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jared 515ab3b019 docs: survey_weight is col 28 under schema v6 (was col 26 in v5)
R-CMD-check / check (push) Failing after 1m49s
Rebase onto the v6 main (bd53230) shifted survey_weight from col 26 to
col 28: v5→v6 inserted cog_legacy_state/cog_legacy_county at positions
10-11 (26→28 cols). Position confirmed against the regenerated v6
fixture and both corpus docs (reader-specification.md §3 'Long parquet
schema (28 columns)' row 28; data_dictionary.md '28-column schema v6'
row 28).
2026-07-23 12:22:25 -04:00
jared d238bc0a22 feat: report the coarse-vs-per-code subset relation in the signposting harness
The coarse and per-code signposting checks are partly DISJOINT, not nested:
coarse fires on queries per-code does not, so the coarse -> percode move
both adds and removes signposting. Every `*_delta_pp` the harness reports is
therefore a NET that can mask a coverage loss in either direction. The
staged-corpus headline (+1.875 pp, coarse 1/640 -> percode 13/640) sits on
top of Corrections losing coverage outright (0.05 -> 0.00, -5 pp).

The cause is structural, not sampling: coarse's coverage test is at recipe
grain and self-coverage-permissive, while per-code requires a DIFFERENT
component of the same recipe. When a whole category is empty in a year --
coarse's own trigger -- and the only covering evidence is the gapped
component's own wide-era aggregate row, per-code cannot fire by
construction. That case is already pinned as intended behaviour in
test-recipes.R; this change measures what it costs, it does not change it.

Measurement and disclosure only. R/suggestions.R is untouched -- which arm
ships is the human ruling at Checkpoint R3.

- header: replace the "noise trade" framing with an explicit statement that
  the checks are partly disjoint and every delta is a net
- .measure_subset_relation(): split the disagreement into violations
  (coarse fired, per-code silent -- coverage LOST) and additions, returning
  the offending rows, not just counts. No assertion: the violation set is
  genuinely non-empty and a stopifnot() would only break the harness that
  is supposed to surface it
- .measure_format_subset_report(): prominent HOLDS / *** VIOLATED ***
  section naming each offending (category, government, year)
- detail gains coarse_gap_years / coarse_recipes / percode_recipes;
  by_category gains n_coarse_only / n_percode_only so the two netted flows
  are visible per category
- new test-signposting-harness.R pins the reporting, including inversion
  guards and an end-to-end case (Broward FY2011 Corrections) where coarse
  fires and per-code does not

Tests: 518 PASS / 0 FAIL / 0 WARN / 0 SKIP (was 476). Mutation-checked:
inverting the violation direction fails 18 assertions, removing the
violation reporting fails 9.
2026-07-23 12:22:24 -04:00
jared e53aeb9643 docs: warn raw-parquet readers that survey_weight is not an aggregation weight
The v5 schema passes the legacy IndFin Weight column through verbatim as
survey_weight. Census documents it as informational-only, and its encoding
is inconsistent across vintages (reciprocal scale most years, direct in
2003, placeholder 1 in 1967-2001 gap years, all-0 in 2007-2012, NA modern),
so weighting amt by it produces silently wrong totals. No uscogdata function
reads the column; this warning is for direct DuckDB/arrow consumers.
Evidence: cog_pipeline/.superpowers/sdd/weight-semantics-findings.md.
2026-07-23 12:22:24 -04:00
jared 9244e08085 feat: add self-coverage decomposition arm to signposting harness
Adds a third comparison arm to measure_signposting_rate(): Task 19c's
first per-code pass (git ref da72bf3, self-coverage allowed) alongside
the existing coarse (b0df1ec) and live corrected per-code arms, pulled
verbatim via the same git-show mechanism (renamed
.measure_load_coarse_impl -> .measure_load_git_impl since it now loads
more than the coarse arm).

Reports both the original delta (self-coverage-allowed rate minus
coarse) and the corrected delta (live per-code rate minus coarse), plus
the self-coverage share of the original delta (queries that fired ONLY
because a component's own aggregate row satisfied its own coverage
check). Verifies percode-fired is always a subset of selfcov-fired
(stopifnot) -- the corrected arm is a strict narrowing of the buggy one,
so the decomposition is exact rather than approximate.
2026-07-23 12:22:23 -04:00
jared 1b2294e3a0 fix: require a DIFFERENT recipe component to cover a per-code gap
.recipe_coverage()'s covered_years were computed once per recipe as a
union across ALL of its components (aggregate rows included), without
excluding the component currently being tested for a gap. So a code
whose only representation in a year was its own wide-era aggregate row
satisfied its own "covered" check -- self-coverage, not the "other
components" review-doc 0.3's criterion actually specifies ("...has no
rows ... but other components do").

.recipe_coverage() now returns (recipe_id, component_code, year)
triples instead of collapsing across components, and
.recipe_component_gapped() excludes the component under test before
checking coverage, so a gap only fires when a genuinely different
sibling component has data in that year.

Adds the boundary test this gap in coverage let slip through untested:
Broward FY2011 alone, where E05/F05/G05 each report solely as their own
wide-era aggregate row and E04/F04/G04 don't exist as codes before 2012
corpus-wide, so none of the three Corrections recipes have any OTHER
component to cover them -- must produce zero suggestions. The existing
2011-2012 combined test still passes, now firing because of the 2012
E05-gapped/E04-covers pair rather than 2011's self-coverage. Updates the
header comment to state the other-component requirement explicitly.
2026-07-23 12:22:23 -04:00
jared 91b64b9b8b feat: add coarse-vs-per-code signposting rate measurement harness
data-raw/measure_signposting_rate.R runs every summary_categories
category x a (seeded, deterministic) sample of up to 20 governments x
the widest pre/post-2012 year span the active corpus actually supports,
through both the R2 coarse .build_suggestions() (pulled verbatim from
git ref b0df1ec, evaluated in an isolated env parented on the uscogdata
namespace) and the current per-code version, and reports the suggestion
rate and delta under each, overall and by category.

Parameterized by USCOGDATA_URL (defaults to the bundled fixture when
unset) so it can be re-run against the staged/full corpus later. Detects
and reports when the active corpus can't fill a full 3-year pre/3-year
post-2012 design instead of padding or fabricating years. This script
measures the coarse-vs-per-code tradeoff; it does not rule on what
suggestion-rate increase is an acceptable amount of added noise -- that
is Jared's call at Checkpoint R3.
2026-07-23 12:22:22 -04:00
jared 267bc24fee feat: narrow harmonization signposting to per-code gap detection
.build_suggestions() previously flagged a recipe only when the WHOLE
category result had zero rows in a requested year, so a multi-code
category where one recipe component was genuinely gapped never fired
if any sibling code (same recipe or not) had data that year. Each
recipe's own in-category component is now checked individually -- a
component fires when it has no rows in a requested (in-scope) year the
recipe's own generic join otherwise covers, even when the overall
category result looks complete.

Decomposes .build_suggestions() into .category_recipe_components/
.recipe_meta/.component_presence/.recipe_coverage/.recipe_component_gapped
helpers, drops the now-unused `result` param, and rewrites the header
comment to describe the new, deliberately wider scope plus the
per-government `covered` guard that still filters recipes with no data
at all (ordinary reporting variance vs. a real format-boundary gap).

Tests pin the multi-code case the coarse check missed (Cleburne County
FY2012: G05 gapped, G04 covers, masked because E04/E05 have data) next
to the still-guarded no-recipe-coverage case (F04/F05 both absent), and
update the Broward 2019-2020 case to its new, correct expectation (fires
for corrections_combined/corrections_other_capital_combined, still
silent for corrections_capital_combined) plus a fresh true-full-coverage
negative case (Maricopa County).
2026-07-23 12:22:22 -04:00
8 changed files with 992 additions and 118 deletions
+1 -24
View File
@@ -21,30 +21,7 @@
.uscogdata_defaults[[key]]
}
#' Resolve the corpus URL, guaranteeing the trailing slash the package assumes.
