# Python Numpy matrix.trace() Function

NumPy Library

NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import it in our program and then we can easily use the functionality of NumPy in our program.

NumPy is a Python library that is frequently used for scientific and statistical analysis. NumPy arrays are grids of the same datatype’s values.

Numpy matrix.trace() Function:

We can find the sum of all the diagonal elements of a matrix using the matrix.trace() method of the Numpy module.

Syntax:

 matrix.trace()

Return Value:

The sum of all the diagonal elements of a given matrix is returned by the trace() function.

## Numpy matrix.trace() Function in Python

### For 2-Dimensional (2D) Matrix

Approach:

• Import numpy module using the import keyword
• Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing some random 2D matrix as an argument to it and store it in a variable
• Apply trace() function on the given matrix to get the sum of all the diagonal elements of a given matrix
• Store it in another variable
• Print the sum of all the diagonal elements of a given matrix.
• The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np

# Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing
# some random 2D matrix as an argument to it and store it in a variable
gvn_matrx = np.matrix('[2, 1; 6, 3]')

# Apply trace() function on the given matrix to get the sum of all the diagonal
# elements of a given matrix
# Store it in another variable
rslt = gvn_matrx.trace()
# Print the sum of all the diagonal elements of a given matrix
print("The sum of all the diagonal elements of a given matrix:")
print(rslt)

Output:

The sum of all the diagonal elements of a given matrix:
[[5]]

### For 3-Dimensional (3D) Matrix

Approach:

• Import numpy module using the import keyword
• Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing some random 3D matrix as an argument to it and store it in a variable
• Apply trace() function on the given matrix to get the sum of all the diagonal elements of a given matrix
• Store it in another variable
• Print the sum of all the diagonal elements of a given matrix.
• The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np

# Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing
# some random 3D matrix as an argument to it and store it in a variable
gvn_matrx = np.matrix('[2, 4, 1; 8, 7, 3; 10, 9, 5]')

# Apply trace() function on the given matrix to get the sum of all the diagonal
# elements of a given matrix
# Store it in another variable
rslt = gvn_matrx.trace()
# Print the sum of all the diagonal elements of a given matrix
print("The sum of all the diagonal elements of a given matrix:")
print(rslt)

Output:

The sum of all the diagonal elements of a given matrix:
[[14]]