dook

.github/404.md

@@ -0,0 +1,5 @@
+# Page not found (404)
+
+The page you requested was not found.  
+
+Please use the links in the navigation bar.

.github/CODEOWNERS

@@ -0,0 +1,3 @@
+# CODEOWNERS for testthat
+# https://www.tidyverse.org/development/understudies
+.github/CODEOWNERS @juniperlsimonis @ethanwhite @weecology

DESCRIPTION

@@ -17,7 +17,7 @@ Authors@R: c(
       comment = c(ORCID = "0000-0002-8630-1458")),
 	person(c("Ethan", "P."), "White", role = c("aut"),
       comment = c(ORCID = "0000-0001-6728-7745")),
-    person(c("S.K.", "Morgan"), "Ernest", role = c("aut"),
+    person(c("S. K.", "Morgan"), "Ernest", role = c("aut"),
       comment = c(ORCID = "0000-0002-6026-8530")))
 Description: Create a directory, populate it with data, build models, forecast rodent populations, and visualize the results. This package provides the functionality underlying the Portal Predictions Project <https://github.com/weecology/portalpredictions> as well as support for exploring and developing new models in sandbox environments.
 URL: https://weecology.github.io/portalcasting, https://github.com/weecology/portalcasting

R/evaluate.R

@@ -32,12 +32,12 @@
 #' 
 #'    evaluate_forecasts(main = main1)
 #'
-#'    ids <- select_forecasts(main = main1)
+#'    ids <- select_forecasts(main = main1)$forecast_id
 #'         
 #'    evaluate_forecast(main        = main1, 
 #'                      forecast_id = ids[1])
 #'
-#'    read_forecast_evaluations(main = main1)
+#'    read_forecasts_evaluations(main = main1)
 #'
 #'    unlink(main1, recursive = TRUE)
 #' }

R/figures.R

@@ -104,7 +104,7 @@ plot_forecasts_error_lead <- function (main                        = ".",
   if (nmodels == 1 & nspecies == 1) {
 
     yy <- round(evals_in$error, 3)
-    yrange <- range(c(0, yy), na.rm = TRUE)
+    yrange <- range(c(-1, yy, 1), na.rm = TRUE)
     xrange <- c(max(evals_in$lead_time_newmoons) + 0.25, 0)
 
     oldpar <- par(no.readonly = TRUE)
@@ -165,7 +165,7 @@ plot_forecasts_error_lead <- function (main                        = ".",
 
       species_in <- evals_in$species %in% species[j]
       yy         <- round(evals_in$error[species_in], 3)
-      yrange     <- range(c(0, yy), na.rm = TRUE)
+      yrange     <- range(c(-1, yy, 1), na.rm = TRUE)
 
       for(i in 1:nmodels){
 
@@ -417,7 +417,7 @@ plot_forecasts_cov_RMSE <- function (main                        = ".",
     abline(h = 0.95, lwd = 2, lty = 3)
 
     in_i <- which(forecast_species == species[i])
-    ymax <- max(forecast_RMSE[in_i], na.rm = TRUE)
+    ymax <- max(c(0, forecast_RMSE[in_i]), na.rm = TRUE)
     x1 <- 0.5
     x2 <- 1
     y1 <- 0 + (i - 1) * 1 * (1/nspecies)
@@ -446,7 +446,7 @@ plot_forecasts_cov_RMSE <- function (main                        = ".",
       rect(j - 0.1, quants[2], j + 0.1, quants[4], col = "white")
       points(c(j - 0.1, j + 0.1), rep(quants[3], 2), type = "l", lwd = 2)
       points(xs, ys2, col = rgb(0.3, 0.3, 0.3, 0.4), pch = 1, cex = 0.5)
-      axis(2, labels = FALSE, tck = 0, at = seq(min(ys) - 2, max(ys) + 2, 0.1))
+      axis(2, labels = FALSE, tck = 0, at = seq(min(c(0, ys)) - 2, max(c(1,ys)) + 2, 0.1))
 
       if (nmodels > 1) {
         axis(1, at = 1:nmodels, labels = models, cex.axis = 1.125, xpd = TRUE)

R/models_jags.R

@@ -17,7 +17,7 @@
 #'
 #' @param inits `list` of model parameter initializer functions. See [`prefab_models_controls`].
 #'
-#' @param model `character` value of the model file name. See [`prefab_models_controls`].
+#' @param model_file `character` value of the model file name. See [`prefab_models_controls`].
 #'
 #' @param data_names `character` vector of data values to include in the data `list`. See [`prefab_models_controls`].
 #'
@@ -75,9 +75,11 @@
 #'    main1 <- file.path(tempdir(), "runjags")
 #'
 #'    setup_dir(main = main1)
-#'    dataset <- "all"
-#'    species <- "DM"
-#'    model   <- "jags_RW"
+#'    dataset    <- "all"
+#'    species    <- "DM"
+#'    model      <- "jags_RW"
+#'    model_file <- gsub("'", "",
+#'                       models_controls(main)[[model]]$fit$full_model_file)
 #'  
 #'    abundance      <- prepare_abundance(main    = main1,
 #'                                        dataset = dataset,
@@ -88,7 +90,11 @@
 #'    metadata       <- read_metadata(main        = main1)
 #'    newmoons       <- read_newmoons(main        = main1)                                        
 #'    covariates     <- read_covariates(main      = main1)
-#'    control_runjags <- runjags_controls( )
+#'    control_runjags <- runjags_controls(nchains = 3, 
+#'                                        adapt   = 1e3, 
+#'                                        burnin  = 1e3, 
+#'                                        sample  = 1e3, 
+#'                                        thin    = 1)
 #'    data_names      <- c("count", "N", "log_mean_count")
 #'
 #'    runjags_model(model = model)
@@ -110,11 +116,11 @@
 #'                       monitors        = c("mu", "sigma"), 
 #'                       inits           = list(mu    = rnorm(1, data$log_mean_count, 0.1),
 #'                                              sigma = runif(1, 0.01, 0.5)), 
-#'                       model           = model,
+#'                       model_file      = model_file,
 #'                       data_names      = data_names,
 #'                       control_runjags = control_runjags)
 #'  
-#'    forecast(object   = fit_runjags,  
+#'    forecast(object   = fit,  
 #'             h        = metadata$time$lead_time_newmoons,   
 #'             level    = metadata$confidence_level,   
 #'             nsamples = metadata$nsamples)
@@ -157,9 +163,9 @@ runjags_inits <- function (inits) {
 #'
 #' @export
 #'
-runjags_model <- function (model) {
+runjags_model <- function (model_file) {
 
