How to plot a 2D matrix in Python with colorbar Matplotlib?

To plot a 2D matrix in Python with a colorbar, we can use NumPy to create a 2D array matrix and use that matrix in the imshow() method along with matplotlib's colorbar functionality.

Steps

• Create a 2D data matrix using NumPy

• Use imshow() method to display data as an image on a 2D regular raster

• Create a colorbar for the ScalarMappable instance using colorbar() method

• Display the figure using show() method

Basic Example with Random Data

Here's how to create a simple 2D matrix plot with a colorbar ?

import numpy as np
import matplotlib.pyplot as plt

# Set figure size for better visualization
plt.rcParams["figure.figsize"] = [7.00, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create a 2D matrix with random data
data2D = np.random.random((50, 50))

# Plot the matrix and store the image object
im = plt.imshow(data2D, cmap="copper_r")

# Add colorbar
plt.colorbar(im)

# Display the plot
plt.show()

Example with Custom Data

You can also create a matrix with structured data for better visualization ?

import numpy as np
import matplotlib.pyplot as plt

# Create a custom 2D matrix
x = np.linspace(-3, 3, 100)
y = np.linspace(-3, 3, 100)
X, Y = np.meshgrid(x, y)

# Create a function for visualization (e.g., Gaussian)
Z = np.exp(-(X**2 + Y**2))

# Plot with different colormap
plt.figure(figsize=(8, 6))
im = plt.imshow(Z, cmap='viridis', extent=[-3, 3, -3, 3])
plt.colorbar(im, label='Intensity')
plt.title('2D Gaussian Distribution')
plt.xlabel('X')
plt.ylabel('Y')
plt.show()

Customizing the Colorbar

You can customize the colorbar appearance and add labels ?

import numpy as np
import matplotlib.pyplot as plt

# Create sample data
data = np.random.randn(30, 30)

# Create the plot
fig, ax = plt.subplots(figsize=(8, 6))
im = ax.imshow(data, cmap='plasma')

# Customize colorbar
cbar = plt.colorbar(im, ax=ax, shrink=0.8)
cbar.set_label('Values', rotation=270, labelpad=15)

# Add title and labels
ax.set_title('2D Matrix Plot with Custom Colorbar')
ax.set_xlabel('Column Index')
ax.set_ylabel('Row Index')

plt.tight_layout()
plt.show()

Key Parameters

Conclusion

Use imshow() with colorbar() to visualize 2D matrices effectively. Choose appropriate colormaps and customize the colorbar labels for better data interpretation.