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# ===== #
library(kohonen)

# Load data, available at https://gist.github.com/ottadini/6068259
somdata <- read.csv("somdata.csv")


# Create SCALED test and training sets from data:
inTrain <- sample(nrow(somdata), nrow(somdata)*(2/3))
training <- scale(somdata[inTrain, ])

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# Source: http://stackoverflow.com/q/7549694/857416

lm_eqn = function(m) {
  # Displays regression line equation and R^2 value on plot
  # Usage:
  # p + annotate("text", x=25, y=300, label=lm_eqn(lm(y ~ x, df)), parse=TRUE)
  
  l <- list(a = format(coef(m)[1], digits = 2),
            b = format(abs(coef(m)[2]), digits = 2),
            r2 = format(summary(m)$r.squared, digits = 3));

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# Base graphics

# Create a PDF for a square shaped plot (e.g. for predictions vs observations regression)

pdf(file="pred-vs-meas_MLR.pdf", width=5, height=5, family="Times")
op <- par(pty='s')  # plot type = square
plot(X, Y, 
     xlab=Xlabel, ylab=Ylabel, ylim=c(0, 3), xlim=c(0, 3)) #
abline(fit, lty=2)
par(op)

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plot.multi.dens <- function(s){
# From: http://onertipaday.blogspot.com.au/2007/09/plotting-two-or-more-overlapping.html
# the input s MUST be a numeric list
# e.g. 
# rating <- rnorm(200)
# rating2 <- rnorm(200, mean=.8)
# plot.multi.dens( list(rating, rating2)) 
    junk.x = NULL
    junk.y = NULL

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# I cannot remember the source for this code. It isn't mine. Probably somewhere on stackoverflow.




require ("kohonen")
require ("latticeExtra")
require ("deldir")
data(wines)
som.wines <- som (scale (wines), grid = somgrid(5, 5, "hexagonal"))

df <- as.data.frame (cbind (som.wines$grid$pts, som.wines$codes))
levelplot (alcohol ~ x * y, data = df, panel = panel.voronoi, aspect = "iso")

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# Cannot remember the source for this code, it isn't mine. 


genHexGrid <- function(dx, ll = c(0, 0), ur = c(1, 1))
{
    dy <- sqrt(3) * dx / 2
    
    x <- seq(ll[1], ur[1] - dx / 2, dx)
    y <- seq(ll[2], ur[2], dy)
    
    y <- rep(y, each = length(x))

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wrap <- function(string){
  paste(strwrap(string), collapse="\n")
}

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