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#!/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()
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