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55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Created on Thu Mar 1 11:30:31 2018
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@author: z5030440
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Contains all the utilities, convenience functions and small functions that do simple things
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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import datetime
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import pdb
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def ecdf(x):
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"""convenience function for computing the empirical CDF"""
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vals, counts = np.unique(x, return_counts=True)
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ecdf = np.cumsum(counts).astype(np.float64)
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ecdf /= ecdf[-1]
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return vals, ecdf
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def intensity_histogram(image):
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"""plots histogram and cumulative distribution of the pixel intensities in an image"""
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imSize = image.shape
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if len(imSize) == 2:
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im = image[:,:].reshape(imSize[0] * imSize[1])
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im = im[~np.isnan(im)]
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fig, (ax1, ax2) = plt.subplots(2,1, sharex=True, figsize = (8,6))
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ax1.hist(im, bins=300)
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ax1.set_title('Probability density function')
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ax2.hist(im, bins=300, cumulative=True, histtype='step')
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ax2.set_title('Cumulative distribution')
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plt.show()
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else:
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for i in range(imSize[2]):
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im = image[:,:,i].reshape(imSize[0] * imSize[1])
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im = im[~np.isnan(im)]
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fig, (ax1, ax2) = plt.subplots(2,1, sharex=True, figsize = (8,6))
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ax1.hist(im, bins=300)
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ax1.set_title('Probability density function')
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ax2.hist(im, bins=300, cumulative=True, histtype='step')
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ax2.set_title('Cumulative distribution')
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plt.show()
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def compare_images(im1, im2):
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"""plots 2 images next to each other, sharing the axis"""
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plt.figure()
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ax1 = plt.subplot(121)
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plt.imshow(im1, cmap='gray')
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ax2 = plt.subplot(122, sharex=ax1, sharey=ax1)
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plt.imshow(im2, cmap='gray')
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plt.show()
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