index int64 0 1,000k | blob_id stringlengths 40 40 | code stringlengths 7 10.4M |
|---|---|---|
18,800 | 8b884e3c246ccd896c2e40d1754d8f1e3a04c556 | import heapq
import sys
input = sys.stdin.readline
dx = [-1, 0, 0, 1]
dy = [0, -1, 1, 0]
n = int(input())
graph = []
for _ in range(n):
graph.append(list(map(int, input().rstrip())))
visited = [[False for _ in range(n)] for _ in range(n)] # 비용 대신 방문 여부 저장
q = []
visited[0][0] = True
cnt = 0
heapq.heappush(q, (cnt, 0, 0)) # cnt 기준 정렬
while q:
cnt, x, y = heapq.heappop(q)
if x == n-1 and y == n-1: # 최종 목적지 도달 시 cnt 출력 및 종료
print(cnt)
break
for i in range(4):
nx = x + dx[i]
ny = y + dy[i]
if 0 <= nx < n and 0 <= ny < n and not visited[nx][ny]:
visited[nx][ny] = True
if graph[nx][ny] == 1:
heapq.heappush(q, (cnt, nx, ny))
else: # 검은 방인 경우 흰 방으로 바꿔주고 cnt++
graph[nx][ny] = 0
heapq.heappush(q, (cnt+1, nx, ny))
|
18,801 | 2422e360495dcc41317369575c2793df4cad4d2e | # SPDX-License-Identifier: BSD-2-Clause
# Copyright (C) 2021 Intel Corporation.
from python_framework.cmd_helper import CMD_helper
import pytest
class Test_hbw_env_var(object):
environ_err_threshold_test = "../environ_err_hbw_threshold_test"
cmd_helper = CMD_helper()
def run_test(self, threshold, kind):
env = "MEMKIND_HBW_THRESHOLD=" + str(threshold)
bin_path = self.cmd_helper.get_command_path(
self.environ_err_threshold_test)
command = " ".join([env, bin_path, kind])
output, retcode = self.cmd_helper.execute_cmd(command)
print(output)
fail_msg = (f"Test failed with error: \nExecution of: \'{command}\'"
f" returns: {retcode} \noutput: {output}")
assert retcode == 0, fail_msg
@pytest.mark.parametrize("kind", ["MEMKIND_HBW", "MEMKIND_HBW_ALL"])
def test_TC_MEMKIND_hbw_threshold_default_value(self, kind):
threshold = 204800
self.run_test(threshold, kind)
@pytest.mark.parametrize("kind", ["MEMKIND_HBW", "MEMKIND_HBW_ALL"])
def test_TC_MEMKIND_hbw_threshold_negative_value(self, kind):
threshold = -1
self.run_test(threshold, kind)
@pytest.mark.parametrize("kind", ["MEMKIND_HBW", "MEMKIND_HBW_ALL"])
def test_TC_MEMKIND_hbw_threshold_low_value(self, kind):
threshold = 1
self.run_test(threshold, kind)
@pytest.mark.parametrize("kind", ["MEMKIND_HBW", "MEMKIND_HBW_ALL"])
def test_TC_MEMKIND_hbw_threshold_high_value(self, kind):
threshold = 1024 * 1024 * 1024
self.run_test(threshold, kind)
|
18,802 | 203baf9cbb81b7127bd74f42662ba72c3f0d322e | file = open("input.in", "r");
def raw_input():
return file.readline();
cases_number = int(raw_input());
cases = [];
done = {};
out = '';
def process(cooker, size, n):
done[cooker] = n;
n+=1;
if not "-" in cooker:
return n;
low = 999999;
a = False;
for index in range(len(cooker)-size+1):
if cooker[index:index+size] == "-"*size:
a = True;
n+=1;
cooker = flip(cooker, index, size);
if a:
return process(cooker, size, n-1);
for index in range(len(cooker)-size+1):
if not flip(cooker, index, size) in done:
low = min(low, process(flip(cooker, index, size), size, n));
elif done[flip(cooker, index, size)]>n:
low = min(low, process(flip(cooker, index, size), size, n));
return low;
def flip(cooker, index, size):
return ''.join(["+" if ((index-1<i<index+size and cooker[i] == "-") or ((index>i or i>index+size-1) and cooker[i] == "+")) else "-" for i in range(len(cooker))]);
for case in range(cases_number):
last_input = raw_input().split(" ");
size = int(last_input[1]);
cooker = last_input[0];
done = {};
temp = process(cooker, size, 0) - 1;
if temp == 999998:
temp = "IMPOSSIBLE";
out = out + "Case #"+str(case+1)+": "+str(temp)+"\n";
print out
open("outputx.in", "w").write(out);
|
18,803 | cf21d33ec0bb1ef4c143a6226e50f80992e4701e | from ._pv import SolarLibrary, simulatePVModule, locToTilt, frankCorrectionFactors, simulatePVModuleDistribution
from ._score import scoreOpenfieldPVLocation
from ._workflow import workflowOpenFieldFixed, workflowOpenFieldTracking, workflowRooftop
|
18,804 | 803fecbd8b3ed7cedd97f1ddf194844122cc54b4 | def solution(total_lambs):
mmin, mmax = 0,0
temp = total_lambs
i = 1
while temp - i >= 0:
temp -= i
i <<= 1
mmin += 1
if total_lambs == 1: mmax = 1
elif total_lambs == 2: mmax = 2
l1, l2 = 1,1
mmax = 2
total_lambs -= 2
while(total_lambs - l1 - l2 >= 0):
total_lambs -= l1 + l2
mmax+=1
l1, l2 = l2, l1+l2
# print(l1,l2)
print(mmax, mmin)
return mmax - mmin
print(solution(2)) |
18,805 | dda2f74f4b001cff159592c00d4a5b4ebb2fbbf4 | Menu = {"The Original BBQ Chicken Chopped": ('salad', ["Chicken", "Onion"], 10),
'Chinese Chicken': ('salad', ['Chicken', 'Green Onion'], 20),
"Roasted Veggie": ('salad', ["LETTUCE", 'cabbage'], 1),
"Thai Chicken": ("pizza", ["chilli", "curry", "chicken"], 10),
"Wild Mushroom": ("pizza", ["white mushroom", 'yellow mushroom'], 10),
"Hawaiian": ("pizza", ["pineapple", "ham"], 10),
"Chicken Tequila Fettuccine": ("pastas", ["chicken", "tequila"], 15),
"Jambalaya Fettuccine": ("pastas", ['Fettuccine', 'salt', 'black pepper'], 16),
"Chicken Piccata": ("pastas", ["piccata", "rotten chicken"], 17)
}
def get_ingredient(name):
if name in Menu.keys():
return Menu[name][1]
else:
return list()
def get_price(name):
if name in Menu.keys():
return Menu[name][2]
else:
return 0
def get_category(name):
if name in Menu.keys():
return Menu[name][0]
else:
return "N/A"
|
18,806 | 7095b9c8ce73af2aec62a601f3be1391124484dc | """
Write a Python program to find the first triangle
number to have over n(given) divisors.
From Wikipedia: A triangular number is a number that is the
sum of all of the natural numbers up to a certain number.
For example, 10 is a triangular number because 1 + 2 + 3 + 4 = 10.
The first 25 triangular numbers are:
1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 78, 91, 105, 120, 136,
153, 171, 190, 210, 231, 253, 276, 300, 325, and 351.
A triangular number is calculated by the equation:
n(n+1)/2
The factors of the first five triangle numbers:
1: 1
3: 1, 3
6: 1, 2, 3, 6
10: 1, 2, 5, 10
15: 1, 3, 5, 15
In the above list 6 is the first triangle number to have over four divisors.
"""
from functools import reduce
def divisors(n):
exp_List = []
ctr = 0
divisor = 2
while divisor <= n:
while n % divisor == 0:
n = n / divisor
ctr += 1
if ctr != 0:
exp_List.append(ctr + 1)
divisor += 1
ctr = 0
return reduce(lambda n, y: n * y, exp_List, 1)
def n_divisors(n):
natural = 1
triangular_num = 0
while True:
triangular_num += natural
natural += 1
if divisors(triangular_num) > n:
break
return triangular_num
print(n_divisors(5)) # 28
print(n_divisors(100)) # 73920
|
18,807 | 87dad27b655093b07d57d755cabec1f0c254ddd4 | #! /usr/bin/python
import sched, time
import requests
import json
import sys
import serial
from time import sleep
s = sched.scheduler(time.time, time.sleep)
def do_something(sc):
print "Getting data..."
try:
bluetoothSerial = serial.Serial( "/dev/rfcomm0", baudrate=9600 )
line =""
flag = 0
email =""
id =""
while True:
for c in bluetoothSerial.read():
print c
if c == '~':
flag = flag + 1
print("Line: " + line)
if flag == 1:
email = line
line = ""
if flag == 2:
id = line
else:
line+=c
if flag == 2:
break
print email
print id
r=requests.post("http://ec2-52-35-75-223.us-west-2.compute.amazonaws.com:3000/attendance/mark",data={'email':email ,'course_id':id})
print r
resp = json.loads(r.text)
print resp
except:
e = sys.exc_info()[0]
sc.enter(2, 1, do_something, (sc,))
s.enter(1, 1, do_something, (s,))
s.run()
|
18,808 | 2574dbd87aacd9825bfcde5c72dd82febb1f7fc6 | from product_database.models import *
from product_database.database import *
from product_database.serializer import *
from product_database.crud import *
from fastapi_jwt_auth import AuthJWT
from fastapi import APIRouter, Depends,Response, status
from utils import *
from product_database.pdfmaker import PdfMaker,ExcelMaker
from starlette.responses import FileResponse
from .pydanticmodels import *
router = APIRouter()
@router.post("/api/category")
def postCategory(category:BasePostCategory,response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
if not get_category(category_name=category.categoryName):
category.created_by=Authorze.get_jwt_subject()
create_category(category)
return {Statuses.status_code:Statuses.HTTP_200_OK,Statuses.status:Statuses.success}
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:"Category already exists"}
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.put("/api/category/{category_id}")
def updateCategory(category_id:int,category:BaseupdateCategory,response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
cateObj=get_category(category_id=category_id)
if cateObj:
category.updated_by=Authorze.get_jwt_subject()
update_category(category,cateObj)
return {Statuses.status_code:Statuses.HTTP_200_OK,Statuses.status:Statuses.success}
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:"Category Not Found"}
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.delete("/api/category/{category_id}")
def deleteCategory(category_id:int,response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
cateObj=get_category(category_id=category_id)
if cateObj:
delete_category([category_id])
return {Statuses.status_code:Statuses.HTTP_200_OK,Statuses.status:Statuses.success}
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:"Category Not Found"}
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.get("/api/product")
def getAllproducts(response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
objs=get_all_products()
return {Statuses.status_code:Statuses.HTTP_200_OK,Statuses.status:Statuses.success,Statuses.count:objs.count(),Statuses.data: SerilizerMixin.serialize(objs,many=True),}
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.post("/api/product")
async def postProduct(product:BasePostProduct,response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
if not get_product(product_name=product.productName):
cateObj=get_category(category_name=product.categoryName)
if cateObj:
product.created_by=Authorze.get_jwt_subject()
product.category_id=cateObj.category_id
del product.categoryName
create_product(product)
return {Statuses.status_code:Statuses.HTTP_200_OK,Statuses.status:Statuses.success}
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:"Category Not Found"}
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:"Product already exists"}
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.put("/api/product/{product_id}")
def updateProduct(product:BaseUpdateProduct,product_id:int,response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
prodObj=get_product(product_id=product_id)
if prodObj:
if product.categoryName!=None:
cateObj=get_category(category_name=product.categoryName)
if cateObj:
product.category_id=cateObj.category_id
else:
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:"Category Not Found"}
del product.categoryName
product.updated_by=Authorze.get_jwt_subject()
update_product(product,prodObj)
return {Statuses.status_code:Statuses.HTTP_200_OK,Statuses.status:Statuses.success}
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:f"Product not found {product_id}"}
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.delete("/api/product/{product_id}")
def deleteProduct(product_id:int,response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
if get_product(product_id=product_id):
delete_product([product_id,])
return {Statuses.status_code:Statuses.HTTP_200_OK,Statuses.status:Statuses.success}
response.status_code=status.HTTP_400_BAD_REQUEST
return {Statuses.status_code:Statuses.HTTP_BAD_REQUEST,Statuses.status:Statuses.failed,Statuses.description:f"Product not found {product_id}"}
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.get("/api/products/exporttopdf")
def productsExportToPdf(response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
pdf=PdfMaker(format='A4')
pdf.set_title("Products List")
pdf.add_page()
validatedObjects=get_all_prodcuts_for_fileUpload()
pdf.makeData(validatedObjects)
pdf.output("productslist.pdf")
return FileResponse("productslist.pdf", media_type='application/octet-stream',filename="productslist.pdf")
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
@router.get("/api/products/exporttoexcel")
def productsExportToExcel(response:Response,Authorze:AuthJWT=Depends()):
Authorze.jwt_required()
try:
validatedObjects=get_all_prodcuts_for_fileUpload()
ExcelMaker().makeExcelSheet(validatedObjects)
return FileResponse("productslist.xls", media_type='application/octet-stream',filename="productslist.xls")
except Exception as exc:
response.status_code=status.HTTP_500_INTERNAL_SERVER_ERROR
ProjectUtils.print_log_msg(exc,ProjectUtils.EXCEPTION)
return {Statuses.status_code:Statuses.HTTP_500_INTERNAL_SERVER_ERROR,Statuses.status:Statuses.exception,Statuses.description:str(exc)}
|
18,809 | ac09aa50a89977384ff3161fd1c2f6f1e96dde16 |
# -*- coding: utf-8 -*-
w = open('arq3.txt','w')
w.write(open('arq.txt').read())
print(w.read()) |
18,810 | 177c8fb3df49f2f8e490c28d4f3b8a1be5557e12 | from flask import render_template, session, redirect, url_for
from . import main
from .forms import newGameForm
from .. import db
from ..models import Game
@main.route('/')
def index():
return '<h1>INDEX</h1>'
@main.route('/viewExistingGames')
def viewGames():
print(Game.query.all())
return '<h1>viewGames</h1>'
@main.route('/viewGameDetails/<game_id>',methods=['GET'])
def viewGameInfo(game_id):
game = Game.query.filter_by(id=game_id).all()
if game:
print(game)
else:
print('no game with that id')
return '<h1>viewing Game Information</h1>'
@main.route('/createGame', methods=['GET','POST'])
def createGame():
form = newGameForm()
db.create_all()
if form.validate_on_submit():
game = Game(rules=form.rules.data)
db.session.add(game)
db.session.commit()
return redirect('/viewExistingGames')
return render_template('createGame.html', form=form)
|
18,811 | 78c582631e025d38bb170d3b91b9362547f5549e | import csv
import math
##################################
# YOUR DESIRED FILENAME AND ROWS OF VALUES GO HERE
fileName = 'basicsine.csv'
rows = 1
##################################
with open(fileName, mode='w') as newFile:
fileWriter = csv.writer(newFile, lineterminator="\n")
amp, offset, pw = [], [], []
for i in range(64):
amp.append("amp{}".format(i))
offset.append("offset{}".format(i))
pw.append("pw{}".format(i))
headers = amp + offset + pw
headers.append("time")
fileWriter.writerow(headers)
for i in range(rows):
amp.clear()
offset.clear()
pw.clear()
for j in range(64):
if (j < 64):
ampVal = 32000 #YOUR FORMULAS FOR AMP, OFFSET, PHASEWORD GO HERE
offsetVal = 0
pwVal = 128 * (j//16)
amp.append(ampVal)
offset.append(offsetVal)
pw.append(pwVal)
else:
amp.append(0)
offset.append(0)
pw.append(0)
newrow = amp + offset + pw
time = 4096 #YOUR TIME FORMULA GOES HERE
newrow.append(time)
fileWriter.writerow(newrow)
|
18,812 | d398d028741443b5f7541e32a56dfc640c132298 | # Write a Python program to create a lambda function that adds 15 to a given
# number passed in as an argument, also create a lambda function that multiplies
# argument x with argument y and print the result.
add_15 = lambda x: x + 15
print(add_15(2))
mul = lambda x, y: x*y
print(mul(3,5))
|
18,813 | 845206ec19cfc8be2b5b6a06476384a4bb1fa661 | # -*- coding: utf-8 -*-
import numpy as np
import sys
from collections import deque
from collections import defaultdict
import heapq
import collections
import itertools
import bisect
from scipy.special import comb
import copy
sys.setrecursionlimit(10**6)
def zz():
return list(map(int, sys.stdin.readline().split()))
def z():
return int(sys.stdin.readline())
def S():
return sys.stdin.readline()[:-1]
def C(line):
return [sys.stdin.readline() for _ in range(line)]
N, M = zz()
A = zz()
A = [-a for a in A]
heapq.heapify(A)
for i in range(M):
money = heapq.heappop(A)
money *= -1
money //= 2
money *= -1
heapq.heappush(A, money)
print(sum(A)*-1)
|
18,814 | 21df4cd59357093814ec6140923fdaa29126a78b | p,p2=input().split()
p=int(p)
p2=int(p2)
c=0
temp=list(map(int,input().split()))
for a in temp:
if(a==p2):
c=c+1
break
if(c!=0):
print("yes")
else:print("no")
|
18,815 | 1b6475733f62e2fefe59b816ac62b31522f17350 | import json
import os
import requests
from dotenv import load_dotenv
from kafka import KafkaProducer
from time import sleep
#---------------------------------------------------------------------------------------------------
def retrieve_response(
URL:str,
key: str,
host:str)->list:
"""Function returns list of JSON objects from REST API endpoint.
@URL: str - URL of REST API to retrieve items from
@key: str - API Key of REST API to retrieve items from
@host: str - Hostname of API to retrieve items from
"""
headers = {
"x-rapidapi-key": key,
"x-rapidapi-host": host
}
request = requests.get(URL, headers = headers)
return json.loads(request.text)
#Loading Environment variables ---
load_dotenv()
API_KEY = os.getenv("API_KEY")
API_HOST = os.getenv("API_HOST")
#Requesting REST API ---
covid_data = retrieve_response(
URL = "https://who-covid-19-data.p.rapidapi.com/api/data",
key = API_KEY,
host = API_HOST
)
#Sending data to Kafka topic ---
producer = KafkaProducer(
bootstrap_servers = "localhost:9092",
value_serializer = lambda message: json.dumps(message).encode("utf8")
)
for record in covid_data:
sleep(3)
producer.send("covid_data", record)
|
18,816 | 437f4fbf2a6b54d9faa87766117de95238ec6871 | from flask import request, jsonify, render_template, flash, redirect, url_for
from flask_login import current_user, login_user, logout_user, login_required
from werkzeug.urls import url_parse
from datetime import datetime
from app import app, db
from app.forms import LoginForm, RegistrationForm, EditProfileForm, ProjectForm, EmptyForm, ResetPasswordRequestForm, ResetPasswordForm
from app.models import User, Project
from app.email import send_password_reset_email
from engine import recommend, api_recommend, find
import pandas as pd
import pickle
# read second column of dataset to obtain project names
df = pd.read_csv('TopStaredRepositories.csv', usecols=[1])
# load model which has already been saved using pickle library
tfidf_vectorizer = pickle.load(open('tfidf_vectorizer.pickle', 'rb'))
cv = pickle.load(open('count_vectorizer.pickle', 'rb'))
# call method before processing any requests
@app.before_request
def before_request():
if current_user.is_authenticated:
current_user.last_seen = datetime.utcnow()
db.session.commit()
# index endpoint
@app.route('/', methods=['GET', 'POST'])
@app.route('/index', methods=['GET', 'POST'])
@login_required
def index():
form = ProjectForm()
if form.validate_on_submit():
project = Project(title=form.title.data, owner=current_user, description=form.description.data, language=form.language.data.upper(), git_url=form.git_url.data, tags=form.tags.data.lower())
db.session.add(project)
db.session.commit()
flash('Project created!')
# redirect to home page to avoid inserting duplicate posts
# if a user refreshes after submitting the form
# (post/redirect/get pattern)
return redirect(url_for('index'))
# get page number from request
page = request.args.get('page', 1, type=int)
projects = current_user.followed_projects().paginate(page, app.config['POSTS_PER_PAGE'], False)
# ternary operators to assign next page url and previous
# page url if there are more projects to display
next_url = url_for('index', page=projects.next_num) \
if projects.has_next else None
prev_url = url_for('index', page=projects.prev_num) \
if projects.has_prev else None
return render_template('index.html', title='Home', form=form, projects=projects.items, next_url=next_url, prev_url=prev_url)
# end of index endpoint
# explore endpoint
@app.route('/explore')
@login_required
def explore():
# get page number from request
page = request.args.get('page', 1, type=int)
projects = Project.query.order_by(Project.timestamp.desc()).paginate(page, app.config['POSTS_PER_PAGE'], False)
# ternary operators to assign next page url and previous
# page url if there are more projects to display
next_url = url_for('explore', page=projects.next_num) \
if projects.has_next else None
prev_url = url_for('explore', page=projects.prev_num) \
if projects.has_prev else None
return render_template('index.html', title='Explore', projects=projects.items, next_url=next_url, prev_url=prev_url)
# end of explore endpoint
# login endpoint
@app.route('/login', methods=['GET', 'POST'])
def login():
# redirect user to index page if they are already logged in
if current_user.is_authenticated:
return redirect(url_for('index'))
form = LoginForm()
# process form submission
if form.validate_on_submit():
# search db for user by username form data
user = User.query.filter_by(username=form.username.data).first()
# conditional for unsuccessful username search OR check_password returns false
if user is None or not user.check_password(form.password.data):
flash('Invalid username or password')
return redirect(url_for('login'))
# successful login
login_user(user, remember=form.remember_me.data)
# set next_page to next argument from request to handle redirects from login_required pages
next_page = request.args.get('next')
# redirect user to index page if no next argument was found, or if next argument contains a URL with another domain
if not next_page or url_parse(next_page).netloc != '':
next_page = url_for('index')
# redirect user to next page after successful login
return redirect(next_page)
# render login template if get request
return render_template('login.html', title='Sign In', form=form)
# end of login endpoint
# logout endpoint
@app.route('/logout')
def logout():
logout_user()
return redirect(url_for('index'))
# end of logout endpoint
# register endpoint
@app.route('/register', methods=['GET', 'POST'])
def register():
# redirect user to index page if they are already logged in
if current_user.is_authenticated:
return redirect(url_for('index'))
form = RegistrationForm()
# process form submission
if form.validate_on_submit():
# create new user object with form data as arguments
user = User(username=form.username.data, email=form.email.data)
user.set_password(form.password.data)
# add user to db
db.session.add(user)
db.session.commit()
flash('You have successfully registered!')
return redirect(url_for('login'))
# render register template if get request
return render_template('register.html', title='Register', form=form)
# end of register endpoint
# user profile endpoint
@app.route('/user/<username>')
@login_required
def user(username):
user = User.query.filter_by(username=username).first_or_404()
users = None
list_of_recs = find(user.id, cv)
print(list_of_recs)
if list_of_recs is not None:
new_df = pd.DataFrame(list_of_recs, columns=['id', 'score'])
new_df['id'] = new_df['id'] + 1
print(new_df)
user_ids = new_df['id']
users = User.query.filter(User.id.in_(user_ids))
following = user.followed.all()
# get followers using backref in association
followers = user.followers.all()
page = request.args.get('page', 1, type=int)
projects = user.projects.order_by(Project.timestamp.desc()).paginate(page, app.config['POSTS_PER_PAGE'], False)
next_url = url_for('user', username=user.username, page=projects.next_num) \
if projects.has_next else None
prev_url = url_for('user', username=user.username, page=projects.prev_num) \
if projects.has_prev else None
form = EmptyForm()
return render_template('user.html', title=f'{user.username}\'s profile', user=user, users=users, following=following, followers=followers, projects=projects.items, next_url=next_url, prev_url=prev_url, form=form)
# end of user profile endpoint
# user popup endpoint
@app.route('/user/<username>/popup')
@login_required
def user_popup(username):
user = User.query.filter_by(username=username).first_or_404()
form = EmptyForm()
return render_template('user_popup.html', user=user, form=form)
# end of user popup endpoint
# edit profile endpoint
@app.route('/edit_profile', methods=['GET', 'POST'])
@login_required
def edit_profile():
form = EditProfileForm(current_user.username)
if form.validate_on_submit():
current_user.username = form.username.data
current_user.about_me = form.about_me.data
db.session.commit()
flash('Your changes have been saved.')
return redirect(url_for('edit_profile'))
elif request.method == 'GET':
form.username.data = current_user.username
form.about_me.data = current_user.about_me
return render_template('edit_profile.html', title='Edit Profile', form=form)
# end of edit profile endpoint
# follow user endpoint
# TODO combine code for follow and unfollow routes to follow DRY best practices
@app.route('/follow/<username>', methods=['POST'])
@login_required
def follow(username):
form = EmptyForm()
if form.validate_on_submit():
user = User.query.filter_by(username=username).first()
if user is None:
flash('User {} not found.'.format(username))
return redirect(url_for('index'))
if user == current_user:
flash('You cannot follow yourself!')
return redirect(url_for('user', username=username))
current_user.follow(user)
db.session.commit()
flash('You are now following {}!'.format(username))
return redirect(url_for('user', username=username))
else:
return redirect(url_for('index'))
# end of follow user endpoint
# unfollow user endpoint
@app.route('/unfollow/<username>', methods=['POST'])
@login_required
def unfollow(username):
form = EmptyForm()
if form.validate_on_submit():
user = User.query.filter_by(username=username).first()
if user is None:
flash('User {} not found.'.format(username))
return redirect(url_for('index'))
if user == current_user:
flash('You cannot unfollow yourself!')
return redirect(url_for('user', username=username))
current_user.unfollow(user)
db.session.commit()
flash('You are no longer following {}.'.format(username))
return redirect(url_for('user', username=username))
else:
return redirect(url_for('index'))
# end of unfollow user endpoint
# reset password request endpoint
@app.route('/reset_password_request', methods=['GET', 'POST'])
def reset_password_request():
if current_user.is_authenticated:
return redirect(url_for('index'))
form = ResetPasswordRequestForm()
if form.validate_on_submit():
user = User.query.filter_by(email=form.email.data).first()
if user:
send_password_reset_email(user)
flash('Check your email for the instructions to reset your password')
return redirect(url_for('login'))
return render_template('reset_password_request.html',
title='Reset Password', form=form)
# end of reset password request endpoint
# reset password endpoint
@app.route('/reset_password/<token>', methods=['GET', 'POST'])
def reset_password(token):
# if user is already signed in
if current_user.is_authenticated:
return redirect(url_for('index'))
user = User.verify_reset_password_token(token)
# redirect to index if token is invalid
if not user:
return redirect(url_for('index'))
# present form to reset password if token is valid
form = ResetPasswordForm()
if form.validate_on_submit():
user.set_password(form.password.data)
db.session.commit()
flash('Your password has been reset.')
return redirect(url_for('login'))
return render_template('reset_password.html', form=form)
# end of reset password endpoint
# language endpoint
@app.route('/language/<language>')
@login_required
def language(language):
page = request.args.get('page', 1, type=int)
projects = Project.query.filter_by(language=language).order_by(Project.timestamp.desc()).paginate(page, app.config['POSTS_PER_PAGE'], False)
next_url = url_for('language', language=language, page=projects.next_num) \
if projects.has_next else None
prev_url = url_for('language', language=language, page=projects.prev_num) \
if projects.has_prev else None
return render_template('index.html', title=language, projects=projects.items, next_url=next_url, prev_url=prev_url)
# end of language endpoint
# rate project endpoint
@app.route('/rate/<id>', methods=['POST'])
@login_required
def rate(id):
form = EmptyForm()
if form.validate_on_submit():
project = Project.query.get(id)
if project is None:
flash('Project ID #{} not found.'.format(id))
return redirect(url_for('index'))
if project.owner == current_user:
flash('You cannot rate your own project!')
return redirect(url_for('project', id=id))
current_user.rate(project)
db.session.commit()
flash('You just rated {}\'s project!'.format(project.owner.username))
return redirect(url_for('project', id=id))
else:
return redirect(url_for('index'))
# end of rate project endpoint
# unrate project endpoint
@app.route('/unrate/<id>', methods=['POST'])
@login_required
def unrate(id):
form = EmptyForm()
if form.validate_on_submit():
project = Project.query.get(id)
if project is None:
flash('Project ID #{} not found.'.format(id))
return redirect(url_for('index'))
if project.owner == current_user:
flash('You cannot unrate your own project!')
return redirect(url_for('project', id=id))
current_user.unrate(project)
db.session.commit()
flash('You just unrated {}\'s project!'.format(project.owner.username))
return redirect(url_for('project', id=id))
else:
return redirect(url_for('index'))
# end of unrate project endpoint
# project endpoint
@app.route('/project/<id>')
@login_required
def project(id):
project = Project.query.get(id)
projects = None
list_of_recs = recommend(project.title, df, tfidf_vectorizer)
print(list_of_recs)
if list_of_recs is not None:
new_df = pd.DataFrame(list_of_recs, columns=['id', 'score'])
new_df['id'] = new_df['id'] + 1
print(new_df)
project_ids = new_df['id']
projects = Project.query.filter(Project.id.in_(project_ids))
form = EmptyForm()
return render_template('project.html', title=project.title, project=project, projects=projects, form=form)
# end of project endpoint
# api endpoint
@app.route('/api/', methods =['POST'])
def process_request():
# get user input
user_input = request.get_json()
# save project name as title
title = user_input['Repository Name']
# call recommend function with necessary arguments
recommended_projects = api_recommend(title, df, tfidf_vectorizer)
return jsonify(recommended_projects)
if __name__ == '__main__':
app.run() |
18,817 | 0c668025ff4b503378f4fb2e189e47f5f89abacb | """Import the name and print all characters"""
name = input("Enter your name")
"""Check the name is not blank"""
while len(name) <= 0:
print("Name is blank. Enter again")
name = input("Enter your name")
#Print odd character in the name
print(name[1:len(name):2])
print(name[::2])
#Print odd character in the name
for i in range(0, len(name), 2):
print(name[i])
|
18,818 | b6a0e2c4f1c2f76efa9d66582e2e29b46b19bab5 | #
# ps3pr2.py (Problem Set 3, Problem 2)
#
# Caesar cipher/decipher
#
# name: Teng Xu
# email: xt@bu.edu
#
# If you worked with a partner, put his or her contact info below:
# partner's name:
# partner's email:
#
# a helper function that could be useful when assessing
# the "Englishness" of a phrase
def letter_prob(c):
""" if c is the space character (' ') or an alphabetic character,
returns c's monogram probability (for English);
returns 1.0 for any other character.
