numpy.nonzero — NumPy v1.11 Manual (original) (raw)
Return the indices of the elements that are non-zero.
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. The corresponding non-zero values can be obtained with:
To group the indices by element, rather than dimension, use:
The result of this is always a 2-D array, with 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. |
See also
Return indices that are non-zero in the flattened version of the input array.
Equivalent ndarray method.
Counts the number of non-zero elements in the input array.
Examples
x = np.eye(3) x array([[ 1., 0., 0.], [ 0., 1., 0.], [ 0., 0., 1.]]) np.nonzero(x) (array([0, 1, 2]), array([0, 1, 2]))
x[np.nonzero(x)] array([ 1., 1., 1.]) np.transpose(np.nonzero(x)) array([[0, 0], [1, 1], [2, 2]])
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 array([[False, False, False], [ True, True, True], [ True, True, True]], dtype=bool) np.nonzero(a > 3) (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))
The nonzero method of the boolean array can also be called.
(a > 3).nonzero() (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))