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Merge pull request #921 from endolith/patch-6
Change colormaps for examples
2 parents 2b4ab26 + 8b80779 commit 5970bde

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‎examples/mplot3d/contour3d_demo.py

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from mpl_toolkits.mplot3d import axes3d
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import matplotlib.pyplot as plt
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.add_subplot(111, projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
7-
cset = ax.contour(X, Y, Z)
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cset = ax.contour(X, Y, Z, cmap=cm.coolwarm)
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ax.clabel(cset, fontsize=9, inline=1)
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plt.show()

‎examples/mplot3d/contour3d_demo2.py

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from mpl_toolkits.mplot3d import axes3d
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import matplotlib.pyplot as plt
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
7-
cset = ax.contour(X, Y, Z, extend3d=True)
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cset = ax.contour(X, Y, Z, extend3d=True, cmap=cm.coolwarm)
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ax.clabel(cset, fontsize=9, inline=1)
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plt.show()

‎examples/mplot3d/contour3d_demo3.py

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from mpl_toolkits.mplot3d import axes3d
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import matplotlib.pyplot as plt
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
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ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
8-
cset = ax.contour(X, Y, Z, zdir='z', offset=-100)
9-
cset = ax.contour(X, Y, Z, zdir='x', offset=-40)
10-
cset = ax.contour(X, Y, Z, zdir='y', offset=40)
9+
cset = ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
10+
cset = ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
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cset = ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
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ax.set_xlabel('X')
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ax.set_xlim(-40, 40)

‎examples/mplot3d/contourf3d_demo.py

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from mpl_toolkits.mplot3d import axes3d
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import matplotlib.pyplot as plt
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
7-
cset = ax.contourf(X, Y, Z)
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cset = ax.contourf(X, Y, Z, cmap=cm.coolwarm)
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ax.clabel(cset, fontsize=9, inline=1)
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plt.show()

‎examples/mplot3d/contourf3d_demo2.py

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from mpl_toolkits.mplot3d import axes3d
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import matplotlib.pyplot as plt
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
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ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
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cset = ax.contourf(X, Y, Z, zdir='z', offset=-100)
14-
cset = ax.contourf(X, Y, Z, zdir='x', offset=-40)
15-
cset = ax.contourf(X, Y, Z, zdir='y', offset=40)
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cset = ax.contourf(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
15+
cset = ax.contourf(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
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cset = ax.contourf(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
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ax.set_xlabel('X')
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ax.set_xlim(-40, 40)

‎examples/mplot3d/subplot3d_demo.py

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X, Y = np.meshgrid(X, Y)
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R = np.sqrt(X**2 + Y**2)
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Z = np.sin(R)
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surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet,
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surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
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linewidth=0, antialiased=False)
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ax.set_zlim3d(-1.01, 1.01)
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‎examples/mplot3d/surface3d_demo.py

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X, Y = np.meshgrid(X, Y)
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R = np.sqrt(X**2 + Y**2)
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Z = np.sin(R)
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surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet,
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surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
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linewidth=0, antialiased=False)
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ax.set_zlim(-1.01, 1.01)
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‎examples/mplot3d/surface3d_radial_demo.py

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X,Y = R*np.cos(P),R*np.sin(P)
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Z = ((R**2 - 1)**2)
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ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet)
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ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.YlGnBu_r)
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ax.set_zlim3d(0, 1)
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ax.set_xlabel(r'$\phi_\mathrm{real}$')
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ax.set_ylabel(r'$\phi_\mathrm{im}$')

‎examples/pylab_examples/agg_buffer_to_array.py

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ax.set_title('a simple figure')
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fig.canvas.draw()
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# grab rhe pixel buffer and dumpy it into a numpy array
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# grab the pixel buffer and dump it into a numpy array
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buf = fig.canvas.buffer_rgba()
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l, b, w, h = fig.bbox.bounds
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X = np.frombuffer(buf, np.uint8)

‎examples/pylab_examples/anchored_artists.py

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@@ -22,7 +22,7 @@ def __init__(self, transform, size, label, loc,
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pad=0.1, borderpad=0.1, sep=2, prop=None, frameon=True):
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"""
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Draw a horizontal bar with the size in data coordinate of the give axes.
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A label will be drawn underneath (center-alinged).
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A label will be drawn underneath (center-aligned).
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pad, borderpad in fraction of the legend font size (or prop)
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sep in points.

