From 17d336fc48b8f442c2a28351c5951a6baa541b6a Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 10:53:17 +0800 Subject: [PATCH 01/10] Rename `get_` to `read_` in functions where data is imported from remote, not just downloaded --- NAMESPACE | 30 +++++++------- R/get_agfd.R | 2 +- R/get_soil_thickness.R | 3 +- R/globals.R | 2 +- ...t_aagis_regions.R => read_aagis_regions.R} | 6 +-- R/{get_abares_trade.R => read_abares_trade.R} | 7 ++-- ..._regions.R => read_abares_trade_regions.R} | 6 +-- ... read_estimates_by_performance_category.R} | 12 +++--- ...tes_by_size.R => read_estimates_by_size.R} | 12 +++--- ....R => read_historical_forecast_database.R} | 16 ++++---- ...R => read_historical_national_estimates.R} | 12 +++--- ...R => read_historical_regional_estimates.R} | 12 +++--- ...es.R => read_historical_state_estimates.R} | 12 +++--- R/read_soil_thickness_stars.R | 4 ++ R/read_soil_thickness_terra.R | 8 +++- README.Rmd | 16 ++++---- README.md | 36 +++++++---------- man/get_agfd.Rd | 4 +- man/get_estimates_by_performance_category.Rd | 40 ------------------- man/get_soil_thickness.Rd | 4 +- ...aagis_regions.Rd => read_aagis_regions.Rd} | 12 +++--- ...t_abares_trade.Rd => read_abares_trade.Rd} | 14 +++---- ...egions.Rd => read_abares_trade_regions.Rd} | 14 +++---- man/read_agfd_dt.Rd | 2 +- man/read_agfd_stars.Rd | 2 +- man/read_agfd_terra.Rd | 2 +- man/read_agfd_tidync.Rd | 2 +- man/read_estimates_by_performance_category.Rd | 40 +++++++++++++++++++ ...s_by_size.Rd => read_estimates_by_size.Rd} | 28 ++++++------- ...d => read_historical_forecast_database.Rd} | 22 +++++----- ... => read_historical_national_estimates.Rd} | 28 ++++++------- ... => read_historical_regional_estimates.Rd} | 28 ++++++------- ....Rd => read_historical_state_estimates.Rd} | 28 ++++++------- man/read_soil_thickness_stars.Rd | 6 +++ man/read_soil_thickness_terra.Rd | 10 ++++- pkgdown/_pkgdown.yml | 21 ++++++---- ...is_regions.R => test-read_aagis_regions.R} | 18 ++++----- ...bares_trade.R => test-read_abares_trade.R} | 8 ++-- ...ons.R => test-read_abares_trade_regions.R} | 12 +++--- ...-read_estimates_by_performance_category.R} | 4 +- ...y_size.R => test-read_estimates_by_size.R} | 4 +- ... test-read_historical_forecast_database.R} | 5 ++- ...test-read_historical_national_estimates.R} | 4 +- ...test-read_historical_regional_estimates.R} | 4 +- ...=> test-read_historical_state_estimates.R} | 4 +- 45 files changed, 294 insertions(+), 272 deletions(-) rename R/{get_aagis_regions.R => read_aagis_regions.R} (97%) rename R/{get_abares_trade.R => read_abares_trade.R} (96%) rename R/{get_abares_trade_regions.R => read_abares_trade_regions.R} (96%) rename R/{get_estimates_by_performance_category.R => read_estimates_by_performance_category.R} (66%) rename R/{get_estimates_by_size.R => read_estimates_by_size.R} (79%) rename R/{get_historical_forecast_database.R => read_historical_forecast_database.R} (91%) rename R/{get_historical_national_estimates.R => read_historical_national_estimates.R} (77%) rename R/{get_historical_regional_estimates.R => read_historical_regional_estimates.R} (79%) rename R/{get_historical_state_estimates.R => read_historical_state_estimates.R} (77%) delete mode 100644 man/get_estimates_by_performance_category.Rd rename man/{get_aagis_regions.Rd => read_aagis_regions.Rd} (86%) rename man/{get_abares_trade.Rd => read_abares_trade.Rd} (81%) rename man/{get_abares_trade_regions.Rd => read_abares_trade_regions.Rd} (78%) create mode 100644 man/read_estimates_by_performance_category.Rd rename man/{get_estimates_by_size.Rd => read_estimates_by_size.Rd} (56%) rename man/{get_historical_forecast_database.Rd => read_historical_forecast_database.Rd} (82%) rename man/{get_historical_national_estimates.Rd => read_historical_national_estimates.Rd} (56%) rename man/{get_historical_regional_estimates.Rd => read_historical_regional_estimates.Rd} (56%) rename man/{get_historical_state_estimates.Rd => read_historical_state_estimates.Rd} (56%) rename tests/testthat/{test-get_aagis_regions.R => test-read_aagis_regions.R} (75%) rename tests/testthat/{test-get_abares_trade.R => test-read_abares_trade.R} (91%) rename tests/testthat/{test-get_abares_trade_regions.R => test-read_abares_trade_regions.R} (81%) rename tests/testthat/{test-get_estimates_by_performance_category.R => test-read_estimates_by_performance_category.R} (75%) rename tests/testthat/{test-get_estimates_by_size.R => test-read_estimates_by_size.R} (83%) rename tests/testthat/{test-get_historical_forecast_database.R => test-read_historical_forecast_database.R} (90%) rename tests/testthat/{test-get_historical_national_estimates.R => test-read_historical_national_estimates.R} (77%) rename tests/testthat/{test-get_historical_regional_estimates.R => test-read_historical_regional_estimates.R} (78%) rename tests/testthat/{test-get_historical_state_estimates.R => test-read_historical_state_estimates.R} (80%) diff --git a/NAMESPACE b/NAMESPACE index e1fa63d..bbb3fc2 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -3,31 +3,31 @@ S3method(print,read.abares.agfd.nc.files) S3method(print,read.abares.soil.thickness.files) export(clear_cache) -export(get_aagis_regions) -export(get_abares_trade) -export(get_abares_trade_regions) export(get_agfd) -export(get_est_by_perf_cat) -export(get_est_by_size) -export(get_estimates_by_performance_category) -export(get_estimates_by_size) -export(get_hist_nat_est) -export(get_hist_reg_est) -export(get_hist_sta_est) -export(get_historical_forecast) -export(get_historical_forecast_database) -export(get_historical_national_estimates) -export(get_historical_regional_estimates) -export(get_historical_state_estimates) export(get_soil_thickness) export(inspect_cache) export(plot) export(print_agfd_nc_file_format) export(print_soil_thickness_metadata) +export(read_aagis_regions) +export(read_abares_trade) +export(read_abares_trade_regions) export(read_agfd_dt) export(read_agfd_stars) export(read_agfd_terra) export(read_agfd_tidync) +export(read_est_by_perf_cat) +export(read_est_by_size) +export(read_estimates_by_performance_category) +export(read_estimates_by_size) +export(read_hist_nat_est) +export(read_hist_reg_est) +export(read_hist_sta_est) +export(read_historical_forecast) +export(read_historical_forecast_database) +export(read_historical_national_estimates) +export(read_historical_regional_estimates) +export(read_historical_state_estimates) export(read_soil_thickness_stars) export(read_soil_thickness_terra) importFrom(data.table,":=") diff --git a/R/get_agfd.R b/R/get_agfd.R index d200299..60ea837 100644 --- a/R/get_agfd.R +++ b/R/get_agfd.R @@ -1,5 +1,5 @@ -#' Fetch Australian Gridded Farm Data +#' Get Australian Gridded Farm Data for Local Use #' #' Downloads The Australian Gridded Farm Data (\acronym{AGFD}) data and unzips #' the compressed files to NetCDF for importing. diff --git a/R/get_soil_thickness.R b/R/get_soil_thickness.R index 9ce621e..70e1e66 100644 --- a/R/get_soil_thickness.R +++ b/R/get_soil_thickness.R @@ -1,4 +1,5 @@ -#' Download Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 + +#' Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use #' #' @param cache `Boolean` Cache the soil thickness data files after download #' using `tools::R_user_dir()` to identify the proper directory for storing diff --git a/R/globals.R b/R/globals.R index d310f6a..470c7aa 100644 --- a/R/globals.R +++ b/R/globals.R @@ -2,8 +2,8 @@ utils::globalVariables(c( "Year_month", # <.download_abares_trade> - "Month_issued", # "lat", # "lon", # + "Month_issued", # NULL )) diff --git a/R/get_aagis_regions.R b/R/read_aagis_regions.R similarity index 97% rename from R/get_aagis_regions.R rename to R/read_aagis_regions.R index 2a84890..f6e28af 100644 --- a/R/get_aagis_regions.R +++ b/R/read_aagis_regions.R @@ -1,5 +1,5 @@ -#' Get AAGIS Region Mapping Files +#' Read AAGIS Region Mapping Files #' #' Download, cache and import the Australian Agricultural and Grazing #' Industries Survey (\acronym{AAGIS} regions geospatial shapefile. Upon @@ -14,7 +14,7 @@ #' closing of the \R session. #' #' @examplesIf interactive() -#' aagis <- get_aagis_regions() +#' aagis <- read_aagis_regions() #' #' plot(aagis) #' @@ -27,7 +27,7 @@ #' @autoglobal #' @export -get_aagis_regions <- function(cache = TRUE) { +read_aagis_regions <- function(cache = TRUE) { aagis <- .check_existing_aagis(cache) if (is.null(aagis)) { aagis <- .download_aagis_shp(cache) diff --git a/R/get_abares_trade.R b/R/read_abares_trade.R similarity index 96% rename from R/get_abares_trade.R rename to R/read_abares_trade.R index 16fdcc2..caceee3 100644 --- a/R/get_abares_trade.R +++ b/R/read_abares_trade.R @@ -1,4 +1,5 @@ -#' Get Data From the ABARES Trade Dashboard + +#' Read Data From the ABARES Trade Dashboard #' #' Fetches and imports \acronym{ABARES} trade data. #' @@ -13,7 +14,7 @@ #' and the files are deleted upon closing of the \R session. #' #' @examplesIf interactive() -#' trade <- get_abares_trade() +#' trade <- read_abares_trade() #' #' trade #' @@ -24,7 +25,7 @@ #' @autoglobal #' @export -get_abares_trade <- function(cache = TRUE) { +read_abares_trade <- function(cache = TRUE) { abares_trade_rds <- file.path(.find_user_cache(), "abares_trade_dir/abares_trade.rds") diff --git a/R/get_abares_trade_regions.R b/R/read_abares_trade_regions.R similarity index 96% rename from R/get_abares_trade_regions.R rename to R/read_abares_trade_regions.R index 19f3d83..54a93c2 100644 --- a/R/get_abares_trade_regions.R +++ b/R/read_abares_trade_regions.R @@ -1,4 +1,4 @@ -#' Get ABARES Trade Data Regions From the ABARES Trade Dashboard +#' Read ABARES Trade Data Regions From the ABARES Trade Dashboard #' #' Fetches and imports \acronym{ABARES} trade regions data. #' @@ -13,7 +13,7 @@ #' `tempdir()` and the files are deleted upon closing of the \R session. #' #' @examplesIf interactive() -#' trade_regions <- get_abares_trade_regions() +#' trade_regions <- read_abares_trade_regions() #' #' trade_regions #' @@ -25,7 +25,7 @@ #' @autoglobal #' @export -get_abares_trade_regions <- function(cache = TRUE) { +read_abares_trade_regions <- function(cache = TRUE) { trade_regions <- .check_existing_trade_regions(cache) if (!is.null(trade_regions)) { return(trade_regions[]) diff --git a/R/get_estimates_by_performance_category.R b/R/read_estimates_by_performance_category.R similarity index 66% rename from R/get_estimates_by_performance_category.R rename to R/read_estimates_by_performance_category.R index 362a7f8..a1c8c94 100644 --- a/R/get_estimates_by_performance_category.R +++ b/R/read_estimates_by_performance_category.R @@ -1,5 +1,5 @@ -#' Get Estimates by Size From ABARES +#' Read Estimates by Size From ABARES #' #' @return A [data.table::data.table] object #' @export @@ -9,12 +9,12 @@ #' @autoglobal #' @examplesIf interactive() #' -#' get_estimates_by_performance_category() +#' read_estimates_by_performance_category() #' #' # or shorter -#' get_est_by_perf_cat() +#' read_est_by_perf_cat() #' -get_estimates_by_performance_category <- get_est_by_perf_cat <- function() { +read_estimates_by_performance_category <- read_est_by_perf_cat <- function() { f <- file.path(tempdir(), "fdp-BySize-ByPerformance.csv") @@ -27,5 +27,5 @@ get_estimates_by_performance_category <- get_est_by_perf_cat <- function() { } #' @export -#' @rdname get_estimates_by_performance_category -get_est_by_perf_cat <- get_estimates_by_performance_category +#' @rdname read_estimates_by_performance_category +read_est_by_perf_cat <- read_estimates_by_performance_category diff --git a/R/get_estimates_by_size.R b/R/read_estimates_by_size.R similarity index 79% rename from R/get_estimates_by_size.R rename to R/read_estimates_by_size.R index 23951fa..3883a87 100644 --- a/R/get_estimates_by_size.R +++ b/R/read_estimates_by_size.R @@ -1,5 +1,5 @@ -#' Get Estimates by Size From ABARES +#' Read Estimates by Size From ABARES #' #' @note #' Columns are renamed and reordered for consistency. @@ -13,12 +13,12 @@ #' @export #' @examplesIf interactive() #' -#' get_estimates_by_size() +#' read_estimates_by_size() #' #' # or shorter -#' get_est_by_size() +#' read_est_by_size() #' -get_estimates_by_size <- get_est_by_size <- function() { +read_estimates_by_size <- read_est_by_size <- function() { f <- file.path(tempdir(), "fdp-beta-performance-by-size.csv") @@ -35,5 +35,5 @@ get_estimates_by_size <- get_est_by_size <- function() { } #' @export -#' @rdname get_estimates_by_size -get_est_by_size <- get_estimates_by_size +#' @rdname read_estimates_by_size +read_est_by_size <- read_estimates_by_size diff --git a/R/get_historical_forecast_database.R b/R/read_historical_forecast_database.R similarity index 91% rename from R/get_historical_forecast_database.R rename to R/read_historical_forecast_database.R index 81da925..3c836c7 100644 --- a/R/get_historical_forecast_database.R +++ b/R/read_historical_forecast_database.R @@ -1,5 +1,5 @@ -#' Get Historical Forecast Database From ABARES +#' Read Historical Forecast Database From ABARES #' #' # Data Dictionary #' The resulting object will contain the following fields. @@ -26,21 +26,21 @@ #' The "Month_issued" column is converted from a character string to a numeric #' value representing the month of year, _e.g._, "March" is converted to `3`. #' -#' @source #' @references +#' @source #' -#' @return A [data.table::data.table] object. +#' @return A [data.table::data.table] object #' #' @autoglobal #' @export #' @examplesIf interactive() #' -#' get_historical_forecast_database() +#' read_historical_forecast_database() #' #' # or shorter -#' get_historical_forecast() +#' read_historical_forecast() #' -get_historical_forecast_database <- function() { +read_historical_forecast_database <- function() { f <- file.path(tempdir(), "historical_db.xlsx") @@ -110,5 +110,5 @@ get_historical_forecast_database <- function() { } #' @export -#' @rdname get_historical_forecast_database -get_historical_forecast <- get_historical_forecast_database +#' @rdname read_historical_forecast_database +read_historical_forecast <- read_historical_forecast_database diff --git a/R/get_historical_national_estimates.R b/R/read_historical_national_estimates.R similarity index 77% rename from R/get_historical_national_estimates.R rename to R/read_historical_national_estimates.R index 27e650d..420ab3f 100644 --- a/R/get_historical_national_estimates.R +++ b/R/read_historical_national_estimates.R @@ -1,5 +1,5 @@ -#' Get Historical National Estimates from ABARES +#' Read Historical National Estimates from ABARES #' #' @note #' Columns are renamed for consistency with other \acronym{ABARES} products @@ -14,12 +14,12 @@ #' @export #' @examplesIf interactive() #' -#' get_historical_national_estimates() +#' read_historical_national_estimates() #' #' # or shorter -#' get_hist_nat_est() +#' read_hist_nat_est() #' -get_historical_national_estimates <- function() { +read_historical_national_estimates <- function() { f <- file.path(tempdir(), "fdp-beta-national-historical.csv") @@ -34,5 +34,5 @@ get_historical_national_estimates <- function() { } #' @export -#' @rdname get_historical_national_estimates -get_hist_nat_est <- get_historical_national_estimates +#' @rdname read_historical_national_estimates +read_hist_nat_est <- read_historical_national_estimates diff --git a/R/get_historical_regional_estimates.R b/R/read_historical_regional_estimates.R similarity index 79% rename from R/get_historical_regional_estimates.R rename to R/read_historical_regional_estimates.R index 3fcf93a..c0186c1 100644 --- a/R/get_historical_regional_estimates.R +++ b/R/read_historical_regional_estimates.R @@ -1,5 +1,5 @@ -#' Get Historical Regional Estimates from ABARES +#' Read Historical Regional Estimates from ABARES #' #' @note #' Columns are renamed for consistency with other \acronym{ABARES} products @@ -13,12 +13,12 @@ #' @source #' @export #' @examplesIf interactive() -#' get_historical_regional_estimates() +#' read_historical_regional_estimates() #' #' # or shorter -#' get_hist_reg_est() +#' read_hist_reg_est() #' -get_historical_regional_estimates <- get_hist_reg_est <- function() { +read_historical_regional_estimates <- read_hist_reg_est <- function() { f <- file.path(tempdir(), "fdp-beta-regional-historical.csv") @@ -39,5 +39,5 @@ get_historical_regional_estimates <- get_hist_reg_est <- function() { } #' @export -#' @rdname get_historical_regional_estimates -get_hist_reg_est <- get_historical_regional_estimates +#' @rdname read_historical_regional_estimates +read_hist_reg_est <- read_historical_regional_estimates diff --git a/R/get_historical_state_estimates.R b/R/read_historical_state_estimates.R similarity index 77% rename from R/get_historical_state_estimates.R rename to R/read_historical_state_estimates.R index d42b484..d105bcc 100644 --- a/R/get_historical_state_estimates.R +++ b/R/read_historical_state_estimates.R @@ -1,5 +1,5 @@ -#' Get Historical State Estimates from ABARES +#' Read Historical State Estimates from ABARES #' #' @note #' Columns are renamed for consistency with other \acronym{ABARES} products @@ -13,12 +13,12 @@ #' @source #' @export #' @examplesIf interactive() -#' get_historical_state_estimates() +#' read_historical_state_estimates() #' #' # or shorter -#' get_hist_sta_est() +#' read_hist_sta_est() #' -get_historical_state_estimates <- get_hist_sta_est <- function() { +read_historical_state_estimates <- read_hist_sta_est <- function() { f <- file.path(tempdir(), "fdp-beta-state-historical.csv") .retry_download( @@ -35,5 +35,5 @@ get_historical_state_estimates <- get_hist_sta_est <- function() { } #' @export -#' @rdname get_historical_state_estimates -get_hist_sta_est <- get_historical_state_estimates +#' @rdname read_historical_state_estimates +read_hist_sta_est <- read_historical_state_estimates diff --git a/R/read_soil_thickness_stars.R b/R/read_soil_thickness_stars.R index 912e105..416cc78 100644 --- a/R/read_soil_thickness_stars.R +++ b/R/read_soil_thickness_stars.R @@ -6,6 +6,10 @@ #' #' @param files An \pkg{read.abares} `read.abares.soil.thickness` object, a #' `list` that contains the \acronym{ESRI} grid file to import +#' +#' @references +#' @source +#' #' @return a [stars] object of the Soil Thickness for Australian Areas of #' Intensive Agriculture of Layer 1 #' diff --git a/R/read_soil_thickness_terra.R b/R/read_soil_thickness_terra.R index 7573a69..a668d83 100644 --- a/R/read_soil_thickness_terra.R +++ b/R/read_soil_thickness_terra.R @@ -4,8 +4,12 @@ #' Read Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 #' data as a [terra::rast] object. #' -#' @param files An \pkg{read.abares} `read.abares.soil.thickness` object, a `list` that -#' contains the \acronym{ESRI} grid file to import +#' @inheritParams read_soil_thickness_stars +#' +#' @references +#' @source + +#' #' @return a [terra::rast] object of the Soil Thickness for Australian Areas of #' Intensive Agriculture of Layer 1 #' diff --git a/README.Rmd b/README.Rmd index 057fe8e..8e48181 100644 --- a/README.Rmd +++ b/README.Rmd @@ -30,18 +30,18 @@ However, if there is a data set that you feel would be useful to be serviced by Data serviced include: - [ABARES Estimates](https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download); - - Historical National Estimates, `get_historical_national_estimate()`; - - Historical State Estimates, `get_historical_state_estimates()`; - - Historical Regional Estimates, `get_historical_regional_estimates()`; - - Estimates by Size, `get_estimates_by_size()`; - - Estimates by Performance Category, `get_estimates_by_performance_category()`; + - Historical National Estimates, `read_historical_national_estimate()`; + - Historical State Estimates, `read_historical_state_estimates()`; + - Historical Regional Estimates, `read_historical_regional_estimates()`; + - Estimates by Size, `read_estimates_by_size()`; + - Estimates by Performance Category, `read_estimates_by_performance_category()`; - the [Australian Gridded Farm Data (AGFD) set](https://www.agriculture.gov.au/abares/research-topics/surveys/farm-survey-data/australian-gridded-farm-data), `get_agfd()`; - the [Australian Agricultural and Grazing Industries Survey (AAGIS)](https://www.agriculture.gov.au/abares/research-topics/surveys/farm-survey-data) region mapping files, `get_aagis_regions()`; -- the [Historical Agricultural Forecast Database](https://www.agriculture.gov.au/abares/research-topics/agricultural-outlook/historical-forecasts#:~:text=About%20the%20historical%20agricultural%20forecast,relevant%20to%20Australian%20agricultural%20markets), `get_historical_forecast_database()`; +- the [Historical Agricultural Forecast Database](https://www.agriculture.gov.au/abares/research-topics/agricultural-outlook/historical-forecasts#:~:text=About%20the%20historical%20agricultural%20forecast,relevant%20to%20Australian%20agricultural%20markets), `read_historical_forecast_database()`; - a [Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) (derived from soil mapping)](https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6) map, `get_soil_thickness()` and; - the [ABARES Trade Data](https://www.agriculture.gov.au/abares/research-topics/trade/dashboard) including; - - Trade Data, `get_abares_trade()` and; - - Trade Region Data, `get_abares_trade_regions()`. + - Trade Data, `read_abares_trade()` and; + - Trade Region Data, `read_abares_trade_regions()`. The files are freely available as CSV files, zip archives of NetCDF files or a zip archives of geospatial shape files. {read.abares} facilitates downloading, caching and importing these files in your R session with your choice of the class of the resulting object(s). diff --git a/README.md b/README.md index 5c431cf..08e7c03 100644 --- a/README.md +++ b/README.md @@ -30,13 +30,14 @@ Data serviced include: - [ABARES Estimates](https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download); - - Historical National Estimates, `get_historical_national_estimate()`; - - Historical State Estimates, `get_historical_state_estimates()`; + - Historical National Estimates, + `read_historical_national_estimate()`; + - Historical State Estimates, `read_historical_state_estimates()`; - Historical Regional Estimates, - `get_historical_regional_estimates()`; - - Estimates by Size, `get_estimates_by_size()`; + `read_historical_regional_estimates()`; + - Estimates by Size, `read_estimates_by_size()`; - Estimates by Performance Category, - `get_estimates_by_performance_category()`; + `read_estimates_by_performance_category()`; - the [Australian Gridded Farm Data (AGFD) set](https://www.agriculture.gov.au/abares/research-topics/surveys/farm-survey-data/australian-gridded-farm-data), `get_agfd()`; @@ -45,7 +46,7 @@ Data serviced include: region mapping files, `get_aagis_regions()`; - the [Historical Agricultural Forecast Database](https://www.agriculture.gov.au/abares/research-topics/agricultural-outlook/historical-forecasts#:~:text=About%20the%20historical%20agricultural%20forecast,relevant%20to%20Australian%20agricultural%20markets), - `get_historical_forecast_database()`; + `read_historical_forecast_database()`; - a [Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) (derived from soil mapping)](https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6) @@ -53,8 +54,8 @@ Data serviced include: - the [ABARES Trade Data](https://www.agriculture.gov.au/abares/research-topics/trade/dashboard) including; - - Trade Data, `get_abares_trade()` and; - - Trade Region Data, `get_abares_trade_regions()`. + - Trade Data, `read_abares_trade()` and; + - Trade Region Data, `read_abares_trade_regions()`. The files are freely available as CSV files, zip archives of NetCDF files or a zip archives of geospatial shape files. {read.abares} @@ -141,26 +142,19 @@ library("read.abares") #> #> plot citation("read.abares") -#> Warning in citation("read.abares"): could not determine year for 'read.abares' -#> from package DESCRIPTION file #> To cite package 'read.abares' in publications use: #> -#> Sparks A (????). _read.abares: Provides simple downloading, parsing -#> and importing of Australian Bureau of Agricultural and Resource -#> Economics and Sciences (ABARES) data sources_. R package version -#> 0.1.0, https://adamhsparks.codeberg.page/read.abares, -#> . +#> Sparks A (????). _read.abares: Simple downloading and importing of +#> ABARES Data_. R package version 0.1.0, +#> . #> #> A BibTeX entry for LaTeX users is #> #> @Manual{, -#> title = {read.abares: Provides simple downloading, parsing and importing of Australian -#> Bureau of Agricultural and Resource Economics and Sciences (ABARES) data -#> sources}, +#> title = {{read.abares}: Simple downloading and importing of ABARES Data}, #> author = {Adam H. Sparks}, -#> note = {R package version 0.1.0, -#> https://adamhsparks.codeberg.page/read.abares}, -#> url = {https://codeberg.org/adamhsparks/read.abares}, +#> note = {R package version 0.1.0}, +#> url = {https://adamhsparks.codeberg.page/read.abares/}, #> } ``` diff --git a/man/get_agfd.Rd b/man/get_agfd.Rd index d09d051..8eaf772 100644 --- a/man/get_agfd.Rd +++ b/man/get_agfd.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/get_agfd.R \name{get_agfd} \alias{get_agfd} -\title{Fetch Australian Gridded Farm Data} +\title{Get Australian Gridded Farm Data for Local Use} \source{ \itemize{ \item Historical climate prices fixed -- \url{https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1036161/3}, @@ -197,7 +197,7 @@ the perspective of Australian farmers}, Climate Risk Management, Volume 35, } \seealso{ Other AGFD: -\code{\link{get_aagis_regions}()}, +\code{\link{read_aagis_regions}()}, \code{\link{read_agfd_dt}()}, \code{\link{read_agfd_stars}()}, \code{\link{read_agfd_terra}()}, diff --git a/man/get_estimates_by_performance_category.Rd b/man/get_estimates_by_performance_category.Rd deleted file mode 100644 index 27d1104..0000000 --- a/man/get_estimates_by_performance_category.Rd +++ /dev/null @@ -1,40 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_estimates_by_performance_category.R -\name{get_estimates_by_performance_category} -\alias{get_estimates_by_performance_category} -\alias{get_est_by_perf_cat} -\title{Get Estimates by Size From ABARES} -\source{ -\url{https://www.agriculture.gov.au/sites/default/files/documents/fdp-BySize-ByPerformance.csv} -} -\usage{ -get_estimates_by_performance_category() - -get_est_by_perf_cat() -} -\value{ -A \link[data.table:data.table]{data.table::data.table} object -} -\description{ -Get Estimates by Size From ABARES -} -\examples{ -\dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} - - get_estimates_by_performance_category() - - # or shorter - get_est_by_perf_cat() -\dontshow{\}) # examplesIf} -} -\references{ -\url{https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download} -} -\seealso{ -Other Estimates: -\code{\link{get_estimates_by_size}()}, -\code{\link{get_historical_national_estimates}()}, -\code{\link{get_historical_regional_estimates}()}, -\code{\link{get_historical_state_estimates}()} -} -\concept{Estimates} diff --git a/man/get_soil_thickness.Rd b/man/get_soil_thickness.Rd index ea5af9b..db6cde2 100644 --- a/man/get_soil_thickness.Rd +++ b/man/get_soil_thickness.