## Time-stamp: "Last modified 2024-04-11 15:28:06 delucia" ## Compile the fortran code. On Linux, if a fortran compiler is ## installed, it should work out of the box setwd("/home/work/simR/Rphree/SpecSim/") system("R CMD SHLIB SS_Sim.f SS_Vario.f -o SSlib.so") dyn.load("SSlib.so") ## Load the functions source("SS_Fun_sim.R") source("SS_Fun_vario.R") setwd("/home/work/simR/Rphree/NAAICE_tug_input/build") library(lattice) library(PoetUtils) PlotField2 <- function (data, grid, nx, ny, contour = TRUE, nlevels = 12, breaks, palette = "heat.colors", rev.palette = TRUE, scale = TRUE, plot.axes = TRUE, ...) { if (!missing(grid)) { xc <- unique(sort(grid$cell$XCOORD)) yc <- unique(sort(grid$cell$YCOORD)) nx <- length(xc) ny <- length(yc) if (!length(data) == nx * ny) stop("Wrong nx, ny or grid") } else { xc <- seq(1, nx) yc <- seq(1, ny) } z <- matrix(round(data, 6), ncol = nx, nrow = ny, byrow = TRUE) pp <- t(z[rev(seq(1, nrow(z))), ]) if (missing(breaks)) { breaks <- pretty(data, n = nlevels) } breakslen <- length(breaks) colors <- do.call(palette, list(n = breakslen - 1)) if (rev.palette) colors <- rev(colors) if (scale) { par(mfrow = c(1, 2)) nf <- layout(matrix(c(1, 2), 1, 2, byrow = TRUE), widths = c(4, 1)) } par(las = 1, mar = c(5, 5, 3, 1)) image(xc, yc, pp, las = 1, asp = 1, breaks = breaks, col = colors, axes = FALSE, ann = plot.axes, ...) if (plot.axes) { axis(1) axis(2) } if (contour) contour(unique(sort(xc)), unique(sort(yc)), pp, breaks = breaks, add = TRUE) if (scale) { par(las = 1, mar = c(5, 1, 5, 5)) PlotImageScale(data, breaks = breaks, add.axis = FALSE, axis.pos = 4, col = colors) axis(4, at = breaks) } invisible(pp) } ## generate a grid. At the moment it must be a cartesian square grid ## with number of cells a power of two, e.g. 128, 256, ... n <- 256 ## we want a 256x256 grid ## Simple structure describing the simulation grid gr <- SS.Grid(nodes=n, side=100) ## fix the seed of RNG for reproducibility set.seed(64276) ## Extract the random numbers (uniform distribution between 0 and 1) ## once and for all randoms <- runif(n**2) ## Anisotropic SpectralSimulations with 2 different isotropic correlation lengths ## using the same random numbers. Here "range" is in meters! a1 <- SS.Sim(vec.rn = randoms, nugget=0., sill=1, type="spherical", range=20, ratio=8, angle = -30, grid=gr, normalize=TRUE) ## Compute the experimental variograms ONLY in X and Y direction. ## "lag" refers to the nodes on one side of the grid, not meters! variog1 <- SS.Vario(a1, grid=gr, lag=2, nstep=72) ## Visualize # cairo_pdf("Spherical_40_80.pdf", height=9, width=9) par(mfrow=c(1,2)) SS.Plot(a1, grid=gr, main="Range 20 m, anisotropy ratio 4", axes=FALSE) axis(1, at=c(-100, 0, 100)) axis(2, at=c(-100, 0, 100)) SS.VarioPlot(vario=variog1, main="Experimental Variograms", lwd=2) lines(variog1$htrue, SS.Spherical(variog1$htrue, range=20, sill=1), col="blue") lines(variog1$htrue, SS.Spherical(variog1$htrue, range=20/4, sill=1), col="red") sim1 <- matrix(a1, n, n) levelplot(sim1) cut1 <- sim1[1:200, 1:200] levelplot(cut1) sd(cut1) mean(cut1) ax <- 1E-6*(cut1 - min(cut1))/max(cut1)+1E-7 ay <- 1E-7*(cut1 - min(cut1))/max(cut1)+1E-7 sd(ax) mean(ax) sd(ay) mean(ay) range(ax) range(ay) PlotField2(log10(ax), nx=200, ny=200, contour = FALSE, xaxs="i", yaxs="i", nlevels=6, plot.axes = FALSE) title(expression(log[10](alpha[x]))) levelplot(log10(t(ax))) levelplot(log10(ay)) data.table::fwrite(ax, "alpha_x.csv", col.names = FALSE) data.table::fwrite(ay, "alpha_y.csv", col.names = FALSE) init <- c(110.01240000000783,55.50867875567298,-1.2162968960604385e-9,4.455329999159673e-7,2.0000000000005577e-12,0.0006151616266928334,0.0006147160946983908) names <- c("H","O","Charge","Ba","Cl","S_6_","Sr") inmat <- matrix(rep(init, 200*200), nrow = 200*200, byrow = TRUE) colnames(inmat) <- names data.table::fwrite(inmat, "barite_200_init.csv", col.names = TRUE) library(PoetUtils) out <- fread("../../build/barite_200_output.csv") cairo_pdf("barite_200_field_alphax.pdf", width = 9, height = 6, family="serif") PlotField2(log10(ax), nx=200, ny=200, contour = FALSE, nlevels=10, palette = "heat.colors", rev.palette = FALSE, plot.axes = FALSE, main=expression(log[10](Sr))) dev.off() cairo_pdf("barite_200_field_Ba.pdf", width = 9, height = 6, family="serif") PlotField2(log10(out$Ba), nx=200, ny=200, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE, main=expression(log[10](Sr))) dev.off() PlotField2(log10(out$H), nx=200, ny=200, contour = FALSE, palette = "terrain.colors", nlevels=10, plot.axes = FALSE, main=expression(log[10](Sr))) PlotField2(out$S_6_, nx=200, ny=200, contour = FALSE, nlevels=10, plot.axes = FALSE, main=expression(log[10](Ba))) ###################### barite large alphamat <- matrix(1e-6, nrow = 1000, ncol = 1000) data.table::fwrite(alphamat, "barite_large_alpha.csv", col.names = FALSE) init <- c(110.0124, 55.508678, -1.216296896e-9, 4.45533e-7, 0, 0.0006151616, 0.0006147161) nams <- c("H","O","Charge","Ba","Cl","S_6_","Sr") names(init) <- nams n <- 1000 inmat <- matrix(rep(init, 1000*1000-n), nrow = 1000*1000 - n, byrow = TRUE) colnames(inmat) <- nams bounds <- c(111.0124, 55.50622, -3.0E-07, 1, 2, 0.01, 0.001) names(bounds) <- nams bmat <- matrix(rep(bounds, n), nrow = n, byrow = TRUE) colnames(bmat) <- nams set.seed(9342) inds <- sample(seq_len(1E6), size=1E6) dim(inmat) dim(bmat) totmat <- rbind(bmat, inmat) dim(totmat) fmat <- totmat[inds, ] xc <- rep(seq(1, 1000), times = 1000) yc <- rep(seq(1, 1000), each = 1000) iplot <- which(fmat[,"Cl"]==2) plot(xc[iplot], 1000-yc[iplot], pch=4, cex=0.5, xaxs="i",yaxs="i") cairo_pdf("barite_large_init_locs.pdf", width = 6, height = 6, family="serif") par(mar=c(1,1,0.5,0.5)) plot(xc[iplot], yc[iplot], pch=4, cex=0.5, las=1, xaxs="i", yaxs="i", xlab="Easting", ylab="Northig", asp=1, axes = FALSE) box() dev.off() data.table::fwrite(fmat, "barite_large_init.csv", col.names = TRUE) out <- fread("../../build/barite_large_output.csv") x11() cairo_pdf("barite_large_field_Ba.pdf", width = 8, height = 6, family="serif") ##par(mar=c(4,4,0.5,0.5)) PlotField2(log10(out$Ba), nx=1000, ny=1000, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE) box() dev.off() init round(rbind(init, bounds), 3) ##### surfex, grid 500x250 nx <- 200 ny <- 100 alphamat <- matrix(1.1e-12, nrow = ny, ncol = nx) data.table::fwrite(alphamat, "surfex_alpha.csv", col.names = FALSE) a <- read.table( textConnection( "H 1.11e+02 120.0, O 5.55e+01 55.1, Charge -2.0e-13 8.0e-17, C(-4) 2.0e-16 2.0e-15, C(4) 2.0e-03 0.2, Ca 2.0e-01 0.03, Cl 3.0e-01 0.5, Fe(2) 1.4e-04 0.0002, Fe(3) 1.3e-09 2.0e-08, H(0) 6.0e-12 2.0e-11, K 2.0e-03 1.0e-05, Mg 1.0e-02 0.2, Na 2.0e-01 0.3, S(-2) 5.9e-10 0, S(2) 8.3e-15 8.3e-12, S(4) 2.1e-14 5.1e-14, S(6) 1.6e-02 0.026, Sr 4.5e-04 0.045, U(4) 2.5e-09 2.5e-08, U(5) 1.6e-10 1.6e-10, U(6) 2.3e-07 1.0e-05" )) vals <- t(a[, 2:3]) nams <- c("H", "O", "Charge", "CH4", "C", "Ca", "Cl", "Fe2", "Fe3", "H0", "K", "Mg", "Na", "HS2", "S2", "S4", "S6","Sr", "U4", "U5", "U6") colnames(vals) <- nams rownames(vals) <- c("IC", "BC") vals length(nams) dim(vals) t(vals) ic <- matrix(rep(vals[1,], nx*ny), nrow = nx*ny, byrow = TRUE) colnames(ic) <- nams