blob_id stringlengths 40 40 | repo_name stringlengths 5 119 | path stringlengths 2 424 | length_bytes int64 36 888k | score float64 3.5 5.22 | int_score int64 4 5 | text stringlengths 27 888k |
|---|---|---|---|---|---|---|
fcfe7333a63629913ea0c3cd56b447477182f188 | ides15/learn-python | /defaultdict.py | 744 | 3.796875 | 4 | from collections import defaultdict
dd = defaultdict(int) # int parameter is just the function int() which returns 0
words = str.split('red blue green red yellow blue red green green red')
for word in words:
dd[word] += 1
print(dd)
print(dd)
# above works because defaultdict will generate a key instead of throwing KeyError
# d = dict()
# words1 = str.split('red blue green red yellow blue red green green red')
# for word in words:
# d[word] += 1
# print(d)
# above won't work because d doesn't already have those keys
def isprimary(c):
if (c == 'red') or (c == 'blue') or (c == 'green'):
return True
return False
dd2 = defaultdict(bool)
for word in words:
dd2[word] = isprimary(word)
print(dd2) |
8e389b4f34ffe1de88cd94f147001e2a2bf27762 | vsseixaso/atal | /lista-1/6.py | 2,194 | 3.671875 | 4 | # https://www.geeksforgeeks.org/traveling-salesman-problem-using-branch-and-bound-2/
import math
MAX_N = float('inf')
def copy_to_final(curr_path):
final_path[:N + 1] = curr_path[:]
final_path[N] = curr_path[0]
def first_min(adj, i):
min = MAX_N
for k in range(N):
if adj[i][k] < min and i != k:
min = adj[i][k]
return min
def second_min(adj, i):
first, second = MAX_N, MAX_N
for j in range(N):
if i == j:
continue
if adj[i][j] <= first:
second = first
first = adj[i][j]
elif(adj[i][j] <= second and adj[i][j] != first):
second = adj[i][j]
return second
def tsp_rec(adj, curr_bound, curr_weight, lvl, curr_path, vis):
global final_res
if lvl == N:
if adj[curr_path[lvl - 1]][curr_path[0]] != 0:
curr_res = curr_weight + adj[curr_path[lvl - 1]][curr_path[0]]
if curr_res < final_res:
copy_to_final(curr_path)
final_res = curr_res
return
for i in range(N):
if (adj[curr_path[lvl-1]][i] != 0 and vis[i] == False):
temp = curr_bound
curr_weight += adj[curr_path[lvl - 1]][i]
if lvl == 1:
curr_bound -= ((first_min(adj, curr_path[lvl - 1]) +
first_min(adj, i)) / 2)
else:
curr_bound -= ((second_min(adj, curr_path[lvl - 1]) +
first_min(adj, i)) / 2)
if curr_bound + curr_weight < final_res:
curr_path[lvl] = i
vis[i] = True
tsp_rec(adj, curr_bound, curr_weight,
lvl + 1, curr_path, vis)
curr_weight -= adj[curr_path[lvl - 1]][i]
curr_bound = temp
vis = [False] * len(vis)
for j in range(lvl):
if curr_path[j] != -1:
vis[curr_path[j]] = True
def tsp(adj):
curr_bound = 0
curr_path = [-1] * (N + 1)
vis = [False] * N
for i in range(N):
curr_bound += (first_min(adj, i) + second_min(adj, i))
curr_bound = math.ceil(curr_bound / 2)
vis[0] = True
curr_path[0] = 0
tsp_rec(adj, curr_bound, 0, 1, curr_path, vis)
N=5
adj = [[0, 3, 1, 5, 8],
[3, 0, 6, 7, 9],
[1, 6, 0, 4, 2],
[5, 7, 4, 0, 3],
[8, 9, 2, 3, 0]]
final_path = [None] * (N + 1)
vis = [False] * N
final_res = MAX_N
tsp(adj)
print("Minimum cost :", final_res)
print("Path Taken : ", end = ' ')
for i in range(N + 1):
print(final_path[i], end = ' ') |
f486c40cb86fd4dce28ca2ab462b71104dfb1b9a | esix/competitive-programming | /e-olymp/~contest-9863/E/main.py | 77 | 3.546875 | 4 | from math import sqrt
a = int(input())
print (3 * a, a * a * sqrt(3) / 4) |
60effd6c7470cf511ddf65addba07459c7f19799 | artkra/stuff | /algos/incr_sub_seq.py | 361 | 3.703125 | 4 | def incsum(nums):
sumlist = nums[:]
for i in range(1,len(nums)):
for j in range(0,i):
if nums[j] < nums[i] and nums[i] + sumlist[j] > sumlist[i]:
sumlist[i] = nums[i] + sumlist[j]
print(sumlist)
return max(sumlist)
if __name__ == '__main__':
arr = [1, 101, 2, 3, 100, 4, 5]
print(incsum(arr)) |
d5be6be0426c6e5e9852da9f2abf48827077b92d | dev-himanshu/TA__Internship_Assignment_Solution | /Question-2.py | 2,300 | 4.09375 | 4 | import re
def supermarket_shopping(budgets):
product_name = input("\nEnter product : ")
product_quantity = float(re.findall(r"[-+]?\d*\.\d+|\d+", input("Enter quantity : "))[0])
product_price = float(input("Enter price : "))
amount_left = 0
for values in shopping_list.values():
amount_left += values[1]
amount_left = budgets - amount_left
if amount_left < product_price:
print("\nCan't buy the product because it's price is more than left amount.\n")
else:
amount_left = 0
if product_name in shopping_list:
shopping_list[product_name][0], shopping_list[product_name][1] = product_quantity, product_price
else:
shopping_list[product_name] = []
shopping_list[product_name].append(product_quantity)
shopping_list[product_name].append(product_price)
for values in shopping_list.values():
amount_left += values[1]
amount_left = budgets - amount_left
print("\nAmount left : {0}.\n".format(amount_left))
if __name__ == "__main__":
shopping_list = {}
budget = int(input("Enter Your Budget : "))
while True:
choice = input(
"1. Add an item.\n2. Exit.\nEnter Your Choice : ")
if choice == "1":
supermarket_shopping(budgets=budget)
elif choice == "2":
amount_left = 0
for values in shopping_list.values():
amount_left += values[1]
amount_left = budget - amount_left
product = ""
max_price_product = 0.0
for j, i in shopping_list.items():
if i[1] <= amount_left:
if max_price_product < i[1]:
product = j
max_price_product = i[1]
if len(product):
print("\nAmount left can buy you {0}.\n".format(product))
print("Grocery List is :")
print("Product Name\tQuantity\tPrice")
for i, j in shopping_list.items():
print(i, "\t", str(j[0]) + " kg", "\t", j[1])
else:
exit("Goodbye!!!")
else:
print("!!! Wrong Selection.\n")
|
8c4b99c9226b67d9eef862620087664a1ef78c73 | Priyankasgowda/90dayschallenge | /p71.py | 1,030 | 4 | 4 | # A recursive Python3 program to print maximum
# number of A's using following four keys
# A recursive function that returns
# the optimal length string for N keystrokes
def findoptimal(N):
# The optimal string length is
# N when N is smaller than
if N<=6:
return N
# Initialize result
maxi=0
# TRY ALL POSSIBLE BREAK-POINTS
# For any keystroke N, we need
# to loop from N-3 keystrokes
# back to 1 keystroke to find
# a breakpoint 'b' after which we
# will have Ctrl-A, Ctrl-C and then
# only Ctrl-V all the way.
for b in range(N-3,0,-1):
curr=(N-b-1)*findoptimal(b)
if curr>maxi:
maxi=curr
return maxi
# Driver program
if __name__=='__main__':
# for the rest of the array we will
# rely on the previous
# entries to compute new ones
for n in range(1,21):
print('Maximum Number of As with ',n,'keystrokes is '
,findoptimal(n))
|
882aaf1d82b6e26c2139b4ff0e8453cd4b1eba46 | 553672759/xxgit | /python/old/sort/bubble_sort.py | 256 | 4.125 | 4 | '''
Created on 2017-1-4
@author:
'''
def bubble_sort(lists):
count=len(lists)
for i in range(0,count):
for j in range(i+1,count):
if lists[i]>lists[j]:
lists[i],lists[j]=lists[j],lists[i]
return lists
|
309eb4aecb11478948d6ee6286213efb5f88c92f | RajDeliwala/PythonPractice | /WholefoodMarketAssesment.py | 907 | 3.84375 | 4 | #Assesment from WholeFoods Market that invloved dealing with queues which have values and prioritys
class PriorityQueue:
def __init__(self):
self.size = 0
self.q = []
def enqueue(self, value, priority):
if self.size >= 5:
self.q.sort()
if self.q[-1] < priority:
self.q.pop()
self.q.append((value,priority))
self.q.append((value,priority))
self.size += 1
def dequeue(self):
if self.size == 0:
return
self.q.pop()
self.size -= 1
def print(self):
self.q.sort()
for tuple in self.q:
print(tuple)
PQ = PriorityQueue()
PQ.enqueue(5,2)
PQ.enqueue(6,1)
PQ.enqueue(7,-1)
PQ.enqueue(3,0)
PQ.dequeue()
PQ.dequeue()
PQ.enqueue(8,3)
PQ.print()
|
446daa60cf9e5145dce7c145ec3be6053f0ade78 | Visorgood/CodeBasics | /Python/BubbleSort.py | 165 | 3.75 | 4 | def BubbleSort(A):
p = True
while p:
p = False
for i in range(1, len(A)):
if A[i - 1] > A[i]:
t = A[i - 1]
A[i - 1] = A[i]
A[i] = t
p = True |
dab6bd15e17b6c29651d359e8b5d223c2e162dc6 | kayodeomotoye/Code_Snippets | /timezones.py | 1,154 | 3.5 | 4 | import pytz
from datetime import datetime, tzinfo
MEETING_HOURS = range(6, 23) # meet from 6 - 22 max
TIMEZONES = set(pytz.all_timezones)
def within_schedule(utc, *timezones):
"""Receive a utc datetime and one or more timezones and check if
they are all within schedule (MEETING_HOURS)"""
try:
tz = [pytz.timezone(_timezone) for _timezone in timezones]
except:
raise ValueError
tz_hour = [tz.fromutc(utc).hour for tz in tz]
return all(item in MEETING_HOURS for item in tz_hour)
#pybites
import pytz
MEETING_HOURS = range(6, 23) # meet from 6 - 22 max
TIMEZONES = set(pytz.all_timezones)
def within_schedule(utc, *timezones):
"""Receive a utc datetime and one or more timezones and check if
they are all within schedule (MEETING_HOURS)"""
utc_aware = utc.replace(tzinfo=pytz.utc)
localized_times = []
for tz in timezones:
if tz not in TIMEZONES:
raise ValueError('not a valid timezone')
tz = pytz.timezone(tz)
localized_times.append(utc_aware.astimezone(tz))
return all(dt.hour in MEETING_HOURS for dt in localized_times)
|
695b7faa4a5c1128c2dcf4f07f148a78ea8f46b1 | heyker/LeetCodeCoding | /src/Contest/16B_1.py | 514 | 3.625 | 4 | #encoding=utf-8
'''
Created on 2016年12月22日
@author: heyker
'''
class Solution(object):
def constructRectangle(self, area):
"""
:type area: int
:rtype: List[int]
"""
if area<=0:
return [0,0]
import math
inter=int(math.sqrt(area))
for i in range(inter,1,-1):
if area%i==0:
return [area/i,i]
return [area,1]
if __name__ == '__main__':
s=Solution()
print s.constructRectangle(1)
pass
|
112dc0431aefe42a952cef20822febbc4220bd0f | dtung011/dtung011 | /Fundamental/Session_3/mxn_ostars.py | 271 | 3.9375 | 4 | m = int(input("Enter number of colummns: "))
n = int(input("Enter number of rows: "))
# print ("*" * n)
for i in range (n):
for j in range (m):
if (i+j) % 2 == 0:
print ("*", end="")
else:
print ("o", end="")
print ("\n") |
2e412d24d1cff9ab36648c80f5ae6d8fd8aca43c | vatasescu-predi-andrei/lab7-Python | /lab 7 task 7.1 chal.py | 375 | 4.21875 | 4 | even=0
odd=0
print("Enter a series of integers, when you are done entering, enter '0'")
userInput=int(input("Please enter a series of integers:"))
while userInput!=0:
if userInput%2==0:
even=even+1
else:
odd=odd+1
userInput=int(input("Please enter a series of integers:"))
print("Even numbers:",even)
print("Odd numbers:",odd)
|
9129c5ca239f03b2e96fa35b0718202cf2835c35 | JiHyeonMon/-pre-Algorithm | /bak-class1/day5/bak10886.py | 452 | 3.546875 | 4 | #10886
#준희는 자기가 팀에서 귀여움을 담당하고 있다고 생각한다. 하지만 연수가 볼 때 그 의견은 뭔가 좀 잘못된 것 같았다. 그렇기에 설문조사를 하여 준희가 귀여운지 아닌지 알아보기로 했다.
cnt = 0
for i in range(int(input())):
if int(input()) == 1:
cnt+=1
else:
cnt-=1
if cnt>0:
print("Junhee is cute!")
else:
print("Junhee is not cute!")
|
ee5e7d04569a6a72a3bb3d7f32c0d39d4943f02d | jainendrak/python-training | /Examples/9NetWorking,Multithreading,re/re/re3.py | 417 | 3.71875 | 4 | import re
text = 'abbaaabbbbaaaaab'
pattern='ab'
occur= len(re.findall(pattern , text))
e=0
while(occur>0):
match = re.search(pattern,text[e:] )
s = match.start()
e = match.end()
print("occurence at (%d--%d)"%(s+e,e+e))
occur-=1
"""
for match in re.findall(pattern, text):
print 'Found at "[%s,%s]"' %(match.start ,match.end)
""" |
6867d43c20c5b709d219921b8ecb40bbcd351d51 | soph714/6.00.1xFall2017 | /Midterm/midterm_5.py | 514 | 3.71875 | 4 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 15 15:58:08 2017
@author: Ted
"""
def dict_invert(d):
'''
code by theosopher
10/15/2017
6.00.1x MITx edX midterm
d: dict
Returns an inverted dictionary according to the instructions above
'''
newD = {}
for key in d.keys():
if d[key] in newD:
newD[d[key]].append(key)
newD[d[key]] = sorted(newD[d[key]])
else:
newD[d[key]] = [key]
return newD |
9c726588d9174979efdb88e236a16af3e017198d | jamiebrynes7/advent-of-code-2017 | /day_3/challenge2.py | 1,952 | 3.828125 | 4 | import sys
import math
def main():
# Get input arguments.
try:
target_value = int(sys.argv[1])
except IndexError:
print("Usage: python challenge1.py <target_value>")
exit(1)
nodes = [Node(0, 0)]
nodes[0].value = 1
square_size = 1
while True:
coords = getListOfCoords(square_size)
for coord in coords:
x, y = coord
node = Node(x, y)
node.findAdjacentNodes(nodes)
value = node.calculateNodeValue()
if value > target_value:
print("The answer is: " + str(value))
return
print("Calculated value of node at {0},{1} to be {2}.".format(x,y,value))
nodes.append(node)
square_size += 1
def getListOfCoords(square_size):
coords = []
x = square_size
y = -square_size + 1
# Go along right edge
for i in range(y,square_size):
coords.append((x,i))
y = square_size
# Go along top edge
for i in range(x, -square_size, -1):
coords.append((i,y))
x = -square_size
# Go along left edge
for i in range(y, -square_size, -1):
coords.append((x,i))
y = -square_size
# Go along bottom edge
for i in range(x, square_size + 1):
coords.append((i,x))
return coords
class Node :
def __init__(self, x, y):
self.x_coord = x
self.y_coord = y
self.adjacent_nodes = []
self.value = 0
def findAdjacentNodes(self, node_list):
for node in node_list:
if abs(node.x_coord - self.x_coord) <= 1 and abs(node.y_coord - self.y_coord) <= 1:
self.adjacent_nodes.append(node)
def calculateNodeValue(self):
self.value = sum(node.value for node in self.adjacent_nodes)
return self.value
if __name__ == "__main__":
main()
|
923e5714e5ad0c9fb3da55e4c8ff3e5a5a1ef338 | paukey/python_pra | /learn_4.5.py | 315 | 4 | 4 | #2017年7月15日
#元组tuple()不能修改,但是可以给存储元组的变量赋值 list[]支持修改
dimensions=(200,40)
for dimension in dimensions:
print('原始元组'+str(dimension))
print('\n')
dimensions=(100,100)
for dimension in dimensions:
print('重新赋值后'+str(dimension))
|
e30869245d2df582300dc65a40d735dc11cf80b7 | nayyanmujadiya/ML-Python-Handson | /src/ml/pca_data_visualization.py | 3,408 | 3.71875 | 4 | '''
Load Iris Dataset
The Iris dataset is one of datasets scikit-learn comes with that do not require the downloading of any file from some external website. The code below will load the iris dataset.
'''
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data"
# loading dataset into Pandas DataFrame
df = pd.read_csv(url, names=['sepal length','sepal width','petal length','petal width','target'])
print(df.head())
'''
Standardize the Data
Since PCA yields a feature subspace that maximizes the variance along the axes, it makes sense to standardize the data, especially, if it was measured on different scales. Although, all features in the Iris dataset were measured in centimeters, let us continue with the transformation of the data onto unit scale (mean=0 and variance=1), which is a requirement for the optimal performance of many machine learning algorithms.