‎examples/pylab_examples/annotation_demo.py

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if 1:
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# You can also use polar notation on a catesian axes. Here the
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# You can also use polar notation on a cartesian axes. Here the
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# native coordinate system ('data') is cartesian, so you need to
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# specify the xycoords and textcoords as 'polar' if you want to
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# use (theta, radius)

‎examples/pylab_examples/axhspan_demo.py

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# draw a default vline at x=1 that spans the yrange
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l = plt.axvline(x=1)
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# draw a thick blue vline at x=0 that spans the the upper quadrant of
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# draw a thick blue vline at x=0 that spans the upper quadrant of
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# the yrange
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l = plt.axvline(x=0, ymin=0.75, linewidth=4, color='b')
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‎examples/pylab_examples/boxplot_demo2.py

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medianY.append(med.get_ydata()[j])
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plt.plot(medianX, medianY, 'k')
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medians[i] = medianY[0]
83-
# Finally, overplot the sample averages, with horixzontal alignment
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# Finally, overplot the sample averages, with horizontal alignment
8484
# in the center of each box
8585
plt.plot([np.average(med.get_xdata())], [np.average(data[i])],
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color='w', marker='*', markeredgecolor='k')

‎examples/pylab_examples/centered_ticklabels.py

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# sometimes it is nice to have ticklabels centered. mpl currently
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# associates a label with a tick, and the label can be aligned
3-
# 'center', 'feft', or 'right' using the horizontal alignment property:
3+
# 'center', 'left', or 'right' using the horizontal alignment property:
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#
55
#
66
# for label in ax.xaxis.get_xticklabels():
7-
# label.set_horizntal_alignment('right')
7+
# label.set_horizontalalignment('right')
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#
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#
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# but this doesn't help center the label between ticks. One solution

‎examples/pylab_examples/colorbar_tick_labelling_demo.py

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import matplotlib.pyplot as plt
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import numpy as np
8-
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from matplotlib import cm
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from numpy.random import randn
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# Make plot with vertical (default) colorbar
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1515
data = np.clip(randn(250, 250), -1, 1)
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17-
cax = ax.imshow(data, interpolation='nearest')
17+
cax = ax.imshow(data, interpolation='nearest', cmap=cm.coolwarm)
1818
ax.set_title('Gaussian noise with vertical colorbar')
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# Add colorbar, make sure to specify tick locations to match desired ticklabels
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2828
data = np.clip(randn(250, 250), -1, 1)
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30-
cax = ax.imshow(data, interpolation='nearest')
30+
cax = ax.imshow(data, interpolation='nearest', cmap=cm.afmhot)
3131
ax.set_title('Gaussian noise with horizontal colorbar')
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cbar = fig.colorbar(cax, ticks=[-1, 0, 1], orientation='horizontal')

‎examples/pylab_examples/contour_image.py

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levels = arange(-2.0, 1.601, 0.4) # Boost the upper limit to avoid truncation
2727
# errors.
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29+
norm = cm.colors.Normalize(vmax=abs(Z).max(), vmin=-abs(Z).max())
30+
cmap = cm.PRGn
31+
2932
figure()
3033

