Files
uscogdata/tests/testthat/test-spending.R
T
jared 4de915b557 feat: cog_recipes + recipe= + signposting suggestions
Adds cog_recipes() to list the curated harmonization_recipes catalog (24
recipes / schema_version >= 5), and a recipe= argument on cog_spending()/
cog_revenue() that runs a recipe's generic multi-code join instead of the
category view: SUM(amt * weight) across whichever component codes are
present for a (year, canonical_govid), scoped by gov_type_scope. The join
deliberately does not filter is_aggregate -- the wide era (<= 2011) exposes
these split families (corrections 04+05, IG *89/*47, U4- rents, etc.) ONLY
as aggregate rows, with leaf codes first appearing in 2012, so excluding
aggregates would zero out the wide-era half of every recipe. This is safe
by corpus construction: wide-era rows are aggregate-only, modern rows are
leaf-only, and every component is year-scoped, so there is no
double-counting. recipe= is mutually exclusive with category=; the result's
subtype column reads "recipe" and category reads the recipe's label.

Adds recipe-component-driven signposting: when a basis="harmonized" +
category query comes back with zero rows in a requested year, and a
harmonization recipe covering that category would actually produce rows
for this government in that year (via the same join .run_recipe() uses),
the recipe is surfaced in provenance$suggestions plus one
cli::cli_inform() message. This is deliberately keyed off recipe
components rather than harmonization_map's suggested_recipe_id column
(which is empty on every live row -- the wide era's split families are
NA-by-construction via aggregate exclusion, not an NA ruling to hang a
suggestion off of).

Also populates the previously-always-empty provenance$series_break_refs
(schema v5 only: series_breaks_pq rows whose fin_code is among the
observed codes and whose break_year falls in the requested span), and
extends cog_explain() with Basis/Harmonization/Recipe/Suggestions/Series
breaks sections.
2026-07-18 23:33:02 -04:00

318 lines
13 KiB
R

test_that("cog_spending returns expected shape for Broward Corrections 2020", {
skip_if_no_corpus()
r <- cog_spending("121011212191", years = 2020L, category = "Corrections")
expect_s3_class(r, "tbl_df")
expected_cols <- c("year", "canonical_govid", "gov_name", "spend_subtype",
"category", "amt_nominal", "codes_included",
"aggregate_fallback", "notes")
expect_true(all(expected_cols %in% names(r)))
expect_equal(unique(r$canonical_govid), "121011212191")
expect_equal(unique(r$year), 2020L)
expect_equal(unique(r$category), "Corrections")
expect_true(all(r$spend_subtype %in% c("operations", "capital")))
expect_true(all(r$amt_nominal > 0))
})
test_that("cog_spending vectorised years + categories", {
skip_if_no_corpus()
r <- cog_spending("121011212191", 2019:2020,
category = c("Corrections", "Police"))
expect_true(all(r$year %in% 2019:2020))
expect_true(all(r$category %in% c("Corrections", "Police")))
expect_gte(nrow(r), 4L)
})
test_that("cog_spending with per_capita adds per-capita nominal column", {
skip_if_no_corpus()
r <- cog_spending("121011212191", 2020L, "Corrections", per_capita = TRUE)
expect_true("amt_per_capita_nominal" %in% names(r))
expect_false("amt_real" %in% names(r))
expect_false("amt_per_capita_real" %in% names(r))
expect_true(all(is.finite(r$amt_per_capita_nominal)))
expect_true(all(r$amt_per_capita_nominal < r$amt_nominal))
})
test_that("cog_spending with adjust_to_year adds real column", {
skip_if_no_corpus()
r <- cog_spending("121011212191", 2019:2020, "Corrections",
adjust_to_year = 2022L)
expect_true("amt_real" %in% names(r))
r2019 <- dplyr::filter(r, year == 2019L)
expect_true(any(r2019$amt_nominal != r2019$amt_real))
})
test_that("cog_spending with per_capita + adjust_to_year adds all columns", {
skip_if_no_corpus()
r <- cog_spending("121011212191", 2020L, "Corrections",
per_capita = TRUE, adjust_to_year = 2022L)
expect_true(all(c("amt_nominal", "amt_real",
"amt_per_capita_nominal", "amt_per_capita_real") %in%
names(r)))
})
test_that("cog_spending for unknown govid returns empty tibble + informs", {
skip_if_no_corpus()
expect_message(
r <- cog_spending("XXXINVALID", 2020L, "Corrections"),
"not found|v0.1"
)
expect_s3_class(r, "tbl_df")
expect_equal(nrow(r), 0L)
expect_true("notes" %in% names(r))
prov <- attr(r, "provenance")
expect_false(is.null(prov))
expect_equal(prov$scope$govids_missing, "XXXINVALID")
expect_equal(length(prov$scope$govids_found), 0L)
})
test_that("cog_spending records found + missing govids in provenance", {
skip_if_no_corpus()
suppressMessages(
r <- cog_spending(c("121011212191", "XXXINVALID"), 2020L, "Corrections")
)
prov <- attr(r, "provenance")
expect_equal(sort(prov$scope$govids_found), "121011212191")
