W3cubDocs

sklearn.utils.validation.check_symmetric

sklearn.utils.validation.check_symmetric(array, tol=1e-10, raise_warning=True, raise_exception=False) [source]

Make sure that array is 2D, square and symmetric.

If the array is not symmetric, then a symmetrized version is returned. Optionally, a warning or exception is raised if the matrix is not symmetric.

Parameters:

Parameters:	`array : nd-array or sparse matrix` Input object to check / convert. Must be two-dimensional and square, otherwise a ValueError will be raised. `tol : float` Absolute tolerance for equivalence of arrays. Default = 1E-10. `raise_warning : boolean (default=True)` If True then raise a warning if conversion is required. `raise_exception : boolean (default=False)` If True then raise an exception if array is not symmetric.
Returns:	`array_sym : ndarray or sparse matrix` Symmetrized version of the input array, i.e. the average of array and array.transpose(). If sparse, then duplicate entries are first summed and zeros are eliminated.

array : nd-array or sparse matrix: Input object to check / convert. Must be two-dimensional and square, otherwise a ValueError will be raised.
tol : float: Absolute tolerance for equivalence of arrays. Default = 1E-10.
raise_warning : boolean (default=True): If True then raise a warning if conversion is required.
raise_exception : boolean (default=False): If True then raise an exception if array is not symmetric.

Returns:

array_sym : ndarray or sparse matrix: Symmetrized version of the input array, i.e. the average of array and array.transpose(). If sparse, then duplicate entries are first summed and zeros are eliminated.