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2ab5420425027c8709ac61acbe154185a0654117 | pcarvalhor/SCRIPTS-DE-ESTUDO | /SCRIPTS DE ESTUDO/casadecambio.py | 625 | 3.578125 | 4 | print('\033[1;34mSeja bem-vindo ao Carvalho Cambios\033[m')
S = float(input('\033[1;31mQuantos reais voce tem?\033[m'))
Z = str(input('\033[1;32mQual moeda voce quer comprar?\033[m')).lower()
if Z == 'dolar':
D = float(5.22)
if Z == 'euro':
D = float(5.67)
if Z == 'libra':
D = float(6.52)
T = S / D
if D == 5.22:
print('\033[1;31mVoce pode comprar {:.0f} dolares'.format(T))
if D == 5.67:
print('Voce pode comprar {:.0f} euros'.format(T))
if D == 6.52:
print('Voce pode comprar {:.0f} libras\033[m'.format(T))
print('\033[1;34mobrigado por comprar na carvalho cambios\033[m')
|
511caa6a153064077476e4c38bd590d51c362789 | MarvinVoV/algorithm-python | /sort/selection_sort.py | 334 | 3.765625 | 4 | def selection_sort(a):
"""
Selection sort
:param a: list
:return: list
"""
if not a or len(a) <= 1:
return
for i in range(len(a)):
p = i
for j in range(i + 1, len(a)):
if a[j] < a[p]:
p = j
a[p], a[i] = a[i], a[p] # swap a[p], a[i]
return a
|
9fb7143527edda33e84be4a2d044a61431c8789d | SajedNahian/SoftDev2 | /listcomp.py | 1,254 | 3.78125 | 4 | UPPERCASE = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
LOWERCASE = UPPERCASE.lower()
DIGITS = [str(i) for i in range(10)]
SPECIAL = "*.!?&#,;:-_"
def threshold_checker(password):
upper = [char for char in password if char in UPPERCASE]
lower = [char for char in password if char in LOWERCASE]
numbers = [char for char in password if char in DIGITS]
specials = [char for char in password if char in SPECIAL]
return len(upper) > 1 and len(lower) > 1 and len(numbers) > 1
def strength_checker(password):
strength = 1
if threshold_checker(password):
p_length = len(password)
if p_length > 10:
strength += 4
else:
strength += p_length - 4
numbers = [char for char in password if char in DIGITS]
upper = [char for char in password if char in UPPERCASE]
lower = [char for char in password if char in LOWERCASE]
specials = [char for char in password if char in SPECIAL]
if len(specials) > 0:
strength += 1
if len(specials) > 2:
strength += 1
if len(numbers) > 2:
strength += 1
if len(upper) > 2:
strength +=1
if len(lower) > 2:
strength +=1
return strength
|
f6a8f87d5beb592f564d16ea02a21022d86b9b39 | vincenttian/Backtesting_Platform | /strategy_random500.py | 2,138 | 3.71875 | 4 | import sqlite3
import math
from pprint import pprint
import random
from security_data import SecurityData
from account_manager import AccountManager
from account_metrics import AccountMetrics
'''
This file sets up a new account for the following trading strategy:
Invest a fixed amount (e.g. 100) of fund into 500 randomly chosen securities.
At the end of each month, replace the entire holdings in the account by investing the fixed
amount of fund to a new set of 500 randomly selected stocks.
'''
if __name__=='__main__':
con = sqlite3.connect('qse_test.db')
security_data = SecurityData(con)
account_manager = AccountManager(con)
account_metrics = AccountMetrics(con)
dates = security_data.get_dates()
stock_ids=security_data.get_security()
if len(stock_ids)<=500:
print "There are insufficient number of securities in the database for this trading strategy."
exit(1)
new_id=account_manager.new_account()
#print new_id
rows=[]
for d in dates:
my_ids=random.sample(stock_ids, 500)
for id in my_ids:
row=[new_id, id, 100, d]
rows.append(row)
account_manager.add_holdings(rows)
account_manager.add_account(new_id,0,"Invest 100 each month in 500 randomly chosen stocks")
all_acct=account_manager.get_accounts()
print "... All Accounts ..."
pprint(all_acct)
print
'''
stocks_071231=account_manager.get_holdings(new_id,"2007-12-31")
num=len(stocks_071231)
print("The number of stocks in the account %s is %s on 2007-12-31" %(new_id,num))
'''
#### Show performance metrics for the new account ####
rslt=account_metrics.all_returns(new_id)
total=sum(rslt)
up_months = 0
down_months = 0
for result in rslt:
if result > 0:
up_months += 1
else:
down_months += 1
print("Account %s Monthly Returns: " %new_id)
print rslt
print("Cumulative Returns: %s" %total)
account_metrics.show_stats(rslt)
print("No. Up Months: %s" %up_months)
print("No. Down Months: %s" %down_months) |
1f15e174430ce0d8cc48bfa57fa75e5ba33588a0 | vincenttian/Backtesting_Platform | /account_manager.py | 3,516 | 3.953125 | 4 | import sqlite3
import math
from pprint import pprint
import random
'''
The class AccountManager contains functions to update information in the account and holding table in the database.
It supports creation of accounts for new trading strategies.
Each entry in the account table represents a stock trading account implementing a trading strategy.
Each entry in the holding table represents a stock holding at a given time in an account.
'''
class AccountManager:
def __init__(self,con):
self.con=con
def get_accounts(self):
'''Return a list of accounts'''
sql='select * from account'
return [r for r in self.con.execute(sql)]
def get_holdings(self, account_id, as_of_date):
'''Return a list of (security, amount) in an account at a given date
acount_id: an integer representing an account id
as_of_date: 'YYYY-MM-DD' text formatted date
'''
sql='select security_id,amount from holding where account_id=? AND as_of_date=?'
return [r for r in self.con.execute(sql,(account_id,as_of_date))]
def new_account(self):
account_id=None
accounts=self.get_accounts()
ids=[r[0] for r in accounts]
account_id=max(ids)+1
return account_id
def add_stock(self, acct, date, security_id, amount):
row=[acct, security_id, amount, date]
sql='insert into holding(account_id,security_id,amount,as_of_date) values (?,?,?,?)'
self.con.execute(sql,row)
self.con.commit()
def delete_stock(self, acct, date, security_id):
'''Remove a stock in the holding table for an account at a given date '''
sql="DELETE FROM holding WHERE account_id=? AND security_id=? AND as_of_date=?"
self.con.execute(sql,(acct,security_id,date))
self.con.commit()
def add_stocks(self, acct, date, stock_rows):
'''The stock_rows is a list of (security_id, amount) tuples '''
sql='insert into holding(account_id,security_id,amount,as_of_date) values (?,?,?,?)'
for stock in stock_rows:
row=[acct, stock[0], stock[1], date]
self.con.execute(sql,row)
self.con.commit()
def add_holdings(self, holding_rows):
'''The holding_rows is a list of (account_id, security_id, amount, date) tuples '''
sql='insert into holding(account_id,security_id,amount,as_of_date) values (?,?,?,?)'
self.con.executemany(sql,holding_rows)
self.con.commit()
def add_account(self, account_id, rating, desc):
sql='insert into account(account_id,rating,desc) values(?,?,?)'
account_row=[account_id, rating, desc]
self.con.execute(sql,account_row)
self.con.commit()
## This function needs further testing
def update_rating(self, account_id, rating):
sql='update account set rating=? where account_id=?'
self.con.execute(sql,(rating,account_id))
self.con.commit()
if __name__=='__main__':
con = sqlite3.connect('qse_test.db')
account_manager = AccountManager(con)
accounts=account_manager.get_accounts()
id=account_manager.new_account()
holding_1=account_manager.get_holdings(1, "2008-01-31")
#account_manager.add_stock(1,"2009-01-31",782,1)
print "...The account Id of a newly created account will be..."
print id
print "...All accounts ..."
pprint(accounts)
print
print "...Holding at one date..."
pprint(holding_1)
print
|
70e15b366634efea90e939c6c169181510818fdb | Sushantghorpade72/100-days-of-coding-with-python | /Day-03/Day3.4_PizzaOrderCalculator.py | 881 | 4.15625 | 4 | '''
Project Name: Pizza Order
Author: Sushant
Tasks:
1. Ask customer for size of pizza
2. Do they want to add pepperoni?
3. Do they want extra cheese?
Given data:
Small piza: $15
Medium pizza: $20
Large pizza: $ 25
Pepperoni for Small Pizza: +$2
Pepperoni for medium & large pizza: +$3
Extra cheese for any size pizza: +$1
'''
print("Welcome to python pizza deliveries!!!")
size = input("What size pizza do you want? S,M or L? ")
add_pep = input("Do you want pepperoni? Y or N: ")
extra_cheese = input("Do you want extra cheese? Y or N: ")
#Price size wise:
bill = 0
if size == "S":
bill += 15
elif size == "M":
bill += 20
else:
bill += 25
if add_pep == "Y":
if size == "S":
bill += 2
else:
bill += 3
if extra_cheese == "Y":
bill += 1
print(f"Your final bill is ${bill}") |
049365f444a456bc954e511b09ca6a7c8a2c6868 | Sushantghorpade72/100-days-of-coding-with-python | /Day-04-Randomization- and-python-lists/Day4.2_Bank_Roulette.py | 278 | 3.84375 | 4 | '''
Project Name: Bank roulette
Author: Sushant
'''
import random
name_str = input("Give me everybody's name, seprated by a comma. ")
names = name_str.split(",")
person_who_pays = random.choice(names)
print(f'{person_who_pays} is going to pay for everyone')
|
6b07d6ae31b51c376a52628ad09e0c25da64a32b | PCvdScheer/Codewars | /Python/factorial/Kata.py | 330 | 3.9375 | 4 | def factorial(n):
if n>12 or 0>n:
raise ValueError('Provided value not within set limit (0 to 12)')
elif n == 0:
return 1
else:
mylist = []
for i in range(1,n+1):
mylist.append(i)
value = 1
for x in mylist:
value = value * x
return value |
962bfd875ae5f4e16a8ce4cbf154d9936fcba550 | PCvdScheer/Codewars | /Python/Reverse every other word in the string/Kata.py | 307 | 3.796875 | 4 | import re
def reverse_alternate(string):
temp = re.sub (' +', ' ', string)
temp = temp.split(' ')
out = []
for i in range(len(temp)):
if (i+1) %2==0:
out.append(temp[i][::-1])
else:
out.append(temp[i])
out1 = ' '.join(out)
return out1.strip() |
68eadbb2dd36110990c732586cf67b27067c4084 | Long0Amateur/Self-learnPython | /Chapter 3 Numbers/A program that prints out the sine and cosine of the angles ranging from 0 to 345 degrees in 15 degrees increment.py | 401 | 3.9375 | 4 | # A program that prints out the sine and cosine of the angles ranging from 0 to 345 degree in
# 15 degrees increments. Each result should be rounded to 4 decimal places.
from math import sin, cos, pi
for i in range(0,360,15):
x = sin((i*pi)/180) # To convert degree to radian, multiplying by pi divided by 180
y = cos((i*pi)/180)
print(i, '---',round(x,4),round(y,4))
|
0d5f545e7bacef8184a4224ad8e9816989ab6e2e | Long0Amateur/Self-learnPython | /Chapter 2 Loops/Chapter 2 (loops).py | 633 | 4.46875 | 4 | # Example 1
for i in range(5):
print('i')
print(sep='')
#Example 2
print('A')
print('B')
for i in range (5):
print('C')
print('D')
print('E')
print(sep='')
#Example 3
print('A')
print('B')
for i in range (5):
print('C')
for i in range (5):
print('D')
print('E')
print(sep='')
#Example 4
for i in range(3):
print(i+1,'--Hello')
print(sep='')
#Example 5
for i in range(5,0,-1):
print(i, end='')
print('Blast off!!!')
print(sep='')
#Example 6
for i in range(4):
print('*'*6)
print(sep='')
#Example 7
for i in range(4):
print('*'*(i+1))
|
8cb56ab0d210e9f3b146f0c9a778ae33b25d614a | Long0Amateur/Self-learnPython | /Chapter 7 Lists/A programs prints a list of 50 random numbers between 1 and 100 .py | 180 | 3.828125 | 4 | # A program generates a list L of 50 random numbers between 1 and 100
from random import randint
L = []
for i in range(50):
L.append(randint(1,100))
print(L)
|
71669b68018642dbf531b2bef3f36e8a677a6634 | Long0Amateur/Self-learnPython | /Chapter 8 More with Lists/A program picks 1 name from a list of names (choice).py | 168 | 3.90625 | 4 | # A program picks a name from a list of names
from random import choice
names = ['Joe','Bob','Sue','Sally']
current_player = choice(names)
print(current_player)
|
ca8c79b60d0858891c593e9bdb34e1b784266715 | Long0Amateur/Self-learnPython | /Chapter 4 If statement/Leap year 2.0.py | 280 | 4.03125 | 4 | # Leap year
x = eval(input('Enter a year:'))
if (x%4) == 0:
if(x%100) ==0:
if (x%400) == 0:
print(x,'Leap year')
else:
print(x,'Not leap year')
else:
print(x,'Leap year')
else:
print(x,'Not leap year')
|
59b46979b7ed16dbb116246773fa8d75e3d139de | Long0Amateur/Self-learnPython | /Chapter 5 Miscellaneous/review/summing.py | 111 | 3.703125 | 4 | # A program adds up the number from 1 to 100
s = 0
for i in range(1,51):
s = s + i
print(s)
|
2f081564ba6182d99df8f9c9d51025eae805ff37 | Long0Amateur/Self-learnPython | /Chapter 8 More with Lists/list comprehension/List comprehension IV (join).py | 189 | 3.734375 | 4 | # A program creates a random assortment of 100 letters
from random import choice
alphabet = 'abcdefghijklmnopqrstuvwxyz'
s = ''.join( choice(alphabet) for i in range(100) )
print(s)
|
db25f02be10a08b3d484a4d7731055f74a62a4aa | Long0Amateur/Self-learnPython | /Chapter 3 Numbers/A program that asks the user to enter an angle in degrees and prints out the sine of that angle.py | 200 | 4.34375 | 4 | # A program that asks the user to enter an angle in degrees and prints out the sine of that angle
from math import sin, pi
x = eval(input('Enter an angle in degrees:'))
print(sin((x*pi)/180))
|
bfd27b9e904038ac5e7dd11294d61b48f9f5c181 | Long0Amateur/Self-learnPython | /Chapter 5 Miscellaneous/review/flag, prime.py | 211 | 3.953125 | 4 | # flag, prime numbers
x = eval(input('Enter number:'))
flag = 0
for i in range (2,x):
if x%i == 0:
flag = 1
if flag == 1:
print(x,'is not prime')
else:
print (x,'is prime')
|
9b4a03cec322c2c28438a0c1df52d36f1dfce769 | Long0Amateur/Self-learnPython | /Chapter 5 Miscellaneous/swapping.py | 297 | 4.21875 | 4 | # A program swaps the values of 3 variables
# x gets value of y, y gets value of z, and z gets value of x
x = 1
y = 2
z = 3
hold = x
x = y
y = hold
hold = y
y = z
z = hold
hold = z
z = x
z = hold
print('Value of x =',x)
print('Value of y =',y)
print('Value of z =',z)
|
ce86a8409845bf69ba15d483e589531407b64a91 | Long0Amateur/Self-learnPython | /Chapter 7 Lists/problem/6. A program modifies a given list using for loop.py | 768 | 3.96875 | 4 | # A program creating list using a for loop
import string
# A list consisting of the integers 0 through 49
L = []
for i in range(50):
L.append(i)
print('A list consisting of the integers 0 through 49:\n',L,'\n')
# A list containing the squares of the integers 1 through 50
N = []
for j in range(1,51):
N.append(j**2)
print('A list containing the squares of the integers 1 through 50:\n',N,'\n')
# The list['a','bb','ccc','dddd',...] that ends with 26 copies of the letter z
s = string.ascii_lowercase
print('Via enumerate method:')
print([(i+1)*char for i, char in enumerate(s)])
print('\n')
print('Via for loop method:')
M = []
length = len(s)
for z in range(0,length):
c = s[z]*(z+1)
M.append(c)
print(M)
|
4af78f23eafc7a91c42c743535ddffaa8d427d01 | Long0Amateur/Self-learnPython | /Chapter 7 Lists/A program prints out two highest and lowest scores in the list.py | 397 | 4.03125 | 4 | # A programs prints out the two largest and two smallest elements of a list
# called scores
from random import randint
scores = []
for i in range(10):
scores.append(randint(0,10))
scores.sort()
print(scores)
print('Two lowest scores:',scores[0],scores[1])
print('Two highest scores:',scores[-1],scores[-2])
print('Average:',sum(scores)/len(scores))
|
8ab960a90654477984660a75a051cd02b87e0be5 | Long0Amateur/Self-learnPython | /Chapter 3 Numbers/A program that generates and prints 50 randoms integers, each between 3 and 6.py | 178 | 4.15625 | 4 | # A program that generates and prints 50 random integers, each between 3 and 6
from random import randint
for i in range (0,50):
x = randint(3,6)
print(x,end=' ')
|
a5391be6c639c900c6f7be8e584d515d5d7b56c4 | Long0Amateur/Self-learnPython | /Chapter 5 Miscellaneous/Natural logarithm.py | 281 | 3.984375 | 4 | # A program asks user to enter a value n, then compute ln(n)
import math
e = 2.718
x = eval(input('Enter a number:'))
s = 0
for i in range(1,x+1):
s = s + 1/i
print('The natural logarithm of',x,'is',s)
y = math.log(x,e)
print('ln(',x,') is',round(y,3))
|
a70f14120ac4fd6df74ec36b96e55257cad237dc | JayantiTA/UDP-clients-server | /clients.py | 1,303 | 3.515625 | 4 | import socket
import sys
import threading
# function send_message() to send message to the server
def send_message(clientSock):
# input client's username as identity
username = input("Input username: ")
# input message and send it to the server
while True:
message = input()
message_send = username + ': ' + message
clientSock.sendto(message_send.encode("utf-8"), (UDP_IP_ADDRESS, UDP_PORT_NO))
# to delete message input
sys.stdout.write("\033[F")
# declare ip address and port
UDP_IP_ADDRESS = '0.0.0.0'
UDP_PORT_NO = 2410
# create socket
clientSock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
# allows sockets to bind() to the same IP:port
clientSock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1)
# allows broadcast UDP packets to be sent and received
clientSock.setsockopt(socket.SOL_SOCKET, socket.SO_BROADCAST, 1)
# bind the socket to address
clientSock.bind((UDP_IP_ADDRESS, UDP_PORT_NO))
# print additional message
print("\nWelcome to WhatsUDP Messenger!")
# create object Thread
clientThread = threading.Thread(target=send_message, args=(clientSock,))
clientThread.start()
# receive broadcast message from server and print it
while True:
data, addr = clientSock.recvfrom(1024)
print(data.decode("utf-8")) |
c5107058ef2aebfe562e200daceb118484c4cad9 | Carbon2015/Python-002 | /week01/Week01_Task01.py | 2,608 | 3.5 | 4 | # 作业一：
# 安装并使用 requests、bs4 库，爬取猫眼电影（）的前 10 个电影名称、电影类型和上映时间，并以 UTF-8 字符集保存到 csv 格式的文件中。
# 猫眼电影网址： https://maoyan.com/films?showType=3
import requests
from bs4 import BeautifulSoup as bs
import pandas as pd
targetUrl = "https://maoyan.com/films?showType=3"
# 增加cookie字段，否则可能去到”验证中心“页面。
header = {
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.116 Safari/537.36",
"cookie": "uuid=33119590CC2811EA989D8534BBE132DAE1777F37D0574C959B3EB84DE37B0413;"}
# 使用requests获取目标页面response
response = requests.get(targetUrl, headers=header)
# 使用BeautifulSoup来parse response为“BeautifulSoup”对象。参见https://www.crummy.com/software/BeautifulSoup/bs4/doc.zh/
parsedData = bs(response.text, "html.parser")
# 最总结果的List，为pandas输出做准备
resultList = []
# 找到指定class的div标签，limit可以限制返回个数。
for movie in parsedData.find_all("div", class_="channel-detail movie-item-title", limit=10):
# 存储每个电影的名称，类型，上映时间为list
tempResult = [movie["title"]]
# 获取每个电影的链接后，拼接url，打开下层页面。
response_L2 = requests.get(str("https://maoyan.com" + movie.find("a")["href"]), headers=header)
parsedData_L2 = bs(response_L2.text, "html.parser")
# 因为电影类型数量不固定，需要for in遍历所有类型。
for movieType in parsedData_L2.find("div", class_="movie-brief-container").find("ul").find("li").find_all("a"):
# 记录电影类型到list
tempResult.append(movieType.get_text().strip())
# 记录电影上映时间到list
# 多次find找到目标的唯一路径。
# .find_all("li")[2] 让我们直接找第三个li而不用遍历。
# .contents[0] 是因为find_all返回的是tag的list。tag的 .contents 属性可以将tag的子节点内容以列表的方式输出。或者使用get_text()也一样。
tempResult.append(
parsedData_L2.find("div", class_="movie-brief-container").find("ul").find_all("li")[2].contents[0][0:10])
# 记录电影信息到最终result列表
resultList.append(tempResult)
# 把list转为pandas的DataFrame
movieFile = pd.DataFrame(data=resultList)
# 写DataFrame为csv文件。中文系统使用GBK编码，英文可以使用utf-8
movieFile.to_csv("./movies_work01.csv", encoding="GBK", index=False, header=False)
|
8f42e52832e46d28c857ee3d84cd19ae49f00b72 | LakshayNagpal/Data-Analyst-Nanodegree | /P6: Intro to Hadoop and MapReduce/reducer_wordcount.py | 739 | 3.546875 | 4 | #!/usr/bin/python
import sys
current_count = 0
current_word = None
# Loop around the data
# It will be in the format key\tval
# Where key is the store name, val is the sale amount
#
# All the sales for a particular store will be presented,
# then the key will change and we'll be dealing with the next store
for line in sys.stdin:
data_mapped = line.strip().split("\t")
if len(data_mapped) != 2:
# Something has gone wrong. Skip this line.
continue
word, count = data_mapped
try:
count = int(count)
except ValueError :
continue
if current_word == word:
current_count +=1
else:
if current_word:
print current_word , "\t" , current_count
current_word = word
current_count = count
|
e93d8b3bc8ceb3d66066bc1e4585e4e82bd001fd | morrislab/plos-medicine-joint-patterns | /scripts/co_occurrences/summarize_deltas.py | 1,179 | 3.53125 | 4 | """
Summarizes deltas.
