How to make create a triangle of "1"?

Question

I want to create this from multiple arrays, best using NumPy:

1 0 0 0 0 0
1 1 0 0 0 0
1 1 1 0 0 0
1 1 1 1 0 0
1 1 1 1 1 0
1 1 1 1 1 1

However, I prefer if a library is used to create this, how do I go about doing this?

Note: NumPy can be used to create the array as well.

There are a lot of answers on SO, but they all provide answers that do not use libraries, and I haven't been able to find anything online to produce this!

@YevhenKuzmovych Just curious how they may help out, I prefer to use them — DialFrost, Aug 12 '22 at 10:00
Does this answer your question? [Extract upper or lower triangular part of a numpy matrix](https://stackoverflow.com/questions/8905501/extract-upper-or-lower-triangular-part-of-a-numpy-matrix) — , Aug 12 '22 at 10:02
@DialFrost Well, you create an array with all ones and "extract" the lower triangular matrix. That is exactly what the proposed answers are doing. — , Aug 12 '22 at 10:11
@Murali Mine is different, I was mainly looking at and pointing out `numpy.tri`, something that the question you provided does not point out — DialFrost, Aug 12 '22 at 10:12

DialFrost · Accepted Answer · 2022-08-12T10:04:55.003

1

Using `numpy.tri`

Syntax:

numpy.tri(N, M=None, k=0, dtype=<class 'float'>, *, like=None)

Basically it creates an array with 1's at and below the given diagonal and 0's elsewhere.

Example:

import numpy as np
np.tri(6, dtype=int)

>>>
array([[1, 0, 0, 0, 0, 0],
       [1, 1, 0, 0, 0, 0],
       [1, 1, 1, 0, 0, 0],
       [1, 1, 1, 1, 0, 0],
       [1, 1, 1, 1, 1, 0],
       [1, 1, 1, 1, 1, 1]])

edited Aug 12 '22 at 10:04

answered Aug 12 '22 at 09:59

DialFrost

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score 1 · Answer 2 · answered Aug 12 '22 at 09:59

1

You can use np.tril:

>>> np.tril(np.ones((6, 6), dtype=int))
array([[1, 0, 0, 0, 0, 0],
       [1, 1, 0, 0, 0, 0],
       [1, 1, 1, 0, 0, 0],
       [1, 1, 1, 1, 0, 0],
       [1, 1, 1, 1, 1, 0],
       [1, 1, 1, 1, 1, 1]])

answered Aug 12 '22 at 09:59

a_guest

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How to make create a triangle of "1"?

2 Answers2

Using numpy.tri

Using `numpy.tri`