Merge branch 'develop' into roxygen-bump

modules/assim.batch/R/plot.da.R

@@ -79,15 +79,10 @@ plot.da <- function(prior.dir, prior.file, in.dir, out.dir, next.run.dir) {
   print(nrow(x))
   print(length(good.runs))
   for (i in seq_along(x)) {
-    trait.entry <- PEcAn.utils::trait.lookup(gsub("[1-2]$", "", traits[i]))
-    if (is.na(trait.entry)) {
-      trait.entry <- PEcAn.utils::trait.lookup(traits[i])
-    }
-
     graphics::plot(x[good.runs, i], y[good.runs],
-         main = trait.entry$figid,
+         main = traits[i]$figid,
          xlim = p.rng[i, ],
-         xlab = trait.entry$units,
+         xlab = traits[i]$units,
          ylab = "-log(likelihood)",
          pch = 1)
     graphics::points(prior.x[, i], prior.y, col = "grey")
@@ -124,19 +119,15 @@ plot.da <- function(prior.dir, prior.file, in.dir, out.dir, next.run.dir) {
     all <- do.call(rbind, lapply(samp, function(chain) chain[thin, i]))
 
     # Density plots
-    trait.entry <- PEcAn.utils::trait.lookup(gsub("[1-2]$", "", traits[i]))
-    if (is.na(trait.entry)) {
-      trait.entry <- PEcAn.utils::trait.lookup(traits[i])
-    }
     graphics::plot(stats::density(all),
          xlim = p.rng[i, ], 
-         main = paste(trait.entry$figid),
+         main = paste(traits[i]$figid),
          type = "l", 
          ylab = "", 
-         xlab = trait.entry$units)
+         xlab = traits[i]$units)
     x <- seq(p.rng[i, 1], p.rng[i, 2], length = 1000)
-    graphics::lines(x, ddist(x, priors[traits[i], ]), col = "grey")
-    graphics::lines(x, ddist(x, priors2[traits[i], ]), col = "grey", lty = 2)
+    graphics::lines(x, ddist(x, priors[traits[i]$id, ]), col = "grey")
+    graphics::lines(x, ddist(x, priors2[traits[i]$id, ]), col = "grey", lty = 2)
   }
 
   # Now approximate posteriors to data assimilation and store them with posteriors from meta

modules/priors/R/plots.R

@@ -48,13 +48,13 @@ plot_posterior.density <- function(posterior.density, base.plot = NULL) {
 ##' @title Prior Figure
 ##' @param priordata observations to be plotted as points
 ##' @param priordensity density of prior distribution, calculated by \code{\link{prior.density}}
-##' @param trait name of trait
+##' @param trait dataframe with id, figid and units of the trait
 ##' @param xlim limits for x axis
 ##' @author David LeBauer
 ##' @return plot / grob of prior distribution with data used to inform the distribution
 ##' @export
 ##' @importFrom ggplot2 ggplot aes theme_bw scale_x_continuous scale_y_continuous element_blank element_text geom_rug geom_line geom_point
-priorfig <- function(priordata = NA, priordensity = NA, trait = "", xlim = "auto", fontsize = 18) {
+priorfig <- function(priordata = NA, priordensity = NA, trait = NA, xlim = "auto", fontsize = 18) {
   if (is.data.frame(priordata)) {
     colnames(priordata) <- "x"
   }
@@ -68,9 +68,9 @@ priorfig <- function(priordata = NA, priordensity = NA, trait = "", xlim = "auto
   }
 
   priorfigure <- ggplot() + theme_bw() +
-    scale_x_continuous(limits = xlim, breaks = x.breaks, name = PEcAn.utils::trait.lookup(trait)$units) +
+    scale_x_continuous(limits = xlim, breaks = x.breaks, name = trait$units) +
     scale_y_continuous(breaks = NULL) +
-    labs(title = PEcAn.utils::trait.lookup(trait)$figid) +
+    labs(title = trait$figid) +
     theme(panel.grid.major = element_blank(),
           panel.grid.minor = element_blank(),
           axis.text.y = element_blank(),    ## hide y axis label
@@ -100,7 +100,7 @@ priorfig <- function(priordata = NA, priordensity = NA, trait = "", xlim = "auto
 ##--------------------------------------------------------------------------------------------------#
 ##' Plot trait density and data
 ##'
-##' @param trait character, name of trait to be plotted
+##' @param trait dataframe with id, figid and units of the trait to be plotted
 ##' @param prior named distribution with parameters
 ##' @param posterior.sample samples from posterior distribution
 ##'   whose density should be plotted
@@ -119,7 +119,8 @@ priorfig <- function(priordata = NA, priordensity = NA, trait = "", xlim = "auto
 ##'                      parama = 20,
 ##'                      paramb = 5)
 ##' data1  <- data.frame(Y = c(19, 21), se = c(1,1))
-##' plot_trait(trait = 'Vcmax',
+##' trait1 <- data.frame(id = 'Vcmax', figid = 'Vcmax', units = 'umol CO2 m-2 s-1')
+##' plot_trait(trait = trait1,
 ##'           prior = prior1,
 ##'           trait.df = data1)
 ##' }
@@ -143,9 +144,6 @@ plot_trait <- function(trait,
   plot_prior     <- !is.null(prior)
   plot_data      <- !is.null(trait.df)
 
-  ## get units for plot title
-  units <- PEcAn.utils::trait.lookup(trait)$units
-
   if(plot_data)  trait.df <- PEcAn.MA::jagify(trait.df)
 
   if (plot_prior) {
@@ -189,8 +187,8 @@ plot_trait <- function(trait,
 
   trait.plot <- base.plot +
     geom_segment(aes(x = min(x.ticks), xend = last(x.ticks), y = 0, yend = 0)) +
-    scale_x_continuous(limits = range(x.ticks), breaks = x.ticks, name = PEcAn.utils::trait.lookup(trait)$units) +
-    labs(title = PEcAn.utils::trait.lookup(trait)$figid) +
+    scale_x_continuous(limits = range(x.ticks), breaks = x.ticks, name = trait$units) +
+    labs(title = trait$figid) +
     theme(axis.text.x = element_text(size = fontsize$axis),
           axis.text.y = element_blank(),
           axis.title.x = element_text(size = fontsize$axis),

modules/priors/vignettes/priors_demo.Rmd

@@ -305,7 +305,7 @@ vcmax.data <- vcmax.data[,c('ft', 'mean', 'se')]
 
 prior.figures[['Vcmax']] <- 
   priorfig(priordensity = vcmax.density, 
-                                     trait = 'Vcmax', 
+                                     trait = dataframe(id = 'Vcmax', figid = 'Vcmax', units = 'umol CO2 m-2 s-1'), 
                                      xlim = range(c(0, max(vcmax.data$mean)))) + 
   geom_point(data = subset(vcmax.data, ft != 2), 
              aes(x=mean, y = (sum(vcmax.c4) + 1:sum(!vcmax.c4))/3000), color = 'grey60') +