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Merge pull request #1132 from allywarner/ComputeSVDBranch
Closes #1134
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‎src/Core/Algorithms/Math/Tests/CMakeLists.txt‎

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@@ -40,6 +40,7 @@ SET(Algorithms_Math_Tests_SRCS
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SelectSubMatrixTests.cc
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GetMatrixSliceAlgoTests.cc
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ComputePCAtest.cc
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ComputeSVDtest.cc
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)
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#SET(Engine_Network_Tests_HEADERS

‎src/Core/Algorithms/Math/Tests/ComputeSVDtest.cc‎

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/*
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For more information, please see: http://software.sci.utah.edu
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The MIT License
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Copyright (c) 2015 Scientific Computing and Imaging Institute,
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University of Utah.
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License for the specific language governing rights and limitations under
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Permission is hereby granted, free of charge, to any person obtaining a
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copy of this software and associated documentation files (the "Software"),
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to deal in the Software without restriction, including without limitation
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the rights to use, copy, modify, merge, publish, distribute, sublicense,
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and/or sell copies of the Software, and to permit persons to whom the
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Software is furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included
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in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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DEALINGS IN THE SOFTWARE.
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*/
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//ComputeSVD algorithm test.
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#include <gtest/gtest.h>
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#include <Core/Datatypes/DenseMatrix.h>
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#include <Core/Datatypes/MatrixComparison.h>
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#include <Testing/Utils/MatrixTestUtilities.h>
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#include <Core/Algorithms/Math/ComputeSVD.h>
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#include <Eigen/SVD>
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using namespace SCIRun::Core::Datatypes;
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using namespace SCIRun::Core::Algorithms::Math;
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using namespace SCIRun::TestUtils;
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namespace
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{
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//Matrix for input.
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DenseMatrixHandle inputMatrix()
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{
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//Hard coded for testing.
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int column1 [12] = {5,4,7,8,10,10,4,6,8,7,9,6};
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int column2 [12] = {7,6,9,8,5,7,9,3,4,5,5,9};
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//Puts the columns into a matrix.
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DenseMatrixHandle inputM(boost::make_shared<DenseMatrix>(12,2));
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for (int i = 0; i < inputM->rows(); i++){
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(*inputM)(i,0) = column1[i];
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(*inputM)(i,1) = column2[i];
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}
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return inputM;
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}
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}
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//Checks if the outputs are correct.
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//U,S,V: U: Left singular matrix, S: Singular values, V: Right singular matrix.
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TEST(ComputeSVDtest, checkOutputs)
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{
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ComputeSVDAlgo algo;
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DenseMatrixHandle m1(inputMatrix());
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DenseMatrixHandle LeftSingularMatrix_U;
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DenseMatrixHandle SingularValues_S;
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DenseMatrixHandle RightSingularMatrix_V;
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//Runs algorithm.
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algo.run(m1,LeftSingularMatrix_U,SingularValues_S,RightSingularMatrix_V);
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//Testing if the results are null.
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ASSERT_NE(nullptr,LeftSingularMatrix_U);
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ASSERT_NE(nullptr,SingularValues_S);
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ASSERT_NE(nullptr,RightSingularMatrix_V);
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//Check the dimensions of the matrices that were created for output.
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//Rows
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ASSERT_EQ(12,LeftSingularMatrix_U->rows());
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ASSERT_EQ(2,SingularValues_S->rows());
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ASSERT_EQ(2,RightSingularMatrix_V->rows());
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//Columns
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ASSERT_EQ(12,LeftSingularMatrix_U->cols());
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ASSERT_EQ(1,SingularValues_S->cols());
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ASSERT_EQ(2,RightSingularMatrix_V->cols());
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//Eigen does not create a diagonal matrix when it computes SVD, it just has a column with the singular values, so we must put it into a diagonal matrix to be able to do some matrix multiplication later.
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DenseMatrix sDiag = Eigen::MatrixXd::Constant(12,2,0);
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sDiag.diagonal() = SingularValues_S->col(0);
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//Multiplying back together and comparing to the centered matrix. They should be equal to each other with some tolerance.
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DenseMatrix product = (*LeftSingularMatrix_U) * sDiag * (*RightSingularMatrix_V).transpose();
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auto expected = *inputMatrix();
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//Comparing each element in the matrices.
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for (int i = 0; i < product.rows(); ++i) {
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for (int j = 0; j < product.cols(); ++j)
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ASSERT_NEAR(expected(i,j), product(i,j), 1e-5);
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}
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}
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//Tests for input with a dimension of zero.
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TEST(ComputeSVDtest, ThrowsForZeroDimensionInput)
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{
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ComputeSVDAlgo algo;
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DenseMatrixHandle m1(new DenseMatrix(5, 0));
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DenseMatrixHandle m2(new DenseMatrix(0, 5));
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DenseMatrixHandle m3(new DenseMatrix(0, 0));
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DenseMatrixHandle LeftSingularMatrix_U;
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DenseMatrixHandle SingularValues_S;
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DenseMatrixHandle RightSingularMatrix_V;
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//Runs algorithm and expects an error.
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EXPECT_ANY_THROW(algo.run(m1,LeftSingularMatrix_U,SingularValues_S,RightSingularMatrix_V));
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EXPECT_ANY_THROW(algo.run(m2,LeftSingularMatrix_U,SingularValues_S,RightSingularMatrix_V));
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EXPECT_ANY_THROW(algo.run(m3,LeftSingularMatrix_U,SingularValues_S,RightSingularMatrix_V));
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}