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3235
subplot(2,2,1)
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3437
cset1 = contourf(X, Y, Z, levels,
35-
cmap=cm.get_cmap('jet', len(levels)-1),
38+
cmap=cm.get_cmap(cmap, len(levels)-1),
39+
norm=norm,
3640
)
3741
# It is not necessary, but for the colormap, we need only the
3842
# number of levels minus 1. To avoid discretization error, use
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6670
subplot(2,2,2)
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68-
imshow(Z, extent=extent)
72+
imshow(Z, extent=extent, cmap=cmap, norm=norm)
6973
v = axis()
7074
contour(Z, levels, hold='on', colors = 'k',
7175
origin='upper', extent=extent)
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subplot(2,2,3)
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77-
imshow(Z, origin='lower', extent=extent)
81+
imshow(Z, origin='lower', extent=extent, cmap=cmap, norm=norm)
7882
v = axis()
7983
contour(Z, levels, hold='on', colors = 'k',
8084
origin='lower', extent=extent)
@@ -89,7 +93,7 @@
8993
# This is intentional. The Z values are defined at the center of each
9094
# image pixel (each color block on the following subplot), so the
9195
# domain that is contoured does not extend beyond these pixel centers.
92-
im = imshow(Z, interpolation='nearest', extent=extent)
96+
im = imshow(Z, interpolation='nearest', extent=extent, cmap=cmap, norm=norm)
9397
v = axis()
9498
contour(Z, levels, hold='on', colors = 'k',
9599
origin='image', extent=extent)

‎examples/pylab_examples/contourf_log.py

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from matplotlib import pyplot as P
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import numpy as np
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from numpy import ma
8-
from matplotlib import colors, ticker
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from matplotlib import colors, ticker, cm
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from matplotlib.mlab import bivariate_normal
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N = 100
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# Automatic selection of levels works; setting the
3232
# log locator tells contourf to use a log scale:
33-
cs = P.contourf(X, Y, z, locator=ticker.LogLocator())
33+
341A cs = P.contourf(X, Y, z, locator=ticker.LogLocator(), cmap=cm.PuBu_r)
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# Alternatively, you can manually set the levels
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# and the norm:

‎examples/pylab_examples/custom_figure_class.py

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"""
2-
You can pass a custom Figure constructor to figure if youy want to derive from the default Figure. This simple example creates a figure with a figure title
2+
You can pass a custom Figure constructor to figure if you want to derive from the default Figure. This simple example creates a figure with a figure title
33
"""
44
from matplotlib.pyplot import figure, show
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from matplotlib.figure import Figure

‎examples/pylab_examples/custom_ticker1.py

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#!/usr/bin/env python
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"""
4-
The new ticker code was designed to explicity support user customized
4+
The new ticker code was designed to explicitly support user customized
55
ticking. The documentation
66
http://matplotlib.sourceforge.net/matplotlib.ticker.html details this
77
process. That code defines a lot of preset tickers but was primarily

‎examples/pylab_examples/customize_rc.py

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"""
3-
I'm not trying to make a good liking figure here, but just to show
3+
I'm not trying to make a good looking figure here, but just to show
44
some examples of customizing rc params on the fly
55
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If you like to work interactively, and need to create different sets
@@ -36,7 +36,7 @@ def set_pub():
3636
rc('xtick.major', size=5, pad=7)
3737
rc('xtick', labelsize=15)
3838

39-
# using aliases for color, linestyle and linewith; gray, solid, thick
39+
# using aliases for color, linestyle and linewidth; gray, solid, thick
4040
rc('grid', c='0.5', ls='-', lw=5)
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rc('lines', lw=2, color='g')
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subplot(312)

‎examples/pylab_examples/date_demo_convert.py

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ax.plot_date(dates, y*y)
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# this is superfluous, since the autoscaler should get it right, but
20-
# use date2num and num2date to to convert between dates and floats if
20+
# use date2num and num2date to convert between dates and floats if
2121
# you want; both date2num and num2date convert an instance or sequence
2222
ax.set_xlim( dates[0], dates[-1] )
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‎examples/pylab_examples/demo_agg_filter.py

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def drop_shadow_line(ax):
224-
# copyed from examples/misc/svg_filter_line.py
224+
# copied from examples/misc/svg_filter_line.py
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226226
# draw lines
227227
l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-",

‎examples/pylab_examples/fancybox_demo.py

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def test2(ax):
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# bbox=round has two optional argument. pad and rounding_size.
45-
# They can be set during the initiallization.
45+
# They can be set during the initialization.
4646
p_fancy = FancyBboxPatch((bb.xmin, bb.ymin),
4747
abs(bb.width), abs(bb.height),
4848
boxstyle="round,pad=0.1",

