin_tokens.offset lcl_2 = (lcl_2, 'Ident not match') lcl_2 = builtin_cons(lcl_2, builtin_nil) lcl_2 = (False, lcl_2) lcl_1 = lcl_2 else: try: _rbnf_cur_token = builtin_tokens.array[builtin_tokens.offset] if (_rbnf_cur_token.idint is 5): builtin_tokens.offset += 1 else: _rbnf_cur_token = None except IndexError: _rbnf_cur_token = None lcl_2 = _rbnf_cur_token rbnf_tmp_2 = lcl_2 lcl_2 = (rbnf_tmp_2 is None) if lcl_2: lcl_3 = builtin_tokens.offset lcl_3 = (lcl_3, 'quote = not match') lcl_3 = builtin_cons(lcl_3, builtin_nil) lcl_3 = (False, lcl_3) lcl_2 = lcl_3 else: lcl_3 = rbnf_named_parse_rbnfmacro_0(builtin_state, builtin_tokens) rbnf_named__check_3 = lcl_3 lcl_3 = rbnf_named__check_3[0] lcl_3 = (lcl_3 == False) if lcl_3: lcl_3 = rbnf_named__check_3 else: lcl_4 = rbnf_named__check_3[1] rbnf_tmp_3 = lcl_4 lcl_4 = rbnf_tmp_1.value lcl_4 = TypeSchema(lcl_4, rbnf_tmp_3) rbnf_tmp_1_ = lcl_4 lcl_4 = (True, rbnf_tmp_1_) lcl_3 = lcl_4 lcl_2 = lcl_3 lcl_1 = lcl_2 lcl_0 = lcl_1 return lcl_0 return rbnf_named_parse_START

39.342787

115

0.521077

4,005

31,907

3.63995

0.057678

0.046097

0.066676

0.061737

0.834545

0.813966

0.796749

0.768212

0.746193

0.720949

0

0.05038

0.423324

31,907

811

116

39.342787

0.741902

0.04745

0

0.728378

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0.013823

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0.043243

false

0.004054

0.005405

0.006757

0.093243

0.001351

0

null

0

1

0

1

0

null

0

7

fdfab47b70fbebb647a8811ec4c49cc974e7d2a0

2,138

py

Python

resource/lib/python2.7/site-packages/pyasn1/type/char.py

claudiopastorini/geofire-python

274e1b1d733a1158e4f36de40f0349dbc1ff6c34

[ "MIT" ]

1,346

2015-01-01T14:52:24.000Z

2022-03-28T12:50:48.000Z

resource/lib/python2.7/site-packages/pyasn1/type/char.py

claudiopastorini/geofire-python

274e1b1d733a1158e4f36de40f0349dbc1ff6c34

[ "MIT" ]

474

2015-01-01T10:27:46.000Z

2022-03-21T12:26:16.000Z

resource/lib/python2.7/site-packages/pyasn1/type/char.py

claudiopastorini/geofire-python

274e1b1d733a1158e4f36de40f0349dbc1ff6c34

[ "MIT" ]

191

2015-01-02T18:27:22.000Z

2022-03-29T10:49:48.000Z

# # This file is part of pyasn1 software. # # Copyright (c) 2005-2017, Ilya Etingof <etingof@gmail.com> # License: http://pyasn1.sf.net/license.html # from pyasn1.type import univ, tag class NumericString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 18) ) class PrintableString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 19) ) class TeletexString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 20) ) class T61String(TeletexString): pass class VideotexString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 21) ) class IA5String(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 22) ) class GraphicString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 25) ) class VisibleString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 26) ) class ISO646String(VisibleString): pass class GeneralString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 27) ) class UniversalString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 28) ) encoding = "utf-32-be" class BMPString(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 30) ) encoding = "utf-16-be" class UTF8String(univ.OctetString): tagSet = univ.OctetString.tagSet.tagImplicitly( tag.Tag(tag.tagClassUniversal, tag.tagFormatSimple, 12) ) encoding = "utf-8"

25.152941

63

0.72217

224

2,138

6.892857

0.276786

0.213731

0.299223

0.178109

0.705311

0

0.025338

0.169317

2,138

84

64

25.452381

0.844032

0.064546

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0.25

0

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0

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false

0.038462

0.019231

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0.538462

0

null

1

0

1

0

null

0

8

8bff9ea0a6eb05b889671d86fee43268398d4a46

51

py

Python

examples/one/rule_5.py

ayushpallav/anthill

740b8fce4281dfc4ca587c21a2d37741c649d870

[ "MIT" ]

14

2020-05-22T20:57:29.000Z

2021-08-19T14:56:32.000Z

examples/one/rule_5.py

ayushpallav/apple-pie

740b8fce4281dfc4ca587c21a2d37741c649d870

[ "MIT" ]

2

2021-01-04T05:05:08.000Z

2021-01-04T05:11:08.000Z

examples/one/rule_5.py

ayushpallav/apple-pie

740b8fce4281dfc4ca587c21a2d37741c649d870

[ "MIT" ]

null

print("-----------------rule_5------------------")

25.5

50

0.215686

3

51

3.333333

1

0

0.02

0.019608

51

1

51

0.18

0

0.803922

0

1

0

true

0

1

0

null

0

1

0

1

0

1

null

0

1

0

1

0

7

e32dd4f05009493a4453bf3c4dacc7d1576697fe

1,729

py

Python

tests/test_generate_binary_overlap_matrix.py

elsandal/pyclesperanto_prototype

7bda828813b86b44b63d73d5e8f466d9769cded1

[ "BSD-3-Clause" ]

64

2020-03-18T12:11:22.000Z

2022-03-31T08:19:18.000Z

tests/test_generate_binary_overlap_matrix.py

elsandal/pyclesperanto_prototype

7bda828813b86b44b63d73d5e8f466d9769cded1

[ "BSD-3-Clause" ]

148

2020-05-14T06:14:11.000Z

2022-03-26T15:02:31.000Z

tests/test_generate_binary_overlap_matrix.py

elsandal/pyclesperanto_prototype

7bda828813b86b44b63d73d5e8f466d9769cded1

[ "BSD-3-Clause" ]

16

2020-05-31T00:53:44.000Z

2022-03-23T13:20:57.000Z

import pyclesperanto_prototype as cle import numpy as np def test_generate_binary_overlap_matrix_2d(): gpu_input1 = cle.push(np.asarray([ [1, 1, 0, 0, 0], [1, 1, 0, 3, 0], [0, 2, 2, 3, 0], [0, 2, 2, 0, 0], [0, 0, 0, 0, 4] ])) gpu_input2 = cle.push(np.asarray([ [1, 1, 2, 2, 2], [1, 1, 2, 2, 2], [1, 0, 0, 2, 2], [1, 0, 0, 2, 2], [1, 2, 2, 2, 2] ])) gpu_reference = cle.push(np.asarray([ [0, 1, 1], [0, 1, 0], [1, 0, 0], [0, 0, 1], [0, 0, 1] ]).T) gpu_binary_overlap_matrix = cle.generate_binary_overlap_matrix(gpu_input1, gpu_input2) a = cle.pull(gpu_binary_overlap_matrix) b = cle.pull(gpu_reference) print(a) print(b) assert (np.allclose(a, b, 0.01)) def test_generate_binary_overlap_matrix_3d(): gpu_input1 = cle.push(np.asarray([ [ [1, 1, 0, 0, 0], [1, 1, 0, 3, 0], ],[ [0, 2, 2, 0, 0], [0, 0, 0, 0, 4] ] ])) gpu_input2 = cle.push(np.asarray([ [ [1, 1, 2, 2, 2], [1, 1, 2, 2, 2], ],[ [1, 0, 0, 2, 2], [1, 2, 2, 2, 2] ] ])) gpu_reference = cle.push(np.asarray([ [0, 1, 1], [0, 1, 0], [1, 0, 0], [0, 0, 1], [0, 0, 1] ]).T) gpu_binary_overlap_matrix = cle.generate_binary_overlap_matrix(gpu_input1, gpu_input2) a = cle.pull(gpu_binary_overlap_matrix) b = cle.pull(gpu_reference) print(a) print(b) assert (np.allclose(a, b, 0.01))

17.824742

90

0.430885

253

1,729

2.782609

0.134387

0.079545

0.059659

0.045455

0.926136

0.829545

0

0.131148

0.400231

1,729

96

91

18.010417

0.547734

0

0.854839

1

0

0.032258

1

0.032258

false

0

0.032258

0

0.064516

0

null

0

1

0

1

0

null

0

8

e34ab2ee36e22be079819640800491e3afe5d0bb

5,973

py

Python

nexus/tests/unit/test_qmcpack_input.py

simonpintarelli/qmcpack

0ab00b7d5bfac2ade860aac513c6e571ae2af13d

[ "NCSA" ]

null

nexus/tests/unit/test_qmcpack_input.py

simonpintarelli/qmcpack

0ab00b7d5bfac2ade860aac513c6e571ae2af13d

[ "NCSA" ]

null

nexus/tests/unit/test_qmcpack_input.py

simonpintarelli/qmcpack

0ab00b7d5bfac2ade860aac513c6e571ae2af13d

[ "NCSA" ]

null

#!/usr/bin/env python def test_generate_kspace_jastrow(): from qmcpack_input import generate_kspace_jastrow kjas = generate_kspace_jastrow(1.0, 2.0, 2, 4) expect = '''<jastrow type="kSpace" name="Jk" source="ion0"> <correlation kc="1.0" type="One-Body" symmetry="isotropic"> <coefficients id="cG1" type="Array"> 0 0 </coefficients> </correlation> <correlation kc="2.0" type="Two-Body" symmetry="isotropic"> <coefficients id="cG2" type="Array"> 0 0 0 0 </coefficients> </correlation> </jastrow> ''' text = kjas.write() assert text == expect #end def test_generate_kspace_jastrow def test_excited_state(): from nexus import generate_physical_system from nexus import generate_qmcpack_input dia = generate_physical_system( units = 'A', axes = [[ 1.785, 1.785, 0. ], [ 0. , 1.785, 1.785], [ 1.785, 0. , 1.785]], elem = ['C','C'], pos = [[ 0. , 0. , 0. ], [ 0.8925, 0.8925, 0.8925]], tiling = [3,1,3], kgrid = (1,1,1), kshift = (0,0,0), C = 4 ) # test kp_index, band_index format (format="band") qmc_optical = generate_qmcpack_input( det_format = 'old', spin_polarized = True, system = dia, excitation = ['up', '0 3 4 4'], # pseudos = ['C.BFD.xml'], jastrows = [], qmc = 'vmc', ) expect = '''<slaterdeterminant> <determinant id="updet" size="36"> <occupation mode="excited" spindataset="0" pairs="1" format="band"> 0 3 4 4 </occupation> </determinant> <determinant id="downdet" size="36"> <occupation mode="ground" spindataset="1"/> </determinant> </slaterdeterminant>'''.strip() text = qmc_optical.get('slaterdeterminant').write().strip() assert(text==expect) # test energy_index (format="energy") qmc_optical = generate_qmcpack_input( det_format = 'old', spin_polarized = True, system = dia, excitation = ['up', '-35 36'], # pseudos = ['C.BFD.xml'], jastrows = [], qmc = 'vmc', ) expect = '''<slaterdeterminant> <determinant id="updet" size="36"> <occupation mode="excited" spindataset="0" pairs="1" format="energy"> -35 36 </occupation> </determinant> <determinant id="downdet" size="36"> <occupation mode="ground" spindataset="1"/> </determinant> </slaterdeterminant>'''.strip() text = qmc_optical.get('slaterdeterminant').write().strip() assert(text==expect) #end def test_excited_state def test_symbolic_excited_state(): from nexus import generate_physical_system from nexus import generate_qmcpack_input # remove once explicit checks/guards for seekpath are made return dia = generate_physical_system( units = 'A', axes = [[ 1.785, 1.785, 0. ], [ 0. , 1.785, 1.785], [ 1.785, 0. , 1.785]], elem = ['C','C'], pos = [[ 0. , 0. , 0. ], [ 0.8925, 0.8925, 0.8925]], use_prim = True, # Use SeeK-path library to identify prim cell tiling = [2,1,2], kgrid = (1,1,1), kshift = (0,0,0), # Assumes we study transitions from Gamma. For non-gamma tilings, use kshift appropriately #C = 4 ) qmc_optical = generate_qmcpack_input( det_format = 'old', input_type = 'basic', spin_polarized = True, system = dia, excitation = ['up', 'gamma vb x cb'], jastrows = [], qmc = 'vmc', ) expect = '''<slaterdeterminant> <determinant id="updet" size="24"> <occupation mode="excited" spindataset="0" pairs="1" format="band"> 0 5 3 6 </occupation> </determinant> <determinant id="downdet" size="24"> <occupation mode="ground" spindataset="1"/> </determinant> </slaterdeterminant>'''.strip() text = qmc_optical.get('slaterdeterminant').write().strip() assert(text==expect) qmc_optical = generate_qmcpack_input( det_format = 'old', input_type = 'basic', spin_polarized = True, system = dia, excitation = ['up', 'gamma vb-1 x cb'], jastrows = [], qmc = 'vmc', ) expect = '''<slaterdeterminant> <determinant id="updet" size="24"> <occupation mode="excited" spindataset="0" pairs="1" format="band"> 0 4 3 6 </occupation> </determinant> <determinant id="downdet" size="24"> <occupation mode="ground" spindataset="1"/> </determinant> </slaterdeterminant>'''.strip() text = qmc_optical.get('slaterdeterminant').write().strip() assert(text==expect) qmc_optical = generate_qmcpack_input( det_format = 'old', input_type = 'basic', spin_polarized = True, system = dia, excitation = ['up', 'gamma vb x cb+1'], jastrows = [], qmc = 'vmc', ) expect = '''<slaterdeterminant> <determinant id="updet" size="24"> <occupation mode="excited" spindataset="0" pairs="1" format="band"> 0 5 3 7 </occupation> </determinant> <determinant id="downdet" size="24"> <occupation mode="ground" spindataset="1"/> </determinant> </slaterdeterminant>'''.strip() text = qmc_optical.get('slaterdeterminant').write().strip() assert(text==expect) #end def test_symbolic_excited_state if __name__ == '__main__': test_generate_kspace_jastrow() #end __main__

30.319797

119

0.535075

633

5,973

4.914692

0.202212

0.010286

0.007715

0.015429

0.802636

0.753134

0.744777

0.733848

0

0.047724

0.319437

5,973

196

120

30.47449

0.717589

0.069814

0

0.740506

1

0

0.398881

0.007577

0

0.037975

1

0.018987

false

0

0.031646

0

0.056962

0

null

0

1

0

1

0

null

0

8

e3655245e3bae3467db180e82379f00daed7f36e

19,218

py

Python

tasks-deploy/getflagchar/check.py

HackerDom/qctf-starter-2018

f4eef0fd41d777661b9fbcc61dcee9709d9f6268

[ "MIT" ]

8

2018-03-15T12:07:11.000Z

2020-12-01T15:02:46.000Z

tasks-deploy/getflagchar/check.py

HackerDom/qctf-starter-2018

f4eef0fd41d777661b9fbcc61dcee9709d9f6268

[ "MIT" ]

17

2020-01-28T22:17:42.000Z

2022-03-11T23:18:09.000Z

tasks-deploy/getflagchar/check.py

HackerDom/qctf-starter-2018

f4eef0fd41d777661b9fbcc61dcee9709d9f6268

[ "MIT" ]

2

2018-11-26T18:54:27.000Z

2018-12-05T17:37:32.000Z

#!/usr/bin/env python3 flags = ['QCTF{e51f2dad87875d76fb081f2b467535ef}', 'QCTF{c89a4b8b181ea0e7666dc8bf93b34779}', 'QCTF{50b59ef5ba8ca7650323b96119507a98}', 'QCTF{fb1c1b7f76e5ca22411fcee3d024ff46}', 'QCTF{4909e8138219a1f5f166e6e06e057cbc}', 'QCTF{649d0b63d4bd82a9af7af03ba46838d3}', 'QCTF{af043650dc65acce4e001425bacbd3f2}', 'QCTF{8e4225e08e6ec2ec1808b6212e8fd813}', 'QCTF{31b1951f567876b0ad957c250402e3e2}', 'QCTF{959f2b0d3fcd298adc4c63fed56c1c5b}', 'QCTF{3a05bfaa08b653a8b9fc085ebd089f62}', 'QCTF{20d739e7472dcf27e77ffb4be40fd3e5}', 'QCTF{eb35b55b59653643a2e625d8826bc84b}', 'QCTF{311e4b1943c17659b9ded0a3e0f57b2b}', 'QCTF{040eaadc3df6ae0ecb33a404f8e03453}', 'QCTF{84801c28a6619841c425f4c13b867a32}', 'QCTF{ab56c77c46c40354e2f38559c034f348}', 'QCTF{f1f9e7257150d40ce3f481aa44517757}', 'QCTF{9d45092f74d5e74772c9e08a7c25690f}', 'QCTF{f0310ec009bdf2c487d7c149b767078b}', 'QCTF{00bc89904ed8ebffc430ca0f64a0467c}', 'QCTF{7984fbee8ea7d5f0e07c36803e2aacc5}', 'QCTF{0088ba127fb34ffa22023757734ad619}', 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'QCTF{43689b43469374eb768fb5d4269be92a}', 'QCTF{e31ff94e5ee5638e7b3c0cde3c2b50dd}', 'QCTF{4cc47b59341b7f0112ba8f4dbdda527c}', 'QCTF{e11501e1bb7da841a2c715eafedccb55}', 'QCTF{6acd2208d0d86fcb796cf8264973fee6}', 'QCTF{d8ee1b7b2772d6aea857929d10fbca8e}', 'QCTF{8c27329ebfdef6480d0c60393a573137}', 'QCTF{b9f5190eb71ca8203f60e2a1a6a652af}', 'QCTF{7e5aa6d503c4c2c944a8148fdf633694}', 'QCTF{9ddcb0e99371e60bbb6cbcae87899fc5}', 'QCTF{e7e75d8e6a4789ea242ece7be93bfc89}', 'QCTF{86546326f5bf721792154c91ede0656d}', 'QCTF{6d36f257d24ee06cc402c3b125d5eaa7}'] def check(attempt, context): if attempt.answer == flags[attempt.participant.id % len(flags)]: return Checked(True) if attempt.answer in flags: return CheckedPlagiarist(False, flags.index(attempt.answer)) return Checked(False)

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8

8b4df837f47359c3edbb01e9064d0908122a237d

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py

Python

autodiff/nn/modules/__init__.py

ryanirl/autodiff

8408a992f065e1fa98923dc36474c746ddc4d096

[ "MIT" ]

null

autodiff/nn/modules/__init__.py

ryanirl/autodiff

8408a992f065e1fa98923dc36474c746ddc4d096

[ "MIT" ]

null

autodiff/nn/modules/__init__.py

ryanirl/autodiff

8408a992f065e1fa98923dc36474c746ddc4d096

[ "MIT" ]

null

from .activation_functions import * from .loss_functions import * from .linear_layers import * from .convolutions import *

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8b67e6cd22fcae0036c13e4006449310df1b6700

22,390

py

Python

scicopia/tests/test_arangodoc.py

pikatech/Scicopia

dcdb3b4f55b9111fa3b4fe78afdb07bb2ceb9985

[ "MIT" ]

null

scicopia/tests/test_arangodoc.py

pikatech/Scicopia

dcdb3b4f55b9111fa3b4fe78afdb07bb2ceb9985

[ "MIT" ]

9

2021-07-24T16:12:03.000Z

2021-07-24T16:58:19.000Z

scicopia/tests/test_arangodoc.py

pikatech/Scicopia

dcdb3b4f55b9111fa3b4fe78afdb07bb2ceb9985

[ "MIT" ]

1

2021-06-18T16:00:06.000Z

import os import scicopia.arangodoc as arangodoc from scicopia.utils.arangodb import connect, select_db def connection(col): # use a config to a test database config = arangodoc.read_config() arangoconn = connect(config) db = select_db(config, arangoconn, create=True) if db.hasCollection(col): collection = db[col] collection.empty() else: collection = db.createCollection(name=col) pdfcol = "import_pdf" if db.hasCollection(pdfcol): pdfcollection = db[pdfcol] pdfcollection.empty() else: pdfcollection = db.createCollection(name=pdfcol) batch_size = 2 return collection, pdfcollection, batch_size def test_create_id(): doc = {"PMID": "12345"} doc_format = "pubmed" arangodoc.create_id(doc, doc_format) assert "id" in doc assert doc["id"] == "PMID12345" def test_zstd_open(): filename = "scicopia/tests/data/bibtex.bib.zst" mode = "rt" encoding = "utf-8" with arangodoc.zstd_open(filename, mode, encoding) as data: lines = data.readlines() assert lines[0] == "@inproceedings{Ipsum2019a,\n" def test_pdfsave(): # no guarantee that the file can open file = "scicopia/tests/data/bibtex_pdf.bib" data = arangodoc.pdfsave(file) assert data[:10] == "B~V00Eio=N" def test_pdfsave_noPDF(): file = "scicopia/tests/data/bibtex.bib" data = arangodoc.pdfsave(file) assert data == "" def test_pdfsave_damagedPDF(): file = "scicopia/tests/data/bibtex_error.bib" data = arangodoc.pdfsave(file) assert data[:10] == "OmA{!Z6IlI" def test_pdfsave_emptyPDF(): file = "scicopia/tests/data/bibtex_error2.bib" data = arangodoc.pdfsave(file) assert data == "" # def test_handleBulkError(): # # spezialzeugs mach ma später # # mit doc_format = "pubmed" muss datenbank inhalt abgefragt werden # # ansonsten fehlermeldungen # handleBulkError(e, docs, collection, doc_format) # def test_parallel_import(): # parallel_import(batch, batch_size, doc_format, open_func, parse, update, pdf) def test_import_file_bibtex(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/bibtex.bib" doc_format = "bibtex" compression = "none" open_func = arangodoc.OPEN_DICT[compression] parse = arangodoc.PARSE_DICT[doc_format] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) for key in ["Ipsum2019a", "Ipsum2019b", "Ipsum2019c"]: assert key in collection assert collection[key]["cited_by"] == "test" assert not key in pdfcollection def test_import_file_arxiv(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/arxiv.xml" doc_format = "arxiv" compression = "none" open_func = arangodoc.OPEN_DICT[compression] parse = arangodoc.PARSE_DICT[doc_format] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) assert "oai:arXiv.org:121518513" in collection def test_import_file_grobid(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/grobid.xml" doc_format = "grobid" compression = "none" open_func = arangodoc.OPEN_DICT[compression] parse = arangodoc.PARSE_DICT[doc_format] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) assert "121518513" in collection def test_import_file_pubmed(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/pubmed.xml" doc_format = "pubmed" compression = "none" open_func = arangodoc.OPEN_DICT[compression] parse = arangodoc.PARSE_DICT[doc_format] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) assert "PMID121518513" in collection def test_import_file_update_pdf(): collection, pdfcollection, batch_size = connection("import_file") doc = collection.createDocument() doc._key = "PDF" doc["test"] = "test" doc.save() file = "scicopia/tests/data/bibtex_pdf.bib" doc_format = "bibtex" compression = "none" open_func = arangodoc.OPEN_DICT[compression] parse = arangodoc.PARSE_DICT[doc_format] update = True pdf = True arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) assert "PDF" in collection assert collection["PDF"]["test"] is None assert "PDF" in pdfcollection # TODO: chatch and assert loggin.error def test_import_file_update_noPDF(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/bibtex.bib" doc_format = "bibtex" compression = "none" open_func = arangodoc.OPEN_DICT[compression] parse = arangodoc.PARSE_DICT[doc_format] update = True pdf = True arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) assert "Ipsum2019a" in collection assert collection["Ipsum2019a"]["test"] == None assert not "Ipsum2019a" in pdfcollection # TODO: chatch and assert loggin.error def test_import_file_update_error(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/bibtex.bib" doc_format = "bibtex" compression = "none" open_func = arangodoc.OPEN_DICT[compression] parse = arangodoc.PARSE_DICT[doc_format] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) # TODO: chatch and assert loggin.error def test_import_file_gz(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/bibtex.bib.gz" doc_format = "bibtex" parse = arangodoc.PARSE_DICT[doc_format] compression = "gzip" open_func = arangodoc.OPEN_DICT[compression] update = True pdf = True arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) for key in ["Ipsum2019a", "Ipsum2019b", "Ipsum2019c"]: try: doc = collection[key] except arangodoc.DocumentNotFoundError: assert False try: doc = pdfcollection[key] assert False except arangodoc.DocumentNotFoundError: pass def test_import_file_bz2(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/bibtex.bib.bz2" doc_format = "bibtex" parse = arangodoc.PARSE_DICT[doc_format] compression = "bzip2" open_func = arangodoc.OPEN_DICT[compression] update = True pdf = True arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) for key in ["Ipsum2019a", "Ipsum2019b", "Ipsum2019c"]: try: doc = collection[key] except arangodoc.DocumentNotFoundError: assert False assert doc["cited_by"] == "test" try: doc = pdfcollection[key] assert False except arangodoc.DocumentNotFoundError: pass def test_import_file_zst(): collection, pdfcollection, batch_size = connection("import_file") file = "scicopia/tests/data/bibtex.bib.zst" doc_format = "bibtex" parse = arangodoc.PARSE_DICT[doc_format] compression = "zstd" open_func = arangodoc.OPEN_DICT[compression] update = True pdf = True arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) for key in ["Ipsum2019a", "Ipsum2019b", "Ipsum2019c"]: try: doc = collection[key] except arangodoc.DocumentNotFoundError: assert False assert doc["cited_by"] == "test" try: doc = pdfcollection[key] assert False except arangodoc.DocumentNotFoundError: pass # tests what happens if the modul is called with wrong combinations def test_import_file_error_bibtex_arxiv(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/bibtex.bib" doc_format = "arxiv" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_bibtex_grobid(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/bibtex.bib" doc_format = "grobid" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_bibtex_pubmed(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/bibtex.bib" doc_format = "pubmed" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_arxiv_bibtex(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/arxiv.xml" doc_format = "bibtex" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_arxiv_grobid(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/arxiv.xml" doc_format = "grobid" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_arxiv_pubmed(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/arxiv.xml" doc_format = "pubmed" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_grobid_bibtex(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/grobid.xml" doc_format = "bibtex" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_grobid_arxiv(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/grobid.xml" doc_format = "arxiv" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_grobid_pubmed(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/grobid.xml" doc_format = "pubmed" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_pubmed_bibtex(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/pubmed.xml" doc_format = "bibtex" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_pubmed_arxiv(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/pubmed.xml" doc_format = "arxiv" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_import_file_error_pubmed_grobid(): collection, pdfcollection, batch_size = connection("import_file_error") pdfcollection = None file = "scicopia/tests/data/pubmed.xml" doc_format = "grobid" parse = arangodoc.PARSE_DICT[doc_format] compression = "none" open_func = arangodoc.OPEN_DICT[compression] update = False pdf = False arangodoc.import_file( file, collection, pdfcollection, batch_size, doc_format, open_func, parse, update, pdf ) def test_locate_bibtex_nonrecursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "bibtex" recursive = False control = [ f"{path}{os.path.sep}bibtex.bib", f"{path}{os.path.sep}bibtex_error.bib", f"{path}{os.path.sep}bibtex_error2.bib", f"{path}{os.path.sep}bibtex_pdf.bib", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control recursive = True def test_locate_bibtex_recursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "bibtex" recursive = True control = [ f"{path}{os.path.sep}bibtex.bib", f"{path}{os.path.sep}bibtex_error.bib", f"{path}{os.path.sep}bibtex_error2.bib", f"{path}{os.path.sep}bibtex_pdf.bib", f"{path}{os.path.sep}test{os.path.sep}r1.bib", f"{path}{os.path.sep}test{os.path.sep}test{os.path.sep}r2.bib", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control def test_locate_arxiv_nonrecursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "arxiv" recursive = False control = [ f"{path}{os.path.sep}arxiv.xml", f"{path}{os.path.sep}grobid.xml", f"{path}{os.path.sep}grobid_error.xml", f"{path}{os.path.sep}grobid_error2.xml", f"{path}{os.path.sep}grobid_error3.xml", f"{path}{os.path.sep}grobid_error4.xml", f"{path}{os.path.sep}grobid_error5.xml", f"{path}{os.path.sep}grobid_error6.xml", f"{path}{os.path.sep}grobid_error7.xml", f"{path}{os.path.sep}pubmed.xml", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control def test_locate_arxiv_recursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "arxiv" recursive = True control = [ f"{path}{os.path.sep}arxiv.xml", f"{path}{os.path.sep}grobid.xml", f"{path}{os.path.sep}grobid_error.xml", f"{path}{os.path.sep}grobid_error2.xml", f"{path}{os.path.sep}grobid_error3.xml", f"{path}{os.path.sep}grobid_error4.xml", f"{path}{os.path.sep}grobid_error5.xml", f"{path}{os.path.sep}grobid_error6.xml", f"{path}{os.path.sep}grobid_error7.xml", f"{path}{os.path.sep}pubmed.xml", f"{path}{os.path.sep}test{os.path.sep}grobid.xml", f"{path}{os.path.sep}test{os.path.sep}r1.xml", f"{path}{os.path.sep}test{os.path.sep}test{os.path.sep}r2.xml", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control def test_locate_grobid_nonrecursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "grobid" recursive = False control = [ f"{path}{os.path.sep}arxiv.xml", f"{path}{os.path.sep}grobid.xml", f"{path}{os.path.sep}grobid_error.xml", f"{path}{os.path.sep}grobid_error2.xml", f"{path}{os.path.sep}grobid_error3.xml", f"{path}{os.path.sep}grobid_error4.xml", f"{path}{os.path.sep}grobid_error5.xml", f"{path}{os.path.sep}grobid_error6.xml", f"{path}{os.path.sep}grobid_error7.xml", f"{path}{os.path.sep}pubmed.xml", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control def test_locate_grobid_recursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "grobid" recursive = True control = [ f"{path}{os.path.sep}arxiv.xml", f"{path}{os.path.sep}grobid.xml", f"{path}{os.path.sep}grobid_error.xml", f"{path}{os.path.sep}grobid_error2.xml", f"{path}{os.path.sep}grobid_error3.xml", f"{path}{os.path.sep}grobid_error4.xml", f"{path}{os.path.sep}grobid_error5.xml", f"{path}{os.path.sep}grobid_error6.xml", f"{path}{os.path.sep}grobid_error7.xml", f"{path}{os.path.sep}pubmed.xml", f"{path}{os.path.sep}test{os.path.sep}grobid.xml", f"{path}{os.path.sep}test{os.path.sep}r1.xml", f"{path}{os.path.sep}test{os.path.sep}test{os.path.sep}r2.xml", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control def test_locate_pubmed_nonrecursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "pubmed" recursive = False control = [ f"{path}{os.path.sep}arxiv.xml", f"{path}{os.path.sep}grobid.xml", f"{path}{os.path.sep}grobid_error.xml", f"{path}{os.path.sep}grobid_error2.xml", f"{path}{os.path.sep}grobid_error3.xml", f"{path}{os.path.sep}grobid_error4.xml", f"{path}{os.path.sep}grobid_error5.xml", f"{path}{os.path.sep}grobid_error6.xml", f"{path}{os.path.sep}grobid_error7.xml", f"{path}{os.path.sep}pubmed.xml", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control def test_locate_pubmed_recursive(): path = "./scicopia/tests/data" compression = "none" doc_format = "pubmed" recursive = True control = [ f"{path}{os.path.sep}arxiv.xml", f"{path}{os.path.sep}grobid.xml", f"{path}{os.path.sep}grobid_error.xml", f"{path}{os.path.sep}grobid_error2.xml", f"{path}{os.path.sep}grobid_error3.xml", f"{path}{os.path.sep}grobid_error4.xml", f"{path}{os.path.sep}grobid_error5.xml", f"{path}{os.path.sep}grobid_error6.xml", f"{path}{os.path.sep}grobid_error7.xml", f"{path}{os.path.sep}pubmed.xml", f"{path}{os.path.sep}test{os.path.sep}grobid.xml", f"{path}{os.path.sep}test{os.path.sep}r1.xml", f"{path}{os.path.sep}test{os.path.sep}test{os.path.sep}r2.xml", ] control.sort() files = arangodoc.locate_files(path, doc_format, recursive, compression) files.sort() assert files == control def test_locate_zstd_bibtex(): path = "./scicopia/tests/data" recursive = False compression = "zstd" doc_format = "bibtex" control = [f"{path}{os.path.sep}bibtex.bib.zst"] files = arangodoc.locate_files(path, doc_format, recursive, compression) assert files == control def test_locate_gzip_bibtex(): path = "./scicopia/tests/data" recursive = False compression = "gzip" doc_format = "bibtex" control = [f"{path}{os.path.sep}bibtex.bib.gz"] files = arangodoc.locate_files(path, doc_format, recursive, compression) assert files == control def test_locate_bzip2_bibtex(): path = "./scicopia/tests/data" recursive = False compression = "bzip2" doc_format = "bibtex" control = [f"{path}{os.path.sep}bibtex.bib.bz2"] files = arangodoc.locate_files(path, doc_format, recursive, compression) assert files == control # def test_main(): # main(doc_format, path, pdf, recursive, compression, update, batch_size) # def test_parallel_main(): # parallel_main(parallel, cluster, doc_format, path, pdf, recursive, compression, update, batch_size)

