Add input checking and improve test coverage

CITATION.cff

@@ -9,7 +9,7 @@ type: software
 license: MIT
 title: 'bpmodels: Simulating and Analysing Transmission Chain Statistics using Branching
   Process Models'
-version: 0.3.0
+version: 0.3.1
 abstract: Provides methods to simulate and analyse the size and length of branching
   processes with an arbitrary offspring distribution. These can be used, for example,
   to analyse the distribution of chain sizes or length of infectious disease outbreaks,
@@ -249,3 +249,15 @@ references:
     given-names: Saralees
     email: [email protected]
   year: '2023'
+- type: software
+  title: checkmate
+  abstract: 'checkmate: Fast and Versatile Argument Checks'
+  notes: Imports
+  url: https://mllg.github.io/checkmate/
+  repository: https://CRAN.R-project.org/package=checkmate
+  authors:
+  - family-names: Lang
+    given-names: Michel
+    email: [email protected]
+    orcid: https://orcid.org/0000-0001-9754-0393
+  year: '2023'

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: bpmodels
 Title: Simulating and Analysing Transmission Chain Statistics using Branching Process
     Models
-Version: 0.3.0
+Version: 0.3.1
 Authors@R: c(
     person("James M.", "Azam", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "https://orcid.org/0000-0001-5782-7330")),
@@ -48,3 +48,5 @@ LazyData: true
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3
 Language: en-GB
+Imports: 
+    checkmate

NEWS.md

@@ -1,3 +1,10 @@
+# bpmodels 0.3.1
+
+## Unit tests and input validation
+
+* The following internal functions now have input validation: `rborel()`, `dborel()`, `complementary_logprob()`, and `rnbinom_mean_disp()`.
+* Code coverage has been improved with more tests on the following functions: `rborel()`, `dborel()`, `chain_sim()`, `rnbinom_mean_disp()`, `complementary_logprob()`, `rgen_length()`, and `rbinom_size()`.
+
 # bpmodels 0.3.0
 
 ## Website

R/borel.r

@@ -1,12 +1,17 @@
 ##' Density of the Borel distribution
 ##'
-##' @param x vector of integers.
-##' @param mu mu parameter.
+##' @param x vector of quantiles; integer.
+##' @param mu mu parameter (the poisson mean); non-negative.
 ##' @param log logical; if TRUE, probabilities p are given as log(p).
 ##' @return probability mass.
 ##' @author Sebastian Funk
 dborel <- function(x, mu, log = FALSE) {
-  if (x < 1) stop("'x' must be greater than 0")
+  checkmate::assert_numeric(
+    x, lower = 1, upper = Inf
+  )
+  checkmate::assert_number(
+    mu, lower = 0, finite = TRUE, na.ok = FALSE
+  )
   ld <- -mu * x + (x - 1) * log(mu * x) - lgamma(x + 1)
   if (!log) ld <- exp(ld)
   return(ld)
@@ -16,11 +21,17 @@ dborel <- function(x, mu, log = FALSE) {
 ##'
 ##' Random numbers are generated by simulating from a Poisson branching process
 ##' @param n number of random variates to generate.
-##' @param mu mu parameter.
+##' @param mu mu parameter (the Poisson mean).
 ##' @param infinite any number to treat as infinite; simulations will be stopped
 ##'     if this number is reached
 ##' @return vector of random numbers
 ##' @author Sebastian Funk
 rborel <- function(n, mu, infinite = Inf) {
+  checkmate::assert_number(
+    n, lower = 1, finite = TRUE, na.ok = FALSE
+  )
+  checkmate::assert_number(
+    mu, lower = 0, finite = TRUE, na.ok = FALSE
+  )
   chain_sim(n, "pois", "size", infinite = infinite, lambda = mu)
 }

R/utils.r

@@ -6,6 +6,9 @@
 #' @author Sebastian Funk
 #' @keywords internal
 complementary_logprob <- function(x) {
+  checkmate::assert_numeric(
+    x, lower = -Inf, upper = 0
+  )
   tryCatch(log1p(-sum(exp(x))), error = function(e) -Inf)
 }
 
