index int64 0 1,000k | blob_id stringlengths 40 40 | code stringlengths 7 10.4M |
|---|---|---|
200 | 1a7e83fe9528b177246d6374ddaf2a76a0046e83 | # coding:utf-8
import jieba
import os
import sys
import math
reload(sys)
sys.setdefaultencoding('utf-8')
from sklearn import feature_extraction
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.feature_extraction.text import CountVectorizer
#import csv
#import pandas
#import numpy
sente... |
201 | 7e7e96fb9377e4dc59a46a46951f5057ecae419a | # -*- coding: utf-8 -*-
import random
import gym
import numpy as np
from collections import deque
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam
from simulation_utils import box, simulation
from kinematics import pose3D
a = np.log(2)/25
apdataX = np.random.random(... |
202 | b6183daa943cc63fd2959e3e54fc1e6af5d761de | # -*- coding: utf-8 -*-
import math
#COMECE SEU CÓDIGO AQUI
f = float(input('Digite o valor de f: '))
L = float(input('Digite o valor de L: '))
Q = float(input('Digite o valor de Q: '))
DeltaH = float(input('Digite o valor de DeltaH: '))
v = float(input('Digite o valor de v: '))
g = 9.81
e = 0.000002
#PROCESSAMENTO
D =... |
203 | 1490fecd6e983c0e3093a45d77d6fb8afdb54718 | # ******************************************************************************
# main.py
#
# Date Name Description
# ======== ========= ========================================================
# 6/5/19 Paudel Initial version,
# ***********************************************************************... |
204 | e5d7cc65041d65f915d4882b4fdad5bebf79a067 | from collections import defaultdict
from typing import Union, Iterable, Sized
import numpy as np
from cached_property import cached_property
from keras.utils import to_categorical
from keras.preprocessing.sequence import pad_sequences
from keras.preprocessing.text import Tokenizer, text_to_word_sequence
class Source... |
205 | e221553f866de8b3e175197a40982506bf8c1ef9 | import torch
import torch.nn.functional as F
import csv
class Net(torch.nn.Module):
def __init__(self, n_feature, n_hidden, n_output):
super(Net, self).__init__()
self.hidden = torch.nn.Linear(n_feature, n_hidden)
self.predict = torch.nn.Linear(n_hidden, n_output)
def forward(self, x... |
206 | 39dda191ab2137b5f5538660f17e39b0a1358bf4 | import numpy as np
import cv2
import colorsys
from matplotlib import pyplot as plt
img = cv2.imread('coins.jpg')
b,g,r = cv2.split(img)
rgb_img = cv2.merge([r,g,b])
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
# Blurring image
grayBlur = cv2.medianBlur(gray, 3)
# Binary threshold
ret, thresh = cv2.threshold(grayBl... |
207 | 0e6e84a31b626639e2aa149fd1ef89f3ef251cd7 | # -*- coding: utf-8 -*-
##################################
# @program synda
# @description climate models data transfer program
# @copyright Copyright "(c)2009 Centre National de la Recherche Scientifique CNRS.
# All Rights Reserved"
# @license CeCILL (https://raw.g... |
208 | c0d71d970b2632dbf182a5ee8bad27d3e41578f6 | #!/Library/Frameworks/Python.framework/Versions/3.7/bin/python3
import sys
def sumInput(text):
f = open(text, 'r')
sum = 0
count = 1
for line in f:
count += 1
line = line.strip()
if (line[0] == '+'):
sum += int(line[1:])
else:
sum -= int(line[1:... |
209 | f14d46bedd5f6e0081a982251ad45e95860ef310 | class HashTable:
def __init__(self):
self.dados = []
def hash(self, chave):
return int(chave)
def __put(self, int, chave, valor):
self.dados.append({chave: valor})
"""
backup = dados
dados = novo_array(t * 2)
for elemento in backup:
hash = hash(elemento.chave)
__put(... |
210 | 21a41356fcedb36223498db0fe783e4a9e8e1ba6 | # help from https://stackoverflow.com/questions/19007383/compare-two-different-files-line-by-line-in-python
with open('Book1.txt', 'r') as file1:
with open('20k.txt', 'r') as file2:
same = set(file1).intersection(file2)
same.discard('\n')
with open('notin20kforBook1.txt', 'w') as file_out:
for line i... |
211 | de7b5e44c5c213e4ab70b0f8c0c402edaf4926e0 |