#'
#' Every consumer builds locations by CONCATENATION -- `paste0(url,
#' "manifest.json")` in manifest.R, `paste0(url, e$path)` in mirror.R, and the
#' parquet glob in views.R -- and mirror.R:104 documents the invariant outright
#' ('url ends in "/"'). Nothing enforced it, so a URL entered without the slash
#' failed silently and misleadingly:
#'
#' HTTPS -> ".../downloadmanifest.json"; the host answers with an HTML 404
#' page, which lands in the JSON parser as the lexical error
#' reported in issue #3 -- pointing the user at "login page / wrong
#' share" when the real cause was one missing character.
#' local -> ".../corpusdata/long/**/*.parquet" and a DuckDB "No files found".
#'
#' Normalizing here fixes every consumer at once, rather than each call site
#' re-deriving the same invariant. An empty setting is passed through
#' untouched so manifest.R's "not configured" guard still fires instead of the
#' value degrading into a bare "/" filesystem root.
#' @noRd
.resolve_url <- function() {
url <- .cfg("url")
if (is.null(url) || !nzchar(url) || grepl("/$", url)) return(url)
paste0(url, "/")
}
.resolve_url <- function() .cfg("url")
.resolve_cache_dir <- function() {
v <- .cfg("cache_dir")
+1 -1
View File
@@ -141,7 +141,7 @@ cog_spending <- function(govid, years, category = NULL,
harmonization <- .build_harmonization_block(
con, govid, years, resolved, flow_prefixes
)
suggestions <- .build_suggestions(con, govid, years, category, result, resolved$basis)
suggestions <- .build_suggestions(con, govid, years, category, resolved$basis)
}
prov <- .build_provenance(
+150 -54
View File
@@ -1,8 +1,9 @@
# R/suggestions.R
# Recipe-component-driven signposting: when a basis = "harmonized" query for
# a category comes back with a coverage gap in some requested years (the
# result has no rows at all in that year) that a harmonization recipe would
# actually fill for this government, surface that recipe as a suggestion.
# a category asks for a code that is itself a harmonization recipe
# component, and that specific code has no rows in some requested years
# while the recipe's own generic join would still fill those years for this
# government, surface that recipe as a suggestion.
#
# This is deliberately keyed off the recipe catalog's component codes, not
# off harmonization_map rows: no live map row carries a non-blank
@@ -12,53 +13,58 @@
# suggestion off of, just a leaf-code absence a recipe happens to fill).
# See docs/phase_r_harmonization_review.md § 0.3.
#
# Scope is deliberately narrow: signposting only runs when the caller
# Scope is deliberately narrow in one respect and, as of Phase R3 Task 19c,
# deliberately WIDE in another: signposting only runs when the caller
# supplied a `category` (an un-scoped, all-categories query has no single
# coverage question to answer) and only flags a recipe when the ACTUAL
# result has zero rows in a requested year AND the candidate recipe's own
# generic join (same join .run_recipe() uses, including its wide-era
# aggregate rows) produces at least one row for this government in that
# year. Checking presence per-government (not corpus-wide) avoids false
# positives from ordinary reporting variance -- most governments don't use
# every sibling code in a multi-code category every year, and that is not
# a format-boundary gap worth signposting.
# coverage question to answer), but within that category it now checks
# EACH recipe component that is itself a category member individually,
# rather than asking whether the whole category *result* has zero rows
# that year. A recipe fires when one of its own components has zero rows
# for this government in a requested year, AND SOME OTHER component of that
# SAME recipe -- excluding the gapped one itself -- has a row (same join
# .run_recipe() uses, aggregate rows included) for that year. This is the
# literal review-doc § 0.3 criterion: "...has no rows ... but other
# components do." A component's OWN aggregate-only row does not satisfy
# its own gap (self-coverage is not "other components"); only a genuinely
# different sibling component can. This fires even if OTHER, unrelated
# codes in the same category have full data that year and the overall
# result looks complete. That is a deliberate narrowing of the R2-era
# false-positive guard: most governments don't use every sibling code in a
# multi-code category every year, and per-code detection WILL flag some of
# that as a "gap" even though it's really just a government not having
# that particular sub-type of spending, not a format-boundary artifact.
# The remaining guard against ordinary reporting variance is the
# per-government, per-OTHER-component `covered` check below (a component
# is only flagged when a DIFFERENT component of the SAME recipe -- not
# some unrelated code, and not the gapped component's own aggregate row --
# actually has something to offer in that year); it no longer tries to
# avoid noise from sibling *codes*, only from a recipe with genuinely
# nothing else to contribute. The acceptable noise level this trade
# produces is a product decision, measured (not tuned here) by
# data-raw/measure_signposting_rate.R and ruled on at Checkpoint R3.
#' Build the `prov$suggestions` list for a (non-recipe) basis = "harmonized"
#' verb call: recipes whose generic join would fill a real gap in `result`.
#'
#' @param con Active DuckDB connection.
#' @param govid Character vector of canonical_govid values (the verb's raw
#' `govid`).
#' @param years Integer vector of requested years.
#' @param category `category` argument as passed to the verb (character
#' vector or `NULL`; suggestions are only computed when non-NULL).
#' @param result The verb's already-computed result tibble (post basis
#' query, pre per_capita/adjust_to_year).
#' @param basis The *resolved* basis (`"harmonized"` or `"raw"`).
#' @return List of `list(recipe_id, label, available_years, hint)`, possibly
#' empty.
#' Recipe components that are classified under the requested category --
#' the codes a category-scoped query actually "requests". A recipe can
#' have components outside the category (e.g. general_gov_e89_wide's E85
#' leg has no category assignment); those never trigger on their own, they
#' just were never part of what this query asked for.
#' @noRd
.build_suggestions <- function(con, govid, years, category, result, basis) {
if (!identical(basis, "harmonized") || is.null(category)) return(list())
candidates <- DBI::dbGetQuery(con, sprintf(
"SELECT DISTINCT recipe_id FROM harmonization_recipes
WHERE component_code IN (
SELECT DISTINCT item_code FROM summary_categories WHERE category IN (%s)
)",
.category_recipe_components <- function(con, category) {
DBI::dbGetQuery(con, sprintf(
"SELECT DISTINCT r.recipe_id, r.component_code, r.year_min, r.year_max,
r.gov_type_scope
FROM harmonization_recipes r
JOIN summary_categories sc
ON sc.item_code = r.component_code AND sc.category IN (%s)",
.sql_lit_chr(category)
))$recipe_id
if (length(candidates) == 0L) return(list())
))
}
result_years <- if (is.null(result) || nrow(result) == 0L) {
integer(0)
} else {
unique(as.integer(result$year))
}
gap_years <- setdiff(as.integer(years), result_years)
if (length(gap_years) == 0L) return(list())
meta <- tibble::as_tibble(DBI::dbGetQuery(con, sprintf(
#' Label + overall year coverage for a set of recipe ids (the suggestion's
#' `label`/`available_years`).
#' @noRd
.recipe_meta <- function(con, candidates) {
tibble::as_tibble(DBI::dbGetQuery(con, sprintf(
"SELECT recipe_id, any_value(label) AS label,
MIN(year_min) AS year_min, MAX(year_max) AS year_max
FROM harmonization_recipes
@@ -66,13 +72,48 @@
GROUP BY recipe_id",
.sql_lit_chr(candidates)
)))
}
# Which (recipe_id, year) pairs the recipe's own generic join actually
# covers for this government, restricted to the gap years -- the same
# join .run_recipe() uses (component year_min/year_max + gov_type_scope,
# no is_aggregate filter), just checking existence instead of summing.
covered <- DBI::dbGetQuery(con, sprintf(
"SELECT DISTINCT r.recipe_id, l.year
#' Which (recipe_id, component_code, year) triples have at least one
#' NOT-aggregate row for these governments -- i.e. that specific requested
#' code itself has data, scoped exactly like .run_recipe()'s join
#' (component year_min/year_max + gov_type_scope). NOT-aggregate mirrors
#' what basis = "harmonized" itself excludes: an aggregate-only year is a
#' gap for that code exactly as it would be in a plain category query.
