jared
cc4d21ec82
cog_find_peers selects peers from canonical_fips_xwalk by same-type,
same-state, and population-range (ratio or absolute) criteria,
ordered by |log(pop_ratio)| ascending.
cog_peer_compare accepts the find_peers result (or a plain character
vector of govids), pulls spending for target + peers via cog_spending,
and appends summary rows (summary_p25/p50/p75) so the whole result
can be faceted by `role` in a single ggplot call. Summary rows honor
per_capita + adjust_to_year by picking the right value column.
target_rank reports the target's rank among target+peers at max(years).
Provenance is rewritten with verb = cog_peer_compare and peer_count.
Also: globalVariables('.data') in zzz.R to silence R CMD check on
tidy-eval pronouns.
Tests: 21 new / 120 total pass. devtools::check() 0E/0W/2N.
91 lines
3.3 KiB
R
91 lines
3.3 KiB
R
test_that("cog_find_peers returns same-type peers in the default pop band", {
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skip_if_no_corpus()
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peers <- cog_find_peers("101006006") # Broward County
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expect_s3_class(peers, "tbl_df")
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expected_cols <- c("canonical_govid", "gov_name", "fips_state",
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"population_acs", "pop_ratio", "rank")
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expect_true(all(expected_cols %in% names(peers)))
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expect_true(all(peers$pop_ratio >= 0.7 & peers$pop_ratio <= 1.3))
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expect_false("101006006" %in% peers$canonical_govid)
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expect_equal(peers$rank, seq_len(nrow(peers)))
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})
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test_that("cog_find_peers respects same_state restriction", {
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skip_if_no_corpus()
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peers <- cog_find_peers("101006006", same_state = TRUE,
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pop_range = c(0.1, 10))
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expect_true(all(peers$fips_state == "12"))
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})
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test_that("cog_find_peers absolute pop range works", {
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skip_if_no_corpus()
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peers <- cog_find_peers("101006006",
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pop_range = c(1.5e6, 2.5e6),
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is_ratio = FALSE, max_peers = 20L)
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expect_true(all(peers$population_acs >= 1.5e6 &
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peers$population_acs <= 2.5e6))
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})
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test_that("cog_find_peers errors cleanly on unknown govid", {
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skip_if_no_corpus()
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expect_error(cog_find_peers("XXXINVALID"), "not found")
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})
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test_that("cog_peer_compare accepts a cog_find_peers result directly", {
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skip_if_no_corpus()
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peers <- cog_find_peers("101006006", max_peers = 4L)
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r <- cog_peer_compare("101006006", peers, "Police", years = 2020L)
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expect_s3_class(r, "tbl_df")
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expect_true("role" %in% names(r))
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expect_setequal(
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unique(r$role),
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c("target", "peer", "summary_p25", "summary_p50", "summary_p75")
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)
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expect_equal(sum(r$role == "target" & r$spend_subtype == "operations"), 1L)
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})
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test_that("cog_peer_compare accepts a character vector of govids", {
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skip_if_no_corpus()
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r <- cog_peer_compare(
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"101006006",
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peers = c("441015015", "441220220"), # Bexar, Tarrant
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category = "Police", years = 2020L
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)
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expect_true("peer" %in% r$role)
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expect_equal(sum(r$role == "peer" & r$spend_subtype == "operations"), 2L)
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})
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test_that("cog_peer_compare summary rows use real per-capita when requested", {
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skip_if_no_corpus()
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r <- cog_peer_compare(
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"101006006",
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peers = c("441015015", "441220220", "231082082"),
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category = "Police", years = 2019:2020,
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per_capita = TRUE, adjust_to_year = 2022L
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)
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summaries <- dplyr::filter(r, grepl("^summary_", role))
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expect_true(all(is.finite(summaries$amt_per_capita_real)))
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# summary rows have NA canonical_govid and named gov_name
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expect_true(all(is.na(summaries$canonical_govid)))
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expect_true(all(grepl("Peer", summaries$gov_name)))
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})
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test_that("cog_peer_compare provenance reports the outer verb + peer count", {
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skip_if_no_corpus()
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r <- cog_peer_compare("101006006",
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peers = c("441015015", "441220220"),
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category = "Police", years = 2020L)
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prov <- attr(r, "provenance")
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expect_equal(prov$verb, "cog_peer_compare")
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expect_equal(prov$peer_count, 2L)
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})
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test_that("cog_peer_compare handles zero peers gracefully", {
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skip_if_no_corpus()
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r <- cog_peer_compare("101006006",
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peers = character(0),
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category = "Police", years = 2020L)
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expect_true(all(r$role == "target"))
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expect_equal(sum(grepl("^summary_", r$role)), 0L)
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})
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