added data-fetchers and kernel-manager unit-tests

tests/unit/statistical_testing/internals/DataFetcherFactory_unittest.cc

@@ -0,0 +1,64 @@
+/*
+ * 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.
+ */
+
+#include <memory>
+#include <cstring>
+#include <shogun/lib/SGMatrix.h>
+#include <shogun/features/Features.h>
+#include <shogun/features/DenseFeatures.h>
+#include <shogun/features/streaming/StreamingDenseFeatures.h>
+#include <shogun/statistical_testing/internals/DataFetcher.h>
+#include <shogun/statistical_testing/internals/StreamingDataFetcher.h>
+#include <shogun/statistical_testing/internals/DataFetcherFactory.h>
+#include <gtest/gtest.h>
+
+using namespace shogun;
+using namespace internal;
+
+TEST(DataFetcherFactory, get_instance)
+{
+	const index_t dim=1;
+	const index_t num_vec=1;
+
+	SGMatrix<float64_t> data_p(dim, num_vec);
+	data_p(0, 0)=0;
+
+	using feat_type=CDenseFeatures<float64_t>;
+	auto feats_p=new feat_type(data_p);
+
+	std::unique_ptr<DataFetcher> fetcher(DataFetcherFactory::get_instance(feats_p));
+	ASSERT_TRUE(strcmp(fetcher->get_name(), "DataFetcher")==0);
+
+	CStreamingDenseFeatures<float64_t> *streaming_p=new CStreamingDenseFeatures<float64_t>(feats_p);
+	SG_REF(streaming_p);
+
+	std::unique_ptr<DataFetcher> streaming_fetcher(DataFetcherFactory::get_instance(streaming_p));
+	ASSERT_TRUE(strcmp(streaming_fetcher->get_name(), "StreamingDataFetcher")==0);
+}

tests/unit/statistical_testing/internals/DataFetcher_unittest.cc

@@ -0,0 +1,140 @@
+/*
+ * 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.
+ */
+
+#include <memory>
+#include <algorithm>
+#include <shogun/lib/SGMatrix.h>
+#include <shogun/features/Features.h>
+#include <shogun/features/DenseFeatures.h>
+#include <shogun/statistical_testing/internals/DataFetcher.h>
+#include <gtest/gtest.h>
+
+using namespace shogun;
+using namespace internal;
+
+TEST(DataFetcher, full_data)
+{
+	const index_t dim=3;
+	const index_t num_vec=8;
+
+	SGMatrix<float64_t> data_p(dim, num_vec);
+	std::iota(data_p.matrix, data_p.matrix+dim*num_vec, 0);
+
+	using feat_type=CDenseFeatures<float64_t>;
+	auto feats_p=new feat_type(data_p);
+
+	DataFetcher fetcher(feats_p);
+
+	fetcher.start();
+	auto curr=fetcher.next();
+	ASSERT_TRUE(curr!=nullptr);
+
+	auto tmp=dynamic_cast<feat_type*>(curr.get());
+	ASSERT_TRUE(tmp!=nullptr);
+
+	curr=fetcher.next();
+	ASSERT_TRUE(curr==nullptr);
+	fetcher.end();
+}
+
+TEST(DataFetcher, block_data)
+{
+	const index_t dim=3;
+	const index_t num_vec=8;
+	const index_t blocksize=2;
+	const index_t num_blocks_per_burst=2;
+
+	SGMatrix<float64_t> data_p(dim, num_vec);
+	std::iota(data_p.matrix, data_p.matrix+dim*num_vec, 0);
+
+	using feat_type=CDenseFeatures<float64_t>;
+	auto feats_p=new feat_type(data_p);
+
+	DataFetcher fetcher(feats_p);
+
+	fetcher.fetch_blockwise()
+		.with_blocksize(blocksize)
+		.with_num_blocks_per_burst(num_blocks_per_burst);
+
+	fetcher.start();
+	auto curr=fetcher.next();
+	ASSERT_TRUE(curr!=nullptr);
+	while (curr!=nullptr)
+	{
+		auto tmp=dynamic_cast<feat_type*>(curr.get());
+		ASSERT_TRUE(tmp!=nullptr);
+		ASSERT_TRUE(tmp->get_num_vectors()==blocksize*num_blocks_per_burst);
+		curr=fetcher.next();
+	}
+	fetcher.end();
+}
+
+TEST(DataFetcher, reset_functionality)
+{
+	const index_t dim=3;
+	const index_t num_vec=8;
+	const index_t blocksize=2;
+	const index_t num_blocks_per_burst=2;
+
+	SGMatrix<float64_t> data_p(dim, num_vec);
+	std::iota(data_p.matrix, data_p.matrix+dim*num_vec, 0);
+
+	using feat_type=CDenseFeatures<float64_t>;
+	auto feats_p=new feat_type(data_p);
+
+	DataFetcher fetcher(feats_p);
+
+	fetcher.start();
+	auto curr=fetcher.next();
+	ASSERT_TRUE(curr!=nullptr);
+
+	auto tmp=dynamic_cast<feat_type*>(curr.get());
+	ASSERT_TRUE(tmp!=nullptr);
+
+	curr=fetcher.next();
+	ASSERT_TRUE(curr==nullptr);
+
+	fetcher.reset();
+	fetcher.fetch_blockwise()
+		.with_blocksize(blocksize)
+		.with_num_blocks_per_burst(num_blocks_per_burst);
+
+	fetcher.start();
+	curr=fetcher.next();
+	ASSERT_TRUE(curr!=nullptr);
+	while (curr!=nullptr)
+	{
+		tmp=dynamic_cast<feat_type*>(curr.get());
+		ASSERT_TRUE(tmp!=nullptr);
+		ASSERT_TRUE(tmp->get_num_vectors()==blocksize*num_blocks_per_burst);
+		curr=fetcher.next();
+	}
+	fetcher.end();
+}

