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9be957a2c85ebd9b19fe425153d975765239ef04 | 9a1a829eee3b08ed3e1c412d183c0967d44d2c70 | /djinsta/djinsta/urls.py | e4141e8f4811e7e5ca3c6e379697a43e7a854454 | [
"MIT"
] | permissive | woshangfenglove/djinsta | 4f6df93719b46008fb4dfa007527f78f565d1eb8 | 3e006a7027de51715ec34211b0bc771893f2f4a1 | refs/heads/master | 2021-09-11T17:44:32.047646 | 2018-04-10T12:50:11 | 2018-04-10T12:50:11 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 794 | py | """djinsta URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path, include
urlpatterns = [
path('', include('djin.urls')),
path('admin/', admin.site.urls),
]
| [
"jacoj82@gmail.com"
] | jacoj82@gmail.com |
b8670c5aaf471c6fa46c46bcd823dc3286c9e1b8 | 713e839939340299fa91711f67a05fff101e8dc1 | /DenoisingNetwork.py | 0cc34c21dcdd7d7dbed204ef46c5f00cd7ebca36 | [] | no_license | wuweijia1994/SmartSpeaker | 50b9d7af41e30de2cd149013cd848d5fe4bbfedb | b362dc0fdea9e969d8a885ba6d1dc1ab45ceb210 | refs/heads/master | 2021-09-08T08:49:54.734607 | 2018-03-08T22:21:41 | 2018-03-08T22:21:41 | 119,096,304 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,044 | py | import torch.nn as nn
class DenoiseNN(nn.Module):
def __init__(self):
super(DenoiseNN, self).__init__()
#Input layer
self.conv1 = nn.Conv2d(1, 1, 3, padding=1)
self.relu_0 = nn.ReLU()
self.linear_1 = nn.Linear(161*11, 1600)
self.relu_1 = nn.ReLU()
self.linear_2 = nn.Linear(1600, 1600)
self.relu_2 = nn.ReLU()
self.linear_3 = nn.Linear(1600, 1600)
self.relu_3 = nn.ReLU()
self.linear_4 = nn.Linear(1600, 1600)
self.relu_4 = nn.ReLU()
#output layer
self.linear_5 = nn.Linear(1600, 161)
self.relu_5 = nn.ReLU()
def forward(self, x):
result = x.view(-1, 161 * 11)
# result = self.relu_0(self.conv1(result))
result = self.relu_1(self.linear_1(result))
result = self.relu_2(self.linear_2(result))
result = self.relu_3(self.linear_3(result))
result = self.relu_4(self.linear_4(result))
result = self.relu_5(self.linear_5(result))
return result | [
"wuweijia1994@gmail.com"
] | wuweijia1994@gmail.com |
627f6d620e34572e7e1f2d032257d42b4ac728de | ec1e8462d5dfe3e7cb63787a2097ddd8b63217f0 | /scripts/run_mdnmp_for_balanceball_real.py | bccef238e3eae66c026a4c15512d7461487c31c8 | [] | no_license | tczhouyou/mpgen | 172899d024788ad120ba1cdfdd125caf6aa21cca | a68c1434ca8f0c02ca1dee615423f07597ac7465 | refs/heads/master | 2023-02-12T11:21:43.119024 | 2021-01-05T11:20:47 | 2021-01-05T11:20:47 | 327,266,411 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,234 | py | import os, inspect, sys
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
os.sys.path.insert(0, currentdir)
os.sys.path.insert(0, '..')
os.sys.path.insert(0, '../experiments/mujoco')
import numpy as np
from models.mdnmp import MDNMP
from mp.qvmp import QVMP
from sklearn.model_selection import train_test_split
from optparse import OptionParser
from experiments.exp_tools import get_training_data_from_2d_grid
import tensorflow as tf
if tf.__version__ < '2.0.0':
import tflearn
VAR_INIT = tflearn.initializations.uniform(minval=-.1, maxval=.1, seed=42)
else:
from tensorflow.keras import initializers
VAR_INIT = initializers.RandomUniform(minval=-0.1, maxval=0.1, seed=42)
parser = OptionParser()
parser.add_option("-m", "--nmodel", dest="nmodel", type="int", default=3)
parser.add_option("-q", "--qfile", dest="qfile", type="string", default="balanceball_queries.csv")
parser.add_option("-w", "--wfile", dest="wfile", type="string", default="balanceball_weights.csv")
parser.add_option("-d", "--result_dir", dest="rdir", type="string", default="results_real_balanceball")
parser.add_option("--grid_samples", dest="is_grid_samples", action="store_true", default=False)
parser.add_option("--num_train", dest="ntrain", type="int", default=10)
parser.add_option("--sample_num", dest="nsamples", type="int", default=10)
parser.add_option("--model_name", dest="model_name", type="string", default="mce")
parser.add_option("--max_epochs", dest="max_epochs", type="int", default=10000)
(options, args) = parser.parse_args(sys.argv)
queries = np.loadtxt(options.qfile, delimiter=',')
vmps = np.loadtxt(options.wfile, delimiter=',')
queries[:,0] = queries[:,0]/20
queries[:,1] = queries[:,1]/30
# prepare model
nn_structure = {'d_feat': 40,
'feat_layers': [20],
'mean_layers': [60],
'scale_layers': [60],
'mixing_layers': [20]}
d_input = np.shape(queries)[-1]
d_output = np.shape(vmps)[1]
tratio = 0.5
if options.is_grid_samples:
_, ids = get_training_data_from_2d_grid(options.ntrain, queries=queries)
trqueries = queries[ids,:]
trvmps = vmps[ids,:]
_, tqueries, _, tvmps = train_test_split(queries, vmps, test_size=tratio, random_state=42)
else:
trqueries, tqueries, trvmps, tvmps = train_test_split(queries, vmps, test_size=tratio, random_state=42)
mdnmp = MDNMP(n_comps=options.nmodel, d_input=d_input, d_output=d_output, nn_structure=nn_structure,
var_init=VAR_INIT, scaling=1.0)
lrate = 0.001
if options.model_name == "omce":
mdnmp.lratio['entropy'] = 10
mdnmp.is_orthogonal_cost = True
mdnmp.is_mce_only = True
mdnmp.is_normalized_grad = False
mdnmp.cross_train = True
mdnmp.nll_lrate = lrate
mdnmp.ent_lrate = lrate
elif options.model_name == "elk":
mdnmp.lratio['entropy'] = 10
mdnmp.is_orthogonal_cost = True
mdnmp.is_mce_only = False
mdnmp.is_normalized_grad = False
mdnmp.cross_train = True
mdnmp.nll_lrate = lrate
mdnmp.ent_lrate = lrate
elif options.model_name == "mce":
mdnmp.lratio['entropy'] = 10
mdnmp.is_orthogonal_cost = False
mdnmp.is_mce_only = True
mdnmp.is_normalized_grad = False
else:
mdnmp.lratio['entropy'] = 0
mdnmp.build_mdn(learning_rate=lrate)
mdnmp.init_train()
is_pos = np.ones(shape=(np.shape(trvmps)[0], 1))
mdnmp.train(trqueries, trvmps, is_pos, max_epochs=options.max_epochs, is_load=False, is_save=False)
result_dir = options.rdir
if not os.path.exists(result_dir):
os.makedirs(result_dir)
wout, _ = mdnmp.predict(tqueries, options.nsamples)
wfname = result_dir + '/' + options.model_name + '_balanceball_testing_weights.csv'
qfname = result_dir + '/' + options.model_name + '_balanceball_testing_queries.csv'
wfile = open(wfname, 'w+')
qfile = open(qfname, 'w+')
for i in range(np.shape(wout)[0]):
weights = wout[i,:,:]
np.savetxt(wfile, weights, delimiter=',')
cquery = np.expand_dims(tqueries[i,:], axis=0)
cqueries = np.tile(cquery, (np.shape(weights)[0], 1))
cqueries[:,0] = cqueries[:,0] * 20
cqueries[:,1] = cqueries[:,1] * 30
np.savetxt(qfile, cqueries, delimiter=',')
| [
"you.zhou@kit.edu"
] | you.zhou@kit.edu |
edb0af5fe1bef9f2bdae693f8f6c6ee8f2cd6483 | 863bc319e092b5127037db0ead15e627e4b0ac72 | /Uncertainty/data/case-ln/case_ln_100.py | 98ae71457dc82915ee0516dd7baec5f5b7b5bdc8 | [
"MIT"
] | permissive | thanever/SOC | ea349e61eebef7f31c610765cd5db1be14b60800 | 7dc33e9f4713d012f206385452987579f46b63eb | refs/heads/master | 2023-08-27T04:57:38.825111 | 2023-08-07T03:20:42 | 2023-08-07T03:20:42 | 212,486,054 | 3 | 1 | null | null | null | null | UTF-8 | Python | false | false | 321,671 | py | from numpy import array
def case_ln_100():
ppc = {"version": '2'}
ppc["baseMVA"] = 100.0
ppc["bus"] = array([
[1.0, 1.0, 36.3818, 9.7018, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[2.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[3.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[4.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[5.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[6.0, 1.0, 7.2764, 2.668, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[7.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[8.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[9.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 11.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[10.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 11.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[11.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 66.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[12.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 66.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[13.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[14.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[15.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 66.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[16.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 66.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[17.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 66.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[18.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 66.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[19.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[20.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[21.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[22.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[23.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[24.0, 2.0, 2.4255, 1.4553, 0.0, 0.0, 1.0, 1.0, 0.0, 6.3, 1.0, 1.1, 0.95, 0.6, 10 ],
[25.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[26.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[27.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[28.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[29.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[30.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 13.8, 1.0, 1.1, 0.95, 0.6, 10 ],
[31.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 13.8, 1.0, 1.1, 0.95, 0.6, 10 ],
[32.0, 2.0, 1.6978, 1.4553, 0.0, 0.0, 1.0, 1.0, 0.0, 20.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[33.0, 2.0, 1.4553, 1.4553, 0.0, 0.0, 1.0, 1.0, 0.0, 15.75, 1.0, 1.1, 0.95, 0.6, 10 ],
[34.0, 2.0, 1.4553, 1.4553, 0.0, 0.0, 1.0, 1.0, 0.0, 15.75, 1.0, 1.1, 0.95, 0.6, 10 ],
[35.0, 2.0, 3.3956, 1.4553, 0.0, 0.0, 1.0, 1.0, 0.0, 24.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[36.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[37.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[38.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[39.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[40.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[41.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[42.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[43.0, 1.0, 41.1356, 1.5426, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[44.0, 1.0, 48.509, 3.0367, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[45.0, 1.0, 48.509, 3.0367, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[46.0, 1.0, 48.509, 3.0367, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[47.0, 1.0, 48.509, 3.0367, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[48.0, 1.0, 24.2545, 3.1579, 1e-06, -1e-06, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[49.0, 1.0, 50.4494, 3.1579, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[50.0, 1.0, 10.0899, 3.1579, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[51.0, 1.0, 29.1054, 9.7018, 5e-07, -5e-07, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[52.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[53.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[54.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[55.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[56.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[57.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[58.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[59.0, 1.0, 48.509, 3.0367, 0.0, 0.0, 1.0, 1.0, 0.0, 220.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[107.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[108.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[109.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 500.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[110.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[111.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[112.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 500.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[113.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 500.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[114.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 500.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[115.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 500.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[116.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 66.0, 1.0, 1.1, 0.95, 0.6, 10 ],
[117.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 35.0, 1.0, 1.1, 0.95, 0.6, 10 ],
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[2.0, 0.0, 0.0, 3.0, 0.0, 29.0, 0.0, 43.5, 21.75, 34.8, 17.4 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 29.0, 0.0, 43.5, 21.75, 34.8, 17.4 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 14.4, 0.0, 21.6, 10.8, 17.28, 8.64 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 14.4, 0.0, 21.6, 10.8, 17.28, 8.64 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 16.8, 0.0, 25.2, 12.6, 20.16, 10.08 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 16.8, 0.0, 25.2, 12.6, 20.16, 10.08 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 48.0, 0.0, 72.0, 36.0, 57.6, 28.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 48.0, 0.0, 72.0, 36.0, 57.6, 28.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 40.0, 0.0, 60.0, 30.0, 48.0, 24.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 40.0, 0.0, 60.0, 30.0, 48.0, 24.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 60.0, 0.0, 90.0, 45.0, 72.0, 36.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 60.0, 0.0, 90.0, 45.0, 72.0, 36.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 84.0, 0.0, 126.0, 63.0, 100.8, 50.4 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 39.6, 0.0, 59.4, 29.7, 47.52, 23.76 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 80.0, 0.0, 120.0, 60.0, 96.0, 48.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 20.0, 0.0, 30.0, 15.0, 24.0, 12.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 36.0, 0.0, 54.0, 27.0, 43.2, 21.6 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 36.0, 0.0, 54.0, 27.0, 43.2, 21.6 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 36.0, 0.0, 54.0, 27.0, 43.2, 21.6 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 36.0, 0.0, 54.0, 27.0, 43.2, 21.6 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 62.8, 0.0, 94.2, 47.1, 75.36, 37.68 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 62.8, 0.0, 94.2, 47.1, 75.36, 37.68 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 320.0, 0.0, 480.0, 240.0, 384.0, 192.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 320.0, 0.0, 480.0, 240.0, 384.0, 192.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 403.2, 0.0, 604.8, 302.4, 483.84, 241.92 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 403.2, 0.0, 604.8, 302.4, 483.84, 241.92 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 54.0, 0.0, 81.0, 40.5, 64.8, 32.4 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 54.0, 0.0, 81.0, 40.5, 64.8, 32.4 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 18.0, 0.0, 27.0, 13.5, 21.6, 10.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 18.0, 0.0, 27.0, 13.5, 21.6, 10.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 18.0, 0.0, 27.0, 13.5, 21.6, 10.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 18.0, 0.0, 27.0, 13.5, 21.6, 10.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 20.0, 0.0, 30.0, 15.0, 24.0, 12.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 20.0, 0.0, 30.0, 15.0, 24.0, 12.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 120.0, 0.0, 180.0, 90.0, 144.0, 72.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 208.0, 0.0, 312.0, 156.0, 249.6, 124.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 12.0, 6.0, 9.6, 4.8 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ],
[2.0, 0.0, 0.0, 3.0, 0.0, 240.0, 0.0, 360.0, 180.0, 288.0, 144.0 ]
])
return ppc | [
"hantong.eee@gmail.com"
] | hantong.eee@gmail.com |
ebba5c2b286a36e7c8f7a892c7503544135da769 | a113ff7ea6f4d45f1084e34a1bc888b04aade8c7 | /Blueprint.py | 915c46f1f63cf55efd619bf0c4b8f89146f28743 | [] | no_license | nomadotto/Chernovitz | c7b84fa0402c9a61146d7fc5e965d594cc06b4a9 | 5794738212648a87d88e187b0755b12e264f3a23 | refs/heads/master | 2020-04-02T15:43:30.429731 | 2018-11-30T17:42:30 | 2018-11-30T17:42:30 | 154,580,902 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,850 | py | from TaskDifficultyCalc import Task
class Blueprint:
def __init__(self, nplayers, tasks=None, card_split=None):
self.nplayers = nplayers
if tasks is not None:
try:
assert nplayers == len(tasks)
self.tasks = tasks
except AssertionError:
raise ValueError('Number of tasks and number of players do not agree')
else:
self.tasks = tasks
if card_split is not None:
try:
assert nplayers == len(card_split)
self.card_split = card_split
except AssertionError:
raise ValueError('Size of Cardsplit and number of players do not agree')
else:
self.card_split = card_split
def make_random_tasks(self):
tasks = []
if self.card_split is None:
self.make_card_split()
for i in range(self.nplayers):
cards = self.card_split[i]
ncards = cards / 6
t = Task(ncards=ncards, hand_size=cards)
t.make_random_requirements()
tasks.append(t)
self.tasks = tasks
def make_card_split(self, deck_size=104):
cards = [0]*self.nplayers
remaining_cards = deck_size - 5*self.nplayers - 6
while remaining_cards > 3*self.nplayers:
elem = map(lambda x: x+3, cards)
cards = elem
remaining_cards += -3*self.nplayers
while remaining_cards > ((self.nplayers/2)*3):
for i in range(self.nplayers/2 + 1, self.nplayers):
cards[i] += 3
remaining_cards += -3
while remaining_cards > 0:
for i in range(self.nplayers-1, 0, -1):
cards[i] += 1
remaining_cards += -1
self.card_split = cards
| [
"ned.damon@dat.com"
] | ned.damon@dat.com |
1d1eb7b895ef58d7411393323789a6cea8d74eb4 | 5ec06dab1409d790496ce082dacb321392b32fe9 | /clients/python/generated/test/test_com_day_cq_wcm_designimporter_parser_taghandlers_factory_text_component_info.py | 9dd311727f08f354672f50c4174ba64c40b3ee04 | [
"Apache-2.0"
] | permissive | shinesolutions/swagger-aem-osgi | e9d2385f44bee70e5bbdc0d577e99a9f2525266f | c2f6e076971d2592c1cbd3f70695c679e807396b | refs/heads/master | 2022-10-29T13:07:40.422092 | 2021-04-09T07:46:03 | 2021-04-09T07:46:03 | 190,217,155 | 3 | 3 | Apache-2.0 | 2022-10-05T03:26:20 | 2019-06-04T14:23:28 | null | UTF-8 | Python | false | false | 1,437 | py | # coding: utf-8
"""
Adobe Experience Manager OSGI config (AEM) API
Swagger AEM OSGI is an OpenAPI specification for Adobe Experience Manager (AEM) OSGI Configurations API # noqa: E501
The version of the OpenAPI document: 1.0.0
Contact: opensource@shinesolutions.com
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import unittest
import swaggeraemosgi
from swaggeraemosgi.models.com_day_cq_wcm_designimporter_parser_taghandlers_factory_text_component_info import ComDayCqWcmDesignimporterParserTaghandlersFactoryTextComponentInfo # noqa: E501
from swaggeraemosgi.rest import ApiException
class TestComDayCqWcmDesignimporterParserTaghandlersFactoryTextComponentInfo(unittest.TestCase):
"""ComDayCqWcmDesignimporterParserTaghandlersFactoryTextComponentInfo unit test stubs"""
def setUp(self):
pass
def tearDown(self):
pass
def testComDayCqWcmDesignimporterParserTaghandlersFactoryTextComponentInfo(self):
"""Test ComDayCqWcmDesignimporterParserTaghandlersFactoryTextComponentInfo"""
# FIXME: construct object with mandatory attributes with example values
# model = swaggeraemosgi.models.com_day_cq_wcm_designimporter_parser_taghandlers_factory_text_component_info.ComDayCqWcmDesignimporterParserTaghandlersFactoryTextComponentInfo() # noqa: E501
pass
if __name__ == '__main__':
unittest.main()
| [
"michael.bloch@shinesolutions.com"
] | michael.bloch@shinesolutions.com |
beb2397dfb0c52fcc0c2f8efa05bb414e3120823 | ef3ea59309b698b931ebdf8a26765c949177dec3 | /Assignment3/Question1/Q1_Part_2.py | 204889eea0c2b6e26ea7f55f91f5fd34fb9c9b40 | [] | no_license | Shivam1989/Python | f50625965fdaeb9b38f2ab725a3456f630731511 | 85eabba70041fb324d40b2473c772a47b3b75d60 | refs/heads/master | 2021-01-13T05:23:48.566132 | 2017-04-22T21:43:25 | 2017-04-22T21:43:25 | 81,393,265 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,638 | py |
# coding: utf-8
# In[2]:
#Import packages
import os
import pandas as pd
# In[3]:
# get current working directory
direct = os.getcwd()
# read csv file from location
df = pd.read_csv(direct+"/"+"Assignment 3/vehicle_collisions.csv", usecols=[0,3,19,20,21,22,23])
df.head()
# In[5]:
location = df[['UNIQUE KEY','BOROUGH']]
vehicle = df[['VEHICLE 1 TYPE','VEHICLE 2 TYPE','VEHICLE 3 TYPE','VEHICLE 4 TYPE','VEHICLE 5 TYPE']]
df_type = vehicle.notnull()
df_type = df_type.applymap(lambda x:1 if x else 0)
df_type = pd.concat([df_location, df_type], axis=1)
df_type.head()
# In[7]:
result = df_type.groupby(df_type['BOROUGH']).sum()
# In[13]:
columns = ['Borough', 'One_Vehicle_Involved', 'Two_Vehicle_Involved', 'Three_Vehicle_Involved', 'More_Vehicle_Involved']
finalResult = pd.DataFrame({'Borough' : result.index, 'One_Vehicle_Involved' : result['VEHICLE 1 TYPE']-result['VEHICLE 2 TYPE'],
'Two_Vehicle_Involved' : result['VEHICLE 2 TYPE']-result['VEHICLE 3 TYPE'], 'Three_Vehicle_Involved' : result['VEHICLE 3 TYPE']-result['VEHICLE 4 TYPE'],
'More_Vehicle_Involved' : result['VEHICLE 4 TYPE'] })
finalResult[columns].head()
# In[14]:
#function to check is directory exists
def CheckDir(path):
directory = os.path.dirname(path) # defining directory path
if not os.path.exists(directory): # checking if directory already exists
os.makedirs(directory) # making a directory
Path =direct+'\Q1_Part_2.csv'
CheckDir(resultsPath)
# Saving our dataFrame to csv file.
finalResult[columns].to_csv(Path, index=False, encoding='utf-8')
# In[ ]:
| [
"shivamgoel@Shivams-MacBook-Pro-2.local"
] | shivamgoel@Shivams-MacBook-Pro-2.local |
7d56c98a3a6883fcac6d9407d1c20e212bd66daf | e28d8813366e0dc35c03f2bd3757c51b198d0cd6 | /Chapter 9/LizardFamily(1).py | b03eb0dcacc157eaaa799c81255899dbe81d9d6a | [] | no_license | wrobelcarter1/CS-126 | b3ae2abcc1b6c84b5f21f391afd6085e3c293c69 | 3664c03327dd9e67d4680ec95f198ee850ee35ab | refs/heads/master | 2020-05-02T11:51:11.794644 | 2019-03-27T07:46:34 | 2019-03-27T07:46:34 | 177,942,105 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,430 | py | '''
(1) Design an object of your choice. Start by using UML and planning the functionality of each method. Initialization of an object must require at least one parameter. You must be able to print your object in a meaningful way and you should define what it means for two objects to be equal. Additionally, your object must do one trick (e.g., generate a random number).
(2) Implement a Class in Python for your newly designed object.
(3) Create three objects: two that are equivalent and one that is not. Show this is the case.
'''
import random
class Lizard:
'''
Lizards can change color.
'''
# class member variable
color_list = ['red', 'orange', 'yellow', 'green', 'blue', 'violet']
#initlaize lizard witha name and color
def __init__(self, p_name, p_color):
self._name = p_name
self._color = p_color
#print(p_name)
# returns the name of the Lizard
def get_name(self):
# if you try access p_name here,
# you will get an error.
#print(p_name)
return self._name
# updates the names of the lizard
def set_name(self, new_name):
if new_name[0].upper() =='L':
self._name = new_name
else:
print("New lizard names must start with L.")
# lizards can change color
# uses class member variables to ensure all lizard have same options
def do_trick(self):
self._color = Lizard.color_list[random.randint(0,5)]
def __str__(self):
result = "Lizard's name is: " + self._name
result += " and its color is: " + self._color + "\n"
# result = 1
return result
def __eq__(self, other):
# two lizards are equal if they are same color
if self._color == other._color:
return True
else:
return False
class LizardFamily:
'''
A lizard family is made up of multiple Lizards.
'''
def __init__(self, size):
self._list_of_lizards = []
for i in range(size):
lizard = self._create_lizard()
self._list_of_lizards.append(lizard)
#self._list_of_lizards.append(self._create_lizard())
# helper methods to create lizard for a given size family
# should only be called from within the LizardFamily class
def _create_lizard(self):
name = input("Enter lizards name: ")
color = input("Enter lizards color: ")
new_lizard = Lizard(name,color)
return new_lizard
def change_colors(self, which_lizard):
self._list_of_lizards[which_lizard].do_trick()
# can you make all lizards changes colors
#for lizard in self._list_of_lizards:
# lizard.do_trick()
def __str__(self):
print("This Lizard family contains...")
result = ""
for lizard in self._list_of_lizards:
result += str(lizard)
return result
# using the Lizard class directly
lenny = Lizard("Leonard", "red")
print(lenny.get_name())
print(lenny)
jenny = Lizard("Jennifer", "green")
lizzy = Lizard("Elizabeth", "red")
print(lenny == lizzy) #
print(lenny == jenny) #
print("Before trick -->", lizzy)
lizzy.do_trick()
print("After trick -->", lizzy)
# using the Lizard Family class, which creates Lizard objects
lazy_lizards = LizardFamily(2)
lazy_lizards.change_colors(1)
print(lazy_lizards)
| [
"noreply@github.com"
] | wrobelcarter1.noreply@github.com |
0cb00b6ac4856750b2b2f64b6022d584a05a725e | a6a06fb05dd8dee0dba93b100ae936f33c0e06b9 | /bin2/grabcut_singleobj_bilinear_test.py | 5d4a1a255c71fe3ca0bd0aa9f0c9083651dbbc8a | [] | no_license | zpahuja/TrackingFromColorization | 879bcdfdfdf965f7364335deef0f72e8dc9a2d2c | d84dcc1548b63d827b0e367eb714e139efd9cf97 | refs/heads/master | 2020-05-04T14:35:45.364312 | 2020-03-10T20:45:23 | 2020-03-10T20:45:23 | 179,203,524 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 12,216 | py | # pylint: disable=I1101
import os
import sys
import time
import copy
import cv2
import numpy as np
import tensorflow as tf
import tensorpack.dataflow as df
from sklearn.cluster import KMeans
from PIL import Image
import mean_field_inference as mfi
from grabcut import grabcut
base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(base_dir)
palette_path = '/home/nfs/zpahuja2/tracking_from_colorization/eval/davisvideochallenge/davis-2017/data/palette.txt'
from tracking_via_colorization.utils.image_process import ImageProcess
from tracking_via_colorization.networks.resnet_colorizer import ResNetColorizer
from tracking_via_colorization.networks.colorizer import Colorizer
from tracking_via_colorization.feeder.dataset import Kinetics, Davis
from tracking_via_colorization.config import Config
from tracking_via_colorization.utils.devices import Devices
color_palette = np.loadtxt(palette_path, dtype=np.uint8).reshape(-1, 3)
palette = color_palette.ravel()
num_segments = {'bike-packing': 2, 'blackswan': 1, 'bmx-trees': 2, 'breakdance': 1, 'camel': 1, 'car-roundabout': 1, 'car-shadow': 1, 'cows': 1, 'dance-twirl': 1, 'dog': 1, 'dogs-jump': 3, 'drift-chicane': 1, 'drift-straight': 1, 'goat': 1,
'gold-fish': 4, 'horsejump-high': 2, 'india': 3, 'judo': 2, 'kite-surf': 2, 'lab-coat': 5, 'libby': 1, 'loading': 3, 'mbike-trick': 2, 'motocross-jump': 2, 'paragliding-launch': 2, 'parkour': 1, 'pigs': 3, 'scooter-black': 2, 'shooting': 2, 'soapbox': 2}
def write_image(image, dirname, frame):
im = Image.fromarray(image)
im.putpalette(palette)
im.save('%s/%05d.png' % (dirname, frame), format='PNG')
def write_kmeans_image(image, mask, dirname, name, frame):
h, w = image.shape[:2]
segments = np.where(mask != 0)
masked_pred = image[segments]
kmeans = KMeans(
n_clusters=num_segments[name], random_state=0).fit(masked_pred)
indexed_prediction = np.zeros((h, w), dtype=np.uint8)
cluster_labels = kmeans.labels_
for idx, label in zip(np.stack(segments, axis=1), cluster_labels):
i, j = idx
indexed_prediction[i, j] = np.uint8(label + 1)
write_image(indexed_prediction, dirname, frame)
def dataflow(name='davis', scale=1, split='val'):
if name == 'davis':
ds = Davis('/data/zubin/videos/davis', name=split,
num_frames=1, shuffle=False)
elif name == 'kinetics':
ds = Kinetics('/data/public/rw/datasets/videos/kinetics',
num_frames=1, skips=[0], shuffle=False)
else:
raise Exception('not support dataset %s' % name)
if name != 'davis':
ds = df.MapData(ds, lambda dp: [dp[0], dp[1], dp[1]])
ds = df.MapData(ds, lambda dp: [
dp[0], # index
dp[1], # original
dp[2], # mask
dp[3], # name
])
feature_size = int(256 * scale)
size = (feature_size, feature_size)
ds = df.MapDataComponent(ds, ImageProcess.resize(
small_axis=feature_size), index=1)
ds = df.MapDataComponent(
ds, lambda images: cv2.resize(images[0], size), index=2)
ds = df.MapData(ds, lambda dp: [
dp[0], # index
dp[1][0], # original small axis 256 x scale
cv2.cvtColor(cv2.resize(dp[1][0], size), cv2.COLOR_BGR2GRAY).reshape(
(size[0], size[1], 1)), # gray (256xscale)x(256xscale)x1
dp[2], # annotated mask 256xscale x 256xscale
dp[3], # name
])
ds = df.MultiProcessPrefetchData(ds, nr_prefetch=32, nr_proc=1)
return ds
def main(args):
Config(args.config)
device_info = Devices.get_devices(gpu_ids=args.gpus)
tf.logging.info('\nargs: %s\nconfig: %s\ndevice info: %s',
args, Config.get_instance(), device_info)
scale = args.scale
ds = dataflow(args.name, scale, args.split)
ds.reset_state()
cmap_size = int(args.cmap * scale)
feature_size = int(256 * scale)
num_inputs = args.num_reference + 1
placeholders = {
'features': tf.placeholder(tf.float32, (None, num_inputs, feature_size, feature_size, 1), 'features'),
'labels': tf.placeholder(tf.int64, (None, num_inputs, cmap_size, cmap_size, 1), 'labels'),
}
hparams = Config.get_instance()['hparams']
hparams['optimizer'] = tf.train.AdamOptimizer()
hparams = tf.contrib.training.HParams(**hparams)
estimator_spec = Colorizer.get('resnet', ResNetColorizer, num_reference=args.num_reference, predict_direction=args.direction)(
features=placeholders['features'],
labels=placeholders['labels'],
mode=tf.estimator.ModeKeys.PREDICT,
params=hparams
)
session = tf.Session()
saver = tf.train.Saver(tf.global_variables())
saver.restore(session, args.checkpoint)
dummy_labels = np.zeros(
(1, num_inputs, cmap_size, cmap_size, 1), dtype=np.int64)
video_index = -1
start_time = time.time()
num_images = 0
output_dir = '%s' % (args.output)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
for frame, image, gray, color, name in ds.get_data():
curr = {'image': image, 'gray': gray, 'color': color}
num_images += 1
if frame == 0:
if video_index != -1:
tf.logging.info('avg elapsed time per image: %.3fsec',
(time.time() - start_time) / num_images)
start_time = time.time()
num_images = 0
video_index += 1
dummy_features = [np.zeros(
(feature_size, feature_size, 1), dtype=np.float32) for _ in range(num_inputs)]
dummy_references = [np.zeros(
(feature_size, feature_size, 3), dtype=np.uint8) for _ in range(args.num_reference)]
dummy_features = dummy_features[1:] + [curr['gray']]
tf.logging.info('video name: %s, video index: %04d',
name, video_index)
if frame <= args.num_reference:
dummy_features = dummy_features[1:] + [curr['gray']]
dummy_references = dummy_references[1:] + [curr['color']]
features = np.expand_dims(
np.stack(dummy_features[1:] + [curr['gray']], axis=0), axis=0)
predictions = session.run(estimator_spec.predictions, feed_dict={
placeholders['features']: features,
placeholders['labels']: dummy_labels,
})
# find mapping from similarity_matrix to frame pixel
matrix_size = cmap_size * cmap_size
indices = np.argmax(predictions['similarity'], axis=-1).reshape((-1,))
mapping = np.zeros((matrix_size, 2))
for i, index in enumerate(indices):
f = (index // (matrix_size)) % args.num_reference
y = index // cmap_size
x = index % cmap_size
mapping[i, :] = [x, (args.num_reference - f - 1) * cmap_size + y]
mapping = np.array(mapping, dtype=np.float32).reshape(
(cmap_size, cmap_size, 2))
height, width = mapping.shape[:2]
reference_colors = np.concatenate(dummy_references, axis=0)
reference_colors = cv2.resize(
reference_colors, (width, height * args.num_reference))
predicted = cv2.remap(reference_colors, mapping,
None, cv2.INTER_LINEAR)
# perform grayscale mfi
grayscale_predicted = cv2.cvtColor(predicted, cv2.COLOR_BGR2GRAY)
_, mask = cv2.threshold(grayscale_predicted, 10,
255, cv2.THRESH_BINARY)
mask_shape = mask.shape
mask_arr = np.asarray(mask).astype(int)
mask_arr = np.where(mask_arr < 128, 0, 1)
denoised_mask_arr = mfi.denoise_image(mask_arr, theta=args.theta)
mask[denoised_mask_arr == 0] = 0
mask[denoised_mask_arr == 1] = 1
height, width = image.shape[:2]
mfi_predicted = cv2.bitwise_and(predicted, predicted, mask=mask)
mfi_mask = cv2.resize(mask * 255, (width, height))
# binarized
_, mfi_mask = cv2.threshold(mfi_mask, 60, 255, cv2.THRESH_BINARY)
mfi_mask[mfi_mask == 255] = 1
# perform grabcut
grabcut_mask = grabcut(image, np.copy(mfi_mask)) # need binary mask
predicted = cv2.resize(predicted, (width, height))
mfi_predicted = cv2.resize(mfi_predicted, (width, height))
if args.name == 'davis':
_, premfi_mask = cv2.threshold(cv2.cvtColor(
predicted, cv2.COLOR_BGR2GRAY), 10, 255, cv2.THRESH_BINARY)
mask_inv = cv2.bitwise_not(premfi_mask)
predicted_image = cv2.add(cv2.bitwise_and(
image, image, mask=mask_inv), predicted)
predicted_image = cv2.addWeighted(image, 0.3, predicted_image, 0.7, 0)
mfi_mask_inv = cv2.bitwise_not(mfi_mask)
mfi_predicted_image = cv2.add(cv2.bitwise_and(
image, image, mask=mfi_mask_inv), mfi_predicted)
mfi_predicted_image = cv2.addWeighted(
image, 0.3, mfi_predicted_image, 0.7, 0)
# grabcut
grabcut_mask_inv = cv2.bitwise_not(grabcut_mask)
grabcut_predicted = cv2.bitwise_and(
predicted, predicted, mask=grabcut_mask)
grabcut_predicted_image = cv2.add(cv2.bitwise_and(
image, image, mask=grabcut_mask_inv), grabcut_predicted)
grabcut_predicted_image = cv2.addWeighted(
image, 0.3, grabcut_predicted_image, 0.7, 0)
stacked = np.concatenate(
[image, predicted_image, mfi_predicted_image, grabcut_predicted_image], axis=1)
# (stacked, premfi_mask, predicted, mfi_mask, mfi_predicted, grabcut_mask, grabcut_predicted)
stacked_dir = os.path.join(output_dir, 'stacked', name)
premfi_mask_dir = os.path.join(output_dir, 'premfi_mask', name)
premfi_predicted_dir = os.path.join(output_dir, 'premfi_predicted', name)
mfi_mask_dir = os.path.join(output_dir, 'mfi_mask', name)
mfi_predicted_dir = os.path.join(output_dir, 'mfi_predicted', name)
grabcut_mask_dir = os.path.join(output_dir, 'grabcut_mask', name)
grabcut_predicted_dir = os.path.join(output_dir, 'grabcut_predicted', name)
if not os.path.exists(stacked_dir):
os.makedirs(stacked_dir)
os.makedirs(premfi_mask_dir)
os.makedirs(premfi_predicted_dir)
os.makedirs(mfi_mask_dir)
os.makedirs(mfi_predicted_dir)
os.makedirs(grabcut_mask_dir)
os.makedirs(grabcut_predicted_dir)
cv2.imwrite('%s/%05d.jpg' % (stacked_dir, frame), stacked)
write_image(premfi_mask, premfi_mask_dir, frame)
write_image(mfi_mask, mfi_mask_dir, frame)
write_image(grabcut_mask, grabcut_mask_dir, frame)
write_kmeans_image(predicted, premfi_mask, premfi_predicted_dir, name, frame)
write_kmeans_image(mfi_predicted, mfi_mask, mfi_predicted_dir, name, frame)
write_kmeans_image(grabcut_predicted, grabcut_mask, grabcut_predicted_dir, name, frame)
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--gpus', type=int, nargs='*', default=[0, 1, 2, 3])
parser.add_argument('--checkpoint', type=str,
default='models/colorizer2/model.ckpt-64000')
parser.add_argument('-c', '--config', type=str, default=None)
parser.add_argument('--cmap', type=int, default=32)
parser.add_argument('-s', '--scale', type=float, default=1)
parser.add_argument('--split', type=str, default='val')
parser.add_argument('-n', '--num-reference', type=int, default=3)
parser.add_argument('-t', '--theta', type=float, default=0.5)
parser.add_argument('-d', '--direction', type=str, default='backward',
help='[forward|backward] backward is default')
parser.add_argument('--name', type=str, default='davis')
parser.add_argument('-o', '--output', type=str, default='results')
parsed_args = parser.parse_args()
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '5'
tf.logging.set_verbosity(tf.logging.INFO)
main(parsed_args)
| [
"zpahuja2@illinois.edu"
] | zpahuja2@illinois.edu |
873b10f66c3979766835a58626e03769970e9bd7 | f82726a396b864360d4ce8adee288cbcdf722ada | /src/starkware/cairo/lang/instances.py | 7094e155350598778a205462557a4079f979d4c2 | [] | no_license | Tachyonic-hash/cairo-lang | 62efd36f50c421ea6e7f97b2c03f288d640b1448 | 95e5c4c55098d8ad3d963151a4c24b53b6709b9a | refs/heads/master | 2023-04-12T07:42:15.083281 | 2021-03-31T09:54:09 | 2021-03-31T10:53:37 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,601 | py | import dataclasses
from dataclasses import field
from typing import Any, Dict
from starkware.cairo.lang.builtins.checkpoints.instance_def import (
CELLS_PER_SAMPLE, CheckpointsInstanceDef)
from starkware.cairo.lang.builtins.hash.instance_def import CELLS_PER_HASH, PedersenInstanceDef
from starkware.cairo.lang.builtins.range_check.instance_def import (
CELLS_PER_RANGE_CHECK, RangeCheckInstanceDef)
from starkware.cairo.lang.builtins.signature.instance_def import (
CELLS_PER_SIGNATURE, EcdsaInstanceDef)
@dataclasses.dataclass
class CairoLayout:
layout_name: str = ''
cpu_component_step: int = 1
# Range check units.
rc_units: int = 16
builtins: Dict[str, Any] = field(default_factory=lambda: {})
# The ratio between the number of public memory cells and the total number of memory cells.
public_memory_fraction: int = 4
memory_units_per_step: int = 8
CELLS_PER_BUILTIN = dict(
pedersen=CELLS_PER_HASH,
range_check=CELLS_PER_RANGE_CHECK,
ecdsa=CELLS_PER_SIGNATURE,
checkpoints=CELLS_PER_SAMPLE,
)
plain_instance = CairoLayout(
layout_name='plain',
)
small_instance = CairoLayout(
layout_name='small',
rc_units=16,
builtins=dict(
output=True,
pedersen=PedersenInstanceDef(
ratio=8,
repetitions=4,
element_height=256,
element_bits=252,
n_inputs=2,
hash_limit=2**251 + 17 * 2**192 + 1,
),
range_check=RangeCheckInstanceDef(
ratio=8,
n_parts=8,
),
ecdsa=EcdsaInstanceDef(
ratio=512,
repetitions=1,
height=256,
n_hash_bits=251,
),
checkpoints=CheckpointsInstanceDef(
sample_ratio=16,
),
)
)
dex_instance = CairoLayout(
layout_name='dex',
rc_units=4,
builtins=dict(
output=True,
pedersen=PedersenInstanceDef(
ratio=8,
repetitions=4,
element_height=256,
element_bits=252,
n_inputs=2,
hash_limit=2**251 + 17 * 2**192 + 1,
),
range_check=RangeCheckInstanceDef(
ratio=8,
n_parts=8,
),
ecdsa=EcdsaInstanceDef(
ratio=512,
repetitions=1,
height=256,
n_hash_bits=251,
),
checkpoints=CheckpointsInstanceDef(
sample_ratio=16,
),
)
)
LAYOUTS: Dict[str, CairoLayout] = {
'plain': plain_instance,
'small': small_instance,
'dex': dex_instance,
}
| [
"lior@starkware.co"
] | lior@starkware.co |
2d466148626bc06813c233670905a712c4cace65 | 6568c06325072d013a96e59e48af0cde30b56e36 | /django_app/main/urls.py | 9d55b69cc13583cf532716652408823ef8c43262 | [] | no_license | byunghyunpark/dgdr-api | 24e1b521c3d37e26afa667bf84b67c5fcbad7bd5 | 829220a893340f2b91ae1b49d674dbc043098d66 | refs/heads/master | 2021-01-01T19:58:00.326553 | 2017-08-17T04:08:46 | 2017-08-17T04:08:46 | 98,728,005 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 402 | py | from django.conf.urls import url
from main.views import TenantFAQView, PartnerFAQView, NewsView, TopBannerView
urlpatterns = [
url(r'^faq/tenant/$', TenantFAQView.as_view(), name='tenant_faq'),
url(r'^faq/partner/$', PartnerFAQView.as_view(), name='partner_faq'),
url(r'^news/$', NewsView.as_view(), name='news'),
url(r'^top-banner/$', TopBannerView.as_view(), name='top_banner'),
]
| [
"openmind8735@gmail.com"
] | openmind8735@gmail.com |
015523de27450f57636ed364496c5071fd5c8fe7 | 3ed34d16700ae9a7aaf20a6b94283431f590c02f | /reinforcement/analysis.py | b67b80b342a601ceedc2aad6eaa120fe2c329041 | [] | no_license | brighteyedathene/2pac | 0db277936b469a8c12f70839887daa90a5b8457d | 93b8133376e3aa60ce360f896cc2441c6056470e | refs/heads/master | 2021-08-20T02:10:53.463463 | 2017-11-28T00:00:13 | 2017-11-28T00:00:13 | 107,329,079 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,311 | py | # analysis.py
# -----------
# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
#
# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
# The core projects and autograders were primarily created by John DeNero
# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
# Student side autograding was added by Brad Miller, Nick Hay, and
# Pieter Abbeel (pabbeel@cs.berkeley.edu).
######################
# ANALYSIS QUESTIONS #
######################
# Set the given parameters to obtain the specified policies through
# value iteration.
def question2():
answerDiscount = 0.1
answerNoise = 0.01
return answerDiscount, answerNoise
def question3a():
answerDiscount = 0.5
answerNoise = 0.01
answerLivingReward = -1
return answerDiscount, answerNoise, answerLivingReward
# If not possible, return 'NOT POSSIBLE'
def question3b():
answerDiscount = 0.5
answerNoise = 0.2
answerLivingReward = -1
return answerDiscount, answerNoise, answerLivingReward
# If not possible, return 'NOT POSSIBLE'
def question3c():
answerDiscount = 0.9
answerNoise = 0.01
answerLivingReward = 0.0
return answerDiscount, answerNoise, answerLivingReward
# If not possible, return 'NOT POSSIBLE'
def question3d():
answerDiscount = 0.9
answerNoise = 0.2
answerLivingReward = 0.0
return answerDiscount, answerNoise, answerLivingReward
# If not possible, return 'NOT POSSIBLE'
def question3e():
answerDiscount = 0.0
answerNoise = 0.0
answerLivingReward = 1
return answerDiscount, answerNoise, answerLivingReward
# If not possible, return 'NOT POSSIBLE'
def question6():
answerEpsilon = None
answerLearningRate = None
return 'NOT POSSIBLE'
# If not possible, return 'NOT POSSIBLE'
if __name__ == '__main__':
print 'Answers to analysis questions:'
import analysis
for q in [q for q in dir(analysis) if q.startswith('question')]:
response = getattr(analysis, q)()
print ' Question %s:\t%s' % (q, str(response))
| [
"brighteyedathene@gmail.com"
] | brighteyedathene@gmail.com |
d024aabd66ac65b89236463be89d34441302ee30 | f13020d150c001ad541e423df5c087c9e4cf57a2 | /src/options/tests/PayoffCalculatorTest.py | 00c975031467714337fb0a25682da4598d283ca7 | [] | no_license | ByteAcademyGrizzlies/unit-testing | 6b18caec43ea44680bc06f2dfb0d533114adb059 | 20f04717bb4aa9aeed56d972f1043d30cdb514bf | refs/heads/master | 2021-01-20T15:13:05.872489 | 2017-05-10T10:59:19 | 2017-05-10T10:59:19 | 90,736,772 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 798 | py | from unittest import TestCase, skip
from unittest.mock import MagicMock, patch, call
from calculators.longputstrategy import LongPutStrategy
from model.optionleg import OptionLeg
from payoffcalculator import PayOffCalculator
class PayOffCalculatorTest(TestCase):
def test_register_strategy(self):
calc = PayOffCalculator()
strategy = LongPutStrategy()
calc.register_strategy(strategy)
self.assertEqual(calc.strategy_map[strategy.STRATEGY_NAME],
strategy,
"The strategy must be registered in the strategy map")
@patch("payoffcalculator.LongPutStrategy", autospec=True)
@patch("payoffcalculator.LongCallStrategy", autospec=True)
def test_calculate(self, longCallMock, longPutMock):
pass
| [
"nikhilpanchal@gmail.com"
] | nikhilpanchal@gmail.com |
a90d1a7521f99528a457f55b6d0a2f55034334d9 | 06e6a1bf665efbca63224dc92bc1ca3df6b11252 | /lesson9/myrequest.py | d2850f54246c344cb70428c6a6ecdf499eac381a | [] | no_license | elemanjan/python_basics | 4522295dfea3e8b652f98679ec19a5b2084a1a5f | 4254d28bd89d4725ad53e1f40f1ea69a72f381e9 | refs/heads/master | 2023-03-29T07:15:45.914776 | 2021-03-30T18:59:13 | 2021-03-30T18:59:13 | 310,350,092 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 88 | py | from requests import get
response = get("https://www.google.kg/")
print(response.text)
| [
"namele93@gmail.com"
] | namele93@gmail.com |
9d6d2a2146c3449dc30329ab4ab3bbe9dff7026e | df51500e73bd8eaf5975f16fb3ef1a677539bd05 | /AoC_day3part1.py | f21485a46c0ede9b6fd3f9b73bbe9ab19cdbba12 | [] | no_license | rag-lub/AdventOfCode | 7348e1a6a6ab0644b0334412d07befe9e34722d4 | d56978f83daaaccf073836482160444742f2f48b | refs/heads/master | 2022-05-25T09:39:06.017719 | 2019-12-20T03:39:32 | 2019-12-20T03:39:32 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,136 | py | #wire1=['R7','D3','R8','U8','L1','D4','R7','U7','L7']
#wire2=['U6','R6','U5','R4','D7','R5','D5','R3']
str1='R994,U598,L555,D997,R997,U529,L251,U533,R640,U120,L813,U927,L908,U214,L276,U306,L679,U187,R156,D654,L866,D520,R299,U424,R683,U49,R965,U531,R303,D4,L210,U425,R99,D892,R564,D671,L294,D908,L89,U855,R275,U790,R214,D588,L754,D873,R297,D97,R979,U850,L953,D281,L580,D254,L747,U115,L996,U641,R976,U585,L383,U498,L112,U329,R650,U772,L952,U325,L861,U831,R71,D853,R696,D812,R389,U456,L710,D116,R789,D829,L57,D940,R908,U569,R617,D832,L492,D397,R152,U898,L960,D806,L867,U928,L617,D281,L516,D214,R426,U530,R694,U774,L752,U215,L930,U305,R463,U774,R234,U786,R425,U470,R90,D383,R692,D626,L160,D588,L141,D351,R574,D237,L869,D499,R873,U856,R148,D919,L582,D804,L413,U201,L247,U907,L828,D279,L28,D950,L587,U290,R636,U344,L591,U118,L614,U203,R381,U634,L301,D197,R594,D373,L459,U504,L703,U852,L672,U613,R816,D712,R813,U97,R824,D690,L556,D308,L568,D924,L384,U540,R745,D679,R705,D808,L346,U927,R145,U751,L769,D152,L648,D553,L738,U456,R864,U486,R894,D923,R76,U211,L78,U145,R977,U297,R93,U200,L71,U665,L392,D309,L399,D594,R118,U552,L328,U317,R369,D109,L673,D306,R441,U836,L305,D59,L870,U648,L817,D381,R676,U711,R115,U344,L815,U286,R194,U526,R844,U106,L547,D312,L116,U783,R786,D390,L115,D483,R691,U802,R569,U13,R854,D90,R22,D819,L440,D13,R438,D640,L952,D394,R984,D825,R1,D554,R349,U746,L816,U301,L397,D85,R437,D746,L698,D75,L964,U155,L268,U612,R838,D338,L188,U38,R830,U538,L245,D885,R194,D989,R8,D69,L268,D677,R163,U784,L308,U605,L737,U919,R117,U449,R698,U547,L134,D860,L234,U923,R495,D55,R954,D531,L212'
str2='L1005,D937,L260,D848,R640,U358,R931,U495,R225,U344,R595,U754,L410,D5,R52,D852,L839,D509,R755,D983,R160,U522,R795,D465,R590,U558,R552,U332,R330,U752,R860,D503,L456,U254,R878,D164,R991,U569,R44,U112,L258,U168,L552,U68,R414,U184,R458,D58,R319,U168,R501,D349,R204,D586,R241,U575,L981,D819,L171,D811,L960,U495,R192,D725,R718,D346,R399,D692,L117,D215,L390,U364,L700,D207,R372,U767,L738,D844,L759,D211,R287,U964,R328,D800,R823,U104,L524,D68,R714,D633,R565,D373,R883,U327,R222,D318,L58,D451,R555,D687,R807,U638,L717,U298,R849,D489,L159,D692,L136,U242,R884,U202,R419,U41,L980,U483,R966,D513,L870,D306,R171,D585,R71,D320,R914,U991,R706,U440,R542,D219,L969,U9,R481,U164,R919,U17,L750,U775,R173,U515,L191,D548,L515,U54,L132,U56,R203,U544,L796,D508,L321,D517,L358,U12,L892,D472,L378,U121,L974,U36,R56,D758,L680,D17,L369,D72,L926,D466,L866,U850,R300,D597,L848,U17,L890,D739,L275,U560,L640,U602,R238,U919,R636,D188,R910,D992,L13,U241,R77,U857,R453,U883,L881,D267,R28,U928,R735,U731,L701,D795,R371,U652,R416,D129,R142,D30,R442,U513,R827,U455,L429,D804,R966,D565,R326,U398,R621,U324,L684,D235,L467,D575,L200,D442,R320,D550,R278,U929,R555,U537,L416,U98,R991,D271,L764,U841,L273,D782,R356,D447,R340,U413,R543,U260,L365,D529,R721,U542,L648,U366,R494,U243,L872,U201,L440,U232,R171,D608,R282,U484,R81,D320,R274,D760,L250,U749,L132,D162,L340,D308,L149,D5,L312,U547,R686,D684,R133,D876,L531,U572,R62,D142,L218,U703,L884,U64,L889,U887,R228,U534,R624,D524,R522,D452,L550,U959,R981,U139,R35,U98,R212'
wire1=list(str1.split(','))
wire2=list(str2.split(','))
#wire1=['R98','U47','R26','D63','R33','U87','L62','D20','R33','U53','R51']
#wire2=['U98','R91','D20','R16','D67','R40','U7','R15','U6','R7']
def path(lst):
line = [(0,0)]
for v in lst:
dir = v[0]
mag = int(v[1:])
for i in range(mag):
point = line[-1]
if dir == 'R':
point = (point[0]+1,point[1])
elif dir == 'U':
point = (point[0],point[1]+1)
elif dir == 'L':
point = (point[0]-1,point[1])
elif dir == 'D':
point = (point[0],point[1]-1)
else:
print('Unexpected Direction')
break
line.append(point)
print(line)
return set(line)
def pointsum(point):
return abs(point[0])+abs(point[1])
wire_set1 = path(wire1)
wire_set2 = path(wire2)
x_set = wire_set1 & wire_set2
print(x_set)
manhatans = []
for point in x_set:
manhatans.append(pointsum(point))
manhatans.remove(0)
print(min(manhatans)) | [
"noreply@github.com"
] | rag-lub.noreply@github.com |
7bbe214387e5f7c40c8ab9da05684bf034fbadf2 | ec78dc43933c610a1b8438c0ec33f9364c3fb000 | /superlist/settings.py | 946460d504e4c07f26e328f3f4662df2162b7dc7 | [] | no_license | Bowser-ai/ttd-django | 49b8ca95999b5bd9c4a8a7f41e34e633fe5ccb0b | 765b3b7eadafef206088f958fead7772e4c864fa | refs/heads/master | 2021-01-09T13:56:36.443560 | 2020-04-14T20:53:33 | 2020-04-14T20:53:33 | 242,327,131 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,494 | py | """
Django settings for superlist project.
