R/ExtractPointValue.R

In rSQM: Statistical Downscaling Toolkit for Climate Change Scenario using Non Parametric Quantile Mapping

ExtractPointValue <- function(xin, yin, ncfile, wdir) {

  # get x and y information
  nc <- ReadNetCDF4(wdir, ncfile)
  x <- nc$x
  y <- nc$y
  var <- nc$var

  ncols <- length(x)
  nrows <- length(y)

  xcoord <- array(0, dim = c(ncols, 2))
  ycoord <- array(0, dim = c(nrows, 2))

  for(i in 1:ncols){
    if(i == ncols){
      xcoord[i,1] <- x[i] - (x[i]-x[i-1])/2.0
      xcoord[i,2] <- x[i] + (x[i]-x[i-1])/2.0
    }else{
      xcoord[i,1] <- x[i] - (x[i+1]-x[i])/2.0
      xcoord[i,2] <- x[i] + (x[i+1]-x[i])/2.0
    }
  }

  for(i in 1:nrows){
    if(i == nrows){
      ycoord[i,1] <- y[i] - (y[i]-y[i-1])/2.0
      ycoord[i,2] <- y[i] + (y[i]-y[i-1])/2.0
    }else{
      ycoord[i,1] <- y[i] - (y[i+1]-y[i])/2.0
      ycoord[i,2] <- y[i] + (y[i+1]-y[i])/2.0
    }
  }

  colnum <- which(xin >= xcoord[,1] & xin < xcoord[,2])
  rownum <- which(yin >= ycoord[,1] & yin < ycoord[,2])

  if(length(dim(var)) == 3){
    var <- var[colnum, rownum, ]
  } else if (length(dim(var)) == 4){
    var <- var[colnum, rownum, , ]
  } else {
    print("Dimensions of the variable is greather than 4!")
  }

  return(var)

}