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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. 
 NotesThe 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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 https://numpy.org/doc/1.19/reference/generated/numpy.ma.MaskedArray.reshape.html