"""
import pandas as pd
from click import *
from logging import *
@command()
@option('--input', required=True, help='the CSV file to read deltas from')
@option('--output', required=True, help='the CSV file to write summaries to')
def main(input, output):
basicConfig(
level=INFO,
handlers=[
StreamHandler(), FileHandler(
'{}.log'.format(output), mode='w')
])
# Load the data.
info('Loading data')
data = pd.read_csv(input)
info('Result: {}'.format(data.shape))
# Calculate summaries.
info('Calculating summaries')
mean_offdiagonal = data.query(
'reference_site_root != co_occurring_site_root')['delta'].mean()
mean_diagonal = data.query(
'reference_site_root == co_occurring_site_root')['delta'].mean()
# Compile the summaries.
info('Compiling summaries')
summary = pd.DataFrame({
'diagonal': ['off_diagonal', 'on_diagonal'],
'mean': [mean_offdiagonal, mean_diagonal]
})
# Write the output.
info('Writing output')
summary.to_csv(output, index=False)
if __name__ == '__main__':
main() |
6760ca99d0f6ddf708a15c4b409074372558db40 | morrislab/plos-medicine-joint-patterns | /scripts/localizations/get_optimal_partial_threshold.py | 1,021 | 3.59375 | 4 | """
Obtains optimal thresholds for partial localization.
This threshold is determined by where the most negative slope occurs.
"""
import pandas as pd
from click import *
from logging import *
@command()
@option('--input', required=True, help='the CSV file to read stats from')
@option(
'--output',
required=True,
help='the text file to output the optimal threshold to')
def main(input: str, output: str):
basicConfig(level=DEBUG)
info('Loading stats')
stats = pd.read_csv(input)
stats.set_index('threshold', drop=False, inplace=True)
debug(f'Result: {stats.shape}')
info('Calculating slopes')
rises = stats['mean'].shift(-1) - stats['mean'].shift(1)
runs = stats['threshold'].shift(-1) - stats['threshold'].shift(1)
slopes = rises / runs
info('Determining optimal threshold')
threshold = slopes.argmin()
info('Writing output')
with open(output, 'w') as handle:
handle.write(str(threshold))
if __name__ == '__main__':
main() |
2db6ef3327edb52ccd1074d7a2f2b3a46aec8c5d | morrislab/plos-medicine-joint-patterns | /scripts/crosstalk/make_data.py | 6,289 | 3.8125 | 4 | """
Generates data for analyzing distributions of scores among patient groups.
Normalizes scores by patient. The end result is that for each patient, scores
will be in the range [0, 1] with the highest-scoring factor having a normalized
score of 1.
"""
from click import *
from logging import *
import janitor as jn
import pandas as pd
import string
def get_threshold(ctx, param, value):
"""
Obtains a threshold from the given parameter.
"""
if value is not None:
try:
return int(value)
except ValueError:
if value not in ['cohort', 'cluster']:
raise ValueError('must be a number, "cohort", or "cluster"')
return value
return 0
def normalize(X: pd.DataFrame) -> pd.DataFrame:
"""
Normalizes scores to the range [0, 1] for a single patient.
Args:
X: data frame containing patient factor scores for a single patient
Returns:
normalized patient factor scores
"""
Y = X.set_index(['factor'])[['score']]
Y['score'] /= Y['score'].max()
return Y
def z_transform(x: pd.Series) -> pd.Series:
"""
Z-transforms scores.
Args:
x: values to Z-transform
Returns:
Z-transformed scores
"""
return (x - x.mean()) / x.std()
@command()
@option(
'--score-input', required=True, help='the CSV file to read scores from')
@option(
'--localization-input',
required=True,
help='the CSV file to read localization data from')
@option('--output', required=True, help='the Feather file to write output to')
@option(
'--letters/--no-letters',
default=False,
help='whether to use letters for factor names')
@option('--count-input', help='the CSV file to read joint counts from')
@option(
'--threshold',
callback=get_threshold,
help=(
'the joint count to calculate to set as a minimum inclusion threshold; '
'"cohort": calculate a global median threshold from the cohort; '
'"cluster": calculate a per-cluster median threshold'))
def main(score_input, localization_input, output, letters, count_input,
threshold):
basicConfig(level=DEBUG)
if threshold == 'none' and not count_input:
raise Exception(
'--count-input must be defined if --threshold is not "none"')
# Load data.
info('Loading scores')
scores = pd.read_csv(score_input)
debug(f'Result: {scores.shape}')
info('Loading localizations')
localizations = pd.read_csv(
localization_input, index_col='subject_id').drop(
'threshold', axis=1)
debug(f'Result: {localizations.shape}')
# Filter the data if needed.
if threshold != 0:
info('Loading joint counts')
counts = pd.read_csv(count_input, index_col=0)
debug(f'Result: {counts.shape}')
if isinstance(threshold, int):
info('Filtering scores')
filtered_counts = counts.query('count >= @threshold')
scores = scores.set_index('subject_id').loc[
filtered_counts.index].reset_index()
debug(f'Result: {scores.shape}')
elif threshold == 'cohort':
info('Calculating median count')
median_count = counts['count'].median()
debug(f'Median: {median_count} joints')
info('Filtering scores')
filtered_counts = counts.query('count >= @median_count')
scores = scores.set_index('subject_id').loc[
filtered_counts.index].reset_index()
debug(f'Result: {scores.shape}')
else:
info('Joining joint counts with classifications')
joined_counts = counts.join(localizations[['classification']])
debug(f'Result: {joined_counts.shape}')
before_n_patients = joined_counts['classification'].value_counts()
for k, v in before_n_patients.iteritems():
debug(f'- {k}: {v} patients')
info('Calculating median counts')
median_counts = pd.Series(
joined_counts.groupby('classification')['count'].median(),
name='median')
debug(f'Result: {median_counts.shape}')
for k, v in median_counts.iteritems():
debug(f'- {k}: {v} joints')
info('Filtering scores')
joined_medians = joined_counts.reset_index(
).set_index('classification').join(
median_counts.to_frame()).reset_index().set_index('subject_id')
to_retain = joined_medians['count'] >= joined_medians['median']
scores = scores.set_index('subject_id').loc[
to_retain].reset_index()
after_n_patients = scores.set_index('subject_id').join(
localizations['classification']).reset_index()[
'classification'].value_counts()
for k, v in after_n_patients.iteritems():
debug(f'- {k}: {v} patients')
debug(f'Result: {scores.shape}')
# Melt data.
info('Melting scores')
scores = scores.melt(
id_vars='subject_id', var_name='factor', value_name='score')
scores['factor'] = scores['factor'].astype(int)
debug(f'Result: {scores.shape}')
# Patient-normalize patient factor scores.
info('Patient-normalizing scores')
scores = scores.groupby('subject_id').apply(normalize).reset_index()
debug(f'Result: {scores.shape}')
# Calculate Z-scores.
info('Calculating Z-scores')
scores['z_score'] = scores.groupby('factor')['score'].apply(z_transform)
debug(f'Result: {scores.shape}')
# Rename factors.
info('Renaming factors')
scores['factor'] = [
f'<{string.ascii_uppercase[x - 1]}>' for x in scores['factor']
] if letters else [f'<{x:02d}>' for x in scores['factor']]
# Join data.
info('Joining data')
joined = scores.set_index('subject_id').join(localizations)
debug(f'Result: {joined.shape}')
# Write output.
info('Writing output')
joined = joined.pipe(
jn.encode_categorical, columns=['classification', 'localization'])
joined.reset_index().to_feather(output)
if __name__ == '__main__':
main() |
fafa60fcff780a161c7889d5d763ecae8dab8849 | consbio/parserutils | /parserutils/numbers.py | 414 | 4.03125 | 4 | from math import isnan, isinf
def is_number(num, if_bool=False):
""" :return: True if num is either an actual number, or an object that converts to one """
if isinstance(num, bool):
return if_bool
elif isinstance(num, int):
return True
try:
number = float(num)
return not (isnan(number) or isinf(number))
except (TypeError, ValueError):
return False
|
29251cbc397c958ab2bb023038dca2a6c58aea9a | sabk18/CS_555_GEDCOM | /src/sprint2/story25.py | 2,455 | 3.53125 | 4 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 2 14:00:42 2020
@author: sabkhalid
"""
#story 25: Unique first names in Family
#No more than one child with the same name and birth date should appear in the family
#step 1: for each row of FAM, chk for children id. for every unique children id, chk for their birth date in INDI. if unique then show that in
#family table.
import unittest
class Unique_birthDate_firstName(unittest.TestCase):
def test_unique_childIDs_true(self):
result = unique_childID(['xyz', 'abc','123'])
self.assertTrue(result, 'True')
def test_unique_childIDs_equal(self):
result1 = unique_childID(['xyz', 'abc','123'])
result2 = unique_childID(['xyz', 'abc','123'])
self.assertEqual(result1, result2)
def test_true_unique_FirstName_BirthDate(self):
result = name_birth(['Meredith - 9th Feb 1995', 'Alex - 30th Jan 1998', 'Christina - 26th July 1990'])
self.assertTrue(result, 'True')
def test_false_unique_FirstName_BirthDate(self):
result= name_birth(['Meredith - 9th Feb 1995', 'Alex - 30th Jan 1998', 'Meredith - 9th Feb 1995'])
self.assertFalse(result, 'False')
def unique_childID(children):
if len(children) == len(set(children)): #chk if unique
return True
else:
return False
def name_birth(data):
if len(data) == len(set(data)):
return True
else:
return False
def s25test(info, file):
for fam in info['FAM']:
if 'CHIL' in info['FAM'][fam]:
children_ids = info['FAM'][fam]['CHIL']
if unique_childID(children_ids):
uniqueChild = []
for child in children_ids:
children_name = info['INDI'][child]['NAME']
name_split = children_name.split('/')
first_name = name_split[0]
#print (first_name)
date_of_birth = info['INDI'][child]['BIRT']
#print (date_of_birth)
child = first_name + ' - ' + date_of_birth
uniqueChild.append(child)
if not name_birth(uniqueChild):
file.write("\nError: For Family ID {}, there should be unique child first name and birth date".format(fam))
return file
if __name__ == '__main__':
unittest.main() |
e480e4a53659ad7983b6be14b4c06dba1fb00c50 | sabk18/CS_555_GEDCOM | /src/sprint3/story41.py | 1,532 | 3.53125 | 4 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 7 22:18:31 2020
@author: sabkhalid
"""
#story41: include partial dates. 'Only Year '
from datetime import *
def partial_date(date):
try:
date_dt = datetime.strptime(date, '%d %b %Y') #change to datetime
Year = date_dt.year
except:
False
return Year
def s41test(info, file):
for indiv in info['INDI']:
if 'BIRT' in info['INDI'][indiv]:
birth_date= info['INDI'][indiv]['BIRT']
birth_date = partial_date(birth_date)
print("\nINDI: {} ".format(indiv) , "Partial Birth Date: {}".format(birth_date))
if 'DEAT' in info['INDI'][indiv]:
death_date = info['INDI'][indiv]['DEAT']
death_date = partial_date(death_date)
print("\nINDI: {} ".format(indiv) , "Partial Death Date: {}".format(death_date))
for fam in info['FAM']:
if 'MARR' in info['FAM'][fam]:
marriage_date= info['FAM'][fam]['MARR']
marriage_date = partial_date(marriage_date)
print("\nINDI: {} ".format(indiv) , "Partial Marriage Date: {}".format(marriage_date))
if 'DIV'in info ['FAM'][fam]:
divorce_date= info['FAM'][fam]['DIV']
divorce_date =partial_date(divorce_date)
print("\nINDI: {} ".format(indiv) , "Partial Divorce Date: {}".format(divorce_date))
return file
|
23094db9ffde4fff11f92010efe854558bb732de | haraldyy/teaching_turtles | /retangulos_e_quadrados.py | 432 | 3.84375 | 4 | from turtle import *
shape("turtle")
#Isso vai desenhar uma estrela cinza clara em um fundo azul escuro
color("WhiteSmoke")
bgcolor("MidnightBlue")
def quadrado():
for i in range(4):
forward(100)
right(90)
def retangulo():
for i in range(2):
right(90)
forward(150)
right(90)
forward(90)
quadrado()
penup()
backward(250)
pendown()
left(90)
retangulo()
|
0e41bd56ce0c6b4761aa3bf3f86b181ea7b70697 | Tuman1/Web-Lessons | /Python Tutorial_String Formatting.py | 1,874 | 4.28125 | 4 | # Python Tutorial: String Formatting - Advanced Operations for Dicts, Lists, Numbers, and Dates
person = {'name':'Jenn', 'age': 23}
# WRONG example
# Sentence = 'My name is ' + person['name'] + ' and i am ' + str(person['age']) + ' years old.'
# print(Sentence)
# Sentence = 'My name is {} and i am {} years old.'.format(person['name'], person['age'])
# print(Sentence)
# Sentence = 'My name is {1} and i am {0} years old.'.format(person['name'], person['age'])
# print(Sentence)
# tag = "h1"
# text = "This is a headline"
#
# Sentence = '<{0}><{1}></{0}>'.format(tag, text)
# print(Sentence)
# Sentence = 'My name is {1[name]} and i am {0[age]} years old.'.format(person, person)
# print(Sentence)
# class Person():
# def __init__(self, name, age):
# self.name = name
# self.age = age
#
# p1 = Person('Jack', '33')
#
# Sentence = 'My name is {0.name} and i am {0.age} years old.'.format(p1)
# print(Sentence)
# Sentence = 'My name is {name} and i am {age} years old.'.format(name = "Garold", age = "33")
# print(Sentence)
#One of the most convinient way to print dictionary
# Sentence = 'My name is {name} and i am {age} years old.'.format(**person)
# print(Sentence)
#Formatting number
# for x in range(1, 11):
# sentence = "The value is {:03}".format(x)
# print(sentence)
# pi = 3.14159265
#
# sentence = 'Pi is equal to {:.2f}'.format(pi)
# print(sentence)
# sentence = '1 Mb is equal to {:,.2f} bytes'.format(1000**2)
# print(sentence)
import datetime
my_date = datetime.datetime(2016,9,24,12,30,45)
