\documentclass[article,nojss]{jss}
\DeclareGraphicsExtensions{.pdf,.eps, .jpg, .png}

\newcommand{\noun}[1]{\textsc{#1}}
%% Bold symbol macro for standard LaTeX users
\providecommand{\boldsymbol}[1]{\mbox{\boldmath $#1$}}

%% Because html converters don't know tabularnewline
\providecommand{\tabularnewline}{\\}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% User specified LaTeX commands.
\newcommand{\ov}{\textbf{\textsf{OceanView }}}
\newcommand{\R}{\proglang{R}}
\title{
  Package \pkg{OceanView}, visualisation of the output of a 3D hydrodynamic model.
}
\Plaintitle{Oceanview}

\Keywords{
  marine science, hydrodynamic models, 3-D data, 4-D data, quiver, image2D,
  \proglang{R}
}

\Plainkeywords{
marine science, hydrodynamic models, 3-D data, 4-D data, quiver, image2D,
R
}


\author{Karline Soetaert\\
NIOZ-Yerseke\\
The Netherlands
}

\Plainauthor{Karline Soetaert}

\Abstract{
  The \R{ }\citep{R2013} package \ov \citep{OceanView} is a compagnon package to the packages
  \pkg{plot3D} \citep{plot3D} and \pkg{plot3Drgl} \citep{plot3Drgl}. 
  These packages contain functions for visualising multidimensional data in 
  base R graphics (\pkg{plot3D}) or in openGL (\pkg{plot3Drgl}). 
  
  \ov is specifically designed for visualising complex oceanographic data.
  
  It can produce a.o. quiver plots, vector plots for visualising flows, 
  it can create movie sequences for depicting particle tracks in 2-D and 3-D, and so on ...
  
  Here we apply \ov for plotting the output of a 3-D hydrodynamic model of the 
  North Sea, as produced by the GETM software \citep{GETM}.  
}

%% The address of (at least) one author should be given
%% in the following format:
\Address{
  Karline Soetaert\\
  Royal Netherlands Institute of Sea Research (NIOZ)\\
  4401 NT Yerseke, Netherlands\\
  E-mail: \email{karline.soetaert@nioz.nl}\\
  URL: \url{http://http://www.nioz.nl/}
}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% R/Sweave specific LaTeX commands.
%% need no \usepackage{Sweave}
%\VignetteIndexEntry{OceanView: Visualising the output of a 3D hydrodynamical model}
%\VignetteKeyword{marine science}
%\VignetteKeyword{hydrodynamic models}
%\VignetteKeyword{3-D data}
%\VignetteKeyword{4-D data}
%\VignetteKeyword{quiver} 
%\VignetteKeyword{image2D}
%\VignettePackage{OceanView}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Begin of the document
\begin{document}




\maketitle

\section{Preamble}
This 'vignette' contains scripts to make figures of the output of the Northsea 
Model as created by the 3-D hydrodynamical model GETM \citep{GETM}. 

As the netcdf file with model output is very large (> 150 MB), 
it is not part of the package nor can it be downloaded. 
Hence you will not be able to recreate this vignette.

However, a similar (but significantly smaller) dataset, \code{Sylt3D} is part of 
the \ov package:

\begin{verbatim}
example(Sylt3D)
\end{verbatim}


\section{Reading data}
We use two packages here, \pkg{RNetCDF} \citep{RNetCDF} for reading netcdf files, 
\pkg{OceanView} \citep{OceanView} for visualising output.
Load the required packages: 
\begin{Schunk}
\begin{Sinput}
 library(RNetCDF)
 library(OceanView)
\end{Sinput}
\end{Schunk}

