xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

80c8b22e2af2e7e9134a3bdb298e726d8fa534fb

94

py

Python

src/jt/jpy/__config__.py

karpierz/jtypes.jpy

28c94ba7f267f0f2626806675eeea443f8546ea1

[ "Apache-2.0" ]

null

src/jt/jpy/__config__.py

karpierz/jtypes.jpy

28c94ba7f267f0f2626806675eeea443f8546ea1

[ "Apache-2.0" ]

null

src/jt/jpy/__config__.py

karpierz/jtypes.jpy

28c94ba7f267f0f2626806675eeea443f8546ea1

[ "Apache-2.0" ]

null

__import__("jvm._util", globals(), None, ["make_config"], 2).make_config("jpy.cfg", "jt.jpy")

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80f840e3522aec5277d91519f019fd687b7575c2

28,738

py

Python

json_api.py

sphoebs/rockshell

a28297b2a3837e63ac7970344a598e51b0c298bc

[ "Apache-2.0" ]

null

json_api.py

sphoebs/rockshell

a28297b2a3837e63ac7970344a598e51b0c298bc

[ "Apache-2.0" ]

null

json_api.py

sphoebs/rockshell

a28297b2a3837e63ac7970344a598e51b0c298bc

[ "Apache-2.0" ]

null

''' Created on Sep 15, 2014 @author: beatricevaleri ''' import fix_path import webapp2 import json from social_login import set_cookie from models import PFuser, Place, Rating, Discount, Coupon, get_db # from __builtin__ import list import logging # from google.appengine.api.datastore_types import GeoPt import logic import time import config from google.appengine.api import taskqueue class MainHandler(webapp2.RequestHandler): def get(self): self.response.write('The api is working!') class UserHandler(webapp2.RequestHandler): def get(self): if 'role' in self.request.url: self.response.set_status(405) return auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) if user_id is None: self.response.set_status(403) self.response.write("You must login first!") return user, status, errcode = logic.user_get(user_id, None) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(PFuser.to_json(user, ['key','first_name','last_name','full_name', 'picture', 'home', 'visited_city', 'settings', 'role'], ['user_id', 'fb_user_id', 'fb_access_token','google_user_id', 'google_access_token', 'created', 'updated,' 'email', 'profile', 'age', 'gender']))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def post(self): post_data = json.loads(self.request.body) if post_data is None: self.response.set_status(400) self.response.write('Missing body') return; if 'role' in self.request.url: if 'key' in post_data: user, status, errcode = logic.user_get(None, post_data['key']) elif 'email' in post_data: user, status, errcode = logic.user_get_by_email(post_data['email']) else: self.response.set_status(400) self.response.write('Missing email or user key') return; if status != "OK": self.response.set_status(errcode) self.response.write(status) if 'role' in post_data: if post_data['role'] == 'None': user.role = None elif post_data['role'] == 'admin': user.role = 'admin' else: self.response.set_status(400) self.response.write('Missing role') return; user, status, errcode = logic.user_update(user, user.key.id(), None) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(PFuser.to_json(user, ['key','first_name','last_name','full_name', 'picture', 'home', 'visited_city', 'settings', 'role'], ['user_id', 'fb_user_id', 'fb_access_token','google_user_id', 'google_access_token', 'created', 'updated,' 'email', 'profile', 'age', 'gender']))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) else: # logging.warn('POST DATA: ' + str(post_data)) try: user = PFuser.from_json(post_data) except TypeError, e: self.response.set_status(400) self.response.write(str(e)) return except Exception, e: self.response.set_status(400) self.response.write(str(e)) return # logging.warn('USER: ' + str(user)) user, status, errcode = logic.user_create(user) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(PFuser.to_json(user, ['key','first_name','last_name','full_name', 'picture', 'home', 'visited_city', 'settings', 'role'], ['user_id', 'fb_user_id', 'fb_access_token','google_user_id', 'google_access_token', 'created', 'updated,' 'email', 'profile', 'age', 'gender']))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def put(self): if 'role' in self.request.url: self.response.set_status(405) return auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) if user_id is None: self.response.set_status(403) self.response.write("You must login first!") return post_data = json.loads(self.request.body) if post_data is None: self.response.set_status(400) self.response.write('Missing body') user = PFuser(post_data) user, status, errcode = logic.user_update(user, user_id, None) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(PFuser.to_json(user, ['key','first_name','last_name','full_name', 'picture', 'home', 'visited_city', 'settings', 'role'], ['user_id', 'fb_user_id', 'fb_access_token','google_user_id', 'google_access_token', 'created', 'updated,' 'email', 'profile', 'age', 'gender']))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) class UserLoginHandler(webapp2.RequestHandler): def post(self): # Saves/retrieves user when he/she logs in post_data = json.loads(self.request.body) if post_data is None: self.response.set_status(400) self.response.write('Missing body') elif 'token' in post_data and 'service' in post_data: user, is_new, status = logic.user_login( post_data['token'], post_data['service']) if status == "OK": try: set_cookie(self.response, 'user', user.user_id, expires=time.time() + config.LOGIN_COOKIE_DURATION, encrypt=True) self.response.headers['Content-Type'] = 'application/json' tmp = json.dumps(PFuser.to_json(user, ['key','first_name','last_name','full_name', 'picture', 'home', 'visited_city', 'settings', 'role'], ['user_id', 'fb_user_id', 'fb_access_token','google_user_id', 'google_access_token', 'created', 'updated,' 'email', 'profile', 'age', 'gender'])) tmp['is_new'] = is_new self.response.write(tmp) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(400) self.response.write(status) else: self.response.set_status(400) self.response.write('Wrong body content') def delete(self): auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) if user_id is None: self.response.write('ok') set_cookie(self.response, 'user', user_id, expires=0, encrypt=True) self.response.write('ok') class PlaceListHandler(webapp2.RequestHandler): def get(self): auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) if 'owned' not in self.request.url: get_values = self.request.GET logging.info("GET PLACES filters: " + str(get_values)) filters = {} if not get_values: get_values = None else: filters['city'] = get_values.get('city') filters['lat'] = get_values.get('lat') filters['lon'] = get_values.get('lon') filters['max_dist'] = get_values.get('max_dist') # plist is already in json. plist, status, errcode = logic.place_list_get(filters, user_id) else : plist, status, errcode = logic.place_owner_list(user_id) if status == "OK": self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(plist)) else: self.response.set_status(errcode) self.response.write(status) def post(self): if 'owned' in self.request.url: self.response.set_status(405) return logging.info("Received new place to save: " + self.request.body) # TODO: only an admin can create new places # auth = self.request.headers.get("Authorization") # if auth is None or len(auth) < 1: # auth = self.request.cookies.get("user") # if auth is None: # user_id = None # else: # user_id = logic.get_current_userid(auth) # if user_id is None: # self.response.set_status(403) # self.response.write("You must login first!") # return body = json.loads(self.request.body) try: place = Place.from_json(body) except TypeError, e: self.response.set_status(400) self.response.write(str(e)) return except Exception, e: self.response.set_status(400) self.response.write(str(e)) return place, status, errcode = logic.place_create(place) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(Place.to_json(place, None, None))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) class PlaceHandler(webapp2.RequestHandler): def get(self, pid): if 'owner' in self.request.url: self.response.set_status(405) return logging.info("Received get place : " + str(pid)) place, status, errcode = logic.place_get(None, pid) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(Place.to_json(place, None,None))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def post(self, pid): if 'owner' not in self.request.url: self.response.set_status(405) return auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") if auth is None: req_id = None else: req_id = logic.get_current_userid(auth) if req_id is None: self.response.set_status(403) self.response.write("You must login first!") return #the body contains at least the email of the user to be set as owner of the place body = json.loads(self.request.body) try: user = PFuser.from_json(body) except TypeError, e: self.response.set_status(400) self.response.write(str(e)) return except Exception, e: self.response.set_status(400) self.response.write(str(e)) return place, status, errcode = logic.place_set_owner(pid, user.email, req_id) if status == "OK": try: self.response.set_status(200) self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(Place.to_json(place, None,None))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def put(self, pid): if 'owner' in self.request.url: self.response.set_status(405) return # auth = self.request.headers.get("Authorization") # if auth is None or len(auth) < 1: # auth = self.request.cookies.get("user") # if auth is None: # user_id = None # else: # user_id = logic.get_current_userid(auth) # if user_id is None: # self.response.set_status(403) # self.response.write("You must login first!") # return body = json.loads(self.request.body) try: place = Place.from_json(body) except TypeError, e: self.response.set_status(400) self.response.write(str(e)) return except Exception, e: self.response.set_status(400) self.response.write(str(e)) return place, status, errcode = logic.place_update(place, None, pid) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' place = Place.to_json(place, None,None) logging.info('Place json: ' + str(place)) self.response.write(json.dumps(place)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def delete(self, pid): if 'owner' in self.request.url: self.response.set_status(405) return auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) user = PFuser.get_by_key(PFuser.make_key(user_id, None)) if user is None or user.role != 'admin': self.response.set_status(403) self.response.write("You must login first!") return res, status, errcode = logic.place_delete(None, pid) if status == "OK": if res == True: self.response.write("The place " + pid + " has been deleted successfully") else: self.response.write("The place " + pid + " cannot be deleted") else: self.response.set_status(errcode) self.response.write(status) class RatingHandler(webapp2.RequestHandler): def post(self): auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") if auth is None: user_id = None else: user_id = logic.get_current_userid(auth) # if user_id is None: # self.response.set_status(403) # self.response.write("You must login first!") # return body = json.loads(self.request.body) try: rating = Rating.from_json(body) except TypeError, e: self.response.set_status(400) self.response.write(str(e)) return except Exception, e: self.response.set_status(400) self.response.write(str(e)) return # if user_id is not None: rating, status, errcode = logic.rating_create(rating, user_id, None) # else : # rating, status, errcode = logic.rating_create(rating, None, None) logging.info(status) if status == "OK": try: self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(Rating.to_json(rating, ['key', 'user', 'place', 'purpose', 'value', 'not_known'], ['creation_time']))) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) class DiscountListHandler(webapp2.RequestHandler): def get(self): #get list of discounts, with filters auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) get_values = self.request.GET filters = {} filters['place'] = get_values.get('place') filters['coupon_user'] = get_values.get('coupon_user') filters['published'] = get_values.get('published') filters['passed'] = get_values.get('passed') dlist, status, errcode = logic.discount_list_get(filters, user_id) if status == "OK": try: dlist = [Discount.to_json(d, None, None) for d in dlist] self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(dlist)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def post(self): #create discount auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) body = json.loads(self.request.body) try: discount = Discount.from_json(body) except TypeError, e: self.response.set_status(400) self.response.write(str(e)) return except Exception, e: self.response.set_status(400) self.response.write(str(e)) return discount, status, errcode = logic.discount_create(discount, user_id) if status == "OK": try: discount = Discount.to_json(discount, None, None) self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(discount)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) class DiscountHandler(webapp2.RequestHandler): def get(self, key): auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) if 'publish' in self.request.url: #publish discount discount, status, errcode = logic.discount_publish(key, user_id) else: #get discount discount, status, errcode = logic.discount_get(key, user_id) if status == "OK": try: discount = Discount.to_json(discount, None, None) self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(discount)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def put(self, key): if 'publish' in self.request.url: self.response.set_status(405) return #update discount auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) body = json.loads(self.request.body) try: discount = Discount.from_json(body) except TypeError, e: self.response.set_status(400) self.response.write(str(e)) return except Exception, e: self.response.set_status(400) self.response.write(str(e)) return discount, status, errcode = logic.discount_update(discount, key, user_id) if status == "OK": try: discount = Discount.to_json(discount, None, None) self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(discount)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def delete(self, key): if 'publish' in self.request.url: self.response.set_status(405) return #delete discount auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) res, status, errcode = logic.discount_delete(key, user_id) if status == "OK": if res == True: self.response.headers['Content-Type'] = 'application/json' self.response.write('{}') elif res == False: self.response.set_status(409) self.response.write("{'error': 'The discount cannot be deleted!'}") else: self.response.set_status(errcode) self.response.write(status) class CouponHandler(webapp2.RequestHandler): def get(self, dkey): auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) code = self.request.GET.get('code') if 'use' in self.request.url: #use coupon coupon, status, errcode = logic.coupon_use(dkey, user_id, code) else: #get coupon coupon, status, errcode = logic.coupon_get_by_code(dkey, user_id, code) if status == "OK": try: coupon = Coupon.to_json(coupon, None, None) self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(coupon)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def post(self, dkey): if 'use' in self.request.url: self.response.set_status(405) return #create coupon auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) coupon, status, errcode = logic.coupon_create(dkey, user_id) if status == "OK": try: coupon = Coupon.to_json(coupon, None, None) self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(coupon)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) def delete(self, dkey): if 'use' in self.request.url: self.response.set_status(405) return #delete coupon auth = self.request.headers.get("Authorization") if auth is None or len(auth) < 1: auth = self.request.cookies.get("user") user_id = logic.get_current_userid(auth) code = self.request.GET.get('code') coupon, status, errcode = logic.coupon_delete(dkey, user_id, code) if status == "OK": try: coupon = Coupon.to_json(coupon, None, None) self.response.headers['Content-Type'] = 'application/json' self.response.write(json.dumps(coupon)) except TypeError, e: self.response.set_status(500) self.response.write(str(e)) else: self.response.set_status(errcode) self.response.write(status) class PlaceMysqlHandler(webapp2.RequestHandler): def get(self): if 'task' in self.request.url: q = taskqueue.Queue('update-clusters-queue') task = taskqueue.Task(url='/api/mysql/places', method='GET') q.add(task) return #json list of places db = get_db() #clear database table try: cursor = db.cursor() sql = 'DELETE FROM places' # logging.info("SQL: " + sql) cursor.execute(sql) db.commit() except ValueError as e: logging.error("Error while deleting data fom places table: " + str(e)) finally: db.close() places, status, errcode = logic.place_list_get({}, None) if places is not None and status == "OK": for p in places: db = get_db() try: cursor = db.cursor() sql = 'INSERT INTO places (pkey, lat, lon) VALUES ("%s", %f, %f)' % (p['key'], p['address']['lat'], p['address']['lon']) # logging.info("SQL: " + sql) cursor.execute(sql) db.commit() except ValueError: logging.error("Invalid data for place: %s, %f, %f" % (p['key'], p['address']['lat'], p['address']['lon'])) finally: db.close() self.response.set_status(200) self.response.write('{}') else: self.response.set_status(errcode) self.response.write(status) app = webapp2.WSGIApplication([ webapp2.Route(r'/api/', handler=MainHandler), webapp2.Route(r'/api/user', handler=UserHandler), webapp2.Route(r'/api/user/role', handler=UserHandler), webapp2.Route(r'/api/user/login', handler=UserLoginHandler), webapp2.Route(r'/api/place', handler=PlaceListHandler), webapp2.Route(r'/api/place/owned', handler=PlaceListHandler), webapp2.Route(r'/api/place/<pid>', handler=PlaceHandler), webapp2.Route(r'/api/place/<pid>/owner', handler=PlaceHandler), webapp2.Route(r'/api/rating', handler=RatingHandler), webapp2.Route(r'/api/discount', handler=DiscountListHandler), webapp2.Route(r'/api/discount/<key>', handler=DiscountHandler), webapp2.Route(r'/api/discount/<key>/publish', handler=DiscountHandler), webapp2.Route(r'/api/discount/<dkey>/coupon', handler=CouponHandler), webapp2.Route(r'/api/discount/<dkey>/coupon/use', handler=CouponHandler), webapp2.Route(r'/api/mysql/places', handler=PlaceMysqlHandler), webapp2.Route(r'/api/mysql/places/task', handler=PlaceMysqlHandler), ], debug=True )

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ff084a878b9abd5c040aec06d6830aa661e5561e

235

py

Python

neighbours/admin.py

kipkemoimayor/Neighbor-hood

28ab8faa0cfea5ed3b7fe47c8ef4b671311734c0

[ "MIT" ]

null

neighbours/admin.py

kipkemoimayor/Neighbor-hood

28ab8faa0cfea5ed3b7fe47c8ef4b671311734c0

[ "MIT" ]

3

2021-03-19T01:04:23.000Z

2021-09-08T01:02:06.000Z

neighbours/admin.py

kipkemoimayor/Neighbor-hood

28ab8faa0cfea5ed3b7fe47c8ef4b671311734c0

[ "MIT" ]

null

from django.contrib import admin from .models import Neighbour,Profile # Register your models here. class NeigborAdmin(admin.ModelAdmin): filter_horizontal=('Neighbour',) admin.site.register(Neighbour) admin.site.register(Profile)

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ff1ea9855ff07dd0c2eabe9ec2485e5f3a114f27

18,333

py

Python

trove_dashboard/content/database_configurations/tests.py

nnumbers/trove-dashboard

1602afbd7e3abfab2e40d931726474de5e9e3d70

[ "Apache-2.0" ]

24

2016-01-06T13:35:26.000Z

2020-12-06T16:52:22.000Z

trove_dashboard/content/database_configurations/tests.py

nnumbers/trove-dashboard

1602afbd7e3abfab2e40d931726474de5e9e3d70

[ "Apache-2.0" ]

null

trove_dashboard/content/database_configurations/tests.py

nnumbers/trove-dashboard

1602afbd7e3abfab2e40d931726474de5e9e3d70

[ "Apache-2.0" ]

15

2016-01-15T20:05:35.000Z

2022-03-17T14:59:43.000Z

# Copyright 2015 Tesora Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import logging from unittest import mock from django.urls import reverse from oslo_serialization import jsonutils from trove_dashboard import api from trove_dashboard.content.database_configurations \ import config_param_manager from trove_dashboard.test import helpers as test INDEX_URL = reverse('horizon:project:database_configurations:index') CREATE_URL = reverse('horizon:project:database_configurations:create') DETAIL_URL = 'horizon:project:database_configurations:detail' ADD_URL = 'horizon:project:database_configurations:add' class DatabaseConfigurationsTests(test.TestCase): @test.create_mocks({api.trove: ('configuration_list',)}) def test_index(self): self.mock_configuration_list.return_value = ( self.database_configurations.list()) res = self.client.get(INDEX_URL) self.mock_configuration_list.assert_called_once_with( test.IsHttpRequest()) self.assertTemplateUsed(res, 'project/database_configurations/index.html') @test.create_mocks({api.trove: ('configuration_list',)}) def test_index_exception(self): self.mock_configuration_list.side_effect = self.exceptions.trove res = self.client.get(INDEX_URL) self.mock_configuration_list.assert_called_once_with( test.IsHttpRequest()) self.assertTemplateUsed( res, 'project/database_configurations/index.html') self.assertEqual(res.status_code, 200) self.assertMessageCount(res, error=1) @test.create_mocks({ api.trove: ('datastore_list', 'datastore_version_list')}) def test_create_configuration(self): self.mock_datastore_list.return_value = self.datastores.list() self.mock_datastore_version_list.return_value = ( self.datastore_versions.list()) res = self.client.get(CREATE_URL) self.mock_datastore_list.assert_called_once_with(test.IsHttpRequest()) self.assert_mock_multiple_calls_with_same_arguments( self.mock_datastore_version_list, 4, mock.call(test.IsHttpRequest(), test.IsA(str))) self.assertTemplateUsed(res, 'project/database_configurations/create.html') @test.create_mocks({api.trove: ('datastore_list',)}) def test_create_configuration_exception_on_datastore(self): self.mock_datastore_list.side_effect = self.exceptions.trove toSuppress = ["trove_dashboard.content." "database_configurations.forms", ] # Suppress expected log messages in the test output loggers = [] for cls in toSuppress: logger = logging.getLogger(cls) loggers.append((logger, logger.getEffectiveLevel())) logger.setLevel(logging.CRITICAL) try: res = self.client.get(CREATE_URL) self.mock_datastore_list.assert_called_once_with( test.IsHttpRequest()) self.assertEqual(res.status_code, 302) finally: # Restore the previous log levels for (log, level) in loggers: log.setLevel(level) @test.create_mocks({ api.trove: ('datastore_list', 'datastore_version_list', 'configuration_create')}) def _test_create_test_configuration(self, config_description=u''): self.mock_datastore_list.return_value = self.datastores.list() self.mock_datastore_version_list.return_value = ( self.datastore_versions.list()) self.mock_configuration_create.return_value = ( self.database_configurations.first()) name = u'config1' values = "{}" ds = self._get_test_datastore('mysql') dsv = self._get_test_datastore_version(ds.id, '5.5') config_datastore = ds.name config_datastore_version = dsv.name post = { 'method': 'CreateConfigurationForm', 'name': name, 'description': config_description, 'datastore': (config_datastore + ',' + config_datastore_version)} res = self.client.post(CREATE_URL, post) self.mock_datastore_list.assert_called_once_with(test.IsHttpRequest()) self.assert_mock_multiple_calls_with_same_arguments( self.mock_datastore_version_list, 4, mock.call(test.IsHttpRequest(), test.IsA(str))) self.mock_configuration_create.assert_called_once_with( test.IsHttpRequest(), name, values, description=config_description, datastore=config_datastore, datastore_version=config_datastore_version) self.assertNoFormErrors(res) self.assertMessageCount(success=1) def test_create_test_configuration(self): self._test_create_test_configuration(u'description of config1') def test_create_test_configuration_with_no_description(self): self._test_create_test_configuration() @test.create_mocks({ api.trove: ('datastore_list', 'datastore_version_list', 'configuration_create')}) def test_create_test_configuration_exception(self): self.mock_datastore_list.return_value = self.datastores.list() self.mock_datastore_version_list.return_value = ( self.datastore_versions.list()) self.mock_configuration_create.side_effect = self.exceptions.trove name = u'config1' values = "{}" config_description = u'description of config1' ds = self._get_test_datastore('mysql') dsv = self._get_test_datastore_version(ds.id, '5.5') config_datastore = ds.name config_datastore_version = dsv.name post = {'method': 'CreateConfigurationForm', 'name': name, 'description': config_description, 'datastore': config_datastore + ',' + config_datastore_version} res = self.client.post(CREATE_URL, post) self.mock_datastore_list.assert_called_once_with(test.IsHttpRequest()) self.assert_mock_multiple_calls_with_same_arguments( self.mock_datastore_version_list, 4, mock.call(test.IsHttpRequest(), test.IsA(str))) self.mock_configuration_create.assert_called_once_with( test.IsHttpRequest(), name, values, description=config_description, datastore=config_datastore, datastore_version=config_datastore_version) self.assertRedirectsNoFollow(res, INDEX_URL) @test.create_mocks({api.trove: ('configuration_get', 'configuration_instances',)}) def test_details_tab(self): config = self.database_configurations.first() self.mock_configuration_get.return_value = config details_url = self._get_url_with_arg(DETAIL_URL, config.id) url = details_url + '?tab=configuration_details__details' res = self.client.get(url) self.assertEqual(2, self.mock_configuration_get.call_count) self.assertTemplateUsed(res, 'project/database_configurations/details.html') @test.create_mocks({api.trove: ('configuration_get',)}) def test_overview_tab_exception(self): config = self.database_configurations.first() self.mock_configuration_get.side_effect = self.exceptions.trove details_url = self._get_url_with_arg(DETAIL_URL, config.id) url = details_url + '?tab=configuration_details__overview' res = self.client.get(url) self.mock_configuration_get.assert_called_once_with( test.IsHttpRequest(), config.id) self.assertRedirectsNoFollow(res, INDEX_URL) @test.create_mocks({ api.trove: ('configuration_parameters_list',), config_param_manager.ConfigParamManager: ('get_configuration', 'configuration_get',)}) def test_add_parameter(self): config = self.database_configurations.first() self.mock_get_configuration.return_value = config self.mock_configuration_get.return_value = config ds = self._get_test_datastore('mysql') dsv = self._get_test_datastore_version(ds.id, '5.5') self.mock_configuration_parameters_list.return_value = ( self.configuration_parameters.list()) res = self.client.get(self._get_url_with_arg(ADD_URL, 'id')) self.mock_get_configuration.assert_called_once() self.mock_configuration_get.assert_called_once_with( test.IsHttpRequest()) self.mock_configuration_parameters_list.assert_called_once_with( test.IsHttpRequest(), ds.name, dsv.name) self.assertTemplateUsed( res, 'project/database_configurations/add_parameter.html') @test.create_mocks({ api.trove: ('configuration_parameters_list',), config_param_manager.ConfigParamManager: ('get_configuration', 'configuration_get',)}) def test_add_parameter_exception_on_parameters(self): try: config = self.database_configurations.first() self.mock_get_configuration.return_value = config self.mock_configuration_get.return_value = config ds = self._get_test_datastore('mysql') dsv = self._get_test_datastore_version(ds.id, '5.5') self.mock_configuration_parameters_list.side_effect = ( self.exceptions.trove) toSuppress = ["trove_dashboard.content." "database_configurations.forms", ] # Suppress expected log messages in the test output loggers = [] for cls in toSuppress: logger = logging.getLogger(cls) loggers.append((logger, logger.getEffectiveLevel())) logger.setLevel(logging.CRITICAL) try: res = self.client.get( self._get_url_with_arg(ADD_URL, config.id)) self.mock_get_configuration.assert_called_once() self.mock_configuration_get.assert_called_once_with( test.IsHttpRequest()) self.mock_configuration_parameters_list. \ assert_called_once_with( test.IsHttpRequest(), ds.name, dsv.name ) self.assertEqual(res.status_code, 302) finally: # Restore the previous log levels for (log, level) in loggers: log.setLevel(level) finally: config_param_manager.delete(config.id) @test.create_mocks( { api.trove: ('configuration_parameters_list', 'configuration_update', 'configuration_get'), config_param_manager.ConfigParamManager: ('add_param',) } ) def test_add_new_parameter(self): config = self.database_configurations.first() try: self.mock_configuration_get.return_value = config ds = self._get_test_datastore('mysql') dsv = self._get_test_datastore_version(ds.id, '5.5') self.mock_configuration_parameters_list.return_value = ( self.configuration_parameters.list()) name = self.configuration_parameters.first().name value = 1 config.values.update({name: value}) self.mock_add_param.return_value = value post = { 'method': 'AddParameterForm', 'name': name, 'value': value} res = self.client.post(self._get_url_with_arg(ADD_URL, config.id), post) self.assertEqual(2, self.mock_configuration_get.call_count) self.mock_configuration_parameters_list.assert_called_once_with( test.IsHttpRequest(), ds.name, dsv.name) self.mock_add_param.assert_called_once_with(name, value) self.mock_configuration_update.assert_called_once_with( test.IsHttpRequest(), config.id, jsonutils.dumps(config.values) ) self.assertNoFormErrors(res) self.assertMessageCount(success=1) finally: config_param_manager.delete(config.id) @test.create_mocks({ api.trove: ('configuration_get', 'configuration_parameters_list',), config_param_manager: ('get',)}) def test_add_parameter_invalid_value(self): try: config = self.database_configurations.first() # setup the configuration parameter manager config_param_mgr = config_param_manager.ConfigParamManager( config.id) config_param_mgr.configuration = config config_param_mgr.original_configuration_values = \ dict.copy(config.values) self.mock_get.return_value = config_param_mgr self.mock_configuration_parameters_list.return_value = ( self.configuration_parameters.list()) name = self.configuration_parameters.first().name value = "non-numeric" post = { 'method': 'AddParameterForm', 'name': name, 'value': value} res = self.client.post(self._get_url_with_arg(ADD_URL, config.id), post) self.assert_mock_multiple_calls_with_same_arguments( self.mock_get, 2, mock.call(test.IsHttpRequest(), test.IsA(str))) self.assert_mock_multiple_calls_with_same_arguments( self.mock_configuration_parameters_list, 2, mock.call(test.IsHttpRequest(), test.IsA(str), test.IsA(str))) self.assertFormError(res, "form", 'value', ['Value must be a number.']) finally: config_param_manager.delete(config.id) @test.create_mocks({api.trove: ('configuration_instances',), config_param_manager: ('get',)}) def test_instances_tab(self): try: config = self.database_configurations.first() # setup the configuration parameter manager config_param_mgr = config_param_manager.ConfigParamManager( config.id) config_param_mgr.configuration = config config_param_mgr.original_configuration_values = \ dict.copy(config.values) self.mock_get.return_value = config_param_mgr self.mock_configuration_instances.return_value = ( self.configuration_instances.list()) details_url = self._get_url_with_arg(DETAIL_URL, config.id) url = details_url + '?tab=configuration_details__instance' res = self.client.get(url) self.assert_mock_multiple_calls_with_same_arguments( self.mock_get, 2, mock.call(test.IsHttpRequest(), config.id)) self.mock_configuration_instances.assert_called_once_with( test.IsHttpRequest(), config.id) table_data = res.context['instances_table'].data self.assertCountEqual( self.configuration_instances.list(), table_data) self.assertTemplateUsed( res, 'project/database_configurations/details.html') finally: config_param_manager.delete(config.id) @test.create_mocks({api.trove: ('configuration_instances',), config_param_manager: ('get',)}) def test_instances_tab_exception(self): try: config = self.database_configurations.first() # setup the configuration parameter manager config_param_mgr = config_param_manager.ConfigParamManager( config.id) config_param_mgr.configuration = config config_param_mgr.original_configuration_values = \ dict.copy(config.values) self.mock_get.return_value = config_param_mgr self.mock_configuration_instances.side_effect = ( self.exceptions.trove) details_url = self._get_url_with_arg(DETAIL_URL, config.id) url = details_url + '?tab=configuration_details__instance' res = self.client.get(url) self.assert_mock_multiple_calls_with_same_arguments( self.mock_get, 2, mock.call(test.IsHttpRequest(), config.id)) self.mock_configuration_instances.assert_called_once_with( test.IsHttpRequest(), config.id) table_data = res.context['instances_table'].data self.assertNotEqual(len(self.configuration_instances.list()), len(table_data)) self.assertTemplateUsed( res, 'project/database_configurations/details.html') finally: config_param_manager.delete(config.id) def _get_url_with_arg(self, url, arg): return reverse(url, args=[arg]) def _get_test_datastore(self, datastore_name): for ds in self.datastores.list(): if ds.name == datastore_name: return ds return None def _get_test_datastore_version(self, datastore_id, datastore_version_name): for dsv in self.datastore_versions.list(): if (dsv.datastore == datastore_id and dsv.name == datastore_version_name): return dsv return None

41.856164

79

0.638084

1,929

18,333

5.740798

0.108346

0.041178

0.058786

0.032509

0.83538

0.794564

0.757269

0.733881

0.714918

0.714376

0

0.003307

0.274314

18,333

437

80

41.951945

0.829074

0.047237

0

0.69209

0

0.094119

0.059326

0

0.138418

1

0.053672

false

0

0.019774

0.002825

0.090395

0

null

0

1

0

null

0

6

20806aefd4c0204e068c1e35e56f85fc8555d694

110

py

Python

python/stage_2/10869.py

smartx-jshan/Coding_Practice

bc7d485e7992031e55df62483818b721ad7d1d4f

[ "Apache-2.0" ]

null

python/stage_2/10869.py

smartx-jshan/Coding_Practice

bc7d485e7992031e55df62483818b721ad7d1d4f

[ "Apache-2.0" ]

null

python/stage_2/10869.py

smartx-jshan/Coding_Practice

bc7d485e7992031e55df62483818b721ad7d1d4f

[ "Apache-2.0" ]

null

a,b = input().split() a = int(a) b = int(b) print (a+b) print (a-b) print (a*b) print (int(a/b)) print (a%b)

11

21

0.545455

26

110

2.307692

0.230769

0.233333

0.466667

0.533333

0.6

0.45

0

0.181818

110

9

22

12.222222

0.666667

0

1

0

false

0

0.625

1

0

null

1

0

1

0

null

0

1

0

6

208d0dd3ce0f13b8d081d2c50b8edc728af81ebf

142

py

Python

vc/manager/__init__.py

very-meanly/vc

41f63e8a8b159f3a49430bbee6872162de060901

[ "MIT" ]

null

vc/manager/__init__.py

very-meanly/vc

41f63e8a8b159f3a49430bbee6872162de060901

[ "MIT" ]

null

vc/manager/__init__.py

very-meanly/vc

41f63e8a8b159f3a49430bbee6872162de060901

[ "MIT" ]

null

from .generation_request import GenerationRequestManager from .generation_result import GenerationResultManager from .user import UserManager

35.5

56

0.894366

14

142

8.928571

0.642857

0.224

0

0.084507

142

3

57

47.333333

0.961538

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

208f4beda6124660dcd451e862316cc13ad6ae03

29

py

Python

pygmy/validator/__init__.py

ParikhKadam/pygmy

eecab36204d41f2c446b86e1e71d9e768b54dd1d

[ "MIT" ]

571

2017-11-17T06:12:21.000Z

2022-03-04T11:58:23.000Z

pygmy/validator/__init__.py

ParikhKadam/pygmy

eecab36204d41f2c446b86e1e71d9e768b54dd1d

[ "MIT" ]

49

2017-11-19T08:25:14.000Z

2022-02-10T07:55:27.000Z

pygmy/validator/__init__.py

ParikhKadam/pygmy

eecab36204d41f2c446b86e1e71d9e768b54dd1d

[ "MIT" ]

104

2018-01-11T20:47:42.000Z

2022-02-27T17:35:48.000Z

from .link import LinkSchema

14.5

28

0.827586

4

29

6

1

0

0.137931

29

1

29

0.96

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

20e0ee09d460c46b63622822daae0c672e471275

32

py

Python

foliant/preprocessors/dbdoc/__init__.py

foliant-docs/foliantcontrib.dbdoc

d8ba23421d54dc171d0c9c18636521ffae66c2de

[ "MIT" ]

3

2020-08-26T11:30:27.000Z

2021-02-10T12:24:07.000Z

foliant/preprocessors/dbdoc/__init__.py

foliant-docs/foliantcontrib.dbdoc

d8ba23421d54dc171d0c9c18636521ffae66c2de

[ "MIT" ]

null

foliant/preprocessors/dbdoc/__init__.py

foliant-docs/foliantcontrib.dbdoc

d8ba23421d54dc171d0c9c18636521ffae66c2de

[ "MIT" ]

1

2022-02-06T15:31:50.000Z

from .dbdoc import Preprocessor

16

31

0.84375

4

32

6.75

1

0

0.125

32

1

32

0.964286

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

20e3496c9caf55d10451163fe0a9e904c84eec88

37

py

Python

src/forms/__init__.py

hallrizon-io/Ydoma_telegram

5ac9d562af451e7b942e3ee4f56574bfca599a1c

[ "MIT" ]

null

src/forms/__init__.py

hallrizon-io/Ydoma_telegram

5ac9d562af451e7b942e3ee4f56574bfca599a1c

[ "MIT" ]

null

src/forms/__init__.py

hallrizon-io/Ydoma_telegram

5ac9d562af451e7b942e3ee4f56574bfca599a1c

[ "MIT" ]

null

from src.forms.RegisterForm import *

18.5

36

0.810811

5

37

6

1

0

0.108108

37

1

37

0.909091

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

458a78e358611e1680044be48d3530347c35265c

43

py

Python

tests/unit/clients/test_apiexternal.py

tehlingchu/anchore-cli

b0df36337f443749991a49263227c1d40989debb

[ "Apache-2.0" ]

110

2017-09-14T02:15:15.000Z

2022-03-30T20:14:21.000Z

tests/unit/clients/test_apiexternal.py

tehlingchu/anchore-cli

b0df36337f443749991a49263227c1d40989debb

[ "Apache-2.0" ]

115

2017-09-22T12:15:30.000Z

2022-01-17T12:31:21.000Z

tests/unit/clients/test_apiexternal.py

tehlingchu/anchore-cli

b0df36337f443749991a49263227c1d40989debb

[ "Apache-2.0" ]

56

2017-09-22T11:26:25.000Z

2022-03-03T14:14:58.000Z

from anchorecli.clients import apiexternal

21.5

42

0.883721

5

43

7.6

1

0

0.093023

43

1

43

0.974359

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

45d0f1f97b47e0198b63da8804a5a7049f450e1c

1,386

py

Python

lda_cf/cf.py

vivienfay/Recommendation-System-based-on-Yelp-Dataset

d0532b86f83fe19d4ff700add69547e2ef3d5a16

[ "MIT" ]

null

lda_cf/cf.py

vivienfay/Recommendation-System-based-on-Yelp-Dataset

d0532b86f83fe19d4ff700add69547e2ef3d5a16

[ "MIT" ]

null

lda_cf/cf.py

vivienfay/Recommendation-System-based-on-Yelp-Dataset

d0532b86f83fe19d4ff700add69547e2ef3d5a16

[ "MIT" ]

null

# Do not run # for collaborative filtering import numpy as np def cf(R,business_id_list): P = np.diag(np.diag(np.dot(R, R.T))) Q = np.diag(np.diag(np.dot(R.T, R))) p = np.diag(np.power(np.diag(P),-1/2)) q = np.diag(np.power(np.diag(Q),-1/2)) #collaboratvie_filtering_user_user collaborative_filtering_user = np.dot(np.dot(np.dot(np.dot(p,R),R.T),p),R) S = collaborative_filtering_user[499,0:100] alex = [(i,S[i]) for i in range(100)] sorted_alex = sorted(alex,key=lambda x: x[1],reverse = True)[0:5] top_movie_index = [ i[0] for i in sorted_alex] top_movie_score = [ i[1] for i in sorted_alex] print("Collaborative_filtering_user_user") print("The top 5 movie is: ",[ business_id_list[a] for a in top_movie_index]) print("Similarity is: ",top_movie_score) #collaboratvie_filtering_item_item collaborative_filtering_user = np.dot(np.dot((np.dot((np.dot(R,q)),R.T)),R),q) S = collaborative_filtering_user[499,0:100] alex = [(i,S[i]) for i in range(100)] sorted_alex = sorted(alex,key=lambda x: x[1],reverse = True)[0:5] top_movie_index = [ i[0] for i in sorted_alex] top_movie_score = [ i[1] for i in sorted_alex] print("Collaborative_filtering_item_item") print("The top 5 movie is: ",[ business_id_list[a] for a in top_movie_index]) print("Similarity is: ",top_movie_score)

38.5

83

0.669553

250

1,386

3.52

0.204

0.056818

0.054545

0.068182

0.806818

0.763636

0.722727

0

0.031524

0.176046

1,386

35

84

39.6

0.739054

0.075758

0

0.583333

0

0.112853

0.051724

0

1

0.041667

false

0

0.041667

0

0.083333

0.25

0

null

0

1

0

null

0

6

b312547db41edb030bbf6fb4173d51632b556936

171

py

Python

src/tuberlin/inventory/admin.py

CircularBerlin/gmit

fbc995f631fa42815deab5cf07e8115a1b964d90

[ "MIT" ]

null

src/tuberlin/inventory/admin.py

CircularBerlin/gmit

fbc995f631fa42815deab5cf07e8115a1b964d90

[ "MIT" ]

null

src/tuberlin/inventory/admin.py

CircularBerlin/gmit

fbc995f631fa42815deab5cf07e8115a1b964d90

[ "MIT" ]

null

from django.contrib import admin from inventory import models admin.site.register(models.Objekt) admin.site.register(models.Person) admin.site.register(models.Material)

21.375

36

0.830409

24

171

5.916667

0.5

0.190141

0.359155

0.485915

0

0.076023

171

7

37

24.428571

0.898734

0

1

0

true

0

0.4

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

b36d8b66d8e9b56a131a50146b5ae6da3f8b123a

7,328

py

Python

tests/schema/product/mutation/product/snapshots/snap_test_delete_product.py

simonsobs/acondbs

6ca11c2889d827ecdb2b54d0cf3b94b8cdd281e6

[ "MIT" ]

null

tests/schema/product/mutation/product/snapshots/snap_test_delete_product.py

simonsobs/acondbs

6ca11c2889d827ecdb2b54d0cf3b94b8cdd281e6

[ "MIT" ]

24

2020-04-02T19:29:07.000Z

2022-03-08T03:05:43.000Z

tests/schema/product/mutation/product/snapshots/snap_test_delete_product.py

simonsobs/acondbs

6ca11c2889d827ecdb2b54d0cf3b94b8cdd281e6

[ "MIT" ]

1

2020-04-08T15:48:28.000Z

# -*- coding: utf-8 -*- # snapshottest: v1 - https://goo.gl/zC4yUc from __future__ import unicode_literals from snapshottest import Snapshot snapshots = Snapshot() snapshots['test_schema_error[error] 1'] = { 'data': { 'allProductFilePaths': { 'edges': [ { 'node': { 'path': 'site1:/path/to/map1' } }, { 'node': { 'path': 'site2:/another/way/map1' } }, { 'node': { 'path': 'site1:/path/to/map2' } }, { 'node': { 'path': 'site1:/path/to/map3' } }, { 'node': { 'path': 'site2:/another/way/map3' } }, { 'node': { 'path': 'site1:/path/to/beam1' } }, { 'node': { 'path': 'site2:/another/way/beam1' } }, { 'node': { 'path': 'site1:/path/to/beam2' } } ] }, 'allProductRelations': { 'edges': [ { 'node': { 'other': { 'name': 'beam1' }, 'self_': { 'name': 'map1' }, 'type_': { 'name': 'child' } } }, { 'node': { 'other': { 'name': 'map1' }, 'self_': { 'name': 'beam1' }, 'type_': { 'name': 'parent' } } }, { 'node': { 'other': { 'name': 'beam2' }, 'self_': { 'name': 'map1' }, 'type_': { 'name': 'child' } } }, { 'node': { 'other': { 'name': 'map1' }, 'self_': { 'name': 'beam2' }, 'type_': { 'name': 'parent' } } }, { 'node': { 'other': { 'name': 'beam2' }, 'self_': { 'name': 'beam1' }, 'type_': { 'name': 'child' } } }, { 'node': { 'other': { 'name': 'beam1' }, 'self_': { 'name': 'beam2' }, 'type_': { 'name': 'parent' } } } ] }, 'allProducts': { 'edges': [ { 'node': { 'name': 'map1' } }, { 'node': { 'name': 'map2' } }, { 'node': { 'name': 'map3' } }, { 'node': { 'name': 'beam1' } }, { 'node': { 'name': 'beam2' } } ] } } } snapshots['test_schema_success[delete] 1'] = { 'data': { 'deleteProduct': { 'ok': True } } } snapshots['test_schema_success[delete] 2'] = { 'data': { 'allProductFilePaths': { 'edges': [ { 'node': { 'path': 'site1:/path/to/map2' } }, { 'node': { 'path': 'site1:/path/to/map3' } }, { 'node': { 'path': 'site2:/another/way/map3' } }, { 'node': { 'path': 'site1:/path/to/beam1' } }, { 'node': { 'path': 'site2:/another/way/beam1' } }, { 'node': { 'path': 'site1:/path/to/beam2' } } ] }, 'allProductRelations': { 'edges': [ { 'node': { 'other': { 'name': 'beam2' }, 'self_': { 'name': 'beam1' }, 'type_': { 'name': 'child' } } }, { 'node': { 'other': { 'name': 'beam1' }, 'self_': { 'name': 'beam2' }, 'type_': { 'name': 'parent' } } } ] }, 'allProducts': { 'edges': [ { 'node': { 'name': 'map2' } }, { 'node': { 'name': 'map3' } }, { 'node': { 'name': 'beam1' } }, { 'node': { 'name': 'beam2' } } ] } } }

27.140741

58

0.165393

247

7,328

4.797571

0.198381

0.094515

0.098734

0.129114

0.843882

0.766245

0.757806

0.694515

0.655696

0

0.02928

0.725027

7,328

269

59

27.241636

0.558809

0.008461

0

0.440613

0

0.154619

0.026848

0

1

0

false

0

0.007663

0

0.007663

0

null

0

1

0

1

0

1

0

null

0

6

ff24c055c749f2d87e45489a31908cad6f882d24

20

py

Python

rFS/__init__.py

osarwar/rFS

17f0300f7bb7be75022fb7ea532c845df5e630fe

[ "MIT" ]

null

rFS/__init__.py

osarwar/rFS

17f0300f7bb7be75022fb7ea532c845df5e630fe

[ "MIT" ]

null

rFS/__init__.py

osarwar/rFS

17f0300f7bb7be75022fb7ea532c845df5e630fe

[ "MIT" ]

null

from .rFS import rfs

20

0.8

4

20

4

0.75

0

0.15

20

1

20

0.941176

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

ff3c1bed928cadace980ac8dbdd7e724a7d64ccc

43

py

Python

baseline/tf/seq2seq/train.py

sagnik/baseline

8d75616e04c1cca509dbebbb6d08ad7e1a7b9f88

[ "Apache-2.0" ]

241

2016-04-25T20:02:31.000Z

2019-09-03T05:44:09.000Z

baseline/tf/seq2seq/train.py

sagnik/baseline

8d75616e04c1cca509dbebbb6d08ad7e1a7b9f88

[ "Apache-2.0" ]

131

2019-10-12T10:53:17.000Z

2021-12-03T19:52:47.000Z

baseline/tf/seq2seq/train.py

sagnik/baseline

8d75616e04c1cca509dbebbb6d08ad7e1a7b9f88

[ "Apache-2.0" ]

75

2016-06-28T01:18:58.000Z

2019-08-29T06:47:22.000Z

from baseline.tf.seq2seq.training import *

21.5

42

0.813953

6

43

5.833333

1

0

0.025641

0.093023

43

1

43

0.871795

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

ff90f79ded27b74af9343a5c1e6358bc398fd0ee

35

py

Python

__init__.py

vinceynhz/library-service-py

a7aad3696294b679a6c8d7b94dad7eafd35c49c7

[ "MIT" ]

null

__init__.py

vinceynhz/library-service-py

a7aad3696294b679a6c8d7b94dad7eafd35c49c7

[ "MIT" ]

null

__init__.py

vinceynhz/library-service-py

a7aad3696294b679a6c8d7b94dad7eafd35c49c7

[ "MIT" ]

null

""" :author: vic on 2021-03-13 """

8.75

26

0.542857

6

35

3.166667

1

0

0.275862

0.171429

35

3

27

11.666667

0.37931

0.742857

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

4472bf44828d54686641610c6197cb92092874b5

26

py

Python

seeding/__init__.py

camall3n/seeding

276b9ff80983ab181eb4efd8bca2adae85b4b159

[ "MIT" ]

7

2021-01-13T18:06:22.000Z

2021-12-22T11:30:49.000Z

seeding/__init__.py

camall3n/seeding

276b9ff80983ab181eb4efd8bca2adae85b4b159

[ "MIT" ]

1

2021-09-22T21:05:12.000Z

2021-09-22T21:09:48.000Z

seeding/__init__.py

camall3n/seeding

276b9ff80983ab181eb4efd8bca2adae85b4b159

[ "MIT" ]

null

from .seeding import seed

13

25

0.807692

4

26

5.25

1

0

0.153846

26

1

26

0.954545

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

4474ad7861cf05f65b02299c6de417213f83bd0f

235

py

Python

transformations/__init__.py

OdysseasPapakyriakou/kMeans

99416c3772b2f7ecbd703d3cc2c8169c4da6b19d

[ "MIT" ]

null

transformations/__init__.py

OdysseasPapakyriakou/kMeans

99416c3772b2f7ecbd703d3cc2c8169c4da6b19d

[ "MIT" ]

null

transformations/__init__.py

OdysseasPapakyriakou/kMeans

99416c3772b2f7ecbd703d3cc2c8169c4da6b19d

[ "MIT" ]

null

# Name: Odysseas Papakyriakou # Student_ID: 12632864 """This package contains a collection of functions to transform data Type: pydoc transformations.functions to see what these functions do """ from .functions import *

29.375

82

0.744681

29

235

6

0.862069

0.126437

0

0.042328

0.195745

235

8

83

29.375

0.878307

0.842553

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

44954952068601f4406b372bd71ce0d1e158930a

13

py

Python

challenges/python-basics/q11.py

ayushnagar123/Data-Science

22fa3a2d2eee1adaf4be51663b61bcae587cfe21

[ "MIT" ]

1

2020-12-19T19:04:41.000Z

challenges/python-basics/q11.py

ayushnagar123/Data-Science

22fa3a2d2eee1adaf4be51663b61bcae587cfe21

[ "MIT" ]

null

challenges/python-basics/q11.py

ayushnagar123/Data-Science

22fa3a2d2eee1adaf4be51663b61bcae587cfe21

[ "MIT" ]

null

print(---10 )

13

0.538462

2

13

3.5

1

0

0.166667

0.076923

13

1

13

0.416667

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

923bc5175d8cbf37c932b7a25037f6b74f337959

251

py

Python

atlas/foundations_core_rest_api_components/src/test/v1/controllers/__init__.py

DeepLearnI/atlas

8aca652d7e647b4e88530b93e265b536de7055ed

[ "Apache-2.0" ]

296

2020-03-16T19:55:00.000Z

2022-01-10T19:46:05.000Z

atlas/foundations_core_rest_api_components/src/test/v1/controllers/__init__.py

DeepLearnI/atlas

8aca652d7e647b4e88530b93e265b536de7055ed

[ "Apache-2.0" ]

