Nlp

NLPobjPerFlux(fluxVector, Prob)[source]

Calculates the value of the objective - (Prob.osense * Prob.user.model.c)/sum(v.^2) based on a flux distribution This function is meant to be used with NLP solvers

USAGE

value = NLPobjPerFlux (fluxVector, Prob)

INPUTS

  • fluxVector – Flux vector

  • Prob – NLP problem structure

OUTPUT

value – -Objective flux / sum(v.^2)

optimizeCbModelNLP(model, varargin)[source]

Optimizes constraint-based model using a non-linear objective

USAGE

[currentSol, allObjValues, allSolutions] = optimizeCbModelNLP (model, varargin)

INPUT

model – COBRA model structure

Optional inputs are parameter/value pairs

OPTIONAL INPUT

  • objFunction – Name of the non-linear matlab function to be optimized (the corresponding m-file must be in the current matlab path) The function receives two arguments, the current flux vector, and the NLPProblem structure.

  • initFunction – Name of the matlab function used to generate random initial starting points. The function will be supplied with two arguments: the model and a cell array of input arguments (specified in the initArgs parameter)

  • osenseStr – Optimization direction (‘max’ or ‘min’), this will override any mention in the model.

  • nOpt – Number of independent optimization runs performed

  • objArgs – Cell array of arguments that are supplied to the objective function as objArguments in the NLPProblem structure (i.e. the second element, will have a field objArguments.)

  • initArgs – Cell array of arguments to the ‘initFunction’, will be provided as second input Argument to the initFunction

  • solveroptions – A Struct with options for the solver used. This is specific to the solver in question, but the fields should relate to options accepted by the solver.

OUTPUTS

  • currentSol – Solution structure

  • allObjValues – Array of objective value of each iteration

  • allSolutions – Array of flux distribution of each iteration

solveCobraNLP(NLPproblem, varargin)[source]

Solves a COBRA non-linear (objective and/or constraints) problem. Solves a problem of the following form: optimize objFunction(x) or c’*x st. \(A*x <=> b or b_L < A*x < b_U\) and \(d_L < d(x) < d_U\) where A is a matrix, d(x) is an optional function and the objective is either a general function or a linear function.

USAGE

solution = solveCobraNLP (NLPproblem, varargin)