4 Ways to Draw a Rectangle in Matplotlib

Hello, geeks, and welcome to today’s article; we will cover the Matplotlib draw a rectangle. Along with that, we will also look at its syntax and parameters for a better overall understanding. Then, we will see the application of all the theory parts through a couple of examples.

So, to draw rectangles on the matplotlib plot, we use the function matplotlib patches Rectangle. This function helps us in plotting the rectangular patch with a specific width and height. As we move ahead, things will become a lot clearer to us. We will be looking at the syntax associated with this function, followed by parameters.

Syntax

matplotlib.patches.Rectangle()

This is the general syntax for our function. It has several parameters associated with it, which we will cover in the next section of this article.

Parameters

1. xy:

This parameter represents the lower left point from which the rectangle plotting will start.

2. width

Through this parameter, user specifies the width of the rectangle that he or she wants to create.

3. height

Through this parameter, user specifies the height of the rectangle that he or she wants to create.

4. angle

This parameter represents the angle of rotation for the created rectangle.

Examples

As we are done with all the theory portions related to the Matplotlib, draw a rectangle. This section will look at how this function works and how it helps us achieve our desired output. We will start with an elementary-level example and gradually move our way to more complicated examples.

1. How to draw a Rectangle in a Plot

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

fig, ax = plt.subplots()
ax.plot([1,5,2],[2,3,4],color="cyan")
ax.add_patch(Rectangle((2, 2), 1, 3,color="yellow"))
plt.xlabel("X-AXIS")
plt.ylabel("Y-AXIS")
plt.title("PLOT-1")

plt.show()

Here, we can see the very first example related to matplotlib patches Rectangle. The primary aim of this example was to get aware of the syntax and how it is executed. To do it, first, we have imported the necessary modules. Then, we created a simple plot and changed its color as per my wish.

Then, to make a rectangle, we have used our functions syntax. Here (2,2) represents the lower-left point from which the rectangle formation will start. Next, we defined 1 and 3 as their width and height for the rectangle. From seeing the output image, it is quite evident that we have executed the program successfully.

2. Draw Matplotlib Rectangle on a scatter plot

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

fig, ax = plt.subplots()
ax.scatter([5, 7, 8, 7, 2, 17, 2, 9,
     4, 11, 12, 9, 6],[99, 86, 87, 88, 100, 86,
     103, 87, 94, 78, 77, 85, 86])
ax.add_patch( Rectangle((5, 82.5),
                        5, 7.5,
                        fc='none',
                        color ='yellow',
                        linewidth = 5,
                        linestyle="dotted") )
plt.xlabel("X-AXIS")
plt.ylabel("Y-AXIS")
plt.title("PLOT-2")

plt.show()

Above, we can see an example related to the scatter plot. A scatter plot is commonly seen in statistics. Herewith, with the help of the for function, we have tried to create a boundary between the like points and outliners. Outliners can be understood as points that are a way to be apart from the rest of the data. If taken into consideration, they can hurt the calculation of the value of central tendencies.

To do so, first, we have created a scatter plot. After this, we have used our function as the above example. Here, we have made specific customizations to the function. We have used “fc,” which decides whether the rectangle will be color filled. Then we used the “linewidth” and “line style” parameters to customize the rectangle border.

3. Plotting a Matplotlib Rectangle on an Image

import matplotlib.pyplot as plt
import matplotlib.patches as patches
from PIL import Image
import numpy as np

x = np.array(Image.open('89.jpg'))
plt.imshow(x)

fig, ax = plt.subplots(1)

ax.imshow(x)

rect = patches.Rectangle((500, 1500), 1400, 1300, linewidth=1,
                         edgecolor='r', facecolor="none")

ax.add_patch(rect)
plt.show()

Here, we have successfully created a rectangle on an image. To do so, we have used our function and specified all the parameters we need.

4. Drawing a 3D Rectangle

The essential thing to draw a 3d rectangle is a set of proper coordinates. Using mpl toolkits, you can then plot a 3d rectangle or parallelepiped using the right sets for vertices. Below, you can see the code through which we can create a 3d rectangle

import numpy as np
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection
import matplotlib.pyplot as plt
points = np.array([[-1, -1, -1],
                  [1, -1, -1 ],
                  [1, 1, -1],
                  [-1, 1, -1],
                  [-1, -1, 1],
                  [1, -1, 1 ],
                  [1, 1, 1],
                  [-1, 1, 1]])
Z = points
Z = 10.0*Z
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
r = [-1,1]
X, Y = np.meshgrid(r, r)
ax.scatter3D(Z[:, 0], Z[:, 1], Z[:, 2])
verts = [[Z[0],Z[1],Z[2],Z[3]],
 [Z[4],Z[5],Z[6],Z[7]],
 [Z[0],Z[1],Z[5],Z[4]],
 [Z[2],Z[3],Z[7],Z[6]],
 [Z[1],Z[2],Z[6],Z[5]],
 [Z[4],Z[7],Z[3],Z[0]]]
ax.add_collection3d(Poly3DCollection(verts, facecolors='cyan', linewidths=1, edgecolors='r', alpha=.20))
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.show()

Also Read: 6 Ways to Plot a Circle in Matplotlib

Conclusion

In this article, we covered the Matplotlib draw rectangle. The function matplotlib patches Rectangle is used to create rectangles in a plot. Besides that, we have also looked at its syntax and parameters. For better understanding, we looked at a couple of examples. We varied the syntax and looked at the output for each case.

I hope this article was able to clear all doubts. But if you have any unsolved queries, feel free to write them down below in the comment section.

Done reading this; why not read about ways to convert float to string next?