from django.conf.urls import url
from .import views
app_name='user'
# user子路由
urlpatterns = [
# user首页
url(r'^$',views.index,name='index'),
# 用户登录
url('login/', views.login, name='login'),
# 用户注册
url('regist/', views.regist, name='regist'),
# 根据id判断用户是否存在
url(r'^getuser\w*/(?P<id>\... |
212 | cc7f1f38efcd4d757c1d11e2bd53695fca44e15a | 'For learning OWL and owlready2'
'From "https://qiita.com/sci-koke/items/a650c09bf77331f5537f"'
'From "https://owlready2.readthedocs.io/en/latest/class.html"'
'* Owlready2 * Warning: optimized Cython parser module "owlready2_optimized" is not available, defaulting to slower Python implementation'
'↑ This wartning mean... |
213 | a2e2528f560f6117d4ceeb9cd20d3f6f6b2a30a7 | # -*- coding: utf-8 -*-
def testeum():
a = 10
print(id(a))
def testedois():
a = 10
print(id(a)) |
214 | e09af436f2fb37d16427aa0b1416d6f2d59ad6c4 | #!/usr/bin/env python3
import argparse
import os
import sys,shutil
from shutil import make_archive
import pathlib
from phpManager import execute,execute_outputfile
from datetime import date,datetime
import re
import pymysql
import tarfile
def append_log(log,message):
f = open(log, "a+")
today = datetime.now()... |
215 | 46adb1834f6013ca0f13a64f280182a805d76278 | #!/usr/bin/python3
# encoding: utf-8
import sys
import argparse
import logging
from pathlib import Path
module = sys.modules['__main__'].__file__
__author__ = 'FFX'
__version__ = '1.0'
log = logging.getLogger(module)
def parse_command_line(argv):
"""Parse command line argument. See -h option
:param argv: ... |
216 | c63e5a2178e82ec6e0e1e91a81145afb735bf7bf | __author__ = 'lei'
import unittest
from ch3.node import TreeNode as t
import ch3.searchRange as sr
class MyTestCase(unittest.TestCase):
def test_1(self):
a = t(2)
b=t(1)
a.left = b
self.assertEqual(sr.searchRange(a,0,4), [1,2])
def test_2(self):
a = t(20)
b = ... |
217 | b77da75b01e96ff89f873f4c5764a62cf68cd576 | from rest_framework import serializers
from .models import *
__all__ = (
'CatalogCoinListSerializer', 'CatalogCoinSerializer', 'SeriesListSerializer', 'CoinListSerializer',
'CoinSerializer', 'CountriesListSerializer',
)
class CountriesListSerializer(serializers.ModelSerializer):
class Meta:
mode... |
218 | 1f0695f0e9745912d8ee3a87e6c9b1272e9ebbae | """
Writes day of the week and time to a file.
Script written for crontab tutorial.
Author: Jessica Yung 2016
"""
import time
filename = "record_time.txt"
# Records time in format Sun 10:00:00
current_time = time.strftime('%a %H:%M:%S')
# Append output to file. 'a' is append mode.
with open(filename, 'a') as hand... |
219 | 142a2ba3ec2f6b35f4339ed9fffe7357c1a85fa0 | import requests
import time
import urllib
import argparse
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from fake_useragent import UserAgent
from multiprocessing import Pool
from lxml.html import fromstring
import os, sys
#text = 'chowchowbaby'
#url='https... |
220 | 2a19c2d6e51e9c123236c58f82de1a39e5db40f4 | import numpy as np
# Copyright 2011 University of Bonn
# Author: Hannes Schulz
def cnan(x):
""" check for not-a-number in parameter x """
if np.isnan(x).sum()>0:
import pdb
pdb.set_trace()
def get_curve_3D(eig, alpha=0.25,g23=0.5,g12=0.5): # renumerated according to sato et al: l3 is smallest... |
221 | 550f5ad4fef77d5795db0393ae0701f679143e72 | #!/usr/bin/env python
# @HEADER
# ************************************************************************
#
# TriBITS: Tribal Build, Integrate, and Test System
# Copyright 2013 Sandia Corporation
#
# Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
# the U.S. Govern... |
222 | 4fa9d16f979acf3edce05a209e1c6636e50fc315 | from jox_api import label_image,Mysql,Utils
from jox_config import api_base_url
import json
class Menu():
def __init__(self):
self.mysqlClass = Mysql.MySQL()
self.timeClass = Utils.Time()
def get_menu(self,type,openid):
try:
if type == 'mine':
self.sql = "SEL... |
