## ---- eval=TRUE---------------------------------------------------------- library( mau ) file<-system.file("extdata", "utilities.txt", package = "mau" ) lines<-readLines( file ) for ( i in 1:length( lines ) ) { cat( lines[i], '\n' ) } ## ----eval=TRUE,message=FALSE, warning=FALSE------------------------------ library( mau ) library( data.table ) library( igraph ) library( ggplot2 ) ## ----eval=TRUE----------------------------------------------------------- index<-data.table( cod = paste( 'A', 1:10, sep = '' ), i1 = c( 0.34, 1, 1, 1, 1, 0.2, 0.7, 0.5, 0.11, 0.8 ), i2 = c( 0.5, 0.5, 1, 0.5, 0.3, 0.1, 0.4, 0.13, 1, 0.74 ), i3 = c( 0.5, 1.0, 0.75, 0.25, 0.1, 0.38, 0.57, 0.97, 0.3, 0.76 ), i4 = c( 0, 0.26, 0.67, 0.74, 0.84, 0.85, 0.74, 0.65, 0.37, 0.92 ) ) ## ---- echo=FALSE, results='asis'----------------------------------------- knitr::kable( index ) ## ----eval=TRUE----------------------------------------------------------- file<-system.file("extdata", "utilities.txt", package = "mau" ) script<-'utilities.R' lines<-17 skip<-2 encoding<-'utf-8' functions<-Read.Utilities( file, script, lines, skip, encoding ) source( 'utilities.R' ) ## ---- echo=FALSE, results='asis'----------------------------------------- knitr::kable( functions ) ## ----eval=TRUE----------------------------------------------------------- # Index positions columns<-c( 2, 3, 4, 5 ) # Function names functions<-sapply( c( 'Project', 'Self implementation', 'External and local relations', 'Scope of capabilities' ), FUN = Stand.String ) names( functions )<-NULL # Evaluation of utilities utilities<-Eval.Utilities( index, columns, functions ) ## ---- echo=FALSE, results='asis'----------------------------------------- knitr::kable( utilities ) ## ----eval=TRUE, fig.show='hold', fig.align="center", fig.width=7, fig.height=6---- file<-system.file("extdata", "tree.csv", package = "mau" ) tree.data<-Read.Tree( file, skip = 0, nrow = 8 ) tree<-Make.Decision.Tree( tree.data ) utilities<-Eval.Utilities( index, columns, functions ) plot( tree, layout = layout_as_tree ) ## ----eval=TRUE----------------------------------------------------------- weights<-tree.data[ !is.na( weight ) ]$weight model<-Compute.Model( tree, utilities, weights ) ## ----eval=TRUE, fig.show='hold', fig.align="center", fig.width=7, fig.height=4---- xlab<-'Utility' ylab<-'Institutions' title<-'Criteria utilities' colors<-c( 'dodgerblue4', 'orange', 'gold', 'red3' ) deep<-2 bar<-Bar.Plot( model, deep, colors, title, xlab, ylab ) plot( bar ) ## ----eval=TRUE, fig.show='hold', fig.show='hold', fig.align="center", fig.width=7, fig.height=4---- n<-800 alpha<-c( 0.2, 0.5, 0.1, 0.2 ) constraints<-list( list( c(1,2), 0.7 ), list( c(3,4), 0.3 ) ) S<-Sim.Const.Weights( n, utilities, alpha, constraints ) plot.S<-Plot.Simulation.Weight( S$simulation, title = 'Simulations', xlab = 'ID', ylab = 'Utility' ) plot( plot.S )