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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
45576ef9da9da86d57d05b3f6633784b1017820e | Python | transientskp/tkp | /tkp/utility/coordinates.py | UTF-8 | 20,422 | 2.90625 | 3 | [
"BSD-2-Clause"
] | permissive | #
# LOFAR Transients Key Project
"""
General purpose astronomical coordinate handling routines.
"""
import datetime
import logging
import math
import sys
import pytz
from astropy import wcs as pywcs
from casacore.measures import measures
from casacore.quanta import quantity
logger = logging.getLogger(__name__)
# No... | true |
046719c95e3e1759e4b24efef4c0aca062e3cd10 | Python | hritik1330/GUVI | /hunter/set-10/94.py | UTF-8 | 96 | 3.234375 | 3 | [] | no_license | ss = list(input().split())
for i in range(len(ss)):
ss[i] = ss[i][::-1]
print(" ".join(ss))
| true |
b92c6c6e33d995fd87273751314705a721ce1cb2 | Python | andrewlarimer/location-buzz | /app/location_analyzer.py | UTF-8 | 15,603 | 2.578125 | 3 | [] | no_license | #!/usr/bin/env python
# coding: utf-8
import googlemaps
import re
from sklearn.cluster import KMeans
from bert_serving.client import BertClient
import requests
import json
from collections import defaultdict, Counter
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import numpy as np
import pandas ... | true |
42b15b419190f9a04b6571029058f973040a9075 | Python | Castor87/pacman | /teste_fontes.py | UTF-8 | 967 | 3.0625 | 3 | [] | no_license | import pygame
BRANCO = (255, 255, 255)
PRETO = (0, 0, 0)
AMARELO = (255, 255, 0)
VERMELHO = (255, 0, 0)
VERDE = (0, 255, 0)
pygame.init()
tela = pygame.display.set_mode((800, 600), 0)
score = 0
fonte = pygame.font.SysFont("calibri", 24, bold=True, italic=False)
while True:
texto = "Score: {}".format(score)
... | true |
0c73c27ba0d59606669b1bfb6dacd863b5ad3bd6 | Python | daclink/Final_Project_IST338 | /logger.py | UTF-8 | 4,350 | 3.0625 | 3 | [] | no_license | ###
# Drew A. Clinkenbeard
# Error Reporter and Logger
# 29 - April - 2014
# Since I broke this apart into multiple classes
# I needed a more flexible logging system.
###
from time import localtime, strftime
class Logger():
def __init__(self, fileName="admm.log"):
"""
I like using tail -F to have a running log... | true |
a3a0d613e0bcddc228850c5b9fb383db8f447b87 | Python | ArseniyCool/Python-YandexLyceum2019-2021 | /Основы программирования Python/5. Debugger/Псевдоним-пасьянс.py | UTF-8 | 845 | 3.828125 | 4 | [] | no_license | # По игре Ним-пасьянс с ограничением:
# можно за один ход взять не больше трёх камней.
# Игрок может попытаться взять больше трёх камней, меньше одного или больше оставшегося количества,
# но в этих случаях его ход игнорируется, и программа ещё раз выводит не изменившееся количество камней.
a = int(input('Введит... | true |
d2d938c136741471f678a2701d513aec58d28ab1 | Python | kajaltingare/Python | /Dictionary/cntWordsIntoDict.py | UTF-8 | 546 | 4.0625 | 4 | [] | no_license | # Write a program to accept a paragraph from user & return a dictionary of count of words in it.
def cntWordsIntoDict(ipString):
opDict={}
for ch in ipString.split():
if(opDict.get(ch)!=None):
opDict[ch]+=1
else:
opDict[ch]=1
return opDict
def main():
... | true |
ce24cdf44ebdcfdfe20b72948a311c65993d4dd1 | Python | harry123180/opencv_find_objects | /GMTCV/ik.py | UTF-8 | 494 | 3.0625 | 3 | [] | no_license | import math
l1 = 4
l2 = 3
pi = 3.14159
x =-4
y = 0
theta = 90
Kdeg = 180/pi
def ik(x,y,theta):
v2 = (pow(x,2)+pow(y,2)-pow(l1,2)-pow(l2,2))/(2*l1*l2)
d2 = math.acos(v2)
k1 = l1+l2*math.cos(d2)
k2 = l2*math.sin(d2)
d1 = math.atan2(y,x)-math.atan2(k2,k1)
fai = theta*pi/180
d3 = (fai-d2-d1)
... | true |
3ae208a9021a62a1030e67b690c5c7dd8b780803 | Python | JINO-ROHIT/IPL-Score-Prediction | /src/train.py | UTF-8 | 2,271 | 2.53125 | 3 | [] | no_license | from ast import parse
import joblib
import os
import argparse
import config
import model_dispatcher
import pandas as pd
import numpy as np
from sklearn import metrics
from sklearn import ensemble
from sklearn.preprocessing import LabelEncoder
from sklearn.metrics import mean_squared_error
df = pd.read_csv(config.TRAIN... | true |
442ce3c013f419ded55bd05c2a017d9e2088fa1a | Python | Manovah/guvi | /code kata/min_to_hrs.py | UTF-8 | 76 | 3.21875 | 3 | [] | no_license | q=int(input())
if(q<59):
print(0,q)
else:
d=q//60
b=q%60
print(d,b)
| true |
7e9ced26af38c3c8e4e10722826244b7d080d330 | Python | QuentinCG/Base-Scripts | /OS_Independent/utils/fb_messenger_send.py | UTF-8 | 4,402 | 2.71875 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Utility functions to send message/image with Facebook messenger (can also be called with shell)
"""
__author__ = 'Quentin Comte-Gaz'
__email__ = "quentin@comte-gaz.com"
__license__ = "MIT License"
__copyright__ = "Copyright Quentin Comte-Gaz (2017)"
__python_version_... | true |
67279ec82cf6e2f8b472727cd58f0068a7e852c0 | Python | lancelafontaine/caproomster | /app/core/equipment_test.py | UTF-8 | 499 | 2.625 | 3 | [] | no_license | from app.core.equipment import Equipment
def test_equipment_with_no_arguments_is_zero_length():
equipment = Equipment("equipmentID_uybino")
