Use assert_eq, use matrix instead of raw array

tests/unit/preprocessor/NormOne_unittest.cc

@@ -17,15 +17,17 @@ class NormOne : public ::testing::Test
 	    : feats(Some<CDenseFeatures<float64_t>>::from_raw(nullptr)),
 	      transformer(some<CNormOne>())
 	{
-		SGMatrix<float64_t> m(data, num_features, num_vectors, false);
-		m = m.clone();
-		feats = some<CDenseFeatures<float64_t>>(m);
+		matrix = SGMatrix<float64_t>(data, num_features, num_vectors, false);
+		auto cloned_matrix = matrix.clone();
+		feats = some<CDenseFeatures<float64_t>>(cloned_matrix);
 	}
 
 protected:
 	float64_t data[6] = {1, 2, 3, 4, 5, 6};
 	float64_t norm[2] = {std::sqrt(1 + 2 * 2 + 3 * 3),
 	                     std::sqrt(4 * 4 + 5 * 5 + 6 * 6)};
+	SGMatrix<float64_t> matrix;
+
 	int32_t num_vectors = 2;
 	int32_t num_features = 3;
 
@@ -39,15 +41,15 @@ TEST_F(NormOne, transform)
 	feats =
 	    wrap(transformer->transform(feats)->as<CDenseFeatures<float64_t>>());
 
-	EXPECT_EQ(feats->get_num_vectors(), num_vectors);
+	ASSERT_EQ(feats->get_num_vectors(), num_vectors);
 
 	for (auto i : range(num_vectors))
 	{
 		SGVector<float64_t> v = feats->get_feature_vector(i);
-		EXPECT_EQ(v.vlen, num_features);
+		ASSERT_EQ(v.vlen, num_features);
 		for (auto j : range(v.vlen))
 		{
-			EXPECT_DOUBLE_EQ(v[j], data[num_features * i + j] / norm[i]);
+			EXPECT_DOUBLE_EQ(v[j], matrix(j, i) / norm[i]);
 		}
 	}
 }
@@ -60,10 +62,10 @@ TEST_F(NormOne, apply_to_vector)
 	{
 		SGVector<float64_t> v = feats->get_feature_vector(i);
 		auto result = transformer->apply_to_feature_vector(v);
-		EXPECT_EQ(result.vlen, num_features);
+		ASSERT_EQ(result.vlen, num_features);
 		for (auto j : range(v.vlen))
 		{
-			EXPECT_DOUBLE_EQ(result[j], data[num_features * i + j] / norm[i]);
+			EXPECT_DOUBLE_EQ(result[j], matrix(j, i) / norm[i]);
 		}
 	}
 }