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Numpy – Get the Upper Triangular Matrix (With Examples)

The Numpy library in Python comes with a number of useful functions to work with and manipulate the data in arrays. In this tutorial, we will look at how to get the upper triangular matrix from a 2d array in Numpy.

How to get the upper triangular matrix in Numpy?

get the upper triangular matrix from a numpy array

You can use the numpy built-in numpy.triu() function to get the upper triangular matrix from a 2d Numpy array. Pass the array as an argument to the function.

The following is the syntax –

numpy.triu(m, k)

The numpy.tril() function takes the following parameters –

  1. m – The input array for which you want to get the upper triangular matrix. For arrays with dimensions greater than 2, the function will apply to the final two axes.
  2. k – The diagonal below which to zero the elements. It is 0 (the main diagonal) by default. Diagonals below the main diagonal have k < 0 and the ones above the main diagonal have k > 0.

It returns a numpy array (the upper triangular matrix of the passed array) with elements below the specified diagonal as 0.

Examples

Let’s now look at examples of using the above syntax to get the upper triangular matrix from a 2d array.

First, we will create a Numpy array that we will use throughout this tutorial.

import numpy as np

# create a 2D numpy array
arr = np.array([
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9],
    [10, 11, 12]
])
# display the matrix
print(arr)

Output:

[[ 1  2  3]
 [ 4  5  6]
 [ 7  8  9]
 [10 11 12]]

Here, we used the numpy.array() function to create a 2d array of shape 4×3 (having 4 rows and 3 columns).

Example 1 – Get the upper triangular matrix with the default diagonal

Let’s now use the numpy.triu() function to get the upper triangular matrix for the 2d array created above. We will use the default diagonal (k = 0).

# get the upper triangular matrix
utm_arr = np.triu(arr)
# display the matrix
print(utm_arr)

Output:

[[1 2 3]
 [0 5 6]
 [0 0 9]
 [0 0 0]]

We get the upper triangular matrix as a numpy array. You can see that the values below the main diagonal are zero in the returned matrix.

Example 2 – Get the upper triangular matrix with a custom diagonal

In the above example, we used the main diagonal to compute our upper triangular matrix.

The numpy.triu() function comes with an optional parameter, k that you can use to specify the diagonal you want to use for computing the upper triangular matrix.

The below image better illustrates the different values of k (representing different diagonals) for our input array.

k is 0 by default. The diagonals below the main diagonal have k < 0 and the diagonals above it have k > 0.

Let’s use k = -1 to get the upper triangular matrix.

# get the upper triangular matrix
utm_arr = np.triu(arr, k=-1)
# display the matrix
print(utm_arr)

Output:

[[ 1  2  3]
 [ 4  5  6]
 [ 0  8  9]
 [ 0  0 12]]

The resulting upper triangular matrix has values below the diagonal, k = -1 as zeros.

Summary

In this tutorial, we looked at how to get the upper triangular matrix of a 2d array in Numpy. The following are the key takeaways from this tutorial.

  • Use the numpy.triu() function to get the upper triangular matrix of an array. Pass the array as an argument.
  • You can specify the diagonal below which you want to keep the values zero using the optional parameter k. By default, it represents the main diagonal, k = 0.

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Author

  • Piyush

    Piyush is a data scientist passionate about using data to understand things better and make informed decisions. In the past, he's worked as a Data Scientist for ZS and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.