blob_id stringlengths 40 40 | language stringclasses 1
value | repo_name stringlengths 5 133 | path stringlengths 2 333 | src_encoding stringclasses 30
values | length_bytes int64 18 5.47M | score float64 2.52 5.81 | int_score int64 3 5 | detected_licenses listlengths 0 67 | license_type stringclasses 2
values | text stringlengths 12 5.47M | download_success bool 1
class |
|---|---|---|---|---|---|---|---|---|---|---|---|
010c0600a789e2140899a93747ded744b90731fe | Python | SilviaC7/NMTF-DrugRepositioning | /load_data_NMTF.py | UTF-8 | 4,407 | 3.0625 | 3 | [
"Apache-2.0"
] | permissive | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue May 28 17:23:26 2019
@author: gaetandissez
This file load create a loader class to import the data from txt and csv files and create required matrices for our problem
"""
#We use networkx as a way to interpret the data and to transform it easily throu... | true |
e76e49afacb2e50941acebe6fe64ba4f731ad70d | Python | leminhds/streamlit-goodreads-analysis- | /goodreads_app.py | UTF-8 | 3,890 | 3.25 | 3 | [] | no_license | import streamlit as st
from streamlit_lottie import st_lottie
import requests
import pandas as pd
import plotly.express as px
st.set_page_config(layout='wide')
def load_lottieurl(url: str):
r = requests.get(url)
if r.status_code != 200:
return None
return r.json()
file_url = 'https://assets4.lott... | true |
2044b94b4f346553e1aa15d8e84de91528ce57a5 | Python | aldemirneto/Exercicios-Uri | /Exercícios/1589.py | UTF-8 | 121 | 3.578125 | 4 | [
"MIT"
] | permissive | c = int(input())
for i in range(c):
x = input().split()
a, b = int(x[0]), int(x[1])
print('{}'.format(a + b)) | true |
de6124c1ce24d5199fcca1b3cd0ce3aef995cbc8 | Python | cchery101/principlescomputing | /user34_B8OE49NgGi_0.py | UTF-8 | 5,435 | 3.6875 | 4 | [] | no_license | """
Clone of 2048 game.
"""
import poc_2048_gui
# Directions, DO NOT MODIFY
UP = 1
DOWN = 2
LEFT = 3
RIGHT = 4
# Offsets for computing tile indices in each direction.
# DO NOT MODIFY this dictionary.
OFFSETS = {UP: (1, 0),
DOWN: (-1, 0),
LEFT: (0, 1),
RIGHT: (0, -1)}
... | true |
42d4e51ca8b30c65026232a9c4a94b5253ee1234 | Python | newmanlucy/uncommon19 | /create_db.py | UTF-8 | 491 | 2.546875 | 3 | [] | no_license | import sqlite3
def create_db():
conn = sqlite3.connect("weather_betting.db")
c = conn.cursor()
c.execute("""
CREATE TABLE users (username TEXT PRIMARY KEY)
""")
c.execute("""
CREATE TABLE bets (
id INTEGER PRIMARY KEY,
atleast INTEGER,
date DATE,
amount INTEGER,
creator_id TEXT,
taker_id TEX... | true |
77acc352e1702d48dfe44c1bde805f0e4ee6217e | Python | nadson-silva/Data-Science | /Data Visualization Course/Bars_comparation.py | UTF-8 | 354 | 3.9375 | 4 | [] | no_license | import matplotlib.pyplot as plt
x1 = [1, 3, 5, 7, 9]
y1 = [5, 6, 4, 8, 1]
x2 = [2, 4, 6, 8, 10]
y2 = [7, 6, 5, 9, 2]
titulo = "Gráfico de barras 2"
eixoX = "Eixo X"
eixoY = "Eixo Y"
plt.title(titulo)
plt.xlabel(eixoX)
plt.ylabel(eixoY)
# Legenda do grafico
plt.bar(x1, y1, label="Grupo 1")
plt.bar(x2, y2, label="Gr... | true |
0af88915ef99436b28a928021c7fa7592c9766cd | Python | djcomidi/projecteuler | /problem173.py | UTF-8 | 412 | 3.09375 | 3 | [] | no_license | def find_laminae(tilesleft, outersize=0):
if tilesleft < 0:
return 0
if outersize == 0:
total = 0
for size in range(2, tilesleft // 4 + 1):
total += find_laminae(tilesleft - (size * 4), size)
return total
else:
newsize = outersize + 2
return 1 + fi... | true |
73ca02358d2f2d76390cd7a4711e6de5ec98e860 | Python | theodao/nanodegree-algorithm-datastructures | /Chapter1/Task2.py | UTF-8 | 618 | 3.546875 | 4 | [] | no_license | """
Read file into texts and calls.
It's ok if you don't understand how to read files
"""
import csv
from collections import defaultdict
with open('texts.csv', 'r') as f:
reader = csv.reader(f)
texts = list(reader)
with open('calls.csv', 'r') as f:
reader = csv.reader(f)
calls = list(reader)
spending... | true |
9103f3f228d1a61486e4cab8caa829c061fc8454 | Python | r3n4t3/python-mini-projects | /virus.py | UTF-8 | 1,343 | 2.921875 | 3 | [] | no_license | import os, datetime, inspect
DATA_TO_INSERT = "A VIRUS JUST INFECTED YOUR FILE"
def search(path):
filesToInfect = []
files = os.listdir(path)
for file in files:
if os.path.isdir(file):
filesToInfect.extend( search(os.path.join(path + "/" + file)) )
elif file[-3:] == '.py':
... | true |
3e792ae5800546332f7bdf53b383c29bbcbecd2e | Python | pyman01/financial1 | /financial1.py | UTF-8 | 3,140 | 3.46875 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""financial1 [Startkapital] [Zinssatz p.a.] [Laufzeit in Jahren]
-h help, diesen "Docstring"-Text anzeigen
-o output, Werte als Datei (raus)schreiben
-p plot, (vorher mit -o generierte) *.dat Dateien zur Darstellung an gnuplot weiterreichen
Beispiel d... | true |
45272a62e476ccee3e2c1ac3aafc85f151ef87e6 | Python | tbgers/rcViewbot | /viewbot.py | UTF-8 | 5,185 | 2.578125 | 3 | [] | no_license | import sys, os, time, datetime, asyncio, aiohttp
