interpretDiscreteGA: Interpreter of output of discrete genetic algorithm

In CNORfuzzy: Addon to CellNOptR: Fuzzy Logic

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

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

    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. 8, 2020, 5 p.m.