223 | e5e012e40a71dee9f4dbd9913590aef125b758df | from classes.Board import Board
class Visualiser:
coordinate_map = ("a", "b", "c", "d", "e", "f", "g", "h")
__dimensions = 8
def __init__(self):
self.map = []
self.__build_map()
def __build_map(self):
"""
Creates the array of the battlefield. Should never be used for ... |
224 | c4e4e54ac93c2acdbd3a1cd22b200341a6e45688 | import pyaudio
import numpy as np
from collections import OrderedDict
import utils
class MasterPlayer(object):
def __init__(self, volume=1., samplesPerSecond=44100):
self.p = pyaudio.PyAudio()
self.volume = volume
self.samplesPerSecond = samplesPerSecond
self.individual_callbacks =... |
225 | 27e9e63338d422b5fca6f7a67fa3d255602a3358 | from abstract_class_V import V
import torch
import torch.nn as nn
class V_test_abstract(V):
def __init__(self):
super(V_test_abstract, self).__init__()
def V_setup(self,y,X,nu):
self.explicit_gradient = False
self.need_higherorderderiv = True
self.dim = X.shape[1]
self... |
226 | ec4348c61cd1c9130543bb20f9ca199399e1caff | class Solution(object):
def restoreIpAddresses(self, s):
"""
:type s: str
:rtype: List[str]
"""
def helper(sb, string, level):
if len(string) == 0:
if level == 4:
ans.append(sb[:-1])
return
if level ... |
227 | d0a3f332e04627eb275168972bd92cd1ea9b9447 | from board.ttt import TTT
from mctsai.mcts import MCTS
import unittest
# skip = [0, 1]
skip = [0]
class TestTTT(unittest.TestCase):
def test_mcts(self):
if 0 in skip:
print("Skipping ai self-play")
return
ttt = TTT()
for i in range(1000):
mcts = MCTS(tt... |
228 | e95bda8be2294c295d89f1c035bc209128fa29c8 | def merge_the_tools(string, k):
# your code goes here
num_sub_strings = len(string)/k
#print num_sub_strings
for idx in range(num_sub_strings):
print "".join(set(list(string[idx * k : (idx + 1) * k])))
|
229 | f85a703b47d981397ed6048e941030a3fbee7b6d | # -*- coding: utf-8 -*-
# Generated by Django 1.9.8 on 2018-04-27 08:05
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('talk', '0023_auto_20180207_1121'),
]
operations = [
migrations.AddField(
... |
230 | 23375760c0943ca177b7009031d9d17a91165c5c | #!/usr/bin/env python
#--coding: utf8--
import time
if __name__ == '__main__':
date = time.strftime('%m-%d')
if date == '03-08':
print '女神节'
elif date == '02-14':
print '情人节'
else:
print '发红包'
print '这是一个测试题' |
231 | f8d815bcdc74452b66a1b3b33bf0fbe976e728c8 | # This is a sample Python script.
# Press Shift+F10 to execute it or replace it with your code.
# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
import tensorflow as tf
from tensorflow.keras import datasets, layers, models
import matplotlib.pyplot as plt
import numpy ... |
232 | ef85f94282bfd7c9491c4e28bab61aaab5c792a5 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'src/ui_LibraryTab.ui'
#
# Created: Tue Jun 9 21:46:41 2015
# by: PyQt5 UI code generator 5.4
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Tab(object):
def setupUi(se... |
233 | 8c8bbbc682889c8d79c893f27def76ad70e8bf8d | DATABASE_NAME = "user_db" |
234 | 9d904225afd4f4d0cf338ae16f031f8ab41639ad | # -*- coding=utf-8 -*-
from mako.template import Template
from xblock.fragment import Fragment
from .lookup import TemplateLookup # xblock_ifmo.lookup
from .utils import deep_update
class FragmentMakoChain(Fragment):
"""
Класс, позволяющий последовательно оборачивать экземпляры Fragment друг в
друга.
... |
235 | 8cc0393082448bb8f61068b5c96e89ef3aee77ed | #coding: utf-8
import logging
from threading import Thread
from ldap import SCOPE_BASE
from seafevents.ldap_syncer.ldap_conn import LdapConn
from seafevents.ldap_syncer.utils import bytes2str, add_group_uuid_pair
from seaserv import get_group_dn_pairs
logger = logging.getLogger(__name__)
def migrate_dn_pairs(set... |
236 | 21af630bf383ee1bdd0f644283f0ddadde71620a | #!/bin/usr/python2.7.x
import os, re, urllib2
def main():
ip = raw_input(" Target IP : ")
check(ip)
def check(ip):
try:
print "Loading Check File Uploader...."