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/get_soil_thickness.R \name{get_soil_thickness} \alias{get_soil_thickness} -\title{Download Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1} +\title{Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use} \source{ \url{https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip} } @@ -26,7 +26,7 @@ the file path of the resulting \acronym{ESRI} Grid file and text file of metadata } \description{ -Download Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 +Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use } \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} diff --git a/man/get_aagis_regions.Rd b/man/read_aagis_regions.Rd similarity index 86% rename from man/get_aagis_regions.Rd rename to man/read_aagis_regions.Rd index b2aeff2..eb1f68d 100644 --- a/man/get_aagis_regions.Rd +++ b/man/read_aagis_regions.Rd @@ -1,13 +1,13 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_aagis_regions.R -\name{get_aagis_regions} -\alias{get_aagis_regions} -\title{Get AAGIS Region Mapping Files} +% Please edit documentation in R/read_aagis_regions.R +\name{read_aagis_regions} +\alias{read_aagis_regions} +\title{Read AAGIS Region Mapping Files} \source{ \url{https://www.agriculture.gov.au/sites/default/files/documents/aagis_asgs16v1_g5a.shp_.zip} } \usage{ -get_aagis_regions(cache = TRUE) +read_aagis_regions(cache = TRUE) } \arguments{ \item{cache}{\code{Boolean} Cache the \acronym{AAGIS} regions' geospatial file @@ -28,7 +28,7 @@ geometries that are present in the original shapefile. } \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} -aagis <- get_aagis_regions() +aagis <- read_aagis_regions() plot(aagis) \dontshow{\}) # examplesIf} diff --git a/man/get_abares_trade.Rd b/man/read_abares_trade.Rd similarity index 81% rename from man/get_abares_trade.Rd rename to man/read_abares_trade.Rd index 615014f..4721ae4 100644 --- a/man/get_abares_trade.Rd +++ b/man/read_abares_trade.Rd @@ -1,13 +1,13 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_abares_trade.R -\name{get_abares_trade} -\alias{get_abares_trade} -\title{Get Data From the ABARES Trade Dashboard} +% Please edit documentation in R/read_abares_trade.R +\name{read_abares_trade} +\alias{read_abares_trade} +\title{Read Data From the ABARES Trade Dashboard} \source{ \url{https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/0} } \usage{ -get_abares_trade(cache = TRUE) +read_abares_trade(cache = TRUE) } \arguments{ \item{cache}{\code{Boolean} Cache the \acronym{ABARES} trade data after download @@ -28,7 +28,7 @@ serviced in this package using a snake_case format and ordered consistently. } \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} -trade <- get_abares_trade() +trade <- read_abares_trade() trade \dontshow{\}) # examplesIf} @@ -38,6 +38,6 @@ trade } \seealso{ Other Trade: -\code{\link{get_abares_trade_regions}()} +\code{\link{read_abares_trade_regions}()} } \concept{Trade} diff --git a/man/get_abares_trade_regions.Rd b/man/read_abares_trade_regions.Rd similarity index 78% rename from man/get_abares_trade_regions.Rd rename to man/read_abares_trade_regions.Rd index 67558b4..d7029b4 100644 --- a/man/get_abares_trade_regions.Rd +++ b/man/read_abares_trade_regions.Rd @@ -1,13 +1,13 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_abares_trade_regions.R -\name{get_abares_trade_regions} -\alias{get_abares_trade_regions} -\title{Get ABARES Trade Data Regions From the ABARES Trade Dashboard} +% Please edit documentation in R/read_abares_trade_regions.R +\name{read_abares_trade_regions} +\alias{read_abares_trade_regions} +\title{Read ABARES Trade Data Regions From the ABARES Trade Dashboard} \source{ \url{https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/2} } \usage{ -get_abares_trade_regions(cache = TRUE) +read_abares_trade_regions(cache = TRUE) } \arguments{ \item{cache}{\code{Boolean} Cache the \acronym{ABARES} trade regions data after @@ -29,7 +29,7 @@ serviced in this package using a snake_case format and ordered consistently. } \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} -trade_regions <- get_abares_trade_regions() +trade_regions <- read_abares_trade_regions() trade_regions \dontshow{\}) # examplesIf} @@ -39,6 +39,6 @@ trade_regions } \seealso{ Other Trade: -\code{\link{get_abares_trade}()} +\code{\link{read_abares_trade}()} } \concept{Trade} diff --git a/man/read_agfd_dt.Rd b/man/read_agfd_dt.Rd index 938958e..f043443 100644 --- a/man/read_agfd_dt.Rd +++ b/man/read_agfd_dt.Rd @@ -181,8 +181,8 @@ the perspective of Australian farmers}, Climate Risk Management, Volume 35, } \seealso{ Other AGFD: -\code{\link{get_aagis_regions}()}, \code{\link{get_agfd}()}, +\code{\link{read_aagis_regions}()}, \code{\link{read_agfd_stars}()}, \code{\link{read_agfd_terra}()}, \code{\link{read_agfd_tidync}()} diff --git a/man/read_agfd_stars.Rd b/man/read_agfd_stars.Rd index caeabd8..4abaa34 100644 --- a/man/read_agfd_stars.Rd +++ b/man/read_agfd_stars.Rd @@ -187,8 +187,8 @@ the perspective of Australian farmers}, Climate Risk Management, Volume 35, } \seealso{ Other AGFD: -\code{\link{get_aagis_regions}()}, \code{\link{get_agfd}()}, +\code{\link{read_aagis_regions}()}, \code{\link{read_agfd_dt}()}, \code{\link{read_agfd_terra}()}, \code{\link{read_agfd_tidync}()} diff --git a/man/read_agfd_terra.Rd b/man/read_agfd_terra.Rd index 3bf9f03..54e9f9a 100644 --- a/man/read_agfd_terra.Rd +++ b/man/read_agfd_terra.Rd @@ -183,8 +183,8 @@ the perspective of Australian farmers}, Climate Risk Management, Volume 35, } \seealso{ Other AGFD: -\code{\link{get_aagis_regions}()}, \code{\link{get_agfd}()}, +\code{\link{read_aagis_regions}()}, \code{\link{read_agfd_dt}()}, \code{\link{read_agfd_stars}()}, \code{\link{read_agfd_tidync}()} diff --git a/man/read_agfd_tidync.Rd b/man/read_agfd_tidync.Rd index 047e083..44536a9 100644 --- a/man/read_agfd_tidync.Rd +++ b/man/read_agfd_tidync.Rd @@ -184,8 +184,8 @@ the perspective of Australian farmers}, Climate Risk Management, Volume 35, } \seealso{ Other AGFD: -\code{\link{get_aagis_regions}()}, \code{\link{get_agfd}()}, +\code{\link{read_aagis_regions}()}, \code{\link{read_agfd_dt}()}, \code{\link{read_agfd_stars}()}, \code{\link{read_agfd_terra}()} diff --git a/man/read_estimates_by_performance_category.Rd b/man/read_estimates_by_performance_category.Rd new file mode 100644 index 0000000..e8e6345 --- /dev/null +++ b/man/read_estimates_by_performance_category.Rd @@ -0,0 +1,40 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/read_estimates_by_performance_category.R +\name{read_estimates_by_performance_category} +\alias{read_estimates_by_performance_category} +\alias{read_est_by_perf_cat} +\title{Read Estimates by Size From ABARES} +\source{ +\url{https://www.agriculture.gov.au/sites/default/files/documents/fdp-BySize-ByPerformance.csv} +} +\usage{ +read_estimates_by_performance_category() + +read_est_by_perf_cat() +} +\value{ +A \link[data.table:data.table]{data.table::data.table} object +} +\description{ +Read Estimates by Size From ABARES +} +\examples{ +\dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} + + read_estimates_by_performance_category() + + # or shorter + read_est_by_perf_cat() +\dontshow{\}) # examplesIf} +} +\references{ +\url{https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download} +} +\seealso{ +Other Estimates: +\code{\link{read_estimates_by_size}()}, +\code{\link{read_historical_national_estimates}()}, +\code{\link{read_historical_regional_estimates}()}, +\code{\link{read_historical_state_estimates}()} +} +\concept{Estimates} diff --git a/man/get_estimates_by_size.Rd b/man/read_estimates_by_size.Rd similarity index 56% rename from man/get_estimates_by_size.Rd rename to man/read_estimates_by_size.Rd index ee47eb1..4f5afee 100644 --- a/man/get_estimates_by_size.Rd +++ b/man/read_estimates_by_size.Rd @@ -1,23 +1,23 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_estimates_by_size.R -\name{get_estimates_by_size} -\alias{get_estimates_by_size} -\alias{get_est_by_size} -\title{Get Estimates by Size From ABARES} +% Please edit documentation in R/read_estimates_by_size.R +\name{read_estimates_by_size} +\alias{read_estimates_by_size} +\alias{read_est_by_size} +\title{Read Estimates by Size From ABARES} \source{ \url{https://www.agriculture.gov.au/sites/default/files/documents/fdp-national-historical.csv} } \usage{ -get_estimates_by_size() +read_estimates_by_size() -get_est_by_size() +read_est_by_size() } \value{ A \link[data.table:data.table]{data.table::data.table} object with the \code{Variable} field as the \code{key}. } \description{ -Get Estimates by Size From ABARES +Read Estimates by Size From ABARES } \note{ Columns are renamed and reordered for consistency. @@ -25,10 +25,10 @@ Columns are renamed and reordered for consistency. \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} -get_estimates_by_size() +read_estimates_by_size() # or shorter -get_est_by_size() +read_est_by_size() \dontshow{\}) # examplesIf} } \references{ @@ -36,9 +36,9 @@ get_est_by_size() } \seealso{ Other Estimates: -\code{\link{get_estimates_by_performance_category}()}, -\code{\link{get_historical_national_estimates}()}, -\code{\link{get_historical_regional_estimates}()}, -\code{\link{get_historical_state_estimates}()} +\code{\link{read_estimates_by_performance_category}()}, +\code{\link{read_historical_national_estimates}()}, +\code{\link{read_historical_regional_estimates}()}, +\code{\link{read_historical_state_estimates}()} } \concept{Estimates} diff --git a/man/get_historical_forecast_database.Rd b/man/read_historical_forecast_database.Rd similarity index 82% rename from man/get_historical_forecast_database.Rd rename to man/read_historical_forecast_database.Rd index c8df1e7..2204b1a 100644 --- a/man/get_historical_forecast_database.Rd +++ b/man/read_historical_forecast_database.Rd @@ -1,22 +1,22 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_historical_forecast_database.R -\name{get_historical_forecast_database} -\alias{get_historical_forecast_database} -\alias{get_historical_forecast} -\title{Get Historical Forecast Database From ABARES} +% Please edit documentation in R/read_historical_forecast_database.R +\name{read_historical_forecast_database} +\alias{read_historical_forecast_database} +\alias{read_historical_forecast} +\title{Read Historical Forecast Database From ABARES} \source{ \url{https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1031941/0} } \usage{ -get_historical_forecast_database() +read_historical_forecast_database() -get_historical_forecast() +read_historical_forecast() } \value{ -A \link[data.table:data.table]{data.table::data.table} object. +A \link[data.table:data.table]{data.table::data.table} object } \description{ -Get Historical Forecast Database From ABARES +Read Historical Forecast Database From ABARES } \details{ \tabular{ll}{ @@ -48,10 +48,10 @@ The resulting object will contain the following fields. \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} -get_historical_forecast_database() +read_historical_forecast_database() # or shorter -get_historical_forecast() +read_historical_forecast() \dontshow{\}) # examplesIf} } \references{ diff --git a/man/get_historical_national_estimates.Rd b/man/read_historical_national_estimates.Rd similarity index 56% rename from man/get_historical_national_estimates.Rd rename to man/read_historical_national_estimates.Rd index 3145e3e..571ae30 100644 --- a/man/get_historical_national_estimates.Rd +++ b/man/read_historical_national_estimates.Rd @@ -1,23 +1,23 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_historical_national_estimates.R -\name{get_historical_national_estimates} -\alias{get_historical_national_estimates} -\alias{get_hist_nat_est} -\title{Get Historical National Estimates from ABARES} +% Please edit documentation in R/read_historical_national_estimates.R +\name{read_historical_national_estimates} +\alias{read_historical_national_estimates} +\alias{read_hist_nat_est} +\title{Read Historical National Estimates from ABARES} \source{ \url{https://www.agriculture.gov.au/sites/default/files/documents/fdp-national-historical.csv} } \usage{ -get_historical_national_estimates() +read_historical_national_estimates() -get_hist_nat_est() +read_hist_nat_est() } \value{ A \link[data.table:data.table]{data.table::data.table} object with the \code{Variable} field as the \code{key}. } \description{ -Get Historical National Estimates from ABARES +Read Historical National Estimates from ABARES } \note{ Columns are renamed for consistency with other \acronym{ABARES} products @@ -26,10 +26,10 @@ serviced in this package using a snake_case format and ordered consistently. \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} - get_historical_national_estimates() + read_historical_national_estimates() # or shorter - get_hist_nat_est() + read_hist_nat_est() \dontshow{\}) # examplesIf} } \references{ @@ -37,9 +37,9 @@ serviced in this package using a snake_case format and ordered consistently. } \seealso{ Other Estimates: -\code{\link{get_estimates_by_performance_category}()}, -\code{\link{get_estimates_by_size}()}, -\code{\link{get_historical_regional_estimates}()}, -\code{\link{get_historical_state_estimates}()} +\code{\link{read_estimates_by_performance_category}()}, +\code{\link{read_estimates_by_size}()}, +\code{\link{read_historical_regional_estimates}()}, +\code{\link{read_historical_state_estimates}()} } \concept{Estimates} diff --git a/man/get_historical_regional_estimates.Rd b/man/read_historical_regional_estimates.Rd similarity index 56% rename from man/get_historical_regional_estimates.Rd rename to man/read_historical_regional_estimates.Rd index a5f41ea..69c1bae 100644 --- a/man/get_historical_regional_estimates.Rd +++ b/man/read_historical_regional_estimates.Rd @@ -1,23 +1,23 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_historical_regional_estimates.R -\name{get_historical_regional_estimates} -\alias{get_historical_regional_estimates} -\alias{get_hist_reg_est} -\title{Get Historical Regional Estimates from ABARES} +% Please edit documentation in R/read_historical_regional_estimates.R +\name{read_historical_regional_estimates} +\alias{read_historical_regional_estimates} +\alias{read_hist_reg_est} +\title{Read Historical Regional Estimates from ABARES} \source{ \url{https://www.agriculture.gov.au/sites/default/files/documents/fdp-regional-historical.csv} } \usage{ -get_historical_regional_estimates() +read_historical_regional_estimates() -get_hist_reg_est() +read_hist_reg_est() } \value{ A \link[data.table:data.table]{data.table::data.table} object with the \code{Variable} field as the \code{key}. } \description{ -Get Historical Regional Estimates from ABARES +Read Historical Regional Estimates from ABARES } \note{ Columns are renamed for consistency with other \acronym{ABARES} products @@ -25,10 +25,10 @@ serviced in this package using a snake_case format and ordered consistently. } \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} - get_historical_regional_estimates() + read_historical_regional_estimates() # or shorter - get_hist_reg_est() + read_hist_reg_est() \dontshow{\}) # examplesIf} } \references{ @@ -36,9 +36,9 @@ serviced in this package using a snake_case format and ordered consistently. } \seealso{ Other Estimates: -\code{\link{get_estimates_by_performance_category}()}, -\code{\link{get_estimates_by_size}()}, -\code{\link{get_historical_national_estimates}()}, -\code{\link{get_historical_state_estimates}()} +\code{\link{read_estimates_by_performance_category}()}, +\code{\link{read_estimates_by_size}()}, +\code{\link{read_historical_national_estimates}()}, +\code{\link{read_historical_state_estimates}()} } \concept{Estimates} diff --git a/man/get_historical_state_estimates.Rd b/man/read_historical_state_estimates.Rd similarity index 56% rename from man/get_historical_state_estimates.Rd rename to man/read_historical_state_estimates.Rd index 7e64f7c..a446ed4 100644 --- a/man/get_historical_state_estimates.Rd +++ b/man/read_historical_state_estimates.Rd @@ -1,23 +1,23 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_historical_state_estimates.R -\name{get_historical_state_estimates} -\alias{get_historical_state_estimates} -\alias{get_hist_sta_est} -\title{Get Historical State Estimates from ABARES} +% Please edit documentation in R/read_historical_state_estimates.R +\name{read_historical_state_estimates} +\alias{read_historical_state_estimates} +\alias{read_hist_sta_est} +\title{Read Historical State Estimates from ABARES} \source{ \url{https://www.agriculture.gov.au/sites/default/files/documents/fdp-state-historical.csv} } \usage{ -get_historical_state_estimates() +read_historical_state_estimates() -get_hist_sta_est() +read_hist_sta_est() } \value{ A \link[data.table:data.table]{data.table::data.table} object with the \code{Variable} field as the \code{key}. } \description{ -Get Historical State Estimates from ABARES +Read Historical State Estimates from ABARES } \note{ Columns are renamed for consistency with other \acronym{ABARES} products @@ -25,10 +25,10 @@ serviced in this package using a snake_case format and ordered consistently. } \examples{ \dontshow{if (interactive()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf} - get_historical_state_estimates() + read_historical_state_estimates() # or shorter - get_hist_sta_est() + read_hist_sta_est() \dontshow{\}) # examplesIf} } \references{ @@ -36,9 +36,9 @@ serviced in this package using a snake_case format and ordered consistently. } \seealso{ Other Estimates: -\code{\link{get_estimates_by_performance_category}()}, -\code{\link{get_estimates_by_size}()}, -\code{\link{get_historical_national_estimates}()}, -\code{\link{get_historical_regional_estimates}()} +\code{\link{read_estimates_by_performance_category}()}, +\code{\link{read_estimates_by_size}()}, +\code{\link{read_historical_national_estimates}()}, +\code{\link{read_historical_regional_estimates}()} } \concept{Estimates} diff --git a/man/read_soil_thickness_stars.Rd b/man/read_soil_thickness_stars.Rd index eee47ed..b389a1e 100644 --- a/man/read_soil_thickness_stars.Rd +++ b/man/read_soil_thickness_stars.Rd @@ -3,6 +3,9 @@ \name{read_soil_thickness_stars} \alias{read_soil_thickness_stars} \title{Read Soil Thickness File With stars} +\source{ +\url{https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip} +} \usage{ read_soil_thickness_stars(files) } @@ -24,6 +27,9 @@ get_soil_thickness(cache = TRUE) |> read_soil_thickness_stars() \dontshow{\}) # examplesIf} } +\references{ +\url{https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6} +} \seealso{ Other soil_thickness: \code{\link{get_soil_thickness}()}, diff --git a/man/read_soil_thickness_terra.Rd b/man/read_soil_thickness_terra.Rd index 885a1b0..85c7d51 100644 --- a/man/read_soil_thickness_terra.Rd +++ b/man/read_soil_thickness_terra.Rd @@ -3,12 +3,15 @@ \name{read_soil_thickness_terra} \alias{read_soil_thickness_terra} \title{Read Soil Thickness File With terra} +\source{ +\url{https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip} +} \usage{ read_soil_thickness_terra(files) } \arguments{ -\item{files}{An \pkg{read.abares} \code{read.abares.soil.thickness} object, a \code{list} that -contains the \acronym{ESRI} grid file to import} +\item{files}{An \pkg{read.abares} \code{read.abares.soil.thickness} object, a +\code{list} that contains the \acronym{ESRI} grid file to import} } \value{ a \link[terra:rast]{terra::rast} object of the Soil Thickness for Australian Areas of @@ -27,6 +30,9 @@ x <- get_soil_thickness(cache = TRUE) |> plot(x) \dontshow{\}) # examplesIf} } +\references{ +\url{https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6} +} \seealso{ Other soil_thickness: \code{\link{get_soil_thickness}()}, diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml index 1322589..409b547 100644 --- a/pkgdown/_pkgdown.yml +++ b/pkgdown/_pkgdown.yml @@ -21,19 +21,24 @@ reference: - read_agfd_stars - read_agfd_terra - read_agfd_tidync + - subtitle: Meta + desc: | + Information about the AGFD NetCDF files and contents + contents: + - print_agfd_nc_file_format - title: Estimates desc: | Fetch and read the ABARES Estimates data contents: - - get_estimates_by_performance_category - - get_estimates_by_size - - get_historical_national_estimates - - get_historical_regional_estimates - - get_historical_state_estimates + - read_estimates_by_performance_category + - read_estimates_by_size + - read_historical_national_estimates + - read_historical_regional_estimates + - read_historical_state_estimates - title: Historical agricultural forecast database desc: | Fetch and read the historical agricultural forecast database - contents: get_historical_forecast_database + contents: read_historical_forecast_database - title: Cache desc: | Work with your local file cache @@ -52,6 +57,6 @@ reference: desc: | Fetch and read ABARES' Australian agricultural export data contents: - - get_abares_trade - - get_abares_trade_regions + - read_abares_trade + - read_abares_trade_regions diff --git a/tests/testthat/test-get_aagis_regions.R b/tests/testthat/test-read_aagis_regions.R similarity index 75% rename from tests/testthat/test-get_aagis_regions.R rename to tests/testthat/test-read_aagis_regions.R index 87ad4fe..f5453d7 100644 --- a/tests/testthat/test-get_aagis_regions.R +++ b/tests/testthat/test-read_aagis_regions.R @@ -3,10 +3,10 @@ withr::local_envvar(R_USER_CACHE_DIR = file.path(tempdir(), "abares.cache.1")) # without caching ---- -test_that("get_aagis_regions doesn't cache", { +test_that("read_aagis_regions doesn't cache", { skip_if_offline() skip_on_ci() - x <- get_aagis_regions(cache = FALSE) + x <- read_aagis_regions(cache = FALSE) expect_s3_class(x, "sf") expect_false(file.exists( file.path(.find_user_cache(), "aagis_regions_dir/aagis.gpkg") @@ -14,7 +14,7 @@ test_that("get_aagis_regions doesn't cache", { }) -test_that("get_aagis_regions skips downloading if still in tempdir()", { +test_that("read_aagis_regions skips downloading if still in tempdir()", { skip_if_offline() skip_on_ci() x <- .check_existing_aagis(cache = FALSE) @@ -23,10 +23,10 @@ test_that("get_aagis_regions skips downloading if still in tempdir()", { # with caching ---- -test_that("get_aagis_regions caches", { +test_that("read_aagis_regions caches", { skip_if_offline() skip_on_ci() - x <- get_aagis_regions(cache = TRUE) + x <- read_aagis_regions(cache = TRUE) expect_s3_class(x, "sf") expect_true(file.exists( file.path(.find_user_cache(), "aagis_regions_dir/aagis.gpkg") @@ -39,7 +39,7 @@ test_that("get_aagis_regions caches", { ))) }) -test_that("get_aagis_regions skips downloading if cache is available", { +test_that("read_aagis_regions skips downloading if cache is available", { skip_if_offline() skip_on_ci() x <- .check_existing_aagis(cache = TRUE) @@ -50,10 +50,10 @@ test_that("get_aagis_regions skips downloading if cache is available", { withr::local_envvar(R_USER_CACHE_DIR = file.path(tempdir(), "abares.cache.2")) -test_that("get_aagis_regions does cache", { +test_that("read_aagis_regions does cache", { skip_if_offline() skip_on_ci() - x <- get_aagis_regions(cache = TRUE) + x <- read_aagis_regions(cache = TRUE) expect_s3_class(x, "sf") expect_true(file.exists( file.path(.find_user_cache(), "aagis_regions_dir/aagis.gpkg") @@ -66,7 +66,7 @@ test_that("get_aagis_regions does cache", { )) }) -test_that("get_aagis_regions skips downloading if still in tempdir()", { +test_that("read_aagis_regions skips downloading if still in tempdir()", { skip_if_offline() skip_on_ci() x <- .check_existing_aagis(cache = TRUE) diff --git a/tests/testthat/test-get_abares_trade.R b/tests/testthat/test-read_abares_trade.R similarity index 91% rename from tests/testthat/test-get_abares_trade.R rename to tests/testthat/test-read_abares_trade.R index be205da..76e4c6b 100644 --- a/tests/testthat/test-get_abares_trade.R +++ b/tests/testthat/test-read_abares_trade.R @@ -4,10 +4,10 @@ withr::local_envvar(R_USER_CACHE_DIR = file.path(tempdir(), "abares.cache.1")) # without caching ---- -test_that("get_abares_trade doesn't cache", { +test_that("read_abares_trade doesn't cache", { skip_if_offline() skip_on_ci() - x <- get_abares_trade(cache = FALSE) + x <- read_abares_trade(cache = FALSE) expect_s3_class(x, c("data.table", "data.frame")) expect_named( x, @@ -57,10 +57,10 @@ test_that("get_abares_trade doesn't cache", { # with caching ---- -test_that("get_abares_trade caches", { +test_that("read_abares_trade caches", { skip_if_offline() skip_on_ci() - x <- get_abares_trade(cache = TRUE) + x <- read_abares_trade(cache = TRUE) expect_s3_class(x, c("data.table", "data.frame")) y <- list.files(file.path(.find_user_cache(), "abares_trade_dir")) expect_true(file.exists( diff --git a/tests/testthat/test-get_abares_trade_regions.R b/tests/testthat/test-read_abares_trade_regions.R similarity index 81% rename from tests/testthat/test-get_abares_trade_regions.R rename to tests/testthat/test-read_abares_trade_regions.R index edf407a..df8b2cf 100644 --- a/tests/testthat/test-get_abares_trade_regions.R +++ b/tests/testthat/test-read_abares_trade_regions.R @@ -4,10 +4,10 @@ withr::local_envvar(R_USER_CACHE_DIR = file.path(tempdir(), "abares.cache.1")) # without caching ---- -test_that("get_abares_trade_regions doesn't cache", { +test_that("read_abares_trade_regions doesn't cache", { skip_if_offline() skip_on_ci() - x <- get_abares_trade_regions(cache = FALSE) + x <- read_abares_trade_regions(cache = FALSE) expect_s3_class(x, c("data.table", "data.frame")) expect_named(x, c("Classification", @@ -34,7 +34,7 @@ test_that("get_abares_trade_regions doesn't cache", { )) }) -test_that("get_abares_trade_regions skips downloading if still in tempdir()", { +test_that("read_abares_trade_regions skips downloading if still in tempdir()", { skip_if_offline() skip_on_ci() x <- .check_existing_trade_regions(cache = FALSE) @@ -43,10 +43,10 @@ test_that("get_abares_trade_regions skips downloading if still in tempdir()", { # with caching ---- -test_that("get_abares_trade_regions caches", { +test_that("read_abares_trade_regions caches", { skip_if_offline() skip_on_ci() - x <- get_abares_trade_regions(cache = TRUE) + x <- read_abares_trade_regions(cache = TRUE) expect_s3_class(x, c("data.table", "data.frame")) y <- list.files(file.path(.find_user_cache(), "abares_trade_dir")) expect_true(file.exists( @@ -57,7 +57,7 @@ test_that("get_abares_trade_regions caches", { )) }) -test_that("get_abares_trade_regions skips downloading if cache is available", { +test_that("read_abares_trade_regions skips downloading if cache is available", { skip_if_offline() skip_on_ci() x <- .check_existing_trade_regions(cache = TRUE) diff --git a/tests/testthat/test-get_estimates_by_performance_category.R b/tests/testthat/test-read_estimates_by_performance_category.R similarity index 75% rename from tests/testthat/test-get_estimates_by_performance_category.R rename to tests/testthat/test-read_estimates_by_performance_category.R index 6d8b643..cf98f31 100644 --- a/tests/testthat/test-get_estimates_by_performance_category.R +++ b/tests/testthat/test-read_estimates_by_performance_category.R @@ -1,7 +1,7 @@ -test_that("get_estimates_by_performance_category() works", { +test_that("read_estimates_by_performance_category() works", { skip_if_offline() skip_on_ci() - x <- get_estimates_by_performance_category() + x <- read_estimates_by_performance_category() expect_named(x, c("Variable", "Year", "Size", "Value", "RSE")) expect_s3_class(x, c("data.table", "data.frame")) expect_identical( diff --git a/tests/testthat/test-get_estimates_by_size.R b/tests/testthat/test-read_estimates_by_size.R similarity index 83% rename from tests/testthat/test-get_estimates_by_size.R rename to tests/testthat/test-read_estimates_by_size.R index 7ec27d5..51ee409 100644 --- a/tests/testthat/test-get_estimates_by_size.R +++ b/tests/testthat/test-read_estimates_by_size.R @@ -1,8 +1,8 @@ -test_that("get_estimates_by_size works", { +test_that("read_estimates_by_size works", { skip_if_offline() skip_on_ci() - x <- get_estimates_by_size() + x <- read_estimates_by_size() expect_named(x, c("Variable", "Year", "Size", "Industry", "Value", "RSE")) expect_s3_class(x, c("data.table", "data.frame")) expect_identical( diff --git a/tests/testthat/test-get_historical_forecast_database.R b/tests/testthat/test-read_historical_forecast_database.R similarity index 90% rename from tests/testthat/test-get_historical_forecast_database.R rename