'''
features = ['sepal length', 'sepal width', 'petal length', 'petal width']
x = df.loc[:, features].values
y = df.loc[:,['target']].values
x = StandardScaler().fit_transform(x)
print(pd.DataFrame(data = x, columns = features).head())
'''
PCA Projection to 2D
The original data has 4 columns (sepal length, sepal width, petal length, and petal width). In this section, the code projects the original data which is 4 dimensional into 2 dimensions. I should note that after dimensionality reduction, there usually isn’t a particular meaning assigned to each principal component. The new components are just the two main dimensions of variation.
'''
pca = PCA(n_components=2)
principalComponents = pca.fit_transform(x)
principalDf = pd.DataFrame(data = principalComponents, columns = ['principal component 1', 'principal component 2'])
principalDf.head(5)
df[['target']].head()
finalDf = pd.concat([principalDf, df[['target']]], axis = 1)
finalDf.head(5)
'''
Visualize 2D Projection
This section is just plotting 2 dimensional data. Notice on the graph below that the classes seem well separated from each other.
'''
fig = plt.figure(figsize = (8,8))
ax = fig.add_subplot(1,1,1)
ax.set_xlabel('Principal Component 1', fontsize = 15)
ax.set_ylabel('Principal Component 2', fontsize = 15)
ax.set_title('2 Component PCA', fontsize = 20)
targets = ['Iris-setosa', 'Iris-versicolor', 'Iris-virginica']
colors = ['r', 'g', 'b']
for target, color in zip(targets,colors):
indicesToKeep = finalDf['target'] == target
ax.scatter(finalDf.loc[indicesToKeep, 'principal component 1']
, finalDf.loc[indicesToKeep, 'principal component 2']
, c = color
, s = 50)
ax.legend(targets)
ax.grid()
plt.show()
'''
Explained Variance
The explained variance tells you how much information (variance) can be attributed to each of the principal components. This is important as while you can convert 4 dimensional space to 2 dimensional space, you lose some of the variance (information) when you do this. By using the attribute explained_variance_ratio_, you can see that the first principal component contains 72.77% of the variance and the second principal component contains 23.03% of the variance. Together, the two components contain 95.80% of the information.
'''
print(pca.explained_variance_ratio_)
|
2ef9752d84bbb0cb63ba346daef045407b502e6d | mrimj106/MriMJ | /check_path_exits.py | 211 | 3.640625 | 4 | #Program to check if path exists or not
import os
f1=os.path.exists("C:/Users/mritsing/Desktop/Python/test1/test3")
if f1==True:
print ("path exists")
else:
print ("path does not exists")
|
b3526d901669658727390ba18365b374a38d84b5 | Mateusmsouza/Rascrapdinha | /BS1.py | 1,473 | 4 | 4 | html = """
<html><head><title>The Dormouse's story</title></head>
<body>
<p class="title"><b>The Dormouse's story</b></p>
<p class="story">Once upon a time there were three little sisters; and their names were
<a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>,
<a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and
<a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>;
and they lived at the bottom of a well.</p>
<p class="story">...</p>
"""
from bs4 import BeautifulSoup
Sopinha = BeautifulSoup(html, 'html.parser')
print(Sopinha.prettify()) # Mostra a variável identada
print("-----------------------------------")
print(Sopinha.title.name) # Mostra o conteudo de <title>
print("-----------------------------------")
print(Sopinha.body) # Busca e exibe a tag body e seu conteúdo
print("-----------------------------------")
print(Sopinha.p['class']) # Exibe a class atribuída a primeir incidência de "p" com class
print("-----------------------------------")
print(Sopinha.a) # Exibe a primeira incidência da tag 'a'
print("-----------------------------------")
print(Sopinha.find_all('a')) # Exibe todas as incidências da tag ('<a>'), separando por virgula
print("-----------------------------------")
print(Sopinha.find(id="link2")) # Exibe a incidência que contém exatamente 'link2' em Id, *caso seja apenas link, não retornará a incidência link2*
print("-----------------------------------")
|
80252d9addcfa50b14ea7999bbb26b30b6afbdd5 | mai20-meet/meetyl1201819 | /lab6.py | 1,149 | 3.984375 | 4 | import turtle
from turtle import Turtle
from random import randint
class Square(Turtle):
def __init__(self, size, color):
Turtle.__init__(self)
self.shapesize= size
turtle.shape("square")
turtle.colormode(255)
# turtle.color(color)
'''
r = randint(0,255)
g = randint(0,255)
b = randint(0,255)
turtle.color((r,g,b))
'''
def random_color(self):
r = randint(0,255)
g = randint(0,255)
b = randint(0,255)
self.color((r,g,b))
self.shape("square")
# t1=Square(10, "blue")
# t1.random_color()
class Hexagon(Turtle):
def __init__(self,size,color,speed):
Turtle.__init__(self)
self.size = size
turtle.begin_poly()
turtle.fillcolor(color)
turtle.speed(speed)
turtle.penup()
turtle.backward(50)
turtle.fd(50)
turtle.right(50)
turtle.fd(50)
turtle.rt(50)
turtle.fd(50)
turtle.rt(50)
turtle.fd(50)
turtle.rt(50)
turtle.fd(50)
turtle.rt(50)
turtle.fd(50)
turtle.rt(50)
turtle.fd(50)
turtle.pendown()
turtle.end_poly()
H = turtle.get_poly()
turtle.register_shape("myFavouriteHexagon", H)
turtle.shape("myFavouriteHexagon")
H=Hexagon(10, "pink",50)
turtle.mainloop()
# |
b59e3d6be4d3c9a9fd56aa98468bf138e1617392 | qw20140729/vip5 | /day3/Day3_Assignment.py | 3,210 | 4.25 | 4 | # 1、打印小猫爱吃鱼，小猫要喝水
class Cat(object):
def __init__(self,name):
self.name = name
def eat(self,food,water):
print("{0}爱吃{1}, {0}要喝{2}".format(self.name,food,water))
def main_ex1():
cat = Cat("小猫")
cat.eat('鱼','水')
"""
2、小明爱跑步，爱吃东西。
1）小明体重75.0公斤
2）每次跑步会减肥0.5公斤
3）每次吃东西体重会增加1公斤
4）小美的体重是45.0公斤
"""
class Person(object):
def __init__(self,name,wg):
self.name = name
self.wg = wg
def weight(self):
print("{0}的体重是{1}公斤".format(self.name,self.wg))
class PerXM(Person):
def __init__(self,name,wg):
Person.__init__(self,name,wg)
def interest(self):
print("{0}爱跑步，爱吃东西。".format(self.name))
def eat(self):
self.weight()
self.wg += 1
print("每次吃东西体重会增加1公斤,体重变为：",self.wg)
def run(self):
self.weight()
self.wg -= 0.5
print("每次跑步会减肥0.5公斤,体重变为：",self.wg)
def main_ex2():
xiaoming = PerXM("小明",75.0)
xiaoming.eat()
xiaoming.run()
# 小美的体重是45.0公斤
xiaom = Person("小美", '45.0')
xiaom.weight()
"""
3、摆放家具
需求：
1）.房子有户型，总面积和家具名称列表
新房子没有任何的家具
2）.家具有名字和占地面积，其中
床：占4平米
衣柜：占2平面
餐桌：占1.5平米
3）.将以上三件家具添加到房子中
4）.打印房子时，要求输出:户型，总面积，剩余面积，家具名称列表
"""
""""
分析：类--房子，方法--添加，属性--总面积、户型、床、衣柜、餐桌
"""
class House(object):
def __init__(self,area,houseType):
self.area = area
self.houseType = houseType
self.bed = 4
self.closet = 2
self.diningTable = 1.5
def add(self):
room = int(self.houseType[0])
hall = int(self.houseType[2])
reArea = self.area-(self.bed+self.closet)*room-self.diningTable*hall
return room,hall,reArea
def print_re(self):
rooms,halls,re = self.add()
print("房子户型{0}，总面积{1}，剩余面积{2}，摆放{3}张床，{3}个衣柜，{4}个餐桌。".\
format(self.houseType,self.area,re,rooms,rooms,halls))
def main_ex3():
house = House(50,'3室1厅')
house.print_re()
"""
4.士兵开枪
需求：
1）.士兵瑞恩有一把AK47
2）.士兵可以开火(士兵开火扣动的是扳机)
3）.枪 能够 发射子弹(把子弹发射出去)
4）.枪 能够 装填子弹 --增加子弹的数量
"""
"""
分析：类-士兵、枪，属性--姓名、子弹，方法开火，发射，装填
"""
class Gun(object):
def __init__(self,bullet):
self.bullet = bullet
def shoot(self):
print(self.bullet.name)
pass
def chargeFull(self):
pass
class soldier(object):
def __init__(self,name):
self.name = name
def main_ex4():
sd = soldier("瑞恩")
gun = Gun(sd)
gun.shoot()
if __name__ == '__main__':
main_ex4()
|
c140cae71898811776201177f3394afcce683f02 | lhj0518/shingu | /11월3일 수업/yesterday.py | 490 | 3.625 | 4 | f=open("yesterday.txt",'r')
yesterday_lyric = ""
while 1:
line = f.readline()
if not line: break
yesterday_lyric=yesterday_lyric+line.strip()+"\n"
f.close()
n1_of_yesterday=yesterday_lyric.upper().count("YESTERDAY")
n2_of_yesterday=yesterday_lyric.count("Yesterday")
n3_of_yesterday=yesterday_lyric.count("yesterday")
print "Number of A Word 'YESTERDAY'",n1_of_yesterday
print "Number of A Word 'Yesterday'",n2_of_yesterday
print "Number of A Word 'yesterday'",n3_of_yesterday
|
8e84ba212d23c8a5a4f3000afbb04eef1d0b2912 | jkirlans5282/Seymour | /algorithm.py | 3,175 | 4.0625 | 4 | #Algorithm Test
#nested dictionary, {username:{resturant:rating}}
users = {
"tom":{"a":1,"b":1,"c":0,"d":-1,"h":1,"f":1},
"beth":{"a":1,"d":-1,"e":1},
"mike":{"b":1,"e":1,"h":1},
"emma":{"d":1,"g":0,"e":1}
}
def addUser(username):
users[username]={}
def addRestaurant(restaurant,username):
while True:
preference =input("[F]avorite, [L]iked, [D]isliked? ").lower()
if preference == "f":
preference = 1
break
elif preference == "l":
preference = 0
break
elif preference == "d":
preference = -1
break
else:
print("not a vaild option")
temp = users[username]
temp[restaurant] = preference
users[username] = temp
def userMatch(username):
otherUsersMatchScore = {}
user = users[username] # assigns users ratings to user
for key in users:
if key != username: # for all except username, We'll need to change this later to avoid lag once our data set gets larger.
name = key # assigns the username to name
temp = users[key] # assigns their ratings to temp
otherUsersMatchScore[name] = 0 # sets otherUsersMatchScore for the other user initially equal to zero
for key in temp: # For resturant rating pairs of the user that isnt the entered username
try:
otherUsersMatchScore[name] = otherUsersMatchScore[name] + (1 * temp[key] * user[key]) # scores the entered users similarity to other users by summing the overlaps in rating. Essentially. (both like it (1,1) adds one to score, one likes other dislikes subtracts one)
except KeyError:
print("keyerror") # hits this when the User has not also been to the resturant. Essentially does nothing.
print(otherUsersMatchScore)
reccommend(otherUsersMatchScore)
def reccommend(otherUsersMatchScore):
restaurants = {}
for key in otherUsersMatchScore:
name = key
weight = otherUsersMatchScore[key]
ratings = users[key] #looks at their ratings
for key in ratings:
try:
restaurants[key] = restaurants[key] + weight * ratings[key]
except KeyError:
restaurants[key] = weight
print(restaurants)
def main():
while True:
navigate =input("[N]ew user, [R]ate restaurant, [P]rint info, [M]atch users, [Q]uit? ").lower()
if navigate == "n":
username =input("Username? ").lower
addUser(username)
elif navigate == "r":
username =input("Username? ").lower()
restaurant =input("Restaurant? ").lower()
addRestaurant(restaurant,username)
elif navigate == "p":
print(users)
elif navigate == "m":
username =input("Username? ").lower()
userMatch(username)
elif navigate == "q":
break
else:
print("Not a valid input value")
main() |
b85955254f4fa2cb76da8df4638e01e2d29936c9 | kevinelong/tyg | /pilot/lib/board.py | 566 | 3.5625 | 4 | class Board:
def __init__(self, width=9, height=9):
self.width = width
self.height = height
self.content = []
def add_item(self, item):
self.content.append(item)
def draw(self):
for y in range(0, self.height):
for x in range(0, self.width):
symbol = "."
for item in self.content:
if item.position.x == x and item.position.y == y:
symbol = item.symbol
print(symbol, end=" ")
print("", end="\r\n") |
99dbfb4fd94a3edc96418bb54237374cdba94061 | Sampreet/Competitive-Programming | /HackerRank/Domains/001 Algorithms/001 Warmup/E - Compare the Triplets [Score If Else]/compare-the-triplets.py | 387 | 3.875 | 4 | def compare_the_triplets(arr_a, arr_b):
n = len(arr_a)
a = sum([1 for i in range(n) if arr_a[i] > arr_b[i]])
b = sum([1 for i in range(n) if arr_a[i] < arr_b[i]])
print(str(a) + ' ' + str(b))
if __name__ == '__main__':
arr_a = list(map(int, input().rstrip().split()))
arr_b = list(map(int, input().rstrip().split()))
compare_the_triplets(arr_a, arr_b) |
7a68d5f286c1b7608380418528fa93e8f557d08f | aparnapr121/python_practice | /mro.py | 390 | 3.546875 | 4 | class A():
def __init__(self):
print("inside A")
super().__init__()
class B(A):
def __init__(self):
print("inside B")
super().__init__()
class C():
def __init__(self):
print("inside C")
#super().__init__()
class D(B,C):
def __init__(self):
print("inside D")
super().__init__()
obj = D()
print(D.__mro__) |
6daee9e1c22c4113fffb60dbe92b1f7b736a379d | marinaoliveira96/python-exercises | /curso_em_video/0069.py | 615 | 3.78125 | 4 | maiores = masc = fem20 = 0
while True:
idade = int(input('Qual a sua idade? '))
if idade > 18:
maiores += 1
sexo = input("Qual é o seu sexo? [F/M] ").strip().lower()[0]
if sexo == 'm':
masc += 1
elif sexo == 'f':
if idade < 20:
fem20 += 1
c = ' '
while c not in 'sn':
c = input('Deseja continuar? [S/N]').strip().lower()[0]
if c == 'n':
break
print(f'''Programa encerrado
total de pessoas com mais de 18 anos igual a {maiores}
total de homens cadastrados igual a {masc}
Total de mulheres com menos de 20 anos igual a {fem20}''')
|
48733fd50e000ea4b216ff6debcdf231747e5a0d | AnaBVA/pythonCCG_2021 | /scripts/ejemplos/read_fasta.py | 314 | 3.515625 | 4 | my_file = open("data/4_dna_sequences.txt", "r")
my_file_contents = my_file.read()
print(my_file_contents)
print(len(my_file_contents))
# Abir archivo
file = open("data/4_dna_sequences.txt", "r")
# Leer las lineas
for line in file:
print("Length: " + str(len(line)) + " " + line)
# Cerrar archivo
file.close()
|
9c82bfb41fe94c2992c435746e516b2647d6ed07 | chenzhiyuan0713/Leetcode | /Easy/Q48.py | 483 | 4.03125 | 4 | """
709. 转换成小写字母
实现函数 ToLowerCase()，该函数接收一个字符串参数 str，并将该字符串中的大写字母转换成小写字母，之后返回新的字符串。
示例 1：
输入: "Hello"
输出: "hello"
示例 2：
输入: "here"
输出: "here"
示例 3：
输入: "LOVELY"
输出: "lovely"
"""
class Solution:
def toLowerCase(self, str: str) -> str:
return str.lower()
answer = Solution()
print(answer.toLowerCase("LOVELY")) |
3ccf0b4d342313ba0714bc6378c5c24ff71b27fe | marceloamaro/Python-Mombaca | /Lista Aula07 - Dicionários e Sets/02.py | 1,107 | 4.25 | 4 | """Escreva uma função que faça a verificação de existência de uma chave dentro de um dicionário. Caso a chave exista a função deve retornar o valor da chave, caso ela não exista, a função deve adicioná-la e retornar o dicionário."""