assert 0 == len(equipment)
def test_equipment_getting_number_of_equipment_needed():
equipment7 = Equipment("equipmentID_ibiubi",laptops=2,projectors=1,whiteboards=4)
assert 7... | true |
f5842ab82da63d07d20db85f63ce4c43747fbe09 | Python | ShreeyaVK/Python_scripts | /change_delimiter.py | UTF-8 | 735 | 2.765625 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 23 19:03:55 2017
@author: Sadhna Kathuria
"""
import pandas as pd
#change the delimter of a dataset
path = 'C:/Users/Sadhna Kathuria/Documents/Shreeya_Programming/Predictive/Chapter 2'
#filename1 = 'titanic3.csv'
filename2 = 'Customer Churn Model.txt'
filename_tab = 'Ta... | true |
409e5a90dad58ad4566b493c3838ad081272a27f | Python | uchicago-cs/icpc-tools | /scoreboard-publish/scoreboard-publish.py | UTF-8 | 15,397 | 2.5625 | 3 | [] | no_license | #!/usr/bin/python
# PC^2 scoreboard publishing script
#
# See README for instructions
#
# (c) 2014, Borja Sotomayor
from argparse import ArgumentParser, FileType
from pprint import pprint as pp
from datetime import datetime
import os
import os.path
import stat
import subprocess
import socket
import time
import re
imp... | true |
ff747d97e8ac35c4b6d43513f01ceec88cbc8ced | Python | hpcloud-mon/monasca_query_language | /mql/influx_repo.py | UTF-8 | 3,897 | 2.515625 | 3 | [
"Apache-2.0"
] | permissive | import datetime
import sys
import numpy
from influxdb import client
import mql_parser
influxdb_client = client.InfluxDBClient(
"192.168.10.6", "8086",
"", "",
"mon")
functions_for_repo = {
'avg': 'mean',
'max': 'max',
'min': 'min',
'count': 'count',
'sum': 'sum',
'rate': 'deriv... | true |
3baf987cd1be64f1e8b5485141022e396003ea1c | Python | PTITLab/Multitask-Breath-Sound | /Breath-Code/dataset.py | UTF-8 | 3,505 | 2.890625 | 3 | [] | no_license | import numpy as np
import keras
from scipy.io import wavfile
import librosa
import os
from keras.utils import to_categorical
class BreathDataGenerator(keras.utils.Sequence):
'Generates data for Keras'
def __init__(self, directory,
list_labels=['normal', 'deep', 'strong'],
... | true |
bee776a208bb4cfb0466fbbba5149af9bebd37a6 | Python | dorx/codesnippetsearch | /code_search/vocabulary.py | UTF-8 | 1,539 | 3.09375 | 3 | [
"MIT"
] | permissive | from typing import List, Dict, Counter as TypingCounter, Optional, Iterator
from collections import Counter
MASK_TOKEN = '%MASK%'
UNKNOWN_TOKEN = '%UNK%'
class Vocabulary:
def __init__(self):
self.token_to_id: Dict[str, int] = {MASK_TOKEN: 0, UNKNOWN_TOKEN: 1}
self.id_to_token: List[str] = [MASK_... | true |
8b55d761ffb598b3a0cd40930860efca84d7e917 | Python | dr-dos-ok/Code_Jam_Webscraper | /solutions_python/Problem_200/3538.py | UTF-8 | 1,434 | 2.859375 | 3 | [] | no_license | #f = open('C:/Users/Avinash/Desktop/Google codejam 2017/pycharmworks/input2', 'r')
# C:\Users\Avinash\Desktop\Google codejam 2017\pycharmworks\AA-small-practice.in
# f = open('C:/Users/Avinash/Desktop/Google codejam 2017/pycharmworks/A-large-practice.in', 'r')
f = open('C:/Users/Avinash/Desktop/Google codejam 2017/p... | true |
10fc9b2d7e508e3e467f4375f6b478f345decde7 | Python | gagejustins/snql | /snql/app/data_scripts/data_api.py | UTF-8 | 1,103 | 2.515625 | 3 | [] | no_license | import pandas as pd
def generate_pairs_owned_over_time_df(conn):
sql="""select
c.month,
count(*) as pairs_owned
from calendar_monthly c
join dim_sneakers s on s.created_at <= c.month
and (sold_at >= c.month or sold_at is null)
and (trashed_at >= c.month or trashed_at is null)
and (given_at >= c.month or give... | true |
1239fe53f1e1b6f81fa4bbf5e2cb2fcbd8cb2c4a | Python | nextwiggin4/TimeRisk | /dice_test.py | UTF-8 | 219 | 3.515625 | 4 | [] | no_license | from dice import *
d1 = Dice()
while True:
turn = input("please select a trun to check: ")
if turn == 'n':
print(d1.next_roll())
else:
print(d1.roll_for_turn(int(turn)))
print(d1.number_of_rols())
| true |
7eeddaa8459d741a5792749effdd1090ef781f3c | Python | linxigal/tfos | /tfos/tf/models/mlp.py | UTF-8 | 2,240 | 2.859375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
:Author : weijinlong
:Time :
:File :
"""
import tensorflow as tf
from tfos.tf import TFModel, TFCompile
class MLPModel(TFModel):
def __init__(self, input_dim=784, hidden_units=300, keep_prob=0.8):
"""
:param input_dim: 输入节点数
:param hidden_units: 隐含层节... | true |
074d56aa9fe8379f522d8d129cefc81cb4a2a805 | Python | michalporeba/cooking-with-python | /steps/step01/recipes.py | UTF-8 | 1,271 | 4.15625 | 4 | [
"MIT"
] | permissive | # the data - for now hardcoded three recipes
recipes = [
{ "name": "lemon cake", "description": "a cake with a lemon"},
{ "name": "brownies", "description": "a simple cake with chocolate"},
{ "name": "cookie"} # there is no description, so we can test this behaviour
]
def display_recipes():
print("Avai... | true |
a7fbce000908fdfbc6bf8dc9a80780b5668698a7 | Python | pps789/introduction-to-deep-learning-2018 | /hw1/q3-3.py | UTF-8 | 775 | 3.125 | 3 | [] | no_license | import numpy as np
import matplotlib
import math
matplotlib.use('Agg')
import matplotlib.pyplot as plt
def inv_F(y):
return -math.log(1-y)
def F(x):
return 1-math.exp(-x)
