/NumPy 1.17

# numpy.ma.nonzero

`numpy.ma.nonzero(self) = <numpy.ma.core._frommethod object>`

Return the indices of unmasked elements that are not zero.

Returns a tuple of arrays, one for each dimension, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values can be obtained with:

```a[a.nonzero()]
```

To group the indices by element, rather than dimension, use instead:

```np.transpose(a.nonzero())
```

The result of this is always a 2d array, with a row for each non-zero element.

Parameters: None `tuple_of_arrays : tuple` Indices of elements that are non-zero.

See also

`numpy.nonzero`
Function operating on ndarrays.
`flatnonzero`
Return indices that are non-zero in the flattened version of the input array.
`ndarray.nonzero`
Equivalent ndarray method.
`count_nonzero`
Counts the number of non-zero elements in the input array.

#### Examples

```>>> import numpy.ma as ma
>>> x = ma.array(np.eye(3))
>>> x
masked_array(
data=[[1., 0., 0.],
[0., 1., 0.],
[0., 0., 1.]],
mask=False,
fill_value=1e+20)
>>> x.nonzero()
(array([0, 1, 2]), array([0, 1, 2]))
```

Masked elements are ignored.

```>>> x[1, 1] = ma.masked
>>> x
masked_array(
data=[[1.0, 0.0, 0.0],
[0.0, --, 0.0],
[0.0, 0.0, 1.0]],
mask=[[False, False, False],
[False,  True, False],
[False, False, False]],
fill_value=1e+20)
>>> x.nonzero()
(array([0, 2]), array([0, 2]))
```

Indices can also be grouped by element.

```>>> np.transpose(x.nonzero())
array([[0, 0],
[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, ma.nonzero(a > 3) yields the indices of the `a` where the condition is true.

```>>> a = ma.array([[1,2,3],[4,5,6],[7,8,9]])
>>> a > 3
masked_array(
data=[[False, False, False],
[ True,  True,  True],
[ True,  True,  True]],
mask=False,
fill_value=True)
>>> ma.nonzero(a > 3)
(array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))
```

The `nonzero` method of the condition array can also be called.

```>>> (a > 3).nonzero()
(array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))
```

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Licensed under the 3-clause BSD License.
https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.ma.nonzero.html