feat: prepare for CRAN release

RobinDenz1 · RobinDenz1 · commit 6f31b2ed029e · 2025-03-30T17:36:51.000+02:00
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: simDAG
 Title: Simulate Data from a DAG and Associated Node Information
-Version: 0.2.2.9000
+Version: 0.3.0
 Authors@R: c(
     person("Robin", "Denz", , "robin.denz@rub.de", role = c("aut", "cre")),
     person("Katharina", "Meiszl", , "meiszl@amib.rub-uni-bochum.de", role = c("aut"))
diff --git a/NEWS.md b/NEWS.md
@@ -114,7 +114,7 @@ Enhancements
 * Added the `reference` argument to `rbernoulli()` and `rcategorical()` to make it easier to specify the reference category when coding the output as a factor variable.
 * `+.DAG` now checks whether the `DAG` would become cyclic when adding a `node()` and returns an error if it does.
 * Added the `include_td_nodes` and `include_root_nodes` arguments to `as.igraph.DAG()`.
-* Changed the default of `n_cores` in the `sim_n_datasets()` function to 1 from `parallel::detectCores()-1`
+* Changed the default of `n_cores` in the `sim_n_datasets()` function to 1 from `parallel::detectCores()`
 * Function input to the `cens_dist` argument in the `node_cox()` function is now allowed.
 * The argument `as_two_cols` was added to the `node_cox()` function to allow users to return only the time-to-event as a single column if no censoring is applied.
 
diff --git a/codemeta.json b/codemeta.json
@@ -8,7 +8,7 @@
   "codeRepository": "https://github.com/RobinDenz1/simDAG",
   "issueTracker": "https://github.com/RobinDenz1/siMDAG/issues",
   "license": "https://spdx.org/licenses/GPL-3.0",
-  "version": "0.2.2",
+  "version": "0.2.2.9000",
   "programmingLanguage": {
     "@type": "ComputerLanguage",
     "name": "R",
@@ -175,6 +175,35 @@
       "@type": "SoftwareApplication",
       "identifier": "parallel",
       "name": "parallel"
+    },
+    {
+      "@type": "SoftwareApplication",
+      "identifier": "utils",
+      "name": "utils"
+    },
+    {
+      "@type": "SoftwareApplication",
+      "identifier": "simr",
+      "name": "simr",
+      "provider": {
+        "@id": "https://cran.r-project.org",
+        "@type": "Organization",
+        "name": "Comprehensive R Archive Network (CRAN)",
+        "url": "https://cran.r-project.org"
+      },
+      "sameAs": "https://CRAN.R-project.org/package=simr"
+    },
+    {
+      "@type": "SoftwareApplication",
+      "identifier": "rsurv",
+      "name": "rsurv",
+      "provider": {
+        "@id": "https://cran.r-project.org",
+        "@type": "Organization",
+        "name": "Comprehensive R Archive Network (CRAN)",
+        "url": "https://cran.r-project.org"
+      },
+      "sameAs": "https://CRAN.R-project.org/package=rsurv"
     }
   ],
   "softwareRequirements": {
@@ -229,7 +258,7 @@
     },
     "SystemRequirements": null
   },
-  "fileSize": "1261.119KB",
+  "fileSize": "1401.968KB",
   "citation": [
     {
       "@type": "CreativeWork",
@@ -252,7 +281,7 @@
   ],
   "releaseNotes": "https://github.com/RobinDenz1/simDAG/blob/master/NEWS.md",
   "readme": "https://github.com/RobinDenz1/simDAG/blob/main/README.md",
-  "contIntegration": ["https://github.com/RobinDenz1/simDAG/actions/workflows/R-CMD-check.yaml", "https://app.codecov.io/gh/RobinDenz1/simDAG?branch=main"],
+  "contIntegration": ["https://github.com/RobinDenz1/simDAG/actions/workflows/R-CMD-check.yaml", "https://app.codecov.io/gh/RobinDenz1/simDAG"],
   "developmentStatus": "https://www.repostatus.org/#active",
   "keywords": ["causal-inference", "directed-acyclic-graph", "simulation"]
 }
diff --git a/man/node_cox.Rd b/man/node_cox.Rd
@@ -60,7 +60,7 @@ Bender R, Augustin T, Blettner M. Generating survival times to simulate Cox prop
 Robin Denz
 }
 \value{
-Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both colums start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.
+Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both columns start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.
 }
 \examples{
 library(simDAG)
diff --git a/man/node_mixture.Rd b/man/node_mixture.Rd
@@ -33,7 +33,7 @@ Robin Denz
 \details{
 Internally, the data is generated by extracting only the relevant part of the already generated \code{data} as defined by the condition and using \code{\link{node}} function to generate the new response-part. This generation is done in the order in which the \code{distr} was specified, meaning that data for the first condition is checked first and so on. There are no safeguards to guarantee that the conditions do not overlap. For example, users are free to set the first condition to something like \code{A > 10} and the next one to \code{A > 11}, in which case the value for every individual with \code{A > 11} is generated twice (first with the first specification, secondly with the next specification). In this case, only the last generated value is retained.
 