print 58*"-"
page = 1
while page <= 21:
bing = "http://www.bing.com/search?q=ip%3A" + \
ip + "+upload&count=50&first=" + str(... |
237 | eb853e430b996a81dc2ef20c320979a3e04d956a | #!/usr/bin/env python3
# -*- coding: UTF-8 -*-
import hashlib
import re
from datetime import datetime
import gevent
import requests
import scrapy
from gevent.pool import Pool
from lxml import etree
from scrapy.http import HtmlResponse
from sqlalchemy import create_engine, func
from sqlalchemy.orm import sessionmaker
... |
238 | bc4684d255a46427f708d8ce8bda2e12fb8c8ffe | # -*- coding: utf-8 -*-
from route4me import Route4Me
API_KEY = "11111111111111111111111111111111"
def main():
r4m = Route4Me(API_KEY)
route = r4m.route
response = route.get_routes(limit=1, offset=0)
if isinstance(response, dict) and 'errors' in response.keys():
print('. '.join(response['err... |
239 | d015a1b27a3a9e7f5e6614da752137064000b905 | #!/usr/bin/env python3
"""Transfer learning with xception"""
import tensorflow.keras as K
from GPyOpt.methods import BayesianOptimization
import pickle
import os
import numpy as np
class my_model():
"""A model bassed on xception"""
def make_model(self, param):
"""makes the model"""
self.lr = ... |
240 | ef6f55bf27982f53441215da6822cfcdc80706a5 | # -*- coding: utf-8 -*-
__author__ = 'Yun'
__project__ = 'DjangoBookTest2'
# from django.template import Template, Context
# from django.template.loader import get_template
# from django.http import HttpResponse
from django.shortcuts import render_to_response
import datetime
def current_datetime(request):
# now ... |
241 | e8226ab6be5c21335d843cba720e66646a2dee4e | import os
import requests
import sqlite3
from models import analytics, jcanalytics
def populate():
url = 'https://api.clicky.com/api/stats/4?site_id=100716069&sitekey=93c104e29de28bd9&type=visitors-list'
date = '&date=last-30-days'
limit = '&limit=all'
output = '&output=json'
total = url+date+limi... |
242 | e616d14827beaa08ab08219421cbf7990cf163fd | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from alipay.aop.api.constant.ParamConstants import *
from alipay.aop.api.domain.InsureAdmitDTO import InsureAdmitDTO
class AlipayInsSceneEcommerceInsureCheckModel(object):
def __init__(self):
self._insure_admit_dto_list = None
self._partn... |
243 | c4ca4b5c77c3c912b44a4853be30298ec845c4fd | #str
owog="Delger"
# len()- urt
# lower()- jijigruuleh
# upper()- tomruulah
# capitalize()- ehnii useg tomruulah
# replace()- temdegt solih
print(owog.find("e"))
print(owog.count("e"))
print(owog[2:10])
a=21
b=21
if a>b:
print("a too ih")
elif a==b:
print("tentsuu")
else:
print("b to... |
244 | 050e2207ac7331444d39305869c4b25bcbc53907 | import pandas as pd
from sklearn.preprocessing import MinMaxScaler
#loading data from CSV
training_data_df = pd.read_csv("sales_data_training.csv")
test_data_df = pd.read_csv("sales_data_test.csv")
#scaler
scaler = MinMaxScaler(feature_range=(0,1))
#scale both inputs and outputs
scaled_training = scaler.fit_transfor... |
245 | df64d769ffba8cddac34282a526122e3c941249d | #!/usr/bin/env python
import os
import tempfile
import shutil
import math
import sys
import subprocess
from irank.config import IrankOptionParser, IrankApp
from irank import db as irank_db
STATUS = 0
def main():
p = IrankOptionParser('%prog -d DEST playlist_name [playlist_name ...]')
p.add_option('-d', '--dest', he... |
246 | 21b295e28a7e4443ea116df1b22ff5074dca955a | n =int(input("nhap gia tri"))
for i in range(1,n+1):
print(i) |
247 | 93737e4c409d0efb1ae2263cb60d4b03d9aad0d8 | import os
import shutil
import argparse
ap = argparse.ArgumentParser()
ap.add_argument('-D','--dir', required=False, help='Directory to sort')
args = vars(ap.parse_args())
if args['dir'] == None:
DIR = os.getcwd()
elif os.path.exists(args['dir']):
DIR = args['dir']
for file in os.listdir(DIR):
if not os.... |
248 | b5611c668a40e1735c92d6d00867885023ad713f | target=[]
with open('IntegerArray.txt','r') as f:
target=f.readlines()
for x in range(len(target)):
target[x]=int(target[x])
def f(A):
if len(A)==1:
return 0
else:
rightStart=len(A)//2
leftArray=A[0:rightStart]
righArray=A[rightStart:]
B,b=count_and_sort(leftArray)
C,c=count_and_sort(righA... |
249 | 09f032301fa9389f6b07687e0ee13844e0b4ddf3 | from artichoke import DefaultManager, Config
from artichoke.helpers import read, prompt