Generated by 'django-admin startproject' using Django 1.11.28.
For more information on this file, see
https://docs.djangoproject.com/en/1.11/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.11/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = ')s8v45fhdf3^fhb6=dort7y7*4ew1zfjg-z=#9-vgm1!pny+cz'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
#'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'list',
'accounts'
]
AUTH_USER_MODEL = 'accounts.User'
AUTHENTICATION_BACKENDS = [
'accounts.authentication.PasswordlessAuthenticationBackend'
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'superlist.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'superlist.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
STATIC_ROOT = os.path.join(BASE_DIR, 'static')
EMAIL_HOST = 'smtp.gmail.com'
EMAIL_HOST_USER = 'martijnvermeulen1@gmail.com'
EMAIL_HOST_PASSWORD = os.environ.get('EMAIL_PASSWORD')
EMAIL_PORT = 587
EMAIL_USE_TLS = True
| [
"martijnvermeulen1@gmail.com"
] | martijnvermeulen1@gmail.com |
aa6e68a5ea3e735216cc14043fdec20566fd4969 | 412a5f96278c9326a486bcbc3c8a210e55f9bc5f | /percolation.py | 098f714205fd0ecbde4d931473d56caed180567e | [] | no_license | omnistegan/Algorithms_I_Assignments | 0b335e12ce815a3087b0849110eecc5e49c6c3c8 | dc0590eb939614b38d64f1cacd8107a2e767b7b0 | refs/heads/master | 2021-01-20T20:08:37.575788 | 2016-07-11T01:04:46 | 2016-07-11T01:04:46 | 63,026,359 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,429 | py | #!/usr/bin/env python
from quickunion03 import Union_Find
from random import randrange
from statistics import mean, stdev
class Perc_Grid():
def __init__(self, n):
# Init a grid size n squared with all spaces initially blocked
self.uf = Union_Find((n*n)+2)
# UF index -1 and -2 reserved for virtual percolation test points
for each in list(range(n)):
self.uf.union(-2, each)
for each in list(range(-2-n, -2)):
self.uf.union(-1, each)
self.size = n
self.grid = [[False for x in range(n)] for y in range(n)]
self.count = 0
def uf_index(self, x, y):
# Return UF index for our 2d x, y coords
return (y*self.size)+x
def open_random_blocked(self):
# Find a randomly selected blocked space and perform self.open() in it.
while True:
randx, randy = (randrange(self.size), randrange(self.size))
if not self.grid[randy][randx]:
self.open(randx, randy)
break
def open(self, x, y):
# Perform opening and unioning operations on a new space
self.grid[y][x] = True
self.count += 1
new_ufi = self.uf_index(x, y)
# Must union with neighbouring open spaces
neighbours = [(x-1, y), (x+1, y), (x, y-1), (x, y+1)]
# Filter out of range neighbours
neighbours = [space for space in neighbours if self.size not in space and -1 not in space]
nei_ufi = []
for each in neighbours:
if self.grid[each[1]][each[0]]:
nei_ufi.append(self.uf_index(*each))
for each in nei_ufi:
self.uf.union(new_ufi, each)
def percolates(self):
return self.uf.connected(-1, -2)
def show_me(self):
for each in pc.grid:
for item in each:
if item is False:
print('X', end='')
else:
print(' ', end='')
print()
def percent_filled(self):
return self.count/(self.size*self.size)
def perform_tests(grid_size, tests):
probabilities = []
for i in range(tests):
pc = Perc_Grid(grid_size)
while not pc.percolates():
pc.open_random_blocked()
probabilities.append(pc.percent_filled())
print('mean = ' + str(mean(probabilities)))
print('stddev = ' + str(stdev(probabilities))) | [
"gmbouvier@gmail.com"
] | gmbouvier@gmail.com |
33d65505e62415ec474373f835f060af9a83c2d8 | 7b12eb45c1ea76ad9c186b858b5dfebf2c5b862a | /.history/DEBER_20210904224213.py | 22245042ab40e7800c1484553318ca360a097082 | [
"MIT"
] | permissive | Alopezm5/PROYECTO-PARTE-1 | a1dce04009b24852c1c60e69bdf602ad3af0574b | bd7a8594edf08d41c6ca544cf6bac01ea4fcb684 | refs/heads/main | 2023-07-25T11:22:17.994770 | 2021-09-07T03:27:34 | 2021-09-07T03:27:34 | 403,670,226 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,323 | py | import os
class Empresa():
def __init__(self,nom="",ruc=0,dire="",tele=0,ciud="",tipEmpr=""):
self.nombre=nom
self.ruc=ruc
self.direccion=dire
self.telefono=tele
self.ciudad=ciud
self.tipoEmpresa=tipEmpr
def datosEmpresa(self):#3
self.nombre=input("Ingresar nombre de la empresa: ")
self.ruc=int(input("Ingresar ruc de la empresa: "))
self.direccion=input("Ingresar la direccion de la empresa: ")
self.telefono=int(input("Ingresar el numero de telefono de la empresa: "))
self.ciudad=input("Ingresar ciudad donde esta la empresa: ")
self.tipoEmpresa=input("Ingresar tipo de empresa publica o privada: ")
def mostrarEmpresa(self):
print("")
print("Datos de la Empresa")
print("La empresa de nombre {}\n De RUC #{} \n Está ubicada en {}\n Se puede comunicar al #{}\n Está empresa esta en la ciudad de {}\n Es una entidad {}".format(self.nombre,self.ruc,self.direccion, self.telefono,self.ciudad, self.tipoEmpresa))
class Empleado(Empresa):
def __init__(self,nom="",cedu=0,dire="",tele=0,email="",estado="",profe="",anti=0,com=0,fNomina="",fIngreso="",iess=0):
self.nombre=nom
self.cedula=cedu
self.direccion=dire
self.telefono=tele
self.correo=email
self.estadocivil=estado
self.profesion=profe
self.antiguedad=anti
self.comision=com
self.fechaNomina=fNomina
self.fechaIngreso=fIngreso
self.iess=iess
def empleado(self):
self.nombre=input("Ingresar nombre del empleado: ")
self.cedula=int(input("Ingresar numero de cedula del empleado: "))
self.direccion=input("Ingresar la direccion del empleado: ")
self.telefono=int(input("Ingresar numero de contacto del empleado: "))
self.correo=input("Ingresar correo personal del empleado: ")
self.iess=float(input("Ingresar valor del iees recordar que debe ser porcentuado Ejemplo si quiere decir 20% debe ingresar 0.20"))
self.fechaNomina=input("Ingresar fecha de nomida (formato año-mes-dia): ")
self.fechaIngreso=input("Ingresar fecha de ingreso (formato año-mes-dia): ")
self.antiguedad=float(input("Ingresar valor de antiguedad"))
self.comision=float(input("Ingresar calor de la comsion: "))
def empleadoObrero(self):
self.estadocivil=input("Ingresar estado civil del empleado: ")
def empleadoOficina(self):
self.profesion=input("Ingresar profesion del empleado: ")
# def mostrarempleado(self):
# print("El empleado: {} con # de C.I. {} \n Con direccion {}, y numero de contacto{}\n Y correo {}".format(self.nombre,self.cedula,self.direccion,self.telefono,self.correo))
class Departamento(Empleado):
def __init__(self,dep=""):
self.departamento=dep
def departa(self):
self.departamento=input("Ingresar el departamento al que pertenece el empleado: ")
def mostrarDeparta(self):
print("El empleado pertenece al departamento de: {}".format(self.departamento))
class Pagos(Empleado):
def __init__(self, desc=0,desper=0,valhora=0,hotraba=0,extra=0):
self.permisos=desper
self.valorhora=valhora
self.horastrabajadas=hotraba
self.valextra=extra
self.sueldo= suel
self.horasRecargo= hrecar
self.horasExtraordinarias=hextra
self.prestamo= pres
self.mesCuota= mcou
self.valor_hora= valho
self.sobretiempo=sobtiem
self.comEmpOficina = comofi
self.antiEmpObrero = antobre
self.iessEmpleado = iemple
self.cuotaPrestamo=cuopres
self.totdes = tot
self.liquidoRecibir = liquid
def pagoNormal(self):
self.sueldo=float(input("Ingresar sueldo del trabajador: $"))
self.prestamo=float(input("Ingresar monto del prestamo que ha generado el empleado: $"))
self.mesCuota=("Ingresar meses qa diferir el prestamo: ")
def pagoExtra(self):
self.horasRecargo=int(input("Ingresar horas de recargo: "))
self.horasExtraordinarias=int(input("Ingresar horas extraordinarias: "))
def calculoSueldo(self):
self.valor_hora=self.sueldo/240
self.sobretiempo= valor_hora * (horasRecargo*0.50+horasExtraordinarias*2)
self.comEmpOficina = self.comision*self.sueldo
self.antiEmpObrero = self.antiguedad*(FechaNomina - FechaIngreso)/365*self.sueldo
self.iessEmpleado = self.iess*(self.sueldo+self.sobretiempo)
self.cuotaPrestamo=self.prestamo/self.mesCuota
if eleccion==1:
self.toting = self.sueldo+self.sobretiempo+ self.comEmpOficina
elif eleccion==2:
self.toting = self.sueldo+self.sobretiempo+self.antiEmpObrero
self.totdes = iessEmpleado + prestamoEmpleado
self.liquidoRecibir = toting - totdes
def mostrarSueldo(self):
print("Arreglar")
emp=Empresa()
emp.datosEmpresa()
emple=Empleado()
emple.empleado()
eleccion=int(input("Va a ingresar un empleado tipo 1. Obreo o 2.Oficina: "))
emple.empleadoObrero()
emple.empleadoOficina()
pag=Pagos()
pag.pagoNormal()
pag.pagoExtra()
pag.calculoSueldo()
os.system ("cls")
emp.mostrarEmpresa()
print("")
emple.mostrarempleado()
print("")
| [
"85761855+Alopezm5@users.noreply.github.com"
] | 85761855+Alopezm5@users.noreply.github.com |
89b21af428d1d308b279efb03d30b5f58713a620 | 2f0c413962f96fe449ddcaf9363f1bdfd4f5e98d | /test/test_gossip.py | 8060199884d775bc93067661bb947acca582a832 | [
"MIT"
] | permissive | vijayanant/kunai | 1d922791dbad8c6132d790d7a58040c3f9ecbedc | 0dfe169731eaceb1bba66e12715b3968d2a3de20 | refs/heads/master | 2021-01-22T12:02:17.293478 | 2014-12-27T13:15:25 | 2014-12-27T13:15:25 | 28,539,772 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 481 | py | #!/usr/bin/env python
# Copyright (C) 2014:
# Gabes Jean, naparuba@gmail.com
import copy
import time
import threading
from kunai_test import *
from kunai.gossip import Gossip
from kunai.broadcast import Broadcaster
class TestGossip(KunaiTest):
def setUp(self):
self.gossip = Gossip({}, threading.RLock(), 'localhost', 6768, 'testing-kunai', 0, 'AAAA', ['linux', 'kv'], [])
def test_gossip(self):
pass
if __name__ == '__main__':
unittest.main()
| [
"naparuba@gmail.com"
] | naparuba@gmail.com |
4923dc156c32629be236e1d36d3fb280e5596a3f | f47fab6263c4ef79e434f891e9804feaf2823ec0 | /shenmeGUI/local_backends/threading_kernel.py | 74c0115e5cb02ad2ca508fb0adc1ad6adf261f09 | [
"MIT"
] | permissive | tigerjang/ShenMeGUI | 722aadef78439b12096bac3232d16398159a4b69 | 55f30a2525a946b7b40fb3f17538b1f4f18c9fcc | refs/heads/master | 2020-04-18T10:02:01.837359 | 2016-09-09T04:59:33 | 2016-09-09T04:59:33 | 66,994,569 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 859 | py | import threading
from Queue import Queue
# import time
from .sp_kernel import SPShell
class ThreadingKernel(SPShell):
def __init__(self):
SPShell.__init__(self)
self._run_request_queue = Queue()
self._thread = threading.Thread(target=self._main_loop)
def _main_loop(self):
rrq = self._run_request_queue
while True:
req_type, req_data = rrq.get(block=True)
if req_type == 'c':
self.run_script(req_data) # TODO
elif req_type == 'o':
obj, args, kwargs = req_data
obj(*args, **kwargs)
def start(self):
self._thread.start()
def run(self, _code):
self._run_request_queue.put(('c', _code))
def run_obj(self, obj, args, kwargs):
self._run_request_queue.put(('o', (obj, args, kwargs)))
| [
"tigerinara"
] | tigerinara |
d54bd5fe22db638f90020f56f76d3532ffacb945 | 3d2ed445d2598576e8f5e3dbc187e8d6d5738508 | /Quick_Sort.py | 042f0757bf855b6ac127a6f0699b75a856aefb2e | [] | no_license | Darkosoftware/Quick-Sort | d5c6130c458953cb587ef1e054a340f1b9ff4628 | b16c1aa9ac14f3e452bcea03b927650973c38570 | refs/heads/main | 2023-06-16T00:57:28.131472 | 2021-07-06T17:53:53 | 2021-07-06T17:53:53 | 383,553,156 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 590 | py | def quicksort(first):
if len(first) <= 1:
sorted_list = first
else:
pivot = first[0]
larger = []
smaller = []
equal = []
for item in first:
if item > pivot:
larger.append(item)
elif item < pivot:
smaller.append(item)
else:
equal.append(item)
sorted_list = quicksort(smaller) + equal + quicksort(larger)
return sorted_list
n = int(input("How many different numbers would you like to sort?: "))
sort_this_list = list(map(int,input("Enter the numbers here: ").strip().split()))[:n]
print(quicksort(sort_this_list))
input("Press enter to close.")
| [
"noreply@github.com"
] | Darkosoftware.noreply@github.com |
37d9893f4b20f60287f6a2e4658eb16c3fa5159a | 6ce52c7d9ec42712445b763bf3e8751929b5b926 | /utils/essentials.py | afb855b3d9e99ca81fddec36ebc3953c9da62080 | [] | no_license | abhishek8899/Relevance-Credibility-NLP | c5bcfeff9f341b96ee4789f4791c1e6c53172c62 | 900571d51fc4b6902fd9945e94a53d25493754df | refs/heads/master | 2022-02-24T06:56:46.322527 | 2019-08-30T17:11:19 | 2019-08-30T17:11:19 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,979 | py | import matplotlib # isort:skip
matplotlib.use('TkAgg') # isort:skip
import matplotlib.pyplot as pl # isort:skip
from dotenv import load_dotenv
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy.ext.declarative import declarative_base
import json
import logging
import numpy as np
import os
import pandas as pd
import seaborn as sns
import sys
import threading
import traceback
# with open('data/essentials/weightage.json') as f:
# weightage_data = json.load(f)
load_dotenv(dotenv_path='.env')
app = Flask(__name__, root_path=os.getcwd())
app.config['SQLALCHEMY_DATABASE_URI'] = os.environ.get('DB_URL')
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db = SQLAlchemy(app)
'''
To create our database based off our model, run the following commands
$ python
>>> from app import db
>>> db.create_all()
>>> exit()'''
Base = declarative_base()
# keywords used to check real_world_presence
hyperlinks_attributes = ['contact', 'email', 'help', 'sitemap']
apiList = {
'lastmod': ['getDate', '', '', 'Integer'],
'domain': ['getDomain', '', '', 'String(120)'],
'inlinks': [
'getInlinks',
'',
'',
'Integer',
],
'outlinks': [
'getOutlinks',
'',
'',
'Integer',
],
'hyperlinks': [
'getHyperlinks',
hyperlinks_attributes,
'',
'JSON',
],
'imgratio': ['getImgratio', '', '', 'FLOAT'],
'brokenlinks': ['getBrokenlinks', '', '', 'Integer'],
'cookie': ['getCookie', '', '', 'Boolean'],
'langcount': ['getLangcount', '', '', 'Integer'],
'misspelled': ['getMisspelled', '', '', 'Integer'],
# 'wot': ['getWot', '', 'JSON'],
'responsive': ['getResponsive', '', '', 'Boolean'],
'ads': ['getAds', '', 'Integer'],
'pageloadtime': ['getPageloadtime', '', '', 'Integer'],
'site': [
'',
'',
'',
'String(120)',
],
}
# A class to catch error and exceptions
class WebcredError(Exception):
"""An error happened during assessment of site.
"""
def __init__(self, message):
self.message = message
def __str__(self):
return repr(self.message)
class MyThread(threading.Thread):
# def __init__(
# self, Module='api', Method=None, Name=None, Url=None, Args=None
# ):
# pass
def __init__(self, func, Name, Url, Args=None):
threading.Thread.__init__(self)
self.func = func
self.name = Name
self.url = Url
self.args = Args
self.result = None
if Args and Args != '':
self.args = Args
def run(self):
try:
if self.args:
self.result = self.func(self.url, self.args)
else:
self.result = self.func(self.url)
except Exception:
# Get current system exception
ex_type, ex_value, ex_traceback = sys.exc_info()
# Extract unformatter stack traces as tuples
trace_back = traceback.extract_tb(ex_traceback)
# Format stacktrace
stack_trace = list()
for trace in trace_back:
stack_trace.append(
"File : %s , Line : %d, Func.Name : %s, Message : %s" %
(trace[0], trace[1], trace[2], trace[3])
)
# print("Exception type : %s " % ex_type.__name__)
try:
if not ex_value.message == 'Response 202':
logger.info('{}:{}'.format(ex_type.__name__, ex_value))
logger.info(stack_trace)
except:
pass
self.result = None
def getResult(self):
return self.result
# clear url if Urlattributes object
def freemem(self):
self.url.freemem()
class Database(object):
def __init__(self, database):
engine = db.engine
# check existence of table in database
if not engine.dialect.has_table(engine, database.__tablename__):
# db.create_all()
Base.metadata.create_all(engine, checkfirst=True)
logger.info('Created table {}'.format(database.__tablename__))
self.db = db
self.database = database
def filter(self, name, value):
# print ("---------------------------------------in filter---------------------------------------")
# print ("name ",name," database ",self.database)
# print ()
return self.db.session.query(
self.database
).filter(getattr(self.database, name) == value)
def exist(self, name, value):
if self.filter(name, value).count():
return True
return False
def getdb(self):
return self.db
def getsession(self):
return self.db.session
def add(self, data):
logger.debug('creating entry')
reg = self.database(data)
self.db.session.add(reg)
self.commit()
def update(self, name, value, data):
# TODO pull out only items of available columns of table
if not self.filter(name, value).count():
self.add(data)
else:
logger.debug('updating entry')
# we want assess_time only at the time of creation
if data.get('assess_time'):
del data['assess_time']
try:
self.filter(name, value).update(data)
# TODO come back and fix the bug
# ConnectionError can't be adapted by sqlalchemy
except Exception:
# Get current system exception
ex_type, ex_value, ex_traceback = sys.exc_info()
# Extract unformatter stack traces as tuples
trace_back = traceback.extract_tb(ex_traceback)
# Format stacktrace
stack_trace = list()
for trace in trace_back:
stack_trace.append(
"File : %s , Line : %d, Func.Name : %s, Message : %s" %
(trace[0], trace[1], trace[2], trace[3])
)
# print("Exception type : %s " % ex_type.__name__)
logger.info(ex_value)
logger.debug(stack_trace)
self.commit()
def commit(self):
try:
self.db.session.commit()
except Exception:
# Get current system exception
ex_type, ex_value, ex_traceback = sys.exc_info()
# Extract unformatter stack traces as tuples
trace_back = traceback.extract_tb(ex_traceback)
# Format stacktrace
stack_trace = list()
for trace in trace_back:
stack_trace.append(
"File : %s , Line : %d, Func.Name : %s, Message : %s" %
(trace[0], trace[1], trace[2], trace[3])
)
# print("Exception type : %s " % ex_type.__name__)
logger.debug(ex_value)
logger.debug(stack_trace)
logger.debug('Rolling back db commit')
self.getsession().rollback()
def getdata(self, name=None, value=None):
# print ("********************************************************************************************")
a=self.filter(name, value).all()[0].__dict__
# print (a["url"])
# print ("********************************************************************************************")
# return self.filter(name, value).all()[0].__dict__
return a
def getcolumns(self):
return self.database.metadata.tables[self.database.__tablename__
].columns.keys()
def gettablename(self):
return self.database.__tablename__
def getcolumndata(self, column):
return self.getsession().query(getattr(self.database, column))
def getdbdata(self):
data = []
for i in self.getcolumndata('url'):
if not self.getdata('url', i).get('error'):
data.append(self.getdata('url', i))
# for d in data:
# print (d['url'])
return data
class Correlation(object):
def __init__(self):
pass
def getcorr(self, data, features_name):
# supply data to np.coorcoef
dataframe = pd.DataFrame(
data=np.asarray(data)[0:, 0:],
index=np.asarray(data)[0:, 0],
columns=features_name
)
corr = dataframe.corr()
return corr
def getheatmap(self, data, features_name):
corr = self.getcorr(data, features_name)
# get correlation heatmap
sns.heatmap(
corr,
xticklabels=features_name,
yticklabels=features_name,
cmap=sns.diverging_palette(220, 10, as_cmap=True)
)
# show graph plot of correlation
pl.show()
| [
"abhishek2mx3@gmail.com"
] | abhishek2mx3@gmail.com |
e7b73b568d45f5e2654f2dd4ac1ef284143b29b6 | ce4eec4a3c36acbb9ee279b4ffa4d3ab57ed7452 | /day3_exercises.py | ff1ce556f6e5548dec34dbba6eb5bd3d2dde8993 | [] | no_license | Shridevi-PythonDev/quotebook | 14abaaf93bd4bb991e2afd56e6f3d183a80e27b2 | 89dc6d36785a635ee088810e16c1b42ccc216590 | refs/heads/main | 2023-03-25T09:01:19.609179 | 2021-03-08T11:53:56 | 2021-03-08T11:53:56 | 345,609,406 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 305 | py | ### Max Value of a list
student_grades =[9.1, 8.8, 7.5]
max_value = max(student_grades)
print(max_value)
#### String Operations
my_string = "Hello World. How are you! How is the weather today??"
print(my_string.lower())
print(my_string.upper())
print(my_string.title())
print(my_string.capitalize())
| [
"shridevi.pythondev@gmail.com"
] | shridevi.pythondev@gmail.com |
02086cbeccc8c19cd85a073f2c7eab29f2e06976 | d2f71636c17dc558e066d150fe496343b9055799 | /eventi/receipts/forms.py | 9d3016a8c6419210c1823d66a44e71eee0f454e5 | [
"MIT"
] | permissive | klebercode/lionsclub | 9d8d11ad6083d25f6d8d92bfbae9a1bbfa6d2106 | 60db85d44214561d20f85673e8f6c047fab07ee9 | refs/heads/master | 2020-06-11T19:45:39.974945 | 2015-04-05T01:11:57 | 2015-04-05T01:11:57 | 33,409,707 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,159 | py | # coding: utf-8
from django import forms
from django.template.loader import render_to_string
from django.core.mail import EmailMultiAlternatives
from eventi.receipts.models import Receipt
from eventi.subscriptions.models import Subscription
class ReceiptForm(forms.ModelForm):
class Meta:
model = Receipt
def send_mail(self, pk):
subject = u'Lions Clubes, comprovante enviado.'
context = {
'name': self.cleaned_data['name'],
'subscription': self.cleaned_data['subscription'],
}
s = Subscription.objects.get(pk=self.cleaned_data['subscription'])
if s:
email_to = s.email
else:
email_to = ''
message = render_to_string('receipts/receipt_mail.txt', context)
message_html = render_to_string('receipts/receipt_mail.html',
context)
msg = EmailMultiAlternatives(subject, message,
'convencao@lionsclubegaranhuns.org.br',
[email_to])
msg.attach_alternative(message_html, 'text/html')
msg.send()
| [
"kleberr@msn.com"
] | kleberr@msn.com |
8e1eae7a39156a126bab8a0e988d2544f6845069 | adabc2aa335c87e43ea65b4d8a4d7ccd720c16c6 | /ecommerce/settings.py | 053abb86ed54a3dd0b3a2ebe7a8831db4e953426 | [
"MIT"
] | permissive | BokijonovM/ecommerce_app | e06507b16f35c2b055b15b642f1fda2c85ea1b8b | c84106543cb4d83ed93580a19f79e1353723d516 | refs/heads/main | 2023-07-02T20:34:26.586041 | 2021-08-01T08:25:22 | 2021-08-01T08:25:22 | 391,569,651 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,426 | py | """
Django settings for ecommerce project.
Generated by 'django-admin startproject' using Django 3.2.5.
For more information on this file, see
https://docs.djangoproject.com/en/3.2/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.2/ref/settings/
"""
import os
from pathlib import Path
# Build paths inside the project like this: BASE_DIR / 'subdir'.
BASE_DIR = Path(__file__).resolve().parent.parent
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.2/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'django-insecure-(@4@^y11ptqfjl$=q*-_nd$l*0@jh3d0u=80oah(0$buykj!y1'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'store.apps.StoreConfig',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'ecommerce.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'ecommerce.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.2/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': BASE_DIR / 'db.sqlite3',
}
}
# Password validation
# https://docs.djangoproject.com/en/3.2/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/3.2/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/3.2/howto/static-files/
# Default primary key field type
# https://docs.djangoproject.com/en/3.2/ref/settings/#default-auto-field
DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'
STATIC_URL = '/static/'
STATICFILES_DIRS = [
os.path.join(BASE_DIR, 'static')
]
MEDIA_URl = '/images/'
MEDIA_ROOT = os.path.join(BASE_DIR, 'static/images') | [
"78298971+BokijonovM@users.noreply.github.com"
] | 78298971+BokijonovM@users.noreply.github.com |
0e02e8d7a9547e324e10f84e09aa426a575894db | f2d3a9163fdbda5d2a8827607b144edb09e9e5ef | /stfba/settings.py | 38faa6dd41da50b46d4ae31252bc31ee64e55cf0 | [
"MIT"
] | permissive | eladnoor/stFBA | 560ceabaaf193ee4431af636f66a83b87c7286c9 | fbaefb48143a5f176aa3a7a9a63a9440ca18236e | refs/heads/master | 2020-04-05T12:59:16.636966 | 2018-06-09T10:05:06 | 2018-06-09T10:05:06 | 94,993,249 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,363 | py | # -*- coding: utf-8 -*-
"""
Created on Wed Mar 23 16:36:02 2016
@author: noore
"""
import os
import pandas as pd
import inspect
import numpy as np
LP_SOLVER = 'gurobi'
SCRIPT_DIR = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
BASE_DIR = os.path.join(*os.path.split(SCRIPT_DIR)[0:-1])
DATA_DIR = os.path.join(BASE_DIR, 'data')
MODEL_DIR = os.path.join(BASE_DIR, 'model')
RESULT_DIR = os.path.join(BASE_DIR, 'res')
IJO1366_JSON_FNAME = os.path.join(MODEL_DIR, 'iJO1366.json')
CORE_SBML_FNAME = os.path.join(MODEL_DIR, 'e_coli_core.xml.gz')
BIGG_METABOLITE_FNAME = os.path.join(DATA_DIR, 'bigg_models_metabolites.txt')
M = 1e6
eps = 1e-6
R = 8.31e-3 # kJ/(K*mol)
DEFAULT_TEMP = 298.15 # K
DEFAULT_IONIC_STRENGTH = 0.1 # mM
DEFAULT_PH = 7.0
DEFAULT_PMG = 14.0
DEFAULT_PHASE = 'aqueous'
RT = R * DEFAULT_TEMP
RTlog10 = RT * np.log(10)
def get_stoichiometry_from_model(model):
sparse = []
for rxn in model.reactions:
for met, coeff in rxn.metabolites.items():
sparse.append([rxn.id, met.id, coeff])
sparse = pd.DataFrame(sparse, columns=['bigg.reaction',
'bigg.metabolite', 'stoichiometry'])
S = sparse.pivot(index='bigg.metabolite', columns='bigg.reaction',
values='stoichiometry')
S.fillna(0, inplace=True)
return S
| [
"noor@imsb.biol.ethz.ch"
] | noor@imsb.biol.ethz.ch |
f3cc938e6a33b8c8d1be6291cf02cb275ac88856 | 75211deb14253833ba937ffdee90ed672d37a3c6 | /CS115b/life.py | 4dcbbb718f230e9c62f6f3e25d4d914ae613fcd4 | [] | no_license | Jerrytd579/CS115 | b3b924cbf52210c701363ae8c292db9946ce86e1 | d1ac812c88966c830ad6cb3c00a25429c6d5acf7 | refs/heads/master | 2022-01-21T23:44:26.559213 | 2019-04-24T16:07:13 | 2019-04-24T16:07:13 | 159,546,560 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,919 | py | #
# life.py - Game of Life lab
#
# Name: Jerry Cheng
# Pledge: I pledge my honor that I have abided by the Stevens Honor System.
#
import random
import sys
def createOneRow(width):
"""Returns one row of zeros of width "width"...
You should use this in your
createBoard(width, height) function."""
row = []
for col in range(width):
row += [0]
return row
def createBoard(width, height):
A = []
for row in range(height):
A += [createOneRow(width)]
return A
# A = createBoard(5, 3)
# print(A)
def printBoard(A):
for row in A:
for col in row:
sys.stdout.write(str(col))
sys.stdout.write('\n')
# A = createBoard(5, 3)
# printBoard(A)
def diagonalize(width, height):
A = createBoard(width, height)
for row in range(height):
for col in range(width):
if row == col:
A[row][col] = 1
else:
A[row][col] = 0
return A
# A = diagonalize(7, 6)
# print(A)
def innerCells(width, height):
A = createBoard(width, height)
for row in range(height):
for col in range(width):
if (row != 0 and row != height - 1) and (col != 0 and col != width - 1):
A[row][col] = 1
return A
# A = innerCells(5, 5)
# printBoard(A)
def randomCells(width, height):
A = innerCells(width, height)
for row in range(height):
for col in range(width):
if A[row][col] == 1:
A[row][col] = random.choice([0, 1])
return A
# A = randomCells(10, 10)
# printBoard(A)
def copy(A):
copy = []
for row in range(len(A)):
newRow = []
for column in range(len(A[row])):
newRow.append(A[row][column])
copy.append(newRow)
return copy
def innerReverse(A):
result = copy(A)
height = len(result)
width = len(result[0])
for row in range(height):
for column in range(width):
if (row == 0 or row == height - 1) or (column == 0 or column == width - 1):
result[row][column] = 0
elif result[row][column] == 1:
result[row][column] = 0
else:
result[row][column] = 1
return result
def next_life_generation(A):
result = []
for i in range(len(A)):
row = []
for j in range(len(A[i])):
sum = 0
if i == 0 or i == len(A) - 1 or j == 0 or j == len(A[i]) - 1:
row.append(0 * j)
continue
for neighbor_i in range(i - 1, i + 2):
for neighbor_j in range(j - 1, j + 2):
sum += A[neighbor_i][neighbor_j]
if A[i][j] == 1:
row.append(1 if sum - A[i][j] == 3 or sum - A[i][j] == 2 else 0)
else:
row.append(1 if sum - A[i][j] == 3 else 0)
result.append(row)
return result
| [
"noreply@github.com"
] | Jerrytd579.noreply@github.com |
a44193e1e5bab37c98a333189d0801452af21ca7 | e7997090baf0c4cfbd22e8653e53d88c2a938281 | /steamlog/views.py | ce4c7440f570d61bdf6819f24c3cd0a711881883 | [] | no_license | veggiedefender/steamlog | 912a5b7a056e3714c52a05cff6df3ff22337a28e | 620f1420c820923c8b6635d0292a60ae8c668758 | refs/heads/master | 2021-01-11T19:43:27.760066 | 2017-09-23T19:33:13 | 2017-09-23T19:33:13 | 74,920,554 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 826 | py | from flask import url_for, redirect, render_template
from steamlog.models import User
from steamlog import app
from flask_login import current_user
@app.route("/")
def index():
if current_user.is_authenticated:
return redirect(url_for("profile_page_steam_id",
steam_id=current_user.steam_id))
else:
return render_template("index.html", user=current_user)
@app.route("/profiles/<steam_id>")
def profile_page_steam_id(steam_id):
profile = User.query.filter_by(steam_id=steam_id).first_or_404()
return render_template("profile.html", profile=profile, user=current_user)
@app.route("/id/<url>")
def profile_page_url(url):
profile = User.query.filter_by(url=url).first_or_404()
return render_template("profile.html", profile=profile, user=current_user)
| [
"jessejesse123@gmail.com"
] | jessejesse123@gmail.com |
ed13833c5bf5473b552251b4e5e2902539e7b71e | 7a31321309eb19548f7336df123eea94092f138b | /social_media/views.py | 9e6746d0f4c36c0c0c70977ab9f9d613df610a81 | [] | no_license | reshmamz/Zartek_Task | aced71c8dea00bea4ff8c32b66574c83bd07827d | 6b0ef8868e31274f6fe7d5af7030fab398e65f4f | refs/heads/master | 2022-11-21T20:00:18.145501 | 2020-07-25T07:12:10 | 2020-07-25T07:12:10 | 280,841,562 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,399 | py | from rest_framework import viewsets,status
from rest_framework.response import Response
from .models import Feed, Like
from .serializers import FeedSerializer,LikesSerializer
class FeedViewSet(viewsets.ViewSet):
def list(self, request):
feed = Feed.objects.all()
serializer = FeedSerializer(feed,many=True)
return Response(serializer.data)
class LikeViewSet(viewsets.ViewSet):
serializer_class = LikesSerializer
def create(self,request):
serializer = LikesSerializer(data=request.data)
if serializer.is_valid():
serializer.save()
return Response({'message':'Success'})
else:
return Response(serializer.errors,status=status.HTTP_404_NOT_FOUND)
def retrieve(self, request, pk=None):
like = Like.objects.get(pk=pk)
serializer = LikesSerializer(like)
return Response(serializer.data)
def update(self,request,pk=None):
like = Like.objects.get(pk=pk)
serializer = LikesSerializer(instance=like,data=request.data)
if serializer.is_valid():
serializer.save()
return Response(serializer.data)
def list(self, request):
like = Like.objects.all()
serializer = LikesSerializer(like,many=True)
print(serializer.data)
return Response(serializer.data)
| [
"reshmamangote97@gmail.com"
] | reshmamangote97@gmail.com |
0a66b57a0a97691dde66f834b3db4d73575278b6 | 883b7a0e8231cd4ca94ab01556995eb13f853357 | /python/predict.py | 1c788f5f897983c4a7388cdc9571ee63d6f244aa | [
"MIT"
] | permissive | gene891212/testAI-for-school | 3a2cea81a086740fcfae609989570a63df859011 | 6620b352506c74c7be0b98fcc7ca07a3820b3414 | refs/heads/master | 2023-07-20T14:46:48.013153 | 2021-08-22T08:05:25 | 2021-08-22T08:05:25 | 387,001,272 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,042 | py | # The steps implemented in the object detection sample code:
# 1. for an image of width and height being (w, h) pixels, resize image to (w', h'), where w/h = w'/h' and w' x h' = 262144
# 2. resize network input size to (w', h')
# 3. pass the image to network and do inference
# (4. if inference speed is too slow for you, try to make w' x h' smaller, which is defined with DEFAULT_INPUT_SIZE (in object_detection.py or ObjectDetection.cs))
import sys
import tensorflow as tf
import numpy as np
from PIL import Image, ImageDraw, ImageFont
from object_detection import ObjectDetection
MODEL_FILENAME = 'model.tflite'
LABELS_FILENAME = 'labels.txt'
class TFLiteObjectDetection(ObjectDetection):
"""Object Detection class for TensorFlow Lite"""
def __init__(self, model_filename, labels):
super(TFLiteObjectDetection, self).__init__(labels)
self.interpreter = tf.lite.Interpreter(model_path=model_filename)
self.interpreter.allocate_tensors()
self.input_index = self.interpreter.get_input_details()[0]['index']
self.output_index = self.interpreter.get_output_details()[0]['index']
def predict(self, preprocessed_image):
inputs = np.array(preprocessed_image, dtype=np.float32)[np.newaxis, :, :, (2, 1, 0)] # RGB -> BGR and add 1 dimension.
# Resize input tensor and re-allocate the tensors.
self.interpreter.resize_tensor_input(self.input_index, inputs.shape)
self.interpreter.allocate_tensors()
self.interpreter.set_tensor(self.input_index, inputs)
self.interpreter.invoke()
return self.interpreter.get_tensor(self.output_index)[0]
def main(image_filename):
# Load labels
with open(LABELS_FILENAME, 'r') as f:
labels = [l.strip() for l in f.readlines()]
od_model = TFLiteObjectDetection(MODEL_FILENAME, labels)
image = Image.open(image_filename)
predictions = od_model.predict_image(image)
# Draw rectangle
for pred in predictions:
if pred['probability'] > .7:
pred_bound = pred['boundingBox']
rect_startwith = (pred_bound['left'] * image.width, pred_bound['top'] * image.height)
pred_shape = [
rect_startwith,
(
rect_startwith[0] + pred_bound['width'] * image.width,
rect_startwith[1] + pred_bound['height'] * image.height
)
]
draw_img = ImageDraw.Draw(image)
draw_img.rectangle(pred_shape, outline='red')
label = [(pred_shape[0][0], pred_shape[0][1] - 15), (pred_shape[1][0], pred_shape[0][1])]
draw_img.rectangle(label, fill='red')
font = ImageFont.truetype("arial.ttf", 16)
draw_img.text((pred_shape[0][0] + 5, pred_shape[0][1] - 15), pred["tagName"], font=font)
print(predictions)
image.show()
if __name__ == '__main__':
if len(sys.argv) <= 1:
print('USAGE: {} image_filename'.format(sys.argv[0]))
else:
main(sys.argv[1])
| [
"gene891212@gmail.com"
] | gene891212@gmail.com |
2e24bd51de5ae9f8d8f82e6141a9dbc61699ec84 | bca6f87ef3021171e1f7d212e65ccdb918de3792 | /helper.py | e96c915f36fa8188d8e2fce3a3b50b04acf86033 | [
"MIT"
] | permissive | ridgedodd/cs3240-labdemo | a81c35c60c5e673d73c6b0d3581b3aa6fb4202e3 | dfde848c37bd8c45bdc7ab9665551be548e9ff3a | refs/heads/master | 2021-01-19T10:36:54.268752 | 2017-02-20T22:30:42 | 2017-02-20T22:30:42 | 82,215,328 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 39 | py | def greeting(msg):
print(msg + " new") | [
"crd4vn@virginia.edu"
] | crd4vn@virginia.edu |
6818c5fc9cc4e7c60201c6be008adce05b30bd86 | 47c20ad6c23f1359f27bff9dbaaa9fb1069ebe31 | /PixivAPI.py | 141b02cfcf7985c9dbb8b3a1d9482b971c60fd8d | [] | no_license | ComfyFluffy/pixivmanager-python | add4f5f089a0af6367522ba60266c69b8c9f4333 | 7eee608eff7ebbbeb00818e149961190f984a1aa | refs/heads/master | 2023-03-10T06:00:48.206247 | 2019-04-04T15:46:33 | 2019-04-04T15:46:33 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,217 | py | import logging
from datetime import datetime
from logging import Logger
import requests
import PixivException
from PixivConfig import HTTP_HEADERS, _retry, init_logger
CLIENT_ID = 'MOBrBDS8blbauoSck0ZfDbtuzpyT'
CLIENT_SECRET = 'lsACyCD94FhDUtGTXi3QzcFE2uU1hqtDaKeqrdwj'
TIMEOUT = 20
proxy = {
'http': 'http://127.0.0.1:8888',
'https': 'http://127.0.0.1:8888',
}
class PixivAPI:
logger = init_logger('_PixivAPI_')
def __init__(self, logger: Logger = None):
if logger:
self.logger = logger
self.s = requests.Session()
self.s.headers = dict(HTTP_HEADERS)
self.pixiv_user_id = -1
if False:
self.s.proxies = proxy
self.s.verify = 'storage/fiddler.pem'
def login(self, username='', password='', refresh_token=''):
auth_url = 'https://oauth.secure.pixiv.net/auth/token'
datas = {
'client_id': CLIENT_ID,
'client_secret': CLIENT_SECRET,
'device_token': 'pixiv',
'get_secure_url': 'true',
}
def on_succeed(login_result):
parsed_result = login_result.json()
user_json = parsed_result['response']['user']
self.pixiv_user_id = user_json['id']
self.s.headers['Authorization'] = 'Bearer ' + parsed_result[
'response']['access_token']
self.refresh_token = parsed_result['response']['refresh_token']
self.logger.info('Login successful! User ID: %s' % user_json['id'])
return {
'status_code': 0,
'status_message': 'OK',
'refresh_token': refresh_token,
'user_id': self.pixiv_user_id
}
def login_password(username, password):
self.logger.info('Login with password...')
datas['grant_type'] = 'password'
datas['username'] = username
datas['password'] = password
login_result = self.s.post(
auth_url, data=datas,
timeout=TIMEOUT) #TODO set post as get_url()
if login_result.status_code == 200:
return on_succeed(login_result)
else:
self.logger.warning('Password error?')
return {'status_code': -1, 'status_message': 'PASSWORD ERROR?'}
def login_token(refresh_token):
self.logger.info('Login with token...')
datas['grant_type'] = 'refresh_token'
datas['refresh_token'] = refresh_token
login_result = self.s.post(auth_url, data=datas, timeout=TIMEOUT)
if login_result.status_code == 200:
return on_succeed(login_result)
else:
self.logger.warning('Can not login with token!')
return {
'status_code': -2,
'status_message': 'TOKEN LOGIN FAILED'
}
try:
if username and password:
return login_password(username, password)
elif refresh_token:
return login_token(refresh_token)
else:
return login_token(self.refresh_token)
except requests.RequestException as e:
self.logger.exception('Network exception when logging in!')
return {
'status_code': -3,
'status_message': 'NETWORK EXCEPTION',
'exception': e
}
@_retry(
requests.RequestException,
delay=1,
tries=8,
error_msg='API network error! Retrying...',
print_traceback=False)
def _get_url(self, url):
self.logger.debug('Accessed url: %s' % url)
if not self.s.headers.get('Authorization'):
self.logger.warning('Empty Pixiv token found! Should login first!')
result = self.s.get(url, timeout=TIMEOUT)
if result.status_code == 200:
return result
elif result.status_code == 400:
self.logger.warning('Status code: 400. Try relogin..')