adapted from:
http://www.cs.chalmers.se/Cs/Grundutb/Kurser/krypto/en_stat.html
"""
if c == ' ': return 0.1904
if c == 'e' or c == 'E': return 0.1017
if c == 't' or c == 'T': return 0.0737
if c == 'a' or c == 'A': return 0.0661
if c == 'o' or c == 'O': return 0.0610
if c == 'i' or c == 'I': return 0.0562
if c == 'n' or c == 'N': return 0.0557
if c == 'h' or c == 'H': return 0.0542
if c == 's' or c == 'S': return 0.0508
if c == 'r' or c == 'R': return 0.0458
if c == 'd' or c == 'D': return 0.0369
if c == 'l' or c == 'L': return 0.0325
if c == 'u' or c == 'U': return 0.0228
if c == 'm' or c == 'M': return 0.0205
if c == 'c' or c == 'C': return 0.0192
if c == 'w' or c == 'W': return 0.0190
if c == 'f' or c == 'F': return 0.0175
if c == 'y' or c == 'Y': return 0.0165
if c == 'g' or c == 'G': return 0.0161
if c == 'p' or c == 'P': return 0.0131
if c == 'b' or c == 'B': return 0.0115
if c == 'v' or c == 'V': return 0.0088
if c == 'k' or c == 'K': return 0.0066
if c == 'x' or c == 'X': return 0.0014
if c == 'j' or c == 'J': return 0.0008
if c == 'q' or c == 'Q': return 0.0008
if c == 'z' or c == 'Z': return 0.0005
return 1.0
#### Put your code for problem 2 below. ####
#1
def rot(c,n):
""" rotate c forward by n characters,
wrapping as needed; only letters change
"""
if 'a' <= c <= 'z':
new_ord = ord(c) + n
if new_ord > ord('z'):
new_ord = new_ord - 26
elif 'A' <= c <= 'Z':
new_ord = ord(c) + n
if new_ord > ord('Z'):
new_ord = new_ord - 26
else:
new_ord = ord(c)
return chr(new_ord)
def encipher(s,n):
if s == '':
return ''
else:
return rot(s[0],n)+ encipher(s[1:],n)
#2
def num_vowels(s):
lc = [1 for c in s if c in 'aeiou']
return sum(lc)
def decipher(s):
options = [encipher(s,n) for n in range(26)]
scored_options = [[num_vowels(x),x] for x in options]
return max(scored_options)[1]
|
18,819 | a6cc980879b822a187cbfeace50d4bac780dd826 | import cv2
face_data = cv2.CascadeClassifier("face_data.xml")
eye_data = cv2.CascadeClassifier("eye_data.xml")
video_capture = cv2.VideoCapture("1.mov")
def detect(frame):
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_data.detectMultiScale(gray, 1.3,5)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = frame[y:y+h, x:x+w]
eyes = eye_data.detectMultiScale(roi_gray, 1.1, 3)
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex, ey), (ex+ew, ey+eh), (0, 255, 0), 2)
return frame
while(True):
ret, frame = video_capture.read()
frame = cv2.flip(frame, 1)
frame = detect(frame)
cv2.imshow('frame',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows() |
18,820 | ffdfbe484e8b0622ed060294f982f1fbe68d7015 | from .loss import Loss
from .coil_model import CoILModel, EncoderModel
from .optimizer import adjust_learning_rate, adjust_learning_rate_auto |
18,821 | f7be940850cea4d94a0f29133d07bac1daa07aa0 | from __future__ import annotations
from typing import List
from heapq import heappop, heappush, heappushpop
from collections import defaultdict
# all heaps in python are minheap. to use minheap as a maxheap u have to make value negative
class Solution:
def medianSlidingWindow(self, nums: List[int], k: int) -> List[float]:
lo, hi = [], []
for i in range(k):
if len(lo) == len(hi):
heappush(hi, -heappushpop(lo, -nums[i]))
else:
heappush(lo, -heappushpop(hi, nums[i]))
ans = [float(hi[0])] if k & 1 else [(hi[0] - lo[0]) / 2.0]
to_remove = defaultdict(int)
for i in range(k, len(nums)):
heappush(lo, -heappushpop(hi, nums[i]))
out_of_window_num = nums[i-k]
if out_of_window_num > -lo[0]:
heappush(hi, -heappop(lo))
to_remove[out_of_window_num] += 1
while lo and to_remove[-lo[0]]:
to_remove[-lo[0]] -= 1
heappop(lo)
while to_remove[hi[0]]:
to_remove[hi[0]] -= 1
heappop(hi)
if k % 2:
ans.append(float(hi[0]))
else:
ans.append((hi[0] - lo[0]) / 2.0)
return ans
# test = Solution()
# test.medianSlidingWindow([1,3,-1,-3,5,3,6,7], 3)
test = Solution()
test.medianSlidingWindow([1,3,-1,-3,5,3,6,7], 4)
# test = Solution()
# test.medianSlidingWindow([1,2,3,4,2,3,1,4,2], 3)
|
18,822 | eedd21d63792df5a4ab1e02863e247509f9657b0 | import numpy as np
from numpy import random
x = random.randint(100,size=(5,10))
arr = np.array([x])
print(np.sort(arr)) |
18,823 | f0068c0446339a67741d7add3efdfd2ac4fb84db | import serial
import csv
# 歩行データの保存先
test_data = 'C:\\Users\\user\\Documents\\Gaitsensor-main\\walkingdata\\walkingdata.csv'
ser = serial.Serial('COM9', baudrate=115200, parity=serial.PARITY_NONE) # COMポートはPC環境によって変化
line = ser.readline()
total_byte = 0
'''
# 初期化 ヘッダーを追加する
header = "bothfoot_L,swing_L,bothfoot_R,swing_R,stand_L,stand_R"
headers = header.split(',')
with open(test_data, 'w',newline="") as f:
writer = csv.writer(f)
writer.writerow(headers)
'''
try:
# 追記
while True:
line = ser.readline()
total_byte = total_byte + len(line.decode('utf-8'))
print(" byte:",len(line.decode('utf-8'))," total_byte:", total_byte)
line_str = (line.decode('utf-8')).replace('\n', '') # byteをstrに変換後、改行コードを削除
lines = line_str.split(',')
print(lines)
with open(test_data, 'a',newline="") as f:
writer = csv.writer(f)
writer.writerow(lines)
except KeyboardInterrupt:
# 確認用
with open(test_data) as f:
print(f.read())
ser.close() |
18,824 | 75ccd5b425a9b738647f89cfd9d015983688daa1 | import argparse
import os
import subprocess
import numpy as np
import pandas as pd
from sklearn.model_selection import KFold
import torch
import yaml
from torch.utils.data import DataLoader
from lstm import GBVSSLSTMModel, GBVSSLSTMTrainer, GBVPPEvaluator, make_datasets
from base.utils import Tools as T
if __name__ == '__main__':
parser = argparse.ArgumentParser(
usage='python submit.py -cp ../result/base_seed_0/config.yaml x N-files '
'-pths ../result/base_seed_0/pths/best.pth x N-files',
add_help=True
)
parser.add_argument('-cp', '--config_path', type=str, nargs='+',
default=['config.yaml'], help='config path')
parser.add_argument('-seed', '--seed', type=int)
parser.add_argument('-nw', '--num_worker', type=int)
parser.add_argument('-memo', '--memo', type=str)
parser.add_argument('-pths', '--pth_paths', type=str, nargs='+')
parser.add_argument('-ent', '--ensemble_type', type=str, default='median')
parser.add_argument('-multi', '--multi_gpu', action='store_true')
parser.add_argument('-sub', '--submit', action='store_true')
parser.add_argument('-no_pp', '--no_post_process', action='store_true')
parser.add_argument('-fn', '--file_name', type=str)
parser.add_argument('-pseudo', '--for_pseudo', action='store_true')
parser.add_argument('-val', '--validation', action='store_true')
parser.add_argument('-ps_th', '--pseudo_threshold', type=float, default=float('inf'))
parser.add_argument('-clip_N', '--clip_N', type=int, default=3)
parser.add_argument('-nsp', '--n_splits', type=int)
parser.add_argument('-stack', '--for_stacking', action='store_true')
parse = parser.parse_args()
nw = 6
val_bs = 128
import torch.multiprocessing
torch.multiprocessing.set_sharing_strategy('file_system')
breath_ids = []
predicts = []
for config_path, pth_path in zip(parse.config_path, parse.pth_paths):
# load yaml
with open(config_path) as f:
config = yaml.load(f, Loader=yaml.SafeLoader)
config['trainer']['save_path'] = config['main']['save_path']
# make dataset & dataloader
with T.timer('data load'):
if parse.validation:
tst_ds = make_datasets(config['dataset'], seed=0)[1]['']
else:
tst_ds = make_datasets(config['dataset'], seed=0, train=False)
tst_dl = DataLoader(tst_ds, batch_size=val_bs, shuffle=False, num_workers=nw)
dataloaders = {'tst': tst_dl}
# make model, loss
if config['model']['model_type'] == 'lstm':
model = GBVSSLSTMModel(config['model']).cuda()
else:
raise Exception
evaluator = GBVPPEvaluator(**config['loss'], summary=None)
# make trainer
trainer = GBVSSLSTMTrainer(model, dataloaders, evaluator, None)
trainer.set_args(config['trainer'])
trainer.load_resume(torch.load(pth_path), config['main'].get('only_model_load', False))
# TEST
with T.timer('testing'):
output = trainer.run_test()
breath_id = torch.cat([out[0].view(-1) for out in output], -1).numpy()
predict = torch.cat([out[1].view(-1) for out in output], -1).numpy()
breath_ids.append(breath_id)
predicts.append(predict.reshape(-1, 80))
breath_ids = np.concatenate(breath_ids, 0)
predicts = np.concatenate(predicts, 0)
n_bid = len(np.unique(breath_ids))
predicts = predicts[breath_ids.argsort(axis=0)].reshape(n_bid, -1, 80).transpose(1,0,2).reshape(-1, n_bid*80)
if parse.for_stacking:
tst_df = pd.read_csv('../input/ventilator-pressure-prediction/train_process.csv')
elif parse.for_pseudo:
predicts_cp = predicts.copy()
predicts_cp = predicts_cp.reshape(predicts.shape[0], -1, 80)
N = parse.clip_N
predicts_cp = np.sort(predicts_cp, axis=0)[N:len(predicts_cp)-N]
pseudo_mask = (predicts_cp[-1] - predicts_cp[0] < parse.pseudo_threshold).reshape(-1)
tst_df['th_mask'] = pseudo_mask
print(f'{pseudo_mask[tst_ds.u_outs == 0].mean()} % used for pseudo')
else:
tst_df = pd.read_csv('../input/ventilator-pressure-prediction/sample_submission.csv')
# ensemble
if parse.ensemble_type == 'mean':
predicts = predicts.mean(0)
elif parse.ensemble_type == 'median':
predicts = np.median(predicts, 0)
if parse.for_stacking:
tst_df['stacking'] = predicts
else:
tst_df['pressure'] = predicts
# post process
if not parse.no_post_process:
print('POST PROCESSING ...')
trn_val_df = pd.read_csv('../input/ventilator-pressure-prediction/train.csv')
unique_pressures = trn_val_df["pressure"].unique()
sorted_pressures = np.sort(unique_pressures)
total_pressures_len = len(sorted_pressures)
def find_nearest(prediction):
insert_idx = np.searchsorted(sorted_pressures, prediction)
if insert_idx == total_pressures_len:
return sorted_pressures[-1]
elif insert_idx == 0:
return sorted_pressures[0]
lower_val = sorted_pressures[insert_idx - 1]
upper_val = sorted_pressures[insert_idx]
return lower_val if abs(lower_val - prediction) < abs(upper_val - prediction) else upper_val
tst_df['pressure'] = tst_df['pressure'].apply(find_nearest)
# split
if parse.n_splits is not None:
kfold = KFold(n_splits=parse.n_splits, shuffle=True, random_state=0)
bids = tst_df.breath_id.unique()
for fold_id, (_, val_idx) in enumerate(kfold.split(range(len(bids)))):
val_bids = bids[val_idx]
tst_df.loc[tst_df.breath_id.isin(val_bids), 'split'] = fold_id
# preserve
if parse.file_name is None:
name = [os.path.splitext(pth_path)[0].split('/') for pth_path in parse.pth_paths]
name = '__'.join([x[-3] + '_' + x[-1] for x in name])
else:
name = parse.file_name
print(f'save as {name}.csv')
root_dir = 'pseudos' if parse.for_pseudo else 'submits'
T.make_dir(f'../{root_dir}')
tst_df.to_csv(f'../{root_dir}/{name}.csv', index=False)
# submit to kaggle
if parse.submit:
message = name
if parse.memo is not None:
message = message + f'\n{parse.memo}'
subprocess.call(f'kaggle competitions submit ventilator-pressure-prediction '\
f'-f ../submits/{name}.csv -m "{message}"', shell=True)
print()
|
18,825 | ab32905baff09977c227180237dd01e65f45d2ec | import module as fib
fib.printFib(1000)
result = fib.fib(1000)
print '\n\nresult: ', result |
18,826 | afdfd2d55664e4a44b8fd896652a84a2202ca79b | import os
import subprocess
import uuid
import boto3
import json
from farm_uploader import proccess_farm_complete
import config_file
def handler(event, context):
key = config_file.KEY
secret_key = config_file.SECRET_KEY
updated_farms_loc = config_file.UPDATED_FARMS_LOC
s3 = boto3.resource('s3',aws_access_key_id =key,aws_secret_access_key=secret_key)
for record in event['Records']:
farm_loc = record['s3']['object']['key']
fname = record['s3']['object']['key'].split('/')[-1]
out_loc = os.path.join(updated_farms_loc,fname)
bucket_name = event['Records'][0]['s3']['bucket']['name']
s3.Bucket(bucket_name).download_file(farm_loc, r'/tmp/farm.json')
with open(r'/tmp/farm.json','r') as f:
farm = json.load(f)
try:
all_data_sets_proccesed = proccess_farm_complete(farm,max_results=1)
is_succeeded = True
except:
is_succeeded = False
tmp_farm_loc = r'/tmp/farm.json'
with open(tmp_farm_loc, 'w+') as f:
json.dump(farm, f)
s3.Object(bucket_name, farm_loc).delete()
s3.Bucket(bucket_name).upload_file(tmp_farm_loc, out_loc)
if not is_succeeded:
error_farms_loc=config_file.ERROR_FARMS_LOC
error_loc = os.path.join(error_farms_loc,fname)
s3.Object(bucket_name, farm_loc).delete()
s3.Bucket(bucket_name).upload_file(tmp_farm_loc, error_loc)
return "ERROR farm {} was not processed".format(farm['id'])
elif not all_data_sets_proccesed:
error_farms_loc = config_file.ERROR_TYPE_SOME_DATA_SET_FARMS_LOC
error_loc = os.path.join(error_farms_loc, fname)
s3.Bucket(bucket_name).upload_file(tmp_farm_loc, error_loc)
return "farm {} was processed on some datasets".format(farm['id'])
else:
return "farm {} processed successfully".format(farm['id'])
|
18,827 | bd172dbc51c3ff50298d9fd62340d719a7da0530 | def is_correct(string):
stack = list()
for c in string:
if c == '(':
stack.append('(')
elif len(stack) > 0:
stack.pop()
else:
return False
return True
def dfs(string):
if len(string) == 0: # 1번
return ''
c_open = 0
c_close = 0
for i in range(len(string)):
if string[i] == '(':
c_open += 1
else:
c_close += 1
if c_open == c_close: # 2번
if is_correct(string[:i + 1]): # 3번
return string[:i + 1] + dfs(string[i + 1:])
else: # 4번
v = '(' + dfs(string[i + 1:]) + ')' # 4-1 ~ 4-3
tmp = ''
for a in range(1, i): # 4-4
if string[a] == '(':
tmp += ')'
else:
tmp += '('
return v + tmp
def solution(p):
answer = dfs(p)
return answer |
18,828 | ec6c467798eda1e2a503a4287061f5573e6f36ab | #!/usr/bin/env python
# coding: utf-8
# In[25]:
import pandas as pd
# In[26]:
import matplotlib.pyplot as plt
# In[27]:
get_ipython().run_line_magic('matplotlib', 'inline')
# In[28]:
names = ['Bob','Jessica','Mary','John','Mel']
# In[29]:
absences = [3,0,1,0,8]
# In[30]:
detentions = [2,1,0,0,1]
# In[31]:
warnings = [2,1,5,1,2]
# In[32]:
GradeList = zip(names,absences,detentions,warnings)
# In[33]:
columns=['Names','Absences','Detentions','Warnings']
# In[34]:
df = pd.DataFrame(data = GradeList,columns=columns)
# In[35]:
df
# In[36]:
df['TotalDemerits']=df['Absences']+df['Detentions']+df['Warnings']
# In[37]:
df
# In[38]:
plt.pie(df['TotalDemerits'])
# In[39]:
plt.pie(df['TotalDemerits'],labels=df['Names'],explode=(0,0,0,0.15,0),startangle=90,autopct='%1.1f%%')
# In[ ]:
# In[ ]:
|
18,829 | 64d182420378886b8ebf552e4c872d8fcaeab3ff | from typing import List
"""
Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.
You may assume that each input would have exactly one solution, and you may not use the same element twice.
You can return the answer in any order.
"""
class Solution:
def twoSum(self, nums: List[int], target: int) -> List[int]:
# two pointers
begin, end = 0, len(nums) - 1
idxd_nums = [(idx, num) for idx, num in enumerate(nums)]
idxd_nums.sort(key=lambda x: x[1])
while begin < end:
curr = idxd_nums[begin][1] + idxd_nums[end][1]
if curr == target:
return [idxd_nums[begin][0], idxd_nums[end][0]]
elif curr > target:
end -= 1
else:
begin += 1
return []
def twoSumHM(self, nums: List[int], target: int) -> List[int]:
# hash map
numMap = {}
for i, num in enumerate(nums):
complement = target - num
if complement in numMap:
return [numMap[complement], i]
numMap[num] = i
return []
def test(*args, expected):
solution = Solution()
output = solution.twoSum(*args)
assert output == expected
if __name__ == '__main__':
test(
[2, 7, 11, 15],
9,
expected=[0, 1]
)
test(
[3, 2, 4],
6,
expected=[1, 2]
)
test(
[3, 3],
6,
expected=[0, 1]
)
|
18,830 | f5933c52c88b6313dcf2e3fa9c40e2fd64ecf3b0 | """ DRF가 제공하는 API views 방식은 2가지가 있다.
1. @api_view 데코레이터를 사용하는 FBV(Function-Based Views)
2. APIView 클래스를 사용하는 CBV(Class-Based Views) """
""" 1. Function-Based Views
- 확장성과 재사용성은 떨어짐
- 하지만 편하게 읽을 수 있고 구현하기도 쉽다"""
# drf에서는 status 기능을 통해 http 상태를 숫자+문자 로 표현해 보다 명확한 상태를 보여준다.
from rest_framework import status
from rest_framework import generics
from rest_framework.decorators import api_view
from rest_framework.response import Response
from rest_framework.reverse import reverse
from snippets.models import Snippet
from snippets.serializers import SnippetSerializer
@api_view(['GET', 'POST'])
def snippet_list(request, format=None): # format=None: 데이터 형태에 대한 포맷정보가 붙는다.
"""
List all code snippets, or create a new snippet.
"""
if request.method == 'GET':
snippets = Snippet.objects.all()
serializer = SnippetSerializer(snippets, many=True)
return Response(serializer.data)
elif request.method == 'POST':
serializer = SnippetSerializer(data=request.data)
if serializer.is_valid():
serializer.save()
return Response(serializer.data, status=status.HTTP_201_CREATED)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
@api_view(['GET', 'PUT', 'DELETE'])
def snippet_detail(request, pk, format=None):
"""
Retrieve, update or delete a code snippet.
"""
try:
snippet = Snippet.objects.get(pk=pk)
except Snippet.DoesNotExist:
return Response(status=status.HTTP_404_NOT_FOUND)
if request.method == 'GET':
serializer = SnippetSerializer(snippet)
return Response(serializer.data)
elif request.method == 'PUT':
serializer = SnippetSerializer(snippet, data=request.data)
if serializer.is_valid():
serializer.save()
return Response(serializer.data)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
elif request.method == 'DELETE':
snippet.delete()
return Response(status=status.HTTP_204_NO_CONTENT) |
18,831 | e80758d6d6341f5bbfcb6ce44f243d12b21c1636 | from .club_solver import attempt_solve |
18,832 | 5d49bd065b979d0cc562991da099dfb8c83dd782 | """
CLI entry point hook.
"""
from argparse import ArgumentParser
from json import loads
def createall_main(graph):
"""
Initialize indexes and mappings.
"""
parser = ArgumentParser()
parser.add_argument("--only", action="append")
parser.add_argument("--skip", action="append")
parser.add_argument("-D", "--drop", action="store_true")
args = parser.parse_args()
graph.elasticsearch_index_registry.createall(
force=args.drop,
only=args.only,
skip=args.skip,
)
def query_main(graph, default_index):
"""
Run a query.
"""
parser = ArgumentParser()
parser.add_argument("-i", "--index", default=default_index)
parser.add_argument("-q", "--query", default='{"match_all": {}}')
parser.add_argument("-f", "--flat", action="store_true")
args = parser.parse_args()
try:
query = loads(args.query)
except Exception:
parser.error("query must be valid json")
response = graph.elasticsearch_client.search(
index=args.index,
body=dict(query=query),
)
if args.flat:
return response["hits"]["hits"]
else:
return response
|
18,833 | d61759a843ad54eeca5cdce8e864db16751b8394 | #텍스트 클리닝과 텍스트 토큰화
#from konlpy.tag import Okt 보통의 경우에는 Okt를 사용하지 x
import json
import os
import re
from pprint import pprint
import rhinoMorph
from collections import Counter
import pandas as pd
import math
from tensorflow.compat.v2.keras.models import model_from_json
from tensorflow.keras.preprocessing.text import Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
import joblib
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
max_words = 5000
max_len = 100
rn = rhinoMorph.startRhino()
# 텍스트 클리닝 - 한글만 남기기
def text_cleaning(doc):
doc = re.sub("[^ㄱ-ㅎㅏ-ㅣ가-힣 ]", "", doc)
return doc
# 불용어 정의
def define_stopwords(path, encoding):
SW = set()
#집합형태로 만들어줘야 중복을 제외하고 출력해줌
#불용어들을 추가할려면 SW.add()이렇게 넣어주면 됨
with open(path, encoding = encoding) as f:
for word in f:
SW.add(word)
return SW
# 모델 로딩
def load_model():
json_file = open("application/model/NLP_model.json", "r")
loaded_model_json = json_file.read()
json_file.close()
# json파일로부터 model 로드하기
loaded_model = model_from_json(loaded_model_json)
# 로드한 model에 weight 로드하기
loaded_model.load_weights("application/model/NLP_weight.h5")
return loaded_model
SW = define_stopwords("application/model/stopwords-ko.txt", encoding = 'utf-8')
tokenizer = joblib.load('application/model/tokenizer.pickle')
# def text_tokenizing(doc):
# return [word for word in rhinoMorph.onlyMorph_list(rn,doc, pos = ['NNG', 'NNP','NP', 'VV', 'VA', 'XR', 'IC', 'MM', 'MAG', 'MAJ'], eomi = False) if word not in SW and len(word) > 1]
# 분석!!!
def sentiment_predict(new_sentence):
score = 0
model = load_model()
if new_sentence != '':
new_sentence1 = text_cleaning(new_sentence)
new_sentence2 = rhinoMorph.onlyMorph_list(rn,new_sentence1, pos = ['NNG', 'NNP','NP', 'VV', 'VA', 'XR', 'IC', 'MM', 'MAG', 'MAJ'], eomi = False)
new_sentence3 = [word for word in new_sentence2 if not word in SW] # 불용어 제거
encoded = tokenizer.texts_to_sequences([new_sentence3]) # 정수 인코딩
if encoded != [[]]:
pad_new = pad_sequences(encoded, maxlen = max_len) # 패딩
score = float(model.predict(pad_new))
return score
|
18,834 | d01105336843a22300c0b0c81e47218cdbe0ae84 | #!/usr/bin/env python3
'''
Task 9.1a
'''
def access_port_generate(dict, template, *args):
result = []
for i in dict.keys():
result.append('interface ' + i)
for item in template:
if 'vlan' in item:
result.append(item + ' ' + str(dict[i]))
else:
result.append(item)
if args:
result.extend(*args)
return result
access_mode_template = [
'switchport mode access', 'switchport access vlan',
'switchport nonegotiate', 'spanning-tree portfast',
'spanning-tree bpduguard enable'
]
access_config = {
'FastEthernet0/12': 10,
'FastEthernet0/14': 11,
'FastEthernet0/16': 17
}
port_security_template = [
'switchport port-security maximum 2',
'switchport port-security violation restrict',
'switchport port-security'
]
# print(access_port_generate(access_config, access_mode_template, port_security_template))
'''
Task 9.2a
'''
trunk_mode_template = [
'switchport mode trunk', 'switchport trunk native vlan 999',
'switchport trunk allowed vlan'
]
trunk_config = {
'FastEthernet0/1': [10, 20, 30],
'FastEthernet0/2': [11, 30],
'FastEthernet0/4': [17]
}
def generate_trunk_config(intf_vlan_mapping, trunk_template):
result = {}
for i in intf_vlan_mapping.keys():
interface = ('interface ' + i)
result[interface] = []
for item in trunk_template:
if 'allowed' in item:
items = ''
for value in intf_vlan_mapping[i]:
items = items + str(value) + ','
items = items[:-1]
result[interface].append(item + ' ' + items)
else:
result[interface].append(item)
return result
# print(generate_trunk_config(trunk_config, trunk_mode_template))
'''
Task 9.3a
'''
def get_int_vlan_map(config_filename):
try:
path = '/home/pashockys/progi_python/pyneng-examples-exercises/exercises/09_functions/'+config_filename
open(path, 'r')
except FileNotFoundError:
print('It seems that you are not at home')
path = '/home/pashockys/Scripts/Natasha/pyneng-examples-exercises/exercises/09_functions/'+config_filename
with open(path, 'r') as f:
result_dict = {}
result_dict_trunk = {}
for index, line in enumerate(f):
if 'interface' in line:
interface = line.strip().split()[1]
if 'access vlan' in line:
result_dict[interface] = int(line.strip().split()[-1])
continue
if 'mode access' in line:
result_dict[interface] = 1
if 'allowed vlan' in line:
result_dict_trunk[interface] = [int(x) for x in line.strip().split()[-1].split(',')]
output = (result_dict, result_dict_trunk)
return output
print(get_int_vlan_map('config_sw2.txt'))
'''
Task 9.4
'''
ignore = ['duplex', 'alias', 'Current configuration']
def ignore_command(command, ignore):
'''
Функция проверяет содержится ли в команде слово из списка ignore.
command - строка. Команда, которую надо проверить
ignore - список. Список слов
Возвращает
* True, если в команде содержится слово из списка ignore
* False - если нет
'''
return any(word in command for word in ignore)
def convert_config_to_dict(config_filename):
try:
path = '/home/pashockys/progi_python/pyneng-examples-exercises/exercises/09_functions/' + config_filename
open(path, 'r')
except FileNotFoundError:
print('It seems that you are not at home')
path = '/home/pashockys/Scripts/Natasha/pyneng-examples-exercises/exercises/09_functions/' + config_filename
with open(path, 'r') as f:
dict_4 = {}
main_line = ''
for line in f:
if not ignore_command(line, ignore) and '!' not in line:
if line[0].isalpha():
main_line = line.strip()
dict_4[main_line] = []
else:
dict_4[main_line].append(line.strip())
type(dict_4[main_line])
return dict_4
# print(convert_config_to_dict('config_sw1.txt'))
|
18,835 | 9ecb75a9e8e915386ad697ed84094e36908fdae9 | # Generated by Django 3.0.5 on 2020-04-13 22:42
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Region',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=120)),
('avgAge', models.IntegerField()),
('avgDailyIncomeInUSD', models.IntegerField()),
('avgDailyIncomePopulation', models.IntegerField()),
],
),
migrations.CreateModel(
name='Covid',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('periodType', models.CharField(max_length=120)),
('timeToElapse', models.IntegerField()),
('reportedCases', models.IntegerField()),
('population', models.IntegerField()),
('populatotalHospitalBedstion', models.IntegerField()),
('totalHospitalBeds', models.IntegerField()),
('region', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='region', to='pai.Region')),
],
),
]
|
18,836 | 9c00d9d293ba819a53e1cbb450254fb93a23837c | import __main__ as main
from Helper.TimerLogger import CodeTimeLogging
fileName = main.__file__
fileName = fileName.split('\\')[-1]
CodeTimeLogging(Flag='F', filename=fileName, Tag='Dynamic-Programing', Difficult='Medium')
# Formula :
def eggDroping(noEggs, nofloar):
dp = [[i if j == 1 else 0 for i in range(nofloar + 1)]for j in range(noEggs + 1)]
[print(x)for x in dp]
for i in range(2, noEggs + 1):
for j in range(1, nofloar + 1):
for k in range(1, j + 1):
print([i - 1, k - 1], [i, j - k], [i, j, k])
dp[i][j] = min(1 + max(dp[i - 1][k - 1],
dp[i][j - k]) for k in range(1, j + 1))
print()
[print(x)for x in dp]
noEggs = 2
nofloar = 6
print(eggDroping(noEggs, nofloar))
|
18,837 | 19234ad3d3ab6ccf5511dd987f3ba474e91de8dd | #!/usr/bin/env python
#
import sys
import copy
from pycondriver import TxtSurface
from pycondriver import Terminal
_ESC = chr(0x1B)
_SPC = 32
# ATTRIBS
_RESET = 0
_BRIGHT = 1
_DIM = 2
_UNDERSCORE = 3
_BLINK = 5
_REVERSE = 7
_HIDDEN = 8
# COLORS
_FG = 30
_BG = 40
_BLACK = 0
_RED = 1
_GREEN = 2
_YELLOW = 3
_BLUE = 4
_MAGENTA = 5
_CYAN = 6
_WHITE = 7
# Simple text surface (for ASCII only)
#
# Each element has this format:
#
# -------X|XXYYYZZZ|CCCCCCCC
#
# XXX: text attribute
# YYY: foreground color
# ZZZ: background color
# CCCCCCCC: character
#
class AsciiSurface(TxtSurface):
def __init__(self, size, data = []):
self.size = size
if not (len(data) == (self.size[0] * self.size[1])):
# Raises an error! (given data is different than
# surface size)
self.srf = [_SPC] * (self.size[0] * self.size[1])
else:
self.srf = data
def clear(self):
self.srf = [_SPC] * (self.size[0] * self.size[1])
def resize(self, new_size):
if new_size == self.size:
return
# Get crop rectangle
min_x = min(self.size[0], new_size[0])
min_y = min(self.size[1], new_size[1])
# Create empty surface
new_srf = [_SPC] * (new_size[0] * new_size[1])
# Copy lines
new_ind = 0
for y in range(min_y):
# Copy source line
new_srf[new_ind : new_ind + min_x] = self.srf[0:min_x]
new_ind += new_size[0]
self.srf = new_srf
self.size = new_size
def blit(self, position, surface):
if (surface.size > self.size):
# Raises an exception!!
return
(px, py) = position
# Compute crop area
line_len = (px + surface.size[0]) % self.size[0]
lines = (px + surface.size[1]) % self.size[1]
# Initial copy index
srf_ind = (py * self.size[0]) + px
# Dump lines
for y in range(lines):
self.srf[srf_ind:srf_ind + line_len] = surface.srf[:line_len]
srf_ind += self.size[0]
self.dirty = True
def set_background(self, attributes, color):
for i in range(len(self.srf)):
char = self.srf[i]
attr = (char >> 8)
char &= 0xFF
# Set new background (saving foreground)
attr &= 0b000111000
attr |= (color & 7)
attr |= (attributes & 7) << 6
self.srf[i] = char | (attr << 8)
def set_foreground(self, attributes, color):
for i in range(len(self.srf)):
char = self.srf[i]
attr = (char >> 8)
char &= 0xFF
# Set new foreground (saving background)
attr &= 0b000000111
attr |= (color & 7) << 3
attr |= (attributes & 7) << 6
self.srf[i] = char | (attr << 8)
def fill(self, char):
(char, attributes, foreground, background) = char
element = (attributes & 7) << 14
element |= (foreground & 7) << 11
element |= (background & 7) << 8
element |= (char & 0xFF)
self.srf = [element] * (self.size[0] * self.size[1])