N = 1000000
# samples!
data = np.random.uniform(0,1,N)
samples = list(map(inv_F, data))
H_sample, X_sample = np.histogram(samples, bins ... | true |
33c165db6d4daeba6c1340cabb6f84dfaed52d06 | Python | remy-algo-dim/AD_serveur | /src/google_filters_to_good_format.py | UTF-8 | 590 | 2.78125 | 3 | [] | no_license | import pandas as pd
"""
Ce fichier a pour but de transformer le format des filtres que l'on telecharge depuis le drive (format CSV),
en bon format pour notre algo. On renseignera donc en input :
- CSV = path du csv telecharge depuis DRIVE
- NON_CLIENT = il s'agit du nom du client figurant dans la premiere colonne du ... | true |
215ace42f4865281b3df20b96fe77ba398df9aaa | Python | Wolvarun9295/PythonLibraries | /Seaborn/Swarm Plot/1.PlotOfBillvsSize.py | UTF-8 | 149 | 2.625 | 3 | [] | no_license | import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
sns.swarmplot(x='total_bill', y='size', data=tips)
plt.show()
| true |
bbe0302aa3aa7622696d2a36d0bd619a94c26357 | Python | LucasOJacintho/DESENVOLVIMENTO-PYTHON | /DESENVOLVIMENTO PYTHON/1014 - Consumo.py | UTF-8 | 101 | 3.0625 | 3 | [] | no_license | distancia=int(input(''))
combustivel=float(input(''))
print ("%.3f" % (distancia/combustivel),'km/l') | true |
f09f7c467bdbfb83b79b41af2003d76057d9d0a3 | Python | HAOYU-LI/Web_Search_Application | /src/Inverted_ID.py | UTF-8 | 3,213 | 2.921875 | 3 | [] | no_license | import os
import re
import sys
import json
class Inverted_ID:
"""
A class that constructs the inverted index for cvpr metadata.
input:
dic : A dictionary that stores the cvpr research papers. e.g.
{'cvpr':
[{'subject': '2013 IEEE Conference on Computer V... | true |
b89e0be3bb1597a95716fe5f194fef0a94df6255 | Python | ewhuang/pacer | /ensg_to_hgnc_conversion.py | UTF-8 | 3,552 | 2.734375 | 3 | [] | no_license | ### Author: Edward Huang
from collections import OrderedDict
import numpy as np
### This script converts the new auc file for drug response in patients to the
### old format that the Mayo data used. Also converts the gene expression table
### to the old format. Lastly, converts the LINCS level 4 data to the old
### f... | true |
b432a9723adf994533ed1bba53f318b62834a3d2 | Python | bobovnii/Stau | /NTupleMaker/test/DatacardProducer/ratioPlotSyst.py | UTF-8 | 5,023 | 2.640625 | 3 | [] | no_license | ######################################################################################
# Script to plot the central, up and down distributions #
# for each MC process and syst uncertainty. #
# The lower pad plots the ratios. #
# It is meant to run on ROOT files produced by the datacardP... | true |
30bbf1c6f184ee2a9a99d92529d37ff0c24a6686 | Python | primus2019/mini-project | /utils/Plots.py | UTF-8 | 2,097 | 2.59375 | 3 | [] | no_license | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from .EDA import feature_VIF
def correlationPlot(ds, features, savefig, title=None):
features = ds.columns.values.tolist() if features == 'all' else features
corr = ds.loc[:, features].corr()
mask = np.zeros_lik... | true |
752bd5e6cc99f72c6814537c118c9ff58134757a | Python | lucaschen321/leetcode | /python/p0424-longest-repeating-character-replacement/p0424-longest-repeating-character-replacement.py | UTF-8 | 1,078 | 3.640625 | 4 | [
"MIT"
] | permissive | from collections import defaultdict
class Solution:
def characterReplacement(self, s: str, k: int) -> int:
if not s:
return 0
character_frequency = defaultdict(int)
character_frequency[s[0]] += 1 # Include 1st character so character_frequency.values() isn't empty
left... | true |
38d76130202cfd90e8de51c59a628bc9acb4b92c | Python | Dhanush33324/Python_Pytest_Demo | /Scenario 1.py | UTF-8 | 2,000 | 2.5625 | 3 | [] | no_license | from selenium import webdriver
from selenium.webdriver.support import expected_conditions
from selenium.webdriver.support.select import Select
from selenium.webdriver.support.wait import WebDriverWait
driver = webdriver.Chrome("./chromedriver")
driver.get("https://rahulshettyacademy.com/seleniumPractise/#/")
search_it... | true |
a41fca7d8eee1fb49cafbeca0b1b1265dd30914a | Python | Artem-Efremov/CodeWars | /Strings/6kyu_Scooby Doo Puzzle.py | UTF-8 | 4,256 | 3.765625 | 4 | [] | no_license | """
Introduction
Good one Shaggy! We all love to watch Scooby Doo, Shaggy Rogers, Fred Jones, Daphne Blake and Velma Dinkley solve the clues and figure out who was the villain. The story plot rarely differed from one episode to the next. Scooby and his team followed the clue then unmasked the villain at the end.
Sc... | true |
5aff677bbf36e68ff625f16c37ccef5c7c643cf3 | Python | DanielJBurbridge/Jetbrains-Academy | /Hyperskill/Python/Medium/Webscraper/Webscraper/1.0/scraper.py | UTF-8 | 293 | 3.09375 | 3 | [] | no_license | import requests
url = input("Input the URL:\n")
r = requests.get(url)
if r.status_code == 200:
r_json = (r.json())
if 'content' in r_json:
print(r_json.get('content'))
else:
print("Invalid quote resource!")
else:
print("Invalid quote resource!")
| true |
50b1e5e598ec042cd656526f3dcf585ae6e68a38 | Python | akiraboy/python_20191010 | /collections_tbier/zad_7.py | UTF-8 | 238 | 3.921875 | 4 | [] | no_license | napis = input("POdaj ciag znaków: ")
samogloski = ['a', 'e', 'i', 'o', 'u', 'y']
ile_samoglosek = 0
for znak in napis:
if znak in samogloski:
ile_samoglosek += 1
print(f"Znaleziono samoglosek: {ile_samoglosek}") | true |
30be00a608cfe4674ffbba5469ad8e9a554c0f06 | Python | git-metal/python-learn | /python-lib/Concurrent/test_threading.py | UTF-8 | 1,450 | 3.359375 | 3 | [] | no_license |
import threading
from time import ctime, sleep
class MyThread(threading.Thread):
def __init__(self, func, args, name=""):
# threading.Thread.__init__(self)
super(MyThread, self).__init__()
self.name = name
self.func = func
self.args = args
def run(self)... | true |
ce6a2a0741353d427a4dc4bead7f9dffa514191f | Python | lukaszmitka/beacon_detector | /scanner.py | UTF-8 | 2,472 | 2.6875 | 3 | [] | no_license | from bluepy.btle import Scanner, DefaultDelegate
import sqlite3
import datetime
class ScanDelegate(DefaultDelegate):
def __init__(self):
DefaultDelegate.__init__(self)
def handleDiscovery(self, dev, isNewDev, isNewData):
if isNewDev:
print "Discovered device", dev.addr
elif... | true |
b4155ca142b910a4062222acc6a9b0557edc9d7c | Python | ibiehler/isabelleb | /Labs/School Greenhouse Gas Emissions/ghg_lab.py | UTF-8 | 4,281 | 3.796875 | 4 | [] | no_license |
'''
Greenhouse gas emissions (GHG) vs. square footage for all school buildings in Chicago
Data set used will be Chicago Energy Benchmark info from 2018
data can be found at...