"""
def verificacao(d, chave):
if chave in d:
print(" Chave existe o valor é =", d[chave])
else:
print("nao presente")
#d[chave] = d.get(chave)
d[chave] = chave
print(d)
d = {'0': 1, '1': 2, '2': 3, '3': 4, '4': 5, '5': 6}
chave = input("digite o a chave para verificação:")
verificacao(d, chave)
"""
dados_pessoais={'nome':"Marcelo",
"idade": 27,
"cidade":'Mombaça',
"estado_civil":'casado'
}
chave=(input("Qual chave voce quer procurar\n"))
def verifica_chave(dados_pessoais, chave):
if chave in dados_pessoais:
print(dados_pessoais[chave])
else:
print("Chave não econtrada")
dados_pessoais[chave]=" "
print(dados_pessoais)
verifica_chave(dados_pessoais,chave) |
82468988688a878e148712b1744ef607e1bfbff6 | AbhiniveshP/Competitive-Coding-4 | /PalindromeLL.py | 1,913 | 3.90625 | 4 | '''
Solution
1. Find the mid of the LL using slow and fast pointers.
2. Reverse the second part of the LL.
3. Check each value in each half of the LL in parallel and return False if not equal, else return True
Time Complexity: O(n) and Space Complexity: O(1)
--- Passed all testcases on Leetcode successfully
'''
# Definition for singly-linked list.
class ListNode(object):
def __init__(self, x):
self.val = x
self.next = None
class Solution(object):
def __reverse(self, head):
'''
:param head: head of the Linked list
:return: reversed Linked List
'''
prevNode = None
currNode = head
nextNode = head.next
while (nextNode != None):
currNode.next = prevNode
prevNode = currNode
currNode = nextNode
nextNode = nextNode.next
currNode.next = prevNode
return currNode
def isPalindrome(self, head):
"""
:type head: ListNode
:rtype: bool
"""
# edge case check
if (head == None or head.next == None):
return True
# initialize slow and fast pointers to find mid of the Linked List
slowNode = head
fastNode = head.next
# find the mid node iteratively
while (fastNode != None and fastNode.next != None):
slowNode = slowNode.next
fastNode = fastNode.next.next
# reverse second half and initialize slow pointer to head again
fastNode = self.__reverse(slowNode.next)
slowNode.next = None
slowNode = head
# check each value in each half of the LL in parallel
while (slowNode != None and fastNode != None):
if (slowNode.val != fastNode.val):
return False
slowNode = slowNode.next
fastNode = fastNode.next
return True |
6dd515adb8689fb2079893bad3a0347cecd9daf4 | NearJiang/Python-route | /stopwatch/test seven.py | 485 | 3.53125 | 4 | import time as q
class stopwatch:
def start(self):
self.begin=q.localtime()
print('开始')
def stop(self):
self.end=q.localtime()
self._calc()
print('结束')
def _calc(self):
self.lasted=[]
self.prompt='共运行了'
for index in range(6):
self.lasted.append(self.end[index]-self.begin[index])
self.prompt += str(self.lasted[index])
print(self.prompt)
|
3ae3f69f13deff622499a9d28025cd8f50798106 | Tanakornguy/Tanakorn_Khuntamanee-CS01 | /CS01-Grading.py | 976 | 3.5625 | 4 | a = int ( input ( ' กรอกคะแนนเก็บ! *คะแนนเก็บไม่เกิน 30 คะแนน : ' ) )
b = int ( input ( ' กรอกคะแนนสอบกลางภาค! *คะแนนสอบกลางภาคไม่เกิน 30 คะแนน : ' ) )
c = int ( input ( ' กรอกคะแนนสอบปลายภาค! *คะแนนสอบปลายภาคไม่เกิน 40 คะแนน : ' ) )
d = a + b + c
if ( d >= 80 ) :
print ( ' ได้เกรด A ' )
elif ( d >= 75 ) :
print ( ' ได้เกรด B+ ' )
elif ( d >= 70 ) :
print ( ' ได้เกรด B ' )
elif ( d >= 65 ) :
print ( ' ได้เกรด C+ ' )
elif ( d >= 60 ) :
print ( ' ได้เกรด C ' )
elif ( d >= 55 ) :
print ( ' ได้เกรด D+ ')
elif ( d >= 50 ) :
print ( ' ได้เกรด D ')
else :
print ( ' ได้เกรด C ' ) |
a592acca804a50637567eb968d3b9118de7dc4f2 | freylis/pyritms | /sort_utils/selection_sort.py | 1,158 | 3.953125 | 4 | """
Сортировка выбором
Бежим по массиву из N элементов N раз, запоминая позицию I
Бежим по массиву от позиции I до конца, запоминая минимальный встреченный элемент и его позицию K
Меняем местами элементы в позиции I и K
n^2
"""
from sort_utils import base
def sort(items):
for index in range(len(items)):
min_element = None
subindex = 0
index_for_replace = None
for subindex, tmp_val in enumerate(items[index:]):
if min_element is None:
min_element = tmp_val
index_for_replace = subindex
continue
if tmp_val < min_element:
min_element = tmp_val
index_for_replace = subindex
continue
if index_for_replace and index != subindex:
items[index], items[index_for_replace + index] = items[index_for_replace + index], items[index]
return items
if __name__ == '__main__':
base.sorting_checker(sort)
|
2fa31b41928f3ff212ae8e1c24ca63580ebb0880 | vsuriya93/Coding-Practice | /Hackerrank/Project Euler/1_multiplesOf3and5.py | 306 | 3.578125 | 4 | # Enter your code here. Read input from STDIN. Print output to STDOUT
n=raw_input()
n=int(n)
for i in range(0,n):
m=raw_input()
m=int(m)
output=0
k=3
a=(m-1)//3
b=(m-1)//5
common=(m-1)/15
output=(3*(a*(a+1))//2)+(5*(b*(b+1))//2)- (15*(common*(common+1))//2)
print output |
5711fb107c6b0136c85a27c6769767055d6e75c4 | overbe/alien_invasion | /data.py | 440 | 3.53125 | 4 | import json
class Storage:
"""A class to manage the data."""
def __init__(self):
self.file = 'db/data.json'
def get_score(self):
try:
with open(self.file) as f:
score = json.load(f)
except FileNotFoundError:
return 0
else:
return score
def set_score(self, score):
with open(self.file, 'w') as f:
json.dump(score, f) |
156638b071e4ae0e12e59da75da6c0733e85722d | nikita1610/100PythonProblems | /Problem89/Day89.py | 202 | 3.703125 | 4 | def check_binary_palindrome(n):
l=[]
while(n>0):
l.append(n%2)
n=n//2
b1="".join(map(str,l))
b2=b1[::-1]
return b1==b2
n=9
ans=check_binary_palindrome(n)
print(ans)
|
fc6b82ceef8a25ef923b62d18e46cb0b03e64166 | Aasthaengg/IBMdataset | /Python_codes/p02401/s270151385.py | 307 | 3.921875 | 4 | #coding:utf-8
def cal(a, b, op):
if op=="+":
return a + b
elif op == "-":
return a - b
elif op == "*":
return a * b
elif op == "/":
return a//b
else:
return -1
while True:
buff = input().split()
a = int(buff[0])
b = int(buff[2])
op = buff[1]
if op == "?":
break
print(cal(a, b, op)) |
d35f55c3d17304bd24f14052553d79f524e7bf0e | vinsonlee/projecteuler | /14.py | 534 | 3.65625 | 4 | N = 1000000
# Cache of Collatz results.
C = {}
C[1] = 1
def collatz(x):
"""
Calculate the number of terms for the sequence starting with x.
"""
if x in C:
return C[x]
elif x % 2 == 0:
answer = 1 + collatz(x / 2)
else:
answer = 1 + collatz(3 * x + 1)
C[x] = answer
return answer
longest_chain = 1
starting_number = 1
for i in range(2, N):
chain = collatz(i)
if chain > longest_chain:
longest_chain = chain
starting_number = i
print starting_number
|
d9ffde7cd3e857be7afde55d4e654c51a3d31acf | maurya-subhashini1/List | /maigic_sqour.py | 714 | 3.59375 | 4 |
maigic_square = [
[8, 3, 4],
[1, 5, 9],
[6, 7, 2]
]
i=0
sum=0
while i<len(maigic_square):
col=0
while col<len(maigic_square):
sum=sum+maigic_square[i][col]
col=col+1
j=0
s=0
while j<len(maigic_square):
col=0
while col<len(maigic_square):
s=s+maigic_square[i][col]
col=col+1
j=j+1
k=0
a=0
while k<len(maigic_square):
dig=0
while dig<len(maigic_square):
a=a+maigic_square[i][dig]
dig=dig+1
k=k+1
i=i+1
print(sum)
print(s)
print(a)
if sum==s==a:
print("its maigic_square")
else:
print("its not maigic_square")
|
69b7dec5566d40b2d62945c2c3477042d22de49f | ThomasHartmannDev/CursoPython | /Programas/01 - Fundamentos/01 - Tipos basicos/exemplo.py | 656 | 4.09375 | 4 |
# Verdadeiro, Falso, nulo
print(True)
print(False)
print(None)
# Tipos numericos
print(1 + 2) #Valor inteiro
print(1.2 + 1) # Valor Float
#Tipos de escrita.
print('Texto dentro de aspas simples')
print("Texto dentro de aspas duplas")
print("você é " + 3 * 'muito ' + 'legal')
#print(3 + '3') --> neste caso gera ambiguidade, ou você soma 3 + 3 ou você concatena para virar 33
#Lista
print([1,2,3]) # Lista possui apenas valores dentro dela.
#outro exemplo
lista = [1,2,3]
print(lista)
#Dict ou Dicionario
print({'nome': 'Thomas','Idade': 17})
# Outro exemplo:
dicionario = {
'Nome':'Thomas',
'Idade': 17,
}
print(dicionario)
|
f9caf4f6b4655269d10315338cdc7fb86313c5b9 | riturajkush/Geeks-for-geeks-DSA-in-python | /Recursion/Power Of Numbers.py | 725 | 4 | 4 | #User function Template for python3
#Complete this function
def power(x,y):
#mod = 10**9+7
if(y == 0): return 1
temp = power(x, int(y / 2))
if (y % 2 == 0):
return ((temp%1000000007) * (temp%1000000007))%1000000007
else:
if(y > 0): return ((x%1000000007) * (temp%1000000007) * (temp%1000000007))%1000000007
#{
# Driver Code Starts
#Initial Template for Python 3
import math
def main():
T=int(input())
while(T>0):
N=input()
R=N[::-1]
ans=power(int(N),int(R))
print(ans)
T-=1
if __name__=="__main__":
main()
# } Driver Code Ends
|
738110b1165d168eaba9da1fb10da23ad870e30f | Upasana360/All-My-Python-Programs | /adv_min_max.py | 732 | 3.875 | 4 | # def func(item):
# return len(item)
# name=['maggie','souravu','sujata','abc','xc']
# print(max(name,key=func))
# #this can also be done by lambda func
# name1=['maggie','souravu','sujata','abc','xc','harshit vasihistha']
# print(max(name1,key=lambda item:len(item)))
# student=[{'names':'upasana','score':90,'age':34},
# {'name':'upasana','score':60,'age':23},
# {'name':'harshit','score':45,'age':32}]
# print(min(student,key=lambda d:d['score']))
# print(min(student,key=lambda item:item.get('age'))['name'])
# print(max(student,key=lambda d:d['score']))
student1={
'harshit':{'score':20,'age':54},
'maggie':{'score':80,'age':48},
'suji':{'score':50,'age':33}
}
print(max(student1,key=lambda item:student1[item]['score']))
|
bac8cdc603195c5b17e6bf46fcd9811ed373507f | HadilOwda/Project2 | /cfp/final2 (copy).py | 4,236 | 3.8125 | 4 | #final project : space invaders by Hadil and Deema
#0-import the libraries which we need
import turtle
import os
import random
#1-set up the screen
wn = turtle.Screen()
wn.title('Space Invaders')
wn.setup(width=700 ,height=700)
wn.bgpic('space_invaders_background.gif')
wn.tracer(0)
#Register the shapes
turtle.register_shape('player.gif')
turtle.register_shape('invader.gif')
#a pen to write Game Over and YOU WON!
pen = turtle.Turtle()
pen.penup()
pen.color('white')
pen.hideturtle()
pen.goto(0,0)
#Draw the border
border = turtle.Turtle()
border.speed(0)
border.color('white')
border.penup()
border.goto(-300,-300)
border.pensize(3)
border.pendown()
for side in range(4):
border.forward(600)
border.left(90)
border.hideturtle()
#Set the score
score = 0
#draw the score on the screen
score_pen = turtle.Turtle()
score_pen.hideturtle()
score_pen.speed(0)
score_pen.color('white')
score_pen.penup()
score_pen.goto(-290,270)
score_string = 'score:'+ str(score)
score_pen.write(score_string ,False , align = 'left',font=("Arial", 16, "normal"))
#2-creat the player turtle
player = turtle.Turtle()
player.shape('player.gif')
player.penup()
player.speed(0)
player.setheading(90)
player.goto(0,-250)
#choose number of enemies
number_of_enemies = 30
#creat an empty list for the enemies
enemies = []
#add enemies to the list
for i in range(number_of_enemies):
enemies.append(turtle.Turtle())
enemy_start_x = -225
enemy_start_y = 250
enemy_number = 0
for enemy in enemies:
#4-creat the enemy
enemy.shape('invader.gif')
enemy.penup()
enemy.speed(0)
x = enemy_start_x + (50 * enemy_number)
y = enemy_start_y
enemy.goto(x,y)
enemy_number+=1
if enemy_number == 10:
enemy_start_y-= 40
enemy_number = 0
enemyspeed = 0.06
#5- creat the palyers bullet turtle
bullet = turtle.Turtle()
bullet.color('yellow')
bullet.shape('triangle')
bullet.penup()
bullet.speed(0)
bullet.setheading(90)
bullet.shapesize(0.5,0.5)
bullet.goto(0,-500)
bullet.hideturtle()
bulletspeed = 5
#define the bullet state (ready or fire)
#ready-ready to fire
#fire_bullet is firing
bulletstate = 'ready'
#3-mover the player turtle
#make a virable to change the position of the player
playersteps = 10
#functions to the key event listeners
#the player movment
def move_right():
x = player.xcor()
x += playersteps
if x > 280:
x = 280 #we chose 280 cuz it's before the border by 20 pixels
player.setx(x)
def move_left():
x = player.xcor()
x -= playersteps
if x <-280:
x = -280 #we chose 280 cuz it's before the border by 20 pixels
player.setx(x)
#fire the bullet
def fire_bullet():
global bulletstate
if bulletstate == 'ready':
bulletstate = 'fire'
#move the bullet above the player
x = player.xcor()
y = player.ycor() + 10
bullet.goto(x,y)
bullet.showturtle()
#check is the bullet is tuouching the enemy
def isCollsion(t1,t2):
distance = t1.distance(t2)
if distance<20:
return True
else:
return False
def check():
for c in enemies:
if c.ycor() <= -270:
pen.color('red')
pen.write('GAME OVER!!',False , align = 'left',font=("Arial", 19, "normal"))
return True
#call our player functions
wn.listen()
wn.onkey(move_right,'Right')
wn.onkey(move_left,'Left')
wn.onkey(fire_bullet,'space')
#Main game loop
while True:
wn.update()
for enemy in enemies:
x = enemy.xcor()+enemyspeed
enemy.setx(x)
if enemy.xcor()>280:
for e in enemies:
y = e.ycor()
y -= 20
e.sety(y)
enemyspeed *= -1
if enemy.xcor()< -270:
for e in enemies:
y = e.ycor()
y -= 20
e.sety(y)
enemyspeed *= -1
if isCollsion(bullet,enemy):
#reset the bullet
bullet.hideturtle()
bulletstate = 'ready'
bullet.goto(0,-400)
enemy.goto(0,10000)
score += 10
score_pen.clear()
score_string = 'score:' + str(score)
score_pen.write(score_string ,False , align = 'left',font=("Arial", 19 , "normal"))
#update score
#fire the bullet
if bulletstate == 'fire':
y = bullet.ycor()+bulletspeed
bullet.sety(y)
#check if the bullet have gone to the top
if bullet.ycor() > 275:
bullet.hideturtle()
bulletstate = 'ready'
if score == 300:
pen.color('green')
pen.write('YOU WON!',False , align = 'left',font=("Arial", 19, "normal"))
if check():
break
turtle.mainloop() |
fc4ce06356d48bfc7c463236583e9eb87a9bcfef | fingerroll/wip | /sort-transformed-array/s1.py | 331 | 3.5625 | 4 | # return sort results
# x^2 should be x*x or x**2
class Solution(object):
def sortTransformedArray(self, nums, a, b, c):
"""
:type nums: List[int]
:type a: int
:type b: int
:type c: int
:rtype: List[int]
"""
return sorted(map(lambda x: a* (x*x) + b*x + c, nums))
|
6d29c26567939e69b424fa33696eed98e34fcf39 | ostrandr6399/CTI-110-1001 | /M4HW2_Pennies_Ostrander.py | 342 | 4.03125 | 4 | #Calculate amount a person earns if salary is one penny a day
#6/19/17
#CTI-110-M4HW4_7
#R.Ostrander
NofDays = int(input('How many days do you want to calculate for?' ))
for day in range (NofDays):
print ('day', day + 1)
pennies = 2**day
print ("This would be your Salary if you earned a penny a day", pennies/100)
|
a9769296aa7bbd95c1b2a4b960d9f3be7b093eef | DarkAlexWang/leetcode | /laioffer/insert_node_sorted_list.py | 463 | 3.921875 | 4 | class Solution:
def insert(self, head, value):
node = ListNode()
if head is None:
node.val = value
node.next = head
head = node
elif head.val >= value:
node.next = head
head = node
else:
cur = head
while cur.next is not None and cur.next.val < value:
cur = cur.next
node.next = cur.next
cur.next = node
|
2b7bafe48f08178a276526d412aad9b746b59dbc | MaksTresh/python-hw-course | /hw18/main.py | 960 | 3.765625 | 4 | import argparse
from PIL import Image
def resize_image(input_image: str, output_image: str, scale: float):
image = Image.open(input_image)
width, height = image.size
size = int(width * scale), int(height * scale)
resized_image = image.resize(size)
resized_image.save(output_image)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Script for resizing an image with a given scale.')
parser.add_argument('-i', '--input-image', dest='input_image', help='Input image', default='input.jpg')
parser.add_argument('-o', '--output-image', dest='output_image', help='Output image', default='output.jpg')
parser.add_argument('-s', '--scale', dest='scale', help='The scale of output image', default=0.5, type=float)
args = parser.parse_args()
if args.scale <= 0:
print('The scale must be greater than zero')
exit(2)
resize_image(args.input_image, args.output_image, args.scale)
|
f5ba6e745291b470a4178ef6666a73b0e5577b1a | ZehuaWang/python_ladder | /python_ladder/python_ladder/BST/BinaryTree.py | 5,551 | 3.9375 | 4 | # -*- coding: utf-8 -*-
"""
Created on Mon Apr 6 17:25:05 2020
@author: ewang
"""
class Stack(object):
def __init__(self):
self.items = []
def push(self, item):
self.items.append(item)
def pop(self):
if not self.is_empty():
return self.items.pop()
def is_empty(self):
return len(self.items) == 0
def peek(self):
if not self.is_empty():
return self.items[-1]
def size(self):
return len(self.items)
def __len__(self):
return self.size()
class Queue(object):
def __init__(self):
self.items = []
def enqueue(self,item):
self.items.insert(0,item)
def dequeue(self):
if not self.is_empty():
return self.items.pop()
def is_empty(self):
return len(self.items) == 0
def peek(self):
if not self.is_empty():
return self.items[-1].value
def __len__(self):
return self.size()
def size(self):
return len(self.items)
class Node(object):
def __init__(self, value):
self.value = value
self.left = None
self.right = None
class BinaryTree(object):
def __init__(self,root):
self.root = Node(root)
def print_tree(self, traversal_type):
if traversal_type == "preorder":
return self.preorder_print(tree.root, "")
elif traversal_type == "inorder":
return self.inorder_print(tree.root, "")
elif traversal_type == "postorder":
return self.postorder_print(tree.root, "")
else:
print("Traversal type " + str(traversal_type) + "is not supported.")
