MansMeg · StaffanBetner · Feb 10, 2022 · Apr 20, 2022 · Apr 20, 2022 · Apr 20, 2022
diff --git a/rpackage/DESCRIPTION b/rpackage/DESCRIPTION
@@ -1,4 +1,4 @@
-Package: ada
+Package: adapop
 Title: Ada Poll of Polls
 Version: 0.4.0
 Authors@R: 
@@ -10,7 +10,7 @@ Description: Functionality for Ada Poll of Polls.
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.1
+RoxygenNote: 7.1.2
 Depends: R (>= 3.5.0)
 Imports:
   checkmate,

diff --git a/rpackage/R/docs_package.R b/rpackage/R/docs_package.R
@@ -1,10 +1,10 @@
-#' ada: Package to run Stan for poll of polls models.
+#' adapop: Package to run Stan for poll of polls models.
 #'
 #' @description
-#' A package to run poll of polls models and Bayeisna election prediction models
+#' A package to run poll of polls models and Bayesian election prediction models
 #'
 #'
 #' @importFrom stats rnorm
 #' @docType package
-#' @name ada
+#' @name adapop
 NULL
diff --git a/rpackage/R/experiment_bash_generation.R b/rpackage/R/experiment_bash_generation.R
@@ -56,7 +56,7 @@ write_uppmax_bash <- function(args, directory, model_config, stan_arguments, sta
   }
   if(!is.null(model_config)){
     model_config <- model_config[!unlist(lapply(model_config, is.na))]
-    suppressMessages(ada::model_config(args$stan_model, x = model_config))
+    suppressMessages(adapop::model_config(args$stan_model, x = model_config))
     mc <- yaml::as.yaml(model_config)
     mc <- gsub(pattern = "\n", replacement = "\n    ", mc)
     mc <- paste0("hyper_parameters:\n    ",mc)

diff --git a/rpackage/R/party_color.R b/rpackage/R/party_color.R
@@ -1,6 +1,6 @@
-#' Get the party color for a given party abbrivation
+#' Get the party color for a given party abbreviation
 #'
-#' @param x a party abbrivation
+#' @param x a party abbreviation
 party_color <- function(x){
   checkmate::assert_string(x)
   # Taken from: https://sv.wikipedia.org/wiki/Mall:Partif%C3%A4rg

diff --git a/rpackage/R/poll_of_polls.R b/rpackage/R/poll_of_polls.R
@@ -66,7 +66,7 @@ poll_of_polls <- function(y,
   }
 
   # SHA is setup both of all
-  fun_args <- names(formals(ada::poll_of_polls))[-which(names(formals(poll_of_polls)) %in% c("...", "cache_dir"))]
+  fun_args <- names(formals(adapop::poll_of_polls))[-which(names(formals(poll_of_polls)) %in% c("...", "cache_dir"))]
   sha_fun_args <- list(y = y,
                        model = readLines(smfp),
                        polls_data = polls_data,

diff --git a/rpackage/R/recompile_stanfit.R b/rpackage/R/recompile_stanfit.R
@@ -1,7 +1,7 @@
 #' Recompile a poll_of_polls object
 #'
 #' @description
-#' The function takes a [poll_of_polls] object and recomplie the code an the data
+#' The function takes a [poll_of_polls] object and recompile the code an the data
 #'
 #' @param x a [poll_of_polls] object
 #'

diff --git a/rpackage/R/reports.R b/rpackage/R/reports.R
@@ -14,7 +14,7 @@ write_report <- function(..., report, parameters = NULL, output_file = NULL, out
     rmd_path <- report
   } else {
     checkmate::assert_choice(report, choices = supported_reports())
-    rmd_path <- system.file(file.path("reports", report), package = "ada")
+    rmd_path <- system.file(file.path("reports", report), package = "adapop")
   }
 
   # Store files to use
@@ -70,7 +70,7 @@ write_report <- function(..., report, parameters = NULL, output_file = NULL, out
 #' Supported reports
 #' @export
 supported_reports <- function(){
-  dir(system.file(file.path("reports"), package = "ada"))
+  dir(system.file(file.path("reports"), package = "adapop"))
 }
 
 

diff --git a/rpackage/data-raw/german_polls_elections.R b/rpackage/data-raw/german_polls_elections.R
@@ -4,7 +4,7 @@ source("data-raw/german_polls_elections_functions.R")
 german_polls <- get_german_polls_data()
 
