numpy.ma.masked_array.reshape
method
- 
masked_array.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.
 
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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 = sExamples
>>> 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) 
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Licensed under the 3-clause BSD License.
    https://numpy.org/doc/1.18/reference/generated/numpy.ma.masked_array.reshape.html