Standalone colorbar (matplotlib)
Question:
I’m rendering some graphics in python with matplotlib, and will include them into a LaTeX paper (using LaTex’s nice tabular alignment instead of fiddling with matplotlib’s ImageGrid, etc.). I would like to create and save a standalone colorbar with savefig, without needing to use imshow.
(the vlim, vmax parameters, as well as the cmap could be provided explicitly)
The only way I could find was quite complicated and (from what I understand) draws a hard-coded rectangle onto the canvas:
http://matplotlib.org/examples/api/colorbar_only.html
Is there an elegant way to create a standalone colorbar with matplotlib?
Answers:
You can create some dummy image and then hide it’s axe. Draw your colorbar in a customize Axes.
import pylab as pl
import numpy as np
a = np.array([[0,1]])
pl.figure(figsize=(9, 1.5))
img = pl.imshow(a, cmap="Blues")
pl.gca().set_visible(False)
cax = pl.axes([0.1, 0.2, 0.8, 0.6])
pl.colorbar(orientation="h", cax=cax)
pl.savefig("colorbar.pdf")
the result:
Using the same idea as in HYRY’s answer, if you want a “standalone” colorbar in the sense that it is independent of the items on a figure (not directly connected with how they are colored), you can do something like the following:
from matplotlib import pyplot as plt
import numpy as np
# create dummy invisible image
# (use the colormap you want to have on the colorbar)
img = plt.imshow(np.array([[0,1]]), cmap="Oranges")
img.set_visible(False)
plt.colorbar(orientation="vertical")
# add any other things you want to the figure.
plt.plot(np.random.rand(30))
So, based on this answer here, if you’re like me and want to avoid this ugly fake plt.imshow(), you can do this in basically two lines:
import matplotlib as mpl
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
col_map = plt.get_cmap('nipy_spectral')
mpl.colorbar.ColorbarBase(ax, cmap=col_map, orientation = 'vertical')
# As for a more fancy example, you can also give an axes by hand:
c_map_ax = fig.add_axes([0.2, 0.8, 0.6, 0.02])
c_map_ax.axes.get_xaxis().set_visible(False)
c_map_ax.axes.get_yaxis().set_visible(False)
# and create another colorbar with:
mpl.colorbar.ColorbarBase(c_map_ax, cmap=col_map, orientation = 'horizontal')
This solution can be also used to draw the colorbar independenly of the content of ax.
Just set fraction = .05.
Code
import matplotlib as mpl
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
fraction = 1 # .05
norm = mpl.colors.Normalize(vmin=-3, vmax=99)
cbar = ax.figure.colorbar(
mpl.cm.ScalarMappable(norm=norm, cmap='Blues'),
ax=ax, pad=.05, extend='both', fraction=fraction)
ax.axis('off')
plt.show()
That reference to http://matplotlib.org/examples/api/colorbar_only.html solved it for me. That example is a little verbose, so here is an easy way to make a standalone colorbar (for posterity)…
import matplotlib.pyplot as plt
import matplotlib as mpl
fig = plt.figure()
ax = fig.add_axes([0.05, 0.80, 0.9, 0.1])
cb = mpl.colorbar.ColorbarBase(ax, orientation='horizontal',
cmap='RdBu')
plt.savefig('just_colorbar', bbox_inches='tight')
Of course, you can specify many other aspects of the Colorbar
import matplotlib.pyplot as plt
import matplotlib as mpl
fig = plt.figure()
ax = fig.add_axes([0.05, 0.80, 0.9, 0.1])
cb = mpl.colorbar.ColorbarBase(ax, orientation='horizontal',
cmap='gist_ncar',
norm=mpl.colors.Normalize(0, 10), # vmax and vmin
extend='both',
label='This is a label',
ticks=[0, 3, 6, 9])
plt.savefig('just_colorbar', bbox_inches='tight')
To add to @blaylockbk’s answer (which is a great solution, even to add to an already created figure), for me the cmap argument won’t take strings for colormap names, but cmap = plt.cm.viridis works, if anyone run into the same problem as I.
