numpy.ma.asarray#

ma.asarray(a, dtype=None, order=None)[source]#

Convert the input to a masked array of the given data-type.

No copy is performed if the input is already an ndarray. If a is a subclass of MaskedArray, a base class MaskedArray is returned.

Parameters:

aarray_like: Input data, in any form that can be converted to a masked array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists, ndarrays and masked arrays.
dtypedtype, optional: By default, the data-type is inferred from the input data.
order{‘C’, ‘F’}, optional: Whether to use row-major (‘C’) or column-major (‘FORTRAN’) memory representation. Default is ‘C’.

Returns:

outMaskedArray: Masked array interpretation of a.

See also

asanyarray: Similar to asarray, but conserves subclasses.

Examples

>>> import numpy as np
>>> x = np.arange(10.).reshape(2, 5)
>>> x
array([[0., 1., 2., 3., 4.],
       [5., 6., 7., 8., 9.]])
>>> np.ma.asarray(x)
masked_array(
  data=[[0., 1., 2., 3., 4.],
        [5., 6., 7., 8., 9.]],
  mask=False,
  fill_value=1e+20)
>>> type(np.ma.asarray(x))
<class 'numpy.ma.MaskedArray'>