Document

reshape(self, *s, **kwargs)

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.

Notes

The reshaping operation cannot guarantee that a copy will not be made, to modify the shape in place, use a.shape = s

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.

Give a new shape to the array without changing its data.

Examples

This example is valid syntax, but we were not able to check execution

>>> 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)

This example is valid syntax, but we were not able to check execution

>>> x = x.reshape((4,1))
... x
masked_array(
  data=[[--],
        [2],
        [3],
        [--]],
  mask=[[ True],
        [False],
        [False],
        [ True]],
  fill_value=999999)

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.ma.core.reshape

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