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
- shapeint 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_arrayarray
- 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) 
