# $Id: $ # Copyright (C) 2010-2013 Johannes Ranke # Contact: jranke@uni-bremen.de # The summary function is an adapted and extended version of summary.modFit # from the FME package, v 1.1 by Soetart and Petzoldt, which was in turn # inspired by summary.nls.lm # This file is part of the R package mkin # mkin is free software: you can redistribute it and/or modify it under the # terms of the GNU General Public License as published by the Free Software # Foundation, either version 3 of the License, or (at your option) any later # version. # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU General Public License for more # details. # You should have received a copy of the GNU General Public License along with # this program. If not, see if(getRversion() >= '2.15.1') utils::globalVariables(c("type", "variable", "observed")) plot.mkinfit <- function(x, fit = x, xlab = "Time", ylab = "Observed", xlim = range(fit$data$time), ylim = c(0, max(fit$data$observed, na.rm = TRUE)), col_obs = 1:length(fit$mkinmod$map), pch_obs = col_obs, lty_obs = rep(1, length(fit$mkinmod$map)), add = FALSE, legend = !add, lpos = "topright", inset = c(0.05, 0.05), ...) { solution_type = fit$solution_type parms.all <- c(fit$bparms.optim, fit$bparms.fixed) ininames <- c( rownames(subset(fit$start, type == "state")), rownames(subset(fit$fixed, type == "state"))) odeini <- parms.all[ininames] names(odeini) <- names(fit$mkinmod$diffs) outtimes <- seq(xlim[1], xlim[2], length.out=100) odenames <- c( rownames(subset(fit$start, type == "deparm")), rownames(subset(fit$fixed, type == "deparm"))) odeparms <- parms.all[odenames] out <- mkinpredict(fit$mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, atol = fit$atol, rtol = fit$rtol, ...) # Set up the plot if not to be added to an existing plot if (add == FALSE) { plot(0, type="n", xlim = xlim, ylim = ylim, xlab = xlab, ylab = ylab, ...) } # Plot the data and model output names(col_obs) <- names(pch_obs) <- names(lty_obs) <- names(fit$mkinmod$map) for (obs_var in names(fit$mkinmod$map)) { points(subset(fit$data, variable == obs_var, c(time, observed)), pch = pch_obs[obs_var], col = col_obs[obs_var]) } matlines(out$time, out[-1], col = col_obs, lty = lty_obs) if (legend == TRUE) { legend(lpos, inset= inset, legend=names(fit$mkinmod$map), col=col_obs, pch=pch_obs, lty=lty_obs) } }