text stringlengths 38 1.54M |
|---|
def SelectionSort(A):
n = len(A)
for j in range(0, n - 1):
imin = j
for i in range(j + 1, n):
if (A[i] < A[imin]):
imin = i
A[imin], A[j] = A[j], A[imin]
|
# coding:utf-8
import os
import time
import tempfile
import aircv as ac
import pytesseract
from PIL import Image
PATH = lambda p: os.path.abspath(p)
TEMP_FILE = PATH(tempfile.gettempdir() + "/temp_screen.png")
class Appium_Extend(object):
def __init__(self, driver):
self.driver = driver
def get_time... |
import numpy as np
import os
years = np.arange(501,525)
v = 'SST'
output = 'ice_month'
for y in years:
os.system('ncra -v ' + v + ' /short/e14/erd561/mom/archive/gfdl_nyf_1080_hist_5069/output' + str(y) + '/' + output + '.nc /g/data/e14/erd561/mom/gfdl_nyf_1080_hist_5069/' + output + str(y) + '_' + v + '.nc')
... |
# -*- coding: utf-8 -*-
import glob
import os
import importlib
import sys
modules = {}
# 출력 결과 비교 모듈을 발견해 봅시다
diff_dir = os.path.dirname(__file__)
sys.path.append(diff_dir)
files = glob.glob(os.path.join(diff_dir, "*.py"))
for file in files:
try:
differ = os.path.basename(file).split(".")[0]
if d... |
from __future__ import division
import numpy as np
import tensorflow.contrib.learn.python.learn as learn
from sklearn import metrics
batch_size = 32
def get_classification_score(train_encodings, train_labels, test_encodings, test_labels, steps):
feature_columns = learn.infer_real_valued_columns_from_input(train_... |
# Copyright 2015 ARM Ltd
#
# 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, soft... |
# coding=utf-8
from django.db import models
from django.utils import timezone
from django.utils.translation import ugettext_lazy as _
from django.contrib.auth.models import User
from django_resized import ResizedImageField
from .choices import *
from star_ratings.models import Rating
class AbsPerm(models.Model):
... |
"""Deck."""
from typing import Optional, List
import requests
import random
class Card:
"""Simple dataclass for holding card information."""
def __init__(self, value: str, suit: str, code: str):
"""Constructor."""
self.value = value
self.suit = suit
self.code = code
se... |
'''
闭包（python可以嵌套定义函数）
-内部函数对外部函数作用域里变量的引用（非全局变量），则称内部函数为闭包
-Python内函数也是对象
-闭包不能修改外部作用域的局部变量
'''
def addx(x):# x是引用环境
def adder(y): return x + y
return adder
# adder为闭包
c = addx(8)# c现在是一个函数
type(c)# function
c(10)# 相当于addx(8)(10) |
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
import copy
class Solution:
def pathSum(self, root: TreeNode, sum: int) -> List[List[int]]:
if root is None: return []
result = []
def dfs(nod... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import sys, getopt
def main(argv):
inputfile = ''
outputfile = ''
try:
opts, args = getopt.getopt(argv,"hf:t:",["ifile=","text="])
except getopt.GetoptError:
print 'Error: SVGtoPDFfromText.py -f <inputfile> -t <text>'
sys.exit(2)
for opt, arg i... |
import os
import re
from os import walk, getcwd
import csv
"""-------------------------------------------------------------------"""
""" Configure Paths"""
valid_txt_path = 'img_handshake_oznaczone/'
detected_txt_path = 'img_handshake_wyliczone/'
outpath = "CSV_dic/"
""" Get input text file list """
txt_name_list ... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu May 21 14:59:55 2020
@author: ganesh
"""
import pandas as pd
