diag(v, k=0)

See the more detailed documentation for numpy.diagonal if you use this function to extract a diagonal and wish to write to the resulting array; whether it returns a copy or a view depends on what version of numpy you are using.

Parameters

v : array_like

If v is a 2-D array, return a copy of its k-th diagonal. If v is a 1-D array, return a 2-D array with v on the k-th diagonal.

k : int, optional

Diagonal in question. The default is 0. Use :None:None:`k>0` for diagonals above the main diagonal, and :None:None:`k<0` for diagonals below the main diagonal.

Returns

out : ndarray

The extracted diagonal or constructed diagonal array.

Extract a diagonal or construct a diagonal array.

See Also

diagflat

Create a 2-D array with the flattened input as a diagonal.

diagonal

Return specified diagonals.

trace

Sum along diagonals.

tril

Lower triangle of an array.

triu

Upper triangle of an array.

Examples

>>> x = np.arange(9).reshape((3,3))
... x
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])

>>> np.diag(x)
array([0, 4, 8])

>>> np.diag(x, k=1)
array([1, 5])

>>> np.diag(x, k=-1)
array([3, 7])

>>> np.diag(np.diag(x))
array([[0, 0, 0],
       [0, 4, 0],
       [0, 0, 8]])

See :

Back References

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dask.array.routines.fliplr dask.array.routines.flipud numpy.ma.extras.diagflat scipy.linalg._decomp_qr.qr scipy.optimize._optimize.fmin_bfgs numpy.compress numpy.diagonal numpy.diagflat scipy.linalg._decomp_svd.svd numpy.select scipy.linalg._decomp_cholesky.cholesky_banded dask.array.routines.apply_along_axis dask.array.creation.diag scipy.linalg._decomp.eig_banded scipy.sparse.linalg._eigen._svds.svds scipy.sparse._construct.diags scipy.linalg._decomp_cholesky.cho_solve_banded dask.array.einsumfuncs.einsum numpy.trace numpy.eye numpy.ma.core.diag scipy.linalg._decomp.eigh

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