#' @noRd
.component_presence <- function(con, candidates, govid, years_lit) {
DBI::dbGetQuery(con, sprintf(
"SELECT DISTINCT r.recipe_id, r.component_code, l.year
FROM long l
JOIN harmonization_recipes r
ON l.item_code = r.component_code
AND l.year BETWEEN r.year_min AND r.year_max
AND (r.gov_type_scope = 'all'
OR (r.gov_type_scope = 'state' AND l.type = 0)
OR (r.gov_type_scope = 'local' AND l.type BETWEEN 1 AND 3))
WHERE NOT l.is_aggregate
AND r.recipe_id IN (%s)
AND l.canonical_govid IN (%s)
AND l.year IN (%s)",
.sql_lit_chr(candidates), .sql_lit_chr(govid), years_lit
))
}
#' Which (recipe_id, component_code, year) triples have at least one row
#' (aggregate rows included) for these governments -- the same scoping
#' .run_recipe()'s join uses (component year_min/year_max + gov_type_scope),
#' just checking existence instead of summing. Kept at per-component grain
#' (not unioned across the whole recipe, unlike the R2/R3-pre-fix version of
#' this function) so a gap check can require the covering evidence to come
#' from a DIFFERENT component -- review-doc § 0.3's "other components", not
#' the gapped component's own aggregate row. This is the per-government
#' guard against ordinary reporting variance: a recipe with genuinely
#' nothing to offer from any OTHER component (aggregate or leaf) never
#' fires.
#' @noRd
.recipe_coverage <- function(con, candidates, govid, years_lit) {
DBI::dbGetQuery(con, sprintf(
"SELECT DISTINCT r.recipe_id, r.component_code, l.year
FROM long l
JOIN harmonization_recipes r
ON l.item_code = r.component_code
@@ -83,13 +124,68 @@
WHERE r.recipe_id IN (%s)
AND l.canonical_govid IN (%s)
AND l.year IN (%s)",
.sql_lit_chr(candidates), .sql_lit_chr(govid),
paste(gap_years, collapse = ",")
.sql_lit_chr(candidates), .sql_lit_chr(govid), years_lit
))
}
#' TRUE if recipe `rid` has at least one requested component with an
#' in-scope requested year that has no data (`present`), in a year some
#' OTHER component of the same recipe is otherwise fillable (`covered`,
#' excluding the component under test) -- the per-code gap the R2
#' whole-result check couldn't see, covered by another component the way
#' review-doc § 0.3 specifies (not by the gapped component's own aggregate
#' row -- that is self-coverage, not "other components", and must not
#' count).
#' @noRd
.recipe_component_gapped <- function(rid, requested, present, covered, years) {
comps <- requested[requested$recipe_id == rid, , drop = FALSE]
for (i in seq_len(nrow(comps))) {
this_code <- comps$component_code[i]
in_scope <- years[years >= comps$year_min[i] & years <= comps$year_max[i]]
if (length(in_scope) == 0L) next
has_data <- present$year[
present$recipe_id == rid & present$component_code == this_code
]
gap_years <- setdiff(in_scope, has_data)
if (length(gap_years) == 0L) next
other_covered_years <- covered$year[
covered$recipe_id == rid & covered$component_code != this_code
]
if (any(gap_years %in% other_covered_years)) return(TRUE)
}
FALSE
}
#' Build the `prov$suggestions` list for a (non-recipe) basis = "harmonized"
#' verb call: recipes whose generic join would fill a real per-code gap for
#' the requested category.
#'
#' @param con Active DuckDB connection.
#' @param govid Character vector of canonical_govid values (the verb's raw
#' `govid`).
#' @param years Integer vector of requested years.
#' @param category `category` argument as passed to the verb (character
#' vector or `NULL`; suggestions are only computed when non-NULL).
#' @param basis The *resolved* basis (`"harmonized"` or `"raw"`).
#' @return List of `list(recipe_id, label, available_years, hint)`, possibly
#' empty.
#' @noRd
.build_suggestions <- function(con, govid, years, category, basis) {
if (!identical(basis, "harmonized") || is.null(category)) return(list())
requested <- .category_recipe_components(con, category)
if (nrow(requested) == 0L) return(list())
candidates <- unique(requested$recipe_id)
years_int <- as.integer(years)
years_lit <- paste(years_int, collapse = ",")
meta <- .recipe_meta(con, candidates)
present <- .component_presence(con, candidates, govid, years_lit)
covered <- .recipe_coverage(con, candidates, govid, years_lit)
suggestions <- list()
for (rid in candidates) {
if (!rid %in% covered$recipe_id) next
if (!.recipe_component_gapped(rid, requested, present, covered, years_int)) next
m <- meta[meta$recipe_id == rid, ]
suggestions[[length(suggestions) + 1L]] <- list(
recipe_id = rid,
+16
View File
@@ -25,6 +25,22 @@ package implements.
- `USCOGDATA_CACHE_DIR` — optional override for the manifest cache directory
- `USCOGDATA_MANIFEST_TTL_SECS` — optional manifest re-fetch TTL (default 3600)
## Raw-parquet caveat: `survey_weight` is not an aggregation weight
Users reading the corpus parquet directly (DuckDB, arrow) will see a
`survey_weight` column (schema v6, col 28). It is legacy Census IndFin
sample-design **metadata passed through verbatim** — the Census Bureau's own
source documentation says it "is for informational purposes only and should
not be used to derive any other statistics" (`_ReadMe_First_IndFin.txt`;
likewise `UserGuide.xls` Data User Note 8: "Do not use the weight field to
derive state or national totals"). The raw encoding is also inconsistent
across vintages (reciprocal scale most years, direct scale in 2003, a `1`
placeholder in 1967/70/71/73/2001, all-`0` in 2007–2012, `NA` for all
modern-source rows), so `sum(amt * survey_weight/10000)`-style expressions
produce silently wrong totals — including exact zeros for 2007–2012. Sum
`amt` unweighted; no uscogdata function reads this column. Full evidence:
`cog_pipeline/.superpowers/sdd/weight-semantics-findings.md`.
