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 "#".
n,m,x,y = map(int, input().split())
A = []
for _ in range(n):
    A.append(input().strip())

pre_white = [0]
pre_black = [0]
for i in range(m):
    hashtags = sum(1 if A[j][i] == "#" else 0 for j in range(n))
    pre_white.append(pre_white[-1] + hashtags)
    pre_black.append(pre_black[-1] + n - hashtags)

dp = [[float("inf")] * 2 for _ in range(m+1)]
dp[0][0] = 0
dp[0][1] = 0

for i in range(1,m+1):
    for j in range(x,y+1):
        if j > i:
            break
        dp[i][0] = min(dp[i][0], dp[i-j][1] + pre_black[i] - pre_black[i-j])
    for j in range(x,y+1):
        if j > i:
            break
        dp[i][1] = min(dp[i][1], dp[i-j][0] + pre_white[i] - pre_white[i-j])


print(min(dp[-1]))