# print(my_date)
# Example what we need -> March 01 2016
# sentence = '{:%B %d, %Y}'.format(my_date)
# print(sentence)
# Example what we need -> March 01, 2016 fell on a Tuesday and was the 061 day of the year.
sentence = '{0:%B %d, %Y} fell on a {0:%A} and was the {0:%j} day of the year.'.format(my_date)
print(sentence)
|
949f77b98a5e36ce0b38ba07937cf73a17120097 | dahea-moon/Algorithm | /leetcode/345_Reverse Vowels of a String.py | 852 | 3.671875 | 4 | from unittest import TestCase
from typing import List
class Solution:
def reverseVowels(self, s: str) -> str:
vowels = ['a', 'e', 'i', 'o', 'u']
s = list(s)
vowel_index = [(idx, char) for idx, char in enumerate(s) if char.lower() in vowels]
j = 0
for i in range(len(vowel_index)-1, -1, -1):
vowel_idx = vowel_index[i][0]
s[vowel_idx] = vowel_index[j][1]
j += 1
return ''.join(s)
class Test(TestCase):
def setUp(self) -> None:
self.solution = Solution()
def test_testcases(self):
test_cases = [
("hello", "holle"),
("leetcode","leotcede")
]
for test_case in test_cases:
answer = self.solution.reverseVowels(test_case[0])
self.assertEqual(answer, test_case[1])
|
5fa5335a5f6a44d3546c47db3b2718cc4a9634ff | dahea-moon/Algorithm | /leetcode/605_Can Place Flowers.py | 1,867 | 3.703125 | 4 | from unittest import TestCase
from typing import List
class Solution:
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
idx = 0
planted = 0
for i in range(n):
while idx < len(flowerbed):
if flowerbed[idx]:
idx += 1
elif not flowerbed[idx]:
if idx == len(flowerbed)-1 and not flowerbed[idx-1]:
flowerbed[idx] = 1
planted += 1
break
elif idx == 0 and not flowerbed[idx+1]:
flowerbed[idx] = 1
planted += 1
break
elif not flowerbed[idx-1] and not flowerbed[idx+1]:
flowerbed[idx] = 1
planted += 1
break
else:
idx += 1
if planted == n:
return True
return False
def fastest(self, flowerbed: List[int], n: int) -> bool:
cnt, beds = 1, 0
for bed in flowerbed:
if bed:
cnt = 0
else:
cnt += 1
if cnt == 3:
cnt = 1
beds += 1
if not flowerbed[-1]:
cnt += 1
if cnt == 3:
beds += 1
return beds >= n
class Test(TestCase):
def setUp(self) -> None:
self.solution = Solution()
def test_testcases(self):
test_cases = [
([1,0,0,0,1], 1, True),
([1,0,0,0,1], 2, False),
([1,0,1,0,1,0,1], 1, False)
]
for test_case in test_cases:
answer = self.solution.canPlaceFlowers(test_case[0], test_case[1])
self.assertEqual(answer, test_case[2])
|
9153885112141bce545f746c8f1aab591766dae1 | Invirent/Tugas-Pertemuan-12 | /code_penulisan_angka.py | 2,031 | 3.546875 | 4 | import os
kata = ['','one ','two ','three ','four ','five ','six ','seven ','eight ','nine ']
belasan = ['','eleven ','twelve ','thirteen ','fourteen ','fifthteen ','sixteen ','seventeen ','eighteen ','nineteen ']
puluhan = ['','ten ','twenty ','thirty ','fourty ','fifty ','sixty ','seventy ','eighty ','ninety ']
def perhitungan(n):
if n <10:
return kata[n]
elif n>=1_000_000_000:
return perhitungan(n//1_000_000_000)+"billion "+(perhitungan(n%1_000_000_000)if n%1_000_000_000 != 0 else '')
elif n>=1_000_000:
return perhitungan(n//1_000_000)+"million "+(perhitungan(n%1_000_000)if n%1_000_000 != 0 else '')
elif n>=1_000:
return perhitungan(n//1000)+"thousand "+(perhitungan(n%1000)if n%1000 != 0 else '')
elif n ==100:
return perhitungan(n//100)+"hundred "+(perhitungan(n%100)if n%100 != 0 else '')
elif n >100:
return perhitungan(n//100)+"hundred and "+(perhitungan(n%100)if n%100 != 0 else '')
else:
if n%10 == 0:
return puluhan[n//10]
elif n<20 and n>10:
return belasan[n//10]
else:
return puluhan[n//10]+ (perhitungan(n%10) if n%10!=0 else ' ')
while True:
os.system("cls")
err=0
print ("Program Angka ke Huruf ")
print ('=======================================')
try:
nomor= int(input('Number? '))
print (perhitungan(nomor))
os.system("pause")
retry=input('Apakah Program ingin Diulang?(Y/N) ')
while True:
if retry.lower() in ['y','n']:
break
if retry.lower() =='n':
break
except ValueError:
print ('Input harus angka')
err+=1
except Exception as e:
print(f'Error Type {e}')
if err == 1:
retry=input('Apakah Program ingin Diulang?(Y/N) ')
while True:
if retry.lower() in ['y','n']:
break
if retry.lower() =='n':
break |
39603555694c8d7f1f7bf47daee88f06ec297e99 | SusyVenta/Chess | /Utils.py | 1,545 | 3.546875 | 4 | class Utils:
def get_current_letter(self, tag_position):
return tag_position[0]
def get_current_number(self, tag_position):
return tag_position[1]
def letter_to_number(self, letter):
letters_and_numbers = {"a": 1, "b": 2, "c": 3, "d": 4, "e": 5, "f": 6, "g": 7, "h": 8}
return letters_and_numbers[letter]
def number_to_letter(self, number):
numbers_and_letters = {1: "a", 2: "b", 3: "c", 4: "d", 5: "e", 6: "f", 7: "g", 8: "h"}
return numbers_and_letters[number]
def all_numbers_except_current_list(self, current_number):
all_numbers = [1, 2, 3, 4, 5, 6, 7, 8]
all_numbers.remove(current_number)
return all_numbers
def all_letters_except_current_list(self, current_letter):
all_letters = ["a", "b", "c", "d", "e", "f", "g", "h"]
all_letters.remove(current_letter)
return all_letters
def end_position_is_free(self, end_coordinates, pieces_position):
if end_coordinates in pieces_position.keys():
return False
return True
def end_position_contains_opponent_piece(self, piece_moved, end_coordinates, pieces_position):
if end_coordinates in pieces_position.keys():
if (piece_moved.islower() and pieces_position[end_coordinates].isupper()) or (
piece_moved.isupper() and pieces_position[end_coordinates].islower()):
return True
return False
def is_white_moving(self, piece_moved):
return piece_moved.isupper()
|
16fc93b40eb0ad8b1b35774e0172315d67b4e46b | koushikd9/Mini_Projects | /Python/RollADice.py | 210 | 3.90625 | 4 | import random
while True:
choice=input("Do you want to Roll Dice or exit:Y/N").capitalize()
if choice=="Y":
print(random.randint(1,6))
elif choice=="N":
print("Bye")
break
|
b7439c8d91988f6652f6dccf2886ac650db178db | yu5shi8/AtCoder | /ABC_A/ABC171A.py | 183 | 3.65625 | 4 | # -*- coding: utf-8 -*-
# A - αlphabet
# https://atcoder.jp/contests/abc171/tasks/abc171_a
S = input()
if S.isupper():
print('A')
else:
print('a')
# 21:00 - 21:02（AC）
|
aaaaf1539dfaf12e1991144d05f3096958bc19d5 | yu5shi8/AtCoder | /ABC_A/ABC046A.py | 200 | 3.515625 | 4 | # -*- coding: utf-8 -*-
# A - AtCoDeerくんとペンキ
# https://atcoder.jp/contests/abc046/tasks/abc046_a
abc = list(map(int, input().split()))
count = (len(abc) + len(set(abc))) - 3
print(count)
|
cc483e1488b21a6666c72989ad9f3be348da652d | yu5shi8/AtCoder | /ABC_A/ABC018A.py | 347 | 3.65625 | 4 | # -*- coding: utf-8 -*-
# A - 豆まき
# https://atcoder.jp/contests/abc018/tasks/abc018_1
a = [1] + [int(input())]
b = [2] + [int(input())]
c = [3] + [int(input())]
rank = [a, b, c]
rank.sort(key=lambda x:-x[1])
for i in range(3):
rank[i].append(i+1)
rank.sort(key=lambda x:x[0])
for i in range(3):
print(rank[i][2])
# 10:09 - 10:18
|
ef83c6b7cebd3095bcd5171043eaa45a7f2baa78 | yu5shi8/AtCoder | /ABC_A/ABC006A.py | 210 | 3.71875 | 4 | # -*- coding: utf-8 -*-
# A - 世界のFizzBuzz
# https://atcoder.jp/contests/abc006/tasks/abc006_1
n = input()
if n.count('3') > 0 or int(n) % 3 == 0:
print('YES')
else:
print('NO')
# 11:03 - 11:07
|
5418ae94592bff2e401f03d295adc3c4aaf2bfa1 | yu5shi8/AtCoder | /ABC_A/ABC092A.py | 431 | 3.5625 | 4 | # -*- coding: utf-8 -*-
# A - Traveling Budget
# https://atcoder.jp/contests/abc092/tasks/abc092_a
a = int(input())
b = int(input())
c = int(input())
d = int(input())
if a >= b and c >= d:
print(b + d)
elif a >= b and c < d:
print(b + c)
elif a < b and c >= d:
print(a + d)
else:
print(a + c)
# min() で比較するとスマートになります
# if min(a, b) and min(c, d):
# print(min(a, b) + min(c, d)) |
bd44ffbfac8714c373eec4a6bb907cf6f32f4aa3 | yu5shi8/AtCoder | /ABC_A/ABC073A.py | 257 | 3.96875 | 4 | # -*- coding: utf-8 -*-
# A - September 9
# https://atcoder.jp/contests/abc073/tasks/abc073_a
n = input()
if n[0] == '9' or n[1] == '9':
print('Yes')
else:
print('No')
# if n[0] == '9' or n[1] == '9':
# ↓ スマートにできる
# if '9' in n:
|
489caf71a3730eb7897cc16629a39715db58022f | yu5shi8/AtCoder | /ARC_A/ARC003A.py | 401 | 3.5625 | 4 | # -*- coding: utf-8 -*-
# A - GPA計算
# https://atcoder.jp/contests/arc003/tasks/arc003_1
N = int(input())
r = input()
cnt = 0
for i in range(N):
if r[i] == 'A':
cnt += 4
elif r[i] == 'B':
cnt += 3
elif r[i] == 'C':
cnt += 2
elif r[i] == 'D':
cnt += 1
else:
cnt += 0
gpa = cnt / N
print('{:.12f}'.format(gpa))
# 15:10 - 15:14（AC）
|
5f024e8fbf88acb26502a5e6e26b16b1b6a10673 | yu5shi8/AtCoder | /ABC_A/ABC088A.py | 200 | 3.5625 | 4 | # -*- coding: utf-8 -*-
# A - Infinite Coins
# https://atcoder.jp/contests/abc088/tasks/abc088_a
n = int(input())
a = int(input())
ans = n % 500
if ans <= a:
print('Yes')
else:
print('No')
|
f65400b3a60dd75d0674a81523e6cc3eebc9bb2d | JoLartey/data | /app.py | 249 | 3.875 | 4 |
print('Hello Notitia-AI C2 Fellow')
# The greet function requests the name of the fellow and then welcomes them to the fellowship.
def greet():
name = input("Please enter your name\n")
print("Welcome to Notitia-AI" + "" + name)
greet() |
efdccd8d87863e0aaa75ef8c76c9b761bb2dd275 | clkadem/Goruntu-Isleme | /intensity_inverse_example.py | 1,811 | 3.515625 | 4 | # intensity transformation
# intensity inverse example
# gamma correction
import os
import matplotlib.pyplot as plt
import numpy as np
print(os.getcwd())
path = "C:\\Users\\Adem\\PycharmProjects\\GörüntüIsleme"
file_name_with_path = path + "\pic_1.jpg"
print(file_name_with_path)
img_0 = plt.imread(file_name_with_path)
plt.imshow(img_0)
plt.show()
print(img_0.ndim,img_0.shape)
print(np.min(img_0),np.max(img_0))
def convert_rgb_to_gray_level(im_1):
m=im_1.shape[0]
n=im_1.shape[1]
im_2=np.zeros((m,n))
for i in range(m):
for j in range(n):
im_2[i,j]=get_distance(im_1[i,j,:])
return im_2
def get_distance(v,w=[1/3,1/3,1/3]):
a,b,c=v[0],v[1],v[2]
w1,w2,w3=w[0],w[1],w[2]
d=((a**2)*w1+(b**2)*w2+(c**2)*w3)*5
return d
def my_f_1(a,b):
assert a>=0;"intensity pozitive","error intensity not pozitive"
if(a<=255-b):
return a+b
else:
return 255
def my_f_2(a):
return int(255-a)
img_1 = convert_rgb_to_gray_level(img_0)
plt.imshow(img_1,cmap='gray')
plt.show()
m,n=img_1.shape
img_2 = np.zeros((m,n),dtype="uint8")
for i in range(m):
for j in range(n):
intensity = img_1[i,j]
#increment = 50
img_2[i,j] = my_f_2(intensity)
plt.subplot(1,2,1)
plt.imshow(img_1,cmap='gray')
plt.subplot(1,2,2)
plt.imshow(img_2,cmap='gray')
plt.show()
x = np.array(list(range(100)))
y1 = np.power(x/float(np.max(x)),1)
y2 = np.power(x/float(np.max(x)),10)
y3 = np.power(x/float(np.max(x)),1/10)
plt.plot(x,y1)
plt.plot(x,y2)
plt.plot(x,y3)
plt.show()
def my_f_3(image_001,gamma):
return np.power(image_001/float(np.max(image_001)),gamma)
x = img_0
img_100 = np.power(x/float(np.max(x)),1)
plt.imshow(img_100)
plt.show() |
5e1f4a6ef075b0ada1c5e5517f4048f1a259307d | glassnotes/Balthasar | /src/balthasar/curve.py | 5,452 | 3.59375 | 4 | #!/usr/bin/python
# -*- coding: utf-8 -*-
#
# curve.py: A class for curves over finite fields in discrete phase space.
#
# © 2016 Olivia Di Matteo ([email protected])
#
# This file is part of the project Balthasar.
# Licensed under BSD-3-Clause
#
from pynitefields import *
class Curve():
""" Class to hold all points in a curve.
Curves are sets of points of the form :math:`(\\alpha, c(\\alpha)` for
all :math:`\\alpha` in a specified GaloisField, where
.. math::
c(\\alpha) = c_0 + c_1 \\alpha + c_2 \\alpha^2 + ...
They are constructed by passing in a list of coefficients in the form
:math:`[c_0, c_1, c_2, \ldots]`.
Args:
coefs (list): The coefficients of the curve.
field (GaloisField): The field over which the curve is defined.
Attributes:
field (GaloisField): The finite field in which is curve is defined
coefs (list): The coefficients :math:`[c_0, c_1, \ldots]`.
form (string): "beta" or "alpha", tells whether to do the curve
as :math:`beta = f(alpha) or alpha = f(beta).
By default, we use the beta form, beta = f(alpha).
is_ray (bool): A Boolean which indicates whether the curve passes
through the point (0, 0) or not
points (list): A list of tuples of field elements which are the
points of this curve over the field.
"""
def __init__(self, coefs, field, form="beta"):
self.field = field
self.coefs = coefs
self.form = form # Default curve in form beta (alpha)
self.is_ray = False # Does it pass through 0, 0
self.points = [] # List of points as tuples
# Determine if the curve is a ray by checking the constant term
if type(coefs[0]) is int:
if coefs[0] == 0:
self.is_ray = True
else:
if coefs[0] == self.field[0]:
self.is_ray = True
# Compute all the points on the curve
for el in field:
if self.form == "beta":
self.points.append( (el, field.evaluate(coefs, el)) )
elif self.form == "alpha":
self.points.append( (field.evaluate(coefs, el), el) )
def __getitem__(self, index):
""" Get a point on the curve.
Args:
index (int): The index at which we would like to
find the value on the curve. Expressed as a power
of the primitive element of the field.
Returns:
The tuple (index, value of the curve at index).
"""
if index < len(self.points) and index >= 0:
return self.points[index]
else:
print("Error, element out of bounds.")
def __iter__(self):
""" Allow the user to iterate over the curve point by point """
return iter(self.points)
def print(self, as_points = False):
""" Print the curve.
Args:
as_points (bool): If True is passed, will print the list of
points on the curve as tuples. By default, prints
the curves as a polynomial.
"""
if as_points == True: # Print the curve as a list of points
for point in self.points:
print(str(point[0].prim_power) + ", " + str(point[1].prim_power), end = "\t")
else: # Print the curve as a polynomial
print(self.form + "(x) = ", end = "")
for i in range(len(self.coefs)):
if type(self.coefs[i]) == int: # Integers
if self.coefs[i] == 0: # Ignore 0 terms unless the curve is 0
continue
if self.coefs[i] == 1 and i == 0: # Only print 1 if it's the constant
print(str(self.coefs[i]), end="")
continue
print(str(self.coefs[i]), end="")
else: # Field elements
if self.coefs[i] == self.field[0]: # Ignore 0 terms unless curve is 0
continue
if (self.coefs[i].prim_power == 1):
if self.field.n > 1:
print("s", end="")
else:
if self.field.n > 1:
print("s" + str(self.coefs[i].prim_power), end="")
else:
print(str(self.coefs[i].prim_power), end="")
if i > 0:
if i == 1:
print(" x", end="")
else:
print(" x" + str(i), end="")
if i != len(self.coefs) - 1:
print(" + ", end = "")
print("")
|
f79f39bfe901c87ae8fdfbaa1b24cbf76bfc20bd | Ngyg520/python--class | /预科/7-12/夜晚作业/字符串方法练习.py | 218 | 3.671875 | 4 | f=open('zfc.txt','r',encoding='utf-8')
for line in f:
list1=line.split('"')
for x in list1:
res=x.startswith('h')
if res==True:
print(x)
else:
continue
f.close()
|
a90ed1ca6f1dd7e673b8b804b655e510da0dbd87 | Ngyg520/python--class | /预科/7-23/函数的参数.py | 1,664 | 3.859375 | 4 | """
座右铭:路漫漫其修远兮,吾将上下而求索
@project:预科
@author:Mr.Yang
@file:函数的参数.PY
@ide:PyCharm
@time:2018-07-23 09:45:55
"""
#1,必备参数(位置参数),实参和形参数量上必须要保持一致
def sum(a,b):
c=a+b
print(c)
sum(1,6)
#2,命名关键字参数:通过定义关键字来获取实参的值,与形参的顺序无关.
def show(name,age):
print('姓名是:%s-年龄是:%s'%(name,age))
show(age=20,name='张三')
#3.默认参数
#使用场景:数据库连接,地址和端口可以设置默认
#使用默认参数的时候,如果给形参传递了实参,则会接受实参的值.如果没有给这个形参传递实参,则形参会采用默认值
def show_one(user='zhangsan',password='123456789'):
print('账号是%s'%user)
print('密码是%s'%password)
show_one('李四','54554')
#4,可变参数(不定长参数)(包括位置参数和关键字参数)
#4-1:位置参数
#形参的数据会根据形参的数量的变换而变化
#*args:接收N个位置参数转化成元组的形式
def show_two(*args):
print(type(args))
print(args)
show_two(1)
show_two(1,2,3)
show_two('曹森')
#4-2:关键字参数
#**kwargs:把N个关键字参数,转化成了字典.
def show_three(**kwargs):
print(type(kwargs))
print(kwargs)
show_three(name='张三',age='20',sex='男')
#尝试写一个函数:把以上所有参数填写进去
def show_all(name,*args,age=20,mother,**kwargs):
print('----',name)
print('===',args)
print('\\\\',age)
print('---',mother)
print('====',kwargs)
show_all('张三',*(10,20),age=34,mother='啊实打实',**{'sex':'女','father':'马云'}) |
1da35e52a93c7f856043ad7dd3cfed3741169d14 | Ngyg520/python--class | /正课/7-25/高阶函数之filter函数.py | 1,253 | 3.734375 | 4 | """
座右铭:路漫漫其修远兮,吾将上下而求索
@project:正课
@author:Mr.Yang
@file:高阶函数之filter函数.PY
@ide:PyCharm
@time:2018-07-25 09:22:58
"""
#filter():用于对一个序列进行过滤或者筛选.
#两个参数:第一个参数:函数,用于设置过滤的内容的逻辑,第二个参数:序列
#返回值也是一个迭代器
#定义一个函数,用于过滤奇偶数
def filter_function(number):
return number%2==1
#filter函数会将序列中每一个元素都传递到函数中执行,在函数中返回True或者false的结果,fileter()函数会根据返回的结果,保留True的元素,过滤掉False的元素
result=filter(filter_function,[1,2,3,4,5,6])
print(result)
for res in result:
print(res,end=',')
#将字符串中的大写的字符过滤掉
#定义一个过滤函数
def filter_upper_char(string):
return string.islower()
result_1=filter(filter_upper_char,'AffgwadfAFS')
print(result_1)
for res in result_1:
print(res,end='.')
#使用lambda函数改造:
result_3=filter(lambda number:number%2==1,[1,2,3,4,5])
print(result_3)
for res in result_3:
print(res,end='-')
result_4=filter(lambda string:string.islower(),'AbcDefG')
print(result_4)
for res in result_4:
print(res,end=',')
|
280d6a67ced86fdb7c8f4004bb891ee7087ad18c | Ngyg520/python--class | /正课第二周/7-30/(重点理解)self对象.py | 1,556 | 4.21875 | 4 | """
座右铭:路漫漫其修远兮,吾将上下而求索
@project:正课第二周
@author:Mr.Yang
@file:self对象.PY
@ide:PyCharm
@time:2018-07-30 14:04:03
"""
class Student(object):
def __init__(self,name,age):
self.name=name
self.age=age
# print('self=',self)
def show(self):
print('调用了show函数')
# print('self=',self)
#self其实本身指代的就是一个对象,这个对象是Student类类型的,self具体指代的是Student哪一个对象,是由Student中的哪一个对象在使用属性或者函数(方法)来决定的
print(Student('张三','20'))
#对象调用中间不能有其他语句，要不每调用一次，就是重新声明，重新声明就是重新分配内存地址
stu =Student('张三','20')
stu.show()
stu_1=stu
print(stu)
print(stu_1)
# stu.show()
stu_one=Student('李四','22')
# stu_one.show()
#对象的内存具有唯一性,两个不同的对象内存是不一样的
#stu和Student('张三','20')之间的关系:
#第一步:当Student('张三','20')执行完毕的时候,实际上已经实例化出来了一个对象,与此同时对象在内存当中已经产生
#第二步:将内存中已经产生的这个对象赋值给了stu这个变量(指针),使用这个变量(指针)来代替Student('张三','20')这个对象来执行函数的调用,属性的调用
#指针是用于指向一个对象的内存地址,方便去操作对象,管理对象.
#一个对象的内存地址可以由多个指针进行指向,但是一个指针只能指向一个对象的内存地址.
|
23b0fbe3cba25c9ef37ddbad2bb345086e63e6be | Ngyg520/python--class | /正课第二周/7-31/对象属性的保护.py | 2,251 | 4.21875 | 4 | """
座右铭:路漫漫其修远兮,吾将上下而求索
@project:正课第二周
@author:Mr.Yang
@file:对象属性的保护.PY
@ide:PyCharm
@time:2018-07-31 09:26:31
"""
#如果有一个对象,当需要对其属性进行修改的时候,有两种方法:
#1.对象名.属性名=属性值------------------>直接修改(不安全)
#2.对象名.方法名( )--------------------->间接修改
#为了更好的保护属性的安全,也就是不让属性被随意的修改,一般的处理方式:
#1,将属性定义为私有属性
#2.添加一个可以调用的方法(函数),通过调用方法来修改属性(还可以在方法中设置一些属性的条件)
class People(object):
#私有属性
def __init__(self,name,age,weight):
#python设置私有属性,需要在属性前加两个_
self.__name=name
self.__age=age
self._weight=weight
#由于私有属性只能在类的内部使用,想要在外部获取私有属性的值,可以通过定义函数来完成
def get_name(self):
return self.__name
#添加修改属性
def set_name(self,name):
if isinstance(name,str):#(属性,限制)
self.__name=name
else:
raise ValueError('name is not"str"type!')
p1=People('张三','20','180')
name=p1.get_name()
print(name)#打印出私有属性
# print(p1.__name)#私有属性无法直接调用
p1.set_name('李四')
print(p1.get_name())#对私有属性进行修改,并且要满足限制"str"
#一般也将_weight这种视为私有属性,不会再类的外部进行访问
print(p1._weight)
#面试题:
#python单_和双_的区别?
#1.__方法名__:内建方法,用户不能这样定义.例如:__init__
#2.__变量名(属性名):全私有属性(变量)/全保护属性(变量).只有类对象自己能访问,子类并不能访问这个属性
#3._变量名(属性名):半保护属性(变量),只有类对象和子类对象能访问到这些变量
#虽然从意义上讲单下划线和双下划线的变量(属性)都属于私有变量(属性),理论上外界不能访问的,但是Python并没有那么严格,仍然是可以强制访问的,因此python的私有仅仅是意义上的私有,只是种规范,可以不遵守
print('强制访问:',p1._People__name) |
cf28d90ba946d4968a7ed1dc0dc538a93d32dc44 | Ngyg520/python--class | /预科/7-11/字典.py | 3,791 | 3.546875 | 4 | #author:yang
#字典:也是 python中内置的一种容器类型.字典是可变的,可以对字典进行增删改查的操作.
#字典有以下特点:
#1,字典是以"键-值"结构来存储数据的,字典照片那个没有索引这个概念,'键':相对于列表中的索引.可以通过键对一个数据进行增删改查.
#2,列表中的索引值是唯一的,键也是唯一的,都不允许重复.
#3,字典是无序的,'键-值'对的存储没有先后顺序,只需要一个键对应一个值.
