Import austraits (#177)

Removal of functions from traits.build to accompany release of austraits 3.0

  *  util_df_to_list and util_list_to_df are now sourced from austraits (as convert_df_to_list and convert_list_to_df)
  * build_combine is now replaced by austraits::bind_databases
  *  plot_trait_distribution_beeswarm, trait_pivot_longer and trait_pivot_wider had been in both packages and have now been removed from traits.build
  *  the function flatten_database is a replacement for database_create_combined_table, which was still on a branch
  *  at the bottom of utils.R, the functions that have been moved and renamed are also assigned their old names, to ensure that the names included in our Eco Informatics publication are still "valid" and that people using old remake/build.R files are not inconvenienced by these changes
  * add deprecation warnings:
    -  Added lifecycle as dependency, reverted function for util_list_to_df1, added deprecation warning, reexported austraits::convert_list_to_df1
    -  Enabled md capabailities in rd docs, added lifecycle as a dependency, reexported austraits::convert_list_to_df2
    -  Deprecated util_list_to_df2 added lifecycle as a dependency, reexported austraits::convert_list_to_df2
    -  Deprecated convert_df_to_list, reexported austraits::convert_list_to_df
    - Deprecated build_combine, reexported austraits::bind_databases
    - Calling incorrect function in utils, added suppresswarnings in tests

---------

Co-authored-by: Fonti Kar <f.kar@unsw.edu.au>

DESCRIPTION

@@ -22,7 +22,8 @@ Depends:
     lubridate,
     readr,
     stringr,
-    tidyr
+    tidyr,
+    austraits
 Imports:
     crayon,
     git2r,
@@ -38,7 +39,8 @@ Imports:
     testthat,
     tibble,
     whisker,
-    yaml
+    yaml,
+    lifecycle
 Suggests:
     furrr,
     remake,
@@ -57,8 +59,10 @@ Suggests:
     zip,
     covr
 Remotes:
-    richfitz/remake
+    richfitz/remake,
+    traitecoevo/austraits
 Encoding: UTF-8
 VignetteBuilder: knitr
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2
 Config/testthat/edition: 3
+Roxygen: list(markdown = TRUE)

NAMESPACE

@@ -1,19 +1,22 @@
 # Generated by roxygen2: do not edit by hand
 
 export("%>%")
+export(bind_databases)
 export(build_add_version)
 export(build_combine)
 export(build_setup_pipeline)
 export(check_pivot_duplicates)
+export(convert_df_to_list)
+export(convert_list_to_df1)
+export(convert_list_to_df2)
 export(dataset_build)
 export(dataset_configure)
 export(dataset_find_taxon)
 export(dataset_process)
 export(dataset_report)
 export(dataset_test)
 export(dataset_update_taxonomy)
-export(db_traits_pivot_longer)
-export(db_traits_pivot_wider)
+export(flatten_database)
 export(get_schema)
 export(get_unit_conversions)
 export(metadata_add_contexts)
@@ -32,7 +35,6 @@ export(metadata_exclude_observations)
 export(metadata_find_taxonomic_change)
 export(metadata_remove_taxonomic_change)
 export(metadata_update_taxonomic_change)
-export(plot_trait_distribution_beeswarm)
 export(read_csv_char)
 export(read_metadata)
 export(util_df_to_list)
@@ -44,6 +46,11 @@ export(util_list_to_df1)
 export(util_list_to_df2)
 export(write_metadata)
 export(write_plaintext)
+importFrom(austraits,bind_databases)
+importFrom(austraits,convert_df_to_list)
+importFrom(austraits,convert_list_to_df1)
+importFrom(austraits,convert_list_to_df2)
+importFrom(austraits,flatten_database)
 importFrom(crayon,"%+%")
 importFrom(crayon,blue)
 importFrom(crayon,green)
@@ -59,6 +66,7 @@ importFrom(dplyr,filter)
 importFrom(dplyr,full_join)
 importFrom(dplyr,mutate)
 importFrom(dplyr,select)
+importFrom(lifecycle,deprecated)
 importFrom(lubridate,dmy)
 importFrom(magrittr,"%>%")
 importFrom(purrr,map_chr)

