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b765d8a9e197945a8d8e649b5d2aab25a4ba41c1 | 1,548 | py | Python | posthog/apps.py | adamb70/posthog | 54ae8f0e70092f86b4aefbd93b56680dbd28b1c5 | [
"MIT"
] | null | null | null | posthog/apps.py | adamb70/posthog | 54ae8f0e70092f86b4aefbd93b56680dbd28b1c5 | [
"MIT"
] | null | null | null | posthog/apps.py | adamb70/posthog | 54ae8f0e70092f86b4aefbd93b56680dbd28b1c5 | [
"MIT"
] | null | null | null | import os
import sys
import posthoganalytics
from django.apps import AppConfig
from django.conf import settings
from posthog.utils import get_git_branch, get_git_commit, get_machine_id
from posthog.version import VERSION
| 34.4 | 111 | 0.628553 |
b765edd3d7064dd1a82224294d673c2cee6bca1a | 836 | py | Python | src/task_timer.py | dlb-rl/pulse-rl | ebe78d2286b2199d18b86941fbc9990e0d5c354a | [
"MIT"
] | 4 | 2021-12-06T09:19:14.000Z | 2022-01-31T13:58:06.000Z | src/task_timer.py | dlb-rl/pulse-rl | ebe78d2286b2199d18b86941fbc9990e0d5c354a | [
"MIT"
] | null | null | null | src/task_timer.py | dlb-rl/pulse-rl | ebe78d2286b2199d18b86941fbc9990e0d5c354a | [
"MIT"
] | null | null | null | import os
import json
import time
from datetime import timedelta
| 26.967742 | 85 | 0.574163 |
b7660ef0961ba8b4931477e766e7019f01819220 | 8,718 | py | Python | tasks-deploy/terminal/check.py | chankruze/qctf-school-2018 | 1e732cf264ee0a94bc2fc1fd8cf3a20660d57605 | [
"MIT"
] | null | null | null | tasks-deploy/terminal/check.py | chankruze/qctf-school-2018 | 1e732cf264ee0a94bc2fc1fd8cf3a20660d57605 | [
"MIT"
] | null | null | null | tasks-deploy/terminal/check.py | chankruze/qctf-school-2018 | 1e732cf264ee0a94bc2fc1fd8cf3a20660d57605 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
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| 670.615385 | 8,408 | 0.848704 |
b76732831186e479ef5311c8854a1d2a5b3efda3 | 18,186 | py | Python | bioshareX/api/views.py | amschaal/bioshare | 7ac5da6874f70605ded8757c46fd9629d2d3d18b | [
"MIT"
] | 7 | 2015-12-10T23:23:53.000Z | 2018-08-22T11:00:28.000Z | bioshareX/api/views.py | amschaal/bioshare | 7ac5da6874f70605ded8757c46fd9629d2d3d18b | [
"MIT"
] | 61 | 2015-12-11T01:26:26.000Z | 2021-10-05T00:25:20.000Z | bioshareX/api/views.py | amschaal/bioshare | 7ac5da6874f70605ded8757c46fd9629d2d3d18b | [
"MIT"
] | 2 | 2019-05-31T16:33:37.000Z | 2021-05-03T20:51:25.000Z | # Create your views here.
from django.core.urlresolvers import reverse
from django.http.response import JsonResponse, HttpResponse
from settings.settings import AUTHORIZED_KEYS_FILE, SITE_URL
from bioshareX.models import Share, SSHKey, MetaData, Tag
from bioshareX.forms import MetaDataForm, json_form_validate
from guardian.shortcuts import get_perms, get_users_with_perms, remove_perm, assign_perm
from bioshareX.utils import JSONDecorator, json_response, json_error, share_access_decorator, safe_path_decorator, validate_email, fetchall,\
test_path, du
from django.contrib.auth.models import User, Group
from django.db.models import Q
import os
from rest_framework.decorators import api_view, detail_route, throttle_classes,\
action
from bioshareX.forms import ShareForm
from guardian.decorators import permission_required
from bioshareX.utils import ajax_login_required, email_users
from rest_framework import generics, viewsets, status
from bioshareX.models import ShareLog, Message
from bioshareX.api.serializers import ShareLogSerializer, ShareSerializer,\
GroupSerializer, UserSerializer, MessageSerializer
from rest_framework.permissions import DjangoModelPermissions, IsAuthenticated
from bioshareX.permissions import ManageGroupPermission
from rest_framework.response import Response
from guardian.models import UserObjectPermission
from django.contrib.contenttypes.models import ContentType
import datetime
from bioshareX.api.filters import UserShareFilter, ShareTagFilter,\
GroupShareFilter, ActiveMessageFilter
from rest_framework.throttling import UserRateThrottle
from django.utils import timezone
import csv
def get_group(request):
query = request.GET.get('query')
try:
group = Group.objects.get(name=query)
return json_response({'group':{'name':group.name}})
except Exception, e:
return json_error([e.message])
"""
Requires: "name", "notes", "filesystem" arguments.
Optional: "link_to_path", "read_only"
"""
class ShareLogList(generics.ListAPIView):
serializer_class = ShareLogSerializer
permission_classes = (IsAuthenticated,)
filter_fields = {'action':['icontains'],'user__username':['icontains'],'text':['icontains'],'paths':['icontains'],'share':['exact']}
# @detail_route(['POST'])
# def remove_user(self,request,*args,**kwargs):
# # user = request.query_params.get('user')
# # self.get_object().user_set.remove(user)
# return Response({'status':'success'})
| 47.11399 | 298 | 0.651875 |
b769a2ddbb714e86c922fd616f0acb57b564206d | 5,192 | py | Python | db_query.py | UiOHive/FinseDashboard | 14184fbc425e87a4b9a13b3a9b31159b181cf357 | [
"MIT"
] | null | null | null | db_query.py | UiOHive/FinseDashboard | 14184fbc425e87a4b9a13b3a9b31159b181cf357 | [
"MIT"
] | null | null | null | db_query.py | UiOHive/FinseDashboard | 14184fbc425e87a4b9a13b3a9b31159b181cf357 | [
"MIT"
] | null | null | null | import datetime
import os, sys
import pprint
import requests
from pandas.io.json import json_normalize
import pandas as pd
URL = 'https://wsn.latice.eu/api/query/v2/'
#URL = 'http://localhost:8000/wsn/api/query/v2/'
#TOKEN = os.getenv('WSN_TOKEN')
TOKEN = os.getenv('WSN_TOKEN')
path = os.getcwd()
if __name__ == '__main__':
# We need an authentication token
TOKEN = os.getenv('WSN_TOKEN')
# Number of elements to return in every query
limit = 100
# Example 1: Get all the fields and tags of a given mote from a given time.
# This is good to explore the data, but bad on performance.
response = query(limit=limit,
serial=0x1F566F057C105487,
time__gte=datetime.datetime(2017, 11, 15),
debug=True,
)
# Example 2: Get the RSSI of an Xbee module identified by its address
print('==============================================')
response = query(limit=limit,
source_addr_long=0x0013A2004105D4B6,
fields=['rssi'],
debug=True,
)
# Example 3: Get the battery and internal temperature from all motes,
# include the serial tag to tell them apart.
# Frames that don't have at least one of the fields we ask for will not be
# included.
print('==============================================')
response = query(limit=limit,
fields=['bat', 'in_temp'],
tags=['serial'],
debug=True,
)
# Example 4: Get the time the frame was received by the Pi
print('==============================================')
response = query(limit=limit,
serial=408520806,
fields=['received'],
debug=True,
)
# Example 5: Get the battery once every hour
response = query(limit=10,
serial=0x1F566F057C105487,
fields=['bat'],
interval=3600,
debug=True,
)
| 28.217391 | 125 | 0.573575 |
b76bc1e49faa136f8b812dcedd6dc878d0d8aa05 | 4,716 | py | Python | src/olympia/reviews/tests/test_models.py | leplatrem/addons-server | 8b5ebda6f33194aa9fce12c0453574e7f850e6ad | [
"BSD-3-Clause"
] | null | null | null | src/olympia/reviews/tests/test_models.py | leplatrem/addons-server | 8b5ebda6f33194aa9fce12c0453574e7f850e6ad | [
"BSD-3-Clause"
] | null | null | null | src/olympia/reviews/tests/test_models.py | leplatrem/addons-server | 8b5ebda6f33194aa9fce12c0453574e7f850e6ad | [
"BSD-3-Clause"
] | null | null | null | from django.utils import translation
from olympia import amo
from olympia.amo.tests import TestCase, ESTestCase
from olympia.addons.models import Addon
from olympia.reviews import tasks
from olympia.reviews.models import (
check_spam, GroupedRating, Review, ReviewFlag, Spam)
from olympia.users.models import UserProfile
| 31.44 | 78 | 0.636556 |
b76c4833b7dafb63e3cda3a938dba6519b8c5061 | 1,544 | py | Python | snpy/spline2/__init__.py | emirkmo/snpy | 2a0153c84477ba8a30310d7dbca3d5a8f24de3c6 | [
"MIT"
] | 6 | 2019-01-14T19:40:45.000Z | 2021-06-05T12:19:39.000Z | snpy/spline2/__init__.py | emirkmo/snpy | 2a0153c84477ba8a30310d7dbca3d5a8f24de3c6 | [
"MIT"
] | 3 | 2017-04-25T20:06:22.000Z | 2021-06-09T20:46:41.000Z | snpy/spline2/__init__.py | emirkmo/snpy | 2a0153c84477ba8a30310d7dbca3d5a8f24de3c6 | [
"MIT"
] | 8 | 2017-04-25T19:57:57.000Z | 2021-11-12T11:54:19.000Z | ''' Spline2.py: wrapper for B. Thijsse et al.'s hyper-spline routines.
Yet another spline interpolation routine. The problem: given a set of
experimental data with noise, find the spline with the optimal number of
knots.
Solution : They use the usual kind of routines to determine least-squares
splines from a given set of knot points. The problem REALLY
boils down to: how many knots do you use? There are two
extremes: put a knot point on each data point to get an
interpolating spline (which sucks for experimental data with
noise). The other extreme is to have the minimal set of knots
to define a polynomial of order k (e.g., a cubic). This also
sucks. Somewhere between the two extremes is a number of
knots that optimally recovers the information in the data and
smooths out the noise.
spline2 starts with a large number of knots (interpolating
spline) and iteratively removes knots until a figure of merit
reaches some prescribed value. In this case, this figure of
merit is the Durbin-Watson statistic, which measures the auto-
correlation between the residuals of the spline fit.
For more details, see:
* Barend J. Thijsse et al., "A Practical Algorithm for Least-Squares
spline Approximation of Data Containing Noise", Computers in Physics,
vol 12 no. 4 July 1998
* http://structureandchange.3me.tudelft.nl/
'''
from .spline2 import *
| 49.806452 | 74 | 0.687824 |
b76e06eb55845d82a11e8d62864a8001b125af43 | 703 | py | Python | halo_app/infra/cache.py | halo-framework/halo-app | 98e057b2f433d97d903589ac75a6c2544174bac8 | [
"MIT"
] | null | null | null | halo_app/infra/cache.py | halo-framework/halo-app | 98e057b2f433d97d903589ac75a6c2544174bac8 | [
"MIT"
] | null | null | null | halo_app/infra/cache.py | halo-framework/halo-app | 98e057b2f433d97d903589ac75a6c2544174bac8 | [
"MIT"
] | null | null | null | from __future__ import annotations
import elasticache_auto_discovery
from pymemcache.client.hash import HashClient
# elasticache settings
elasticache_config_endpoint = "your-elasticache-cluster-endpoint:port"
nodes = elasticache_auto_discovery.discover(elasticache_config_endpoint)
nodes = map(lambda x: (x[1], int(x[2])), nodes)
memcache_client = HashClient(nodes)
def put(requestId, event):
"""
This function puts into memcache and get from it.
Memcache is hosted using elasticache
"""
# Put the UUID to the cache.
memcache_client.set(requestId, event)
| 25.107143 | 72 | 0.752489 |
b76e3c3a78b500e4bd43645ac8426138d20f7491 | 659 | py | Python | uniclass_to_nf_ea_com_source/b_code/migrators/uniclass_raw_to_domain/evolve/evolve_stage_4/domain_table_data_processor/parent_code_column_adder.py | boro-alpha/uniclass_to_nf_ea_com | 753e97467ce53c25bc86341b915489c2eeeb3f49 | [
"MIT"
] | 2 | 2021-08-09T14:40:04.000Z | 2022-03-13T22:22:19.000Z | uniclass_to_nf_ea_com_source/b_code/migrators/uniclass_raw_to_domain/evolve/evolve_stage_4/domain_table_data_processor/parent_code_column_adder.py | boro-alpha/uniclass_to_nf_ea_com | 753e97467ce53c25bc86341b915489c2eeeb3f49 | [
"MIT"
] | null | null | null | uniclass_to_nf_ea_com_source/b_code/migrators/uniclass_raw_to_domain/evolve/evolve_stage_4/domain_table_data_processor/parent_code_column_adder.py | boro-alpha/uniclass_to_nf_ea_com | 753e97467ce53c25bc86341b915489c2eeeb3f49 | [
"MIT"
] | null | null | null | import numpy as np
from uniclass_to_nf_ea_com_source.b_code.configurations.common_constants.uniclass_bclearer_constants import PARENT_CODE_COLUMN_NAME, \
UNICLASS2015_OBJECT_TABLE_NAME
| 27.458333 | 134 | 0.752656 |
b771162a3330c2472592fd5f42c757bebf6eb7a4 | 12,046 | py | Python | ext/ANTsPyNet/antspynet/utilities/mixture_density_utilities.py | tsmonteiro/fmri_proc | ee740cfa3c3a7ef8e1ee1ebd3b286a66712e0ec1 | [
"MIT"
] | 2 | 2021-11-16T10:00:33.000Z | 2021-12-13T02:57:40.000Z | ext/ANTsPyNet/antspynet/utilities/mixture_density_utilities.py | tsmonteiro/fmri_proc | ee740cfa3c3a7ef8e1ee1ebd3b286a66712e0ec1 | [
"MIT"
] | null | null | null | ext/ANTsPyNet/antspynet/utilities/mixture_density_utilities.py | tsmonteiro/fmri_proc | ee740cfa3c3a7ef8e1ee1ebd3b286a66712e0ec1 | [
"MIT"
] | 1 | 2021-12-13T02:57:27.000Z | 2021-12-13T02:57:27.000Z |
import keras.backend as K
from keras.engine import Layer, InputSpec
from keras.layers import Concatenate
from keras import initializers
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
def get_mixture_density_loss_function(output_dimension, number_of_mixtures):
"""
Returns a loss function for the mixture density.
Arguments
---------
output_dimension : integer
Dimensionality of the output.
number_of_mixtures : integer
Number of gaussians used.
Returns
-------
Function
A function providing the mean square error accuracy
"""
with tf.name_scope("MixtureDensityNetwork"):
return(loss_function)
def get_mixture_density_sampling_function(output_dimension, number_of_mixtures):
"""
Returns a sampling function for the mixture density.
Arguments
---------
output_dimension : integer
Dimensionality of the output.
number_of_mixtures : integer
Number of gaussians used.
Returns
-------
Function
A function providing the mean square error accuracy
"""
with tf.name_scope("MixtureDensityNetwork"):
return(sampling_function)
def get_mixture_density_mse_function(output_dimension, number_of_mixtures):
"""
Returns a mse function for the mixture density.
Arguments
---------
output_dimension : integer
Dimensionality of the output.
number_of_mixtures : integer
Number of gaussians used.
Returns
-------
Function
A function providing the mean square error accuracy
"""
with tf.name_scope("MixtureDensityNetwork"):
return(mse_accuracy_function)
def split_mixture_parameters(parameters, output_dimension, number_of_mixtures):
"""
Splits the mixture parameters.
Arguments
---------
parameters : tuple
Parameter to split
output_dimension : integer
Dimensionality of the output.
number_of_mixtures : integer
Number of gaussians used.
Returns
-------
List of arrays
Separate mixture parameters
"""
dimension = number_of_mixtures * output_dimension
mu = parameters[:dimension]
sigma = parameters[dimension:(2 * dimension)]
pi_logits = parameters[-number_of_mixtures:]
return([mu, sigma, pi_logits])
def mixture_density_software_max(logits, temperature=1.0):
"""
Softmax function for mixture density with temperature adjustment.
Arguments
---------
logits : list or numpy array
input
temperature :
The temperature for to adjust the distribution (default 1.0)
Returns
-------
Scalar
Softmax loss value.
"""
e = np.array(logits) / temperature
e -= np.max(e)
e = np.exp(e)
distribution = e / np.sum(e)
return(distribution)
def sample_from_categorical_distribution(distribution):
"""
Softmax function for mixture density with temperature adjustment.
Arguments
---------
distribution :
input categorical distribution from which to sample.
Returns
-------
Scalar
A single sample.
"""
r = np.random.rand(1)
accumulate = 0
for i in range(len(distribution)):
accumulate += distribution[i]
if accumulate >= r:
return(i)
tf.logging.info('Error: sampling categorical model.')
return(-1)
def sample_from_output(parameters, output_dimension, number_of_mixtures,
temperature=1.0, sigma_temperature=1.0):
"""
Softmax function for mixture density with temperature adjustment.
Arguments
---------
output_dimension : integer
Dimensionality of the output.
number_of_mixtures : integer
Number of gaussians used.
temperature :
The temperature for to adjust the distribution (default 1.0)
sigma_temperature :
The temperature for to adjust the distribution (default 1.0)
Returns
-------
Scalar
A single sample.
"""
mu, sigma, pi = split_mixture_parameters(parameters, output_dimension, number_of_mixtures)
pi_softmax = mixture_density_software_max(pi, temperature=temperature)
m = sample_from_categorical_distribution(pi_softmax)
mu_vector = mu[m * output_dimension:(m + 1) * output_dimension]
sigma_vector = sigma[m * output_dimension:(m + 1) * output_dimension] * sigma_temperature
covariance_matrix = np.identity(output_dimension) * sigma_vector
sample = np.random.multivariate_normal(mu_vector, covariance_matrix, 1)
return(sample)
| 30.651399 | 94 | 0.628341 |
b7712de7485aecf34c54bcaa9134a8c65cfc7aa6 | 1,481 | py | Python | test.py | pnawalramka/cowin | f8ce6286d38fc0616a385ac0a971c8947f71348c | [
"MIT"
] | null | null | null | test.py | pnawalramka/cowin | f8ce6286d38fc0616a385ac0a971c8947f71348c | [
"MIT"
] | null | null | null | test.py | pnawalramka/cowin | f8ce6286d38fc0616a385ac0a971c8947f71348c | [
"MIT"
] | null | null | null | import json
from unittest import mock, TestCase
import check_availability
json_data = \
"""
{
"centers": [
{
"center_id": 1234,
"name": "District General Hostpital",
"name_l": "",
"address": "45 M G Road",
"address_l": "",
"state_name": "Maharashtra",
"state_name_l": "",
"district_name": "Satara",
"district_name_l": "",
"block_name": "Jaoli",
"block_name_l": "",
"pincode": "413608",
"lat": 28.7,
"long": 77.1,
"from": "09:00:00",
"to": "18:00:00",
"fee_type": "Free",
"vaccine_fees": [
{
"vaccine": "COVISHIELD",
"fee": "250"
}
],
"sessions": [
{
"session_id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
"date": "31-05-2021",
"available_capacity": 50,
"available_capacity_dose1": 25,
"available_capacity_dose2": 25,
"min_age_limit": 18,
"vaccine": "COVISHIELD",
"slots": [
"FORENOON",
"AFTERNOON"
]
}
]
}
]
}
"""
| 21.779412 | 63 | 0.532073 |
b771d6a65389f019399e4105e7ca9559208f9b9c | 271 | py | Python | pycon_project/apps/proposals/admin.py | mitsuhiko/pycon | 73688a82080539a1c0d575cf3248f55fefb6b9ba | [
"BSD-3-Clause"
] | 1 | 2017-09-04T08:19:08.000Z | 2017-09-04T08:19:08.000Z | pycon_project/apps/proposals/admin.py | mitsuhiko/pycon | 73688a82080539a1c0d575cf3248f55fefb6b9ba | [
"BSD-3-Clause"
] | null | null | null | pycon_project/apps/proposals/admin.py | mitsuhiko/pycon | 73688a82080539a1c0d575cf3248f55fefb6b9ba | [
"BSD-3-Clause"
] | null | null | null | from django.contrib import admin
from proposals.models import Proposal, ProposalSessionType
admin.site.register(ProposalSessionType)
admin.site.register(Proposal,
list_display = ["title", "session_type", "audience_level", "cancelled", "extreme_pycon", "invited"]
) | 30.111111 | 103 | 0.785978 |
b7720c668afa28b45e212a7ec9a950d7f27725bb | 12,805 | py | Python | cemc/mcmc/cov_reaction_crd.py | davidkleiven/WangLandau | 0b253dd98033c53560fe95c76f5e38257834bdf6 | [
"MIT"
] | 2 | 2022-02-10T00:38:53.000Z | 2022-03-17T22:08:40.000Z | cemc/mcmc/cov_reaction_crd.py | davidkleiven/CEMC | 0b253dd98033c53560fe95c76f5e38257834bdf6 | [
"MIT"
] | 30 | 2018-05-21T14:52:00.000Z | 2021-02-24T07:45:09.000Z | cemc/mcmc/cov_reaction_crd.py | davidkleiven/WangLandau | 0b253dd98033c53560fe95c76f5e38257834bdf6 | [
"MIT"
] | 3 | 2018-10-09T14:03:32.000Z | 2022-02-09T05:36:05.000Z | import sys
from cemc.mcmc import ReactionCrdInitializer, ReactionCrdRangeConstraint
import numpy as np
from itertools import product
import time
from numpy.linalg import inv
def log(self, msg):
print(msg)
def set(self, atoms, value):
"""Create an atoms object with the correct reaction coordinate.
:param Atoms atom: Atoms object (not used, using the one attached
to the MC object). Argument only included traj_full = TrajectoryWriter(self.traj_file, mode="a")
traj_clst = TrajectoryWriter(self.traj_file_clst, mode="a")parent class
has it.
:param float value: Target value for the react traj_full = TrajectoryWriter(self.traj_file, mode="a")
traj_clst = TrajectoryWriter(self.traj_file_clst, mode="a")dinate
"""
from random import choice, shuffle
# Make sure that the observer is initialized correctly
self.cov_obs.init_com_and_covariance()
self.fixed_nucl_mc.network([])
max_attempts = 1000 * len(self.fixed_nucl_mc.atoms)
attempt = 0
neighbors = self.fixed_nucl_mc.network_clust_indx
atoms = self.fixed_nucl_mc.atoms
calc = atoms.get_calculator()
current_value = self.get(atoms)
current_diff = abs(value - current_value)
should_increase_value = current_diff < value
shoud_decrease_value = not should_increase_value
mc = self.fixed_nucl_mc
output_every = 15
now = time.time()
while attempt < max_attempts:
if self.fixed_nucl_mc.network.num_root_nodes() > 1:
raise RuntimeError("For some unknown reason there are "
"more than one cluster!")
attempt += 1
surf_atoms = self.surface_atoms
rand_surf_atom = choice(surf_atoms)
rand_surf_atom2 = choice(surf_atoms)
shuffle(neighbors)
found_swap_candidate = False
for indx in neighbors:
t_indx = mc.get_translated_indx(rand_surf_atom2, indx)
symb = mc.atoms[t_indx].symbol
if symb == self.matrix_element:
old_symb = mc.atoms[rand_surf_atom].symbol
ch1 = (rand_surf_atom, old_symb, symb)
ch2 = (t_indx, symb, old_symb)
system_changes = [ch1, ch2]
if self.fixed_nucl_mc.network.move_creates_new_cluster(system_changes):
continue
assert self.fixed_nucl_mc.network.num_root_nodes() == 1
if mc._no_constraint_violations(system_changes):
calc.calculate(atoms, ["energy"], system_changes)
found_swap_candidate = True
break
if not found_swap_candidate:
continue
# Get bases its calculation on the atom tracker
new_value = self.get(atoms, system_changes=system_changes)
new_diff = abs(new_value - value)
if time.time() - now > output_every:
print("Current value: {} Target value: {}"
"".format(new_value, value))
sys.stdout.flush()
now = time.time()
if new_diff < current_diff:
# The candidate trial moves brings the system closer to the
# target value, so we accept this move
current_diff = new_diff
# We need to update the covariance observer
self.cov_obs(system_changes)
# Update the network
assert self.fixed_nucl_mc.network.num_root_nodes() == 1
self.fixed_nucl_mc.network(system_changes)
assert self.fixed_nucl_mc.network.num_root_nodes() == 1
# Update the symbol tracker
self.fixed_nucl_mc._update_tracker(system_changes)
calc.clear_history()
else:
calc.undo_changes()
assert self.fixed_nucl_mc.network.num_root_nodes() == 1
if should_increase_value and new_value > value:
break
elif shoud_decrease_value and new_value < value:
break
if attempt == max_attempts:
raise CouldNotFindValidStateError("Did not manage to find a state "
"with reaction coordinate "
"{}!".format(value))
class CovarianceRangeConstraint(ReactionCrdRangeConstraint):
"""Constraint to ensure that the system stays without its bounds.
:param FixedNucleusMC fixed_nuc_mc: Monte Carlo object
:param list range: Upper and lower bound of the reaction coordinate
:param CovarianceCrdInitializer cov_init: Initializer
:param bool verbose: If True print messages every 10 sec
if the constraint is violated
"""
def get_new_value(self, system_changes):
"""Get new value for reaction coordinate.
:param list system_changes: List with the proposed changes
:return: Reaction coordate after the change
:rtype: float
"""
# Get the new value of the observer
new_val = self._cov_init.get(None, system_changes=system_changes)
return new_val
def __call__(self, system_changes):
"""Check the system is in a valid state after the changes.
:param list system_changes: Proposed changes
:return: True/False, if True the system is still within the bounds
:rtype: bool
"""
new_val = self.get_new_value(system_changes)
ok = (new_val >= self.range[0] and new_val < self.range[1])
if not ok and self.verbose:
# The evaluation of this constraint can be time consuming
# so let the user know at regular intervals
if time.time() - self.last_print > 10:
print("Move violates constraint")
self.last_print = time.time()
return ok
| 38.338323 | 109 | 0.617415 |
b77285d78a57f47f11411ca9d0f97da9f2e1f31c | 3,810 | py | Python | mysql/main.py | migachevalexey/BigQuery-integrations | d44546fbd3ff116e35ef90800ade2399e7266d9e | [
"MIT"
] | null | null | null | mysql/main.py | migachevalexey/BigQuery-integrations | d44546fbd3ff116e35ef90800ade2399e7266d9e | [
"MIT"
] | null | null | null | mysql/main.py | migachevalexey/BigQuery-integrations | d44546fbd3ff116e35ef90800ade2399e7266d9e | [
"MIT"
] | null | null | null | from google.cloud import bigquery
from mysql.connector import connect
import os
# writeable part of the filesystem for Cloud Functions instance
gc_write_dir = "/tmp"
def get_file_mysql(mysql_configuration):
"""
Querying data using Connector/Python via *host* MySQL server.
The function return the full path to the file that has been downloaded.
"""
# construct MySQLConnection object and query table on a server
try:
cnx = connect(user = mysql_configuration["user"], password = mysql_configuration["psswd"], host = mysql_configuration["host"],
database = mysql_configuration["database"], port = mysql_configuration["port"] )
cursor = cnx.cursor(dictionary = True)
cursor.execute(mysql_configuration["query"])
results = cursor.fetchall()
file_name = "mysql.txt"
with open(file_name, "w") as output_file:
for row in results:
output_file.write(json.dumps(row) + "\n")
file_location = gc_write_dir + "/" + file_name
print("Query <" + mysql_configuration["query"] + "> has completed successfully.")
finally:
try:
cursor.close()
cnx.close()
except:
print("Connection has not been established.")
return file_location
def give_file_gbq(path_to_file, bq_configuration):
"""
Download file from *path_to_file* to BigQuery table using *bq_configuration* settings.
"""
# construct Client object with the path to the table in which data will be stored
client = bigquery.Client(project = bq_configuration["project_id"])
dataset_ref = client.dataset(bq_configuration["dataset_id"])
table_ref = dataset_ref.table(bq_configuration["table_id"])
# determine uploading options
job_config = bigquery.LoadJobConfig()
job_config.source_format = "NEWLINE_DELIMITED_JSON"
job_config.write_disposition = bq_configuration["write_disposition"]
job_config.autodetect = True
# upload the file to BigQuery table
with open(path_to_file, "rb") as source_file:
job = client.load_table_from_file(source_file, table_ref, location = bq_configuration["location"], job_config = job_config)
job.result()
print("The Job " + job.job_id + " in status " + job.state + " for table " + bq_configuration["project_id"] + "." + bq_configuration["dataset_id"] + "." + bq_configuration["table_id"] + ".")
def mysql(request):
"""
Function to execute.
"""
try:
# get POST data from Flask.request object
request_json = request.get_json()
mysql_configuration = request_json["mysql"]
bq_configuration = request_json["bq"]
if not mysql_configuration.get("query"):
mysql_configuration["query"] = "SELECT * FROM " + mysql_configuration["table_id"]
if not mysql_configuration.get("port"):
mysql_configuration["port"] = 3306
if not bq_configuration.get("location"):
bq_configuration["location"] = "US"
bq_configuration["write_disposition"] = "WRITE_TRUNCATE"
except Exception as error:
print("An error occured with POST request data.")
print(str(error))
raise SystemExit
# go to writable directory
os.chdir(gc_write_dir)
# get the file from MySQL server
try:
mysql_file = get_file_mysql(mysql_configuration)
except Exception as error:
print("An error occured trying to get file from MySQL server.")
print(str(error))
raise SystemExit
# upload the file to BigQuery
try:
give_file_gbq(mysql_file, bq_configuration)
except Exception as error:
print("An error occured trying to upload file to Google BigQuery.")
print(str(error)) | 39.6875 | 193 | 0.664829 |
b7728a4f2303e9918fa06fb3ec419829f1f73d23 | 2,413 | py | Python | arthur.carvalho/snakepro/game.py | LUDUSLab/stem-games | 347afa8b1511d76f8070fa69f27a49b57e551376 | [
"MIT"
] | 2 | 2021-01-24T01:04:34.000Z | 2021-05-06T16:25:53.000Z | arthur.carvalho/snakepro/game.py | LUDUSLab/stem-games | 347afa8b1511d76f8070fa69f27a49b57e551376 | [
"MIT"
] | null | null | null | arthur.carvalho/snakepro/game.py | LUDUSLab/stem-games | 347afa8b1511d76f8070fa69f27a49b57e551376 | [
"MIT"
] | 3 | 2021-01-26T21:35:43.000Z | 2021-05-06T16:06:47.000Z | from config import *
from fruit import *
from snakebody import *
from wall import *
# score
score_font = pygame.font.Font('assets/PressStart2P.ttf', 30)
score = 0
# game over
game_ove_font = pygame.font.Font('assets/PressStart2P.ttf', 60)
game_over_text = game_ove_font.render('Game Over', True, color_black, color_73ED73)
play_sound = 0
snake_direction = 0
| 25.135417 | 110 | 0.574803 |
b7728d4f3bcf2508223268aec9d55c9c7919b6a4 | 821 | py | Python | preprocessing_pipeline/so/util/log.py | sotorrent/preprocessing-pipeline | d407a56760fa5ab975dc2043c89f478bd7c89e99 | [
"Apache-2.0"
] | null | null | null | preprocessing_pipeline/so/util/log.py | sotorrent/preprocessing-pipeline | d407a56760fa5ab975dc2043c89f478bd7c89e99 | [
"Apache-2.0"
] | null | null | null | preprocessing_pipeline/so/util/log.py | sotorrent/preprocessing-pipeline | d407a56760fa5ab975dc2043c89f478bd7c89e99 | [
"Apache-2.0"
] | 1 | 2021-09-22T16:07:18.000Z | 2021-09-22T16:07:18.000Z | import logging
from preprocessing_pipeline.so.util.config import LOG_LEVEL
def initialize_logger(logger_name):
"""
Configure a named logger (see https://stackoverflow.com/a/43794480).
"""
# create logger for module
module_logger = logging.getLogger(logger_name)
# set lowest log level the logger will handle (but not necessarily output)
module_logger.setLevel(LOG_LEVEL)
# disable propagation to root logger
module_logger.propagate = False
log_formatter = logging.Formatter(fmt='%(asctime)s [%(levelname)s] [%(name)s]: %(message)s')
# write log messages to console
console_handler = logging.StreamHandler()
console_handler.setFormatter(log_formatter)
console_handler.setLevel(LOG_LEVEL)
module_logger.addHandler(console_handler)
return module_logger
| 30.407407 | 96 | 0.742996 |
b7734741f7d6376de18287d5b5965809361df47f | 995 | py | Python | utilityFunction/CommandFunc.py | The-Fragment/FragmentFembot | bca0027b423753eb162590e8fd440a2c1e65d133 | [
"MIT"
] | null | null | null | utilityFunction/CommandFunc.py | The-Fragment/FragmentFembot | bca0027b423753eb162590e8fd440a2c1e65d133 | [
"MIT"
] | 3 | 2021-03-23T04:58:47.000Z | 2021-04-02T02:40:54.000Z | utilityFunction/CommandFunc.py | The-Fragment/FragmentFembot | bca0027b423753eb162590e8fd440a2c1e65d133 | [
"MIT"
] | null | null | null | import random
# Ex. takes in 2d20 and outputs the string Rolling 2 d20
# Ex. takes in 2d20 and outputs resultString = 11, 19 results = 30 numDice = 2
| 27.638889 | 78 | 0.582915 |
b773ef3748302d9fb0e80bd06beb0fda6a677835 | 12,339 | py | Python | src/reviews/tests/test_forms.py | Talengi/phase | 60ff6f37778971ae356c5b2b20e0d174a8288bfe | [
"MIT"
] | 8 | 2016-01-29T11:53:40.000Z | 2020-03-02T22:42:02.000Z | src/reviews/tests/test_forms.py | Talengi/phase | 60ff6f37778971ae356c5b2b20e0d174a8288bfe | [
"MIT"
] | 289 | 2015-03-23T07:42:52.000Z | 2022-03-11T23:26:10.000Z | src/reviews/tests/test_forms.py | Talengi/phase | 60ff6f37778971ae356c5b2b20e0d174a8288bfe | [
"MIT"
] | 7 | 2015-12-08T09:03:20.000Z | 2020-05-11T15:36:51.000Z | # -*- coding: utf-8 -*-
import datetime
from django.test import TestCase
from django.contrib.contenttypes.models import ContentType
from accounts.factories import UserFactory
from categories.factories import CategoryFactory
from documents.factories import DocumentFactory
from default_documents.models import ContractorDeliverable
from default_documents.forms import ContractorDeliverableRevisionForm
from default_documents.factories import (ContractorDeliverableFactory,
ContractorDeliverableRevisionFactory)
from reviews.models import Review
| 34.275 | 86 | 0.630359 |
b77448adc21f21e754acd95d28d79c117e90042e | 2,814 | py | Python | WWW/pycopia/WWW/HTML5simple.py | kdart/pycopia | 1446fabaedf8c6bdd4ab1fc3f0ea731e0ef8da9d | [
"Apache-2.0"
] | 89 | 2015-03-26T11:25:20.000Z | 2022-01-12T06:25:14.000Z | WWW/pycopia/WWW/HTML5simple.py | kdart/pycopia | 1446fabaedf8c6bdd4ab1fc3f0ea731e0ef8da9d | [
"Apache-2.0"
] | 1 | 2015-07-05T03:27:43.000Z | 2015-07-11T06:21:20.000Z | WWW/pycopia/WWW/HTML5simple.py | kdart/pycopia | 1446fabaedf8c6bdd4ab1fc3f0ea731e0ef8da9d | [
"Apache-2.0"
] | 30 | 2015-04-30T01:35:54.000Z | 2022-01-12T06:19:49.000Z | #!/usr/bin/python2.7
# -*- coding: utf-8 -*-
# vim:ts=4:sw=4:softtabstop=4:smarttab:expandtab
# 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.
"""
Simple HTML5 top-level boilerplate generator.
"""
from __future__ import absolute_import
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import division
# Currenty using this subset of HTML5 features shared by both FF 3.6.x and Chrome 10
BROWSER_FEATURES = ['applicationcache', 'backgroundsize', 'borderimage', 'borderradius',
'boxshadow', 'canvas', 'canvastext', 'csscolumns', 'cssgradients',
'csstransforms', 'draganddrop', 'flexbox', 'fontface', 'geolocation',
'hashchange', 'hsla', 'js', 'localstorage', 'multiplebgs', 'opacity',
'postmessage', 'rgba', 'sessionstorage', 'svg', 'svgclippaths', 'textshadow',
'webworkers']
NO_BROWSER_FEATURES = ['no-audio', 'no-cssanimations', 'no-cssreflections',
'no-csstransforms3d', 'no-csstransitions', 'no-history', 'no-indexeddb',
'no-inlinesvg', 'no-smil', 'no-touch', 'no-video', 'no-webgl', 'no-websockets',
'no-websqldatabase']
FEATURE_CLASS = " ".join(BROWSER_FEATURES) + " " + " ".join(NO_BROWSER_FEATURES)
#### simple templates for use by mostly client-side apps.
SIMPLE_TEMPLATE = """<?xml version="1.0" encoding="{charset}"?>
<!DOCTYPE html>
<html lang="en" xmlns="http://www.w3.org/1999/xhtml" class="{features}">
<head>
<meta charset="{charset}" />
<meta name="robots" content="noindex" />
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
<title>{title}</title>
<link href="/media/css/{appname}.css" type="text/css" rel="stylesheet" />
<!-- <script src="/media/js/modernizr-1.7.min.js" type="text/javascript"></script> -->
<script src="/media/js/packed.js" type="text/javascript"></script>
<script src="/media/js/{appname}.js" type="text/javascript"></script>
</head>
<body>
{body}
</body>
</html>
"""
if __name__ == "__main__":
docs = new_simple_document("myapp", "MyApp", "utf-8")
print (docs)
| 35.620253 | 90 | 0.678749 |
b77490b49e8e303cfb2f69ab8e30192b9d37bd8f | 2,077 | py | Python | zairachem/reports/report.py | ersilia-os/ersilia-automl-chem | fabb1f05d17cff11ec0e084495eed4c0152f2f63 | [
"MIT"
] | null | null | null | zairachem/reports/report.py | ersilia-os/ersilia-automl-chem | fabb1f05d17cff11ec0e084495eed4c0152f2f63 | [
"MIT"
] | null | null | null | zairachem/reports/report.py | ersilia-os/ersilia-automl-chem | fabb1f05d17cff11ec0e084495eed4c0152f2f63 | [
"MIT"
] | null | null | null | from .plots import (
ActivesInactivesPlot,
ConfusionPlot,
RocCurvePlot,
ProjectionPlot,
RegressionPlotRaw,
HistogramPlotRaw,
RegressionPlotTransf,
HistogramPlotTransf,
Transformation,
IndividualEstimatorsAurocPlot,
InidvidualEstimatorsR2Plot,
)
from .. import ZairaBase
from ..vars import REPORT_SUBFOLDER
| 28.847222 | 69 | 0.692826 |
b777765b36345a7cbdc249bcc3d7922fbe5e7398 | 2,198 | py | Python | tests/backend/configobj.py | edyan/python-anyconfig | d237909a6e4848737539b80951b710238c72052f | [
"MIT"
] | null | null | null | tests/backend/configobj.py | edyan/python-anyconfig | d237909a6e4848737539b80951b710238c72052f | [
"MIT"
] | null | null | null | tests/backend/configobj.py | edyan/python-anyconfig | d237909a6e4848737539b80951b710238c72052f | [
"MIT"
] | null | null | null | #
# Copyright (C) 2013 - 2017 Satoru SATOH <ssato @ redhat.com>
# License: MIT
#
# pylint: disable=missing-docstring,invalid-name,too-few-public-methods
# pylint: disable=ungrouped-imports
from __future__ import absolute_import
import anyconfig.backend.configobj as TT
import tests.backend.common as TBC
from anyconfig.compat import OrderedDict as ODict
CNF_0_S = """\
# This is the 'initial_comment'
# Which may be several lines
keyword1 = value1
'keyword 2' = 'value 2'
[ "section 1" ]
# This comment goes with keyword 3
keyword 3 = value 3
'keyword 4' = value4, value 5, 'value 6'
[[ sub-section ]] # an inline comment
# sub-section is inside "section 1"
'keyword 5' = 'value 7'
'keyword 6' = '''A multiline value,
that spans more than one line :-)
The line breaks are included in the value.'''
[[[ sub-sub-section ]]]
# sub-sub-section is *in* 'sub-section'
# which is in 'section 1'
'keyword 7' = 'value 8'
[section 2] # an inline comment
keyword8 = "value 9"
keyword9 = value10 # an inline comment
# The 'final_comment'
# Which also may be several lines
"""
_ML_0 = """A multiline value,
that spans more than one line :-)
The line breaks are included in the value."""
CNF_0 = ODict((('keyword1', 'value1'),
('keyword 2', 'value 2'),
('section 1',
ODict((('keyword 3', 'value 3'),
('keyword 4', ['value4', 'value 5', 'value 6']),
('sub-section',
ODict((('keyword 5', 'value 7'),
('keyword 6', _ML_0),
('sub-sub-section',
ODict((('keyword 7', 'value 8'), ))))))))),
('section 2',
ODict((('keyword8', 'value 9'), ('keyword9', 'value10'))))))
# vim:sw=4:ts=4:et:
| 27.135802 | 76 | 0.589172 |
b777b683adb530c1229387728fa21c1239e09fa6 | 23 | py | Python | backend/lorre/__init__.py | nhurman/Lorre | 9a19d00809bd3850d288c9ef1166da016d29b819 | [
"MIT"
] | null | null | null | backend/lorre/__init__.py | nhurman/Lorre | 9a19d00809bd3850d288c9ef1166da016d29b819 | [
"MIT"
] | null | null | null | backend/lorre/__init__.py | nhurman/Lorre | 9a19d00809bd3850d288c9ef1166da016d29b819 | [
"MIT"
] | null | null | null | __author__ = 'nhurman'
| 11.5 | 22 | 0.73913 |
b778baead541bab3544aa4b5bfec40bbfb0e7118 | 1,794 | py | Python | tests/test_spider.py | aezhov/sw_downloader | 325f6fe98579dda4f98613e4513fc46c7bd962c7 | [
"MIT"
] | 1 | 2020-01-23T06:56:34.000Z | 2020-01-23T06:56:34.000Z | tests/test_spider.py | aezhov/sw_downloader | 325f6fe98579dda4f98613e4513fc46c7bd962c7 | [
"MIT"
] | null | null | null | tests/test_spider.py | aezhov/sw_downloader | 325f6fe98579dda4f98613e4513fc46c7bd962c7 | [
"MIT"
] | 2 | 2020-01-23T06:56:36.000Z | 2020-01-24T05:34:25.000Z | import requests
from scrapy.http import HtmlResponse
from sw_downloader.sw_downloader.spiders.smashing_magazine \
import SmashingMagazineSpider
| 39.866667 | 70 | 0.628763 |
b778ede17d0ff72b747e93fc5f260c19e384862d | 160 | py | Python | 1_PROGI/Exe 5.py | Julymusso/IFES | 939277c375dacc7750705c5593537d80ab4cbc0e | [
"MIT"
] | null | null | null | 1_PROGI/Exe 5.py | Julymusso/IFES | 939277c375dacc7750705c5593537d80ab4cbc0e | [
"MIT"
] | null | null | null | 1_PROGI/Exe 5.py | Julymusso/IFES | 939277c375dacc7750705c5593537d80ab4cbc0e | [
"MIT"
] | null | null | null | #var
#num, media, i: inteiro
media=0
for i in range(1,11,1):
num=int(input("Digite um nmero: "))
media = media+num
media=media/i
print (media) | 17.777778 | 40 | 0.61875 |
b7794cab91544e360a3b3517961177ee512565ea | 4,289 | py | Python | rio/tasks.py | soasme/rio | e6b89634db8d3ad75ac7f7b25ddec5b19d4f66e2 | [
"MIT"
] | null | null | null | rio/tasks.py | soasme/rio | e6b89634db8d3ad75ac7f7b25ddec5b19d4f66e2 | [
"MIT"
] | 14 | 2016-04-14T04:18:41.000Z | 2016-05-12T03:46:37.000Z | rio/tasks.py | soasme/rio | e6b89634db8d3ad75ac7f7b25ddec5b19d4f66e2 | [
"MIT"
] | 1 | 2016-04-06T08:54:20.000Z | 2016-04-06T08:54:20.000Z | # -*- coding: utf-8 -*-
"""
rio.tasks
~~~~~~~~~~
Implement of rio tasks based on celery.
"""
from time import time
from celery import chord
from requests import ConnectionError
from celery.utils.log import get_task_logger
from rio.core import celery
from rio.core import sentry
from rio.utils.http import dispatch_webhook_request
from rio.utils.http import raven_context
from rio.utils.http import FailureWebhookError
from rio.utils.template import format_template
from rio.signals import webhook_ran
logger = get_task_logger(__name__)
def exec_event(event, webhooks, payload):
"""Execute event.
Merge webhooks run set to do some stats after all
of the webhooks been responded successfully.
+---------+
|webhook-1+--------------------+
+---------+ |
|
+---------+ |
|webhook-2+-------------+ |
+---------+ +------+-----+
|merge runset+------>
+---------+ +------+-----+
|webhook-3+-------------+ |
+---------+ |
|
+---------+ |
|... +--------------------+
+---------+
Error webhook will be propagated. Note that other webhook
calls will still execute.