f = open('/dev/null', 'w')
sys.stderr = f
def moveCursor(x, y):
sys.stdout.write("\033[" + str(y) + ";" + str(x) + "H")
sys.stdout.flush()
# | dark | bright |
# --------+------+--------+
# black | 0 | 8 |
# red | 1 | 9 |
# green ... | true |
7f17b523ac8d55c05a00f6b992407bdfc8140b13 | Python | Mintic-ProyectoAUBONPAIN/RETO_FINAL_2022_GRUPO4_AU_BON_PAIN | /models.py | UTF-8 | 1,466 | 2.640625 | 3 | [
"MIT"
] | permissive | from datetime import datetime
from werkzeug.security import generate_password_hash, check_password_hash
from app import db, login_manager
from flask_login import UserMixin
@login_manager.user_loader
def load_user(id):
return User.query.get(int(id))
# ------- Create the User Model -------
class User(db.Model,... | true |
6c08fd006182fdd25d4ff886c891d3c84090b92f | Python | Jeremip11/precog | /href.py | UTF-8 | 4,825 | 2.640625 | 3 | [
"ISC"
] | permissive | from urlparse import urlparse, urljoin, urlunparse
from re import match
def get_redirect(req_part, ref_url, slash_count=3):
'''
>>> get_redirect('/style.css?q=Hi', 'http://preview.local/foo/bar/baz/')
'/foo/bar/baz/style.css?q=Hi'
>>> get_redirect('/style.css?q=Hi', 'http://preview.local/foo/bar/b... | true |
d84f7b232027ea9f6f718682be773c0ad4085b49 | Python | gladiopeace/csc-manager-ui | /app_tools/os_utils.py | UTF-8 | 277 | 2.90625 | 3 | [] | no_license | import os
import shutil
import sys
def restart_program():
python = sys.executable
os.execl(python, python, *sys.argv)
def copy_tmp_file(old_file):
new_file = old_file + "tmp"
shutil.copy(old_file, new_file)
print("Make copy {}. Done!".format(new_file))
| true |
fb5febffb56ec5070bc05c82408740eeba40bbb9 | Python | janmotl/rf | /rf_test.py | UTF-8 | 2,721 | 3.046875 | 3 | [
"BSD-2-Clause"
] | permissive | import unittest
from numpy.testing import assert_almost_equal
from rf import RF
from numpy import *
# Data
y = array([0, 1, 0, 1, 1])
X0 = array([[0], [1], [0], [1], [1]])
X1 = array([[0, 1], [1, 0], [0, 1], [1, 2], [1, 3]])
X2 = array([[0, 3], [1, 2], [0, 0], [1, 2], [1, 3]])
# Numpy warnings to errors
seterr(all=... | true |
83c0adea2b0a854b237f166487c355bd0741d4d0 | Python | flodesi/NEATris | /main.py | UTF-8 | 6,101 | 2.71875 | 3 | [] | no_license | #!/usr/bin/python3
import os
import pickle
from time import sleep
import neat
import pygame
from Tetris.tetris import Tetris
from Tetris.global_variables import ROTATE_KEY, RIGHT_KEY, LEFT_KEY, DOWN_KEY
from utils import attempt
import argparse
pygame.init()
pygame.display.set_caption('NEATris')
with open("winner_wi... | true |
8b0e4e63fec9623369c48c3b6fa1e855008b2ef6 | Python | sahands/problem-solving | /misc/acmpacnw2013/janeway.py | UTF-8 | 4,716 | 3.359375 | 3 | [] | no_license | from __future__ import division
from math import sqrt, atan2, pi
from sys import stdin
__author__ = "Sahand Saba"
EPS = 1e-6
class Point(object):
__slots__ = ['x', 'y']
def __init__(self, xx=0.0, yy=0.0):
self.x = float(xx)
self.y = float(yy)
def angle(self):
"""
Retur... | true |
8f9990feb63ebbf56e1b40b234fe05a5111a38fd | Python | Wahe3bru/IoT_temp | /send_email.py | UTF-8 | 2,747 | 3.09375 | 3 | [] | no_license | # https://changhsinlee.com/pyderpuffgirls-ep4/
import os
import smtplib
import ssl
from email.mime.text import MIMEText
from email.mime.application import MIMEApplication
from email.mime.multipart import MIMEMultipart
from pathlib import Path
def send_email(username, password, recipient, subject, body, attachment=None... | true |
19c16d22d0223a5d8b94be289c19b3803c383df3 | Python | siddharth456/Python_Scripts_1 | /for_loop_through_dictionary.py | UTF-8 | 256 | 3.203125 | 3 | [] | no_license | test_dict={"Name":"Ankit Kumar","Age":"29","Profession":"IT","Location":"New Delhi"}
# for key in test_dict:
for key,value in test_dict.items():
# print(key+": "+test_dict[key])
print(key+":"+value)
# key for getting key and test_dict[key] for value | true |
2e14df6f369217d7cb7ebc09361a0121e330fc7b | Python | linsalrob/Genotype-Phenotype-Modeling | /scripts/gapfill_from_reactions.py | UTF-8 | 18,180 | 2.65625 | 3 | [
"MIT"
] | permissive | import argparse
import copy
import sys
import PyFBA
__author__ = 'Rob Edwards'
"""
This code is designed to exemplify some of the gap-filling approaches. If you start with an ungapfilled set of
reactions, we iteratively try to build on the model until it is complete, and then we use the bisection code
to trim out rea... | true |
7a3abbaea203e851049a59d339a48743ae5a1537 | Python | RoyRin/Computational_Physics_2016 | /proj3_MonteCarlo/IsingModel_Metropolis.py | UTF-8 | 8,272 | 2.875 | 3 | [] | no_license | from pylab import *
import numpy as np
import matplotlib.pyplot as plt
import math
import matplotlib.mlab as mlab
import random
spins =100
aveSpinGroup = 10
ising = []
J = -0.20 #alignmentE = -0.20 # energy of alignment
mu = 0.33
B = 0.
kB = 1.0
temperature = 100.
time = 150.
