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 "#".
row, col, x, y = map(int, input().strip().split())
mat = []
for i in range(row):
    mat.append(list(input()))

black_pre, white_pre = [0 for i in range(col+1)], [0 for i in range(col+1)]

for j in range(1,col+1):
    w = 0; b = 0
    for i in range(row):
        if mat[i][j-1] == '.':
            w += 1
        else:
            b += 1
    black_pre[j] += black_pre[j-1]+b
    white_pre[j] += white_pre[j-1]+w

dp = [[float('inf') for i in range(col+1)] for i in range(2)]
dp[0][0] = 0; dp[1][0] = 0
# print("#######")
# print(white_pre, black_pre)
# print("#######")
for i in range(1, col+1):
    for j in range(x, y+1):
        if i-j >= 0:
            dp[0][i] = min(dp[0][i], dp[1][i-j] + white_pre[i]-white_pre[i-j])
            dp[1][i] = min(dp[1][i], dp[0][i-j] + black_pre[i]-black_pre[i-j])
            # print("---")
            # for i in dp:
            #     print(i)
            # print("---")
print(min(dp[0][-1], dp[1][-1]))




