numpy.asarray()

numpy.asarray(a, dtype=None, order=None) [source]

Convert the input to an array.

Parameters:

Parameters:	a : array_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. 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?.
Returns:	out : ndarray Array interpretation of `a`. No copy is performed if the input is already an ndarray. If `a` is a subclass of ndarray, a base class ndarray is returned.

a : array_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.

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?.

Returns:

out : ndarray

Array interpretation of a. No copy is performed if the input is already an ndarray. If a is a subclass of ndarray, a base class ndarray is returned.

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.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.matrix, np.ndarray)
True
>>> a = np.matrix([[1, 2]])
>>> np.asarray(a) is a
False
>>> np.asanyarray(a) is a
True

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.asarray.html

doc_NumPy

2017-01-10 18:12:51

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