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 "#".
def arr_inp():
    return [int(x) for x in stdin.readline().split()]


def get_col(arr, i):
    return [row[i] for row in arr]


def str_inp(n):
    return [input() for x in range(n)]


def dp(i, mi, pre):
    if i == m:
        if mi < x or mi > y:
            return float('inf')
        return 0
    ret = mem[i, mi,pre]
    if ret != -1:
        return ret
    ret = float('inf')
    if pre == '*':
        ret = min(ret, mat2[i] + dp(i + 1, mi + 1, '.'), n - mat2[i] + dp(i + 1, mi + 1, '#'))

    if pre == '#':
        if mi < y:
            ret = min(ret, n - mat2[i] + dp(i + 1, mi + 1, '#'))
        ret = min(ret, mat2[i] + dp(i + 1, 1, '.'))

    if pre == '.':
        if mi < y:
            ret = min(ret, mat2[i] + dp(i + 1, mi + 1, '.'))
        ret = min(ret, n - mat2[i] + dp(i + 1, 1, '#'))

    mem[i, mi] = ret
    return ret


from collections import defaultdict
from sys import stdin

n, m, x, y = arr_inp()
mat, mem = str_inp(n), defaultdict(lambda: -1)
mat2 = [n - get_col(mat, i).count('#') for i in range(m)]
print(dp(0, 0, '*'))
