Simplify code by dropping support for legacy Python (#1143)

* Simplify code by dropping support for legacy Python

* sort() --> sorted()
This commit is contained in:
Christian Clauss
2019-08-19 15:37:49 +02:00
committed by GitHub
parent 32aa7ff081
commit 47a9ea2b0b
145 changed files with 367 additions and 976 deletions

View File

@ -1,7 +1,6 @@
"""
author : Mayank Kumar Jha (mk9440)
"""
from __future__ import print_function
from typing import List
import time
import matplotlib.pyplot as plt
@ -10,7 +9,7 @@ def find_max_sub_array(A,low,high):
if low==high:
return low,high,A[low]
else :
mid=(low+high)//2
mid=(low+high)//2
left_low,left_high,left_sum=find_max_sub_array(A,low,mid)
right_low,right_high,right_sum=find_max_sub_array(A,mid+1,high)
cross_left,cross_right,cross_sum=find_max_cross_sum(A,low,mid,high)
@ -30,7 +29,7 @@ def find_max_cross_sum(A,low,mid,high):
if summ > left_sum:
left_sum=summ
max_left=i
summ=0
summ=0
for i in range(mid+1,high+1):
summ+=A[i]
if summ > right_sum:
@ -40,7 +39,7 @@ def find_max_cross_sum(A,low,mid,high):
def max_sub_array(nums: List[int]) -> int:
"""
Finds the contiguous subarray (can be empty array)
Finds the contiguous subarray (can be empty array)
which has the largest sum and return its sum.
>>> max_sub_array([-2,1,-3,4,-1,2,1,-5,4])
@ -50,14 +49,14 @@ def max_sub_array(nums: List[int]) -> int:
>>> max_sub_array([-1,-2,-3])
0
"""
best = 0
current = 0
for i in nums:
current += i
best = 0
current = 0
for i in nums:
current += i
if current < 0:
current = 0
best = max(best, current)
return best
return best
if __name__=='__main__':
inputs=[10,100,1000,10000,50000,100000,200000,300000,400000,500000]
@ -68,8 +67,8 @@ if __name__=='__main__':
(find_max_sub_array(li,0,len(li)-1))
end=time.time()
tim.append(end-strt)
print("No of Inputs Time Taken")
for i in range(len(inputs)):
print("No of Inputs Time Taken")
for i in range(len(inputs)):
print(inputs[i],'\t\t',tim[i])
plt.plot(inputs,tim)
plt.xlabel("Number of Inputs");plt.ylabel("Time taken in seconds ")
@ -77,4 +76,4 @@ if __name__=='__main__':