# depth first search
# pre-order in-order post-order
def preorder_print(self, start, traversal):
"""" root -> left -> right"""
if start:
traversal += (str(start.value) + "-")
traversal = self.preorder_print(start.left, traversal)
traversal = self.preorder_print(start.right, traversal)
return traversal
def inorder_print(self, start, traversal):
"""left -> root -> right"""
if start:
traversal = self.inorder_print(start.left, traversal)
traversal += (str(start.value) + "-")
traversal = self.inorder_print(start.right, traversal)
return traversal
def postorder_print(self, start, traversal):
""""left -> right -> root"""
if start:
traversal = self.postorder_print(start.left, traversal)
traversal = self.postorder_print(start.right, traversal)
traversal += (str(start.value) + "-")
return traversal
def reverse_levelorder_print(self, start):
if start is None:
return
queue = Queue()
stack = Stack()
queue.enqueue(start)
traversal = ""
while len(queue) > 0:
node = queue.dequeue()
stack.push(node)
if node.right:
queue.enqueue(node.right)
if node.left:
queue.enqueue(node.left)
while len(stack) > 0:
node = stack.pop()
traversal += str(node.value) + "-"
return traversal
# breadth-first search
def levelorder_print(self,start):
if start:
visit_queue = []
visit_queue.append([start])
res = []
res.append([start.value])
# for child in visit_queue:
# level_res = []
# if child.left:
# visit_queue.append(child.left)
# level_res.append(child.left.value)
# if child.right:
# visit_queue.append(child.right)
# level_res.append(child.right.value)
# if len(level_res) != 0:
# res.append(level_res)
# visit_queue.pop()
while visit_queue:
children = visit_queue.pop()
level_res = []
level_visit_queue = []
for child in children:
if child.left:
level_visit_queue.append(child.left)
level_res.append(child.left.value)
if child.right:
level_visit_queue.append(child.right)
level_res.append(child.right.value)
if len(level_visit_queue) != 0:
visit_queue.append(level_visit_queue)
if len(level_res) != 0:
res.append(level_res)
return res
# 1
# / \
# 2 3
# / \ / \
# 4 6 7 5
tree = BinaryTree(1)
tree.root.left = Node(2)
tree.root.right = Node(3)
#tree.root.left.left = Node(4)
#tree.root.left.right = Node(6)
tree.root.right.left = Node(7)
tree.root.right.right = Node(5)
print(tree.levelorder_print(tree.root))
print(tree.reverse_levelorder_print(tree.root))
|
cae173457f536050c15faff7d02e4a61aeb67b14 | VladimirBa/python_starter_homework | /006_Functions 2/006_homework_1.py | 382 | 3.703125 | 4 | z = 0
print(z)
def greeting(z):
while z < 2:
print('Hello!')
z += 1
print(z)
greeting(z)
def out_f():
x = 1
def inn_f():
global x
print(x)
x = 2
print(x)
inn_f()
print(x)
def in_inn_f():
nonlocal x
x = 3
print(x)
in_inn_f()
print(x)
x = 10
print(x)
out_f()
print(x)
|
8085318e2af09eee96dfb9ff6cfe42a58c03ae0c | YusefQuinlan/PythonTutorial | /Intermediate/2.2 Tkinter/2.2.12_Tkinter_Lambda_Command.py | 3,209 | 3.96875 | 4 | # -*- coding: utf-8 -*-
"""
Created on Thu Jun 11 18:10:54 2020
@author: Yusef Quinlan
"""
"""
The following demonstrates that using the button without passing an argument
to the function xreturn() an error is produced.
"""
from tkinter import *
Window =Tk()
Window.title("Lambdas")
Label1 = Label(Window,text="The following button returns x times 8")
Label1.pack()
x = 3
def xreturn(j):
Label(Window, text=str(x * j)).pack()
Button1 = Button(Window, text="this button returns x times 8", command=xreturn).pack()
Window.mainloop()
"""
if we pass 8 to the xreturn command normally then the xreturn function packs a
label of the value x * 8 before the button renders and the button does not function
as intended, no idea why this happens in tkinter, but for whatever reason one
cannot simply pass a function with an argument to the command parameter of a
tkinter widget.
"""
from tkinter import *
Window =Tk()
Window.title("Lambdas")
Label1 = Label(Window,text="The following button returns x times 8")
Label1.pack()
x = 3
def xreturn(j):
Label(Window, text=str(x * j)).pack()
Button1 = Button(Window, text="this button returns x times 8", command=xreturn(8)).pack()
Window.mainloop()
"""
However by passing the command as a lambda and passing a value into a variable and
using the function with that variable as an argument, we can use the function
with a parameter without any weird errors or unintended functionality.
"""
from tkinter import *
Window =Tk()
Window.title("Lambdas")
Label1 = Label(Window,text="The following button returns x times 8")
Label1.pack()
x = 3
def xreturn(j):
Label(Window, text=str(x * j)).pack()
Button1 = Button(Window, text="this button returns x times 8", command= lambda j=8: xreturn(j)).pack()
Window.mainloop()
"""
The following demonstrates that we can pass several argument values to
xreturn(j) to several buttons, and they all work as intended thanks to lambda.
"""
from tkinter import *
Window =Tk()
Window.title("Lambdas")
Label1 = Label(Window,text="The following button returns x times 8")
Label1.pack()
x = 3
def xreturn(j):
Label(Window, text=str(x * j)).pack()
Button1 = Button(Window, text="this button returns x times 8", command= lambda j=8: xreturn(j)).pack()
Button2 = Button(Window, text="this button returns x times 5", command= lambda j=5: xreturn(j)).pack()
Button3 = Button(Window, text="this button returns x times 2", command= lambda j=2: xreturn(j)).pack()
Window.mainloop()
# Showing that lambda can be used for more than one function such as xset.
from tkinter import *
Window =Tk()
Window.title("Lambdas")
Label1 = Label(Window,text="The following button returns x times 8")
Label1.pack()
x = 3
def xreturn(j):
Label(Window, text=str(x * j)).pack()
def xset(i):
global x
x = i
Button1 = Button(Window, text="this button returns x times 8", command= lambda j=8: xreturn(j)).pack()
Button2 = Button(Window, text="this button returns x times 5", command= lambda j=5: xreturn(j)).pack()
Button3 = Button(Window, text="this button returns x times 2", command= lambda j=2: xreturn(j)).pack()
Button4 = Button(Window, text="this button sets x to 2", command= lambda setval=2: xset(setval)).pack()
Window.mainloop() |
87fb68d880f6c4c05161b8a531de14274a971661 | rodhoda2020/PyCharm-Library | /REST APIs with Flask and Python/1. Full Python Refresher/32_custom_error_classes.py | 1,315 | 3.921875 | 4 | class TooManyPagesReadError(ValueError): # Inside the parameter is the parent class that we can inherit from
pass
class Book:
def __init__(self, name: str, page_count: int):
self.name = name
self.page_count = page_count
self.pages_read = 0
def __repr__(self):
return (
f'<Book {self.name}, read {self.pages_read} pages out of {self.page_count}'
)
def read(self, pages: int):
if self.pages_read + pages > self.page_count:
raise TooManyPagesReadError(
f'You tried to read {self.pages_read + pages} pages, but this book only has '
f'{self.page_count} pages.'
)
self.pages_read += pages
print(f'You have now read {self.pages_read} pages out of {self.page_count}.')
python101 = Book('Python 101', 50)
try:
python101.read(35)
python101.read(50)
except TooManyPagesReadError as e:
print(e)
#This will print the error message without showing the traceback
# The error we face is that the book contains 50 pages, but if we send two parameters
# that, together, would add up to 85, this would still be accepted by the program
# The issue with this is that it does not leave a simple message for the user
# Instead, you can use the try and except method
|
90ddb7c77c93c5d35d5f53c39128d4eb30630f17 | Wesleysou/Exer-CRS- | /Programas/Aula-10/Aula 07 04/exer 2.py | 481 | 3.828125 | 4 | nomes=[]
nota=[]
resp='S'
while(resp=='s'or resp=='S'):
n=input('Digite o nome dos alunos')
parcial=float(input('Digite a nota da parcial'))
nome.append(n)
nota.append(parcial)
resp=(input('Digite s para continuar'))
acum=0
for i in range(len(nota)):
acum=acum+nota[i]
media=acum/len(nota)
print(media)
for i in range(len(nota)):
if(nota[i]>=media):
print('O aluno',nomes[i],'está acima da média')
print('nota',nota[i])
|
8a11ee715aa143a95b245dcc0bce050a24fdaa05 | ace231/CS299_Labs | /lyP3.py | 1,373 | 3.671875 | 4 | # Alfredo Ceballos
# CS 299
# Project 3
# Problem 1 #
# Farenheit to Celsius formula : Tc = (Tf - 32) / 1.8
def faren_to_cels(f):
return (f - 32) / 1.8
f_temp = -459.67 # Just start off at absolute zero
while f_temp <= 200:
if f_temp == -459.67:
print("%7.2fF %7.2fC absolute zero" % (f_temp, faren_to_cels(f_temp)))
f_temp = -60.0
elif f_temp == 30:
# We're incrementing by 10 but set to 32
# or else it'll skip and keep going up
print("%7.2fF %7.2fC" % (f_temp, faren_to_cels(f_temp)))
f_temp = 32
print("%7.2fF %7.2fC freezing//melting point of water" \
% (f_temp, faren_to_cels(f_temp)))
f_temp -= 2 # Set back to 30
elif f_temp == 70:
print("%7.2fF %7.2fC room temperature" % (f_temp, faren_to_cels(f_temp)))
elif f_temp == 90:
print("%7.2fF %7.2fC" % (f_temp, faren_to_cels(f_temp)))
f_temp = 98.6
print("%7.2fF %7.2fC body temperature" % (f_temp, faren_to_cels(f_temp)))
f_temp -= 8.6
elif f_temp == 200:
print("%7.2fF %7.2fC" % (f_temp, faren_to_cels(f_temp)))
f_temp = 212
print("%7.2fF %7.2fC boiling temperature of water" \
% (f_temp, faren_to_cels(f_temp)))
else:
print("%7.2fF %7.2fC" % (f_temp, faren_to_cels(f_temp)))
f_temp += 10
|
f573943c8878046121855d538f199cab790b0b35 | Parfen1984/pythonproject-Public | /Zadanie2.py | 202 | 3.875 | 4 | for i in range(1, 101, 1):
print (i)
if i % 3 == 0:
print(f" {i} Good")
elif i % 5 == 0:
print(f" {i} BETTER ")
if i % 3 ==0 and i % 5 == 0:
print(f" {i} Best ")
|
f188eccae4970a4a38aa79d9f316cb0979f153fa | HagenGaryP/lpthw | /ex12.py | 802 | 4.5 | 4 | # Exercise 12: Prompting People
# When you typed input() you were typing the "(" and ")" characters,
# which are parenthesis characters. This is similar to when you
# used them to do a format with extra variables, as in f"{x} {y}".
# For input you can also put in a prompt to show the user, so they
# know what to type.
# Put a string that you want for the prompt inside the ()
# i.e., y = input("Name? ")
# This prompts the user with "Name?" and puts the reslut into the
# variable 'y'.
# We can rewrite ex11 by using input for all the prompting.
age = input("How old are you, in years? ")
height = input("How tall are you, in inches? ")
weight = input("How much do you weigh, in pounds? ")
print(f"So, you're {age} years old, {height} inches tall, and weigh {weight}lbs.") |
f5e20133d54f0411ce970c0e99abfd68bd1dfcc7 | uannabi/DesignPatterns | /CreationalPatterns/abstractFactory.py | 1,136 | 4.3125 | 4 | class Owl:
"""one of the objects to be returned"""
def speak(self):
return "whooom!"
def __str__(self):
return "Owl"
class OwlFactory:
"""concrete factory"""
def get_pet(self):
"""return a owl object"""
return Owl()
def get_food(self):
"""return a owl food object"""
return "Owl Food!"
class PetStore:
"""petstore houses our Abstract factory"""
def __init__(self, pet_factory=None):
"""pet_factory is our abstract factory"""
self._pet_factory = pet_factory
def show_pet(self):
"""utility method to display the details of the objects return by the PetFactory"""
pet = self._pet_factory.get_pet()
pet_food = self._pet_factory.get_food()
print("Our pet is '{}!".format(pet))
print("Our pet says hello by '{}!".format(pet.speak()))
print("Its food is '{}!".format(pet_food))
# Create a Concrete Factory
factory = OwlFactory()
# Create a pet store housing our Abstract Factory
shop = PetStore(factory)
# Invoke the utility method to show the details of our pet
shop.show_pet()
|
d756f9ef654ec60400b8538b19b97439a38d4eb7 | niklashauschel/minesweeper | /src/logic.py | 10,442 | 3.6875 | 4 | # !/usr/bin/python
"""
@ author : Till Fetzer
@ e-mail : till.fetzer@googlemail.com
@ date : 23.05.2019
"""
import random # stantard liberies
import numpy as np
from logging import *
filename = 'logic'
class Board():
"""
creating and working an the board
"""
def __init__(self, colums, rows, bombs, board): # sometimes only board is use an rest the other
"""
in: rows and colums and bombs all numbers or an board for testing cases
do: create a list with bombs and not bombs fileds and shuffle them randomly
then formate this list to an 2d array or only the board for testing cases as board
out: the 2d array with random bombs or the tsting case board
TODO: add Properties set for rows, colums, bombs, board
"""
self.logNameClass = 'Board'
logNameMethod = '__init__'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
self.rows = rows
self.colums = colums
self.bombs = bombs
if board is None:
notBombs = self.rows * self.colums - bombs
if (notBombs > 0):
self.board = [10]*self.bombs + notBombs*[0] # 10 is standing for bombs
random.shuffle(self.board)
self.board = np.array(self.board, dtype=int).reshape(rows, colums)
log.debug("Board is created sucessful")
else:
log.error("There are to many bombs")
else:
self.board = board
log.debug("Board is set from outside")
def getBoard(self):
"""
getter for board
TODO: addProperties get for board
"""
logNameMethod = 'getBoard'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
log.debug('getBoard call and Board looks like: \n {}'.format(self.board))
return self.board
def getValueFromBoard(self, colum, row):
"""
getter for special value on index
"""
logNameMethod = 'getValueFromBoard'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
try:
log.debug('value of return is {}'.format(self.board[row][colum]))
return(self.board[row][colum])
except IndexError:
log.error('IndexError')
def getClickedFieldsAmount(self):
"""
in: -
do: marked the clicked fileds
out: amound of clicked fileds
"""
logNameMethod = 'getClieckedFieldsAmound'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
result = np.where(self.board == 11)
listOfCoordinates = list(zip(result[1], result[0]))
log.debug('value of return is {}'.format(len(listOfCoordinates)))
return len(listOfCoordinates)
def createWarnFields(self):
"""
in: -
do: write on the filed with no bombs how much bombs are int the near
out: the filed with everyfiled the number of bombs in the near
"""
logNameMethod = 'createWarnFields'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
result = np.where(self.board == 10)
listOfCoordinates = list(zip(result[1], result[0]))
for cord in listOfCoordinates:
rowsOfBomb = cord[1]
columsOfBomb = cord[0]
for(rowsNeighbor, columsNeighbor) in self.getNeighbours(columsOfBomb, rowsOfBomb):
if(rowsNeighbor >= 0 and
rowsNeighbor < self.rows and
columsNeighbor >= 0 and columsNeighbor < self.colums):
self.board[rowsNeighbor][columsNeighbor] += 1
log.debug('Board after creating Warnfileds looks like: \n {}'.format(self.board))
def setValueFromBoard(self, colum, row):
"""
in: position of clicked field
do: set the filed clicked (value=11)
out: -
"""
logNameMethod = 'setValueFromBoard'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
self.board[row][colum] = 11
log.debug('value is setted as 11 that mean clicked')
def getNeighbours(self, colum, row):
'''
Free from minesweeper.py
why a extra method?
