From d48624bf232ab71760fabb3e00c133dc871b8841 Mon Sep 17 00:00:00 2001 From: Anastasiia Kutakh Date: Fri, 27 Aug 2021 12:35:06 -0400 Subject: [PATCH] . --- CDTools/models/polarized_fancy_ptycho.py | 25 ++++++++++++------------ 1 file changed, 13 insertions(+), 12 deletions(-) diff --git a/CDTools/models/polarized_fancy_ptycho.py b/CDTools/models/polarized_fancy_ptycho.py index e16b664..bfe5c15 100644 --- a/CDTools/models/polarized_fancy_ptycho.py +++ b/CDTools/models/polarized_fancy_ptycho.py @@ -3,6 +3,7 @@ from CDTools.models import CDIModel, FancyPtycho from CDTools.datasets import Ptycho2DDataset from CDTools import tools from CDTools.tools import plotting as p +# from CDTools.tools import polarized_plotting as pp from CDTools.tools import analysis from matplotlib import pyplot as plt from datetime import datetime @@ -490,30 +491,30 @@ class PolarizedFancyPtycho(FancyPtycho): plot_list = [ ('', - lambda self, fig, dataset: self.plot_wavefront_variation(dataset,fig=fig,mode='root_sum_intensity',image_title='Root Summed Probe Intensities',image_colorbar_title='Square Root of Intensity'), + lambda self, fig, dataset: self.plot_wavefront_variation(dataset, fig=fig, mode='root_sum_intensity', image_title='Root Summed Probe Intensities', image_colorbar_title='Square Root of Intensity'), lambda self: len(self.weights.shape) >= 2), ('', - lambda self, fig, dataset: self.plot_wavefront_variation(dataset,fig=fig,mode='amplitude',image_title='Probe Amplitudes (scroll to view modes)',image_colorbar_title='Probe Amplitude'), + lambda self, fig, dataset: self.plot_wavefront_variation(dataset, fig=fig, mode='amplitude', image_title='Probe Amplitudes (scroll to view modes)', image_colorbar_title='Probe Amplitude'), lambda self: len(self.weights.shape) >= 2), ('', - lambda self, fig, dataset: self.plot_wavefront_variation(dataset,fig=fig,mode='phase',image_title='Probe Phases (scroll to view modes)',image_colorbar_title='Probe Phase'), + lambda self, fig, dataset: self.plot_wavefront_variation(dataset, fig=fig, mode='phase', image_title='Probe Phases (scroll to view modes)', image_colorbar_title='Probe Phase'), lambda self: len(self.weights.shape) >= 2), ('Basis Probe Amplitudes (scroll to view modes)', - lambda self, fig: p.plot_amplitude(self.probe, fig=fig, basis=self.probe_basis,units=self.units)), + lambda self, fig: p.plot_amplitude(self.probe, fig=fig, basis=self.probe_basis, units=self.units)), ('Basis Probe Phases (scroll to view modes)', - lambda self, fig: p.plot_phase(self.probe, fig=fig, basis=self.probe_basis,units=self.units)), + lambda self, fig: p.plot_phase(self.probe, fig=fig, basis=self.probe_basis, units=self.units)), ('Average Density Matrix Amplitudes', - lambda self, fig: p.plot_amplitude(np.nanmean(np.abs(self.get_rhos()),axis=0), fig=fig), - lambda self: len(self.weights.shape) >=2), + lambda self, fig: p.plot_amplitude(np.nanmean(np.abs(self.get_rhos()), axis=0), fig=fig), + lambda self: len(self.weights.shape) >= 2), ('% Power in Top Mode (only accurate after tidy_probes)', - lambda self, fig, dataset: p.plot_nanomap(self.corrected_translations(dataset), analysis.calc_top_mode_fraction(self.get_rhos()), fig=fig,units=self.units), - lambda self: len(self.weights.shape) >=2), + lambda self, fig, dataset: p.plot_nanomap(self.corrected_translations(dataset), analysis.calc_top_mode_fraction(self.get_rhos()), fig=fig, units=self.units), + lambda self: len(self.weights.shape) >= 2), ('Object Amplitude', - lambda self, fig: p.plot_amplitude(self.obj, fig=fig, basis=self.probe_basis,units=self.units)), + lambda self, fig: p.plot_amplitude(self.obj, fig=fig, basis=self.probe_basis, units=self.units)), ('Object Phase', - lambda self, fig: p.plot_phase(self.obj, fig=fig, basis=self.probe_basis,units=self.units)), + lambda self, fig: p.plot_phase(self.obj, fig=fig, basis=self.probe_basis, units=self.units)), ('Corrected Translations', - lambda self, fig, dataset: p.plot_translations(self.corrected_translations(dataset), fig=fig,units=self.units)), + lambda self, fig, dataset: p.plot_translations(self.corrected_translations(dataset), fig=fig, units=self.units)), ('Background', lambda self, fig: plt.figure(fig.number) and plt.imshow(self.background.detach().cpu().numpy()**2)) ]