exhaustive: Exhaustive search over the optimisation of a PKN model on...

View source: R/exhaustive.R

exhaustiveR Documentation

Exhaustive search over the optimisation of a PKN model on MIDAS data.

Description

This function performs an exhaustive search of the parameter space tring all the solutions. It is used internally by the genetic algorithm when a small model has to be optimised and the number of solutions to try is smaller than the number of iterations that the Genetic Algorithm will perform.

Usage

exhaustive(CNOlist, model, shuffle=FALSE, Nmax=NULL, verbose=TRUE, sizeFac =
0.0001, NAFac = 1, relTol=0.1, timeIndex=2)

Arguments

CNOlist

a CNOlist on which the score is based (based on valueSignals[[2]], i.e. data at time 1)

model

a model structure, as created by readSIF, normally pre-processed but that is not a requirement of this function

shuffle

The list of bitstrings is set up arbitrarely. You may want to shuffle it.

Nmax

The total number of computation will be 2 to the power N, where N is the size of the model (ReacID field). The total number of computation can be large. You may want to set a maximumn number of computation using Nmax.

sizeFac

the scaling factor for the size term in the objective function, default to 0.0001

NAFac

the scaling factor for the NA term in the objective function, default to 1

relTol

the relative tolerance for the best bitstring reported by the genetic algorithm, i.e., how different from the best solution, default set to 0.1 Not yet implemented.

verbose

logical (default to TRUE) do you want the statistics of each generation to be printed on the screen?

timeIndex

the index of the time point to optimize. Must be greater or equal to 2 (1 corresponds to time=0). Must be less than the number of time points. Default is 2.

Value

This function returns a list with elements:

bString

the best bitstring

bScore

the best score

all_scores

all scores that have been computed

results

a matrix with columns "Generation","Best_score","Best_bitString","Stall_Generation","Avg_Score_Gen","Best_score_Gen","Best_bit_Gen","Iter_time"

stringsTol

the bitstrings whose scores are within the tolerance

stringsTolScores

the scores of the above-mentioned strings

Note that the field results, is not yet populated but maybe in the future.

Author(s)

T. Cokelaer

See Also

gaBinaryT1

Examples

data(CNOlistToy,package="CellNOptR")
data(ToyModel,package="CellNOptR")

#pre-process model

model = preprocessing(CNOlistToy, ToyModel)

#optimise

results <-exhaustive(
	CNOlist=CNOlistToy,
	model=model,
    shuffle=TRUE,
    Nmax=1000,
	verbose=FALSE)

saezlab/CellNOptR documentation built on April 16, 2024, 5:21 a.m.