self.logger.debug('%s | %s' % (url, result.text))
self.login()
result = self.s.get(url)
if result.status_code != 200:
self.logger.error('Still got %s ! | %s | %s' %
(result.status_code, url, result.text))
return result
elif result.status_code == 403:
self.logger.warning(
'Status code: 403 | %s, wait for 1 min and retry...' %
result.text)
result = self._get_url(url)
if result.status_code == 403:
self.logger.error('Still got %s ! | %s | %s' %
(result.status_code, url, result.text))
else:
self.logger.warn('Status code: %d' % result.status_code)
self.logger.debug('%s | %s' % (url, result.text))
return result
def get_url(self, url, caller=''):
result = self._get_url(url)
if result.status_code == 200:
return result
else:
self.logger.warn('%s(%r) Got empty result' % (caller, url))
def raw_user_detail(self, user_id):
return self.get_url(
'https://app-api.pixiv.net/v1/user/detail?user_id=%s' % user_id,
'raw_user')
def raw_user_bookmark_first(self, user_id, private=False):
p = 'private' if private else 'public'
return self.get_url(
'https://app-api.pixiv.net/v1/user/bookmarks/illust?user_id=%s&restrict=%s'
% (user_id, p), 'raw_bookmark_first')
def raw_works_detail(self, work_id):
return self.get_url(
'https://app-api.pixiv.net/v1/illust/detail?illust_id=%s' %
work_id, 'raw_work_detail')
def raw_ugoira_metadata(self, ugoira_id):
return self.get_url(
'https://app-api.pixiv.net/v1/ugoira/metadata?illust_id=%s' %
ugoira_id, 'raw_ugoira')
def raw_user_works(self, user_id):
return self.get_url(
'https://app-api.pixiv.net/v1/user/illusts?user_id=%s' % user_id,
'raw_user_works')
#TODO 过滤器
| [
"xxwows233@outlook.com"
] | xxwows233@outlook.com |
4e60cac49c40a5301812eb918353abb49b33caf4 | db55823daba264b02ff70199f454e5996addd367 | /node_modules/secp256k1/build/config.gypi | 323033e82118d227f1ca29bcaefa2e3cec11447c | [
"MIT",
"LicenseRef-scancode-warranty-disclaimer"
] | permissive | reqdot/kickstart | 04490611aa0ef0249aa7f15c8c71b4dcff5f666e | 1154b8b1f4163fec52675d07dbf02ac5fb9651f1 | refs/heads/master | 2020-03-27T11:38:18.296050 | 2018-08-28T19:49:36 | 2018-08-28T19:49:36 | 146,498,921 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,207 | gypi | # Do not edit. File was generated by node-gyp's "configure" step
{
"target_defaults": {
"cflags": [],
"default_configuration": "Release",
"defines": [],
"include_dirs": [],
"libraries": []
},
"variables": {
"asan": 0,
"coverage": "false",
"debug_devtools": "node",
"debug_http2": "false",
"debug_nghttp2": "false",
"force_dynamic_crt": 0,
"host_arch": "x64",
"icu_data_file": "icudt60l.dat",
"icu_data_in": "../../deps/icu-small/source/data/in/icudt60l.dat",
"icu_endianness": "l",
"icu_gyp_path": "tools/icu/icu-generic.gyp",
"icu_locales": "en,root",
"icu_path": "deps/icu-small",
"icu_small": "true",
"icu_ver_major": "60",
"llvm_version": 0,
"node_byteorder": "little",
"node_enable_d8": "false",
"node_enable_v8_vtunejit": "false",
"node_install_npm": "true",
"node_module_version": 57,
"node_no_browser_globals": "false",
"node_prefix": "/usr/local",
"node_release_urlbase": "https://nodejs.org/download/release/",
"node_shared": "false",
"node_shared_cares": "false",
"node_shared_http_parser": "false",
"node_shared_libuv": "false",
"node_shared_nghttp2": "false",
"node_shared_openssl": "false",
"node_shared_zlib": "false",
"node_tag": "",
"node_target_type": "executable",
"node_use_bundled_v8": "true",
"node_use_dtrace": "true",
"node_use_etw": "false",
"node_use_lttng": "false",
"node_use_openssl": "true",
"node_use_perfctr": "false",
"node_use_v8_platform": "true",
"node_without_node_options": "false",
"openssl_fips": "",
"openssl_no_asm": 0,
"shlib_suffix": "57.dylib",
"target_arch": "x64",
"uv_parent_path": "/deps/uv/",
"uv_use_dtrace": "true",
"v8_enable_gdbjit": 0,
"v8_enable_i18n_support": 1,
"v8_enable_inspector": 1,
"v8_no_strict_aliasing": 1,
"v8_optimized_debug": 0,
"v8_promise_internal_field_count": 1,
"v8_random_seed": 0,
"v8_trace_maps": 0,
"v8_use_snapshot": "true",
"want_separate_host_toolset": 0,
"xcode_version": "7.0",
"nodedir": "/Users/jihyunkim/.node-gyp/8.11.3",
"standalone_static_library": 1,
"dry_run": "",
"legacy_bundling": "",
"save_dev": "",
"viewer": "man",
"commit_hooks": "true",
"browser": "",
"only": "",
"also": "",
"rollback": "true",
"usage": "",
"globalignorefile": "/usr/local/etc/npmignore",
"shell": "/bin/bash",
"maxsockets": "50",
"init_author_url": "",
"shrinkwrap": "true",
"metrics_registry": "https://registry.npmjs.org/",
"parseable": "",
"init_license": "ISC",
"timing": "",
"if_present": "",
"cache_max": "Infinity",
"init_author_email": "",
"sign_git_tag": "",
"git_tag_version": "true",
"cert": "",
"local_address": "",
"long": "",
"registry": "https://registry.npmjs.org/",
"fetch_retries": "2",
"message": "%s",
"key": "",
"versions": "",
"globalconfig": "/usr/local/etc/npmrc",
"logs_max": "10",
"always_auth": "",
"prefer_online": "",
"cache_lock_retries": "10",
"global_style": "",
"heading": "npm",
"searchlimit": "20",
"fetch_retry_mintimeout": "10000",
"offline": "",
"read_only": "",
"access": "",
"json": "",
"allow_same_version": "",
"description": "true",
"engine_strict": "",
"https_proxy": "",
"userconfig": "/Users/jihyunkim/.npmrc",
"init_module": "/Users/jihyunkim/.npm-init.js",
"cidr": "",
"node_version": "8.11.3",
"user": "",
"editor": "vi",
"auth_type": "legacy",
"save": "true",
"ignore_prepublish": "",
"tag": "latest",
"script_shell": "",
"progress": "true",
"global": "",
"searchstaleness": "900",
"optional": "true",
"ham_it_up": "",
"bin_links": "true",
"force": "",
"save_prod": "",
"searchopts": "",
"node_gyp": "/usr/local/lib/node_modules/npm/node_modules/node-gyp/bin/node-gyp.js",
"depth": "Infinity",
"sso_poll_frequency": "500",
"rebuild_bundle": "true",
"unicode": "true",
"fetch_retry_maxtimeout": "60000",
"tag_version_prefix": "v",
"strict_ssl": "true",
"sso_type": "oauth",
"scripts_prepend_node_path": "warn-only",
"save_prefix": "^",
"ca": "",
"group": "20",
"fetch_retry_factor": "10",
"dev": "",
"save_exact": "",
"cache_lock_stale": "60000",
"prefer_offline": "",
"version": "",
"cache_min": "10",
"otp": "",
"cache": "/Users/jihyunkim/.npm",
"searchexclude": "",
"color": "true",
"package_lock": "true",
"package_lock_only": "",
"save_optional": "",
"user_agent": "npm/5.6.0 node/v8.11.3 darwin x64",
"ignore_scripts": "",
"cache_lock_wait": "10000",
"production": "",
"save_bundle": "",
"send_metrics": "",
"umask": "0022",
"init_version": "1.0.0",
"node_options": "",
"scope": "",
"git": "git",
"init_author_name": "",
"unsafe_perm": "true",
"tmp": "/var/folders/zl/vkq013f90_l830h_y_y4b_3m0000gn/T",
"onload_script": "",
"prefix": "/usr/local",
"link": ""
}
}
| [
"repl8124@gmail.com"
] | repl8124@gmail.com |
4b5ce157886ae6f7d16078d25f22aed1aede4df3 | 04b1803adb6653ecb7cb827c4f4aa616afacf629 | /chrome/chrome_cleaner/cleaner/DEPS | 9648b97a1c3d91971cbc9b21e5c24b58308df304 | [
"BSD-3-Clause"
] | permissive | Samsung/Castanets | 240d9338e097b75b3f669604315b06f7cf129d64 | 4896f732fc747dfdcfcbac3d442f2d2d42df264a | refs/heads/castanets_76_dev | 2023-08-31T09:01:04.744346 | 2021-07-30T04:56:25 | 2021-08-11T05:45:21 | 125,484,161 | 58 | 49 | BSD-3-Clause | 2022-10-16T19:31:26 | 2018-03-16T08:07:37 | null | UTF-8 | Python | false | false | 52 | include_rules = [
"+components/chrome_cleaner",
]
| [
"sunny.nam@samsung.com"
] | sunny.nam@samsung.com | |
345609bb71c26e11984ec13c344bf06118aba6c9 | fd23d035d6607f5b879d47aaae680715720ab5b4 | /hangman/hangman_test.py | 98e10249f7ec7ddc24759823e0345cfa4dabed67 | [] | no_license | wisemoron/python | 7fa05cacf57eb0f557ab9dc3eb1ea8bf4a05ec45 | 9511fa49de3b9372c1c3f6919ae74256189daa49 | refs/heads/master | 2023-01-22T15:48:06.571406 | 2023-01-03T22:37:16 | 2023-01-03T22:37:16 | 171,977,110 | 0 | 0 | null | 2023-01-03T22:25:49 | 2019-02-22T02:02:53 | Python | UTF-8 | Python | false | false | 6,706 | py | import sys
import colorama, random
import urllib.request
from urllib.error import URLError, HTTPError
keep_playing = 'Y'
word_used = []
game_wordlist = []
wordlist2 = []
wordlist = ["Mansoor Bhai", "Girdhar Niwas", "Rashid Wadia", "Janata Book Depot", "Theobroma", "Sahakari Bhandar", "Cafe Royal",
"Trattoria", "Strand Book Depot", "Colaba Market", "Radio Club", "Electric House", "Regal Cinema", "Bade Miyan",
"Gateway of India", "Apollo Bunder", "The Scholar High School", "Campion", "Madras Cafe", "Kailash Parbat", "Navy Nagar",
"Sasoon Dock", "Cafe Mondegar", "Cafe Leopold", "Tetsuma", "Bayview Cafe"]
losing_taunts = ["Shame on you. Seriously.", "LOOOOSEERRR!", "Hey outsider who's never lived in Bombay - ", "WOW. You know NOTHING.",
"Sheeesh, how are you still alive?", "Wrong Hangman game. You need the Iceland version. Fewer places.",
"Such a kid. Go home and sleep.", "Beta .. tumse na ho paayega.", "Makes you wonder, doesn't it? Who are these people who think you're intelligent?",
"Yeah, you're not beating this. FOR SURE.", "Quit while this is not yet embarrassing. I mean it.", "All you need now is a noose. Let the Hangman do the rest.",
"Man.. yo daddy so dumb, he got hit by a parked car."]
winning_taunts = ["Fine. You did it. Bleh.", "So you lived in South Bombay. You knew the answer. Big deal!", "CLAP ... CLAP.. CL..AP",
"Check out the big brains, eh? Quick what's the root of 349 .. ", "Okay, well done. *yawn*",
"NOICE! What .. you expecting a reward or something now?", "Aww, isn't that adorable? You got one.", "You know you can't keep up this winning streak, yeah?",
]
colorama.init()
def layout_settings():
# sys.stderr.write('\x1b[2J\x1b[H')
print(chr(27) + "[2J")
sys.stdout.write('\n' * 11)
print("\t\t\t\t H A N G M A N: The South Bombay Edition")
print("\t\t\t\t=========================================\n\n")
sys.stdout.write('\t' * 4)
return
def choose_word(wordlist, word_used):
index = -1
while index not in word_used:
if len(wordlist) == len(word_used):
index = -1
break
index = random.randint(0, len(wordlist) - 1)
if index in word_used:
index = -1
continue
word_used.append(index)
return index
def choose_losing_taunt(losing_taunts):
index = random.randint(0, len(losing_taunts) - 1)
return index
def choose_winning_taunt(winning_taunts):
index = random.randint(0, len(winning_taunts) - 1)
return index
def lay_board(word):
counter = 0
layout_settings()
sys.stdout.write("\n\n\t\t\t\tTries: " + str(numtries) + "\n\n\t\t\t\t")
for pos in range(len(word)):
if word.find(' ', pos) == pos:
space_positions.append(pos)
for dash in range(len(word)):
if len(space_positions) > 0 and dash == space_positions[counter]:
sys.stdout.write(' ')
if counter + 1 < len(space_positions):
counter = counter + 1
else:
sys.stdout.write('__ ')
return
def accept_input(letter, ip_letter, used_letter):
ip_letter = input("\n\t\t\t\tGo on. Take a guess: ")
if ip_letter[0] not in letter:
letter.append(ip_letter[0])
return ip_letter[0]
def find_letter_in_word(word, letter, letters_found, ip_letter, numtries):
counter = 0
found_letter = 0
layout_settings()
for pos, char in enumerate(word):
if char.lower() in letter or char in letter:
sys.stdout.write(char.upper() + ' ')
if (char.lower() == ip_letter[0] or char == ip_letter[0])\
and (ip_letter[0] not in used_letter):
letters_found = letters_found + 1
found_letter = 1
else:
if len(space_positions) > 0 and pos == space_positions[counter]:
sys.stdout.write(' ')
if counter + 1 < len(space_positions):
counter = counter + 1
else:
sys.stdout.write('__ ')
if numtries >= 0 and found_letter == 1:
numtries = numtries - 1
return letters_found, numtries
'''
def populate_wordlist_from_url(wordlist, listurl):
with urllib.request.urlopen(listurl) as url:
for line in url:
line_words = line.decode('utf-8').split('\\n') # handles the b' at the beginning
for word in line_words:
wordlist.append(word.replace('\n', ''))
return
'''
def populate_wordlist_from_url(wordlist, listurl):
return_code = 0
try:
url = urllib.request.urlopen(listurl)
for line in url:
line_words = line.decode('utf-8').split('\\n') # handles the b' at the beginning
for word in line_words:
wordlist.append(word.replace('\n', ''))
except HTTPError as e:
print("HTTP error: ", e.code)
return_code = 1
except URLError as e:
print("URL error: ", e.reason)
return_code = 1
return return_code
return_code = populate_wordlist_from_url(wordlist2, "https://raw.githubusercontent.com/wisemoron/python/master/hangman/test_wordlist.txt")
if return_code == 1:
game_wordlist = wordlist
else:
game_wordlist = wordlist2
while keep_playing == "Y":
index = choose_word(game_wordlist, word_used)
if index == -1:
print("\n\n\t\t\t\tAll words attempted!")
break
word = game_wordlist[index]
space_positions = []
letter = []
used_letter = []
numtries = 0
letters_found = 0
ip_letter = ""
lay_board(word)
while letters_found < (len(word) - len(space_positions)) and numtries < 10:
ip_letter = accept_input(letter, ip_letter, used_letter)
if ip_letter[0] in used_letter:
letters_found, numtries = find_letter_in_word(word, letter, letters_found, ip_letter[0], numtries)
print("\n\n\t\t\t\tLetter used. Guess another .. ")
continue
else:
letters_found, numtries = find_letter_in_word(word, letter, letters_found, ip_letter[0], numtries)
numtries = numtries + 1
used_letter.append(ip_letter[0])
print("\n\n\t\t\t\tTries: ", numtries)
if numtries == 10:
print("\n\t\t\t\t" + losing_taunts[choose_losing_taunt(losing_taunts)] + " The answer is: ", word)
elif letters_found == (len(word) - len(space_positions)) and numtries < 10:
print("\n\t\t\t\t", winning_taunts[choose_winning_taunt(winning_taunts)])
keep_playing = input("\n\t\t\t\tAnother one? ").upper() | [
"47875402+wisemoron@users.noreply.github.com"
] | 47875402+wisemoron@users.noreply.github.com |
023b58296e4925c5b65036563c3cd12d57e83077 | dc529ac2a73ebcbe4a4974757ae6beb7ead2a85a | /notebooks/globalgoals-pyglobalgoals.py.py | d1aaa7175844e43a40ae9177540a31d8c60d0e9d | [
"BSD-3-Clause"
] | permissive | westurner/pyglobalgoals | 19a611794eb11aa355ab0cd57b2b40a949b34c0f | 768e8dd236fd23e233e33cd9af03284ca4b9dddf | refs/heads/master | 2021-06-30T00:26:06.430143 | 2016-03-08T23:20:14 | 2016-03-08T23:20:14 | 42,337,725 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 16,352 | py |
# coding: utf-8
# # @TheGlobalGoals for Sustainable Development
# ## Background
#
# * Homepage: **http://www.globalgoals.org/**
# - Twitter: https://twitter.com/TheGlobalGoals
# - Instagram: https://instagram.com/TheGlobalGoals/
# - Facebook: https://www.facebook.com/globalgoals.org
# - YouTube: https://www.youtube.com/channel/UCRfuAYy7MesZmgOi1Ezy0ng/
# - Hashtag: **#GlobalGoals**
# - https://twitter.com/hashtag/GlobalGoals
# - https://instagram.com/explore/tags/GlobalGoals/
# - https://www.facebook.com/hashtag/GlobalGoals
# - Hashtag: #TheGlobalGoals
# - https://twitter.com/hashtag/TheGlobalGoals
# - https://instagram.com/explore/tags/TheGlobalGoals/
# - https://www.facebook.com/hashtag/TheGlobalGoals
#
#
# ### pyglobalgoals
#
# * Homepage: https://github.com/westurner/pyglobalgoals
# * Src: https://github.com/westurner/pyglobalgoals
# * Download: https://github.com/westurner/pyglobalgoals/releases
#
# ### Objectives
#
# * [x] ENH: Read and parse TheGlobalGoals from globalgoals.org
# * [x] ENH: Download (HTTP GET) each GlobalGoal tile image to ``./notebooks/data/images/``
# * [-] ENH: Generate e.g. tweets for each GlobalGoal (e.g. **##gg17** / **##GG17**)
# * [x] ENH: Save TheGlobalGoals to a JSON-LD document
# * [-] ENH: Save TheGlobalGoals with Schema.org RDF vocabulary (as JSON-LD)
# * [-] ENH: Save TheGlobalGoals as ReStructuredText with headings and images
# * [-] ENH: Save TheGlobalGoals as Markdown with headings and images
# * [-] ENH: Save TheGlobalGoals as RDFa with headings and images
# * [ ] ENH: Save TheGlobalGoals as RDFa with images like http://globalgoals.org/
# * [-] DOC: Add narrative documentation where necessary
# * [-] REF: Refactor and extract methods from ``./notebooks/`` to ``./pyglobalgoals/``
#
# ## Implementation
#
# * Python package: [**pyglobalgoals**](#pyglobalgoals)
#
# * Jupyter notebook: **``./notebooks/globalgoals-pyglobalgoals.py.ipynb``**
# * Src: https://github.com/westurner/pyglobalgoals/blob/master/notebooks/globalgoals-pyglobalgoals.py.ipynb
# * Src: https://github.com/westurner/pyglobalgoals/blob/master/notebooks/globalgoals-pyglobalgoals.py.py
# * Src: https://github.com/westurner/pyglobalgoals/blob/develop/notebooks/globalgoals-pyglobalgoals.py.ipynb
# * Src: https://github.com/westurner/pyglobalgoals/blob/v0.1.2/notebooks/globalgoals-pyglobalgoals.py.ipynb
# * Src: https://github.com/westurner/pyglobalgoals/blob/v0.2.1/notebooks/globalgoals-pyglobalgoals.py.ipynb
#
# * [x] Download HTML with requests
# * [x] Parse HTML with beautifulsoup
# * [x] Generate JSON[-LD] with ``collections.OrderedDict``
# * [-] REF: Functional methods -> more formal type model -> ``pyglobalgoals.<...>``
#
#
# * [JSON-LD](#JSONLD) document: **``./notebooks/data/globalgoals.jsonld``**
# * Src: https://github.com/westurner/pyglobalgoals/blob/master/notebooks/data/globalgoals.jsonld
#
#
# ### JSON-LD
#
# * Wikipedia: https://en.wikipedia.org/wiki/JSON-LD
# * Homepage: http://json-ld.org/
# * Docs: http://json-ld.org/playground/
# * Hashtag: #JSONLD
#
# ### RDFa
#
# * Wikipedia: https://en.wikipedia.org/wiki/RDFa
# * Standard: http://www.w3.org/TR/rdfa-core/
# * Docs: http://www.w3.org/TR/rdfa-primer/
# * Hashtag: #RDFa
# In[1]:
#!conda install -y beautiful-soup docutils jinja2 requests
get_ipython().system(u"pip install -U beautifulsoup4 jinja2 'requests<2.8' requests-cache version-information # tweepy")
import bs4
import jinja2
import requests
import requests_cache
requests_cache.install_cache('pyglobalgoals_cache')
#!pip install -U version_information
get_ipython().magic(u'load_ext version_information')
get_ipython().magic(u'version_information jupyter, bs4, jinja2, requests, requests_cache, version_information')
# In[2]:
url = "http://www.globalgoals.org/"
req = requests.get(url)
#print(req)
#print(sorted(dir(req)))
#req.<TAB>
#req??<[Ctrl-]Enter>
if not req.ok:
raise Exception(req)
content = req.content
print(content[:20])
# In[ ]:
# In[3]:
bs = bs4.BeautifulSoup(req.content)
print(bs.prettify())
# In[4]:
tiles = bs.find_all(class_='goal-tile-wrapper')
pp(tiles)
# In[5]:
tile = tiles[0]
print(tile)
# In[6]:
link = tile.findNext('a')
img = link.findNext('img')
img_title = img['alt'][:-5]
img_src = img['src']
link_href = link['href']
example = {'name': img_title, 'img_src': img_src, 'href': link_href}
print(example)
# In[7]:
import collections
def get_data_from_goal_tile_wrapper_div(node, n=None):
link = node.findNext('a')
img = link.findNext('img')
img_title = img['alt'][:-5]
img_src = img['src']
link_href = link['href']
output = collections.OrderedDict({'@type': 'un:GlobalGoal'})
if n:
output['n'] = n
output['name'] = img_title
output['image'] = img_src
output['url'] = link_href
return output
def get_goal_tile_data(bs):
for i, tile in enumerate(bs.find_all(class_='goal-tile-wrapper'), 1):
yield get_data_from_goal_tile_wrapper_div(tile, n=i)
tiles = list(get_goal_tile_data(bs))
import json
print(json.dumps(tiles, indent=2))
goal_tiles = tiles[:-1]
# In[ ]:
# In[8]:
import codecs
from path import Path
def build_default_context():
context = collections.OrderedDict()
# context["dc"] = "http://purl.org/dc/elements/1.1/"
context["schema"] = "http://schema.org/"
# context["xsd"] = "http://www.w3.org/2001/XMLSchema#"
# context["ex"] = "http://example.org/vocab#"
# context["ex:contains"] = {
# "@type": "@id"
# }
# default attrs (alternative: prefix each with schema:)
# schema.org/Thing == schema:Thing (!= schema:thing)
context["name"] = "http://schema.org/name"
context["image"] = {
"@type": "@id",
"@id": "http://schema.org/image"
}
context["url"] = {
"@type": "@id",
"@id":"http://schema.org/url"
}
context["description"] = {
"@type": "http://schema.org/Text",
"@id": "http://schema.org/description"
}
return context
DEFAULT_CONTEXT = build_default_context()
def goal_tiles_to_jsonld(nodes, context=None, default_context=DEFAULT_CONTEXT):
data = collections.OrderedDict()
if context is None and default_context is not None:
data['@context'] = build_default_context()
elif context:
data['@context'] = context
elif default_context:
data['@context'] = default_context
data['@graph'] = nodes
return data
DATA_DIR = Path('.') / 'data'
#DATA_DIR = Path(__file__).dirname
#DATA_DIR = determine_path_to(current_notebook) # PWD initially defaults to nb.CWD
DATA_DIR.makedirs_p()
GLOBAL_GOALS_JSONLD_PATH = DATA_DIR / 'globalgoals.jsonld'
def write_global_goals_jsonld(goal_tiles, path=GLOBAL_GOALS_JSONLD_PATH):
goal_tiles_jsonld = goal_tiles_to_jsonld(goal_tiles)
with codecs.open(path, 'w', 'utf8') as fileobj:
json.dump(goal_tiles_jsonld, fileobj, indent=2)
def read_global_goals_jsonld(path=GLOBAL_GOALS_JSONLD_PATH, prettyprint=True):
with codecs.open(path, 'r', 'utf8') as fileobj:
global_goals_dict = json.load(fileobj,
object_pairs_hook=collections.OrderedDict)
return global_goals_dict
def print_json_dumps(global_goals_dict, indent=2):
print(json.dumps(global_goals_dict, indent=indent))
write_global_goals_jsonld(goal_tiles)
global_goals_dict = read_global_goals_jsonld(path=GLOBAL_GOALS_JSONLD_PATH)
assert global_goals_dict == goal_tiles_to_jsonld(goal_tiles)
print_json_dumps(global_goals_dict)
# In[9]:
def build_tweet_for_goal_tile(node):
return '##gg{n} {name} {url} {image} @TheGlobalGoals #GlobalGoals'.format(**node)
tweets = list(build_tweet_for_goal_tile(tile) for tile in goal_tiles)
tweets
# In[10]:
for node in goal_tiles:
img_basename = node['image'].split('/')[-1]
node['image_basename'] = img_basename
node['tweet_txt'] = build_tweet_for_goal_tile(node)
print(json.dumps(goal_tiles, indent=2))
# In[11]:
#!conda install -y pycurl
try:
import pycurl
except ImportError as e:
import warnings
warnings.warn(unicode(e))
def pycurl_download_file(url, dest_path, follow_redirects=True):
with open(dest_path, 'wb') as f:
c = pycurl.Curl()
c.setopt(c.URL, url)
c.setopt(c.WRITEDATA, f)
if follow_redirects:
c.setopt(c.FOLLOWLOCATION, True)
c.perform()
c.close()
return (url, dest_path)
# In[12]:
import requests
def requests_download_file(url, dest_path, **kwargs):
local_filename = url.split('/')[-1]
# NOTE the stream=True parameter
r = requests.get(url, stream=True)
with open(dest_path, 'wb') as f:
for chunk in r.iter_content(chunk_size=1024):
if chunk: # filter out keep-alive new chunks
f.write(chunk)
f.flush()
return (url, dest_path)
# In[13]:
import urllib
def urllib_urlretrieve_download_file(url, dest_path):
"""
* https://docs.python.org/2/library/urllib.html#urllib.urlretrieve
"""
(filename, headers) = urlllib.urlretrieve(url, dest_path)
return (url, filename)
# In[14]:
def deduplicate_on_attr(nodes, attr='image_basename'):
attrindex = collections.OrderedDict()
for node in nodes:
attrindex.setdefault(node[attr], [])
attrindex[node[attr]].append(node)
return attrindex
def check_for_key_collisions(dict_of_lists):
for name, _nodes in dict_of_lists.items():
if len(_nodes) > 1:
raise Exception(('duplicate filenames:')
(name, nodes))
attrindex = deduplicate_on_attr(goal_tiles, attr='image_basename')
check_for_key_collisions(attrindex)
#
IMG_DIR = DATA_DIR / 'images'
IMG_DIR.makedirs_p()
def download_goal_tile_images(nodes, img_path):
for node in nodes:
dest_path = img_path / node['image_basename']
source_url = node['image']
(url, dest) = requests_download_file(source_url, dest_path)
node['image_path'] = dest
print((node['n'], node['name']))
print((node['image_path']))
# time.sleep(1) # see: requests_cache
download_goal_tile_images(goal_tiles, IMG_DIR)
tiles_jsonld = goal_tiles_to_jsonld(goal_tiles)
print(json.dumps(tiles_jsonld, indent=2))
# In[15]:
#import jupyter.display as display
import IPython.display as display
display.Image(goal_tiles[0]['image_path'])
# In[16]:
import IPython.display
for tile in goal_tiles:
x = IPython.display.Image(tile['image_path'])
x
# In[17]:
import IPython.display
def display_goal_images():
for tile in goal_tiles:
yield IPython.display.Image(tile['image_path'])
x = list(display_goal_images())
#pp(x)
IPython.display.display(*x)
# In[18]:
import string
print(string.punctuation)
NOT_URI_CHARS = dict.fromkeys(string.punctuation + string.digits)
NOT_URI_CHARS.pop('-')
NOT_URI_CHARS.pop('_')
def _slugify(txt):
"""an ~approximate slugify function for human-readable URI #fragments"""
txt = txt.strip().lower()
chars = (
(c if c != ' ' else '-') for c in txt if
c not in NOT_URI_CHARS)
return u''.join(chars)
def _slugify_single_dash(txt):
"""
* unlike docutils, this function does not strip stopwords like 'and' and 'or'
TODO: locate this method in docutils
"""
def _one_dash_only(txt):
count = 0
for char in txt:
if char == '-':
count += 1
else:
if count:
yield '-'
yield char
count = 0
return u''.join(_one_dash_only(_slugify(txt)))
for node in goal_tiles:
node['name_numbered'] = "%d. %s" % (node['n'], node['name'])
node['slug_rst'] = _slugify_single_dash(node['name'])
node['slug_md'] = _slugify_single_dash(node['name'])
print_json_dumps(goal_tiles)
# In[19]:
import IPython.display
def display_goal_images():
for tile in goal_tiles:
yield IPython.display.Markdown("## %s" % tile['name_numbered'])
yield IPython.display.Image(tile['image_path'])
yield IPython.display.Markdown(tile['tweet_txt'].replace('##', '\##'))
x = list(display_goal_images())
#pp(x)
IPython.display.display(*x)
# In[20]:
TMPL_RST = """
The Global Goals
******************
.. contents::
{% for node in nodes %}
{{ node['name_numbered'] }}
======================================================
| {{ node['url'] }}
.. image:: {{ node['image'] }}{# node['image_path'] #}
:target: {{ node['url'] }}
:alt: {{ node['name'] }}
..
{{ node['tweet_txt'] }}
{% endfor %}
"""
tmpl_rst = jinja2.Template(TMPL_RST)
output_rst = tmpl_rst.render(nodes=goal_tiles)
print(output_rst)
# In[21]:
output_rst_path = DATA_DIR / 'globalgoals.rst'
with codecs.open(output_rst_path, 'w', encoding='utf-8') as f:
f.write(output_rst)
print("# wrote goals to %r" % output_rst_path)
# In[22]:
import docutils.core
output_rst_html = docutils.core.publish_string(output_rst, writer_name='html')
print(bs4.BeautifulSoup(output_rst_html).find(id='the-global-goals'))
# In[23]:
IPython.display.HTML(output_rst_html)
# In[24]:
TMPL_MD = """
# The Global Goals
**Contents:**
{% for node in nodes %}
* [{{ node['name_numbered'] }}](#{{ node['slug_md'] }})
{%- endfor %}
{% for node in nodes %}
## {{ node['name_numbered'] }}
{{ node['url'] }}
[![{{node['name_numbered']}}]({{ node['image'] }})]({{ node['url'] }})
> {{ node['tweet_txt'] }}
{% endfor %}
"""
tmpl_md = jinja2.Template(TMPL_MD)
output_markdown = tmpl_md.render(nodes=goal_tiles)
print(output_markdown)
# In[25]:
output_md_path = DATA_DIR / 'globalgoals.md'
with codecs.open(output_md_path, 'w', encoding='utf-8') as f:
f.write(output_markdown)
print("# wrote goals to %r" % output_md_path)
# In[26]:
IPython.display.Markdown(output_markdown)
# In[27]:
context = dict(nodes=goal_tiles)
# In[28]:
TMPL_HTML = """
<h1>The Global Goals</h1>
<h2>Contents:</h2>
{% for node in nodes %}
<li><a href="#{{node.slug_md}}">{{node.name_numbered}}</a></li>
{%- endfor %}
{% for node in nodes %}
<div class="goal-tile">
<h2><a name="#{{node.slug_md}}">{{ node.name_numbered }}</a></h2>
<a href="{{node.url}}">{{node.url}} </a>
<a href="{{node.url}}">
<img src="{{node.image}}" alt="{{node.name_numbered}}"/>{{node.url}} </a>
<div style="margin-left: 12px">
{{ node.tweet_txt }}
</div>
</div>
{% endfor %}
"""
tmpl_html = jinja2.Template(TMPL_HTML)
output_html = tmpl_html.render(**context)
print(output_html)
# In[29]:
output_html_path = DATA_DIR / 'globalgoals.html'
with codecs.open(output_html_path, 'w', encoding='utf-8') as f:
f.write(output_html)
print("# wrote goals to %r" % output_html_path)
# In[30]:
IPython.display.HTML(output_html)
# In[31]:
import jinja2
# TODO: prefix un:
TMPL_RDFA_HTML5 = ("""
<div prefix="schema: http://schema.org/
un: http://schema.un.org/#">
<h1>The Global Goals</h1>
<h2>Contents:</h2>
{%- for node in nodes %}
<li><a href="#{{node.slug_md}}">{{node.name_numbered}}</a></li>
{%- endfor %}
{% for node in nodes %}
<div class="goal-tile" resource="{{node.url}}" typeof="un:GlobalGoal">
<div style="display:none">
<meta property="schema:name">{{node.name}}</meta>
<meta property="schema:image">{{node.image}}</meta>
<meta property="#n">{{node.n}}</meta>
</div>
<h2><a name="#{{node.slug_md}}">{{ node.name_numbered }}</a></h2>
<a property="schema:url" href="{{node.url}}">{{node.url}} </a>
<a href="{{node.url}}">
<img src="{{node.image}}" alt="{{node.name_numbered}}"/>{{node.url}} </a>
<div style="margin-left: 12px">
{{ node.tweet_txt }}
</div>
</div>
{% endfor %}
</div>
"""
)
tmpl_rdfa_html5 = jinja2.Template(TMPL_RDFA_HTML5)
output_rdfa_html5 = tmpl_rdfa_html5.render(**context)
print(output_rdfa_html5)
# In[32]:
output_rdfa_html5_path = DATA_DIR / 'globalgoals.rdfa.html5.html'
with codecs.open(output_rdfa_html5_path, 'w', encoding='utf-8') as f:
f.write(output_rdfa_html5_path)
print("# wrote goals to %r" % output_rdfa_html5_path)
# In[33]:
IPython.display.HTML(output_rdfa_html5)
# In[34]:
# tmpl_html
# tmpl_rdfa_html5
import difflib
for line in difflib.unified_diff(
TMPL_HTML.splitlines(),
TMPL_RDFA_HTML5.splitlines()):
print(line)
| [
"wes@wrd.nu"
] | wes@wrd.nu |
12e691ff091406c9f6076d7c9c0f340cfa984fbe | 6822f0461381978d1cd85b82b48437621a0dfa5f | /python/Geek-00/代码/lesson06/demo0/demo0/spiders/spider.py | 734e1d88762c4fb0581ca2e967306787b5408ff5 | [] | no_license | iceycc/daydayup | 53eb0a6bf1878195695868701912e08730d08f17 | 91c6f547f80111dc5d45e172041437c3fffb5386 | refs/heads/master | 2023-08-10T10:14:49.139447 | 2023-07-26T01:53:08 | 2023-07-26T01:53:08 | 217,419,257 | 4 | 4 | null | null | null | null | UTF-8 | Python | false | false | 218 | py | # -*- coding: utf-8 -*-
import scrapy
class SpiderSpider(scrapy.Spider):
name = 'spider'
allowed_domains = ['example.com']
start_urls = ['http://example.com/']
def parse(self, response):
pass
| [
"w@icey.cc"
] | w@icey.cc |
fee2e7e85fd97f95bfea8e5a4c9bfbaf48c5d3df | e204623da7c836b95f209cc7fb357dc0b7f60548 | /meetings/admin.py | 0d6435eab6b99696f4439688f520fcfc68c0a66a | [] | no_license | juliocebrito/syfboyaca4gavantel | 9551db0a9b74dadf831362ceb0f685a482afa828 | c9e9cc5f591dddaa53e3d1fd3db50d16d34424d7 | refs/heads/master | 2022-04-30T00:06:57.239452 | 2019-08-05T15:12:23 | 2019-08-05T15:12:23 | 196,095,965 | 0 | 0 | null | 2022-04-22T22:00:52 | 2019-07-09T23:08:12 | JavaScript | UTF-8 | Python | false | false | 975 | py | from django.contrib import admin
from .models import Meeting, Point
class PointInline(admin.TabularInline):
model = Point
@admin.register(Meeting)
class MeetingAdmin(admin.ModelAdmin):
resource_class = Meeting
list_display = (
'id',
'date',
'type_meeting',
'state',
'sub_state',
'created_at',
'updated_at',
)
list_filter = ('state', 'sub_state', 'created_at', 'updated_at')
search_fields = ['id', 'date', 'type_meeting']
inlines = [PointInline]
@admin.register(Point)
class PointAdmin(admin.ModelAdmin):
resource_class = Point
list_display = (
'id',
'meeting',
'name',
'description',
'comments',
'point_state',
'state',
'sub_state',
'created_at',
'updated_at',
)
list_filter = ('state', 'sub_state', 'created_at', 'updated_at')
search_fields = ['id', 'meeting', 'name', 'point_state']
| [
"jucebridu@gmail.com"
] | jucebridu@gmail.com |
dc19ab8b235780639ad2feb8c4186df77242cd8a | 47fb4e962cf4a2fc85721faea0e7a764f4e443dc | /astrogrid/mwe.py | 276f36a12b96308d59d54628beecc1b49ca393a0 | [
"MIT"
] | permissive | jesaerys/astrogrid | d068e5b626dc3f7065d7bbbee3af98952891cfde | a6f7f92058c3b935d7274e97f8633f0b962b7ce8 | refs/heads/master | 2016-09-05T16:28:22.372053 | 2014-09-18T18:49:05 | 2014-09-18T18:49:05 | 20,024,189 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 15,428 | py | """
===============
`astrogrid.mwe`
===============
Mosaicking utilities.
"mwe" stands for `montage_wrapper` extension. Montage and `montage_wrapper`
are powerful and useful tools. The goal of this package is only to make
certain things in the Montage workflow a little easier.
Functions
---------
======== ==============
`mosaic` Make a mosaic.
======== ==============
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import astropy.io.fits
import montage_wrapper as montage
import numpy as np
import os
import shutil
from . import wcs
def mosaic(input_files, mosaic_file, work_dir, background_match=False,
cdelt=None, density=False, equinox=None, header=None,
level_only=False, north_aligned=False, postprocess=None,
preprocess=None, system=None, weights_file=None):
"""Make a mosiac.
High-level wrapper around several Montage operations similar to
`montage_wrapper.mosaic`. The main differences are 1) added support for
preprocessing the input images before reprojection and postprocessing
the final image after mosaicking, 2) options for using images in total
flux units instead of flux density (as assumed by Montage), 3) more of
the `montage_wrapper.mMakeHdr` keywords available for header creation,
and 4) the `whole` keyword for `montage_wrapper.mProjExec` is
automatically set to True when `background_match` is True. The latter
is important since backround matching behaves unreliably otherwise.
Parameters
----------
input_files : list or string
List of paths to the input images. This may also be the path to a
directory containing all input images, in which case `input_files`
will automatically be set to a list of all files in the directory
ending with ".fits".
mosaic_file : str
Path to the output mosaic file. The final mosaic always has the
same units as the `input_files` images.
work_dir : str
Path to the working directory for all intermediate files produced
by Montage. The directory has the following structure::
work_dir/
input/
Contains either symlinks to `input_files` or new files
depending on the `preprocess` and `density` keywords.
Assuming the `density` keyword has been set correctly, these
images will always be in flux density units.
reprojected/
The reprojected images.
differences/
Difference calculations for background matching (only if
`background_match` is True).
corrected/
Background-matched images (only if `background_match` is
True).
output/
The intermediate mosiac used to produce the final mosaic
file, depending on the `density` and `postprocess` keywords.
background_match : bool, optional
If True, match the background levels of the reprojected images
before mosaicking. Automatically sets ``whole = True`` in
`montage_wrapper.mProjExec`. Default is False.
cdelt : float, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
density : bool, optional
If True, the input images are in flux density units (i.e., signal
per unit pixel area). If False (default), the input images are
assumed to be in units of total flux, and are automatically scaled
to flux density before reprojection.
equinox : str, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
header : str, optional
Path to the template header file describing the output mosaic.
Default is None, in which case a template header is created
automatically using `montage_wrapper.mMakeHdr` and the `cdelt`,
`equinox`, `north_aligned`, and `system` keyword arguments.
level_only : bool, optional
See `montage_wrapper.mBgModel`. Ignored if `background_match` is
False. Default is False.
north_aligned : bool, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
postprocess, preprocess : function, optional
Functions for processing the raw input images before the input
density images are created (`preprocess`) and after the final
mosaic is created (`postprocess`). The function arguments should be
the image data array and the image header
(`astropy.io.fits.Header`), and the return values should be the
same. Default is None.
system : str, optional
See `header` and `montage_wrapper.mMakeHdr`. Default is None.
weights_file : str, optional
Path to output pixel weights file. Pixel weights are derived from
the final mosaic area file. Weights are normalized to 1, and
represent coverage of the mosaic area by the input images. Unlike
Montage area files, regions where the input images overlap are not
considered. Default is None.
Returns
-------
None
"""
# Get list of files if input_files is a directory name
if isinstance(input_files, basestring):
dirname = os.path.dirname(input_files)
input_files = [os.path.join(dirname, basename)
for basename in os.listdir(dirname)
if os.path.splitext(basename)[1] == '.fits']
# Create working directory
try:
os.makedirs(work_dir)
except OSError:
shutil.rmtree(work_dir)
os.makedirs(work_dir)
# Create input directory, populate it, and get image metadata
input_dir = os.path.join(work_dir, 'input')
os.mkdir(input_dir)
if preprocess or not density:
# Create new input files
for input_file in input_files:
data, hdr = astropy.io.fits.getdata(input_file, header=True)
if preprocess:
data, hdr = preprocess(data, hdr)
if not density:
# Convert total flux into flux density
dx, dy = wcs.calc_pixscale(hdr, ref='crpix').arcsec
pixarea = dx * dy # arcsec2
data /= pixarea
# Write
basename = os.path.basename(input_file)
basename = '_density'.join(os.path.splitext(basename))
new_input_file = os.path.join(input_dir, basename)
hdu = astropy.io.fits.PrimaryHDU(data, header=hdr)
hdu.writeto(new_input_file)
else:
# Symlink existing files
for input_file in input_files:
basename = os.path.basename(input_file)
new_input_file = os.path.join(input_dir, basename)
os.symlink(input_file, new_input_file)
input_table = os.path.join(input_dir, 'input.tbl')
montage.mImgtbl(input_dir, input_table, corners=True)
# Template header
if header is None:
template_header = os.path.join(work_dir, 'template.hdr')
montage.mMakeHdr(input_table, template_header, cdelt=cdelt,
equinox=equinox, north_aligned=north_aligned,
system=system)
else:
template_header = header
# Create reprojection directory, reproject, and get image metadata
proj_dir = os.path.join(work_dir, 'reprojected')
os.makedirs(proj_dir)
whole = True if background_match else False
stats_table = os.path.join(proj_dir, 'mProjExec_stats.log')
montage.mProjExec(input_table, template_header, proj_dir, stats_table,
raw_dir=input_dir, whole=whole)
reprojected_table = os.path.join(proj_dir, 'reprojected.tbl')
montage.mImgtbl(proj_dir, reprojected_table, corners=True)
# Background matching
if background_match:
diff_dir = os.path.join(work_dir, 'differences')
os.makedirs(diff_dir)
# Find overlaps
diffs_table = os.path.join(diff_dir, 'differences.tbl')
montage.mOverlaps(reprojected_table, diffs_table)
# Calculate differences between overlapping images
montage.mDiffExec(diffs_table, template_header, diff_dir,
proj_dir=proj_dir)
# Find best-fit plane coefficients
fits_table = os.path.join(diff_dir, 'fits.tbl')
montage.mFitExec(diffs_table, fits_table, diff_dir)
# Calculate corrections
corr_dir = os.path.join(work_dir, 'corrected')
os.makedirs(corr_dir)
corrections_table = os.path.join(corr_dir, 'corrections.tbl')
montage.mBgModel(reprojected_table, fits_table, corrections_table,
level_only=level_only)
# Apply corrections
montage.mBgExec(reprojected_table, corrections_table, corr_dir,
proj_dir=proj_dir)
img_dir = corr_dir
else:
img_dir = proj_dir
# Make mosaic
output_dir = os.path.join(work_dir, 'output')
os.makedirs(output_dir)
out_image = os.path.join(output_dir, 'mosaic.fits')
montage.mAdd(reprojected_table, template_header, out_image,
img_dir=img_dir, exact=True)
# Pixel areas and weights
if weights_file or not density:
area_file = '_area'.join(os.path.splitext(out_image))
area, hdr = astropy.io.fits.getdata(area_file, header=True) # steradians
area *= (180/np.pi*3600)**2 # arcsec2
dx, dy = wcs.calc_pixscale(hdr, ref='crpix').arcsec
pixarea = dx * dy # arcsec2
area = np.clip(area, 0, pixarea) # Don't care about overlaps
if weights_file:
weights = area / pixarea # Normalize to 1
hdu = astropy.io.fits.PrimaryHDU(weights, header=hdr)
try:
hdu.writeto(weights_file)
except IOError:
os.remove(weights_file)
hdu.writeto(weights_file)
# Write final mosaic
dirname = os.path.dirname(mosaic_file)
try:
os.makedirs(dirname)
except OSError:
pass
if postprocess or not density:
# Create new file
data, hdr = astropy.io.fits.getdata(out_image, header=True)
if not density:
# Convert flux density into total flux
data *= area
if postprocess:
data, hdr = postprocess(data, hdr)
# Write
hdu = astropy.io.fits.PrimaryHDU(data, header=hdr)
try:
hdu.writeto(mosaic_file)
except IOError:
os.remove(mosaic_file)
hdu.writeto(mosaic_file)
else:
# Move existing file
os.rename(out_image, mosaic_file)
return
"""
Notes
-----
- Input and reprojected maps were compared for 21 PHAT bricks. For a
given brick, the percent difference between the pixel sum of the
native map and the pixel sum of the reprojected map was less than
~0.01%. The average percent difference was ~0.001%.
- mProjExec and mProject produce nearly identical results (within
~0.01%).
- Settings that affect reprojection: mProject has the 'z' flag, which
controls the drizzle factor. 1 seems to be the default, and appears
to give the best results anyway so there is no reason to change it.
mProjExec doesn't really have any settings that change the
reprojection results.
- Pixel area varies slightly accross brick 15 in both the native and
the reprojected images. The effect causes only ~0.001% difference
between the minimum and maximum areas, however, so the pixels can be
safely treated as having constant area.
- Three pixel area calculation methods were tested: 1) calculate the
areas of all pixels from the coordinates of their corners assuming
spherical rectangles, 2) calculate the areas of all pixels from their
x and y scales assuming planar rectangles, and 3) same as 2, but only
calculate the area for the reference pixel and assume that value for
all of the pixels. All three area calculation methods agree to within
~0.01% to ~0.001%. Might as well just use the simplest method (3).
"""
def _montage_test():
# create density images
input_dir = os.path.dirname(density_files[0])
# image metadata
meta1_file = os.path.join(input_dir, 'meta1.tbl')
montage.mImgtbl(input_dir, meta1_file, corners=True)
# make header
#lon, lat = [], []
#for density_file in density_files:
# data, hdr = astropy.io.fits.getdata(density_file, header=True)
# wcs = astropy.wcs.WCS(hdr)
# x1, y1 = 0.5, 0.5
# y2, x2 = data.shape
# x2, y2 = x2 + 0.5, y2 + 0.5
# x, y = [x1, x2, x2, x1], [y1, y1, y2, y2]
# ln, lt = wcs.wcs_pix2world(x, y, 1)
# lon += list(ln)
# lat += list(lt)
#lon1, lon2 = np.min(lon), np.max(lon)
#lat1, lat2 = np.min(lat), np.max(lat)
hdr_file = os.path.join(os.path.dirname(input_dir), 'test.hdr')
montage.mMakeHdr(meta1_file, hdr_file)
# reproject
proj_dir = os.path.dirname(proj_files[0])
safe_mkdir(proj_dir)
stats_file = os.path.join(proj_dir, 'stats.tbl')
montage.mProjExec(meta1_file, hdr_file, proj_dir, stats_file,
raw_dir=input_dir, exact=True)
# image metadata
meta2_file = os.path.join(proj_dir, 'meta2.tbl')
montage.mImgtbl(proj_dir, meta2_file, corners=True)
# Background modeling
diff_dir = os.path.join(os.path.dirname(proj_dir), 'difference')
safe_mkdir(diff_dir)
diff_file = os.path.join(diff_dir, 'diffs.tbl')
montage.mOverlaps(meta2_file, diff_file)
montage.mDiffExec(diff_file, hdr_file, diff_dir, proj_dir)
fits_file = os.path.join(diff_dir, 'fits.tbl')
montage.mFitExec(diff_file, fits_file, diff_dir)
# Background matching
corr_dir = os.path.join(os.path.dirname(proj_dir), 'correct')
safe_mkdir(corr_dir)
corr_file = os.path.join(corr_dir, 'corrections.tbl')
montage.mBgModel(meta2_file, fits_file, corr_file, level_only=False)
montage.mBgExec(meta2_file, corr_file, corr_dir, proj_dir=proj_dir)
# Native mosaic
projadd_file = config.path('{:s}.reproject.add'.format(kind))
projadd_dir, filename = os.path.split(projadd_file)
filename, ext = os.path.splitext(filename)
filename = '{0:s}_native{1:s}'.format(filename, ext)
projaddnative_file = os.path.join(projadd_dir, filename)
safe_mkdir(projadd_dir)
montage.mAdd(meta2_file, hdr_file, projaddnative_file, img_dir=corr_dir, exact=True)
# Reproject to final header
header_file = config.path('{:s}.hdr'.format(kind))
montage.mProject(projaddnative_file, projadd_file, header_file)
# Postprocess
data, hdr = astropy.io.fits.getdata(projaddnative_file, header=True)
x1, x2 = 900, 1900
y1, y2 = 3000, 4500
val = np.mean(data[y1:y2,x1:x2])
data, hdr = astropy.io.fits.getdata(projadd_file, header=True)
data = data - val
areaadd_file = config.path('{:s}.area.add'.format(kind))
area = astropy.io.fits.getdata(areaadd_file) * (180/np.pi*3600)**2 # arcsec2
data = data * area
add_file = config.path('{:s}.add'.format(kind))
dirname = os.path.dirname(add_file)
safe_mkdir(dirname)
if os.path.exists(add_file):
os.remove(add_file)
hdu = astropy.io.fits.PrimaryHDU(data, header=hdr)
hdu.writeto(add_file)
| [
"jacob.simones@gmail.com"
] | jacob.simones@gmail.com |
dc9c1fe37255938851aaf3a338906fbb2638fc4b | fa93e53a9eee6cb476b8998d62067fce2fbcea13 | /devel/.private/pal_navigation_msgs/lib/python2.7/dist-packages/pal_navigation_msgs/msg/_Emergency.py | 8a07633f4c000d1376f965e9af610397e31a6813 | [] | no_license | oyetripathi/ROS_conclusion_project | 2947ee2f575ddf05480dabc69cf8af3c2df53f73 | 01e71350437d57d8112b6cec298f89fc8291fb5f | refs/heads/master | 2023-06-30T00:38:29.711137 | 2021-08-05T09:17:54 | 2021-08-05T09:17:54 | 392,716,311 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 6,296 | py | # This Python file uses the following encoding: utf-8
"""autogenerated by genpy from pal_navigation_msgs/Emergency.msg. Do not edit."""
import codecs
import sys
python3 = True if sys.hexversion > 0x03000000 else False
import genpy
import struct
import std_msgs.msg
class Emergency(genpy.Message):
_md5sum = "a23e1ed551a213a5d03f1cf6db037717"
_type = "pal_navigation_msgs/Emergency"
_has_header = False # flag to mark the presence of a Header object
_full_text = """# Emergency stop msg
bool data
bool forward
bool backward
std_msgs/String[] msgs
================================================================================
MSG: std_msgs/String
string data
"""
__slots__ = ['data','forward','backward','msgs']
_slot_types = ['bool','bool','bool','std_msgs/String[]']
def __init__(self, *args, **kwds):
"""
Constructor. Any message fields that are implicitly/explicitly
set to None will be assigned a default value. The recommend
use is keyword arguments as this is more robust to future message
changes. You cannot mix in-order arguments and keyword arguments.
