# Tk_perlin_noise3.py

# Tk_perlin_noise3.py

from Tkinter import *
from PIL import Image, ImageTk
import random
import math
import time
ww = 600
hh = 600

if 1:
    root = Tk()
    root.title("Tk Perlin Noise")
    root.geometry("%dx%d+-10+0"%(ww,hh))
    canvas = Canvas(root, width=ww, height=hh)
    canvas.pack()
0

if 1:
    data = []
    img = Image.new("RGB", (ww, hh))

    octaves = int(math.log(max(ww, hh), 2.0))
    persistence = random.random()
    imgAr = [[0.0 for i in range(ww)] for j in range(hh)] # image array
    totAmp = 0.0
    for k in range(octaves):
        freq = 2 ** k
        amp = persistence ** k
        totAmp += amp
        # create an image from n by m grid of random numbers (w/ amplitude)
        # using Bilinear Interpolation
        n = freq + 1; m = freq + 1 # grid size
        ar = [[random.random() * amp for i in range(n)] for j in range(m)]
        nx = ww / (n - 1.0); ny = hh / (m - 1.0)
        for ky in range(hh):
            for kx in range(ww):
                i = int(kx / nx); j = int(ky / ny)
                dx0 = kx - i * nx; dx1 = nx - dx0
                dy0 = ky - j * ny; dy1 = ny - dy0
                z = ar[j][i] * dx1 * dy1
                z += ar[j][i + 1] * dx0 * dy1
                z += ar[j + 1][i] * dx1 * dy0
                z += ar[j + 1][i + 1] * dx0 * dy0
                z /= nx * ny
                imgAr[ky][kx] += z # add image layers together

    # paint image
    pixels = []
    for ky in range(hh):
        for kx in range(ww):
            c = int(imgAr[ky][kx] / totAmp * 255)
            pixels.append((c, c, c))

    img.putdata(pixels)

    imgTk = ImageTk.PhotoImage(img)
    canvas.create_image(0, 0, anchor=NW, image=imgTk)
    canvas.update()