## Developer notes
### Testing
+563
View File
@@ -0,0 +1,563 @@
# data-raw/measure_signposting_rate.R
#
# Phase R3 Task 19c: measures the harmonization-signposting suggestion rate
# under THREE `.build_suggestions()` implementations, over a realistic query
# battery:
# every summary_categories category
# x a 3-year pre/post-2012 span (the wide-aggregate -> modern-leaf
# format-boundary window; falls back to the widest span the corpus
# actually supports if it can't fill a full 3+3 design -- see
# .measure_year_span())
# x up to N_GOV sampled governments (seeded, deterministic)
#
# The three arms, oldest to newest:
# - "coarse" (git ref b0df1ec, the merged R2 tip): a year counts as
# gapped only when the WHOLE category result has zero rows that year.
# - "selfcov" (git ref da72bf3, Task 19c's first per-code pass, since
# amended after review): per-code, but a component's gap could be
# satisfied by ANY component of the recipe INCLUDING ITSELF -- so a
# code whose only representation in a year was its own wide-era
# aggregate row satisfied its own coverage check. Flagged in review as
# not matching review-doc S: 0.3's literal criterion ("... has no rows
# ... but OTHER components do") and fixed in the next commit.
# - "percode" (live code): per-code, requiring a genuinely DIFFERENT
# sibling component to supply the covering evidence -- the shipped,
# corrected implementation.
#
# READ THIS BEFORE QUOTING ANY DELTA FROM THIS SCRIPT
# -----------------------------------------------------
# The coarse and per-code checks are PARTLY DISJOINT, not nested. Per-code
# is NOT a strict widening of coarse: there are queries coarse fires on that
# per-code does not, so moving coarse -> percode both ADDS and REMOVES
# signposting. Every `*_delta_pp` figure this script reports -- overall and
# per category -- is therefore a NET of those two flows and can mask a
# coverage loss in either direction. A headline "+X pp" can sit on top of
# categories that lost coverage outright (a NEGATIVE corrected_delta_pp),
# and a category-level zero can be an add and a loss cancelling. Read
# `$subset_relation` (printed under "Subset relation" below) alongside any
# delta; that section is where the two flows are separated.
#
# The disjointness is structural, not a sampling artifact. Both arms pair a
# gap test with a coverage test, and it is the COVERAGE test that differs:
# - coarse: gap = the WHOLE category result has zero rows that year;
# covered = the recipe's generic join has ANY row that year
# (unioned across all components -- a component's own
# aggregate row counts).
# - percode: gap = one specific component has no non-aggregate row that
# year; covered = a DIFFERENT component of the SAME recipe has
# a row that year (self-coverage explicitly excluded, per
# review-doc S: 0.3's "...but OTHER components do").
# So when a whole category is empty in a year -- exactly coarse's trigger --
# and the only covering evidence is the gapped component's own wide-era
# aggregate row, coarse fires and per-code CANNOT: there is by construction
# no other component to supply the evidence. That case is already pinned as
# intended behaviour in tests/testthat/test-recipes.R ("per-code gap does
# NOT fire when a code's only coverage is its own aggregate row"). This
# script's job is to say how often it costs coverage, not to relitigate it.
#
# This script MEASURES the deltas; it does not decide whether the resulting
# signposting trade -- added "noise" in one direction, lost whole-category
# gap coverage in the other -- is acceptable. That is Jared's ruling at
# Checkpoint R3 (see
# cog_pipeline/.superpowers/sdd/phase-r-task-19c-brief.md). The selfcov arm
# exists purely to answer a narrower, mechanical question for that ruling:
# how much of the coarse -> percode delta was ever attributable to the
# self-coverage bug (selfcov -> percode), as opposed to genuine
# other-component coverage (coarse -> percode directly)?
#
# All three arms no longer coexist in R/suggestions.R (each superseded the
# last in place), so this script pulls each VERBATIM from git history and
# evaluates it in an isolated environment parented on the uscogdata
# namespace, so each still resolves the unchanged sibling helpers it
# depends on (.sql_lit_chr()) exactly as the live package did at that
# commit. This guarantees every non-live arm is the actual shipped code at
# that point, not a hand-reconstruction that could silently drift from what
# really shipped.
#
# Usage (from the uscogdata package root; a git checkout, not a tarball):
# Rscript data-raw/measure_signposting_rate.R
# USCOGDATA_URL=<staged-corpus-url> Rscript data-raw/measure_signposting_rate.R
#
# Or from R:
# source("data-raw/measure_signposting_rate.R")
# res <- measure_signposting_rate(corpus_url = "<url>")
# res$summary; res$by_category
#' Pull a historical `.build_suggestions()` (and whatever helpers it uses)
#' verbatim from git history and evaluate it in an isolated environment
#' parented on the uscogdata namespace, so it resolves unchanged sibling
#' helpers (`.sql_lit_chr()`) the same way the live package does.
#' @noRd
.measure_load_git_impl <- function(git_ref, git_path = "R/suggestions.R") {
old_src <- tryCatch(
system2("git", c("show", sprintf("%s:%s", git_ref, git_path)),
stdout = TRUE, stderr = TRUE),
error = function(e) NULL
)
status <- attr(old_src, "status")
if (is.null(old_src) || (!is.null(status) && status != 0L) ||
!any(grepl("^\\.build_suggestions", old_src))) {
stop(
"Could not retrieve the .build_suggestions() implementation from ",
"git ref '", git_ref, "' at '", git_path, "'. Run this script from ",
"inside the uscogdata git checkout (not a tarball/installed copy).",
call. = FALSE
)
}
env <- new.env(parent = asNamespace("uscogdata"))
# eval(parse()) here is safe: `old_src` is not external/untrusted input --
# it is this repo's OWN historical R/suggestions.R, fetched via `git show`
# from a fixed, hardcoded internal commit ref (overridable only by a
# caller who already has R-level code execution in this dev-only
# measurement script). No network or user-supplied data reaches this call.
eval(parse(text = old_src), envir = env)
stopifnot(is.function(env$.build_suggestions))
env
}
#' Resolve the query battery's year span: a `pre_n`-year window immediately
#' before `boundary_year` unioned with a `post_n`-year window starting at
#' `boundary_year` (default 3+3 around 2012, the wide-aggregate ->
#' modern-leaf format boundary). Falls back to every distinct year the
#' corpus actually has in `long` when it can't fill that full design, and
#' says so explicitly in `$note` rather than silently padding or
#' fabricating years.
#' @noRd
.measure_year_span <- function(con, boundary_year = 2012L,
pre_n = 3L, post_n = 3L) {
available <- sort(as.integer(
DBI::dbGetQuery(con, "SELECT DISTINCT year FROM long")$year
))
desired_pre <- (boundary_year - pre_n):(boundary_year - 1L)
desired_post <- boundary_year:(boundary_year + post_n - 1L)
actual_pre <- intersect(desired_pre, available)
actual_post <- intersect(desired_post, available)
full_design <- length(actual_pre) == pre_n && length(actual_post) == post_n
if (full_design) {
years <- sort(c(actual_pre, actual_post))
note <- sprintf(
"Full %d-year pre/%d-year post-%d design available -- using years: %s.",
pre_n, post_n, boundary_year, paste(years, collapse = ", ")
)
} else {
years <- available
note <- sprintf(paste(
"Corpus does NOT support a full %d-year pre/%d-year post-%d span",
"(desired pre-window %s -> only %s present; desired post-window %s",
"-> only %s present). Falling back to the WIDEST span this corpus",
"supports: all %d distinct year(s) actually in `long`: %s.",
"This is NOT a 3-year pre/post-%d design -- reported as measured,",
"not padded or fabricated."
),
pre_n, post_n, boundary_year,
paste(desired_pre, collapse = ","),
if (length(actual_pre)) paste(actual_pre, collapse = ",") else "none",
paste(desired_post, collapse = ","),
if (length(actual_post)) paste(actual_post, collapse = ",") else "none",
length(available), paste(available, collapse = ", "),
boundary_year)
}
list(years = years, full_design = full_design, note = note,
available = available)
}
#' Deterministically sample up to `n` distinct governments that actually
#' report *something* in the battery's year span (querying a government
#' with zero presence in every measured year isn't a realistic query).
#' @noRd
.measure_sample_govids <- function(con, years, n = 20L, seed = 19L) {
pool <- DBI::dbGetQuery(con, sprintf(
"SELECT DISTINCT canonical_govid FROM long WHERE year IN (%s)
ORDER BY canonical_govid",
paste(years, collapse = ",")
))$canonical_govid
if (length(pool) <= n) return(sort(pool))
set.seed(seed)
sort(sample(pool, n))
}
#' Comma-join a suggestion list's recipe ids (stable order) for the detail
#' frame's audit columns; `""` when nothing fired.
#' @noRd
.measure_recipe_ids <- function(suggestions) {
if (length(suggestions) == 0L) return("")
paste(sort(vapply(suggestions, function(s) s$recipe_id, character(1))),
collapse = ",")
}
#' Run one (category, government) query through the coarse (`coarse_env`),
#' self-coverage-allowed (`selfcov_env`), and live per-code
#' `.build_suggestions()` and return a one-row summary of what each fired.
#'
#' Also records the coarse arm's OWN trigger evidence -- `coarse_gap_years`,
#' the requested years in which the whole category result has zero rows --
#' so a coarse-fired/per-code-silent disagreement can be named down to
#' (category, government, year) instead of just counted. Per-code's gap
#' years are deliberately NOT re-derived here: that would mean
#' reimplementing `.recipe_component_gapped()`'s set arithmetic in the
#' measurement harness, where it could silently drift from the code under
#' measurement. Per-code rows are identified by the recipe ids they fired.