57

2020-03-17T11:15:57.000Z

2021-07-10T14:42:27.000Z

atlas/foundations_core_rest_api_components/src/test/v1/controllers/__init__.py

DeepLearnI/atlas

8aca652d7e647b4e88530b93e265b536de7055ed

[ "Apache-2.0" ]

38

2020-03-17T21:06:05.000Z

2022-02-08T03:19:34.000Z

from test.v1.controllers.test_projects_controller import TestProjectsController from test.v1.controllers.test_job_logs_controller import TestJobLogsController from test.v1.controllers.test_authentication_controller import TestAuthenticationController

62.75

91

0.916335

28

251

7.964286

0.464286

0.107623

0.134529

0.282511

0.336323

0

0.012552

0.047809

251

4

91

62.75

0.920502

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

2bdae93e7db58ef9ac9d609f61c07a74a25436e2

89

py

Python

app/service/__init__.py

Andrewpqc/hackerthon_sentiment_analysis

0fcb530f5a8ef269007dfea44d245e74eaf9fef7

[ "MIT" ]

null

app/service/__init__.py

Andrewpqc/hackerthon_sentiment_analysis

0fcb530f5a8ef269007dfea44d245e74eaf9fef7

[ "MIT" ]

null

app/service/__init__.py

Andrewpqc/hackerthon_sentiment_analysis

0fcb530f5a8ef269007dfea44d245e74eaf9fef7

[ "MIT" ]

null

from flask import Blueprint service = Blueprint("service", __name__) from . import views

22.25

40

0.786517

11

89

6

0.636364

0.484848

0

0.134831

89

3

41

29.666667

0.857143

0

0.078652

0

1

0

false

0

0.666667

0

0.666667

1

0

null

1

0

1

0

null

0

1

0

1

0

6

2be1a5c613deb1ec616fd831507fc40925cced0a

110

py

Python

Pyflai/style/color/__init__.py

CMakerA/Pyflai

4c3ed66d0d046de56c4bf6a04cb6ce8ebdf34693

[ "Apache-2.0" ]

1

2018-02-14T08:33:25.000Z

Pyflai/style/color/__init__.py

CMakerA/Pyflai

4c3ed66d0d046de56c4bf6a04cb6ce8ebdf34693

[ "Apache-2.0" ]

null

Pyflai/style/color/__init__.py

CMakerA/Pyflai

4c3ed66d0d046de56c4bf6a04cb6ce8ebdf34693

[ "Apache-2.0" ]

null

__all__ = ["Color", "Colors"] from Pyflai.style.color.Color import * from Pyflai.style.color.Colors import *

22

39

0.736364

15

110

5.133333

0.466667

0.285714

0.38961

0.519481

0

0.118182

110

4

40

27.5

0.793814

0

0.1

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

6

9213835156615e129442f860d7461c795af0efb8

202

py

Python

product/admin.py

SamuelCalabriaC/Booksy-

daba45134ff15b27f6e6ade181656259a0839334

[ "PostgreSQL", "Unlicense", "MIT" ]

null

product/admin.py

SamuelCalabriaC/Booksy-

daba45134ff15b27f6e6ade181656259a0839334

[ "PostgreSQL", "Unlicense", "MIT" ]

null

product/admin.py

SamuelCalabriaC/Booksy-

daba45134ff15b27f6e6ade181656259a0839334

[ "PostgreSQL", "Unlicense", "MIT" ]

null

from django.contrib import admin from product import models # Register your models here. admin.site.register(models.ProductModel) admin.site.register(models.Image) admin.site.register(models.Category)

25.25

40

0.826733

28

202

5.964286

0.5

0.161677

0.305389

0.413174

0

0.084158

202

7

41

28.857143

0.902703

0.128713

0

1

0

true

0

0.4

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

a603e62b580b144b3ffa2743a94ee09c60daa35d

58

py

Python

python/tvm/tensor_graph/core2/nn/optimizer/__init__.py

QinHan-Erin/AMOS

634bf48edf4015e4a69a8c32d49b96bce2b5f16f

[ "Apache-2.0" ]

22

2022-03-18T07:29:31.000Z

2022-03-23T14:54:32.000Z

python/tvm/tensor_graph/core2/nn/optimizer/__init__.py

QinHan-Erin/AMOS

634bf48edf4015e4a69a8c32d49b96bce2b5f16f

[ "Apache-2.0" ]

null

python/tvm/tensor_graph/core2/nn/optimizer/__init__.py

QinHan-Erin/AMOS

634bf48edf4015e4a69a8c32d49b96bce2b5f16f

[ "Apache-2.0" ]

2

2022-03-18T08:26:34.000Z

2022-03-20T06:02:48.000Z

from .adam import * from .base import * from .sgd import *

19.333333

19

0.706897

9

58

4.555556

0.555556

0.487805

0

0.189655

58

3

20

19.333333

0.87234

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

a65ef02bd566feed806b975f566d3756c8840380

94

py

Python

example/hamblog/hash_password.py

movermeyer/cellardoor

25192b07224ff7bd33fd29ebac07340bef53a2ed

[ "MIT" ]

null

example/hamblog/hash_password.py

movermeyer/cellardoor

25192b07224ff7bd33fd29ebac07340bef53a2ed

[ "MIT" ]

3

2015-01-31T14:53:06.000Z

2015-02-01T19:04:30.000Z

example/hamblog/hash_password.py

movermeyer/cellardoor

25192b07224ff7bd33fd29ebac07340bef53a2ed

[ "MIT" ]

2

2015-01-31T14:54:28.000Z

2018-03-05T17:33:42.000Z

import hashlib def hash_password(password): return hashlib.sha1(SALT + password).hexdigest()

23.5

49

0.797872

12

94

6.166667

0.75

0

0.011765

0.095745

94

4

49

23.5

0.858824

0

1

0.333333

false

0.666667

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

a6694779ba7273d0426925b5033e5a1a5fbdea30

25

py

Python

branch_3.py

drednout5786/test_git

dd2b900b8f9cd9d51aa6a6c16918877507da6ec9

[ "MIT" ]

null

branch_3.py

drednout5786/test_git

dd2b900b8f9cd9d51aa6a6c16918877507da6ec9

[ "MIT" ]

null

branch_3.py

drednout5786/test_git

dd2b900b8f9cd9d51aa6a6c16918877507da6ec9

[ "MIT" ]

null

print("This is branch 3")

25

0.72

5

25

3.6

1

0

0.045455

0.12

25

1

25

0.772727

0

0.615385

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

a669489cbc2b14cf5676d80917f0c47f58512d6f

101

py

Python

src/lib/transformer/__init__.py

Alan-yly/FairMOT

68f6f996dc84303b4f4a28a89a47fa51b6628be5

[ "MIT" ]

null

src/lib/transformer/__init__.py

Alan-yly/FairMOT

68f6f996dc84303b4f4a28a89a47fa51b6628be5

[ "MIT" ]

null

src/lib/transformer/__init__.py

Alan-yly/FairMOT

68f6f996dc84303b4f4a28a89a47fa51b6628be5

[ "MIT" ]

null

from ..transformer import Models from ..transformer import Sublayers from ..transformer import Layers

33.666667

35

0.831683

12

101

7

0.5

0.535714

0.75

0

0.108911

101

3

36

33.666667

0.933333

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

a68006498ca95a93ba30e736e4627f064f2753e7

8,011

py

Python

tests/ikea_light_switch_test.py

Robert1991/appdaemon

ba346d5b79d24ae7684390e717c1030e317d7600

[ "Unlicense" ]

null

tests/ikea_light_switch_test.py

Robert1991/appdaemon

ba346d5b79d24ae7684390e717c1030e317d7600

[ "Unlicense" ]

null

tests/ikea_light_switch_test.py

Robert1991/appdaemon

ba346d5b79d24ae7684390e717c1030e317d7600

[ "Unlicense" ]

null

from apps.lights.ikea_light_switch import IkeaLightSwitch import pytest from appdaemontestframework import automation_fixture from mock import Mock @automation_fixture(IkeaLightSwitch) def light_switch(given_that): given_that.passed_arg('light_switch_sensor').is_set_to( 'sensor.some_light_switch') given_that.passed_arg('light_group').is_set_to( 'light.some_controlled_lights') given_that.passed_arg('scene_input_select').is_set_to( 'input_select.some_scene_input_select') given_that.passed_arg('scene_prefix').is_set_to( 'Prefix') given_that.passed_arg('dim_step_size').is_set_to( 'input_number.some_dim_step_size_slider') IkeaLightSwitch.initialize_on_creation = False IkeaLightSwitch.scene_utils = Mock() def test_decrease_brightness_turns_on_light_group_when_off(light_switch, given_that, assert_that): given_that.state_of( 'input_number.some_dim_step_size_slider').is_set_to('25.0') given_that.state_of('light.some_controlled_lights').is_set_to('off', {'entity_id': ["light.light_1", "light.light_2"]}) light_switch.increase_brightness(None, None, None, None, None) assert_that('light.some_controlled_lights').was.turned_on() def test_decrease_brightness_only_turned_on_lights_get_dimmed(light_switch, given_that, assert_that): given_that.state_of( 'input_number.some_dim_step_size_slider').is_set_to('25.0') given_that.state_of('light.some_controlled_lights').is_set_to('on', {'entity_id': ["light.some_turned_on_light", "light.some_light_without_brightness_toggle", "light.some_turned_off_light"]}) given_that.state_of('light.some_turned_on_light').is_set_to('on', {'brightness': "125"}) given_that.state_of( 'light.some_light_without_brightness_toggle').is_set_to('on') given_that.state_of('light.some_turned_off_light').is_set_to('off') light_switch.decrease_brightness(None, None, None, None, None) assert_that('light.some_turned_on_light').was.turned_on(brightness=100) assert_that('light.some_light_without_brightness_toggle').was_not.turned_on() assert_that('light.some_turned_off_light').was_not.turned_on() def test_decrease_brightness_turns_off_light_when_brightness_0(light_switch, given_that, assert_that): given_that.state_of( 'input_number.some_dim_step_size_slider').is_set_to('25.0') given_that.state_of('light.some_controlled_lights').is_set_to('on', {'entity_id': ["light.light_1", "light.light_2"]}) given_that.state_of('light.light_1').is_set_to('on', {'brightness': "12"}) given_that.state_of('light.light_2').is_set_to('on', {'brightness': "125"}) light_switch.decrease_brightness(None, None, None, None, None) assert_that('light.light_1').was.turned_off() assert_that('light.light_2').was.turned_on(brightness=100) def test_increase_brightness_only_turned_on_lights_get_dimmed(light_switch, given_that, assert_that): given_that.state_of( 'input_number.some_dim_step_size_slider').is_set_to('25.0') given_that.state_of('light.some_controlled_lights').is_set_to('on', {'entity_id': ["light.some_turned_on_light", "light.some_light_without_brightness_toggle", "light.some_turned_off_light"]}) given_that.state_of('light.some_turned_on_light').is_set_to('on', {'brightness': "125"}) given_that.state_of( 'light.some_light_without_brightness_toggle').is_set_to('on') given_that.state_of('light.some_turned_off_light').is_set_to('off') light_switch.increase_brightness(None, None, None, None, None) assert_that('light.some_turned_on_light').was.turned_on(brightness=150) assert_that('light.some_turned_off_light').was_not.turned_on() assert_that('light.some_light_without_brightness_toggle').was_not.turned_on() def test_increase_brightness_only_increases_to_max_255(light_switch, given_that, assert_that): given_that.state_of( 'input_number.some_dim_step_size_slider').is_set_to('25.0') given_that.state_of('light.some_controlled_lights').is_set_to('on', {'entity_id': ["light.light_1", "light.light_2"]}) given_that.state_of('light.light_1').is_set_to('on', {'brightness': "250"}) given_that.state_of('light.light_2').is_set_to('on', {'brightness': "125"}) light_switch.increase_brightness(None, None, None, None, None) assert_that('light.light_1').was.turned_on(brightness=255) assert_that('light.light_2').was.turned_on(brightness=150) def test_increase_brightness_turns_on_light_group_when_off(light_switch, given_that, assert_that): given_that.state_of( 'input_number.some_dim_step_size_slider').is_set_to('25.0') given_that.state_of('light.some_controlled_lights').is_set_to('off', {'entity_id': ["light.light_1", "light.light_2"]}) light_switch.increase_brightness(None, None, None, None, None) assert_that('light.some_controlled_lights').was.turned_on() def test_toggle_light_group_is_turned_on_when_off(light_switch, given_that, assert_that): given_that.state_of('light.some_controlled_lights').is_set_to('off') light_switch.toggle_light_group(None, None, None, None, None) assert_that('light.some_controlled_lights').was.turned_on() def test_toggle_light_group_is_turned_off_when_on(light_switch, given_that, assert_that): given_that.state_of('light.some_controlled_lights').is_set_to('on') light_switch.toggle_light_group(None, None, None, None, None) assert_that('light.some_controlled_lights').was.turned_off() def test_switch_to_next_scene(light_switch, given_that, assert_that): given_that.state_of( 'input_select.some_scene_input_select').is_set_to('Test 1') light_switch.switch_to_next_scene(None, None, None, None, None) assert_that('input_select/select_next') \ .was.called_with(entity_id='input_select.some_scene_input_select') light_switch.scene_utils.turn_on_current_scene.assert_called_once_with( "Prefix", "input_select.some_scene_input_select") def test_switch_to_previous_scene(light_switch, given_that, assert_that): given_that.state_of( 'input_select.some_scene_input_select').is_set_to('Test 1') light_switch.switch_to_previous_scene(None, None, None, None, None) assert_that('input_select/select_previous') \ .was.called_with(entity_id='input_select.some_scene_input_select') light_switch.scene_utils.turn_on_current_scene.assert_called_once_with( "Prefix", "input_select.some_scene_input_select")

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0

null

0

1

0

null

0

6

a6a9ed53a35164197250c9c2fe9a7acaaec29ea7

150

py

Python

test.py

Caamno-Davrin/Davrin-V.13

82763d3a8dcb66fb20b99e54384d10161ab98fb5

[ "MIT" ]

null

test.py

Caamno-Davrin/Davrin-V.13

82763d3a8dcb66fb20b99e54384d10161ab98fb5

[ "MIT" ]

null

test.py

Caamno-Davrin/Davrin-V.13

82763d3a8dcb66fb20b99e54384d10161ab98fb5

[ "MIT" ]

null

import subprocess subprocess.call("wget -O test.sh https://gitlab.com/game.packs/version.4.10.2021/-/raw/master/test.sh && bash test.sh", shell=True)

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a6cdf2e05e36020b5173d3b98f3c647ff7c4405f

1,505

py

Python

segmentation_models_pytorch_4TorchLessThan120/demo.py

chaineypung/CCF-BDCI-2021-ULSEG-Rank1st

a0e32cf006ffc006dfbf238d0b57d6ce09708d12

[ "MIT" ]

19

2022-01-25T16:24:31.000Z

2022-01-28T02:41:06.000Z

segmentation_models_pytorch_4TorchLessThan120/demo.py

chaineypung/CCF-BDCI-2021-Ultrasonic-Image-Tumor-Segmentation-Rank1st

a0e32cf006ffc006dfbf238d0b57d6ce09708d12

[ "MIT" ]

null

segmentation_models_pytorch_4TorchLessThan120/demo.py

chaineypung/CCF-BDCI-2021-Ultrasonic-Image-Tumor-Segmentation-Rank1st

a0e32cf006ffc006dfbf238d0b57d6ce09708d12

[ "MIT" ]

2

2022-01-26T03:04:51.000Z

2022-01-27T02:23:05.000Z

import torch import segmentation_models_pytorch_4TorchLessThan120 as smp ecname = 'efficientnet-b5' cudaa = 1 model = smp.Unet(encoder_name=ecname, encoder_weights=None, in_channels=3,classes=1) model.cuda(cudaa) mask = model((torch.ones([3, 3, 256, 256])).cuda(cudaa)) print('Unet is ok') model = smp.Linknet(encoder_name=ecname, encoder_weights=None, in_channels=3,classes=1) model.cuda(cudaa) mask = model((torch.ones([3, 3, 256, 256])).cuda(cudaa)) print('Linknet is ok') model = smp.FPN(encoder_name=ecname, encoder_weights=None, in_channels=3,classes=1) model.cuda(cudaa) mask = model((torch.ones([3, 3, 256, 256])).cuda(cudaa)) print('FPN is ok') model = smp.PSPNet(encoder_name=ecname, encoder_weights=None, in_channels=3,classes=1) model.cuda(cudaa) mask = model((torch.ones([3, 3, 256, 256])).cuda(cudaa)) print('PSPNet is ok') model = smp.DeepLabV3Plus(encoder_name=ecname, encoder_weights=None, in_channels=3,classes=1) model.cuda(cudaa) mask = model((torch.ones([3, 3, 256, 256])).cuda(cudaa)) print('DeepLabV3Plus is ok') model = smp.PAN(encoder_name=ecname, encoder_weights=None, in_channels=3,classes=1) model.cuda(cudaa) mask = model((torch.ones([3, 3, 256, 256])).cuda(cudaa)) print('PAN is ok') model = smp.PAN(encoder_name=ecname, encoder_weights='advprop', in_channels=3,classes=1) model.cuda(cudaa) mask = model((torch.ones([3, 3, 256, 256])).cuda(cudaa)) print('downloading is ok')

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0.144186

1,505

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null

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1

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1

0

null

0

6

4707c30bdb25e9ea7521c175a475a52c6263a6c8

24

py

Python

__init__.py

DamonDeng/deepracer_sample

8ed6a79b8185e802245eacec0e7553d0d9760f83

[ "MIT" ]

null

__init__.py

DamonDeng/deepracer_sample

8ed6a79b8185e802245eacec0e7553d0d9760f83

[ "MIT" ]

null

__init__.py

DamonDeng/deepracer_sample

8ed6a79b8185e802245eacec0e7553d0d9760f83

[ "MIT" ]

null

from race_utils import *

24

0.833333

4

24

4.75

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0

0.125

24

1

24

0.904762

0

1

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true

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null

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null

0

1

0

1

0

1

0

6

471c26e2b6cb896c4df0a465091d760abe607501

15,919

py

Python

cddm/plot.py

arkomatej/cddm

c21f28360d4ccdefa6758a06c71e757abc77efaf

[ "MIT" ]

null

cddm/plot.py

arkomatej/cddm

c21f28360d4ccdefa6758a06c71e757abc77efaf

[ "MIT" ]

null

cddm/plot.py

arkomatej/cddm

c21f28360d4ccdefa6758a06c71e757abc77efaf

[ "MIT" ]

null

"""plotting functions and classes""" from __future__ import division, print_function, absolute_import import numpy as np import matplotlib.pyplot as plt from matplotlib.widgets import Slider #import matplotlib.animation as animation from matplotlib.animation import FuncAnimation #from matplotlib.patches import Circle from ddm.core.ddm_tools import sector_indexmap, line_indexmap, correlate from cdiff_new import log_merge, normalize_data #I am using a class instead of function, so that plot objects have references and not garbage collected in interactive mode class show_video(object): """Shows video in plot. You need to hold reference to this object, otherwise it will not work in interactive mode. """ def __init__(self,video, fftshift = False, logplot = False, cmap = None): def norm(frame): if fftshift: frame = np.fft.fftshift(frame) #if is complex or logplot if np.issubdtype(video.dtype, np.complexfloating) or logplot: frame = np.abs(frame) if logplot: frame = np.log(1 + frame) return frame self.fig, self.ax1 = plt.subplots() plt.subplots_adjust(bottom=0.25) frame = norm(video[0]) self.imax= self.ax1.imshow(frame,cmap = cmap)#, animated=True) #hist, n = np.histogram(frame.ravel(),255,(0,255)) #self.hisl, = self.ax2.plot(hist) #self.cb = plt.colorbar() self.axindex = plt.axes([0.25, 0.15, 0.65, 0.03]) self.sindex = Slider(self.axindex, "frame",0,video.shape[0]-1,valinit = 0, valfmt='%i') def update(val): i = int(self.sindex.val) frame= norm(video[i]) self.imax.set_data(frame) #hist, n = np.histogram(frame.ravel(),255,(0,255)) #self.hisl.set_ydata(hist) self.fig.canvas.draw_idle() self.ids = self.sindex.on_changed(update) # self.playax = plt.axes([0.8, 0.025, 0.1, 0.04]) # self.playbutton = Button(self.playax, 'Play', hovercolor='0.975') # self.stopax = plt.axes([0.6, 0.025, 0.1, 0.04]) # self.stopbutton = Button(self.stopax, 'Stop', hovercolor='0.975') # # def update_anim(i): # self.imax.set_data(norm(video[i])) # self.sindex.set_val(i) # return self.imax, # # def play_video(event): # #disconnect slider move event # self.sindex.disconnect(self.ids) # if hasattr(self, "ani"): # self.ani.event_source.stop() # start = int(self.sindex.val) # if start == video.shape[0] -1: # start = 0 # self.ani = FuncAnimation(self.fig, update_anim, frames=range(start,video.shape[0]), blit=True, interval = 1, repeat = False) # # def stop_video(event): # self.ani.event_source.stop() # del self.ani # gc.collect() # self.ids = self.sindex.on_changed(update) # # self.playbutton.on_clicked(play_video) # self.stopbutton.on_clicked(stop_video) #plt.show() def test_show_video(): video = np.random.randint(0,255,(1024,256,256),"uint8") plot = show_video(video) class show_histogram(object): """Shows video in plot. You need to hold reference to this object, otherwise it will not work in interactive mode. """ def __init__(self,video): self.fig, self.ax1 = plt.subplots() plt.subplots_adjust(bottom=0.25) frame = video[0] hist, n = np.histogram(frame.ravel(),255,(0,255)) self.hisl, = self.ax1.plot(hist) self.axindex = plt.axes([0.25, 0.15, 0.65, 0.03]) self.sindex = Slider(self.axindex, "frame",0,video.shape[0]-1,valinit = 0, valfmt='%i') def update(val): i = int(self.sindex.val) frame= video[i] hist, n = np.histogram(frame.ravel(),255,(0,255)) self.hisl.set_ydata(hist) self.fig.canvas.draw_idle() self.ids = self.sindex.on_changed(update) #plt.show() def test_show_histogram(): video = np.random.randint(0,255,(1024,256,256),"uint8") plot = show_histogram(video) class show_fftdata(object): """Shows correlation data in plot. You need to hold reference to this object, otherwise it will not work in interactive mode. """ def __init__(self,data, semilogx = True, normalize = True, sector = 5, angle = 0, kstep = 1): self.shape = data.shape self.data = data self.fig, (self.ax1,self.ax2) = plt.subplots(1,2,gridspec_kw = {'width_ratios':[3, 1]}) plt.subplots_adjust(bottom=0.25) graph_shape = self.shape[0], self.shape[1] graph = np.zeros(graph_shape) max_k_value = np.sqrt((graph_shape[0]//2+1)**2+ graph_shape[1]**2) *np.sqrt(2) graph[0,0] = max_k_value self.im = self.ax2.imshow(graph, extent=[0,self.shape[1],self.shape[0]//2+1,-self.shape[0]//2-1]) #self.ax2.grid() norm = data[:,:,0] if normalize == False: norm = np.ones_like(norm) if semilogx == True: self.l, = self.ax1.semilogx(data[0,0,:]/norm[0,0]) else: self.l, = self.ax1.plot(data[0,0,:]/norm[0,0]) self.kax = plt.axes([0.1, 0.15, 0.65, 0.03]) self.kindex = Slider(self.kax, "k",0,max_k_value,valinit = 0, valfmt='%i') self.phiax = plt.axes([0.1, 0.10, 0.65, 0.03]) self.phiindex = Slider(self.phiax, "$\phi$",-90,90,valinit = angle, valfmt='%.2f') self.sectorax = plt.axes([0.1, 0.05, 0.65, 0.03]) self.sectorindex = Slider(self.sectorax, "sector",0,180,valinit = sector, valfmt='%.2f') def update(val): k = self.kindex.val phi = self.phiindex.val sector = self.sectorindex.val ki = int(round(- k * np.sin(np.pi/180 * phi))) kj = int(round(k * np.cos(np.pi/180 * phi))) #self.l.set_ydata(data[ki,kj,:]/norm[ki,kj]) # recompute the ax.dataLim self.ax1.relim() # update ax.viewLim using the new dataLim self.ax1.autoscale_view() graph = np.zeros((self.shape[0], self.shape[1])) if sector != 0: indexmap = sector_indexmap(self.shape[0],self.shape[1],phi, sector, kstep) else: indexmap = line_indexmap(self.shape[0],self.shape[1],phi) #graph = np.concatenate((indexmap[:,:,np.newaxis],indexmap[:,:,np.newaxis],indexmap[:,:,np.newaxis]),-1) #make color image graph = indexmap mask = (indexmap == int(round(k))) graph[mask] = max_k_value +1 avg_data = correlate(self.data[mask,:]).mean(0) self.l.set_ydata(avg_data/avg_data[0]) avg_graph = np.zeros(graph_shape) avg_graph[mask] = 1 #graph[ki,kj] = 1 #print (ki,kj) self.im.set_data(np.fft.fftshift(graph,0)) #circ = Circle((ki,kj),5) #self.ax2.add_patch(circ) self.fig.canvas.draw_idle() self.update = update self.kindex.on_changed(update) self.phiindex.on_changed(update) self.sectorindex.on_changed(update) plt.show() class CorrelationViewer(object): """Shows correlation data in plot. You need to hold reference to this object, otherwise it will not work in interactive mode. """ def init(self,data, semilogx = True, normalize = True): self.shape = data.shape self.data = data self.fig, (self.ax1,self.ax2) = plt.subplots(1,2,gridspec_kw = {'width_ratios':[3, 1]}) plt.subplots_adjust(bottom=0.25) graph_shape = self.shape[0], self.shape[1] self._graph_shape = graph_shape graph = np.zeros(graph_shape) max_graph_value = max(graph_shape[0]//2+1, graph_shape[1]) graph[0,0] = max_graph_value self._max_graph_value = max_graph_value self.im = self.ax2.imshow(graph, extent=[0,self.shape[1],self.shape[0]//2+1,-self.shape[0]//2-1]) #self.ax2.grid() norm = data[:,:,0] if normalize == False: norm = np.ones_like(norm) self._norm = norm self._data = data if semilogx == True: self.l, = self.ax1.semilogx(data[0,0,:]/norm[0,0]) else: self.l, = self.ax1.plot(data[0,0,:]/norm[0,0]) self.kax = plt.axes([0.1, 0.15, 0.65, 0.03]) self.kindex = Slider(self.kax, "k",0,data.shape[1]-1,valinit = 0, valfmt='%i') self.phiax = plt.axes([0.1, 0.10, 0.65, 0.03]) self.phiindex = Slider(self.phiax, "$\phi$",-90,90,valinit = 0, valfmt='%.2f') self.sectorax = plt.axes([0.1, 0.05, 0.65, 0.03]) self.sectorindex = Slider(self.sectorax, "sector",0,180,valinit = 5, valfmt='%.2f') def update(val): self.update() self.kindex.on_changed(update) self.phiindex.on_changed(update) self.sectorindex.on_changed(update) def update2(*args): self.update() return self.l, self.ani = FuncAnimation(self.fig, update2, interval=1000, blit=False) def update(self): k = self.kindex.val phi = self.phiindex.val sector = self.sectorindex.val ki = int(round(- k * np.sin(np.pi/180 * phi))) kj = int(round(k * np.cos(np.pi/180 * phi))) self.l.set_ydata(self._data[ki,kj,:]/self._norm[ki,kj]) graph = np.zeros((self.shape[0], self.shape[1])) if sector != 0: indexmap = sector_indexmap(self.shape[0],self.shape[1],phi, sector, 1) else: indexmap = line_indexmap(self.shape[0],self.shape[1],phi) #graph = np.concatenate((indexmap[:,:,np.newaxis],indexmap[:,:,np.newaxis],indexmap[:,:,np.newaxis]),-1) #make color image graph = indexmap mask = (indexmap == int(round(k))) graph[mask] = self._max_graph_value +1 avg_data = self.data[mask,:].mean(0) self.l.set_ydata(avg_data/avg_data[0]) # recompute the ax.dataLim self.ax1.relim() # update ax.viewLim using the new dataLim self.ax1.autoscale_view() avg_graph = np.zeros(self._graph_shape) avg_graph[mask] = 1 #graph[ki,kj] = 1 #print (ki,kj) self.im.set_data(np.fft.fftshift(graph,0)) #circ = Circle((ki,kj),5) #self.ax2.add_patch(circ) #self.fig.canvas.draw_idle() #self.fig.canvas.flush_events() #try: # self.fig.canvas.start_event_loop(0.5) #except: # pass def show(self): """Shows video.""" self.fig.show() def test_show_correlation(): video = np.random.randint(0,255,(256,129,1024*8),"uint8") viewer = CorrelationViewer() viewer.init(video) return viewer class CorrelationViewer2(object): """Shows correlation data in plot. You need to hold reference to this object, otherwise it will not work in interactive mode. """ def init(self,data, semilogx = True, normalize = True): #self.shape = data.shape (self.count_fast, self.data_fast), (self.count_slow, self.data_slow) = data self.shape = self.data_fast.shape[0:-1] self.fig, (self.ax1,self.ax2) = plt.subplots(1,2,gridspec_kw = {'width_ratios':[3, 1]}) self.fig.show() plt.subplots_adjust(bottom=0.25) graph_shape = self.shape[0], self.shape[1] self._graph_shape = graph_shape graph = np.zeros(graph_shape) max_graph_value = max(graph_shape[0]//2+1, graph_shape[1]) graph[0,0] = max_graph_value self._max_graph_value = max_graph_value self.im = self.ax2.imshow(graph, extent=[0,self.shape[1],self.shape[0]//2+1,-self.shape[0]//2-1]) #self.ax2.grid() cfast_avg = self.data_fast[0,0] cslow_avg = self.data_slow[:,0,0] normalize_data(cfast_avg, self.count_fast, cfast_avg) normalize_data(cslow_avg, self.count_slow, cslow_avg) t, avg_data = log_merge(cfast_avg,cslow_avg) if semilogx == True: self.l, = self.ax1.semilogx(avg_data/avg_data[0]) else: self.l, = self.ax1.plot(avg_data/avg_data[0]) self.kax = plt.axes([0.1, 0.15, 0.65, 0.03]) self.kindex = Slider(self.kax, "k",0,self.shape[1]-1,valinit = 0, valfmt='%i') self.phiax = plt.axes([0.1, 0.10, 0.65, 0.03]) self.phiindex = Slider(self.phiax, "$\phi$",-90,90,valinit = 0, valfmt='%.2f') self.sectorax = plt.axes([0.1, 0.05, 0.65, 0.03]) self.sectorindex = Slider(self.sectorax, "sector",0,180,valinit = 5, valfmt='%.2f') def update(val): self.update() self.kindex.on_changed(update) self.phiindex.on_changed(update) self.sectorindex.on_changed(update) def update2(*args): self.update() return self.l, #self.ani = FuncAnimation(self.fig, update2, interval=1000, blit=False) def update(self): k = self.kindex.val phi = self.phiindex.val sector = self.sectorindex.val #ki = int(round(- k * np.sin(np.pi/180 * phi))) #kj = int(round(k * np.cos(np.pi/180 * phi))) #self.l.set_ydata(self._data[ki,kj,:]/self._norm[ki,kj]) graph = np.zeros((self.shape[0], self.shape[1])) if sector != 0: indexmap = sector_indexmap(self.shape[0],self.shape[1],phi, sector, 1) else: indexmap = line_indexmap(self.shape[0],self.shape[1],phi) #graph = np.concatenate((indexmap[:,:,np.newaxis],indexmap[:,:,np.newaxis],indexmap[:,:,np.newaxis]),-1) #make color image graph = indexmap mask = (indexmap == int(round(k))) graph[mask] = self._max_graph_value +1 cfast_avg = self.data_fast[mask,:].mean(0) cslow_avg = self.data_slow[:,mask,:].mean(1) normalize_data(cfast_avg, self.count_fast, cfast_avg) normalize_data(cslow_avg, self.count_slow, cslow_avg) t, avg_data = log_merge(cfast_avg,cslow_avg) self.l.set_ydata(avg_data/avg_data[0]) self.l.set_xdata(t) # recompute the ax.dataLim self.ax1.relim() # update ax.viewLim using the new dataLim self.ax1.autoscale_view() avg_graph = np.zeros(self._graph_shape) avg_graph[mask] = 1 #graph[ki,kj] = 1 #print (ki,kj) self.im.set_data(np.fft.fftshift(graph,0)) #circ = Circle((ki,kj),5) #self.ax2.add_patch(circ) self.fig.canvas.draw() self.fig.canvas.flush_events() plt.pause(0.01) #try: # self.fig.canvas.start_event_loop(0.5) #except: # pass def show(self): """Shows video.""" self.fig.show()

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Python

ethsnarks_loopring/__init__.py

Linq-Liquidity-Network/ethsnarks-loopring

c27644ced40ff8758e8e780f17a208f063fc4965

[ "MIT" ]

null

ethsnarks_loopring/__init__.py

Linq-Liquidity-Network/ethsnarks-loopring

c27644ced40ff8758e8e780f17a208f063fc4965

[ "MIT" ]

null

ethsnarks_loopring/__init__.py

Linq-Liquidity-Network/ethsnarks-loopring

c27644ced40ff8758e8e780f17a208f063fc4965

[ "MIT" ]

null

from . import poseidon from .field import FQ, SNARK_SCALAR_FIELD from .poseidon import poseidon_params, poseidon from .eddsa import PureEdDSA, PoseidonEdDSA

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src/test2.py

joebhakim/mimic_understander

62c146e966cbd5d5e815db4580388977792c7ce7

[ "MIT" ]

null

src/test2.py

joebhakim/mimic_understander

62c146e966cbd5d5e815db4580388977792c7ce7

[ "MIT" ]

null

src/test2.py

joebhakim/mimic_understander

62c146e966cbd5d5e815db4580388977792c7ce7

[ "MIT" ]

null

import numpy as np print(2+2)

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py

Python

core/Home/__init__.py

earlfunk21/MoraxApp

5a2ba1630feca22abeb4892b784cea38174f6d87

[ "MIT" ]

null

core/Home/__init__.py

earlfunk21/MoraxApp

5a2ba1630feca22abeb4892b784cea38174f6d87

[ "MIT" ]

null

core/Home/__init__.py

earlfunk21/MoraxApp

5a2ba1630feca22abeb4892b784cea38174f6d87

[ "MIT" ]

null

from .home import HomeScreen

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Python

tests/test_io/test_io_saliva.py

Zwitscherle/BioPsyKit

7200c5f1be75c20f53e1eb4c991aca1c89e3dd88

[ "MIT" ]

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2020-11-05T13:34:55.000Z

2022-03-11T16:20:10.000Z

tests/test_io/test_io_saliva.py

Zwitscherle/BioPsyKit

7200c5f1be75c20f53e1eb4c991aca1c89e3dd88

[ "MIT" ]

14

2021-03-11T14:43:52.000Z

2022-03-10T19:44:57.000Z

tests/test_io/test_io_saliva.py

Zwitscherle/BioPsyKit

7200c5f1be75c20f53e1eb4c991aca1c89e3dd88

[ "MIT" ]

3

2021-09-13T13:14:38.000Z

2022-02-19T09:13:25.000Z

from contextlib import contextmanager from pathlib import Path import numpy as np import pandas as pd import pytest from pandas._testing import assert_frame_equal, assert_index_equal from biopsykit.io.saliva import load_saliva_plate, load_saliva_wide_format, save_saliva from biopsykit.utils.exceptions import FileExtensionError, ValidationError TEST_FILE_PATH = Path(__file__).parent.joinpath("../test_data") @contextmanager def does_not_raise(): yield def time_log_no_index(): df = pd.DataFrame( columns=["subject", "condition", "Baseline", "Intervention", "Stress", "Recovery", "End"], index=range(0, 2) ) return df def time_log_correct(): df = pd.DataFrame( [ ["12:32:05", "12:33:10", "12:35:00", "12:39:45", "12:42:00"], ["12:54:50", "12:55:50", "12:57:55", "12:58:00", "13:02:10"], ], columns=["Baseline", "Intervention", "Stress", "Recovery", "End"], index=pd.MultiIndex.from_tuples( [("Vp01", "Intervention"), ("Vp02", "Control")], names=["subject", "condition"] ), ) return df def time_log_not_continuous_correct(): df = pd.DataFrame( [["12:32:05", "12:33:10", "12:35:00", "12:39:45"], ["12:54:50", "12:55:50", "12:57:55", "12:58:00"]], columns=pd.MultiIndex.from_product([["phase1", "phase2"], ["start", "end"]], names=[None, "time"]), index=pd.MultiIndex.from_tuples( [("Vp01", "Intervention"), ("Vp02", "Control")], names=["subject", "condition"] ), ) return df def subject_condition_list_correct(): return pd.DataFrame( ["Intervention", "Control", "Control", "Intervention"], columns=["condition"], index=pd.Index(["Vp01", "Vp02", "Vp03", "Vp04"], name="subject"), ) def subject_condition_list_correct_dict(): return {"Control": ["Vp02", "Vp03"], "Intervention": ["Vp01", "Vp04"]} def questionnaire_data_no_remove(): return pd.DataFrame( { "PSS_01": [4, 2, 3, -66, np.nan], "PANAS_01": [2, 1, 4, -66, np.nan], }, index=pd.MultiIndex.from_arrays( [ ["Vp01", "Vp02", "Vp03", "Vp04", "Vp05"], ["Control", "Intervention", "Intervention", "Control", "Control"], ["pre", "pre", "post", "post", "pre"], ], names=["subject", "condition", "time"], ), ) def questionnaire_data_replace_missing(): return pd.DataFrame( { "PSS_01": [4, 2, 3, np.nan, np.nan], "PANAS_01": [2, 1, 4, np.nan, np.nan], }, index=pd.MultiIndex.from_arrays( [ ["Vp01", "Vp02", "Vp03", "Vp04", "Vp05"], ["Control", "Intervention", "Intervention", "Control", "Control"], ["pre", "pre", "post", "post", "pre"], ], names=["subject", "condition", "time"], ), ) def questionnaire_data_remove_nan(): return pd.DataFrame( { "PSS_01": [4, 2, 3, -66], "PANAS_01": [2, 1, 4, -66], }, index=pd.MultiIndex.from_arrays( [ ["Vp01", "Vp02", "Vp03", "Vp04"], ["Control", "Intervention", "Intervention", "Control"], ["pre", "pre", "post", "post"], ], names=["subject", "condition", "time"], ), ) def questionnaire_data_replace_missing_remove_nan(): return pd.DataFrame( { "PSS_01": [4, 2, 3], "PANAS_01": [2, 1, 4], }, index=pd.MultiIndex.from_arrays( [["Vp01", "Vp02", "Vp03"], ["Control", "Intervention", "Intervention"], ["pre", "pre", "post"]], names=["subject", "condition", "time"], ), ) def result_dict_correct(): return { "Vp01": pd.DataFrame(columns=["data"], index=pd.Index(range(0, 2), name="time")), "Vp02": pd.DataFrame(columns=["data"], index=pd.Index(range(0, 2), name="time")), "Vp03": pd.DataFrame(columns=["data"], index=pd.Index(range(0, 2), name="time")), } def saliva_data_invalid_format(): index = pd.MultiIndex.from_product([["Vp01", "Vp02", "Vp03"], ["S0", "S1", "S2", "S3"]], names=["ID", "value"]) return pd.DataFrame( {"cortisol": [0.1, 0.2, 0.3, 0.4, 0.11, 0.21, 0.31, 0.41, 0.12, 0.22, 0.32, 0.42]}, index=index, ) def saliva_data_samples(): index = pd.MultiIndex.from_product( [["Vp01", "Vp02", "Vp03"], ["S0", "S1", "S2", "S3"]], names=["subject", "sample"] ) return pd.DataFrame( {"cortisol": [0.1, 0.2, 0.3, 0.4, 0.11, 0.21, 0.31, 0.41, 0.12, 0.22, 0.32, 0.42]}, index=index, ) def saliva_data_samples_days(): index = pd.MultiIndex.from_product( [["Vp01", "Vp02"], ["T1", "T2"], ["S0", "S1", "S2"]], names=["subject", "day", "sample"], ) return pd.DataFrame( { "cortisol": [ 0.1, 0.2, 0.3, 0.15, 0.25, 0.35, 0.11, 0.21, 0.31, 0.16, 0.26, 0.36, ] }, index=index, ) def saliva_data_samples_time(): index = pd.MultiIndex.from_product( [["Vp01", "Vp02", "Vp03"], ["S0", "S1", "S2", "S3"]], names=["subject", "sample"] ) return pd.DataFrame( {"cortisol": [0.1, 0.2, 0.3, 0.4, 0.11, 0.21, 0.31, 0.41, 0.12, 0.22, 0.32, 0.42], "time": [0, 10, 20, 30] * 3}, index=index, ) def saliva_data_samples_condition(): index = pd.MultiIndex.from_tuples( [ ("Control", "Vp01", "S0"), ("Control", "Vp01", "S1"), ("Control", "Vp01", "S2"), ("Control", "Vp01", "S3"), ("Intervention", "Vp02", "S0"), ("Intervention", "Vp02", "S1"), ("Intervention", "Vp02", "S2"), ("Intervention", "Vp02", "S3"), ("Control", "Vp03", "S0"), ("Control", "Vp03", "S1"), ("Control", "Vp03", "S2"), ("Control", "Vp03", "S3"), ], names=["condition", "subject", "sample"], ) return pd.DataFrame( {"cortisol": [0.1, 0.2, 0.3, 0.4, 0.11, 0.21, 0.31, 0.41, 0.12, 0.22, 0.32, 0.42]}, index=index, ) def saliva_data_samples_time_condition(): index = pd.MultiIndex.from_tuples( [ ("Control", "Vp01", "S0"), ("Control", "Vp01", "S1"), ("Control", "Vp01", "S2"), ("Control", "Vp01", "S3"), ("Intervention", "Vp02", "S0"), ("Intervention", "Vp02", "S1"), ("Intervention", "Vp02", "S2"), ("Intervention", "Vp02", "S3"), ("Control", "Vp03", "S0"), ("Control", "Vp03", "S1"), ("Control", "Vp03", "S2"), ("Control", "Vp03", "S3"), ], names=["condition", "subject", "sample"], ) return pd.DataFrame( {"cortisol": [0.1, 0.2, 0.3, 0.4, 0.11, 0.21, 0.31, 0.41, 0.12, 0.22, 0.32, 0.42], "time": [0, 10, 20, 30] * 3}, index=index, ) class TestIoSaliva: @pytest.mark.parametrize( "file_path, saliva_type, sample_id_col, data_col, id_col_names, regex_str, " "sample_times, condition_list, expected", [ ("cortisol_plate_samples.xlsx", "cortisol", None, None, None, None, None, None, does_not_raise()), ("cortisol_plate_samples.xlsx", "cortisol", "sample ID", None, None, None, None, None, does_not_raise()), ( "cortisol_plate_samples.xlsx", "cortisol", "sample ID", "cortisol (nmol/l)", None, None, None, None, does_not_raise(), ), ( "cortisol_plate_samples.xlsx", "cortisol", "sample ID", "cortisol (nmol/l)", ["subject", "sample"], r"(Vp\d+) (S\d)", None, None, does_not_raise(), ), ( "cortisol_plate_samples.xlsx", "cortisol", "sample ID", "cortisol (nmol/l)", None, r"(Vp\d+) (S\d)", None, None, does_not_raise(), ), ( "cortisol_plate_samples.xlsx", "cortisol", "sample ID", "cortisol (nmol/l)", None, r"(Vp\d+) (S\d)", [0, 10, 20, 30], None, does_not_raise(), ), ( "cortisol_plate_samples.xlsx", "cortisol", "sample ID", "cortisol (nmol/l)", None, r"(Vp\d+) (S\d)", None, ["Control", "Condition", "Control"], does_not_raise(), ), ( "cortisol_plate_samples.xlsx", "cortisol", "sample ID", "cortisol (nmol/l)", None, r"(Vp\d+) (S\d)", None, ["Control", "Condition", "Control", "Condition"], pytest.raises(ValueError), ), ( "cortisol_plate_samples.csv", "cortisol", None, None, None, None, None, None, pytest.raises(FileExtensionError), ), ("cortisol_plate_samples.xlsx", "amylase", None, None, None, None, None, None, pytest.raises(ValueError)), ( "cortisol_plate_samples.xlsx", "cortisol", "sample", None, None, None, None, None, pytest.raises(ValueError), ), ( "cortisol_plate_samples.xlsx", "cortisol", None, "data", None, None, None, None, pytest.raises(ValueError), ), ( "cortisol_plate_samples.xlsx", "cortisol", None, None, None, "test", None, None, pytest.raises(ValueError), ), ( "cortisol_plate_samples.xlsx", "cortisol", None, None, None, r"Vp\d{2} S(\d)", None, None, pytest.raises(ValueError), ), ( "cortisol_plate_samples.xlsx", "cortisol", None, None, None, None, [0, 10, 20, 30, 40], None, pytest.raises(ValueError), ), ( "cortisol_plate_samples.xlsx", "cortisol", None, None, ["subject", "day", "sample"], None, None, None, pytest.raises(ValueError), ), ( "cortisol_plate_samples_wrong_number.xlsx", "cortisol", None, None, None, None, None, None, pytest.raises(ValueError), ), ], ) def test_load_saliva_plate_raises( self, file_path, saliva_type, sample_id_col, data_col, id_col_names, regex_str, sample_times, condition_list, expected, ): with expected: load_saliva_plate( file_path=TEST_FILE_PATH.joinpath(file_path), saliva_type=saliva_type, sample_id_col=sample_id_col, data_col=data_col, id_col_names=id_col_names, regex_str=regex_str, sample_times=sample_times, condition_list=condition_list, ) @pytest.mark.parametrize( "file_path, id_col_names, regex_str, expected", [ ( "cortisol_plate_samples.xlsx", ["subject", "sample"], r"(Vp\d+) (S\d)", pd.MultiIndex.from_product( [["Vp01", "Vp02", "Vp03"], ["S0", "S1", "S2", "S3"]], names=["subject", "sample"] ), ), ( "cortisol_plate_samples.xlsx", ["subject", "sample"], r"(Vp\w+) (S\w)", pd.MultiIndex.from_product( [["Vp01", "Vp02", "Vp03"], ["S0", "S1", "S2", "S3"]], names=["subject", "sample"] ), ), ( "cortisol_plate_samples.xlsx", ["subject", "sample"], r"(Vp\d{2}) (S\d)", pd.MultiIndex.from_product( [["Vp01", "Vp02", "Vp03"], ["S0", "S1", "S2", "S3"]], names=["subject", "sample"] ), ), ( "cortisol_plate_samples.xlsx", ["subject", "sample"], r"Vp(\w+) S(\d)", pd.MultiIndex.from_product([["01", "02", "03"], ["0", "1", "2", "3"]], names=["subject", "sample"]), ), ( "cortisol_plate_samples_days.xlsx", ["subject", "day", "sample"], r"(Vp\d+) (T\d) (S\d)", pd.MultiIndex.from_product( [["Vp01", "Vp02"], ["T1", "T2"], ["S0", "S1", "S2"]], names=["subject", "day", "sample"], ), ), ( "cortisol_plate_samples_days.xlsx", ["subject", "day", "sample"], r"Vp(\d+) (T\d) S(\d)", pd.MultiIndex.from_product( [["01", "02"], ["T1", "T2"], ["0", "1", "2"]], names=["subject", "day", "sample"], ), ), ], ) def test_load_saliva_plate_regex(self, file_path, id_col_names, regex_str, expected): data_out = load_saliva_plate( TEST_FILE_PATH.joinpath(file_path), saliva_type="cortisol", id_col_names=id_col_names, regex_str=regex_str ) assert_index_equal(data_out.index, expected) @pytest.mark.parametrize( "file_path, id_col_names, sample_times, condition_list, regex_str, expected", [ ("cortisol_plate_samples.xlsx", None, None, None, r"(Vp\d+) (S\d)", saliva_data_samples()), ("cortisol_plate_samples.xlsx", None, [0, 10, 20, 30], None, r"(Vp\d+) (S\d)", saliva_data_samples_time()), ( "cortisol_plate_samples.xlsx", None, [0, 10, 20, 30], ["Control", "Intervention", "Control"], r"(Vp\d+) (S\d)", saliva_data_samples_time_condition(), ), ( "cortisol_plate_samples.xlsx", None, [0, 10, 20, 30], {"Control": ["Vp01", "Vp03"], "Intervention": ["Vp02"]}, r"(Vp\d+) (S\d)", saliva_data_samples_time_condition(), ), ( "cortisol_plate_samples.xlsx", None, [0, 10, 20, 30], pd.DataFrame( {"subject": ["Vp01", "Vp02", "Vp03"], "condition": ["Control", "Intervention", "Control"]} ).set_index("subject"), r"(Vp\d+) (S\d)", saliva_data_samples_time_condition(), ), ( "cortisol_plate_samples.xlsx", None, None, ["Control", "Intervention", "Control"], r"(Vp\d+) (S\d)", saliva_data_samples_condition(), ), ("cortisol_plate_samples_days.xlsx", None, None, None, r"(Vp\d+) (T\d) (S\d)", saliva_data_samples_days()), ], ) def test_load_saliva_plate(self, file_path, id_col_names, sample_times, condition_list, regex_str, expected): data_out = load_saliva_plate( TEST_FILE_PATH.joinpath(file_path), saliva_type="cortisol", id_col_names=id_col_names, regex_str=regex_str, sample_times=sample_times, condition_list=condition_list, ) assert_frame_equal(data_out, expected) @pytest.mark.parametrize( "file_path, expected", [ ("cortisol_plate_samples_empty.xlsx", pytest.raises(ValueError)), ], ) def test_load_saliva_plate_empty_sample(self, file_path, expected): with expected: load_saliva_plate( TEST_FILE_PATH.joinpath(file_path), saliva_type="cortisol", ) @pytest.mark.parametrize( "input_data, saliva_type, file_path, expected", [ (saliva_data_samples(), "cortisol", "test_saliva.csv", does_not_raise()), (saliva_data_samples(), "cortisol", "test_saliva.xlsx", does_not_raise()), (saliva_data_samples(), "cortisol", "test_saliva.xls", does_not_raise()), (saliva_data_samples_time(), "cortisol", "test_saliva_time.csv", does_not_raise()), (saliva_data_samples_days(), "cortisol", "test_saliva_days.csv", does_not_raise()), (saliva_data_samples_condition(), "cortisol", "test_saliva_condition.csv", does_not_raise()), (saliva_data_samples_time_condition(), "cortisol", "test_saliva_condition.csv", does_not_raise()), (saliva_data_samples(), "amylase", "test_saliva.csv", pytest.raises(ValidationError)), (saliva_data_samples(), "cortisol", "test_saliva.txt", pytest.raises(FileExtensionError)), (saliva_data_invalid_format(), "cortisol", "test_saliva.csv", pytest.raises(ValidationError)), ], ) def test_save_saliva_raises(self, input_data, saliva_type, file_path, expected, tmp_path): with expected: save_saliva(tmp_path.joinpath(file_path), input_data, saliva_type=saliva_type) @pytest.mark.parametrize( "file_path, subject_col, condition_col, additional_index_cols, sample_times, expected", [ ("cortisol_wide_samples.xlsx", None, None, None, None, does_not_raise()), ("cortisol_wide_samples.csv", None, None, None, None, does_not_raise()), ("cortisol_wide_samples.csv", None, None, [], None, does_not_raise()), ("cortisol_wide_samples.csv", "subject", None, None, None, does_not_raise()), ("cortisol_wide_samples.csv", "subject", None, None, [0, 10, 20, 30], does_not_raise()), ("cortisol_wide_samples.csv", "ID", None, None, None, pytest.raises(ValidationError)), ("cortisol_wide_samples.csv", None, None, "day", None, pytest.raises(ValidationError)), ("cortisol_wide_samples_other_names.csv", None, None, None, None, pytest.raises(ValidationError)), ("cortisol_wide_samples_other_names.csv", "ID", None, None, None, does_not_raise()), ("cortisol_wide_samples.csv", None, "condition", None, None, pytest.raises(ValidationError)), ("cortisol_wide_samples.csv", None, None, None, [0, 10, 20, 30, 40], pytest.raises(ValueError)), ("cortisol_wide_samples.csv", None, None, None, [10, 0, 20, 30, 40], pytest.raises(ValueError)), ("cortisol_wide_samples_condition.csv", None, None, None, None, does_not_raise()), ("cortisol_wide_samples_condition.csv", None, "condition", None, None, does_not_raise()), ("cortisol_wide_samples_condition.csv", None, "Group", None, None, pytest.raises(ValidationError)), ( "cortisol_wide_samples_condition_other_names.csv", None, None, None, None, does_not_raise(), ), # works but result is not in the correct format ( "cortisol_wide_samples_condition_other_names.csv", None, "condition", None, None, pytest.raises(ValidationError), ), ( "cortisol_wide_samples_condition_other_names.csv", None, "Group", None, None, does_not_raise(), ), ( "cortisol_wide_samples_days.csv", None, None, None, None, does_not_raise(), ), # works but result is not in the correct format ("cortisol_wide_samples_days.csv", None, None, "day", None, does_not_raise()), ("cortisol_wide_samples_days.csv", None, None, ["day"], None, does_not_raise()), ], ) def test_load_saliva_wide_format_raises( self, file_path, subject_col, condition_col, additional_index_cols, sample_times, expected ): with expected: load_saliva_wide_format( TEST_FILE_PATH.joinpath(file_path), saliva_type="cortisol", subject_col=subject_col, condition_col=condition_col, sample_times=sample_times, additional_index_cols=additional_index_cols, ) @pytest.mark.parametrize( "file_path, subject_col, condition_col, sample_times, additional_index_cols, expected", [ ("cortisol_wide_samples.xlsx", None, None, None, None, saliva_data_samples()), ("cortisol_wide_samples.csv", None, None, None, None, saliva_data_samples()), ("cortisol_wide_samples.csv", "subject", None, None, None, saliva_data_samples()), ("cortisol_wide_samples.csv", "subject", None, [0, 10, 20, 30], None, saliva_data_samples_time()), ("cortisol_wide_samples_other_names.csv", "ID", None, None, None, saliva_data_samples()), ("cortisol_wide_samples_condition.csv", None, None, None, None, saliva_data_samples_condition()), ("cortisol_wide_samples_condition.csv", None, "condition", None, None, saliva_data_samples_condition()), ( "cortisol_wide_samples_condition_other_names.csv", None, "Group", None, None, saliva_data_samples_condition(), ), ("cortisol_wide_samples_days.csv", None, None, None, "day", saliva_data_samples_days()), ], ) def test_load_saliva_wide_format( self, file_path, subject_col, condition_col, sample_times, additional_index_cols, expected ): data_out = load_saliva_wide_format( TEST_FILE_PATH.joinpath(file_path), saliva_type="cortisol", subject_col=subject_col, condition_col=condition_col, sample_times=sample_times, additional_index_cols=additional_index_cols, ) assert_frame_equal(data_out, expected)

