# What is the numpy.tri() Method

Numpy tri() method returns an array with ones at and below the k-th diagonal and zeros elsewhere, where k is the given parameter”.

## Syntax

``````numpy.tri(rows, columns, k, dtype)
``````

## Parameters

The tri() function takes four parameters, out of which three parameters are optional.

1. rows: It represents the number of rows.
2. columns: It is the number of columns; by default, it is equal to the number of rows.
3. k: It is an integer value and 0 by default. If the value of k>0, it means the diagonal is above the main diagonal, and if not, vice versa follows.
4. dtype: It is optional to mention by default. It takes float. (It is the data type of the returned array).

## Return Value

The tri() function returns an array with 1’s and 0’s values.

## Example 1: How to Use the numpy.tri() Method

``````import numpy as np

print("tri with 3 rows 3 col and k=1 : \n", np.tri(3, 3, 1,
dtype=float), "\n")
print("tri with 3 rows and 5 columns considering main diagonal : \n",
np.tri(3, 5, 0), "\n")

print("tri with 3 rows and 5 columns and k=-1: \n", np.tri(3, 5, -1), "\n")``````

Output

``````tri with 3 rows 3 col and k=1 :
[[1. 1. 0.]
[1. 1. 1.]
[1. 1. 1.]]

tri with 3 rows and 5 columns considering main diagonal :
[[1. 0. 0. 0. 0.]
[1. 1. 0. 0. 0.]
[1. 1. 1. 0. 0.]]

tri with 3 rows and 5 columns and k=-1:
[[0. 0. 0. 0. 0.]
[1. 0. 0. 0. 0.]
[1. 1. 0. 0. 0.]] ``````

## Example 2: Using a 4X4 matrix

``````import numpy as np

print("tri with 4 rows 4 col and k=1 : \n", np.tri(4, 4, 1, dtype=float), "\n")
``````

Output

``````tri with 4 rows 4 col and k=1 :
[[1. 1. 0. 0.]
[1. 1. 1. 0.]
[1. 1. 1. 1.]
[1. 1. 1. 1.]]
``````

That’s it.

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