:mod:`memote.support.consistency_helpers`
=========================================

.. py:module:: memote.support.consistency_helpers

.. autoapi-nested-parse::

   Helper functions for stoichiometric consistency checks.

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Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   memote.support.consistency_helpers.stoichiometry_matrix
   memote.support.consistency_helpers.nullspace


.. function:: stoichiometry_matrix(metabolites, reactions)

   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.













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.. function:: nullspace(matrix, atol=1e-13, rtol=0.0)

   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:

       **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.








   .. rubric:: 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.

   .. rubric:: References

   Adapted from:
   https://scipy.github.io/old-wiki/pages/Cookbook/RankNullspace.html

   .. only:: latex

      




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