https://data.cityofchicago.org/api/views/xq83-jr8c/rows.csv?accessType=DOWNLOAD
Energy Efficiency of Chicago Schools (35pts)
Chicago require... | true |
6dbe60c72d7495e4fedc5daa877f280a2b02b25e | Python | sWizad/diffeqsolver | /main5.py | UTF-8 | 8,668 | 3.0625 | 3 | [] | no_license | """ NN to solve 1st order ODE problems
based on Rosenbrock Euler method
"""
# Import the required modules
from __future__ import division
import numpy as np
import os, sys
import matplotlib.pyplot as plt
import tensorflow as tf
from utils import colored_hook
# tf.enable_eager_execution()
# This makes the plots ap... | true |
9dc55b66267bf64baac83be1e6d6f798c9d96468 | Python | redixhumayun/ctci | /HackerRank/projectEuler.py | UTF-8 | 1,448 | 3.421875 | 3 | [] | no_license | import unittest
import pdb
from fractions import Fraction
def findSumOfProducts(number):
result = 0
for num in range(5, number + 1):
pdb.set_trace()
result += findMaxProduct(num)
return result
def findMaxProduct(n):
max_value = 0
for divisor in range(1, n):
product = Fracti... | true |
551d351319962976d1c5729157cc9c054385d368 | Python | Ro9ueAdmin/django-orchestra | /orchestra/permissions/options.py | UTF-8 | 3,550 | 3.0625 | 3 | [
"BSD-3-Clause"
] | permissive | import functools
import inspect
# WARNING: *MAGIC MODULE*
# This is not a safe place, lot of magic is happening here
class Permission(object):
"""
Base class used for defining class and instance permissions.
Enabling an ''intuitive'' interface for checking permissions:
# Define permiss... | true |
42a2887dc16e67b1f43de510a505912a05a87061 | Python | Debdut24/Pong | /puddle.py | UTF-8 | 478 | 3.734375 | 4 | [] | no_license | from turtle import Turtle
class Puddle(Turtle):
def __init__(self, x, y):
super().__init__()
self.x = x
self.y = y
self.color("white")
self.shape("square")
self.penup()
self.shapesize(stretch_wid=5, stretch_len=1)
self.goto(x, y)
def move_up(self... | true |
782c4d867fe81a436f2dd6c061ee2bbd7f5f8eba | Python | purnima64/DS_Titanic | /basic_fun.py | UTF-8 | 2,280 | 3.6875 | 4 | [] | no_license | import numpy as np
import pandas as pd
def basic_df_exploration(df):
"""
Provides basic data exploration details
Params:
-------
df: pandas dataframe
Returns:
--------
None
Prints the following output:
- Shape
- Column name and respective types
- Descriptive stats
- ... | true |
64769cc0532a2e48c4e607781a4cc342dbcf5d74 | Python | LCDG-tim/2020-exos | /arbres3.py | UTF-8 | 2,185 | 3.421875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Tue Nov 24 15:37:37 2020
@author: timot
"""
class ABR:
def __init__(self,val):
self.valeur=val
self.gauche=None
self.droite=None
def inserer(self,x):
if x<self.valeur:
if self.gauche!=None:# si il y a un noeud à gauche
... | true |
ccbdfe9e20b716053ce7e286dc1b4f060a9b40a4 | Python | aspcodenet/IotListLabbar | /IotListLabbar/Lab1.py | UTF-8 | 199 | 3.59375 | 4 | [] | no_license |
lista = []
for i in range(0,4):
lista.append(int(input(f"Mata in tal {i+1}:")))
largestSoFar = lista[0]
for i in lista:
if i > largestSoFar:
largestSoFar = i
print(largestSoFar)
| true |
3e3c620aa3287ba9266d0eb61a0d92a45c0e7e5a | Python | runzezhang/Code-NoteBook | /lintcode/1243-number-of-segments-in-a-string.py | UTF-8 | 1,475 | 3.828125 | 4 | [
"Apache-2.0"
] | permissive | Description
中文
English
Count the number of segments in a string, where a segment is defined to be a contiguous sequence of non-space characters.
the string does not contain any non-printable characters.
Have you met this question in a real interview?
Example
Example:
Input: "Hello, my name is John"
Output: 5
Expla... | true |
37e9c844ce04a3c8f7af90584a1609da00787292 | Python | kdungs/adventofcode | /2021/05.py | UTF-8 | 1,434 | 3.78125 | 4 | [] | no_license | #!/usr/bin/env python3
from collections import defaultdict
with open("data/05.txt") as f:
lines = f.readlines()
points = defaultdict(int)
for line in lines:
left, right = line.split(" -> ")
x1, y1 = map(int, left.split(","))
x2, y2 = map(int, right.split(","))
if x1 != x2 and y1 != y2:
#... | true |
ceb98003f824c3a85ed547bbbc63f7a47354fdde | Python | javierwilson/commcare-hq | /corehq/blobs/tests/util.py | UTF-8 | 940 | 2.609375 | 3 | [] | no_license | from shutil import rmtree
from tempfile import mkdtemp
import corehq.blobs as blobs
from corehq.blobs.fsdb import FilesystemBlobDB
class TemporaryFilesystemBlobDB(FilesystemBlobDB):
"""Create temporary blob db and install as global blob db
Global blob DB can be retrieved with `corehq.blobs.get_blob_db()`
... | true |
03c879bb46dee0e3eba046547eae73819ecf1ae1 | Python | ChidinmaKO/Chobe-Py-Challenges | /bites/bite155.py | UTF-8 | 1,397 | 3.828125 | 4 | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | import re
import shlex
def split_words_and_quoted_text(text):
"""Split string text by space unless it is
wrapped inside double quotes, returning a list
of the elements.
