adding unit tests for internal functions

DESCRIPTION

@@ -2,7 +2,7 @@ Package: SimCorMultRes
 Type: Package
 Title: Simulates Correlated Multinomial Responses
 Description: Simulates correlated multinomial responses conditional on a marginal model specification.
-Version: 1.6.7
+Version: 1.6.8
 Depends: R(>= 2.15.0)
 Imports: 
     evd,

README.md

@@ -4,7 +4,7 @@
 # SimCorMultRes: Simulates Correlated Multinomial Responses
 
 [![Github
-version](https://img.shields.io/badge/GitHub%20-1.6.7-orange.svg)](%22commits/master%22)
+version](https://img.shields.io/badge/GitHub%20-1.6.8-orange.svg)](%22commits/master%22)
 [![Travis-CI Build
 Status](https://travis-ci.org/AnestisTouloumis/SimCorMultRes.svg?branch=master)](https://travis-ci.org/AnestisTouloumis/SimCorMultRes)
 [![Project Status: Active The project has reached a stable, usable state

inst/NEWS

@@ -1,6 +1,8 @@
+Version 1.6.8 [2019-07-23]
+ * Added unit tests for internal functions.
+
 Version 1.6.7 [2019-07-22]
  * Improved R code readability.
- * Added unit tests for internal functions.
 
 Version 1.6.6 [2019-07-09]
  * Minor fixed to comply with lintr.

tests/testthat/test_internal_functions.R

@@ -2,26 +2,29 @@ check_cluster_size
 
 test_that("checking cluster size", {
   expect_silent(check_cluster_size(2))
-  expect_error(check_cluster_size(1))
-  expect_error(check_cluster_size(2.5))
+  expect_error(check_cluster_size(1),
+               "'clsize' must be a positive integer greater than or equal to two") # nolintr
+  expect_error(check_cluster_size(2.5),
+               "'clsize' must be a positive integer greater than or equal to two") # nolintr
 })
 
 test_that("checking categories", {
   expect_silent(check_ncategories(3))
-  expect_error(check_ncategories(2))
-  expect_error(check_ncategories(2.5))
+  expect_error(check_ncategories(2),
+               "'ncategories' must be numeric greater or equal to three")
+  expect_error(check_ncategories(5.5),
+               "'ncategories' must be a positive integer")
 })
 
 
 test_that("creating marginal distributions", {
   expect_equal(create_distribution("probit"), "qnorm")
-  expect_equal(create_distribution("logit"), "qlogis" )
+  expect_equal(create_distribution("logit"), "qlogis")
   expect_equal(create_distribution("cloglog"), "qgumbel")
   expect_equal(create_distribution("cauchit"), "qcauchy")
 })
 
 
-
 test_that("checking correlation matrix", {
   cluster_size <- 5
   categories_no <- 3
@@ -31,13 +34,23 @@ test_that("checking correlation matrix", {
   correlation_matrix_3 <- matrix(1,  cluster_size * (categories_no - 1),
                                  cluster_size * (categories_no - 1))
   expect_error(check_correlation_matrix(correlation_matrix_1, cluster_size,
-                                        rfctn = "rbin"))
+                                        rfctn = "rbin"),
+               "'cor_matrix' must be positive definite")
   expect_error(check_correlation_matrix(correlation_matrix_1, cluster_size,
-                                        rfctn = "rmult.clm"))
+                                        rfctn = "rmult.clm"),
+               "'cor_matrix' must be positive definite")
   expect_error(check_correlation_matrix(correlation_matrix_2, cluster_size,
-                                        rfctn = "rmult.bcl", categories_no))
+                                        rfctn = "rmult.bcl", categories_no),
+               "'cor_matrix' must be positive definite")
+  expect_error(check_correlation_matrix(correlation_matrix_1, cluster_size,
+                                        rfctn = "rmult.bcl", categories_no),
+               "'cor_matrix' must be a 15x15 matrix")
   expect_error(check_correlation_matrix(correlation_matrix_3, cluster_size,
-                                        rfctn = "rmult.crm", categories_no))
+                                        rfctn = "rmult.crm", categories_no),
+               "'cor_matrix' must be positive definite")
+  expect_error(check_correlation_matrix(correlation_matrix_2, cluster_size,
+                                        rfctn = "rmult.crm", categories_no),
+               "'cor_matrix' must be a 10x10 matrix")
   correlation_matrix_4 <- diag(1, cluster_size)
   correlation_matrix_5 <- diag(1,  cluster_size * categories_no)
   correlation_matrix_6 <- diag(1,  cluster_size * (categories_no - 1))
@@ -54,3 +67,44 @@ test_that("checking correlation matrix", {
                                         rfctn = "rmult.crm", categories_no),
                correlation_matrix_6)
 })
+
+test_that("checking covariates formula", {
+  xformula <- ~ -1
+  expect_error(check_xformula(xformula),
+               "No covariates were found in 'formula'")
+  xformula <-  ~ x1 + x2
+  expect_equal(check_xformula(xformula), as.formula(~ x1 + x2))
+  xformula <- y ~ x1 + x2
+  expect_equal(check_xformula(xformula), as.formula(y ~ x1 + x2))
+  xformula <- y ~ x1 + x2 - 1
+  expect_equal(check_xformula(xformula), as.formula(y ~ x1 + x2))
+})
+
+test_that("checking intercepts", {
+  cluster_size <- 5
+  rfctn <- "rbin"
+  intercepts <- c(-Inf, 3, Inf)
+  expect_error(check_intercepts(intercepts, cluster_size, rfctn),
+               "'intercepts' must not be Inf or -Inf")
+  intercepts <- c(2, 3)
+  expect_error(check_intercepts(intercepts, cluster_size, rfctn),
+               "'intercepts' must have either one or 5 elements")
+  intercepts <- 2
+  ans <- rep(intercepts, cluster_size)
+  ans <- cbind(-Inf, ans, Inf)
+  colnames(ans) <- c("","intercepts","")
+  expect_equal(check_intercepts(intercepts, cluster_size, rfctn), ans)
+  intercepts <- 1:cluster_size
+  ans <- cbind(-Inf, intercepts, Inf)
+  colnames(ans) <- c("","intercepts","")
+  expect_equal(check_intercepts(intercepts, cluster_size, rfctn), ans)
+  rfctn <- "rmult.clm"
+  intercepts <- c(-Inf, 3, Inf)
+  expect_error(check_intercepts(intercepts, cluster_size, rfctn),
+               "'intercepts' must not be Inf or -Inf")
+  intercepts <- c(2, 3)
+  ans <- matrix(intercepts, nrow = cluster_size, ncol = 2, byrow = TRUE)
+  ans <- cbind(-Inf, ans, Inf)
+  colnames(ans) <- NULL
+  expect_equal(check_intercepts(intercepts, cluster_size, rfctn), ans)
+})