to tests/testthat/test-read_historical_forecast_database.R index 23fe4fe..d1d3dcc 100644 --- a/tests/testthat/test-get_historical_forecast_database.R +++ b/tests/testthat/test-read_historical_forecast_database.R @@ -1,7 +1,8 @@ -test_that("get_historical_forecast() works", { + +test_that("read_historical_forecast() works", { skip_if_offline() skip_on_ci() - x <- get_historical_forecast() + x <- read_historical_forecast() expect_named( x, c( diff --git a/tests/testthat/test-get_historical_national_estimates.R b/tests/testthat/test-read_historical_national_estimates.R similarity index 77% rename from tests/testthat/test-get_historical_national_estimates.R rename to tests/testthat/test-read_historical_national_estimates.R index 2469784..0d69051 100644 --- a/tests/testthat/test-get_historical_national_estimates.R +++ b/tests/testthat/test-read_historical_national_estimates.R @@ -1,8 +1,8 @@ -test_that("get_historical_national_estimates works", { +test_that("read_historical_national_estimates works", { skip_if_offline() skip_on_ci() - x <- get_historical_national_estimates() + x <- read_historical_national_estimates() expect_named(x, c("Variable", "Year", "Industry", "Value", "RSE")) expect_s3_class(x, c("data.table", "data.frame")) expect_identical( diff --git a/tests/testthat/test-get_historical_regional_estimates.R b/tests/testthat/test-read_historical_regional_estimates.R similarity index 78% rename from tests/testthat/test-get_historical_regional_estimates.R rename to tests/testthat/test-read_historical_regional_estimates.R index 0871373..9d5b102 100644 --- a/tests/testthat/test-get_historical_regional_estimates.R +++ b/tests/testthat/test-read_historical_regional_estimates.R @@ -1,8 +1,8 @@ -test_that("get_historical_regional_estimates works", { +test_that("read_historical_regional_estimates works", { skip_if_offline() skip_on_ci() - x <- get_historical_regional_estimates() + x <- read_historical_regional_estimates() expect_named(x, c("Variable", "Year", "ABARES_region", "Value", "RSE")) expect_s3_class(x, c("data.table", "data.frame")) expect_identical( diff --git a/tests/testthat/test-get_historical_state_estimates.R b/tests/testthat/test-read_historical_state_estimates.R similarity index 80% rename from tests/testthat/test-get_historical_state_estimates.R rename to tests/testthat/test-read_historical_state_estimates.R index b942dbf..da19658 100644 --- a/tests/testthat/test-get_historical_state_estimates.R +++ b/tests/testthat/test-read_historical_state_estimates.R @@ -1,8 +1,8 @@ -test_that("get_historical_state_estimates works", { +test_that("read_historical_state_estimates works", { skip_if_offline() skip_on_ci() - x <- get_historical_state_estimates() + x <- read_historical_state_estimates() expect_named(x, c("Variable", "Year", "State", "Industry", "Value", "RSE")) expect_s3_class(x, c("data.table", "data.frame")) expect_identical( From 40e5b058fa55a7d366ea7200d6de79eca7b11451 Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 10:53:30 +0800 Subject: [PATCH 02/10] Correct URLs --- inst/CITATION | 2 +- vignettes/read.abares.Rmd | 609 ++++++++++++++++----------------- vignettes/read.abares.Rmd.orig | 2 +- 3 files changed, 293 insertions(+), 320 deletions(-) diff --git a/inst/CITATION b/inst/CITATION index 84d5533..734e1e5 100644 --- a/inst/CITATION +++ b/inst/CITATION @@ -7,4 +7,4 @@ bibentry( ), year = sub("-.*", "", meta$Date), note = sprintf("R package version %s", meta$Version), - url = "https://adamhsparks.codeberg.page/read.abares/") + url = "https://adamhsparks.github.io/read.abares/") diff --git a/vignettes/read.abares.Rmd b/vignettes/read.abares.Rmd index 70befc2..db5a4ad 100644 --- a/vignettes/read.abares.Rmd +++ b/vignettes/read.abares.Rmd @@ -1,7 +1,7 @@ --- title: "read.abares" author: "Adam H. Sparks" -date: "2024-12-07" +date: "2024-12-08" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{read.abares} @@ -13,7 +13,7 @@ vignette: > This vignette demonstrates some of the functionality of {read.abares}. -Please note that not all functions are demonstrated here, please refer to the [documentation reference](https://adamhsparks.codeberg.page/read.abares/reference/) for a full list of functionality. +Please note that not all functions are demonstrated here, please refer to the [documentation reference](https://adamhsparks.github.io/read.abares/reference/) for a full list of functionality. The worked examples here show some of the more advanced features that {read.abares} offers beyond just fetching and importing data, _e.g._, the Australian Gridded Farm Data, which can be downloaded, cached and then imported using one of four types of object or the soil thickness data, which includes rich metadata. ## Working With AGFD Data @@ -47,16 +47,16 @@ Check the file format information for the NetCDF files. ``` r print_agfd_nc_file_format() -#> ──────────────────────────────────────────────────────────────────────────────────────── -#> Each of the layers in simulation output data is represented as a 2D raster in NETCDF -#> files, with the following grid format: +#> ──────────────────────────────────────────────────────────────────────────────────────────────────── +#> Each of the layers in simulation output data is represented as a 2D raster in NETCDF files, with +#> the following grid format: #> CRS: EPSG:4326 - WGS 84 – Geographic #> Extent: 111.975 -44.525 156.275 -9.975 #> Unit: Degrees #> Width: 886 #> Height: 691 #> Cell size: 0.05 degree x 0.05 degree -#> ──────────────────────────────────────────────────────────────────────────────────────── +#> ──────────────────────────────────────────────────────────────────────────────────────────────────── #> For further details, see the ABARES website, #> ``` @@ -76,20 +76,20 @@ star <- get_agfd(cache = TRUE) |> head(star[[1]]) #> stars object with 2 dimensions and 6 attributes #> attribute(s): -#> Min. 1st Qu. Median Mean -#> farmno 15612.000000 233091.50000000 329567.0000000 324737.7187618 -#> R_total_hat_ha 2.954396 7.88312157 21.7520529 169.5139301 -#> C_total_hat_ha 1.304440 4.34079101 9.9449849 93.2210542 -#> FBP_fci_hat_ha -143.759785 3.60529967 11.5796641 76.2928759 -#> FBP_fbp_hat_ha -349.521639 3.36599833 11.5074294 60.0750936 -#> A_wheat_hat_ha 0.000000 0.04062786 0.1114289 0.1365683 -#> 3rd Qu. Max. NA's -#> farmno 418508.5000000 669706.0000000 443899 -#> R_total_hat_ha 174.8553843 2415.7556059 443899 -#> C_total_hat_ha 95.7221857 1853.5385298 443899 -#> FBP_fci_hat_ha 77.6748501 1186.5830232 443899 -#> FBP_fbp_hat_ha 62.8596117 1240.6003218 443899 -#> A_wheat_hat_ha 0.2112845 0.5047761 565224 +#> Min. 1st Qu. Median Mean 3rd Qu. +#> farmno 15612.000000 233091.50000000 329567.0000000 324737.7187618 418508.5000000 +#> R_total_hat_ha 2.954396 7.88312157 21.7520529 169.5139301 174.8553843 +#> C_total_hat_ha 1.304440 4.34079101 9.9449849 93.2210542 95.7221857 +#> FBP_fci_hat_ha -143.759785 3.60529967 11.5796641 76.2928759 77.6748501 +#> FBP_fbp_hat_ha -349.521639 3.36599833 11.5074294 60.0750936 62.8596117 +#> A_wheat_hat_ha 0.000000 0.04062786 0.1114289 0.1365683 0.2112845 +#> Max. NA's +#> farmno 669706.0000000 443899 +#> R_total_hat_ha 2415.7556059 443899 +#> C_total_hat_ha 1853.5385298 443899 +#> FBP_fci_hat_ha 1186.5830232 443899 +#> FBP_fbp_hat_ha 1240.6003218 443899 +#> A_wheat_hat_ha 0.5047761 565224 #> dimension(s): #> from to refsys values x/y #> lon 1 886 WGS 84 [886] 112,...,156.2 [x] @@ -127,9 +127,9 @@ tdnc <- get_agfd(cache = TRUE) |> head(tdnc[[1]]) #> $source #> # A tibble: 1 × 2 -#> access source -#> -#> 1 2024-12-07 23:43:59 /Users/adamsparks/Library/Caches/org.R-project.R/R/read.abares/hi… +#> access source +#> +#> 1 2024-12-08 10:28:31 /Users/adamsparks/Library/Caches/org.R-project.R/R/read.abares/historical_cli… #> #> $axis #> # A tibble: 84 × 3 @@ -203,78 +203,70 @@ Download or load from the local cache and read the AGFD files as a {data.table} get_agfd(cache = TRUE) |> read_agfd_dt() |> head() -#> id farmno R_total_hat_ha C_total_hat_ha FBP_fci_hat_ha -#> -#> 1: f2022.c1991.p2022.t2022.nc 15612 7.636519 4.405228 3.231292 -#> 2: f2022.c1991.p2022.t2022.nc 21495 14.811169 9.165632 5.645538 -#> 3: f2022.c1991.p2022.t2022.nc 23418 24.874456 14.858595 10.015861 -#> 4: f2022.c1991.p2022.t2022.nc 24494 15.043653 9.326359 5.717294 -#> 5: f2022.c1991.p2022.t2022.nc 32429 23.630099 13.681063 9.949036 -#> 6: f2022.c1991.p2022.t2022.nc 32485 15.009926 9.815501 5.194425 -#> FBP_fbp_hat_ha A_wheat_hat_ha H_wheat_dot_hat A_barley_hat_ha H_barley_dot_hat -#> -#> 1: 1.766127 NaN NaN NaN NaN -#> 2: 6.178280 NaN NaN NaN NaN -#> 3: 15.504923 NaN NaN NaN NaN -#> 4: 7.212161 NaN NaN NaN NaN -#> 5: 9.612778 NaN NaN NaN NaN -#> 6: 6.582035 NaN NaN NaN NaN -#> A_sorghum_hat_ha H_sorghum_dot_hat A_oilseeds_hat_ha H_oilseeds_dot_hat -#> -#> 1: NaN NaN NaN NaN -#> 2: NaN NaN NaN NaN -#> 3: NaN NaN NaN NaN -#> 4: NaN NaN NaN NaN -#> 5: NaN NaN NaN NaN -#> 6: NaN NaN NaN NaN -#> R_wheat_hat_ha R_sorghum_hat_ha R_oilseeds_hat_ha R_barley_hat_ha Q_wheat_hat_ha -#> -#> 1: NaN NaN NaN NaN NaN -#> 2: NaN NaN NaN NaN NaN -#> 3: NaN NaN NaN NaN NaN -#> 4: NaN NaN NaN NaN NaN -#> 5: NaN NaN NaN NaN NaN -#> 6: NaN NaN NaN NaN NaN -#> Q_barley_hat_ha Q_sorghum_hat_ha Q_oilseeds_hat_ha S_wheat_cl_hat_ha -#> -#> 1: NaN NaN NaN NaN -#> 2: NaN NaN NaN NaN -#> 3: NaN NaN NaN NaN -#> 4: NaN NaN NaN NaN -#> 5: NaN NaN NaN NaN -#> 6: NaN NaN NaN NaN -#> S_sheep_cl_hat_ha S_sheep_births_hat_ha S_sheep_deaths_hat_ha S_beef_cl_hat_ha -#> -#> 1: 0.000046854152 0.000048411171 0.000007187978 0.02034820 -#> 2: 0.000066325878 0.000057753874 0.000009039695 0.02974461 -#> 3: 0.000007771546 0.000007320093 0.000000000000 0.05393181 -#> 4: 0.000070963917 0.000062521929 0.000009726773 0.03057606 -#> 5: 0.000007780997 0.000006834211 0.000000000000 0.04944272 -#> 6: 0.000059600116 0.000053976389 0.000008478467 0.03322463 -#> S_beef_births_hat_ha S_beef_deaths_hat_ha Q_beef_hat_ha Q_sheep_hat_ha Q_lamb_hat_ha -#> -#> 1: 0.005212591 0.000989490 0.004790528 0.00007117650 0 -#> 2: 0.007970856 0.001468278 0.009646485 0.00009448864 0 -#> 3: 0.014745383 0.002867331 0.014401773 0.00001299674 0 -#> 4: 0.008602196 0.001446424 0.009577272 0.00010191595 0 -#> 5: 0.011527594 0.002491037 0.014668761 0.00001283228 0 -#> 6: 0.008456550 0.001627910 0.009281578 0.00008869032 0 -#> R_beef_hat_ha R_sheep_hat_ha R_lamb_hat_ha C_fodder_hat_ha C_fert_hat_ha -#> -#> 1: 7.392679 0.010222802 0 0.3553107 0.0007795925 -#> 2: 14.281910 0.014485890 0 0.7040333 0.0670951492 -#> 3: 24.308574 0.001821158 0 0.9473936 0.1475929946 -#> 4: 14.518771 0.015352095 0 0.7060111 0.0764850563 -#> 5: 23.060943 0.001892115 0 1.0269189 0.1592835324 -#> 6: 14.474964 0.013278806 0 0.7019839 0.0997758317 -#> C_fuel_hat_ha C_chem_hat_ha A_total_cropped_ha FBP_pfe_hat_ha farmland_per_cell -#> -#> 1: 0.4282799 0.0002169123 0.000001588013 2.142158 62.26270 -#> 2: 0.5663560 0.0212989625 0.000144292922 6.679382 61.71605 -#> 3: 0.9244438 0.0398376851 0.000296036096 16.185389 61.82964 -#> 4: 0.5688555 0.0223214940 0.000151675639 7.711993 72.85995 -#> 5: 0.8337981 0.0416492516 0.000316535762 10.294743 61.82964 -#> 6: 0.5575842 0.0293469147 0.000201161236 7.101658 61.71605 +#> id farmno R_total_hat_ha C_total_hat_ha FBP_fci_hat_ha FBP_fbp_hat_ha +#> +#> 1: f2022.c1991.p2022.t2022.nc 15612 7.636519 4.405228 3.231292 1.766127 +#> 2: f2022.c1991.p2022.t2022.nc 21495 14.811169 9.165632 5.645538 6.178280 +#> 3: f2022.c1991.p2022.t2022.nc 23418 24.874456 14.858595 10.015861 15.504923 +#> 4: f2022.c1991.p2022.t2022.nc 24494 15.043653 9.326359 5.717294 7.212161 +#> 5: f2022.c1991.p2022.t2022.nc 32429 23.630099 13.681063 9.949036 9.612778 +#> 6: f2022.c1991.p2022.t2022.nc 32485 15.009926 9.815501 5.194425 6.582035 +#> A_wheat_hat_ha H_wheat_dot_hat A_barley_hat_ha H_barley_dot_hat A_sorghum_hat_ha +#> +#> 1: NaN NaN NaN NaN NaN +#> 2: NaN NaN NaN NaN NaN +#> 3: NaN NaN NaN NaN NaN +#> 4: NaN NaN NaN NaN NaN +#> 5: NaN NaN NaN NaN NaN +#> 6: NaN NaN NaN NaN NaN +#> H_sorghum_dot_hat A_oilseeds_hat_ha H_oilseeds_dot_hat R_wheat_hat_ha R_sorghum_hat_ha +#> +#> 1: NaN NaN NaN NaN NaN +#> 2: NaN NaN NaN NaN NaN +#> 3: NaN NaN NaN NaN NaN +#> 4: NaN NaN NaN NaN NaN +#> 5: NaN NaN NaN NaN NaN +#> 6: NaN NaN NaN NaN NaN +#> R_oilseeds_hat_ha R_barley_hat_ha Q_wheat_hat_ha Q_barley_hat_ha Q_sorghum_hat_ha +#> +#> 1: NaN NaN NaN NaN NaN +#> 2: NaN NaN NaN NaN NaN +#> 3: NaN NaN NaN NaN NaN +#> 4: NaN NaN NaN NaN NaN +#> 5: NaN NaN NaN NaN NaN +#> 6: NaN NaN NaN NaN NaN +#> Q_oilseeds_hat_ha S_wheat_cl_hat_ha S_sheep_cl_hat_ha S_sheep_births_hat_ha +#> +#> 1: NaN NaN 0.000046854152 0.000048411171 +#> 2: NaN NaN 0.000066325878 0.000057753874 +#> 3: NaN NaN 0.000007771546 0.000007320093 +#> 4: NaN NaN 0.000070963917 0.000062521929 +#> 5: NaN NaN 0.000007780997 0.000006834211 +#> 6: NaN NaN 0.000059600116 0.000053976389 +#> S_sheep_deaths_hat_ha S_beef_cl_hat_ha S_beef_births_hat_ha S_beef_deaths_hat_ha Q_beef_hat_ha +#> +#> 1: 0.000007187978 0.02034820 0.005212591 0.000989490 0.004790528 +#> 2: 0.000009039695 0.02974461 0.007970856 0.001468278 0.009646485 +#> 3: 0.000000000000 0.05393181 0.014745383 0.002867331 0.014401773 +#> 4: 0.000009726773 0.03057606 0.008602196 0.001446424 0.009577272 +#> 5: 0.000000000000 0.04944272 0.011527594 0.002491037 0.014668761 +#> 6: 0.000008478467 0.03322463 0.008456550 0.001627910 0.009281578 +#> Q_sheep_hat_ha Q_lamb_hat_ha R_beef_hat_ha R_sheep_hat_ha R_lamb_hat_ha C_fodder_hat_ha +#> +#> 1: 0.00007117650 0 7.392679 0.010222802 0 0.3553107 +#> 2: 0.00009448864 0 14.281910 0.014485890 0 0.7040333 +#> 3: 0.00001299674 0 24.308574 0.001821158 0 0.9473936 +#> 4: 0.00010191595 0 14.518771 0.015352095 0 0.7060111 +#> 5: 0.00001283228 0 23.060943 0.001892115 0 1.0269189 +#> 6: 0.00008869032 0 14.474964 0.013278806 0 0.7019839 +#> C_fert_hat_ha C_fuel_hat_ha C_chem_hat_ha A_total_cropped_ha FBP_pfe_hat_ha farmland_per_cell +#> +#> 1: 0.0007795925 0.4282799 0.0002169123 