Open the NETCDF file with the output of the Northsea simulation,
 and print its content:
\footnote{Note: the text in \code{boxes} is the R-code; the text below boxes in this \code{format}
  (if any) is output, produced by \R.}
\begin{Schunk}
\begin{Sinput}
 d.nc <- open.nc( "ns_06nm_sept_1997_3d.nc")  
 print.nc(d.nc)
\end{Sinput}
\begin{Soutput}
dimensions:
        xc = 111 ;
        yc = 87 ;
        level = 26 ;
        time = UNLIMITED ; // (30 currently)
variables:
        int grid_type ;
        int vert_cord ;
        int ioff ;
                ioff:long_name = "index offset (i)" ;
        int joff ;
                joff:long_name = "index offset (j)" ;
        double dx ;
                dx:units = "m" ;
                dx:long_name = "grid spacing (x)" ;
        double dy ;
                dy:units = "m" ;
                dy:long_name = "grid spacing (y)" ;
        double xc(xc) ;
                xc:units = "m" ;
        double yc(yc) ;
                yc:units = "m" ;
        double lonc(xc, yc) ;
                lonc:units = "degrees_east" ;
                lonc:long_name = "longitude" ;
                lonc:valid_range = -180180 ;
                lonc:_FillValue = -999 ;
                lonc:missing_value = -999 ;
        double latc(xc, yc) ;
                latc:units = "degrees_north" ;
                latc:long_name = "latitude" ;
                latc:valid_range = -9090 ;
                latc:_FillValue = -999 ;
                latc:missing_value = -999 ;
        double convc(xc, yc) ;
                convc:units = "degrees" ;
                convc:long_name = "grid rotation" ;
                convc:valid_range = -180180 ;
                convc:_FillValue = -999 ;
                convc:missing_value = -999 ;
        double latu(xc, yc) ;
                latu:units = "degrees" ;
                latu:long_name = "latu" ;
                latu:valid_range = -9090 ;
                latu:_FillValue = -999 ;
                latu:missing_value = -999 ;
        double latv(xc, yc) ;
                latv:units = "degrees" ;
                latv:long_name = "latv" ;
                latv:valid_range = -9090 ;
                latv:_FillValue = -999 ;
                latv:missing_value = -999 ;
        double level(level) ;
                level:units = "level" ;
        double bathymetry(xc, yc) ;
                bathymetry:units = "m" ;
                bathymetry:long_name = "bathymetry" ;
                bathymetry:valid_range = -54000 ;
                bathymetry:_FillValue = -10 ;
                bathymetry:missing_value = -10 ;
        float time(time) ;
                time:units = "seconds since 1997-09-01 00:00:00" ;
                time:long_name = "time" ;
        float elev(xc, yc, time) ;
                elev:units = "m" ;
                elev:long_name = "elevation" ;
                elev:valid_range = -1515 ;
                elev:_FillValue = -9999 ;
                elev:missing_value = -9999 ;
        float u(xc, yc, time) ;
                u:units = "m/s" ;
                u:long_name = "int. zonal vel." ;
                u:valid_range = -33 ;
                u:_FillValue = -9999 ;
                u:missing_value = -9999 ;
        float v(xc, yc, time) ;
                v:units = "m/s" ;
                v:long_name = "int. meridional vel." ;
                v:valid_range = -33 ;
                v:_FillValue = -9999 ;
                v:missing_value = -9999 ;
        float h(xc, yc, level, time) ;
                h:units = "m" ;
                h:long_name = "layer thickness" ;
                h:_FillValue = -9999 ;
                h:missing_value = -9999 ;
        float hcc(xc, yc, level) ;
                hcc:units = "" ;
                hcc:long_name = "hcc" ;
                hcc:valid_range = 01 ;
                hcc:_FillValue = -1 ;
                hcc:missing_value = -1 ;
        float uu(xc, yc, level, time) ;
                uu:units = "m/s" ;
                uu:long_name = "zonal vel." ;
                uu:valid_range = -33 ;
                uu:_FillValue = -9999 ;
                uu:missing_value = -9999 ;
        float vv(xc, yc, level, time) ;
                vv:units = "m/s" ;
                vv:long_name = "meridional vel." ;
                vv:valid_range = -33 ;
                vv:_FillValue = -9999 ;
                vv:missing_value = -9999 ;
        float w(xc, yc, level, time) ;
                w:units = "m/s" ;
                w:long_name = "vertical vel." ;
                w:valid_range = -33 ;
                w:_FillValue = -9999 ;
                w:missing_value = -9999 ;
        float salt(xc, yc, level, time) ;
                salt:units = "PSU" ;
                salt:long_name = "salinity" ;
                salt:valid_range = 040 ;
                salt:_FillValue = -9999 ;
                salt:missing_value = -9999 ;
        float temp(xc, yc, level, time) ;
                temp:units = "degC" ;
                temp:long_name = "temperature" ;
                temp:valid_range = 040 ;
                temp:_FillValue = -9999 ;
                temp:missing_value = -9999 ;

