Fix a bug for nlme with parent only, improve examples

2 files changed, 10 insertions, 32 deletions

diff --git a/R/nlme.mmkin.R b/R/nlme.mmkin.R
index d4720e79..22a70f18 100644
--- a/R/nlme.mmkin.R
+++ b/R/nlme.mmkin.R
@@ -53,6 +53,7 @@ get_deg_func <- function() {
 #' f_nlme_dfop <- nlme(f["DFOP", ])
 #' AIC(f_nlme_sfo, f_nlme_dfop)
 #' print(f_nlme_dfop)
+#' plot(f_nlme_dfop)
 #' endpoints(f_nlme_dfop)
 #' \dontrun{
 #'   f_nlme_2 <- nlme(f["SFO", ], start = c(parent_0 = 100, log_k_parent = 0.1))
@@ -63,58 +64,36 @@ get_deg_func <- function() {
 #'     A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE)
 #'   m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
 #'     A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE)
-#'   m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-#'     A1 = mkinsub("SFO"), quiet = TRUE)
 #'   m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
 #'     A1 = mkinsub("SFO"), quiet = TRUE)
 #'
 #'   f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo,
 #'    "SFO-SFO-ff" = m_sfo_sfo_ff,
-#'    "FOMC-SFO" = m_fomc_sfo,
 #'    "DFOP-SFO" = m_dfop_sfo),
 #'     ds_2, quiet = TRUE)
-#'   plot(f_2["SFO-SFO", 3:4]) # Separate fits for datasets 3 and 4
 #'
 #'   f_nlme_sfo_sfo <- nlme(f_2["SFO-SFO", ])
-#'   # plot(f_nlme_sfo_sfo) # not feasible with pkgdown figures
-#'   plot(f_nlme_sfo_sfo, 3:4) # Global mixed model: Fits for datasets 3 and 4
+#'   plot(f_nlme_sfo_sfo)
 #'
 #'   # With formation fractions
 #'   f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])
-#'   plot(f_nlme_sfo_sfo_ff, 3:4) # chi2 different due to different df attribution
+#'   plot(f_nlme_sfo_sfo_ff)
 #'
-#'   # For more parameters, we need to increase pnlsMaxIter and the tolerance
+#'   # For the following fit we need to increase pnlsMaxIter and the tolerance
 #'   # to get convergence
-#'   f_nlme_fomc_sfo <- nlme(f_2["FOMC-SFO", ],
-#'     control = list(pnlsMaxIter = 100, tolerance = 1e-4), verbose = TRUE)
 #'   f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
 #'     control = list(pnlsMaxIter = 120, tolerance = 5e-4), verbose = TRUE)
-#'   plot(f_2["FOMC-SFO", 3:4])
-#'   plot(f_nlme_fomc_sfo, 3:4)
 #'
-#'   plot(f_2["DFOP-SFO", 3:4])
-#'   plot(f_nlme_dfop_sfo, 3:4)
+#'   plot(f_nlme_dfop_sfo)
 #'
-#'   anova(f_nlme_dfop_sfo, f_nlme_fomc_sfo, f_nlme_sfo_sfo)
-#'   anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo) # if we ignore FOMC
+#'   anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo)
 #'
 #'   endpoints(f_nlme_sfo_sfo)
 #'   endpoints(f_nlme_dfop_sfo)
 #'
 #'   if (length(findFunction("varConstProp")) > 0) { # tc error model for nlme available
-#'     # Attempts to fit metabolite kinetics with the tc error model
-#'     #f_2_tc <- mmkin(list("SFO-SFO" = m_sfo_sfo,
-#'     #  "SFO-SFO-ff" = m_sfo_sfo_ff,
-#'     #  "FOMC-SFO" = m_fomc_sfo,
-#'     #  "DFOP-SFO" = m_dfop_sfo),
-#'     #   ds_2, quiet = TRUE,
-#'     #   error_model = "tc")
-#'     #f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ], control = list(maxIter = 100))
-#'     #f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ])
-#'     #f_nlme_dfop_sfo_tc <- update(f_nlme_dfop_sfo, weights = varConstProp(),
-#'     #  control = list(sigma = 1, msMaxIter = 100, pnlsMaxIter = 15))
-#'     # Fitting metabolite kinetics with nlme.mmkin and the two-component
-#'     # error model currently does not work, at least not with these data.
+#'     # Attempts to fit metabolite kinetics with the tc error model are possible,
+#'     # but need tweeking of control values and sometimes do not converge
 #'
 #'     f_tc <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, error_model = "tc")
 #'     f_nlme_sfo_tc <- nlme(f_tc["SFO", ])
diff --git a/R/plot.nlme.mmkin.R b/R/plot.nlme.mmkin.R
index 2356070e..223aba68 100644
--- a/R/plot.nlme.mmkin.R
+++ b/R/plot.nlme.mmkin.R
@@ -99,7 +99,7 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
       transform_fractions = fit_1$transform_fractions)
 
     odeini <- degparms_all[ds_i, odeini_names]
-    names(odeini) <- gsub("_0", "", names(odeini))
+    names(odeini) <- gsub("_0", "", odeini_names)
 
     out <- mkinpredict(x$mkinmod, odeparms, odeini,
       outtimes, solution_type = solution_type,
@@ -116,7 +116,7 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
     transform_fractions = fit_1$transform_fractions)
 
   odeini_pop <- degparms_all_pop[odeini_names]
-  names(odeini_pop) <- gsub("_0", "", names(odeini_pop))
+  names(odeini_pop) <- gsub("_0", "", odeini_names)
 
   pred_pop <- as.data.frame(
     mkinpredict(x$mkinmod, odeparms_pop, odeini_pop,
@@ -171,7 +171,6 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
       maxabs = max(abs(observed_row$residual), na.rm = TRUE)
     }
 
-
     if (identical(resplot, "time")) {
       plot(0, type = "n", xlim = xlim, xlab = "Time",
         ylim = c(-1.2 * maxabs, 1.2 * maxabs),