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DOC : minor import tweaks
1 parent 0eaedc8 commit 8247c2d

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Lines changed: 14 additions & 21 deletions

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‎doc/users/plotting/colormaps/Lfunction.py‎

Lines changed: 6 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -1,16 +1,14 @@
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'''
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Recreate Josef Albers plot illustrating the Weber-Fechner law and illustrate
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with the binary matplotlib colormap, too. Trying to show the difference between
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Recreate Josef Albers plot illustrating the Weber-Fechner law and illustrate
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with the binary matplotlib colormap, too. Trying to show the difference between
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adding blackness to a color at different rates.
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'''
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import numpy as np
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import matplotlib.pyplot as plt
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from skimage import io, color
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import pdb
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from skimage import color
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import matplotlib as mpl
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from mpl_toolkits.mplot3d import Axes3D
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from matplotlib import cm, colors
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from matplotlib import cm
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mpl.rcParams.update({'font.size': 20})
@@ -90,7 +88,7 @@
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# common ylabel
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ax1.text(-0.3, 3.8, 'Additional Parts Black',
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ax1.text(-0.3, 3.8, 'Additional Parts Black',
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rotation=90, transform=ax1.transAxes)
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ax2.spines['left'].set_visible(False)
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# common ylabel
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ax1.text(-0.3, 4.0, 'Steps through map indices',
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ax1.text(-0.3, 4.0, 'Steps through map indices',
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rotation=90, transform=ax1.transAxes)
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fig.subplots_adjust(hspace=0.0)

‎doc/users/plotting/colormaps/grayscale.py‎

Lines changed: 2 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -3,13 +3,11 @@
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Uses lightness L* as a proxy for grayscale value.
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'''
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from skimage import io, color
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from skimage import color
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import cm
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import matplotlib as mpl
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import pdb
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from scipy.optimize import curve_fit
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mpl.rcParams.update({'font.size': 14})
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mpl.rcParams['font.sans-serif'] = 'Arev Sans, Bitstream Vera Sans, Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif'
@@ -40,7 +38,7 @@
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'gnuplot', 'gnuplot2', 'ocean', 'rainbow',
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'terrain', 'flag', 'prism'])]
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# indices to step through colormap
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# indices to step through colormap
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x = np.linspace(0.0, 1.0, 100)
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nrows = max(len(cmap_list) for cmap_category, cmap_list in cmaps)
@@ -78,4 +76,3 @@ def plot_color_gradients(cmap_category, cmap_list):
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for cmap_category, cmap_list in cmaps:
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plot_color_gradients(cmap_category, cmap_list)
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‎doc/users/plotting/colormaps/lightness.py‎

Lines changed: 6 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -2,13 +2,11 @@
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For each colormap, plot the lightness parameter L* from CIELAB colorspace along the y axis vs index through the colormap. Colormaps are examined in categories as in the original matplotlib gallery of colormaps.
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'''
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from skimage import io, color
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from skimage import color
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import cm
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import matplotlib as mpl
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import pdb
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from scipy.optimize import curve_fit
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mpl.rcParams.update({'font.size': 14})
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mpl.rcParams['font.sans-serif'] = 'Arev Sans, Bitstream Vera Sans, Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif'
@@ -39,7 +37,7 @@
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'gnuplot', 'gnuplot2', 'ocean', 'rainbow',
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'terrain', 'flag', 'prism'])]
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# indices to step through colormap
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# indices to step through colormap
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x = np.linspace(0.0, 1.0, 100)
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# Do plot
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dsub = 5 # number of colormaps per subplot
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if cmap_category == 'Diverging': # because has 13 colormaps
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dsub = 6
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elif cmap_category == 'Sequential2':
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elif cmap_category == 'Sequential2':
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dsub = 7
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elif cmap_category == 'Sequential':
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elif cmap_category == 'Sequential':
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dsub = 7
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nsubplots = int(np.ceil(len(cmap_list)/float(dsub)))
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ax = fig.add_subplot(nsubplots, 1, i+1)
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# pdb.set_trace()
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for j, cmap in enumerate(cmap_list[i*dsub:(i+1)*dsub]):
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# Get rgb values for colormap
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ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap, s=300, linewidths=0.)
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ax.axis([-0.1,6.1,0,100])
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locs.append(x[int(x.size/2.)]+j*dc) # store locations for colormap labels
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# Set up labels for colormaps
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ax.xaxis.set_ticks_position('top')
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ticker = mpl.ticker.FixedLocator(locs)

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