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7274ce3bfe
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62741343ee
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62741343ee | ||
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0c7c7eb299
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+136
-54
@@ -84,6 +84,21 @@
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#' @return List of `list(recipe_id, label, available_years, hint,
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#' @return List of `list(recipe_id, label, available_years, hint,
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#' ig_recipe_id, trigger, suppressed_amount, suppressed_years,
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#' ig_recipe_id, trigger, suppressed_amount, suppressed_years,
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#' suppressed_codes)`, possibly empty.
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#' suppressed_codes)`, possibly empty.
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#'
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#' Decomposed (Issue #33) into three extracted helpers to stay within the
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#' project's "functions under 50 lines" convention:
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#' \itemize{
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#' \item `.query_candidate_recipes()` -- candidate recipe lookup by
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#' category/subtype scope + M/L exclusion.
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#' \item `.query_recipe_meta()` -- metadata (label, year spans).
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#' \item `.query_covered_years()` -- Path 1 gap-year coverage via the
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#' recipe's own generic join.
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#' }
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#' The for-loop that merges covered-years + suppressed-components into
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#' suggestion objects stays inline here because it interleaves
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#' empty_hit/supp_hit precedence with field assembly. Likewise kept inline:
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#' the M/L-exclusion design-comment block and the final
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#' `.attach_ig_counterparts()` call.
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#' @noRd
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#' @noRd
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.build_suggestions <- function(con, cohort, years, category, result, basis,
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.build_suggestions <- function(con, cohort, years, category, result, basis,
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flow_prefixes, long_view,
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flow_prefixes, long_view,
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@@ -111,28 +126,8 @@
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# by `category` (`.ALL_CATEGORIES` is never a row in
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# by `category` (`.ALL_CATEGORIES` is never a row in
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# `summary_categories.category`, so a category-keyed sub-select always
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# `summary_categories.category`, so a category-keyed sub-select always
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# came back empty here). The M/L exclusion below is unchanged either way.
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# came back empty here). The M/L exclusion below is unchanged either way.
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candidate_scope_sql <- if (isTRUE(all_categories)) {
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candidates <- .query_candidate_recipes(con, category, all_categories,
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sprintf(
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subtype_col, subtype_scope)
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"SELECT DISTINCT item_code FROM summary_categories WHERE %s IN (%s)",
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subtype_col, .sql_lit_chr(subtype_scope)
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)
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} else {
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sprintf(
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"SELECT DISTINCT item_code FROM summary_categories WHERE category IN (%s)",
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.sql_lit_chr(category)
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)
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}
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candidates <- DBI::dbGetQuery(con, sprintf(
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"SELECT DISTINCT recipe_id FROM harmonization_recipes
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WHERE component_code IN (
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%s
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)
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AND recipe_id NOT IN (
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SELECT DISTINCT recipe_id FROM harmonization_recipes
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WHERE LEFT(component_code, 1) IN ('M', 'L')
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)",
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candidate_scope_sql
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))$recipe_id
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if (length(candidates) == 0L) return(list())
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if (length(candidates) == 0L) return(list())
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result_years <- if (is.null(result) || nrow(result) == 0L) {
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result_years <- if (is.null(result) || nrow(result) == 0L) {
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@@ -164,36 +159,11 @@
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if (length(gap_years) == 0L && nrow(supp) == 0L) return(list())
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if (length(gap_years) == 0L && nrow(supp) == 0L) return(list())
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meta <- tibble::as_tibble(DBI::dbGetQuery(con, sprintf(
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meta <- .query_recipe_meta(con, candidates)
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"SELECT recipe_id, any_value(label) AS label,
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MIN(year_min) AS year_min, MAX(year_max) AS year_max
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FROM harmonization_recipes
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WHERE recipe_id IN (%s)
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GROUP BY recipe_id",
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.sql_lit_chr(candidates)
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)))
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# Path 1 (unchanged): (recipe, year) pairs the recipe's own generic join
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# Path 1 (unchanged): (recipe, year) pairs the recipe's own generic join
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# covers for this government, restricted to the gap years.
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# covers for this government, restricted to the gap years.