The available fields are:
data,forward,backward,msgs
:param args: complete set of field values, in .msg order
:param kwds: use keyword arguments corresponding to message field names
to set specific fields.
"""
if args or kwds:
super(Emergency, self).__init__(*args, **kwds)
# message fields cannot be None, assign default values for those that are
if self.data is None:
self.data = False
if self.forward is None:
self.forward = False
if self.backward is None:
self.backward = False
if self.msgs is None:
self.msgs = []
else:
self.data = False
self.forward = False
self.backward = False
self.msgs = []
def _get_types(self):
"""
internal API method
"""
return self._slot_types
def serialize(self, buff):
"""
serialize message into buffer
:param buff: buffer, ``StringIO``
"""
try:
_x = self
buff.write(_get_struct_3B().pack(_x.data, _x.forward, _x.backward))
length = len(self.msgs)
buff.write(_struct_I.pack(length))
for val1 in self.msgs:
_x = val1.data
length = len(_x)
if python3 or type(_x) == unicode:
_x = _x.encode('utf-8')
length = len(_x)
buff.write(struct.Struct('<I%ss'%length).pack(length, _x))
except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self)))))
except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self)))))
def deserialize(self, str):
"""
unpack serialized message in str into this message instance
:param str: byte array of serialized message, ``str``
"""
if python3:
codecs.lookup_error("rosmsg").msg_type = self._type
try:
if self.msgs is None:
self.msgs = None
end = 0
_x = self
start = end
end += 3
(_x.data, _x.forward, _x.backward,) = _get_struct_3B().unpack(str[start:end])
self.data = bool(self.data)
self.forward = bool(self.forward)
self.backward = bool(self.backward)
start = end
end += 4
(length,) = _struct_I.unpack(str[start:end])
self.msgs = []
for i in range(0, length):
val1 = std_msgs.msg.String()
start = end
end += 4
(length,) = _struct_I.unpack(str[start:end])
start = end
end += length
if python3:
val1.data = str[start:end].decode('utf-8', 'rosmsg')
else:
val1.data = str[start:end]
self.msgs.append(val1)
return self
except struct.error as e:
raise genpy.DeserializationError(e) # most likely buffer underfill
def serialize_numpy(self, buff, numpy):
"""
serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module
"""
try:
_x = self
buff.write(_get_struct_3B().pack(_x.data, _x.forward, _x.backward))
length = len(self.msgs)
buff.write(_struct_I.pack(length))
for val1 in self.msgs:
_x = val1.data
length = len(_x)
if python3 or type(_x) == unicode:
_x = _x.encode('utf-8')
length = len(_x)
buff.write(struct.Struct('<I%ss'%length).pack(length, _x))
except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self)))))
except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self)))))
def deserialize_numpy(self, str, numpy):
"""
unpack serialized message in str into this message instance using numpy for array types
:param str: byte array of serialized message, ``str``
:param numpy: numpy python module
"""
if python3:
codecs.lookup_error("rosmsg").msg_type = self._type
try:
if self.msgs is None:
self.msgs = None
end = 0
_x = self
start = end
end += 3
(_x.data, _x.forward, _x.backward,) = _get_struct_3B().unpack(str[start:end])
self.data = bool(self.data)
self.forward = bool(self.forward)
self.backward = bool(self.backward)
start = end
end += 4
(length,) = _struct_I.unpack(str[start:end])
self.msgs = []
for i in range(0, length):
val1 = std_msgs.msg.String()
start = end
end += 4
(length,) = _struct_I.unpack(str[start:end])
start = end
end += length
if python3:
val1.data = str[start:end].decode('utf-8', 'rosmsg')
else:
val1.data = str[start:end]
self.msgs.append(val1)
return self
except struct.error as e:
raise genpy.DeserializationError(e) # most likely buffer underfill
_struct_I = genpy.struct_I
def _get_struct_I():
global _struct_I
return _struct_I
_struct_3B = None
def _get_struct_3B():
global _struct_3B
if _struct_3B is None:
_struct_3B = struct.Struct("<3B")
return _struct_3B
| [
"sandeepan.ghosh.ece20@itbhu.ac.in"
] | sandeepan.ghosh.ece20@itbhu.ac.in |
e0718b4f12184db6ea4c15fbd4918f1f3212a582 | 8e39a4f4ae1e8e88d3b2d731059689ad5b201a56 | /lib32-apps/lib32-libXext/lib32-libXext-1.3.3.py | 773e23325d398e9fbe0d784a04ec5d4ef87625a4 | [] | no_license | wdysln/new | d5f5193f81a1827769085932ab7327bb10ef648e | b643824b26148e71859a1afe4518fe05a79d333c | refs/heads/master | 2020-05-31T00:12:05.114056 | 2016-01-04T11:38:40 | 2016-01-04T11:38:40 | 37,287,357 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 359 | py | metadata = """
summary @ 11 miscellaneous extensions library
homepage @ http://xorg.freedesktop.org/
license @ MIT
src_url @ http://xorg.freedesktop.org/releases/individual/lib/libXext-$version.tar.bz2
arch @ ~x86_64
"""
depends = """
runtime @ sys-libs/glibc x11-libs/libX11 x11-proto/xextproto
"""
srcdir = "libXext-%s" % version
get("main/lib32_utils")
| [
"zirkovandersen@gmail.com"
] | zirkovandersen@gmail.com |
0ee0628059ce0bbdb5a337a48cab93a60ec822f8 | 468f7b1d7639e2465b2ba4e0f960c8a75a10eb89 | /kerasAC/cross_validate.py | 8322e8d37895ddfb25a8c3cf60d3670904215752 | [
"MIT"
] | permissive | soumyakundu/kerasAC | 874a7453044050afa3198c5bd3c34185b53ea571 | f692abf1c6003a9f0d917117f3579a0746ed3b5a | refs/heads/master | 2020-04-23T04:34:10.659657 | 2019-02-14T23:01:42 | 2019-02-14T23:01:42 | 156,909,046 | 0 | 0 | null | 2019-02-15T18:13:21 | 2018-11-09T19:32:57 | Python | UTF-8 | Python | false | false | 6,381 | py | from .splits import *
from .config import args_object_from_args_dict
from .train import *
from .predict import *
from .interpret import *
import argparse
import pdb
def parse_args():
parser=argparse.ArgumentParser(add_help=True)
parser.add_argument("--multi_gpu",action="store_true",default=False)
parser.add_argument("--assembly",default="hg19")
parser.add_argument("--data_path",help="path that stores training/validation/test data")
parser.add_argument("--model_hdf5",required=True)
parser.add_argument("--batch_size",type=int,default=1000)
parser.add_argument("--init_weights",default=None)
parser.add_argument("--ref_fasta",default="/mnt/data/annotations/by_release/hg19.GRCh37/hg19.genome.fa")
parser.add_argument("--w1_w0_file",default=None)
parser.add_argument("--save_w1_w0", default=None,help="output text file to save w1 and w0 to")
parser.add_argument("--weighted",action="store_true")
parser.add_argument('--w1',nargs="*", type=float, default=None)
parser.add_argument('--w0',nargs="*", type=float, default=None)
parser.add_argument("--from_checkpoint_weights",default=None)
parser.add_argument("--from_checkpoint_arch",default=None)
parser.add_argument("--num_tasks",required=True,type=int)
parser.add_argument("--num_train",type=int,default=700000)
parser.add_argument("--num_valid",type=int,default=150000)
#add functionality to train on individuals' allele frequencies
parser.add_argument("--vcf_file",default=None)
parser.add_argument("--global_vcf",action="store_true")
parser.add_argument("--revcomp",action="store_true")
parser.add_argument("--epochs",type=int,default=40)
parser.add_argument("--patience",type=int,default=3)
parser.add_argument("--patience_lr",type=int,default=2,help="number of epochs with no drop in validation loss after which to reduce lr")
parser.add_argument("--architecture_spec",type=str,default="basset_architecture_multitask")
parser.add_argument("--architecture_from_file",type=str,default=None)
parser.add_argument("--tensorboard",action="store_true")
parser.add_argument("--tensorboard_logdir",default="logs")
parser.add_argument("--squeeze_input_for_gru",action="store_true")
parser.add_argument("--seed",type=int,default=1234)
parser.add_argument("--train_upsample", type=float, default=None)
parser.add_argument("--valid_upsample", type=float, default=None)
parser.add_argument("--threads",type=int,default=1)
parser.add_argument("--max_queue_size",type=int,default=100)
parser.add_argument('--weights',help='weights file for the model')
parser.add_argument('--yaml',help='yaml file for the model')
parser.add_argument('--json',help='json file for the model')
parser.add_argument('--predict_chroms',default=None)
parser.add_argument('--data_hammock',help='input file is in hammock format, with unique id for each peak')
parser.add_argument('--variant_bed')
parser.add_argument('--predictions_pickle',help='name of pickle to save predictions',default=None)
parser.add_argument('--accuracy_metrics_file',help='file name to save accuracy metrics',default=None)
parser.add_argument('--predictions_pickle_to_load',help="if predictions have already been generated, provide a pickle with them to just compute the accuracy metrics",default=None)
parser.add_argument('--background_freqs',default=None)
parser.add_argument('--flank',default=500,type=int)
parser.add_argument('--mask',default=10,type=int)
parser.add_argument('--center_on_summit',default=False,action='store_true',help="if this is set to true, the peak will be centered at the summit (must be last entry in bed file or hammock) and expanded args.flank to the left and right")
parser.add_argument("--interpret_chroms",nargs="*")
parser.add_argument("--interpretation_outf",default=None)
parser.add_argument("--method",choices=['gradxinput','deeplift'],default="deeplift")
parser.add_argument('--task_id',type=int)
parser.add_argument('--chromsizes',default='/mnt/data/annotations/by_release/hg19.GRCh37/hg19.chrom.sizes')
parser.add_argument("--interpret",action="store_true",default=False)
return parser.parse_args()
def cross_validate(args):
if type(args)==type({}):
args=args_object_from_args_dict(args)
#run training on each of the splits
if args.assembly not in splits:
raise Exception("Unsupported genome assembly:"+args.assembly+". Supported assemblies include:"+str(splits.keys())+"; add splits for this assembly to splits.py file")
args_dict=vars(args)
print(args_dict)
base_model_file=str(args_dict['model_hdf5'])
base_accuracy_file=str(args_dict['accuracy_metrics_file'])
base_interpretation=str(args_dict['interpretation_outf'])
base_predictions_pickle=str(args_dict['predictions_pickle'])
for split in splits[args.assembly]:
print("Starting split:"+str(split))
test_chroms=splits[args.assembly][split]['test']
validation_chroms=splits[args.assembly][split]['valid']
train_chroms=list(set(chroms[args.assembly])-set(test_chroms+validation_chroms))
#convert args to dict
args_dict=vars(args)
args_dict['train_chroms']=train_chroms
args_dict['validation_chroms']=validation_chroms
#set the training arguments specific to this fold
args_dict['model_hdf5']=base_model_file+"."+str(split)
print("Training model")
train(args_dict)
#set the prediction arguments specific to this fold
if args.save_w1_w0!=None:
args_dict["w1_w0_file"]=args.save_w1_w0
args_dict['accuracy_metrics_file']=base_accuracy_file+"."+str(split)
args_dict['predictions_pickle']=base_predictions_pickle+"."+str(split)
args_dict['predict_chroms']=test_chroms
print("Calculating predictions on the test fold")
predict(args_dict)
if args.interpret==True:
args_dict['interpret_chroms']=test_chroms
args_dict['interpretation_outf']=base_interpretation+'.'+str(split)
print("Running interpretation on the test fold")
interpret(args_dict)
def main():
args=parse_args()
cross_validate(args)
if __name__=="__main__":
main()
| [
"annashcherbina@gmail.com"
] | annashcherbina@gmail.com |
bbf6e7137aa181623ce45aa134f2a2b6292bbae1 | 91538738e746ec7bda3237186501780e7223c872 | /pattern92.py | f525231a457277fe5a6b656b3d22732bda6195b1 | [] | no_license | sub7ata/Pattern-Programs-in-Python | 71ab67a20c5347881625fc75a32eb69a211f7a7a | a5758460ed3a901f2faa7517fa80ab3e496b2276 | refs/heads/master | 2020-07-05T18:05:08.396103 | 2019-11-21T15:57:42 | 2019-11-21T15:57:42 | 202,722,723 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 367 | py | """
Example
Enter a number:5
5 5
4 4
3 3
2 2
1
"""
num = int(input("Enter a number:"))
for i in range(1,num+1):
print(" "*(i-1),end="")
for j in range(i,i+1):
print(num+1-i,end=" ")
if i<=4:
print(" "*(2*num-2*i-2),end="")
for k in range(i,i+1):
print(num+1-i,end=" ")
print() | [
"sub7ata@gmail.com"
] | sub7ata@gmail.com |
a1ee9dd36bec6ac5b2c5fcfb664c79cf089b0fd3 | 944d3c07a3e0edb65f41a4a302f494e6b44e3f45 | /nntoolbox/callbacks/lookahead.py | d87b7f399790c6d799238d7cf9b99033b6816ce0 | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | nhatsmrt/nn-toolbox | acbc753d6081ed1e2ed91ac0fd3343287c78a094 | 689b9924d3c88a433f8f350b89c13a878ac7d7c3 | refs/heads/master | 2022-12-05T21:11:23.725346 | 2021-08-15T17:03:34 | 2021-08-15T17:03:34 | 189,150,286 | 19 | 3 | Apache-2.0 | 2023-09-08T19:29:53 | 2019-05-29T04:25:16 | Python | UTF-8 | Python | false | false | 2,535 | py | from .callbacks import Callback
from ..utils import copy_model, get_device
from typing import Dict, Any
from torch.nn import Module
__all__ = ['LookaheadOptimizer']
class LookaheadOptimizer(Callback):
"""
Lookahead Optimizer: Keep track of a set of "slow weights", which only update periodically. (UNTESTED)
References:
Michael R. Zhang, James Lucas, Geoffrey Hinton, Jimmy Ba. "Lookahead Optimizer: k steps forward, 1 step back."
https://arxiv.org/abs/1907.08610
"""
def __init__(
self, step_size: float=0.5, update_every: int=1, timescale: str="iter", device=get_device()
):
"""
https://arxiv.org/pdf/1803.05407.pdf
:param model: the model currently being trained
:param step_size: the stepsize for slow weight update
:param average_after: the first epoch to start averaging
:param update_every: how many epochs/iters between each average update
"""
assert timescale == "epoch" or timescale == "iter"
self.step_size = step_size
self._update_every = update_every
self._timescale = timescale
self._device = device
def on_train_begin(self):
self._model = self.learner._model
self._model_slow = copy_model(self._model).to(self._device)
def on_epoch_end(self, logs: Dict[str, Any]) -> bool:
if self._timescale == "epoch":
if logs["epoch"] % self._update_every == 0:
self.update_slow_weights()
print("Update slow weights after epoch " + str(logs["epoch"]))
return False
def on_batch_end(self, logs: Dict[str, Any]):
if self._timescale == "iter":
if logs["iter_cnt"] % self._update_every == 0:
self.update_slow_weights()
print("Update slow weights after iteration " + str(logs["iter_cnt"]))
def on_train_end(self):
self._model_slow.to(self.learner._device)
for inputs, labels in self.learner._train_data:
self._model_slow(inputs.to(self.learner._device))
self.learner._model = self._model_slow
def update_slow_weights(self):
for model_p, slow_p in zip(self._model.parameters(), self._model_slow.parameters()):
slow_p.data.add_(self.step_size * (model_p.data.to(slow_p.data.dtype) - slow_p.data))
def get_final_model(self) -> Module:
"""
Return the post-training average model
:return: the averaged model
"""
return self._model_slow
| [
"nhatsmrt@uw.edu"
] | nhatsmrt@uw.edu |
8d53cbcccb8f3553634fea7794ccdadc976c14f3 | e6ebf40ceae0bdf4377cb56a702617243e1afa3f | /Api_liliang/venv/Lib/site-packages/tests/test_suds.py | 856ee664787fd0ceaa2079b23d86b93215f0ce30 | [] | no_license | liliangyuzhou/api | 0c94b8ecff6724943a1d2e5f98739c3b8820366e | 11a4aeb608396bdd1f80399f5a6fabbcc80d725a | refs/heads/master | 2020-06-24T14:37:18.091642 | 2019-07-26T09:34:53 | 2019-07-26T09:34:53 | 198,988,563 | 7 | 0 | null | null | null | null | UTF-8 | Python | false | false | 80,619 | py | # -*- coding: utf-8 -*-
# This program is free software; you can redistribute it and/or modify
# it under the terms of the (LGPL) GNU Lesser General Public License as
# published by the Free Software Foundation; either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library Lesser General Public License for more details at
# ( http://www.gnu.org/licenses/lgpl.html ).
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
# written by: Jurko Gospodnetić ( jurko.gospodnetic@pke.hr )
"""
General suds Python library unit tests.
Implemented using the 'pytest' testing framework.
This whole module should be refactored into more specialized modules as more
tests get added to it and it acquires more structure.
"""
if __name__ == "__main__":
from . import __init__
__init__.runUsingPyTest(globals())
import suds
import tests
import pytest
import re
import xml.sax
# TODO: Update the current choice parameter handling implementation to make
# this test pass.
@pytest.mark.xfail
def test_choice_parameter_implementation_inconsistencies():
"""
Choice parameter support implementation needs to be cleaned up.
If you declare a message part's element of a simple type X, or you define
it as a complex type having a single member of type X, and suds has been
configured to automatically unwrap such single-member complex types, the
web service proxy object's constructed function declarations should match.
They should both accept a single parameter of type X.
However the current choice support implementation causes only the 'complex'
case to get an additional 'choice' flag information to be included in the
constructed parameter definition structure.
"""
client = lambda x, y : tests.client_from_wsdl(tests.wsdl_input(x, y))
client_simple_short = client("""\
<xsd:element name="Elemento" type="xsd:string" />""", "Elemento")
client_simple_long = client("""\
<xsd:element name="Elemento">
<xsd:simpleType>
<xsd:restriction base="xsd:string" />
</xsd:simpleType>
</xsd:element>""", "Elemento")
client_complex_wrapped = client("""\
<xsd:element name="Wrapper">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="Elemento" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>""", "Wrapper")
method_param = lambda x : x.sd[0].ports[0][1][0][1][0]
method_param_simple_short = method_param(client_simple_short)
method_param_simple_long = method_param(client_simple_long)
method_param_complex_wrapped = method_param(client_complex_wrapped)
assert len(method_param_simple_short) == len(method_param_simple_long)
assert len(method_param_simple_long) == len(method_param_complex_wrapped)
def test_converting_client_to_string_must_not_raise_an_exception():
client = tests.client_from_wsdl(suds.byte_str(
"<?xml version='1.0' encoding='UTF-8'?><root />"))
str(client)
def test_converting_metadata_to_string():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="AAA">
<xsd:sequence>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
<xsd:element name="u3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:schema>
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
# Metadata with empty content.
metadata = client.wsdl.__metadata__
assert len(metadata) == 0
assert "<empty>" == str(metadata)
# Metadata with non-empty content.
metadata = client.factory.create("AAA").__metadata__
assert len(metadata) == 2
metadata_string = str(metadata)
assert re.search(" sxtype = ", metadata_string)
assert re.search(" ordering\[\] = ", metadata_string)
def test_empty_invalid_wsdl(monkeypatch):
wsdl = suds.byte_str("")
monkeypatch.delitem(locals(), "e", False)
e = pytest.raises(xml.sax.SAXParseException, tests.client_from_wsdl, wsdl)
assert e.value.getMessage() == "no element found"
def test_empty_valid_wsdl():
client = tests.client_from_wsdl(suds.byte_str(
"<?xml version='1.0' encoding='UTF-8'?><root />"))
assert not client.wsdl.services, "No service definitions must be read " \
"from an empty WSDL."
def test_enumeration_type_string_should_contain_its_value():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:simpleType name="AAA">
<xsd:restriction base="xsd:string">
<xsd:enumeration value="One" />
<xsd:enumeration value="Two" />
<xsd:enumeration value="Thirty-Two" />
</xsd:restriction>
</xsd:simpleType>
</xsd:schema>
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
enumeration_data = client.wsdl.schema.types["AAA", "my-namespace"]
# Legend:
# eX - enumeration element.
# aX - ancestry for the enumeration element.
(e1, a1), (e2, a2), (e3, a3) = enumeration_data
assert isinstance(e1, suds.xsd.sxbasic.Enumeration)
assert isinstance(e2, suds.xsd.sxbasic.Enumeration)
assert isinstance(e3, suds.xsd.sxbasic.Enumeration)
assert e1.name == "One"
assert e2.name == "Two"
assert e3.name == "Thirty-Two"
# Python 3 output does not include a trailing L after long integer
# output, while Python 2 does. For example: 0x12345678 is output as
# 0x12345678L in Python 2 and simply as 0x12345678 in Python 3.
assert re.match('<Enumeration:0x[0-9a-f]+L? name="One" />$', e1.str())
assert re.match('<Enumeration:0x[0-9a-f]+L? name="Two" />$', e2.str())
assert re.match('<Enumeration:0x[0-9a-f]+L? name="Thirty-Two" />$',
e3.str())
def test_function_parameters_global_sequence_in_a_sequence():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="UngaBunga">
<xsd:sequence>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
<xsd:element name="u3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
<xsd:element name="Elemento">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2" type="UngaBunga" />
<xsd:element name="x3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:Elemento" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert len(service.types) == 1
# Method parameters as read from the service definition.
assert len(service.params) == 3
assert service.params[0][0].name == "x1"
assert service.params[0][0].type == _string_type
assert isinstance(service.params[0][1], suds.xsd.sxbuiltin.XString)
assert service.params[1][0].name == "x2"
assert service.params[1][0].type == ("UngaBunga", "my-namespace")
assert isinstance(service.params[1][1], suds.xsd.sxbasic.Complex)
assert service.params[2][0].name == "x3"
assert service.params[2][0].type == _string_type
assert isinstance(service.params[2][1], suds.xsd.sxbuiltin.XString)
# Method parameters as read from a method object.
assert len(service.ports) == 1
port, methods = service.ports[0]
assert len(methods) == 1
method_name, method_params = methods[0]
assert method_name == "f"
assert len(method_params) == 3
assert method_params[0][0] == "x1"
assert method_params[0][1] is service.params[0][0]
assert method_params[1][0] == "x2"
assert method_params[1][1] is service.params[1][0]
assert method_params[2][0] == "x3"
assert method_params[2][1] is service.params[2][0]
def test_function_parameters_local_choice():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="Elemento">
<xsd:complexType>
<xsd:choice>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
</xsd:choice>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:Elemento" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert not service.types
# Method parameters as read from the service definition.
assert len(service.params) == 2
assert service.params[0][0].name == "u1"
assert service.params[0][0].type == _string_type
assert isinstance(service.params[0][1], suds.xsd.sxbuiltin.XString)
assert service.params[1][0].name == "u2"
assert service.params[1][0].type == _string_type
assert isinstance(service.params[1][1], suds.xsd.sxbuiltin.XString)
# Method parameters as read from a method object.
assert len(service.ports) == 1
port, methods = service.ports[0]
assert len(methods) == 1
method_name, method_params = methods[0]
assert method_name == "f"
assert len(method_params) == 2
assert method_params[0][0] == "u1"
assert method_params[0][1] is service.params[0][0]
assert method_params[1][0] == "u2"
assert method_params[1][1] is service.params[1][0]
# Construct method parameter element object.
paramOut = client.factory.create("Elemento")
_assert_dynamic_type(paramOut, "Elemento")
assert not paramOut.__keylist__
def test_function_parameters_local_choice_in_a_sequence():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="Elemento">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2">
<xsd:complexType>
<xsd:choice>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
<xsd:element name="u3" type="xsd:string" />
</xsd:choice>
</xsd:complexType>
</xsd:element>
<xsd:element name="x3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:Elemento" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert not service.types
# Method parameters as read from the service definition.
assert len(service.params) == 3
assert service.params[0][0].name == "x1"
assert service.params[0][0].type == _string_type
assert isinstance(service.params[0][1], suds.xsd.sxbuiltin.XString)
assert service.params[1][0].name == "x2"
assert service.params[1][0].type is None
assert isinstance(service.params[1][1], suds.xsd.sxbasic.Element)
assert service.params[2][0].name == "x3"
assert service.params[2][0].type == _string_type
assert isinstance(service.params[2][1], suds.xsd.sxbuiltin.XString)
# Method parameters as read from a method object.
assert len(service.ports) == 1
port, methods = service.ports[0]
assert len(methods) == 1
method_name, method_params = methods[0]
assert method_name == "f"
assert len(method_params) == 3
assert method_params[0][0] == "x1"
assert method_params[0][1] is service.params[0][0]
assert method_params[1][0] == "x2"
assert method_params[1][1] is service.params[1][0]
assert method_params[2][0] == "x3"
assert method_params[2][1] is service.params[2][0]
# Construct method parameter element object.
paramOut = client.factory.create("Elemento")
_assert_dynamic_type(paramOut, "Elemento")
assert paramOut.x1 is None
_assert_dynamic_type(paramOut.x2, "x2")
assert not paramOut.x2.__keylist__
assert paramOut.x3 is None
# Construct method parameter objects with a locally defined type.
paramIn = client.factory.create("Elemento.x2")
_assert_dynamic_type(paramIn, "x2")
assert not paramOut.x2.__keylist__
assert paramIn is not paramOut.x2
def test_function_parameters_local_sequence_in_a_sequence():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="Elemento">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
<xsd:element name="u3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
<xsd:element name="x3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:Elemento" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert not service.types
# Method parameters as read from the service definition.
assert len(service.params) == 3
assert service.params[0][0].name == "x1"
assert service.params[0][0].type == _string_type
assert isinstance(service.params[0][1], suds.xsd.sxbuiltin.XString)
assert service.params[1][0].name == "x2"
assert service.params[1][0].type is None
assert isinstance(service.params[1][1], suds.xsd.sxbasic.Element)
assert service.params[2][0].name == "x3"
assert service.params[2][0].type == _string_type
assert isinstance(service.params[2][1], suds.xsd.sxbuiltin.XString)
# Method parameters as read from a method object.
assert len(service.ports) == 1
port, methods = service.ports[0]
assert len(methods) == 1
method_name, method_params = methods[0]
assert method_name == "f"
assert len(method_params) == 3
assert method_params[0][0] == "x1"
assert method_params[0][1] is service.params[0][0]
assert method_params[1][0] == "x2"
assert method_params[1][1] is service.params[1][0]
assert method_params[2][0] == "x3"
assert method_params[2][1] is service.params[2][0]
# Construct method parameter element object.
paramOut = client.factory.create("Elemento")
_assert_dynamic_type(paramOut, "Elemento")
assert paramOut.x1 is None
_assert_dynamic_type(paramOut.x2, "x2")
assert paramOut.x2.u1 is None
assert paramOut.x2.u2 is None
assert paramOut.x2.u3 is None
assert paramOut.x3 is None
# Construct method parameter objects with a locally defined type.
paramIn = client.factory.create("Elemento.x2")
_assert_dynamic_type(paramIn, "x2")
assert paramIn.u1 is None
assert paramIn.u2 is None
assert paramIn.u3 is None
assert paramIn is not paramOut.x2
def test_function_parameters_sequence_in_a_choice():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="Choice">
<xsd:complexType>
<xsd:choice>
<xsd:element name="a1" type="xsd:string" />
<xsd:element name="sequence">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="e1" type="xsd:string" />
<xsd:element name="e2" type="xsd:string" />
<xsd:element name="e3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
<xsd:element name="a2" type="xsd:string" />
</xsd:choice>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:Choice" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
# Input #1.
request = _construct_SOAP_request(client, 'f', a1="Wackadoodle")
assert tests.compare_xml_to_string(request, """\
<?xml version="1.0" encoding="UTF-8"?>
<SOAP-ENV:Envelope xmlns:ns0="my-namespace" xmlns:ns1="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:SOAP-ENV="http://schemas.xmlsoap.org/soap/envelope/">
<SOAP-ENV:Header/>
<ns1:Body>
<ns0:Choice>
<ns0:a1>Wackadoodle</ns0:a1>
</ns0:Choice>
</ns1:Body>
</SOAP-ENV:Envelope>""")
# Input #2.
param = client.factory.create("Choice.sequence")
param.e2 = "Wackadoodle"
request = _construct_SOAP_request(client, 'f', sequence=param)
assert tests.compare_xml_to_string(request, """\
<?xml version="1.0" encoding="UTF-8"?>
<SOAP-ENV:Envelope xmlns:ns0="my-namespace" xmlns:ns1="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:SOAP-ENV="http://schemas.xmlsoap.org/soap/envelope/">
<SOAP-ENV:Header/>
<ns1:Body>
<ns0:Choice>
<ns0:sequence>
<ns0:e1/>
<ns0:e2>Wackadoodle</ns0:e2>
<ns0:e3/>
</ns0:sequence>
</ns0:Choice>
</ns1:Body>
</SOAP-ENV:Envelope>""")
def test_function_parameters_sequence_in_a_choice_in_a_sequence():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="External">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="choice">
<xsd:complexType>
<xsd:choice>
<xsd:element name="a1" type="xsd:string" />
<xsd:element name="sequence">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="e1" type="xsd:string" />
<xsd:element name="e2" type="xsd:string" />
<xsd:element name="e3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
<xsd:element name="a2" type="xsd:string" />
</xsd:choice>
</xsd:complexType>
</xsd:element>
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:External" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
# Construct input parameters.
param = client.factory.create("External.choice")
param.sequence = client.factory.create("External.choice.sequence")
param.sequence.e2 = "Wackadoodle"
# Construct a SOAP request containing our input parameters.
request = _construct_SOAP_request(client, 'f', param)
assert tests.compare_xml_to_string(request, """\
<?xml version="1.0" encoding="UTF-8"?>
<SOAP-ENV:Envelope xmlns:ns0="my-namespace" xmlns:ns1="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:SOAP-ENV="http://schemas.xmlsoap.org/soap/envelope/">
<SOAP-ENV:Header/>
<ns1:Body>
<ns0:External>
<ns0:choice>
<ns0:sequence>
<ns0:e1/>
<ns0:e2>Wackadoodle</ns0:e2>
<ns0:e3/>
</ns0:sequence>
</ns0:choice>
</ns0:External>
</ns1:Body>
</SOAP-ENV:Envelope>""")
def test_function_parameters_strings():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="Elemento">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2" type="xsd:string" />
<xsd:element name="x3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:Elemento" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert not service.types
# Method parameters as read from the service definition.
assert len(service.params) == 3
assert service.params[0][0].name == "x1"
assert service.params[0][0].type == _string_type
assert isinstance(service.params[0][1], suds.xsd.sxbuiltin.XString)
assert service.params[1][0].name == "x2"
assert service.params[1][0].type == _string_type
assert isinstance(service.params[1][1], suds.xsd.sxbuiltin.XString)
assert service.params[2][0].name == "x3"
assert service.params[2][0].type == _string_type
assert isinstance(service.params[2][1], suds.xsd.sxbuiltin.XString)
# Method parameters as read from a method object.
assert len(service.ports) == 1
port, methods = service.ports[0]
assert len(methods) == 1
method_name, method_params = methods[0]
assert method_name == "f"
assert len(method_params) == 3
assert method_params[0][0] == "x1"
assert method_params[0][1] is service.params[0][0]
assert method_params[1][0] == "x2"
assert method_params[1][1] is service.params[1][0]
assert method_params[2][0] == "x3"
assert method_params[2][1] is service.params[2][0]
def test_global_enumeration():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:simpleType name="AAA">
<xsd:restriction base="xsd:string">
<xsd:enumeration value="One" />
<xsd:enumeration value="Two" />
<xsd:enumeration value="Thirty-Two" />
</xsd:restriction>
</xsd:simpleType>
</xsd:schema>
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
assert len(client.sd) == 1
service = client.sd[0]
assert len(service.types) == 1
for typeTuple in service.types:
# Tuple containing the same object twice.
assert len(typeTuple) == 2
assert typeTuple[0] is typeTuple[1]
aType = service.types[0][0]
assert isinstance(aType, suds.xsd.sxbasic.Simple)
assert aType.name == "AAA"
assert aType.enum()
assert aType.mixed()
assert aType.restriction()
assert not aType.choice()
assert not aType.sequence()
assert len(aType.rawchildren) == 1
assert isinstance(aType.rawchildren[0], suds.xsd.sxbasic.Restriction)
assert aType.rawchildren[0].ref == _string_type
enum = client.factory.create("AAA")
assert enum.One == "One"
assert enum.Two == "Two"
assert getattr(enum, "Thirty-Two") == "Thirty-Two"
def test_global_sequence_in_a_global_sequence():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="Oklahoma">
<xsd:sequence>
<xsd:element name="c1" type="xsd:string" />
<xsd:element name="c2" type="xsd:string" />
<xsd:element name="c3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
<xsd:complexType name="Wackadoodle">
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2" type="Oklahoma" />
<xsd:element name="x3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:schema>
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert len(service.types) == 2
for typeTuple in service.types:
# Tuple containing the same object twice.
assert len(typeTuple) == 2
assert typeTuple[0] is typeTuple[1]
aTypeIn = service.types[0][0]
assert isinstance(aTypeIn, suds.xsd.sxbasic.Complex)
assert aTypeIn.name == "Oklahoma"
assert not aTypeIn.sequence()
assert aTypeIn.rawchildren[0].sequence()
aTypeOut = service.types[1][0]
assert isinstance(aTypeOut, suds.xsd.sxbasic.Complex)
assert aTypeOut.name == "Wackadoodle"
assert not aTypeOut.sequence()
assert aTypeOut.rawchildren[0].sequence()
assert len(aTypeOut.rawchildren) == 1
children = aTypeOut.children()
assert isinstance(children, list)
assert len(children) == 3
assert children[0][0].name == "x1"
assert children[0][0].type == _string_type
assert children[1][0].name == "x2"
assert children[1][0].type == ("Oklahoma", "my-namespace")
assert children[2][0].name == "x3"
assert children[2][0].type == _string_type
sequenceOut = client.factory.create("Wackadoodle")
_assert_dynamic_type(sequenceOut, "Wackadoodle")
assert sequenceOut.__metadata__.sxtype is aTypeOut
assert sequenceOut.x1 is None
sequenceIn = sequenceOut.x2
assert sequenceOut.x3 is None
_assert_dynamic_type(sequenceIn, "Oklahoma")
assert sequenceIn.__metadata__.sxtype is aTypeIn
assert sequenceIn.c1 is None
assert sequenceIn.c2 is None
assert sequenceIn.c3 is None
def test_global_string_sequence():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="Oklahoma">
<xsd:sequence>
<xsd:element name="c1" type="xsd:string" />
<xsd:element name="c2" type="xsd:string" />
<xsd:element name="c3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:schema>
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert len(service.types) == 1
for typeTuple in service.types:
# Tuple containing the same object twice.
assert len(typeTuple) == 2
assert typeTuple[0] is typeTuple[1]
aType = service.types[0][0]
assert isinstance(aType, suds.xsd.sxbasic.Complex)
assert aType.name == "Oklahoma"
assert not aType.choice()
assert not aType.enum()
assert not aType.mixed()
assert not aType.restriction()
assert not aType.sequence()
assert len(aType.rawchildren) == 1
sequence_node = aType.rawchildren[0]
assert isinstance(sequence_node, suds.xsd.sxbasic.Sequence)
assert sequence_node.sequence()
assert len(sequence_node) == 3
sequence_items = sequence_node.children()
assert isinstance(sequence_items, list)
assert len(sequence_items) == 3
assert sequence_items[0][0].name == "c1"
assert sequence_items[0][0].type == _string_type
assert sequence_items[1][0].name == "c2"
assert sequence_items[1][0].type == _string_type
assert sequence_items[2][0].name == "c3"
assert sequence_items[2][0].type == _string_type
sequence = client.factory.create("Oklahoma")
getattr(sequence, "c1")
getattr(sequence, "c2")
getattr(sequence, "c3")
pytest.raises(AttributeError, getattr, sequence, "nonExistingChild")
assert sequence.c1 is None
assert sequence.c2 is None
assert sequence.c3 is None
sequence.c1 = "Pero"
sequence.c3 = "Zdero"
assert sequence.c1 == "Pero"
assert sequence.c2 is None
assert sequence.c3 == "Zdero"
def test_local_sequence_in_a_global_sequence():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="Wackadoodle">
<xsd:sequence>
<xsd:element name="x1">
<xsd:complexType name="Oklahoma">
<xsd:sequence>
<xsd:element name="c1" type="xsd:string" />
<xsd:element name="c2" type="xsd:string" />
<xsd:element name="c3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
<xsd:element name="x2">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="s" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:sequence>
</xsd:complexType>
</xsd:schema>
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
assert len(service.types) == 1
aTypeOut = service.types[0][0]
assert isinstance(aTypeOut, suds.xsd.sxbasic.Complex)
assert aTypeOut.name == "Wackadoodle"
assert not aTypeOut.sequence()
assert aTypeOut.rawchildren[0].sequence()
children = aTypeOut.children()
assert isinstance(children, list)
assert len(children) == 2
aTypeIn1 = children[0][0]
assert isinstance(aTypeIn1, suds.xsd.sxbasic.Element)
assert not aTypeIn1.sequence()
assert aTypeIn1.rawchildren[0].rawchildren[0].sequence()
aTypeIn2 = children[1][0]
assert isinstance(aTypeIn2, suds.xsd.sxbasic.Element)
assert not aTypeIn2.sequence()
assert aTypeIn2.rawchildren[0].rawchildren[0].sequence()
assert aTypeIn1.rawchildren[0].name == "Oklahoma"
assert aTypeIn1.rawchildren[0].type is None
namespace1 = aTypeIn1.rawchildren[0].namespace()
assert namespace1 == ("ns", "my-namespace")
assert aTypeIn2.rawchildren[0].name is None
assert aTypeIn2.rawchildren[0].type is None
assert aTypeIn1.rawchildren[0].namespace() is namespace1
sequenceOut = client.factory.create("Wackadoodle")
_assert_dynamic_type(sequenceOut, "Wackadoodle")
assert sequenceOut.__metadata__.sxtype is aTypeOut
sequenceIn1 = sequenceOut.x1
sequenceIn2 = sequenceOut.x2
_assert_dynamic_type(sequenceIn1, "x1")
_assert_dynamic_type(sequenceIn2, "x2")
assert sequenceIn1.__metadata__.sxtype is aTypeIn1
assert sequenceIn2.__metadata__.sxtype is aTypeIn2
assert sequenceIn1.c1 is None
assert sequenceIn1.c2 is None
assert sequenceIn1.c3 is None
assert sequenceIn2.s is None
def test_no_trailing_comma_in_function_prototype_description_string__0():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="InputData">
<xsd:complexType>
<xsd:sequence />
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:InputData" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
s = str(client)
assert " f()\n" in s
def test_no_trailing_comma_in_function_prototype_description_string__1():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="InputData">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:InputData" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
s = str(client)
assert " f(xs:string x1)\n" in s
def test_no_trailing_comma_in_function_prototype_description_string__3():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="InputData">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2" type="xsd:string" />
<xsd:element name="x3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:InputData" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
s = str(client)
assert " f(xs:string x1, xs:string x2, xs:string x3)\n" in s
def test_no_types():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema" />
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
assert len(client.sd) == 1
service = client.sd[0]
assert not client.wsdl.schema.types
assert not service.types
pytest.raises(suds.TypeNotFound, client.factory.create, "NonExistingType")
def test_parameter_referencing_missing_element(monkeypatch):
wsdl = tests.wsdl_input("", "missingElement")
monkeypatch.delitem(locals(), "e", False)
e = pytest.raises(suds.TypeNotFound, tests.client_from_wsdl, wsdl).value
assert str(e) == "Type not found: '(missingElement, my-namespace, )'"
# TODO: Update the current restriction type input parameter handling so they get
# 'unwrapped' correctly instead of each of their enumeration values getting
# interpreted as a separate input parameter.
@pytest.mark.xfail
def test_restrictions():
client_unnamed = tests.client_from_wsdl(tests.wsdl_input("""\
<xsd:element name="Elemento">
<xsd:simpleType>
<xsd:restriction base="xsd:int">
<xsd:enumeration value="1" />
<xsd:enumeration value="3" />
<xsd:enumeration value="5" />
</xsd:restriction>
</xsd:simpleType>
</xsd:element>""", "Elemento"))
client_named = tests.client_from_wsdl(tests.wsdl_input("""\
<xsd:simpleType name="MyType">
<xsd:restriction base="xsd:int">
<xsd:enumeration value="1" />
<xsd:enumeration value="3" />
<xsd:enumeration value="5" />
</xsd:restriction>
</xsd:simpleType>
<xsd:element name="Elemento" type="ns:MyType" />""", "Elemento"))
client_twice_restricted = tests.client_from_wsdl(tests.wsdl_input("""\
<xsd:simpleType name="MyTypeGeneric">
<xsd:restriction base="xsd:int">
<xsd:enumeration value="1" />
<xsd:enumeration value="2" />
<xsd:enumeration value="3" />
<xsd:enumeration value="4" />
<xsd:enumeration value="5" />
</xsd:restriction>
</xsd:simpleType>
<xsd:simpleType name="MyType">
<xsd:restriction base="ns:MyTypeGeneric">
<xsd:enumeration value="1" />
<xsd:enumeration value="3" />
<xsd:enumeration value="5" />
</xsd:restriction>
</xsd:simpleType>
<xsd:element name="Elemento" type="ns:MyType" />""", "Elemento"))
element_qref = ("Elemento", "my-namespace")
type_named_qref = ("MyType", "my-namespace")
element_unnamed = client_unnamed.wsdl.schema.elements[element_qref]
element_named = client_named.wsdl.schema.elements[element_qref]
element_twice_restricted = client_twice_restricted.wsdl.schema.elements[
element_qref]
type_unnamed = element_unnamed.resolve()
type_named = element_named.resolve()
type_twice_restricted = element_twice_restricted.resolve()
assert type_unnamed is element_unnamed
assert type_named is client_named.wsdl.schema.types[type_named_qref]
assert type_twice_restricted is client_twice_restricted.wsdl.schema.types[
type_named_qref]
# Regression test against suds automatically unwrapping input parameter
# type's enumeration values as separate parameters.
params_unnamed = client_unnamed.sd[0].params
params_named = client_named.sd[0].params
params_twice_restricted = client_twice_restricted.sd[0].params
assert len(params_unnamed) == 1
assert len(params_named) == 1
assert len(params_twice_restricted) == 1
assert params_unnamed[0][0] is element_unnamed
assert params_unnamed[0][1] is type_unnamed
assert params_named[0][0] is element_named
assert params_named[0][1] is type_named
assert params_twice_restricted[0][0] is element_twice_restricted
assert params_twice_restricted[0][1] is type_twice_restricted
def test_schema_node_occurrences():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
"""
+ _element_node_xml("AnElement1")
+ _element_node_xml("AnElement2", min=1)
+ _element_node_xml("AnElement3", max=1)
+ _element_node_xml("AnOptionalElement1", min=0)
+ _element_node_xml("AnOptionalElement2", min=0, max=1)
+ _element_node_xml("Array_0_2", min=0, max=2)
+ _element_node_xml("Array_0_999", min=0, max=999)
+ _element_node_xml("Array_0_X", min=0, max="unbounded")
+ _element_node_xml("Array_x_2", max=2)
+ _element_node_xml("Array_x_999", max=999)
+ _element_node_xml("Array_x_X", max="unbounded")
+ _element_node_xml("Array_1_2", min=1, max=2)
+ _element_node_xml("Array_1_999", min=1, max=999)
+ _element_node_xml("Array_1_X", min=1, max="unbounded")
+ _element_node_xml("Array_5_5", min=5, max=5)
+ _element_node_xml("Array_5_999", min=5, max=999)
+ _element_node_xml("Array_5_X", min=5, max="unbounded")
+ """
</xsd:schema>
</wsdl:types>
</wsdl:definitions>
"""))
schema = client.wsdl.schema
def a(schema, name, min=None, max=None):
element = schema.elements[name, "my-namespace"]
if min is None:
assert element.min is None
min = 1
else:
assert str(min) == element.min
if max is None:
assert element.max is None
max = 1
else:
assert str(max) == element.max
expected_optional = min == 0
assert expected_optional == element.optional()
expected_required = not expected_optional
assert expected_required == element.required()
expected_multi_occurrence = (max == "unbounded") or (max > 1)
assert expected_multi_occurrence == element.multi_occurrence()
a(schema, "AnElement1")
a(schema, "AnElement2", min=1)
a(schema, "AnElement3", max=1)
a(schema, "AnOptionalElement1", min=0)
a(schema, "AnOptionalElement2", min=0, max=1)
a(schema, "Array_0_2", min=0, max=2)
a(schema, "Array_0_999", min=0, max=999)
a(schema, "Array_0_X", min=0, max="unbounded")
a(schema, "Array_x_2", max=2)
a(schema, "Array_x_999", max=999)
a(schema, "Array_x_X", max="unbounded")
a(schema, "Array_1_2", min=1, max=2)
a(schema, "Array_1_999", min=1, max=999)
a(schema, "Array_1_X", min=1, max="unbounded")
a(schema, "Array_5_5", min=5, max=5)
a(schema, "Array_5_999", min=5, max=999)
a(schema, "Array_5_X", min=5, max="unbounded")
def test_schema_node_resolve():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="Typo">
<xsd:sequence>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
<xsd:element name="u3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
<xsd:element name="Elemento">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2" type="Typo" />
<xsd:element name="x3">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="a1" type="xsd:string" />
<xsd:element name="a2" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:sequence>
</xsd:complexType>
</xsd:element>
<xsd:element name="ElementoTyped" type="Typo" />
</xsd:schema>
</wsdl:types>
</wsdl:definitions>
"""))
schema = client.wsdl.schema
# Collect references to the test schema type nodes.
assert len(schema.types) == 1
typo = schema.types["Typo", "my-namespace"]
typo_u1 = typo.children()[0][0]
assert typo_u1.name == "u1"
# Collect references to the test schema element nodes.
assert len(schema.elements) == 2
elemento = schema.elements["Elemento", "my-namespace"]
elemento_x2 = elemento.children()[1][0]
assert elemento_x2.name == "x2"
elemento_x3 = elemento.children()[2][0]
assert elemento_x3.name == "x3"
elementoTyped = schema.elements["ElementoTyped", "my-namespace"]
# Resolving top-level locally defined non-content nodes.
assert typo.resolve() is typo
# Resolving a correctly typed top-level locally typed element.
assert elemento.resolve() is elemento
# Resolving top-level globally typed elements.
assert elementoTyped.resolve() is typo
# Resolving a subnode referencing a globally defined type.
assert elemento_x2.resolve() is typo
# Resolving a locally defined subnode.
assert elemento_x3.resolve() is elemento_x3
# Resolving builtin type nodes.
assert typo_u1.resolve().__class__ is suds.xsd.sxbuiltin.XString
assert typo_u1.resolve(nobuiltin=False).__class__ is \
suds.xsd.sxbuiltin.XString
assert typo_u1.resolve(nobuiltin=True) is typo_u1
assert elemento_x2.resolve(nobuiltin=True) is typo
assert elemento_x3.resolve(nobuiltin=True) is elemento_x3
def test_schema_node_resolve__nobuiltin_caching():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="Elemento1" type="xsd:string" />
<xsd:element name="Elemento2" type="xsd:string" />
<xsd:element name="Elemento3" type="xsd:string" />
<xsd:element name="Elemento4" type="xsd:string" />
</xsd:schema>
</wsdl:types>
</wsdl:definitions>
"""))
schema = client.wsdl.schema
# Collect references to the test schema element nodes.
assert len(schema.elements) == 4
e1 = schema.elements["Elemento1", "my-namespace"]
e2 = schema.elements["Elemento2", "my-namespace"]
e3 = schema.elements["Elemento3", "my-namespace"]
e4 = schema.elements["Elemento4", "my-namespace"]
# Repeating the same resolve() call twice makes sure that the first call
# does not cache an incorrect value, thus causing the second call to return
# an incorrect result.
assert e1.resolve().__class__ is suds.xsd.sxbuiltin.XString
assert e1.resolve().__class__ is suds.xsd.sxbuiltin.XString
assert e2.resolve(nobuiltin=True) is e2
assert e2.resolve(nobuiltin=True) is e2
assert e3.resolve().__class__ is suds.xsd.sxbuiltin.XString
assert e3.resolve(nobuiltin=True) is e3
assert e3.resolve(nobuiltin=True) is e3
assert e4.resolve(nobuiltin=True) is e4
assert e4.resolve().__class__ is suds.xsd.sxbuiltin.XString
assert e4.resolve().__class__ is suds.xsd.sxbuiltin.XString
def test_schema_node_resolve__invalid_type():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="Elemento1" type="Elemento1" />
<xsd:element name="Elemento2" type="Elemento1" />
<xsd:element name="Elemento3" type="XXX" />
</xsd:schema>
</wsdl:types>
</wsdl:definitions>
"""))
schema = client.wsdl.schema
assert len(schema.elements) == 3
elemento1 = schema.elements["Elemento1", "my-namespace"]
elemento2 = schema.elements["Elemento2", "my-namespace"]
elemento3 = schema.elements["Elemento3", "my-namespace"]
pytest.raises(suds.TypeNotFound, elemento1.resolve)
pytest.raises(suds.TypeNotFound, elemento2.resolve)
pytest.raises(suds.TypeNotFound, elemento3.resolve)
def test_schema_node_resolve__references():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="Typo">
<xsd:sequence>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
<xsd:element name="u3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
<xsd:element name="ElementoTyped" type="Typo" />
<xsd:element name="ElementoTyped11" ref="ElementoTyped" />
<xsd:element name="ElementoTyped12" ref="ElementoTyped11" />
<xsd:element name="ElementoTyped13" ref="ElementoTyped12" />
<xsd:element name="ElementoTyped21" ref="ElementoTyped" />
<xsd:element name="ElementoTyped22" ref="ElementoTyped21" />
<xsd:element name="ElementoTyped23" ref="ElementoTyped22" />
<xsd:element name="ElementoTypedX" ref="ElementoTypedX" />
<xsd:element name="ElementoTypedX1" ref="ElementoTypedX2" />
<xsd:element name="ElementoTypedX2" ref="ElementoTypedX1" />
</xsd:schema>
</wsdl:types>
</wsdl:definitions>
"""))
schema = client.wsdl.schema
# Collect references to the test schema element & type nodes.
assert len(schema.types) == 1
typo = schema.types["Typo", "my-namespace"]
assert len(schema.elements) == 10
elementoTyped = schema.elements["ElementoTyped", "my-namespace"]
elementoTyped11 = schema.elements["ElementoTyped11", "my-namespace"]
elementoTyped12 = schema.elements["ElementoTyped12", "my-namespace"]
elementoTyped13 = schema.elements["ElementoTyped13", "my-namespace"]
elementoTyped21 = schema.elements["ElementoTyped21", "my-namespace"]
elementoTyped22 = schema.elements["ElementoTyped22", "my-namespace"]
elementoTyped23 = schema.elements["ElementoTyped23", "my-namespace"]
elementoTypedX = schema.elements["ElementoTypedX", "my-namespace"]
elementoTypedX1 = schema.elements["ElementoTypedX1", "my-namespace"]
elementoTypedX2 = schema.elements["ElementoTypedX2", "my-namespace"]