#声明一个空字典
dict1={}
#声明一个非空字典
#键:adc,辅助,打野,中单,上单
#值:uzi,ming,mlxg,小虎,letme
dict2={'adc':'uzi','辅助':'ming','打野':'mlxg','中单':'xiaohu','上单':'letme'}
#计算内存中,True-1,False-0.1和True,0和False不能同时为字典中的键,同时存在会产生冲突
#列表和字典都不能当键,元组可以,是因为通常情况下,键不可变,而列表可变,元组不可变.
dict3={True:'true',(1,2,3):'(1,2,3)'}
print(dict3)
#------------------------------添加数据------------------------------
#数据的时候,要指定一个键,并且要给该键赋一个值.
dict2['替补']='karsa'
print(dict2)
#-----------------------------查询数据-------------------------------
name=dict2 ['adc']
print(name)
name1=dict2['辅助']
print(name1)
#------------------------------常用的函数-----------------------------------
dict4={'name':"张三",'age':20,'sex':'男'}
#P.get():根据键获取对应的值,如果字典中不存在这个键,则默认采用后面的默认值.如果存在该键,则直接取字典中的值
#get()函数:第一个参数:键 第二个参数:默认值
res=dict4 .get('name','李四')
print('----',res)
res1=dict4.get('height','170')
print(res1)
#2,items():将字典中的每一个键值对设置成元组的形式,并且存储在列表之中
res2=dict4.items()
print(res2)
#字典第一种遍历方式
for key,value in dict4 .items():
print(key,value)
#字典第二种遍历方式,只取键,不取值.相当于遍历键(name,age,sex)
for key,value in enumerate(dict4):
print('====',key,value)
#3.keys()取出字典中的所有的键并存放在列表中.
res3=dict4.keys()
print(res3)
#4.values:取出字典中所有的值并存放在列表中.
res4=dict4.values()
print(res4)
#5,pop():根据键删除字典中的值,返回的结果是删除的这个键对应的值
res5=dict4.pop('sex')
print(res5)
#6.setdefault():根据键获取对应的值,如果存在该键,则直接获取字典中的值.如果字典中不存在这个键,则采取后面默认的值.并且将该键与值加入到原始字典中.
dict5={'name':'麻子','age':21,'sex':'女'}
res6=dict5.setdefault('name','王二')
print('-----',res6)
res7=dict5.setdefault('height',180)
print('====',res7)
print(dict5)
#7.popitem():随机返回并删除字典中的一对键值对(一般会删除末尾的键值对),返回值是一个被删除的键值对组成的元组
res8=dict5.popitem()
print('被删除的',res8)
print(dict5)
#8.fromkeys():生成一个字典,第一个函数是键,第二个参数是值,如果第一个参数填写的是可迭代对象,则会将对象中的每一个元素拆分成一个元素当做键,并且对应的值都为第二个参数
dict6=dict.fromkeys('12',[1,2])
print(dict6)
dict7=dict.fromkeys('1','hhh')
print(dict7)#老师说10年用不上一次
#9.update():用于将一个字典添加到另一个字典中.
dict8={'射手':'iboy','辅助':'meiko'}
dict9={'打野':'7酱','中单':'scount','上单':'ray'}
dict8.update(dict9)
#10.判断一个键是否在一个字典中
if '射手' in dict8 :
print('存在射手这个键')
#11.clear():清除所有键值对
dict8.clear()
print(dict8)
#12.del:根据键删除字典中的值
dict10={'name':'张三'}
del dict10 ['name']
print(dict10)
|
a62a4f8dfa911c1f3bde259e14efe019c5b7ddc1 | Ngyg520/python--class | /预科/7-23/生成器函数.py | 1,580 | 4.125 | 4 | """
座右铭:路漫漫其修远兮,吾将上下而求索
@project:预科
@author:Mr.Yang
@file:生成器函数.PY
@ide:PyCharm
@time:2018-07-23 14:34:00
"""
#生成器函数:当一个函数带有yieid关键字的时候,那么他将不再是一个普通的函数,而是一个生成器generator
#yieid和return;这俩个关键字十分的相似,yieid每次只返回一个值,而return则会把最终的结果一次返回
#每当代码执行到yieid的时候就会直接将yieid后面的值返回出,下一次迭代的时候,会从上一次遇到yieid之后的代码开始执行
def test():
list1=[]
for x in range (1,10):
list1.append(x)
return list1
res=test()
print(res)
def test_1():
for x in range (1,10):
yield x
generator=test_1()
print(generator)
print(next(generator))
print(next(generator))
print(next(generator))
#生成器函数的例子:母鸡下蛋
#1,一次性把所有的鸡蛋全部下下来.
#如果一次把所有的鸡蛋全部下下来,一是十分占地方,而是容易坏掉.
def chicken_lay_eggs():
#鸡蛋筐列表
basket=[]
for egg in range (1,101):
basket.append(egg)
return basket
eggs =chicken_lay_eggs()
print('一筐鸡蛋:',eggs)
#这样做的好处:第一是省地方,第二是下一个吃一个,不会坏掉
def chicken_lay_eggs_1():
for egg in range(1,101):
print('战斗母鸡正在下第{}个蛋'.format(egg))
yield egg
print('我把第{}个蛋给吃了!'.format(egg))
eggs_1=chicken_lay_eggs_1()
print(next(eggs_1))
print(next(eggs_1))
print(next(eggs_1)) |
d5a6aea9ce496970111d058fa130c14d4d318c31 | Ngyg520/python--class | /预科/7-11/晚间复习.py | 3,317 | 4.03125 | 4 | #列表,元组,字典
list=[]
tuple=(20,1,3,5)
dict={}
set1=set()
#-----------添加数据-------------
list.append('李四')
print(list)
list.insert(0,'张三')
print(list)
dict['A']='阿罗多姿'
print(dict)
set1.add(1)
print(set1)
#---------查询数据------------
name=list[0:2]
print(name)
name1=list[:]
print(name1)
name2=list[-1]
print(name2)
for x in list:
print('---',x)
for y in range (0,len(list)):
print('==',list[y])
for y in range (0,len(list)):
print('==',y)
#枚举函数
for index,value in enumerate(list):
print(index,value)
a = tuple[0]#按索引查询
print(a)
b= tuple [0:1]
print(b)
for z in range(0,len(tuple)):#按索引值列举所有
print(tuple[z])
for e in tuple:#直接列举所有
print(e)
for index,value in enumerate(tuple):#枚举列举
print(index,value)
name= dict['A']#按键查询
print(name)
#-------------------------修改数据------------------
list[0]='王五'#根据索引修改列表的值
print(list)
dict[1]='wangbadan'#字典添加键值对
print(dict)
res2=dict.pop('A')#根据键删除数据
print('---',dict)
tuple1=('多','来','米','发',[('锁','拉')],'西')#元组无法对一级值进行修改添加,可对二级进行
res=tuple1[4][0]
print(res)
tuple1[4][0]=('王八蛋')#对元组进行修改
print(tuple1)
#-----------------------常用函数-------------------
num=list.count('李四')#统计值出现的次数
print(num)
num1=list.index('王五')#显示值的索引
print(num1)
list.reverse()#将列表进行反转
print(list)
list1=['武器','安妮']
list.extend(list1)#合并列表
print(list)
list.clear()#清空列表所有值
print(list)
while len(list):#使用循环删除列表中所有的元素
del list[0]
print('---',list)
list2=['剑圣','剑姬','巨人','剑魔']
del list2[0]#根据索引值删除值
print(list2)
list2.pop(1)#根据索引值删除值
print(list2)
list2.pop()#默认删除最后的值
print(list2)
list2.remove('剑姬')#直接删除填写的元素,如果存在多个,则默认删除第一个符合条件的
print(list2)
sex=tuple.count(20)#统计次数
print(sex)
sex1=tuple.index(20)#打印列表元素的索引值,存在多个,则默认打印第一个元素的索引值
print(sex1)
dict2={'name':"张三",'age':20,'sex':'男'}
#get():根据键获取对应的值,如果字典中不存在这个键,则默认采用后面的默认值.如果存在该键,则直接取字典中的值
sex2=dict2.get('name','李四')
print(sex2)
sex3=dict2.get('height',150)
print(sex3)
#items():将字典中的每一个键值对设置成元组的形式,并且存储在列表之中
sex4=dict.items()
print(sex4)
#字典第一种遍历
for key, value in dict2.items():
print(key,value)
#第二种遍历
for key ,value in enumerate(dict2):
print(key,value)
#打印出来的是删除的键对应的值
sex5=dict2.pop('name')
print(sex5)
#setdefault():根据键获取对应的值,如果存在该键,则直接获取字典中的值.如果字典中不存在这个键,则采取后面默认的值.并且将该键与值加入到原始字典中.
sex6=dict2.setdefault('age','19')
print(sex6)
#fromkeys():生成一个字典,第一个函数是键,第二个参数是值
dict3=dict.fromkeys('1',[3])
print(dict3)
print(dict2)
#update():用于将一个字典添加到另一个字典中
dict2.update(dict3)
|
a7b4bb3d047da001a63dbc9560a84a4542d2a8ea | Ngyg520/python--class | /正课第二周/7-31/类的多继承.py | 659 | 3.734375 | 4 | """
座右铭:路漫漫其修远兮,吾将上下而求索
@project:正课第二周
@author:Mr.Yang
@file:类的多继承.PY
@ide:PyCharm
@time:2018-07-31 16:10:38
"""
#定义一个A类
class A(object):
def print_test(self):
print('A类')
class B(object):
def print_test(self):
print('B类')
class C(A,B):
def print_test(self):
print('C类')
#面试题:
#在上面多继承的例子中,如果父类A,B都有一个同名的方法,name通过子类调用的时候,会调用哪一个?
obj_c=C()
obj_c.print_test()
#先调用自己的类,再调用父类
print(C.__mro__)#可以查看C类的对象搜索方法时的先后顺序
|
27f8780f3f00118b1d34db5b2c593f2bc802b28f | Ngyg520/python--class | /正课第二周/7-31/类的单继承.py | 2,148 | 3.96875 | 4 | """
座右铭:路漫漫其修远兮,吾将上下而求索
@project:正课第二周
@author:Mr.Yang
@file:类的单继承.PY
@ide:PyCharm
@time:2018-07-31 15:43:05
"""
#面向对象编程的三个基本特征:封装,继承,多态
#函数是封装的最基本单位,而类和对象属于更高级的封装形态,在类中封装用于保存数据,也可以在类中封装函数用于操作数据,不同的功能和逻辑又可以封装成不同的函数
#继承:
#继承的优势:可以更好的实现代码的重用
#1.子类可以继承父类,子类会拥有父类中所有的属性,子类不需要重复声明,父类的对象是不能够调用子类的属性和方法的,这种继承属于单项继承
#2.当父类当中的属性和函数不符合子类需求的时候,子类可以重写父类的属性和方法,或者自定义一些新的方法
#object是所有类的父类(根类,基类)
#Animal类是object的子类,object是Animal的父类
#如果一个类没有特别指定父类,一般都是继承于object
class Animal(object):
def __init__(self,name,age,sex):
self.name=name
self.age=age
self.__sex=sex
def run(self):
print('跑')
def eat(self):
print('吃')
def __sleep(self):
print('睡')
#声明一个狗类继承于Animal
class Dog(Animal):
def wangwang(self):
print('叫')
an=Animal('gou','20','公')
print(an.name)
print(an.age)
# print(an._Animal__sex)
an.run()
an.eat()
# an.wangwang()
#Dog类中,虽然并没有声明__init__这个初始化函数,但是由于Dog类继承于Animal类,所以,Dog类中的对象也去执行了Animal的初始化函数,才创建Dog类对象的时候,必须指定__init__函数中的实参
dog=Dog('藏獒','8','母')
print(dog.name)
print(dog.age)
dog.run()
dog.eat()
# print(dog._dog__sex)
#dog._Dog__sleep()
#总结:
#1.私有属性,不能通过对象直接访问,但是可以通过设置方法(函数)访问
#2.父类中的私有属性,私有方法,不会被子类继承,也不能被访问(可以强制访问)
#3.一般情况下,私有属性还有私有方法,是不可以被外部所访问的(强制访问除外) |
b8a2c3747c37ee4d7ad47a35a006009c65639132 | Abhishek-Bajpai/hackerrank | /exepy.py | 120 | 3.5625 | 4 |
def gcd(a,b):
while( b!=0):
temp = a
a = b
b = temp % b
return a
print(gcd(60, 96))
|
4aa5b7924d8f7d10a1ec7f7c7b1c1a41a9996665 | Lyndondshelton/Cryptographic-System | /Encoder.py | 4,935 | 3.59375 | 4 | import math
import numpy as np
#
# Initialization of the encryption and decryption dictionaries. alpha_encrypt will return the value of a letter,
# alpha_decrypt will return the letter associated with a value.
#
alpha_encrypt = {' ': 0, 'A': 3, 'B': 6, 'C': 9, 'D': 12, 'E': 15, 'F': 18, 'G': 21, 'H': 24, 'I': 27, 'J': 30, 'K': 33,
'L': 36, 'M': 39, 'N': 42, 'O': 45, 'P': 48, 'Q': 51, 'R': 54, 'S': 57, 'T': 60, 'U': 63, 'V': 66,
'W': 69, 'X': 72, 'Y': 75, 'Z': 78, ',': 81, '.': 84, '?': 87, '!': 90, "'": 93, '-': 96, '0': 99,
'1': 102, '2': 105, '3': 108, '4': 111, '5': 114, '6': 117, '7': 120, '8': 123, '9': 126}
alpha_decrypt = {0: ' ', 3: 'A', 6: 'B', 9: 'C', 12: 'D', 15: 'E', 18: 'F', 21: 'G', 24: 'H', 27: 'I', 30: 'J', 33: 'K',
36: 'L', 39: 'M', 42: 'N', 45: 'O', 48: 'P', 51: 'Q', 54: 'R', 57: 'S', 60: 'T', 63: 'U', 66: 'V',
69: 'W', 72: 'X', 75: 'Y', 78: 'Z', 81: ',', 84: '.', 87: '?', 90: '!', 93: "'", 96: '-', 99: '0',
102: '1', 105: '2', 108: '3', 111: '4', 114: '5', 117: '6', 120: '7', 123: '8', 126: '9'}
#
# Initialization of the Matrix encryption key. MATRIX_KEY is final and should not be changed.
#
MATRIX_KEY = [
[2, 3, 6, 7],
[1, 4, 5, 2],
[6, 7, 3, 2],
[9, 10, 2, 3]
]
#
# Initialization of the empty matrices.
#
Y = [] # The encryption matrix that will hold the values of the message
ENC = [] # The encrypted matrix. ENC = Y * MATRIX_KEY
DEC = [] # The decrypted matrix. DEC = ENC * inv_matrix_key
string = input("Enter a message: ").upper() # Get the message as input from the user
#
# Row and Column configuration.
#
x_rows = len(MATRIX_KEY) # The number of rows in MATRIX_KEY
x_cols = len(MATRIX_KEY[0]) # The number of columns in MATRIX_KEY
y_rows = math.ceil(len(string) / x_rows) # The number of rows needed for matrix Y to fit the length of the string
y_cols = x_rows # The number of columns in matrix Y needs to be equal to the number of rows in MATRIX_KEY
entries_in_y = y_rows * x_cols # The number of total entries in matrix Y
CAESAR_KEY = x_rows * (alpha_encrypt['B'] - alpha_encrypt['A']) # The key used for the caesar cipher. CAESAR_KEY is final and should not be changed.
max_value = alpha_encrypt['9'] + CAESAR_KEY # The largest possible value of a character in the alphabet
#
# Encrypt the message by using the caesar cipher then the encryption matrix Y
#
# return ENC
#
def encryption(s):
# Caesar cypher initialization. Increment the values of alpha_encrypt by 3, creating a caesar cipher.
for x in alpha_encrypt:
alpha_encrypt[x] = (alpha_encrypt[x] + CAESAR_KEY) % max_value
# While the number of characters in s is less than the number of entries in ENC, create spaces to fill the gaps.
while len(s) < entries_in_y:
s = s + ' '
# For the number of characters in s, place the value of each character in their proper places in Y.
char_count = 0
for i in range(y_rows):
Y.append([])
for j in range(y_cols):
Y[i].append(alpha_encrypt[s[char_count]])
char_count += 1
# Matrix multiplication on Y * MATRIX_KEY = ENC
for i in range(len(Y)):
ENC.append([])
for j in range(len(MATRIX_KEY[0])):
e = 0
for c in range(len(MATRIX_KEY)):
e += Y[i][c] * MATRIX_KEY[c][j]
ENC[i].append(e)
return ENC
#
# Decrypt the message from the ENC matrix, using the INV_MATRIX_KEY and the caesar_key.
#
# return decrypted_message
#
def decryption(enc_mat):
# Initialization of the MATRIX_KEY inverse
inv_matrix_key = np.linalg.inv(MATRIX_KEY)
# Initialization of the decrypted message
decrypted_message = ''
# Matrix multiplication on enc_mat * INV_MATRIX_KEY = D
for i in range(len(enc_mat)):
DEC.append([])
for j in range(len(inv_matrix_key[0])):
d = 0
for c in range(len(inv_matrix_key)):
d += enc_mat[i][c] * inv_matrix_key[c][j]
DEC[i].append(round(d))
# For each of the values in DEC, use the caesar_key to find the original values and decrypt the message
for i in range(len(DEC)):
for j in range(len(DEC[0])):
DEC[i][j] = (DEC[i][j] - CAESAR_KEY) % max_value
decrypted_message += alpha_decrypt[DEC[i][j]]
return decrypted_message
# The following lines will encrypt the string and print the encrypted matrix ENC to the screen, then decrypt ENC and
# print the decrypted matrix DEC and the original message to the screen.
print("\nThe Encrypted Matrix(ENC): {}\n".format(encryption(string)))
message = decryption(ENC)
print("The Decrypted Matrix(DEC): {}".format(DEC))
print("The decrypted message: {}".format(message))
|
9e57dbd5a0eb34bd3ed3567b5c83fd2cfed10ebc | Psami-wondah/shiiiiii | /atm shii.py | 1,383 | 3.78125 | 4 | from datetime import datetime
now = datetime.now()
currentDt = now.strftime("%d/%m/%Y %H:%M:%S")
allowedUsers = ['Seyi', 'Sam', 'Love']
allowedPassword = ['passwordSeyi', 'passwordSam', 'passwordLove']
Balance = 0
name = input('What is your name? \n')
if name in allowedUsers:
password = input('Your password \n')
userId = allowedUsers.index(name)
if password == allowedPassword[userId]:
print(currentDt)
print('Welcome ', name)
print('These are the available options:')
print('1. Withdrawal')
print('2. Cash Deposit')
print('3. Complaint')
selectedOption = int(input('Please select an option \n'))
if selectedOption == 1:
withdrawalAmount = int(input('How much would you like to withdraw? \n'))
print('Take your cash')
elif selectedOption == 2:
depositAmount = int(input('How much would you like to deposit \n'))
Balance = Balance + depositAmount
print('Your balance is:', Balance)
elif selectedOption == 3:
issue = input('What issue will you like to report? \n')
print('Thank you for contacting us')
else:
print('Invalid option selected, please try again')
else:
print('Password incorrect please try again')
else:
print("Name not found please try again")
|
607d083c65f3d595701c5b185fa55e87f4f78cc5 | Prasannarajmallipudi/Python_ToT_2019 | /gcdnumber.py | 314 | 3.890625 | 4 | #from math import gcd
#print(gcd(20, 8))
a = int(input('Please input the First Number:'))
b = int(input('Please input the Second Number:'))
while b != 0:
gcd = b
b = a % b
a = gcd
print(gcd)
'''
for i in range(1,b+1):
if a % i == 0 and b % i == 0:
gcd = i
print(gcd)'''
|
9a303764d51699ab237fe658e66a4e498b57df8c | greg-dry/BlackJack | /blackjack.py | 4,943 | 3.796875 | 4 | import random
import math
suits = ('Hearts', 'Diamonds', 'Spades', 'Clubs')
ranks = ('Ace','Two', 'Three', 'Four', 'Five', 'Six', 'Seven', 'Eight', 'Nine', 'Ten', 'Jack', 'Queen', 'King')
values = {'Ace': 1, 'Two': 2, 'Three': 3, 'Four': 4, 'Five': 5, 'Six': 6, 'Seven': 7, 'Eight': 8, 'Nine': 9, 'Ten': 10, 'Jack': 10, 'Queen': 10, 'King': 10}
class Card:
def __init__(self, rank, suit):
self.rank = rank
self.suit = suit
self.value = values[rank]
def __str__(self):
return f'{self.rank} of {self.suit}'
class Deck(Card):
def __init__(self):
self.all_cards = []
for suit in suits:
for rank in ranks:
self.all_cards.append(Card(rank, suit))
def shuffle(self):
random.shuffle(self.all_cards)
def remove_card(self):
return self.all_cards.pop(0)
class Player(Deck, Card):
def __init__(self, balance):
self.balance = balance
self.my_cards = []
self.values = []
def __str__(self):
return f"You have ${self.balance}."