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755735f0648a7f36cc89a9f9eea7c4d2c965aaaf

98

py

Python

MultiDet/data/__init__.py

ydlstartx/MultiDet

82c62222f2bb9daeb1e07dc984b1e6b7b8d89a51

[ "MIT" ]

null

MultiDet/data/__init__.py

ydlstartx/MultiDet

82c62222f2bb9daeb1e07dc984b1e6b7b8d89a51

[ "MIT" ]

null

MultiDet/data/__init__.py

ydlstartx/MultiDet

82c62222f2bb9daeb1e07dc984b1e6b7b8d89a51

[ "MIT" ]

null

from . import genRecordIO from . import loadimg from .genRecordIO import * from .loadimg import *

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6

f32e31d3fa0bfe4c33b6cefcf76583d812ec931e

13,038

py

Python

tests/widgets/test_wizard.py

ffaraone/interrogatio

8b66e7fe73d14bfda38cc2eb3aecb3291e4afda1

[ "BSD-3-Clause" ]

5

2019-02-19T13:10:39.000Z

2022-03-04T19:11:04.000Z

tests/widgets/test_wizard.py

ffaraone/interrogatio

8b66e7fe73d14bfda38cc2eb3aecb3291e4afda1

[ "BSD-3-Clause" ]

11

2020-03-24T16:58:41.000Z

2021-12-14T10:19:17.000Z

tests/widgets/test_wizard.py

ffaraone/interrogatio

8b66e7fe73d14bfda38cc2eb3aecb3291e4afda1

[ "BSD-3-Clause" ]

2

2019-05-31T08:36:26.000Z

2020-12-18T17:58:50.000Z

from interrogatio.handlers import get_instance, QHandler from interrogatio.validators import RequiredValidator from interrogatio.widgets.wizard import WizardDialog def test_wizard_init_default(): questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) assert len(wz.steps) == 2 def test_wizard_init_intro_summary(): questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers, intro='intro', summary=True) assert len(wz.steps) == 4 def test_wizard_get_title(): questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) assert wz.get_title() == 'title - 1 of 2' def test_wizard_get_steps_label(): questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) steps_lables = wz.get_steps_labels() class_current = steps_lables.children[0].content.text[0][0] assert 'class:dialog.step.current ' == class_current assert '1. Question1' == steps_lables.children[0].content.text[0][1] assert 'class:dialog.step ' == steps_lables.children[1].content.text[0][0] assert '2. Question2' == steps_lables.children[1].content.text[0][1] def test_wizard_get_status(): questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) assert wz.get_status().text == '' wz.error_messages = 'An error' assert wz.get_status().content.text[0][0] == 'class:error' assert wz.get_status().content.text[0][1] == 'An error' def test_wizard_cancel(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) wz.cancel() mocked_app.exit.assert_called_once_with(result=False) def test_wizard_next(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] mocked_validate = mocker.patch.object(WizardDialog, 'validate') wz = WizardDialog('title', handlers) wz.next() # noqa: B305 assert wz.current_step_idx == 1 assert wz.current_step == wz.steps[1] assert len(wz.buttons) == 3 assert wz.previous_btn in wz.buttons mocked_validate.assert_called_once() def test_wizard_previous(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] mocker.patch.object(WizardDialog, 'validate') wz = WizardDialog('title', handlers) wz.next() # noqa: B305 wz.previous() assert wz.current_step_idx == 0 assert wz.current_step == wz.steps[0] assert len(wz.buttons) == 2 assert wz.previous_btn not in wz.buttons def test_wizard_next_latest_step(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] mocked_validate = mocker.patch.object(WizardDialog, 'validate') wz = WizardDialog('title', handlers) wz.next() # noqa: B305 wz.next() # noqa: B305 assert wz.current_step_idx == 1 assert wz.current_step == wz.steps[1] assert len(wz.buttons) == 3 assert wz.previous_btn in wz.buttons assert mocked_validate.call_count == 2 mocked_app.exit.assert_called_once_with(result=True) def test_wizard_previous_first_step(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] mocker.patch.object(WizardDialog, 'validate') wz = WizardDialog('title', handlers) wz.next() # noqa: B305 wz.previous() wz.previous() assert wz.current_step_idx == 0 assert wz.current_step == wz.steps[0] assert len(wz.buttons) == 2 assert wz.previous_btn not in wz.buttons def test_wizard_next_latest_step_with_summary(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] mocked_validate = mocker.patch.object(WizardDialog, 'validate') wz = WizardDialog('title', handlers, summary=True) wz.next() # noqa: B305 wz.next() # noqa: B305 wz.next() # noqa: B305 assert wz.current_step_idx == 2 assert wz.current_step == wz.steps[2] assert len(wz.buttons) == 3 assert wz.previous_btn in wz.buttons assert mocked_validate.call_count == 3 mocked_app.exit.assert_called_once_with(result=True) def test_get_summary(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, { 'name': 'question2', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [{'name': 'required'}], }, ] handlers = [get_instance(q) for q in questions] mocker.patch.object( QHandler, 'get_formatted_value', side_effect=['value1', 'value2'], ) wz = WizardDialog('title', handlers, summary=True) summary = wz.get_summary() expected_text1 = summary.content.text[0][1] + summary.content.text[1][1] expected_text2 = summary.content.text[2][1] + summary.content.text[3][1] assert 'Question1: value1' in expected_text1 assert 'Question2: value2' in expected_text2 def test_single_step(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) wz.next() # noqa: B305 assert wz.current_step_idx == 0 assert wz.current_step == wz.steps[0] assert len(wz.buttons) == 2 assert wz.previous_btn not in wz.buttons mocked_app.exit.assert_called_once_with(result=True) def test_wizard_next_validate_invalid(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', 'validators': [RequiredValidator('This field is required')], }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) wz.next() # noqa: B305 assert wz.current_step_idx == 0 assert wz.current_step == wz.steps[0] assert len(wz.buttons) == 2 assert wz.error_messages == 'This field is required' def test_wizard_get_current_step_container(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) assert wz.get_current_step_container() == wz.steps[0]['layout'] def test_wizard_get_buttons_container(mocker): mocked_app = mocker.MagicMock() mocker.patch('interrogatio.widgets.wizard.get_app', return_value=mocked_app) questions = [ { 'name': 'question1', 'type': 'input', 'message': 'message', 'description': 'description', }, ] handlers = [get_instance(q) for q in questions] wz = WizardDialog('title', handlers) assert wz.get_buttons_container() is not None

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0.820318

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false

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0.050667

0

null

0

1

0

null

0

6

343b0f5ccee58923806cd75ac8a4874cffedfff2

5,243

py

Python

model.py

Janik135/AttentionDeepMIL

03609a56a6527b9cab666d07037b0513be682577

[ "MIT" ]

null

model.py

Janik135/AttentionDeepMIL

03609a56a6527b9cab666d07037b0513be682577

[ "MIT" ]

null

model.py

Janik135/AttentionDeepMIL

03609a56a6527b9cab666d07037b0513be682577

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F class Attention(nn.Module): def __init__(self): super(Attention, self).__init__() self.L = 500 self.D = 128 self.K = 1 self.feature_extractor_part1 = nn.Sequential( nn.Conv2d(409, 36, kernel_size=5), nn.ReLU(), nn.MaxPool2d(2, stride=2), nn.Conv2d(36, 48, kernel_size=5), nn.ReLU(), nn.MaxPool2d(2, stride=2) ) self.feature_extractor_part2 = nn.Sequential( nn.Linear(48 * 5 * 1, self.L), nn.ReLU(), # nn.Dropout() ) self.attention = nn.Sequential( nn.Linear(self.L, self.D), nn.Tanh(), nn.Linear(self.D, self.K) ) self.classifier = nn.Sequential( # nn.Linear(self.L*self.K, self.L*self.K), # nn.ReLU(), nn.Linear(self.L*self.K, 2), nn.LogSoftmax() ) def forward(self, x): #x = x.squeeze(0) H = self.feature_extractor_part1(x) H = H.view(-1, 48 * 5 * 1) H = self.feature_extractor_part2(H) # NxL ''' A = self.attention(H) # NxK A = torch.transpose(A, 1, 0) # KxN A = F.softmax(A, dim=1) # softmax over N M = torch.mm(A, H) # KxL ''' Y_prob = self.classifier(H) # Y_hat = Y_prob.float() Y_hat = Y_prob.argmax(dim=1, keepdim=True) #Y_hat = torch.argmax(Y_prob).float().view(-1) # Y_hat = torch.ge(Y_prob, 0.5).float() return Y_prob, Y_hat # AUXILIARY METHODS def calculate_classification_error(self, X, Y): Y = Y.float() _, Y_hat = self.forward(X) # print(Y, Y_hat) error = 1. - Y_hat.eq(Y).cpu().float().mean().data.item() return error, Y_hat def calculate_balanced_error(self, X, Y): Y = Y.float() _, Y_hat = self.forward(X) # print(Y, Y_hat) error = 1. - Y_hat.eq(Y).cpu().float().mean().data.item() return error, Y_hat def calculate_objective(self, X, Y): Y = Y.float() Y_prob, _ = self.forward(X) Y_prob = torch.clamp(Y_prob, min=1e-5, max=1. - 1e-5) neg_log_likelihood = -1. * (Y * torch.log(Y_prob) + (1. - Y) * torch.log(1. - Y_prob)) # negative log bernoulli return neg_log_likelihood def calculate_nll(self, X, Y): Y_prob, _ = self.forward(X) # Y_prob = torch.clamp(Y_prob, min=1e-5, max=1. - 1e-5) weight = torch.Tensor([0.8, 0.2]) loss = nn.NLLLoss(weight=weight, reduction="sum") neg_log_likelihood = loss(Y_prob, Y) return neg_log_likelihood class GatedAttention(nn.Module): def __init__(self): super(GatedAttention, self).__init__() self.L = 500 self.D = 128 self.K = 1 self.feature_extractor_part1 = nn.Sequential( nn.Conv2d(3, 20, kernel_size=5), nn.ReLU(), nn.MaxPool2d(2, stride=2), nn.Conv2d(20, 50, kernel_size=5), nn.ReLU(), nn.MaxPool2d(2, stride=2) ) self.feature_extractor_part2 = nn.Sequential( nn.Linear(50 * 11 * 11, self.L), nn.ReLU(), ) self.attention_V = nn.Sequential( nn.Linear(self.L, self.D), nn.Tanh() ) self.attention_U = nn.Sequential( nn.Linear(self.L, self.D), nn.Sigmoid() ) self.attention_weights = nn.Linear(self.D, self.K) self.classifier = nn.Sequential( nn.Linear(self.L*self.K, 2), nn.LogSoftmax() ) def forward(self, x): x = x.squeeze(0) H = self.feature_extractor_part1(x) H = H.view(-1, 50 * 11 * 11) H = self.feature_extractor_part2(H) # NxL A_V = self.attention_V(H) # NxD A_U = self.attention_U(H) # NxD A = self.attention_weights(A_V * A_U) # element wise multiplication # NxK A = torch.transpose(A, 1, 0) # KxN A = F.softmax(A, dim=1) # softmax over N M = torch.mm(A, H) # KxL Y_prob = self.classifier(M) # Y_hat = torch.ge(Y_prob, 0.5).float() Y_hat = torch.argmax(Y_prob).float().view(-1) return Y_prob, Y_hat, A # AUXILIARY METHODS def calculate_classification_error(self, X, Y): Y = Y.float() _, Y_hat, _ = self.forward(X) error = 1. - Y_hat.eq(Y).cpu().float().mean().item() return error, Y_hat def calculate_objective(self, X, Y): Y = Y.float() Y_prob, _, A = self.forward(X) Y_prob = torch.clamp(Y_prob, min=1e-5, max=1. - 1e-5) neg_log_likelihood = -1. * (Y * torch.log(Y_prob) + (1. - Y) * torch.log(1. - Y_prob)) # negative log bernoulli return neg_log_likelihood, A def calculate_nll(self, X, Y): Y_prob, _, A = self.forward(X) # Y_prob = torch.clamp(Y_prob, min=1e-5, max=1. - 1e-5) # weight = torch.Tensor([0.8, 0.2]) loss = nn.NLLLoss() neg_log_likelihood = loss(Y_prob, Y) return neg_log_likelihood, A

29.127778

120

0.530994

745

5,243

3.566443

0.147651

0.052691

0.047422

0.052691

0.833271

0.821227

0.803161

0.76402

0.702672

0

0.03795

0.326531

5,243

179

121

29.290503

0.714528

0.105283

0

0.575

0

0.000669

0

1

0.091667

false

0

0.025

0

0.208333

0

null

0

1

0

null

0

6

1b17fdea0b992ed52b1963b045e5497632bd582e

6,633

py

Python

cdshealpix/tests/test_benchmark_healpix.py

cds-astro/cds-healpix-python

bc02f2e7ccad1d55f3a5e4caac689d8cc29eadeb

[ "BSD-3-Clause" ]

3

2019-01-30T13:34:51.000Z

2020-11-11T07:31:12.000Z

cdshealpix/tests/test_benchmark_healpix.py

cds-astro/cds-healpix-python

bc02f2e7ccad1d55f3a5e4caac689d8cc29eadeb

[ "BSD-3-Clause" ]

9

2019-07-04T08:09:47.000Z

2021-03-10T16:51:18.000Z

cdshealpix/tests/test_benchmark_healpix.py

cds-astro/cds-healpix-python

bc02f2e7ccad1d55f3a5e4caac689d8cc29eadeb

[ "BSD-3-Clause" ]

1

2019-07-04T11:23:20.000Z

import pytest import astropy.units as u import numpy as np import astropy_healpix from ..nested import lonlat_to_healpix, \ healpix_to_lonlat, \ healpix_to_skycoord, \ vertices, \ neighbours, \ cone_search from astropy.coordinates import Longitude, Latitude @pytest.mark.benchmark(group="lonlat_to_healpix_broadcast") def test_lonlat_to_healpix_broadcast(benchmark): size = 10000 depth = np.random.randint(low=0, high=29, size=10) lon = Longitude(np.random.rand(size) * 360, u.deg) lat = Latitude(np.random.rand(size) * 180 - 90, u.deg) ipixels = benchmark(lonlat_to_healpix, lon=lon[:, np.newaxis], lat=lat[:, np.newaxis], depth=depth[np.newaxis, :], num_threads=1) @pytest.mark.benchmark(group="lonlat_to_healpix_broadcast") def test_lonlat_to_healpix_broadcast_multithread(benchmark): size = 10000 depth = np.random.randint(low=0, high=29, size=10) lon = Longitude(np.random.rand(size) * 360, u.deg) lat = Latitude(np.random.rand(size) * 180 - 90, u.deg) ipixels = benchmark(lonlat_to_healpix, lon=lon[:, np.newaxis], lat=lat[:, np.newaxis], depth=depth[np.newaxis, :]) @pytest.mark.benchmark(group="lonlat_to_healpix_broadcast") def test_lonlat_to_healpix_astropy_broadcast(benchmark): depth = np.random.randint(low=0, high=29, size=10) nside = 2 ** depth size = 10000 lon = np.random.rand(size) * 360 * u.deg lat = (np.random.rand(size) * 180 - 90) * u.deg ipixels = benchmark(astropy_healpix.core.lonlat_to_healpix, lon=lon[:, np.newaxis], lat=lat[:, np.newaxis], nside=nside[np.newaxis, :], order='nested') @pytest.mark.benchmark(group="lonlat_to_healpix") def test_lonlat_to_healpix(benchmark): size = 10000 depth = 12 lon = Longitude(np.random.rand(size) * 360, u.deg) lat = Latitude(np.random.rand(size) * 180 - 90, u.deg) ipixels = benchmark(lonlat_to_healpix, lon=lon, lat=lat, depth=depth, num_threads=1) @pytest.mark.benchmark(group="lonlat_to_healpix") def test_lonlat_to_healpix_multithread(benchmark): size = 10000 depth = 12 lon = Longitude(np.random.rand(size) * 360, u.deg) lat = Latitude(np.random.rand(size) * 180 - 90, u.deg) ipixels = benchmark(lonlat_to_healpix, lon=lon, lat=lat, depth=depth) @pytest.mark.benchmark(group="lonlat_to_healpix") def test_lonlat_to_healpix_astropy(benchmark): size = 10000 depth = 12 nside = 1 << depth lon = np.random.rand(size) * 360 * u.deg lat = (np.random.rand(size) * 180 - 90) * u.deg ipixels = benchmark(astropy_healpix.core.lonlat_to_healpix, lon=lon, lat=lat, nside=nside, order='nested') @pytest.mark.benchmark(group="healpix_to_lonlat_broadcast") def test_healpix_to_lonlat_broadcast(benchmark): size = 1000 depth = np.random.randint(low=0, high=29, size=10) ipixels = np.random.randint(12 * 4 ** np.min(depth), size=size) lon, lat = benchmark(healpix_to_lonlat, ipix=ipixels[:, np.newaxis], depth=depth[np.newaxis, :], num_threads=1) @pytest.mark.benchmark(group="healpix_to_lonlat_broadcast") def test_healpix_to_lonlat_broadcast_multithread(benchmark): size = 1000 depth = np.random.randint(low=0, high=29, size=10) ipixels = np.random.randint(12 * 4 ** np.min(depth), size=size) lon, lat = benchmark(healpix_to_lonlat, ipix=ipixels[:, np.newaxis], depth=depth[np.newaxis, :]) @pytest.mark.benchmark(group="healpix_to_lonlat_broadcast") def test_healpix_to_lonlat_astropy_broadcast(benchmark): size = 1000 depth = np.random.randint(low=0, high=29, size=10) nside = 2 ** depth ipixels = np.random.randint(12 * 4 ** np.min(depth), size=size) lon, lat = benchmark(astropy_healpix.core.healpix_to_lonlat, healpix_index=ipixels[:, np.newaxis], nside=nside[np.newaxis, :], order='nested') @pytest.mark.benchmark(group="healpix_to_lonlat") def test_healpix_to_lonlat(benchmark): size = 10000 depth = 12 ipixels = np.random.randint(12 * 4 ** (depth), size=size) lon, lat = benchmark(healpix_to_lonlat, ipix=ipixels, depth=depth, num_threads=1) @pytest.mark.benchmark(group="healpix_to_lonlat") def test_healpix_to_lonlat_multithread(benchmark): size = 10000 depth = 12 ipixels = np.random.randint(12 * 4 ** (depth), size=size) lon, lat = benchmark(healpix_to_lonlat, ipix=ipixels, depth=depth) @pytest.mark.benchmark(group="healpix_to_lonlat") def test_healpix_to_lonlat_astropy(benchmark): size = 10000 depth = 12 nside = 1 << depth ipixels = np.random.randint(12 * 4 ** (depth), size=size) lon, lat = benchmark(astropy_healpix.core.healpix_to_lonlat, healpix_index=ipixels, nside=nside, order='nested') def test_healpix_to_skycoord(): skycoord = healpix_to_skycoord(ipix=[0, 2, 4], depth=0) @pytest.mark.benchmark(group="vertices") def test_healpix_vertices_lonlat(benchmark): depth = 12 size = 100000 ipixels = np.random.randint(12 * 4**(depth), size=size) lon, lat = benchmark(vertices, ipix=ipixels, depth=depth, num_threads=1) @pytest.mark.benchmark(group="vertices") def test_healpix_vertices_lonlat_multithread(benchmark): depth = 12 size = 100000 ipixels = np.random.randint(12 * 4**(depth), size=size) lon, lat = benchmark(vertices, ipix=ipixels, depth=depth) @pytest.mark.benchmark(group="vertices") def test_healpix_vertices_lonlat_astropy(benchmark): depth = 12 size = 100000 ipixels = np.random.randint(12 * 4**(depth), size=size) lon2, lat2 = benchmark(astropy_healpix.core.boundaries_lonlat, healpix_index=ipixels, nside=(1 << depth), step=1, order='nested') @pytest.mark.benchmark(group="neighbours") def test_healpix_neighbours(benchmark): depth = 12 size = 100000 ipixels = np.random.randint(12 * 4**(depth), size=size) res = benchmark(neighbours, ipix=ipixels, depth=depth) lon_c = np.random.rand(1)[0] * 360 * u.deg lat_c = (np.random.rand(1)[0] * 180 - 90) * u.deg radius_c = np.random.rand(1)[0] * 45 * u.deg depth_c = 5 @pytest.mark.benchmark(group="cone_search") def test_cone_search(benchmark): res = benchmark.pedantic(cone_search, kwargs={'lon': Longitude(lon_c), 'lat': Latitude(lat_c), 'radius': radius_c, 'depth': depth_c}, iterations=10, rounds=100) @pytest.mark.benchmark(group="cone_search") def test_cone_search_astropy(benchmark): nside = 1 << depth_c res = benchmark.pedantic(astropy_healpix.core.healpix_cone_search, kwargs={'lon': lon_c, 'lat': lat_c, 'radius': radius_c, 'nside': nside, 'order': 'nested'}, iterations=10, rounds=100)

34.727749

189

0.700739

948

6,633

4.726793

0.079114

0.055345

0.063602

0.096407

0.828833

0.81098

0.785093

0.783754

0.762107

0

0.045569

0.159656

6,633

190

34.910526

0.758342

0

0.612245

0

0.059551

0.024423

0

1

0.129252

false

0

0.040816

0

0.170068

0

null

0

1

0

null

0

6

1b4c6226b1840ffbaec25fc9041c21431e08e249

43

py

Python

tests/unit/test_potato.py

noahbaxter/SoundCloudDegater

93a5e1ef6c9c39307b0f518e7e6e1838c1514cce

[ "Apache-2.0" ]

null

tests/unit/test_potato.py

noahbaxter/SoundCloudDegater

93a5e1ef6c9c39307b0f518e7e6e1838c1514cce

[ "Apache-2.0" ]

null

tests/unit/test_potato.py

noahbaxter/SoundCloudDegater

93a5e1ef6c9c39307b0f518e7e6e1838c1514cce

[ "Apache-2.0" ]

null

def test_potato(): print("potato")

10.75

20

0.581395

5

43

4.8

0.8

0

0.255814

43

3

21

14.333333

0.75

0

0.153846

0

1

0.5

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

6

1b4e5f4af649e9503c4e81e3210050705b689713

128

py

Python

kueue/__init__.py

jarojasm95/kueue

ca6f906b915ef25fb5c2e03d3477a0808258d247

[ "MIT" ]

3

2020-12-11T21:39:28.000Z

2021-05-04T23:19:59.000Z

kueue/__init__.py

jarojasm95/kueue

ca6f906b915ef25fb5c2e03d3477a0808258d247

[ "MIT" ]

null

kueue/__init__.py

jarojasm95/kueue

ca6f906b915ef25fb5c2e03d3477a0808258d247

[ "MIT" ]

null

# flake8: noqa from kueue.config import KueueConfig from kueue.consumer import TaskExecutorConsumer from kueue.task import task

25.6

47

0.84375

17

128

6.352941

0.588235

0.25

0

0.00885

0.117188

128

4

48

32

0.946903

0.09375

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

1b55373ab5e251c8ad9d76fa0100d2d9c269ef5d

25,612

py

Python

IBOPE.py

FredericoCastilho/medicaoIBOPE

50761e3cf1e0e15174b674623b3aa7164292db3c

[ "MIT" ]

null

IBOPE.py

FredericoCastilho/medicaoIBOPE

50761e3cf1e0e15174b674623b3aa7164292db3c

[ "MIT" ]

null

IBOPE.py

FredericoCastilho/medicaoIBOPE

50761e3cf1e0e15174b674623b3aa7164292db3c

[ "MIT" ]

null

print("-------------") print("| IBOPE |") print("-------------") ponto_pnt=int(716007) ponto_grande_sp=int(205377) ponto_grande_rj=int(125721) ponto_grande_bh=int(55610) ponto_grande_portoAlegre=int(40332) ponto_grande_recife=int(37569) ponto_grande_salvador=int(36627) ponto_grande_fortaleza=int(36088) ponto_grande_curitiba=int(32449) ponto_distrito_federal=int(27337) ponto_grande_goiania=int(24317) ponto_grande_belem=int(23001) ponto_grande_campinas=int(22289) ponto_grande_manaus=int(19774) ponto_grande_vitoria=int(18578) ponto_grande_floripa=int(10936) tot_pessoas_pnt=int(0) lista_regiao=[] regiao=["PAINEL NACIONAL DE TELEVISÃO", "SÃO PAULO", "RIO DE JANEIRO", "BELO HORIZONTE", "PORTO ALEGRE", "RECIFE", "SALVADOR", "FORTALEZA", "CURITIBA", "DISTRITO FEDERAL", "GOIÂNIA", "BELÉM", "CAMPINAS", "MANAUS", "VITÓRIA", "FLORIANÓPOLIS"] resp=str("N") resp_menu_audiencia=int(0) while (resp=="N"): while ((resp_menu_audiencia!=1) or (resp_menu_audiencia!=2)): print("""MENU CADASTRO DE AUDIÊNCIA [ 1 ] AUDIÊNCIA NACIONAL(PNT) [ 2 ] AUDIÊNCIA DE UMA REGIÃO METROPOLINATA [ 3 ] AUDIÊNCIA DE TODAS AS 15 REGIÕES METROPOLITANAS [ 4 ] SAIR""") resp_menu_audiencia = int(input("QUAL A ESCOLHA?")) if resp_menu_audiencia==1: nome_programa=str(input("NOME DA ATRAÇÃO:")).strip() nome_programa=nome_programa.upper() tot_pontos_pnt=int((input("DIGITE OS PONTOS DA AUDIÊNCIA NACIONAL(PNT) DA ATRAÇÃO:"))) tot_pessoas_pnt = tot_pontos_pnt*ponto_pnt print("-=" * 20) print(""" ATRAÇÃO:{} PAINEL NACIONAL DE TELEVISÃO AUDIÊNCIA:{} PONTOS UM(1) PONTO NO PNT EQUIVALE:{} PESSOAS """.format(nome_programa, tot_pontos_pnt, ponto_pnt)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} NO PNT FOI DE {}\n".format(nome_programa, tot_pessoas_pnt)) print("-=" * 20) elif resp_menu_audiencia==2: print("CADASTRANDO AUDIÊNCIA POR REGIÃO...") nome_programa = str(input("NOME DA ATRAÇÃO:")).strip() nome_programa=nome_programa.upper() print("""ESCOLHA A REGIÃO METROPOLITANA: [ 1 ] SÃO PAULO [ 2 ] RIO DE JANEIRO [ 3 ] BELO HORIZONTE [ 4 ] PORTO ALEGRE [ 5 ] RECIFE [ 6 ] SALVADOR [ 7 ] FORTALEZA [ 8 ] CURITIBA [ 9 ] DISTRITO FEDERAL [ 10] GOIÂNIA [ 11] BELÉM [ 12] CAMPINAS [ 13] MANAUS [ 14] VITÓRIA [ 15] FLORIANÓPOLIS """) escolha_regiao=int(input("QUAL A OPÇÃO?")) if (escolha_regiao==1): nome_regiao=str("SÃO PAULO") tot_pontos_sp=int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {}:".format(nome_programa))) tot_pessoas_sp=(tot_pontos_sp*ponto_grande_sp) print("-="*20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_sp, ponto_grande_sp)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_sp)) print("-=" * 20) elif (escolha_regiao==2): nome_regiao=str("RIO DE JANEIRO") tot_pontos_rj = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {}:".format(nome_programa))) tot_pessoas_rj=(tot_pontos_rj*ponto_grande_rj) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_rj, ponto_grande_rj)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_rj)) print("-=" * 20) elif (escolha_regiao==3): nome_regiao=str("BELO HORIZONTE") tot_pontos_bh = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {}:".format(nome_programa))) tot_pessoas_bh=(tot_pontos_bh*ponto_grande_bh) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_bh, ponto_grande_bh)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_bh)) print("-=" * 20) elif (escolha_regiao==4): nome_regiao=str("PORTO ALEGRE") tot_pontos_portoalegre = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {}:".format(nome_programa))) tot_pessoas_portoalegre=(tot_pontos_portoalegre*ponto_grande_portoAlegre) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_portoalegre, ponto_grande_portoAlegre)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_portoalegre)) print("-=" * 20) elif (escolha_regiao==5): nome_regiao=str("RECIFE") tot_pontos_recife = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {}:".format(nome_programa))) tot_pessoas_recife=(tot_pontos_recife*ponto_grande_recife) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_recife, ponto_grande_recife)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_recife)) print("-=" * 20) elif (escolha_regiao==6): nome_regiao=str("SALVADOR") tot_pontos_salvador = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_salvador=(tot_pontos_salvador*ponto_grande_salvador) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_salvador, ponto_grande_salvador)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_salvador)) print("-=" * 20) elif (escolha_regiao==7): nome_regiao=str("FORTALEZA") tot_pontos_fortaleza = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_fortaleza=(tot_pontos_fortaleza*ponto_grande_fortaleza) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_fortaleza, ponto_grande_fortaleza)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_fortaleza)) print("-=" * 20) elif (escolha_regiao==8): nome_regiao=str("CURITIBA") tot_pontos_curitiba = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_curitiba=(tot_pontos_curitiba*ponto_grande_curitiba) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_curitiba, ponto_grande_curitiba)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_curitiba)) print("-=" * 20) elif (escolha_regiao==9): nome_regiao=str("DISTRITO FEDERAL") tot_pontos_df = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_df=(tot_pontos_df*ponto_distrito_federal) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_df, ponto_distrito_federal)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_df)) elif (escolha_regiao==10): nome_regiao=str("GOIÂNIA") tot_pontos_goiania = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_goiania=(tot_pontos_goiania*ponto_grande_goiania) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_goiania, ponto_grande_goiania)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_goiania)) print("-=" * 20) elif (escolha_regiao==11): nome_regiao=str("BELÉM") tot_pontos_belem = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_belem=(tot_pontos_belem*ponto_grande_belem) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_belem, ponto_grande_belem)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_belem)) print("-=" * 20) elif (escolha_regiao==12): nome_regiao=str("CAMPINAS") tot_pontos_campinas = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_campinas=(tot_pontos_campinas*ponto_grande_campinas) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_campinas, ponto_grande_campinas)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_campinas)) print("-=" * 20) elif (escolha_regiao==13): nome_regiao=str("MANAUS") tot_pontos_manaus = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_manaus=(tot_pontos_manaus*ponto_grande_manaus) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_manaus, ponto_grande_manaus)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_manaus)) print("-=" * 20) elif (escolha_regiao==14): nome_regiao=str("VITÓRIA") tot_pontos_vitoria = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_vitoria=(tot_pontos_vitoria*ponto_grande_vitoria) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_vitoria, ponto_grande_vitoria)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_vitoria)) print("-=" * 20) elif (escolha_regiao==15): nome_regiao=str("FLORIANÓPOLIS") tot_pontos_floripa = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {}:".format(nome_programa))) tot_pessoas_floripa=(tot_pontos_floripa*ponto_grande_floripa) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao, tot_pontos_floripa, ponto_grande_floripa)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao, tot_pessoas_floripa)) print("-=" * 20) elif resp_menu_audiencia==3: nome_programa = str(input("NOME DA ATRAÇÃO:")).strip() nome_programa=nome_programa.upper() nome_regiao1=str("SÃO PAULO") escolha_regiao = 1 tot_pontos_sp=int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {} EM {}:".format(nome_programa, nome_regiao1))) tot_pessoas_sp=(tot_pontos_sp*ponto_grande_sp) print("-="*20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1)PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao1, tot_pontos_sp, ponto_grande_sp)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao1, tot_pessoas_sp)) print("-=" * 20) nome_regiao2=str("RIO DE JANEIRO") escolha_regiao = 2 tot_pontos_rj = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {} EM {}:".format(nome_programa, nome_regiao2))) tot_pessoas_rj=(tot_pontos_rj*ponto_grande_rj) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao2, tot_pontos_rj, ponto_grande_rj)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao2, tot_pessoas_rj)) print("-=" * 20) nome_regiao3=str("BELO HORIZONTE") escolha_regiao = 3 tot_pontos_bh = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {} EM {} :".format(nome_programa, nome_regiao3))) tot_pessoas_bh=(tot_pontos_bh*ponto_grande_bh) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao3, tot_pontos_bh, ponto_grande_bh)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao3, tot_pessoas_bh)) print("-=" * 20) nome_regiao4=str("PORTO ALEGRE") escolha_regiao = 4 tot_pontos_portoalegre = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {} EM {}:".format(nome_programa, nome_regiao4))) tot_pessoas_portoalegre=(tot_pontos_portoalegre*ponto_grande_portoAlegre) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao4, tot_pontos_portoalegre, ponto_grande_portoAlegre)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao4, tot_pessoas_portoalegre)) print("-=" * 20) nome_regiao5=str("RECIFE") escolha_regiao = 5 tot_pontos_recife = int(input("DIGITE A AUDIÊNCIA EM PONTOS DA ATRAÇÃO {} EM {}:".format(nome_programa, nome_regiao5))) tot_pessoas_recife=(tot_pontos_recife*ponto_grande_recife) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao5, tot_pontos_recife, ponto_grande_recife)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao5, tot_pessoas_recife)) print("-=" * 20) nome_regiao6=str("SALVADOR") escolha_regiao = 6 tot_pontos_salvador = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao6))) tot_pessoas_salvador=(tot_pontos_salvador*ponto_grande_salvador) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao6, tot_pontos_salvador, ponto_grande_salvador)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao6, tot_pessoas_salvador)) print("-=" * 20) nome_regiao7=str("FORTALEZA") escolha_regiao = 7 tot_pontos_fortaleza = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao7))) tot_pessoas_fortaleza=(tot_pontos_fortaleza*ponto_grande_fortaleza) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao7, tot_pontos_fortaleza, ponto_grande_fortaleza)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} DE {} PESSOAS".format(nome_programa, nome_regiao7, tot_pessoas_fortaleza)) print("-=" * 20) nome_regiao8=str("CURITIBA") escolha_regiao = 8 tot_pontos_curitiba = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao8))) tot_pessoas_curitiba=(tot_pontos_curitiba*ponto_grande_curitiba) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao8, tot_pontos_curitiba, ponto_grande_curitiba)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao8, tot_pessoas_curitiba)) print("-=" * 20) nome_regiao9=str("DISTRITO FEDERAL") escolha_regiao = 9 tot_pontos_df = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao9))) tot_pessoas_df=(tot_pontos_df*ponto_distrito_federal) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao9, tot_pontos_df, ponto_distrito_federal)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao9, tot_pessoas_df)) nome_regiao10=str("GOIÂNIA") escolha_regiao = 10 tot_pontos_goiania = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao10))) tot_pessoas_goiania=(tot_pontos_goiania*ponto_grande_goiania) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao10, tot_pontos_goiania, ponto_grande_goiania)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao10, tot_pessoas_goiania)) print("-=" * 20) nome_regiao11=str("BELÉM") escolha_regiao = 11 tot_pontos_belem = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao11))) tot_pessoas_belem=(tot_pontos_belem*ponto_grande_belem) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao11, tot_pontos_belem, ponto_grande_belem)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao11, tot_pessoas_belem)) print("-=" * 20) nome_regiao12=str("CAMPINAS") escolha_regiao = 12 tot_pontos_campinas = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao12))) tot_pessoas_campinas=(tot_pontos_campinas*ponto_grande_campinas) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao12, tot_pontos_campinas, ponto_grande_campinas)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao12, tot_pessoas_campinas)) print("-=" * 20) nome_regiao13=str("MANAUS") escolha_regiao = 13 tot_pontos_manaus = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao13))) tot_pessoas_manaus=(tot_pontos_manaus*ponto_grande_manaus) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao13, tot_pontos_manaus, ponto_grande_manaus)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao13, tot_pessoas_manaus)) print("-=" * 20) nome_regiao14=str("VITÓRIA") escolha_regiao = 14 tot_pontos_vitoria = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao14))) tot_pessoas_vitoria=(tot_pontos_vitoria*ponto_grande_vitoria) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao14, tot_pontos_vitoria, ponto_grande_vitoria)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao14, tot_pessoas_vitoria)) print("-=" * 20) nome_regiao15=str("FLORIANÓPOLIS") escolha_regiao = 15 tot_pontos_floripa = int(input("DIGITE A AUDIÊNCIA EM PONTOS DO PROGRAMA {} EM {}:".format(nome_programa, nome_regiao15))) tot_pessoas_floripa=(tot_pontos_floripa*ponto_grande_floripa) print("-=" * 20) print(""" ATRAÇÃO:{} REGIÃO METROPOLITANA:{} AUDIÊNCIA:{} PONTOS UM(1) PONTO EQUIVALE:{} PESSOAS """.format(nome_programa, nome_regiao15, tot_pontos_floripa, ponto_grande_floripa)) print("O TOTAL DE PESSOAS QUE ASSITIRAM A ATRAÇÃO {} EM {} FOI DE {} PESSOAS".format(nome_programa, nome_regiao15, tot_pessoas_floripa)) print("-=" * 20) elif resp_menu_audiencia==4: break resp=str(input("DESEJA SAIR?[S/N]")).strip() resp=resp.upper() print("SAINDO DO PROGRAMA...")

51.224

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null

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6

1b5f610c4c1a73954a5531011bd3b9af0922128f

156

py

Python

src/services/processing/__init__.py

Gabvaztor/tensorflowCode

e206ea4544552b87c2d43274cea3182f6b385a87

[ "Apache-2.0" ]

4

2019-12-14T08:06:18.000Z

2020-09-12T10:09:31.000Z

src/services/processing/__init__.py

Gabvaztor/tensorflowCode

e206ea4544552b87c2d43274cea3182f6b385a87

[ "Apache-2.0" ]

null

src/services/processing/__init__.py

Gabvaztor/tensorflowCode

e206ea4544552b87c2d43274cea3182f6b385a87

[ "Apache-2.0" ]

2

2020-09-12T10:10:07.000Z

2021-09-15T11:58:37.000Z

import sys, os import src.services.processing.CPrediction #sys.path.append(os.path.dirname(__file__)) sys.path.append(__file__) sys.path.append(CPrediction)

31.2

43

0.820513

23

156

5.217391

0.478261

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0

0.044872

156

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0.805369

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true

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1

0

1

0

null

0

1

0

1

0

6

1b66d75799d313f00a6209a94040c337396b29d6

32

py

Python

03 Time Series Analysis/test.py

BIll666YOYOYO/123

7eea2c27717ad2ccfcd33ca65c1ae5eadde741b9

[ "Apache-2.0" ]

242

2021-04-24T15:53:25.000Z

2022-03-31T10:51:18.000Z

03 Time Series Analysis/test.py

zsl24/Time-Series-Analysis-Tutorial

fb9374baa7101748e2cf05fdb9911e4471d5196e

[ "Apache-2.0" ]

null

03 Time Series Analysis/test.py

zsl24/Time-Series-Analysis-Tutorial

fb9374baa7101748e2cf05fdb9911e4471d5196e

[ "Apache-2.0" ]

86

2021-04-25T02:54:56.000Z

2022-03-29T02:56:50.000Z

print("This is a test.py file.")

32

0.6875

7

32

3.142857

1

0

0.125

32

1

32

0.785714

0

0.69697

0

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0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

1b67f1537c7b11a87ff530f232c62367cd241310

1,072

py

Python

Python_Basics/05_Nested_Conditional_Statements_Exercise/04_Summer_outfit.py

Dochko0/Python

e9612c4e842cfd3d9a733526cc7485765ef2238f

[ "MIT" ]

null

Python_Basics/05_Nested_Conditional_Statements_Exercise/04_Summer_outfit.py

Dochko0/Python

e9612c4e842cfd3d9a733526cc7485765ef2238f

[ "MIT" ]

null

Python_Basics/05_Nested_Conditional_Statements_Exercise/04_Summer_outfit.py

Dochko0/Python

e9612c4e842cfd3d9a733526cc7485765ef2238f

[ "MIT" ]

null

temperature = int(input()) time = input().lower() if 10<=temperature<=18: if time == "morning": print(f'It\'s {temperature} degrees, get your Sweatshirt and Sneakers.') elif time == 'afternoon': print(f'It\'s {temperature} degrees, get your Shirt and Moccasins.') elif time == 'evening': print(f'It\'s {temperature} degrees, get your Shirt and Moccasins.') elif 18<temperature<24: if time == "morning": print(f'It\'s {temperature} degrees, get your Shirt and Moccasins.') elif time == 'afternoon': print(f'It\'s {temperature} degrees, get your T-Shirt and Sandals.') elif time == 'evening': print(f'It\'s {temperature} degrees, get your Shirt and Moccasins.') elif 25<=temperature: if time == "morning": print(f'It\'s {temperature} degrees, get your T-Shirt and Sandals.') elif time == 'afternoon': print(f'It\'s {temperature} degrees, get your Swim Suit and Barefoot.') elif time == 'evening': print(f'It\'s {temperature} degrees, get your Shirt and Moccasins.')