For example
if text =
'Should give "3 elements only"'
the resulting list would be:
['Should', '... | true |
83339f9e2e2f9ab76f41bd75814dd4b58b599d38 | Python | fernandochimi/python-data-analysis | /python_data_analysis/chapter_03/03-linear-algebra.py | UTF-8 | 221 | 3.078125 | 3 | [] | no_license | # coding: utf-8
import numpy as np
A = np.mat("2 4 6; 4 2 6; 10 -4 18")
print "A\n", A
inverse = np.linalg.inv(A)
print "Inverse of A\n", inverse
print "Check\n", A * inverse
print "Error\n", A * inverse - np.eye(3)
| true |
c0d48ae35700a9bf4baf94fa1e6b3f32030fbfc0 | Python | maxdatascience/tic-tac-toe | /tic-tac-toe.py | UTF-8 | 3,270 | 4.1875 | 4 | [] | no_license | import random
def display_board(board):
print('\n'*100)
print(f"| {board[7]} | {board[8]} | {board[9]} |")
print("-------------")
print(f"| {board[4]} | {board[5]} | {board[6]} |")
print("-------------")
print(f"| {board[1]} | {board[2]} | {board[3]} |")
def player_input():
""... | true |
091824f44461290479800b6f5b33923bcfead9d0 | Python | LibriCerule/Cerulean_Tracking | /db_unittest.py | UTF-8 | 1,461 | 2.59375 | 3 | [
"MIT"
] | permissive | from tracker_database import TrackerDatabase
test_uuid = "de305d54-75b4-431b-adb2-eb6b9e546014"
test_uuid2 = "de305d54-75b4-431b-adb2-eb6b9e546015"
def test_track_new_package():
test_name = "4401 Wilson Blvd #810, Arlington, VA 22203"
test_lat = 0
test_lon = 0
test_delivered = False
test_time = "2... | true |
ac9947fe8f632200c831439009a2610e6673dc1a | Python | ashutoshdhondkar/basic-python | /comprehension_exercise.py | UTF-8 | 498 | 4.3125 | 4 | [] | no_license | #Wap to check whether an input number is multiple of 5 and is greater than 17
'''
#without comprehension
ip=int(input("Enter a number : "))
if(ip%5==0) and (ip>17):
print("Satisfied")
else:
print("Not satisfied")
'''
# with comprehension
def check(num):
if(num%5==0 and num>17):
... | true |
ef9c01c7d62edf3c170a2bfb2f79545e9fac4a22 | Python | minbbaevw/multi.plus.py | /main.py | UTF-8 | 1,375 | 4.34375 | 4 | [] | no_license | # Дан массив целых чисел. Нужно найти сумму элементов с четными индексами (0-й, 2-й, 4-й итд), затем перемножить эту сумму и последний элемент исходного массива. Не забудьте, что первый элемент массива имеет индекс 0.
# Для пустого массива результат всегда 0 (ноль).
# Входные данные: Список (list) целых чисел (int).
... | true |
2b1a6f8ddbeb857738b34659c2da131f3c627ce1 | Python | subicWang/leetcode_aotang | /tools/binarytree.py | UTF-8 | 3,592 | 3.5 | 4 | [] | no_license | # -*- coding: utf-8 -*-
"""
Aouther: Subic
Time: 2019/8/28: 10:08
"""
from collections import Iterable
import networkx as nx
import matplotlib.pyplot as plt
class Node(object):
def __init__(self, value, left=None, right=None):
self.val = value
self.left = left
self.right = right
class Bin... | true |
fa95b14cee4d49c0e64817a0e6c43c222f6fc9fb | Python | andreas19/pygemina | /src/gemina/__main__.py | UTF-8 | 3,156 | 2.84375 | 3 | [
"BSD-3-Clause"
] | permissive | # flake8: noqa
"""Usage:
gemina encrypt -i INFILE -o OUTFILE [-V N] (-p | -k) [INPUT]
gemina decrypt -i INFILE -o OUTFILE (-p | -k) [INPUT]
gemina verify -i INFILE (-p | -k) [INPUT]
gemina create -o OUTFILE [-V N]
Commands:
encrypt encrypt a file
decrypt decrypt a file
verify verify a file
create... | true |
8ee17ccebc20de05c3e6e1b868ea89d7a4597738 | Python | dwtrain/Gitpractice | /calc.py | UTF-8 | 320 | 3.515625 | 4 | [] | no_license | def add(x,y):
return x+y
def sub(x,y):
return x-y
def mult(x,y):
return x*y
def divide(x,y):
if(y==0):
return NULL
else:
return x/y
def mod(x,n):
return x%n
print('these are math operations')
print(add(2,4))
print(sub(2,4))
print(mult(2,4))
print(divide(2,4))
print(mod(2,4))
| true |
108565a87cf38864a7ced4482f9753a2a9159475 | Python | 499244188/Python | /1datetime.py | UTF-8 | 1,448 | 3.625 | 4 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Wed Apr 13 14:06:18 2017
@author: Z
"""
from datetime import datetime
now = datetime.now()
print(now)
print(type(now))
#指定时间日期
dt = datetime(2017,5,4,23,1)
print(dt)
dt.timestamp()#把datatime转为timestamp
t = 3600*24*360*48-3600*24*11
print(datetime.fromtimestamp(t))
t = 14939... | true |
58b8f72c633407e708f248f6cc3d1fd931d7540c | Python | Dharian/pythonProject | /Ejercicios/Listas/Ejercicio 9 LIstas.py | UTF-8 | 404 | 3.796875 | 4 | [
"MIT"
] | permissive | def cargarLista():
lista=[]
for x in range(5):
lista.append(str(input("Ingresa tus cinco palabras favoritas")))
print(lista[x])
comprobarLongitud(lista)
def comprobarLongitud(lista):
for elemento in lista:
if len(elemento) > 5:
print(elemento)
else:
p... | true |
7b6c0519f2e32876ba7e16973eb7f88672eed47a | Python | sekunder/SWDB-KART | /pca/main.py | UTF-8 | 1,344 | 3.328125 | 3 | [] | no_license | from sklearn.preprocessing import StandardScaler
import numpy as np
def pca(X, ndims=3):
"""Runs PCA on provided data, X, and returns the projection onto ndims principal components.
This function assumes X has data series in columns.
This function also returns the covariance matrix of the data (scaled to zero norm a... | true |
45fdf75a9b30b797f1090d38a62c184c9e204a3d | Python | BartlomiejCiurus/PythonClasses | /Functions/4.2.py | UTF-8 | 841 | 3.65625 | 4 | [] | no_license | __author__ = 'Bartek'
def print_ruler(number):
ruler = ""
limiter = " "
counter = 0
border_value = 10
for i in range(1, number):
ruler += "|...."