def player_hit(self, new_card):
self.my_cards.append(new_card)
self.values.append(new_card.value)
def make_a_bet(self):
print(myplayer)
while True:
try:
bet = int(input('Make a bet: '))
except:
print('invalid input')
else:
if bet > self.balance:
print('You do not have the funds in your balance to make that bet')
else:
new_balance = self.balance - bet
print(f"You now have ${new_balance}")
break
class Dealer(Deck):
def __init__(self):
self.dealer_cards = []
self.dealer_values = []
def dealer_hit(self, new_card):
self.dealer_cards.append(new_card)
self.dealer_values.append(new_card.value)
mydeck = Deck()
myplayer = Player(balance = 100)
mydealer = Dealer()
print('Welcome to BlackJack')
while True:
try:
play_choice = int(input("do you want to play? Enter 1 for Yes, 2 for No: "))
except:
print('Invalid answer')
else:
break
if play_choice == 1:
print("Ok let's play!")
game_on = True
else:
print("Goodbye")
game_on = False
mydeck.shuffle()
top_card = mydeck.remove_card()
myplayer.player_hit(top_card)
def game_play():
while game_on == True:
myplayer.make_a_bet()
break
print(f"Your card is {myplayer.my_cards[0]}")
players_turn = True
while players_turn == True:
try:
hit_choice = int(input("Would you like to hit? Enter 1 for Yes, 2 for No: "))
except:
print('invalid answer')
else:
if hit_choice == 1:
top_card = mydeck.remove_card()
myplayer.player_hit(top_card)
print(f"Your card is {myplayer.my_cards[-1]}")
player_current_value = sum(myplayer.values)
print('your current hand value is ' + str(player_current_value))
if player_current_value > 21:
print('You went over 21, game over')
break
elif player_current_value == 21:
print('you won!')
break
else:
pass
else:
player_current_value = sum(myplayer.values)
print('your current hand value is ' + str(player_current_value))
print('It is now the dealers turn')
top_card = mydeck.remove_card()
mydealer.dealer_hit(top_card)
print(f"The dealer's card is {mydealer.dealer_cards[0]}")
dealer_wins = False
while dealer_wins == False:
top_card = mydeck.remove_card()
mydealer.dealer_hit(top_card)
print(f"The dealer's card is {mydealer.dealer_cards[-1]}")
dealer_current_value = sum(mydealer.dealer_values)
print('Dealers current hand value is ' + str(dealer_current_value))
if dealer_current_value > 21:
print('Dealer went over 21, you win!')
dealer_wins = True
players_turn = False
elif dealer_current_value > player_current_value and dealer_current_value <= 21:
print('dealer has higher hand, you lose.')
dealer_wins = True
players_turn = False
else:
pass
game_play()
|
524b33b034b850a6ef1a8bcc9c5f6c321bb76ccb | skydeamon/Pre-Bootcamp-Coding-Challenge | /Task3.py | 345 | 3.765625 | 4 | """
Created on 11/04/2020
@author: SkyCharmingDeamon
_Umuzi_
Pre-bootcamp challenges tast 3: functions
A function that takes 2 numbers as input. If either of the numbers is 65, OR if the sum of the numbers is 65 then return true. Otherwise return false,
"""
def function(a,b):
return (a == 65 or b == 65 or (a + b) == 65)
|
f2f85ec9808c7dedfb4d7d11215aa37e3a5c0de4 | AnikaitSahota/Naive-Bayes-classifiers | /Codes/Matrix.py | 3,918 | 4.1875 | 4 | """
Author : Anikait Sahota
Status : no error
Dated : 21 March 2019
"""
def matrix_multiplication(a,b):
""" function to multiply matrix a with matrix b -> aXb
Arguments:
a and b are two dimensional matrices """
if len(a[0])!=len(b): # if number of columns of matrix a == number of rows of matrix b
return(False) # these matrices can't be multiplied hence False
tmp_k=len(b)
m_a=len(a) #number of rows
n_b=len(b[0]) #number of columns
result=[[None for i in range (n_b)] for i in range (m_a)] #creating matrix with dimensions of resultanst matrix
for i in range (m_a):
for j in range (n_b):
sum=0
for k in range (tmp_k):
sum+=a[i][k]*b[k][j]
result[i][j]=float(sum)
return(result)
def transpose(a):
""" function to return transpose of 'a' matrix
Arguments:
a is the input matrix """
m = len(a) # numner of rows in given matrix
n = len(a[0]) # number of columns in given matrix
result = [[None for i in range (m)] for j in range (n)] #creating a matrix while swaping the number of rows with number of columns
for i in range(m) : # for loop to assign values to result matrix
for j in range(n):
result[j][i] = a[i][j]
return(result) # returning the matrix
def determinent(a):
""" function to return determinent of the given matrix a using the recursiion
Argument:
a is the input square matrix to find determinent"""
n = len(a)
if(n == 1): # base case for 1X1 square matric
return a[0][0] ;
elif(n == 2): # base case for 2X2 square matrix
return(a[0][0]*a[1][1] - a[0][1]*a[1][0])
else: # for all cases above 2X2
result = 0 # resultant determinent
tmp_matrix = [[None for i in range (n-1)]for j in range (n-1)] # matrix with (n-1)X(n-1) dimensions for recursion
for i in range (n):
for j in range (n): # loop for assigning the value to (n-1)X(n-1) square matrix
temp_index = 0
for k in range (n):
if(k != i and temp_index < n and j>0):
tmp_matrix[j-1][temp_index] = a[j][k]
temp_index += 1
result += ((-1)**(i))*(a[0][i])*determinent(tmp_matrix) # calculating the determinent
return result # returning the determinent value
def Adjoint(a):
""" fuction to find adjoint of a matrix and return it
Argument:
a is the input matrix"""
n = len(a) # number of columns and rows of square matrix
result = [[None for i in range (n)]for j in range(n)]
if(n == 1): # base case for 1X1 matrix
result[0][0] = 1
elif(n == 2): # base case for 2X2 matrix
result[0][0] = a[1][1]
result[0][1] = -1*a[0][1]
result[1][0] = -1*a[1][0]
result[1][1] = a[0][0]
""" it converts matrix
| a b | --> | d -b |
| c d | | -c a | """
else:
tmp_matrix = [[None for i in range (n-1)]for j in range (n-1)] # tempararory matrix for finding determinent
for i in range (n): # for loop for result matrix
for j in range (n): # for loop for result matrix
tmp_i = 0
for k in range (n): # for loop for formig determinent matrix
tmp_j = 0
for l in range (n): # for loop for forming determinent matrix
if(k != i and l != j):
tmp_matrix[tmp_i][tmp_j] = a[k][l]
tmp_j += 1
if(tmp_j == n-1):
tmp_i += 1
result[j][i] = ((-1)**(i+j))*determinent(tmp_matrix) # used (j,i) instead of (i,j) to form transpose
return result # returning the Adjoint matrix of a
def inverse(a) :
""" function to find inverse of a matrix
return inverse of matrix if possible othervise Fasle
Arguments:
a is the input matrix """
det = determinent(a) # finding determinent of matrix 'a'
if(det == 0): # if det == 0 hence it is singular matrix , inverse not possible
return False
Adj = Adjoint(a) # finding Adjoint of matrix
if(det != 1):
for i in range (len(a)): # for loop Adj(a)/det(a)
for j in range (len(a)):
Adj[i][j] /= det
return Adj # returning the inverse of matrix 'a'
a = [['Ab','Cd'],['Ef','Gh']]
#print(transpose(a)) |
a86010ff291698cf14382ff1bfd77c3a1aaf3617 | kkyoung28/Programming-Python- | /Function2.py | 3,547 | 3.6875 | 4 | #p107~109
import random
# def rolling_dice():
# n=random.randint(1, 6)
# print("6면 주사위 굴린 결과 : ",n) #1<=n<=6 랜덤수
# def rolling_dice(pip):
# n=random.randint(1,pip)
# print(pip, "면 주사위 굴린 결과 : ",n) #1<=n<=pip 랜덤
def rolling_dice(pip, repeat):
for r in range(1, repeat+1):
n = random.randint(1,pip)
print(pip, "면 주사위 굴린 결과 ",r, ":" ,n) #1<=n<=pip 랜덤
rolling_dice(6, 1)
rolling_dice(6, 2)
rolling_dice(12, 0)
rolling_dice(20, -3)
#p109
def star():
print("*****")
star() #*****
star() #*****
star() #*****
#p113
print("핱")
print("핱","읖")
print("핱","읖","큷")
print("핱","읖","큷","슾")
print("핱","읖","큷","슾","별")
#p114
# def p(*args):
# string=""
# for a in args:
# string += a
# print(string)
# p("핱")
# p("핱","읖")
# p("핱","읖","큷","슾")
#p114
def p(space, space_num,*args):
string=args[0]
for i in range(1, len(args)):
string +=(space * space_num)+args[i]
print(string)
p(",",3,"핱","읖")
p("별",2,"핱","읖","큷")
p("_",3,"핱","읖","큷","슾")
#p115
def star2(ch, *nums):
for i in range(len(nums)):
print(ch * nums[i])
star2("읖", 3) #읖읖읖
star2("핱",1,2,3) #핱
#핱핱
#핱핱핱
#p116
def fn(a,b,c,d,e):
print(a,b,c,d,e)
fn(1,2,3,4,5)
fn(10,20,30,40,50)
fn(5,6,7,8,9)
fn(a=1, b=2,c=3,d=4,e=5)
fn(e=5, d=4, c=3, b=2, a=1)
fn(1, 2, c=3, e=5, d=4)
#fn(d=4, e=5, 1, 2, 3) #에러
#p118
#***__***
#***__***
#***__***
def star3(mark, repeat, space, space_repeat, line):
for _ in range(line):
string= (mark*repeat)+(space*space_repeat)+(mark*repeat)
print(string)
star3("*", 3, "_", 2, 3)
#p119
def hello(msg="안녕하세요"):
print(msg+"!")
hello("하이")
hello("hi")
hello()
#p120
def hello2(name, msg="안녕하세요"):
print(name+"님, "+msg+"!")
hello2("김가영", "오랜만이에요")
hello2("김선옥")
#hello2() #에러 name 인자 없음
def fn2(a, b=[]):
b.append(a)
print(b)
fn2(3) #[].append(3) => [3]
fn2(5) #[].append(5) => [5]:x [3,5]:o
fn2(10) #[3, 5, 10]
fn2(7, [1]) #[3, 5, 10, 1, 7]:x vs [1, 7]:o
#fn2(a=7, b=[1]):
#print([1].append(7))
#p123
def gugudan(dan=2):
#1~9 i
for i in range(1, 9+1):
#print(dan, "X",i, "=", dan*i)
print(str(dan)+"x"+str(i)+"="+str(dan*i))
gugudan(3) #3단 출력
gugudan(2) #2단 출력
gugudan() #2단 출력
#p125
def sum(*numbers):
sum_value=0
for number in numbers:
sum_value += number
return sum_value
print("1 + 3 =", sum(1, 3))
print("1 + 3 + 5 + 7=", sum(1, 3, 5, 7))
def min(*numbers):
min_value=numbers[0]
for number in numbers:
if min_value > number:
min_value = number
return min_value
print("min(3, 6, -2)=", min(3, 6, -2))
def max(*numbers):
max_value=numbers[0]
for number in numbers:
if max_value < number:
max_value = number
return max_value
print("max(8, 1, -1, 12) =", max(8, 1, -1, 12))
def multi_num(multi, start, end):
result = []
for n in range(start, end):
if n % multi == 0:
result.append(n)
return result
print("multi_num(17, 1, 200)=",multi_num(17, 1, 200))
print("multi_num(3, 1, 100)=",multi_num(3, 1, 100))
def min_max(*args):
min_value = args[0]
max_value = args[0]
for a in args:
if min_value > a:
min_value = a
if max_value < a:
max_value = a
return min_value, max_value
min, max = min_max(52, -3, 23, 89, -21)
print("최솟값", min, "최댓값:", max)
|
85012bb061be955cb0e30489928b014f2b3f1053 | RussH-code/Forest-Fire-Simulation | /sims.py | 19,935 | 3.53125 | 4 | """
This module contains: simulation(), simulation_combine() and sim_plot(). The simulation and simulation_combine functions run the forest fire simulation. The simulation function only changes one parameter at a time, this is useful for studying the effect of one parameter on the function. The simulation_combine function can take values to change both the lightning and new tree growth probabilities, this is useful for looking at the effect of changing both these parameters. The sim_plot is used for creating graphs of these simulations: a line graph showing the changing proportion of trees on fire and alive trees, and a dynamic bar chart representing the number of cells in the grid that are empty, on fire or alive.
"""
#Import all the needed modules
from animation import animate, animate_with_rain
from setup import initialise, init, reset, initialise_with_rain
import config
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from IPython.display import HTML
def simulation(parameter, sim_values, times = 1, GRID_HEIGHT = config.GRID_HEIGHT, GRID_WIDTH = config.GRID_WIDTH, lightning = config.lightning, tree_growth = config.tree_growth, frame_num = config.frame, cloud_th = config.cloud_th, rain = False):
"""
Runs forest fire simulation for a parameter over the specified values for specified number of times.
Note: the parameters that are not changed will be run as specified in config.py so this should be checked before running
Args:
parameter : (int) the parameter to be changed in the simulation
0 = tree_growth
1 = lightning
2 = GRID_HEIGHT and GRID_WIDTH
3 = rain
sim_values : (numpy ndarray) a 1D array corresponding to the probabilities/values of the parameter(s) to be used in simulation
times : (int) number of times to repeat the simulation, defaults to 10
GRID_HEIGHT (int): The grid height, default value set in the config
GRID_WIDTH (int): The grid width, default value set in the config
lightning (float): The probability that lightning, default value set in the config
tree_growth (float): The probability that a new tree, default value set in the config
frame_num (int): The number of frames to run the simulation
rain (boolean): If true, the simulation will be run with the effect of rain, defaults to false
Returns:
mean_remaining_trees : (list) a list of floats containing the mean values of the remaining number of trees
one mean value is returned for each value in sim_values
mean_last_frame : (list) a list of floats containing the mean values of the last frame number
one mean value is returned for each value in sim_values
Raises:
ValueError: If any of the arguments are of the correct type but not a valid value
TypeError: If any of the arguments are not of the correct data type
"""
#Checks the number of the times argument is above 0
if times <= 0:
raise ValueError("Number of times must be at least 1!")
#Checks the simulation values are stored in a numpy array
elif (type(sim_values) != np.ndarray):
raise TypeError("Invalid simulation value type, only accepts 1D numpy array!")
#Checks there is at least one value in the values for the testing
elif (sim_values.size <= 0 ):
raise ValueError("Must have at least one value in simualation values!")
#Checks the paramater value is valid (either 0, 1, 2 or 3)
elif (parameter > 3 or parameter < 0):
raise ValueError("Invalid parameter values, see documentation.")
#Check the grid height and width are positive and probabilities of lightning and tree growth are between 0 and 1.
elif (GRID_HEIGHT <= 0 or GRID_WIDTH <= 0 or lightning > 1 or lightning < 0 or tree_growth > 1 or tree_growth < 0):
raise ValueError("Invalid values!")
#If parameter is 3 (simulating rain) and rain is false, raises an error,
elif (parameter == 3 and rain == False):
raise ValueError("Conflicting rain argument!")
#If the frame number is smaller than 1, raise an error
elif(frame_num < 1):
raise ValueError("Invalid frame number, frame number must be at least 1!")
#Creates two empty arrays
#This first array will store the proportion of the grid that are still alive trees for each value in the parameter. A mean is taken for
#each value.
mean_remaining_trees = []
#This array will store the value of the last frame. This is either the frame the simulation has burnt out at or the max frame number as
#previously set. A mean is taken for each value.
mean_last_frame = []
#Iterate over each value in the simulation values so each one is tested.
for param in list(sim_values):
#Set empty list for this value
#This array will store the proportion of the grid that are still trees in each simulation for one value when the simulation has
#ended. This can either be ending by the grid burning out or the max number of frames is reached.
remaining_trees_per_sim = []
#This array will store the number of the last frame that the simulation ends on. This can either be when the simulation burns out
#or when the max number of frames has ended.
last_frame_per_sim = []
#Repeat this simulation the number of times set as specified in the "times" argument
for time in range(times):
#Reset the variables in config.py
reset()
#Change the frame number and last_frame in config.py
config.frame = frame_num
config.last_frame = frame_num
#If rain effect is not activated
if(rain == False):
#Checks which parameter is to be tested and sets the appropriate parameter.
#If it is 0: in the initialize function set tree growth to be the value in the list
if (parameter == 0):
fig = initialise(tree_growth = param, GRID_HEIGHT = GRID_HEIGHT, GRID_WIDTH = GRID_WIDTH, lightning = lightning)
#If it is 1: in the initialize function set to lightning to be the value in the list
elif (parameter == 1):
fig = initialise(lightning = param, GRID_HEIGHT = GRID_HEIGHT, GRID_WIDTH = GRID_WIDTH, tree_growth = tree_growth)
#If it is 2: in the initialize function set it to grid height and width
#Note: as this grid is a square only one value is used for both grid height, grid width
elif (parameter == 2):
fig = initialise(GRID_HEIGHT = param, GRID_WIDTH = param, lightning = lightning, tree_growth = tree_growth)
#Run the FuncAnimation function from the MatPlot Library (see packages imported) using the appropriate parameters
#Fig makes sure the output is placed in a figure
#animate_with_rain calls the animate_with_rain function (see modules imported)
#the number of frames is set to the value declared in the config module
#Interval of 1 to proceed through the animation faster
#The init function (see the init module) is called first to set up the plot.
anim = FuncAnimation(fig, animate, frames=config.frame, interval=1, init_func = init)
#Display this in HTML
HTML(anim.to_jshtml())
#If rain is in effect
else:
#Checks which parameter is to be tested and sets the appropriate parameter.
#If it is 0: in the initialize function set tree growth to be the value in the list
if (parameter == 0):
fig = initialise_with_rain(tree_growth = param, GRID_HEIGHT = GRID_HEIGHT, GRID_WIDTH = GRID_WIDTH, lightning = lightning, cloud_th = cloud_th)
#If it is 1: in the initialize function set to lightning to be the value in the list
elif (parameter == 1):
fig = initialise_with_rain(lightning = param, GRID_HEIGHT = GRID_HEIGHT, GRID_WIDTH = GRID_WIDTH, tree_growth = tree_growth, cloud_th = cloud_th)
#If it is 2: in the initialize function set it to grid height and width
#Note: as this grid is a square only one value is used for both grid height, grid width
elif (parameter == 2):
fig = initialise_with_rain(GRID_HEIGHT = param, GRID_WIDTH = param, lightning = lightning, tree_growth = tree_growth, cloud_th = cloud_th)
#If it is 3 set it to cloud threshold
elif (parameter == 3):
fig = initialise_with_rain(cloud_th = 1-param, GRID_HEIGHT = GRID_HEIGHT, GRID_WIDTH = GRID_WIDTH, lightning = lightning, tree_growth = tree_growth)
# we do 1 minus the cloud threshold so we can plot the rain probability and the trend is easier to interoperate
#Run the FuncAnimation function from the MatPlot Library (see packages imported) using the appropriate parameters
#Fig makes sure the output is placed in a figure
#animate calls the animate function (see modules imported)
#the number of frames is set to the value declared in the config module
#Interval of 1 to proceed through the animation faster
#The init function (see the init module) is called first to set up the plot.
anim = FuncAnimation(fig, animate_with_rain, frames=config.frame, interval=1, init_func = init)
#Display this in HTML
HTML(anim.to_jshtml())
#Set the remaining trees to be the proportion of alive trees in the last frame. This value is appended to the array storing the
#number of remaining trees in the simulations
remaining_trees_per_sim.append(config.prop_of_trees[-1])
#Set the last frame in a simulation and add this to the array storing number of the last frames.
last_frame_per_sim.append(config.last_frame)
#There is now an array for one value in the parameter list. A mean of each list is then taken to find the mean number of trees
#remaining and mean value for the last frame. This value is then appended to the arrays containing the mean for each value.
mean_remaining_trees.append(np.mean(np.array(remaining_trees_per_sim)))
mean_last_frame.append(np.mean(np.array(last_frame_per_sim)))
#Return the mean remaining tree number and mean last frame lists.
return mean_remaining_trees, mean_last_frame
def simulation_combine(light_values, tree_values, times = 1, frame_num = config.frame):
"""
Runs forest fire simulation over specified values for the specified number of times. Each lightning probability is tested against each new
tree value for the number of times specified.