"""
calls = (
call_webhook.s(event, webhook, payload)
for webhook in webhooks
)
callback = merge_webhooks_runset.s()
call_promise = chord(calls)
promise = call_promise(callback)
return promise
| 26.312883 | 77 | 0.55211 |
b77a241d42c4accce70a300b51e344bbc1b51e81 | 2,932 | py | Python | security_app/createuserpoolgroup.py | jagalembu/chalice_cognito_multi_tenancy | b1a6569e716848adfd5b443239fca1ae883d4f4b | [
"MIT"
] | null | null | null | security_app/createuserpoolgroup.py | jagalembu/chalice_cognito_multi_tenancy | b1a6569e716848adfd5b443239fca1ae883d4f4b | [
"MIT"
] | null | null | null | security_app/createuserpoolgroup.py | jagalembu/chalice_cognito_multi_tenancy | b1a6569e716848adfd5b443239fca1ae883d4f4b | [
"MIT"
] | null | null | null | import os
import uuid
import json
import argparse
import boto3
USERPOOL = {
'env_var_poolid': 'APPUSERPOOLID',
'env_var_cognito_url': 'COGNITOJWKSURL',
'env_var_pool_client': 'APPCLIENTID',
}
if __name__ == '__main__':
main() | 30.863158 | 104 | 0.645634 |
b77c8918ea2f71cb1258eb1a156531c01f3b83b2 | 269 | py | Python | Chapter 07/hmac-md5.py | Prakshal2607/Effective-Python-Penetration-Testing | f49fedc172a1add45edb21f66f74746dfa9c944a | [
"MIT"
] | 346 | 2016-06-21T11:39:39.000Z | 2022-01-26T03:19:29.000Z | Chapter 07/hmac-md5.py | liceaga/Effective-Python-Penetration-Testing | 0b043885231662efd63402eec3c9cb413b9693e2 | [
"MIT"
] | 1 | 2016-06-21T11:44:42.000Z | 2016-11-17T05:10:08.000Z | Chapter 07/hmac-md5.py | liceaga/Effective-Python-Penetration-Testing | 0b043885231662efd63402eec3c9cb413b9693e2 | [
"MIT"
] | 210 | 2016-06-22T12:08:47.000Z | 2022-03-16T15:54:30.000Z | import hmac
hmac_md5 = hmac.new('secret-key')
f = open('sample-file.txt', 'rb')
try:
while True:
block = f.read(1024)
if not block:
break
hmac_md5.update(block)
finally:
f.close()
digest = hmac_md5.hexdigest()
print digest | 16.8125 | 33 | 0.598513 |
b77cac8f40a35a229bb7b41f7b04619f55a2baf4 | 31,686 | py | Python | dingtalk/python/alibabacloud_dingtalk/alitrip_1_0/models.py | yndu13/dingtalk-sdk | 700fb7bb49c4d3167f84afc5fcb5e7aa5a09735f | [
"Apache-2.0"
] | null | null | null | dingtalk/python/alibabacloud_dingtalk/alitrip_1_0/models.py | yndu13/dingtalk-sdk | 700fb7bb49c4d3167f84afc5fcb5e7aa5a09735f | [
"Apache-2.0"
] | null | null | null | dingtalk/python/alibabacloud_dingtalk/alitrip_1_0/models.py | yndu13/dingtalk-sdk | 700fb7bb49c4d3167f84afc5fcb5e7aa5a09735f | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
# This file is auto-generated, don't edit it. Thanks.
from Tea.model import TeaModel
from typing import Dict, List
| 33.636943 | 142 | 0.581424 |
b7800aafff5c8094f397d2e3b7573a73689dfdba | 560 | py | Python | src/while_exit.py | Alex9808/py101 | 18c585c1433e8ec6f5e4962e556a781e0c3c3cd5 | [
"MIT"
] | 25 | 2018-08-14T22:13:13.000Z | 2021-07-23T04:14:06.000Z | src/while_exit.py | Alex9808/py101 | 18c585c1433e8ec6f5e4962e556a781e0c3c3cd5 | [
"MIT"
] | 1 | 2021-05-21T23:46:42.000Z | 2021-05-21T23:46:42.000Z | src/while_exit.py | Alex9808/py101 | 18c585c1433e8ec6f5e4962e556a781e0c3c3cd5 | [
"MIT"
] | 34 | 2018-07-30T20:48:17.000Z | 2022-02-04T19:01:27.000Z | #!/usr/bin/env python
''' Este programa se repetir 3 veces o hasta que se ingrese
la palabra "despedida" y desplegar slo el nmero de intentos
fallidos hasta que cualquiera de los eventos ocurentradara. Al
ingresar la palabra "termina" el programa se detendr.'''
entrada = ""
suma = 0
while suma < 3:
entrada = input("Clave:")
if entrada == "despedida":
break
elif entrada == "termina":
exit()
suma = suma + 1
print("Intento %d. \n " % suma)
print("Tuviste %d intentos fallidos." % suma)
| 29.473684 | 67 | 0.630357 |
b78064bab0e579a79f199c581d29dfd0023d9a67 | 1,337 | py | Python | src/kong/db.py | paulgessinger/kong | b1e2ec0c18f432fa2419b2b0dc95ee1e391cf7a5 | [
"MIT"
] | 3 | 2020-02-14T09:23:56.000Z | 2020-08-24T16:19:00.000Z | src/kong/db.py | paulgessinger/kong | b1e2ec0c18f432fa2419b2b0dc95ee1e391cf7a5 | [
"MIT"
] | 159 | 2019-09-16T19:17:16.000Z | 2022-03-29T19:12:37.000Z | src/kong/db.py | paulgessinger/kong | b1e2ec0c18f432fa2419b2b0dc95ee1e391cf7a5 | [
"MIT"
] | null | null | null | """
Singleton database instance
"""
from typing import TYPE_CHECKING, Any, List, ContextManager, Tuple, Iterable
if not TYPE_CHECKING:
from playhouse.sqlite_ext import SqliteExtDatabase, AutoIncrementField
else: # pragma: no cover
database = SqliteExtDatabase(None)
| 20.890625 | 86 | 0.449514 |
b7828d9ca80482a07e76866d18c12b99668834d3 | 2,582 | py | Python | selenium_wrapper/factory.py | dfeeley/selenium-wrapper | f69576802e7847d120a051a2902da5750b9c6203 | [
"MIT"
] | 1 | 2022-01-14T20:21:19.000Z | 2022-01-14T20:21:19.000Z | selenium_wrapper/factory.py | dfeeley/selenium-wrapper | f69576802e7847d120a051a2902da5750b9c6203 | [
"MIT"
] | null | null | null | selenium_wrapper/factory.py | dfeeley/selenium-wrapper | f69576802e7847d120a051a2902da5750b9c6203 | [
"MIT"
] | null | null | null | import os
from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from selenium.webdriver.chrome.options import Options
from .driver import Driver
| 39.723077 | 84 | 0.703718 |
b782afffa41a32debaad33cd5a697c066dc182f8 | 14,153 | py | Python | networking_cisco/tests/unit/saf/agent/vdp/test_lldpad.py | arvindsharma16/networking-cisco | 2f38c25742296f07ab80479c152504353da0a1d4 | [
"Apache-2.0"
] | null | null | null | networking_cisco/tests/unit/saf/agent/vdp/test_lldpad.py | arvindsharma16/networking-cisco | 2f38c25742296f07ab80479c152504353da0a1d4 | [
"Apache-2.0"
] | null | null | null | networking_cisco/tests/unit/saf/agent/vdp/test_lldpad.py | arvindsharma16/networking-cisco | 2f38c25742296f07ab80479c152504353da0a1d4 | [
"Apache-2.0"
] | 1 | 2020-08-31T22:53:38.000Z | 2020-08-31T22:53:38.000Z | # Copyrigh 2015 Cisco Systems.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import collections
import mock
from neutron.tests import base
from networking_cisco.apps.saf.agent.vdp import lldpad
from networking_cisco.apps.saf.agent.vdp import lldpad_constants as vdp_con
from networking_cisco.apps.saf.common import dfa_sys_lib as utils
try:
OrderedDict = collections.OrderedDict
except AttributeError:
import ordereddict
OrderedDict = ordereddict.OrderedDict
| 50.366548 | 79 | 0.466191 |
b7836e4485ed6acdd7e26cba6a9e54fccf62bd20 | 15,656 | py | Python | py/prospect/viewer/cds.py | segasai/prospect | 0237fad5b04f5a982ba4178320e1ca5bb5fa408f | [
"BSD-3-Clause"
] | 4 | 2018-10-22T21:12:43.000Z | 2019-07-11T20:08:12.000Z | py/prospect/viewer/cds.py | segasai/prospect | 0237fad5b04f5a982ba4178320e1ca5bb5fa408f | [
"BSD-3-Clause"
] | 54 | 2019-12-07T08:24:53.000Z | 2022-02-25T10:17:59.000Z | py/prospect/viewer/cds.py | segasai/prospect | 0237fad5b04f5a982ba4178320e1ca5bb5fa408f | [
"BSD-3-Clause"
] | 5 | 2019-12-20T21:47:40.000Z | 2021-01-20T23:54:43.000Z | # Licensed under a 3-clause BSD style license - see LICENSE.rst
# -*- coding: utf-8 -*-
"""
===================
prospect.viewer.cds
===================
Class containing all bokeh's ColumnDataSource objects needed in viewer.py
"""
import numpy as np
from pkg_resources import resource_filename
import bokeh.plotting as bk
from bokeh.models import ColumnDataSource
_specutils_imported = True
try:
from specutils import Spectrum1D, SpectrumList
except ImportError:
_specutils_imported = False
from ..coaddcam import coaddcam_prospect
from ..utilities import supported_desitarget_masks, vi_file_fields
def _airtovac(w):
"""Convert air wavelengths to vacuum wavelengths. Don't convert less than 2000 .
Parameters
----------
w : :class:`float`
Wavelength [] of the line in air.
Returns
-------
:class:`float`
Wavelength [] of the line in vacuum.
"""
if w < 2000.0:
return w;
vac = w
for iter in range(2):
sigma2 = (1.0e4/vac)*(1.0e4/vac)
fact = 1.0 + 5.792105e-2/(238.0185 - sigma2) + 1.67917e-3/(57.362 - sigma2)
vac = w*fact
return vac
| 45.37971 | 135 | 0.551993 |
b785c28b83b4fcf0dd190a336d9e93908aec9ec2 | 4,865 | py | Python | tests/test_32_read_registration.py | jschlyter/oidcendpoint | 3192e6043f00b22809f63329893c50bedbdeafbc | [
"Apache-2.0"
] | null | null | null | tests/test_32_read_registration.py | jschlyter/oidcendpoint | 3192e6043f00b22809f63329893c50bedbdeafbc | [
"Apache-2.0"
] | null | null | null | tests/test_32_read_registration.py | jschlyter/oidcendpoint | 3192e6043f00b22809f63329893c50bedbdeafbc | [
"Apache-2.0"
] | null | null | null | # -*- coding: latin-1 -*-
import json
import pytest
from oidcendpoint.endpoint_context import EndpointContext
from oidcendpoint.oidc.authorization import Authorization
from oidcendpoint.oidc.read_registration import RegistrationRead
from oidcendpoint.oidc.registration import Registration
from oidcendpoint.oidc.token import AccessToken
from oidcendpoint.oidc.userinfo import UserInfo
from oidcmsg.oidc import RegistrationRequest
KEYDEFS = [
{"type": "RSA", "key": "", "use": ["sig"]},
{"type": "EC", "crv": "P-256", "use": ["sig"]},
]
RESPONSE_TYPES_SUPPORTED = [
["code"],
["token"],
["id_token"],
["code", "token"],
["code", "id_token"],
["id_token", "token"],
["code", "token", "id_token"],
["none"],
]
CAPABILITIES = {
"subject_types_supported": ["public", "pairwise"],
"grant_types_supported": [
"authorization_code",
"implicit",
"urn:ietf:params:oauth:grant-type:jwt-bearer",
"refresh_token",
],
}
msg = {
"application_type": "web",
"redirect_uris": [
"https://client.example.org/callback",
"https://client.example.org/callback2",
],
"client_name": "My Example",
"client_name#ja-Jpan-JP": "",
"subject_type": "pairwise",
"token_endpoint_auth_method": "client_secret_basic",
"jwks_uri": "https://client.example.org/my_public_keys.jwks",
"userinfo_encrypted_response_alg": "RSA1_5",
"userinfo_encrypted_response_enc": "A128CBC-HS256",
"contacts": ["ve7jtb@example.org", "mary@example.org"],
"request_uris": [
"https://client.example.org/rf.txt#qpXaRLh_n93TT",
"https://client.example.org/rf.txt",
],
"post_logout_redirect_uris": [
"https://rp.example.com/pl?foo=bar",
"https://rp.example.com/pl",
],
}
CLI_REQ = RegistrationRequest(**msg)
| 35.510949 | 87 | 0.567523 |
b786deb138ef01a31f9f64e2908250e1c39d81e6 | 253 | py | Python | thippiproject/modelapp/admin.py | Anandgowda18/djangocomplete | c9eebe7834e404c73deca295289142a1e95ab573 | [
"Apache-2.0"
] | null | null | null | thippiproject/modelapp/admin.py | Anandgowda18/djangocomplete | c9eebe7834e404c73deca295289142a1e95ab573 | [
"Apache-2.0"
] | null | null | null | thippiproject/modelapp/admin.py | Anandgowda18/djangocomplete | c9eebe7834e404c73deca295289142a1e95ab573 | [
"Apache-2.0"
] | 1 | 2021-08-31T10:20:49.000Z | 2021-08-31T10:20:49.000Z | from django.contrib import admin
from modelapp.models import Project
# Register your models here.
admin.site.register(Project,Projectadmin) | 31.625 | 73 | 0.786561 |
b786e3a7dfda3169fee4e233a099bad862bcb4ab | 621 | py | Python | 2013.6/2015.6.py | luisalvaradoar/olimpiada.ct | aea479116036abe1c9cca3b482fed61f275ed319 | [
"Apache-2.0"
] | null | null | null | 2013.6/2015.6.py | luisalvaradoar/olimpiada.ct | aea479116036abe1c9cca3b482fed61f275ed319 | [
"Apache-2.0"
] | null | null | null | 2013.6/2015.6.py | luisalvaradoar/olimpiada.ct | aea479116036abe1c9cca3b482fed61f275ed319 | [
"Apache-2.0"
] | null | null | null |
main()
#15 min | 19.40625 | 58 | 0.516908 |
b78725b75722098cca7515b9adddc2dea857de17 | 538 | py | Python | hash.py | STR-Coding-Club/blockchain-demo | fae29a52d97c7595fa1e9d99527c4b034b721b8f | [
"MIT"
] | null | null | null | hash.py | STR-Coding-Club/blockchain-demo | fae29a52d97c7595fa1e9d99527c4b034b721b8f | [
"MIT"
] | null | null | null | hash.py | STR-Coding-Club/blockchain-demo | fae29a52d97c7595fa1e9d99527c4b034b721b8f | [
"MIT"
] | null | null | null | import hashlib, json
# def hash(to_hash):
# h = hashlib.md5()
# h.update(bytes(str(to_hash), 'utf-8'))
# return h.hexdigest()
| 24.454545 | 92 | 0.60223 |
b78782c19f15096aec39ba8d508066aa4591ae37 | 1,008 | py | Python | covid-modeling-master/generate_ma_csv.py | rdkap42/caedus-covid | f64a833bdf386708fcb9394f94026c48f8d474ee | [
"MIT"
] | 10 | 2020-03-17T21:21:50.000Z | 2020-04-30T02:30:47.000Z | covid-modeling-master/generate_ma_csv.py | rdkap42/caedus-covid | f64a833bdf386708fcb9394f94026c48f8d474ee | [
"MIT"
] | 5 | 2020-03-17T04:39:03.000Z | 2021-04-30T21:11:14.000Z | covid-modeling-master/generate_ma_csv.py | rdkap42/caedus-covid | f64a833bdf386708fcb9394f94026c48f8d474ee | [
"MIT"
] | null | null | null | import logging
import time
import numpy as np
from eda import ma_data, tx_data
from sir_fitting_us import seir_experiment, make_csv_from_tx_traj
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
logger.info("Fitting model.")
# initial values taken from previous fit, used to seed MH sampler efficiently.
x0 = np.array([ 0.393, -2.586, -3.241, -5.874, -24.999])
# ma_traj = seir_experiment(ma_data, x0, iterations=10000)
tx_traj = seir_experiment(tx_data, x0, iterations=10000)
# mean_ll = np.mean([ll for (x, ll) in ma_traj])
mean_ll = np.mean([ll for (x, ll) in tx_traj])
logger.info("Model fitting finished with mean log-likelihood: {}".format(mean_ll))
if mean_ll < -2000:
raise AssertionError(
"""Mean log-likelihood {} less than threshold of
-20. This is probably an error.""".format(mean_ll)
)
underscored_time = time.ctime().replace(" ", "_")
fname = "ma_seir_output_{}.csv".format(underscored_time)
make_csv_from_tx_traj(tx_traj, tx_data, fname)
| 31.5 | 82 | 0.727183 |
b7886dbd5b5bd5591584039afc3ce54cfdba530a | 6,877 | py | Python | For_Simulator/learning/plot_gmm_nd.py | a-taniguchi/CSL-BGM | 64bd803289e55b76a219c02ea040325a8a5b949e | [
"MIT"
] | 1 | 2018-09-27T12:19:05.000Z | 2018-09-27T12:19:05.000Z | learning/plot_gmm_nd.py | neuronalX/CSL-BGM | 2fc66611928783c9b65c675ec84d9c06e0b6cd8a | [
"MIT"
] | null | null | null | learning/plot_gmm_nd.py | neuronalX/CSL-BGM | 2fc66611928783c9b65c675ec84d9c06e0b6cd8a | [
"MIT"
] | 1 | 2018-09-27T12:19:21.000Z | 2018-09-27T12:19:21.000Z | #coding:utf-8
#gaussian plot (position category)
#Akira Taniguchi 2016/06/16
import itertools
import numpy as np
from scipy import linalg
import matplotlib.pyplot as plt
import matplotlib as mpl
from sklearn import mixture
from __init__ import *
from numpy.random import multinomial,uniform,dirichlet
from scipy.stats import multivariate_normal,invwishart,rv_discrete
trialname = "testss"#raw_input("trialname?(folder) >")
start = "1"#raw_input("start number?>")
end = "40"#raw_input("end number?>")
filename = raw_input("learning trial name?>")#"001"#
sn = int(start)
en = int(end)
Data = int(en) - int(sn) +1
foldername = datafolder + trialname+"("+str(sn).zfill(3)+"-"+str(en).zfill(3)+")"
Mu_p = [ np.array([0 for i in xrange(dim_p)]) for k in xrange(Kp) ]
Sig_p = [ np.eye(dim_p)*sig_p_init for k in xrange(Kp) ]
#p_dm = [[[-0.3945, 0.0165]], [[-0.3555, -0.006], [-0.336, 0.18]], [[-0.438, -0.0315], [-0.315, 0.0225], [-0.2355, 0.18]], [[-0.453, -0.018], [-0.3, -0.1005], [-0.258, -0.0255]], [[-0.438, 0.036], [-0.318, 0.1875], [-0.3, 0.0795]], [[-0.5535, 0.0675], [-0.336, -0.0465]], [[-0.3885, 0.0555], [-0.3465, -0.126]], [[-0.3555, -0.1425], [-0.324, -0.039], [-0.273, 0.0825]], [[-0.3885, 0.135]], [[-0.285, -0.0135]], [[-0.5265, 0.045], [-0.33, 0.18], [-0.2685, 0.0165]], [[-0.453, 0.015], [-0.3795, 0.231]], [[-0.3825, -0.231]], [[-0.327, -0.18], [-0.309, -0.0075]], [[-0.3735, -0.1455]], [[-0.2685, -0.0135]], [[-0.438, 0.033], [-0.36, 0.204], [-0.2955, 0.0855]], [[-0.45, 0.048]], [[-0.447, -0.006], [-0.3735, 0.1785]], [[-0.4005, 0.1755], [-0.2655, -0.0705]]]
p_temp = []
#for d in xrange(D):
# p_temp = p_temp + p_dm[d]
#[[-0.319936213, 0.117489433],[-0.345566772, -0.00810185],[-0.362990185, -0.042447971],[-0.277759177, 0.083363745]]
#Sig_p = [[] , [], [] ,[]]
#Sig_p[0] = [[0.010389635, 0.001709343],[0.001709343, 0.018386732]]
#[[0.005423979, 0.000652657],[0.000652657, 0.001134736]]
#Sig_p[1] = [[0.001920786, -0.001210214],[-0.001210214, 0.002644612]]
#Sig_p[2] = [[0.003648299, -0.000312398],[-0.000312398, 0.001518234]]
#Sig_p[3] = [[0.001851727, -0.000656013],[-0.000656013, 0.004825636]]
k=0
for line in open(foldername +'/' + filename + '/' + trialname + '_'+ filename +'_Mu_p.csv', 'r'):
itemList = line[:-1].split(',')
#for i in xrange(len(itemList)):
Mu_p[k] = [float(itemList[0]),float(itemList[1])]
k = k + 1
k=0
i=0
for line in open(foldername +'/' + filename + '/' + trialname + '_'+ filename +'_Sig_p.csv', 'r'):
itemList = line[:-1].split(',')
if k < Kp:
if (i == 0):
#for i in xrange(len(itemList)):
print itemList
Sig_p[k][0][0] = float(itemList[0])
Sig_p[k][0][1] = float(itemList[1])
i = i + 1
elif (i == 1):
#for i in xrange(len(itemList)):
print itemList
Sig_p[k][1][0] = float(itemList[0])
Sig_p[k][1][1] = float(itemList[1])
i = i + 1
elif (i == 2):
i = 0
k = k + 1
zp = []
pi_p = [0.0 for k in range(Kp)] #[0.017826621173443864,0.28554229470170217,0.041570976925928926,0.1265347852145472,0.52852532198437785]
dm = 0
for line in open(foldername +'/' + filename + '/' + trialname + '_'+ filename +'_zp.csv', 'r'):
itemList = line[:-1].split(',')
for i in range(len(itemList)):
if itemList[i] != '':
#print dm,itemList[i]
zp = zp + [int(itemList[i])]
dm = dm + 1
for line in open(foldername +'/' + filename + '/' + trialname + '_'+ filename +'_pi_p.csv', 'r'):
itemList = line[:-1].split(',')
for i in range(len(pi_p)):
pi_p[i] = float(itemList[i])
colors = ['b', 'g', 'm', 'r', 'c', 'y', 'k', 'orange', 'purple', 'brown']
color_iter = itertools.cycle(colors)
splot = plt.subplot(1, 1,1)
for k,(mean,covar,color) in enumerate(zip(Mu_p,Sig_p,color_iter)):
v, w = linalg.eigh(covar)
u = w[0] / linalg.norm(w[0])
angle = np.arctan(u[1] / u[0])
angle = 180 * angle / np.pi # convert to degrees
ell = mpl.patches.Ellipse([mean[1],mean[0]], v[0], v[1], 180 + angle, color=color)
ell.set_clip_box(splot.bbox)
ell.set_alpha(0.5)
#splot.add_artist(ell)
#
for i in range(int(5000*2*pi_p[k])):#)):#
X = multivariate_normal.rvs(mean=mean, cov=covar)
plt.scatter(X[1],X[0], s=5, marker='.', color=color, alpha=0.2)
#
#for i in range(len(p_temp)):
# plt.scatter(p_temp[i][1],p_temp[i][0], marker='x', c=colors[zp[i]])
"""
# Number of samples per component
n_samples = 500
# Generate random sample, two components
np.random.seed(0)
C = np.array([[0., -0.1], [1.7, .4]])
X = np.r_[np.dot(np.random.randn(n_samples, 2), C),
.7 * np.random.randn(n_samples, 2) + np.array([-6, 3])]
# Fit a mixture of Gaussians with EM using five components
#gmm = mixture.GMM(n_components=5, covariance_type='full')
#gmm.fit(X)
# Fit a Dirichlet process mixture of Gaussians using five components
dpgmm = mixture.DPGMM(n_components=5, covariance_type='full')
dpgmm.fit(X)
#for i, (clf, title) in enumerate([#(gmm, 'GMM'),
# (dpgmm, 'Dirichlet Process GMM')]):
"""
#clf=dpgmm
title = 'Position category'#data'
#Y_ = clf.predict(X)
#print Y_
"""
for i, (mean, covar, color) in enumerate(zip(
clf.means_, clf._get_covars(), color_iter)):
v, w = linalg.eigh(covar)
print covar
u = w[0] / linalg.norm(w[0])
# as the DP will not use every component it has access to
# unless it needs it, we shouldn't plot the redundant
# components.
#if not np.any(Y_ == i):
# continue
#plt.scatter(X[Y_ == i, 0], X[Y_ == i, 1], .8, color=color)
# Plot an ellipse to show the Gaussian component
angle = np.arctan(u[1] / u[0])
angle = 180 * angle / np.pi # convert to degrees
ell = mpl.patches.Ellipse(mean, v[0], v[1], 180 + angle, color=color)
ell.set_clip_box(splot.bbox)
ell.set_alpha(0.5)
splot.add_artist(ell)
"""
plt.ylim(-0.2, -0.8)
plt.xlim(-0.3, 0.3)
#plt.xticks([-0.8+0.1*i for i in range(7)])
#plt.yticks([-0.3+0.1*i for i in range(7)])
plt.title(title)
#w, h = plt.get_figwidth(), plt.get_figheight()
#ax = plt.add_axes((0.5 - 0.5 * 0.8 * h / w, 0.1, 0.8 * h / w, 0.8))
#aspect = (ax.get_xlim()[1] - ax.get_xlim()[0]) / (ax.get_ylim()[1] - ax.get_ylim()[0])
#ax.set_aspect(aspect)
plt.gca().set_aspect('equal', adjustable='box')
plt.savefig(foldername +'/' + filename + '/' + trialname + '_'+ filename +'_position_data_plot_p1nd.eps', dpi=150)
plt.savefig(foldername +'/' + filename + '/' + trialname + '_'+ filename +'_position_data_plot_p1nd.png', dpi=150)
plt.show()
| 38.418994 | 757 | 0.574378 |
b789e2f11f57608cb00f55b63d916cf77099aa18 | 338 | py | Python | condiment/tests/test_simple.py | WeilerWebServices/Kivy | 54e3438156eb0c853790fd3cecc593f09123f892 | [
"MIT"
] | 3 | 2020-09-13T09:55:02.000Z | 2021-01-23T11:13:59.000Z | condiment/tests/test_simple.py | WeilerWebServices/Kivy | 54e3438156eb0c853790fd3cecc593f09123f892 | [
"MIT"
] | 2 | 2018-03-16T22:01:12.000Z | 2020-01-13T10:33:22.000Z | condiment/tests/test_simple.py | WeilerWebServices/Kivy | 54e3438156eb0c853790fd3cecc593f09123f892 | [
"MIT"
] | 2 | 2015-04-26T15:31:40.000Z | 2017-09-12T12:36:14.000Z | #exclude
import condiment; condiment.install()
#endexclude
if WITH_TIMEBOMB:
timebomb = int(WITH_TIMEBOMB)
print 'timebomb feature is activated, and set to', timebomb
if WITH_INAPP_PURCHASE:
print 'inapp purchase feature is activated'
if WITH_TIMEBOMB and WITH_INAPP_PURCHASE:
print 'both features have been activated'
| 24.142857 | 63 | 0.775148 |
b78d491f7594796538d954c219bf7266a1779707 | 1,096 | py | Python | tests/init.py | touqir14/Emergent | 0782e1304702f3c95092953ce5da1d8ed69bbe6f | [
"MIT"
] | null | null | null | tests/init.py | touqir14/Emergent | 0782e1304702f3c95092953ce5da1d8ed69bbe6f | [
"MIT"
] | null | null | null | tests/init.py | touqir14/Emergent | 0782e1304702f3c95092953ce5da1d8ed69bbe6f | [
"MIT"
] | null | null | null | import pathlib
import os
import sys
from multiprocessing import resource_tracker
modify_resource_tracker()
add_Emergent_paths()
| 27.4 | 106 | 0.718978 |
b78f243f121a8fb7c7eb83f7fd3d5745810817b9 | 12,586 | py | Python | data-processor/modules/wikia_handler.py | stephanietuerk/art-history-jobs | d10718ce7c8eb591cea9808945d01a2273425a58 | [
"MIT"
] | null | null | null | data-processor/modules/wikia_handler.py | stephanietuerk/art-history-jobs | d10718ce7c8eb591cea9808945d01a2273425a58 | [
"MIT"
] | null | null | null | data-processor/modules/wikia_handler.py | stephanietuerk/art-history-jobs | d10718ce7c8eb591cea9808945d01a2273425a58 | [
"MIT"
] | null | null | null | import csv
import re
import unicodedata
import bs4
import wikia
from modules import utils
from modules.config import Config
| 44.161404 | 245 | 0.571667 |
b78f91bde4f8867fdadaaee058845f1ee62f598c | 3,949 | py | Python | ucsmsdk/mometa/cimcvmedia/CimcvmediaExtMgmtRuleEntry.py | anoop1984/python_sdk | c4a226bad5e10ad233eda62bc8f6d66a5a82b651 | [
"Apache-2.0"
] | null | null | null | ucsmsdk/mometa/cimcvmedia/CimcvmediaExtMgmtRuleEntry.py | anoop1984/python_sdk | c4a226bad5e10ad233eda62bc8f6d66a5a82b651 | [
"Apache-2.0"
] | null | null | null | ucsmsdk/mometa/cimcvmedia/CimcvmediaExtMgmtRuleEntry.py | anoop1984/python_sdk | c4a226bad5e10ad233eda62bc8f6d66a5a82b651 | [
"Apache-2.0"
] | null | null | null | """This module contains the general information for CimcvmediaExtMgmtRuleEntry ManagedObject."""
import sys, os
from ...ucsmo import ManagedObject
from ...ucscoremeta import UcsVersion, MoPropertyMeta, MoMeta
from ...ucsmeta import VersionMeta
| 58.940299 | 248 | 0.66042 |
b78fac6287214282885abd8ffbebb076e0bdd37a | 3,672 | py | Python | paddlescience/pde/pde_navier_stokes.py | juneweng/PaddleScience | f30ce908b6fbec2403936007d12d9701f74fd00e | [
"Apache-2.0"
] | null | null | null | paddlescience/pde/pde_navier_stokes.py | juneweng/PaddleScience | f30ce908b6fbec2403936007d12d9701f74fd00e | [
"Apache-2.0"
] | null | null | null | paddlescience/pde/pde_navier_stokes.py | juneweng/PaddleScience | f30ce908b6fbec2403936007d12d9701f74fd00e | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .pde_base import PDE
| 40.351648 | 223 | 0.510349 |
b7907344916d1e840e9f663cfdac58234f01e739 | 327 | py | Python | tests/strict/it_mod_double_fun.py | Euromance/pycopy | 540cfcc52d17667a5f6b2a176427cc031029b78f | [
"MIT"
] | 663 | 2018-12-30T00:17:59.000Z | 2022-03-14T05:03:41.000Z | tests/strict/it_mod_double_fun.py | Euromance/pycopy | 540cfcc52d17667a5f6b2a176427cc031029b78f | [
"MIT"
] | 41 | 2019-06-06T08:31:19.000Z | 2022-02-13T16:53:41.000Z | tests/strict/it_mod_double_fun.py | Euromance/pycopy | 540cfcc52d17667a5f6b2a176427cc031029b78f | [
"MIT"
] | 60 | 2019-06-01T04:25:00.000Z | 2022-02-25T01:47:31.000Z | import mod
try:
mod.foo = foo
except RuntimeError:
print("RuntimeError1")
print(mod.foo())
try:
mod.foo = 1
except RuntimeError:
print("RuntimeError2")
print(mod.foo)
try:
mod.foo = 2
except RuntimeError:
print("RuntimeError3")
print(mod.foo)
| 10.21875 | 26 | 0.642202 |
b791735533ee827f9ea58cc60b007fcd8bb18dbd | 2,295 | py | Python | LungCancer.py | SpiroGanas/Lung-Cancer-Machine-Learning | 4e38b3df9b560194f67ab03e9aaefad6c84216db | [
"MIT"
] | 1 | 2019-04-28T02:25:32.000Z | 2019-04-28T02:25:32.000Z | LungCancer.py | SpiroGanas/Lung-Cancer-Machine-Learning | 4e38b3df9b560194f67ab03e9aaefad6c84216db | [
"MIT"
] | null | null | null | LungCancer.py | SpiroGanas/Lung-Cancer-Machine-Learning | 4e38b3df9b560194f67ab03e9aaefad6c84216db | [
"MIT"
] | null | null | null | # Spiro Ganas
# 9/27/17
#
# Python 3 script to
######### NOTES ########################################
# 1. Each "slice" is a 512x512 image, stored in a single .dcm file.
# 2. A 3-dimensional CT Scan consists of between 94 and 541 slices (according to the Stage 1 data).
# 3. We need to rescale all the CT scans so they have the same number of slices.
#########################################################
####### CONSTANTS ##########################
# This folder contains one subfolder per patient
data_dir = 'D:\\Lung Cancer Dataset\\stage1'
# This CSV lists all patients and shows which ones have canver
truth_file = 'D:\\Lung Cancer Dataset\\stage1_labels.csv'
# These values are used to downscale the images to a uniform size
IMAGE_DIMESNION = 512 # Downscale the images so the size of a slice is IMAGE_DIMENSIONxIMAGE_DIMENSION
NUMBER_OF_SLICES =20 # A patient can have between X and Y slices. This downscales all patients to the same number of slices.
#############################################
import dicom #http://pydicom.readthedocs.io/en/stable/getting_started.html
#print("pydicom version: ", dicom.__version__)
import os
import math
import numpy as np
import pandas as pd
import tensorflow as tf
# Change this to wherever you are storing your data:
# IF YOU ARE FOLLOWING ON KAGGLE, YOU CAN ONLY PLAY WITH THE SAMPLE DATA, WHICH IS MUCH SMALLER
labels_df = pd.read_csv(truth_file, index_col=0)
#patients = list(labels_df.index.values)
patients = os.listdir(data_dir)
print(labels_df.head())
print(patients)
print(len(patients))
temp_min = 9999
temp_max = 0
for patient in patients:
try:
label = labels_df.get_value(patient, 'cancer')
path = data_dir +'/'+ patient
# a couple great 1-liners from: https://www.kaggle.com/gzuidhof/data-science-bowl-2017/full-preprocessing-tutorial
slices = [dicom.read_file(path + '/' + s) for s in os.listdir(path)]
slices.sort(key=lambda x: int(x.ImagePositionPatient[2]))
print(slices[0].pixel_array.shape, len(slices))
if len(slices)>temp_max: temp_max=len(slices)
if len(slices) < temp_min: temp_min = len(slices)
except:
pass
print("Minimum number of slices:", temp_min)
print("Maximum number of slices:", temp_max)
| 27.650602 | 127 | 0.662309 |
b791ac3d3021c73d2b06aeec225eba82f7ecf599 | 852 | py | Python | setup.py | LEGO-Robotics/aistorms | abfb6b978215507d331d9ade764310ee9d8c9448 | [
"MIT"
] | 1 | 2020-06-06T22:47:09.000Z | 2020-06-06T22:47:09.000Z | setup.py | AntoniLuongPham/LEGO-Mindstorms-AI | abfb6b978215507d331d9ade764310ee9d8c9448 | [
"MIT"
] | null | null | null | setup.py | AntoniLuongPham/LEGO-Mindstorms-AI | abfb6b978215507d331d9ade764310ee9d8c9448 | [
"MIT"
] | 1 | 2020-06-08T15:53:42.000Z | 2020-06-08T15:53:42.000Z | import json
import os
from setuptools import find_packages, setup
PACKAGE_NAMESPACE_NAME = 'aistorms'
METADATA_FILE_NAME = 'metadata.json'
REQUIREMENTS_FILE_NAME = 'requirements.txt'
_metadata = \
json.load(
open(os.path.join(
os.path.dirname(__file__),
PACKAGE_NAMESPACE_NAME,
METADATA_FILE_NAME)))
setup(
name=_metadata['PACKAGE'],
author=_metadata['AUTHOR'],
author_email=_metadata['AUTHOR_EMAIL'],
url=_metadata['URL'],
version=_metadata['VERSION'],
description=_metadata['DESCRIPTION'],
long_description=_metadata['DESCRIPTION'],
keywords=_metadata['DESCRIPTION'],
packages=find_packages(),
include_package_data=True,
install_requires=
[s for s in open(REQUIREMENTS_FILE_NAME).readlines()
if not s.startswith('#')])
| 24.342857 | 60 | 0.676056 |
b791e622824560b49e99db6ea638309e033920f8 | 3,357 | py | Python | scripts/merge.py | jgonzalezdemendibil/movie_publisher | 0e58cb616e6e6c2c5cac7cb5016e0874c0409b42 | [
"BSD-3-Clause"
] | null | null | null | scripts/merge.py | jgonzalezdemendibil/movie_publisher | 0e58cb616e6e6c2c5cac7cb5016e0874c0409b42 | [
"BSD-3-Clause"
] | null | null | null | scripts/merge.py | jgonzalezdemendibil/movie_publisher | 0e58cb616e6e6c2c5cac7cb5016e0874c0409b42 | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/python
# Copied from https://raw.githubusercontent.com/srv/srv_tools/kinetic/bag_tools/scripts/merge.py since this script is
# not released for indigo.
"""
Copyright (c) 2015,
Enrique Fernandez Perdomo
Clearpath Robotics, Inc.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of Systems, Robotics and Vision Group, University of
the Balearican Islands nor the names of its contributors may be used to
endorse or promote products derived from this software without specific
prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
from __future__ import print_function
import rosbag
import argparse
import os
import sys
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description='Merge multiple bag files into a single one.')
parser.add_argument('inbag', help='input bagfile(s)', nargs='+')
parser.add_argument('--output', help='output bag file', default='output.bag')
parser.add_argument('--topics', help='topics to merge from the input bag files', nargs='+', default=None)
parser.add_argument('--exclude_topics', help='topics not to merge from the input bag files', nargs='+', default=[])
args = parser.parse_args()
try:
sys.exit(merge(args.inbag, args.output, args.topics, args.exclude_topics))
except Exception, e:
import traceback
traceback.print_exc() | 42.493671 | 117 | 0.739053 |
b7925483ba95f2bb530529066114343ba1164af4 | 1,567 | py | Python | src/pyforest/auto_import.py | tnwei/pyforest | 73b36298e8cbce9a861c13c01509e34f0e3397fe | [
"MIT"
] | 1,002 | 2019-08-13T15:00:39.000Z | 2022-03-29T19:14:41.000Z | src/pyforest/auto_import.py | tnwei/pyforest | 73b36298e8cbce9a861c13c01509e34f0e3397fe | [
"MIT"
] | 40 | 2019-08-13T19:17:49.000Z | 2022-02-14T08:46:09.000Z | src/pyforest/auto_import.py | tnwei/pyforest | 73b36298e8cbce9a861c13c01509e34f0e3397fe | [
"MIT"
] | 202 | 2019-08-13T19:37:25.000Z | 2022-03-21T20:05:27.000Z | from pathlib import Path
IPYTHON_STARTUP_FOLDER = Path.home() / ".ipython" / "profile_default" / "startup"
STARTUP_FILE = IPYTHON_STARTUP_FOLDER / "pyforest_autoimport.py"
| 31.34 | 137 | 0.699426 |
b7936727533c1b6e64a5988a2f89fc499bcee832 | 23,430 | py | Python | tests/torch/pruning/test_model_pruning_analysis.py | sarthakpati/nncf | 29ad62c664c1dd53b3c8c50fc001a1b36bd1e8ac | [
"Apache-2.0"
] | null | null | null | tests/torch/pruning/test_model_pruning_analysis.py | sarthakpati/nncf | 29ad62c664c1dd53b3c8c50fc001a1b36bd1e8ac | [
"Apache-2.0"
] | 1 | 2021-07-23T07:46:52.000Z | 2021-07-23T07:46:52.000Z | tests/torch/pruning/test_model_pruning_analysis.py | sarthakpati/nncf | 29ad62c664c1dd53b3c8c50fc001a1b36bd1e8ac | [
"Apache-2.0"
] | null | null | null | """
Copyright (c) 2020 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from typing import Callable
from typing import Dict
from typing import List
from typing import Tuple
from typing import Type
import pytest
import torch
from torch import nn
from nncf.common.graph import NNCFNodeName
from nncf.common.pruning.clusterization import Cluster
from nncf.common.pruning.clusterization import Clusterization
from nncf.common.pruning.model_analysis import ModelAnalyzer
from nncf.common.pruning.model_analysis import cluster_special_ops
from nncf.torch.dynamic_graph.graph_tracer import ModelInputInfo
from nncf.torch.layers import NNCF_PRUNING_MODULES_DICT
from nncf.torch.nncf_network import NNCFNetwork
from nncf.torch.pruning.export_helpers import PTElementwise
from nncf.torch.pruning.export_helpers import PTIdentityMaskForwardOps
from nncf.torch.pruning.export_helpers import PT_PRUNING_OPERATOR_METATYPES
from nncf.common.pruning.utils import is_depthwise_conv
from nncf.torch.pruning.filter_pruning.algo import FilterPruningBuilder
from tests.torch.helpers import create_compressed_model_and_algo_for_test
from tests.torch.helpers import create_nncf_model_and_single_algo_builder
from tests.torch.pruning.helpers import PruningTestModelEltwise
from tests.torch.pruning.helpers import PruningTestModelSharedConvs
from tests.torch.pruning.helpers import TestModelBranching
from tests.torch.pruning.helpers import TestModelDiffConvs
from tests.torch.pruning.helpers import TestModelEltwiseCombination
from tests.torch.pruning.helpers import TestModelResidualConnection
from tests.torch.pruning.helpers import TestModelShuffleNetUnit
from tests.torch.pruning.helpers import TestModelShuffleNetUnitDW
from tests.torch.pruning.helpers import get_basic_pruning_config
# pylint: disable=protected-access
GROUP_PRUNING_MODULES_TEST_CASES = [
GroupPruningModulesTestStruct(model=PruningTestModelEltwise,
non_pruned_module_nodes=['PruningTestModelEltwise/NNCFConv2d[conv1]/conv2d_0',
'PruningTestModelEltwise/NNCFConv2d[conv4]/conv2d_0'],
pruned_groups=[['PruningTestModelEltwise/NNCFConv2d[conv2]/conv2d_0',
'PruningTestModelEltwise/NNCFConv2d[conv3]/conv2d_0']],
pruned_groups_by_node_id=[[3, 4]],
prune_params=(False, False, False)),
GroupPruningModulesTestStruct(model=PruningTestModelEltwise,
non_pruned_module_nodes=[],
pruned_groups=[['PruningTestModelEltwise/NNCFConv2d[conv1]/conv2d_0'],
['PruningTestModelEltwise/NNCFConv2d[conv4]/conv2d_0'],
['PruningTestModelEltwise/NNCFConv2d[conv2]/conv2d_0',
'PruningTestModelEltwise/NNCFConv2d[conv3]/conv2d_0']],
pruned_groups_by_node_id=[[1], [7], [3, 4]],
prune_params=(True, True, False)),
GroupPruningModulesTestStruct(model=TestModelBranching,
non_pruned_module_nodes=[],
pruned_groups=[['TestModelBranching/NNCFConv2d[conv1]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv2]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv3]/conv2d_0']],
pruned_groups_by_node_id=[[1, 2, 4]],
prune_params=(True, True, False)),
GroupPruningModulesTestStruct(model=TestModelBranching,
non_pruned_module_nodes=['TestModelBranching/NNCFConv2d[conv1]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv2]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv3]/conv2d_0'],
pruned_groups=[['TestModelBranching/NNCFConv2d[conv4]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv5]/conv2d_0']],
pruned_groups_by_node_id=[[7, 8]],
prune_params=(False, True, False)),
GroupPruningModulesTestStruct(model=TestModelBranching,
non_pruned_module_nodes=['TestModelBranching/NNCFConv2d[conv4]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv5]/conv2d_0'],
pruned_groups=[['TestModelBranching/NNCFConv2d[conv1]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv2]/conv2d_0',
'TestModelBranching/NNCFConv2d[conv3]/conv2d_0']],
pruned_groups_by_node_id=[[1, 2, 4]],
prune_params=(True, False, False)),
GroupPruningModulesTestStruct(model=TestModelResidualConnection,
non_pruned_module_nodes=['TestModelResidualConnection/NNCFConv2d[conv4]/conv2d_0',
'TestModelResidualConnection/NNCFConv2d[conv5]/conv2d_0'],
pruned_groups=[['TestModelResidualConnection/NNCFConv2d[conv1]/conv2d_0',
'TestModelResidualConnection/NNCFConv2d[conv2]/conv2d_0',
'TestModelResidualConnection/NNCFConv2d[conv3]/conv2d_0']],
pruned_groups_by_node_id=[[1, 2, 4]],
prune_params=(True, True, False)),
GroupPruningModulesTestStruct(model=TestModelEltwiseCombination,
non_pruned_module_nodes=[],
pruned_groups=[['TestModelEltwiseCombination/NNCFConv2d[conv1]/conv2d_0',
'TestModelEltwiseCombination/NNCFConv2d[conv2]/conv2d_0',
'TestModelEltwiseCombination/NNCFConv2d[conv4]/conv2d_0',
'TestModelEltwiseCombination/NNCFConv2d[conv3]/conv2d_0',],
['TestModelEltwiseCombination/NNCFConv2d[conv5]/conv2d_0',
'TestModelEltwiseCombination/NNCFConv2d[conv6]/conv2d_0']],
pruned_groups_by_node_id=[[1, 2, 4, 6], [8, 9]],
prune_params=(True, True, False)),
GroupPruningModulesTestStruct(model=PruningTestModelSharedConvs,
non_pruned_module_nodes=['PruningTestModelSharedConvs/NNCFConv2d[conv1]/conv2d_0',
'PruningTestModelSharedConvs/NNCFConv2d[conv3]/conv2d_0',
'PruningTestModelSharedConvs/NNCFConv2d[conv3]/conv2d_1'],
pruned_groups=[['PruningTestModelSharedConvs/NNCFConv2d[conv2]/conv2d_0',
'PruningTestModelSharedConvs/NNCFConv2d[conv2]/conv2d_1']],
pruned_groups_by_node_id=[[3, 4]],
prune_params=(False, False, False))
]
GROUP_SPECIAL_MODULES_TEST_CASES = [
GroupSpecialModulesTestStruct(
model=TestModelBranching,
eltwise_clusters=[[3, 5], [9]],
),
GroupSpecialModulesTestStruct(
model=TestModelResidualConnection,
eltwise_clusters=[[3, 5], [9]],
),
GroupSpecialModulesTestStruct(
model=TestModelEltwiseCombination,
eltwise_clusters=[[3, 5, 7], [10]]
)
]
MODEL_ANALYSER_TEST_CASES = [
ModelAnalyserTestStruct(
model=TestModelResidualConnection,
ref_can_prune={0: True, 1: True, 2: True, 3: True, 4: True, 5: True, 6: True, 7: False, 8: False, 9: False,
10: False, 11: False, 12: False}
)
]
IS_MODULE_PRUNABLE_TEST_CASES = [
ModulePrunableTestStruct(
model=TestModelDiffConvs,
config_params={},
is_module_prunable={'TestModelDiffConvs/NNCFConv2d[conv1]/conv2d_0': False,
'TestModelDiffConvs/NNCFConv2d[conv2]/conv2d_0': True,
'TestModelDiffConvs/NNCFConv2d[conv3]/conv2d_0': False,
'TestModelDiffConvs/NNCFConv2d[conv4]/conv2d_0': False},
),
ModulePrunableTestStruct(
model=TestModelDiffConvs,
config_params={'prune_first_conv': True, 'prune_last_conv': True},
is_module_prunable={'TestModelDiffConvs/NNCFConv2d[conv1]/conv2d_0': True,
'TestModelDiffConvs/NNCFConv2d[conv2]/conv2d_0': True,
'TestModelDiffConvs/NNCFConv2d[conv3]/conv2d_0': False,
'TestModelDiffConvs/NNCFConv2d[conv4]/conv2d_0': False},
),
ModulePrunableTestStruct(
model=TestModelDiffConvs,
config_params={'prune_first_conv': True, 'prune_last_conv': True, 'prune_downsample_convs': True},
is_module_prunable={'TestModelDiffConvs/NNCFConv2d[conv1]/conv2d_0': True,
'TestModelDiffConvs/NNCFConv2d[conv2]/conv2d_0': True,
'TestModelDiffConvs/NNCFConv2d[conv3]/conv2d_0': True,
'TestModelDiffConvs/NNCFConv2d[conv4]/conv2d_0': False},
),
ModulePrunableTestStruct(
model=TestModelBranching,
config_params={},
is_module_prunable={'TestModelBranching/NNCFConv2d[conv1]/conv2d_0': False,
'TestModelBranching/NNCFConv2d[conv2]/conv2d_0': False,
'TestModelBranching/NNCFConv2d[conv3]/conv2d_0': False,
'TestModelBranching/NNCFConv2d[conv4]/conv2d_0': False,
'TestModelBranching/NNCFConv2d[conv5]/conv2d_0': False},
),
ModulePrunableTestStruct(
model=TestModelBranching,
config_params={'prune_first_conv': True, 'prune_last_conv': True, },
is_module_prunable={'TestModelBranching/NNCFConv2d[conv1]/conv2d_0': True,
'TestModelBranching/NNCFConv2d[conv2]/conv2d_0': True,
'TestModelBranching/NNCFConv2d[conv3]/conv2d_0': True,
'TestModelBranching/NNCFConv2d[conv4]/conv2d_0': True,
'TestModelBranching/NNCFConv2d[conv5]/conv2d_0': True},
),
ModulePrunableTestStruct(
model=TestModelShuffleNetUnitDW,
config_params={'prune_first_conv': True, 'prune_last_conv': True, },
is_module_prunable={
'TestModelShuffleNetUnitDW/NNCFConv2d[conv]/conv2d_0': True,
'TestModelShuffleNetUnitDW/TestShuffleUnit[unit1]/NNCFConv2d[dw_conv4]/conv2d_0': False,
'TestModelShuffleNetUnitDW/TestShuffleUnit[unit1]/NNCFConv2d[expand_conv5]/conv2d_0': True,
'TestModelShuffleNetUnitDW/TestShuffleUnit[unit1]/NNCFConv2d[compress_conv1]/conv2d_0': True,
'TestModelShuffleNetUnitDW/TestShuffleUnit[unit1]/NNCFConv2d[dw_conv2]/conv2d_0': False,
'TestModelShuffleNetUnitDW/TestShuffleUnit[unit1]/NNCFConv2d[expand_conv3]/conv2d_0': True},
),
ModulePrunableTestStruct(
model=TestModelShuffleNetUnit,
config_params={'prune_first_conv': True, 'prune_last_conv': True, },
is_module_prunable={'TestModelShuffleNetUnit/NNCFConv2d[conv]/conv2d_0': True,
'TestModelShuffleNetUnit/TestShuffleUnit[unit1]/NNCFConv2d[compress_conv1]/conv2d_0': True,
'TestModelShuffleNetUnit/TestShuffleUnit[unit1]/NNCFConv2d[dw_conv2]/conv2d_0': True,
'TestModelShuffleNetUnit/TestShuffleUnit[unit1]/NNCFConv2d[expand_conv3]/conv2d_0': True},
)
]
| 51.721854 | 119 | 0.660606 |
b7937e5f465626651bc0a037a47d5bc1cfd62cdf | 261 | py | Python | tests/future_division_eval.py | mayl8822/onelinerizer | bad341f261d35e56872b4c22297a44dc6d5cfab3 | [
"MIT"
] | 1,062 | 2015-11-18T01:04:33.000Z | 2022-03-29T07:13:30.000Z | tests/future_division_eval.py | CoDeRgAnEsh/1line | 507ef35b0006fc2998463dee92c2fdae53fe0694 | [
"MIT"
] | 26 | 2015-11-17T06:58:07.000Z | 2022-01-15T18:11:16.000Z | tests/future_division_eval.py | CoDeRgAnEsh/1line | 507ef35b0006fc2998463dee92c2fdae53fe0694 | [
"MIT"
] | 100 | 2015-11-17T09:01:22.000Z | 2021-09-12T13:58:28.000Z | from __future__ import division
print eval('1/2')
exec('print 1/2')
eval(compile('print 1/2', 'wat.py', 'exec'))
print eval(compile('1/2', 'wat.py', 'eval'))
print eval(compile('1/2', 'wat.py', 'eval', 0, 0))
print eval(compile('1/2', 'wat.py', 'eval', 0, ~0))
| 32.625 | 51 | 0.62069 |
b7939b77631def2ec27e1370419a519e33e2db7a | 180 | py | Python | matchms/similarity/spec2vec/__init__.py | fossabot/matchms | 090db31b22829dc224e5ed78fb4901e8c14a8e92 | [
"Apache-2.0"
] | null | null | null | matchms/similarity/spec2vec/__init__.py | fossabot/matchms | 090db31b22829dc224e5ed78fb4901e8c14a8e92 | [
"Apache-2.0"
] | null | null | null | matchms/similarity/spec2vec/__init__.py | fossabot/matchms | 090db31b22829dc224e5ed78fb4901e8c14a8e92 | [
"Apache-2.0"
] | null | null | null | from .Document import Document
from .SpectrumDocument import SpectrumDocument
from .Spec2Vec import Spec2Vec
__all__ = [
"Document",
"SpectrumDocument",
"Spec2Vec"
]
| 16.363636 | 46 | 0.738889 |
b794d1e8ea63cc3bf3146f5e45ab36528d92826b | 22,826 | py | Python | cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_wanphy_ui_oper.py | tkamata-test/ydk-py | b637e7853a8edbbd31fbc05afa3aa4110b31c5f9 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_wanphy_ui_oper.py | tkamata-test/ydk-py | b637e7853a8edbbd31fbc05afa3aa4110b31c5f9 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | cisco-ios-xr/ydk/models/cisco_ios_xr/Cisco_IOS_XR_wanphy_ui_oper.py | tkamata-test/ydk-py | b637e7853a8edbbd31fbc05afa3aa4110b31c5f9 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | """ Cisco_IOS_XR_wanphy_ui_oper
This module contains a collection of YANG definitions
for Cisco IOS\-XR wanphy\-ui package operational data.
