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

By default, the reshaping operation will make a copy if a view with different strides is not possible. To ensure a view, pass copy=False.

Examples

>>> 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)