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40145bc055
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4 changed files with 272 additions and 0 deletions
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.gitignore
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.gitignore
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data/
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BIN
.swa.py.swp
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BIN
.swa.py.swp
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swa.py
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swa.py
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#! /usr/bin/python3
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from spacepy import pycdf
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import numpy as np
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import datetime
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
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# Data directory
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datadir = '/home/nicolassurface/ET-U2-SWA/data'
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# EAS1 filename
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fname_1 = 'solo_L1_swa-eas1-NM3D_20220407T000004-20220407T060504_V01.cdf'
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# EAS2 filename
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fname_2 = 'solo_L1_swa-eas2-NM3D_20220407T000004-20220407T060504_V01.cdf'
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# EAS1
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file_1 = pycdf.CDF(datadir+fname_1)
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time_1 = file_1['EPOCH'][...]
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counts_1 = file_1['SWA_EAS1_Data'][...]
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elev_1 = file_1['SWA_EAS_ELEVATION'][...]
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azim_1 = file_1['SWA_EAS_AZIMUTH'][...]
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energy_1 = file_1['SWA_EAS1_ENERGY'][...]
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file_1.close()
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# EAS2
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file_2 = pycdf.CDF(datadir+fname_2)
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time_2 = file_2['EPOCH'][...]
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counts_2 = file_2['SWA_EAS2_Data'][...]
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elev_2 = file_2['SWA_EAS_ELEVATION'][...]
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azim_2 = file_2['SWA_EAS_AZIMUTH'][...]
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energy_2 = file_2['SWA_EAS2_ENERGY'][...]
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file_2.close()
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# Sum over energy, azimuth and elevation:
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def sum3d(counts, dimA, dimB, dimC):
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sum3d_counts = np.sum(np.sum(np.sum(counts, axis=dimA), axis=dimB), axis=dimC)
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return sum3d_counts.T
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counts_tot_1 = sum3d(counts_1, 3, 2, 1) # EAS1
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counts_tot_2 = sum3d(counts_2, 3, 2, 1) # EAS2
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def sum2d(counts, dimA, dimB):
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sum2d_counts = np.sum(np.sum(counts, axis=dimA), axis=dimB)
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return sum2d_counts.T
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# Sum over azimuth and elevation:
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counts_energy_spectro_1 = sum2d(counts_1, 3, 1) # EAS1
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counts_energy_spectro_2 = sum2d(counts_2, 3, 1) # EAS2
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# Sum over energy and elevtion
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counts_azim_spectro_1 = sum2d(counts_1, 2, 1) # EAS1
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counts_azim_spectro_2 = sum2d(counts_2, 2, 1) # EAS2
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# Sum over energy and azimuth
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counts_elev_spectro_1 = sum2d(counts_1, 3, 2) # EAS1
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counts_elev_spectro_2 = sum2d(counts_2, 3, 2) # EAS2
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def make_plots(fname, time, counts_tot, energy, azim, elev, counts_energy_spectro, counts_azim_spectro, counts_elev_spectro):
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# Set figure size
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fig = plt.figure(figsize=(15,10))
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fig.subplots_adjust(hspace=0.25)
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# Set time range
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t1 = datetime.datetime(year=int(fname[22:26]), month=int(fname[26:28]), day=int(fname[28:30]), \
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hour=int(fname[31:33]), minute=int(fname[33:35])) # set start time
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t2 = datetime.datetime(year=int(fname[38:42]), month=int(fname[42:44]), day=int(fname[44:46]), \
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hour=int(fname[47:49]), minute=int(fname[49:51])) # set end time
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xfmt = mdates.DateFormatter('%H:%M')
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# Line plot
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x = time
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y = counts_tot
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ax1 = fig.add_subplot(411)
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ax1.plot(x, y, linewidth=0.5, color='k')
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ax1.xaxis.set_major_formatter(xfmt)
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ax1.set_xlim(t1, t2)
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ax1.ticklabel_format(axis='y', style='sci', scilimits=(0,0))
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ax1.set_xlabel('Time (HH:MM)')
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ax1.set_ylabel('Total counts')
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ax1.grid(linestyle=':', linewidth=0.5)
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ax1.set_title('SWA-EAS%s Nominal Mode 3D Data: %s %s-%s\n' %(str(fname)[15:16], str(t1)[0:10], str(t1)[11:16], str(t2)[11:16]))
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ax1_divider = make_axes_locatable(ax1)
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ax1.tick_params(width=0.5, length=1.5)
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cax1 = ax1_divider.append_axes('right', size='2%', pad='2%')
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cax1.axis('off')
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cax1.tick_params(width=0.5, length=1.5)
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# Energy spectrogram
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x, y = np.meshgrid(time, energy[1,:])
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ax2 = fig.add_subplot(412)
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CS2 = ax2.pcolormesh(x[:,:], y[:,:], np.log10(counts_energy_spectro[:,:]), cmap='jet') # plot spectrogram
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ax2.set_yscale('log')
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ax2.xaxis.set_major_formatter(xfmt)
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ax2.set_xlim(t1, t2)
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ax2.tick_params(labelbottom=True)
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ax2.set_xlabel('Time (HH:MM)')
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ax2.set_ylabel('Energy (eV)')
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ax2.grid(linestyle=':', linewidth=0.5)
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ax2_divider = make_axes_locatable(ax2)
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ax2.tick_params(width=0.5, length=1.5)
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cax2 = ax2_divider.append_axes('right', size='2%', pad='2%')
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cax2.tick_params(width=0.5, length=1.5)
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cbar2 = plt.colorbar(CS2, cax=cax2, label='$\mathregular{log_{10}}$(Counts)')
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cbar2.minorticks_off()
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# Azimuth spectrogram
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x, y = np.meshgrid(time, azim)
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ax3 = fig.add_subplot(413)
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CS3 = ax3.pcolormesh(x[:,:], y[:,:], counts_azim_spectro[:,:], cmap='jet')
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ax3.xaxis.set_major_formatter(xfmt)
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ax3.set_xlim(t1, t2)
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ax3.tick_params(labelbottom=True)
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ax3.set_xlabel('Time (HH:MM)')
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ax3.set_ylabel('Azimuth ($^\circ$)')
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ax3.grid(linestyle=':', linewidth=0.5)
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ax3_divider = make_axes_locatable(ax3)
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ax3.tick_params(width=0.5, length=1.5)
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cax3 = ax3_divider.append_axes('right', size='2%', pad='2%')
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cax3.tick_params(width=0.5, length=1.5)
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cbar3 = plt.colorbar(CS3, cax=cax3, label='Counts')
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cbar3.formatter.set_powerlimits((0,0))
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cbar3.minorticks_off()
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# Elevation spectrogram
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x, y = np.meshgrid(time, elev)
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ax4 = fig.add_subplot(414)
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CS4 = ax4.pcolormesh(x[:,:], y[:,:], counts_elev_spectro[:,:][::-1], cmap='jet')
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ax4.xaxis.set_major_formatter(xfmt)
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ax4.set_xlim(t1, t2)
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ax4.set_xlabel('Time (HH:MM)')
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ax4.set_ylabel('Elevation ($^\circ$)')
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ax4.grid(linestyle=':', linewidth=0.5)
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ax4_divider = make_axes_locatable(ax4)
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ax4.tick_params(width=0.5, length=1.5)
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cax4 = ax4_divider.append_axes('right', size='2%', pad='2%')
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cax4.tick_params(width=0.5, length=1.5)
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cbar4 = plt.colorbar(CS4, cax=cax4, label='Counts')
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cbar4.formatter.set_powerlimits((0,0))
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cbar4.minorticks_off()
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return
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if __name__ == "__main__":
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make_plots(fname_1, time_1, counts_tot_1, energy_1, azim_1, elev_1, counts_energy_spectro_1, counts_azim_spectro_1, counts_elev_spectro_1)
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136
swa_eas.py
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swa_eas.py
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#! /usr/bin/python3
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from spacepy import pycdf
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import numpy as np
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import datetime
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
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# Data directory
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datadir = '/home/nicolassurface/ET-U2-SWA/data'
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# EAS1 filename
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fname_1 = 'solo_L1_swa-eas1-NM3D_20220407T000004-20220407T060504_V01.cdf'
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# EAS2 filename
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fname_2 = 'solo_L1_swa-eas2-NM3D_20220407T000004-20220407T060504_V01.cdf'
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# EAS1
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file_1 = pycdf.CDF(datadir+fname_1)
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time_1 = file_1['EPOCH'][...]
