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# $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 <http://www.gnu.org/licenses/>
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$fixed, type == "state")))
odeini <- parms.all[ininames]
# Order initial state variables
names(odeini) <- sub("_0", "", names(odeini))
odeini <- odeini[names(fit$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)
}
}
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