- 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

4 files changed, 95 insertions, 83 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))
   }
 }
diff --git a/TODO b/TODO
index fb8b80d6..2577d8ef 100644
--- a/TODO
+++ b/TODO
@@ -1,11 +1,11 @@
 Must have:
-- Adapt mkinplot function
+- Some more testing with coupled models with FOMC, DFOP, HS and SFORB for parent
+- Some testing with SFORB for metabolites
 
 Nice to have:
-- Fix remaining problem with the schaefer complex test data (test.R: fit.2.eigen)
 - Calculate confidence intervals for parameters assuming normal distribution
 - Calculate confidence intervals for DT50 and DT90 values when only one parameter is involved
-- Add unit tests for mkinfit
+- Add more unit tests for mkinfit
 - Document validation against fits documented in chapter 13 of FOCUS (2006)
 - Reproduce example anaylses (L1, L2, ...) in FOCUS (2006)
 - Generate confidence intervals for DT50 and DT90 values for other cases
diff --git a/inst/unitTests/runit.mkinfit.R b/inst/unitTests/runit.mkinfit.R
index 2030f852..e2fc8c3f 100644
--- a/inst/unitTests/runit.mkinfit.R
+++ b/inst/unitTests/runit.mkinfit.R
@@ -222,6 +222,43 @@ test.FOCUS_2006_SFORB <- function()
   checkIdentical(dev.B.SFORB.2 < 1, rep(TRUE, length(dev.B.SFORB.2)))

 } # }}}

 

+# Test SFO_SFO model with FOCUS_2006_D against Schaefer 2007 paper, tolerance = 1% # {{{

+test.FOCUS_2006_D_SFO_SFO <- function()

+{

+  SFO_SFO.1 <- mkinmod(parent = list(type = "SFO", to = "m1"),

+         m1 = list(type = "SFO"), use_of_ff = "min")

+  SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"),

+         m1 = list(type = "SFO"), use_of_ff = "max")

+

+  fit.1.e <- mkinfit(SFO_SFO.1, FOCUS_2006_D)

+  fit.1.d <- mkinfit(SFO_SFO.1, solution_type = "deSolve", FOCUS_2006_D)

+  #fit.2.e <- mkinfit(SFO_SFO.2, FOCUS_2006_D, plot=TRUE)

+  SFO <- mkinmod(parent = list(type = "SFO"))

+  f.SFO <- mkinfit(SFO, FOCUS_2006_D)

+  #fit.2.e <- mkinfit(SFO_SFO.2, parms.ini = f.SFO$odeparms.final, FOCUS_2006_D)

+  fit.2.d <- mkinfit(SFO_SFO.2, solution_type = "deSolve", FOCUS_2006_D)

+  # Eigenvalue based solution with maximum use of formation fractions only 

+  # works correctly with initial parameters very close to final parameters!

+  fit.2.e <- mkinfit(SFO_SFO.2, parms.ini = fit.2.d$odeparms.final, FOCUS_2006_D)

+

+  FOCUS_2006_D_results_schaefer07_means <- c(

+    parent_0 = 99.65, DT50_parent = 7.04, DT50_m1 = 131.34)

+

+  r.1.e <- c(fit.1.e$parms.all[[1]], fit.1.e$distimes[[1]])

+  r.1.d <- c(fit.1.d$parms.all[[1]], fit.1.d$distimes[[1]])

+  r.2.e <- c(fit.2.e$parms.all[[1]], fit.2.e$distimes[[1]])

+  r.2.d <- c(fit.2.d$parms.all[[1]], fit.2.d$distimes[[1]])

+

+  dev.1.e <- 100 * (r.1.e - FOCUS_2006_D_results_schaefer07_means)/r.1.e 

+  checkIdentical(as.numeric(abs(dev.1.e)) < 1, rep(TRUE, 3))

+  dev.1.d <- 100 * (r.1.d - FOCUS_2006_D_results_schaefer07_means)/r.1.d 

+  checkIdentical(as.numeric(abs(dev.1.d)) < 1, rep(TRUE, 3))

+  dev.2.e <- 100 * (r.2.e - FOCUS_2006_D_results_schaefer07_means)/r.2.e 

+  checkIdentical(as.numeric(abs(dev.2.e)) < 1, rep(TRUE, 3))

+  dev.2.d <- 100 * (r.2.d - FOCUS_2006_D_results_schaefer07_means)/r.2.d 

+  checkIdentical(as.numeric(abs(dev.2.d)) < 1, rep(TRUE, 3))

+} # }}}

+

 # Test eigenvalue based fit to Schaefer 2007 data against solution from conference paper {{{

 test.mkinfit.schaefer07_complex_example <- function()

 {

@@ -258,4 +295,42 @@ test.mkinfit.schaefer07_complex_example <- function()
   checkIdentical(r$mkin.deviation < 10, rep(TRUE, length(r$mkin.deviation)))

 } # }}}

 

+# Test deSolve based fit to Schaefer 2007 data against solution from conference paper {{{

+test.mkinfit.schaefer07_complex_example <- function()

+{

+  schaefer07_complex_model <- mkinmod(

+    parent = list(type = "SFO", to = c("A1", "B1", "C1"), sink = FALSE),

+    A1 = list(type = "SFO", to = "A2"),

+    B1 = list(type = "SFO"),

+    C1 = list(type = "SFO"),

+    A2 = list(type = "SFO"))

+  

+  # Works fine with n.outtimes = 1000 but takes too much time

+  #   fit <- mkinfit(schaefer07_complex_model, 

+  #     mkin_wide_to_long(schaefer07_complex_case, time = "time"), 

+  #     n.outtimes = 1000, solution_type = "deSolve")

+  #   s <- summary(fit)

+  #   r <- schaefer07_complex_results

+  #   attach(as.list(fit$parms.all))

+  #   k_parent <- sum(k_parent_A1, k_parent_B1, k_parent_C1)

+  #   r$mkin <- c(

+  #     k_parent,

+  #     s$distimes["parent", "DT50"],

+  #     s$ff["parent_A1"],

+  #     sum(k_A1_sink, k_A1_A2),

+  #     s$distimes["A1", "DT50"],

+  #     s$ff["parent_B1"],

+  #     k_B1_sink,

+  #     s$distimes["B1", "DT50"],

+  #     s$ff["parent_C1"],

+  #     k_C1_sink,

+  #     s$distimes["C1", "DT50"],

+  #     s$ff["A1_A2"],

+  #     k_A2_sink,

+  #     s$distimes["A2", "DT50"])

+  #   r$means <- (r$KinGUI + r$ModelMaker)/2

+  #   r$mkin.deviation <- abs(round(100 * ((r$mkin - r$means)/r$means), digits=1))

+  #   checkIdentical(r$mkin.deviation < 10, rep(TRUE, length(r$mkin.deviation)))

+} # }}}

+

 # vim: set foldmethod=marker ts=2 sw=2 expandtab: