tracker,
force_gap=gap,
force_streaker_offset=streaker_offset)
#tracker.quad_wake = False
sim_screens = fprop_dict['sim_screens']
#self.plot_streaker_calib()
meas_screens = self.get_meas_screens()
offsets = self.offsets
rms_sim = np.zeros(len(offsets))
centroid_sim = rms_sim.copy()
for n_proj, (_meas_screen, sim_screen,
offset) in enumerate(zip(meas_screens, sim_screens, offsets)):
color = ms.colorprog(n_proj, offsets)
_meas_screen.plot_standard(sp_proj,
label='%.2f mm' % (offset * 1e3),
color=color)
sim_screen.plot_standard(sp_proj, color=color, ls='--')
centroid_sim[n_proj] = sim_screen.mean()
rms_sim[n_proj] = sim_screen.rms()
opt_values[gap_ctr] += _meas_screen.compare(sim_screen)
nonzero = offsets != 0
distance_arr = gap / 2. - np.abs(self.offsets - streaker_offset)
xx_plot = distance_arr[nonzero] * 1e6
sort = np.argsort(xx_plot)
xx_plot = xx_plot[sort]
xx_plot -= xx_plot.min()
sp.tick_params(axis='y', labelsize=fs_label)
for sp in bpm_sp_dict2.values():
sp.set_xlim(-5, 5)
sp.set_ylim(-0.2, 0.2)
offset_arr = np.array(offset_list) * 1e3
ms.figure('Summary')
subplot = ms.subplot_factory(1, 1)
sp = subplot(1,
title='Summary',
xlabel='Gap',
ylabel='Structure offset fit [$\mu$m]')
labelled_ctrs = set()
for gap, offset, bpm, bpm_ctr in zip(gap_list, offset_arr, bpm_plot_list,
bpm_plot_ctr_list):
if bpm_ctr not in labelled_ctrs:
label = bpm
labelled_ctrs.add(bpm_ctr)
else:
label = None
sp.scatter(gap, offset, color=ms.colorprog(bpm_ctr, bpm_list), label=label)
sp.axhline(offset_arr.mean(), color='black', ls='--')
sp.legend()
ms.saveall('/tmp/offset_for_paper', ending='.pdf')
plt.show()
sp_ctr = 1
sp_screen = subplot(sp_ctr,
title='Measured projections',
xlabel='x (mm)',
ylabel='Intensity (arb. units)')
sp_ctr += 1
sp_profile = subplot(sp_ctr,
title='Reconstructed profiles',
xlabel='x (mm)',
ylabel='I (kA)')
sp_ctr += 1
rms_list = []
for ctr, output_dict in enumerate(output_dicts):
color = ms.colorprog(ctr, output_dicts)
gauss_dict = output_dict['gauss_dict']
gauss_dict['meas_screen'].plot_standard(sp_screen)
profile = gauss_dict['reconstructed_profile']
rms_list.append(profile.rms())
profile.plot_standard(sp_profile,
center='Mean',
label='%.1f fs' % (rms_list[-1] * 1e15))
rms_index = np.argsort(rms_list)[len(rms_list) // 2]
gauss_dict = output_dicts[rms_index]['gauss_dict']
gauss_dict['meas_screen'].plot_standard(sp_screen, color='red', lw=3)
profile = gauss_dict['reconstructed_profile']
label = '%.1f fs' % (rms_list[rms_index] * 1e15)
for gap_ctr, gap in enumerate(gap_arr):
sc.gap0 = gap
sc.fit()
streaker_offset = sc.fit_dicts_gap_order['centroid'][sc.fit_gap][sc.fit_order]['streaker_offset']
offset_list, gauss_dicts = sc.reconstruct_current(tracker, gauss_kwargs, plot_details=False)
distance_arr = gap/2. - np.abs(offset_list)
sc.plot_reconstruction(blmeas_profile=blmeas_profile, figsize=(20, 12))
ms.plt.suptitle('%.3f' % (gap*1e3))
print('%i out of %i done' % (gap_ctr+1, len(gap_arr)))
rms_arr = np.array([x['reconstructed_profile'].rms() for x in gauss_dicts])
all_rms_arr[gap_ctr] = rms_arr
d_arr2 = distance_arr - distance_arr.min()
sort = np.argsort(d_arr2)
_label = '%.3f' % (gap*1e3)
#sp_centroid.plot(d_arr2, centroid_arr, label=_label)
sp_rms.plot(d_arr2[sort]*1e6, rms_arr[sort]*1e15, label=_label, marker='.', color=ms.colorprog(gap_ctr, gap_arr))
fit = np.polyfit(d_arr2[sort], rms_arr[sort], 1)[0]
lin_fit[gap_ctr] = fit
sp_overview.errorbar(gap_arr*1e3, all_rms_arr.mean(axis=-1)*1e15, yerr=all_rms_arr.std(axis=-1)*1e15)
sp_std.plot(gap_arr*1e3, all_rms_arr.std(axis=-1)/all_rms_arr.mean(axis=-1), marker='.')
sp_fit.plot(gap_arr*1e3, lin_fit*1e15/1e6, marker='.')
sp_rms.legend()
ms.saveall('./album061/%s_file_%i' % (method, file_index), empty_suptitle=False)
if not args.noshow:
ms.show()