text: /*
   * Copyright (c) The Shogun Machine Learning Toolbox
   * Written (w) 2014 Khaled Nasr
   * 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/config.h>
  
  #ifdef HAVE_LINALG_LIB
  #include <shogun/mathematics/linalg/linalg.h>
  #include <shogun/lib/SGMatrix.h>
  #include <shogun/lib/SGVector.h>
  #include <gtest/gtest.h>
  
  #ifdef HAVE_EIGEN3
  #include <shogun/mathematics/eigen3.h>
  #endif // HAVE_EIGEN3
  
  #ifdef HAVE_VIENNACL
  #include <shogun/lib/GPUMatrix.h>
  #include <shogun/lib/GPUVector.h>
  #endif
  
  using namespace shogun;
  
  #ifdef HAVE_EIGEN3
  TEST(MaxMatrix, eigen3_backend)
  {
  	SGMatrix<float64_t> A(3,3);
  	
  	float64_t a[] = {1, 2, 5, 8, 3, 1, 0, -1, 4};
  	
  	for (int32_t i=0; i<9; i++)
  		A[i] = a[i];
  	
  	for (int32_t i=0; i<9; i++)
  		EXPECT_NEAR(8, linalg::max<linalg::Backend::EIGEN3>(A), 1e-15);
  }
  
  TEST(MaxVector, eigen3_backend)
  {
  	SGVector<float64_t> A(9);
  	
  	float64_t a[] = {1, 2, 5, 8, 3, 1, 0, -1, 4};
  	
  	for (int32_t i=0; i<9; i++)
  		A[i] = a[i];
  	
  	for (int32_t i=0; i<9; i++)
  		EXPECT_NEAR(8, linalg::max<linalg::Backend::EIGEN3>(A), 1e-15);
  }
  #endif // HAVE_EIGEN3
  
  #ifdef HAVE_VIENNACL
  TEST(MaxMatrix, viennacl_backend)
  {
  	CGPUMatrix<float64_t> A(3,3);
  	
  	float64_t a[] = {1, 2, 5, 8, 3, 1, 0, -1, 4};
  	
  	for (int32_t i=0; i<9; i++)
  		A[i] = a[i];
  	
  	for (int32_t i=0; i<9; i++)
  		EXPECT_NEAR(8, linalg::max<linalg::Backend::VIENNACL>(A), 1e-15);
  }
  
  TEST(MaxVector, viennacl_backend)
  {
  	CGPUVector<float64_t> A(9);
  	
  	float64_t a[] = {1, 2, 5, 8, 3, 1, 0, -1, 4};
  	
  	for (int32_t i=0; i<9; i++)
  		A[i] = a[i];
  	
  	for (int32_t i=0; i<9; i++)
  		EXPECT_NEAR(8, linalg::max<linalg::Backend::VIENNACL>(A), 1e-15);
  }
  #endif // HAVE_VIENNACL
  
  #endif // HAVE_LINALG_LIB
  