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authorJohannes Ranke <jranke@uni-bremen.de>2023-03-22 07:49:39 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2023-03-22 07:49:39 +0100
commit81bb17f887f192a5ee4f77829a65689934776471 (patch)
tree2f8560bb50983696ad278480b430c8349961cf9f /R/plot.mixed.mmkin.R
parent28286eeaca84c85d2f4c3cddc9524d56d23b9aa0 (diff)
Fix plotting saemix without covariates, polish
Better linetypes and labels
Diffstat (limited to 'R/plot.mixed.mmkin.R')
-rw-r--r--R/plot.mixed.mmkin.R15
1 files changed, 11 insertions, 4 deletions
diff --git a/R/plot.mixed.mmkin.R b/R/plot.mixed.mmkin.R
index 68f8d577..466e55fc 100644
--- a/R/plot.mixed.mmkin.R
+++ b/R/plot.mixed.mmkin.R
@@ -13,7 +13,9 @@ utils::globalVariables("ds")
#' In case there is a covariate model, the behaviour depends on the value
#' of 'covariates'
#' @param covariates Data frame with covariate values for all variables in
-#' any covariate models in the object. If given, it overrides 'covariate_quantiles'
+#' any covariate models in the object. If given, it overrides 'covariate_quantiles'.
+#' Each line in the data frame will result in a line drawn for the population.
+#' Rownames are used in the legend to label the lines.
#' @param covariate_quantiles This argument only has an effect if the fitted
#' object has covariate models. If so, the default is to show three population
#' curves, for the 5th percentile, the 50th percentile and the 95th percentile
@@ -77,7 +79,7 @@ plot.mixed.mmkin <- function(x,
obs_vars = names(x$mkinmod$map),
standardized = TRUE,
covariates = NULL,
- covariate_quantiles = c(0.05, 0.5, 0.95),
+ covariate_quantiles = c(0.5, 0.05, 0.95),
xlab = "Time",
xlim = range(x$data$time),
resplot = c("predicted", "time"),
@@ -151,6 +153,10 @@ plot.mixed.mmkin <- function(x,
covariates = as.data.frame(
apply(x$covariates, 2, quantile,
covariate_quantiles, simplify = FALSE))
+ rownames(covariates) <- paste(
+ ifelse(length(x$covariate_models) == 1,
+ "Covariate", "Covariates"),
+ rownames(covariates))
}
degparms_pop <- parms(x, covariates = covariates)
pop_curves <- TRUE
@@ -160,9 +166,10 @@ plot.mixed.mmkin <- function(x,
}
}
- # Make sure degparms_pop is a matrix, population curve variants in columns, if any
+ # Make sure degparms_pop is a matrix, columns corresponding to population curve(s)
if (is.null(dim(degparms_pop))) {
- degparms_pop <- matrix(degparms_pop)
+ degparms_pop <- matrix(degparms_pop, ncol = 1,
+ dimnames = list(names(degparms_pop), "Population"))
}
degparms_fixed <- fit_1$fixed$value

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