# For referenced element node chains try resolving their nodes in both
# directions and try resolving them twice to try and avoid any internal
# resolve result caching that might cause some resursive resolution branch
# to not get taken.
# Note that these assertions are actually redundant since inter-element
# references get processed and referenced type information merged back into
# the referencee when the schema information is loaded so no recursion is
# needed here in the first place. The tests should still be left in place
# and pass to serve as a safeguard in case this reference processing gets
# changed in the future.
assert elementoTyped11.resolve() is typo
assert elementoTyped11.resolve() is typo
assert elementoTyped13.resolve() is typo
assert elementoTyped13.resolve() is typo
assert elementoTyped23.resolve() is typo
assert elementoTyped23.resolve() is typo
assert elementoTyped21.resolve() is typo
assert elementoTyped21.resolve() is typo
# Recursive element references.
assert elementoTypedX.resolve() is elementoTypedX
assert elementoTypedX1.resolve() is elementoTypedX1
assert elementoTypedX2.resolve() is elementoTypedX2
def test_schema_object_child_access_by_index():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="Oklahoma">
<xsd:sequence>
<xsd:element name="c1" type="xsd:string" />
<xsd:element name="c2" type="xsd:string" />
<xsd:element name="c3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:schema>
</wsdl:types>
<wsdl:portType name="dummyPortType">
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
service = client.sd[0]
aType = service.types[0][0]
sequence = aType.rawchildren[0]
assert isinstance(sequence, suds.xsd.sxbasic.Sequence)
children = aType.children()
assert isinstance(children, list)
assert sequence[-1] is None
# TODO: Children are returned as a 2-tuple containing the child element and
# its ancestry (list of its parent elements). For some reason the ancestry
# list is returned as a new list on every __getitem__() call and so can not
# be compared using the 'is' operator. Also the children() function and
# accesing children by index does not seem to return ancestry lists of the
# same depth. See whether this can be updated so we always get the same
# ancestry list object.
# TODO: Add more detailed tests for the ancestry list structure.
# TODO: Add more detailed tests for the rawchildren list structure.
assert isinstance(sequence[0], tuple)
assert len(sequence[0]) == 2
assert sequence[0][0] is children[0][0]
assert isinstance(sequence[1], tuple)
assert len(sequence[1]) == 2
assert sequence[1][0] is children[1][0]
assert isinstance(sequence[2], tuple)
assert len(sequence[2]) == 2
assert sequence[2][0] is children[2][0]
assert sequence[3] is None
def test_simple_wsdl():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:element name="f">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="a" type="xsd:string" />
<xsd:element name="b" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
<xsd:element name="fResponse">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="c" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
<wsdl:message name="fRequestMessage">
<wsdl:part name="parameters" element="ns:f" />
</wsdl:message>
<wsdl:message name="fResponseMessage">
<wsdl:part name="parameters" element="ns:fResponse" />
</wsdl:message>
<wsdl:portType name="dummyPortType">
<wsdl:operation name="f">
<wsdl:input message="ns:fRequestMessage" />
<wsdl:output message="ns:fResponseMessage" />
</wsdl:operation>
</wsdl:portType>
<wsdl:binding name="dummy" type="ns:dummyPortType">
<soap:binding style="document"
transport="http://schemas.xmlsoap.org/soap/http" />
<wsdl:operation name="f">
<soap:operation soapAction="f" style="document" />
<wsdl:input><soap:body use="literal" /></wsdl:input>
<wsdl:output><soap:body use="literal" /></wsdl:output>
</wsdl:operation>
</wsdl:binding>
<wsdl:service name="dummy">
<wsdl:port name="dummy" binding="ns:dummy">
<soap:address location="https://localhost/dummy" />
</wsdl:port>
</wsdl:service>
</wsdl:definitions>
"""))
# Target namespace.
assert client.wsdl.tns[0] == "ns"
assert client.wsdl.tns[1] == "my-namespace"
# Elements.
assert len(client.wsdl.schema.elements) == 2
elementIn = client.wsdl.schema.elements["f", "my-namespace"]
elementOut = client.wsdl.schema.elements["fResponse", "my-namespace"]
assert isinstance(elementIn, suds.xsd.sxbasic.Element)
assert isinstance(elementOut, suds.xsd.sxbasic.Element)
assert elementIn.name == "f"
assert elementOut.name == "fResponse"
assert len(elementIn.children()) == 2
param_in_1 = elementIn.children()[0][0]
param_in_2 = elementIn.children()[1][0]
assert param_in_1.name == "a"
assert param_in_1.type == _string_type
assert param_in_2.name == "b"
assert param_in_2.type == _string_type
assert len(elementOut.children()) == 1
param_out_1 = elementOut.children()[0][0]
assert param_out_1.name == "c"
assert param_out_1.type == _string_type
# Service definition.
assert len(client.sd) == 1
service_definition = client.sd[0]
assert service_definition.wsdl is client.wsdl
# Service.
assert len(client.wsdl.services) == 1
service = client.wsdl.services[0]
assert service_definition.service is service
# Ports.
assert len(service.ports) == 1
port = service.ports[0]
assert len(service_definition.ports) == 1
assert len(service_definition.ports[0]) == 2
assert service_definition.ports[0][0] is port
# Methods (from wsdl).
assert len(port.methods) == 1
method = port.methods["f"]
assert method.name == "f"
assert method.location == "https://localhost/dummy"
# Operations (from wsdl).
assert len(client.wsdl.bindings) == 1
binding_qname, binding = _first_from_dict(client.wsdl.bindings)
assert binding_qname == ("dummy", "my-namespace")
assert binding.__class__ is suds.wsdl.Binding
assert len(binding.operations) == 1
operation = list(binding.operations.values())[0]
input = operation.soap.input.body
output = operation.soap.output.body
assert len(input.parts) == 1
assert len(output.parts) == 1
input_element_qname = input.parts[0].element
output_element_qname = output.parts[0].element
assert input_element_qname == elementIn.qname
assert output_element_qname == elementOut.qname
# Methods (from service definition, for format specifications see the
# suds.serviceDefinition.ServiceDefinition.addports() docstring).
port, methods = service_definition.ports[0]
assert len(methods) == 1
method_name, method_params = methods[0]
assert method_name == "f"
param_name, param_element, param_ancestry = method_params[0]
assert param_name == "a"
assert param_element is param_in_1
assert len(param_ancestry) == 3
assert type(param_ancestry[0]) is suds.xsd.sxbasic.Element
assert param_ancestry[0].name == "f"
assert type(param_ancestry[1]) is suds.xsd.sxbasic.Complex
assert type(param_ancestry[2]) is suds.xsd.sxbasic.Sequence
param_name, param_element, param_ancestry = method_params[1]
assert param_name == "b"
assert param_element is param_in_2
assert len(param_ancestry) == 3
assert type(param_ancestry[0]) is suds.xsd.sxbasic.Element
assert param_ancestry[0].name == "f"
assert type(param_ancestry[1]) is suds.xsd.sxbasic.Complex
assert type(param_ancestry[2]) is suds.xsd.sxbasic.Sequence
def test_wsdl_schema_content():
client = tests.client_from_wsdl(suds.byte_str("""\
<?xml version='1.0' encoding='UTF-8'?>
<wsdl:definitions targetNamespace="my-namespace"
xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/"
xmlns:ns="my-namespace"
xmlns:soap="http://schemas.xmlsoap.org/wsdl/soap/">
<wsdl:types>
<xsd:schema targetNamespace="my-namespace"
elementFormDefault="qualified"
attributeFormDefault="unqualified"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<xsd:complexType name="UngaBunga">
<xsd:sequence>
<xsd:element name="u1" type="xsd:string" />
<xsd:element name="u2" type="xsd:string" />
<xsd:element name="u3" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
<xsd:complexType name="Fifi">
<xsd:sequence>
<xsd:element name="x" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
<xsd:element name="Elemento">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="x1" type="xsd:string" />
<xsd:element name="x2" type="UngaBunga" />
<xsd:element name="x3">
<xsd:complexType>
<xsd:sequence>
<xsd:element name="a1" type="xsd:string" />
<xsd:element name="a2" type="xsd:string" />
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:sequence>
</xsd:complexType>
</xsd:element>
</xsd:schema>
</wsdl:types>
</wsdl:definitions>
"""))
# Elements.
assert len(client.wsdl.schema.elements) == 1
elemento = client.wsdl.schema.elements["Elemento", "my-namespace"]
assert isinstance(elemento, suds.xsd.sxbasic.Element)
pytest.raises(KeyError, client.wsdl.schema.elements.__getitem__,
("DoesNotExist", "OMG"))
# Types.
assert len(client.wsdl.schema.types) == 2
unga_bunga = client.wsdl.schema.types["UngaBunga", "my-namespace"]
assert isinstance(unga_bunga, suds.xsd.sxbasic.Complex)
fifi = client.wsdl.schema.types["Fifi", "my-namespace"]
assert isinstance(unga_bunga, suds.xsd.sxbasic.Complex)
pytest.raises(KeyError, client.wsdl.schema.types.__getitem__,
("DoesNotExist", "OMG"))
def _assert_dynamic_type(anObject, typename):
assert anObject.__module__ == suds.sudsobject.__name__
assert anObject.__metadata__.sxtype.name == typename
# In order to be compatible with old style classes (py2 only) we need to
# access the object's class information using its __class__ member and not
# the type() function. type() function always returns <type 'instance'> for
# old-style class instances while the __class__ member returns the correct
# class information for both old and new-style classes.
assert anObject.__class__.__module__ == suds.sudsobject.__name__
assert anObject.__class__.__name__ == typename
def _construct_SOAP_request(client, operation_name, *args, **kwargs):
"""
Returns a SOAP request for a given web service operation invocation.
To make the test case code calling this function simpler, assumes we want
to call the operation on the given client's first service & port.
"""
method = client.wsdl.services[0].ports[0].methods[operation_name]
return method.binding.input.get_message(method, args, kwargs)
def _element_node_xml(name, min=None, max=None):
s = []
s.append(' <xsd:element name="')
s.append(name)
s.append('" type="xsd:string" ')
if min is not None:
s.append('minOccurs="%s" ' % (min,))
if max is not None:
s.append('maxOccurs="%s" ' % (max,))
s.append('/>\n')
return ''.join(s)
def _first_from_dict(d):
"""Returns the first name/value pair from a dictionary or None if empty."""
for x in list(d.items()):
return x[0], x[1]
_string_type = ("string", "http://www.w3.org/2001/XMLSchema")
| [
"liliang-sj@bestpay.com.cn"
] | liliang-sj@bestpay.com.cn |
496605879f80e93ccd8035858dcdcfc9c3775f68 | e96561d1cf5160b21173f7bddcf9280313cbb081 | /Python/Hailstone/Hailstone.py | 817afc406a8e3abb69c1cc755c0037e9fd319f83 | [] | no_license | luoqiangwei/puzzle | cce4563c9c68a019a519e85b1fa0b4fd31c36eb2 | 5830af112e5d829dcd9d7e8ae4677f464975a02c | refs/heads/master | 2020-03-28T03:02:35.239892 | 2019-02-27T05:14:53 | 2019-02-27T05:14:53 | 147,615,247 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 280 | py |
def Hailstone(n):
if (n <= 1):
return set(["1"])
elif (n % 2 == 0):
return set([str(n)]).union(Hailstone(int(n / 2)))
elif (n % 2 == 1):
return set([str(n)]).union(Hailstone(int(3 * n + 1)))
if __name__ == "__main__":
print(Hailstone(27)) | [
"luoqiangwei@live.cn"
] | luoqiangwei@live.cn |
4caff3a852ce95ba82421cb9e414c8da0743babf | 20303fce6d1b384858b7ef9a06ca8b50e006849b | /blog/migrations/0001_initial.py | ffe9c404beb4978e69900821cf307dacef7f7b94 | [] | no_license | patriciaaparicio/my-first-blog | 566ac5b246f50eecbdcfebf7590cefc0539dbe82 | a42603acc2d9dd6676e41d48dc9bdf0e9df72369 | refs/heads/master | 2020-04-01T05:35:29.522497 | 2018-10-13T20:06:18 | 2018-10-13T20:06:18 | 152,910,538 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 986 | py | # Generated by Django 2.0.9 on 2018-10-13 19:27
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='Post',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=200)),
('text', models.TextField()),
('created_date', models.DateTimeField(default=django.utils.timezone.now)),
('published_date', models.DateTimeField(blank=True, null=True)),
('author', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
]
| [
"patyaparicio@live.com.mx"
] | patyaparicio@live.com.mx |
066f1468dcad77bbbba420be664825ae167ba1e7 | f6252f763b46053d81ffcc19919a5adcb0fff069 | /trax/tf_numpy/numpy/tests/utils_test.py | 2558976fd867d9db4baf0bf87b1ce79b48145b68 | [
"Apache-2.0"
] | permissive | codespeakers/trax | ee5da9e39b83b173034ff2638d856dec38e9675a | 9fc11bca7accda0394d629cac96558f4539d7f61 | refs/heads/master | 2020-12-14T15:50:49.634706 | 2020-01-18T20:52:27 | 2020-01-18T20:52:27 | 234,796,218 | 0 | 0 | Apache-2.0 | 2020-01-18T20:51:52 | 2020-01-18T20:51:51 | null | UTF-8 | Python | false | false | 1,847 | py | # coding=utf-8
# Copyright 2019 The Trax Authors.
#
# 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.
"""Tests for utils.py."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow.compat.v2 as tf
from trax.tf_numpy.numpy import utils
class UtilsTest(tf.test.TestCase):
# pylint: disable=unused-argument
def testNpDoc(self):
def np_fun(x):
"""np_fun docstring."""
return
@utils.np_doc(np_fun)
def f():
"""f docstring."""
return
expected = """TensorFlow variant of `numpy.np_fun`.
Unsupported arguments: `x`.
f docstring.
Documentation for `numpy.np_fun`:
np_fun docstring."""
self.assertEqual(f.__doc__, expected)
def testNpDocErrors(self):
def np_fun(x, y=1, **kwargs):
return
# pylint: disable=unused-variable
with self.assertRaisesRegexp(TypeError, 'Cannot find parameter'):
@utils.np_doc(np_fun)
def f1(a):
return
with self.assertRaisesRegexp(TypeError, 'is of kind'):
@utils.np_doc(np_fun)
def f2(x, kwargs):
return
with self.assertRaisesRegexp(
TypeError, 'Parameter "y" should have a default value'):
@utils.np_doc(np_fun)
def f3(x, y):
return
if __name__ == '__main__':
tf.enable_v2_behavior()
tf.test.main()
| [
"copybara-worker@google.com"
] | copybara-worker@google.com |
68b0dbaac4f9ec7efec94b6d6ed57ddd32eefac6 | 4442ca88743678e88097c984ca94cebb7f757b04 | /src/8_model_selection.py | a88367cc14a3c69fc2dc1472a0d219bfacb74d3a | [] | no_license | yollalala/scikit-learn-practices | 98476d5cacd90caba51671732c101fa31c163c62 | 59ebbe0c045916109d4f4f07e2ecb018b74de87c | refs/heads/master | 2020-03-25T19:42:53.171190 | 2018-12-25T21:53:25 | 2018-12-25T21:53:25 | 144,096,514 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,426 | py | ### model selection practice
### tutorials from scikit-learn documentation
### this practice used built-in datasets on scikit-learn library
from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_val_score
from sklearn import datasets
from sklearn.svm import SVC
import numpy as np
### random split the datasets into training sets and test sets
# load iris dataset
iris = datasets.load_iris()
# print the dataset's shape
print(iris.data.shape, iris.target.shape)
# split the dataset
# holding out 40% for testing
X_train, X_test, y_train, y_test = train_test_split(iris.data,
iris.target, test_size=0.4, random_state=0)
# print the shape of splitted datasets
print(X_train.shape, y_train.shape)
print(X_test.shape, y_test.shape)
# train svm model
clf = SVC(kernel='linear', C=1).fit(X_train, y_train)
# print the score
print(clf.score(X_test, y_test))
### cross validation metrics
clf = SVC(kernel='linear', C=1)
scores = cross_val_score(clf, iris.data, iris.target, cv=5)
# print all scores
print(scores)
# print average and standard deviation of the scores
print('Accuracy: %0.2f (+/- %0.2f)' % (scores.mean(), scores.std() * 2))
# change the scoring parameter
scores = cross_val_score(clf, iris.data, iris.target, cv=5, scoring='f1_macro')
print(scores)
# pass a cross validation iterator instead
from sklearn.model_selection import ShuffleSplit
n_samples = iris.data.shape[0]
cv = ShuffleSplit(n_splits=5, test_size=0.3, random_state=0)
scores = cross_val_score(clf, iris.data, iris.target, cv=cv)
print(scores)
# data transformation
from sklearn import preprocessing
X_train, X_test, y_train, y_test = train_test_split(iris.data,
iris.target, test_size=0.4, random_state=0)
scaler = preprocessing.StandardScaler().fit(X_train)
X_train_transformed = scaler.transform(X_train)
clf = SVC(C=1).fit(X_train_transformed, y_train)
X_test_transformed = scaler.transform(X_test)
score = clf.score(X_test_transformed, y_test)
print(score)
# make pipeline to compact the behaviors under cross-validation
from sklearn.pipeline import make_pipeline
clf = make_pipeline(preprocessing.StandardScaler(), SVC(C=1))
scores = cross_val_score(clf, iris.data, iris.target, cv=cv)
print(scores)
# use cross_validate for multiple metrics
from sklearn.model_selection import cross_validate
from sklearn.metrics import recall_score
scoring = ['precision_macro', 'recall_macro']
clf = SVC(kernel='linear', C=1, random_state=0)
scores = cross_validate(clf, iris.data, iris.target, scoring=scoring,
cv=5, return_train_score=False)
# print scores keys (based on metrics)
print(sorted(scores.keys()))
# print score of recall macro of the test set
print(scores['test_recall_macro'])
# or use a dict to mapping the scorer name to predefined or custom function
from sklearn.metrics.scorer import make_scorer
scoring = {'prec_macro': 'precision_macro',
'rec_micro': make_scorer(recall_score, average='macro')}
scores = cross_validate(clf, iris.data, iris.target, scoring=scoring,
cv=5, return_train_score=True)
# print the score keys
print(sorted(scores.keys()))
# print score of recall macro of the train set
print(scores['train_rec_micro'])
# use cross_validate for single metrics
scores = cross_validate(clf, iris.data, iris.target,
scoring='precision_macro', cv=5, return_train_score=True)
# print the scores keys
print(sorted(scores))
# print the score of test set
print(scores['test_score'])
| [
"yollandasekarrini@gmail.com"
] | yollandasekarrini@gmail.com |
1d77cbfd80b1f6ec236953a1d767cc6340842c4f | c858d9511cdb6a6ca723cd2dd05827d281fa764d | /MFTU/lesson 8/practice/minkowski_curve.py | b1f2a0c187c3359f45a4c64ed166b194bb559ba2 | [] | no_license | DontTouchMyMind/education | 0c904aa929cb5349d7af7e06d9b1bbaab972ef95 | 32a53eb4086b730cc116e633f68cf01f3d4ec1d1 | refs/heads/master | 2021-03-12T11:15:02.479779 | 2020-09-17T08:19:50 | 2020-09-17T08:19:50 | 246,616,542 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 671 | py | from turtle import *
shape('turtle')
speed()
size = 50
def minkowski_curve(length, n):
"""
Function draws a minkowski curve
:param length: simple line length
:param n: recursion depth
:return:
"""
if n == 0:
forward(length)
return
minkowski_curve(length, n - 1)
left(90)
minkowski_curve(length, n - 1)
right(90)
minkowski_curve(length, n - 1)
right(90)
minkowski_curve(length, n - 1)
minkowski_curve(length, n - 1)
left(90)
minkowski_curve(length, n - 1)
left(90)
minkowski_curve(length, n - 1)
right(90)
minkowski_curve(length, n - 1)
minkowski_curve(size / 4, 5)
| [
"tobigface@gmail.com"
] | tobigface@gmail.com |
c89ecebe6da3c083f8978f4fb83e408f75c4852d | 61ec4f47b157aa1625ceea59303a251f02d39863 | /flask-taskr/taskrenv/bin/coverage | f8d0ce37ca920026fdf618bec3f1bbd4d6d62128 | [] | no_license | cgorrell/RealPython | 5f1dbe9937286b385c2d80147ded1d2fd16ad324 | d871b1d5ea3d9eacec7acf051d016707b347ad6d | refs/heads/master | 2016-09-06T21:48:05.628538 | 2014-06-26T16:13:28 | 2014-06-26T16:13:28 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 342 | #!/home/pi/RealPython/flask-taskr/taskrenv/bin/python
# EASY-INSTALL-ENTRY-SCRIPT: 'coverage==3.7.1','console_scripts','coverage'
__requires__ = 'coverage==3.7.1'
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.exit(
load_entry_point('coverage==3.7.1', 'console_scripts', 'coverage')()
)
| [
"cgorrell@furbishco.com"
] | cgorrell@furbishco.com | |
c0dfa9fc23af773b362407fae9acb2392d70dbc9 | fca8d59d535472c6869438fbd096653c8e3f36fa | /containers/postscore/app/postscore.py | efdd81509342e078b94ffc93d04cb954da1ef887 | [] | no_license | SydneyDockerMeetupAWS/meetup-code | e848b937d34985459b703ffc4ffced469824bd9b | 3804a2fda7490842822a34432510333064080feb | refs/heads/master | 2021-06-16T16:56:17.808281 | 2017-04-28T06:41:52 | 2017-04-28T06:41:52 | 85,008,420 | 5 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,126 | py | from flask import Flask, request
from flask_cors import CORS
import boto3
import json
import re
import requests
import os
import uuid
# Initialisation
app = Flask(__name__)
# Get the environment variables that aren't handled by Boto3 internally
# Enable CORS
ENABLE_CORS = os.environ.get('ENABLE_CORS')
if ENABLE_CORS is not None and ENABLE_CORS.lower() in ('true', 'yes', 'on'):
CORS(app)
# Region
AWS_DEFAULT_REGION = os.environ.get('AWS_DEFAULT_REGION')
if AWS_DEFAULT_REGION is None:
try:
r = requests.get('http://169.254.169.254/latest/dynamic/instance-identity/document',timeout=5)
AWS_DEFAULT_REGION = r.json()['region']
except Exception as e:
AWS_DEFAULT_REGION = 'us-east-1'
# Table Name
AWS_DYNAMODB_TABLE_NAME = os.environ.get('AWS_DYNAMODB_TABLE_NAME')
if AWS_DYNAMODB_TABLE_NAME is None:
raise ValueError('AWS_DYNAMODB_TABLE_NAME was not set')
# Create client
client = boto3.client('dynamodb',AWS_DEFAULT_REGION)
def inInput(input, keys):
for index, item in enumerate(keys):
if item not in input:
return False, item
return True, None
def throwBadRequestError(message):
return json.dumps({ 'Error' : '400 Bad Request: ' + message }), 400
def throwServiceUnavailableError(message):
return json.dumps({ 'Error' : '503 Service Unavailable: ' + message}), 503
@app.route('/')
def healthcheck():
return 'This host is healthy!', 200
@app.route('/pscore', methods=['POST'])
def pscore():
# Attempt to get the JSON object
try:
input = request.get_json()
except Exception as e:
returnJSON = {
'Error' : str(e)
}
return json.dumps(returnJSON), 400
# Validate User Input - Fields
inInputTest, missingField = inInput(input, ["Username","Score","Completed"])
if not inInputTest:
return throwBadRequestError('Missing field: \'%s\'' % missingField)
# Validate User Input - Field Username
if not re.match("^[a-zA-Z0-9]{3,10}$", str(input['Username'])):
return throwBadRequestError('Field \'Username\' has invalid value \'%s\', should match regex \'^[a-zA-Z0-9]{3,10}$\'' % str(input['Username']))
username = str(input['Username'])
# Validate User Input - Field Score
if isinstance(input['Score'], int):
if input['Score'] < 0:
return throwBadRequestError('Field \'Score\' has invalid value \'%d\', should be a positive integer' % input['Score'])
score = input['Score']
elif not str(input['Score']).isdigit():
return throwBadRequestError('Field \'Score\' has invalid value \'%s\', should be a positive integer.' % str(input['Score']))
else:
score = int(input['Score'])
# Validate User Input - Field Completed
if input['Completed'] in (True, False):
if input['Completed']:
completed = True
else:
completed = False
elif str(input['Completed']).lower() in ('true', 'yes', 'on'):
completed = True
elif str(input['Completed']).lower() in ('false', 'no', 'off'):
completed = False
else:
return throwBadRequestError('Field \'Completed\' has invalid value \'%s\', should be a boolean value: True | False' % str(input['Completed']))
# Prepare Confirmation Message
returnJSON = {
'Id' : uuid.uuid4().hex,
'Username' : username,
'Score' : score,
'Completed' : completed
}
# Attempt PutItem
try:
response = client.put_item(
TableName=AWS_DYNAMODB_TABLE_NAME,
Item={
'id' : { 'S' : returnJSON['Id'] },
'username' : { 'S' : returnJSON['Username']},
'score' : { 'N' : str(returnJSON['Score'])},
'completed' : { 'BOOL' : returnJSON['Completed']}
},
)
except Exception as e:
return throwServiceUnavailableError('Attempted to put item into DynamoDB, got the following error: %s' % str(e))
return json.dumps(returnJSON), 200
| [
"bertiet@amazon.com"
] | bertiet@amazon.com |
219ecdcca20b2b6ae2df729c0b04f80903956b35 | f84998eddfe0800e525a5ef34dd8fac1898665b2 | /pyski/pyski.py | 1594fda402a49ea6f246a07eb80280dcf44b5817 | [
"MIT"
] | permissive | asmodehn/adam | 76fdd8b7e54c50b20b87309609452293dbc76123 | 98060d76c3aebbada257cd348532509bb2986a5d | refs/heads/master | 2023-09-03T11:28:40.023415 | 2017-12-01T15:50:38 | 2017-12-01T15:50:38 | 106,175,072 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,011 | py | import sys
import cmd
import types
from inspect import signature
from svm import stk_set, stk_get, dup, drop, swap, over, rot
#TODO : unify interface using list of args.
# combinators
# Note how we apply only the immediate composition for B.
def B(x, y, z):
return x, y(z)
def C(x, y, z):
return x, z, y
def K(x, y):
return x
def W(x, y):
return x, y, y
class StackREPL(cmd.Cmd):
"""
Design notes. Cmd is based on the usual model of command + params, or function + arguments.
We want to have a stack based concatenative language, so we need to find the middle ground here...
Each time the user type return, one computation is effectuated
First computation is the current input line (command style) if there is one otherwise current stack (last first)
Any unknown word will be added to the stack and only considered as (unknown symbolic) param, not command.
"""
intro = 'Welcome to pyski. Type help or ? to list commands.\n'
prompt = ' '
file = None
# defining basic combinators with the host language features
env = {
'B': lambda *args: args,
'C': lambda x, y, z: x(y)(z),
'K': lambda x: x,
'W': lambda x: x,
}
# interpreter with the host language features
def evl(self, xpr):
for c in xpr:
try:
yield StackREPL.cmb[c]
except Exception:
raise # TODO : proper handling...
def prompt_refresh(self):
# note : we need the reversed stack for a left prompt
self.prompt = " ".join(reversed(tuple(stk_get()))) + ' '
def do_dup(self, arg):
"""duplicates its argument and push it up to the stack.
Extra arguments are treated before, following stack semantics.
This might seem a bit confusing and might be improved by switching prefix/postfix input semantics and repl design...
"""
stk_set(*dup(*stk_get()))
def do_drop(self, arg):
stk_set(*drop(*stk_get()))
def do_swap(self, arg):
stk_set(*swap(*stk_get()))
def do_over(self, arg):
stk_set(*over(*stk_get()))
def do_rot(self, arg):
stk_set(*rot(*stk_get()))
def default(self, line):
"""Called on an input line when the command prefix is not recognized.
This method automatically adds the command as undefined word, and recurse on argument (until one known command is found).
"""
# lets extract the command
cmd, arg, line = self.parseline(line)
if cmd: # checking for ''
# an add it to the stack (PUSH)
stk_set(cmd, *stk_get())
def emptyline(self):
"""
Called when the input line is empty
This executes one computation on the existing stack
:return:
"""
stkline = " ".join(stk_get())
if stkline:
self.onecmd(stkline)
# this parse in the opposite direction
# def parseline(self, line):
# """Parse the line into a command name and a string containing
# the arguments. Returns a tuple containing (command, args, line).
# 'command' and 'args' may be None if the line couldn't be parsed.
#
# Note this is the reverse as the default cmd implementation : the last word is the command.
# """
# line = line.strip()
# if not line:
# return None, None, line
# elif line[-1] == '?':
# line = line[:-1] + ' help'
# elif line[-1] == '!':
# if hasattr(self, 'do_shell'):
# line = line[:-1] + ' shell'
# else:
# return None, None, line
# i, n = 0, len(line)
# while i < n and line[-i] in self.identchars: i = i + 1
# cmd, arg = line[-i:].strip(), line[:-i]
#
# return cmd, arg, line
def parseline(self, line):
"""Parse the line into a command name and a string containing
the arguments. Returns a tuple containing (command, args, line).
'command' and 'args' may be None if the line couldn't be parsed.
"""
line = line.strip()
if not line:
return None, None, line
elif line[0] == '?':
line = 'help ' + line[1:]
elif line[0] == '!':
if hasattr(self, 'do_shell'):
line = 'shell ' + line[1:]
else:
return None, None, line
i, n = 0, len(line)
while i < n and line[i] in self.identchars: i = i+1
cmd, arg = line[:i], line[i:].strip()
return cmd, arg, line
def postcmd(self, stop, line):
"""Hook method executed just after a command dispatch is finished."""
cmd, arg, line = self.parseline(line)
if arg: # keep rest of the line in cmdqueue, and execute it in cmdloop.
self.cmdqueue.append(arg)
# update prompt
self.prompt_refresh()
return stop
# basic REPL commands
# def do_help(self, arg):
# ""
# def do_shell(self, arg):
# ""
def do_eof(self, arg):
'Stop recording, close the pyski window, and exit.'
print('Thank you for using pyski')
self.close()
return True
# ----- record and playback -----
def do_record(self, arg):
'Save future commands to filename: RECORD rose.cmd'
self.file = open(arg, 'w')
def do_playback(self, arg):
'Playback commands from a file: PLAYBACK rose.cmd'
self.close()
with open(arg) as f:
self.cmdqueue.extend(f.read().splitlines())
def precmd(self, line):
line = line.lower()
if self.file and 'playback' not in line:
print(line, file=self.file)
return line
def close(self):
if self.file:
self.file.close()
self.file = None
if __name__ == '__main__':
StackREPL().cmdloop()
# TODO : separate the evaluator- loop from the read / print loop, to allow to implement word rewriting as a "view/controller" only,
# where the evaluator is kind of the model (on top of the VM for operational semantics, and some type checker/theorem proofer for denotational semantics)...
# maybe even with network protocol in between.
# HOWEVER the read/print entire state must be kept in the evaluator or the VM (and per user)
# => Our evaluator (as a reflective tower) is always running (in a specific location) , like a server, and need a second input interface to manipulate the stored read/print state.
# Maybe the read/print state could also be linked to the tower level ???
# an evaluator can usually be split into a free monad and an interpretor. So maybe we need another construct here...
# But the Free Monad might be the correct math concept that is necessary for a "location" => where current state of computation is kept.
# Comparing with living system theory, encoder/decoder is not needed in homoiconic language, channel, net and time are hardware devices that can be interfaced with teh language somehow, and associator, decider and memory are all done by the free monad implementation.
# The transducer is the interpreter.
# This seems to suggest there would be more to the free monad than just a monad ( how to actually reflection, continuations, etc. ??)...
# It seems also that the free monad could be the place to store configuration of the ditor as well as hte place to implement "optimization" features for the language
# (for ex. a term configured in editor and always used could have a direct VM implementation, rather than rewrite it, and use hte implementation of each of its parts...)
# Maybe there should be a configurable term rewritter between the monad and the interpreter ?? It would rewrite what is unknown by the free monad into what is known... We still need to understand how this is different from the actual interpreter...
# We should keep all this on the side for later, after the curses based view has been developed.
| [
"asmodehn@gmail.com"
] | asmodehn@gmail.com |
2939d6f897536a43f1da5f5d28c7bb3987908837 | 92c97303fd4c4e880ffaa930b448937ebfd64162 | /38-loop-to-fill-list-w-input.py | 74401dc855d3c6b2af61c5464798116f0df8320e | [] | no_license | lxmambo/caleb-curry-python | 90a9be3e907a6bce81cb88a37f2286ad4eb54002 | fe5c2daa724ba3b818e20744ff18061542bff02f | refs/heads/master | 2023-01-02T20:11:14.887681 | 2020-10-31T23:27:54 | 2020-10-31T23:27:54 | 297,479,315 | 5 | 2 | null | null | null | null | UTF-8 | Python | false | false | 418 | py | #my code
continue_loop = True
list_of_words = []
while continue_loop:
word = input("tell me a word: ")
list_of_words.append(word)
if word == 'stop':
continue_loop = False
print(list_of_words)
#caleb's code
favs = []
print("enter a food: ('q' to quit)")
while True:
data = input()
if str.lower(data) == 'q':
break
favs.append(data)
for food in favs:
print("you said:",food) | [
"joao_santos_2003@hotmail.com"
] | joao_santos_2003@hotmail.com |
1fb238264c57b6f0be1de31b814b0afa6b28f463 | f51fdc803eab05cef2b6c0b446c8af848859a237 | /pchome/pchome_selenium.py | d1ce4cec82b3f3eff72b131b93e3f7600f1de8a0 | [] | no_license | liaosboy/web_crawer | 7cb11b83dc83e00bacd25b223bb31d77bac56dfc | e3f676bf4162d2726f292ac084e4a9750834b9fc | refs/heads/master | 2022-12-10T05:36:11.995401 | 2020-09-06T14:04:02 | 2020-09-06T14:04:02 | 263,523,298 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,135 | py |
from selenium import webdriver
from bs4 import BeautifulSoup
import random as rnd
import random as rnd
import time
import pandas as pd
from openpyxl import load_workbook
import re
import requests
urls = []
def get_Prod_url(keyword):
urls.clear()
browser = webdriver.Chrome()
browser.get("https://24h.pchome.com.tw/")
time.sleep(rnd.uniform(5, 7))
print('inputting value')
search_box = browser.find_element_by_id('keyword')
search_box.send_keys(keyword)
time.sleep(rnd.uniform(1, 3))
print('do click')
search_btn = browser.find_element_by_id('doSearch')
search_box.send_keys("\n")
time.sleep(rnd.uniform(1, 3))
print('choose category')
pattern = re.compile(keyword)
alis = browser.find_elements_by_xpath("//a[@href]")
for a in alis:
match = pattern.match(a.text)
if match:
a.click()
break
time.sleep(rnd.uniform(1, 3))
print('scroll page')
for i in range(1, 30):
browser.execute_script(
'window.scrollTo(0, document.body.scrollHeight)')
time.sleep(1)
print('get source')
html = browser.page_source
browser.close()
soup = BeautifulSoup(html)
title = soup.find_all('h5', {"class": "prod_name"})
for h5 in title:
alis = h5.find_all('a')
for a in alis:
url = "https:"+a['href']
urls.append(url)
def open_prod_page(url):
browser = webdriver.Chrome()
browser.get(url)
time.sleep(rnd.uniform(2, 5))
html = browser.page_source
soup = BeautifulSoup(html)
title = soup.find('title')
title_len = len(title)-15
name = title.text[:title_len]
print(name)
browser.close()
time.sleep(rnd.uniform(1, 3))
def open_all_url():
for url in urls:
open_prod_page(url)
get_Prod_url("顯示卡")
open_all_url()
# get_Prod_url("筆記電腦")
""" data = {"網址": urls}
df = pd.DataFrame(data)
book = load_workbook('pchome_url.xlsx')
writer = pd.ExcelWriter('pchome_url.xlsx', engine='openpyxl')
writer.book = book
df.to_excel(writer, keyword)
writer.save()
writer.close() """
| [
"nick87101227@gmail.com"
] | nick87101227@gmail.com |
f1c4caad5266b2e17020cc4bd4dbf9a3098a0328 | 50a7c55e00b661746fc953ee4940a8f3bf976b18 | /re/finditer.py | 1b7d9113e6a970ba95af69dd0b1a2430e16c9f36 | [] | no_license | cponeill/pymotw-practice-examples | a9e049a5aee671c8bfc958c6a5bfcfb764f12444 | 6e87ca8be925bc103afb7c0f80da8a69f1e80a4c | refs/heads/master | 2021-01-13T13:14:39.216035 | 2017-10-25T14:31:58 | 2017-10-25T14:31:58 | 72,708,203 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 212 | py | # finditer.py
import re
text = 'abbaaabbbbaaaaa'
pattern = 'ab'
for match in re.finditer(pattern, text):
s = match.start()
e = match.end()
print('Found {!r} at {:d}:{:d}'.format(text[s:e], s, e))
| [
"caseyoneill78@hotmail.com"
] | caseyoneill78@hotmail.com |
2e46b79c0f693869b30caf5163a700cfd9886c80 | e0f33c9509a40388120f335acd6cb168a5bf77d1 | /TimeSeriesCausality/venv/Scripts/pip3-script.py | 0bd7ee770d9e75f2c840332d6683244c5e9bb446 | [] | no_license | caozixuan/TimeSeriesCausality | 8edab3f27bcbe190fb7ef643882ed6a7b973b60e | 1655da1697ee82030cf4a4a5ddd8f43a74c82a12 | refs/heads/master | 2020-04-16T02:50:44.556265 | 2019-01-30T08:40:49 | 2019-01-30T08:40:49 | 165,210,396 | 1 | 0 | null | null | null | null | WINDOWS-1252 | Python | false | false | 437 | py | #!C:\Users\²Ü×ÓÐù\Projects\Research\TimeSeriesCausality\venv\Scripts\python.exe -x
# EASY-INSTALL-ENTRY-SCRIPT: 'pip==10.0.1','console_scripts','pip3'
__requires__ = 'pip==10.0.1'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('pip==10.0.1', 'console_scripts', 'pip3')()
)
| [
"1240292104@qq.com"
] | 1240292104@qq.com |
51d0800b7796a9c9b5e740cf810e2bbafd5fa4f2 | 1993bbaef9166118a72aa00576aee510ea0d9411 | /unused.py | 9e098f0ccd54f416b425a5ba4714280741a4e385 | [] | no_license | NeliocmSampaio/Search_AI | 87e53560d694180d8c85a26f83d325f094288a47 | 085b5f6249b131de81cf9113b9fd8a2fda519db5 | refs/heads/master | 2020-03-15T07:23:32.053137 | 2018-09-19T13:00:58 | 2018-09-19T13:00:58 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 702 | py | def vldfs( self, u, destiny, visitados, custo, l ):
visitados[u] = 1
if u==destiny:
return custo
if l==0:
visitados[u] = 0
return -1
for i in self.adj[u]:
if visitados[i[0]]==0:
r = self.vldfs(i[0], destiny, visitados, custo+i[1], l-1 )
if r!=-1:
return r
visitados[u] = 0
return -1
def ldfs(self, start, destiny, l):
visitados = [ 0 for i in range(self.v) ]
return self.vldfs( start, destiny, visitados, 0, l )
from PIL import Image
import numpy as np
array = np.zeros([255, 255, 3], dtype=np.uint8)
array[:,:] = [255, 128, 0]
image = Image.fromarray( array, 'RGB' )
image.save("teste.png") | [
"neliocmsampaio@gmail.com"
] | neliocmsampaio@gmail.com |
3ea1333c1ed615d23dd8f185c4a7e2b76ea96dcd | 0d1610eb32205cef33e039253b8d0b390d5562d1 | /educa/courses/migrations/0004_course_students.py | 99bafdb0103593499cc14e8bff112e819d916828 | [] | no_license | pujansoni/DjangoProjects | 0104e5ee241967b378e76c9dee7c655264e5e4c4 | dcfd03e577e7078ade8acd20e393f367a67cb4a8 | refs/heads/master | 2023-03-12T10:38:00.179206 | 2021-03-08T02:12:53 | 2021-03-08T02:12:53 | 284,309,183 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 550 | py | # Generated by Django 3.0.11 on 2021-03-03 20:43
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('courses', '0003_auto_20201130_1534'),
]
operations = [
migrations.AddField(
model_name='course',
name='students',
field=models.ManyToManyField(blank=True, related_name='courses_joined', to=settings.AUTH_USER_MODEL),
),
]
| [
"pujansoni1997@gmail.com"
] | pujansoni1997@gmail.com |
e335d60251086114cb52a4079269a9e182b68b52 | eec520199808cf6ef94b340dc2a8737e2fdd72b3 | /kokoro-count.py | 851834a8ad4ad5b530ae6b44dba0ff59766bbb58 | [] | no_license | UmaTakenaka/DataScience | 76b5ffca21dede0a8703d06fa2d1ee65be8cdc21 | 5cb8a401fb929f76fd95f82f8a8fab999c8d1411 | refs/heads/master | 2020-06-27T13:12:19.320994 | 2019-08-01T13:59:50 | 2019-08-01T13:59:50 | 199,962,797 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 992 | py | from janome.tokenizer import Tokenizer
import zipfile
import os.path, urllib.request as req
url = "https://www.aozora.gr.jp/cards/000148/files/773_ruby_5968.zip"
local = "773_ruby_5968.zip"
if not os.path.exists(local):
print("ZIPファイルをダウンロード")
req.urlretrieve(url, local)
# zipファイル内のテキスト読み込む
zf = zipfile.ZipFile(local, 'r')
fp = zf.open('kokoro.txt', 'r')
bindata = fp.read()
txt = bindata.decode('shift_jis')
# 形態素解析オブジェクト
t = Tokenizer()
# テキストの処理
word_dic = {}
lines = txt.split("\r\n")
for line in lines:
malist = t.tokenize(line)
for w in malist:
word = w.surface
ps = w.part_of_speech
if ps.find('名詞') < 0: continue
if not word in word_dic:
word_dic[word] = 0
word_dic[word] += 1
keys = sorted(word_dic.items(), key = lambda x:x[1], reverse=True)
for word, cnt in keys[:50]:
print("{0}({1})".format(word, cnt), end="") | [
"yumatakenaka@yumanoMacBook-Pro.local"
] | yumatakenaka@yumanoMacBook-Pro.local |
28adbd0bc49fa4b0432715d7189df8a41ae312c9 | 719a2b3bf777f12ba9da153453ca30a2dc9ebb36 | /variables_and_loops.py | 3bbe7ac5ed01e47c9fa730a483b07b5022d1b867 | [
"MIT"
] | permissive | carlosruperto/astr-119-hw-2 | e3ffcabeba521e2432d2a9972ce695c5eaf231cf | 3a7a043bb56775f7824ea382605415900c777439 | refs/heads/main | 2023-01-02T16:33:56.702234 | 2020-10-22T10:35:52 | 2020-10-22T10:35:52 | 306,298,078 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 652 | py | import numpy as numpy #we use numpy for lots of things
def main():
i = 0 #integers can be declared with a number
n = 10 #here is another integer
x = 119.0 #floating point nums are declared with a "."
# we can use numpy to declare arrays quickly
y = np.zero(n,dtype=float) #declares 10 zeros as floats using np
# we can use for loops to iterate with a variable
for i in range(n): #i in range [0,n-1]
y[i] = 2.0 * float(i) + 1. #set y = 2i+i as floats
# we can also simply iterate through a variable
for y_element in y:
print(y_element)
#execute the main function
if __name__ == "__main__":
main() | [
"noreply@github.com"
] | carlosruperto.noreply@github.com |
789fecb34c78b79dfcb7857c201d79e69574fa94 | cc5eeb91ab5afc8ad67f01e954de46b99c52a616 | /ClassiferFinal.py | 4440b5a512dd0e62e517612070c24e486574ae74 | [] | no_license | cyberdrk/NaiveBayesClassifier | 1902bde5fabe0c4a940bb4ae203f79cb538f886e | a14baeb952ef717d38059242c9718a893905167d | refs/heads/master | 2021-05-03T05:18:18.826466 | 2018-03-18T04:56:34 | 2018-03-18T04:56:34 | 120,635,704 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,757 | py | ############################################################################
############################################################################
# Importing necessary packages
import numpy as np
import scipy
import matplotlib.pyplot as plt
from sklearn.utils import check_random_state
from sklearn.utils import shuffle as util_shuffle
from sklearn.preprocessing import scale
from pandas import DataFrame
############################################################################
############################################################################
def make_moons(n_samples=100, shuffle=True, noise=None, random_state=None):
"""Make two interleaving half circles
A simple toy dataset to visualize clustering and classification
algorithms. Read more in the :ref:`User Guide <sample_generators>`.
Parameters
----------
n_samples : int, optional (default=100)
The total number of points generated.
shuffle : bool, optional (default=True)
Whether to shuffle the samples.
noise : double or None (default=None)
Standard deviation of Gaussian noise added to the data.
random_state : int, RandomState instance or None, optional (default=None)
If int, random_state is the seed used by the random number generator;
If RandomState instance, random_state is the random number generator;
If None, the random number generator is the RandomState instance used
by `np.random`.
Returns
-------
X : array of shape [n_samples, 2]
The generated samples.
y : array of shape [n_samples]
The integer labels (0 or 1) for class membership of each sample.
