trackit_3D: Trackit 3D

In janjansen86/ptrackr: Tracking Individual Particles Through 2D- and 3D-Space

Description

Function to track particles through a 3D ROMS-field.

Usage

trackit_3D(pts, romsobject, w_sink = 100, time = 50, romsparams = NULL,
  loop_trackit = FALSE, time_steps_in_s = 1800)

Arguments

pts	input points
w_sink	sinking rate m/days
time	total number of days to run the model
loop_trackit	Default is FALSE, automatically turns TRUE when called from loopit_2D3D
kdtree	kd tree

Details

Due to the limitation of RAM available, time is restricted depending on the number of particles (too long runs might give an error because the generated vector is too large)

Value

list(ptrack = ptrack, pnow = pnow, plast = plast, stopindex = stopindex, indices = indices, indices_2D = indices_2D)

Examples

data(surface_chl)
data(toyROMS)
pts <- create_points_pattern(surface_chl, multi=100)
track <- trackit_3D(pts = pts, romsobject = toyROMS)

## checking the results
plot(pts)
points(track$pnow, col = "red")

# library(rgl)
# plot3d(pts, zlim = c(-1500,1))
# plot3d(track$pnow, col = "red", add = TRUE)

## better:
library(rasterVis)
library(rgdal)

ra <- raster(nrow = 50, ncol = 50, ext = extent(surface_chl))
r_roms <- rasterize(x = cbind(as.vector(toyROMS$lon_u), as.vector(toyROMS$lat_u)), y = ra, field = as.vector(-toyROMS$h))
pr <- projectRaster(r_roms, crs = "+proj=laea +lon_0=137 +lat_0=-66")  #get the right projection (through the centre)

plot3D(pr, adjust = FALSE, zfac = 50)                    # plot bathymetry with 50x exaggerated depth
points <- matrix(NA, ncol=3, nrow=dim(track$ptrack)[1])  # get Tracking-points
for(i in seq_len(dim(track$ptrack)[1])){
  points[i,] <- track$ptrack[i,,track$stopindex[i]] 
}
pointsxy <- project(as.matrix(points[,1:2]), projection(pr))  #projection on Tracking-points
points3d(pointsxy[,1], pointsxy[,2], points[,3]*50)

ptsxy <- project(as.matrix(pts[,1:2]), projection(pr))  #projection on Tracking-points
points3d(ptsxy[,1], ptsxy[,2], pts[,3]*50, col = "red")

janjansen86/ptrackr documentation built on May 18, 2019, 2:38 p.m.