[mlpack-git] master: Fix tests that rely on DatasetInfo. (39b1bd7)

[gitdub at big.cc.gt.atl.ga.us]

Repository : https://github.com/mlpack/mlpack

On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/de9cc4b05069e1fa4793d9355f2f595af5ff45d2...6070527af14296cd99739de6c62666cc5d2a2125

>---------------------------------------------------------------

commit 39b1bd76c91edc1c5cd0a9fafe4114d83261cd05
Author: Ryan Curtin <ryan at ratml.org>
Date:   Sat Oct 17 11:33:43 2015 -0400

    Fix tests that rely on DatasetInfo.


>---------------------------------------------------------------

39b1bd76c91edc1c5cd0a9fafe4114d83261cd05
 src/mlpack/tests/hoeffding_tree_test.cpp | 18 +++++++++---------
 src/mlpack/tests/load_save_test.cpp      |  2 +-
 2 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/src/mlpack/tests/hoeffding_tree_test.cpp b/src/mlpack/tests/hoeffding_tree_test.cpp
index 7ffe083..2f76f03 100644
--- a/src/mlpack/tests/hoeffding_tree_test.cpp
+++ b/src/mlpack/tests/hoeffding_tree_test.cpp
@@ -208,7 +208,7 @@ BOOST_AUTO_TEST_CASE(HoeffdingCategoricalSplitSplitTest)
 
   // No training is necessary because we can just call CreateChildren().
   std::vector<StreamingDecisionTree<HoeffdingSplit<>>> children;
-  data::DatasetInfo info;
+  data::DatasetInfo info(3);
   info.MapString("hello", 0); // Make dimension 0 categorical.
   HoeffdingCategoricalSplit<GiniImpurity>::SplitInfo splitInfo(3);
 
@@ -229,7 +229,7 @@ BOOST_AUTO_TEST_CASE(HoeffdingCategoricalSplitSplitTest)
 BOOST_AUTO_TEST_CASE(HoeffdingSplitNoSplitTest)
 {
   // Make all dimensions categorical.
-  data::DatasetInfo info;
+  data::DatasetInfo info(3);
   info.MapString("cat1", 0);
   info.MapString("cat2", 0);
   info.MapString("cat3", 0);
@@ -266,7 +266,7 @@ BOOST_AUTO_TEST_CASE(HoeffdingSplitEasySplitTest)
   // dimension, category 0 will only receive points with class 0, and category 1
   // will only receive points with class 1.  In the second dimension, all points
   // will have category 0 (so it is useless).
-  data::DatasetInfo info;
+  data::DatasetInfo info(2);
   info.MapString("cat0", 0);
   info.MapString("cat1", 0);
   info.MapString("cat0", 1);
@@ -294,7 +294,7 @@ BOOST_AUTO_TEST_CASE(HoeffdingSplitProbability1SplitTest)
   // dimension, category 0 will only receive points with class 0, and category 1
   // will only receive points with class 1.  In the second dimension, all points
   // will have category 0 (so it is useless).
-  data::DatasetInfo info;
+  data::DatasetInfo info(2);
   info.MapString("cat0", 0);
   info.MapString("cat1", 0);
   info.MapString("cat0", 1);
@@ -321,7 +321,7 @@ BOOST_AUTO_TEST_CASE(HoeffdingSplitProbability1SplitTest)
 BOOST_AUTO_TEST_CASE(HoeffdingSplitAlmostPerfectSplit)
 {
   // Two categories and two dimensions.
-  data::DatasetInfo info;
+  data::DatasetInfo info(2);
   info.MapString("cat0", 0);
   info.MapString("cat1", 0);
   info.MapString("cat0", 1);
@@ -356,7 +356,7 @@ BOOST_AUTO_TEST_CASE(HoeffdingSplitAlmostPerfectSplit)
 BOOST_AUTO_TEST_CASE(HoeffdingSplitEqualSplitTest)
 {
   // Two categories and two dimensions.
-  data::DatasetInfo info;
+  data::DatasetInfo info(2);
   info.MapString("cat0", 0);
   info.MapString("cat1", 0);
   info.MapString("cat0", 1);
@@ -382,7 +382,7 @@ BOOST_AUTO_TEST_CASE(HoeffdingSplitEqualSplitTest)
  */
 BOOST_AUTO_TEST_CASE(StreamingDecisionTreeSimpleDatasetTest)
 {
-  DatasetInfo info;
+  DatasetInfo info(3);
   info.MapString("cat0", 0);
   info.MapString("cat1", 0);
   info.MapString("cat2", 0);
@@ -601,7 +601,7 @@ BOOST_AUTO_TEST_CASE(NumericHoeffdingTreeTest)
   // Generate data.
   arma::mat dataset(3, 9000);
   arma::Row<size_t> labels(9000);
-  data::DatasetInfo info; // All features are numeric.
+  data::DatasetInfo info(3); // All features are numeric.
   for (size_t i = 0; i < 9000; i += 3)
   {
     dataset(0, i) = mlpack::math::Random();
@@ -669,7 +669,7 @@ BOOST_AUTO_TEST_CASE(BinaryNumericHoeffdingTreeTest)
   // Generate data.
   arma::mat dataset(4, 9000);
   arma::Row<size_t> labels(9000);
-  data::DatasetInfo info; // All features are numeric, except the fourth.
+  data::DatasetInfo info(4); // All features are numeric, except the fourth.
   info.MapString("0", 3);
   for (size_t i = 0; i < 9000; i += 3)
   {
diff --git a/src/mlpack/tests/load_save_test.cpp b/src/mlpack/tests/load_save_test.cpp
index dbd657f..68adc85 100644
--- a/src/mlpack/tests/load_save_test.cpp
+++ b/src/mlpack/tests/load_save_test.cpp
@@ -816,7 +816,7 @@ BOOST_AUTO_TEST_CASE(LoadTextTest)
  */
 BOOST_AUTO_TEST_CASE(DatasetInfoTest)
 {
-  DatasetInfo di;
+  DatasetInfo di(100);
 
   // Do all types default to numeric?
   for (size_t i = 0; i < 100; ++i)