from fabric.api import env, task, run
import os
chars = ''.join(chr(c) if chr(c).isupper() or chr(c).islower() else '_' for c in range(256))
class MagicDefaultManager(DefaultManager):
def __init__(self, env):
self.en... |
250 | 68b967ecf18d576758cf05e889919944cfc34dcd | """
generalised behaviour for actors and vacancies
"""
from mesa import Agent
from random import shuffle
import numpy as np
class Entity(Agent):
"""
superclass for vacancy and actor agents
not intended to be used on its own, but to inherit its methods to multiple other agents
"""
def __init__(sel... |
251 | 46babde9c26a944c9d29121b6bbf89a32f242a81 | import simple_draw as sd
import random
# sd.resolution = (1400, 900)
# Prepare data for the sun function
def sun_prepare(xpoint, ypoint, radius, color, angle):
delta_list = []
radius_list = []
for delta in range(0, 360, angle):
delta_list.append(delta)
radius_list.append(random.randint(ra... |
252 | e736991f364ba9ff709348e4b1f612b1e9673281 | from flask import *
app=Flask(__name__)
from app import views
from app import admin_views
from app import usr_reg
from app import cookie
from app import db_connect |
253 | 07215403750be53994ae36727b6f790202b88697 | # Inspiration: [Fake Album Covers](https://fakealbumcovers.com/)
from IPython.display import Image as IPythonImage
from PIL import Image
from PIL import ImageFont
from PIL import ImageDraw
import requests
from xml.etree import ElementTree as ET
def display_cover(top,bottom ):
name='album_art_raw.png'
alb... |
254 | 18d3f58048b7e5d792eb2494ecc62bb158ac7407 | from flask import Flask
from flask import render_template
from flask import make_response
import json
from lib import powerswitch
app = Flask(__name__)
@app.route('/')
def hello_world():
return render_template('index.html')
@app.route('/on/')
def on():
state = powerswitch.on()
return json.dumps(state)
... |
255 | 869284fa531a93c1b9812ed90a560d0bb2f87e97 | # fonction pour voir quel est le plus grand entre l'energie limite et l'enerve potentiel
def ep (m,h,el,g=9.8):
E=m*h*g
if E<el:
print ("le plus grand est : el")
else:
print ("le plus grand est : E")
ep(3,4,5)
#fontion fibonaci 0 1 1 2 3 5 8 13
def fibonaci(n):
for i in range(0,n,):
... |
256 | d126efa91b964a3a374d546bb860b39ae26dfa22 | """A tiny example binary for the native Python rules of Bazel."""
import unittest
from bazel_tutorial.examples.py.lib import GetNumber
from bazel_tutorial.examples.py.fibonacci.fib import Fib
class TestGetNumber(unittest.TestCase):
def test_ok(self):
self.assertEqual(GetNumber(), 42)
def test_fib(self):
... |
257 | e582787a912f479830ed99575b2c6adb8088b4e5 | from flask import Flask, request
from flask import jsonify
from preprocessing import QueryProcessor
from flask_cors import CORS
app = Flask(__name__)
CORS(app)
qp = QueryProcessor()
@app.route('/search_general', methods=['POST'])
def query():
message = None
searchQuery = request.json['searchQuery']
resul... |
258 | cf0cf028d5f67e8deca8ebd3ad76d9c1e3563002 | #!/usr/bin/python2
import sys
import argparse
"""
This program generates an extract table having the following format:
<S1> <S2> <S3> ... <Sn> ||| <T1> <T2> <T3> ... <Tk> ||| 0-0
Each line is a mapping from a source sentence to target sentence
with special delimiter characters.
You can give the output of this s... |
259 | f8bf7e2d8f06bbd00f04047153833c07bf483fd3 | from django.apps import AppConfig
class PyrpgConfig(AppConfig):
name = 'PyRPG'
|
260 | 48677d73f6489ce789884a9dff5d50c23f47d8b3 | __author__ = 'simon.hughes'
from sklearn.feature_extraction import DictVectorizer
from WindowFeatures import compute_middle_index
from collections import Counter
class WindowFeatureExtractor(object):
"""
A simple wrapper class that takes a number of window based feature extractor
functions and applies the... |
261 | 65aa85675393efa1a0d8e5bab4b1dbf388018c58 |
indelCost = 1
swapCost = 13
subCost = 12
noOp = 0
def alignStrings(x,y):
nx = len(x)
ny = len(y)
S = matrix(nx+1, ny+1) #??
for i in range (nx+1)
for j in range (ny+1)
if i == 0: #if the string is empty
S[i][j] = j #this will put all the letters from j in i
elif j == 0: #if the second string ... |
262 | 47c1ad4bd1ceffa38eef467ea8eb59dbd2fc2ebb | from packet import Packet
from packetConstructor import PacketConstructor
import threading
import time
class PacketSender:
"""
Packet represents a simulated UDP packet.
