text stringlengths 38 1.54M |
|---|
import numpy as np, matplotlib.pyplot as plt
d = np.load('2457548.45923.npz')
NOT_REAL_ANTS="0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 66, 67... |
"""
This problem was asked by Amazon.
Run-length encoding is a fast and simple method of encoding strings.
The basic idea is to represent repeated successive characters
as a single count and character.
For example, the string "AAAABBBCCDAA" would be encoded as "4A3B2C1D2A".
Implement run-length encoding and decoding.... |
In this kata you are required to, given a string, replace every letter with its position in the alphabet.
If anything in the text isn't a letter, ignore it and don't return it.
"a" = 1, "b" = 2, etc.
soln:
from string import ascii_lowercase
LETTERS = {letter: str(index) for index, letter in enumerate(ascii_lo... |
#!/usr/bin/python3
# -*- coding: utf-8 -*-
# (C) w:fa:User:Reza1615, 2020
# (C) w:fa:User:Huji, 2020
# Distributed under the terms of the CC-BY-SA 3.0
import pywikibot
from persiantools import digits
from datetime import datetime
month_names = [
"ژانویه",
"فوریه",
"مارس",
"آوریل",... |
import os.path
import shutil
import sys
import numpy as np
import gc
import tensorflow as tf
from nets import nets
from data import data
from runs import preprocessing
import pickle
def evaluate_network(opt):
# Initialize dataset and creates TF records if they do not exist
dataset = data.ImagenetDataset(opt)
... |
#!/bin/python3
import math
import os
import random
import re
import sys
class SinglyLinkedListNode:
def __init__(self, node_data):
self.data = node_data
self.next = None
class SinglyLinkedList:
def __init__(self):
self.head = None
def print_singly_linked_list(node, sep, fptr):
wh... |
from scipy import signal
import numpy as np # linear algebra
import matplotlib.pyplot as plt
DeltaQ = 150 #Internal heat gain difference between day and night
#day_DeltaQ = DeltaQ #Day Delta Q internal [W]
Qday = 400 #Day internal heat gain W
nightQ ... |
#!usr/bin/pytthon
# coding:utf-8
from numpy import *
# 已知用户物品矩阵为dataMat ，行为物品，列为用户
# 计算用户相似度
# -----------------
# 余弦相似度计算
# 欧式距离计算
def eulidSim(inA, inB):
return 1.0 / (1.0 + linalg.norm(inA, inB))
# 皮尔逊系数计算
def pearsSim(inA, inB):
if len(inA) <3 : return 1.0
# 将值从[-1, 1]映射到[0, 1]
return 0.5+0.5*corr... |
#!/usr/bin/python3
# import socket programming library
import socket
import json
import time
import csv
import hadoop
import pandas
from io import StringIO
# import thread module
from _thread import *
import threading
print_lock = threading.Lock()
def processJobInfo(stats):
statsstr = '\n'.join(stats)
p... |
import cv2
import cvzone
from cvzone.SelfiSegmentationModule import SelfiSegmentation
import os
cap = cv2.VideoCapture('1.avi')
cap.set(3, 640)
cap.set(4, 480)
cap.set(cv2.CAP_PROP_FPS, 60)
segmentor = SelfiSegmentation()
fpsReader = cvzone.FPS()
imgBg = cv2.imread('Images/1.jpg')
imgBg = cv2.resize(imgBg,(640, 480))
... |
import tensorflow as tf
import models.bert_util.bert_utils
from explain.explain_model import CrossEntropyModeling, CorrelationModeling
from explain.pairing.match_predictor import build_model
from tf_util.tf_logging import tf_logging
from trainer.multi_gpu_support import get_multiple_models, get_avg_loss, get_avg_tenso... |
def try5():
d = Definer()
m = d.matcher
f1 = CFunc(PrimTypes.INT)
f1.add(CPtr(CPtr(PrimTypes.VOID)))
m.add_rule(CPtr(PrimTypes.VOID), 'PVOID')
m.add_rule(PrimTypes.INT, 'INT')
m.tree_names_list.append('MYSTRUC')
# m.add_rule(CPtr(f1), 'MY_PROC')
s1 = CStruct()
s1.add(PrimTypes.UI... |
from uncertainties import ufloat
from uncertainties.umath import *
print
print '*************Values *********************'
print
H = ufloat(67.4000000, 1.40000000) # H = 67.4+/-1.4
h = H/100.0
print 'h = ', h
obh2 = ufloat(0.0220700000, 0.000330000000)
print 'obh2 = ' , obh2
ob = obh2/h**2
ErrorLnOb = 0.00124
LnOb =... |
numList = []
for x in range(5):
numList.append(int(input("Number " + str(x+1) + ": ")))
print("You entered: " + str(numList))
avg = 0
for x in numList:
avg += int(x)
avg = avg / len(numList)
print("The average is: " + str(avg))
print("The range is: " + str(len(numList)))
rem = int(input("Which item do you want ... |
# -*- mode: Python; -*-
'''Implementation of vrt-data.'''
