numpy.ma.masked_all#
- ma.masked_all(shape, dtype=<class 'float'>)[source]#
Empty masked array with all elements masked.
Return an empty masked array of the given shape and dtype, where all the data are masked.
- Parameters:
- shapeint or tuple of ints
Shape of the required MaskedArray, e.g.,
(2, 3)
or2
.- dtypedtype, optional
Data type of the output.
- Returns:
- aMaskedArray
A masked array with all data masked.
See also
masked_all_like
Empty masked array modelled on an existing array.
Notes
Unlike other masked array creation functions (e.g.
numpy.ma.zeros
,numpy.ma.ones
, numpy.ma.full),masked_all
does not initialize the values of the array, and may therefore be marginally faster. However, the values stored in the newly allocated array are arbitrary. For reproducible behavior, be sure to set each element of the array before reading.Examples
>>> np.ma.masked_all((3, 3)) masked_array( data=[[--, --, --], [--, --, --], [--, --, --]], mask=[[ True, True, True], [ True, True, True], [ True, True, True]], fill_value=1e+20, dtype=float64)
The
dtype
parameter defines the underlying data type.>>> a = np.ma.masked_all((3, 3)) >>> a.dtype dtype('float64') >>> a = np.ma.masked_all((3, 3), dtype=np.int32) >>> a.dtype dtype('int32')