eye(N, M=None, k=0, dtype=<class 'float'>, order='C', *, like=None)

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.

versionadded

like : array_like

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.

versionadded

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.

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

See Also

diag

diagonal 2-D array from a 1-D array specified by the user.

identity

(almost) equivalent function

Examples

>>> np.eye(2, dtype=int)
array([[1, 0],
       [0, 1]])

>>> np.eye(3, k=1)
array([[0.,  1.,  0.],
       [0.,  0.,  1.],
       [0.,  0.,  0.]])

See :

Back References

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scipy.linalg._decomp_update.qr_insert dask.array.reductions.trace dask.array.ufunc.conjugate scipy.linalg._solvers.solve_continuous_lyapunov dask.array.ufunc.logical_xor scipy.linalg._decomp_lu.lu_factor scipy.sparse.linalg._eigen.arpack.arpack.eigsh dask.array.ufunc.fmin dask.array.ufunc.minimum dask.array.ufunc.fmax scipy.signal._bsplines.spline_filter scipy.linalg._solvers.solve_discrete_lyapunov dask.array.routines.shape scipy.fft._basic.ifftn scipy.optimize._qap.quadratic_assignment scipy.fft._basic.ifft2 scipy.linalg._decomp_update.qr_delete scipy.linalg._decomp_update.qr_update dask.array.routines.count_nonzero scipy.sparse.linalg._eigen.arpack.arpack.eigs scipy.linalg._decomp_qr.qr_multiply dask.array.ufunc.maximum

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GitHub : /numpy/lib/twodim_base.py#161
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