`memote.support.consistency_helpers`¶

Helper functions for stoichiometric consistency checks.

Module Contents¶

`stoichiometry_matrix`(metabolites, reactions)	Return the stoichiometry matrix representation of a set of reactions.
`nullspace`(matrix, atol=1e-13, rtol=0.0)	Compute an approximate basis for the null space (kernel) of a matrix.

memote.support.consistency_helpers.stoichiometry_matrix(metabolites, reactions)[source]¶

Return the stoichiometry matrix representation of a set of reactions.

The reactions and metabolites order is respected. All metabolites are expected to be contained and complete in terms of the reactions.

Parameters:	reactions : iterable A somehow ordered list of unique reactions. metabolites : iterable A somehow ordered list of unique metabolites.
Returns:	numpy.array The 2D array that represents the stoichiometry matrix. dict A dictionary mapping metabolites to row indexes. dict A dictionary mapping reactions to column indexes.

memote.support.consistency_helpers.nullspace(matrix, atol=1e-13, rtol=0.0)[source]¶

Compute an approximate basis for the null space (kernel) of a matrix.

The algorithm used by this function is based on the singular value decomposition of the given matrix.

Parameters:

Parameters:	matrix : ndarray The matrix should be at most 2-D. A 1-D array with length k will be treated as a 2-D with shape (1, k) atol : float The absolute tolerance for a zero singular value. Singular values smaller than `atol` are considered to be zero. rtol : float The relative tolerance for a zero singular value. Singular values less than the relative tolerance times the largest singular value are considered to be zero.
Returns:	ndarray If `matrix` is an array with shape (m, k), then the returned nullspace will be an array with shape `(k, n)`, where n is the estimated dimension of the nullspace.

matrix : ndarray: The matrix should be at most 2-D. A 1-D array with length k will be treated as a 2-D with shape (1, k)
atol : float: The absolute tolerance for a zero singular value. Singular values smaller than atol are considered to be zero.
rtol : float: The relative tolerance for a zero singular value. Singular values less than the relative tolerance times the largest singular value are considered to be zero.

Returns:

ndarray: If matrix is an array with shape (m, k), then the returned nullspace will be an array with shape (k, n), where n is the estimated dimension of the nullspace.

Notes

If both atol and rtol are positive, the combined tolerance is the maximum of the two; that is:

tol = max(atol, rtol * smax)

Singular values smaller than tol are considered to be zero.

References