# Plot of the Results of Sobol' Sensitivity Analysis for Objects of Class `ODEsobol` `plot.ODEsobol` plots the results of Sobol' SA for objects of class `ODEsobol`. ```r ## S3 method for class 'ODEsobol' plot(x, pars_plot = NULL, state_plot = names(x)[1], colors_pars = NULL, main_title = NULL, legendPos = "outside", type = "l", ...) ``` ## Arguments - `x`: [`ODEsobol`] output of `ODEsobol` (of class `ODEsobol`). - `pars_plot`: [`character(k)`] names of the `k` parameters to be plotted. If `NULL` (the default), all parameters are plotted. - `state_plot`: [`character(1)`] name of the state variable to be plotted. Defaults to the name of the first state variable. - `colors_pars`: [`character(>= k)`] vector of the colors to be used for the `k` different parameters. Must be at least of length `k` (only the first `k` elements will be used, though). If `NULL` (the default), `rainbow(k)` is used. - `main_title`: [`character(1)`] common title for the two graphics. Default is `NULL`, which means an automatic title is generated. - `legendPos`: [`character(1)`] keyword for the legend position, either one of those specified in `legend` or `"outside"` (the default), which means the legend is placed under the plot (useful, if there are many parameters in the model). - `type`: [`character(1)`] plot type, i.e. `"p", "l", "b", "c", "o", "s", "h"` or `"n"`. Defaults to `"l"`. - `...`: additional arguments passed to `plot.default`. ## Returns TRUE (invisible; for testing purposes). ## Details First order and total Sobol' sensitivity indices are plotted for one state variable (chosen by argument `state_plot`) and the parameters named in `pars_plot` against time. If no parameters are named in `pars_plot`, the sensitivity indices for all parameters are plotted. ## Note Not all arguments of `plot.default` can be passed by `...`, for example `xlab` and `ylab` are fixed. ## Examples ```r ##### Lotka-Volterra equations ##### LVmod <- function(Time, State, Pars) { with(as.list(c(State, Pars)), { Ingestion <- rIng * Prey * Predator GrowthPrey <- rGrow * Prey * (1 - Prey/K) MortPredator <- rMort * Predator dPrey <- GrowthPrey - Ingestion dPredator <- Ingestion * assEff - MortPredator return(list(c(dPrey, dPredator))) }) } LVpars <- c("rIng", "rGrow", "rMort", "assEff", "K") LVbinf <- c(0.05, 0.05, 0.05, 0.05, 1) LVbsup <- c(1.00, 3.00, 0.95, 0.95, 20) LVinit <- c(Prey = 1, Predator = 2) LVtimes <- c(0.01, seq(1, 50, by = 1)) set.seed(59281) # Warning: The following code might take very long! LVres_sobol <- ODEsobol(mod = LVmod, pars = LVpars, state_init = LVinit, times = LVtimes, n = 500, rfuncs = "runif", rargs = paste0("min = ", LVbinf, ", max = ", LVbsup), sobol_method = "Martinez", ode_method = "lsoda", parallel_eval = TRUE, parallel_eval_ncores = 2) my_cols <- c("firebrick", "orange2", "dodgerblue", "forestgreen", "black") plot(LVres_sobol, colors_pars = my_cols) plot(LVres_sobol, pars_plot = c("rGrow", "rMort"), state_plot = "Predator", colors_pars = my_cols[2:3]) ##### A network of 4 mechanical oscillators connected in a circle ##### M_mat <- rep(2, 4) K_mat <- diag(rep(2 * (2*pi*0.17)^2, 4)) K_mat[1, 2] <- K_mat[2, 3] <- K_mat[3, 4] <- K_mat[1, 4] <- 2 * (2*pi*0.17)^2 / 10 D_mat <- diag(rep(0.05, 4)) library("ODEnetwork") lfonet <- ODEnetwork(masses = M_mat, dampers = D_mat, springs = K_mat) LFOpars <- c("k.1", "k.2", "k.3", "k.4", "d.1", "d.2", "d.3", "d.4") LFObinf <- c(rep(0.2, 4), rep(0.01, 4)) LFObsup <- c(rep(20, 4), rep(0.1, 4)) lfonet <- setState(lfonet, state1 = rep(2, 4), state2 = rep(0, 4)) LFOtimes <- seq(25, 150, by = 2.5) set.seed(1739) # Warning: The following code might take very long! suppressWarnings( LFOres_sobol <- ODEsobol(mod = lfonet, pars = LFOpars, times = LFOtimes, n = 500, rfuncs = "runif", rargs = paste0("min = ", LFObinf, ", max = ", LFObsup), sobol_method = "Martinez", parallel_eval = TRUE, parallel_eval_ncores = 2) ) plot(LFOres_sobol, pars_plot = paste0("k.", 1:4), state_plot = "x.2", colors_pars = my_cols) ``` ## See Also `ODEsobol, soboljansen, sobolmartinez` ## Author(s) Stefan Theers, Frank Weber

plot.ODEsobol function