import os
from subprocess import Popen, PIPE
from libvrt.args import BadData
from libvrt.args import transput_args
# TODO here AND rel-tools to RAISE not EXIT on failure
from libvrt.bins import SORT
from libvrt.dataline import valuegetter
# remnants of vrt... |
# Regex
'''
You have a test string S. Your task is to match the string hackerrank. This is case sensitive.
'''
Regex_Pattern = r'hackerrank' # Do not delete 'r'.
import re
Test_String = input()
match = re.findall(Regex_Pattern, Test_String)
print("Number of matches :", len(match))
# Matching Anything But a Newlin... |
# --------------
# Importing header files
import numpy as np
# Path of the file has been stored in variable called 'path'
data = np.genfromtxt(path,delimiter=",",skip_header=1)
print ("\nData: \n\n",data)
print ("\nTypeof data: \n\n",type(data))
#New record
new_record=[[50, 9, 4, 1, 0, 0, 40, 0]]
census... |
import os
#declarar variables
Comensal,Azafata,precio1,precio2,precio3="","",0,0,0
#INPUT
Comensal=os.sys.argv[1]
Azafata=os.sys.argv[2]
precio1=int(os.sys.argv[3])
precio2=int(os.sys.argv[4])
precio3=int(os.sys.argv[5])
#PROCESSING
total =int(precio1 + precio2 + precio3)
#OUTPUT
print(" ############################... |
from typing import Dict, List, Optional
from pydantic import BaseModel
class RecognitionModel(BaseModel):
error: bool = False
error_msg: str = ""
data: Dict = {}
|
from django.db import models
# Create your models here.
class Employee(models.Model):
fullname = models.CharField(max_length=30)
job = models.CharField(max_length=15)
salary = models.IntegerField()
email = models.EmailField(max_length=50)
def __str__(self):
return self.fullname + "," + se... |
from .distributions import GMMDiag, GMMFull, MoE
import tensorflow as tf
import tensorflow.compat.v1 as tf1
from ..utils.tf_utils import log_normalize
class GMMApprox(object):
def __init__(self, log_unnormalized_prob, gmm=None, k=10, loc=0., std=1., ndim=None, loc_tril=None,
samples=20, temp=1., cov_type='diag')... |
# -*- coding:utf-8 -*-
import sys
sys.path.append('..')