44.666667

80

0.63806

146

1,072

4.684932

0.212329

0.078947

0.105263

0.118421

0.827485

0

0.011862

0.213619

1,072

24

81

44.666667

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0.391304

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null

0

1

0

null

0

6

1ba464f1e4cbeb15b89882de8eaccbae9175371b

119

py

Python

242-valid-anagram/242-valid-anagram.py

Atri10/Leet-code---Atri_Patel

49fc59b9147a44ab04a66128fbb2ef259b5f7b7c

[ "MIT" ]

1

2021-10-10T20:21:18.000Z

242-valid-anagram/242-valid-anagram.py

Atri10/Leet-code---Atri_Patel

49fc59b9147a44ab04a66128fbb2ef259b5f7b7c

[ "MIT" ]

null

242-valid-anagram/242-valid-anagram.py

Atri10/Leet-code---Atri_Patel

49fc59b9147a44ab04a66128fbb2ef259b5f7b7c

[ "MIT" ]

null

class Solution: def isAnagram(self, s: str, t: str) -> bool:return collections.Counter(s) == collections.Counter(t)

59.5

103

0.714286

17

119

5

0.705882

0.423529

0

0.134454

119

2

103

59.5

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false

0

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null

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1

0

null

0

1

0

1

0

6

1bd2b9dc3f0c3f01eb1358a4db8c812e63696a59

24,891

py

Python

autodiff/reverse.py

sandrawing/cs107-FinalProject

f8f884d22f55c3b47d9524621bdcab41d69b2690

[ "MIT" ]

null

autodiff/reverse.py

sandrawing/cs107-FinalProject

f8f884d22f55c3b47d9524621bdcab41d69b2690

[ "MIT" ]

null

autodiff/reverse.py

sandrawing/cs107-FinalProject

f8f884d22f55c3b47d9524621bdcab41d69b2690

[ "MIT" ]

null

import numpy as np class Reverse(): def __init__(self, val): """ Initializes Reverse object with a value that was passed in Inputs: Scalar or list or numpy array Returns: A Reverse object initialized with the value that is passed in Example: >>> x = Reverse([5,6]) >>> x.val array([5, 6]) """ if isinstance(val, (int, float)): self.val = np.array([val]) elif isinstance(val, list): self.val = np.array(val) elif isinstance(val, np.ndarray): self.val = val else: raise TypeError("Please enter a valid type (float, int, list or np.ndarray).") self.children = [] self.gradient_value = None def reset_gradient(self): """ Sets the gradient of all its children to None Inputs: None Returns: None Example: >>> w = Reverse([1,4]) >>> x = Reverse([2,5]) >>> y = Reverse([3,6]) >>> z = (2*x-w**2)/(x+y**w) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.28 , 0.00154082]) >>> x.reset_gradient() >>> grads = [] >>> for _, child in x.children: ... grads.append(child.gradient_value) ... for _, child2 in child.children: ... grads.append(child2.gradient_value) ... >>> print(grads) [None, None, None, None] """ self.gradient_value = None for _, child in self.children: child.reset_gradient() def get_gradient(self): """ Calculates the gradient with respect to the Reverse instance Inputs: None Returns: The gradient value (float) Example: >>> w = Reverse([1,4]) >>> x = Reverse([2,5]) >>> y = Reverse([3,6]) >>> z = (2*x-w**2)/(x+y**w) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.28 , 0.00154082]) """ if self.gradient_value is None: self.gradient_value = sum( weight * child.get_gradient() for weight, child in self.children ) return self.gradient_value def __add__(self, other): """ Overloads the addition operation Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the addition operation perform Example: >>> x = Reverse([5,6]) >>> y = Reverse([1,2]) >>> z = x + y >>> z.gradient_value = 1 >>> x.get_gradient() array([1., 1.]) >>> >>> x = Reverse([5,6]) >>> z = x + 3 >>> z.gradient_value = 1 >>> x.get_gradient() array([1., 1.]) """ if isinstance(other, int) or isinstance(other, float): other = Reverse([other]*len(self.val)) z = Reverse(self.val + other.val) one_array = np.ones(self.val.shape) self.children.append((one_array, z)) # weight = dz/dself = 1 other.children.append((one_array, z)) # weight = dz/dother = 1 return z def __radd__(self, other): """ Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the addition operation performed between the argument that was passed in and the Reverse object Example: >>> x = Reverse([5,6]) >>> z = 1 + x >>> z.gradient_value = 1 >>> x.get_gradient() array([1., 1.]) """ return self + other def __sub__(self, other): """ Overloads the subtraction operation Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the subtraction operation performed between the Reverse object and the argument that was passed in Example: >>> x = Reverse([5,6]) >>> y = Reverse([1,2]) >>> z = x - y >>> z.gradient_value = 1 >>> x.get_gradient() array([1., 1.]) >>> >>> x = Reverse([5,6]) >>> z = x - 3 >>> z.gradient_value = 1 >>> x.get_gradient() array([1., 1.]) """ if isinstance(other, int) or isinstance(other, float): other = Reverse([other]*len(self.val)) z = Reverse(self.val - other.val) self.children.append((np.ones(self.val.shape), z)) # weight = dz/dself = 1 other.children.append((-np.ones(self.val.shape), z)) # weight = dz/dother = -1 return z def __rsub__(self, other): """ Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the subtraction operation performed between the Reverse object and the argument that was passed in Example: >>> x = Reverse([5,6]) >>> z = 2 - x >>> z.gradient_value = 1 >>> x.get_gradient() array([-1., -1.]) """ if isinstance(other, int) or isinstance(other, float): other = Reverse([other]*len(self.val)) z = Reverse( -self.val + other.val) self.children.append((-np.ones(self.val.shape), z)) # weight = dz/dself = 1 other.children.append((np.ones(self.val.shape), z)) # weight = dz/dother = -1 return z def __mul__(self, other): """ Overloads the multiplication operation Inputs: Scalar or Reverse Instance Returns: A new AutoDiff object which is the result of the multiplication operation performed between the AutoDiff object and the argument that was passed in Example: >>> x = Reverse([5,6]) >>> y = Reverse([1,2]) >>> z = x * y >>> z.gradient_value = 1 >>> x.get_gradient() array([1, 2]) >>> >>> x = Reverse([5,6]) >>> z = x * 3 >>> z.gradient_value = 1 >>> x.get_gradient() array([3, 3]) """ if isinstance(other, int) or isinstance(other, float): other = Reverse([other]*len(self.val)) z = Reverse(self.val * other.val) self.children.append((other.val, z)) # weight = dz/dself = other.value other.children.append((self.val, z)) # weight = dz/dother = self.value return z def __rmul__(self, other): """ Inputs: Scalar or AutoDiff Instance Returns: A new AutoDiff object which is the result of the multiplication operation performed between the AutoDiff object and the argument that was passed in Example: >>> x = Reverse([5,6]) >>> z = 2 * x >>> z.gradient_value = 1 >>> x.get_gradient() array([2, 2]) """ return self * other def __truediv__(self, other): """ Overloads the division operation Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the Reverse object divided by the argument that was passed in Example: >>> x = Reverse([5,6]) >>> y = Reverse([1,2]) >>> z = x / y >>> z.gradient_value = 1 >>> x.get_gradient() array([1. , 0.5]) >>> >>> x = Reverse([5,6]) >>> z = x / 3 >>> z.gradient_value = 1 >>> x.get_gradient() array([0.33333333, 0.33333333]) """ return self * (other ** (-1)) def __rtruediv__(self, other): """ Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the argument that was passed in divided by the Reverse object Example: >>> x = Reverse([5,6]) >>> z = 2 / x >>> z.gradient_value = 1 >>> x.get_gradient() array([-0.08 , -0.05555556]) """ return other*(self**(-1)) def __pow__(self, other): """ Overloads the power operation Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the Reverse object being raised to the power of the argument that was passed in Example: >>> x = Reverse([5,6]) >>> y = Reverse([1,2]) >>> z = x ** y >>> z.gradient_value = 1 >>> x.get_gradient() array([ 1., 12.]) >>> >>> x = Reverse([5,6]) >>> z = x ** 3 >>> z.gradient_value = 1 >>> x.get_gradient() array([ 75., 108.]) """ if isinstance(other, Reverse): if len(other.val) == 1: other_val = other.val*np.ones(self.val.shape) elif len(other.val) != len(self.val): raise ValueError("You must have two vectors of the same length to use power on both.") else: other_val = other.val[:] val = np.array([float(v) ** o for v, o in zip(self.val, other_val)]) z = Reverse(val) temp_der = np.array([float(v) ** (o - 1) for v, o in zip(self.val, other_val)]) self.children.append((other_val * temp_der, z)) # weight = dz/dself other.children.append((val*np.log(self.val), z)) return z elif isinstance(other, (float, int)): val = np.array([float(v) ** other for v in self.val]) z = Reverse(val) temp_der = np.array([float(v) ** (other - 1) for v in self.val]) self.children.append((other * temp_der, z)) # self.children.append((other*(self.val**(other-1)), z)) return z else: raise TypeError("Please us power with another Reverse object, int or float.") def __rpow__(self, other): """ Inputs: Scalar or Reverse Instance Returns: A new Reverse object which is the result of the argument that was passed in being raised to the power of the Reverse object Example: >>> x = Reverse([5,6]) >>> z = 2 ** x >>> z.gradient_value = 1 >>> x.get_gradient() array([22.18070978, 44.36141956]) """ if isinstance(other, Reverse): if len(other.val) == 1: other_val = other.val*np.ones(self.val.shape) elif len(other.val) != len(self.val): raise ValueError("You must have two vectors of the same length to use power on both.") else: other_val = other.val[:] val = np.array([float(o) ** v for v, o in zip(self.val, other_val)]) z = Reverse(val) temp_der = np.array([(v*(float(o) ** (v-1))) for v, o in zip(self.val, other_val)]) other.children.append((temp_der, z)) self.children.append((val*np.log(other.val), z)) return z elif isinstance(other, (float, int)): val = np.array([float(other) ** v for v in self.val]) z = Reverse(val) self.children.append((val*np.log(other), z)) return z else: raise TypeError("Please us power with another Reverse object, int or float.") def __neg__(self): """ Inputs: None Returns: A new Reverse object which has the signs of the value and derivative reversed Example: >>> x = Reverse([5,6]) >>> z = -x >>> z.gradient_value = 1 >>> x.get_gradient() array([-1, -1]) """ return self.__mul__(-1) def __pos__(self): """ Inputs: None Returns: The Reverse instance itself Example: >>> x = Reverse([5,6]) >>> z = +x >>> z.gradient_value = 1 >>> x.get_gradient() 1 """ return self def sin(self): """ Inputs: None Returns: A new Reverse object with the sine computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.sin(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.28366219, 0.96017029]) """ z = Reverse(np.sin(self.val)) self.children.append((np.cos(self.val), z)) # z = sin(x) => dz/dx = cos(x) return z def cos(self): """ Inputs: None Returns: A new Reverse object with the cosine computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.cos(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.95892427, 0.2794155 ]) """ z = Reverse(np.cos(self.val)) self.children.append((-np.sin(self.val), z)) return z def tan(self): """ Inputs: None Returns: A new Reverse object with the tangent computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.tan(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([12.42788171, 1.0846846 ]) """ z = Reverse(np.tan(self.val)) self.children.append((1 / (np.cos(self.val) ** 2), z)) return z def sinh(self): """ Inputs: None Returns: A new Reverse object with the hyperbolic sine computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.sinh(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([ 74.20994852, 201.71563612]) """ z = Reverse(np.sinh(self.val)) self.children.append((np.cosh(self.val), z)) return z def cosh(self): """ Inputs: None Returns: A new Reverse object with the hyperbolic cosine computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.cosh(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([ 74.20321058, 201.71315737]) """ z = Reverse(np.cosh(self.val)) self.children.append((np.sinh(self.val), z)) return z def tanh(self): """ Inputs: None Returns: A new Reverse object with the hyperbolic tangent computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.tanh(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([1.81583231e-04, 2.45765474e-05]) """ z = Reverse(np.tanh(self.val)) self.children.append((1 / (np.cosh(self.val) ** 2), z)) return z def exp(self): """ Inputs: None Returns: A new Reverse object with the natural exponential computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.exp(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([148.4131591 , 403.42879349]) """ z = Reverse(np.exp(self.val)) self.children.append((np.exp(self.val), z)) return z def exp_base(self, base): """ Inputs: scalar Returns: A new Reverse object with the exponential (using a specified base) computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.exp_base(x, 2) >>> z.gradient_value = 1 >>> x.get_gradient() array([22.18070978, 44.36141956]) """ if isinstance(base, (int, float)): return self.__rpow__(base) else: raise TypeError("Please enter an int or float for base.") #z = Reverse(base ** self.val) #self.children.append(((base ** self.val) * np.log(base), z)) #return z def arcsin(self): """ Inputs: None Returns: A new Reverse object with the inverse sine computation done on the value and derivative Example: >>> x = Reverse([0.5,0.6]) >>> z = Reverse.arcsin(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([1.15470054, 1.25 ]) """ z = Reverse(np.arcsin(self.val)) self.children.append((1 / (1 - (self.val**2))**0.5, z)) return z def arccos(self): """ Inputs: None Returns: A new Reverse object with the inverse cosine computation done on the value and derivative Example: >>> x = Reverse([0.5,0.6]) >>> z = Reverse.arccos(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([-1.15470054, -1.25 ]) """ z = Reverse(np.arccos(self.val)) self.children.append((-1 / (1 - (self.val**2))**0.5, z)) return z def arctan(self): """ Inputs: None Returns: A new Reverse object with the inverse cosine computation done on the value and derivative Example: >>> x = Reverse([0.5,0.6]) >>> z = Reverse.arctan(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.8 , 0.73529412]) """ z = Reverse(np.arctan(self.val)) self.children.append((1 / (1 + (self.val**2)), z)) return z def logistic(self): """ Inputs: None Returns: A new Reverse object calculated with logistic function Example: >>> x = Reverse([5,6]) >>> z = Reverse.logistic(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.00664806, 0.00246651]) """ z = Reverse(1/(1+np.exp(-self.val))) self.children.append((np.exp(-self.val)/((1+np.exp(-self.val))**2), z)) # Need to make sure this is correct return z def sqrt(self): """ Inputs: None Returns: A new Reverse object with the square root computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.sqrt(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.2236068 , 0.20412415]) """ z = Reverse(self.val ** (1 / 2)) self.children.append(((1 / 2) * (self.val ** (- 1 / 2)), z)) return z def ln(self): """ Inputs: None Returns: A new Reverse object with the natural log computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.ln(x) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.2 , 0.16666667]) """ if (np.all(self.val > 0)) : z = Reverse(np.log(self.val)) self.children.append(( 1 / self.val , z)) return z else: raise ValueError("Reverse.ln only takes in positive numbers as arguments.") def log(self, base): """ Inputs: scalar Returns: A new Reverse object with the log (using a specified base) computation done on the value and derivative Example: >>> x = Reverse([5,6]) >>> z = Reverse.log(x, 2) >>> z.gradient_value = 1 >>> x.get_gradient() array([0.28853901, 0.24044917]) """ if (np.all(self.val > 0) and base > 0): z = Reverse(np.log(self.val) / np.log(base)) self.children.append((1 / (self.val * np.log(base)), z)) return z else: raise ValueError("Reverse.log only takes in positive numbers as arguments.") def __eq__(self, other): """ Overloads the equal comparision operator (==) Inputs: Reverse Instance Returns: True if self and other Reverse instance have the same value; False if not Example: >>> v = Reverse([3,4]) >>> w = Reverse([4,6]) >>> x = Reverse([5,6]) >>> y = Reverse([5,6]) >>> v == w array([False, False]) >>> w == x array([False, True]) >>> x == y array([ True, True]) """ if isinstance(other, (int, float)): return np.equal(self.val, other) elif isinstance(other, Reverse): return np.equal(self.val, other.val) else: raise TypeError("Please only compare Reverse object with another Reverse object or int or float.") def __ne__(self, other): """ Overloads the not equal comparision operator (!=) Inputs: Reverse Instance Returns: False if self and other Reverse instance have the same value; True if not Example: >>> v = Reverse([3,4]) >>> w = Reverse([4,6]) >>> x = Reverse([5,6]) >>> y = Reverse([5,6]) >>> v != w array([ True, True]) >>> w != x array([ True, False]) >>> x != y array([False, False]) """ if isinstance(other, (int, float)): return not np.equal(self.val, other) elif isinstance(other, Reverse): return self.val != other.val else: raise TypeError("Please only compare Reverse object with another Reverse object or int or float.") def __lt__(self, other): """ Compares the value of the Reverse instance with the input Inputs: Scalar or Reverse Instance Returns: True if self.value is less than other.value or if self.value is less than other; False if not Example: >>> v = Reverse([3,4]) >>> w = Reverse([4,6]) >>> x = Reverse([5,6]) >>> y = Reverse([5,6]) >>> v < w array([ True, True]) >>> w < x array([ True, False]) >>> x < y array([False, False]) """ if isinstance(other, (int, float)): return np.less(self.val, other) elif isinstance(other, Reverse): return np.less(self.val, other.val) else: raise TypeError("Please only compare Reverse object with another Reverse object or int or float.") def __le__(self, other): """ Compares the value of the Reverse instance with the input Inputs: Scalar or Reverse Instance Returns: True if self.value is less than or equal to other.value or if self.value is less than or equal to other; False if not Example: >>> v = Reverse([3,4]) >>> w = Reverse([4,6]) >>> x = Reverse([5,6]) >>> y = Reverse([5,6]) >>> w <= v array([False, False]) >>> x <= w array([False, True]) >>> y <= x array([ True, True]) """ if isinstance(other, (int, float)): return np.less_equal(self.val, other) elif isinstance(other, Reverse): return np.less_equal(self.val, other.val) else: raise TypeError("Please only compare Reverse object with another Reverse object or int or float.") def __gt__(self, other): """ Compares the value of the Reverse instance with the input Inputs: Scalar or Reverse Instance Returns: True if self.value is greater than other.value or if self.value is greater than other; False if not Example: >>> v = Reverse([3,4]) >>> w = Reverse([4,6]) >>> x = Reverse([5,6]) >>> y = Reverse([5,6]) >>> w > v array([ True, True]) >>> x > w array([ True, False]) >>> y > x array([False, False]) """ if isinstance(other, (int, float)): return np.greater(self.val, other) elif isinstance(other, Reverse): return np.greater(self.val, other.val) else: raise TypeError("Please only compare Reverse object with another Reverse object or int or float.") def __ge__(self, other): """ Compares the value of the Reverse instance with the input Inputs: Scalar or Reverse Instance Returns: True if self.value is greater than or equal to other.value or if self.value is greater than or equal to other; False if not Example: >>> v = Reverse([3,4]) >>> w = Reverse([4,6]) >>> x = Reverse([5,6]) >>> y = Reverse([5,6]) >>> v >= w array([False, False]) >>> w >= x array([False, True]) >>> x >= y array([ True, True]) """ if isinstance(other, (int, float)): return np.greater_equal(self.val, other) elif isinstance(other, Reverse): return np.greater_equal(self.val, other.val) else: raise TypeError("Please only compare Reverse object with another Reverse object or int or float.")

31.870679

115

0.516894

3,105

24,891

4.082126

0.077617

0.041972

0.029822

0.028402

0.821223

0.798974

0.774043

0.734675

0.704063

0.686154

0

0.03735

0.348158

24,891

780

116

31.911538

0.743852

0.464184

0

0.388889

0

0.09773

0

1

0.166667

false

0

0.00463

0

0.37037

0

null

0

1

0

null

0

6

59ef10c1e8a7ae7230bc83156110a832123a6a06

25

py

Python

ctaplot/gammaboard/__init__.py

vuillaut/CTAPLOT

3a7757f6e2487806ca87e41fcd123ccfbd4b964c

[ "MIT" ]

5

2018-07-03T16:13:29.000Z

2021-02-22T13:59:57.000Z

ctaplot/gammaboard/__init__.py

vuillaut/CTAPLOT

3a7757f6e2487806ca87e41fcd123ccfbd4b964c

[ "MIT" ]

39

2020-03-10T16:52:45.000Z

2022-01-26T14:13:40.000Z

ctaplot/gammaboard/__init__.py

vuillaut/CTAPLOT

3a7757f6e2487806ca87e41fcd123ccfbd4b964c

[ "MIT" ]

6

2019-11-22T10:01:23.000Z

2021-09-20T12:32:34.000Z

from .gammaboard import *

25

0.8

3

25

6.666667

1

0

0.12

25

1

25

0.909091

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

9429c67430b1baa12991cd707c77b4e879e47c1f

29,908

py

Python

amparex/api/articles_api.py

Inch4Tk/amparex_python_api

f372c15a1e67293329bdd8bee8ad66624ed1341f

[ "Apache-2.0" ]

null

amparex/api/articles_api.py

Inch4Tk/amparex_python_api

f372c15a1e67293329bdd8bee8ad66624ed1341f

[ "Apache-2.0" ]

null

amparex/api/articles_api.py

Inch4Tk/amparex_python_api

f372c15a1e67293329bdd8bee8ad66624ed1341f

[ "Apache-2.0" ]

null

""" AMPAREX Rest API Documentation This is the description of the AMPAREX Rest API. All REST calls plus the corresponding data model are described in this documentation. Direct calls to the server are possible over this page. Following steps are needed to use the API: 1. Get the alias identifier of your login account from AMPAREX Software (Branch office administration) -> Service accounts -> your service account -> copy alias token) 2. Please use the login URL /alias/{alias}/login under section \"Login\" below with your credentials to get a valid bearer token. 3. Copy bearer token from login response 3. Then click \"Authorize\" on the top of this page 4. Insert into the field \"value\": \"Bearer {Your Bearer token}\" (without {}) for example \"Bearer 334d34d3dgh5tz5h5h\" 4. Click Authorize 5. Bearer token will be automatically used in the header for every following API call. 6. Now you are ready to use the API See also [documentation](https://manual.amparex.com/display/HAN/AMPAREX+API) for help Documentation of all the used fields and objects is at the bottom of this page called \"Models\" # noqa: E501 The version of the OpenAPI document: 1.0.0 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from amparex.api_client import ApiClient, Endpoint as _Endpoint from amparex.model_utils import ( # noqa: F401 check_allowed_values, check_validations, date, datetime, file_type, none_type, validate_and_convert_types ) from amparex.model.article_detail import ArticleDetail from amparex.model.article_search_query import ArticleSearchQuery from amparex.model.list_result_wrapper_article_detail import ListResultWrapperArticleDetail from amparex.model.list_result_wrapper_article_overview import ListResultWrapperArticleOverview from amparex.model.list_result_wrapper_sales_price import ListResultWrapperSalesPrice from amparex.model.sales_price_search_query import SalesPriceSearchQuery class ArticlesApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client self.get_article_image_using_get_endpoint = _Endpoint( settings={ 'response_type': (str,), 'auth': [ 'security_token' ], 'endpoint_path': '/alias/{alias}/protected/articles/{articleid}/images/{imageid}', 'operation_id': 'get_article_image_using_get', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'alias', 'articleid', 'imageid', 'image_width', ], 'required': [ 'alias', 'articleid', 'imageid', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'alias': (str,), 'articleid': (str,), 'imageid': (str,), 'image_width': (int,), }, 'attribute_map': { 'alias': 'alias', 'articleid': 'articleid', 'imageid': 'imageid', 'image_width': 'imageWidth', }, 'location_map': { 'alias': 'path', 'articleid': 'path', 'imageid': 'path', 'image_width': 'query', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/octet-stream', 'application/json' ], 'content_type': [], }, api_client=api_client ) self.get_article_order_by_fields_using_get_endpoint = _Endpoint( settings={ 'response_type': ([str],), 'auth': [ 'security_token' ], 'endpoint_path': '/alias/{alias}/protected/articles/orderbyfields', 'operation_id': 'get_article_order_by_fields_using_get', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'alias', ], 'required': [ 'alias', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'alias': (str,), }, 'attribute_map': { 'alias': 'alias', }, 'location_map': { 'alias': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.get_article_using_get_endpoint = _Endpoint( settings={ 'response_type': (ArticleDetail,), 'auth': [ 'security_token' ], 'endpoint_path': '/alias/{alias}/protected/articles/{id}', 'operation_id': 'get_article_using_get', 'http_method': 'GET', 'servers': None, }, params_map={ 'all': [ 'alias', 'id', ], 'required': [ 'alias', 'id', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'alias': (str,), 'id': (str,), }, 'attribute_map': { 'alias': 'alias', 'id': 'id', }, 'location_map': { 'alias': 'path', 'id': 'path', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [], }, api_client=api_client ) self.search_articles_using_post_endpoint = _Endpoint( settings={ 'response_type': (ListResultWrapperArticleOverview,), 'auth': [ 'security_token' ], 'endpoint_path': '/alias/{alias}/protected/articles/search', 'operation_id': 'search_articles_using_post', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'alias', 'article_search_query', ], 'required': [ 'alias', 'article_search_query', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'alias': (str,), 'article_search_query': (ArticleSearchQuery,), }, 'attribute_map': { 'alias': 'alias', }, 'location_map': { 'alias': 'path', 'article_search_query': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) self.search_detailed_articles_using_post_endpoint = _Endpoint( settings={ 'response_type': (ListResultWrapperArticleDetail,), 'auth': [ 'security_token' ], 'endpoint_path': '/alias/{alias}/protected/articles/detailedsearch', 'operation_id': 'search_detailed_articles_using_post', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'alias', 'article_search_query', ], 'required': [ 'alias', 'article_search_query', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'alias': (str,), 'article_search_query': (ArticleSearchQuery,), }, 'attribute_map': { 'alias': 'alias', }, 'location_map': { 'alias': 'path', 'article_search_query': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) self.search_sales_prices_using_post_endpoint = _Endpoint( settings={ 'response_type': (ListResultWrapperSalesPrice,), 'auth': [ 'security_token' ], 'endpoint_path': '/alias/{alias}/protected/articles/salesprices/search', 'operation_id': 'search_sales_prices_using_post', 'http_method': 'POST', 'servers': None, }, params_map={ 'all': [ 'alias', 'search_query', ], 'required': [ 'alias', 'search_query', ], 'nullable': [ ], 'enum': [ ], 'validation': [ ] }, root_map={ 'validations': { }, 'allowed_values': { }, 'openapi_types': { 'alias': (str,), 'search_query': (SalesPriceSearchQuery,), }, 'attribute_map': { 'alias': 'alias', }, 'location_map': { 'alias': 'path', 'search_query': 'body', }, 'collection_format_map': { } }, headers_map={ 'accept': [ 'application/json' ], 'content_type': [ 'application/json' ] }, api_client=api_client ) def get_article_image_using_get( self, alias, articleid, imageid, **kwargs ): """Get image of article as blob # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_article_image_using_get(alias, articleid, imageid, async_req=True) >>> result = thread.get() Args: alias (str): alias articleid (str): articleid imageid (str): imageid Keyword Args: image_width (int): imageWidth. [optional] _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: str If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['alias'] = \ alias kwargs['articleid'] = \ articleid kwargs['imageid'] = \ imageid return self.get_article_image_using_get_endpoint.call_with_http_info(**kwargs) def get_article_order_by_fields_using_get( self, alias, **kwargs ): """Get possible fields for orderby of article fields # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_article_order_by_fields_using_get(alias, async_req=True) >>> result = thread.get() Args: alias (str): alias Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: [str] If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['alias'] = \ alias return self.get_article_order_by_fields_using_get_endpoint.call_with_http_info(**kwargs) def get_article_using_get( self, alias, id, **kwargs ): """Get one specific article detail by id # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_article_using_get(alias, id, async_req=True) >>> result = thread.get() Args: alias (str): alias id (str): id Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ArticleDetail If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['alias'] = \ alias kwargs['id'] = \ id return self.get_article_using_get_endpoint.call_with_http_info(**kwargs) def search_articles_using_post( self, alias, article_search_query, **kwargs ): """Get a list of articles # noqa: E501 Get a list of articles by a search query, paging is used, specify limit and page; Model Type: ArticleOverview is returned # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.search_articles_using_post(alias, article_search_query, async_req=True) >>> result = thread.get() Args: alias (str): alias article_search_query (ArticleSearchQuery): articleSearchQuery Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ListResultWrapperArticleOverview If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['alias'] = \ alias kwargs['article_search_query'] = \ article_search_query return self.search_articles_using_post_endpoint.call_with_http_info(**kwargs) def search_detailed_articles_using_post( self, alias, article_search_query, **kwargs ): """Get a list of detailed articles # noqa: E501 Get a list of detailed articles by a search query, contains more details than /search including properties & images, paging is used, specify limit and page; Model Type: ArticleDetail is returned # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.search_detailed_articles_using_post(alias, article_search_query, async_req=True) >>> result = thread.get() Args: alias (str): alias article_search_query (ArticleSearchQuery): articleSearchQuery Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ListResultWrapperArticleDetail If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['alias'] = \ alias kwargs['article_search_query'] = \ article_search_query return self.search_detailed_articles_using_post_endpoint.call_with_http_info(**kwargs) def search_sales_prices_using_post( self, alias, search_query, **kwargs ): """Get a list of article sales prices # noqa: E501 Get a list of sales prices by a search query, paging is used, specify limit and page; Model Type: SalesPrice is returned # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.search_sales_prices_using_post(alias, search_query, async_req=True) >>> result = thread.get() Args: alias (str): alias search_query (SalesPriceSearchQuery): searchQuery Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ListResultWrapperSalesPrice If the method is called asynchronously, returns the request thread. """ kwargs['async_req'] = kwargs.get( 'async_req', False ) kwargs['_return_http_data_only'] = kwargs.get( '_return_http_data_only', True ) kwargs['_preload_content'] = kwargs.get( '_preload_content', True ) kwargs['_request_timeout'] = kwargs.get( '_request_timeout', None ) kwargs['_check_input_type'] = kwargs.get( '_check_input_type', True ) kwargs['_check_return_type'] = kwargs.get( '_check_return_type', True ) kwargs['_host_index'] = kwargs.get('_host_index') kwargs['alias'] = \ alias kwargs['search_query'] = \ search_query return self.search_sales_prices_using_post_endpoint.call_with_http_info(**kwargs)

36.787208

1,241

0.503979

2,787

29,908

5.170075

0.101902

0.029981

0.021653

0.022486

0.7995

0.783538

0.776112

0.743979

0.727948

0.704004

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0.003685

0.410191

29,908

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1,242

36.832512

0.813152

0.363281

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0.050454

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0.012635

false

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null

0

1

0

1

0

null

0

6

9463deadcfa17ccf35f107205845360501c66aab

69

py

Python

biasd/src/__init__.py

MeganArms/biasd

b96c1e45d075ca54d2119ff126ae311166b2c03b

[ "MIT" ]

null

biasd/src/__init__.py

MeganArms/biasd

b96c1e45d075ca54d2119ff126ae311166b2c03b

[ "MIT" ]

null

biasd/src/__init__.py

MeganArms/biasd

b96c1e45d075ca54d2119ff126ae311166b2c03b

[ "MIT" ]

2

2018-10-15T17:11:10.000Z

2020-08-03T01:10:12.000Z

from numba_biasd_likelihood import log_likelihood,sum_log_likelihood

34.5

68

0.927536

10

69

5.9

0.7

0.440678

0

0.057971

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69

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1

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0

null

0

1

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1

0

1

0

6

84bde032e3ec55091fc429fe45d7a69884c795d1

7,438

py

Python

tests/test_djangocms_alias_integration.py

Aiky30/djangocms-content-expiry

da7d348bcdafbf1a9862e4cc69a8363b3305a31a

[ "BSD-3-Clause" ]

null

tests/test_djangocms_alias_integration.py

Aiky30/djangocms-content-expiry

da7d348bcdafbf1a9862e4cc69a8363b3305a31a

[ "BSD-3-Clause" ]

4

2021-09-27T10:15:13.000Z

2021-11-23T17:18:04.000Z

tests/test_djangocms_alias_integration.py

Aiky30/djangocms-content-expiry

da7d348bcdafbf1a9862e4cc69a8363b3305a31a

[ "BSD-3-Clause" ]

4

2021-09-06T20:13:45.000Z

2021-10-02T15:00:58.000Z

import datetime from django.contrib.sites.models import Site from django.contrib.sites.shortcuts import get_current_site from django.test import override_settings from cms.test_utils.testcases import CMSTestCase from djangocms_alias.models import Alias as AliasModel, AliasContent, Category from djangocms_versioning.models import Version from djangocms_content_expiry.cms_config import _get_excluded_alias_site_list from djangocms_content_expiry.models import ContentExpiry class ContentExpirySiteAliasHelperTestCase(CMSTestCase): @classmethod def setUpTestData(cls): # Site 1 cls.site_1 = Site.objects.get(id=1) # Site 2 cls.site_2 = Site(id=2, domain='example-2.com', name='example-2.com') cls.site_2.save() cls.category = Category.objects.create(name='site test category') def setUp(self): self.superuser = self.get_superuser() Site.objects.clear_cache() # Record that is expired by 1 day language = "en" # Create contents unbound to a site alias_1 = AliasModel.objects.create( category=self.category, ) self.alias_content_1 = AliasContent.objects.create( alias=alias_1, name="no site alias 1", language=language, ) self.alias_1_version = Version.objects.create(content=self.alias_content_1, created_by=self.superuser) self.alias_1_version.publish(self.superuser) # Create contents on site 1 alias_2 = AliasModel.objects.create( category=self.category, site=self.site_1, ) self.alias_content_2 = AliasContent.objects.create( alias=alias_2, name="site 1 alias 1", language=language, ) self.alias_2_version = Version.objects.create(content=self.alias_content_2, created_by=self.superuser) self.alias_2_version.publish(self.superuser) # Create contents on site 2 alias_3 = AliasModel.objects.create( category=self.category, site=self.site_2, ) self.alias_content_3 = AliasContent.objects.create( alias=alias_3, name="site 1 alias 1", language=language, ) self.alias_3_version = Version.objects.create(content=self.alias_content_3, created_by=self.superuser) self.alias_3_version.publish(self.superuser) def tearDown(self): Site.objects.clear_cache() def test_helper_alias_exclusion_list_current_site(self): """ The list of Alias objects must be filtered by the default / current site """ alias_exclusion_list = _get_excluded_alias_site_list(self.site_1) self.assertNotIn(self.alias_content_1.pk, alias_exclusion_list) self.assertNotIn(self.alias_content_2.pk, alias_exclusion_list) self.assertIn(self.alias_content_3.pk, alias_exclusion_list) @override_settings(SITE_ID=2) def test_helper_alias_exclusion_list_other_site(self): """ The list of Alias objects must be filtered by a different site """ alias_exclusion_list = _get_excluded_alias_site_list(self.site_2) self.assertNotIn(self.alias_content_1.pk, alias_exclusion_list) self.assertIn(self.alias_content_2.pk, alias_exclusion_list) self.assertNotIn(self.alias_content_3.pk, alias_exclusion_list) class ContentExpiryChangelistAliasContentSiteTestCase(CMSTestCase): @classmethod def setUpTestData(cls): # Site 1 cls.site_1 = Site.objects.get(id=1) # Site 2 cls.site_2 = Site(id=2, domain='example-2.com', name='example-2.com') cls.site_2.save() cls.category = Category.objects.create(name='site test category') def setUp(self): self.superuser = self.get_superuser() Site.objects.clear_cache() # Record that is expired by 1 day from_date = datetime.datetime.now() expire_at = from_date + datetime.timedelta(days=10) language = "en" # Create contents unbound to a site alias_1 = AliasModel.objects.create( category=self.category, ) self.alias_content_1 = AliasContent.objects.create( alias=alias_1, name="no site alias 1", language=language, ) self.alias_1_version = Version.objects.create(content=self.alias_content_1, created_by=self.superuser) # Set the expiry date closer than the default self.alias_1_version.contentexpiry.expires = expire_at self.alias_1_version.contentexpiry.save() self.alias_1_version.publish(self.superuser) # Create contents on site 1 alias_2 = AliasModel.objects.create( category=self.category, site=self.site_1, ) self.alias_content_2 = AliasContent.objects.create( alias=alias_2, name="site 1 alias 1", language=language, ) self.alias_2_version = Version.objects.create(content=self.alias_content_2, created_by=self.superuser) # Set the expiry date closer than the default self.alias_2_version.contentexpiry.expires = expire_at self.alias_2_version.contentexpiry.save() self.alias_2_version.publish(self.superuser) # Create contents on site 2 alias_3 = AliasModel.objects.create( category=self.category, site=self.site_2, ) self.alias_content_3 = AliasContent.objects.create( alias=alias_3, name="site 1 alias 1", language=language, ) self.alias_3_version = Version.objects.create(content=self.alias_content_3, created_by=self.superuser) # Set the expiry date closer than the default self.alias_3_version.contentexpiry.expires = expire_at self.alias_3_version.contentexpiry.save() self.alias_3_version.publish(self.superuser) def tearDown(self): Site.objects.clear_cache() def test_pages_filtered_by_default_site(self): """ The list of change objects must be filtered by the default / current site """ endpoint = self.get_admin_url(ContentExpiry, "changelist") with self.login_user_context(self.get_superuser()): response = self.client.get(endpoint) queryset_result = response.context_data['cl'].result_list # Sanity check that the correct site 1 is used self.assertEqual(get_current_site(response.request), self.site_1) self.assertTrue(len(queryset_result), 1) self.assertTrue(queryset_result.first().pk, self.alias_1_version.contentexpiry.pk) @override_settings(SITE_ID=2) def test_pages_filtered_by_other_site(self): """ The list of change objects must be filtered by a different site """ endpoint = self.get_admin_url(ContentExpiry, "changelist") with self.login_user_context(self.get_superuser()): response = self.client.get(endpoint) queryset_result = response.context_data['cl'].result_list # Sanity check that the correct site 2 is used self.assertEqual(get_current_site(response.request), self.site_2) self.assertTrue(len(queryset_result), 1) self.assertTrue(queryset_result.first().pk, self.alias_2_version.contentexpiry.pk)

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ca53ffcf11ab07c500f83f99a24423a50bdef22e

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py

Python

test/test_nothing.py

jsafyan/pymc4

f892450faa2aba07273e1661a2c9d2cc81a78a97

[ "Apache-2.0" ]

null

test/test_nothing.py

jsafyan/pymc4

f892450faa2aba07273e1661a2c9d2cc81a78a97

[ "Apache-2.0" ]

null

test/test_nothing.py

jsafyan/pymc4

f892450faa2aba07273e1661a2c9d2cc81a78a97

[ "Apache-2.0" ]

null

from pymc4 import * # pylint: disable=wildcard-import def test_nothing(): assert 1 == 1

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04a606295a719fe3f56fc1e0c479546d912d18cb

28

py

Python

src/__init__.py

xiaojieluo/webnav

c9811c629e98d6ec1dd9c5dd97c587c68ab54685

[ "MIT" ]

null

src/__init__.py

xiaojieluo/webnav

c9811c629e98d6ec1dd9c5dd97c587c68ab54685

[ "MIT" ]

null

src/__init__.py

xiaojieluo/webnav

c9811c629e98d6ec1dd9c5dd97c587c68ab54685

[ "MIT" ]

null

from src.route import route

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1

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6

04cc62e96497ffa2a83b0f37b6fd52f8ef217622

426

py

Python

example_pipelines/__init__.py

tum-db/mlinspect4sql

863f1a98baff92341722b4fb180008cf9b518b80

[ "Apache-2.0" ]

40

2020-10-20T15:56:35.000Z

2022-02-22T14:48:09.000Z

example_pipelines/__init__.py

tum-db/mlinspect4sql

863f1a98baff92341722b4fb180008cf9b518b80

[ "Apache-2.0" ]

55

2020-10-21T15:37:44.000Z

2022-02-10T02:44:18.000Z

example_pipelines/__init__.py

tum-db/mlinspect4sql

863f1a98baff92341722b4fb180008cf9b518b80

[ "Apache-2.0" ]

9

2021-01-15T15:53:25.000Z

2022-03-31T23:42:12.000Z

""" Packages and classes we want to expose to users """ from ._pipelines import ADULT_SIMPLE_PY, ADULT_SIMPLE_IPYNB, ADULT_SIMPLE_PNG, ADULT_COMPLEX_PY, ADULT_COMPLEX_PNG, \ COMPAS_PY, COMPAS_PNG, HEALTHCARE_PY, HEALTHCARE_PNG __all__ = [ 'ADULT_SIMPLE_PY', 'ADULT_SIMPLE_IPYNB', 'ADULT_SIMPLE_PNG', 'ADULT_COMPLEX_PY', 'ADULT_COMPLEX_PNG', 'COMPAS_PY', 'COMPAS_PNG', 'HEALTHCARE_PY', 'HEALTHCARE_PNG', ]

32.769231

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null

0

6

04dc87e1db7556f3b15b867fb608ebd7c44d0b38

49

py

Python

enthought/traits/ui/value_tree.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/traits/ui/value_tree.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/traits/ui/value_tree.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from traitsui.value_tree import *

16.333333

33

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7

49

5.428571

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49

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34

24.5

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null

0

1

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1

0

1

0

6

b6bd3d547aa5101fafa66d705c75e453124be724

132

py

Python

pgmpy/independencies/__init__.py

anaviltripathi/pgmpy

24300984c66562219a09a3e9deb5e158bb021adb

[ "MIT" ]

1

2016-08-27T18:30:57.000Z

pgmpy/independencies/__init__.py

anaviltripathi/pgmpy

24300984c66562219a09a3e9deb5e158bb021adb

[ "MIT" ]

20

2019-02-22T09:24:57.000Z

2019-02-25T14:53:54.000Z

pgmpy/independencies/__init__.py

anaviltripathi/pgmpy

24300984c66562219a09a3e9deb5e158bb021adb

[ "MIT" ]

2

2017-03-21T22:49:36.000Z

2018-10-31T16:07:49.000Z

from .Independencies import Independencies, IndependenceAssertion __all__ = ['Independencies', 'IndependenceAssertion']

26.4

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1

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6

8e10b7026676c666e6e4f77753aaa7c1bcc618ef

46

py

Python

src/Sixth Chapter/Example1.py

matthijskrul/ThinkPython

34c1d81f4ef535c32b8b0309b23c7ca37f851606

[ "MIT" ]

null

src/Sixth Chapter/Example1.py

matthijskrul/ThinkPython

34c1d81f4ef535c32b8b0309b23c7ca37f851606

[ "MIT" ]

null

src/Sixth Chapter/Example1.py

matthijskrul/ThinkPython

34c1d81f4ef535c32b8b0309b23c7ca37f851606

[ "MIT" ]

null

def is_divisible(x, y): return x % y == 0

15.333333

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null

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1

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null

0

1

0

1

0

6

8e14737849ce24c515224ae9a1888f3e58c8d72c

47

py

Python

tests/conll_test.py

ChadiHelwe/PyArabicNLP

10e6450d322261e173cde4e6111d117656f9607c

[ "MIT" ]

3

2020-04-13T13:44:22.000Z

2020-12-05T15:20:10.000Z

tests/conll_test.py

ChadiHelwe/PyArabicNLP

10e6450d322261e173cde4e6111d117656f9607c

[ "MIT" ]

null

tests/conll_test.py

ChadiHelwe/PyArabicNLP

10e6450d322261e173cde4e6111d117656f9607c

[ "MIT" ]

null

from pyarabicnlp.metrics.conll import ner_score

47

0.893617

7

47

5.857143

1

0

0.06383

47

1

47

0.931818

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1

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true

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null

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0

null

0

1

0

1

0

1

0

6

8e2a825c71b4bf789af839303da6d8a1c4e91380

523

py

Python

resources/PyInstaller-3.0/tests/old_suite/basic/pkg2/a.py

dvt32/mypymodoro

7d2db639ea828e4db9caa84cd6f747f542ab22d8

[ "MIT" ]

null

resources/PyInstaller-3.0/tests/old_suite/basic/pkg2/a.py

dvt32/mypymodoro

7d2db639ea828e4db9caa84cd6f747f542ab22d8

[ "MIT" ]

null

resources/PyInstaller-3.0/tests/old_suite/basic/pkg2/a.py

dvt32/mypymodoro

7d2db639ea828e4db9caa84cd6f747f542ab22d8

[ "MIT" ]

null

#----------------------------------------------------------------------------- # Copyright (c) 2013, PyInstaller Development Team. # # Distributed under the terms of the GNU General Public License with exception # for distributing bootloader. # # The full license is in the file COPYING.txt, distributed with this software. #----------------------------------------------------------------------------- """ pkg2.a defines overridden and a_func """ def a_func(): return "a_func from pkg2.a" print("pkg2.a imported")

30.764706

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523

4.962963

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0.05597

0

0.015251

0.122371

523

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1

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null

0

1

0

1

0

6

8e3132a9d29f790e0f4d25778576dcd8cfee750a

146

py

Python

_solved/solutions/01-introduction-geospatial-data1.py

song-zi/geopandas-tutorial

5c0012d5747b03233f51d215cd7f74f59823da66

[ "BSD-3-Clause" ]

6

2019-02-06T14:30:43.000Z

2019-05-16T08:37:12.000Z

_solved/solutions/01-introduction-geospatial-data23.py

glenn6452/geopandas-philippines

2153a940ca6e810d96d82198e3f05a0b34c6e2f5

[ "BSD-3-Clause" ]

null

_solved/solutions/01-introduction-geospatial-data23.py

glenn6452/geopandas-philippines

2153a940ca6e810d96d82198e3f05a0b34c6e2f5

[ "BSD-3-Clause" ]

5

2019-02-07T10:06:05.000Z

2022-03-21T13:15:49.000Z

districts = geopandas.read_file("data/paris_districts_utm.geojson") stations = geopandas.read_file("data/paris_sharing_bike_stations_utm.geojson")

73

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1

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1

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0

6

f3eabeb780691952eecf61362801c0d29c4374a8

41

py

Python

common/api-auth.py

newsettle/ns4_chatbot

526b97aa31292c28d10518bbfaa7466b8ba109ee

[ "Apache-2.0" ]

51

2019-03-29T11:47:55.000Z

2021-04-16T02:40:35.000Z

common/api-auth.py

piginzoo/ns4_chatbot

526b97aa31292c28d10518bbfaa7466b8ba109ee

[ "Apache-2.0" ]

7

2019-04-16T01:46:01.000Z

2022-03-11T23:44:09.000Z

common/api-auth.py

newsettle/ns4_chatbot

526b97aa31292c28d10518bbfaa7466b8ba109ee

[ "Apache-2.0" ]

20

2019-04-02T03:37:38.000Z

2021-12-31T09:25:12.000Z

class API_Auth: def init(self): pass

8.2

16

0.682927

7

41

3.857143

1

0

0.219512

41

5

17

8.2

0.84375

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0.333333

0

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null

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1

0

1

0

1

0

6

6d41edc4056742859627e701926da6c02802f41a

28

py

Python

cornac/models/c2pf/__init__.py

GuoJingyao/cornac

e7529990ec1dfa586c4af3de98e4b3e00a786578

[ "Apache-2.0" ]

null

cornac/models/c2pf/__init__.py

GuoJingyao/cornac

e7529990ec1dfa586c4af3de98e4b3e00a786578

[ "Apache-2.0" ]

null

cornac/models/c2pf/__init__.py

GuoJingyao/cornac

e7529990ec1dfa586c4af3de98e4b3e00a786578

[ "Apache-2.0" ]

null

from .recom_c2pf import C2PF

28

0.857143

5

28

4.6

0.8

0

0.08

0.107143

28

1

28

0.84

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true

0

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1

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0

1

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null

0

1

0

1

0

1

0

6

edd40ad56a324901283b25604113bd19aedc88f7

86

py

Python

afs/service/ProjectServiceError.py

chanke/afspy

525e7b3b53e58be515f11b83cc59ddb0765ef8e5

[ "BSD-2-Clause" ]

null

afs/service/ProjectServiceError.py

chanke/afspy

525e7b3b53e58be515f11b83cc59ddb0765ef8e5

[ "BSD-2-Clause" ]

null

afs/service/ProjectServiceError.py

chanke/afspy

525e7b3b53e58be515f11b83cc59ddb0765ef8e5

[ "BSD-2-Clause" ]

null

from afs.util.AFSError import AFSError class ProjectServiceError(AFSError): pass

17.2

38

0.802326

10

86

6.9

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86

4

39

21.5

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true

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null

0

1

0

1

0

6

eddc08cd12443d0964fc532c2aa749466ac14b87

3,918

py

Python

snoopy/embedding/tf_hub.py

easeml/snoopy

bd087cbd512d2f1872fe156a6b0f0223a77c9419

[ "MIT" ]

null

snoopy/embedding/tf_hub.py

easeml/snoopy

bd087cbd512d2f1872fe156a6b0f0223a77c9419

[ "MIT" ]

null

snoopy/embedding/tf_hub.py

easeml/snoopy

bd087cbd512d2f1872fe156a6b0f0223a77c9419

[ "MIT" ]

null

from dataclasses import dataclass from typing import Callable, Tuple import numpy as np import tensorflow as tf import tensorflow_hub as tf_hub import torch as pt from .base import EmbeddingModel, EmbeddingModelSpec, _ImageTransformationHelper as Ith from .._logging import get_logger from .._utils import get_tf_device from ..custom_types import DataType _logger = get_logger(__name__) @dataclass class TFHubImageSpec(EmbeddingModelSpec): url: str output_dimension: int required_image_size: Tuple[int, int] def load(self, device: pt.device) -> EmbeddingModel: return _ImageInner.get_instance(self, device) @property def data_type(self) -> DataType: return DataType.IMAGE class _ImageInner(EmbeddingModel): _instances = dict() def __init__(self, spec: TFHubImageSpec, device: pt.device): self._device = device self._tf_device = get_tf_device(device) with tf.device(self._tf_device): self._model = tf_hub.KerasLayer(spec.url, trainable=False) self._required_image_size = spec.required_image_size self._output_dimension = spec.output_dimension @classmethod def get_instance(cls, spec: TFHubImageSpec, device: pt.device) -> EmbeddingModel: combination_string = (spec.url, get_tf_device(device)) if combination_string not in cls._instances: _logger.info(f"Initializing {combination_string[0]} on {combination_string[1]}") cls._instances[combination_string] = cls(spec, device) return cls._instances[combination_string] def move_to(self, device: pt.device) -> None: self._device = device self._tf_device = get_tf_device(device) @property def output_dimension(self) -> int: return self._output_dimension def get_data_preparation_function(self) -> Callable: return lambda feature: Ith.central_crop_with_resize_3_channels(feature, self._required_image_size) def apply_embedding(self, features: np.ndarray) -> pt.Tensor: with tf.device(self._tf_device): tf_tensor = tf.convert_to_tensor(features) tf_result = self._model(tf_tensor) return pt.as_tensor(tf_result.numpy(), device=self._device) @dataclass class TFHubTextSpec(EmbeddingModelSpec): url: str output_dimension: int def load(self, device: pt.device) -> EmbeddingModel: return _TextInner.get_instance(self, device) @property def data_type(self) -> DataType: return DataType.TEXT class _TextInner(EmbeddingModel): _instances = dict() def __init__(self, spec: TFHubTextSpec, device: pt.device): self._device = device self._tf_device = get_tf_device(device) with tf.device(self._tf_device): self._model = tf_hub.KerasLayer(spec.url, trainable=False) self._output_dimension = spec.output_dimension @classmethod def get_instance(cls, spec: TFHubTextSpec, device: pt.device) -> EmbeddingModel: combination_string = (spec.url, get_tf_device(device)) if combination_string not in cls._instances: _logger.info(f"Initializing {combination_string[0]} on {combination_string[1]}") cls._instances[combination_string] = cls(spec, device) return cls._instances[combination_string] def move_to(self, device: pt.device) -> None: self._device = device self._tf_device = get_tf_device(device) @property def output_dimension(self) -> int: return self._output_dimension def get_data_preparation_function(self) -> Callable: return lambda x: x def apply_embedding(self, features: np.ndarray) -> pt.Tensor: with tf.device(self._tf_device): tf_tensor = tf.convert_to_tensor(features) tf_result = self._model(tf_tensor) return pt.as_tensor(tf_result.numpy(), device=self._device)