timeplots =time/1.0
timeplotsteps = int(... | true |
18909f578c7a27e8d600e8a593ad6151a3ee3bc4 | Python | dr-dos-ok/Code_Jam_Webscraper | /solutions_python/Problem_76/128.py | UTF-8 | 689 | 2.828125 | 3 | [] | no_license | filename = input("Enter file name of test case: ")
rfname = input("Enter result file name: ")
file = open(filename)
ipt = file.readlines()
ls = int(ipt[0])
res = []
for n in range(2,ls*2+1,2):
print(n)
cln = ipt[n]
cln = cln.strip()
cln = cln.split(" ")
for i in range(len(cln)):
cln[i] = int(cln[... | true |
40cea76e7b4698ac5db4cc7078a5d9c0f5e53f6d | Python | lars76/pysais-utf8 | /test_pysais.py | UTF-8 | 1,965 | 3.25 | 3 | [
"MIT"
] | permissive | from unittest import TestCase
from sais import *
import operator
def find_all_matches(suffix_arr, text, query):
def binary_search(lo, hi, op):
m = len(query)
while lo < hi:
mid = (lo + hi) // 2
suffix = suffix_arr[mid]
if op(text[suffix:suffix+m], query):
... | true |
6d97a6078e81d6f1bee2fab626fa1abffdefc582 | Python | spearfish/python-crash-course | /example/06.3.4_enumerate_values.py | UTF-8 | 379 | 3.25 | 3 | [] | no_license | #!/usr/bin/env python3
fav_langs = {
'jen' : 'python',
'sarah' : 'c',
'edward' : 'ruby',
'phil' : 'python'
}
print("The following langs are mentioned : ")
for lang in fav_langs.values() :
print("\t" + lang)
print("Let's eliminate the dumplicates")
print(type(set(fav_langs.values())))
for... | true |
e5a5ed5f8fb038975c978e324998e32a3fb118cb | Python | Rafapia/Deep-Reinforcement-Learning-Algorithms-with-PyTorch | /DeepRL/agents/policy_gradient_agents/REINFORCE.py | UTF-8 | 4,407 | 3.109375 | 3 | [
"MIT"
] | permissive | import numpy as np
import torch
import torch.optim as optim
from torch.distributions import Categorical
from agents.Base_Agent import Base_Agent
class REINFORCE(Base_Agent):
agent_name = "REINFORCE"
def __init__(self, config):
Base_Agent.__init__(self, config)
self.policy = self.create_NN(input... | true |
c2374c893b39197c1b452f162d494a9652ff251d | Python | 1802343117/Python-Learn | /Python Basic grammar/Exercise32.py | UTF-8 | 1,034 | 3.03125 | 3 | [] | no_license | from threading import Thread
import requests
# 继承Thread类创建自定义的线程类
class DownloadHandle(Thread):
def __init__(self, url, name):
super().__init__()
self.url = url
self.name = name
def run(self):
filename = self.name
print(filename)
resp = reques... | true |
3859d5c6b46487868abfe99a577a8a7a7fb6d8a8 | Python | karthikeyankadirvel/MachineLearning | /Descision_Tree.py | UTF-8 | 3,608 | 2.71875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Sat Nov 16 20:53:27 2019
@author: karth
"""
import numpy as np
import math
import pandas as pd
from collections import Counter
import os
os.chdir(r"C:\Users\karth\JupyterProjects\MachineLearning")
#%%
data=pd.read_excel("data.xlsx")
x=data[['Chest_pain', 'Leg_pain', 'Kideney_pain... | true |
291757e8260bd50b94ab1329fec46d1a29a15cb5 | Python | Winterbl00m/URISE-solarforecasting | /LSTM_model.py | UTF-8 | 7,376 | 3.09375 | 3 | [] | no_license | # Importing the libraries
import tensorflow as tf
from tensorflow import keras
import pandas as pd
import random
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.models import Model
from tensorflow.keras.layers import LSTM, Dense, Input, concatenate
import matplotlib.pyplot as plt
from tensorfl... | true |
9dc8753b1ae2acd4dddd3969000958010c9e3b9c | Python | siolag161/markov_generator | /tests/markogen_tests.py | UTF-8 | 3,146 | 2.9375 | 3 | [] | no_license |
from nose.tools import *
from collections import deque
import unittest
from markogen.models import *
from markogen.tools import *
# def setup():
# print "SETUP!"
# def teardown():
# print "TEAR DOWN!"
# def test_basic():
# print "I RAN!"
class testGraphModel(unittest.TestCase):
def test_constru... | true |
30af63aea12a4a80920278874ad596d824c5fc25 | Python | alahoo/BitTornado | /BitTornado/Application/parseargs.py | UTF-8 | 3,954 | 3.28125 | 3 | [
"MIT"
] | permissive | def formatDefinitions(options, COLS, presets={}):
"""Format command-line options and documentation to fit into a given
column width
Parameters
tuple[] - (flag, default, docstring) tuples describing each flag
int - Number of columns to write
dict - {flag: value} overrides for ... | true |
e89df5bd00a860aaad6018eb0f22a2b05e50b231 | Python | HantaoShu/OpenDrug | /baseline_methods/run_rf.py | UTF-8 | 2,394 | 2.625 | 3 | [
"Apache-2.0"
] | permissive | import argparse
import pickle
import numpy as np
from scipy.stats import pearsonr
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import make_scorer
from sklearn.model_selection import KFold, cross_val_score, GridSearchCV
def pearson_corr(y, y_pred, **kwargs):
if np.isnan(y).any() or np.i... | true |
1f129d4e8fabc4492abb6ad9b3b852fd37bd8553 | Python | Danny0327/MisionTIC2022 | /Modulo1_Python_MisionTIC2022_Main/Semana_3/Retos/P22/Reto_3_P22_Casos_de_prueba.py | UTF-8 | 2,389 | 3.6875 | 4 | [] | no_license | def Agendamiento(eventos: list):
agenda = {} #Inicializar diccionario
for fEvento,hEvento,aEvento in eventos: #Ciclo para agregar un nuevo evento
if agenda.get(fEvento) == None: #Fuerza la entrada
agenda[fEvento] = [] #Creacion de un nuevo evento
... | true |
d7a9e645ee17a1231be7c22e0b1da4cd796e80e3 | Python | GassaFM/contests | /facebook/fbhc2016-qual/agen.py | UTF-8 | 168 | 2.8125 | 3 | [] | no_license | import random
t = 1
n = 2000
print t
for k in range (t):
print n
for i in range (n):
print random.randint (-10000, +10000),
print random.randint (-10000, +10000)
| true |
73609ca0cadad2e0c568eacf4c7fa874fdf5e2fb | Python | Bruce-Decker/VRTube | /selenium/test01.py | UTF-8 | 1,627 | 2.96875 | 3 | [
"Apache-2.0"
] | permissive | """
Setup
1. Install Python selenium module: $ pip install selenium
2. Download Chrome Webdriver and place in /usr/local/bin
"""
import time
from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.chrome.options import Options
def main():
#ip = "local... | true |
d9c64cc5482099f10f68ccdcd6d31afac9250c7c | Python | MohamedGhadie/edgotype_fitness_effect | /code_extra/produce_ppi_models_5.py | UTF-8 | 1,965 | 2.515625 | 3 | [] | no_license | #----------------------------------------------------------------------------------------
# Produce PPI structural models.
# Call script from directory ../data/processed/<interactome_name>/model_based/ppi_models.
#----------------------------------------------------------------------------------------
import os
from p... | true |
b0a8ab20d0002efa3ed0f51238397dca999efc3e | Python | fuktommy/homebin | /mkrss | UTF-8 | 8,778 | 2.5625 | 3 | [
"BSD-2-Clause"
] | permissive | #!/usr/bin/python3
"""Make RSS for file list.
It requires rss.py by Fuktommy.