 # Get all in same format/colnames
-german_polls$PublYearMonth <- paste0(lubridate::year(german_polls$Datum), "-", tolower(ada:::month_abbr_en())[lubridate::month(german_polls$Datum)])
+german_polls$PublYearMonth <- paste0(lubridate::year(german_polls$Datum), "-", tolower(adapop:::month_abbr_en())[lubridate::month(german_polls$Datum)])
 german_polls$Company <-  as.factor(german_polls$Institut)
 german_polls$Uncertain <- german_polls$`Nichtwähler/Unentschl.`
 german_polls$n <- as.integer(german_polls$Befragte)

diff --git a/rpackage/data-raw/pd_test.R b/rpackage/data-raw/pd_test.R
@@ -1,4 +1,4 @@
-library(ada)
+library(adapop)
 data("swe_polls")
 pd <- polls_data(y = swe_polls[,3:11]/100,
                  house = swe_polls$Company,

diff --git a/rpackage/data-raw/spanish_polls_elections.R b/rpackage/data-raw/spanish_polls_elections.R
@@ -53,7 +53,7 @@ pls[[7]] <- get_wikipedia_spanish_polls_data(wiki_url, xpath = wiki_table_xpath,
 
 
 spanish_polls <- dplyr::bind_rows(pls)
-spanish_polls$PublYearMonth <- paste0(lubridate::year(spanish_polls$to), "-", tolower(ada:::month_abbr_en())[lubridate::month(spanish_polls$to)])
+spanish_polls$PublYearMonth <- paste0(lubridate::year(spanish_polls$to), "-", tolower(adapop:::month_abbr_en())[lubridate::month(spanish_polls$to)])
 spanish_polls$Company <- as.factor(spanish_polls$house)
 
 spanish_polls$Uncertain <- NA

diff --git a/rpackage/data-raw/spanish_polls_elections_functions.R b/rpackage/data-raw/spanish_polls_elections_functions.R
@@ -63,7 +63,7 @@ parse_date <- function(d, info){
   checkmate::assert_string(d)
   checkmate::assert_string(info)
 
-  month_abbr <- ada:::month_abbr_en()
+  month_abbr <- adapop:::month_abbr_en()
 
   ds <- strsplit(d, split = "–")[[1]]
   ds <- stringr::str_trim(ds)

diff --git a/rpackage/inst/reports/evaluate_elections.Rmd b/rpackage/inst/reports/evaluate_elections.Rmd
@@ -10,9 +10,9 @@ output:
 
 ```{r setup, include=FALSE}
 knitr::opts_chunk$set(echo = TRUE)
-library(ada)
+library(adapop)
 paths_to_pop_objects <- "[pop_paths]"
-pops <- ada:::rmd_read_pops(paths_to_pop_objects)
+pops <- adapop:::rmd_read_pops(paths_to_pop_objects)
 
 parameter_path <- "[parameter_path]"
 param_default <- c("full_period" = FALSE, 
@@ -21,16 +21,16 @@ param_default <- c("full_period" = FALSE,
                    "election_campaigns" = FALSE,
                    "diagnostics_table" = TRUE,
                    "model_information" = TRUE)
-params <- ada:::rmd_read_params(parameter_path)
-params <- ada:::rmd_parse_parameters(params, param_default)
+params <- adapop:::rmd_read_params(parameter_path)
+params <- adapop:::rmd_parse_parameters(params, param_default)
 
-parties <- ada:::rmd_pops_unique_parties(pops)
+parties <- adapop:::rmd_pops_unique_parties(pops)
 
-mi <- ada:::rmd_model_settings_with_unique(pops)
+mi <- adapop:::rmd_model_settings_with_unique(pops)
 mi <- mi[order(mi$y, mi$polls_time_to, mi$model_setting),]
 mi$model <- mi$i
 
-mu <- ada:::rmd_model_settings_unique(pops)
+mu <- adapop:::rmd_model_settings_unique(pops)
 
 ```
 
@@ -54,9 +54,9 @@ if(params$diagnostics_table){
 
   cat("\n## Model calibration \n")
 
-  per <- ada:::rmd_last_known_state_percentile(pops)
+  per <- adapop:::rmd_last_known_state_percentile(pops)
   per$ndraws <- NULL
-  nmi <- ada:::rmd_model_settings_with_unique(pops)
+  nmi <- adapop:::rmd_model_settings_with_unique(pops)
   per <- merge(per, nmi[, c("sha", "model_setting", "polls_time_to")])
   model_settings <- sort(unique(per$model_setting))
 
