Auto-generate benchmarks with genthat, and run them

Benchmarks/genthat-CRAN/README.md

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+# Genthat testcases
+
+These benchmarks are automatically extracted from CRAN packages using genthat by the scripts in `Setup/genthat`.
+

Benchmarks/genthat-CRAN/generated/APCanalysis/EERpenalties/test-2.R

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+
+
+genthat_extracted_call <- function() {
+    APCanalysis:::EERpenalties(n = 8, k = 5, m = 5, eer = 0.25, reps = 15000)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/APCanalysis/FDRpenalties/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    APCanalysis:::FDRpenalties(n = 8, k = 5, m = 5, fdr = 0.05, reps = 12000)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/APCanalysis/IERpenalties/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    APCanalysis:::IERpenalties(n = 8, k = 5, m = 5, ier = 0.01, reps = 15000)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/APCanalysis/apc/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    PB12response <- APCanalysis::PB12response
+    PB12matrix <- APCanalysis::PB12matrix
+    APCanalysis:::apc(y = PB12response, x = PB12matrix, maxsize = 6, level = 0.2, method = 2, reps = 10000)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/APCanalysis/plot.apc/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    my.apc <- structure(list(Results = structure(list(Model = structure(c(7L, 3L, 1L, 6L, 2L, 4L, 5L), .Label = c("+ B", 
+        "+ D", "+ H", "+ I", "+ J", "+ K", "intercept"), class = "factor"), Size = 0:6, RSS = c(2851.2042, 1533.449, 997.8466, 
+        491.4964, 160.6414, 8.3445, 4.0604), APC = c(7.9555, 7.9483, 8.2006, 8.2455, 7.9602, 5.9386, 6.2103), Active = structure(c(2L, 
+        2L, 2L, 2L, 2L, 2L, 1L), .Label = c(" ", "*  "), class = "factor")), class = "data.frame", row.names = c("", "xH", 
+        "xB", "xK", "xD", "xI", "xJ")), Penalties = c(0, 0.613, 1.295, 2.048, 2.881, 3.817, 4.809), Level = 0.2, ErrorType = "EER", 
+        k = 11L, maxsize = 6, apc = structure(5.93860463652268, names = "xI"), Ests = structure(c(4.8275, 10.4791666666667, 
+            6.68083333333333, 6.49583333333334, -5.25083333333334, -3.5625, -0.597499999999997, 0.377500000000002, 0.312500000000001, 
+            0.2725, -0.135833333333332, -0.0741666666666676), names = c("(Intercept)", "xH", "xB", "xK", "xD", "xI", "xJ", 
+            "xC", "xF", "xG", "xA", "xE")), ActEffs = "B, D, H, I, K", NonActEffs = "A, C, E, F, G, J"), class = "apc")
+    APCanalysis:::plot.apc(x = my.apc)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/APCanalysis/summary.apc/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    my.apc <- structure(list(Results = structure(list(Model = structure(c(7L, 3L, 1L, 6L, 2L, 4L, 5L), .Label = c("+ B", 
+        "+ D", "+ H", "+ I", "+ J", "+ K", "intercept"), class = "factor"), Size = 0:6, RSS = c(2851.2042, 1533.449, 997.8466, 
+        491.4964, 160.6414, 8.3445, 4.0604), APC = c(7.9555, 7.9483, 8.2006, 8.2455, 7.9602, 5.9386, 6.2103), Active = structure(c(2L, 
+        2L, 2L, 2L, 2L, 2L, 1L), .Label = c(" ", "*  "), class = "factor")), class = "data.frame", row.names = c("", "xH", 
+        "xB", "xK", "xD", "xI", "xJ")), Penalties = c(0, 0.613, 1.295, 2.048, 2.881, 3.817, 4.809), Level = 0.2, ErrorType = "EER", 
+        k = 11L, maxsize = 6, apc = structure(5.93860463652268, names = "xI"), Ests = structure(c(4.8275, 10.4791666666667, 
+            6.68083333333333, 6.49583333333334, -5.25083333333334, -3.5625, -0.597499999999997, 0.377500000000002, 0.312500000000001, 
+            0.2725, -0.135833333333332, -0.0741666666666676), names = c("(Intercept)", "xH", "xB", "xK", "xD", "xI", "xJ", 
+            "xC", "xF", "xG", "xA", "xE")), ActEffs = "B, D, H, I, K", NonActEffs = "A, C, E, F, G, J"), class = "apc")
+    APCanalysis:::summary.apc(object = my.apc)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/BASIX/BASIX.combnapply/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    vec <- c(1, 3, 5, 7, 9, 10)
+    BASIX:::BASIX.combnapply(vec = vec)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/BASIX/BASIX.equal/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    b <- c(1, 9, 3, 4, 5, 6, 7, 8, 9, 10)
+    a <- 1:10
+    BASIX:::BASIX.equal(a = a, b = b)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/BASIX/BASIX.find.interval/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    vec <- c(1, 3, 5, 7, 9, 10)
+    to <- 8
+    from <- 5
+    BASIX:::BASIX.find.interval(vec = vec, from = from, to = to, start = 1)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/BASIX/BASIX.match/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    vec <- c(2, 3, 4, 10, 11)
+    elements <- c(1, 2, 10)
+    BASIX:::BASIX.match(elements = elements, vec = vec)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/BASIX/BASIX.table/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    mat <- structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(3L, 3L))
+    BASIX:::BASIX.table(matrix = mat)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/BASIX/BASIX.unique/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    mat <- structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(3L, 3L))
+    BASIX:::BASIX.unique(matrix = mat)
+}
+
+
+
+

Benchmarks/genthat-CRAN/generated/abc/plot.gfit/test-1.R

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+
+
+genthat_extracted_call <- function() {
+    res.gfit.bott <- structure(list(dist.sim = c(1.94792260837597, 2.48685540768078, 2.20072789722867, 1.90543387838366, 
+        2.02150262739967, 1.77656019685176, 1.91338570248844, 1.82429571532952, 2.64783696107181, 2.71029891434803), dist.obs = 1.99776885122106), 
+        class = "gfit")
+    abc:::plot.gfit(x = res.gfit.bott, main = "Histogram under H0")
+}
+
+
+
+