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null

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7

8bb0435141f25dba4db9f0b61a98dd248615661a

2,500

py

Python

tests/beta_tests/test_author_disambiguation_a_name_is_a_name.py

the-zebulan/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

40

2016-03-09T12:26:20.000Z

2022-03-23T08:44:51.000Z

tests/beta_tests/test_author_disambiguation_a_name_is_a_name.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

null

tests/beta_tests/test_author_disambiguation_a_name_is_a_name.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

36

2016-11-07T19:59:58.000Z

2022-03-31T11:18:27.000Z

import unittest from katas.beta.author_disambiguation_a_name_is_a_name import could_be class CouldBeTestCase(unittest.TestCase): def test_true_1(self): self.assertTrue(could_be('Carlos Ray Norris', 'Carlos Ray Norris')) def test_true_2(self): self.assertTrue(could_be('Carlos Ray Norris', 'Carlos Ray')) def test_true_3(self): self.assertTrue(could_be('Carlos Ray Norris', 'Ray Norris')) def test_true_4(self): self.assertTrue(could_be('Carlos Ray Norris', 'Carlos Norris')) def test_true_5(self): self.assertTrue(could_be('Carlos Ray Norris', 'Norris')) def test_true_6(self): self.assertTrue(could_be('Carlos Ray Norris', 'Carlos')) def test_true_7(self): self.assertTrue(could_be('Carlos Ray Norris', 'Norris Carlos')) def test_true_8(self): self.assertTrue(could_be('Carlos Ray Norris', 'carlos ray norris')) def test_true_9(self): self.assertTrue(could_be('Carlos Ray Norris', 'Norris! ?ray')) def test_true_10(self): self.assertTrue(could_be('Carlos Ray Norris', 'Carlos. Ray; Norris,')) def test_true_11(self): self.assertTrue(could_be('Carlos Ray Norris', 'Carlos:Ray Norris')) def test_true_12(self): self.assertTrue(could_be('Carlos-Ray Norris', 'Carlos-Ray Norris:')) def test_true_13(self): self.assertTrue(could_be('Carlos Ray-Norris', 'Carlos? Ray-Norris')) def test_false_1(self): self.assertFalse(could_be('Carlos Ray Norris', 'Carlos Ray Norr')) def test_false_2(self): self.assertFalse(could_be('Carlos Ray Norris', 'Ra Norris')) def test_false_3(self): self.assertFalse(could_be('', 'C')) def test_false_4(self): self.assertFalse(could_be('', '')) def test_false_5(self): self.assertFalse(could_be('Carlos Ray Norris', ' ')) def test_false_6(self): self.assertFalse(could_be('Carlos-Ray Norris', 'Carlos Ray-Norris')) def test_false_7(self): self.assertFalse(could_be('Carlos Ray Norris', 'Carlos-Ray Norris')) def test_false_8(self): self.assertFalse(could_be('Carlos-Ray Norris', 'Carlos Ray-Norris')) def test_false_9(self): self.assertFalse(could_be('Carlos Ray Norris', 'Carlos Ray-Norris')) def test_false_10(self): self.assertFalse(could_be('Carlos Ray', 'Carlos Ray Norris')) def test_false_11(self): self.assertFalse(could_be('Carlos', 'Carlos Ray Norris'))

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null

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1

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1

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7

479170a1915faaf8e993c8e139f39c76e54a1117

10,062

py

Python

tests/test_parse.py

artisanofcode/python-twelvefactor

f4bb3e35228dba211c99c6f0912d42ab1c0105ef

[ "MIT" ]

1

2019-05-01T06:24:24.000Z

tests/test_parse.py

artisanofcode/python-twelvefactor

f4bb3e35228dba211c99c6f0912d42ab1c0105ef

[ "MIT" ]

481

2018-11-21T05:48:20.000Z

2021-03-08T09:29:29.000Z

tests/test_parse.py

artisanofcode/python-twelvefactor

f4bb3e35228dba211c99c6f0912d42ab1c0105ef

[ "MIT" ]

null

import cmath import itertools import math import typing import unittest.mock as mock import hypothesis import hypothesis.strategies as st import pytest import twelvefactor # Generate all possible case permutations of the strings in TRUE_STRINGS TRUE_STRINGS = [ v for s in twelvefactor.Config.TRUE_STRINGS for v in map( "".join, itertools.product(*((c.upper(), c.lower()) for c in s)) ) ] @hypothesis.given(value=st.sampled_from(TRUE_STRINGS)) def test_it_should_be_able_to_parse_true(value: str) -> None: """ it should be able to parse true. """ config = twelvefactor.Config() assert config.parse(value=value, type_=bool) @hypothesis.given(value=st.text().filter(lambda x: x not in TRUE_STRINGS)) def test_it_should_be_able_to_parse_false(value: str) -> None: """ it should be able to parse false. """ config = twelvefactor.Config() assert not config.parse(value=value, type_=bool) @hypothesis.given(value=st.text()) def test_it_should_be_able_to_parse_strings(value: str) -> None: """ it should be able to parse strings. """ config = twelvefactor.Config() assert config.parse(value=value) == value @hypothesis.given(value=st.integers()) def test_it_should_be_able_to_parse_integers(value: int) -> None: """ it should be able to parse integers. """ config = twelvefactor.Config() assert config.parse(value=str(value), type_=int) == value @hypothesis.given(value=st.floats()) def test_it_should_be_able_to_parse_floats(value: float) -> None: """ it should be able to parse floats. """ config = twelvefactor.Config() result = config.parse(value=str(value), type_=float) if math.isnan(value): assert math.isnan(result) else: assert result == value @hypothesis.given(value=st.complex_numbers()) def test_it_should_be_able_to_parse_complex_numbers(value: complex) -> None: config = twelvefactor.Config() result = config.parse(value=str(value), type_=complex) if cmath.isnan(value): assert cmath.isnan(result) else: assert result == value @hypothesis.given(value=st.lists(elements=st.booleans())) def test_it_should_be_able_to_parse_boolean_list( value: typing.List[bool] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=list, subtype=bool ) assert result == value @hypothesis.given(value=st.lists(elements=st.booleans()).map(tuple)) def test_it_should_be_able_to_parse_boolean_tuple( value: typing.Tuple[bool, ...] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=tuple, subtype=bool ) assert result == value @hypothesis.given(value=st.lists(elements=st.booleans()).map(set)) def test_it_should_be_able_to_parse_boolean_set( value: typing.Set[bool] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=set, subtype=bool ) assert result == value @hypothesis.given(value=st.lists(elements=st.booleans()).map(frozenset)) def test_it_should_be_able_to_parse_boolean_frozenset( value: typing.FrozenSet[bool] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=frozenset, subtype=bool ) assert result == value @hypothesis.given(value=st.lists(elements=st.integers())) def test_it_should_be_able_to_parse_integer_list( value: typing.List[int] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=list, subtype=int ) assert result == value @hypothesis.given(value=st.lists(elements=st.integers()).map(tuple)) def test_it_should_be_able_to_parse_integer_tuple( value: typing.Tuple[int, ...] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=tuple, subtype=int ) assert result == value @hypothesis.given(value=st.lists(elements=st.integers()).map(set)) def test_it_should_be_able_to_parse_integer_set( value: typing.Set[int] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=set, subtype=int ) assert result == value @hypothesis.given(value=st.lists(elements=st.integers()).map(frozenset)) def test_it_should_be_able_to_parse_integer_frozenset( value: typing.FrozenSet[int] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=frozenset, subtype=int ) assert result == value @hypothesis.given(value=st.lists(elements=st.floats(allow_nan=False))) def test_it_should_be_able_to_parse_float_list( value: typing.List[float] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=list, subtype=float ) assert result == value @hypothesis.given( value=st.lists(elements=st.floats(allow_nan=False)).map(tuple) ) def test_it_should_be_able_to_parse_float_tuple( value: typing.Tuple[float, ...] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=tuple, subtype=float ) assert result == value @hypothesis.given(value=st.lists(elements=st.floats(allow_nan=False)).map(set)) def test_it_should_be_able_to_parse_float_set( value: typing.Set[float] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=set, subtype=float ) assert result == value @hypothesis.given( value=st.lists(elements=st.floats(allow_nan=False)).map(frozenset) ) def test_it_should_be_able_to_parse_float_frozenset( value: typing.FrozenSet[float] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=frozenset, subtype=float ) assert result == value @hypothesis.given(value=st.lists(elements=st.complex_numbers(allow_nan=False))) def test_it_should_be_able_to_parse_complex_number_list( value: typing.List[complex] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=list, subtype=complex ) assert result == value @hypothesis.given( value=st.lists(elements=st.complex_numbers(allow_nan=False)).map(tuple) ) def test_it_should_be_able_to_parse_complex_number_tuple( value: typing.Tuple[complex, ...] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=tuple, subtype=complex ) assert result == value @hypothesis.given( value=st.lists(elements=st.complex_numbers(allow_nan=False)).map(set) ) def test_it_should_be_able_to_parse_complex_number_set( value: typing.Set[complex] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=set, subtype=complex ) assert result == value @hypothesis.given( value=st.lists(elements=st.complex_numbers(allow_nan=False)).map(frozenset) ) def test_it_should_be_able_to_parse_complex_number_frozenset( value: typing.FrozenSet[complex] ) -> None: config = twelvefactor.Config() result = config.parse( value=",".join(str(v) for v in value), type_=frozenset, subtype=complex ) assert result == value @hypothesis.given( value=st.lists( elements=st.text().filter( lambda x: "," not in x and x.strip(" ") == x and bool(x.strip(" ")) ) ) ) def test_it_should_be_able_to_parse_string_list( value: typing.List[str] ) -> None: config = twelvefactor.Config() result = config.parse(value=",".join(value), type_=list) assert result == value @hypothesis.given( value=st.lists( elements=st.text().filter( lambda x: "," not in x and x.strip(" ") == x and bool(x.strip(" ")) ) ).map(tuple) ) def test_it_should_be_able_to_parse_string_tuple( value: typing.Tuple[str, ...] ) -> None: config = twelvefactor.Config() result = config.parse(value=",".join(value), type_=tuple) assert result == value @hypothesis.given( value=st.lists( elements=st.text().filter( lambda x: "," not in x and x.strip(" ") == x and bool(x.strip(" ")) ) ).map(set) ) def test_it_should_be_able_to_parse_string_set(value: typing.Set[str]) -> None: config = twelvefactor.Config() result = config.parse(value=",".join(value), type_=set) assert result == value @hypothesis.given( value=st.lists( elements=st.text().filter( lambda x: "," not in x and x.strip(" ") == x and bool(x.strip(" ")) ) ).map(frozenset) ) def test_it_should_be_able_to_parse_string_frozenset( value: typing.FrozenSet[str] ) -> None: config = twelvefactor.Config() result = config.parse(value=",".join(value), type_=frozenset) assert result == value @hypothesis.given( value=st.lists( elements=st.text().filter( lambda x: "," not in x and x.strip(" ") == x and bool(x.strip(" ")) ) ) ) def test_it_should_be_able_to_parse_string_list_with_extra_space( value: typing.List[str] ) -> None: config = twelvefactor.Config() result = config.parse(value=" , ".join(value), type_=list) assert result == value @hypothesis.given(value=st.text(), error=st.text()) def test_it_should_raise_error_on_invalid_value( value: str, error: str ) -> None: config = twelvefactor.Config() type_ = mock.Mock(side_effect=ValueError(error)) with pytest.raises(twelvefactor.ConfigError) as excinfo: config.parse(value=value, type_=type_) assert str(excinfo.value) == error

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0.675114

1,372

10,062

4.751458

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0.040497

0.049087

0.068722

0.832336

0.813162

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0

null

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0

1

0

null

0

7

47ed4e7352e39169b884af321c5e1828cfe92b5b

331

py

Python

tests/parser/aggregates.duplicated.4.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/aggregates.duplicated.4.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/aggregates.duplicated.4.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

input = """ mysum(X) :- #sum{P: c(P)} = X, dom(X). mycount(X) :- #count{P: c(P)} = X, dom(X). dom(0). dom(1). c(X) | d(X) :- dom(X). :- not c(0). :- not c(1). """ output = """ mysum(X) :- #sum{P: c(P)} = X, dom(X). mycount(X) :- #count{P: c(P)} = X, dom(X). dom(0). dom(1). c(X) | d(X) :- dom(X). :- not c(0). :- not c(1). """

15.761905

42

0.41994

70

331

1.985714

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0.115108

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0

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0.199396

331

20

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null

0

13

9a089d46dcb34110c0294ff51baac4f6fc1fc325

3,992

py

Python

tests/unittest_typesafe.py

Hc10b/py3traits

713eec35a5a2f4eba6801c1c7660b863eb692bcc

[ "Apache-2.0" ]

25

2015-05-25T20:27:43.000Z

2020-08-30T16:37:59.000Z

tests/unittest_typesafe.py

Hc10b/py3traits

713eec35a5a2f4eba6801c1c7660b863eb692bcc

[ "Apache-2.0" ]

2

2017-11-02T09:02:37.000Z

2020-06-16T20:39:56.000Z

tests/unittest_typesafe.py

Hc10b/py3traits

713eec35a5a2f4eba6801c1c7660b863eb692bcc

[ "Apache-2.0" ]

3

2015-05-25T20:34:13.000Z

2020-06-16T13:51:37.000Z

#!/usr/bin/python -tt # -*- coding: utf-8 -*- import unittest from pytraits import type_safe class TestTypeSafe(unittest.TestCase): def test_shows_unassigned_arguments_error_for_omitted_arguments(self): # We need to make sure that when user misses argument from the # function call, we show proper error message. @type_safe def checked(existing, missing): pass with self.assertRaisesRegex(TypeError, ".*missing 1 required.*"): checked(True) def test_shows_unassigned_arguments_error_for_ommitted_arguments_with_type(self): # Even if argument has any arguments with annotated type, we still # need to give proper error message, when that argument has been # omitted. @type_safe def checked(existing, missing: int): pass with self.assertRaisesRegex(TypeError, ".*missing 1 required.*"): checked(True) def test_uses_default_value_for_omitted_arguments(self): # Missing arguments with default values should be properly used when # arguments are omitted. @type_safe def checked(existing, missing_with_default=42): return missing_with_default self.assertEqual(checked(True), 42) def test_uses_default_value_for_omitted_arguments_with_type(self): # Missing arguments with default values should be properly used when # arguments are omitted even when there are annotated arguments. @type_safe def checked(existing, missing_with_default: int=42): return missing_with_default self.assertEqual(checked(True), 42) def test_ignores_default_value_when_argument_given_with_type(self): # Missing arguments with default values should be properly used when # arguments are omitted even when there are annotated arguments. @type_safe def checked(existing, missing_with_default: int=42): return missing_with_default self.assertEqual(checked(True, 52), 52) def test_handles_properly_tuple_arguments(self): @type_safe def checked(existing, *remainder): return existing self.assertEqual(checked(True), True) def test_handles_properly_tuple_arguments_with_type(self): @type_safe def checked(existing: bool, *remainder): return existing self.assertEqual(checked(True), True) def test_handles_properly_tuple_arguments_with_type(self): @type_safe def checked(existing: bool, *remainder): return existing with self.assertRaisesRegex(TypeError, "While calling.*"): checked(2, "tuple", "args") def test_shows_proper_error_when_too_many_args_given(self): @type_safe def checked(existing): return missing_with_default with self.assertRaisesRegex(TypeError, ".*takes 1 positional.*"): self.assertEqual(checked(True, 52), 52) def test_shows_proper_error_when_too_many_args_given_with_type(self): @type_safe def checked(existing: bool): return missing_with_default with self.assertRaisesRegex(TypeError, ".*takes 1 positional.*"): self.assertEqual(checked(True, 52), 52) def test_shows_proper_error_when_too_many_args_given_with_default(self): @type_safe def checked(existing=False): return missing_with_default with self.assertRaisesRegex(TypeError, ".*takes from 0 to 1 positional.*"): self.assertEqual(checked(True, 52), 52) def test_shows_proper_error_when_too_many_args_given_with_type_and_default(self): @type_safe def checked(existing: bool=False): return missing_with_default with self.assertRaisesRegex(TypeError, ".*takes from 0 to 1 positional.*"): self.assertEqual(checked(True, 52), 52) if __name__ == '__main__': unittest.main()

35.017544

85

0.681363

480

3,992

5.385417

0.195833

0.059574

0.051064

0.083559

0.821277

0.774081

0.700967

0.652611

0.639458

0

0.013249

0.243737

3,992

113

86

35.327434

0.842994

0.159068

0

0.652778

0

0.055024

0

0.222222

1

0.333333

false

0.027778

0.138889

0.513889

0

null

0

1

0

1

0

null

0

1

0

1

0

8

9a56cbb0dde4556de3fae0c2dcf578272a4c9aad

32,367

py

Python

game/content/ghplots/dd_roadstops.py

AmkG/gearhead-caramel

0238378295a09b4b33adb2ec0854fa06b0ad7b1b

[ "Apache-2.0" ]

null

game/content/ghplots/dd_roadstops.py

AmkG/gearhead-caramel

0238378295a09b4b33adb2ec0854fa06b0ad7b1b

[ "Apache-2.0" ]

null

game/content/ghplots/dd_roadstops.py

AmkG/gearhead-caramel

0238378295a09b4b33adb2ec0854fa06b0ad7b1b

[ "Apache-2.0" ]

