flopscope.

flopscope.numpy.eye

fnp.eye(N, M=None, k=0, dtype=<class 'float'>, order='C', *, device=None, like=None)[flopscope source][numpy source]

Return a 2-D array with ones on the diagonal and zeros elsewhere.

Adapted from NumPy docs np.eye

Areacore
Typefree
NumPy Refnp.eye
Cost
0
Flopscope Context

Create identity matrix.

Parameters

N:int

Number of rows in the output.

M:int, optional

Number of columns in the output. If None, defaults to N.

k:int, optional

Index of the diagonal: 0 (the default) refers to the main diagonal, a positive value refers to an upper diagonal, and a negative value to a lower diagonal.

dtype:data-type, optional

Data-type of the returned array.

order:{'C', 'F'}, optional

Whether the output should be stored in row-major (C-style) or column-major (Fortran-style) order in memory.

device:str, optional

The device on which to place the created array. Default: None. For Array-API interoperability only, so must be "cpu" if passed.

Added in version 2.0.0.
like:array_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.

Added in version 1.20.0.

Returns

I:ndarray of shape (N,M)

An array where all elements are equal to zero, except for the k-th diagonal, whose values are equal to one.

See also

Examples

>>> import flopscope.numpy as fnp
>>> flops.eye(2, dtype=int)
array([[1, 0],
       [0, 1]])
>>> flops.eye(3, k=1)
array([[0.,  1.,  0.],
       [0.,  0.,  1.],
       [0.,  0.,  0.]])