#' @noRd
.measure_one_query <- function(con, coarse_env, selfcov_env, category,
category_type, govid, years) {
view <- if (identical(category_type, "revenue")) {
"revenue_annotated_harmonized"
} else {
"spending_annotated_harmonized"
}
subtype_col <- if (identical(category_type, "revenue")) {
"revenue_subtype"
} else {
"spend_subtype"
}
sql <- .build_verb_sql(view, subtype_col, govid, years, category)
result <- tibble::as_tibble(DBI::dbGetQuery(con, sql))
coarse_sugg <- coarse_env$.build_suggestions(
con, govid, years, category, result, "harmonized"
)
selfcov_sugg <- selfcov_env$.build_suggestions(
con, govid, years, category, "harmonized"
)
percode_sugg <- .build_suggestions(con, govid, years, category, "harmonized")
result_years <- if (nrow(result) == 0L) integer(0) else unique(as.integer(result$year))
gap_years <- sort(setdiff(as.integer(years), result_years))
data.frame(
category = category,
category_type = category_type,
canonical_govid = govid,
n_result_rows = nrow(result),
coarse_gap_years = paste(gap_years, collapse = ","),
n_coarse = length(coarse_sugg),
n_selfcov = length(selfcov_sugg),
n_percode = length(percode_sugg),
fired_coarse = length(coarse_sugg) > 0L,
fired_selfcov = length(selfcov_sugg) > 0L,
fired_percode = length(percode_sugg) > 0L,
coarse_recipes = .measure_recipe_ids(coarse_sugg),
percode_recipes = .measure_recipe_ids(percode_sugg),
stringsAsFactors = FALSE
)
}
#' Columns that identify a disagreeing query well enough for a human to go
#' and inspect it, in print order. Intersected with what `detail` actually
#' has, so this works on a minimal hand-built frame too.
#' @noRd
.MEASURE_IDENTITY_COLS <- c(
"category", "category_type", "canonical_govid", "coarse_gap_years",
"n_result_rows", "coarse_recipes", "percode_recipes"
)
#' Separate the two flows the `*_delta_pp` figures net together.
#'
#' Per-code is NOT a widening of coarse (see this file's header): the two
#' checks pair different gap tests with different coverage tests, so moving
#' coarse -> percode both adds and removes firings. This splits the
#' disagreement into:
#' - `violations`: coarse fired, per-code did NOT -- signposting coverage
#' LOST. These are what a net delta hides. `holds` is FALSE whenever
#' this is non-empty, i.e. whenever coarse is not a subset of per-code.
#' - `additions`: per-code fired, coarse did NOT -- the expected gain.
#'
#' Deliberately returns the offending rows, not just counts, so the
#' Checkpoint R3 ruling can be made against named (category, government,
#' year) cases. Deliberately does NOT assert -- the violation set is really
#' non-empty on the staged corpus, and a hard assertion here would only
#' break the harness that is supposed to report it.
#' @noRd
.measure_subset_relation <- function(detail) {
required <- c("category", "canonical_govid", "fired_coarse", "fired_percode")
absent <- if (is.data.frame(detail)) setdiff(required, names(detail)) else required
if (!is.data.frame(detail) || length(absent) > 0L) {
stop("`detail` must be a data frame with columns ",
paste(required, collapse = ", "), " (missing: ",
paste(absent, collapse = ", "), ").", call. = FALSE)
}
fired_coarse <- as.logical(detail$fired_coarse)
fired_percode <- as.logical(detail$fired_percode)
if (anyNA(fired_coarse) || anyNA(fired_percode)) {
stop("`fired_coarse`/`fired_percode` must be non-NA logicals.", call. = FALSE)
}
keep <- intersect(.MEASURE_IDENTITY_COLS, names(detail))
viol_idx <- which(fired_coarse & !fired_percode)
add_idx <- which(fired_percode & !fired_coarse)
list(
holds = length(viol_idx) == 0L,
n_queries = nrow(detail),
n_coarse_fired = sum(fired_coarse),
n_percode_fired = sum(fired_percode),
n_both = sum(fired_coarse & fired_percode),
n_violations = length(viol_idx),
n_additions = length(add_idx),
violations = detail[viol_idx, keep, drop = FALSE],
additions = detail[add_idx, keep, drop = FALSE]
)
}
#' Render a data frame of disagreeing queries as indented report lines,
#' capped at `max_rows` with an explicit note about what was withheld (the
#' full set is always in the returned `$subset_relation`).
#' @noRd
.measure_fmt_rows <- function(df, max_rows = 50L) {
if (nrow(df) == 0L) return(" (none)")
shown <- utils::head(df, max_rows)
out <- paste0(" ", utils::capture.output(print(shown, row.names = FALSE)))
if (nrow(df) > max_rows) {
out <- c(out, sprintf(" ... %d more row(s) not shown; full set in $subset_relation.",
nrow(df) - max_rows))
}
out
}
#' Format `.measure_subset_relation()` as a prominent, clearly-labelled
#' report section. States plainly whether coarse is a subset of per-code
#' and, when it is not, exactly where it breaks.
#' @noRd
.measure_format_subset_report <- function(rel, max_rows = 50L) {
lines <- c(
"==== Subset relation: is COARSE a subset of PER-CODE? ====",
sprintf("Queries: %d | coarse fired: %d | per-code fired: %d | both: %d",
rel$n_queries, rel$n_coarse_fired, rel$n_percode_fired, rel$n_both)
)
if (rel$holds) {
lines <- c(lines, sprintf(paste(
"HOLDS: coarse IS a subset of per-code -- 0 of %d queries fire under",
"coarse but not per-code. On THIS battery the delta is a pure",
"addition of %d query/queries, with no coverage lost."
), rel$n_queries, rel$n_additions))
} else {
lines <- c(lines,
"*** VIOLATED: coarse is NOT a subset of per-code. ***",
sprintf(paste(
"%d of %d queries fire under COARSE but NOT under PER-CODE:",
"signposting coverage the move LOSES."
), rel$n_violations, rel$n_queries),
sprintf(paste(
"Every delta reported above is therefore a NET of %d addition(s)",
"MINUS %d loss(es), and understates both. Do not read it as",
"'per-code fires wherever coarse did, plus more'."
), rel$n_additions, rel$n_violations),
"",
paste(" COVERAGE LOST -- coarse fired, per-code silent.",
"`coarse_gap_years` is the requested year(s) in which the whole",
"category result was empty (coarse's own trigger evidence):"),
.measure_fmt_rows(rel$violations, max_rows)
)
}
c(lines, "",
sprintf(" COVERAGE ADDED -- per-code fired, coarse silent (%d query/queries):",
rel$n_additions),
.measure_fmt_rows(rel$additions, max_rows))
}
#' Measure the coarse-vs-per-code signposting suggestion rate over a
#' realistic query battery (every category x a pre/post-boundary_year span
#' x up to n_gov sampled governments).
#'
#' @param corpus_url Corpus to measure against. Defaults to
#' `Sys.getenv("USCOGDATA_URL")`; if that's unset, falls back to the
#' bundled v5 fixture (so the script runs out of the box). Re-run with
#' `USCOGDATA_URL` pointed at the staged/full corpus later.
#' @param n_gov Governments to sample (deterministically). "Up to" -- if
#' the corpus has fewer distinct governments in the measured years than
#' this, every one of them is used.
#' @param seed Sampling seed (fixed for reproducibility).
#' @param boundary_year,pre_years_n,post_years_n Define the desired query
#' span: `pre_years_n` years immediately before `boundary_year`, unioned
#' with `post_years_n` years starting at `boundary_year`. Falls back to
#' the corpus's widest actually-available span when this can't be filled
#' (see `.measure_year_span()`).
#' @param coarse_ref Git ref to pull the R2 coarse `.build_suggestions()`
#' from.