-Note that it is also possible to use the mixture node itself inside the conditions or \code{\link{node}} calls in \code{distr}, because it is directly added to the \code{data} before the first condition is applied (by setting everyong to the \code{default} value). See examples.
+Note that it is also possible to use the mixture node itself inside the conditions or \code{\link{node}} calls in \code{distr}, because it is directly added to the \code{data} before the first condition is applied (by setting everyone to the \code{default} value). See examples.
 
 Additionally, because the output of each of the parts of the mixture distributions is forced into one vector, they might be coerced from one class to another, depending on the input to \code{distr} and the order used. This also needs to be taken care of by the user.
 }
diff --git a/man/node_rsurv.Rd b/man/node_rsurv.Rd
@@ -89,7 +89,7 @@ Demarqui Fabio N. Simulation of Survival Data with the Package rsurv. (2024) arX
 Robin Denz
 }
 \value{
-Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both colums start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.
+Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both columns start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.
 }
 \examples{
 library(simDAG)
diff --git a/tests/testthat/test_node_custom.r b/tests/testthat/test_node_custom.r
@@ -16,3 +16,15 @@ test_that("multiple columns in custom root", {
   expect_true(nrow(data)==100)
   expect_equal(colnames(data), c("A", "B", "C"))
 })
+
+test_that("node needs intercept", {
+
+  test_fun <- function(data, intercept) {
+    return(data)
+  }
+
+  assign("test_fun", test_fun, envir=.GlobalEnv)
+
+  expect_true(node_needs_intercept(test_fun))
+  expect_true(node_needs_intercept("test_fun"))
+})
diff --git a/tests/testthat/test_node_mixture.r b/tests/testthat/test_node_mixture.r
@@ -105,6 +105,24 @@ test_that("conditions not covering all scenarios, using default", {
   expect_equal(round(mean(data$Y[data$A==0]), 3), -2.711)
 })
 
+test_that("calling the function directly", {
+
+  set.seed(1535434)
+
+  dag <- empty_dag() +
+    node("A", type="rbernoulli") +
+    node("B", type="rnorm")
+  data <- as.data.frame(sim_from_dag(dag, n_sim=100))
+
+  out <- node_mixture("Y", data=data, parents="A",
+       distr=list(
+         "A==0", node(".", type="gaussian", formula= ~ -2 + B*2, error=1)
+       ), default=10)
+
+  expect_true(all(out[data$A==1]==10))
+  expect_equal(round(mean(out[data$A==0]), 3), -2.711)
+})
+
 test_that("nothing in distr defined", {
   expect_error({
     dag <- empty_dag() +
diff --git a/tests/testthat/test_str_eq_rsurv.r b/tests/testthat/test_str_eq_rsurv.r
@@ -1,24 +1,72 @@
 
 test_that("general test case", {
 
-  node <- node("Bla", type="aftreg", formula= ~ -2 + A*0.1 + B*3,
+  node <- node("Bla", type="aftreg", formula= ~ A*0.1 + B*3,
                baseline="weibull", shape=1, scale=2)
 
   out1 <- str_eq_rsurv(node, "aftreg")
   out2 <- str_eq_aftreg(node)
 
   expect_equal(out1, out2)
-  expect_equal(out1, c("Bla[T] ~ aftreg(-2 + A*0.1 + B*3, dist='weibull')",
+  expect_equal(out1, c("Bla[T] ~ aftreg(A*0.1 + B*3, dist='weibull')",
                        "Bla[C] ~ Inf"))
 })
 
 test_that("with censoring", {
 
-  node <- node("Bla2", type="ahreg", formula= ~ -2 + A*0.1 + B*3,
+  node <- node("Bla2", type="ahreg", formula= ~ A*0.1 + B*3,
                baseline="weibull", shape=1, scale=2,
                cens_dist="runif", cens_args=list(min=0, max=10))
 