null

from pbge.plots import Plot from pbge.dialogue import Offer, ContextTag from game import teams, services, ghdialogue from game.ghdialogue import context import gears import pbge from .dd_main import DZDRoadMapExit,RoadNode import random from game.content import gharchitecture,ghwaypoints,plotutility,ghterrain,backstory,GHNarrativeRequest,PLOT_LIST class DZD_DeadZoneTown(Plot): LABEL = "DZD_ROADSTOP" active = True scope = True def custom_init(self, nart): town_name = self._generate_town_name() town_fac = self.register_element( "METRO_FACTION", gears.factions.Circle(nart.camp,parent_faction=gears.factions.DeadzoneFederation,name="the {} Council".format(town_name)) ) team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team", allies=(team1,), faction=town_fac) myscene = gears.GearHeadScene(50, 50, town_name, player_team=team1, civilian_team=team2, scale=gears.scale.HumanScale, is_metro=True, faction=town_fac, attributes=( gears.personality.DeadZone, gears.tags.City, gears.tags.SCENE_PUBLIC)) myscene.exploration_music = 'Doctor_Turtle_-_04_-_Lets_Just_Get_Through_Christmas.ogg' npc = gears.selector.random_character(50, local_tags=myscene.attributes) npc.place(myscene, team=team2) npc2 = gears.selector.random_character(50, local_tags=myscene.attributes,job=gears.jobs.choose_random_job((gears.tags.Laborer,),self.elements["LOCALE"].attributes)) npc2.place(myscene, team=team2) defender = self.register_element( "DEFENDER", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.choose_random_job((gears.tags.Police,),self.elements["LOCALE"].attributes), faction=town_fac )) defender.place(myscene, team=team2) myscenegen = pbge.randmaps.CityGridGenerator(myscene, gharchitecture.HumanScaleGreenzone(), road_terrain=ghterrain.Flagstone) self.register_scene(nart, myscene, myscenegen, ident="LOCALE") mystory = self.register_element("BACKSTORY",backstory.Backstory(commands=("DZTOWN_FOUNDING",),elements={"LOCALE":self.elements["LOCALE"]})) self.register_element("METRO", myscene.metrodat) self.register_element("METROSCENE", myscene) self.register_element("DZ_NODE_FRAME",RoadNode.FRAME_TOWN) myroom2 = self.register_element("_ROOM2", pbge.randmaps.rooms.Room(3, 3, anchor=pbge.randmaps.anchors.east), dident="LOCALE") towngate = self.register_element("ENTRANCE", DZDRoadMapExit(roadmap=self.elements["DZ_ROADMAP"], node=self.elements["DZ_NODE"],name="The Highway", desc="The highway stretches far beyond the horizon, all the way back to the green zone.", anchor=pbge.randmaps.anchors.east, plot_locked=True), dident="_ROOM2") # Gonna register the entrance under another name for the subplots. self.register_element("MISSION_GATE", towngate) # Add the order. This subplot will add a leader, guards, police, and backstory to the town. tplot = self.add_sub_plot(nart, "DZRS_ORDER") # Add the services. tplot = self.add_sub_plot(nart, "DZRS_GARAGE") tplot = self.add_sub_plot(nart, "DZRS_HOSPITAL") #tplot = self.add_sub_plot(nart, "DZDHB_EliteEquipment") #tplot = self.add_sub_plot(nart, "DZDHB_BlueFortress") #tplot = self.add_sub_plot(nart, "DZDHB_BronzeHorseInn") #tplot = self.add_sub_plot(nart, "DZDHB_LongRoadLogistics") # Black Isle Pub # Wujung Tires - Conversion supplies # Hwang-Sa Mission # Reconstruction Site # Add the local tarot. #threat_card = nart.add_tarot_card(self, (game.content.ghplots.dd_tarot.MT_THREAT,), ) #game.content.mechtarot.Constellation(nart, self, threat_card, threat_card.get_negations()[0], steps=3) return True TOWN_NAME_PATTERNS = ("Fort {}","{} Fortress","{} Oasis","Mount {}", "{}", "Castle {}", "{} Ruins", "{} Spire") def _generate_town_name(self): return random.choice(self.TOWN_NAME_PATTERNS).format(gears.selector.DEADZONE_TOWN_NAMES.gen_word()) def METROSCENE_ENTER(self, camp): # Upon entering this scene, deal with any dead or incapacitated party members. # Also, deal with party members who have lost their mecha. This may include the PC. etlr = plotutility.EnterTownLanceRecovery(camp, self.elements["METROSCENE"], self.elements["METRO"]) if not etlr.did_recovery: # We can maybe load a lancemate scene here. Yay! nart = GHNarrativeRequest(camp, pbge.plots.PlotState().based_on(self), adv_type="DZD_LANCEDEV", plot_list=PLOT_LIST) if nart.story: nart.build() class DZD_DeadZoneVillage(Plot): LABEL = "DZD_ROADSTOP" active = True scope = True def custom_init(self, nart): town_name = self._generate_town_name() town_fac = self.register_element( "METRO_FACTION", gears.factions.Circle(nart.camp,parent_faction=gears.factions.DeadzoneFederation,name="the {} Council".format(town_name)) ) team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team", allies=(team1,), faction=town_fac) myscene = gears.GearHeadScene(50, 50, town_name, player_team=team1, civilian_team=team2, scale=gears.scale.HumanScale, is_metro=True, faction=town_fac, attributes=( gears.personality.DeadZone, gears.tags.Village, gears.tags.SCENE_PUBLIC)) myscene.exploration_music = 'Doctor_Turtle_-_04_-_Lets_Just_Get_Through_Christmas.ogg' npc = gears.selector.random_character(50, local_tags=myscene.attributes) npc.place(myscene, team=team2) defender = self.register_element( "DEFENDER", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.choose_random_job((gears.tags.Police,),self.elements["LOCALE"].attributes), faction=town_fac )) defender.place(myscene, team=team2) myscenegen = pbge.randmaps.CityGridGenerator(myscene, gharchitecture.HumanScaleDeadzone(), road_terrain=ghterrain.Flagstone) self.register_scene(nart, myscene, myscenegen, ident="LOCALE") self.register_element("METRO", myscene.metrodat) self.register_element("METROSCENE", myscene) self.register_element("DZ_NODE_FRAME",RoadNode.FRAME_VILLAGE) mystory = self.register_element("BACKSTORY",backstory.Backstory(commands=("DZTOWN_FOUNDING",),elements={"LOCALE":self.elements["LOCALE"]})) myroom2 = self.register_element("_ROOM2", pbge.randmaps.rooms.Room(3, 3, anchor=pbge.randmaps.anchors.east), dident="LOCALE") towngate = self.register_element("ENTRANCE", DZDRoadMapExit(roadmap=self.elements["DZ_ROADMAP"], node=self.elements["DZ_NODE"],name="The Highway", desc="The highway stretches far beyond the horizon, all the way back to the green zone.", anchor=pbge.randmaps.anchors.east, plot_locked=True), dident="_ROOM2") # Gonna register the entrance under another name for the subplots. self.register_element("MISSION_GATE", towngate) # Add the order. This subplot will add a leader, guards, police, and backstory to the town. tplot = self.add_sub_plot(nart, "DZRS_ORDER") # Add the services. tplot = self.add_sub_plot(nart, "DZRS_GARAGE") tplot = self.add_sub_plot(nart, "DZRS_HOSPITAL") #tplot = self.add_sub_plot(nart, "DZDHB_EliteEquipment") #tplot = self.add_sub_plot(nart, "DZDHB_BlueFortress") #tplot = self.add_sub_plot(nart, "DZDHB_BronzeHorseInn") #tplot = self.add_sub_plot(nart, "DZDHB_LongRoadLogistics") # Black Isle Pub # Wujung Tires - Conversion supplies # Hwang-Sa Mission # Reconstruction Site # Add the local tarot. #threat_card = nart.add_tarot_card(self, (game.content.ghplots.dd_tarot.MT_THREAT,), ) #game.content.mechtarot.Constellation(nart, self, threat_card, threat_card.get_negations()[0], steps=3) return True TOWN_NAME_PATTERNS = ("{} Village","{} Hamlet","Camp {}","Mount {}", "{}", "{} Ruins" ) def _generate_town_name(self): return random.choice(self.TOWN_NAME_PATTERNS).format(gears.selector.DEADZONE_TOWN_NAMES.gen_word()) def METROSCENE_ENTER(self, camp): # Upon entering this scene, deal with any dead or incapacitated party members. # Also, deal with party members who have lost their mecha. This may include the PC. etlr = plotutility.EnterTownLanceRecovery(camp, self.elements["METROSCENE"], self.elements["METRO"]) if not etlr.did_recovery: # We can maybe load a lancemate scene here. Yay! nart = GHNarrativeRequest(camp, pbge.plots.PlotState().based_on(self), adv_type="DZD_LANCEDEV", plot_list=PLOT_LIST) if nart.story: nart.build() # ********************** # *** DZRS_ORDER *** # ********************** class DemocraticOrder(Plot): # This town is governed by a mayor. LABEL = "DZRS_ORDER" active = True scope = "METRO" def custom_init(self, nart): # Create a building within the town. building = self.register_element("_EXTERIOR", ghterrain.ResidentialBuilding( waypoints={"DOOR": ghwaypoints.ScrapIronDoor(name="Town Hall")}, tags=[pbge.randmaps.CITY_GRID_ROAD_OVERLAP]), dident="LOCALE") # Add the interior scene. team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team",faction=self.elements["METRO_FACTION"]) intscene = gears.GearHeadScene(35, 35, "Town Hall", player_team=team1, civilian_team=team2, attributes=(gears.tags.SCENE_PUBLIC, gears.tags.SCENE_GOVERNMENT), scale=gears.scale.HumanScale) intscenegen = pbge.randmaps.SceneGenerator(intscene, gharchitecture.ResidentialBuilding()) self.register_scene(nart, intscene, intscenegen, ident="INTERIOR", dident="LOCALE") foyer = self.register_element('_introom', pbge.randmaps.rooms.ClosedRoom(anchor=pbge.randmaps.anchors.south,), dident="INTERIOR") mycon2 = plotutility.TownBuildingConnection(self, self.elements["LOCALE"], intscene, room1=building, room2=foyer, door1=building.waypoints["DOOR"], move_door1=False) npc = self.register_element("LEADER", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.ALL_JOBS["Mayor"], faction = self.elements["METRO_FACTION"] )) npc.place(intscene, team=team2) self.town_origin_ready = True bodyguard = self.register_element( "BODYGUARD", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.choose_random_job((gears.tags.Military,),self.elements["LOCALE"].attributes), faction = self.elements["METRO_FACTION"] )) bodyguard.place(intscene, team=team2) return True def _tell_town_origin(self,camp): self.town_origin_ready = False def LEADER_offers(self, camp): mylist = list() mylist.append(Offer("[HELLO] Welcome to {}.".format(str(self.elements["LOCALE"])), context=ContextTag([context.HELLO]), )) if self.town_origin_ready: mylist.append(Offer(" ".join(self.elements["BACKSTORY"].results["text"]), context=ContextTag([context.INFO]),effect=self._tell_town_origin, data={"subject":"this place"}, no_repeats=True )) return mylist class MilitaryOrder(Plot): # This town is governed by a warlord. LABEL = "DZRS_ORDER" active = True scope = "METRO" @classmethod def matches(cls, pstate): """Returns True if this town has a CONFLICT background.""" return pstate.elements["BACKSTORY"] and "CONFLICT" in pstate.elements["BACKSTORY"].generated_state.keywords def custom_init(self, nart): # Create a building within the town. building = self.register_element("_EXTERIOR", ghterrain.ScrapIronBuilding( waypoints={"DOOR": ghwaypoints.ScrapIronDoor(name="Town Hall")}, tags=[pbge.randmaps.CITY_GRID_ROAD_OVERLAP]), dident="LOCALE") # Add the interior scene. team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team",faction=self.elements["METRO_FACTION"]) intscene = gears.GearHeadScene(35, 35, "Town Hall", player_team=team1, civilian_team=team2, attributes=(gears.tags.SCENE_PUBLIC, gears.tags.SCENE_GOVERNMENT), scale=gears.scale.HumanScale) intscenegen = pbge.randmaps.SceneGenerator(intscene, gharchitecture.FortressBuilding()) self.register_scene(nart, intscene, intscenegen, ident="INTERIOR", dident="LOCALE") foyer = self.register_element('_introom', pbge.randmaps.rooms.ClosedRoom(anchor=pbge.randmaps.anchors.south,), dident="INTERIOR") mycon2 = plotutility.TownBuildingConnection(self, self.elements["LOCALE"], intscene, room1=building, room2=foyer, door1=building.waypoints["DOOR"], move_door1=False) npc = self.register_element("LEADER", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.ALL_JOBS["Warlord"], faction = self.elements["METRO_FACTION"] )) npc.place(intscene, team=team2) self.town_origin_ready = True bodyguard = self.register_element( "BODYGUARD", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.choose_random_job((gears.tags.Military,),self.elements["LOCALE"].attributes), faction = self.elements["METRO_FACTION"] )) bodyguard.place(intscene, team=team2) return True def _tell_town_origin(self,camp): self.town_origin_ready = False def LEADER_offers(self, camp): mylist = list() mylist.append(Offer("[HELLO] This is {}.".format(str(self.elements["LOCALE"])), context=ContextTag([context.HELLO]), )) if self.town_origin_ready: mylist.append(Offer(" ".join(self.elements["BACKSTORY"].results["text"]), context=ContextTag([context.INFO]),effect=self._tell_town_origin, data={"subject":"this place"}, no_repeats=True )) return mylist class TechnocraticOrder(Plot): # This town is governed by a technocrat. LABEL = "DZRS_ORDER" active = True scope = "METRO" @classmethod def matches(cls, pstate): """Returns True if this town has a SPACE background.""" return pstate.elements["BACKSTORY"] and "SPACE" in pstate.elements["BACKSTORY"].generated_state.keywords def custom_init(self, nart): # Create a building within the town. building = self.register_element("_EXTERIOR", ghterrain.BrickBuilding( waypoints={"DOOR": ghwaypoints.ScrapIronDoor(name="Town Hall")}, tags=[pbge.randmaps.CITY_GRID_ROAD_OVERLAP]), dident="LOCALE") # Add the interior scene. team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team",faction=self.elements["METRO_FACTION"]) intscene = gears.GearHeadScene(35, 35, "Town Hall", player_team=team1, civilian_team=team2, attributes=(gears.tags.SCENE_PUBLIC, gears.tags.SCENE_GOVERNMENT), scale=gears.scale.HumanScale) intscenegen = pbge.randmaps.SceneGenerator(intscene, gharchitecture.DefaultBuilding(floor_terrain=ghterrain.WhiteTileFloor)) self.register_scene(nart, intscene, intscenegen, ident="INTERIOR", dident="LOCALE") foyer = self.register_element('_introom', pbge.randmaps.rooms.ClosedRoom(anchor=pbge.randmaps.anchors.south,), dident="INTERIOR") mycon2 = plotutility.TownBuildingConnection(self, self.elements["LOCALE"], intscene, room1=building, room2=foyer, door1=building.waypoints["DOOR"], move_door1=False) npc = self.register_element("LEADER", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.ALL_JOBS["Technocrat"], faction = self.elements["METRO_FACTION"] )) npc.place(intscene, team=team2) self.town_origin_ready = True bodyguard = self.register_element( "BODYGUARD", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.choose_random_job((gears.tags.Adventurer,),self.elements["LOCALE"].attributes), faction = self.elements["METRO_FACTION"] )) bodyguard.place(intscene, team=team2) return True def _tell_town_origin(self,camp): self.town_origin_ready = False def LEADER_offers(self, camp): mylist = list() mylist.append(Offer("[HELLO] You are in {}.".format(str(self.elements["LOCALE"])), context=ContextTag([context.HELLO]), )) if self.town_origin_ready: mylist.append(Offer(" ".join(self.elements["BACKSTORY"].results["text"]), context=ContextTag([context.INFO]),effect=self._tell_town_origin, data={"subject":"this place"}, no_repeats=True )) return mylist class VaultOrder(Plot): LABEL = "DZRS_ORDER" active = True scope = "METRO" @classmethod def matches(cls, pstate): """Returns True if this town has a FALLOUT_SHELTER background.""" return pstate.elements["BACKSTORY"] and "FALLOUT_SHELTER" in pstate.elements["BACKSTORY"].generated_state.keywords def custom_init(self, nart): # Add the interior scene. team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team",faction=self.elements["METRO_FACTION"]) intscene = gears.GearHeadScene(35, 35, "Fallout Shelter", player_team=team1, civilian_team=team2, attributes=(gears.tags.SCENE_PUBLIC, gears.tags.SCENE_GOVERNMENT, gears.tags.SCENE_RUINS), scale=gears.scale.HumanScale) intscenegen = pbge.randmaps.SceneGenerator(intscene, gharchitecture.DefaultBuilding()) self.register_scene(nart, intscene, intscenegen, ident="INTERIOR", dident="LOCALE") foyer = self.register_element('_introom', pbge.randmaps.rooms.ClosedRoom(anchor=pbge.randmaps.anchors.south,), dident="INTERIOR") mycon2 = plotutility.TownBuildingConnection(self, self.elements["LOCALE"], intscene, room2=foyer, door1=ghwaypoints.UndergroundEntrance(name="Fallout Shelter")) npc = self.register_element("LEADER", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.ALL_JOBS["Mayor"], faction = self.elements["METRO_FACTION"] )) npc.place(intscene, team=team2) self.town_origin_ready = True bodyguard = self.register_element( "BODYGUARD", gears.selector.random_character( self.rank, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.choose_random_job((gears.tags.Adventurer,),self.elements["LOCALE"].attributes), faction = self.elements["METRO_FACTION"] )) bodyguard.place(intscene, team=team2) return True def _tell_town_origin(self,camp): self.town_origin_ready = False def LEADER_offers(self, camp): mylist = list() mylist.append(Offer("[HELLO] Welcome to the heart of {}.".format(str(self.elements["LOCALE"])), context=ContextTag([context.HELLO]), )) if self.town_origin_ready: mylist.append(Offer(" ".join(self.elements["BACKSTORY"].results["text"]), context=ContextTag([context.INFO]),effect=self._tell_town_origin, data={"subject":"this place"}, no_repeats=True )) return mylist # *********************** # *** DZRS_GARAGE *** # *********************** class SomewhatOkayGarage(Plot): LABEL = "DZRS_GARAGE" active = True scope = "INTERIOR" def custom_init(self, nart): # Create a building within the town. npc_name,garage_name = self.generate_npc_and_building_name() building = self.register_element("_EXTERIOR", ghterrain.ScrapIronBuilding( waypoints={"DOOR": ghwaypoints.ScrapIronDoor(name=garage_name)}, tags=[pbge.randmaps.CITY_GRID_ROAD_OVERLAP]), dident="LOCALE") # Add the interior scene. team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team") intscene = gears.GearHeadScene(35, 35, garage_name, player_team=team1, civilian_team=team2, attributes=(gears.tags.SCENE_PUBLIC, gears.tags.SCENE_GARAGE, gears.tags.SCENE_SHOP), scale=gears.scale.HumanScale) intscenegen = pbge.randmaps.SceneGenerator(intscene, gharchitecture.ScrapIronWorkshop()) self.register_scene(nart, intscene, intscenegen, ident="INTERIOR", dident="LOCALE") foyer = self.register_element('_introom', pbge.randmaps.rooms.ClosedRoom(anchor=pbge.randmaps.anchors.south,), dident="INTERIOR") foyer.contents.append(ghwaypoints.MechEngTerminal()) foyer.contents.append(ghwaypoints.MechaPoster()) mycon2 = plotutility.TownBuildingConnection(self, self.elements["LOCALE"], intscene, room1=building, room2=foyer, door1=building.waypoints["DOOR"], move_door1=False) npc = self.register_element("SHOPKEEPER", gears.selector.random_character( self.rank, name=npc_name, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.ALL_JOBS["Mechanic"] )) npc.place(intscene, team=team2) self.shop = services.Shop(npc=npc, shop_faction=gears.factions.TerranDefenseForce, ware_types=services.GENERAL_STORE_PLUS_MECHA, rank=self.rank // 2) return True def SHOPKEEPER_offers(self, camp): mylist = list() mylist.append(Offer("[HELLO] Welcome to {}, where [shop_slogan]!".format(str(self.elements["INTERIOR"])), context=ContextTag([context.HELLO]), )) mylist.append(Offer("[OPENSHOP]", context=ContextTag([context.OPEN_SHOP]), effect=self.shop, data={"shop_name": str(self.elements["INTERIOR"]), "wares": "good stuff"} )) return mylist NAME_PATTERNS = ("{npc}'s Service","{town} Garage", "{npc}'s Sales & Service", "{npc}'s Mechastop") def generate_npc_and_building_name(self): npc_name = gears.selector.EARTH_NAMES.gen_word() building_name = random.choice(self.NAME_PATTERNS).format(npc=npc_name,town=str(self.elements["LOCALE"])) return npc_name,building_name class FranklyBoringGarage(Plot): LABEL = "DZRS_GARAGE" active = True scope = "INTERIOR" def custom_init(self, nart): # Create a building within the town. npc_name,garage_name = self.generate_npc_and_building_name() building = self.register_element("_EXTERIOR", ghterrain.ScrapIronBuilding( waypoints={"DOOR": ghwaypoints.ScrapIronDoor(name=garage_name)}, tags=[pbge.randmaps.CITY_GRID_ROAD_OVERLAP]), dident="LOCALE") # Add the interior scene. team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team") intscene = gears.GearHeadScene(35, 35, garage_name, player_team=team1, civilian_team=team2, attributes=(gears.tags.SCENE_PUBLIC, gears.tags.SCENE_GARAGE), scale=gears.scale.HumanScale) intscenegen = pbge.randmaps.SceneGenerator(intscene, gharchitecture.ScrapIronWorkshop()) self.register_scene(nart, intscene, intscenegen, ident="INTERIOR", dident="LOCALE") foyer = self.register_element('_introom', pbge.randmaps.rooms.ClosedRoom(anchor=pbge.randmaps.anchors.south,), dident="INTERIOR") foyer.contents.append(ghwaypoints.MechEngTerminal()) foyer.contents.append(ghwaypoints.MechaPoster()) mycon2 = plotutility.TownBuildingConnection(self, self.elements["LOCALE"], intscene, room1=building, room2=foyer, door1=building.waypoints["DOOR"], move_door1=False) npc = self.register_element("SHOPKEEPER", gears.selector.random_character( self.rank, name=npc_name, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.ALL_JOBS["Mechanic"] )) npc.place(intscene, team=team2) self.shop = services.Shop(npc=npc, shop_faction=gears.factions.TerranDefenseForce, ware_types=services.BARE_ESSENTIALS_STORE, rank=self.rank // 4) return True def SHOPKEEPER_offers(self, camp): mylist = list() mylist.append(Offer("[HELLO]".format(str(self.elements["INTERIOR"])), context=ContextTag([context.HELLO]), )) mylist.append(Offer("[OPENSHOP]", context=ContextTag([context.OPEN_SHOP]), effect=self.shop, data={"shop_name": str(self.elements["INTERIOR"]), "wares": "essentials"} )) return mylist NAME_PATTERNS = ("{npc}'s Garage","{town} Garage","{town} Repairs", "{town} Service Center", "{town} Fixit Shop") def generate_npc_and_building_name(self): npc_name = gears.selector.EARTH_NAMES.gen_word() building_name = random.choice(self.NAME_PATTERNS).format(npc=npc_name,town=str(self.elements["LOCALE"])) return npc_name,building_name # ************************* # *** DZRS_HOSPITAL *** # ************************* class DeadzoneClinic(Plot): LABEL = "DZRS_HOSPITAL" active = True scope = "INTERIOR" def custom_init(self, nart): # Create a building within the town. myname = "{} Clinic".format(self.elements["LOCALE"]) building = self.register_element("_EXTERIOR", ghterrain.BrickBuilding( waypoints={"DOOR": ghwaypoints.WoodenDoor(name=myname)}, tags=[pbge.randmaps.CITY_GRID_ROAD_OVERLAP]), dident="LOCALE") # Add the interior scene. team1 = teams.Team(name="Player Team") team2 = teams.Team(name="Civilian Team") intscene = gears.GearHeadScene(35, 35, myname, player_team=team1, civilian_team=team2, attributes=(gears.tags.SCENE_PUBLIC, gears.tags.SCENE_HOSPITAL), scale=gears.scale.HumanScale) intscenegen = pbge.randmaps.SceneGenerator(intscene, gharchitecture.HospitalBuilding()) self.register_scene(nart, intscene, intscenegen, ident="INTERIOR", dident="LOCALE") foyer = self.register_element('_introom', pbge.randmaps.rooms.ClosedRoom(anchor=pbge.randmaps.anchors.south, ), dident="INTERIOR") mycon2 = plotutility.TownBuildingConnection(self, self.elements["LOCALE"], intscene, room1=building, room2=foyer, door1=building.waypoints["DOOR"], move_door1=False) npc = self.register_element("DOCTOR", gears.selector.random_character(50, local_tags=self.elements["LOCALE"].attributes, job=gears.jobs.ALL_JOBS["Doctor"])) npc.place(intscene, team=team2) return True def DOCTOR_offers(self, camp): mylist = list() mylist.append(Offer("[HELLO] How are you feeling today?", context=ContextTag([context.HELLO]), )) return mylist # ********************* # *** DZRS_SHOP *** # *********************

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165

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Python

vimfiles/bundle/vim-python/submodules/pylint/tests/regrtest_data/absimp/string.py

ciskoinch8/vimrc

5bf77a7e7bc70fac5173ab2e9ea05d7dda3e52b8

[ "MIT" ]

463

2015-01-15T08:17:42.000Z

2022-03-28T15:10:20.000Z

vimfiles/bundle/vim-python/submodules/pylint/tests/regrtest_data/absimp/string.py

ciskoinch8/vimrc

5bf77a7e7bc70fac5173ab2e9ea05d7dda3e52b8

[ "MIT" ]

52

2015-01-06T02:43:59.000Z

2022-03-14T11:15:21.000Z

vimfiles/bundle/vim-python/submodules/pylint/tests/regrtest_data/absimp/string.py

ciskoinch8/vimrc

5bf77a7e7bc70fac5173ab2e9ea05d7dda3e52b8

[ "MIT" ]

249

2015-01-07T22:49:49.000Z

2022-03-18T02:32:06.000Z

""" https://www.logilab.org/ticket/70495 https://www.logilab.org/ticket/70565 """ from __future__ import absolute_import, print_function import string print(string)

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py

Python

pybind/slxos/v17r_2_00/ntp/__init__.py

extremenetworks/pybind

44c467e71b2b425be63867aba6e6fa28b2cfe7fb

[ "Apache-2.0" ]

null

pybind/slxos/v17r_2_00/ntp/__init__.py

extremenetworks/pybind

44c467e71b2b425be63867aba6e6fa28b2cfe7fb

[ "Apache-2.0" ]

null

pybind/slxos/v17r_2_00/ntp/__init__.py

extremenetworks/pybind

44c467e71b2b425be63867aba6e6fa28b2cfe7fb

[ "Apache-2.0" ]

1

2021-11-05T22:15:42.000Z

from operator import attrgetter import pyangbind.lib.xpathhelper as xpathhelper from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType from pyangbind.lib.base import PybindBase from decimal import Decimal from bitarray import bitarray import __builtin__ import server import authentication_key import peer import disable class ntp(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module brocade-ntp - based on the path /ntp. Each member element of the container is represented as a class variable - with a specific YANG type. """ __slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__server','__authentication_key','__peer','__source_ip','__disable','__authenticate','__trusted_key','__master',) _yang_name = 'ntp' _rest_name = 'ntp' _pybind_generated_by = 'container' def __init__(self, *args, **kwargs): path_helper_ = kwargs.pop("path_helper", None) if path_helper_ is False: self._path_helper = False elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper): self._path_helper = path_helper_ elif hasattr(self, "_parent"): path_helper_ = getattr(self._parent, "_path_helper", False) self._path_helper = path_helper_ else: self._path_helper = False extmethods = kwargs.pop("extmethods", None) if extmethods is False: self._extmethods = False elif extmethods is not None and isinstance(extmethods, dict): self._extmethods = extmethods elif hasattr(self, "_parent"): extmethods = getattr(self._parent, "_extmethods", None) self._extmethods = extmethods else: self._extmethods = False self.__authenticate = YANGDynClass(base=YANGBool, is_leaf=True, yang_name="authenticate", rest_name="authenticate", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Enable NTP authentication. Default = Disabled', u'cli-full-command': None, u'callpoint': u'ntp_auth_cp', u'sort-priority': u'32', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='empty', is_config=True) self.__source_ip = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'chassis-ip': {'value': 1}, u'mm-ip': {'value': 2}},), default=unicode("mm-ip"), is_leaf=True, yang_name="source-ip", rest_name="source-ip", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure the source ip to be used for NTP', u'cli-full-command': None, u'callpoint': u'ntp_srcip_cp', u'sort-priority': u'33'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='srcip_type', is_config=True) self.__server = YANGDynClass(base=YANGListType("ip",server.server, yang_name="server", rest_name="server", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}), is_container='list', yang_name="server", rest_name="server", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) self.__trusted_key = YANGDynClass(base=TypedListType(allowed_type=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1 .. 65535']})), is_leaf=False, yang_name="trusted-key", rest_name="trusted-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP trusted key', u'cli-full-command': None, u'callpoint': u'ntp_trust_cp', u'sort-priority': u'31', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='trust-key', is_config=True) self.__disable = YANGDynClass(base=disable.disable, is_container='container', presence=False, yang_name="disable", rest_name="disable", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Disabling NTP Server/Client mode', u'callpoint': u'ntp_disable_cp', u'sort-priority': u'29', u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='container', is_config=True) self.__master = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'2 .. 15']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(8), is_leaf=True, yang_name="master", rest_name="master", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP Master', u'cli-full-command': None, u'callpoint': u'ntp_master_cp', u'sort-priority': u'34'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='uint32', is_config=True) self.__peer = YANGDynClass(base=YANGListType("peer_ip",peer.peer, yang_name="peer", rest_name="peer", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='peer-ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}), is_container='list', yang_name="peer", rest_name="peer", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) self.__authentication_key = YANGDynClass(base=YANGListType("keyid",authentication_key.authentication_key, yang_name="authentication-key", rest_name="authentication-key", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='keyid', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}), is_container='list', yang_name="authentication-key", rest_name="authentication-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) load = kwargs.pop("load", None) if args: if len(args) > 1: raise TypeError("cannot create a YANG container with >1 argument") all_attr = True for e in self._pyangbind_elements: if not hasattr(args[0], e): all_attr = False break if not all_attr: raise ValueError("Supplied object did not have the correct attributes") for e in self._pyangbind_elements: nobj = getattr(args[0], e) if nobj._changed() is False: continue setmethod = getattr(self, "_set_%s" % e) if load is None: setmethod(getattr(args[0], e)) else: setmethod(getattr(args[0], e), load=load) def _path(self): if hasattr(self, "_parent"): return self._parent._path()+[self._yang_name] else: return [u'ntp'] def _rest_path(self): if hasattr(self, "_parent"): if self._rest_name: return self._parent._rest_path()+[self._rest_name] else: return self._parent._rest_path() else: return [u'ntp'] def _get_server(self): """ Getter method for server, mapped from YANG variable /ntp/server (list) """ return self.__server def _set_server(self, v, load=False): """ Setter method for server, mapped from YANG variable /ntp/server (list) If this variable is read-only (config: false) in the source YANG file, then _set_server is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_server() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=YANGListType("ip",server.server, yang_name="server", rest_name="server", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}), is_container='list', yang_name="server", rest_name="server", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """server must be of a type compatible with list""", 'defined-type': "list", 'generated-type': """YANGDynClass(base=YANGListType("ip",server.server, yang_name="server", rest_name="server", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}), is_container='list', yang_name="server", rest_name="server", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True)""", }) self.__server = t if hasattr(self, '_set'): self._set() def _unset_server(self): self.__server = YANGDynClass(base=YANGListType("ip",server.server, yang_name="server", rest_name="server", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}), is_container='list', yang_name="server", rest_name="server", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP server', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'35', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-server'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) def _get_authentication_key(self): """ Getter method for authentication_key, mapped from YANG variable /ntp/authentication_key (list) """ return self.__authentication_key def _set_authentication_key(self, v, load=False): """ Setter method for authentication_key, mapped from YANG variable /ntp/authentication_key (list) If this variable is read-only (config: false) in the source YANG file, then _set_authentication_key is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_authentication_key() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=YANGListType("keyid",authentication_key.authentication_key, yang_name="authentication-key", rest_name="authentication-key", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='keyid', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}), is_container='list', yang_name="authentication-key", rest_name="authentication-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """authentication_key must be of a type compatible with list""", 'defined-type': "list", 'generated-type': """YANGDynClass(base=YANGListType("keyid",authentication_key.authentication_key, yang_name="authentication-key", rest_name="authentication-key", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='keyid', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}), is_container='list', yang_name="authentication-key", rest_name="authentication-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True)""", }) self.__authentication_key = t if hasattr(self, '_set'): self._set() def _unset_authentication_key(self): self.__authentication_key = YANGDynClass(base=YANGListType("keyid",authentication_key.authentication_key, yang_name="authentication-key", rest_name="authentication-key", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='keyid', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}), is_container='list', yang_name="authentication-key", rest_name="authentication-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'authentication key', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'30', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'cli-incomplete-command': None, u'callpoint': u'ntp-key'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) def _get_peer(self): """ Getter method for peer, mapped from YANG variable /ntp/peer (list) """ return self.__peer def _set_peer(self, v, load=False): """ Setter method for peer, mapped from YANG variable /ntp/peer (list) If this variable is read-only (config: false) in the source YANG file, then _set_peer is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_peer() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=YANGListType("peer_ip",peer.peer, yang_name="peer", rest_name="peer", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='peer-ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}), is_container='list', yang_name="peer", rest_name="peer", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """peer must be of a type compatible with list""", 'defined-type': "list", 'generated-type': """YANGDynClass(base=YANGListType("peer_ip",peer.peer, yang_name="peer", rest_name="peer", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='peer-ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}), is_container='list', yang_name="peer", rest_name="peer", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True)""", }) self.__peer = t if hasattr(self, '_set'): self._set() def _unset_peer(self): self.__peer = YANGDynClass(base=YANGListType("peer_ip",peer.peer, yang_name="peer", rest_name="peer", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='peer-ip', extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}), is_container='list', yang_name="peer", rest_name="peer", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-suppress-key-sort': None, u'info': u'Configure NTP peer', u'cli-no-key-completion': None, u'cli-suppress-mode': None, u'sort-priority': u'36', u'cli-suppress-list-no': None, u'cli-full-no': None, u'cli-compact-syntax': None, u'cli-suppress-key-abbreviation': None, u'callpoint': u'ntp-peer'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='list', is_config=True) def _get_source_ip(self): """ Getter method for source_ip, mapped from YANG variable /ntp/source_ip (srcip_type) """ return self.__source_ip def _set_source_ip(self, v, load=False): """ Setter method for source_ip, mapped from YANG variable /ntp/source_ip (srcip_type) If this variable is read-only (config: false) in the source YANG file, then _set_source_ip is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_source_ip() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'chassis-ip': {'value': 1}, u'mm-ip': {'value': 2}},), default=unicode("mm-ip"), is_leaf=True, yang_name="source-ip", rest_name="source-ip", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure the source ip to be used for NTP', u'cli-full-command': None, u'callpoint': u'ntp_srcip_cp', u'sort-priority': u'33'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='srcip_type', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """source_ip must be of a type compatible with srcip_type""", 'defined-type': "brocade-ntp:srcip_type", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'chassis-ip': {'value': 1}, u'mm-ip': {'value': 2}},), default=unicode("mm-ip"), is_leaf=True, yang_name="source-ip", rest_name="source-ip", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure the source ip to be used for NTP', u'cli-full-command': None, u'callpoint': u'ntp_srcip_cp', u'sort-priority': u'33'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='srcip_type', is_config=True)""", }) self.__source_ip = t if hasattr(self, '_set'): self._set() def _unset_source_ip(self): self.__source_ip = YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'chassis-ip': {'value': 1}, u'mm-ip': {'value': 2}},), default=unicode("mm-ip"), is_leaf=True, yang_name="source-ip", rest_name="source-ip", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure the source ip to be used for NTP', u'cli-full-command': None, u'callpoint': u'ntp_srcip_cp', u'sort-priority': u'33'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='srcip_type', is_config=True) def _get_disable(self): """ Getter method for disable, mapped from YANG variable /ntp/disable (container) """ return self.__disable def _set_disable(self, v, load=False): """ Setter method for disable, mapped from YANG variable /ntp/disable (container) If this variable is read-only (config: false) in the source YANG file, then _set_disable is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_disable() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=disable.disable, is_container='container', presence=False, yang_name="disable", rest_name="disable", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Disabling NTP Server/Client mode', u'callpoint': u'ntp_disable_cp', u'sort-priority': u'29', u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """disable must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=disable.disable, is_container='container', presence=False, yang_name="disable", rest_name="disable", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Disabling NTP Server/Client mode', u'callpoint': u'ntp_disable_cp', u'sort-priority': u'29', u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='container', is_config=True)""", }) self.__disable = t if hasattr(self, '_set'): self._set() def _unset_disable(self): self.__disable = YANGDynClass(base=disable.disable, is_container='container', presence=False, yang_name="disable", rest_name="disable", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Disabling NTP Server/Client mode', u'callpoint': u'ntp_disable_cp', u'sort-priority': u'29', u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='container', is_config=True) def _get_authenticate(self): """ Getter method for authenticate, mapped from YANG variable /ntp/authenticate (empty) """ return self.__authenticate def _set_authenticate(self, v, load=False): """ Setter method for authenticate, mapped from YANG variable /ntp/authenticate (empty) If this variable is read-only (config: false) in the source YANG file, then _set_authenticate is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_authenticate() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=YANGBool, is_leaf=True, yang_name="authenticate", rest_name="authenticate", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Enable NTP authentication. Default = Disabled', u'cli-full-command': None, u'callpoint': u'ntp_auth_cp', u'sort-priority': u'32', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='empty', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """authenticate must be of a type compatible with empty""", 'defined-type': "empty", 'generated-type': """YANGDynClass(base=YANGBool, is_leaf=True, yang_name="authenticate", rest_name="authenticate", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Enable NTP authentication. Default = Disabled', u'cli-full-command': None, u'callpoint': u'ntp_auth_cp', u'sort-priority': u'32', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='empty', is_config=True)""", }) self.__authenticate = t if hasattr(self, '_set'): self._set() def _unset_authenticate(self): self.__authenticate = YANGDynClass(base=YANGBool, is_leaf=True, yang_name="authenticate", rest_name="authenticate", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Enable NTP authentication. Default = Disabled', u'cli-full-command': None, u'callpoint': u'ntp_auth_cp', u'sort-priority': u'32', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='empty', is_config=True) def _get_trusted_key(self): """ Getter method for trusted_key, mapped from YANG variable /ntp/trusted_key (trust-key) """ return self.__trusted_key def _set_trusted_key(self, v, load=False): """ Setter method for trusted_key, mapped from YANG variable /ntp/trusted_key (trust-key) If this variable is read-only (config: false) in the source YANG file, then _set_trusted_key is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_trusted_key() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=TypedListType(allowed_type=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1 .. 65535']})), is_leaf=False, yang_name="trusted-key", rest_name="trusted-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP trusted key', u'cli-full-command': None, u'callpoint': u'ntp_trust_cp', u'sort-priority': u'31', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='trust-key', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """trusted_key must be of a type compatible with trust-key""", 'defined-type': "brocade-ntp:trust-key", 'generated-type': """YANGDynClass(base=TypedListType(allowed_type=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1 .. 65535']})), is_leaf=False, yang_name="trusted-key", rest_name="trusted-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP trusted key', u'cli-full-command': None, u'callpoint': u'ntp_trust_cp', u'sort-priority': u'31', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='trust-key', is_config=True)""", }) self.__trusted_key = t if hasattr(self, '_set'): self._set() def _unset_trusted_key(self): self.__trusted_key = YANGDynClass(base=TypedListType(allowed_type=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'1 .. 65535']})), is_leaf=False, yang_name="trusted-key", rest_name="trusted-key", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP trusted key', u'cli-full-command': None, u'callpoint': u'ntp_trust_cp', u'sort-priority': u'31', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='trust-key', is_config=True) def _get_master(self): """ Getter method for master, mapped from YANG variable /ntp/master (uint32) """ return self.__master def _set_master(self, v, load=False): """ Setter method for master, mapped from YANG variable /ntp/master (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_master is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_master() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'2 .. 15']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(8), is_leaf=True, yang_name="master", rest_name="master", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP Master', u'cli-full-command': None, u'callpoint': u'ntp_master_cp', u'sort-priority': u'34'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='uint32', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """master must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'2 .. 15']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(8), is_leaf=True, yang_name="master", rest_name="master", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP Master', u'cli-full-command': None, u'callpoint': u'ntp_master_cp', u'sort-priority': u'34'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='uint32', is_config=True)""", }) self.__master = t if hasattr(self, '_set'): self._set() def _unset_master(self): self.__master = YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), restriction_dict={'range': [u'2 .. 15']}), default=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32)(8), is_leaf=True, yang_name="master", rest_name="master", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'NTP Master', u'cli-full-command': None, u'callpoint': u'ntp_master_cp', u'sort-priority': u'34'}}, namespace='urn:brocade.com:mgmt:brocade-ntp', defining_module='brocade-ntp', yang_type='uint32', is_config=True) server = __builtin__.property(_get_server, _set_server) authentication_key = __builtin__.property(_get_authentication_key, _set_authentication_key) peer = __builtin__.property(_get_peer, _set_peer) source_ip = __builtin__.property(_get_source_ip, _set_source_ip) disable = __builtin__.property(_get_disable, _set_disable) authenticate = __builtin__.property(_get_authenticate, _set_authenticate) trusted_key = __builtin__.property(_get_trusted_key, _set_trusted_key) master = __builtin__.property(_get_master, _set_master) _pyangbind_elements = {'server': server, 'authentication_key': authentication_key, 'peer': peer, 'source_ip': source_ip, 'disable': disable, 'authenticate': authenticate, 'trusted_key': trusted_key, 'master': master, }

