Introduction
Matplotlib is a powerful library for creating visualizations in Python. Sometimes, when creating plots, you may need to adjust the subplot parameters manually. This lab will show you how to programmatically adjust subplot parameters based on the size of the labels.
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Import the necessary libraries
We will need matplotlib.pyplot and matplotlib.transforms to create the plot and manipulate the subplot parameters.
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
Create the plot
Let's create a simple line plot with some long y-labels.
fig, ax = plt.subplots()
ax.plot(range(10))
ax.set_yticks([2, 5, 7], labels=['really, really, really', 'long', 'labels'])
Define the draw callback function
We will define a function that will be called every time the plot is drawn. This function will calculate the bounding boxes of the y-labels, determine if the subplot leaves enough room for the labels, and adjust the subplot parameters if necessary.
def on_draw(event):
bboxes = []
for label in ax.get_yticklabels():
## Bounding box in pixels
bbox_px = label.get_window_extent()
## Transform to relative figure coordinates. This is the inverse of
## transFigure.
bbox_fig = bbox_px.transformed(fig.transFigure.inverted())
bboxes.append(bbox_fig)
## the bbox that bounds all the bboxes, again in relative figure coords
bbox = mtransforms.Bbox.union(bboxes)
if fig.subplotpars.left < bbox.width:
## Move the subplot left edge more to the right
fig.subplots_adjust(left=1.1*bbox.width) ## pad a little
fig.canvas.draw()
Connect the draw event to the callback function
We need to connect the draw_event to our on_draw function.
fig.canvas.mpl_connect('draw_event', on_draw)
Show the plot
Finally, we will show the plot.
plt.show()
Summary
In this lab, we learned how to programmatically adjust subplot parameters based on the size of the labels. We used the matplotlib.transforms module to calculate the bounding boxes of the labels and the draw_event to call our on_draw function.