#b <- commandArgs()

#data <- read.delim(b[6], header=TRUE, sep = ",", dec=".", fill = TRUE, comment.char="")
#mindensity <- as.numeric(b[7])
#tol <- as.numeric(b[8])
#ctol <- as.numeric(b[9])
#width <- as.numeric(b[10])

data <- read.delim("iris.txt", header=TRUE, sep = ",", dec=".", fill = TRUE, comment.char="")
mindensity <- .3
tol <- 0.0001
ctol <- .5
width <- .45
len <- length(data[1,])-1
coef <- 1/(length(data[,1])*width^len)
coef2 <- (1/((2*pi)^(len/2)))
coef3 <- 1/(length(data[,1])*width^(len+2))
denom <- 2*width^2
attractors <- data[,1:len]


for(i in 1:length(data[,1])) {
  print(i)
  xt <- data[i,1:len]
  xt1 <- data[i,1:len]
  while(1) {
    sumk <- array(0,dim=len)
    for(j in 1:length(data[,1])) {
      sumk <- sumk + (coef2 * exp((-1*(as.numeric(dist(rbind(xt,data[j,1:len]),method="euclidean")))^2)/denom)) * (data[j,1:len] - xt)
    }
    xt1 <- xt + mindensity*coef3*sumk
    if(dist(rbind(xt1,xt),method="euclidean") <= tol) break
    xt <- xt1
  }
  sumk <- 0
  for(j in 1:length(data[,1])) {
    sumk <- sumk + coef2 * exp((-1*(as.numeric(dist(rbind(xt1,data[j,1:len]),method="euclidean")))^2)/denom)
  }
  if((coef * sumk) < mindensity) {
    attractors[i,] <- array(Inf, dim=len)
  } else {
    attractors[i,] <- xt1
  }
}

for(i in 1:length(attractors[,1])) {
  if(attractors[i,1] == Inf){
    min <- Inf
    xt <- data[i,1:len]
    for(j in 1:length(attractors[,1])) {
      if(dist(rbind(data[i,1:len],attractors[j,]),method="euclidean") < min) {
        min <- dist(rbind(data[i,1:len],attractors[j,]),method="euclidean")
        xt <- attractors[j,]
      }
    }
    attractors[i,] <- xt
  }
}

dens_attractors <- list()
clusters <- array(0,dim=length(data[,1]))
c_cluster <- 0
for(i in 1:length(data[,1])) {
  if(clusters[i] == 0) {
    dens_attractors[length(dens_attractors)+1] <- i
    c_cluster <- c_cluster + 1
    clusters[i] <- c_cluster
    for(j in i:length(attractors[,1])) {
      if(clusters[j] == c_cluster) {
        for(k in i:length(attractors[,1])) {
          if(clusters[k] == 0)
            if(dist(rbind(attractors[j,],attractors[k,]),method="euclidean") <= ctol)
              clusters[k] <- c_cluster
        }
      }
    }
  }
}