from Model.BookModel import BookModel
from Model.ISBNBookModel import IsbnBookModel
from View.BookView import BookView
class BookController(object):
def __init__(self):
self.Model = BookModel()
self.View = BookView()
#上传图书ISBN信息
'... |
max = 1000000
primes = [True]*max
for i in range(2,max):
x = 2*i
while x < max:
primes[x] = False
x += i
print(primes[:30])
count = 1
x = 2
while count < 10001:
x += 1
if primes[x]:
count += 1
print(x)
|
import re, time, json, threading, requests, traceback
from datetime import datetime
import paho.mqtt.client as mqtt
import DAN, SA
def df_func_name(df_name):
return re.sub(r'-', r'_', df_name)
MQTT_broker = getattr(SA,'MQTT_broker', None)
MQTT_port = getattr(SA,'MQTT_port', 1883)
MQTT_User = getattr(SA,'MQTT_User... |
from histogram_functions import get_words
from histogram_lists import count_words
import random
def sample_by_frequency(histogram):
# Find the most any word appears and set max_frequency equal to that value
max_frequency = 0
for item in histogram:
if item[1] > max_frequency:
max_freque... |
from hwt.hdlObjects.operator import Operator
from hwt.hdlObjects.operatorDefs import AllOps
from hwt.hdlObjects.types.defs import BOOL
from hwt.hdlObjects.value import Value
class EventCapableVal(Value):
def _hasEvent__val(self, now):
BoolVal = BOOL.getValueCls()
return BoolVal(self.updateTime == ... |
import logging
class LastLogsHandler(logging.Handler):
def __init__(self, size):
logging.Handler.__init__(self)
self.strA = []
self.i = 0
self.len = size
for i in range(self.len):
self.strA.append(None)
def emit(self, record):
self.strA[self.i] = re... |
from numpy import *
import pylab
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plot
set_printoptions(precision = 3)
#Datos: distribución normal multivariada en 3d
mean = [1,5,10]
cov = [[-1,1,2], [-2,3,1],[4,0,3]]
d = random.multivariada_normal(mean,cov,1000)
#representació gráfica de los dato... |
#1/2/3
import numpy as np
import pandas as pd
site=('https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/04_Apply/Students_Alcohol_Consumption/student-mat.csv')
df = pd.read_csv(site)
#4
df_slice = df.loc[:,'school':'guardian']
#5/6/8
str_func = lambda x: x.capitalize()
df['Mj... |
import os
#imput
densidad=int(os.sys.argv[1])
altura=int(os.sys.argv[2])
gravedad=float(os.sys.argv[3])
#processing
presion=(densidad*altura*gravedad)
#output
if (presion>42):
print("presion en estado critico para el producto")
if(presion<42 and presion>30):
print("tengan cuidado")
if(presion<20):
print("to... |
#!/usr/bin/python
"""
unpickle.py: A subset of unpickling code from pickle.py.
- We don't want to ship the pickler.
- We only need to handle the v2 protocol
- We only need to handle the parts of the protocol that we use.
For reference, the _RuntimeType hierarchy seems to require 15 unique
instructions + PROTO and STO... |
from random import choice
from time import sleep
STUDENTS = [
'Name 1',
'Name 2',
'Name 3',
]
def rien_ne_va_plus(hot_seats, safe_students):
if hot_seats == []:
hot_seats = STUDENTS.copy()
safe_students = []
print(f"Students on the hot seats for the next question:\n\t{', '.join(hot_seats)}\n")... |
rzymskie ={ 1:'I', 2:'II', 3:'III', 4:"IV", 5:"V", 6:"VI", 7:"VII", 8:"VIII", 9:'IX', 10:"X"}
cyfra = input("podaj liczbę: ")
#po_rzymsku = rzymskie[liczba]
#print(po_rzymsku)
#cyfra 28
cyfra_dziesiatek = int(cyfra[-2])# przedostatnia cyfra, przdostatni znak zamieniona na cyfrę
cyfra_jedności= int(cyfra[-1])
jednosci... |
#!/usr/bin/python
""" Script to make light budget calculations for permitted cable lengths for a
given TAP or appropriate TAP for current link. """
from decimal import Decimal, getcontext
def menu():
""" High level menu for available options. """