# Need to crop text lines?
def dump(self, position, text, attributes, foreground, background):
attributes = (attributes & 7) << 14
attributes |= (foreground & 7) << 11
attributes |= (background & 7) << 8
# Make surface index
ind = (self.size[0] * (position[1] % self.size[1]) +
(position[0] % self.size[0]))
for itext in range(len(text)):
self.srf[ind + itext] = (attributes << 8) | ord(text[itext])
def char_at(self, position):
element = self.srf[(self.size[0] * (position[1] % self.size[1])) +
(position[0] % self.size[0])]
return (element & 0xFF,
(element & 0b11100000000000000) >> 14,
(element & 0b11100000000000) >> 11,
(element & 0b11100000000) >> 8)
def set_char(self, position, char):
self.srf[(self.size[0] * (position[1] % self.size[1])) +
(position[0] % self.size[0])] = (
(char[0] & 0xFF) | ((char[1] & 7) << 14) | ((char[2] & 7) << 11) |
(char[3] & 7 << 8))
# Terminal
class AsciiTerminal(AsciiSurface):
def __init__(self, size = None):
if size is None:
size = self.__getConsoleSize()
AsciiSurface.__init__(self, size)
self.reset()
def reset(self):
self.__cls()
self.attr = 0
self.fg_color = _BLACK
self.bg_color = _WHITE
self.fill((_SPC, self.attr, self.fg_color, self.bg_color))
self.frame()
def maximize(self):
size = self.__getConsoleSize()
if (size != self.size):
self.resize(size)
self.frame()
def frame(self):
attribute = -1
self.__setCursorPos((0, 0))
for ind in range(len(self.srf)):
char = self.srf[ind]
new_attribute = (char & 0xFF00)
if (new_attribute != attribute):
attribute = new_attribute
self.__set_attributes(attribute >> 8)
sys.stdout.write(chr(char & 0xFF))
sys.stdout.flush()
self.dirty = False
def close(self, with_clear = False):
self.__set_attributes(449)
if with_clear:
self.__cls()
def __getConsoleSize(self):
def ioctl_GWINSZ(fd):
try:
import fcntl, termios, struct, os
cr = struct.unpack('hh',
fcntl.ioctl(fd, termios.TIOCGWINSZ, '1234'))
except:
return None
return cr
cr = ioctl_GWINSZ(0) or ioctl_GWINSZ(1) or ioctl_GWINSZ(2)
if not cr:
try:
fd = os.open(os.ctermid(), os.O_RDONLY)
cr = ioctl_GWINSZ(fd)
os.close(fd)
except:
pass
if not cr:
try:
cr = (env['LINES'], env['COLUMNS'])
except:
cr = (25, 80)
return int(cr[1]), int(cr[0])
def __set_attributes(self, attrs):
sys.stdout.write(_ESC + '[' + str((attrs & 0b111000000) >> 6)+ ';' +
str(((attrs & 0b111000) >> 3) + _FG) + ';' +
str((attrs & 0b111) + _BG) + 'm')
sys.stdout.flush()
def __setCursorPos(self, pos):
sys.stdout.write(_ESC + '[' + str(pos[1] % self.size[1]) + ';' +
str(pos[0] & self.size[0]) + 'f')
sys.stdout.flush()
def __cls(self):
sys.stdout.write(_ESC + '[2J')
sys.stdout.flush()
if __name__ == '__main__':
term = AsciiTerminal()
term.set_background(0, _RED)
term.frame()
term.close()
|
18,838 | 737e4959f4028803b68e175d32a419988891ccb9 | from __future__ import division
import os
import random
import sys
import logging
import cv2
import fire
import numpy as np
import tensorflow as tf
import tensorflow.contrib.metrics as metrics
import time
import pickle
import commons
from configs import VGGConf
from networks import VGG16
from pystopwatch import StopWatchManager
_log_level = logging.DEBUG
_logger = logging.getLogger('ADNetRunner')
_logger.setLevel(_log_level)
ch = logging.StreamHandler(sys.stdout)
ch.setLevel(_log_level)
formatter = logging.Formatter('[%(asctime)s] [%(name)s] [%(levelname)s] %(message)s')
ch.setFormatter(formatter)
_logger.addHandler(ch)
class VGGRunner:
MAX_BATCHSIZE = 512
def __init__(self):
self.tensor_input = tf.placeholder(tf.float32, shape=(None, 128, 128, 3), name='input')
self.tensor_lb = tf.placeholder(tf.int32, shape=(None, ), name='lb_action')
self.tensor_is_training = tf.placeholder(tf.bool, name='is_training')
self.learning_rate_placeholder = tf.placeholder(tf.float32, [], name='learning_rate')
config = tf.ConfigProto() #log_device_placement=True)
self.persistent_sess = tf.Session(config=config)
self.model = VGG16(self.learning_rate_placeholder)
self.model.create_network(self.tensor_input, self.tensor_lb, self.tensor_is_training)
#self.persistent_sess.run(tf.global_variables_initializer())
self.model.read_original_weights(self.persistent_sess)
self.iteration = 0
self.imgwh = None
self.loss = []
self.train, self.test =[], []
self.train_lb, self.test_lb = [], []
self.stopwatch = StopWatchManager()
def read_train_test(self, data_path, is_train=True):
path = commons.get_image_pathes(data_path)
images, labels = commons.read_image_lb_path(path, is_train)
train_f_num = VGGConf.g()['train_folder_num']
test_f_num = VGGConf.g()['test_folder_num']
f_num = train_f_num + test_f_num
print(f_num)
assert f_num == len(images)
assert len(images) == len(labels)
for idx in range(f_num):
if idx < train_f_num:
if not is_train: continue
self.train.extend(images[idx])
self.train_lb.extend(labels[idx])
print("Train data is added")
else:
self.test.extend(images[idx])
self.test_lb.extend(labels[idx])
print("Test data is added")
_temp = [0,0,0,0,0]
for i, a in enumerate(self.train_lb):
_temp[int(a)]+=1
print("Trainind Data Label Distribution: ", _temp)
print("READING DATA IS COMPLETED")
def label_index(self):
label_array = np.array(self.test_lb)
self.lb_idx = []
for i in range(5):
self.lb_idx.append(list(np.where(label_array==i)))
def run_train(self, data_path='./data'):
train = pickle.load(open('train_img.txt','rb'))
self.train, self.train_lb = [], []
for lb in range(5):
self.train.extend(train[lb])
num_lb = len(train[lb])
self.train_lb.extend([lb]*num_lb)
#self.read_train_test(data_path)
train_num = len(self.train)
train_index = list(range(train_num))
EPOCH = VGGConf.g()['epoch']
BATCH_SIZE = VGGConf.g()['minibatch_size']
BATCH_NUM = int(len(train_index)/BATCH_SIZE) - 1
learning_rate = VGGConf.g()['learning_rate']
print("START TO TRAIN")
for epoch_iter in range(EPOCH):
iter = 0
#if epoch_iter != 0 and epoch_iter % 100 ==0 : learning_rate *= 0.5
random.shuffle(train_index)
#for i in range(5): random.shuffle(self.lb_idx[i])
for batch_iter in range(BATCH_NUM):
batch_img = commons.choices_by_idx(self.train, train_index[iter*BATCH_SIZE: (iter+1)*BATCH_SIZE])
batch_lb = commons.choices_by_idx(self.train_lb, train_index[iter*BATCH_SIZE: (iter+1)*BATCH_SIZE])
_, loss = self.persistent_sess.run(
[self.model.opt, self.model.loss],
feed_dict={
self.tensor_input: np.array(batch_img)/255.,
self.tensor_lb: batch_lb,
self.learning_rate_placeholder: learning_rate,
self.tensor_is_training: True
}
)
print("{}/{} BATCH LOSS: {}".format(batch_iter, BATCH_NUM, np.sum(loss)))
iter +=1
self.model.save_train_model(self.persistent_sess, VGGConf.g()['save_weight_dir'])
self.run_test(weight_load=False)
def run_test(self, weight_load=True, data_path='./data'):
test = pickle.load(open('test_img.txt','rb'))
self.test, self.test_lb = [], []
for lb in range(5):
self.test.extend(test[lb])
num_lb = len(test[lb])
self.test_lb.extend([lb]*num_lb)
MAX_BATCHSIZE = self.MAX_BATCHSIZE
if weight_load:
#self.read_train_test(data_path, is_train=False)
self.model.read_original_weights(self.persistent_sess)
test_num = len(self.test)
if test_num % self.MAX_BATCHSIZE == 0 :
test_batch_num = int(test_num / self.MAX_BATCHSIZE)
else:
test_batch_num = int(test_num / self.MAX_BATCHSIZE) + 1
test_output = []
test_idx = list(range(test_num))
test_iter = 0
print("START TO TEST")
for batch_iter in range(test_batch_num):
if batch_iter == test_batch_num - 1:
batch_img = commons.choices_by_idx(self.test, test_idx[test_iter*MAX_BATCHSIZE:])
batch_lb = commons.choices_by_idx(self.test_lb, test_idx[test_iter*MAX_BATCHSIZE:])
else:
batch_img = commons.choices_by_idx(self.test, test_idx[test_iter*MAX_BATCHSIZE: (test_iter+1)*MAX_BATCHSIZE])
batch_lb = commons.choices_by_idx(self.test_lb, test_idx[test_iter*MAX_BATCHSIZE: (test_iter+1)*MAX_BATCHSIZE])
output = self.persistent_sess.run(
self.model.output, feed_dict={
self.tensor_input: np.array(batch_img)/255.,
self.tensor_lb: batch_lb,
self.tensor_is_training: False
}
)
test_output.extend(output)
test_iter +=1
pickle.dump(self.test_lb, open('./gt.txt', 'wb'))
pickle.dump(test_output, open('./pred.txt', 'wb'))
accuracy = 0.0
for idx, output in enumerate(test_output):
max_idx = np.argmax(output)
if max_idx == int(self.test_lb[idx]): accuracy+=1.0
accuracy = accuracy / (len(self.test_lb))
print("Test Accuracy: ", accuracy)
def _get_features(self, samples):
feats = []
for batch in commons.chunker(samples, ADNetRunner.MAX_BATCHSIZE):
feats_batch = self.persistent_sess.run(self.adnet.layer_feat, feed_dict={
self.adnet.input_tensor: batch
})
feats.extend(feats_batch)
return feats
# train_fc_finetune_hem
self._finetune_fc(
img, pos_boxes, neg_boxes, pos_lb_action,
ADNetConf.get()['initial_finetune']['learning_rate'],
ADNetConf.get()['initial_finetune']['iter']
)
self.histories.append((pos_boxes, neg_boxes, pos_lb_action, np.copy(img), self.iteration))
_logger.info('ADNetRunner.initial_finetune t=%.3f' % t)
self.stopwatch.stop('initial_finetune')
def __del__(self):
self.persistent_sess.close()
if __name__ == '__main__':
VGGConf.get('./conf/conf.yaml')
random.seed(1258)
np.random.seed(1258)
tf.set_random_seed(1258)
fire.Fire(VGGRunner)
|
18,839 | 2b3b54ae787394a82f5e8e2c089948e8dc1be13b | import psycopg2, os, pickle
import simplejson as json
import pandas as pd
from collections import defaultdict
from classification_common import *
from text_utils import *
db='o360'
username='ryan'
hostname='192.168.11.31'
def concept_export():
conn = psycopg2.connect(dbname=db, user=username, host=hostname)
cur = conn.cursor()
try:
cur.execute("""select c.name concept_name,
initcap(c.name) concept_display,
enabled,
cd.name domain_name,
concept_terms,
concept_x,
concept_y
from concept c
inner join concept_terms ct on (ct.concept_id = c.id)
inner join concept_domain cd on (cd.id = c.domain_id)
inner join concept_xy xy on (xy.concept_name = c.name)""")
rows = cur.fetchall()
finally:
cur.close()
conn.close()
concepts = []
for row in rows:
concept_id = row[0]
concept = {}
concept['id'] = concept_id
concept['name'] = row[1]
concept['enabled'] = row[2]
concept['domain'] = row[3]
term_str = row[4]
concept['terms'] = [ [ tw.split(';')[0], float(tw.split(';')[1]) ] for tw in term_str.split('|') ]
concepts.append(concept)
concept['concept_x'] = row[5]
concept['concept_y'] = row[6]
return concepts
def build_series(concepts, vector_dir, min_score=.5):
concept_series = defaultdict(lambda: [])
for concept in concepts:
print '\t', concept['id']
pos_concept = concept['id']
neg_concept = 'random'
pipeline = pickle.load(open(concept_pipeline(pos_concept, neg_concept), 'rb'))
classifier = pipeline.named_steps['classifier']
concept_series[pos_concept].append( ['Week', 'Signal'] )
vecfiles = os.listdir(vector_dir)
vecfiles.sort()
for vecfile in vecfiles:
X_sel = pickle.load(open(vector_dir+'/'+vecfile, 'r'))
tokens = vecfile.split('-')
week_dir = '-'.join(tokens[:3])
probs = classifier.predict_proba(X_sel)
pos_indices = [ i for i in range(X_sel.shape[0]) if probs[i,1] > min_score]
range_pct = (len(pos_indices) / float(X_sel.shape[0])) * 100.0
concept_series[pos_concept].append( [week_dir, range_pct] )
return concept_series
def append_concept_pcts(concepts):
SIG_FILE = os.environ['NM_HOME']+'/Data/concept_percentages.csv'
signals = {}
df = pd.read_csv(SIG_FILE, index_col=0)
for row in df.iterrows():
concept = row[0]
digitalTotalPct = row[1][0]
nmTotalPct = row[1][1]
digital3month = row[1][2]
nmRev3month = row[1][3]
nmRevPct3month = row[1][4]
nmRevDelta3Month = row[1][5]
signals[concept] = (digitalTotalPct, nmTotalPct, digital3month, nmRev3month, nmRevPct3month, nmRevDelta3Month)
for concept in concepts:
ss = signals[ concept['id'] ]
concept['digital_total_pct'] = ss[0]
concept['nm_total_pct'] = ss[1] ###*** Temporary (see below)
concept['3m_digital_pct'] = ss[2]
concept['3m_nm_revenue'] = ss[3]
concept['3m_nm_revenue_pct'] = ss[4]
concept['3m_nm_delta_revenue'] = ss[5]
return concepts
def append_digital_series(concepts, vector_dir):
print 'Building weekly series'
signals = build_series(concepts, vector_dir)
for concept in concepts:
weekly_signal = signals[ concept['id'] ]
smoothed_signal = pd.read_csv('/tmp/'+concept['id']+'-smooth-signal.csv')
smoothed = []
smoothed.append(['Week', 'Signal'])
for row in smoothed_signal.itertuples():
smoothed.append( [ row[1], row[2] ] )
#concept['series_weekly_digital'] = weekly_signal
concept['smoothed_weekly_digital_pct'] = smoothed
return concepts
def append_saks_dress_pct(concepts):
concept_dress = {}
dress_df = pd.read_csv( os.environ['NM_HOME']+'/Data/nm_saks_pct.csv')
for row in dress_df.itertuples():
concept = row[1]
nm_pct = row[2]
saks_pct = row[3]
concept_dress[concept] = (nm_pct, saks_pct)
for concept in concepts:
ss = concept_dress[ concept['id'] ]
concept['nm_product_pct'] = ss[0]
concept['saks_product_pct'] = ss[1]
return concepts
def write_file(concepts, filename):
with open(filename, 'w') as f:
f.write(json.dumps(concepts, sort_keys=True, indent=4))
f.flush()
VECTOR_DIR = os.environ['NM_HOME']+'/Data/Temporal/vectors'
concepts = concept_export()
concepts = append_concept_pcts(concepts)
concepts = append_digital_series(concepts, VECTOR_DIR)
concepts = append_saks_dress_pct(concepts)
write_file(concepts, '/tmp/concept_export.json') |
18,840 | eda7d631cebc64db1c3c9347421a9a4bb9747e4c | import webbrowser, sys, pyperclip
sys.argv # ['mapit.py', '200', 'elim nagar', 'perungudi']
#Check if commant line arguments were passed
if len(sys.argv) > 1:
# ['mapit.py', '200', 'elim nagar', 'perungudi'] -> ' 200 elim nagar perungui'
address = ' '.join(sys.argv[1:])
else:
address = pyperclip.paste()
webbrowser.open('https://www.google.com/maps/place/' + address)
|
18,841 | b3d86eaf26985d94d03b9d721e57e25383c34727 | # !/usr/bin/env python
# -*- coding:utf-8 -*-
# project name: Android_Ui_Automation
# author: "Lei Yong"
# creation time: 2018/1/10 下午6:35
# Email: leiyong711@163.com
import os
import re
def getDevices():
# 获取手机信息
def Info():
# 手机信息正则限制
def modified(name):
try:
reu = list(os.popen(name).readlines())
return re.findall('.*', reu[0])[0] # ([^\s\\\]+)
except:
return 'Get error'
brand = modified('adb shell getprop ro.product.brand') # 读取手机品牌
phone_models = modified('adb shell getprop ro.semc.product.name') # 读取设备型号
deviceVersion = modified('adb shell getprop ro.build.version.release') # 读取设备系统版本号
readDeviceId = list(os.popen('adb devices').readlines()) # 读取设备 id
devices = str(readDeviceId[1])[:-8] # 正则表达式匹配出 id 信息
# devices = re.findall(r'^\w*\b', readDeviceId[1])[0] # 正则表达式匹配出 id 信息
# if phone_models == '':
# phone_models = u'获取失败'
if not devices:
devices = 'Get error'
return brand, phone_models, deviceVersion, devices # 返回品牌、型号、系统版本、设备id
# 得到运行内存
def men(devices):
cmd = "adb -s "+devices+ " shell cat /proc/meminfo"
get_cmd = os.popen(cmd).readlines()
men_total = 0
men_total_str = "MemTotal"
for line in get_cmd:
if line.find(men_total_str) >= 0:
men_total = line[len(men_total_str) +1:].replace("kB", "").strip()
break
ram = int(men_total) / 1024
return str(ram) + "MB"
# 得到CPU核心数
def cpu(devices):
cmd = "adb -s " +devices +" shell cat /proc/cpuinfo"
get_cmd = os.popen(cmd).readlines()
find_str = "processor"
int_cpu = 0
for line in get_cmd:
if line.find(find_str) >= 0:
int_cpu += 1
return str(int_cpu) + "核"
# 得到手机分辨率
def appPix(devices):
try:
result = os.popen("adb -s %s shell wm size" % devices, "r")
return result.readline().split("Physical size:")[1]
except:
return 'Get error'
# 获取电量
def batteryCapacity():
get_cmd = os.popen("adb shell dumpsys battery").readlines()
for i in range(0, len(get_cmd)):
a = str(get_cmd[i])
b = 'level'
p = a.find(b)
try:
if p != -1:
s = get_cmd[i].split('level')
Battery = "".join(s).strip('\n').strip("'").strip(' : ')
return int(Battery)
except:
return u'获取电量失败'
return 'Get error'
startPower = batteryCapacity()
brand, model, systemVersion, deviceId = Info() # 返回品牌、型号、系统版本、设备id
men = men(deviceId)
cpu = cpu(deviceId)
appPix = appPix(deviceId)
x = ["brand = %s\nmodel = %s\nplatformName = Android\nsystemVersion = %s\ndeviceId = %s\nmen = %s\ncpu = %s\nappPix = %s\nstartPower = %s\n"
% (brand, model, systemVersion, deviceId, men, cpu, appPix, startPower)]
with open("../config/app.conf", "a") as f: # 写出应用配置信息
f.write("\n[phoneConf]\n")
for i in x:
f.write(i)
# 获取启动类
if __name__ == '__main__':
getDevices()
|
18,842 | 10d5b45b8e1ed3f4996554b0575a0e25e7580099 | import sublime, sublime_plugin
_start = -1
class StartSelection(sublime_plugin.TextCommand):
def run(self, edit):
global _start
for sel in self.view.sel():
if sel.empty():
_start = sel.begin()
class EndSelection(sublime_plugin.TextCommand):
def run(self, edit):
global _start
start = _start
end = -1
for sel in self.view.sel():
if sel.empty():
end = sel.begin()
if start != -1 and end != -1:
self.view.sel().clear()
self.view.sel().add(sublime.Region(start, end))
|
18,843 | baf7e27310fe7b9f191ea1566fb7a2edbb459a81 | import pymongo
###Connection
myclient = pymongo.MongoClient("mongodb://localhost:27017/")
mydb = myclient["mydatabase"] # Db
mycol = mydb["customers"] #table
x = mycol.find({},{ "_id": 0, "name": 1, "address": 1 })
# x = mycol.find({},{ "address": 0 })
for y in x:
print(y) |
18,844 | 8106d062f12b060461a7d9cea7969dae412cd6a7 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import locality.models
class Migration(migrations.Migration):
dependencies = [
('locality', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Ballot',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('date', models.DateField(default=None, help_text=b'The day of the election.', null=True)),
('locality', models.ForeignKey(to='locality.Locality')),
],
options={
'ordering': ('date', 'locality__name', 'locality__short_name'),
},
),
migrations.CreateModel(
name='BallotItem',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('contest_type', models.CharField(help_text=b'Office if the contest is for a person, referendum if the contest is for an issue.', max_length=1, choices=[(b'R', b'Referendum'), (b'O', b'Office')])),
],
options={
'ordering': ('ballot__date', 'ballot__locality__short_name', 'ballot__locality__name'),
},
bases=(models.Model, locality.models.ReverseLookupStringMixin),
),
migrations.CreateModel(
name='BallotItemSelection',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
],
options={
'ordering': ('ballot_item__ballot__date', 'ballot_item__ballot__locality__short_name', 'ballot_item__ballot__locality__name'),
},
bases=(models.Model, locality.models.ReverseLookupStringMixin),
),
migrations.CreateModel(
name='Office',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('name', models.CharField(help_text='The office name.', max_length=255)),
('description', models.CharField(help_text='The office description.', max_length=1024)),
('locality', models.ForeignKey(to='locality.Locality')),
],
options={
'ordering': ('locality__short_name', 'locality__name', 'name'),
},
),
migrations.CreateModel(
name='Party',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('photo_url', models.ImageField(default=None, null=True, upload_to=b'', blank=True)),
('website_url', models.URLField(default=None, null=True, blank=True)),
('facebook_url', models.URLField(default=None, null=True, blank=True)),
('twitter_url', models.URLField(default=None, null=True, blank=True)),
('name', models.CharField(help_text='The party name.', max_length=255)),
],
options={
'ordering': ('name',),
'verbose_name_plural': 'parties',
},
),
migrations.CreateModel(
name='Candidate',
fields=[
('ballotitemselection_ptr', models.OneToOneField(parent_link=True, auto_created=True, primary_key=True, serialize=False, to='ballot.BallotItemSelection')),
('photo_url', models.ImageField(default=None, null=True, upload_to=b'', blank=True)),
('website_url', models.URLField(default=None, null=True, blank=True)),
('facebook_url', models.URLField(default=None, null=True, blank=True)),
('twitter_url', models.URLField(default=None, null=True, blank=True)),
('first_name', models.CharField(default=None, max_length=255, null=True, help_text="The person's first name.")),
('middle_name', models.CharField(default=None, max_length=255, null=True, help_text="The person's middle name.", blank=True)),
('last_name', models.CharField(help_text="The person's last name.", max_length=255)),
],
options={
'ordering': ('ballot_item__ballot__date', 'ballot_item__ballot__locality__short_name', 'ballot_item__ballot__locality__name', 'office_election__office__name', 'last_name', 'first_name', 'middle_name'),
},
bases=('ballot.ballotitemselection', models.Model),
),
migrations.CreateModel(
name='OfficeElection',
fields=[
('ballotitem_ptr', models.OneToOneField(parent_link=True, auto_created=True, primary_key=True, serialize=False, to='ballot.BallotItem')),
('office', models.ForeignKey(to='ballot.Office')),
],
options={
'ordering': ('ballot__date', 'ballot__locality__short_name', 'ballot__locality__name', 'office__name'),
},
bases=('ballot.ballotitem',),
),
migrations.CreateModel(
name='Referendum',
fields=[
('ballotitem_ptr', models.OneToOneField(parent_link=True, auto_created=True, primary_key=True, serialize=False, to='ballot.BallotItem')),
('photo_url', models.ImageField(default=None, null=True, upload_to=b'', blank=True)),
('website_url', models.URLField(default=None, null=True, blank=True)),
('facebook_url', models.URLField(default=None, null=True, blank=True)),
('twitter_url', models.URLField(default=None, null=True, blank=True)),
('title', models.CharField(help_text='The referendum title', max_length=255)),
('number', models.CharField(default=None, max_length=5, null=True, help_text="The referendum's number or letter.")),
],
options={
'ordering': ('ballot__date', 'ballot__locality__short_name', 'ballot__locality__name', 'number', 'title'),
},
bases=('ballot.ballotitem', models.Model),
),
migrations.CreateModel(
name='ReferendumSelection',
fields=[
('ballotitemselection_ptr', models.OneToOneField(parent_link=True, auto_created=True, primary_key=True, serialize=False, to='ballot.BallotItemSelection')),
('photo_url', models.ImageField(default=None, null=True, upload_to=b'', blank=True)),
('website_url', models.URLField(default=None, null=True, blank=True)),
('facebook_url', models.URLField(default=None, null=True, blank=True)),
('twitter_url', models.URLField(default=None, null=True, blank=True)),
('in_favor', models.NullBooleanField(default=None)),
],
options={
'abstract': False,
},
bases=('ballot.ballotitemselection', models.Model),
),
migrations.AddField(
model_name='ballotitemselection',
name='ballot_item',
field=models.ForeignKey(to='ballot.BallotItem'),
),
migrations.AddField(
model_name='ballotitem',
name='ballot',
field=models.ForeignKey(related_name='ballot_items', to='ballot.Ballot'),
),
migrations.AddField(
model_name='candidate',
name='office_election',
field=models.ForeignKey(to='ballot.OfficeElection'),
),
migrations.AddField(
model_name='candidate',
name='party',
field=models.ForeignKey(default=None, blank=True, to='ballot.Party', null=True),
),
]
|
18,845 | 416754307d4c3233c246de5b77db5b7e8c18990d | __author__ = 'ejanlav'
from abc import ABCMeta, abstractmethod
class ChromosomeFactory:
__metaclass__ = ABCMeta
@abstractmethod
def create_random_chromosome(self):
pass
@abstractmethod
def create_chromosome(self, bits):
pass
|
18,846 | 833d578fefa9e3f7d3bc7d0309fa08627b113227 | print('Hello, Welcome to the Radian Counter')
degrees = input('Please input your angle here : ')
radian = float(degrees) * 3.14 / 180
print('Your radian is', radian)
print('Thankyou for using Radian Converter') |
18,847 | 987d6601c4e86288d19de9d731662f8a450c17b9 | #for문 _ 인덱스 이용4
my_list = [100, 200, 400, 800]
for i in range(len(my_list) -1):
print(my_list[i+1]-my_list[i]) |
18,848 | 9bd8101702fce9f3ba17da0fd1bbcdec3fabc867 | import boto3
import smtplib
import pandas as pd
from time import strftime
from extData.sele_v2 import dataExt
from em.ol.olProps import olProps_var
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from aws.meyita.props.pgprodConProps import pgprod_prop
class morningPending():
def __init__(self):
# connection string reference to rds
con = pgprod_prop()
# Query determines the hight of pending loans right before funding occurs
qry_Pend = """
select
pd,
cntformer,
sumformer,
cntnewdm,
sumnewdm,
cntnew,
sumnew,
cnttotal,
sumtotal
FROM <table>
WHERE sumtotal = (
SELECT DISTINCT
max(sumtotal)
FROM <table name>
WHERE pd = current_date
--WHERE pd = '2019-01-29'
AND ph in (4,5,6,7))
AND pd = current_date;
"""
# pandas dataframe
df_Pend = pd.read_sql_query(qry_Pend, con.pgprodcon)
df_Pend = df_Pend.drop_duplicates()
self.cntFormer = format(int(df_Pend['cntformer']), ',')
self.revFormerTotal = format(int(df_Pend['sumformer']), ',')
self.cnt_new_dm_Total = format(int(df_Pend['cntnewdm']), ',')
self.revNew_dm_Total = format(int(df_Pend['sumnewdm']), ',')
self.cntNewTotal = format(int(df_Pend['cntnew']), ',')
self.revNewTotal = format(int(df_Pend['sumnew']), ',')
self.cntTotal = format(int(df_Pend['cnttotal']), ',')
self.revFundedTotal = format(int(df_Pend['sumtotal']), ',')
self.calcPendingTotal = int(df_Pend['sumtotal'])
def mornPending_var():
return mornPending()
# Get, Set CVF from previous day
class mornCVF():
# if the value of CVF is null or an error then it will auto assign $50,000
def __init__(self):
# connection string reference to rds
con = pgprod_prop()
# Retrieves the cvf from the previous night
qry_mornCVF = """
select ulday, sumh from <table name> where ulday = current_date - 1;
"""
# pandas dataframe
df_mornCVF = pd.read_sql_query(qry_mornCVF, con=con.pgprodcon)
df_mornCVF = df_mornCVF.drop_duplicates()
try:
blankIndex = [''] * len(df_mornCVF)
df_mornCVF.index = blankIndex
self.sumH = df_mornCVF['sumh'].astype(float)
except Exception as e:
print("CVF calculation error: " + str(e))
self.sumH = float(50000)
def mornCVF_var():
return mornCVF()
# Get, Set 4 am added loans sumtotal from previous day
class morn4amloansTotal():
def __init__(self):
# Retrieves the 4 am added loans
con = pgprod_prop()
qry_4amloans = """select max(sumtotal) as sumtotal from <table name>s where pd = current_date"""
fourDF = pd.read_sql_query(sql=qry_4amloans, con=con.pgprodcon)
fourDF = fourDF.drop_duplicates()
try:
blankIndex = [''] * len(fourDF)
fourDF.index = blankIndex
self.fourAMAddedLoansSumtotal = fourDF['sumtotal']
except Exception as e:
print("4 am clac error: " + str(e))
#print(fourDF['sumtotal'])
def morn4amloansTotal_var():
return morn4amloansTotal()
# Get, Set 5 am added loans sumtotal from previous day
class morn5amloansTotal():
def __init__(self):
# Retrieves the 5 am added loans
con = pgprod_prop()
qry_5amloans = """select max(sumtotal) as sumtotal from <table name> where pd = current_date"""
fiveDF = pd.read_sql_query(sql=qry_5amloans, con=con.pgprodcon)
fiveDF = fiveDF.drop_duplicates()
try:
blankIndex = [''] * len(fiveDF)
fiveDF.index = blankIndex
self.fiveAMAddedLoansSumtotal = fiveDF['sumtotal']
except Exception as e:
print("5 am clac error: " + str(e))
def morn5amloansTotal_var():
return morn5amloansTotal()
# Get, Set 6 am added loans sumtotal from previous day
class morn6amloansTotal():
def __init__(self):
# Retrieves the 5 am added loans
con = pgprod_prop()
qry_6amloans = """select max(sumtotal) as sumtotal from <table name> where pd = current_date"""
sixDF = pd.read_sql_query(sql=qry_6amloans, con=con.pgprodcon)
sixDF = sixDF.drop_duplicates()
try:
blankIndex = [''] * len(sixDF)
sixDF.index = blankIndex
self.sixAMAddedLoansSumtotal = sixDF['sumtotal']
except Exception as e:
print("6 am clac error: " + str(e))
def morn6amloansTotal_var():
return morn6amloansTotal()
# download raw and upload aggrigates to rds
def morn4amLoansDLUL():
dataExt(turl=["Loan_Search2","exit"])
#print('Starting morning forecast')
var = pgprod_prop()
con = var.pgprodcon
cursor = con.cursor()
try:
cd = strftime("%m/%d/%Y")
tr = cd + ' 04'
lsRaw = "<file path>"
df = pd.read_csv("<file path>",
index_col='Loan#')
df['Loan Amount'] = df[df.columns[10]].replace('[\$,]', '', regex=True).astype(float)
newLoans = df[df['Loan Date/Time'].str.contains(tr)].sum().fillna(0)['Loan Amount']
lsCalc = newLoans
qryrf = """
INSERT INTO
<table name> (pd,sumtotal)
VALUES (current_date,""" + str(lsCalc) + """)
"""
cursor.execute(qryrf)
con.commit()
cursor.close()
con.close()
except Exception as e:
#print("4 am Loans failed: " + str(e))
try:
day = strftime("%d")
month = strftime("%m")
year = strftime("%Y")
date = year + "-" + month + "-" + day
lsCalce = int(0)
qryrf = """
INSERT INTO
<table name> (pd,sumtotal)
VALUES (current_date,""" + str(lsCalce) + """)
"""
cursor.execute(qryrf)
con.commit()
cursor.close()
con.close()
except Exception as e:
print("Back up 4 am Loans failed: " + str(e))
def morn5amLoansDLUL():
dataExt(turl=["Loan_Search2","exit"])
#print('Starting morning forecast')
var = pgprod_prop()
con = var.pgprodcon
cursor = con.cursor()
try:
cd = strftime("%m/%d/%Y")
tr = cd + ' 05'
lsRaw = "C<file path>"
df = pd.read_csv("<file path>",
index_col='Loan#')
df['Loan Amount'] = df[df.columns[10]].replace('[\$,]', '', regex=True).astype(float)
newLoans = df[df['Loan Date/Time'].str.contains(tr)].sum().fillna(0)['Loan Amount']
lsCalc = newLoans
#print(lsCalc)
qryrf = """
INSERT INTO
<table name> (pd,sumtotal)
VALUES (current_date,""" + str(lsCalc) + """)
"""
cursor.execute(qryrf)
con.commit()
cursor.close()
con.close()
except Exception as e:
print("5 am Loans failed: " + str(e))
try:
day = strftime("%d")
month = strftime("%m")
year = strftime("%Y")
date = year + "-" + month + "-" + day
lsCalce = int(0)
qryrf = """
INSERT INTO
<table name> (pd,sumtotal)
VALUES (current_date,""" + str(lsCalce) + """)
"""
cursor.execute(qryrf)
con.commit()
cursor.close()
con.close()
except Exception as e:
print("Back up 5 am Loans failed: " + str(e))
def morn6amLoansDLUL():
dataExt(turl=["Loan_Search2","exit"])
#print('Starting morning forecast')
var = pgprod_prop()
con = var.pgprodcon
cursor = con.cursor()
try:
cd = strftime("%m/%d/%Y")
tr = cd + ' 06'
lsRaw = "<csv file location>"
df = pd.read_csv("<csv file location>",
index_col='Loan#')
df['Loan Amount'] = df[df.columns[10]].replace('[\$,]', '', regex=True).astype(float)
newLoans = df[df['Loan Date/Time'].str.contains(tr)].sum().fillna(0)['Loan Amount']
lsCalc = newLoans
#print(lsCalc)
qryrf = """
INSERT INTO
<table name> (pd,sumtotal)
VALUES (current_date,""" + str(lsCalc) + """)
"""
cursor.execute(qryrf)
con.commit()
cursor.close()
con.close()
except Exception as e:
print("6 am Loans failed: " + str(e))
try:
day = strftime("%d")
month = strftime("%m")
year = strftime("%Y")
date = year + "-" + month + "-" + day
lsCalce = int(0)
qryrf = """
INSERT INTO
<table name> (pd,sumtotal)
VALUES (current_date,""" + str(lsCalce) + """)
"""
cursor.execute(qryrf)
con.commit()
cursor.close()
con.close()
except Exception as e:
print("Back up 6 am Loans failed: " + str(e))
# Morning Forecast Calculation
class mornForecastCalc():
def __init__(self):
#print("Start Morning Forecast")
if morn4amloansTotal_var().fourAMAddedLoansSumtotal is None :
addL4 = 0
else:
addL4 = morn4amloansTotal_var().fourAMAddedLoansSumtotal
if morn5amloansTotal_var().fiveAMAddedLoansSumtotal is None:
addL5 = 0
else:
addL5 = morn5amloansTotal_var().fiveAMAddedLoansSumtotal
if morn6amloansTotal_var().sixAMAddedLoansSumtotal is None:
addL6 = 0
else:
addL6 = morn6amloansTotal_var().sixAMAddedLoansSumtotal
cvf = mornCVF_var().sumH
mp = mornPending_var().calcPendingTotal
#print("4 am added loans: " + str(addL4))
#print("5 am added loans: " + str(addL5))
#print("6 am added loans: " + str(addL6))
#print("CVF total: " + str(cvf))
#print("Pending total: " + str(mp))
addedLoans = [addL4, addL5, addL6]
hrR = max(addedLoans, key=lambda item:item[0])
print('Loans Added per Hour')
print(hrR)
totalHrR = hrR * 8
print('Total loans per hour')
print(totalHrR)
print('cfv')
print(cvf)
#print("added by hour: " + str(hrR))
self.morningFundingForecast = ((hrR * 8) + mp) + cvf
print("morning forecast is: " + str(self.morningFundingForecast))
def mornForecastCalc_var():
return mornForecastCalc()
# Load Morning Forecast to rds table
def mornforecastUL():
var = pgprod_prop()
con = var.pgprodcon
cursor = con.cursor()
mf = int(mornForecastCalc_var().morningFundingForecast)
qryrf = """
INSERT INTO
<table name> (pd,mornforecast)
VALUES (current_date,""" + str(mf) + """)
"""
cursor.execute(qryrf)
con.commit()
cursor.close()
con.close()
# mornforecast DynamoDB UL
def mornforecastDynamoDBUL():
cd = strftime("%Y-%m-%d")
mf = int(mornForecastCalc_var().morningFundingForecast)
sesh = boto3.Session()
dynamodb = sesh.resource('dynamodb', region_name="us-east-2")
table = dynamodb.Table('<table name>')
table.put_item(
Item={
"uldate":cd,
"mornforecast": mf
}
)
print("Successfully updated mornforecast table in dynamoDB")
# risk forecast
class mornRiskCalc():
def __init__(self):
con = pgprod_prop()
print('initiating risk forecast')
qry_rf = """
SELECT
*
FROM <table name>
WHERE CAST(fdate as date) = current_date;
"""
# risk forecast
rfDF = pd.read_sql_query(qry_rf, con.pgprodcon)
self.rfTotal = format(int(rfDF['ftotal']), ',')
#print('rftotal')
print(self.rfTotal)
def mornRiskCalc_var():
return mornRiskCalc()
# email report
def morningFundingReportEM():
msg = MIMEMultipart()
recpSolo = ["<Your email>"]
recpTest = ["<your test distro>"]
recp = ["<your distro list>"]
sender = "<your email address>"
msg['To'] = ", ".join(recpSolo)
msg['From'] = sender
msg['Subject'] = "<your subject line>"
bodyORG = MIMEText("""
<html>You HTML for the email.</html>
""", 'html', 'utf-8')
msg.attach(bodyORG)
olp = olProps_var()
s = smtpserver = smtplib.SMTP("smtp-mail.outlook.com", 587)
smtpserver.ehlo()
smtpserver.starttls()
smtpserver.login(olp.MSUS, olp.MSPS)
s.sendmail(sender, recpSolo, msg.as_string())
print('done!')
s.close()
|
18,849 | 93318111f44618e4453e61f0097f691ff3c1103d | from django.contrib import admin
# Register your models here.
from administration.models import Etudiant, Promotion,Departement,Personnel,Filiere,Specialite,Classe,Enseignent
class EtudiantAdmin(admin.ModelAdmin):
exclude = ('profil',)
fields = (('nom', 'prenom'),('telephon','email'),('ine','classe','promotion'),('cni','user'))
list_display = ('nom', 'prenom','telephon','email', 'ine','classe')
list_filter = ('classe','classe__specialite','classe__specialite__filiere')
search_fields = ('ine', 'nom', 'prenom')
class EnseignentAdmin(admin.ModelAdmin):
exclude = ('profil',)
fieldsets = (
("Information Personnelle", {
'fields': ('nom', 'prenom', 'cni','user')
}),
('Information Suplémentaire', {
'classes': ('wide ', 'extrapretty'),
'fields': ('telephon','email','departement'),
}),
)
list_display = ('nom', 'prenom', 'cni','telephon','email','departement','profil')
list_filter = ('departement',)
search_fields = ('cni', 'nom', 'prenom')
class ClasseAdmin(admin.ModelAdmin):
exclude = ('code',)
list_display = ('code', 'anneeScolaire', 'specialite')
list_filter = ('specialite','specialite__filiere')
search_fields = ('code','anneeScolaire')
class SpecialiteAdmin(admin.ModelAdmin):
exclude = ('code',)
list_display = ('code', 'nom', 'filiere')
list_filter = ('filiere','filiere__departement')
search_fields = ('code', 'nom')
class FiliereAdmin(admin.ModelAdmin):
exclude = ('code',)
list_display = ('code', 'nom', 'departement')
list_filter = ('departement',)
search_fields = ('code', 'nom')
class DepartementAdmin(admin.ModelAdmin):
exclude = ('code',)
list_display = ('code', 'nom')
search_fields = ('code', 'nom')
class PromotionAdmin(admin.ModelAdmin):
exclude = ('code',)
list_display = ('code', 'nom')
search_fields = ('code', 'nom')
class PersonnelAdmin(admin.ModelAdmin):
exclude = ('profil',)
fields = (('nom', 'prenom'),('telephon','email'),('cni','user'))
list_display = ('nom', 'prenom','telephon','email','cni','profil','user')
admin.site.register(Personnel, PersonnelAdmin)
admin.site.register(Etudiant, EtudiantAdmin)
admin.site.register(Enseignent, EnseignentAdmin)
admin.site.register(Classe, ClasseAdmin)
admin.site.register(Specialite, SpecialiteAdmin)
admin.site.register(Filiere, FiliereAdmin)
admin.site.register(Departement, DepartementAdmin)
admin.site.register(Promotion, PromotionAdmin)
|
18,850 | bf4ec1aff600f2fb28cab38f5916e6519f42b3d0 | # baekjoon source = "https://www.acmicpc.net/problem/10951"
while True:
try:
a,b = map(int,input().split())
except:
break
print(a+b) |
18,851 | 18cc07319531661afb280cbc09f13f16da90e6cb | # Generated by Django 3.0.8 on 2020-07-22 12:22
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("basket", "0008_auto_20190926_1547"),
]
operations = [
migrations.AddField(
model_name="line",
name="date_updated",
field=models.DateTimeField(
auto_now=True, db_index=True, verbose_name="Date Updated"
),
),
]
|
18,852 | 0044dc5d9b625fc015164d9bac2013e90decbb2a | import pandas as pd
## for Data Studio , I've to generate another csv because Data Studio works with only Lat/Long.
## So, generate csv then join Lat/Long columns into one with comma separated.
cols_to_keep = ['Town_Name_MMR','Tsp_Pcode','Longitude', 'Latitude']
df2 = pd.read_excel('./pcode_9_2.xlsx', sheet_name='04_Town', engine='openpyxl')
df2 = df2[cols_to_keep]
print(df2.shape)
## drop duplicated Tsp_pcode rows
df2 = df2.drop_duplicates(subset = ['Tsp_Pcode'])
df2['combined'] = df2[['Latitude','Longitude']].apply(lambda x: ",".join(x.values.astype(str)), axis=1)
df2 = df2.dropna()
#print(df2.shape)
#df2.to_csv(r'.\df2.csv')
#print(df2.head())
## previous data reading
df3 = pd.read_csv("edit_pcode.csv", encoding='utf-8')
## Remove (South)/(East),etc extra word from First_sr column
df3['First_sr'] = df3['First_sr'].replace(regex=[r'\(\w+\)'], value='').str.strip()
print(pd.unique(df3['First_sr']))
#print(df3.shape)
#print(df3.head())
merged = pd.merge(df3, df2, on='Tsp_Pcode', how='inner')
print(merged.shape)
#print(merged.columns)
#merged.to_csv(r'.\pcode_studio.csv')
|
18,853 | 26387dbc7b571f51132f502b771c06474fec6622 | str='y'
while(str=='y' or str=='Y'):
src=int(input("Enter the Source:"))
des=int(input("Enter the Destination:"))
total_km=des-src
print("Total kilometer is:",total_km,"km")
print("1.Micro","2.Micro","3.Prime")
c=int(input("Make ur choice:"))
if(c==1):
money=total_km*10
print("The cost for your travel is:",money,"Rs")
elif(c==2):
money=total_km*20
print("The cost for your travel is:",money,"Rs")
elif(c==3):
money=total_km*30
print("The cost for your travel is:",money,"Rs")
else:
print("Please make a choice")
str=input("Do u want to continue(y/n)?")
