Create a boolean mask from an array.

Return m as a boolean mask, creating a copy if necessary or requested. The function can accept any sequence that is convertible to integers, or nomask. Does not require that contents must be 0s and 1s, values of 0 are interepreted as False, everything else as True.

Parameters: m : array_like Potential mask. copy : bool, optional Whether to return a copy of m (True) or m itself (False). shrink : bool, optional Whether to shrink m to nomask if all its values are False. dtype : dtype, optional Data-type of the output mask. By default, the output mask has a dtype of MaskType (bool). If the dtype is flexible, each field has a boolean dtype. result : ndarray A boolean mask derived from m.

Examples

```>>> import numpy.ma as ma
>>> m = [True, False, True, True]
array([ True, False,  True,  True], dtype=bool)
>>> m = [1, 0, 1, 1]
array([ True, False,  True,  True], dtype=bool)
>>> m = [1, 0, 2, -3]
array([ True, False,  True,  True], dtype=bool)
```

Effect of the shrink parameter.

```>>> m = np.zeros(4)
>>> m
array([ 0.,  0.,  0.,  0.])
False
array([False, False, False, False], dtype=bool)
```

Using a flexible dtype.

```>>> m = [1, 0, 1, 1]
>>> n = [0, 1, 0, 0]
>>> arr = []
>>> for man, mouse in zip(m, n):
...     arr.append((man, mouse))
>>> arr
[(1, 0), (0, 1), (1, 0), (1, 0)]
>>> dtype = np.dtype({'names':['man', 'mouse'],
'formats':[np.int, np.int]})
>>> arr = np.array(arr, dtype=dtype)
>>> arr
array([(1, 0), (0, 1), (1, 0), (1, 0)],
dtype=[('man', '<i4'), ('mouse', '<i4')])