Custom Spines with Axisartist

Introduction

This tutorial will show you how to use the Matplotlib library to create custom spines at specific positions.

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Import Libraries

First, we need to import the necessary libraries for this tutorial. We will be using Matplotlib and NumPy.

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits import axisartist

Create Figure and Subplots

We will create a figure with two subplots using the add_gridspec method.

fig = plt.figure(figsize=(6, 3), layout="constrained")
gs = fig.add_gridspec(1, 2)

Create Subplot 1

In the first subplot, we will create a new axis that passes through y=0 using axisartist.Axes. We will also make the other spines invisible.

ax0 = fig.add_subplot(gs[0, 0], axes_class=axisartist.Axes)
ax0.axis["y=0"] = ax0.new_floating_axis(nth_coord=0, value=0, axis_direction="bottom")
ax0.axis["y=0"].toggle(all=True)
ax0.axis["y=0"].label.set_text("y = 0")
ax0.axis["bottom", "top", "right"].set_visible(False)

Create Subplot 2

In the second subplot, we will use axisartist.axislines.AxesZero to automatically create xzero and yzero axes. We will make the other spines invisible and set the xzero axis visible.

ax1 = fig.add_subplot(gs[0, 1], axes_class=axisartist.axislines.AxesZero)
ax1.axis["xzero"].set_visible(True)
ax1.axis["xzero"].label.set_text("Axis Zero")
ax1.axis["bottom", "top", "right"].set_visible(False)

Plot Data

Now that we have created our subplots, we can plot our data using np.sin(x).

x = np.arange(0, 2*np.pi, 0.01)
ax0.plot(x, np.sin(x))
ax1.plot(x, np.sin(x))

Show Plot

Finally, we can display our plot using plt.show().

plt.show()

Summary

In this tutorial, we learned how to create custom spines at specific positions using the Matplotlib library. We created a figure with two subplots and used axisartist.Axes and axisartist.axislines.AxesZero to create our spines. We also made the other spines invisible and set the xzero axis visible. Finally, we plotted our data and displayed our plot.