|
18,854 | 79cd8ce36cb90e19cc34f07cc113ddc79875603a | import cv2
import dlib
import os
import sys
import numpy as np
def rect_to_bb(rect):
x = rect.left()
y = rect.top()
w = rect.right() - x
h = rect.bottom() - y
left = int(x + w/2 - 128)
right = left + 256
top = 0
bottom = 256
return (left, top, right, bottom)
def resize(image, width=456):
r = width * 1.0 / image.shape[1]
dim = (width, int(image.shape[0] * r))
resized = cv2.resize(image, dim, interpolation=cv2.INTER_AREA)
return resized
image_root = '/home/work_nfs3/xswang/data/avatar/Obama/clip/select/images/'
save_root = '/home/work_nfs3/xswang/data/avatar/Obama/clip/select/images_crop/'
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("/home/work_nfs3/xswang/data/avatar/Obama/data_processing_code/shape_predictor_68_face_landmarks.dat")
names = os.listdir(image_root)
i = 0
total = len(names)
log_file = 'log/crop_image.text'
for name in names:
i += 1
file_path = os.path.join(image_root,name)
save_file = os.path.join(save_root,name)
if not os.path.exists(save_file):
os.mkdir(save_file)
image_names = os.listdir(file_path)
first_path = os.path.join(file_path,image_names[0])
first_image = cv2.imread(first_path)
first_image = resize(first_image, width=456)
gray = cv2.cvtColor(first_image, cv2.COLOR_BGR2GRAY)
rect = detector(gray, 1)
try:
x1,y1,x2,y2 = rect_to_bb(rect[0])
px1,py1,px2,py2 = x1,y1,x2,y2
except:
x1,y1,x2,y2 = px1,py1,px2,py2
pass
if abs(x1-x2)<10 or abs(y1-y2)<10:
x1,y1,x2,y2 = px1,py1,px2,py2
for image_name in image_names:
save_path = os.path.join(save_file,image_name)
image_path = os.path.join(file_path,image_name)
image = cv2.imread(image_path)
image = resize(image, width=456)
crop_img = image[y1:y2,x1:x2]
cv2.imwrite(save_path, crop_img)
info = 'processed the %d of total %d image'%(i,total)
print(info)
# if i % 10 == 0 or i == total:
# with open(log_file,'a') as f:
# f.writelines(info) |
18,855 | 70cbf599bf231adaad6cd2b9e951b4de259be161 | from sklearn import svm
import numpy as np
import matplotlib.pyplot as plt
def main():
data=np.loadtxt('nonlinsep.txt',dtype='float',delimiter=',')
X=data[:,0:2]
Y=data[:,2]
clf = svm.SVC(kernel='rbf',degree=2)
clf.fit(X, Y)
print("Intercept:")
print(clf.intercept_)
print("Weights:")
print(clf.dual_coef_[0])
h=0.02
fignum=2
x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1
y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1
xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])
Z=Z.reshape(xx.shape)
plt.figure(fignum, figsize=(4, 3))
#plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired)
plt.contour(xx, yy, Z, colors=['k', 'k', 'k'], linestyles=['--', '-', '--'],
levels=[-.5, 0, .5])
plt.scatter(X[:, 0], X[:, 1], c=Y, cmap=plt.cm.Paired, edgecolors='k')
plt.xlim(x_min, x_max)
plt.ylim(y_min, y_max)
plt.axis('tight')
plt.show()
if __name__ == "__main__":
main() |
18,856 | b23f950a6c0f88d1577a42bfad3c8716f9fb35e4 |
# credits: https://www.kaggle.com/guglielmocamporese/macro-f1-score-keras
# https://stackoverflow.com/questions/58931078/how-to-replace-certain-parts-of-a-tensor-on-the-condition-in-keras/58931377#58931377
def f1(y_true, y_pred, dtype="float32"):
dtype = "float32"
y_pred = K.cast(y_pred, dtype)
y_true = K.cast(y_true, dtype)
y_pred = K.cast(K.greater(K.clip(y_pred, 0, 1), THRESHOLD), dtype)
tp = K.sum(y_true * y_pred, axis=0)
tn = K.sum(K.cast((1 - y_true) * (1 - y_pred), dtype), axis=0)
fp = K.sum(K.cast((1 - y_true) * y_pred, dtype), axis=0)
fn = K.sum(K.cast(y_true * (1 - y_pred), dtype), axis=0)
p = K.cast(tp / (tp + fp + K.epsilon()), dtype)
r = K.cast(tp / (tp + fn + K.epsilon()), dtype)
diff = 2 * p * r
suma = p + r + K.epsilon()
d0 = K.equal(diff, 0)
s0 = K.equal(suma, 0)
# sum zeros are replaced by ones on division
rel_dev = diff / K.switch(s0, K.ones_like(suma), suma)
rel_dev = K.switch(d0 & s0, K.zeros_like(rel_dev), rel_dev)
try:
# ~ is the bitwise complement operator in python which essentially calculates (-x - 1)
rel_dev = K.switch(-d0 - 1 & s0, K.sign(diff), rel_dev)
except:
rel_dev = K.switch(~d0 & s0, K.sign(diff), rel_dev)
f1 = rel_dev
return K.cast(K.mean(f1), dtype)
# some basic useless model
def create_model(input_shape):
model = Sequential()
model.add(Conv2D(8, (3, 3), activation="relu", input_shape=input_shape))
model.add(BatchNormalization(axis=-1))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(16, (3, 3), activation="relu"))
model.add(BatchNormalization(axis=-1))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(32, (3, 3), activation="relu"))
model.add(BatchNormalization(axis=-1))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(64, (3, 3), activation="relu"))
model.add(BatchNormalization(axis=-1))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(128, (3, 3), activation="relu"))
model.add(BatchNormalization(axis=-1))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(256, (3, 3), activation="relu"))
model.add(BatchNormalization(axis=-1))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dropout(0.5))
# model.add(Dense(28))
# model.add(Activation('relu'))
# model.add(Dropout(0.1))
model.add(Dense(28))
model.add(Activation("sigmoid"))
return model
|
18,857 | 2b55f0eaacd01cbbb313c759591ef596cdeb1548 | import threading
import logging
import uuid
import events
import queue
import helpers
import socket
from config_wrapper import config
from critical_section_leaver import CriticalSectionLeaver
from painter import DrawingQueueEvent
from message_sender import MessageSender
from dummy_message_sender import DummyMessageSender
import json
logger = logging.getLogger(__name__)
class ModelThread(threading.Thread):
def __init__(self, event_queue, paint_queue, time_offset, init_data=None, init_connection=None):
super(ModelThread, self).__init__()
# Queues
self.event_queue = event_queue
self.paint_queue = paint_queue
#Event handling
self.handlers = {}
self.initialize_handlers()
# Unique uuid identifying clients in the network
self.uuid = uuid.uuid4().hex
# Flag indicating weather we want to enter critical section when the token comes
self.want_to_enter_critical_section = False
# Information about critical section like the timestamp and client uuid which is in the section
self.critical_section = None
# Time offset between ntp server and local time
self.time_offset = time_offset
# Value of the last token we have received
self.last_token = None
# Initial board state
self.board_state = [[0 for _ in range(config.getint('Tkinter', 'CanvasY'))] for _ in range(config.getint('Tkinter', 'CanvasX'))]
# If we are the first client
if not init_data:
self.next_hop_info = None
self.next_next_hop_info = None
self.sending_queue = None
self.message_sender = None
self.predecessor = None
self.last_token = 0
else:
self.next_hop_info = init_data['next_hop']
if not init_data['next_next_hop']:
# If there is no next_next_hop init data in the response we are the second client so we set
# next next hop as our address
self.next_next_hop_info = (helpers.get_self_ip_address(), config.getint('NewPredecessorListener', 'Port'))
else:
# If there are more thant two clients we set the value from the response
self.next_next_hop_info = init_data['next_next_hop']
# Address of our predecessor
self.predecessor = init_connection.getsockname()
# We initialize connection to our next hop and we start sending queue
ip, port = init_data['next_hop']
s = socket.create_connection((ip, port))
self.sending_queue = queue.Queue(maxsize=0)
self.message_sender = MessageSender(self.event_queue, self.sending_queue, s)
self.message_sender.start()
self.initialize_board(init_data['board_state'])
if init_data['critical_section_state']:
self.critical_section = init_data['critical_section_state']
self.paint_queue.put({'type': DrawingQueueEvent.BOARD_CLOSED})
# We signal that client has initialized properly
init_connection.shutdown(1)
init_connection.close()
# We start a dummy message sender event which will create dummy messages to detect connection breaks
self.dummy_message_sender = DummyMessageSender(self.event_queue, self.uuid)
self.dummy_message_sender.start()
def run(self):
while True:
(e) = self.event_queue.get()
handler_function = self.handlers[type(e).__name__]
handler_function(e)
def initialize_board(self, board_state):
for counter in (len(board_state)):
x_coord, y_coord = board_state[counter]
try:
self.board_state[x_coord][y_coord] = 1
except IndexError:
return
self.paint_queue.put({'type': DrawingQueueEvent.DRAWING, 'data': (board_state, 1)})
def initialize_handlers(self):
# Inner Handlers
self.handlers['InnerNewClientRequestEvent'] = self.handle_new_client_request
self.handlers['InnerNewPredecessorRequestEvent'] = self.handle_new_predecessor_request_event
self.handlers['InnerDrawingInformationEvent'] = self.handle_inner_draw_information_event
self.handlers['InnerWantToEnterCriticalSection'] = self.inner_handle_want_to_enter_critical_section_event
self.handlers['InnerLeavingCriticalSection'] = self.inner_leaving_critical_section_event
self.handlers['InnerNextHopBroken'] = self.inner_next_hop_broken_event
# Outter handlers
self.handlers['DrawingInformationEvent'] = self.handle_drawing_information_event
self.handlers['EnteredCriticalSectionEvent'] = self.handle_entering_critical_section
self.handlers['LeavingCriticalSectionEvent'] = self.handle_leaving_critical_section
self.handlers['TokenPassEvent'] = self.handle_token_pass_event
self.handlers['NewNextNextHop'] = self.handle_new_next_next_hop_event
self.handlers['TokenReceivedQuestionEvent'] = self.handle_token_received_question_event
self.handlers['DummyMessageEvent'] = self.handle_dummy_message_event
############################################################################################
#
# Inner Event handlers
############################################################################################
def handle_inner_draw_information_event(self, event):
def draw_points(event):
color = event.data['color']
points = event.data['points']
try:
for point in points:
x,y = point
self.board_state[x][y] = color
except IndexError as e:
return
self.paint_queue.put({'type': DrawingQueueEvent.DRAWING, 'data': (points, color)})
if (self.sending_queue):
self.sending_queue.put(
events.DrawingInformationEvent(self.uuid, helpers.get_current_timestamp(), points, color))
if not self.critical_section:
draw_points(event)
elif self.critical_section['timestamp'] > event.data['timestamp']:
draw_points(event)
elif self.critical_section['client_uuid'] == self.uuid:
draw_points(event)
elif self.critical_section['client_uuid'] != self.uuid:
pass
def inner_handle_want_to_enter_critical_section_event(self, _):
self.want_to_enter_critical_section = True
def inner_leaving_critical_section_event(self, _):
self.critical_section = None
self.paint_queue.put({"type": DrawingQueueEvent.BOARD_OPEN})
if self.sending_queue:
self.sending_queue.put(events.LeavingCriticalSectionEvent(helpers.get_current_timestamp(), self.uuid))
self.sending_queue.put(events.TokenPassEvent(self.last_token))
else:
self.event_queue.put(events.LeavingCriticalSectionEvent(helpers.get_current_timestamp(), self.uuid))
self.event_queue.put(events.TokenPassEvent(self.last_token))
def inner_next_hop_broken_event(self, _):
# If we detect that the next hop connection is down we want to:
# 1.Try to reconnect to the client
# 2.If reconnect fails we want to connect to our next next hop
# 3.When we succesfully connect to our next next hop we want to send recovery token question
# in case that the dead client was holding the token the moment he died
ip, port = self.next_next_hop_info
# If we are the only client left we reset the data to the initial state
if ip == helpers.get_self_ip_address():
self.critical_section = None
self.next_hop_info = None
self.next_next_hop_info = None
if self.message_sender:
self.message_sender.stop()
self.sending_queue = None
self.message_sender = None
self.predecessor = None
self.last_token = 0
self.paint_queue.put({'type': DrawingQueueEvent.BOARD_OPEN})
return
def connect_to_next_next_hop(self):
ip, port = self.next_next_hop_info
try:
s = socket.create_connection((ip, port))
self.sending_queue = queue.Queue(maxsize=0)
self.message_sender = MessageSender(self.event_queue, self.sending_queue, s)
self.message_sender.start()
self.next_hop_info = self.next_next_hop_info
# After we connect to a new client we have to check whether the dead client wasn't in posession
# of token
self.sending_queue.put(events.TokenReceivedQuestionEvent(self.last_token))
except Exception as e:
logger.error(e)
ip, port = self.next_hop_info
try:
s = socket.create_connection((ip, port))
self.sending_queue = queue.Queue(maxsize=0)
self.message_sender = MessageSender(self.event_queue, self.sending_queue, s)
self.message_sender.start()
except ConnectionRefusedError as e:
logger.error(e)
connect_to_next_next_hop(self)
############################################################################################
#
# Event handlers
############################################################################################
def handle_new_client_request(self, event):
# At first we want to receive information to properly connect as new predecessor after sending init_data
message_size = event.data['connection'].recv(8)
message_size = int.from_bytes(message_size, byteorder='big')
message = b''
while len(message) < message_size:
packet = event.data['connection'].recv(message_size - len(message))
if not packet:
return None
message += packet
client_request = json.loads(message.decode('utf-8'))
first_client = not self.next_hop_info
# When we detect a new client connecting we want to;
# 1.Send him the initial data over the connection we already established
# 2.Connect to him as a predecessor
# Gather the initial board state (only the coloured spots)
marked_spots = [(x, y) for x in range(len(self.board_state)) for y in range(len(self.board_state[x])) if self.board_state[x][y] == 1]
# If we have next hop information we send it, if we do not have we are the first client so we send our
# information as the first hop information
next_hop = (helpers.get_self_ip_address(), config.getint('NewPredecessorListener', 'Port')) if first_client else self.next_hop_info
# If we are the first client next next hop is None
response = events.NewClientResponseEvent(next_hop, self.next_next_hop_info, marked_spots, self.critical_section)
message = helpers.event_to_message(response)
message_size = (len(message)).to_bytes(8, byteorder='big')
event.data['connection'].send(message_size)
event.data['connection'].send(message)
try:
message = event.data['connection'].recv(8)
except Exception as ex:
if message == b'':
# Only case when we have a succesfull read of 0 bytes is when other socket shutdowns normally
pass
else:
logger.error(ex)
#Client did not initializ correctly so we abort the process
return
# If we are not the first client we have to update our next next hop to our previous next hop
if not first_client:
self.next_next_hop_info = self.next_hop_info
else:
# If we are the first client we update our next next hop info to self address
self.next_next_hop_info = (
helpers.get_self_ip_address(), config.getint('NewPredecessorListener', 'Port')
)
# We stop current message sender if it exists
if self.message_sender:
self.message_sender.stop()
# We update our next hop info with the newest client request
self.next_hop_info = client_request['data']['address']
ip, port = self.next_hop_info
# We establish a new connection and a new message sender
connection = socket.create_connection((ip, port), 100)
self.sending_queue = queue.Queue(maxsize=0)
self.message_sender = MessageSender(self.event_queue, self.sending_queue, connection)
self.message_sender.start()
if first_client and self.last_token != None:
# If we are the first client we start passing of the token
self.sending_queue.put(events.TokenPassEvent(self.last_token))
def handle_drawing_information_event(self, event):
def draw_point(event):
points = event.data['points']
color = event.data['color']
try:
for point in points:
x,y = point
self.board_state[x][y] = color
except IndexError:
return
self.paint_queue.put({'type': DrawingQueueEvent.DRAWING, 'data': (points, color)})
if self.sending_queue:
self.sending_queue.put(event)
if event.data['client_uuid'] == self.uuid:
return
if not self.critical_section:
draw_point(event)
elif self.critical_section['timestamp'] > event.data['timestamp']:
draw_point(event)
elif self.critical_section['client_uuid'] == event.data['client_uuid']:
draw_point(event)
elif self.critical_section['client_uuid'] != event.data['client_uuid']:
pass
def handle_new_predecessor_request_event(self, event):
# The moment we have a new predecessor this means that the client before our predecessor
# has a new next next hop address (which is our address) and our predecessor has new next next hop (which is
# our next hop)
self.predecessor = event.data['client_address']
self_address = (helpers.get_self_ip_address(), config.getint('NewPredecessorListener', 'Port'))
# Special case if we have only 2 nodes left
if self.predecessor[0] == self.next_hop_info[0]:
self.sending_queue.put(events.NewNextNextHop(self.predecessor, self_address))
self.next_next_hop_info = (helpers.get_self_ip_address(), config.getint('NewPredecessorListener', 'Port'))
else:
# We send information to predecessor of our predecessor about his new next next hop address
self.sending_queue.put(events.NewNextNextHop(self_address, self.predecessor))
# We send information to our predecessor about his new next next hop
self.sending_queue.put(events.NewNextNextHop(self.next_hop_info, self_address))
def handle_entering_critical_section(self, event):
data = event.data
if (data['client_uuid']) == self.uuid:
return
self.critical_section = {
'timestamp': data['timestamp'],
'client_uuid': data['client_uuid']
}
self.paint_queue.put({'type': DrawingQueueEvent.BOARD_CLOSED})
self.sending_queue.put(event)
def handle_leaving_critical_section(self, event):
data = event.data
if (data['client_uuid']) == self.uuid:
return
if self.critical_section and self.critical_section['client_uuid'] == event.data['client_uuid']:
self.paint_queue.put({'type': DrawingQueueEvent.BOARD_OPEN})
self.critical_section = None
self.sending_queue.put(event)
def handle_token_pass_event(self, event):
token = event.data['token'] + 1
self.last_token = token
if self.critical_section:
# If we have received the token and the critical section exists we unvalidate critical secion info
self.critical_section = None
self.paint_queue.put({'type': DrawingQueueEvent.BOARD_OPEN})
if self.want_to_enter_critical_section:
timestamp = helpers.get_current_timestamp()
self.critical_section = {
'timestamp': timestamp,
'client_uuid': self.uuid
}
leave_critical_section_deamon = CriticalSectionLeaver(self.event_queue)
leave_critical_section_deamon.start()
self.want_to_enter_critical_section = False
self.paint_queue.put({'type': DrawingQueueEvent.BOARD_CONTROLLED})
self.sending_queue.put(events.EnteredCriticalSectionEvent(timestamp, self.uuid))
else:
if self.sending_queue:
self.sending_queue.put(events.TokenPassEvent(token))
def handle_new_next_next_hop_event(self, event):
post_destination_ip, _ = event.data['destination_next_hop']
next_hop_ip, _ = self.next_hop_info
# We are the recipient of the message
if post_destination_ip == next_hop_ip:
self.next_next_hop_info = event.data['new_address']
else:
self.sending_queue.put(event)
def handle_token_received_question_event(self, event):
# We check weather the last token we received is greater than
# the token from the request
# If it is, this means that the disconnected client was not in posession of the token when he disconnected
# If it was we have to unvalidate critial secion information and send token further
if self.last_token > event.data['token'] + 1:
return
else:
self.critical_section = None
self.paint_queue.put({'type': DrawingQueueEvent.BOARD_OPEN})
token = event.data['token'] + 1 if event.data['token'] else self.last_token + 1
self.sending_queue.put(events.TokenPassEvent(token))
def handle_dummy_message_event(self, event):
if self.uuid != event.data['uuid']:
return
else:
if self.sending_queue:
self.sending_queue.put(event)
|
18,858 | 3d2d480736be98a7f7a76296101410950c73264f | import sys
sys.path.append("D:\\github\\LeetCode_python")
from Utilities.Tree import MNode
def postorder(root: MNode) -> list:
res = []
if root is None:
return res
def posOrder(root):
if root is None:
return
childrens = root.children
for child in childrens:
posOrder(child)
res.append(root.val)
posOrder(root)
return res
def postorder2(root: MNode) -> list:
res = []
stack = [root]
while stack:
node = stack.pop()
res.append(node.val)
childrens = node.children
for child in childrens:
if child:
stack.append(child)
return res[::-1] |
18,859 | b172e1be85980ce1a907799019d1cecbcadf69bc | # -*- coding: utf-8 -*-
# Resource object code
#
# Created: Wed Jul 3 00:58:50 2013
# by: The Resource Compiler for PySide (Qt v4.8.4)
#
# WARNING! All changes made in this file will be lost!
from PySide import QtCore
qt_resource_data = b"\x00\x00\xeb\xa6\x89PNG\x0d\x0a\x1a\x0a\x00\x00\x00\x0dIHDR\x00\x00\x02\x00\x00\x00\x02\x00\x08\x06\x00\x00\x00\xf4x\xd4\xfa\x00\x00\x00\x06bKGD\x00\x00\x00\x00\x00\x00\xf9C\xbb\x7f\x00\x00\x00\x09pHYs\x00\x00\x0b\x12\x00\x00\x0b\x12\x01\xd2\xdd~\xfc\x00\x00\x00\x07tIME\x07\xdd\x07\x02\x0c:,d6\xfa4\x00\x00 \x00IDATx\xda\xec\xbd{\xb4$YY'\xfa\xdb;\x22\x1f\xe7TU\xbfi\xba\xbb\xba\xa1\x1f\x80\xba\x00\x1d\xb0AD@\x14E\x87\x11\xf1\x01\xa2\xcc\xc0\xe0\x0b\x1d\x1dgfy\x1d\xe6.\xbc\xc3\x8cKadfy\xaf\xca\x5cu\xb8\xc80\x17\xaf<\xae\xa8KtPX\x02\xd2\xd0\xd0\xdd\xa5^G\x5c\x8c\xd0/\xba\xbb\xaa\xba\xaa\xba\xaa\xce\xfbdfD\xec}\xff\xd8\x11'w~\xf9\xed\x1d\x91\xe7\x9c<'3\xcf\xf7[+V\xe6\xc9\x8c\xcc\x93\x19\x19\xb1\x7f\xbf\xef\xf7}\xfb\xdb\x80@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ \x10\x08\x04\x02\x81@ 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qt_resource_name = b"\x00\x0e\x085\xb9\x95\x00z\x00i\x00n\x00c\x00d\x00a\x00t\x00a\x00s\x00o\x00u\x00r\x00c\x00e\x00\x06\x07\x03}\xc3\x00i\x00m\x00a\x00g\x00e\x00s\x00\x12\x0f4\x99\x87\x00z\x00i\x00n\x00c\x00_\x00d\x00a\x00t\x00a\x00_\x00i\x00c\x00o\x00n\x00.\x00p\x00n\x00g"
qt_resource_struct = b"\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x22\x00\x02\x00\x00\x00\x01\x00\x00\x00\x03\x00\x00\x004\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00"
def qInitResources():
QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
|
18,860 | 4b1d4cd34cc5d244afe23092926222ef223f32fb | from pytorch_helper.settings.options import TaskMode
from pytorch_helper.settings.spaces import Spaces
from pytorch_helper.task import Batch
from tasks.bevnet import BEVNetTask
@Spaces.register(Spaces.NAME.TASK, 'IV2BEVTask')
class IV2BEVTask(BEVNetTask):
def __init__(self, task_option):
task_option.task_mode = TaskMode.TEST
super(IV2BEVTask, self).__init__(task_option)
self.cc_oracle = task_option.test_option.cc_oracle
self.pose_oracle = task_option.test_option.pose_oracle
self.iv_map = task_option.test_option.iv_map
self.plane_height = 1.75
if self.iv_map == 'feet_map':
self.plane_height = 0.
self.map_scale = self.loss_fn.map_loss_fn.magnitude_scale
def model_forward_backward(
self, batch: Batch, backward=False
):
image = batch.gt['image']
fu, fv = batch.gt['camera_fu'], batch.gt['camera_fv']
pred = self.model.forward(image, fu, fv)
if self.pose_oracle:
h_cam = batch.gt['camera_height']
p_cam = batch.gt['camera_angle']
else:
h_cam = pred['camera_height']
p_cam = pred['camera_angle']
if self.cc_oracle:
input_map = batch.gt[self.iv_map] * self.map_scale
else:
input_map = pred[self.iv_map]
bevmap, bev_scale, bev_center = self.unwrapped_model.bev_transform(
input_map, self.plane_height, h_cam, p_cam, fu, fv
)
roi = self.unwrapped_model.bev_transform.get_iv_roi(
bevmap.size(), h_cam, p_cam, fu, fv, filled=True
)
bs = input_map.size(0)
s_iv = (input_map * roi.float()).view(bs, -1).sum(-1)
s_bev = bevmap.view(bs, -1).sum(-1) + 1e-16
bevmap *= (s_iv / s_bev).view(bs, 1, 1, 1)
pred = dict(
bev_map=bevmap,
camera_height=h_cam,
camera_angle=p_cam,
bev_scale=bev_scale,
bev_center=bev_center
)
pred[self.iv_map] = input_map
loss = self.sync_value(self.loss_fn.forward(pred, batch.gt))
batch.pred = pred
batch.loss = self.sync_value(loss)
batch.size = image.size(0)
return batch
|
18,861 | 19c754e5a429c606c742286d2228974f8b60fd67 | motorcycles = ['honda', 'yamaha', 'suzuki']
print(motorcycles)
motorcycles[0] = 'ducati'
print(motorcycles)
motorcycles.append('triumph')
print(motorcycles)
motorcycles.insert(1, 'harley davidson')
print(motorcycles)
del motorcycles[0]
print(motorcycles)
popped_motorcycle = motorcycles.pop()
print(popped_motorcycle)
print(motorcycles)
first_motorcycle = motorcycles.pop(0)
print('The first motorcycle that I owned was a ' + first_motorcycle.title() + '.')
motorcycles.remove('yamaha')
print(motorcycles) |
18,862 | c1599649725deb539139cda951facea20f8ceaed | import argparse
from collections import defaultdict
import operator
import sys
parser=argparse.ArgumentParser()
parser.add_argument('-i','--input',type=argparse.FileType('rU'),nargs='+',help='list of replicates read count files to merge')
parser.add_argument('-o','--output',type=argparse.FileType('w'),help='combined read count file for DeSEQ1 input file')
parser.add_argument('-d','--deseq',action='store_true',help='if you want just seperate read count file for DESEQ2')
parser.add_argument('-p','--prefix',type=str, help='output file prefix or suffix to output file name')
parser.add_argument('-x','--exclude_intergenic',action='store_true',help='do not include int regions')
args=parser.parse_args()
all_isols2isol2read_counts = defaultdict(dict)
all_regions = []
files = []
file_count = 0
for f in args.input:
gene2count = []
file_name = str(f).split(' ')
isol_name = file_name[2].split('.')
try:
final_isol_name = isol_name[0][1:]
print final_isol_name
except IndexError:
print 'Do your input files contain a "_" seperating the name from the replicate? or are the replicate names unique?'
sys.exit()
files.append(final_isol_name)
file_count += 1
if args.deseq:
out_file_name=(final_isol_name+'_'+str(args.prefix)+'.txt')
sep_out_file = open(out_file_name,'w')
count_line = 0
for line in f:
count_line += 1
if count_line == 1:
pass
else:
info = line.strip().split(',')
if len(info) == 1:
pass
else:
if info[3] == 'CDS':
all_isols2isol2read_counts[final_isol_name][info[2]]=(info[4])
if args.deseq:
gene_count = (info[2],info[4])
gene2count.append(gene_count)
if file_count == 1:
all_regions.append(info[2])
else:
all_isols2isol2read_counts[final_isol_name][info[1]]=(info[4])
if args.deseq:
gene_count = (info[1],info[4])
gene2count.append(gene_count)
if file_count == 1:
all_regions.append(info[1])
sorted_gene2count = sorted(gene2count, key=lambda tup: (tup[0]))
for x in sorted_gene2count:
sep_out_file.write(x[0]+'\t'+x[1]+'\n')
if args.output:
args.output.write('Gene'+'\t'+str(files[0])+'\t'+str(files[1])+'\t'+str(files[2])+'\t'+str(files[3])+'\t'+str(files[4])+'\t'+str(files[5])+'\n')
for g in all_regions:
# don't want intergenic
if args.exclude_intergenic:
if 'intergenic' in g:
pass
else:
first_rep = all_isols2isol2read_counts.get(files[0])
first_rep_gene = first_rep.get(g)
second_rep = all_isols2isol2read_counts.get(files[1])
second_rep_gene = second_rep.get(g)
third_rep = all_isols2isol2read_counts.get(files[2])
third_rep_gene = third_rep.get(g)
fourth_rep = all_isols2isol2read_counts.get(files[3])
fourth_rep_gene = fourth_rep.get(g)
fifth_rep = all_isols2isol2read_counts.get(files[4])
fifth_rep_gene = fifth_rep.get(g)
sixth_rep = all_isols2isol2read_counts.get(files[5])
sixth_rep_gene = sixth_rep.get(g)
args.output.write(g+'\t'+first_rep_gene+'\t'+second_rep_gene+'\t'+third_rep_gene+'\t'+fourth_rep_gene+'\t'+fifth_rep_gene+'\t'+sixth_rep_gene+'\n')
else:
first_rep = all_isols2isol2read_counts.get(files[0])
first_rep_gene = first_rep.get(g)
second_rep = all_isols2isol2read_counts.get(files[1])
second_rep_gene = second_rep.get(g)
third_rep = all_isols2isol2read_counts.get(files[2])
third_rep_gene = third_rep.get(g)
fourth_rep = all_isols2isol2read_counts.get(files[3])
fourth_rep_gene = fourth_rep.get(g)
fifth_rep = all_isols2isol2read_counts.get(files[4])
fifth_rep_gene = fifth_rep.get(g)
sixth_rep = all_isols2isol2read_counts.get(files[5])
sixth_rep_gene = sixth_rep.get(g)
args.output.write(g+'\t'+first_rep_gene+'\t'+second_rep_gene+'\t'+third_rep_gene+'\t'+fourth_rep_gene+'\t'+fifth_rep_gene+'\t'+sixth_rep_gene+'\n')
|
18,863 | 5d243e6a0598459dcdb93239a256f9e52fd7efca | # -*- coding: utf-8 -*-
import random
import math
class QueueError(Exception): pass
class DeviceQueue(object):
def __init__(self, capacity):
if not isinstance(capacity, int) or capacity <= 0:
raise QueueError()
self._capacity = capacity
self._count = 0
def is_full(self):
return self._capacity == self._count
def is_empty(self):
return self._count == 0
def clear(self):
self._count = 0
def enqueue(self):
if self.is_full():
raise QueueError
self._count = self._count + 1
def dequeue(self):
if self.is_empty():
raise QueueError
self._count = self._count - 1
class ModelEvent(object):
def __init__(self, time):
self._time = time
def get_planned_time(self):
return self._time
class GenerationEvent(ModelEvent):
def __init__(self, time):
super(GenerationEvent, self).__init__(time)
def __repr__(self):
return "Generate at %f" % self.get_planned_time()
class ProcessingEvent(ModelEvent):
def __init__(self, time):
super(ProcessingEvent, self).__init__(time)
def __repr__(self):
return "Process at %f" % self.get_planned_time()
class Generator(object):
def __init__(self, excepted_value):
self._expected_value = excepted_value
def generate_time(self):
return (0 - self._expected_value) * math.log(1 - random.random())
def generate_event(self, model_time):
return GenerationEvent(self.generate_time() + model_time)
class Processor(object):
def __init__(self, expected_value, halfrange):
self._expected_value = expected_value
self._halfrange = halfrange
def generate_time(self):
return random.uniform(self._expected_value - self._halfrange, self._expected_value + self._halfrange)
def generate_event(self, model_time):
return ProcessingEvent(self.generate_time() + model_time)
class Model(object):
def __init__(self, gen_expected_value, process_expected_value, process_halfrange, queue_capacity, eps, with_return=False):
self._generator = Generator(gen_expected_value)
self._processor = Processor(process_expected_value, process_halfrange)
self._queue = DeviceQueue(queue_capacity)
self._events_list = []
self._model_time = 0
self._with_return = with_return
self._processing = False
self._eps = eps
self._logger = []
def reinit(self):
self._queue.clear()
self._events_list = []
self._model_time = 0
self._processing = False
self._logger = []
def handle_generation(self):
self._events_list.insert(0, self._generator.generate_event(self._model_time))
if self._queue.is_full():
self._logger.append("В %f заявка не попала в очередь из-за нехватки места" % self._model_time)
return False
if self._processing:
self._queue.enqueue()
else:
self._events_list.insert(0, self._processor.generate_event(self._model_time))
self._processing = True
self._logger.append("В %f произошло успешное генерирование заявки. В очереди занято %d/%d" % (self._model_time, self._queue._count, self._queue._capacity))
return True
def handle_processing(self):
if self._queue.is_empty() and self._with_return:
self._events_list.insert(0, self._processor.generate_event(self._model_time))
elif self._queue.is_empty() and not self._with_return:
self._processing = False
elif not self._queue.is_empty():
self._events_list.insert(0, self._processor.generate_event(self._model_time))
if not self._with_return:
self._queue.dequeue()
self._logger.append("В %f произошла обработка заявки. В очереди занято %d/%d" % (self._model_time, self._queue._count, self._queue._capacity))
def handle_event(self, ev, processed, rejected):
print(repr(ev))
if isinstance(ev, GenerationEvent):
if self.handle_generation():
return (processed, rejected)
else:
return (processed + 1, rejected + 1)
elif isinstance(ev, ProcessingEvent):
self.handle_processing()
return (processed + 1, rejected)
else:
assert 0
def run_dt(self, dt, to_process):
self.reinit()
processed = 0
rejected = 0
self._events_list.insert(0, self._generator.generate_event(self._model_time))
while processed < to_process:
while True:
try:
ev = self._events_list.pop()
except IndexError:
self._events_list.insert(0, self._generator.generate_event(self._model_time))
if math.fabs(ev.get_planned_time() - self._model_time) < self._eps: # process event
(processed, rejected) = self.handle_event(ev, processed, rejected)
self._events_list.sort(key=lambda x: x.get_planned_time(), reverse=True)
if processed < to_process:
continue
else:
break
elif ev.get_planned_time() < self._model_time: # timeout of event
print("timeout")
continue
elif ev.get_planned_time() > self._model_time: # return to queue
self._events_list.insert(0, ev)
self._events_list.sort(key=lambda x: x.get_planned_time(), reverse=True)
break
self._model_time = self._model_time + dt
return self._model_time, rejected, self._logger
def run_event(self, to_process):
self.reinit()
processed = 0
rejected = 0
self._events_list.insert(0, self._generator.generate_event(self._model_time))
self._events_list.sort(key=lambda x: x.get_planned_time(), reverse=True)
while processed < to_process:
ev = self._events_list.pop()
if ev.get_planned_time() == self._model_time: # process event
(processed, rejected) = self.handle_event(ev, processed, rejected)
self._events_list.sort(key=lambda x: x.get_planned_time(), reverse=True)
elif ev.get_planned_time() > self._model_time: # return to queue
self._model_time = ev.get_planned_time()
self._events_list.insert(0, ev)
self._events_list.sort(key=lambda x: x.get_planned_time(), reverse=True)
else:
assert 0
return self._model_time, rejected, self._logger
|
18,864 | ac9d76b796db670a3b8634bfc42e59d96e36a32f | #!/usr/bin/python
#Source: https://github.com/GDSSecurity/mangers-oracle
import math, os, sys
from time import time
from subprocess import Popen, PIPE
def modpow(base, exponent, modulus):
result = 1
while exponent > 0:
if exponent & 1 == 1:
result = (result * base) % modulus
exponent = exponent >> 1
base = (base * base) % modulus
return result
def timeSend(f):
half = modpow(f, e, n)
whole = (half * c) % n
str = hex(whole)[2:-1]
start = time()
p = Popen(["./decrypt", str], stdout=PIPE)
output = p.communicate()[0]
stop = time()
return stop - start, output
################################################################################
def buildTiming(n, e, c):
records = {}
for trials in range(1, 1000):
for i in range(1, 20):
if trials == 1: records[i] = []
f1 = pow(2, i)
time, output = timeSend(f1)
records[i].append(time)
#print time, lessThanB(output), i
for i in range(1,20):
f = open('trials.' + str(i), 'w')
for l in records[i]:
f.write(str(l)+"\n")
################################################################################
################################################################################
if __name__ == "__main__":
n = 157864837766412470414898605682479126709913814457720048403886101369805832566211909035448137352055018381169566146003377316475222611235116218157405481257064897859932106980034542393008803178451117972197473517842606346821132572405276305083616404614783032204836434549683833460267309649602683257403191134393810723409
e = 0x10001
c = int('5033692c41c8a1bdc2c78eadffc47da73470b2d25c9dc0ce2c0d0282f0d5f845163ab6f2f296540c1a1090d826648e12644945ab922a125bb9c67f8caaef6b4abe06b92d3365075fbb5d8f19574ddb5ee80c0166303702bbba249851836a58c3baf23f895f9a16e5b15f2a698be1e3efb74d5c5c4fddc188835a16cf7c9c132c', 16)
p = int('2ea4875381beb0f84818ce1c4df72574f194f7abefe9601b21da092f484fa886ff0de66edf8babd4bd5b35dfdb0e642382947270a8f197e3cbaaa37cb8f7007f4604794a51c3bd65f8d17bfad9e699726ff9f61b99762d130777872eb4e9f1532cf3bfbfc3d2ad5d8d4582cc90a2e59915c462967b19965f77225447ce660d', 16)
buildTiming(n, e, c)
|
18,865 | b8fa212eae116d7e07e231154d9e486f0bcbf4e9 | # -*- coding: utf-8 -*-
import re
import yaml
import logging
def parse_hostname(output):
'''Parse the hostname in the show run config and return string'''
regexp = 'hostname\W+(\S+)'
try:
result = re.search(regexp,output).group(1)
except AttributeError:
logging.warning('Unnable to parse the name of the device, please check the conf on unknown devcie')
return 'unkonwn_device'
return result
def read_yml_file(file_to_read):
''' Read the yaml file and return the dict with cred of the devices '''
result = None
with open(file_to_read) as f:
result = yaml.load(f)
return result
def write_to_file(output,file_name):
with open(file_name,'w') as f:
logging.info('Writing a file to {}'.format(file_name))
f.write(output)
|
18,866 | 48983a9ff033f44a4ce976d8739a62e6a0b7c971 | #
from operator import add
__author__ = 'Aaron Yang'
__email__ = 'byang971@usc.edu'
__date__ = '11/28/2019 4:31 PM'
import sys
from pyspark import SparkContext
def splitFunc(row):
col_bar, col_beer, col_price = row.split(',')
if col_beer.startswith('Bud'):
return col_bar, int(col_price)
if __name__ == "__main__":
# input_file_path = "sells.csv"
# output_file_path = "output.txt"
# input_file_path = sys.argv[1]
# output_file_path = sys.argv[2]
d = [('hello', 1), ('world', 1), ('hello', 1), ('this', 1), ('world', 1)]
sc = SparkContext.getOrCreate()
data = sc.parallelize(d, 2)
# ss = data.countByKey()
ss = data.reduceByKey(add).collect()
print(ss)
|
18,867 | 3ad13014b009750eaa2ec801e7463a96b1068a36 | import pandas as pd
import io, sys, os
from os import path, listdir
from datetime import datetime, timedelta
from flask import Flask, make_response
app = Flask(__name__)
@app.route('/', methods=['GET', 'POST'])
def hello_world(request):
"""Responds to any HTTP request.
