numpy.ma.MaskedArray.reshape¶
method
-
MaskedArray.
reshape
(self, *s, **kwargs)[source]¶ Give a new shape to the array without changing its data.
Returns a masked array containing the same data, but with a new shape. The result is a view on the original array; if this is not possible, a ValueError is raised.
Parameters: - shape : int or tuple of ints
The new shape should be compatible with the original shape. If an integer is supplied, then the result will be a 1-D array of that length.
- order : {‘C’, ‘F’}, optional
Determines whether the array data should be viewed as in C (row-major) or FORTRAN (column-major) order.
Returns: - reshaped_array : array
A new view on the array.
See also
reshape
- Equivalent function in the masked array module.
numpy.ndarray.reshape
- Equivalent method on ndarray object.
numpy.reshape
- Equivalent function in the NumPy module.
Notes
The reshaping operation cannot guarantee that a copy will not be made, to modify the shape in place, use
a.shape = s
Examples
>>> x = np.ma.array([[1,2],[3,4]], mask=[1,0,0,1]) >>> x masked_array( data=[[--, 2], [3, --]], mask=[[ True, False], [False, True]], fill_value=999999) >>> x = x.reshape((4,1)) >>> x masked_array( data=[[--], [2], [3], [--]], mask=[[ True], [False], [False], [ True]], fill_value=999999)