// global attributes:
                :title = "North Sea - 6nm" ;
                :history = "Generated by getm, ver. 1.8.0" ;
\end{Soutput}
\end{Schunk}

\subsection{Reading the data}
The data are read:
\begin{Schunk}
\begin{Sinput}
 lat_c <- var.get.nc(d.nc, "latc")
 lon_c <- var.get.nc(d.nc, "lonc")
 time  <- var.get.nc(d.nc, "time")
 level <- var.get.nc(d.nc, "level")
 convc <- var.get.nc(d.nc, "convc")  
 xc    <- var.get.nc(d.nc, "xc") / 1000  # in km
 yc    <- var.get.nc(d.nc, "yc") / 1000
 dx    <- var.get.nc(d.nc, "dx") / 1000
 dy    <- var.get.nc(d.nc, "dy") / 1000
 hcc   <- var.get.nc(d.nc, "hcc")
 h     <- var.get.nc(d.nc, "h")
 bathy <- var.get.nc(d.nc, "bathymetry")
 # get 2-D data
 u     <- var.get.nc(d.nc, "u")
 v     <- var.get.nc(d.nc, "v")
 elev  <- var.get.nc(d.nc, "elev")
 temp  <- var.get.nc(d.nc, "temp")
 ww    <- var.get.nc(d.nc, "w")
 uu    <- var.get.nc(d.nc, "uu")
 vv    <- var.get.nc(d.nc, "vv")
\end{Sinput}
\end{Schunk}
Show some values: the grid spacing, and he ranges of the velocities:
:
\begin{Schunk}
\begin{Sinput}
 c(dx, dy)
\end{Sinput}
\begin{Soutput}
[1] 11.112 11.112
\end{Soutput}
\begin{Sinput}
 range(uu, na.rm = TRUE)
\end{Sinput}
\begin{Soutput}
[1] -1.217723  1.751082
\end{Soutput}
\begin{Sinput}
 range(vv, na.rm = TRUE)
\end{Sinput}
\begin{Soutput}
[1] -1.303300  2.244228
\end{Soutput}
\begin{Sinput}
 range(ww, na.rm = TRUE)
\end{Sinput}
\begin{Soutput}
[1] -0.01644286  0.02704342
\end{Soutput}
\end{Schunk}
\subsection{Box depths}