option = raw_input("""\nWhat would you like to do:
1 -... |
class Node(object):
def __init__(self, data = None, next_node = None):
self.data = data
self.next = next_node
def __str__(self):
return str(self.data)
def get_data(self):
return self.data
def print_list(node):
while node:
print(node.get_data())
... |
class Config(object):
DEBUG = True
SQLALCHEMY_DATABASE_URI = "mysql://dev:dev@localhost/ssi"
SQLALCHEMY_ECHO = False
SECRET_KEY = "secret" |
from StringIO import StringIO
import tornado.gen
import tornado.testing
import tornado.web
from tornado.httpclient import HTTPResponse, HTTPRequest
from mainhandler import MainHandler
class MainHandlerTest(tornado.testing.AsyncHTTPTestCase):
"Test fixture for MainHandler class"
def __init__(self, *args, **kw... |
import hashlib
import imghdr
import sec
import db_op
__all__ = ['get_type_by_stream', 'save_file', 'get_hashcode', 'get_default',
'get_image']
_SAVE_PATH = '/Yagra/upload/'
_DEFAULT_IMG = '/Yagra/web/static/rex.jpeg'
def get_type_by_stream(stream):
"""Check the data stream and return what type of ima... |
# Linear Regression Machine Learning Program
#
# Sources used:
# - https://towardsdatascience.com/master-machine-learning-multiple-linear-regression-from-scratch-with-python-ac716a9b78a4
# Sean Taylor Thomas
import numpy as np
import matplotlib.pyplot as plt
# from matplotlib import rcParams
# rcParams['figure.figsize... |
from collections import deque
queue = deque(["Eric", "John", "Michael"])
queue.append("Ben")
queue.append("Helen")
print queue
print queue.popleft()
print queue |
import numpy as np
# Creating an 1d - array
li = [1, 2, 3]
arr = np.array(li)
print(arr)
# Creating an 2d - array
li = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
arr = np.array(li)
print(arr)
# Creating an array of a number sequence
arr = np.arange(0, 10)
print(arr)
arr = np.arange(0, 10, step=2)
print(arr)
# Creating an 1-... |
def is_palindrome_permutation(strng):
cache = set()
for char in strng.lower():
if char in cache:
cache.remove(char)
else:
cache.add(char)
return len(cache) <= 1
is_palindrome_permutation('RACECAR') |
import cv2
def bgr8_to_jpeg(value):
if value is None:
return bytes()
return bytes(cv2.imencode('.jpg', value)[1]) |
from soda.execution.table import Table
class Column:
def __init__(self, table: "Table", column_name: str):
from soda.sodacl.column_configurations_cfg import ColumnConfigurationsCfg
self.data_source_scan = table.data_source_scan
self.table = table
self.column_name = str(column_name... |
import numpy as np
import sys
from ..mike_model.tariff import Tariff
class Customer:
"""Can be resident, strata body, or ENO representing aggregation of residents."""
def __init__(self, name, study, timeseries):
self.name = name
self.study = study
self.ts = timeseries
self.t... |
from django.db.models.signals import class_prepared
def patch_user(sender, *args, **kwargs):
authmodels = 'django.contrib.auth.models'
if sender.__name__ == 'User' and sender.__module__ == authmodels:
# patch the length
sender._meta.get_field('username').max_length = 80
# patch the ... |
# Created by MechAviv
# Quest ID :: 61145
# Mysterious Merchant Matilda
sm.setSpeakerID(9201451)
sm.removeEscapeButton()
sm.flipDialogue()
sm.sendNext("Hi! My name is #bMatilda#k.\r\nI sell lots of handy stuff. And not like those OTHER people that say that.\r\n You have the look of someone about to do something stu... |
from django.db import models
from django.contrib.auth.models import User
class Ban( models.Model ):
id = models.AutoField( primary_key = True )
user = models.OneToOneField( User )
ip_address = models.IPAddressField()
start_dtm = models.DateTimeField()
end_dtm = models.DateTimeField()
