[mlpack-svn] r10763 - mlpack/trunk/src/mlpack/tests

[fastlab-svn at coffeetalk-1.cc.gatech.edu]

Author: rcurtin
Date: 2011-12-14 03:19:14 -0500 (Wed, 14 Dec 2011)
New Revision: 10763

Modified:
   mlpack/trunk/src/mlpack/tests/nbc_test.cpp
Log:
Restructure test.


Modified: mlpack/trunk/src/mlpack/tests/nbc_test.cpp
===================================================================
--- mlpack/trunk/src/mlpack/tests/nbc_test.cpp	2011-12-14 08:04:33 UTC (rev 10762)
+++ mlpack/trunk/src/mlpack/tests/nbc_test.cpp	2011-12-14 08:19:14 UTC (rev 10763)
@@ -4,7 +4,7 @@
  * Test for the Naive Bayes classifier.
  */
 #include <mlpack/core.hpp>
-#include <mlpack/methods/naive_bayes/simple_nbc.hpp>
+#include <mlpack/methods/naive_bayes/naive_bayes_classifier.hpp>
 
 #include <boost/test/unit_test.hpp>
 
@@ -13,53 +13,51 @@
 
 BOOST_AUTO_TEST_SUITE(NBCTest);
 
-BOOST_AUTO_TEST_CASE(SimpleNBCTest)
+BOOST_AUTO_TEST_CASE(NaiveBayesClassifierTest)
 {
-  const char* filename_train_ = "trainSet.csv";
-  const char* filename_test_ = "testSet.csv";
-  const char* train_result_ = "trainRes.csv";
-  const char* test_result_ = "testRes.csv";
-  size_t number_of_classes_ = 2;
+  const char* trainFilename = "trainSet.csv";
+  const char* testFilename = "testSet.csv";
+  const char* trainResultFilename = "trainRes.csv";
+  const char* testResultFilename = "testRes.csv";
+  size_t classes = 2;
 
-  arma::mat train_data, train_res, calc_mat;
-  data::Load(filename_train_, train_data, true);
-  data::Load(train_result_, train_res, true);
+  arma::mat trainData, trainRes, calcMat;
+  data::Load(trainFilename, trainData, true);
+  data::Load(trainResultFilename, trainRes, true);
 
-  //Does not actually grab number_of_classes from the command line, as this
-  //is a boost unit test.
-  SimpleNaiveBayesClassifier nbc_test_(train_data, number_of_classes_);
+  NaiveBayesClassifier<> nbcTest(trainData, classes);
 
-  size_t number_of_features = nbc_test_.means_.n_rows;
-  calc_mat.zeros(2 * number_of_features + 1, number_of_classes_);
+  size_t dimension = nbcTest.Means().n_rows;
+  calcMat.zeros(2 * dimension + 1, classes);
 
-  for (size_t i = 0; i < number_of_features; i++)
+  for (size_t i = 0; i < dimension; i++)
   {
-    for (size_t j = 0; j < number_of_classes_; j++)
+    for (size_t j = 0; j < classes; j++)
     {
-      calc_mat(i, j) = nbc_test_.means_(i, j);
-      calc_mat(i + number_of_features, j) = nbc_test_.variances_(i, j);
+      calcMat(i, j) = nbcTest.Means()(i, j);
+      calcMat(i + dimension, j) = nbcTest.Variances()(i, j);
     }
   }
 
-  for (size_t i = 0; i < number_of_classes_; i++)
-    calc_mat(2 * number_of_features, i) = nbc_test_.class_probabilities_(i);
+  for (size_t i = 0; i < classes; i++)
+    calcMat(2 * dimension, i) = nbcTest.Probabilities()(i);
 
-  for(size_t i = 0; i < calc_mat.n_rows; i++)
-    for(size_t j = 0; j < number_of_classes_; j++)
-      BOOST_REQUIRE_CLOSE(train_res(i, j) + .00001, calc_mat(i, j), .01);
+  for(size_t i = 0; i < calcMat.n_rows; i++)
+    for(size_t j = 0; j < classes; j++)
+      BOOST_REQUIRE_CLOSE(trainRes(i, j) + .00001, calcMat(i, j), .01);
 
-  arma::mat test_data, test_res;
-  arma::vec test_res_vec, calc_vec;
-  data::Load(filename_test_, test_data, true);
-  data::Load(test_result_, test_res, true);
+  arma::mat testData;
+  arma::Mat<size_t> testRes;
+  arma::Col<size_t> calcVec;
+  data::Load(testFilename, testData, true);
+  data::Load(testResultFilename, testRes, true);
 
-  nbc_test_.Classify(test_data, calc_vec);
+  testData.shed_row(testData.n_rows - 1); // Remove the labels.
 
-  size_t number_of_datum = test_data.n_cols;
-  test_res_vec = test_res.col(0);
+  nbcTest.Classify(testData, calcVec);
 
-  for(size_t i = 0; i < number_of_datum; i++)
-    BOOST_REQUIRE_EQUAL(test_res_vec(i), calc_vec(i));
+  for(size_t i = 0; i < testData.n_cols; i++)
+    BOOST_REQUIRE_EQUAL(testRes(i), calcVec(i));
 }
 
 BOOST_AUTO_TEST_SUITE_END();