Because you need the Neighbours for a field in morec then one Mthod
in: the colum and row from one field
do: calculate the neighbars
out: the neighbarsfrom one field
'''
NEIGHBOURS = ((-1, -1), (-1, 0), (-1, 1),
(0, -1), (0, 1),
(1, -1), (1, 0), (1, 1))
return ((row + neighborRow, colum + neighborColum) for (neighborRow, neighborColum) in NEIGHBOURS)
def getAllOtherOpenFields(self, colum, row, _openfields):
'''
in: an field with no bombs in the neighborhood and
openfields list which is a list off allready calculatec that they have to be open in before rekursiv method
call has to be null to beginning
do: search all fields around which have no bombs around and also the first field which have bombs around
out: all fields which should open in minesweeper, if you press a button on the filed
'''
logNameMethod = 'getAllOtherOpenFields'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
log.debug('rekursiv call witth colum:{} row:{}'.format(colum, row))
openfields = _openfields
if not openfields:
openfields.append((colum, row))
for(rowsNeighbor, columsNeighbor) in self.getNeighbours(colum, row):
if(rowsNeighbor >= 0 and
rowsNeighbor < self.rows and
columsNeighbor >= 0 and columsNeighbor < self.colums and
not((columsNeighbor, rowsNeighbor) in openfields)):
openfields.append((columsNeighbor, rowsNeighbor))
if(self.board[rowsNeighbor][columsNeighbor] == 0):
self.getAllOtherOpenFields(columsNeighbor, rowsNeighbor, openfields)
elif(rowsNeighbor == row + 1 and
columsNeighbor == colum + 1 and self.board[rowsNeighbor][columsNeighbor]):
return openfields
elif (rowsNeighbor == row + 1 and
columsNeighbor == colum + 1):
return openfields
def checkAllNeighboursWhereBombs(self):
"""
One off the methods there are only needed for checking if it is logical solvable
in: the board after the method create warnfields
do: Check if a bomb has only bombs as neighbour if not
but all bombs at the value off 10
out: True or False
"""
logNameMethod = 'checkAllNeighboursWhereBombs'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
self.createWarnFields()
test = np.where(self.board == 18)
if(len(test[0]) != 0 and len(test[1]) != 0):
log.debug('All Neighbours are bombs')
return True
else:
morethan10 = np.where(self.board > 10)
listOfCoordinates = list(zip(morethan10[0], morethan10[1]))
for cord in listOfCoordinates:
rowsof10 = cord[0]
columsof10 = cord[1]
self.board[rowsof10][columsof10] = 10
log.debug('not all Neighbours are bombs')
return False
def isBoardSolvable(self):
"""
One off the methods there are only needed for checking if it is logical solvable
without it you can easily replace isBoardSolvable with createwarnfield in ooGUI.py
and attach on this method and self.board[rowsneighbor][columsneighbor] != 10 in the ifclouse
in: the board after init and the output of checkAllNeighboursWhereBombs and if it work mirrorAxis
do: check if it is logical solvable
out: create new init for not solvable or do nothing for solvable
TODO: because logical solvable is not needed it is not check if it works, when it is not solvable in
logical way
"""
logNameMethod = 'isBoardSolvable'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
result = np.where(self.board == 8)
if((len(result[0]) != 0 and len(result[1]) != 0) or self.checkAllNeighboursWhereBombs()):
# or self.mirrorAxis()
log.debug('it is not solvable, create new board')
self.__init__(self.colums, self.rows, self.bombs, None)
else:
log.debug('Allright it is solvable')
pass
def mirrorAxis(self):
"""
One off the methods there are only needed for checking if it is logical solvable
in: the board off init
do: check if there are any mirrorAxis that make the game in most off the cases unsolvable in logcial way
examples off logical unsolvable fileds are in the folder notsolvable fields
out: if it has mirrorAxis or not
TODO: it is not tested and implement in the project, because this not part off the project needs
you have it seen only as idee
"""
logNameMethod = 'mirrorAxis'
log = getLogger(filename + '.' + self.logNameClass + '.' + logNameMethod)
halfcolum = int(np.ceil(self.colums/2)) - 1
halfrow = int(np.ceil(self.rows/2)) - 1
for i in range(self.rows-1):
for j in range(halfcolum):
if(self.board[i][halfcolum - j - 1] == self.board[i][halfcolum + j] and
i == halfcolum):
return True
else:
i = self.rows
for i in range(self.colums):
for j in range(halfrow):
if(self.board[halfrow - j - 1][i] == self.board[halfrow + j][i] and
i == halfrow):
return True
else:
i = self.colums
log.debug('No MirrorAxis in Board')
return False
|
4535916ed1aaca9cf5134108991d872ce3a938f4 | Husayn17/Code-Lagos-Trials | /project-guessing.py | 1,364 | 3.9375 | 4 | import random
def compare_number(numbers, user_guess):
wrongright = [0,0] #wrong, then right
for i in range(len(numbers)):
if numbers[i] == user_guess[i]:
wrongright[1]+=1
else:
wrongright[0]+=1
return wrongright
if __name__=='__main__':
playings = True #Play the game
numbers = str(random.randint(0,99)) #random 2 digit number
guesses = 0
print('Lets play a Guessing Game!\nI will generate a number, and you would have to guess the numbers one digit at a time.\nFor every number in the wrong place, you get a wrong.\nFor every one in the right place, you get a right.\nThe game ends when you get 2 rights.\nType exit at any time to exit.') #Explanation
while playings:
user_guess = input('Give me your best guess!')
if user_guess == 'exit':
break
wrongrightcount = compare_number(numbers, user_guess)
guesses+=1
print(' You have '+ str(wrongrightcount[0]) + ' wrongs, and ' + str(wrongrightcount[1]) + ' rights.')
if wrongrightcount[1]==2:
playings = False
print(' You win the game after ' + str(guesses) + '! The number was '+str(numbers))
break #redundant exit
else:
print('Your guess inst quite right, try again.')
|
3f3c65621a8c08e005a3efe10aeb16c43524a08a | amandathedev/Python-Fundamentals | /12_string_formatting/12_01_fstring.py | 1,791 | 4.34375 | 4 | '''
Using f-strings, print out the name, last name, and quote of each person in the given dictionary,
formatted like so:
"The inspiring quote" - Lastname, Firstname
'''
famous_quotes = [
{"full_name": "Isaac Asimov", "quote": "I do not fear computers. I fear lack of them."},
{"full_name": "Emo Philips", "quote": "A computer once beat me at chess, but it was no match for me at "
"kick boxing."},
{"full_name": "Edsger W. Dijkstra", "quote": "Computer Science is no more about computers than astronomy "
"is about telescopes."},
{"full_name": "Bill Gates", "quote": "The computer was born to solve problems that did not exist before."},
{"full_name": "Norman Augustine", "quote": "Software is like entropy: It is difficult to grasp, weighs nothing, "
"and obeys the Second Law of Thermodynamics; i.e., it always increases."},
{"full_name": "Nathan Myhrvold", "quote": "Software is a gas; it expands to fill its container."},
{"full_name": "Alan Bennett", "quote": "Standards are always out of date. That’s what makes them standards."}
]
# https://stackoverflow.com/questions/55433855/how-to-combine-list-of-dictionaries-based-on-key
for x in famous_quotes:
print(f"\"{x['quote']}\" - {', '.join(reversed(x['full_name'].split()))}")
# quote_names = [k['full_name'] for k in famous_quotes]
# quote = [i['quote'] for i in famous_quotes]
# print(f"\"{quote[0]}\" - {quote_names[0]} ")
# print(f"\"{quote[1]}\" - {quote_names[1]} ")
# print(f"\"{quote[2]}\" - {quote_names[2]} ")
# print(f"\"{quote[3]}\" - {quote_names[3]} ")
# print(f"\"{quote[4]}\" - {quote_names[4]} ")
# print(f"\"{quote[5]}\" - {quote_names[5]} ")
# print(f"\"{quote[6]}\" - {quote_names[6]} ") |
0e3629079a7462207d09e209cc7041df8e8be539 | jliversi/advent_of_code | /2021/python_version/d14/solution.py | 2,496 | 3.65625 | 4 | # INPUT_FILE = 'input.txt'
INPUT_FILE = 'test_input.txt'
def parse_input(file_name):
with open(file_name, 'r') as f:
start, rules = f.read().split('\n\n')
rules = {rule.split(' -> ')[0]: rule.split(' -> ')[1].strip() for rule in rules.split('\n')}
return start.strip(), rules
def part_one_step(string, rules):
insertions = dict()
# build insertions
for i in range(len(string) - 1):
substr = string[i:i+2]
if substr in rules:
insertions[i] = rules[substr]
new_str = []
for i in range(len(string)):
new_str.append(string[i])
if i in insertions: new_str.append(insertions[i])
return ''.join(new_str)
def string_to_char_pairs(string):
result = dict()
for i in range(len(string) - 1):
char_pair = string[i:i+2]
result[char_pair] = result.get(char_pair, 0) + 1
return result
def char_pairs_to_count_dict(char_pairs, first_char, last_char):
count = dict()
for char_pair, amt in char_pairs.items():
for char in char_pair:
count[char] = count.get(char,0) + (amt / 2)
count[first_char] += 1
count[last_char] += 1
return count
def step(char_pairs, rules):
result = dict()
for pair in char_pairs:
if pair in rules:
amt = char_pairs[pair]
x = pair[0] + rules[pair]
y = rules[pair] + pair[1]
result[x] = result.get(x, 0) + amt
result[y] = result.get(y, 0) + amt
else:
result[pair] = char_pairs[pair]
return result
def part_one(start, rules):
polymer_string = start
for i in range(10):
polymer_string = part_one_step(polymer_string, rules)
char_count = {}
for char in polymer_string:
char_count[char] = char_count.get(char, 0) + 1
answer = max(char_count.values()) - min(char_count.values())
print(answer)
def part_two(start, rules):
first_char, last_char = start[0], start[-1]
char_pairs = string_to_char_pairs(start)
for i in range(40):
print('Working on step ', i+1, '...')
char_pairs = step(char_pairs, rules)
# print(char_pairs)
char_count = char_pairs_to_count_dict(char_pairs, first_char, last_char)
# print(char_count)
answer = max(char_count.values()) - min(char_count.values())
print(answer)
def main():
start, rules = parse_input(INPUT_FILE)
# part_one(start, rules)
part_two(start, rules)
if __name__ == '__main__':
main() |
bc576e57bcba7a8c18f437a5ffb8adfc7012d8bf | GutiEsteban/FundamentosDeProgramacionOrdenado | /ejercicio 4.py | 436 | 3.84375 | 4 | num1=int(input("ingrese el primer numero:"))
num2=int(input("ingrese el suegundo numero:"))
num3=int(input("ingrese el tercer numero:"))
num4=int(input("ingrese el cuarto numero:"))
sumadelos2primerosnumeros=num1+num2
productodel3y4=num3*num4
print("el resultado de los dos primeros numeros es :")
print(sumadelos2primerosnumeros)
print("el resultado de el producto del cuarto y el tercer numero es :")
print(productodel3y4)
|
dfa387d4cc1e04da47f5b3a40d4024a19c9f7f74 | dimtsap/UQpy | /src/UQpy/SampleMethods/MCMC/mcmc.py | 21,671 | 3.546875 | 4 | import numpy as np
from UQpy.Distributions import Distribution
class MCMC:
"""
Generate samples from arbitrary user-specified probability density function using Markov Chain Monte Carlo.
This is the parent class for all MCMC algorithms. This parent class only provides the framework for MCMC and cannot
be used directly for sampling. Sampling is done by calling the child class for the specific MCMC algorithm.
**Inputs:**
* **dimension** (`int`):
A scalar value defining the dimension of target density function. Either `dimension` and `nchains` or `seed`
must be provided.
* **pdf_target** ((`list` of) callables):
Target density function from which to draw random samples. Either `pdf_target` or `log_pdf_target` must be
provided (the latter should be preferred for better numerical stability).
If `pdf_target` is a callable, it refers to the joint pdf to sample from, it must take at least one input `x`,
which are the point(s) at which to evaluate the pdf. Within MCMC the `pdf_target` is evaluated as:
``p(x) = pdf_target(x, *args_target)``
where `x` is a ndarray of shape (nsamples, dimension) and `args_target` are additional positional arguments that
are provided to MCMC via its `args_target` input.
If `pdf_target` is a list of callables, it refers to independent marginals to sample from. The marginal in
dimension `j` is evaluated as: ``p_j(xj) = pdf_target[j](xj, *args_target[j])`` where `x` is a ndarray of shape
(nsamples, dimension)
* **log_pdf_target** ((`list` of) callables):
Logarithm of the target density function from which to draw random samples. Either `pdf_target` or
`log_pdf_target` must be provided (the latter should be preferred for better numerical stability).
Same comments as for input `pdf_target`.
* **args_target** ((`list` of) `tuple`):
Positional arguments of the pdf / log-pdf target function. See `pdf_target`
* **seed** (`ndarray`):
Seed of the Markov chain(s), shape ``(nchains, dimension)``. Default: zeros(`nchains` x `dimension`).
If `seed` is not provided, both `nchains` and `dimension` must be provided.
* **nburn** (`int`):
Length of burn-in - i.e., number of samples at the beginning of the chain to discard (note: no thinning during
burn-in). Default is 0, no burn-in.
* **jump** (`int`):
Thinning parameter, used to reduce correlation between samples. Setting `jump=n` corresponds to skipping `n-1`
states between accepted states of the chain. Default is 1 (no thinning).
* **nchains** (`int`):
The number of Markov chains to generate. Either `dimension` and `nchains` or `seed` must be provided.
* **save_log_pdf** (`bool`):
Boolean that indicates whether to save log-pdf values along with the samples. Default: False
* **verbose** (`boolean`)
Set ``verbose = True`` to print status messages to the terminal during execution.
* **concat_chains** (`bool`):
Boolean that indicates whether to concatenate the chains after a run, i.e., samples are stored as an `ndarray`
of shape (nsamples * nchains, dimension) if True, (nsamples, nchains, dimension) if False. Default: True
* **random_state** (None or `int` or ``numpy.random.RandomState`` object):
Random seed used to initialize the pseudo-random number generator. Default is None.
If an integer is provided, this sets the seed for an object of ``numpy.random.RandomState``. Otherwise, the
object itself can be passed directly.
**Attributes:**
* **samples** (`ndarray`)
Set of MCMC samples following the target distribution, `ndarray` of shape (`nsamples` * `nchains`, `dimension`)
or (nsamples, nchains, dimension) (see input `concat_chains`).
* **log_pdf_values** (`ndarray`)
Values of the log pdf for the accepted samples, `ndarray` of shape (nchains * nsamples,) or (nsamples, nchains)
* **nsamples** (`list`)
Total number of samples; The `nsamples` attribute tallies the total number of generated samples. After each
iteration, it is updated by 1. At the end of the simulation, the `nsamples` attribute equals the user-specified
value for input `nsamples` given to the child class.
* **nsamples_per_chain** (`list`)
Total number of samples per chain; Similar to the attribute `nsamples`, it is updated during iterations as new
samples are saved.
* **niterations** (`list`)
Total number of iterations, updated on-the-fly as the algorithm proceeds. It is related to number of samples as
niterations=nburn+jump*nsamples_per_chain.
* **acceptance_rate** (`list`)
Acceptance ratio of the MCMC chains, computed separately for each chain.
**Methods:**
"""
# Last Modified: 10/05/20 by Audrey Olivier
def __init__(self, dimension=None, pdf_target=None, log_pdf_target=None, args_target=None, seed=None, nburn=0,
jump=1, nchains=None, save_log_pdf=False, verbose=False, concat_chains=True, random_state=None):
if not (isinstance(nburn, int) and nburn >= 0):
raise TypeError('UQpy: nburn should be an integer >= 0')
if not (isinstance(jump, int) and jump >= 1):
raise TypeError('UQpy: jump should be an integer >= 1')
self.nburn, self.jump = nburn, jump
self.seed = self._preprocess_seed(seed=seed, dim=dimension, nchains=nchains)
self.nchains, self.dimension = self.seed.shape
# Check target pdf
self.evaluate_log_target, self.evaluate_log_target_marginals = self._preprocess_target(
pdf_=pdf_target, log_pdf_=log_pdf_target, args=args_target)
self.save_log_pdf = save_log_pdf
self.concat_chains = concat_chains
self.random_state = random_state
if isinstance(self.random_state, int):
self.random_state = np.random.RandomState(self.random_state)
elif not isinstance(self.random_state, (type(None), np.random.RandomState)):
raise TypeError('UQpy: random_state must be None, an int or an np.random.RandomState object.')
self.verbose = verbose
self.log_pdf_target = log_pdf_target
self.pdf_target = pdf_target
self.args_target = args_target
# Initialize a few more variables
self.samples = None
self.log_pdf_values = None
self.acceptance_rate = [0.] * self.nchains
self.nsamples, self.nsamples_per_chain = 0, 0
self.niterations = 0 # total nb of iterations, grows if you call run several times
def run(self, nsamples=None, nsamples_per_chain=None):
"""
Run the MCMC algorithm.
