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1 | 1 | '''
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2 |
| -For each colormap, plot the lightness parameter L* from CIELAB colorspace |
3 |
| -along the y axis vs index through the colormap. Colormaps are examined in |
| 2 | +For each colormap, plot the lightness parameter L* from CIELAB colorspace |
| 3 | +along the y axis vs index through the colormap. Colormaps are examined in |
4 | 4 | categories as in the original matplotlib gallery of colormaps.
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5 | 5 | '''
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6 | 6 |
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7 | 7 | import colorconv as color
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| 8 | +from colormaps import cmaps |
8 | 9 | #from skimage import color
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9 | 10 | # we are using a local copy of colorconv from scikit-image to
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10 | 11 | # reduce dependencies.
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11 |
| -# You should probably use the one from scikit-image in most cases. |
| 12 | +# You should probably use the one from scikit-image in most cases. |
12 | 13 | import numpy as np
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13 | 14 | import matplotlib.pyplot as plt
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14 | 15 | from matplotlib import cm
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26 | 27 | mpl.rcParams['mathtext.sf'] = 'sans'
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27 | 28 | mpl.rcParams['mathtext.fallback_to_cm'] = 'True'
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28 | 29 |
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29 |
| -# Have colormaps separated into categories: |
30 |
| -# http://matplotlib.org/examples/color/colormaps_reference.html |
31 |
| - |
32 |
| -cmaps = [('Sequential', ['Blues', 'BuGn', 'BuPu', |
33 |
| - 'GnBu', 'Greens', 'Greys', 'Oranges', 'OrRd', |
34 |
| - 'PuBu', 'PuBuGn', 'PuRd', 'Purples', 'RdPu', |
35 |
| - 'Reds', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd']), |
36 |
| - ('Sequential (2)', ['afmhot', 'autumn', 'bone', 'cool', 'copper', |
37 |
| - 'gist_heat', 'gray', 'hot', 'inferno', 'magma', |
38 |
| - 'pink', 'plasma', 'spring', 'summer', 'viridis', |
39 |
| - 'winter']), |
40 |
| - ('Diverging', ['BrBG', 'bwr', 'coolwarm', 'PiYG', 'PRGn', 'PuOr', |
41 |
| - 'RdBu', 'RdGy', 'RdYlBu', 'RdYlGn', 'Spectral', |
42 |
| - 'seismic']), |
43 |
| - ('Qualitative', ['Accent', 'Dark2', 'Paired', 'Pastel1', |
44 |
| - 'Pastel2', 'Set1', 'Set2', 'Set3']), |
45 |
| - ('Miscellaneous', ['gist_earth', 'terrain', 'ocean', 'gist_stern', |
46 |
| - 'brg', 'CMRmap', 'cubehelix', |
47 |
| - 'gnuplot', 'gnuplot2', 'gist_ncar', |
48 |
| - 'nipy_spectral', 'jet', 'rainbow', |
49 |
| - 'gist_rainbow', 'hsv', 'flag', 'prism'])] |
50 |
| - |
51 | 30 | # indices to step through colormap
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52 | 31 | x = np.linspace(0.0, 1.0, 100)
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53 | 32 |
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84 | 63 | # Do separately for each category so each plot can be pretty
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85 | 64 | # to make scatter markers change color along plot:
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86 | 65 | # http://stackoverflow.com/questions/8202605/matplotlib-scatterplot-colour-as-a-function-of-a-third-variable
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87 |
| - if cmap_category=='Sequential': |
| 66 | + if cmap_category=='Perceptually Uniform Sequential': |
| 67 | + dc = 1.15 # spacing between colormaps |
| 68 | + ax.scatter(x+j*dc, lab[0,::-1,0], c=x, cmap=cmap, |
| 69 | + s=300, linewidths=0.) |
| 70 | + if i==2: |
| 71 | + ax.axis([-0.1,4.1,0,100]) |
| 72 | + else: |
| 73 | + ax.axis([-0.1,4.7,0,100]) |
| 74 | + locs.append(x[-1]+j*dc) # store locations for colormap labels |
| 75 | + |
| 76 | + elif cmap_category=='Sequential': |
88 | 77 | dc = 0.6 # spacing between colormaps
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89 | 78 | ax.scatter(x+j*dc, lab[0,::-1,0], c=x, cmap=cmap + '_r',
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90 | 79 | s=300, linewidths=0.)
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