RG#85: Plotting XY plot with cluster and adding ellipse to it

# data 
set.seed (1234)
c1 <- rnorm (40, 0.1, 0.02); c2 <- rnorm (40, 0.3, 0.01)
c3 <- rnorm (40, 0.5, 0.01); c4 <- rnorm (40, 0.7, 0.01)
c5 <- rnorm (40, 0.9, 0.03)
Yv <- 0.3 + rnorm (200, 0.05, 0.05)
myd <- data.frame (Xv = round (c(c1, c2, c3, c4, c5), 2), Yv = round (Yv, 2),
 cltr = factor (rep(1:5, each = 40)))

library(devtools)
require(ggplot2)
source_url("https://raw.github.com/low-decarie/FAAV/master/r/stat-ellipse.R")

ggplot(myd, aes(x=Xv, y=Yv, color=cltr)) + ylim (c(0, 0.1 + max(myd$Yv))) + stat_ellipse() +
xlim (c(0, 0.1 + max(myd$Xv))) +
 geom_point(shape=20, size = 5) +
 scale_colour_manual ( values = c("red", "green", "purple", "yellow", "blue4")) +
 theme_bw()



# plot using base:

plot(myd$Xv, myd$Yv, col = myd$cltr, pch = 19, cex = 1.5)


# interactively identifying the points, use stop when done  
identify (myd$Xv, myd$Yv,labels = row.names(myd))

plot(myd$Xv, myd$Yv, col = myd$cltr, pch = 19, cex = 1.5)

# add points by clicking, use stop when done  

pl <- locator (type = "p", pch = 2, col = "green1")

pl # see the coordinates on added points 

plot(myd$Xv, myd$Yv, col = myd$cltr, pch = 19, cex = 1.5)

# add lines by clicking 

cord <- locator (type = "l", col = "green1", lwd = 2)

cord # display coordinates 

# interactive scatter plot 
require(iplots) 
iplot(myd$Xv, myd$Yv, col = myd$cltr, pch = 19, size = 5, ylim = c(0, 1), xlim = c(0,1))

RG#23: plot correlation: heat map and using ellipse

#data
set.seed(1234)
xm1 <- matrix(rnorm(100*10, rnorm(100, 0.5, 0.1)), nrow=100, ncol=10, byrow=FALSE)
xm2 <- matrix(rnorm(100*10, rnorm(100, 0.5, 0.1)), nrow=100, ncol=10, byrow=FALSE)
xm3 <- matrix(rnorm(100*10, rnorm(100, 0.5, 0.1)), nrow=100, ncol=10, byrow=FALSE)
dd <- cbind(xm1, xm2, xm3)
 cor <- cor(dd)# calculate correlation matrix


require(ellipse)
plotcorr(cor, outline = TRUE, col = "darkgreen", numbers = FALSE, type = "full", diag = FALSE)















#heatmap plot for the data using ggplot2.

require(ggplot2)
# first need to reshape data to long form
require(reshape)
cor.melt <- data.frame(melt(cor) )
ggplot(cor.melt , aes(x=X1,y=X2, z= value)) + geom_tile(aes(fill= value)) + scale_fill_gradient(low="red", high="green") + theme_bw()