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bundles / numpy 2.4.4 / numpy / nonzero

_ArrayFunctionDispatcher

numpy:nonzero

source: /numpy/_core/fromnumeric.py :1993

Signature

def   nonzero ( a )

Summary

Return the indices of the elements that are non-zero.

Extended Summary

Returns a tuple of arrays, one for each dimension of a, containing the indices of the non-zero elements in that dimension. The values in a are always tested and returned in row-major, C-style order.

To group the indices by element, rather than dimension, use argwhere, which returns a row for each non-zero element.

Parameters

a : array_like

Input array.

Returns

tuple_of_arrays : tuple

Indices of elements that are non-zero.

Notes

While the nonzero values can be obtained with a[nonzero(a)], it is recommended to use x[x.astype(bool)] or x[x != 0] instead, which will correctly handle 0-d arrays.

Examples

import numpy as np
x = np.array([[3, 0, 0], [0, 4, 0], [5, 6, 0]])
x
np.nonzero(x)
✓
x[np.nonzero(x)]
np.transpose(np.nonzero(x))
✓
A common use for ``nonzero`` is to find the indices of an array, where a condition is True. Given an array `a`, the condition `a` > 3 is a boolean array and since False is interpreted as 0, np.nonzero(a > 3) yields the indices of the `a` where the condition is true. 
a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
a > 3
np.nonzero(a > 3)
✓
Using this result to index `a` is equivalent to using the mask directly: 
a[np.nonzero(a > 3)]
a[a > 3]  # prefer this spelling
✓
``nonzero`` can also be called as a method of the array. 
(a > 3).nonzero()
✓

See also

count_nonzero

Counts the number of non-zero elements in the input array.

flatnonzero

Return indices that are non-zero in the flattened version of the input array.

ndarray.nonzero

Equivalent ndarray method.

Aliases

  • numpy.nonzero

Referenced by

This package

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