32.92437

106

0.703675

482

3,918

5.412863

0.192946

0.05826

0.042928

0.055194

0.786892

0.766194

0.735148

0.702951

0.666156

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0.00161

0.207249

3,918

118

107

33.20339

0.838377

0

0.689655

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0.023481

0

1

0.183908

false

0

0.114943

0.091954

0.563218

0

null

0

1

0

null

0

1

0

6

eddd6cc1b3fb3ab542a67a2838370f9eee3b307e

37

py

Python

fix15/__init__.py

davidmreed/fix15

0e76df68f8cc69b7d0937e77dc270e47e1798b0a

[ "MIT" ]

8

2018-07-09T13:39:51.000Z

2020-12-02T00:53:14.000Z

fix15/__init__.py

davidmreed/fix15

0e76df68f8cc69b7d0937e77dc270e47e1798b0a

[ "MIT" ]

null

fix15/__init__.py

davidmreed/fix15

0e76df68f8cc69b7d0937e77dc270e47e1798b0a

[ "MIT" ]

null

from .fix15 import to18, process_file

37

0.837838

6

37

5

1

0

0.121212

0.108108

37

1

37

0.787879

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

edeea6584120cf965deb43efc40912ef9ea3571f

389

py

Python

visionlib/__init__.py

sumeshmn/Visionlib

c543ee038d6d1dcf9d88a8d7a782addd998e6036

[ "MIT" ]

null

visionlib/__init__.py

sumeshmn/Visionlib

c543ee038d6d1dcf9d88a8d7a782addd998e6036

[ "MIT" ]

null

visionlib/__init__.py

sumeshmn/Visionlib

c543ee038d6d1dcf9d88a8d7a782addd998e6036

[ "MIT" ]

null

from visionlib.face.detection import FDetector from visionlib.utils.imgutils import Image from visionlib.gender.detection import GDetector from visionlib.object.detection.detection import ODetection from visionlib.object.classifier.xception_detector import Xceptionv1 from visionlib.object.classifier.inception_detector import Inception from visionlib.keypoints.detection import KDetector

48.625

68

0.884319

47

389

7.276596

0.425532

0.266082

0.166667

0.169591

0

0.00277

0.071979

389

7

69

55.571429

0.944598

0

1

0

true

0

1

0

1

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null

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0

1

0

1

0

null

0

1

0

1

0

1

0

6

edf254f736113e511f4f6e8d0a7137ba3412afd6

92

py

Python

course1/env/__init__.py

uofon-shaowen/SummerCourse2021

f3b4d3ef947190b42cf675ce4b17d6fbcf1f9da0

[ "MIT" ]

28

2021-08-12T09:36:54.000Z

2022-02-08T09:19:40.000Z

course1/env/__init__.py

uofon-shaowen/SummerCourse2021

f3b4d3ef947190b42cf675ce4b17d6fbcf1f9da0

[ "MIT" ]

2

2021-08-22T11:49:53.000Z

2021-08-25T02:31:53.000Z

course1/env/__init__.py

uofon-shaowen/SummerCourse2021

f3b4d3ef947190b42cf675ce4b17d6fbcf1f9da0

[ "MIT" ]

22

2021-08-16T12:23:13.000Z

2021-12-02T07:58:09.000Z

from .snakes import * from .sokoban import * from .ccgame import * from .gridworld import *

18.4

24

0.73913

12

92

5.666667

0.5

0.441176

0

0.173913

92

4

25

23

0.894737

0

1

0

true

0

1

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1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

6124a1b233541075cfa056e062ef330738f2652f

204

py

Python

src/rreil/address.py

tizmd/python-gdsl

d5782490a9a8b67b7e5667fafb51409c3693b010

[ "MIT" ]

null

src/rreil/address.py

tizmd/python-gdsl

d5782490a9a8b67b7e5667fafb51409c3693b010

[ "MIT" ]

null

src/rreil/address.py

tizmd/python-gdsl

d5782490a9a8b67b7e5667fafb51409c3693b010

[ "MIT" ]

null

class Address(object): def __init__(self, size, address): self.size = size self.address = address def __str__(self): return "{%d} %s" % (self.size, self.address)

25.5

53

0.563725

24

204

4.458333

0.458333

0.224299

0.280374

0

0.303922

204

7

54

29.142857

0.753521

0

0.034314

0

1

0.333333

false

0

0.166667

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

b62d18be64587ba593ca69919ae293cc6abeefff

914

py

Python

03 Python/Entwicklung eines IoT-Devices/aufgabe/src/my_iot_device/pubsub.py

DennisSchulmeister/dhbwka-wwi-iottech-quellcodes

58f86907af31187f267a9ea476f061cc59098ebd

[ "CC-BY-4.0" ]

null

03 Python/Entwicklung eines IoT-Devices/aufgabe/src/my_iot_device/pubsub.py

DennisSchulmeister/dhbwka-wwi-iottech-quellcodes

58f86907af31187f267a9ea476f061cc59098ebd

[ "CC-BY-4.0" ]

null

03 Python/Entwicklung eines IoT-Devices/aufgabe/src/my_iot_device/pubsub.py

DennisSchulmeister/dhbwka-wwi-iottech-quellcodes

58f86907af31187f267a9ea476f061cc59098ebd

[ "CC-BY-4.0" ]

1

2020-10-10T20:24:05.000Z

import os, threading class PublishSubscribeBroker: """ Diese Klasse implementiert einen einfachen lokalen Message Broker zur Umsetzung des Publish/Subscribe (oder auch Observer) Patterns. Beliebige Threads können üb er die publish()-Methode beliebige Nachrichten an beliebige Topics senden, wobei ein Topic hierbei einfach durch seinen Namen identifiziert wird und eine Nachricht aus den Positionsparametern (*args) und Namensparametern (**kwargs) der publish()-Methode besteht. Empfänger kann jede Methode sein, welche die *args und **kwargs der gesendeten Nachrichten verarbeiten kann. Hierfür können mit die Empfängermethoden mit subscribe() und unsubscribe() den Topics zugeordnet werden. Die Empfängermethoden werden dabei stets in einem eigenen Thread ausgeführt, um sie somit von den Senderthreads zu entkoppeln. """ pass # TODO

41.545455

71

0.752735

108

914

6.37037

0.768519

0.040698

0

0.203501

914

22

72

41.545455

0.945055

0.844639

0

0.045455

0

1

0

true

0.333333

0

0.666667

0

null

0

1

0

null

0

1

0

1

0

1

0

6

b68deae9df96ef6f73fcedb03806e117e47f522c

362

py

Python

tools/split_list.py

dpukhkaiev/BRISE

642077f7e7def6371716ba05b46413edd8b98c74

[ "MIT" ]

3

2018-07-19T09:15:20.000Z

2019-03-07T05:50:35.000Z

tools/split_list.py

dpukhkaiev/BRISE

642077f7e7def6371716ba05b46413edd8b98c74

[ "MIT" ]

null

tools/split_list.py

dpukhkaiev/BRISE

642077f7e7def6371716ba05b46413edd8b98c74

[ "MIT" ]

null

class SplitList: list = [] def __init__(self, alist, wanted_parts): self.list = self.split_list(alist = alist, wanted_parts= wanted_parts) def split_list(self, alist, wanted_parts=1): length = len(alist) return [alist[i * length // wanted_parts: (i + 1) * length // wanted_parts] for i in range(wanted_parts)]

40.222222

83

0.629834

48

362

4.479167

0.375

0.35814

0.223256

0.186047

0

0.007407

0.254144

362

9

84

40.222222

0.788889

0

1

0.25

false

0

0.625

0

null

1

0

1

0

null

0

1

0

1

0

6

b69aa0c2ef8198deb8695ee3acc0c6a673f1e617

119

py

Python

mailer/gmail.py

jasonwee/common-util-py

c444b2fb0702d26cd8ed27250206401526dbcead

[ "Apache-2.0" ]

1

2021-06-25T11:56:08.000Z

mailer/gmail.py

jasonwee/common-util-py

c444b2fb0702d26cd8ed27250206401526dbcead

[ "Apache-2.0" ]

null

mailer/gmail.py

jasonwee/common-util-py

c444b2fb0702d26cd8ed27250206401526dbcead

[ "Apache-2.0" ]

1

2021-06-25T12:00:22.000Z

def send_text(): print("sending text email to gmail") def send_html(): print("sending html email to gmail")

14.875

40

0.672269

18

119

4.333333

0.5

0.179487

0.307692

0

0.210084

119

7

41

17

0.829787

0

0.461538

0

1

0.5

true

0

0.5

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

1e052fdb7b5a0e0be2db85ea5f67b4b343f52be2

32

py

Python

dsb/drawer/__init__.py

Firemoon777/dialog-sticker-bot

6a7b5670d573fd78c8639c06f22c66d2088ec568

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

6

2021-12-28T14:03:15.000Z

2022-01-02T02:26:33.000Z

dsb/drawer/__init__.py

Firemoon777/dialog-sticker-bot

6a7b5670d573fd78c8639c06f22c66d2088ec568

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

1

2021-12-30T10:29:29.000Z

dsb/drawer/__init__.py

Firemoon777/dialog-sticker-bot

6a7b5670d573fd78c8639c06f22c66d2088ec568

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

1

2022-02-05T12:17:45.000Z

from .drawer import BubbleDrawer

32

0.875

4

32

7

1

0

0.09375

32

1

32

0.965517

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

1e2ca3a760f9247df07f6d6022fdb82815258c76

20

py

Python

ansys/mapdl/core/_commands/display_/__init__.py

da1910/pymapdl

305b70b30e61a78011e974ff4cb409ee21f89e13

[ "MIT" ]

194

2016-10-21T08:46:41.000Z

2021-01-06T20:39:23.000Z

ansys/mapdl/core/_commands/display_/__init__.py

da1910/pymapdl

305b70b30e61a78011e974ff4cb409ee21f89e13

[ "MIT" ]

463

2021-01-12T14:07:38.000Z

2022-03-31T22:42:25.000Z

ansys/mapdl/core/_commands/display_/__init__.py

da1910/pymapdl

305b70b30e61a78011e974ff4cb409ee21f89e13

[ "MIT" ]

66

2016-11-21T04:26:08.000Z

2020-12-28T09:27:27.000Z

from . import setup

10

19

0.75

3

20

5

1

0

0.2

20

1

20

0.9375

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

1e4fde041c5f31d7c576e536be7dea5db3fc0137

11,470

py

Python

test/unit/test_buildconfigurationsets.py

SakuragawaAsaba/pnc-cli

0e0c5976766f6d2e32980c39ebc30950fc02960e

[ "Apache-2.0" ]

null

test/unit/test_buildconfigurationsets.py

SakuragawaAsaba/pnc-cli

0e0c5976766f6d2e32980c39ebc30950fc02960e

[ "Apache-2.0" ]

null

test/unit/test_buildconfigurationsets.py

SakuragawaAsaba/pnc-cli

0e0c5976766f6d2e32980c39ebc30950fc02960e

[ "Apache-2.0" ]

null

import argparse import pytest __author__ = 'Tom' from test import testutils from mock import MagicMock, patch, call from pnc_cli import buildconfigurationsets from pnc_cli.swagger_client import BuildconfigurationsetsApi from pnc_cli.swagger_client import BuildConfigurationSetRest from pnc_cli.swagger_client import BuildconfigurationsApi def test_create_build_config_set_object(**kwargs): compare = BuildConfigurationSetRest() compare.name = 'testerino' compare.product_version_id = 1 result = buildconfigurationsets._create_build_config_set_object(name='testerino', product_version_id=1) assert result.to_dict() == compare.to_dict() @patch('pnc_cli.buildconfigurationsets.sets_api.get_all', return_value=MagicMock(content=[1, 2, 3])) def test_list_build_configuration_sets(mock): result = buildconfigurationsets.list_build_configuration_sets_raw() mock.assert_called_once_with(page_size=200, q="", sort="") assert result == [1, 2, 3] @patch('pnc_cli.buildconfigurationsets._create_build_config_set_object', return_value='test-config-set') @patch('pnc_cli.buildconfigurationsets.sets_api.create_new', return_value=MagicMock(content='SUCCESS')) def test_create_build_configuration_set(mock_create_new, mock_create_object): result = buildconfigurationsets.create_build_configuration_set_raw(name='newname', product_version_id=1, build_configuration_ids=[1, 2, 3]) mock_create_object.assert_called_once_with(name='newname', product_version_id=1, build_configuration_ids=[1, 2, 3]) mock_create_new.assert_called_once_with(body='test-config-set') assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.get_specific', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_get_build_configuration_set_id(mock_sets_api, mock_get_specific, mock_set_id): result = buildconfigurationsets.get_build_configuration_set_raw(id=1) mock_set_id.assert_called_once_with(mock_sets_api, 1, None) mock_get_specific.assert_called_once_with(id=1) assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.get_specific', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_get_build_configuration_set_name(mock_sets_api, mock_get_specific, mock_set_id): result = buildconfigurationsets.get_build_configuration_set_raw(name='testerino') mock_set_id.assert_called_once_with(mock_sets_api, None, 'testerino') mock_get_specific.assert_called_once_with(id=1) assert result == 'SUCCESS' @patch('pnc_cli.buildconfigurationsets.sets_api.get_specific') @patch('pnc_cli.buildconfigurationsets.sets_api.update', return_value=MagicMock(content='SUCCESS')) def test_update_build_configuration_set(mock_update, mock_get_specific): mock = MagicMock() mockcontent = MagicMock(content=mock) mock_get_specific.return_value = mockcontent result = buildconfigurationsets.update_build_configuration_set_raw(1, product_version_id='updated') mock_get_specific.assert_called_once_with(id=1) mock_update.assert_called_once_with(id=1, body=mock) assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.delete_specific', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_delete_build_config_set(mock_sets_api, mock_delete, mock_set_id): result = buildconfigurationsets.delete_build_configuration_set_raw(id=1) mock_set_id.assert_called_once_with(mock_sets_api, 1, None) mock_delete.assert_called_once_with(id=1) assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.delete_specific', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_delete_build_config_set_name(mock_sets_api, mock_delete, mock_set_id): result = buildconfigurationsets.delete_build_configuration_set_raw(name='testerino') mock_set_id.assert_called_once_with(mock_sets_api, None, 'testerino') mock_delete.assert_called_once_with(id=1) assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.build', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_build_set_id(mock_sets_api, mock_build, mock_set_id): result = buildconfigurationsets.build_set_raw(id=1) mock_set_id.assert_called_once_with(mock_sets_api, 1, None) mock_build.assert_called_once_with(id=1) assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.build', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_build_set_name(mock_sets_api, mock_build, mock_set_id): result = buildconfigurationsets.build_set_raw(name='testerino') mock_set_id.assert_called_once_with(mock_sets_api, None, 'testerino') mock_build.assert_called_once_with(id=1) assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.get_configurations', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_list_build_configurations_for_set_id(mock_sets_api, mock_get_configurations, mock_set_id): result = buildconfigurationsets.list_build_configurations_for_set_raw(id=1) mock_set_id.assert_called_once_with(mock_sets_api, 1, None) mock_get_configurations.assert_called_once_with(id=1, page_size=200, q="", sort="") assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.get_configurations', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_list_build_configurations_for_set_name(mock_sets_api, mock_get_configurations, mock_set_id): result = buildconfigurationsets.list_build_configurations_for_set_raw(name='testerino') mock_set_id.assert_called_once_with(mock_sets_api, None, 'testerino') mock_get_configurations.assert_called_once_with(id=1, page_size=200, q='', sort='') assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.common.get_entity', return_value='BuildConfiguration') @patch('pnc_cli.buildconfigurationsets.sets_api.add_configuration', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) @patch('pnc_cli.buildconfigurationsets.configs_api', autospec=BuildconfigurationsApi) def test_add_build_configuration_to_set_id(mock_configs_api, mock_sets_api, mock_add_config, mock_get_entity, mock_set_id): result = buildconfigurationsets.add_build_configuration_to_set_raw(set_id=1, config_id=1) set_id_calls = [call(mock_sets_api, 1, None), call(mock_configs_api, 1, None)] mock_set_id.assert_has_calls(set_id_calls) mock_get_entity.assert_called_once_with(mock_configs_api, 1) mock_add_config.assert_called_once_with(id=1, body='BuildConfiguration') assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.common.get_entity', return_value='BuildConfiguration') @patch('pnc_cli.buildconfigurationsets.sets_api.add_configuration', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) @patch('pnc_cli.buildconfigurationsets.configs_api', autospec=BuildconfigurationsApi) def test_add_build_configuration_to_set_name(mock_configs_api, mock_sets_api, mock_add_config, mock_get_entity, mock_set_id): result = buildconfigurationsets.add_build_configuration_to_set_raw(set_name='testerino', config_id=1) set_id_calls = [call(mock_sets_api, None, 'testerino'), call(mock_configs_api, 1, None)] mock_set_id.assert_has_calls(set_id_calls) mock_get_entity.assert_called_once_with(mock_configs_api, 1) mock_add_config.assert_called_once_with(id=1, body='BuildConfiguration') assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.remove_configuration', return_value=MagicMock(content="removed")) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) @patch('pnc_cli.buildconfigurationsets.configs_api', autospec=BuildconfigurationsApi) def test_remove_build_configuration_from_set_id(mock_configs_api, mock_sets_api, mock_remove_configuration, mock_set_id): response = buildconfigurationsets.remove_build_configuration_from_set_raw(set_id=1, config_id=100) set_id_calls = [call(mock_sets_api, 1, None), call(mock_configs_api, 100, None)] mock_set_id.assert_has_calls(set_id_calls) mock_remove_configuration.assert_called_once_with(id=1, config_id=1) assert response == "removed" @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.remove_configuration', return_value=MagicMock(content="removed")) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) @patch('pnc_cli.buildconfigurationsets.configs_api', autospec=BuildconfigurationsApi) def test_remove_build_configuration_from_set_name(mock_configs_api, mock_sets_api, mock_remove_configuration, mock_set_id): response = buildconfigurationsets.remove_build_configuration_from_set_raw(set_name='test', config_name='test_conf') set_id_calls = [call(mock_sets_api, None, 'test'), call(mock_configs_api, None, 'test_conf')] mock_set_id.assert_has_calls(set_id_calls) mock_remove_configuration.assert_called_once_with(id=1, config_id=1) assert response == "removed" @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.get_build_records', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_list_build_records_for_set_id(mock_sets_api, mock_get_records, mock_set_id): result = buildconfigurationsets.list_build_records_for_set_raw(id=1) mock_set_id.assert_called_once_with(mock_sets_api, 1, None) mock_get_records.assert_called_once_with(id=1, page_size=200, q="", sort="") assert result == 'SUCCESS' @patch('pnc_cli.common.set_id', return_value=1) @patch('pnc_cli.buildconfigurationsets.sets_api.get_build_records', return_value=MagicMock(content='SUCCESS')) @patch('pnc_cli.buildconfigurationsets.sets_api', autospec=BuildconfigurationsetsApi) def test_list_build_records_for_set_name(mock_sets_api, mock_get_records, mock_set_id): result = buildconfigurationsets.list_build_records_for_set_raw(name='testerino') mock_set_id.assert_called_once_with(mock_sets_api, None, 'testerino') mock_get_records.assert_called_once_with(id=1, page_size=200, q='', sort='') assert result == 'SUCCESS'

56.782178

125

0.815955

1,583

11,470

5.473784

0.053696

0.048471

0.067282

0.140912

0.881823

0.875014

0.843508

0.820427

0.810617

0.804847

0

0.008524

0.079425

11,470

201

126

57.064677

0.812103

0

0.561728

0

0.225371

0.181604

0

0.32716

1

0.111111

false

0

0.049383

0

0.160494

0

null

0

1

0

null

0

6

1e9b9a52f58ccd04306a224872d66dd40add7622

232

py

Python

scripts/download_datasets.py

rwiteshbera/code-generator

2cbc24b3908bc0b84088c4c272b8f5cb848410fd

[ "BSD-3-Clause" ]

28

2021-04-20T13:33:12.000Z

2022-01-01T11:53:52.000Z

scripts/download_datasets.py

rwiteshbera/code-generator

2cbc24b3908bc0b84088c4c272b8f5cb848410fd

[ "BSD-3-Clause" ]

112

2021-04-22T02:07:43.000Z

2022-03-28T01:28:05.000Z

scripts/download_datasets.py

rwiteshbera/code-generator

2cbc24b3908bc0b84088c4c272b8f5cb848410fd

[ "BSD-3-Clause" ]

21

2021-04-21T07:48:29.000Z

2022-02-04T19:40:54.000Z

from torchvision import datasets datasets.CIFAR10("~/data", train=True, download=True) datasets.CIFAR10("~/data", train=False, download=True) datasets.VOCSegmentation( "~/data", year="2012", image_set="train", download=True )

25.777778

59

0.737069

28

232

6.071429

0.535714

0.211765

0.223529

0.282353

0

0.038095

0.094828

232

8

60

29

0.771429

0

0.116379

0

1

0

true

0

0.166667

0

0.166667

0

1

0

null

1

0

1

0

null

0

1

0

6

1ea89eb7822d7414215bf9084a854561248688b7

85

py

Python

software/misc/get_gene_ne_header.py

Searchlight2/Searchlight2

87c85975be49c503f79063d72d321da21a6c6341

[ "MIT" ]

17

2018-12-11T13:36:12.000Z

2022-03-31T06:27:59.000Z

software/misc/get_gene_ne_header.py

Searchlight2/Searchlight2

87c85975be49c503f79063d72d321da21a6c6341

[ "MIT" ]

1

2019-11-26T11:00:57.000Z

2019-11-26T11:01:12.000Z

software/misc/get_gene_ne_header.py

Searchlight2/Searchlight2

87c85975be49c503f79063d72d321da21a6c6341

[ "MIT" ]

7

2020-05-21T16:35:41.000Z

2022-03-31T06:28:01.000Z

def get_gene_ne_header(global_variables): return global_variables["sample_list"]

28.333333

42

0.823529

12

85

5.333333

0.833333

0.46875

0

0.094118

85

3

42

28.333333

0.831169

0

0.127907

0

1

0.5

false

0

0.5

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

1ebfc67cb0aac1272a1d0ac720c624d17e783c6d

156

py

Python

api/src/controller/controllers.py

IchiroKobayashi/ichi-flask-challenge

93222f50db7ace48646963abd4f323c1689568ed

[ "MIT" ]

null

api/src/controller/controllers.py

IchiroKobayashi/ichi-flask-challenge

93222f50db7ace48646963abd4f323c1689568ed

[ "MIT" ]

null

api/src/controller/controllers.py

IchiroKobayashi/ichi-flask-challenge

93222f50db7ace48646963abd4f323c1689568ed

[ "MIT" ]

null

from .scrape_controller import scrape_by_id, scrape_honda from .user_controller import get_user __all__ = [ scrape_by_id, scrape_honda, get_user ]

19.5

57

0.788462

23

156

4.73913

0.434783

0.293578

0.183486

0.293578

0.385321

0

0.160256

156

7

58

22.285714

0.832061

0

1

0

false

0

0.333333

0

0.333333

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1

0

null

1

0

1

0

null

0

1

0

6

949b2993e0a8dfbde9ad57188ba73d10578cfdea

4,300

py

Python

gewittergefahr/gg_utils/longitude_conversion_test.py

dopplerchase/GewitterGefahr

4415b08dd64f37eba5b1b9e8cc5aa9af24f96593

[ "MIT" ]

26

2018-10-04T01:07:35.000Z

2022-01-29T08:49:32.000Z

gewittergefahr/gg_utils/longitude_conversion_test.py

liuximarcus/GewitterGefahr

d819874d616f98a25187bfd3091073a2e6d5279e

[ "MIT" ]

4

2017-12-25T02:01:08.000Z

2018-12-19T01:54:21.000Z

gewittergefahr/gg_utils/longitude_conversion_test.py

liuximarcus/GewitterGefahr

d819874d616f98a25187bfd3091073a2e6d5279e

[ "MIT" ]

11

2017-12-10T23:05:29.000Z

2022-01-29T08:49:33.000Z

"""Unit tests for longitude_conversion.py.""" import unittest import numpy from gewittergefahr.gg_utils import longitude_conversion as lng_conversion TOLERANCE = 1e-6 LONGITUDES_POSITIVE_IN_WEST_DEG = numpy.array([ [numpy.nan, 45., 90.], [45., 90., 135.], [90., 135., 180.], [135., 180., 225.], [180., 225., 270.], [225., 270., 315.], [270., 315., 0.], [315., 0., numpy.nan], [0., numpy.nan, numpy.nan]]) LONGITUDES_NEGATIVE_IN_WEST_DEG = numpy.array([ [numpy.nan, 45., 90.], [45., 90., 135.], [90., 135., 180.], [135., 180., -135.], [180., -135., -90.], [-135., -90., -45.], [-90., -45., 0.], [-45., 0., numpy.nan], [0., numpy.nan, numpy.nan]]) LONGITUDES_MIXED_SIGNS_DEG = numpy.array([ [numpy.nan, 45., 90.], [45., 90., 135.], [90., 135., 180.], [135., 180., 225.], [180., -135., 270.], [-135., -90., 315.], [270., -45., 0.], [315., 0., numpy.nan], [0., numpy.nan, numpy.nan]]) class LongitudeConversionTests(unittest.TestCase): """Each method is a unit test for longitude_conversion.py.""" def test_convert_lng_negative_in_west_inputs_mixed(self): """Ensures correct output from convert_lng_negative_in_west. In this case, inputs have mixed signs. """ these_longitudes_deg = lng_conversion.convert_lng_negative_in_west( LONGITUDES_MIXED_SIGNS_DEG) self.assertTrue( numpy.allclose(these_longitudes_deg, LONGITUDES_NEGATIVE_IN_WEST_DEG, atol=TOLERANCE, equal_nan=True)) def test_convert_lng_negative_in_west_inputs_negative(self): """Ensures correct output from convert_lng_negative_in_west. In this case, inputs are already negative in western hemisphere. """ these_longitudes_deg = lng_conversion.convert_lng_negative_in_west( LONGITUDES_NEGATIVE_IN_WEST_DEG) self.assertTrue( numpy.allclose(these_longitudes_deg, LONGITUDES_NEGATIVE_IN_WEST_DEG, atol=TOLERANCE, equal_nan=True)) def test_convert_lng_negative_in_west_inputs_positive(self): """Ensures correct output from convert_lng_negative_in_west. In this case, inputs are positive in western hemisphere. """ these_longitudes_deg = lng_conversion.convert_lng_negative_in_west( LONGITUDES_POSITIVE_IN_WEST_DEG) self.assertTrue( numpy.allclose(these_longitudes_deg, LONGITUDES_NEGATIVE_IN_WEST_DEG, atol=TOLERANCE, equal_nan=True)) def test_convert_lng_positive_in_west_inputs_mixed(self): """Ensures correct output from convert_lng_positive_in_west. In this case, inputs have mixed signs. """ these_longitudes_deg = lng_conversion.convert_lng_positive_in_west( LONGITUDES_MIXED_SIGNS_DEG) self.assertTrue( numpy.allclose(these_longitudes_deg, LONGITUDES_POSITIVE_IN_WEST_DEG, atol=TOLERANCE, equal_nan=True)) def test_convert_lng_positive_in_west_inputs_negative(self): """Ensures correct output from convert_lng_positive_in_west. In this case, inputs are negative in western hemisphere. """ these_longitudes_deg = lng_conversion.convert_lng_positive_in_west( LONGITUDES_NEGATIVE_IN_WEST_DEG) self.assertTrue( numpy.allclose(these_longitudes_deg, LONGITUDES_POSITIVE_IN_WEST_DEG, atol=TOLERANCE, equal_nan=True)) def test_convert_lng_positive_in_west_inputs_positive(self): """Ensures correct output from convert_lng_positive_in_west. In this case, inputs are already positive in western hemisphere. """ these_longitudes_deg = lng_conversion.convert_lng_positive_in_west( LONGITUDES_POSITIVE_IN_WEST_DEG) self.assertTrue( numpy.allclose(these_longitudes_deg, LONGITUDES_POSITIVE_IN_WEST_DEG, atol=TOLERANCE, equal_nan=True)) if __name__ == '__main__': unittest.main()

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4,300

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0.071542

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0.071542

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0.846184

0.827901

0

0.05335

0.267674

4,300

126

76

34.126984

0.745634

0.179302

0

0.658228

0

0.002363

0

0.075949

1

0.075949

false

0

0.037975

0

0.126582

0

null

0

1

0

null

0

6

94c28927b13867d34579f0b6e6101e1be01282d6

469,245

py

Python

util/data.py

pszwed-ai/fcm_classifier_transformer

48ab1d98be136f71ecbc4ea808b6f8ceaca62a7e

[ "MIT" ]

1

2021-08-23T05:44:40.000Z

util/data.py

pszwed-ai/fcm_classifier_transformer

48ab1d98be136f71ecbc4ea808b6f8ceaca62a7e

[ "MIT" ]

null

util/data.py

pszwed-ai/fcm_classifier_transformer

48ab1d98be136f71ecbc4ea808b6f8ceaca62a7e

[ "MIT" ]