Synopsis:
mkrss.py [/path/to/html/dir] > rss.xml
mkrss.py -b /path/to/html/dir file_list > rss.xml
find /path/to/html/dir -type f | \
mkrss.py -b /path/to/html/dir > rss.xml
Options:
-h header_file: File includes ti... | true |
c24aeb0709fd726b28a252b2d23f6c8b6a3f812d | Python | goiri/greendcsimulator | /timelist.py | UTF-8 | 2,129 | 3.515625 | 4 | [] | no_license | #!/usr/bin/env python2.7
from commons import interpolate
"""
Class to implement a series of values in time
"""
class TimeList:
def __init__(self, continous=True):
self.list = [] # [(time, value),...]
self.continous = continous
def __str__(self):
return str(self.list)
def __len__(self):
return len(self.l... | true |
0c6aeed30a4f5f0f861cf70be525731c1a2c5a26 | Python | justin8/video_utils | /tests/test_video.py | UTF-8 | 5,720 | 2.640625 | 3 | [
"MIT"
] | permissive | import pytest
import os
from os import path
from mock import patch
import pickle
from video_utils import Video, Codec
def test_minimal():
v = Video("foo.mkv", "/not-a-real-path/bar")
assert v.name == "foo.mkv"
assert v.dir_path == "/not-a-real-path/bar"
def test_full_path():
v = Video("foo.mkv", "/... | true |
c15b53b5146ea1c3e0216dd8523a23d08b26c0aa | Python | klmitch/bark | /bark/handlers.py | UTF-8 | 14,448 | 2.828125 | 3 | [
"Apache-2.0"
] | permissive | # Copyright 2012 Rackspace
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | true |
76ba6e2e17b24b716fcd2135205d455b68a17c7e | Python | shuaiweixiaozi/pytorch_example | /ts_example/ts_utils/feature_engineering.py | UTF-8 | 4,211 | 2.625 | 3 | [] | no_license | import numpy as np
import pandas as pd
import warnings
from statsmodels.tsa.stattools import acf
warnings.filterwarnings('ignore')
def sin_transform(values):
return np.sin(2*np.pi*values/len(set(values)))
def cos_transform(values):
return np.cos(2*np.pi*values/len(set(values)))
def get_yearly_autocorr(da... | true |
85e3c1f5fca1a068f75259f6a29c0934f672de77 | Python | Wangjk1997/DT | /d_function.py | UTF-8 | 2,670 | 2.90625 | 3 | [] | no_license | from math import log2
def find_max_gain(dataset):
#对每个特征找到其分类的类别
num_feature = len(dataset[0]) - 1
feature_set = list()
for i in range(0,num_feature):
tmp_feature = list()
for tmp in dataset:
if not tmp[i] in tmp_feature:
tmp_feature.append(tmp[i])
... | true |
9f6e71d2b6edee357d69aef795a686b0ce85e1ff | Python | olimpiojunior/Estudos_Python | /Section_10/map.py | UTF-8 | 1,110 | 4.15625 | 4 | [] | no_license | """
map - função map realiza mapeamento de valores para função
function - f(x)
dados - a1, a2, a3 ... an
map object: map(f, dados) -> f(a1), f(a2), f(a3), ...f(an)
-------------------------------------------------------------------
import math
def calc(r):
return math.pi * (r**2)
raios = [1, 2.2, 3., 4, 5.7, 8]
l... | true |
2a30c98f77eba33dac02d7c7a22c324255d0dfb9 | Python | antondelchev/Python-Basics | /First-Steps-in-Coding---Exercise/04. Vacation books list.py | UTF-8 | 208 | 3.15625 | 3 | [] | no_license | total_pages = int(input())
pages_per_hour = int(input())
days_to_read = int(input())
hours_to_read_book = total_pages / pages_per_hour
hours_per_day = hours_to_read_book / days_to_read
print(hours_per_day)
| true |
e611d078eb1fc31ea9ddb3e2f5272aabd345bdaf | Python | nanoracket/loan-schedule | /loan.py | UTF-8 | 6,057 | 2.984375 | 3 | [] | no_license | from datetime import date, datetime, timedelta
from uuid import uuid4
from database import Database
db = Database()
class Loan():
def __init__(self, data_map):
self.id = data_map["id"]
self.monthlyPaymentAmount = data_map["monthlyPaymentAmount"]
self.paymentDueDay = data_map["payment... | true |
00f7d24c71ec408d756581b53364598e824c8214 | Python | NandanParamashiva/Artificial-Intelligence | /HW1/Avi/1/homework.py | UTF-8 | 17,513 | 3.046875 | 3 | [] | no_license | #!/usr/bin/env python
from sys import exit
from collections import deque
_DEBUG_ENABLE = True
OFFSETLIVETRAFFIC = 4
ROOTNODEID = -100
ALGOS = ('BFS', 'DFS', 'UCS', 'A*')
def Debug_print(msg):
""" Method to print the debug messages """
global _DEBUG_ENABLE
if _DEBUG_ENABLE is True:
print 'DEBUG:'+ msg
cla... | true |
0db6a3441a104ec8e2fe4fd20b590b128afdb01e | Python | sstewart0/data_science_projects | /Airbnb/bnb/NER/clean_data.py | UTF-8 | 5,692 | 3.25 | 3 | [] | no_license | """
Clean data:
1. Remove special characters: !@£$%^&*() ...
2. Change all "words" to lower case
3. Remove possessive pronouns, e.g. Stephen's ---> Stephen
4. Amend abbreviations e.g. apt ---> apartment; {BR,bdrm,...} ---> bedroom
5. Separate numbers and words e.g. 2bath ---> 2 bath
6. Change nu... | true |
fafc3b9aa6b4f98d06cef2821380ce156529461b | Python | clellmann/particle-kriging | /dags/functions/kriging.py | UTF-8 | 3,302 | 3 | 3 | [] | no_license | import numpy as np
import pandas as pd
from haversine import haversine
def krige_point(distance_vector, distance_matrix, semivariogram, train_values):
"""
Kriges a point (kriging based location prediction).
