numpy.ma.resize

numpy.ma.resize(x, new_shape)

Return a new masked array with the specified size and shape.

This is the masked equivalent of the numpy.resize function. The new array is filled with repeated copies of x (in the order that the data are stored in memory). If x is masked, the new array will be masked, and the new mask will be a repetition of the old one.

See also

numpy.resize

Equivalent function in the top level NumPy module.

Examples

>>> import numpy.ma as ma
>>> a = ma.array([[1, 2] ,[3, 4]])
>>> a[0, 1] = ma.masked
>>> a
masked_array(data =
 [[1 --]
 [3 4]],
             mask =
 [[False  True]
 [False False]],
       fill_value = 999999)
>>> np.resize(a, (3, 3))
array([[1, 2, 3],
       [4, 1, 2],
       [3, 4, 1]])
>>> ma.resize(a, (3, 3))
masked_array(data =
 [[1 -- 3]
 [4 1 --]
 [3 4 1]],
             mask =
 [[False  True False]
 [False False  True]
 [False False False]],
       fill_value = 999999)

A MaskedArray is always returned, regardless of the input type.

>>> a = np.array([[1, 2] ,[3, 4]])
>>> ma.resize(a, (3, 3))
masked_array(data =
 [[1 2 3]
 [4 1 2]
 [3 4 1]],
             mask =
 False,
       fill_value = 999999)