The output of the model lacks an output variable that has the depth, in the middle of
each compartment. It is created from the thickness of each box (h).
First we take the temporal mean of the box thicknesses:
\begin{Schunk}
\begin{Sinput}
 hh <- apply(h, MARGIN = 1:3, FUN = mean)
\end{Sinput}
\end{Schunk}
Then we take the cumulative sum of the box thicknesses. 
This gives the depth at the box interfaces:
\begin{Schunk}
\begin{Sinput}
 depth <- hh
 depth[ , ,1] <-  0
 for (i in 26:2) 
   depth[ , , i-1] <- depth[ , , i-1] + depth[ , , i]
\end{Sinput}
\end{Schunk}
Then we take the mean of the interfaces, to get the depth at the centre of a box.
\begin{Schunk}
\begin{Sinput}
 for (i in 2:26) 
   depth[ , , i] <- 0.5*(depth[ , , i-1] + depth[ , , i])
\end{Sinput}
\end{Schunk}
\clearpage
\section{Plot bathymetry and grid}
\code{jet2.col} from the package \code{plot3D} is a suitable color scheme, not too dark.
\begin{Schunk}
\begin{Sinput}
 par(mfrow = c(2, 2))
 col <- jet2.col(100)
 #
 # Plot every fourth grid point
 plot(x = lon_c[seq(1, length(lon_c), by = 4)], 
      y = lat_c[seq(1, length(lat_c), by = 4)], 
      xlab = "longitude", ylab = "latitude",
      pch = ".", main = "grid points")
 legend("bottom", legend = paste (c("x: ", "y: "), dim(lon_c)))
 #
 # Plot the bathymetry on the grid (distorted)
 image2D(bathy, x = xc, y = yc, NAcol = "black", 
       col = col, xlab = "km", ylab = "km",
       main = "Bathymetry on grid", clab = c("","","m"))
 #
 # The bathymetry on regular coordinates - shade emphasises bathymetry
 image2D(bathy, x = lon_c, y = lat_c, NAcol = "black", shade = 0.15,
       col = col, main = "Bathymetry on coordinates",
       xlab = "longitude", ylab = "latitude", clab = c("","","m"))
 #
 # add transect line
 lines(lon_c[30,], lat_c[30,]) # from where the sigma grid is plotted
 #
 # plot the sigma grid on transect line
 matplot(x = yc, depth[30,,], type = "l", col = "black", 
         main = "sigma grid", ylab = "depth, m", xlab = "y", 
         lty = 1, ylim = c(140, 0))
 lines(yc, bathy[30, ], lwd = 2, col = "red")
\end{Sinput}
\end{Schunk}

\setkeys{Gin}{width=1.0\textwidth}
\begin{figure}[h]
\begin{center}
\includegraphics{Northsea-bathy}
\end{center}
\caption{Bathymetry and grid}
\label{fig:fo}
\end{figure}

\subsection{Another bathymetric view}
Bathymetric data can also be plotted as perspective plots.
\begin{Schunk}
\begin{Sinput}
 par(mfrow = c(1, 1))
 # make bathymetry that does not have NAs (for z-values)
 D <- bathy ;  D[is.na(D)] <- 0
 persp3D(x = xc, y = yc, z = -D, colvar = -bathy, 
   col = "grey", shade = 0.5, scale = FALSE, phi = 80, 
   NAcol = grey(0.2), theta = 0, box = FALSE)
\end{Sinput}
\end{Schunk}
\setkeys{Gin}{width=1.0\textwidth}
\begin{figure}[h]
\begin{center}
\includegraphics{northsea-bathy2}
\end{center}
\caption{Bathymetry in perspective}
\label{fig:fo}
\end{figure}
To zoom, rotate, cut, try:
\begin{verbatim}
plotrgl()
plotdev(xlim = c(-100, 500), ylim = c(5667, 6300), zlim = c(-50,0), phi = 50)
\end{verbatim}
\clearpage

\section{integrated velocities}
The arrays \code{u}, \code{v} contain depth-average velocities, as they vary in time.
We calculate the average velocity over the 30 days of the simulation:
\begin{Schunk}
\begin{Sinput}
 U <- apply (u, FUN = mean, MARGIN = 1:2)
 V <- apply (v, FUN = mean, MARGIN = 1:2)
 meanV <- sqrt(U^2 + V^2)
\end{Sinput}
\end{Schunk}
We plot the average velocities as quivers on an image:
\begin{Schunk}
\begin{Sinput}
 par(mfrow = c(1, 1))
 image2D(z = meanV, x = lon_c, y = lat_c, 
       col = col, NAcol = grey(0.4), 
       main = "Mean velocity", clab = c("","","m/s"))
 quiver2D(U, V, x = lon_c, y = lat_c, add = TRUE, 
       by = 2, scale = 3, lwd = 2, arr.max = 0.3)
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-014}
Try this, and use left and right mousekey:
\begin{verbatim}
image2Drgl(z = meanV, x = lon_c, y = lat_c, 
      col = col, NAcol = grey(0.4), 
      main = "Mean velocity")
quiver2Drgl(U, V, x = lon_c, y = lat_c, add = TRUE, 
      by = 2, scale = 3, lwd = 2, arr.max = 0.2)
# select a rectangular region
cutrgl()      
\end{verbatim}

