2.1.1.3.1.2. enkie.estimators.equilibrator_gibbs_estimator

Estimation of Gibbs free energies using eQuilibrator.

2.1.1.3.1.2.1. Module Contents

class enkie.estimators.equilibrator_gibbs_estimator.EquilibratorGibbsEstimator(rmse_inf: enkie.commons.Q = DEFAULT_RMSE)[source]

Bases: enkie.estimators.gibbs_estimator_interface.GibbsEstimatorInterface

Estimation of Gibbs free energies using equilibrator_api.

Parameters:

rmse_inf (Q, optional) – Uncertainty to use for unknown groups or compounds.

property eq_api[source]

Gets the equilibrator API object.

property rmse_inf[source]

Gets the uncertainty used for unknown compounds or groups.

property incorrect_metabolites: List[str][source]

Gets the list of metabolites that are not correctly recognized by equilibrator.

get_dfg0_prime(S: numpy.array, metabolites: List[enkie.miriam_metabolite.MiriamMetabolite], parameters: enkie.compartment_parameters.CompartmentParameters) → Tuple[enkie.commons.Q, enkie.commons.Q][source]

Estimates the standard Gibbs free energies for a reaction network using equilibrator-api.

Parameters:

  • S (np.array) – n-by-m stoichiometric matrix of the reaction network.

  • metabolites (List[Metabolite]) – A m-elements list describing the compounds in the network.

  • compartment_parameters (CompartmentParameters) – The prior for the physiological parameters of each compartment, such as pH and ionic strength.

Returns:

A tuple, whose first element is the vector of the mean estimate, and the second is a square root \(Q\) of the covariance matrix on the estimation uncertainty \(\Sigma\), such that \(QQ^\intercal = \Sigma\).

Return type:

Tuple[Q, Q]