Function filled

numpy/ma/core.py:631–690

Return input as an `~numpy.ndarray`, with masked values replaced by `fill_value`. If `a` is not a `MaskedArray`, `a` itself is returned. If `a` is a `MaskedArray` with no masked values, then ``a.data`` is returned. If `a` is a `MaskedArray` and `fill_value` is None, `fill_v

(a, fill_value=None)

def filled(a, fill_value=None):
    """
    Return input as an `~numpy.ndarray`, with masked values replaced by
    `fill_value`.

    If `a` is not a `MaskedArray`, `a` itself is returned.
    If `a` is a `MaskedArray` with no masked values, then ``a.data`` is
    returned.
    If `a` is a `MaskedArray` and `fill_value` is None, `fill_value` is set to
    ``a.fill_value``.

    Parameters
    ----------
    a : MaskedArray or array_like
        An input object.
    fill_value : array_like, optional.
        Can be scalar or non-scalar. If non-scalar, the
        resulting filled array should be broadcastable
        over input array. Default is None.

    Returns
    -------
    a : ndarray
        The filled array.

    See Also
    --------
    compressed

    Examples
    --------
    >>> import numpy as np
    >>> import numpy.ma as ma
    >>> x = ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0],
    ...                                                [1, 0, 0],
    ...                                                [0, 0, 0]])
    >>> x.filled()
    array([[999999,      1,      2],
           [999999,      4,      5],
           [     6,      7,      8]])
    >>> x.filled(fill_value=333)
    array([[333,   1,   2],
           [333,   4,   5],
           [  6,   7,   8]])
    >>> x.filled(fill_value=np.arange(3))
    array([[0, 1, 2],
           [0, 4, 5],
           [6, 7, 8]])

    """
    if hasattr(a, 'filled'):
        return a.filled(fill_value)

    elif isinstance(a, ndarray):
        # Should we check for contiguity ? and a.flags['CONTIGUOUS']:
        return a
    elif isinstance(a, dict):
        return np.array(a, 'O')