I would like to add a separate colorbar to each subplot in a 2x2 plot.
fig , ( (ax1,ax2) , (ax3,ax4)) = plt.subplots(2, 2,sharex = True,sharey=True)
z1_plot = ax1.scatter(x,y,c = z1,vmin=0.0,vmax=0.4)
plt.colorbar(z1_plot,cax=ax1)
z2_plot = ax2.scatter(x,y,c = z2,vmin=0.0,vmax=40)
plt.colorbar(z1_plot,cax=ax2)
z3_plot = ax3.scatter(x,y,c = z3,vmin=0.0,vmax=894)
plt.colorbar(z1_plot,cax=ax3)
z4_plot = ax4.scatter(x,y,c = z4,vmin=0.0,vmax=234324)
plt.colorbar(z1_plot,cax=ax4)
plt.show()
I thought that this is how you do it, but the resulting plot is really messed up; it just has an all grey background and ignores the set_xlim , set_ylim commands I have (not shown here for simplicity). + it shows no color bars. Is this the right way to do it?
I also tried getting rid of the "cax = ...", but then the colorbar all goes on the bottom right plot and not to each separate plot!
This question is related to
python
matplotlib
colorbar
Please have a look at this matplotlib example page. There it is shown how to get the following plot with four individual colorbars for each subplot:
I hope this helps.
You can further have a look here, where you can find a lot of what you can do with matplotlib
.
In plt.colorbar(z1_plot,cax=ax1)
, use ax=
instead of cax=
, i.e. plt.colorbar(z1_plot,ax=ax1)
This can be easily solved with the the utility make_axes_locatable
. I provide a minimal example that shows how this works and should be readily adaptable:
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np
m1 = np.random.rand(3, 3)
m2 = np.arange(0, 3*3, 1).reshape((3, 3))
fig = plt.figure(figsize=(16, 12))
ax1 = fig.add_subplot(121)
im1 = ax1.imshow(m1, interpolation='None')
divider = make_axes_locatable(ax1)
cax = divider.append_axes('right', size='5%', pad=0.05)
fig.colorbar(im1, cax=cax, orientation='vertical')
ax2 = fig.add_subplot(122)
im2 = ax2.imshow(m2, interpolation='None')
divider = make_axes_locatable(ax2)
cax = divider.append_axes('right', size='5%', pad=0.05)
fig.colorbar(im2, cax=cax, orientation='vertical');
Specify the ax
argument to matplotlib.pyplot.colorbar()
, e.g.
import numpy as np
import matplotlib.pyplot as plt
fig, ax = plt.subplots(2, 2)
for i in range(2):
for j in range(2):
data = np.array([[i, j], [i+0.5, j+0.5]])
im = ax[i, j].imshow(data)
plt.colorbar(im, ax=ax[i, j])
plt.show()
Try to use the func below to add colorbar:
def add_colorbar(mappable):
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib.pyplot as plt
last_axes = plt.gca()
ax = mappable.axes
fig = ax.figure
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cbar = fig.colorbar(mappable, cax=cax)
plt.sca(last_axes)
return cbar
Then you codes need to be modified as:
fig , ( (ax1,ax2) , (ax3,ax4)) = plt.subplots(2, 2,sharex = True,sharey=True)
z1_plot = ax1.scatter(x,y,c = z1,vmin=0.0,vmax=0.4)
add_colorbar(z1_plot)
Source: Stackoverflow.com