Velocity (log scale) draped on the bathymetry.
\begin{Schunk}
\begin{Sinput}
 persp3D(x = xc, y = yc, z = -D, colvar = meanV, 
   lighting = TRUE, scale = FALSE, phi = 80, box = FALSE, 
   log = "c", clab= "m/s", main = "Mean velocity", 
   NAcol = grey(0.2), theta = 0, inttype = 2)
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-015}

\clearpage
\section{Quivers at selected time points}
We can also easily visualise quivers at selected time points:
\begin{Schunk}
\begin{Sinput}
 tselect <- time[seq(from = 1, to = 30, by = 8)]
 par(oma = c(0, 0, 2, 0), las = 1)
 quiver2D(u, v, x = xc, y = yc, 
        subset = (time %in% tselect), 
        scale = 3, arr.max = 0.2, by = 3, mask = bathy, 
        NAcol = "darkgrey", main = paste("day ", tselect/86400))
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-016}

\clearpage
\section{surface elevation, for selected time steps}
To depict the surface elevation at 3 time points, we use \code{image2D}.
\begin{Schunk}
\begin{Sinput}
 zlim <- range(elev, na.rm = TRUE)
 tselect <- time[c(1, 10, 20)]
\end{Sinput}
\end{Schunk}
\begin{Schunk}
\begin{Sinput}
 par(oma = c(0, 0, 2, 0))
 pm <- par(mar = c(2, 2, 2, 0))
 image2D(elev, subset = (time %in% tselect), mfrow = c(2, 2), 
       NAcol = "black", axes = FALSE, xlab = "", ylab = "", 
       contour = TRUE, main = paste("day ", tselect/3600/24), 
       zlim = zlim, colkey = FALSE)
 colkey(clim = zlim, clab = "m")
 mtext (outer = TRUE, side = 3, "SURFACE ELEVATION", line = 0)
 par(mar = pm)
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-018}
The range of surface elevation, averaged over time is plotted, and contours 
are added:
\begin{Schunk}
\begin{Sinput}
 tidal.range <- apply(elev, MARGIN = 1:2, 
                      FUN = function(x) diff(range(x)))
\end{Sinput}
\end{Schunk}
\begin{Schunk}
\begin{Sinput}
 tselect <- time[seq(from = 1, to = 30, length.out = 9)]
 par(mfrow = c(1, 1))
 image2D(x = xc, y = yc, z = tidal.range, contour = TRUE, 
   NAcol = "darkgrey", clab = "m", main = "tidal range")
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-020}
\clearpage
\section{surface temperature, for selected time steps}
\code{temp} contains 3D temperature data at all time steps. 
The surface data are selected frist, and then plotted for a selection of time steps.
\begin{Schunk}
\begin{Sinput}
 surfTemp <- temp[ , , 26, ]
 zlim <- range(surfTemp, na.rm = TRUE)
\end{Sinput}
\end{Schunk}
\begin{Schunk}
\begin{Sinput}
 par(oma = c(0, 0, 2, 0))
 pm <- par(mar = c(2, 2, 2, 0))
 image2D(surfTemp, subset = (time %in% tselect), mfrow = c(3, 3), 
       NAcol = "darkgrey", axes = FALSE, xlab = "", ylab = "",
       main = paste("day ", tselect/3600/24), zlim = zlim, clab = "dg")
 mtext (outer = TRUE, side = 3, "SURFACE TEMPERATURE")
 par(mar = pm)
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-022}
\clearpage
\section{mean temperature along a NS-depth and a SW-depth transect}
For two transects, first the time-mean temperature is estimated (\code{apply}).
The temperature matrix is then converted from sigma coordinates to depth values 
(\code{mapsigma}), increasing the resolution (\code{resfac}).
Then the \code{image} is generated.
\begin{Schunk}
\begin{Sinput}
 par(oma = c(0, 0, 2, 0))
 par(mfrow = c(2, 1))
 TranTemp <- apply(temp[30 , , , ], MARGIN = 1:2, FUN = mean)
 MS <- mapsigma(TranTemp, sigma = depth[30, , ], x = yc, resfac = 2) 
 image2D(MS$var, y = MS$depth, x = MS$x, ylim = rev(range(MS$depth)), 
       NAcol = "black", ylab = "depth, m", xlab = "ypos, km", 
       main = "NS transect at x = 30", clab = c("","dgC"))
 TranTemp <- apply(temp[  , 68, , ], MARGIN = 1:2, FUN = mean)
 MS       <- mapsigma(TranTemp, sigma = depth[ ,68, ], x = xc, resfac = 2)