Args:
request (flask.Request): HTTP request object.
Returns:
The response text or any set of values that can be turned into a
Response object using
`make_response <http://flask.pocoo.org/docs/1.0/api/#flask.Flask.make_response>`.
"""
raw_text = request.form.get('raw_text')
paydate = request.form.get('raw_date')
raw_csv = request.files.get('raw_csv').read()
print(f'raw_text: {raw_text}')
print(f'paydate: {paydate}')
print(f'raw_csv: {raw_csv}')
#print(f'{pd.__version__}')
# can't do this:
# print(f'csv3 head regular bytes: {pd.read_csv(csv3).head(1)}')
# flask.Response('', headers={'Content-Type': 'text/html'})
# return str(pd.read_csv(io.BytesIO(csv3)).to_dict())
# res = make_response('<html><head><title>JBoss - Error report</title></head></html>', {'Content-Type': 'text/html', 'Access-Control-Allow-Origin': '*'})
#res = make_response(pd.read_csv(io.BytesIO(raw_csv)).to_html(), {'Content-Type': 'text/html', 'Access-Control-Allow-Origin': '*'})
#file_name = make_response(pd.read_csv(io.BytesIO(raw_csv), encoding='unicode_escape'), {'Content-Type': 'multipart/form-data', 'Access-Control-Allow-Origin': '*'})
df = pd.read_csv(io.BytesIO(raw_csv), encoding='unicode_escape')
#print(f'df: {df}, type df: {type(df)}')
result = reconcile_month(df, paydate)
result = result.to_html()
#print(f'result of reconcile_month: {result}')
return result
# Start reconcile.py
def reconcile_month(df, paydate):
'''
Takes two strings as args. file_name, paydate 'M-D-YYYY' or 'MM-DD-YYYY'
Returns final dataframe dfs_x
'''
# Find path to file, assign file_name, and print name of file we're running
#path = os.getcwd()
#file_name = os.path.join(path, file_name)
#pd.set_option('max_colwidth', 400)
#print(f'file_name: {file_name}')
# Create datetime object YYYY-MM-DD from user input
our_dt = datetime.strptime(paydate, '%Y-%m-%d').date()
#print(f'our_dt: {our_dt}')
# FUNCTION CALL to all other functs via coop_df
# Return compiled dataframe at html
final_df = coop_df(df, our_dt)
# try:
# final_df.to_html(
# 'file.html',
# columns=['Month', 'Week', 'Totals_WnT', 'Wages', 'Taxes', 'Employees'],
# justify='left',
# float_format='$%.2f')
# except KeyError:
# final_df.to_html(
# 'file.html',
# columns=['Month', 'Totals_WnT', 'Wages', 'Taxes', 'Employees'],
# justify='left',
# float_format='$%.2f')
return final_df
#print(f'final_df output: {final_df}')
#print(f'res: {res}, type res: {type(res)}')
#if __name__ == '__main__':
# reconcile_month(sys.argv[1], sys.argv[2])
# Start coop_df.py
def coop_df(df, datetime_obj):
'''
Intermediary funct btw reconcile.py and mums_little_helper.py
Takes file_name & date as datetime object from reconcile_month
Runs all other functions.
Returns dataframe to reconcile.py. Dataframe returned represents one paycheck week,
unless it detects a week that straddles two months, in which case the dataframe
returned will represent two paycheck weeks.
'''
# Parse datetime_obj into year, month, day
y = datetime_obj.year
m = datetime_obj.month
d = datetime_obj.day
#ps_a, ps_b, dr_a, dr_b = slice_the_cack('datasets/Test file MMG2.CSV', 2019, 10, 10)
ps_a, dr_a = slice_the_cack(df, y, m, d)
depts = get_employees_by_dept(ps_a, dr_a)
account_sums = get_sums(ps_a, dr_a, depts)
piece_dict = pieces_of_me(account_sums, depts)
dfs = sum_and_separate_by_dept(piece_dict)
dfs_x = merge_dfs(dfs)
# Check number of months present in initial dfs_x here
if dfs_x['Month'].nunique() > 1:
# if > 1, find previous week
prev_dt = datetime_obj - timedelta(weeks = 1)
# if previous week's month == initial week's month, run second time with previous week
if prev_dt.month == m:
dfs_pw = coop_df(df, prev_dt)
dfs_pw['Week'] = dfs_pw['Wages'].apply(lambda x: 'A')
dfs_x['Week'] = dfs_x['Wages'].apply(lambda x: 'B')
dfs_x = pd.concat([dfs_pw, dfs_x])
#print(f'This is concat with PW:\n {dfs_x}')
return dfs_x
#print(f'prev_dt loop: {prev_dt, list_of_dfs_x}')
else:
#print(f'This found PW was out of month:\n {dfs_x}')
return dfs_x
else:
#print(f'This is returning only one initial week:\n {dfs_x}')
return dfs_x
# Start mums_little_helper.py
def slice_the_cack(df, year, month, day,):
'''
Takes a Timestamp.
Returns a dictionary of the Saturday through Sunday
daterange before the previous Thursday where the keys
are the int month numbers and the values
are the percentage of days in each month
of the total days returned in all months.
'''
pr = df
pr['Date'] = pd.to_datetime(pr['Date'])
pr.dropna(subset=['Date'], inplace=True)
pr['Year'] = pr.copy()['Date'].dt.year
pr['Month'] = pr.copy()['Date'].dt.month
paydate_entered = pd.Timestamp(year=year, month=month, day=day, freq='D')
#Based on paydate_entered, assign either week-immediately-before or week-of to dr_a
if paydate_entered.weekday() <= 2:
su = paydate_entered - ((paydate_entered.weekday() + 8) * paydate_entered.freq)
sa = paydate_entered - ((paydate_entered.weekday() + 2) * paydate_entered.freq)
else:
su = paydate_entered - ((paydate_entered.weekday() + 1) * paydate_entered.freq)
sa = su + 6 * paydate_entered.freq
#
# if paydate_entered.weekday() <= 2:
# su = paydate_entered - ((paydate_entered.weekday() + 15) * paydate_entered.freq)
# sa = paydate_entered - ((paydate_entered.weekday() + 9) * paydate_entered.freq)
# else:
# su = paydate_entered - ((paydate_entered.weekday() + 8) * paydate_entered.freq)
# sa = paydate_entered - ((paydate_entered.weekday() + 2) * paydate_entered.freq)
#EX. for 10-3, we assign dr_a the week-of 9-29 thru 10-5
dr_a = pd.date_range(start=su, end=sa, freq='D')
su = dr_a[0]
#paycheck_span = first arg of get_sums AND a df displaying the sat to sun of dr_a
ps_a = pr[ (pr['Date'] >= dr_a[0]) & (pr['Date'] <= dr_a[-1]) ]
# # dr_b as week following dr_a
# nexsu = dr_a[-1]+1*dr_a.freq
# nexsa = dr_a[-1]+7*dr_a.freq
# dr_b = pd.date_range(start=nexsu, end=nexsa, freq='D')
# ps_b = pr[ (pr['Date'] >= dr_b[0]) & (pr['Date'] <= dr_b[-1]) ]
return ps_a, dr_a
def get_sums(paycheck_span, dr, depts):
'''
Takes a df and a pd.date_range
Returns
{'fractmo': {9: 1.0},
'txs_by_emp': {'Adams, L': 46.32,
'Avery, B': 25.77,
'Bingo, Nolan': 39.650000000000006,
'Conde, Barb': 23.59,
'Clyde-Owens, L': 48.42,
'Chorse, MD': 33.42,
'Fray-Chase, Jay': 27.94,
'Gunn, Jim': 46.88,
'Graybranch, Linne': 57.209999999999994,
'Hedrovin, Zed': 15.509999999999998,
'Heart, Ray': 48.14,
'LaRay, Jane': 43.42,
'Lentifold, Eddie': 22.65,
'Mattison, Ronnie G.': 38.1,
'Peace, Jesse B.'': 31.34,
'Peet, Angela L': 61.23,
'Pino, Kola': 29.37,
'Picken, James': 42.79,
'Rich, Chiccie SR.': 35.74,
'Ryan, Noam': 31.37,
'Stark, Nancy B': 3.35,
'Teddy, Aimee': 31.02,
'Van Wilson, Len P.': 61.56,
'Wavering, Lindsay': 41.96},
'wgs': {'61101 · Salary & Wages-Packaging': 444.38,
'61104 · Salary & Wages-Bakery': 2602.4799999999996,
'61107 · Salary & Wages-Deli': 774.28,
'61109 · Salary & Wages-Produce': 643.31,
'61141 · Salary & Wages-Admin': 4110.31,
'61142 · Salary & Wages-Store': 2804.06}}
'''
fractmo_dict = {}
#print(f'paycheck_span: {paycheck_span}')
#Finds the week before dr passed originally
#This daterange represents the days that were actually worked
#Allows fractmo_dict to iterate over appropriate week
prevsun = dr[0] - 7 * dr.freq
prevsat = dr[0] - 1 * dr.freq
dr = pd.date_range(start=prevsun, end=prevsat, freq='D')
for d in dr:
try:
fractmo_dict[d.month] = fractmo_dict[d.month] + 1
except:
fractmo_dict[d.month] = 1
#divide each value by the sum
total = sum(fractmo_dict.values(), 0.0)
for key in fractmo_dict:
fractmo_dict[key] = fractmo_dict[key] / total
#print(f'get_sums: {fractmo_dict[key]}')
paycheck_span = paycheck_span[ (paycheck_span['Num'] != 'Accrued Pay')]
#Group paycheck_span by summed amount in each account for the week
wnt = paycheck_span.groupby(['Account'], as_index=False)['Amount'].sum()
#Dict of taxes sums per week by employee name
vnt = paycheck_span.groupby(['Account', 'Name'], as_index=False)['Amount'].sum()
#print(f'vnt: {vnt}')
emp_txs = vnt[ (vnt['Account'] == '61210 · FICA Expense') | (vnt['Account'] == '61230 · NYUI Expense') ]
#print(f'emp_txs: {emp_txs}')
txs_by_emp = emp_txs.groupby(['Name'])['Amount'].sum().to_dict()
#Dict of taxes sums per week, by department, according to emp-dept assignments
# hold_tbe = {}
# for n, t in txs_by_emp.items():
#
# hold_tbe[n] = t
dept_taxes = {}
for d, l in depts.items():
dept_taxes[d] = 0
for n in l:
dept_taxes[d] += txs_by_emp[n]
# print(f'hold_tbe: {hold_tbe}')
# print(f'dept_taxes: {dept_taxes}')
txs_for_depts_emps = dept_taxes
#Dict of only salary & wages accounts' sums
wgs = wnt[ (wnt['Account'] != '61210 · FICA Expense') & (wnt['Account'] != '61230 · NYUI Expense') ]
wgs_sums_dict = wgs.groupby(['Account'])['Amount'].sum().iloc[:].to_dict()
return {'txs_for_depts_emps': txs_for_depts_emps, 'txs_by_emp': txs_by_emp, 'wgs': wgs_sums_dict, 'fractmo': fractmo_dict}
def get_tax_dept(ps):
'''
Returns the department and amount for the employee
where the employee made the highest total amount for
that month.
file_name (str): path to csv file
year (int): year over which to look for dept
month (int): month over which to look for dept
employee_name (str): name of employee to look up
'''
#concatenate your two paycheck_spans
#frames = [ps, pst]
#print(pr['Date'])
#pr = pd.read_csv(pr, encoding='unicode_escape')
#pr['Date'] = pd.to_datetime(pr['Date'])
# drop null dates (just the last row)
# drop that weird first column, the useless Clr and Balance cols too
#pr.drop(columns=['Unnamed: 0', 'Clr', 'Balance'], inplace=True)
# # Remove FUPAs
# pr = pr[ (pr['Account'] != '61210 · FICA Expense') & \
# (pr['Account'] != '61220 · FUTA Expense') & \
# (pr['Account'] != '61230 · NYUI Expense') ]
# create month and year cols
#pr['Year'] = pr.copy()['Date'].dt.year
#pr['Month'] = pr.copy()['Date'].dt.month
# get sum totals per employee by y/m/name/dept
ps = ps.groupby(['Name', 'Account']).sum().reset_index()
# Sort the df based on Year, Month, Name, Account, then Amount
# We need this for the next rank step, and will then join
# the two results together.
ps.sort_values(['Name', 'Amount'], inplace=True, ascending=False)
# create the ranks for each month/name combination. Record number
# 1 should (but isn't) the department where the employee made the
# most money that month
ranks = ps.groupby(by=['Name'])['Amount'].rank(method='first')
ranks = ranks.astype('int32')
ranks.name = 'Rank'
#print(ranks.head(20))
# Join the pr dataframe and the ranks dataframe back together
wbd = pd.merge(ps, ranks, left_index=True, right_index=True)
# create a composite join key for wbd
wbd['cjk'] = wbd['Name'] + wbd['Rank'].astype('str')
# the rank that corresponds to the employee's highest earning department for that month
max_ranks = wbd.groupby(['Name'])['Rank'].max().reset_index()
# create a composite join key for max_ranks
max_ranks['cjk'] = max_ranks['Name'] + \
max_ranks['Rank'].astype('str')
# join the wbd and max_ranks table on their composite keys
res = pd.merge(
max_ranks,
wbd,
how='left',
on='cjk',
suffixes=('_mr', '')
)[['Name', 'Account']]
#print(res)
res = res.set_index('Name')
# fetch the user requested information from the res dataframe
#vals = res[ (res['Year'] == year) & (res['Month'] == month) & (res['Name'] == employees) ].values
# out_dict = {}
# for i, j in zip(vals[0], ['year', 'month', 'name', 'dept', 'amount']):
# out_dict[j] = i
# out_df = pd.DataFrame(out_dict, index=[1])
#res_dict = res.set_index('Name').to_dict()
return res
def get_employees_by_dept(ps, dr):
depts = get_tax_dept(ps)
depts = depts.reset_index()
depts = depts.groupby(['Account'])['Name']
ebd = {}
for d, n in depts:
ebd[d] = []
#print(f'd: {d}\ntype of d: {type(d)}\n')
#print(f'n: {n}\ntype of n: {type(n)}')
for v in n:
ebd[d].append(v)
return ebd
def pieces_of_me(account_sums, depts):
'''
Takes dict that looks like dis.
ratio of days in months within our one week paycheck range,
sum of taxes by account,
sum of salary and wages by dept.
{'fractmo': {9: 1.0},
'txs_by_emp': {'Adams, L': 46.32,
'Avery, B': 25.77,
'Bingo, Nolan': 39.650000000000006,
'Conde, Barb': 23.59,
'Clyde-Owens, L': 48.42,
'Chorse, MD': 33.42,
'Fray-Chase, Jay': 27.94,
'Gunn, Jim': 46.88,
'Graybranch, Linne': 57.209999999999994,
'Hedrovin, Zed': 15.509999999999998,
'Heart, Ray': 48.14,
'LaRay, Jane': 43.42,
'Lentifold, Eddie': 22.65,
'Mattison, Ronnie G.': 38.1,
'Peace, Jesse B.'': 31.34,
'Peet, Angela L': 61.23,
'Pino, Kola': 29.37,
'Picken, James': 42.79,
'Rich, Chiccie SR.': 35.74,
'Ryan, Noam': 31.37,
'Stark, Nancy B': 3.35,
'Teddy, Aimee': 31.02,
'Van Wilson, Len P.': 61.56,
'Wavering, Lindsay': 41.96},
'wgs': {'61101 · Salary & Wages-Packaging': 444.38,
'61104 · Salary & Wages-Bakery': 2602.4799999999996,
'61107 · Salary & Wages-Deli': 774.28,
'61109 · Salary & Wages-Produce': 643.31,
'61141 · Salary & Wages-Admin': 4110.31,
'61142 · Salary & Wages-Store': 2804.06}}
Returns dict that looks like dis
{9: {'txs_by_emp': {'Adams, L': 46.32,
'Avery, B': 25.77,
'Bingo, Nolan': 39.650000000000006,
'Conde, Barb': 23.59,
'Clyde-Owens, L': 48.42,
'Chorse, MD': 33.42,
'Fray-Chase, Jay': 27.94,
'Gunn, Jim': 46.88,
'Graybranch, Linne': 57.209999999999994,
'Hedrovin, Zed': 15.509999999999998,
'Heart, Ray': 48.14,
'LaRay, Jane': 43.42,
'Lentifold, Eddie': 2222.65,
'Mattison, Ronnie G.': 38.1,
'Peace, Jesse B.': 31.34,
'Peet, Angela L': 61.23,
'Pino, Kola': 29.37,
'Picken, James': 42.79,
'Rich, Chiccie SR.': 35.74,
'Ryan, Noam': 31.37,
'Stark, Nancy B': 3.35,
'Teddy, Aimee': 31.02,
'Van Wilson, Len P.': 61.56,
'Wavering, Lindsay': 41.96},
'wgs': {'61101 · Salary & Wages-Packaging': 444.38,
'61104 · Salary & Wages-Bakery': 2602.4799999999996,
'61107 · Salary & Wages-Deli': 774.28,
'61109 · Salary & Wages-Produce': 643.31,
'61141 · Salary & Wages-Admin': 4110.31,
'61142 · Salary & Wages-Store': 2804.06}}}
'''
#iterate thru each of the account dicts
#mult'ing by the ratio of days in first month (from fractmo_dict)
#populate a dcit or df with
# {key = month:
# {key = account: value = sum as ratio of number of days within key month}.
# {key = month:
# {key = account: value = sum as ratio of number of days within key month}.
piece_dict = {}
for k, v in account_sums['fractmo'].items():
piece_dict[k] = {}
piece_dict[k]['wgs'] = {}
for i, j in account_sums['wgs'].items():
# This is how we get weekly fractional wages
piece_dict[k]['wgs'][i] = j * v
piece_dict[k]['txs_for_depts_emps'] = {}
for m, n in account_sums['txs_for_depts_emps'].items():
# This is how we get weekly sums of taxes according to depts emps are assigned
piece_dict[k]['txs_for_depts_emps'][m] = n * v
# tbe = {}
# for m, n in account_sums['txs_by_emp'].items():
# # This is how we get weekly fractional taxes by employee
# tbe[m] = n * v
# This adds emps listed by dept to piece_dict for later use in sum_and_separate_by_dept
#piece_dict[k]['depts'] = depts
tbebd = {}
for d, l in depts.items():
tbebd[d] = {}
for n in l:
tbebd[d][n] = round(account_sums['txs_by_emp'][n] * v, 2)
piece_dict[k]['depts'] = tbebd
# print(f'tbebd')
# pprint(tbebd)
cn = {}
for d, t in account_sums['txs_for_depts_emps'].items():
cn[d] = (t + account_sums['wgs'][d]) * v
piece_dict[k]['cn'] = cn
#one col be the dept names --- one col be wages plus txs_for_depts_emps
return piece_dict
def make_lists_for_laterframes(generic_dict):
'''
Returns mini dfs out of series fed
'wages','taxes','employees' indexed by dept
'''
# print(f'generic_dict')
# pprint(generic_dict)
list_of_depts = []
list_of_things = []
for d, t in generic_dict.items():
list_of_depts.append(d)
list_of_things.append(t)
return list_of_depts, list_of_things
def sum_and_separate_by_dept(piece_dict):
'''
Takes a dict that looks like dis
{9: {'txs_by_emp': {'Adams, L': 46.32,
'Avery, B': 25.77,
'Bingo, Nolan': 39.650000000000006,
'Conde, Barb': 23.59,
'Clyde-Owens, L': 48.42,
'Chorse, MD': 33.42,
'Fray-Chase, Jay': 27.94,
'Gunn, Jim': 46.88,
'Graybranch, Linne': 57.209999999999994,
'Hedrovin, Zed': 15.509999999999998,
'Heart, Ray': 48.14,
'LaRay, Jane': 43.42,
'Lentifold, Eddie': 2222.65,
'Mattison, Ronnie G.': 38.1,
'Peace, Jesse B.': 31.34,
'Peet, Angela L': 61.23,
'Pino, Kola': 29.37,
'Picken, James': 42.79,
'Rich, Chiccie SR.': 35.74,
'Ryan, Noam': 31.37,
'Stark, Nancy B': 3.35,
'Teddy, Aimee': 31.02,
'Van Wilson, Len P.': 61.56,
'Wavering, Lindsay': 41.96},
'wgs': {'61101 · Salary & Wages-Packaging': 444.38,
'61104 · Salary & Wages-Bakery': 2602.4799999999996,
'61107 · Salary & Wages-Deli': 774.28,
'61109 · Salary & Wages-Produce': 643.31,
'61141 · Salary & Wages-Admin': 4110.31,
'61142 · Salary & Wages-Store': 2804.06}}}
Returns a list of dicts that looks like dis
list_of_wgs_by_dept
[{'61101 · Salary & Wages-Packaging': 89.43714285714285,
'61104 · Salary & Wages-Bakery': 632.0857142857143,
'61107 · Salary & Wages-Deli': 239.61714285714282,
'61109 · Salary & Wages-Produce': 178.0971428571428,
'61141 · Salary & Wages-Admin': 1342.802857142857,
'61142 · Salary & Wages-Store': 566.3571428571428}]
list_of_wgs_by_dept
[{'61101 · Salary & Wages-Packaging': 89.43714285714285,
'61104 · Salary & Wages-Bakery': 632.0857142857143,
'61107 · Salary & Wages-Deli': 239.61714285714282,
'61109 · Salary & Wages-Produce': 178.0971428571428,
'61141 · Salary & Wages-Admin': 1342.802857142857,
'61142 · Salary & Wages-Store': 566.3571428571428},
{'61101 · Salary & Wages-Packaging': 223.59285714285713,
'61104 · Salary & Wages-Bakery': 1580.2142857142858,
'61107 · Salary & Wages-Deli': 599.0428571428571,
'61109 · Salary & Wages-Produce': 445.2428571428571,
'61141 · Salary & Wages-Admin': 3357.0071428571428,
'61142 · Salary & Wages-Store': 1415.892857142857}]
'''
# print(f'piece_dict')
# pprint(piece_dict)
dfs = []
for m in piece_dict:
# Create wage dataframe
depts, wages = make_lists_for_laterframes(piece_dict[m]['wgs'])
df = pd.DataFrame(([0] * len(depts)), columns=['Wages'], index=[depts])
df['Wages'] = wages
df['Month'] = [m] * df.shape[0]
dfs.append(df)
# Create tax dataframe
depts, taxes = make_lists_for_laterframes(piece_dict[m]['txs_for_depts_emps'])
tax_df = pd.DataFrame(([0] * len(depts)), columns=['Taxes'], index=[depts])
tax_df.columns = ['Taxes']
tax_df['Taxes'] = taxes
dfs.append(tax_df)
# Create employee dataframe
depts, emps = make_lists_for_laterframes(piece_dict[m]['depts'])
emp_df = pd.DataFrame(([0] * len(depts)), columns=['Employees'], index=[depts])
emp_df['Employees'] = emps
dfs.append(emp_df)
depts, credit_new = make_lists_for_laterframes(piece_dict[m]['cn'])
cn_df = pd.DataFrame(([0] * len(depts)), columns=['Totals_WnT'], index=[depts])
cn_df['Totals_WnT'] = credit_new
dfs.append(cn_df)
return dfs
def merge_dfs(dfs):
# This is a trial way to loop through dfs indices and build dfs_x dataframe
# group_df = []
# x = []
# for i, df in enumerate(dfs):
# print(i)
# if i % 2 == 0 and i != 0:
# x.append(df)
# print(x)
# group_df.append(x)
# x = []
# else:
# x.append(df)
dfs_x = []
dfs_a = dfs[0].merge(dfs[1], left_index=True, right_index=True)\
.merge(dfs[2], left_index=True, right_index=True)\
.merge(dfs[3], left_index=True, right_index=True)
dfs_x.append(dfs_a)
if len(dfs) > 4:
dfs_b = dfs[4].merge(dfs[5], left_index=True, right_index=True)\
.merge(dfs[6], left_index=True, right_index=True)\
.merge(dfs[7], left_index=True, right_index=True)
dfs_x.append(dfs_b)
#dfs_x = pd.concat([dfs_a, dfs_b])
dfs_x = pd.concat(dfs_x)
return dfs_x
|
18,868 | a47ab129f47af8b27e26fbb6d34395a909036a58 | import numpy as np
def LDA_to_1dim(data,label):
#calculate distance between mean in new coordinates
# calculate within class scatter matrices.
#data is assumend to be in num_exam x dim format
# label is assumed to contain 1 and 0
data = np.asarray(data)
label = np.asarray(label)
c1data_index = np.where(label == 0)
c2data_index=np.where(label == 1)
c1data = data[c1data_index]
c2data = data[c2data_index]
mean_c1 = np.matrix(np.mean(c1data,axis=0))
print("shape of mean_c1 is",mean_c1.shape)
mean_c2 = np.matrix(np.mean(c2data,axis=0))
c1_cov = np.matmul((c1data-mean_c1).T, c1data-mean_c1)
c2_cov = np.matmul((c2data-mean_c2).T,c2data-mean_c2)
sw_inverse = np.linalg.inv(c1_cov + c2_cov)
sb = np.matmul((mean_c1-mean_c2).T,mean_c1-mean_c2)
# print(sb)
print("shape of sb is",sb.shape)
eig_val,eig_vec = np.linalg.eig(np.matmul(sw_inverse,sb))
index = np.argsort(eig_val)
reqd_vec = eig_vec[:,index[len(index)-1]]
return np.matmul(data,reqd_vec),reqd_vec
#data=[[1,2,2],[1,1,1],[1,2,3]]
#label=[0,1,1]
#data = np.asarray(data)
#label = np.asarray(label)
#c1data_index = np.where(label == 0)
#c2data_index=np.where(label == 1)
#
#c1data = data[c1data_index]
#c2data = data[c2data_index]
|
18,869 | edae1b6db7c865ebd4f8b5306c6431a60f0017c1 | f = open("./7/data.txt", "r")
all_rules = f.read().split("\n")
target_color = "shiny gold"
count = 0
good_rules = []
def find_color(rules, target):
for rule in rules:
if target in rule and rule[:len(target)] != target:
#global count
#count += 1
if rule not in good_rules:
good_rules.append(rule)
new_target = rule.split(" ")[0] + " " + rule.split(" ")[1]
#all_rules.remove(rule)
find_color(all_rules, new_target)
find_color(all_rules, target_color)
print(len(good_rules))
rules_dict = {}
for rule in all_rules:
new_key = rule.split(" ")[0] + " " + rule.split(" ")[1]
content = rule.split(" bags contain ")[1]
single_content = content.split(", ")
content_dict = {el.split(" ")[1] + " " + el.split(" ")[2] : el.split(" ")[0] for el in single_content}
rules_dict[new_key] = content_dict
#print(rules_dict["posh salmon"])
def count_bags(target):
if "other bags." in rules_dict[target]:
return 0
else:
total = 0
for k in rules_dict[target].keys():
total += (count_bags(k) + 1) * int(rules_dict[target][k])
return total
print(count_bags("shiny gold"))
|
18,870 | d580bbdfb3de6226fb9c2a17d1854eebef25e5e3 | class Solution:
def minRemoveToMakeValid(self, s: str) -> str:
_list = list(s)
stack = []
for i in range(len(_list)):
if _list[i]=='(':
stack.append(i)
elif _list[i]==')':
if stack:
stack.pop()
else:
_list[i]=''
if stack:
for i in stack:
_list[i]='0'
return re.sub('[0]','',''.join(_list))
|
18,871 | 22e1c0c3d86ab7b6188d4decc41dfeca8c74e9d3 | ###################
print "run : --- Match a pattern with a genetic algorithm"
###################
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-W", "--width", help="width", action="store", type=int, dest="width", default=32)
parser.add_option("-H", "--height", help="height", action="store", type=int, dest="height", default=32)
parser.add_option("-p", "--pattern", help="pattern to draw", action="store", type=str, dest="pattern", default="square")
parser.add_option("-g", "--genotypes", help="the number of genotypes", action="store", type=int, dest="genotypes", default=10)
parser.add_option("-i", "--iteration_limit", help="limit the number of generations", action="store", type=int, dest="max_generations", default=10)
parser.add_option("-m", "--mutation_chance", help="the mutation probability", action="store", type=float, dest="mutation_chance", default=0.1)
parser.add_option("-a", "--always_best", help="the fittest always breed", action="store_true", dest="always_best", default=False)
parser.add_option("-l", "--parents_live", help="the fittest always survive", action="store_true", dest="parents_live", default=False)
parser.add_option("-v", "--verbose", help="turn on verbose mode", action="store_true", dest="verbose", default=False)
(options, args) = parser.parse_args()
if options.verbose:
print "run : --- Options"
print "run : width: ",options.width
print "run : height: ",options.height
print "run : pattern: ",options.pattern
print "run : n genotypes: ",options.genotypes
print "run : maximum generations: ",options.max_generations
print "run : mutation probability: ",options.mutation_chance
print "run : fittest always survives: ",options.always_best
print "run : verbose: ",options.verbose
###################
import Canvas
import FitnessMeasures
import Line
import Population
import Tools
import time
###################
print "run : generating an empty canvas"
canvas = Canvas.Canvas(options.width,options.height)
if options.pattern == "square":
print "run : Drawing a square on the board"
canvas.add_line(Line.Line(10,10, options.width-10,10))
canvas.add_line(Line.Line(options.width-10,10, options.width-10,options.height-10))
canvas.add_line(Line.Line(options.width-10,options.height-10, 10,options.height-10))
canvas.add_line(Line.Line(10,options.height-10, 10,10))
n_lines = 4
else:
assert False, "Invalid pattern requested: %s"%options.pattern
file_name = "/zinc/web/copernicium/04/images/ideal.bmp"
canvas.save(file_name)
print "run : Saved target canvas as: %s"%file_name
print "run : Generating fitness measure"
fitness = FitnessMeasures.CanvasFitnessMeasure(canvas)
bases = Tools.MinBases(max(options.width,options.height))
print "run : max dimension: %i, bases: %i (2^%i = %i)"%(max(options.width,options.height),bases,bases,2**bases)
print "run : --- Generate a population"
population = \
Population.Population(fitness,
n_genotypes=options.genotypes,
n_genes=4*n_lines,
n_bases=bases,
mutation_chance=options.mutation_chance,
always_best=options.always_best,
verbose=options.verbose)
generation = 0
evolution = []
###################
print "run : --- Running"
ga_start = time.time()
while(True):
generation +=1
if (options.max_generations != -1) and (generation > options.max_generations): break
if options.verbose or (generation%100 == 0):
best_result = max(population.fitness)
print "run : generation[%i], best result: %.1f"%(generation,best_result)
# print population
if options.verbose: print "run : selecting fittest"
fittest = population.select_fittest(force_always_best=True)[0]
best_canvas = population.generate_canvas(fittest)
# evolution.append((fittest,
# max(population.fitness),
# best_canvas,
# fittest.genes))
# if (best_result > threshold): break
if options.verbose: print "run : fittest: %s"%(fittest.name)
population.breed_next_generation()
population.eval()
ga_end = time.time()
print population
best_result = max(population.fitness)
fittest = population.select_fittest(force_always_best=True)[0]
best_canvas = population.generate_canvas(fittest)
coding_used = fittest.genes
print "run : final generation[%i], best result: %f"%(generation, best_result)
print "run : solution: %s"%repr(fittest)
print "run : ",coding_used
print "run : ",best_canvas
print "run : time taken: %.2f s"%(ga_end-ga_start)
# # ###################
# # print "run : --- Brute force problem solving"
# # brute_start = time.time()
# # best_circle = Tools.SolveBoard(board,path,verbose=False)
# # brute_end = time.time()
# # print "run : solution: %s"%repr(best_circle)
# # print "run : time taken: %.2f s"%(brute_end-brute_start)
###################
print "test : --- Best canvas to file"
file_name = "/zinc/web/copernicium/04/images/test.bmp"
best_canvas.save(file_name)
# print "run : --- Write path to file"
# file_name = "path.csv"
# Tools.WritePathToFile(best_path,points,file_name)
# print "run : --- Write scores to file"
# file_name = "evolution.json"
# Tools.WriteEvolutionToJSON(evolution,points,fitness,file_name)
# print "run : --- Write genotype to file"
# file_name = "genotype.json"
# Tools.WriteGenotypeToJSON(fittest[0],file_name,coding=coding_used)
# print "run : --- Write evolution of path to file"
# file_name = "evolution.csv"
# Tools.WriteCirclesToCSV(best_path,file_name,scores=scores)
# print "run : --- Write parameters to file"
# file_name = "parameters.csv"
# Tools.WriteParametersToFile(options,file_name)
# print "run : --- Write results to files"
# results = {
# "GA result":repr(fittest[0].eval())[:-4],
# "GA time" :"%.2f s"%(ga_end-ga_start),
# "GA score" :"%.2f"%sqrt(best_result),
# "Brute force circle":repr(best_circle)[:-4],
# "Brute force Time" :"%.2f s"%(brute_end-brute_start),
# "Brute force score" :"%.2f"%best_circle.r
# }
# file_name = "results.json"
# import json
# with open(file_name, 'wb') as fp: json.dump(results, fp)
###################
print "run : --- done\n" |
18,872 | fefa3002b02285bd9449da0bf12a2bd72aeee763 | # -*- coding: utf-8 -*-
"""Iris_DTC_task4.py
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1I2p5hWK_rpMjAUiyCxqx8soodObqbrjV
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
df=pd.read_csv("Iris.csv")
df
df.info()
df.describe()
df.isnull().sum()
from sklearn.preprocessing import LabelEncoder
lab=LabelEncoder()
df.iloc[:,-1]=lab.fit_transform(df.iloc[:,-1])
df
X=df.iloc[:,1:5].values
y=df.iloc[:,-1].values
print("Dependent Variables:", df.columns[1:5])
print("Target Variable:", df.columns[-1])
sns.pairplot(df,hue='Species')
plt.show()
plt.figure(figsize=(12,12))
plt.subplot(2,2,1)
sns.boxplot(x='Species',y='SepalLengthCm',data=df)
plt.subplot(2,2,2)
sns.boxplot(x="Species",y="SepalWidthCm",data=df)
plt.subplot(2,2,3)
sns.boxplot(x="Species",y="PetalLengthCm",data=df)
plt.subplot(2,2,4)
sns.boxplot(x="Species",y="PetalWidthCm",data=df)
from sklearn.model_selection import train_test_split
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=0)
print("X_train :",X_train.shape)
print("X_test :",X_test.shape)
print("y_train :",y_train.shape)
print("y_test :",y_test.shape)
from sklearn.tree import DecisionTreeClassifier
dct=DecisionTreeClassifier()
dct.fit(X_train,y_train)
dct.score(X_test,y_test)
y_pred=dct.predict(X_test)
y_pred
from sklearn.metrics import confusion_matrix
cm=confusion_matrix(y_test,y_pred)
cm
from sklearn import metrics
from sklearn.metrics import accuracy_score
print('Accuracy Score:', accuracy_score(y_test, y_pred))
from sklearn.tree import export_graphviz
export_graphviz(dct,out_file="tree.dot")
import graphviz
with open("tree.dot") as f:
dot_graph = f.read()
graphviz.Source(dot_graph)
from sklearn.externals.six import StringIO
from IPython.display import Image
import pydotplus
dot_data = StringIO()
export_graphviz(dct, out_file=dot_data, feature_names=df.columns[1:5],
filled=True, rounded=True
)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
Image(graph.create_png())
|
18,873 | 8dd2d267fd23c07545f68d01e24613624b24c500 | #!/usr/bin/env python3.7
import os
import json
import copy
import datetime
from smbus2 import SMBus
from cereal import log
from common.basedir import BASEDIR
from common.params import Params
from common.realtime import sec_since_boot, DT_TRML
from common.numpy_fast import clip
from common.filter_simple import FirstOrderFilter
from selfdrive.version import terms_version, training_version
from selfdrive.swaglog import cloudlog
import selfdrive.messaging as messaging
from selfdrive.services import service_list
from selfdrive.loggerd.config import get_available_percent
ThermalStatus = log.ThermalData.ThermalStatus
CURRENT_TAU = 15. # 15s time constant
DAYS_NO_CONNECTIVITY_MAX = 7 # do not allow to engage after a week without internet
DAYS_NO_CONNECTIVITY_PROMPT = 4 # send an offroad prompt after 4 days with no internet
with open(BASEDIR + "/selfdrive/controls/lib/alerts_offroad.json") as json_file:
OFFROAD_ALERTS = json.load(json_file)
def read_tz(x):
with open("/sys/devices/virtual/thermal/thermal_zone%d/temp" % x) as f:
ret = max(0, int(f.read()))
return ret
def read_thermal():
dat = messaging.new_message()
dat.init('thermal')
dat.thermal.cpu0 = read_tz(5)
dat.thermal.cpu1 = read_tz(7)
dat.thermal.cpu2 = read_tz(10)
dat.thermal.cpu3 = read_tz(12)
dat.thermal.mem = read_tz(2)
dat.thermal.gpu = read_tz(16)
dat.thermal.bat = read_tz(29)
return dat
LEON = False
def setup_eon_fan():
global LEON
os.system("echo 2 > /sys/module/dwc3_msm/parameters/otg_switch")
bus = SMBus(7, force=True)
try:
bus.write_byte_data(0x21, 0x10, 0xf) # mask all interrupts
bus.write_byte_data(0x21, 0x03, 0x1) # set drive current and global interrupt disable
bus.write_byte_data(0x21, 0x02, 0x2) # needed?