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covered <- if (length(gap_years) == 0L) {
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covered <- .query_covered_years(con, candidates, cohort, gap_years)
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data.frame(recipe_id = character(0), year = integer(0))
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} else {
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DBI::dbGetQuery(con, sprintf(
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"SELECT DISTINCT r.recipe_id, l.year
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FROM long l
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JOIN harmonization_recipes r
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ON l.item_code = r.component_code
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AND l.year BETWEEN r.year_min AND r.year_max
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AND (r.gov_type_scope = 'all'
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OR (r.gov_type_scope = 'state' AND l.type = 0)
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OR (r.gov_type_scope = 'local' AND l.type BETWEEN 1 AND 3))
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WHERE r.recipe_id IN (%s)
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AND %s
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AND l.year IN (%s)",
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.sql_lit_chr(candidates), .cohort_sql(cohort, "l.canonical_govid"),
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paste(gap_years, collapse = ",")
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))
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}
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suggestions <- list()
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suggestions <- list()
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for (rid in candidates) {
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for (rid in candidates) {
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@@ -227,6 +197,122 @@
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.attach_ig_counterparts(con, suggestions, flow_prefixes)
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.attach_ig_counterparts(con, suggestions, flow_prefixes)
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}
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}
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#' Query candidate harmonization recipe IDs for a coverage-gap suggestion.
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#'
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#' Selects recipes whose component codes fall within the requested scope
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#' (category or subtype allowlist), excluding any recipe that is ITSELF an
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#' intergovernmental (M/L) recipe -- i.e. every one of its own component
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#' codes is M/L-prefixed. Without this exclusion, a category whose
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#' summary_categories rows span both a Direct family (e.g. E04/E05,
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#' "Corrections") and its M/L counterpart (M04/M05) makes the M/L recipe
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#' itself a raw top-level candidate for a plain `cog_spending()` call --
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#' following that hint would silently return intergovernmental dollars
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#' under `expenditure_concept = "direct"` provenance.
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#'
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#' In all-categories mode (`all_categories = TRUE`) the inner sub-select is
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#' scoped by `subtype_col`/`subtype_scope` -- the same allowlist
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#' `.build_verb_sql()` applies as a WHERE predicate to make the summed
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#' result a *concept* (see R/spending.R), not by `category`.
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#' `.ALL_CATEGORIES` ("All Categories") is never itself a row in
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#' `summary_categories.category`, so a category-keyed sub-select always
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#' returns zero candidates and silently disables signposting.
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#'
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#' @param con Active DuckDB connection.
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#' @param category Category name, or `NULL`.
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#' @param all_categories `TRUE` when the caller used `.ALL_CATEGORIES`.
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#' @param subtype_col Name of the summary_categories subtype column to
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#' scope by when `all_categories = TRUE`; ignored otherwise.
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#' @param subtype_scope Character vector of subtype values to scope by
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#' when `all_categories = TRUE`; ignored otherwise.
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#' @return Character vector of recipe IDs (possibly empty).
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#' @noRd
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.query_candidate_recipes <- function(con, category, all_categories = FALSE,
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subtype_col = NULL,
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subtype_scope = NULL) {
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candidate_scope_sql <- if (isTRUE(all_categories)) {
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sprintf(
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"SELECT DISTINCT item_code FROM summary_categories WHERE %s IN (%s)",
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subtype_col, .sql_lit_chr(subtype_scope)
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)
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} else {
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sprintf(
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"SELECT DISTINCT item_code FROM summary_categories WHERE category IN (%s)",
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.sql_lit_chr(category)
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)
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}
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DBI::dbGetQuery(con, sprintf(
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"SELECT DISTINCT recipe_id FROM harmonization_recipes
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WHERE component_code IN (
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%s
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)
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AND recipe_id NOT IN (
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SELECT DISTINCT recipe_id FROM harmonization_recipes
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WHERE LEFT(component_code, 1) IN ('M', 'L')
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)",
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candidate_scope_sql
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))$recipe_id
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}
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#' Query gap-year coverage: which (recipe, year) pairs the recipe's own
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#' generic join covers for this government, restricted to `gap_years`.
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#'
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#' This is Path 1 of a suggestion (unchanged): it finds recipes whose
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#' component codes' generic join produces at least one row for this
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#' government in each gap year -- i.e. the category returned nothing in
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#' that year but a recipe would fill it.
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#'
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#' @param con Active DuckDB connection.
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#' @param candidates Character vector of recipe IDs to check coverage for.
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#' @param cohort The verb's cohort object (see `.make_cohort()`), rendered
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#' into the govid predicate on the joined `long` scan via `.cohort_sql()`.
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#' @param gap_years Integer vector of requested years absent from the
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#' result.
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#' @return Data frame with columns `recipe_id` (character) and `year`
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#' (integer). Returns an empty data frame (`recipe_id = character(0)`,
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#' `year = integer(0)`) when `gap_years` is empty, so callers can safely
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#' reference `$recipe_id`.
