

In [2]:

    
def plot_comparisons(grid, scale_factor, noise):
    x = np.arange(-1.8, 1.8 + 0.001, grid)
    print(x)
    y = np.arange(-1.5, 1.5 + 0.001, grid)
    print(y)
    coords = (y, x)

    xx, yy = np.meshgrid(x, y)

    dose_ref = np.exp(-(xx**10 + yy**10))

    plt.figure()
    plt.title('Reference dose | Grid = {} cm'.format(grid))
    plt.xlabel('x (cm)')
    plt.ylabel('y (cm)')

    plt.imshow(
        dose_ref, clim=(0, 1.04), extent=[-1.8-grid/2, 1.8+grid/2, -1.5-grid/2, 1.5+grid/2])
    plt.colorbar()

    # ===

    dose_eval = dose_ref * scale_factor

    plt.figure()
    plt.title('Evaluation dose | Grid = {} cm | {} x larger than ref'.format(grid, scale_factor))
    plt.xlabel('x (cm)')
    plt.ylabel('y (cm)')

    plt.imshow(
        dose_eval, clim=(0, 1.04), extent=[-1.8-grid/2, 1.8+grid/2, -1.5-grid/2, 1.5+grid/2])
    plt.colorbar()


    # ===

    dose_ref_noise = (
        np.random.normal(loc=0, scale=noise, size=np.shape(dose_ref)) +
        dose_ref)

    plt.figure()
    plt.title('Reference dose with standard normal noise of {} | Grid = {} cm'.format(noise, grid))
    plt.xlabel('x (cm)')
    plt.ylabel('y (cm)')

    plt.imshow(
        dose_ref_noise, clim=(0, 1.04), extent=[-1.8-grid/2, 1.8+grid/2, -1.5-grid/2, 1.5+grid/2])
    plt.colorbar()
    
    
    # ===
    
    gamma_no_noise = calc_gamma(
        coords, dose_ref,
        coords, dose_eval,
        0.3, 0.03, lower_dose_cutoff=0.1, maximum_test_distance=0.6)

    plt.figure()
    plt.title('Gamma with no reference noise | Grid = {} cm'.format(grid))
    plt.xlabel('x (cm)')
    plt.ylabel('y (cm)')

    plt.imshow(
        gamma_no_noise, clim=(0, 2), extent=[-1.8-grid/2, 1.8+grid/2, -1.5-grid/2, 1.5+grid/2],
        cmap='coolwarm')
    plt.colorbar()
    
    plt.show()
    valid_gamma_no_noise = gamma_no_noise[~np.isnan(gamma_no_noise)]
    no_noise_passing = np.sum(valid_gamma_no_noise <= 1) / len(valid_gamma_no_noise)
    print("Passing rate with no reference noise = {0:.2f}".format(no_noise_passing))
    
    plt.figure()
    plt.title('Histogram of gamma with no reference noise | Grid = {} cm'.format(grid))
    plt.xlabel('Gamma')
    plt.ylabel('Number of pixels')
    
    plt.hist(valid_gamma_no_noise, 20)

    
    # ===
    
    gamma_with_noise = calc_gamma(
        coords, dose_ref_noise,
        coords, dose_eval,
        0.3, 0.03, lower_dose_cutoff=0.2, maximum_test_distance=0.6)

    plt.figure()
    plt.title('Gamma with reference noise of {} | Grid = {} cm'.format(noise, grid))
    plt.xlabel('x (cm)')
    plt.ylabel('y (cm)')

    plt.imshow(
        gamma_with_noise, clim=(0, 2), extent=[-1.8-grid/2, 1.8+grid/2, -1.5-grid/2, 1.5+grid/2],
        cmap='coolwarm')
    plt.colorbar()
    
    plt.show()
    valid_gamma_with_noise = gamma_with_noise[~np.isnan(gamma_with_noise)]
    with_noise_passing = np.sum(valid_gamma_with_noise <= 1) / len(valid_gamma_with_noise)
    print("Passing rate with reference noise of {0} = {1:.2f}".format(noise, with_noise_passing))

    plt.figure()
    plt.title('Histogram of gamma with reference noise of {} | Grid = {} cm'.format(noise, grid))
    plt.xlabel('Gamma')
    plt.ylabel('Number of pixels')
    valid_gamma_with_noise = gamma_with_noise[~np.isnan(gamma_with_noise)]
    plt.hist(valid_gamma_with_noise, 20)
    


grid = 0.1
scale_factor = 1.035
noise = 0.01

plot_comparisons(grid, scale_factor, noise)









    



[ -1.80000000e+00  -1.70000000e+00  -1.60000000e+00  -1.50000000e+00
  -1.40000000e+00  -1.30000000e+00  -1.20000000e+00  -1.10000000e+00
  -1.00000000e+00  -9.00000000e-01  -8.00000000e-01  -7.00000000e-01
  -6.00000000e-01  -5.00000000e-01  -4.00000000e-01  -3.00000000e-01
  -2.00000000e-01  -1.00000000e-01   1.55431223e-15   1.00000000e-01
   2.00000000e-01   3.00000000e-01   4.00000000e-01   5.00000000e-01
   6.00000000e-01   7.00000000e-01   8.00000000e-01   9.00000000e-01
   1.00000000e+00   1.10000000e+00   1.20000000e+00   1.30000000e+00
   1.40000000e+00   1.50000000e+00   1.60000000e+00   1.70000000e+00
   1.80000000e+00]
[ -1.50000000e+00  -1.40000000e+00  -1.30000000e+00  -1.20000000e+00
  -1.10000000e+00  -1.00000000e+00  -9.00000000e-01  -8.00000000e-01
  -7.00000000e-01  -6.00000000e-01  -5.00000000e-01  -4.00000000e-01
  -3.00000000e-01  -2.00000000e-01  -1.00000000e-01   1.33226763e-15
   1.00000000e-01   2.00000000e-01   3.00000000e-01   4.00000000e-01
   5.00000000e-01   6.00000000e-01   7.00000000e-01   8.00000000e-01
   9.00000000e-01   1.00000000e+00   1.10000000e+00   1.20000000e+00
   1.30000000e+00   1.40000000e+00   1.50000000e+00]






    












    












    












    












    



Passing rate with no reference noise = 0.63






    












    












    



Passing rate with reference noise of 0.01 = 0.95



In [3]:

    
grid = 0.2
scale_factor = 1.035
noise = 0.01

plot_comparisons(grid, scale_factor, noise)









    



[ -1.80000000e+00  -1.60000000e+00  -1.40000000e+00  -1.20000000e+00
  -1.00000000e+00  -8.00000000e-01  -6.00000000e-01  -4.00000000e-01
  -2.00000000e-01  -4.44089210e-16   2.00000000e-01   4.00000000e-01
   6.00000000e-01   8.00000000e-01   1.00000000e+00   1.20000000e+00
   1.40000000e+00   1.60000000e+00   1.80000000e+00]
[-1.5 -1.3 -1.1 -0.9 -0.7 -0.5 -0.3 -0.1  0.1  0.3  0.5  0.7  0.9  1.1  1.3
  1.5]






    












    












    












    












    



Passing rate with no reference noise = 0.62






    












    












    



Passing rate with reference noise of 0.01 = 0.81