This module contains definitions
for the following management objects\:
wanphy\: WANPHY operational data
Copyright (c) 2013\-2016 by Cisco Systems, Inc.
All rights reserved.
"""
import re
import collections
from enum import Enum
from ydk.types import Empty, YList, YLeafList, DELETE, Decimal64, FixedBitsDict
from ydk.errors import YPYError, YPYModelError
| 30.434667 | 293 | 0.423596 |
b79500b1906f3f8e77f736bcb5d3e403aa5d9a7d | 773 | py | Python | test/unit/solver/test_lamb.py | megvii-research/basecls | 6b395a0a888370b4523764afb78a5a7634a3f6cd | [
"Apache-2.0"
] | 23 | 2021-12-08T02:35:01.000Z | 2022-03-16T02:23:19.000Z | test/unit/solver/test_lamb.py | megvii-research/basecls | 6b395a0a888370b4523764afb78a5a7634a3f6cd | [
"Apache-2.0"
] | 4 | 2021-12-23T11:31:17.000Z | 2022-02-28T01:35:31.000Z | test/unit/solver/test_lamb.py | megvii-research/basecls | 6b395a0a888370b4523764afb78a5a7634a3f6cd | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python3
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
import megengine as mge
import numpy as np
import pytest
from megengine.autodiff import GradManager
from basecls.solver.optimizer import LAMB
| 26.655172 | 67 | 0.633894 |
b7961cc47beaac8f9cce44564f475f951b32b24b | 2,180 | py | Python | onenote-dump/__main__.py | genericmoniker/onenote-dump | 78b2ee2dcf854f6bc989d3081f42c97f245e49cc | [
"MIT"
] | 39 | 2019-07-17T06:08:56.000Z | 2022-03-22T09:48:58.000Z | onenote-dump/__main__.py | nicknickel/onenote-dump | 84607f89f8c14c51796ab660dc0e741af3ccf55c | [
"MIT"
] | 5 | 2020-07-02T02:44:38.000Z | 2021-11-11T18:16:13.000Z | onenote-dump/__main__.py | nicknickel/onenote-dump | 84607f89f8c14c51796ab660dc0e741af3ccf55c | [
"MIT"
] | 6 | 2020-11-01T12:46:56.000Z | 2022-01-12T22:24:50.000Z | import argparse
import logging
import os
import pathlib
import time
import log
import onenote_auth
import onenote
import pipeline
logger = logging.getLogger()
main()
| 27.25 | 76 | 0.624771 |
b7971aac602f7d60f9d06ecc4d523b5988cef546 | 10,391 | py | Python | venv/lib/python3.8/site-packages/ansible_collections/community/aws/tests/unit/plugins/modules/test_data_pipeline.py | saeedya/docker-ansible | 6fb0cfc6bc4a5925b21380952a5a4502ec02119a | [
"Apache-2.0"
] | 7 | 2021-11-16T04:05:42.000Z | 2022-02-19T21:14:29.000Z | venv/lib/python3.8/site-packages/ansible_collections/community/aws/tests/unit/plugins/modules/test_data_pipeline.py | saeedya/docker-ansible | 6fb0cfc6bc4a5925b21380952a5a4502ec02119a | [
"Apache-2.0"
] | 1 | 2022-03-12T02:25:26.000Z | 2022-03-12T02:25:26.000Z | venv/lib/python3.8/site-packages/ansible_collections/community/aws/tests/unit/plugins/modules/test_data_pipeline.py | saeedya/docker-ansible | 6fb0cfc6bc4a5925b21380952a5a4502ec02119a | [
"Apache-2.0"
] | 1 | 2022-03-01T05:43:07.000Z | 2022-03-01T05:43:07.000Z | # (c) 2017 Red Hat Inc.
#
# This file is part of Ansible
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
# Make coding more python3-ish
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import collections
import os
import json
import pytest
from ansible.module_utils._text import to_text
# Magic... Incorrectly identified by pylint as unused
from ansible_collections.amazon.aws.tests.unit.utils.amazon_placebo_fixtures import maybe_sleep # pylint: disable=unused-import
from ansible_collections.amazon.aws.tests.unit.utils.amazon_placebo_fixtures import placeboify # pylint: disable=unused-import
from ansible_collections.community.aws.plugins.modules import data_pipeline
# test_api_gateway.py requires the `boto3` and `botocore` modules
boto3 = pytest.importorskip('boto3')
def test_create_pipeline_already_exists(placeboify, maybe_sleep, dp_setup):
connection = placeboify.client('datapipeline')
changed, result = data_pipeline.create_pipeline(connection, dp_setup.module)
assert changed is False
assert "Data Pipeline ansible-test-create-pipeline is present" in result['msg']
def test_pipeline_field(placeboify, maybe_sleep, dp_setup):
connection = placeboify.client('datapipeline')
pipeline_field_info = data_pipeline.pipeline_field(connection, dp_setup.data_pipeline_id, "@pipelineState")
assert pipeline_field_info == "PENDING"
def test_define_pipeline(placeboify, maybe_sleep, dp_setup):
connection = placeboify.client('datapipeline')
changed, result = data_pipeline.define_pipeline(connection, dp_setup.module, dp_setup.objects, dp_setup.data_pipeline_id)
assert 'has been updated' in result
def test_deactivate_pipeline(placeboify, maybe_sleep, dp_setup):
connection = placeboify.client('datapipeline')
changed, result = data_pipeline.deactivate_pipeline(connection, dp_setup.module)
assert "Data Pipeline ansible-test-create-pipeline deactivated" in result['msg']
def test_activate_without_population(placeboify, maybe_sleep, dp_setup):
connection = placeboify.client('datapipeline')
with pytest.raises(Exception) as error_message:
changed, result = data_pipeline.activate_pipeline(connection, dp_setup.module)
assert error_message == "You need to populate your pipeline before activation."
def test_create_pipeline(placeboify, maybe_sleep):
connection = placeboify.client('datapipeline')
params = {'name': 'ansible-unittest-create-pipeline',
'description': 'ansible-datapipeline-unit-test',
'state': 'present',
'timeout': 300,
'tags': {}}
m = FakeModule(**params)
changed, result = data_pipeline.create_pipeline(connection, m)
assert changed is True
assert result['msg'] == "Data Pipeline ansible-unittest-create-pipeline created."
data_pipeline.delete_pipeline(connection, m)
def test_create_pipeline_with_tags(placeboify, maybe_sleep):
connection = placeboify.client('datapipeline')
params = {'name': 'ansible-unittest-create-pipeline_tags',
'description': 'ansible-datapipeline-unit-test',
'state': 'present',
'tags': {'ansible': 'test'},
'timeout': 300}
m = FakeModule(**params)
changed, result = data_pipeline.create_pipeline(connection, m)
assert changed is True
assert result['msg'] == "Data Pipeline ansible-unittest-create-pipeline_tags created."
data_pipeline.delete_pipeline(connection, m)
def test_delete_nonexistent_pipeline(placeboify, maybe_sleep):
connection = placeboify.client('datapipeline')
params = {'name': 'ansible-test-nonexistent',
'description': 'ansible-test-nonexistent',
'state': 'absent',
'objects': [],
'tags': {'ansible': 'test'},
'timeout': 300}
m = FakeModule(**params)
changed, result = data_pipeline.delete_pipeline(connection, m)
assert changed is False
def test_delete_pipeline(placeboify, maybe_sleep):
connection = placeboify.client('datapipeline')
params = {'name': 'ansible-test-nonexistent',
'description': 'ansible-test-nonexistent',
'state': 'absent',
'objects': [],
'tags': {'ansible': 'test'},
'timeout': 300}
m = FakeModule(**params)
data_pipeline.create_pipeline(connection, m)
changed, result = data_pipeline.delete_pipeline(connection, m)
assert changed is True
def test_build_unique_id_different():
m = FakeModule(**{'name': 'ansible-unittest-1', 'description': 'test-unique-id'})
m2 = FakeModule(**{'name': 'ansible-unittest-1', 'description': 'test-unique-id-different'})
assert data_pipeline.build_unique_id(m) != data_pipeline.build_unique_id(m2)
def test_build_unique_id_same():
m = FakeModule(**{'name': 'ansible-unittest-1', 'description': 'test-unique-id', 'tags': {'ansible': 'test'}})
m2 = FakeModule(**{'name': 'ansible-unittest-1', 'description': 'test-unique-id', 'tags': {'ansible': 'test'}})
assert data_pipeline.build_unique_id(m) == data_pipeline.build_unique_id(m2)
def test_build_unique_id_obj():
# check that the object can be different and the unique id should be the same; should be able to modify objects
m = FakeModule(**{'name': 'ansible-unittest-1', 'objects': [{'first': 'object'}]})
m2 = FakeModule(**{'name': 'ansible-unittest-1', 'objects': [{'second': 'object'}]})
assert data_pipeline.build_unique_id(m) == data_pipeline.build_unique_id(m2)
def test_format_tags():
unformatted_tags = {'key1': 'val1', 'key2': 'val2', 'key3': 'val3'}
formatted_tags = data_pipeline.format_tags(unformatted_tags)
for tag_set in formatted_tags:
assert unformatted_tags[tag_set['key']] == tag_set['value']
| 40.909449 | 128 | 0.698008 |
b7977b33c0e4a7ba789fa84d50fd2df4ed4339db | 3,433 | py | Python | Janela/Cadastro_clientes/Clientes.py | marcosj046/Treinando-Python-Tkinter | 7b88a6b6afba46e6c013b65b952723047c173901 | [
"MIT"
] | null | null | null | Janela/Cadastro_clientes/Clientes.py | marcosj046/Treinando-Python-Tkinter | 7b88a6b6afba46e6c013b65b952723047c173901 | [
"MIT"
] | null | null | null | Janela/Cadastro_clientes/Clientes.py | marcosj046/Treinando-Python-Tkinter | 7b88a6b6afba46e6c013b65b952723047c173901 | [
"MIT"
] | null | null | null | import sqlite3
import tkinter as tk
import pandas as pd
#----------------------------------------------
#Para criao do banco de dados retira o comentrio (#) da linha 9 23 somente a primeira vez que rodar o cd,
#depois, basta comentar novamente.
#Criando o Banco de Dados
# conexao = sqlite3.connect('Clientes.db')
#
# c = conexao.cursor()
#
# c.execute(''' CREATE TABLE clientes (
# Nome text,
# Sobrenome text,
# Email text,
# Telefone text
# )
# ''')
#
# conexao.commit()
# conexao.close()
#-----------------------------------------------
#Criando as funes
#Criando a funo para exportar as informaes do banco em formato xlxs
#-----------------------------------------------
janela = tk.Tk() #estartando a janela
janela.title("Cadastro de Clientes") #Inserindo um ttulo na janela
#Criando as Labels:
label_nome = tk.Label(janela, text="Nome")
label_nome.grid(row=0, column=0, padx=10, pady=10)
label_sobrenome = tk.Label(janela, text="Sobrenome")
label_sobrenome.grid(row=1, column=0, padx=10, pady=10)
label_email = tk.Label(janela, text="Email")
label_email.grid(row=2, column=0, padx=10, pady=10)
label_telefone = tk.Label(janela, text="Telefone")
label_telefone.grid(row=3, column=0, padx=10, pady=10)
#-------------------------------------------------------
#Entrys
entry_nome = tk.Entry(janela, text="Nome", width=30)
entry_nome.grid(row=0, column=2, padx=10, pady=10)
entry_sobrenome = tk.Entry(janela, text="Sobrenome", width=30)
entry_sobrenome.grid(row=1, column=2, padx=10, pady=10)
entry_email = tk.Entry(janela, text="Email", width=30)
entry_email.grid(row=2, column=2, padx=10, pady=10)
entry_telefone = tk.Entry(janela, text="Telefone", width=30)
entry_telefone.grid(row=3, column=2, padx=10, pady=10)
#Botes
botao_Cadastrar = tk.Button(janela, text="Cadastrar Cliente", command = cadastrar_cliente)
botao_Cadastrar.grid(row=4, column=0, padx=10, pady=10, columnspan=2, ipadx=80)
botao_exportar = tk.Button(janela, text="Exportar Cliente", command = exportar_cliente)
botao_exportar.grid(row=4, column=2, padx=10, pady=10, columnspan=2, ipadx=80)
#Obs: ipadx=80 - Basicamente serve para alargar uma estrutura especifca
janela.mainloop() | 33.990099 | 171 | 0.669677 |
b79823a97f320a9bd4990bfd614e964f079da76e | 14,382 | py | Python | pygitbucket/client.py | SimiCode/pygitbucket | 46a22fcc0292231905eb4e0e2da47f8a85743bbd | [
"MIT"
] | 1 | 2021-07-04T19:45:05.000Z | 2021-07-04T19:45:05.000Z | pygitbucket/client.py | SimiCode/pygitbucket | 46a22fcc0292231905eb4e0e2da47f8a85743bbd | [
"MIT"
] | null | null | null | pygitbucket/client.py | SimiCode/pygitbucket | 46a22fcc0292231905eb4e0e2da47f8a85743bbd | [
"MIT"
] | null | null | null | import math
import requests
from pygitbucket.exceptions import (
UnknownError,
InvalidIDError,
NotFoundIDError,
NotAuthenticatedError,
PermissionError,
)
| 28.821643 | 117 | 0.578779 |
b79836d2b12f5a44dd3688e75af8cc0da3616913 | 3,982 | py | Python | egg/zoo/basic_games/data_readers.py | renata-nerenata/EGG | b8532efc3569defabeba6851986cecb0c6640984 | [
"MIT"
] | 1 | 2021-05-26T14:23:25.000Z | 2021-05-26T14:23:25.000Z | egg/zoo/basic_games/data_readers.py | renata-nerenata/EGG | b8532efc3569defabeba6851986cecb0c6640984 | [
"MIT"
] | 1 | 2019-10-31T16:21:01.000Z | 2019-10-31T16:21:01.000Z | egg/zoo/basic_games/data_readers.py | renata-nerenata/EGG | b8532efc3569defabeba6851986cecb0c6640984 | [
"MIT"
] | null | null | null | # Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch.utils.data import Dataset
import numpy as np
# These input-data-processing classes take input data from a text file and convert them to the format
# appropriate for the recognition and discrimination games, so that they can be read by
# the standard pytorch DataLoader. The latter requires the data reading classes to support
# a __len__(self) method, returning the size of the dataset, and a __getitem__(self, idx)
# method, returning the idx-th item in the dataset. We also provide a get_n_features(self) method,
# returning the dimensionality of the Sender input vector after it is transformed to one-hot format.
# The AttValRecoDataset class is used in the reconstruction game. It takes an input file with a
# space-delimited attribute-value vector per line and creates a data-frame with the two mandatory
# fields expected in EGG games, namely sender_input and labels.
# In this case, the two fields contain the same information, namely the input attribute-value vectors,
# represented as one-hot in sender_input, and in the original integer-based format in
# labels.
# The AttValDiscriDataset class, used in the discrimination game takes an input file with a variable
# number of period-delimited fields, where all fields but the last represent attribute-value vectors
# (with space-delimited attributes). The last field contains the index (counting from 0) of the target
# vector.
# Here, we create a data-frame containing 3 fields: sender_input, labels and receiver_input (these are
# expected by EGG, the first two mandatorily so).
# The sender_input corresponds to the target vector (in one-hot format), labels are the indices of the
# target vector location and receiver_input is a matrix with a row for each input vector (in input order).
| 45.770115 | 106 | 0.678805 |
b798b33e304086ef9c7efe2c716e2e87dfcb993a | 3,594 | py | Python | viroconcom/read_write.py | adrdrew/viroconcom | 3eb748ba8e3e076eddd174a0fcdfee3917aa4045 | [
"MIT"
] | null | null | null | viroconcom/read_write.py | adrdrew/viroconcom | 3eb748ba8e3e076eddd174a0fcdfee3917aa4045 | [
"MIT"
] | 1 | 2020-05-18T11:06:28.000Z | 2020-05-18T11:06:28.000Z | viroconcom/read_write.py | adrdrew/viroconcom | 3eb748ba8e3e076eddd174a0fcdfee3917aa4045 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Reads datasets, reads and writes contour coordinates.
"""
import numpy as np
import csv
def read_ecbenchmark_dataset(path='datasets/1year_dataset_A.txt'):
"""
Reads a 2D dataset that uses a an ASCI format with ';' as a seperator.
This format has been used in the EC benchmark,
see https://github.com/ec-benchmark-organizers/ec-benchmark .
Parameters
----------
path : string
Path to dataset including the file name, defaults
to '../datasets/1year_dataset_A.txt'
Returns
-------
x : ndarray of doubles
Observations of the environmental variable 1.
y : ndarray of doubles
Observations of the environmental variable 2.
x_label : str
Label of the environmantal variable 1.
y_label : str
Label of the environmental variable 2.
"""
x = list()
y = list()
x_label = None
y_label = None
with open(path, newline='') as csv_file:
reader = csv.reader(csv_file, delimiter=';')
idx = 0
for row in reader:
if idx == 0:
x_label = row[1][1:] # Ignore first char (is a white space).
y_label = row[2][1:] # Ignore first char (is a white space).
if idx > 0: # Ignore the header
x.append(float(row[1]))
y.append(float(row[2]))
idx = idx + 1
x = np.asarray(x)
y = np.asarray(y)
return (x, y, x_label, y_label)
def write_contour(x, y, path, label_x='Variable x (unit)',
label_y='Variable y (unit)'):
"""
Writes 2D contour coordinates in an ASCI format with ';' as a seperator.
Parameters
----------
x : ndarray of doubles
Values in the first dimensions of the contour's coordinates.
y : ndarray of doubles
Values in the second dimensions of the contour's coordinates.
path : string
Path including folder and file name where the contour should be saved.
label_x : str
Name and unit of the first environmental variable,
defaults to 'Variable x (unit), could be, for exmaple,
'Significant wave height (m)'.
label_y : str
Name and unit of the second environmental variable,
defaults to 'Variable y (unit)', could be, for example,
'Zero-up-crossing period (s)'.
"""
with open(path, mode='w', newline='') as contour_file:
contour_writer = csv.writer(contour_file, delimiter=';', quotechar='"', quoting=csv.QUOTE_MINIMAL)
contour_writer.writerow([label_x, label_y])
for xi,yi in zip(x,y):
contour_writer.writerow([str(xi), str(yi)])
def read_contour(path):
"""
Reads 2D contour coordinates in an ASCI format with ';' as a seperator.
Parameters
----------
path : string
Path to contour including the file name.
Returns
-------
x : ndarray of doubles
Observations of the environmental variable 1.
y : ndarray of doubles
Observations of the environmental variable 2.
"""
x = list()
y = list()
with open(path, newline='') as csv_file:
reader = csv.reader(csv_file, delimiter=';')
idx = 0
for row in reader:
if idx > 0: # Ignore the header
x.append(float(row[0]))
y.append(float(row[1]))
idx = idx + 1
x = np.asarray(x)
y = np.asarray(y)
return (x, y)
| 31.526316 | 107 | 0.574012 |
b798e6d01b3ed050802b1fbfc6ef1f267c2dd36a | 601 | py | Python | check_python_install/check_numba.py | sdpython/_check_python_install | 06a34e3b8559370c8c41b655ed2acc72c7f1bf34 | [
"MIT"
] | null | null | null | check_python_install/check_numba.py | sdpython/_check_python_install | 06a34e3b8559370c8c41b655ed2acc72c7f1bf34 | [
"MIT"
] | 2 | 2019-11-07T18:11:18.000Z | 2021-01-02T11:49:38.000Z | check_python_install/check_numba.py | sdpython/_check_python_install | 06a34e3b8559370c8c41b655ed2acc72c7f1bf34 | [
"MIT"
] | null | null | null | """
@file
@brief Test for :epkg:`cartopy`.
"""
import numpy
import numba
def check_numba():
"""
Runs a sample with :epkg:`numba`.
"""
Y = numpy.random.rand(10).astype(numpy.double)
X = numpy.random.rand(10, 2).astype(numpy.double)
w = numpy.random.rand(2).astype(numpy.double)
return logistic_regression(Y, X, w, 2)
| 24.04 | 86 | 0.62396 |
b799cded976768ac0fb3f24b3d043843412ec29f | 4,056 | py | Python | Round 3/fence_design.py | e-ntro-py/GoogleCodeJam-2021 | c42283480fa20a853c6d31d5faf0e83c6ad0f5f7 | [
"MIT"
] | 30 | 2021-03-27T20:18:15.000Z | 2022-03-19T06:18:58.000Z | Round 3/fence_design.py | e-ntro-py/GoogleCodeJam-2021 | c42283480fa20a853c6d31d5faf0e83c6ad0f5f7 | [
"MIT"
] | 1 | 2021-05-24T19:14:29.000Z | 2021-05-25T04:14:10.000Z | Round 3/fence_design.py | e-ntro-py/GoogleCodeJam-2021 | c42283480fa20a853c6d31d5faf0e83c6ad0f5f7 | [
"MIT"
] | 7 | 2021-03-28T12:38:55.000Z | 2021-09-19T15:30:39.000Z | # Copyright (c) 2021 kamyu. All rights reserved.
#
# Google Code Jam 2021 Round 3 - Problem C. Fence Design
# https://codingcompetitions.withgoogle.com/codejam/round/0000000000436142/0000000000813bc7
#
# Time: O(NlogN) on average, pass in PyPy2 but Python2
# Space: O(N)
#
from random import seed, randint
# Compute the cross product of vectors AB and AC
CW, COLLINEAR, CCW = range(-1, 2)
seed(0)
for case in xrange(input()):
print 'Case #%d: %s' % (case+1, fence_design())
| 38.264151 | 115 | 0.554487 |
b79b05e86bdffa34c0cb47c7868d179ea550149c | 50,505 | py | Python | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/pygsl/_block.py | poojavade/Genomics_Docker | 829b5094bba18bbe03ae97daf925fee40a8476e8 | [
"Apache-2.0"
] | 1 | 2019-07-29T02:53:51.000Z | 2019-07-29T02:53:51.000Z | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/pygsl/_block.py | poojavade/Genomics_Docker | 829b5094bba18bbe03ae97daf925fee40a8476e8 | [
"Apache-2.0"
] | 1 | 2021-09-11T14:30:32.000Z | 2021-09-11T14:30:32.000Z | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/pygsl/_block.py | poojavade/Genomics_Docker | 829b5094bba18bbe03ae97daf925fee40a8476e8 | [
"Apache-2.0"
] | 2 | 2016-12-19T02:27:46.000Z | 2019-07-29T02:53:54.000Z | # This file was automatically generated by SWIG (http://www.swig.org).
# Version 2.0.11
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info
if version_info >= (2,6,0):
__block = swig_import_helper()
del swig_import_helper
else:
import __block
del version_info
try:
_swig_property = property
except NameError:
pass # Python < 2.2 doesn't have 'property'.
try:
_object = object
_newclass = 1
except AttributeError:
_newclass = 0
gsl_vector_set_zero = __block.gsl_vector_set_zero
gsl_vector_set_all = __block.gsl_vector_set_all
gsl_vector_set_basis = __block.gsl_vector_set_basis
gsl_vector_fread = __block.gsl_vector_fread
gsl_vector_fwrite = __block.gsl_vector_fwrite
gsl_vector_fscanf = __block.gsl_vector_fscanf
gsl_vector_fprintf = __block.gsl_vector_fprintf
gsl_vector_reverse = __block.gsl_vector_reverse
gsl_vector_swap = __block.gsl_vector_swap
gsl_vector_swap_elements = __block.gsl_vector_swap_elements
gsl_vector_max = __block.gsl_vector_max
gsl_vector_min = __block.gsl_vector_min
gsl_vector_minmax = __block.gsl_vector_minmax
gsl_vector_max_index = __block.gsl_vector_max_index
gsl_vector_min_index = __block.gsl_vector_min_index
gsl_vector_minmax_index = __block.gsl_vector_minmax_index
gsl_vector_isnull = __block.gsl_vector_isnull
gsl_matrix_set_zero = __block.gsl_matrix_set_zero
gsl_matrix_set_all = __block.gsl_matrix_set_all
gsl_matrix_set_identity = __block.gsl_matrix_set_identity
gsl_matrix_fread = __block.gsl_matrix_fread
gsl_matrix_fwrite = __block.gsl_matrix_fwrite
gsl_matrix_fscanf = __block.gsl_matrix_fscanf
gsl_matrix_fprintf = __block.gsl_matrix_fprintf
gsl_matrix_swap = __block.gsl_matrix_swap
gsl_matrix_swap_rows = __block.gsl_matrix_swap_rows
gsl_matrix_swap_columns = __block.gsl_matrix_swap_columns
gsl_matrix_swap_rowcol = __block.gsl_matrix_swap_rowcol
gsl_matrix_transpose = __block.gsl_matrix_transpose
gsl_matrix_max = __block.gsl_matrix_max
gsl_matrix_min = __block.gsl_matrix_min
gsl_matrix_minmax = __block.gsl_matrix_minmax
gsl_matrix_max_index = __block.gsl_matrix_max_index
gsl_matrix_min_index = __block.gsl_matrix_min_index
gsl_matrix_minmax_index = __block.gsl_matrix_minmax_index
gsl_matrix_isnull = __block.gsl_matrix_isnull
gsl_matrix_diagonal = __block.gsl_matrix_diagonal
gsl_matrix_subdiagonal = __block.gsl_matrix_subdiagonal
gsl_matrix_superdiagonal = __block.gsl_matrix_superdiagonal
gsl_vector_float_set_zero = __block.gsl_vector_float_set_zero
gsl_vector_float_set_all = __block.gsl_vector_float_set_all
gsl_vector_float_set_basis = __block.gsl_vector_float_set_basis
gsl_vector_float_fread = __block.gsl_vector_float_fread
gsl_vector_float_fwrite = __block.gsl_vector_float_fwrite
gsl_vector_float_fscanf = __block.gsl_vector_float_fscanf
gsl_vector_float_fprintf = __block.gsl_vector_float_fprintf
gsl_vector_float_reverse = __block.gsl_vector_float_reverse
gsl_vector_float_swap = __block.gsl_vector_float_swap
gsl_vector_float_swap_elements = __block.gsl_vector_float_swap_elements
gsl_vector_float_max = __block.gsl_vector_float_max
gsl_vector_float_min = __block.gsl_vector_float_min
gsl_vector_float_minmax = __block.gsl_vector_float_minmax
gsl_vector_float_max_index = __block.gsl_vector_float_max_index
gsl_vector_float_min_index = __block.gsl_vector_float_min_index
gsl_vector_float_minmax_index = __block.gsl_vector_float_minmax_index
gsl_vector_float_isnull = __block.gsl_vector_float_isnull
gsl_matrix_float_set_zero = __block.gsl_matrix_float_set_zero
gsl_matrix_float_set_all = __block.gsl_matrix_float_set_all
gsl_matrix_float_set_identity = __block.gsl_matrix_float_set_identity
gsl_matrix_float_fread = __block.gsl_matrix_float_fread
gsl_matrix_float_fwrite = __block.gsl_matrix_float_fwrite
gsl_matrix_float_fscanf = __block.gsl_matrix_float_fscanf
gsl_matrix_float_fprintf = __block.gsl_matrix_float_fprintf
gsl_matrix_float_swap = __block.gsl_matrix_float_swap
gsl_matrix_float_swap_rows = __block.gsl_matrix_float_swap_rows
gsl_matrix_float_swap_columns = __block.gsl_matrix_float_swap_columns
gsl_matrix_float_swap_rowcol = __block.gsl_matrix_float_swap_rowcol
gsl_matrix_float_transpose = __block.gsl_matrix_float_transpose
gsl_matrix_float_max = __block.gsl_matrix_float_max
gsl_matrix_float_min = __block.gsl_matrix_float_min
gsl_matrix_float_minmax = __block.gsl_matrix_float_minmax
gsl_matrix_float_max_index = __block.gsl_matrix_float_max_index
gsl_matrix_float_min_index = __block.gsl_matrix_float_min_index
gsl_matrix_float_minmax_index = __block.gsl_matrix_float_minmax_index
gsl_matrix_float_isnull = __block.gsl_matrix_float_isnull
gsl_matrix_float_diagonal = __block.gsl_matrix_float_diagonal
gsl_matrix_float_subdiagonal = __block.gsl_matrix_float_subdiagonal
gsl_matrix_float_superdiagonal = __block.gsl_matrix_float_superdiagonal
gsl_vector_long_set_zero = __block.gsl_vector_long_set_zero
gsl_vector_long_set_all = __block.gsl_vector_long_set_all
gsl_vector_long_set_basis = __block.gsl_vector_long_set_basis
gsl_vector_long_fread = __block.gsl_vector_long_fread
gsl_vector_long_fwrite = __block.gsl_vector_long_fwrite
gsl_vector_long_fscanf = __block.gsl_vector_long_fscanf
gsl_vector_long_fprintf = __block.gsl_vector_long_fprintf
gsl_vector_long_reverse = __block.gsl_vector_long_reverse
gsl_vector_long_swap = __block.gsl_vector_long_swap
gsl_vector_long_swap_elements = __block.gsl_vector_long_swap_elements
gsl_vector_long_max = __block.gsl_vector_long_max
gsl_vector_long_min = __block.gsl_vector_long_min
gsl_vector_long_minmax = __block.gsl_vector_long_minmax
gsl_vector_long_max_index = __block.gsl_vector_long_max_index
gsl_vector_long_min_index = __block.gsl_vector_long_min_index
gsl_vector_long_minmax_index = __block.gsl_vector_long_minmax_index
gsl_vector_long_isnull = __block.gsl_vector_long_isnull
gsl_matrix_long_set_zero = __block.gsl_matrix_long_set_zero
gsl_matrix_long_set_all = __block.gsl_matrix_long_set_all
gsl_matrix_long_set_identity = __block.gsl_matrix_long_set_identity
gsl_matrix_long_fread = __block.gsl_matrix_long_fread
gsl_matrix_long_fwrite = __block.gsl_matrix_long_fwrite
gsl_matrix_long_fscanf = __block.gsl_matrix_long_fscanf
gsl_matrix_long_fprintf = __block.gsl_matrix_long_fprintf
gsl_matrix_long_swap = __block.gsl_matrix_long_swap
gsl_matrix_long_swap_rows = __block.gsl_matrix_long_swap_rows
gsl_matrix_long_swap_columns = __block.gsl_matrix_long_swap_columns
gsl_matrix_long_swap_rowcol = __block.gsl_matrix_long_swap_rowcol
gsl_matrix_long_transpose = __block.gsl_matrix_long_transpose
gsl_matrix_long_max = __block.gsl_matrix_long_max
gsl_matrix_long_min = __block.gsl_matrix_long_min
gsl_matrix_long_minmax = __block.gsl_matrix_long_minmax
gsl_matrix_long_max_index = __block.gsl_matrix_long_max_index
gsl_matrix_long_min_index = __block.gsl_matrix_long_min_index
gsl_matrix_long_minmax_index = __block.gsl_matrix_long_minmax_index
gsl_matrix_long_isnull = __block.gsl_matrix_long_isnull
gsl_matrix_long_diagonal = __block.gsl_matrix_long_diagonal
gsl_matrix_long_subdiagonal = __block.gsl_matrix_long_subdiagonal
gsl_matrix_long_superdiagonal = __block.gsl_matrix_long_superdiagonal
gsl_vector_int_set_zero = __block.gsl_vector_int_set_zero
gsl_vector_int_set_all = __block.gsl_vector_int_set_all
gsl_vector_int_set_basis = __block.gsl_vector_int_set_basis
gsl_vector_int_fread = __block.gsl_vector_int_fread
gsl_vector_int_fwrite = __block.gsl_vector_int_fwrite
gsl_vector_int_fscanf = __block.gsl_vector_int_fscanf
gsl_vector_int_fprintf = __block.gsl_vector_int_fprintf
gsl_vector_int_reverse = __block.gsl_vector_int_reverse
gsl_vector_int_swap = __block.gsl_vector_int_swap
gsl_vector_int_swap_elements = __block.gsl_vector_int_swap_elements
gsl_vector_int_max = __block.gsl_vector_int_max
gsl_vector_int_min = __block.gsl_vector_int_min
gsl_vector_int_minmax = __block.gsl_vector_int_minmax
gsl_vector_int_max_index = __block.gsl_vector_int_max_index
gsl_vector_int_min_index = __block.gsl_vector_int_min_index
gsl_vector_int_minmax_index = __block.gsl_vector_int_minmax_index
gsl_vector_int_isnull = __block.gsl_vector_int_isnull
gsl_matrix_int_set_zero = __block.gsl_matrix_int_set_zero
gsl_matrix_int_set_all = __block.gsl_matrix_int_set_all
gsl_matrix_int_set_identity = __block.gsl_matrix_int_set_identity
gsl_matrix_int_fread = __block.gsl_matrix_int_fread
gsl_matrix_int_fwrite = __block.gsl_matrix_int_fwrite
gsl_matrix_int_fscanf = __block.gsl_matrix_int_fscanf
gsl_matrix_int_fprintf = __block.gsl_matrix_int_fprintf
gsl_matrix_int_swap = __block.gsl_matrix_int_swap
gsl_matrix_int_swap_rows = __block.gsl_matrix_int_swap_rows
gsl_matrix_int_swap_columns = __block.gsl_matrix_int_swap_columns
gsl_matrix_int_swap_rowcol = __block.gsl_matrix_int_swap_rowcol
gsl_matrix_int_transpose = __block.gsl_matrix_int_transpose
gsl_matrix_int_max = __block.gsl_matrix_int_max
gsl_matrix_int_min = __block.gsl_matrix_int_min
gsl_matrix_int_minmax = __block.gsl_matrix_int_minmax
gsl_matrix_int_max_index = __block.gsl_matrix_int_max_index
gsl_matrix_int_min_index = __block.gsl_matrix_int_min_index
gsl_matrix_int_minmax_index = __block.gsl_matrix_int_minmax_index
gsl_matrix_int_isnull = __block.gsl_matrix_int_isnull
gsl_matrix_int_diagonal = __block.gsl_matrix_int_diagonal
gsl_matrix_int_subdiagonal = __block.gsl_matrix_int_subdiagonal
gsl_matrix_int_superdiagonal = __block.gsl_matrix_int_superdiagonal
gsl_vector_short_set_zero = __block.gsl_vector_short_set_zero
gsl_vector_short_set_all = __block.gsl_vector_short_set_all
gsl_vector_short_set_basis = __block.gsl_vector_short_set_basis
gsl_vector_short_fread = __block.gsl_vector_short_fread
gsl_vector_short_fwrite = __block.gsl_vector_short_fwrite
gsl_vector_short_fscanf = __block.gsl_vector_short_fscanf
gsl_vector_short_fprintf = __block.gsl_vector_short_fprintf
gsl_vector_short_reverse = __block.gsl_vector_short_reverse
gsl_vector_short_swap = __block.gsl_vector_short_swap
gsl_vector_short_swap_elements = __block.gsl_vector_short_swap_elements
gsl_vector_short_max = __block.gsl_vector_short_max
gsl_vector_short_min = __block.gsl_vector_short_min
gsl_vector_short_minmax = __block.gsl_vector_short_minmax
gsl_vector_short_max_index = __block.gsl_vector_short_max_index
gsl_vector_short_min_index = __block.gsl_vector_short_min_index
gsl_vector_short_minmax_index = __block.gsl_vector_short_minmax_index
gsl_vector_short_isnull = __block.gsl_vector_short_isnull
gsl_matrix_short_set_zero = __block.gsl_matrix_short_set_zero
gsl_matrix_short_set_all = __block.gsl_matrix_short_set_all
gsl_matrix_short_set_identity = __block.gsl_matrix_short_set_identity
gsl_matrix_short_fread = __block.gsl_matrix_short_fread
gsl_matrix_short_fwrite = __block.gsl_matrix_short_fwrite
gsl_matrix_short_fscanf = __block.gsl_matrix_short_fscanf
gsl_matrix_short_fprintf = __block.gsl_matrix_short_fprintf
gsl_matrix_short_swap = __block.gsl_matrix_short_swap
gsl_matrix_short_swap_rows = __block.gsl_matrix_short_swap_rows
gsl_matrix_short_swap_columns = __block.gsl_matrix_short_swap_columns
gsl_matrix_short_swap_rowcol = __block.gsl_matrix_short_swap_rowcol
gsl_matrix_short_transpose = __block.gsl_matrix_short_transpose
gsl_matrix_short_max = __block.gsl_matrix_short_max
gsl_matrix_short_min = __block.gsl_matrix_short_min
gsl_matrix_short_minmax = __block.gsl_matrix_short_minmax
gsl_matrix_short_max_index = __block.gsl_matrix_short_max_index
gsl_matrix_short_min_index = __block.gsl_matrix_short_min_index
gsl_matrix_short_minmax_index = __block.gsl_matrix_short_minmax_index
gsl_matrix_short_isnull = __block.gsl_matrix_short_isnull
gsl_matrix_short_diagonal = __block.gsl_matrix_short_diagonal
gsl_matrix_short_subdiagonal = __block.gsl_matrix_short_subdiagonal
gsl_matrix_short_superdiagonal = __block.gsl_matrix_short_superdiagonal
gsl_vector_char_set_zero = __block.gsl_vector_char_set_zero
gsl_vector_char_set_all = __block.gsl_vector_char_set_all
gsl_vector_char_set_basis = __block.gsl_vector_char_set_basis
gsl_vector_char_fread = __block.gsl_vector_char_fread
gsl_vector_char_fwrite = __block.gsl_vector_char_fwrite
gsl_vector_char_fscanf = __block.gsl_vector_char_fscanf
gsl_vector_char_fprintf = __block.gsl_vector_char_fprintf
gsl_vector_char_reverse = __block.gsl_vector_char_reverse
gsl_vector_char_swap = __block.gsl_vector_char_swap
gsl_vector_char_swap_elements = __block.gsl_vector_char_swap_elements
gsl_vector_char_max = __block.gsl_vector_char_max
gsl_vector_char_min = __block.gsl_vector_char_min
gsl_vector_char_minmax = __block.gsl_vector_char_minmax
gsl_vector_char_max_index = __block.gsl_vector_char_max_index
gsl_vector_char_min_index = __block.gsl_vector_char_min_index
gsl_vector_char_minmax_index = __block.gsl_vector_char_minmax_index
gsl_vector_char_isnull = __block.gsl_vector_char_isnull
gsl_matrix_char_set_zero = __block.gsl_matrix_char_set_zero
gsl_matrix_char_set_all = __block.gsl_matrix_char_set_all
gsl_matrix_char_set_identity = __block.gsl_matrix_char_set_identity
gsl_matrix_char_fread = __block.gsl_matrix_char_fread
gsl_matrix_char_fwrite = __block.gsl_matrix_char_fwrite
gsl_matrix_char_fscanf = __block.gsl_matrix_char_fscanf
gsl_matrix_char_fprintf = __block.gsl_matrix_char_fprintf
gsl_matrix_char_swap = __block.gsl_matrix_char_swap
gsl_matrix_char_swap_rows = __block.gsl_matrix_char_swap_rows
gsl_matrix_char_swap_columns = __block.gsl_matrix_char_swap_columns
gsl_matrix_char_swap_rowcol = __block.gsl_matrix_char_swap_rowcol
gsl_matrix_char_transpose = __block.gsl_matrix_char_transpose
gsl_matrix_char_max = __block.gsl_matrix_char_max
gsl_matrix_char_min = __block.gsl_matrix_char_min
gsl_matrix_char_minmax = __block.gsl_matrix_char_minmax
gsl_matrix_char_max_index = __block.gsl_matrix_char_max_index
gsl_matrix_char_min_index = __block.gsl_matrix_char_min_index
gsl_matrix_char_minmax_index = __block.gsl_matrix_char_minmax_index
gsl_matrix_char_isnull = __block.gsl_matrix_char_isnull
gsl_matrix_char_diagonal = __block.gsl_matrix_char_diagonal
gsl_matrix_char_subdiagonal = __block.gsl_matrix_char_subdiagonal
gsl_matrix_char_superdiagonal = __block.gsl_matrix_char_superdiagonal
gsl_vector_complex_set_zero = __block.gsl_vector_complex_set_zero
gsl_vector_complex_set_all = __block.gsl_vector_complex_set_all
gsl_vector_complex_set_basis = __block.gsl_vector_complex_set_basis
gsl_vector_complex_fread = __block.gsl_vector_complex_fread
gsl_vector_complex_fwrite = __block.gsl_vector_complex_fwrite
gsl_vector_complex_fscanf = __block.gsl_vector_complex_fscanf
gsl_vector_complex_fprintf = __block.gsl_vector_complex_fprintf
gsl_vector_complex_reverse = __block.gsl_vector_complex_reverse
gsl_vector_complex_swap = __block.gsl_vector_complex_swap
gsl_vector_complex_swap_elements = __block.gsl_vector_complex_swap_elements
gsl_vector_complex_isnull = __block.gsl_vector_complex_isnull
gsl_matrix_complex_set_zero = __block.gsl_matrix_complex_set_zero
gsl_matrix_complex_set_all = __block.gsl_matrix_complex_set_all
gsl_matrix_complex_set_identity = __block.gsl_matrix_complex_set_identity
gsl_matrix_complex_fread = __block.gsl_matrix_complex_fread
gsl_matrix_complex_fwrite = __block.gsl_matrix_complex_fwrite
gsl_matrix_complex_fscanf = __block.gsl_matrix_complex_fscanf
gsl_matrix_complex_fprintf = __block.gsl_matrix_complex_fprintf
gsl_matrix_complex_swap = __block.gsl_matrix_complex_swap
gsl_matrix_complex_swap_rows = __block.gsl_matrix_complex_swap_rows
gsl_matrix_complex_swap_columns = __block.gsl_matrix_complex_swap_columns
gsl_matrix_complex_swap_rowcol = __block.gsl_matrix_complex_swap_rowcol
gsl_matrix_complex_transpose = __block.gsl_matrix_complex_transpose
gsl_matrix_complex_isnull = __block.gsl_matrix_complex_isnull
gsl_matrix_complex_diagonal = __block.gsl_matrix_complex_diagonal
gsl_matrix_complex_subdiagonal = __block.gsl_matrix_complex_subdiagonal
gsl_matrix_complex_superdiagonal = __block.gsl_matrix_complex_superdiagonal
gsl_vector_complex_float_set_zero = __block.gsl_vector_complex_float_set_zero
gsl_vector_complex_float_set_all = __block.gsl_vector_complex_float_set_all
gsl_vector_complex_float_set_basis = __block.gsl_vector_complex_float_set_basis
gsl_vector_complex_float_fread = __block.gsl_vector_complex_float_fread
gsl_vector_complex_float_fwrite = __block.gsl_vector_complex_float_fwrite
gsl_vector_complex_float_fscanf = __block.gsl_vector_complex_float_fscanf
gsl_vector_complex_float_fprintf = __block.gsl_vector_complex_float_fprintf
gsl_vector_complex_float_reverse = __block.gsl_vector_complex_float_reverse
gsl_vector_complex_float_swap = __block.gsl_vector_complex_float_swap
gsl_vector_complex_float_swap_elements = __block.gsl_vector_complex_float_swap_elements
gsl_vector_complex_float_isnull = __block.gsl_vector_complex_float_isnull
gsl_matrix_complex_float_set_zero = __block.gsl_matrix_complex_float_set_zero
gsl_matrix_complex_float_set_all = __block.gsl_matrix_complex_float_set_all
gsl_matrix_complex_float_set_identity = __block.gsl_matrix_complex_float_set_identity
gsl_matrix_complex_float_fread = __block.gsl_matrix_complex_float_fread
gsl_matrix_complex_float_fwrite = __block.gsl_matrix_complex_float_fwrite
gsl_matrix_complex_float_fscanf = __block.gsl_matrix_complex_float_fscanf
gsl_matrix_complex_float_fprintf = __block.gsl_matrix_complex_float_fprintf
gsl_matrix_complex_float_swap = __block.gsl_matrix_complex_float_swap
gsl_matrix_complex_float_swap_rows = __block.gsl_matrix_complex_float_swap_rows
gsl_matrix_complex_float_swap_columns = __block.gsl_matrix_complex_float_swap_columns
gsl_matrix_complex_float_swap_rowcol = __block.gsl_matrix_complex_float_swap_rowcol
gsl_matrix_complex_float_transpose = __block.gsl_matrix_complex_float_transpose
gsl_matrix_complex_float_isnull = __block.gsl_matrix_complex_float_isnull
gsl_matrix_complex_float_diagonal = __block.gsl_matrix_complex_float_diagonal
gsl_matrix_complex_float_subdiagonal = __block.gsl_matrix_complex_float_subdiagonal
gsl_matrix_complex_float_superdiagonal = __block.gsl_matrix_complex_float_superdiagonal
# This file is compatible with both classic and new-style classes.
| 41.161369 | 90 | 0.825542 |
b79b4b3441162b8ce9025428d639fcec36693cf3 | 42 | py | Python | tests/__init__.py | chasefinch/amp-renderer | a226140d8a8a6f8c21c073e394b672cf75c8671e | [
"Apache-2.0"
] | 13 | 2020-08-19T18:37:01.000Z | 2021-12-10T17:33:14.000Z | tests/__init__.py | chasefinch/amp-renderer | a226140d8a8a6f8c21c073e394b672cf75c8671e | [
"Apache-2.0"
] | 5 | 2020-08-24T18:31:12.000Z | 2022-02-07T17:36:59.000Z | tests/__init__.py | chasefinch/amp-renderer | a226140d8a8a6f8c21c073e394b672cf75c8671e | [
"Apache-2.0"
] | null | null | null | """Tests for the AMP Renderer project."""
| 21 | 41 | 0.690476 |
b79c02ce02e6d31db2455c7ba97e981d1dda98d5 | 3,564 | py | Python | sudoku/sudoku.py | Ostap2003/backtracking-team-project | 2a6fb2fc80dcdd286c76dbc3b546baf452098d98 | [
"MIT"
] | null | null | null | sudoku/sudoku.py | Ostap2003/backtracking-team-project | 2a6fb2fc80dcdd286c76dbc3b546baf452098d98 | [
"MIT"
] | null | null | null | sudoku/sudoku.py | Ostap2003/backtracking-team-project | 2a6fb2fc80dcdd286c76dbc3b546baf452098d98 | [
"MIT"
] | null | null | null |
from pprint import pprint
'''The module has class Grid for solving sudoku.