R/pivot.R

@@ -30,108 +30,3 @@ check_pivot_wider <- function(dataset) {
   }
 
 }
-
-
-#' @title Pivot long format data into a wide format
-#'
-#' @description `trait_pivot_wider` "widens" long format data ("tidy data").
-#'
-#' Databases built with `traits.build` are organised in a long format where observations are on different rows and the
-#' type of observation is denoted by various identifying columns (e.g `trait_name`, `dataset_id`,
-#' `observation_id`, etc.).
-#' This function converts the data into wide format so that each trait in its own column.
-#'
-#' @param traits The traits table from database (list object)
-#' @return A tibble in wide format
-#' @details `trait_pivot_wider` will return a single wide tibble; note that some meta-data columns
-#' (unit, replicates, measurement_remarks, basis_of_record, basis_of_value) will be excluded to
-#' produce a useful wide tibble.
-#' @examples
-#' \dontrun{
-#' data <- austraits$traits %>% filter(dataset_id == "Falster_2003")
-#' data # Long format
-#' traits_wide <- trait_pivot_wider(data)
-#' traits_wide # Wide format
-#' }
-#' @author Daniel Falster - daniel.falster@unsw.edu.au
-#' @export
-db_traits_pivot_wider <- function(traits) {
-
-  metadata_cols <- c("unit", "replicates", "measurement_remarks", "basis_of_value")
-
-  # A check for if there are more than 1 value_type for a given taxon_name, observation_id and method
-  check_value_type <- traits %>%
-    dplyr::select(dplyr::all_of(c(
-      "trait_name", "value", "dataset_id", "observation_id", "method_id", "method_context_id",
-      "repeat_measurements_id", "value_type"))) %>%
-    dplyr::group_by(
-      .data$dataset_id, .data$observation_id, .data$method_id,
-      .data$method_context_id, .data$repeat_measurements_id) %>%
-    dplyr::summarise(n_value_type = length(unique(.data$value_type))) %>%
-    dplyr::arrange(.data$observation_id) %>%
-    dplyr::filter(.data$n_value_type > 1)
-
-  if (nrow(check_value_type) > 1) {
-
-    traits %>%
-      tidyr::pivot_wider(
-        names_from = "trait_name",
-        values_from = "value",
-        id_cols = -dplyr::all_of(metadata_cols)
-      )
-
-  } else {
-
-    metadata_cols <- c(metadata_cols, "value_type")
-
-    traits %>%
-      tidyr::pivot_wider(
-        names_from = "trait_name",
-        values_from = "value",
-        id_cols = -dplyr::all_of(metadata_cols)
-      )
-  }
-
-}
-
-
-#' @title Pivot wide format data into a long format
-#'
-#' @description `trait_pivot_longer` "gathers" wide format data into a "tidy" format.
-#'
-#' This function converts the data into long format where observations are on different rows and the type of
-#' observation is denoted by the `trait_name` column.
-#' In other words, `trait_pivot_longer` reverts the actions of `trait_pivot_wider`.
-#' @param wide_data Output from `trait_pivot_wider` (a tibble of wide data)
-#' @return A tibble in long format
-#' @details
-#' `trait_pivot_longer` will return a tibble with fewer columns than the original traits table
-#' The excluded columns include: "unit", "replicates", "measurement_remarks", "basis_of_record",
-#' "basis_of_value" # Double check #TODO
-#'
-#' @examples
-#' \dontrun{
-#' data <- austraits$traits %>%
-#' filter(dataset_id == "Falster_2003")
-#' data # Long format
-#' traits_wide <- trait_pivot_wider(data)
-#' traits_wide # Wide format
-#'
-#' values_long <- trait_pivot_longer(traits_wide)
-#' }
-#' @author Daniel Falster - daniel.falster@unsw.edu.au
-#' @author Fonti Kar - fonti.kar@unsw.edu.au
-#' @export
-db_traits_pivot_longer <- function(wide_data) {
-
-  # The start of the trait columns is after `original_name`
-  start_of_trait_cols <- which(names(wide_data) == "original_name") + 1
-
-  wide_data %>%
-    tidyr::pivot_longer(
-      cols = start_of_trait_cols:ncol(.),
-      names_to = "trait_name",
-      values_drop_na = TRUE
-    )
-
-}