Args:
distance_vector (np.array): Distance vector from training points to prediction po... | true |
c04e61778a7ee950b36d04d473d363dc3aafd7eb | Python | ADanciulescu/Midas | /data_fetchers/candle_fetcher.py | UTF-8 | 7,090 | 2.984375 | 3 | [] | no_license | ##fetches candle data and completes a large candle table for each currency
from poloniex import Poloniex
from tools import timestamp_to_date
from db_manager import DBManager
from candle_table import CandleTable
from candle import Candle
from tools import date_to_timestamp
from candle_parser import CandleParser
import... | true |
3472112d93db211635af5a5ff1476815755683d9 | Python | EhwaZoom/bpgen | /bpgen/commands/create_module.py | UTF-8 | 545 | 2.625 | 3 | [
"Apache-2.0"
] | permissive | import os
from bpgen.path import get_path_to_templates, get_path_to_module
from bpgen.utils import print_and_exit
def handle(arguments):
path_to_module = get_path_to_module(
arguments.output,
arguments.module_name
)
path_to_module_templates = get_path_to_templates(path_to_module)
mod... | true |
ae8a51bc000b75bc65d815ca8dd0f28a2d3c9f37 | Python | NLeSC/ShiCo | /shico/vocabularyaggregator.py | UTF-8 | 5,713 | 3.515625 | 4 | [
"Apache-2.0"
] | permissive | import six
from sortedcontainers import SortedDict
from collections import defaultdict
from utils import weightJSD, weightGauss, weightLinear
from format import getRangeMiddle
class VocabularyAggregator():
'''A VocabularyAggregator takes a vocabulary produced by a VocabularyMonitor
and aggregates them over a ... | true |
9ade88cd867f754f173e79398d05afc5dbfda845 | Python | Tyrpix/ICUSystem | /ICUSystem.py | UTF-8 | 1,986 | 3.46875 | 3 | [] | no_license | # Constructs the object ICU System with all patient objects and their respective data which is stored in a list
from HRDayOne import HRDayOne
from InitialLR import InitialLR
import datetime
class ICUSystem:
def __init__(self):
# Holds diagnosis for each patient (patient + hourly round data)
self.d... | true |
fb852d8e47ad84686f7530ba443881d5cd9cd212 | Python | Aasthaengg/IBMdataset | /Python_codes/p03135/s769595462.py | UTF-8 | 73 | 3.234375 | 3 | [] | no_license | str=input()
str=str.split(" ")
T=float(str[0])
X=float(str[1])
print(T/X) | true |
6b02e0ac9b6c207d1b568a68d4bc1e531012d84e | Python | ALMTC/Logica-de-programacao | /Python/16.py | UTF-8 | 218 | 3.640625 | 4 | [] | no_license | print 'Digite o salario'
a=input()
print 'Digite a primeira conta'
b=input()
print 'Digite a segunda conta'
c=input()
b=b+(b*2)/100.0
c=c+(c*2)/100.0
r=a-b-c
print 'Sobram ' + str(r) + 'R$ do salario minimo'
| true |
faaee3f4f93d6e096102a64daf8df64ebacf0007 | Python | FazeelUsmani/Leetcode | /07 July Leetcode Challenge 2021/02_findKclosestEle.py | UTF-8 | 474 | 3.640625 | 4 | [
"MIT"
] | permissive | class Solution:
def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]:
# Initialize binary search bounds
left = 0
right = len(arr) - k
# Binary search against the criteria described
while left < right:
mid = (left + right) // 2
... | true |
7444fe6cfa924d1ee82ee97531b484dfb4bab49b | Python | vradenbr/cti110 | /P5HW1_RandomNumber_VradenburghRyan.py | UTF-8 | 3,097 | 4.96875 | 5 | [] | no_license | # A simple program that generates a random number and allows the user to guess the number.
# 23APR2021
# CTI-110 P5HW1 - Random Number
# Ryan Vradenburgh
#
'''
BEGIN
Menu Function:
Option 1: Play Game
Option 2: Exit Program
Accept User Input
Return User Input
Game Function:
Generate... | true |
d9e086a1f6d7f0716f63a5d9e2db329d1c061935 | Python | poohcid/class | /PSIT/20.py | UTF-8 | 448 | 3.28125 | 3 | [] | no_license | """Gift I"""
def main():
"""Function process and print"""
result = more(int(input()), more(int(input()), 0))
result = more(int(input()), more(int(input()), result))
result = more(int(input()), more(int(input()), result))
result = more(int(input()), more(int(input()), result))
print(result)
def... | true |
b1e92d4b88b5e60a3e415fff4415f083b89aa5be | Python | onikazu/ProgramingCompetitionPractice | /Atcoder/abc092/b.py | UTF-8 | 189 | 2.703125 | 3 | [] | no_license | n = int(input())
d, x = list(map(int, input().split()))
a = [int(input()) for _ in range(n)]
ans = 0
for i in range(len(a)):
ans += 1
ans += (d - 1) // a[i]
ans += x
print(ans)
| true |
42ba89d3685cc3dbd5a30d38a68b8a0ca67b430d | Python | Kninoxx/python-random-quote | /rnd.py | UTF-8 | 129 | 2.609375 | 3 | [] | no_license | import random
rnd=random.randrange(100000,999999)
def function():
print(rnd)
if __name__ == "__main__":
function()
| true |
31d7f20c0e9bd0e43bb16774986001f3489f2333 | Python | BogdanTodor/Discord-InsultBot | /InsultBot.py | UTF-8 | 2,252 | 3.25 | 3 | [] | no_license | from discord.ext import commands
import discord
from random import *
linkInsult = ['Insert insults in the list here. These will be called when someone links anything in the chat']
TOKEN = 'Your token here'
client = discord.Client()
@client.event
async def on_message(message):
if message.author == client.user:
... | true |
44b29c319f523d32567fd58f81cdeaadcd60a425 | Python | ptmcg/plaso | /tests/analysis/tagging.py | UTF-8 | 4,061 | 2.515625 | 3 | [
"Apache-2.0"
] | permissive | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Tests for the tagging analysis plugin."""
from __future__ import unicode_literals
import unittest
from plaso.analysis import tagging
from plaso.lib import timelib
from plaso.containers import events
from tests import test_lib as shared_test_lib
from tests.analysis i... | true |
ace57fb0c473ab3cf50e031c0cdf270a3a3b112d | Python | Yangyu0879/Tongji-SE-2018-OS-Project | /MemoryManagement/MemoryManagement.py | UTF-8 | 4,029 | 2.9375 | 3 | [] | no_license | import random
class MemoryManagementCore:
def __init__(self):
self.blockPage=[[-1 for i in range(4)] for i in range(2)]#用于存放当前在物理内存中的页号
self.blockFIFOQueue=[-1]*320#FIFO算法所需要使用的队列
self.queueHead=0#队列头部
self.queueCurrent=0#队列尾部
self.blockLRUSignal=[0]*4#LRU算法所需的列表
sel... | true |
4f742afef81edfebf23b97ae8677e47d2224a49c | Python | jeremymaignan/facebook-messenger-analytics | /api/src/apis/message.py | UTF-8 | 5,056 | 2.546875 | 3 | [
"MIT"
] | permissive | from collections import defaultdict
import emoji
import langid
import pycountry
from flask import request
from apis.base import Base
from models import db
from models.message import Message
from schemas.message import MessageSchema
from utils import messages
from utils.logger import log
from utils.registry import reg... | true |
067515b9e57fc850a2767340e49e1734f8e63a53 | Python | Kvazar78/Skillbox | /16_list2/dz/task_10.py | UTF-8 | 1,032 | 3.8125 | 4 | [] | no_license | def comparison(seq, seq_r, i_s):
result = False
i_sr = 0
for num in range(i_s, len(sequence)):
if seq[num] ==seq_r[i_sr]:
i_sr += 1
result = True
else:
result = False
break
return result
count_num = int(input('Кол-во чисел: '))
sequence =... | true |
b4e31bad24d8878abc6a237a40d493bf905cf08d | Python | marsella/euler-project | /pe22.py | UTF-8 | 502 | 3.46875 | 3 | [] | no_license | # alphebetize a list, calculate scores, sum the scores
# project_euler.com/problem=22
def alphabetize(file_name = "names.txt"):
f = open(file_name, 'r')
names = []
for line in f:
names = str.split(str.replace(str.replace(line, '\"', ''), '\r', ''), ',')
names.sort()
# replace each name with its score
... | true |
67f70f8c7aaffee96efae8b1efe4e596cfd1dd88 | Python | steven-mathew/contest-problems | /python-solutions/System.py | UTF-8 | 320 | 3.265625 | 3 | [] | no_license | n = int(input())
coefficients = []
for i in range(n+1):
coefficients.append(float(input()))
first = coefficients[0]
last = coefficients[-1]
ans = (abs(float(last)/first))**(float(1)/n)
if n%2:
if last * first > 0:
ans=-ans
else:
if coefficients[-2]*last > 0:
ans=-ans
k='%.6f'%ans
print(k) | true |
16a5678555056b619918b3b0c57aa679e5961f19 | Python | tushar-1996/Anamoly-Detection-with-Continous-Learning-Algorithm | /Models/lowerdim.py | UTF-8 | 4,507 | 2.75 | 3 | [] | no_license | import csv
import re
#import pandas as pd
import numpy as np
#import tensorflow as tf
#from sklearn.metrics import f1_score
from sklearn.manifold import TSNE
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
START_CUTOFF = 30.0
train_features = []
train_labels = []
val_features = []
val_labels ... | true |
b5a17863a4e0c9072427aab288e8104505d82409 | Python | mtlynch/sia_load_tester | /sia_load_tester/upload_queue.py | UTF-8 | 1,740 | 2.71875 | 3 | [
"MIT"
] | permissive | import logging
import Queue
import sia_client as sc
logger = logging.getLogger(__name__)
def from_upload_jobs(upload_jobs):
"""Creates a new upload queue from a list of upload jobs.
