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unit tests
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@@ -441,94 +441,111 @@ test_that("test-sir.R", {
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# Tests must pass even when only 1 core is available; parallel = TRUE then
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# silently falls back to sequential, but results must still be identical.
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set.seed(42)
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n_par <- 200
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df_par <- data.frame(
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mo = "B_ESCHR_COLI",
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AMC = as.mic(sample(c("0.25", "0.5", "1", "2", "4", "8", "16", "32"), n_par, TRUE)),
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GEN = as.mic(sample(c("0.5", "1", "2", "4", "8", "16", "32", "64"), n_par, TRUE)),
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CIP = as.mic(sample(c("0.001", "0.002", "0.004", "0.008", "0.016", "0.032"), n_par, TRUE)),
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PEN = sample(c("S", "I", "R", NA_character_), n_par, TRUE),
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stringsAsFactors = FALSE
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)
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if (AMR:::pkg_is_available("future.apply")) {
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set.seed(42)
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n_par <- 200
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df_par <- data.frame(
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mo = "B_ESCHR_COLI",
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AMC = as.mic(sample(c("0.25", "0.5", "1", "2", "4", "8", "16", "32"), n_par, TRUE)),
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GEN = as.mic(sample(c("0.5", "1", "2", "4", "8", "16", "32", "64"), n_par, TRUE)),
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CIP = as.mic(sample(c("0.001", "0.002", "0.004", "0.008", "0.016", "0.032"), n_par, TRUE)),
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PEN = sample(c("S", "I", "R", NA_character_), n_par, TRUE),
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stringsAsFactors = FALSE
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)
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# clear any existing history before comparing
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sir_interpretation_history(clean = TRUE)
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sir_seq <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE))
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log_seq <- sir_interpretation_history(clean = TRUE)
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# clear any existing history before comparing
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sir_interpretation_history(clean = TRUE)
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sir_seq <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE))
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log_seq <- sir_interpretation_history(clean = TRUE)
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sir_par <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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log_par <- sir_interpretation_history(clean = TRUE)
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future::plan(future::multicore)
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n_max_workers <- future::nbrOfWorkers()
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# 1. parallel = TRUE gives identical SIR results to sequential
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expect_identical(sir_seq[["AMC"]], sir_par[["AMC"]])
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expect_identical(sir_seq[["GEN"]], sir_par[["GEN"]])
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expect_identical(sir_seq[["CIP"]], sir_par[["CIP"]])
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expect_identical(sir_seq[["PEN"]], sir_par[["PEN"]])
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sir_par <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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log_par <- sir_interpretation_history(clean = TRUE)
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# 2. same number of log rows as sequential
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expect_equal(nrow(log_seq), nrow(log_par))
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# 1. parallel = TRUE gives identical SIR results to sequential
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expect_identical(sir_seq[["AMC"]], sir_par[["AMC"]])
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expect_identical(sir_seq[["GEN"]], sir_par[["GEN"]])
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expect_identical(sir_seq[["CIP"]], sir_par[["CIP"]])
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expect_identical(sir_seq[["PEN"]], sir_par[["PEN"]])
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# 3. pre-existing log entries must not be duplicated
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# run sequential once to populate the history, then run parallel and
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# verify the new parallel run adds exactly as many rows as sequential
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sir_interpretation_history(clean = TRUE)
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suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE)) # populate history
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pre_n <- nrow(sir_interpretation_history())
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suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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post_n <- nrow(sir_interpretation_history())
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expect_equal(post_n - pre_n, nrow(log_seq)) # exactly one run's worth of new rows
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sir_interpretation_history(clean = TRUE)
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# 2. same number of log rows as sequential
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expect_equal(nrow(log_seq), nrow(log_par))
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# 4. two sequential runs and two parallel runs yield identical results
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sir_par2 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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expect_identical(sir_par[["AMC"]], sir_par2[["AMC"]])
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expect_identical(sir_par[["GEN"]], sir_par2[["GEN"]])
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# 3. pre-existing log entries must not be duplicated
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# run sequential once to populate the history, then run parallel and
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# verify the new parallel run adds exactly as many rows as sequential
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sir_interpretation_history(clean = TRUE)
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future::plan(future::sequential)
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suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE)) # populate history
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pre_n <- nrow(sir_interpretation_history())
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future::plan(future::multicore)
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suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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post_n <- nrow(sir_interpretation_history())
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expect_equal(post_n - pre_n, nrow(log_seq)) # exactly one run's worth of new rows
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sir_interpretation_history(clean = TRUE)
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# 5. max_cores = 1 gives same results as default sequential
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sir_mc1 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE, max_cores = 1L))
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expect_identical(sir_seq[["AMC"]], sir_mc1[["AMC"]])
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expect_identical(sir_seq[["GEN"]], sir_mc1[["GEN"]])
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# 4. two sequential runs and two parallel runs yield identical results
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sir_par2 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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expect_identical(sir_par[["AMC"]], sir_par2[["AMC"]])
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expect_identical(sir_par[["GEN"]], sir_par2[["GEN"]])
