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fix parallel

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dr. M.S. (Matthijs) Berends
2026-04-30 00:41:17 +02:00
parent 20c9447096
commit 49e440d037
14 changed files with 155 additions and 174 deletions
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52
tests/testthat/test-sir.R
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@@ -408,13 +408,13 @@ test_that("test-sir.R", {
# Issue #278: re-running as.sir() on already-<sir> data must preserve columns
df_already_sir <- data.frame(
mo = "B_ESCHR_COLI",
mo = "B_ESCHR_COLI",
AMC = as.mic(c("1", "2", "4")),
GEN = sample(c("S", "I", "R"), 3, replace = TRUE),
stringsAsFactors = FALSE
)
first_pass <- suppressMessages(as.sir(df_already_sir, col_mo = "mo", info = FALSE))
second_pass <- suppressMessages(as.sir(first_pass, col_mo = "mo", info = FALSE))
first_pass <- suppressMessages(as.sir(df_already_sir, col_mo = "mo", info = FALSE))
second_pass <- suppressMessages(as.sir(first_pass, col_mo = "mo", info = FALSE))
expect_equal(ncol(first_pass), ncol(second_pass))
expect_true(is.sir(second_pass[["AMC"]]))
expect_true(is.sir(second_pass[["GEN"]]))
@@ -424,15 +424,15 @@ test_that("test-sir.R", {
# Issue #278: metadata columns whose names coincidentally match antibiotic
# codes (e.g. 'patient' -> OXY, 'ward' -> PRU) must not be processed
df_meta <- data.frame(
mo = "B_ESCHR_COLI",
mo = "B_ESCHR_COLI",
patient = paste0("Pt_", 1:20),
ward = rep(c("ICU", "Surgery", "Outpatient", "ED"), 5),
AMC = as.mic(rep(c("1", "2", "4", "8"), 5)),
ward = rep(c("ICU", "Surgery", "Outpatient", "ED"), 5),
AMC = as.mic(rep(c("1", "2", "4", "8"), 5)),
stringsAsFactors = FALSE
)
df_meta_sir <- suppressMessages(as.sir(df_meta, col_mo = "mo", info = FALSE))
expect_true("patient" %in% colnames(df_meta_sir))
expect_true("ward" %in% colnames(df_meta_sir))
expect_true("ward" %in% colnames(df_meta_sir))
expect_false(is.sir(df_meta_sir[["patient"]]))
expect_false(is.sir(df_meta_sir[["ward"]]))
expect_true(is.sir(df_meta_sir[["AMC"]]))
@@ -444,7 +444,7 @@ test_that("test-sir.R", {
set.seed(42)
n_par <- 200
df_par <- data.frame(
mo = "B_ESCHR_COLI",
mo = "B_ESCHR_COLI",
AMC = as.mic(sample(c("0.25", "0.5", "1", "2", "4", "8", "16", "32"), n_par, TRUE)),
GEN = as.mic(sample(c("0.5", "1", "2", "4", "8", "16", "32", "64"), n_par, TRUE)),
CIP = as.mic(sample(c("0.001", "0.002", "0.004", "0.008", "0.016", "0.032"), n_par, TRUE)),
@@ -506,14 +506,16 @@ test_that("test-sir.R", {
# verify identical output to sequential for a dataset with 2 AB columns so
# pieces_per_col = ceiling(max_cores / 2) >= 2 and row batching activates
df_wide <- data.frame(
mo = "B_ESCHR_COLI",
mo = "B_ESCHR_COLI",
AMC = as.mic(sample(c("1", "2", "4", "8"), n_par, TRUE)),
GEN = as.mic(sample(c("1", "2", "4", "8"), n_par, TRUE)),
stringsAsFactors = FALSE
)
sir_wide_seq <- suppressMessages(as.sir(df_wide, col_mo = "mo", info = FALSE))
sir_wide_par <- suppressMessages(as.sir(df_wide, col_mo = "mo", info = FALSE,
parallel = TRUE, max_cores = 8L))
sir_wide_par <- suppressMessages(as.sir(df_wide,
col_mo = "mo", info = FALSE,
parallel = TRUE, max_cores = 8L
))
expect_identical(sir_wide_seq[["AMC"]], sir_wide_par[["AMC"]])
expect_identical(sir_wide_seq[["GEN"]], sir_wide_par[["GEN"]])
@@ -536,9 +538,9 @@ test_that("custom reference_data: non-EUCAST/CLSI guideline produces R", {
# coerce_reference_data_columns() will coerce mo/ab to the right class.
my_bp <- clinical_breakpoints[clinical_breakpoints$method == "MIC" &
clinical_breakpoints$type == "human", ][1, ]
my_bp$guideline <- "MyLab 2025"
my_bp$mo <- "B_ACHRMB_XYLS" # plain character — coerced to <mo>
my_bp$ab <- "MEM" # plain character — coerced to <ab>
my_bp$guideline <- "MyLab 2025"
my_bp$mo <- "B_ACHRMB_XYLS" # plain character — coerced to <mo>
my_bp$ab <- "MEM" # plain character — coerced to <ab>
my_bp$breakpoint_S <- 8
my_bp$breakpoint_R <- 32
@@ -556,26 +558,30 @@ test_that("custom reference_data: non-EUCAST/CLSI guideline produces R", {
# guideline explicitly set: same result when it matches the data
expect_equal(as.character(suppressMessages(
as.sir(as.mic(64), mo = "B_ACHRMB_XYLS", ab = "MEM",
guideline = "MyLab 2025", reference_data = my_bp)
as.sir(as.mic(64),
mo = "B_ACHRMB_XYLS", ab = "MEM",
guideline = "MyLab 2025", reference_data = my_bp
)
)), "R")
})
test_that("custom reference_data: host = NA acts as host-agnostic fallback", {
my_bp <- clinical_breakpoints[clinical_breakpoints$method == "MIC" &
clinical_breakpoints$type == "human", ][1, ]
my_bp$guideline <- "MyLab 2025"
my_bp$mo <- "B_ACHRMB_XYLS"
my_bp$ab <- "MEM"
my_bp$type <- "animal"
my_bp$host <- NA # logical NA — coerced to character by coerce_reference_data_columns()
my_bp$guideline <- "MyLab 2025"
my_bp$mo <- "B_ACHRMB_XYLS"
my_bp$ab <- "MEM"
my_bp$type <- "animal"
my_bp$host <- NA # logical NA — coerced to character by coerce_reference_data_columns()
my_bp$breakpoint_S <- 8
my_bp$breakpoint_R <- 32
# NA host should match when no species-specific row exists
result <- suppressMessages(
as.sir(as.mic(64), mo = "B_ACHRMB_XYLS", ab = "MEM",
host = "dogs", breakpoint_type = "animal", reference_data = my_bp)
as.sir(as.mic(64),
mo = "B_ACHRMB_XYLS", ab = "MEM",
host = "dogs", breakpoint_type = "animal", reference_data = my_bp
)
)
expect_equal(as.character(result), "R")
})