Introduction
Matplotlib is a popular data visualization library in Python. It can be used to create a variety of different types of plots and charts. One of the functions provided by Matplotlib is matshow(), which can be used to visualize a 2D matrix or array as a color-coded image. In this lab, we will go through the steps to use matshow() to visualize a 2D array.
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Import Required Libraries
To use matshow(), we will need to import the Matplotlib library. We will also use NumPy to create a 2D array for visualization.
import matplotlib.pyplot as plt
import numpy as np
Create the 2D Array
Next, we will create a 2D array using NumPy. In this example, we will create a diagonal matrix with values ranging from 0 to 14.
a = np.diag(range(15))
Visualize the 2D Array using matshow()
Now we can use matshow() to visualize the 2D array as a color-coded image.
plt.matshow(a)
plt.show()
Interpret the Visualization
In the visualization generated by matshow(), each value in the 2D array is represented by a color. The color map used by default in Matplotlib is a gradient from blue to red, with blue representing the lowest values and red representing the highest values. In this particular visualization, the diagonal of the matrix is white, which indicates that the values on the diagonal are the highest in the matrix.
Summary
In this lab, we have learned how to use matshow() in Matplotlib to visualize a 2D array as a color-coded image. We first imported the required libraries, then created a 2D array using NumPy, and finally used matshow() to visualize the array. By interpreting the visualization, we can gain insights into the values and structure of the 2D array.