0.000001588013 2.142158 62.26270 +#> 2: 0.0670951492 0.5663560 0.0212989625 0.000144292922 6.679382 61.71605 +#> 3: 0.1475929946 0.9244438 0.0398376851 0.000296036096 16.185389 61.82964 +#> 4: 0.0764850563 0.5688555 0.0223214940 0.000151675639 7.711993 72.85995 +#> 5: 0.1592835324 0.8337981 0.0416492516 0.000316535762 10.294743 61.82964 +#> 6: 0.0997758317 0.5575842 0.0293469147 0.000201161236 7.101658 61.71605 #> lon lat #> #> 1: 142.60 -10.75 @@ -325,23 +317,22 @@ By default, a brief bit of metadata is printed to the console when you call the library(read.abares) get_soil_thickness(cache = TRUE) #> -#> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - +#> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) ── #> #> ── Dataset ANZLIC ID ANZCW1202000149 ── #> -#> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the -#> 0.01 X 0.01 degree quadrat. +#> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the 0.01 X 0.01 +#> degree quadrat. #> #> Custodian: CSIRO Land & Water #> #> Jurisdiction Australia #> -#> Short Description The digital map data is provided in geographical coordinates based on -#> the World Geodetic System 1984 (WGS84) datum. This raster data set has a grid -#> resolution of 0.001 degrees (approximately equivalent to 1.1 km). +#> Short Description The digital map data is provided in geographical coordinates based on the World +#> Geodetic System 1984 (WGS84) datum. This raster data set has a grid resolution of 0.001 degrees +#> (approximately equivalent to 1.1 km). #> -#> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a -#> base dataset. +#> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a base dataset. #> #> Data Type: Spatial representation type RASTER #> @@ -353,19 +344,18 @@ get_soil_thickness(cache = TRUE) #> #> Scale: Scale/ resolution 1:1 000 000 #> -#> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil -#> constituent in either volume or mass terms (bulk density is also needed) - for example, -#> the volume of water stored in the rooting zone potentially available for plant use, to -#> assess total stores of soil carbon for greenhouse inventory or to assess total stores -#> of nutrients. +#> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil constituent +#> in either volume or mass terms (bulk density is also needed) - for example, the volume of water +#> stored in the rooting zone potentially available for plant use, to assess total stores of soil +#> carbon for greenhouse inventory or to assess total stores of nutrients. #> -#> Provide indications of probable thickness soil layer 1 in agricultural areas where soil -#> thickness testing has not been carried out. +#> Provide indications of probable thickness soil layer 1 in agricultural areas where soil thickness +#> testing has not been carried out. #> -#> Use Limitation: This dataset is bound by the requirements set down by the National Land -#> & Water Resources Audit -#> To see the full metadata, call `print_soil_thickness_metadata()` on a soil thickness -#> object in your R session. +#> Use Limitation: This dataset is bound by the requirements set down by the National Land & Water +#> Resources Audit +#> To see the full metadata, call `print_soil_thickness_metadata()` on a soil thickness object in your +#> R session. ``` But, {read.abares} provides a function for you to browse the soil thickness metadata in your console. @@ -376,73 +366,68 @@ library(read.abares) get_soil_thickness(cache = TRUE) |> print_soil_thickness_metadata() #> -#> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - +#> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) ── #> #> ── Dataset ANZLIC ID ANZCW1202000149 ── #> #> Dataset ANZLIC ID ANZCW1202000149 #> -#> Title Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A -#> Horizon - top-soil) (derived from soil mapping) +#> Title Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - +#> top-soil) (derived from soil mapping) #> #> Custodian CSIRO, Land & Water #> #> Jurisdiction Australia #> -#> Description Abstract Surface of predicted Thickness of soil layer 1 (A Horizon - -#> top-soil) surface for the intensive agricultural areas of Australia. Data modelled -#> from area based observations made by soil agencies both State and CSIRO and presented -#> as .0.01 degree grid cells. -#> -#> Topsoils (A horizons) are defined as the surface soil layers in which organic matter -#> accumulates, and may include dominantly organic surface layers (O and P horizons). -#> -#> The depth of topsoil is important because, with their higher organic matter contents, -#> topsoils (A horizon) generally have more suitable properties for agriculture, including -#> higher permeability and higher levels of soil nutrients. -#> -#> Estimates of soil depths are needed to calculate the amount of any soil constituent in -#> either volume or mass terms (bulk density is also needed) - for example, the volume of -#> water stored in the rooting zone potentially available for plant use, to assess total -#> stores of soil carbon for Greenhouse inventory or to assess total stores of nutrients. -#> -#> The pattern of soil depth is strongly related to topography - the shape and slope of -#> the land. Deeper soils are typically found in the river valleys where soils accumulate -#> on floodplains and at the footslopes of ranges (zones of deposition), while soils on -#> hillslopes (zones of erosion) tend to be shallow. Map of thickness of topsoil was -#> derived from soil map data and interpreted tables of soil properties for specific soil -#> groups. -#> -#> The quality of data on soil depth in existing soil profile datasets is questionable and -#> as the thickness of soil horizons varies locally with topography, values for map units -#> are general averages. -#> -#> The final ASRIS polygon attributed surfaces are a mosaic of all of the data obtained -#> from various state and federal agencies. The surfaces have been constructed with the -#> best available soil survey information available at the time. The surfaces also rely on -#> a number of assumptions. One being that an area weighted mean is a good estimate of the -#> soil attributes for that polygon or map-unit. Another assumption made is that the -#> look-up tables provided by McKenzie et al. (2000), state and territories accurately -#> depict the soil attribute values for each soil type. -#> -#> The accuracy of the maps is most dependent on the scale of the original polygon data -#> sets and the level of soil survey that has taken place in each state. The scale of the -#> various soil maps used in deriving this map is available by accessing the data-source -#> grid, the scale is used as an assessment of the likely accuracy of the modelling. The -#> Atlas of Australian Soils is considered to be the least accurate dataset and has -#> therefore only been used where there is no state based data. Of the state datasets -#> Western Australian sub-systems, South Australian land systems and NSW soil landscapes -#> and reconnaissance mapping would be the most reliable based on scale. NSW soil -#> landscapes and reconnaissance mapping use only one dominant soil type per polygon in -#> the estimation of attributes. South Australia and Western Australia use several soil -#> types per polygon or map-unit. -#> -#> The digital map data is provided in geographical coordinates based on the World -#> Geodetic System 1984 (WGS84) datum. This raster data set has a grid resolution of 0.001 -#> degrees (approximately equivalent to 1.1 km). -#> -#> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a -#> base dataset. +#> Description Abstract Surface of predicted Thickness of soil layer 1 (A Horizon - top-soil) surface +#> for the intensive agricultural areas of Australia. Data modelled from area based observations made +#> by soil agencies both State and CSIRO and presented as .0.01 degree grid cells. +#> +#> Topsoils (A horizons) are defined as the surface soil layers in which organic matter accumulates, +#> and may include dominantly organic surface layers (O and P horizons). +#> +#> The depth of topsoil is important because, with their higher organic matter contents, topsoils (A +#> horizon) generally have more suitable properties for agriculture, including higher permeability and +#> higher levels of soil nutrients. +#> +#> Estimates of soil depths are needed to calculate the amount of any soil constituent in either +#> volume or mass terms (bulk density is also needed) - for example, the volume of water stored in the +#> rooting zone potentially available for plant use, to assess total stores of soil carbon for +#> Greenhouse inventory or to assess total stores of nutrients. +#> +#> The pattern of soil depth is strongly related to topography - the shape and slope of the land. +#> Deeper soils are typically found in the river valleys where soils accumulate on floodplains and at +#> the footslopes of ranges (zones of deposition), while soils on hillslopes (zones of erosion) tend +#> to be shallow. Map of thickness of topsoil was derived from soil map data and interpreted tables +#> of soil properties for specific soil groups. +#> +#> The quality of data on soil depth in existing soil profile datasets is questionable and as the +#> thickness of soil horizons varies locally with topography, values for map units are general +#> averages. +#> +#> The final ASRIS polygon attributed surfaces are a mosaic of all of the data obtained from various +#> state and federal agencies. The surfaces have been constructed with the best available soil survey +#> information available at the time. The surfaces also rely on a number of assumptions. One being +#> that an area weighted mean is a good estimate of the soil attributes for that polygon or map-unit. +#> Another assumption made is that the look-up tables provided by McKenzie et al. (2000), state and +#> territories accurately depict the soil attribute values for each soil type. +#> +#> The accuracy of the maps is most dependent on the scale of the original polygon data sets and the +#> level of soil survey that has taken place in each state. The scale of the various soil maps used +#> in deriving this map is available by accessing the data-source grid, the scale is used as an +#> assessment of the likely accuracy of the modelling. The Atlas of Australian Soils is considered to +#> be the least accurate dataset and has therefore only been used where there is no state based data. +#> Of the state datasets Western Australian sub-systems, South Australian land systems and NSW soil +#> landscapes and reconnaissance mapping would be the most reliable based on scale. NSW soil +#> landscapes and reconnaissance mapping use only one dominant soil type per polygon in the estimation +#> of attributes. South Australia and Western Australia use several soil types per polygon or +#> map-unit. +#> +#> The digital map data is provided in geographical coordinates based on the World Geodetic System +#> 1984 (WGS84) datum. This raster data set has a grid resolution of 0.001 degrees (approximately +#> equivalent to 1.1 km). +#> +#> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a base dataset. #> #> Search Word(s) AGRICULTURE SOIL Physics Models #> @@ -452,51 +437,47 @@ get_soil_thickness(cache = TRUE) |> #> #> GEN Name #> -#> Geographic Bounding Box North Bounding Latitude -10.707149 South Bounding Latitude -#> -43.516831 East Bounding Longitude 113.19673 West Bounding Longitude 153.990779 -#> -#> Geographic Extent Polygon(s) 115.0 -33.5,115.7 -33.3,115.7 -31.7,113.2 -26.2,113.5 -#> -25.4,114.1 -26.4,114.3 -26.0,113.4 -24.3,114.1 -21.8,122.3 -18.2,122.2 -17.2,126.7 -#> -13.6,129.1 -14.9,130.6 -12.3,132.6 -12.1,132.5 -11.6,131.9 -11.3,132.0 -11.1,137.0 -#> -12.2,135.4 -14.7,140.0 -17.7,140.8 -17.4,141.7 -15.1,141.4 -13.7,142.2 -10.9,142.7 -#> -10.7,143.9 -14.5,144.6 -14.1,145.3 -14.9,146.3 -18.8,148.9 -20.5,150.9 -22.6,153.2 -#> -25.9,153.7 -28.8,153.0 -31.3,150.8 -34.8,150.0 -37.5,147.8 -37.9,146.3 -39.0,144.7 -#> -38.4,143.5 -38.8,141.3 -38.4,139.7 -37.3,139.7 -36.9,139.9 -36.7,138.9 -35.5,138.1 -#> -35.7,138.6 -34.7,138.1 -34.2,137.8 -35.1,136.9 -35.3,137.0 -34.9,137.5 -34.9,137.4 -#> -34.0,137.9 -33.5,137.8 -32.6,137.3 -33.6,135.9 -34.7,136.1 -34.8,136.0 -35.0,135.1 -#> -34.6,135.2 -34.5,135.4 -34.5,134.7 -33.3,134.0 -32.9,133.7 -32.1,133.3 -32.2,132.2 -#> -32.0,131.3 -31.5,127.3 -32.3,126.0 -32.3,123.6 -33.9,123.2 -34.0,122.1 -34.0,121.9 -#> -33.8,119.9 -34.0,119.6 -34.4,118.0 -35.1,116.0 -34.8,115.0 -34.3,115.0 -33.5 -#> -#> 147.8 -42.9,147.9 -42.6,148.2 -42.1,148.3 -42.3,148.3 -41.3,148.3 -41.0,148.0 -#> -40.7,147.4 -41.0,146.7 -41.1,146.6 -41.2,146.5 -41.1,146.4 -41.2,145.3 -40.8,145.3 -#> -40.7,145.2 -40.8,145.2 -40.8,145.2 -40.8,145.0 -40.8,144.7 -40.7,144.7 -41.2,145.2 -#> -42.2,145.4 -42.2,145.5 -42.4,145.5 -42.5,145.2 -42.3,145.5 -43.0,146.0 -43.3,146.0 -#> -43.6,146.9 -43.6,146.9 -43.5,147.1 -43.3,147.0 -43.1,147.2 -43.3,147.3 -42.8,147.4 -#> -42.9,147.6 -42.8,147.5 -42.8,147.8 -42.9,147.9 -43.0,147.7 -43.0,147.8 -43.2,147.9 -#> -43.2,147.9 -43.2,148.0 -43.2,148.0 -43.1,148.0 -42.9,147.8 -42.9 -#> -#> 136.7 -13.8,136.7 -13.7,136.6 -13.7,136.6 -13.8,136.4 -13.8,136.4 -14.1,136.3 -#> -14.2,136.9 -14.3,137.0 -14.2,136.9 -14.2,136.7 -14.1,136.9 -13.8,136.7 -13.8,136.7 -#> -13.8 +#> Geographic Bounding Box North Bounding Latitude -10.707149 South Bounding Latitude -43.516831 East +#> Bounding Longitude 113.19673 West Bounding Longitude 153.990779 +#> +#> Geographic Extent Polygon(s) 115.0 -33.5,115.7 -33.3,115.7 -31.7,113.2 -26.2,113.5 -25.4,114.1 +#> -26.4,114.3 -26.0,113.4 -24.3,114.1 -21.8,122.3 -18.2,122.2 -17.2,126.7 -13.6,129.1 -14.9,130.6 +#> -12.3,132.6 -12.1,132.5 -11.6,131.9 -11.3,132.0 -11.1,137.0 -12.2,135.4 -14.7,140.0 -17.7,140.8 +#> -17.4,141.7 -15.1,141.4 -13.7,142.2 -10.9,142.7 -10.7,143.9 -14.5,144.6 -14.1,145.3 -14.9,146.3 +#> -18.8,148.9 -20.5,150.9 -22.6,153.2 -25.9,153.7 -28.8,153.0 -31.3,150.8 -34.8,150.0 -37.5,147.8 +#> -37.9,146.3 -39.0,144.7 -38.4,143.5 -38.8,141.3 -38.4,139.7 -37.3,139.7 -36.9,139.9 -36.7,138.9 +#> -35.5,138.1 -35.7,138.6 -34.7,138.1 -34.2,137.8 -35.1,136.9 -35.3,137.0 -34.9,137.5 -34.9,137.4 +#> -34.0,137.9 -33.5,137.8 -32.6,137.3 -33.6,135.9 -34.7,136.1 -34.8,136.0 -35.0,135.1 -34.6,135.2 +#> -34.5,135.4 -34.5,134.7 -33.3,134.0 -32.9,133.7 -32.1,133.3 -32.2,132.2 -32.0,131.3 -31.5,127.3 +#> -32.3,126.0 -32.3,123.6 -33.9,123.2 -34.0,122.1 -34.0,121.9 -33.8,119.9 -34.0,119.6 -34.4,118.0 +#> -35.1,116.0 -34.8,115.0 -34.3,115.0 -33.5 +#> +#> 147.8 -42.9,147.9 -42.6,148.2 -42.1,148.3 -42.3,148.3 -41.3,148.3 -41.0,148.0 -40.7,147.4 +#> -41.0,146.7 -41.1,146.6 -41.2,146.5 -41.1,146.4 -41.2,145.3 -40.8,145.3 -40.7,145.2 -40.8,145.2 +#> -40.8,145.2 -40.8,145.0 -40.8,144.7 -40.7,144.7 -41.2,145.2 -42.2,145.4 -42.2,145.5 -42.4,145.5 +#> -42.5,145.2 -42.3,145.5 -43.0,146.0 -43.3,146.0 -43.6,146.9 -43.6,146.9 -43.5,147.1 -43.3,147.0 +#> -43.1,147.2 -43.3,147.3 -42.8,147.4 -42.9,147.6 -42.8,147.5 -42.8,147.8 -42.9,147.9 -43.0,147.7 +#> -43.0,147.8 -43.2,147.9 -43.2,147.9 -43.2,148.0 -43.2,148.0 -43.1,148.0 -42.9,147.8 -42.9 +#> +#> 136.7 -13.8,136.7 -13.7,136.6 -13.7,136.6 -13.8,136.4 -13.8,136.4 -14.1,136.3 -14.2,136.9 +#> -14.3,137.0 -14.2,136.9 -14.2,136.7 -14.1,136.9 -13.8,136.7 -13.8,136.7 -13.8 #> #> 139.5 -16.6,139.7 -16.5,139.4 -16.5,139.2 -16.7,139.3 -16.7,139.5 -16.6 #> #> 153.0 -25.2,153.0 -25.7,153.1 -25.8,153.4 -25.0,153.2 -24.7,153.2 -25.0,153.0 -25.2 #> -#> 137.5 -36.1,137.7 -35.9,138.1 -35.9,137.9 -35.7,137.6 -35.7,137.6 -35.6,136.6 -#> -35.8,136.7 -36.1,137.2 -36.0,137.5 -36.1 +#> 137.5 -36.1,137.7 -35.9,138.1 -35.9,137.9 -35.7,137.6 -35.7,137.6 -35.6,136.6 -35.8,136.7 +#> -36.1,137.2 -36.0,137.5 -36.1 #> #> 143.9 -39.7,144.0 -39.6,144.1 -39.8,143.9 -40.2,143.9 -40.0,143.9 -39.7 #> -#> 148.0 -39.7,147.7 -39.9,147.9 -39.9,148.0 -40.1,148.1 -40.3,148.3 -40.2,148.3 -#> -40.0,148.0 -39.7 +#> 148.0 -39.7,147.7 -39.9,147.9 -39.9,148.0 -40.1,148.1 -40.3,148.3 -40.2,148.3 -40.0,148.0 -39.7 #> #> 148.1 -40.4,148.0 -40.4,148.4 -40.3,148.4 -40.5,148.1 -40.4 #> -#> 130.4 -11.3,130.4 -11.2,130.6 -11.3,130.7 -11.4,130.9 -11.3,131.0 -11.4,131.1 -#> -11.3,131.2 -11.4,131.3 -11.2,131.5 -11.4,131.5 -11.5,131.0 -11.9,130.8 -11.8,130.6 -#> -11.7,130.0 -11.8,130.1 -11.7,130.3 -11.7,130.1 -11.5,130.4 -11.3 +#> 130.4 -11.3,130.4 -11.2,130.6 -11.3,130.7 -11.4,130.9 -11.3,131.0 -11.4,131.1 -11.3,131.2 +#> -11.4,131.3 -11.2,131.5 -11.4,131.5 -11.5,131.0 -11.9,130.8 -11.8,130.6 -11.7,130.0 -11.8,130.1 +#> -11.7,130.3 -11.7,130.1 -11.5,130.4 -11.3 #> #> Data Currency Beginning date 1999-09-01 #> @@ -510,108 +491,101 @@ get_soil_thickness(cache = TRUE) |> #> #> Available Format Type DIGITAL - ESRI Arc/Info integer GRID #> -#> Access Constraint Subject to the terms & condition of the data access & management -#> agreement between the National Land & Water Audit and ANZLIC parties -#> -#> Data Quality Lineage The soil attribute surface was created using the following -#> datasets 1. The digital polygon coverage of the Soil-Landforms of the Murray Darling -#> Basis (MDBSIS)(Bui et al. 1998), classified as principal profile forms (PPF's) -#> (Northcote 1979). 2. The digital Atlas of Australian Soils (Northcote et -#> al.1960-1968)(Leahy, 1993). 3. Western Australia land systems coverage (Agriculture -#> WA). 4. Western Australia sub-systems coverage (Agriculture WA). 5. Ord river catchment -#> soils coverage (Agriculture WA). 6. Victoria soils coverage (Victorian Department of -#> Natural Resources and Environment - NRE). 7. NSW Soil Landscapes and reconnaissance -#> soil landscape mapping (NSW Department of Land and Water Conservation - DLWC). 8. New -#> South Wales Land systems west (NSW Department of Land and Water Conservation - DLWC). -#> 9. South Australia soil land-systems (Primary Industries and Resources South Australia -#> - PIRSA). 10. Northern Territory soils coverage (Northern Territory Department of -#> Lands, Planning and Environment). 11. A mosaic of Queensland soils coverages -#> (Queensland Department of Natural Resources - QDNR). 12. A look-up table linking PPF -#> values from the Atlas of Australian Soils with interpreted soil attributes (McKenzie et -#> al. 2000). 13. Look_up tables provided by WA Agriculture linking WA soil groups with -#> interpreted soil attributes. 14. Look_up tables provided by PIRSA linking SA soil -#> groups with interpreted soil attributes. -#> -#> The continuous raster surface representing Thickness of soil layer 1 was created by -#> combining national and state level digitised land systems maps and soil surveys linked -#> to look-up tables listing soil type and corresponding attribute values. -#> -#> Because thickness is used sparingly in the Factual Key, estimations of thickness in the -#> look-up tables were made using empirical correlations for particular soil types. -#> -#> To estimate a soil attribute where more than one soil type was given for a polygon or -#> map-unit, the soil attribute values related to each soil type in the look-up table were -#> weighted according to the area occupied by that soil type within the polygon or -#> map-unit. The final soil attribute values are an area weighted average for a polygon or -#> map-unit. The polygon data was then converted to a continuous raster surface using the -#> soil attribute values calculated for each polygon. -#> -#> The ASRIS soil attribute surfaces created using polygon attribution relied on a number -#> of data sets from various state agencies. Each polygon data set was turned into a -#> continuous surface grid based on the calculated soil attribute value for that polygon. -#> The grids where then merged on the basis that, where available, state data replaced the -#> Atlas of Australian Soils and MDBSIS. MDBSIS derived soil attribute values were -#> restricted to areas where MDBSIS was deemed to be more accurate that the Atlas of -#> Australian Soils (see Carlile et al (2001a). -#> -#> In cases where a soil type was missing from the look-up table or layer 2 did not exist -#> for that soil type, the percent area of the soils remaining were adjusted prior to -#> calculating the final soil attribute value. The method used to attribute polygons was -#> dependent on the data supplied by individual State agencies. -#> -#> The modelled grid was resampled from 0.0025 degree cells to 0.01 degree cells using -#> bilinear interpolation -#> -#> Positional Accuracy The predictive surface is a 0.01 X 0.01 degree grid and has a -#> locational accurate of about 1m. -#> -#> The positional accuracy of the defining polygons have variable positional accuracy most -#> locations are expected to be within 100m of the recorded location. The vertical -#> accuracy is not relevant. The positional assessment has been made by considering the -#> tools used to generate the locational information and contacting the data providers. -#> -#> The other parameters used in the production of the led surface have a range of -#> positional accuracy ranging from + - 50 m to + - kilometres. This contribute to the -#> loss of attribute accuracy in the surface. -#> -#> Attribute Accuracy Input attribute accuracy for the areas is highly variable. The -#> predictive has a variable and much lower attribute accuracy due to the irregular -#> distribution and the limited positional accuracy of the parameters used for modelling. -#> -#> There are several sources of error in estimating soil depth and thickness of horizons -#> for the look-up tables. Because thickness is used sparingly in the Factual Key, -#> estimations of thickness in the look-up tables were made using empirical correlations -#> for particular soil types. The quality of data on soil depth in existing soil profile -#> datasets is questionable, in soil mapping, thickness of soil horizons varies locally -#> with topography, so values for map units are general averages. The definition of the -#> depth of soil or regolith is imprecise and it can be difficult to determine the lower -#> limit of soil. -#> -#> The assumption made that an area weighted mean of soil attribute values based on soil -#> type is a good estimation of a soil property is debatable, in that it does not supply -#> the soil attribute value at any given location. Rather it is designed to show national -#> and regional patterns in soil properties. The use of the surfaces at farm or catchment -#> scale modelling may prove inaccurate. Also the use of look-up tables to attribute soil -#> types is only as accurate as the number of observations used to estimate a attribute -#> value for a soil type. Some soil types in the look-up tables may have few observations, -#> yet the average attribute value is still taken as the attribute value for that soil -#> type. Different states are using different taxonomic schemes making a national soil -#> database difficult. Another downfall of the area weighted approach is that some soil -#> types may not be listed in look-up tables. If a soil type is a dominant one within a -#> polygon or map-unit, but is not listed within the look-up table or is not attributed -#> within the look-up table then the final soil attribute value for that polygon will be -#> biased towards the minor soil types that do exist. This may also happen when a large -#> area is occupied by a soil type which has no B horizon. In this case the final soil -#> attribute value will be area weighted on the soils with a B horizon, ignoring a major -#> soil type within that polygon or map-unit. The layer 2 surfaces have large areas of -#> no-data because all soils listed for a particular map-unit or polygon had no B horizon. -#> -#> Logical Consistency Surface is fully logically consistent as only one parameter is -#> shown, as predicted average Soil Thickness within each grid cell -#> -#> Completeness Surface is nearly complete. There are some areas (about %1 missing) for -#> which insufficient parameters were known to provide a useful prediction and thus -#> attributes are absent in these areas. +#> Access Constraint Subject to the terms & condition of the data access & management agreement +#> between the National Land & Water Audit and ANZLIC parties +#> +#> Data Quality Lineage The soil attribute surface was created using the following datasets 1. The +#> digital polygon coverage of the Soil-Landforms of the Murray Darling Basis (MDBSIS)(Bui et al. +#> 1998), classified as principal profile forms (PPF's) (Northcote 1979). 2. The digital Atlas of +#> Australian Soils (Northcote et al.1960-1968)(Leahy, 1993). 3. Western Australia land systems +#> coverage (Agriculture WA). 4. Western Australia sub-systems coverage (Agriculture WA). 5. Ord river +#> catchment soils coverage (Agriculture WA). 6. Victoria soils coverage (Victorian Department of +#> Natural Resources and Environment - NRE). 7. NSW Soil Landscapes and reconnaissance soil landscape +#> mapping (NSW Department of Land and Water Conservation - DLWC). 8. New South Wales Land systems +#> west (NSW Department of Land and Water Conservation - DLWC). 9. South Australia soil land-systems +#> (Primary Industries and Resources South Australia - PIRSA). 10. Northern Territory soils coverage +#> (Northern Territory Department of Lands, Planning and Environment). 11. A mosaic of Queensland +#> soils coverages (Queensland Department of Natural Resources - QDNR). 12. A look-up table linking +#> PPF values from the Atlas of Australian Soils with interpreted soil attributes (McKenzie et al. +#> 2000). 13. Look_up tables provided by WA Agriculture linking WA soil groups with interpreted soil +#> attributes. 14. Look_up tables provided by PIRSA linking SA soil groups with interpreted soil +#> attributes. +#> +#> The continuous raster surface representing Thickness of soil layer 1 was created by combining +#> national and state level digitised land systems maps and soil surveys linked to look-up tables +#> listing soil type and corresponding attribute values. +#> +#> Because thickness is used sparingly in the Factual Key, estimations of thickness in the look-up +#> tables were made using empirical correlations for particular soil types. +#> +#> To estimate a soil attribute where more than one soil type was given for a polygon or map-unit, the +#> soil attribute values related to each soil type in the look-up table were weighted according to the +#> area occupied by that soil type within the polygon or map-unit. The final soil attribute values are +#> an area weighted average for a polygon or map-unit. The polygon data was then converted to a +#> continuous raster surface using the soil attribute values calculated for each polygon. +#> +#> The ASRIS soil attribute surfaces created using polygon attribution relied on a number of data sets +#> from various state agencies. Each polygon data set was turned into a continuous surface grid based +#> on the calculated soil attribute value for that polygon. The grids where then merged on the basis +#> that, where available, state data replaced the Atlas of Australian Soils and MDBSIS. MDBSIS +#> derived soil attribute values were restricted to areas where MDBSIS was deemed to be more accurate +#> that the Atlas of Australian Soils (see Carlile et al (2001a). +#> +#> In cases where a soil type was missing from the look-up table or layer 2 did not exist for that +#> soil type, the percent area of the soils remaining were adjusted prior to calculating the final +#> soil attribute value. The method used to attribute polygons was dependent on the data supplied by +#> individual State agencies. +#> +#> The modelled grid was resampled from 0.0025 degree cells to 0.01 degree cells using bilinear +#> interpolation +#> +#> Positional Accuracy The predictive surface is a 0.01 X 0.01 degree grid and has a locational +#> accurate of about 