kinplot <- function(kinobject,
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$parent,
xlab = xlab,
ylab = ylab,
ylim = ylim
)
n.m <- length(kinfits)
colors <- ltys <- 1:n.m
names(colors) <- names(ltys) <- names(kinfits)
ltext <- paste(kinobject$parent, "measured")
for (kinmodel in names(kinfits))
{
m = kinfits[[kinmodel]]
if(class(m) == "nls") {
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))
}