bus.write_byte_data(0x21, 0x04, 0x4) # manual override source
except IOError:
print("LEON detected")
#os.system("echo 1 > /sys/devices/soc/6a00000.ssusb/power_supply/usb/usb_otg")
LEON = True
bus.close()
last_eon_fan_val = None
def set_eon_fan(val):
global LEON, last_eon_fan_val
if last_eon_fan_val is None or last_eon_fan_val != val:
bus = SMBus(7, force=True)
if LEON:
try:
i = [0x1, 0x3 | 0, 0x3 | 0x08, 0x3 | 0x10][val]
bus.write_i2c_block_data(0x3d, 0, [i])
except IOError:
# tusb320
if val == 0:
bus.write_i2c_block_data(0x67, 0xa, [0])
else:
bus.write_i2c_block_data(0x67, 0xa, [0x20])
bus.write_i2c_block_data(0x67, 0x8, [(val-1)<<6])
else:
bus.write_byte_data(0x21, 0x04, 0x2)
bus.write_byte_data(0x21, 0x03, (val*2)+1)
bus.write_byte_data(0x21, 0x04, 0x4)
bus.close()
last_eon_fan_val = val
# temp thresholds to control fan speed - high hysteresis
_TEMP_THRS_H = [50., 65., 80., 10000]
# temp thresholds to control fan speed - low hysteresis
_TEMP_THRS_L = [42.5, 57.5, 72.5, 10000]
# fan speed options
_FAN_SPEEDS = [0, 16384, 32768, 65535]
# max fan speed only allowed if battery is hot
_BAT_TEMP_THERSHOLD = 45.
def handle_fan(max_cpu_temp, bat_temp, fan_speed):
new_speed_h = next(speed for speed, temp_h in zip(_FAN_SPEEDS, _TEMP_THRS_H) if temp_h > max_cpu_temp)
new_speed_l = next(speed for speed, temp_l in zip(_FAN_SPEEDS, _TEMP_THRS_L) if temp_l > max_cpu_temp)
if new_speed_h > fan_speed:
# update speed if using the high thresholds results in fan speed increment
fan_speed = new_speed_h
elif new_speed_l < fan_speed:
# update speed if using the low thresholds results in fan speed decrement
fan_speed = new_speed_l
if bat_temp < _BAT_TEMP_THERSHOLD:
# no max fan speed unless battery is hot
fan_speed = min(fan_speed, _FAN_SPEEDS[-2])
set_eon_fan(fan_speed//16384)
return fan_speed
def thermald_thread():
setup_eon_fan()
# prevent LEECO from undervoltage
BATT_PERC_OFF = 10 if LEON else 3
# now loop
thermal_sock = messaging.pub_sock(service_list['thermal'].port)
health_sock = messaging.sub_sock(service_list['health'].port)
location_sock = messaging.sub_sock(service_list['gpsLocation'].port)
fan_speed = 0
count = 0
off_ts = None
started_ts = None
started_seen = False
thermal_status = ThermalStatus.green
thermal_status_prev = ThermalStatus.green
usb_power = True
usb_power_prev = True
health_sock.RCVTIMEO = int(1000 * 2 * DT_TRML) # 2x the expected health frequency
current_filter = FirstOrderFilter(0., CURRENT_TAU, DT_TRML)
health_prev = None
current_connectivity_alert = None
params = Params()
while 1:
health = messaging.recv_sock(health_sock, wait=True)
location = messaging.recv_sock(location_sock)
location = location.gpsLocation if location else None
msg = read_thermal()
# clear car params when panda gets disconnected
if health is None and health_prev is not None:
params.panda_disconnect()
health_prev = health
if health is not None:
usb_power = health.health.usbPowerMode != log.HealthData.UsbPowerMode.client
# loggerd is gated based on free space
avail = get_available_percent() / 100.0
# thermal message now also includes free space
msg.thermal.freeSpace = avail
with open("/sys/class/power_supply/battery/capacity") as f:
msg.thermal.batteryPercent = int(f.read())
with open("/sys/class/power_supply/battery/status") as f:
msg.thermal.batteryStatus = f.read().strip()
with open("/sys/class/power_supply/battery/current_now") as f:
msg.thermal.batteryCurrent = int(f.read())
with open("/sys/class/power_supply/battery/voltage_now") as f:
msg.thermal.batteryVoltage = int(f.read())
with open("/sys/class/power_supply/usb/present") as f:
msg.thermal.usbOnline = bool(int(f.read()))
current_filter.update(msg.thermal.batteryCurrent / 1e6)
# TODO: add car battery voltage check
max_cpu_temp = max(msg.thermal.cpu0, msg.thermal.cpu1,
msg.thermal.cpu2, msg.thermal.cpu3) / 10.0
max_comp_temp = max(max_cpu_temp, msg.thermal.mem / 10., msg.thermal.gpu / 10.)
bat_temp = msg.thermal.bat/1000.
fan_speed = handle_fan(max_cpu_temp, bat_temp, fan_speed)
msg.thermal.fanSpeed = fan_speed
# thermal logic with hysterisis
if max_cpu_temp > 107. or bat_temp >= 63.:
# onroad not allowed
thermal_status = ThermalStatus.danger
elif max_comp_temp > 92.5 or bat_temp > 60.: # CPU throttling starts around ~90C
# hysteresis between onroad not allowed and engage not allowed
thermal_status = clip(thermal_status, ThermalStatus.red, ThermalStatus.danger)
elif max_cpu_temp > 87.5:
# hysteresis between engage not allowed and uploader not allowed
thermal_status = clip(thermal_status, ThermalStatus.yellow, ThermalStatus.red)
elif max_cpu_temp > 80.0:
# uploader not allowed
thermal_status = ThermalStatus.yellow
elif max_cpu_temp > 75.0:
# hysteresis between uploader not allowed and all good
thermal_status = clip(thermal_status, ThermalStatus.green, ThermalStatus.yellow)
else:
# all good
thermal_status = ThermalStatus.green
# **** starting logic ****
# Check for last update time and display alerts if needed
now = datetime.datetime.now()
try:
last_update = datetime.datetime.fromisoformat(params.get("LastUpdateTime", encoding='utf8'))
except (TypeError, ValueError):
last_update = now
dt = now - last_update
if dt.days > DAYS_NO_CONNECTIVITY_MAX:
if current_connectivity_alert != "expired":
current_connectivity_alert = "expired"
params.delete("Offroad_ConnectivityNeededPrompt")
params.put("Offroad_ConnectivityNeeded", json.dumps(OFFROAD_ALERTS["Offroad_ConnectivityNeeded"]))
elif dt.days > DAYS_NO_CONNECTIVITY_PROMPT:
remaining_time = str(DAYS_NO_CONNECTIVITY_MAX - dt.days)
if current_connectivity_alert != "prompt" + remaining_time:
current_connectivity_alert = "prompt" + remaining_time
alert_connectivity_prompt = copy.copy(OFFROAD_ALERTS["Offroad_ConnectivityNeededPrompt"])
alert_connectivity_prompt["text"] += remaining_time + " days."
params.delete("Offroad_ConnectivityNeeded")
params.put("Offroad_ConnectivityNeededPrompt", json.dumps(alert_connectivity_prompt))
elif current_connectivity_alert is not None:
current_connectivity_alert = None
params.delete("Offroad_ConnectivityNeeded")
params.delete("Offroad_ConnectivityNeededPrompt")
# start constellation of processes when the car starts
ignition = health is not None and health.health.started
do_uninstall = params.get("DoUninstall") == b"1"
accepted_terms = params.get("HasAcceptedTerms") == terms_version
completed_training = params.get("CompletedTrainingVersion") == training_version
should_start = ignition
# have we seen a panda?
passive = (params.get("Passive") == "1")
# with 2% left, we killall, otherwise the phone will take a long time to boot
should_start = should_start and msg.thermal.freeSpace > 0.02
# confirm we have completed training and aren't uninstalling
should_start = should_start and accepted_terms and (passive or completed_training) and (not do_uninstall)
# if any CPU gets above 107 or the battery gets above 63, kill all processes
# controls will warn with CPU above 95 or battery above 60
if thermal_status >= ThermalStatus.danger:
should_start = False
if thermal_status_prev < ThermalStatus.danger:
params.put("Offroad_TemperatureTooHigh", json.dumps(OFFROAD_ALERTS["Offroad_TemperatureTooHigh"]))
else:
if thermal_status_prev >= ThermalStatus.danger:
params.delete("Offroad_TemperatureTooHigh")
if should_start:
off_ts = None
if started_ts is None:
started_ts = sec_since_boot()
started_seen = True
os.system('echo performance > /sys/class/devfreq/soc:qcom,cpubw/governor')
else:
started_ts = None
if off_ts is None:
off_ts = sec_since_boot()
os.system('echo powersave > /sys/class/devfreq/soc:qcom,cpubw/governor')
# shutdown if the battery gets lower than 3%, it's discharging, we aren't running for
# more than a minute but we were running
if msg.thermal.batteryPercent < BATT_PERC_OFF and msg.thermal.batteryStatus == "Discharging" and \
started_seen and (sec_since_boot() - off_ts) > 60:
os.system('LD_LIBRARY_PATH="" svc power shutdown')
msg.thermal.chargingError = current_filter.x > 0. and msg.thermal.batteryPercent < 90 # if current is positive, then battery is being discharged
msg.thermal.started = started_ts is not None
msg.thermal.startedTs = int(1e9*(started_ts or 0))
msg.thermal.thermalStatus = thermal_status
thermal_sock.send(msg.to_bytes())
if usb_power_prev and not usb_power:
params.put("Offroad_ChargeDisabled", json.dumps(OFFROAD_ALERTS["Offroad_ChargeDisabled"]))
elif usb_power and not usb_power_prev:
params.delete("Offroad_ChargeDisabled")
thermal_status_prev = thermal_status
usb_power_prev = usb_power
print(msg)
# report to server once per minute
if (count % int(60. / DT_TRML)) == 0:
cloudlog.event("STATUS_PACKET",
count=count,
health=(health.to_dict() if health else None),
location=(location.to_dict() if location else None),
thermal=msg.to_dict())
count += 1
def main(gctx=None):
thermald_thread()
if __name__ == "__main__":
main()
|
18,874 | 924a6da759ae32f5a2a883ed3239cf847dff4a9b | """
问题描述: 牛牛与妞妞闲来无聊，便拿出扑克牌来进行游戏。游戏的规则很简单，两个人随机
抽取四张牌，四张牌的数字和最大的取胜（该扑克牌总张数为52张，没有大小王，A=1，J=11，
Q=12，K=13，每种数字有四张牌），现在两人已经分别亮出了自己的前三张牌，牛牛想要知
道自己要赢得游戏的概率有多大。
输入包含两行，第一行输入三个整数a1，b1，c1(1≤a1，b1，c1≤13)，表示牛牛亮出的扑克牌。
第二行输入三个整数a2，b2，c2(1≤a2，b2，c2≤13)，表示妞妞所亮出的扑克牌。
示例:
3 5 7
2 6 8
输出:
0.3995
"""
class Solution:
def get_properties(self, a1, a2, a3, b1, b2, b3):
a = [0 for _ in range(60)]
vis = [0 for _ in range(15)]
vis[a1] += 1
vis[a2] += 1
vis[a3] += 1
vis[b1] += 1
vis[b2] += 1
vis[b3] += 1
sum1 = a1 + a2 + a3
sum2 = b1 + b2 + b3
cnt = 0
l, r = 0, 0
for i in range(1, 14):
for j in range(0, 4-vis[i]):
a[cnt] = i
cnt += 1
for i in range(cnt):
sum1 += a[i]
for j in range(cnt):
if i == j:
continue
sum2 += a[j]
r += 1
if sum1 > sum2:
l += 1
sum2 -= a[j]
sum1 -= a[i]
print('%.4f' % (l / r))
if __name__ == '__main__':
s = Solution()
a, b, c = list(map(int, input().split()))
d, e, f = list(map(int, input().split()))
s.get_properties(a, b, c, d, e, f) |
18,875 | 45dc38155b0cbd7bd1b4f0d14a2f17ec78bb44e8 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# ==============================================================================
# \file gen-records.py
# \author chenghuige
# \date 2019-07-27 22:33:36.314010
# \Description
# ==============================================================================
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import os
from absl import app as absl_app
from absl import flags
FLAGS = flags.FLAGS
import glob
from tqdm import tqdm
import multiprocessing
from multiprocessing import Value
import gezi
import melt
from config import *
import pandas as pd
import tensorflow as tf
flags.DEFINE_string('input', None, '')
flags.DEFINE_string('out_dir', None, '')
flags.DEFINE_bool('over_write', True, '')
counter = Value('i', 0)
def get_out_file(infile):
infile_ = os.path.basename(infile)
ofile_ = infile_.replace('.csv', '.record')
ofile = os.path.join(FLAGS.out_dir, ofile_)
return ofile
def build_features(infile):
ofile = get_out_file(infile)
if not FLAGS.over_write:
if os.path.exists(ofile):
print('-----exists', ofile)
return
df = pd.read_csv(infile)
with melt.tfrecords.Writer(ofile) as writer:
for _, row in tqdm(df.iterrows(), total=len(df), ascii=True):
id = row['id_code']
label = 0
if 'diagnosis' in row:
label = row['diagnosis']
image_file = f'{FLAGS.out_dir}_images/{id}.png'
image = melt.read_image(image_file)
feature = {'id': melt.bytes_feature(id),
'label': melt.int64_feature(label),
'image': melt.bytes_feature(image)}
record = tf.train.Example(features=tf.train.Features(feature=feature))
writer.write(record)
global counter
with counter.get_lock():
counter.value += 1
def main(_):
input = f'{FLAGS.dir}/{FLAGS.input}'
files = glob.glob(input)
gezi.sprint(input)
FLAGS.out_dir = f'{FLAGS.dir}/tfrecords/{FLAGS.out_dir}'
out_dir = FLAGS.out_dir
if not os.path.exists(out_dir):
print('make new dir: [%s]' % out_dir, file=sys.stderr)
os.makedirs(out_dir)
gezi.sprint(out_dir)
pool = multiprocessing.Pool()
pool.map(build_features, files)
pool.close()
pool.join()
print('num_records:', counter.value)
out_file = '{}/num_records.txt'.format(out_dir)
gezi.write_to_txt(counter.value, out_file)
if __name__ == '__main__':
absl_app.run(main)
|
18,876 | 43d92d891add165e77066bcc14b60507cd09ee57 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('gallery', '0002_exhibition'),
]
operations = [
migrations.AlterField(
model_name='exhibition',
name='end',
field=models.DateField(default=None, null=True, blank=True),
preserve_default=True,
),
]
|
18,877 | 0dad65680aaa9c12f13b0fa8904635b8e6d9918c | #!/usr/bin/env python
import sys
import rospy
from srv_example.srv import *
# Service call handler
def add_two_ints_client(x, y):
# Wait for service to become available
rospy.wait_for_service('add_two_ints')
try:
# The service proxy handles the service call, like a temporary node!
# add_two_ints is the service name
# AddTwoInts is the service type/file
add_two_ints = rospy.ServiceProxy('add_two_ints', AddTwoInts)
resp1 = add_two_ints(x, y)
return resp1.Sum
except rospy.ServiceException, e:
print("Service call failed: %s" % e)
# Invalid call reminder
def usage():
return "Usage: %s [x y]" % sys.argv[0]
if __name__ == "__main__":
# If the service call was properly formatted, proceed
if len(sys.argv) == 3:
x = int(sys.argv[1])
y = int(sys.argv[2])
# Else, remind the user of the proper usage
else:
print(usage())
sys.exit(1) # Terminate the script
print("Requesting %s+%s" % (x, y))
print("%s + %s = %s" % (x, y, add_two_ints_client(x, y)))
|
18,878 | 6f9a24fa9c1cdf0b9f9cccb1366f76aeb40d9e3b | #Initializing a 2D list
list = [[10,2,34,56],[122,34,45,67],[23,2232,12]]
#Prints all the lists present inside a list
print(list)
#prints the second element in the first list
print(list[0][1])
#Prints the fourth element in the second list
print(list[1][3])
#prints the last element in the third list
print(list[2][2])
#Appends data in the third list
list[2].append(100)
#Modifying the value in the third list
list[2][0] = 500
#Prints the modified list after appending and modify the contents in the list
print("Modified list:",list)
#List iteration for 2D lists
print()
#Method 1
def method1_2D(list):
for i in range(len(list)):
for j in range(len(list[i])):
print(list[i][j],end=" ") #Ends with a space instead of a newline
print()
#Method 2
def method2_2D(list):
for inner in list:
for item in inner:
print(item,end=" ")
print()
print("2D List iteration using method 1:")
method1_2D(list)
print("\n2D List iteration using method 2")
method2_2D(list)
#Sorting 2D lists
listSort=[[23,34,341,213],[10,11,4,'bye','hi'],[12]]
print("The 2D list before sorting:",listSort)
print("The 2D list after sorting:")
print(sorted(listSort))
#Different ways to sort a 2D list
listScores=[[6,4,2,1],[6,6,1,2],[2,5,4,3,4,1],[6,1,6,2,6,6,6,6,3]]
print(sorted(listScores,key=sum)) #Sort based on the sum of each list
def avg(listScores):
return sum(listScores) / len(listScores)
print(sorted(listScores,key=avg)) #Sort based on the average of each list |
18,879 | 35fb8b65466652335b4b9b1ed86ea5bea8b08df8 | import json
from six.moves.urllib.parse import parse_qsl, urlparse
import pytest
import workos
from workos.sso import SSO
from workos.utils.connection_types import ConnectionType
from workos.utils.request import RESPONSE_TYPE_CODE
class TestSSO(object):
@pytest.fixture(autouse=True)
def setup(self, set_api_key_and_project_id):
self.provider = ConnectionType.GoogleOAuth
self.customer_domain = "workos.com"
self.redirect_uri = "https://localhost/auth/callback"
self.state = json.dumps({"things": "with_stuff",})
self.sso = SSO()
@pytest.fixture
def mock_profile(self):
return {
"id": "prof_01DWAS7ZQWM70PV93BFV1V78QV",
"email": "demo@workos-okta.com",
"first_name": "WorkOS",
"last_name": "Demo",
"connection_id": "conn_01EMH8WAK20T42N2NBMNBCYHAG",
"connection_type": "OktaSAML",
"idp_id": "00u1klkowm8EGah2H357",
"raw_attributes": {
"email": "demo@workos-okta.com",
"first_name": "WorkOS",
"last_name": "Demo",
},
}
@pytest.fixture
def mock_connection(self):
return {
"object": "connection",
"id": "conn_id",
"status": "linked",
"name": "Google OAuth 2.0",
"connection_type": "GoogleOAuth",
"oauth_uid": "oauth-uid.apps.googleusercontent.com",
"oauth_secret": "oauth-secret",
"oauth_redirect_uri": "https://auth.workos.com/sso/oauth/google/chicken/callback",
"saml_entity_id": None,
"saml_idp_url": None,
"saml_relying_party_trust_cert": None,
"saml_x509_certs": None,
"domains": [
{
"object": "connection_domain",
"id": "domain_id",
"domain": "terrace-house.com",
},
],
}
def test_authorization_url_throws_value_error_with_missing_domain_and_provider(
self,
):
with pytest.raises(ValueError, match=r"Incomplete arguments.*"):
self.sso.get_authorization_url(
redirect_uri=self.redirect_uri, state=self.state
)
def test_authorization_url_throws_value_error_with_incorrect_provider_type(self):
with pytest.raises(
ValueError, match="'provider' must be of type ConnectionType"
):
self.sso.get_authorization_url(
provider="foo", redirect_uri=self.redirect_uri, state=self.state
)
def test_authorization_url_has_expected_query_params_with_provider(self):
authorization_url = self.sso.get_authorization_url(
provider=self.provider, redirect_uri=self.redirect_uri, state=self.state
)
parsed_url = urlparse(authorization_url)
assert dict(parse_qsl(parsed_url.query)) == {
"provider": str(self.provider.value),
"client_id": workos.project_id,
"redirect_uri": self.redirect_uri,
"response_type": RESPONSE_TYPE_CODE,
"state": self.state,
}
def test_authorization_url_has_expected_query_params_with_domain(self):
authorization_url = self.sso.get_authorization_url(
domain=self.customer_domain,
redirect_uri=self.redirect_uri,
state=self.state,
)
parsed_url = urlparse(authorization_url)
assert dict(parse_qsl(parsed_url.query)) == {
"domain": self.customer_domain,
"client_id": workos.project_id,
"redirect_uri": self.redirect_uri,
"response_type": RESPONSE_TYPE_CODE,
"state": self.state,
}
def test_authorization_url_has_expected_query_params_with_domain_and_provider(self):
authorization_url = self.sso.get_authorization_url(
domain=self.customer_domain,
provider=self.provider,
redirect_uri=self.redirect_uri,
state=self.state,
)
parsed_url = urlparse(authorization_url)
assert dict(parse_qsl(parsed_url.query)) == {
"domain": self.customer_domain,
"provider": str(self.provider.value),
"client_id": workos.project_id,
"redirect_uri": self.redirect_uri,
"response_type": RESPONSE_TYPE_CODE,
"state": self.state,
}
def test_get_profile_returns_expected_workosprofile_object(
self, mock_profile, mock_request_method
):
response_dict = {
"profile": {
"object": "profile",
"id": mock_profile["id"],
"email": mock_profile["email"],
"first_name": mock_profile["first_name"],
"connection_id": mock_profile["connection_id"],
"connection_type": mock_profile["connection_type"],
"last_name": mock_profile["last_name"],
"idp_id": mock_profile["idp_id"],
"raw_attributes": {
"email": mock_profile["raw_attributes"]["email"],
"first_name": mock_profile["raw_attributes"]["first_name"],
"last_name": mock_profile["raw_attributes"]["last_name"],
},
},
"access_token": "01DY34ACQTM3B1CSX1YSZ8Z00D",
}
mock_request_method("post", response_dict, 200)
profile = self.sso.get_profile(123)
assert profile.to_dict() == mock_profile
def test_create_connection(self, mock_request_method, mock_connection):
response_dict = {
"object": "connection",
"id": mock_connection["id"],
"name": mock_connection["name"],
"status": mock_connection["status"],
"connection_type": mock_connection["connection_type"],
"oauth_uid": mock_connection["oauth_uid"],
"oauth_secret": mock_connection["oauth_secret"],
"oauth_redirect_uri": mock_connection["oauth_redirect_uri"],
"saml_entity_id": mock_connection["saml_entity_id"],
"saml_idp_url": mock_connection["saml_idp_url"],
"saml_relying_party_trust_cert": mock_connection[
"saml_relying_party_trust_cert"
],
"saml_x509_certs": mock_connection["saml_x509_certs"],
"domains": mock_connection["domains"],
}
mock_request_method("post", mock_connection, 201)
connection = self.sso.create_connection("draft_conn_id")
assert connection == response_dict
|
18,880 | d08d03887b6b47369ddff95ddc570626ea309462 | import cherrypy
import core.config as s_config
import core.models.tablet
import core.api.gameapi
import core.api.viewerapi
import core.api.scoutingapi
import core.api.teamapi
import core.api.eventapi
import core.api.tabletapi
import core.api.matchapi
if __name__ == '__main__':
cherrypy.config.update(
{'server.socket_host': '0.0.0.0',
'server.socket_port': 8080})
conf = {"/": {'tools.staticdir.on': True,
'tools.staticdir.dir': s_config.web_base(),
'tools.response_headers.on': True,
'tools.response_headers.headers': [('Access-Control-Allow-Origin', '*')]}}
def secure_headers():
cherrypy.response.headers["Access-Control-Allow-Origin"] = "*"
cherrypy.tools.secure_headers = cherrypy.Tool(
'before_handler', secure_headers, None, priority=30)
cherrypy.tree.mount(core.api.viewerapi.ViewerApi(False), '/view', config=conf)
cherrypy.tree.mount(core.api.gameapi.GameApi(), '/game', config=conf)
cherrypy.tree.mount(core.api.teamapi.TeamApi(), '/team', config=conf)
cherrypy.tree.mount(core.api.tabletapi.TabletApi(), '/tablet', config=conf)
cherrypy.tree.mount(core.api.eventapi.EventApi(), '/event', config=conf)
cherrypy.tree.mount(core.api.matchapi.MatchApi(), '/match', config=conf)
cherrypy.tree.mount(core.api.scoutingapi.ScoutingApi(), '/', config=conf)
cherrypy.engine.signals.subscribe()
cherrypy.engine.start()
cherrypy.engine.block()
|
18,881 | ecd1a49319674ffa9f7370e2a5e83bfff42ea5af | uri="mongodb://admin:admin1@ds053300.mlab.com:53300/c4e25"
#1.connect to mlab server
from pymongo import MongoClient
client=MongoClient(uri)
#2.get a database
db= client.get_database()
# #3. get a CONNECTION
# collection = db.test_collection
# #4.CREATE A DOCUMENT
# import datetime
# post={
# "author": "Mike",
# "text": "My first blog post!",
# "tags": ["mongodb", "python", "pymongo"],
# "date": datetime.datetime.utcnow()
# }
# #5.inseert document
# posts = db.posts
# post_id = posts.insert_one(post).inserted_id
# post_id
#3. get a CONNECTION
post_collection = db["post"]
#4.CREATE A DOCUMENT
new_post={
"title":"sunny day", #field title
"content":"hello",
}
#5.inseert document
post_collection.insert_one(new_post)
# for post in post_collection.find():
# print(post_collection)
# # close connection
# client.close()
# # lazyloading
# post_list=post_collection.find()
# # first_post=post_list[0]
# # print(first_post)
# for p in post_list:
# print(p)
|
18,882 | 5094f06c9a6f31bcce066454ea982aed0f087d1a | import numpy as np
a = np.array([1,2,3])
print(a)
# Multi-dimension
b = np.array([[10,12,13,14],[21,22,23,24]])
#3d
c = np.array([ [[1,2],[3,4],[9,10]],[[5,6],[7,8],[11,12]] ])
print(b)
print(c)
#Get dimension
print(a.ndim)
print(b.ndim)
print(c.ndim)
# Get Shape
print(a.shape)
# The outermost dimension will have 2 arrays, each with 4 elements:
print(b.shape)
# The outermost dimension will have 2 arrays that contains 3 arrays, each with 2 elements:
print(c.shape)
# Get Size (count num of elements in whole)
print(a.size)
print(b.size)
|
18,883 | 373a6bdb981a3a030d14ace02ff53e9c1a3ef10d | # testsplitter.py
import splitter
import doctest
nfail, ntests = doctest.testmod(splitter)
print(nfail, ntests) |
18,884 | 07098c3bd38a5aa4ca99411e2fcb0fb69740e8ec | #!/usr/bin/env python
# -*- coding:utf-8 -*-
# Time: 2019/10/15 11:14
# Author: Hou hailun
class ListNode(object):
def __init__(self, x):
self.val = x
self.next = None
class Solution(object):
def middleNode(self, head):
"""
:type head: ListNode
:rtype: ListNode
"""
# 快慢指针，快指针每次走2步，慢指针每次走1步
if head is None and head.next is None:
return head
slow = head
fast = head
while fast and fast.next:
fast = fast.next.next
slow = slow.next
return slow |
18,885 | 07cdc6c5bf6d25fa9b4c97dc9f59034565aa6748 | # -*- coding: utf-8 -*-
import scrapy
import json
from ..items import BookItem
class Z51zhySpider(scrapy.Spider):
name = 'z51zhy'
allowed_domains = ['51zhy.cn']
custom_settings = {
'DOWNLOADER_MIDDLEWARES': {
'book.middlewares.Z51ZHYBookDownloaderMiddleware': 543,
},
'ITEM_PIPELINES': {
'book.pipelines.Z51ZHYBookPDFPipeline': 300
},
'FILES_STORE': 'z51zhy/',
'DOWNLOAD_DELAY': 3,
}
def start_requests(self):
headers = {
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
'Accept-Encoding': 'gzip, deflate',
'Accept-Language': 'zh-HK,zh;q=0.9,en-US;q=0.8,en;q=0.7,zh-TW;q=0.6',
'Cache-Control': 'max-age=0',
'Connection': 'keep-alive',
'Host': 'yd.51zhy.cn',
'Upgrade-Insecure-Requests': '1',
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.130 Safari/537.36',
}
url = 'http://yd.51zhy.cn/ebook/web/search/search4HomePage'
total = 20600
# total = 15
size = 15
max_page = int(total / size) + 1
for i in range(1, max_page):
yield scrapy.Request(url='{}?currentPage={}'.format(url, i), headers=headers, callback=self.parse)
def parse(self, response):
url = 'https://bridge.51zhy.cn/transfer/content/authorize'
ids = response.css('ul li.ebook-item input.search_Input::attr(value)').getall()
meta = response.meta
for id in ids:
meta['id'] = id
form = {
'id': id,
'BridgePlatformName': 'phei_yd_web',
'DeviceToken': 'ebookE0415F559DF90E6D52123BBB653436B2',
'AppId': '3',
'type': 'aes'
}
yield scrapy.FormRequest(url=url, meta=meta, formdata=form, callback=self.parse_authorize)
def parse_authorize(self, response):
data = json.loads(response.text)
o = data['Data']
meta = response.meta
meta['url'] = o['Url']
meta['key'] = o['Key']
url = 'https://bridge.51zhy.cn/transfer/Content/Detail?AppId=3&BridgePlatformName=phei_yd_web&id={}'.format(response.meta['id'])
form = {
'id': meta['id'],
'BridgePlatformName': 'phei_yd_web',
'DeviceToken': 'ebookE0415F559DF90E6D52123BBB653436B2',
'AppId': '3'
}
yield scrapy.FormRequest(url=url, meta=meta, formdata=form, callback=self.parse_detail)
def parse_detail(self, response):
data = json.loads(response.text)
o = data['Data']
book = BookItem()
book['img'] = o['CoverUrl']
book['price'] = o['CurrentPrice']
book['name'] = o['Title']
book['publishdate'] = o['PublishDate']
book['id'] = response.meta['id']
book['writer'] = o['Author']
book['file_urls'] = [response.meta['url']]
book['files'] = []
book['key'] = response.meta['key']
yield book
|
18,886 | 2ca34b75f0a72be52613aaa52c4d474b76bfcafc | import numpy as np
import scr.FigureSupport as Fig
class Game(object):
def __init__(self, id, prob_head):
self._id = id
self._rnd = np.random
self._rnd.seed(id)
self._probHead = prob_head # probability of flipping a head
self._countWins = 0 # number of wins, set to 0 to begin
self._reward = 0
def simulate(self, n_of_flips):
count_tails = 0 # number of consecutive tails so far, set to 0 to begin
# flip the coin 20 times
for i in range(n_of_flips):
# in the case of flipping a heads
if self._rnd.random_sample() < self._probHead:
if count_tails >= 2: # if the series is ..., T, T, H
self._countWins += 1 # increase the number of wins by 1
count_tails = 0 # the tails counter needs to be reset to 0 because a heads was flipped
# in the case of flipping a tails
else:
count_tails += 1 # increase tails count by one
def get_reward(self):
# calculate the reward from playing a single game
self._reward = 100*self._countWins - 250
return self._reward
class SetOfGames:
def __init__(self, prob_head, n_games):
self._gameRewards = [] # create an empty list where rewards will be stored
# simulate the games
for n in range(n_games):
# create a new game
game = Game(id=n, prob_head=prob_head)
# simulate the game with 20 flips
game.simulate(20)
# store the reward
self._gameRewards.append(game.get_reward())
def get_all_reward(self):
return self._gameRewards
def get_ave_reward(self):
""" returns the average reward from all games"""
return sum(self._gameRewards) / len(self._gameRewards)
def prob_lose(self):
tlr = 0 # the times that you lose money
for everyreward in self._gameRewards:
if everyreward < 0:
tlr += 1
return tlr/len(self._gameRewards)
# run trail of 1000 games to calculate expected reward
games = SetOfGames(prob_head=0.5, n_games=1000)
# print all rewards
print('All reward:', games.get_all_reward())
# print the average reward
print('Expected reward when the probability of head is 0.5:', games.get_ave_reward())
#Problem 1:Draw the histogram of rewards in 1000 games with a fair coin
Fig.graph_histogram(
observations=games.get_all_reward(),
title='Histogram of Game Reward',
x_label='Reward($)',
y_label='Count')
# Answer for problem 1:
#the minimum and maximum reward that I expect to see is $-250 and $250
# Problem 2:Estimate the probability of losing money in this game
print('The probability of losing money in this game:',games.prob_lose()) |
18,887 | 953ce684746ee979795a6a347242ac157b9dd7f8 | """utils.py"""
# -*- coding: utf-8 -*-
import uuid
import hashlib
import json
from django.db import IntegrityError, transaction
from django.core.exceptions import ObjectDoesNotExist
from django.db.models import Q, Exists, OuterRef, Count
from notifications.signals import notify
from papersfeed import constants
from papersfeed.utils.base_utils import is_parameter_exists, get_results_from_queryset, ApiError
from papersfeed.utils.collections.utils import __get_collection_user_count
from papersfeed.models.users.user import User
from papersfeed.models.users.user_follow import UserFollow
from papersfeed.models.collections.collection import Collection
from papersfeed.models.collections.collection_user import CollectionUser, COLLECTION_USER_TYPE
def select_session(args):
"""Sign In"""
is_parameter_exists([
constants.EMAIL, constants.PASSWORD
], args)
# Email
email = args[constants.EMAIL]
# Password
password = args[constants.PASSWORD]
# Request
request = args[constants.REQUEST]
try:
user = User.objects.get(email=email)
except ObjectDoesNotExist:
raise ApiError(constants.NOT_EXIST_OBJECT)
else:
if not __is_correct_password(password, user):
raise ApiError(constants.AUTH_ERROR)
# Set Session Id
request.session[constants.ID] = user.id
users, _, _ = __get_users(Q(id=user.id), user, None)
if not users:
raise ApiError(constants.NOT_EXIST_OBJECT)
return users[0]
def delete_session(args):
"""Sign Out"""
# Request
request = args[constants.REQUEST]
