Merge branch 'issue-17' into develop (close #17)

* issue-17:
  Sped up `inference_help.R` tests (#17)
  Rewritten output as unit tests (#17)
  Restyled test file (#17)
  Added original `inference_help.R` (#17)
  Increment version number to 1.4.4.9035

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: EMJMCMC
 Type: Package
 Title: Flexible Bayesian Nonlinear Model Configuration
-Version: 1.4.4.9034
+Version: 1.4.4.9035
 Date: 2022-03-06
 Authors@R:
   c(

tests/testthat/test-inference-help.R

@@ -0,0 +1,108 @@
+# simulate Gaussian responses
+threads <- 1L
+n_dims <- c(11, 100)
+set.seed(040590)
+X1 <- as.data.frame(
+  array(
+    data = rbinom(n = prod(n_dims), size = 1, prob = runif(n = prod(n_dims), 0, 1)),
+    dim = rev(n_dims)
+  )
+)
+Y1 <- rnorm(
+  n = n_dims[2],
+  mean = 1 + 0.7 * (X1$V1 * X1$V4) + 0.8896846 * (X1$V8 * X1$V11) + 1.434573 * (X1$V5 * X1$V9),
+  sd = 1
+)
+X1$Y1 <- Y1
+
+# specify the initial formula
+formula1 <- as.formula(
+  paste(colnames(X1)[ncol(X1)], "~ 1 +", paste0(colnames(X1)[-c(ncol(X1))], collapse = "+"))
+)
+data.example <- as.data.frame(X1)
+
+# run the inference with robust g prior
+res4G <- suppressMessages(
+  LogicRegr(
+    formula = formula1, data = data.example, family = "Gaussian", prior = "G",
+    report.level = 0.5, d = 15, cmax = 2, kmax = 15, p.and = 0.9, p.not = 0.01,
+    p.surv = 0.2, ncores = threads, print.freq = 0L
+  )
+)
+# run the inference with Jeffrey's prior
+res4J <- suppressMessages(
+  LogicRegr(
+    formula = formula1, data = data.example, family = "Gaussian", prior = "J",
+    report.level = 0.5, d = 15, cmax = 2, kmax = 15, p.and = 0.9, p.not = 0.01,
+    p.surv = 0.2, ncores = threads, print.freq = 0L
+  )
+)
+
+# change to Bernoulli responses
+X1 <- as.data.frame(
+  array(data = rbinom(n = prod(n_dims), size = 1, prob = 0.3), dim = rev(n_dims))
+)
+Y1 <- -0.7 + 1 * ((1 - X1$V1) * (X1$V4)) + 1 * (X1$V8 * X1$V11) + 1 * (X1$V5 * X1$V9)
+X1$Y1 <- round(1.0 / (1.0 + exp(-Y1)))
+
+# specify the initial formula
+formula1 <- as.formula(
+  paste(colnames(X1)[ncol(X1)], "~ 1 +", paste0(colnames(X1)[-c(ncol(X1))], collapse = "+"))
+)
+data.example <- as.data.frame(X1)
+
+# run the inference with robust g prior
+res1G <- suppressWarnings(
+  suppressMessages(
+    LogicRegr(
+      formula = formula1, data = data.example, family = "Bernoulli", prior = "G",
+      report.level = 0.5, d = 15, cmax = 2, kmax = 15, p.and = 0.9, p.not = 0.2,
+      p.surv = 0.2, ncores = threads, print.freq = 0L
+    )
+  )
+)
+
+# run the inference with Jeffrey's prior
+res1J <- suppressWarnings(
+  suppressMessages(
+    LogicRegr(
+      formula = formula1, data = data.example, family = "Bernoulli", prior = "J",
+      report.level = 0.5, d = 15, cmax = 2, kmax = 15, p.and = 0.9, p.not = 0.2,
+      p.surv = 0.2, ncores = threads, print.freq = 0L
+    )
+  )
+)
+test_that("outputs are correct", {
+  expect_equal(
+    res4G$feat.stat,
+    matrix(c("I(((V5))&((V9)))", "0.998464672344289"), nrow = 1)
+  )
+  expect_equal(
+    res4J$feat.stat,
+    matrix(c( "I(((V5))&((V9)))", "0.995269065749787"), nrow = 1)
+  )
+  expect_equal(
+    res1G$feat.stat,
+    matrix(
+      c(
+        "I((1-(V1))&((V4)))", "0.999999996715506",
+        "I(V8)", "0.999999302544405",
+        "I(V11)", "0.999997483629185",
+        "I(((((V5))))&((V9)))", "0.958531256229637"
+      ),
+      nrow = 4, ncol = 2, byrow = TRUE
+    )
+  )
+  expect_equal(
+    res1J$feat.stat,
+    matrix(
+      c(
+        "I(((V11))&((V8)))", "0.999994827992723",
+        "I(V1)", "0.97262338705771",
+        "I(V5)", "0.949549067791939",
+        "I(((V9)))", "0.941316258317002"
+      ),
+      nrow = 4, ncol = 2, byrow = TRUE
+    )
+  )
+})