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# $Id: kinplot.R 117 2011-06-14 08:52:14Z kati $
# Copyright (C) 2008-2013 Johannes Ranke
# Contact: mkin-devel@lists.berlios.de
# This file is part of the R package kinfit
# kinfit 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/>
utils::globalVariables("x")
kinplot <- function(kinobject,
main = "",
xlab = "Time [days]", ylab = "Parent [% of applied radioactivity]",
ylim = c("auto", "auto"),
lpos = "topright")
{
kindata <- na.omit(kinobject$data)
kinfits <- kinobject$fits
if (ylim[1] == "auto") ylim[1] <- 0
if (ylim[2] == "auto") ylim[2] <- max(kindata$parent)
ylim <- as.numeric(ylim)
plot(kindata$t, kindata$parent,
main = main,
xlab = xlab,
ylab = ylab,
ylim = ylim
)
n.m <- length(kinfits)
colors <- ltys <- 1:n.m
names(colors) <- names(ltys) <- names(kinfits)
ltext <- paste(kinobject$parent, "measured")
for (kinmodel in names(kinfits))
{
m = kinfits[[kinmodel]]
if(class(m) == "nls") {
if (!"parent.0" %in% names(coef(m))) {
switch(kinmodel,
SFO = lines(
t <- seq(min(kindata$t), max(kindata$t), length.out=500),
predict(m,
newdata = data.frame(t)),
col = colors[[kinmodel]],
lty = ltys[[kinmodel]]),
FOMC = lines(
t <- seq(min(kindata$t), max(kindata$t), length.out=500),
predict(m,
newdata = data.frame(t)),
col = colors[[kinmodel]],
lty = ltys[[kinmodel]]),
HS = lines(
t <- seq(min(kindata$t), max(kindata$t), length.out=500),
predict(m,
newdata = data.frame(t)),
col = colors[[kinmodel]],
lty = ltys[[kinmodel]]),
DFOP = lines(
t <- seq(min(kindata$t), max(kindata$t), length.out=500),
predict(m,
newdata = data.frame(t)),
col = colors[[kinmodel]],
lty = ltys[[kinmodel]])
)
ltext <- c(ltext, paste("Fitted", kinmodel, "model"))
} else {
switch(kinmodel,
SFO = curve(SFO(x,
coef(m)[["parent.0"]],
coef(m)[["k"]]),
from = min(kindata$t), to = max(kindata$t), add=TRUE,
col = colors[[kinmodel]],
lty = ltys[[kinmodel]]),
FOMC = curve(FOMC(x,
coef(m)[["parent.0"]],
coef(m)[["alpha"]],
coef(m)[["beta"]]),
from = min(kindata$t), to = max(kindata$t), add=TRUE,
col = colors[[kinmodel]],
lty = ltys[[kinmodel]]),
HS = curve(HS(x,
coef(m)[["parent.0"]],
coef(m)[["k1"]],
coef(m)[["k2"]],
coef(m)[["tb"]]),
from = min(kindata$t), to = max(kindata$t), add=TRUE,
col = colors[[kinmodel]],
lty = ltys[[kinmodel]]),
DFOP = curve(DFOP(x,
coef(m)[["parent.0"]],
coef(m)[["k1"]],
coef(m)[["k2"]],
coef(m)[["g"]]),
from = min(kindata$t), to = max(kindata$t), add=TRUE,
col = colors[[kinmodel]],
lty = ltys[[kinmodel]]))
ltext <- c(ltext, paste("Fitted", kinmodel, "model"))
}
} else {
ltext <- c(ltext, paste(kinmodel, "model failed"))
ltys[[kinmodel]] <- NA
}
}
legend(lpos, bty="n", inset = 0.05,
legend = ltext,
pch = c(1, rep(NA, n.m)),
lty = c(NA, ltys),
col = c(1, colors))
}
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