Introduction
Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. One of the features of Matplotlib is the ability to create customized box styles.
In this lab, you will learn how to implement custom box styles in Matplotlib. You will learn how to create a custom box style as a function and as a class. You will also learn how to register a custom box style with Matplotlib.
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Implement a custom box style as a function
Custom box styles can be implemented as functions that take arguments specifying both a rectangular box and the amount of "mutation", and return the "mutated" path. Here, we will implement a custom box style that returns a new path which adds an "arrow" shape on the left of the box.
import matplotlib.pyplot as plt
from matplotlib.patches import BoxStyle
from matplotlib.path import Path
def custom_box_style(x0, y0, width, height, mutation_size):
"""
Given the location and size of the box, return the path of the box around
it.
Rotation is automatically taken care of.
Parameters
----------
x0, y0, width, height : float
Box location and size.
mutation_size : float
Mutation reference scale, typically the text font size.
"""
# padding
mypad = 0.3
pad = mutation_size * mypad
# width and height with padding added.
width = width + 2 * pad
height = height + 2 * pad
# boundary of the padded box
x0, y0 = x0 - pad, y0 - pad
x1, y1 = x0 + width, y0 + height
# return the new path
return Path([(x0, y0),
(x1, y0), (x1, y1), (x0, y1),
(x0-pad, (y0+y1)/2), (x0, y0),
(x0, y0)],
closed=True)
fig, ax = plt.subplots(figsize=(3, 3))
ax.text(0.5, 0.5, "Test", size=30, va="center", ha="center", rotation=30,
bbox=dict(boxstyle=custom_box_style, alpha=0.2))
plt.show()
Implement a custom box style as a class
Custom box styles can also be implemented as classes that implement __call__. The classes can then be registered into the BoxStyle._style_list dict, which allows specifying the box style as a string, bbox=dict(boxstyle="registered_name,param=value,...", ...).
class MyStyle:
"""A simple box."""
def __init__(self, pad=0.3):
"""
The arguments must be floats and have default values.
Parameters
----------
pad : float
amount of padding
"""
self.pad = pad
super().__init__()
def __call__(self, x0, y0, width, height, mutation_size):
"""
Given the location and size of the box, return the path of the box
around it.
Rotation is automatically taken care of.
Parameters
----------
x0, y0, width, height : float
Box location and size.
mutation_size : float
Reference scale for the mutation, typically the text font size.
"""
# padding
pad = mutation_size * self.pad
# width and height with padding added
width = width + 2.*pad
height = height + 2.*pad
# boundary of the padded box
x0, y0 = x0 - pad, y0 - pad
x1, y1 = x0 + width, y0 + height
# return the new path
return Path([(x0, y0),
(x1, y0), (x1, y1), (x0, y1),
(x0-pad, (y0+y1)/2.), (x0, y0),
(x0, y0)],
closed=True)
BoxStyle._style_list["angled"] = MyStyle # Register the custom style.
fig, ax = plt.subplots(figsize=(3, 3))
ax.text(0.5, 0.5, "Test", size=30, va="center", ha="center", rotation=30,
bbox=dict(boxstyle="angled,pad=0.5", alpha=0.2))
del BoxStyle._style_list["angled"] # Unregister it.
plt.show()
Register the custom box style with Matplotlib
Once you have implemented a custom box style as a class, you can register it with Matplotlib. This allows you to specify the box style as a string, bbox=dict(boxstyle="registered_name,param=value,...", ...).
BoxStyle._style_list["angled"] = MyStyle # Register the custom style.
Use the custom box style
Once you have implemented and registered a custom box style, you can use it with Axes.text.
fig, ax = plt.subplots(figsize=(3, 3))
ax.text(0.5, 0.5, "Test", size=30, va="center", ha="center", rotation=30,
bbox=dict(boxstyle="angled,pad=0.5", alpha=0.2))
Summary
In this lab, you learned how to implement custom box styles in Matplotlib. You learned how to create a custom box style as a function and as a class. You also learned how to register a custom box style with Matplotlib and how to use it with Axes.text.
🚀 Practice Now: Custom Box Styles in Matplotlib
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