ruler += "|\n"
for character in ruler:
if character == '|':
ruler += str(counter)
counter += 1
... | true |
b3ec75f76aa090dab2d5fd8237b9d7ffc6b981f9 | Python | gdurin/Python-in-the-lab | /problems/plot3D_withcolors.py | UTF-8 | 580 | 2.765625 | 3 | [
"CC-BY-3.0"
] | permissive | import numpy as np
import pandas as pd
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
data = pd.read_csv("output_point.csv", names=['x','y','z','R','G','B'])
c = [mcolors.to_hex([r/255,g/255... | true |
c690610208b79cb822ddbf41ce7fd9a407d8b00c | Python | haribogummi/test | /anotation1.py | UTF-8 | 907 | 2.578125 | 3 | [] | no_license | # coding: UTF-8
import re
import sys
import csv
def position():
dic1={}
dic2={}
f=open("snp_test.csv","rb")
datareader = csv.reader(f)
for row in datareader:
dic2={row[1]:row[2]}
dic1.update(dic2)
return dic1
f.close()
def search():
dic1=position()
c=0
print "Position,Nuc,n_p,Start,End,Type"
for k,... | true |
47a53542ffae6efd469c633154fe5af425a87af9 | Python | baez97/shonen | /Source Code/Estado.py | UTF-8 | 1,877 | 3.109375 | 3 | [] | no_license | import pygame
from pygame.locals import *
class Estado:
def pintar(self, personaje):
self.grafico.pintar(personaje)
def getImage(self):
return self.image
def isUp(self):
return False
def isDown(self):
return False
def isRight(self):
return False
def isL... | true |
8e5f4d6addb9f956efb0907c36dd4f69e8f12635 | Python | yellowrangler/vue | /systemscripts/putvue.py | UTF-8 | 811 | 2.96875 | 3 | [] | no_license | #!/usr/bin/env python
#!/usr/bin/env python3
import sys
import subprocess
import glob
# global variables
mysqlcommand = "mysql -u tarryc -p vue < "
file_list = []
cmd = "no file selected"
file_list = glob.glob('vue-*python.sql')
l = len(file_list)
i = 0
while (i < l):
name = file_list[i]
print name
answer = raw... | true |
5c89f0b24ef920a2fa5c9b2cbd372881868bbb1f | Python | yeasin50/Traffic-Sign-Classification | /traffic_sign_net.py | UTF-8 | 3,371 | 2.765625 | 3 | [] | no_license | #!/usr/bin/env python
# coding: utf-8
# # <center> TrafficSignNet
# Conv2D
# input: (None, 32, 32, 3)
# output: (None, 32, 32, 8)
#
# Activation
# input: (None, 32,32,8)
# output: (None, 32,32,8)
#
# BatchNormalization
# input: (None, 32, 32, 8)
# output: (None, 32, 32, 8)
#
# MaxP... | true |
098f3382a214dd08406eae9310623053599fd72a | Python | pheldox/Covid-19-Tweet-Classification | /app.py | UTF-8 | 2,293 | 3.0625 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 6 21:37:09 2020
@author: Ayush
"""
# covid 19 tweets
import streamlit as st
import pickle
import numpy as np
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
from nltk.stem import WordNetLemmatizer
from PIL import Image
import re... | true |
28803ddbabe66f9294d4cfb1e2780e5418ff49c4 | Python | kevjam/fake-news-classifier | /src/predict.py | UTF-8 | 2,428 | 2.625 | 3 | [] | no_license | from preprocess import filter_dataset
from utils.tokenizing import segment_zh_data, tokenize
from utils.storage import load_tokenizers
# -------------- General Packages --------------
# Data Manipulation
import pandas as pd
import numpy as np
# For Saving/Loading Files
import os
from keras.models import lo... | true |
08c7a5a38bf556feb2270064acae6082b1251ea3 | Python | junli-cs-fiu/spinner_public | /matrix.py | UTF-8 | 1,224 | 2.984375 | 3 | [] | no_license | import numpy as np
def Cauchy(m, n):
x = np.array(xrange(n + 1, n + m + 1))
y = np.array(xrange(1, n + 1))
x = x.reshape((-1, 1))
diff_matrix = x - y
cauchym = 1.0 / diff_matrix
return cauchym
def RS(n, k):
I = np.identity(k)
P = Cauchy(n - k, k)
return np.concatenate((I, P), axis... | true |
92197a7af9b0cd9ba5a036f49b23cae7b1b182d4 | Python | jobafash/InterviewPrep | /educative.io/patterns/bfs/easy4.py | UTF-8 | 2,272 | 4.65625 | 5 | [] | no_license | '''
Given a binary tree, populate an array to represent the averages of all of its levels.
Solution#
This problem follows the Binary Tree Level Order Traversal pattern. We can follow the same BFS approach. The only difference will be that instead of keeping track of all nodes of a level, we will only track the runnin... | true |
9b043b127f870220d33161f7b1a1cc229fd10b19 | Python | tcbrouwer/FourierMonitor | /HarmonicAI/main.py | UTF-8 | 384 | 2.9375 | 3 | [] | no_license | import random
import math
from FourierClerk import FourierClerk
clerk = FourierClerk(1000)
supervisor = FourierClerk(10)
print(clerk.get_coefficients_for_channel(0))
for i in range(0,2000):
clerk.note([math.sin(math.pi * i/10)])
#clerk.note([random.random()])
supervisor.note(clerk.get_coefficients_for_cha... | true |
8c88611626c37a22dc1ca4ca4d76db530a61d8fe | Python | ProximaB/Control-of-a-mobile-robot-with-extrinsic-feedback | /Find_Detect_base/qt6clock.py | UTF-8 | 1,077 | 2.71875 | 3 | [] | no_license | import cv2
def start_webcam(self):
if not self.cameraRuns:
self.capture = cv2.VideoCapture(cv2.CAP_DSHOW)
self.cameraRuns = not self.cameraRuns
self.timer = QTimer(self)
self.timer.timeout.connect(self.update_frame)
self.timer.start(2)
from PyQt5.QtCo... | true |
712bfa1d9fc2476c22fd135f2332df416e25bdf0 | Python | vparikh10/facial-expression-classifier | /fec/classifier/gl_data.py | UTF-8 | 2,096 | 2.625 | 3 | [] | no_license | import numpy as np
from boto.s3.connection import S3Connection
import os
from filechunkio import FileChunkIO
import math
import pandas as pd
_conn = None
def get_connection():
"""Get the boto connection to Amazon S3
This method assumes the environment variables AWS_ACCESS_KEY_ID and
AWS_SECRET_ACCESS_K... | true |
f8ab8524e8caae4e35e1a6360a1a74cc58c2d5a2 | Python | Lan2008-StudioPro/Python_Singular | /Homework/20210321/t2_climate.py | UTF-8 | 560 | 4.34375 | 4 | [] | no_license | #溫度問題
while True:
a=input('今天攝氏幾度？')
try:
a=int(a)
except:
print('蛤？我問你溫度你回答這什麼鬼東西？')
else:
if a>=40:
print('怎麼可能？這麼熱！')
elif a<=10:
print('天哪！太冷了吧～')
else:
print('真舒適的溫度！')
"""
Topic:輸入溫度，如果溫度>=40度C,顯示: 太熱,
如果溫度<= 10 顯示:太冷... | true |
b0e9b6eecb284ae06b2169c65d1d99aa90802b34 | Python | py2-10-2017/MatthewKim | /Fundamentals/DebuggingLearn.py | UTF-8 | 120 | 3.34375 | 3 | [] | no_license | def multiply(arr,num):
for x in arr:
arr[x] *= num
return x
a = [2,4,10,16]
b = multiply(a,5)
print b
| true |
8444472261faf517ddb82e348afe0690bd4c7b45 | Python | SHawkeye77/game_1 | /items_all/items_research_dome.py | UTF-8 | 6,261 | 3.171875 | 3 | [] | no_license | """
Holds items specifically made in the research dome
"""
from items import Item
from items_all.items_general import *
############################# Achebe Office Items ############################
class WetWipes(Item):
def __init__(self):
super().__init__(name=["Wet Wipes", "Wipes"], can_pick_up=True,
... | true |
708333088d6d79c3df015aa2450c2691903a5793 | Python | SMG2S/SMG2S | /scripts/verification.py | UTF-8 | 4,885 | 2.546875 | 3 | [
"MIT"
] | permissive | '''
MIT License
Copyright (c) 2019 Xinzhe WU @ Maison de la Simulation, France
Copyright (c) 2019-2022, Xinzhe Wu @ Simulation and Data Laboratory Quantum
Materials, Forschungszentrum Juelich GmbH.
