numpy.ma.masked_array.reshape¶
-
masked_array.
reshape
(*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]) >>> print(x) [[-- 2] [3 --]] >>> x = x.reshape((4,1)) >>> print(x) [[--] [2] [3] [--]]