#' @param selfcov_ref Git ref to pull Task 19c's first, self-coverage-
#' allowed per-code `.build_suggestions()` from (amended after review).
#' @param verbose Print progress/notes as the battery runs.
#' @return Invisibly, a list with `corpus_url`, `years`, `span_note`,
#' `full_design`, `govids`, `seed`, `detail` (one row per query),
#' `by_category`, and `summary`.
#' @noRd
measure_signposting_rate <- function(corpus_url = Sys.getenv("USCOGDATA_URL", unset = NA),
n_gov = 20L,
seed = 19L,
boundary_year = 2012L,
pre_years_n = 3L,
post_years_n = 3L,
coarse_ref = "b0df1ec",
selfcov_ref = "da72bf3",
verbose = TRUE) {
pkgload::load_all(".", quiet = TRUE)
if (is.na(corpus_url) || !nzchar(corpus_url)) {
corpus_url <- paste0(
system.file("extdata/fixture_corpus", package = "uscogdata"), "/"
)
if (verbose) {
message("No USCOGDATA_URL set; defaulting to the bundled v5 fixture: ",
corpus_url)
}
}
old_url <- Sys.getenv("USCOGDATA_URL", unset = NA)
cog_close()
Sys.setenv(USCOGDATA_URL = corpus_url)
on.exit({
cog_close()
if (is.na(old_url)) Sys.unsetenv("USCOGDATA_URL") else Sys.setenv(USCOGDATA_URL = old_url)
}, add = TRUE)
con <- cog_open()
coarse_env <- .measure_load_git_impl(git_ref = coarse_ref)
selfcov_env <- .measure_load_git_impl(git_ref = selfcov_ref)
span <- .measure_year_span(con, boundary_year, pre_years_n, post_years_n)
years <- span$years
if (verbose) message(span$note)
govids <- .measure_sample_govids(con, years, n = n_gov, seed = seed)
if (verbose) {
message(sprintf("Sampled %d government(s) (seed = %d) from %d present in years %s.",
length(govids), seed,
length(DBI::dbGetQuery(con, sprintf(
"SELECT DISTINCT canonical_govid FROM long WHERE year IN (%s)",
paste(years, collapse = ",")))$canonical_govid),
paste(years, collapse = ", ")))
}
categories <- DBI::dbGetQuery(con,
"SELECT DISTINCT category, category_type FROM summary_categories
WHERE category IS NOT NULL ORDER BY category_type, category")
if (verbose) {
message(sprintf("Battery: %d categories x %d governments = %d queries.",
nrow(categories), length(govids),
nrow(categories) * length(govids)))
}
rows <- vector("list", nrow(categories) * length(govids))
k <- 0L
for (ci in seq_len(nrow(categories))) {
for (gv in govids) {
k <- k + 1L
rows[[k]] <- .measure_one_query(
con, coarse_env, selfcov_env,
category = categories$category[ci],
category_type = categories$category_type[ci],
govid = gv, years = years
)
}
}
detail <- do.call(rbind, rows)
# percode only ever fires where selfcov also fires (percode is a strict
# narrowing of selfcov: same gap detection, plus the self-coverage path
# removed) -- this is what makes the decomposition below exact rather
# than approximate. Checked, not assumed.
stopifnot(all(detail$fired_percode <= detail$fired_selfcov))
detail$fired_selfcov_only <- detail$fired_selfcov & !detail$fired_percode
# coarse vs percode is NOT a subset relation the way percode vs selfcov
# is (see header). Measured and REPORTED, never asserted: the violation
# set is genuinely non-empty on the staged corpus, and a stopifnot() here
# would break the harness whose whole job is to surface it.
subset_relation <- .measure_subset_relation(detail)
detail$coarse_only <- detail$fired_coarse & !detail$fired_percode
detail$percode_only <- detail$fired_percode & !detail$fired_coarse
by_category <- dplyr::summarise(
dplyr::group_by(detail, category, category_type),
n_queries = dplyr::n(),
coarse_rate = mean(fired_coarse),
selfcov_rate = mean(fired_selfcov),
percode_rate = mean(fired_percode),
original_delta_pp = (mean(fired_selfcov) - mean(fired_coarse)) * 100,
corrected_delta_pp = (mean(fired_percode) - mean(fired_coarse)) * 100,
selfcov_share_pp = mean(fired_selfcov_only) * 100,
# the two flows corrected_delta_pp nets together, per category
n_coarse_only = sum(coarse_only),
n_percode_only = sum(percode_only),
.groups = "drop"
)
by_category <- dplyr::arrange(by_category, dplyr::desc(corrected_delta_pp))
summary_overall <- data.frame(
n_queries = nrow(detail),
n_categories = nrow(categories),
n_governments = length(govids),
coarse_fired = sum(detail$fired_coarse),
selfcov_fired = sum(detail$fired_selfcov),
percode_fired = sum(detail$fired_percode),
coarse_rate = mean(detail$fired_coarse),
selfcov_rate = mean(detail$fired_selfcov),
percode_rate = mean(detail$fired_percode)
)
summary_overall$original_delta_pp <- (summary_overall$selfcov_rate - summary_overall$coarse_rate) * 100
summary_overall$corrected_delta_pp <- (summary_overall$percode_rate - summary_overall$coarse_rate) * 100
summary_overall$selfcov_share_pp <- mean(detail$fired_selfcov_only) * 100
summary_overall$relative_increase <- if (summary_overall$coarse_rate > 0) {
summary_overall$percode_rate / summary_overall$coarse_rate - 1
} else {
NA_real_
}
if (verbose) {
message(sprintf(
"Coarse rate: %.4f (%d/%d) | Self-cov-allowed rate: %.4f (%d/%d) | Corrected per-code rate: %.4f (%d/%d)",
summary_overall$coarse_rate, summary_overall$coarse_fired, summary_overall$n_queries,
summary_overall$selfcov_rate, summary_overall$selfcov_fired, summary_overall$n_queries,
summary_overall$percode_rate, summary_overall$percode_fired, summary_overall$n_queries
))
message(sprintf(
"Original delta (selfcov - coarse): %+.2f pp | Corrected delta (percode - coarse): %+.2f pp | Self-coverage share of original delta: %.2f pp (%d/%d queries fired ONLY via self-coverage)",
summary_overall$original_delta_pp, summary_overall$corrected_delta_pp,
summary_overall$selfcov_share_pp,
sum(detail$fired_selfcov_only), summary_overall$n_queries
))
message(if (subset_relation$holds) {
sprintf("Subset relation coarse <= percode HOLDS (0 coarse-only firings); delta is a pure addition of %d.",
subset_relation$n_additions)
} else {
sprintf("*** Subset relation coarse <= percode VIOLATED: %d coarse-only firing(s) LOST vs %d percode-only added. Deltas above are NETS. ***",
subset_relation$n_violations, subset_relation$n_additions)
})
}
invisible(list(
corpus_url = corpus_url,
years = years,
span_note = span$note,
full_design = span$full_design,
govids = govids,
seed = seed,
n_categories = nrow(categories),
detail = detail,
by_category = by_category,
summary = summary_overall,
subset_relation = subset_relation
))
}
if (identical(environment(), globalenv()) && sys.nframe() == 0L) {
res <- measure_signposting_rate()
cat("\n==== Query battery ====\n")
cat("Corpus:", res$corpus_url, "\n")
cat("Years:", paste(res$years, collapse = ", "), "\n")
cat("Full 3-year pre/post-2012 design achieved:", res$full_design, "\n")
cat(res$span_note, "\n")
cat("Governments sampled:", length(res$govids), "\n\n")
cat("==== Overall summary (coarse / self-coverage-allowed / corrected per-code) ====\n")
print(res$summary)
cat("\n==== By category (sorted by corrected delta, descending) ====\n")
cat("NOTE: corrected_delta_pp is a NET. n_coarse_only = firings LOST going\n")
cat("coarse -> percode; n_percode_only = firings ADDED. A category can be\n")
cat("negative (net coverage loss) even when the overall figure is positive.\n")
print(as.data.frame(res$by_category), row.names = FALSE)
cat("\n")
cat(paste(.measure_format_subset_report(res$subset_relation), collapse = "\n"), "\n")
}
-38
View File
@@ -26,41 +26,3 @@ test_that(".resolve_cache_dir falls back to R_user_dir", {
})
})
})