null

import numpy as np from io import StringIO _glass = """1,1.52101,13.64,4.49,1.10,71.78,0.06,8.75,0.00,0.00,1 2,1.51761,13.89,3.60,1.36,72.73,0.48,7.83,0.00,0.00,1 3,1.51618,13.53,3.55,1.54,72.99,0.39,7.78,0.00,0.00,1 4,1.51766,13.21,3.69,1.29,72.61,0.57,8.22,0.00,0.00,1 5,1.51742,13.27,3.62,1.24,73.08,0.55,8.07,0.00,0.00,1 6,1.51596,12.79,3.61,1.62,72.97,0.64,8.07,0.00,0.26,1 7,1.51743,13.30,3.60,1.14,73.09,0.58,8.17,0.00,0.00,1 8,1.51756,13.15,3.61,1.05,73.24,0.57,8.24,0.00,0.00,1 9,1.51918,14.04,3.58,1.37,72.08,0.56,8.30,0.00,0.00,1 10,1.51755,13.00,3.60,1.36,72.99,0.57,8.40,0.00,0.11,1 11,1.51571,12.72,3.46,1.56,73.20,0.67,8.09,0.00,0.24,1 12,1.51763,12.80,3.66,1.27,73.01,0.60,8.56,0.00,0.00,1 13,1.51589,12.88,3.43,1.40,73.28,0.69,8.05,0.00,0.24,1 14,1.51748,12.86,3.56,1.27,73.21,0.54,8.38,0.00,0.17,1 15,1.51763,12.61,3.59,1.31,73.29,0.58,8.50,0.00,0.00,1 16,1.51761,12.81,3.54,1.23,73.24,0.58,8.39,0.00,0.00,1 17,1.51784,12.68,3.67,1.16,73.11,0.61,8.70,0.00,0.00,1 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,3,750,35 ,0 23 ,2,500,26 ,0 23 ,2,500,26 ,0 23 ,8,2000,64 ,0 16 ,3,750,50 ,0 23 ,3,750,33 ,0 21 ,3,750,38 ,0 23 ,2,500,28 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,1 21 ,1,250,21 ,0 21 ,1,250,21 ,0 21 ,5,1250,60 ,0 23 ,4,1000,45 ,0 21 ,4,1000,52 ,0 22 ,1,250,22 ,1 11 ,2,500,70 ,0 23 ,5,1250,58 ,0 23 ,3,750,40 ,0 23 ,3,750,41 ,0 14 ,3,750,83 ,0 21 ,2,500,35 ,0 26 ,5,1250,49 ,1 23 ,6,1500,70 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,4,1000,53 ,0 21 ,6,1500,86 ,0 23 ,3,750,48 ,0 21 ,2,500,41 ,0 21 ,3,750,64 ,0 16 ,2,500,70 ,0 21 ,3,750,70 ,0 23 ,4,1000,87 ,0 23 ,3,750,89 ,0 23 ,2,500,87 ,0 35 ,3,750,64 ,0 38 ,1,250,38 ,0 38 ,1,250,38 ,0 40 ,1,250,40 ,0 74 ,1,250,74 ,0 2 ,43,10750,86 ,1 6 ,22,5500,28 ,1 2 ,34,8500,77 ,1 2 ,44,11000,98 ,0 0 ,26,6500,76 ,1 2 ,41,10250,98 ,1 3 ,21,5250,42 ,1 2 ,11,2750,23 ,0 2 ,21,5250,52 ,1 2 ,13,3250,32 ,1 4 ,4,1000,4 ,1 2 ,11,2750,26 ,0 2 ,11,2750,28 ,0 3 ,14,3500,35 ,0 4 ,16,4000,38 ,1 4 ,6,1500,14 ,0 3 ,5,1250,12 ,1 4 ,33,8250,98 ,1 3 ,10,2500,33 ,1 4 ,10,2500,28 ,1 2 ,11,2750,40 ,1 2 ,11,2750,41 ,1 4 ,13,3250,39 ,1 1 ,10,2500,43 ,1 4 ,9,2250,28 ,0 2 ,4,1000,11 ,0 2 ,5,1250,16 ,1 2 ,15,3750,64 ,0 5 ,24,6000,79 ,0 2 ,6,1500,22 ,1 4 ,5,1250,16 ,1 2 ,4,1000,14 ,1 4 ,8,2000,28 ,0 2 ,4,1000,14 ,0 2 ,6,1500,26 ,0 4 ,5,1250,16 ,1 2 ,7,1750,32 ,1 2 ,6,1500,26 ,1 2 ,8,2000,38 ,1 2 ,2,500,4 ,1 2 ,6,1500,28 ,1 2 ,10,2500,52 ,0 4 ,16,4000,70 ,1 4 ,2,500,4 ,1 1 ,14,3500,95 ,0 4 ,2,500,4 ,1 7 ,14,3500,48 ,0 2 ,3,750,11 ,0 2 ,12,3000,70 ,1 4 ,7,1750,32 ,1 4 ,4,1000,16 ,0 2 ,6,1500,35 ,1 4 ,6,1500,28 ,1 2 ,3,750,14 ,0 2 ,4,1000,23 ,0 4 ,4,1000,18 ,0 5 ,6,1500,28 ,0 4 ,6,1500,30 ,0 14 ,5,1250,14 ,0 3 ,8,2000,50 ,0 4 ,11,2750,64 ,1 4 ,9,2250,52 ,0 4 ,16,4000,98 ,1 7 ,10,2500,47 ,0 4 ,14,3500,86 ,0 2 ,9,2250,75 ,0 4 ,6,1500,35 ,0 4 ,9,2250,55 ,0 4 ,6,1500,35 ,1 2 ,6,1500,45 ,0 2 ,6,1500,47 ,0 4 ,2,500,9 ,0 2 ,2,500,11 ,1 2 ,2,500,11 ,0 2 ,2,500,11 ,1 4 ,6,1500,38 ,1 3 ,4,1000,29 ,1 9 ,9,2250,38 ,0 11 ,5,1250,18 ,0 2 ,3,750,21 ,0 2 ,1,250,2 ,0 2 ,1,250,2 ,1 2 ,1,250,2 ,0 2 ,1,250,2 ,0 2 ,1,250,2 ,0 2 ,1,250,2 ,0 2 ,1,250,2 ,1 2 ,1,250,2 ,0 2 ,1,250,2 ,0 2 ,1,250,2 ,0 2 ,1,250,2 ,0 11 ,11,2750,38 ,0 2 ,3,750,22 ,0 9 ,11,2750,49 ,1 5 ,11,2750,75 ,0 3 ,5,1250,38 ,0 3 ,1,250,3 ,1 4 ,6,1500,43 ,0 2 ,3,750,24 ,0 12 ,11,2750,39 ,0 2 ,2,500,14 ,0 4 ,6,1500,46 ,0 9 ,3,750,14 ,0 14 ,8,2000,26 ,0 4 ,2,500,13 ,0 4 ,11,2750,95 ,0 2 ,7,1750,77 ,0 2 ,7,1750,77 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,1 4 ,1,250,4 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,0 4 ,1,250,4 ,1 4 ,1,250,4 ,0 4 ,7,1750,62 ,0 4 ,1,250,4 ,0 4 ,4,1000,34 ,1 11 ,6,1500,28 ,0 13 ,3,750,14 ,1 7 ,5,1250,35 ,0 9 ,9,2250,54 ,0 11 ,2,500,11 ,0 2 ,5,1250,63 ,0 7 ,11,2750,89 ,0 8 ,9,2250,64 ,0 2 ,2,500,22 ,0 6 ,3,750,26 ,0 12 ,15,3750,71 ,0 13 ,3,750,16 ,0 11 ,16,4000,89 ,0 4 ,5,1250,58 ,0 14 ,7,1750,35 ,0 11 ,4,1000,27 ,0 7 ,9,2250,89 ,1 11 ,8,2000,52 ,1 7 ,5,1250,52 ,0 11 ,6,1500,41 ,0 10 ,5,1250,38 ,0 14 ,2,500,14 ,1 14 ,2,500,14 ,0 14 ,2,500,14 ,0 2 ,2,500,33 ,0 11 ,3,750,23 ,0 14 ,8,2000,46 ,0 9 ,1,250,9 ,0 16 ,5,1250,27 ,0 14 ,4,1000,26 ,0 4 ,2,500,30 ,0 14 ,3,750,21 ,0 16 ,16,4000,77 ,0 4 ,2,500,31 ,0 14 ,8,2000,50 ,0 11 ,3,750,26 ,0 14 ,7,1750,45 ,0 15 ,5,1250,33 ,0 16 ,2,500,16 ,0 16 ,3,750,21 ,0 11 ,8,2000,72 ,0 11 ,1,250,11 ,0 11 ,1,250,11 ,0 11 ,1,250,11 ,0 11 ,1,250,11 ,1 11 ,1,250,11 ,0 2 ,3,750,75 ,1 2 ,3,750,77 ,0 16 ,4,1000,28 ,0 16 ,15,3750,87 ,0 16 ,14,3500,83 ,0 16 ,10,2500,62 ,0 16 ,3,750,23 ,0 14 ,3,750,26 ,0 23 ,19,4750,62 ,0 11 ,7,1750,75 ,0 14 ,3,750,28 ,0 20 ,14,3500,69 ,1 4 ,2,500,46 ,0 11 ,2,500,25 ,0 11 ,3,750,37 ,0 16 ,4,1000,33 ,0 21 ,7,1750,38 ,0 13 ,7,1750,76 ,0 16 ,6,1500,50 ,0 14 ,3,750,33 ,0 14 ,1,250,14 ,0 14 ,1,250,14 ,0 14 ,1,250,14 ,0 14 ,1,250,14 ,0 14 ,1,250,14 ,0 14 ,1,250,14 ,0 17 ,7,1750,58 ,1 14 ,3,750,35 ,0 14 ,3,750,35 ,0 16 ,7,1750,64 ,0 21 ,2,500,21 ,0 16 ,3,750,35 ,0 16 ,1,250,16 ,0 16 ,1,250,16 ,0 16 ,1,250,16 ,0 16 ,1,250,16 ,0 16 ,1,250,16 ,0 14 ,2,500,29 ,0 11 ,4,1000,74 ,0 11 ,2,500,38 ,1 21 ,6,1500,48 ,0 23 ,2,500,23 ,0 23 ,6,1500,45 ,0 14 ,2,500,35 ,1 16 ,6,1500,81 ,0 16 ,4,1000,58 ,0 16 ,5,1250,71 ,0 21 ,2,500,26 ,0 21 ,3,750,35 ,0 21 ,3,750,35 ,0 23 ,8,2000,69 ,0 21 ,3,750,38 ,0 23 ,3,750,35 ,0 21 ,3,750,40 ,0 23 ,2,500,28 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 25 ,6,1500,50 ,0 21 ,1,250,21 ,0 21 ,1,250,21 ,0 23 ,3,750,39 ,0 21 ,2,500,33 ,0 14 ,3,750,79 ,0 23 ,1,250,23 ,1 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,1,250,23 ,0 23 ,4,1000,52 ,0 23 ,1,250,23 ,0 23 ,7,1750,88 ,0 16 ,3,750,86 ,0 23 ,2,500,38 ,0 21 ,2,500,52 ,0 23 ,3,750,62 ,0 39 ,1,250,39 ,0 72 ,1,250,72 ,0""" _balance="""0,1,1,1,1 1,1,1,1,2 1,1,1,1,3 1,1,1,1,4 1,1,1,1,5 1,1,1,2,1 1,1,1,2,2 1,1,1,2,3 1,1,1,2,4 1,1,1,2,5 1,1,1,3,1 1,1,1,3,2 1,1,1,3,3 1,1,1,3,4 1,1,1,3,5 1,1,1,4,1 1,1,1,4,2 1,1,1,4,3 1,1,1,4,4 1,1,1,4,5 1,1,1,5,1 1,1,1,5,2 1,1,1,5,3 1,1,1,5,4 1,1,1,5,5 2,1,2,1,1 0,1,2,1,2 1,1,2,1,3 1,1,2,1,4 1,1,2,1,5 0,1,2,2,1 1,1,2,2,2 1,1,2,2,3 1,1,2,2,4 1,1,2,2,5 1,1,2,3,1 1,1,2,3,2 1,1,2,3,3 1,1,2,3,4 1,1,2,3,5 1,1,2,4,1 1,1,2,4,2 1,1,2,4,3 1,1,2,4,4 1,1,2,4,5 1,1,2,5,1 1,1,2,5,2 1,1,2,5,3 1,1,2,5,4 1,1,2,5,5 2,1,3,1,1 2,1,3,1,2 0,1,3,1,3 1,1,3,1,4 1,1,3,1,5 2,1,3,2,1 1,1,3,2,2 1,1,3,2,3 1,1,3,2,4 1,1,3,2,5 0,1,3,3,1 1,1,3,3,2 1,1,3,3,3 1,1,3,3,4 1,1,3,3,5 1,1,3,4,1 1,1,3,4,2 1,1,3,4,3 1,1,3,4,4 1,1,3,4,5 1,1,3,5,1 1,1,3,5,2 1,1,3,5,3 1,1,3,5,4 1,1,3,5,5 2,1,4,1,1 2,1,4,1,2 2,1,4,1,3 0,1,4,1,4 1,1,4,1,5 2,1,4,2,1 0,1,4,2,2 1,1,4,2,3 1,1,4,2,4 1,1,4,2,5 2,1,4,3,1 1,1,4,3,2 1,1,4,3,3 1,1,4,3,4 1,1,4,3,5 0,1,4,4,1 1,1,4,4,2 1,1,4,4,3 1,1,4,4,4 1,1,4,4,5 1,1,4,5,1 1,1,4,5,2 1,1,4,5,3 1,1,4,5,4 1,1,4,5,5 2,1,5,1,1 2,1,5,1,2 2,1,5,1,3 2,1,5,1,4 0,1,5,1,5 2,1,5,2,1 2,1,5,2,2 1,1,5,2,3 1,1,5,2,4 1,1,5,2,5 2,1,5,3,1 1,1,5,3,2 1,1,5,3,3 1,1,5,3,4 1,1,5,3,5 2,1,5,4,1 1,1,5,4,2 1,1,5,4,3 1,1,5,4,4 1,1,5,4,5 0,1,5,5,1 1,1,5,5,2 1,1,5,5,3 1,1,5,5,4 1,1,5,5,5 2,2,1,1,1 0,2,1,1,2 1,2,1,1,3 1,2,1,1,4 1,2,1,1,5 0,2,1,2,1 1,2,1,2,2 1,2,1,2,3 1,2,1,2,4 1,2,1,2,5 1,2,1,3,1 1,2,1,3,2 1,2,1,3,3 1,2,1,3,4 1,2,1,3,5 1,2,1,4,1 1,2,1,4,2 1,2,1,4,3 1,2,1,4,4 1,2,1,4,5 1,2,1,5,1 1,2,1,5,2 1,2,1,5,3 1,2,1,5,4 1,2,1,5,5 2,2,2,1,1 2,2,2,1,2 2,2,2,1,3 0,2,2,1,4 1,2,2,1,5 2,2,2,2,1 0,2,2,2,2 1,2,2,2,3 1,2,2,2,4 1,2,2,2,5 2,2,2,3,1 1,2,2,3,2 1,2,2,3,3 1,2,2,3,4 1,2,2,3,5 0,2,2,4,1 1,2,2,4,2 1,2,2,4,3 1,2,2,4,4 1,2,2,4,5 1,2,2,5,1 1,2,2,5,2 1,2,2,5,3 1,2,2,5,4 1,2,2,5,5 2,2,3,1,1 2,2,3,1,2 2,2,3,1,3 2,2,3,1,4 2,2,3,1,5 2,2,3,2,1 2,2,3,2,2 0,2,3,2,3 1,2,3,2,4 1,2,3,2,5 2,2,3,3,1 0,2,3,3,2 1,2,3,3,3 1,2,3,3,4 1,2,3,3,5 2,2,3,4,1 1,2,3,4,2 1,2,3,4,3 1,2,3,4,4 1,2,3,4,5 2,2,3,5,1 1,2,3,5,2 1,2,3,5,3 1,2,3,5,4 1,2,3,5,5 2,2,4,1,1 2,2,4,1,2 2,2,4,1,3 2,2,4,1,4 2,2,4,1,5 2,2,4,2,1 2,2,4,2,2 2,2,4,2,3 0,2,4,2,4 1,2,4,2,5 2,2,4,3,1 2,2,4,3,2 1,2,4,3,3 1,2,4,3,4 1,2,4,3,5 2,2,4,4,1 0,2,4,4,2 1,2,4,4,3 1,2,4,4,4 1,2,4,4,5 2,2,4,5,1 1,2,4,5,2 1,2,4,5,3 1,2,4,5,4 1,2,4,5,5 2,2,5,1,1 2,2,5,1,2 2,2,5,1,3 2,2,5,1,4 2,2,5,1,5 2,2,5,2,1 2,2,5,2,2 2,2,5,2,3 2,2,5,2,4 0,2,5,2,5 2,2,5,3,1 2,2,5,3,2 2,2,5,3,3 1,2,5,3,4 1,2,5,3,5 2,2,5,4,1 2,2,5,4,2 1,2,5,4,3 1,2,5,4,4 1,2,5,4,5 2,2,5,5,1 0,2,5,5,2 1,2,5,5,3 1,2,5,5,4 1,2,5,5,5 2,3,1,1,1 2,3,1,1,2 0,3,1,1,3 1,3,1,1,4 1,3,1,1,5 2,3,1,2,1 1,3,1,2,2 1,3,1,2,3 1,3,1,2,4 1,3,1,2,5 0,3,1,3,1 1,3,1,3,2 1,3,1,3,3 1,3,1,3,4 1,3,1,3,5 1,3,1,4,1 1,3,1,4,2 1,3,1,4,3 1,3,1,4,4 1,3,1,4,5 1,3,1,5,1 1,3,1,5,2 1,3,1,5,3 1,3,1,5,4 1,3,1,5,5 2,3,2,1,1 2,3,2,1,2 2,3,2,1,3 2,3,2,1,4 2,3,2,1,5 2,3,2,2,1 2,3,2,2,2 0,3,2,2,3 1,3,2,2,4 1,3,2,2,5 2,3,2,3,1 0,3,2,3,2 1,3,2,3,3 1,3,2,3,4 1,3,2,3,5 2,3,2,4,1 1,3,2,4,2 1,3,2,4,3 1,3,2,4,4 1,3,2,4,5 2,3,2,5,1 1,3,2,5,2 1,3,2,5,3 1,3,2,5,4 1,3,2,5,5 2,3,3,1,1 2,3,3,1,2 2,3,3,1,3 2,3,3,1,4 2,3,3,1,5 2,3,3,2,1 2,3,3,2,2 2,3,3,2,3 2,3,3,2,4 1,3,3,2,5 2,3,3,3,1 2,3,3,3,2 0,3,3,3,3 1,3,3,3,4 1,3,3,3,5 2,3,3,4,1 2,3,3,4,2 1,3,3,4,3 1,3,3,4,4 1,3,3,4,5 2,3,3,5,1 1,3,3,5,2 1,3,3,5,3 1,3,3,5,4 1,3,3,5,5 2,3,4,1,1 2,3,4,1,2 2,3,4,1,3 2,3,4,1,4 2,3,4,1,5 2,3,4,2,1 2,3,4,2,2 2,3,4,2,3 2,3,4,2,4 2,3,4,2,5 2,3,4,3,1 2,3,4,3,2 2,3,4,3,3 0,3,4,3,4 1,3,4,3,5 2,3,4,4,1 2,3,4,4,2 0,3,4,4,3 1,3,4,4,4 1,3,4,4,5 2,3,4,5,1 2,3,4,5,2 1,3,4,5,3 1,3,4,5,4 1,3,4,5,5 2,3,5,1,1 2,3,5,1,2 2,3,5,1,3 2,3,5,1,4 2,3,5,1,5 2,3,5,2,1 2,3,5,2,2 2,3,5,2,3 2,3,5,2,4 2,3,5,2,5 2,3,5,3,1 2,3,5,3,2 2,3,5,3,3 2,3,5,3,4 0,3,5,3,5 2,3,5,4,1 2,3,5,4,2 2,3,5,4,3 1,3,5,4,4 1,3,5,4,5 2,3,5,5,1 2,3,5,5,2 0,3,5,5,3 1,3,5,5,4 1,3,5,5,5 2,4,1,1,1 2,4,1,1,2 2,4,1,1,3 0,4,1,1,4 1,4,1,1,5 2,4,1,2,1 0,4,1,2,2 1,4,1,2,3 1,4,1,2,4 1,4,1,2,5 2,4,1,3,1 1,4,1,3,2 1,4,1,3,3 1,4,1,3,4 1,4,1,3,5 0,4,1,4,1 1,4,1,4,2 1,4,1,4,3 1,4,1,4,4 1,4,1,4,5 1,4,1,5,1 1,4,1,5,2 1,4,1,5,3 1,4,1,5,4 1,4,1,5,5 2,4,2,1,1 2,4,2,1,2 2,4,2,1,3 2,4,2,1,4 2,4,2,1,5 2,4,2,2,1 2,4,2,2,2 2,4,2,2,3 0,4,2,2,4 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0.3,0.37,0.4,0.45,0.5,0.0,0.48,0.41,6 0.57,0.59,0.49,0.86,0.5,0.0,0.47,0.22,1 0.38,0.4,0.39,0.19,0.5,0.0,0.46,0.62,1 0.77,0.74,0.37,0.29,0.5,0.0,0.45,0.22,3 0.47,0.38,0.58,0.19,0.5,0.0,0.57,0.22,2 0.5,0.61,0.44,0.2,0.5,0.0,0.49,0.22,0 0.41,0.45,0.46,0.23,0.5,0.0,0.5,0.7,2 0.46,0.62,0.46,0.54,0.5,0.0,0.51,0.27,0 0.74,0.75,0.45,0.44,0.5,0.0,0.52,0.22,8 0.52,0.53,0.58,0.69,0.5,0.0,0.5,0.22,0 0.41,0.47,0.5,0.14,0.5,0.0,0.53,0.37,1 0.25,0.4,0.52,0.15,0.5,0.0,0.56,0.28,1 0.58,0.56,0.38,0.39,0.5,0.0,0.54,0.57,1 0.32,0.29,0.29,0.08,0.5,0.0,0.52,0.22,6 0.38,0.48,0.57,0.3,0.5,0.0,0.41,0.11,2 0.39,0.58,0.47,0.18,0.5,0.0,0.48,0.22,0 0.38,0.47,0.47,0.18,0.5,0.0,0.44,0.26,0 0.63,0.57,0.5,0.48,0.5,0.0,0.51,0.22,0 0.51,0.45,0.62,0.25,0.5,0.0,0.59,0.22,0 0.59,0.67,0.54,0.19,0.5,0.0,0.48,0.6,1 0.6,0.61,0.54,0.11,0.5,0.0,0.46,0.22,2 0.48,0.61,0.57,0.17,0.5,0.0,0.45,0.22,2 0.71,0.5,0.5,0.18,0.5,0.0,0.46,0.22,2 0.61,0.48,0.54,0.25,0.5,0.0,0.5,0.22,2 0.38,0.32,0.64,0.41,0.5,0.0,0.44,0.11,2 0.38,0.4,0.66,0.35,0.5,0.0,0.43,0.11,2 0.81,0.62,0.43,0.17,0.5,0.0,0.53,0.22,5 0.47,0.43,0.61,0.4,0.5,0.0,0.48,0.47,1 0.67,0.57,0.36,0.19,0.5,0.0,0.56,0.22,5 0.43,0.4,0.6,0.16,0.5,0.0,0.53,0.39,1 0.65,0.54,0.54,0.13,0.5,0.0,0.53,0.22,2 """ _tic_tac_toe="""0,0,0,0,2,2,0,2,2,0 0,0,0,0,2,2,2,0,2,0 0,0,0,0,2,2,2,2,0,0 0,0,0,0,2,2,2,1,1,0 0,0,0,0,2,2,1,2,1,0 0,0,0,0,2,2,1,1,2,0 0,0,0,0,2,1,2,2,1,0 0,0,0,0,2,1,2,1,2,0 0,0,0,0,2,1,1,2,2,0 0,0,0,0,1,2,2,2,1,0 0,0,0,0,1,2,2,1,2,0 0,0,0,0,1,2,1,2,2,0 0,0,0,2,0,2,0,2,2,0 0,0,0,2,0,2,2,0,2,0 0,0,0,2,0,2,2,2,0,0 0,0,0,2,0,2,2,1,1,0 0,0,0,2,0,2,1,2,1,0 0,0,0,2,0,2,1,1,2,0 0,0,0,2,0,1,2,2,1,0 0,0,0,2,0,1,2,1,2,0 0,0,0,2,0,1,1,2,2,0 0,0,0,2,2,0,0,2,2,0 0,0,0,2,2,0,2,0,2,0 0,0,0,2,2,0,2,2,0,0 0,0,0,2,2,0,2,1,1,0 0,0,0,2,2,0,1,2,1,0 0,0,0,2,2,0,1,1,2,0 0,0,0,2,2,1,0,2,1,0 0,0,0,2,2,1,0,1,2,0 0,0,0,2,2,1,2,0,1,0 0,0,0,2,2,1,2,1,0,0 0,0,0,2,2,1,1,0,2,0 0,0,0,2,2,1,1,2,0,0 0,0,0,2,2,1,1,1,1,0 0,0,0,2,1,0,2,2,1,0 0,0,0,2,1,0,2,1,2,0 0,0,0,2,1,0,1,2,2,0 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2,1,0,2,0,1,0,2,0,0 2,1,0,2,0,1,0,1,1,0 2,1,0,2,2,0,0,1,0,0 2,1,0,2,2,0,1,0,0,0 2,1,0,2,2,1,0,0,0,0 2,1,0,2,1,0,0,2,0,0 2,1,0,2,1,0,1,1,0,0 2,1,0,2,1,2,0,0,0,0 2,1,0,1,0,0,0,2,2,0 2,1,0,1,0,0,2,2,0,0 2,1,0,1,0,2,0,0,2,0 2,1,0,1,0,2,0,2,0,0 2,1,0,1,0,2,0,1,1,0 2,1,0,1,0,1,0,2,1,0 2,1,0,1,0,1,0,1,2,0 2,1,0,1,2,0,0,2,0,0 2,1,0,1,2,0,2,0,0,0 2,1,0,1,2,0,1,1,0,0 2,1,0,1,2,2,0,0,0,0 2,1,0,1,1,0,2,1,0,0 2,1,0,1,1,0,1,2,0,0 2,1,2,0,0,0,0,2,1,0 2,1,2,0,0,0,0,1,2,0 2,1,2,0,0,0,2,0,1,0 2,1,2,0,0,0,2,1,0,0 2,1,2,0,0,0,1,0,2,0 2,1,2,0,0,0,1,2,0,0 2,1,2,0,0,0,1,1,1,0 2,1,2,0,2,1,0,0,0,0 2,1,2,0,1,2,0,0,0,0 2,1,2,2,0,1,0,0,0,0 2,1,2,2,1,0,0,0,0,0 2,1,2,1,0,2,0,0,0,0 2,1,2,1,2,0,0,0,0,0 2,1,2,1,1,1,0,0,0,0 2,1,1,0,0,0,0,2,2,0 2,1,1,0,0,0,2,0,2,0 2,1,1,0,0,0,2,2,0,0 2,1,1,0,0,0,2,1,1,0 2,1,1,0,0,0,1,2,1,0 2,1,1,0,0,0,1,1,2,0 2,1,1,0,2,2,0,0,0,0 2,1,1,2,0,2,0,0,0,0 2,1,1,2,2,0,0,0,0,0 2,1,1,2,1,1,0,0,0,0 2,1,1,1,2,1,0,0,0,0 2,1,1,1,1,2,0,0,0,0 1,0,0,2,0,2,0,2,1,0 1,0,0,2,0,2,0,1,2,0 1,0,0,2,0,2,2,0,1,0 1,0,0,2,0,2,1,0,2,0 1,0,0,2,0,1,0,2,2,0 1,0,0,2,0,1,2,0,2,0 1,0,0,2,2,0,2,1,0,0 1,0,0,2,2,0,1,2,0,0 1,0,0,2,1,0,2,2,0,0 1,0,0,1,0,2,0,2,2,0 1,0,0,1,0,2,2,0,2,0 1,0,0,1,2,0,2,2,0,0 1,0,2,0,0,0,2,2,1,0 1,0,2,0,0,0,2,1,2,0 1,0,2,0,0,0,1,2,2,0 1,0,2,0,0,2,2,0,1,0 1,0,2,0,0,1,2,0,2,0 1,0,2,2,0,0,2,0,1,0 1,0,2,2,0,0,1,0,2,0 1,0,2,2,0,2,0,0,1,0 1,0,2,2,0,2,1,0,0,0 1,0,2,2,0,1,0,0,2,0 1,0,2,2,0,1,2,0,0,0 1,0,2,2,0,1,1,0,1,0 1,0,2,2,2,1,0,0,0,0 1,0,2,2,1,2,0,0,0,0 1,0,2,1,0,0,2,0,2,0 1,0,2,1,0,2,2,0,0,0 1,0,2,1,0,2,1,0,1,0 1,0,2,1,0,1,2,0,1,0 1,0,2,1,0,1,1,0,2,0 1,0,2,1,2,2,0,0,0,0 1,0,1,0,0,2,2,0,2,0 1,0,1,2,0,0,2,0,2,0 1,0,1,2,0,2,0,0,2,0 1,0,1,2,0,2,2,0,0,0 1,0,1,2,0,2,1,0,1,0 1,0,1,2,0,1,2,0,1,0 1,0,1,2,0,1,1,0,2,0 1,0,1,1,0,2,2,0,1,0 1,0,1,1,0,2,1,0,2,0 1,0,1,1,0,1,2,0,2,0 1,2,0,0,0,0,2,2,1,0 1,2,0,0,0,0,2,1,2,0 1,2,0,0,0,0,1,2,2,0 1,2,0,0,0,2,0,2,1,0 1,2,0,0,0,2,0,1,2,0 1,2,0,0,0,1,0,2,2,0 1,2,0,0,2,0,2,1,0,0 1,2,0,0,1,0,2,2,0,0 1,2,0,2,0,0,0,2,1,0 1,2,0,2,0,0,0,1,2,0 1,2,0,2,0,0,2,1,0,0 1,2,0,2,0,0,1,2,0,0 1,2,0,2,0,2,0,0,1,0 1,2,0,2,0,2,0,1,0,0 1,2,0,2,0,1,0,0,2,0 1,2,0,2,0,1,0,2,0,0 1,2,0,2,0,1,0,1,1,0 1,2,0,2,2,0,0,1,0,0 1,2,0,2,2,0,1,0,0,0 1,2,0,2,2,1,0,0,0,0 1,2,0,2,1,0,0,2,0,0 1,2,0,2,1,0,2,0,0,0 1,2,0,2,1,0,1,1,0,0 1,2,0,2,1,2,0,0,0,0 1,2,0,1,0,0,0,2,2,0 1,2,0,1,0,0,2,2,0,0 1,2,0,1,0,2,0,0,2,0 1,2,0,1,0,2,0,2,0,0 1,2,0,1,0,2,0,1,1,0 1,2,0,1,0,1,0,2,1,0 1,2,0,1,0,1,0,1,2,0 1,2,0,1,2,0,2,0,0,0 1,2,0,1,2,0,1,1,0,0 1,2,0,1,2,2,0,0,0,0 1,2,0,1,1,0,2,1,0,0 1,2,0,1,1,0,1,2,0,0 1,2,2,0,0,0,0,2,1,0 1,2,2,0,0,0,0,1,2,0 1,2,2,0,0,0,2,0,1,0 1,2,2,0,0,0,2,1,0,0 1,2,2,0,0,0,1,0,2,0 1,2,2,0,0,0,1,2,0,0 1,2,2,0,0,0,1,1,1,0 1,2,2,0,2,1,0,0,0,0 1,2,2,0,1,2,0,0,0,0 1,2,2,2,0,1,0,0,0,0 1,2,2,2,1,0,0,0,0,0 1,2,2,1,0,2,0,0,0,0 1,2,2,1,2,0,0,0,0,0 1,2,2,1,1,1,0,0,0,0 1,2,1,0,0,0,0,2,2,0 1,2,1,0,0,0,2,0,2,0 1,2,1,0,0,0,2,2,0,0 1,2,1,0,0,0,2,1,1,0 1,2,1,0,0,0,1,2,1,0 1,2,1,0,0,0,1,1,2,0 1,2,1,0,2,2,0,0,0,0 1,2,1,2,0,2,0,0,0,0 1,2,1,2,2,0,0,0,0,0 1,2,1,2,1,1,0,0,0,0 1,2,1,1,2,1,0,0,0,0 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1,12,1,0,766,2,1,4,0,0,3,0,66,0,0,1,1,1,1,0,1 1,15,0,0,2728,0,2,4,0,1,2,0,35,1,0,3,0,1,0,0,0 3,12,1,0,1881,1,1,2,1,0,2,3,44,0,2,1,1,1,0,0,0 3,6,1,3,709,3,4,2,3,0,2,0,27,0,0,1,3,1,1,1,0 1,36,1,0,4795,1,4,4,1,0,1,2,30,0,0,1,2,1,0,0,0 0,27,1,0,3416,1,1,3,0,0,2,3,27,0,0,1,2,1,1,0,0 0,18,1,2,2462,1,1,2,0,0,2,3,22,0,0,1,0,1,1,0,1 2,21,0,2,2288,1,4,4,1,0,4,1,23,0,0,1,0,1,0,0,0 1,48,4,5,3566,4,2,4,0,0,2,3,30,0,0,1,0,1,1,0,0 0,6,0,3,860,1,0,1,1,0,4,2,39,0,0,2,0,1,0,0,0 2,12,0,3,682,4,2,4,1,0,3,3,51,0,0,2,0,1,0,0,0 0,36,0,2,5371,1,1,3,0,1,2,1,28,0,0,2,0,1,1,0,0 2,18,0,0,1582,3,0,4,0,0,4,3,46,0,0,2,0,1,1,0,0 2,6,1,0,1346,4,0,2,0,0,4,2,42,1,1,1,0,2,0,0,0 2,10,1,0,1924,1,1,1,0,0,4,1,38,0,0,1,0,1,0,1,0 3,36,1,0,5848,1,1,4,0,0,1,3,24,0,0,1,0,1,1,0,0 1,24,0,4,7758,3,0,2,1,0,4,2,29,0,2,1,0,1,1,0,0 1,24,2,5,6967,4,2,4,0,0,4,3,36,0,2,1,2,1,0,0,0 0,12,1,2,1282,1,1,2,1,0,4,3,20,0,2,1,0,1,1,0,1 0,9,0,7,1288,4,0,3,0,1,4,0,48,0,0,2,0,2,1,1,0 0,12,4,9,339,1,0,4,3,0,1,3,45,1,0,1,1,1,1,0,0 1,24,1,3,3512,4,2,2,0,0,3,3,38,1,0,2,0,1,0,0,0 2,6,0,0,1898,0,1,1,0,0,2,0,34,0,0,2,1,2,1,0,0 2,24,0,0,2872,4,0,3,0,0,4,0,36,0,0,1,0,2,0,0,0 2,18,0,3,1055,1,4,4,1,0,1,1,30,0,0,2,0,1,1,0,0 2,15,1,6,1262,2,2,4,0,0,3,1,36,0,0,2,0,1,0,0,0 1,10,1,3,7308,1,3,2,0,0,4,2,70,1,1,1,2,1,0,0,0 2,36,1,3,909,2,0,4,0,0,4,1,36,0,0,1,0,1,1,0,0 2,6,1,2,2978,2,1,1,0,0,2,3,32,0,0,1,0,1,0,0,0 0,18,1,2,1131,1,3,4,1,0,2,3,33,0,0,1,0,1,1,0,1 1,11,1,2,1577,3,4,4,1,0,1,0,20,0,0,1,0,1,1,0,0 2,24,1,2,3972,1,2,2,1,0,4,1,25,0,2,1,0,1,0,0,0 1,24,0,5,1935,1,0,4,2,0,4,0,31,0,0,2,0,1,0,0,1 0,15,3,3,950,1,0,4,0,0,3,3,33,0,2,2,0,2,1,0,1 2,12,1,2,763,1,1,4,1,0,1,0,26,0,0,1,0,1,0,0,0 1,24,2,2,2064,1,3,3,1,0,2,1,34,0,0,1,2,1,0,0,1 1,8,1,0,1414,1,1,4,0,1,2,0,33,0,0,1,0,1,1,1,0 0,21,2,1,3414,1,4,2,0,0,1,1,26,0,0,2,0,1,1,0,1 2,30,4,4,7485,0,3,4,1,0,1,0,53,1,0,1,2,1,0,0,1 0,12,1,2,2577,1,1,2,2,0,1,3,42,0,0,1,0,1,1,0,0 0,6,0,0,338,2,0,4,0,0,4,3,52,0,0,2,0,1,1,0,0 2,12,1,0,1963,1,2,4,0,0,2,3,31,0,2,2,2,2,0,0,0 0,21,0,3,571,1,0,4,0,0,4,0,65,0,0,2,0,1,1,0,0 2,36,2,5,9572,1,4,1,2,0,1,3,28,0,0,2,0,1,1,0,1 1,36,2,5,4455,1,1,2,2,0,2,0,30,2,0,2,2,1,0,0,1 0,21,4,3,1647,0,1,4,0,0,2,1,40,0,0,2,1,2,1,0,1 2,24,0,2,3777,3,1,4,0,0,4,0,50,0,0,1,0,1,0,0,0 1,18,0,3,884,1,0,4,0,0,4,3,36,1,0,1,0,2,0,0,1 2,15,0,0,1360,1,1,4,0,0,2,1,31,0,0,2,0,1,1,0,0 1,9,4,4,5129,1,0,2,1,0,4,2,74,1,1,1,2,2,0,0,1 1,16,0,3,1175,1,3,2,0,0,3,3,68,0,1,3,3,1,0,0,0 0,12,1,0,674,4,2,4,3,0,1,1,20,0,0,1,0,1,1,0,1 1,18,3,2,3244,1,1,1,1,0,4,3,33,1,0,2,0,1,0,0,0 2,24,1,5,4591,3,1,2,0,0,3,1,54,0,0,3,2,1,0,0,1 1,48,3,5,3844,4,2,4,0,0,4,2,34,0,1,1,1,2,1,0,1 1,27,1,5,3915,1,1,4,0,0,2,3,36,0,0,1,0,2,0,0,1 2,6,1,0,2108,1,2,2,3,0,2,0,29,0,2,1,0,1,1,0,0 1,45,1,0,3031,4,1,4,0,1,4,1,21,0,2,1,0,1,1,0,1 1,9,0,1,1501,1,0,2,1,0,3,3,34,0,0,2,2,1,0,0,1 2,6,0,0,1382,1,1,1,1,0,1,3,28,0,0,2,0,1,0,0,0 1,12,1,2,951,4,4,4,1,0,4,3,27,1,2,4,0,1,1,0,1 1,24,1,4,2760,0,0,4,0,0,4,2,36,1,1,1,0,1,0,0,0 1,18,2,2,4297,1,0,4,2,0,3,2,40,0,0,1,2,1,0,0,1 2,9,0,1,936,2,0,4,0,0,2,3,52,0,0,2,0,1,0,0,0 0,12,1,3,1168,1,1,4,3,0,3,0,27,0,0,1,1,1,1,0,0 2,27,2,5,5117,1,2,3,0,0,4,3,26,0,0,2,0,1,1,0,0 0,12,1,9,902,1,2,4,3,0,4,1,21,0,2,1,0,1,1,0,1 2,12,0,3,1495,1,0,4,0,0,1,0,38,0,0,2,1,2,1,0,0 0,30,0,4,10623,1,0,3,0,0,4,2,38,0,1,3,2,2,0,0,0 2,12,0,2,1935,1,0,4,0,0,4,0,43,0,0,3,0,1,0,0,0 1,12,0,6,1424,1,2,4,0,0,3,1,26,0,0,1,0,1,1,0,0 0,24,1,5,6568,1,1,2,3,0,2,3,21,2,0,1,1,1,1,0,0 2,12,1,4,1413,3,2,3,0,0,2,1,55,0,0,1,0,1,1,1,0 2,9,0,0,3074,0,1,1,0,0,2,0,33,0,0,2,0,2,1,0,0 2,36,1,0,3835,0,0,2,1,0,4,0,45,0,0,1,1,1,0,0,0 0,27,3,5,5293,1,3,2,0,0,4,1,50,2,0,2,0,1,0,0,1 3,30,2,5,1908,1,0,4,0,0,4,0,66,0,0,1,2,1,0,0,1 2,36,0,0,3342,0,0,4,0,0,2,3,51,0,0,1,0,1,0,0,0 1,6,0,9,932,0,2,1,1,0,3,1,39,0,0,2,1,1,1,0,0 0,18,3,5,3104,1,2,3,0,0,1,1,31,1,0,1,0,1,0,0,0 3,36,1,0,3913,1,1,2,0,0,2,0,23,0,0,1,0,1,0,0,0 0,24,1,2,3021,1,1,2,2,0,2,0,24,0,2,1,1,1,1,0,0 2,10,1,3,1364,1,1,2,1,0,4,3,64,0,0,1,0,1,0,0,0 1,12,1,0,625,1,4,4,3,1,1,0,26,1,0,1,1,1,1,0,0 0,12,1,1,1200,0,1,4,1,0,4,1,23,1,2,1,0,1,0,0,0 2,12,1,0,707,1,1,4,0,0,2,0,30,1,0,2,0,1,1,0,0 2,24,2,5,2978,0,1,4,0,0,4,0,32,0,0,2,0,2,0,0,0 2,15,1,4,4657,1,1,3,0,0,2,3,30,0,0,1,0,1,0,0,0 2,36,3,7,2613,1,1,4,0,0,2,3,27,0,0,2,0,1,1,0,0 1,48,1,0,10961,3,2,1,0,2,2,2,27,1,0,2,0,1,0,0,1 0,12,1,2,7865,1,0,4,0,0,4,2,53,0,1,1,2,1,0,0,1 2,9,1,0,1478,1,2,4,0,0,2,3,22,0,0,1,0,1,1,0,1 0,24,1,2,3149,1,4,4,0,0,1,2,22,1,1,1,0,1,1,0,0 3,36,1,0,4210,1,1,4,0,0,2,3,26,0,0,1,0,1,1,0,1 2,9,1,3,2507,2,0,2,0,0,4,2,51,0,1,1,1,1,1,0,0 2,12,1,0,2141,4,2,3,0,0,1,2,35,0,0,1,0,1,1,0,0 1,18,1,0,866,1,1,4,3,1,2,0,25,0,0,1,1,1,1,0,0 2,4,0,0,1544,1,2,2,0,0,1,0,42,0,0,3,1,2,1,0,0 0,24,1,0,1823,1,3,4,0,0,2,3,30,2,0,1,2,2,1,0,1 1,6,1,3,14555,0,3,1,0,0,2,1,23,0,0,1,3,1,0,0,1 1,21,1,5,2767,4,0,4,2,0,2,3,61,1,2,2,1,1,1,0,1 2,12,0,0,1291,1,1,4,1,0,2,1,35,0,0,2,0,1,1,0,0 0,30,1,0,2522,1,0,1,0,1,3,1,39,0,0,1,0,2,1,0,0 0,24,1,3,915,0,0,4,1,0,2,3,29,1,0,1,0,1,1,0,1 2,6,1,0,1595,1,2,3,0,0,2,1,51,0,0,1,0,2,1,0,0 0,48,3,4,4605,1,0,3,0,0,4,2,24,0,1,2,0,2,1,0,1 2,12,0,5,1185,1,1,3,1,0,2,0,27,0,0,2,0,1,1,0,0 2,12,4,9,3447,2,1,4,1,0,3,0,35,0,0,1,1,2,1,0,0 2,24,1,5,1258,1,2,4,0,0,1,0,25,0,0,1,0,1,0,0,0 2,12,0,0,717,1,0,4,0,0,4,0,52,0,0,3,0,1,1,0,0 2,6,3,3,1204,4,1,4,0,0,1,2,35,1,2,1,0,1,1,1,0 3,24,1,2,1925,1,1,2,0,0,2,0,26,0,0,1,0,1,1,0,0 2,18,1,0,433,1,3,3,1,2,4,0,22,0,2,1,0,1,1,0,1 0,6,0,3,666,3,2,3,1,0,4,0,39,0,0,2,1,1,0,0,0 3,12,1,2,2251,1,1,1,1,0,2,3,46,0,0,1,1,1,1,0,0 1,30,1,3,2150,1,1,4,1,1,2,2,24,1,0,1,0,1,1,0,1 2,24,2,2,4151,4,1,2,0,0,3,1,35,0,0,2,0,1,1,0,0 1,9,1,2,2030,0,2,2,0,0,1,3,24,0,0,1,0,1,0,0,0 1,60,2,0,7418,0,1,1,0,0,1,0,27,0,0,1,1,1,1,0,0 2,24,0,0,2684,1,1,4,0,0,2,0,35,0,0,2,1,1,1,0,0 0,12,4,0,2149,1,1,4,2,0,1,2,29,0,1,1,0,1,1,0,1 2,15,1,4,3812,4,4,1,1,0,4,3,23,0,0,1,0,1,0,0,0 2,11,0,0,1154,4,3,4,1,0,4,0,57,0,0,3,1,1,1,0,0 0,12,1,2,1657,1,1,2,0,0,2,0,27,0,0,1,0,1,1,0,0 0,24,1,0,1603,1,0,4,1,0,4,3,55,0,0,1,0,1,1,0,0 0,18,0,3,5302,1,0,2,0,0,4,2,36,0,1,3,2,1,0,0,0 2,12,0,1,2748,1,0,2,1,0,4,2,57,1,1,3,1,1,1,0,0 2,10,0,3,1231,1,0,3,0,0,4,0,32,0,0,2,1,2,1,1,0 1,15,1,0,802,1,0,4,0,0,3,3,37,0,0,1,0,2,1,0,1 2,36,0,5,6304,0,0,4,0,0,4,0,36,0,0,2,0,1,1,0,0 2,24,1,0,1533,1,4,4,1,0,3,3,38,2,0,1,0,1,0,0,0 0,14,1,3,8978,1,0,1,2,0,4,1,45,0,0,1,2,1,0,1,1 2,24,1,0,999,0,0,4,0,0,2,3,25,0,0,2,0,1,1,0,0 2,18,1,3,2662,0,2,4,0,0,3,1,32,0,0,1,0,1,1,1,0 2,12,0,2,1402,2,2,3,1,0,4,3,37,0,2,1,0,1,0,0,0 1,48,4,3,12169,0,3,4,0,2,4,2,36,0,1,1,2,1,0,0,0 1,48,1,0,3060,1,2,4,0,0,4,0,28,0,0,2,0,1,1,0,1 0,30,1,7,11998,1,4,1,2,0,1,2,34,0,0,1,1,1,0,0,1 2,9,1,0,2697,1,1,1,0,0,2,0,32,0,0,1,0,2,1,0,0 2,18,0,0,2404,1,1,2,1,0,2,3,26,0,0,2,0,1,1,0,0 0,12,1,2,1262,0,0,2,2,0,4,1,49,0,0,1,1,1,0,0,0 2,6,1,2,4611,1,4,1,1,0,4,1,32,0,0,1,0,1,1,0,1 2,24,1,0,1901,4,1,4,0,0,4,3,29,0,2,1,2,1,0,0,0 2,15,0,4,3368,3,0,3,0,0,4,2,23,0,2,2,0,1,0,0,0 2,12,1,2,1574,1,1,4,0,0,2,0,50,0,0,1,0,1,1,0,0 3,18,4,0,1445,0,2,4,0,0,4,3,49,1,0,1,1,1,1,0,0 2,15,0,2,1520,0,0,4,0,0,4,1,63,0,0,1,0,1,1,0,0 1,24,0,3,3878,4,4,4,2,0,2,3,37,0,0,1,0,1,0,0,0 0,47,1,3,10722,1,4,1,1,0,1,0,35,0,0,1,1,1,0,0,0 0,48,1,4,4788,1,2,4,0,0,3,1,26,0,0,1,0,2,1,0,0 1,48,2,8,7582,4,3,2,0,0,4,2,31,0,1,1,2,1,0,0,0 1,12,1,0,1092,1,1,4,1,1,4,0,49,0,0,2,0,1,0,0,0 0,24,2,0,1024,1,4,4,3,0,4,0,48,2,0,1,0,1,1,0,1 2,12,1,5,1076,1,1,2,3,0,2,0,26,0,0,1,0,1,0,1,0 1,36,1,4,9398,1,4,1,3,0,4,3,28,0,2,1,2,1,0,0,1 0,24,0,4,6419,1,0,2,1,0,4,2,44,0,1,2,2,2,0,0,0 3,42,0,4,4796,1,0,4,0,0,4,2,56,0,1,1,0,1,1,0,0 2,48,0,5,7629,0,0,4,2,0,2,3,46,1,0,2,2,2,1,0,0 1,48,1,2,9960,1,4,1,1,0,2,3,26,0,0,1,0,1,0,0,1 2,12,1,4,4675,0,4,1,1,0,4,3,20,0,2,1,0,1,1,0,0 2,10,1,3,1287,0,0,4,0,2,2,1,45,0,0,1,1,1,1,1,0 2,18,1,2,2515,1,1,3,0,0,4,0,43,0,0,1,0,1,0,0,0 1,21,0,2,2745,3,2,3,0,0,2,3,32,0,0,2,0,1,0,0,0 2,6,1,3,672,1,3,1,1,0,4,0,54,0,0,1,3,1,0,0,0 1,36,3,0,3804,1,1,4,1,0,1,3,42,0,0,1,0,1,0,0,1 3,24,0,3,1344,0,2,4,0,0,2,0,37,1,0,2,1,2,1,0,1 0,10,0,3,1038,1,2,4,0,2,3,1,49,0,0,2,0,1,0,0,0 2,48,0,3,10127,2,1,2,0,0,2,2,44,1,1,1,0,1,1,0,1 2,6,1,2,1543,3,1,4,2,0,2,0,33,0,0,1,0,1,1,0,0 2,30,1,4,4811,0,2,2,1,0,4,1,24,2,2,1,1,1,1,0,0 0,12,1,0,727,4,4,4,3,0,3,2,33,0,0,1,1,1,0,0,1 1,8,1,2,1237,1,1,3,1,0,4,0,24,0,0,1,0,1,1,0,1 1,9,1,3,276,1,1,4,3,0,4,0,22,0,2,1,1,1,1,0,0 1,48,1,8,5381,0,3,3,0,0,4,2,40,1,1,1,3,1,0,0,0 2,24,1,2,5511,4,1,4,0,0,1,3,25,2,0,1,0,1,1,0,0 3,24,1,2,3749,1,4,2,1,0,4,3,26,0,0,1,0,1,1,0,0 1,12,1,3,685,1,2,2,3,0,3,3,25,1,0,1,1,1,1,0,1 3,4,1,3,1494,0,4,1,0,0,2,0,29,0,0,1,1,2,1,1,0 0,36,4,2,2746,1,0,4,0,0,4,3,31,1,0,1,0,1,1,0,1 0,12,1,2,708,1,1,2,0,1,3,1,38,0,0,1,1,2,1,0,0 1,24,1,2,4351,0,1,1,1,0,4,1,48,0,0,1,1,1,0,0,0 2,12,0,1,701,1,1,4,0,0,2,3,32,0,0,2,0,1,1,0,0 0,15,2,2,3643,1,0,1,1,0,4,1,27,0,0,2,1,1,1,0,0 1,30,0,3,4249,1,3,4,3,0,2,3,28,0,0,2,2,1,1,0,1 0,24,1,0,1938,1,4,4,2,0,3,1,32,0,0,1,0,1,1,0,1 0,24,1,4,2910,1,2,2,0,0,1,2,34,0,1,1,2,1,0,0,0 0,18,1,2,2659,3,1,4,0,0,2,3,28,0,0,1,0,1,1,0,0 2,18,0,3,1028,1,1,4,1,0,3,0,36,0,0,2,0,1,1,0,0 0,8,0,3,3398,1,2,1,0,0,4,0,39,0,0,2,1,1,1,1,0 2,12,0,2,5801,0,0,2,0,0,4,1,49,0,2,1,0,1,0,0,0 2,24,1,3,1525,3,2,4,1,0,3,3,34,0,0,1,0,2,0,0,0 3,36,1,0,4473,1,0,4,0,0,2,3,31,0,0,1,0,1,1,0,0 1,6,1,0,1068,1,0,4,0,0,4,3,28,0,0,1,0,2,1,0,0 0,24,0,4,6615,1,3,2,0,0,4,2,75,0,1,2,2,1,0,0,0 2,18,0,1,1864,4,1,4,1,0,2,0,30,0,0,2,0,1,1,0,1 1,60,1,3,7408,4,4,4,1,0,2,1,24,0,0,1,2,1,1,0,1 2,48,0,4,11590,4,1,2,1,0,4,3,24,1,2,2,1,1,1,0,1 0,24,3,2,4110,1,0,3,0,0,4,2,23,1,2,2,0,2,1,0,1 0,6,0,2,3384,1,1,1,2,0,4,0,44,0,2,1,2,1,0,0,1 1,13,1,0,2101,1,4,2,1,1,4,1,23,0,0,1,1,1,1,0,0 0,15,1,6,1275,0,1,4,1,0,2,3,24,0,2,1,0,1,1,0,1 0,24,1,2,4169,1,1,4,0,0,4,1,28,0,0,1,0,1,1,0,0 1,10,1,2,1521,1,1,4,2,0,2,3,31,0,0,1,1,1,1,0,0 1,24,0,1,5743,1,4,2,1,0,4,2,24,0,1,2,0,1,0,0,0 0,21,1,2,3599,1,2,1,1,0,4,3,26,0,2,1,1,1,1,0,0 1,18,1,0,3213,2,4,1,3,0,3,0,25,0,2,1,0,1,1,0,0 1,18,1,5,4439,1,0,1,0,2,1,0,33,1,0,1,2,1,0,0,0 3,10,1,3,3949,1,4,1,0,1,1,1,37,0,0,1,1,2,1,0,0 2,15,0,0,1459,1,1,4,1,0,2,3,43,0,0,1,1,1,1,0,0 1,13,0,0,882,1,4,4,0,1,4,0,23,0,0,2,0,1,1,0,0 1,24,1,0,3758,2,3,1,1,0,4,2,23,0,2,1,3,1,1,0,0 2,6,2,5,1743,4,1,1,0,0,2,0,34,0,0,2,1,1,1,0,0 1,9,0,1,1136,3,0,4,0,0,3,2,32,0,1,2,0,2,1,0,1 2,9,1,6,1236,1,4,1,1,0,4,0,23,0,2,1,0,1,0,0,0 1,9,1,2,959,1,1,1,1,0,2,3,29,0,0,1,0,1,1,1,1 2,18,0,4,3229,0,3,2,0,0,4,2,38,0,0,1,2,1,0,0,0 0,12,3,0,6199,1,1,4,0,0,2,1,28,0,2,2,0,1,0,0,1 2,10,1,1,727,2,0,4,0,0,4,2,46,0,1,1,0,1,0,0,0 1,24,1,3,1246,1,4,4,0,0,2,0,23,2,0,1,1,1,1,0,1 2,12,0,0,2331,0,0,1,0,2,4,0,49,0,0,1,0,1,0,0,0 2,36,2,0,4463,1,1,4,0,0,2,3,26,0,0,2,2,1,0,0,1 2,12,1,0,776,1,1,4,3,0,2,0,28,0,0,1,0,1,1,0,0 0,30,1,2,2406,1,2,4,1,0,4,0,23,0,2,1,0,1,1,0,1 1,18,1,1,1239,0,1,4,0,0,4,2,61,0,1,1,0,1,1,0,0 3,12,1,0,3399,0,0,2,0,0,3,3,37,0,0,1,2,1,1,0,0 3,12,2,3,2247,1,1,2,1,0,2,3,36,2,0,2,0,1,0,0,0 2,6,1,2,1766,1,1,1,3,0,2,1,21,0,2,1,0,1,1,0,0 0,18,1,2,2473,1,3,4,0,0,1,3,25,0,0,1,3,1,1,0,1 2,12,1,5,1542,1,2,2,0,0,4,3,36,0,0,1,0,1,0,0,0 2,18,0,4,3850,1,2,3,0,0,1,3,27,0,0,2,0,1,1,0,0 0,18,1,2,3650,1,4,1,1,0,4,3,22,0,2,1,0,1,1,0,0 0,36,1,2,3446,1,0,4,0,0,2,3,42,0,0,1,0,2,1,0,1 1,18,1,2,3001,1,2,2,1,0,4,0,40,0,2,1,0,1,1,0,0 2,36,1,3,3079,0,1,4,0,0,4,0,36,0,0,1,0,1,1,0,0 2,18,0,0,6070,1,0,3,0,0,4,3,33,0,0,2,0,1,0,0,0 2,10,0,2,2146,1,4,1,1,0,3,0,23,0,2,2,0,1,1,0,0 2,60,0,3,13756,0,0,2,0,0,4,2,63,1,1,1,2,1,0,0,0 1,60,4,8,14782,4,0,3,1,0,4,2,60,1,1,2,2,1,0,0,1 0,48,4,5,7685,1,2,2,1,1,4,3,37,0,2,1,0,1,1,0,1 2,18,2,0,2320,1,3,2,3,0,3,0,34,0,0,2,0,1,1,0,0 2,7,2,0,846,0,0,3,0,0,4,2,36,0,1,1,0,1,1,0,0 1,36,1,3,14318,1,0,4,0,0,2,2,57,0,1,1,2,1,0,0,1 2,6,0,3,362,4,1,4,1,0,4,3,52,0,0,2,1,1,1,0,0 0,20,1,2,2212,0,2,4,0,0,4,3,39,0,0,1,0,1,0,0,0 1,18,1,4,12976,1,3,3,1,0,4,2,38,0,1,1,2,1,0,0,1 2,22,1,3,1283,0,2,4,1,0,4,1,25,0,2,1,0,1,1,0,0 3,12,1,3,1330,1,4,4,0,0,1,0,26,0,0,1,0,1,1,0,0 2,30,2,5,4272,4,1,2,0,0,2,1,26,0,0,2,1,1,1,0,0 2,18,0,0,2238,1,1,2,1,0,1,3,25,0,0,2,0,1,1,0,0 2,18,1,0,1126,0,4,4,1,0,2,0,21,0,2,1,0,1,0,0,0 1,18,0,2,7374,1,3,4,0,0,4,1,40,2,0,2,2,1,0,0,0 1,15,0,5,2326,2,1,2,0,0,4,3,27,1,0,1,0,1,1,0,0 2,9,1,5,1449,1,2,3,1,0,2,3,27,0,0,2,0,1,1,0,0 2,18,1,3,1820,1,1,2,3,0,2,1,30,0,0,1,2,1,0,0,0 1,12,1,2,983,3,4,1,1,0,4,0,19,0,2,1,1,1,1,0,0 0,36,1,3,3249,1,2,2,0,0,4,2,39,1,1,1,2,2,0,0,0 0,6,0,0,1957,1,2,1,1,0,4,3,31,0,0,1,0,1,1,0,0 2,9,0,2,2406,1,3,2,0,0,3,3,31,0,0,1,2,1,1,0,0 1,39,2,1,11760,4,2,2,0,0,3,2,32,0,2,1,0,1,0,0,0 0,12,1,2,2578,1,3,3,1,0,4,2,55,0,1,1,2,1,1,0,0 0,36,0,2,2348,1,1,3,3,0,2,1,46,0,0,2,0,1,0,0,0 1,12,1,3,1223,1,0,1,2,0,1,0,46,0,2,2,0,1,1,0,1 2,24,0,0,1516,3,1,4,1,0,1,0,43,0,0,2,1,1,1,0,0 2,18,1,0,1473,1,4,3,3,0,4,0,39,0,0,1,0,1,0,0,0 1,18,0,5,1887,0,1,4,3,0,4,0,28,1,0,2,0,1,1,0,0 2,24,2,5,8648,1,4,2,0,0,2,3,27,1,0,2,0,1,0,0,1 2,14,2,3,802,1,1,4,0,0,2,3,27,0,0,2,1,1,1,0,0 1,18,2,3,2899,0,0,4,0,0,4,3,43,0,0,1,0,2,1,0,0 1,24,1,0,2039,1,4,1,3,0,1,1,22,0,0,1,0,1,0,0,1 2,24,0,4,2197,0,2,4,0,0,4,3,43,0,0,2,0,2,0,0,0 0,15,1,0,1053,1,4,4,3,0,2,0,27,0,0,1,0,1,1,1,0 2,24,1,0,3235,2,0,3,2,0,2,3,26,0,0,1,2,1,0,0,0 3,12,0,3,939,2,2,4,3,0,2,0,28,0,0,3,0,1,0,0,1 1,24,1,0,1967,1,0,4,1,0,4,3,20,0,0,1,0,1,0,0,0 2,33,0,4,7253,1,2,3,0,0,2,3,35,0,0,2,2,1,0,0,0 2,12,0,5,2292,1,3,4,0,0,2,3,42,2,0,2,2,1,0,0,1 2,10,1,3,1597,2,1,3,0,0,2,2,40,0,2,1,1,2,1,1,0 0,24,1,3,1381,0,1,4,1,0,2,1,35,0,0,1,0,1,1,0,1 2,36,0,4,5842,1,0,2,0,0,2,1,35,0,0,2,0,2,0,0,0 0,12,1,3,2579,1,4,4,0,0,1,0,33,0,0,1,1,2,1,0,1 0,18,2,1,8471,0,1,1,1,0,2,3,23,0,2,2,0,1,0,0,0 2,21,1,3,2782,2,2,1,1,0,2,3,31,1,0,1,2,1,1,0,0 1,18,1,3,1042,0,1,4,1,0,2,1,33,0,0,1,0,1,1,0,1 2,15,1,3,3186,3,2,2,1,0,3,3,20,0,2,1,0,1,1,0,0 1,12,1,4,2028,0,1,4,0,0,2,3,30,0,0,1,0,1,1,0,0 1,12,0,3,958,1,2,2,0,0,3,0,47,0,0,2,1,2,1,0,0 2,21,2,2,1591,4,2,4,0,0,3,0,34,0,0,2,2,1,1,0,0 1,12,1,2,2762,0,0,1,1,0,2,1,25,1,0,1,0,1,0,0,1 1,18,1,4,2779,1,1,1,3,0,3,3,21,0,2,1,0,1,0,0,0 2,28,0,0,2743,1,0,4,0,0,2,3,29,0,0,2,0,1,1,0,0 2,18,0,0,1149,3,1,4,0,0,3,0,46,0,0,2,0,1,1,0,0 2,9,1,2,1313,1,0,1,0,0,4,3,20,0,0,1,0,1,1,0,0 0,18,0,7,1190,1,3,2,1,0,4,2,55,0,1,3,3,2,1,0,1 2,5,1,5,3448,1,2,1,0,0,4,0,74,0,0,1,1,1,1,0,0 1,24,1,8,11328,1,1,2,0,2,3,3,29,1,0,2,2,1,0,0,1 0,6,0,2,1872,1,3,4,0,0,4,2,36,0,1,3,2,1,0,0,0 2,24,0,7,2058,1,1,4,2,0,2,0,33,0,0,2,0,1,0,0,0 0,9,1,2,2136,1,1,3,0,0,2,0,25,0,0,1,0,1,1,0,0 1,12,1,0,1484,0,1,2,3,0,1,0,25,0,0,1,0,1,0,0,1 2,6,1,7,660,2,2,2,3,0,4,0,23,0,2,1,1,1,1,0,0 2,24,0,3,1287,3,0,4,1,0,4,0,37,0,0,2,0,1,0,0,0 0,42,0,7,3394,1,3,4,0,2,4,3,65,0,0,2,3,1,1,0,0 3,12,4,5,609,1,4,4,1,0,1,0,26,0,0,1,3,1,1,0,1 2,12,1,3,1884,1,0,4,0,0,4,3,39,0,0,1,2,1,0,0,0 0,12,1,2,1620,1,1,2,1,2,3,1,30,0,0,1,0,1,1,0,0 1,20,2,8,2629,1,1,2,0,0,3,3,29,1,0,2,0,1,0,0,0 2,12,1,1,719,1,0,4,0,0,4,3,41,1,0,1,1,2,1,0,1 1,48,0,2,5096,1,1,2,1,0,3,3,30,0,0,1,2,1,0,0,1 2,9,0,1,1244,0,0,4,1,0,4,1,41,0,2,2,1,1,1,0,0 0,36,1,3,1842,1,4,4,1,0,4,3,34,0,0,1,0,1,0,0,1 1,7,1,0,2576,1,1,2,0,1,2,0,35,0,0,1,0,1,1,0,0 3,12,1,2,1424,0,0,3,1,0,4,0,55,0,0,1,2,1,0,0,0 1,15,2,7,1512,3,1,3,3,0,3,1,61,2,0,2,0,1,1,0,1 