Grid should be given as a list of integers or a path to a file.
'''
# grid = [ [3, 0, 6, 5, 0, 8, 4, 0, 0],
# [5, 2, 0, 0, 0, 0, 0, 0, 0],
# [0, 8, 7, 0, 0, 0, 0, 3, 1],
# [0, 0, 3, 0, 1, 0, 0, 8, 0],
# [9, 0, 0, 8, 6, 3, 0, 0, 5],
# [0, 5, 0, 0, 9, 0, 6, 0, 0],
# [1, 3, 0, 0, 0, 0, 2, 5, 0],
# [0, 0, 0, 0, 0, 0, 0, 7, 4],
# [0, 0, 5, 2, 0, 6, 3, 0, 0] ]
sudoku = Grid('grid_2.txt')
sudoku.solve_sudoku(0, 0)
sudoku.write_to_file()
| 28.741935 | 81 | 0.45679 |
b79f4a64c362393fd37c99b135489a7797ae3252 | 1,421 | py | Python | device_e2e/sync/test_sync_c2d.py | dt-boringtao/azure-iot-sdk-python | 35a09679bdf4d7a727391b265a8f1fbb99a30c45 | [
"MIT"
] | null | null | null | device_e2e/sync/test_sync_c2d.py | dt-boringtao/azure-iot-sdk-python | 35a09679bdf4d7a727391b265a8f1fbb99a30c45 | [
"MIT"
] | null | null | null | device_e2e/sync/test_sync_c2d.py | dt-boringtao/azure-iot-sdk-python | 35a09679bdf4d7a727391b265a8f1fbb99a30c45 | [
"MIT"
] | null | null | null | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
import pytest
import logging
import json
import threading
from utils import get_random_dict
logger = logging.getLogger(__name__)
logger.setLevel(level=logging.INFO)
# TODO: add tests for various application properties
# TODO: is there a way to call send_c2d so it arrives as an object rather than a JSON string?
| 30.891304 | 93 | 0.713582 |
b79f9124d587b0b999491249d4952350ec3b140e | 6,588 | py | Python | addons/mixer/blender_data/tests/test_bpy_blend_diff.py | trisadmeslek/V-Sekai-Blender-tools | 0d8747387c58584b50c69c61ba50a881319114f8 | [
"MIT"
] | null | null | null | addons/mixer/blender_data/tests/test_bpy_blend_diff.py | trisadmeslek/V-Sekai-Blender-tools | 0d8747387c58584b50c69c61ba50a881319114f8 | [
"MIT"
] | null | null | null | addons/mixer/blender_data/tests/test_bpy_blend_diff.py | trisadmeslek/V-Sekai-Blender-tools | 0d8747387c58584b50c69c61ba50a881319114f8 | [
"MIT"
] | null | null | null | # GPLv3 License
#
# Copyright (C) 2020 Ubisoft
#
# 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, see <https://www.gnu.org/licenses/>.
import unittest
from bpy import data as D # noqa
from bpy import types as T # noqa
from mixer.blender_data.bpy_data_proxy import BpyDataProxy
from mixer.blender_data.diff import BpyBlendDiff
from mixer.blender_data.filter import test_properties
| 41.961783 | 120 | 0.622495 |
b7a030be152f3c0e93089efb532b4fde2f3761dd | 17,258 | py | Python | dependencies/svgwrite/examples/ltattrie/tiling_part_5.py | charlesmchen/typefacet | 8c6db26d0c599ece16f3704696811275120a4044 | [
"Apache-2.0"
] | 21 | 2015-01-16T05:10:02.000Z | 2021-06-11T20:48:15.000Z | dependencies/svgwrite/examples/ltattrie/tiling_part_5.py | charlesmchen/typefacet | 8c6db26d0c599ece16f3704696811275120a4044 | [
"Apache-2.0"
] | 1 | 2019-09-09T12:10:27.000Z | 2020-05-22T10:12:14.000Z | dependencies/svgwrite/examples/ltattrie/tiling_part_5.py | charlesmchen/typefacet | 8c6db26d0c599ece16f3704696811275120a4044 | [
"Apache-2.0"
] | 2 | 2015-05-03T04:51:08.000Z | 2018-08-24T08:28:53.000Z | #!/usr/bin/python
# -*- coding: utf-8 -*-
import math, sys
import svgwrite
#
# http://www.w3.org/TR/SVG11/struct.html#UseElement
#
# For more information on tesselation / tiling see http://en.wikipedia.org/wiki/Wallpaper_group
# The organization of these tilings are from the interesting book
# Designing Testellations: The Secrets of Interlocking Patterns by Jinny Beyer.
PROGNAME = sys.argv[0].rstrip('.py')
if __name__ == '__main__':
create_svg(PROGNAME + '.svg')
# vim: expandtab shiftwidth=4 tabstop=8 softtabstop=4 textwidth=99
| 51.825826 | 137 | 0.670877 |
b7a3ac719d785e13f7265ad9a05f4b664dd99826 | 3,685 | py | Python | MIssions_to_Mars/scrape_mars_mission.py | pwickliff1/web-scraping-challenge | 56e2b5e6905c17fce762aeb2ae1ad8cb0f48f8d6 | [
"ADSL"
] | null | null | null | MIssions_to_Mars/scrape_mars_mission.py | pwickliff1/web-scraping-challenge | 56e2b5e6905c17fce762aeb2ae1ad8cb0f48f8d6 | [
"ADSL"
] | null | null | null | MIssions_to_Mars/scrape_mars_mission.py | pwickliff1/web-scraping-challenge | 56e2b5e6905c17fce762aeb2ae1ad8cb0f48f8d6 | [
"ADSL"
] | null | null | null | # Dependencies
from bs4 import BeautifulSoup
import requests
import re
import pandas as pd
| 35.095238 | 172 | 0.686567 |
b7a7160ec0048a1f0be91a335c4abd54fb69fa8b | 10,165 | py | Python | guiapp/meditech_nls_parser/old/meditech_nls_to_xml.py | gcampuzano14/PathISTabs | ae29a0b71647ecb32fc40e234b5c7276ab5333d9 | [
"MIT"
] | 1 | 2017-07-28T14:01:32.000Z | 2017-07-28T14:01:32.000Z | guiapp/meditech_nls_parser/old/meditech_nls_to_xml.py | gcampuzano14/PathISTabs | ae29a0b71647ecb32fc40e234b5c7276ab5333d9 | [
"MIT"
] | null | null | null | guiapp/meditech_nls_parser/old/meditech_nls_to_xml.py | gcampuzano14/PathISTabs | ae29a0b71647ecb32fc40e234b5c7276ab5333d9 | [
"MIT"
] | 1 | 2019-02-14T06:07:24.000Z | 2019-02-14T06:07:24.000Z | #!/usr/bin/env python
import os
import re
import csv
# with open(outxml, "r") as out:
# t = out.read()
# with open(outxml, "w") as out:
# u = t.encode('latin1','xmlcharrefreplace').decode('utf8','xmlcharrefreplace')
# u = u.decode("utf-8").replace(u"\u2022", "*").u.encode("utf-8")
# out.write(u)
fil()
| 50.073892 | 174 | 0.52789 |
b7a7213417448a10f646593e2af28f99d94c2f47 | 3,144 | py | Python | paper_plots/small_vs_large_box.py | finn-dodgson/DeepHalos | 86e0ac6c24ac97a0a2a0a60a7ea3721a04bd050c | [
"MIT"
] | null | null | null | paper_plots/small_vs_large_box.py | finn-dodgson/DeepHalos | 86e0ac6c24ac97a0a2a0a60a7ea3721a04bd050c | [
"MIT"
] | null | null | null | paper_plots/small_vs_large_box.py | finn-dodgson/DeepHalos | 86e0ac6c24ac97a0a2a0a60a7ea3721a04bd050c | [
"MIT"
] | null | null | null | import numpy as np
from plots import plots_for_predictions as pp
from utilss import distinct_colours as dc
import matplotlib.pyplot as plt
c = dc.get_distinct(4)
path = '/Users/luisals/Documents/deep_halos_files/mass_range_13.4/random_20sims_200k/lr5e-5/'
p1 = np.load(path + "seed_20/predicted_sim_6_epoch_09.npy")
t1 = np.load(path + "seed_20/true_sim_6_epoch_09.npy")
p_big = np.load("/Users/luisals/Projects/DLhalos/bigbox/raw/predicted_sim_L200_N1024_genetIC3_epoch_10.npy")
t_big = np.load("/Users/luisals/Projects/DLhalos/bigbox/raw/true_sim_L200_N1024_genetIC3_epoch_10.npy")
path_av = "/Users/luisals/Documents/deep_halos_files/mass_range_13.4/random_20sims_200k/averaged_boxes/log_alpha_-4.3/"
p_av = np.load(path_av + "predicted_sim_6_epoch_32.npy")
t_av = np.load(path_av + "true_sim_6_epoch_32.npy")
p_av_big = np.load("/Users/luisals/Projects/DLhalos/bigbox/avg/predicted_sim_L200_N1024_genetIC3_epoch_18.npy")
t_av_big = np.load("/Users/luisals/Projects/DLhalos/bigbox/avg/true_sim_L200_N1024_genetIC3_epoch_18.npy")
# Raw-density case
f1, a, m = pp.plot_histogram_predictions(p1, t1, radius_bins=False, particle_ids=None, errorbars=False,
label=r"$L_\mathrm{box}=50 \, \mathrm{Mpc} \,/ \,h$", color="C0")
f11, a1, m1 = pp.plot_histogram_predictions(p_big, t_big, radius_bins=False, particle_ids=None, errorbars=False, fig=f1,
axes=a, color="C1", label=r"$L_\mathrm{box}=200 \, \mathrm{Mpc} \,/ \,h$")
a1[0].set_ylabel(r"$n_{\mathrm{particles}}$", fontsize=16)
[a.set_xlabel(r"$\log(M_{\mathrm{predicted}}/M_{\mathrm{true}})$", fontsize=16) for a in a1]
plt.savefig("/Users/lls/Documents/Papers/dlhalos_paper/small_vs_large_box.pdf")
# Averaged-density case
f1, a, m = pp.plot_histogram_predictions(p_av, t_av, radius_bins=False, particle_ids=None, errorbars=False,
label=r"$L_\mathrm{box}=50 \, \mathrm{Mpc} \,/ \,h$", color="C0")
f11, a1, m1 = pp.plot_histogram_predictions(p_av_big, t_av_big, radius_bins=False, particle_ids=None, errorbars=False, fig=f1,
axes=a, color="C1", label=r"$L_\mathrm{box}=200 \, \mathrm{Mpc} \,/ \,h$")
a1[0].set_ylabel(r"$n_{\mathrm{particles}}$", fontsize=16)
[a.set_xlabel(r"$\log(M_{\mathrm{predicted}}/M_{\mathrm{true}})$", fontsize=16) for a in a1]
plt.savefig("/Users/luisals/Documents/Papers/dlhalos_paper/averaged_small_vs_large_box.pdf")
# Averaged-density case
f1, a, m = pp.plot_histogram_predictions(p_big, t_big, radius_bins=False, particle_ids=None, errorbars=False,
label="Raw density", color="C0")
f11, a1, m1 = pp.plot_histogram_predictions(p_av_big, t_av_big, radius_bins=False, particle_ids=None, errorbars=False, fig=f1,
axes=a, color="C1", label="Averaged density")
a1[0].set_ylabel(r"$n_{\mathrm{particles}}$", fontsize=16)
[a.set_xlabel(r"$\log(M_{\mathrm{predicted}}/M_{\mathrm{true}})$", fontsize=16) for a in a1]
plt.savefig("/Users/luisals/Documents/Papers/dlhalos_paper/raw_vs_averaged_large_box.pdf")
| 60.461538 | 126 | 0.699746 |
b7a964ee74b74803fefa91500045e19a16c2244a | 85,945 | py | Python | regions.py | greggy/python-ipgeobase | 593e4dc7e55e0c90a1979e586f03c013f6ac057a | [
"BSD-3-Clause"
] | 1 | 2017-11-12T11:26:25.000Z | 2017-11-12T11:26:25.000Z | regions.py | greggy/python-ipgeobase | 593e4dc7e55e0c90a1979e586f03c013f6ac057a | [
"BSD-3-Clause"
] | null | null | null | regions.py | greggy/python-ipgeobase | 593e4dc7e55e0c90a1979e586f03c013f6ac057a | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
REGIONS = {'USRI': 'Rhode Island', 'UY02': 'Canelones', 'KR21': 'Ulsan-gwangyoksi', 'KR20': 'Kyongsang-namdo', 'KM02': 'Grande Comore', 'KM03': 'Moheli', 'CO22': 'Putumayo', 'BN18': 'Zou', 'BN17': 'Plateau', 'BN16': 'Oueme', 'BN15': 'Tutong', 'BN14': 'Littoral', 'BN13': 'Donga', 'BN12': 'Kouffo', 'BN11': 'Collines', 'BN10': 'Temburong', 'KP09': 'Kangwon-do', 'KP08': 'Kaesong-si', 'KP07': 'Hwanghae-bukto', 'KP06': 'Hwanghae-namdo', 'KP01': 'Chagang-do', 'KP03': 'Hamgyong-namdo', 'IS40': 'Norourland Eystra', 'CO28': 'Tolima', 'TH77': 'Amnat Charoen', 'CO29': 'Valle del Cauca', 'TH76': 'Udon Thani', 'IS44': 'Vestfiroir', 'IS45': 'Vesturland', 'MK80': 'Plasnica', 'MK81': 'Podares', 'MK82': 'Prilep', 'MK83': 'Probistip', 'MK84': 'Radovis', 'MK85': 'Rankovce', 'MK86': 'Resen', 'MK87': 'Rosoman', 'MK88': 'Rostusa', 'MK89': 'Samokov', 'NG23': 'Kaduna', 'NG22': 'Cross River', 'SZ05': 'Praslin', 'SZ04': 'Shiselweni', 'SZ03': 'Manzini', 'SZ02': 'Lubombo', 'SZ01': 'Hhohho', 'NG26': 'Benue', 'BG41': 'Gabrovo', 'BG40': 'Dobrich', 'BG43': 'Khaskovo', 'BG42': 'Grad Sofiya', 'BG45': 'Kyustendil', 'BG44': 'Kurdzhali', 'BG47': 'Montana', 'BG46': 'Lovech', 'BG49': 'Pernik', 'BG48': 'Pazardzhik', 'NG24': 'Katsina', 'DO19': 'Salcedo', 'KH18': 'Svay Rieng', 'KH19': 'Takeo', 'KH12': 'Pursat', 'KH13': 'Preah Vihear', 'KH10': 'Mondulkiri', 'KH11': 'Phnum Penh', 'KH16': 'Siem Reap', 'KH17': 'Stung Treng', 'KH14': 'Prey Veng', 'KH15': 'Ratanakiri Kiri', 'GN15': 'Kerouane', 'GN16': 'Kindia', 'GN17': 'Kissidougou', 'GN10': 'Forecariah', 'GN11': 'Fria', 'GN12': 'Gaoual', 'GN13': 'Gueckedou', 'GN18': 'Koundara', 'GN19': 'Kouroussa', 'GBR1': 'Ballymoney', 'GBR3': 'Belfast', 'GBR2': 'Banbridge', 'GBR5': 'Castlereagh', 'GBR4': 'Carrickfergus', 'GBR7': 'Cookstown', 'GBR6': 'Coleraine', 'GBR9': 'Down', 'GBR8': 'Craigavon', 'CZ87': 'Plzensky kraj', 'CZ86': 'Pardubicky kraj', 'CZ85': 'Moravskoslezsky kraj', 'CZ84': 'Olomoucky kraj', 'CZ83': 'Liberecky kraj', 'CZ82': 'Kralovehradecky kraj', 'CZ81': 'Karlovarsky kraj', 'CZ80': 'Vysocina', 'CZ89': 'Ustecky kraj', 'CZ88': 'Stredocesky kraj', 'MD87': 'Soroca', 'MD86': 'Soldanesti', 'MD85': 'Singerei', 'MD84': 'Riscani', 'MD83': 'Rezina', 'MD81': 'Ocnita', 'MD80': 'Nisporeni', 'VN55': 'Binh Thuan', 'MD89': 'Straseni', 'MD88': 'Stefan-Voda', 'CN09': 'Henan', 'CN08': 'Heilongjiang', 'CN03': 'Jiangxi', 'CN02': 'Zhejiang', 'CN01': 'Anhui', 'CN07': 'Fujian', 'CN06': 'Qinghai', 'CN05': 'Jilin', 'CN04': 'Jiangsu', 'DE04': 'Hamburg', 'VN50': 'Vinh Phu', 'PE09': 'Huancavelica', 'PE08': 'Cusco', 'PE01': 'Amazonas', 'PE03': 'Apurimac', 'PE02': 'Ancash', 'PE05': 'Ayacucho', 'PE04': 'Arequipa', 'PE07': 'Callao', 'PE06': 'Cajamarca', 'AE02': 'Ajman', 'DE08': 'Rheinland-Pfalz', 'AE01': 'Abu Dhabi', 'AE06': 'Sharjah', 'AE07': 'Umm Al Quwain', 'GY19': 'Upper Takutu-Upper Essequibo', 'GY18': 'Upper Demerara-Berbice', 'AE04': 'Fujairah', 'AF08': 'Ghazni', 'GY13': 'East Berbice-Corentyne', 'GY12': 'Demerara-Mahaica', 'GY11': 'Cuyuni-Mazaruni', 'GY10': 'Barima-Waini', 'GY17': 'Potaro-Siparuni', 'GY16': 'Pomeroon-Supenaam', 'GY15': 'Mahaica-Berbice', 'GY14': 'Essequibo Islands-West Demerara', 'BI10': 'Bururi', 'BI11': 'Cankuzo', 'BI12': 'Cibitoke', 'BI13': 'Gitega', 'BI14': 'Karuzi', 'BI15': 'Kayanza', 'BI16': 'Kirundo', 'BI17': 'Makamba', 'BI18': 'Muyinga', 'BI19': 'Ngozi', 'IE02': 'Cavan', 'USSC': 'South Carolina', 'AF02': 'Badghis', 'USSD': 'South Dakota', 'IE06': 'Donegal', 'IE04': 'Cork', 'MK93': 'Sopotnica', 'MK92': 'Sopiste', 'MK91': 'Sipkovica', 'MK90': 'Saraj', 'MK97': 'Staro Nagoricane', 'MK96': 'Star Dojran', 'MK95': 'Staravina', 'MK94': 'Srbinovo', 'MK99': 'Struga', 'MK98': 'Stip', 'CD01': 'Bandundu', 'KG01': 'Bishkek', 'CD05': 'Katanga', 'CD04': 'Kasai-Oriental', 'CD06': 'Kinshasa', 'SD32': 'Bahr al Ghazal', 'LB02': 'Al Janub', 'LB03': 'Liban-Nord', 'LB01': 'Beqaa', 'LB06': 'Liban-Sud', 'LB07': 'Nabatiye', 'LB04': 'Beyrouth', 'LB05': 'Mont-Liban', 'LB08': 'Beqaa', 'LB09': 'Liban-Nord', 'KH05': 'Kampong Thum', 'KH04': 'Kampong Speu', 'KH07': 'Kandal', 'KH06': 'Kampot', 'KH01': 'Batdambang', 'KH03': 'Kampong Chhnang', 'KH02': 'Kampong Cham', 'KH09': 'Kracheh', 'KH08': 'Koh Kong', 'PT02': 'Aveiro', 'PT03': 'Beja', 'PT04': 'Braga', 'PT05': 'Braganca', 'PT06': 'Castelo Branco', 'PT07': 'Coimbra', 'PT08': 'Evora', 'PT09': 'Faro', 'GN07': 'Dinguiraye', 'GN06': 'Dalaba', 'GN05': 'Dabola', 'GN04': 'Conakry', 'GN03': 'Boke', 'GN02': 'Boffa', 'GN01': 'Beyla', 'GN09': 'Faranah', 'SI17': 'Crnomelj', 'SI16': 'Crna na Koroskem', 'SK06': 'Trencin', 'SK07': 'Trnava', 'SK04': 'Nitra', 'SK05': 'Presov', 'SK02': 'Bratislava', 'SK03': 'Kosice', 'SK01': 'Banska Bystrica', 'SK08': 'Zilina', 'GBW5': 'South Lanarkshire', 'MX27': 'Tabasco', 'CN32': 'Sichuan', 'CN33': 'Chongqing', 'CN30': 'Guangdong', 'CN31': 'Hainan', 'BH17': 'Al Janubiyah', 'VE18': 'Portuguesa', 'VE19': 'Sucre', 'VE11': 'Falcon', 'VE12': 'Guarico', 'VE13': 'Lara', 'VE14': 'Merida', 'VE15': 'Miranda', 'VE16': 'Monagas', 'VE17': 'Nueva Esparta', 'BH16': 'Al Asimah', 'NE07': 'Zinder', 'MX10': 'Durango', 'MX11': 'Guanajuato', 'MX12': 'Guerrero', 'MX13': 'Hidalgo', 'MX14': 'Jalisco', 'MX15': 'Mexico', 'MX16': 'Michoacan de Ocampo', 'MX17': 'Morelos', 'MX18': 'Nayarit', 'MX19': 'Nuevo Leon', 'DZ55': 'Tipaza', 'BI02': 'Bujumbura', 'BI09': 'Bubanza', 'CV10': 'Sao Nicolau', 'CV11': 'Sao Vicente', 'CV13': 'Mosteiros', 'CV14': 'Praia', 'CV15': 'Santa Catarina', 'CV16': 'Santa Cruz', 'CV17': 'Sao Domingos', 'CV18': 'Sao Filipe', 'CV19': 'Sao Miguel', 'PHB8': 'Cotabato', 'PHB9': 'Dagupan', 'PHB3': 'Calbayog', 'ER01': 'Anseba', 'ER03': "Debubawi K'eyih Bahri", 'ER02': 'Debub', 'ER05': "Ma'akel", 'ER04': 'Gash Barka', 'ER06': "Semenawi K'eyih Bahri", 'NE08': 'Niamey', 'TH80': 'Sa Kaeo', 'PHB5': 'Canlaon', 'TD08': 'Logone Occidental', 'TD09': 'Logone Oriental', 'TD04': 'Chari-Baguirmi', 'TD05': 'Guera', 'TD06': 'Kanem', 'TD07': 'Lac', 'TD01': 'Batha', 'TD02': 'Biltine', 'TD03': 'Borkou-Ennedi-Tibesti', 'LB11': 'Baalbek-Hermel', 'LB10': 'Aakk', 'PT13': 'Leiria', 'PT11': 'Guarda', 'PT10': 'Madeira', 'PT17': 'Porto', 'PT16': 'Portalegre', 'PT14': 'Lisboa', 'PT19': 'Setubal', 'PT18': 'Santarem', 'GN32': 'Kankan', 'GN33': 'Koubia', 'GN30': 'Coyah', 'GN31': 'Dubreka', 'GN36': 'Lola', 'GN37': 'Mandiana', 'GN34': 'Labe', 'GN35': 'Lelouma', 'GN38': 'Nzerekore', 'GN39': 'Siguiri', 'MW22': 'Salima', 'ES56': 'Catalonia', 'ES55': 'Castilla y Leon', 'JM14': 'Saint Thomas', 'ES54': 'Castilla-La Mancha', 'JP47': 'Okinawa', 'MW26': 'Balaka', 'JM16': 'Westmoreland', 'ES52': 'Aragon', 'CN21': 'Ningxia', 'CN20': 'Nei Mongol', 'CN23': 'Shanghai', 'CN22': 'Beijing', 'CN25': 'Shandong', 'CN24': 'Shanxi', 'CN26': 'Shaanxi', 'CN29': 'Yunnan', 'CN28': 'Tianjin', 'JM11': 'Saint Elizabeth', 'LT59': 'Marijampoles Apskritis', 'LT58': 'Klaipedos Apskritis', 'JM12': 'Saint James', 'VE03': 'Apure', 'VE02': 'Anzoategui', 'VE01': 'Amazonas', 'JP41': 'Tottori', 'LT57': 'Kauno Apskritis', 'LT56': 'Alytaus Apskritis', 'VE05': 'Barinas', 'VE04': 'Aragua', 'FRB2': 'Lorraine', 'FRB1': 'Limousin', 'VN54': 'Binh Dinh', 'FRB6': 'Picardie', 'FRB7': 'Poitou-Charentes', 'EC08': 'El Oro', 'EC09': 'Esmeraldas', 'FRB4': 'Nord-Pas-de-Calais', 'EC01': 'Galapagos', 'EC02': 'Azuay', 'EC03': 'Bolivar', 'EC04': 'Canar', 'EC05': 'Carchi', 'EC06': 'Chimborazo', 'EC07': 'Cotopaxi', 'MX03': 'Baja California Sur', 'MX02': 'Baja California', 'MX01': 'Aguascalientes', 'MX07': 'Coahuila de Zaragoza', 'MX06': 'Chihuahua', 'MX05': 'Chiapas', 'MX04': 'Campeche', 'CAPE': 'Prince Edward Island', 'MX09': 'Distrito Federal', 'MX08': 'Colima', 'SI66': 'Loski Potok', 'SI64': 'Logatec', 'ZM07': 'Southern', 'ZM06': 'North-Western', 'SI62': 'Ljubno', 'ZM05': 'Northern', 'PA06': 'Herrera', 'PA01': 'Bocas del Toro', 'UG90': 'Mukono', 'CV02': 'Brava', 'CV01': 'Boa Vista', 'KY08': 'Western', 'ZM01': 'Western', 'CV05': 'Paul', 'CV04': 'Maio', 'KY04': 'South Town', 'KY05': 'Spot Bay', 'KY06': 'Stake Bay', 'CV08': 'Sal', 'KY01': 'Creek', 'KY02': 'Eastern', 'KY03': 'Midland', 'US44': 'Rhode Island', 'MZ03': 'Inhambane', 'US47': 'Tennessee', 'US40': 'Oklahoma', 'US41': 'Oregon', 'US42': 'Pennsylvania', 'IQ08': 'Dahuk', 'IQ09': 'Dhi Qar', 'IQ06': 'Babil', 'IQ07': 'Baghdad', 'IQ04': 'Al Qadisiyah', 'IQ05': 'As Sulaymaniyah', 'IQ02': 'Al Basrah', 'LA14': 'Xiangkhoang', 'IQ01': 'Al Anbar', 'TD14': 'Tandjile', 'TD13': 'Salamat', 'TD12': 'Ouaddai', 'TD11': 'Moyen-Chari', 'TD10': 'Mayo-Kebbi', 'GT22': 'Zacapa', 'GT21': 'Totonicapan', 'GT20': 'Suchitepequez', 'GBA8': 'Blackburn with Darwen', 'GBA9': 'Blackpool', 'PT22': 'Viseu', 'PT23': 'Azores', 'PT20': 'Viana do Castelo', 'PT21': 'Vila Real', 'GN29': 'Yomou', 'GN28': 'Tougue', 'EE10': 'Parnu', 'GN25': 'Pita', 'GN27': 'Telimele', 'GN21': 'Macenta', 'GBA2': 'Barnet', 'GN23': 'Mamou', 'GN22': 'Mali', 'GR47': 'Dhodhekanisos', 'GBA3': 'Barnsley', 'GR46': 'Lasithi', 'GBA4': 'Bath and North East Somerset', 'GBA5': 'Bedfordshire', 'GR44': 'Rethimni', 'GBA6': 'Bexley', 'GBA7': 'Birmingham', 'AD08': 'Escaldes-Engordany', 'AD03': 'Encamp', 'AD02': 'Canillo', 'AD07': 'Andorra la Vella', 'AD06': 'Sant Julia de Loria', 'AD05': 'Ordino', 'AD04': 'La Massana', 'CG08': 'Plateaux', 'LY57': 'Gharyan', 'CG01': 'Bouenza', 'CG06': 'Likouala', 'CG07': 'Niari', 'CG04': 'Kouilou', 'CG05': 'Lekoumou', 'VN44': 'Dac Lac', 'VN45': 'Dong Nai', 'LT64': 'Utenos Apskritis', 'LT65': 'Vilniaus Apskritis', 'LT62': 'Taurages Apskritis', 'LT63': 'Telsiu Apskritis', 'LT60': 'Panevezio Apskritis', 'LT61': 'Siauliu Apskritis', 'VN49': 'Song Be', 'JP28': 'Nara', 'JP29': 'Niigata', 'JP24': 'Miyagi', 'JP25': 'Miyazaki', 'JP26': 'Nagano', 'JP27': 'Nagasaki', 'JP20': 'Kochi', 'JP21': 'Kumamoto', 'JP22': 'Kyoto', 'JP23': 'Mie', 'EC19': 'Tungurahua', 'EC18': 'Pichincha', 'EC13': 'Los Rios', 'EC12': 'Loja', 'EC11': 'Imbabura', 'EC10': 'Guayas', 'EC17': 'Pastaza', 'EC15': 'Morona-Santiago', 'EC14': 'Manabi', 'SI04': 'Bohinj', 'SI05': 'Borovnica', 'SI06': 'Bovec', 'SI07': 'Brda', 'SI01': 'Ajdovscina', 'SI02': 'Beltinci', 'SI03': 'Bled', 'MX32': 'Zacatecas', 'SI09': 'Brezovica', 'MX30': 'Veracruz-Llave', 'MX31': 'Yucatan', 'DO18': 'Puerto Plata', 'PHA9': 'Cabanatuan', 'PHA8': 'Butuan', 'PHA7': 'Batangas City', 'PHA6': 'Basilan City', 'PHA5': 'Bais', 'PHA4': 'Baguio', 'PHA3': 'Bago', 'PHA2': 'Bacolod', 'PHA1': 'Angeles', 'JP42': 'Toyama', 'BI21': 'Ruyigi', 'BI20': 'Rutana', 'BI23': 'Mwaro', 'BI22': 'Muramvya', 'PA10': 'Veraguas', 'MZ10': 'Manica', 'MZ11': 'Maputo', 'IQ18': 'Salah ad Din', 'PH29': 'Ilocos Sur', 'IQ11': 'Arbil', 'IQ10': 'Diyala', 'IQ13': "At Ta'mim", 'IQ12': "Karbala'", 'IQ15': 'Ninawa', 'IQ14': 'Maysan', 'IQ17': 'An Najaf', 'IQ16': 'Wasit', 'TJ02': 'Khatlon', 'TJ03': 'Sughd', 'TJ01': 'Kuhistoni Badakhshon', 'GT12': 'Peten', 'GT13': 'Quetzaltenango', 'GT10': 'Jalapa', 'GT11': 'Jutiapa', 'GT16': 'Sacatepequez', 'GT17': 'San Marcos', 'GT14': 'Quiche', 'GT15': 'Retalhuleu', 'GT18': 'Santa Rosa', 'GT19': 'Solola', 'PSWE': 'West Bank', 'PY23': 'Alto Paraguay', 'PY21': 'Nueva Asuncion', 'PY20': 'Chaco', 'QA06': 'Ar Rayyan', 'QA04': 'Al Khawr', 'QA05': 'Al Wakrah Municipality', 'QA02': 'Al Ghuwariyah', 'QA03': 'Al Jumaliyah', 'QA01': 'Ad Dawhah', 'QA08': 'Madinat ach Shamal', 'QA09': 'Umm Salal', 'GBU5': 'East Dunbartonshire', 'UY03': 'Cerro Largo', 'UY01': 'Artigas', 'UY06': 'Flores', 'UY07': 'Florida', 'UY04': 'Colonia', 'UY05': 'Durazno', 'UY08': 'Lavalleja', 'UY09': 'Maldonado', 'CH10': 'Inner-Rhoden', 'GBU6': 'East Lothian', 'CH11': 'Luzern', 'CG14': 'Cuvette-Ouest', 'CG11': 'Pool', 'CG10': 'Sangha', 'CG13': 'Cuvette', 'CG12': 'Brazzaville', 'UA24': "Volyns'ka Oblast'", 'UA25': "Zakarpats'ka Oblast'", 'UA26': "Zaporiz'ka Oblast'", 'UA27': "Zhytomyrs'ka Oblast'", 'UA20': "Sevastopol'", 'UA21': "Sums'ka Oblast'", 'UA22': "Ternopil's'ka Oblast'", 'UA23': "Vinnyts'ka Oblast'", 'IT20': 'Veneto', 'US11': 'District of Columbia', 'VE21': 'Trujillo', 'VE20': 'Tachira', 'VE23': 'Zulia', 'VE22': 'Yaracuy', 'VE25': 'Distrito Federal', 'VN52': 'Ho Chi Minh', 'VN51': 'Ha Noi', 'VE26': 'Vargas', 'VN59': 'Ha Tay', 'VN58': 'Ha Giang', 'LY62': 'Yafran', 'JP39': 'Tokushima', 'JP38': 'Tochigi', 'JP37': 'Shizuoka', 'JP36': 'Shimane', 'JP35': 'Shiga', 'JP34': 'Saitama', 'JP33': 'Saga', 'JP32': 'Osaka', 'JP31': 'Okayama', 'JP30': 'Oita', 'MX29': 'Tlaxcala', 'MX28': 'Tamaulipas', 'SI15': 'Crensovci', 'SI14': 'Cerkno', 'SI13': 'Cerknica', 'SI12': 'Cerklje na Gorenjskem', 'SI11': 'Celje', 'MX21': 'Puebla', 'MX20': 'Oaxaca', 'MX23': 'Quintana Roo', 'MX22': 'Queretaro de Arteaga', 'MX25': 'Sinaloa', 'MX24': 'San Luis Potosi', 'SI19': 'Divaca', 'MX26': 'Sonora', 'LY60': 'Surt', 'MD61': 'Basarabeasca', 'MD60': 'Balti', 'MD63': 'Briceni', 'KN10': 'Saint Paul Charlestown', 'KN11': 'Saint Peter Basseterre', 'KN12': 'Saint Thomas Lowland', 'MD62': 'Bender', 'KN15': 'Trinity Palmetto Point', 'PHB2': 'Cagayan de Oro', 'MD65': 'Cantemir', 'PHB1': 'Cadiz', 'PHB6': 'Cavite City', 'PHB7': 'Cebu City', 'PHB4': 'Caloocan', 'MD64': 'Cahul', 'CI75': 'Bafing', 'CI74': 'Agneby', 'CI77': 'Denguele', 'CI76': 'Bas-Sassandra', 'CI79': 'Fromager', 'CI78': 'Dix-Huit Montagnes', 'FRB5': 'Pays de la Loire', 'EC24': 'Orellana', 'EC22': 'Sucumbios', 'EC23': 'Napo', 'EC20': 'Zamora-Chinchipe', 'CV20': 'Tarrafal', 'KW02': 'Al Kuwayt', 'KW01': 'Al Ahmadi', 'KW07': 'Al Farwaniyah', 'KW05': 'Al Jahra', 'CH19': 'Thurgau', 'KW08': 'Hawalli', 'KW09': 'Mubarak al Kabir', 'PA09': 'San Blas', 'PA08': 'Panama', 'ZM09': 'Lusaka', 'ZM08': 'Copperbelt', 'PA05': 'Darien', 'PA04': 'Colon', 'PA07': 'Los Santos', 'ZM04': 'Luapula', 'ZM03': 'Eastern', 'ZM02': 'Central', 'PA03': 'Cocle', 'PA02': 'Chiriqui', 'MZ01': 'Cabo Delgado', 'US45': 'South Carolina', 'US46': 'South Dakota', 'MZ02': 'Gaza', 'MZ05': 'Sofala', 'MZ04': 'Maputo', 'MZ07': 'Niassa', 'MZ06': 'Nampula', 'MZ09': 'Zambezia', 'MZ08': 'Tete', 'US48': 'Texas', 'US49': 'Utah', 'GD05': 'Saint Mark', 'GD04': 'Saint John', 'GD06': 'Saint Patrick', 'GD01': 'Saint Andrew', 'GD03': 'Saint George', 'GD02': 'Saint David', 'IS09': 'Eyjafjardarsysla', 'IS05': 'Austur-Hunavatnssysla', 'IS06': 'Austur-Skaftafellssysla', 'IS07': 'Borgarfjardarsysla', 'IS03': 'Arnessysla', 'AU02': 'New South Wales', 'AU03': 'Northern Territory', 'AU01': 'Australian Capital Territory', 'AU06': 'Tasmania', 'AU07': 'Victoria', 'AU04': 'Queensland', 'AU05': 'South Australia', 'AU08': 'Western Australia', 'BO09': 'Tarija', 'BM10': 'Southampton', 'BM11': 'Warwick', 'GT09': 'Izabal', 'GT08': 'Huehuetenango', 'GT05': 'El Progreso', 'GT04': 'Chiquimula', 'GT07': 'Guatemala', 'GT06': 'Escuintla', 'GT01': 'Alta Verapaz', 'GT03': 'Chimaltenango', 'GT02': 'Baja Verapaz', 'PY19': 'Canindeyu', 'PY12': 'Misiones', 'PY13': 'Neembucu', 'PY10': 'Guaira', 'PY11': 'Itapua', 'PY16': 'Presidente Hayes', 'PY17': 'San Pedro', 'PY15': 'Paraguari', 'QA11': 'Jariyan al Batnah', 'QA10': 'Al Wakrah', 'QA12': "Umm Sa'id", 'AF41': 'Daykondi', 'AF40': 'Parvan', 'AF42': 'Panjshir', 'GBY1': 'Flintshire', 'GBY2': 'Gwynedd', 'GBY3': 'Merthyr Tydfil', 'GBY4': 'Monmouthshire', 'GBY5': 'Neath Port Talbot', 'GBY6': 'Newport', 'GBY7': 'Pembrokeshire', 'GBY8': 'Powys', 'GBY9': 'Rhondda Cynon Taff', 'UY19': 'Treinta y Tres', 'UY18': 'Tacuarembo', 'UY15': 'Salto', 'UY14': 'Rocha', 'UY17': 'Soriano', 'UY16': 'San Jose', 'UY11': 'Paysandu', 'UY10': 'Montevideo', 'UY13': 'Rivera', 'UY12': 'Rio Negro', 'CL16': 'Arica y Parinacota', 'CL17': 'Los Rios', 'CL14': 'Los Lagos', 'CL15': 'Tarapaca', 'SN14': 'Saint-Louis', 'SN15': 'Matam', 'CL10': 'Magallanes y de la Antartica Chilena', 'CL11': 'Maule', 'BZ01': 'Belize', 'BZ02': 'Cayo', 'BZ03': 'Corozal', 'BZ04': 'Orange Walk', 'BZ05': 'Stann Creek', 'BZ06': 'Toledo', 'CASK': 'Saskatchewan', 'RU87': 'Yamal-Nenets', 'RU86': 'Voronezh', 'RU85': 'Vologda', 'RU84': 'Volgograd', 'RU83': 'Vladimir', 'VN67': 'Ninh Binh', 'VN64': 'Quang Tri', 'VN65': 'Nam Ha', 'VN68': 'Ninh Thuan', 'VN69': 'Phu Yen', 'RU89': 'Yevrey', 'RU88': "Yaroslavl'", 'JP08': 'Fukushima', 'JP09': 'Gifu', 'JP02': 'Akita', 'JP03': 'Aomori', 'JP01': 'Aichi', 'JP06': 'Fukui', 'JP07': 'Fukuoka', 'JP04': 'Chiba', 'JP05': 'Ehime', 'SI22': 'Dol pri Ljubljani', 'SI20': 'Dobrepolje', 'SI26': 'Duplek', 'SI27': 'Gorenja Vas-Poljane', 'SI24': 'Dornava', 'SI25': 'Dravograd', 'SI28': 'Gorisnica', 'SI29': 'Gornja Radgona', 'GBE4': 'Essex', 'GBE5': 'Gateshead', 'GBE6': 'Gloucestershire', 'GBE7': 'Greenwich', 'GBE1': 'East Riding of Yorkshire', 'GBE2': 'East Sussex', 'GBE3': 'Enfield', 'GBE8': 'Hackney', 'GBE9': 'Halton', 'KN03': 'Saint George Basseterre', 'KN02': 'Saint Anne Sandy Point', 'KN01': 'Christ Church Nichola Town', 'KN07': 'Saint John Figtree', 'KN06': 'Saint John Capisterre', 'KN05': 'Saint James Windward', 'KN04': 'Saint George Gingerland', 'KN09': 'Saint Paul Capisterre', 'KN08': 'Saint Mary Cayon', 'CI88': 'Sud-Bandama', 'CI89': 'Sud-Comoe', 'CI84': 'Moyen-Cavally', 'CI85': 'Moyen-Comoe', 'CI86': "N'zi-Comoe", 'CI87': 'Savanes', 'CI80': 'Haut-Sassandra', 'CI81': 'Lacs', 'CI82': 'Lagunes', 'CI83': 'Marahoue', 'NG16': 'Ogun', 'AZ18': 'Fuzuli', 'AZ19': 'Gadabay', 'NG11': 'Federal Capital Territory', 'US56': 'Wyoming', 'US55': 'Wisconsin', 'US54': 'West Virginia', 'US53': 'Washington', 'US51': 'Virginia', 'US50': 'Vermont', 'PHC5': 'Dumaguete', 'PHC4': 'Dipolog', 'PHC7': 'Gingoog', 'PHC6': 'General Santos', 'PHC1': 'Danao', 'PHC3': 'Davao City', 'PHC2': 'Dapitan', 'CO38': 'Magdalena', 'PHC9': 'Iloilo City', 'SN12': 'Ziguinchor', 'SN13': 'Louga', 'TH48': 'Chanthaburi', 'TH49': 'Trat', 'TH44': 'Chachoengsao', 'TH45': 'Prachin Buri', 'IS15': 'Kjosarsysla', 'TH47': 'Rayong', 'TH40': 'Krung Thep', 'TH41': 'Phayao', 'TH42': 'Samut Prakan', 'IS10': 'Gullbringusysla', 'BM07': "Saint George's", 'BM06': 'Saint George', 'BM05': 'Pembroke', 'BM04': 'Paget', 'BM03': 'Hamilton', 'BM02': 'Hamilton', 'BM01': 'Devonshire', 'BM09': 'Smiths', 'BM08': 'Sandys', 'SIK5': 'Preddvor', 'USDC': 'District of Columbia', 'PY05': 'Caazapa', 'PY04': 'Caaguazu', 'PY07': 'Concepcion', 'PY06': 'Central', 'PY01': 'Alto Parana', 'PY03': 'Boqueron', 'PY02': 'Amambay', 'PY08': 'Cordillera', 'AF30': 'Balkh', 'AF31': 'Jowzjan', 'AF32': 'Samangan', 'AF33': 'Sar-e Pol', 'AF34': 'Konar', 'AF35': 'Laghman', 'AF36': 'Paktia', 'AF37': 'Khowst', 'AF38': 'Nurestan', 'AF39': 'Oruzgan', 'GBX3': 'Bridgend', 'GBX2': 'Blaenau Gwent', 'GBX1': 'Isle of Anglesey', 'ML10': 'Kidal', 'GBX6': 'Ceredigion', 'GBX5': 'Cardiff', 'GBX4': 'Caerphilly', 'GBX9': 'Denbighshire', 'GBX8': 'Conwy', 'AM08': "Syunik'", 'AM09': 'Tavush', 'AM02': 'Ararat', 'AM03': 'Armavir', 'AM01': 'Aragatsotn', 'AM06': 'Lorri', 'AM07': 'Shirak', 'AM04': "Geghark'unik'", 'AM05': "Kotayk'", 'CL09': 'Los Lagos', 'CL08': "Libertador General Bernardo O'Higgins", 'SN09': 'Fatick', 'SN03': 'Diourbel', 'SN01': 'Dakar', 'CL02': 'Aisen del General Carlos Ibanez del Campo', 'SN07': 'Thies', 'CL04': 'Araucania', 'SN05': 'Tambacounda', 'CL06': 'Bio-Bio', 'SN10': 'Kaolack', 'UA08': "Khersons'ka Oblast'", 'UA09': "Khmel'nyts'ka Oblast'", 'USMN': 'Minnesota', 'UA02': "Chernihivs'ka Oblast'", 'UA03': "Chernivets'ka Oblast'", 'UA01': "Cherkas'ka Oblast'", 'UA06': "Ivano-Frankivs'ka Oblast'", 'UA07': "Kharkivs'ka Oblast'", 'UA04': "Dnipropetrovs'ka Oblast'", 'UA05': "Donets'ka Oblast'", 'SN11': 'Kolda', 'VN62': 'Khanh Hoa', 'VN79': 'Hai Duong', 'VN78': 'Da Nang', 'VN63': 'Kon Tum', 'VN75': 'Tra Vinh', 'VN74': 'Thua Thien', 'VN77': 'Vinh Long', 'VN76': 'Tuyen Quang', 'VN71': 'Quang Ngai', 'VN60': 'Ha Tinh', 'VN73': 'Soc Trang', 'VN72': 'Quang Tri', 'VN61': 'Hoa Binh', 'VN66': 'Nghe An', 'RU82': 'Ust-Orda Buryat', 'JP15': 'Ishikawa', 'JP14': 'Ibaraki', 'JP17': 'Kagawa', 'JP16': 'Iwate', 'JP11': 'Hiroshima', 'RU81': "Ul'yanovsk", 'JP13': 'Hyogo', 'JP12': 'Hokkaido', 'IL03': 'HaZafon', 'IL02': 'HaMerkaz', 'IL01': 'HaDarom', 'RU80': 'Udmurt', 'JP19': 'Kanagawa', 'JP18': 'Kagoshima', 'IL05': 'Tel Aviv', 'IL04': 'Hefa', 'SI39': 'Ivancna Gorica', 'SI38': 'Ilirska Bistrica', 'SI35': 'Hrpelje-Kozina', 'SI34': 'Hrastnik', 'SI37': 'Ig', 'SI36': 'Idrija', 'SI31': 'Gornji Petrovci', 'SI30': 'Gornji Grad', 'SI32': 'Grosuplje', 'EE20': 'Viljandimaa', 'GBD6': 'Dorset', 'GBD5': 'Doncaster', 'GBD4': 'Devon', 'GBD3': 'Derbyshire', 'GBD2': 'Derby', 'GBD1': 'Darlington', 'GBD9': 'Ealing', 'GBD8': 'Durham', 'BR01': 'Acre', 'BR02': 'Alagoas', 'BR03': 'Amapa', 'BR04': 'Amazonas', 'BR05': 'Bahia', 'BR06': 'Ceara', 'BR07': 'Distrito Federal', 'BR08': 'Espirito Santo', 'CI92': 'Zanzan', 'CI91': 'Worodougou', 'CI90': 'Vallee du Bandama', 'PK03': 'North-West Frontier', 'PK02': 'Balochistan', 'IT10': 'Marche', 'IT11': 'Molise', 'IT12': 'Piemonte', 'IT13': 'Puglia', 'IT14': 'Sardegna', 'IT15': 'Sicilia', 'IT16': 'Toscana', 'IT17': 'Trentino-Alto Adige', 'IT18': 'Umbria', 'IT19': "Valle d'Aosta", 'PHD1': 'Iriga', 'PHD2': 'La Carlota', 'PHD3': 'Laoag', 'PHD4': 'Lapu-Lapu', 'PHD5': 'Legaspi', 'PHD6': 'Lipa', 'PHD7': 'Lucena', 'PHD8': 'Mandaue', 'PHD9': 'Manila', 'PK08': 'Islamabad', 'BB01': 'Christ Church', 'IS28': 'Skagafjardarsysla', 'IS29': 'Snafellsnes- og Hnappadalssysla', 'BB04': 'Saint James', 'BB05': 'Saint John', 'TH59': 'Ranong', 'TH58': 'Chumphon', 'TH57': 'Prachuap Khiri Khan', 'IS23': 'Rangarvallasysla', 'TH55': 'Samut Sakhon', 'TH54': 'Samut Songkhram', 'TH53': 'Nakhon Pathom', 'TH52': 'Ratchaburi', 'TH51': 'Suphan Buri', 'TH50': 'Kanchanaburi', 'BT20': 'Thimphu', 'BT21': 'Tongsa', 'BT22': 'Wangdi Phodrang', 'CR07': 'Puntarenas', 'CR06': 'Limon', 'CR04': 'Heredia', 'CR03': 'Guanacaste', 'CR02': 'Cartago', 'CR01': 'Alajuela', 'CR08': 'San Jose', 'HN02': 'Choluteca', 'HN03': 'Colon', 'HN01': 'Atlantida', 'HN06': 'Cortes', 'HN07': 'El Paraiso', 'HN04': 'Comayagua', 'HN05': 'Copan', 'HN08': 'Francisco Morazan', 'HN09': 'Gracias a Dios', 'GL01': 'Nordgronland', 'GL03': 'Vestgronland', 'GL02': 'Ostgronland', 'ET50': 'Hareri Hizb', 'ET51': 'Oromiya', 'ET52': 'Sumale', 'ET53': 'Tigray', 'ET54': 'YeDebub Biheroch Bihereseboch na Hizboch', 'AF23': 'Kandahar', 'AF27': 'Vardak', 'IE29': 'Westmeath', 'AF24': 'Kondoz', 'IE24': 'Roscommon', 'IE25': 'Sligo', 'IE26': 'Tipperary', 'IE27': 'Waterford', 'IE20': 'Mayo', 'IE21': 'Meath', 'IE22': 'Monaghan', 'IE23': 'Offaly', 'ML07': 'Koulikoro', 'ML06': 'Sikasso', 'ML05': 'Segou', 'ML04': 'Mopti', 'ML03': 'Kayes', 'AM10': "Vayots' Dzor", 'ML01': 'Bamako', 'ML09': 'Gao', 'ML08': 'Tombouctou', 'UA15': "L'vivs'ka Oblast'", 'UA14': "Luhans'ka Oblast'", 'UA17': "Odes'ka Oblast'", 'UA16': "Mykolayivs'ka Oblast'", 'UA11': 'Krym', 'UA10': "Kirovohrads'ka Oblast'", 'UA13': "Kyyivs'ka Oblast'", 'UA12': 'Kyyiv', 'GBV9': 'Orkney', 'UA19': "Rivnens'ka Oblast'", 'UA18': "Poltavs'ka Oblast'", 'GBV8': 'North Lanarkshire', 'GBV5': 'Midlothian', 'GBV4': 'Inverclyde', 'VN09': 'Dong Thap', 'VN01': 'An Giang', 'VN03': 'Ben Tre', 'VN05': 'Cao Bang', 'NG56': 'Nassarawa', 'MV41': 'Meemu', 'MV40': 'Maale', 'MV43': 'Noonu', 'PL80': 'Podkarpackie', 'SI49': 'Komen', 'PL82': 'Pomorskie', 'MV42': 'Gnaviyani', 'PL84': 'Swietokrzyskie', 'PL85': 'Warminsko-Mazurskie', 'PL86': 'Wielkopolskie', 'PL87': 'Zachodniopomorskie', 'SI40': 'Izola-Isola', 'MV45': 'Shaviyani', 'SI42': 'Jursinci', 'SI44': 'Kanal', 'SI45': 'Kidricevo', 'SI46': 'Kobarid', 'MV44': 'Raa', 'MV47': 'Vaavu', 'MV46': 'Thaa', 'GBG2': 'Isle of Wight', 'GBG3': 'Islington', 'GBG1': 'Hounslow', 'GBG6': 'Kingston upon Hull', 'GBG7': 'Kingston upon Thames', 'GBG4': 'Kensington and Chelsea', 'GBG5': 'Kent', 'GBG8': 'Kirklees', 'GBG9': 'Knowsley', 'MKC3': 'Zelino', 'BR13': 'Maranhao', 'BR11': 'Mato Grosso do Sul', 'MKC2': 'Zelenikovo', 'BR17': 'Paraiba', 'BR16': 'Para', 'BR15': 'Minas Gerais', 'BR14': 'Mato Grosso', 'FJ04': 'Rotuma', 'FJ05': 'Western', 'BR18': 'Parana', 'FJ01': 'Central', 'FJ02': 'Eastern', 'FJ03': 'Northern', 'MKC6': 'Zrnovci', 'PH08': 'Batanes', 'PH09': 'Batangas', 'PH04': 'Aklan', 'PH05': 'Albay', 'PH06': 'Antique', 'PH07': 'Bataan', 'PH01': 'Abra', 'PH02': 'Agusan del Norte', 'PH03': 'Agusan del Sur', 'IT03': 'Calabria', 'IT02': 'Basilicata', 'IT01': 'Abruzzi', 'IT07': 'Lazio', 'IT06': 'Friuli-Venezia Giulia', 'IT05': 'Emilia-Romagna', 'IT04': 'Campania', 'IT09': 'Lombardia', 'IT08': 'Liguria', 'PHE3': 'Olongapo', 'PHE2': 'Naga', 'PHE1': 'Marawi', 'PHE7': 'Pagadian', 'PHE6': 'Ozamis', 'PHE5': 'Oroquieta', 'PHE4': 'Ormoc', 'PHE9': 'Pasay', 'PHE8': 'Palayan', 'TH68': 'Songkhla', 'TH69': 'Pattani', 'TH62': 'Phuket', 'TH63': 'Krabi', 'TH60': 'Surat Thani', 'TH61': 'Phangnga', 'TH66': 'Phatthalung', 'TH67': 'Satun', 'TH64': 'Nakhon Si Thammarat', 'TH65': 'Trang', 'MS01': 'Saint Anthony', 'MS02': 'Saint Georges', 'MS03': 'Saint Peter', 'VE24': 'Dependencias Federales', 'SIB3': 'Sentilj', 'DE12': 'Mecklenburg-Vorpommern', 'DE13': 'Sachsen', 'DE10': 'Schleswig-Holstein', 'DE11': 'Brandenburg', 'DE16': 'Berlin', 'DE14': 'Sachsen-Anhalt', 'DE15': 'Thuringen', 'MU20': 'Savanne', 'MU21': 'Agalega Islands', 'MU22': 'Cargados Carajos', 'MU23': 'Rodrigues', 'HN18': 'Yoro', 'HN15': 'Olancho', 'HN14': 'Ocotepeque', 'HN17': 'Valle', 'HN16': 'Santa Barbara', 'HN11': 'Islas de la Bahia', 'HN10': 'Intibuca', 'HN13': 'Lempira', 'HN12': 'La Paz', 'IS35': 'Vestur-Hunavatnssysla', 'IS34': 'Vestur-Bardastrandarsysla', 'IS37': 'Vestur-Skaftafellssysla', 'IS36': 'Vestur-Isafjardarsysla', 'IS31': 'Sudur-Mulasysla', 'IS30': 'Strandasysla', 'IS32': 'Sudur-Tingeyjarsysla', 'HT03': 'Nord-Ouest', 'USFL': 'Florida', 'USFM': 'Federated States of Micronesia', 'ET49': 'Gambela Hizboch', 'ET48': 'Dire Dawa', 'ZW10': 'Harare', 'ET47': 'Binshangul Gumuz', 'ET46': 'Amara', 'ET45': 'Afar', 'ET44': 'Adis Abeba', 'AF18': 'Nangarhar', 'AF19': 'Nimruz', 'AF17': 'Lowgar', 'AF14': 'Kapisa', 'AF13': 'Kabol', 'AF10': 'Helmand', 'AF11': 'Herat', 'GBZ1': 'Swansea', 'GBZ3': 'Vale of Glamorgan', 'GBZ2': 'Torfaen', 'GBZ4': 'Wrexham', 'AO08': 'Huambo', 'AO09': 'Huila', 'AO01': 'Benguela', 'AO02': 'Bie', 'AO03': 'Cabinda', 'AO04': 'Cuando Cubango', 'AO05': 'Cuanza Norte', 'AO06': 'Cuanza Sul', 'AO07': 'Cunene', 'TO03': 'Vava', 'NP08': 'Lumbini', 'NP09': 'Mahakali', 'NP06': 'Karnali', 'NP07': 'Kosi', 'NP04': 'Gandaki', 'NP05': 'Janakpur', 'NP02': 'Bheri', 'NP03': 'Dhawalagiri', 'NP01': 'Bagmati', 'VN13': 'Hai Phong', 'UG84': 'Kitgum', 'UG85': 'Kyenjojo', 'UG86': 'Mayuge', 'UG87': 'Mbale', 'UG80': 'Kaberamaido', 'UG81': 'Kamwenge', 'UG82': 'Kanungu', 'UG83': 'Kayunga', 'UG88': 'Moroto', 'UG89': 'Mpigi', 'SI53': 'Kranjska Gora', 'SI52': 'Kranj', 'SI51': 'Kozje', 'SI50': 'Koper-Capodistria', 'SI57': 'Lasko', 'SI55': 'Kungota', 'SI54': 'Krsko', 'GBF9': 'Hillingdon', 'GBF8': 'Hertford', 'EE08': 'Laane-Virumaa', 'EE09': 'Narva', 'GBF5': 'Hartlepool', 'GBF4': 'Harrow', 'GBF7': 'Herefordshire', 'GBF6': 'Havering', 'GBF1': 'Hammersmith and Fulham', 'EE03': 'Ida-Virumaa', 'GBF3': 'Haringey', 'GBF2': 'Hampshire', 'BR28': 'Sergipe', 'BR29': 'Goias', 'BR26': 'Santa Catarina', 'BR27': 'Sao Paulo', 'BR24': 'Rondonia', 'BR25': 'Roraima', 'BR22': 'Rio Grande do Norte', 'BR23': 'Rio Grande do Sul', 'BR20': 'Piaui', 'BR21': 'Rio de Janeiro', 'SI76': 'Mislinja', 'PH19': 'Catanduanes', 'PH18': 'Capiz', 'PH17': 'Camiguin', 'PH16': 'Camarines Sur', 'PH15': 'Camarines Norte', 'PH14': 'Cagayan', 'PH13': 'Bulacan', 'PH12': 'Bukidnon', 'PH11': 'Bohol', 'PH10': 'Benguet', 'US08': 'Colorado', 'US09': 'Connecticut', 'CH25': 'Zurich', 'CH24': 'Zug', 'CH23': 'Vaud', 'CH22': 'Valais', 'CH21': 'Uri', 'CH20': 'Ticino', 'US01': 'Alabama', 'US02': 'Alaska', 'US04': 'Arizona', 'US05': 'Arkansas', 'US06': 'California', 'NA25': 'Kavango', 'PHF8': 'Silay', 'PHF9': 'Surigao', 'PHF6': 'San Jose', 'PHF7': 'San Pablo', 'PHF4': 'San Carlos', 'PHF5': 'San Carlos', 'PHF2': 'Quezon City', 'PHF3': 'Roxas', 'PHF1': 'Puerto Princesa', 'LA02': 'Champasak', 'NA21': 'Windhoek', 'USGA': 'Georgia', 'NA20': 'Karasburg', 'NA23': 'Hereroland Oos', 'USGU': 'Guam', 'BT06': 'Chhukha', 'BT07': 'Chirang', 'BT05': 'Bumthang', 'BT08': 'Daga', 'BT09': 'Geylegphug', 'KZ14': 'Qyzylorda', 'KZ15': 'East Kazakhstan', 'KZ16': 'North Kazakhstan', 'KZ17': 'Zhambyl', 'KZ10': 'South Kazakhstan', 'KZ11': 'Pavlodar', 'KZ12': 'Qaraghandy', 'KZ13': 'Qostanay', 'LU02': 'Grevenmacher', 'PHC8': 'Iligan', 'TH75': 'Ubon Ratchathani', 'IS41': 'Norourland Vestra', 'IS42': 'Suourland', 'IS43': 'Suournes', 'TH71': 'Ubon Ratchathani', 'TH70': 'Yala', 'TH73': 'Nakhon Phanom', 'TH72': 'Yasothon', 'TH79': 'Nong Bua Lamphu', 'TH78': 'Mukdahan', 'ZW05': 'Mashonaland West', 'ZW04': 'Mashonaland East', 'ZW07': 'Matabeleland South', 'ZW06': 'Matabeleland North', 'ZW01': 'Manicaland', 'ZW03': 'Mashonaland Central', 'ZW02': 'Midlands', 'ZW09': 'Bulawayo', 'ZW08': 'Masvingo', 'FM02': 'Pohnpei', 'FM01': 'Kosrae', 'DE05': 'Hessen', 'IS17': 'Myrasysla', 'DE07': 'Nordrhein-Westfalen', 'DE06': 'Niedersachsen', 'DE01': 'Baden-Wurttemberg', 'DE03': 'Bremen', 'DE02': 'Bayern', 'NR08': 'Denigomodu', 'DE09': 'Saarland', 'TH46': 'Chon Buri', 'NR09': 'Ewa', 'AF09': 'Ghowr', 'SC20': 'Pointe La Rue', 'SC21': 'Port Glaud', 'AF01': 'Badakhshan', 'IE03': 'Clare', 'AF03': 'Baghlan', 'IE01': 'Carlow', 'AF05': 'Bamian', 'IE07': 'Dublin', 'AF07': 'Faryab', 'AF06': 'Farah', 'VN39': 'Lang Son', 'TH43': 'Nakhon Nayok', 'AO19': 'Bengo', 'AO18': 'Lunda Sul', 'AO13': 'Namibe', 'AO12': 'Malanje', 'AO17': 'Lunda Norte', 'AO16': 'Zaire', 'AO15': 'Uige', 'AO14': 'Moxico', 'TW04': "T'ai-wan", 'TW03': "T'ai-pei", 'TW02': 'Kao-hsiung', 'TW01': 'Fu-chien', 'NP11': 'Narayani', 'NP10': 'Mechi', 'NP13': 'Sagarmatha', 'NP12': 'Rapti', 'NP14': 'Seti', 'EG05': 'Al Gharbiyah', 'SIA7': 'Rogaska Slatina', 'SIA6': 'Rogasovci', 'SIA3': 'Radovljica', 'SIA2': 'Radlje ob Dravi', 'SIA1': 'Radenci', 'SIA8': 'Rogatec', 'CAMB': 'Manitoba', 'EG03': 'Al Buhayrah', 'JP46': 'Yamanashi', 'JM15': 'Trelawny', 'JP44': 'Yamagata', 'JP45': 'Yamaguchi', 'JM10': 'Saint Catherine', 'JP43': 'Wakayama', 'JP40': 'Tokyo', 'JM13': 'Saint Mary', 'UG97': 'Yumbe', 'UG96': 'Wakiso', 'UG95': 'Soroti', 'UG94': 'Sironko', 'UG93': 'Rukungiri', 'UG92': 'Pader', 'UG91': 'Nakapiripirit', 'SI61': 'Ljubljana', 'SI68': 'Lukovica', 'EE19': 'Valgamaa', 'EE18': 'Tartumaa', 'VN24': 'Long An', 'VN23': 'Lam Dong', 'VN20': 'Ho Chi Minh', 'VN21': 'Kien Giang', 'EE11': 'Parnumaa', 'GBA1': 'Barking and Dagenham', 'EE13': 'Raplamaa', 'EE12': 'Polvamaa', 'EE15': 'Sillamae', 'EE14': 'Saaremaa', 'EE17': 'Tartu', 'EE16': 'Tallinn', 'BR31': 'Tocantins', 'BR30': 'Pernambuco', 'IR43': 'Khorasan-e Shemali', 'PH28': 'Ilocos Norte', 'RUCI': 'Chechnya Republic', 'PH22': 'Basilan', 'PH23': 'Eastern Samar', 'PH20': 'Cavite', 'PH21': 'Cebu', 'PH26': 'Davao Oriental', 'PH27': 'Ifugao', 'PH24': 'Davao', 'PH25': 'Davao del Sur', 'CH12': 'Neuchatel', 'CH13': 'Nidwalden', 'US19': 'Iowa', 'US18': 'Indiana', 'CH16': 'Schaffhausen', 'CH17': 'Schwyz', 'CH14': 'Obwalden', 'CH15': 'Sankt Gallen', 'US13': 'Georgia', 'US12': 'Florida', 'CH18': 'Solothurn', 'US10': 'Delaware', 'US17': 'Illinois', 'US16': 'Idaho', 'US15': 'Hawaii', 'PHG8': 'Aurora', 'PHG1': 'Tacloban', 'PHG3': 'Tagbilaran', 'PHG2': 'Tagaytay', 'PHG5': 'Toledo', 'PHG4': 'Tangub', 'PHG7': 'Zamboanga', 'PHG6': 'Trece Martires', 'BT11': 'Lhuntshi', 'BT10': 'Ha', 'BT13': 'Paro', 'BT12': 'Mongar', 'BT15': 'Punakha', 'BT14': 'Pemagatsel', 'BT17': 'Samdrup', 'BT16': 'Samchi', 'BT19': 'Tashigang', 'BT18': 'Shemgang', 'KZ07': 'West Kazakhstan', 'KZ06': 'Atyrau', 'KZ05': 'Astana', 'KZ04': 'Aqtobe', 'KZ03': 'Aqmola', 'KZ02': 'Almaty City', 'KZ01': 'Almaty', 'KZ09': 'Mangghystau', 'KZ08': 'Bayqonyr', 'KR19': 'Taejon-jikhalsi', 'TH01': 'Mae Hong Son', 'TH02': 'Chiang Mai', 'TH03': 'Chiang Rai', 'TH04': 'Nan', 'TH05': 'Lamphun', 'TH06': 'Lampang', 'TH07': 'Phrae', 'TH08': 'Tak', 'TH09': 'Sukhothai', 'FM04': 'Yap', 'TN28': 'Madanin', 'TN29': 'Gabes', 'TN22': 'Siliana', 'TN23': 'Sousse', 'TN27': 'Ben Arous', 'UG52': 'Mbarara', 'DK18': 'Midtjylland', 'DK19': 'Nordjylland', 'DK17': 'Hovedstaden', 'UG50': 'Masindi', 'DZ24': 'Jijel', 'DZ25': 'Laghouat', 'NG50': 'Rivers', 'NG51': 'Sokoto', 'DZ20': 'Blida', 'CH08': 'Glarus', 'NG54': 'Ekiti', 'NG55': 'Gombe', 'IE15': 'Laois', 'IE14': 'Leitrim', 'IE16': 'Limerick', 'IE11': 'Kerry', 'IE10': 'Galway', 'IE13': 'Kilkenny', 'IE12': 'Kildare', 'IE19': 'Louth', 'IE18': 'Longford', 'SIB2': 'Sencur', 'HT09': 'Nord', 'SIB1': 'Semic', 'SIB6': 'Sevnica', 'SIB7': 'Sezana', 'SIB4': 'Sentjernej', 'USDE': 'Delaware', 'SIB8': 'Skocjan', 'SIB9': 'Skofja Loka', 'HT06': 'Artibonite', 'HT07': 'Centre', 'LR21': 'Gbarpolu', 'JM09': 'Saint Ann', 'JM08': 'Saint Andrew', 'JM07': 'Portland', 'JM04': 'Manchester', 'JM02': 'Hanover', 'JM01': 'Clarendon', 'AO20': 'Luanda', 'SI71': 'Medvode', 'VN80': 'Ha Nam', 'SI73': 'Metlika', 'SI72': 'Menges', 'SI74': 'Mezica', 'SI77': 'Moravce', 'VN81': 'Hung Yen', 'SI79': 'Mozirje', 'SI78': 'Moravske Toplice', 'VN82': 'Nam Dinh', 'GBO9': 'Waltham Forest', 'VN84': 'Quang Nam', 'LU01': 'Diekirch', 'LU03': 'Luxembourg', 'VN85': 'Thai Nguyen', 'VN86': 'Vinh Puc Province', 'VN87': 'Can Tho', 'FM03': 'Chuuk', 'VN30': 'Quang Ninh', 'VN33': 'Tay Ninh', 'VN32': 'Son La', 'VN35': 'Thai Binh', 'VN34': 'Thanh Hoa', 'VN37': 'Tien Giang', 'VN89': 'Lai Chau', 'NR04': 'Anibare', 'NR05': 'Baiti', 'NR06': 'Boe', 'NR07': 'Buada', 'NR01': 'Aiwo', 'NR02': 'Anabar', 'NR03': 'Anetan', 'EG08': 'Al Jizah', 'EG09': 'Al Minufiyah', 'EG04': 'Al Fayyum', 'GBO6': 'Trafford', 'EG06': 'Al Iskandariyah', 'EG07': "Al Isma'iliyah", 'EG01': 'Ad Daqahliyah', 'EG02': 'Al Bahr al Ahmar', 'GBO7': 'Wakefield', 'PH35': 'Lanao del Sur', 'PH34': 'Lanao del Norte', 'PH37': 'Leyte', 'PH36': 'La Union', 'PH31': 'Isabela', 'PH30': 'Iloilo', 'PH33': 'Laguna', 'PH32': 'Kalinga-Apayao', 'PH39': 'Masbate', 'PH38': 'Marinduque', 'US26': 'Michigan', 'US27': 'Minnesota', 'US24': 'Maryland', 'US25': 'Massachusetts', 'US22': 'Louisiana', 'US23': 'Maine', 'US20': 'Kansas', 'US21': 'Kentucky', 'US28': 'Mississippi', 'US29': 'Missouri', 'NG52': 'Bayelsa', 'NG53': 'Ebonyi', 'DZ26': 'Mascara', 'DZ27': "M'sila", 'CH09': 'Graubunden', 'DZ21': 'Bouira', 'DZ22': 'Djelfa', 'DZ23': 'Guelma', 'CH05': 'Bern', 'CH04': 'Basel-Stadt', 'CH07': 'Geneve', 'CH06': 'Fribourg', 'CH01': 'Aargau', 'DZ29': 'Oum el Bouaghi', 'CH03': 'Basel-Landschaft', 'CH02': 'Ausser-Rhoden', 'VE08': 'Cojedes', 'USAK': 'Alaska', 'USAL': 'Alabama', 'USAA': 'Armed Forces Americas', 'USAE': 'Armed Forces Europe', 'USAZ': 'Arizona', 'USAS': 'American Samoa', 'USAR': 'Arkansas', 'USAP': 'Armed Forces Pacific', 'ES51': 'Andalucia', 'MU13': 'Flacq', 'MU12': 'Black River', 'MU15': 'Moka', 'MU14': 'Grand Port', 'MU17': 'Plaines Wilhems', 'MU16': 'Pamplemousses', 'MU19': 'Riviere du Rempart', 'MU18': 'Port Louis', 'TH13': 'Phichit', 'TH12': 'Phitsanulok', 'TH11': 'Kamphaeng Phet', 'TH10': 'Uttaradit', 'TH17': 'Nong Khai', 'TH16': 'Nakhon Sawan', 'TH15': 'Uthai Thani', 'TH14': 'Phetchabun', 'TH18': 'Loei', 'TN39': 'Manouba', 'TN38': 'Aiana', 'TN33': 'Sidi Bou Zid', 'TN32': 'Sfax', 'TN31': 'Kebili', 'TN37': 'Zaghouan', 'TN36': 'Tunis', 'TN35': 'Tozeur', 'TN34': 'Tataouine', 'TG25': 'Plateaux', 'TG24': 'Maritime', 'TG26': 'Savanes', 'TG23': 'Kara', 'TG22': 'Centrale', 'NG25': 'Anambra', 'YE24': 'Lahij', 'YE25': 'Ta', 'YE20': "Al Bayda'", 'YE21': 'Al Jawf', 'YE22': 'Hajjah', 'YE23': 'Ibb', 'TR58': 'Sivas', 'CZ52': 'Hlavni mesto Praha', 'MM08': 'Mandalay', 'MM09': 'Pegu', 'MM06': 'Kayah State', 'MM07': 'Magwe', 'MM04': 'Kachin State', 'MM05': 'Karan State', 'MM02': 'Chin State', 'MM03': 'Irrawaddy', 'MM01': 'Rakhine State', 'VE06': 'Bolivar', 'RS01': 'Kosovo', 'RS02': 'Vojvodina', 'SIC9': 'Store', 'SIC8': 'Starse', 'SIC5': 'Smarje pri Jelsah', 'SIC4': 'Slovenske Konjice', 'SIC7': 'Sostanj', 'SIC6': 'Smartno ob Paki', 'SIC1': 'Skofljica', 'HT15': 'Nippes', 'TR54': 'Sakarya', 'TO01': 'Ha', 'GBX7': 'Carmarthenshire', 'SE08': 'Jonkopings Lan', 'SE09': 'Kalmar Lan', 'AR24': 'Tucuman', 'AR23': 'Tierra del Fuego', 'AR22': 'Santiago del Estero', 'AR21': 'Santa Fe', 'AR20': 'Santa Cruz', 'SE02': 'Blekinge Lan', 'SE03': 'Gavleborgs Lan', 'SE05': 'Gotlands Lan', 'SE06': 'Hallands Lan', 'SE07': 'Jamtlands Lan', 'SI88': 'Osilnica', 'SI89': 'Pesnica', 'SI84': 'Nova Gorica', 'SI86': 'Odranci', 'SI87': 'Ormoz', 'SI80': 'Murska Sobota', 'SI81': 'Muta', 'SI82': 'Naklo', 'SI83': 'Nazarje', 'GBC6': 'Cornwall', 'GBC7': 'Coventry', 'GBC4': 'Camden', 'GBC5': 'Cheshire', 'GBC2': 'Calderdale', 'GBC3': 'Cambridgeshire', 'GBC1': 'Bury', 'MD58': 'Stinga Nistrului', 'MD59': 'Anenii Noi', 'GBC8': 'Croydon', 'GBC9': 'Cumbria', 'NR14': 'Yaren', 'NR13': 'Uaboe', 'NR12': 'Nibok', 'NR11': 'Meneng', 'NR10': 'Ijuw', 'EG19': "Bur Sa'id", 'EG18': 'Bani Suwayf', 'EG17': 'Asyut', 'EG16': 'Aswan', 'EG15': 'As Suways', 'EG14': 'Ash Sharqiyah', 'EG13': 'Al Wadi al Jadid', 'EG12': 'Al Qalyubiyah', 'EG11': 'Al Qahirah', 'EG10': 'Al Minya', 'ZA10': 'North-West', 'PH41': 'Mindoro Oriental', 'PH42': 'Misamis Occidental', 'PH43': 'Misamis Oriental', 'PH44': 'Mountain', 'PH45': 'Negros Occidental', 'PH46': 'Negros Oriental', 'PH47': 'Nueva Ecija', 'PH48': 'Nueva Vizcaya', 'PH49': 'Palawan', 'JO12': 'At Tafilah', 'JO13': 'Az Zarqa', 'JO10': 'Al Mafraq', 'JO11': 'Amman Governorate', 'JO16': 'Amman', 'JO14': 'Irbid', 'NG05': 'Lagos', 'US31': 'Nebraska', 'US30': 'Montana', 'US33': 'New Hampshire', 'US32': 'Nevada', 'US35': 'New Mexico', 'US34': 'New Jersey', 'US37': 'North Carolina', 'US36': 'New York', 'US39': 'Ohio', 'US38': 'North Dakota', 'DZ37': 'Annaba', 'DZ36': 'Ain Temouchent', 'DZ35': 'Ain Defla', 'DZ34': 'Adrar', 'DZ33': 'Tebessa', 'NG48': 'Ondo', 'DZ31': 'Skikda', 'DZ30': 'Sidi Bel Abbes', 'NG45': 'Abia', 'NG44': 'Yobe', 'NG47': 'Enugu', 'NG46': 'Bauchi', 'NG41': 'Kogi', 'NG40': 'Kebbi', 'DZ39': 'Bordj Bou Arreridj', 'DZ38': 'Bechar', 'CL01': 'Valparaiso', 'CL03': 'Antofagasta', 'CL05': 'Atacama', 'CL07': 'Coquimbo', 'AE05': 'Ras Al Khaimah', 'BO05': 'Oruro', 'BO04': 'La Paz', 'BO07': 'Potosi', 'BO06': 'Pando', 'BO01': 'Chuquisaca', 'TH28': 'Buriram', 'TH29': 'Surin', 'TH26': 'Chaiyaphum', 'TH27': 'Nakhon Ratchasima', 'TH24': 'Maha Sarakham', 'TH25': 'Roi Et', 'TH22': 'Khon Kaen', 'TH23': 'Kalasin', 'TH20': 'Sakon Nakhon', 'TH21': 'Nakhon Phanom', 'TN06': 'Jendouba', 'TN02': 'Kasserine', 'TN03': 'Kairouan', 'SIL3': 'Ruse', 'NA27': 'Namaland', 'MV37': 'Haa Dhaalu', 'MW04': 'Chitipa', 'MW05': 'Thyolo', 'MW06': 'Dedza', 'MW07': 'Dowa', 'MW02': 'Chikwawa', 'MW03': 'Chiradzulu', 'MW08': 'Karonga', 'MW09': 'Kasungu', 'TR82': 'Cankiri', 'TR83': 'Gaziantep', 'TR80': 'Sirnak', 'TR81': 'Adana', 'TR86': 'Ardahan', 'TR87': 'Bartin', 'TR84': 'Kars', 'TR85': 'Zonguldak', 'TR88': 'Igdir', 'TR89': 'Karabuk', 'SD44': 'Central Equatoria State', 'MM11': 'Shan State', 'MM10': 'Sagaing', 'MM13': 'Mon State', 'MM12': 'Tenasserim', 'MM14': 'Rangoon', 'MM17': 'Yangon', 'BF15': 'Bam', 'BF19': 'Boulkiemde', 'NG37': 'Edo', 'SL01': 'Eastern', 'SL03': 'Southern', 'SL02': 'Northern', 'SL04': 'Western Area', 'SID8': 'Velike Lasce', 'SID1': 'Sveti Jurij', 'SID2': 'Tolmin', 'SID3': 'Trbovlje', 'SID4': 'Trebnje', 'SID5': 'Trzic', 'SID6': 'Turnisce', 'SID7': 'Velenje', 'DZ51': 'Relizane', 'AR12': 'La Rioja', 'AR13': 'Mendoza', 'AR10': 'Jujuy', 'AR11': 'La Pampa', 'AR16': 'Rio Negro', 'AR17': 'Salta', 'LY61': 'Tarabulus', 'AR15': 'Neuquen', 'SE12': 'Kronobergs Lan', 'AR18': 'San Juan', 'AR19': 'San Luis', 'SE16': 'Ostergotlands Lan', 'SE15': 'Orebro Lan', 'SE14': 'Norrbottens Lan', 'SI99': 'Radece', 'SI98': 'Racam', 'SI97': 'Puconci', 'SI94': 'Postojna', 'SI92': 'Podcetrtek', 'SI91': 'Pivka', 'VN70': 'Quang Binh', 'GBB1': 'Bolton', 'GBB3': 'Bracknell Forest', 'GBB2': 'Bournemouth', 'GBB5': 'Brent', 'GBB4': 'Bradford', 'GBB7': 'Bristol', 'GBB6': 'Brighton and Hove', 'GBB9': 'Buckinghamshire', 'GBB8': 'Bromley', 'RU18': 'Evenk', 'RU19': 'Ingush', 'RU14': 'Chita', 'RU15': 'Chukot', 'RU16': 'Chuvashia', 'RU17': 'Dagestan', 'RU10': 'Bryansk', 'RU11': 'Buryat', 'RU12': 'Chechnya', 'RU13': 'Chelyabinsk', 'EG22': 'Matruh', 'EG23': 'Qina', 'EG20': 'Dumyat', 'EG21': 'Kafr ash Shaykh', 'EG26': "Janub Sina'", 'EG27': "Shamal Sina'", 'EG24': 'Suhaj', 'ZA03': 'Free State', 'ZA02': 'KwaZulu-Natal', 'ZA01': 'North-Western Province', 'PH50': 'Pampanga', 'PH57': 'North Cotabato', 'PH56': 'Maguindanao', 'PH55': 'Samar', 'PH54': 'Romblon', 'ZA09': 'Limpopo', 'ZA08': 'Northern Cape', 'JO09': 'Al Karak', 'JO07': 'Ma', 'JO02': "Al Balqa'", 'TZ22': 'Zanzibar North', 'RO28': 'Neamt', 'AZ38': 'Qabala', 'AZ39': 'Qax', 'AZ34': 'Naftalan', 'AZ35': 'Naxcivan', 'AZ36': 'Neftcala', 'AZ37': 'Oguz', 'AZ30': 'Lankaran', 'AZ31': 'Lerik', 'AZ32': 'Masalli', 'JP10': 'Gumma', 'DZ03': 'Batna', 'DZ01': 'Alger', 'DZ06': 'Medea', 'DZ07': 'Mostaganem', 'DZ04': 'Constantine', 'VC05': 'Saint Patrick', 'VC04': 'Saint George', 'NG32': 'Oyo', 'VC06': 'Grenadines', 'VC01': 'Charlotte', 'NG35': 'Adamawa', 'VC03': 'Saint David', 'VC02': 'Saint Andrew', 'USCT': 'Connecticut', 'IL06': 'Yerushalayim', 'USCA': 'California', 'USCO': 'Colorado', 'ZA07': 'Mpumalanga', 'ZA06': 'Gauteng', 'ZA05': 'Eastern Cape', 'TH39': 'Pathum Thani', 'TH38': 'Nonthaburi', 'TH31': 'Narathiwat', 'TH30': 'Sisaket', 'TH33': 'Sing Buri', 'TH32': 'Chai Nat', 'TH35': 'Ang Thong', 'TH34': 'Lop Buri', 'TH37': 'Saraburi', 'TH36': 'Phra Nakhon Si Ayutthaya', 'TN10': 'Qafsah', 'TN15': 'Al Mahdia', 'VN53': 'Ba Ria-Vung Tau', 'TN17': 'Bajah', 'TN16': 'Al Munastir', 'TN19': 'Nabeul', 'TN18': 'Bizerte', 'LC10': 'Vieux-Fort', 'LC11': 'Praslin', 'DK21': 'Syddanmark', 'DK20': 'Sjelland', 'MW17': 'Nkhata Bay', 'MW16': 'Ntcheu', 'MW15': 'Mzimba', 'MW13': 'Mchinji', 'MW12': 'Mangochi', 'MW11': 'Lilongwe', 'MW19': 'Nsanje', 'MW18': 'Nkhotakota', 'TR91': 'Osmaniye', 'TR90': 'Kilis', 'TR93': 'Duzce', 'TR92': 'Yalova', 'YE08': 'Al Hudaydah', 'YE02': 'Adan', 'YE03': 'Al Mahrah', 'YE01': 'Abyan', 'YE06': 'Al Ghaydah', 'YE04': 'Hadramawt', 'YE05': 'Shabwah', 'CZ78': 'Jihomoravsky kraj', 'CZ79': 'Jihocesky kraj', 'BF20': 'Ganzourgou', 'BF21': 'Gnagna', 'BF28': 'Kouritenga', 'GBQ1': 'Wirral', 'SIE9': 'Zavrc', 'SIE3': 'Vodice', 'SIE2': 'Vitanje', 'SIE1': 'Vipava', 'SIE7': 'Zagorje ob Savi', 'SIE6': 'Vuzenica', 'SIE5': 'Vrhnika', 'SE26': 'Stockholms Lan', 'SE27': 'Skane Lan', 'SE24': 'Vasternorrlands Lan', 'SE25': 'Vastmanlands Lan', 'SE22': 'Varmlands Lan', 'SE23': 'Vasterbottens Lan', 'SE21': 'Uppsala Lan', 'SE28': 'Vastra Gotaland', 'LY52': 'Awbari', 'LY53': 'Az Zawiyah', 'LY50': 'Al Khums', 'LY51': 'An Nuqat al Khams', 'AR09': 'Formosa', 'AR08': 'Entre Rios', 'LY54': 'Banghazi', 'LY55': 'Darnah', 'AR05': 'Cordoba', 'AR04': 'Chubut', 'AR07': 'Distrito Federal', 'AR06': 'Corrientes', 'AR01': 'Buenos Aires', 'AR03': 'Chaco', 'AR02': 'Catamarca', 'NE03': 'Dosso', 'NE02': 'Diffa', 'NE01': 'Agadez', 'CA08': 'Ontario', 'CA09': 'Prince Edward Island', 'LR22': 'River Gee', 'NE04': 'Maradi', 'CA04': 'New Brunswick', 'CA05': 'Newfoundland and Labrador', 'CA07': 'Nova Scotia', 'CA01': 'Alberta', 'CA02': 'British Columbia', 'CA03': 'Manitoba', 'GBD7': 'Dudley', 'GBM8': 'Southwark', 'GBM9': 'Staffordshire', 'MD78': 'Ialoveni', 'EE21': 'Vorumaa', 'GBM4': 'Southampton', 'GBM5': 'Southend-on-Sea', 'GBM6': 'South Gloucestershire', 'GBM7': 'South Tyneside', 'MD72': 'Dubasari', 'GBM1': 'Slough', 'GBM2': 'Solihull', 'GBM3': 'Somerset', 'RU09': 'Belgorod', 'RU08': 'Bashkortostan', 'RU07': "Astrakhan'", 'RU06': "Arkhangel'sk", 'RU05': 'Amur', 'RU04': 'Altaisky krai', 'RU03': 'Gorno-Altay', 'RU02': 'Aginsky Buryatsky AO', 'RU01': 'Adygeya', 'PH68': 'Quirino', 'PH69': 'Siquijor', 'PH66': 'Zamboanga del Sur', 'PH67': 'Northern Samar', 'PH64': 'Zambales', 'PH65': 'Zamboanga del Norte', 'PH62': 'Surigao del Sur', 'PH63': 'Tarlac', 'PH60': 'Sulu', 'PH61': 'Surigao del Norte', 'CO24': 'Risaralda', 'CO25': 'San Andres y Providencia', 'CO26': 'Santander', 'CO27': 'Sucre', 'CO20': 'Narino', 'CO21': 'Norte de Santander', 'AZ29': 'Lankaran', 'AZ28': 'Lacin', 'AZ27': 'Kurdamir', 'AZ26': 'Kalbacar', 'AZ25': 'Ismayilli', 'AZ24': 'Imisli', 'AZ23': 'Haciqabul', 'AZ22': 'Goycay', 'AZ21': 'Goranboy', 'AZ20': 'Ganca', 'NG29': 'Kano', 'NG28': 'Imo', 'DZ19': 'Biskra', 'DZ18': 'Bejaia', 'DZ15': 'Tlemcen', 'DZ14': 'Tizi Ouzou', 'NG21': 'Akwa Ibom', 'NG27': 'Borno', 'DZ10': 'Saida', 'DZ13': 'Tiaret', 'DZ12': 'Setif', 'NA05': 'Grootfontein', 'FI14': 'Eastern Finland', 'FI15': 'Western Finland', 'FI13': 'Southern Finland', 'VU10': 'Malakula', 'VU11': 'Paama', 'VU12': 'Pentecote', 'VU13': 'Sanma', 'VU14': 'Shepherd', 'VU15': 'Tafea', 'VU16': 'Malampa', 'VU17': 'Penama', 'NG57': 'Zamfara', 'HT13': 'Sud-Est', 'HT12': 'Sud', 'HT11': 'Ouest', 'HT10': 'Nord-Est', 'BA02': 'Republika Srpska', 'BA01': 'Federation of Bosnia and Herzegovina', 'SIC2': 'Slovenj Gradec', 'USLA': 'Louisiana', 'LC09': 'Soufriere', 'LC08': 'Micoud', 'LC03': 'Castries', 'LC02': 'Dauphin', 'LC01': 'Anse-la-Raye', 'LC07': 'Laborie', 'LC06': 'Gros-Islet', 'LC05': 'Dennery', 'LC04': 'Choiseul', 'ES57': 'Extremadura', 'MW23': 'Zomba', 'MW20': 'Ntchisi', 'MW21': 'Rumphi', 'ES53': 'Canarias', 'MW27': 'Likoma', 'MW24': 'Blantyre', 'MW25': 'Mwanza', 'MW28': 'Machinga', 'MW29': 'Mulanje', 'ES59': 'Pais Vasco', 'ES58': 'Galicia', 'YE15': 'Sa', 'YE14': "Ma'rib", 'YE16': 'San', 'YE11': 'Dhamar', 'YE10': 'Al Mahwit', 'MN19': 'Uvs', 'UG29': 'Bushenyi', 'BF34': 'Passore', 'BF36': 'Sanguie', 'BF33': 'Oudalan', 'MN13': 'Hovsgol', 'AL50': 'Tirane', 'AL51': 'Vlore', 'HR20': 'Zagrebacka', 'HR21': 'Grad Zagreb', 'LY49': 'Al Jabal al Akhdar', 'LY48': 'Al Fatih', 'LY45': 'Zlitan', 'LY47': 'Ajdabiya', 'LY41': 'Tarhunah', 'LY42': 'Tubruq', 'CA14': 'Nunavut', 'CA13': 'Northwest Territories', 'CA12': 'Yukon Territory', 'CA11': 'Saskatchewan', 'CA10': 'Quebec', 'FR99': 'Basse-Normandie', 'FR98': 'Auvergne', 'FR97': 'Aquitaine', 'MD69': 'Criuleni', 'MD68': 'Cimislia', 'GBL9': 'Sheffield', 'GBL8': 'Sefton', 'GBL7': 'Sandwell', 'GBL6': 'Shropshire', 'GBL5': 'Salford', 'GBL4': 'Rutland', 'GBL3': 'Rotherham', 'GBL2': 'Rochdale', 'GBL1': 'Richmond upon Thames', 'MD66': 'Calarasi', 'RU38': 'Krasnodar', 'RU39': 'Krasnoyarsk', 'SIF2': 'Ziri', 'SIF3': 'Zrece', 'SIF1': 'Zelezniki', 'RU32': 'Khanty-Mansiy', 'RU33': 'Kirov', 'RU30': 'Khabarovsk', 'RU31': 'Khakass', 'RU36': 'Koryak', 'RU37': 'Kostroma', 'RU34': 'Komi', 'RU35': 'Komi-Permyak', 'RW12': 'Kigali', 'RW13': 'Nord', 'RW11': 'Est', 'RW14': 'Ouest', 'RW15': 'Sud', 'BO08': 'Santa Cruz', 'MO01': 'Ilhas', 'PH71': 'Sultan Kudarat', 'PH70': 'South Cotabato', 'PH72': 'Tawitawi', 'CO37': 'Caldas', 'CO36': 'Boyaca', 'CO35': 'Bolivar', 'CO34': 'Distrito Especial', 'CO33': 'Cundinamarca', 'CO32': 'Casanare', 'CO31': 'Vichada', 'CO30': 'Vaupes', 'AZ12': 'Beylaqan', 'AZ13': 'Bilasuvar', 'AZ10': 'Balakan', 'AZ11': 'Barda', 'AZ16': 'Daskasan', 'AZ17': 'Davaci', 'AZ14': 'Cabrayil', 'AZ15': 'Calilabad', 'WS02': 'Aiga-i-le-Tai', 'WS03': 'Atua', 'WS06': 'Va', 'WS07': 'Gagaifomauga', 'WS04': 'Fa', 'WS05': 'Gaga', 'WS08': 'Palauli', 'WS09': 'Satupa', 'USMT': 'Montana', 'USMS': 'Mississippi', 'USMP': 'Northern Mariana Islands', 'USMO': 'Missouri', 'FI06': 'Lapland', 'FI01': 'Aland', 'USMH': 'Marshall Islands', 'USME': 'Maine', 'USMD': 'Maryland', 'USMA': 'Massachusetts', 'FI08': 'Oulu', 'PK07': 'Northern Areas', 'PK06': 'Azad Kashmir', 'PK05': 'Sindh', 'PK04': 'Punjab', 'RO38': 'Vaslui', 'RO39': 'Valcea', 'PK01': 'Federally Administered Tribal Areas', 'RO34': 'Suceava', 'RO35': 'Teleorman', 'RO36': 'Timis', 'RO37': 'Tulcea', 'RO30': 'Prahova', 'RO31': 'Salaj', 'RO32': 'Satu Mare', 'RO33': 'Sibiu', 'IR38': 'Qazvin', 'IR39': 'Qom', 'MD51': 'Gagauzia', 'IR34': 'Markazi', 'IR35': 'Mazandaran', 'IR36': 'Zanjan', 'IR37': 'Golestan', 'IR30': 'Khorasan', 'IR31': 'Yazd', 'IR32': 'Ardabil', 'IR33': 'East Azarbaijan', 'MD57': 'Chisinau', 'BB02': 'Saint Andrew', 'BB03': 'Saint George', 'NO20': 'Vestfold', 'BB06': 'Saint Joseph', 'BB07': 'Saint Lucy', 'BB08': 'Saint Michael', 'BB09': 'Saint Peter', 'IS20': 'Nordur-Mulasysla', 'IS21': 'Nordur-Tingeyjarsysla', 'BF59': 'Koulpelogo', 'ES60': 'Comunidad Valenciana', 'MK47': 'Konce', 'MW30': 'Phalombe', 'MK48': 'Kondovo', 'MK49': 'Konopiste', 'BF48': 'Bougouriba', 'BF49': 'Boulgou', 'SC22': 'Saint Louis', 'SC23': 'Takamaka', 'BF40': 'Soum', 'BF42': 'Tapoa', 'BF44': 'Zoundweogo', 'BF45': 'Bale', 'BF46': 'Banwa', 'BF47': 'Bazega', 'AL49': 'Shkoder', 'AL48': 'Lezhe', 'AL47': 'Kukes', 'AL46': 'Korce', 'AL45': 'Gjirokaster', 'AL44': 'Fier', 'AL43': 'Elbasan', 'AL42': 'Durres', 'AL41': 'Diber', 'AL40': 'Berat', 'LK10': 'Kandy', 'LK11': 