# ---------------------------------------------------------------------------
# Trailing-slash normalization (uscogdata #3 follow-up).
#
# EVERY consumer builds paths by concatenation: paste0(url, "manifest.json")
# (manifest.R), paste0(url, e$path) (mirror.R), and the parquet glob in
# views.R. mirror.R:104 even comments 'url ends in "/"' -- an assumption the
# package documents and relies on but never enforced.
#
# A URL missing its trailing slash therefore fails SILENTLY and confusingly:
# HTTPS -> ".../downloadmanifest.json" -> the host answers with an HTML 404
# page -> the jsonlite lexical error that issue #3 reported;
# local -> ".../corpusdata/long/**/*.parquet" -> DuckDB "No files found".
# Neither message points at the real cause. Normalize once, at resolution.
# ---------------------------------------------------------------------------
test_that(".resolve_url appends a missing trailing slash", {
withr::local_envvar(USCOGDATA_URL = "https://example.org/s/TOKEN/download")
expect_equal(.resolve_url(), "https://example.org/s/TOKEN/download/")
})
test_that(".resolve_url leaves an existing trailing slash alone", {
withr::local_envvar(USCOGDATA_URL = "https://example.org/s/TOKEN/download/")
expect_equal(.resolve_url(), "https://example.org/s/TOKEN/download/")
})
test_that(".resolve_url normalizes a local path without a trailing slash", {
withr::local_envvar(USCOGDATA_URL = "/tmp/corpus")
expect_equal(.resolve_url(), "/tmp/corpus/")
})
test_that(".resolve_url does not invent a slash for an empty setting", {
# An unset/empty URL must stay empty so the "not configured" guard in
# manifest.R still fires, rather than degrading into a bare "/" root.
withr::local_envvar(USCOGDATA_URL = "")
withr::local_options(uscogdata.url = "")
expect_equal(.resolve_url(), "")
})
+97 -1
View File
@@ -176,6 +176,16 @@ test_that("recipe = requires schema_version >= 5", {
})
# --- signposting -------------------------------------------------------
#
# Phase R3 / Task 19c: .build_suggestions() was narrowed from a whole-result
# gap check (R2: does the ENTIRE category result have zero rows in a
# requested year) to per-code gap detection (does a specific recipe
# component -- itself a member of the requested category -- have zero rows
# in a year the recipe's own generic join otherwise covers). See
# R/suggestions.R's header comment and docs/phase_r_harmonization_review.md
# § 0.3. The R2 test below ("...across the 2011->2012 gap") is unaffected
# by the refinement (it already passed under both the coarse and per-code
# rule). The next few pin cases the coarse rule specifically could NOT see.
test_that("signposting suggests corrections_combined across the 2011->2012 gap", {
skip_if_no_corpus()
@@ -193,10 +203,96 @@ test_that("signposting suggests corrections_combined across the 2011->2012 gap",
expect_equal(hit$available_years, c(1967L, 2023L))
})
test_that("no signposting when the result already has full year coverage", {
test_that("per-code gap does NOT fire when a code's only coverage is its own aggregate row (self-coverage is not \"other components\")", {
skip_if_no_corpus()
# Broward, FY2011 ONLY (isolating the 2011 half of the query above): E05,
# F05, and G05 each report SOLELY as a wide-era AGGREGATE row that year
# (216088, 1453, 270 respectively); E04/F04/G04 -- their modern-only
# siblings -- don't exist as codes at all before 2012, corpus-wide (zero
# rows for any government). Each component's own aggregate row would
# trivially satisfy a same-component "covered" check, but review-doc
# § 0.3's criterion is explicit that a gap must be covered by "OTHER
# components", not the gapped component's own aggregate form. With no
# OTHER component present for any of the three Corrections recipes in
# 2011, none of them should fire -- this is what the combined
# 2011-2012 test above actually relies on 2012 (E05 gapped, E04 -- a
# genuinely different component -- covers) to fire, not 2011.
r <- cog_spending("121011212191", years = 2011L, category = "Corrections")
prov <- attr(r, "provenance")
expect_length(prov$suggestions, 0L)
})
test_that("per-code gap fires even when a sibling code masks the whole-result check (Cleburne County, FY2012)", {
skip_if_no_corpus()
# Cleburne County, AL (canonical_govid 011029122489), FY2012: E04 ($854)
# and E05 ($1) both report ("operations" subtype), and G04 ($14,000,
# corrections_other_capital_combined's modern-only leg) also reports
# ("capital" subtype) -- so the WHOLE category result is non-empty for
# 2012 (2 rows) and the R2 whole-result check would never look further.
# But G05 -- G04's OWN recipe sibling, the 1967-2023 wide leg -- has
# ZERO rows at all that year: a genuine, per-code gap the recipe exists
# to bridge, invisible at the category-result grain because it's masked
# by G04's own data, let alone the unrelated E04/E05 pair.
r <- cog_spending("011029122489", years = 2012L, category = "Corrections")
expect_equal(nrow(r), 2L) # operations + capital rows: a non-empty result
prov <- attr(r, "provenance")
ids <- vapply(prov$suggestions, function(s) s$recipe_id, character(1))
expect_true("corrections_other_capital_combined" %in% ids)
hit <- prov$suggestions[[which(ids == "corrections_other_capital_combined")]]
expect_equal(hit$hint, "re-run with recipe = 'corrections_other_capital_combined'")
expect_equal(hit$available_years, c(1967L, 2023L))
# corrections_combined must NOT fire: E04 AND E05 both have real 2012
# data for this government, so neither of ITS OWN components is gapped.
expect_false("corrections_combined" %in% ids)
})
test_that("per-code gap does not fire when no recipe component has any data at all (ordinary reporting variance, not a format-boundary gap)", {
skip_if_no_corpus()
# Same government/year as above: F04 and F05 (corrections_capital_combined)
# are BOTH completely absent -- Cleburne simply never reported capital
# corrections spending under that code family in 2012, wide-era or
# modern. The recipe's own generic join (aggregate-inclusive, either
# component) has nothing to offer either, so this must stay silent --
# the per-government `covered` guard the header comment describes is
# unchanged and still does this filtering.
r <- cog_spending("011029122489", years = 2012L, category = "Corrections")
prov <- attr(r, "provenance")
ids <- vapply(prov$suggestions, function(s) s$recipe_id, character(1))
expect_false("corrections_capital_combined" %in% ids)
})
test_that("per-code gap fires for Broward 2019-2020 even though the category result looks complete", {
skip_if_no_corpus()