@@ -43,14 +46,23 @@ rgen_length <- function(n, x, prob) {
 #' Negative binomial random numbers parametrized
 #' in terms of mean and dispersion coefficient
 #' @param n number of samples to draw
-#' @param mn mean of distribution
-#' @param disp dispersion coefficient (var/mean)
+#' @param mn mean of distribution; Must be > 0.
+#' @param disp dispersion coefficient (var/mean); Must be > 1.
 #' @return vector containing the random numbers
 #' @author Flavio Finger
 #' @export
 #' @examples
 #' rnbinom_mean_disp(n = 5, mn = 4, disp = 2)
 rnbinom_mean_disp <- function(n, mn, disp) {
+  checkmate::assert_number(
+    n, lower = 1, finite = TRUE, na.ok = FALSE
+  )
+  checkmate::assert_number(
+    disp, lower = 1, finite = TRUE, na.ok = FALSE
+  )
+  checkmate::assert_number(
+    mn, lower = 1E-100, finite = TRUE, na.ok = FALSE
+  )
   size <- mn / (disp - 1)
   stats::rnbinom(n, size = size, mu = mn)
 }

tests/testthat/test-borel.r

@@ -0,0 +1,28 @@
+test_that("We can calculate probabilities and sample", {
+  expect_gt(dborel(1, 0.5), 0)
+  expect_identical(dborel(1, 0.5, log = TRUE), -0.5)
+  expect_length(rborel(2, 0.9), 2)
+})
+
+test_that("Errors are thrown", {
+  expect_error(
+    dborel(x = 0, mu = 0.5),
+    "is not >= 1"
+  )
+  expect_error(
+    dborel(x = 1, mu = -0.5),
+    "is not >= 0"
+  )
+  expect_error(
+    dborel(x = 1, mu = Inf),
+    "Must be finite"
+  )
+  expect_error(
+    rborel(n = 0, mu = -0.5),
+    "is not >= 1"
+  )
+  expect_error(
+    rborel(n = 0, mu = Inf),
+    "is not >= 1"
+  )
+})

tests/testthat/test-utils.R

@@ -0,0 +1,60 @@
+test_that("Util functions work", {
+  expect_length(rnbinom_mean_disp(n = 5, mn = 4, disp = 2), 5)
+  expect_length(rgen_length(n = 1, x = c(1, 2, 3), prob = 0.3), 3)
+  expect_length(rbinom_size(n = 1, x = c(1, 2, 3), prob = 0.3), 3)
+  expect_identical(complementary_logprob(x = 0), -Inf)
+  expect_identical(complementary_logprob(x = -Inf), 0)
+  expect_lt(complementary_logprob(x = -0.1), 0)
+})
+
+test_that("Errors are thrown", {
+  # Checks on 'disp' argument
+  expect_error(
+    rnbinom_mean_disp(n = 5, mn = 4, disp = 0.9),
+    "is not >= 1"
+  )
+  expect_error(
+    rnbinom_mean_disp(n = 5, mn = 4, disp = NA),
+    "May not be NA"
+  )
+  expect_error(
+    rnbinom_mean_disp(n = 5, mn = 4, disp = Inf),
+    "Must be finite"
+  )
+  # Checks on 'n' argument
+  expect_error(
+    rnbinom_mean_disp(n = 0, mn = 4, disp = 2),
+    "is not >= 1"
+  )
+  expect_error(
+    rnbinom_mean_disp(n = NA, mn = 4, disp = 2),
+    "May not be NA"
+  )
+  expect_error(
+    rnbinom_mean_disp(n = Inf, mn = 4, disp = 2),
+    "Must be finite"
+  )
+  # Checks on 'mn' argument
+  expect_error(
+    rnbinom_mean_disp(n = 2, mn = 0, disp = 2)
+  )
+  expect_error(
+    rnbinom_mean_disp(n = 2, mn = NA, disp = 2),
+    "May not be NA"
+  )
+  expect_error(
+    rnbinom_mean_disp(n = 2, mn = Inf, disp = 2),
+    "Must be finite"
+  )
+})
+
+test_that("Errors are thrown", {
+  expect_error(
+    complementary_logprob(0.1),
+    "is not <= 0"
+  )
+  expect_error(
+    complementary_logprob(Inf),
+    "is not <= 0"
+  )
+})