online python to c converter
lista[2:10] = [7]
online python to c converter
from collections import deque
def BFS(a, b, target):
# Map is used to store the states, every
# state is hashed to binary value to
# indicate either that state is visited
# before or not
m = {}
isSolvable = False
path = []
# Queue to maintain states
q = deque()
# Initialing with initial state
q.append((0, 0))
while (len(q) > 0):
# Current state
u = q.popleft()
#q.pop() #pop off used state
# If this state is already visited
if ((u[0], u[1]) in m):
continue
# Doesn't met jug constraints
if ((u[0] > a or u[1] > b or
u[0] < 0 or u[1] < 0)):
continue
# Filling the vector for constructing
# the solution path
path.append([u[0], u[1]])
# Marking current state as visited
m[(u[0], u[1])] = 1
# If we reach solution state, put ans=1
if (u[0] == target or u[1] == target):
isSolvable = True
if (u[0] == target):
if (u[1] != 0):
# Fill final state
path.append([u[0], 0])
else:
if (u[0] != 0):
# Fill final state
path.append([0, u[1]])
# Print the solution path
sz = len(path)
for i in range(sz):
print("(", path[i][0], ",",
path[i][1], ")")
break
# If we have not reached final state
# then, start developing intermediate
# states to reach solution state
q.append([u[0], b]) # Fill Jug2
q.append([a, u[1]]) # Fill Jug1
for ap in range(max(a, b) + 1):
# Pour amount ap from Jug2 to Jug1
c = u[0] + ap
d = u[1] - ap
# Check if this state is possible or not
if (c == a or (d == 0 and d >= 0)):
q.append([c, d])
# Pour amount ap from Jug 1 to Jug2
c = u[0] - ap
d = u[1] + ap
# Check if this state is possible or not
if ((c == 0 and c >= 0) or d == b):
q.append([c, d])
# Empty Jug2
q.append([a, 0])
# Empty Jug1
q.append([0, b])
# No, solution exists if ans=0
if (not isSolvable):
print ("No solution")
# Driver code
if __name__ == '__main__':
Jug1, Jug2, target = 4, 3, 2
print("Path from initial state "
"to solution state ::")
BFS(Jug1, Jug2, target)
# This code is contributed by mohit kumar 29
online python to c converter
import random
from collections import defaultdict
def main_roll():
dice_amount = int(input("Enter the number of dice: ")) # Total Number of Dice Being Rolled
sides_of_dice = int(input("Enter the number of sides: ")) # Total Number of Sides per Die
rolls_of_dice = int(input("Enter the number of rolls to simulate: ")) # Total Number of Times Each Die Rolled
result = roll(dice_amount, sides_of_dice, rolls_of_dice) # This stores the results
maxH = 0 # Used for formulating
for i in range(dice_amount, dice_amount * sides_of_dice + 1):
if result[i] / rolls_of_dice > maxH: maxH = result[i] / rolls_of_dice
for i in range(dice_amount, dice_amount * sides_of_dice + 1):
print('{:2d}{:10d}{:8.2%} {}'.format(i, result[i], result[i] / rolls_of_dice, '#' * int(result[i] / rolls_of_dice / maxH * 40)))
def roll(dice_amount, sides_of_dice, rolls):
d = defaultdict(int)
for _ in range(rolls):
d[sum(random.randint(1, sides_of_dice) for _ in range(dice_amount))] += 1
return d
main_roll()
online python to c converter
if number == 2 : prime_con = True
if number>2 and number%2==0 : prime_con = False
stopper = math.floor(math.sqrt(number))
for j in range(3,100,2):
if number%j==0:
prime_con = False
break
online python to c converter
for i in range(gradient1b.shape[0]):
for j in range(gradient1b.shape[1]):
if gradient1b[i, j] > thresholdHi:
gradient2b[i, j] = 0
elif ((gradient1b[i, j] <= thresholdHi) and (gradient1b[i, j] > thresholdLo)):
#gradient2b[i, j] = gradient1b[i, j] #255 #Binary thresholding
gradient2b[i, j] = 255 #Binary thresholding
else:
gradient2b[i, j] = 0
online python to c converter
a=[]
def knapsack(pro,wt,c,n,ans):
global a
if n==0 or c==0:
a+=ans,
elif wt[n-1]>c:
knapsack(pro,wt,c,n-1,ans)
else:
knapsack(pro,wt,c-wt[n-1],n-1,ans+pro[n-1])
knapsack(pro,wt,c,n-1,ans)
n=int(input())
profit=list(map(int,input().split()))
weights=list(map(int,input().split()))
capacity=int(input())
knapsack(profit,weights,capacity,n,0)
a.sort(reverse=True)
print(a[1 if a[0]<=10 and a[0]%3 else 0])
online python to c converter
def djikstra(graph, initial):
visited_weight_map = {initial: 0}
nodes = set(graph.nodes)
# Haven't visited every node
while nodes:
next_node = min(
node for node in nodes if node in visited
)
if next_node is None:
# If we've gone through them all
break
nodes.remove(next_node)
current_weight = visited_weight_map[next_node]
for edge in graph.edges[next_node]:
# Go over every edge connected to the node
weight = current_weight + graph.distances[(next_node, edge)]
if edge not in visited_weight_map or weight < visited_weight_map[edge]:
visited_weight_map[edge] = weight
return visited
online python to c converter
# A brute force approach based
# implementation to find if a number
# can be written as sum of two squares.
# function to check if there exist two
# numbers sum of whose squares is n.
def sumSquare( n) :
i = 1
while i * i <= n :
j = 1
while(j * j <= n) :
if (i * i + j * j == n) :
print(i, "^2 + ", j , "^2" )
return True
j = j + 1
i = i + 1
return False
# driver Program
n = 25
if (sumSquare(n)) :
print("Yes")
else :
print( "No")
Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us