# numpy.ma.resize¶

ma.resize(x, new_shape)[source]

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))
masked_array(
data=[[1, 2, 3],
[4, 1, 2],
[3, 4, 1]],
mask=False,
fill_value=999999)
>>> 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)
```