'Kegalla', 'LK12': 'Kurunegala', 'LK14': 'Matale', 'LK15': 'Matara', 'LK16': 'Moneragala', 'LK17': 'Nuwara Eliya', 'LK18': 'Polonnaruwa', 'LK19': 'Puttalam', 'LV18': 'Limbazu', 'CF11': 'Ouaka', 'CF12': 'Ouham', 'CF13': 'Ouham-Pende', 'CF14': 'Cuvette-Ouest', 'CF15': 'Nana-Grebizi', 'CF16': 'Sangha-Mbaere', 'CF17': 'Ombella-Mpoko', 'CF18': 'Bangui', 'LY30': 'Murzuq', 'LY34': 'Sabha', 'LR01': 'Bong', 'LR06': 'Maryland', 'LR07': 'Monrovia', 'LR04': 'Grand Cape Mount', 'LR05': 'Lofa', 'LR09': 'Nimba', 'CANB': 'New Brunswick', 'RU25': 'Kaluga', 'RU24': 'Kalmyk', 'GBO8': 'Walsall', 'VN83': 'Phu Tho', 'RU21': 'Ivanovo', 'RU20': 'Irkutsk', 'RU23': 'Kaliningrad', 'RU22': 'Kabardin-Balkar', 'GBO2': 'Telford and Wrekin', 'GBO3': 'Thurrock', 'GBO1': 'Tameside', 'RU29': 'Kemerovo', 'RU28': 'Karelia', 'GBO4': 'Torbay', 'GBO5': 'Tower Hamlets', 'SIG4': 'Dobrova-Horjul-Polhov Gradec', 'SIG7': 'Domzale', 'CANL': 'Newfoundland', 'PH40': 'Mindoro Occidental', 'RW09': 'Kigali', 'ZA11': 'Western Cape', 'RW07': 'Kibungo', 'RW06': 'Gitarama', 'RW01': 'Butare', 'GA01': 'Estuaire', 'GA02': 'Haut-Ogooue', 'GA03': 'Moyen-Ogooue', 'GA04': 'Ngounie', 'GA05': 'Nyanga', 'GA06': 'Ogooue-Ivindo', 'GA07': 'Ogooue-Lolo', 'GA08': 'Ogooue-Maritime', 'GA09': 'Woleu-Ntem', 'TT08': 'Saint George', 'TT09': 'Saint Patrick', 'TT04': 'Nariva', 'TT05': 'Port-of-Spain', 'TT06': 'Saint Andrew', 'TT07': 'Saint David', 'TT01': 'Arima', 'TT02': 'Caroni', 'TT03': 'Mayaro', 'CANS': 'Nova Scotia', 'AZ05': 'Agstafa', 'AZ04': 'Agdas', 'AZ07': 'Ali Bayramli', 'AZ06': 'Agsu', 'AZ01': 'Abseron', 'AZ03': 'Agdam', 'AZ02': 'Agcabadi', 'AZ09': 'Baki', 'AZ08': 'Astara', 'CO02': 'Antioquia', 'CO03': 'Arauca', 'CO01': 'Amazonas', 'CO06': 'Boyaca Department', 'CO07': 'Caldas Department', 'CO04': 'Atlantico', 'CO05': 'Bolivar Department', 'CO08': 'Caqueta', 'CO09': 'Cauca', 'WS11': 'Vaisigano', 'WS10': 'Tuamasaga', 'GQ03': 'Annobon', 'GQ04': 'Bioko Norte', 'GQ05': 'Bioko Sur', 'GQ06': 'Centro Sur', 'GQ07': 'Kie-Ntem', 'GQ08': 'Litoral', 'GQ09': 'Wele-Nzas', 'TZ24': 'Rukwa', 'TZ25': 'Zanzibar Urban', 'TZ26': 'Arusha', 'TZ27': 'Manyara', 'TZ20': 'Pemba South', 'TZ21': 'Zanzibar Central', 'RO29': 'Olt', 'TZ23': 'Dar es Salaam', 'RO27': 'Mures', 'RO26': 'Mehedinti', 'RO25': 'Maramures', 'RO23': 'Iasi', 'RO22': 'Ialomita', 'RO21': 'Hunedoara', 'RO20': 'Harghita', 'IR29': 'Kerman', 'IR28': 'Esfahan', 'IR27': 'Zanjan', 'IR26': 'Tehran', 'IR25': 'Semnan', 'IR24': 'Markazi', 'IR23': 'Lorestan', 'IR22': 'Bushehr', 'IR21': 'Zanjan', 'LY56': 'Ghadamis', 'USNY': 'New York', 'USNV': 'Nevada', 'USNJ': 'New Jersey', 'USNH': 'New Hampshire', 'USNM': 'New Mexico', 'USNC': 'North Carolina', 'USND': 'North Dakota', 'USNE': 'Nebraska', 'VU18': 'Shefa', 'NO18': 'Troms', 'NO19': 'Vest-Agder', 'NO16': 'Sor-Trondelag', 'NO17': 'Telemark', 'NO14': 'Rogaland', 'NO15': 'Sogn og Fjordane', 'NO12': 'Oslo', 'NO13': 'Ostfold', 'NO10': 'Nord-Trondelag', 'NO11': 'Oppland', 'NG49': 'Plateau', 'MK44': 'Kisela Voda', 'MK45': 'Klecevce', 'MK46': 'Kocani', 'BF58': 'Kossi', 'MK40': 'Karbinci', 'MK41': 'Karpos', 'MK42': 'Kavadarci', 'MK43': 'Kicevo', 'BF53': 'Kadiogo', 'BF52': 'Ioba', 'BF51': 'Houet', 'BF50': 'Gourma', 'BF57': 'Kompienga', 'BF56': 'Komondjari', 'BF55': 'Komoe', 'BF54': 'Kenedougou', 'BY03': "Hrodzyenskaya Voblasts'", 'BY02': "Homyel'skaya Voblasts'", 'BY01': "Brestskaya Voblasts'", 'BY07': "Vitsyebskaya Voblasts'", 'BY06': "Mahilyowskaya Voblasts'", 'BY05': "Minskaya Voblasts'", 'BY04': 'Minsk', 'LK03': 'Badulla', 'LK02': 'Anuradhapura', 'LK01': 'Amparai', 'LK07': 'Hambantota', 'LK06': 'Galle', 'LK04': 'Batticaloa', 'LK09': 'Kalutara', 'CANT': 'Northwest Territories', 'CANU': 'Nunavut', 'PSGZ': 'Gaza', 'NG43': 'Taraba', 'NG42': 'Osun', 'CF03': 'Haute-Kotto', 'CF02': 'Basse-Kotto', 'CF01': 'Bamingui-Bangoran', 'CF07': 'Lobaye', 'CF06': 'Kemo', 'CF05': 'Haut-Mbomou', 'CF04': 'Mambere-Kadei', 'CF09': 'Nana-Mambere', 'CF08': 'Mbomou', 'KI01': 'Gilbert Islands', 'KI02': 'Line Islands', 'KI03': 'Phoenix Islands', 'HR08': 'Licko-Senjska', 'HR09': 'Medimurska', 'HR06': 'Koprivnicko-Krizevacka', 'HR07': 'Krapinsko-Zagorska', 'HR04': 'Istarska', 'HR05': 'Karlovacka', 'HR02': 'Brodsko-Posavska', 'HR03': 'Dubrovacko-Neretvanska', 'HR01': 'Bjelovarsko-Bilogorska', 'RU50': 'Nenets', 'LR19': 'Grand Gedeh', 'LR18': 'River Cess', 'VN92': 'Dien Bien', 'LR14': 'Montserrado', 'LR17': 'Margibi', 'LR11': 'Grand Bassa', 'LR10': 'Sino', 'LR13': 'Maryland', 'LR12': 'Grand Cape Mount', 'GBN5': 'Suffolk', 'GBN4': 'Stoke-on-Trent', 'GBN7': 'Surrey', 'GBN6': 'Sunderland', 'GBN1': 'St. Helens', 'GBN3': 'Stockton-on-Tees', 'GBN2': 'Stockport', 'GBN9': 'Swindon', 'GBN8': 'Sutton', 'VN93': 'Hau Giang', 'RU51': 'Nizhegorod', 'VN91': 'Dak Nong', 'VN90': 'Lao Cai', 'RU54': 'Omsk', 'RU55': 'Orenburg', 'RU56': 'Orel', 'RU57': 'Penza', 'RU58': "Perm'", 'RU59': "Primor'ye", 'SIH4': 'Jesenice', 'SIH6': 'Kamnik', 'SIH7': 'Kocevje', 'SH01': 'Ascension', 'SH03': 'Tristan da Cunha', 'SH02': 'Saint Helena', 'LI22': 'River Gee', 'LI21': 'Gbarpolu', 'TT12': 'Victoria', 'TT11': 'Tobago', 'TT10': 'San Fernando', 'AZ70': 'Zaqatala', 'AZ71': 'Zardab', 'BS30': 'Kemps Bay', 'BS31': 'Marsh Harbour', 'BS32': 'Nichollstown and Berry Islands', 'BS33': 'Rock Sound', 'CO19': 'Meta', 'DZ43': 'El Oued', 'DZ40': 'Boumerdes', 'DZ41': 'Chlef', 'CO15': 'Guainia', 'CO14': 'Guaviare', 'CO17': 'La Guajira', 'CO16': 'Huila', 'CO11': 'Choco', 'CO10': 'Cesar', 'DZ48': 'Mila', 'DZ49': 'Naama', 'USOH': 'Ohio', 'USOK': 'Oklahoma', 'RO18': 'Galati', 'RO19': 'Gorj', 'USOR': 'Oregon', 'RO12': 'Caras-Severin', 'RO13': 'Cluj', 'RO10': 'Bucuresti', 'RO11': 'Buzau', 'RO16': 'Dambovita', 'RO17': 'Dolj', 'RO14': 'Constanta', 'RO15': 'Covasna', 'IR18': 'Semnan Province', 'IR19': 'Markazi', 'IR12': 'Kerman', 'IR13': 'Bakhtaran', 'IR10': 'Ilam', 'IR11': 'Hormozgan', 'IR16': 'Kordestan', 'IR17': 'Mazandaran', 'IR15': 'Khuzestan', 'NA14': 'Outjo', 'NA15': 'Owambo', 'NA16': 'Rehoboth', 'NA17': 'Swakopmund', 'NA10': 'Maltahohe', 'NA11': 'Okahandja', 'NA12': 'Omaruru', 'NA13': 'Otjiwarongo', 'NA18': 'Tsumeb', 'VE09': 'Delta Amacuro', 'BH08': 'Al Mintaqah al Gharbiyah', 'BH09': 'Mintaqat Juzur Hawar', 'BH02': 'Al Manamah', 'BH01': 'Al Hadd', 'BH06': 'Sitrah', 'BH05': 'Jidd Hafs', 'BD86': 'Sylhet', 'BD84': 'Chittagong', 'BD85': 'Barisal', 'BD82': 'Khulna', 'BD83': 'Rajshahi', 'BD81': 'Dhaka', 'AF26': 'Takhar', 'NO09': 'Nordland', 'NO08': 'More og Romsdal', 'VU09': 'Epi', 'VU08': 'Efate', 'NO01': 'Akershus', 'VE07': 'Carabobo', 'NO02': 'Aust-Agder', 'NO05': 'Finnmark', 'NO04': 'Buskerud', 'NO07': 'Hordaland', 'NO06': 'Hedmark', 'KN13': 'Saint Thomas Middle Island', 'AF29': 'Paktika', 'AF28': 'Zabol', 'ES07': 'Islas Baleares', 'SY04': 'Ar Raqqah', 'SY05': "As Suwayda'", 'SY06': 'Dar', 'SY07': 'Dayr az Zawr', 'SY01': 'Al Hasakah', 'SY02': 'Al Ladhiqiyah', 'SY03': 'Al Qunaytirah', 'SY08': 'Rif Dimashq', 'SY09': 'Halab', 'BF66': 'Nayala', 'BF67': 'Noumbiel', 'BF64': 'Namentenga', 'BF65': 'Naouri', 'BF62': 'Loroum', 'BF63': 'Mouhoun', 'BF60': 'Kourweogo', 'BF61': 'Leraba', 'BF68': 'Oubritenga', 'BF69': 'Poni', 'MK57': 'Kumanovo', 'MK56': 'Kukurecani', 'MK55': 'Kuklis', 'MK54': 'Krusevo', 'MK53': 'Krivogastani', 'MK52': 'Kriva Palanka', 'MK51': 'Kratovo', 'SC09': 'Bel Air', 'SC06': 'Baie Lazare', 'SC07': 'Baie Sainte Anne', 'SC04': 'Anse Louis', 'SC05': 'Anse Royale', 'SC02': 'Anse Boileau', 'SC03': 'Anse Etoile', 'MK59': 'Lipkovo', 'MK58': 'Labunista', 'LK36': 'Western', 'LK34': 'Southern', 'LK35': 'Uva', 'LK32': 'North Western', 'LK33': 'Sabaragamuwa', 'LK30': 'North Central', 'LK31': 'Northern', 'AM11': 'Yerevan', 'LY13': "Ash Shati'", 'HR19': 'Zadarska', 'HR18': 'Vukovarsko-Srijemska', 'HR11': 'Pozesko-Slavonska', 'HR10': 'Osjecko-Baranjska', 'HR13': 'Sibensko-Kninska', 'HR12': 'Primorsko-Goranska', 'HR15': 'Splitsko-Dalmatinska', 'HR14': 'Sisacko-Moslavacka', 'HR17': 'Viroviticko-Podravska', 'HR16': 'Varazdinska', 'GBI1': 'Luton', 'GBI2': 'Manchester', 'GBI3': 'Medway', 'GBI4': 'Merton', 'GBI5': 'Middlesbrough', 'GBI6': 'Milton Keynes', 'GBI7': 'Newcastle upon Tyne', 'GBI8': 'Newham', 'GBI9': 'Norfolk', 'RU43': 'Lipetsk', 'ID10': 'Yogyakarta', 'RU41': 'Kursk', 'RU40': 'Kurgan', 'RU47': 'Moskva', 'RU46': 'Mordovia', 'RU45': 'Mariy-El', 'RU44': 'Magadan', 'RU49': 'Murmansk', 'RU48': 'Moscow City', 'ID12': 'Kalimantan Selatan', 'ID13': 'Kalimantan Tengah', 'SII9': 'Luce', 'SII7': 'Loska Dolina', 'SII6': 'Ljutomer', 'SII5': 'Litija', 'SII3': 'Lenart', 'SII2': 'Kuzma', 'CAON': 'Ontario', 'LI10': 'Triesenberg', 'LI11': 'Vaduz', 'DZ46': 'Illizi', 'DZ47': 'Khenchela', 'DZ44': 'El Tarf', 'DZ45': 'Ghardaia', 'CD12': 'Sud-Kivu', 'CD10': 'Maniema', 'CD11': 'Nord-Kivu', 'DZ42': 'El Bayadh', 'BS35': 'San Salvador and Rum Cay', 'AZ63': 'Xizi', 'SV10': 'San Salvador', 'AZ61': 'Xankandi', 'AZ60': 'Xacmaz', 'AZ67': 'Yevlax', 'AZ66': 'Yardimli', 'AZ65': 'Xocavand', 'AZ64': 'Xocali', 'AZ69': 'Zangilan', 'AZ68': 'Yevlax', 'SV12': 'San Vicente', 'BS23': 'New Providence', 'BS22': 'Harbour Island', 'DZ53': 'Tamanghasset', 'DZ52': 'Souk Ahras', 'BS27': "Governor's Harbour", 'BS26': 'Fresh Creek', 'BS25': 'Freeport', 'BS24': 'Acklins and Crooked Islands', 'BS29': 'High Rock', 'BS28': 'Green Turtle Cay', 'CO12': 'Cordoba', 'BO03': 'El Beni', 'GBU8': 'Edinburgh', 'BO02': 'Cochabamba', 'GBU9': 'Falkirk', 'RO05': 'Bihor', 'RO04': 'Bacau', 'RO07': 'Botosani', 'MY09': 'Pulau Pinang', 'RO01': 'Alba', 'RO03': 'Arges', 'RO02': 'Arad', 'MY02': 'Kedah', 'MY03': 'Kelantan', 'MY01': 'Johor', 'MY06': 'Pahang', 'MY07': 'Perak', 'MY04': 'Melaka', 'MY05': 'Negeri Sembilan', 'TZ02': 'Pwani', 'TZ03': 'Dodoma', 'TZ06': 'Kilimanjaro', 'TZ07': 'Lindi', 'TZ04': 'Iringa', 'TZ05': 'Kigoma', 'TZ08': 'Mara', 'TZ09': 'Mbeya', 'BH15': 'Al Muharraq', 'NA06': 'Kaokoland', 'AT09': 'Wien', 'NA04': 'Gobabis', 'BH11': 'Al Mintaqah al Wusta', 'BH10': 'Al Mintaqah ash Shamaliyah', 'NA01': 'Bethanien', 'BH12': 'Madinat', 'AT03': 'Niederosterreich', 'AT02': 'Karnten', 'AT01': 'Burgenland', 'BH19': 'Al Wusta', 'BH18': 'Ash Shamaliyah', 'AT05': 'Salzburg', 'NA08': 'Keetmanshoop', 'GW06': 'Cacheu', 'GW07': 'Tombali', 'GW04': 'Oio', 'GW05': 'Bolama', 'GR50': 'Khios', 'GR51': 'Lesvos', 'GW01': 'Bafata', 'USHI': 'Hawaii', 'IR05': 'Kohkiluyeh va Buyer Ahmadi', 'IR04': 'Sistan va Baluchestan', 'IR07': 'Fars', 'IR01': 'Azarbayjan-e Bakhtari', 'IR03': 'Chahar Mahall va Bakhtiari', 'IR09': 'Hamadan', 'IR08': 'Gilan', 'TR28': 'Giresun', 'TR24': 'Erzincan', 'TR25': 'Erzurum', 'TR26': 'Eskisehir', 'TR20': 'Denizli', 'TR21': 'Diyarbakir', 'TR22': 'Edirne', 'TR23': 'Elazig', 'SI47': 'Kobilje', 'SY14': 'Tartus', 'SY13': 'Dimashq', 'SY12': 'Idlib', 'SY11': 'Hims', 'SY10': 'Hamah', 'ID41': 'Sulawesi Barat', 'ID40': 'Kepulauan Riau', 'BF71': 'Seno', 'BF70': 'Sanmatenga', 'BF73': 'Sourou', 'BF72': 'Sissili', 'BF75': 'Yagha', 'BF74': 'Tuy', 'BF77': 'Ziro', 'BF76': 'Yatenga', 'DO14': 'Maria Trinidad Sanchez', 'DO15': 'Monte Cristi', 'DO16': 'Pedernales', 'DO17': 'Peravia', 'DO10': 'La Altagracia', 'DO11': 'Elias Pina', 'DO12': 'La Romana', 'MK62': 'Makedonska Kamenica', 'MK63': 'Makedonski Brod', 'MK60': 'Lozovo', 'MK61': 'Lukovo', 'MK66': 'Miravci', 'MK67': 'Mogila', 'MK64': 'Mavrovi Anovi', 'MK65': 'Meseista', 'SC11': 'Cascade', 'SC10': 'Bel Ombre', 'MK68': 'Murtino', 'MK69': 'Negotino', 'SC15': 'La Digue', 'SC14': "Grand' Anse", 'SC17': 'Mont Buxton', 'SC16': 'La Riviere Anglaise', 'NI18': 'Region Autonoma Atlantico Sur', 'NI14': 'Rio San Juan', 'NI15': 'Rivas', 'NI16': 'Zelaya', 'NI17': 'Autonoma Atlantico Norte', 'NI10': 'Managua', 'NI11': 'Masaya', 'NI12': 'Matagalpa', 'NI13': 'Nueva Segovia', 'LK29': 'Central', 'LK28': 'Vavuniya', 'LK21': 'Trincomalee', 'LK20': 'Ratnapura', 'LK23': 'Colombo', 'LK25': 'Jaffna', 'LK24': 'Gampaha', 'LK27': 'Mullaittivu', 'LK26': 'Mannar', 'CM04': 'Est', 'CM05': 'Littoral', 'LY03': 'Al Aziziyah', 'LY05': 'Al Jufrah', 'LY08': 'Al Kufrah', 'SO05': 'Galguduud', 'GBH3': 'Leeds', 'GBH2': 'Lancashire', 'GBH1': 'Lambeth', 'GBH7': 'Lincolnshire', 'GBH6': 'Lewisham', 'GBH5': 'Leicestershire', 'GBH4': 'Leicester', 'GBH9': 'London', 'GBH8': 'Liverpool', 'RU78': "Tyumen'", 'RU79': 'Tuva', 'RU76': 'Tula', 'RU77': "Tver'", 'RU74': 'Taymyr', 'RU75': 'Tomsk', 'RU72': 'Tambovskaya oblast', 'RU73': 'Tatarstan', 'RU70': "Stavropol'", 'RU71': 'Sverdlovsk', 'SIJ9': 'Piran', 'SIJ2': 'Maribor', 'SIJ1': 'Majsperk', 'SIJ7': 'Novo Mesto', 'SIJ5': 'Miren-Kostanjevica', 'LI01': 'Balzers', 'AE03': 'Dubai', 'LI03': 'Gamprin', 'LI02': 'Eschen', 'LI05': 'Planken', 'LI04': 'Mauren', 'LI07': 'Schaan', 'LI06': 'Ruggell', 'LI09': 'Triesen', 'LI08': 'Schellenberg', 'KG02': 'Chuy', 'KG03': 'Jalal-Abad', 'UG28': 'Bundibugyo', 'CD02': 'Equateur', 'KG06': 'Talas', 'KG07': 'Ysyk-Kol', 'KG04': 'Naryn', 'KG05': 'Osh', 'CD09': 'Orientale', 'CD08': 'Bas-Congo', 'KG08': 'Osh', 'KG09': 'Batken', 'UG26': 'Apac', 'AZ58': 'Tovuz', 'AZ59': 'Ucar', 'AZ56': 'Susa', 'AZ57': 'Tartar', 'AZ54': 'Sumqayit', 'AZ55': 'Susa', 'AZ52': 'Samux', 'AZ53': 'Siyazan', 'AZ50': 'Samaxi', 'AZ51': 'Samkir', 'MC03': 'Monte-Carlo', 'BS18': 'Ragged Island', 'BS16': 'Mayaguana', 'BS15': 'Long Island', 'BS13': 'Inagua', 'BS10': 'Exuma', 'KY07': 'West End', 'MO02': 'Macau', 'MY15': 'Labuan', 'MY14': 'Kuala Lumpur', 'MY17': 'Putrajaya', 'MY16': 'Sabah', 'MY11': 'Sarawak', 'MY13': 'Terengganu', 'MY12': 'Selangor', 'USIA': 'Iowa', 'USID': 'Idaho', 'USIN': 'Indiana', 'USIL': 'Illinois', 'PH53': 'Rizal', 'TZ19': 'Kagera', 'TZ18': 'Tanga', 'TZ15': 'Shinyanga', 'TZ14': 'Ruvuma', 'TZ17': 'Tabora', 'TZ16': 'Singida', 'TZ11': 'Mtwara', 'TZ10': 'Morogoro', 'TZ13': 'Pemba North', 'TZ12': 'Mwanza', 'NA32': 'Kunene', 'NA33': 'Ohangwena', 'NA30': 'Hardap', 'NA31': 'Karas', 'NA36': 'Omusati', 'NA37': 'Oshana', 'NA34': 'Okavango', 'NA35': 'Omaheke', 'LA17': 'Louangphrabang', 'NA38': 'Oshikoto', 'NA39': 'Otjozondjupa', 'LA13': 'Xaignabouri', 'LA10': 'Savannakhet', 'LA11': 'Vientiane', 'BJ08': 'Atakora', 'BJ09': 'Atlanyique', 'BJ07': 'Alibori', 'GW11': 'Bissau', 'GW10': 'Gabu', 'GR45': 'Iraklion', 'GW12': 'Biombo', 'GR43': 'Khania', 'GR42': 'Lakonia', 'GR41': 'Arkadhia', 'GR40': 'Messinia', 'GR49': 'Kikladhes', 'GR48': 'Samos', 'USVI': 'Virgin Islands', 'CO18': 'Magdalena Department', 'ES27': 'La Rioja', 'ES29': 'Madrid', 'TR39': 'Kirklareli', 'TR38': 'Kayseri', 'TR37': 'Kastamonu', 'TR35': 'Izmir', 'TR34': 'Istanbul', 'TR33': 'Isparta', 'TR32': 'Mersin', 'TR31': 'Hatay', 'PL81': 'Podlaskie', 'PL83': 'Slaskie', 'NZE9': 'Canterbury', 'NZE8': 'Bay of Plenty', 'NZE7': 'Auckland', 'DO09': 'Independencia', 'DO08': 'Espaillat', 'TH56': 'Phetchaburi', 'DO06': 'Duarte', 'DO05': 'Distrito Nacional', 'DO04': 'Dajabon', 'DO03': 'Barahona', 'DO02': 'Baoruco', 'DO01': 'Azua', 'MK79': 'Petrovec', 'MK78': 'Pehcevo', 'MK75': 'Orasac', 'MK74': 'Ohrid', 'MK77': 'Oslomej', 'MK76': 'Orizari', 'MK71': 'Novaci', 'MK70': 'Negotino-Polosko', 'MK73': 'Oblesevo', 'MK72': 'Novo Selo', 'RU52': 'Novgorod', 'NI09': 'Madriz', 'NI08': 'Leon', 'NI07': 'Jinotega', 'NI06': 'Granada', 'NI05': 'Esteli', 'NI04': 'Chontales', 'NI03': 'Chinandega', 'NI02': 'Carazo', 'NI01': 'Boaco', 'RU53': 'Novosibirsk', 'IQ03': 'Al Muthanna', 'HU41': 'Salgotarjan', 'HU40': 'Zalaegerszeg', 'HU43': 'Erd', 'HU42': 'Szekszard', 'GBK8': 'Redbridge', 'GBK9': 'Redcar and Cleveland', 'GBK6': 'Portsmouth', 'GBK7': 'Reading', 'GBK4': 'Plymouth', 'GBK5': 'Poole', 'GBK2': 'Oxfordshire', 'GBK3': 'Peterborough', 'GBK1': 'Oldham', 'RU69': 'Smolensk', 'RU68': 'North Ossetia', 'SIK7': 'Ptuj', 'RU61': 'Rostov', 'RU60': 'Pskov', 'RU63': 'Sakha', 'RU62': "Ryazan'", 'RU65': 'Samara', 'RU64': 'Sakhalin', 'RU67': 'Saratov', 'RU66': 'Saint Petersburg City', 'SA08': 'Al Qasim', 'SA09': 'Al Qurayyat', 'SA05': 'Al Madinah', 'SA06': 'Ash Sharqiyah', 'SA02': 'Al Bahah', 'SA03': 'Al Jawf', 'SO20': 'Woqooyi Galbeed', 'SO21': 'Awdal', 'SO22': 'Sool', 'CAAB': 'Alberta', 'UG37': 'Kampala', 'UG36': 'Kalangala', 'UG31': 'Hoima', 'UG30': 'Gulu', 'UG33': 'Jinja', 'UG39': 'Kapchorwa', 'UG38': 'Kamuli', 'AZ49': 'Salyan', 'AZ48': 'Saki', 'AZ41': 'Qobustan', 'AZ40': 'Qazax', 'AZ43': 'Qubadli', 'AZ42': 'Quba', 'AZ45': 'Saatli', 'AZ44': 'Qusar', 'AZ47': 'Saki', 'AZ46': 'Sabirabad', 'BS05': 'Bimini', 'BS06': 'Cat Island', 'MA46': 'Fes-Boulemane', 'MA47': 'Marrakech-Tensift-Al Haouz', 'MA45': 'Grand Casablanca', 'MA48': 'Meknes-Tafilalet', 'MA49': 'Rabat-Sale-Zemmour-Zaer', 'VU07': 'Torba', 'VU06': 'Aoba', 'VU05': 'Ambrym', 'LA09': 'Saravan', 'LA08': 'Phongsali', 'NA29': 'Erongo', 'NA28': 'Caprivi', 'LA01': 'Attapu', 'NA24': 'Hereroland Wes', 'LA03': 'Houaphan', 'NA26': 'Mariental', 'LA05': 'Louang Namtha', 'LA04': 'Khammouan', 'LA07': 'Oudomxai', 'NA22': 'Damaraland', 'MR12': 'Inchiri', 'MR10': 'Guidimaka', 'MR11': 'Tiris Zemmour', 'BJ18': 'Zou', 'BJ13': 'Donga', 'BJ12': 'Kouffo', 'BJ11': 'Collines', 'BJ10': 'Borgou', 'BJ17': 'Plateau', 'BJ16': 'Oueme', 'BJ15': 'Mono', 'BJ14': 'Littoral', 'CU08': 'Cienfuegos', 'CU09': 'Granma', 'CU01': 'Pinar del Rio', 'CU02': 'Ciudad de la Habana', 'CU03': 'Matanzas', 'CU04': 'Isla de la Juventud', 'CU05': 'Camaguey', 'CU07': 'Ciego de Avila', 'GE04': 'Ajaria', 'GE05': 'Akhalgoris Raioni', 'GE06': "Akhalk'alak'is Raioni", 'GE07': "Akhalts'ikhis Raioni", 'GE01': 'Abashis Raioni', 'GE02': 'Abkhazia', 'GE03': 'Adigenis Raioni', 'GE08': 'Akhmetis Raioni', 'GE09': 'Ambrolauris Raioni', 'ES31': 'Murcia', 'ES32': 'Navarra', 'ES34': 'Asturias', 'ES39': 'Cantabria', 'TR08': 'Artvin', 'TR09': 'Aydin', 'TR02': 'Adiyaman', 'TR03': 'Afyonkarahisar', 'TR07': 'Antalya', 'TR04': 'Agri', 'TR05': 'Amasya', 'USMI': 'Michigan', 'DO32': 'Monte Plata', 'DO33': 'San Cristobal', 'DO30': 'La Vega', 'DO31': 'Monsenor Nouel', 'DO36': 'San Jose de Ocoa', 'DO37': 'Santo Domingo', 'DO34': 'Distrito Nacional', 'DO35': 'Peravia', 'MK08': 'Bogdanci', 'MK09': 'Bogomila', 'MK01': 'Aracinovo', 'MK02': 'Bac', 'MK03': 'Belcista', 'MK04': 'Berovo', 'MK05': 'Bistrica', 'MK06': 'Bitola', 'MK07': 'Blatec', 'CABC': 'British Columbia', 'RU27': 'Karachay-Cherkess', 'NZF6': 'Northland', 'NZF7': 'Otago', 'NZF4': 'Marlborough', 'NZF5': 'Nelson', 'NZF2': "Hawke's Bay", 'NZF3': 'Manawatu-Wanganui', 'NZF1': 'Gisborne', 'VN46': 'Dong Thap', 'NZF8': 'Southland', 'NZF9': 'Taranaki', 'HU38': 'Tatabanya', 'HU39': 'Veszprem', 'AR14': 'Misiones', 'HU30': 'Kaposvar', 'HU31': 'Kecskemet', 'HU32': 'Nagykanizsa', 'HU33': 'Nyiregyhaza', 'HU34': 'Sopron', 'HU35': 'Szekesfehervar', 'HU36': 'Szolnok', 'HU37': 'Szombathely', 'GBJ9': 'Nottinghamshire', 'GBJ8': 'Nottingham', 'GBJ1': 'Northamptonshire', 'GBJ3': 'North Lincolnshire', 'GBJ2': 'North East Lincolnshire', 'GBJ5': 'North Tyneside', 'GBJ4': 'North Somerset', 'GBJ7': 'North Yorkshire', 'GBJ6': 'Northumberland', 'SIL1': 'Ribnica', 'DM10': 'Saint Paul', 'DM11': 'Saint Peter', 'SIL7': 'Sentjur pri Celju', 'SIL8': 'Slovenska Bistrica', 'SA19': 'Tabuk', 'SA17': 'Jizan', 'SA16': 'Najran', 'SA15': 'Al Hudud ash Shamaliyah', 'SA14': 'Makkah', 'SA13': "Ha'il", 'SD40': 'Al Wahadah State', 'SA10': 'Ar Riyad', 'UG40': 'Kasese', 'UG41': 'Kibale', 'UG42': 'Kiboga', 'UG43': 'Kisoro', 'UG45': 'Kotido', 'UG46': 'Kumi', 'UG47': 'Lira', 'CL12': 'Region Metropolitana', 'MA51': 'Doukkala-Abda', 'MA50': 'Chaouia-Ouardigha', 'MA53': 'Guelmim-Es Smara', 'MA52': 'Gharb-Chrarda-Beni Hssen', 'MA55': 'Souss-Massa-Dr', 'MA54': 'Oriental', 'MA57': 'Tanger-Tetouan', 'MA56': 'Tadla-Azilal', 'MA59': 'La', 'MA58': 'Taza-Al Hoceima-Taounate', 'CL13': 'Tarapaca', 'USKY': 'Kentucky', 'USKS': 'Kansas', 'MR09': 'Tagant', 'MR08': 'Dakhlet Nouadhibou', 'MR01': 'Hodh Ech Chargui', 'MR03': 'Assaba', 'MR02': 'Hodh El Gharbi', 'MR05': 'Brakna', 'MR04': 'Gorgol', 'MR07': 'Adrar', 'MR06': 'Trarza', 'BB11': 'Saint Thomas', 'BB10': 'Saint Philip', 'CU13': 'Las Tunas', 'CU12': 'Holguin', 'CU11': 'La Habana', 'CU10': 'Guantanamo', 'CU16': 'Villa Clara', 'CU15': 'Santiago de Cuba', 'CU14': 'Sancti Spiritus', 'GE17': "Dedop'listsqaros Raioni", 'GE16': "Ch'okhatauris Raioni", 'GE15': "Ch'khorotsqus Raioni", 'GE14': "Chiat'ura", 'GE13': 'Borjomis Raioni', 'GE12': 'Bolnisis Raioni', 'GE11': "Baghdat'is Raioni", 'GE10': 'Aspindzis Raioni', 'GE19': "Dushet'is Raioni", 'GE18': 'Dmanisis Raioni', 'TR15': 'Burdur', 'TR14': 'Bolu', 'TR17': 'Canakkale', 'TR16': 'Bursa', 'TR11': 'Bilecik', 'TR10': 'Balikesir', 'TR13': 'Bitlis', 'TR12': 'Bingol', 'TR19': 'Corum', 'BE10': 'Brabant Wallon', 'BE11': 'Brussels Hoofdstedelijk Gewest', 'BE12': 'Vlaams-Brabant', 'SC08': 'Beau Vallon', 'USTN': 'Tennessee', 'MK50': 'Kosel', 'DO25': 'Santiago', 'DO24': 'San Pedro De Macoris', 'DO27': 'Valverde', 'DO26': 'Santiago Rodriguez', 'DO21': 'Sanchez Ramirez', 'DO20': 'Samana', 'DO23': 'San Juan', 'DO29': 'Hato Mayor', 'DO28': 'El Seibo', 'SC01': 'Anse aux Pins', 'MK19': 'Cesinovo', 'MK18': 'Centar Zupa', 'MK13': 'Cair', 'MK12': 'Brvenica', 'MK11': 'Bosilovo', 'MK10': 'Bogovinje', 'MK17': 'Centar', 'MK16': 'Cegrane', 'MK15': 'Caska', 'MK14': 'Capari', 'BG33': 'Mikhaylovgrad', 'BG38': 'Blagoevgrad', 'BG39': 'Burgas', 'NZG1': 'Waikato', 'ID11': 'Kalimantan Barat', 'NZG3': 'West Coast', 'NZG2': 'Wellington', 'ID14': 'Kalimantan Timur', 'ID15': 'Lampung', 'ID16': 'Maluku', 'ID17': 'Nusa Tenggara Barat', 'ID18': 'Nusa Tenggara Timur', 'ID19': 'Riau', 'GBU4': 'East Ayrshire', 'SV11': 'Santa Ana', 'HU29': 'Hodmezovasarhely', 'SV13': 'Sonsonate', 'SV14': 'Usulutan', 'GBU1': 'Clackmannanshire', 'GBU2': 'Dumfries and Galloway', 'GBU3': 'Dundee City', 'HU23': 'Veszprem', 'HU22': 'Vas', 'HU21': 'Tolna', 'HU20': 'Jasz-Nagykun-Szolnok', 'HU27': 'Dunaujvaros', 'HU26': 'Bekescsaba', 'HU25': 'Gyor', 'HU24': 'Zala', 'MKC4': 'Zitose', 'DM09': 'Saint Patrick', 'DM08': 'Saint Mark', 'DM05': 'Saint John', 'DM04': 'Saint George', 'DM07': 'Saint Luke', 'DM06': 'Saint Joseph', 'DM03': 'Saint David', 'DM02': 'Saint Andrew', 'SD30': 'Ash Shamaliyah', 'SD31': 'Ash Sharqiyah', 'SA20': 'Al Jawf', 'SD33': 'Darfur', 'SD34': 'Kurdufan', 'SD35': 'Upper Nile', 'SO02': 'Banaadir', 'SO03': 'Bari', 'SO01': 'Bakool', 'SO06': 'Gedo', 'SO07': 'Hiiraan', 'SO04': 'Bay', 'CM07': 'Nord-Ouest', 'CM08': 'Ouest', 'CM09': 'Sud-Ouest', 'SO08': 'Jubbada Dhexe', 'SO09': 'Jubbada Hoose', 'PH51': 'Pangasinan', 'LV28': 'Talsu', 'LV29': 'Tukuma', 'LV20': 'Madonas', 'LV21': 'Ogres', 'LV22': 'Preilu', 'LV23': 'Rezekne', 'LV24': 'Rezeknes', 'LV25': 'Riga', 'LV26': 'Rigas', 'LV27': 'Saldus', 'MC01': 'La Condamine', 'MC02': 'Monaco', 'IR42': 'Khorasan-e Razavi', 'UG56': 'Mubende', 'UG59': 'Ntungamo', 'UG58': 'Nebbi', 'PH59': 'Southern Leyte', 'PH58': 'Sorsogon', 'PG18': 'Sandaun', 'PG19': 'Enga', 'PG10': 'East New Britain', 'PG11': 'East Sepik', 'PG12': 'Madang', 'PG13': 'Manus', 'PG14': 'Morobe', 'PG15': 'New Ireland', 'PG16': 'Western Highlands', 'PG17': 'West New Britain', 'RO41': 'Calarasi', 'RO40': 'Vrancea', 'RO43': 'Ilfov', 'RO42': 'Giurgiu', 'GR18': 'Thesprotia', 'GR19': 'Preveza', 'GR10': 'Grevena', 'GR11': 'Kozani', 'GR12': 'Imathia', 'GR13': 'Thessaloniki', 'GR14': 'Kavala', 'GR15': 'Khalkidhiki', 'GR16': 'Pieria', 'GR17': 'Ioannina', 'USTX': 'Texas', 'GE22': 'Goris Raioni', 'GE23': 'Gurjaanis Raioni', 'GE20': 'Gardabanis Raioni', 'GE21': 'Gori', 'GE26': 'Kaspis Raioni', 'GE27': 'Kharagaulis Raioni', 'GE24': 'Javis Raioni', 'GE25': "K'arelis Raioni", 'IR41': 'Khorasan-e Janubi', 'IR40': 'Yazd', 'GE28': 'Khashuris Raioni', 'GE29': 'Khobis Raioni', 'TR60': 'Tokat', 'TR61': 'Trabzon', 'TR62': 'Tunceli', 'TR63': 'Sanliurfa', 'TR64': 'Usak', 'TR65': 'Van', 'TR66': 'Yozgat', 'TR68': 'Ankara', 'TR69': 'Gumushane', 'BE09': 'West-Vlaanderen', 'BE08': 'Oost-Vlaanderen', 'BE07': 'Namur', 'BE06': 'Luxembourg', 'BE05': 'Limburg', 'BE04': 'Liege', 'BE03': 'Hainaut', 'BE01': 'Antwerpen', 'UZ14': 'Toshkent', 'UZ12': 'Surkhondaryo', 'UZ13': 'Toshkent', 'UZ10': 'Samarqand', 'UZ11': 'Sirdaryo', 'AZ33': 'Mingacevir', 'NG39': 'Jigawa', 'MK26': 'Dobrusevo', 'MK27': 'Dolna Banjica', 'MK24': 'Demir Hisar', 'MK25': 'Demir Kapija', 'MK22': 'Delcevo', 'MK23': 'Delogozdi', 'MK20': 'Cucer-Sandevo', 'MK21': 'Debar', 'MV38': 'Kaafu', 'MV39': 'Lhaviyani', 'MK28': 'Dolneni', 'MK29': 'Dorce Petrov', 'NG30': 'Kwara', 'NG31': 'Niger', 'DZ09': 'Oran', 'NG36': 'Delta', 'GM04': 'Upper River', 'GM05': 'Western', 'GM07': 'North Bank', 'GM01': 'Banjul', 'GM02': 'Lower River', 'GM03': 'Central River', 'CAQC': 'Quebec', 'ID03': 'Bengkulu', 'ID02': 'Bali', 'ID01': 'Aceh', 'ID07': 'Jawa Tengah', 'ID06': 'Jawa Barat', 'ID05': 'Jambi', 'ID04': 'Jakarta Raya', 'CO23': 'Quindio', 'ID09': 'Papua', 'ID08': 'Jawa Timur', 'SV03': 'Chalatenango', 'GBT6': 'Aberdeenshire', 'GBT5': 'Aberdeen City', 'GBT4': 'Strabane', 'GBT3': 'Omagh', 'GBT2': 'North Down', 'GBT1': 'Newtownabbey', 'RU42': 'Leningrad', 'SV09': 'San Miguel', 'SV08': 'Morazan', 'GBT9': 'Scottish Borders', 'GBT8': 'Argyll and Bute', 'MV34': 'Gaafu Alifu', 'MV35': 'Gaafu Dhaalu', 'SIN5': 'Zalec', 'SIN2': 'Videm', 'SIN3': 'Vojnik', 'MKA9': 'Vasilevo', 'SD28': "Al Istiwa'iyah", 'MKA3': 'Suto Orizari', 'MKA2': 'Studenicani', 'MKA1': 'Strumica', 'MKA7': 'Topolcani', 'MKA6': 'Tetovo', 'MKA5': 'Tearce', 'MKA4': 'Sveti Nikole', 'CM13': 'Nord', 'CM12': 'Extreme-Nord', 'CM11': 'Centre', 'CM10': 'Adamaoua', 'SO19': 'Togdheer', 'SO18': 'Nugaal', 'CM14': 'Sud', 'SO14': 'Shabeellaha Hoose', 'SO16': 'Woqooyi Galbeed', 'SO11': 'Nugaal', 'SO10': 'Mudug', 'SO13': 'Shabeellaha Dhexe', 'SO12': 'Sanaag', 'LV33': 'Ventspils', 'LV32': 'Ventspils', 'LV31': 'Valmieras', 'LV30': 'Valkas', 'UG69': 'Katakwi', 'UG66': 'Bugiri', 'UG67': 'Busia', 'UG65': 'Adjumani', 'UG60': 'Pallisa', 'UG61': 'Rakai', 'FRA7': 'Haute-Normandie', 'FRA6': 'Franche-Comte', 'FRA5': 'Corse', 'FRA4': 'Champagne-Ardenne', 'FRA3': 'Centre', 'FRA2': 'Bretagne', 'HU10': 'Hajdu-Bihar', 'HU11': 'Heves', 'FRA9': 'Languedoc-Roussillon', 'FRA8': 'Ile-de-France', 'PG09': 'Eastern Highlands', 'PG08': 'Chimbu', 'PG03': 'Milne Bay', 'PG02': 'Gulf', 'PG01': 'Central', 'PG07': 'North Solomons', 'PG06': 'Western', 'PG05': 'Southern Highlands', 'PG04': 'Northern', 'IN30': 'Arunachal Pradesh', 'IN31': 'Mizoram', 'IN32': 'Daman and Diu', 'VN47': 'Kien Giang', 'IN34': 'Bihar', 'IN35': 'Madhya Pradesh', 'IN36': 'Uttar Pradesh', 'IN37': 'Chhattisgarh', 'IN38': 'Jharkhand', 'IN39': 'Uttarakhand', 'USUT': 'Utah', 'VN43': 'An Giang', 'MD67': 'Causeni', 'OM04': 'Ash Sharqiyah', 'OM05': 'Az Zahirah', 'OM06': 'Masqat', 'OM07': 'Musandam', 'OM01': 'Ad Dakhiliyah', 'OM02': 'Al Batinah', 'OM03': 'Al Wusta', 'OM08': 'Zufar', 'GR09': 'Kastoria', 'GR08': 'Florina', 'PHH2': 'Quezon', 'PHH3': 'Negros Occidental', 'GR03': 'Xanthi', 'GR02': 'Rodhopi', 'GR01': 'Evros', 'GR07': 'Pella', 'GR06': 'Kilkis', 'GR05': 'Serrai', 'GR04': 'Drama', 'GE39': 'Ninotsmindis Raioni', 'GE38': "Mts'khet'is Raioni", 'GE35': 'Marneulis Raioni', 'GE34': 'Lentekhis Raioni', 'GE37': 'Mestiis Raioni', 'GE36': 'Martvilis Raioni', 'GE31': "K'ut'aisi", 'GE30': 'Khonis Raioni', 'GE33': "Lanch'khut'is Raioni", 'GE32': 'Lagodekhis Raioni', 'TR73': 'Nigde', 'TR72': 'Mardin', 'TR71': 'Konya', 'TR70': 'Hakkari', 'TR77': 'Bayburt', 'TR76': 'Batman', 'TR75': 'Aksaray', 'TR74': 'Siirt', 'TR79': 'Kirikkale', 'TR78': 'Karaman', 'IE31': 'Wicklow', 'IE30': 'Wexford', 'UZ09': 'Qoraqalpoghiston', 'UZ08': 'Qashqadaryo', 'UZ01': 'Andijon', 'KM01': 'Anjouan', 'UZ03': 'Farghona', 'UZ02': 'Bukhoro', 'UZ05': 'Khorazm', 'UZ04': 'Jizzakh', 'UZ07': 'Nawoiy', 'UZ06': 'Namangan', 'BW10': 'Southern', 'BW11': 'North-West', 'MK31': 'Dzepciste', 'MK30': 'Drugovo', 'MK33': 'Gevgelija', 'MK32': 'Gazi Baba', 'MK35': 'Gradsko', 'MK34': 'Gostivar', 'MK37': 'Izvor', 'MK36': 'Ilinden', 'MK39': 'Kamenjane', 'MK38': 'Jegunovce', 'RU26': 'Kamchatka', 'ID38': 'Sulawesi Selatan', 'ID39': 'Irian Jaya Barat', 'ID36': 'Papua', 'ID37': 'Riau', 'ID34': 'Gorontalo', 'ID35': 'Kepulauan Bangka Belitung', 'ID32': 'Sumatera Selatan', 'ID33': 'Banten', 'ID30': 'Jawa Barat', 'ID31': 'Sulawesi Utara', 'GBW2': 'Renfrewshire', 'GBW3': 'Shetland Islands', 'GBW1': 'Perth and Kinross', 'GBW6': 'Stirling', 'GBW7': 'West Dunbartonshire', 'GBW4': 'South Ayrshire', 'AZ62': 'Xanlar', 'GBW8': 'Eilean Siar', 'GBW9': 'West Lothian', 'MKB6': 'Vranestica', 'MKB7': 'Vrapciste', 'MKB4': 'Vinica', 'MKB5': 'Vitoliste', 'MKB2': 'Velesta', 'MKB3': 'Vevcani', 'MKB1': 'Veles', 'MKB8': 'Vratnica', 'MKB9': 'Vrutok', 'LV06': 'Daugavpils', 'LV07': 'Daugavpils', 'LV04': 'Bauskas', 'LV05': 'Cesu', 'LV02': 'Aluksnes', 'LV03': 'Balvu', 'LV01': 'Aizkraukles', 'LV08': 'Dobeles', 'LV09': 'Gulbenes', 'UG79': 'Kabarole', 'UG78': 'Iganga', 'DZ50': 'Ouargla', 'UG71': 'Masaka', 'UG70': 'Luwero', 'UG73': 'Nakasongola', 'UG72': 'Moyo', 'UG74': 'Sembabule', 'UG77': 'Arua', 'UG76': 'Tororo', 'HU01': 'Bacs-Kiskun', 'FRB3': 'Midi-Pyrenees', 'HU03': 'Bekes', 'HU02': 'Baranya', 'HU05': 'Budapest', 