Finish cleaning analyze_fft_ellipses.py
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@ -14,8 +14,7 @@ INTERESTING_VALUES_OF_AXES = {
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Axis.ORDINATE: [0, 25, 40, 55, 70, 85, 100, 117, 135, 150, 167, 182],
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}
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halfHeight = height // 2
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halfWidth = width // 2
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halfHeight, halfWidth = np.array(secondImage.shape) // 2
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PROFILES_OF_AXES = {
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Axis.ABSCISSA: secondImage[halfHeight , halfWidth:],
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Axis.ORDINATE: secondImage[halfHeight:, halfWidth ],
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@ -24,7 +23,7 @@ PROFILES_OF_AXES = {
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colorsOfAxes = {}
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for axis in Axis:
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plt.title('Axis Fourier transform profile\n\nLocal extremas have been listed manually from the Fourier transform visualization')
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plt.title('Profiles of Fourier transform axes\n\nLocal extremas have been listed manually from the Fourier transform visualization')
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plt.xlabel('Fourier transform axis')
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plt.ylabel('Fourier transform logarithmic intensity')
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height, width = secondImage.shape
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@ -40,18 +39,18 @@ for axis in Axis:
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def flattenDictValues(dict_):
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return itertools.chain(*dict_.values())
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# How to avoid hardcoding the default color being `black`?
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# TODO: How to avoid hardcoding the default color being `black`?
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MATPLOTLIB_DEFAULT_COLOR = 'black'
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allInterestingValuesOfAxes = list(set(flattenDictValues(INTERESTING_VALUES_OF_AXES)))
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ticks = list(plt.xticks()[0]) + allInterestingValuesOfAxes
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plt.xticks(ticks)
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for tickIndex, tick in enumerate(ticks):
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for axis in Axis:
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if tick in INTERESTING_VALUES_OF_AXES[axis]:
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#plt.xticklabels()[tickIndex].set_color(colorsOfAxes[axis])
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pltTick = plt.xticks()[1][tickIndex]
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pltTick.set_color(MATPLOTLIB_DEFAULT_COLOR if axis == list(Axis)[-1] and pltTick.get_color() != MATPLOTLIB_DEFAULT_COLOR else colorsOfAxes[axis])
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# Changing tick color would be nice too, see https://stackoverflow.com/questions/49997934/change-color-of-specific-ticks-at-plot-with-matplotlib#comment108290728_49998338
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# TODO: Changing tick color would be nice too, see https://stackoverflow.com/questions/49997934/change-color-of-specific-ticks-at-plot-with-matplotlib#comment108290728_49998338
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allInterestingValuesOfAxesMin = min(allInterestingValuesOfAxes)
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allInterestingValuesOfAxesMax = max(allInterestingValuesOfAxes)
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