matplotlib.patches.Rectangle in Python

Last Updated : 27 Apr, 2020

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

matplotlib.patches.Rectangle

The matplotlib.patches.Rectangle class is used to rectangle patch to a plot with lower left at xy = (x, y) with specified width, height and rotation angle.

Syntax: class matplotlib.patches.Rectangle(xy, width, height, angle=0.0, **kwargs) Parameters:

xy: Lower left point to start the rectangle plotting
width : width of the rectangle
height: Height of the rectangle.
angle: Angle of rotation of the rectangle.

The below table has a list of valid kwargs;

PROPERTY	DESCRIPTION
agg_filter	a filter function that takes a (m, n, 3) float array and a dpi value that returns a (m, n, 3) array
alpha	float or None
animated	bool
antialiased or aa	unknown
capstyle	{‘butt’, ’round’, ‘projecting’}
clip_box	Bbox
clip_on	bool
clip_path	[(Path, Transform)\|Patch\|None]
color	color or sequence of rgba tuples
contains	callable
edgecolor or ec or edgecolors	color or None or ‘auto’
facecolor or fc or facecolors	color or None
figure	figure
fill	bool
gid	str
hatch	{‘/’, ‘\’, ‘\|’, ‘-‘, ‘+’, ‘x’, ‘o’, ‘O’, ‘.’, ‘*’}
in_layout	bool
joinstyle	{‘miter’, ’round’, ‘bevel’}
linestyle or ls	{‘-‘, ‘–‘, ‘-.’, ‘:’, ”, (offset, on-off-seq), …}
linewidth or linewidths or lw	float or None
path_effects	AbstractPathEffect
picker	None or bool or float or callable
path_effects	AbstractPathEffect
picker	float or callable[[Artist, Event], Tuple[bool, dict]]
rasterized	bool or None
sketch_params	(scale: float, length: float, randomness: float)
snap	bool or None
transform	matplotlib.transforms.Transform
url	str
visible	bool
zorder	float

Example 1:

Python3 1==

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle


# The image
X = np.arange(16).reshape(4, 4)

# highlight some feature in the
# middle boxes.
fig = plt.figure()

ax = fig.add_subplot(111)
ax.imshow(X, cmap = plt.cm.gray,
          interpolation ='nearest')
ax.add_patch( Rectangle((0.5, 0.5),
                        2, 2,
                        fc ='none', 
                        ec ='g',
                        lw = 10) )

plt.show()

Output:

Example 2:

Python3 1==

import matplotlib
import matplotlib.pyplot as plt


fig = plt.figure()
ax = fig.add_subplot(111)

rect1 = matplotlib.patches.Rectangle((-200, -100),
                                     400, 200,
                                     color ='green')

rect2 = matplotlib.patches.Rectangle((0, 150),
                                     300, 20,
                                     color ='pink')

rect3 = matplotlib.patches.Rectangle((-300, -50),
                                     40, 200,
                                     color ='yellow')

ax.add_patch(rect1)
ax.add_patch(rect2)
ax.add_patch(rect3)

plt.xlim([-400, 400])
plt.ylim([-400, 400])

plt.show()