Improve validation and coverage in calc_MinDose().

R-Lum · Feb 28, 2025 · 73e4241 · 73e4241
1 parent 9b86a24
commit 73e4241
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diff --git a/R/calc_MinDose.R b/R/calc_MinDose.R
@@ -384,6 +384,7 @@ calc_MinDose <- function(
   ## check if this function is called by calc_MaxDose()
   if ("invert" %in% names(extraArgs)) {
     invert <- extraArgs$invert
+    .validate_logical_scalar(invert)
     if (!log) {
       log <- TRUE # overwrite user choice as max dose model currently only supports the logged version
       cat(paste("\n[WARNING] The maximum dose model only supports the logged version.",
@@ -396,6 +397,7 @@ calc_MinDose <- function(
   ## console output
   if ("verbose" %in% names(extraArgs)) {
     verbose <- extraArgs$verbose
+    .validate_logical_scalar(verbose)
   } else {
     verbose <- TRUE
   }
@@ -404,39 +406,45 @@ calc_MinDose <- function(
   # first level bootstrap
   if ("bs.M" %in% names(extraArgs)) {
     M <- as.integer(extraArgs$bs.M)
+    .validate_positive_scalar(M, int = TRUE, name = "'bs.M'")
   } else {
     M <- 1000
   }
 
   # second level bootstrap
   if ("bs.N" %in% names(extraArgs)) {
     N <- as.integer(extraArgs$bs.N)
+    .validate_positive_scalar(N, int = TRUE, name= "'bs.N'")
   } else {
     N <- 3*M
   }
 
   # KDE bandwith
   if ("bs.h" %in% names(extraArgs)) {
     h <- extraArgs$bs.h
+    .validate_positive_scalar(h, name = "'bs.h'")
   } else {
     h <- (sd(data[ ,1])/sqrt(length(data[ ,1])))*2
   }
 
   # standard deviation of sigmab
   if ("sigmab.sd" %in% names(extraArgs)) {
     sigmab.sd <- extraArgs$sigmab.sd
+    .validate_positive_scalar(sigmab.sd)
   } else {
     sigmab.sd <- 0.04
   }
 
   if ("debug" %in% names(extraArgs)) {
     debug <- extraArgs$debug
+    .validate_logical_scalar(debug)
   } else {
     debug <- FALSE
   }
 
   if ("cores" %in% names(extraArgs)) {
     cores <- extraArgs$cores
+    .validate_positive_scalar(cores, int = TRUE)
   } else {
     cores <- parallel::detectCores()
     if (multicore)

diff --git a/tests/testthat/test_calc_MinDose.R b/tests/testthat/test_calc_MinDose.R
@@ -28,6 +28,30 @@ test_that("input validation", {
                "'par' should be a positive integer scalar")
   expect_error(calc_MinDose(ExampleData.DeValues$CA1, par = 2),
                "'par' can only be set to 3 or 4")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            invert = "error"),
+               "'invert' should be a single logical value")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            verbose = "error"),
+               "'verbose' should be a single logical value")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            debug = "error"),
+               "'debug' should be a single logical value")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            sigmab.sd = c(0.01, 0.02)),
+               "'sigmab.sd' should be a positive scalar")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            bootstrap = TRUE, bs.M = -1),
+               "'bs.M' should be a positive integer scalar")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            bootstrap = TRUE, bs.N = -1),
+               "'bs.N' should be a positive integer scalar")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            bootstrap = TRUE, bs.h = -1),
+               "'bs.h' should be a positive scalar")
+  expect_error(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                            cores = -1),
+               "'cores' should be a positive integer scalar")
 })
 
 test_that("check class and length of output", {
@@ -81,6 +105,11 @@ test_that("check class and length of output", {
                               par = 4, gamma.lower = 2, log.output = TRUE,
                               bootstrap = TRUE, bs.M = 10, bs.N = 5, bs.h=100),
                  "Gamma is larger than mu, consider running the model with new")
+  expect_output(calc_MinDose(ExampleData.DeValues$CA1 / 100, sigmab = 0.1,
+                             verbose = TRUE, log.output = TRUE, par = 4))
+  expect_silent(calc_MinDose(ExampleData.DeValues$CA1, sigmab = 0.1,
+                             verbose = FALSE, invert = TRUE,
+                             bootstrap = TRUE, bs.M = 10, bs.N = 5, bs.h = 10))
   })
 })