Notes

For square empty arrays the result is returned True by convention. Complex valued arrays are tested for symmetricity and not for being Hermitian (see examples)

The diagonal of the array is not scanned. Thus if there are infs, NaNs or similar problematic entries on the diagonal, they will be ignored. However, :None:None:`numpy.inf` will be treated as a number, that is to say [[1, inf], [inf, 2]] will return True . On the other hand :None:None:`numpy.NaN` is never symmetric, say, [[1, nan], [nan, 2]] will return False .

When atol and/or rtol are set to , then the comparison is performed by numpy.allclose and the tolerance values are passed to it. Otherwise an exact comparison against zero is performed by internal functions. Hence performance can improve or degrade depending on the size and dtype of the array. If one of atol or rtol given the other one is automatically set to zero.

Parameters

a : ndarray

Input array of size (N, N).

atol : float, optional

Absolute error bound

rtol : float, optional

Relative error bound

Raises

TypeError

If the dtype of the array is not supported, in particular, NumPy float16, float128 and complex256 dtypes for exact comparisons.

Returns

sym : bool

Returns True if the array symmetric.

issymmetric(a, atol=None, rtol=None) Check if a square 2D array is symmetric.

See Also

ishermitian

Check if a square 2D array is Hermitian

Examples

>>> from scipy.linalg import issymmetric
>>> A = np.arange(9).reshape(3, 3)
>>> A = A + A.T
>>> issymmetric(A)
True
>>> Ac = np.array([[1. + 1.j, 3.j], [3.j, 2.]])
>>> issymmetric(Ac)  # not Hermitian but symmetric
True

See :

Back References

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

scipy.linalg._cythonized_array_utils.ishermitian

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

---

GitHub : None#None
type: <class 'builtin_function_or_method'>
Commit: