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numpy.asanyarray
numpy.asanyarray(a, dtype=None, order=None)[source]-
Convert the input to an ndarray, but pass ndarray subclasses through.
- Parameters
-
aarray_like-
Input data, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays.
dtypedata-type, optional-
By default, the data-type is inferred from the input data.
order{‘C’, ‘F’}, optional-
Whether to use row-major (C-style) or column-major (Fortran-style) memory representation. Defaults to ‘C’.
- Returns
-
outndarray or an ndarray subclass-
Array interpretation of
a. Ifais an ndarray or a subclass of ndarray, it is returned as-is and no copy is performed.
See also
asarray-
Similar function which always returns ndarrays.
ascontiguousarray-
Convert input to a contiguous array.
asfarray-
Convert input to a floating point ndarray.
asfortranarray-
Convert input to an ndarray with column-major memory order.
asarray_chkfinite-
Similar function which checks input for NaNs and Infs.
fromiter-
Create an array from an iterator.
fromfunction-
Construct an array by executing a function on grid positions.
Examples
Convert a list into an array:
>>> a = [1, 2] >>> np.asanyarray(a) array([1, 2])Instances of
ndarraysubclasses are passed through as-is:>>> a = np.array([(1.0, 2), (3.0, 4)], dtype='f4,i4').view(np.recarray) >>> np.asanyarray(a) is a True
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https://numpy.org/doc/1.19/reference/generated/numpy.asanyarray.html