mail = pd.read_csv('/home/ganesh/Desktop/SpamClassifier-master/smsspamcollection/SMSSpamCollection', sep='\t',
names=["label", "message"])
# the above note pad is ... |
'''
if a image (e.g., segmentation maps) is composed of several components, but there are some noise, which are in form of isolated components
we can then remove the extra noise with following codes
Dong Nie
12/17/2016
'''
import numpy as np
import SimpleITK as sitk
from multiprocessing import Pool
import os... |
import random, string
def rndText(letters=15, lines=3, spaces=5):
return "\n".join("".join((random.choice(string.letters + ' ' * spaces) for _ in xrange(letters))) for _ in xrange(lines))
RESET = '\x1b[0m'
BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = ['\x1b[1;{}m'.format(30+i) for i in range(8)]
i... |
import numpy as np
# unique class values
def y_Encoder(classList):
num_class = len(classList)
classDict = {}
for i,classElem in enumerate(classList):
code = np.zeros((num_class,))
code[i] = 1.0
classDict[classElem] = code
return classDict
# from nltk.corpus import wordnet as ... |
x = int(input('Quanti voti ha ricevuto il 1° candidato? '))
y = int(input('Quanti voti ha ricevuto il 2° candidato? '))
z = x+y
d = (x/z)*100
u = (y/z)*100
print('Percentuale 1° candidato: ', d, '%')
print('percentuale 2° candidato: ', u, '%')
if d>u :
print('Il primo candidato ha vinto!')
if d<u :
pr... |
import orderbook as ob
o = ob.Orderbook('new_orderbook.h5')
o.read_data('SPY','order_book')
o.rollup_orderbook()
o.plot_bid_ask_prices()
o.plot_bid_ask_spread()
o.plot_interpacket_gap()
o.plot_order_traffic(40)
|
from os import path
d = path.dirname(__file__)
d = '/'.join(d.split('/')[:-2])
audio_num_mel_bins = 80
audio_sample_rate = 16000
num_freq = 513
symbol_size = 256
n_fft = 1024
rescale = True
rescaling_max = 0.999
hop_size = 256
win_size = 1024
frame_shift_ms = None
preemphasize = True
preemphasis = 0.97
min_level_db = ... |
from django.test import TestCase
from django.contrib.auth.models import User
from django.test import Client
import json
from assets.constants import SUPERVISOR, ADMIN
from authentication.models import UserRole
from authentication.tests.helper_functions import create_new_user, log_in
class AuthenticationViewTestCase(... |
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
class preprocess:
def __init__(self, FLAGS):
self.dataset_path = FLAGS.dataset_path
def Mnist2data(self):
self.mnist = input_data.read_data_sets(self.dataset_path+"/MNIST_data/", one_hot=True)
... |
real = float(input('\nDigite um valor em Reais: R$'))
peso = real * 13.63
iene = real * 19.80
dolar = real / 5.33
euro = real / 6.33
libra = real / 7.00
print('\nCONVERSOR DE MOEDAS')
print('-'*25)
print('Peso Argentino: $ {:.2f}' .format(peso))
print('Iene: ¥ {:.2f}' .format(iene))
print('Dolar: U$ {:.2f}' .format(dol... |
import os
from contextlib import contextmanager
try:
import psycopg2cffi as psycopg2
except ImportError:
import psycopg2
import queries
DB_CONNECT = os.getenv('NHLDB_CONNECT')
@contextmanager
def session(connect=None, pool_size=10, is_tornado=False):
if connect is None:
connect = DB_CONNECT
... |
import config.config as config
# Decoder class for use with a rotary encoder.
class decoder:
"""Class to decode mechanical rotary encoder pulses."""
def __init__(self, pi, rot_gpioA, rot_gpioB, switch_gpio, rotation_callback, switch_callback):
"""
Instantiate the class with the p... |
#!/usr/bin/env python
#==============================================================================
# gtf2juncs.py
#
# Shawn Driscoll
# 20160819
#
# Gene Expression Laboratory, Pfaff
# Salk Institute for Biological Studies
#
# Print out a file of junctions from a GTF annotation. this will include
# gene name, id, st... |
"""
Script to easily read in and plot the results of BestTrack output
Example Usage: python plotBestTrack.py 20150408_20150409 -i tracks
"""
import argparse
import datetime
from datetime import timedelta
import time
import numpy as np
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import s... |
import flask_bootstrap
from flask_wtf import form
from flask import request
import forms
import time
from forms import *
from flask import abort
from werkzeug.exceptions import Unauthorized
from flask import Flask, render_template, session, Response, request
from flask import render_template, flash, redirect, url_for
f... |
from __future__ import print_function, division
import os, json, random
from PIL import Image
import numpy as np
import torch
import torchvision
from torch.utils.data import Dataset
from envs.config import Config
from torchvision import transforms
import cv2
import utils.video_transforms as video_transforms
#import vid... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# camera.py
# Copyright (c) 2017-2021, Richard Gerum
#
# This file is part of the cameratransform package.
#
# cameratransform is free software: you can redistribute it and/or modify
# it under the terms of the MIT licence.
#
# cameratransform is distributed in the hope th... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
this module is to inspect keys, expecially keys with colon.
'''
import audit
import re
import json
import codecs
OSM_PATH = "sample.osm"
OUTPUT = "inspect_keys.json"
get_element = audit.get_element
LOWER_COLON = audit.LOWER_COLON
'''
The functi... |
from django.db import models
from django.contrib.auth.models import User
# Create your models here.
class Profile(models.Model):
GENDER = (
('M', 'Male'),
('F', 'Female')
)
user = models.OneToOneField(User)
age = models.IntegerField(default=0)
gender = models.CharField(max_length=1,... |
# -*- coding: utf-8 -*-
"""
Created on 2018/11/7 10:34
@author: royce.mao
# 构造第2阶段，小图片数字的识别检测网络
"""
from __future__ import print_function
from __future__ import absolute_import
from keras.models import Model
from keras.layers import Conv2D, Reshape, Input, Activation, Convolution2D, MaxPooling2D, ZeroPadding2D, Add, B... |
# -*- coding: utf-8 -*-
import cv2
import sys
import face_recognition
import os
import MySQLdb
import numpy as np
from datetime import datetime
import databaseScript
path = "ImagesAttendance"
images = []
classNames = []
myList = os.listdir(path)
# print(myList)
for cl in myList:
curImage = cv2.imread(f'{path}/{cl}'... |
"""Add first/last name fields to user table.
Revision ID: 81162fe5d987
Revises: 4e8beae024e9
Create Date: 2018-11-28 22:14:00.933976
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '81162fe5d987'
down_revision = '4e8beae024e9'
branch_labels = None
depends_on = ... |
#remove dublets
List=[1,2,4,7,22,3,5,6,3,1,22,1,4,5,2,3,4,5,6,7,5]
NewList=[]
for number in List:
if number not in NewList:
NewList.append(number) #append means- put into
print(NewList)
#sort list
NewList.sort()
print(NewList)
|
import pygame
import time
import random
import numpy as np
from PIL import Image
import env
from game.Board import BoardSingleton
from game.Snake import Snake
from game.Food import Food
from game.EventListener import EventListener
class SnakeGameEnv():
def __init__(self):
self.board = BoardSingleton.getI... |
import math
# import matplotlib.pyplot as plt
import numpy as np
from ... environment.simulator.models import Simulation
from ... import db
# To differentiate first and last from movement display
MARKER_FIRST = {
'marker': "o",
'markerfacecolor': "green",
'markersize': "14",
... |
# coding: utf-8
# # Introducing Pandas
#
# Pandas is a Python library that makes handling tabular data easier. Since we're doing data science - this is something we'll use from time to time!