Args:
light_values : (numpy ndarray) a 1D array corresponding to the probabilities/values of lightning to be used in the simulation
tree_values : (numpy ndarray) a 1D array corresponding to the probabilities/values of new tree growth to be used in the simulation
times : (int) number of times to repeat the simulation, defaults to 10
frame_num (int): The number of frames to run simulation
Returns:
mean_remaining_trees : (list) a list of floats containing the mean values of the remaining number of trees
one mean value is returned for each value combination of lightning values and new tree values
mean_last_frame : (list) a list of floats containing the mean values of the last frame number
one mean value is returned for each value combination of lightning values and new tree values
condition: (list) a list of pairs of values representing the lightning and new tree probabilities used as (lightning, new tree)
Raises:
ValueError: If any of the arguments are of the correct type but not a valid value
TypeError: If any of the arguments are not of the correct data type
"""
#Checks the number of the times argument is above 0
if times <= 0:
raise ValueError("Number of times must be at least 1!")
#Checks the simulation values are stored in a numpy array
elif (type(light_values) != np.ndarray):
raise TypeError("Invalid simulation value type, only accepts 1D numpy array!")
#Checks there is at least one value in the values for the testing
elif (light_values.size <= 0 ):
raise ValueError("Must have at least one value in simualation values!")
#Checks the simulation values are stored in a numpy array
elif (type(tree_values) != np.ndarray):
raise TypeError("Invalid simulation value type, only accepts 1D numpy array!")
#Checks there is at least one value in the values for the testing
elif (tree_values.size <= 0 ):
raise ValueError("Must have at least one value in simualation values!")
#If the frame number is smaller than 1, raise an error
elif(frame_num < 1):
raise ValueError("Invalid frame number, frame number must be at least 1!")
#Creates two empty arrays
#This first array will store the proportion of the grid that are still alive trees for each value in parameter. A mean is taken for
#each value.
mean_remaining_trees = []
#This array will store the value of the last frame. This is either the frame the simulation has burnt out at or the max frame number as
#previously set. A mean is taken for each value.
mean_last_frame = []
#This array will store each condition for tabulating and visualising the data.
condition = []
#Iterate over each value in the simulation values so each one is tested.
for lightning_value in list(light_values):
#for each value in the lightning list iterate over the new tree probability list and test each one.
for tree_value in list(tree_values):
#Set empty list for this value
remaining_trees_per_sim = []
last_frame_per_sim = []
#Repeat this simulation the number of times set as specified in the "times" argument
for time in range(times):
#Reset the variables in config.py
reset()
#Change the frame number in config.py
config.frame = frame_num
config.last_frame = frame_num
#Set the probabilities of new tree growth and lightning to be the values specified in the lists using the initialize
#function (see the initialize module)
fig = initialise(tree_growth = tree_value, lightning = lightning_value)
#Run the FuncAnimation function from the MatPlot Library (see packages imported) using the appropriate parameters
#Fig makes sure the output is placed in a figure
#animate calls the animate function (see modules imported)
#the number of frames is set to the value declared in config module
#Interval of 1 to proceed through the animation faster
#The init function (see the init module) is called first to set up the plot.
anim = FuncAnimation(fig, animate, frames=config.frame, interval=1, init_func = init)
#Display this in HTML so can be displayed in a Jupiter Notebook
HTML(anim.to_jshtml())
#Set the remaining trees to be the proportion of alive trees in the last frame. This value is appended to the array storing
#the number of remaining of trees in the simulations
remaining_trees_per_sim.append(config.prop_of_trees[-1])
#Set the last frame in a simulation and add this to the array storing number of the last frames.
last_frame_per_sim.append(config.last_frame)
#There is now an array for set of conditions. A mean of each list is then taken to find the mean number of trees
#remaining and mean value for the last frame. This value is then appended to the arrays containing the mean for each value.
mean_remaining_trees.append(np.mean(np.array(remaining_trees_per_sim)))
mean_last_frame.append(np.mean(np.array(last_frame_per_sim)))
#The condition tested is then appended to the list of conditions
condition.append((lightning_value, tree_value))
#Return the mean remaining tree number, mean last frame and conditions
return mean_remaining_trees, mean_last_frame, condition
def sim_plot(sim_values, rem_trees, last_frame, x_axis):
"""
This function plots the proportion of trees in the last frame and the number of frames in the simulation and is used after the simulation function to visualise the results.
Args:
sim_values: (numpy ndarray) a 1D array corresponding to the probabilities/values of the parameter(s) to be used in simulation
rem_trees: (list) a list of floats containing the mean values of the remaining number of trees
last_frame: (list) a list of floats containing the mean values of the last frame number
x_axis: (string) label for the x axis of the plot
Raises:
Type Error: An incorrect data type is passed into the parameters, simulation values must be added as a numpy array.
Value Error: The lists or array are not the same length and so could not be plotted together.
"""
#Checks that the simulation values are in a numpy array
if (type(sim_values) != np.ndarray):
raise TypeError("Invalid simulation value type, only accepts 1D numpy array!")
#Checks all arguments are of the same length and so can be plotted together
elif (sim_values.size != len(rem_trees) or sim_values.size != len(last_frame)):
raise ValueError("Arguments are of differen size/lengths!")
#Creates two subplots and sets the figure size to be 12x5
size_sim, axes = plt.subplots(1, 2, sharex = True, figsize = (12, 5))
#For the first plot:
#Plot the simulation values against the list of values contaning the remaining trees
axes[0].plot(list(sim_values), rem_trees)
#Add a title to the plot
axes[0].set_title("No. of remaining trees in last frame")
#Set the y axis label
axes[0].set_ylabel("Proportion of trees")
#For the second plot:
#Plot the simulation values against the list of values containing the last frame numbers
axes[1].plot(list(sim_values), last_frame)
#Add a title to the plot
axes[1].set_title("No. of frames in simulation")
#Set the y axis label
axes[1].set_ylabel("Frame number")
#Add an x axis label for the simulation values and set this at the bottom of the plot in the center
size_sim.text(0.5, 0.04, x_axis, ha='center')
#Display the plot
plt.show()
|
4724c8dead863938ccb4c7ce4c65a31f29f2363f | LeonKennedy/DataStructureAlgorithm | /Knapsack.py | 2,136 | 3.609375 | 4 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Filename: Knapsack.py
# @Author: olenji - [email protected]
# @Description: 0-1 背包问题
# @Create: 2019-07-10 22:48
# @Last Modified: 2019-07-10 22:48
from copy import copy
from typing import List
class Knapsack:
def __init__(self):
self.maxW = 9
self.items = [2, 2, 4, 6, 3]
self.values = [3, 4, 8, 9, 6]
print(f"item weight: {self.items}")
def backtracking(self, i, bag):
if i >= len(self.items):
yield bag
else:
negative_bag = copy(bag)
yield from self.backtracking(i + 1, negative_bag)
if sum(bag) + self.items[i] > self.maxW:
yield bag
else:
sub_bag = copy(bag)
sub_bag.append(self.items[i])
yield from self.backtracking(i + 1, sub_bag)
def dynamic(self):
states = [-1] * (self.maxW + 1)
states[0] = 0
n = len(states)
for i, item in enumerate(self.items):
for j in range(n-1, -1, -1): # 这里的倒叙是关键， 不然会覆盖之后的值
if states[j] >= 0 and j + item < n and states[j + item] < states[j] + self.values[i]:
states[j + item] = self.values[i] + states[j]
return states
def find_combine(self, states) -> List:
# 打印组合
max_value = max(states)
max_weight = states.index(max_value)
print(f"max value: {max_value} max weight: {max_weight}")
output = list()
for i, item in enumerate(self.items):
if states[max_weight - item] == max_value - self.values[i]:
output.append(i)
max_value -= self.values[i]
max_weight -= item
return output
if __name__ == "__main__":
k = Knapsack()
max_bag = []
print('---- backtracking --- ')
for bag in k.backtracking(0, []):
if sum(bag) > sum(max_bag):
max_bag = bag
print(max_bag)
print('---- dynamic --- ')
states = k.dynamic()
output = k.find_combine(states)
print(output) |
7b98b8dd7e3a060af3ed6f3f7a7769fbb65af04e | LeonKennedy/DataStructureAlgorithm | /leetcode/MergeSortedLists.py | 1,536 | 4.03125 | 4 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Filename: MergeSortedLists.py
# @Author: olenji - [email protected]
# @Description: 合并多个有序列表
# https://leetcode.com/problems/merge-k-sorted-lists/
# @Create: 2019-07-20 17:24
# @Last Modified: 2019-07-20 17:24
from typing import List
from queue import PriorityQueue
import sys
class ListNode:
__slots__ = 'val', 'next'
def __init__(self, x):
self.val = x
self.next = None
def __lt__(self, other):
return self.val < other.val
class MergeSortedLists:
def mergeKLists(self, lists: List[ListNode]) -> ListNode:
head = ListNode(None)
tail = head
q = PriorityQueue()
for node in lists:
if node: q.put(node)
while q.qsize() > 0:
tail.next = q.get()
tail = tail.next
if tail.next: q.put(tail.next)
return head.next
def print_list(data):
if data is None:
return
p = data
while p.next is not None:
print(p.val, end='->')
p = p.next
print(p.val)
if __name__ == "__main__":
data = [
[5, 4, 1],
[4, 3, 1],
[6, 2]
]
input = list()
for l in data:
head = ListNode(None)
for d in l:
t = ListNode(d)
t.next = head.next
head.next = t
input.append(head.next)
for l in input:
print_list(l)
m = MergeSortedLists()
# input = [None, None]
output = m.mergeKLists(input)
print_list(output)
|
2cb2346e70db90645b00a7e910c0bf85c691dfff | LeonKennedy/DataStructureAlgorithm | /graph/TopologicalSort.py | 1,217 | 3.625 | 4 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Filename: TopologicalSort.py
# @Author: olenji - [email protected]
# @Description:
# @Create: 2019-08-16 15:39
# @Last Modified: 2019-08-16 15:39
from Graph import AdjacencyMap
def topological_sort(graph: AdjacencyMap):
incount = dict()
queue = list()
for vertex in graph.vertices:
incount[vertex] = graph.degree(vertex, False)
walk = None
while len(incount):
if walk == incount:
break
walk = incount.copy()
for k,v in walk.items():
if v == 0:
queue.append(k)
for e in graph.incident_edges(k):
incount[e.destination] -= 1
del incount[k]
return queue
if __name__ == '__main__':
dg = AdjacencyMap(is_directed=True)
dg.insert_edges(1, 2)
dg.insert_edges(1, 3)
dg.insert_edges(4, 3)
dg.insert_edges(3, 5)
dg.insert_edges(3, 6)
dg.insert_edges(4, 6)
dg.insert_edges(5, 7)
dg.insert_edges(1, 7)
dg.insert_edges(7, 8)
dg.insert_edges(2, 8)
# dg.insert_edges(5, 1) # 如果有环 就退出
# dg.insert_edges(9, 8)
# dg.insert_edges(8, 9)
print(topological_sort(dg))
|
5840829e5f7c53e2d6416bba1d77ca793d8d62be | LeonKennedy/DataStructureAlgorithm | /leetcode/nqueue.py | 2,528 | 3.78125 | 4 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Filename: nqueue.py
# @Author: olenji - [email protected]
# @Description: 51. N-Queens
# The n-queens puzzle is the problem of
# placing n queens on an n×n chessboard
# such that no two queens attack each other.
# Given an integer n, return all distinct solutions to the n-queens puzzle.
#
# Each solution contains a distinct board configuration of the n-queens' placement,
# where 'Q' and '.' both indicate a queen and an empty space respectively.
# Input: 4
# Output: [
# [".Q..", // Solution 1
# "...Q",
# "Q...",
# "..Q."],
#
# ["..Q.", // Solution 2
# "Q...",
# "...Q",
# ".Q.."]
# ]
# @Create: 2019-07-10 11:00
# @Last Modified: 2019-07-10 11:00
from typing import List
from array import array
import copy
class NQueue:
def solveNQueens(self, n: int) -> List[List[str]]:
chessboard = [array('u', '.' * n) for i in range(n)]
output = list()
for complete_chessboard in self.assign(chessboard, 0):
solution = list()
for row in complete_chessboard:
solution.append(''.join(['Q' if i == 'Q' else '.' for i in row]))
output.append(solution)
return output
def totalNQueens(self, n: int) -> int:
chessboard = [array('u', '.' * n) for i in range(n)]
num = 0
for complete_chessboard in self.assign(chessboard, 0):
num += 1
return num
def assign(self, chessboard: List[List[str]], layer: int) -> List[List[str]]:
for column, cell in enumerate(chessboard[layer]):
if cell != '.':
continue
sub_chessboard = copy.deepcopy(chessboard)
sub_chessboard[layer][column] = 'Q'
if layer == len(chessboard) - 1:
yield sub_chessboard
else:
self.fill(sub_chessboard, layer, column)
for output in self.assign(sub_chessboard, layer+1):
yield output
def fill(self, chessboard, layer, column):
for row in chessboard:
row[column] = '+'
chessboard[layer][column] = 'Q'
length = len(chessboard)
i = layer + 1
while i < length:
left = column - i + layer
if left >= 0:
chessboard[i][left] = '+'
right = column + i - layer
if right < length:
chessboard[i][right] = '+'
i += 1
if __name__ == "__main__":
q = NQueue()
print(q.solveNQueens(4)) |
ce6179fc4574abb0e25669192dad041088c0ea7b | JustCreature/Py_practice | /practice.py | 10,814 | 4.09375 | 4 | """This is the list of my practical work of learning OOP. (Uncomment he part of code you want to run)"""
"""Class and object creation"""
#
# import random
#
# class Warrior:
# def __init__(self, name):
# self.name = name
# self.hp = 100
#
# def gotHurt(self):
# self.hp -= 20
#
#
# first = Warrior('first')
# second = Warrior('second')
#
# while first.hp > 0 and second.hp > 0:
# turn = random.randint(0, 1)
# if turn == 0:
# whoAt = first
# whoHurt = second
# else:
# whoAt = second
# whoHurt = first
# whoHurt.gotHurt()
# txt = f"The {whoAt.name} attaced the {whoHurt.name}\n" \
# f"The {whoHurt.name} has {whoHurt.hp} lives"
# print(txt)
#
# print("The first won") if first.hp > 0 else print("The second won")
###################
###################
"""Constructor __init__"""
# import random
# class Employee:
# def __init__(self, name, last_name, quall=1):
# self.name = name
# self.last_name = last_name
# self.quall = quall
#
# def info(self):
# return self.name + self.last_name + self.quall
#
# def __del__(self):
# return print(f"Goodbye Mr.{self.name} {self.last_name}")
#
#
# person1 = Employee('Ivan', 'Ivanov', random.randint(1, 5))
# person2 = Employee('Nikolay', 'Nikolayev')
# person3 = Employee('Sergey', 'Sergeyev', random.randint(1, 5))
#
# emps = []
# emps.append(person1)
# emps.append(person2)
# emps.append(person3)
#
# arr = []
# arr.append(person1.quall)
# arr.append(person2.quall)
# arr.append(person3.quall)
# weak = arr.index(min(arr))
#
# emps[weak].__del__()
#
# input()
#################
#################
"""Inheritance"""
# import random
#
#
# class Person:
# def __init__(self, id, team):
# self.id = id
# self.team = team
#
#
# class Hero(Person):
# def __init__(self, id, team):
# Person.__init__(self, id, team)
# self.level = 0
#
# def level_up(self):
# self.level += 1
#
# class Soldier(Person):
# def follow_hero(self, my_hero):
# pass
#
#
# hero1 = Hero(1, 1)
# hero2 = Hero(2, 2)
#
# sold1 = []
# sold2 = []
#
# i = 0
#
# while i < random.randint(10, 15):
# check = random.randint(1, 2)
# if check == 1:
# sold = Soldier(i, 1)
# sold1.append(sold)
# else:
# sold = Soldier(i, 2)
# sold2.append(sold)
#
# i += 1
#
# hero1.level_up() if len(sold1) > len(sold2) else hero2.level_up()
#
# x = sold1[random.randint(0, len(sold1))]
# x.follow_hero(hero1)
#
# print(f"Hero 1 level is {hero1.level}")
# print(f"Hero 2 level is {hero2.level}")
#
# print(f"Soldier {x.id} is following hero {hero1.id}")
############################
############################
"""Polimorphism"""
#
# class Thing:
# def __init__(self, material):
# self.material = material
#
# def __add__(self, other):
# if self.material == other.material:
# return f"The room furniture is made of {self.material}"
# else:
# return "The room furniture is made of different materials"
#
#
# class Table(Thing):
# def somethig(self):
# pass
#
#
# class Chair(Thing):
# def anything(self):
# pass
#
#
# table = Table(str(input("Enter material of table...\n")))
# chair = Chair(str(input("Enter material of chair...\n")))
#
# print(table + chair)
#
###############################
###############################
"""Encapsulation"""
#
# class Calculate:
# __usage = 0
#
# def __init__(self, a, b):
# self.val = Calculate.__calk(a, b)
#
# def __setattr__(self, attr, value):
# if attr == 'val':
# self.__dict__[attr] = value
# else:
# raise AttributeError
#
# def __calk(a, b):
# return a * b / 2 * b
#
# def get_val(self):
# return self.val
#
# def set_usage(n):
# Calculate.__usage = n
#
# def get_usage():
# return Calculate.__usage
#
# q = Calculate(5, 5)
# print(q.get_val())
#
# q.val = 5
# print(q.get_val())
#
# i = 0
#
# while i != '':
# i += 1
# q = input("First number\n")
# if q == 'exit':
# print(f"Goodbye. You used the function {Calculate.get_usage()} times")
# break
# w = input("Second number\n")
# if w == 'exit':
# print(f"Goodbye. You used the function {Calculate.get_usage()} times")
# break
# q = int(q)
# w = int(w)
# print(Calculate(q, w).get_val())
# Calculate.set_usage(i)
#
###################################
###################################
"""Composition"""
# import math
# import sys
#
# class Room:
# def __init__(self, width, length, height):
# self.set_sides(width, length, height)
# self.wd = []
#
# def getRolls(self, l, w):
# self.__rolls = math.ceil(self.get_work_surface() / (l * w))
#
# def set_sides(self, width, length, height):
# self.__width = width
# self.__length = length
# self.__height = height
#
# def lastDel(self):
# self.wd.pop()
#
# def clearWD(self):
# self.wd.clear()
#
# def addWD(self, w = 1, h = 1):
# self.wd.append(WinDoor(w, h))
#
# def get_work_surface(self):
# self.__work_surf = self.get_square()
# if len(self.wd) > 0:
# for i in self.wd:
# self.__work_surf -= i.get_sq()
# return self.__work_surf
#
# def get_square(self):
# self.__square = 2 * self.__height * (self.__length + self.__width)
# return self.__square
#
#
# class WinDoor:
# def __init__(self, x, y):
# self.__square = x * y
#
# def get_sq(self):
# return self.__square
#
#
# ask = 0
#
# while ask != 'exit':
# try:
# l = float(input("Enter your room width\n"))
# w = float(input("Enter your room length\n"))
# h = float(input("Enter your room height\n"))
# r1 = Room(l, w, h)
# except ValueError:
# print("Incorrect input")
# break
#
# while ask != exit:
# ask = input("\nWhat do you want? Choose ONE!!!\n1 - Count square, 2 - Count the amount of rolls, "
# "3 - Add window-door,\n4 - delete last added window-door, 5 - Count work surface, "
# "6 - New room parametrs,\nexit - stop the program\n")
# if not str(ask).isdigit() and ask != 'exit' or ask == ' ' or ask == '':
# print("Incorrect input")
# sys.exit()
# if ask == 'exit':
# sys.exit()
# ask = int(ask)
# if ask == 1:
# print(f"\nThe square is {r1.get_square()}\n")
# elif ask == 2:
# l = float(input("The length of your roll:\n"))
# w = float(input("The width of your roll:\n"))
# print(f"\nYou'll need {r1.getRolls(l, w)} rolls\n")
# elif ask == 3:
# try:
# l = float(input("The length of your window-door(or leave it empty):\n"))
# w = float(input("The width of your window-door(or leave it empty):\n"))
# r1.addWD(l, w)
# except ValueError:
# pass
# r1.addWD()
# elif ask == 4:
# r1.lastDel()
# elif ask == 5:
# print(f"\nThe work surface is {r1.get_work_surface()}\n")
# elif ask == 6:
# break
# print("GoodBye")
##########################
##########################
"""Operator overload"""
#
# class Snow:
# def __init__(self, q):
# self.q = q
#
# def __add__(self, other):
# return self.q - other.q
#
# def __sub__(self, other):
# return self.q + other.q
#
# def __mul__(self, other):
# return self.q / other.q
#
# def __truediv__(self, other):
# return self.q // other.q
#
# def __call__(self, ar):
# self.q = ar
#
# def makeSnow(self, row_quant):
# self.qw = self.q / row_quant
# i = 0
# row = ''
# while i < self.qw:
# row += row_quant * "*" + "\n"
# i += 1
# return row
#
#
# s1 = Snow(20)
# s2 = Snow(50)
# x = s1 + s2
# print(x)
# print(s1.makeSnow(5))
# s1(10)
# print(s1.makeSnow(5))
#
#####################################
#####################################
"""Modules and packages"""
#
# import geometry
# from geometry import planimetry as pl, stereometry as st
#
# b = st.Ball(5)
# a = pl.Circle(5)
#
# print(a.length(), b.V())
#
# print(geometry.stereometry.__doc__)
#
########################
########################
"""Just prog"""
#
# import random
#
#
# class Data:
# def __init__(self, *info):
# self.info = info
#
# def __getitem__(self, item):
# return self.info[item]
#
#
# class Teacher:
# def teach(self, info, *pupil):
# for i in pupil:
# i.take(info)
#
#
# class Pupil:
# def __init__(self):
# self.knowledge = []
#
# def take(self, info):
# self.knowledge.append(info)
# self.knowledge = set(self.knowledge)
# self.knowledge = list(self.knowledge)
#
# def forget(self):
# self.out = random.randint(0, len(self.knowledge) - 1)
# self.knowledge.pop(self.out)
#
#
# lesson = Data('class', 'object', 'inheritance', 'polimorphism', 'encapsulation')
# marIvanna = Teacher()
# vasya = Pupil()
# petya = Pupil()
#
# marIvanna.teach(lesson[2], vasya, petya)
# marIvanna.teach(lesson[0], petya)
#
# print(f"Vasya knows {vasya.knowledge}")
# print(f"Petya knows {petya.knowledge}")
#
# i = 0
# for i in range(3):
# selfEd = random.randint(0, len(lesson.info) - 1)
# petya.take(lesson[selfEd])
# vasya.take(lesson[selfEd])
#
# petya.forget()
#
# print(f"Vasya knows {vasya.knowledge}")
# print(f"Petya knows {petya.knowledge}")
#
#####################
#####################
"""Static methods"""
#
# from math import pi
#
# class Cylinder:
# @staticmethod
# def __make_area(d, h):
# circle = pi * d ** 2 / 4
# side = pi * d * h
# return round(circle*2 + side, 2)
#
# def __init__(self, diametr, hight):
# self.diametr = diametr
# self.hight = hight
# self.__count_area()
#
# def __count_area(self):
# self.__area = self.__make_area(self.diametr, self.hight)
#
# def __setattr__(self, key, value):
# if key != 'diametr' or key != 'hight':
# self.__dict__[key] = value
# else:
# raise AttributeError
#
# def get_area(self):
# self.__count_area()
# return self.__area
#
#
# a = Cylinder(1, 2)
# print(a.get_area())
#
# print(a._Cylinder__make_area(2, 2))
#
# a.diametr = 2
#
# print(a.get_area())
#
########################
########################
|
5d78a0925d11a2978b91d75f298730931692a4cd | nschalla/GUVI_Home | /333.py | 120 | 3.875 | 4 | n=int(input("enter the number"))
sum = 0
while (num > 0):
sum += int(n % 10)
n = int(n / 10)
print(sum)
|
d1771a309ef434261340ad20b2937d96dedd188f | nschalla/GUVI_Home | /555.py | 62 | 3.90625 | 4 | '''reverse the given number'''
n=int(input()[::-1])
print(n) |
42b32eeaa42d5962f29f4d1235951a38e014dd77 | gabrielsgradinar/exercicios-hacker-rank | /introduction/if-else.py | 458 | 3.859375 | 4 | #!/bin/python3
import math
import os
import random
import re
import sys
if __name__ == '__main__':
n = int(input().strip())
def is_even(n):
if n % 2 == 0:
return True
return False
if not is_even(n):
print("Weird")
if is_even(n) and n in range(2, 6):
print("Not Weird")
if is_even(n) and n in range(6, 21):
print("Weird")
if is_even(n) and n > 20:
print("Not Weird") |
5470b091b9bd46530850873c488b5598249d3a0b | roger2399/python-practice | /loop_traversal.py | 145 | 3.765625 | 4 | fruit = "banana"
index = 0
while len(fruit) > index:
letter = fruit[index]
print (letter)
index += 1
|
ed6d0b6d1f7240a0e3caba4092c71d7d42b2b8ac | vanman247/Stat-GUI | /Tests/pearson_Coor1.py | 1,483 | 3.59375 | 4 | from scipy.stats import pearsonr
from tkinter import *
from tkinter import filedialog
def main(url = "adult.csv", data1="age", data2="y"):
direc="C:/Users/Ammon Van/Desktop/Fun Projects/Statistic Analysis/Tests"
filetypes = (("CSV", "*.CSV"), ("All Files", "*.*"))
url = filedialog.askopenfilename(initialdir=direc, title="Open File", filetypes=filetypes)
url = open(url, "r")
stuff = url.read()
text1.insert(END, stuff)
url.close()
## data1 =
## data2 =
try:
print("Pearson’s Correlation Coefficient \n \n \n")
print("_____ASSUMPTIONS______")
print(" 1. Observations in each sample are independent and identically distributed")
print(" 2. Observations in each sample are normally distributed")
print(" 3. Observations in each sample have the same variance \n")
pearson(url = url, data1=data1, data2=data2)
except ValueError:
print(ValueError)
print("Passed")
return
def pearson(url = "adult.csv", data1="age", data2="y"):
df = pd.read_csv(url)
df = df.select_dtypes(include=["float64", "int64"])
stat, p = pearsonr(df["{}".format(data1)], df["{}".format(data2)])
print('stat=%.4f, p=%.4f' % (stat, p), "\n")
if p > 0.05:
print('H0: the two samples are probably independent. \n \n \n')
else:
print('H1: there is probably a dependency between the samples \n \n \n')
if __name__ == "__main__":
main()
|
266db82f465a561b52a117fa38cb97ee80aa0d4d | dsssssssss9/pimoroni-pico | /micropython/examples/pico_display/buttons.py | 1,998 | 3.5 | 4 | # This example shows you a simple, non-interrupt way of reading Pico Display's buttons with a loop that checks to see if buttons are pressed.
