def asanyarray(a, dtype=None):
"""
Convert the input to a masked array, conserving subclasses.
If `a` is a subclass of `MaskedArray`, its class is conserved.
No copy is performed if the input is already an `ndarray`.
Parameters
----------
a : array_like
Input data, in any form that can be converted to an array.
dtype : dtype, optional
By default, the data-type is inferred from the input data.
order : {'C', 'F'}, optional
Whether to use row-major ('C') or column-major ('FORTRAN') memory
representation. Default is 'C'.
Returns
-------
out : MaskedArray
MaskedArray interpretation of `a`.
See Also
--------
asarray : Similar to `asanyarray`, but does not conserve subclass.
Examples
--------
>>> x = np.arange(10.).reshape(2, 5)
>>> x
array([[ 0., 1., 2., 3., 4.],
[ 5., 6., 7., 8., 9.]])
>>> np.ma.asanyarray(x)
masked_array(data =
[[ 0. 1. 2. 3. 4.]
[ 5. 6. 7. 8. 9.]],
mask =
False,
fill_value = 1e+20)
>>> type(np.ma.asanyarray(x))
<class 'numpy.ma.core.MaskedArray'>
"""
return masked_array(a, dtype=dtype, copy=False, keep_mask=True, subok=True)
##############################################################################
# Pickling #
##############################################################################
评论列表
文章目录