#
# It's one of three libraries you'll encounter repeatedly in the field of data science:
#
# ## Pandas
# Introduces "Data F... |
""" Captcha.Visual.Backgrounds
Background layers for visual CAPTCHAs
SimpleCaptcha Package
Forked from PyCAPTCHA Copyright (C) 2004 Micah Dowty <micah@navi.cx>
"""
from simplecaptcha.visual import Layer, pictures
import random
from PIL import Image, ImageDraw
class SolidColor(Layer):
"""A solid color background... |
import imapclient
import pyzmail
imapObj = imapclient.IMAPClient('imap.gmail.com', ssl=True)
imapObj.login(' chokkadibhat@gmail.com ', ' abhI$hek15 ')
imapObj.select_folder('INBOX', readonly=True)
UIDs = imapObj.search(['SINCE 05-Jul-2014'])
#UIDs have list of message ID
rawMessages = imapObj.fetch([40041], ['BO... |
from django.urls import path
from . import views
app_name = 'logtest'
urlpatterns = [
path('', views.IndexView.as_view(), name='index'),
path('today_access', views.TodayAccessView.as_view(), name='today_access'),
path('recent_log_table', views.RecentLogView.as_view(), name='recent_log_table'),
path('e... |
from os import environ
'''
smtplib is a less secure method than google auth.
To use google auth, see https://github.com/shankarj67/python-gmail-api
'''
import smtplib
def send_email(ads_msgs):
#ads_msgs: a list of strings.
gmail_bot = environ['gmail_bot']
gmail_bot_pwd = environ['gmail_bot_pwd']
sent... |
import pytest
import numpy as np
from astropy import units as u
from ..flux import compute_flux
def strip_parentheses(string):
return string.replace('(', '').replace(')', '')
COMBINATIONS = \
[
(np.array([1, 2, 3]) * u.Jy, u.Jy, {}, 6 * u.Jy),
(np.array([1, 2, 3]) * u.mJy, u.Jy, {}, 0.006 * u.Jy),
... |
from rest_framework.serializers import ModelSerializer, ReadOnlyField
from .models import Investment as InvestmentModel
class InvestmentSerializer(ModelSerializer):
investmentId = ReadOnlyField(source='id')
class Meta:
model = InvestmentModel
fields = ['investmentId', 'username', 'amount', '... |
#!/usr/bin/env python
# get_all_kmers.py
seq = 'GCCGGCCCTCAGACAGGAGTGGTCCTGGATG'
kmer_length = 7
stop = len(seq) - kmer_length + 1
for start in range(0, stop):
kmer = seq[start:start + kmer_length]
print(kmer)
|
#!/usr/bin/env python3
import os
import sys
import gzip
from Bio import SeqIO
#functions for trimming and merging fastq files, and characterizing fastq files
def cut_primers(file, primer, raw_dir, trimmed_dir):
#Cut primer sequences off from beginning of a read and send to new "trimmed" file
#Input: zipped fa... |
# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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 a... |
bp = list(input())
ab = "abcdefghijklmnopqrstuvwxyz"
AB = "abcdefghijklmnopqrstuvwxyz".upper()
for a in ab:
p = list(filter(lambda x: x != a and x != a.upper(), bp))
Done = False
while not Done:
Done = True
i = 1
while i < len(p):