1m. +#> +#> The positional accuracy of the defining polygons have variable positional accuracy most locations +#> are expected to be within 100m of the recorded location. The vertical accuracy is not relevant. +#> The positional assessment has been made by considering the tools used to generate the locational +#> information and contacting the data providers. +#> +#> The other parameters used in the production of the led surface have a range of positional accuracy +#> ranging from + - 50 m to + - kilometres. This contribute to the loss of attribute accuracy in the +#> surface. +#> +#> Attribute Accuracy Input attribute accuracy for the areas is highly variable. The predictive has a +#> variable and much lower attribute accuracy due to the irregular distribution and the limited +#> positional accuracy of the parameters used for modelling. +#> +#> There are several sources of error in estimating soil depth and thickness of horizons for the +#> look-up tables. Because thickness is used sparingly in the Factual Key, estimations of thickness +#> in the look-up tables were made using empirical correlations for particular soil types. The +#> quality of data on soil depth in existing soil profile datasets is questionable, in soil mapping, +#> thickness of soil horizons varies locally with topography, so values for map units are general +#> averages. The definition of the depth of soil or regolith is imprecise and it can be difficult to +#> determine the lower limit of soil. +#> +#> The assumption made that an area weighted mean of soil attribute values based on soil type is a +#> good estimation of a soil property is debatable, in that it does not supply the soil attribute +#> value at any given location. Rather it is designed to show national and regional patterns in soil +#> properties. The use of the surfaces at farm or catchment scale modelling may prove inaccurate. Also +#> the use of look-up tables to attribute soil types is only as accurate as the number of observations +#> used to estimate a attribute value for a soil type. Some soil types in the look-up tables may have +#> few observations, yet the average attribute value is still taken as the attribute value for that +#> soil type. Different states are using different taxonomic schemes making a national soil database +#> difficult. Another downfall of the area weighted approach is that some soil types may not be listed +#> in look-up tables. If a soil type is a dominant one within a polygon or map-unit, but is not listed +#> within the look-up table or is not attributed within the look-up table then the final soil +#> attribute value for that polygon will be biased towards the minor soil types that do exist. This +#> may also happen when a large area is occupied by a soil type which has no B horizon. In this case +#> the final soil attribute value will be area weighted on the soils with a B horizon, ignoring a +#> major soil type within that polygon or map-unit. The layer 2 surfaces have large areas of no-data +#> because all soils listed for a particular map-unit or polygon had no B horizon. +#> +#> Logical Consistency Surface is fully logically consistent as only one parameter is shown, as +#> predicted average Soil Thickness within each grid cell +#> +#> Completeness Surface is nearly complete. There are some areas (about %1 missing) for which +#> insufficient parameters were known to provide a useful prediction and thus attributes are absent in +#> these areas. #> #> Contact Information Contact Organisation (s) CSIRO, Land & Water #> @@ -643,8 +617,8 @@ get_soil_thickness(cache = TRUE) |> #> #> Feature attribute name VALUE #> -#> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the -#> 0.01 X 0.01 degree quadrat +#> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the 0.01 X 0.01 +#> degree quadrat #> #> Data Type Spatial representation type RASTER #> @@ -656,17 +630,16 @@ get_soil_thickness(cache = TRUE) |> #> #> Scale Scale/ resolution 1:1 000 000 #> -#> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil -#> constituent in either volume or mass terms (bulk density is also needed) - for example, -#> the volume of water stored in the rooting zone potentially available for plant use, to -#> assess total stores of soil carbon for Greenhouse inventory or to assess total stores -#> of nutrients. +#> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil constituent +#> in either volume or mass terms (bulk density is also needed) - for example, the volume of water +#> stored in the rooting zone potentially available for plant use, to assess total stores of soil +#> carbon for Greenhouse inventory or to assess total stores of nutrients. #> -#> Provide indications of probable Thickness soil layer 1 in agricultural areas where soil -#> thickness testing has not been carried out +#> Provide indications of probable Thickness soil layer 1 in agricultural areas where soil thickness +#> testing has not been carried out #> -#> Use Use Limitation This dataset is bound by the requirements set down by the National -#> Land & Water Resources Audit +#> Use Use Limitation This dataset is bound by the requirements set down by the National Land & Water +#> Resources Audit ``` But you can also access it directly and use pander::pander() to include it in a document like this vignette. diff --git a/vignettes/read.abares.Rmd.orig b/vignettes/read.abares.Rmd.orig index e569c0d..e0dc870 100644 --- a/vignettes/read.abares.Rmd.orig +++ b/vignettes/read.abares.Rmd.orig @@ -18,7 +18,7 @@ knitr::opts_chunk$set( ``` This vignette demonstrates some of the functionality of {read.abares}. -Please note that not all functions are demonstrated here, please refer to the [documentation reference](https://adamhsparks.codeberg.page/read.abares/reference/) for a full list of functionality. +Please note that not all functions are demonstrated here, please refer to the [documentation reference](https://adamhsparks.github.io/read.abares/reference/) for a full list of functionality. The worked examples here show some of the more advanced features that {read.abares} offers beyond just fetching and importing data, _e.g._, the Australian Gridded Farm Data, which can be downloaded, cached and then imported using one of four types of object or the soil thickness data, which includes rich metadata. ## Working With AGFD Data From f0d23dfa968197e77a8ea07f84df971ef31f1d5f Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 10:53:44 +0800 Subject: [PATCH 03/10] Update codemeta.json --- codemeta.json | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/codemeta.json b/codemeta.json index e3e10a9..591cf86 100644 --- a/codemeta.json +++ b/codemeta.json @@ -8,7 +8,7 @@ "codeRepository": "https://github.com/adamhsparks/read.abares", "issueTracker": "https://github.com/adamhsparks/read.abares/issues", "license": "https://spdx.org/licenses/MIT", - "version": "0.1.0", + "version": "1.0.0", "programmingLanguage": { "@type": "ComputerLanguage", "name": "R", @@ -333,7 +333,7 @@ }, "SystemRequirements": null }, - "fileSize": "390.78KB", + "fileSize": "393.785KB", "citation": [ { "@type": "SoftwareSourceCode", @@ -345,8 +345,8 @@ } ], "name": "{read.abares}: Simple downloading and importing of ABARES Data", - "url": "https://adamhsparks.codeberg.page/read.abares/", - "description": "R package version 0.1.0" + "url": "https://adamhsparks.github.io/read.abares/", + "description": "R package version 1.0.0" } ], "releaseNotes": "https://github.com/adamhsparks/read.abares/blob/master/NEWS.md", From 38bf7a616a0b86c7d7e7631f32da24f17fadfedc Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 10:53:59 +0800 Subject: [PATCH 04/10] Update NEWS.md for v1.0.0 --- NEWS.md | 46 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 46 insertions(+) diff --git a/NEWS.md b/NEWS.md index 2322d94..e8a33a9 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,49 @@ +# read.abares 1.0.0 + +## Major changes + +* Rename functions that both download and read files into active R session from `get_` to `read_` to avoid confusion with functions that only fetch data and have separate `read_` functions + +* Adds new function, `print_agfd_nc_file_format()` to provide details on the AGFD NetCDF files' contents + +* Uses Geopackages for {sf} objects rather than .Rds, faster and smaller file sizes when caching + +* Checks and corrects the geometries of the AAGIS Regions shapefile upon import and applies to the cached object if applicable + +## Bug fixes + +* No longer checks the length of a Boolean vector when checking the number of files in the cache before proceeding with removing them + +* Fixes bugs in `get_agfd()` when creating the directories for saving the downloaded file + +* Fixes bug in `get_aagis_regions()` when creating the cached object file + +* Fixes "URL" field in DESCRIPTION file, thanks @mpadge + +## Minor changes + +* Improved documentation + + * All data sets now have an `@source` field that points to the file being provided + + * All data sets now have an `@references` field that points to references for the data + +* Code linting thanks to [{flint}](https://flint.etiennebacher.com) + +* Use {httr2} to handle downloads + + * Increase timeout values to deal with stubborn long-running file downloads + +* Use {brio} to write downloads to disk + +* Use {httptest2} to help test downloads + +* Gracefully handle errors when AGFD zip files are corrupted on download, provide the user with an informative message and remove corrupted download + +* Tests are run in parallel for quicker testing + +* {sf} operations are now quiet when reading data where possible + # read.abares 0.1.0 - Submission to rOpenSci for [peer code review](https://github.com/ropensci/software-review/issues) From dcb262be3579f1c426223e1e5a45dcef7f7a719e Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 10:54:18 +0800 Subject: [PATCH 05/10] Increment version to v1.0.0 --- DESCRIPTION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 6144c31..9992beb 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -3,7 +3,7 @@ Package: read.abares Title: Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources -Version: 0.1.0 +Version: 1.0.0 Authors@R: c( person("Adam H.", "Sparks", , "adamhsparks@gmail.com", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-0061-8359")), From 1bc69a35300d52cc73955fb3c1d24de1a1752aac Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 10:57:15 +0800 Subject: [PATCH 06/10] Update citation --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 08e7c03..8143188 100644 --- a/README.md +++ b/README.md @@ -145,16 +145,16 @@ citation("read.abares") #> To cite package 'read.abares' in publications use: #> #> Sparks A (????). _read.abares: Simple downloading and importing of -#> ABARES Data_. R package version 0.1.0, -#> . +#> ABARES Data_. R package version 1.0.0, +#> . #> #> A BibTeX entry for LaTeX users is #> #> @Manual{, #> title = {{read.abares}: Simple downloading and importing of ABARES Data}, #> author = {Adam H. Sparks}, -#> note = {R package version 0.1.0}, -#> url = {https://adamhsparks.codeberg.page/read.abares/}, +#> note = {R package version 1.0.0}, +#> url = {https://adamhsparks.github.io/read.abares/}, #> } ``` From 8e510ff6040691348c847f4ef662a4b08e79fa26 Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 11:03:22 +0800 Subject: [PATCH 07/10] Fix nonascii char --- R/get_agfd.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/get_agfd.R b/R/get_agfd.R index 60ea837..10dde39 100644 --- a/R/get_agfd.R +++ b/R/get_agfd.R @@ -265,7 +265,7 @@ print_agfd_nc_file_format <- function() { cli::cat_line() cli::cli_dl( c( - "{.strong CRS}" = "EPSG:4326 - WGS 84 – Geographic", + "{.strong CRS}" = "EPSG:4326 - WGS 84 - Geographic", "{.strong Extent}" = "111.975 -44.525 156.275 -9.975", "{.strong Unit}" = "Degrees", "{.strong Width}" = "886", From ba5fb82376748d5b64223c9ae2d35345ecba2ed8 Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 11:06:52 +0800 Subject: [PATCH 08/10] update WORDLIST --- codemeta.json | 2 +- inst/WORDLIST | 8 +++++++- 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/codemeta.json b/codemeta.json index 591cf86..3634a5b 100644 --- a/codemeta.json +++ b/codemeta.json @@ -333,7 +333,7 @@ }, "SystemRequirements": null }, - "fileSize": "393.785KB", + "fileSize": "393.438KB", "citation": [ { "@type": "SoftwareSourceCode", diff --git a/inst/WORDLIST b/inst/WORDLIST index a90589d..bbb8673 100644 --- a/inst/WORDLIST +++ b/inst/WORDLIST @@ -21,6 +21,7 @@ FBP FYs GRDC Geopackage +Geopackages Gridded ISSN Landforms @@ -42,6 +43,7 @@ PIRSA PPF PPF's QDNR +Rds Soh Topsoils WGS @@ -50,11 +52,13 @@ abares agfd al backcast +brio broadacre coverages crm de digitised +doi et ev farmno @@ -68,13 +72,15 @@ funder geospatial gridded hillslopes +https +httptest +httr kilometres labour locational modelled modelling multilayer -nc oilseeds pfe quadrat From c187c4e11c7fad177c8d0018aec365be05daf514 Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 11:12:02 +0800 Subject: [PATCH 09/10] correct YAML structure --- pkgdown/_pkgdown.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml index 409b547..862af88 100644 --- a/pkgdown/_pkgdown.yml +++ b/pkgdown/_pkgdown.yml @@ -21,7 +21,7 @@ reference: - read_agfd_stars - read_agfd_terra - read_agfd_tidync - - subtitle: Meta +- subtitle: Meta desc: | Information about the AGFD NetCDF files and contents contents: From bae13d29a555201a11d7d6dc65dbf68e36d15380 Mon Sep 17 00:00:00 2001 From: "Adam H. Sparks" Date: Sun, 8 Dec 2024 11:15:37 +0800 Subject: [PATCH 10/10] fix YAML --- pkgdown/_pkgdown.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml index 862af88..77548a9 100644 --- a/pkgdown/_pkgdown.yml +++ b/pkgdown/_pkgdown.yml @@ -7,7 +7,7 @@ reference: - title: AAGIS Regions desc: | Fetch and read the AAGIS regions - contents: get_aagis_regions + contents: read_aagis_regions - title: AGFD - subtitle: Fetch desc: |