plotMeanFuzzyFit: Simulates models returned from multiple cFL runs and plots...

In CNORfuzzy: Addon to CellNOptR: Fuzzy Logic

Description

Uses post refinement threshold (selection threshold) to choose reduced refined model resulting from each run. Simulates model and plots result and fit to data

Usage

  plotMeanFuzzyFit(postRefThresh, allFinalMSEs, allRes, plotPDF=FALSE, tag=NULL,
show=TRUE, plotParams=list(cex=0.8, cmap_scale=1))

Arguments

postRefThresh

Post refinement threshold (selection threshold) chosen from plot produced by compileMultiRes

.

allFinalMSEs	matrix containing MSEs produced by compileMultiRes
allRes	list containing results of several CNORwrapFuzzy runs
plotPDF	TRUE or FALSE depending on if a PDF file should be saved
tag	String to include in filename of PDF plot
show	If the plot should be displayed
plotParams	a list of option related to the PDF and plotting outputs. (1) cex is the font size of the header. (2) cmap_scale below 1 allows to put more emphasizes on low errors (default 1 means all colors have the same weight). See plotOptimResultsPan from CellNOptR for other fields.

Value

This function does not have any output, it just plots and saves results if applicable.

Author(s)

M.K. Morris

Examples

    data(ToyModel, package="CellNOptR")
    data(CNOlistToy,package="CellNOptR")
    paramsList = defaultParametersFuzzy(CNOlistToy, ToyModel)
    N = 10
    allRes = list()

    ## Not run: 
    for (i in 1:N){
        Res = CNORwrapFuzzy(CNOlistToy, ToyModel, paramsList)
        allRes[[i]] = Res
    }

    summary = compileMultiRes(allRes)
    plotMeanFuzzyFit(0.1, summary$allFinalMSEs, allRes)

    
## End(Not run)

CNORfuzzy documentation built on Nov. 8, 2020, 5 p.m.