   out <- str_eq_rsurv(node, "aftreg")
-  expect_equal(out, c("Bla2[T] ~ aftreg(-2 + A*0.1 + B*3, dist='weibull')",
+  expect_equal(out, c("Bla2[T] ~ aftreg(A*0.1 + B*3, dist='weibull')",
                       "Bla2[C] ~ runif(min=0, max=10)"))
 })
+
+test_that("with parents / betas specified", {
+  node <- node("Bla", type="aftreg",
+               parents=c("A", "B"),
+               betas=c(0.1, 3),
+               dist="weibull", shape=1, scale=2)
+  out <- structural_equation(node)
+  expect_equal(out, c("Bla[T] ~ aftreg(0.1*A + 3*B, dist='weibull')",
+                      "Bla[C] ~ Inf"))
+})
+
+test_that("correct output with structural_equation()", {
+
+  # aftreg
+  node <- node("Bla", type="aftreg", formula= ~ A*0.1 + B*3,
+               baseline="weibull", shape=1, scale=2)
+  out <- structural_equation(node)
+  expect_equal(out, c("Bla[T] ~ aftreg(A*0.1 + B*3, dist='weibull')",
+                      "Bla[C] ~ Inf"))
+
+  # ahreg
+  node <- node("Bla", type="ahreg", formula= ~ A*0.1 + B*3,
+               baseline="weibull", shape=1, scale=2)
+  out <- structural_equation(node)
+  expect_equal(out, c("Bla[T] ~ ahreg(A*0.1 + B*3, dist='weibull')",
+                      "Bla[C] ~ Inf"))
+
+  # ehreg
+  node <- node("Bla", type="ehreg", formula= ~ A*0.1 + B*3,
+               baseline="weibull", shape=1, scale=2)
+  out <- structural_equation(node)
+  expect_equal(out, c("Bla[T] ~ ehreg(A*0.1 + B*3, dist='weibull')",
+                      "Bla[C] ~ Inf"))
+
+  # poreg
+  node <- node("Bla", type="poreg", formula= ~ A*0.1 + B*3,
+               baseline="weibull", shape=1, scale=2)
+  out <- structural_equation(node)
+  expect_equal(out, c("Bla[T] ~ poreg(A*0.1 + B*3, dist='weibull')",
+                      "Bla[C] ~ Inf"))
+
+  # ypreg
+  node <- node("Bla", type="ypreg", formula= ~ A*0.1 + B*3,
+               baseline="weibull", shape=1, scale=2)
+  out <- structural_equation(node)
+  expect_equal(out, c("Bla[T] ~ ypreg(A*0.1 + B*3, dist='weibull')",
+                      "Bla[C] ~ Inf"))
+})

Original file line number	Diff line number	Diff line change
`@@ -60,7 +60,7 @@ Bender R, Augustin T, Blettner M. Generating survival times to simulate Cox prop`
`60`	`60`	`Robin Denz`
`61`	`61`	`}`
`62`	`62`	`\value{`
`63`		`-Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both colums start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.`
	`63`	`+Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both columns start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.`
`64`	`64`	`}`
`65`	`65`	`\examples{`
`66`	`66`	`library(simDAG)`
Original file line number	Diff line number	Diff line change
`@@ -33,7 +33,7 @@ Robin Denz`
`33`	`33`	`\details{`
`34`	`34`	Internally, the data is generated by extracting only the relevant part of the already generated \code{data} as defined by the condition and using \code{\link{node}} function to generate the new response-part. This generation is done in the order in which the \code{distr} was specified, meaning that data for the first condition is checked first and so on. There are no safeguards to guarantee that the conditions do not overlap. For example, users are free to set the first condition to something like \code{A > 10} and the next one to \code{A > 11}, in which case the value for every individual with \code{A > 11} is generated twice (first with the first specification, secondly with the next specification). In this case, only the last generated value is retained.
`35`	`35`
`36`		`-Note that it is also possible to use the mixture node itself inside the conditions or \code{\link{node}} calls in \code{distr}, because it is directly added to the \code{data} before the first condition is applied (by setting everyong to the \code{default} value). See examples.`
	`36`	`+Note that it is also possible to use the mixture node itself inside the conditions or \code{\link{node}} calls in \code{distr}, because it is directly added to the \code{data} before the first condition is applied (by setting everyone to the \code{default} value). See examples.`
`37`	`37`
`38`	`38`	`Additionally, because the output of each of the parts of the mixture distributions is forced into one vector, they might be coerced from one class to another, depending on the input to \code{distr} and the order used. This also needs to be taken care of by the user.`
`39`	`39`	`}`
Original file line number	Diff line number	Diff line change
`@@ -89,7 +89,7 @@ Demarqui Fabio N. Simulation of Survival Data with the Package rsurv. (2024) arX`
`89`	`89`	`Robin Denz`
`90`	`90`	`}`
`91`	`91`	`\value{`
`92`		`-Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both colums start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.`
	`92`	`+Returns a \code{data.table} of length \code{nrow(data)} containing two columns if \code{as_two_cols=TRUE} and always when \code{cens_dist} is specified. In this case, both columns start with the nodes \code{name} and end with \code{_event} and \code{_time}. The first is a logical vector, the second a numeric one. If \code{as_two_cols=FALSE} and \code{cens_dist} is \code{NULL}, a numeric vector is returned instead.`
`93`	`93`	`}`
`94`	`94`	`\examples{`
`95`	`95`	`library(simDAG)`