From 1678a6fbdb4c32e3e21beace264e9869654e7a88 Mon Sep 17 00:00:00 2001
From: pommedeterresautee <Salutation33>
Date: Wed, 2 Dec 2015 10:40:15 +0100
Subject: [PATCH] Increase cover of tests #Rstat

---
 R-package/tests/testthat/test_helpers.R | 39 ++++++++++++++-----------
 1 file changed, 22 insertions(+), 17 deletions(-)

diff --git a/R-package/tests/testthat/test_helpers.R b/R-package/tests/testthat/test_helpers.R
index 262ec1cd6..efc22f0b9 100644
--- a/R-package/tests/testthat/test_helpers.R
+++ b/R-package/tests/testthat/test_helpers.R
@@ -14,50 +14,55 @@ df[,AgeCat := as.factor(ifelse(Age > 30, "Old", "Young"))]
 df[,ID := NULL]
 sparse_matrix <- sparse.model.matrix(Improved~.-1, data = df)
 output_vector <- df[,Y := 0][Improved == "Marked",Y := 1][,Y]
-bst <- xgboost(data = sparse_matrix, label = output_vector, max.depth = 9,
-               eta = 1, nthread = 2, nround = 10, objective = "binary:logistic")
+bst.Tree <- xgboost(data = sparse_matrix, label = output_vector, max.depth = 9,
+               eta = 1, nthread = 2, nround = 10, objective = "binary:logistic", booster = "gbtree")
+
+bst.GLM <- xgboost(data = sparse_matrix, label = output_vector,
+                   eta = 1, nthread = 2, nround = 10, objective = "binary:logistic", booster = "gblinear")
 
 feature.names <- agaricus.train$data@Dimnames[[2]]
 
 test_that("xgb.dump works", {
-  capture.output(print(xgb.dump(bst)))
-  expect_true(xgb.dump(bst, 'xgb.model.dump', with.stats = T))
+  capture.output(print(xgb.dump(bst.Tree)))
+  capture.output(print(xgb.dump(bst.GLM)))
+  expect_true(xgb.dump(bst.Tree, 'xgb.model.dump', with.stats = T))
 })
 
 test_that("xgb.model.dt.tree works with and without feature names", {
   names.dt.trees <- c("ID", "Feature", "Split", "Yes", "No", "Missing", "Quality", "Cover",
    "Tree", "Yes.Feature", "Yes.Cover", "Yes.Quality", "No.Feature", "No.Cover", "No.Quality")
-  dt.tree <- xgb.model.dt.tree(feature_names = feature.names, model = bst)
+  dt.tree <- xgb.model.dt.tree(feature_names = feature.names, model = bst.Tree)
   expect_equal(names.dt.trees, names(dt.tree))
   expect_equal(dim(dt.tree), c(162, 15))
-  xgb.model.dt.tree(model = bst)
+  xgb.model.dt.tree(model = bst.Tree)
 })
 
 test_that("xgb.importance works with and without feature names", {
-  importance <- xgb.importance(feature_names = sparse_matrix@Dimnames[[2]], model = bst)
-  expect_equal(dim(importance), c(7, 4))
-  expect_equal(colnames(importance), c("Feature", "Gain", "Cover", "Frequency"))
-  xgb.importance(model = bst)
+  importance.Tree <- xgb.importance(feature_names = sparse_matrix@Dimnames[[2]], model = bst.Tree)
+  expect_equal(dim(importance.Tree), c(7, 4))
+  expect_equal(colnames(importance.Tree), c("Feature", "Gain", "Cover", "Frequency"))
+  xgb.importance(model = bst.Tree)
+  xgb.plot.importance(importance_matrix = importance.Tree)
 })
 
 test_that("xgb.importance works with GLM model", {
-  bst.GLM <- xgboost(data = sparse_matrix, label = output_vector,
-                 eta = 1, nthread = 2, nround = 10, objective = "binary:logistic", booster = "gblinear")
   importance.GLM <- xgb.importance(feature_names = sparse_matrix@Dimnames[[2]], model = bst.GLM)
   expect_equal(dim(importance.GLM), c(10, 2))
   expect_equal(colnames(importance.GLM), c("Feature", "Weight"))
   xgb.importance(model = bst.GLM)
+  xgb.plot.importance(importance.GLM)
 })
 
 test_that("xgb.plot.tree works with and without feature names", {
-  xgb.plot.tree(feature_names = feature.names, model = bst)
-  xgb.plot.tree(model = bst)
+  xgb.plot.tree(feature_names = feature.names, model = bst.Tree)
+  xgb.plot.tree(model = bst.Tree)
 })
 
 test_that("xgb.plot.multi.trees works with and without feature names", {
-  xgb.plot.multi.trees(model = bst, feature_names = feature.names, features.keep = 3)
-  xgb.plot.multi.trees(model = bst, features.keep = 3)
+  xgb.plot.multi.trees(model = bst.Tree, feature_names = feature.names, features.keep = 3)
+  xgb.plot.multi.trees(model = bst.Tree, features.keep = 3)
 })
+
 test_that("xgb.plot.deepness works", {
-  xgb.plot.deepness(model = bst)
+  xgb.plot.deepness(model = bst.Tree)
 })