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counts_1 = file_1['SWA_EAS1_Data'][...]
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elev_1 = file_1['SWA_EAS_ELEVATION'][...]
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azim_1 = file_1['SWA_EAS_AZIMUTH'][...]
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energy_1 = file_1['SWA_EAS1_ENERGY'][...]
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file_1.close()
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# EAS2
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file_2 = pycdf.CDF(datadir+fname_2)
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time_2 = file_2['EPOCH'][...]
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counts_2 = file_2['SWA_EAS2_Data'][...]
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elev_2 = file_2['SWA_EAS_ELEVATION'][...]
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azim_2 = file_2['SWA_EAS_AZIMUTH'][...]
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energy_2 = file_2['SWA_EAS2_ENERGY'][...]
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file_2.close()
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# Sum over energy, azimuth and elevation:
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def sum3d(counts, dimA, dimB, dimC):
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sum3d_counts = np.sum(np.sum(np.sum(counts, axis=dimA), axis=dimB), axis=dimC)
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return sum3d_counts.T
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counts_tot_1 = sum3d(counts_1, 3, 2, 1) # EAS1
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counts_tot_2 = sum3d(counts_2, 3, 2, 1) # EAS2
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def sum2d(counts, dimA, dimB):
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sum2d_counts = np.sum(np.sum(counts, axis=dimA), axis=dimB)
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return sum2d_counts.T
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# Sum over azimuth and elevation:
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counts_energy_spectro_1 = sum2d(counts_1, 3, 1) # EAS1
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counts_energy_spectro_2 = sum2d(counts_2, 3, 1) # EAS2
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# Sum over energy and elevtion
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counts_azim_spectro_1 = sum2d(counts_1, 2, 1) # EAS1
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counts_azim_spectro_2 = sum2d(counts_2, 2, 1) # EAS2
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# Sum over energy and azimuth
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counts_elev_spectro_1 = sum2d(counts_1, 3, 2) # EAS1
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counts_elev_spectro_2 = sum2d(counts_2, 3, 2) # EAS2
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def make_plots(fname, time, counts_tot, energy, azim, elev, counts_energy_spectro, counts_azim_spectro, counts_elev_spectro):
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# Set figure size
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fig = plt.figure(figsize=(15,10))
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fig.subplots_adjust(hspace=0.25)
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# Set time range
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t1 = datetime.datetime(year=int(fname[22:26]), month=int(fname[26:28]), day=int(fname[28:30]), \
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hour=int(fname[31:33]), minute=int(fname[33:35])) # set start time
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t2 = datetime.datetime(year=int(fname[38:42]), month=int(fname[42:44]), day=int(fname[44:46]), \
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hour=int(fname[47:49]), minute=int(fname[49:51])) # set end time
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xfmt = mdates.DateFormatter('%H:%M')
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# Line plot
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x = time
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y = counts_tot
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ax1 = fig.add_subplot(411)
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ax1.plot(x, y, linewidth=0.5, color='k')
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ax1.xaxis.set_major_formatter(xfmt)
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ax1.set_xlim(t1, t2)
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ax1.ticklabel_format(axis='y', style='sci', scilimits=(0,0))
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ax1.set_xlabel('Time (HH:MM)')
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ax1.set_ylabel('Total counts')
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ax1.grid(linestyle=':', linewidth=0.5)
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ax1.set_title('SWA-EAS%s Nominal Mode 3D Data: %s %s-%s\n' %(str(fname)[15:16], str(t1)[0:10], str(t1)[11:16], str(t2)[11:16]))
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ax1_divider = make_axes_locatable(ax1)
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ax1.tick_params(width=0.5, length=1.5)
