jared
9233c3d18e
Six skipped tests, one per issue opened from the Madison walkthrough audit (docs/walkthroughs/FINDINGS.md in cog_explorer). Each asserts the desired behaviour, so it fails today and goes green when the fix lands; each is guarded by a single skip() naming its issue and finding IDs, so the suite stays green and activating a test is a one-line deletion. test-expenditure-concepts.R #11 F-012, F-017, F-018 test-revenue-concept-insurance-trust.R #12 F-014 test-coverage-disclosure.R #13 F-020, F-023 test-peer-summary-scope.R #14 F-021 test-amount-units-documented.R #15 F-004 test-gov-search-literal-match.R #16 F-025 helper-walkthrough-raw.R reads the corpus's long parquet partitions directly, bypassing uscogdata's SQL views. Every expected amount comes from there rather than from the verb under test - verifying an absence through the filter that creates it proves nothing, which was the most common defect in the audit itself. Verified: with the skips removed all six fail (or error) against the bundled fixture; with them in place the full suite is 576 pass / 0 fail / 6 skip.
93 lines
4.7 KiB
R
93 lines
4.7 KiB
R
# Madison walkthrough audit -- findings F-020 and F-023. Tracked as uscogdata#13.
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# See docs/walkthroughs/FINDINGS.md in cog_explorer.
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#
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# The owner's settled design (2026-07-28): a `coverage` argument on
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# cog_geographic_rollup(), cog_find_peers()/cog_peer_compare() and their
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# cog-api equivalents --
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# "all" every unit that reported that year (today's behaviour, DEFAULT)
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# "census" census years only (years ending 2 or 7)
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# "consistent" only units reporting in every requested year (balanced panel)
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# -- PLUS always-on coverage metadata on every result regardless of mode:
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# n_units_reporting, n_units_expected, is_census_year.
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#
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# Motivating principle: using these verbs correctly must not require the user to
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# know that the Census of Governments is a complete census only in years ending
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# in 2 and 7.
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#
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# The helper below accepts that metadata either as columns on the returned
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# tibble or as a per-year table in provenance$coverage -- the design fixes the
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# three field names and that they reach the caller, not the container.
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wt_coverage <- function(x) {
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prov <- attr(x, "provenance")
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cov <- prov$coverage
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if (is.null(cov)) {
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needed <- c("year", "n_units_reporting", "n_units_expected", "is_census_year")
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expect_true(all(needed %in% names(x)))
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cov <- unique(x[, needed])
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}
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cov[order(cov$year), ]
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}
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test_that("multi-government aggregates disclose reporting coverage on every result", {
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testthat::skip("Blocked on uscogdata#13 (findings F-020, F-023)")
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# -- F-020: geographic rollups -------------------------------------------
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# Wisconsin's city/village universe is 608 governments. On the bundled
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# fixture, FY2012 (a census year) has 597 of them reporting while FY2019 and
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# FY2020 (sample years) have 112 and 114 -- an 18%-98% swing that today's
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# return value says nothing about. Counts cross-checked against the raw
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# corpus, not through cog_geographic_rollup(), which is under test.
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wi <- cog_gov_search(name = NULL, state = "WI", type = "city")
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expect_equal(nrow(wi), 608L)
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roll <- cog_geographic_rollup(govids = list(city = wi$canonical_govid),
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category = NULL, years = c(2011L, 2012L, 2019L, 2020L))
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cov <- wt_coverage(roll)
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expect_equal(cov$n_units_expected, rep(608L, 4L))
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expect_equal(cov$n_units_reporting, c(152L, 597L, 112L, 114L))
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expect_equal(cov$is_census_year, c(FALSE, TRUE, FALSE, FALSE))
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raw_2012 <- wt_raw_query(paste0(
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"SELECT COUNT(DISTINCT canonical_govid) n FROM read_parquet('", wt_corpus_glob(), "') ",
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"WHERE type = 2 AND fips_state = 55 AND year = 2012 ",
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"AND LEFT(item_code, 1) IN ('E','F','G') AND NOT is_aggregate"))
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expect_equal(cov$n_units_reporting[cov$year == 2012], as.integer(raw_2012$n[[1]]))
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# -- F-023: peer cohorts --------------------------------------------------
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# CHILTON CITY, WI (ACS population 4,017): a 15-peer cohort fixed at FY2012
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# reports 15 of 15 in FY2012 and only 3 of 15 in FY2019 and FY2020. Nothing
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# in cog_peer_compare()'s return distinguishes those years today.
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chilton <- "552015177095"
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peers <- cog_find_peers(chilton, year = 2012L, max_peers = 15L)
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expect_equal(nrow(peers), 15L)
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cmp <- cog_peer_compare(target_govid = chilton, peers = peers, category = NULL,
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years = c(2012L, 2019L, 2020L), per_capita = TRUE)
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cov_peers <- wt_coverage(cmp)
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expect_equal(cov_peers$n_units_expected, rep(15L, 3L))
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expect_equal(cov_peers$n_units_reporting, c(15L, 3L, 3L))
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expect_equal(cov_peers$is_census_year, c(TRUE, FALSE, FALSE))
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# -- the three coverage modes --------------------------------------------
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expect_equal(attr(cog_peer_compare(target_govid = chilton, peers = peers,
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category = NULL, years = c(2012L, 2019L, 2020L),
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per_capita = TRUE),
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"provenance")$coverage_mode, "all") # unchanged default
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consistent <- cog_peer_compare(target_govid = chilton, peers = peers,
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category = NULL, years = c(2012L, 2019L, 2020L),
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per_capita = TRUE, coverage = "consistent")
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n_by_year <- tapply(consistent$canonical_govid[consistent$role == "peer"],
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consistent$year[consistent$role == "peer"],
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function(g) length(unique(g)))
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expect_equal(unname(as.integer(n_by_year)), c(3L, 3L, 3L)) # balanced panel
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census_only <- cog_geographic_rollup(govids = list(city = wi$canonical_govid),
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category = NULL,
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years = c(2011L, 2012L, 2019L, 2020L),
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coverage = "census")
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expect_equal(sort(unique(census_only$year)), 2012)
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})
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