numpy.ma.array
-
numpy.ma.array(data, dtype=None, copy=False, order=None, mask=False, fill_value=None, keep_mask=True, hard_mask=False, shrink=True, subok=True, ndmin=0)
[source] -
An array class with possibly masked values.
Masked values of True exclude the corresponding element from any computation.
Construction:
x = MaskedArray(data, mask=nomask, dtype=None, copy=False, subok=True, ndmin=0, fill_value=None, keep_mask=True, hard_mask=None, shrink=True, order=None)
- Parameters
-
-
dataarray_like
-
Input data.
-
masksequence, optional
-
Mask. Must be convertible to an array of booleans with the same shape as
data
. True indicates a masked (i.e. invalid) data. -
dtypedtype, optional
-
Data type of the output. If
dtype
is None, the type of the data argument (data.dtype
) is used. Ifdtype
is not None and different fromdata.dtype
, a copy is performed. -
copybool, optional
-
Whether to copy the input data (True), or to use a reference instead. Default is False.
-
subokbool, optional
-
Whether to return a subclass of
MaskedArray
if possible (True) or a plainMaskedArray
. Default is True. -
ndminint, optional
-
Minimum number of dimensions. Default is 0.
-
fill_valuescalar, optional
-
Value used to fill in the masked values when necessary. If None, a default based on the data-type is used.
-
keep_maskbool, optional
-
Whether to combine
mask
with the mask of the input data, if any (True), or to use onlymask
for the output (False). Default is True. -
hard_maskbool, optional
-
Whether to use a hard mask or not. With a hard mask, masked values cannot be unmasked. Default is False.
-
shrinkbool, optional
-
Whether to force compression of an empty mask. Default is True.
-
order{‘C’, ‘F’, ‘A’}, optional
-
Specify the order of the array. If order is ‘C’, then the array will be in C-contiguous order (last-index varies the fastest). If order is ‘F’, then the returned array will be in Fortran-contiguous order (first-index varies the fastest). If order is ‘A’ (default), then the returned array may be in any order (either C-, Fortran-contiguous, or even discontiguous), unless a copy is required, in which case it will be C-contiguous.
-
© 2005–2020 NumPy Developers
Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.18/reference/generated/numpy.ma.array.html