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moved compute_distance to twodistributiontest, added unittest
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139 changes: 139 additions & 0 deletions
139
tests/unit/statistical_testing/TwoDistributionTest_unittest.cc
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| /* | ||
| * Copyright (c) The Shogun Machine Learning Toolbox | ||
| * Written (w) 2016 Soumyajit De | ||
| * All rights reserved. | ||
| * | ||
| * Redistribution and use in source and binary forms, with or without | ||
| * modification, are permitted provided that the following conditions are met: | ||
| * | ||
| * 1. Redistributions of source code must retain the above copyright notice, this | ||
| * list of conditions and the following disclaimer. | ||
| * 2. Redistributions in binary form must reproduce the above copyright notice, | ||
| * this list of conditions and the following disclaimer in the documentation | ||
| * and/or other materials provided with the distribution. | ||
| * | ||
| * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND | ||
| * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
| * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
| * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR | ||
| * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
| * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
| * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
| * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
| * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
| * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
| * | ||
| * The views and conclusions contained in the software and documentation are those | ||
| * of the authors and should not be interpreted as representing official policies, | ||
| * either expressed or implied, of the Shogun Development Team. | ||
| */ | ||
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|
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| #include <shogun/base/some.h> | ||
| #include <shogun/lib/SGVector.h> | ||
| #include <shogun/lib/SGMatrix.h> | ||
| #include <shogun/features/Features.h> | ||
| #include <shogun/features/DenseFeatures.h> | ||
| #include <shogun/features/streaming/generators/MeanShiftDataGenerator.h> | ||
| #include <shogun/distance/CustomDistance.h> | ||
| #include <shogun/distance/EuclideanDistance.h> | ||
| #include <shogun/statistical_testing/TwoDistributionTest.h> | ||
| #include <gtest/gtest.h> | ||
| #include <gmock/gmock.h> | ||
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| namespace shogun | ||
| { | ||
|
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| class CTwoDistributionTestMock : public CTwoDistributionTest | ||
| { | ||
| public: | ||
| MOCK_METHOD0(compute_statistic, float64_t()); | ||
| MOCK_METHOD0(sample_null, SGVector<float64_t>()); | ||
| }; | ||
|
|
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| } | ||
|
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| using namespace shogun; | ||
|
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| TEST(TwoDistributionTest, compute_distance_dense) | ||
| { | ||
| const index_t m=5; | ||
| const index_t n=10; | ||
| const index_t dim=1; | ||
| const float64_t difference=0.5; | ||
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| auto gen_p=some<CMeanShiftDataGenerator>(0, dim, 0); | ||
| auto gen_q=some<CMeanShiftDataGenerator>(difference, dim, 0); | ||
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| auto feats_p=static_cast<CDenseFeatures<float64_t>*>(gen_p->get_streamed_features(m)); | ||
| auto feats_q=static_cast<CDenseFeatures<float64_t>*>(gen_q->get_streamed_features(n)); | ||
|
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| auto test=some<CTwoDistributionTestMock>(); | ||
| test->set_p(feats_p); | ||
| test->set_q(feats_q); | ||
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| auto distance=test->compute_distance(); | ||
| auto distance_mat1=distance->get_distance_matrix(); | ||
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| SGMatrix<float64_t> data_p_and_q(1, m+n); | ||
| auto data_p=feats_p->get_feature_matrix(); | ||
| auto data_q=feats_q->get_feature_matrix(); | ||
| std::copy(data_p.data(), data_p.data()+data_p.size(), data_p_and_q.data()); | ||
| std::copy(data_q.data(), data_q.data()+data_q.size(), data_p_and_q.data()+data_p.size()); | ||
| auto feats_p_and_q=new CDenseFeatures<float64_t>(data_p_and_q); | ||
|
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| auto euclidean_distance=some<CEuclideanDistance>(); | ||
| euclidean_distance->init(feats_p_and_q, feats_p_and_q); | ||
| auto distance_mat2=euclidean_distance->get_distance_matrix(); | ||
|
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| EXPECT_TRUE(distance_mat1.num_rows==distance_mat2.num_rows); | ||
| EXPECT_TRUE(distance_mat1.num_cols==distance_mat2.num_cols); | ||
| for (size_t i=0; i<distance_mat1.size(); ++i) | ||
| EXPECT_NEAR(distance_mat1.data()[i], distance_mat2.data()[i], 1E-6); | ||
|
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| SG_UNREF(distance); | ||
| } | ||
|
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| TEST(TwoDistributionTest, compute_distance_streaming) | ||
| { | ||
| const index_t m=5; | ||
| const index_t n=10; | ||
| const index_t dim=1; | ||
| const float64_t difference=0.5; | ||
|
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| auto gen_p=new CMeanShiftDataGenerator(0, dim, 0); | ||
| auto gen_q=new CMeanShiftDataGenerator(difference, dim, 0); | ||
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| auto test=some<CTwoDistributionTestMock>(); | ||
| test->set_p(gen_p); | ||
| test->set_q(gen_q); | ||
| test->set_num_samples_p(m); | ||
| test->set_num_samples_q(n); | ||
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| sg_rand->set_seed(12345); | ||
| auto distance=test->compute_distance(); | ||
| auto distance_mat1=distance->get_distance_matrix(); | ||
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| sg_rand->set_seed(12345); | ||
| auto feats_p=static_cast<CDenseFeatures<float64_t>*>(gen_p->get_streamed_features(m)); | ||
| auto feats_q=static_cast<CDenseFeatures<float64_t>*>(gen_q->get_streamed_features(n)); | ||
|
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| SGMatrix<float64_t> data_p_and_q(1, m+n); | ||
| auto data_p=feats_p->get_feature_matrix(); | ||
| auto data_q=feats_q->get_feature_matrix(); | ||
| std::copy(data_p.data(), data_p.data()+data_p.size(), data_p_and_q.data()); | ||
| std::copy(data_q.data(), data_q.data()+data_q.size(), data_p_and_q.data()+data_p.size()); | ||
| auto feats_p_and_q=new CDenseFeatures<float64_t>(data_p_and_q); | ||
| SG_UNREF(feats_p); | ||
| SG_UNREF(feats_q); | ||
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| auto euclidean_distance=some<CEuclideanDistance>(); | ||
| euclidean_distance->init(feats_p_and_q, feats_p_and_q); | ||
| auto distance_mat2=euclidean_distance->get_distance_matrix(); | ||
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| EXPECT_TRUE(distance_mat1.num_rows==distance_mat2.num_rows); | ||
| EXPECT_TRUE(distance_mat1.num_cols==distance_mat2.num_cols); | ||
| for (size_t i=0; i<distance_mat1.size(); ++i) | ||
| EXPECT_NEAR(distance_mat1.data()[i], distance_mat2.data()[i], 1E-6); | ||
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| SG_UNREF(distance); | ||
| } |