Function asarray

numpy/ma/core.py:8626–8673

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 ---------- a : array_like Input data, in any form that c

(a, dtype=None, order=None)

def asarray(a, dtype=None, order=None):
    """
    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
    ----------
    a : array_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.
    dtype : dtype, 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
    -------
    out : MaskedArray
        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'>

    """
    order = order or 'C'
    return masked_array(a, dtype=dtype, copy=False, keep_mask=True,
                        subok=False, order=order)


def asanyarray(a, dtype=None, order=None):