dfba.model

Definition of DfbaModel class.

Module Contents

Classes

DfbaModel(cobra_object: Model) Class representation for a dynamic FBA model.
dfba.model.logger[source]
class dfba.model.DfbaModel(cobra_object: Model)[source]

Bases: cobra.Object

Class representation for a dynamic FBA model.

Parameters:cobra_object (cobra.Model) – Existing cobra.Model object representing FBA model.
cobra_model[source]

Existing cobra.Model object containing FBA model (reactions, metabolites, objective).

Type:cobra.Model
reactions[source]

A DictList object where the key is the reaction identifier and the value a cobra.Reaction object in cobra_model attribute.

Type:DictList
objectives[source]

A list containing identifiers of reactions to be used as objectives in lexicographic optimization (currently not supported)

Type:list
directions[source]

A list containing directions (max or min) of each objective in lexicographic optimization (currently not supported)

Type:list
kinetic_variables[source]

A DictList object where the key is the kinetic variable identifier and the value a KineticVariable object.

Type:DictList
exchange_fluxes[source]

A DictList object where the key is the reaction identifier and the value an ExchangeFlux object.

Type:DictList
user_data[source]

A read only attribute containing user data of the model to be passed to algorithm prior to simulation.

Type:dfba_utils.UserData
solver_data[source]

An attribute containing data for the solver to be used for simulation of the model.

Type:dfba_utils.SolverData
id :str[source]

.

cobra_model :Model[source]

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reactions :DictList[source]

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objectives :List[source]

.

directions :List[source]

.

kinetic_variables :DictList[source]

.

exchange_fluxes :DictList[source]

.

user_data :UserData[source]

.

solver_data :SolverData[source]

.

add_objectives(self, objectives: List, directions: List)[source]

Add objectives.

Parameters:
  • objectives (list) – The list of reaction indetifiers to be added to the model as objectives for lexicographic optimization.
  • directions (list) – The list of directions (max or min) of each objective to be added to the model for lexicographic optimization.
add_kinetic_variables(self, kinetic_variable_list: List)[source]

Add kinetic variables.

Parameters:kinetic_variable_list (list) – The list of indetifiers of kinetic variables to be added to the model.
add_exchange_fluxes(self, exchange_flux_list: List)[source]

Add exchange fluxes.

Parameters:exchange_flux_list (list) – list of identifiers of exchange fluxes to be added to the model.
add_initial_conditions(self, initial_conditions: Dict)[source]

Add initial conditions.

Parameters:initial_conditions (dict) – A dict where the key is the kinetic variable identifier and the value an initial condition.
add_rhs_expression(self, kinetic_variable_id: str, expression: Expression, control_parameters: Optional[List[ControlParameter]] = None)[source]

Add rhs expression.

Parameters:
  • kinetic_variable_id (string) – Identifier of the kinetic variable to be supplied with rhs expression for calculating its derivative wrt time.
  • expression (optlang.symbolics expression) – The symbolic expression for calculating derivative of kinetic variable wrt time.
  • control_parameters (list) – A list of ControlParameter objects (if any) appearing in the supplied symbolic expression.
add_exchange_flux_lb(self, exchange_flux_id: str, expression: Expression, condition: Optional[Expression] = None, control_parameters: Optional[List[ControlParameter]] = None)[source]

Add exchange flux lower bound.

Parameters:
  • exchange_flux_id (string) – Indetifier of the exchange flux to be supplied with expression for calculating its lower bound.
  • expression (optlang.symbolics expression) – The symbolic expression for calculating lower bound of exchange flux. Convention is that lower bounds of exchange fluxes come with negative sign and therefore expression should be non-negative,representing the magnitude of this lower bound.
  • condition (optlang.symbolics expression) – The symbolic expression for non-negative condition on metabolite concentrations required for correct evaluation of lower bound expression. Numerical approximation can generate unphysical, negative concetration values.
  • control_parameters (list) – A list of ControlParameter objects (if any) appearing in the supplied symbolic expression.
add_exchange_flux_ub(self, exchange_flux_id: str, expression: Expression, condition: Optional[Expression] = None, control_parameters: Optional[List[ControlParameter]] = None)[source]

Add exchange flux upper bound.

Parameters:
  • exchange_flux_id (string) – Indetifier of the exchange flux to be supplied with expression for calculating its upper bound.
  • expression (optlang.symbolics expression) – The symbolic expression for calculating upper bound of exchange flux. Convention is that upper bounds of exchange fluxes come with positive sign and therefore expression should be non-negative, representing the magnitude of this upper bound.
  • condition (optlang.symbolics expression) – The symbolic expression for non-negative condition on metabolite concentrations required for correct evaluation of upper bound expression. Numerical approximation can generate unphysical, negative concetration values.
  • control_parameters (list) – A list of ControlParameter objects (if any) appearing in the supplied symbolic expression.
simulate(self, tstart: float, tstop: float, tout: float, output_fluxes: Optional[List[str]] = None)[source]

Simulate model.

Parameters:
  • tstart (float) – Initial time point to be used in simulation of the model.
  • tstop (float) – Final time point to be used in simulation of the model.
  • tout (float) – Output frequency to be used in simulation of the model.
  • output_fluxes (list) – Optional list of reaction ids whose fluxes are to be printed to results along with kinetic variables.
Returns:

  1. time, concentrations (in self.kinetic_variables)
  2. time, flux trajectories (in )
Return type:

tuple of 2 pd.Dataframe’s
lp_problem(self)[source]

LP problem.

Returns:lp_problem – SWIGLPK object representing FBA model as pointer to GLPK problem
Return type:Swig Object of type glp_prob *
add_to_library(self, tstart: float, tstop: float, tout: float, print_fluxes: List[Reaction], directory: str)[source]

Add model to library.

Parameters ——- tstart : float

Initial time point to be used in simulation of the model.
tstop : float
Final time point to be used in simulation of the model.
tout : float
Length of time interval for output.
print_fluxes : list
List of reactions whose fluxes are to be printed to results along with kinetic variables.
directory: string
Path to temporary directory containing library.