nonzero(a)
                       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.
When called on a zero-d array or scalar,         nonzero(a)
 is treated as         nonzero(atleast_1d(a))
.
.. deprecated:: 1.17.0
    Use `atleast_1d` explicitly if this behavior is deliberate.
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.
Input array.
Indices of elements that are non-zero.
Return the indices of the elements that are non-zero.
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.
>>> x = np.array([[3, 0, 0], [0, 4, 0], [5, 6, 0]])
... x array([[3, 0, 0], [0, 4, 0], [5, 6, 0]])
>>> np.nonzero(x) (array([0, 1, 2, 2]), array([0, 1, 0, 1]))
>>> x[np.nonzero(x)] array([3, 4, 5, 6])
>>> np.transpose(np.nonzero(x)) array([[0, 0], [1, 1], [2, 0], [2, 1]])
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]])
>>> np.nonzero(a > 3) (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))
Using this result to index a is equivalent to using the mask directly:
>>> a[np.nonzero(a > 3)] array([4, 5, 6, 7, 8, 9])
>>> a[a > 3] # prefer this spelling array([4, 5, 6, 7, 8, 9])
        nonzero
 can also be called as a method of the array.
>>> (a > 3).nonzero() (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.ma.core.where
        numpy.isin
        dask.array.core.Array.nonzero
        numpy.core._multiarray_umath.where
        numpy.count_nonzero
        numpy.where
        numpy.flatnonzero
        numpy.ma.core.MaskedArray.nonzero
        dask.array.routines.nonzero
        numpy.argwhere
        skimage.morphology._flood_fill.flood
        numpy.ma.core.nonzero
        skimage.transform.finite_radon_transform.ifrt2
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