if (p[i] in ab and p[i-1] == p[i].upper... |
import sys
import os
import argparse
import json
import csv
import numpy as np
import matplotlib.pyplot as plt
from sklearn import model_selection
from sklearn.cross_decomposition import PLSRegression
from sklearn.metrics import mean_squared_error, r2_score
import model_io
import pls_analysis
fontSize = 8
totalItems... |
from django.shortcuts import render
from .models import Price, Site
# Create your views here.
def home (request):
return render(request, 'home.html')
def prices(request):
prices = Price.objects.order_by('price_base')
return render(request, 'prices.html', {'prices': prices})
def sites(request):
sites ... |
# -*- coding: utf-8 -*-
# from subprocess import *
# import threading
import time
import subprocess
import tornado.process
gProjectName = "PD_103023_ELK"
gVersion="6.6.6.6"
gCmdLine = "start -branch %s -setVersion %s -uploadFtp -signature\n"
# gProcess = subprocess.Popen('ffmpeg.exe', bufsize=10240, s... |
#!/usr/bin/python
import random
def lessthan(test, pivot):
return test < pivot
def greaterthan(test, pivot):
return pivot < test
def partition(a, left, right, predicate):
pivot = a[right]
il = left
ir = right
while il < ir:
while il < right and predicate(a[il], pivot):
... |
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 17 11:05:50 2018
@author: dell
"""
from tkinter import *
from PIL import Image, ImageTk
from tkinter.messagebox import *
import main3x1
import main3x2
import main3x3
import main3x4
import main3x5
import main3x6
import qjbl
qjbl.bl()
def info():
'... |
import os
from setuptools import setup, find_packages
import distutils.cmd
import distutils.log
from version import get_git_version
VERSION, SOURCE_LABEL = get_git_version()
PROJECT = 'dossier.models'
AUTHOR = 'Diffeo, Inc.'
AUTHOR_EMAIL = 'support@diffeo.com'
URL = 'http://github.com/dossier/dossier.models'
DESC = ... |
#coding:utf-8
from django.shortcuts import render, render_to_response
from django.contrib import auth
# Create your views here.
def login(request, **kwargs):
print "into login"
'''
response = render_to_response('login/login.html')
# 在客户端Cookie中添加Post表单token，避免用户重复提交表单
response.set_cookie("postToken... |
# Generated by Django 3.1.3 on 2020-11-25 12:02
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Initial_Contact',
fields=[... |
"""
Using for loop to calculate the summary from 1 to 100
"""
sum = 0
for x in range(1,101):
sum += x
print("The summary from 1 to 100 is %f" % sum)
############################################################
"""
Using for-in loop to calculate the even summary from 1 to 100
"""
sum = 0
for y in range(0, 101, ... |
import os
import SocketServer
from ComputerVision.FaceDetector import FaceDetector
from ComputerVision.CV2Wrapper import CV2Wrapper
from Database.DBWrapper import DBWrapper
class WebInterfaceTCPHandler(SocketServer.BaseRequestHandler):
"""
The request handler class for our server.
It is instantiated onc... |
import os, sys
sys.path.append('/var/scalak/scalakweb')
os.environ['PYTHON_EGG_CACHE'] = '/var/scalak/python_egg_cache'
from paste.deploy import loadapp
application = loadapp('config:/var/scalak/scalakweb/production.ini')
|
#!/usr/bin/python
import sys
flag=0
for input_line in sys.stdin:
line = input_line.strip().split(",")
if (flag ==0):
columns=line
flag=1
else:
disno = float(line[11])
print "{0}\t{1}".format(disno,str(input_line.strip())) |
from bs4 import BeautifulSoup
data = open('/home/fenris/work/Internshit/Kamtech/out/Bike Rental System.html','r')
soup = BeautifulSoup(data, 'lxml')
inner_ul = soup.find_all('ul')
lists = {}
for ultag in soup.find_all('ul'):
temp = []
for litag in ultag.find_all('li'):
temp.append(litag.text.split)
... |
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
random_array = np.linspace(0,2*np.pi,100) #generamos el array con 100 elementos aleatorios entre 0 y 2*PI
array_sin = np.sin(random_array) #generamos el seno de todos los elementos anteriores
array_cos = np.cos(random_array) #generamos el cos... |
# -*- coding: utf-8 -*-
def booleNett(phrase):
'''
phrase : chaîne de caractères.