'HU04': 'Borsod-Abauj-Zemplen', 'HU07': 'Debrecen', 'HU06': 'Csongrad', 'HU09': 'Gyor-Moson-Sopron', 'HU08': 'Fejer', 'FRB8': "Provence-Alpes-Cote d'Azur", 'FRB9': 'Rhone-Alpes', 'DZ54': 'Tindouf', 'GBT7': 'Angus', 'SV02': 'Cabanas', 'DZ56': 'Tissemsilt', 'SV01': 'Ahuachapan', 'CAYT': 'Yukon Territory', 'SV07': 'La Union', 'SV06': 'La Paz', 'SV05': 'La Libertad', 'SI08': 'Brezice', 'SV04': 'Cuscatlan', 'IN23': 'Punjab', 'IN22': 'Puducherry', 'IN21': 'Orissa', 'IN20': 'Nagaland', 'IN26': 'Tripura', 'IN25': 'Tamil Nadu', 'IN24': 'Rajasthan', 'IN29': 'Sikkim', 'IN28': 'West Bengal', 'NZ10': 'Chatham Islands', 'TN14': 'El Kef', 'GR36': 'Argolis', 'GR37': 'Korinthia', 'GR34': 'Evvoia', 'GR35': 'Attiki', 'GR32': 'Fokis', 'GR33': 'Voiotia', 'GR30': 'Evritania', 'GR31': 'Aitolia kai Akarnania', 'GR38': 'Akhaia', 'GR39': 'Ilia', 'USVT': 'Vermont', 'GE48': 'Samtrediis Raioni', 'GE49': 'Senakis Raioni', 'USVA': 'Virginia', 'GE40': 'Onis Raioni', 'GE41': "Ozurget'is Raioni", 'GE42': "P'ot'i", 'GE43': 'Qazbegis Raioni', 'GE44': 'Qvarlis Raioni', 'GE45': "Rust'avi", 'GE46': "Sach'kheris Raioni", 'GE47': 'Sagarejos Raioni', 'TR48': 'Mugla', 'TR49': 'Mus', 'TR46': 'Kahramanmaras', 'TR44': 'Malatya', 'TR45': 'Manisa', 'TR43': 'Kutahya', 'TR40': 'Kirsehir', 'TR41': 'Kocaeli', 'SD29': 'Al Khartum', 'MKA8': 'Valandovo', 'BW09': 'South-East', 'BW08': 'North-East', 'BW05': 'Kgatleng', 'BW04': 'Kgalagadi', 'BW06': 'Kweneng', 'BW01': 'Central', 'BW03': 'Ghanzi', 'VN88': 'Dak Lak', 'SD27': 'Al Wusta', 'ID29': 'Maluku Utara', 'ID28': 'Maluku', 'ID21': 'Sulawesi Tengah', 'ID20': 'Sulawesi Selatan', 'ID23': 'Sulawesi Utara', 'ID22': 'Sulawesi Tenggara', 'ID25': 'Sumatera Selatan', 'ID24': 'Sumatera Barat', 'ID26': 'Sumatera Utara', 'AG01': 'Barbuda', 'AG03': 'Saint George', 'AG04': 'Saint John', 'AG05': 'Saint Mary', 'AG06': 'Saint Paul', 'AG07': 'Saint Peter', 'AG08': 'Saint Philip', 'AG09': 'Redonda', 'GBV7': 'North Ayrshire', 'GBV6': 'Moray', 'GBV1': 'Fife', 'MY08': 'Perlis', 'GBV3': 'Highland', 'GBV2': 'Glasgow City', 'RO06': 'Bistrita-Nasaud', 'CV07': 'Ribeira Grande', 'MKC1': 'Zajas', 'KE01': 'Central', 'KE02': 'Coast', 'KE03': 'Eastern', 'MKC5': 'Zletovo', 'KE05': 'Nairobi Area', 'KE06': 'North-Eastern', 'KE07': 'Nyanza', 'KE08': 'Rift Valley', 'KE09': 'Western', 'LV11': 'Jelgava', 'LV10': 'Jekabpils', 'LV13': 'Jurmala', 'LV12': 'Jelgavas', 'LV15': 'Kuldigas', 'LV14': 'Kraslavas', 'LV17': 'Liepajas', 'LV16': 'Liepaja', 'LV19': 'Ludzas', 'RO09': 'Brasov', 'RO08': 'Braila', 'MN25': 'Orhon', 'MN24': 'Govisumber', 'MN23': 'Darhan-Uul', 'MN22': 'Erdenet', 'MN21': 'Bulgan', 'MN20': 'Ulaanbaatar', 'FRC1': 'Alsace', 'ST01': 'Principe', 'ST02': 'Sao Tome', 'BG50': 'Pleven', 'IN18': 'Meghalaya', 'IN19': 'Karnataka', 'IN16': 'Maharashtra', 'IN17': 'Manipur', 'IN14': 'Lakshadweep', 'IN12': 'Jammu and Kashmir', 'IN13': 'Kerala', 'IN10': 'Haryana', 'IN11': 'Himachal Pradesh', 'HU16': 'Pest', 'USWY': 'Wyoming', 'HU17': 'Somogy', 'USWV': 'West Virginia', 'HU14': 'Nograd', 'HU15': 'Pecs', 'USWI': 'Wisconsin', 'BG58': 'Sofiya', 'HU12': 'Komarom-Esztergom', 'TM02': 'Balkan', 'USWA': 'Washington', 'HU13': 'Miskolc', 'KR18': 'Kwangju-jikhalsi', 'FRA1': 'Bourgogne', 'KR14': 'Kyongsang-bukto', 'KR15': 'Taegu-jikhalsi', 'KR16': 'Cholla-namdo', 'KR17': "Ch'ungch'ong-namdo", 'KR10': 'Pusan-jikhalsi', 'KR11': "Seoul-t'ukpyolsi", 'KR12': "Inch'on-jikhalsi", 'KR13': 'Kyonggi-do', 'PG20': 'National Capital', 'HU18': 'Szabolcs-Szatmar-Bereg', 'HU19': 'Szeged', 'GR21': 'Larisa', 'GR20': 'Arta', 'GR23': 'Kardhitsa', 'GR22': 'Trikala', 'GR25': 'Kerkira', 'GR24': 'Magnisia', 'GR27': 'Kefallinia', 'GR26': 'Levkas', 'GR29': 'Fthiotis', 'GR28': 'Zakinthos', 'GE59': 'Tsalkis Raioni', 'GE58': 'Tsalenjikhis Raioni', 'GE53': "T'erjolis Raioni", 'GE52': "T'elavis Raioni", 'GE51': "T'bilisi", 'GE50': 'Sighnaghis Raioni', 'GE57': "Ts'ageris Raioni", 'GE56': 'Tqibuli', 'GE55': "T'ianet'is Raioni", 'GE54': "T'et'ritsqaros Raioni", 'TR59': 'Tekirdag', 'NA07': 'Karibib', 'BH14': 'Madinat Hamad', 'TR50': 'Nevsehir', 'TR53': 'Rize', 'TR52': 'Ordu', 'TR55': 'Samsun', 'TO02': 'Tongatapu', 'TR57': 'Sinop', 'AT08': 'Vorarlberg', 'NA03': 'Boesmanland', 'NA02': 'Caprivi Oos', 'BH13': 'Ar Rifa', 'AT07': 'Tirol', 'AT06': 'Steiermark', 'NA09': 'Luderitz', 'MV05': 'Laamu', 'AT04': 'Oberosterreich', 'MV01': 'Seenu', 'GBQ8': 'Armagh', 'GBQ9': 'Ballymena', 'GBU7': 'East Renfrewshire', 'GBQ2': 'Wokingham', 'GBQ3': 'Wolverhampton', 'GBQ4': 'Worcestershire', 'GBQ5': 'York', 'GBQ6': 'Antrim', 'GBQ7': 'Ards', 'EE06': 'Kohtla-Jarve', 'EE07': 'Laanemaa', 'EE04': 'Jarvamaa', 'MN18': 'Tov', 'EE05': 'Jogevamaa', 'MN12': 'Hovd', 'EE02': 'Hiiumaa', 'MN10': 'Govi-Altay', 'MN11': 'Hentiy', 'MN16': 'Selenge', 'MN17': 'Suhbaatar', 'MN14': 'Omnogovi', 'MN15': 'Ovorhangay', 'GW02': 'Quinara', 'EE01': 'Harjumaa', 'SB10': 'Central', 'SB11': 'Western', 'SB12': 'Choiseul', 'SB13': 'Rennell and Bellona', 'MV36': 'Haa Alifu', 'IN09': 'Gujarat', 'IN01': 'Andaman and Nicobar Islands', 'IN03': 'Assam', 'IN02': 'Andhra Pradesh', 'IN05': 'Chandigarh', 'BS34': 'Sandy Point', 'IN07': 'Delhi', 'IN06': 'Dadra and Nagar Haveli', 'CY04': 'Nicosia', 'CY05': 'Limassol', 'CY06': 'Paphos', 'IN33': 'Goa', 'CY01': 'Famagusta', 'CY02': 'Kyrenia', 'CY03': 'Larnaca', 'MV30': 'Alifu', 'MG04': 'Toamasina', 'MG05': 'Antananarivo', 'MG06': 'Toliara', 'MG01': 'Antsiranana', 'MG02': 'Fianarantsoa', 'MG03': 'Mahajanga', 'KR06': 'Kangwon-do', 'KR05': "Ch'ungch'ong-bukto", 'KR03': 'Cholla-bukto', 'KR01': 'Cheju-do', 'MV31': 'Baa', 'SR14': 'Nickerie', 'SR15': 'Para', 'SR16': 'Paramaribo', 'SR17': 'Saramacca', 'SR10': 'Brokopondo', 'SR11': 'Commewijne', 'SR12': 'Coronie', 'SR13': 'Marowijne', 'SR18': 'Sipaliwini', 'SR19': 'Wanica', 'MV32': 'Dhaalu', 'MV33': 'Faafu ', 'GE64': 'Zugdidis Raioni', 'GE62': "Zestap'onis Raioni", 'GE63': 'Zugdidi', 'GE60': 'Tsqaltubo', 'GE61': 'Vanis Raioni', 'USPR': 'Puerto Rico', 'USPW': 'Palau', 'USPA': 'Pennsylvania', 'GH10': 'Upper East', 'GH11': 'Upper West', 'GBS7': 'Magherafelt', 'BG63': 'Vidin', 'BG62': 'Veliko Turnovo', 'BG61': 'Varna', 'BG60': 'Turgovishte', 'GBS4': 'Limavady', 'BG65': 'Yambol', 'BG64': 'Vratsa', 'GBS5': 'Lisburn', 'SM04': 'Faetano', 'SM05': 'Fiorentino', 'GBP9': 'Windsor and Maidenhead', 'GBP8': 'Wiltshire', 'GBP3': 'Warwickshire', 'GBP2': 'Warrington', 'GBP1': 'Wandsworth', 'GBS1': 'Dungannon', 'GBP7': 'Wigan', 'GBP6': 'West Sussex', 'GBP5': 'Westminster', 'GBP4': 'West Berkshire', 'DJ01': 'Ali Sabieh', 'DJ06': 'Dikhil', 'DJ07': 'Djibouti', 'DJ04': 'Obock', 'DJ05': 'Tadjoura', 'DJ08': 'Arta', 'LY58': 'Misratah', 'LY59': 'Sawfajjin', 'KH30': 'Pailin', 'NL02': 'Friesland', 'NL03': 'Gelderland', 'NL01': 'Drenthe', 'NL06': 'Noord-Brabant', 'NL07': 'Noord-Holland', 'NL04': 'Groningen', 'NL05': 'Limburg', 'NL08': 'Overijssel', 'NL09': 'Utrecht', 'MN05': 'Darhan', 'MN07': 'Dornogovi', 'MN06': 'Dornod', 'MN01': 'Arhangay', 'MN03': 'Bayan-Olgiy', 'MN02': 'Bayanhongor', 'LR20': 'Lofa', 'MN09': 'Dzavhan', 'MN08': 'Dundgovi', 'NE06': 'Tahoua', 'NE05': 'Niamey', 'JM17': 'Kingston', 'CH26': 'Jura', 'SB07': 'Isabel', 'SB06': 'Guadalcanal', 'SB03': 'Malaita', 'SB09': 'Temotu', 'SB08': 'Makira', 'PE23': 'Tacna', 'PE22': 'San Martin', 'PE21': 'Puno', 'PE20': 'Piura', 'PE25': 'Ucayali', 'PE24': 'Tumbes', 'MD79': 'Leova', 'MD76': 'Glodeni', 'PL79': 'Opolskie', 'PL78': 'Mazowieckie', 'MD77': 'Hincesti', 'PL75': 'Lubelskie', 'PL74': 'Lodzkie', 'PL77': 'Malopolskie', 'PL76': 'Lubuskie', 'MD74': 'Falesti', 'PL73': 'Kujawsko-Pomorskie', 'PL72': 'Dolnoslaskie', 'MD75': 'Floresti', 'MD73': 'Edinet', 'MD70': 'Donduseni', 'BF78': 'Zondoma', 'MD71': 'Drochia', 'SC19': 'Plaisance', 'BN08': 'Belait', 'BN09': 'Brunei and Muara', 'SC18': 'Mont Fleuri', 'BN07': 'Alibori', 'KP12': "P'yongyang-si", 'KP13': 'Yanggang-do', 'KP11': "P'yongan-bukto", 'KP17': 'Hamgyong-bukto', 'KP14': "Namp'o-si", 'KP15': "P'yongan-namdo", 'KP18': 'Najin Sonbong-si', 'SC13': "Grand' Anse", 'SC12': 'Glacis', 'GH01': 'Greater Accra', 'GH03': 'Brong-Ahafo', 'GH02': 'Ashanti', 'GH05': 'Eastern', 'GH04': 'Central', 'GH06': 'Northern', 'GH09': 'Western', 'GH08': 'Volta', 'BG56': 'Sliven', 'BG57': 'Smolyan', 'BG54': 'Shumen', 'BG55': 'Silistra', 'BG52': 'Razgrad', 'BG53': 'Ruse', 'RU90': 'Permskiy Kray', 'BG51': 'Plovdiv', 'TM05': 'Mary', 'TM04': 'Lebap', 'TM01': 'Ahal', 'TM03': 'Dashoguz', 'BG59': 'Stara Zagora', 'SE18': 'Sodermanlands Lan', 'HU28': 'Eger', 'RU91': 'Krasnoyarskiy Kray', 'CN11': 'Hunan', 'HT14': "Grand' Anse", 'KH29': 'Batdambang', 'KH25': 'Banteay Meanchey', 'NL15': 'Overijssel', 'NL16': 'Flevoland', 'NL11': 'Zuid-Holland', 'NL10': 'Zeeland', 'LS18': 'Quthing', 'LS19': 'Thaba-Tseka', 'LS10': 'Berea', 'LS11': 'Butha-Buthe', 'LS12': 'Leribe', 'LS13': 'Mafeteng', 'LS14': 'Maseru', 'LS15': 'Mohales Hoek', 'LS16': 'Mokhotlong', 'LS17': 'Qachas Nek', 'GBS6': 'Derry', 'SM01': 'Acquaviva', 'SM02': 'Chiesanuova', 'SM03': 'Domagnano', 'GBS2': 'Fermanagh', 'GBS3': 'Larne', 'SM06': 'Borgo Maggiore', 'SM07': 'San Marino', 'SM08': 'Monte Giardino', 'SM09': 'Serravalle', 'GBS8': 'Moyle', 'GBS9': 'Newry and Mourne', 'CZ90': 'Zlinsky kraj', 'MD90': 'Taraclia', 'MD91': 'Telenesti', 'MD92': 'Ungheni', 'CN18': 'Guizhou', 'CN19': 'Liaoning', 'CN10': 'Hebei', 'SE10': 'Dalarnas Lan', 'CN12': 'Hubei', 'CN13': 'Xinjiang', 'CN14': 'Xizang', 'CN15': 'Gansu', 'CN16': 'Guangxi', 'PE18': 'Moquegua', 'PE19': 'Pasco', 'PE16': 'Loreto', 'PE17': 'Madre de Dios', 'PE14': 'Lambayeque', 'PE15': 'Lima', 'PE12': 'Junin', 'PE13': 'La Libertad', 'PE10': 'Huanuco', 'PE11': 'Ica'}
| 21,486.25 | 85,919 | 0.602339 |
b7a9d3a60ea32292f1f1a315f0e465e4cf861159 | 236 | py | Python | configs/semantic_guided/CE.py | hukkelas/full_body_anonymization | c61745b137c84ffb742ef6ab2f4721db4acf22b7 | [
"MIT"
] | 27 | 2022-01-06T20:15:24.000Z | 2022-03-29T11:54:49.000Z | configs/semantic_guided/CE.py | hukkelas/full_body_anonymization | c61745b137c84ffb742ef6ab2f4721db4acf22b7 | [
"MIT"
] | 2 | 2022-03-17T06:04:23.000Z | 2022-03-25T08:50:57.000Z | configs/semantic_guided/CE.py | hukkelas/full_body_anonymization | c61745b137c84ffb742ef6ab2f4721db4acf22b7 | [
"MIT"
] | 2 | 2022-01-07T13:16:59.000Z | 2022-01-16T02:10:50.000Z | _base_config_ = ["base.py"]
generator = dict(
input_cse=True,
use_cse=True
)
discriminator=dict(
pred_only_cse=False,
pred_only_semantic=True
)
loss = dict(
gan_criterion=dict(type="segmentation", seg_weight=.1)
)
| 15.733333 | 58 | 0.699153 |
b7ac37d5a23a4e9b74f4c14b649516c082ec539d | 676 | py | Python | test/compiler/test-encode.py | xupingmao/minipy | 5bce2f238925eb92fe9ff7d935f59ef68daa257a | [
"MIT"
] | 52 | 2016-07-11T10:14:35.000Z | 2021-12-09T09:10:43.000Z | test/compiler/test-encode.py | xupingmao/snake | c956f151ed1ebd2faeaf1565352b59ca5a8fa0b4 | [
"MIT"
] | 13 | 2016-07-24T13:50:37.000Z | 2019-03-02T06:56:18.000Z | test/compiler/test-encode.py | xupingmao/snake | c956f151ed1ebd2faeaf1565352b59ca5a8fa0b4 | [
"MIT"
] | 9 | 2017-01-27T10:46:04.000Z | 2021-12-09T09:10:46.000Z | # -*- coding:utf-8 -*-
# @author xupingmao <578749341@qq.com>
# @since 2020/10/20 00:19:47
# @modified 2020/10/20 00:42:52
import sys
sys.path.append("src/python")
from mp_encode import *
test_compile("assign-number")
test_compile("assign-multi")
test_compile("if-in")
| 25.037037 | 67 | 0.668639 |
b7ad32170df3a150ccda1de3243e006af407c590 | 3,719 | py | Python | paragen/optim/__init__.py | godweiyang/ParaGen | 9665d1244ea38a41fc06b4e0a7f6411985e2221f | [
"Apache-2.0"
] | null | null | null | paragen/optim/__init__.py | godweiyang/ParaGen | 9665d1244ea38a41fc06b4e0a7f6411985e2221f | [
"Apache-2.0"
] | null | null | null | paragen/optim/__init__.py | godweiyang/ParaGen | 9665d1244ea38a41fc06b4e0a7f6411985e2221f | [
"Apache-2.0"
] | null | null | null | from copy import deepcopy
from inspect import getfullargspec
import importlib
import json
import os
import logging
logger = logging.getLogger(__name__)
from torch.optim.optimizer import Optimizer
from paragen.optim.optimizer import Optimizer
from paragen.utils.rate_schedulers import create_rate_scheduler
from paragen.utils.runtime import Environment
from paragen.utils.registry import setup_registry
register_optim, create_optim, registry = setup_registry('optim', Optimizer, force_extend=False)
modules_dir = os.path.dirname(__file__)
for file in os.listdir(modules_dir):
path = os.path.join(modules_dir, file)
if (
not file.startswith('_')
and not file.startswith('.')
and (file.endswith('.py') or os.path.isdir(path))
):
module_name = file[:file.find('.py')] if file.endswith('.py') else file
module = importlib.import_module('paragen.optim.' + module_name)
| 35.419048 | 112 | 0.633235 |
b7adb4099781c23875a3639ae37c4e4a5bb88239 | 2,860 | py | Python | joyvillage/joy/views.py | IreneMercy/Joy-Village-Backup | f038e33aa5c28337bc20c6fcd3273ef37d283564 | [
"MIT"
] | null | null | null | joyvillage/joy/views.py | IreneMercy/Joy-Village-Backup | f038e33aa5c28337bc20c6fcd3273ef37d283564 | [
"MIT"
] | 9 | 2021-03-19T09:58:55.000Z | 2022-03-12T00:22:50.000Z | joyvillage/joy/views.py | IreneMercy/Joy-Foundation | f038e33aa5c28337bc20c6fcd3273ef37d283564 | [
"MIT"
] | null | null | null | from __future__ import unicode_literals
from django.shortcuts import render, redirect
from django.http import HttpResponse, HttpResponseRedirect
from .models import Events, Gallery, News, Careers, Partners
from django.core.mail import send_mail,BadHeaderError
from django.conf import settings
from.forms import ContactForm
from django.contrib import messages
| 29.484536 | 103 | 0.640909 |
b7ae3072a6046637d4bd29d21eabd8d449e98c65 | 274 | py | Python | src/events/admin.py | cbsBiram/xarala__ssr | 863e1362c786daa752b942b796f7a015211d2f1b | [
"FSFAP"
] | null | null | null | src/events/admin.py | cbsBiram/xarala__ssr | 863e1362c786daa752b942b796f7a015211d2f1b | [
"FSFAP"
] | null | null | null | src/events/admin.py | cbsBiram/xarala__ssr | 863e1362c786daa752b942b796f7a015211d2f1b | [
"FSFAP"
] | null | null | null | from django.contrib import admin
from django_summernote.admin import SummernoteModelAdmin
from .models import Event, Speaker
admin.site.register(Event, EventAdmin)
admin.site.register(Speaker)
| 22.833333 | 56 | 0.813869 |
b7af3d0ba516d34beefe1df3aa1a2a39558521ee | 318 | py | Python | python/cython_build.py | n1tk/batch_jaro_winkler | 421c7e3a5bedce89e8c00216b90d32d1629073a2 | [
"MIT"
] | 22 | 2020-04-30T17:56:29.000Z | 2022-01-19T21:05:15.000Z | python/cython_build.py | n1tk/batch_jaro_winkler | 421c7e3a5bedce89e8c00216b90d32d1629073a2 | [
"MIT"
] | 2 | 2021-01-19T14:07:22.000Z | 2021-11-24T16:32:46.000Z | python/cython_build.py | n1tk/batch_jaro_winkler | 421c7e3a5bedce89e8c00216b90d32d1629073a2 | [
"MIT"
] | 3 | 2020-10-28T20:56:29.000Z | 2022-02-25T23:29:05.000Z |
from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
import sys
python_version = sys.version_info[0]
setup(
name='batch_jaro_winkler',
ext_modules=cythonize([Extension('batch_jaro_winkler', ['cbatch_jaro_winkler.pyx'])], language_level=python_version)
) | 24.461538 | 118 | 0.811321 |
b7afa43603c9767401a62b1a4fe6fc631887605a | 6,647 | py | Python | venv/lib/python3.7/site-packages/google/type/postal_address_pb2.py | nicholasadamou/StockBird | 257396479667863d4ee122ea46adb86087c9aa78 | [
"Apache-2.0"
] | 15 | 2020-06-29T08:33:39.000Z | 2022-02-12T00:28:51.000Z | venv/lib/python3.7/site-packages/google/type/postal_address_pb2.py | nicholasadamou/StockBird | 257396479667863d4ee122ea46adb86087c9aa78 | [
"Apache-2.0"
] | 21 | 2020-03-01T18:21:09.000Z | 2020-05-26T14:49:08.000Z | venv/lib/python3.7/site-packages/google/type/postal_address_pb2.py | nicholasadamou/StockBird | 257396479667863d4ee122ea46adb86087c9aa78 | [
"Apache-2.0"
] | 11 | 2020-06-29T08:40:24.000Z | 2022-02-24T17:39:16.000Z | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: google/type/postal_address.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name='google/type/postal_address.proto',
package='google.type',
syntax='proto3',
serialized_options=_b('\n\017com.google.typeB\022PostalAddressProtoP\001ZFgoogle.golang.org/genproto/googleapis/type/postaladdress;postaladdress\242\002\003GTP'),
serialized_pb=_b('\n google/type/postal_address.proto\x12\x0bgoogle.type\"\xfd\x01\n\rPostalAddress\x12\x10\n\x08revision\x18\x01 \x01(\x05\x12\x13\n\x0bregion_code\x18\x02 \x01(\t\x12\x15\n\rlanguage_code\x18\x03 \x01(\t\x12\x13\n\x0bpostal_code\x18\x04 \x01(\t\x12\x14\n\x0csorting_code\x18\x05 \x01(\t\x12\x1b\n\x13\x61\x64ministrative_area\x18\x06 \x01(\t\x12\x10\n\x08locality\x18\x07 \x01(\t\x12\x13\n\x0bsublocality\x18\x08 \x01(\t\x12\x15\n\raddress_lines\x18\t \x03(\t\x12\x12\n\nrecipients\x18\n \x03(\t\x12\x14\n\x0corganization\x18\x0b \x01(\tBu\n\x0f\x63om.google.typeB\x12PostalAddressProtoP\x01ZFgoogle.golang.org/genproto/googleapis/type/postaladdress;postaladdress\xa2\x02\x03GTPb\x06proto3')
)
_POSTALADDRESS = _descriptor.Descriptor(
name='PostalAddress',
full_name='google.type.PostalAddress',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='revision', full_name='google.type.PostalAddress.revision', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='region_code', full_name='google.type.PostalAddress.region_code', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='language_code', full_name='google.type.PostalAddress.language_code', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='postal_code', full_name='google.type.PostalAddress.postal_code', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sorting_code', full_name='google.type.PostalAddress.sorting_code', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='administrative_area', full_name='google.type.PostalAddress.administrative_area', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='locality', full_name='google.type.PostalAddress.locality', index=6,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sublocality', full_name='google.type.PostalAddress.sublocality', index=7,
number=8, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='address_lines', full_name='google.type.PostalAddress.address_lines', index=8,
number=9, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='recipients', full_name='google.type.PostalAddress.recipients', index=9,
number=10, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='organization', full_name='google.type.PostalAddress.organization', index=10,
number=11, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=50,
serialized_end=303,
)
DESCRIPTOR.message_types_by_name['PostalAddress'] = _POSTALADDRESS
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
PostalAddress = _reflection.GeneratedProtocolMessageType('PostalAddress', (_message.Message,), dict(
DESCRIPTOR = _POSTALADDRESS,
__module__ = 'google.type.postal_address_pb2'
# @@protoc_insertion_point(class_scope:google.type.PostalAddress)
))
_sym_db.RegisterMessage(PostalAddress)
DESCRIPTOR._options = None
# @@protoc_insertion_point(module_scope)
| 47.141844 | 711 | 0.746352 |
b7aff83ef7243e9bfde2d005caee3accba55ac07 | 612 | py | Python | dataprep/tests/data_connector/test_integration.py | dylanzxc/dataprep | 21ef62936eeec28495763f35fcb3cb07f71de6f6 | [
"MIT"
] | 1 | 2020-12-18T13:16:38.000Z | 2020-12-18T13:16:38.000Z | dataprep/tests/data_connector/test_integration.py | bexxmodd/dataprep | 3aaa626bfaf9270cf56ffb70280cbcd8031f3ac3 | [
"MIT"
] | null | null | null | dataprep/tests/data_connector/test_integration.py | bexxmodd/dataprep | 3aaa626bfaf9270cf56ffb70280cbcd8031f3ac3 | [
"MIT"
] | null | null | null | from ...data_connector import Connector
from os import environ
| 24.48 | 81 | 0.666667 |
b7b0446dcbe64c12f7cc04baa8e64d8c7155c9fb | 6,294 | py | Python | plot_helpers.py | aspuru-guzik-group/QNODE | 1ec3767c7b574eaeb7b0ec05d1be54983f8972bd | [
"MIT"
] | 14 | 2021-11-06T19:32:56.000Z | 2022-02-08T19:53:28.000Z | plot_helpers.py | aspuru-guzik-group/QNODE | 1ec3767c7b574eaeb7b0ec05d1be54983f8972bd | [
"MIT"
] | null | null | null | plot_helpers.py | aspuru-guzik-group/QNODE | 1ec3767c7b574eaeb7b0ec05d1be54983f8972bd | [
"MIT"
] | null | null | null | import os
import torch
import numpy as np
import math
import matplotlib.pyplot as plt
from matplotlib import cm
from qutip import *
import imageio
plt.rcParams['axes.labelsize'] = 16
from matplotlib import rc
rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
rc('text', usetex=True)
def animate_recon(xt, xm, xe, title=''):
"""x is [ts,3]"""
images = []
for x, label, col in zip([xt, xm, xe],['training dynamics', 'latent neural ode reconstruction','latent neural ode extrapolation' ], ['black','limegreen', 'blue']):
for i, v in enumerate(x):
bloch = bloch_format(Bloch())
bloch.add_vectors(v)
bloch.vector_color =[col]
bloch.render()
s = x[:i+1]
#print(v, s[-1])
bloch.axes.plot(s[:,1], -s[:,0], s[:,2], color=col)
if label =='latent neural ode reconstruction':
bloch.axes.plot(xt[:,1], -xt[:,0], xt[:,2], color='black')
if label =='latent neural ode extrapolation':
bloch.axes.plot(xt[:,1], -xt[:,0], xt[:,2], color='black')
bloch.axes.plot(xm[:,1], -xm[:,0], xm[:,2], color='limegreen')
plt.suptitle(label, fontdict={'color':col})
plt.savefig('exp/temp_file.png')
images.append(imageio.imread('exp/temp_file.png'))
imageio.mimsave('exp/'+title+'.gif', images, duration=0.05)
def animate_traj(xt, title=''):
"""xt, xm is [ts,3] --> generate gif of both simultaneously"""
images = []
for i, vt in enumerate(xt):
bloch = bloch_format(Bloch())
bloch.add_vectors(vt)
bloch.vector_color =['black']
bloch.render()
t = xt[:i+1]
bloch.axes.plot(t[:,1], -t[:,0], t[:,2], color='black', label='dynamics')
#plt.legend(loc='lower center')
#plt.suptitle('latent neural ode --', fontdict={'color':'limegreen'})
#plt.title('True quantum dynamics', fontdict={'color':'black'})
plt.savefig('exp/temp_file.png', bbox_inches='tight')
images.append(imageio.imread('exp/temp_file.png'))
imageio.mimsave('exp/'+title+'.gif', images, duration=0.05)
def animate_recon_(xt, xm, title=''):
"""xt, xm is [ts,3] --> generate gif of both simultaneously"""
images = []
for i, (vt, vm) in enumerate(zip(xt,xm)):
bloch = bloch_format(Bloch())
bloch.add_vectors(vt)
bloch.add_vectors(vm)
bloch.vector_color =['black', 'limegreen']
bloch.render()
t = xt[:i+1]
m = xm[:i+1]
bloch.axes.plot(t[:,1], -t[:,0], t[:,2], color='black', label='train')
bloch.axes.plot(m[:,1], -m[:,0], m[:,2], color='limegreen', label='neural ode')
#plt.legend(loc='lower center')
plt.suptitle('latent neural ode --', fontdict={'color':'limegreen'})
plt.title('True quantum dynamics', fontdict={'color':'black'})
plt.savefig('exp/temp_file.png')
images.append(imageio.imread('exp/temp_file.png'))
imageio.mimsave('exp/'+title+'.gif', images, duration=0.05)
def animate_single_traj(x, title=''):
"""x is [ts,3]"""
images = []
for i, v in enumerate(x):
bloch = Bloch()
bloch.add_vectors(v)
bloch.add_points(v)
bloch.render()
s = x[:i+1]
print(v, s[-1])
bloch.axes.plot(s[:,1], -s[:,0], s[:,2], color='limegreen')
plt.savefig('exp/temp_file.png')
images.append(imageio.imread('exp/temp_file.png'))
imageio.mimsave('exp/traj'+title+'.gif', images, duration=0.125)
os.remove('exp/temp_file.png')
def construct_gif(xs, title=''):
""" constructs a gif of stationary bloch trajectories """
cmap = cm.get_cmap('Greens', len(xs))
cols = cmap(range(len(xs)))
images = []
for i, x in enumerate(xs):
filename='temp_file.png'
plot_traj_bloch(x, filename)
images.append(imageio.imread('exp/'+filename))
imageio.mimsave('exp/'+title+'.gif', images, duration=0.5)
os.remove('exp/temp_file.png')
| 35.965714 | 167 | 0.58659 |
b7b1005f9392e0dbc05eef28e9be52e84c7d4a58 | 17,348 | py | Python | state.py | Lekensteyn/wgll | 11ac7925687bfc1866d3702f821230233fe3a8de | [
"MIT"
] | 1 | 2021-11-27T17:29:43.000Z | 2021-11-27T17:29:43.000Z | state.py | Lekensteyn/wgll | 11ac7925687bfc1866d3702f821230233fe3a8de | [
"MIT"
] | null | null | null | state.py | Lekensteyn/wgll | 11ac7925687bfc1866d3702f821230233fe3a8de | [
"MIT"
] | null | null | null | # State tracking for WireGuard protocol operations.
# Author: Peter Wu <peter@lekensteyn.nl>
# Licensed under the MIT license <http://opensource.org/licenses/MIT>.
import base64
import hashlib
import inspect
import socket
import traceback
from noise_wg import NoiseWG, crypto_scalarmult_base, aead_encrypt, aead_decrypt
class StateR0(Base):
class StateI1(Base):
fields = ['Tsend', 'Trecv']
class StateR1(Base):
# SpubI and time are not really needed by the handshake, but perhaps this
# could serve as debugging aid.
fields = ['SpubI', 'time', 'Tsend', 'Trecv']
class Data(Base):
class Field:
def __init__(self, name, size, constructor=None, fixed=None):
self.name = name
self.size = size
self.fixed = fixed
if constructor is None:
self._constructor = constructor
| 34.557769 | 85 | 0.606006 |
b7b19fe3229937c45439013a0185385ffb6134b0 | 2,007 | py | Python | BAMF_Detect/modules/dendroid.py | bwall/bamfdetect | 3b0b96a8b2285a1a4b3e3cf5ed1b5ad422b91ed1 | [
"MIT"
] | 152 | 2015-02-04T16:34:53.000Z | 2021-07-27T19:00:40.000Z | BAMF_Detect/modules/dendroid.py | bwall/bamfdetect | 3b0b96a8b2285a1a4b3e3cf5ed1b5ad422b91ed1 | [
"MIT"
] | null | null | null | BAMF_Detect/modules/dendroid.py | bwall/bamfdetect | 3b0b96a8b2285a1a4b3e3cf5ed1b5ad422b91ed1 | [
"MIT"
] | 30 | 2015-03-31T10:20:32.000Z | 2022-02-09T16:17:04.000Z | from common import Modules, data_strings, load_yara_rules, AndroidParseModule, ModuleMetadata
from base64 import b64decode
from string import printable
Modules.list.append(dendroid()) | 33.45 | 119 | 0.521176 |
b7b264987ed766841bcdbbf47f7266aa100f16c2 | 8,942 | py | Python | corehq/ex-submodules/couchforms/tests/test_analytics.py | caktus/commcare-hq | fae9c0f792b4889b768252d3895d9d1884ce0d3b | [
"BSD-3-Clause"
] | null | null | null | corehq/ex-submodules/couchforms/tests/test_analytics.py | caktus/commcare-hq | fae9c0f792b4889b768252d3895d9d1884ce0d3b | [
"BSD-3-Clause"
] | 40 | 2021-07-20T15:55:08.000Z | 2022-03-25T17:21:36.000Z | corehq/ex-submodules/couchforms/tests/test_analytics.py | caktus/commcare-hq | fae9c0f792b4889b768252d3895d9d1884ce0d3b | [
"BSD-3-Clause"
] | null | null | null | import datetime
import uuid
from django.test import TestCase
from mock import patch
from requests import ConnectionError
from couchforms.analytics import (
app_has_been_submitted_to_in_last_30_days,
domain_has_submission_in_last_30_days,
get_all_xmlns_app_id_pairs_submitted_to_in_domain,
get_exports_by_form,
get_first_form_submission_received,
get_form_analytics_metadata,
get_last_form_submission_received,
get_number_of_forms_in_domain,
update_analytics_indexes,
)
from couchforms.models import XFormInstance, XFormError
from pillowtop.es_utils import initialize_index_and_mapping
from testapps.test_pillowtop.utils import process_pillow_changes
from corehq.apps.es.tests.utils import es_test
from corehq.elastic import get_es_new, send_to_elasticsearch
from corehq.form_processor.interfaces.processor import FormProcessorInterface
from corehq.form_processor.tests.utils import FormProcessorTestUtils
from corehq.form_processor.utils import TestFormMetadata
from corehq.pillows.mappings.xform_mapping import XFORM_INDEX_INFO
from corehq.util.elastic import ensure_index_deleted
from corehq.util.test_utils import (
DocTestMixin,
disable_quickcache,
get_form_ready_to_save,
trap_extra_setup,
)
TEST_ES_META = {
XFORM_INDEX_INFO.index: XFORM_INDEX_INFO
}
| 40.645455 | 113 | 0.674122 |
b7b2bf3009f886fb399b6a73378d628699d8010a | 462 | py | Python | src/pythae/models/svae/svae_config.py | eknag/benchmark_VAE | 8b727f29a68aff7771c4c97aff15f75f88320e1f | [
"Apache-2.0"
] | 1 | 2022-03-20T20:23:59.000Z | 2022-03-20T20:23:59.000Z | src/pythae/models/svae/svae_config.py | eknag/benchmark_VAE | 8b727f29a68aff7771c4c97aff15f75f88320e1f | [
"Apache-2.0"
] | null | null | null | src/pythae/models/svae/svae_config.py | eknag/benchmark_VAE | 8b727f29a68aff7771c4c97aff15f75f88320e1f | [
"Apache-2.0"
] | null | null | null | from pydantic.dataclasses import dataclass
from ...models import VAEConfig
| 27.176471 | 99 | 0.690476 |
b7b3ac20c4a0978bc24a666dd7cd9ac25c00bc3a | 7,486 | py | Python | amck/imat/download_data.py | aaronmckinstry706/imaterialist | ebed3f3bd9e231f0852aa30c7bbfafe94d5dbce1 | [
"MIT"
] | null | null | null | amck/imat/download_data.py | aaronmckinstry706/imaterialist | ebed3f3bd9e231f0852aa30c7bbfafe94d5dbce1 | [
"MIT"
] | null | null | null | amck/imat/download_data.py | aaronmckinstry706/imaterialist | ebed3f3bd9e231f0852aa30c7bbfafe94d5dbce1 | [
"MIT"
] | null | null | null | # Parts of code taken from https://www.kaggle.com/aloisiodn/python-3-download-multi-proc-prog-bar-resume by Dourado.
