import numpy as np
import math

def imgStats(img):
    mean = np.zeros(3)
    std = np.zeros(3)
    for i in range(img.shape[2]):
        mean[i] = np.mean(img[:, :, i])
        std[i] = np.std(img[:, :, i])
    return mean, std

def calcNormalFunc(mean, sd, len):
    f = np.zeros(len, dtype=np.longdouble)
    
    # calculate PDF
    for x in range(len):
        exp = (-(x - mean) ** 2)/(2 * sd ** 2)
        f[x] = 1 / math.sqrt(2 * np.pi * sd** 20 ) * (math.exp(exp))

    # normalize PDF
    max = np.amax(f)
    min = np.amin(f)
    for x in range(len):
        f[x] = (f[x] - min) / (max - min)

    return f