Apairage des parenthèses nécessaires, espaces tolérés, tous les autres caractères hors opérateurs sont considérés comme variables
'''
# 1-On enlève les espaces
phrase=phrase.decode(encoding='UTF-8')
phrase=phr... |
import random
from django.core.management.base import BaseCommand
from django.contrib.admin.utils import flatten
from django_seed import Seed
from playlists import models as playlist_models
from users import models as user_models
from songs import models as song_models
class Command(BaseCommand):
"""
class: ... |
"""
Example explaining the peculiriaties of evaluation
"""
from ml_recsys_tools.datasets.prep_movielense_data import get_and_prep_data
import pandas as pd
from ml_recsys_tools.data_handlers.interaction_handlers_base import ObservationsDF
from ml_recsys_tools.recommenders.lightfm_recommender import LightFMRecommender
... |
import psycopg2
connect_str = "dbname='empleado' user='cursoPython'host='localhost' password='1234567890'"
conexion = psycopg2.connect(connect_str)
cur = conexion.cursor() #
rows= cur.execute("SELECT * FROM empleado")
rows= cur.fetchall()
for row in rows:
print("ID: ",row[0],"\nNombre: ",row[1],row[2],"\nSueldo: "... |
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from fbprophet import Prophet
# setting the Seaborn aesthetics.
sns.set(font_scale=1.3)
df = pd.read_csv('ts_df.csv')
m = Prophet()
m.fit(df)
forecast = m.predict(df)
fig = m.plot_components(forecast)
plt.show()
|
#-*- coding: utf-8 -*-
from ElasticSearchManager import esManager
class EVElasticSearch:
"""Base Class for EV Data Objects"""
_internalCount = 0
_es = esManager()
def __init__(self):
self._internalCount = self._internalCount + 1
def showCount(self):
return self._internalCount
... |
from transformers import GPT2LMHeadModel, BertTokenizer, GPT2Config, TrainingArguments, Trainer
import torch
import os
import argparse
import random
import numpy as np
import sys
sys.path.append('/home/user/project/text_generation/')
from src.util import read_data, split_data
from src.text_keywords_generation.datase... |
import atm.database as db
from utilities import *
eval = db.Database('sqlite', '../../atm.db')
################## database and datarun
# print_hp_summary(eval, 1)
# print_summary(eval, 1)
print_method_summary(eval, 1) |
from typing import Union, List
import requests
from Summary import Summary
from Provinces import Provinces
from SummaryAll import SummaryAll
from SummaryByProvince import SummaryByProvince
from SummaryByRegion import SummaryByRegion
class CovidSdk:
__split_data = None
@staticmethod
def summary(province:... |
#!/usr/bin/python3
import os
from formula import formula
insightType = os.environ.get("INSIGHT_TYPE")
contribution = os.environ.get("CONTRIBUTION")
formula.Run(insightType, contribution)
|
from django.db import models
from django.contrib.auth.models import AbstractUser
from django.db.models.signals import post_save,pre_save
from django.dispatch import receiver
from django.contrib.auth.models import UserManager
# Create your models here.
USER_CHOICES=(
("PATIENT", "PATIENT"),
("DOCTOR", "DOCTOR"... |
from ply import lex
literals = ['[', ']']
tokens = ['PLUS', 'MINUS', 'LSHIFT', 'RSHIFT', 'OUTPUT', 'INPUT']
t_PLUS = '\+'
t_MINUS = '-'
t_LSHIFT = '<'
t_RSHIFT = '>'
t_OUTPUT = '\.'
