import matplotlib.pyplot as plt
from matplotlib import rc
import numpy as np
from sys import argv

def hsv2rgb(h, s, v):
    c = v*s
    x = c * (1-abs((h/60)%2-1))
    m = v - c
    res = None
    if h >= 0 and h < 60:
        res = (c, x, 0)
    elif 60 <= h and h < 120:
        res = (x, c, 0)
    elif 120 <= h and h < 180:
        res = (0, c, x)
    elif 180 <= h and h < 240:
        res = (0, x, c)
    elif 240 <= h and h < 300:
        res = (x, 0, c)
    elif 300 <= h and h <= 360:
        res = (c, 0, x)
    return (res[0] + m, res[1] + m, res[2] + m)

def normalize(vector):
    magnitude = np.linalg.norm(vector)
    return [x / magnitude for x in vector]


if __name__ == '__main__':
    f = open('big.dem')
    data = f.readlines()

    width, height, distance = [int(x) for x in data[0].rstrip().split(' ')]

    map = [[float(cell) for cell in line.rstrip().split(' ')] for line in data[1:]]

    max = np.amax(map)

    #calculate normals
    normals = []
    for z in range(0, height):
        normals.append([])
        for x in range(0, width):
            try:
                hl = map[z][x-1]
                hr = map[z][x+1]
                hd = map[z-1][x]
                hu = map[z+1][x]
            except IndexError:
                #edge pixels, i don't care
                hl = 0
                hr = 0
                hd = 0
                hu = 0

            normals[z].append(normalize([hl - hr, 2.0, hd - hu]))


    sun = normalize([0.5, 1.0, 0.0])

    base_brightness = 0.8
    strength = 0.2

    hues = np.linspace(135, 0, 1024)
    for z in range(0, len(map)):
        for x in range(0, len(map[z])):
            idx = int(((map[z][x] - 13) / max) * 1024) - 1
            #get the dot product
            cosine = np.dot(normals[z][x], sun)
            cosine = cosine if cosine >= 0 else 0
            map[z][x] = list(hsv2rgb(hues[idx], 1, base_brightness + strength * cosine))

    plt.imshow(map)
    plt.show()