getLBodeMINLPObjFunction: Get the objective function to evaluate the fitness of a given...
In CNORode: ODE add-on to CellNOptR

Description Usage Arguments Details Value Author(s) See Also Examples

This function configures returns the objective function that can be used to evaluate the fitness of a logic based ODE model using a particular set of parameters and model structure. This function can be particular useful if you are planing to couple a mixed integer nonlinear programming optimization solver. The returned value of the objective function corresponds to the mean squared value.

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	getLBodeMINLPObjFunction(cnolist, model, ode_parameters, indices=NULL, time = 1, 
	verbose = 0, transfer_function = 3, reltol = 1e-04, atol = 0.001, maxStepSize = Inf, 
	maxNumSteps = 1e+05, maxErrTestsFails = 50, nan_fac = 1)

`cnolist`	A list containing the experimental design and data.
`model`	The logic model to be simulated.
`ode_parameters`	A list with the ODEs parameter information. Obtained with `createLBodeContPars`.
`indices`	Indices to map data in the model. Obtained with indexFinder function from CellNOptR.
`time`	An integer with the index of the time point to start the simulation. Default is 1.
`verbose`	A logical value that triggers a set of comments.
`transfer_function`	The type of used transfer. Use 1 for no transfer function, 2 for Hill function and 3 for normalized Hill function.
`reltol`	Relative Tolerance for numerical integration.
`atol`	Absolute tolerance for numerical integration.
`maxStepSize`	The maximum step size allowed to ODE solver.
`maxNumSteps`	The maximum number of internal steps between two points being sampled before the solver fails.
`maxErrTestsFails`	Specifies the maximum number of error test failures permitted in attempting one step.
`nan_fac`	A penalty for each data point the model is not able to simulate. We recommend higher than 0 and smaller that 1.

Check CellNOptR for details about the cnolist and the model format. For more details in the configuration of the ODE solver check the CVODES manual.

Returns a function to evaluate the model fitness. This function receives a continuous parameter vector.

David Henriques, Thomas Cokelaer

CellNOptR createLBodeContPars

library(CNORode)
data("ToyCNOlist",package="CNORode");
data("ToyModel",package="CNORode");
data("ToyIndices",package="CNORode");

ode_parameters=createLBodeContPars(model,random=TRUE);
minlp_obj_function=getLBodeMINLPObjFunction(cnolistCNORodeExample, model,ode_parameters,indices);

n_int_vars=dim(model$interMat)[2];
x_int=round(runif(n_int_vars))
x_cont=ode_parameters$parValues;
x=c(x_cont,x_int);
f=minlp_obj_function(x);