gaussian_comparison.py

import numpy as np
import matplotlib.pyplot as plt
import sys
import abel

transforms = {
  "basex": abel.basex.basex_transform,   
  # "linbasex": abel.linbasex.linbasex_transform,
  "direct": abel.direct.direct_transform,      
  "hansenlaw": abel.hansenlaw.hansenlaw_transform,
  "onion_bordas": abel.onion_bordas.onion_bordas_transform,
  "onion_dasch": abel.dasch.onion_peeling_transform, 
  "three_point": abel.dasch.three_point_transform,
  "two_point" : abel.dasch.two_point_transform,
}

ntrans = np.size(transforms.keys())  # number of transforms

n = 201
r_max = 50
sigma = 10

ref = abel.tools.analytical.GaussianAnalytical(n, r_max, sigma, symmetric=False)
fig, axs = plt.subplots(ntrans, 1, figsize=(4,8), tight_layout=True, sharex=True, sharey=True)

for row, (label, transFunc) in enumerate(transforms.iteritems()):
    print label
    axs[row].plot(ref.r, ref.func, label='Analytical', lw=1)
    forward = np.copy(ref.abel)

    inverse = transFunc(forward,dr=ref.dr, direction='inverse')
    # if label == 'onion_bordas':
    #     inverse = inverse*ref.dr
    axs[row].plot(ref.r, inverse, label=label, ls='dashed', lw=1)
    
    axs[row].plot(ref.r, (inverse-ref.func)*10, color='r', lw=1, label='Error (x10)')
    axs[row].axhline(0, color='r', alpha=0.3, lw=1)
    
    axs[row].legend(loc='upper right', frameon=False)
    
    axs[row].set_ylim(-0.3,1.2)

plt.show()