"""
# The next seq num for sent packets
seq_num = 0
# The next seq num for acks that we're waiting for
next_seq_num = 0
... |
263 | 24cdbbadc8ff1c7ad5d42eeb518cb6c2b34724a2 | from openfermion import QubitOperator, FermionOperator
from openfermion.transforms import jordan_wigner
from src.utils import QasmUtils, MatrixUtils
from src.ansatz_elements import AnsatzElement, DoubleExchange
import itertools
import numpy
class EfficientDoubleExchange(AnsatzElement):
def __init__(self, qubit_... |
264 | 2843845848747c723d670cd3a5fcb7127153ac7e | from flask import Flask
from sim.toggle import ToggleSensor
from sim.sensor import Sensor
app = Flask(__name__)
sensors = [
ToggleSensor(id="s-01", description="lampadina"),
ToggleSensor(id="s-02", description="lampadina"),
ToggleSensor(id="s-03", description="allarme atomico"),
ToggleSensor(id="s-04... |
265 | f5bd41f4aaff616a332d80ec44c364ffc91c58f0 | # %load q03_skewness_log/build.py
from scipy.stats import skew
import pandas as pd
import numpy as np
data = pd.read_csv('data/train.csv')
# Write code here:
def skewness_log(df):
df['SalePrice_New'] = np.log(df['SalePrice'])
df['GrLivArea_New'] = np.log(df['GrLivArea'])
skewed_slPri = skew(df['SalePrice... |
266 | d65f858c3ad06226b83d2627f6d38e03eae5b36c | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Phase transition module
"""
import utils
import datetime
import itertools
import numpy as np
import recovery as rec
import sampling as smp
import graphs_signals as gs
import pathos.multiprocessing as mp
from tqdm import tqdm
## MAIN FUNCTIONS ##
def grid_evalua... |
267 | f97a892e6e0aa258ad917c4a73a66e89b0dc3253 |
# coding: utf-8
# In[1]:
import sys
sys.path.extend(['detection', 'train'])
# from detection folder
from MtcnnDetector import MtcnnDetector
from detector import Detector
from fcn_detector import FcnDetector
# from train folder
from model_factory import P_Net, R_Net, O_Net
import config as config
from preprocess.uti... |
268 | f19d8aa2104240cc93a0146f1b14c635e7cd3a41 | #! /usr/bin/env python
import ldac
from numpy import *
import shearprofile as sp
import sys
import os, subprocess
import pylab
if len(sys.argv) != 6:
sys.stderr.write("wrong number of arguments!\n")
sys.exit(1)
catfile= sys.argv[1]
clusterz=float(sys.argv[2])
center= map(float,sys.argv[3].split(','))
pixsc... |
269 | 0e58834120c34b5152026bde6d089be19244e21a | import os
from MdApi import MdApi
class Adapter(MdApi):
def __init__(self):
super(Adapter, self).__init__()
def connect(self):
self.createFtdcMdApi(os.getcwd())
self.registerFront('tcp://180.168.146.187:10010')
def onFrontConnected(self):
print 'front succ... |
270 | df40b0628d6a180a98cd385145ee7c65ecb78256 | import os
import tensorflow as tf
import torch
from tqdm import tqdm
from glob import glob
import numpy as np
from collections.abc import Iterable
from utils.hparams import HParam
#from utils.audio import Audio
#import librosa
#python encoder_inference.py --in_dir training_libri_mel/train/ --gpu_str 5
#python tfrecord... |
271 | ed7b29a4d7f3a48884434373418c3528f2f397ac | #!/usr/bin/python3
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'
os.environ['KERAS_BACKEND'] = 'tensorflow'
import numpy as np
import sys
from util import load_model
from keras.preprocessing.text import hashing_trick
from keras.preprocessing.sequence import pad_sequences
from southpar... |
272 | b6d8a918659f733919fe3bb4be9037e36ad32386 | import queue
import sys
import logging
from superai.common import InitLog
logger = logging.getLogger(__name__)
# 2维到1维
def hwToidx(x: int, y: int, weight: int):
return y * weight + x
# 1维到2维
def idxTohw(idx, weight: int):
return [idx % weight, idx // weight]
# 10x10 cell idx 到 [x,y]
def idxToXY(idx, cel... |
273 | 7930bb813bd546747c7c65b661900939f5ba93f1 | user_input = input() #abv>1>1>2>2asdasd
exploded_str = user_input
for n in range(len(user_input)):
explosion_strength = 0
if user_input[n] == ">":
explosion_strength += int(user_input[n+1])
if user_input[n+explosion_strength] != ">":
exploded_str = user_input[:n] + user_input[n+ex... |
274 | c6cf085330f47ffb139c5acc91d91e9758f5396a | from page_objects import PageObject, PageElement
class MainPage(PageObject):
level_menu_opened = False
level_menu_created = False
css_input = PageElement(css='input.input-strobe')
level_text_span = PageElement(css='span.level-text')
instruction_h2 = PageElement(css='h2.order')
enter_button = P... |
275 | c2ddf31bce4a5f3ae2b0d5455bbc9942f92bff40 | import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
from keras.models import load_model
from utils import resize_to_fit, clear_chunks, stack_windows
from imutils import paths
import numpy as np
import imutils
import cv2 as cv2
import pickle
from tqdm import tqdm
c1_correct = 0
c2_correct = 0
c3_correct = 0
c4_correct ... |
276 | 75e6554ea3c327c87a2a65710a7f1d55e9933bb0 | # Author: BeiYu
# Github: https://github.com/beiyuouo
# Date : 2021/2/21 21:57
# Description:
__author__ = "BeiYu"
from utils.init_env import set_seed
from utils.options import *
import os
import logging
import torch
from torch import nn
from torch import optim
from torch.optim.lr_scheduler import MultiStepLR
from ... |
277 | 58f3b8c5470c765c81f27d39d9c28751a8c2b719 | """Ex026 Faça um programa que leia uma frase pelo teclado e mostre:
Quantas vezes aparece a letra "A".