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d01687f736e357983424ef314c79072066cdcee1

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py

Python

seekr2/tests/test_converge.py

seekrcentral/seekr2

45154d477147f9278b97491a6270ff31435c837b

[ "MIT" ]

1

2021-07-14T16:13:17.000Z

seekr2/tests/test_converge.py

seekrcentral/seekr2

45154d477147f9278b97491a6270ff31435c837b

[ "MIT" ]

10

2021-05-26T15:29:46.000Z

2021-09-20T18:23:20.000Z

seekr2/tests/test_converge.py

seekrcentral/seekr2

45154d477147f9278b97491a6270ff31435c837b

[ "MIT" ]

1

2021-05-22T01:15:46.000Z

""" test_converge.py Testing converge.py """ import os import glob import pytest import seekr2.converge as converge import seekr2.tests.test_common_converge as test_common_converge import seekr2.modules.common_analyze as common_analyze import seekr2.modules.common_converge as common_converge def test_converge_default(smoluchowski_mmvt_model): steps = 1000 cutoff = 0.1 minimum_anchor_transitions = 100 image_directory = common_analyze.make_image_directory( smoluchowski_mmvt_model, None) k_on_state = 0 smoluchowski_mmvt_model, standard_time, standard_k_on\ = test_common_converge.make_model_completed(smoluchowski_mmvt_model, steps) data_sample_list = converge.converge( smoluchowski_mmvt_model, k_on_state, image_directory=image_directory, verbose=True) rmsd_convergence_results = common_converge.calc_RMSD_conv_amount( smoluchowski_mmvt_model, data_sample_list) transition_minima, transition_prob_results, transition_time_results \ = common_converge.calc_transition_steps( smoluchowski_mmvt_model, data_sample_list[-1]) bd_transition_counts = data_sample_list[-1].bd_transition_counts converge.print_convergence_results( smoluchowski_mmvt_model, rmsd_convergence_results, cutoff, transition_prob_results, transition_time_results, minimum_anchor_transitions, bd_transition_counts) return def test_converge_no_bd(smoluchowski_mmvt_model): steps = 1000 cutoff = 0.1 minimum_anchor_transitions = 100 k_on_state = 0 smoluchowski_mmvt_model, standard_time, standard_k_on\ = test_common_converge.make_model_completed(smoluchowski_mmvt_model, steps) smoluchowski_mmvt_model.browndye_settings = None smoluchowski_mmvt_model.k_on_info = None data_sample_list = converge.converge( smoluchowski_mmvt_model, k_on_state, image_directory=None, verbose=False) rmsd_convergence_results = common_converge.calc_RMSD_conv_amount( smoluchowski_mmvt_model, data_sample_list) transition_minima, transition_prob_results, transition_time_results \ = common_converge.calc_transition_steps( smoluchowski_mmvt_model, data_sample_list[-1]) bd_transition_counts = data_sample_list[-1].bd_transition_counts converge.print_convergence_results( smoluchowski_mmvt_model, rmsd_convergence_results, cutoff, transition_prob_results, transition_time_results, minimum_anchor_transitions, bd_transition_counts) return def test_converge_missing_bd(smoluchowski_mmvt_model): steps = 1000 cutoff = 0.1 minimum_anchor_transitions = 100 k_on_state = 0 smoluchowski_mmvt_model, standard_time, standard_k_on\ = test_common_converge.make_model_completed(smoluchowski_mmvt_model, steps) b_surface_dir_path = os.path.join( smoluchowski_mmvt_model.anchor_rootdir, smoluchowski_mmvt_model.k_on_info.b_surface_directory) results_glob = os.path.join(b_surface_dir_path, "results*.xml") for results_file in glob.glob(results_glob): print("removing file:", results_file) os.remove(results_file) data_sample_list = converge.converge( smoluchowski_mmvt_model, k_on_state, image_directory=None, verbose=False) rmsd_convergence_results = common_converge.calc_RMSD_conv_amount( smoluchowski_mmvt_model, data_sample_list) transition_minima, transition_prob_results, transition_time_results \ = common_converge.calc_transition_steps( smoluchowski_mmvt_model, data_sample_list[-1]) bd_transition_counts = data_sample_list[-1].bd_transition_counts converge.print_convergence_results( smoluchowski_mmvt_model, rmsd_convergence_results, cutoff, transition_prob_results, transition_time_results, minimum_anchor_transitions, bd_transition_counts) return def test_converge_missing_anchor_stats(smoluchowski_mmvt_model): steps = 1000 cutoff = 0.1 minimum_anchor_transitions = 100 k_on_state = 0 smoluchowski_mmvt_model, standard_time, standard_k_on\ = test_common_converge.make_model_completed(smoluchowski_mmvt_model, steps) anchor_dir_path = os.path.join( smoluchowski_mmvt_model.anchor_rootdir, smoluchowski_mmvt_model.anchors[1].directory, smoluchowski_mmvt_model.anchors[1].production_directory) results_glob = os.path.join(anchor_dir_path, "mmvt*.out") for results_file in glob.glob(results_glob): os.remove(results_file) data_sample_list = converge.converge( smoluchowski_mmvt_model, k_on_state, image_directory=None, verbose=False) rmsd_convergence_results = common_converge.calc_RMSD_conv_amount( smoluchowski_mmvt_model, data_sample_list) transition_minima, transition_prob_results, transition_time_results \ = common_converge.calc_transition_steps( smoluchowski_mmvt_model, data_sample_list[-1]) bd_transition_counts = data_sample_list[-1].bd_transition_counts converge.print_convergence_results( smoluchowski_mmvt_model, rmsd_convergence_results, cutoff, transition_prob_results, transition_time_results, minimum_anchor_transitions, bd_transition_counts) return def test_converge_sparse_anchor_stats(smoluchowski_mmvt_model): steps = 1000 cutoff = 0.1 minimum_anchor_transitions = 100 k_on_state = 0 smoluchowski_mmvt_model, standard_time, standard_k_on\ = test_common_converge.make_model_completed(smoluchowski_mmvt_model, steps) anchor_dir_path = os.path.join( smoluchowski_mmvt_model.anchor_rootdir, smoluchowski_mmvt_model.anchors[1].directory, smoluchowski_mmvt_model.anchors[1].production_directory) results_glob = os.path.join(anchor_dir_path, "mmvt*.out") for results_file in glob.glob(results_glob): with open(results_file, "w") as f: f.write('#"Bounced boundary ID","bounce index","total time (ps)"\n') f.write('1,0,0.442\n') data_sample_list = converge.converge( smoluchowski_mmvt_model, k_on_state, image_directory=None, verbose=False) rmsd_convergence_results = common_converge.calc_RMSD_conv_amount( smoluchowski_mmvt_model, data_sample_list) transition_minima, transition_prob_results, transition_time_results \ = common_converge.calc_transition_steps( smoluchowski_mmvt_model, data_sample_list[-1]) bd_transition_counts = data_sample_list[-1].bd_transition_counts converge.print_convergence_results( smoluchowski_mmvt_model, rmsd_convergence_results, cutoff, transition_prob_results, transition_time_results, minimum_anchor_transitions, bd_transition_counts) return

43.478528

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null

0

8

d01ce01a0e8f9b145f5144d930aab2cad9982fad

228

py

Python

.yw_pipeline/yw_pipeline.py

youwol/workspace-explorer

353a2bc041d0440486b555a5544cda181a2536bd

[ "MIT" ]

null

.yw_pipeline/yw_pipeline.py

youwol/workspace-explorer

353a2bc041d0440486b555a5544cda181a2536bd

[ "MIT" ]

null

.yw_pipeline/yw_pipeline.py

youwol/workspace-explorer

353a2bc041d0440486b555a5544cda181a2536bd

[ "MIT" ]

null

from youwol.configuration import Pipeline from youwol.configuration import UserConfiguration def pipeline(configuration: UserConfiguration) -> Pipeline: return configuration.get_custom_pipeline("typescript-webpack-npm")

25.333333

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0.106383

0.244681

0.308511

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8

d03ea717c4d5616e5684f1053382d9d0f701fe37

14,505

py

Python

src/control_any_sim/interactions.py

DavidMichaelH/TS4ControlAnySim

b80204cfb84522b9b77aeeed8b507d7d4cb23d38

[ "Apache-2.0" ]

25

2019-11-09T12:21:12.000Z

2022-02-14T11:08:48.000Z

src/control_any_sim/interactions.py

DavidMichaelH/TS4ControlAnySim

b80204cfb84522b9b77aeeed8b507d7d4cb23d38

[ "Apache-2.0" ]

41

2019-10-27T13:47:02.000Z

2021-12-05T18:59:08.000Z

src/control_any_sim/interactions.py

DavidMichaelH/TS4ControlAnySim

b80204cfb84522b9b77aeeed8b507d7d4cb23d38

[ "Apache-2.0" ]

16

2019-12-23T14:57:27.000Z

2022-03-25T01:51:21.000Z

import traceback import services # pylint: disable=import-error from interactions.base.immediate_interaction import ImmediateSuperInteraction # pylint: disable=import-error,no-name-in-module from singletons import DEFAULT # pylint: disable=import-error from event_testing.results import TestResult # pylint: disable=import-error from sims4.utils import flexmethod # pylint: disable=import-error from control_any_sim.services.selection_group import SelectionGroupService from control_any_sim.util.logger import Logger class SimMakeSelectableInteraction(ImmediateSuperInteraction): # pylint: disable=too-few-public-methods @flexmethod def test(cls, inst, *args, target=DEFAULT, context=None, **kwargs) -> TestResult: # pylint: disable=no-self-argument try: inst_or_cls = inst if inst is not None else cls Logger.log("testing SimMakeSelectableInteraction, context: {} {}" .format(args, kwargs)) if target: info_target = target.sim_info Logger.log('info_target: {}'.format(info_target)) if context is not None and context.target_sim_id is not None: target_id = context.target_sim_id info_target = services.sim_info_manager().get(target_id) Logger.log('info_target: {}'.format(info_target)) sim_is_selectable = (SelectionGroupService .get(0).is_selectable(info_target.id)) Logger.log("sim_is_selectable: {}".format(sim_is_selectable)) if sim_is_selectable: fail = TestResult(False, "sim is already selectable", inst) Logger.log('fail result: {}'.format(repr(fail))) return fail if target is None or target.sim_info.id != info_target.id: return TestResult.TRUE return (super(SimMakeSelectableInteraction, inst_or_cls) .test(*args, target=target, context=context, **kwargs)) except BaseException: Logger.log(traceback.format_exc()) def _run_interaction_gen(self, timeline): Logger.log("running make selectable interaction...") try: super()._run_interaction_gen(timeline) sim_info = self.target.sim_info if self.context.target_sim_id is not None: sim_info = (services.sim_info_manager() .get(self.context.target_sim_id)) Logger.log("got sim info {} {}" .format(sim_info.first_name, sim_info.last_name)) SelectionGroupService \ .get(services.active_household_id()) \ .make_sim_selectable(sim_info) Logger.log("sim is now selectable!") services.get_first_client().set_active_sim_by_id(sim_info.id) Logger.log("sim is now active!") return True except BaseException: Logger.log(traceback.format_exc()) class SimMakeNotSelectableInteraction(ImmediateSuperInteraction): # pylint: disable=too-few-public-methods @flexmethod def test(cls, inst, *args, target=DEFAULT, context=None, **kwargs) -> TestResult: # pylint: disable=no-self-argument inst_or_cls = inst if inst is not None else cls Logger.log("testing SimMakeNotSelectableInteraction, context: {} {}" .format(args, kwargs)) if target: info_target = target.sim_info Logger.log('info_target: {}'.format(info_target)) if context is not None and context.target_sim_id is not None: target_id = context.target_sim_id info_target = services.sim_info_manager().get(target_id) Logger.log('info_target: {}'.format(info_target)) if cls.must_be_selectable(info_target): return TestResult(False, "sim is in active household and has to be selectable") sim_is_selectable = (SelectionGroupService .get(0).is_selectable(info_target.id)) Logger.log("sim_is_selectable: {}".format(sim_is_selectable)) if not sim_is_selectable: return TestResult(False, "sim is not selectable", inst) if target is None or target.sim_info.id != info_target.id: return TestResult.TRUE return (super(SimMakeNotSelectableInteraction, inst_or_cls) .test(*args, target=target, context=context, **kwargs)) def _run_interaction_gen(self, timeline): Logger.log("running make not selectable interaction...") try: super()._run_interaction_gen(timeline) sim_info = self.target.sim_info if self.context.target_sim_id is not None: sim_info = (services.sim_info_manager() .get(self.context.target_sim_id)) Logger.log("got sim info {} {}" .format(sim_info.first_name, sim_info.last_name)) SelectionGroupService \ .get(services.active_household_id()) \ .remove_sim(sim_info) Logger.log("sim is now not selectable anymore!") return True except BaseException: Logger.log(traceback.format_exc()) @classmethod def must_be_selectable(cls, sim_info): return services.active_household_id() == sim_info.household_id class SimAddRoomMateInteraction(ImmediateSuperInteraction): @flexmethod def test(cls, inst, *args, target=DEFAULT, context=None, **kwargs) -> TestResult: # pylint: disable=no-self-argument try: Logger.log("testing SimAddRoomMateInteraction, context: {} {}".format(args, kwargs)) inst_or_cls = inst if inst is not None else cls roommate_service = services.get_roommate_service() household_id = context.sim.sim_info.household_id if roommate_service is None: return TestResult.NONE if target: info_target = target.sim_info if context.target_sim_id is not None: target_id = context.target_sim_id info_target = services.sim_info_manager().get(target_id) Logger.log('info_target: {}'.format(info_target)) if context.sim.sim_info.id == info_target.id: return TestResult(False, "sim can not be it's own roommate", inst) if roommate_service.is_sim_info_roommate(info_target, household_id): return TestResult(False, "sim is already roommate of this household") return (super(SimAddRoomMateInteraction, inst_or_cls) .test(*args, target=target, context=context, **kwargs)) except BaseException: Logger.log(traceback.format_exc()) def _run_interaction_gen(self, timeline): try: Logger.log("running turn into roommate interaction...") super()._run_interaction_gen(timeline) sim_info = self.target.sim_info home_zone_id = self.get_sim_info_home_zone_id(self.context.sim.sim_info) if self.context.target_sim_id is not None: sim_info = (services.sim_info_manager() .get(self.context.target_sim_id)) Logger.log("got sim info {} {}" .format(sim_info.first_name, sim_info.last_name)) services.get_roommate_service().add_roommate(sim_info, home_zone_id) Logger.log("sim is now a roommate!") return True except BaseException: Logger.log(traceback.format_exc()) @staticmethod def get_sim_info_home_zone_id(sim_info): if sim_info.household is None: return 0 home_zone_id = sim_info.household.home_zone_id if not home_zone_id: return sim_info.roommate_zone_id return home_zone_id class SimRemoveRoomMateInteraction(ImmediateSuperInteraction): @flexmethod def test(cls, inst, *args, target=DEFAULT, context=None, **kwargs) -> TestResult: # pylint: disable=no-self-argument try: inst_or_cls = inst if inst is not None else cls roommate_service = services.get_roommate_service() if roommate_service is None: return TestResult.NONE Logger.log("testing SimRemoveRoomMateInteraction, context: {} {}" .format(args, kwargs)) if target: info_target = target.sim_info if context.target_sim_id is not None: target_id = context.target_sim_id info_target = services.sim_info_manager().get(target_id) household_id = context.sim.sim_info.household_id Logger.log('info_target: {}'.format(info_target)) if context.sim.sim_info.id == info_target.id: return TestResult(False, "sim can not be it's own roommate", inst) if not roommate_service.is_sim_info_roommate(info_target, household_id): return TestResult(False, "sim is not a roommate of current household", inst) return (super(SimRemoveRoomMateInteraction, inst_or_cls) .test(*args, target=target, context=context, **kwargs)) except BaseException: Logger.log(traceback.format_exc()) def _run_interaction_gen(self, timeline): try: Logger.log("running remove roommate interaction...") super()._run_interaction_gen(timeline) sim_info = self.target.sim_info if self.context.target_sim_id is not None: sim_info = (services.sim_info_manager() .get(self.context.target_sim_id)) Logger.log("got sim info {} {}" .format(sim_info.first_name, sim_info.last_name)) services.get_roommate_service().remove_roommate(sim_info) Logger.log("sim is now not a roommate anymore!") return True except BaseException: Logger.log(traceback.format_exc()) class SimHouseholdNpcOnInteraction(ImmediateSuperInteraction): @flexmethod def test(cls, inst, *args, target=DEFAULT, context=None, **kwargs) -> TestResult: # pylint: disable=no-self-argument try: inst_or_cls = inst if inst is not None else cls selection_group = SelectionGroupService.get(services.active_household_id()) Logger.log("testing SimHouseholdNpcOnInteraction, context: {} {}" .format(args, kwargs)) if target: info_target = target.sim_info if context.target_sim_id is not None: target_id = context.target_sim_id info_target = services.sim_info_manager().get(target_id) Logger.log('info_target: {}'.format(info_target)) if selection_group.is_household_npc(info_target): return TestResult(False, "sim is already a household npc", inst) if info_target.household_id != services.active_household_id(): return TestResult(False, "sim is not a member of the active household", inst) return (super(SimHouseholdNpcOnInteraction, inst_or_cls) .test(*args, target=target, context=context, **kwargs)) except BaseException: Logger.log(traceback.format_exc()) def _run_interaction_gen(self, timeline): try: Logger.log("running household npc on interaction...") super()._run_interaction_gen(timeline) sim_info = self.target.sim_info if self.context.target_sim_id is not None: sim_info = (services.sim_info_manager() .get(self.context.target_sim_id)) Logger.log("got sim info {} {}" .format(sim_info.first_name, sim_info.last_name)) selection_group = SelectionGroupService.get(services.active_household_id()) selection_group.add_household_npc(sim_info) Logger.log("sim is now a household npc!") return True except BaseException: Logger.log(traceback.format_exc()) class SimHouseholdNpcOffInteraction(ImmediateSuperInteraction): @flexmethod def test(cls, inst, *args, target=DEFAULT, context=None, **kwargs) -> TestResult: # pylint: disable=no-self-argument try: inst_or_cls = inst if inst is not None else cls selection_group = SelectionGroupService.get(services.active_household_id()) Logger.log("testing SimHouseholdNpcOffInteraction, context: {} {}" .format(args, kwargs)) if target: info_target = target.sim_info if context.target_sim_id is not None: target_id = context.target_sim_id info_target = services.sim_info_manager().get(target_id) Logger.log('info_target: {}'.format(info_target)) if not selection_group.is_household_npc(info_target): return TestResult(False, "sim is not a household npc", inst) if info_target.household_id != services.active_household_id(): return TestResult(False, "sim is not a member of the active household", inst) return (super(SimHouseholdNpcOffInteraction, inst_or_cls) .test(*args, target=target, context=context, **kwargs)) except BaseException: Logger.log(traceback.format_exc()) def _run_interaction_gen(self, timeline): try: Logger.log("running household npc off interaction...") super()._run_interaction_gen(timeline) sim_info = self.target.sim_info if self.context.target_sim_id is not None: sim_info = (services.sim_info_manager() .get(self.context.target_sim_id)) Logger.log("got sim info {} {}" .format(sim_info.first_name, sim_info.last_name)) selection_group = SelectionGroupService.get(services.active_household_id()) selection_group.remove_household_npc(sim_info) Logger.log("sim is now a normal household member!") return True except BaseException: Logger.log(traceback.format_exc())

36.721519

127

0.624061

1,650

14,505

5.249091

0.075152

0.063041

0.044337

0.049879

0.818728

0.798176

0.782011

0.774737

0.749798

0.736405

0

0.000387

0.287073

14,505

394

128

36.814721

0.837153

0.030196

0

0.717557

0

0.100761

0.012453

0

1

0.053435

false

0

0.030534

0.003817

0.225191

0

null

0

1

0

1

0

null

0

7

d06e4e8d74f6408120323b4c1512cbe6e356a50f

1,545

py

Python

test_base.py

src-d/tech-mapping

8739762e2d63b1cdf686e6b1adf52523c07e9fca

[ "Apache-2.0" ]

null

test_base.py

src-d/tech-mapping

8739762e2d63b1cdf686e6b1adf52523c07e9fca

[ "Apache-2.0" ]

null

test_base.py

src-d/tech-mapping

8739762e2d63b1cdf686e6b1adf52523c07e9fca

[ "Apache-2.0" ]

2

2020-01-02T07:56:28.000Z

2021-01-28T11:20:58.000Z

import tm def test_make_snapshots(): base = tm._utc_iso("2013-01-01") lower = tm._utc_iso("2013-01-01") upper = tm._utc_iso("2013-02-01") period = tm._timedelta_days(7) assert [ tm._utc_iso("2013-01-01"), tm._utc_iso("2013-01-08"), tm._utc_iso("2013-01-15"), tm._utc_iso("2013-01-22"), tm._utc_iso("2013-01-29"), ] == tm.make_snapshots(lower, upper, base, period) def test_make_snapshots_middle(): base = tm._utc_iso("2013-01-01") lower = tm._utc_iso("2013-01-06") upper = tm._utc_iso("2013-01-24") period = tm._timedelta_days(7) assert [ tm._utc_iso("2013-01-08"), tm._utc_iso("2013-01-15"), tm._utc_iso("2013-01-22"), ] == tm.make_snapshots(lower, upper, base, period) def test_snapshot_tracker(): base = tm._utc_iso("2013-01-01") lower = tm._utc_iso("2013-01-06") upper = tm._utc_iso("2013-01-24") period = tm._timedelta_days(7) snapshots = tm.make_snapshots(lower, upper, base, period) # assert [ # tm._utc_iso("2013-01-08"), # tm._utc_iso("2013-01-15"), # tm._utc_iso("2013-01-22"), # ] == snapshots tracker = tm._SnapshotTracker(snapshots) assert not tracker.snapshots_for_date(tm._utc_iso("2013-01-24")) assert tracker.snapshots_for_date(tm._utc_iso("2013-01-21")) == [ tm._utc_iso("2013-01-22") ] assert tracker.snapshots_for_date(tm._utc_iso("2013-01-07")) == [ tm._utc_iso("2013-01-15"), tm._utc_iso("2013-01-08"), ]

30.9

69

0.607767

241

1,545

3.585062

0.141079

0.150463

0.240741

0.361111

0.847222

0.813657

0.78588

0.74537

0.607639

0

0.172809

0.209709

1,545

49

70

31.530612

0.534808

0.075081

0

0.578947

0

0.16163

0

0.131579

1

0.078947

false

0

0.026316

0

0.105263

0

null

0

1

0

null

0

8

4bf728582289f272dea861ee582062d24c00c31e

314

py

Python

2752.py

heltonricardo/URI

160cca22d94aa667177c9ebf2a1c9864c5e55b41

[ "MIT" ]

6

2021-04-13T00:33:43.000Z

2022-02-10T10:23:59.000Z

2752.py

heltonricardo/URI

160cca22d94aa667177c9ebf2a1c9864c5e55b41

[ "MIT" ]

null

2752.py

heltonricardo/URI

160cca22d94aa667177c9ebf2a1c9864c5e55b41

[ "MIT" ]

3

2021-03-23T18:42:24.000Z

2022-02-10T10:24:07.000Z

print('<AMO FAZER EXERCICIO NO URI>') print('< AMO FAZER EXERCICIO NO URI>') print('<AMO FAZER EXERCICIO >') print('<AMO FAZER EXERCICIO NO URI>') print('<AMO FAZER EXERCICIO NO URI >') print('<AMO FAZER EXERCICIO NO URI>') print('< AMO FAZER EXERCICIO >') print('<AMO FAZER EXERCICIO >')

34.888889

41

0.640127

42

314

4.785714

0.142857

0.318408

0.517413

0.875622

1

0

0.207006

314

8

42

39.25

0.807229

0

1

0

0.745223

0

1

0

true

0

1

0

null

1

0

1

0

1

0

1

0

null

0

1

0

1

0

14

324bc26fb80ba4177de6e84a40cad0a49867d69d

12,911

py

Python

xlist/find.py

ihgazni2/xlist

3c4cc976dcfabc8bb18022389e67d78ce4bfd659

[ "MIT" ]

null

xlist/find.py

ihgazni2/xlist

3c4cc976dcfabc8bb18022389e67d78ce4bfd659

[ "MIT" ]

null

xlist/find.py

ihgazni2/xlist

3c4cc976dcfabc8bb18022389e67d78ce4bfd659

[ "MIT" ]