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# 6. max_cores = 2 and max_cores = 3 give same results as sequential
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sir_mc2 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE, max_cores = 2L))
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sir_mc3 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE, max_cores = 3L))
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expect_identical(sir_seq[["AMC"]], sir_mc2[["AMC"]])
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expect_identical(sir_seq[["GEN"]], sir_mc3[["GEN"]])
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# 5. max_cores = 1 gives same results as default sequential
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future::plan(future::multicore, workers = 1)
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sir_mc1 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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expect_identical(sir_seq[["AMC"]], sir_mc1[["AMC"]])
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expect_identical(sir_seq[["GEN"]], sir_mc1[["GEN"]])
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# 7. single-column data frame falls back silently to sequential
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df_single <- df_par[, c("mo", "AMC")]
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sir_single_seq <- suppressMessages(as.sir(df_single, col_mo = "mo", info = FALSE))
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sir_single_par <- suppressMessages(as.sir(df_single, col_mo = "mo", info = FALSE, parallel = TRUE))
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expect_identical(sir_single_seq[["AMC"]], sir_single_par[["AMC"]])
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# 6. max_cores = 2 and max_cores = 3 give same results as sequential
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if (n_max_workers >= 3) {
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future::plan(future::multicore, workers = 2)
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sir_mc2 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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future::plan(future::multicore, workers = 3)
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sir_mc3 <- suppressMessages(as.sir(df_par, col_mo = "mo", info = FALSE, parallel = TRUE))
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expect_identical(sir_seq[["AMC"]], sir_mc2[["AMC"]])
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expect_identical(sir_seq[["GEN"]], sir_mc3[["GEN"]])
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}
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# 9. row-batch mode (n_cols < n_cores): force row splitting via max_cores and
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# verify identical output to sequential for a dataset with 2 AB columns so
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# pieces_per_col = ceiling(max_cores / 2) >= 2 and row batching activates
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df_wide <- data.frame(
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mo = "B_ESCHR_COLI",
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AMC = as.mic(sample(c("1", "2", "4", "8"), n_par, TRUE)),
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GEN = as.mic(sample(c("1", "2", "4", "8"), n_par, TRUE)),
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stringsAsFactors = FALSE
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)
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sir_wide_seq <- suppressMessages(as.sir(df_wide, col_mo = "mo", info = FALSE))
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sir_wide_par <- suppressMessages(as.sir(df_wide,
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col_mo = "mo", info = FALSE,
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parallel = TRUE, max_cores = 8L
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))
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expect_identical(sir_wide_seq[["AMC"]], sir_wide_par[["AMC"]])
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expect_identical(sir_wide_seq[["GEN"]], sir_wide_par[["GEN"]])
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# 7. single-column data frame falls back silently to sequential
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df_single <- df_par[, c("mo", "AMC")]
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future::plan(future::sequential)
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sir_single_seq <- suppressMessages(as.sir(df_single, col_mo = "mo", info = FALSE))
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future::plan(future::multicore)
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sir_single_par <- suppressMessages(as.sir(df_single, col_mo = "mo", info = FALSE, parallel = TRUE))
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expect_identical(sir_single_seq[["AMC"]], sir_single_par[["AMC"]])
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# 8. info = TRUE with parallel does not produce per-column worker messages
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# (messages should only appear in the main process, not duplicated from workers)
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msgs <- capture.output(
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suppressWarnings(as.sir(df_par, col_mo = "mo", info = TRUE, parallel = TRUE)),
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type = "message"
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)
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# each AB column name should appear at most once in all messages combined
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for (ab_nm in c("AMC", "GEN", "CIP", "PEN")) {
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n_mentions <- sum(grepl(ab_nm, msgs, fixed = TRUE))
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expect_lte(n_mentions, 1L)
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# 8. row-batch mode (n_cols < n_cores): force row splitting via max_cores and
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# verify identical output to sequential for a dataset with 2 AB columns so
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# pieces_per_col = ceiling(max_cores / 2) >= 2 and row batching activates
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df_wide <- data.frame(
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mo = "B_ESCHR_COLI",
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AMC = as.mic(sample(c("1", "2", "4", "8"), n_par, TRUE)),
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GEN = as.mic(sample(c("1", "2", "4", "8"), n_par, TRUE)),
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stringsAsFactors = FALSE
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)
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future::plan(future::sequential)
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sir_wide_seq <- suppressMessages(as.sir(df_wide, col_mo = "mo", info = FALSE))
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future::plan(future::multicore)
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sir_wide_par <- suppressMessages(as.sir(df_wide,
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col_mo = "mo", info = FALSE,
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parallel = TRUE, max_cores = 8L
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))
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expect_identical(sir_wide_seq[["AMC"]], sir_wide_par[["AMC"]])
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expect_identical(sir_wide_seq[["GEN"]], sir_wide_par[["GEN"]])
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# 8. info = TRUE with parallel does not produce per-column worker messages
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# (messages should only appear in the main process, not duplicated from workers)
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msgs <- capture.output(
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suppressWarnings(as.sir(df_par, col_mo = "mo", info = TRUE, parallel = TRUE)),
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type = "message"
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)
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# each AB column name should appear at most once in all messages combined
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for (ab_nm in c("AMC", "GEN", "CIP", "PEN")) {
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n_mentions <- sum(grepl(ab_nm, msgs, fixed = TRUE))
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expect_lte(n_mentions, 1L)
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}
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future::plan(future::sequential)
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}
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})
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