## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", dev = "png", dev.args = list(type = "cairo-png"), fig.width = 5, fig.height = 5 * 5 / 7 # out.width = 250, # out.height = 250 ) options("bitmapType" = "cairo") ## ----setup-------------------------------------------------------------------- suppressPackageStartupMessages(library(fmesher)) set.seed(1234L) ## ----basic2,fig.cap="2D triangulation mesh"----------------------------------- domain <- cbind(rnorm(4, sd = 3), rnorm(4)) (mesh2 <- fm_mesh_2d( boundary = fm_extensions(domain, c(2.5, 5)), max.edge = c(0.5, 2) )) ## ----basic1,fig.cap="1D B-spline function space basis functions"-------------- (mesh1 <- fm_mesh_1d( c(0, 2, 4, 7, 10), boundary = "free", # c("neumann", "dirichlet"), degree = 2 )) ## ----lookup2------------------------------------------------------------------ pts <- cbind(rnorm(400, sd = 3), rnorm(400)) # Find what triangle each point is in, and it triangular Barycentric # coordinates bary <- fm_bary(mesh2, loc = pts) # How many points are outside the mesh? sum(is.na(bary$t)) head(bary$bary) # Evaluate basis functions basis <- fm_basis(mesh2, loc = pts) # Raw SparseMatrix basis_object <- fm_basis(mesh2, loc = pts, full = TRUE) # fm_basis object sum(!basis_object$ok) # Construct an evaluator object evaluator <- fm_evaluator(mesh2, loc = pts) sum(!fm_basis(evaluator, full = TRUE)$ok) # Values for the basis function weights; for ordinary 2d meshes this coincides # with the resulting values at the vertices, but this is not true for e.g. # 2nd order B-splines on 1d meshes. field <- mesh2$loc[, 1] value <- fm_evaluate(evaluator, field = field) sum(abs(pts[, 1] - value), na.rm = TRUE) ## ----lookup1,fig.cap="Evaluated 1D function"---------------------------------- pts1 <- seq(-2, 12, length.out = 1000) # Find what segment, and its interval Barycentric coordinates bary1 <- fm_bary(mesh1, loc = pts1) # Points outside the interval are treated differently depending on the # boundary conditions: sum(is.na(bary1$t)) head(bary1$bary) # Evaluate basis functions basis1 <- fm_basis(mesh1, loc = pts1) # Raw SparseMatrix basis1_object <- fm_basis(mesh1, loc = pts1, full = TRUE) # fm_basis object sum(!basis1_object$ok) # Construct an evaluator object. evaluator1 <- fm_evaluator(mesh1, loc = pts1) # mesh_1d basis functions are defined everywhere sum(!fm_basis(evaluator1, full = TRUE)$ok) # Values for the basis function weights; for ordinary 2d meshes this coincides # with the resulting values at the vertices, but this is not true for e.g. # 2nd order B-splines on 1d meshes. field1 <- rnorm(fm_dof(mesh1)) value1 <- fm_evaluate(evaluator1, field = field1) plot(pts1, value1, type = "l") ## ----fig.cap="2D triangulation mesh (base graphics version)"------------------ plot(mesh2) ## ----fig.cap="2D triangulation mesh (ggplot version)"------------------------- suppressPackageStartupMessages(library(ggplot2)) ggplot() + geom_fm(data = mesh2) ## ----fig.cap="1D B-spline function space basis functions with evaluated function (ggplot version)"---- ggplot() + geom_fm(data = mesh1, weights = field1 + 2, xlim = c(-2, 12)) + geom_fm(data = mesh1, linetype = 2, alpha = 0.5, xlim = c(-2, 12)) ## ----------------------------------------------------------------------------- fem1 <- fm_fem(mesh1, order = 2) names(fem1) fem2 <- fm_fem(mesh2, order = 2) names(fem2) ## ----sim,fig.cap="Simulated 2D Matérn field"---------------------------------- samp <- fm_matern_sample(mesh2, alpha = 2, rho = 4, sigma = 1)[, 1] evaluator <- fm_evaluator( mesh2, lattice = fm_evaluator_lattice(mesh2, dims = c(150, 50)) ) image(evaluator$x, evaluator$y, fm_evaluate(evaluator, field = samp), asp = 1)