diff options
Diffstat (limited to 'R')
| -rw-r--r-- | R/mkinfit.R | 15 | ||||
| -rw-r--r-- | R/mkinplot.R | 82 |
2 files changed, 17 insertions, 80 deletions
diff --git a/R/mkinfit.R b/R/mkinfit.R index 6e455e1..cb0396f 100644 --- a/R/mkinfit.R +++ b/R/mkinfit.R @@ -170,13 +170,11 @@ mkinfit <- function(mkinmod, observed, # We need to return some more data for summary and plotting
fit$solution_type <- solution_type
- if (solution_type == "eigen") {
- fit$coefmat <- mkinmod$coefmat
- }
- # We also need various other information for summary and plotting
- fit$map <- mkinmod$map
- fit$diffs <- mkinmod$diffs
+ # We also need the model for summary and plotting
+ fit$mkinmod <- mkinmod
+
+ # We need data and predictions for summary and plotting
fit$observed <- mkin_long_to_wide(observed)
predicted_long <- mkin_wide_to_long(out_predicted, time = "time")
fit$predicted <- out_predicted
@@ -348,6 +346,7 @@ summary.mkinfit <- function(object, data = TRUE, distimes = TRUE, ...) { Rversion = paste(R.version$major, R.version$minor, sep="."),
date.fit = object$date,
date.summary = date(),
+ use_of_ff = object$mkinmod$use_of_ff,
residuals = object$residuals,
residualVariance = resvar,
sigma = sqrt(resvar),
@@ -358,7 +357,7 @@ summary.mkinfit <- function(object, data = TRUE, distimes = TRUE, ...) { stopmess = message,
par = param)
- ans$diffs <- object$diffs
+ ans$diffs <- object$mkinmod$diffs
if(data) ans$data <- object$data
ans$start <- object$start
@@ -411,7 +410,7 @@ print.summary.mkinfit <- function(x, digits = max(3, getOption("digits") - 3), . }
printff <- !is.null(x$ff)
- if(printff){
+ if(printff & x$use_of_ff == "min"){
cat("\nEstimated formation fractions:\n")
print(data.frame(ff = x$ff), digits=digits,...)
}
diff --git a/R/mkinplot.R b/R/mkinplot.R index d665bc2..789a6f9 100644 --- a/R/mkinplot.R +++ b/R/mkinplot.R @@ -1,14 +1,14 @@ mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$data$time), ylim = range(fit$data$observed, na.rm = TRUE), legend = TRUE, ...) { - solution = fit$solution + solution_type = fit$solution_type fixed <- fit$fixed$value names(fixed) <- rownames(fit$fixed) - parms.all <- c(fit$par, fixed) + parms.all <- c(fit$parms.all, fixed) ininames <- c( rownames(subset(fit$start, type == "state")), rownames(subset(fit$fixed, type == "state"))) odeini <- parms.all[ininames] - names(odeini) <- names(fit$diffs) + names(odeini) <- names(fit$mkinmod$diffs) outtimes <- seq(xlim[1], xlim[2], length.out=100) @@ -17,84 +17,22 @@ mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$dat rownames(subset(fit$fixed, type == "deparm"))) odeparms <- parms.all[odenames] - # 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"]) - for (var in names(fit$map)) { - if(length(fit$map[[var]]) == 1) { - out_transformed[var] <- out[, var] - } else { - out_transformed[var] <- rowSums(out[, fit$map[[var]]]) - } - } + out <- mkinpredict(fit$mkinmod, odeparms, odeini, outtimes, + solution_type = solution_type, ...) # 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$map)) { + col_obs <- pch_obs <- 1:length(fit$mkinmod$map) + names(col_obs) <- names(pch_obs) <- names(fit$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_transformed$time, out_transformed[-1]) + matlines(out$time, out[-1]) if (legend == TRUE) { - legend("topright", inset=c(0.05, 0.05), legend=names(fit$map), + legend("topright", inset=c(0.05, 0.05), legend=names(fit$mkinmod$map), col=col_obs, pch=pch_obs, lty=1:length(pch_obs)) } } |