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authorJohannes Ranke <jranke@uni-bremen.de>2020-10-26 14:23:04 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2020-10-26 14:23:04 +0100
commitb81cd4b32c8411637f31164cc696a471b1074baa (patch)
tree6da1066ff09111710a32ec98f3f156f532e3db4b /R/plot.nlme.mmkin.R
parent9bfc85d605ae54623f63b7e3cdb36f5ac64876c1 (diff)
Put the legend in its own area for plot.nlme.mmkin
Diffstat (limited to 'R/plot.nlme.mmkin.R')
-rw-r--r--R/plot.nlme.mmkin.R46
1 files changed, 27 insertions, 19 deletions
diff --git a/R/plot.nlme.mmkin.R b/R/plot.nlme.mmkin.R
index a27f0caa..afb682a7 100644
--- a/R/plot.nlme.mmkin.R
+++ b/R/plot.nlme.mmkin.R
@@ -5,11 +5,10 @@ if(getRversion() >= '2.15.1') utils::globalVariables("ds")
#' @param x An object of class \code{\link{nlme.mmkin}}
#' @param i A numeric index to select datasets for which to plot the nlme fit,
#' in case plots get too large
-#' @param main The main title placed on the outer margin of the plot.
#' @inheritParams plot.mkinfit
-#' @param legends An index for the fits for which legends should be shown.
#' @param standardized Should the residuals be standardized? Only takes effect if
#' `resplot = "time"`.
+#' @param rel.height.legend The relative height of the legend shown on top
#' @param rel.height.bottom The relative height of the bottom plot row
#' @param ymax Vector of maximum y axis values
#' @param \dots Further arguments passed to \code{\link{plot.mkinfit}} and
@@ -31,6 +30,7 @@ if(getRversion() >= '2.15.1') utils::globalVariables("ds")
#' A1 = mkinsub("SFO"), quiet = TRUE)
#' f <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, cores = 1)
#' plot(f[, 3:4], standardized = TRUE)
+#'
#' library(nlme)
#' # For this fit we need to increase pnlsMaxiter, and we increase the
#' # tolerance in order to speed up the fit for this example evaluation
@@ -38,15 +38,15 @@ if(getRversion() >= '2.15.1') utils::globalVariables("ds")
#' plot(f_nlme)
#' @export
plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
- main = NULL,
obs_vars = names(x$mkinmod$map),
standardized = TRUE,
xlab = "Time",
xlim = range(x$data$time),
- legends = 1,
- lpos = "topright", inset = c(0.05, 0.05),
resplot = c("predicted", "time"),
ymax = "auto", maxabs = "auto",
+ ncol.legend = ifelse(length(i) <= 3, length(i) + 1, ifelse(length(i) <= 8, 3, 4)),
+ nrow.legend = ceiling((length(i) + 1) / ncol.legend),
+ rel.height.legend = 0.03 + 0.08 * nrow.legend,
rel.height.bottom = 1.1,
pch_ds = 1:length(i),
col_ds = pch_ds + 1,
@@ -65,7 +65,7 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
names(degparms_fixed) <- rownames(fit_1$fixed)
degparms_all <- cbind(as.matrix(degparms_optim),
matrix(rep(degparms_fixed, nrow(degparms_optim)),
- ncol = length(degparms_fixed),
+ ncol = length(degparms_fixed),
nrow = nrow(degparms_optim), byrow = TRUE))
degparms_all_names <- c(degparms_optim_names, names(degparms_fixed))
colnames(degparms_all) <- degparms_all_names
@@ -81,14 +81,27 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
n_plot_rows = length(obs_vars)
n_plots = n_plot_rows * 2
- # Set relative plot heights, so the first and the last plot are the norm
- # and the middle plots (if n_plot_rows >2) are smaller by rel.height.middle
- rel.heights <- if (n_plot_rows > 1) c(rep(1, n_plot_rows - 1), rel.height.bottom) else 1
+ # Set relative plot heights, so the first plot row is the norm
+ rel.heights <- if (n_plot_rows > 1) {
+ c(rel.height.legend, c(rep(1, n_plot_rows - 1), rel.height.bottom))
+ } else {
+ c(rel.height.legend, 1)
+ }
- layout_matrix = matrix(1:n_plots,
- n_plot_rows, 2, byrow = TRUE)
+ layout_matrix = matrix(c(1, 1, 2:(n_plots + 1)),
+ n_plot_rows + 1, 2, byrow = TRUE)
layout(layout_matrix, heights = rel.heights)
+ par(mar = c(0.1, 2.1, 0.6, 2.1))
+
+ plot(0, type = "n", axes = FALSE, ann = FALSE)
+ legend("center", bty = "n", ncol = ncol.legend,
+ legend = c("Population", ds_names[i]),
+ lty = c(1, lty_ds), lwd = c(2, rep(1, length(i))),
+ col = c(1, col_ds),
+ pch = c(NA, pch_ds))
+
+
solution_type = fit_1$solution_type
outtimes <- sort(unique(c(x$data$time,
@@ -96,6 +109,7 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
pred_ds <- purrr::map_dfr(i, function(ds_i) {
odeparms_trans <- degparms_all[ds_i, odeparms_names]
+ names(odeparms_trans) <- odeparms_names # needed if only one odeparm
odeparms <- backtransform_odeparms(odeparms_trans,
x$mkinmod,
transform_rates = fit_1$transform_rates,
@@ -162,14 +176,6 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
col = col_ds[ds_i], lty = lty_ds[ds_i])
}
- if (plot_row %in% legends) {
- legend(lpos, inset = inset,
- legend = c("Population", ds_names[i]),
- lty = c(1, lty_ds), lwd = c(2, rep(1, length(i))),
- col = c(1, col_ds),
- pch = c(NA, pch_ds))
- }
-
if (identical(maxabs, "auto")) {
maxabs = max(abs(observed_row$residual), na.rm = TRUE)
}
@@ -194,6 +200,8 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
ylim = c(-1.2 * maxabs, 1.2 * maxabs),
ylab = if (standardized) "Standardized residual" else "Residual")
+ abline(h = 0, lty = 2)
+
for (ds_i in seq_along(i)) {
observed_row_ds <- merge(
subset(observed_row, ds == ds_names[ds_i], c("time", "residual")),

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