permaban =... |
# 배열 array의 i번째 숫자부터 j번째 숫자까지 자르고 정렬했을 때, k번째에 있는 수를 구하려 합니다.
# 예를 들어 array가 [1, 5, 2, 6, 3, 7, 4], i = 2, j = 5, k = 3이라면
# array의 2번째부터 5번째까지 자르면 [5, 2, 6, 3]입니다.
# 1에서 나온 배열을 정렬하면 [2, 3, 5, 6]입니다.
# 2에서 나온 배열의 3번째 숫자는 5입니다.
# 배열 array, [i, j, k]를 원소로 가진 2차원 배열 commands가 매개변수로 주어질 때,
# commands의 모든 원소에 대해 앞서 설명한 연산을... |
import gym
import gym.spaces as spaces
import Game
class CustomEnv(gym.Env):
def __init__(self):
self.pygame = Game.Pygame2D()
self.action_space = spaces.Discrete(180)
rows_player_obs = [5] * 15
penality_player_obs = [1] * 7
board_player_obs = [1] * 25
n... |
from details.models import Person
from django.forms import Textarea, CheckboxSelectMultiple
from django.forms.models import ModelMultipleChoiceField
from django.utils.translation import ugettext as _
from django.contrib import admin
from django.conf import settings
from django.db import models
from common.admintools i... |
"""
Model for the adventure.
"""
# pylint: disable=too-few-public-methods
from django.db import models
from .mixins import TimestampMixin, DescriptionNotesMixin
class Adventure(models.Model, TimestampMixin, DescriptionNotesMixin):
"""
Model for the adventure.
"""
name = models.CharField(max_length=12... |
import json
import pandas as pd
import numpy as np
from tqdm import tqdm
def get_spdat_feat_types(df):
'''
Get lists of features containing the single-valued categorical and noncategorical feature names in the SPDAT data
:param df: Pandas DataFrame containing client SPDAT question info
:return: List of... |
## Ch09 P9.6
from car import Car
myCar = Car(50)
myCar.addGas(20)
myCar.drive(100)
print(myCar.getGasLevel()) |
def spiralNumbers(m):
mx = [[0 for i in range(m)] for j in range(m)]
cnt = 1
for i in range(m):
mx[0][i] = cnt
cnt += 1
n = m - 1
while cnt < m ** 2:
for j in range(m // 2):
for i in range(n):
mx[i + j + 1][m - j - 1] = cnt
cnt += ... |
#!/usr/bin/env python
# coding: utf-8
# In[17]:
import cv2
import numpy as np
import glob
import matplotlib.pyplot as plt
import PIL
import time
import os
# In[49]:
img_dir = os.path.join(r"Images","*g")
img_dir = glob.glob(img_dir)
image_l = []
# In[50]:
def MSE(image1_gray_resized_np,image2_gray_resized_np... |
# Handle all the exceptions!
#Setup
actor = {"name": "John Cleese", "rank": "awesome"}
#Function to modify, should return the last name of the actor [try except block]
def get_last_name():
try:
return actor["last_name"]
except:
namelist=[]
namelist= actor["name"].split()
return ... |
HTTP_HEADER_LIST = [
"REMOTE_ADDR",
"REMOTE_HOST",
"X_FORWARDED_FOR",
"TZ",
"QUERY_STRING",
"CONTENT_LENGTH",
"CONTENT_TYPE",
"LC_CTYPE",
"SERVER_PROTOCOL",
"SERVER_SOFTWARE",
]
MASKED_DATA = "XXXXXXXXX"
CONTENT_TYPE_JSON = "application/json"
CONTENT_TYPE_METHOD_MAP = {CONTENT_... |
# Copyright (c) 2010 Jeremy Thurgood <firxen+boto@gmail.com>
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, mod... |
'''
Surprisingly there are only three numbers that can be written as the sum of fourth powers of their digits:
1634 = 14 + 64 + 34 + 44
8208 = 84 + 24 + 04 + 84
9474 = 94 + 44 + 74 + 44
As 1 = 14 is not a sum it is not included.
The sum of these numbers is 1634 + 8208 + 9474 = 19316.
