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uscogdata/R/explain.R
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feat: complete = TRUE fills absent cells with their meaning (#18)
Sparsification (cog_pipeline#64, SB194) stopped the corpus storing the wide
era's explicit zeros, which made absence ambiguous:

  <= FY2011  dense_source   absent => Census published $0
  >= FY2012  sparse_source  absent => not reported, unknown

A wide-era query whose cells were all $0 had begun returning nothing at all,
with no way to get them back -- strictly less than the reader exposed before,
which is why #64 filed this follow-on.

complete = TRUE fills the requested grid from `code_set` and stamps every row
with value_source: "reported", "census_zero" (amt 0), or "not_reported"
(amt NA). The NA is the point. Filling a modern absence with 0 would invent
data, which is exactly the error the representation contract exists to
prevent -- and it makes this strictly MORE informative than the
pre-sparsification corpus, which could not tell a published zero from an
unreported cell either.

Measured on the fixture, Broward County: FY2011 returns 28 reported + 16
census_zero; FY2019 returns 30 reported + 14 not_reported. The five
categories that walkthrough finding F-006 read as "retired at FY2012" now
report themselves correctly as census_zero before and not_reported after.

Scoping decisions, each of which would invent rows if taken loosely:

  - The grid is per government TYPE (code_set.type). Filling against the
    union of all types would give a county cells like "state IG transfer to
    school districts", indistinguishable from real census zeros.
  - NOT is_aggregate, mirroring spending_long/revenue_long. Without it the
    grid offers cells those views never return, so each would fill as a
    phantom $0.
  - Filling happens BEFORE per_capita and inflation, so a census_zero stays
    0 through both and a not_reported stays NA rather than becoming 0.

Two new views (36-representation, 37-code_set) are gated on the manifest
LISTING those tables, not on schema_version. Sparsification did not bump the
version -- the fixture this package shipped against until 2026-07-30 was
already v6 and carried neither table -- so a version gate would register a
view over a missing file and fail at CREATE VIEW time on exactly the corpora
the check exists to tolerate. with_corpus_missing_representation() models
that corpus and asserts the abort.

Refused where the fill would be guesswork, both classed
uscogdata_complete_unsupported: a recipe defines its own component codes and
never touches summary_categories; the intergovernmental leg deliberately
keeps aggregate rows (inst/sql/24-ig_long.sql) so its cells are not the ones
code_set describes.

Expected cell sets in the tests are computed from the corpus parquet
directly, never through the verb -- verifying what a filter does through
that same filter proves nothing.

Closes DoD 2, 3 and 4 of #18. DoD 5 (the cog-api follow-on) is filed
separately.

Suite: 658 pass / 0 fail / 3 skip (was 629/0/3). rcmdcheck clean.
2026-07-30 11:47:51 -04:00

