#!/usr/bin/env python

import numpy as np


def main():

    dataz = np.genfromtxt('data/example.csv', delimiter=',', names=True)

    y = dataz['attitude']
    x = dataz['correct']
    print 'x = {} {}'.format(x, np.mean(x))
    print 'y = {} {}'.format(y, np.mean(y))

    delta_x = x - np.mean(x)
    delta_y = y - np.mean(y)
    delta_xy = delta_x*delta_y
    delta2_x = delta_x**2
    delta2_y = delta_y**2
    print 'delta_x = {} {}'.format(delta_x, np.sum(delta_x))
    print 'delta_y = {} {}'.format(delta_y, np.sum(delta_y))
    print 'delta_xy = {} {}'.format(delta_xy, np.sum(delta_xy))
    print 'delta2_x = {} {}'.format(delta2_x, np.sum(delta2_x))
    print 'delta2_y = {} {}'.format(delta2_y, np.sum(delta2_y))

    Sx = np.sqrt(np.sum(delta2_x)/(delta2_x.size - 1))
    Sy = np.sqrt(np.sum(delta2_y)/(delta2_y.size - 1))
    r = np.sum(delta_xy)/np.sqrt(np.sum(delta2_x)*np.sum(delta2_y))
    print 'Sx = {}'.format(Sx)
    print 'Sy = {}'.format(Sy)
    print 'r = {}'.format(r)
    print 'r^2 = {}'.format(r**2)
    print 'r^2 dB = {}'.format(10.0*np.log10(r**2))

    b = r*(Sy/Sx)
    a = np.mean(y) - b*np.mean(x)
    print 'b = {}'.format(b)
    print 'a = {}'.format(a)

    print '  (attitude) \t= {}(correct) + {}'.format(b, a)


if __name__ == '__main__':
    main()