numpy.asarray#
- numpy.asarray(a, dtype=None, order=None, *, device=None, copy=None, like=None)#
Convert the input to an array.
- Parameters:
- aarray_like
Input data, in any form that can be converted to an array. This includes 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’, ‘A’, ‘K’}, optional
Memory layout. ‘A’ and ‘K’ depend on the order of input array a. ‘C’ row-major (C-style), ‘F’ column-major (Fortran-style) memory representation. ‘A’ (any) means ‘F’ if a is Fortran contiguous, ‘C’ otherwise ‘K’ (keep) preserve input order Defaults to ‘K’.
- devicestr, optional
The device on which to place the created array. Default: None. For Array-API interoperability only, so must be
"cpu"
if passed.New in version 2.0.0.
- copybool, optional
If
True
, then the object is copied. IfNone
then the object is copied only if needed, i.e. if__array__
returns a copy, if obj is a nested sequence, or if a copy is needed to satisfy any of the other requirements (dtype
,order
, etc.). ForFalse
it raises aValueError
if a copy cannot be avoided. Default:None
.New in version 2.0.0.
- likearray_like, optional
Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as
like
supports the__array_function__
protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.New in version 1.20.0.
- Returns:
- outndarray
Array interpretation of
a
. No copy is performed if the input is already an ndarray with matching dtype and order. Ifa
is a subclass of ndarray, a base class ndarray is returned.
See also
asanyarray
Similar function which passes through subclasses.
ascontiguousarray
Convert input to a contiguous array.
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.asarray(a) array([1, 2])
Existing arrays are not copied:
>>> a = np.array([1, 2]) >>> np.asarray(a) is a True
If
dtype
is set, array is copied only if dtype does not match:>>> a = np.array([1, 2], dtype=np.float32) >>> np.shares_memory(np.asarray(a, dtype=np.float32), a) True >>> np.shares_memory(np.asarray(a, dtype=np.float64), a) False
Contrary to
asanyarray
, ndarray subclasses are not passed through:>>> issubclass(np.recarray, np.ndarray) True >>> a = np.array([(1., 2), (3., 4)], dtype='f4,i4').view(np.recarray) >>> np.asarray(a) is a False >>> np.asanyarray(a) is a True