This function samples from the MCMC chains and appends samples to existing ones (if any). This method leverages
the ``run_iterations`` method that is specific to each algorithm.
**Inputs:**
* **nsamples** (`int`):
Number of samples to generate.
* **nsamples_per_chain** (`int`)
Number of samples to generate per chain.
Either `nsamples` or `nsamples_per_chain` must be provided (not both). Not that if `nsamples` is not a multiple
of `nchains`, `nsamples` is set to the next largest integer that is a multiple of `nchains`.
"""
# Initialize the runs: allocate space for the new samples and log pdf values
final_nsamples, final_nsamples_per_chain, current_state, current_log_pdf = self._initialize_samples(
nsamples=nsamples, nsamples_per_chain=nsamples_per_chain)
if self.verbose:
print('UQpy: Running MCMC...')
# Run nsims iterations of the MCMC algorithm, starting at current_state
while self.nsamples_per_chain < final_nsamples_per_chain:
# update the total number of iterations
self.niterations += 1
# run iteration
current_state, current_log_pdf = self.run_one_iteration(current_state, current_log_pdf)
# Update the chain, only if burn-in is over and the sample is not being jumped over
# also increase the current number of samples and samples_per_chain
if self.niterations > self.nburn and (self.niterations - self.nburn) % self.jump == 0:
self.samples[self.nsamples_per_chain, :, :] = current_state.copy()
if self.save_log_pdf:
self.log_pdf_values[self.nsamples_per_chain, :] = current_log_pdf.copy()
self.nsamples_per_chain += 1
self.nsamples += self.nchains
if self.verbose:
print('UQpy: MCMC run successfully !')
# Concatenate chains maybe
if self.concat_chains:
self._concatenate_chains()
def run_one_iteration(self, current_state, current_log_pdf):
"""
Run one iteration of the MCMC algorithm, starting at `current_state`.
This method is over-written for each different MCMC algorithm. It must return the new state and associated
log-pdf, which will be passed as inputs to the ``run_one_iteration`` method at the next iteration.
**Inputs:**
* **current_state** (`ndarray`):
Current state of the chain(s), `ndarray` of shape ``(nchains, dimension)``.
* **current_log_pdf** (`ndarray`):
Log-pdf of the current state of the chain(s), `ndarray` of shape ``(nchains, )``.
**Outputs/Returns:**
* **new_state** (`ndarray`):
New state of the chain(s), `ndarray` of shape ``(nchains, dimension)``.
* **new_log_pdf** (`ndarray`):
Log-pdf of the new state of the chain(s), `ndarray` of shape ``(nchains, )``.
"""
return [], []
####################################################################################################################
# Helper functions that can be used by all algorithms
# Methods update_samples, update_accept_ratio and sample_candidate_from_proposal can be called in the run stage.
# Methods preprocess_target, preprocess_proposal, check_seed and check_integers can be called in the init stage.
def _concatenate_chains(self):
"""
Concatenate chains.
Utility function that reshapes (in place) attribute samples from (nsamples, nchains, dimension) to
(nsamples * nchains, dimension), and log_pdf_values from (nsamples, nchains) to (nsamples * nchains, ).
No input / output.
"""
self.samples = self.samples.reshape((-1, self.dimension), order='C')
if self.save_log_pdf:
self.log_pdf_values = self.log_pdf_values.reshape((-1, ), order='C')
return None
def _unconcatenate_chains(self):
"""
Inverse of concatenate_chains.
Utility function that reshapes (in place) attribute samples from (nsamples * nchains, dimension) to
(nsamples, nchains, dimension), and log_pdf_values from (nsamples * nchains) to (nsamples, nchains).
No input / output.
"""
self.samples = self.samples.reshape((-1, self.nchains, self.dimension), order='C')
if self.save_log_pdf:
self.log_pdf_values = self.log_pdf_values.reshape((-1, self.nchains), order='C')
return None
def _initialize_samples(self, nsamples, nsamples_per_chain):
"""
Initialize necessary attributes and variables before running the chain forward.
Utility function that allocates space for samples and log likelihood values, initialize sample_index,
acceptance ratio. If some samples already exist, allocate space to append new samples to the old ones. Computes
the number of forward iterations nsims to be run (depending on burnin and jump parameters).
**Inputs:**
* nchains (int): number of chains run in parallel
* nsamples (int): number of samples to be generated
* nsamples_per_chain (int): number of samples to be generated per chain
**Output/Returns:**
* nsims (int): Number of iterations to perform
* current_state (ndarray of shape (nchains, dim)): Current state of the chain to start from.
"""
if ((nsamples is not None) and (nsamples_per_chain is not None)) or (
nsamples is None and nsamples_per_chain is None):
raise ValueError('UQpy: Either nsamples or nsamples_per_chain must be provided (not both)')
if nsamples_per_chain is not None:
if not (isinstance(nsamples_per_chain, int) and nsamples_per_chain >= 0):
raise TypeError('UQpy: nsamples_per_chain must be an integer >= 0.')
nsamples = int(nsamples_per_chain * self.nchains)
else:
if not (isinstance(nsamples, int) and nsamples >= 0):
raise TypeError('UQpy: nsamples must be an integer >= 0.')
nsamples_per_chain = int(np.ceil(nsamples / self.nchains))
nsamples = int(nsamples_per_chain * self.nchains)
if self.samples is None: # very first call of run, set current_state as the seed and initialize self.samples
self.samples = np.zeros((nsamples_per_chain, self.nchains, self.dimension))
if self.save_log_pdf:
self.log_pdf_values = np.zeros((nsamples_per_chain, self.nchains))
current_state = np.zeros_like(self.seed)
np.copyto(current_state, self.seed)
current_log_pdf = self.evaluate_log_target(current_state)
if self.nburn == 0: # if nburn is 0, save the seed, run one iteration less
self.samples[0, :, :] = current_state
if self.save_log_pdf:
self.log_pdf_values[0, :] = current_log_pdf
self.nsamples_per_chain += 1
self.nsamples += self.nchains
final_nsamples, final_nsamples_per_chain = nsamples, nsamples_per_chain
else: # fetch previous samples to start the new run, current state is last saved sample
if len(self.samples.shape) == 2: # the chains were previously concatenated
self._unconcatenate_chains()
current_state = self.samples[-1]
current_log_pdf = self.evaluate_log_target(current_state)
self.samples = np.concatenate(
[self.samples, np.zeros((nsamples_per_chain, self.nchains, self.dimension))], axis=0)
if self.save_log_pdf:
self.log_pdf_values = np.concatenate(
[self.log_pdf_values, np.zeros((nsamples_per_chain, self.nchains))], axis=0)
final_nsamples = nsamples + self.nsamples
final_nsamples_per_chain = nsamples_per_chain + self.nsamples_per_chain
return final_nsamples, final_nsamples_per_chain, current_state, current_log_pdf
def _update_acceptance_rate(self, new_accept=None):
"""
Update acceptance rate of the chains.
Utility function, uses an iterative function to update the acceptance rate of all the chains separately.
**Inputs:**
* new_accept (list (length nchains) of bool): indicates whether the current state was accepted (for each chain
separately).
"""
self.acceptance_rate = [na / self.niterations + (self.niterations - 1) / self.niterations * a
for (na, a) in zip(new_accept, self.acceptance_rate)]
@staticmethod
def _preprocess_target(log_pdf_, pdf_, args):
"""
Preprocess the target pdf inputs.
Utility function (static method), that transforms the log_pdf, pdf, args inputs into a function that evaluates
log_pdf_target(x) for a given x. If the target is given as a list of callables (marginal pdfs), the list of
log margianals is also returned.
**Inputs:**
* log_pdf_ ((list of) callables): Log of the target density function from which to draw random samples. Either
pdf_target or log_pdf_target must be provided.
* pdf_ ((list of) callables): Target density function from which to draw random samples. Either pdf_target or
log_pdf_target must be provided.
* args (tuple): Positional arguments of the pdf target.
**Output/Returns:**
* evaluate_log_pdf (callable): Callable that computes the log of the target density function
* evaluate_log_pdf_marginals (list of callables): List of callables to compute the log pdf of the marginals
"""
# log_pdf is provided
if log_pdf_ is not None:
if callable(log_pdf_):
if args is None:
args = ()
evaluate_log_pdf = (lambda x: log_pdf_(x, *args))
evaluate_log_pdf_marginals = None
elif isinstance(log_pdf_, list) and (all(callable(p) for p in log_pdf_)):
if args is None:
args = [()] * len(log_pdf_)
if not (isinstance(args, list) and len(args) == len(log_pdf_)):
raise ValueError('UQpy: When log_pdf_target is a list, args should be a list (of tuples) of same '
'length.')
evaluate_log_pdf_marginals = list(
map(lambda i: lambda x: log_pdf_[i](x, *args[i]), range(len(log_pdf_))))
evaluate_log_pdf = (lambda x: np.sum(
[log_pdf_[i](x[:, i, np.newaxis], *args[i]) for i in range(len(log_pdf_))]))
else:
raise TypeError('UQpy: log_pdf_target must be a callable or list of callables')
# pdf is provided
elif pdf_ is not None:
if callable(pdf_):
if args is None:
args = ()
evaluate_log_pdf = (lambda x: np.log(np.maximum(pdf_(x, *args), 10 ** (-320) * np.ones((x.shape[0],)))))
evaluate_log_pdf_marginals = None
elif isinstance(pdf_, (list, tuple)) and (all(callable(p) for p in pdf_)):
if args is None:
args = [()] * len(pdf_)
if not (isinstance(args, (list, tuple)) and len(args) == len(pdf_)):
raise ValueError('UQpy: When pdf_target is given as a list, args should also be a list of same '
'length.')
evaluate_log_pdf_marginals = list(
map(lambda i: lambda x: np.log(np.maximum(pdf_[i](x, *args[i]),
10 ** (-320) * np.ones((x.shape[0],)))),
range(len(pdf_))
))
evaluate_log_pdf = (lambda x: np.sum(
[np.log(np.maximum(pdf_[i](x[:, i, np.newaxis], *args[i]), 10**(-320)*np.ones((x.shape[0],))))
for i in range(len(log_pdf_))]))
else:
raise TypeError('UQpy: pdf_target must be a callable or list of callables')
else:
raise ValueError('UQpy: log_pdf_target or pdf_target should be provided.')
return evaluate_log_pdf, evaluate_log_pdf_marginals
@staticmethod
def _preprocess_seed(seed, dim, nchains):
"""
Preprocess input seed.
Utility function (static method), that checks the dimension of seed, assign [0., 0., ..., 0.] if not provided.
**Inputs:**
* seed (ndarray): seed for MCMC
* dim (int): dimension of target density
**Output/Returns:**
* seed (ndarray): seed for MCMC
* dim (int): dimension of target density
"""
if seed is None:
if dim is None or nchains is None:
raise ValueError('UQpy: Either `seed` or `dimension` and `nchains` must be provided.')
seed = np.zeros((nchains, dim))
else:
seed = np.atleast_1d(seed)
if len(seed.shape) == 1:
seed = np.reshape(seed, (1, -1))
elif len(seed.shape) > 2:
raise ValueError('UQpy: Input seed should be an array of shape (dimension, ) or (nchains, dimension).')
if dim is not None and seed.shape[1] != dim:
raise ValueError('UQpy: Wrong dimensions between seed and dimension.')
if nchains is not None and seed.shape[0] != nchains:
raise ValueError('UQpy: The number of chains and the seed shape are inconsistent.')
return seed
@staticmethod
def _check_methods_proposal(proposal):
"""
Check if proposal has required methods.
Utility function (static method), that checks that the given proposal distribution has 1) a rvs method and 2) a
log pdf or pdf method. If a pdf method exists but no log_pdf, the log_pdf methods is added to the proposal
object. Used in the MH and MMH initializations.
**Inputs:**
* proposal (Distribution object): proposal distribution
"""
if not isinstance(proposal, Distribution):
raise TypeError('UQpy: Proposal should be a Distribution object')
if not hasattr(proposal, 'rvs'):
raise AttributeError('UQpy: The proposal should have an rvs method')
if not hasattr(proposal, 'log_pdf'):
if not hasattr(proposal, 'pdf'):
raise AttributeError('UQpy: The proposal should have a log_pdf or pdf method')
proposal.log_pdf = lambda x: np.log(np.maximum(proposal.pdf(x), 10 ** (-320) * np.ones((x.shape[0],))))
|
5ecee8c8ee06f6bb2e16ff1566a02c355783d44a | yiming1012/MyLeetCode | /LeetCode/动态规划法(dp)/322. Coin Change.py | 2,388 | 3.8125 | 4 | '''
You are given coins of different denominations and a total amount of money amount. Write a function to compute
the fewest number of coins that you need to make up that amount.
If that amount of money cannot be made up by any combination of the coins, return -1.
Example 1:
Input: coins = [1, 2, 5], amount = 11
Output: 3
Explanation: 11 = 5 + 5 + 1
Example 2:
Input: coins = [2], amount = 3
Output: -1
Note:
You may assume that you have an infinite number of each kind of coin.
'''
import sys
from typing import List
class Solution:
def coinChange(self, coins: List[int], amount: int) -> int:
'''
执行用时 :1408 ms, 在所有 Python3 提交中击败了81.06%的用户
内存消耗 :13.6 MB, 在所有 Python3 提交中击败了20.77%的用户
:param coins:
:param amount:
:return:
'''
if len(coins) == 0 or amount < 0:
return -1
dp = [amount + 1] * (amount + 1)
dp[0] = 0
for coin in coins:
for i in range(coin, amount + 1):
# print(coin, i)
dp[i] = min(dp[i], dp[i - coin] + 1)
return dp[amount] if dp[amount] != amount + 1 else -1
def coinChange2(self, coins: List[int], amount: int) -> int:
'''
执行用时 :1408 ms, 在所有 Python3 提交中击败了81.06%的用户
内存消耗 :13.6 MB, 在所有 Python3 提交中击败了20.77%的用户
:param coins:
:param amount:
:return:
'''
if len(coins) == 0 or amount < 0:
return -1
# 逆序排列
coins.sort(reverse=True)
#
ans = sys.maxsize
ans = self.dfs(coins, 0, amount, 0, ans)
# dfs:depth-first-search
return ans if ans != sys.maxsize else -1
def dfs(self, coins, index, amount, count, ans):
coin = coins[index]
if index == len(coins) - 1:
if amount % coin == 0:
ans = min(ans, count + amount // coin)
else:
for i in range(amount // coin, -1, -1):
if i + count >= ans:
break
self.dfs(coins, index + 1, amount - i * coin, i + count, ans)
return ans
if __name__ == '__main__':
coins = [1, 2, 5]
coins2 = [3]
amount = 11
s = Solution()
print(s.coinChange2(coins, amount))
|
255ff9b4c292216d37ae823cb095f335d68644b8 | QLGQ/learning-python | /map.py | 131 | 3.65625 | 4 | #output the square of 0,1,2,3...100 into a list
def square(n):
return n*n
L1 = range(101)
L2 = list(map(square, L1))
print(L2)
|
c8013fadd47b2207036b30f261d113a16370e244 | RafaelSanzio0/FACULDADE-PYTHON.1 | /AULAS ATT/AULA08-ATT/AT01-AULA08.py | 128 | 3.6875 | 4 | #ATIVIDADE DE LABORATÓRIO 01 - AULA 08
#EXIBIR OS 10 PRIMEIROS MULTIPLOS DE 30
x = 0
while x <= 30:
print(x)
x = x+3 |
b6ce95ba6b0a9a43d64fae5f0fb2d8d6673bdfa1 | FahimFBA/Python-Data-Structures-by-University-of-Michigan | /Dictionary/main.py | 276 | 3.90625 | 4 | # Many Counters with a Dictionary
# One common use of dictionaries is counting how often we "see" something
ccc = dict()
ccc['ccev'] = 1
ccc['cwen'] = 1
print(ccc)
# Output: {'ccev': 1, 'cwen': 1}
ccc['cwen'] = ccc['cwen'] + 1
print(ccc)
# Output : {'ccev': 1, 'cwen': 2} |
27ad56538c8ccaebd8eabc54b6e98588888b799f | alokaviraj/python-program-3 | /circle.py | 115 | 4.03125 | 4 | r=int(input("enter the radius of the circle"))
pie=3.14
area=pie*r*r
c=2*pie*r
print("area=",area)
print("cir=",c)
|
5d015a849beac9cf504cd4480f69f8f2755e616b | DevenMarrero/KTANE-Bot | /Password.py | 1,416 | 3.671875 | 4 | from Voice import speak
def password(text):
curr_password = []
crow1 = []
crow3 = []
txt = text.lower()
text = txt.split(' next ')
try:
row1 = text[0].split()
row3 = text[1].split()
except IndexError:
speak('Say Next in between rows')
return
for word in row1:
lrow = word.replace(word, word[0])
crow1.append(lrow)
letters = ' '.join([str(elem) for elem in crow1])
curr_password.append(letters)
for word in row3:
lrow = word.replace(word, word[0])
crow3.append(lrow)
letters = ' '.join([str(elem) for elem in crow3])
curr_password.append(letters)
passwords = ['about',
'after', 'again', 'below', 'could', 'every', 'first', 'found', 'great',
'house', 'large', 'learn', 'never', 'other', 'place', 'plant', 'point',
'right', 'small', 'sound', 'spell', 'still', 'study', 'their', 'there',
'these', 'thing', 'think', 'three', 'water', 'where', 'which', 'world',
'would', 'write']
posibles = []
for password in passwords:
if password[0] in curr_password[0] and password[2] in curr_password[1]:
posibles.append(password)
janswer = ' '.join([str(elem) for elem in posibles])
if janswer.strip() == '':
speak('No Possible answers')
return
speak(janswer)
|
cf020c231163feb33010b2de13fa8aad0c9cb32d | zhanglintc/leetcode | /Python/Trapping Rain Water.py | 1,391 | 3.796875 | 4 | # Trapping Rain Water
