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-rw-r--r--R/mkinplot.R83
1 files changed, 67 insertions, 16 deletions
diff --git a/R/mkinplot.R b/R/mkinplot.R
index d2880c0..d665bc2 100644
--- a/R/mkinplot.R
+++ b/R/mkinplot.R
@@ -1,5 +1,6 @@
-mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$data$time), ylim = range(fit$data$observed, na.rm = TRUE), ...)
+mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$data$time), ylim = range(fit$data$observed, na.rm = TRUE), legend = TRUE, ...)
{
+ solution = fit$solution
fixed <- fit$fixed$value
names(fixed) <- rownames(fit$fixed)
parms.all <- c(fit$par, fixed)
@@ -16,12 +17,60 @@ mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$dat
rownames(subset(fit$fixed, type == "deparm")))
odeparms <- parms.all[odenames]
- # Solve the ode
- out <- ode(
- y = odeini,
- times = outtimes,
- func = fit$mkindiff,
- parms = odeparms)
+ # Solve the system
+ evalparse <- function(string)
+ {
+ eval(parse(text=string), as.list(c(odeparms, odeini)))
+ }
+ if (solution == "analytical") {
+ parent.type = names(fit$map[[1]])[1]
+ parent.name = names(fit$diffs)[[1]]
+ o <- switch(parent.type,
+ SFO = SFO.solution(outtimes,
+ evalparse(parent.name),
+ evalparse(paste("k", parent.name, "sink", sep="_"))),
+ FOMC = FOMC.solution(outtimes,
+ evalparse(parent.name),
+ evalparse("alpha"), evalparse("beta")),
+ DFOP = DFOP.solution(outtimes,
+ evalparse(parent.name),
+ evalparse("k1"), evalparse("k2"),
+ evalparse("g")),
+ HS = HS.solution(outtimes,
+ evalparse(parent.name),
+ evalparse("k1"), evalparse("k2"),
+ evalparse("tb")),
+ SFORB = SFORB.solution(outtimes,
+ evalparse(parent.name),
+ evalparse(paste("k", parent.name, "free_bound", sep="_")),
+ evalparse(paste("k", parent.name, "bound_free", sep="_")),
+ evalparse(paste("k", parent.name, "free_sink", sep="_")))
+ )
+ out <- cbind(outtimes, o)
+ dimnames(out) <- list(outtimes, c("time", parent.name))
+ }
+ if (solution == "eigen") {
+ coefmat.num <- matrix(sapply(as.vector(fit$coefmat), evalparse),
+ nrow = length(odeini))
+ e <- eigen(coefmat.num)
+ c <- solve(e$vectors, odeini)
+ f.out <- function(t) {
+ e$vectors %*% diag(exp(e$values * t), nrow=length(odeini)) %*% c
+ }
+ o <- matrix(mapply(f.out, outtimes),
+ nrow = length(odeini), ncol = length(outtimes))
+ dimnames(o) <- list(names(odeini), NULL)
+ out <- cbind(time = outtimes, t(o))
+ }
+ if (solution == "deSolve") {
+ out <- ode(
+ y = odeini,
+ times = outtimes,
+ func = fit$mkindiff,
+ parms = odeparms,
+ atol = fit$atol
+ )
+ }
# Output transformation for models with unobserved compartments like SFORB
out_transformed <- data.frame(time = out[,"time"])
@@ -36,14 +85,16 @@ mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$dat
# Plot the data and model output
plot(0, type="n",
xlim = xlim, ylim = ylim,
- xlab = xlab, ylab = ylab, ...)
- col_obs <- pch_obs <- 1:length(fit$map)
- names(col_obs) <- names(pch_obs) <- names(fit$map)
- for (obs_var in names(fit$map)) {
- points(subset(fit$data, variable == obs_var, c(time, observed)),
- pch = pch_obs[obs_var], col = col_obs[obs_var])
- }
- matlines(out_transformed$time, out_transformed[-1])
- legend("topright", inset=c(0.05, 0.05), legend=names(fit$map),
+ xlab = xlab, ylab = ylab, ...)
+ col_obs <- pch_obs <- 1:length(fit$map)
+ names(col_obs) <- names(pch_obs) <- names(fit$map)
+ for (obs_var in names(fit$map)) {
+ points(subset(fit$data, variable == obs_var, c(time, observed)),
+ pch = pch_obs[obs_var], col = col_obs[obs_var])
+ }
+ matlines(out_transformed$time, out_transformed[-1])
+ if (legend == TRUE) {
+ legend("topright", inset=c(0.05, 0.05), legend=names(fit$map),
col=col_obs, pch=pch_obs, lty=1:length(pch_obs))
+ }
}

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