null

from .cmmn import null,undefined def find_fst_iv(ol,test_func,*args): length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(cond): return({'index':i,'value':ol[i]}) else: pass return(null) def find_fst_v(ol,test_func,*args): length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(cond): return(ol[i]) else: pass return(null) def find_fst_i(ol,test_func,*args): length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(cond): return(i) else: pass return(null) def find_fst_not_iv(ol,test_func,*args): length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(not(cond)): return({'index':i,'value':ol[i]}) else: pass return(null) def find_fst_not_v(ol,test_func,*args): length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(not(cond)): return(ol[i]) else: pass return(null) def find_fst_not_i(ol,test_func,*args): length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(not(cond)): return(i) else: pass return(null) def find_lst_iv(ol,test_func,*args): length = ol.__len__() for i in range(length-1,-1,-1): cond = test_func(ol[i],*args) if(cond): return({'index':i,'value':ol[i]}) else: pass return(null) def find_lst_i(ol,test_func,*args): length = ol.__len__() for i in range(length-1,-1,-1): cond = test_func(ol[i],*args) if(cond): return(i) else: pass return(null) def find_lst_v(ol,test_func,*args): length = ol.__len__() for i in range(length-1,-1,-1): cond = test_func(ol[i],*args) if(cond): return(ol[i]) else: pass return(null) def find_lst_not_iv(ol,test_func,*args): length = ol.__len__() for i in range(length-1,-1,-1): cond = test_func(ol[i],*args) if(not(cond)): return({'index':i,'value':ol[i]}) else: pass return(null) def find_lst_not_i(ol,test_func,*args): length = ol.__len__() for i in range(length-1,-1,-1): cond = test_func(ol[i],*args) if(not(cond)): return(i) else: pass return(null) def find_lst_not_v(ol,test_func,*args): length = ol.__len__() for i in range(length-1,-1,-1): cond = test_func(ol[i],*args) if(not(cond)): return(ol[i]) else: pass return(null) ### def find_which_iv(ol,test_func,which,*args): length = ol.__len__() seq = -1 for i in range(0,length): cond = test_func(ol[i],*args) if(cond): seq = seq + 1 if(seq == which): return({'index':i,'value':ol[i]}) else: pass else: pass return(null) def find_which_i(ol,test_func,which,*args): rslt = find_which_iv(ol,test_func,which,*args) rslt = rslt if(rslt == null) else rslt['index'] return(rslt) def find_which_v(ol,test_func,which,*args): rslt = find_which_iv(ol,test_func,which,*args) rslt = rslt if(rslt == null) else rslt['value'] return(rslt) def find_which_not_iv(ol,test_func,which,*args): length = ol.__len__() seq = -1 for i in range(0,length): cond = not(test_func(ol[i],*args)) if(cond): seq = seq + 1 if(seq == which): return({'index':i,'value':ol[i]}) else: pass else: pass return(null) def find_which_not_i(ol,test_func,which,*args): rslt = find_which_not_iv(ol,test_func,which,*args) rslt = rslt if(rslt == null) else rslt['index'] return(rslt) def find_which_not_v(ol,test_func,which,*args): rslt = find_which_not_iv(ol,test_func,which,*args) rslt = rslt if(rslt == null) else rslt['value'] return(rslt) def find_some_iv(ol,test_func,*seqs,**kwargs): rslt =[] seqs = list(seqs) length = ol.__len__() seq = -1 other_args = kwargs['other_args'] if('other_args' in kwargs) else [] for i in range(0,length): cond = test_func(ol[i],*other_args) if(cond): seq = seq + 1 if(seq in seqs): rslt.append({'index':i,'value':ol[i]}) else: pass else: pass return(rslt) def find_some_i(ol,test_func,*seqs,**kwargs): rslt = find_some_iv(ol,test_func,*seqs,**kwargs) rslt = list(map(lambda r:r['index'],rslt)) return(rslt) def find_some_v(ol,test_func,*seqs,**kwargs): rslt = find_some_iv(ol,test_func,*seqs,**kwargs) rslt = list(map(lambda r:r['value'],rslt)) return(rslt) def find_some_not_iv(ol,test_func,*seqs,**kwargs): rslt =[] seqs = list(seqs) length = ol.__len__() seq = -1 other_args = kwargs['other_args'] if('other_args' in kwargs) else [] for i in range(0,length): cond = not(test_func(ol[i],*other_args)) if(cond): seq = seq + 1 if(seq in seqs): rslt.append({'index':i,'value':ol[i]}) else: pass else: pass return(rslt) def find_some_not_i(ol,test_func,*seqs,**kwargs): rslt = find_some_not_iv(ol,test_func,*seqs,**kwargs) rslt = list(map(lambda r:r['index'],rslt)) return(rslt) def find_some_not_v(ol,test_func,*seqs,**kwargs): rslt = find_some_not_iv(ol,test_func,*seqs,**kwargs) rslt = list(map(lambda r:r['value'],rslt)) return(rslt) def find_all_iv(ol,test_func,*args): rslt =[] length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(cond): rslt.append({'index':i,'value':ol[i]}) else: pass return(rslt) def find_all_i(ol,test_func,*args): rslt = find_all_iv(ol,test_func,*args) rslt = list(map(lambda r:r['index'],rslt)) return(rslt) def find_all_v(ol,test_func,*args): rslt = find_all_iv(ol,test_func,*args) rslt = list(map(lambda r:r['value'],rslt)) return(rslt) def find_all_not_iv(ol,test_func,*args): rslt =[] length = ol.__len__() for i in range(0,length): cond = test_func(ol[i],*args) if(cond): pass else: rslt.append({'index':i,'value':ol[i]}) return(rslt) def find_all_not_i(ol,test_func,*args): rslt = find_all_not_iv(ol,test_func,*args) rslt = list(map(lambda r:r['index'],rslt)) return(rslt) def find_all_not_v(ol,test_func,*args): rslt = find_all_not_iv(ol,test_func,*args) rslt = list(map(lambda r:r['value'],rslt)) return(rslt) ############ def find_fst_gt_iv(ol,value): test_func = lambda r,v:(r>v) rslt = find_fst_iv(ol,test_func,value) return(rslt) def find_fst_gt_i(ol,value): test_func = lambda r,v:(r>v) rslt = find_fst_i(ol,test_func,value) return(rslt) def find_fst_gt_v(ol,value): test_func = lambda r,v:(r>v) rslt = find_fst_v(ol,test_func,value) return(rslt) def find_lst_gt_iv(ol,value): test_func = lambda r,v:(r>v) rslt = find_lst_iv(ol,test_func,value) return(rslt) def find_lst_gt_i(ol,value): test_func = lambda r,v:(r>v) rslt = find_lst_i(ol,test_func,value) return(rslt) def find_lst_gt_v(ol,value): test_func = lambda r,v:(r>v) rslt = find_lst_v(ol,test_func,value) return(rslt) def find_which_gt_iv(ol,value): test_func = lambda r,v:(r>v) rslt = find_which_iv(ol,test_func,which,value) return(rslt) def find_which_gt_i(ol,value): test_func = lambda r,v:(r>v) rslt = find_which_i(ol,test_func,which,value) return(rslt) def find_which_gt_v(ol,value): test_func = lambda r,v:(r>v) rslt = find_which_v(ol,test_func,which,value) return(rslt) def find_some_gt_iv(ol,value,*seqs): test_func = lambda r,v:(r>v) rslt = find_some_iv(ol,test_func,value,*seqs) return(rslt) def find_some_gt_i(ol,value,*seqs): test_func = lambda r,v:(r>v) rslt = find_some_i(ol,test_func,value,*seqs) return(rslt) def find_some_gt_v(ol,value,*seqs): test_func = lambda r,v:(r>v) rslt = find_some_v(ol,test_func,value,*seqs) return(rslt) def find_all_gt_iv(ol,value): test_func = lambda r,v:(r>v) rslt = find_all_iv(ol,test_func,value) return(rslt) def find_all_gt_i(ol,value): test_func = lambda r,v:(r>v) rslt = find_all_i(ol,test_func,value) return(rslt) def find_all_gt_v(ol,value): test_func = lambda r,v:(r>v) rslt = find_all_v(ol,test_func,value) return(rslt) def find_fst_lt_iv(ol,value): test_func = lambda r,v:(r<v) rslt = find_fst_iv(ol,test_func,value) return(rslt) def find_fst_lt_i(ol,value): test_func = lambda r,v:(r<v) rslt = find_fst_i(ol,test_func,value) return(rslt) def find_fst_lt_v(ol,value): test_func = lambda r,v:(r<v) rslt = find_fst_v(ol,test_func,value) return(rslt) def find_lst_lt_iv(ol,value): test_func = lambda r,v:(r<v) rslt = find_lst_iv(ol,test_func,value) return(rslt) def find_lst_lt_i(ol,value): test_func = lambda r,v:(r<v) rslt = find_lst_i(ol,test_func,value) return(rslt) def find_lst_lt_v(ol,value): test_func = lambda r,v:(r<v) rslt = find_lst_v(ol,test_func,value) return(rslt) def find_which_lt_iv(ol,value): test_func = lambda r,v:(r<v) rslt = find_which_iv(ol,test_func,which,value) return(rslt) def find_which_lt_i(ol,value): test_func = lambda r,v:(r<v) rslt = find_which_i(ol,test_func,which,value) return(rslt) def find_which_lt_v(ol,value): test_func = lambda r,v:(r<v) rslt = find_which_v(ol,test_func,which,value) return(rslt) def find_some_lt_iv(ol,value,*seqs): test_func = lambda r,v:(r<v) rslt = find_some_iv(ol,test_func,value,*seqs) return(rslt) def find_some_lt_i(ol,value,*seqs): test_func = lambda r,v:(r<v) rslt = find_some_i(ol,test_func,value,*seqs) return(rslt) def find_some_lt_v(ol,value,*seqs): test_func = lambda r,v:(r<v) rslt = find_some_v(ol,test_func,value,*seqs) return(rslt) def find_all_lt_iv(ol,value): test_func = lambda r,v:(r<v) rslt = find_all_iv(ol,test_func,value) return(rslt) def find_all_lt_i(ol,value): test_func = lambda r,v:(r<v) rslt = find_all_i(ol,test_func,value) return(rslt) def find_all_lt_v(ol,value): test_func = lambda r,v:(r<v) rslt = find_all_v(ol,test_func,value) return(rslt) def find_fst_eq_iv(ol,value): test_func = lambda r,v:(r==v) rseq = find_fst_iv(ol,test_func,value) return(rseq) def find_fst_eq_i(ol,value): test_func = lambda r,v:(r==v) rseq = find_fst_i(ol,test_func,value) return(rseq) def find_fst_eq_v(ol,value): test_func = lambda r,v:(r==v) rseq = find_fst_v(ol,test_func,value) return(rseq) def find_lst_eq_iv(ol,value): test_func = lambda r,v:(r==v) rseq = find_lst_iv(ol,test_func,value) return(rseq) def find_lst_eq_i(ol,value): test_func = lambda r,v:(r==v) rseq = find_lst_i(ol,test_func,value) return(rseq) def find_lst_eq_v(ol,value): test_func = lambda r,v:(r==v) rseq = find_lst_v(ol,test_func,value) return(rseq) def find_which_eq_iv(ol,value): test_func = lambda r,v:(r==v) rseq = find_which_iv(ol,test_func,which,value) return(rseq) def find_which_eq_i(ol,value): test_func = lambda r,v:(r==v) rseq = find_which_i(ol,test_func,which,value) return(rseq) def find_which_eq_v(ol,value): test_func = lambda r,v:(r==v) rseq = find_which_v(ol,test_func,which,value) return(rseq) def find_some_eq_iv(ol,value,*seqs): test_func = lambda r,v:(r==v) rseq = find_some_iv(ol,test_func,value,*seqs) return(rseq) def find_some_eq_i(ol,value,*seqs): test_func = lambda r,v:(r==v) rseq = find_some_i(ol,test_func,value,*seqs) return(rseq) def find_some_eq_v(ol,value,*seqs): test_func = lambda r,v:(r==v) rseq = find_some_v(ol,test_func,value,*seqs) return(rseq) def find_all_eq_iv(ol,value): test_func = lambda r,v:(r==v) rseq = find_all_iv(ol,test_func,value) return(rseq) def find_all_eq_i(ol,value): test_func = lambda r,v:(r==v) rseq = find_all_i(ol,test_func,value) return(rseq) def find_all_eq_v(ol,value): test_func = lambda r,v:(r==v) rseq = find_all_v(ol,test_func,value) return(rseq)

21.846024

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0.120299

0.108131

0.994746

0.994331

0.985205

0.979812

0.974696

0.94953

0

0.003907

0.246689

12,911

590

73

21.883051

0.739667

0

0.775656

0

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false

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0.002387

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null

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410b72a8cec3b5a8c08467aa6472a24882c2e9cc

41,157

py

Python

Test_Scripts/create_node_test.py

karlflores/WatchYourBackProject

00a7c32e46ea0b75580d17ea6a22372e4a005627

[ "Unlicense" ]

null

Test_Scripts/create_node_test.py

karlflores/WatchYourBackProject

00a7c32e46ea0b75580d17ea6a22372e4a005627

[ "Unlicense" ]

null

Test_Scripts/create_node_test.py

karlflores/WatchYourBackProject

00a7c32e46ea0b75580d17ea6a22372e4a005627

[ "Unlicense" ]

null

from DepreciatedBoard.Board import Board from Constants import constant from Agents.Minimax import Minimax # create a new board game board_game = Board() board_game.print_board() # create the starting node -- this node is black node = Minimax.create_node(board_game, constant.BLACK_PIECE, None) node.board.print_board() print(node.available_moves) print(node.colour) print() # to create a child node we apply one of the move from black to the next node child = Minimax.create_node(node.board,Board.get_opp_piece_type(node.colour),node.available_moves[2]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print() print("UNDO MOVE") child.board.undo_move() child.board.print_board() print(child.board.eliminated_pieces) print(child.board.piece_pos) child = Minimax.create_node(child.board,Board.get_opp_piece_type(child.colour),child.available_moves[3]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print(child.board.piece_pos) child = Minimax.create_node(child.board,Board.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(len(child.available_moves)) print(child.board.piece_pos) child = Minimax.create_node(child.board,Board.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print(child.board.move_counter) print(child.board.piece_pos) print("UNDO MOVE") child.board.undo_move() child.board.print_board() print(child.board.eliminated_pieces) print(child.board.piece_pos) print(child.board.action_applied) print("UNDO MOVE") child.board.undo_move() child.board.print_board() print(child.board.eliminated_pieces) print(child.board.piece_pos) print(child.board.action_applied) print("UNDO MOVE") child.board.undo_move() child.board.print_board() print(child.board.eliminated_pieces) print(child.board.piece_pos) print(child.board.action_applied) ''' child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print(child.board.move_counter) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print(child.board.move_counter) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print(child.board.move_counter) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print(child.board.move_counter) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(len(child.available_moves)) print(child.colour) print(child.board.move_counter) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print(child.available_moves[7]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[7]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[7]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[7]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[7]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[7]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print(child.board.phase) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print(str(child.board.phase)+ " THIS") child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[1]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[2]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[1]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[5]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[3]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[5]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[3]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[5]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[3]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[5]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[3]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.available_moves[5]) child = Minimax.create_node(child.board,DepreciatedBoard.get_opp_piece_type(child.colour),child.available_moves[3]) child.board.print_board() print(child.available_moves) print(child.colour) print(child.board.move_counter) print() print(child.board.eliminated_pieces) ''' ''' print("UNDO MOVE") child.board.undo_move() child.board.print_board() print(child.board.eliminated_pieces) print(child.board.piece_pos) print("UNDO MOVE") child.board.undo_move() child.board.print_board() print("UNDO MOVE") child.board.undo_move() child.board.print_board() print("UNDO MOVE") child.board.undo_move() child.board.print_board() '''

33.515472

115

0.828729

6,104

41,157

5.359436

0.008191

0.183713

0.25729

0.207618

0.986672

0.985266

0

0.007379

0.03856

41,157

1,227

116

33.542787

0.819358

0.003547

0

0.773585

0

0.019989

0

1

0

false

0

0.056604

0

0.056604

0.754717

0

null

0

1

0

1

0

null

0

1

0

10

f5af0646112bf02b9b1450e6d605ff35ac44404e

112

py

Python

view/python_core/rois/iltis_rois/__init__.py

galizia-lab/pyview

07bef637b0c60fae8830c1b3947e4a7bcd14bb2c

[ "BSD-3-Clause" ]

2

2021-11-07T10:17:16.000Z

2021-11-07T10:17:19.000Z

view/python_core/rois/iltis_rois/__init__.py

galizia-lab/pyview

07bef637b0c60fae8830c1b3947e4a7bcd14bb2c

[ "BSD-3-Clause" ]

5

2021-11-03T12:43:03.000Z

2021-12-16T10:34:52.000Z

view/python_core/rois/iltis_rois/__init__.py

galizia-lab/pyview

07bef637b0c60fae8830c1b3947e4a7bcd14bb2c

[ "BSD-3-Clause" ]

1

2021-09-23T15:46:26.000Z

from .text_based import CircleILTISROIData, PolygonILTISROIData from .tiff_based import SpatialFootprintROIData

37.333333

63

0.892857

11

112

8.909091

0.727273

0.22449

0

0.080357

112

2

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0

1

0

true

0

1

0

1

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1

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null

1

0

1

0

null

0

1

0

1

0

1

0

7

eb03d7b295fc0e85739b7e29272bf77d0fd90688

13,598

py

Python

backend/tests/testU.py

debiai/debiai

7c5d00d13e7795c61e46f03c0653cb785bcc95e2

[ "Apache-2.0" ]

2

2022-03-11T17:34:54.000Z

2022-03-15T14:06:48.000Z

backend/tests/testU.py

DebiAI/debiai

7c5d00d13e7795c61e46f03c0653cb785bcc95e2

[ "Apache-2.0" ]

1

2022-03-01T14:36:19.000Z

backend/tests/testU.py

DebiAI/debiai

7c5d00d13e7795c61e46f03c0653cb785bcc95e2

[ "Apache-2.0" ]

null

import requests import ujson as json import random appUrl = "http://localhost:8080/" # ============== PROJECTS TEST ================= def test_get_projects(): url = appUrl + "projects" resp = requests.request("GET", url, headers={}, data={}) assert resp.status_code == 200 assert type(json.loads(resp.text)) is list def test_get_bad_project(): url = appUrl + "projects/IDONSNTEXIST" payload = {} headers = {} resp = requests.request("GET", url, headers=headers, data=payload) assert resp.status_code == 404 def test_project_noName(): # create url = appUrl + "projects" resp = requests.post(url=url, headers={}, json={}) assert resp.status_code == 200 data = json.loads(resp.text) projID = data["id"] print(projID) print(type(projID)) assert isinstance(projID, unicode) assert len(projID) > 0 # Find back url = appUrl + "projects/" + projID resp = requests.request("GET", url, headers={}, json={}) assert resp.status_code == 200 proj = json.loads(resp.text) print(proj) print(type(proj)) assert type(proj) is dict assert proj["models"] == [] assert proj["evaluations"] == [] assert proj["datasets"] == [] assert proj["blockLevelInfo"] == [] assert len(proj["name"]) > 0 # remove url = appUrl + "projects/" + projID resp = requests.request("DELETE", url, headers={}, data={}) assert resp.status_code == 200 # Dont Find back url = appUrl + "projects/" + projID payload = {} headers = {} resp = requests.request("GET", url, headers=headers, json=payload) assert resp.status_code == 404 def test_project_name(): testProjectName = "My greate project" testProjectId = "" # Create url = appUrl + "projects" payload = {"projectName": testProjectName, "blockLevelInfo": []} headers = {'content-type': "application/json"} resp = requests.post(url=url, headers=headers, json=payload) assert resp.status_code == 200 data = json.loads(resp.text) testProjectId = data["id"] print(testProjectId) assert isinstance(testProjectId, unicode) assert len(testProjectId) > 0 # Get url = appUrl + "projects/" + testProjectId payload = {} headers = {} resp = requests.request("GET", url, headers=headers, data=payload) assert resp.status_code == 200 proj = json.loads(resp.text) print(proj) assert type(proj) is dict assert proj["models"] == [] assert proj["evaluations"] == [] assert proj["datasets"] == [] assert proj["blockLevelInfo"] == [] assert len(proj["name"]) > 0 assert proj["name"] == testProjectName # remove url = appUrl + "projects/" + testProjectId resp = requests.request("DELETE", url, headers=headers, data=payload) assert resp.status_code == 200 # remove Again url = appUrl + "projects/" + testProjectId resp = requests.request("DELETE", url, headers=headers, data=payload) assert resp.status_code == 404 # Dont Find back url = appUrl + "projects/" + testProjectId payload = {} headers = {} resp = requests.request("GET", url, headers=headers, json=payload) assert resp.status_code == 404 def test_project_nameTooLong(): testProjectName = "My greate project that is clearely too long \ stop stop stop stop" # Create url = appUrl + "projects" payload = {"projectName": testProjectName, "blockLevelInfo": []} headers = {'content-type': "application/json"} resp = requests.post(url=url, headers=headers, json=payload) assert resp.status_code == 400 # ============== BLOCKS TEST ================= testProjectId = "" def test_get_Block_BadProject(): url = appUrl + "projects/IDONTEXIST/blocks/" payload = {} headers = {} resp = requests.get(url=url, json=payload, headers=headers) assert resp.status_code == 404 def test_get_Block(): global testProjectId # create Project url = appUrl + "projects" resp = requests.post(url=url, headers={}, json={}) assert resp.status_code == 200 data = json.loads(resp.text) testProjectId = data["id"] print(testProjectId) assert isinstance(testProjectId, unicode) assert len(testProjectId) > 0 url = appUrl + "projects/" + testProjectId + "/blocks" resp = requests.get(url=url, json={}, headers={}) print(resp.text) assert resp.status_code == 200 data = json.loads(resp.text) blocks = data["blocks"] assert blocks == [] def test_post_block_badProjectName(): url = appUrl + "projects/IDONTEXIST/blocks" payload = { "parentId": "", "blockName": "block1", "groundThruthList": {"toto": "tata"}, "inputList": {"toto": "tata"}, "contextList": {"toto": "tata"}, } headers = {'content-type': "application/json"} resp = requests.post(url=url, json=payload, headers=headers) assert resp.status_code == 404 def test_post_block_badParents(): url = appUrl + "projects/" + testProjectId + "/blocks" payload = { "parentId": "IDONTEXIST", "blockName": "poorBlock", "groundThruthList": {"toto": "tata"}, "inputList": {"toto": "tata"}, "contextList": {"toto": "tata"}, } headers = {'content-type': "application/json"} resp = requests.post(url=url, json=payload, headers=headers) assert resp.status_code == 404 def test_post_block(): blockName = "My first block" # ADD first block url = appUrl + "projects/" + testProjectId + "/blocks" payload = { "blockName": blockName, "parentId": "", "groundThruthList": {"toto": "tata"}, "inputList": {"toto": "tata"}, "contextList": {"toto": "tata"}, } resp = requests.post(url=url, json=payload, headers={ 'content-type': "application/json"}) assert resp.status_code == 200 data = json.loads(resp.text) blockTestId = data["blockId"] assert isinstance(blockTestId, unicode) assert len(blockTestId) > 0 # Get url = appUrl + "projects/" + testProjectId + "/blocks" resp = requests.get(url=url, json={}, headers={}) print(resp.text) assert resp.status_code == 200 data = json.loads(resp.text) blocks = data["blocks"] assert len(blocks) == 1 myBlock = blocks[0] assert myBlock["name"] == blockName # add block to the block url = appUrl + "projects/" + testProjectId + "/blocks" payload = { "blockName": "The very second Second", "parentId": blockTestId, "groundThruthList": {"toto": "tata"}, "inputList": {"toto": "tata"}, "contextList": {"toto": "tata"}, } headers = {'content-type': "application/json"} resp = requests.post(url=url, json=payload, headers=headers) assert resp.status_code == 200 data = json.loads(resp.text) secBlockId = data["blockId"] assert len(secBlockId) > 0 # Get depth url = appUrl + "projects/" + testProjectId + "/blocks?depth=1" resp = requests.get(url=url, json={}, headers={}) print(resp.text) assert resp.status_code == 200 data = json.loads(resp.text) blocks = data["blocks"] assert len(blocks) == 1 block = data["blocks"][0] assert type(block["childrenInfoList"]) is list assert len(block["childrenInfoList"]) == 1 # Delete url = appUrl + "projects/" + testProjectId + "/blocks/" + secBlockId resp = requests.delete(url=url, json={}, headers={}) assert resp.status_code == 200 # Get depth url = appUrl + "projects/" + testProjectId + "/blocks?depth=1" resp = requests.get(url=url, json={}, headers={}) print(resp.text) assert resp.status_code == 200 data = json.loads(resp.text) blocks = data["blocks"] assert len(blocks) == 1 block = data["blocks"][0] assert type(block["childrenInfoList"]) is list assert len(block["childrenInfoList"]) == 0 # Delete Again url = appUrl + "projects/" + testProjectId + "/blocks/" + secBlockId resp = requests.delete(url=url, json={}, headers={}) assert resp.status_code == 404 # Delete First url = appUrl + "projects/" + testProjectId + "/blocks/" + blockTestId resp = requests.delete(url=url, json={}, headers={}) assert resp.status_code == 200 # Get url = appUrl + "projects/" + testProjectId + "/blocks" resp = requests.get(url=url, json={}, headers={}) print(resp.text) assert resp.status_code == 200 data = json.loads(resp.text) blocks = data["blocks"] assert len(blocks) == 0 def test_delete_block_badProj(): url = appUrl + "projects/IDONTEXIST/blocks/TODELETE" resp = requests.delete(url=url) assert resp.status_code == 404 def test_delete_block_badBlock(): url = appUrl + "projects/" + testProjectId + "/blocks/IDONTEXIST" resp = requests.delete(url=url) assert resp.status_code == 404 # remove project url = appUrl + "projects/" + testProjectId resp = requests.request("DELETE", url, headers={}, data={}) assert resp.status_code == 200 # ============== DATASETS TEST ================= def test_post_dataset_badProject(): url = appUrl + "projects/IDONTEXIST/datasets/" payload = { "datasetName": "Greate dataset", "blockIdList": [] } headers = {'content-type': "application/json"} resp = requests.post(url=url, json=payload, headers=headers) assert resp.status_code == 404 def test_post_dataset_badBlocks(): # Create project url = appUrl + "projects" payload = {"projectName": "My greate project with dataset", "blockLevelInfo": []} headers = {'content-type': "application/json"} resp = requests.post(url=url, headers=headers, json=payload) assert resp.status_code == 200 pId = json.loads(resp.text)["id"] # Add dataset url = appUrl + "projects/" + pId + "/datasets" payload = { "datasetName": "I am a dataset", "blockIdList": ["toto", "IDONTEXIST", "tutu"] } headers = {'content-type': "application/json"} resp = requests.post(url=url, json=payload, headers=headers) assert resp.status_code == 404 # remove project url = appUrl + "projects/" + pId resp = requests.request("DELETE", url, headers={}, data={}) assert resp.status_code == 200 def test_post_dataset(): # Create project url = appUrl + "projects" payload = {"projectName": "My greate project with dataset", "blockLevelInfo": []} headers = {'content-type': "application/json"} resp = requests.post(url=url, headers=headers, json=payload) assert resp.status_code == 200 pId = json.loads(resp.text)["id"] # Get url = appUrl + "projects/" + pId resp = requests.request("GET", url, headers={}, data={}) assert resp.status_code == 200 proj = json.loads(resp.text) print(proj) assert type(proj) is dict assert proj["datasets"] == [] # create dataset url = appUrl + "projects/" + pId + "/datasets" payload = { "datasetName": "I am a dataset", "blockIdList": [] # empty blocks ref } headers = {'content-type': "application/json"} resp = requests.post(url=url, json=payload, headers=headers) assert resp.status_code == 200 print(resp.text) datasetId = json.loads(resp.text)["id"] # get Dataset with project url = appUrl + "projects/" + pId resp = requests.request("GET", url, headers={}, data={}) assert resp.status_code == 200 proj = json.loads(resp.text) assert type(proj) is dict assert len(proj["datasets"]) == 1 assert proj["datasets"][0]["id"] == datasetId # delete dataset url = appUrl + "projects/" + pId + "/datasets/" + datasetId resp = requests.delete(url=url, json={}, headers={}) assert resp.status_code == 200 # Delete again resp = requests.delete(url=url, json={}, headers={}) assert resp.status_code == 404 # remove project url = appUrl + "projects/" + pId resp = requests.request("DELETE", url, headers={}, data={}) assert resp.status_code == 200 def test_post_dataset_withCreatedBlock(): # Create project url = appUrl + "projects" payload = {"projectName": "My greate project with dataset", "blockLevelInfo": []} headers = {'content-type': "application/json"} resp = requests.post(url=url, headers=headers, json=payload) assert resp.status_code == 200 pId = json.loads(resp.text)["id"] # ADD block url = appUrl + "projects/" + pId + "/blocks" payload = { "blockName": "My first block", "parentId": "", "groundThruthList": {"toto": "tata"}, "inputList": {"toto": "tata"}, "contextList": {"toto": "tata"}, } resp = requests.post(url=url, json=payload, headers={ 'content-type': "application/json"}) assert resp.status_code == 200 data = json.loads(resp.text) blockTestId = data["blockId"] assert len(blockTestId) > 0 # addadataset url = appUrl + "projects/" + pId + "/datasets" payload = { "datasetName": "dataset with blocks", "blockIdList": [blockTestId] } headers = {'content-type': "application/json"} resp = requests.post(url=url, json=payload, headers=headers) print(resp.text) assert resp.status_code == 200 # remove project url = appUrl + "projects/" + pId resp = requests.request("DELETE", url, headers={}, data={}) assert resp.status_code == 200

30.488789

73

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eb44b27e4ea1b9f6af02466617b1a465b7da5c97

130

py

Python

ontology-tools/CMCLABoxManagement/chemaboxwriters/chemaboxwriters/ontospecies/__init__.py

cambridge-cares/TheWorldAvatar

baf08ddc090414c6d01e48c74b408f2192461e9e

[ "MIT" ]

21

2021-03-08T01:58:25.000Z

2022-03-09T15:46:16.000Z

ontology-tools/CMCLABoxManagement/chemaboxwriters/chemaboxwriters/ontospecies/__init__.py

cambridge-cares/TheWorldAvatar

baf08ddc090414c6d01e48c74b408f2192461e9e

[ "MIT" ]

63

2021-05-04T15:05:30.000Z

2022-03-23T14:32:29.000Z

ontology-tools/CMCLABoxManagement/chemaboxwriters/chemaboxwriters/ontospecies/__init__.py

cambridge-cares/TheWorldAvatar

baf08ddc090414c6d01e48c74b408f2192461e9e

[ "MIT" ]

15

2021-03-08T07:52:03.000Z

2022-03-29T04:46:20.000Z

from chemaboxwriters.ontospecies.pipeline import assemble_os_pipeline from chemaboxwriters.ontospecies.writeabox import write_abox

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7

deb50a9135b23b65cc2cbbeacc9a5f6c64dbf6e6

15,182

py

Python

pyswitch/os/slxos/base/mct.py

mfeed/PySwitchLib

54e872bcbe77f2ae840d845dadb7c5b9c12482ed

[ "Apache-2.0" ]

6

2017-10-02T21:02:02.000Z

2018-07-04T13:56:55.000Z

pyswitch/os/slxos/base/mct.py

mfeed/PySwitchLib

54e872bcbe77f2ae840d845dadb7c5b9c12482ed

[ "Apache-2.0" ]

23

2017-10-03T18:49:11.000Z

2019-07-20T00:25:44.000Z

pyswitch/os/slxos/base/mct.py

mfeed/PySwitchLib

54e872bcbe77f2ae840d845dadb7c5b9c12482ed

[ "Apache-2.0" ]