t_INPUT = ','
t_ignore = ' \t'
def t_NEWLINE(t):
r'\n'
pass
def t_error(t):
print("Illegal Character... |
SIGN_MASK = 1 << 32
def max_old(a, b):
if (a - b) & SIGN_MASK:
return b
return a
def max_with_overflow(a, b):
# overflow would be caused by different signed params
# e.g. a = INT_MAX (2^31 - 1) and b = -15
if (a & SIGN_MASK and not b & SIGN_MASK) or (not a & SIGN_MASK and not b & SI... |
from sqlalchemy import DateTime, Float, create_engine, Column, String, Integer, ForeignKey
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.exc import IntegrityError
from sqlalchemy.sql import func
from flask import Flask, request, jsonify
... |
import boto3
import sys
sys.path.append("./packages")
import mysql.connector as mysql_connector
import tornado.escape as tornado
if __name__ == '__main__':
response = boto3.client('health', region_name='us-east-1').describe_event_details_for_organization(
organizationEventDetailFilters=[
{
... |
from __future__ import print_function
import platform
import sys
import struct
import socket
import threading
import types
import time
from .config import DEBUG, HOST, PORT, MSG_TIMEOUT, SOCK_TIMEOUT, GET_PORT_ATTEMPT_COUNT
from ._datatypes import *
from .utils import show_error_message
EVENTS_NAMES = (
'evitem... |
# Adapted from Graham Neubig's Paired Bootstrap script
# https://github.com/neubig/util-scripts/blob/master/paired-bootstrap.py
import numpy as np
from sklearn.metrics import f1_score, precision_score, recall_score
from tqdm import tqdm
EVAL_TYPE_ACC = "acc"
EVAL_TYPE_BLEU = "bleu"
EVAL_TYPE_BLEU_DETOK = "bleu_detok"... |
#encoding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
class Swish(nn.Module):
def __init__(self):
super(Act_op, self).__init__()
def forward(self, x):
x = x * F.sigmoid(x)
return x
'''
## 由于 Function 可能需要暂存 input tensor。
## 因此，建议不复用 Function 对象，以避免遇到内存提前释... |
#YOur Script is was update by Hirokaazo Nagata
#fb : Hirokazo Nagata
#gmail : ziadabouelfarah2@gmail.com
import os,time
print('''
XX MMMMMMMMMMMMMMMMss''' '''ssMMMMMMMMMMMMMMMM XX
XX MMMMMMMMMMMMyy'' ''yyMMMMMMMMMMMM XX
XX MMMMMMMMyy'' ... |
import docx
import os
''' Function: read_file(file_name, item_type)
Parameters: file_name - the name of the file to be read.
item_type - user-inputted search term to specify what is parsed for in the document.
os.path.dirname(os.path.abspath(__file__))+"\\" is the current working director... |
"""
This is a setup.py script generated by py2applet
Usage:
python setup.py py2app
"""
from setuptools import setup
with open("README.md", 'r') as f:
long_description = f.read()
APP = ['BuildTool\\main.py']
DATA_FILES = []
OPTIONS = {}
setup(
app=APP,
data_files=DATA_FILES,
options={'py2app': O... |
from github import Github
#Hesabımıza Giriş Yapıyoruz.
try:
git_hesap = Github("K_Adı", "Sifre")
#print("Hesabınıza başarı ile giriş yapıldı.")
except:
print("Hesabınıza giriş başarısız!")
#Githubda arama yapmak ve çıktı almak.
try:
repos = git_hesap.search_repositories(query="language:py... |
from Core.Globals import *
from Mapping import Mapping, E
class VehicleMapping(Mapping):
def __init__(self,target):
self.target = target
class Keyboard1Mapping(VehicleMapping):
IMAGE = 'Keyboard1Mapping.png'
def __init__(self,target):
VehicleMapping.__init__(self,target)
... |
import psycopg2
import pandas
import numpy
import objects
import config
db = objects.Database(config.server, config.database, config.user, config.password)
