- Some more unit tests

- Some more other tests in test.R
- Adaptation of mkinplot



git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@36 edb9625f-4e0d-4859-8d74-9fd3b1da38cb

2 files changed, 17 insertions, 80 deletions

diff --git a/R/mkinfit.R b/R/mkinfit.R
index 6e455e18..cb0396f7 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 d665bc23..789a6f98 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))
   }
 }