Permission is hereby granted, free of charge,... | true |
e8885c972bf210344f8d892ba43b2eb4537589c4 | Python | erosethan/Proyecto-Compiladores-1 | /main.py | UTF-8 | 517 | 2.78125 | 3 | [] | no_license | #!/usr/bin/python
import automata, nodo, expreg
entrada = input()
expresionRegular = expreg.marcarConcatenacion(entrada)
print(entrada + ' ===> ' + expresionRegular + '\n')
expresionRegular = expreg.infijaAPosfija(expresionRegular)
inicioAutomata = automata.expregAThompson(expresionRegular)
automata.generarImagen(... | true |
944be212b7f66b29ba240ab8703291f9cc863192 | Python | zzong2006/coding-problems-study | /pythonProject/leetcode/First Missing Positive.py | UTF-8 | 514 | 3.09375 | 3 | [] | no_license | from typing import List
class Solution:
def firstMissingPositive(self, nums: List[int]) -> int:
if not nums:
return 1
else:
max_val = max(nums)
if max_val <= 0:
return 1
else:
num_set = set(nums)
for i... | true |
125d0ffd669a416346ee2edcc48baabf61b8e14f | Python | edu-sense-com/OSE-Python-Course | /SPP/Modul_05/przestawieniowe.py | UTF-8 | 3,626 | 3.953125 | 4 | [
"MIT"
] | permissive | class Skaut_Cipher:
def __init__(self, text: str, direction: str="E") -> None:
"""
direction: E -> for encryption - default
direction: D -> for decryption
"""
self.direction = direction
self.input_text = text.upper() if self.direction == "E" else ""
self.text_... | true |
1e1a1215e058abea0dfeb04b584c726bb22f195d | Python | jhelphenstine/python-class-exercises | /server.py | UTF-8 | 3,221 | 2.921875 | 3 | [] | no_license | #!/usr/bin/python
# Task: Implement a server to run on an Ubuntu system. It must:
# -- hold a port
# -- receive commands -- in the form of command-line arguments
# -- execute commands -- via os library
# -- return the results -- capture stdout/stderr...
# immediate considerations:
# we'll need sockets
# w... | true |
e43b789c39d64d3991b7118f85f02c82cb605a14 | Python | bpull/FST | /fornick/split.py | UTF-8 | 276 | 2.921875 | 3 | [] | no_license | fp = open("tickers.txt","r")
fp2=open("companies.txt","w")
for line in fp:
newlist = []
for word in line.split():
if word == "reports":
break
else:
newlist.append(word)
fp2.write(newlist.pop(0) + " "+" ".join(newlist)+"\n")
| true |
0590e7cc54b683444f9eff18fddb3ee9732e9382 | Python | MichaelPHartmann/Custom-Analysis-Tools | /main.py | UTF-8 | 799 | 2.65625 | 3 | [] | no_license | """
This is the general working file for accessing the different analysis tools.
All of the tools will be accessed from here to keep clutter down and keep the modules clean.
This also may be used for developing new tools, but they must be moved to their own modules when done.
Export or pickling may happen here for now ... | true |
805c7c4fd5e848a6988eab6846b7f9546adc3a78 | Python | techsharif/python_training_2021 | /day1/function.py | UTF-8 | 89 | 3 | 3 | [] | no_license | # def hello ():
# print("hello")
# hello()
def add(a, b):
print(a+b)
add(4, 5) | true |
d6122eb9d0b547020a0d0e0de14335f3af383ee1 | Python | PEDSnet/Data-Quality-Analysis | /Tools/ConflictResolution/resolvers/ba_001.py | UTF-8 | 2,591 | 2.90625 | 3 | [
"BSD-2-Clause"
] | permissive | # function to resolve conflicts from log file
# Inputs: (i) log_issue - an object read the log file (ii) secondary_issue - a similar issue read from the secondary
# report,
# (iii) threshold_l, and threshold_u are the thresholds corresponding to the check type CA-006
# returns a set of objects that would replace the s... | true |
e575a68d176957788541953feec141022412d060 | Python | Mathakgale/level-0-coding-challenge | /task1.py | UTF-8 | 105 | 3.703125 | 4 | [] | no_license |
x = 0
y = 1
print(f"x = {x}")
print(f"y = {y}")
x = x + 3
y = y + x
print(f"x = {x}")
print(f"y = {y}") | true |
2df354300958188d20f0eabd5d791146f0215c6d | Python | wsgan001/PyFPattern | /Data Set/bug-fixing-5/a9efceb30baa6002b4ea7f551c94f5e65e9d6f41-<_label_path_from_index>-fix.py | UTF-8 | 475 | 2.640625 | 3 | [] | no_license | def _label_path_from_index(self, index):
'\n given image index, find out annotation path\n\n Parameters:\n ----------\n index: int\n index of a specific image\n\n Returns:\n ----------\n full path of annotation file\n '
label_file = os.path.join... | true |
577438bcffa25dd5552a557e661b88db540ae9dc | Python | Aasthaengg/IBMdataset | /Python_codes/p02712/s061370665.py | UTF-8 | 189 | 3.203125 | 3 | [] | no_license | N = int(input())
ans = [0] * (N+1)
for i in range(N+1):
if i % 3 != 0 and i % 5 != 0 and i % 15 != 0:
ans[i] = ans[i-1] + i
else:
ans[i] = ans[i-1]
print(ans[-1])
| true |
897f9ae2bab6ea1212577bfecc210e17a737b78f | Python | JiachenLi/PythonLearning | /emailaddress2.py | UTF-8 | 351 | 3 | 3 | [] | no_license | # !/usr/bin/env python3
# -*- coding: utf-8 -*-
' a test module '
__author__ = 'Jiachen Li'
import re
def name_of_email(addr):
s = str(addr)
m = re.match(r'/^\<([a-zA-Z\s]+)\>\s([a-zA-Z][a-zA-Z\d\_\.]*@[a-zA-Z\d]+\.[a-zA-Z]{2,3})$/', s)
if m:
print(m.group(1))
else:
pr... | true |
1811d475dff7f4d0cec5289ec42b86008cad493b | Python | nosleep123/shawn-sascode | /Scraper.py | UTF-8 | 3,856 | 2.734375 | 3 | [] | no_license |
import logging
import os
DEFAULT_DATA_PATH = os.path.abspath(os.path.join(
os.path.dirname('/Users/shuhao/PycharmProjects/Learning/data/SEC'), '..', 'SEC-Edgar-Data'))
