86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
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# ARES/HADES/BORG Package -- ./scripts/check_gradients.py
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# Copyright (C) 2014-2020 Guilhem Lavaux <guilhem.lavaux@iap.fr>
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# Copyright (C) 2009-2020 Jens Jasche <jens.jasche@fysik.su.se>
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#
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# Additional contributions from:
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# Guilhem Lavaux <guilhem.lavaux@iap.fr> (2023)
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#
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#+
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import matplotlib
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matplotlib.use('Agg')
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from ares_tools import read_all_h5
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import pylab as plt
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from sys import argv
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file='dump.h5'
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if (len(argv) > 1):
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file = argv[1]
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print('Reading from %s.' % file)
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g=read_all_h5(file)
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#ss=16
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#step=10
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ss=4#8*8
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step=5
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prior = g.scalars.gradient_array_prior[::ss,:,:].flatten()
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prior_ref = g.scalars.gradient_array_prior[::ss,:,:].flatten()
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dpr_adj_re= prior.real
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dpr_ref_re= prior_ref.real
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dpr_adj_im= prior.imag
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dpr_ref_im= prior_ref.imag
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lh = g.scalars.gradient_array_lh[::ss,:,:].flatten()
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lh_ref = g.scalars.gradient_array_lh_ref[::ss,:,:].flatten()
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dlh_adj_re= lh.real
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dlh_ref_re= 1*lh_ref.real
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dlh_adj_im= lh.imag
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dlh_ref_im= 1*lh_ref.imag
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fig = plt.figure(figsize=(12, 6))
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fig.subplots_adjust(left=0.08, right=0.98, bottom=0.1, top=0.95, wspace=0.25, hspace=0.16)
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ax1=plt.subplot(2,2,1) # left subplot in top row
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plt.axhline(0.0, color='black', linestyle=':')
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plt.plot(dpr_adj_re[::step],'ro',markersize=5.)
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plt.plot(dpr_ref_re[::step],color='blue')
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ax1.yaxis.get_major_formatter().set_powerlimits((-2, 2))
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ax1.xaxis.set_ticklabels('')
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plt.ylabel('dPSI_prior_real')
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ax2=plt.subplot(2,2,2) # right subplot in top row
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plt.axhline(0.0, color='black', linestyle=':')
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gg,=plt.plot(dpr_adj_im[::step],'ro',markersize=5.)
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rr,=plt.plot(dpr_ref_im[::step],color='blue')
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ax2.legend((gg,rr),('gradient','finite diff'))
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ax2.yaxis.get_major_formatter().set_powerlimits((-2, 2))
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ax2.xaxis.set_ticklabels('')
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plt.ylabel('dPSI_prior_imag')
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ax3=plt.subplot(2,2,3) # left subplot in bottom row
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plt.axhline(0.0, color='black', linestyle=':')
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plt.plot(dlh_adj_re[::step],'ro',markersize=5.)
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plt.plot(dlh_ref_re[::step],color='blue')
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ax3.yaxis.get_major_formatter().set_powerlimits((-2, 2))
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plt.xlabel('voxel ID')
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plt.ylabel('dPSI_likelihood_real')
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ax4=plt.subplot(2,2,4) # right subplot in bottom row
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plt.axhline(0.0, color='black', linestyle=':')
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plt.plot(dlh_adj_im[::step],'ro',markersize=5.)
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plt.plot(dlh_ref_im[::step],color='blue')
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ax4.yaxis.get_major_formatter().set_powerlimits((-2, 2))
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plt.xlabel('voxel ID')
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plt.ylabel('dPSI_likelihood_imag')
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plt.savefig('check_gradient.png')
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#plt.scatter(dpr_adj_re,dpr_ref_re)
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#plt.show()
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