cutAndPlotResultsT1: Plot the results of an optimisation at t1

In saezlab/CellNOptR: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data

Plot the results of an optimisation at t1

Description

This function takes a model and an optimised bitstring, it cuts the model according to the bitstring and plots the results of the simulation along with the experimental data.

Usage

cutAndPlotResultsT1(model, bString, simList=NULL, CNOlist, indexList=NULL, plotPDF =
FALSE, tag = NULL, tPt=CNOlist@timepoints[2],  plotParams = list(maxrow=10))

Arguments

model	a model (the full one that was used for optimisation)
bString	a bitstring for T1 as output by gaBinaryT1 (i.e. a vector of 1s and 0s)
simList	deprecated argument kept for back compatibility. a simlist corresponding to the model, as output by prep4sim
CNOlist	a CNOlist, corresponding to the optimisation one
indexList	deprecated argument kept for back compatibility. an indexList, produced by indexFinder ran on the model and the CNOlist above
plotPDF	TRUE or FALSE; tells whether you want a pdf to be produced or not
tag	NULL or string; tells whether you want to prefix filenames with a tag (replaces the default behaviour).
tPt	The number of time points in the data.
plotParams	a list of option related to the PDF and plotting outputs. (1) maxrow is the maximum number of row used to plot the results. See plotOptimResultsPan for other fields.

Value

This function returns plotted MSEs and list of filenames generated (if any)

Author(s)

C.Terfve, T. Cokelaer,A. MacNamara

See Also

gaBinaryT1

Examples

#load data

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

#pre-process model
model = preprocessing(CNOlistToy, ToyModel)

#optimise
ToyT1opt<-gaBinaryT1(
	CNOlist=CNOlistToy,
	model=model,
	maxGens=20, 
	popSize = 10,
	verbose=FALSE)

#plotting
cutAndPlotResultsT1(
	model=model,
	CNOlist=CNOlistToy,
	bString=ToyT1opt$bString,
	plotPDF=FALSE)

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