Em que posição ela aparece a primeira vez.
Em que posição ela aparece pela última vez."""
frase = str(input('Digite uma frase: ')).strip().lower()
n_a = frase.count('a')
f_a = frase.find('a')+1
l_a= frase.rfind('a')-1... |
278 | d83f2d9bb25a46bc7344b420ce65bf729165e6b9 | from django.apps import AppConfig
class FosAppConfig(AppConfig):
name = 'fos_app'
|
279 | d2b05c5653ca6c6b7219f6c0393e81c9425b5977 | """
HLS: Check if Twin Granule Exists
"""
from typing import Dict
import os
import re
import boto3
from botocore.errorfactory import ClientError
from datetime import date
s3 = boto3.client("s3")
bucket = os.getenv("SENTINEL_INPUT_BUCKET", None)
print(bucket)
if bucket is None:
raise Exception("No Input Bucket set"... |
280 | c73a199d1c1c1867f3d53ceebf614bc9b65c0d5e | from django.contrib import admin
from ticket.models import Ticket, UserTicket, AuxiliaryTicket
@admin.register(Ticket)
class TicketAdmin(admin.ModelAdmin):
pass
@admin.register(AuxiliaryTicket)
class AuxiliaryTicketAdmin(admin.ModelAdmin):
pass
@admin.register(UserTicket)
class UserTicketAdmin(admin.Mode... |
281 | e564e0d05c3c0e60f356422722803df510d9dd0b | import numpy as np
import pandas as pd
from sklearn.metrics import confusion_matrix
from sklearn.metrics import classification_report
from sklearn.metrics import precision_score, recall_score, f1_score
from scipy.optimize import fsolve
import numba
from numba import njit,jit
#
@jit(parallel = True)
def conventional_tes... |
282 | 9bc13c608c079cbf23ed04f29edd1fd836214cde | from rest_framework import viewsets, mixins
from .models import Comment, Post
from .serializer import CommentSerializer, PostSerializer, AllCommentSerializer
class PostViewSet(viewsets.ModelViewSet):
serializer_class = PostSerializer
queryset = Post.objects.all()
class CommentViewSet(viewsets.GenericViewSet... |
283 | b11e2837d3ba9c14770b8039186a2175adc41ea1 | from .server import CanvasServer
try:
from .jupyter import JupyterCanvas, create_jupyter_canvas
HAS_JUPYTER = True
except:
HAS_JUPYTER = False
JupyterCanvas = None # type: ignore
def http_server(
file: str = None, host: str = "localhost", port: int = 5050
) -> CanvasServer:
"""Creates a new... |
284 | 2da7892722afde5a6f87e3bd6d5763c895ac96c9 | import json
import os
import ipdb
from tqdm import tqdm
import argparse
from os import listdir
from os.path import isfile, join
import pickle
import joblib
from collections import Counter
from shutil import copyfile
import networkx as nx
import spacy
import nltk
import numpy as np
nltk.download('stopwords')
nltk_stopw... |
285 | e38ae7f91deed1be00e60b7516210ea1feefe23e | import sys
import os
from configparser import ConfigParser
import logging
from mod_argparse import setup_cli
from checkers.IndexFile import DocumentIndex, ProgressNoteIndex
from checkers import source_files
from utilities import write_to_file, strip # , write_to_db_isok
# import pandas as pd
logger = logging.getLogger... |
286 | 069338b188f3cf16357b2502cbb3130b69918bd9 | from .cli import cli
if __name__ == "__main__":
exit(cli.main(prog_name="htmap"))
|
287 | b52269237d66ea50c453395b9536f25f1310bf2e | #!/usr/bin/env python2.7
# -*- coding: utf-8 -*-
import re
from blessings import Terminal
from validate_email import validate_email
import requests
import sys
_site_ = sys.argv[1]
_saida_ = sys.argv[2]
_file_ = open(_saida_, "w")
t = Terminal()
r = requests.get(_site_, headers={'User-Agent': 'Mozilla/5.0 (Windows NT 6.... |
288 | 8c539dbbb762717393b9a71ddca8eb3872890854 | import re
import os
import pandas as pd
instruments_file = os.path.abspath("instruments.csv")
input_names_file = os.path.abspath("names.txt")
output_names_file = os.path.abspath("names.csv")
inst_name_file = os.path.abspath("name_instrument.csv")
