numpy.asarray¶

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

Convert the input to an array.

Parameters:	a : array_like Input data, in any form that can be converted to an array. Thisincludes lists, lists of tuples, tuples, tuples of tuples, tuplesof 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) orcolumn-major (Fortran-style) memory representation.Defaults to ‘C’.
Returns:	out : ndarray Array interpretation ofa. No copy is performed if the inputis already an ndarray with matching dtype and order. Ifa is asubclass of ndarray, a base class ndarray is returned.

See also

asanyarray

Similar function which passes through subclasses.

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.asarray(a)array([1, 2])

Existing arrays are not copied:

>>>a=np.array([1,2])>>>np.asarray(a)isaTrue

Ifdtype 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)isaTrue>>>np.asarray(a,dtype=np.float64)isaFalse

Contrary toasanyarray, ndarray subclasses are not passed through:

>>>issubclass(np.matrix,np.ndarray)True>>>a=np.matrix([[1,2]])>>>np.asarray(a)isaFalse>>>np.asanyarray(a)isaTrue