‎src/Modules/Math/Tests/CMakeLists.txt‎

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AddKnownsToLinearSystemTests.cc
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PortCachingUnitTest.cc
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ComputePCAtest.cc
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ComputeSVDtest.cc
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)
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#SET(Engine_Network_Tests_HEADERS

‎src/Modules/Math/Tests/ComputeSVDtest.cc‎

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/*
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For more information, please see: http://software.sci.utah.edu
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The MIT License
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Copyright (c) 2015 Scientific Computing and Imaging Institute,
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University of Utah.
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License for the specific language governing rights and limitations under
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Permission is hereby granted, free of charge, to any person obtaining a
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copy of this software and associated documentation files (the "Software"),
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to deal in the Software without restriction, including without limitation
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the rights to use, copy, modify, merge, publish, distribute, sublicense,
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and/or sell copies of the Software, and to permit persons to whom the
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Software is furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included
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in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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DEALINGS IN THE SOFTWARE.
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*/
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//ComputeSVD module test.
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#include <Testing/ModuleTestBase/ModuleTestBase.h>
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#include <Modules/Legacy/Math/ComputeSVD.h>
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#include <Core/Datatypes/DenseColumnMatrix.h>
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#include <Core/Datatypes/DenseMatrix.h>
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#include <Testing/Utils/MatrixTestUtilities.h>
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using namespace SCIRun;
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using namespace SCIRun::Modules::Math;
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using namespace SCIRun::Dataflow::Networks;
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using namespace SCIRun::Core::Datatypes;
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using namespace SCIRun::Testing;
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using namespace SCIRun::TestUtils;
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class ComputeSVDtest : public ModuleTest
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{
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};
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//Checks for null input.
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TEST_F(ComputeSVDtest, CheckInputNull)
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{
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auto svdMod = makeModule("ComputeSVD");
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MatrixHandle nullMatrix;
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stubPortNWithThisData(svdMod, 0, nullMatrix);
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EXPECT_THROW(svdMod -> execute(), NullHandleOnPortException);
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}
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//Checks for dense input.
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TEST_F(ComputeSVDtest, CheckInputDense)
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{
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auto svdMod = makeModule("ComputeSVD");
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MatrixHandle denseMatrix = MAKE_DENSE_MATRIX_HANDLE((1,2,5,6)(3,4,7,9)(7,8,9,1)(2,3,5,9));
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stubPortNWithThisData(svdMod, 0, denseMatrix);
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EXPECT_NO_THROW(svdMod -> execute());
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}
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//ComputePCA currently only supports dense input, but we will leave these if we want to change it later.
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//There is a check for this in the algorithm.
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//Checks for column input.
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TEST_F(ComputeSVDtest, CheckInputColumn)
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{
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auto svdMod = makeModule("ComputeSVD");
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DenseColumnMatrixHandle columnInput(new DenseColumnMatrix(5));
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(*columnInput) << 1,2,3,4,5;
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stubPortNWithThisData(svdMod, 0, columnInput);
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EXPECT_NO_THROW(svdMod -> execute());
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}
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//Checks for sparse input.
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TEST_F(ComputeSVDtest, CheckInputSparse)
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{
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auto svdMod = makeModule("ComputeSVD");
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MatrixHandle sparseMatrix = MAKE_SPARSE_MATRIX_HANDLE((0,0,0,0)(5,8,0,0)(0,0,3,0)(0,6,0,0));
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stubPortNWithThisData(svdMod, 0, sparseMatrix);
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EXPECT_NO_THROW(svdMod -> execute());
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}
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