interpretDiscreteGA {CNORfuzzy} | R Documentation |
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.
interpretDiscreteGA(model, paramsList, intString, bitString=NULL)
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. |
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.
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. |
M.K. Morris
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)