@@ -91,8 +91,8 @@ if(params$diagnostics_table){
 if(params$diagnostics_table){
 
   cat("\n## Model performance\n")
-  rmse_res <- ada:::rmd_last_known_state_evaluation_by_model_setting(pops, type = "rmse")
-  elpd_res <- ada:::rmd_last_known_state_evaluation_by_model_setting(pops, type = "elpd")
+  rmse_res <- adapop:::rmd_last_known_state_evaluation_by_model_setting(pops, type = "rmse")
+  elpd_res <- adapop:::rmd_last_known_state_evaluation_by_model_setting(pops, type = "elpd")
   res <- cbind(rmse_res[,c("model_setting", "rmse")], elpd_res[,c("elpd", "n")])
   print(knitr::kable(res, 
                      digits = 3, 
@@ -105,14 +105,14 @@ if(params$diagnostics_table){
 if(params$diagnostics_table){
 
   cat("\n## RMSE by Country\n")
-  nmi <- ada:::rmd_model_settings_with_unique(pops)
-  per <- ada:::rmd_last_known_state_evaluation(pops, type = "rmse")
+  nmi <- adapop:::rmd_model_settings_with_unique(pops)
+  per <- adapop:::rmd_last_known_state_evaluation(pops, type = "rmse")
   per <- merge(per, nmi[, c("sha", "model_setting", "polls_time_to")])
   per <- per[order(per$polls_time_to, per$model_setting),]
 
   # Germany
   party <- "SPD" 
-  pnm <- make.names(ada:::rmd_get_other_parties_in_known_state(party))
+  pnm <- make.names(adapop:::rmd_get_other_parties_in_known_state(party))
   per_germany <- per[!is.na(per[[party]]), c("polls_time_to", "model_setting", "sha", "ndraws", pnm[pnm%in%colnames(per)])]
   if(nrow(per_germany) > 0){
     print(knitr::kable(per_germany, 
@@ -123,7 +123,7 @@ if(params$diagnostics_table){
 
   # Sweden
   party <- "M" 
-  pnm <- make.names(ada:::rmd_get_other_parties_in_known_state(party))
+  pnm <- make.names(adapop:::rmd_get_other_parties_in_known_state(party))
   per_swe <- per[!is.na(per[[party]]), c("polls_time_to", "model_setting", "sha", "ndraws", pnm[pnm%in%colnames(per)])]
   if(nrow(per_swe) > 0){
     print(knitr::kable(per_swe, 
@@ -139,14 +139,14 @@ if(params$diagnostics_table){
 if(params$diagnostics_table){
 
   cat("\n## ELDP by Country\n")
-  nmi <- ada:::rmd_model_settings_with_unique(pops)
-  per <- ada:::rmd_last_known_state_evaluation(pops, type = "elpd")
+  nmi <- adapop:::rmd_model_settings_with_unique(pops)
+  per <- adapop:::rmd_last_known_state_evaluation(pops, type = "elpd")
   per <- merge(per, nmi[, c("sha", "model_setting", "polls_time_to")])
   per <- per[order(per$polls_time_to, per$model_setting),]
 
   # Germany
   party <- "SPD" 
-  pnm <- make.names(ada:::rmd_get_other_parties_in_known_state(party))
+  pnm <- make.names(adapop:::rmd_get_other_parties_in_known_state(party))
   per_germany <- per[!is.na(per[[party]]), c("polls_time_to", "model_setting", "sha", "ndraws", pnm[pnm%in%colnames(per)])]
   if(nrow(per_germany) > 0){
     print(knitr::kable(per_germany, 
@@ -157,7 +157,7 @@ if(params$diagnostics_table){
 
   # Sweden
   party <- "M" 
-  pnm <- make.names(ada:::rmd_get_other_parties_in_known_state(party))
+  pnm <- make.names(adapop:::rmd_get_other_parties_in_known_state(party))
   per_swe <- per[!is.na(per[[party]]), c("polls_time_to", "model_setting", "sha", "ndraws", pnm[pnm%in%colnames(per)])]
   if(nrow(per_swe) > 0){
     print(knitr::kable(per_swe, 
@@ -174,14 +174,14 @@ if(params$diagnostics_table){
 if(params$diagnostics_table){
 
   cat("\n## Percentiles by Country\n")
-  nmi <- ada:::rmd_model_settings_with_unique(pops)
-  per <- ada:::rmd_last_known_state_percentile(pops)
+  nmi <- adapop:::rmd_model_settings_with_unique(pops)
+  per <- adapop:::rmd_last_known_state_percentile(pops)
   per <- merge(per, nmi[, c("sha", "model_setting", "polls_time_to")])
   per <- per[order(per$polls_time_to, per$model_setting),]
 
   # Germany
   party <- "SPD" 
-  pnm <- make.names(ada:::rmd_get_other_parties_in_known_state(party))
+  pnm <- make.names(adapop:::rmd_get_other_parties_in_known_state(party))
   per_germany <- per[!is.na(per[[party]]), c("polls_time_to", "model_setting", "sha", "ndraws", pnm[pnm%in%colnames(per)])]
   if(nrow(per_germany) > 0){
     print(knitr::kable(per_germany, 
@@ -192,7 +192,7 @@ if(params$diagnostics_table){
 
