numpy.ma.MaskedArray.reshape

method

ma.MaskedArray.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:

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

Try it in your browser!

>>> import numpy as np
>>> 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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