Function asanyarray

numpy/ma/core.py:8253–8299

Convert the input to a masked array, conserving subclasses. If `a` is a subclass of `MaskedArray`, its class is conserved. No copy is performed if the input is already an `ndarray`. Parameters ---------- a : array_like Input data, in any form that can be converted

(a, dtype=None)

def asanyarray(a, dtype=None):
    """
    Convert the input to a masked array, conserving subclasses.

    If `a` is a subclass of `MaskedArray`, its class is conserved.
    No copy is performed if the input is already an `ndarray`.

    Parameters
    ----------
    a : array_like
        Input data, in any form that can be converted to an array.
    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
        MaskedArray interpretation of `a`.

    See Also
    --------
    asarray : Similar to `asanyarray`, but does not conserve subclass.

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

    """
    # workaround for #8666, to preserve identity. Ideally the bottom line
    # would handle this for us.
    if isinstance(a, MaskedArray) and (dtype is None or dtype == a.dtype):
        return a
    return masked_array(a, dtype=dtype, copy=False, keep_mask=True, subok=True)


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