2,36,0,4,11054,0,1,4,0,0,2,3,30,0,0,1,2,1,0,0,0 2,6,1,0,518,1,1,3,1,0,1,0,29,0,0,1,0,1,1,0,0 2,12,3,2,2759,1,0,2,0,0,4,1,34,0,0,2,0,1,1,0,0 2,24,1,4,2670,1,0,4,0,0,4,3,35,0,0,1,2,1,0,0,0 0,24,1,3,4817,1,2,2,0,2,3,1,31,0,0,1,0,1,0,0,1 2,24,1,4,2679,1,4,4,1,0,1,2,29,0,0,1,2,1,0,0,0 0,11,0,3,3905,1,1,2,0,0,2,0,36,0,2,2,0,2,1,0,0 0,12,1,4,3386,1,0,3,0,0,4,2,35,0,1,1,0,1,0,0,1 0,6,1,6,343,1,4,4,1,0,1,0,27,0,0,1,0,1,1,0,0 2,18,1,0,4594,1,4,3,0,0,2,3,32,0,0,1,0,1,0,0,0 0,36,1,2,3620,1,1,1,0,1,2,1,37,0,0,1,0,2,1,0,0 0,15,1,3,1721,1,4,2,0,0,3,0,36,0,0,1,0,1,1,0,0 1,12,1,2,3017,1,4,3,1,0,1,0,34,0,2,1,2,1,1,0,0 1,12,1,9,754,0,0,4,0,0,4,1,38,0,0,2,0,1,1,0,0 2,18,1,5,1950,1,2,4,0,0,1,3,34,2,0,2,0,1,0,0,0 0,24,1,4,2924,1,1,3,0,1,4,2,63,1,0,1,0,2,0,0,0 0,24,2,0,1659,1,4,4,1,0,2,3,29,0,2,1,1,1,0,0,1 2,48,2,0,7238,0,0,3,0,0,3,3,32,1,0,2,0,2,1,0,0 2,33,2,5,2764,1,1,2,1,0,2,3,26,0,0,2,0,1,0,0,0 2,24,2,4,4679,1,2,3,0,0,3,3,35,0,0,2,1,1,0,0,0 1,24,1,0,3092,4,4,3,3,0,2,3,22,0,2,1,0,1,0,0,1 0,6,1,1,448,1,4,4,1,0,4,1,23,0,0,1,0,1,1,0,1 0,9,1,3,654,1,1,4,0,0,3,3,28,0,0,1,1,1,1,0,1 2,6,1,9,1238,0,3,4,0,0,4,1,36,0,0,1,2,2,0,0,0 1,18,0,0,1245,1,1,4,3,0,2,3,33,0,0,1,0,1,1,0,1 0,18,3,2,3114,1,4,1,1,0,4,1,26,0,2,1,0,1,1,0,1 2,39,1,4,2569,2,1,4,0,0,4,3,24,0,0,1,0,1,1,0,0 3,24,1,0,5152,1,2,4,0,0,2,3,25,1,0,1,0,1,1,0,0 1,12,1,5,1037,4,2,3,0,0,4,0,39,0,0,1,1,1,1,0,0 0,15,0,2,1478,1,0,4,0,0,4,3,44,0,0,2,0,2,0,0,0 1,12,0,0,3573,1,1,1,1,0,1,0,23,0,0,1,1,1,1,0,0 1,24,1,3,1201,1,4,4,0,0,1,1,26,0,0,1,0,1,1,0,0 0,30,1,2,3622,3,0,4,1,0,4,1,57,0,2,2,0,1,0,0,0 2,15,2,2,960,3,2,3,1,0,2,1,30,0,0,2,0,1,1,0,0 2,12,0,3,1163,2,1,4,0,0,4,0,44,0,0,1,0,1,0,0,0 1,6,2,3,1209,1,3,4,0,0,4,1,47,0,0,1,2,1,0,0,1 2,12,1,0,3077,1,1,2,0,0,4,3,52,0,0,1,0,1,0,0,0 2,24,1,3,3757,1,0,4,1,2,4,2,62,0,1,1,0,1,0,0,0 2,10,1,3,1418,4,1,3,0,0,2,0,35,0,2,1,1,1,1,1,0 2,6,1,3,3518,1,1,2,0,1,3,1,26,0,2,1,0,1,1,0,0 2,12,0,0,1934,1,0,2,0,0,2,2,26,0,0,2,0,1,1,0,0 1,27,3,5,8318,1,0,2,1,0,4,2,42,0,1,2,2,1,0,0,1 2,6,0,0,1237,4,1,1,1,0,1,1,27,0,0,2,0,1,1,0,0 1,6,1,0,368,0,0,4,0,0,4,1,38,0,0,1,0,1,1,0,0 0,12,0,3,2122,1,1,3,0,0,2,0,39,0,2,2,1,2,1,1,0 0,24,1,2,2996,0,1,2,3,0,4,3,20,0,0,1,0,1,1,0,1 1,36,1,2,9034,4,4,4,0,2,1,2,29,0,2,1,2,1,0,0,1 2,24,0,2,1585,1,2,4,0,0,3,1,40,0,0,2,0,1,1,0,0 1,18,1,0,1301,1,0,4,3,1,2,0,32,0,0,1,1,1,1,0,0 3,6,0,3,1323,4,0,2,2,0,4,3,28,0,0,2,0,2,0,0,0 0,24,1,3,3123,1,4,4,1,0,1,1,27,0,0,1,0,1,1,0,1 0,36,1,4,5493,1,0,2,0,0,4,2,42,0,1,1,0,2,1,0,0 3,9,1,0,1126,4,0,2,2,0,4,0,49,0,0,1,0,1,1,0,0 1,24,0,0,1216,4,4,4,0,0,4,2,38,1,0,2,0,2,1,0,1 0,24,1,3,1207,1,4,4,1,0,4,1,24,0,2,1,0,1,1,0,1 2,10,1,3,1309,0,1,4,0,1,4,1,27,0,0,1,1,1,1,0,1 3,15,0,4,2360,2,1,2,0,0,2,3,36,0,0,1,0,1,0,0,0 1,15,4,3,6850,4,3,1,0,0,2,1,34,0,0,1,2,2,0,0,1 2,24,1,0,1413,1,1,4,3,0,2,1,28,0,0,1,0,1,1,0,0 2,39,1,4,8588,4,0,4,0,0,2,3,45,0,0,1,2,1,0,0,0 0,12,1,3,759,1,2,4,0,0,2,0,26,0,0,1,0,1,1,0,1 2,36,1,4,4686,1,1,2,0,0,2,2,32,0,1,1,2,1,0,0,0 3,15,1,5,2687,1,2,2,0,0,4,1,26,0,2,1,0,1,0,0,0 1,12,2,0,585,1,1,4,3,2,4,0,20,0,2,2,0,1,1,0,0 2,24,1,3,2255,0,4,4,0,0,1,1,54,0,0,1,0,1,1,0,0 0,6,0,3,609,1,2,4,1,0,3,1,37,0,0,2,0,1,1,1,0 0,6,0,3,1361,1,4,2,0,0,4,0,40,0,0,1,1,2,1,1,0 2,36,0,2,7127,1,4,2,1,0,4,1,23,0,2,2,0,1,0,0,1 0,6,1,3,1203,4,0,3,0,0,2,1,43,0,0,1,0,1,0,0,0 2,6,0,0,700,0,0,4,0,0,4,2,36,0,1,2,0,1,1,0,0 2,24,0,7,5507,1,0,3,0,0,4,2,44,0,1,2,0,1,1,0,0 0,18,1,0,3190,1,1,2,1,0,2,0,24,0,0,1,0,1,1,0,1 0,48,3,2,7119,1,1,3,0,0,4,2,53,0,1,2,0,2,1,0,1 2,24,1,4,3488,4,2,3,1,0,4,3,23,0,0,1,0,1,1,0,0 1,18,1,0,1113,1,1,4,1,1,4,0,26,0,0,1,1,2,1,0,0 1,26,1,4,7966,1,4,2,0,0,3,3,30,0,0,2,0,1,1,0,0 2,15,0,1,1532,4,1,4,1,0,3,3,31,0,0,1,0,1,1,0,0 2,4,0,0,1503,1,2,2,0,0,1,0,42,0,0,2,1,2,1,0,0 0,36,1,0,2302,1,1,4,2,0,4,3,31,0,2,1,0,1,1,0,1 0,6,1,3,662,1,4,3,0,0,4,0,41,0,0,1,1,2,0,0,0 1,36,1,1,2273,1,2,3,0,0,1,3,32,0,0,2,0,2,1,0,0 1,15,1,3,2631,4,1,2,1,0,4,3,28,0,2,2,0,1,0,0,1 2,12,2,4,1503,1,1,4,3,0,4,0,41,0,2,1,0,1,1,0,0 2,24,1,0,1311,4,2,4,3,0,3,1,26,0,0,1,0,1,0,0,0 2,24,1,0,3105,0,4,4,0,0,2,3,25,0,0,2,0,1,1,0,0 3,21,0,1,2319,1,4,2,2,0,1,3,33,0,2,1,0,1,1,0,1 0,6,1,3,1374,0,3,4,1,0,3,1,75,0,0,1,2,1,0,0,0 1,18,0,2,3612,1,0,3,1,0,4,1,37,0,0,1,0,1,0,0,0 0,48,1,3,7763,1,0,4,0,0,4,2,42,1,1,1,2,1,1,0,1 3,18,1,2,3049,1,4,1,1,0,1,1,45,2,0,1,1,1,1,0,0 1,12,1,0,1534,1,4,1,3,0,1,0,23,0,2,1,0,1,1,0,1 2,24,2,3,2032,1,0,4,0,0,4,2,60,0,1,2,0,1,0,0,0 0,30,1,2,6350,0,0,4,0,0,4,1,31,0,0,1,0,1,1,0,1 3,18,1,2,2864,1,1,2,0,0,1,0,34,0,0,1,1,2,1,0,1 2,12,0,3,1255,1,0,4,0,0,4,0,61,0,0,2,1,1,1,0,0 0,24,2,3,1333,1,3,4,0,0,2,0,43,0,1,2,0,2,1,0,1 2,24,0,3,2022,1,1,4,1,0,4,3,37,0,0,1,0,1,0,0,0 2,24,1,0,1552,1,2,3,0,0,1,3,32,1,0,1,0,2,1,0,0 0,12,4,0,626,1,1,4,1,0,4,0,24,1,0,1,1,1,1,0,1 2,48,0,4,8858,0,2,2,0,0,1,2,35,0,1,2,0,1,0,0,0 2,12,0,7,996,0,2,4,1,0,4,0,23,0,0,2,0,1,1,0,0 2,6,4,0,1750,2,0,2,0,0,4,1,45,1,0,1,1,2,1,0,0 0,48,1,0,6999,1,2,1,3,1,1,0,34,0,0,2,0,1,0,0,1 1,12,0,3,1995,4,4,4,0,0,1,3,27,0,0,1,0,1,1,0,0 1,9,1,1,1199,1,2,4,1,0,4,1,67,0,0,2,2,1,0,0,0 1,12,1,0,1331,1,4,2,0,0,1,3,22,2,0,1,0,1,1,0,1 1,18,3,3,2278,4,4,3,1,0,3,3,28,0,0,2,0,1,1,0,1 2,21,3,3,5003,0,1,1,1,0,4,1,29,1,0,2,0,1,0,0,1 0,24,4,2,3552,1,2,3,0,0,4,3,27,1,0,1,0,1,1,0,1 1,18,0,2,1928,1,4,2,0,0,2,0,31,0,0,2,1,1,1,0,1 0,24,1,4,2964,0,0,4,0,0,4,2,49,1,1,1,0,2,0,0,0 0,24,4,0,1546,1,2,4,0,1,4,3,24,1,2,1,1,1,1,0,1 3,6,2,0,683,1,4,2,1,0,1,1,29,1,0,1,0,1,1,0,0 1,36,1,3,12389,0,1,1,0,0,4,2,37,0,1,1,0,1,0,0,1 1,24,2,5,4712,0,1,4,0,0,2,1,37,1,0,2,2,1,0,0,0 1,24,2,0,1553,4,2,3,1,0,2,1,23,0,2,2,0,1,0,0,0 0,12,1,3,1372,1,2,2,2,0,3,3,36,0,0,1,0,1,1,0,1 2,24,0,0,2578,3,0,2,0,0,2,3,34,0,0,1,0,1,1,0,0 1,48,1,0,3979,0,2,4,0,0,1,3,41,0,0,2,0,2,0,0,0 0,48,1,0,6758,1,1,3,1,0,2,3,31,0,0,1,0,1,0,0,1 0,24,1,2,3234,1,4,4,1,0,4,0,23,0,2,1,1,1,0,0,1 2,30,0,0,5954,1,2,3,0,2,2,3,38,0,0,1,0,1,1,0,0 2,24,1,4,5433,0,3,2,1,0,4,1,26,0,2,1,2,1,0,0,0 0,15,1,5,806,1,1,4,1,0,4,1,22,0,0,1,1,1,1,0,0 1,9,1,0,1082,1,0,4,0,0,4,3,27,0,0,2,1,1,1,0,0 2,15,0,2,2788,1,2,2,1,2,3,3,24,1,0,2,0,1,1,0,0 1,12,1,0,2930,1,2,2,1,0,1,0,27,0,0,1,0,1,1,0,0 2,24,0,1,1927,0,1,3,1,0,2,3,33,0,0,2,0,1,0,0,0 1,36,0,3,2820,1,4,4,2,0,4,3,27,0,0,2,0,1,1,0,1 2,24,1,9,937,1,4,4,3,0,3,3,27,0,0,2,1,1,1,0,0 1,18,0,3,1056,1,0,3,0,1,3,0,30,1,0,2,0,1,1,0,1 1,12,0,3,3124,1,4,1,0,0,3,0,49,1,0,2,1,2,1,0,0 2,9,1,2,1388,1,1,4,1,0,2,0,26,0,2,1,0,1,1,0,0 1,36,1,7,2384,1,4,4,0,0,1,2,33,0,2,1,1,1,1,0,1 2,12,1,3,2133,0,0,4,1,0,4,2,52,0,1,1,2,1,0,0,0 0,18,1,2,2039,1,1,1,1,0,4,0,20,1,2,1,0,1,1,0,1 0,9,0,3,2799,1,1,2,0,0,2,0,36,0,2,2,0,2,1,0,0 0,12,1,2,1289,1,1,4,0,1,1,1,21,0,0,1,1,1,1,0,0 0,18,1,6,1217,1,1,4,3,0,3,0,47,0,0,1,1,1,0,0,1 0,12,0,2,2246,1,0,3,0,0,3,1,60,0,0,2,0,1,1,0,1 0,12,0,0,385,1,2,4,1,0,3,0,58,0,0,4,1,1,0,0,0 1,24,2,3,1965,0,1,4,1,0,4,3,42,0,2,2,0,1,0,0,0 2,21,1,5,1572,3,0,4,1,0,4,0,36,1,0,1,1,1,1,0,0 1,24,1,3,2718,1,1,3,1,0,4,1,20,0,2,1,1,1,0,0,1 0,24,4,8,1358,0,0,4,0,0,3,3,40,2,0,1,2,1,0,0,1 1,6,4,3,931,4,4,1,1,0,1,1,32,2,0,1,1,1,1,0,1 0,24,1,3,1442,1,2,4,1,0,4,3,23,0,2,2,0,1,1,0,1 1,24,3,5,4241,1,1,1,0,0,4,0,36,0,0,3,1,1,0,0,1 2,18,0,3,2775,1,2,2,0,0,2,1,31,1,0,2,0,1,1,0,1 2,24,2,5,3863,1,1,1,0,0,2,2,32,0,1,1,0,1,1,0,0 1,7,1,0,2329,1,4,1,1,1,1,0,45,0,0,1,0,1,1,0,0 1,9,1,2,918,1,1,4,1,0,1,1,30,0,0,1,0,1,1,0,1 1,24,4,1,1837,1,2,4,1,0,4,2,34,1,1,1,1,1,1,0,1 2,36,1,2,3349,1,1,4,1,0,2,3,28,0,0,1,2,1,0,0,1 3,10,1,2,1275,1,4,4,1,0,2,1,23,0,0,1,0,1,1,0,0 0,24,4,2,2828,2,1,4,0,0,4,0,22,2,0,1,0,1,0,0,0 2,24,0,5,4526,1,1,3,0,0,2,0,74,0,0,1,2,1,0,0,0 1,36,1,0,2671,4,1,4,1,2,4,2,50,0,1,1,0,1,1,0,1 2,18,1,0,2051,1,4,4,0,0,1,0,33,0,0,1,0,1,1,0,0 2,15,1,4,1300,0,0,4,0,0,4,2,45,1,1,1,0,2,1,0,0 0,12,1,6,741,4,3,4,1,0,3,1,22,0,0,1,0,1,1,0,1 3,10,1,3,1240,4,0,1,1,0,4,2,48,0,1,1,1,2,1,0,1 0,21,1,0,3357,3,4,4,1,0,2,3,29,1,0,1,0,1,1,0,0 0,24,4,4,3632,1,1,1,1,1,4,3,22,1,2,1,0,1,1,1,0 2,18,2,2,1808,1,2,4,1,0,1,0,22,0,0,1,0,1,1,0,1 1,48,3,5,12204,0,1,2,0,0,2,3,48,1,0,1,2,1,0,0,0 1,60,2,0,9157,0,1,2,0,0,2,2,27,0,1,1,2,1,1,0,0 0,6,0,3,3676,1,1,1,0,0,3,0,37,0,2,3,0,2,1,0,0 1,30,1,2,3441,4,1,2,1,2,4,3,21,0,2,1,0,1,1,0,1 2,12,1,3,640,1,1,4,2,0,2,0,49,0,0,1,1,1,1,0,0 1,21,0,5,3652,1,2,2,0,0,3,1,27,0,0,2,0,1,1,0,0 2,18,0,3,1530,1,1,3,0,0,2,1,32,1,0,2,0,1,1,0,1 2,48,1,5,3914,0,1,4,2,0,2,0,38,1,0,1,0,1,1,0,1 0,12,1,2,1858,1,4,4,1,0,1,3,22,0,2,1,0,1,1,0,0 0,18,1,0,2600,1,1,4,0,0,4,2,65,0,1,2,0,1,1,0,1 2,15,1,0,1979,0,0,4,0,0,2,3,35,0,0,1,0,1,1,0,0 3,6,1,2,2116,1,1,2,0,0,2,0,41,0,0,1,0,1,0,0,0 1,9,4,3,1437,4,2,2,0,0,3,2,29,0,0,1,0,1,1,0,1 2,42,0,2,4042,2,1,4,0,0,4,0,36,0,0,2,0,1,0,0,0 2,9,1,1,3832,0,0,1,0,0,4,0,64,0,0,1,1,1,1,0,0 0,24,1,0,3660,1,1,2,1,0,4,3,28,0,0,1,0,1,1,0,0 0,18,4,2,1553,1,1,4,0,0,3,3,44,1,0,1,0,1,1,0,1 1,15,1,0,1444,0,4,4,0,0,1,1,23,0,0,1,0,1,1,0,0 2,9,1,2,1980,1,4,2,1,2,2,3,19,0,2,2,0,1,1,0,1 1,24,1,3,1355,1,4,3,1,0,4,3,25,0,0,1,1,1,0,0,1 2,12,1,1,1393,1,0,4,0,0,4,1,47,1,0,3,0,2,0,0,0 2,24,1,0,1376,2,2,4,1,0,1,3,28,0,0,1,0,1,1,0,0 2,60,2,0,15653,1,2,2,0,0,4,3,21,0,0,2,0,1,0,0,0 2,12,1,0,1493,1,4,4,1,0,3,3,34,0,0,1,0,2,1,0,0 0,42,2,0,4370,1,2,3,0,0,2,1,26,1,0,2,0,2,0,0,1 0,18,1,1,750,1,3,4,1,0,1,0,27,0,0,1,3,1,1,0,1 1,15,1,7,1308,1,0,4,0,0,4,3,38,0,0,2,1,1,1,0,0 2,15,1,1,4623,4,1,3,0,0,2,1,40,0,0,1,2,1,0,0,1 2,24,0,0,1851,1,2,4,3,1,2,3,33,0,0,2,0,1,0,0,0 0,18,0,0,1880,1,2,4,3,0,1,1,32,0,0,2,2,1,0,0,0 2,36,2,5,7980,0,4,4,0,0,4,3,27,0,2,2,0,1,0,0,1 0,30,3,2,4583,1,1,2,2,1,2,0,32,0,0,2,0,1,1,0,0 2,12,1,3,1386,2,1,2,1,0,2,1,26,0,0,1,0,1,1,0,1 3,24,1,3,947,1,2,4,0,0,3,2,38,1,1,1,0,2,1,0,1 0,12,1,1,684,1,1,4,0,0,4,3,40,0,2,1,1,2,1,0,1 0,48,1,1,7476,1,2,4,0,0,1,2,50,0,1,1,2,1,0,0,0 1,12,1,2,1922,1,1,4,0,0,2,1,37,0,0,1,1,1,1,0,1 0,24,1,3,2303,1,0,4,0,2,1,0,45,0,0,1,0,1,1,0,1 1,36,2,3,8086,4,0,2,0,0,4,3,42,0,0,4,2,1,0,0,1 2,24,0,4,2346,1,2,4,0,0,3,3,35,0,0,2,0,1,0,0,0 0,14,1,3,3973,1,3,1,0,0,4,2,22,0,1,1,0,1,1,0,0 1,12,1,3,888,1,0,4,0,0,4,3,41,1,0,1,1,2,1,0,1 2,48,1,0,10222,0,2,4,0,0,3,3,37,2,0,1,0,1,0,0,0 1,30,3,5,4221,1,1,2,1,0,1,3,28,0,0,2,0,1,1,0,0 1,18,0,2,6361,1,0,2,0,0,1,2,41,0,0,1,0,1,0,0,0 3,12,1,0,1297,1,1,3,3,0,4,0,23,0,2,1,0,1,1,0,0 0,12,1,3,900,0,1,4,3,0,2,3,23,0,0,1,0,1,1,0,1 2,21,1,2,2241,1,0,4,0,0,2,0,50,0,0,2,0,1,1,0,0 1,6,2,2,1050,1,3,4,0,0,1,1,35,2,0,2,2,1,0,0,0 3,6,0,1,1047,1,1,2,1,0,4,1,50,0,0,1,1,1,1,0,0 2,24,0,8,6314,1,3,4,0,2,2,2,27,1,0,2,2,1,0,0,0 1,30,4,2,3496,3,1,4,0,0,2,3,34,2,0,1,0,2,0,0,0 2,48,4,5,3609,1,1,1,1,0,1,0,27,2,0,1,0,1,1,0,0 0,12,0,3,4843,1,0,3,0,2,4,1,43,0,2,2,0,1,0,0,1 3,30,0,0,3017,1,0,4,0,0,4,1,47,0,0,1,0,1,1,0,0 2,24,0,5,4139,4,1,3,0,0,3,1,27,0,0,2,1,1,0,0,0 2,36,1,5,5742,4,2,2,0,0,2,3,31,0,0,2,0,1,0,0,0 2,60,1,3,10366,1,0,2,0,0,4,1,42,0,0,1,2,1,0,0,0 2,6,0,3,2080,2,1,1,3,0,2,3,24,0,0,1,0,1,1,0,0 2,21,2,5,2580,2,4,4,0,0,2,0,41,1,0,1,1,2,1,0,1 2,30,0,0,4530,1,2,4,1,0,4,3,26,0,2,1,2,1,0,0,0 2,24,0,2,5150,1,0,4,0,0,4,3,33,0,0,1,0,1,0,0,0 1,72,1,0,5595,4,1,2,3,0,2,3,24,0,0,1,0,1,1,0,1 0,24,1,0,2384,1,0,4,0,0,4,0,64,1,2,1,1,1,1,0,0 2,18,1,0,1453,1,4,3,1,0,1,0,26,0,0,1,0,1,1,0,0 2,6,1,1,1538,1,4,1,1,0,2,2,56,0,0,1,0,1,1,0,0 2,12,1,0,2279,0,1,4,0,0,4,2,37,0,1,1,0,1,0,0,0 2,15,2,0,1478,1,1,4,3,0,3,0,33,1,0,2,0,1,1,0,0 2,24,0,0,5103,1,4,3,3,0,3,2,47,0,1,3,0,1,0,0,0 1,36,2,5,9857,4,2,1,0,0,3,1,31,0,0,2,1,2,0,0,0 2,60,1,3,6527,0,1,4,0,0,4,2,34,0,1,1,0,2,0,0,0 3,10,0,0,1347,0,2,4,0,0,2,1,27,0,0,2,0,1,0,0,0 1,36,2,3,2862,4,0,4,0,0,3,2,30,0,1,1,0,1,1,0,0 2,9,1,0,2753,4,0,3,0,2,4,3,35,0,0,1,0,1,0,0,0 0,12,1,3,3651,3,1,1,0,0,3,1,31,0,0,1,0,2,1,0,0 0,15,0,2,975,1,1,2,2,0,3,1,25,0,0,2,0,1,1,0,0 1,15,1,7,2631,4,1,3,1,0,2,0,25,0,0,1,1,1,1,0,0 1,24,1,0,2896,4,4,2,0,0,1,3,29,0,0,1,0,1,1,0,0 0,6,0,3,4716,0,4,1,0,0,3,0,44,0,0,2,1,2,1,0,0 2,24,1,0,2284,1,2,4,0,0,2,3,28,0,0,1,0,1,0,0,0 2,6,1,4,1236,2,1,2,0,0,4,1,50,0,2,1,0,1,1,0,0 1,12,1,0,1103,1,2,4,0,1,3,0,29,0,0,2,0,1,1,1,0 2,12,0,3,926,1,3,1,1,0,2,1,38,0,0,1,3,1,1,0,0 2,18,0,0,1800,1,1,4,0,0,2,3,24,0,0,2,0,1,1,0,0 3,15,1,1,1905,1,0,4,0,0,4,3,40,0,2,1,2,1,0,0,0 2,12,1,2,1123,2,1,4,1,0,4,3,29,0,2,1,1,1,1,0,1 0,48,0,4,6331,1,0,4,0,0,4,2,46,0,1,2,0,1,0,0,1 3,24,1,0,1377,4,0,4,1,0,2,2,47,0,1,1,0,1,0,0,0 1,30,2,5,2503,4,0,4,0,0,2,1,41,2,0,2,0,1,1,0,0 1,27,1,5,2528,1,4,4,1,0,1,1,32,0,0,1,0,2,0,0,0 2,15,1,3,5324,2,0,1,1,0,4,2,35,0,1,1,0,1,1,0,0 1,48,1,3,6560,4,2,3,0,0,2,1,24,0,0,1,0,1,1,0,1 1,12,3,2,2969,1,4,4,1,0,3,1,25,0,2,2,0,1,1,0,1 1,9,1,0,1206,1,0,4,1,0,4,0,25,0,0,1,0,1,1,0,0 1,9,1,0,2118,1,1,2,0,0,2,0,37,0,0,1,1,2,1,0,0 2,18,0,0,629,2,0,4,0,0,3,1,32,1,0,2,2,1,0,0,0 0,6,4,1,1198,1,0,4,1,0,4,2,35,0,1,1,0,1,1,0,1 2,21,1,4,2476,0,0,4,0,0,4,0,46,0,0,1,2,1,0,0,0 0,9,0,0,1138,1,1,4,0,0,4,0,25,0,0,2,1,1,1,0,0 1,60,1,3,14027,1,2,4,0,0,2,2,27,0,0,1,2,1,0,0,1 2,30,0,4,7596,0,0,1,0,0,4,3,63,0,0,2,0,1,1,0,0 2,30,0,0,3077,0,0,3,0,0,2,3,40,0,0,2,0,2,0,0,0 2,18,1,0,1505,1,1,4,0,0,2,2,32,0,1,1,2,1,0,0,0 3,24,0,0,3148,0,1,3,0,0,2,3,31,0,0,2,0,1,0,0,0 1,20,3,4,6148,4,0,3,3,0,4,3,31,1,0,2,0,1,0,0,0 3,9,3,0,1337,1,4,4,0,0,2,3,34,0,0,2,2,1,0,0,1 1,6,4,1,433,3,4,4,1,0,2,1,24,1,2,1,0,2,1,0,1 0,12,1,3,1228,1,1,4,1,0,2,0,24,0,0,1,1,1,1,0,1 1,9,1,0,790,2,1,4,1,0,3,0,66,0,0,1,1,1,1,0,0 2,27,1,3,2570,1,1,3,1,0,3,0,21,0,2,1,0,1,1,0,1 2,6,0,3,250,3,1,2,1,0,2,0,41,1,0,2,1,1,1,0,0 2,15,0,0,1316,2,1,2,3,0,2,1,47,0,0,2,1,1,1,0,0 0,18,1,0,1882,1,1,4,1,0,4,3,25,1,2,2,0,1,1,0,1 1,48,4,5,6416,1,0,4,1,0,3,2,59,0,2,1,0,1,1,0,1 3,24,0,5,1275,3,1,2,2,0,4,0,36,0,0,2,0,1,0,0,0 1,24,2,0,6403,1,4,1,0,0,2,3,33,0,0,1,0,1,1,0,0 0,24,1,0,1987,1,1,2,0,0,4,0,21,0,2,1,1,2,1,0,1 1,8,1,0,760,1,2,4,1,1,2,0,44,0,0,1,1,1,1,0,0 2,24,1,4,2603,3,1,2,1,0,4,3,28,0,2,1,0,1,0,0,0 2,4,0,3,3380,1,2,1,1,0,1,0,37,0,0,1,0,2,1,0,0 1,36,4,6,3990,0,4,3,1,0,2,2,29,1,0,1,3,1,1,0,0 1,24,1,4,11560,1,1,1,1,0,4,3,23,0,2,2,2,1,1,0,1 0,18,1,3,4380,4,1,3,0,0,4,3,35,0,0,1,1,2,0,0,0 2,6,0,3,6761,1,2,1,0,0,3,2,45,0,0,2,2,2,0,0,0 1,30,3,5,4280,4,1,4,1,0,4,3,26,0,2,2,1,1,1,0,1 0,24,4,3,2325,4,2,2,0,0,3,3,32,1,0,1,0,1,1,0,0 1,10,4,0,1048,1,1,4,0,0,4,0,23,2,0,1,1,1,1,0,0 2,21,1,0,3160,0,0,4,0,0,3,1,41,0,0,1,0,1,0,0,0 0,24,4,2,2483,2,1,4,0,0,4,0,22,2,0,1,0,1,0,0,0 0,39,0,2,14179,0,2,4,0,0,4,1,30,0,0,2,2,1,0,0,0 0,13,0,5,1797,1,4,3,0,0,1,1,28,1,0,2,1,1,1,0,0 0,15,1,3,2511,1,3,1,1,0,4,3,23,0,2,1,0,1,1,0,0 0,12,1,3,1274,1,4,3,1,0,1,0,37,0,0,1,1,1,1,0,1 2,21,1,4,5248,0,1,1,0,0,3,3,26,0,0,1,0,1,1,0,0 2,15,1,4,3029,1,2,2,0,0,2,3,33,0,0,1,0,1,1,0,0 0,6,1,2,428,1,0,2,1,0,1,1,49,1,0,1,0,1,0,0,0 0,18,1,3,976,1,4,1,1,0,2,3,23,0,0,1,1,1,1,0,1 1,12,1,5,841,4,2,2,1,0,4,0,23,0,2,1,1,1,1,0,0 2,30,0,0,5771,1,2,4,1,0,2,3,25,0,0,2,0,1,1,0,0 2,12,2,7,1555,3,0,4,0,0,4,2,55,0,1,2,0,2,1,0,1 0,24,1,3,1285,0,2,4,1,0,4,2,32,0,2,1,0,1,1,0,1 3,6,0,3,1299,1,1,1,0,0,1,0,74,0,0,3,3,2,1,1,0 3,15,0,0,1271,0,1,3,0,0,4,2,39,0,1,2,0,1,0,0,1 2,24,1,3,1393,1,1,2,0,1,2,0,31,0,0,1,0,1,0,0,0 0,12,0,3,691,1,0,4,0,0,3,1,35,0,0,2,0,1,1,0,1 2,15,0,3,5045,0,0,1,1,0,4,3,59,0,0,1,0,1,0,0,0 0,18,0,2,2124,1,1,4,1,0,4,0,24,0,2,2,0,1,1,0,1 0,12,1,0,2214,1,1,4,0,0,3,1,24,0,0,1,1,1,1,0,0 2,21,0,3,12680,0,0,4,0,0,4,2,30,0,1,1,2,1,0,0,1 2,24,0,3,2463,4,2,4,3,0,3,1,27,0,0,2,0,1,0,0,0 1,12,1,0,1155,1,0,3,3,1,3,0,40,1,0,2,1,1,1,0,0 0,30,1,2,3108,1,4,2,2,0,4,1,31,0,0,1,1,1,1,0,1 2,10,1,4,2901,0,4,1,1,0,4,0,31,0,2,1,0,1,1,0,0 1,12,0,2,3617,1,0,1,0,0,4,3,28,0,2,3,0,1,0,0,0 2,12,0,0,1655,1,0,2,0,0,4,0,63,0,0,2,1,1,0,0,0 0,24,1,4,2812,0,0,2,1,0,4,0,26,0,2,1,0,1,1,0,0 0,36,0,1,8065,1,1,3,1,0,2,2,25,0,0,2,2,1,0,0,1 2,21,0,4,3275,1,0,1,0,0,4,3,36,0,0,1,2,1,0,0,0 2,24,0,0,2223,4,0,4,0,0,4,1,52,1,0,2,0,1,1,0,0 3,12,0,3,1480,2,3,2,0,0,4,2,66,1,1,3,3,1,1,0,0 0,24,1,3,1371,0,1,4,1,0,4,0,25,0,2,1,0,1,1,0,1 2,36,0,3,3535,1,2,4,0,0,4,3,37,0,0,2,0,1,0,0,0 0,18,1,0,3509,1,2,4,1,1,1,0,25,0,0,1,0,1,1,0,0 2,36,0,4,5711,3,0,4,0,0,2,3,38,0,0,2,2,1,0,0,0 1,18,1,7,3872,1,3,2,1,0,4,3,67,0,0,1,0,1,0,0,0 1,39,0,0,4933,1,2,2,0,1,2,0,25,0,0,2,0,1,1,0,1 2,24,0,3,1940,3,0,4,0,0,4,0,60,0,0,1,0,1,0,0,0 1,12,3,9,1410,1,1,2,0,0,2,0,31,0,0,1,1,1,0,0,0 1,12,1,3,836,4,4,4,1,0,2,1,23,1,0,1,1,1,1,0,1 1,20,1,4,6468,0,3,1,2,0,4,0,60,0,0,1,2,1,0,0,0 1,18,1,5,1941,3,1,4,0,0,2,1,35,0,0,1,1,1,0,0,0 2,22,1,0,2675,2,0,3,0,0,4,3,40,0,0,1,0,1,1,0,0 2,48,0,4,2751,0,0,4,0,0,3,3,38,0,0,2,0,2,0,0,0 1,48,2,1,6224,1,0,4,0,0,4,2,50,0,1,1,0,1,1,0,1 0,40,0,1,5998,1,1,4,0,0,3,2,27,1,0,1,0,1,0,0,1 1,21,1,5,1188,1,0,2,1,0,4,1,39,0,0,1,0,2,1,0,1 2,24,1,4,6313,0,0,3,0,0,4,3,41,0,0,1,2,2,0,0,0 2,6,0,2,1221,0,1,1,3,0,2,1,27,0,0,2,0,1,1,0,0 3,24,1,2,2892,1,0,3,2,0,4,2,51,0,1,1,0,1,1,0,0 2,24,1,2,3062,2,0,4,0,0,3,2,32,0,2,1,0,1,0,0,0 2,9,1,2,2301,4,4,2,1,0,4,1,22,0,2,1,0,1,1,0,0 0,18,1,4,7511,0,0,1,0,0,4,1,51,0,1,1,0,2,0,0,1 2,12,0,2,1258,1,4,2,1,0,4,1,22,0,2,2,1,1,1,0,0 2,24,2,3,717,0,0,4,3,0,4,3,54,0,0,2,0,1,0,0,0 1,9,1,3,1549,0,4,4,0,0,2,0,35,0,0,1,3,1,1,0,0 2,24,0,1,1597,1,0,4,0,0,4,2,54,0,1,2,0,2,1,0,0 1,18,0,0,1795,1,0,3,1,1,4,0,48,1,2,2,1,1,0,0,0 0,20,0,2,4272,1,0,1,1,0,4,1,24,0,0,2,0,1,1,0,0 2,12,0,0,976,0,0,4,0,0,4,3,35,0,0,2,0,1,1,0,0 1,12,1,3,7472,0,3,1,1,0,2,0,24,0,2,1,3,1,1,0,0 0,36,1,3,9271,1,2,2,0,0,1,3,24,0,0,1,0,1,0,0,1 1,6,1,0,590,1,4,3,3,0,3,0,26,0,0,1,1,1,1,1,0 2,12,0,0,930,0,0,4,0,0,4,0,65,0,0,4,0,1,1,0,0 1,42,4,4,9283,1,3,1,0,0,2,2,55,1,1,1,2,1,0,0,0 1,15,3,3,1778,1,4,2,1,0,1,0,26,0,2,2,3,1,1,0,1 1,8,1,5,907,1,4,3,3,0,2,0,26,0,0,1,0,1,0,0,0 1,6,1,0,484,1,2,3,3,1,3,0,28,1,0,1,1,1,1,0,0 0,36,0,4,9629,1,2,4,0,0,4,3,24,0,0,2,0,1,0,0,1 0,48,1,6,3051,1,1,3,0,0,4,3,54,0,0,1,0,1,1,0,1 0,48,1,3,3931,1,2,4,0,0,4,2,46,0,1,1,0,2,1,0,1 1,36,2,3,7432,1,1,2,1,0,2,1,54,0,2,1,0,1,1,0,0 2,6,1,6,1338,2,1,1,2,0,4,0,62,0,0,1,0,1,1,0,0 2,6,0,0,1554,1,2,1,1,0,2,3,24,0,2,2,0,1,0,0,0 0,36,1,8,15857,1,3,2,2,2,3,3,43,0,0,1,2,1,1,0,0 0,18,1,0,1345,1,1,4,3,0,3,0,26,1,0,1,0,1,1,0,1 2,12,1,3,1101,1,1,3,3,0,2,0,27,0,0,2,0,1,0,0,0 3,12,1,0,3016,1,1,3,3,0,1,3,24,0,0,1,0,1,1,0,0 0,36,1,2,2712,1,0,2,0,0,2,1,41,1,0,1,0,2,1,0,1 0,8,0,3,731,1,0,4,0,0,4,0,47,0,0,2,1,1,1,0,0 2,18,0,2,3780,1,4,3,2,0,2,3,35,0,0,2,2,1,0,0,0 0,21,0,3,1602,1,0,4,3,0,3,3,30,0,0,2,0,1,0,0,0 0,18,0,3,3966,1,0,1,1,0,4,0,33,1,2,3,0,1,0,0,1 2,18,3,5,4165,1,1,2,0,0,2,3,36,2,0,2,0,2,1,0,1 0,36,1,4,8335,0,0,3,0,0,4,2,47,0,1,1,0,1,1,0,1 1,48,2,5,6681,0,1,4,0,0,4,2,38,0,1,1,0,2,0,0,0 2,24,2,5,2375,2,1,4,0,0,2,3,44,0,0,2,0,2,0,0,0 0,18,1,3,1216,1,4,4,1,0,3,3,23,0,2,1,0,1,0,0,1 0,45,3,5,11816,1,0,2,0,0,4,3,29,0,2,2,0,1,1,0,1 1,24,1,0,5084,0,0,2,1,0,4,3,42,0,0,1,0,1,0,0,0 3,15,1,0,2327,1,4,2,1,0,3,0,25,0,0,1,1,1,1,0,1 0,12,3,3,1082,1,1,4,0,0,4,3,48,1,0,2,0,1,1,0,1 2,12,1,0,886,0,1,4,1,0,2,3,21,0,0,1,0,1,1,0,0 2,4,1,2,601,1,4,1,1,0,3,0,23,0,2,1,1,2,1,0,0 0,24,0,4,2957,1,0,4,0,0,4,1,63,0,0,2,0,1,0,0,0 2,24,0,0,2611,1,0,4,3,2,3,0,46,0,0,2,0,1,1,0,0 0,36,1,2,5179,1,2,4,0,0,2,1,29,0,0,1,0,1,1,0,1 2,21,2,4,2993,1,1,3,0,0,2,0,28,2,0,2,1,1,1,0,0 2,18,1,7,1943,1,4,4,1,0,4,0,23,0,0,1,0,1,1,0,1 2,24,4,5,1559,1,2,4,0,0,4,3,50,1,0,1,0,1,0,0,0 2,18,1,2,3422,1,0,4,0,0,4,1,47,1,0,3,0,2,0,0,0 1,21,1,2,3976,0,2,2,0,0,3,3,35,0,0,1,0,1,0,0,0 2,18,1,3,6761,0,1,2,0,0,4,3,68,0,2,2,0,1,1,0,1 2,24,1,3,1249,1,4,4,3,0,2,0,28,0,0,1,0,1,1,0,0 0,9,1,0,1364,1,2,3,0,0,4,0,59,0,0,1,0,1,1,0,0 0,12,1,0,709,1,0,4,0,0,4,0,57,2,0,1,1,1,1,0,1 0,20,0,3,2235,1,1,4,3,1,2,1,33,1,2,2,0,1,1,1,1 2,24,0,4,4042,0,2,3,0,0,4,1,43,0,0,2,0,1,0,0,0 2,15,0,0,1471,1,1,4,0,0,4,2,35,0,1,2,0,1,0,0,0 0,18,4,3,1442,1,2,4,0,0,4,2,32,0,1,2,1,2,1,0,1 2,36,2,3,10875,1,0,2,0,0,2,3,45,0,0,2,0,2,0,0,0 2,24,1,3,1474,4,4,4,3,0,3,0,33,0,0,1,0,1,0,0,0 2,10,1,9,894,0,2,4,1,0,3,1,40,0,0,1,0,1,0,0,0 2,15,0,2,3343,1,1,4,0,0,2,2,28,0,1,1,0,1,0,0,0 0,15,1,3,3959,1,1,3,1,0,2,1,29,0,0,1,0,1,0,0,1 2,9,1,3,3577,4,1,1,0,1,2,0,26,0,2,1,0,2,1,1,0 2,24,0,4,5804,3,1,4,0,0,2,0,27,0,0,2,0,1,1,0,0 2,18,2,5,2169,1,1,4,3,0,2,3,28,0,0,1,0,1,0,0,1 0,24,1,0,2439,1,4,4,1,0,4,0,35,0,0,1,0,1,0,0,1 2,27,0,2,4526,3,4,4,0,0,2,0,32,2,0,2,1,2,0,0,0 2,10,1,2,2210,1,1,2,0,0,2,0,25,1,2,1,1,1,1,0,1 2,15,1,2,2221,2,1,2,1,0,4,3,20,0,2,1,0,1,1,0,0 0,18,1,0,2389,1,4,4,1,0,1,3,27,2,0,1,0,1,1,0,0 2,12,0,2,3331,1,0,2,0,0,4,1,42,2,0,1,0,1,1,0,0 2,36,1,5,7409,0,0,3,0,0,2,1,37,0,0,2,0,1,1,0,0 0,12,1,2,652,1,0,4,1,0,4,1,24,0,2,1,0,1,1,0,0 2,36,2,2,7678,2,2,2,1,0,4,3,40,0,0,2,0,1,0,0,0 3,6,0,3,1343,1,0,1,0,0,4,0,46,0,0,2,0,2,1,1,0 0,24,0,5,1382,4,2,4,0,0,1,0,26,0,0,2,0,1,0,0,0 2,15,1,6,874,0,4,4,1,0,1,0,24,0,0,1,0,1,1,0,0 0,12,1,2,3590,1,1,2,0,2,2,1,29,0,0,1,1,2,1,0,0 1,11,0,3,1322,3,1,4,1,0,4,3,40,0,0,2,0,1,1,0,0 0,18,4,0,1940,1,4,3,0,2,4,2,36,1,1,1,2,1,0,0,0 2,36,1,0,3595,1,0,4,0,0,2,3,28,0,0,1,0,1,1,0,0 0,9,1,3,1422,1,4,3,0,0,2,2,27,0,1,1,2,1,0,0,1 2,30,0,0,6742,0,2,2,0,0,3,1,36,0,0,2,0,1,1,0,0 2,24,1,4,7814,1,2,3,0,0,3,3,38,0,0,1,2,1,0,0,0 2,24,1,4,9277,0,1,2,2,0,4,2,48,0,1,1,0,1,0,0,0 1,30,0,3,2181,0,0,4,0,0,4,0,36,0,0,2,0,1,1,0,0 2,18,0,0,1098,1,3,4,1,0,4,3,65,0,0,2,3,1,1,0,0 1,24,1,2,4057,1,2,3,2,0,3,3,43,0,0,1,0,1,0,0,1 0,12,1,1,795,1,4,4,1,0,4,1,53,0,0,1,0,1,1,0,1 1,24,0,5,2825,0,2,4,0,0,3,2,34,0,0,2,0,2,0,0,0 1,48,1,5,15672,1,1,2,0,0,2,3,23,0,0,1,0,1,0,0,1 2,36,0,3,6614,1,0,4,0,0,4,3,34,0,0,2,2,1,0,0,0 2,28,4,4,7824,0,4,3,0,1,4,0,40,1,2,2,0,2,0,0,0 0,27,0,5,2442,1,0,4,0,0,4,3,43,2,0,4,2,2,0,0,0 2,15,0,0,1829,1,0,4,0,0,4,3,46,0,0,2,0,1,0,0,0 0,12,0,3,2171,1,1,4,0,0,4,1,38,1,0,2,1,1,1,1,0 1,36,0,4,5800,1,1,3,0,0,4,3,34,0,0,2,0,1,0,0,0 2,18,0,0,1169,0,1,4,0,0,3,1,29,0,0,2,0,1,0,0,0 2,36,2,4,8947,0,2,3,0,0,2,3,31,2,0,1,2,2,0,0,0 0,21,1,0,2606,1,4,4,1,0,4,1,28,0,2,1,2,1,0,0,0 2,12,0,2,1592,3,2,3,1,0,2,1,35,0,0,1,0,1,1,1,0 2,15,1,2,2186,0,2,1,1,0,4,0,33,1,2,1,1,1,1,0,0 0,18,1,2,4153,1,1,2,0,2,3,3,42,0,0,1,0,1,1,0,1 0,16,0,3,2625,1,0,2,0,1,4,1,43,1,2,1,0,1,0,0,1 2,20,0,3,3485,0,4,2,2,0,4,0,44,0,0,2,0,1,0,0,0 2,36,0,4,10477,0,0,2,0,0,4,2,42,0,1,2,0,1,1,0,0 2,15,1,0,1386,0,1,4,3,0,2,0,40,0,2,1,0,1,0,0,0 2,24,1,0,1278,1,0,4,0,0,1,0,36,0,0,1,2,1,0,0,0 0,12,1,0,1107,1,1,2,0,0,2,0,20,0,2,1,2,2,0,0,0 0,21,1,3,3763,0,2,2,0,2,2,0,24,0,0,1,1,1,1,1,0 1,36,1,1,3711,0,1,2,3,0,2,3,27,0,0,1,0,1,1,0,0 2,15,2,4,3594,1,4,1,1,0,2,1,46,0,0,2,1,1,1,0,0 1,9,1,3,3195,0,1,1,1,0,2,0,33,0,0,1,1,1,1,0,0 2,36,2,0,4454,1,1,4,1,0,4,0,34,0,0,2,0,1,1,0,0 1,24,0,2,4736,1,4,2,1,0,4,3,25,1,0,1,1,1,1,0,1 1,30,1,0,2991,0,0,2,1,0,4,3,25,0,0,1,0,1,1,0,0 2,11,1,5,2142,3,0,1,2,0,2,0,28,0,0,1,0,1,0,0,0 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1,128,48,45,194,40.5,0.613,24,1 0,161,50,0,0,21.9,0.254,65,0 6,151,62,31,120,35.5,0.692,28,0 2,146,70,38,360,28,0.337,29,1 0,126,84,29,215,30.7,0.52,24,0 14,100,78,25,184,36.6,0.412,46,1 8,112,72,0,0,23.6,0.84,58,0 0,167,0,0,0,32.3,0.839,30,1 2,144,58,33,135,31.6,0.422,25,1 5,77,82,41,42,35.8,0.156,35,0 5,115,98,0,0,52.9,0.209,28,1 3,150,76,0,0,21,0.207,37,0 2,120,76,37,105,39.7,0.215,29,0 10,161,68,23,132,25.5,0.326,47,1 0,137,68,14,148,24.8,0.143,21,0 0,128,68,19,180,30.5,1.391,25,1 2,124,68,28,205,32.9,0.875,30,1 6,80,66,30,0,26.2,0.313,41,0 0,106,70,37,148,39.4,0.605,22,0 2,155,74,17,96,26.6,0.433,27,1 3,113,50,10,85,29.5,0.626,25,0 7,109,80,31,0,35.9,1.127,43,1 2,112,68,22,94,34.1,0.315,26,0 3,99,80,11,64,19.3,0.284,30,0 3,182,74,0,0,30.5,0.345,29,1 3,115,66,39,140,38.1,0.15,28,0 6,194,78,0,0,23.5,0.129,59,1 4,129,60,12,231,27.5,0.527,31,0 3,112,74,30,0,31.6,0.197,25,1 0,124,70,20,0,27.4,0.254,36,1 13,152,90,33,29,26.8,0.731,43,1 2,112,75,32,0,35.7,0.148,21,0 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0,73,0,0,0,21.1,0.342,25,0 11,111,84,40,0,46.8,0.925,45,1 2,112,78,50,140,39.4,0.175,24,0 3,132,80,0,0,34.4,0.402,44,1 2,82,52,22,115,28.5,1.699,25,0 6,123,72,45,230,33.6,0.733,34,0 0,188,82,14,185,32,0.682,22,1 0,67,76,0,0,45.3,0.194,46,0 1,89,24,19,25,27.8,0.559,21,0 1,173,74,0,0,36.8,0.088,38,1 1,109,38,18,120,23.1,0.407,26,0 1,108,88,19,0,27.1,0.4,24,0 6,96,0,0,0,23.7,0.19,28,0 1,124,74,36,0,27.8,0.1,30,0 7,150,78,29,126,35.2,0.692,54,1 4,183,0,0,0,28.4,0.212,36,1 1,124,60,32,0,35.8,0.514,21,0 1,181,78,42,293,40,1.258,22,1 1,92,62,25,41,19.5,0.482,25,0 0,152,82,39,272,41.5,0.27,27,0 1,111,62,13,182,24,0.138,23,0 3,106,54,21,158,30.9,0.292,24,0 3,174,58,22,194,32.9,0.593,36,1 7,168,88,42,321,38.2,0.787,40,1 6,105,80,28,0,32.5,0.878,26,0 11,138,74,26,144,36.1,0.557,50,1 3,106,72,0,0,25.8,0.207,27,0 6,117,96,0,0,28.7,0.157,30,0 2,68,62,13,15,20.1,0.257,23,0 9,112,82,24,0,28.2,1.282,50,1 0,119,0,0,0,32.4,0.141,24,1 2,112,86,42,160,38.4,0.246,28,0 2,92,76,20,0,24.2,1.698,28,0 6,183,94,0,0,40.8,1.461,45,0 0,94,70,27,115,43.5,0.347,21,0 2,108,64,0,0,30.8,0.158,21,0 4,90,88,47,54,37.7,0.362,29,0 0,125,68,0,0,24.7,0.206,21,0 0,132,78,0,0,32.4,0.393,21,0 5,128,80,0,0,34.6,0.144,45,0 4,94,65,22,0,24.7,0.148,21,0 7,114,64,0,0,27.4,0.732,34,1 0,102,78,40,90,34.5,0.238,24,0 2,111,60,0,0,26.2,0.343,23,0 1,128,82,17,183,27.5,0.115,22,0 10,92,62,0,0,25.9,0.167,31,0 13,104,72,0,0,31.2,0.465,38,1 5,104,74,0,0,28.8,0.153,48,0 2,94,76,18,66,31.6,0.649,23,0 7,97,76,32,91,40.9,0.871,32,1 1,100,74,12,46,19.5,0.149,28,0 0,102,86,17,105,29.3,0.695,27,0 4,128,70,0,0,34.3,0.303,24,0 6,147,80,0,0,29.5,0.178,50,1 4,90,0,0,0,28,0.61,31,0 3,103,72,30,152,27.6,0.73,27,0 2,157,74,35,440,39.4,0.134,30,0 1,167,74,17,144,23.4,0.447,33,1 0,179,50,36,159,37.8,0.455,22,1 11,136,84,35,130,28.3,0.26,42,1 0,107,60,25,0,26.4,0.133,23,0 1,91,54,25,100,25.2,0.234,23,0 1,117,60,23,106,33.8,0.466,27,0 5,123,74,40,77,34.1,0.269,28,0 2,120,54,0,0,26.8,0.455,27,0 1,106,70,28,135,34.2,0.142,22,0 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1,140,74,26,180,24.1,0.828,23,0 1,144,82,46,180,46.1,0.335,46,1 8,107,80,0,0,24.6,0.856,34,0 13,158,114,0,0,42.3,0.257,44,1 2,121,70,32,95,39.1,0.886,23,0 7,129,68,49,125,38.5,0.439,43,1 2,90,60,0,0,23.5,0.191,25,0 7,142,90,24,480,30.4,0.128,43,1 3,169,74,19,125,29.9,0.268,31,1 0,99,0,0,0,25,0.253,22,0 4,127,88,11,155,34.5,0.598,28,0 4,118,70,0,0,44.5,0.904,26,0 2,122,76,27,200,35.9,0.483,26,0 6,125,78,31,0,27.6,0.565,49,1 1,168,88,29,0,35,0.905,52,1 2,129,0,0,0,38.5,0.304,41,0 4,110,76,20,100,28.4,0.118,27,0 6,80,80,36,0,39.8,0.177,28,0 10,115,0,0,0,0,0.261,30,1 2,127,46,21,335,34.4,0.176,22,0 9,164,78,0,0,32.8,0.148,45,1 2,93,64,32,160,38,0.674,23,1 3,158,64,13,387,31.2,0.295,24,0 5,126,78,27,22,29.6,0.439,40,0 10,129,62,36,0,41.2,0.441,38,1 0,134,58,20,291,26.4,0.352,21,0 3,102,74,0,0,29.5,0.121,32,0 7,187,50,33,392,33.9,0.826,34,1 3,173,78,39,185,33.8,0.97,31,1 10,94,72,18,0,23.1,0.595,56,0 1,108,60,46,178,35.5,0.415,24,0 5,97,76,27,0,35.6,0.378,52,1 4,83,86,19,0,29.3,0.317,34,0 1,114,66,36,200,38.1,0.289,21,0 1,149,68,29,127,29.3,0.349,42,1 5,117,86,30,105,39.1,0.251,42,0 1,111,94,0,0,32.8,0.265,45,0 4,112,78,40,0,39.4,0.236,38,0 1,116,78,29,180,36.1,0.496,25,0 0,141,84,26,0,32.4,0.433,22,0 2,175,88,0,0,22.9,0.326,22,0 2,92,52,0,0,30.1,0.141,22,0 3,130,78,23,79,28.4,0.323,34,1 8,120,86,0,0,28.4,0.259,22,1 2,174,88,37,120,44.5,0.646,24,1 2,106,56,27,165,29,0.426,22,0 2,105,75,0,0,23.3,0.56,53,0 4,95,60,32,0,35.4,0.284,28,0 0,126,86,27,120,27.4,0.515,21,0 8,65,72,23,0,32,0.6,42,0 2,99,60,17,160,36.6,0.453,21,0 1,102,74,0,0,39.5,0.293,42,1 11,120,80,37,150,42.3,0.785,48,1 3,102,44,20,94,30.8,0.4,26,0 1,109,58,18,116,28.5,0.219,22,0 9,140,94,0,0,32.7,0.734,45,1 13,153,88,37,140,40.6,1.174,39,0 12,100,84,33,105,30,0.488,46,0 1,147,94,41,0,49.3,0.358,27,1 1,81,74,41,57,46.3,1.096,32,0 3,187,70,22,200,36.4,0.408,36,1 6,162,62,0,0,24.3,0.178,50,1 4,136,70,0,0,31.2,1.182,22,1 1,121,78,39,74,39,0.261,28,0 3,108,62,24,0,26,0.223,25,0 0,181,88,44,510,43.3,0.222,26,1 8,154,78,32,0,32.4,0.443,45,1 1,128,88,39,110,36.5,1.057,37,1 7,137,90,41,0,32,0.391,39,0 0,123,72,0,0,36.3,0.258,52,1 1,106,76,0,0,37.5,0.197,26,0 6,190,92,0,0,35.5,0.278,66,1 2,88,58,26,16,28.4,0.766,22,0 9,170,74,31,0,44,0.403,43,1 9,89,62,0,0,22.5,0.142,33,0 10,101,76,48,180,32.9,0.171,63,0 2,122,70,27,0,36.8,0.34,27,0 5,121,72,23,112,26.2,0.245,30,0 1,126,60,0,0,30.1,0.349,47,1 1,93,70,31,0,30.4,0.315,23,0""" #------------------------------------------------------------------------------------------------------------------------ #------------------------------------------------------------------------------------------------------------------------ #------------------------------------------------------------------------------------------------------------------------ #------------------------------------------------------------------------------------------------------------------------ _name2data = {'glass':_glass, 'seeds':_seeds, 'ionosphere':_ionosphere, 'sonar':_sonar, 'blood_transfusion':_blood_transfusion, 'balance':_balance, 'vehicle':_vehicle, 'ecoli':_ecoli, 'yeast':_yeast, 'tic_tac_toe':_tic_tac_toe, 'heart': _heart, 'haberman': _haberman, 'german_credit': _german_credit, 'diabets':_diabets, } def _get_data(name): input = _name2data.get(name,None) if input is not None: input = StringIO(input) else: input = name + '.csv' Z = np.loadtxt(input, delimiter=',') return Z def load_local_glass(): Z = _get_data('glass') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_seeds(): Z = _get_data('seeds') X=Z[:,:-1] y=Z[:,-1].astype(int) return X,y def load_local_ionosphere(): Z = _get_data('ionosphere') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_sonar(): Z = _get_data('sonar') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_blood_transfusion(): Z = _get_data('blood_transfusion') X=Z[:,:-1] y=Z[:,-1].astype(int) return X,y def load_local_balance(): Z = _get_data('balance') X=Z[:,1:] y=Z[:,0].astype(int) return X,y def load_local_vehicle(): Z = _get_data('vehicle') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_ecoli(): Z = _get_data('ecoli') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_yeast(): Z = _get_data('yeast') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_tic_tac_toe(): Z = _get_data('tic_tac_toe') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_heart(): Z = _get_data('heart') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_haberman(): Z = _get_data('haberman') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_german_credit(): Z = _get_data('german_credit') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y def load_local_diabets(): Z = _get_data('diabets') X=Z[:,1:-1] y=Z[:,-1].astype(int) return X,y

