Mastering Inset Axes in Matplotlib

Introduction

Matplotlib is a powerful data visualization library in Python. It provides a variety of plots and charts to visualize data in a meaningful way. In this lab, we will learn how to create inset axes within the main plot axes using fig.add_axes in Matplotlib.

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Import Required Libraries

We start by importing the necessary libraries, which include Matplotlib and NumPy.

import matplotlib.pyplot as plt
import numpy as np

Generate Data

In this step, we generate some data to use for the plot. We will create a Gaussian colored noise using NumPy's convolve function and plot it using Matplotlib.

np.random.seed(19680801)
dt = 0.001
t = np.arange(0.0, 10.0, dt)
r = np.exp(-t[:1000] / 0.05)
x = np.random.randn(len(t))
s = np.convolve(x, r)[:len(x)] * dt

fig, main_ax = plt.subplots()
main_ax.plot(t, s)

Set Limits and Labels

In this step, we set the limits and labels for the main plot axes.

main_ax.set_xlim(0, 1)
main_ax.set_ylim(1.1 * np.min(s), 2 * np.max(s))
main_ax.set_xlabel('time (s)')
main_ax.set_ylabel('current (nA)')
main_ax.set_title('Gaussian colored noise')

Create Inset Axes

In this step, we create two inset axes within the main plot axes using fig.add_axes. One will display a histogram of the data, and the other will display the impulse response.

## Create right inset axes
right_inset_ax = fig.add_axes([.65, .6, .2, .2], facecolor='k')
right_inset_ax.hist(s, 400, density=True)
right_inset_ax.set(title='Probability', xticks=[], yticks=[])

## Create left inset axes
left_inset_ax = fig.add_axes([.2, .6, .2, .2], facecolor='k')
left_inset_ax.plot(t[:len(r)], r)
left_inset_ax.set(title='Impulse response', xlim=(0, .2), xticks=[], yticks=[])

Display the Plot

In this step, we display the plot using the plt.show() function.

plt.show()

Summary

In this lab, we learned how to create inset axes within the main plot axes using fig.add_axes in Matplotlib. We generated data, set limits and labels, created two inset axes, and displayed the plot. This technique can be useful when we want to zoom in on a particular area of the plot or display additional information related to the data.

Creating Inset Axes