4

2018-02-27T05:43:37.000Z

2019-06-30T13:30:25.000Z

# 2017.01.30 15:56:30 IST # Embedded file name: pyswitch/isis.py """ Copyright 2015 Brocade Communications Systems, Inc. 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. """ from pyswitch.utilities import Util class Mct(object): """ The MCT class holds all relevent methods and attributes for the MCT capabilities of the SLXOS device. Attributes: None """ @property def valid_int_types(self): return [] @property def valid_intp_types(self): return [] @property def os(self): return 'slxos' def __init__(self, callback): """ ISIS object init. Args: callback: Callback function that will be called for each action. Returns: ISIS Object Raises: None """ self._callback = callback self._cli = None def mct_client_create(self, **kwargs): """ Configure/get/delete mct client under the mct cluster Args: cluster_name (str): MCT Cluster Name. cluster_id (int): . MCT Cluster ID. client_name (str): MCT Client Name. client_id (int): . MCT Client ID. (Valid Values: 1-512) client_deploy (bool): Deploy. (True, False) get (bool): Get config instead of editing config. (True, False) delete (bool): Delete config. (True, False) callback (function): A function executed upon completion of the method. The only parameter passed to `callback` will be the ``ElementTree`` `config`. Returns: Return value of `callback`. Raises: KeyError: if `cluster_name`, `cluster_id` `client_name`, `client_id` are not specified. Examples: >>> import pyswitch.device >>> conn = ('10.24.39.211', '22') >>> auth = ('admin', 'password') >>> with pyswitch.device.Device(conn=conn, auth=auth) as dev: ... dev.mct.mct_client_create(client_deploy=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') ... output = dev.mct.mct_client_create(get=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') ... print output ... dev.mct.mct_client_create(delete=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') """ cluster_name = kwargs.pop('cluster_name') cluster_id = kwargs.pop('cluster_id') client_name = kwargs.pop('client_name', None) client_id = kwargs.pop('client_id', None) client_deploy = kwargs.pop('client_deploy', None) mct_args = {} get_config = kwargs.pop('get', False) delete = kwargs.pop('delete', False) callback = kwargs.pop('callback', self._callback) if cluster_id not in xrange(1, 65536): raise ValueError("cluster_id %s must be in range `1-65535`" % (cluster_id)) if client_id is not None and not xrange(1, 513): raise ValueError("client_id %s must be in range `1-512`" % (client_id)) mct_args = dict(cluster=(cluster_name, str(cluster_id))) if delete: method_name = 'cluster_client_delete' mct_args.update(client=(client_name, str(client_id))) config = (method_name, mct_args) return callback(config) if not get_config: method_name = 'cluster_client_create' mct_args.update(client=(client_name, str(client_id)), client_deploy=client_deploy) config = (method_name, mct_args) return callback(config) elif get_config: method_name = 'cluster_client_get' mct_args.update(client=(client_name, str(client_id))) config = (method_name, mct_args) output = callback(config, handler='get_config') if output.data != '<output></output>': result = True else: result = False return result def mct_client_interface_create(self, **kwargs): """ Configure/get/delete mct client interface under the mct client Args: cluster_name (str): MCT Cluster Name. cluster_id (int): . MCT Cluster ID. client_name (str): MCT Client Name. client_id (int): . MCT Client ID. (Valid Values: 1-512) intf_type (str): Type of interface. ['Ethernet', 'Port_channel'] intf_name (str): Intername name. client_deploy (bool): Deploy. (True, False) get (bool): Get config instead of editing config. (True, False) delete (bool): Delete config. (True, False) callback (function): A function executed upon completion of the method. The only parameter passed to `callback` will be the ``ElementTree`` `config`. Returns: Return value of `callback`. Raises: KeyError: if `intf_name`, `cluster_name`, `cluster_id` `client_name`, `client_id` are not specified. Examples: >>> import pyswitch.device >>> conn = ('10.24.39.211', '22') >>> auth = ('admin', 'password') >>> with pyswitch.device.Device(conn=conn, auth=auth) as dev: ... dev.mct.mct_client_interface_create(client_deploy=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1', ... intf_type='Ethernet', intf_name='0/35') ... output = dev.mct.mct_client_interface_create(get=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') ... print output ... dev.mct.mct_client_interface_create(delete=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') """ cluster_name = kwargs.pop('cluster_name') cluster_id = kwargs.pop('cluster_id') client_name = kwargs.pop('client_name', None) client_id = kwargs.pop('client_id', None) mct_args = {} get_config = kwargs.pop('get', False) delete = kwargs.pop('delete', False) callback = kwargs.pop('callback', self._callback) if cluster_id not in xrange(1, 65536): raise ValueError("cluster_id %s must be in range `1-65535`" % (cluster_id)) if client_id is not None and not xrange(1, 513): raise ValueError("client_id %s must be in range `1-512`" % (client_id)) mct_args = dict(cluster=(cluster_name, str(cluster_id))) if delete: method_name = 'cluster_client_client_interface_delete' mct_args.update(client=(client_name, str(client_id))) config = (method_name, mct_args) return callback(config) if not get_config: intf_name = kwargs.pop('intf_name') intf_type = kwargs.pop('intf_type', 'Ethernet') if intf_type == 'ethernet': intf_type = 'Ethernet' if intf_type == 'port_channel': intf_type = 'Port-channel' if intf_type not in ['Ethernet', 'Port-channel']: raise ValueError('intf_type %s must be either' '`Ethernet or Port-channel`' % (intf_type)) method_name = 'cluster_client_client_interface_update' mct_args.update(client=(client_name, str(client_id)), if_type=intf_type, if_value=intf_name) config = (method_name, mct_args) return callback(config) elif get_config: method_name = 'cluster_client_client_interface_get' mct_args.update(client=(client_name, str(client_id))) config = (method_name, mct_args) output = callback(config, handler='get_config') util = Util(output.data) if output.data != '<output></output>': result = util.find(util.root, './/if-value') else: result = None return result def mct_client_deploy(self, **kwargs): """ Configure/get/delete mct client deploy. Args: cluster_name (str): MCT Cluster Name. cluster_id (int): . MCT Cluster ID. client_name (str): MCT Client Name. client_id (int): . MCT Client ID. (Valid Values: 1-512) client_deploy (bool): Deploy. (True, False) get (bool): Get config instead of editing config. (True, False) delete (bool): Delete config. (True, False) callback (function): A function executed upon completion of the method. The only parameter passed to `callback` will be the ``ElementTree`` `config`. Returns: Return value of `callback`. Raises: KeyError: if `client_deploy`, `cluster_name`, `cluster_id` `client_name`, `client_id` are not specified. Examples: >>> import pyswitch.device >>> conn = ('10.24.39.211', '22') >>> auth = ('admin', 'password') >>> with pyswitchdevice.Device(conn=conn, auth=auth) as dev: ... dev.mct.mct_client_deploy(client_deploy=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') ... output = dev.mct.mct_client_deploy(get=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') ... print output ... dev.mct.mct_client_deploy(delete=True, ... cluster_id=1, cluster_name='pod-cluster') ... client_id=1, client_name='client1') """ cluster_name = kwargs.pop('cluster_name') cluster_id = kwargs.pop('cluster_id') client_name = kwargs.pop('client_name') client_id = kwargs.pop('client_id') client_deploy = kwargs.pop('client_deploy', None) mct_args = {} get_config = kwargs.pop('get', False) delete = kwargs.pop('delete', False) callback = kwargs.pop('callback', self._callback) if cluster_id not in xrange(1, 65536): raise ValueError("cluster_id %s must be in range `1-65535`" % (cluster_id)) if client_id not in xrange(1, 513): raise ValueError("client_id %s must be in range `1-512`" % (client_id)) mct_args = dict(cluster=(cluster_name, str(cluster_id))) if delete: method_name = 'cluster_client_deploy_delete' mct_args.update(client=(client_name, str(client_id))) config = (method_name, mct_args) return callback(config) if not get_config: method_name = 'cluster_client_deploy_update' mct_args.update(client=(client_name, str(client_id)), client_deploy=client_deploy) config = (method_name, mct_args) return callback(config) elif get_config: method_name = 'cluster_client_deploy_get' mct_args.update(client=(client_name, str(client_id))) config = (method_name, mct_args) output = callback(config, handler='get_config') if output.data != '<output></output>': result = True else: result = False return result def mct_cluster_create(self, **kwargs): """Configure Name of MCT cluster Args: cluster_name: Name of Overlay Gateway cluster_id: Name of Overlay Gateway get (bool): Get config instead of editing config. (True, False) delete (bool): True, delete the overlay gateway config. (True, False) callback (function): A function executed upon completion of the method. The only parameter passed to `callback` will be the ``ElementTree`` `config`. Returns: Return value of `callback`. Raises: KeyError: if `gw_name` is not passed. ValueError: if `gw_name` is invalid. Examples: >>> import pyswitch.device >>> conn = ('10.24.39.211', '22') >>> auth = ('admin', 'password') >>> with pyswitch.device.Device(conn=conn, auth=auth) as dev: ... output = dev.mct.mct_cluster_create( ... cluster_name='Leaf', cluster_id=10) ... output = dev.mct.mct_cluster_create(get=True) ... print output ... dev.mct.mct_cluster_create(delete=True) """ cluster_name = kwargs.pop('cluster_name', None) cluster_id = kwargs.pop('cluster_id', None) mct_args = {} get_config = kwargs.pop('get', False) delete = kwargs.pop('delete', False) callback = kwargs.pop('callback', self._callback) if cluster_id is not None and not xrange(1, 65536): raise ValueError("cluster_id %s must be in range `1-65535`" % (cluster_id)) if delete: mct_args = dict(cluster=(cluster_name, str(cluster_id))) method_name = 'cluster_delete' config = (method_name, mct_args) return callback(config) if not get_config: mct_args = dict(cluster=(cluster_name, str(cluster_id))) method_name = 'cluster_create' config = (method_name, mct_args) return callback(config) elif get_config: method_name = 'cluster_get' config = (method_name, mct_args) output = callback(config, handler='get_config') util = Util(output.data) result = util.find(util.root, './/cluster-name'),\ util.find(util.root, './/cluster-id') return result

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a0d4a82035398d7885a84c76eb8fe1a7f17d6126

10,865

py

Python

bitcoin/defaults.py

wizardofozzie/python-bitcoin

cffe691507b3414d62f1235dbb0e635f1c49ab0f

[ "MIT" ]

1

2020-12-30T15:38:47.000Z

bitcoin/defaults.py

wizardofozzie/python-bitcoin

cffe691507b3414d62f1235dbb0e635f1c49ab0f

[ "MIT" ]

null

bitcoin/defaults.py

wizardofozzie/python-bitcoin

cffe691507b3414d62f1235dbb0e635f1c49ab0f

[ "MIT" ]

1

2020-12-30T15:38:33.000Z

# -*- coding: utf-8 -*- # Copyright © 2012-2014 by its contributors. See AUTHORS for details. # Distributed under the MIT/X11 software license, see the accompanying # file LICENSE or http://www.opensource.org/licenses/mit-license.php. CLIENT_VERSION_MAJOR = 0 CLIENT_VERSION_MINOR = 8 CLIENT_VERSION_REVISION = 2 CLIENT_VERSION_BUILD = 2 CLIENT_VERSION = ( 1000000 * CLIENT_VERSION_MAJOR + 10000 * CLIENT_VERSION_MINOR + 100 * CLIENT_VERSION_REVISION + 1 * CLIENT_VERSION_BUILD) LOCKTIME_THRESHOLD = 500000000 from .core import ChainParameters from .tools import target_from_compact, Constant, LinearArithmetic, SteppedGeometric CHAIN_PARAMETERS = { 'bitcoin.org' : ChainParameters( magic = 'f9beb4d9'.decode('hex'), port = 8333, genesis = ( 'AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAO6Pt/Xp7ErJ6xyw+Z3aPYX/IG8OI' 'ilEyOp+4qkseXkopq19J//8AHR2sK3wBAQAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA' 'AAAAAP////9NBP//AB0BBEVUaGUgVGltZXMgMDMvSmFuLzIwMDkgQ2hhbmNlbGxvciBvbiBicmlu' 'ayBvZiBzZWNvbmQgYmFpbG91dCBmb3IgYmFua3P/////AQDyBSoBAAAAQ0EEZ4r9sP5VSCcZZ/Gm' 'cTC3EFzWqCjgOQmmeWLg6h9h3rZJ9rw/TO84xPNVBOUewRLeXDhN97oLjVeKTHAra/EdX6wAAAAA' ).decode('base64'), testnet = False, pubkey_hash_prefix = 0, script_hash_prefix = 5, secret_prefix = 128, max_value = 2100000000000000L, transient_reward = SteppedGeometric(50*100000000, 210000), transient_budget = lambda *args, **kwargs:(0, {}), perpetual_reward = Constant(0), perpetual_budget = lambda *args, **kwargs:(0, {}), fee_budget = lambda *args, **kwargs:(0, {}), maximum_target = target_from_compact(0x1d00ffff), next_target = lambda *args, **kwargs:0, alert_keys = [], checkpoints = { 0: 0x000000000019d6689c085ae165831e934ff763ae46a2a6c172b3f1b60a8ce26fL, 11111: 0x0000000069e244f73d78e8fd29ba2fd2ed618bd6fa2ee92559f542fdb26e7c1dL, 33333: 0x000000002dd5588a74784eaa7ab0507a18ad16a236e7b1ce69f00d7ddfb5d0a6L, 74000: 0x0000000000573993a3c9e41ce34471c079dcf5f52a0e824a81e7f953b8661a20L, 105000: 0x00000000000291ce28027faea320c8d2b054b2e0fe44a773f3eefb151d6bdc97L, 134444: 0x00000000000005b12ffd4cd315cd34ffd4a594f430ac814c91184a0d42d2b0feL, 168000: 0x000000000000099e61ea72015e79632f216fe6cb33d7899acb35b75c8303b763L, 193000: 0x000000000000059f452a5f7340de6682a977387c17010ff6e6c3bd83ca8b1317L, 210000: 0x000000000000048b95347e83192f69cf0366076336c639f9b7228e9ba171342eL, 216116: 0x00000000000001b4f4b433e81ee46494af945cf96014816a4e2370f11b23df4eL, 225430: 0x00000000000001c108384350f74090433e7fcf79a606b8e797f065b130575932L, }, features = {}), 'testnet3.bitcoin.org' : ChainParameters( magic = '0b110907'.decode('hex'), port = 18333, genesis = ( 'AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAO6Pt/Xp7ErJ6xyw+Z3aPYX/IG8OI' 'ilEyOp+4qkseXkra5UlN//8AHRqkrhgBAQAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA' 'AAAAAP////9NBP//AB0BBEVUaGUgVGltZXMgMDMvSmFuLzIwMDkgQ2hhbmNlbGxvciBvbiBicmlu' 'ayBvZiBzZWNvbmQgYmFpbG91dCBmb3IgYmFua3P/////AQDyBSoBAAAAQ0EEZ4r9sP5VSCcZZ/Gm' 'cTC3EFzWqCjgOQmmeWLg6h9h3rZJ9rw/TO84xPNVBOUewRLeXDhN97oLjVeKTHAra/EdX6wAAAAA' ).decode('base64'), testnet = True, pubkey_hash_prefix = 111, script_hash_prefix = 196, secret_prefix = 239, max_value = 2100000000000000L, transient_reward = SteppedGeometric(50*100000000, 210000), transient_budget = lambda *args, **kwargs:(0, {}), perpetual_reward = Constant(0), perpetual_budget = lambda *args, **kwargs:(0, {}), fee_budget = lambda *args, **kwargs:(0, {}), maximum_target = target_from_compact(0x1d00ffff), next_target = lambda *args, **kwargs:0, alert_keys = [], checkpoints = { 0: 0x000000000933ea01ad0ee984209779baaec3ced90fa3f408719526f8d77f4943L, 546: 0x000000002a936ca763904c3c35fce2f3556c559c0214345d31b1bcebf76acb70L, }, features = {}), 'freico.in' : ChainParameters( magic = '2cfe7e6d'.decode('hex'), port = 8639, genesis = ( 'AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAvcj0mpGkU1oV92tIbMn+DXC9qogS' '9YzoC6Qel6obO/XQzdRQ//8AHWpylRABAgAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA' 'AAAAAP////9NBP//AB0BBEVUZWxlZ3JhcGggMjcvSnVuLzIwMTIgQmFyY2xheXMgaGl0IHdpdGgg' 'wqMyOTBtIGZpbmUgb3ZlciBMaWJvciBmaXhpbmf/////CIk0KO0FAAAAQ0EEZ4r9sP5VSCcZZ/Gm' 'cTC3EFzWqCjgOQmmeWLg6h9h3rZJ9rw/TO84xPNVBOUewRLeXDhN97oLjVeKTHAra/EdX6wBAAAA' 'AAAAACMgUCnRgODF7XmNh3sa2pl3KYbBQiypMsQbLQQAAAAAAAB1AAEAAAAAAAAA/VMBAyAgIHVN' 'MQFNZXRhbHMgd2VyZSBhbiBpbXBsaWNpdGx5IGFidXNpdmUgYWdyZWVtZW50LgpNb2Rlcm4gInBh' 'cGVyIiBpcyBhIGZsYXdlZCB0b29sLCBpdHMgZW5naW5lZXJpbmcgaXMgYSBuZXN0IG9mIGxlZWNo' 'ZXMuClRoZSBvbGQgbW9uZXkgaXMgb2Jzb2xldGUuCkxldCB0aGUgaW5kaXZpZHVhbCBtb25ldGl6' 'ZSBpdHMgY3JlZGl0IHdpdGhvdXQgY2FydGVsIGludGVybWVkaWFyaWVzLgpHaXZlIHVzIGEgcmVu' 'dC1sZXNzIGNhc2ggc28gd2UgY2FuIGJlIGZyZWUgZm9yIHRoZSBmaXJzdCB0aW1lLgpMZXQgdGhp' 'cyBiZSB0aGUgYXdhaXRlZCBkYXduLnV2qRQO8PnRmmUwI1VBRqhmI4uIIryE34isAQAAAAAAAAD6' 'CCAgICAgICAgdUzUIkxldCB1cyBjYWxjdWxhdGUsIHdpdGhvdXQgZnVydGhlciBhZG8sIGluIG9y' 'ZGVyIHRvIHNlZSB3aG8gaXMgcmlnaHQuIiAtLUdvdHRmcmllZCBXaWxoZWxtIExlaWJuaXoKzr7C' 'tO+9peKIgO+9pWDvvInjgIDjgIDjgIDjgIAgIG4K77+j44CA44CA44CAICDvvLzjgIDjgIAgIO+8' 'iCBF77yJIGdvb2Qgam9iLCBtYWFrdSEK776M44CA44CA44CAICAv44O9IOODvV/vvI/vvI91dqkU' 'wmvl7ICapL9rMKqJgjz/fO3DZ5qIrAEAAAAAAAAAXwYgICAgICB1PEljaCB3w7xuc2NoZSBGcmVp' 'Y29pbiB2aWVsIEVyZm9sZyB6dW0gTnV0emVuIGRlciA5OSBQcm96ZW50IXV2qRQpOazWADcoGnCO' 'sR5OntpFLAKeyoisAQAAAAAAAACYDSAgICAgICAgICAgICB1TG0iVGhlIHZhbHVlIG9mIGEgbWFu' 'IHNob3VsZCBiZSBzZWVuIGluIHdoYXQgaGUgZ2l2ZXMgYW5kIG5vdCBpbiB3aGF0IGhlIGlzIGFi' 'bGUgdG8gcmVjZWl2ZS4iIC0tQWxiZXJ0IEVpbnN0ZWludXapFPnKXKq0vaTcKLVVaqeaLuwER/C/' 'iKwBAAAAAAAAAIAMICAgICAgICAgICAgdUxWIkFuIGFybXkgb2YgcHJpbmNpcGxlcyBjYW4gcGVu' 'ZXRyYXRlIHdoZXJlIGFuIGFybXkgb2Ygc29sZGllcnMgY2Fubm90LiIgLS1UaG9tYXMgUGFpbmV1' 'dqkUCPMgy7QaGuJbeU9hdflggGgZifOIrMxglIwLAAAAGXapFIXlQUTEAgpl+gqP26yLunXbwv0A' 'iKwAAAAAAAAAAA==' ).decode('base64'), testnet = False, pubkey_hash_prefix = 0, script_hash_prefix = 5, secret_prefix = 128, max_value = 9999999999999999L, transient_reward = LinearArithmetic(50*100000000, 210000), transient_budget = lambda *args, **kwargs:(0, {}), perpetual_reward = Constant(0), perpetual_budget = lambda *args, **kwargs:(0, {}), fee_budget = lambda *args, **kwargs:(0, {}), maximum_target = target_from_compact(0x1d00ffff), next_target = lambda *args, **kwargs:0, alert_keys = [], checkpoints = { 0: 0x000000000c29f26697c30e29039927ab4241b5fc2cc76db7e0dafa5e2612ad46L, 10080: 0x00000000003ff9c4b806639ec4376cc9acafcdded0e18e9dbcc2fc42e8e72331L, 15779: 0x000000000003eb31742b35f5efd8ffb5cdd19dcd8e82cdaad90e592c450363b6L, }, features = {}), 'testnet.freico.in' : ChainParameters( magic = '5ed67cf3'.decode('hex'), port = 18639, genesis = ( 'AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAvcj0mpGkU1oV92tIbMn+DXC9qogS' '9YzoC6Qel6obO/XQzdRQ//8AHfF1q7gBAgAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA' 'AAAAAP////9NBP//AB0BBEVUZWxlZ3JhcGggMjcvSnVuLzIwMTIgQmFyY2xheXMgaGl0IHdpdGgg' 'wqMyOTBtIGZpbmUgb3ZlciBMaWJvciBmaXhpbmf/////CIk0KO0FAAAAQ0EEZ4r9sP5VSCcZZ/Gm' 'cTC3EFzWqCjgOQmmeWLg6h9h3rZJ9rw/TO84xPNVBOUewRLeXDhN97oLjVeKTHAra/EdX6wBAAAA' 'AAAAACMgUCnRgODF7XmNh3sa2pl3KYbBQiypMsQbLQQAAAAAAAB1AAEAAAAAAAAA/VMBAyAgIHVN' 'MQFNZXRhbHMgd2VyZSBhbiBpbXBsaWNpdGx5IGFidXNpdmUgYWdyZWVtZW50LgpNb2Rlcm4gInBh' 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'IHNob3VsZCBiZSBzZWVuIGluIHdoYXQgaGUgZ2l2ZXMgYW5kIG5vdCBpbiB3aGF0IGhlIGlzIGFi' 'bGUgdG8gcmVjZWl2ZS4iIC0tQWxiZXJ0IEVpbnN0ZWludXapFPnKXKq0vaTcKLVVaqeaLuwER/C/' 'iKwBAAAAAAAAAIAMICAgICAgICAgICAgdUxWIkFuIGFybXkgb2YgcHJpbmNpcGxlcyBjYW4gcGVu' 'ZXRyYXRlIHdoZXJlIGFuIGFybXkgb2Ygc29sZGllcnMgY2Fubm90LiIgLS1UaG9tYXMgUGFpbmV1' 'dqkUCPMgy7QaGuJbeU9hdflggGgZifOIrMxglIwLAAAAGXapFIXlQUTEAgpl+gqP26yLunXbwv0A' 'iKwAAAAAAAAAAA==' ).decode('base64'), testnet = False, pubkey_hash_prefix = 111, script_hash_prefix = 196, secret_prefix = 239, max_value = 9999999999999999L, transient_reward = LinearArithmetic(50*100000000, 210000), transient_budget = lambda *args, **kwargs:(0, {}), perpetual_reward = Constant(0), perpetual_budget = lambda *args, **kwargs:(0, {}), fee_budget = lambda *args, **kwargs:(0, {}), maximum_target = target_from_compact(0x1d00ffff), next_target = lambda *args, **kwargs:0, alert_keys = [], checkpoints = { 0: 0x000000000c29f26697c30e29039927ab4241b5fc2cc76db7e0dafa5e2612ad46L, 10080: 0x00000000003ff9c4b806639ec4376cc9acafcdded0e18e9dbcc2fc42e8e72331L, 15779: 0x000000000003eb31742b35f5efd8ffb5cdd19dcd8e82cdaad90e592c450363b6L, }, features = {}), }

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0.733456

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1

null

1

0

1

0

10

a0df29c4d9dbb2f34a7de75033cb7b0d52fc14f1

5,039

py

Python

tests/test_diff.py

suganthsundar/melano

8e9dd57d3ce9945b18e64da6b0df30811018fbf0

[ "MIT" ]

null

tests/test_diff.py

suganthsundar/melano

8e9dd57d3ce9945b18e64da6b0df30811018fbf0

[ "MIT" ]

null

tests/test_diff.py

suganthsundar/melano

8e9dd57d3ce9945b18e64da6b0df30811018fbf0

[ "MIT" ]

null

import nose from melano.diff import (json_diff, list_diff) def test_diff_json_simple_equal(): errors = json_diff(x=dict(x=1, y=2, z=3), y=dict(x=1, y=2, z=3)) nose.tools.assert_equal(len(errors), 0) def test_diff_json_simple_not_equal(): errors = json_diff(x=dict(a=1, b=1, c=3), y=dict(a=1, b=2, c=3)) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISMATCH') nose.tools.assert_equal(errors[0]['field'], 'b') nose.tools.assert_equal(errors[0]['x'], 1) nose.tools.assert_equal(errors[0]['y'], 2) nose.tools.assert_equal(errors[0]['message'], 'b: 1 (int) != 2 (int)') def test_diff_json_simple_missing_x(): errors = json_diff(x=dict(a=1, b=2), y=dict(a=1, b=2, c=3)) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISSING') nose.tools.assert_equal(errors[0]['field'], 'c') nose.tools.assert_equal(errors[0]['y'], 3) nose.tools.assert_equal(errors[0]['message'], 'c: not found') def test_diff_json_simple_missing_y(): errors = json_diff(x=dict(a=1, b=2, c=3), y=dict(a=1, b=2)) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISSING') nose.tools.assert_equal(errors[0]['field'], 'c') nose.tools.assert_equal(errors[0]['x'], 3) nose.tools.assert_equal(errors[0]['message'], 'c: not found') def test_diff_list_simple_missing_y(): errors = list_diff(x=[1, 2, 3], y=[1, 2]) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISSING') nose.tools.assert_equal(errors[0]['x'], 3) nose.tools.assert_equal(errors[0]['message'], '[2]: not found') def test_diff_list_simple_mismatch(): errors = list_diff(x=[1, 3], y=[1, 2]) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISMATCH') nose.tools.assert_equal(errors[0]['x'], 3) nose.tools.assert_equal(errors[0]['y'], 2) nose.tools.assert_equal(errors[0]['message'], '[1]: 3 (int) != 2 (int)') def test_diff_json_nested_missing_field(): x = dict(name='john', age=22, address=dict(address1='20 XYZ', state='CA'), phone_numbers=[123456, 345678]) y = dict(name='john', age=22, address=dict(address1='20 XYZ'), phone_numbers=[123456, 345678]) errors = json_diff(x, y) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISSING') nose.tools.assert_equal(errors[0]['field'], 'address.state') nose.tools.assert_equal(errors[0]['x'], 'CA') nose.tools.assert_equal(errors[0]['message'], 'address.state: not found') def test_diff_json_nested_mismatch_value(): x = dict(name='john', age=22, address=dict(address1='20 XYZ', state='CA'), phone_numbers=[123456, 345678]) y = dict(name='john', age=22, address=dict(address1='20 XYZ', state='PA'), phone_numbers=[123456, 345678]) errors = json_diff(x, y) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISMATCH') nose.tools.assert_equal(errors[0]['field'], 'address.state') nose.tools.assert_equal(errors[0]['x'], 'CA') nose.tools.assert_equal(errors[0]['y'], 'PA') nose.tools.assert_equal(errors[0]['message'], 'address.state: CA (str) != PA (str)') def test_diff_json_nested_dict_list_mismatch(): x = dict(name='john', age=22, addresses=[dict(address1='20 XYZ', state='CA')]) y = dict(name='john', age=22, addresses=[dict(address1='20 XYZ', state='PA')]) errors = json_diff(x, y) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISMATCH') nose.tools.assert_equal(errors[0]['field'], 'addresses[0].state') nose.tools.assert_equal(errors[0]['x'], 'CA') nose.tools.assert_equal(errors[0]['y'], 'PA') nose.tools.assert_equal(errors[0]['message'], 'addresses[0].state: CA (str) != PA (str)') def test_diff_json_nested_dict_list_missing_x(): x = dict(name='john', age=22, addresses=[dict(address1='20 XYZ', state='CA')]) y = dict(name='john', age=22, addresses=[]) errors = json_diff(x, y) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISSING') nose.tools.assert_equal(errors[0]['field'], 'addresses[0]') nose.tools.assert_equal(errors[0]['x'], dict(address1='20 XYZ', state='CA')) nose.tools.assert_equal(errors[0]['message'], 'addresses[0]: not found') def test_diff_json_nested_dict_list_missing_y(): x = dict(name='john', age=22, addresses=[dict(address1='20 XYZ', state='CA')]) y = dict(name='john', age=22, addresses=[dict(address1='20 XYZ', state='CA'), dict(address1='10 XYZ', state='PA')]) errors = json_diff(x, y) nose.tools.assert_equal(len(errors), 1) nose.tools.assert_equal(errors[0]['type'], 'MISSING') nose.tools.assert_equal(errors[0]['field'], 'addresses[1]') nose.tools.assert_equal(errors[0]['y'], dict(address1='10 XYZ', state='PA')) nose.tools.assert_equal(errors[0]['message'], 'addresses[1]: not found')

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5,039

110

120

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0.126437

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0

null

0

1

0

null

0

1

0

9

9d06e989d5295450ccfd2124029464298f434eb9

4,644

py

Python

test/test_kill.py

trentm/python-process

94d2c62244d3c634a3a56a1dde0c09cf2d18fbb2

[ "MIT" ]

1

2019-08-06T09:30:40.000Z

test/test_kill.py

trentm/python-process

94d2c62244d3c634a3a56a1dde0c09cf2d18fbb2

[ "MIT" ]

null

test/test_kill.py

trentm/python-process

94d2c62244d3c634a3a56a1dde0c09cf2d18fbb2

[ "MIT" ]

1

2021-04-23T10:07:35.000Z

"""Test simple Process.kill() usage.""" import os import sys import time import pprint import unittest import threading if not sys.platform.startswith("win"): import signal import process class KillTestCase(unittest.TestCase): def _KillAndReturn(self, child): try: child.kill() except OSError, ex: self._failedToKill = 1 else: self._failedToKill = 0 def test_ProcessProxy_kill(self): p = process.ProcessProxy(['hang']) time.sleep(2) p.kill() retval = p.wait() if not sys.platform.startswith("win"): # Can check on Unix if the retval indicates that the process # was signaled. Otherwise the test is just to ensure that we # got here (i.e. didn't hang). self.failUnless(os.WIFSIGNALED(retval)) def test_ProcessProxy_kill_twice(self): # Killing an already terminated process should not raise an # exception. p = process.ProcessProxy(['hang']) time.sleep(2) p.kill() retval = p.wait() if not sys.platform.startswith("win"): # Can check on Unix if the retval indicates that the process # was signaled. Otherwise the test is just to ensure that we # got here (i.e. didn't hang). self.failUnless(os.WIFSIGNALED(retval)) p.kill() if not sys.platform.startswith("win"): def test_ProcessProxy_kill_SIGKILL(self): p = process.ProcessProxy(['hang']) time.sleep(1) p.kill(sig=signal.SIGKILL) retval = p.wait() self.failUnless(os.WIFSIGNALED(retval)) self.failUnless(os.WTERMSIG(retval) == signal.SIGKILL) # XXX Could add tests for other signals but would have to launch an # app that would respond to those signals in a measurable way and # then terminate. def test_ProcessProxy_kill_from_parent_subthread(self): p = process.ProcessProxy(['hang']) t = threading.Thread(target=self._KillAndReturn, kwargs={'child':p}) t.start() p.wait() t.join() if self._failedToKill: self.fail("Could not kill the child process from a thread "\ "spawned by the parent *after* the child was spawn.\n") def test_ProcessOpen_kill(self): p = process.ProcessOpen(['hang']) time.sleep(2) p.kill() retval = p.wait() if not sys.platform.startswith("win"): # Can check on Unix if the retval indicates that the process # was signaled. Otherwise the test is just to ensure that we # got here (i.e. didn't hang). self.failUnless(os.WIFSIGNALED(retval)) def test_ProcessOpen_kill_twice(self): # Killing an already terminated process should not raise an # exception. p = process.ProcessOpen(['hang']) time.sleep(2) p.kill() retval = p.wait() if not sys.platform.startswith("win"): # Can check on Unix if the retval indicates that the process # was signaled. Otherwise the test is just to ensure that we # got here (i.e. didn't hang). self.failUnless(os.WIFSIGNALED(retval)) p.kill() if not sys.platform.startswith("win"): def test_ProcessOpen_kill_SIGKILL(self): p = process.ProcessOpen(['hang']) time.sleep(1) p.kill(sig=signal.SIGKILL) retval = p.wait() self.failUnless(os.WIFSIGNALED(retval)) self.failUnless(os.WTERMSIG(retval) == signal.SIGKILL) # XXX Could add tests for other signals but would have to launch an # app that would respond to those signals in a measurable way and # then terminate. def test_ProcessOpen_kill_from_parent_subthread(self): p = process.ProcessOpen(['hang']) t = threading.Thread(target=self._KillAndReturn, kwargs={'child':p}) t.start() p.wait() t.join() if self._failedToKill: self.fail("Could not kill the child process from a thread "\ "spawned by the parent *after* the child was spawn.\n") def suite(): """Return a unittest.TestSuite to be used by test.py.""" return unittest.makeSuite(KillTestCase) if __name__ == "__main__": import logging logging.basicConfig() testsupport.setup() sys.argv.insert(1, "-v") # always want verbose output unittest.main()

