merged lin_reg python files, added comment on Ramanujan's version of gamma

function to sterling_approx;

1 files changed, 0 insertions, 50 deletions

diff --git a/lin_reg.py b/lin_reg.py
deleted file mode 100644
index 8fb88b2..0000000
--- a/lin_reg.py
+++ /dev/null
@@ -1,50 +0,0 @@
-#!/usr/bin/python
-#/usr/local/bin/python2.7
-
-import numpy as np
-
-
-def main():
-
-    dataz = np.genfromtxt('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)
-
-    b = r*(sy/sx)
-    a = np.mean(y) - b*np.mean(x)
-    print 'b = {}'.format(b)
-    print 'a = {}'.format(a)
-
-    err = y - (a + b*x)
-    b_err = np.sqrt(np.sum(err**2.0)/((x.size - 2)*np.sum(delta2_x)))
-    a_err = np.sqrt(np.sum(x**2.0)*np.sum(err**2.0)/(x.size*(x.size - 2)*np.sum(delta2_x)))
-    print 'b_err = {}'.format(b_err)
-    print 'a_err = {}'.format(a_err)
-
-    print '  (attitude) \t= {}(correct) + {}'.format(b, a)
-
-
-if __name__ == '__main__':
-    main()