update docs

NAMESPACE

@@ -25,4 +25,5 @@ importFrom(ggplot2,geom_smooth)
 importFrom(ggplot2,ggplot)
 importFrom(ggplot2,guide_legend)
 importFrom(ggplot2,guides)
+importFrom(ggplot2,scale_y_continuous)
 useDynLib(epikinetics, .registration = TRUE)

R/epikinetics-package.R

@@ -11,7 +11,7 @@
 #' @importFrom data.table .NGRP
 #' @importFrom data.table .SD
 #' @importFrom data.table data.table
-#' @importFrom ggplot2 aes facet_wrap geom_point geom_ribbon geom_line geom_smooth ggplot guides guide_legend
+#' @importFrom ggplot2 aes facet_wrap geom_point geom_ribbon geom_line geom_smooth ggplot guides guide_legend scale_y_continuous
 #' @useDynLib epikinetics, .registration = TRUE
 ## usethis namespace: end
 

R/plot.R

@@ -23,12 +23,12 @@ plot_prior_predictive <- function(priors,
     validate_required_cols(data, c("time_since_last_exp", "value"))
   }
   params <- data.table(
-    t0 = rnorm(n_draws, priors$mu_t0, priors$sigma_t0), # titre value at t0
-    tp = rnorm(n_draws, priors$mu_tp, priors$sigma_tp), # time of peak
-    ts = rnorm(n_draws, priors$mu_ts, priors$sigma_ts), # time of set point
-    m1 = rnorm(n_draws, priors$mu_m1, priors$sigma_m1), # gradient 1
-    m2 = rnorm(n_draws, priors$mu_m2, priors$sigma_m2), # gradient 2
-    m3 = rnorm(n_draws, priors$mu_m3, priors$sigma_m3) # gradient 3
+    t0 = stats::rnorm(n_draws, priors$mu_t0, priors$sigma_t0), # titre value at t0
+    tp = stats::rnorm(n_draws, priors$mu_tp, priors$sigma_tp), # time of peak
+    ts = stats::rnorm(n_draws, priors$mu_ts, priors$sigma_ts), # time of set point
+    m1 = stats::rnorm(n_draws, priors$mu_m1, priors$sigma_m1), # gradient 1
+    m2 = stats::rnorm(n_draws, priors$mu_m2, priors$sigma_m2), # gradient 2
+    m3 = stats::rnorm(n_draws, priors$mu_m3, priors$sigma_m3) # gradient 3
   )
 
   times <- data.table(t = 1:tmax)
@@ -66,7 +66,7 @@ plot_data <- function(data, covariates) {
 
 #' Plot method for "biokinetics_population_trajectories" class
 #'
-#' @param x An object of class "biokinetics_population_trajectories". These are
+#' @param trajectories An object of class "biokinetics_population_trajectories". These are
 #' generated by running biokinetics$simulate_populate_trajectories().
 #' @param data Optional data.table containing raw data as provided to the
 #' biokinetics model.