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55.361609

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1

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1

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null

0

6

a2079f311c011a4f3a38af03b8cf16c287bf6985

930

py

Python

temboo/core/Library/Box/Collaborations/__init__.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

7

2016-03-07T02:07:21.000Z

2022-01-21T02:22:41.000Z

temboo/core/Library/Box/Collaborations/__init__.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

null

temboo/core/Library/Box/Collaborations/__init__.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

8

2016-06-14T06:01:11.000Z

2020-04-22T09:21:44.000Z

from temboo.Library.Box.Collaborations.AddCollaboration import AddCollaboration, AddCollaborationInputSet, AddCollaborationResultSet, AddCollaborationChoreographyExecution from temboo.Library.Box.Collaborations.DeleteCollaboration import DeleteCollaboration, DeleteCollaborationInputSet, DeleteCollaborationResultSet, DeleteCollaborationChoreographyExecution from temboo.Library.Box.Collaborations.GetCollaboration import GetCollaboration, GetCollaborationInputSet, GetCollaborationResultSet, GetCollaborationChoreographyExecution from temboo.Library.Box.Collaborations.GetPendingCollaborations import GetPendingCollaborations, GetPendingCollaborationsInputSet, GetPendingCollaborationsResultSet, GetPendingCollaborationsChoreographyExecution from temboo.Library.Box.Collaborations.UpdateCollaboration import UpdateCollaboration, UpdateCollaborationInputSet, UpdateCollaborationResultSet, UpdateCollaborationChoreographyExecution

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930

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true

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null

0

1

0

1

0

1

0

6

a217f402576e06b01719e48e2ec96a22ef60f1ef

86

py

Python

graphene_django/forms/__init__.py

joerhodes3/graphene-django

99892eba853bf060d25a4314c9db3ad28949c824

[ "MIT" ]

null

graphene_django/forms/__init__.py

joerhodes3/graphene-django

99892eba853bf060d25a4314c9db3ad28949c824

[ "MIT" ]

null

graphene_django/forms/__init__.py

joerhodes3/graphene-django

99892eba853bf060d25a4314c9db3ad28949c824

[ "MIT" ]

null

from .forms import GlobalIDFormField, GlobalIDMultipleChoiceField, HeaderForm # noqa

43

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86

10.428571

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86

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86

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1

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null

0

1

0

1

0

1

0

6

bf68ebc92a8c72ed3ec06f1a23785197eee6bbea

38

py

Python

IA/Python/5/5.1/2.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

1

2022-02-23T12:47:00.000Z

IA/Python/5/5.1/2.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

null

IA/Python/5/5.1/2.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

null

def search(x, ln): return x in ln

12.666667

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0.605263

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0.289474

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0.851852

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null

0

1

0

1

0

6

bf8a16654d6b04a56a187eb703641e22b5766022

76

py

Python

app/blog/__init__.py

chetat/market-research

8eac059f91ea41b8b885d1f2bbe14029292bf61c

[ "MIT" ]

null

app/blog/__init__.py

chetat/market-research

8eac059f91ea41b8b885d1f2bbe14029292bf61c

[ "MIT" ]

null

app/blog/__init__.py

chetat/market-research

8eac059f91ea41b8b885d1f2bbe14029292bf61c

[ "MIT" ]

1

2021-03-15T19:24:38.000Z

from app.blog.views import blog # noqa from app.blog import errors # noqa

25.333333

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6

bf8e2132bd11a7cdeb85a5871c2b3ebaf9c92c05

126

py

Python

authApp/admin.py

Alex-Bruno/steller-web

9dba1766989f9aaf165a26434dda40cf5c5cc409

[ "MIT" ]

null

authApp/admin.py

Alex-Bruno/steller-web

9dba1766989f9aaf165a26434dda40cf5c5cc409

[ "MIT" ]

null

authApp/admin.py

Alex-Bruno/steller-web

9dba1766989f9aaf165a26434dda40cf5c5cc409

[ "MIT" ]

null

from django.contrib import admin from .models import User @admin.register(User) class UserAdmin(admin.ModelAdmin): pass

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null

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1

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1

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6

bfa5393ee5f707ad2ed686b0f46a7809b0b27831

93

py

Python

amazonadapi/__init__.py

accuenmedia/amazonadapi

6bf16b8d616745886c6defc8984e9e40a6666c5a

[ "MIT" ]

null

amazonadapi/__init__.py

accuenmedia/amazonadapi

6bf16b8d616745886c6defc8984e9e40a6666c5a

[ "MIT" ]

null

amazonadapi/__init__.py

accuenmedia/amazonadapi

6bf16b8d616745886c6defc8984e9e40a6666c5a

[ "MIT" ]

null

#!/usr/bin/env python from amazonadapi.base import Base from amazonadapi.order import Order

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1

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1

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1

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6

44a5aea3b968b100c625330b619470465a600dea

26

py

Python

hius/__init__.py

WoolenSweater/liteapi

01339f65b68af67253459609fb60ae35e5a50604

[ "MIT" ]

null

hius/__init__.py

WoolenSweater/liteapi

01339f65b68af67253459609fb60ae35e5a50604

[ "MIT" ]

null

hius/__init__.py

WoolenSweater/liteapi

01339f65b68af67253459609fb60ae35e5a50604

[ "MIT" ]

null

from hius.app import Hius

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25

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0

null

0

1

0

1

0

1

0

6

44a681c04d60aaff5a13039071de8cb30e8d5423

5,908

py

Python

ctrack/register/tests/test_css.py

yulqen/ctrack

b370cdda72e7fab9b85a4e737923fabef679e31d

[ "MIT" ]

null

ctrack/register/tests/test_css.py

yulqen/ctrack

b370cdda72e7fab9b85a4e737923fabef679e31d

[ "MIT" ]

16

2020-08-13T09:18:57.000Z

2021-11-05T14:32:05.000Z

ctrack/register/tests/test_css.py

hammerheadlemon/ctrack

b370cdda72e7fab9b85a4e737923fabef679e31d

[ "MIT" ]

null

import pytest from ctrack.register.css import Swimlane from ctrack.register.models import CAFSingleDateEvent, EventType pytestmark = pytest.mark.django_db @pytest.mark.parametrize( "e_type,css_str,id_str", [ ( EventType.CAF_INITIAL_CAF_RECEIVED.name, ' style="background-color: green; color: white;"', "caf-initial-received-event", ), ( EventType.CAF_INITIAL_REVIEW_COMPLETE.name, ' style="background-color: green; color: white;"', "caf-initial-review-complete-event", ), ], ) def test_can_get_class_string(caf, user, e_type, css_str, id_str): org_name = caf.organisation.name event = CAFSingleDateEvent.objects.create( type_descriptor=e_type, related_caf=caf, date="2020-10-20", user=user ) sl = Swimlane(org_name, [event]) assert sl.tag_attrs(event).inline_style == css_str assert sl.tag_attrs(event).id_str == id_str def test_progress_chart_css_initial_review_only(caf, user): accept = ("<tr>\n" "<td>{}</td>\n" "<td style=\"background-color: green; color: white;\">CAF_INITIAL_CAF_RECEIVED</td>\n" "<td>CAF_INITIAL_REVIEW_COMPLETE</td>\n" "<td>CAF_FEEDBACK_EMAILED_OES</td>\n" "<td>CAF_RECEIVED</td>\n" "<td>CAF_EMAILED_ROSA</td>\n" "<td>CAF_VALIDATION_SIGN_OFF</td>\n" "<td>CAF_VALIDATION_RECORD_EMAILED_TO_OES</td>\n" "<td>CAF_PEER_REVIEW_PERIOD</td>\n" "<td>CAF_VALIDATION_PERIOD</td>\n" "</tr>") org_name = caf.organisation.name caf_initial = CAFSingleDateEvent.objects.create( type_descriptor=EventType.CAF_INITIAL_CAF_RECEIVED.name, related_caf=caf, date="2020-10-20", user=user, ) output = Swimlane(org_name, [caf_initial]) assert output.tr == accept.format(org_name) def test_progress_chart_css_initial_two_events(caf, user): accept = ("<tr>\n" "<td>{}</td>\n" "<td style=\"background-color: green; color: white;\">CAF_INITIAL_CAF_RECEIVED</td>\n" "<td style=\"background-color: green; color: white;\">CAF_INITIAL_REVIEW_COMPLETE</td>\n" "<td>CAF_FEEDBACK_EMAILED_OES</td>\n" "<td>CAF_RECEIVED</td>\n" "<td>CAF_EMAILED_ROSA</td>\n" "<td>CAF_VALIDATION_SIGN_OFF</td>\n" "<td>CAF_VALIDATION_RECORD_EMAILED_TO_OES</td>\n" "<td>CAF_PEER_REVIEW_PERIOD</td>\n" "<td>CAF_VALIDATION_PERIOD</td>\n" "</tr>") org_name = caf.organisation.name caf_initial = CAFSingleDateEvent.objects.create( type_descriptor=EventType.CAF_INITIAL_CAF_RECEIVED.name, related_caf=caf, date="2020-10-20", user=user, ) caf_reviewed = CAFSingleDateEvent.objects.create( type_descriptor=EventType.CAF_INITIAL_REVIEW_COMPLETE.name, related_caf=caf, date="2020-10-20", user=user, ) output = Swimlane(org_name, [caf_initial, caf_reviewed]) assert output.tr == accept.format(org_name) def test_progress_chart_css_second_event(caf, user): accept = ("<tr>\n" "<td>{}</td>\n" "<td>CAF_INITIAL_CAF_RECEIVED</td>\n" "<td style=\"background-color: green; color: white;\">CAF_INITIAL_REVIEW_COMPLETE</td>\n" "<td>CAF_FEEDBACK_EMAILED_OES</td>\n" "<td>CAF_RECEIVED</td>\n" "<td>CAF_EMAILED_ROSA</td>\n" "<td>CAF_VALIDATION_SIGN_OFF</td>\n" "<td>CAF_VALIDATION_RECORD_EMAILED_TO_OES</td>\n" "<td>CAF_PEER_REVIEW_PERIOD</td>\n" "<td>CAF_VALIDATION_PERIOD</td>\n" "</tr>") org_name = caf.organisation.name caf_reviewed = CAFSingleDateEvent.objects.create( type_descriptor=EventType.CAF_INITIAL_REVIEW_COMPLETE.name, related_caf=caf, date="2020-10-20", user=user, ) output = Swimlane(org_name, [caf_reviewed]) assert output.tr == accept.format(org_name) def test_table_row_builder(user, caf): e1 = CAFSingleDateEvent.objects.create( type_descriptor=EventType.CAF_INITIAL_CAF_RECEIVED.name, related_caf=caf, date="2020-10-20", user=user, ) e2 = CAFSingleDateEvent.objects.create( type_descriptor=EventType.CAF_INITIAL_REVIEW_COMPLETE.name, related_caf=caf, date="2020-10-20", user=user, ) org_name = caf.organisation.name sl = Swimlane(org_name, [e1, e2]) assert sl.table_row_builder() == ( "<tr>\n" f"<td>{caf.organisation.name}</td>\n" '<td style="background-color: green; color: white;">CAF_INITIAL_CAF_RECEIVED</td>\n' '<td style="background-color: green; color: white;">CAF_INITIAL_REVIEW_COMPLETE</td>\n' "<td>CAF_FEEDBACK_EMAILED_OES</td>\n" "<td>CAF_RECEIVED</td>\n" "<td>CAF_EMAILED_ROSA</td>\n" "<td>CAF_VALIDATION_SIGN_OFF</td>\n" "<td>CAF_VALIDATION_RECORD_EMAILED_TO_OES</td>\n" "<td>CAF_PEER_REVIEW_PERIOD</td>\n" "<td>CAF_VALIDATION_PERIOD</td>\n" "</tr>" ) def test_table_row_builder_with_no_events(user, caf): org_name = caf.organisation.name sl = Swimlane(org_name, []) assert sl.table_row_builder() == ( "<tr>\n" f"<td>{caf.organisation.name}</td>\n" "<td>CAF_INITIAL_CAF_RECEIVED</td>\n" '<td>CAF_INITIAL_REVIEW_COMPLETE</td>\n' "<td>CAF_FEEDBACK_EMAILED_OES</td>\n" "<td>CAF_RECEIVED</td>\n" "<td>CAF_EMAILED_ROSA</td>\n" "<td>CAF_VALIDATION_SIGN_OFF</td>\n" "<td>CAF_VALIDATION_RECORD_EMAILED_TO_OES</td>\n" "<td>CAF_PEER_REVIEW_PERIOD</td>\n" "<td>CAF_VALIDATION_PERIOD</td>\n" "</tr>" )

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null

0

1

0

null

0

6

7812cc9c402e0590bb7e7d7636b0ca341976a926

42

py

Python

whatlangid/exceptions.py

bung87/whatlangid

594c7d1c5bf5ea277426190c65900d38020b4391

[ "Apache-2.0" ]

6

2018-06-29T19:28:29.000Z

2020-04-01T11:22:44.000Z

whatlangid/exceptions.py

bung87/whatlangid

594c7d1c5bf5ea277426190c65900d38020b4391

[ "Apache-2.0" ]

5

2018-05-31T02:40:19.000Z

2019-11-04T07:12:56.000Z

whatlangid/exceptions.py

bung87/whatlangid

594c7d1c5bf5ea277426190c65900d38020b4391

[ "Apache-2.0" ]

3

2018-06-29T19:29:08.000Z

2020-04-01T11:51:37.000Z

class InsufficientError(ValueError): pass

21

41

0.857143

4

42

9

1

0

0.071429

42

1

42

0.923077

0

1

0

true

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null

0

1

0

null

0

1

0

1

0

6

7885c54204555c866d629dcbb34ed60d1118a623

3,392

py

Python

scripts/immgen.asm.py

devbored/pineapplecore

311f703347fc448ae5792bbb33e896d58931486a

[ "MIT" ]

null

scripts/immgen.asm.py

devbored/pineapplecore

311f703347fc448ae5792bbb33e896d58931486a

[ "MIT" ]

null

scripts/immgen.asm.py

devbored/pineapplecore

311f703347fc448ae5792bbb33e896d58931486a

[ "MIT" ]

null

#! /usr/bin/env python3 from common import * # Try each immediate-based RV32I instruction with random operands as the test vector test_assembly = f''' # Need to use (L#) for jump labels here to later get imm. value from for gold vector L0: jalr x{randReg(x0=False)}, x{randReg(x0=False)}, {randImmI()} L1: lb x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L2: lh x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L3: lw x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L4: lbu x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L5: lhu x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L6: addi x{randReg(x0=False)}, x{randReg(x0=False)}, {randImmI()} L7: slti x{randReg(x0=False)}, x{randReg(x0=False)}, {randImmI()} L8: sltiu x{randReg(x0=False)}, x{randReg(x0=False)}, {randImmI()} L9: xori x{randReg(x0=False)}, x{randReg(x0=False)}, {randImmI()} L10: ori x{randReg(x0=False)}, x{randReg(x0=False)}, {randImmI()} L11: andi x{randReg(x0=False)}, x{randReg(x0=False)}, {randImmI()} L12: slli x{randReg(x0=False)}, x{randReg(x0=False)}, {randShamt()} L13: srli x{randReg(x0=False)}, x{randReg(x0=False)}, {randShamt()} L14: srai x{randReg(x0=False)}, x{randReg(x0=False)}, {randShamt()} L15: sb x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L16: sh x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L17: sw x{randReg(x0=False)}, {randImmI()}(x{randReg(x0=False)}) L18: lui x{randReg(x0=False)}, {randImmU()} L19: auipc x{randReg(x0=False)}, {randImmU()} L20: jal x{randReg(x0=False)}, L{random.randint(0,20)} beq x{randReg(x0=False)}, x{randReg(x0=False)}, L{random.randint(0,20)} bne x{randReg(x0=False)}, x{randReg(x0=False)}, L{random.randint(0,20)} blt x{randReg(x0=False)}, x{randReg(x0=False)}, L{random.randint(0,20)} bge x{randReg(x0=False)}, x{randReg(x0=False)}, L{random.randint(0,20)} bltu x{randReg(x0=False)}, x{randReg(x0=False)}, L{random.randint(0,20)} bgeu x{randReg(x0=False)}, x{randReg(x0=False)}, L{random.randint(0,20)} ''' if __name__ == "__main__": # Input test vector outfile = f"{basenameNoExt('build', __file__)}.s" with open(outfile, 'w') as fp: print(test_assembly, file=fp) # Output/gold test vector outfileGold = f"{basenameNoExt('build', __file__)}_gold.mem" test_gold = asmStr2AsmList(test_assembly) with open(outfileGold, 'w') as fp: lineCount = 0 for gold in test_gold: if len(gold) == 4: imm = gold[3] if 'b' not in gold[0] else (int(gold[3][1:]) - lineCount)*4 print(f"{int(imm) & 0xffffffff:032b}", file=fp) else: if '(' in gold[2]: imm = gold[2].split('(')[0] print(f"{int(imm) & 0xffffffff:032b}", file=fp) else: imm = gold[2] if 'j' not in gold[0] else (int(gold[2][1:]) - lineCount)*4 if 'lui' == gold[0] or 'auipc' == gold[0]: print(f"{((int(imm) & 0xffffffff) << 12):032b}", file=fp) else: print(f"{int(imm) & 0xffffffff:032b}", file=fp) lineCount += 1

53.84127

93

0.568396

490

3,392

3.889796

0.259184

0.214061

0.267576

0.401364

0.63851

0.614376

0.601784

0.579748

0.562959

0.147954

0

0.055684

0.237618

3,392

62

94

54.709677

0.681361

0.043337

0

0.111111

0

0.481481

0.710892

0.426412

0

0.012342

0

1

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false

0

0.018519

0

0.018519

0.092593

0

null

1

0

1

null

0

6

78afd7dd952adecb53d7c602516c6f441e1fe422

79

py

Python

renderer/__init__.py

Jack12xl/a-toy-fluid-engine

45ce4007ce6e804dcfdee8da307e131c9c3e7c7d

[ "MIT" ]

21

2020-09-17T10:51:55.000Z

2022-03-15T20:27:00.000Z

renderer/__init__.py

Jack12xl/a-toy-fluid-engine

45ce4007ce6e804dcfdee8da307e131c9c3e7c7d

[ "MIT" ]

8

2020-09-18T08:52:34.000Z

2021-02-07T09:27:49.000Z

renderer/__init__.py

Jack12xl/myFluid

45ce4007ce6e804dcfdee8da307e131c9c3e7c7d

[ "MIT" ]

1

2020-09-20T11:10:35.000Z

from .Renderer2D import * from .Renderer25D import * from .Renderer29D import *

26.333333

26

0.78481

9

79

6.888889

0.555556

0.322581

0

0.073529

0.139241

79

3

27

26.333333

0.838235

0

1

0

true

0

1

0

1

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null

1

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0

null

0

1

0

1

0

1

0

6

1551f26e7ff07daab4ba7d84be16723a3b74fd64

7,854

py

Python

tests/unit/grpc_internals/zeebe_job_adapter_test.py

verotel/pyzeebe

8fc8c07a9316cc10155cd03fb0b45c226fecf469

[ "MIT" ]

null

tests/unit/grpc_internals/zeebe_job_adapter_test.py

verotel/pyzeebe

8fc8c07a9316cc10155cd03fb0b45c226fecf469

[ "MIT" ]

null

tests/unit/grpc_internals/zeebe_job_adapter_test.py

verotel/pyzeebe

8fc8c07a9316cc10155cd03fb0b45c226fecf469

[ "MIT" ]

null

from random import randint from unittest.mock import MagicMock from uuid import uuid4 import grpc import pytest from zeebe_grpc.gateway_pb2 import * from pyzeebe.exceptions import ActivateJobsRequestInvalid, JobAlreadyDeactivated, JobNotFound from pyzeebe.job.job import Job from pyzeebe.task.task import Task from tests.unit.utils.grpc_utils import GRPCStatusCode from tests.unit.utils.random_utils import RANDOM_RANGE, random_job def create_random_task_and_activate(grpc_servicer, task_type: str = None) -> str: if task_type: mock_task_type = task_type else: mock_task_type = str(uuid4()) task = Task(task_type=mock_task_type, task_handler=lambda x: x, exception_handler=lambda x: x) job = random_job(task) grpc_servicer.active_jobs[job.key] = job return mock_task_type def get_first_active_job(task_type, zeebe_adapter) -> Job: return next(zeebe_adapter.activate_jobs(task_type=task_type, max_jobs_to_activate=1, request_timeout=10, timeout=100, variables_to_fetch=[], worker=str(uuid4()))) def test_activate_jobs(zeebe_adapter, grpc_servicer): task_type = create_random_task_and_activate(grpc_servicer) active_jobs_count = randint(4, 100) counter = 0 for i in range(0, active_jobs_count): create_random_task_and_activate(grpc_servicer, task_type) for job in zeebe_adapter.activate_jobs(task_type=task_type, worker=str(uuid4()), timeout=randint(10, 100), request_timeout=100, max_jobs_to_activate=1, variables_to_fetch=[]): counter += 1 assert isinstance(job, Job) assert counter == active_jobs_count + 1 def test_activate_jobs_invalid_worker(zeebe_adapter): with pytest.raises(ActivateJobsRequestInvalid): next(zeebe_adapter.activate_jobs(task_type=str(uuid4()), worker=None, timeout=randint(10, 100), request_timeout=100, max_jobs_to_activate=1, variables_to_fetch=[])) def test_activate_jobs_invalid_job_timeout(zeebe_adapter): with pytest.raises(ActivateJobsRequestInvalid): next(zeebe_adapter.activate_jobs(task_type=str(uuid4()), worker=str(uuid4()), timeout=0, request_timeout=100, max_jobs_to_activate=1, variables_to_fetch=[])) def test_activate_jobs_invalid_task_type(zeebe_adapter): with pytest.raises(ActivateJobsRequestInvalid): next(zeebe_adapter.activate_jobs(task_type=None, worker=str(uuid4()), timeout=randint(10, 100), request_timeout=100, max_jobs_to_activate=1, variables_to_fetch=[])) def test_activate_jobs_invalid_max_jobs(zeebe_adapter): with pytest.raises(ActivateJobsRequestInvalid): next(zeebe_adapter.activate_jobs(task_type=str(uuid4()), worker=str(uuid4()), timeout=randint(10, 100), request_timeout=100, max_jobs_to_activate=0, variables_to_fetch=[])) def test_activate_jobs_common_errors_called(zeebe_adapter): zeebe_adapter._common_zeebe_grpc_errors = MagicMock() error = grpc.RpcError() error._state = GRPCStatusCode(grpc.StatusCode.INTERNAL) zeebe_adapter._gateway_stub.ActivateJobs = MagicMock(side_effect=error) jobs = zeebe_adapter.activate_jobs(task_type=str(uuid4()), worker=str(uuid4()), timeout=randint(10, 100), request_timeout=100, max_jobs_to_activate=0, variables_to_fetch=[]) for job in jobs: raise Exception(f"This should not return jobs! Job: {job}") zeebe_adapter._common_zeebe_grpc_errors.assert_called() def test_complete_job(zeebe_adapter, grpc_servicer): task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) response = zeebe_adapter.complete_job(job_key=job.key, variables={}) assert isinstance(response, CompleteJobResponse) def test_complete_job_not_found(zeebe_adapter): with pytest.raises(JobNotFound): zeebe_adapter.complete_job(job_key=randint(0, RANDOM_RANGE), variables={}) def test_complete_job_already_completed(zeebe_adapter, grpc_servicer): task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) zeebe_adapter.complete_job(job_key=job.key, variables={}) with pytest.raises(JobAlreadyDeactivated): zeebe_adapter.complete_job(job_key=job.key, variables={}) def test_complete_job_common_errors_called(zeebe_adapter, grpc_servicer): zeebe_adapter._common_zeebe_grpc_errors = MagicMock() error = grpc.RpcError() error._state = GRPCStatusCode(grpc.StatusCode.INTERNAL) zeebe_adapter._gateway_stub.CompleteJob = MagicMock(side_effect=error) task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) zeebe_adapter.complete_job(job_key=job.key, variables={}) zeebe_adapter._common_zeebe_grpc_errors.assert_called() def test_fail_job(zeebe_adapter, grpc_servicer): task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) response = zeebe_adapter.fail_job(job_key=job.key, message=str(uuid4())) assert isinstance(response, FailJobResponse) def test_fail_job_not_found(zeebe_adapter): with pytest.raises(JobNotFound): zeebe_adapter.fail_job(job_key=randint(0, RANDOM_RANGE), message=str(uuid4())) def test_fail_job_already_failed(zeebe_adapter, grpc_servicer): task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) zeebe_adapter.fail_job(job_key=job.key, message=str(uuid4())) with pytest.raises(JobAlreadyDeactivated): zeebe_adapter.fail_job(job_key=job.key, message=str(uuid4())) def test_fail_job_common_errors_called(zeebe_adapter, grpc_servicer): zeebe_adapter._common_zeebe_grpc_errors = MagicMock() error = grpc.RpcError() error._state = GRPCStatusCode(grpc.StatusCode.INTERNAL) zeebe_adapter._gateway_stub.FailJob = MagicMock(side_effect=error) task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) zeebe_adapter.fail_job(job_key=job.key, message=str(uuid4())) zeebe_adapter._common_zeebe_grpc_errors.assert_called() def test_throw_error(zeebe_adapter, grpc_servicer): task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) response = zeebe_adapter.throw_error(job_key=job.key, message=str(uuid4())) assert isinstance(response, ThrowErrorResponse) def test_throw_error_job_not_found(zeebe_adapter): with pytest.raises(JobNotFound): zeebe_adapter.throw_error(job_key=randint(0, RANDOM_RANGE), message=str(uuid4())) def test_throw_error_already_thrown(zeebe_adapter, grpc_servicer): task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) zeebe_adapter.throw_error(job_key=job.key, message=str(uuid4())) with pytest.raises(JobAlreadyDeactivated): zeebe_adapter.throw_error(job_key=job.key, message=str(uuid4())) def test_throw_error_common_errors_called(zeebe_adapter, grpc_servicer): zeebe_adapter._common_zeebe_grpc_errors = MagicMock() error = grpc.RpcError() error._state = GRPCStatusCode(grpc.StatusCode.INTERNAL) zeebe_adapter._gateway_stub.ThrowError = MagicMock(side_effect=error) task_type = create_random_task_and_activate(grpc_servicer) job = get_first_active_job(task_type, zeebe_adapter) zeebe_adapter.throw_error(job_key=job.key, message=str(uuid4())) zeebe_adapter._common_zeebe_grpc_errors.assert_called()

42.454054

111

0.755284

1,050

7,854

5.242857

0.099048

0.13515

0.021253

0.041417

0.80327

0.782198

0.762761

0.747321

0.726067

0.692643

0

0.013562

0.15508

7,854

184

112

42.684783

0.816004

0

0.430769

0

0.004966

0

0.069231

1

0.153846

false

0

0.084615

0.007692

0.253846

0

null

0

1

0

null

0

6

15a258e137fed24740151aeb6bfe11e3b463e2d8

36

py

Python

__init__.py

RiverArchitect/riverarchitect

be21ff3c69c9cc0e50a7360c360cc435ad9eafb3

[ "BSD-3-Clause" ]

null

__init__.py

RiverArchitect/riverarchitect

be21ff3c69c9cc0e50a7360c360cc435ad9eafb3

[ "BSD-3-Clause" ]

null

__init__.py

RiverArchitect/riverarchitect

be21ff3c69c9cc0e50a7360c360cc435ad9eafb3

[ "BSD-3-Clause" ]

null

print("Hi from RiverArchitect RTD")

18

35

0.777778

5

36

5.6

1

0

0.111111

36

1

36

0.875

0

0.722222

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

15ba5c0c1ab92b31d54b9da8e6a1680c43b489ff

33

py

Python

agegrader/__init__.py

cablespaghetti/agegrader

5b748ab645875416228348931e711e33f88ad514

[ "BSD-2-Clause" ]

4

2016-09-22T17:57:01.000Z

2021-12-17T21:57:39.000Z

agegrader/__init__.py

cablespaghetti/agegrader

5b748ab645875416228348931e711e33f88ad514

[ "BSD-2-Clause" ]

1

2021-12-24T08:09:33.000Z

2021-12-24T17:51:02.000Z

agegrader/__init__.py

cablespaghetti/agegrader

5b748ab645875416228348931e711e33f88ad514

[ "BSD-2-Clause" ]

1

2021-12-23T23:15:58.000Z

from .agegrader import AgeGrader

16.5

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ec629c206a9051ff031344c6d9939ed31db678ea

265

py

Python

msdtk/scripts/pmi_wrapper.py

alabamagan/maxillary_sinus_diagnosis_toolkit

2529578a35f16787d63dfc18a37c9a19738dd665

[ "MIT" ]

null

msdtk/scripts/pmi_wrapper.py

alabamagan/maxillary_sinus_diagnosis_toolkit

2529578a35f16787d63dfc18a37c9a19738dd665

[ "MIT" ]

null

msdtk/scripts/pmi_wrapper.py

alabamagan/maxillary_sinus_diagnosis_toolkit

2529578a35f16787d63dfc18a37c9a19738dd665

[ "MIT" ]

null

#==================================================== # This script is used together with guild. #---------------------------------------------------- from pytorch_med_imaging.main import console_entry import argparse if __name__ == '__main__': console_entry()

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6

ec985d1ec8cf83107ac7e92ea053054a662bc593

171

py

Python

python/testData/inspections/PyArgumentListInspection/implicitResolveResult.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/inspections/PyArgumentListInspection/implicitResolveResult.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/inspections/PyArgumentListInspection/implicitResolveResult.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

class Baz: def long_unique_identifier(self): pass def xyzzy(baz): baz.long_unique_identifier(1, 2, 3) # don't perform validation for implicit resolve results

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1

0

1

0

1

0

6

01b7cf1fec6d401c56b25a2e12e92d35e39f076e

905

py

Python

test/test_xml.py

colinta/plywood

49cf98f198da302ec66e11338320c6b72b642ffa

[ "BSD-2-Clause-FreeBSD" ]

1

2015-06-11T06:17:42.000Z

test/test_xml.py

colinta/plywood

49cf98f198da302ec66e11338320c6b72b642ffa

[ "BSD-2-Clause-FreeBSD" ]

null

test/test_xml.py

colinta/plywood

49cf98f198da302ec66e11338320c6b72b642ffa

[ "BSD-2-Clause-FreeBSD" ]

null

from . import assert_output def test_xml_attribute(): input = ''' div(xmlns='urn:loc.gov:books', xmlns:isbn='urn:ISBN:0-395-36341-6') ''' desired = '''<div xmlns="urn:loc.gov:books" xmlns:isbn="urn:ISBN:0-395-36341-6"></div>\n''' assert_output(input, desired) def test_xml_constructor(): input = ''' <book xmlns='urn:loc.gov:books', xmlns:isbn='urn:ISBN:0-395-36341-6'>: <isbn:number>: 1568491379 ''' desired = '''<book xmlns="urn:loc.gov:books" xmlns:isbn="urn:ISBN:0-395-36341-6"> <isbn:number>1568491379</isbn:number> </book> ''' assert_output(input, desired) def test_xml_self_close(): input = ''' <book xmlns='urn:loc.gov:books', xmlns:isbn='urn:ISBN:0-395-36341-6'>: <isbn:number> ''' desired = '''<book xmlns="urn:loc.gov:books" xmlns:isbn="urn:ISBN:0-395-36341-6"> <isbn:number /> </book> ''' assert_output(input, desired)

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1

0

1

null

0

6

01fd8b8173d4efb3a3c22e5ad36f2f9862ee6c65

33

py

Python

generate/__init__.py

SunYanCN/tendecomlib

3473d05855c87e39c162c3fea6fe59f94344735b

[ "MIT" ]

null

generate/__init__.py

SunYanCN/tendecomlib

3473d05855c87e39c162c3fea6fe59f94344735b

[ "MIT" ]

null

generate/__init__.py

SunYanCN/tendecomlib

3473d05855c87e39c162c3fea6fe59f94344735b

[ "MIT" ]

null

from .random import random_tensor

33

0.878788

5

33

5.6

0.8

0

0.090909

33

1

33

0.933333

0

1

0

true

0

1

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1

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1

0

null

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1

0

null

0

1

0

1

0

1

0

6

bf1cacc08ca3c54c418fbd8b768a3b194678ec69

8,413

py

Python

generatePages/scholarship.py

Sonalisinghal/techhelpher

226743685d0e72a763db33f312eae2b7a8454d92

[ "CC-BY-3.0" ]

1

2020-05-30T14:24:22.000Z

generatePages/scholarship.py

Sonalisinghal/techhelpher

226743685d0e72a763db33f312eae2b7a8454d92

[ "CC-BY-3.0" ]

1

2021-03-15T06:18:03.000Z

generatePages/scholarship.py

Sonalisinghal/techhelpher

226743685d0e72a763db33f312eae2b7a8454d92

[ "CC-BY-3.0" ]

null

datasets=[ {"Scholarship":"AnitaB.org Grace hopper Scholarship","About":"The GHC Scholars Program provides funds for women who are either undergraduate students, graduate students, or faculty to attend Grace Hopper Celebration.","Eligibility":"For students: Women, 18+ by September of that year. Full-time student enrolled in an accredited degree program at a college or university pursuing Computer Science/Engineering or related fields.","Applications open":"January","Application Close":"March","Benefits":"Scholarship covers the cost of individual registration for the GHC, hotel accommodation, airfare and stipend (to be used for travel, meals, and incidentals such as rideshares, baggage fees, etc.)","ImageName":"ghc.jpg","Link":"https://ghc.anitab.org/2020-student-academic/scholarships/"}, {"Scholarship":"AnitaB.org Pass it on awards","About":"The cash award helps fund women in computing or projects that inspire and support girls and women to enter computing. Recipients are encouraged to \"pass on\" the benefits they gain from the award, creating a movement of women helping women.","Eligibility":"Any woman over 18 may apply, though she must be in or aspiring to be in computing fields","Applications open":"January","Application Close":"March","Benefits":"Awards range up to $1,000 USD","ImageName":"passiton.jpg","Link":"https://systers.submittable.com/submit/76301/systers-pass-it-on-awards"}, {"Scholarship":"Adobe Women In tech Scholarship","About":"Aim towards creating gender equality in science, technology and engineering domains by encouraging women to showcase their excellence in computing and technology and become future leaders and role models in the field.","Eligibility":"Be an Indian female citizen student,enrolled as a full time student in a formal technology 4 year BE / B.Tech education program or an Integrated ME/MS/MTech program at an Indian University, completing the program next year.\nShould be pursuing a Major or Minor in Computer Science/Engineering or related fields.","Applications open":"August","Application Close":"September","Benefits":"Tution fee for remainder of recipient's education, Opportunity for summer internship at Adobe India, Mentoring by a senior technology leader from Adobe, Travel to Grace Hopper Conference India, including participation fees.","ImageName":"adobe.jpg","Link":"https://research.adobe.com/adobe-india-women-in-technology-scholarship/"}, {"Scholarship":"Venkat Panchapakesan Memorial Scholarship by Google","About":"Scholarship for people who are passionate to leverage the field of computer science to transform systems","Eligibility":"Indian, Full time student pursuing Computer Science/Engineering or related fields.","Applications open":"August","Application Close":"September","Benefits":"750 USD (must be spent on tuition, fees, books, supplies and equipment required for the students' classes at their primary university)","ImageName":"google.jpg","Link":"https://buildyourfuture.withgoogle.com/scholarships/venkat-panchapakesan-memorial-scholarship/"}, {"Scholarship":"Red Hat","About":"These awards are given to honor women who make important contributions to open source projects and communities, or those making innovative use of open source methodology.","Eligibility":"Women","Applications open":"January","Application Close":"January","Benefits":"$2,500 stipend, Paid registration, flight, and hotel accommodations for Red Hat Summit","ImageName":"redhat.jpg","Link":"https://www.redhat.com/en/about/women-in-open-source"}, {"Scholarship":"Google Women tech Makers","About":"An academic scholarship, awarded based on academic performance, leadership, and impact on the community of women in tech.","Eligibility":"Women, in year 1 or year 2 of their undergraduate program","Applications open":"March","Application Close":"April","Benefits":"Stipend and invitation to attend Women Techmakers Scholars' Retreat","ImageName":"wtm.jpg","Link":"https://www.womentechmakers.com/scholars"}, {"Scholarship":"Western Digital Scholarship Program","About":"Aim to encourage STEM education for underrepresented and underprivileged students","Eligibility":"Undergraduate student enrolled (or to be enrolled) on a full-time basis at an accredited four-year college or university in the United States, China, Japan, India, Malaysia, Philippines or Thailand (pursuing Computer Science, Engineering, Mathematics or Science)","Applications open":"January","Application Close":"April","Benefits":"Upto $5000","ImageName":"westerndigital.jpg","Link":"https://www.westerndigital.com/company/corporate-philanthropy/scholarship-programs"}, {"Scholarship":"Nutanix .heart WIT Scholarship","About":"Scholarships to help young women develop the skills they need to pursue their passion of computer science.","Eligibility":"Female students in the United States, India, UK and Serbia in Final year of undergraduate degree or higher degree pursuing Computer Science or related field","Applications open":"November","Application Close":"May","Benefits":"Upto $2500 in India and Siberia, Upto $7500 in USA and UK","ImageName":"nutanix.jpg","Link":"https://www.nutanix.com/scholarships"}, {"Scholarship":"Adobe Research Women in Tech Scholarship","About":"This scholarship recognizes outstanding undergraduate and masters female students anywhere in the world who are studying computer science.","Eligibility":"Female student currently enrolled as an undergraduate (2nd year or above) or masters student at a university pursuing Computer Science or related field.","Applications open":"August","Application Close":"September","Benefits":"$10000, Creative cloud Membership, Internship opportunity","ImageName":"adoberesearchscholarship.jpg","Link":"https://research.adobe.com/scholarship/"} {"Scholarship":"Adobe Research Women in Tech Scholarship","About":"This scholarship recognizes outstanding undergraduate and masters female students anywhere in the world who are studying computer science.","Eligibility":"Female student currently enrolled as an undergraduate (2nd year or above) or masters student at a university pursuing Computer Science or related field.","Applications open":"August","Application Close":"September","Benefits":"$10000, Creative cloud Membership, Internship opportunity","ImageName":"adoberesearchscholarship.jpg","Link":"https://research.adobe.com/scholarship/"} ] # Western Digital STEM Scholarship: https://www.westerndigital.com/.../scholarship-programs: Due 11:59PM PST on April 2, 2020 # Nutanix Scholarship: https://www.nutanix.com/scholarships: Due May 14th 2020 # Three major Palantir Scholarships (Best for students studying in US/Canada/Mexico): https://www.palantir.com/.../scholarship/wit-north-america/, # https://www.palantir.com/students/scholarship/future/, # https://www.palantir.com/students/scholarship/global-impact/ # First two due 5th April and last one due 14th June 2020 # Google WTM scholarship # Rails Girls Summer of Code Fellowship, Google Summer of Code/Google Season of Docs (currently open) # Outreachy fellowship # Mozilla Summer MVP Program (Scholarship) # Adobe Research Women in Tech Scholarship # Facebook Research Fellowship # Facebook GHC scholarship # Twitter GHC scholarship # Snap Research Scholarship/Fellowship # Toptal STEM scholarship # Quip Diversity Scholarship # Microsoft Diversity Scholarship # Qualcomm WeTech Scholarship # Qualcomm Innovation Fellowship # Student of Vision ABIE Award # Western Union Scholarship # Google VPM scholarship for Indian students # https://docs.google.com/document/d/17_IrpCVZzFUTJN-YJ2a_LZgbHE04Q7z5N_PZ8f16BmA/mobilebasic # Summer Intern opportunities in Technology and Social Good Research # Cadence Women in Tech Scholarship: # https://www.cadence.com/en_US/home/company/cadence-academic-network/women-in-tech-scholarship.html?fbclid=IwAR0w_TIQzoTsmvjS27MaenVfjp03kBXlQmrutey054T7Zgc8CtYZcOVW8pk # $5,000 scholarship # The Prodigy Finance Global Scholarship: # https://prodigyfinance.com/community/scholarship?fbclid=IwAR0gesUNcoJKORZAArOBTKlBP7brNXyRXaHo-Ywfto5kudvUp7H8PIk0lGQ#wit # $10,000 scholarship # McKinsey Achievement Award: # https://www.mckinsey.com/careers/mckinsey-achievement-awards/overview?fbclid=IwAR3yrq_x9eLBJNokIbslAXfhre5Jzpj4rcbfoUOFJoz_Nh9FHsfQH13Ub4U # $2,500 scholarship and mentorship

115.246575

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6

171f4d4eeb194070c1e3d778bcdde5f52ee252ff

194

py

Python

models/__init__.py

vfleaking/max-margin

dd69c1f3901ede9174dcb27e79819bc83b4f8942

[ "MIT" ]

3

2020-05-02T17:23:03.000Z

2021-01-16T07:49:30.000Z

models/__init__.py

vfleaking/max-margin

dd69c1f3901ede9174dcb27e79819bc83b4f8942

[ "MIT" ]

null

models/__init__.py

vfleaking/max-margin

dd69c1f3901ede9174dcb27e79819bc83b4f8942

[ "MIT" ]

null

from .base_model import * from .simple_sequential import * from .initializers import * from .lr_schedulers import * from .archivers import * from .l2_attack import * from .linf_attack import *

21.555556

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9

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