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cax1 = ax1_divider.append_axes('right', size='2%', pad='2%')
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cax1.axis('off')
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cax1.tick_params(width=0.5, length=1.5)
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# Energy spectrogram
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x, y = np.meshgrid(time, energy[1,:])
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ax2 = fig.add_subplot(412)
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CS2 = ax2.pcolormesh(x[:,:], y[:,:], np.log10(counts_energy_spectro[:,:]), cmap='jet') # plot spectrogram
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ax2.set_yscale('log')
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ax2.xaxis.set_major_formatter(xfmt)
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ax2.set_xlim(t1, t2)
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ax2.tick_params(labelbottom=True)
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ax2.set_xlabel('Time (HH:MM)')
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ax2.set_ylabel('Energy (eV)')
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ax2.grid(linestyle=':', linewidth=0.5)
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ax2_divider = make_axes_locatable(ax2)
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ax2.tick_params(width=0.5, length=1.5)
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cax2 = ax2_divider.append_axes('right', size='2%', pad='2%')
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cax2.tick_params(width=0.5, length=1.5)
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cbar2 = plt.colorbar(CS2, cax=cax2, label='$\mathregular{log_{10}}$(Counts)')
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cbar2.minorticks_off()
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# Azimuth spectrogram
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x, y = np.meshgrid(time, azim)
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ax3 = fig.add_subplot(413)
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CS3 = ax3.pcolormesh(x[:,:], y[:,:], counts_azim_spectro[:,:], cmap='jet')
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ax3.xaxis.set_major_formatter(xfmt)
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ax3.set_xlim(t1, t2)
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ax3.tick_params(labelbottom=True)
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ax3.set_xlabel('Time (HH:MM)')
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ax3.set_ylabel('Azimuth ($^\circ$)')
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ax3.grid(linestyle=':', linewidth=0.5)
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ax3_divider = make_axes_locatable(ax3)
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ax3.tick_params(width=0.5, length=1.5)
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cax3 = ax3_divider.append_axes('right', size='2%', pad='2%')
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cax3.tick_params(width=0.5, length=1.5)
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cbar3 = plt.colorbar(CS3, cax=cax3, label='Counts')
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cbar3.formatter.set_powerlimits((0,0))
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cbar3.minorticks_off()
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# Elevation spectrogram
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x, y = np.meshgrid(time, elev)
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ax4 = fig.add_subplot(414)
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CS4 = ax4.pcolormesh(x[:,:], y[:,:], counts_elev_spectro[:,:][::-1], cmap='jet')
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ax4.xaxis.set_major_formatter(xfmt)
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ax4.set_xlim(t1, t2)
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ax4.set_xlabel('Time (HH:MM)')
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ax4.set_ylabel('Elevation ($^\circ$)')
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ax4.grid(linestyle=':', linewidth=0.5)
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ax4_divider = make_axes_locatable(ax4)
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ax4.tick_params(width=0.5, length=1.5)
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cax4 = ax4_divider.append_axes('right', size='2%', pad='2%')
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cax4.tick_params(width=0.5, length=1.5)
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cbar4 = plt.colorbar(CS4, cax=cax4, label='Counts')
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cbar4.formatter.set_powerlimits((0,0))
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cbar4.minorticks_off()
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return
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if __name__ == "__main__":
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make_plots(fname_1, time_1, counts_tot_1, energy_1, azim_1, elev_1, counts_energy_spectro_1, counts_azim_spectro_1, counts_elev_spectro_1)
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