 image2D(MS$var, y = MS$depth, x = MS$x, ylim = rev(range(MS$depth)), 
       NAcol = "black", ylab = "depth, m", xlab = "xpos, km", 
       main = "EW transect at y = 68", clab = c("","dgC"))
 mtext (outer = TRUE, side = 3, "Temperature transects")
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-023}
\clearpage
\section{time-averaged vertical velocities at several depths}
Here we create the temporally averaged vertical velocities, at 
selected depth levels and remove the N and E points, as they are unstable:
\begin{Schunk}
\begin{Sinput}
 wmean <- apply(ww, MARGIN = 1:3, FUN = mean)
 subset.level <- c(2, 5, 15, 25)
 x.remove <- 105:111 ; y.remove <- 82:87
\end{Sinput}
\end{Schunk}
\begin{Schunk}
\begin{Sinput}
 par(oma = c(0, 0, 2, 0))
 image2D(wmean[-x.remove, -y.remove, ], NAcol = "black", 
       main = paste("depth level", subset.level), zlim = c(-1e-3, 4e-4),
       subset = (level %in% subset.level), clab = c("w","m/s"))
 mtext (outer = TRUE, side = 3, "Vertical velocity")
\end{Sinput}
\end{Schunk}
\includegraphics{northsea-025}
\clearpage
\section{time-averaged horizontal velocity vectors at several depths}
\code{uu} and \code{vv} contain 3D output of horizontal velocities 
at all time points. We first create temporally averaged velocities:
\begin{Schunk}
\begin{Sinput}
 umean <- apply(uu, MARGIN = 1:3, FUN = mean)
 vmean <- apply(vv, MARGIN = 1:3, FUN = mean)
\end{Sinput}
\end{Schunk}
The unstable N and E points are removed and a quiver produced:
\begin{Schunk}
\begin{Sinput}
 par(oma = c(0, 0, 2, 0))
 quiver2D(umean[-x.remove, -y.remove, ], vmean[-x.remove, -y.remove, ], 
        NAcol = "grey", mask = bathy[-x.remove, -y.remove], 
        main = paste("depth level", subset.level), by = 3,
        scale = 3, arr.max = 0.2, subset = (level %in% subset.level))
 mtext (outer = TRUE, side = 3, "Time-average flows")
\end{Sinput}
\end{Schunk}
\includegraphics{Northsea-027}
\clearpage
\section{NE and SW transects of time-averaged flows}
The vertical velocities are 1000 times smaller than the horizontal ones; 
so to produce the quiver plots, they are multiplied with 1000:
\begin{Schunk}
\begin{Sinput}
 par(mfrow = c(2, 1), mar = c(4, 4, 2, 2))
 # NS transect
 Tran.u <- mapsigma(umean[30 , -y.remove, ], sigma = depth[30, -y.remove,])
 Tran.w <- mapsigma(wmean[30 , -y.remove, ], sigma = depth[30, -y.remove,])
 TotVelo <- sqrt(Tran.u$var^2 + Tran.w$var^2 )
 DD <- Tran.w$depth
 # ranges of u and v
 range(Tran.u$var, na.rm = TRUE)
\end{Sinput}
\begin{Soutput}
[1] -0.09098173  0.12890817
\end{Soutput}
\begin{Sinput}
 range(Tran.w$var, na.rm = TRUE)
\end{Sinput}
\begin{Soutput}
[1] -7.923670e-05  7.631142e-05
\end{Soutput}
\begin{Sinput}
 #
 image2D(TotVelo, y = DD, x = yc[ -y.remove], col = col, 
       ylim = rev(range(DD)), NAcol = "black", resfac = 2,
       ylab = "depth, m", xlab = "ypos, km", 
       main = "NS transect at x = 30")
 quiver2D(Tran.u$var, Tran.w$var*1000, arr.min = 0.1, arr.max = 0.1,
        y = DD, x = yc[ -y.remove], 
        by = c(2,1), scale = 3, add = TRUE)
 #
 # EW transect
 Tran.v <- mapsigma(vmean[-x.remove , 68, ], sigma = depth[-x.remove, 68,])
 Tran.w <- mapsigma(wmean[-x.remove , 68, ], sigma = depth[-x.remove, 68,])
 TotVelo <- sqrt(Tran.v$var^2 + Tran.w$var^2 + 1e-8)
 DD <- Tran.w$depth
 image2D(TotVelo, y = DD, x = xc[ -x.remove], col = col, 
       ylim = rev(range(DD)), NAcol = "black", resfac = 2,
       ylab = "depth, m", xlab = "xpos, km", 
       main = "EW transect at y = 68")
 quiver2D(Tran.v$var, Tran.w$var*1000, arr.min = 0.1, arr.max = 0.1,
        y = DD, x = xc[ -x.remove], 
        by = c(2, 1), scale = 3, add = TRUE)
 mtext (outer = TRUE, side = 3, "Flow transects")
\end{Sinput}
\end{Schunk}
\includegraphics{northsea-028}