tests/unit/statistical_testing/DataManager_unittest.cc → tests/unit/statistical_testing/internals/DataManager_unittest.cc

@@ -41,7 +41,7 @@
 using namespace shogun;
 using namespace internal;
 
-TEST(DataManager, whole_data_one_distribution_normal_feats)
+TEST(DataManager, full_data_one_distribution_normal_feats)
 {
 	const index_t dim=3;
 	const index_t num_vec=8;
@@ -71,7 +71,7 @@ TEST(DataManager, whole_data_one_distribution_normal_feats)
 	mgr.end();
 }
 
-TEST(DataManager, whole_data_one_distribution_streaming_feats)
+TEST(DataManager, full_data_one_distribution_streaming_feats)
 {
 	const index_t dim=3;
 	const index_t num_vec=8;
@@ -104,7 +104,7 @@ TEST(DataManager, whole_data_one_distribution_streaming_feats)
 	mgr.end();
 }
 
-TEST(DataManager, whole_data_two_distributions_normal_feats)
+TEST(DataManager, full_data_two_distributions_normal_feats)
 {
 	const index_t dim=3;
 	const index_t num_vec=8;
@@ -142,7 +142,7 @@ TEST(DataManager, whole_data_two_distributions_normal_feats)
 	ASSERT_TRUE(next_burst.empty());
 }
 
-TEST(DataManager, whole_data_two_distributions_streaming_feats)
+TEST(DataManager, full_data_two_distributions_streaming_feats)
 {
 	const index_t dim=3;
 	const index_t num_vec=8;

tests/unit/statistical_testing/internals/KernelManager_unittest.cc

@@ -0,0 +1,69 @@
+/*
+ * 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.
+ */
+
+#include <shogun/lib/SGMatrix.h>
+#include <shogun/features/Features.h>
+#include <shogun/features/DenseFeatures.h>
+#include <shogun/kernel/GaussianKernel.h>
+#include <shogun/statistical_testing/internals/KernelManager.h>
+#include <gtest/gtest.h>
+
+using namespace shogun;
+using namespace internal;
+
+TEST(KernelManager, store_precompute_restore)
+{
+	const index_t dim=1;
+	const index_t num_vec=1;
+	const index_t num_kernels=1;
+
+	SGMatrix<float64_t> data_p(dim, num_vec);
+	data_p(0, 0)=0;
+
+	auto feats=new CDenseFeatures<float64_t>(data_p);
+	auto kernel=new CGaussianKernel();
+	kernel->set_width(0.5);
+
+	KernelManager kernel_mgr(num_kernels);
+	const KernelManager& const_kernel_mgr=kernel_mgr;
+
+	kernel_mgr.kernel_at(0)=kernel;
+	ASSERT_TRUE(const_kernel_mgr.kernel_at(0)->get_kernel_type()==K_GAUSSIAN);
+
+	CKernel* k=const_kernel_mgr.kernel_at(0);
+	k->init(feats, feats);
+	kernel_mgr.precompute_kernel_at(0);
+	ASSERT_TRUE(const_kernel_mgr.kernel_at(0)!=kernel);
+	ASSERT_TRUE(const_kernel_mgr.kernel_at(0)->get_kernel_type()==K_CUSTOM);
+
+	kernel_mgr.restore_kernel_at(0);
+	ASSERT_TRUE(const_kernel_mgr.kernel_at(0)==kernel);
+	ASSERT_TRUE(const_kernel_mgr.kernel_at(0)->get_kernel_type()==K_GAUSSIAN);
+}