expect_equal(sort(prov$scope$govids_missing), "XXXINVALID")
})
test_that("cog_spending result has provenance attribute matching schema", {
skip_if_no_corpus()
r <- cog_spending("121011212191", 2020L, "Corrections")
prov <- attr(r, "provenance")
expect_type(prov, "list")
expect_equal(prov$verb, "cog_spending")
required <- c("verb", "target", "years", "scope", "manifest", "sql_query")
expect_true(all(required %in% names(prov)))
expect_equal(prov$years, 2020L)
expect_equal(prov$category, "Corrections")
expect_type(prov$sql_query, "character")
expect_true(grepl("spending_annotated", prov$sql_query))
expect_type(prov$codes_summed$observed, "character")
expect_true(all(c("E04") %in% prov$codes_summed$observed))
})
test_that("cog_spending rejects invalid inputs", {
expect_error(cog_spending(list(), 2020L), "character|data frame")
expect_error(cog_spending("121011212191", "2020"), "years")
})
test_that("cog_spending accepts a cog_gov_search result directly", {
skip_if_no_corpus()
picks <- cog_gov_search("^BROWARD COUNTY$", state = "FL", type = "county")
expect_gt(nrow(picks), 0L)
r <- cog_spending(picks, 2020L, "Corrections")
expect_equal(unique(r$canonical_govid), "121011212191")
})
test_that("cog_spending accepts a cog_find_peers result directly", {
skip_if_no_corpus()
peers <- cog_find_peers("121011212191", max_peers = 3L)
r <- cog_spending(peers, 2020L, "Police")
expect_setequal(unique(r$canonical_govid),
sort(peers$canonical_govid))
})
test_that("cog_spending rejects data.frame without canonical_govid column", {
bad <- tibble::tibble(foo = "bar")
expect_error(cog_spending(bad, 2020L), "canonical_govid")
})
test_that("cog_spending accepts a basket-mode cog_gov_search result", {
skip_if_no_corpus()
basket <- cog_gov_search(
name = c("BROWARD COUNTY", "SAN DIEGO COUNTY"),
state = c("FL", "CA")
)
expect_equal(nrow(basket), 2L)
spending <- cog_spending(basket, years = 2019:2020, category = "Police")
expect_s3_class(spending, "tbl_df")
expect_setequal(unique(spending$canonical_govid), basket$canonical_govid)
})
test_that("per_capita denominator is the per-year F-33 population", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", years = 2019:2020,
category = "Police", per_capita = TRUE)
r_ops <- r[r$spend_subtype == "operations", ]
# Implied denominator from amt_nominal / amt_per_capita_nominal
implied_pop <- r_ops$amt_nominal / r_ops$amt_per_capita_nominal
names(implied_pop) <- r_ops$year
# Use absolute tolerance: within 1 person of per-year F-33 values.
# Hardcoded values are Broward County's per-year Census F-33 population
# from the bundled fixture (regenerated 2026-07-11 against cog_pipeline
# publish tree, pipeline_commit 1a00925, Phase P schema_version 4).
# 1,940,907 is the static ACS 2018-2022 5-year value the legacy
# implementation would use; we assert it is NOT what we get.
expect_true(abs(implied_pop[["2019"]] - 1935878) < 1)
expect_true(abs(implied_pop[["2020"]] - 1952778) < 1)
expect_false(all(abs(implied_pop - 1940907) < 1))
})
})
test_that("pop_source = 'census_f33' does not produce unavailable-pop note", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", years = 2019L,
category = "Police", per_capita = TRUE)
expect_true(all(r$pop_source == "census_f33"))
expect_true(all(is.na(r$notes) | r$notes == "" |
!grepl("No population denominator", r$notes)))
})
})
test_that("aggregate fallback + unavailable pop produce concatenated notes", {
# Unit-level test of .notes_column with a synthetic data frame so we don't
# depend on having a type-4/5 gov in the fixture.
result <- tibble::tibble(
aggregate_fallback = c(FALSE, TRUE, TRUE),
pop_source = c("census_f33", "census_f33", "unavailable")
)
notes <- uscogdata:::.notes_column(result)
expect_equal(notes[1], "")
expect_equal(notes[2], "Aggregate fallback applied; see cog_explain()")
expect_equal(notes[3],
"Aggregate fallback applied; see cog_explain(); No population denominator available for this gov type")
})
test_that("provenance records per-year denominator metadata", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", years = 2019:2020,
category = "Police", per_capita = TRUE)
pc <- attr(r, "provenance")$transformations$per_capita
expect_true(pc$applied)
expect_match(pc$denominator_source, "Census F-33", fixed = FALSE)
expect_match(pc$denominator_source, "per-year", fixed = TRUE)
expect_equal(pc$pop_source_counts$census_f33, nrow(r))
expect_equal(pc$pop_source_counts$unavailable, 0L)
expect_equal(length(pc$popyear_range), 2L)
})
})
# --- basis = "harmonized" / "raw" (Phase R2, schema v5) --------------------
test_that("basis = 'raw' reproduces the pre-harmonization Broward Police totals", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", years = 2019:2020, category = "Police",
basis = "raw")
