asarray(a, dtype=None, order=None, *, like=None)
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.
By default, the data-type is inferred from the input data.
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'.
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.
Array interpretation of a
. No copy is performed if the input is already an ndarray with matching dtype and order. If a
is a subclass of ndarray, a base class ndarray is returned.
Convert the input to an array.
asanyarray
Similar function which passes through subclasses.
asarray_chkfinite
Similar function which checks input for NaNs and Infs.
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.
fromfunction
Construct an array by executing a function on grid positions.
fromiter
Create an array from an iterator.
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.asarray(a, dtype=np.float32) is a True
>>> np.asarray(a, dtype=np.float64) is a False
Contrary to asanyarray
, ndarray subclasses are not passed through:
>>> issubclass(np.recarray, np.ndarray) True
>>> a = np.array([(1.0, 2), (3.0, 4)], dtype='f4,i4').view(np.recarray)
... np.asarray(a) is a False
>>> np.asanyarray(a) is a TrueSee :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.spatial._kdtree.KDTree.query_ball_point
scipy.optimize._optimize.fmin_cg
pandas.core.series.Series.__array__
numpy.asarray_chkfinite
scipy.spatial.transform._rotation.Rotation
pandas.core.dtypes.cast.infer_dtype_from_array
numpy.ma.core.asanyarray
numpy.require
scipy.signal._ltisys.dlsim
numpy.asanyarray
dask.array.chunk_types.register_chunk_type
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