try:
del request.session[constants.ID]
except KeyError:
pass
def select_me(args):
"""Get Current User"""
# Request User-
request_user = args[constants.USER] if constants.USER in args else None
# User ID
user_id = request_user.id
users, _, _ = __get_users(Q(id=user_id), request_user, None)
if not users:
raise ApiError(constants.NOT_EXIST_OBJECT)
return users[0]
def insert_user(args):
"""Insert New User"""
is_parameter_exists([
constants.EMAIL, constants.USERNAME, constants.PASSWORD
], args)
# # Request User
# request_user = args[constants.USER]
# Email
email = args[constants.EMAIL]
# User Name
username = args[constants.USERNAME]
# Password
password = args[constants.PASSWORD]
# Check parameters are valid
if not email or not username or not password:
raise ApiError(constants.PARAMETER_ERROR)
# Check username
if User.objects.filter(username=username).exists():
raise ApiError(constants.USERNAME_ALREADY_EXISTS)
# Check email
if User.objects.filter(email=email).exists():
raise ApiError(constants.EMAIL_ALREADY_EXISTS)
hashed, salt = __hash_password(password)
try:
user = User.objects.create_user(
description=None, email=email, username=username, password=hashed, salt=salt
)
except IntegrityError:
raise ApiError(constants.USERNAME_ALREADY_EXISTS)
users, _, _ = __get_users(Q(id=user.id), user, None)
if not users:
raise ApiError(constants.NOT_EXIST_OBJECT)
return users[0]
def update_user(args):
"""Update User"""
# User
user = args[constants.USER]
# Descrpition
description = args[constants.DESCRIPTION] if constants.DESCRIPTION in args else None
# Email
email = args[constants.EMAIL] if constants.EMAIL in args else None
# User Name
username = args[constants.USERNAME] if constants.USERNAME in args else None
# Password
password = args[constants.PASSWORD] if constants.PASSWORD in args else None
# User Photo Index
photo_index = args[constants.PHOTO_INDEX] if constants.PHOTO_INDEX in args else None
# Update Descrpition
if description is not None: #deleting description also should be supported
# Change Description
user.description = description
# Update Email
if email:
# Check email
if User.objects.filter(email=email).exists():
raise ApiError(constants.EMAIL_ALREADY_EXISTS)
# Change Email
user.email = email
# Update User Name
if username:
# Check username
if User.objects.filter(username=username).exists():
raise ApiError(constants.USERNAME_ALREADY_EXISTS)
# Change User Name
user.username = username
# Update Password
if password:
hashed, salt = __hash_password(password)
# Change Password
user.password = hashed
user.salt = salt
if photo_index is not None:
user.photoIndex = photo_index
user.save()
users, _, _ = __get_users(Q(id=user.id), user, None)
if not users:
raise ApiError(constants.NOT_EXIST_OBJECT)
return users[0]
def remove_user(args):
"""Resign"""
# Request User
request_user = args[constants.USER]
# Request
request = args[constants.REQUEST]
# Delete Session
try:
del request.session[constants.ID]
except KeyError:
pass
# Delete User
request_user.delete()
def select_user(args):
"""Get Single User"""
is_parameter_exists([
constants.ID
], args)
# Request User
request_user = args[constants.USER] if constants.USER in args else None
# User ID
user_id = args[constants.ID]
users, _, _ = __get_users(Q(id=user_id), request_user, None)
if not users:
raise ApiError(constants.NOT_EXIST_OBJECT)
return users[0]
def select_user_search(args):
"""Select User Search"""
is_parameter_exists([
constants.TEXT
], args)
# Request User
request_user = args[constants.USER]
# Search Keyword
keyword = args[constants.TEXT]
# Page Number
page_number = 1 if constants.PAGE_NUMBER not in args else int(args[constants.PAGE_NUMBER])
# User Queryset
queryset = User.objects.filter(Q(username__icontains=keyword)).values_list('id', flat=True)
total_count = queryset.count() # count whole users
# User Ids
user_ids = get_results_from_queryset(queryset, 10, page_number)
# is_finished
is_finished = not user_ids.has_next()
# Users
users, _, _ = __get_users(Q(id__in=user_ids), request_user, 10)
return users, page_number, is_finished, total_count
def select_user_following(args):
"""Select Users User is Following"""
is_parameter_exists([
constants.ID
], args)
# Request User
request_user = args[constants.USER]
# Requested User ID
requested_user_id = args[constants.ID]
# Page Number
page_number = 1 if constants.PAGE_NUMBER not in args else int(args[constants.PAGE_NUMBER])
# Check User Id
if not User.objects.filter(id=requested_user_id).exists():
raise ApiError(constants.NOT_EXIST_OBJECT)
# Following QuerySet
queryset = UserFollow.objects.filter(following_user=requested_user_id).values_list('followed_user', flat=True)
# User Ids
user_ids = get_results_from_queryset(queryset, 10, page_number)
# is_finished
is_finished = not user_ids.has_next()
# Filter Query
filter_query = Q(id__in=user_ids)
# Users
users, _, _ = __get_users(filter_query, request_user, 10)
return users, page_number, is_finished
def select_user_followed(args):
"""Select User’s Followers"""
is_parameter_exists([
constants.ID
], args)
# Request User
request_user = args[constants.USER]
# Requested User ID
requested_user_id = args[constants.ID]
# Page Number
page_number = 1 if constants.PAGE_NUMBER not in args else int(args[constants.PAGE_NUMBER])
# Check User Id
if not User.objects.filter(id=requested_user_id).exists():
raise ApiError(constants.NOT_EXIST_OBJECT)
# Follower QuerySet
queryset = UserFollow.objects.filter(followed_user=requested_user_id).values_list('following_user', flat=True)
# User Ids
user_ids = get_results_from_queryset(queryset, 10, page_number)
# is_finished
is_finished = not user_ids.has_next()
# Filter Query
filter_query = Q(id__in=user_ids)
# Users
users, _, _ = __get_users(filter_query, request_user, 10)
return users, page_number, is_finished
def get_users(filter_query, request_user, count):
"""Public Get Users"""
return __get_users(filter_query, request_user, count)
def insert_follow(args):
"""Insert Follow"""
is_parameter_exists([
constants.ID
], args)
# Followed User Id
followed_user_id = int(args[constants.ID])
# Following User
request_user = args[constants.USER]
following_user_id = request_user.id
# Self Follow
if followed_user_id == following_user_id:
raise ApiError(constants.UNPROCESSABLE_ENTITY)
# If Not Already Following, Create One
if not UserFollow.objects.filter(following_user_id=following_user_id, followed_user_id=followed_user_id).exists():
userfollow = UserFollow(following_user_id=following_user_id, followed_user_id=followed_user_id)
userfollow.save()
followed_user = User.objects.get(id=followed_user_id)
notify.send(
request_user,
recipient=[followed_user],
verb='started following you',
action_object=userfollow,
target=followed_user
)
follow_counts = __get_follower_count([followed_user_id], 'followed_user_id')
return {constants.FOLLOWER: follow_counts[followed_user_id] if followed_user_id in follow_counts else 0}
def remove_follow(args):
"""Remove Follow"""
is_parameter_exists([
constants.ID
], args)
# Followed User Id
followed_user_id = int(args[constants.ID])
# Following User
following_user_id = args[constants.USER].id
# Delete Existing Follow
UserFollow.objects.filter(following_user_id=following_user_id, followed_user_id=followed_user_id).delete()
follow_counts = __get_follower_count([followed_user_id], 'followed_user_id')
return {constants.FOLLOWER: follow_counts[followed_user_id] if followed_user_id in follow_counts else 0}
def select_user_collection(args):
"""Get Users of the given Collection"""
is_parameter_exists([
constants.ID
], args)
collection_id = args[constants.ID]
request_user = args[constants.USER]
# Decide if results include request_user if she or he is one of members
includes_me = True if constants.INCLUDES_ME not in args else json.loads(args[constants.INCLUDES_ME])
# Page Number
page_number = 1 if constants.PAGE_NUMBER not in args else int(args[constants.PAGE_NUMBER])
# Check Collection Id
if not Collection.objects.filter(id=collection_id).exists():
raise ApiError(constants.NOT_EXIST_OBJECT)
# Members QuerySet (except 'pending')
if includes_me:
query = Q(collection_id=collection_id) & ~Q(type=COLLECTION_USER_TYPE[2])
else:
query = Q(collection_id=collection_id) & ~Q(user_id=request_user.id) & ~Q(type=COLLECTION_USER_TYPE[2])
queryset = CollectionUser.objects.filter(query)
# Members(including owner) Of Collections
collection_members = get_results_from_queryset(queryset, 10, page_number)
# is_finished
is_finished = not collection_members.has_next()
# Member Ids
member_ids = [collection_member.user_id for collection_member in collection_members]
member_ids = list(set(member_ids))
# Get Members
params = {
constants.COLLECTION_ID: collection_id
}
members, _, _ = __get_users(Q(id__in=member_ids), request_user, 10, params=params)
return members, page_number, is_finished
def insert_user_collection(args):
"""Add Users(members) of the given Collection"""
is_parameter_exists([
constants.ID, constants.USER_IDS
], args)
collection_id = int(args[constants.ID])
user_ids = args[constants.USER_IDS]
request_user = args[constants.USER]
# Check Collection Id
try:
collection = Collection.objects.get(id=collection_id)
except ObjectDoesNotExist:
raise ApiError(constants.NOT_EXIST_OBJECT)
# Self Add
if request_user.id in user_ids:
raise ApiError(constants.UNPROCESSABLE_ENTITY)
# Add Users to Collection
for user_id in user_ids:
CollectionUser.objects.update_or_create(
collection_id=collection_id,
user_id=user_id,
type=COLLECTION_USER_TYPE[2], # pending until invitees accept
)
invited_users = User.objects.filter(Q(id__in=user_ids))
notify.send(
request_user,
recipient=invited_users,
verb='invited you to',
target=collection
)
# Get the number of Members(including owner) Of Collections
user_counts = __get_collection_user_count([collection_id], 'collection_id')
return {constants.USERS: user_counts[collection_id] if collection_id in user_counts else 0}
@transaction.atomic
def update_user_collection(args):
"""Transfer ownership of the Collection to the User"""
is_parameter_exists([
constants.ID, constants.USER_ID
], args)
collection_id = int(args[constants.ID])
user_id = args[constants.USER_ID]
request_user = args[constants.USER]
# Revoke ownership from request_user
try:
collection_user = CollectionUser.objects.get(collection_id=collection_id, user_id=request_user.id)
except ObjectDoesNotExist:
raise ApiError(constants.NOT_EXIST_OBJECT)
# if request_user is not owner, then raise AUTH_ERROR
if collection_user.type != COLLECTION_USER_TYPE[0]:
raise ApiError(constants.AUTH_ERROR)
collection_user.type = COLLECTION_USER_TYPE[1] # change to member
collection_user.save()
# Grant ownership to the user whose id is user_id
try:
collection_user = CollectionUser.objects.get(collection_id=collection_id, user_id=user_id)
except ObjectDoesNotExist:
raise ApiError(constants.NOT_EXIST_OBJECT)
collection_user.type = COLLECTION_USER_TYPE[0] # change to owner
collection_user.save()
def remove_user_collection(args):
"""Remove the Users from the Collection"""
is_parameter_exists([
constants.ID, constants.USER_IDS
], args)
collection_id = int(args[constants.ID])
user_ids = json.loads(args[constants.USER_IDS])
request_user = args[constants.USER]
# Check Collection Id
if not Collection.objects.filter(id=collection_id).exists():
raise ApiError(constants.NOT_EXIST_OBJECT)
# if request_user is not owner, then raise AUTH_ERROR
collection_user = CollectionUser.objects.get(collection_id=collection_id, user_id=request_user.id)
if collection_user.type != COLLECTION_USER_TYPE[0]:
raise ApiError(constants.AUTH_ERROR)
# the owner cannot delete himself or herself
# if the owner want to leave a collection, he or she must transfer it to other user
# or deleting the collection would be a solution
if request_user.id in user_ids:
raise ApiError(constants.UNPROCESSABLE_ENTITY)
CollectionUser.objects.filter(user_id__in=user_ids, collection_id=collection_id).delete()
# Get the number of Members(including owner) Of Collections
user_counts = __get_collection_user_count([collection_id], 'collection_id')
return {constants.USERS: user_counts[collection_id] if collection_id in user_counts else 0}
def remove_user_collection_self(args):
"""Leave the collection (member)"""
is_parameter_exists([
constants.ID
], args)
collection_id = int(args[constants.ID])
request_user = args[constants.USER]
# Check Collection Id
if not Collection.objects.filter(id=collection_id).exists():
raise ApiError(constants.NOT_EXIST_OBJECT)
try:
collection_user = CollectionUser.objects.get(collection_id=collection_id, user_id=request_user.id)
except ObjectDoesNotExist:
raise ApiError(constants.NOT_EXIST_OBJECT)
# if request_user is not member, then raise AUTH_ERROR
# the owner cannot delete himself or herself
# if the owner want to leave a collection, he or she must transfer it to other user
# or deleting the collection would be a solution
if collection_user.type != COLLECTION_USER_TYPE[1]:
raise ApiError(constants.AUTH_ERROR)
collection_user.delete()
# Get the number of Members(including owner) Of Collections
user_counts = __get_collection_user_count([collection_id], 'collection_id')
return {constants.USERS: user_counts[collection_id] if collection_id in user_counts else 0}
def update_user_collection_pending(args):
"""'pending' user accepts invitation"""
is_parameter_exists([
constants.ID
], args)
collection_id = int(args[constants.ID])
request_user = args[constants.USER]
# Check CollectionUser
try:
collection_user = CollectionUser.objects.get(collection_id=collection_id, user_id=request_user.id)
except ObjectDoesNotExist:
raise ApiError(constants.NOT_EXIST_OBJECT)
# Check Collection Id
if not Collection.objects.filter(id=collection_id).exists():
raise ApiError(constants.NOT_EXIST_OBJECT)
# if request_user is not 'pending', then raise AUTH_ERROR
if collection_user.type != COLLECTION_USER_TYPE[2]:
raise ApiError(constants.AUTH_ERROR)
collection_user.type = COLLECTION_USER_TYPE[1] # change to member
collection_user.save()
# Get the number of Members(including owner) Of Collections
user_counts = __get_collection_user_count([collection_id], 'collection_id')
return {constants.USERS: user_counts[collection_id] if collection_id in user_counts else 0}
def remove_user_collection_pending(args):
"""'pending' user dismisses invitation"""
is_parameter_exists([
constants.ID
], args)
collection_id = int(args[constants.ID])
request_user = args[constants.USER]
# Check Collection Id
if not Collection.objects.filter(id=collection_id).exists():
raise ApiError(constants.NOT_EXIST_OBJECT)
# Check CollectionUser
try:
collection_user = CollectionUser.objects.get(collection_id=collection_id, user_id=request_user.id)
except ObjectDoesNotExist:
raise ApiError(constants.NOT_EXIST_OBJECT)
# if request_user is not 'pending', then raise AUTH_ERROR
if collection_user.type != COLLECTION_USER_TYPE[2]:
raise ApiError(constants.AUTH_ERROR)
collection_user.delete()
def select_user_following_collection(args):
"""Get Following Users Not in Collection"""
is_parameter_exists([
constants.COLLECTION_ID
], args)
# Collection ID
collection_id = args[constants.COLLECTION_ID]
# Request User
request_user = args[constants.USER]
# Page Number
page_number = 1 if constants.PAGE_NUMBER not in args else int(args[constants.PAGE_NUMBER])
# QuerySet
queryset = UserFollow.objects.annotate(
is_in_collection=__is_in_collection('followed_user', collection_id)
).filter(
following_user=request_user.id,
is_in_collection=False
).values_list('followed_user', flat=True)
# User Ids
user_ids = get_results_from_queryset(queryset, 10, page_number)
# is_finished
is_finished = not user_ids.has_next()
# Filter Query
filter_query = Q(id__in=user_ids)
# Users
users, _, _ = __get_users(filter_query, request_user, 10)
return users, page_number, is_finished
def select_user_search_collection(args):
"""Search Users Not in Collection"""
is_parameter_exists([
constants.TEXT, constants.COLLECTION_ID
], args)
# Collection ID
collection_id = args[constants.COLLECTION_ID]
# Request User
request_user = args[constants.USER]
# Search Keyword
keyword = args[constants.TEXT]
# Page Number
page_number = 1 if constants.PAGE_NUMBER not in args else int(args[constants.PAGE_NUMBER])
# User Queryset
queryset = User.objects.annotate(
is_in_collection=__is_in_collection('id', collection_id)
).filter(
username__icontains=keyword,
is_in_collection=False
).values_list('id', flat=True)
# User Ids
user_ids = get_results_from_queryset(queryset, 10, page_number)
# is_finished
is_finished = not user_ids.has_next()
# Users
users, _, _ = __get_users(Q(id__in=user_ids), request_user, 10)
return users, page_number, is_finished
def __get_users(filter_query, request_user, count, params=None):
"""Get Users By Query"""
params = {} if params is None else params
collection_id = None if constants.COLLECTION_ID not in params else params[constants.COLLECTION_ID]
queryset = User.objects.filter(
filter_query
).annotate(
is_following=__is_following('id', request_user),
is_followed=__is_followed('id', request_user)
)
# FIXME: This function needs refactoring so that it works like that of collections/utils or reviews/utils
total_count = queryset.count() if constants.TOTAL_COUNT in params else None
users = get_results_from_queryset(queryset, count)
pagination_value = users[len(users) - 1].id if users else 0
users = __pack_users(users, request_user, collection_id=collection_id)
return users, pagination_value, total_count
def __pack_users(users, request_user, collection_id=None):
"""Pack User Info"""
packed = []
user_ids = [user.id for user in users]
# Follower Count
follower_counts = __get_follower_count(user_ids, 'followed_user_id')
# Following Count
following_counts = __get_following_count(user_ids, 'following_user_id')
for user in users:
user_id = user.id
packed_user = {
constants.ID: user_id,
constants.USERNAME: user.username,
constants.EMAIL: user.email,
constants.DESCRIPTION: user.description if user.description else '',
constants.PHOTO_INDEX: user.photoIndex,
constants.COUNT: {
constants.FOLLOWER: follower_counts[user_id] if user_id in follower_counts else 0,
constants.FOLLOWING: following_counts[user_id] if user_id in following_counts else 0
}
}
if request_user and user.id != request_user.id:
# 내 정보가 아니면 follow 관계 여부 추가
packed_user[constants.IS_FOLLOWED] = user.is_followed
packed_user[constants.IS_FOLLOWING] = user.is_following
if collection_id:
packed_user[constants.COLLECTION_USER_TYPE] = CollectionUser.objects.get(
user_id=user_id, collection_id=collection_id
).type
packed.append(packed_user)
return packed
def __is_in_collection(outer_ref, collection_id):
"""Check User in Collection"""
# NOTE: This function assume 'pending' users are members of the collection.
# So, 'pending' users don't appear on InviteToCollectionModal
return Exists(
CollectionUser.objects.filter(
user_id=OuterRef(outer_ref),
collection_id=collection_id
)
)
def __is_following(outer_ref, request_user):
"""Check User Following"""
return Exists(
UserFollow.objects.filter(
followed_user_id=OuterRef(outer_ref),
following_user_id=request_user.id if request_user else None
)
)
def __is_followed(outer_ref, request_user):
"""Check User Followed"""
return Exists(
UserFollow.objects.filter(
followed_user_id=request_user.id if request_user else None,
following_user_id=OuterRef(outer_ref)
)
)
def __get_follower_count(user_ids, group_by_field):
"""User Follower Count"""
followers = UserFollow.objects.filter(
Q(followed_user_id__in=user_ids)
).values(
group_by_field
).annotate(
follower_count=Count(group_by_field)
).order_by(
group_by_field
)
return {follower[group_by_field]: follower['follower_count'] for follower in followers}
def __get_following_count(user_ids, group_by_field):
"""User Following Count"""
followings = UserFollow.objects.filter(
Q(following_user_id__in=user_ids)
).values(
group_by_field
).annotate(
following_count=Count(group_by_field)
).order_by(
group_by_field
)
return {following[group_by_field]: following['following_count'] for following in followings}
def __hash_password(password):
"""Hash Password"""
salt = str(uuid.uuid4())
hashed_password = hashlib.sha256(salt.encode() + password.encode()).hexdigest()
return hashed_password, salt
# 비밀번호 확인
def __is_correct_password(password, user):
if user.salt is None:
raise ApiError(constants.AUTH_ERROR)
hashed_password = hashlib.sha256(user.salt.encode() + password.encode()).hexdigest()
return hashed_password == user.password
|
18,888 | 068ad64ba4426fec9b60e08eb582ae824a419b68 | """Example of the usage of EmotionsList"""
from examples.adt_realization.emotions_list import EmotionsList
print("File to train model:")
EMOTIONS_LIST = EmotionsList('NRC-Emotion-Intensity-Lexicon-v1.txt')
print(EMOTIONS_LIST.database)
print("\nTweet:")
TWEET = "I am very sad during the quarantine period"
EMOTIONS_LIST.set_tweet(TWEET)
print(EMOTIONS_LIST.tweet)
print("\nMain EMOTION of the TWEET:")
EMOTIONS_LIST.get_tweet_emotion()
print(EMOTIONS_LIST.emotions)
print("\nEmotions and their probabilities:")
EMOTIONS_LIST.get_emotions_probability()
print(EMOTIONS_LIST.probabilities)
|
18,889 | 682aecc21348feb99f04dcef433e1540bb18b0bd | from django.shortcuts import render, redirect, get_object_or_404
from django.contrib.auth import authenticate, login, logout
from django.contrib.auth.decorators import login_required
from .forms import signUpForm, EventForm, AddMemberForm, AddLocation
import requests
from datetime import datetime, date
from django.http import HttpResponse, HttpResponseRedirect, JsonResponse, Http404
from django.views import generic
from django.utils.safestring import mark_safe
from datetime import timedelta, date
import calendar
from django.contrib.auth.mixins import LoginRequiredMixin
from django.urls import reverse_lazy
from django.core.files.storage import FileSystemStorage
from django.contrib import messages
from .models import *
from .utils import Calendar
from django.forms.models import model_to_dict
from django.contrib.auth.forms import UserCreationForm
#the tag @login_required make it so that only logged user can access the view
@login_required
def indexView(request):
# the view collects infromation from multiple table, event and returns them to the user
user = CustomUser.objects.get(username= request.user)
today = datetime.today()
start_time = today.replace(hour=23, minute=59)
end_time = today.replace(hour=00, minute=1)
events = Event.objects.filter(user = user)
notes = Notes.objects.filter(user=user)
events_today = []
for event in events:
#filtering events to see which are active on the day
if event.start_time <= start_time and event.end_time >= end_time:
#adding event infromation in a dictionary
event_today = {
'event_id' : event.id,
'start_time': event.start_time,
'end_time' : event.end_time,
'content' : event.description,
'title': event.title
}
#appending created dictionary
events_today.append(event_today)
context = {
'events_today' : events_today,
'notes' : notes
}
return render(request, "index.html", context)
#homepage view
def homeView(request):
#check if user is authenticated
if request.user.is_authenticated:
#if true render index
return redirect("manCal:index")
#else render homepage
return render(request, 'home.html')
#login view
def loginView(request):
# Get username and password from request
username = request.POST['username']
password = request.POST['password']
# Authenticate the user, if it exist returns a user object, otherwise an None
user = authenticate(request, username=username, password=password)
# If user is authenticated
if user is not None:
# Save username and password to the session, plus loggedin variable set to True
request.session['username'] = username
request.session['password'] = password
context = {
'username': username,
'password': password,
'loggedin': True
}
response = render(request, 'index.html', context)
# Remember last login in cookie
now = D.datetime.utcnow()
max_age = 365 * 24 * 60 * 60 #one year
delta = now + D.timedelta(seconds=max_age)
format = "%a, %d-%b-%Y %H:%M:%S GMT"
expires = D.datetime.strftime(delta, format)
response.set_cookie('last_login',now,expires=expires)
#return response
return redirect("/index")
else:
Http404('Wrong credentials')
# If logged in, session variables are cleaned up and user logged out. Otherwise redirected to login page
@login_required
def logoutView(request):
logout(request)
#registration
def signUpView(request):
#checking if methos is POST
if request.method == "POST":
#getting from from request
form = signUpForm(request.POST)
#validateing from
if form.is_valid():
#if valid save and redirect to login with messege
form.save()
messages.success(request,"Registration Successful!")
return redirect("/login")
else:
#error
print('failed after falidation')
else:
#clean up form
form = signUpForm()
return render(request, "signup.html", {"form": form})
#view to updated account info
@login_required
def profileView(request):
#checking request methos
if request.method == 'POST':
#extracting form infromation form request and storing them in local variable
user = CustomUser.objects.get(username= request.user)
first_name = request.POST.get('first_name')
last_name = request.POST.get('last_name')
email = request.POST.get('email')
#updateding existing value with updated one
user.first_name= first_name
user.last_name = last_name
user.email=email
#save and redirect to same page
user.save()
return redirect("manCal:profile")
context = {
}
return render(request, "profile.html", context)
# start calendar render views
#get date for starting calendar date
def get_date(req_day):
if req_day:
year, month = (int(x) for x in req_day.split('-'))
return date(year, month, day=1)
return datetime.today()
#action to go prev month
def prev_month(d):
#changeing the day with which the calendar is started
first = d.replace(day=1)
prev_month = first - timedelta(days=1)
#coverting and formatting data for html
month = 'month=' + str(prev_month.year) + '-' + str(prev_month.month)
return month
##same as prev_month
def next_month(d):
days_in_month = calendar.monthrange(d.year, d.month)[1]
last = d.replace(day=days_in_month)
next_month = last + timedelta(days=1)
month = 'month=' + str(next_month.year) + '-' + str(next_month.month)
return month
#calendar genric list view
class CalendarView(LoginRequiredMixin, generic.ListView):
model = Event
#template to render
template_name = 'calendar.html'
#setting up context data
def get_context_data(self, **kwargs):
#supercalss call
context = super().get_context_data(**kwargs)
#getting date for calendar start
d = get_date(self.request.GET.get('month', None))
user = CustomUser.objects.get(username= self.request.user)
#pasing initializing variable for calendar
cal = Calendar(d.year, d.month, user)
html_cal = cal.formatmonth(withyear=True)
#getting user notes
notes = Notes.objects.filter(user=user)
#defining new context data
context['calendar'] = mark_safe(html_cal)
context['prev_month'] = prev_month(d)
context['next_month'] = next_month(d)
context['notes'] = notes
context['user']= user
return context
#create events
@login_required
def create_event(request):
form = EventForm(request.POST or None)
#checking if the request type is post and if the form is valid
if request.POST and form.is_valid():
#getting specific inputs from Django form and storing them in separated variable
title = form.cleaned_data['title']
description = form.cleaned_data['description']
start_time = form.cleaned_data['start_time']
end_time = form.cleaned_data['end_time']
location = form.cleaned_data['location']
#creating new event object
Event.objects.get_or_create(
user=request.user,
title=title,
description=description,
start_time=start_time,
end_time=end_time,
location= location
)
return HttpResponseRedirect(reverse('manCal:calendar'))
return render(request, 'event.html', {'form': form})
#generic update view for event edit
class EventEdit(LoginRequiredMixin, generic.UpdateView):
#In which model the data are stored
model = Event
#fields to update
fields = ['title', 'description', 'start_time', 'end_time', 'location']
#template to use to get data
template_name = 'event.html'
#generic delete vie for event delete
class EventDelete(LoginRequiredMixin, generic.DeleteView):
model = Event
template_name = 'event_delete.html'
success_url = reverse_lazy('manCal:calendar')
#overriding data in confermation form to provide cancel button
def post(self, request, *args, **kwargs):
if "cancel" in request.POST:
return redirect('manCal:calendar')
else:
return super(EventDelete, self).post(request, *args, **kwargs)
#event details view
@login_required
def event_details(request, event_id):
#locating event in database useing the event_id given in the url
event = Event.objects.get(id=event_id)
#getting members and files attached to the event
eventmember = EventMember.objects.filter(event=event)
eventfiles = EventFiles.objects.filter(event=event)
#defining variables for API call
API_KEY = 'AIzaSyDio4Zj99JOhP8SBQBM3CydIsc91ld-Jbs'
address = event.location
params = {
'key' : API_KEY,
'address': address
}
lat = 51.509865
lon = -0.118092
base_url = 'https://maps.googleapis.com/maps/api/geocode/json?'
#API response conteining geo-cordinates
response = requests.get(base_url, params=params).json()
#checking if the request was succesful
if response['status'] == 'OK':
geometry = response['results'][0]['geometry']
#obtaing latiture and longitude
lat = geometry['location']['lat']
lon = geometry['location']['lng']
context = {
#pasing retrived data to the template
'event': event,
'eventmember': eventmember,
'eventfiles': eventfiles,
'lat' : lat,
'lon' : lon,
}
return render(request, 'event-details.html', context)
#weather view
@login_required
def weatherView(request):
#API variable for weather API
url = 'http://api.openweathermap.org/data/2.5/onecall?lat={lat}&exclude=hourly,minutely&lon={lon}&units=metric&appid=dbd607d4b59f61a34125bf4f2a185f8d'
user = CustomUser.objects.get(username= request.user)
#API variable for google API
API_KEY = 'AIzaSyDio4Zj99JOhP8SBQBM3CydIsc91ld-Jbs'
base_url = 'https://maps.googleapis.com/maps/api/geocode/json?'