data.table::fwrite(ic, "surfex_init.csv", col.names = TRUE) dput(vals[2,]) out <- fread("../../build/surfex_output.csv") x11() cairo_pdf("surfex_field_U6.pdf", width = 10, height = 6, family="serif") out <- fread("../../build/surfex_output.csv") PlotField2(log10(out$U6), nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "cm.colors", plot.axes = FALSE, rev.palette = FALSE) dev.off() cairo_pdf("surfex_field_Na.pdf", width = 10, height = 6, family="serif") out <- fread("../../build/surfex_output.csv") PlotField2(out$Na, nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "topo.colors", plot.axes = FALSE, rev.palette = TRUE) dev.off() PlotField2(log10(out$U4), nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE) out$U4[seq(50*200, 51*200)] PlotField2(out$Na, nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE) out$Na[seq(50*200, 51*200)] out$Cl[seq(50*200, 51*200)] PlotField2(log10(out$Fe2), nx=nx, ny=ny, contour = FALSE, nlevels=12, palette = "terrain.colors", plot.axes = FALSE) PlotField2((out$Cl), nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE) dev.off() ##### debug, grid 200x100 nx <- 200 ny <- 100 alphamat <- matrix(1.1e-11, nrow = ny, ncol = nx) data.table::fwrite(alphamat, "debug_alpha.csv", col.names = FALSE) a <- read.table( textConnection( "H 1.11e+02 120.0, O 5.55e+01 55.1, Charge -2.0e-13 8.0e-17, C(-4) 2.0e-16 2.0e-15, C(4) 2.0e-03 0.2, Ca 2.0e-01 0.03, Cl 3.0e-01 0.5, Fe(2) 1.4e-04 0.0002, Fe(3) 1.3e-09 2.0e-08, H(0) 6.0e-12 2.0e-11, K 2.0e-03 1.0e-05, Mg 1.0e-02 0.2, Na 2.0e-01 0.3, S(-2) 5.9e-10 0, S(2) 8.3e-15 8.3e-12, S(4) 2.1e-14 5.1e-14, S(6) 1.6e-02 0.026, Sr 4.5e-04 0.045, U(4) 2.5e-09 2.5e-08, U(5) 1.6e-10 1.6e-10, U(6) 2.3e-07 1.0e-05" )) vals <- t(a[, 2:3]) nams <- c("H", "O", "Charge", "CH4", "C", "Ca", "Cl", "Fe2", "Fe3", "H0", "K", "Mg", "Na", "HS2", "S2", "S4", "S6","Sr", "U4", "U5", "U6") colnames(vals) <- nams rownames(vals) <- c("IC", "BC") vals length(nams) dim(vals) t(vals) ic <- matrix(rep(vals[1,], nx*ny), nrow = nx*ny, byrow = TRUE) colnames(ic) <- nams data.table::fwrite(ic, "debug_init.csv", col.names = TRUE) dput(vals[2,]) out <- fread("debug_output.csv") x11() ## cairo_pdf("debug_field_U6.pdf", width = 10, height = 6, family="serif") # out <- fread("./debug_output.csv") PlotField2(log10(out$U6), nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "cm.colors", plot.axes = FALSE, rev.palette = FALSE) ##dev.off() ## cairo_pdf("debug_field_Na.pdf", width = 10, height = 6, family="serif") out2 <- fread("./debug_output.csv") PlotField2(out2$Na, nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "topo.colors", plot.axes = FALSE, rev.palette = TRUE) ## dev.off() out2$Na[seq(1, 200)] range(out2$Na) PlotField2(log10(out$U4), nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE) out$U4[seq(50*200, 51*200)] PlotField2(out2$Fe3, nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE) out2$Na[seq(20*200, 21*200)] out$Cl[seq(50*200, 51*200)] PlotField2(log10(out$Fe2), nx=nx, ny=ny, contour = FALSE, nlevels=12, palette = "terrain.colors", plot.axes = FALSE) PlotField2((out$Cl), nx=nx, ny=ny, contour = FALSE, nlevels=10, palette = "terrain.colors", plot.axes = FALSE) dev.off() library(Rcpp) cppFunction("static const std::vector gen_seq(int from, int to) { int vsize = to - from + 1; std::vector vec(vsize); for (int i = 0; i < vsize; i++) { vec[i] = i+from; } return vec; }") gen_seq(24, 49) cppFunction("static const std::vector gen_vec(int elems) { std::vector vec(elems); for (int i = 0; i < elems; i++) { vec[i] = i; } return vec; }") gen_vec(20)