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huc12_summary.R
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huc12_summary.R
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#' Download HUC12 Summary
#'
#' @description Provides summary data for a 12-digit Hydrologic Unit Code
#' (HUC12), based on Assessment Units in the HUC12. Watershed boundaries may
#' cross state boundaries, so the service may return assessment units from
#' multiple organizations. Returns the assessment units in the HUC12, size and
#' percentages of assessment units considered Good, Unknown, or Impaired.
#'
#' @param huc (character) Specifies the 12-digit HUC to be summarized. required
#' @param tidy (logical) \code{TRUE} (default) the function returns a tidied
#' tibble. \code{FALSE} the function returns the raw JSON string.
#' @param .unnest (logical) \code{TRUE} (default) the function attempts to unnest
#' data to longest format possible. This defaults to \code{TRUE} for backwards
#' compatibility but it is suggested to use \code{FALSE}.
#' @param ... list of curl options passed to [crul::HttpClient()]
#'
#' @return If \code{tidy = FALSE} the raw JSON string is returned, else the JSON
#' data is parsed and returned as a list of tibbles that include a list of
#' seven tibbles.
#' @note See [domain_values] to search values that can be queried.
#' @import tibblify
#' @importFrom checkmate assert_character assert_logical makeAssertCollection
#' reportAssertions
#' @importFrom dplyr select
#' @importFrom fs path
#' @importFrom jsonlite fromJSON
#' @importFrom tidyr unnest
#' @importFrom tidyselect everything
#' @export
#' @examples
#'
#' \dontrun{
#' ## Return a list of tibbles with summary data about a single huc12
#' x <- huc12_summary(huc = "020700100204")
#'
#' ## Return as a JSON string
#' x <- huc12_summary(huc = "020700100204", tidy = TRUE)
#' }
huc12_summary <- function(huc,
tidy = TRUE,
.unnest = TRUE,
...) {
## check connectivity
con_check <- check_connectivity()
if(!isTRUE(con_check)){
return(invisible(NULL))
}
## check that arguments are character
coll <- checkmate::makeAssertCollection()
mapply(FUN = checkmate::assert_character,
x = list(huc),
.var.name = c("huc"),
MoreArgs = list(null.ok = FALSE,
add = coll))
checkmate::reportAssertions(coll)
## check logical
coll <- checkmate::makeAssertCollection()
mapply(FUN = checkmate::assert_logical,
x = list(tidy, .unnest),
.var.name = c("tidy", ".unnest"),
MoreArgs = list(null.ok = FALSE,
add = coll))
checkmate::reportAssertions(coll)
args <- list(huc = huc)
path = "attains-public/api/huc12summary"
## download data
content <- xGET(path,
args,
file = NULL,
...)
if(is.null(content)) return(content)
if(!isTRUE(tidy)) {
return(content)
} else {
## parse JSON
json_list <- jsonlite::fromJSON(content,
simplifyVector = FALSE,
simplifyDataFrame = FALSE,
flatten = FALSE)
## create tibblify specification
spec <- spec_huc12()
## nested list -> rectangle
content <- tibblify(json_list, spec = spec, unspecified = "drop")
## if unnest = FALSE do not unnest lists
if(!isTRUE(.unnest)) {
return(content$items)
}
## create separate tibbles to return as list
content_huc_summary <- select(content$items, -c("assessment_units",
"summary_by_IR_category",
"summary_by_overall_status",
"summary_by_use_group",
"summary_by_use",
"summary_by_parameter_impairments",
"summary_restoration_plans",
"summary_vision_restoration_plans"))
content_assessment_units <- select(content$items, c("assessment_units"))
content_assessment_units <- unnest(content_assessment_units,
cols = everything(), keep_empty = TRUE)
content_IR_summary <- select(content$items, c("summary_by_IR_category"))
content_IR_summary <- unnest(content_IR_summary, cols = everything(),
keep_empty = TRUE)
content_status_summary <- select(content$items, c("summary_by_overall_status"))
content_status_summary <- unnest(content_status_summary,
cols = everything(), keep_empty = TRUE)
content_use_group_summary <- select(content$items, c("summary_by_use_group"))
content_use_group_summary <- unnest(content_use_group_summary,
cols = everything(), keep_empty = TRUE)
content_use_group_summary <- unnest(content_use_group_summary,
cols = everything(), keep_empty = TRUE)
content_use <- select(content$items, c("summary_by_use"))
content_use <- unnest(content_use, cols = everything(), keep_empty = TRUE)
content_use <- unnest(content_use, cols = everything(), keep_empty = TRUE)
content_parameter_impairment <- select(content$items,
c("summary_by_parameter_impairments"))
content_parameter_impairment <- unnest(content_parameter_impairment,
cols = everything(),
keep_empty = TRUE)
content_restoration_plans <- select(content$items,
c("summary_restoration_plans"))
content_restoration_plans <- unnest(content_restoration_plans,
cols = everything(), keep_empty = TRUE)
content_vision_restoration_plans <- select(content$items,