# Regression pin captured against the schema v5 fixture (2026-07-18,
# pipeline_commit ece9b32) before basis = "harmonized" existed as a
# concept; these are the same totals the pre-Phase-R2 default query
# returned (spending_annotated is untouched by the harmonized views).
ops <- r$amt_nominal[r$year == 2019L & r$spend_subtype == "operations"]
cap <- r$amt_nominal[r$year == 2020L & r$spend_subtype == "capital"]
expect_equal(ops, 483560000)
expect_equal(cap, 26693000)
expect_equal(attr(r, "provenance")$basis, "raw")
})
})
test_that("basis = 'harmonized' (default) matches 'raw' when no harmonization rule applies", {
skip_if_no_corpus()
with_fixture_corpus({
# Every `method = "collapse"` mapping in the curated harmonization_map
# ends by FY2004 for codes inside the spending/revenue flow-type
# prefixes (E/F/G/K, T/A/U/B/C/D); the one collapse extending to FY2011
# (L38/M38 -> L36/M36) is intergovernmental-transfer (L/M prefix) codes
# that were never part of spending_long/revenue_long to begin with. So
# for the fixture's 2011-2020 window, basis = "harmonized" is a
# data-verified no-op vs "raw" for in-scope codes -- this is the
# positive-control counterpart to the synthetic REPLACE-mechanism test
# in test-views.R, which proves the fold itself works when data exists.
r_raw <- cog_spending("121011212191", c(2011L, 2012L, 2019L, 2020L),
"Police", basis = "raw")
r_harm <- cog_spending("121011212191", c(2011L, 2012L, 2019L, 2020L),
"Police", basis = "harmonized")
expect_equal(attr(r_harm, "provenance")$basis, "harmonized")
expect_equal(
r_harm$amt_nominal[order(r_harm$year, r_harm$spend_subtype)],
r_raw$amt_nominal[order(r_raw$year, r_raw$spend_subtype)]
)
})
})
test_that("basis defaults to 'harmonized' when not passed", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", 2020L, "Police")
expect_equal(attr(r, "provenance")$basis, "harmonized")
})
})
test_that("provenance carries basis + harmonization block with na_rows_excluded", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", 2011:2012, "Corrections")
prov <- attr(r, "provenance")
expect_equal(prov$basis, "harmonized")
expect_true(prov$harmonization$applied)
expect_true(prov$harmonization$na_rows_excluded >= 0L)
expect_true(prov$harmonization$na_amount_excluded >= 0)
# Data-verified for this fixture: none of the discontinued_na rulings
# (S74, Z61, X04, X06, the debt-detail family, L24) fall inside the
# E/F/G/K spending prefixes, so the exclusion count is exactly zero for
# every year in the bundled window -- see
# docs/phase_r_harmonization_review.md § 1.3/1.4.
expect_equal(prov$harmonization$na_rows_excluded, 0L)
expect_equal(prov$harmonization$na_amount_excluded, 0)
})
})
test_that("basis = 'raw' never populates the harmonization exclusion block", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", 2020L, "Corrections", basis = "raw")
h <- attr(r, "provenance")$harmonization
expect_false(h$applied)
expect_equal(h$na_rows_excluded, 0L)
})
})
test_that("v4 corpus: basis silently resolves to raw (default) with a provenance note", {
skip_if_no_corpus()
with_doctored_schema_version(4L, {
r <- cog_spending("121011212191", 2019L, "Police")
prov <- attr(r, "provenance")
expect_equal(prov$basis, "raw")
expect_match(prov$basis_note, "raw", fixed = TRUE)
expect_match(prov$basis_note, "schema_version", fixed = TRUE)
expect_false(prov$harmonization$applied)
})
})
test_that("v4 corpus: explicit basis = 'harmonized' aborts", {
skip_if_no_corpus()
with_doctored_schema_version(4L, {
expect_error(
cog_spending("121011212191", 2019L, "Police", basis = "harmonized"),
class = "uscogdata_basis_unsupported"
)
})
})
test_that("provenance$series_break_refs is a populated-when-applicable character vector", {
skip_if_no_corpus()
with_fixture_corpus({
r <- cog_spending("121011212191", 2020L, "Corrections")
refs <- attr(r, "provenance")$series_break_refs
expect_type(refs, "character")
# No catalogued series_breaks_pq row falls inside this fixture's
# 2011/2012/2019/2020 window for the codes this query touches (E04/G04)
# -- data-verified; the mechanism itself is what's under test here, via
# a query-shaped unit test in test-views.R since the fixture has no
# positive case to pin against.
expect_equal(refs, character(0))
})
})
test_that("v4 corpus: explicit basis = 'raw' still works", {
skip_if_no_corpus()
with_doctored_schema_version(4L, {
r <- cog_spending("121011212191", 2019L, "Police", basis = "raw")
expect_equal(attr(r, "provenance")$basis, "raw")
expect_gt(nrow(r), 0L)
})
})