34.147059

77

0.595607

572

4,644

4.763986

0.227273

0.02055

0.046972

0.041101

0.801835

0.785321

0.774679

0.728807

0

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0.306632

4,644

135

78

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0

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null

0

0.098901

null

0.010989

0

null

0

1

0

null

0

1

0

7

9d07a8d154ed7de323371ba616ca9f44a5e988d6

126

py

Python

discord/template.py

kuzaku-developers/disnake

61cc1ad4c2bafd39726a1447c85f7e469e41af10

[ "MIT" ]

null

discord/template.py

kuzaku-developers/disnake

61cc1ad4c2bafd39726a1447c85f7e469e41af10

[ "MIT" ]

null

discord/template.py

kuzaku-developers/disnake

61cc1ad4c2bafd39726a1447c85f7e469e41af10

[ "MIT" ]

null

from disnake.template import * from disnake.template import __dict__ as __original_dict__ locals().update(__original_dict__)

25.2

58

0.84127

16

126

5.75

0.5625

0.23913

0.413043

0.543478

0

0.095238

126

4

59

31.5

0.807018

0

1

0

true

0

0.666667

0

0.666667

0

1

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null

1

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null

0

1

0

1

0

1

0

8

9d0d559bb682cd82800e8f64e4632224a758e22f

6,280

py

Python

tests/test_orset.py

anshulahuja98/python3-crdt

b2e5d67580c562ae08d56127f41f7562e3ebe8e9

[ "MIT" ]

48

2019-02-16T08:01:52.000Z

2022-03-19T00:45:13.000Z

tests/test_orset.py

geetesh-gupta/python3-crdt

02dfc28895da031169fbc8bd9ae1434dbfacd8b9

[ "MIT" ]

5

2020-10-01T09:52:38.000Z

2021-05-18T09:32:35.000Z

tests/test_orset.py

anshulahuja98/python3-crdt

b2e5d67580c562ae08d56127f41f7562e3ebe8e9

[ "MIT" ]

3

2019-02-16T08:01:54.000Z

2022-01-29T15:58:14.000Z

import unittest import uuid import py3crdt from py3crdt.orset import ORSet class TestORSet(unittest.TestCase): def setUp(self): # Create a ORSet self.orset1 = ORSet(uuid.uuid4()) # Create another ORSet self.orset2 = ORSet(uuid.uuid4()) # Add elements to orset1 self.orset1.add('a', uuid.uuid4()) self.orset1.add('b', uuid.uuid4()) # Add elements to orset1 self.orset2.add('b', uuid.uuid4()) self.orset2.add('c', uuid.uuid4()) self.orset2.add('d', uuid.uuid4()) def test_elements_add_correctly_orset(self): self.assertEqual([_['elem'] for _ in self.orset1.A], ['a', 'b']) self.assertEqual([_['elem'] for _ in self.orset1.R], []) self.assertEqual([_['elem'] for _ in self.orset2.A], ['b', 'c', 'd']) self.assertEqual([_['elem'] for _ in self.orset2.R], []) def test_querying_orset_without_removal_and_merging(self): # Check orset1 querying self.assertTrue(self.orset1.query('a')) self.assertTrue(self.orset1.query('b')) self.assertFalse(self.orset1.query('c')) self.assertFalse(self.orset1.query('d')) # Check orset2 querying self.assertFalse(self.orset2.query('a')) self.assertTrue(self.orset2.query('b')) self.assertTrue(self.orset2.query('c')) self.assertTrue(self.orset2.query('d')) def test_merging_orset_without_removal(self): # Check orset1 merging self.orset1.merge(self.orset2) self.assertEqual([_['elem'] for _ in self.orset1.A], ['a', 'b', 'c', 'd']) for _ in self.orset1.A: if _['elem'] == 'b': self.assertEqual(len(_['tags']), 2) break self.assertEqual([_['elem'] for _ in self.orset1.R], []) # Check orset2 merging self.orset2.merge(self.orset1) self.assertEqual([_['elem'] for _ in self.orset2.A], ['a', 'b', 'c', 'd']) for _ in self.orset2.A: if _['elem'] == 'b': self.assertEqual(len(_['tags']), 2) break self.assertEqual([_['elem'] for _ in self.orset2.R], []) # Check if they are both equal self.assertEqual([_['elem'] for _ in self.orset1.A], [_['elem'] for _ in self.orset2.A]) self.assertEqual([_['elem'] for _ in self.orset1.R], [_['elem'] for _ in self.orset2.R]) def test_querying_orset_with_merging_without_removal(self): # Check orset2 merging self.orset2.merge(self.orset1) self.assertTrue(self.orset2.query('a')) self.assertTrue(self.orset2.query('b')) self.assertTrue(self.orset2.query('c')) self.assertTrue(self.orset2.query('d')) # Check orset1 merging self.orset1.merge(self.orset2) self.assertTrue(self.orset1.query('a')) self.assertTrue(self.orset1.query('b')) self.assertTrue(self.orset1.query('c')) self.assertTrue(self.orset1.query('d')) def test_elements_remove_correctly_orset(self): # Remove elements from orset1 self.orset1.remove('b') self.assertEqual([_['elem'] for _ in self.orset1.A], ['a', 'b']) self.assertEqual([_['elem'] for _ in self.orset1.R], ['b']) # Remove elements from orset2 self.orset2.remove('b') self.orset2.remove('c') self.assertEqual([_['elem'] for _ in self.orset2.A], ['b', 'c', 'd']) self.assertEqual([_['elem'] for _ in self.orset2.R], ['b', 'c']) def test_querying_orset_without_merging_with_removal(self): # Remove elements from orset1 self.orset1.remove('b') # Check orset1 querying self.assertTrue(self.orset1.query('a')) self.assertFalse(self.orset1.query('b')) self.assertFalse(self.orset1.query('c')) self.assertFalse(self.orset1.query('d')) # Remove elements from orset2 self.orset2.remove('b') self.orset2.remove('c') # Check orset2 querying self.assertFalse(self.orset2.query('a')) self.assertFalse(self.orset2.query('b')) self.assertFalse(self.orset2.query('c')) self.assertTrue(self.orset2.query('d')) def test_merging_orset_with_removal(self): # Remove elements from orset1 self.orset1.remove('b') # Remove elements from orset2 self.orset2.remove('b') self.orset2.remove('c') # Check orset1 merging self.orset1.merge(self.orset2) self.assertEqual([_['elem'] for _ in self.orset1.A], ['a', 'b', 'c', 'd']) self.assertEqual([_['elem'] for _ in self.orset1.R], ['b', 'c']) for _ in self.orset1.R: if _['elem'] == 'b': self.assertEqual(len(_['tags']), 2) break # Check orset2 merging self.orset2.merge(self.orset1) self.assertEqual([_['elem'] for _ in self.orset2.A], ['a', 'b', 'c', 'd']) self.assertEqual([_['elem'] for _ in self.orset2.R], ['b', 'c']) for _ in self.orset2.R: if _['elem'] == 'b': self.assertEqual(len(_['tags']), 2) break # Check if they are both equal self.assertEqual([_['elem'] for _ in self.orset1.A], [_['elem'] for _ in self.orset2.A]) self.assertEqual([_['elem'] for _ in self.orset1.R], [_['elem'] for _ in self.orset2.R]) def test_querying_orset_with_merging_with_removal(self): # Remove elements from orset1 self.orset1.remove('b') # Remove elements from orset2 self.orset2.remove('b') self.orset2.remove('c') # Merge orset2 to orset1 self.orset1.merge(self.orset2) # Merge orset1 to orset2 self.orset2.merge(self.orset1) # Check orset1 querying self.assertTrue(self.orset1.query('a')) self.assertFalse(self.orset1.query('b')) self.assertFalse(self.orset1.query('c')) self.assertTrue(self.orset1.query('d')) # Check orset2 querying self.assertTrue(self.orset2.query('a')) self.assertFalse(self.orset2.query('b')) self.assertFalse(self.orset2.query('c')) self.assertTrue(self.orset2.query('d')) if __name__ == '__main__': unittest.main()

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8

9d5a37b8d78917875c09c5b3a9f6821993c04f5a

23,507

py

Python

source/tests.py

kroopson/rbfblender

cbaa39546fd22274fa0d5fe956838dbfe4d9d715

[ "MIT" ]

3

2019-01-10T20:33:21.000Z

2019-05-03T12:47:07.000Z

source/tests.py

kroopson/rbfblender

cbaa39546fd22274fa0d5fe956838dbfe4d9d715

[ "MIT" ]

null

source/tests.py

kroopson/rbfblender

cbaa39546fd22274fa0d5fe956838dbfe4d9d715

[ "MIT" ]

null

import unittest import maya.OpenMaya as om import maya.standalone maya.standalone.initialize() import maya.cmds as cmds import os import sys sys.path.append(os.path.dirname(__file__)) cmds.loadPlugin("rbfblender") class TestRbfBlender(unittest.TestCase): def setUp(self): cmds.file(new=True, f=True) def create_rbfblender(self): try: node = cmds.createNode("rbfblender", n="blender") success = True except: success = False return success def test_node_creation(self): success = self.create_rbfblender() try: rbf_nodes = cmds.ls(type="rbfblender") if rbf_nodes: success = True else: success = False except: success = False self.assert_(success, "Failed to create the node.") def test_input_attribute(self): success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") rbf_nodes = cmds.ls(type="rbfblender") rbf_node = rbf_nodes[0] self.assert_(cmds.attributeQuery("input", n=rbf_node, ex=True), "Failed to get the input attribute") self.assert_(cmds.attributeQuery("output", n=rbf_node, ex=True), "Failed to get the output attribute") self.assert_(cmds.attributeQuery("poses", n=rbf_node, ex=True), "Failed to get the poses attribute") try: cmds.setAttr("blender.poses[0].poseInputs[0]", 1.0) cmds.setAttr("blender.poses[0].poseName", "test", type="string") cmds.setAttr("blender.poses[0].poseValues[0]", 1.0) success = True except: success = False self.assert_(success, "Failed to set the poses attribute") def test_output_attribute(self): print "###################################################" print "TEST OUTPUT ATTRIBUTE" success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") try: cmds.setAttr("blender.input[0]", .4) cmds.setAttr("blender.poses[0].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[0].poseName", "test", type="string") cmds.setAttr("blender.poses[0].poseValues[0]", 0.5) cmds.setAttr("blender.poses[1].poseInputs[0]", 1.0) cmds.setAttr("blender.poses[1].poseName", "test", type="string") cmds.setAttr("blender.poses[1].poseValues[0]", 1.0) success = True except Exception, e: success = False print e self.assert_(success, "Failed to set the poses attribute") cmds.getAttr("blender.output[0]") cmds.setAttr("blender.input[0]", .0) cmds.getAttr("blender.output[0]") cmds.setAttr("blender.input[0]", 1) cmds.getAttr("blender.output[0]") cmds.setAttr("blender.input[0]", .5) cmds.getAttr("blender.output[0]") def test_passive_output(self): print "###################################################" print "TEST PASSIVE_OUTPUT ATTRIBUTE" success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") try: cmds.setAttr("blender.input[0]", .4) cmds.setAttr("blender.poses[0].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[0].poseName", "test", type="string") cmds.setAttr("blender.poses[0].poseValues[0]", 0.5) cmds.setAttr("blender.poses[1].poseInputs[0]", 1.0) cmds.setAttr("blender.poses[1].poseName", "test", type="string") cmds.setAttr("blender.poses[1].poseValues[0]", 1.0) success = True except Exception, e: success = False print e self.assert_(success, "Failed to set the poses attribute") target_locator = cmds.spaceLocator()[0] cmds.connectAttr("blender.output[0]", target_locator + ".translateX") cmds.setAttr("blender.input[0]", 1.0) self.assert_(abs(cmds.getAttr(target_locator + ".translateX") - 1.0) < .0004, "Bad value of connected attribute " + str(cmds.getAttr(target_locator + ".translateX"))) cmds.setAttr(target_locator + ".translateX", 2.0) self.assert_(cmds.getAttr(target_locator + ".translateX") == 2.0, "Bad value of passive attribute " + str(cmds.getAttr(target_locator + ".translateX"))) def test_single_pose(self): print "###################################################" print "TEST SINGLE POSE" success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") try: cmds.setAttr("blender.input[0]", .4) cmds.setAttr("blender.poses[0].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[0].poseName", "test", type="string") cmds.setAttr("blender.poses[0].poseValues[0]", 0.5) success = True except Exception, e: success = False print e self.assert_(success, "Failed to set the poses attribute") cmds.getAttr("blender.output[0]") def test_duplicated_pose(self): print "###################################################" print "TEST DUPLICATED POSE" success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") try: cmds.setAttr("blender.input[0]", .4) cmds.setAttr("blender.poses[0].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[0].poseName", "test", type="string") cmds.setAttr("blender.poses[0].poseValues[0]", 0.5) cmds.setAttr("blender.poses[1].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[1].poseName", "test", type="string") cmds.setAttr("blender.poses[1].poseValues[0]", 0.5) success = True except Exception, e: success = False print e self.assert_(success, "Failed to set the poses attribute") cmds.getAttr("blender.output[0]") def test_non_square_attribute(self): print "###################################################" print "TEST NON SQUARE ATTRIBUTE" success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") try: cmds.setAttr("blender.input[0]", 1.0) cmds.setAttr("blender.input[1]", 0.0) cmds.setAttr("blender.poses[0].poseInputs[0]", 1.0) cmds.setAttr("blender.poses[0].poseInputs[1]", 0.0) cmds.setAttr("blender.poses[0].poseInputs[2]", 0.0) cmds.setAttr("blender.poses[0].poseName", "test", type="string") cmds.setAttr("blender.poses[0].poseValues[0]", 1.0) cmds.setAttr("blender.poses[0].poseValues[1]", 0.5) cmds.setAttr("blender.poses[1].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[1].poseInputs[1]", 1.0) cmds.setAttr("blender.poses[1].poseInputs[2]", 0.0) cmds.setAttr("blender.poses[1].poseName", "test", type="string") cmds.setAttr("blender.poses[1].poseValues[0]", 0.0) cmds.setAttr("blender.poses[1].poseValues[1]", 0.6) cmds.setAttr("blender.poses[2].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[2].poseInputs[1]", 0.0) cmds.setAttr("blender.poses[2].poseInputs[2]", 1.0) cmds.setAttr("blender.poses[2].poseName", "test", type="string") cmds.setAttr("blender.poses[2].poseValues[0]", 0.0) cmds.setAttr("blender.poses[2].poseValues[1]", 0.7) success = True except Exception, e: success = False print e self.assert_(success, "Failed to set the poses attribute") cmds.getAttr("blender.output[0]") cmds.getAttr("blender.output[1]") def test_multi_output_attribute(self): print "###################################################" print "TEST MULTI OUTPUT ATTRIBUTE" success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") cmds.setAttr("blender.output[0]", 0.0) cmds.setAttr("blender.output[1]", 0.0) cmds.setAttr("blender.output[2]", 0.0) try: cmds.setAttr("blender.input[0]", 1.0) cmds.setAttr("blender.input[1]", 0.0) cmds.setAttr("blender.input[2]", 0.0) cmds.setAttr("blender.poses[0].poseInputs[0]", 1.0) cmds.setAttr("blender.poses[0].poseInputs[1]", 0.0) cmds.setAttr("blender.poses[0].poseInputs[2]", 0.0) cmds.setAttr("blender.poses[0].poseName", "test", type="string") cmds.setAttr("blender.poses[0].poseValues[0]", 1.0) cmds.setAttr("blender.poses[0].poseValues[1]", 0.5) cmds.setAttr("blender.poses[0].poseValues[2]", 0.0) cmds.setAttr("blender.poses[1].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[1].poseInputs[1]", 1.0) cmds.setAttr("blender.poses[1].poseInputs[2]", 0.0) cmds.setAttr("blender.poses[1].poseName", "test", type="string") cmds.setAttr("blender.poses[1].poseValues[0]", 0.0) cmds.setAttr("blender.poses[1].poseValues[1]", 0.6) cmds.setAttr("blender.poses[1].poseValues[2]", 0.0) cmds.setAttr("blender.poses[2].poseInputs[0]", 0.0) cmds.setAttr("blender.poses[2].poseInputs[1]", 0.0) cmds.setAttr("blender.poses[2].poseInputs[2]", 1.0) cmds.setAttr("blender.poses[2].poseName", "test", type="string") cmds.setAttr("blender.poses[2].poseValues[0]", 0.0) cmds.setAttr("blender.poses[2].poseValues[1]", 0.7) cmds.setAttr("blender.poses[2].poseValues[2]", 1.0) success = True except Exception, e: success = False print e self.assert_(success, "Failed to set the poses attribute") cmds.getAttr("blender.output[0]") cmds.getAttr("blender.output[1]") cmds.getAttr("blender.output[2]") def test_cubes(self): print "###################################################" print "TEST CUBES" cube_test = cmds.polyCube()[0] cube_a = cmds.polyCube()[0] cube_b = cmds.polyCube()[0] cube_c = cmds.polyCube()[0] cmds.setAttr(cube_a + ".translate", -1, 0, 0) cmds.setAttr(cube_b + ".translate", 0, 0, 1) cmds.setAttr(cube_c + ".translate", 1, 0, 0) cmds.setAttr(cube_a + ".scale", 2, 1, 1) cmds.setAttr(cube_b + ".scale", 1, 2, 1) cmds.setAttr(cube_c + ".scale", 1, 1, 2) success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") try: cmds.connectAttr(cube_test + ".translateX", "blender.input[0]") cmds.connectAttr(cube_test + ".translateZ", "blender.input[1]") cmds.connectAttr("blender.output[0]", cube_test + ".scaleX") cmds.connectAttr("blender.output[1]", cube_test + ".scaleY") cmds.connectAttr("blender.output[2]", cube_test + ".scaleZ") print "!! Creating pose 0" cmds.connectAttr(cube_a + ".translateX", "blender.poses[0].poseInputs[0]") cmds.connectAttr(cube_a + ".translateZ", "blender.poses[0].poseInputs[1]") cmds.connectAttr(cube_a + ".scaleX", "blender.poses[0].poseValues[0]") cmds.connectAttr(cube_a + ".scaleY", "blender.poses[0].poseValues[1]") cmds.connectAttr(cube_a + ".scaleZ", "blender.poses[0].poseValues[2]") print "!! Creating pose 1" cmds.connectAttr(cube_b + ".translateX", "blender.poses[1].poseInputs[0]") cmds.connectAttr(cube_b + ".translateZ", "blender.poses[1].poseInputs[1]") cmds.connectAttr(cube_b + ".scaleX", "blender.poses[1].poseValues[0]") cmds.connectAttr(cube_b + ".scaleY", "blender.poses[1].poseValues[1]") cmds.connectAttr(cube_b + ".scaleZ", "blender.poses[1].poseValues[2]") print "!! Creating pose 2" cmds.connectAttr(cube_c + ".translateX", "blender.poses[2].poseInputs[0]") cmds.connectAttr(cube_c + ".translateZ", "blender.poses[2].poseInputs[1]") cmds.connectAttr(cube_c + ".scaleX", "blender.poses[2].poseValues[0]") cmds.connectAttr(cube_c + ".scaleY", "blender.poses[2].poseValues[1]") cmds.connectAttr(cube_c + ".scaleZ", "blender.poses[2].poseValues[2]") success = True except Exception, e: success = False print e cmds.setAttr(cube_test + ".translate", -1, 0, 0) self.assert_( cmds.getAttr(cube_test + ".scale") == [(2, 1, 1)], "Bad result" + str(cmds.getAttr(cube_test + ".scale") )) cmds.setAttr(cube_test + ".translate", 0, 0, 1) self.assert_( cmds.getAttr(cube_test + ".scale") == [(1, 2, 1)], "Bad result") cmds.setAttr(cube_test + ".translate", 1, 0, 0) self.assert_( cmds.getAttr(cube_test + ".scale") == [(1, 1, 2)], "Bad result" + str(cmds.getAttr(cube_test + ".scale"))) def test_cubes_multiquadratic(self): print "###################################################" print "TEST CUBES MULTIQUADRATIC" cube_test = cmds.polyCube()[0] cube_a = cmds.polyCube()[0] cube_b = cmds.polyCube()[0] cube_c = cmds.polyCube()[0] cmds.setAttr(cube_a + ".translate", -1, 0, 0) cmds.setAttr(cube_b + ".translate", 0, 0, 1) cmds.setAttr(cube_c + ".translate", 1, 0, 0) cmds.setAttr(cube_a + ".scale", 2, 1, 1) cmds.setAttr(cube_b + ".scale", 1, 2, 1) cmds.setAttr(cube_c + ".scale", 1, 1, 2) success = self.create_rbfblender() cmds.setAttr("blender.rbfKernel", 1) cmds.setAttr("blender.blurParameter", 2.0) self.assert_(success, "Failed to create the node.") try: cmds.connectAttr(cube_test + ".translateX", "blender.input[0]") cmds.connectAttr(cube_test + ".translateZ", "blender.input[1]") cmds.connectAttr("blender.output[0]", cube_test + ".scaleX") cmds.connectAttr("blender.output[1]", cube_test + ".scaleY") cmds.connectAttr("blender.output[2]", cube_test + ".scaleZ") print "!! Creating pose 0" cmds.connectAttr(cube_a + ".translateX", "blender.poses[0].poseInputs[0]") cmds.connectAttr(cube_a + ".translateZ", "blender.poses[0].poseInputs[1]") cmds.connectAttr(cube_a + ".scaleX", "blender.poses[0].poseValues[0]") cmds.connectAttr(cube_a + ".scaleY", "blender.poses[0].poseValues[1]") cmds.connectAttr(cube_a + ".scaleZ", "blender.poses[0].poseValues[2]") print "!! Creating pose 1" cmds.connectAttr(cube_b + ".translateX", "blender.poses[1].poseInputs[0]") cmds.connectAttr(cube_b + ".translateZ", "blender.poses[1].poseInputs[1]") cmds.connectAttr(cube_b + ".scaleX", "blender.poses[1].poseValues[0]") cmds.connectAttr(cube_b + ".scaleY", "blender.poses[1].poseValues[1]") cmds.connectAttr(cube_b + ".scaleZ", "blender.poses[1].poseValues[2]") print "!! Creating pose 2" cmds.connectAttr(cube_c + ".translateX", "blender.poses[2].poseInputs[0]") cmds.connectAttr(cube_c + ".translateZ", "blender.poses[2].poseInputs[1]") cmds.connectAttr(cube_c + ".scaleX", "blender.poses[2].poseValues[0]") cmds.connectAttr(cube_c + ".scaleY", "blender.poses[2].poseValues[1]") cmds.connectAttr(cube_c + ".scaleZ", "blender.poses[2].poseValues[2]") success = True except Exception, e: success = False print e cmds.setAttr(cube_test + ".translate", -1, 0, 0) result = cmds.getAttr(cube_test + ".scale")[0] self.assertAlmostEquals( result[0], 2.0 , 4, "Bad result for thin plate" + str(cmds.getAttr(cube_test + ".scale") )) self.assertAlmostEquals( result[1], 1.0 ,4, "Bad result for thin plate" + str(cmds.getAttr(cube_test + ".scale") )) self.assertAlmostEquals( result[2], 1.0 ,4, "Bad result for thin plate" + str(cmds.getAttr(cube_test + ".scale") )) def test_cubes_thin_plate(self): print "###################################################" print "TEST CUBES THIN PLATE KERNEL" cube_test = cmds.polyCube()[0] cube_a = cmds.polyCube()[0] cube_b = cmds.polyCube()[0] cube_c = cmds.polyCube()[0] cmds.setAttr(cube_a + ".translate", -1, 0, 0) cmds.setAttr(cube_b + ".translate", 0, 0, 1) cmds.setAttr(cube_c + ".translate", 1, 0, 0) cmds.setAttr(cube_a + ".scale", 2, 1, 1) cmds.setAttr(cube_b + ".scale", 1, 2, 1) cmds.setAttr(cube_c + ".scale", 1, 1, 2) success = self.create_rbfblender() cmds.setAttr("blender.rbfKernel", 4) cmds.setAttr("blender.blurParameter", 2.0) self.assert_(success, "Failed to create the node.") try: cmds.connectAttr(cube_test + ".translateX", "blender.input[0]") cmds.connectAttr(cube_test + ".translateZ", "blender.input[1]") cmds.connectAttr("blender.output[0]", cube_test + ".scaleX") cmds.connectAttr("blender.output[1]", cube_test + ".scaleY") cmds.connectAttr("blender.output[2]", cube_test + ".scaleZ") print "!! Creating pose 0" cmds.connectAttr(cube_a + ".translateX", "blender.poses[0].poseInputs[0]") cmds.connectAttr(cube_a + ".translateZ", "blender.poses[0].poseInputs[1]") cmds.connectAttr(cube_a + ".scaleX", "blender.poses[0].poseValues[0]") cmds.connectAttr(cube_a + ".scaleY", "blender.poses[0].poseValues[1]") cmds.connectAttr(cube_a + ".scaleZ", "blender.poses[0].poseValues[2]") print "!! Creating pose 1" cmds.connectAttr(cube_b + ".translateX", "blender.poses[1].poseInputs[0]") cmds.connectAttr(cube_b + ".translateZ", "blender.poses[1].poseInputs[1]") cmds.connectAttr(cube_b + ".scaleX", "blender.poses[1].poseValues[0]") cmds.connectAttr(cube_b + ".scaleY", "blender.poses[1].poseValues[1]") cmds.connectAttr(cube_b + ".scaleZ", "blender.poses[1].poseValues[2]") print "!! Creating pose 2" cmds.connectAttr(cube_c + ".translateX", "blender.poses[2].poseInputs[0]") cmds.connectAttr(cube_c + ".translateZ", "blender.poses[2].poseInputs[1]") cmds.connectAttr(cube_c + ".scaleX", "blender.poses[2].poseValues[0]") cmds.connectAttr(cube_c + ".scaleY", "blender.poses[2].poseValues[1]") cmds.connectAttr(cube_c + ".scaleZ", "blender.poses[2].poseValues[2]") success = True except Exception, e: success = False print e cmds.setAttr(cube_test + ".translate", -1, 0, 0) result = cmds.getAttr(cube_test + ".scale")[0] self.assertAlmostEquals( result[0], 2.0 , 4, "Bad result for thin plate" + str(cmds.getAttr(cube_test + ".scale") )) self.assertAlmostEquals( result[1], 1.0 ,4, "Bad result for thin plate" + str(cmds.getAttr(cube_test + ".scale") )) self.assertAlmostEquals( result[2], 1.0 ,4, "Bad result for thin plate" + str(cmds.getAttr(cube_test + ".scale") )) def test_current_pose_index(self): print "###################################################" print "TEST CURRENT_POSE_INDEX" cube_test = cmds.polyCube()[0] cube_a = cmds.polyCube()[0] cube_b = cmds.polyCube()[0] cube_c = cmds.polyCube()[0] cmds.setAttr(cube_a + ".translate", -1, 0, 0) cmds.setAttr(cube_b + ".translate", 0, 0, 1) cmds.setAttr(cube_c + ".translate", 1, 0, 0) cmds.setAttr(cube_a + ".scale", 2, 1, 1) cmds.setAttr(cube_b + ".scale", 1, 2, 1) cmds.setAttr(cube_c + ".scale", 1, 1, 2) success = self.create_rbfblender() self.assert_(success, "Failed to create the node.") try: cmds.connectAttr(cube_test + ".translateX", "blender.input[0]") cmds.connectAttr(cube_test + ".translateZ", "blender.input[1]") cmds.connectAttr("blender.output[0]", cube_test + ".scaleX") cmds.connectAttr("blender.output[1]", cube_test + ".scaleY") cmds.connectAttr("blender.output[2]", cube_test + ".scaleZ") print "!! Creating pose 0" cmds.connectAttr(cube_a + ".translateX", "blender.poses[0].poseInputs[0]") cmds.connectAttr(cube_a + ".translateZ", "blender.poses[0].poseInputs[1]") cmds.connectAttr(cube_a + ".scaleX", "blender.poses[0].poseValues[0]") cmds.connectAttr(cube_a + ".scaleY", "blender.poses[0].poseValues[1]") cmds.connectAttr(cube_a + ".scaleZ", "blender.poses[0].poseValues[2]") print "!! Creating pose 1" cmds.connectAttr(cube_b + ".translateX", "blender.poses[1].poseInputs[0]") cmds.connectAttr(cube_b + ".translateZ", "blender.poses[1].poseInputs[1]") cmds.connectAttr(cube_b + ".scaleX", "blender.poses[1].poseValues[0]") cmds.connectAttr(cube_b + ".scaleY", "blender.poses[1].poseValues[1]") cmds.connectAttr(cube_b + ".scaleZ", "blender.poses[1].poseValues[2]") print "!! Creating pose 2" cmds.connectAttr(cube_c + ".translateX", "blender.poses[2].poseInputs[0]") cmds.connectAttr(cube_c + ".translateZ", "blender.poses[2].poseInputs[1]") cmds.connectAttr(cube_c + ".scaleX", "blender.poses[2].poseValues[0]") cmds.connectAttr(cube_c + ".scaleY", "blender.poses[2].poseValues[1]") cmds.connectAttr(cube_c + ".scaleZ", "blender.poses[2].poseValues[2]") success = True except Exception, e: success = False print e cmds.setAttr(cube_test + ".translate", -1, 0, 0) self.assert_( cmds.getAttr("blender.currentPoseIndex") == 0, "Bad result - expected 0 got " + str(cmds.getAttr("blender.currentPoseIndex") )) cmds.setAttr(cube_test + ".translate", 0, 0, 1) self.assert_( cmds.getAttr("blender.currentPoseIndex") == 1, "Bad result - expected 1 got " + str(cmds.getAttr("blender.currentPoseIndex") )) cmds.setAttr(cube_test + ".translate", 1, 0, 0) self.assert_( cmds.getAttr("blender.currentPoseIndex") == 2, "Bad result - expected 1 got " + str(cmds.getAttr("blender.currentPoseIndex") )) if __name__ == '__main__': unittest.main()

