CODEWITHSUNDEEP
pythonmatplotlibplot
EFL
EFL

Reputation: 1008

Matplotlib subplot: imshow + plot

I want to create a plot that looks like the image below. There are two unique plots in the figure. img1 was generated using plt.imshow(), while img2 was generated using plt.plot(). The code I used to generate each of the plots is provided below

plt.clf()
plt.imshow(my_matrix)
plt.savefig("mymatrix.png")

plt.clf()
plt.plot(x,y,'o-')
plt.savefig("myplot.png")

The matrix used in img1 is 64x64. The same range for img2's x-axis (x=range(64)). Ideally, the x-axes of the two img2's align with the axes of img1.

It is important to note that the final image is reminiscent of seaborn's jointplot(), but the marginal subplots (img2) in the image below do not show distribution plots.

Ideal output with annotation

Upvotes: 3

Views: 4540

Answers (1)

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339120

You can use the make_axes_locatable functionality of the mpl_toolkits.axes_grid1 to create shared axes along both directions of the central imshow plot.

Here is an example:

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np; np.random.seed(0)

Z = np.random.poisson(lam=6, size=(64,64))
x = np.mean(Z, axis=0)
y = np.mean(Z, axis=1)

fig, ax = plt.subplots()
ax.imshow(Z)

# create new axes on the right and on the top of the current axes.
divider = make_axes_locatable(ax)
axtop = divider.append_axes("top", size=1.2, pad=0.3, sharex=ax)
axright = divider.append_axes("right", size=1.2, pad=0.4, sharey=ax)
#plot to the new axes
axtop.plot(np.arange(len(x)), x, marker="o", ms=1, mfc="k", mec="k")
axright.plot(y, np.arange(len(y)), marker="o", ms=1, mfc="k", mec="k")
#adjust margins
axright.margins(y=0)
axtop.margins(x=0)
plt.tight_layout()
plt.show()

enter image description here

Upvotes: 4

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