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)