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59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
from __future__ import division, print_function, absolute_import
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import numpy as np
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from matplotlib import pyplot as plt
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import pickle
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from CDTools.tools import cmath, plotting
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from CDTools.tools.analysis import *
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#
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# Note that much of this functionality is duplicated by the convenience
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# script. Try running:
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#
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# python -m CDTools.scripts.synthesize example_reconstructions/gold_balls_ensemble.pickle
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#
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# Which will perform much of the same analysis on any saved reconstruction
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# ensemble
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#
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with open('example_reconstructions/gold_balls_ensemble.pickle', '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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# Now we synthesize the object using the tool from CDTools
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synth_probe, synth_obj, aligned_objs = synthesize_reconstructions(
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dataset['probe'], dataset['obj'])
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# And then we calculate the consistency PRTF from this
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freqs, prtf = calc_consistency_prtf(synth_obj, aligned_objs, dataset['basis'][0])
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# Plot the first mode in detail
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plotting.plot_phase(synth_probe[0],basis=dataset['basis'][0])
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plotting.plot_amplitude(synth_probe[0],basis=dataset['basis'][0])
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plotting.plot_colorized(synth_probe[0],basis=dataset['basis'][0])
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# Just plot the colorized version of the subdominant modes
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plotting.plot_colorized(synth_probe[1],basis=dataset['basis'][0])
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plotting.plot_colorized(synth_probe[2],basis=dataset['basis'][0])
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plotting.plot_amplitude(synth_obj,basis=dataset['basis'][0])
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plotting.plot_colorized(synth_obj,basis=dataset['basis'][0])
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plotting.plot_phase(synth_obj,basis=dataset['basis'][0])
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# Now plot the 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.show()
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