   # Sweden
   party <- "M" 
-  pnm <- make.names(ada:::rmd_get_other_parties_in_known_state(party))
+  pnm <- make.names(adapop:::rmd_get_other_parties_in_known_state(party))
   per_swe <- per[!is.na(per[[party]]), c("polls_time_to", "model_setting", "sha", "ndraws", pnm[pnm%in%colnames(per)])]
   if(nrow(per_swe) > 0){
     print(knitr::kable(per_swe, 
@@ -224,7 +224,7 @@ if(params$last_election_period){
                   shift_latent_days = 6L,
                   from = unname(pop$model_time_range["to"] - 150),
                   to = unname(pop$model_time_range["to"]),
-                  latent_state_colour = ada:::party_color(party)) + 
+                  latent_state_colour = adapop:::party_color(party)) + 
         geom_known_state(ks, party) + 
         ggplot2::theme_bw()
       tit <- paste0("From ", mi$polls_time_to[j], ": Setting ", mi$model_setting[j], " (model ", mi$i[j], ") ")
@@ -246,7 +246,7 @@ if(params$last_election_period){
 if(params$diagnostics_table){
 
   cat("## Model diagnostics\n")
-  tab <- ada:::rmd_model_diagnostic_table(pops)
+  tab <- adapop:::rmd_model_diagnostic_table(pops)
   n <- 5
   it <- ncol(tab)%/%n; rest <- ncol(tab)%%n
   if(rest > 0) it <- it + 1L

diff --git a/rpackage/inst/reports/industry_bias.Rmd b/rpackage/inst/reports/industry_bias.Rmd
@@ -12,9 +12,9 @@ output:
 knitr::opts_chunk$set(echo = TRUE)
 
 
-library(ada)
+library(adapop)
 paths_to_pop_objects <- "[pop_paths]"
-pops <- ada:::rmd_read_pops(paths_to_pop_objects)
+pops <- adapop:::rmd_read_pops(paths_to_pop_objects)
 
 parameter_path <- "[parameter_path]"
 param_default <- c("full_period" = FALSE, 
@@ -25,16 +25,16 @@ param_default <- c("full_period" = FALSE,
                    "model_information" = TRUE,
                    "traceplots" = FALSE,
                    "dev" = "png")
-params <- ada:::rmd_read_params(parameter_path)
-params <- ada:::rmd_parse_parameters(params, param_default)
+params <- adapop:::rmd_read_params(parameter_path)
+params <- adapop:::rmd_parse_parameters(params, param_default)
 
-parties <- ada:::rmd_pops_unique_parties(pops)
+parties <- adapop:::rmd_pops_unique_parties(pops)
 
-mi <- ada:::rmd_model_settings_with_unique(pops)
+mi <- adapop:::rmd_model_settings_with_unique(pops)
 mi <- mi[order(mi$y, mi$polls_time_to, mi$model_setting),]
 mi$model <- mi$i
 
-mu <- ada:::rmd_model_settings_unique(pops)
+mu <- adapop:::rmd_model_settings_unique(pops)
 
 knitr::opts_chunk$set(dev = params$dev)
 ```
@@ -63,7 +63,7 @@ if(params$last_election_period){
     for(j in 1:nrow(mi)){
       cat("\n")
       pop <- pops[[mi$i[j]]]
-      knm <- ada:::rmd_get_kappa_name(pop)
+      knm <- adapop:::rmd_get_kappa_name(pop)
       if(!(party %in% pop$y)) next
       no_kappa <- pop$stan_fit@par_dims[[knm]][1]
       date_idx <- (length(pop$known_state$date) - no_kappa + 2L):length(pop$known_state$date)
@@ -87,7 +87,7 @@ if(params$traceplots){
   for(j in 1:nrow(mi)){
       cat("\n")
       pop <- pops[[mi$i[j]]]
-      knm <- ada:::rmd_get_kappa_name(pop)
+      knm <- adapop:::rmd_get_kappa_name(pop)
       parties <- pop$y
       no_kappa <- pop$stan_fit@par_dims[[knm]][1]
       param <- paste0(knm, "[", no_kappa, ",", seq_along(pop$y), "]")
@@ -138,7 +138,7 @@ if(params$traceplots){
   for(j in 1:nrow(mi)){
       cat("\n")
       pop <- pops[[mi$i[j]]]
-      knm <- ada:::rmd_get_kappa_name(pop)
+      knm <- adapop:::rmd_get_kappa_name(pop)
       parties <- pop$y
       no_kappa <- pop$stan_fit@par_dims[[knm]][1]
       param <- paste0("sigma_kappa[", seq_along(pop$y), "]")
@@ -212,7 +212,7 @@ if(params$last_election_period){
 if(params$diagnostics_table){
 
   cat("## Model diagnostics\n")
-  tab <- ada:::rmd_model_diagnostic_table(pops)
+  tab <- adapop:::rmd_model_diagnostic_table(pops)
   n <- 5
   it <- ncol(tab)%/%n; rest <- ncol(tab)%%n
   if(rest > 0) it <- it + 1L