# NOT RUN {
require(PairViz)
data <- mtcars[,c(1,3:6)]
cols <- c("red","green")[mtcars[,9]+1 ] # transmission type, red=automatic
# add a correlation guide and find "better" hamiltonians...
# add a correlation guide...
corw <- dist2edge(as.dist(cor(data)))
edgew <- cbind(corw*(corw>0), corw*(corw<0))
# add a correlation guide to a PCP, positive cors shown in blue, negative in purple...
# }
# NOT RUN {
dev.new(width=3,height=3)
par(cex.axis=.65)
guided_pcp(data,edgew, pcp.col=cols,
main="Correlation guided PCP",bar.col = c("blue","purple"))
dev.new(width=7,height=3)
par(cex.axis=.65)
guided_pcp(data,edgew, path=eulerian, pcp.col=cols,lwd=2,
main="Correlation guided Eulerian PCP",bar.col = c("blue","purple"),bar.axes=TRUE)
# }
# NOT RUN {
# Scagnostic guides are useful here- see the demos for more examples.
# }
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