interpretDiscreteGA: Interpreter of output of discrete genetic algorithm

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

View source: R/interpretDiscreteGA.R

Description

This function takes the integer string output by the discrete genetic algorithm for training a cFL model and generates the corresponding model based on the Fuzzy parameters.

Usage

1
interpretDiscreteGA(model,  paramsList, intString, bitString=NULL)

Arguments

model

PKN trained (same model input as to gaDiscrete).

paramsList

List containing parameters (see defaultParametersFuzzy). Only the fuzzy parameters are used.

intString

Integer string resulting from gaDiscrete (in bString field of gaDiscreteT1 output).

bitString

(optional) if you want to cut additional interactions from the model. Used in reduceFuzzy function.

Details

After the discreteGA chooses transfer functions from a discrete set of transfer functions and removing interactions inconsistent with the data, this function interprets the output and returns an actual model using these transfer functions as well as a model from which logical redundancy was cut.

Value

model

The selected initial model based on the provided bitstring.

simList

The corresponding data related to Model field

bitString

The bitstring corresponding to the Model field

cutModel

Same as Model but redundant reactions are also removed.

cutSimList

The corresponding data related to cutModel field

cutBitString

The corresponding bitstring related to cutModel field.

Author(s)

M.K. Morris

See Also

gaDiscreteT1

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
    data(ToyModel, package="CellNOptR")
    data(CNOlistToy,package="CellNOptR")
    paramsList = defaultParametersFuzzy()
    ## Not run: 

        # preprocessing (see CNORwrapFuzzy or gaDiscreteT1)
        T1opt = gaDiscreteT1(....)  # see CNORwrapFuzzy or gaDiscreteT1 for details
        interpretDiscreteGA(ToyModel, paramsList, T1opt$bString)

## End(Not run)

CNORfuzzy documentation built on Nov. 1, 2018, 2:23 a.m.