Creates a new queue of files to upload by starting with the full input
dataset and removing any files that are uploaded (... | true |
4e1adfe79ee2a7dbb0209f1919c40f30476ad436 | Python | DaniAkiode/portfollio | /Python Practice/Software Development/Login 6.0.py | UTF-8 | 1,580 | 3.390625 | 3 | [] | no_license | #-------------------------------------------------------------------------------
# Name: module1
# Purpose:
#
# Author: Guest123
#
# Created: 20/02/2018
# Copyright: (c) Guest123 2018
# Licence: <your licence>
#-------------------------------------------------------------------------------
#User... | true |
5ae23da5659a3c0fe8a798e4541dc0cf2badfde3 | Python | suyash248/ds_algo | /DynamicProgramming/equalSumSubsets.py | UTF-8 | 2,939 | 4.125 | 4 | [
"Apache-2.0"
] | permissive | from Array import empty_2d_array
# Time complexity: O(2^n)
# Space complexity: O(n)
def is_subset_sum(arr, n, half_sum):
"""
Algorithm ->
Let is_subset_sum(arr, n, sum/2) be the function that returns true if there is a subset of arr[0..n-1]
with sum equal to sum/2(i.e. half_sum).
Case 1: If sum o... | true |
9c7a8e47fb6691e7d1002f06dffe8bd712dd7043 | Python | adishavit/cvxpy | /cvxpy/constraints/power.py | UTF-8 | 9,243 | 2.828125 | 3 | [
"Apache-2.0"
] | permissive | """
Copyright 2021 the CVXPY developers
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, so... | true |
dbf8caee912ccf0d005787363e2a4a45143f1c70 | Python | lydialaseur/btree | /createMyIndex.py | UTF-8 | 1,888 | 2.96875 | 3 | [] | no_license | from btreeindex import BTreeIndex
from btreenode import BTreeNode
import os
# os.chdir('/usr/share/databases/FanFiction/')
table_dir = 'stories'
col = 'AUTHOR'
p = 3
idx = BTreeIndex(table_dir,col,3)
num_insertions, num_levels = idx.create()
print(num_insertions)
# print the first first 2 levels of the tree
print(... | true |
8069b6d3f604282d584297dcbe9b0a0a708f4f7c | Python | DaHuO/Supergraph | /codes/CodeJamCrawler/16_0_2_neat/16_0_2_tli_codejam2016QB.py | UTF-8 | 371 | 3.453125 | 3 | [] | no_license | t = input()
for i in xrange(t):
s = raw_input()
num_inversions = 0
cur_char = s[0]
for j in xrange(1, len(s)):
if cur_char != s[j]:
num_inversions += 1
cur_char = s[j]
parity = 0 if s[0] == '+' else 1
parity += num_inversions
c = num_inversions + parity %... | true |
c00364957bad4e4dd02c56af233c9997c7dcc0bd | Python | vedaant-varshney/FitnessDetection | /SecondTutSet/histograms.py | UTF-8 | 863 | 3.140625 | 3 | [] | no_license | import cv2
import numpy as np
import matplotlib.pyplot as plt
img = cv2.imread("images/Lionel-Messi.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Creating Grayscale Histogram
# Note that we can create a histogram based on the mask of an image
gray_hist = cv2.calcHist([gray], channels=[0], mask=N... | true |
38dbb40ee45e8573f32bd0a83fc103445b86cf99 | Python | joepatmckenna/normal_forms | /normal_forms/examples/normal_form/for_plotting.py | UTF-8 | 663 | 3 | 3 | [
"MIT"
] | permissive | import matplotlib.pyplot as plt
import numpy as np
def before_and_after(f, h, x_min=-1, x_max=1, y_min=-1, y_max=1):
fig, ax = plt.subplots(1, 2, figsize=(8, 3))
x = np.linspace(x_min, x_max, 500)
y = np.linspace(y_min, y_max, 500)
X, Y = np.meshgrid(x, y)
Z = np.array([[f(xi, yi) for xi in x] fo... | true |
c65fc51d04feed5dd3fc33e0d29e37704a902947 | Python | ahakingdom/codesters-graphics | /codesters/examples/wip/frogger.py | UTF-8 | 4,664 | 3.109375 | 3 | [
"MIT"
] | permissive | ## FROGGER BY SHIRLEY
## LOCATED HERE: https://www.codesters.com/preview/86a38f1a916adbfd928e4b4d54c758e2782f115a/
import codesters
stage = codesters.Environment()
start_ground = codesters.Rectangle(0, -240, 500, 25, "darkgreen")
mid_ground = codesters.Rectangle(0, 0, 500, 25, "darkgreen")
end_ground = codesters.Re... | true |
eb9562021fc4b0f8ac9730bd056e5fde5dccbfd2 | Python | sasakishun/atcoder | /ABC/ABC114/D.py | UTF-8 | 2,349 | 3.609375 | 4 | [] | no_license | n = int(input())
# 入力 : 自然数 ex) 12
# 出力 : 約数リスト ex) [(2,2),(3,1)]
def factorize(n):
fct = [] # prime factor
b, e = 2, 0 # base, exponent
while b * b <= n:
while n % b == 0:
n = n // b
e = e + 1
if e > 0:
fct.append((b, e))
b, e = b + 1, 0
... | true |
42a9f4723def5027b4cdc8893aba7c2244842fed | Python | darshandoshi95/PYQT_apps | /UDEMY course codes/Code/Section1/Video4_Layout_of_widgets_1_POSITIONAL.py | UTF-8 | 16,054 | 2.5625 | 3 | [] | no_license | '''
Created on Aug 25, 2017
@author: Burkhard A. Meier
'''
# Using the final GUI created in Video 1.3
# import sys
# from PyQt5.QtWidgets import QApplication, QMainWindow, QAction
# from PyQt5.QtGui import QIcon
#
# class GUI(QMainWindow):
# def __init__(self):
# super(... | true |
62bfe22a743b31f9d68266d4e8b23780bf269595 | Python | nikkss94/Social-_Pandas_Network | /testpanda.py | UTF-8 | 1,171 | 3 | 3 | [] | no_license | from panda import Panda
import unittest
class TestPanda(unittest.TestCase):
def setUp(self):
self.vladko = Panda('Vladko', 'vladko@pandamail.com', 'male')
def test_is_male(self):
self.assertEqual(self.vladko.isMale(), True)
def test_is_female(self):
self.assertEqual(self.vladko.is... | true |