"""
n_samples_out = n_samples // 2 # Floor division
n_samples_in = n_samples - n_samples_out # splitting it into two halves
generator = check_random_state(random_state)
outer_circ_x = np.cos(np.linspace(0, np.pi, n_samples_out))
outer_circ_y = np.sin(np.linspace(0, np.pi, n_samples_out))
inner_circ_x = 1 - np.cos(np.linspace(0, np.pi, n_samples_in))
inner_circ_y = 1 - np.sin(np.linspace(0, np.pi, n_samples_in)) - 1
X = np.vstack((np.append(outer_circ_x, inner_circ_x),
np.append(outer_circ_y, inner_circ_y))).T
y = np.hstack([np.zeros(n_samples_out, dtype=np.intp),
np.ones(n_samples_in, dtype=np.intp)])
if shuffle:
X, y = util_shuffle(X, y, random_state=generator)
if noise is not None:
X += generator.normal(scale=noise, size=X.shape)
return X, y
############################################################################
# generating 2D classification dataset
crts, Class = make_moons(n_samples = 2000, noise = 0.08, random_state= 0)
Class = Class + 1
df = DataFrame(dict(x=crts[:, 0], y = crts[:, 1], label = Class))
colors = {1:'red', 2:'blue'}
fig, ax = plt.subplots()
############################################################################
############################################################################
# Separating the co ordinates according to the classes CLASSES 1 followed by CLASSES 2
grouped = df.groupby('label')
u = [] # The MEAN
gX = [] # Group
for key, group in grouped:
gX.append(group.values)
u.append(group.mean().values)
group.plot(ax = ax, kind = 'scatter', x = 'x', y = 'y', label = key, color = colors[key])
plt.savefig('graph.png')
gX = np.array(gX)
print gX
############################################################################
X = gX[:, :, -2]
Y = gX[:, :, -1]
classes = gX[:, :, -3]
print "Classes"
classes = np.hstack(classes)
print classes
print "Xh"
Xh = np.hstack(X)
print Xh
print "Yh"
Yh = np.hstack(Y)
print Yh
print "XY"
XY = np.column_stack((Xh, Yh))
print XY
############################################################################
# Calculating Covariance
print "Covariance"
C = np.cov(Xh, Yh)
print C
print "Cinv"
Cinv = np.linalg.inv(C)
print Cinv
############################################################################
############################################################################
'''
The Gaussain Bayes Classifier is:
log (Likelihood Ratio ^) = W' * X + b
where
W = (u1 - u2)' * Cinv * X
b = 0.5 * ((u2' * Cinv * u2) - (u1' * Cinv * u1))
Now, if the Likelihood Ratio is:
Greater than 1? Class 0 Txt Book Class 1
Lesser than 1? Class 1 Txt Book Class 2
Now, if the Logarithm of the Likelihood Ratio is:
Greater than log(1) = 0? Class 0 Txt Book Class 1
Lesser than log(1) = 0? Class 1 Txt Book Class 2
'''
############################################################################
############################################################################
# Finding W
mask = [False, True, True]
u1 = u[0] # Mean of Class 1
u2 = u[1] # Mean of Class 2
u1 = u1[mask]
u2 = u2[mask]
print "u1 - u2"
print (u1 - u2).T.shape
############################################################################
stage1W = np.asmatrix(np.dot((u1 - u2).T, Cinv))
print "stage1W"
print stage1W.shape
print "W"
W = np.dot(stage1W, XY.T)
print W
print "Weight W: "
print W.shape
############################################################################
############################################################################
# Finding b
u1 = np.asmatrix(u1)
u2 = np.asmatrix(u2)
print "Stage 1b"
stage11b = np.dot(u2, Cinv)
stage1b = np.dot(stage11b, u2.T)
stage1b = np.asscalar(np.array(stage1b))
print "Stage 2b"
stage22b = np.dot(u1, Cinv)
stage2b = np.dot(stage22b, u1.T)
stage2b = np.asscalar(np.array(stage2b))
b = 0.5 * (stage1b - stage2b)
print "Bias b: "
print b
############################################################################
############################################################################
# Calculating error rate
print "xtest"
xtest = XY[:, 0]
xtest = np.asmatrix(xtest)
print xtest.shape
ytest = np.multiply(W, xtest)
ytest = np.add(ytest, b)
print ytest
# ERROR CLASSIFICATION
print "CLASSIFICATION"
ytest[ytest > 0] = 1
ytest[ytest < 1] = 2
print ytest
print classes
error = ytest - classes
SQE = np.power(error, [2])
ERR = np.sum(SQE)
print "CLASSIFICATION ERROR RATE:"
MSE = (ERR / 2000) * 100
print MSE
ytest = np.subtract(ytest, [1])
ax.plot(xtest, ytest, marker = 'x', linewidth = 10 )
plt.show()
############################################################################
############################################################################ | [
"noreply@github.com"
] | cyberdrk.noreply@github.com |
73e9bc17dbc5b0fbf47a1c3ecbd9c85bd8b9835c | 4899980c7405f47f216800f543b2883cb0762f7e | /mne/datasets/config.py | 5e3e76b02571fdcfbb66d26f55386734f66d7483 | [
"LicenseRef-scancode-unknown-license-reference"
] | permissive | guiomar/mne-python | 57f940a6580d313ec2e13968da6203204b84cb2f | 2d19800a07904cfe69c1ba290c3eaf712625c6ab | refs/heads/main | 2023-09-01T23:05:39.345722 | 2021-11-23T14:26:21 | 2021-11-23T14:26:21 | 335,304,159 | 0 | 0 | BSD-3-Clause | 2021-02-02T13:49:20 | 2021-02-02T13:49:20 | null | UTF-8 | Python | false | false | 12,840 | py | # Authors: Adam Li <adam2392@gmail.com>
# Daniel McCloy <dan@mccloy.info>
#
# License: BSD Style.
_bst_license_text = """
License
-------
This tutorial dataset (EEG and MRI data) remains a property of the MEG Lab,
McConnell Brain Imaging Center, Montreal Neurological Institute,
McGill University, Canada. Its use and transfer outside the Brainstorm
tutorial, e.g. for research purposes, is prohibited without written consent
from the MEG Lab.
If you reference this dataset in your publications, please:
1) acknowledge its authors: Elizabeth Bock, Esther Florin, Francois Tadel
and Sylvain Baillet, and
2) cite Brainstorm as indicated on the website:
http://neuroimage.usc.edu/brainstorm
For questions, please contact Francois Tadel (francois.tadel@mcgill.ca).
"""
_hcp_mmp_license_text = """
License
-------
I request access to data collected by the Washington University - University
of Minnesota Consortium of the Human Connectome Project (WU-Minn HCP), and
I agree to the following:
1. I will not attempt to establish the identity of or attempt to contact any
of the included human subjects.
2. I understand that under no circumstances will the code that would link
these data to Protected Health Information be given to me, nor will any
additional information about individual human subjects be released to me
under these Open Access Data Use Terms.
3. I will comply with all relevant rules and regulations imposed by my
institution. This may mean that I need my research to be approved or
declared exempt by a committee that oversees research on human subjects,
e.g. my IRB or Ethics Committee. The released HCP data are not considered
de-identified, insofar as certain combinations of HCP Restricted Data
(available through a separate process) might allow identification of
individuals. Different committees operate under different national, state
and local laws and may interpret regulations differently, so it is
important to ask about this. If needed and upon request, the HCP will
provide a certificate stating that you have accepted the HCP Open Access
Data Use Terms.
4. I may redistribute original WU-Minn HCP Open Access data and any derived
data as long as the data are redistributed under these same Data Use Terms.
5. I will acknowledge the use of WU-Minn HCP data and data derived from
WU-Minn HCP data when publicly presenting any results or algorithms
that benefitted from their use.
1. Papers, book chapters, books, posters, oral presentations, and all
other printed and digital presentations of results derived from HCP
data should contain the following wording in the acknowledgments
section: "Data were provided [in part] by the Human Connectome
Project, WU-Minn Consortium (Principal Investigators: David Van Essen
and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and
Centers that support the NIH Blueprint for Neuroscience Research; and
by the McDonnell Center for Systems Neuroscience at Washington
University."
2. Authors of publications or presentations using WU-Minn HCP data
should cite relevant publications describing the methods used by the
HCP to acquire and process the data. The specific publications that
are appropriate to cite in any given study will depend on what HCP
data were used and for what purposes. An annotated and appropriately
up-to-date list of publications that may warrant consideration is
available at http://www.humanconnectome.org/about/acknowledgehcp.html
3. The WU-Minn HCP Consortium as a whole should not be included as an
author of publications or presentations if this authorship would be
based solely on the use of WU-Minn HCP data.
6. Failure to abide by these guidelines will result in termination of my
privileges to access WU-Minn HCP data.
"""
# To update the `testing` or `misc` datasets, push or merge commits to their
# respective repos, and make a new release of the dataset on GitHub. Then
# update the checksum in the MNE_DATASETS dict below, and change version
# here: ↓↓↓↓↓ ↓↓↓
RELEASES = dict(testing='0.128', misc='0.23')
TESTING_VERSIONED = f'mne-testing-data-{RELEASES["testing"]}'
MISC_VERSIONED = f'mne-misc-data-{RELEASES["misc"]}'
# To update any other dataset besides `testing` or `misc`, upload the new
# version of the data archive itself (e.g., to https://osf.io or wherever) and
# then update the corresponding checksum in the MNE_DATASETS dict entry below.
MNE_DATASETS = dict()
# MANDATORY KEYS:
# - archive_name : the name of the compressed file that is downloaded
# - hash : the checksum type followed by a colon and then the checksum value
# (examples: "sha256:19uheid...", "md5:upodh2io...")
# - url : URL from which the file can be downloaded
# - folder_name : the subfolder within the MNE data folder in which to save and
# uncompress (if needed) the file(s)
#
# OPTIONAL KEYS:
# - config_key : key to use with `mne.set_config` to store the on-disk location
# of the downloaded dataset (ex: "MNE_DATASETS_EEGBCI_PATH").
# Testing and misc are at the top as they're updated most often
MNE_DATASETS['testing'] = dict(
archive_name=f'{TESTING_VERSIONED}.tar.gz', # 'mne-testing-data',
hash='md5:88c04e31fd496f394fa96fe7cdd70217',
url=('https://codeload.github.com/mne-tools/mne-testing-data/'
f'tar.gz/{RELEASES["testing"]}'),
folder_name='MNE-testing-data',
config_key='MNE_DATASETS_TESTING_PATH',
)
MNE_DATASETS['misc'] = dict(
archive_name=f'{MISC_VERSIONED}.tar.gz', # 'mne-misc-data',
hash='md5:01e409d82ff11ca8b19a27c4f7ee6794',
url=('https://codeload.github.com/mne-tools/mne-misc-data/tar.gz/'
f'{RELEASES["misc"]}'),
folder_name='MNE-misc-data',
config_key='MNE_DATASETS_MISC_PATH'
)
MNE_DATASETS['fnirs_motor'] = dict(
archive_name='MNE-fNIRS-motor-data.tgz',
hash='md5:c4935d19ddab35422a69f3326a01fef8',
url='https://osf.io/dj3eh/download?version=1',
folder_name='MNE-fNIRS-motor-data',
config_key='MNE_DATASETS_FNIRS_MOTOR_PATH',
)
MNE_DATASETS['kiloword'] = dict(
archive_name='MNE-kiloword-data.tar.gz',
hash='md5:3a124170795abbd2e48aae8727e719a8',
url='https://osf.io/qkvf9/download?version=1',
folder_name='MNE-kiloword-data',
config_key='MNE_DATASETS_KILOWORD_PATH',
)
MNE_DATASETS['multimodal'] = dict(
archive_name='MNE-multimodal-data.tar.gz',
hash='md5:26ec847ae9ab80f58f204d09e2c08367',
url='https://ndownloader.figshare.com/files/5999598',
folder_name='MNE-multimodal-data',
config_key='MNE_DATASETS_MULTIMODAL_PATH',
)
MNE_DATASETS['opm'] = dict(
archive_name='MNE-OPM-data.tar.gz',
hash='md5:370ad1dcfd5c47e029e692c85358a374',
url='https://osf.io/p6ae7/download?version=2',
folder_name='MNE-OPM-data',
config_key='MNE_DATASETS_OPM_PATH',
)
MNE_DATASETS['phantom_4dbti'] = dict(
archive_name='MNE-phantom-4DBTi.zip',
hash='md5:938a601440f3ffa780d20a17bae039ff',
url='https://osf.io/v2brw/download?version=2',
folder_name='MNE-phantom-4DBTi',
config_key='MNE_DATASETS_PHANTOM_4DBTI_PATH',
)
MNE_DATASETS['sample'] = dict(
archive_name='MNE-sample-data-processed.tar.gz',
hash='md5:12b75d1cb7df9dfb4ad73ed82f61094f',
url='https://osf.io/86qa2/download?version=5',
folder_name='MNE-sample-data',
config_key='MNE_DATASETS_SAMPLE_PATH',
)
MNE_DATASETS['somato'] = dict(
archive_name='MNE-somato-data.tar.gz',
hash='md5:32fd2f6c8c7eb0784a1de6435273c48b',
url='https://osf.io/tp4sg/download?version=7',
folder_name='MNE-somato-data',
config_key='MNE_DATASETS_SOMATO_PATH'
)
MNE_DATASETS['spm'] = dict(
archive_name='MNE-spm-face.tar.gz',
hash='md5:9f43f67150e3b694b523a21eb929ea75',
url='https://osf.io/je4s8/download?version=2',
folder_name='MNE-spm-face',
config_key='MNE_DATASETS_SPM_FACE_PATH',
)
# Visual 92 categories has the dataset split into 2 files.
# We define a dictionary holding the items with the same
# value across both files: folder name and configuration key.
MNE_DATASETS['visual_92_categories'] = dict(
folder_name='MNE-visual_92_categories-data',
config_key='MNE_DATASETS_VISUAL_92_CATEGORIES_PATH',
)
MNE_DATASETS['visual_92_categories_1'] = dict(
archive_name='MNE-visual_92_categories-data-part1.tar.gz',
hash='md5:74f50bbeb65740903eadc229c9fa759f',
url='https://osf.io/8ejrs/download?version=1',
folder_name='MNE-visual_92_categories-data',
config_key='MNE_DATASETS_VISUAL_92_CATEGORIES_PATH',
)
MNE_DATASETS['visual_92_categories_2'] = dict(
archive_name='MNE-visual_92_categories-data-part2.tar.gz',
hash='md5:203410a98afc9df9ae8ba9f933370e20',
url='https://osf.io/t4yjp/download?version=1',
folder_name='MNE-visual_92_categories-data',
config_key='MNE_DATASETS_VISUAL_92_CATEGORIES_PATH',
)
MNE_DATASETS['mtrf'] = dict(
archive_name='mTRF_1.5.zip',
hash='md5:273a390ebbc48da2c3184b01a82e4636',
url='https://osf.io/h85s2/download?version=1',
folder_name='mTRF_1.5',
config_key='MNE_DATASETS_MTRF_PATH'
)
MNE_DATASETS['refmeg_noise'] = dict(
archive_name='sample_reference_MEG_noise-raw.zip',
hash='md5:779fecd890d98b73a4832e717d7c7c45',
url='https://osf.io/drt6v/download?version=1',
folder_name='MNE-refmeg-noise-data',
config_key='MNE_DATASETS_REFMEG_NOISE_PATH'
)
MNE_DATASETS['ssvep'] = dict(
archive_name='ssvep_example_data.zip',
hash='md5:af866bbc0f921114ac9d683494fe87d6',
url='https://osf.io/z8h6k/download?version=5',
folder_name='ssvep-example-data',
config_key='MNE_DATASETS_SSVEP_PATH'
)
MNE_DATASETS['erp_core'] = dict(
archive_name='MNE-ERP-CORE-data.tar.gz',
hash='md5:5866c0d6213bd7ac97f254c776f6c4b1',
url='https://osf.io/rzgba/download?version=1',
folder_name='MNE-ERP-CORE-data',
config_key='MNE_DATASETS_ERP_CORE_PATH',
)
MNE_DATASETS['epilepsy_ecog'] = dict(
archive_name='MNE-epilepsy-ecog-data.tar.gz',
hash='md5:ffb139174afa0f71ec98adbbb1729dea',
url='https://osf.io/z4epq/download?revision=1',
folder_name='MNE-epilepsy-ecog-data',
config_key='MNE_DATASETS_EPILEPSY_ECOG_PATH',
)
# Fieldtrip CMC dataset
MNE_DATASETS['fieldtrip_cmc'] = dict(
archive_name='SubjectCMC.zip',
hash='md5:6f9fd6520f9a66e20994423808d2528c',
url='https://osf.io/j9b6s/download?version=1',
folder_name='MNE-fieldtrip_cmc-data',
config_key='MNE_DATASETS_FIELDTRIP_CMC_PATH'
)
# brainstorm datasets:
MNE_DATASETS['bst_auditory'] = dict(
archive_name='bst_auditory.tar.gz',
hash='md5:fa371a889a5688258896bfa29dd1700b',
url='https://osf.io/5t9n8/download?version=1',
folder_name='MNE-brainstorm-data',
config_key='MNE_DATASETS_BRAINSTORM_PATH',
)
MNE_DATASETS['bst_phantom_ctf'] = dict(
archive_name='bst_phantom_ctf.tar.gz',
hash='md5:80819cb7f5b92d1a5289db3fb6acb33c',
url='https://osf.io/sxr8y/download?version=1',
folder_name='MNE-brainstorm-data',
config_key='MNE_DATASETS_BRAINSTORM_PATH',
)
MNE_DATASETS['bst_phantom_elekta'] = dict(
archive_name='bst_phantom_elekta.tar.gz',
hash='md5:1badccbe17998d18cc373526e86a7aaf',
url='https://osf.io/dpcku/download?version=1',
folder_name='MNE-brainstorm-data',
config_key='MNE_DATASETS_BRAINSTORM_PATH',
)
MNE_DATASETS['bst_raw'] = dict(
archive_name='bst_raw.tar.gz',
hash='md5:fa2efaaec3f3d462b319bc24898f440c',
url='https://osf.io/9675n/download?version=2',
folder_name='MNE-brainstorm-data',
config_key='MNE_DATASETS_BRAINSTORM_PATH',
)
MNE_DATASETS['bst_resting'] = dict(
archive_name='bst_resting.tar.gz',
hash='md5:70fc7bf9c3b97c4f2eab6260ee4a0430',
url='https://osf.io/m7bd3/download?version=3',
folder_name='MNE-brainstorm-data',
config_key='MNE_DATASETS_BRAINSTORM_PATH',
)
# HF-SEF
MNE_DATASETS['hf_sef_raw'] = dict(
archive_name='hf_sef_raw.tar.gz',
hash='md5:33934351e558542bafa9b262ac071168',
url='https://zenodo.org/record/889296/files/hf_sef_raw.tar.gz',
folder_name='hf_sef',
config_key='MNE_DATASETS_HF_SEF_PATH',
)
MNE_DATASETS['hf_sef_evoked'] = dict(
archive_name='hf_sef_evoked.tar.gz',
hash='md5:13d34cb5db584e00868677d8fb0aab2b',
url=('https://zenodo.org/record/3523071/files/'
'hf_sef_evoked.tar.gz'),
folder_name='hf_sef',
config_key='MNE_DATASETS_HF_SEF_PATH',
)
# "fake" dataset (for testing)
MNE_DATASETS['fake'] = dict(
archive_name='foo.tgz',
hash='md5:3194e9f7b46039bb050a74f3e1ae9908',
url=('https://github.com/mne-tools/mne-testing-data/raw/master/'
'datasets/foo.tgz'),
folder_name='foo',
config_key='MNE_DATASETS_FAKE_PATH'
)
| [
"noreply@github.com"
] | guiomar.noreply@github.com |
0813a6db4825a70d70cbfe0b46ea9a83a3a09ba4 | eeb9582944d59345d9285101f47722058989f825 | /python/basic/list1.py | 97568116e7ddb6cce01207e2cd04187fd7d1a703 | [
"Apache-2.0"
] | permissive | mtraverso/varios | 193c9cca733ddf161c0dc8bf7f341b779f32cc4d | d161557fc6eb904f0618019da9f9225207c9e88c | refs/heads/master | 2021-01-13T16:17:55.913438 | 2017-02-16T15:36:09 | 2017-02-16T15:36:09 | 81,254,962 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,203 | py | #!/usr/bin/python -tt
# Copyright 2010 Google Inc.
# Licensed under the Apache License, Version 2.0
# http://www.apache.org/licenses/LICENSE-2.0
# Google's Python Class
# http://code.google.com/edu/languages/google-python-class/
# Basic list exercises
# Fill in the code for the functions below. main() is already set up
# to call the functions with a few different inputs,
# printing 'OK' when each function is correct.
# The starter code for each function includes a 'return'
# which is just a placeholder for your code.
# It's ok if you do not complete all the functions, and there
# are some additional functions to try in list2.py.
# A. match_ends
# Given a list of strings, return the count of the number of
# strings where the string length is 2 or more and the first
# and last chars of the string are the same.
# Note: python does not have a ++ operator, but += works.
def match_ends(words):
result = 0
for word in words:
if len(word) >= 2 and word[0] == word[len(word)-1]:
result+=1
return result
# B. front_x
# Given a list of strings, return a list with the strings
# in sorted order, except group all the strings that begin with 'x' first.
# e.g. ['mix', 'xyz', 'apple', 'xanadu', 'aardvark'] yields
# ['xanadu', 'xyz', 'aardvark', 'apple', 'mix']
# Hint: this can be done by making 2 lists and sorting each of them
# before combining them.
def front_x(words):
listX = list()
listNX = list()
for word in words:
if word[0] == "x":
listX.append(word)
else:
listNX.append(word)
listX.sort()
listNX.sort()
return listX + listNX
# C. sort_last
# Given a list of non-empty tuples, return a list sorted in increasing
# order by the last element in each tuple.
# e.g. [(1, 7), (1, 3), (3, 4, 5), (2, 2)] yields
# [(2, 2), (1, 3), (3, 4, 5), (1, 7)]
# Hint: use a custom key= function to extract the last element form each tuple.
def sort_last(tuples):
sortedL = sorted(tuples,key=lambda val: val[len(val)-1])
return sortedL
# Simple provided test() function used in main() to print
# what each function returns vs. what it's supposed to return.
def test(got, expected):
if got == expected:
prefix = ' OK '
else:
prefix = ' X '
print '%s got: %s expected: %s' % (prefix, repr(got), repr(expected))
# Calls the above functions with interesting inputs.
def main():
print 'match_ends'
test(match_ends(['aba', 'xyz', 'aa', 'x', 'bbb']), 3)
test(match_ends(['', 'x', 'xy', 'xyx', 'xx']), 2)
test(match_ends(['aaa', 'be', 'abc', 'hello']), 1)
print
print 'front_x'
test(front_x(['bbb', 'ccc', 'axx', 'xzz', 'xaa']),
['xaa', 'xzz', 'axx', 'bbb', 'ccc'])
test(front_x(['ccc', 'bbb', 'aaa', 'xcc', 'xaa']),
['xaa', 'xcc', 'aaa', 'bbb', 'ccc'])
test(front_x(['mix', 'xyz', 'apple', 'xanadu', 'aardvark']),
['xanadu', 'xyz', 'aardvark', 'apple', 'mix'])
print
print 'sort_last'
test(sort_last([(1, 3), (3, 2), (2, 1)]),
[(2, 1), (3, 2), (1, 3)])
test(sort_last([(2, 3), (1, 2), (3, 1)]),
[(3, 1), (1, 2), (2, 3)])
test(sort_last([(1, 7), (1, 3), (3, 4, 5), (2, 2)]),
[(2, 2), (1, 3), (3, 4, 5), (1, 7)])
if __name__ == '__main__':
main()
| [
"matias.traverso@mercadolibre.com"
] | matias.traverso@mercadolibre.com |
3b742be826e8f3b22f0c32552d5d1ae3d60db579 | 1bccf3653d2a0b9b926b662074cc3de078f25554 | /rory_test.py | 17fe23271831ee94cafe33cdecac42580df99388 | [] | no_license | irishroryc/CV_1 | e7fd3174b72aacf103179b433e8d442dde698314 | b6d73dc394d4904d67ea7a35e442d889772f7c40 | refs/heads/master | 2020-04-22T12:13:09.003968 | 2019-02-12T19:42:34 | 2019-02-12T19:42:34 | 170,365,121 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,635 | py | """
Tests for students for the Hybrid images (PA1) assignment
Convention: append an integer to the end of the test, for multiple versions of
the same test at different difficulties. Higher numbers are more difficult
(lower thresholds or accept fewer mistakes). Example:
test_all_equal1(self):
...
test_all_equal2(self):
...
"""
import sys
sys.path.append('/Users/kb/bin/opencv-3.1.0/build/lib/')
import unittest
import cv2
import numpy as np
import hybrid
class TestGaussianKernel2D(unittest.TestCase):
def test_5_5_5(self):
a = np.array([[ 0.03688345, 0.03916419, 0.03995536, 0.03916419, 0.03688345],
[ 0.03916419, 0.04158597, 0.04242606, 0.04158597, 0.03916419],
[ 0.03995536, 0.04242606, 0.04328312, 0.04242606, 0.03995536],
[ 0.03916419, 0.04158597, 0.04242606, 0.04158597, 0.03916419],
[ 0.03688345, 0.03916419, 0.03995536, 0.03916419, 0.03688345]])
# alternate result, which is based on more exact numeric integral
a_alternate = np.array([[0.03689354, 0.03916709, 0.03995566, 0.03916709, 0.03689354],
[0.03916709, 0.04158074, 0.0424179, 0.04158074, 0.03916709],
[0.03995566, 0.0424179, 0.04327192, 0.0424179, 0.03995566],
[0.03916709, 0.04158074, 0.0424179, 0.04158074, 0.03916709],
[0.03689354, 0.03916709, 0.03995566, 0.03916709, 0.03689354]])
self.assertTrue(np.allclose(hybrid.gaussian_blur_kernel_2d(5, 5, 5), a, rtol=1e-4, atol=1e-08)
or np.allclose(hybrid.gaussian_blur_kernel_2d(5, 5, 5), a_alternate, rtol=1e-4, atol=1e-08))
def test_1_7_3(self):
a = np.array([[ 0.00121496, 0.00200313, 0.00121496],
[ 0.01480124, 0.02440311, 0.01480124],
[ 0.06633454, 0.10936716, 0.06633454],
[ 0.10936716, 0.18031596, 0.10936716],
[ 0.06633454, 0.10936716, 0.06633454],
[ 0.01480124, 0.02440311, 0.01480124],
[ 0.00121496, 0.00200313, 0.00121496]])
# alternate result, which is based on more exact numeric integral
a_alternate = np.array([[0.00166843, 0.00264296, 0.00166843],
[0.01691519, 0.02679535, 0.01691519],
[0.0674766, 0.10688965, 0.0674766 ],
[0.10688965, 0.16932386, 0.10688965],
[0.0674766, 0.10688965, 0.0674766 ],
[0.01691519, 0.02679535, 0.01691519],
[0.00166843, 0.00264296, 0.00166843]])
self.assertTrue(np.allclose(hybrid.gaussian_blur_kernel_2d(1, 7, 3), a, rtol=1e-4, atol=1e-08)
or np.allclose(hybrid.gaussian_blur_kernel_2d(1, 7, 3), a_alternate, rtol=1e-4, atol=1e-08))
def test_1079_3_5(self):
a = np.array([[ 0.06600011, 0.06685595, 0.06714369, 0.06685595, 0.06600011],
[ 0.06628417, 0.06714369, 0.06743267, 0.06714369, 0.06628417],
[ 0.06600011, 0.06685595, 0.06714369, 0.06685595, 0.06600011]])
# alternate result, which is based on more exact numeric integral
a_alternate = np.array([[0.06600058, 0.06685582, 0.06714335, 0.06685582, 0.06600058],
[0.06628444, 0.06714335, 0.06743212, 0.06714335, 0.06628444],
[0.06600058, 0.06685582, 0.06714335, 0.06685582, 0.06600058]])
self.assertTrue(np.allclose(hybrid.gaussian_blur_kernel_2d(10.79, 3, 5), a, rtol=1e-4, atol=1e-08)
or np.allclose(hybrid.gaussian_blur_kernel_2d(10.79, 3, 5), a_alternate, rtol=1e-4, atol=1e-08))
if __name__ == '__main__':
np.random.seed(4670)
unittest.main()
| [
"roryc@Rorys-MacBook-Pro.local"
] | roryc@Rorys-MacBook-Pro.local |
992aa9a41358de2ca0e114a8a437307e2492efc7 | 80d6259a79fa84dbe4b71d8aee654bcce610602e | /decoSample.py | 778b0b7a77783d98981eb60a5a37e9b514c8c372 | [] | no_license | ttylinux/LearnPython | ee8466f4f46554d48c107ebe83ec278d141fd279 | 9de6a47f1c68ea065d094008358cf5147bd5f93a | refs/heads/master | 2020-05-17T19:56:43.444327 | 2015-07-13T03:20:14 | 2015-07-13T03:20:14 | 38,341,778 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,331 | py | def simple_decorator(decorator):
'''This decorator can be used to turn simple functions
into well-behaved decorators, so long as the decorators
are fairly simple. If a decorator expects a function and
returns a function (no descriptors), and if it doesn't
modify function attributes or docstring, then it is
eligible to use this. Simply apply @simple_decorator to
your decorator and it will automatically preserve the
docstring and function attributes of functions to which
it is applied.'''
def new_decorator(f):
g = decorator(f)
print('g = decorator(f)')
g.__name__ = f.__name__
g.__doc__ = f.__doc__
g.__dict__.update(f.__dict__)
return g
# Now a few lines needed to make simple_decorator itself
# be a well-behaved decorator.
new_decorator.__name__ = decorator.__name__
print('new_decorator.__name__ = decorator.__name__')
new_decorator.__doc__ = decorator.__doc__
new_decorator.__dict__.update(decorator.__dict__)
return new_decorator
#
# Sample Use:
#
# my_simple_logging_decorator = simple_decorator(my_simple_logging_decorator)
@simple_decorator
def my_simple_logging_decorator(func):
def you_will_never_see_this_name(*args, **kwargs):
print('calling {}'.format(func.__name__))
return func(*args, **kwargs)
return you_will_never_see_this_name
# double = my_simple_logging_decorator(double)
# double = simple_decorator(my_simple_logging_decorator)(double) ---先执行simple_decorator的函数体
# double = new_decorator(double) ---然后执行new_decorator的函数体;该方法返回的是没有装饰的my_simple_logging_decorator(double)
# double = my_simple_logging_decorator(double)，这是没有装饰的my_simple_logging_decorator;执行you_will_never_see_this_name的函数体
@my_simple_logging_decorator
def double(x):
'Doubles a number.'
print('Doubles a number.')
return 2 * x
assert double.__name__ == 'double'
assert double.__doc__ == 'Doubles a number.'
print(double(155))
#输出结果:
#new_decorator.__name__ = decorator.__name__ ---这是simple_decorator的函数体
#g = decorator(f) ---这是new_decorator的函数体
#calling double ---这是you_will_never_see_this_name的函数体
#Doubles a number.---这是double的函数体
#310
| [
"albertxiaoyu@163.com"
] | albertxiaoyu@163.com |
8b44a827c459ed67c259ab72d48e14f076f7b707 | 131140eea42a13f7e9e384def3b0ffff9950dabb | /uploader.py | bd52c18eb3c8ff58eba66710578fc93bd521a8ee | [] | no_license | hackathon-ro/raspihome | 02a5494247af473bcccbd00e9a89ea2a695cccb2 | 823789e85efc945640d35a166e3455601b2ae5db | refs/heads/master | 2021-01-22T11:51:10.193808 | 2013-04-22T18:30:00 | 2013-04-22T18:30:00 | 9,563,968 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 5,643 | py | #!/usr/bin/python
'''
Created on 6 Jun 2012
@author: Jeremy Blythe
Motion Uploader - uploads videos to Google Drive
Read the blog entry at http://jeremyblythe.blogspot.com for more information
'''
import smtplib
from datetime import datetime
import os.path
import sys
import base64
import gdata.data
import gdata.docs.data
import gdata.docs.client
import ConfigParser
class MotionUploader:
def __init__(self, config_file_path):
# Load config
config = ConfigParser.ConfigParser()
config.read(config_file_path)
# GMail account credentials
self.username = config.get('gmail', 'user')
self.password = config.get('gmail', 'password')
self.from_name = config.get('gmail', 'name')
self.sender = config.get('gmail', 'sender')
# Recipient email address (could be same as from_addr)
self.recipient = config.get('gmail', 'recipient')
# Subject line for email
self.subject = config.get('gmail', 'subject')
# First line of email message
self.message = config.get('gmail', 'message')
# Folder (or collection) in Docs where you want the videos to go
self.folder = config.get('docs', 'folder')
# Options
self.delete_after_upload = config.getboolean('options', 'delete-after-upload')
self.send_email = config.getboolean('options', 'send-email')
self._create_gdata_client()
def _create_gdata_client(self):
"""Create a Documents List Client."""
self.client = gdata.docs.client.DocsClient(source='motion_uploader')
self.client.http_client.debug = False
self.client.client_login(self.sender, self.password, service=self.client.auth_service, source=self.client.source)
def _get_folder_resource(self):
"""Find and return the resource whose title matches the given folder."""
col = None
for resource in self.client.GetAllResources(uri='/feeds/default/private/full/-/folder'):
if resource.title.text == self.folder:
col = resource
break
return col
def _send_email(self,msg,imgpath):
'''Send an email using the GMail account.'''
senddate=datetime.strftime(datetime.now(), '%Y-%m-%d')
# Read a file and encode it into base64 format
fo = open(imgpath, "rb")
filecontent = fo.read()
encodedcontent = base64.b64encode(filecontent) # base64
imgfile=os.path.basename(imgpath)
marker = "AUNIQUEMARKER"
p1="Date: %s\r\nFrom: %s <%s>\r\nTo: %s\r\nSubject: %s\r\nContent-Type: multipart/mixed; boundary=%s\r\n--%s\r\n" % (senddate, self.from_name, self.sender, self.recipient, self.subject, marker, marker)
p2="Content-Type: text/plain\r\nContent-Transfer-Encoding:8bit\r\n\r\n%s\r\n--%s\r\n" % (msg, marker)
p3="Content-Type: multipart/mixed; name=""%s""\r\nContent-Transfer-Encoding:base64\r\nContent-Disposition: attachment; filename=%s\r\n\r\n%s\r\n--%s--\r\n" % (imgfile, imgfile, encodedcontent, marker)
server = smtplib.SMTP('smtp.gmail.com:587')
server.starttls()
server.login(self.username, self.password)
server.sendmail(self.sender, self.recipient, p1+p2+p3)
server.quit()
def _upload(self, video_file_path, folder_resource):
'''Upload the video and return the doc'''
doc = gdata.docs.data.Resource(type='video', title=os.path.basename(video_file_path))
media = gdata.data.MediaSource()
media.SetFileHandle(video_file_path, 'video/avi')
doc = self.client.CreateResource(doc, media=media, collection=folder_resource)
return doc
def upload_video(self, video_file_path):
"""Upload a video to the specified folder. Then optionally send an email and optionally delete the local file."""
folder_resource = self._get_folder_resource()
if not folder_resource:
raise Exception('Could not find the %s folder' % self.folder)
doc = self._upload(video_file_path, folder_resource)
if self.send_email:
video_link = None
for link in doc.link:
if 'video.google.com' in link.href:
video_link = link.href
break
# Send an email with the link if found
msg = self.message
if video_link:
msg += '\n\n' + video_link
imgfile = os.path.splitext(video_file_path)[0] + ".jpg"
self._send_email(msg,imgfile)
if self.delete_after_upload:
os.remove(imgfile)
if self.delete_after_upload:
os.remove(video_file_path)
if __name__ == '__main__':
try:
if len(sys.argv) < 3:
exit('Motion Uploader - uploads videos to Google Drive\n by Jeremy Blythe (http://jeremyblythe.blogspot.com)\n\n Usage: uploader.py {config-file-path} {video-file-path}')
cfg_path = sys.argv[1]
vid_path = sys.argv[2]
if not os.path.exists(cfg_path):
exit('Config file does not exist [%s]' % cfg_path)
if not os.path.exists(vid_path):
exit('Video file does not exist [%s]' % vid_path)
MotionUploader(cfg_path).upload_video(vid_path)
except gdata.client.BadAuthentication:
exit('Invalid user credentials given.')
except gdata.client.Error:
exit('Login Error')
except Exception as e:
exit('Error: [%s]' % e)
| [
"petrescs+github@gmail.com"
] | petrescs+github@gmail.com |
2e8692153e8631b8e0a381191beddedb83a9b760 | 5e601244fbf32ee5190fb5210a0cd334473a0abe | /projects/WindowsSystemOps/Services/pyAutoResetPrinterWin32.py | c9fdba47c8f7031abcb85ddd9dc5a51b53b36df7 | [] | no_license | DingGuodong/LinuxBashShellScriptForOps | 69ebe45cf3f92b741a078b9b78c2600328ce9b9e | b2ca1e4c870626dd078d447e2d1479b08602bdf6 | refs/heads/master | 2023-08-21T20:53:40.617397 | 2023-07-17T01:41:05 | 2023-07-17T01:41:05 | 57,015,255 | 453 | 343 | null | 2023-02-16T01:29:23 | 2016-04-25T05:55:28 | Python | UTF-8 | Python | false | false | 8,573 | py | #!/usr/bin/python
# encoding: utf-8
# -*- coding: utf-8 -*-
"""
Created by PyCharm.
File Name: LinuxBashShellScriptForOps:pyAutoResetPrinterWin32.py
Version: 0.0.1
Author: Guodong
Author Email: dgdenterprise@gmail.com
URL: https://github.com/DingGuodong/LinuxBashShellScriptForOps
Download URL: https://github.com/DingGuodong/LinuxBashShellScriptForOps/tarball/master
Create Date: 2018/10/10
Create Time: 10:44
Description: auto reset Spooler(Print Spooler) service when printer failure occurs
Long Description:
References: http://timgolden.me.uk/pywin32-docs/win32print.html
Prerequisites: pypiwin32: pip install pypiwin32
Optional: install 'pywin32'
Development Status: 3 - Alpha, 5 - Production/Stable
Environment: Console
Intended Audience: System Administrators, Developers, End Users/Desktop
License: Freeware, Freely Distributable
Natural Language: English, Chinese (Simplified)
Operating System: POSIX :: Linux, Microsoft :: Windows
Programming Language: Python :: 2.6
Programming Language: Python :: 2.7
Topic: Utilities
"""
import os
import sys
import time
from collections import Counter
from hashlib import md5
import win32print
import win32service
import win32serviceutil
def reset_printer():
"""
Note: administrator privilege is required
this function do three things:
1. stop Print Spooler service
2. delete all job files
3. start Print Spooler service
:return:
"""
service_name = 'spooler'.capitalize()
win_dir = os.environ.get('windir', r'C:\Windows')
printer_path = r"System32\spool\PRINTERS"
path = os.path.join(win_dir, printer_path)
status_code_map = {
0: "UNKNOWN",
1: "STOPPED",
2: "START_PENDING",
3: "STOP_PENDING",
4: "RUNNING"
}
print "printer spool folder is: %s" % path
if os.path.exists(path):
if os.listdir(path):
print "reset printer spooler service in progress ..."
status_code = win32serviceutil.QueryServiceStatus(service_name)[1]
if status_code == win32service.SERVICE_RUNNING or status_code == win32service.SERVICE_START_PENDING:
print "stopping service {service}".format(service=service_name)
win32serviceutil.StopService(serviceName=service_name)
# waiting for service stop, in case of WindowsError exception
# 'WindowsError: [Error 32]' which means
# 'The process cannot access the file because it is being used by another process'.
running_flag = True
while running_flag:
print "waiting for service {service} stop.".format(service=service_name)
status_code = win32serviceutil.QueryServiceStatus(service_name)[1]
time.sleep(2)
if status_code == win32service.SERVICE_STOPPED:
running_flag = False
for top, dirs, nondirs in os.walk(path, followlinks=True):
for item in nondirs:
path_to_remove = os.path.join(top, item)
try:
os.remove(path_to_remove)
except WindowsError:
time.sleep(2)
r""" KNOWN ISSUE:
It will also can NOT remove some files in some Windows, such as 'Windows Server 2012'
Because file maybe used by a program named "Print Filter Pipeline Host",
"C:\Windows\System32\printfilterpipelinesvc.exe"
It will throw out 'WindowsError: [Error 32]' exception again.
"""
os.remove(path_to_remove)
except Exception as e:
print e
print e.args
print e.message
print "file removed: {file}".format(file=path_to_remove)
status_code = win32serviceutil.QueryServiceStatus(service_name)[1]
if status_code != win32service.SERVICE_RUNNING and status_code != win32service.SERVICE_START_PENDING:
print "starting service {service}".format(service=service_name)
win32serviceutil.StartService(serviceName=service_name)
else:
print "current printer spooler in good state, skipped."
else:
print "Error: {path} not found, system files broken!".format(path=path)
sys.exit(1)
status_code = win32serviceutil.QueryServiceStatus(service_name)[1]
if status_code == win32service.SERVICE_RUNNING or status_code == win32service.SERVICE_START_PENDING:
print "[OK] reset printer spooler service successfully!"
else:
print "current service code is {code}, and service state is {state}.".format(code=status_code,
state=status_code_map[status_code])
try:
print "trying start spooler service..."
win32serviceutil.StartService(serviceName=service_name)
status_code = win32serviceutil.QueryServiceStatus(service_name)[1]
if status_code == win32service.SERVICE_RUNNING or status_code == win32service.SERVICE_START_PENDING:
print "service {service} started.".format(service=service_name)
except Exception as e:
print e
print [msg for msg in e.args]
def printer_watchdog():
print win32print.EnumPrinters(win32print.PRINTER_ENUM_LOCAL) # get local printers
print win32print.EnumPrinters(win32print.PRINTER_ENUM_CONNECTIONS) # get printers which other computer shared
default_printer_name = win32print.GetDefaultPrinter()
printer = win32print.OpenPrinter(default_printer_name)
print win32print.GetPrinter(printer)
jobs_list = list()
total_seconds = 60 * 5 # reset after 60*5 seconds, see 'known issue 2' in this file.
sleep_seconds = 10
times = total_seconds / sleep_seconds
current_times = 0
while True:
jobs = win32print.EnumJobs(printer, 0, 3, 1)
# except: pywintypes.error: (1722, 'EnumJobs', 'RPC 服务器不可用。'), ignored this except
# 0 is location of first job,
# 3 is number of jobs to enumerate,
# 1 is job info level, can be 1(win32print.JOB_INFO_1), 2, 3. 3 is reserved, 1 and 2 can NOT get job status, :(
if len(jobs) >= 1:
for job in jobs:
filename = job.get('pDocument')
job_id = job.get('JobId', md5(filename).hexdigest())
job_status = job.get('Status', 0)
if job_status in [0x00000002, 0x00000004, 0x00000800]: # JOB_STATUS_ERROR
"""
Refers:
https://docs.microsoft.com/en-us/windows/desktop/printdocs/job-info-2
~\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\WinSDK\Include\WinSpool.h
"""
print "printer need to be reset, ... "
reset_printer()
jobs_list = [] # make sure there are not same job id in list
current_times = 0
print "Current job: ", job_id, job.get('pUserName'), job.get('Submitted'), job.get(
'pMachineName'), filename, "[ %d/%d ]" % (times, current_times + 1)
jobs_list.append(job_id)
# if any([jid in jobs_list for jid in (jobs[0].get('JobId'), jobs[-1].get('JobId'))]):
# current_times += 1
if Counter(jobs_list).most_common(1)[0][1] > 1:
current_times += 1
if current_times > times:
""" KNOWN ISSUE 2:
It will reset when a document sends lots of pages to printer.
This script may reset printer before job finished which is not expected.
"""
print "printer need to be reset, ... "
reset_printer()
jobs_list = [] # make sure there are not same job id in list
current_times = 0
else:
jobs_list = []
current_times = 0
print 'looks good, keep watching ...'
time.sleep(sleep_seconds)
if __name__ == '__main__':
printer_watchdog()
| [
"uberurey_ups@163.com"
] | uberurey_ups@163.com |
d1babdca76706a0ad8ca6d2dd9ec579794454141 | dbfc0e0fc2067bf21269dd0a83a529bae238a011 | /orders/urls.py | c258f6e6c5847a4997ab62d36cfc555010cec37b | [] | no_license | Thib-G/cs50project3 | 351cd117752beeeddf57a63f36be6fc1dfae2243 | cf1b2a0efb520805ac77e3b157c85ff7ea374821 | refs/heads/master | 2021-06-21T05:32:27.493974 | 2020-12-21T16:36:33 | 2020-12-21T16:36:33 | 144,454,723 | 0 | 2 | null | null | null | null | UTF-8 | Python | false | false | 326 | py | from django.urls import path
from . import views
app_name = 'orders'
urlpatterns = [
path('', views.IndexView.as_view(), name='index'),
path('cart/', views.CartView.as_view(), name='cart'),
path('cart/add', views.add_to_cart, name='add_to_cart'),
path('cart/delete', views.delete_cart, name='delete_cart')
]
| [
"thibaut.g@protonmail.com"
] | thibaut.g@protonmail.com |
1a9a4270be4ff626f37d62e737ec76b8fe34e6f2 | ca7e190dc8551264417964029473532761e0e9cd | /14/main.py | 620b0846477066fb9c18c5063e9fe9d07414a3ff | [] | no_license | leonleon123/AoC2020 | f872c9f9e2bbc5a8b817c3e612d082825297a332 | 4a2c879ca4490a88a07fc27506edae63f5366223 | refs/heads/master | 2023-02-07T05:12:06.198011 | 2020-12-25T18:01:48 | 2020-12-25T18:01:48 | 317,612,607 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 764 | py | def sub_bin(tmp, i, n, c):
for x in bin(i)[2:].zfill(n):
tmp[tmp.index(c)] = x
return "".join(tmp)
def replace_floating(adr, mask):
n, adr = mask.count("X"), [m if m in "1X" else v for m, v in zip(mask, adr)]
return [sub_bin([*adr], i, n, "X") for i in range(2**n)]
with open("input.txt") as file:
p1, p2 = {}, {}
for line in file.read().split("\n"):
adr, val = line.split(" = ")
if adr == "mask":
mask = val
else:
p1[int(adr[4:-1])] = (int(val) | int(mask.replace("X", "0"), 2)) & int(mask.replace("X", "1"), 2)
for a in replace_floating(bin(int(adr[4:-1]))[2:].zfill(36), mask):
p2[a] = int(val)
print(sum(p1.values()), sum(p2.values()), sep="\n")
| [
"lele.slav@gmail.com"
] | lele.slav@gmail.com |
635200a8db1ecb79752b90c7330d891670f8b070 | 9d7d88cc4dc326993c6be9ba2a79b5afe86254c5 | /tests/layers/test_position_embedding.py | c110c9a2872554a666f6bd1bc69f201b2421ab25 | [] | no_license | LeeKLTW/posner | 7ebe0e287c8a9db91e150ba08c41772757b2639f | 9a1c6e00c463644a78ebf413b676c74c846dc23d | refs/heads/master | 2022-12-16T17:32:38.327191 | 2020-02-26T11:50:47 | 2020-02-26T11:50:47 | 240,471,085 | 5 | 1 | null | 2022-12-08T03:36:50 | 2020-02-14T09:22:13 | Python | UTF-8 | Python | false | false | 2,839 | py | # -*- coding: utf-8 -*-
import os
import tempfile
import unittest
import numpy as np
from tensorflow import keras
from posner.layers import PositionEmbedding
class TestSinCosPosEmbd(unittest.TestCase):
def test_invalid_output_dim(self):
with self.assertRaises(NotImplementedError):
PositionEmbedding(
mode=PositionEmbedding.MODE_EXPAND,
output_dim=5,
)
def test_missing_output_dim(self):
with self.assertRaises(NotImplementedError):
PositionEmbedding(
mode=PositionEmbedding.MODE_EXPAND,
)
def test_add(self):
seq_len = np.random.randint(1, 10)
embed_dim = np.random.randint(1, 20) * 2
inputs = np.ones((1, seq_len, embed_dim))
model = keras.models.Sequential()
model.add(PositionEmbedding(
input_shape=(seq_len, embed_dim),
mode=PositionEmbedding.MODE_ADD,
name='Pos-Embd',
))
model.compile('adam', 'mse')
model_path = os.path.join(tempfile.gettempdir(),
'pos_embd_%f.h5' % np.random.random())
model.save(model_path)
model = keras.models.load_model(model_path, custom_objects={
'PositionEmbedding': PositionEmbedding})
model.summary()
predicts = model.predict(inputs)[0].tolist()
for i in range(seq_len):
for j in range(embed_dim):
actual = predicts[i][j]
if j % 2 == 0:
expect = 1.0 + np.sin(i / 10000.0 ** (float(j) / embed_dim))
else:
expect = 1.0 + np.cos(i / 10000.0 ** ((j - 1.0) / embed_dim))
self.assertAlmostEqual(expect, actual, places=6,
msg=(embed_dim, i, j, expect, actual))
def test_concat(self):
seq_len = np.random.randint(1, 10)
feature_dim = np.random.randint(1, 20)
embed_dim = np.random.randint(1, 20) * 2
inputs = np.ones((1, seq_len, feature_dim))
model = keras.models.Sequential()
model.add(PositionEmbedding(
input_shape=(seq_len, feature_dim),
output_dim=embed_dim,
mode=PositionEmbedding.MODE_CONCAT,
name='Pos-Embd',
))
model.compile('adam', 'mse')
model_path = os.path.join(tempfile.gettempdir(),
'test_pos_embd_%f.h5' % np.random.random())
model.save(model_path)
model = keras.models.load_model(model_path, custom_objects={
'PositionEmbedding': PositionEmbedding})
model.summary()
predicts = model.predict(inputs)[0].tolist()
for i in range(seq_len):
for j in range(embed_dim):
actual = predicts[i][feature_dim + j]
if j % 2 == 0:
expect = np.sin(i / 10000.0 ** (float(j) / embed_dim))
else:
expect = np.cos(i / 10000.0 ** ((j - 1.0) / embed_dim))
self.assertAlmostEqual(expect, actual, places=6,
msg=(embed_dim, i, j, expect, actual))
| [
"LeeKLTW@gmail.com"
] | LeeKLTW@gmail.com |
8fa6f2a0ca82a11c4141dd2ad51069fac2099528 | 9e9c0790cc04642ee177d0980b6b0130905405e6 | /misc/webdriver-w3c-tests/client/exceptions.py | a92abf0206317521fdceaefb3d436ee1ceba198e | [
"BSD-3-Clause"
] | permissive | zhuyongyong/crosswalk-test-suite | 9b2c6f8ba55b4461c4b05c07b27e0f5bdf46974b | 24f3f8cfa663a365b0a22685d5bd096a637f72db | refs/heads/master | 2021-01-23T21:03:44.786333 | 2016-06-28T05:22:50 | 2016-06-28T05:22:50 | 20,671,988 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,513 | py | """Definition of WebDriverException classes."""
def create_webdriver_exception_strict(status_code, message):
"""Create the appropriate WebDriverException given the status_code."""
if status_code in _exceptions_strict:
return _exceptions_strict[status_code](message)
return UnknownStatusCodeException("[%s] %s" % (status_code, message))
def create_webdriver_exception_compatibility(status_code, message):
"""Create the appropriate WebDriverException given the status_code."""
if status_code in _exceptions_compatibility:
return _exceptions_compatibility[status_code](message)
return UnknownStatusCodeException("[%s] %s" % (status_code, message))
class WebDriverException(Exception):
"""Base class for all WebDriverExceptions."""
class UnableToSetCookieException(WebDriverException):
"""A request to set a cookie's value could not be satisfied."""
class InvalidElementStateException(WebDriverException):
"""An element command could not be completed because the element is
in an invalid state (e.g. attempting to click an element that is no
longer attached to the DOM).