-  scan(file  = model,
+  scan(file  = model_file,
        what  = "character",
        quiet = TRUE)
 
@@ -221,14 +227,14 @@ fit_runjags <- function (abundance,
                          covariates, 
                          monitors, 
                          inits,
-                         model,
+                         model_file,
                          data_names,
                          control_runjags = runjags_controls( )) {
 
   monitor    <- runjags_monitors(monitors = monitors,
                                  metadata = metadata)  
   init       <- runjags_inits(inits       = inits)  
-  jags_model <- runjags_model(model       = model)  
+  jags_model <- runjags_model(model_file  = model_file)  
   data       <- runjags_data(data_names   = data_names,
                              abundance    = abundance,
                              metadata     = metadata,

R/models_tsglm.R

@@ -42,7 +42,7 @@
 #' \dontrun{
 #'    main1 <- file.path(tempdir(), "metatsglm")
 #'
-#'    setup_dir(main = main1)
+#'    setup_production(main = main1)
 #'    dataset <- "all"
 #'    species <- "DM"
 #'    model   <- "pevGARCH"

R/process_casts.R

@@ -71,12 +71,12 @@
 #'                          args = fit_args)
 #'  
 #'  
-#'    forecast_args  <- named_null_list(element_names = names(model_controls$cast$args))
+#'    forecast_args  <- named_null_list(element_names = names(model_controls$forecast$args))
 #'    for (i in 1:length(forecast_args)) {
-#'      forecast_args[[i]] <- eval(parse(text = model_controls$cast$args[i]))
+#'      forecast_args[[i]] <- eval(parse(text = model_controls$forecast$args[i]))
 #'    }
 #'  
-#'    model_forecast <- do.call(what = model_controls$cast$fun,
+#'    model_forecast <- do.call(what = model_controls$forecast$fun,
 #'                              args = forecast_args)
 #'  
 #'    process_model_output(main           = main1,
@@ -91,7 +91,6 @@
 #'                                                         forecast_table = cast_table)
 #'    cast_tables    <- read_forecast_tables(main = main1)
 #'    cast_metadata  <- read_forecast_metadata(main = main1)
-#'    cast_fit       <- read_model_fit(main = main1)
 #'    cast_forecast  <- read_model_forecast(main = main1)
 #'
 #'    casts_metadata <- read_forecasts_metadata(main = main1)

_pkgdown.yml

@@ -4,7 +4,34 @@ development:
   mode: auto
 
 template:
-  bootstrap: 5
+  bootstrap: 5         
+
+news:
+  releases:
+  - text: "Version 0.50.0"
+    href: https://github.com/weecology/portalcasting/releases/tag/v0.50.0
+
+home:
+  strip_header: true
+
+authors:
+  Juniper L. Simonis:
+    href: https://www.dapperstats.com/author/dr.-juniper-l.-simonis/
+  Glenda M. Yenni:
+    href: https://www.weecology.org/author/glenda-m.-yenni/
+  Ellen K. Bledsoe:
+    href: https://nature.arizona.edu/ellen-bledsoe
+  Erica M. Christensen:
+    href: https://scholar.google.com/citations?user=_cBpCegAAAAJ&hl=en
+  Henry Senyondo:
+    href: https://www.weecology.org/author/henry-senyondo/
+  Hao Ye:
+    href: https://haoye.us/
+  Ethan P. White:
+    href: https://www.weecology.org/author/ethan-white/
+  S. K. Morgan Ernest:
+    href: https://www.weecology.org/author/morgan-ernest/
+
 
 navbar:
   title: "portalcasting"
@@ -13,7 +40,7 @@ navbar:
     right: [twitter, github, website] 
   components: 
     articles:
-      text: "Vignettes"
+      text: "Articles"
       menu:
        - text: "Current Models"
          href: articles/current_models.html
@@ -23,12 +50,6 @@ navbar:
          href: articles/adding_model_and_data.html
        - text: "Codebase"
          href: articles/codebase.html
-    reference: 
-      text: "Reference"
-      href: reference/index.html
-    news: 
-      text: "News"
-      href: news/index.html
     twitter:
       icon: fa-twitter
       href: https://twitter.com/weecology