c("summary_vision_restoration_plans"))
content_vision_restoration_plans <- unnest(content_vision_restoration_plans,
cols = everything(),
keep_empty = TRUE)
content <- list(
huc_summary = content_huc_summary,
au_summary = content_assessment_units,
ir_summary = content_IR_summary,
status_summary = content_status_summary,
use_group_summary = content_use_group_summary,
use_summary = content_use,
param_summary = content_parameter_impairment,
res_plan_summary = content_restoration_plans,
vision_plan_summary = content_vision_restoration_plans
)
return(content)
}
}
#' Create tibblify specification for huc12_summary
#' @return tibblify specification
#' @keywords internal
#' @noRd
#' @import tibblify
spec_huc12 <- function() {
spec <- tspec_object(
"items" = tib_df(
"items",
"huc12" = tib_chr("huc12", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE),
"total_catchment_area_sq_mi" = tib_dbl("totalCatchmentAreaSqMi", required = FALSE),
"total_huc_area_sq_mi" = tib_dbl("totalHucAreaSqMi", required = FALSE),
"assessed_catchment_area_sq_mi" = tib_dbl("assessedCatchmentAreaSqMi", required = FALSE),
"assessed_cathcment_area_percent" = tib_dbl("assessedCatchmentAreaPercent", required = FALSE),
"assessed_good_catchment_area_sq_mi" = tib_dbl("assessedGoodCatchmentAreaSqMi", required = FALSE),
"assessed_good_catchment_area_percent" = tib_dbl("assessedGoodCatchmentAreaPercent", required = FALSE),
"assessed_unknown_catchment_area_sq_mi" = tib_dbl("assessedUnknownCatchmentAreaSqMi", required = FALSE),
"assessed_unknown_catchment_area_percent" = tib_dbl("assessedUnknownCatchmentAreaPercent", required = FALSE),
"contain_impaired_waters_catchment_area_sq_mi" = tib_dbl("containImpairedWatersCatchmentAreaSqMi", required = FALSE),
"contain_impaired_catchment_area_percent" = tib_dbl("containImpairedWatersCatchmentAreaPercent", required = FALSE),
"contain_restoration_catchment_area_sq_mi" = tib_dbl("containRestorationCatchmentAreaSqMi", required = FALSE),
"contain_restoration_catchment_area_percent" = tib_dbl("containRestorationCatchmentAreaPercent", required = FALSE),
"assessment_units" = tib_df(
"assessmentUnits",
"assessment_unit_id" = tib_chr("assessmentUnitId", required = FALSE)
),
"summary_by_IR_category" = tib_df(
"summaryByIRCategory",
"EPA_IR_category_name" = tib_chr("epaIRCategoryName", required = FALSE),
"catchment_size_sq_mi" = tib_dbl("catchmentSizeSqMi", required = FALSE),
"catchment_size_percent" = tib_dbl("catchmentSizePercent", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE),
),
"summary_by_overall_status" = tib_df(
"summaryByOverallStatus",
"overall_status" = tib_chr("overallStatus", required = FALSE),
"catchment_size_sq_mi" = tib_dbl("catchmentSizeSqMi", required = FALSE),
"catchment_size_percent" = tib_dbl("catchmentSizePercent", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE)
),
"summary_by_use_group" = tib_df(
"summaryByUseGroup",
"use_group_name" = tib_chr("useGroupName", required = FALSE),
"use_attainment_summary" = tib_df(
"useAttainmentSummary",
"use_attainment" = tib_chr("useAttainment", required = FALSE),
"catchment_size_sq_mi" = tib_dbl("catchmentSizeSqMi", required = FALSE),
"catchment_size_percent" = tib_dbl("catchmentSizePercent", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE)
),
),
"summary_by_use" = tib_df(
"summaryByUse",
"use_name" = tib_chr("useName", required = FALSE),
"use_group_name" = tib_chr("useGroupName", required = FALSE),
"use_attainment_summary" = tib_df(
"useAttainmentSummary",
"use_attainment" = tib_chr("useAttainment", required = FALSE),
"catchment_size_sq_mi" = tib_dbl("catchmentSizeSqMi", required = FALSE),
"catchment_size_percent" = tib_dbl("catchmentSizePercent", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE)
),
),
"summary_by_parameter_impairments" = tib_df(
"summaryByParameterImpairments",
"parameter_group_name" = tib_chr("parameterGroupName", required = FALSE),
"catchment_size_sq_mi" = tib_dbl("catchmentSizeSqMi", required = FALSE),
"catchment_size_percent" = tib_dbl("catchmentSizePercent", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE)
),
"summary_restoration_plans" = tib_df(
"summaryRestorationPlans",
"summary_type_name" = tib_chr("summaryTypeName", required = FALSE),
"catchment_size_sq_mi" = tib_dbl("catchmentSizeSqMi", required = FALSE),
"catchment_size_percent" = tib_dbl("catchmentSizePercent", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE),
),
"summary_vision_restoration_plans" = tib_df(
"summaryVisionRestorationPlans",
"summary_type_name" = tib_chr("summaryTypeName", required = FALSE),
"catchment_size_sq_mi" = tib_dbl("catchmentSizeSqMi", required = FALSE),
"catchment_size_percent" = tib_dbl("catchmentSizePercent", required = FALSE),
"assessment_unit_count" = tib_int("assessmentUnitCount", required = FALSE),
),
),
"count" = tib_int("count", required = FALSE),
)
return(spec)
}