import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import scipy.signal as signal
import numpy as np

# Tweakable
strip_count = 12 # amount of subdivisions on x-axis
effect_power = 12 # bump effect strength
hMap = mpimg.imread("h3.png") # heightmap to apply
cMap = 'viridis' # matplotlib colormap

imgRes = [int(len(hMap[0])),int(len(hMap))]
stripSize = [int(imgRes[0]/strip_count),imgRes[1]]
final = np.zeros((imgRes[1],imgRes[0])) # placeholder for final image, filled with .0

def draw_strip(id): # -> void
        for y in range(len(noise)):
            for x in range(len(noise[0])):
                # calculate pixel movement based on heightmap
                hv = int(hMap[y][x+stripSize[0]*id][0]*effect_power)
                final[y][x+stripSize[0]*id] = final[y][x-stripSize[0]+stripSize[0]*id+hv]

def get_smooth_noise(size):
    n = np.random.uniform(1.,.0,size)
    n = signal.convolve2d(n, np.ones((4,4)) / 16,"same")
    for y in range(len(n)):
        for i in range(0,2):
            n[y][i] = (n[y][i+1] + n[y][i+2] + n[y][i+3] + n[y][i+4])/4
        n[y][len(n[0])-1] = (n[y][0] + n[y][1] + n[y][2])/3
    return n

def create_stereogram():
    # Drawing first reference strip of noise
    for y in range(len(noise)):
        for x in range(len(noise[0])):
            final[y][x] = noise[y][x]

    for i in range(1,strip_count):
        draw_strip(i)

    pltimg = plt.imshow(final,cmap=cMap)
    plt.show()

noise = get_smooth_noise((stripSize[1],stripSize[0]))
create_stereogram()