Introduction
This lab is a step-by-step tutorial on how to connect events in one window, for example, a mouse press, to another figure window in Python Matplotlib.
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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.
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Set up the environment
First, we need to set up the Python environment and import the necessary libraries.
import matplotlib.pyplot as plt
import numpy as np
## Fixing random state for reproducibility
np.random.seed(19680801)
figsrc, axsrc = plt.subplots(figsize=(3.7, 3.7))
figzoom, axzoom = plt.subplots(figsize=(3.7, 3.7))
axsrc.set(xlim=(0, 1), ylim=(0, 1), autoscale_on=False,
title='Click to zoom')
axzoom.set(xlim=(0.45, 0.55), ylim=(0.4, 0.6), autoscale_on=False,
title='Zoom window')
x, y, s, c = np.random.rand(4, 200)
s *= 200
axsrc.scatter(x, y, s, c)
axzoom.scatter(x, y, s, c)
Define the on_press function
Next, we define a function called on_press that will adjust the z and y limits of the second window based on the location of a mouse click in the first window.
def on_press(event):
if event.button != 1:
return
x, y = event.xdata, event.ydata
axzoom.set_xlim(x - 0.1, x + 0.1)
axzoom.set_ylim(y - 0.1, y + 0.1)
figzoom.canvas.draw()
Connect the event to the function
Now, we connect the button press event in the first window to the on_press function we just defined.
figsrc.canvas.mpl_connect('button_press_event', on_press)
Display the plot
Finally, we display the plot to the user.
plt.show()
Summary
In this lab, we learned how to connect events in one window, for example, a mouse press, to another figure window in Python Matplotlib. We also learned how to define a function to adjust the limits of the second window based on the location of a mouse click in the first window, and how to connect the button press event to this function.