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#' @noRd
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.query_covered_years <- function(con, candidates, cohort, gap_years) {
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if (length(gap_years) == 0L) {
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return(data.frame(recipe_id = character(0), year = integer(0)))
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}
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DBI::dbGetQuery(con, sprintf(
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"SELECT DISTINCT r.recipe_id, l.year
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FROM long l
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JOIN harmonization_recipes r
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ON l.item_code = r.component_code
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AND l.year BETWEEN r.year_min AND r.year_max
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AND (r.gov_type_scope = 'all'
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OR (r.gov_type_scope = 'state' AND l.type = 0)
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OR (r.gov_type_scope = 'local' AND l.type BETWEEN 1 AND 3))
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WHERE r.recipe_id IN (%s)
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AND %s
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AND l.year IN (%s)",
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.sql_lit_chr(candidates), .cohort_sql(cohort, "l.canonical_govid"),
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paste(gap_years, collapse = ",")
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))
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}
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#' Query recipe metadata: labels and year spans for a set of candidate
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#' recipes.
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#'
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#' @param con Active DuckDB connection.
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#' @param candidates Character vector of recipe IDs to look up.
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#' @return Tibble with columns `recipe_id`, `label`, `year_min` (int), and
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#' `year_max` (int).
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#' @noRd
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.query_recipe_meta <- function(con, candidates) {
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tibble::as_tibble(DBI::dbGetQuery(con, sprintf(
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"SELECT recipe_id, any_value(label) AS label,
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MIN(year_min) AS year_min, MAX(year_max) AS year_max
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FROM harmonization_recipes
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WHERE recipe_id IN (%s)
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GROUP BY recipe_id",
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.sql_lit_chr(candidates)
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)))
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}
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#' Attach `ig_recipe_id` to each suggestion: the intergovernmental-expenditure
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#' Attach `ig_recipe_id` to each suggestion: the intergovernmental-expenditure
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#' recipe (an M-to-local or L-to-state recipe) whose component codes cover
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#' recipe (an M-to-local or L-to-state recipe) whose component codes cover
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#' exactly the same set of function suffixes as the firing recipe's own
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#' exactly the same set of function suffixes as the firing recipe's own
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@@ -272,7 +358,7 @@
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#' `R/basis.R`). This blocks a recipe surfaced through a mis-scoped
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#' `R/basis.R`). This blocks a recipe surfaced through a mis-scoped
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#' category from ever reaching the M/L search, e.g. `cog_spending()`'s
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#' category from ever reaching the M/L search, e.g. `cog_spending()`'s
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#' flow_prefixes are `c("E","F","G")`, which `ig_federal_b47_wide`'s own
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#' flow_prefixes are `c("E","F","G")`, which `ig_federal_b47_wide`'s own
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#' `"B"` is not part of.
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#' "B" is not part of.
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#' 2. `own_prefix %in% c("E","F","G")`: M/L only ever pairs with the
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#' 2. `own_prefix %in% c("E","F","G")`: M/L only ever pairs with the
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#' DIRECT-expenditure family, never with revenue (`cog_revenue()`'s
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#' DIRECT-expenditure family, never with revenue (`cog_revenue()`'s
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#' flow_prefixes already fold B/C/D in as ordinary revenue -- there is
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#' flow_prefixes already fold B/C/D in as ordinary revenue -- there is
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@@ -280,10 +366,6 @@
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#' adds one for spending) and never with ANOTHER M/L recipe (without
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#' adds one for spending) and never with ANOTHER M/L recipe (without
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#' this check, `ige_local_m47_wide` would wrongly match sibling
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#' this check, `ige_local_m47_wide` would wrongly match sibling
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#' `ige_state_l47_wide` on their shared {"47","94"} suffix set).
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#' `ige_state_l47_wide` on their shared {"47","94"} suffix set).
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#' Condition 1 alone does not catch this: under `cog_revenue()`,
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#' `ig_federal_b47_wide`'s own `"B"` IS inside revenue's own
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#' `flow_prefixes`, so only this second, family-specific check blocks
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#' the search.
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#' @noRd
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#' @noRd
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.attach_ig_counterparts <- function(con, suggestions, flow_prefixes) {
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.attach_ig_counterparts <- function(con, suggestions, flow_prefixes) {
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if (length(suggestions) == 0L) return(suggestions)
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if (length(suggestions) == 0L) return(suggestions)
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Reference in New Issue
Block a user