# for leetcode problems
# 2014.10.27 by zhanglin
# Problem Link:
# https://leetcode.com/problems/trapping-rain-water/
# Problem:
# Given n non-negative integers representing an elevation map where the width of each bar is 1,
# compute how much water it is able to trap after raining.
# For example,
# Given [0,1,0,2,1,0,1,3,2,1,2,1], return 6.
# 3| _
# 2| _ | |_ _
# 1| _ | |_ _| |_| |_
# 0| | | | | | |
# |-------------------------
# 0 1 0 2 1 0 1 3 2 1 2 1 0
# The above elevation map is represented by array [0,1,0,2,1,0,1,3,2,1,2,1].
# In this case, 6 units of rain water are being trapped.
# Thanks Lane for contributing this image!
class Solution:
# @param A, a list of integers
# @return an integer
def trap(self, A):
if A == []:
return 0
water = 0 # the water can be trapped
max_idx = A.index(max(A)) # index of highest plank
sub_max = 0
for i in range(max_idx): # from left to highest
if A[i] < sub_max
water += sub_max - A[i]
else:
sub_max = A[i]
sub_max = 0
for i in range(len(A) - 1, max_idx, -1): # from right to highest
if A[i] < sub_max
water += sub_max - A[i]
else:
sub_max = A[i]
return water
|
c99d5459c4ba2dee61238efdec6a2e1d06ac20cd | Kaustav-Biswas/Practice | /Regex Substitution.py | 945 | 4.53125 | 5 | '''
The re.sub() tool (sub stands for substitution) evaluates a pattern and, for each valid match, it calls a method (or lambda).
The method is called for all matches and can be used to modify strings in different ways.
The re.sub() method returns the modified string as an output.
Task
You are given a text of lines. The text contains && and || symbols.
Your task is to modify those symbols to the following:
&& -> and
|| -> or
Both && and || should have a space " " on both sides.
Input Format
The first line contains the integer, N.
The next N lines each contain a line of the text.
Constraints
0<N<100
Neither && nor || occur in the start or end of each line.
Output Format
Output the modified text.
'''
import re
#text = '\n'.join([input() for _ in range(int(input()))])
for _ in range(int(input())):
text = input()
text = re.sub(r' &&(?= )', ' and', text)
text = re.sub(r' \|\|(?= )', ' or', text)
print(text)
|
a26f269bbf1b1661d44635e49e32033f7c4928ba | Malkeet786/Python | /Chapter4/03_listmethod.py | 205 | 3.53125 | 4 | l1=[1,7,8,21,4,15,6]
# print(l1)
# l1.sort() sort list
# l1.reverse() reverse list
#l1.append(45) #adds att end of List
l1.insert(2,100) # Insert 2 at index
l1.pop(4)#remove
l1.remove(15) #remove
print(l1) |
9a34a32b8720648ae0b66cc835b4c8aec13faeb2 | luohaha66/MyCode | /leet_code/python/#23_merge_k_lists.py | 2,262 | 3.6875 | 4 | """
合并 k 个排序链表，返回合并后的排序链表。请分析和描述算法的复杂度。
示例:
输入:
[
1->4->5,
1->3->4,
2->6
]
输出: 1->1->2->3->4->4->5->6
"""
class ListNode:
def __init__(self, x):
self.val = x
self.next = None
class Solution:
def mergeKLists(self, lists: list) -> list:
if not lists:
return []
n = len(lists)
return self.merge(lists, 0, n - 1)
def merge(self, lists, left, right):
if left == right:
return lists[left]
mid = left + (right - left) // 2
l1 = self.merge(lists, left, mid)
l2 = self.merge(lists, mid + 1, right)
return self.mergeTwoLists(l1, l2)
def mergeTwoLists(self, l1, l2):
if not l1:
return l2
if not l2:
return l1
if l1.val < l2.val:
l1.next = self.mergeTwoLists(l1.next, l2)
return l1
else:
l2.next = self.mergeTwoLists(l1, l2.next)
return l2
def version_one(self, lists: list):
import heapq
dummy = ListNode(0)
p = dummy
head = []
for i in range(len(lists)):
if lists[i]:
heapq.heappush(head, (lists[i].val, i))
lists[i] = lists[i].next
while head:
val, idx = heapq.heappop(head)
p.next = ListNode(val)
p = p.next
if lists[idx]:
heapq.heappush(head, (lists[idx].val, idx))
lists[idx] = lists[idx].next
return dummy.next
a = ListNode(1)
b = ListNode(2)
c = ListNode(3)
d = ListNode(6)
e = ListNode(8)
a.next = b
b.next = c
c.next = d
d.next = e
p = a
while p:
print(p.val, '->', end='')
p = p.next
print()
f = ListNode(1)
g = ListNode(4)
h = ListNode(5)
i = ListNode(6)
j = ListNode(7)
f.next = g
g.next = h
h.next = i
i.next = j
p = f
while p:
print(p.val, '->', end='')
p = p.next
print()
j = ListNode(2)
k = ListNode(6)
l = ListNode(9)
j.next = k
k.next = l
p = j
while p:
print(p.val, '->', end='')
p = p.next
print()
lists = [a, f, j]
s = Solution()
p = s.mergeTwoLists(a, f)
while p:
print(p.val, '->', end='')
p = p.next
print()
|
12144c6aaed7acb04bd38928d7c6c6609b94e90d | wshis77/leetcode | /best-time-to-buy-and-sell-stock-ii.py | 912 | 3.546875 | 4 | class Solution:
# @param prices, a list of integer
# @return an integer
def maxProfit(self, prices):
i = 0
size = len(prices)
buy = None
sell = None
result = 0
direction = []
while i < size:
if i+1 == size:
direction.append("DOWN")
else:
if prices[i] < prices[i+1]:
direction.append("UP")
else:
direction.append("DOWN")
i = i + 1
i= 0
while i < size:
while i < size and direction[i] == "DOWN":
i = i + 1
if i >= size:
buy = None
else:
buy = prices[i]
#print "buy " + str(buy)
i = i + 1
while i < size and direction[i] == "UP":
i = i + 1
if i >= size:
sell = None
else:
#print "i " + str(i)
sell = prices[i]
#print "sell " + str(sell)
i = i + 1
if buy != None and sell != None:
result = result + sell - buy
return result
s = Solution()
print s.maxProfit([1,3,2,4,6,1,-1])
|
0c56780e1a4341e7f9b5b7f44e2f30db4de277e7 | Systemad/OOP-Python | /lists-dicts/list2.py | 703 | 3.8125 | 4 | ## Only print odd numbers
'''
tal = [3, 2, 8, 9, 7, 2]
odd = [num for num in tal if num % 2 == 1]
print(odd)
'''
productList = []
class kop:
product = ""
price = 0
productNumber = ""
amount = int(input("Hur många varor: "))
for i in range(amount):
prod = input("vilken product? ")
pric = int(input("Vad kostar det? "))
productNum = int(input("Product nummer? "))
#kop.product = prod
#kop.price = pric
#kop.productNumber = productNum
productList.append(prod)
productList.append(pric)
productList.append(productNum)
print(productList)
#("Din product är: " , kop.product) #
#
#print("Din product kostar: " , kop.price)
#print("Produkt nummer är: " , kop.productNumber)
|
dfcec46b826e32778b088e65e9b2ee61ac06a31c | JoseCardena365/practicas | /entrada.py | 177 | 3.609375 | 4 | #capturamos la entreda de teclado y la guardamos en una variable
esto_es_una_entrada = input("ingrese algo: ")
#imprimimos lo capturado por teclado
print(estos_es_una_entrada)
|
1c7c74551d97a5a8bf44fc425a7f1e69d621710a | HelenaJanda/pyladies-7 | /zaverecny-projekt/asteroids/v07_fly_out/spaceship.py | 1,666 | 3.5 | 4 | import pyglet
import math
# Degrees per second
ROTATION_SPEED = 200
ACCELERATION = 200
class Spaceship:
def __init__(self):
self.x = 0
self.y = 0
self.x_speed = 0
self.y_speed = 0
self.rotation = 0
image = pyglet.image.load("../assets/PNG/playerShip1_blue.png")
# Image is positioned by its middle, not lower left corner
# Also important for rotation
# // means integer division (floor) - 5//2 is 2 but 5/2 is 2.5
image.anchor_x = image.width // 2
image.anchor_y = image.height // 2
self.sprite = pyglet.sprite.Sprite(image)
def draw(self):
self.sprite.x = self.x
self.sprite.y = self.y
# we have rotation in rads, pyglet uses degrees
# also, pyglet's zero is up, ours is on the right, right?
self.sprite.rotation = 90 - math.degrees(self.rotation)
self.sprite.draw()
def tick(self, time_elapsed, keys_pressed, window):
if pyglet.window.key.LEFT in keys_pressed:
self.rotation = self.rotation + time_elapsed*ROTATION_SPEED
if pyglet.window.key.RIGHT in keys_pressed:
self.rotation = self.rotation - time_elapsed*ROTATION_SPEED
if pyglet.window.key.UP in keys_pressed:
self.x_speed += time_elapsed * ACCELERATION * math.cos(self.rotation)
self.y_speed += time_elapsed * ACCELERATION * math.sin(self.rotation)
self.x = self.x + time_elapsed*self.x_speed
self.y = self.y + time_elapsed*self.y_speed
# infinite space - wraparound coordinates
self.x %= window.width
self.y %= window.height
|
88037302efb31cbd034dfcedba9bb888ba9bac06 | ps4417/algorithm | /Codeup/코드업 기초 100제/1088.py | 293 | 3.765625 | 4 | # 3의 배수는 통과?
# 1부터 입력한 정수까지 1씩 증가시켜 출력하는 프로그램을 작성하되,
# 3의 배수인 경우는 출력하지 않도록 만들어보자.
a = int(input())
for i in range(1,a+1):
if(i%3==0):
continue
else:
print(i,end=" ") |
c2f97fab7e4abd3cb196b87280ea93a0023115ab | Javty/Python_Learning | /Web_APIS/Loop_dic.py | 2,385 | 4.0625 | 4 | favorites = {'color': 'purple', 'number': 42, 'animal': 'turtle', 'language': 'python'}
dictionary = {'key1': 'value1', 'key2': 'value2', 'key3': 'value3'}
for key in dictionary:
print(key)
for key in dictionary.keys():
print(key)
for value in dictionary.values():
print(value)
for entry in dictionary.items():
print(entry)
for key, value in favorites.items():
print(f"my favorite {key} is {value}")
#split and count
str = 'it appears that the the appears the most in the sentence'
list = str.split(" ")
dict = {}
for word in list:
if word in dict:
dict[word] = dict[word] + 1
else:
dict[word] = 1
for key, value in dict.items():
print(f"\'{key}\' appears {value} time(s) in the string")
# Loop over list
foods = [['apple', 'banana', 'orange'],['carrot', 'cucumber', 'tomato']]
for e in foods:
print(e)
for e in foods[0]:
print(e)
# Loop Over dictionaries
pets = {
'birds': {
'parrot': 'Arthur',
'canary': 'Ford'
},
'fish': {
'goldfish': 'Zaphod',
'koi': 'Trillium'
}
}
for e in pets:
print(e)
print("new for:")
for e in pets["birds"]:
print(e)
print("new for:")
for e in pets["fish"]:
print(e)
print("new for:")
for e in pets["birds"].values():
print(e)
#list of dictionares
weather = [
{
'date':'today',
'state': 'cloudy',
'temp': 68.5
},
{
'date':'tomorrow',
'state': 'sunny',
'temp': 74.8
}
]
for e in weather[0].values():
print(e)
for e in weather[0]:
print(e)
for e in weather:
print(e['date'])
print(e['state'])
print(e['temp'])
for e in weather:
print(e['date'])
print(e['state'])
print(e['temp'])
for forecast in weather:
print(forecast['date'])
print(forecast['state'])
print(forecast['temp'])
#for forecast in weather:
# print('The weather for ' + forecast['date'] + ' will be ' + forecast['state'] + ' with a temperature of ' + str(forecast['temp']) + ' degrees.')
for forecast in weather:
print(f"The weather for {forecast['date']} will be {forecast['state']} with a temperature of {forecast['temp']} degrees.")
for forecast in weather:
date = forecast['date']
state = forecast['state']
temp = forecast['temp']
print(f"The weather for {date} will be {state} with a temperature of {temp} degrees.")
|
c78f5ae78fbba039794e0159fba8eed302487c9a | DaveRiv/Euler_Project | /project_euler.py | 632 | 4.34375 | 4 | '''
1. List all the natural numbers from 0 to 10 that are mulitples of 3 and 5
2. List all natural numbers from 1 to 1000 that are mulitple of 3 and 5 and the return the sum
'''
def if_multiple(nat_number):
''' return True if it is a multiple of 3 or 5'''
if nat_number % 3 == 0 or nat_number % 5 == 0:
print nat_number
return True
else :
return False
'''end of one funcetion '''
def append_to_array(myarray, item_to_append):
'''appends item_to_array to myarray '''
def sum_numbers( number ):
''' Sum all of the nmbers'''
return
|
f16c4b3141683628250a7f6245fb2f360437822f | kpessa/CodeSignal | /py/floorDivision.py | 491 | 3.578125 | 4 | def division1(x, y):
return x // y
def division2(x, y):
return int(x / y)
testInput = [
{
'x': 15,
'y': -4
},
{
'x': 17,
'y': 13
},
{
'x': 5,
'y': 10
},
{
'x': -10,
'y': -3
},
{
'x': -8,
'y': 2
}
]
for item in testInput:
print(
f"x: {item['x']}, y: {item['y']}\n"
f"Div1: {division1(**item)}\n"
f"Div2: {division2(**item)}\n"
)
#%% |
97219c62a5f57e378ca8217081f60499906471ac | hectorlopezmonroy/HackerRank | /Programming Languages/Python/Strings/What's Your Name?/Solution.py | 884 | 4.28125 | 4 | # -*- coding: utf-8 -*-
# You are given the first name and last name of a person on two different lines.
# Your task is to read them and print the following:
#
# Hello firstname lastname! You just delved into python.
#
# Input Format
#
# The first line contains the first name, and the second line contains the last
# name.
#
# Constraints
#
# The length of the first and last name <= '10'.
#
# Output Format
#
# Print the output as mentioned above.
#
# Sample Input
#
# Ross
# Taylor
#
# Sample Output
#
# Hello Ross Taylor! You just delved into python.
#
# Explanation
#
# The input read by the program is stored as a string data type. A string is a
# collection of characters.
def print_full_name(a, b):
print(f'Hello {a} {b}! You just delved into python.')
if __name__ == '__main__':
first_name = input()
last_name = input()
print_full_name(first_name, last_name)
|
6397379e6c67538607d5d6b9025980830877b539 | fatimaparada/Linear-Regression | /Linear_regression_nosklearn.py | 5,145 | 3.890625 | 4 | #Writing code that implements gradient descent to perform linear regression
#Yeswanth Bogireddy & Fatima Parada-Taboada
import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import random
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from sklearn.metrics import r2_score
#import dataset
dataset = pd.read_csv('https://raw.githubusercontent.com/fatimaparada/Assignment1/master/Copy%20of%20Concrete_Data.csv')
# Plot everything
plt.figure(figsize=(15, 10))
plt.scatter(dataset['Cement (component 1)(kg in a m^3 mixture)'], dataset['Concrete compressive strength(MPa, megapascals) '])
#Splitting data
X_train, X_test, y_train, y_test = train_test_split(dataset['Cement (component 1)(kg in a m^3 mixture)'],
dataset['Concrete compressive strength(MPa, megapascals) '])
#Plotting training and testing data
plt.figure(figsize=(15, 10))
plt.scatter(X_train, y_train, color = 'blue', label='Training Data')
plt.scatter(X_test, y_test, color = 'red', label='Testing Data')
class GradientDescent:
def __init__(self, alp, bta, iterations, momentumsInterval): #------------------->Constructor to intialize the values for gradient descent.
