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Modified plotting scripts for thesis

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yosata committed 2022-06-17 10:41:02 +02:00
1 parent 914910e684
commit 1b3a1e0821
20 files changed
+76 -33
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scripts/SPIE/plot_wfe_analysis.py
+34 -13
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@@ -27,8 +27,8 @@ if __name__ == '__main__':
###############################
# Load in the data
r_airy, r_err_airy = load_variable('./data/lowpass_frequency_filter_airy_distance.pkl')
x0_airy, y0_airy, x0_airy_err, y0_airy_err = load_variable('./data/lowpass_frequency_filter_airy_locations.pkl')
r_airy, r_err_airy = load_variable('./data/WFE frequency analysis/lowpass_frequency_filter_airy_distance.pkl')
x0_airy, y0_airy, x0_airy_err, y0_airy_err = load_variable('./data/WFE frequency analysis/lowpass_frequency_filter_airy_locations.pkl')
central_frequencies = np.asarray([0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 25,
30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200,
220, 250, 280, 310, 340, 370, 400, 450, 500])
@@ -37,19 +37,30 @@ if __name__ == '__main__':
r_err_airy_mas = r_err_airy * platescale
# Plotting the centroid shift for all bandpasses
fig = plt.figure(figsize=(9,7))
fig = plt.figure(figsize=(6.4,4.8))
ax1 = fig.add_subplot(111)
ax1.scatter(central_frequencies, r_airy_mas, edgecolor='k', facecolors='none', alpha=0.7)
ax1.set_xscale('log')
ax1.set_xlabel('Cut-off Frequency of the lowpass filter ($\\rho/\\rho_c$)', fontsize=18)
ax1.set_ylabel('Centroid shift (mas)', fontsize=18)
ax1.tick_params(labelsize=18)
ax1.tick_params(axis='both', which='both', direction='in', labelsize=16, zorder=-1,)
ax1.grid(True, alpha=0.3, which='major')
ax1.grid(True, alpha=0.1, which='minor')
ax1.set_xlim([0.3,550])
plt.tight_layout()
plt.savefig('./figures/wfe_frequency_analysis/lowpass_spatial_freq_distance.png', bbox_inches='tight', transparent=True)
plt.savefig('./figures/wfe_frequency_analysis/lowpass_spatial_freq_distance.pdf', bbox_inches='tight', transparent=True)
figtitle = 'new_lowpass_spatial_freq_distance'
if figtitle:
plt.savefig('{}.pdf'.format(figtitle),
bbox_inches='tight',
transparent=False,
facecolor=(1, 1, 0, 0.0))
plt.savefig('{}.png'.format(figtitle),
bbox_inches='tight',
transparent=False,
facecolor=(1, 1, 0, 0.0))
plt.show()
# plt.savefig('./figures/wfe_frequency_analysis/lowpass_spatial_freq_distance.png', bbox_inches='tight', transparent=True)
# plt.savefig('./figures/wfe_frequency_analysis/lowpass_spatial_freq_distance.pdf', bbox_inches='tight', transparent=True)
@@ -60,9 +71,9 @@ if __name__ == '__main__':
################################
# Load in the data
r_airy, r_err_airy = load_variable('./data/bandpass_frequency_filter_airy_distance.pkl')
x0_airy, y0_airy, x0_airy_err, y0_airy_err = load_variable('./data/bandpass_frequency_filter_airy_locations.pkl')
central_frequencies = load_variable('./data/bandpass_frequency_filter_central_frequencies.pkl')
r_airy, r_err_airy = load_variable('./data/WFE frequency analysis/bandpass_frequency_filter_airy_distance.pkl')
x0_airy, y0_airy, x0_airy_err, y0_airy_err = load_variable('./data/WFE frequency analysis/bandpass_frequency_filter_airy_locations.pkl')
central_frequencies = load_variable('./data/WFE frequency analysis/bandpass_frequency_filter_central_frequencies.pkl')
print(central_frequencies, len(central_frequencies), len(r_airy))
r_airy_mas = r_airy * platescale
r_err_airy_mas = r_err_airy * platescale
@@ -77,7 +88,7 @@ if __name__ == '__main__':
# Plotting the centroid shift for all bandpasses
fig = plt.figure(figsize=(9,7))
fig = plt.figure(figsize=(6.4,4.8))
ax1 = fig.add_subplot(111)
ax1.scatter(central_frequencies, r_airy_mas, edgecolor='k', facecolors='none', alpha=0.7)
ax1.plot(central_frequencies[2:], 10**best_fit_y[2:], 'b-', alpha=0.5, label='Best fit: $y = 0.030 x^{-0.602}$')
@@ -85,13 +96,23 @@ if __name__ == '__main__':
ax1.set_yscale('log')
ax1.set_xlabel('Central Frequency of the bandpass filter ($\\rho/\\rho_c$)', fontsize=18)
ax1.set_ylabel('Centroid shift (mas)', fontsize=18)
ax1.tick_params(labelsize=18)
ax1.tick_params(axis='both', which='both', direction='in', labelsize=16, zorder=-1,)
ax1.grid(True, alpha=0.3, which='major')
ax1.grid(True, alpha=0.1, which='minor')
ax1.set_xlim([0.3,550])
ax1.set_ylim([10**-6, 10**0])
ax1.legend(fontsize=18)
plt.tight_layout()
plt.savefig('./figures/wfe_frequency_analysis/bandpass_spatial_freq_distance.png', bbox_inches='tight', transparent=True)
plt.savefig('./figures/wfe_frequency_analysis/bandpass_spatial_freq_distance.pdf', bbox_inches='tight', transparent=True)
figtitle = 'bandpass_spatial_freq_distance'
if figtitle:
plt.savefig('{}.pdf'.format(figtitle),
bbox_inches='tight',
transparent=False,
facecolor=(1, 1, 0, 0.0))
plt.savefig('{}.png'.format(figtitle),
bbox_inches='tight',
transparent=False,
facecolor=(1, 1, 0, 0.0))
# plt.savefig('./figures/wfe_frequency_analysis/bandpass_spatial_freq_distance.png', bbox_inches='tight', transparent=True)
# plt.savefig('./figures/wfe_frequency_analysis/bandpass_spatial_freq_distance.pdf', bbox_inches='tight', transparent=True)
plt.show()