07d7b9afd80da3257fb6959b7935087ea88c6b46 | Python | nielsonnp/segundoperiodo | /exercicio2/questao3.py | UTF-8 | 551 | 4.15625 | 4 | [] | no_license |
notas = []
aprovado = 0
reprovado = 0
print('Digite notas de 0 - 100:')
for i in range(0,10):
nome = input("Qual o seu Nome? ")
n1 = float(input("Digite a primeira nota: "))
n2 = float(input("Digite a segunda nota: "))
n3 = float(input("Digite a terceira nota: "))
media = (n1+n2+n3)/3
notas.a... | true |
cb2f295b427d064a63e9f59e465605de0f565e4a | Python | omerk2511/dropbox | /client/controllers/directory.py | UTF-8 | 1,506 | 2.671875 | 3 | [
"MIT"
] | permissive | from common import Codes, Message
from ..handlers.connection import Connection
class DirectoryController(object):
@staticmethod
def create_directory(name, parent, token, group=None):
"""
Creates a directory
args: name, parent, token, group
ret: response
"""
requ... | true |
5a0a5a7f19a659699cce15d83d232a581ec741a8 | Python | joobn72/hacker-scripts | /src/hs-work.py | UTF-8 | 1,258 | 3.0625 | 3 | [] | no_license | # Author: Areeb Beigh
# Created: 10th April 2016
'''
Description: Opens all the project files in config.ini [hs-work] with
Microsoft Visual Studio Code (code must be in PATH)
'''
import os, configparser, sys
# Gets the root directory (Drive letter in case of windows)
rootDirectory = os.path.splitdrive(sys.executabl... | true |
5d5bac79ca8e1cd34cc520ff6717c58db7ad1d04 | Python | 6GeniusTurtle9/TIL | /공부/2월 공부/백준_색종이.py | UTF-8 | 325 | 3.09375 | 3 | [] | no_license | T = int(input())
arr = [[0]*101 for _ in range(101)]
cnt = 0
for tc in range(T):
left, bot = map(int, input().split())
for i in range(left, left+10):
for j in range(bot, bot+10):
arr[i][j] = 1
for i in range(101):
for j in range(101):
if arr[i][j] == 1:
cnt +=1
print... | true |
7c9f88df5c21ee3cac58445ae75d1ae9f9eca5d3 | Python | DgFutureLab/satoyama-api | /app/tests/test_api_response.py | UTF-8 | 2,533 | 2.875 | 3 | [
"MIT"
] | permissive | from app.resources import ApiResponse
from satoyama.models import *
import unittest
from datetime import datetime
import json
from seeds.nodes import NodeSeeder
class Badboy(object):
def __init__(self, msg = "I'm a bad object."):
self.message = msg
def json(self):
"""
This badboy deliberately returns somethi... | true |
595b928039a0296a185988908d454f119fe5063e | Python | RoboticImaging/LearnLFOdo_IROS2021 | /multiwarp_dataloader.py | UTF-8 | 38,870 | 2.5625 | 3 | [] | no_license | import torch.utils.data as data
import numpy as np
import random
import torch
import os
from epimodule import load_multiplane_focalstack
from epimodule import load_tiled_epi_vertical, load_tiled_epi_horizontal, load_tiled_epi_full
from epimodule import load_stacked_epi, load_stacked_epi_no_repeats
from epimodule impor... | true |
7825d80b911b8ae23aedaf5ed369e7b0322ae7a2 | Python | s-light/pocketbeagle_python_tests | /cp_blinka/APDS9960.py | UTF-8 | 1,241 | 2.84375 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
simple test for adafruit-circuitpython-apds9960.
based on
https://learn.adafruit.com/adafruit-apds9960-breakout/circuitpython
"""
import time
import board
import busio
import adafruit_apds9960.apds9960
print("apds9960 i2c tests")
print("setup i2c")
i2c ... | true |
c5bef9b92241c51f512bcbedafa4289f3f1619e9 | Python | Yuandi888/algorithm014-algorithm014 | /Week_03/105_Construct_Binary_Tree_from_Preorder_and_Inorder_Traversal.py | UTF-8 | 1,163 | 4.125 | 4 | [] | no_license | # 105. Construct Binary Tree from Preorder and Inorder Traversal
# 105. 从前序与中序遍历序列构造二叉树
'''
https://leetcode-cn.com/problems/construct-binary-tree-from-preorder-and-inorder-traversal/solution/xiong-mao-shua-ti-python3-xian-xu-zhao-gen-hua-fen/
通过先序遍历我们可以找到root，知道inorder中，当前root的左侧的所有点就是其左子树，root的右侧的所有点就是当前root的右子树，再递归对... | true |
e7e4038017b6f6fdea335244095100e390d4b1c7 | Python | cwcurtis/SDSU-REU-PROJECT | /my_fft.py | UTF-8 | 802 | 2.796875 | 3 | [] | no_license | import pyfftw
class my_fft():
def __init__(self,KT):
physv = pyfftw.empty_aligned(KT, dtype = 'complex128')
freqv = pyfftw.empty_aligned(KT, dtype = 'complex128')
fft_f = pyfftw.FFTW(physv, freqv)
fft_in = pyfftw.FFTW(freqv, physv, direction='FFTW_BACKWARD')
self.physv = ... | true |
38d99d8312ae1c836de455fd60c0a2cde7c68f68 | Python | mathiver/scikit-learn | /examples/document_clustering.py | UTF-8 | 3,152 | 3.109375 | 3 | [
"BSD-3-Clause"
] | permissive | """
=======================================
Clustering text documents using k-means
=======================================
This is an example showing how the scikit-learn can be used to cluster
documents by topics using a bag-of-words approach. This example uses
a scipy.sparse matrix to store the features instead of ... | true |
b8d834bf3f364c08f535721a9c65e02c9db45981 | Python | zedko/NT | /bank_app/tests/test_account.py | UTF-8 | 1,816 | 3.0625 | 3 | [] | no_license | import unittest
from moneyed import Money
from bank_app import Account
from bank_app import BalanceException
from bank_app import Operation
from bank_app import settings
class TestAccount(unittest.TestCase):
def setUp(self) -> None:
self.acc = Account('Joe')
self.operations = [
Opera... | true |