#chekc if the search form was submitted or the page was reloaded
if request.method == 'POST':
#if form submitted, get input from request
location = request.POST.get('location')
#check if location already exist
cityCount = Locations.objects.filter(user=user).filter(location = location).count()
form = AddLocation(request.POST)
#validateing from
if form.is_valid():
if cityCount == 0:
#if city does not exist in database
params = {
'key' : API_KEY,
'address': location
}
#check if the location exist useing google API
response_test = requests.get(base_url, params=params).json()
if response_test['status'] == 'OK':
#if exist save city in database
obj= form.save(commit=False)
obj.user = user
obj.save()
#should be simple params not weather becasue we are useing Google API
paramsWeather = {
'key' : API_KEY,
'address': obj.location
}
#getting location cord
response = requests.get(base_url, params=paramsWeather).json()
if response['status'] == 'OK':
#if infomation available
geometry = response['results'][0]['geometry']
lat = geometry['location']['lat']
lon = geometry['location']['lng']
#send request for weather information
r = requests.get(url.format(lat=lat, lon=lon)).json()
#adding info in dictionary
city_weather = {
'location_id' : obj.id,
'city' : obj.location,
'temperature' : round(r['current']['temp']),
'main' : r['daily'][0]['weather'][0]['main'],
'icon' : r['daily'][0]['weather'][0]['icon'],
'tempMax' : round(r['daily'][0]['temp']['max']),
'tempMin' : round(r['daily'][0]['temp']['min']),
}
#return dictionary to Ajax reqeust with JsonResponse
return JsonResponse({'city_weather' : city_weather, 'errorCode' : "200"}, status= 200)
else:
return JsonResponse({'error' : "Location not found", 'errorCode' : "500"}, status= 200)
elif cityCount > 0:
return JsonResponse({'error' : "Location already added", 'errorCode' : "500"}, status= 200)
return JsonResponse({'error' : "Invalid input", 'errorCode' : "500"}, status= 200)
form = AddLocation()
#if the page was loaded without from submittion
#get all weather location saved by the user
cities = Locations.objects.filter(user=user)
#create empty arrasy to store all weather data about each city
weather_data = []
#do the same thing as we did when a city was added for each city in the database
for city in cities:
params = {
'key' : API_KEY,
'address': city.location
}
response = requests.get(base_url, params=params).json()
if response['status'] == 'OK':
geometry = response['results'][0]['geometry']
#check if lat and lgn are obtained correctly
lat = geometry['location']['lat']
lon = geometry['location']['lng']
r = requests.get(url.format(lat=lat, lon=lon)).json()
city_weather = {
'location_id' : city.id,
'city' : city.location,
'temperature' : round(r['current']['temp']),
'main' : r['daily'][0]['weather'][0]['main'],
'icon' : r['daily'][0]['weather'][0]['icon'],
'tempMax' : round(r['daily'][0]['temp']['max']),
'tempMin' : round(r['daily'][0]['temp']['min']),
}
#append the data for the city to weather_data before passing to the next city
weather_data.append(city_weather)
context = {
'form' : form,
'weather_data' : weather_data,
}
return render(request, 'weather.html', context)
#add a member for an event
@login_required
def add_eventmember(request, event_id):
forms = AddMemberForm()
#check request method
if request.method == 'POST':
#if POST validate and sabe
forms = AddMemberForm(request.POST)
if forms.is_valid():
member = EventMember.objects.filter(event=event_id)
event = Event.objects.get(id=event_id)
#maximum 9 member for event
if member.count() <= 9:
#save meber
user = forms.cleaned_data['user']
EventMember.objects.create(
event=event,
user=user
)
return redirect('manCal:event-detail', event_id = event.id,)
else:
print('--------------User limit exceed!-----------------')
context = {
'form': forms
}
return render(request, 'add_member.html', context)
#delete member
@login_required
def member_delete(request, member_id):
#get member useing the member_id in the url
member = EventMember.objects.get(id= member_id)
#delete form database
member.delete()
#return succesfful response to Ajax request
return JsonResponse({'result' : 'ok'}, status=200)
#delete file, same process as delete member
@login_required
def file_delete(request, file_id):
file = EventFiles.objects.get(id = file_id)
file.delete()
return JsonResponse({'result' : 'ok'}, status=200)
#delete location, same process as delete member
@login_required
def location_delete(request, location_id):
location = Locations.objects.get(id = location_id)
location.delete()
return JsonResponse({'result' : 'ok'}, status=200)
#note delte same process as delete member
@login_required
def note_delete(request, note_id):
note= Notes.objects.get(id= note_id)
note.delete()
return JsonResponse({'result' : 'ok'}, status=200)
#add file for event view
@login_required
def add_files(request):
#getting the event to which we want to add file
event_id = request.POST.get('event_id')
event = Event.objects.get(id=event_id)
#list of the file to upload, this is a list becasue in the HTML form we allowed the user to select multiple files
files = request.FILES.getlist('files')
#looping throw all seleted files
for file in files:
fs= FileSystemStorage()
#saveing the file and getting the path to it
file_path = fs.save(file.name, file)
#creating new EventFiles object
sfile= EventFiles(event = event, files = file_path)
#saveing the object
sfile.save()
return redirect('manCal:event-detail', event_id = event_id,)
#create note
@login_required
def add_note(request):
#getting the user and the content of the note
if request.method == 'POST':
user = CustomUser.objects.get(username= request.user)
note = request.POST.get('note')
#createing new note
new_note = Notes.objects.create(
user = user,
note = note
)
#returning created object to Ajax request converting the model data to dictionary
return JsonResponse({'note' : model_to_dict(new_note)}, status=200)
#update note status
@login_required
def note_complited(request, note_id):
#getting note from note id
note = Notes.objects.get(id=note_id)
#changeing note staus
if note.complited == True:
note.complited = False
elif note.complited == False:
note.complited = True
#saveing new status
note.save()
#returning to ajax like in crete note
return JsonResponse({'note' : model_to_dict(note)}, status=200)
#exercise detail view
@login_required
def healthView(request):
user = CustomUser.objects.get(username= request.user)
#get exercise details if already created
if Exercise.objects.filter(user= user).exists():
exercise = Exercise.objects.get(user= user)
context = {
'exercise' : exercise
}
#passing data to template
return render(request, 'health.html', context)
#if not exist render without exercise data
return render(request, 'health.html')
#update exercise
@login_required
def addExercise(request):
if request.method == 'POST':
#get variable from post request
user = CustomUser.objects.get(username= request.user)
lunges_set = int(request.POST.get('Lunges_set'))
lunges_rep = int(request.POST.get('Lunges_rep'))
pushups_set = int(request.POST.get('Pushups_set'))
pushups_rep = int(request.POST.get('Pushups_rep'))
squats_set = int(request.POST.get('Squats_set'))
squats_rep = int(request.POST.get('Squats_rep'))
burpees_set = int(request.POST.get('Burpees_set'))
burpees_rep = int(request.POST.get('Burpees_rep'))
planks_set = int(request.POST.get('Planks_set'))
planks_rep = int(request.POST.get('Planks_rep'))
#if no previews data exsist, create new one
if not Exercise.objects.filter(user= user).exists():
Exercise.objects.create(
user= user,
Lunges_set = lunges_set,
Lunges_rep = lunges_rep,
Pushups_set = pushups_set,
Pushups_rep = pushups_rep,
Squats_set = squats_set,
Squats_rep = squats_rep,
Burpees_set = burpees_set,
Burpees_rep = burpees_rep,
Planks_set = planks_set,
Planks_rep = planks_rep
)
return redirect("manCal:health")
# if exist update existing dat
else:
exercise = Exercise.objects.get(user= user)
exercise.Lunges_set = lunges_set
exercise.Lunges_rep = lunges_rep
exercise.Pushups_set = pushups_set
exercise.Pushups_rep = pushups_rep
exercise.Squats_set = squats_set
exercise.Squats_rep = squats_rep
exercise.Burpees_set = burpees_set
exercise.Burpees_rep = burpees_rep
exercise.Planks_set = planks_set
exercise.Planks_rep = planks_rep
exercise.save()
return redirect("manCal:health")
|
18,890 | 5271467e75f99de6ae3732dfe4dbef82daf4892b | import logging
def medical_issue():
med = str(input("Do you had a medical condition?(Enter Y fro yes and N for no) : "))
print(med)
if med == 'y' or med =='Y':
print("You are allowed to give exams")
else:
print("You are not allowed to give exams")
def cal_attendancepercentage():
try:
totalDays = int(input("Please enter total number of days of classes : "))
daysAttended =int(input("Please enter number of days you atteneded classes : "))
percentage = daysAttended/float(totalDays) * 100
if percentage > 75:
print("Attandance percentage is {} .You are allowed to give exams".format(percentage))
else:
medical_issue()
except ValueError:
logging.error("Error")
print("Please enter a proper value")
cal_attendancepercentage()
|
18,891 | 351485deeec0ada458d9808ae3da2b7d8aec5321 | """
@author: Heerozh (Zhang Jianhao)
@copyright: Copyright 2019, Heerozh. All rights reserved.
@license: Apache 2.0
@email: heeroz@gmail.com
"""
import torch
import math
from .factor import CustomFactor, CrossSectionFactor
from .engine import OHLCV
from ..parallel import (linear_regression_1d, quantile, pearsonr, masked_mean, masked_sum,
nanmean, nanstd)
class StandardDeviation(CustomFactor):
inputs = [OHLCV.close]
_min_win = 2
def compute(self, data):
return data.nanstd()
class RollingHigh(CustomFactor):
inputs = (OHLCV.close,)
win = 5
_min_win = 2
def compute(self, data):
return data.nanmax()
class RollingLow(CustomFactor):
inputs = (OHLCV.close,)
win = 5
_min_win = 2
def compute(self, data):
return data.nanmin()
class RollingLinearRegression(CustomFactor):
_min_win = 2
def __init__(self, win, x, y):
super().__init__(win=win, inputs=[x, y])
def compute(self, x, y):
def lin_reg(_y, _x=None):
if _x is None:
_x = torch.arange(_y.shape[2], device=_y.device, dtype=_y.dtype)
_x = _x.repeat(_y.shape[0], _y.shape[1], 1)
m, b = linear_regression_1d(_x, _y, dim=2)
return torch.cat([m.unsqueeze(-1), b.unsqueeze(-1)], dim=-1)
if x is None:
return y.agg(lin_reg)
else:
return y.agg(lin_reg, y)
@property
def coef(self):
return self[0]
@property
def intercept(self):
return self[1]
class RollingMomentum(CustomFactor):
inputs = (OHLCV.close,)
win = 20
_min_win = 2
def compute(self, prices):
def polynomial_reg(_y):
x = torch.arange(_y.shape[2], device=_y.device, dtype=_y.dtype)
ones = torch.ones(x.shape[0], device=_y.device, dtype=_y.dtype)
x = torch.stack([ones, x, x ** 2]).T.repeat(_y.shape[0], _y.shape[1], 1, 1)
xt = x.transpose(-2, -1)
ret = (xt @ x).inverse() @ xt @ _y.unsqueeze(-1)
return ret.squeeze(-1)
return prices.agg(polynomial_reg)
@property
def gain(self):
"""gain>0 means stock gaining, otherwise is losing."""
return self[1]
@property
def accelerate(self):
"""accelerate>0 means stock accelerating, otherwise is decelerating."""
return self[2]
@property
def intercept(self):
return self[0]
class RollingQuantile(CustomFactor):
inputs = (OHLCV.close, 5)
_min_win = 2
def compute(self, data, bins):
def _quantile(_data):
return quantile(_data, bins, dim=2)[:, :, -1]
return data.agg(_quantile)
class HalfLifeMeanReversion(CustomFactor):
_min_win = 2
def __init__(self, win, data, mean, mask=None):
lag = data.shift(1) - mean
diff = data - data.shift(1)
lag.set_mask(mask)
diff.set_mask(mask)
super().__init__(win=win, inputs=[lag, diff, math.log(2)])
def compute(self, lag, diff, ln2):
def calc_h(_x, _y):
_lambda, _ = linear_regression_1d(_x, _y, dim=2)
return -ln2 / _lambda
return lag.agg(calc_h, diff)
class RollingCorrelation(CustomFactor):
_min_win = 2
def compute(self, x, y):
def _corr(_x, _y):
return pearsonr(_x, _y, dim=2, ddof=1)
return x.agg(_corr, y)
class InformationCoefficient(CrossSectionFactor):
def __init__(self, x, y, mask=None):
super().__init__(win=1, inputs=[x, y], mask=mask)
def compute(self, x, y):
ic = pearsonr(x, y, dim=1, ddof=1)
return ic.unsqueeze(-1).repeat(1, y.shape[1])
def to_ir(self, win):
class RollingIC2IR(CustomFactor):
def compute(self, ic):
def _to_ir(_ic):
# Fundamental Law of Active Management: ir = ic * sqrt(b), 1/sqrt(b) = std(ic)
return nanmean(_ic, dim=2) / nanstd(_ic, dim=2, ddof=1)
return ic.agg(_to_ir)
return RollingIC2IR(win=win, inputs=[self])
class CrossSectionR2(CrossSectionFactor):
def __init__(self, y_hat, y, mask=None):
super().__init__(win=1, inputs=[y_hat, y], mask=mask)
def compute(self, y_hat, y):
mask = torch.isnan(y_hat) | torch.isnan(y)
y_bar = masked_mean(y, mask, dim=1).unsqueeze(-1)
ss_tot = masked_sum((y - y_bar) ** 2, mask, dim=1)
ss_reg = masked_sum((y_hat - y_bar) ** 2, mask, dim=1)
return (ss_reg / ss_tot).unsqueeze(-1).repeat(1, y.shape[1])
STDDEV = StandardDeviation
MAX = RollingHigh
MIN = RollingLow
|
18,892 | be31a2955d76bedccc372b7c6dcbe981fe597210 | import numpy as np
import scipy.integrate as integrate
from math import sin, cos
class LTI:
def __init__(self, state_0):
""" pos = [x,y,z] attitude = [rool,pitch,yaw]
"""
self.state = state_0
self.s_dot = 0
self.hist = []
self.time = 0.0
control_frequency = 200 # Hz for attitude control loop
self.dt = 1.0 / control_frequency
self.desired_state = 0
def reset(self):
self.state = np.random.rand() - 0.5
self.desired_state = np.random.rand()*2 - 1
self.hist = []
return self.state
def state_dot(self, state, t, u, time):
x1 = state
b = 1
a = 1
self.s_dot = 0.0
#d =0.014*sin(time*5)
self.s_dot = -a*x1 + b*u
return self.s_dot
def reward(self,desired_state,u):
return -10*(self.state - desired_state)**2 - 0.5*u**2
def update(self, u):
#saturate u
u = np.clip(u,-10,10)
out = integrate.odeint(self.state_dot, self.state, [0,self.dt], args = (u,self.time))
self.time += self.dt
#print out
self.state = out[1]
self.hist.append(np.array(self.state[0]))
def step(self, action):
done = False
#action = agent.do_action(env.state)
self.update(self.desired_state - action)
reward = self.reward(self.desired_state, action)
if abs(self.state) > 3 or abs(self.s_dot)>50:
done = True
return self.state[0], reward, done, {}
|
18,893 | e0fdd7d60b1682e544a5656971fcba236cc7f5e4 | from django.db import models
# Create your models here.
class intro(models.Model):
name=models.CharField(max_length=50,blank=True, null=True)
img=models.ImageField(blank=True, null=True)
twitter=models.URLField(max_length=200,blank=True, null=True)
facebook=models.URLField(max_length=200,blank=True, null=True)
instagram=models.URLField(max_length=200,blank=True, null=True)
telegram=models.URLField(max_length=200,blank=True, null=True)
git=models.URLField(max_length=200,blank=True, null=True)
linkedin=models.URLField(max_length=200,blank=True, null=True)
class basic(models.Model):
name = models.CharField(max_length=50, blank=True, null=True)
title = models.CharField(max_length=200, blank=True, null=True)
address = models.CharField(max_length=100, blank=True, null=True)
mobile = models.IntegerField(blank=True, null=True)
email = models.EmailField(max_length=254, blank=True, null=True)
def __str__(self):
return self.name
class education(models.Model):
edutitle = models.CharField(max_length=100, blank=True, null=True)
eduDateTo = models.DateField(blank=True, null=True)
eduDateFrom = models.DateField(blank=True, null=True)
eduFrom = models.CharField(max_length=100, blank=True, null=True)
eduDis = models.CharField(max_length=250, blank=True, null=True)
def __str__(self):
return self.edutitle
class experiance(models.Model):
title = models.CharField(max_length=100, blank=True, null=True)
date = models.DateField(blank=True, null=True)
state = models.CharField(max_length=50, blank=True, null=True)
country = models.CharField(max_length=50, blank=True, null=True)
dis1 = models.CharField(max_length=200, blank=True, null=True)
dis2 = models.CharField(max_length=200, blank=True, null=True)
dis3 = models.CharField(max_length=200, blank=True, null=True)
dis4 = models.CharField(max_length=200, blank=True, null=True)
def __str__(self):
return self.title
class category(models.Model):
name = models.CharField(max_length=50, blank=True, null=True)
def __str__(self):
return self.name
class product(models.Model):
cat=models.ForeignKey(category, on_delete=models.CASCADE)
img=models.ImageField(blank=True, null=True)
title=models.CharField(max_length=50,blank=True, null=True)
subtitle=models.CharField(max_length=50,blank=True, null=True)
link=models.URLField(max_length=200,blank=True, null=True)
def __str__(self):
return self.title + '---' + str(self.cat.name)
class about(models.Model):
head=models.CharField(max_length=50,blank=True, null=True)
img=models.ImageField(blank=True, null=True)
s_Intro=models.CharField(max_length=150,blank=True, null=True)
dob=models.DateField(blank=True, null=True)
website=models.URLField(max_length=200,blank=True, null=True)
mobile=models.IntegerField(blank=True, null=True)
city=models.CharField(max_length=50,blank=True, null=True)
age=models.IntegerField(blank=True, null=True)
degree=models.CharField(max_length=50,blank=True, null=True)
email=models.EmailField(max_length=254,blank=True, null=True)
country=models.CharField(max_length=50,blank=True, null=True)
introduction=models.CharField(max_length=500,blank=True, null=True)
freelance=models.BooleanField(blank=True, null=True)
avail=models.BooleanField(blank=True, null=True)
def __str__(self):
return self.head
class testimonial(models.Model):
img=models.ImageField(blank=True, null=True)
name=models.CharField(max_length=50,blank=True, null=True)
designation=models.CharField( max_length=50,blank=True, null=True)
comments=models.TextField(blank=True, null=True)
def __str__(self):
return self.name
class services(models.Model):
icon=models.CharField(max_length=50,blank=True, null=True)
title=models.CharField(max_length=50,blank=True, null=True)
caption=models.TextField(blank=True, null=True)
color=models.CharField(max_length=50,blank=True, null=True)
def __str__(self):
return self.title
class contact(models.Model):
name=models.CharField(max_length=50,blank=True, null=True)
email=models.EmailField(max_length=254,blank=True, null=True)
subject=models.CharField(max_length=100,blank=True, null=True)
message=models.CharField(max_length=150,blank=True, null=True)
def __str__(self):
return self.name + '-----' + self.email
|
18,894 | f005d7aedf6cd214ca668232e05769d8dd99e4e4 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import serial
import rospy
import readchar
import math
from sensor_msgs.msg import *
from geometry_msgs.msg import Twist
ser=serial.Serial(
port = '/dev/vsrc',
baudrate = 115200,
parity = serial.PARITY_NONE,
bytesize = serial.EIGHTBITS,
stopbits = serial.STOPBITS_ONE,
timeout = None,
xonxoff = 0,
rtscts = 0,
# interCharTimeout = None
)
#グローバル関数
L_motion_deg = 0
R_motion_deg = 0
####初期設定################################################################################################
def first_set():
print "[First_set]"
print "<pose_init>"
ser.write("@00c8:T8000:T8000:T8000:T0000:T8000:T8000:T8000:T8000:T8000:T8000:T8000:T8000:T8000::::::T8000:T8000:T6800:T9800:T6800:T9800:T8000:T8000:T9800:T6800:T9800:T6800\n")
print ser.readline(),
rospy.sleep(1)
print "<R>"
ser.write("R\n")
print ser.readline(),
rospy.sleep(1)
print "<get_enc>"
ser.write(":Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx::::::T8000:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx:T8000:Cxxxx:Cxxxx:Cxxxx:Cxxxx:Cxxxx\n");
print ser.readline(),
rospy.sleep(1)
print "<gain_on>"
ser.write(":P0100:P0100:P0040:P0080:P0045:P0040:P0040:P0080:P0045:P0040:P0080:P0200:P0016::::::P0001:P0001:P0001:P0001:P0001:P0001:P0001:P0001:P0001:P0001:P0001:P0001\n")
print ser.readline(),
rospy.sleep(1)
####cul_motion##############################################################################################
def cul_wheel(vel,ang):
global L_motion_deg
global R_motion_deg
motion = [0]*3
motion_in = 0
time = 0.1
#単位時間あたりの移動距離
print "vel:",+vel #vel:速度[m/s]
print "ang:",+ang #ang:角速度[rad/s]
print "time:",+time #time:単位時間[s]
motion_in = vel * 10 #translate 'm' to 'cm'
motion_ang = (ang * 180 /math.pi) * 0.35 #0.35は回転1度あたりの定数（要調整）
print "motion_in:",+motion_in
#モーションの計算
if ang == 0: #前後直進
L_motion_deg += motion_in
R_motion_deg += motion_in
elif ang < 0: #右回転
L_motion_deg += motion_in
L_motion_deg -= motion_ang
R_motion_deg += motion_in
R_motion_deg += motion_ang
elif ang > 0: #左回転
L_motion_deg += motion_in
L_motion_deg -= motion_ang
R_motion_deg += motion_in
R_motion_deg += motion_ang
#初期化
motion_in = 0
vel = 0
print L_motion_deg
print R_motion_deg
#10→16進
motion[0] = '%04x' %(time * 40)
motion[1] = '%x' %(32768 + L_motion_deg * 44)
motion[2] = '%x' %(32768 - R_motion_deg * 44)
return motion
####callback########################################################################################################
def callback(cmd_vel):
#0の時は何もしない
if cmd_vel.linear.x == 0 and cmd_vel.angular.z == 0:
return
#速度から距離とモーションタイムを計算
motion = cul_wheel(cmd_vel.linear.x,cmd_vel.angular.z)
#モーションの送信
print "[MOTION_SEND]"
print motion
ser.write("@"+motion[0]+":T"+motion[1]+":T"+motion[2]+":T8000:T0000:T8000:T8000:T8000:T8000:T8000:T8000:T8000:T8000:T8000::::::T8000:T8000:T6800:T9800:T6800:T9800:T8000:T8000:T9800:T6800:T9800:T6800\n")
print ser.readline(),
rospy.sleep(0.1)
return
####メイン関数###############################################################################################
if __name__ == '__main__':
#初期設定
first_set()
print "If you want to end this program, push 'ctrlC' and next 'q' key!"
while True:
#cmd_velの読み込み
rospy.init_node('sobit_telecon', anonymous=True)
sub = rospy.Subscriber('cmd_vel_mux/input/teleop', Twist, callback)
rospy.spin()
#キー入力(q)で終了
kb = readchar.readchar()
if kb == "q":
print("[exit program]")
print "<pose_init>"
ser.write("@00c8:T8000:T8000:T8000:T0000:T8000:T8000:T8000:T8000:T8000:T8000:T8000:T8000:T8000::::::T8000:T8000:T6800:T9800:T6800:T9800:T8000:T8000:T9800:T6800:T9800:T6800\n")
print ser.readline(),
rospy.sleep(3)
print "<gain_off>"
ser.write("P0000\n")
print ser.readline(),
break
|
18,895 | dd6bd46a30bcb773fa9fe1b249d715190a6171ef | from puzzle import Puzzle
class WordLadderPuzzle(Puzzle):
"""
A word-ladder puzzle that may be solved, unsolved, or even unsolvable.
"""
def __init__(self, from_word, to_word, ws):
"""
Create a new word-ladder puzzle with the aim of stepping
from from_word to to_word using words in ws, changing one
character at each step.
@type from_word: str
@type to_word: str
@type ws: set[str]
@rtype: None
"""
(self._from_word, self._to_word, self._word_set) = (from_word,
to_word, ws)
# set of characters to use for 1-character changes
self._chars = "abcdefghijklmnopqrstuvwxyz"
# implement __eq__ and __str__
# __repr__ is up to you
def __str__(self):
"""
Return a human-readable string representation of WordLadderPuzzle self.
>>> word_set = {'came', 'case', 'cast', 'cost'}
>>> s = WordLadderPuzzle("same", "cost", word_set)
>>> print(s)
same
"""
return self._from_word
def __eq__(self, other):
"""
Return whether WordLadderPuzzle self is equivalent to other
@param self: WordLadderPuzzle
@param other: WordLadderPuzzle | Any
@rtype: bool
>>> word_set = {'came', 'case', 'cast', 'cost'}
>>> s = WordLadderPuzzle("same", "cost", word_set)
>>> s2 = WordLadderPuzzle("same", "cost", word_set)
>>> s == s2
True
>>> s3 = WordLadderPuzzle("cost", "same", word_set)
>>> s == s3
False
"""
return isinstance(other, WordLadderPuzzle) and (self._from_word ==
other._from_word and
self._to_word ==
other._to_word)
# override extensions
# legal extensions are WordLadderPuzzles that have a from_word that can
# be reached from this one by changing a single letter to one of those
# in self._chars
def extensions(self):
"""
Return list of extensions of WordLadderPuzzle self.
@type self: WordLadderPuzzle
@rtype: list[WordLadderPuzzle]
>>> word_set = {'came', 'case', 'cast', 'cost'}
>>> s = WordLadderPuzzle("same", "cost", word_set)
>>> s2 = WordLadderPuzzle("came", "cost", {'case', 'cast', 'cost'})
>>> s2 in s.extensions()
True
>>> s3 = WordLadderPuzzle("same", "cost", set())
>>> s3.extensions() is None
True
"""
if len(self._word_set) == 0:
return None
else:
filtered_words = self._filter_len()
usable_words = self._usable_word(filtered_words)
extensions = []
for word in usable_words:
new_copy = filtered_words.copy()
new_copy.discard(word)
extensions.append(WordLadderPuzzle(word, self._to_word,
new_copy))
return extensions
# override is_solved
# this WordLadderPuzzle is solved when _from_word is the same as
# _to_word
def is_solved(self):
"""
Return whether WordLadderPuzzle self is solved.
@type self: WordLadderPuzzle
@rtype: bool
>>> word_set = {'came', 'case', 'cast', 'cost'}
>>> s = WordLadderPuzzle("cost", "cost", word_set)
>>> s.is_solved()
True
>>> s2 = WordLadderPuzzle("same", "cost", word_set)
>>> s2.is_solved()
False
"""
return self._from_word == self._to_word
# Helper Methods
def _usable_word(self, filtered_words):
"""
Return a set of words that have only a 1 letter difference from
self._from_word.
@type filtered_words: set{str}
@type self: WordLadderPuzzle
@rtype: set{str}
"""
usable = set()
for word in filtered_words:
counter = 0
for x in range(0, len(self._to_word)):
if word[x] == self._from_word[x]:
counter += 1
if counter == len(self._to_word) - 1:
usable.add(word)
return usable
def _filter_len(self):
"""
Return a set of words that have the same length as self.to_word
@type self: WordLadderPuzzle
@rtype: set{str}
"""
if max([len(x) for x in self._word_set]) == len(self._to_word):
return self._word_set
else:
new_words = set()
for word in self._word_set:
if len(self._from_word) == len(word):
new_words.add(word)
return new_words
if __name__ == '__main__':
import doctest
doctest.testmod()
from puzzle_tools import breadth_first_solve, depth_first_solve
from time import time
with open("words", "r") as words:
word_set = set(words.read().split())
w = WordLadderPuzzle("same", "cost", word_set)
start = time()
sol = breadth_first_solve(w)
end = time()
print("Solving word ladder from same->cost")
print("...using breadth-first-search")
print("Solutions: {} took {} seconds.".format(sol, end - start))
start = time()
sol = depth_first_solve(w)
end = time()
print("Solving word ladder from same->cost")
print("...using depth-first-search")
print("Solutions: {} took {} seconds.".format(sol, end - start))
|
18,896 | d8efdefcfe5697a302a68107dad48b479c51b4de | # -*- coding: utf-8 -*-
# The above line is for turkish characters in comments, unless it is there a encoding error is raised in the server
from .. import ManagerType, PageType
from .. import logger
import datetime
class BaseRowScrapper:
test_model = ''
page_type = ''
def __init__(self, html_row):
self.row = html_row
def get(self):
model = self.page_type.model()
# Jockey, owner and trainer's have their id's just like the horse's own id. We are only interested in their
# ids so we don't bother to get their names
model.jockey_id = self.get_manager_id(ManagerType.Jockey)
model.owner_id = self.get_manager_id(ManagerType.Owner)
model.trainer_id = self.get_manager_id(ManagerType.Trainer)
return model
def get_manager_id(self, _type):
"""
:param _type: The content of the column where the according type of manager is
:return: id of the desired manager either Jockey, Owner or Trainer
"""
pass
@staticmethod
def get_id_from_a(a):
""""
The url's contain the id, after the phrase Id=
:param a: The html code of a tag
:return: id of the supplied a tag
"""
if a:
# We split from that and take the rest
id_ = a['href'].split("Id=")[1]
# We split one more time in case of there is more after the id
# We take the first part this time
id_ = id_.split("&")[0]
return id_
class BaseRaceDayRowScrapper(BaseRowScrapper):
"""
Class name used for horses' name in TJK's site, after "gunluk-GunlukYarisProgrami-"
Ex: <td class="gunluk-GunlukYarisProgrami-AtAdi">
"""
horse_name_class_name = ''
"""
Beginning of the class name used for each row in the tables, Fixture and Result tables has it differently
Ex for fixture: <td class="gunluk-GunlukYarisProgrami-AtAdi">
Ex for result: <td class="gunluk-GunlukYarisSonuclari-AtAdi3">
"""
td_class_base = ''
def get(self):
model = super(BaseRaceDayRowScrapper, self).get()
# The third column in the table contains the name of the horse and a link that goes to that horse's page.
# Also the link will have the id of the horse and the abbreviations that come after the name which tells
# status information, for example whether the horse will run with an eye patch and etc.
# More info is here: http://www.tjk.org/TR/YarisSever/Static/Page/Kisaltmalar
horse_name_html = self.get_column(self.horse_name_class_name).find('a')
# first element is the name it self, others are the abbreviations, so we get the first and assign it as name
model.horse_name = str(horse_name_html.contents[0]).replace(" ", '')
# Now get the id of the horse from that url
model.horse_id = int(self.get_id_from_a(horse_name_html))
# Get the model of the horse from the fourth column
model.horse_age = self.get_column_content("Yas")
# Horses father and mother are combined in a single column in separate <a> So we find all the <a> in the
# column and only get their id's from respected links. Father is the first, mother is the second
parent_links = self.get_column("Baba").find_all('a', href=True)
# Process the father
model.horse_father_id = int(self.get_id_from_a(parent_links[0]))
# Process the mother
model.horse_mother_id = int(self.get_id_from_a(parent_links[1]))
# Get the weight of the horse during the time of the race
model.horse_weight = self.get_column_content("Kilo")
return model
def get_manager_id(self, _type):
"""
:param _type: The content of the column where the according type of manager is
:return: id of the desired manager either Jockey, Owner or Trainer
"""
try:
# Sometimes the info is not there, so we have to be safe
return int(self.get_id_from_a(self.get_column(_type.value).find('a', href=True)))
except:
# Info is not there, mark it as missing
return -1
def get_column(self, col_name):
"""
:param col_name: The value after the gunluk-GunlukYarisSonuclari-{0}
:return: The content in the column(td) that has a class name starting with gunluk-GunlukYarisSonuclari-
"""
return self.row.find("td", class_="{0}{1}".format(self.td_class_base, col_name))
def get_column_content(self, col_name):
"""
Striped_strings property returns a collection containing the values. Then ve do a string join to have the
actual value in the tag. The value might me missing, then we simply return -1 to indicate that it is missing.
:param col_name: The value after the gunluk-GunlukYarisSonuclari-{0}
:return: The content in the column(td) that has a class name starting with gunluk-GunlukYarisSonuclari-
"""
column = self.get_column(col_name)
return "".join(column.stripped_strings if column else '-1')
class FixtureRowScrapper(BaseRaceDayRowScrapper):
"""
Ex: <td class="gunluk-GunlukYarisProgrami-AtAdi">
"""
horse_name_class_name = "AtAdi"
td_class_base = 'gunluk-GunlukYarisProgrami-'
page_type = PageType.Fixture
def get(self):
fixture = super(FixtureRowScrapper, self).get()
fixture.order = int(self.get_column_content('SiraId'))
return fixture
class ResultRowScrapper(BaseRaceDayRowScrapper):
"""
Ex: <td class="gunluk-GunlukYarisProgrami-AtAdi3">
"""
horse_name_class_name = "AtAdi3"
td_class_base = 'gunluk-GunlukYarisSonuclari-'
page_type = PageType.Result
def get(self):
result = super(ResultRowScrapper, self).get()
# Horses name still has the order that horse started the race in the first place.
# Example "KARAHİNDİBAYA (7)"
horse_name_and_order = result.horse_name.split("(")
result.horse_name = str(horse_name_and_order[0])
# Example after split: "7)"
result.order = int(horse_name_and_order[1].replace(')', ''))
# Get the result of the horse from the second column
result.result = self.get_column_content("SONUCNO")
# Horses sometimes may not run
# Horses might not run that race or cannot finish it for various reasons. In that case what we get is an
# empty string, we mark it as -1 if that happens
if not result.result:
result.result = -1
else:
result.result = int(result.result)
# Get the time that it took horse to run this race
result.time = self.get_column_content("Derece")
# Hc and Hk are two different handicap types that is possible
result.handicap = int(self.get_column_content("Hc") or self.get_column_content("Hk"))
return result
class HorseRowScrapper(BaseRowScrapper):
page_type = PageType.Horse
def __init__(self, html_row):
super(HorseRowScrapper, self).__init__(html_row)
# Most of the columns do not have classes, we get all columns and assign each by hard-coding indexes
self.columns = self.row.find_all("td")
def get(self):
model = super(HorseRowScrapper, self).get()
date_and_race_id = self.columns[0]
model.race_date = datetime.datetime.strptime(date_and_race_id.text, '\n%d.%m.%Y ')
try:
race_url = date_and_race_id.find('a', href=True)['href']
# Race id is after the only hash-tag
# Ex: /TR/YarisSever/Info/Page/GunlukYarisSonuclari?QueryParameter_Tarih=04/08/2017#111471
# Split by hash-tag and get the second
model.race_id = race_url.split('#')[1]
except TypeError:
# Some results don't have the races linked to them, so we mark it as missing
model.race_id = -1
model.city = str(self.get_column(1))
model.distance = self.get_column(2)
model.track_type = str(self.get_column(3))
model.result = self.get_column(4)
model.time = str(self.get_column(5))
model.horse_weight = str(self.get_column(6))
model.handicap = self.get_column(14)
return model
def get_manager_id(self, _type):
"""
:param _type: The content of the column where the according type of manager is
:return: id of the desired manager either Jockey, Owner or Trainer
"""
index = 0
if _type is ManagerType.Jockey:
index = 7
elif _type is ManagerType.Trainer:
index = 12
elif _type is ManagerType.Owner:
index = 13
else:
raise Exception("Manager type not recognized!")
try:
return self.get_id_from_a(self.columns[index].find('a', href=True))
except:
raise Exception(self.row)
def get_column(self, index):
column = self.columns[index].stripped_strings
for col in column:
return col
return -1
|
18,897 | c3aac2690a4d31c71123cc24c6d1731aa4c9dcb2 | from collections import Counter
from document_stats.algorithms import preprocessingHelper
doc_1 = 'Convolutional Neural Networks are very similar to ordinary Neural Networks from the previous chapter'
doc_2 = 'Convolutional Neural Networks take advantage of the fact that the input consists of images and they constrain the architecture in a more sensible way.'
doc_3 = 'In particular, unlike a regular Neural Network, the layers of a ConvNet have neurons arranged in 3 dimensions: width, height, depth.'
doc_4 = "saf saofjıosafıjsa fkjdsjfdjlf gıosdılgkdslgkd saf saf elli altmış elli altmış elli altmış elli altmış elli altmış elli altmış elli altmış elli altmış elli elli elli"
docs = [doc_1, doc_2, doc_3, doc_4]
def frequency(corpus, n_most, useStopwords):
list_of_frequency = []
txt = ""
for i in corpus:
txt += i
txt += " "
if useStopwords == True:
txt = preprocessingHelper.preprocessing(txt)
else:
txt = preprocessingHelper.preprocessing(txt, False)
most_occur = Counter(txt).most_common(n_most)
list_of_frequency.append(most_occur)
return list_of_frequency
#print(frequency(docs,6, False))
def frequencySep(corpus, n_most, useStopwords):
if useStopwords == True:
corpus = preprocessingHelper.alldocclean_(corpus)
else:
corpus = preprocessingHelper.alldocclean_(corpus, False)
split_list = list(map(str.split, corpus))
list_of_frequency = []
for sample in split_list:
most_occur = Counter(sample).most_common(n_most)
list_of_frequency.append(most_occur)
return list_of_frequency
#print(frequencySep(docs, 5, True))
|
18,898 | ab75ea86edb27961288bad5764d2e2a44370d087 | product = [2,]
power = 1
while power < 1000:
insert = False
for n in range(len(product)):
if n == 0 and product[n] > 4:
product[n] = int(str(product[n] * 2)[1])
insert = True
elif product[n] > 4:
product[n] = int(str(product[n]*2)[1])
product[n-1] = product[n-1] + 1
else:
product[n] = product[n]*2
if insert:
product.insert(0,1)
power += 1
answer = 0
for digit in product:
answer += digit
print answer
|
18,899 | c99633a3202076abe0e306ce0421cbb760322706 | import glob
import matplotlib.pyplot as plt
from statistics import median, mean
colours = ['r','c','b','m','k']
number = []
orfbin = []
orf_stat = []
bins = [x*1000 for x in range(1,16)]
for filename in glob.glob("??.*orf_coords"):
no = filename[:2]
number.append(no)
orf_sub_bin = []
with open(filename, 'r') as fr:
fr = fr.read().splitlines()
for line in fr:
if not ">" in line:
line = line.split()
orf_sub_bin.append(int(line[-2]))
orfbin.append(orf_sub_bin)
orf_sub_stat = [max(orf_sub_bin), min(orf_sub_bin),
median(orf_sub_bin), round(mean(orf_sub_bin),0)]
orf_stat.append(orf_sub_stat)
plt.figure()
for i in range(len(number)):
plt.hist(orfbin[i], histtype='step', color=colours[i], label=number[i], bins=bins)
plt.xlabel("Size (bp)")
plt.ylabel("Count")
plt.title("Distribution of Predicted ORF Size")
plt.legend(loc="upper right")
# plt.show()
plt.savefig("ORF_Stat_fig.png")
plt.savefig("ORF_Stat_fig.svg")
print ("Finished.")
|
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