You've got an *n* × *m* pixel picture. Each pixel can be white or black. Your task is to change the colors of as few pixels as possible to obtain a barcode picture.

A picture is a barcode if the following conditions are fulfilled: 
 -  All pixels in each column are of the same color. -  The width of each monochrome vertical line is at least *x* and at most *y* pixels. In other words, if we group all neighbouring columns of the pixels with equal color, the size of each group can not be less than *x* or greater than *y*.
The first line contains four space-separated integers *n*, *m*, *x* and *y* (1 ≤ *n*, *m*, *x*, *y* ≤ 1000; *x* ≤ *y*).

Then follow *n* lines, describing the original image. Each of these lines contains exactly *m* characters. Character "." represents a white pixel and "#" represents a black pixel. The picture description doesn't have any other characters besides "." and "#".
import sys
input = lambda: sys.stdin.readline().rstrip()
from collections import defaultdict

N,M,X,Y = map(int, input().split())
S = []
for _ in range(N):
    S.append(input())

A = []
for i in range(M):
    cnt = defaultdict(int)
    for j in range(N):
        cnt[S[j][i]]+=1
    A.append((cnt['.'],cnt['#']))

INF = float('inf')
dp = [[INF,INF] for _ in range(Y+1)]
dp[0][0] = dp[0][1] = 0
for i in range(M):
    ndp = [[INF,INF] for _ in range(Y+1)]
    for j in range(Y+1):
        if j<Y:
            ndp[j+1][0] = min(ndp[j+1][0], dp[j][0]+A[i][1])
            ndp[j+1][1] = min(ndp[j+1][1], dp[j][1]+A[i][0])
    
        if j>=X:
            ndp[1][1] = min(ndp[1][1], dp[j][0]+A[i][0])
            ndp[1][0] = min(ndp[1][0], dp[j][1]+A[i][1])
    dp = ndp

ans = INF
for i in range(X,Y+1):
    ans = min(ans, min(dp[i]))
print(ans)