\section{plotting irregular transects, along a ship track}
Fot this figure, we will extract data along a (hypothetical) ship track:
\begin{Schunk}
\begin{Sinput}
 track <- cbind(seq(400, 600, length.out = 50),
                seq(6400, 6500, length.out = 50))
 # Draw the bathymetry on km grid
 par(mfrow = c(2, 2))
 image2D(bathy, x = xc, y = yc, NAcol = "black",
       xlim = c(200, 700), ylim = c(6100, 6600),
       col = col, xlab = "km", ylab = "km",
       clab = c("","","m"), main = "cruise track")
 # add track
 points(track, pch = ".", cex=3)
 # Depth on track
 trackBat <- extract(var = bathy, x = xc, y = yc, xyto = track)
 plot(x = trackBat$xy[,1], y =-trackBat$var, type = "l", xlab = "xc",
   ylab = "m", main = "bathymetry on track")
 # temperature
 Avgtemp <- apply(temp, MARGIN = 1:3, FUN = mean, na.rm = TRUE)
 tempSigma <- transectsigma(var = Avgtemp, sigma = depth, 
   x = as.vector(xc), y = as.vector(yc), to = track, resfac = 3)
 image2D(tempSigma$var, x = tempSigma$x, y = tempSigma$depth,
   ylim = rev(range(tempSigma$depth)), NAcol = "black",
   main = "temperature on track")
 # vertical velocity
 wSigma <- transectsigma(var = wmean, sigma = depth, 
   x = as.vector(xc), y = as.vector(yc), to = track, resfac = 3)
 image2D(wSigma$var, x = wSigma$x, y = wSigma$depth,
   ylim = rev(range(tempSigma$depth)), NAcol = "black",
   main = "vertical velocity on track")
\end{Sinput}
\end{Schunk}
\includegraphics{northsea-029}

\section{Finally}

This vignette was made with Sweave \citep{Leisch02}.

\clearpage
\bibliography{vignettes}

\end{document}