"""
class NoSuchElementException(WebDriverException):
"""An element could not be located on the page using the given
search parameters.
"""
class TimeoutException(WebDriverException):
"""An operation did not complete before its timeout expired."""
class ElementNotSelectableException(InvalidElementStateException):
"""An attempt was made to select an element that cannot be selected."""
class ElementNotVisibleException(InvalidElementStateException):
"""An element command could not be completed because the element is
not visible on the page.
"""
class ImeEngineActivationFailedException(WebDriverException):
"""An IME engine could not be started."""
class ImeNotAvailableException(ImeEngineActivationFailedException):
"""IME was not available."""
class InvalidCookieDomainException(UnableToSetCookieException):
"""An illegal attempt was made to set a cookie under a different
domain than the current page.
"""
class InvalidElementCoordinatesException(WebDriverException):
"""The coordinates provided to an interactions operation are invalid."""
class InvalidSelectorException(NoSuchElementException):
"""Argument was an invalid selector (e.g. XPath/CSS)."""
class JavascriptErrorException(WebDriverException):
"""An error occurred while executing user supplied JavaScript."""
class MoveTargetOutOfBoundsException(InvalidElementStateException):
"""The target for mouse interaction is not in the browser's viewport
and cannot be brought into that viewport.
"""
class NoSuchAlertException(WebDriverException):
"""An attempt was made to operate on a modal dialog when one was not open."""
class NoSuchFrameException(WebDriverException):
"""A request to switch to a frame could not be satisfied because
the frame could not be found."""
class NoSuchWindowException(WebDriverException):
"""A request to switch to a different window could not be satisfied
because the window could not be found.
"""
class ScriptTimeoutException(TimeoutException):
"""A script did not complete before its timeout expired."""
class SessionNotCreatedException(WebDriverException):
"""A new session could not be created."""
class StaleElementReferenceException(InvalidElementStateException):
"""An element command failed because the referenced element is no
longer attached to the DOM.
"""
class UnexpectedAlertOpenException(WebDriverException):
"""A modal dialog was open, blocking this operation."""
class UnknownCommandException(WebDriverException):
"""A command could not be executed because the remote end is not
aware of it.
"""
class UnknownErrorException(WebDriverException):
"""An unknown error occurred in the remote end while processing
the command.
"""
class UnsupportedOperationException(WebDriverException):
"""Indicates that a command that should have executed properly
cannot be supported for some reason.
"""
class UnknownStatusCodeException(WebDriverException):
"""Exception for all other status codes."""
_exceptions_strict = {
"element not selectable": ElementNotSelectableException,
"element not visible": ElementNotVisibleException,
"ime engine activation failed": ImeEngineActivationFailedException,
"ime not available": ImeNotAvailableException,
"invalid cookie domain": InvalidCookieDomainException,
"invalid element coordinates": InvalidElementCoordinatesException,
"invalid element state": InvalidElementStateException,
"invalid selector": InvalidSelectorException,
"javascript error": JavascriptErrorException,
"move target out of bounds": MoveTargetOutOfBoundsException,
"no such alert": NoSuchAlertException,
"no such element": NoSuchElementException,
"no such frame": NoSuchFrameException,
"no such window": NoSuchWindowException,
"script timeout": ScriptTimeoutException,
"session not created": SessionNotCreatedException,
"stale element reference": StaleElementReferenceException,
"success": None,
"timeout": TimeoutException,
"unable to set cookie": UnableToSetCookieException,
"unexpected alert open": UnexpectedAlertOpenException,
"unknown command": UnknownCommandException,
"unknown error": UnknownErrorException,
"unsupported operation": UnsupportedOperationException,
}
_exceptions_compatibility = {
15: ElementNotSelectableException,
11: ElementNotVisibleException,
31: ImeEngineActivationFailedException,
30: ImeNotAvailableException,
24: InvalidCookieDomainException,
29: InvalidElementCoordinatesException,
12: InvalidElementStateException,
19: InvalidSelectorException,
32: InvalidSelectorException,
17: JavascriptErrorException,
34: MoveTargetOutOfBoundsException,
27: NoSuchAlertException,
7: NoSuchElementException,
8: NoSuchFrameException,
23: NoSuchWindowException,
28: ScriptTimeoutException,
6: SessionNotCreatedException,
33: SessionNotCreatedException,
10: StaleElementReferenceException,
0: None, # success
21: TimeoutException,
25: UnableToSetCookieException,
26: UnexpectedAlertOpenException,
9: UnknownCommandException,
13: UnknownErrorException,
# "unsupported operation": UnsupportedOperationException
}
| [
"zhiqiang.zhang@intel.com"
] | zhiqiang.zhang@intel.com |
32a8c7009b65c10a721a5143e21f6c5b7b0b11bc | fec9a37e270cb57c3894ecd14ab1a85d7a48d738 | /exercises/test5.py | 52448a9644a27ef18429325391d085cc9250d834 | [] | no_license | ianlaiky/DeepLearningTensorflowNew | d76e430d87cd2ecdb8c4efaf55e46fafc7947dc5 | f44dd7794faecbfd7efa5fb993f6db206efcaa1b | refs/heads/master | 2021-04-28T03:41:20.302868 | 2018-02-20T08:28:48 | 2018-02-20T08:28:48 | 122,145,040 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,459 | py | import tensorflow as tf
# step 1: pre-process the data
from tensorflow.examples.tutorials.mnist import input_data
#skipped
# CIFAR-10 dataset from Keras
from tensorflow.python.keras.datasets import cifar10
(X_train, y_train), (X_test, y_test) = cifar10.load_data()
X_train = cifar10.train.images
y_train = cifar10.train.labels
X_test = cifar10.test.images
y_test = cifar10.test.labels
x = tf.placeholder(tf.float32, [None, 784])
y = tf.placeholder(tf.float32, [None, 10])
W = tf.Variable(tf.truncated_normal([784, 10], stddev=0.1))
b = tf.Variable(tf.truncated_normal([10], stddev=0.1))
# step 2: setup the model
yhat = tf.nn.softmax(tf.matmul(x, W) + b)
# step 3: define the loss function
loss = -tf.reduce_sum(y * tf.log(yhat))
# step 4: define the optimiser
train = tf.train.GradientDescentOptimizer(0.01).minimize(loss)
# step 5: train the mode
is_correct = tf.equal(tf.argmax(y, 1), tf.argmax(yhat, 1))
accuracy = tf.reduce_mean(tf.cast(is_correct, tf.float32))
sess = tf.Session()
init = tf.global_variables_initializer()
sess.run(init)
for i in range(1000):
batch_X, batch_y = mnist.train.next_batch(100)
train_data = {x: batch_X, y: batch_y}
sess.run(train, feed_dict=train_data)
print(i + 1, "Training Accuracy = ", sess.run(accuracy, feed_dict=train_data))
# step 6:evaulate the model
test_data = {x: X_test, y: y_test}
print("Testing accuracy =", sess.run(accuracy, feed_dict=test_data))
# step 7: save the model
| [
"152772a@mymail.nyp.edu.sg"
] | 152772a@mymail.nyp.edu.sg |
4b9e5e9bcb60bd8d5541609d8aa0a1987ed39d88 | df57e8fdf253130ff4ada4a9d3848f26734a0927 | /Machine Learning A-Z - udemy - superdatascience/import.py | 8295eafa70cf950a7e9e78b839a33eb894dde79d | [] | no_license | tmPolla/Data_Scientists | 8ab752330db99ae7a1bee8e5c3ab31295ef2b4fd | 1a499d7c0477f1554316bab6a1e132e4637e12b7 | refs/heads/master | 2021-01-13T09:44:18.394625 | 2018-08-14T12:59:18 | 2018-08-14T12:59:18 | 76,177,897 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,503 | py | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 23 11:12:00 2018
@author: Polla
"""
import pandas as pd
dataset=pd.read_csv('Data.csv')
print(dataset)
X=dataset.iloc[:,:-1].values
print("X values are:")
print(X)
y=dataset.iloc[:,3].values
print("y values are:")
print(y)
# MIMSSING DATA
from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values='NaN', strategy= 'mean', axis=0)
imputer.fit(X[:,1:3])
X[:, 1:3]=imputer.transform(X[:, 1:3])
print("X values are after the imputer")
print(X)
#CATEGORICAL AND DUMMY VARIABLE
# Categorical variable transform to integer
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_X=LabelEncoder()
# country column
X[:,0] = labelencoder_X.fit_transform(X[:,0])
print("X values are after the first labelencoder")
print(X)
# create dummy variables
onehotencoder=OneHotEncoder(categorical_features=[0])
X = onehotencoder.fit_transform(X).toarray()
print("X values are after the first dummy transform")
print(X)
labelencoder_y=LabelEncoder()
y = labelencoder_y.fit_transform(y)
# SPLITTING TRAIN AND TEST SET
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size=0.2, random_state=0)
#random_state=0 if we would like to see the same result
# FEATURE SCALING
from sklearn.preprocessing import StandardScaler
sc_X=StandardScaler()
X_train = sc_X.fit_transform(X_train)
X_test = sc_X.transform(X_test)
| [
"noreply@github.com"
] | tmPolla.noreply@github.com |
e94874c2604b0d7e7933ff6e49dd6c0d433bcf83 | 981bbfb302606f25f34e15c74237a80d6868f190 | /053.Maximum Subarray/solution.py | 050e4cd01e3f19afa65d2c5df60cdcb0808539d0 | [
"MIT"
] | permissive | lovexln001/LeetCode | f2d1f659666e9eb4fa339f1b2f4a6c015eca9d83 | 5ca0e743a4f10ac5f6cdf3314f6c81d356181f81 | refs/heads/master | 2020-03-11T18:06:36.816136 | 2018-05-08T14:55:10 | 2018-05-08T14:55:10 | 130,167,428 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 312 | py | #!/usr/bin/env python
# encoding: utf-8
class Solution(object):
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
l = g =float("-inf")
for num in nums:
l = max(num,l+num)
g = max(g,l)
return g
| [
"lovexln001@163.com"
] | lovexln001@163.com |
17a5b8659e14c201ad12ac9f18525fb17aba949f | 674f5dde693f1a60e4480e5b66fba8f24a9cb95d | /armulator/armv6/opcodes/concrete/add_sp_plus_register_thumb_t3.py | 1df3c88b2a6cafe7aa3816167f947a12888f3b06 | [
"MIT"
] | permissive | matan1008/armulator | 75211c18ebc9cd9d33a02890e76fc649483c3aad | 44f4275ab1cafff3cf7a1b760bff7f139dfffb07 | refs/heads/master | 2023-08-17T14:40:52.793120 | 2023-08-08T04:57:02 | 2023-08-08T04:57:02 | 91,716,042 | 29 | 7 | MIT | 2023-08-08T04:55:59 | 2017-05-18T16:37:55 | Python | UTF-8 | Python | false | false | 919 | py | from armulator.armv6.bits_ops import substring, bit_at, chain
from armulator.armv6.opcodes.abstract_opcodes.add_sp_plus_register_thumb import AddSpPlusRegisterThumb
from armulator.armv6.shift import decode_imm_shift, SRType
class AddSpPlusRegisterThumbT3(AddSpPlusRegisterThumb):
@staticmethod
def from_bitarray(instr, processor):
rm = substring(instr, 3, 0)
type_ = substring(instr, 5, 4)
imm2 = substring(instr, 7, 6)
rd = substring(instr, 11, 8)
imm3 = substring(instr, 14, 12)
setflags = bit_at(instr, 20)
shift_t, shift_n = decode_imm_shift(type_, chain(imm3, imm2, 2))
if rd == 13 and (shift_t != SRType.LSL or shift_n > 3) or (rd == 15 and not setflags) or rm in (13, 15):
print('unpredictable')
else:
return AddSpPlusRegisterThumbT3(instr, setflags=setflags, m=rm, d=rd, shift_t=shift_t, shift_n=shift_n)
| [
"matan1008@gmail.com"
] | matan1008@gmail.com |
7f62c8837ee86647e3a52e1060c0c72187d0a97e | d68ee9d9351a819a1e26ff72c04455c768599543 | /python/miniGL/material.py | 6c1a9d676eff9cf51bab01ea504b0016948382d1 | [] | no_license | donkaban/3d-i-free | 4b1a5652a3ca822e66a1c4ca0bd59588da677e91 | 53f2f746bd3bf93a110c3021ad02a4ce30cb1714 | refs/heads/master | 2020-04-17T17:00:08.332527 | 2015-02-21T17:27:43 | 2015-02-21T17:27:43 | 20,293,925 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,146 | py | from OpenGL.GL import *
from OpenGL.GLUT import *
class Material:
__id = None
__cache = {}
def __init__(self, tag, vertex, fragment):
if tag in Material.__cache:
print 'load material {0:s} from cache'.format(tag)
self.__id = Material.__cache[tag]
else:
v_str = open(vertex).read()
f_str = open(fragment).read()
vsh = self.__compile(v_str, GL_VERTEX_SHADER)
fsh = self.__compile(f_str, GL_FRAGMENT_SHADER)
self.__id = self.__link(vsh, fsh)
Material.__cache[tag] = self.__id
print 'create material {0:s}'.format(tag)
@staticmethod
def __compile(source, shader_type):
shader = glCreateShader(shader_type)
glShaderSource(shader, source)
glCompileShader(shader)
result = glGetShaderiv(shader, GL_COMPILE_STATUS)
if not result:
raise RuntimeError('shader compile error : {0:s}'.format(glGetShaderInfoLog(shader)))
return shader
@staticmethod
def __link(vsh, fsh):
prg = glCreateProgram()
glAttachShader(prg, vsh)
glAttachShader(prg, fsh)
glLinkProgram(prg)
glValidateProgram(prg)
if glGetProgramiv(prg, GL_VALIDATE_STATUS) == GL_FALSE:
raise RuntimeError('shader link error : {0:s}'.format(glGetProgramInfoLog(prg)))
return prg
def set_attributes(self):
pos_id = glGetAttribLocation(self.__id, 'position')
tex_id = glGetAttribLocation(self.__id, 'texcoord')
nor_id = glGetAttribLocation(self.__id, 'normal')
if pos_id != -1:
glVertexAttribPointer(pos_id, 3, GL_FLOAT, GL_FALSE, 32, None)
glEnableVertexAttribArray(pos_id)
if tex_id != -1:
glVertexAttribPointer(tex_id, 2, GL_FLOAT, GL_FALSE, 32, ctypes.c_void_p(12))
glEnableVertexAttribArray(tex_id)
if nor_id != -1:
glVertexAttribPointer(nor_id, 3, GL_FLOAT, GL_FALSE, 32, ctypes.c_void_p(20))
glEnableVertexAttribArray(nor_id)
def set_uniform_matrix(self, k, value):
uid = glGetUniformLocation(self.__id, k)
if uid != -1:
glUniformMatrix4fv(uid, 1, GL_FALSE, value)
def set_uniform_vec4(self, k, x, y, z, w):
uid = glGetUniformLocation(self.__id, k)
if uid != -1:
glUniform4f(uid, x, y, z, w)
def set_uniform_vec3(self, k, x, y, z):
uid = glGetUniformLocation(self.__id, k)
if uid != -1:
glUniform3f(uid, x, y, z)
def set_uniform_float(self, k, value):
uid = glGetUniformLocation(self.__id, k)
if uid != -1:
glUniform1f(uid, value)
def set_texture(self, num, texture):
t = [GL_TEXTURE0, GL_TEXTURE1, GL_TEXTURE2, GL_TEXTURE3]
n = ['texture0', 'texture1', 'texture2', 'texture3']
uid = glGetUniformLocation(self.__id, n[num])
if uid != -1:
glActiveTexture(t[num])
glBindTexture(GL_TEXTURE_2D, texture.id)
glUniform1i(uid, num)
@property
def id(self):
return self.__id
| [
"k.shabordin@gmail.com"
] | k.shabordin@gmail.com |
187fa1300ef6602cc7e96f49e8b17d48262718c8 | d8522d4045e9fd04c82ae28c0be37f20cd99cac3 | /test/test_kana_model.py | 9026af56fb4be411662e96867905868544be073c | [] | no_license | AuTa/aniseed | 3c1dd9b2cff3c0c4403633006e426fc66ab6ca06 | b5f2da6a3450531b4337aa24f6e572132d34589f | refs/heads/master | 2021-01-11T11:56:49.866251 | 2016-12-17T03:22:19 | 2016-12-17T03:22:19 | 76,701,292 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,146 | py | # coding: utf-8
import unittest
from app.models import Kana, PronunciationOfKanamoji
from app import create_app
from database import SQLALCHEMY
from flask import current_app
class KanaModelTestCase(unittest.TestCase):
def setUp(self):
self.db = SQLALCHEMY('testing')
self.db.create_all()
def tearDown(self):
self.db.drop_all()
def test_pronun(self):
PronunciationOfKanamoji.insert_pronunciations(self.db)
with self.db.session as session:
pronun = PronunciationOfKanamoji.query(session) \
.filter_by(character='Seion').first()
self.assertTrue(pronun is not None)
def test_kana(self):
PronunciationOfKanamoji.insert_pronunciations(self.db)
Kana.insert_kanas(self.db)
with self.db.session as session:
kana = Kana.query(session).filter_by(romaji='a').first()
self.assertTrue(kana.hiragana == 'あ')
character = PronunciationOfKanamoji.query(session) \
.filter_by(id=kana.pronunciation_id) \
.first().character
self.assertTrue(character == 'Seion')
| [
"auta520@live.com"
] | auta520@live.com |
2c4b2b0ec91552fe1678a062a6205b317a38e054 | a829f1cf62f7ec5bc339a5dce62e988a03e494ff | /pyscripts/decorator.py | 77545362c77987d66a9cfe21d26c00b4a33d5d4e | [] | no_license | satyamsoni2211/pyprojects | ae01c6ddd966299d703c906f77355907e573cada | bbe05e6cd63bdf83469d6a45fb0165142a5598af | refs/heads/master | 2020-03-10T17:40:20.079073 | 2018-04-24T16:57:13 | 2018-04-24T16:57:13 | 129,505,540 | 0 | 0 | null | 2018-04-14T19:56:42 | 2018-04-14T10:09:35 | Python | UTF-8 | Python | false | false | 995 | py |
import os
import logging
global loggers
loggers = {}
def dec(func):
def wrapper(*args,**kwargs):
logger = getlog(func.__name__) #gettng the logger handle
logger.info('This is decorator for function {}'.format(func.__name__))
logger.info('calling function {}'.format(func.__name__))
logger.info('calling function {} with arguments {}'.format(func.__name__,' '.join([str(i) for i in args])))
return func(*args,**kwargs)
return wrapper
def getlog(name):
global loggers
if name in loggers.keys():
return loggers[name]
else:
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(name)
handler = logging.FileHandler('{}.log'.format(name))
handler.setLevel(logging.INFO)
logger.addHandler(handler)
loggers[name] = logger
return logger
@dec
def identity(a):
print('id for var {} is {}'.format(a,id(a)))
@dec
def sums(a):
b = 1
return a+b
b = 'satyam'
a = 2
print(identity.__name__)
identity(b)
print('calling sums')
print(sums(a)) | [
"satyamsoni@hotmail.co.uk"
] | satyamsoni@hotmail.co.uk |
c0a7b464a516649b519144925a7eeb68171d5a74 | 7a5e9c806d3ebd93d387918a1d258021d447a47d | /base/driver.py | 57416a17705398413bd1cb0b3e1cdab8356cdbed | [] | no_license | Liu-01/pytest-yaml-appium | 5e70a515c6f1caeb892de5618031256c7a1021c8 | cb0c9b246eceb9a6600ec7f6b0cbc0c30c9ff0ee | refs/heads/master | 2022-08-05T06:26:16.783242 | 2020-05-25T14:23:11 | 2020-05-25T14:23:11 | 266,798,165 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 818 | py | '''
这里构建一个安卓驱动
'''
from appium import webdriver
def init_dirver():
desired_caps=dict()
# 系统名
desired_caps['platformName']='Android'
# 设备版本
desired_caps['platformVersion']='5.1.1'
# 设备名
desired_caps['deviceName']='116cfa91'
# 包名
desired_caps['appPackage']='com.android.settings'
# 启动名
desired_caps['appActivity']='.Settings'
# 允许中文输入
desired_caps['unicodeKeyboard']='True'
# 收起键盘
desired_caps['resetKeyboard']='True'
# 自动打开程序
desired_caps['autoLaunch']='False'
# 重置应用
desired_caps['noReset']='True'
# toast
desired_caps['automationName']='uiautomator2'
driver=webdriver.Remote('http://127.0.0.1:4723/wd/hub',desired_caps)
return driver | [
"1558826079@qq.com"
] | 1558826079@qq.com |
0e02aa64e88f8cd0103a0bc833aa86ea0ea95fbc | f68afe06e4bbf3d523584852063e767e53441b2b | /Toontown/toontown/toon/DistributedNPCToonBase.py | d205a2543f853382aff51eef5c62dc2aa6178d61 | [] | no_license | DankMickey/Toontown-Offline-Squirting-Flower-Modded- | eb18908e7a35a5f7fc95871814207858b94e2600 | 384754c6d97950468bb62ddd8961c564097673a9 | refs/heads/master | 2021-01-19T17:53:36.591832 | 2017-01-15T02:00:04 | 2017-01-15T02:00:04 | 34,639,744 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 4,444 | py | from pandac.PandaModules import *
from otp.nametag.NametagGroup import NametagGroup
from direct.directnotify import DirectNotifyGlobal
from direct.fsm import ClassicFSM
from direct.fsm import State
from toontown.toonbase import ToontownGlobals
import DistributedToon
from direct.distributed import DistributedObject
import NPCToons
from toontown.quest import Quests
from direct.distributed import ClockDelta
from toontown.quest import QuestParser
from toontown.quest import QuestChoiceGui
from direct.interval.IntervalGlobal import *
import random
class DistributedNPCToonBase(DistributedToon.DistributedToon):
def __init__(self, cr):
try:
self.DistributedNPCToon_initialized
except:
self.DistributedNPCToon_initialized = 1
DistributedToon.DistributedToon.__init__(self, cr)
self.__initCollisions()
self.setPickable(0)
self.setPlayerType(NametagGroup.CCNonPlayer)
def disable(self):
self.ignore('enter' + self.cSphereNode.getName())
DistributedToon.DistributedToon.disable(self)
def delete(self):
try:
self.DistributedNPCToon_deleted
except:
self.DistributedNPCToon_deleted = 1
self.__deleteCollisions()
DistributedToon.DistributedToon.delete(self)
def generate(self):
DistributedToon.DistributedToon.generate(self)
self.cSphereNode.setName(self.uniqueName('NPCToon'))
self.detectAvatars()
self.setParent(ToontownGlobals.SPRender)
self.startLookAround()
def generateToon(self):
self.setLODs()
self.generateToonLegs()
self.generateToonHead()
self.generateToonTorso()
self.generateToonColor()
self.parentToonParts()
self.rescaleToon()
self.resetHeight()
self.rightHands = []
self.leftHands = []
self.headParts = []
self.hipsParts = []
self.torsoParts = []
self.legsParts = []
self.__bookActors = []
self.__holeActors = []
def announceGenerate(self):
self.initToonState()
DistributedToon.DistributedToon.announceGenerate(self)
def initToonState(self):
self.setAnimState('neutral', 0.9, None, None)
npcOrigin = render.find('**/npc_origin_' + str(self.posIndex))
if not npcOrigin.isEmpty():
self.reparentTo(npcOrigin)
self.initPos()
def initPos(self):
self.clearMat()
def wantsSmoothing(self):
return 0
def detectAvatars(self):
self.accept('enter' + self.cSphereNode.getName(), self.handleCollisionSphereEnter)
def ignoreAvatars(self):
self.ignore('enter' + self.cSphereNode.getName())
def getCollSphereRadius(self):
return 3.25
def __initCollisions(self):
self.cSphere = CollisionTube(0.0, 1.0, 0.0, 0.0, 1.0, 5.0, self.getCollSphereRadius())
self.cSphere.setTangible(0)
self.cSphereNode = CollisionNode('cSphereNode')
self.cSphereNode.addSolid(self.cSphere)
self.cSphereNodePath = self.attachNewNode(self.cSphereNode)
self.cSphereNodePath.hide()
self.cSphereNode.setCollideMask(ToontownGlobals.WallBitmask)
def __deleteCollisions(self):
del self.cSphere
del self.cSphereNode
self.cSphereNodePath.removeNode()
del self.cSphereNodePath
def handleCollisionSphereEnter(self, collEntry):
pass
def setupAvatars(self, av):
self.ignoreAvatars()
av.headsUp(self, 0, 0, 0)
self.headsUp(av, 0, 0, 0)
av.stopLookAround()
av.lerpLookAt(Point3(-0.5, 4, 0), time=0.5)
self.stopLookAround()
self.lerpLookAt(Point3(av.getPos(self)), time=0.5)
def b_setPageNumber(self, paragraph, pageNumber):
self.setPageNumber(paragraph, pageNumber)
self.d_setPageNumber(paragraph, pageNumber)
def d_setPageNumber(self, paragraph, pageNumber):
timestamp = ClockDelta.globalClockDelta.getFrameNetworkTime()
self.sendUpdate('setPageNumber', [paragraph, pageNumber, timestamp])
def freeAvatar(self):
base.localAvatar.posCamera(0, 0)
base.cr.playGame.getPlace().setState('walk')
def setPositionIndex(self, posIndex):
self.posIndex = posIndex
def _startZombieCheck(self):
pass
def _stopZombieCheck(self):
pass
| [
"jareddarty96@gmail.com"
] | jareddarty96@gmail.com |
0f92d183dd80697c0761f9cf3934f51b3b3fd1d8 | 9ad21dda46963fcdfe1e908596745d1d97be3dbc | /models/amenity.py | 311c788d33abae282b7e95c9912d537cf31539e6 | [
"LicenseRef-scancode-public-domain"
] | permissive | mj31508/AirBnB_clone_v2 | ef903558983fc84ca7b31d20a40eedad9e622979 | c676bc5fc6184aeb38f8669f7d295fef06e57165 | refs/heads/master | 2021-01-19T17:59:20.638896 | 2017-09-07T00:37:03 | 2017-09-07T00:37:03 | 101,103,176 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 731 | py | #!/usr/bin/python3
"""
Amenity Class from Models Module
"""
from models.base_model import BaseModel, Base, Column, String, Table
from sqlalchemy.orm import relationship, backref
from os import getenv
class Amenity(BaseModel):
"""Amenity class handles all application amenities"""
if getenv("HBNB_TYPE_STORAGE") == "db":
__tablename__ = "amenities"
name = Column(String(128), nullable=False)
place_amenities = relationship("PlaceAmenity", backref="amenities",
cascade="all, delete, delete-orphan")
else:
name = ""
def __init__(self, *args, **kwargs):
"""instantiates a new amenity"""
super().__init__(self, *args, **kwargs)
| [
"mj31508@gmail.com"
] | mj31508@gmail.com |
e01b46a13eff35b59fd20f81fd9afde4896971a0 | 0bf97b013a50470996c6f945eb97a006791d17c5 | /reefsource/core/rest_framework/validators.py | 8e282937c993881591ff54199408d6a47dcf5f87 | [] | no_license | reefsource/reefsource | 8df0ce6df71b7bef48e964beede148b99503ffe9 | b9b41cf3f153f7602d6e465a331eeca4dd2b5638 | refs/heads/development | 2021-01-20T14:58:54.204277 | 2017-09-14T05:44:05 | 2017-09-14T05:44:05 | 90,697,275 | 3 | 0 | null | 2017-08-28T07:42:26 | 2017-05-09T03:13:29 | Python | UTF-8 | Python | false | false | 228 | py | from rest_framework import serializers
class NonBlankValidator():
def __call__(self, value):
if not value:
message = 'This field must not be blank'
raise serializers.ValidationError(message) | [
"lkarolewski@gmail.com"
] | lkarolewski@gmail.com |
9824e8f3323ccaf51b83d8378449d3418e15c6d3 | d90d5449be9d0464b7c2ed5e58d790d423ff9f15 | /updates/migrations/0005_project_full_description.py | 6543d0bdcdb09bc846febcb0ccffed40ae4fdb04 | [] | no_license | iprnq9/msat | a767921b9af619023283fd9fc0c4cea1f9a8ad5a | 979bc4c1f898ee059d67a4faf62b8d447aa9c5da | refs/heads/master | 2020-07-05T19:14:34.010500 | 2016-11-17T03:02:41 | 2016-11-17T03:02:41 | 73,984,372 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 515 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.9.8 on 2016-11-13 02:11
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('updates', '0004_project_quick_description'),
]
operations = [
migrations.AddField(
model_name='project',
name='full_description',
field=models.TextField(default='Full description'),
preserve_default=False,
),
]
| [
"iprnq9@mst.edu"
] | iprnq9@mst.edu |
f49797c0281db20c2228be300124006e55582419 | c1e83561f44fa384bc7f07e2da30a9fcd1c34f89 | /mmdet/models/detectors/__init__.py | 77ade1b8ed7cb61dd8103b41c7eb9bbebe6cfb03 | [
"Apache-2.0"
] | permissive | zehuichen123/mmdet1.0 | cba04e4d2a5f75ba52cd0545fd18f5bf61175780 | 6475512521fd2122dc5f26f5894b5444418d2b34 | refs/heads/master | 2022-11-11T11:16:22.458048 | 2020-06-27T11:06:16 | 2020-06-27T11:06:16 | 275,354,522 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 898 | py | from .atss import ATSS
from .base import BaseDetector
from .cascade_rcnn import CascadeRCNN
from .double_head_rcnn import DoubleHeadRCNN
from .fast_rcnn import FastRCNN
from .faster_rcnn import FasterRCNN
from .fcos import FCOS
from .fovea import FOVEA
from .grid_rcnn import GridRCNN
from .htc import HybridTaskCascade
from .mask_rcnn import MaskRCNN
from .mask_scoring_rcnn import MaskScoringRCNN
from .reppoints_detector import RepPointsDetector
from .retinanet import RetinaNet
from .rpn import RPN
from .single_stage import SingleStageDetector
from .two_stage import TwoStageDetector
from .solo import SOLO
__all__ = [
'ATSS', 'BaseDetector', 'SingleStageDetector', 'TwoStageDetector', 'RPN',
'FastRCNN', 'FasterRCNN', 'MaskRCNN', 'CascadeRCNN', 'HybridTaskCascade',
'DoubleHeadRCNN', 'RetinaNet', 'FCOS', 'GridRCNN', 'MaskScoringRCNN',
'RepPointsDetector', 'FOVEA', 'SOLO'
]
| [
"czh"
] | czh |
9ee5271e11b9372ae4941f2deb71115913141731 | 57c0e19529c3283be273b2a0339470ddcf470138 | /Mp3 Player.py | fd5e56a94533b487787b46cb7c891fe098edda4f | [
"Apache-2.0"
] | permissive | harishsg99/My-Week-end-products | a6b76b1573382d6229c1d9de6d24fe982b3eaa56 | bfdca740540270f90507c23adad0a6cd184950b8 | refs/heads/master | 2022-12-21T19:55:17.671587 | 2020-08-20T02:47:54 | 2020-08-20T02:47:54 | 286,051,692 | 2 | 0 | MIT | 2020-08-13T09:05:47 | 2020-08-08T13:48:17 | Python | UTF-8 | Python | false | false | 7,066 | py | import os
import threading
import time
import tkinter.messagebox
from tkinter import *
from tkinter import filedialog
from tkinter import ttk
from ttkthemes import themed_tk as tk
from mutagen.mp3 import MP3
from pygame import mixer
root = tk.ThemedTk()
root.get_themes() # Returns a list of all themes that can be set
root.set_theme("radiance") # Sets an available theme
# Fonts - Arial (corresponds to Helvetica), Courier New (Courier), Comic Sans MS, Fixedsys,
# MS Sans Serif, MS Serif, Symbol, System, Times New Roman (Times), and Verdana
#
# Styles - normal, bold, roman, italic, underline, and overstrike.
statusbar = ttk.Label(root, text="Welcome to Melody", relief=SUNKEN, anchor=W, font='Times 10 italic')
statusbar.pack(side=BOTTOM, fill=X)
# Create the menubar
menubar = Menu(root)
root.config(menu=menubar)
# Create the submenu
subMenu = Menu(menubar, tearoff=0)
playlist = []
# playlist - contains the full path + filename
# playlistbox - contains just the filename
# Fullpath + filename is required to play the music inside play_music load function
def browse_file():
global filename_path
filename_path = filedialog.askopenfilename()
add_to_playlist(filename_path)
mixer.music.queue(filename_path)
def add_to_playlist(filename):
filename = os.path.basename(filename)
index = 0
playlistbox.insert(index, filename)
playlist.insert(index, filename_path)
index += 1
menubar.add_cascade(label="File", menu=subMenu)
subMenu.add_command(label="Open", command=browse_file)
subMenu.add_command(label="Exit", command=root.destroy)
def about_us():
tkinter.messagebox.showinfo('About Melody', 'This is a music player build using Python Tkinter by Harish')
subMenu = Menu(menubar, tearoff=0)
menubar.add_cascade(label="Help", menu=subMenu)
subMenu.add_command(label="About Us", command=about_us)
mixer.init() # initializing the mixer
root.title("Melody")
root.iconbitmap(r'images/melody.ico')
# Root Window - StatusBar, LeftFrame, RightFrame
# LeftFrame - The listbox (playlist)
# RightFrame - TopFrame,MiddleFrame and the BottomFrame
leftframe = Frame(root)
leftframe.pack(side=LEFT, padx=30, pady=30)
playlistbox = Listbox(leftframe)
playlistbox.pack()
addBtn = ttk.Button(leftframe, text="+ Add", command=browse_file)
addBtn.pack(side=LEFT)
def del_song():
selected_song = playlistbox.curselection()
selected_song = int(selected_song[0])
playlistbox.delete(selected_song)
playlist.pop(selected_song)
delBtn = ttk.Button(leftframe, text="- Del", command=del_song)
delBtn.pack(side=LEFT)
rightframe = Frame(root)
rightframe.pack(pady=30)
topframe = Frame(rightframe)
topframe.pack()
lengthlabel = ttk.Label(topframe, text='Total Length : --:--')
lengthlabel.pack(pady=5)
currenttimelabel = ttk.Label(topframe, text='Current Time : --:--', relief=GROOVE)
currenttimelabel.pack()
def show_details(play_song):
file_data = os.path.splitext(play_song)
if file_data[1] == '.mp3':
audio = MP3(play_song)
total_length = audio.info.length
else:
a = mixer.Sound(play_song)
total_length = a.get_length()
# div - total_length/60, mod - total_length % 60
mins, secs = divmod(total_length, 60)
mins = round(mins)
secs = round(secs)
timeformat = '{:02d}:{:02d}'.format(mins, secs)
lengthlabel['text'] = "Total Length" + ' - ' + timeformat
t1 = threading.Thread(target=start_count, args=(total_length,))
t1.start()
def start_count(t):
global paused
# mixer.music.get_busy(): - Returns FALSE when we press the stop button (music stop playing)
# Continue - Ignores all of the statements below it. We check if music is paused or not.
current_time = 0
while current_time <= t and mixer.music.get_busy():
if paused:
continue
else:
mins, secs = divmod(current_time, 60)
mins = round(mins)
secs = round(secs)
timeformat = '{:02d}:{:02d}'.format(mins, secs)
currenttimelabel['text'] = "Current Time" + ' - ' + timeformat
time.sleep(1)
current_time += 1
def play_music():
global paused
if paused:
mixer.music.unpause()
statusbar['text'] = "Music Resumed"
paused = FALSE
else:
try:
stop_music()
time.sleep(1)
selected_song = playlistbox.curselection()
selected_song = int(selected_song[0])
play_it = playlist[selected_song]
mixer.music.load(play_it)
mixer.music.play()
statusbar['text'] = "Playing music" + ' - ' + os.path.basename(play_it)
show_details(play_it)
except:
tkinter.messagebox.showerror('File not found', 'Melody could not find the file. Please check again.')
def stop_music():
mixer.music.stop()
statusbar['text'] = "Music Stopped"
paused = FALSE
def pause_music():
global paused
paused = TRUE
mixer.music.pause()
statusbar['text'] = "Music Paused"
def rewind_music():
play_music()
statusbar['text'] = "Music Rewinded"
def set_vol(val):
volume = float(val) / 100
mixer.music.set_volume(volume)
# set_volume of mixer takes value only from 0 to 1. Example - 0, 0.1,0.55,0.54.0.99,1
muted = FALSE
def mute_music():
global muted
if muted: # Unmute the music
mixer.music.set_volume(0.7)
volumeBtn.configure(image=volumePhoto)
scale.set(70)
muted = FALSE
else: # mute the music
mixer.music.set_volume(0)
volumeBtn.configure(image=mutePhoto)
scale.set(0)
muted = TRUE
middleframe = Frame(rightframe)
middleframe.pack(pady=30, padx=30)
playPhoto = PhotoImage(file='images/play.png')
playBtn = ttk.Button(middleframe, image=playPhoto, command=play_music)
playBtn.grid(row=0, column=0, padx=10)
stopPhoto = PhotoImage(file='images/stop.png')
stopBtn = ttk.Button(middleframe, image=stopPhoto, command=stop_music)
stopBtn.grid(row=0, column=1, padx=10)
pausePhoto = PhotoImage(file='images/pause.png')
pauseBtn = ttk.Button(middleframe, image=pausePhoto, command=pause_music)
pauseBtn.grid(row=0, column=2, padx=10)
# Bottom Frame for volume, rewind, mute etc.
bottomframe = Frame(rightframe)
bottomframe.pack()
rewindPhoto = PhotoImage(file='images/rewind.png')
rewindBtn = ttk.Button(bottomframe, image=rewindPhoto, command=rewind_music)
rewindBtn.grid(row=0, column=0)
mutePhoto = PhotoImage(file='images/mute.png')
volumePhoto = PhotoImage(file='images/volume.png')
volumeBtn = ttk.Button(bottomframe, image=volumePhoto, command=mute_music)
volumeBtn.grid(row=0, column=1)
scale = ttk.Scale(bottomframe, from_=0, to=100, orient=HORIZONTAL, command=set_vol)
scale.set(70) # implement the default value of scale when music player starts
mixer.music.set_volume(0.7)
scale.grid(row=0, column=2, pady=15, padx=30)
def on_closing():
stop_music()
root.destroy()
root.protocol("WM_DELETE_WINDOW", on_closing)
root.mainloop()
| [
"noreply@github.com"
] | harishsg99.noreply@github.com |
1a2f4478fe86735f8c3590ae191a1535f26ead5e | 9b80999a1bdd3595022c9abf8743a029fde3a207 | /32-Writing Functions in Python /More on Decorators /Counter.py | 2be3435d9e6819985cf09452b2f9ff7746cd86e5 | [] | no_license | vaibhavkrishna-bhosle/DataCamp-Data_Scientist_with_python | 26fc3a89605f26ac3b77c15dbe45af965080115a | 47d9d2c8c93e1db53154a1642b6281c9149af769 | refs/heads/master | 2022-12-22T14:01:18.140426 | 2020-09-23T11:30:53 | 2020-09-23T11:30:53 | 256,755,894 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 807 | py | '''You're working on a new web app, and you are curious about how many times each of the functions in it gets called. So you decide to write a decorator that adds a counter to each function that you decorate. You could use this information in the future to determine whether there are sections of code that you could remove because they are no longer being used by the app.'''
def counter(func):
def wrapper(*args, **kwargs):
wrapper.count += 1
# Call the function being decorated and return the result
return func(*args, **kwargs)
wrapper.count = 0
# Return the new decorated function
return wrapper
# Decorate foo() with the counter() decorator
@counter
def foo():
print('calling foo()')
foo()
foo()
print('foo() was called {} times.'.format(foo.count)) | [
"vaibhavkrishna.bhosle@gmail.com"
] | vaibhavkrishna.bhosle@gmail.com |
af6d0c0bda1e996a2c4e3f97d83350512ffb05c8 | 311e8af4e95c8baccd2ba6548361d3d3be39fb73 | /utils/dem.py | 38f4e342528de8abb757f50643d2bd603da4f4b9 | [] | no_license | roukaour/frontier | 7873cede18313bf65481ea69b21c1d2ae81841d6 | c1ab4ff0ea6619692cbc9e238cd91f4112cc8857 | refs/heads/master | 2021-09-03T05:03:24.409092 | 2018-01-05T20:38:23 | 2018-01-05T20:38:23 | 116,423,692 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 15,441 | py | # http://www.gdal.org/
# gdal-translate 10.2.1.1043901.dem -of PNM -ot UInt16 -co MAXVAL=8367 bar.ppm
import sys
def maybe(f, s):
return f(s) if s.strip() else None
def fortran_float(s):
return float(s.replace('D', 'E'))
def split_fixed(s, size):
return [s[i:i+size] for i in xrange(0, len(s), size)]
def dms_to_decimal(dms):
# dms string format: SDDDMMSS.SSSS
# + sign is implied; no leading zeros in components
s = -1 if dms[0] == '-' else 1
d = float(dms[1:4])
m = float(dms[4:6])
s = float(dms[6:13])
return s * (d + (m * 60 + s) / 3600)
class DEM_Profile(object):
def __init__(self):
pass
def parse_b_record(self, record):
# A two-element array containing the row and column
# identification number of the DEM profile contained in this
# record. See figure 2-3. The row and column numbers may range
# from 1 to m and 1 to n. The row number is normally set to 1.
# The column identification is the profile sequence number.
self.row, self.column = map(int, split_fixed(record[0:12], 6))
# A two-element array containing the number (m, n) of elevations
# in the DEM profile. See figure 2-3. The first element in the
# field corresponds to the number of rows of nodes in this
# profile. The second element is set to 1, specifying 1 column
# per B record.
self.rows, self.columns = map(int, split_fixed(record[12:24], 6))
# A two-element array containing the ground planimetric
# coordinates (X_gp ,Y_gp) of the first elevation in the
# profile. See figure 2-3.
self.first_elevation_ground_planimetric_coords = tuple(map(fortran_float, split_fixed(record[24:72], 24)))
# The values are in the units of measure given by data element
# 9, logical record type A.
self.local_datum_elevation = fortran_float(record[72:96])
# A two-element array of minimum and maximum elevations for the
# profile. The values are in the units of measure given by data
# element 9 in logical record type A and are the algebraic
# result of the method outlined in data element 6 of this
# record.
self.min_elevation, self.max_elevation = map(fortran_float, split_fixed(record[96:144], 24))
# An m,n array of elevations for the profile. Elevations are
# expressed in units of resolution. A maximum of six characters
# are allowed for each integer elevation value. See data element
# 15 in appendix 2-A. A value in this array would be multiplied
# by the "z spatial resolution (data element 15, record type A)"
# and added to the "Elevation of local datum for the profile
# (data element 4, record type B)" to obtain the elevation for
# the point. The planimetric ground coordinates of point X_gp,
# Y_gp are computed according to the formulas in figure 2-3.
self.elevations = [[None] * self.rows for i in xrange(self.columns)]
row = 0
col = 0
pos = 145
while pos + 6 <= DEM.BLOCK_SIZE:
self.elevations[col][row] = int(record[pos:pos+6])
col += 1
if col == self.columns:
col = 0
row += 1
if row == self.rows:
return None
pos += 6
return (row, col)
def parse_continued_b_record(self, record, next_coords):
row, col = next_coords
pos = 0
while pos + 6 <= DEM.BLOCK_SIZE:
self.elevations[col][row] = int(record[pos:pos+6])
col += 1
if col == self.columns:
col = 0
row += 1
if row == self.rows:
return None
pos += 6
return (row, col)
class DEM(object):
BLOCK_SIZE = 1024
def __init__(self):
pass
def parse(self, path):
# Open DEM file
f = open(path, 'rb')
# Parse A record
a_record = f.read(DEM.BLOCK_SIZE)
self.parse_a_record(a_record)
# Parse B records
self.dem_profiles = {}
for i in xrange(self.columns):
profile = DEM_Profile()
b_record = f.read(DEM.BLOCK_SIZE)
next_coords = profile.parse_b_record(b_record)
while next_coords:
continued_b_record = f.read(DEM.BLOCK_SIZE)
next_coords = profile.parse_continued_b_record(continued_b_record, next_coords)
self.dem_profiles[(profile.row, profile.column)] = profile
# Parse C record
c_record = f.read(DEM.BLOCK_SIZE)
self.parse_c_record(c_record)
# Close DEM file
f.close()
def parse_a_record(self, record):
# The authorized digital cell name followed by a comma, space,
# and the two-character State designator(s) separated by
# hyphens. Abbreviations for other countries, such as Canada and
# Mexico, shall not be represented in the DEM header.
self.file_name = record[0:40].strip()
# Free format descriptor field, contains useful information
# related to digital process such as digitizing instrument,
# photo codes, slot widths, etc.
self.file_description = record[40:80].strip()
# filler = record[80:109]
# SE geographic quadrangle corner ordered as:
# x = Longitude = SDDDMMSS.SSSS
# y = Latitude = SDDDMMSS.SSSS
# (neg sign (S) right justified, no leading zeroes, plus sign
# (S) implied)
self.se_corner_lat_lon = tuple(map(dms_to_decimal, split_fixed(record[109:135], 13)))
# 1=Autocorrelation RESAMPLE Simple bilinear
# 2=Manual profile GRIDEM Simple bilinear
# 3=DLG/hypsography CTOG 8-direction linear
# 4=Interpolation from photogrammetric system contours DCASS
# 4-direction linear
# 5=DLG/hypsography LINETRACE, LT4X Complex linear
# 6=DLG/hypsography CPS-3, ANUDEM, GRASS Complex polynomial
# 7=Electronic imaging (non-photogrametric), active or
# passive, sensor systems
self.process_code = int(record[135:136])
# filler = record[136:137]
# This code is specific to 30-minute DEM's. Identifies
# 1:100,000-scale sections.
self.sectional_indicator = record[137:140].strip()
# Free format Mapping Origin Code. Example: MAC, WMC, MCMC,
# RMMC, FS, BLM, CONT (contractor), XX (state postal code).
self.origin_code = record[140:144].strip()
# 1=DEM-1
# 2=DEM-2
# 3=DEM-3
# 4=DEM-4
self.dem_level_code = int(record[144:150])
# 1=regular
# 2=random, reserved for future use
self.elevation_pattern_code = int(record[150:156])
# 0=Geographic
# 1=UTM
# 2=State plane
# For codes 3-20, see Appendix 2-G. Code 0 represents the
# geographic (latitude/longitude) system for 30-minute, 1-degree
# and Alaska DEM's. Code 1 represents the current use of the UTM
# coordinate system for 7.5-minute DEM's
self.ground_planimetric_reference_system_code = int(record[156:162])
# Codes for State plane and UTM coordinate zones are given in
# appendixes 2-E and 2-F for 7.5-minute DEM's. Code is set to
# zero if element 5 is also set to zero, defining data as
# geographic.
self.ground_planimetric_reference_system_zone_code = int(record[162:168])
# Definition of parameters for various projections is given in
# Appendix F. All 15 fields of this element are set to zero and
# should be ignored when geographic, UTM, or State plane
# coordinates are coded in data element 5.
# Definition of parameters for various projections is given in
# Appendix F. All 15 fields of this element are set to zero and
# should be ignored when geographic, UTM, or State plane
# coordinates are coded in data element 5.
self.map_projection_params = tuple(map(fortran_float, split_fixed(record[168:528], 24)))
# 0=radians
# 1=feet
# 2=meters
# 3=arc-seconds
# Normally set to code 2 for 7.5-minute DEM's. Always set to
# code 3 for 30-minute, 1-degree, and Alaska DEMs.
self.ground_planimetric_coord_unit_code = int(record[528:534])
# 1=feet
# 2=meters
# Normally code 2, meters, for 7.5-minute, 30-minute, 1-degree,
# and Alaska DEM's.
self.elevation_coord_unit_code = int(record[534:540])
# Set to n=4.
self.dem_coverage_polygon_sides = int(record[540:546])
# The coordinates of the quadrangle corners are ordered in a
# clockwise direction beginning with the southwest corner. The
# array is stored as as pairs of eastings and northings.
self.dem_quadrangle_boundary_ground_coords = tuple(map(tuple, split_fixed(map(fortran_float, split_fixed(record[546:738], 24)), 2)))
# The values are in the unit of measure given by data element 9
# in this record and are the algebraic result of the method
# outlined in data element 6, logical record B.
self.dem_min_elevation, self.dem_max_elevation = map(fortran_float, split_fixed(record[738:786], 24))
# Counterclockwise angle (in radians) from the primary axis of
# ground planimetric reference to the primary axis of the DEM
# local reference system. See figure 2-3. Set to zero to align
# with the coordinate system specified in element 5.
self.ground_planimetric_reference_system_angle = fortran_float(record[786:810])
# 0=unknown accuracy
# 1=accuracy information is given in logical record type C
self.elevation_accuracy_code = int(record[810:816])
