matplotlib colorbar in each subplot

Solution 1:

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:

bar to each image

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');

Solution 2:

In plt.colorbar(z1_plot,cax=ax1), use ax= instead of cax=, i.e. plt.colorbar(z1_plot,ax=ax1)

Solution 3:

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: enter image description here

I hope this helps.
You can further have a look here, where you can find a lot of what you can do with matplotlib.

Solution 4:

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()

enter image description here

Solution 5:

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)