# Improvements on the original script:
# * you can choose which dataset to download;
# * uses threads instead of processes;
# * unpacks data into .../label/id.jpg directory structure, which can be used easily via classes in PyTorch;
# * performance-relevant parameters are command line arguments.
# For performance parameters, the recommended values (from my machine; probably requires tweaking for others) are 100
# connection pools, 128 threads. Not all images with working URLs will be retrieved, but about 90-95% of them will. As
# a consequence, to ensure that nearly all images have been downloaded, repeat the script 3-4 times.
import argparse
import io
import json
import logging
import multiprocessing.pool as pool
import pathlib
import random
import sys
import typing
import urllib3
import PIL.Image as Image
from tqdm import tqdm
# Get command line arguments.
arg_parser = argparse.ArgumentParser(
description='Downloads the data files using the links given in the JSON training, validation, and test files. '
'Assumes that the files are stored in the directory data/metadata (relative to the current working '
'directory). Training files will be written to data/training/label_id/image_id.jpg, validation files '
'will be written to data/validation/label_id/image_id.jpg, and test files will be written to '
'data/testing/image_id.jpg.')
arg_parser.add_argument(
'--num-pools', '-p', type=int, default=10, help='Number of connection pools to cache at one time.')
arg_parser.add_argument(
'--num-workers', '-w', type=int, default=8, help='Number of threads to perform downloads.')
arg_parser.add_argument(
'--verbose', '-v', action='count', help='Print additional output messages. Can be passed multiple times. Once '
'prints additional status information, and two or more times prints '
'debugging information.', default=0)
arg_parser.add_argument(
'--limit', '-l', type=int, default=sys.maxsize, help='Maximum number of files to download before stopping.')
arg_parser.add_argument(
'--re-download', action='store_true', default=False, help='Whether to re-download existing files.')
arg_parser.add_argument(
'--dataset', '-d', type=str, choices={'training', 'validation', 'testing'}, help='Which dataset to download.')
parsed_args = arg_parser.parse_args()
# Set up logging.
urllib3.disable_warnings()
LOGGER = logging.getLogger(__name__)
STDOUT_HANDLER = logging.StreamHandler(sys.stdout)
if parsed_args.verbose == 1:
STDOUT_HANDLER.setLevel(logging.INFO)
elif parsed_args.verbose >= 2:
STDOUT_HANDLER.setLevel(logging.DEBUG)
LOGGER.addHandler(STDOUT_HANDLER)
LOGGER.setLevel(logging.DEBUG)
# Initialize globals.
failed_downloads = []
http = urllib3.PoolManager(num_pools=parsed_args.num_pools)
training_base_dir = pathlib.Path('data/training')
validation_base_dir = pathlib.Path('data/validation')
testing_base_dir = pathlib.Path('data/testing')
metadata_base_dir = pathlib.Path('data/metadata')
with metadata_base_dir.joinpath('train.json').open('r') as training_urls_file:
training_urls_json = json.load(training_urls_file)
with metadata_base_dir.joinpath('validation.json').open('r') as validation_urls_file:
validation_urls_json = json.load(validation_urls_file)
with metadata_base_dir.joinpath('test.json').open('r') as testing_urls_file:
testing_urls_json = json.load(testing_urls_file)
num_training_images = len(training_urls_json['images'])
num_validation_images = len(validation_urls_json['images'])
num_testing_images = len(testing_urls_json['images'])
LOGGER.info('{} training images, {} validation images, and {} testing images.'.format(
num_training_images, num_validation_images, num_testing_images))
thread_pool = pool.ThreadPool(processes=parsed_args.num_workers)
if parsed_args.dataset == 'training':
training_image_info = []
for image_info, annotation_info in zip(training_urls_json['images'], training_urls_json['annotations']):
training_image_info.append((image_info['url'][0], image_info['image_id'], annotation_info['label_id'],
training_base_dir))
random.shuffle(training_image_info)
with tqdm(total=len(training_image_info), desc='Training images') as t:
for i, _ in enumerate(thread_pool.imap_unordered(download_labeled_image, training_image_info)):
t.update(1)
if i >= parsed_args.limit:
break
elif parsed_args.dataset == 'validation':
validation_image_info = []
for image_info, annotation_info in zip(validation_urls_json['images'], validation_urls_json['annotations']):
validation_image_info.append((image_info['url'][0], image_info['image_id'], annotation_info['label_id'],
validation_base_dir))
random.shuffle(validation_image_info)
with tqdm(total=len(validation_image_info), desc='Validation images') as t:
for i, _ in enumerate(thread_pool.imap_unordered(download_labeled_image, validation_image_info)):
t.update(1)
if i >= parsed_args.limit:
break
elif parsed_args.dataset == 'testing':
testing_image_info = []
for image_info in testing_urls_json['images']:
testing_image_info.append((image_info['url'][0], image_info['image_id'], testing_base_dir))
random.shuffle(testing_image_info)
with tqdm(total=len(testing_image_info), desc='Testing images') as t:
for i, _ in enumerate(thread_pool.imap_unordered(download_unlabeled_image, testing_image_info)):
t.update(1)
if i >= parsed_args.limit:
break
LOGGER.info('{} images could not be retrieved.'.format(len(failed_downloads)))
| 41.821229 | 118 | 0.716137 |
b7b473cc7728c8bc405a3042f957fe877f0c27c2 | 790 | py | Python | JTP Recap./2.Program_IO/function.py | SNP0301/Study_Python | bb7ce7a0d915131c281152e7faee5b57c290df6b | [
"MIT"
] | null | null | null | JTP Recap./2.Program_IO/function.py | SNP0301/Study_Python | bb7ce7a0d915131c281152e7faee5b57c290df6b | [
"MIT"
] | null | null | null | JTP Recap./2.Program_IO/function.py | SNP0301/Study_Python | bb7ce7a0d915131c281152e7faee5b57c290df6b | [
"MIT"
] | null | null | null | """
Function
def function_name(arg1, arg2, ...) :
<op 1>
<op 2>
...
Function with undefined amount of input
def fn_name(*args) --> args' elements make tuple.
kwargs = Keyword Parameter
>>> def print_kwargs(**kwargs):
... print(kwargs)
...
>>> print_kwargs(a=1)
{'a':1}
>>> print_kwargs(name='foo', age=3)
{'age':3, 'name':'foo'}
**args_name = make args_name as a dictionary
clearing & assignment : element should be added in the last part of args
Lambda : another method to make fn
lambda arg1, arg2, .. : operation_of_fn
>>> add = lambda a,b : a+b
>>> result = add(3,4)
>>> print(result)
7
lambda can return result with out expression 'return'
Contents Source : https://wikidocs.net/24
""" | 22.571429 | 72 | 0.596203 |
b7b56be6d7b0d5e174db26b106b5f7914f624c31 | 2,437 | py | Python | tweet/common.py | skiwheelr/URS | 45746c945af2ea62a5ddb675c6a8e4e2fe4b5a93 | [
"MIT"
] | 4 | 2021-02-15T02:02:38.000Z | 2022-03-04T16:38:44.000Z | tweet/common.py | skiwheelr/URS | 45746c945af2ea62a5ddb675c6a8e4e2fe4b5a93 | [
"MIT"
] | null | null | null | tweet/common.py | skiwheelr/URS | 45746c945af2ea62a5ddb675c6a8e4e2fe4b5a93 | [
"MIT"
] | 2 | 2021-02-11T01:10:27.000Z | 2021-02-25T19:20:04.000Z | all
import tweepy, config, users, re, groupy
from tweepy import OAuthHandler
from tweepy import API
print(tweepy.__version__)
auth = OAuthHandler(config.consumer_key, config.consumer_secret)
auth.set_access_token(config.access_token,config.access_token_secret)
api = tweepy.API(auth)
from groupy.client import Client
client = Client.from_token(config.groupme_token)
exp = r'\$([A-Z]{3,4})'
one = []
two = []
three = []
all = []
#mrzackmorris
for user in users.list[:1]:
userID = user
tweets = api.user_timeline(screen_name=userID,count=100, include_rts = False, tweet_mode='extended')
for info in tweets:
if re.findall(exp,info.full_text):
for ticker in re.findall(exp,info.full_text):
if ticker not in one:
one.append(ticker)
# print(user, " mentioned ", re.findall(exp,info.full_text))
print(user, "mentioned", one)
#pharmdca
for user in users.list[1:2]:
userID = user
tweets = api.user_timeline(screen_name=userID,count=100, include_rts = False, tweet_mode='extended')
for info in tweets:
if re.findall(exp,info.full_text):
for ticker in re.findall(exp,info.full_text):
if ticker not in two:
two.append(ticker)
# print(user, " mentioned ", re.findall(exp,info.full_text))
print(user, "mentioned", two)
#ripster47
for user in users.list[2:3]:
userID = user
tweets = api.user_timeline(screen_name=userID,count=100, include_rts = False, tweet_mode='extended')
for info in tweets:
if re.findall(exp,info.full_text):
for ticker in re.findall(exp,info.full_text):
if ticker not in three:
three.append(ticker)
# print(user, " mentioned ", re.findall(exp,info.full_text))
print(user, "mentioned", three)
a_set = set(one)
b_set = set(two)
c_set = set(three)
if (a_set & b_set & c_set):
all.append(a_set & b_set & c_set)
print("All 3 mentioned ", all)
messenger(all)
else: print("Nothing Notable")
| 33.847222 | 120 | 0.636849 |
b7b6119291ad7a11b8a2999460f70e3f10db60c8 | 8,486 | py | Python | crystalpy/examples/PlotData1D.py | oasys-kit/crystalpy | 4852851c622ef914844178577dea4075e92cd8dd | [
"MIT"
] | null | null | null | crystalpy/examples/PlotData1D.py | oasys-kit/crystalpy | 4852851c622ef914844178577dea4075e92cd8dd | [
"MIT"
] | null | null | null | crystalpy/examples/PlotData1D.py | oasys-kit/crystalpy | 4852851c622ef914844178577dea4075e92cd8dd | [
"MIT"
] | null | null | null | """
---OK---
"""
from collections import OrderedDict
import copy
import numpy as np
from crystalpy.examples.Values import Interval
| 32.389313 | 111 | 0.582371 |
b7b6ad2f30eeeef89f8be32e1b423aba5b40b98c | 51 | py | Python | src/deep_dialog/usersims/__init__.py | Yuqing2018/tcbot_python3 | 583ce1b670f7c67669ff437e69eb09832e784da6 | [
"MIT"
] | null | null | null | src/deep_dialog/usersims/__init__.py | Yuqing2018/tcbot_python3 | 583ce1b670f7c67669ff437e69eb09832e784da6 | [
"MIT"
] | null | null | null | src/deep_dialog/usersims/__init__.py | Yuqing2018/tcbot_python3 | 583ce1b670f7c67669ff437e69eb09832e784da6 | [
"MIT"
] | null | null | null | from .usersim_rule import *
from .realUser import * | 25.5 | 27 | 0.784314 |
b7b6cb22cdbe422b0a500a1606789a7d83af799b | 38,534 | py | Python | hs_file_types/models/geofeature.py | tommac7/hydroshare | 87c4543a55f98103d2614bf4c47f7904c3f9c029 | [
"BSD-3-Clause"
] | null | null | null | hs_file_types/models/geofeature.py | tommac7/hydroshare | 87c4543a55f98103d2614bf4c47f7904c3f9c029 | [
"BSD-3-Clause"
] | null | null | null | hs_file_types/models/geofeature.py | tommac7/hydroshare | 87c4543a55f98103d2614bf4c47f7904c3f9c029 | [
"BSD-3-Clause"
] | null | null | null | import os
import logging
import shutil
import zipfile
import xmltodict
from lxml import etree
from osgeo import ogr, osr
from django.core.exceptions import ValidationError
from django.db import models, transaction
from django.utils.html import strip_tags
from django.template import Template, Context
from dominate.tags import legend, table, tbody, tr, th, div
from hs_core.models import Title, CoreMetaData
from hs_core.hydroshare import utils
from hs_core.forms import CoverageTemporalForm
from hs_core.signals import post_add_geofeature_aggregation
from hs_geographic_feature_resource.models import GeographicFeatureMetaDataMixin, \
OriginalCoverage, GeometryInformation, FieldInformation
from base import AbstractFileMetaData, AbstractLogicalFile, FileTypeContext
UNKNOWN_STR = "unknown"
def extract_metadata_and_files(resource, res_file, file_type=True):
"""
validates shape files and extracts metadata
:param resource: an instance of BaseResource
:param res_file: an instance of ResourceFile
:param file_type: A flag to control if extraction being done for file type or resource type
:return: a dict of extracted metadata, a list file paths of shape related files on the
temp directory, a list of resource files retrieved from iRODS for this processing
"""
shape_files, shp_res_files = get_all_related_shp_files(resource, res_file, file_type=file_type)
temp_dir = os.path.dirname(shape_files[0])
if not _check_if_shape_files(shape_files):
if res_file.extension.lower() == '.shp':
err_msg = "There was a problem parsing the component files associated with " \
"{folder_path} as a geographic shapefile. This may be because a component " \
"file is corrupt or missing. The .shp, .shx, and .dbf shapefile component " \
"files are required. Other shapefile component files " \
"(.cpg, .prj, .sbn, .sbx, .xml, .fbn, .fbx, .ain, .aih, .atx, .ixs, .mxs) " \
"should also be added where available."
err_msg = err_msg.format(folder_path=res_file.short_path)
else:
err_msg = "One or more dependent shape files are missing in the selected zip file " \
"or one or more files are not of shape file type."
if os.path.isdir(temp_dir):
shutil.rmtree(temp_dir)
raise ValidationError(err_msg)
shp_file = ''
for f in shape_files:
if f.lower().endswith('.shp'):
shp_file = f
break
try:
meta_dict = extract_metadata(shp_file_full_path=shp_file)
return meta_dict, shape_files, shp_res_files
except Exception as ex:
# remove temp dir
if os.path.isdir(temp_dir):
shutil.rmtree(temp_dir)
if file_type:
msg = "GeoFeature file type. Error when setting file type. Error:{}"
else:
msg = "Failed to parse the .shp file. Error{}"
msg = msg.format(ex.message)
raise ValidationError(msg)
def add_metadata(resource, metadata_dict, xml_file, logical_file=None):
"""
creates/updates metadata at resource and file level
:param resource: an instance of BaseResource
:param metadata_dict: dict containing extracted metadata
:param xml_file: file path (on temp directory) of the xml file that is part of the
geo feature files
:param logical_file: an instance of GeoFeatureLogicalFile if metadata needs to be part of the
logical file
:return:
"""
# populate resource and logical file level metadata
target_obj = logical_file if logical_file is not None else resource
if "coverage" in metadata_dict.keys():
coverage_dict = metadata_dict["coverage"]['Coverage']
target_obj.metadata.coverages.all().filter(type='box').delete()
target_obj.metadata.create_element('coverage',
type=coverage_dict['type'],
value=coverage_dict['value'])
originalcoverage_dict = metadata_dict["originalcoverage"]['originalcoverage']
if target_obj.metadata.originalcoverage is not None:
target_obj.metadata.originalcoverage.delete()
target_obj.metadata.create_element('originalcoverage', **originalcoverage_dict)
field_info_array = metadata_dict["field_info_array"]
target_obj.metadata.fieldinformations.all().delete()
for field_info in field_info_array:
field_info_dict = field_info["fieldinformation"]
target_obj.metadata.create_element('fieldinformation', **field_info_dict)
geometryinformation_dict = metadata_dict["geometryinformation"]
if target_obj.metadata.geometryinformation is not None:
target_obj.metadata.geometryinformation.delete()
target_obj.metadata.create_element('geometryinformation', **geometryinformation_dict)
if xml_file:
shp_xml_metadata_list = parse_shp_xml(xml_file)
for shp_xml_metadata in shp_xml_metadata_list:
if 'description' in shp_xml_metadata:
# overwrite existing description metadata - at the resource level
if not resource.metadata.description:
abstract = shp_xml_metadata['description']['abstract']
resource.metadata.create_element('description',
abstract=abstract)
elif 'title' in shp_xml_metadata:
title = shp_xml_metadata['title']['value']
title_element = resource.metadata.title
if title_element.value.lower() == 'untitled resource':
resource.metadata.update_element('title', title_element.id, value=title)
if logical_file is not None:
logical_file.dataset_name = title
logical_file.save()
elif 'subject' in shp_xml_metadata:
# append new keywords to existing keywords - at the resource level
existing_keywords = [subject.value.lower() for
subject in resource.metadata.subjects.all()]
keyword = shp_xml_metadata['subject']['value']
if keyword.lower() not in existing_keywords:
resource.metadata.create_element('subject', value=keyword)
# add keywords at the logical file level
if logical_file is not None:
if keyword not in logical_file.metadata.keywords:
logical_file.metadata.keywords += [keyword]
logical_file.metadata.save()
def get_all_related_shp_files(resource, selected_resource_file, file_type):
"""
This helper function copies all the related shape files to a temp directory
and return a list of those temp file paths as well as a list of existing related
resource file objects
:param resource: an instance of BaseResource to which the *selecetd_resource_file* belongs
:param selected_resource_file: an instance of ResourceFile selected by the user to set
GeoFeaureFile type (the file must be a .shp or a .zip file)
:param file_type: a flag (True/False) to control resource VS file type actions
:return: a list of temp file paths for all related shape files, and a list of corresponding
resource file objects
"""
shape_temp_files = []
shape_res_files = []
temp_dir = ''
if selected_resource_file.extension.lower() == '.shp':
for f in resource.files.all():
if f.file_folder == selected_resource_file.file_folder:
if f.extension.lower() == '.xml' and not f.file_name.lower().endswith('.shp.xml'):
continue
if f.extension.lower() in GeoFeatureLogicalFile.get_allowed_storage_file_types():
collect_shape_resource_files(f)
for f in shape_res_files:
temp_file = utils.get_file_from_irods(f)
if not temp_dir:
temp_dir = os.path.dirname(temp_file)
else:
file_temp_dir = os.path.dirname(temp_file)
dst_dir = os.path.join(temp_dir, os.path.basename(temp_file))
shutil.copy(temp_file, dst_dir)
shutil.rmtree(file_temp_dir)
temp_file = dst_dir
shape_temp_files.append(temp_file)
elif selected_resource_file.extension.lower() == '.zip':
temp_file = utils.get_file_from_irods(selected_resource_file)
temp_dir = os.path.dirname(temp_file)
if not zipfile.is_zipfile(temp_file):
if os.path.isdir(temp_dir):
shutil.rmtree(temp_dir)
raise ValidationError('Selected file is not a zip file')
zf = zipfile.ZipFile(temp_file, 'r')
zf.extractall(temp_dir)
zf.close()
for dirpath, _, filenames in os.walk(temp_dir):
for name in filenames:
if name == selected_resource_file.file_name:
# skip the user selected zip file
continue
file_path = os.path.abspath(os.path.join(dirpath, name))
shape_temp_files.append(file_path)
shape_res_files.append(selected_resource_file)
return shape_temp_files, shape_res_files
def _check_if_shape_files(files, temp_files=True):
"""
checks if the list of file temp paths in *files* are part of shape files
must have all these file extensions: (shp, shx, dbf)
:param files: list of files located in temp directory in django if temp_file is True, otherwise
list of resource files are from django db
:param temp_files: a flag to treat list of files *files* as temp files or not
:return: True/False
"""
# Note: this is the original function (check_fn_for_shp) in geo feature resource receivers.py
# used by is_shapefiles
# at least needs to have 3 mandatory files: shp, shx, dbf
if len(files) >= 3:
# check that there are no files with same extension
if temp_files:
# files are on temp directory
file_extensions = set([os.path.splitext(os.path.basename(f).lower())[1] for f in files])
else:
# files are in db
file_extensions = set([f.extension.lower() for f in files])
if len(file_extensions) != len(files):
return False
# check if there is the xml file
xml_file = ''
for f in files:
if temp_files:
# files are on temp directory
if f.lower().endswith('.shp.xml'):
xml_file = f
else:
# files are in db
if f.file_name.lower().endswith('.shp.xml'):
xml_file = f
if temp_files:
# files are on temp directory
file_names = set([os.path.splitext(os.path.basename(f))[0] for f in files if
not f.lower().endswith('.shp.xml')])
else:
# files are in db
file_names = set([os.path.splitext(os.path.basename(f.file_name))[0] for f in files if
not f.file_name.lower().endswith('.shp.xml')])
if len(file_names) > 1:
# file names are not the same
return False
# check if xml file name matches with other file names
if xml_file:
# -8 for '.shp.xml'
if temp_files:
# files are on temp directory
xml_file_name = os.path.basename(xml_file)
else:
# files are in db
xml_file_name = xml_file.file_name
if xml_file_name[:-8] not in file_names:
return False
for ext in file_extensions:
if ext not in GeoFeatureLogicalFile.get_allowed_storage_file_types():
return False
for ext in ('.shp', '.shx', '.dbf'):
if ext not in file_extensions:
return False
else:
return False
# test if we can open the shp file
if temp_files:
# files are on temp directory
shp_file = [f for f in files if f.lower().endswith('.shp')][0]
driver = ogr.GetDriverByName('ESRI Shapefile')
dataset = driver.Open(shp_file)
if dataset is None:
return False
dataset = None
return True
def extract_metadata(shp_file_full_path):
"""
Collects metadata from a .shp file specified by *shp_file_full_path*
:param shp_file_full_path:
:return: returns a dict of collected metadata
"""
try:
metadata_dict = {}
# wgs84 extent
parsed_md_dict = parse_shp(shp_file_full_path)
if parsed_md_dict["wgs84_extent_dict"]["westlimit"] != UNKNOWN_STR:
wgs84_dict = parsed_md_dict["wgs84_extent_dict"]
# if extent is a point, create point type coverage
if wgs84_dict["westlimit"] == wgs84_dict["eastlimit"] \
and wgs84_dict["northlimit"] == wgs84_dict["southlimit"]:
coverage_dict = {"Coverage": {"type": "point",
"value": {
"east": wgs84_dict["eastlimit"],
"north": wgs84_dict["northlimit"],
"units": wgs84_dict["units"],
"projection": wgs84_dict["projection"]
}}}
else: # otherwise, create box type coverage
coverage_dict = {"Coverage": {"type": "box",
"value": parsed_md_dict["wgs84_extent_dict"]}}
metadata_dict["coverage"] = coverage_dict
# original extent
original_coverage_dict = {}
original_coverage_dict["originalcoverage"] = {"northlimit":
parsed_md_dict
["origin_extent_dict"]["northlimit"],
"southlimit":
parsed_md_dict
["origin_extent_dict"]["southlimit"],
"westlimit":
parsed_md_dict
["origin_extent_dict"]["westlimit"],
"eastlimit":
parsed_md_dict
["origin_extent_dict"]["eastlimit"],
"projection_string":
parsed_md_dict
["origin_projection_string"],
"projection_name":
parsed_md_dict["origin_projection_name"],
"datum": parsed_md_dict["origin_datum"],
"unit": parsed_md_dict["origin_unit"]
}
metadata_dict["originalcoverage"] = original_coverage_dict
# field
field_info_array = []
field_name_list = parsed_md_dict["field_meta_dict"]['field_list']
for field_name in field_name_list:
field_info_dict_item = {}
field_info_dict_item['fieldinformation'] = \
parsed_md_dict["field_meta_dict"]["field_attr_dict"][field_name]
field_info_array.append(field_info_dict_item)
metadata_dict['field_info_array'] = field_info_array
# geometry
geometryinformation = {"featureCount": parsed_md_dict["feature_count"],
"geometryType": parsed_md_dict["geometry_type"]}
metadata_dict["geometryinformation"] = geometryinformation
return metadata_dict
except:
raise ValidationError("Parsing of shapefiles failed!")
def parse_shp(shp_file_path):
"""
:param shp_file_path: full file path fo the .shp file
output dictionary format
shp_metadata_dict["origin_projection_string"]: original projection string
shp_metadata_dict["origin_projection_name"]: origin_projection_name
shp_metadata_dict["origin_datum"]: origin_datum
shp_metadata_dict["origin_unit"]: origin_unit
shp_metadata_dict["field_meta_dict"]["field_list"]: list [fieldname1, fieldname2...]
shp_metadata_dict["field_meta_dict"]["field_attr_dic"]:
dict {"fieldname": dict {
"fieldName":fieldName,
"fieldTypeCode":fieldTypeCode,
"fieldType":fieldType,
"fieldWidth:fieldWidth,
"fieldPrecision:fieldPrecision"
}
}
shp_metadata_dict["feature_count"]: feature count
shp_metadata_dict["geometry_type"]: geometry_type
shp_metadata_dict["origin_extent_dict"]:
dict{"west": east, "north":north, "east":east, "south":south}
shp_metadata_dict["wgs84_extent_dict"]:
dict{"west": east, "north":north, "east":east, "south":south}
"""
shp_metadata_dict = {}
# read shapefile
driver = ogr.GetDriverByName('ESRI Shapefile')
dataset = driver.Open(shp_file_path)
# get layer
layer = dataset.GetLayer()
# get spatialRef from layer
spatialRef_from_layer = layer.GetSpatialRef()
if spatialRef_from_layer is not None:
shp_metadata_dict["origin_projection_string"] = str(spatialRef_from_layer)
prj_name = spatialRef_from_layer.GetAttrValue('projcs')
if prj_name is None:
prj_name = spatialRef_from_layer.GetAttrValue('geogcs')
shp_metadata_dict["origin_projection_name"] = prj_name
shp_metadata_dict["origin_datum"] = spatialRef_from_layer.GetAttrValue('datum')
shp_metadata_dict["origin_unit"] = spatialRef_from_layer.GetAttrValue('unit')
else:
shp_metadata_dict["origin_projection_string"] = UNKNOWN_STR
shp_metadata_dict["origin_projection_name"] = UNKNOWN_STR
shp_metadata_dict["origin_datum"] = UNKNOWN_STR
shp_metadata_dict["origin_unit"] = UNKNOWN_STR
field_list = []
filed_attr_dic = {}
field_meta_dict = {"field_list": field_list, "field_attr_dict": filed_attr_dic}
shp_metadata_dict["field_meta_dict"] = field_meta_dict
# get Attributes
layerDefinition = layer.GetLayerDefn()
for i in range(layerDefinition.GetFieldCount()):
fieldName = layerDefinition.GetFieldDefn(i).GetName()
field_list.append(fieldName)
attr_dict = {}
field_meta_dict["field_attr_dict"][fieldName] = attr_dict
attr_dict["fieldName"] = fieldName
fieldTypeCode = layerDefinition.GetFieldDefn(i).GetType()
attr_dict["fieldTypeCode"] = fieldTypeCode
fieldType = layerDefinition.GetFieldDefn(i).GetFieldTypeName(fieldTypeCode)
attr_dict["fieldType"] = fieldType
fieldWidth = layerDefinition.GetFieldDefn(i).GetWidth()
attr_dict["fieldWidth"] = fieldWidth
fieldPrecision = layerDefinition.GetFieldDefn(i).GetPrecision()
attr_dict["fieldPrecision"] = fieldPrecision
# get layer extent
layer_extent = layer.GetExtent()
# get feature count
featureCount = layer.GetFeatureCount()
shp_metadata_dict["feature_count"] = featureCount
# get a feature from layer
feature = layer.GetNextFeature()
# get geometry from feature
geom = feature.GetGeometryRef()
# get geometry name
shp_metadata_dict["geometry_type"] = geom.GetGeometryName()
# reproject layer extent
# source SpatialReference
source = spatialRef_from_layer
# target SpatialReference
target = osr.SpatialReference()
target.ImportFromEPSG(4326)
# create two key points from layer extent
left_upper_point = ogr.Geometry(ogr.wkbPoint)
left_upper_point.AddPoint(layer_extent[0], layer_extent[3]) # left-upper
right_lower_point = ogr.Geometry(ogr.wkbPoint)
right_lower_point.AddPoint(layer_extent[1], layer_extent[2]) # right-lower
# source map always has extent, even projection is unknown
shp_metadata_dict["origin_extent_dict"] = {}
shp_metadata_dict["origin_extent_dict"]["westlimit"] = layer_extent[0]
shp_metadata_dict["origin_extent_dict"]["northlimit"] = layer_extent[3]
shp_metadata_dict["origin_extent_dict"]["eastlimit"] = layer_extent[1]
shp_metadata_dict["origin_extent_dict"]["southlimit"] = layer_extent[2]
# reproject to WGS84
shp_metadata_dict["wgs84_extent_dict"] = {}
if source is not None:
# define CoordinateTransformation obj
transform = osr.CoordinateTransformation(source, target)
# project two key points
left_upper_point.Transform(transform)
right_lower_point.Transform(transform)
shp_metadata_dict["wgs84_extent_dict"]["westlimit"] = left_upper_point.GetX()
shp_metadata_dict["wgs84_extent_dict"]["northlimit"] = left_upper_point.GetY()
shp_metadata_dict["wgs84_extent_dict"]["eastlimit"] = right_lower_point.GetX()
shp_metadata_dict["wgs84_extent_dict"]["southlimit"] = right_lower_point.GetY()
shp_metadata_dict["wgs84_extent_dict"]["projection"] = "WGS 84 EPSG:4326"
shp_metadata_dict["wgs84_extent_dict"]["units"] = "Decimal degrees"
else:
shp_metadata_dict["wgs84_extent_dict"]["westlimit"] = UNKNOWN_STR
shp_metadata_dict["wgs84_extent_dict"]["northlimit"] = UNKNOWN_STR
shp_metadata_dict["wgs84_extent_dict"]["eastlimit"] = UNKNOWN_STR
shp_metadata_dict["wgs84_extent_dict"]["southlimit"] = UNKNOWN_STR
shp_metadata_dict["wgs84_extent_dict"]["projection"] = UNKNOWN_STR
shp_metadata_dict["wgs84_extent_dict"]["units"] = UNKNOWN_STR
return shp_metadata_dict
def parse_shp_xml(shp_xml_full_path):
"""
Parse ArcGIS 10.X ESRI Shapefile Metadata XML. file to extract metadata for the following
elements:
title
abstract
keywords
:param shp_xml_full_path: Expected fullpath to the .shp.xml file
:return: a list of metadata dict
"""
metadata = []
try:
if os.path.isfile(shp_xml_full_path):
with open(shp_xml_full_path) as fd:
xml_dict = xmltodict.parse(fd.read())
dataIdInfo_dict = xml_dict['metadata']['dataIdInfo']
if 'idCitation' in dataIdInfo_dict:
if 'resTitle' in dataIdInfo_dict['idCitation']:
if '#text' in dataIdInfo_dict['idCitation']['resTitle']:
title_value = dataIdInfo_dict['idCitation']['resTitle']['#text']
else:
title_value = dataIdInfo_dict['idCitation']['resTitle']
title_max_length = Title._meta.get_field('value').max_length
if len(title_value) > title_max_length:
title_value = title_value[:title_max_length-1]
title = {'title': {'value': title_value}}
metadata.append(title)
if 'idAbs' in dataIdInfo_dict:
description_value = strip_tags(dataIdInfo_dict['idAbs'])
description = {'description': {'abstract': description_value}}
metadata.append(description)
if 'searchKeys' in dataIdInfo_dict:
searchKeys_dict = dataIdInfo_dict['searchKeys']
if 'keyword' in searchKeys_dict:
keyword_list = []
if type(searchKeys_dict["keyword"]) is list:
keyword_list += searchKeys_dict["keyword"]
else:
keyword_list.append(searchKeys_dict["keyword"])
for k in keyword_list:
metadata.append({'subject': {'value': k}})
except Exception:
# Catch any exception silently and return an empty list
# Due to the variant format of ESRI Shapefile Metadata XML
# among different ArcGIS versions, an empty list will be returned
# if any exception occurs
metadata = []
finally:
return metadata
| 44.547977 | 100 | 0.61338 |
b7b9397bbe8da7007b207fc6a20f4e6b29704b5a | 1,313 | py | Python | tests/test_node.py | mjholtkamp/py-iptree | 97025f03247dbc91424898fd28f7be1448d5fce5 | [
"Apache-2.0"
] | null | null | null | tests/test_node.py | mjholtkamp/py-iptree | 97025f03247dbc91424898fd28f7be1448d5fce5 | [
"Apache-2.0"
] | null | null | null | tests/test_node.py | mjholtkamp/py-iptree | 97025f03247dbc91424898fd28f7be1448d5fce5 | [
"Apache-2.0"
] | null | null | null | import unittest
from iptree import IPNode
| 28.543478 | 62 | 0.552932 |
b7b981be89ff3733793d9540e9d6338ff12dd2df | 208 | py | Python | Codewars/8kyu/invert-values/Python/test.py | RevansChen/online-judge | ad1b07fee7bd3c49418becccda904e17505f3018 | [
"MIT"
] | 7 | 2017-09-20T16:40:39.000Z | 2021-08-31T18:15:08.000Z | Codewars/8kyu/invert-values/Python/test.py | RevansChen/online-judge | ad1b07fee7bd3c49418becccda904e17505f3018 | [
"MIT"
] | null | null | null | Codewars/8kyu/invert-values/Python/test.py | RevansChen/online-judge | ad1b07fee7bd3c49418becccda904e17505f3018 | [
"MIT"
] | null | null | null | # Python - 3.4.3
Test.it('Basic Tests')
Test.assert_equals(invert([1, 2, 3, 4, 5]), [-1, -2, -3, -4, -5])
Test.assert_equals(invert([1, -2, 3, -4, 5]), [-1, 2, -3, 4, -5])
Test.assert_equals(invert([]), [])
| 29.714286 | 65 | 0.548077 |
b7ba3cc002a49b7880bf396084b5e2214c7d5cdf | 1,239 | py | Python | locustfile_create_order.py | Ashutosh-Kaushik/ss-load-test-locust | 286e3cecad39f5ce991717e117392332a9810d64 | [
"Apache-2.0"
] | 1 | 2022-03-31T05:34:33.000Z | 2022-03-31T05:34:33.000Z | locustfile_create_order.py | Ashutosh-Kaushik/ss-load-test-locust | 286e3cecad39f5ce991717e117392332a9810d64 | [
"Apache-2.0"
] | null | null | null | locustfile_create_order.py | Ashutosh-Kaushik/ss-load-test-locust | 286e3cecad39f5ce991717e117392332a9810d64 | [
"Apache-2.0"
] | null | null | null | import csv
import random
import warnings
import os
from locust import HttpUser, task, between
body = {
"campaignid":"5kXk20gGDISJdM5el5IT",
"walletamount":"0"
}
header = {
"Host": "fkhapi.sastasundar.com",
"Apptype": "N",
"Appversion": "4.0.4",
"Appversioncode": "109",
"Deviceid": "81653dce-0dd2-4201-8916-4aecbdd89269",
"Devicedensity": "320",
"Devicedensitytype": "xhdpi",
"Deviceheight": "1184",
"Devicewidth": "768",
"Devicename": "Unknown Google Nexus 4",
"Deviceosinfo": "5.1",
"Networkinfo": "Wifi",
"Accesstoken": "PDWZ5pStjE",
"Refdeviceid": "4dd29c0f2f8d1842",
"Userid": "4937724",
"Pincode": "700120",
"Is_panindia": "0",
"Warehouse_id": "1",
"Content-Type": "application/json",
"Content-Length": "56",
"Accept-Encoding": "gzip, deflate",
"User-Agent": "okhttp/5.0.0-alpha.2"
} | 25.8125 | 88 | 0.637611 |
b7bae45b9bc9f5897fbcca4960ef6f0a8e4b7699 | 1,358 | py | Python | compy/plot/grid.py | tilleyd/compy | b63188341d0c66c0ecd810e29918e569c519b296 | [
"MIT"
] | null | null | null | compy/plot/grid.py | tilleyd/compy | b63188341d0c66c0ecd810e29918e569c519b296 | [
"MIT"
] | null | null | null | compy/plot/grid.py | tilleyd/compy | b63188341d0c66c0ecd810e29918e569c519b296 | [
"MIT"
] | null | null | null | """Contains the grid class to create multiple figures."""
from typing import Optional, Tuple
from .figure import Figure
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
| 29.521739 | 78 | 0.581001 |
b7bb34b596fa5c54c79635a6e0d79f862d482ebf | 30,005 | py | Python | parallel_accel/shared/parallel_accel/shared/schemas/external.py | google/parallel_accel | b58fda1c3a22f2aaa9a97337d602cd72c49ee8be | [
"Apache-2.0"
] | 1 | 2021-12-19T21:17:02.000Z | 2021-12-19T21:17:02.000Z | parallel_accel/shared/parallel_accel/shared/schemas/external.py | google/parallel_accel | b58fda1c3a22f2aaa9a97337d602cd72c49ee8be | [
"Apache-2.0"
] | null | null | null | parallel_accel/shared/parallel_accel/shared/schemas/external.py | google/parallel_accel | b58fda1c3a22f2aaa9a97337d602cd72c49ee8be | [
"Apache-2.0"
] | null | null | null | # Copyright 2021 The ParallelAccel Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://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.
# ==============================================================================
"""This module provides types definitions."""
import dataclasses
import enum
import json
import time
from typing import Any, Dict, List, Optional, Union
import uuid
import linear_algebra
import marshmallow
import marshmallow_dataclass
import marshmallow_enum
#####################################
# Utility functions #
#####################################
def decode(
schema: marshmallow.Schema, data: str, **kwargs
) -> dataclasses.dataclass:
"""Decodes input string using provided schema.
Args:
schema: Schema to be used for deserialization.
data: JSON-encoded data to be deserialized.
**kwargs: Extra keyworded arguments to be passed to
`marshmallow.Schemas.loads` method.
Returns:
Deserialized `dataclasses.dataclass` object.
"""
return schema.loads(data, **kwargs)
def encode(
schema: marshmallow.Schema, data: dataclasses.dataclass, **kwargs
) -> str:
"""Encodes input data using provided schema.
Args:
schema: Schema to be used for serialization.
data: Dataclass object to be serialized.
**kwargs: Extra keyworded arguments to be passed to
`marshmallow.Schemas.dumps` method.
Returns:
JSON-encoded serialized data.
"""
return schema.dumps(data, separators=(",", ":"), **kwargs)
#####################################
# Types aliases #
#####################################
OperatorsType = List[linear_algebra.ops.ProbBasisAxisSum]
#####################################
# marshmallow helpers #
#####################################
_SerializedLinearAlgebraObject = Dict[str, Any]
_SerializedProbBasisAxisSums = List[List[Dict[str, Any]]]
# `linear_algebra` offers only functions to dump and load objects from the JSON encoded
# string, and does not support builtin dict objects. When we call json.dumps()
# over already JSON encoded string, all quotation marks and brackets are
# prefixed with the backslash. Instead, we can convert JSON object to the dict
# type and reduce serialized object size.
def _deserialize_linear_algebra_object(data: _SerializedLinearAlgebraObject) -> Any:
"""Deserializes linear_algebra object from dict type.
Since `linear_algebra` does not provide function to load objects from builtin dict
objects, we need some workaround here: first we dump the dict object into
JSON encoded string, then parse them into `linear_algebra` object.
Args:
data: Dict encoded linear_algebra object.
Returns:
Deserialized linear_algebra object.
"""
return linear_algebra.read_json(json_text=json.dumps(data))
def _serialize_linear_algebra_object(obj: Any) -> _SerializedLinearAlgebraObject:
"""Serializes linear_algebra object to dict type.
Since `linear_algebra` does not provide function to dump objects into builtin dict
objects, we need some workaround here: first we dump the `linear_algebra` object into
JSON encoded string, then parsing them into dict object.
Args:
data: linear_algebra object to be encoded.
Returns:
Serialized linear_algebra object.
"""
return json.loads(linear_algebra.to_json(obj))
Graph = marshmallow_dataclass.NewType(
"Graph", linear_algebra.Graph, field=_LinearAlgebraField
)
Operators = marshmallow_dataclass.NewType(
"Operators", OperatorsType, field=_OperatorsField
)
ParamResolver = marshmallow_dataclass.NewType(
"ParamResolver", linear_algebra.ParamResolver, field=_LinearAlgebraField
)
Result = marshmallow_dataclass.NewType("Result", linear_algebra.Result, field=_LinearAlgebraField)
Sweepable = marshmallow_dataclass.NewType(
"Sweepable", linear_algebra.study.Sweepable, field=_LinearAlgebraField
)
#####################################
# Server side events #
#####################################
#####################################
# API relevant types #
#####################################
#####################################
# Jobs relevant types #
#####################################
class JobStatus(enum.IntEnum):
"""Current job status.
Attributes:
NOT_STARTED: The job was added to the queue.
IN_PROGRESS: The job is being processed.
COMPLETE: Simulation has been completed successfully.
ERROR: Simulation has failed.
"""
NOT_STARTED = 0
IN_PROGRESS = 1
COMPLETE = 2
ERROR = 3
#####################################
# Expectation job relevant types #
#####################################
########################################
# Noisy expectation job relevant types #
########################################
#####################################
# Sample job relevant types #
#####################################
#####################################
# Jobs queue relevant types #
#####################################
class JobType(enum.IntEnum):
"""Simulation job type.
Attributes:
SAMPLE: Sampling.
EXPECTATION: Expectation values.
NOISY_EXPECTATION: Noisy expectation values.
"""
SAMPLE = 0
EXPECTATION = 1
NOISY_EXPECTATION = 2
#####################################
# Tasks relevant types #
#####################################
class TaskState(enum.IntEnum):
"""Current task state.
Attributes:
PENDING: Task is scheduled for execution.
RUNNING: Task is running.
DONE: Task is finished.
"""
PENDING = 0
RUNNING = 1
DONE = 2
#####################################
# Worker relevant types #
#####################################
class WorkerState(enum.IntEnum):
"""ASIC worker state.
Attributes:
BOOTING: Worker is booting.
ERROR: Worker encountered an error.
IDLE: Worker is idling.
OFFLINE: Worker is offline.
PROCESSING_JOB: Worker is processing a job.
SHUTTING_DOWN: Worker is shutting down.
"""
OFFLINE = 0
BOOTING = 1
SHUTTING_DOWN = 2
IDLE = 3
PROCESSING_JOB = 4
ERROR = 5
#####################################
# marshmallow schemas #
#####################################
class _SSERenderer:
"""A helper class for serializing and deserializing objects to server side
events message format.
The server side event message is UTF-8 text data separated by a pair of
newline characters.
"""
(
APIErrorSchema,
ExpectationBatchJobContextSchema,
ExpectationBatchJobResultSchema,
ExpectationJobContextSchema,
ExpectationJobResultSchema,
ExpectationJobStatusEventSchema,
ExpectationSweepJobContextSchema,
ExpectationSweepJobResultSchema,
JobProgressSchema,
JobResultSchema,
JobStatusEventSchema,
JobSubmittedSchema,
JobsQueueSchema,
NoisyExpectationJobContextSchema,
NoisyExpectationJobResultSchema,
NoisyExpectationJobStatusEventSchema,
PendingJobSchema,
SampleBatchJobContextSchema,
SampleBatchJobResultSchema,
SampleJobContextSchema,
SampleJobResultSchema,
SampleJobStatusEventSchema,
SampleSweepJobContextSchema,
SampleSweepJobResultSchema,
ServerSideEventSchema,
StreamTimeoutEventSchema,
TaskStatusEventSchema,
TaskStatusSchema,
TaskSubmittedSchema,
WorkerSchema,
) = tuple(
marshmallow_dataclass.class_schema(x, base_schema=y)()
for x, y in (
(APIError, None),
(ExpectationBatchJobContext, None),
(ExpectationBatchJobResult, _BaseSchema),
(ExpectationJobContext, None),
(ExpectationJobResult, _BaseSchema),
(ExpectationJobStatusEvent, _SSEBaseSchema),
(ExpectationSweepJobContext, None),
(ExpectationSweepJobResult, _BaseSchema),
(JobProgress, None),
(JobResult, _BaseSchema),
(JobStatusEvent, _SSEBaseSchema),
(JobSubmitted, None),
(JobsQueue, None),
(NoisyExpectationJobContext, None),
(NoisyExpectationJobResult, _BaseSchema),
(NoisyExpectationJobStatusEvent, _SSEBaseSchema),
(PendingJob, None),
(SampleBatchJobContext, None),
(SampleBatchJobResult, _BaseSchema),
(SampleJobContext, None),
(SampleJobResult, _BaseSchema),
(SampleJobStatusEvent, _SSEBaseSchema),
(SampleSweepJobContext, None),
(SampleSweepJobResult, _BaseSchema),
(ServerSideEvent, _SSEBaseSchema),
(StreamTimeoutEvent, _SSEBaseSchema),
(TaskStatusEvent, _SSEBaseSchema),
(TaskStatus, _BaseSchema),
(TaskSubmitted, None),
(Worker, _BaseSchema),
)
)
| 28.549001 | 113 | 0.627629 |
b7bb41a1d668770a899b52a1a2113000001bd07c | 1,040 | py | Python | godot-toolkit/godot_config_file.py | WiggleWizard/godot-toolkit | e17b7666ed80e3ab25ee65c43eb1ba9b13634070 | [
"MIT"
] | null | null | null | godot-toolkit/godot_config_file.py | WiggleWizard/godot-toolkit | e17b7666ed80e3ab25ee65c43eb1ba9b13634070 | [
"MIT"
] | null | null | null | godot-toolkit/godot_config_file.py | WiggleWizard/godot-toolkit | e17b7666ed80e3ab25ee65c43eb1ba9b13634070 | [
"MIT"
] | null | null | null | try:
from configparser import RawConfigParser
except ImportError:
from ConfigParser import RawConfigParser
| 41.6 | 79 | 0.5 |
b7bd5a3b425952bf3f2c75d16b604d8c223988c4 | 683 | py | Python | DMOJ/CCC/escape room.py | eddiegz/Personal-C | f7869826216e5c665f8f646502141f0dc680e545 | [
"MIT"
] | 3 | 2021-05-15T08:18:09.000Z | 2021-05-17T04:41:57.000Z | DMOJ/CCC/escape room.py | eddiegz/Personal-C | f7869826216e5c665f8f646502141f0dc680e545 | [
"MIT"
] | null | null | null | DMOJ/CCC/escape room.py | eddiegz/Personal-C | f7869826216e5c665f8f646502141f0dc680e545 | [
"MIT"
] | null | null | null | import collections
m=int(input())
n=int(input())
grid=[]
for i in range(m):
grid.append(list(map(int,input().split())))
factor=collections.defaultdict(list)
print('yes' if dfs(0, 0) else 'no')
| 22.032258 | 58 | 0.513909 |
b7bd809bb95458cc851905998de0d036112332ab | 2,556 | py | Python | volume_loader.py | xeTaiz/deep-volumetric-ambient-occlusion | 8492ad957f1440d5bf93139f7cf9ee4c7997b0e2 | [
"MIT"
] | 9 | 2020-08-24T20:03:17.000Z | 2022-02-17T07:38:55.000Z | volume_loader.py | xeTaiz/deep-volumetric-ambient-occlusion | 8492ad957f1440d5bf93139f7cf9ee4c7997b0e2 | [
"MIT"
] | null | null | null | volume_loader.py | xeTaiz/deep-volumetric-ambient-occlusion | 8492ad957f1440d5bf93139f7cf9ee4c7997b0e2 | [
"MIT"
] | 1 | 2021-07-12T01:39:24.000Z | 2021-07-12T01:39:24.000Z | import os
import pydicom
import numpy as np
import dicom_numpy
from utils import hidden_errors
from tf_utils import *
from pathlib import Path
def read_dicom_folder(dicom_folder, rescale=None):
''' Reads all .dcm files in `dicom_folder` and merges them to one volume
Returns:
The volume and the affine transformation from pixel indices to xyz coordinates
'''
dss = [pydicom.dcmread(str(dicom_folder/dcm)) for dcm in os.listdir(dicom_folder) if dcm.endswith('.dcm')]
vol, mat = dicom_numpy.combine_slices(dss, rescale)
return vol, dss[0]
def get_largest_dir(dirs, minsize=100):
''' Returns the dir with the most files from `dirs`'''
m = max(dirs, key=lambda d: len(os.listdir(d)) if os.path.isdir(d) else 0)
if len(os.listdir(m)) >= minsize: return m
else: return None
__all__ = ['read_dicom_folder', 'get_largest_dir', 'get_volume_gen', 'get_volume_dirs']
| 44.068966 | 127 | 0.620892 |
b7c03a0cfc79b571a75dfb907cc43fbd5d0b1bf0 | 5,056 | py | Python | sudoku_solver/gui.py | andrewhalle/sudoku_solver | 56b88c49a3637449507a9afa66ec3d617d2118a5 | [
"MIT"
] | null | null | null | sudoku_solver/gui.py | andrewhalle/sudoku_solver | 56b88c49a3637449507a9afa66ec3d617d2118a5 | [
"MIT"
] | null | null | null | sudoku_solver/gui.py | andrewhalle/sudoku_solver | 56b88c49a3637449507a9afa66ec3d617d2118a5 | [
"MIT"
] | null | null | null | import sys
from PyQt5.QtCore import Qt, QSize, QPoint
from PyQt5.QtWidgets import QApplication, QDialog, QWidget, QLabel, QPushButton, QVBoxLayout, QHBoxLayout
from PyQt5.QtGui import QPainter, QColor, QPen, QFont
from .sudoku import Sudoku
def main():
app = QApplication([])
gui = SudokuDialog()
sys.exit(app.exec_())
| 36.637681 | 135 | 0.585443 |