# Read population data.
dfPopulation = pandas.read_excel(r"C:\Users\hoged\OneDrive\Skrivebord\Speciale\Data\Population (2019).xlsx", skiprows=2, nrows=106, usec... |
import unittest
from src.core import formi
# [] TODO: add test to combine more than 1 operations
class FormiCoreTestCase(unittest.TestCase):
""" Test formi.py core functions """
def test_join_string_function(self):
result = formi.join_string('the\nquick')
expected = 'the, quick'
sel... |
from PyQt5.QtWidgets import *
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtMultimedia import *
from random import randint
from doudizhu import poker_distribute, pattern_spot, cards_validate, strategy, compare, ai_jiaofen, rearrange, print_cards
import json, socket, threading, struct, sys, os, doudi... |
from django.conf.urls import url
from . import views
from django.conf import settings
from django.conf.urls.static import static
import django.contrib.staticfiles
urlpatterns = [
url(r'^amadon$', views.index),
url(r'^amadon/checkout$', views.checkout),
url(r'^amadon/buy$', views.buy),
] |
"""
leetcode 108
"""
def convert_sorted_array_to_bst(nums):
if not len(nums):
return None
half = len(nums) // 2
root = TreeNode(nums[half])
root.left = convert_sorted_array_to_bst(nums[:half])
root.right = convert_sorted_array_to_bst(nums[half+1:])
return root
|
import numpy as np
from core.soft import bezier
from numpy import sin, cos
from core.anim import Animation
from core.obj import Vector, Line, Curve
sHandSpeed = 12
mHandSpeed = sHandSpeed/60
hHandSpeed = mHandSpeed/12
b = bezier([0, 0, 0, 1, 1, 1, 1, 1])
def update_s(s, t, tmax):
t *= -sHandSpeed * 2*np.pi
t... |
import tensorflow as tf
from BNN import readData
import numpy as np
tf.reset_default_graph()
def conv2d(x, W):
"""conv2d returns a 2d convolution layer with full stride."""
return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding='SAME')
def max_pool_2x2(x):
"""max_pool_2x2 down samples a feature map by ... |
#!/usr/bin/env python
from logging import basicConfig, getLogger, DEBUG
logger = getLogger(__name__)
OBJECT = 'Logical Port'
MODULE = 'Logical Switching'
def get_list(client, logical_switch_id=None):
"""
This function returns all T0 logical routers in NSX
:param client: bravado client for NSX
:retu... |
import numpy as np
import pandas as pd
import faiss
from sentence_transformers import SentenceTransformer
from tqdm import tqdm
class Clusterer:
def __init__(self, data: pd.DataFrame, model=None):
self.model = model
self.data = data
@staticmethod
def chunks(lst, n):
for i in rang... |
from operator import itemgetter
import psycopg2
import networkx as nx
import matplotlib.pyplot as plt
from networkx.drawing.nx_agraph import graphviz_layout
from subprocess import call
import pandas as pd
def select(query):
con = None
result = None
try:
con = psycopg2.connect(database='MovieLens'... |
import skimage
from skimage import io
import os
import glob
IMAGE_PATH = 'data/raw/images_train_rev1/'
IMAGE_BW_PATH = 'data/bw/images_train_rev1/'
if not os.path.isdir('data/bw/'):
os.mkdir('data/bw/')
if not os.path.isdir(IMAGE_BW_PATH):
os.mkdir(IMAGE_BW_PATH)
images = glob.glob(
os.path.join(IMAGE_PA... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
# 1. variable definition
x1 = 1.0
x1_node = {"requires_grad": True, "grad": 0, "backward_branches": []}
x2 = np.pi / 4
x2_node = {"requires_grad": True, "grad": 0, "backward_branches": []}
# 2. forward propagation
y1 = 2 * x1
y1_node = {
"requir... |
# coding: utf-8
import MySQLdb
import datetime, time
import csv
host = 'localhost'
db = MySQLdb.connect(host, 'root', 'vis_2014', 'FinanceVis')
cursor = db.cursor()
headers = ["Date", "Open", "High", "Low", "Close", "Volume", "Adj Close",
"predict_news_word", "predict_twitter_word", "bias_news_word", "bias... |
with open('../result/csi.bin', 'U') as inf:
for line in inf:
feats = line.strip().split(' ')
print len(feats)
break
|
from ximea import xiapi
import cv2
import time
from camera_setting import white_balance_adjustment
def adjust_camera(cam):
img =xiapi.Image()
while cv2.waitKey(33) != 27:
cam.get_image(img)
data = img.get_image_data_numpy()
cv2.imshow("img", data)
cam = xiapi.Camera()
# start communic... |
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