Matplotlib Scroll Event

Introduction

This lab will guide you through a step-by-step process of how to use the scroll event in Matplotlib. The scroll event can be used to navigate through 2D slices of 3D data.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Import necessary libraries

First, we need to import the necessary libraries which include Matplotlib and NumPy.

import matplotlib.pyplot as plt
import numpy as np

Create the data

We will create 3D data using NumPy's ogrid function.

x, y, z = np.ogrid[-10:10:100j, -10:10:100j, 1:10:20j]
X = np.sin(x * y * z) / (x * y * z)

Create the IndexTracker class

The IndexTracker class will keep track of the current slice index and update the plot accordingly.

class IndexTracker:
    def __init__(self, ax, X):
        self.index = 0
        self.X = X
        self.ax = ax
        self.im = ax.imshow(self.X[:, :, self.index])
        self.update()

    def on_scroll(self, event):
        increment = 1 if event.button == 'up' else -1
        max_index = self.X.shape[-1] - 1
        self.index = np.clip(self.index + increment, 0, max_index)
        self.update()

    def update(self):
        self.im.set_data(self.X[:, :, self.index])
        self.ax.set_title(
            f'Use scroll wheel to navigate\nindex {self.index}')
        self.im.axes.figure.canvas.draw()

Create the plot and connect the scroll event

We will create the plot using Matplotlib's subplots function and pass the created IndexTracker object to it. Then, we will connect the scroll event to the figure canvas using mpl_connect.

fig, ax = plt.subplots()
tracker = IndexTracker(ax, X)

fig.canvas.mpl_connect('scroll_event', tracker.on_scroll)
plt.show()

Summary

In this lab, we learned how to use the scroll event in Matplotlib to navigate through 2D slices of 3D data. We created a IndexTracker class to keep track of the current slice index and updated the plot accordingly. Finally, we created the plot and connected the scroll event to the figure canvas.