numpy.asanyarray — NumPy v1.15 Manual (original) (raw)
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-style) or column-major (Fortran-style) memory representation. Defaults to ‘C’. |
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| 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
Similar function which always returns ndarrays.
Convert input to a contiguous array.
Convert input to a floating point ndarray.
Convert input to an ndarray with column-major memory order.
Similar function which checks input for NaNs and Infs.
Create an array from an iterator.
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.array([(1.0, 2), (3.0, 4)], dtype='f4,i4').view(np.recarray) np.asanyarray(a) is a True