Find the sum of all the numbers ... |
# Prim algorithm
# input where n is weight of each edge
# 0,2,1,0,0
# 2,0,1,2,3
# 1,1,0,0,4
# 0,2,0,0,2
# 0,3,4,2,0
import random as rand
def printGraph(g):
for row in g:
print (row)
print ("---------------------------\n")
def fillGraph (inputfile):
graph = []
f = open(inputfile,"r+")
n... |
from setuptools import setup, find_packages
setup(
name='pyIID',
version='',
packages=find_packages(exclude=['doc', 'benchmarks', 'extra', 'scripts', 'examples' ,]),
url='',
license='',
author='christopher',
author_email='',
description='', requires=['scipy']
)
|
import torch
a = torch.rand((16, 1024, 14, 24))
b = torch.rand((16, 1024, 14, 24))
c = torch.cat([a, b], dim=1)
print(c.shape) |
import torch
import torch.nn as nn
from torch.autograd import Variable
"""
Generator network
"""
class _netG(nn.Module):
def __init__(self, opt, nclasses):
super(_netG, self).__init__()
self.ndim = 2*opt.ndf
self.ngf = opt.ngf
self.nz = opt.nz
self.gpu = opt.gpu
... |
# -*- coding=utf-8 -*-
#---------------------------------------
# 程序：豆瓣相册爬虫
# 版本：0.2
# 作者：Will
# 日期：2014-07-17
# 语言：Python 2.7
# 功能：将相册中照片全部抓下来
# 改进：优先抓取大图；用户只需输入相册编号，自动计算所有页
#---------------------------------------
import urllib
import re
import datetime
import time
import urllib2
impor... |
import sys
n = int(sys.stdin.readline())
for i in range(n):
a, b = list(sys.stdin.readline().strip())
a = ord(a) - ord('a')
b = int(b) - 1
t = 0
if 0<=a+2<=7 and 0<=b+1<=7:
t+=1
if 0<=a+2<=7 and 0<=b-1<=7:
t+=1
if 0<=a-2<=7 and 0<=b+1<=7:
t+=1
if 0<=a-2<=7 and 0<=b-1<=7:
t+=1
if 0<=a+1<=7 and 0<=b+2<=... |
from rest_framework import mixins
from rest_framework import viewsets
class CreateListRetrieveViewset(
mixins.ListModelMixin,
mixins.CreateModelMixin,
mixins.RetrieveModelMixin,
viewsets.GenericViewSet,
):
pass
class CreateViewset(
mixins.CreateModelMixin, viewsets.GenericViewSet,
):
pas... |
#!/usr/bin/env python
"""
The n^(th) term of the sequence of triangle numbers is given by,
t_(n) = 1/2n(n+1); so the first ten triangle numbers are:
1, 3, 6, 10, 15, 21, 28, 36, 45, 55, ...
By converting each letter in a word to a number corresponding to its
alphabetical position and adding these values we form a w... |
# -*- coding: utf-8 -*-
import numpy as np
"""Function used to compute the loss."""
def compute_loss_mse(y, tx, w):
"""MAE"""
e = y - tx.dot(w)
return (np.linalg.norm(e) ** 2) / len(y)
def compute_loss_mae(y, tx, w):
"""MSE"""
e = y - tx.dot(w)
mae = 0.5 * (np.linalg.norm(e, 1)) / len(y)
... |
API_HOSTS = {
"test": "http://192.168.1.100:11002/wp-json/wc/v3/",
"dev": "",
"prod": ""
}
DB_HOST = {
} |
import sys #sys is built in library(the bread and butter)
try: #underneath the block try block, you "try" a piece of code that you think might give you an error
#In my case, I didn't install request when running
import requests
except ImportError:
#Write specific error
#We are looking for an I... |
#!/usr/bin/python
# The MIT License (MIT)
#
# Copyright (c) 2017 Massimiliano Patacchiola
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation ... |
from django.shortcuts import render, redirect
from django.http import Http404
from django.contrib import messages
from django.core.mail import send_mail
from Modelos.models import (
empresas,
activi_comerciales,
productos,
servicios,
usuarios,
)
from Global.usuario import Usuario
from Cliente.carri... |
from pathlib import Path
from django.urls import path
from . import views
from .models import Record
activity_short = Path(__file__).parts[-2]
app_name = activity_short
urlpatterns = [
path('', views.FilterRecord.as_view(), name='index'),
path('record/', views.GetRecord.as_view(), name='grecord'),
path('f... |
"""
delete.py
"""
import requests
from .exceptions import AgaveFilesError
from ..utils import handle_bad_response_status_code
def files_delete(tenant_url, access_token, file_path):
""" Remove a file or direcotry from a remote system
"""
