sl.grid.reduce: Remove Nodes (and Elements) From an Unstructured Grid

In helgegoessling/spheRlab: Spherical Geometry, Analysis, and Plotting of Geoscientific Data on Arbitrary Grids

Remove Nodes (and Elements) From an Unstructured Grid

Description

Remove nodes and corresponding elements from an unstructured grid. Nodes that are left without any adjacent element are removed as well. Neighbourhood information is updated accordingly.

Usage

sl.grid.reduce(grd, remove.points, set.coast = TRUE, set.openbound = FALSE, return.info = TRUE, auto.reduce = TRUE)

Arguments

grd	a spheRlab grid list as returned by sl.grid.readFESOM or sl.grid.curvilin2unstr. Must contain at least the following list-elements: elem (Ne x Me matrix; Melem=3 in case of a triangular grid), neighnodes (Nnn x Mnn matrix), and neighelems (Nne x Mne matrix). These matrices can contain NAs in the respective right-most columns. If auto.reduce=TRUE, additional list-elements in grd that are vectors are reduced as well whereby their length is used to detect whether they hold information valid for nodes or for elements.
remove.points	an integer or logical vector specifying the nodes to be removed. Note that additional nodes are removed if they end up without adjacent elements.
set.coast	a logical value specifying whether to flag nodes adjacent to removed elements (due to the removal of nodes) as coastal in grd$coast.
set.openbound	a logical value specifying whether to flag nodes adjacent to removed elements (due to the removal of nodes) as open boundary nodes in grd$openbound.
return.info	a logical value specifying whether to return the indices of which nodes and elements of the original grid have been kept. Can be used e.g. to extract corresponding data values valid for the unreduced grid.
auto.reduce	a logical value specifying whether to reduce additional list-elements in grd that are vectors. If so, the vector length is used to detect whether the list-elements hold information valid for nodes or for elements.

Details

If auto.reduce=TRUE, additional list-elements in grd that are vectors are reduced as well whereby their length is used to detect whether they hold information valid for nodes or for elements.

Value

a grid list with the same (partly modified) elements as grd. If return.info=TRUE, an additional element reduce.kept with sub-elements nodes and elems providing the indices of nodes and elements of the original grid that have been kept.

Author(s)

Helge Goessling

See Also

sl.grid.curvilin2unstr, sl.grid.mergepoints

Examples

# generate an example curvilinear grid
lon.0 = seq(-60,60,5)
lat.0 = seq(-30,30,5)
grd.0 = sl.grid.curvilin2unstr(lon = lon.0, lat = lat.0)
abg = sl.lonlatrot2abg(c(5,-20,0))
rot.lonlat = sl.rot(lon = grd.0$lon, lat = grd.0$lat, alpha = abg[1], beta = abg[2], gamma = abg[3])
grd = grd.0
grd$lon = rot.lonlat$lon
grd$lat = rot.lonlat$lat

# generate corresponding example data and insert NAs that define a land mask (arbitrary,
# not matching true land coordinates)
dat = exp(-((sl.gc.dist(lon = c(180,grd$lon), lat = c(85,grd$lat), sequential = FALSE)/0.4)^2))
dat.orig = dat
dat[c(7,140,250)] = NA
for (i in 1:2) {
  for (j in which(is.na(dat))) {
    dat[grd$neighnodes[j,]] = NA
  }
}

# remove land nodes from the grid
grd.reduced = sl.grid.reduce(grd = grd, remove.points = is.na(dat), return.info = TRUE)

# compute the 0.15-contour on the reduced grid
cont = sl.contours(var = dat[grd.reduced$reduce.kept$nodes], elem = grd.reduced$elem, levels = 0.15, neighmat = grd.reduced$neighnodes, lon = grd.reduced$lon, lat = grd.reduced$lat)

# plot
pir = sl.plot.init(projection = "polar", do.init.device = FALSE, col.background = "lightgrey")
cb1 = sl.plot.field.elem(pir, dat.orig, lon = grd$lon, lat=grd$lat, elem=grd$elem,
colbar = sl.colbar(cols=c("red","yellow")))
cb2 = sl.plot.field.elem(pir, dat[grd.reduced$reduce.kept$nodes], lon = grd.reduced$lon,
lat = grd.reduced$lat, elem = grd.reduced$elem, colbar = sl.colbar(cols=c("darkblue","white")))
cont = sl.contours(var = dat[grd.reduced$reduce.kept$nodes], elem = grd.reduced$elem,
levels = 0.15, neighmat = grd.reduced$neighnodes, lon = grd.reduced$lon, lat = grd.reduced$lat)
sl.plot.contours(pir, cont, col = "white", lwd = 2)
sl.plot.end(pir, do.close.device = FALSE)

helgegoessling/spheRlab documentation built on April 8, 2024, 8:34 a.m.