import picodisplay as display
import utime
# Initialise display with a bytearray display buffer
buf = bytearray(display.get_width() * display.get_height() * 2)
display.init(buf)
display.set_backlight(0.5)
# sets up a handy function we can call to clear the screen
def clear():
display.set_pen(0, 0, 0)
display.clear()
display.update()
while True:
if display.is_pressed(display.BUTTON_A): # if a button press is detected then...
clear() # clear to black
display.set_pen(255, 255, 255) # change the pen colour
display.text("Button A pressed", 10, 10, 240, 4) # display some text on the screen
display.update() # update the display
utime.sleep(1) # pause for a sec
clear() # clear to black again
elif display.is_pressed(display.BUTTON_B):
clear()
display.set_pen(0, 255, 255)
display.text("Button B pressed", 10, 10, 240, 4)
display.update()
utime.sleep(1)
clear()
elif display.is_pressed(display.BUTTON_X):
clear()
display.set_pen(255, 0, 255)
display.text("Button X pressed", 10, 10, 240, 4)
display.update()
utime.sleep(1)
clear()
elif display.is_pressed(display.BUTTON_Y):
clear()
display.set_pen(255, 255, 0)
display.text("Button Y pressed", 10, 10, 240, 4)
display.update()
utime.sleep(1)
clear()
else:
display.set_pen(255, 0, 0)
display.text("Press any button!", 10, 10, 240, 4)
display.update()
utime.sleep(0.1) # this number is how frequently the Pico checks for button presses
|
1b81f53332ac9ed7f14bd9d1146d309f92eb3573 | seilcho7/algorithm-practice | /algo_3.py | 2,075 | 3.65625 | 4 | # movie theater problem
# nCols = 16
# nRows = 11
# col = 5
# row = 3
# affected_column = nCols - (col -1)
# affected_rows = nRows - row
# affected_peeps = affected_column * affected_rows
# print(affected_peeps)
# elevator problem
# left_elevator = "left"
# right_elevator = 'right'
# def elevator(left, right, call):
# if abs((call-left)) < abs((call-right)):
# print(left_elevator)
# elif abs((call-left)) > abs((call-right)):
# print(right_elevator)
# elif abs((call-left)) == abs((call-right)):
# print(right_elevator)
# elevator(0, 1, 0)
# elevator(0, 1, 1)
# elevator(0, 1, 2)
# elevator(0, 0, 0)
# elevator(0, 2, 1)
# def checklists(list_a, list_b):
# result = []
# counter = 0
# if len(list_a) == len(list_b):
# for num in list_a:
# while counter < len(list_b):
# if num == list_b[counter]:
# result.append(list_b.pop(counter))
# counter += 1
# break
# else:
# counter += 1
# counter = 0
# else:
# print('false')
# print(result)
# if len(result) == len(list_a):
# print('true')
# else:
# print('false')
# checklists([1,2,3,4], [1,2,3,4])
# checklists([1,2,3,4], [1,4,5,6])
# checklists([1,2,3,4], [1,4,4,2])
# checklists([1,2,3,4], [1,4,3,2])
# checklists([1,2,3,4,5], [1,2,3,4])
# checklists([1,1,1,1], [1,1,1,2])
# checklists([1,1,2,2], [2,2,2,1])
# better way
def are_they_the_same(a, b):
counter = {}
counter2 = {}
for i in a:
counter[i] = 0
for i in a:
counter[i] += 1
for i in b:
counter2[i] = 0
for i in b:
counter2[i] += 1
resultFalse = 0
for key in counter.keys():
if key in counter2.keys():
if counter[key] == counter2[key]:
pass
else:
resultFalse = 1
if resultFalse == 1:
return False
else:
return True
print(are_they_the_same([1,2,3,4], [1,2,3,4])) |
c4c6d1dfddde4594f435a910147ee36b107e87b9 | Pakizer/PragmatechFoundationProject | /tasks/7.py | 303 | 4.15625 | 4 | link[https://www.hackerrank.com/challenges/py-if-else/problem]
n = input('Bir eded daxil edin :')
n=int(n)
if n%2==0 and n>0:
if n in range(2,5):
print('Not Weird')
if n in range(6,20):
print ('Weird')
else:
print('Not Weird')
else:
print('Weird') |
f7e9b67df56874a72f9b38844b2e0ced43313850 | tothricsaj/dataStructures | /LinkedList/simply/python/main.py | 348 | 3.515625 | 4 | import LinkedList as ll
if __name__ == '__main__':
print('Hello LinkedList!!!\n')
llist = ll.LinkedList()
llist.add(1)
llist.add(2)
llist.add(3)
llist.add('What the bloody horse lungs....????')
# llist.printAll()
llist.shift(0)
llist.shift(-1)
llist.shift(-2)
llist.shift(-3)
llist.printAll()
|
3f95d9eb38c10dedc759e9d59c6337dec412f6b0 | jjauzion/salesman_problem | /src/population.py | 4,710 | 3.859375 | 4 | # -*-coding:Utf-8 -*
import random
from src.city import City
from src.individual import Individual
import src.param as param
class Population():
"""Class population is a set of Individual"""
count = 0
final = 0
def __init__(self, city2travel=None, population_size=None):
"""Constructor of Population. Requires list of cities and pop size"""
self.list = []
self.size = 0
self.generation = Population.count
Population.count += 1
def __getitem__(self, index):
return self.list[index]
def __setitem__(self, index, value):
if isinstance(value, list):
for item in value:
if not isinstance(item, Individual):
raise TypeError("value contains {} item and should only\
contains Individual elements".format(type(value)))
elif not isinstance(value, Individual):
raise TypeError("value is {} and should be a Individual element"\
.format(type(value)))
self.list[index] = value
def __add__(self, new):
"""Add a new individual to the population"""
if not isinstance(new, Individual):
raise TypeError("Type {} can't be added to the population,\
must be an Individual".format(type(new)))
self.list.append(new)
self.size += 1
return self
def __iter__(self):
for i in self.list:
yield i
def __repr__(self):
return "Generation {}: av fitness = {:.1f} ; best fitness = {:.1f} ; nb individual = {}"\
.format(self.generation, self.av_fitness, self.best_performer.fitness, self.size)
def random_population(self, city2travel, population_size):
"""Generate a random population"""
self.size = population_size
for i in range(self.size):
self.list.append(Individual(city_list=city2travel))
self.compute_stats()
self.compute_breed_probability()
def compute_stats(self):
"""Compute statistics of the population:
self.worse_performer : worse individual performer
self.best_performer : best individual performer
self.av_fitness : average fitness of the entire population
"""
self.worse_performer = self.list[0]
self.best_performer = self.list[0]
self.av_fitness = 0
for i in self.list:
self.av_fitness += i.fitness
if i.fitness < self.best_performer.fitness:
self.best_performer = i
elif i.fitness > self.worse_performer.fitness:
self.worse_performer = i
self.av_fitness = self.av_fitness / self.size
def compute_breed_probability(self):
"""Compute the breed probability of every individual.
The probability is higher for individual with high performance
"""
self.best_performer.adjusted_fitness = (self.best_performer.fitness -\
self.worse_performer.fitness) * -1
if self.best_performer.adjusted_fitness == 0:
Population.final = 1
for i in self.list:
i.adjusted_fitness =\
(i.fitness - self.worse_performer.fitness) * -1
if Population.final:
i.breed_proba = 100
else:
i.breed_proba =\
i.adjusted_fitness * 100 / self.best_performer.fitness
def pick_parents(self):
"""Pick randomly two parents from the indivduals pool.
Indivdual with high breed propability have higher chances to be picked.
Return a tuple of two Individuals.
"""
parent = []
while len(parent) < 2:
element = random.choice(self.list)
if element.breed_proba >= random.randrange(101):
if len(parent) >= 1 and element != parent[0]:
parent.append(element)
elif len(parent) < 1:
parent.append(element)
return (parent[0], parent[1])
def next_generation(self):
"""Generate the next generation based on the current population
The next generation's individuals are sons of the current population.
The function return a new instance of a Population class.
"""
next_gen = Population()
i = 0
while i < self.size:
father, mother = self.pick_parents()
next_gen = next_gen + Individual(father=father, mother=mother)
i += 1
next_gen.compute_stats()
next_gen.compute_breed_probability()
return next_gen
|
19e9415ff1883e29e995c0bea242524a1f9bb625 | himashugit/python_dsa | /string/List/module/forloop/range.py | 230 | 4.03125 | 4 | # 5 is the stop value and o is the start value
print(list(range(5))) # we use list to conver the result in the list format in python3
print(list(range(0,20,2))) # result will be 0,2,4,6..18 so 20-2 will be last number to print
|
7481502d696c2d5a78261dd7becc48f8a849ca6f | himashugit/python_dsa | /string/join_Center_zerofill.py | 204 | 3.640625 | 4 | x="hello"
print("-".join(x))
# center
my_str="python"
my_Strn1="scripting"
my_Str2="lang"
print(f'{my_str.center(12)}\n{my_Strn1.center(20)}\n{my_Str2.center(20)}')
zero="python"
print(zero.zfill(10))
|
06badb56fb645ab46abc58aae9871c5f913a4bbc | himashugit/python_dsa | /string/List/module/forloop/read_string_printwith_indexvalue.py | 994 | 3.859375 | 4 | '''
usr_strng= input("Enter your string: ")
index=0 # index var is defined
for each_char in usr_strng:
print(f' {each_char} -->{index}')
index=index+1 # we're increasing index value by 1
'''
import os
req_path= input("Enter your dir path: ")
if os.path.isfile(req_path):
print(f' the {req_path} is a file pls provide dir ')
else:
all_f_ds= os.listdir(req_path)
if len(all_f_ds)==0:
print(f" the given path {req_path} is empty")
else:
req_ex=input("Enter the req file extention .py/.sh/.log/.txt: ")
req_files=[]
for each_file in all_f_ds:
if each_file.endswith(req_ex):
req_files.append(each_file)
if len(req_files)==0:
print(f'There are no {req_ex} files in the location of {req_path}')
else:
print(f'There are {len(req_files)} files in the loc of {req_path} with an extention of {req_ex}')
print(f'the reuired files are: {req_files}')
|
3a57aa31606b198a76d98cff001fec94613a18e4 | himashugit/python_dsa | /variables/var.py | 99 | 4.0625 | 4 | x = 3 # x is var to store value here
y = 5
print(x)
myname="himanshu"
print(myname,type(myname))
|
edfd81e4cbd96b77f1666534f7532b0886f8ec4e | himashugit/python_dsa | /func_with_Arg_returnvalues.py | 617 | 4.15625 | 4 | '''
def addition(a,b):
result = a+b
return result # this value we're sending back to main func to print
def main():
a = eval(input("Enter your number: "))
b = eval(input("Enter your 2ndnumber: "))
result = addition(a,b) # calling addition func & argument value and storing in result
print(f' "the addition of {a} and {b} is {result}"')
main() # calling main func
'''
def multiply_num_10(value):
#result = value*10
#return result
return value*10
def main():
num=eval(input("Enter a number:"))
result=multiply_num_10(num)
print("The value is: ", result)
main() |
38c8fc1d0c52d8d25cb810d8e272961831471ccf | chrisjdavie/compsci_basics | /number_theory/primality_test/naive.py | 634 | 3.578125 | 4 | from math import sqrt
from parameterized import parameterized
import unittest
class Test(unittest.TestCase):
@parameterized.expand([
(11, True),
(15, False),
(1, False),
(5, True),
(4, False),
(49, False)
])
def test(self, target, is_prime_expected):
self.assertEqual(is_prime(target), is_prime_expected)
def is_prime(target):
if target < 2:
return False
if not target%2 or not target%3:
return False
for i in range(5, int(sqrt(target)) + 1, 6):
if not target%i or not target%(i+2):
return False
return True
|
2d92ff696bd8fb26b608b6c50ce5681c12f972bd | chrisjdavie/compsci_basics | /stacks/next_greater_element/heap.py | 1,089 | 3.8125 | 4 | """
Given an array A [ ] having distinct elements, the task is to find the next greater element for each element of the array in order of their appearance in the array. If no such element exists, output -1.
https://practice.geeksforgeeks.org/problems/next-larger-element/0
"""
from heapq import heappush, heappop
from parameterized import parameterized
import unittest
class Test(unittest.TestCase):
@parameterized.expand([
("provided example 0", [1, 3, 2, 4], [3, 4, 4, -1]),
("provided example 1", [4, 5, 2, 25], [5, 25, 25, -1]),
("provided example 2", [7, 8, 1, 4], [8, -1, 4, -1])
])
def test(self, _, input_arr, expected_output):
self.assertEqual(next_greater_element(input_arr), expected_output)
def next_greater_element(arr):
value_heap = []
next_greater = [-1]*len(arr)
for ind, value in enumerate(arr):
while value_heap and value_heap[0][0] < value:
_, lower_ind = heappop(value_heap)
next_greater[lower_ind] = value
heappush(value_heap, (value, ind))
return next_greater
|
78fbd0e815c8cf689d089a7abcd84576aab9fe32 | chrisjdavie/compsci_basics | /dynamic_programming/partition_problem/playing.py | 557 | 3.765625 | 4 | from copy import copy
def _rec(arr, n, m):
if n < 1:
return
yield from _rec(arr, n-1, m)
for i in range(1,m):
arr_loop = copy(arr)
arr_loop[n-1] = i
yield arr_loop
yield from _rec(arr_loop, n-1, m)
def main(n, m):
arr = [0]*n
yield arr
yield from _rec(arr, n-1, m)
for i in range(1,m):
arr_loop = copy(arr)
arr_loop[n-1] = i
yield arr_loop
yield from _rec(arr_loop, n-1, m)
if __name__ == "__main__":
for arr in main(4, 3):
print(arr)
|
d0d3c2a049951c3c8b4d57ada259ceefd6fd79b4 | chrisjdavie/compsci_basics | /dynamic_programming/pick_from_top_or_bottom/memoization.py | 1,794 | 3.609375 | 4 | import unittest
from parameterized import parameterized
class Test(unittest.TestCase):
@parameterized.expand([
("provided example 0", [5, 3, 7, 10], 15),
("provided example 1", [8, 15, 3, 7], 22),
("one number", [1], 1),
("two numbers highest", [1, 2], 2),
("three numbers", [1, 2, 3], 4),
("four numbers out of order", [3, 15, 2, 1], 16)
])
def test(self, _, stack, expected_winnings):
self.assertEqual(pick_from_top_or_bottom(stack), expected_winnings)
def cache(func):
prev_vals = None
def cached_func(stack, n_lhs, n_rhs):
nonlocal prev_vals
key = (n_lhs, n_rhs)
if key == (0, len(stack)-1):
prev_vals = {}
if key not in prev_vals:
prev_vals[key] = func(stack, n_lhs, n_rhs)
return prev_vals[key]
return cached_func
@cache
def _pick_from_top_or_bottom(stack, n_lhs, n_rhs):
if n_lhs == n_rhs:
return stack[n_lhs], 0
best_other_l, best_mine_l = _pick_from_top_or_bottom(stack, n_lhs+1, n_rhs)
best_mine_l += stack[n_lhs]
best_other_r, best_mine_r = _pick_from_top_or_bottom(stack, n_lhs, n_rhs-1)
best_mine_r += stack[n_rhs]
if best_mine_l > best_mine_r:
return best_mine_l, best_other_l
return best_mine_r, best_other_r
def pick_from_top_or_bottom(stack):
"""Consider a row of n coins of values v1 . . . vn, where n is even. We play a game against an opponent by alternating turns. In each turn, a player selects either the first or last coin from the row, removes it from the row permanently, and receives the value of the coin. Determine the maximum possible amount of money we can definitely win if we move first."""
