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// Sumatra?

  FindInString(`%$('AcroRead')`,'SumatraPDF',1,2,1000,1);
  IfOK(!"Relax;",!"JMP('not_sumatra')");
  Run('%$("AcroRead"); -reuse-instance -inverse-search "\"%B\WinEdt.exe\" \"[Open(|%%f|);SelPar(%%l,8);]\"" "%P\%N.pdf"','%P',0,0,'%N.pdf - SumatraPDF',1,1);
  DDEOpen('',"SUMATRA","control",1);
// send a DDE command to perform forward-search
// the format of the DDE command is [ForwardSearch("<pdffilepath>","<sourcefilepath>",<line>,<column>[,<newwindow>, <setfocus>])]
//    if newwindow = 1 then a new window is created even if the file is already open
//    if focus = 1 then the focus is set to the window

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updown_colors <- function(n = 50, down.col = 1/3, up.col=1, saturation = 1)
{ 
  c(hsv(down.col, saturation, seq(1,0,length=n)), hsv(up.col, saturation, seq(0,1,length=n))) 
}

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# one sample normal test
norm_test1 <- function(x.n, x.mu, x.var, mu, side=0)
{
  nu <- x.n - 1
  z <- (x.mu - mu) / sqrt(x.var / x.n)
  p <- p.value(pnorm, z, side=side)
  data.frame(mean=x.mu, df=nu, statistic=z, p.value=p)
}

# two samples normal test

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# one sample t-test
t_test1 <- function(x.n, x.mu, x.var, mu, side=0)
{
  nu <- x.n - 1
  t <- (x.mu - mu) / sqrt(x.var / x.n)
  p <- p.value(pt, t, params=nu, side=side)
  data.frame(mean=x.mu, df=nu, statistic=t, p.value=p)
}

# two samples t-test

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p_value <- function(cdf, z, params=numeric(0), side=0)
{
  n <- length(params)
  p <- switch(n+1,
    cdf(z),
    cdf(z, params),
    cdf(z, params[1], params[2]),
    cdf(z, params[1], params[2], params[3])
  )
  if (side < 0) p

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fold_change <- function(x, y, confidence.level=90, var.equal=F)
{
  fc.interval(length(x), mean(x), var(x), length(y), mean(y), var(y), confidence.level, var.equal)
}

fc.interval <- function(x.n, x.mu, x.var, y.n, y.mu, y.var, confidence.level=90, var.equal=F)
{
  mu <- x.mu - y.mu
  if (var.equal) {
    nu <- x.n + y.n - 2

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robust_fold_change <- function(case, control)
{
  m <- dim(case)[2]
  n <- dim(control)[2]
  fc.raw <- matrix(nrow=dim(case)[1], ncol=m*n)
  for (i in 1:m) {
    for (j in 1:n) {
      fc.raw[, (i-1)*m+j] <- case[,i] - control[,j]
    }
  }

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merge_rows <- function(x, method=mean, na.rm=FALSE) 
{
  x <- as.matrix(x[!is.na(rownames(x)), ])
  r <- unique(rownames(x))
  m <- length(r)
  if (dim(x)[1] != m) {
    y <- matrix(nrow=m, ncol=dim(x)[2])
    rownames(y) <- r
    colnames(y) <- colnames(x)
    for (i in 1:m) {

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diffusion_kernel <- function(adj, beta = 1)
{
  lap <- adj - diag(rowSums(adj))
  eig <- eigen(lap)
  dif <- eig$vectors %*% diag(exp(beta * eig$values)) %*% t(eig$vectors)
  dif
}