self.alp = alp
self.bta = bta
self.iteration_1 = iterations
self.size = 0
self.momentum = momentumsInterval
self.optimalweights = []
self.optimal_bias = 0
def calcPredition(self, X_train, coefficients, intercept): #------------------------->Prediction
predictions = pd.Series()
predictions = 0
for i in range(len(coefficients)):
predictions = coefficients[i] * X_train.values
predictions += intercept
return predictions
def calcLoss(self, X_train, y_train, coefficients, intercept): #-----------------> MSE
predictions = self.calcPredition(X_train, coefficients, intercept)
return ((predictions - y_train) ** 2).sum() * (1 / (2 * self.size))
def run_gradient_descent(self, X_train, y_train, coefficients, intercept):#-------------------> Preforms momentum gradient decesnt
i = 0
while i < self.iteration_1:
predictions = self.calcPredition(X_train, coefficients, intercept)
intercept_derivative = (1 / self.size) * (predictions - y_train).sum()
self.momentum[0] = (self.bta * self.momentum[0]) + ((i - self.bta) * intercept_derivative)
intercept -= ((self.alp) * self.momentum[0])
for j in range(len(coefficients)):
coeff_derivative = (1 / self.size) * ((predictions - y_train) * X_train).sum()
self.momentum[j + 1] = (self.bta * self.momentum[j + 1]) + ((1 - self.bta) * coeff_derivative)
coefficients[j] -= (self.alp * self.momentum[j + 1])
i += 1
error = self.calcLoss(X_train, y_train, coefficients, intercept)
return error, coefficients, intercept
def momentumGradientD(self, X_train, y_train): #----------------> Calling mgd with randomly generated values
self.size = X_train.shape[0]
i = 0
minError = float('inf')
init_intercept = y_train.values.min()
iterations = int(y_train.values.max()) - int(y_train.values.min())
while i < iterations:
coefficients = []
coefficients.append(random.uniform(0.0, 8.0)) # change it
currentError, coefficients, intercept = self.run_gradient_descent(X_train, y_train, coefficients, init_intercept)
if (currentError < minError):
minError = currentError
self.optimalweights = coefficients
self.optimal_bias = init_intercept
init_intercept += 0.4
i += 0.4
#Print(i,bias/intercept,curr_error,coeff)
return minError, self.optimalweights, self.optimal_bias
def predict(self, X_test):
return self.calcPredition(X_test, self.optimalweights, self.optimal_bias)
alp = 0.00005
bta = 0.9
iterations = 1000
#import dataset
dataset = pd.read_csv('https://raw.githubusercontent.com/fatimaparada/Assignment1/master/Copy%20of%20Concrete_Data.csv')
size = dataset.shape[0]
momentumIterval = [0, 0]
model = GradientDescent(alp, bta, iterations, momentumIterval)
#print(dataset['Concrete compressive strength(MPa, megapascals) '].min())
#print(dataset['Concrete compressive strength(MPa, megapascals) '].max())
print(model.momentumGradientD(dataset['Cement (component 1)(kg in a m^3 mixture)'],
dataset['Concrete compressive strength(MPa, megapascals) ']))
print((model).optimalweights,(model).optimal_bias)
predictions = model.predict(X_test)
print('Mean squared error: ')
print(mean_squared_error(y_test.values, predictions))
print('R2 scored: ')
print(r2_score(y_test.values, predictions))
plt.figure(figsize=(15,10))
plt.plot(X_test, predictions, color='g', label='Linear Regression')
plt.scatter(X_test, y_test, label='Actual Testing Data')
|
fd7461e07c537977c05be0024432dfcbcc677c5d | JiaquanYe/LeetCodeSolution | /Tree/sword_SymmetryTree.py | 938 | 4.0625 | 4 | """
问题描述：判断二叉树是否为对称的二叉树，如果一棵二叉树和其镜像二叉树一样，那么它就是对称的
references : symmetrical Tree: https://blog.csdn.net/ustcer_93lk/article/details/80373736
mirror Tree: https://blog.csdn.net/ustcer_93lk/article/details/80373690
"""
class TreeNode():
def __init__(self, data=-1, left=None, right=None):
self.data = data
self.left = left
self.right = right
def isSymmetrical(treeRoot1, treeRoot2):
if treeRoot1.data == -1 and treeRoot2.data == -1: #两个都是空，一样
return True
elif treeRoot1.data == -1 or treeRoot2.data == -1 : #一个都是空，一样
return False
elif treeRoot1.data != treeRoot2.data: #根节点不一样
return False
else:
return isSymmetrical(treeRoot1.left,treeRoot2.right) and isSymmetrical(treeRoot1.right, treeRoot2.left)
|
dabfaa57bb7de346012def3c984541909a571462 | devLorran/Python | /ex0075.py | 634 | 4.0625 | 4 | '''Desenvolva um programa que leia quatro valores pelo teclado e guarde-os em uma tupla. No final mostra:
A) Quantas vezes apareceu o valor 9. Usar length()
B) Em que posição foi digitado o primeiro valor 3.
C) Quais foram os números pares.'''
par = 0
num = tuple(int(input('Digite um número: ').format(n+1))for n in range(4))
try:
print(f'O valor 3 foi digitado na posição: {num.index(3)+1}ª')
except:
print('O valor 3 não foi encontrado!')
print(f'O valor 9 foi digitado {num.count(9)} vezes!')
for n in num:
if n % 2 == 0:
par += 1
print(f'Foram digitados {par} pares na telas!')
|
35e62eda0b812e1e06f5d40d13b538e63df188dd | abhaybd/AoC2020 | /day2/day2part2.py | 324 | 3.71875 | 4 | with open("input.txt") as f:
lines = f.readlines()
def is_valid(line: str):
positions, letter, password = line.split(" ", 3)
letter = letter[0]
p1, p2 = [int(x)-1 for x in positions.split("-")]
return (password[p1] == letter) ^ (password[p2] == letter)
print(sum([is_valid(line) for line in lines]))
|
615461843c643d53b05359368e62feac992c6ecc | arrimonhere/Python-Calculator | /Python Calculator With Function.py | 2,507 | 4.21875 | 4 | # Calculator With Function
# Code By Ar Rimon Ahmed
# Function For Addition
def Addition(x,y) :
return x+y
# Function For Substraction
def Substraction(x,y) :
return x-y
# Function For Multliplication
def Multliplication(x,y) :
return x*y
# Function For Division
def Division(x,y) :
return x/y
# Function For Square
def Square(x) :
return x**2
# Function For Cube
def Cube(x) :
return x**3
print("For Addition Enter : +\nFor Substraction : -\nFor Multliplication : *\nFor Division : /\n For Square : ^\nAnd For Cube : @")
Choose=input("\nEnter Your Choice (+,-,* or /) : ")
# Condition For Addition
if Choose=="+" :
print("\nWelcome \nYou Decided To Do Addition Of Two Number.\n")
num1=int(input("Enter First Number : "))
num2=int(input("Enter Second Number : "))
print("\nThe Addition Of Two Number Is : ",num1,"+",num2,"=", Addition(num1,num2))
# Condition For Substraction
elif Choose=="-" :
print("\nWelcome \nYou Decided To Do Substraction Of Two Number.\n")
num1=int(input("Enter First Number : "))
num2=int(input("Enter Second Number : "))
print("\nThe Substraction Of Two Number Is : ",num1,"-",num2,"=", Substraction(num1,num2))
# Condition For Multliplication
elif Choose=="*" :
print("\nWelcome \nYou Decided To Do Multliplication Of Two Number.\n")
num1=int(input("Enter First Number : "))
num2=int(input("Enter Second Number : "))
print("\nThe Multliplication Of Two Number Is : ",num1,"*",num2,"=", Multliplication(num1,num2))
# Condition For Division
elif Choose=="/" :
print("\nWelcome \nYou Decided To Do Division Of Two Number.\n")
num1=int(input("Enter First Number : "))
num2=int(input("Enter Second Number : "))
print("\nThe Substraction Of Two Number Is : ",num1,"/",num2,"=", Division(num1,num2))
# Condition For Square
elif Choose=="^" :
print("\nWelcome \nYou Decided To Do Square Of A Number.\n")
num1=int(input("Enter Any Number : "))
print("\nThe Square Of Your Number Is : ",num1,"*",num1,"=", Square(num1))
# Condition For Cube
elif Choose=="@" :
print("\nWelcome \nYou Decided To Do Cube Of A Number.\n")
num1=int(input("Enter Any Number : "))
print("\nThe Cube Of Your Number Is : ",num1,"*",num1,"*",num1,"=", Cube(num1))
# Condition If Don't Understand One Desicion
else :
print("\nSorry \nWe Cannot Understand Your Desicion.\n")
print("Please Try Again, With Correct Desicion.") |
14b5eca6f4fd9fd68fcbb3842941a58c3c7b07bb | jsarraga/week1 | /Quiz_1/Quiz1_Solution/solution.py | 757 | 3.71875 | 4 | import json
# * Write a function ```readcurrency(filename)```
def readcurrency(filename):
# read the lines of a file
with open(filename, 'r') as file_object:
lines = file_object.readlines()
new_list = []
# Separate lines into two values
for line in lines:
new_dict = {}
line = line.strip().split()
new_dict['symbol'] = line[0]
new_dict['rate'] = float(line[1])
new_list.append(new_dict)
return new_list
# print(readcurrency('currency.txt'))
def save(filename, a_list):
with open(filename, 'w') as file_object:
new_data = {'data': a_list}
json.dump(new_data, file_object, indent=2)
save('currency.json',readcurrency('currency.txt')) |
de46e0cae69ac24a678ca7b7404ab5eda3852bc4 | zacharybraxton-lpsr/class-samples | /dawgz.py | 196 | 3.734375 | 4 | print("How many dogs do you have")
puppie = raw_input()
puppie2 = int(puppie)
puppie2 = puppie2 + 4
puppie2 = puppie2 + 4
print("In two months, you will have " + str(puppie2) + " puppies")
|
5f6b409db562ff6ae2324ece1da712a66c7c5495 | amalija-ramljak/advent-of-code-2018 | /day25 - hot chocolate delivery/25.py | 1,002 | 3.625 | 4 | def get_manhattan(loc1, loc2):
return sum([abs(a-b) for a, b in zip(loc1, loc2)])
stars = []
while True:
line = input()
if line == "":
break
line = line.split(",")
for i, el in enumerate(line):
line[i] = int(el)
line = tuple(line)
stars.append(line)
constellations = dict()
count = 0
for star in stars:
cons = []
for con in constellations:
for con_star in constellations[con]:
if get_manhattan(star, con_star) <= 3:
cons.append(con)
break
if len(cons) == 1:
constellations[cons[0]] |= {star}
elif len(cons) == 0:
constellations[count] = {star}
count += 1
elif len(cons) > 1:
new_const = {star}
for con in cons:
for con_star in constellations[con]:
new_const |= {con_star}
constellations.pop(con)
constellations[count] = new_const
count += 1
print(len(constellations))
|
1aa877893d8caefda91a1749b95cf381de2248ca | kyakusahmed/talent_show | /reception.py | 587 | 3.734375 | 4 | file = open('VIP.txt','r')
file1 = open('Ord.txt','r')
ORD = []
VIP = []
for line in file:
VIP.append(line)
for line in file1:
ORD.append(line)
def registration_checker(name,data):
result = "User Not Registered"
for fullname in data:
if fullname.casefold().find(name.casefold()) != -1:
result = fullname
return result
return result
while True:
name1 = input("enter your name! ")
print(registration_checker(name1,VIP))
print(registration_checker(name1,ORD))
|
70ca90a56a5c87dbc3e8f2e7d427591f46c24c92 | untiwe/citrom_test | /usermanager/package.py | 642 | 3.78125 | 4 | import string
import secrets
import random
#пример из документации https://docs.python.org/3/library/secrets.html
def gen_new_password():
'''Функция возвращает пароль 6-10 символов'''
alphabet = string.ascii_letters + string.digits
while True:
range_password = random.randint(6, 10)
password = ''.join(secrets.choice(alphabet) for i in range(range_password))
if (any(c.islower() for c in password)
and any(c.isupper() for c in password)
and sum(c.isdigit() for c in password) >= 3):
break
return password |
660545710fb4151683cc94aba57c55c31f043a41 | chixujohnny/Leetcode | /Leetcode2020/剑指offer/树/剑指 Offer 32 - I. 从上到下打印二叉树【树的BFS队列打印】[2刷].py | 1,254 | 3.875 | 4 | # coding: utf-8
# Definition for a binary tree node.
class TreeNode(object):
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution(object):
def levelOrder(self, root):
"""
:type root: TreeNode
:rtype: List[int]
"""
if root == None:
return []
res = [root.val]
queue = [root] # List[Treenode]
while queue != []:
if queue[0].left != None:
queue.append(queue[0].left)
res.append(queue[0].left.val)
if queue[0].right != None:
queue.append(queue[0].right)
res.append(queue[0].right.val)
queue = queue[1:] # pop
return res
treeList = [3,9,20,None,None,15,7]
def CreateBineryTree(root, treeList, i):
if i < len(treeList):
if treeList[i] == None:
return None
else:
root = TreeNode(treeList[i])
root.left = CreateBineryTree(root.left, treeList, 2*i+1)
root.right = CreateBineryTree(root.right, treeList, 2*i+2)
return root
return root
root = CreateBineryTree(None, treeList, 0)
s = Solution()
print s.levelOrder(root) |
f0600c53972831fd5c600166e66ef536596cdede | rushirg/LeetCode-Problems | /solutions/how-many-numbers-are-smaller-than-the-current-number.py | 873 | 3.75 | 4 | """
1365. How Many Numbers Are Smaller Than the Current Number
https://leetcode.com/problems/how-many-numbers-are-smaller-than-the-current-number/submissions/
"""
class Solution:
def smallerNumbersThanCurrent(self, nums: List[int]) -> List[int]:
ans = []
for x in range(len(nums)):
count = 0
for y in range(len(nums)):
if(nums[y] < nums[x] and x != y):
count += 1
ans.append(count)
return ans
"""
Method 2
Faster 108ms using collections Counter
from collections import Counter
class Solution:
def smallerNumbersThanCurrent(self, nums: List[int]) -> List[int]:
ans = []
count = Counter(nums)
for x in nums:
cnt = 0
for i in range(x):
cnt += count[i]
ans.append(cnt)
return ans
"""
|
031ed345b1ac49b3d312ecaecb49aeaa53db5910 | luwinher/Python_Practice | /gPython/fifteen.py | 279 | 3.5 | 4 | #
"""Q15:利用条件运算符的嵌套来完成此题：学习成绩>=90分的同学用A表示，60-89分之间的用B表示，60分以下的用C表示。"""
score = int(input("请输入该同学分数："))
S = 'A' if (score>=90) else ('B' if (score>=60) else 'C')
print(S)
|
e21748123819863d928a1ed5363e8f8a1ee0ebce | carlitomm/python_prog_course | /practica9.py | 464 | 3.921875 | 4 | def dec2bin(number):
bin = ""
if number == 0:
return "0"
while number > 0:
bin = bin + (str(number%2))
number = int(number / 2)
return bin[::-1]
try:
number = int(input("ingrese el numero a convertir "))
print (dec2bin(number))
except:
print(".....ERROR...ingrese un numero entero")
# https://alumnosuacj-my.sharepoint.com/:v:/g/personal/al206563_alumnos_uacj_mx/EUJUj7VVHQVHvXrDWYs2DJYB412bbZZkbi-RXDY7K2o_yw
|
423b768d5fb196bbcd77e5d7be41f90036639870 | Pobe16/python-labs | /strings_and_functions/returnvalues3.py | 1,543 | 4.1875 | 4 | # Modify the program so it check that the temperature value is numeric
# Temperature conversion program
def centigradeToFahrenheit(cent):
fahr = (9.0 / 5.0) * cent + 32
return fahr
def fahrenheitToCentigrade(fahr):
cent = (5.0 / 9.0) * (fahr - 32)
return cent
def isNumber(value):
try:
var = float(value)
return True
except (TypeError, ValueError):
return False
print("Welcome to the temperature conversion program")
print("---------------------------------------------")
print()
while True:
# Print out the menu:
print("Please select a conversion:")
print("1 Centigrade to Fahrenheit")
print("2 Fahrenheit to Centigrade")
print("3 Exit program")
# Get the user's choice:
convert = input("> ")
if convert == '1':
value = input("Please enter value in degrees Centigrade: ")
if isNumber(value):
value = float(value)
result = centigradeToFahrenheit(value)
print(result, "degrees Fahrenheit")
else:
print("Value is invalid - try again")
elif convert == '2':
value = input("Please enter value in degrees Fahrenheit: ")
if isNumber(value):
value = float(value)
result = fahrenheitToCentigrade(value)
print(result, "degrees Centigrade")
else:
print("Value is invalid - try again")
elif convert == '3':
print("Bye...")
break
else:
print("Invalid choice - try again")
print()
|
88dc8de7f934476fbf22635cdb0a7c15c3362f7d | yashu762001/Python-Tutorial | /DataType/Set.py | 504 | 4.15625 | 4 | animals = {"lion","lion","lion","tiger","giraffe","elephant"}
print(animals)
print(len(animals))
print(animals.__contains__("lion"))
# print(animals[2])
# Since there is a random distribution so we can't say that at this particular location this string is gonna come.
print(animals.add("peacock"))
print(animals)
animals.add("hello")
print(animals)
obj = {"lion","tiger","Dog","Cat","Mouse"}
# print(obj)
# animals = animals.intersection(obj)
# print(animals)
animals = animals.union(obj)
print(animals) |
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