return _pick_from_top_or_bottom(stack, 0, len(stack)-1)[0]
|
f9fea5999edbcad89bc88a0c6ab3d38f238a699f | chrisjdavie/compsci_basics | /sorting_and_searching/key_pair/solve.py | 911 | 3.609375 | 4 | """Given an array A[] of n numbers and another number x, determine whether or not there exist two elements in A whose sum is exactly x."""
from parameterized import parameterized
import unittest
class Test(unittest.TestCase):
@parameterized.expand([
(16, [1, 4, 45, 6, 10, 8], True),
(10, [1, 2, 4, 3, 6], True),
(1, [1, 0], True),
(2, [0, 1], False),
(5, [0, 2, 1], False),
(3, [0, 2, 1], True)
])
def test(self, target, arr, expected_result):
self.assertEqual(sum_values_match_target(target, arr), expected_result)
def sum_values_match_target(target, arr):
arr.sort()
i_lhs = 0
i_rhs = len(arr) - 1
while i_lhs < i_rhs:
summ = arr[i_lhs] + arr[i_rhs]
if summ == target:
return True
elif summ > target:
i_rhs -= 1
else:
i_lhs += 1
return False
|
011660b420866fac9fbfd80c72f0924bff71f8c4 | chrisjdavie/compsci_basics | /dynamic_programming/subset_sum/recursive.py | 785 | 3.546875 | 4 | import unittest
from parameterized import parameterized
class Test(unittest.TestCase):
@parameterized.expand([
("provided example", [3, 34, 4, 12, 5, 2], 9, True),
("single value true", [1], 1, True),
("single value false", [1], 2, False),
("three values true", [1, 2, 3], 5, True),
("three values false", [2, 4, 6], 5, False)
])
def test(self, _, arr, target, expected_result):
self.assertIs(subset_sum(arr, target), expected_result)
def _subset_sum(arr, target, n):
if n < 0 or target < 0:
return False
if target == 0:
return True
return _subset_sum(arr, target - arr[n-1], n-1) or _subset_sum(arr, target, n-1)
def subset_sum(arr, target):
return _subset_sum(arr, target, len(arr))
|
575f4c1f07957af2be9b688ce5b5333c25d4b441 | samcoh/Data-Manipulation | /SQL/hw9_ec1.py | 1,379 | 3.84375 | 4 | import sqlite3 as sqlite
import datetime
conn = sqlite.connect('Northwind_small.sqlite')
cur = conn.cursor()
def extra_credit():
statement = 'SELECT CustomerId,OrderDate '
statement += 'FROM [Order] '
statement += 'ORDER BY CustomerId'
row = cur.execute(statement)
ids = []
print('CustomerID, '+'Order Date, '+ 'Previous Order Date, '+'Days Passed')
for x in row:
if x[0] not in ids:
ids.append(x[0])
previous_date = x[1]
list_ = previous_date.split('-')
year = int(list_[0])
month = int(list_[1])
date = int(list_[2])
continue
else:
order = x[1]
order_date_list = order.split('-')
year_order = int(order_date_list[0])
month_order = int(order_date_list[1])
date_order = int(order_date_list[2])
new_order = datetime.date(year_order, month_order, date_order)
old_order = datetime.date(year, month, date)
subtract = new_order - old_order
days_passed = subtract.days
print(x[0]+',' + str(x[1])+"," + previous_date + ","+ str(days_passed))
previous_date = x[1]
list_= previous_date.split('-')
year = int(list_[0])
month = int(list_[1])
date = int(list_[2])
extra_credit()
|
08f6dcabed5205513d36aae8ce1bb1f7dbe7baff | egoetz/clustering-analysis | /k_means.py | 6,690 | 3.6875 | 4 | # E Goetz
# Basic implementation of the k-means clustering algorithm
from clusteringalgorithm import ClusteringAlgorithm
from random import uniform
from numpy import ndarray, zeros, array_equal
class KMeans(ClusteringAlgorithm):
def __init__(self, data, answer_key, dimension_minimums=None,
dimension_maximums=None, verbose=False):
"""
Cluster data using the k-means algorithm.
:param data: the data set to be clustered
:param answer_key: the expected clusters
:param dimension_minimums: the smallest values of each dimension in the
data set
:param dimension_maximums: the largest values of each dimension in the
data set
:param verbose: whether to print progress messages
"""
self.verboseprint(verbose, "Calling KMeans")
self.answer_key = answer_key
self.generated_samples = data
self.cluster_membership = None
self.dimension_minimums = dimension_minimums
self.dimension_maximums = dimension_maximums
# get minimums and maximums for each dimension
if self.dimension_minimums is None or self.dimension_maximums is None:
if self.dimension_minimums is None:
self.dimension_minimums = self.generated_samples[0].copy()
if self.dimension_maximums is None:
self.dimension_maximums = self.generated_samples[0].copy()
for point in self.generated_samples:
for ith_dimension in range(len(point)):
if point[ith_dimension] < self.dimension_minimums[
ith_dimension]:
self.dimension_minimums[ith_dimension] = point[
ith_dimension]
elif point[ith_dimension] > self.dimension_maximums[
ith_dimension]:
self.dimension_maximums[ith_dimension] = point[
ith_dimension]
self.verboseprint(verbose, "Found the minimal value for each data "
"point dimension: {}".format(
self.dimension_minimums))
self.verboseprint(verbose, "Found the maximum value for each data "
"point dimension: {}".format(
self.dimension_maximums))
self.get_k(verbose)
def get_k(self, verbose):
"""
Get the number of clusters or k that has the smallest percent error.
:param verbose: whether to print progress messages
:return: None
:side effect: self.k, self.cluster_membership, and self.percent_error
are set to the k, cluster_membership, and percent_error values of the
clustering attempt with the smallest percent error.
"""
self.percent_error = None
for k in range(1, len(self.generated_samples)):
self.verboseprint(verbose, "Setting k to {}".format(k))
means = self.initialize(k)
old_means = None
clusters = None
while old_means is None or not array_equal(means, old_means):
clusters = self.assign(means)
old_means = means.copy()
means = self.update(k, clusters, old_means)
current_error = self.get_percent_error(clusters, self.answer_key)
if self.percent_error is None or self.percent_error > \
current_error:
self.verboseprint(verbose, "\tNew Percent error: {}".format(
current_error))
self.percent_error = current_error
self.cluster_membership = clusters
self.k = k
if self.percent_error == 0:
return
def initialize(self, k):
"""
Initialize the k means to random values that are inclusively within
the maximum range of the data points for every dimension.
:return: An ndarray holding k random points with the same number of
dimensions as the points in self.generated_samples
"""
means = ndarray((k, len(self.generated_samples[0])))
for cluster_k in range(k):
for dimension in range(len(self.generated_samples[0])):
means[cluster_k][dimension] = uniform(self.dimension_minimums[
dimension], self.
dimension_maximums[dimension])
return means
def assign(self, means):
"""
Assign all data points in the class to the closest mean.
:return: An ndarray holding a number representing cluster membership
for every point.
"""
cluster_membership = ndarray((len(self.generated_samples),), dtype=
int)
for point_index in range(len(self.generated_samples)):
minimum_distance = None
cluster = None
for mean_index in range(len(means)):
distance = 0
for i in range(len(self.generated_samples[point_index])):
distance += (means[mean_index][i] - self.
generated_samples[point_index][i])**2
distance = distance / 2
if minimum_distance is None or distance < minimum_distance:
minimum_distance = distance
cluster = mean_index
cluster_membership[point_index] = cluster
return cluster_membership
def update(self, k, clusters, old_means):
"""
Update the k means to be the mean of the data points that
are assigned to their cluster.
:return: An ndarray holding k points that are the means of the k
clusters
"""
new_means = zeros((k, len(self.generated_samples[0])))
cluster_sizes = zeros((k,))
for point_index in range(len(self.generated_samples)):
mean_index = clusters[point_index]
cluster_sizes[mean_index] += 1
for dimension in range(len(self.generated_samples[point_index])):
new_means[mean_index][dimension] += self.generated_samples[
point_index][dimension]
for mean_index in range(len(new_means)):
if cluster_sizes[mean_index] != 0:
new_means[mean_index] = new_means[mean_index] / cluster_sizes[
mean_index]
else:
new_means[mean_index] = old_means[mean_index]
return new_means
|
ce3606b2dd45f71f61953d4e8542384584b733e0 | bharathulaprasad/Sentiment-Analysis-on-US-Airlines-Twitter-data | /US Airlines Twitter Sentiment Analysis .py | 11,465 | 3.671875 | 4 | #!/usr/bin/env python
# coding: utf-8
# ### Importing the necessary libraries
# In[1]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
# ### Importing the data
# In[2]:
data=pd.read_csv("Tweets.csv")
data.columns
# In[3]:
data.head()
# In[4]:
data.tail()
# ### Data Understanding and preprocessing
# In[5]:
data.describe(include='all')
# In[6]:
### From the above descriptive statistics we could see that
### 1.airline_sentiment has most of its tweets negative
### 2.Customer Service Issue is the mostly occured negative reason
### 3.United airlines is the most appeared one among all the airlines.
### 4.Most of the tweets are from Boston MA
### 5.We can see missing values in negativereason,negativereason_confidence,airline_sentiment_gold,negativereason_gold,
### tweet_coord,tweet_location,user_timezone
# In[7]:
data['negativereason'].value_counts()
# In[8]:
data['tweet_id']
# In[9]:
## checking for null values
data.isnull().sum()
# In[10]:
data.shape
# In[11]:
data['airline_sentiment']
# In[12]:
data['tweet_coord']
# In[16]:
data.info()
# In[17]:
data['airline_sentiment'].value_counts()
# In[18]:
data['airline_sentiment_confidence'].value_counts()
# In[19]:
## number of values with airline_sentiment_confidence<=0.5
(data['airline_sentiment_confidence']<=0.5).value_counts()
# ### Sentiment for each airline
# #### 1.we look for total number of tweets for each airline
# #### 2.Then we will calculate the number of positive,negative,nuetral tweets for each airline
# #### 3.we plot those counts of sentiments for each airline
# In[20]:
print("total number of tweets for each airline \n",data.groupby('airline')['airline_sentiment'].count().sort_values(ascending=False))
# In[21]:
#Plotting the number of tweets each airlines has received
colors=sns.color_palette("husl", 10)
pd.Series(data["airline"]).value_counts().plot(kind = "bar",
color=colors,figsize=(8,6),fontsize=10,rot = 0, title = "Total No. of Tweets for each Airlines")
plt.xlabel('Airlines', fontsize=10)
plt.ylabel('No. of Tweets', fontsize=10)
# In[22]:
airlines=['United','US Airways','American','Southwest','Delta','Virgin America']
plt.figure(1,figsize=(15,9)) ## Represents the width and height of overall figure
for i in airlines:
indices=airlines.index(i) ## will return the indices 0,1,2,3,4,5 for respective values of i
## i.e. for i='United',indices=0 and so on for other values
plt.subplot(2,3,indices+1) ## (x,y,z)it represents the x=height,y=width of plot and z= plot traversal towards right
## the values should be 1<=num<=6 ,where num is x,y,z
new_df=data[data['airline']==i]
count=new_df['airline_sentiment'].value_counts()
Index=[1,2,3]
plt.bar(Index,count,color=['red','grey','green'])
plt.xticks(Index,['negative','nuetral','positive'])
plt.ylabel("count Mood")
plt.xlabel("Mood")
plt.title("count of moods of"+i)
# #### The above plots convey us:
# ##### 1.United,US Airways and the American airlines are the ones which recieve more negative tweets
# ##### 2.VirginAmerica is the airlines with most balanced tweets
# In[23]:
#Plotting the number of each type of sentiments
colors=sns.color_palette("husl", 10)
pd.Series(data["airline_sentiment"]).value_counts().plot(kind = "bar",
color=colors,figsize=(8,6),rot=0, title = "Total No. of Tweets for Each Sentiment")
plt.xlabel('Sentiments', fontsize=10)
plt.ylabel('No. of Tweets', fontsize=10)
# In[24]:
colors=sns.color_palette("husl", 10)
pd.Series(data["airline_sentiment"]).value_counts().plot(kind="pie",colors=colors,
labels=["negative", "neutral", "positive"],explode=[0.05,0.02,0.04],
shadow=True,autopct='%.2f', fontsize=12,figsize=(6, 6),title = "Total Tweets for Each Sentiment")
# ### The most used words in Positive ,Negative and Neutral tweets
# #### 1.wordcloud is the best way to identify the most used words
# #### 2.Wordcloud is a great tool for visualizing nlp data.
# #### 3.The larger the words in the wordcloud image , the more is the frequency of that word in our text data.
# In[25]:
from wordcloud import WordCloud ,STOPWORDS
# ### wordcloud for negative sentiment of tweets
# In[26]:
new_df=data[data['airline_sentiment']=='negative']
words = ' '.join(new_df['text'])
cleaned_word = " ".join([word for word in words.split()
if 'http' not in word
and not word.startswith('@')
and word != 'RT'
])
wordcloud = WordCloud(stopwords=STOPWORDS,
background_color='black',
width=3000,
height=2500
).generate(cleaned_word)
plt.figure(1,figsize=(12, 12))
plt.imshow(wordcloud)
plt.axis('off')
plt.show()
# In[27]:
## In a wordcloud the words which are bigger are the once which occured the most in our given text
## The words which are bigger in the above negative sentiment wordcloud are the ones having more influence among
## the negative sentimnet texts.
## i.e. Customer service,late flight,cant tell,cancelled flight,plane,help,delay etc.. are most occured and influenced words for negative sentiments.
# In[28]:
#Plotting all the negative reasons
color=sns.color_palette("husl", 10)
pd.Series(data["negativereason"]).value_counts().plot(kind = "bar",
color=color,figsize=(8,6),title = "Total Negative Reasons")
plt.xlabel('Negative Reasons', fontsize=10)
plt.ylabel('No. of Tweets', fontsize=10)
# In[29]:
color=sns.color_palette("husl", 10)
pd.Series(data["negativereason"]).value_counts().head(5).plot(kind="pie",
labels=["Customer Service Issue", "Late Flight", "Can't Tell","Cancelled Flight","Lost Luggage"],
colors=color,autopct='%.2f',explode=[0.05,0,0.02,0.03,0.04],shadow=True,
fontsize=12,figsize=(6, 6),title="Top 5 Negative Reasons")
# ## Word cloud for positive sentiments
# In[30]:
new_df=data[data['airline_sentiment']=='positive']
words = ' '.join(new_df['text'])
cleaned_word = " ".join([word for word in words.split()
if 'http' not in word
and not word.startswith('@')
and word != 'RT'
])
wordcloud = WordCloud(stopwords=STOPWORDS,
background_color='black',
width=3000,
height=2500
).generate(cleaned_word)
plt.figure(1,figsize=(12, 12))
plt.imshow(wordcloud)
plt.axis('off')
plt.show()
# In[31]:
## The words which are bigger in the above positive sentiment wordcloud are the ones having more influence among
## the positive sentiment texts.
## i.e.thank,awesome,great,flight,trip etc.. are most occured and influenced words for positive sentiments.
# ## Word cloud for neutral sentiments
# In[32]:
df=data[data['airline_sentiment']=='neutral']
words = ' '.join(df['text'])
cleaned_word = " ".join([word for word in words.split()
if 'http' not in word
and not word.startswith('@')
and word != 'RT'])
wordcloud = WordCloud(stopwords=STOPWORDS,
background_color='black',
width=3000,
height=2500
).generate(cleaned_word)
plt.figure(1,figsize=(12, 12))
plt.imshow(wordcloud)
plt.axis('off')
plt.show()
# In[33]:
air_senti=pd.crosstab(data.airline, data.airline_sentiment)
air_senti
# In[34]:
percent=air_senti.apply(lambda a: a / a.sum() * 100, axis=1)
percent
# In[35]:
pd.crosstab(index =data["airline"],columns = data["airline_sentiment"]).plot(kind='bar',
figsize=(10, 6),alpha=0.5,rot=0,stacked=True,title="Airline Sentiment")
# In[36]:
percent.plot(kind='bar',figsize=(10, 6),alpha=0.5,
rot=0,stacked=True,title="Airline Sentiment Percentage")
# In[37]:
data['tweet_created'] = pd.to_datetime(data['tweet_created'])
data["date_created"] = data["tweet_created"].dt.date
# In[38]:
data["date_created"]
# In[39]:
df = data.groupby(['date_created','airline'])
df = df.airline_sentiment.value_counts()
df.unstack()
# In[40]:
from nltk.corpus import stopwords
stop_words=stopwords.words('english')
print(list(stop_words))
# In[41]:
def tweet_to_words(raw_tweet):
letters_only = re.sub("[^a-zA-Z]", " ",raw_tweet)
words = letters_only.lower().split()
stops = set(stopwords.words("english"))
meaningful_words = [w for w in words if not w in stops]
return( " ".join( meaningful_words ))
# In[42]:
def clean_tweet_length(raw_tweet):
letters_only = re.sub("[^a-zA-Z]", " ",raw_tweet)
words = letters_only.lower().split()
stops = set(stopwords.words("english"))
meaningful_words = [w for w in words if not w in stops]
return(len(meaningful_words))
# In[43]:
data['sentiment']=data['airline_sentiment'].apply(lambda x: 0 if x=='negative' else 1)
data.sentiment.head()
# In[44]:
#Splitting the data into train and test
data['clean_tweet']=data['text'].apply(lambda x: tweet_to_words(x))
data['Tweet_length']=data['text'].apply(lambda x: clean_tweet_length(x))
train,test = train_test_split(data,test_size=0.2,random_state=42)
# In[45]:
train_clean_tweet=[]
for tweets in train['clean_tweet']:
train_clean_tweet.append(tweets)
test_clean_tweet=[]
for tweets in test['clean_tweet']:
test_clean_tweet.append(tweets)
# In[46]:
from sklearn.feature_extraction.text import CountVectorizer
v = CountVectorizer(analyzer = "word")
train_features= v.fit_transform(train_clean_tweet)
test_features=v.transform(test_clean_tweet)
# In[51]:
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC, LinearSVC, NuSVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier
from sklearn.metrics import accuracy_score
# In[52]:
Classifiers = [
LogisticRegression(C=0.000000001,solver='liblinear',max_iter=200),
KNeighborsClassifier(3),
SVC(kernel="rbf", C=0.025, probability=True),
DecisionTreeClassifier(),
RandomForestClassifier(n_estimators=200),
AdaBoostClassifier()]
# In[53]:
dense_features=train_features.toarray()
dense_test= test_features.toarray()
Accuracy=[]
Model=[]
for classifier in Classifiers:
try:
fit = classifier.fit(train_features,train['sentiment'])
pred = fit.predict(test_features)
except Exception:
fit = classifier.fit(dense_features,train['sentiment'])
pred = fit.predict(dense_test)
accuracy = accuracy_score(pred,test['sentiment'])
Accuracy.append(accuracy)
Model.append(classifier.__class__.__name__)
print('Accuracy of '+classifier.__class__.__name__+' is '+str(accuracy))
# In[55]:
Index = [1,2,3,4,5,6]
plt.bar(Index,Accuracy)
plt.xticks(Index, Model, rotation=45)
plt.ylabel('Accuracy')
plt.xlabel('Model')
plt.title('Accuracies of Models')
|
c9361ac9212e8bd0441b05a26940729dd6915861 | itsMagondu/python-snippets | /fib.py | 921 | 4.21875 | 4 | #This checks if a certain number num is a number in the fibbonacci sequence.
#It loops till the number is the sequence is either greater or equal to the number in the sequence.
#Thus we validate if the number is in the fibonacci sequence.
import sys
tot = sys.stdin.readline().strip()
try:
tot = int(tot)
except ValueError:
pass
def fibTest(f0,f1,f,num):
f0 = f1
f1 = f
f = f0+f1
if int(f) < int(num):
f0,f1,f,num = fibTest(f0,f1,f,num)
else:
if f == int(num):
print "IsFibo"
else:
print "IsNotFibo"
return f0,f1,f,num
def getFibnumber(f0,f1):
return f0+f1
while tot:
num = sys.stdin.readline().strip()
f0 = 0
f1 = 1
f = getFibnumber(f0,f1)
try:
num = int(num)
if num != 0 or num != 1:
fibTest(f0,f1,f,num)
tot -= 1
except ValueError:
pass
|
389887394ef680275f708fd4e8fc0370e3aafaf2 | itsMagondu/python-snippets | /utopia.py | 173 | 3.5 | 4 | doub = True
h = 1
cyc = 10
while cyc:
if doub == True:
h = h*2
doub = False
else:
h = h+1
doub = True
print h
cyc = cyc -1
|
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