# Broward reports E04 + G04 (modern leaf codes) in BOTH 2019 and 2020 but
# never reports E05 or G05 (their own recipe siblings) in either year --
# a real per-code gap in two of the three Corrections recipes, invisible
# under the R2 coarse check because the category *result* is non-empty
# both years (this replaces the old R2-era "full year coverage" test,
# whose premise -- that a non-empty result implies nothing to signpost --
# is exactly what this refinement narrows; see data-raw/
# measure_signposting_rate.R for the measured rate change this causes).
# corrections_capital_combined correctly stays silent: Broward reports
# neither F04 nor F05 in 2019 or 2020, so that recipe's own join has
# nothing to offer either (ordinary non-reporting, not a format-boundary
# gap) -- the per-government `covered` guard still does its job here too.
r <- cog_spending("121011212191", years = 2019:2020, category = "Corrections")
prov <- attr(r, "provenance")
ids <- vapply(prov$suggestions, function(s) s$recipe_id, character(1))
expect_true("corrections_combined" %in% ids)
expect_true("corrections_other_capital_combined" %in% ids)
expect_false("corrections_capital_combined" %in% ids)
})
test_that("no signposting when every recipe component genuinely has data (true full per-code coverage)", {
skip_if_no_corpus()
# Maricopa County, AZ (canonical_govid 041013160815): all six Corrections
# codes (E04, E05, F04, F05, G04, G05) report real, nonzero, non-aggregate
# amounts in BOTH 2019 and 2020 -- genuinely nothing for any recipe to
# fill, even at the finer per-code grain this refinement now checks.
r <- cog_spending("041013160815", years = 2019:2020, category = "Corrections")
prov <- attr(r, "provenance")
expect_length(prov$suggestions, 0L)
})
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# tests/testthat/test-signposting-harness.R
#
# Pins the subset-relation REPORTING in data-raw/measure_signposting_rate.R.
#
# Phase R3 Task 19c narrowed signposting from a coarse whole-result gap
# check to per-code gap detection. Those two checks are partly DISJOINT,
# not nested: a query can fire under coarse and stay silent under per-code,
# so the harness's `*_delta_pp` figures are NETS that can hide a coverage
# loss. `.measure_subset_relation()` is what separates the two flows, and
# `.measure_format_subset_report()` is what puts the loss in front of a
# human. Both are load-bearing for the Checkpoint R3 ruling, so both are
# pinned here: if the violation detection is deleted, inverted, or quietly
# downgraded to a count with no identities, these tests fail.
#
# These tests do NOT assert that the violation set is empty -- it is
# genuinely non-empty, and asserting otherwise would be pinning a bug as a
# contract. They assert only that a real violation is DETECTED and NAMED.
# The harness lives in data-raw/, which is .Rbuildignore'd, so it is absent
# from an installed/checked tarball. Source it into an env parented on the
# namespace so it resolves the package internals it calls (.build_verb_sql,
# .build_suggestions) exactly as it does when run for real.
harness_env <- function() {
path <- testthat::test_path("..", "..", "data-raw", "measure_signposting_rate.R")
skip_if_not(file.exists(path),
"data-raw/ is .Rbuildignore'd; harness not present in this tree")
env <- new.env(parent = asNamespace("uscogdata"))
source(path, local = env)
env
}
# A detail frame in exactly the shape .measure_one_query() emits, covering
# all four quadrants of the coarse x percode cross-tab.
fake_detail <- function() {
data.frame(
category = c("Corrections", "Other Taxes", "Police", "Fire"),
category_type = c("expenditure", "revenue", "expenditure", "expenditure"),
canonical_govid = c("121011212191", "472155175824", "011029122489",
"041013160815"),
n_result_rows = c(0L, 1L, 2L, 6L),
coarse_gap_years = c("2011", "", "", ""),
fired_coarse = c(TRUE, FALSE, TRUE, FALSE),
fired_percode = c(FALSE, TRUE, TRUE, FALSE),
coarse_recipes = c("corrections_combined", "", "police_combined", ""),
percode_recipes = c("", "t29_license_wide", "police_combined", ""),
stringsAsFactors = FALSE
)
}
test_that(".measure_subset_relation() separates coverage LOST from coverage ADDED", {
e <- harness_env()
rel <- e$.measure_subset_relation(fake_detail())
# Row 1 (coarse fired, per-code silent) is the violation; row 2 is the
# addition; row 3 agrees; row 4 is silent.
expect_false(rel$holds)
expect_equal(rel$n_violations, 1L)
expect_equal(rel$n_additions, 1L)
expect_equal(rel$n_coarse_fired, 2L)
expect_equal(rel$n_percode_fired, 2L)
expect_equal(rel$n_both, 1L)
expect_equal(rel$n_queries, 4L)
# The violation must be NAMED down to (category, government, year), not
# merely counted -- that is what makes it inspectable at Checkpoint R3.
expect_equal(rel$violations$category, "Corrections")
expect_equal(rel$violations$canonical_govid, "121011212191")
expect_equal(rel$violations$coarse_gap_years, "2011")
expect_equal(rel$violations$coarse_recipes, "corrections_combined")
# Inversion guard: an implementation that swapped the two directions
# would report the addition as a violation and vice versa.
expect_false("Other Taxes" %in% rel$violations$category)
expect_equal(rel$additions$category, "Other Taxes")
expect_false("Corrections" %in% rel$additions$category)
# Agreeing and silent queries belong to neither set.
expect_false("Police" %in% c(rel$violations$category, rel$additions$category))
expect_false("Fire" %in% c(rel$violations$category, rel$additions$category))
})
test_that(".measure_subset_relation() reports holds = TRUE only when nothing fires coarse-only", {
e <- harness_env()
# Drop the violating row: coarse is now genuinely a subset of per-code.
clean <- fake_detail()[-1L, , drop = FALSE]
rel <- e$.measure_subset_relation(clean)
expect_true(rel$holds)
expect_equal(rel$n_violations, 0L)
expect_equal(nrow(rel$violations), 0L)
expect_equal(rel$n_additions, 1L)
})
test_that(".measure_subset_relation() validates its input rather than silently mis-reporting", {
e <- harness_env()
expect_error(e$.measure_subset_relation("not a data frame"), "must be a data frame")
expect_error(e$.measure_subset_relation(fake_detail()[, c("category", "canonical_govid")]),
"fired_coarse")
bad <- fake_detail()
bad$fired_percode[1] <- NA
expect_error(e$.measure_subset_relation(bad), "non-NA logicals")
})
test_that("the subset report NAMES a coarse-only firing as a violation", {
e <- harness_env()
txt <- paste(e$.measure_format_subset_report(e$.measure_subset_relation(fake_detail())),
collapse = "\n")
# Stated plainly as a violation, not buried.
expect_match(txt, "VIOLATED")
expect_match(txt, "COVERAGE LOST")
expect_no_match(txt, "HOLDS")
# ...and the offending query named, so a human can go look at it.
expect_match(txt, "Corrections")
expect_match(txt, "121011212191")
expect_match(txt, "2011")
# ...and the delta explicitly flagged as a net of both directions.
expect_match(txt, "NET")
})
test_that("the subset report says HOLDS when coarse really is a subset", {
e <- harness_env()
rel <- e$.measure_subset_relation(fake_detail()[-1L, , drop = FALSE])
txt <- paste(e$.measure_format_subset_report(rel), collapse = "\n")
expect_match(txt, "HOLDS")
expect_no_match(txt, "VIOLATED")
expect_no_match(txt, "COVERAGE LOST")
})
test_that("a REAL coarse-fires/per-code-silent query is measured and reported as a violation", {
skip_if_no_corpus()
# Broward County FY2011, Corrections: E05/F05/G05 report SOLELY as
# wide-era aggregate rows, which basis = "harmonized" excludes, so the
# whole category result is empty -- coarse's trigger. Their modern-only
# siblings E04/F04/G04 do not exist as codes at all before 2012, so no
# OTHER component can supply per-code's covering evidence and per-code
# is structurally unable to fire. This is the disjointness the harness
# exists to surface, measured end-to-end through the real git-loaded
# coarse arm and the live per-code arm (not a hand-built frame).
e <- harness_env()
con <- uscogdata:::cog_open()
row <- e$.measure_one_query(
con,
coarse_env = e$.measure_load_git_impl("b0df1ec"),
selfcov_env = e$.measure_load_git_impl("da72bf3"),
category = "Corrections", category_type = "expenditure",
govid = "121011212191", years = 2011L
)
expect_true(row$fired_coarse)
expect_false(row$fired_percode)
expect_equal(row$n_result_rows, 0L)
expect_equal(row$coarse_gap_years, "2011")
rel <- e$.measure_subset_relation(row)
expect_false(rel$holds)
expect_equal(rel$n_violations, 1L)
expect_equal(rel$violations$canonical_govid, "121011212191")
txt <- paste(e$.measure_format_subset_report(rel), collapse = "\n")
expect_match(txt, "VIOLATED")
expect_match(txt, "121011212191")
})