# A three-element array of DEM spatial resolution for x, y, z.
# Values are expressed in units of resolution. The units of
# measure are consistent with those indicated by data elements 8
# and 9 in this record.
# Only integer values are permitted for the x and y resolutions.
# For all USGS DEMs except the 1-degree DEM, z resolutions of 1
# decimal place for feet and 2 decimal places for meters are
# permitted.
self.dem_spatial_resolution = tuple(map(fortran_float, split_fixed(record[816:852], 12)))
# When the row value m is set to 1 the n value describes the
# number of columns in the DEM file.
self.rows, self.columns = map(int, split_fixed(record[852:864], 6))
# Present only if two or more primary intervals exist (level 2
# DEM's only).
self.max_primary_contour_interval = maybe(int, record[864:869])
# Corresponds to the units of the map largest primary contour
# interval (level 2 DEM's only).
# 0=N.A.
# 1=feet
# 2=meters
self.source_contour_interval_units = maybe(int, record[869:870])
# Corresponds to the units of the map smallest primary contour
# interval (level 2 DEM's only).
# 1=feet
# 2=meters
self.min_primary_contour_interval = maybe(int, record[870:875])
# "YYYY" 4 character year, e.g. 1975, 1997, 2001, etc.
# Synonymous with the original compilation data and/or the date
# of the photography.
self.data_source_data = int(record[876:880])
# "YYYY" 4 character year. Synonymous with the date of
# completion and/or the date of revision.
self.data_revision_data = int(record[880:884])
# "I" Indicates all processes of part 3, Quality Control have
# been performed.
self.inspection_flag = record[884:885]
# 0=No validation performed.
# 1=RMSE computed from test points (record C added), no
# quantitative test, no interactive DEM editing or review.
# 2=Batch process water body edit and RMSE computed from test
# points.
# 3=Review and edit, including water edit. No RMSE computed from
# test points.
# 4=Level 1 DEM's reviewed and edited. Includes water body
# editing. RMSE computed from test points.
# 5=Level 2 and 3 DEM's reviewed and edited. Includes water body
# editing and verification or vertical integration of
# planimetric categories (other than hypsography or
# hydrography if authorized). RMSE computed from test points.
self.data_validation_flag = int(record[885:886])
# 0=none
# 1=suspect areas
# 2=void areas
# 3=suspect and void areas
self.suspect_and_void_area_flag = int(record[886:888])
# 1=local mean sea level
# 2=National Geodetic Vertical Datum 1929 (NGVD 29)
# 3=North American Vertical Datum 1988 (NAVD 88)
# (note: see appendix 2-H for datum information)
self.vertical_datum = int(record[888:890])
# 1=North American Datum 1927 (NAD 27)
# 2=World Geodetic System 1972 (WGS 72)
# 3=WGS 84
# 4=NAD 83
# 5=Old Hawaii Datum
# 6=Puerto Rico Datum
# (note: see appendix 2-H for datum information)
self.horizontal_datum = int(record[890:892])
# 01-99
# Primarily a DMA specific field. (For USGS use, set to 01)
self.data_edition = int(record[892:896])
# If element 25 indicates a void, this field (right justified)
# contains the percentage of nodes in the file set to void
# (-32,767).
self.percent_void = maybe(int, record[896:900])
# Edge match status flag. Ordered West, North, East, and South.
# See section 2.2.4 for valid flags and explanation of codes.
self.edge_match_flag = tuple(map(int, split_fixed(record[900:908], 2)))
# Value is in the form of SFFF.DD. Value is the average shift
# value for the four quadrangle corners obtained from program
# VERTCON. Always add this value to convert to NAVD88.
self.vertical_datum_shift = fortran_float(record[908:915])
def parse_c_record(self, record):
# Code indicating availability of statistics in data element 2.
# 1=available
# 0=unavailable
self.has_absolute_datum_rmse = maybe(int, record[0:6])
# RMSE of file's datum relative to absolute datum (x, y, z).
# RMSE integer values are in the same unit of measure given by
# data elements 8 and 9 of logical record type A.
self.absolute_datum_rmse = tuple(map(int, split_fixed(record[6:24], 6))) or None
# Sample size on which statistics in data element 2 are based.
# If 0, then accuracy will be assumed to be estimated rather
# than computed.
self.absolute_datum_rmse_sample_size = maybe(int, record[24:30])
# Code indicating availability of statistics in data element 5.
# 1=available
# 0=unavailable
self.has_relative_datum_rmse = maybe(int, record[30:36])
# RMSE of DEM data relative to file's datum (x, y, z).
# RMSE integer values are in the same unit of measure given by
# data elements 8 and 9 of logical record type A.
self.relative_datum_rmse = tuple(map(int, split_fixed(record[36:54], 6))) or None
# Sample size on which statistics in data element 5 are based.
# If 0, then accuracy will be assumed to be estimated rather
# than computed.
self.relative_datum_rmse_sample_size = maybe(int, record[54:60])
def main():
# Parse DEM
dem_path = r'E:\Desktop\cse528-terrain\10.2.1.1043901.dem'
dem = DEM()
dem.parse(dem_path)
# Print DEM data
w = max(len(dem.dem_profiles[c].elevations[0]) for c in dem.dem_profiles)
h = dem.columns
sys.stderr.write('%d by %d\n' % (w, h))
min_el = min(min(dem.dem_profiles[c].elevations[0]) for c in dem.dem_profiles)
max_el = max(max(dem.dem_profiles[c].elevations[0]) for c in dem.dem_profiles)
el_range = max_el - min_el
sys.stderr.write('%d to %d is %d\n' % (min_el, max_el, el_range))
sys.stdout.write('P3 %d %d %d\n' % (w, h, el_range))
for r in xrange(1, h+1):
es = dem.dem_profiles[(1, r)].elevations[0]
if r < h / 2:
for c in xrange(w - len(es)):
sys.stdout.write('0 0 0 ')
for el in es:
#el = int(255 * float(el - min_el) / el_range)
el = el - min_el
sys.stdout.write('%d %d %d ' % (el, el, el))
sys.stderr.write('row %d has %d; needs %d more\n' % (r, len(es), w - len(es)))
if r >= h / 2:
for c in xrange(w - len(es)):
sys.stdout.write('0 0 0 ')
sys.stdout.write('\n')
if __name__ == '__main__':
main()
| [
"remy.oukaour@gmail.com"
] | remy.oukaour@gmail.com |
001ba98220b5ff69f7b0459f557657e2ffae8cc9 | 09a3892bc1c726e4ea78d478cc9e02202905fa66 | /odd_even_letter_cases.py | 7a6b30f09c96a6001f34a27b8971a5c66edee2a5 | [] | no_license | addyj4922/python-programs | 9e8c350f219c3c1dad917626da22eb4b09f203e8 | 1e01fb861a0797e702fc401c26161e0995c8e299 | refs/heads/master | 2020-04-13T02:18:36.730717 | 2019-04-05T11:04:18 | 2019-04-05T11:04:18 | 162,899,138 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 282 | py | def myfunc(name):
a=name.lower()
l=list(a)
l1=[]
s=''
for i in range(0,len(l)):
if i%2==0:
b=l[i].upper()
l1.append(b)
else:
l1.append(l[i])
s=''.join(l1)
print(s)
myfunc('heLLO worLd')
| [
"noreply@github.com"
] | addyj4922.noreply@github.com |
25545f18df80bd90c776c1063f9fda4a12af8a0e | 2e3e81c13be559f430ddd67a9aad1114a21fafef | /database_dialog/sql_tasks.py | 69e30b550b62bf75b1d9d2f8ef9a2cb13e7f0b18 | [] | no_license | Drew973/pts_site_categorizer | e08a78f0e33845501333a1b23d1d86d6c79a5a2a | 843d8ccb851964a076259ad219abeb30b806ce39 | refs/heads/main | 2023-07-29T00:01:37.423739 | 2020-11-04T15:57:34 | 2020-11-04T15:57:34 | 310,049,359 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,777 | py |
from qgis.core import QgsTask
from qgis.utils import iface
from psycopg2.extras import execute_batch
class cancelable_sql(QgsTask):
def __init__(self,con,sql,args=None,sucess_message=None):
QgsTask.__init__(self)
self.con=con
self.cur=con.cursor()
self.sql=sql
self.args=args
self.sucess_message=sucess_message
def run(self):
cur=self.con.cursor()
try:
with self.con:
if self.args:
self.cur.execute(self.sql,self.args)
else:
self.cur.execute(self.sql)#with makes con commit here
return True
except Exception as e:
self.err=e
return False
#result bool
def finished(self,result):
iface.messageBar().clearWidgets()
if result:
if self.sucess_message:
iface.messageBar().pushMessage(self.sucess_message)
else:
iface.messageBar().pushMessage(str(self.err))
def cancel(self):
self.con.cancel()#psycopg2 conection can be cancelled from any thread.
QgsTask.cancel(self)
class cancellable_batch(cancelable_sql):
def run(self):
cur=self.con.cursor()
try:
with self.con:
execute_batch(self.cur,q,vals)
return True
except Exception as e:
self.err=e
return False
class cancelable_queries(QgsTask):
#args is list of arguments.
def __init__(self,con,queries,args=None,sucess_message=None):
QgsTask.__init__(self)
self.con=con
self.cur=con.cursor()
self.queries=queries
if args:
if len(args)==len(queries):
self.args=args
else:
raise ValueError('cancelable_queries:length of queries!= length of arguments')
else:
self.args=[None for q in queries]
self.sucess_message=sucess_message
def run(self):
cur=self.con.cursor()
try:
with self.con: #with makes con commit here
for i,v in enumerate(self.queries):
if self.isCanceled():
return False
self.cur.execute(v,self.args[i])
self.setProgress(100*float(i)/len(self.queries))#setProgress takes float from 0 to 100 and emits progressChanged signal
return True
except Exception as e:
self.err=e
return False
#result bool
def finished(self,result):
iface.messageBar().clearWidgets()
if result:
if self.sucess_message:
iface.messageBar().pushMessage(self.sucess_message)
else:
iface.messageBar().pushMessage(str(self.err))
def cancel(self):
self.con.cancel()#psycopg2 conection can be cancelled from any thread.
QgsTask.cancel(self)
class cancelable_batches(cancelable_queries):
def run(self):
cur=self.con.cursor()
try:
with self.con: #with makes con commit here
for i,v in enumerate(self.queries):
if self.isCanceled():
return False
execute_batch(self.cur,v,self.args[i])
self.setProgress(100*float(i)/len(self.queries))#setProgress takes float from 0 to 100 and emits progressChanged signal
return True
except Exception as e:
self.err=e
return False
| [
"Drew.Bennett@PTS.local"
] | Drew.Bennett@PTS.local |
88b3862c2cdf3a5e4affa06d8c636cd9a52de4a6 | cdae0c3e86620063edddacf8d11d68dea8703d14 | /03_bulk_download_read_in/Python Scripts/claims/claims_2019.py | f4cf4b0f5a127096cf3027968609bba2cd010647 | [] | no_license | Cativolcus/PatentsView-Code-Snippets | 6acd8f3ac608635f46e48aae443c9ce53de1b028 | 0bee4eab7d19117301089b6458af32dba42142e3 | refs/heads/master | 2023-05-01T15:06:11.166651 | 2021-05-03T20:04:56 | 2021-05-03T20:04:56 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 785 | py | #Read-in script for 2019 Claims Data
# Importing necessary packages.
import os
import zipfile as zip
import pandas as pd
import csv
import numpy as np
# Set up file path:
# Please include the folder path of the file you are reading. Ex: os.chdir("C:/Users/johnsmith/Downloads")
os.chdir("")
file_name = "claims_2019.tsv.zip"
f_name = "claims_2019.tsv"
# Selecting the zip file.
zf = zip.ZipFile(file_name)
# Reading the selected file in the zip.
df = pd.read_csv(zf.open(f_name), delimiter="\t", quoting=csv.QUOTE_NONNUMERIC)
# Print first five observations
print(df.head())
# Print summary of data: number of columns, observations, and each variable data type
print(len(df))
df.info()
# Provide additional information on certain variables.
print(df.describe(exclude=[np.number]))
| [
"65043717+ahasanbasri@users.noreply.github.com"
] | 65043717+ahasanbasri@users.noreply.github.com |
fe960a75b3d5f3e05f7f5592e928700113940458 | 08c1a032c8216072d2553a129c4790e0555044db | /dataSource_Mango_Persistent_TCP.py | 5f6bc993ba2680d28055bf961b70f603013b2b5b | [] | no_license | Yafitush/Mango | 9171637b617809159e7b223766cf20afb2491abc | fcc793a2749748eb9c927e7f4cdaa14ab660a1ae | refs/heads/master | 2021-01-10T14:40:24.976855 | 2016-01-14T14:13:52 | 2016-01-14T14:13:52 | 48,546,170 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,121 | py | __author__ = 'Yafit'
class DataSource_MANGO_PERSISTENT_TCP:
def __init__(self, xid="", name="", enabled="true", purgeType="YEARS", editPermission="superadmin",
purgeOverride="false", purgePeriod=1, logLevel="LOG_LEVEL_NONE", acceptPointUpdates="true",
authorizationKey="abra_cadabra", port=55, saveRealtimeData="true", socketTimeout=5000, useCompression="true",
useCrc="true"):
self.xid = xid
self.name = name
self.enabled = enabled
self.type = "PERSISTENT"
self.alarmLevels = {"DATA_SOURCE_EXCEPTION_EVENT": "URGENT"}
self.purgeType = purgeType
self.editPermission = editPermission
self.purgeOverride = purgeOverride
self.purgePeriod = purgePeriod
self.logLevel = logLevel
self.acceptPointUpdates = acceptPointUpdates
self.authorizationKey = authorizationKey
self.port = port
self.saveRealtimeData = saveRealtimeData
self.socketTimeout = socketTimeout
self.useCompression = useCompression
self.useCrc = useCrc
| [
"trabelsiyafit@gmail.com"
] | trabelsiyafit@gmail.com |
4856288bd9541b5caa96a0ea2e85cd69b7d31a65 | ece0d321e48f182832252b23db1df0c21b78f20c | /engine/2.80/scripts/addons/add_curve_extra_objects/__init__.py | 1653ad86f875ef36beef157620f21d7633f0d31a | [
"Unlicense",
"GPL-3.0-only",
"Font-exception-2.0",
"GPL-3.0-or-later",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-public-domain-disclaimer",
"Bitstream-Vera",
"LicenseRef-scancode-blender-2010",
"LGPL-2.1-or-later",
... | permissive | byteinc/Phasor | 47d4e48a52fa562dfa1a2dbe493f8ec9e94625b9 | f7d23a489c2b4bcc3c1961ac955926484ff8b8d9 | refs/heads/master | 2022-10-25T17:05:01.585032 | 2019-03-16T19:24:22 | 2019-03-16T19:24:22 | 175,723,233 | 3 | 1 | Unlicense | 2022-10-21T07:02:37 | 2019-03-15T00:58:08 | Python | UTF-8 | Python | false | false | 12,422 | py | # ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# ##### END GPL LICENSE BLOCK #####
# Contributed to by:
# testscreenings, Alejandro Omar Chocano Vasquez, Jimmy Hazevoet, meta-androcto #
# Cmomoney, Jared Forsyth, Adam Newgas, Spivak Vladimir, Jared Forsyth, Atom #
# Antonio Osprite, Marius Giurgi (DolphinDream)
bl_info = {
"name": "Extra Objects",
"author": "Multiple Authors",
"version": (0, 1, 3),
"blender": (2, 80, 0),
"location": "View3D > Add > Curve > Extra Objects",
"description": "Add extra curve object types",
"warning": "",
"wiki_url": "https://wiki.blender.org/index.php/Extensions:2.6/Py/"
"Scripts/Curve/Curve_Objects",
"category": "Add Curve"
}
if "bpy" in locals():
import importlib
importlib.reload(add_curve_aceous_galore)
importlib.reload(add_curve_spirals)
importlib.reload(add_curve_torus_knots)
importlib.reload(add_surface_plane_cone)
importlib.reload(add_curve_curly)
importlib.reload(beveltaper_curve)
importlib.reload(add_curve_celtic_links)
importlib.reload(add_curve_braid)
importlib.reload(add_curve_simple)
importlib.reload(add_curve_spirofit_bouncespline)
else:
from . import add_curve_aceous_galore
from . import add_curve_spirals
from . import add_curve_torus_knots
from . import add_surface_plane_cone
from . import add_curve_curly
from . import beveltaper_curve
from . import add_curve_celtic_links
from . import add_curve_braid
from . import add_curve_simple
from . import add_curve_spirofit_bouncespline
import bpy
from bpy.types import (
Menu,
AddonPreferences,
)
from bpy.props import (
StringProperty,
BoolProperty,
)
def convert_old_presets(data_path, msg_data_path, old_preset_subdir,
new_preset_subdir, fixdic={}, ext=".py"):
"""
convert old presets
"""
def convert_presets(self, context):
if not getattr(self, data_path, False):
return None
import os
target_path = os.path.join("presets", old_preset_subdir)
target_path = bpy.utils.user_resource('SCRIPTS',
target_path)
# created an anytype op to run against preset
op = type('', (), {})()
files = [f for f in os.listdir(target_path) if f.endswith(ext)]
if not files:
print("No old presets in %s" % target_path)
setattr(self, msg_data_path, "No old presets")
return None
new_target_path = os.path.join("presets", new_preset_subdir)
new_target_path = bpy.utils.user_resource('SCRIPTS',
new_target_path,
create=True)
for f in files:
file = open(os.path.join(target_path, f))
for line in file:
if line.startswith("op."):
exec(line)
file.close()
for key, items in fixdic.items():
if hasattr(op, key) and isinstance(getattr(op, key), int):
setattr(op, key, items[getattr(op, key)])
# create a new one
new_file_path = os.path.join(new_target_path, f)
if os.path.isfile(new_file_path):
# do nothing
print("Preset %s already exists, passing..." % f)
continue
file_preset = open(new_file_path, 'w')
file_preset.write("import bpy\n")
file_preset.write("op = bpy.context.active_operator\n")
for prop, value in vars(op).items():
if isinstance(value, str):
file_preset.write("op.%s = '%s'\n" % (prop, str(value)))
else:
file_preset.write("op.%s = %s\n" % (prop, str(value)))
file_preset.close()
print("Writing new preset to %s" % new_file_path)
setattr(self, msg_data_path, "Converted %d old presets" % len(files))
return None
return convert_presets
# Addons Preferences
class CurveExtraObjectsAddonPreferences(AddonPreferences):
bl_idname = __name__
spiral_fixdic = {
"spiral_type": ['ARCH', 'ARCH', 'LOG', 'SPHERE', 'TORUS'],
"curve_type": ['POLY', 'NURBS'],
"spiral_direction": ['COUNTER_CLOCKWISE', 'CLOCKWISE']
}
update_spiral_presets_msg : StringProperty(
default="Nothing to do"
)
update_spiral_presets : BoolProperty(
name="Update Old Presets",
description="Update presets to reflect data changes",
default=False,
update=convert_old_presets(
"update_spiral_presets", # this props name
"update_spiral_presets_msg", # message prop
"operator/curve.spirals",
"curve_extras/curve.spirals",
fixdic=spiral_fixdic
)
)
show_menu_list : BoolProperty(
name="Menu List",
description="Show/Hide the Add Menu items",
default=False
)
show_panel_list : BoolProperty(
name="Panels List",
description="Show/Hide the Panel items",
default=False
)
def draw(self, context):
layout = self.layout
box = layout.box()
box.label(text="Spirals:")
if self.update_spiral_presets:
box.label(text=self.update_spiral_presets_msg, icon="FILE_TICK")
else:
box.prop(self, "update_spiral_presets")
icon_1 = "TRIA_RIGHT" if not self.show_menu_list else "TRIA_DOWN"
box = layout.box()
box.prop(self, "show_menu_list", emboss=False, icon=icon_1)
if self.show_menu_list:
box.label(text="Items located in the Add Menu > Curve (default shortcut Ctrl + A):",
icon="LAYER_USED")
box.label(text="2D Objects:", icon="LAYER_ACTIVE")
box.label(text="Angle, Arc, Circle, Distance, Ellipse, Line, Point, Polygon,",
icon="LAYER_USED")
box.label(text="Polygon ab, Rectangle, Rhomb, Sector, Segment, Trapezoid",
icon="LAYER_USED")
box.label(text="Curve Profiles:", icon="LAYER_ACTIVE")
box.label(text="Arc, Arrow, Cogwheel, Cycloid, Flower, Helix (3D),",
icon="LAYER_USED")
box.label(text="Noise (3D), Nsided, Profile, Rectangle, Splat, Star",
icon="LAYER_USED")
box.label(text="Curve Spirals:", icon="LAYER_ACTIVE")
box.label(text="Archemedian, Logarithmic, Spheric, Torus",
icon="LAYER_USED")
box.label(text="Knots:", icon="LAYER_ACTIVE")
box.label(text="Torus Knots Plus, Celtic Links, Braid Knot",
icon="LAYER_USED")
box.label(text="Curly Curve", icon="LAYER_ACTIVE")
box.label(text="Bevel/Taper:", icon="LAYER_ACTIVE")
box.label(text="Add Curve as Bevel, Add Curve as Taper",
icon="LAYER_USED")
box.label(text="Items located in the Add Menu > Surface (default shortcut Ctrl + A):",
icon="LAYER_USED")
box.label(text="Wedge, Cone, Star, Plane",
icon="LAYER_ACTIVE")
icon_2 = "TRIA_RIGHT" if not self.show_panel_list else "TRIA_DOWN"
box = layout.box()
box.prop(self, "show_panel_list", emboss=False, icon=icon_2)
if self.show_panel_list:
box.label(text="Panel located in 3D View Tools Region > Create:",
icon="LAYER_ACTIVE")
box.label(text="Spline:", icon="LAYER_ACTIVE")
box.label(text="SpiroFit, Bounce Spline, Catenary", icon="LAYER_USED")
box.label(text="Panel located in 3D View Tools Region > Tools:",
icon="LAYER_ACTIVE")
box.label(text="Simple Curve:", icon="LAYER_ACTIVE")
box.label(text="Available if the Active Object is a Curve was created with 2D Objects",
icon="LAYER_USED")
class INFO_MT_curve_knots_add(Menu):
# Define the "Extras" menu
bl_idname = "INFO_MT_curve_knots_add"
bl_label = "Plants"
def draw(self, context):
layout = self.layout
layout.operator_context = 'INVOKE_REGION_WIN'
layout.operator("curve.torus_knot_plus", text="Torus Knot Plus")
layout.operator("curve.celtic_links", text="Celtic Links")
layout.operator("curve.add_braid", text="Braid Knot")
layout.operator("object.add_spirofit_spline", icon="FORCE_MAGNETIC")
layout.operator("object.add_bounce_spline", icon="FORCE_HARMONIC")
layout.operator("object.add_catenary_curve", icon="FORCE_CURVE")
# Define "Extras" menus
def menu_func(self, context):
layout = self.layout
layout.operator_menu_enum("curve.curveaceous_galore", "ProfileType", icon='CURVE_DATA')
layout.operator_menu_enum("curve.spirals", "spiral_type", icon='CURVE_DATA')
if context.mode != 'OBJECT':
# fix in D2142 will allow to work in EDIT_CURVE
return None
layout.separator()
layout.menu(INFO_MT_curve_knots_add.bl_idname, text="Knots", icon='CURVE_DATA')
layout.separator()
layout.operator("curve.curlycurve", text="Curly Curve", icon='CURVE_DATA')
#layout.menu(VIEW3D_MT_bevel_taper_curve_menu, text="Bevel/Taper", icon='CURVE_DATA')
def menu_surface(self, context):
self.layout.separator()
if context.mode == 'EDIT_SURFACE':
self.layout.operator("curve.smooth_x_times", text="Special Smooth", icon="MOD_CURVE")
elif context.mode == 'OBJECT':
self.layout.operator("object.add_surface_wedge", text="Wedge", icon="SURFACE_DATA")
self.layout.operator("object.add_surface_cone", text="Cone", icon="SURFACE_DATA")
self.layout.operator("object.add_surface_star", text="Star", icon="SURFACE_DATA")
self.layout.operator("object.add_surface_plane", text="Plane", icon="SURFACE_DATA")
# Register
classes = [
CurveExtraObjectsAddonPreferences,
INFO_MT_curve_knots_add
]
def register():
from bpy.utils import register_class
for cls in classes:
register_class(cls)
add_curve_simple.register()
add_curve_spirals.register()
add_curve_aceous_galore.register()
add_curve_torus_knots.register()
add_curve_braid.register()
add_curve_celtic_links.register()
add_curve_curly.register()
add_curve_spirofit_bouncespline.register()
add_surface_plane_cone.register()
# Add "Extras" menu to the "Add Curve" menu
bpy.types.VIEW3D_MT_curve_add.append(menu_func)
# Add "Extras" menu to the "Add Surface" menu
bpy.types.VIEW3D_MT_surface_add.append(menu_surface)
def unregister():
# Remove "Extras" menu from the "Add Curve" menu.
bpy.types.VIEW3D_MT_curve_add.remove(menu_func)
# Remove "Extras" menu from the "Add Surface" menu.
bpy.types.VIEW3D_MT_surface_add.remove(menu_surface)
add_surface_plane_cone.unregister()
add_curve_spirofit_bouncespline.unregister()
add_curve_curly.unregister()
add_curve_celtic_links.unregister()
add_curve_braid.unregister()
add_curve_torus_knots.unregister()
add_curve_aceous_galore.unregister()
add_curve_spirals.unregister()
add_curve_simple.unregister()
from bpy.utils import unregister_class
for cls in reversed(classes):
unregister_class(cls)
if __name__ == "__main__":
register()
| [
"admin@irradiate.net"
] | admin@irradiate.net |
e2e697cd6e4af498e1bac14df59b72e7db0ebf8d | d713487a245bd053f59cb9296ff201f2920af6ad | /project/maps/recommend.py | 4a363c70c431fb895b33edfd7648204871de61ab | [] | no_license | hhe8/CS61A | ce36e0c14c937370d86d628958da6deb110aa34b | 9ef427ab17a5a571cccab1b56d7541c45660fd34 | refs/heads/master | 2021-01-10T20:58:14.507015 | 2015-07-19T23:08:08 | 2015-07-19T23:08:08 | 38,461,848 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 8,169 | py | """A Yelp-powered Restaurant Recommendation Program"""
from abstractions import *
from utils import distance, mean, zip, enumerate, sample
from visualize import draw_map
from data import RESTAURANTS, CATEGORIES, USER_FILES, load_user_file
from ucb import main, trace, interact
def find_closest(location, centroids):
"""Return the item in CENTROIDS that is closest to LOCATION. If two
centroids are equally close, return the first one.
>>> find_closest([3, 4], [[0, 0], [2, 3], [4, 3], [5, 5]])
[2, 3]
"""
"*** YOUR CODE HERE ***"
d = [distance(location,center) for center in centroids]
return centroids[d.index(min(d))]
def group_by_first(pairs):
"""Return a list of pairs that relates each unique key in [key, value]
pairs to a list of all values that appear paired with that key.
Arguments:
pairs -- a sequence of pairs
>>> example = [ [1, 2], [3, 2], [2, 4], [1, 3], [3, 1], [1, 2] ]
>>> group_by_first(example)
[[2, 3, 2], [2, 1], [4]]
"""
# Optional: This implementation is slow because it traverses the list of
# pairs one time for each key. Can you improve it?
keys = []
for key, _ in pairs:
if key not in keys:
keys.append(key)
return [[y for x, y in pairs if x == key] for key in keys]
def group_by_centroid(restaurants, centroids):
"""Return a list of lists, where each list contains all restaurants nearest
to some item in CENTROIDS. Each item in RESTAURANTS should appear once in
the result, along with the other restaurants nearest to the same centroid.
No empty lists should appear in the result.
"""
"*** YOUR CODE HERE ***"
restaurant_min_center = []
for restaurant in restaurants:
restaurant_min_center.append(find_closest(restaurant_location(restaurant),centroids))
return group_by_first(zip(restaurant_min_center,restaurants))
def find_centroid(restaurants):
"""Return the centroid of the locations of RESTAURANTS."""
"*** YOUR CODE HERE ***"
return [mean([restaurant_location(restaurant)[x] for restaurant in restaurants]) for x in [0,1] ]
def k_means(restaurants, k, max_updates=100):
"""Use k-means to group RESTAURANTS by location into K clusters."""
assert len(restaurants) >= k, 'Not enough restaurants to cluster'
old_centroids, n = [], 0
# Select initial centroids randomly by choosing K different restaurants
centroids = [restaurant_location(r) for r in sample(restaurants, k)]
while old_centroids != centroids and n < max_updates:
old_centroids = centroids
"*** YOUR CODE HERE ***"
clusters = group_by_centroid(restaurants,old_centroids)
centroids = [find_centroid(cluster) for cluster in clusters]
n += 1
return centroids
def find_predictor(user, restaurants, feature_fn):
"""Return a rating predictor (a function from restaurants to ratings),
for USER by performing least-squares linear regression using FEATURE_FN
on the items in RESTAURANTS. Also, return the R^2 value of this model.
Arguments:
user -- A user
restaurants -- A sequence of restaurants
feature_fn -- A function that takes a restaurant and returns a number
"""
reviews_by_user = {review_restaurant_name(review): review_rating(review)
for review in user_reviews(user).values()}
xs = [feature_fn(r) for r in restaurants]
ys = [reviews_by_user[restaurant_name(r)] for r in restaurants]
"*** YOUR CODE HERE ***"
b, a, r_squared = 0, 0, 0 # REPLACE THIS LINE WITH YOUR SOLUTION
mean_x = mean(xs)
mean_y = mean(ys)
s_xx = sum([pow(x-mean_x,2) for x in xs])
s_yy = sum([pow(y-mean_y,2) for y in ys])
xy_pair = zip(xs,ys)
s_xy = sum([(pair[0]-mean_x)*(pair[1]-mean_y) for pair in xy_pair])
b = s_xy/s_xx
a = mean_y-b*mean_x
r_squared = pow(s_xy,2)/(s_xx*s_yy)
def predictor(restaurant):
return b * feature_fn(restaurant) + a
return predictor, r_squared
def best_predictor(user, restaurants, feature_fns):
"""Find the feature within FEATURE_FNS that gives the highest R^2 value
for predicting ratings by the user; return a predictor using that feature.
Arguments:
user -- A user
restaurants -- A dictionary from restaurant names to restaurants
feature_fns -- A sequence of functions that each takes a restaurant
"""
reviewed = list(user_reviewed_restaurants(user, restaurants).values())
"*** YOUR CODE HERE ***"
predictor_r_squared=[find_predictor(user,reviewed,feature)[1] for feature in feature_fns]
predictor =[find_predictor(user,reviewed,feature)[0] for feature in feature_fns]
max_index = predictor_r_squared.index(max(predictor_r_squared))
return predictor[max_index]
def rate_all(user, restaurants, feature_functions):
"""Return the predicted ratings of RESTAURANTS by USER using the best
predictor based a function from FEATURE_FUNCTIONS.
Arguments:
user -- A user
restaurants -- A dictionary from restaurant names to restaurants
"""
# Use the best predictor for the user, learned from *all* restaurants
# (Note: the name RESTAURANTS is bound to a dictionary of all restaurants)
predictor = best_predictor(user, RESTAURANTS, feature_functions)
"*** YOUR CODE HERE ***"
reviewed = list(user_reviewed_restaurants(user,restaurants).keys())
restaurant_name_list = list(restaurants.keys())
unreviewed = [x for x in restaurant_name_list if x not in reviewed]
ratings = {x:user_rating(user,x) for x in reviewed}
for x in unreviewed:
ratings[x]=predictor(restaurants[x])
return ratings
def search(query, restaurants):
"""Return each restaurant in RESTAURANTS that has QUERY as a category.
Arguments:
query -- A string
restaurants -- A sequence of restaurants
"""
"*** YOUR CODE HERE ***"
return [restaurant for restaurant in restaurants if query in restaurant_categories(restaurant)]
def feature_set():
"""Return a sequence of feature functions."""
return [restaurant_mean_rating,
restaurant_price,
restaurant_num_ratings,
lambda r: restaurant_location(r)[0],
lambda r: restaurant_location(r)[1]]
@main
def main(*args):
import argparse
parser = argparse.ArgumentParser(
description='Run Recommendations',
formatter_class=argparse.RawTextHelpFormatter
)
parser.add_argument('-u', '--user', type=str, choices=USER_FILES,
default='test_user',
metavar='USER',
help='user file, e.g.\n' +
'{{{}}}'.format(','.join(sample(USER_FILES, 3))))
parser.add_argument('-k', '--k', type=int, help='for k-means')
parser.add_argument('-q', '--query', choices=CATEGORIES,
metavar='QUERY',
help='search for restaurants by category e.g.\n'
'{{{}}}'.format(','.join(sample(CATEGORIES, 3))))
parser.add_argument('-p', '--predict', action='store_true',
help='predict ratings for all restaurants')
args = parser.parse_args()
# Select restaurants using a category query
if args.query:
results = search(args.query, RESTAURANTS.values())
restaurants = {restaurant_name(r): r for r in results}
else:
restaurants = RESTAURANTS
# Load a user
assert args.user, 'A --user is required to draw a map'
user = load_user_file('{}.dat'.format(args.user))
# Collect ratings
if args.predict:
ratings = rate_all(user, restaurants, feature_set())
else:
restaurants = user_reviewed_restaurants(user, restaurants)
ratings = {name: user_rating(user, name) for name in restaurants}
# Draw the visualization
restaurant_list = list(restaurants.values())
if args.k:
centroids = k_means(restaurant_list, min(args.k, len(restaurant_list)))
else:
centroids = [restaurant_location(r) for r in restaurant_list]
draw_map(centroids, restaurant_list, ratings)
| [
"hhe8@uchicago.edu"
] | hhe8@uchicago.edu |
b4d966c812f623f655c3c45b0d426e121fea8073 | 1b6a816f4c6f496cc38ee1b5c5b7c2d8c1a38a59 | /backend/users/migrations/0009_token.py | 5b217a89a11d0b431d9af78e92e7a4c6e4de4dc7 | [] | no_license | localboy/empee | d4bd51a7ba8fc51aaed1cc4dfaaf66edd08a0ca8 | b2aad8daa2b50a1cf393cee44432444661a66241 | refs/heads/master | 2021-01-10T08:12:05.826572 | 2018-04-25T10:53:30 | 2018-04-25T10:53:30 | 52,681,573 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 907 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.9.2 on 2016-04-07 09:34
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('users', '0008_account_image'),
]
operations = [
migrations.CreateModel(
name='Token',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('token', models.CharField(max_length=250)),
('expire_date', models.DateTimeField()),
('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='token_user', to=settings.AUTH_USER_MODEL)),
],
),
]
| [
"jakir@skylark.com"
] | jakir@skylark.com |
b37518ea6e71d2bfbce6dd7613cdae72767dc2d5 | 53fab060fa262e5d5026e0807d93c75fb81e67b9 | /backup/user_383/ch84_2019_06_06_20_42_07_280719.py | c024c1d4525f58eee0be02e2b9c6b8bdfb678c43 | [] | no_license | gabriellaec/desoft-analise-exercicios | b77c6999424c5ce7e44086a12589a0ad43d6adca | 01940ab0897aa6005764fc220b900e4d6161d36b | refs/heads/main | 2023-01-31T17:19:42.050628 | 2020-12-16T05:21:31 | 2020-12-16T05:21:31 | 306,735,108 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 151 | py | def inverte_dicionario(dicionario):
dic={}
for k,v in dicionario.items():
if k not in dic:
dic[v] = [k]
else:
dic[i].append(k)
return dic | [
"you@example.com"
] | you@example.com |
3e02054f06af47425f874171b112433e6801cf4d | e6dab5aa1754ff13755a1f74a28a201681ab7e1c | /.parts/lib/django-1.2/tests/regressiontests/forms/localflavor/au.py | aeb1337e0162f17d8ed5184078850e0af2b835dc | [] | no_license | ronkagan/Euler_1 | 67679203a9510147320f7c6513eefd391630703e | 022633cc298475c4f3fd0c6e2bde4f4728713995 | refs/heads/master | 2021-01-06T20:45:52.901025 | 2014-09-06T22:34:16 | 2014-09-06T22:34:16 | 23,744,842 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 111 | py | /home/action/.parts/packages/googleappengine/1.9.4/lib/django-1.2/tests/regressiontests/forms/localflavor/au.py | [
"ron.y.kagan@gmail.com"
] | ron.y.kagan@gmail.com |
66ae71ed528fe12d0af5e8baef4fc65e0e6293d7 | 6d652bc92e51475a3ff8a8b3af74fe5658f44988 | /predict.py | 99fa357d7261be6843b9c3daaf2ef41b94c4cbbf | [] | no_license | gongzishuye/seq2seq | ff32c9d54a4686eea0708adc57b54c8b88d41f2d | b2ebcf5c8f4715bd58b2f0804be51f4d8f8807fc | refs/heads/master | 2020-05-26T01:51:49.474882 | 2019-05-22T15:29:28 | 2019-05-22T15:29:28 | 188,065,860 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,634 | py | import tensorflow as tf
from data_helpers import loadDataset, getBatches, sentence2enco
from model import Seq2SeqModel
import sys
import numpy as np
tf.app.flags.DEFINE_integer('rnn_size', 128, 'Number of hidden units in each layer')
tf.app.flags.DEFINE_integer('num_layers', 1, 'Number of layers in each encoder and decoder')
tf.app.flags.DEFINE_integer('embedding_size', 128, 'Embedding dimensions of encoder and decoder inputs')
tf.app.flags.DEFINE_float('learning_rate', 0.0001, 'Learning rate')
tf.app.flags.DEFINE_integer('batch_size', 128, 'Batch size')
tf.app.flags.DEFINE_integer('numEpochs', 6, 'Maximum # of training epochs')
tf.app.flags.DEFINE_integer('steps_per_checkpoint', 100, 'Save model checkpoint every this iteration')
tf.app.flags.DEFINE_string('model_dir', 'model/', 'Path to save model checkpoints')
tf.app.flags.DEFINE_string('model_name', 'chatbot.ckpt', 'File name used for model checkpoints')
FLAGS = tf.app.flags.FLAGS
data_path = 'data/dataset-cornell-length10-filter1-vocabSize40000.pkl'
word2id, id2word, trainingSamples = loadDataset(data_path)
def predict_ids_to_seq(predict_ids, id2word, beam_szie):
'''
将beam_search返回的结果转化为字符串
:param predict_ids: 列表，长度为batch_size，每个元素都是decode_len*beam_size的数组
:param id2word: vocab字典
:return:
'''
for single_predict in predict_ids:
for i in range(beam_szie):
predict_list = np.ndarray.tolist(single_predict[:, :, i])
predict_seq = [id2word[idx] for idx in predict_list[0]]
print(" ".join(predict_seq))
with tf.Session() as sess:
model = Seq2SeqModel(FLAGS.rnn_size, FLAGS.num_layers, FLAGS.embedding_size, FLAGS.learning_rate, word2id,
mode='decode', use_attention=False, beam_search=False, beam_size=5, max_gradient_norm=5.0)
ckpt = tf.train.get_checkpoint_state(FLAGS.model_dir)
if ckpt and tf.train.checkpoint_exists(ckpt.model_checkpoint_path):
print('Reloading model parameters..')
model.saver.restore(sess, ckpt.model_checkpoint_path)
else:
raise ValueError('No such file:[{}]'.format(FLAGS.model_dir))
sys.stdout.write("> ")
sys.stdout.flush()
sentence = sys.stdin.readline()
while sentence:
batch = sentence2enco(sentence, word2id)
predicted_ids = model.infer(sess, batch)
print(predicted_ids)
print(predicted_ids[0].shape)
# print(predicted_ids)
predict_ids_to_seq(predicted_ids, id2word, 1)
print("> ", "")
sys.stdout.flush()
sentence = sys.stdin.readline()
| [
"clbupt@126.com"
] | clbupt@126.com |
0a3c2b0a002cf9764b2f5687b2a9b646a20c3a0c | 383f6af87df71826218db68b1637b5a9d198865f | /gan_git-02/gan_git/compare_gan/architectures/resnet5.py | ec00f54c363906895bd2e27dafbdcce7e416033d | [
"Apache-2.0"
] | permissive | youbin-jia/jyb_paper | 59a2c2517f366799109e3a0ae306d4a43b160dfa | cdff5c8214b8895ac31d519458ad626d24a5ca9b | refs/heads/master | 2022-04-19T23:13:22.772166 | 2020-04-20T00:11:20 | 2020-04-20T00:11:20 | 255,092,174 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,251 | py | # coding=utf-8
# Copyright 2018 Google LLC & Hwalsuk Lee.
#
# 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.
"""A deep neural architecture with residual blocks and skip connections.
It contains 5 residual blocks in both the generator and discriminator and
supports 128x128 resolution. Details can be found in "Improved Training
of Wasserstein GANs", Gulrajani I. et al. 2017. The related code is available at
https://github.com/igul222/improved_wgan_training/blob/master/gan_64x64.py.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from compare_gan.architectures import arch_ops as ops
from compare_gan.architectures import resnet_ops
import numpy as np
from six.moves import range
import tensorflow as tf
class Generator(resnet_ops.ResNetGenerator):
"""ResNet generator consisting of 5 blocks, outputs 128x128x3 resolution."""
def __init__(self, ch=64, channels=(8, 8, 4, 4, 2, 1), **kwargs):
super(Generator, self).__init__(**kwargs)
self._ch = ch
self._channels = channels
def apply(self, z, y, is_training):
"""Build the generator network for the given inputs.
Args:
z: `Tensor` of shape [batch_size, z_dim] with latent code.
y: `Tensor` of shape [batch_size, num_classes] with one hot encoded
labels.
is_training: boolean, are we in train or eval model.
Returns:
A tensor of size [batch_size] + self._image_shape with values in [0, 1].
"""
# Each block upscales by a factor of 2.
seed_size = 4
image_size = self._image_shape[0]
# Map noise to the actual seed.
net = ops.linear(
z,
self._ch * self._channels[0] * seed_size * seed_size,
scope="fc_noise")
# Reshape the seed to be a rank-4 Tensor.
net = tf.reshape(
net,
[-1, seed_size, seed_size, self._ch * self._channels[0]],
name="fc_reshaped")
up_layers = np.log2(float(image_size) / seed_size)
if not up_layers.is_integer():
raise ValueError("log2({}/{}) must be an integer.".format(
image_size, seed_size))
if up_layers < 0 or up_layers > 5:
raise ValueError("Invalid image_size {}.".format(image_size))
up_layers = int(up_layers)
for block_idx in range(5):
block = self._resnet_block(
name="B{}".format(block_idx + 1),
in_channels=self._ch * self._channels[block_idx],
out_channels=self._ch * self._channels[block_idx + 1],
scale="up" if block_idx < up_layers else "none")
net = block(net, z=z, y=y, is_training=is_training)
net = self.batch_norm(
net, z=z, y=y, is_training=is_training, name="final_norm")
net = tf.nn.relu(net)
net = ops.conv2d(net, output_dim=self._image_shape[2],
k_h=3, k_w=3, d_h=1, d_w=1, name="final_conv")
net = tf.nn.sigmoid(net)
return net
class Discriminator(resnet_ops.ResNetDiscriminator):
"""ResNet5 discriminator, 5 blocks, supporting 128x128x3 and 128x128x1."""
def __init__(self, ch=64, channels=(1, 2, 4, 4, 8, 8), **kwargs):
super(Discriminator, self).__init__(**kwargs)
self._ch = ch
self._channels = channels
def apply(self, x, y, is_training):
"""Apply the discriminator on a input.
Args:
x: `Tensor` of shape [batch_size, ?, ?, ?] with real or fake images.
y: `Tensor` of shape [batch_size, num_classes] with one hot encoded
labels.
is_training: Boolean, whether the architecture should be constructed for
training or inference.
Returns:
Tuple of 3 Tensors, the final prediction of the discriminator, the logits
before the final output activation function and logits form the second
last layer.
"""
resnet_ops.validate_image_inputs(x)
colors = x.shape[3]
if colors not in [1, 3]:
raise ValueError("Number of color channels not supported: {}".format(
colors))
block = self._resnet_block(
name="B0",
in_channels=colors,
out_channels=self._ch,
scale="down")
output = block(x, z=None, y=y, is_training=is_training)
for block_idx in range(5):
block = self._resnet_block(
name="B{}".format(block_idx + 1),
in_channels=self._ch * self._channels[block_idx],
out_channels=self._ch * self._channels[block_idx + 1],
scale="down")
output = block(output, z=None, y=y, is_training=is_training)
output = tf.nn.relu(output)
pre_logits = tf.reduce_mean(input_tensor=output, axis=[1, 2])
out_logit = ops.linear(pre_logits, 1, scope="disc_final_fc",
use_sn=self._spectral_norm)
out = tf.nn.sigmoid(out_logit)
return out, out_logit, pre_logits
| [
"2448396171@qq.com"
] | 2448396171@qq.com |
4e0e283ebd57d220e4070f2d22e550491adfc318 | ea9b92426976f23267796897349e6ca9afe10ccc | /run_cv.py | 8da8f489dfaa8c728bf872f4b1e81e286b127708 | [] | no_license | Kevin-chen-sheng/GCN-DBP | 493a28c563ad0bff1a92b640383a5a32e2d719ba | 2f2f45f10c9781eec19f174c62ebafdc5fd68f4b | refs/heads/main | 2023-02-09T17:03:15.514862 | 2021-01-04T08:38:02 | 2021-01-04T08:38:02 | 303,096,732 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,235 | py | from sklearn.model_selection import StratifiedKFold
#import argparse
import numpy as np
from prepare_data import prepare_data
from build_graph import build_graph
from train import train
import tensorflow as tf
'''
def getopt():
parse=argparse.ArgumentParser()
parse.add_argument('-cv','--crossvalidation',type=int,default=5)
parse.add_argument('-k','--kmer',type=int,default=5)
parse.add_argument('-fa','--fasta',type=str)
args=parse.parse_args()
return args
'''
def split2cv(cv,fasta_path,dataset_name):
fasta=open(fasta_path,'r')
seqs_list=[]
for line in fasta:
if line.startswith('>'):
continue
seqs_list.append(line.strip())
n_sample=len(seqs_list)
print('the number of sentence:',n_sample)
y=np.array([1]*int(n_sample//2)+[0]*int(n_sample//2))
X=np.array(seqs_list)
indices=np.arange(n_sample)
print('indices.shape',indices.shape)
np.random.shuffle(indices)
seqs=X[indices]
labels=y[indices]
print('seqs.shape:',seqs.shape)
print('labels.shape',labels.shape)
skflod=StratifiedKFold(n_splits=cv)
i=1
for train,test in skflod.split(seqs,labels):
print('train.shape:',train.shape)
print('test.shape',test.shape)
train_object=open('./data/corpus/'+dataset_name+'_cv'+str(i)+'.train.txt','w')
train_seqs=seqs[train]
print("train_seqs.shape",train_seqs.shape)
train_object.writelines([line+'\n' for line in train_seqs])
train_object.close()
test_object=open('./data/corpus/'+dataset_name+'_cv'+str(i)+'.test.txt','w')
test_seqs=seqs[test]
print("test_seqs.shape",test_seqs.shape)
test_object.writelines([line+'\n' for line in test_seqs])
test_object.close()
train_labels=open('./data/corpus/'+dataset_name+'_cv'+str(i)+'.train.label','w')
train_y=labels[train]
print("train_labels.shape",train_y.shape)
train_labels.writelines([str(e)+'\n' for e in train_y])
train_labels.close()
test_labels=open('./data/corpus/'+dataset_name+'_cv'+str(i)+'.test.label','w')
test_y=labels[test]
print("test_labels.shape",test_y.shape)
test_labels.writelines([str(e)+'\n' for e in test_y])
test_labels.close()
i+=1
if __name__ == "__main__":
flags = tf.app.flags
FLAGS = flags.FLAGS
#args=getopt()
cv=5
k=3
fasta_name='PDB14120.txt'
#fasta_name='train.txt'
data_name=fasta_name.split('.')[0]
split2cv(cv,fasta_name,data_name)
test_acc=[]
test_pred=[]
test_labels=[]
for i in range (cv):
temp_data_name=data_name+'_cv'+str(i+1)
print(temp_data_name)
prepare_data(temp_data_name,k)
build_graph(temp_data_name,20,20)
acc,pred,labels=train(temp_data_name)
test_acc.extend([acc])
test_labels.extend(labels)
test_pred.extend(pred)
print('cv_acc:',np.mean(np.array(test_acc)))
np.savetxt(data_name+'_cv_acc_result.csv',np.array(test_acc),delimiter=',',fmt='%5f')
np.savetxt(data_name+'cv_pred.csv',np.array([test_labels,test_pred]).T,delimiter=',',fmt='%d')
| [
"654622131@qq.com"
] | 654622131@qq.com |
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