8000 New Colormaps to docs by mdboom · Pull Request #5284 · matplotlib/matplotlib · GitHub
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New Colormaps to docs #5284

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Merged
merged 10 commits into from
Oct 21, 2015
Merged

New Colormaps to docs #5284

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8aec046
Add new colormaps to colormaps_reference
jenshnielsen Aug 19, 2015
4bc613f
Add new colormaps to lightness
jenshnielsen Aug 19, 2015
cda8be5
Lfunction tweak size and pep8
jenshnielsen Aug 19, 2015
b6565ea
Add colormaps to grayscale
jenshnielsen Aug 19, 2015
38b8911
colormaps format text
jenshnielsen Aug 19, 2015
db5f443
"perceptually uniform"
mdboom Oct 20, 2015
db403c3
Formatting only
mdboom Oct 20, 2015
e3bdf44
Add new category for perceptually uniform colormaps
mdboom Oct 20, 2015
ba19f2b
Can't reuse mapping here.
mdboom Oct 20, 2015
e01552c
Address @QuLogic's feedback
mdboom Oct 21, 2015
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Add new colormaps to lightness 
Also partly pep8 and make the figure a bit smaller
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@jenshnielsen
jenshnielsen committed Aug 19, 2015
commit 4bc613f447653ec816f8154fbdffad27d610f46d
57 changes: 35 additions & 22 deletions doc/users/plotting/colormaps/lightness.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,15 +6,17 @@

import colorconv as color
#from skimage import color
# we are using a local copy of colorconv from scikit-image to reduce dependencies.
# we are using a local copy of colorconv from scikit-image to
# reduce dependencies.
# You should probably use the one from scikit-image in most cases.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import matplotlib as mpl

mpl.rcParams.update({'font.size': 14})
mpl.rcParams['font.sans-serif'] = 'Arev Sans, Bitstream Vera Sans, Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif'
mpl.rcParams.update({'font.size': 12})
mpl.rcParams['font.sans-serif'] = ('Arev Sans, Bitstream Vera Sans,'
'Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif')
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Indent again.

mpl.rcParams['mathtext.fontset'] = 'custom'
mpl.rcParams['mathtext.cal'] = 'cursive'
mpl.rcParams['mathtext.rm'] = 'sans'
Expand All @@ -24,15 +26,17 @@
mpl.rcParams['mathtext.sf'] = 'sans'
mpl.rcParams['mathtext.fallback_to_cm'] = 'True'

# Have colormaps separated into categories: http://matplotlib.org/examples/color/colormaps_reference.html
# Have colormaps separated into categories:
# http://matplotlib.org/examples/color/colormaps_reference.html

cmaps = [('Sequential', ['Blues', 'BuGn', 'BuPu',
'GnBu', 'Greens', 'Greys', 'Oranges', 'OrRd',
'PuBu', 'PuBuGn', 'PuRd', 'Purples', 'RdPu',
'Reds', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd']),
('Sequential (2)', ['afmhot', 'autumn', 'bone', 'cool', 'copper',
'gist_heat', 'gray', 'hot', 'pink',
'spring', 'summer', 'winter']),
'gist_heat', 'gray', 'hot', 'inferno', 'magma',
'pink', 'plasma', 'spring', 'summer', 'viridis',
'winter']),
('Diverging', ['BrBG', 'bwr', 'coolwarm', 'PiYG', 'PRGn', 'PuOr',
'RdBu', 'RdGy', 'RdYlBu', 'RdYlGn', 'Spectral',
'seismic']),
Expand Down Expand Up @@ -60,14 +64,13 @@
dsub = 7
nsubplots = int(np.ceil(len(cmap_list)/float(dsub)))

fig = plt.figure(figsize=(11.5,4*nsubplots))
fig = plt.figure(figsize=(7,2.6*nsubplots))

for i, subplot in enumerate(range(nsubplots)):

locs = [] # locations for text labels

ax = fig.add_subplot(nsubplots, 1, i+1)
# pdb.set_trace()

for j, cmap in enumerate(cmap_list[i*dsub:(i+1)*dsub]):

Expand All @@ -79,10 +82,12 @@

# Plot colormap L values
# Do separately for each category so each plot can be pretty
# to make scatter markers change color along plot: http://stackoverflow.com/questions/8202605/matplotlib-scatterplot-colour-as-a-function-of-a-third-variable
# to make scatter markers change color along plot:
# http://stackoverflow.com/questions/8202605/matplotlib-scatterplot-colour-as-a-function-of-a-third-variable
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It's (apparently) a little known secret that stackoverflow links can be shortened to http://stackoverflow.com/q/8202605

if cmap_category=='Sequential':
dc = 0.6 # spacing between colormaps
ax.scatter(x+j*dc, lab[0,::-1,0], c=x, cmap=cmap + '_r', s=300, linewidths=0.)
ax.scatter(x+j*dc, lab[0,::-1,0], c=x, cmap=cmap + '_r',
s=300, linewidths=0.)
if i==2:
ax.axis([-0.1,4.1,0,100])
else:
Expand All @@ -91,27 +96,34 @@

elif cmap_category=='Sequential (2)':
dc = 1.15
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap, s=300, linewidths=0.)
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap,
s=300, linewidths=0.)
ax.axis([-0.1,7.0,0,100])
locs.append(x[-1]+j*dc) # store locations for colormap labels
# store locations for colormap labels
locs.append(x[-1]+j*dc)

elif cmap_category=='Diverging':
dc = 1.2
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap, s=300, linewidths=0.)
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap,
s=300, linewidths=0.)
ax.axis([-0.1,7.1,0,100])
locs.append(x[int(x.size/2.)]+j*dc) # store locations for colormap labels

# store locations for colormap labels
locs.append(x[int(x.size/2.)]+j*dc)
elif cmap_category=='Qualitative':
dc = 1.3
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap, s=300, linewidths=0.)
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap,
s=300, linewidths=0.)
ax.axis([-0.1,6.3,0,100])
locs.append(x[int(x.size/2.)]+j*dc) # store locations for colormap labels
# store locations for colormap labels
locs.append(x[int(x.size/2.)]+j*dc)

elif cmap_category=='Miscellaneous':
dc = 1.25
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap, s=300, linewidths=0.)
ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap,
s=300, linewidths=0.)
ax.axis([-0.1,6.1,0,100])
locs.append(x[int(x.size/2.)]+j*dc) # store locations for colormap labels
# store locations for colormap labels
locs.append(x[int(x.size/2.)]+j*dc)

# Set up labels for colormaps
ax.xaxis.set_ticks_position('top')
Expand All @@ -123,8 +135,9 @@
for label in labels:
label.set_rotation(60)

ax.set_xlabel(cmap_category + ' colormaps', fontsize=22)
fig.text(-0.005, 0.55, 'Lightness $L^*$', fontsize=18, transform=fig.transFigure, rotation=90)
ax.set_xlabel(cmap_category + ' colormaps', fontsize=14)
fig.text(0.0, 0.55, 'Lightness $L^*$', fontsize=12,
transform=fig.transFigure, rotation=90)

fig.tight_layout(h_pad=0.05)
fig.tight_layout(h_pad=0.05, pad=1.5)
plt.show()
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