# Set request url.
endpoint = "{0}/{1}/{2}".format(tenant_url... |
def numPaths(y, x):
if y==0 and x==0:
return 1
if y<0 or x<0:
return 0
right = numPaths(y, x-1)
down = numPaths(y-1, x)
return right+down
def test1():
y = 2
x = 3
res = numPaths(y, x)
print("res: ", res)
test1() |
from tqdm import tqdm
import numpy as np
import os ; os.environ['HDF5_DISABLE_VERSION_CHECK']='2'
import tensorflow as tf
import tensorflow_datasets as tfds
# from codecs import open
ds, info = tfds.load('imdb_reviews/subwords8k',
with_info=True,
as_supervised=True)
train_ex... |
import random
a = [4,5,2]
#값에 access
a[0]
a[1]
a[2]
# 리스트에 랜덤한 value 5 insert append
'''
Data Structure
자료구조 지만 많이 사용되기 때문에 basic part에서 설명함.
선형구조
-initialiaztion
-init
a = []
a = [1, 2, 3, 4]
-Data add
append 함수를 사용
for i in range(1,101):
a.append(i)
-check length
len(a)
-delete
del a[2]
-insert
a.insert(... |
#!/usr/bin/env python3
"""
Takes input a relatedness file, a fam file, and a list of individuals and extracts the sub-matrix from the relatedness file
for the given individuals
Jean-Tristan Brandenburg
"""
import sys
import pandas as pd
import numpy as np
import argparse
EOL=chr(10)
def errorMessage10(phe):
... |
# -*- coding: utf-8 -*-
import h5py
import numpy as np
from sklearn.utils import shuffle
from keras.models import *
from keras.layers import *
import pandas as pd
from keras.preprocessing.image import *
# bottleneck产生测试特征
np.random.seed(2017)
X_train = []
X_test = []
y_pred = []
for filename in ["gap_InceptionV3.h5... |
list=["a","e","i","o","u","A","E","I","O","U"]
a=str(input("enter the value:"))
if (a in list):
print ("vowel")
else:
print ("consonant")
|
import pygame
class Settings():
'''Класс для хранения всех настроек классификатора рукописных чисел'''
def __init__(self):
'''Инициализирует настройки классификатора'''
#Параметры экрана
self.screen_width = 415
self.screen_height = 250
self.bg_color = (100, 150, 255)
#Параметры доски для рисования
sel... |
"""
TIME LIMIT PER TEST: 3 seconds
MEMORY LIMIT PER TEST: 256 megabytes
INPUT: standard input
OUTPUT: standard output
"Contestant who earns a score equal to or greater than the k-th place finisher's score will advance to the next
round, as long as the contestant earns a posit... |
import os
def clear(): return os.system('cls')
should_continue = True
def cipherUnrestricted(message, direction, caesarNumber):
cipheredMessage = ""
if direction == 'e':
for letter in message:
if letter.isalpha():
cipheredMessage += chr((ord(letter) -
... |
from random import *
from metodusok import *
from targy import *
targyak = Targy("teritve", "troli")
print(targyak)
also = bekerszam("Alsóhatár?: ",1,7)
felso = bekerszam("Felsőhatár?: ",5,10)
darab = bekerszam("Darab?: ",1,5)
szamok = []
for i in range(darab):
#veletlenszam = randint(also,felso)
szamok.append... |
aa8=int(input())
b6=[int(x) for x in input().split()]
zzz=0
for x in range(aa8):
for y in range(x):
if b6[y]<b6[x]:
yyy+=b6[j]
print(zzz)
