diff options
author | Johannes Ranke <jranke@uni-bremen.de> | 2020-10-26 14:23:04 +0100 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2020-10-26 14:23:04 +0100 |
commit | b81cd4b32c8411637f31164cc696a471b1074baa (patch) | |
tree | 6da1066ff09111710a32ec98f3f156f532e3db4b /R | |
parent | 9bfc85d605ae54623f63b7e3cdb36f5ac64876c1 (diff) |
Put the legend in its own area for plot.nlme.mmkin
Diffstat (limited to 'R')
-rw-r--r-- | R/nlme.R | 6 | ||||
-rw-r--r-- | R/nlme.mmkin.R | 2 | ||||
-rw-r--r-- | R/plot.nlme.mmkin.R | 46 |
3 files changed, 34 insertions, 20 deletions
@@ -48,8 +48,12 @@ #' start = mean_dp) #' summary(m_nlme) #' plot(augPred(m_nlme, level = 0:1), layout = c(3, 1)) -#' # augPred does not seem to work on fits with more than one state +#' # augPred does not work on fits with more than one state #' # variable +#' # +#' # The procedure is greatly simplified by the nlme.mmkin function +#' f_nlme <- nlme(f) +#' plot(f_nlme) #' #' @return A function that can be used with nlme #' @export diff --git a/R/nlme.mmkin.R b/R/nlme.mmkin.R index 22a70f18..d3369cf5 100644 --- a/R/nlme.mmkin.R +++ b/R/nlme.mmkin.R @@ -55,6 +55,7 @@ get_deg_func <- function() { #' 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)) #' update(f_nlme_2, random = parent_0 ~ 1) @@ -101,6 +102,7 @@ get_deg_func <- function() { #' AIC(f_nlme_sfo, f_nlme_sfo_tc, f_nlme_dfop, f_nlme_dfop_tc) #' print(f_nlme_dfop_tc) #' } +#' #' f_2_obs <- mmkin(list("SFO-SFO" = m_sfo_sfo, #' "DFOP-SFO" = m_dfop_sfo), #' ds_2, quiet = TRUE, error_model = "obs") 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")), |