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98 lines
3.5 KiB
Python
98 lines
3.5 KiB
Python
from __future__ import division, print_function, absolute_import
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import numpy as np
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import torch as t
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from matplotlib import pyplot as plt
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import pickle
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import argparse
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from CDTools.tools import cmath, plotting
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from CDTools.tools.analysis import *
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def make_argparser():
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument('file', help='The reconstruction file to calculate metrics for')
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parser.add_argument('--use-probe', '-up', action='store_true', help='Use the probe instead of the object to align the reconstructions')
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return parser
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if __name__ == '__main__':
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args = make_argparser().parse_args()
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with open(args.file, 'rb') as f:
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dataset = pickle.load(f)
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# This converts from a list of dictionaries to a dictionary of lists
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# It's safe to assume that all elements have the same set of keys
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if type(dataset) == type([]):
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dataset = {key: [element[key] for element in dataset]
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for key in dataset[0]}
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calc_prtf = True
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else:
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# If it's a length-one reconstruction
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dataset = {key: [dataset[key]] for key in dataset}
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calc_prtf = False
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# Orthogonalize the probes
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dataset['probe'] = [orthogonalize_probes(p) for p in dataset['probe']]
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print('hi')
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synth_probe, synth_obj, aligned_objs = synthesize_reconstructions(
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dataset['probe'], dataset['obj'], args.use_probe)
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print('hey')
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if calc_prtf:
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freqs, prtf = calc_consistency_prtf(synth_obj, aligned_objs, dataset['basis'][0], nbins=200)
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# Either plot the only probe, or plot the dominant probe
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if len(synth_probe.shape) == 2:
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plotting.plot_phase(synth_probe,basis=dataset['basis'][0])
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plotting.plot_amplitude(synth_probe,basis=dataset['basis'][0])
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plotting.plot_colorized(synth_probe,basis=dataset['basis'][0])
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else:
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# Plot as many probes as exist
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try:
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for i in range(0,50):
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plotting.plot_phase(synth_probe[i],basis=dataset['basis'][0])
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plt.title('Probe ' + str(i+1) + 'Phase')
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plotting.plot_amplitude(synth_probe[i],basis=dataset['basis'][0])
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plt.title('Probe ' + str(i+1) + ' Amplitude')
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plotting.plot_colorized(synth_probe[i],basis=dataset['basis'][0])
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plt.title('Probe ' + str(i+1) + ' Colorized')
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except IndexError:
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pass
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plotting.plot_amplitude(aligned_objs[0][300:-300,300:-300],basis=dataset['basis'][0])
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plotting.plot_colorized(aligned_objs[0][300:-300,300:-300],basis=dataset['basis'][0])
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plotting.plot_phase(aligned_objs[0][300:-300,300:-300],basis=dataset['basis'][0])
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plotting.plot_amplitude(synth_obj[300:-300,300:-300],basis=dataset['basis'][0])
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plotting.plot_colorized(synth_obj[300:-300,300:-300],basis=dataset['basis'][0])
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plotting.plot_phase(synth_obj[300:-300,300:-300],basis=dataset['basis'][0])
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try:
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real_translations = dataset['translation'][0]
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real_translations -= np.min(real_translations,axis=0)[None,:]
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real_translations = real_translations
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plotting.plot_translations(real_translations)
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plotting.plot_nanomap(real_translations,dataset['weights'][0])
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except:
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pass
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plt.figure()
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plt.imshow(np.sqrt(dataset['background'][0]))
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if calc_prtf:
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plt.figure()
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plt.plot(freqs*1e-6, prtf)
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plt.xlabel('Spatial Frequency (cycles/um)')
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plt.ylabel('Consistency Based PRTF')
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plt.grid()
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plt.show()
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