|
# Created by Brian Mascitello to calculate a specific polynomial's root.
def mathproblem(x0):
""" function mathproblem(x0) finds a root of the nonlinear
function specified by f and fprime. y = 2 ** x - 3 ** (x / 2) - 1;
yprime = 0.693147 * (2 ** x) - (1.098612 * 3 ** (x / 2)) / 2; Result
x ... |
from flask import Flask
import bot_nmap as botmap
import json
app = Flask(__name__)
@app.route('/nmap/<ip>',methods=['GET'])
def nmap(ip):
return json.dumps(botmap.getPorts(ip))
app.run(host='0.0.0.0',use_reloader=False)
|
import imp, os.path, sys, time
from watchdog.observers import Observer
from watchdog.events import PatternMatchingEventHandler
import mockingbeat
class MyHandler(PatternMatchingEventHandler):
patterns = []
@staticmethod
def dispatch(event):
if event.src_path == ifn:
load()
ifn = ofn = None
def load():
stdo... |
# Необходимо набрать из каждый пары ровно одно число так, чтобы сумма всех выбранных числе не делилась на 31
# и при этом была максимально возможной.
f = open("27v01_B.txt", 'r')
f_len = int(f.readline())
a = []
for i in range(f_len):
j, k = map(int, f.readline().split())
a.append([max(j, k), min(j, k), abs(j-k... |
from .views import AccessViewSet
def register(router):
router.register(r'access', AccessViewSet, base_name='access')
|
import math
import numpy as np, cv2
width = 640
height = 480
referencePoints = np.float32(
[[width/4,height/4],
[3*width/4,height/4],
[3*width/4,3*height/4],
[width/4,3*height/4]])
currentPoint = -1
calibrating = True
fullScreen = False
names = ['0', 'A risada mais engraçada Pânico na TV.avi', 'Sabe de nada inoce... |
# Dependencies
import requests
from splinter import Browser
from webdriver_manager.chrome import ChromeDriverManager
import pandas as pd
from flask_pymongo import PyMongo
from pymongo import MongoClient
from bs4 import BeautifulSoup as bs
def get_mars_table():
#Get Mars Facts
mars_facts_url = 'https://space-fa... |
# Strings
#######################################################################################################################
#
# Anton and Artur are old friends. Today they practice in writing strings. Anton must write each string
# with the lengths exactly N , based on the alphabet of size M . And Arthur, on... |
from notes.infraestructure.adapter.sqlalchemy import SqlAlchemyAdapter
from notes.domain.entity.notes import Notes
class NotesSqlAlchemyRepository:
def __init__(self):
self.__adapter = SqlAlchemyAdapter()
self.__adapter.entity = Notes
def create(self, notes: Notes):
try:
... |
import unittest
from google_finance import GoogleFinance
class TddInPythonExample_Plotter(unittest.TestCase):
def test_savepng(self):
gf = GoogleFinance()
gf.plot()
def test_addidxcolumn(self):
gf = GoogleFinance()
reshaped = gf.addidxcolumn([
[-1, 240, 239, 240, ... |
from ScenarioHelper import *
def main():
CreateScenaFile(
"t1310_1.bin", # FileName
"t1310", # MapName
"t1310", # Location
0x00BD, # MapIndex
"ed7161",
0x00002000, # Flags
... |
import nltk
from urllib.request import urlopen
from nltk import word_tokenize
Single_PMID = "24964572"
PMIDs = ["28483577", "24964572", "27283605"]
Pubtator_Info_URL = "https://www.ncbi.nlm.nih.gov/research/pubtator-api/publications/export/pubtator?pmids=24964572"
Pubtator_Info = urlopen(Pubtator_Info_URL, None, t... |
if 'c' in 'Python':
print 'YES'
else:
print 'NO'
#http://www.hacksparrow.com/python-check-if-a-character-or-substring-is-in-a-string.html |
# -*- coding: utf-8 -*-
# cython: language_level=3, always_allow_keywords=True
## Copyright 2007-2018 by LivingLogic AG, Bayreuth/Germany
## Copyright 2007-2018 by Walter Dörwald
##
## All Rights Reserved
##
## See ll/xist/__init__.py for the license
"""
This namespace module implements Atom 1.0 as specified by :rfc... |
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