Function reshape

numpy/ma/core.py:7647–7694

Returns an array containing the same data with a new shape. Refer to `MaskedArray.reshape` for full documentation. See Also -------- MaskedArray.reshape : equivalent function Examples -------- Reshaping a 1-D array: >>> a = np.ma.array([1, 2, 3, 4]) >>> n

(a, new_shape, order='C')

def reshape(a, new_shape, order='C'):
    """
    Returns an array containing the same data with a new shape.

    Refer to `MaskedArray.reshape` for full documentation.

    See Also
    --------
    MaskedArray.reshape : equivalent function

    Examples
    --------
    Reshaping a 1-D array:

    >>> a = np.ma.array([1, 2, 3, 4])
    >>> np.ma.reshape(a, (2, 2))
    masked_array(
      data=[[1, 2],
            [3, 4]],
      mask=False,
      fill_value=999999)

    Reshaping a 2-D array:

    >>> b = np.ma.array([[1, 2], [3, 4]])
    >>> np.ma.reshape(b, (1, 4))
    masked_array(data=[[1, 2, 3, 4]],
                 mask=False,
           fill_value=999999)

    Reshaping a 1-D array with a mask:

    >>> c = np.ma.array([1, 2, 3, 4], mask=[False, True, False, False])
    >>> np.ma.reshape(c, (2, 2))
    masked_array(
      data=[[1, --],
            [3, 4]],
      mask=[[False,  True],
            [False, False]],
      fill_value=999999)

    """
    # We can't use 'frommethod', it whine about some parameters. Dmmit.
    try:
        return a.reshape(new_shape, order=order)
    except AttributeError:
        _tmp = np.asarray(a).reshape(new_shape, order=order)
        return _tmp.view(MaskedArray)


def resize(x, new_shape):