Speed of Light Part 1

Back to 2014.

Initial Python code example for Speed of Light lab.

import numpy as np
import pylab as plt

dif = np.loadtxt('data_IA_far.txt')
dtf = np.loadtxt('data_TM_far.txt')

#Python slice notation:
print "IA's data =", dif
print "IA's 1st column with rev/s =", dif[:,0]
print "IA's 2nd column with positions (mm) =", dif[:,1]

#Average across different measurements
velocity_far = (dif[:,0]+dtf[:,0])/2 #Velocities in 1st column
displace_far = (dif[:,1]+dtf[:,1])/2 #Displacements in 2nd column

#Take out offset in data
offset_TM_far = (dtf[:,1]-displace_far).mean()
offset_IA_far = (dif[:,1]-displace_far).mean()
print "Offsets =", offset_TM_far, offset_IA_far
dtf[:,1] -= offset_TM_far
dif[:,1] -= offset_IA_far

#Compute scatter between different measurements
N=2 #only two datasets from TM and IA used
var_array_far = ((dtf[:,1]-displace_far)**2+(dif[:,1]-displace_far)**2)/(N-1)
var_far = var_array_far.mean()/N #variance on mean divide by N
print 'Error on far data =', np.sqrt(var_far)

#Plot
plt.errorbar(velocity_far, displace_far, np.sqrt(var_far), fmt='.', label='Far')
plt.ylabel('Distance (mm)')
plt.xlabel('Angular velocity (rev/s)')
plt.legend(loc='upper left')
plt.savefig('data_example.png')
plt.clf()