reg_ex = '; |, |\\*|\n'
name_header = ["first_name", "last_name"]
def ... |
289 | 0db0daf9bea254cffaec1280cd13b2d70368cd94 | import numpy.random as rnd
import numpy as np
B=100000
N1=50
N2=50
p1mle=0.3
p2mle=0.4
taumle=p2mle-p1mle
estimate=[]
for i in range(B):
p1=0.0
for j in range(N1):
if(rnd.uniform(0,1)<p1mle):
p1+=1
p1/=N1
p2=0.0
for j in range(N2):
if(rnd.uniform(0,1)<p2mle):
p2+=1
p2/=N2
estimate.append(p2-p... |
290 | a90b7e44cc54d4f96a13e5e6e2d15b632d3c4983 | import random
import string
import steembase
import struct
import steem
from time import sleep
from time import time
from steem.transactionbuilder import TransactionBuilder
from steembase import operations
from steembase.transactions import SignedTransaction
from resultthread import MyThread
from charm.toolbox.pairingg... |
291 | ee80169afd4741854eff8619822a857bbf757575 | '''
Created on 27 Mar 2015
@author: Jon
'''
import matplotlib.pyplot as plt
from numerical_functions import Timer
import numerical_functions.numba_funcs.indexing as indexing
import numpy as np
import unittest
class Test(unittest.TestCase):
def test_take(self):
x = np.linspace( 0, 100 )
... |
292 | ce6dba2f682b091249f3bbf362bead4b95fee1f4 | """
.. currentmodule:: jotting
.. automodule:: jotting.book
:members:
.. automodule:: jotting.to
:members:
.. automodule:: jotting.read
:members:
.. automodule:: jotting.style
:members:
"""
from .book import book
from . import style, to, read, dist
|
293 | 99c839eddcbe985c81e709878d03c59e3be3c909 | #coding=utf-8
#########################################
# dbscan：
# 用法说明：读取文件
# 生成路径文件及簇文件，输出分类准确率
#########################################
from matplotlib.pyplot import *
import matplotlib.pyplot as plt
from collections import defaultdict
import random
from math import *
import numpy
import datetime
... |
294 | bf8bbeb408cb75af314ef9f3907456036e731c0b | def solution(S):
# write your code in Python 3.6
# Definitions
log_sep = ','
num_sep = '-'
time_sep = ':'
# Initialization
from collections import defaultdict
# defaultdict initialize missing key to default value -> 0
bill = defaultdict(int)
total = defaultdict(int)
calls = S... |
295 | 35ae9c86594b50bbe4a67d2cc6b20efc6f6fdc64 | #配置我们文件所在目录的搜寻环境
import os,sys
#第一步先拿到当前文件的路径
file_path = os.path.abspath(__file__)
#第二步 根据这个路径去拿到这个文件所在目录的路径
dir_path = os.path.dirname(file_path)
#第三步：讲这个目录的路径添加到我们的搜寻环境当中
sys.path.append(dir_path)
#第四步，动态设置我们的setting文件
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "gulishop.settings")
#第五步，让设置好的环境初始化生效
... |
296 | d34159536e860719094a36cfc30ffb5fcae72a9a | #API End Points by Mitul
import urllib.error, urllib.request, urllib.parse
import json
target = 'http://py4e-data.dr-chuck.net/json?'
local = input('Enter location: ')
url = target + urllib.parse.urlencode({'address': local, 'key' : 42})
print('Retriving', url)
data = urllib.request.urlopen(url).read()
print('Retrive... |
297 | c382b298cce8d7045d6ce8a84f90b3800dba7717 | # Generated by Django 3.0.7 on 2020-06-15 15:26
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('products', '0003_auto_20200615_1225'),
]
operations = [
migrations.AlterField(
model_name='product',
name='harmoniza... |
298 | 3372d98ff91d90558a87293d4032820b1662d60b | from django.conf.urls import patterns, url
from riskDashboard2 import views
urlpatterns = patterns('',
#url(r'getdata', views.vulnData, name='getdata'),
url(r'appmanagement', views.appmanagement, name='appmanagement'),
url(r'^.*', views.index, name='index'),
)
|
299 | 0465e33d65c2ce47ebffeec38db6908826bf4934 | people = 20
cats = 30
dogs = 15
if people < cats:
print("Too many cats")
elif people > cats:
print("Not many cats")
else:
print("we cannnot decide") |
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