Reputation: 565
I have this code which calculates the number of inversions in an array. It works fine for small arrays.
But for arrays of size more than 500,the value differs by 20 -50 from the correct value
def merge(left,right):
result=[]
i,j,inv=0,0,0
while i<len(left) and j<len(right):
if left[i]<right[j]:
result.append(left[i])
i=i+1
else:
result.append(right[j])
j=j+1
inv=inv+len(left)-i
result+=left[i:]
result+=right[j:]
return result,inv
def mergesort(li):
if len(li)<2:
return li,0
middle=len(li)//2
left,invl=mergesort(li[:middle])
right,invr=mergesort(li[middle:])
result,invs= merge(left,right)
inv=invl+invr+invs
return result,inv
if __name__ == '__main__':
n=int(raw_input())
ans=[]
for i in range(n):
m=int(raw_input())
li=raw_input().split(' ')
print len(li)
result,inversions=mergesort(li)
ans.append(inversions)
for i in range(n):
print ans[i]
What is it that I am missing?
Upvotes: 0
Views: 195
Reputation: 183918
You don't need large arrays to get a wrong inversion count:
>>> mergesort([1,1,1,1])
([1, 1, 1, 1], 6)
Your mistake is that you count all pairs of equal elements as inversions,
if left[i]<right[j]:
result.append(left[i])
i=i+1
should be
if left[i] <= right[j]:
result.append(left[i])
i=i+1
so that equal elements are not swapped and counted as inversions.
The short arrays you received contained no duplicates, but the larger ones did.
Upvotes: 4