knitr::opts_chunk$set(echo = TRUE) library(GridFCM) library(OpenRepGrid) library(knitr) library(rgl) library(shiny) library(plotly) knitr::knit_hooks$set(webgl = hook_webgl)
GRIDFCM REPORT
bertin(render.grid, colors = c("white","#005440"))
bertin(render.imp, colors = c("#F52722","#e5e5e5","#a5d610"))
BIPLOTS
biplotSimple(render.grid, c.label.col = "darkred")
biplot2d(render.grid, c.label.col = "darkred")
biplot3d(render.grid, c.label.col = "darkred")
CLUSTER ANALYSIS
cluster(render.grid, along = 1)
cluster(render.grid, along = 2)
COGNITIVE INDECES
COR.IDEAL <- elementCor(render.grid)[1,ncol(render.grid)] PVEFF <- indexPvaff(render.grid) INTc <- indexIntensity(render.grid)[[1]] INTc <- INTc[order(-INTc)] INTe <- indexIntensity(render.grid)[[2]] INTe <- INTe[order(-INTe)] INT <- indexIntensity(render.grid)[[5]] CON <- indexConflict1(render.grid)[[4]] kable(data.frame(COR.IDEAL,PVEFF,INT,CON),col.names = c("Cor. Self / Ideal-Self","PVAFF","Intensity","Conflicts"))
kable(INTc, col.names = "Intensity")
kable(INTe, col.names = "Intensity")
dilemma <- indexDilemma(render.grid)
IMPLICATIVE DILEMMAS
colnames(dilemma$res1)[1] <- "Status" kable(dilemma$res1)
kable(dilemma$res4)
IDEAL MAP DIGRAPH
idealdigraph(render.grid,render.imp)
idealdigraph(render.grid,render.imp, inc=TRUE)
inc <- inc_index(render.grid,render.imp) inc <- inc[order(-inc[,3]),] kable(inc)
SELF MAP DIGRAPH
rgl.clear() fcmdigraph3D(render.grid,render.imp, niter = 1)
fcmdigraph(render.grid,render.imp,niter = 1, layout = "mds")
fcmdigraph(render.grid,render.imp,niter = 1, layout = "graphopt")
fcmdigraph(render.grid,render.imp,niter = 1, layout = "rtcircle")
fcmdigraph(render.grid,render.imp,niter = 1, layout = "circle")
fcmdigraph(render.grid,render.imp,niter = 1, layout = "grid")
convergence <- fcminfer(render.grid, render.imp)$convergence
rgl.clear() fcmdigraph3D(render.grid,render.imp, niter = convergence )
fcmdigraph(render.grid,render.imp,niter = convergence, layout = "mds")
fcmdigraph(render.grid,render.imp,niter = convergence, layout = "graphopt")
fcmdigraph(render.grid,render.imp,niter = convergence, layout = "rtcircle")
fcmdigraph(render.grid,render.imp,niter = convergence, layout = "circle")
fcmdigraph(render.grid,render.imp,niter = convergence, layout = "grid")
PERSONAL CONSTRUCT SYSTEM DYNAMICS
pcsd(render.grid,render.imp)
sum.pcsd <- pcsd_summary(render.grid, render.imp) sum.pcsd <- sum.pcsd[order(-sum.pcsd[,3]),] kable(sum.pcsd)
auc.pcsd <- auc_index(render.grid, render.imp) auc.pcsd <- auc.pcsd[order(-auc.pcsd)] kable(auc.pcsd, col.names = "AUC")
sd.pcsd <- stability_index(render.grid, render.imp) sd.pcsd <- sd.pcsd[order(sd.pcsd)] kable(sd.pcsd, col.names = "SD")
pcsd_derivative(render.grid,render.imp)
FCM INDECES
n.edges <- sum(getRatingLayer(render.imp) != 0) n.vertex <- ncol(getRatingLayer(render.imp)) dens <- density_index(render.imp) degree <- cbind(degree_index(render.imp)[[1]],degree_index(render.imp)[[2]],degree_index(render.imp)[[3]]) degree <- degree[order(-degree[,3]),] close <- close_index(render.imp) close <- close[order(-close)] betw <- betw_index(render.imp) betw <- betw[order(-betw)] kable(data.frame(n.vertex,n.edges, dens),col.names = c("Vertexes","Edges","Density"))
kable(degree, col.names = c("Outputs","Inputs","All"))
kable(close, col.names = "Centrality")
kable(betw, col.names = "Centrality")
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