diag(v)

This docstring was copied from numpy.diag.

Some inconsistencies with the Dask version may exist.

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 (Not supported in Dask)

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

This example is valid syntax, but we were not able to check execution

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

This example is valid syntax, but we were not able to check execution

>>> np.diag(x)  # doctest: +SKIP
array([0, 4, 8])

This example is valid syntax, but we were not able to check execution

>>> np.diag(x, k=1)  # doctest: +SKIP
array([1, 5])

This example is valid syntax, but we were not able to check execution

>>> np.diag(x, k=-1)  # doctest: +SKIP
array([3, 7])

This example is valid syntax, but we were not able to check execution

>>> np.diag(np.diag(x))  # doctest: +SKIP
array([[0, 0, 0],
       [0, 4, 0],
       [0, 0, 8]])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.reductions.trace dask.array.routines.select dask.array.creation.diagonal dask.array.routines.compress

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