I’m rendering some graphics in python with matplotlib, and will include them into a LaTeX paper (using LaTex’s nice tabular alignment instead of fiddling with matplotlib’s ImageGrid, etc.). I would like to create and save a standalone colorbar with savefig, without needing to use imshow.
(the vlim, vmax parameters, as well as the cmap could be provided explicitly)
The only way I could find was quite complicated and (from what I understand) draws a hard-coded rectangle onto the canvas:
http://matplotlib.org/examples/api/colorbar_only.html
Is there an elegant way to create a standalone colorbar with matplotlib?
You can create some dummy image and then hide it’s axe. Draw your colorbar in a customize Axes.
import pylab as pl
import numpy as np
a = np.array([[0,1]])
pl.figure(figsize=(9, 1.5))
img = pl.imshow(a, cmap="Blues")
pl.gca().set_visible(False)
cax = pl.axes([0.1, 0.2, 0.8, 0.6])
pl.colorbar(orientation="h", cax=cax)
pl.savefig("colorbar.pdf")
the result:
Using the same idea as in HYRY’s answer, if you want a “standalone” colorbar in the sense that it is independent of the items on a figure (not directly connected with how they are colored), you can do something like the following:
from matplotlib import pyplot as plt
import numpy as np
# create dummy invisible image
# (use the colormap you want to have on the colorbar)
img = plt.imshow(np.array([[0,1]]), cmap="Oranges")
img.set_visible(False)
plt.colorbar(orientation="vertical")
# add any other things you want to the figure.
plt.plot(np.random.rand(30))
So, based on this answer here, if you’re like me and want to avoid this ugly fake plt.imshow(), you can do this in basically two lines:
import matplotlib as mpl
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
col_map = plt.get_cmap('nipy_spectral')
mpl.colorbar.ColorbarBase(ax, cmap=col_map, orientation = 'vertical')
# As for a more fancy example, you can also give an axes by hand:
c_map_ax = fig.add_axes([0.2, 0.8, 0.6, 0.02])
c_map_ax.axes.get_xaxis().set_visible(False)
c_map_ax.axes.get_yaxis().set_visible(False)
# and create another colorbar with:
mpl.colorbar.ColorbarBase(c_map_ax, cmap=col_map, orientation = 'horizontal')
This solution can be also used to draw the colorbar independenly of the content of ax.
Just set fraction = .05.
Code
import matplotlib as mpl
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
fraction = 1 # .05
norm = mpl.colors.Normalize(vmin=-3, vmax=99)
cbar = ax.figure.colorbar(
mpl.cm.ScalarMappable(norm=norm, cmap='Blues'),
ax=ax, pad=.05, extend='both', fraction=fraction)
ax.axis('off')
plt.show()
That reference to http://matplotlib.org/examples/api/colorbar_only.html solved it for me. That example is a little verbose, so here is an easy way to make a standalone colorbar (for posterity)…
import matplotlib.pyplot as plt
import matplotlib as mpl
fig = plt.figure()
ax = fig.add_axes([0.05, 0.80, 0.9, 0.1])
cb = mpl.colorbar.ColorbarBase(ax, orientation='horizontal',
cmap='RdBu')
plt.savefig('just_colorbar', bbox_inches='tight')
Of course, you can specify many other aspects of the Colorbar
import matplotlib.pyplot as plt
import matplotlib as mpl
fig = plt.figure()
ax = fig.add_axes([0.05, 0.80, 0.9, 0.1])
cb = mpl.colorbar.ColorbarBase(ax, orientation='horizontal',
cmap='gist_ncar',
norm=mpl.colors.Normalize(0, 10), # vmax and vmin
extend='both',
label='This is a label',
ticks=[0, 3, 6, 9])
plt.savefig('just_colorbar', bbox_inches='tight')
To add to @blaylockbk’s answer (which is a great solution, even to add to an already created figure), for me the cmap argument won’t take strings for colormap names, but cmap = plt.cm.viridis works, if anyone run into the same problem as I.