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90 lines
3.5 KiB
Python
90 lines
3.5 KiB
Python
import numpy as np
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import os
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import sys
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sys.path.insert(0, '/Users/joost/Dropbox/Werk/PhD/Documents/Published/FourierOptics GitHub release/')
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from fourierOptics import *
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'''
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Author: Joost van den Born, PhD student at University of Groningen
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Contact: born@astro.rug.nl
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Description: Script to generate the plots of the relation between the
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Strehl ratio and the RMS of the Wavefront Error. A comparison
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with the Marechal approximation is made.
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Script made for the SPIE manuscript.
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'''
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def expected_strehl2(rms, l):
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return np.exp( -(2*np.pi*rms/l)**2 )
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def append_to_existing_data(A, filename):
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if os.path.exists(filename):
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A_o = load_variable(filename)
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A = np.append(A, A_o)
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return A
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def plot_some_stuff():
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fig = plt.figure(figsize=(6.4,4.8))
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ax = fig.add_subplot(111)
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ax2 = ax.twiny()
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rmsValues = rmsList[:25]
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for i in range(len(rms_zern_list_complete)):
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ax.plot((0.8138)*rms_zern_list_complete[i]*1e6, strehl_zern_complete[i], 'y-',
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alpha=0.1, linewidth=.5)
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ax.plot((0.8138)*rms_psd_list_complete[i]*1e6, strehl_psd_complete[i], 'b-',
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alpha=0.1, linewidth=.5)
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ax.plot(np.linspace(1e-6,1e-3,100)*1e6, expected_strehl2(np.linspace(1e-6,1e-3,100),l),'k--',
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label='$S=\\exp[-(2\\pi\\sigma/\\lambda)^2]$')
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ax.errorbar((0.8138)*rmsValues*1e6, mean_strehl_zern, yerr=err_strehl_zern, color='y',
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linestyle='-', label='Zernikes', capsize=3, markeredgewidth=1)#,
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# linewidth=1)
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ax.errorbar((0.8138)*rmsValues*1e6, mean_strehl_psd, yerr=err_strehl_psd, color='b',
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linestyle='-', label='PSD', capsize=3, markeredgewidth=1)#,
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# linewidth=1)
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ax.set_xlabel('$\\sigma_{\\mathrm{WFE}}$ (nm)', fontsize=18)
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ax.set_ylabel('Strehl', fontsize=18)
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ax.set_ylim([0,1])
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ax.set_xlim([np.min(rmsValues)*1e6*(0.8138), np.max(rmsValues)*1e6*(0.8138)])
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ax2.set_xlim([np.min(rmsValues*(0.8138)/l), np.max(rmsValues*(0.8138)/l)])
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ax2.set_xlabel('$\\sigma/\\lambda$', fontsize=18)
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ax.legend(fontsize=18)
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ax.grid(True, alpha=0.3)
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ax.tick_params(axis='both', which='both', direction='in', labelsize=16, zorder=-1,)
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ax2.tick_params(axis='both', which='both', direction='in', labelsize=16, zorder=-1,)
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plt.tight_layout()
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# plt.savefig('./figures/SR_relation_WFE_on_ADC_p1_obscured.png', bbox_inches='tight', transparent=True)
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# plt.savefig('./figures/SR_relation_WFE_on_ADC_p1_obscured.pdf', bbox_inches='tight', transparent=True)
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figtitle = 'new_SR_relation_WFE_on_ADC_p1_obscured'
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if figtitle:
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plt.savefig('{}.pdf'.format(figtitle),
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bbox_inches='tight',
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transparent=False,
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facecolor=(1, 1, 0, 0.0))
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plt.savefig('{}.png'.format(figtitle),
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bbox_inches='tight',
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transparent=False,
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facecolor=(1, 1, 0, 0.0))
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plt.show()
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if __name__ == '__main__':
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plt.rc('font', family='serif')
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plt.rc('text', usetex=True)
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plt.rc('axes', labelsize='large')
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l = 1.49e-3
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rmsList = load_variable('./data/Strehl relation analysis/SR_RMS_values_obscured.pkl')
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strehl_zern_complete = load_variable('./data/Strehl relation analysis/SR_strehl_zern_obscured.pkl')
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strehl_psd_complete = load_variable('./data/Strehl relation analysis/SR_strehl_psd_obscured.pkl')
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rms_zern_list_complete = load_variable('./data/Strehl relation analysis/SR_rms_zern_complete_obscured.pkl')
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rms_psd_list_complete = load_variable('./data/Strehl relation analysis/SR_rms_psd_complete_obscured.pkl')
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mean_strehl_zern = np.mean(strehl_zern_complete, axis=0)
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err_strehl_zern = np.std(strehl_zern_complete, axis=0)
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mean_strehl_psd = np.mean(strehl_psd_complete, axis=0)
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err_strehl_psd = np.std(strehl_psd_complete, axis=0)
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plot_some_stuff()
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