‎examples/pylab_examples/finance_work2.py

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fig = plt.figure(facecolor='white')
98-
axescolor = '#f6f6f6' # the axies background color
98+
axescolor = '#f6f6f6' # the axes background color
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100100
ax1 = fig.add_axes(rect1, axisbg=axescolor) #left, bottom, width, height
101101
ax2 = fig.add_axes(rect2, axisbg=axescolor, sharex=ax1)

‎examples/pylab_examples/ganged_plots.py

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#!/usr/bin/env python
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"""
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To create plots that share a common axes (visually) you can set the
4-
hspace bewtween the subplots close to zero (do not use zero itself).
4+
hspace between the subplots close to zero (do not use zero itself).
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Normally you'll want to turn off the tick labels on all but one of the
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axes.
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‎examples/pylab_examples/griddata_demo.py

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zi = griddata(x,y,z,xi,yi,interp='linear')
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# contour the gridded data, plotting dots at the nonuniform data points.
1818
CS = plt.contour(xi,yi,zi,15,linewidths=0.5,colors='k')
19-
CS = plt.contourf(xi,yi,zi,15,cmap=plt.cm.jet)
19+
CS = plt.contourf(xi,yi,zi,15,cmap=plt.cm.rainbow,
20+
vmax=abs(zi).max(), vmin=-abs(zi).max())
2021
plt.colorbar() # draw colorbar
2122
# plot data points.
2223
plt.scatter(x,y,marker='o',c='b',s=5,zorder=10)

‎examples/pylab_examples/hexbin_demo.py

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"""
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import numpy as np
9-
import matplotlib.cm as cm
10-
import matplotlib.pyplot as plt
9+
import matplotlib.pyplot as plt
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np.random.seed(0)
1312
n = 100000
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2120
plt.subplots_adjust(hspace=0.5)
2221
plt.subplot(121)
23-
plt.hexbin(x,y, cmap=cm.jet)
22+
plt.hexbin(x,y, cmap=plt.cm.YlOrRd_r)
2423
plt.axis([xmin, xmax, ymin, ymax])
2524
plt.title("Hexagon binning")
2625
cb = plt.colorbar()
2726
cb.set_label('counts')
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2928
plt.subplot(122)
30-
plt.hexbin(x,y,bins='log', cmap=cm.jet)
29+
plt.hexbin(x,y,bins='log', cmap=plt.cm.YlOrRd_r)
3130
plt.axis([xmin, xmax, ymin, ymax])
3231
plt.title("With a log color scale")
3332
cb = plt.colorbar()

‎examples/pylab_examples/hexbin_demo2.py

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gridsize=30
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plt.subplot(211)
42-
plt.hexbin(x,y, C=z, gridsize=gridsize, marginals=True)
42+
plt.hexbin(x,y, C=z, gridsize=gridsize, marginals=True, cmap=plt.cm.RdBu,
43+
vmax=abs(z).max(), vmin=-abs(z).max())
4344
plt.axis([xmin, xmax, ymin, ymax])
4445
cb = plt.colorbar()
4546
cb.set_label('mean value')
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4748

4849
plt.subplot(212)
49-
plt.hexbin(x,y, gridsize=gridsize)
50+
plt.hexbin(x,y, gridsize=gridsize, cmap=plt.cm.Blues_r)
5051
plt.axis([xmin, xmax, ymin, ymax])
5152
cb = plt.colorbar()
5253
cb.set_label('N observations')

‎examples/pylab_examples/image_demo.py

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Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
1212
Z = Z2-Z1 # difference of Gaussians
1313

14-
im = plt.imshow(Z, interpolation='bilinear', cmap=cm.gray,
15-
origin='lower', extent=[-3,3,-3,3])
14+
im = plt.imshow(Z, interpolation='bilinear', cmap=cm.RdYlGn,
15+
origin='lower', extent=[-3,3,-3,3],
16+
vmax=abs(Z).max(), vmin=-abs(Z).max())
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1718
plt.show()
1819

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