search
Search
Unlock 100+ guides
search toc
close
Cancel
Post
account_circle
Profile
exit_to_app
Sign out
What does this mean?
Why is this true?
Give me some examples!
search
keyboard_voice
close
Searching Tips
Search for a recipe:
"Creating a table in MySQL"
Search for an API documentation: "@append"
Search for code: "!dataframe"
Apply a tag filter: "#python"
Useful Shortcuts
/ to open search panel
Esc to close search panel
to navigate between search results
d to clear all current filters
Enter to expand content preview
Doc Search
Code Search Beta
SORRY NOTHING FOUND!
mic
Start speaking...
Voice search is only supported in Safari and Chrome.
Shrink
Navigate to

# NumPy | tri method

schedule Aug 12, 2023
Last updated
local_offer
PythonNumPy
Tags
expand_more
mode_heat
Master the mathematics behind data science with 100+ top-tier guides
Start your free 7-days trial now!

Numpy's `tri(~)` method creates a 2D Numpy array that represents a lower triangular matrix. The values at and below the main diagonal are filled with 1s, while everywhere else with 0s.

# Parameters

1. `N` | `int`

The number of rows of the resulting array.

2. `M` | `int` | `optional`

The number of columns of the resulting array. By default, `M=N`.

3. `k`link | `int` | `optional`

The number of diagonals to exclude or include.

A positive value for `k` represents inclusion. `k=1` means that we include an additional diagonal on top of main diagonal.

A negative value for `k` represents exclusion. `k=-1` means that the main diagonal is excluded. `k=-2` means that the main diagonal and the diagonal underneath are excluded.

By default, `k=0`, which means that a perfect lower triangle is returned.

4. `dtype` | `string` or `type` | `optional`

The data type of the resulting array. By default, `dtype=float`.

# Return value

A Numpy array representing a lower triangular matrix.

# Examples

## Basic usage

To create a 3 by 3 lower triangular matrix:

``` np.tri(3) array([[ 1., 0., 0.], [ 1., 1., 0.], [ 1., 1., 1.]]) ```

To create a 3 by 4 lower triangular matrix of type `int`:

``` np.tri(3, 4, dtype=int) array([[1, 0, 0, 0], [1, 1, 0, 0], [1, 1, 1, 0]]) ```

## Specifying a positive k

To include an additional diagonal, set `k=1`:

``` np.tri(3, k=1, dtype=int) array([[1, 1, 0], [1, 1, 1], [1, 1, 1]]) ```

## Specifying a negative k

To exclude the main diagonal, set `k=-1`:

``` np.tri(3, k=-1) array([[ 0., 0., 0.], [ 1., 0., 0.], [ 1., 1., 0.]]) ```
Edited by 0 others
thumb_up
thumb_down
Comment
Citation
Ask a question or leave a feedback...
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!