# checkfitlighting.py
# compute RMS deviation from average intensity of all the white squares
# to see how well the lighting correction worked

import numpy, Image
from scipy import *
from scipy.linalg import *

def checkfitlight(im):
    w, h = im.size
    if w*10 == h*14:
        rows = 10; cols = 14; s = w/14
    else:
        assert False, 'unexpected aspect ratio'

    whites = [1, 4, 7, 10, 40, 70, 100, 140, 137, 134, 131, 91, 61, 31, 45]
    greys = [3, 6, 9, 11, 20, 41, 50, 71, 75, 80, 101, 110, 121, 130, 132, 135, 138]
    blacks = [2, 5, 8, 21, 30, 46, 60, 81, 90, 111, 120, 133, 136, 139]
    greys2 = [46, 95, 56, 85, 66, 107, 75, 76, 65, 106, 86, 55, 96, 45]

    squareset = [whites, greys]
    squaresetnames = ["white", "grey"]
    stds = []
    for squares, sqname in zip(squareset, squaresetnames):
        n = len(squares)
        rgb = zeros([n, 3])
        for k, sq in enumerate(squares):
            row = (sq-1) % rows
            col = (sq-1) / rows
            y = row - (rows - 1)/2.0
            x = col - (cols - 1)/2.0
            box = (col*s, row*s, col*s+s, row*s+s)
            imc = im.crop(box)
            band = imc.split()
            for b, c in zip([0, 1, 2], ['R', 'G', 'B']):
                a = numpy.asarray(band[b])
                avg = mean(a)
                rgb[k, b] = avg
        #print "rgb=", rgb
        #print "mean=", rgb.mean(0)
        #print "std= ", rgb.std(0)
        rgbmean = rgb.mean(0)
        rgb = rgb / rgbmean # normalized intensities
        #print "mean=", rgb.mean(0)
        st = rgb.std(0)
        #print "std= ", st
        mst = mean(st)
        #print sqname, "std =", mst,
        stds.append(mst)
    return stds