numpy.asanyarray¶
- numpy.asanyarray(a, dtype=None, order=None)[source]¶
Convert the input to an ndarray, but pass ndarray subclasses through.
Parameters: a : array_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.
dtype : data-type, 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 (‘F’) memory representation. Defaults to ‘C’.
Returns: out : ndarray or an ndarray subclass
Array interpretation of a. If a is 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 ndarray subclasses are passed through as-is:
>>> a = np.matrix([1, 2]) >>> np.asanyarray(a) is a True