349d9e89c2ac9017fca6e7f1cfd648ce1ed888a0 | Python | pico4girls/pico_native | /msg_app.py | UTF-8 | 1,966 | 2.53125 | 3 | [] | no_license | from appJar import gui
import requests
#from utils import test_action, rfid_thread
# create the GUI & set a title
app = gui("pico_native")
def songChanged(rb):
print(app.getRadioButton(rb))
import serial
'''
ser = serial.Serial('/dev/cu.usbserial-A6026SIM', 9600)
BAUD_RATE = 9600
RFID_BYTES = 12
START_CHAR = '\... | true |
2368182d6ade98e0539cdcc877f1d5c33b750748 | Python | Kuluso97/Emory_cs534_hw2 | /q5_script.py | UTF-8 | 821 | 3.03125 | 3 | [] | no_license | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.ensemble import GradientBoostingClassifier
## Load Data
df = pd.read_csv('hw2_data_2.txt', sep='\t')
X_train, y_train = np.array(df.iloc[:700, :-1]), np.array(df.iloc[:700, -1])
X_test, y_test = np.array(df.iloc[700:, :-1]), np.array(... | true |
2732a3b2d11ce122819a003f1ab83035ec7aa178 | Python | mHacks2021/pythonbook | /实例学习Numpy与Matplotlib/Nump 矩阵聚合.py | UTF-8 | 629 | 3.265625 | 3 | [
"LicenseRef-scancode-mulanpsl-1.0-en",
"MulanPSL-1.0",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | import numpy as np
a1 = np.array([i for i in range(1,5)])
a2 = a1.reshape((2,2))
print(f"a1 = {a1} "
f"a2 = {a2} "
)
print(f"np.sum(a2) = {np.sum(a2)}\n"
f"np.sum(a2,axis = 0) = {np.sum(a2,axis = 0)}\n"
f"np.std(a2) = {np.std(a2)}\n"
f"np.mean(a2) = {np.mean(a2)}\n"
f"np.var(a2) = {np.var(a2)}\n"
f"n... | true |
3d80dae16736cf371b6b54b6ae2ec2877006a0e0 | Python | curiosity29/MyGts | /Python/Python/PTVP/R-K.py | UTF-8 | 4,683 | 3.171875 | 3 | [] | no_license | from sympy import *
from math import *
import sys
class rungekutta_oop:
#{
def __init__(self, expr, x_0, y_0, h, n, s):
#{
x = symbols("x")
y = symbols("y")
func = sympify(expr)
self.y_0 = y_0 # Giá trị ban đầu của x
self.x_0 = x_... | true |
df0345dd804000b3a625ee977d4739d3b3d4c56a | Python | matthewjblatz/Portfolio | /Assignments/Security - A2 - Math + Python Scripts/AccurateButSlow.py | UTF-8 | 378 | 3.0625 | 3 | [] | no_license | import math
import time
found=0;
num=15000088;
count=899999;
start_time=time.time();
while (found==0):
for i in range(2,num):
if count%i==0:
break;
else:
if(count==990000):
print "The 990000th Prime:",num;
found=1;
count=count+1;
num=num+2;
... | true |
bea315e4a6f16f4ef242e9fce1a37c9e48fcad9a | Python | DuongHoangThuy/Python_iris | /irisnew.py | UTF-8 | 6,713 | 2.671875 | 3 | [] | no_license | import cv2,os
import cv2.cv as cv
import numpy as np
path = "image"
path0 = path+"/iris"
path1 = path0+"/test"
path2 = path0+"/test_iris_pupil"
path3 = path0+"/iris_pupil"
path4 = path0+"/normalization_Xp"
path41 = path0+"/normalization_p"
path5 = path0+"/LBP_Xp"
path51 = path0+"/LBP_p"
path6 = path0+"/iris_pupil_c"
f... | true |
a592fa7dcdd25665b5c549027bfacd4db2b0c4ba | Python | YoussefBoubekri/Python_Selenium | /PageObjects/GooglePage.py | UTF-8 | 726 | 2.765625 | 3 | [] | no_license | from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from BasePageObject.Base_Page_Object import Page
class GooglePage(Page):
#Elements
url = "" # base url + /page.php... for any additional url request....
search_button = (By.CSS_SELECTO... | true |
799cc94211b6ee0f09b8390a1b6679f5164b3a6a | Python | desktopgame/python-study | /httpTest2/app/main.py | UTF-8 | 419 | 2.84375 | 3 | [] | no_license | import requests
import time
import json
# Unityで起動したサーバから座標データをJsonとして送ってもらう
url = 'http://localhost:8080/'
msg = ''
while True:
response = requests.get(url)
msg = response.text.strip()
try:
data = json.loads(msg)
print('x=%f y=%f z=%f' % (data["x"], data["y"], data["z"]))
time.slee... | true |
07172d0285978bfd2d2efa6155153044c22cedee | Python | wabradshaw/aOrAn | /aOrAnScript.py | UTF-8 | 1,732 | 3.40625 | 3 | [
"Apache-2.0"
] | permissive | # This is a quick and dirty script that uses a corpus to decide whether or
# not a pattern is most often used with 'a' or 'an'. The result is a file
# containg the list of patterns that use 'an'.
#
# The script requires two source files, one containing 'an' data and one
# containing 'a' data. Testing was done usin... | true |
feeb0a1e75343b2207d9aaabb3d8eb95f9a0927f | Python | xyuae/yelp-data-challenge | /loadTable/jsonToCsv_business_hours.py | UTF-8 | 487 | 2.84375 | 3 | [] | no_license | import csv
import json
with open('user_business_hours.csv', 'wb+') as fout:
csv_file = csv.writer(fout)
csv_file.writerow(['business_id', 'hours'])
count = 0
with open('yelp_academic_dataset_business.json') as fin:
for line in fin:
line_contents = json.loads(line)
business_id = line_contents['business_id']... | true |
30f92f9b250f2864a6f48f725c0595f91173b2fe | Python | scurry222/holbertonschool-higher_level_programming | /0x07-python-test_driven_development/2-matrix_divided.py | UTF-8 | 1,157 | 3.3125 | 3 | [] | no_license | #!/usr/bin/python3
"""
This function containts matrix_divided
"""
def matrix_divided(matrix, div):
"""
Args:
matrix: to divide
div: divisor
"""
new_matrix = []
j = 0
if type(matrix) is not list or len(matrix) < 2:
raise TypeError("matrix must be a matrix (list of lists)"... | true |