228 lines
7.6 KiB
R

# R/explain.R
#' Explain a verb result's provenance
#'
#' Prints the structured provenance attached to a tibble returned by any
#' `cog_*` verb, or returns it as a list for downstream use (MCP tools,
#' dashboards, JSON export).
#'
#' @param result A tibble returned by a `cog_*` verb.
#' @param format `"print"` (default) for a human-readable cli summary;
#' returns `result` invisibly for chaining. `"list"` returns the raw
#' provenance list (identical to `attr(result, "provenance")`).
#' @return Either `result` (invisibly) or the provenance list.
#' @export
cog_explain <- function(result, format = c("print", "list")) {
format <- match.arg(format)
prov <- attr(result, "provenance")
if (is.null(prov)) {
cli::cli_abort(c(
"No `provenance` attribute on result.",
i = "Pass a tibble returned by a cog_* verb (e.g. cog_spending())."
))
}
if (format == "list") return(prov)
.print_provenance(prov)
invisible(result)
}
#' @noRd
.print_provenance <- function(prov) {
cli::cli_h1("{prov$verb}()")
tgt_ids <- paste(prov$target$canonical_govid, collapse = ", ")
tgt_names <- if (length(prov$target$gov_name) == 0L) {
"(no rows returned)"
} else {
paste(prov$target$gov_name, collapse = ", ")
}
cli::cli_text("Target: {tgt_names} [canonical_govid: {tgt_ids}]")
yrs <- prov$years
cli::cli_text(if (length(yrs) == 1L) {
"Year: {yrs}"
} else {
"Years: {min(yrs)}-{max(yrs)} ({length(yrs)} years)"
})
if (!is.null(prov$category)) {
cli::cli_text("Category: {paste(prov$category, collapse = ', ')}")
} else {
cli::cli_text("Category: (all)")
}
if (!is.null(prov$basis)) {
note <- if (!is.null(prov$basis_note) && !is.na(prov$basis_note)) {
sprintf(" (%s)", prov$basis_note)
} else {
""
}
cli::cli_text("Basis: {prov$basis}{note}")
}
if (!is.null(prov$expenditure_concept)) {
concept_note <- if (!is.null(prov$expenditure_concept_note) &&
!is.na(prov$expenditure_concept_note)) {
sprintf(" (%s)", prov$expenditure_concept_note)
} else {
""
}
cli::cli_text("Concept: {prov$expenditure_concept}{concept_note}")
if (isTRUE(prov$expenditure_concept_direct_suppressed)) {
cli::cli_alert_warning(
"Direct leg unavailable for at least one requested (year, category) -- affected rows report intergovernmental dollars alone, not Direct + IG. See each row's notes."
)
}
}
cli::cli_h2("Codes observed")
codes <- prov$codes_summed$observed
if (length(codes) == 0L) {
cli::cli_alert_info("No item codes matched.")
} else {
cli::cli_ul(codes)
}
if (isTRUE(prov$aggregate_fallback$applied)) {
cli::cli_h2("Aggregate fallback")
cli::cli_alert_warning(
"Aggregate fallback used for years: {paste(prov$aggregate_fallback$years, collapse = ', ')}"
)
}
h <- prov$harmonization
if (!is.null(h) && isTRUE(h$applied)) {
cli::cli_h2("Harmonization")
cli::cli_text(
"Excluded {h$na_rows_excluded} row(s) with no harmonized_code (${format(h$na_amount_excluded, big.mark = ',')})"
)
}
rc <- prov$recipe
if (!is.null(rc)) {
cli::cli_h2("Recipe")
cli::cli_text("{rc$recipe_id}: {rc$label}")
comp_lines <- vapply(rc$components, function(x) {
sprintf("%s (%s, %s-%s, weight=%s)", x$component_code, x$gov_type_scope,
x$year_min, x$year_max, x$weight)
}, character(1))
cli::cli_ul(comp_lines)
}
if (length(prov$suggestions) > 0L) {
cli::cli_h2("Suggestions")
sugg_lines <- vapply(prov$suggestions, function(s) {
sprintf("%s -- %s (years %s-%s): %s", s$recipe_id, s$label,
s$available_years[1], s$available_years[2], s$hint)
}, character(1))
cli::cli_ul(sugg_lines)
}
if (isTRUE(prov$completion$applied)) {
cli::cli_h2("Completion")
cli::cli_text(
"Filled {prov$completion$rows_filled} absent cell(s) from the corpus code set."
)
rules <- prov$completion$absence_means
if (length(rules) > 0L) {
cli::cli_ul(vapply(names(rules), function(y) {
sprintf("%s: an absent cell means %s", y,
if (identical(rules[[y]], "census_zero")) {
"Census published $0 (filled as 0)"
} else {
"the government did not report (filled as NA, not 0)"
})
}, character(1)))
}
}
if (length(prov$series_break_refs) > 0L) {
cli::cli_h2("Series breaks")
cli::cli_ul(.series_break_story_lines(prov$series_break_refs))
}
# Kept in a section of its own: these qualify the whole result, so folding
# them in with the per-code breaks above would invite reading them as a
# caveat about one series.
if (length(prov$corpus_break_refs) > 0L) {
cli::cli_h2("Corpus-wide caveats")
cli::cli_ul(.series_break_story_lines(prov$corpus_break_refs))
}
cli::cli_h2("Transformations")
uc <- prov$transformations$units_conversion
if (isTRUE(uc$applied)) {
cli::cli_text("Units: {uc$source_unit} -> {uc$target_unit} (x{uc$multiplier})")
}
pc <- prov$transformations$per_capita
if (isTRUE(pc$applied)) {
cli::cli_text("Per-capita denominator: {pc$denominator_source}")
if (length(pc$popyear_range) == 2L) {
lo <- .expand_popyear(pc$popyear_range[1])
hi <- .expand_popyear(pc$popyear_range[2])
cli::cli_text(" popyear range: {lo}-{hi}")
}
if (!is.null(pc$pop_source_counts)) {
cli::cli_text(
" pop_source counts: census_f33={pc$pop_source_counts$census_f33}, unavailable={pc$pop_source_counts$unavailable}"
)
}
}
infl <- prov$transformations$inflation
if (isTRUE(infl$applied)) {
cli::cli_text("Inflation: {infl$index}, base year {infl$base_year}")
}
cli::cli_h2("Scope")
cli::cli_text(
"Included gov types: {paste(prov$scope$gov_types_included, collapse = ', ')}"
)
cli::cli_text(
"Excluded gov types: {paste(prov$scope$gov_types_excluded, collapse = ', ')}"
)
if (nzchar(prov$scope$scope_note %||% "")) {
cli::cli_text("Note: {prov$scope$scope_note}")
}
cli::cli_h2("Data vintage")
cli::cli_text(
"Manifest schema v{prov$manifest$schema_version}, pipeline {prov$manifest$pipeline_commit}, built {prov$manifest$built_at}"
)
invisible(NULL)
}
# One "break-story" line per referenced break_id: "SB109 (2005): <join_advice>".
# Re-queries series_breaks_pq for the detail (break_year, join_advice) that
# provenance$series_break_refs deliberately doesn't carry (the schema keeps
# that field to a plain id array). Falls back to bare ids if no session is
# available (e.g. explaining a result after cog_close()) rather than
# erroring cog_explain() over a cosmetic detail.
#' @noRd
.series_break_story_lines <- function(break_ids) {
con <- tryCatch(.ensure_session(), error = function(e) NULL)
if (is.null(con) || !DBI::dbIsValid(con)) return(break_ids)
detail <- tryCatch(
DBI::dbGetQuery(con, sprintf(
"SELECT break_id, break_year, join_advice FROM series_breaks_pq
WHERE break_id IN (%s) ORDER BY break_id",
.sql_lit_chr(break_ids)
)),
error = function(e) NULL
)
if (is.null(detail) || nrow(detail) == 0L) return(break_ids)
sprintf("%s (%s): %s", detail$break_id, detail$break_year, detail$join_advice)
}
# Expand a 2-digit Census popyear (e.g. 19) to a 4-digit calendar year (2019).
# F-33 metadata stores popyear as 2 digits; pivot at 70 to handle a future
# corpus that ever spans pre-1970 vintages, though current scope is 2000+.
#' @noRd
.expand_popyear <- function(yy) {
yy <- as.integer(yy)
if (length(yy) == 0L || is.na(yy)) return(NA_integer_)
if (yy >= 100L) return(yy) # already 4-digit
if (yy < 70L) return(2000L + yy)
1900L + yy
}