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0.111883

0.931357

0.894526

0.876303

0.863872

0.85144

0.838082

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0.26205

23,507

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47.297787

0.712803

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8

c248c19b6421ee8b976eb5f21ebcbfeb863abee7

334,075

py

Python

datapreprocessing/linepointfunctions_split_0610_20190920.py

Andyzr/work_zone_safety

e653740e7a42f06536f64c199388fd40d85aaaae

[ "MIT" ]

null

datapreprocessing/linepointfunctions_split_0610_20190920.py

Andyzr/work_zone_safety

e653740e7a42f06536f64c199388fd40d85aaaae

[ "MIT" ]

null

datapreprocessing/linepointfunctions_split_0610_20190920.py

Andyzr/work_zone_safety

e653740e7a42f06536f64c199388fd40d85aaaae

[ "MIT" ]

null

import shapefile # import finoa import shapely # import matplotlib import numpy as np import matplotlib.pyplot as plt # import matplotlib.pyplot as plt # import pandas as pd from pyproj import Proj, transform # import stateplane __author__ = 'Zhuoran Zhang' def distPL(Point, lineseg): # input:Point(x,y);lineseg[(x,y),(x,y),(x,y)...] # output:distance xp, yp = Point[0], Point[1] # lat lon distlist = [] for i in range(len(lineseg) - 1): x1, y1 = lineseg[i][0], lineseg[i][1] x2, y2 = lineseg[i + 1][0], lineseg[i + 1][1] point = [x1, y1, x2, y2] dist12 = [np.sqrt((xp - x1) ** 2 + (yp - y1) ** 2), np.sqrt((xp - x2) ** 2 + (yp - y2) ** 2)] dist3 = (abs((y2 - y1) * xp - (x2 - x1) * yp + x2 * y1 - y2 * x1)) / (np.sqrt((y2 - y1) ** 2 + (x2 - x1) ** 2)) if x1 == x2: if yp > min(y1, y2) and yp < max(y1, y2): dist = dist3 else: dist = np.min(dist12) elif y1 == y2: if xp > min(x1, x2) and xp < max(x1, x2): dist = dist3 else: dist = np.min(dist12) else: k = (y2 - y1) / (x2 - x1) x0 = (k ** 2 * x1 + k * (yp - y1) + xp) / (k ** 2 + 1) y0 = k * (x0 - x1) + y1 if x0 > min(x1, x2) and x0 < max(x1, x2) and y0 > min(y1, y2) and y0 < max(y1, y2): dist = dist3 else: dist = np.min(dist12) distlist.append(dist) return np.min(distlist) def distPP(P1, P2): distP = np.sqrt((P1[0] - P2[0]) ** 2 + (P1[1] - P2[1]) ** 2) return distP def LineInPointBox(i, startkeyuni, endkeyuni, bufferlat, bufferlon, road): if min(endkeyuni[i][0][0], startkeyuni[i][0][0]) - bufferlon < road.shape.bbox[0] and \ max(endkeyuni[i][0][0], startkeyuni[i][0][0]) + bufferlon > road.shape.bbox[0] and \ min(endkeyuni[i][0][1], startkeyuni[i][0][1]) - bufferlat < road.shape.bbox[1] and \ max(endkeyuni[i][0][1], startkeyuni[i][0][1]) + bufferlat > road.shape.bbox[1]: return True elif min(endkeyuni[i][0][0], startkeyuni[i][0][0]) - bufferlon < road.shape.bbox[2] and \ max(endkeyuni[i][0][0], startkeyuni[i][0][0]) + bufferlon > road.shape.bbox[2] and \ min(endkeyuni[i][0][1], startkeyuni[i][0][1]) - bufferlat < road.shape.bbox[3] and \ max(endkeyuni[i][0][1], startkeyuni[i][0][1]) + bufferlat > road.shape.bbox[3]: return True else: return False def PointBox(i, startkeyuni, endkeyuni, bufferlat, bufferlon, road): if road.shape.bbox[0] - bufferlon < startkeyuni[i][0][0] and road.shape.bbox[2] + bufferlon > startkeyuni[i][0][0] \ and road.shape.bbox[1] - bufferlat < startkeyuni[i][0][1] and road.shape.bbox[3] + bufferlat > \ startkeyuni[i][0][1]: return True elif road.shape.bbox[0] - bufferlon < endkeyuni[i][0][0] and road.shape.bbox[2] + bufferlon > endkeyuni[i][0][0] \ and road.shape.bbox[1] - bufferlat < endkeyuni[i][0][1] and road.shape.bbox[3] + bufferlat > \ endkeyuni[i][0][1]: return True elif min(endkeyuni[i][0][0], startkeyuni[i][0][0]) - bufferlon < road.shape.bbox[0] and \ max(endkeyuni[i][0][0], startkeyuni[i][0][0]) + bufferlon > road.shape.bbox[0] and \ min(endkeyuni[i][0][1], startkeyuni[i][0][1]) - bufferlat < road.shape.bbox[1] and \ max(endkeyuni[i][0][1], startkeyuni[i][0][1]) + bufferlat > road.shape.bbox[1]: return True elif min(endkeyuni[i][0][0], startkeyuni[i][0][0]) - bufferlon < road.shape.bbox[2] and \ max(endkeyuni[i][0][0], startkeyuni[i][0][0]) + bufferlon > road.shape.bbox[2] and \ min(endkeyuni[i][0][1], startkeyuni[i][0][1]) - bufferlat < road.shape.bbox[3] and \ max(endkeyuni[i][0][1], startkeyuni[i][0][1]) + bufferlat > road.shape.bbox[3]: return True else: return False def PointInLineBox(i, startkeyuni, bufferlat, bufferlon, roadshapebbox): if roadshapebbox[0] - bufferlon < startkeyuni[i][0][0] and roadshapebbox[2] + bufferlon > startkeyuni[i][0][0] \ and roadshapebbox[1] - bufferlat < startkeyuni[i][0][1] and roadshapebbox[3] + bufferlat > \ startkeyuni[i][0][1]: return True else: return False def DrawKeyPoint(i, road_shaperecords, endkeyuni, startkeyuni, wz_start, wz_end, wz_route, bufferlat, bufferlon): plt.figure(1) # plt.subplot(211) for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): shape3 = road shape_ex = shape3.shape x_lon = [] y_lat = [] for ip in range(len(shape_ex.points)): lat1 = shape_ex.points[ip][1] lon1 = shape_ex.points[ip][0] x_lon.append(lon1) y_lat.append(lat1) # print(x_lon,y_lat) # plt.plot(x_lon,y_lat) ori_wz_end_lat = wz_end["y_end"][i] ori_wz_end_lon = wz_end["x_end"][i] # print(case_wz_end_lat, case_wz_end_lon) # plt.plot(ori_wz_end_lon,ori_wz_end_lat,'og',label ='Original End') ori_wz_start_lat = wz_start["y_bgn"][i] ori_wz_start_lon = wz_start["x_bgn"][i] # print(case_wz_end_lat, case_wz_end_lon) # plt.plot(ori_wz_start_lon,ori_wz_start_lat,'ok',label ='Original Start') case_wz_end_lat = endkeyuni[i][0][1] case_wz_end_lon = endkeyuni[i][0][0] # print(case_wz_end_lat, case_wz_end_lon) # plt.plot(case_wz_end_lon,case_wz_end_lat,'*b',label ='Matched End') case_wz_start_lat = startkeyuni[i][0][1] case_wz_start_lon = startkeyuni[i][0][0] # print(case_wz_start_lat, case_wz_start_lon) # plt.plot(case_wz_start_lon,case_wz_start_lat,'*r',label ='Matched Start') plt.legend(loc='upper right') plt.title('Big Map of Work Zone-' + str(i) + " on State Plane") plt.savefig("./CMU_rcrs_all_events_08-2015_04-2017/Figures/BigMapStatePlane_" + str(i) + ".png") plt.figure(2) # plt.subplot(212) for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4) and \ (LineInPointBox(i, startkeyuni, endkeyuni, 1e-2, 1e-2, road) or \ PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox) or \ PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox)): shape3 = road shape_ex = shape3.shape x_lon = [] y_lat = [] for ip in range(len(shape_ex.points)): lat1 = shape_ex.points[ip][1] lon1 = shape_ex.points[ip][0] x_lon.append(lon1) y_lat.append(lat1) # print(x_lon,y_lat) # plt.plot(x_lon,y_lat) ori_wz_end_lat = wz_end["y_end"][i] ori_wz_end_lon = wz_end["x_end"][i] # print(case_wz_end_lat, case_wz_end_lon) # plt.plot(ori_wz_end_lon,ori_wz_end_lat,'og',label ='Original End') ori_wz_start_lat = wz_start["y_bgn"][i] ori_wz_start_lon = wz_start["x_bgn"][i] # print(case_wz_end_lat, case_wz_end_lon) # plt.plot(ori_wz_start_lon,ori_wz_start_lat,'ok',label ='Original Start') case_wz_end_lat = endkeyuni[i][0][1] case_wz_end_lon = endkeyuni[i][0][0] # print(case_wz_end_lat, case_wz_end_lon) # plt.plot(case_wz_end_lon,case_wz_end_lat,'*b',label ='Matched End') case_wz_start_lat = startkeyuni[i][0][1] case_wz_start_lon = startkeyuni[i][0][0] # print(case_wz_start_lat, case_wz_start_lon) # plt.plot(case_wz_start_lon,case_wz_start_lat,'*r',label ='Matched Start') plt.legend(loc='upper right') plt.title('Detailed Map of Work Zone-' + str(i) + " on State Plane") plt.savefig("./CMU_rcrs_all_events_08-2015_04-2017/Figures/DetailedMapStatePlane_" + str(i) + ".png") plt.show() def road_direction(wz_direction, startkeyuni_i, road_point_j1): wzx, wzy = startkeyuni_i[0][0], startkeyuni_i[0][1] roadx, roady = road_point_j1[0], road_point_j1[1] if wz_direction == "NORTH": if roadx > wzx: return True else: return False elif wz_direction == "SOUTH": if roadx < wzx: return True else: return False elif wz_direction == "EAST": if roady < wzy: return True else: return False elif wz_direction == "WEST": if roady > wzy: return True else: return False # significant error!!!!!!!!!!!!!!!!!!!!!!!!!!! def drawline(i): shapetest = shapefile.Reader("./CMU_rcrs_all_events_08-2015_04-2017/shapefile/SplittedLine_WZ" + str(i) + ".shp") shapetest_sr = shapetest.shapeRecords() # print(len(shapetest_sr)) plt.figure(1) for road in shapetest_sr: x_lon = [] y_lat = [] for ip in range(len(road.shape.points)): # lat1, lon1 =transform(inProj,outProj,shape_ex.points[ip][0],shape_ex.points[ip][1]) x_lon.append(road.shape.points[ip][0]) y_lat.append(road.shape.points[ip][1]) # print(x_lon) # plt.plot(x_lon,y_lat) case_wz_end_lon, case_wz_end_lat = endkeyuni[i][0][0], endkeyuni[i][0][1] # print(case_wz_end_lat, case_wz_end_lon) # plt.plot(case_wz_end_lon,case_wz_end_lat,'*b',label ='Matched End') case_wz_start_lon, case_wz_start_lat = startkeyuni[i][0][0], startkeyuni[i][0][1] # print(case_wz_start_lat, case_wz_start_lon) # plt.plot(case_wz_start_lon,case_wz_start_lat,'*r',label ='Matched Start') plt.legend(loc='upper right') plt.title('Splitted of Work Zone-' + str(i) + " on State South") plt.savefig("./CMU_rcrs_all_events_08-2015_04-2017/Figures/lineMapStateSouth_" + str(i) + ".png") def callinelength5(i): shapetest = shapefile.Reader("./CMU_rcrs_all_events_08-2015_04-2017/shapefile5/SplittedLine_WZ" + str(i) + ".shp") shapetest_sr = shapetest.shapeRecords() length = 0 for road in shapetest_sr: for ip in range(len(road.shape.points) - 1): lon1, lat1 = road.shape.points[ip][0], road.shape.points[ip][1] lon2, lat2 = road.shape.points[ip + 1][0], road.shape.points[ip + 1][1] length = length + np.sqrt((lon1 - lon2) ** 2 + (lat1 - lat2) ** 2) return length def callinelength2019(i, loc="./CMU_rcrs_all_events_08-2015_04-2017/shapefile5/SplittedLine_WZ"): shapetest = shapefile.Reader(loc + str(i) + ".shp") shapetest_sr = shapetest.shapeRecords() length = 0 for road in shapetest_sr: for ip in range(len(road.shape.points) - 1): lon1, lat1 = road.shape.points[ip][0], road.shape.points[ip][1] lon2, lat2 = road.shape.points[ip + 1][0], road.shape.points[ip + 1][1] length = length + np.sqrt((lon1 - lon2) ** 2 + (lat1 - lat2) ** 2) return length def direction_match(wzdiri, roaddiri): if str(wzdiri)[0:1] == roaddiri: return True elif (str(wzdiri)[0:1] == 'B') and (roaddiri == 'O'): return True elif roaddiri == 'B': return True else: return False def FindSplittedLine5_bi(i, roads, road_shaperecords, endkeyuni, startkeyuni, wz_route, bufferlat, bufferlon, workzone_DIRECTION): w = shapefile.Writer() w.fields = roads.fields[1:] records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and (direction_match(workzone_DIRECTION[i], road.record[10])): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 10 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 10 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and (direction_match(workzone_DIRECTION[i], road.record[10])): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 10 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("k1 ori = "+str(k1)) collection.remove(road) else: if scountlist < 3: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("scountlist ==1,k1="+str(k1)) collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print(scountlist,smark) # print("road_direction,k1="+str(k1)) # print(road.record) collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 10 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue # handle collection, delete the odd/even segnumber that is different from # print('k2='+str(k2)) # print('k1='+str(k1)) # print("scountlist,ecountlist,smark,emark") # print(scountlist,ecountlist,smark,emark) records.append(srecord) pointsparts.append([spoints]) try: records.append(erecord) pointsparts.append([epoints]) except: pass itercount = 0 while (k1 == []) and itercount < 10: bufferlat, bufferlon = bufferlat * 5, bufferlon * 5 records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and ( direction_match(workzone_DIRECTION[i], road.record[10])): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 10 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 10 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and ( direction_match(workzone_DIRECTION[i], road.record[10])): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 10: smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 10: emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP( startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue itercount = itercount + 1 # print(itercount) # print(k1,k2) k1_latlon = k1[1], k1[0] try: k2_latlon = k2[1], k2[0] except: k2_latlon = startkeyuni[i][0][1], startkeyuni[i][0][0] case_wz_end_lat, case_wz_end_lon = endkeyuni[i][0][1], endkeyuni[i][0][0] # print(case_wz_end_lat, case_wz_end_lon) # plt.figure(i) # plt.plot(case_wz_end_lon,case_wz_end_lat,'*b',label ='Matched End') case_wz_start_lat, case_wz_start_lon = startkeyuni[i][0][1], startkeyuni[i][0][0] # print(case_wz_start_lat, case_wz_start_lon) # plt.plot(case_wz_start_lon,case_wz_start_lat,'*r',label ='Matched Start') # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') # plt.plot(k2_latlon[1],k2_latlon[0],'og',label ='k2') iter_count = 1 k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 while k12_j and iter_count < 100: collection2 = collection.copy() for road in collection: if distPP(k1_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection2.remove(road) # print('l1') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection3 = collection2.copy() for road in collection2: if distPP(k2_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection3.remove(road) # print('l2') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection4 = collection3.copy() for road in collection3: if distPP(k1_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection4.remove(road) # print('l3') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection5 = collection4.copy() for road in collection4: if distPP(k2_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection5.remove(road) # print('l4') break iter_count = iter_count + 1 k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 5 and distPP(k2, startkeyuni[i][0]) > 5 if k12_j == False: break collection = collection5.copy() # print(iter_count) # plt.legend(loc='upper right') # elif LineInPointBox(i,startkeyuni,endkeyuni,1e-2,1e-2,road): # pointsparts.append(road.shape.points) # records.append(road.record) # print(len(pointsparts)) # print(len(records)) for idex in range(len(pointsparts)): # print(pointsparts[idex]) # print(records[idex]) # print(len(records[idex][0])) w.line(parts=pointsparts[idex]) w.record(*records[idex][0]) w.null() w.save('CMU_rcrs_all_events_08-2015_04-2017/shapefile5_bi/SplittedLine_WZ' + str(i)) def FindSplittedLine6_5(i, roads, road_shaperecords, endkeyuni, startkeyuni, wz_route, bufferlat, bufferlon, workzone_DIRECTION): w = shapefile.Writer() w.fields = roads.fields[1:] records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 1 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 1 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 1 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("k1 ori = "+str(k1)) collection.remove(road) else: if scountlist < 3: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("scountlist ==1,k1="+str(k1)) collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break print(scountlist) print(smark) print("road_direction,k1=" + str(k1)) collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 1 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue # handle collection, delete the odd/even segnumber that is different from # print('k2='+str(k2)) # print('k1='+str(k1)) # print("scountlist,ecountlist,smark,emark") # print(scountlist,ecountlist,smark,emark) records.append(srecord) pointsparts.append([spoints]) try: records.append(erecord) pointsparts.append([epoints]) except: pass itercount = 0 while (k1 == []) and itercount < 10: bufferlat, bufferlon = bufferlat * 5, bufferlon * 5 records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 1 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 1 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 1: smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 1: emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP( startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue itercount = itercount + 1 # print(itercount) # print(k1,k2) k1_latlon = k1[1], k1[0] try: k2_latlon = k2[1], k2[0] except: k2_latlon = startkeyuni[i][0][1], startkeyuni[i][0][0] case_wz_end_lat, case_wz_end_lon = endkeyuni[i][0][1], endkeyuni[i][0][0] # print(case_wz_end_lat, case_wz_end_lon) # plt.figure(i) # plt.plot(case_wz_end_lon,case_wz_end_lat,'*b',label ='Matched End') case_wz_start_lat, case_wz_start_lon = startkeyuni[i][0][1], startkeyuni[i][0][0] # print(case_wz_start_lat, case_wz_start_lon) # plt.plot(case_wz_start_lon,case_wz_start_lat,'*r',label ='Matched Start') # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') # plt.plot(k2_latlon[1],k2_latlon[0],'og',label ='k2') iter_count = 1 k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 while k12_j and iter_count < 100: collection2 = collection.copy() for road in collection: if distPP(k1_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection2.remove(road) # print('l1') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection3 = collection2.copy() for road in collection2: if distPP(k2_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection3.remove(road) # print('l2') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection4 = collection3.copy() for road in collection3: if distPP(k1_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection4.remove(road) # print('l3') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection5 = collection4.copy() for road in collection4: if distPP(k2_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection5.remove(road) # print('l4') break iter_count = iter_count + 1 k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 5 and distPP(k2, startkeyuni[i][0]) > 5 if k12_j == False: break collection = collection5.copy() # print(iter_count) # plt.legend(loc='upper right') # elif LineInPointBox(i,startkeyuni,endkeyuni,1e-2,1e-2,road): # pointsparts.append(road.shape.points) # records.append(road.record) # print(len(pointsparts)) # print(len(records)) for idex in range(len(pointsparts)): # print(pointsparts[idex]) # print(records[idex]) # print(len(records[idex][0])) w.line(parts=pointsparts[idex]) w.record(*records[idex][0]) w.null() w.save('CMU_rcrs_all_events_08-2015_04-2017/shapefile5/SplittedLine_WZ' + str(i)) def FindSplittedLine7(i, roads, road_shaperecords, endkeyuni, startkeyuni, wz_route, bufferlat, bufferlon, workzone_DIRECTION, fileloc='CMU_rcrs_all_events_08-2015_04-2017/shapefile5/SplittedLine_WZ'): w = shapefile.Writer() w.fields = roads.fields[1:] records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 1 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 1 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 1 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("k1 ori = "+str(k1)) collection.remove(road) else: if scountlist < 3: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("scountlist ==1,k1="+str(k1)) collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break print(scountlist) print(smark) print("road_direction,k1=" + str(k1)) collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 1 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue # handle collection, delete the odd/even segnumber that is different from # print('k2='+str(k2)) # print('k1='+str(k1)) # print("scountlist,ecountlist,smark,emark") # print(scountlist,ecountlist,smark,emark) records.append(srecord) pointsparts.append([spoints]) try: records.append(erecord) pointsparts.append([epoints]) except: pass itercount = 0 while (k1 == []) and itercount < 10: bufferlat, bufferlon = bufferlat * 5, bufferlon * 5 records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 1 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 1 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if road.record[0] == str(wz_route[i]).zfill(4): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 1: smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 1: emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP( startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue itercount = itercount + 1 # print(itercount) # print(k1,k2) k1_latlon = k1[1], k1[0] try: k2_latlon = k2[1], k2[0] except: k2_latlon = startkeyuni[i][0][1], startkeyuni[i][0][0] case_wz_end_lat, case_wz_end_lon = endkeyuni[i][0][1], endkeyuni[i][0][0] # print(case_wz_end_lat, case_wz_end_lon) # plt.figure(i) # plt.plot(case_wz_end_lon,case_wz_end_lat,'*b',label ='Matched End') case_wz_start_lat, case_wz_start_lon = startkeyuni[i][0][1], startkeyuni[i][0][0] # print(case_wz_start_lat, case_wz_start_lon) # plt.plot(case_wz_start_lon,case_wz_start_lat,'*r',label ='Matched Start') # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') # plt.plot(k2_latlon[1],k2_latlon[0],'og',label ='k2') iter_count = 1 k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 while k12_j and iter_count < 100: collection2 = collection.copy() for road in collection: if distPP(k1_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection2.remove(road) # print('l1') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection3 = collection2.copy() for road in collection2: if distPP(k2_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection3.remove(road) # print('l2') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection4 = collection3.copy() for road in collection3: if distPP(k1_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection4.remove(road) # print('l3') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection5 = collection4.copy() for road in collection4: if distPP(k2_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection5.remove(road) # print('l4') break iter_count = iter_count + 1 k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 5 and distPP(k2, startkeyuni[i][0]) > 5 if k12_j == False: break collection = collection5.copy() # print(iter_count) # plt.legend(loc='upper right') # elif LineInPointBox(i,startkeyuni,endkeyuni,1e-2,1e-2,road): # pointsparts.append(road.shape.points) # records.append(road.record) # print(len(pointsparts)) # print(len(records)) for idex in range(len(pointsparts)): # print(pointsparts[idex]) # print(records[idex]) # print(len(records[idex][0])) w.line(parts=pointsparts[idex]) # w.line( pointsparts[idex]) w.record(*records[idex][0]) w.null() w.save(fileloc + str(i)) # bi def FindSplittedLine7_bi(i, roads, road_shaperecords, endkeyuni, startkeyuni, wz_route, bufferlat, bufferlon, workzone_DIRECTION, fileloc): w = shapefile.Writer() w.fields = roads.fields[1:] records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and (direction_match(workzone_DIRECTION[i], road.record[10])): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 10 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 10 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and (direction_match(workzone_DIRECTION[i], road.record[10])): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 10 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("k1 ori = "+str(k1)) collection.remove(road) else: if scountlist < 3: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print("scountlist ==1,k1="+str(k1)) collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break # print(scountlist,smark) # print("road_direction,k1="+str(k1)) # print(road.record) collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 10 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]): emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue # handle collection, delete the odd/even segnumber that is different from # print('k2='+str(k2)) # print('k1='+str(k1)) # print("scountlist,ecountlist,smark,emark") # print(scountlist,ecountlist,smark,emark) records.append(srecord) pointsparts.append([spoints]) try: records.append(erecord) pointsparts.append([epoints]) except: pass itercount = 0 while (k1 == []) and itercount < 10: bufferlat, bufferlon = bufferlat * 5, bufferlon * 5 records = [] pointsparts = [] k1 = [] k2 = [] collection = set() smark = 0 emark = 0 scountlist = 0 ecountlist = 0 for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and ( direction_match(workzone_DIRECTION[i], road.record[10])): if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] scount = distPL(startkeyuni[i][0], vetice) < 10 and distPL(endkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) scountlist = scountlist + scount if PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] ecount = distPL(endkeyuni[i][0], vetice) < 10 and distPL(startkeyuni[i][0], vetice) < distPP( endkeyuni[i][0], startkeyuni[i][0]) ecountlist = ecountlist + ecount for road in road_shaperecords: if (road.record[0] == str(wz_route[i]).zfill(4)) and ( direction_match(workzone_DIRECTION[i], road.record[10])): collection.add(road) if PointInLineBox(i, startkeyuni, bufferlat, bufferlon, road.shape.bbox): for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(startkeyuni[i][0], vetice) < 10: smark = smark + 1 cosup = distPP(endkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: if smark <= 1: srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j + 1]): srecord = [road.record] spoints = [] spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k1 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: spoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) spoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) spoints.append(k1) break collection.remove(road) else: if smark <= 1: srecord = [road.record] spoints = [] for jm in range(j + 1): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP(startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if scountlist == 1: if distPP(endkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP(endkeyuni[i][0], k1): srecord = [road.record] spoints = [] for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j + 1): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: if road_direction(workzone_DIRECTION[i], startkeyuni[i], road.shape.points[j]): srecord = [road.record] spoints = [] k1 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j): spoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) spoints.append((startkeyuni[i][0][0], startkeyuni[i][0][1])) cosk1 = distPP(startkeyuni[i][0], endkeyuni[i][0]) - distPP( startkeyuni[i][0], k1) if cosk1 < 0: k1 = ((endkeyuni[i][0][0], endkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(endkeyuni[i][0], vetice_mm) > 1: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: spoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) spoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) spoints.insert(0, k1) break collection.remove(road) else: continue elif PointInLineBox(i, endkeyuni, bufferlat, bufferlon, road.shape.bbox): # print('a') for j in range(len(road.shape.points) - 1): subpart = [] vetice = [[road.shape.points[j][0], road.shape.points[j][1]], [road.shape.points[j + 1][0], road.shape.points[j + 1][1]]] if distPL(endkeyuni[i][0], vetice) < 10: emark = emark + 1 cosup = distPP(startkeyuni[i][0], [road.shape.points[j][0], \ road.shape.points[j][1]]) - distPP(startkeyuni[i][0], [ road.shape.points[j + 1][0], \ road.shape.points[j + 1][1]]) if cosup > 0: # print('d') if emark <= 1: erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove((road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove((road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print("cosup>0emark<=1") # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][ 1]]) < distPP(startkeyuni[i][0], k2): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j + 1]): erecord = [road.record] epoints = [] epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) for jm in range(j + 1, len(road.shape.points)): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) k2 = ((road.shape.points[len(road.shape.points) - 1][0], \ road.shape.points[len(road.shape.points) - 1][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(len(road.shape.points) - j - 2): vetice_mm = [[road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][ 1]], \ [road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][ 1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) else: epoints.remove( (road.shape.points[len(road.shape.points) - js - 1][0], \ road.shape.points[len(road.shape.points) - js - 1][1])) epoints.remove( (road.shape.points[len(road.shape.points) - js - 2][0], \ road.shape.points[len(road.shape.points) - js - 2][1])) epoints.append(k2) break # print(k2) try: collection.remove(road) except: pass else: # print("e") # print(cosup) # print(j) if emark <= 1: # print(emark) # print("emark<=1") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: if ecountlist == 1: if distPP(startkeyuni[i][0], [road.shape.points[0][0], \ road.shape.points[0][1]]) < distPP( startkeyuni[i][0], k2): erecord = [road.record] epoints = [] k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print("ecountlist=2") # print(k2) try: collection.remove(road) except: pass else: if road_direction(workzone_DIRECTION[i], endkeyuni[i], road.shape.points[j]): # print("f") erecord = [road.record] epoints = [] for jm in range(j + 1): epoints.append((road.shape.points[jm][0], road.shape.points[jm][1])) epoints.append((endkeyuni[i][0][0], endkeyuni[i][0][1])) k2 = ((road.shape.points[0][0], \ road.shape.points[0][1])) cosk2 = distPP(endkeyuni[i][0], startkeyuni[i][0]) - distPP(endkeyuni[i][0], k2) if cosk2 < 0: k2 = ((startkeyuni[i][0][0], startkeyuni[i][0][1])) for js in range(j): vetice_mm = [[road.shape.points[js][0], \ road.shape.points[js][1]], \ [road.shape.points[js + 1][0], \ road.shape.points[js + 1][1]]] if distPL(startkeyuni[i][0], vetice_mm) > 1: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) else: epoints.remove((road.shape.points[js][0], \ road.shape.points[js][1])) epoints.remove((road.shape.points[js + 1][0], \ road.shape.points[js + 1][1])) epoints.insert(0, k2) break # print(k2) try: collection.remove(road) except: pass else: continue itercount = itercount + 1 # print(itercount) # print(k1,k2) k1_latlon = k1[1], k1[0] try: k2_latlon = k2[1], k2[0] except: k2_latlon = startkeyuni[i][0][1], startkeyuni[i][0][0] case_wz_end_lat, case_wz_end_lon = endkeyuni[i][0][1], endkeyuni[i][0][0] # print(case_wz_end_lat, case_wz_end_lon) # plt.figure(i) # plt.plot(case_wz_end_lon,case_wz_end_lat,'*b',label ='Matched End') case_wz_start_lat, case_wz_start_lon = startkeyuni[i][0][1], startkeyuni[i][0][0] # print(case_wz_start_lat, case_wz_start_lon) # plt.plot(case_wz_start_lon,case_wz_start_lat,'*r',label ='Matched Start') # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') # plt.plot(k2_latlon[1],k2_latlon[0],'og',label ='k2') iter_count = 1 k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 while k12_j and iter_count < 100: collection2 = collection.copy() for road in collection: if distPP(k1_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection2.remove(road) # print('l1') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection3 = collection2.copy() for road in collection2: if distPP(k2_latlon, [road.shape.points[0][1], road.shape.points[0][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[len(road.shape.points) - 1][1], \ road.shape.points[len(road.shape.points) - 1][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection3.remove(road) # print('l2') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection4 = collection3.copy() for road in collection3: if distPP(k1_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k1_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k1_latlon[1],k1_latlon[0],'ob',label ='k1') collection4.remove(road) # print('l3') break k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 1 and distPP(k2, startkeyuni[i][0]) > 1 if k12_j == False: break collection5 = collection4.copy() for road in collection4: if distPP(k2_latlon, [road.shape.points[len(road.shape.points) - 1][1], road.shape.points[len(road.shape.points) - 1][0]]) < 1: records.append([road.record]) pointsparts.append([road.shape.points]) k2_latlon = road.shape.points[0][1], road.shape.points[0][0] # plt.plot(k2_latlon[1],k2_latlon[0],'or',label ='k2') collection5.remove(road) # print('l4') break iter_count = iter_count + 1 k1 = k1_latlon[1], k1_latlon[0] k2 = k2_latlon[1], k2_latlon[0] # print("k1="+str(k1)+", k2="+str(k2)) k12_j = distPP(k1_latlon, k2_latlon) > 5 and distPP(k1, endkeyuni[i][0]) > 5 and distPP(k2, startkeyuni[i][0]) > 5 if k12_j == False: break collection = collection5.copy() # print(iter_count) # plt.legend(loc='upper right') # elif LineInPointBox(i,startkeyuni,endkeyuni,1e-2,1e-2,road): # pointsparts.append(road.shape.points) # records.append(road.record) # print(len(pointsparts)) # print(len(records)) for idex in range(len(pointsparts)): # print(pointsparts[idex]) # print(records[idex]) # print(len(records[idex][0])) w.line(parts=pointsparts[idex]) w.record(*records[idex][0]) w.null() w.save(fileloc + str(i))

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