xorbits.numpy.identity(n, dtype=None, sparse=False, gpu=None, chunk_size=None)[source]#

Return the identity array.

The identity array is a square array with ones on the main diagonal.

  • n (int) – Number of rows (and columns) in n x n output.

  • dtype (data-type, optional) – Data-type of the output. Defaults to float.

  • like (array_like, optional (Not supported yet)) –

    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(numpy).


outn x n array with its main diagonal set to one, and all other elements 0.

Return type



>>> np.identity(3)  
array([[1.,  0.,  0.],
       [0.,  1.,  0.],
       [0.,  0.,  1.]])
sparse: bool, optional

Create sparse tensor if True, False as default

gpubool, optional

Allocate the tensor on GPU if True, False as default

This docstring was copied from numpy.