# -*- coding:utf-8 -*-
# This script will download all the 10-K, 10-Q and 8-K
# provided that of company symbol and its cik code.
class HoldingIn... | true |
4d68b1e6413d7d15f01902a1f3b32a86b4fde8ae | Python | zhangweisgithub/demo | /python_module/asyncio_module/case2.py | UTF-8 | 2,633 | 3.828125 | 4 | [] | no_license | # !/usr/bin/env python
# -*- coding: utf-8 -*-
"""
可等待对象
如果一个对象可以在 await 语句中使用，那么它就是 可等待 对象。许多 asyncio API 都被设计为接受可等待对象。
可等待 对象有三种主要类型: 协程, 任务 和 Future.
"""
print("---------------------协程-------------------------")
"""
协程函数: 定义形式为 async def 的函数;
协程对象: 调用 协程函数 所返回的对象。
"""
import asyncio
async def nested():
return... | true |
cf6fb96b2e2dd3c49fd399938623478f8d986fdd | Python | bolton-nate/ttt_minimax | /main.py | UTF-8 | 4,080 | 3.484375 | 3 | [] | no_license | # This is where your main() function will go.
# The main() function will tie all other functions together.
# You may add other functions here as needed.
from userInput import *
from computerInput import *
from computerRandom import *
from computerMinimax import *
from computerAlphaBeta import *
from Game import *
tota... | true |
eb9de6d661fa1ed71f06142a46caae0a59f52529 | Python | try1995/Linear-classifier | /activation_statistic.py | UTF-8 | 1,527 | 3.015625 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as plt
from time import time
'''激活函数策略和权值的选择'''
start = time()
D = np.random.randn(1000, 500)
hidden_layer_sizes = [500]*10
nonlinearities = ['tanh']*len(hidden_layer_sizes)
'''激活函数'''
act = {"relu": lambda x: np.maximum(0, x), 'tanh': lambda x: np.tanh(x),
'sigmoid'... | true |
f26eeb9f03ebac01629696e35ea122aa535e7bbf | Python | Kimseongick/2017_NIMS_CNC_Problem | /04_Code.py | UTF-8 | 8,933 | 2.625 | 3 | [] | no_license | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib', 'inline')
# In[2]:
data_1 = pd.read_csv('data/data_1.csv', header=None, index_col=None)
data_2 = pd.read_csv('data/data_2.csv', header=None, index_col=N... | true |
62ea2f4508ce0d0dc9efe8c61e76abeeacd98985 | Python | gustavobiage/URI_Solutions | /AD-HOC/1441.py | UTF-8 | 180 | 3.125 | 3 | [] | no_license | while 1:
hstr = input()
h = int(hstr)
if h == 0:
break
m = 1
while h != 1:
if h > m:
m = h
if h % 2 == 1:
h = 3 * h + 1
else:
h = h / 2
h = int(h)
print(m) | true |
f7a8ab7ad061c1a5433d7d9a1867909a30be186e | Python | hatopoppoK3/AtCoder-Practice | /AOJ/ALDS1/002/C.py | UTF-8 | 845 | 3.59375 | 4 | [] | no_license | def bubble_sort(A, N):
A = list(A)
for i in range(1, N):
for j in range(0, N-i):
if A[j][1] > A[j+1][1]:
A[j], A[j+1] = A[j+1], A[j]
tmp = []
for x, y in A:
tmp.append(x+str(y))
return tmp
def selection_sort(A, N):
A = list(A)
for i in range(0, N... | true |
adc02d239be6ef8375f83e00f752deb9bfcb75c5 | Python | araghuram3/SF_NN | /evaluate_data.py | UTF-8 | 1,234 | 2.59375 | 3 | [] | no_license | # script to process data
# will depend on how the data is imported
# write now will assume it is placed in a folder "test" in the same directory
# import statments
import matplotlib.pyplot as plt
# tensorflow statements
import tensorflow as tf
layers = tf.keras.layers
from tensorflow.keras.preprocessing.ima... | true |
1330e427651c295ed4b4cb79f33bc2bce1743d97 | Python | ycxzfforever/Python_Study | /time.py | UTF-8 | 1,184 | 3.515625 | 4 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import time; # 引入time模块
import calendar;
ticks = time.time()
print "当前时间戳为:", ticks
localtime = time.localtime(time.time())
print "当前时间结构体：",localtime
print "当前时间：",time.asctime(localtime)
# 格式化成2016-03-20 11:45:39形式
print time.strftime("%Y-%m-%d %H:%M:%S %A %B %x %X %... | true |
2a28c8391fc043e005b0e27e0109492299030186 | Python | KarenWest/pythonClassProjects | /newtonRaphsonMethod.py | UTF-8 | 1,090 | 4 | 4 | [] | no_license | #Summary - admittedly--had help from internet search here! Have not learned all these tricks yet.
# Solve for a zero of function using Newton-Raphson method
#Usage
# real = func(real)
# real = funcd(real)
# real = newton(func, funcd, real [, TOL=real])
#""" Ubiquitous Newton-Raphson algorithm for solvi... | true |
d682a3f8a3332e2e45fd66d7cfdb97138375c071 | Python | KiranChavan326/sdet | /python/acc2.py | UTF-8 | 153 | 3.8125 | 4 | [] | no_license | num = int(input("Enter the number :"))
mod = num%2
if mod>0:
print("You picked the old number")
else:
print("You picked the even numer") | true |