1 files changed, 0 insertions, 317 deletions
diff --git a/eigen/test/eigen2/eigen2_sparse_basic.cpp b/eigen/test/eigen2/eigen2_sparse_basic.cpp
deleted file mode 100644
index 0490776..0000000
--- a/eigen/test/eigen2/eigen2_sparse_basic.cpp
+++ /dev/null
@@ -1,317 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "sparse.h"
-
-template<typename SetterType,typename DenseType, typename Scalar, int Options>
-bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
-  typedef SparseMatrix<Scalar,Options> SparseType;
-  {
-    sm.setZero();
-    SetterType w(sm);
-    std::vector<Vector2i> remaining = nonzeroCoords;
-    while(!remaining.empty())
-    {
-      int i = ei_random<int>(0,remaining.size()-1);
-      w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
-      remaining[i] = remaining.back();
-      remaining.pop_back();
-    }
-  }
-  return sm.isApprox(ref);
-}
-
-template<typename SetterType,typename DenseType, typename T>
-bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
-  sm.setZero();
-  std::vector<Vector2i> remaining = nonzeroCoords;
-  while(!remaining.empty())
-  {
-    int i = ei_random<int>(0,remaining.size()-1);
-    sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
-    remaining[i] = remaining.back();
-    remaining.pop_back();
-  }
-  return sm.isApprox(ref);
-}
-
-template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
-{
-  const int rows = ref.rows();
-  const int cols = ref.cols();
-  typedef typename SparseMatrixType::Scalar Scalar;
-  enum { Flags = SparseMatrixType::Flags };
-  
-  double density = std::max(8./(rows*cols), 0.01);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  Scalar eps = 1e-6;
-
-  SparseMatrixType m(rows, cols);
-  DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
-  DenseVector vec1 = DenseVector::Random(rows);
-  Scalar s1 = ei_random<Scalar>();
-
-  std::vector<Vector2i> zeroCoords;
-  std::vector<Vector2i> nonzeroCoords;
-  initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
-  
-  if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
-    return;
-
-  // test coeff and coeffRef
-  for (int i=0; i<(int)zeroCoords.size(); ++i)
-  {
-    VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
-    if(ei_is_same_type<SparseMatrixType,SparseMatrix<Scalar,Flags> >::ret)
-      VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
-  }
-  VERIFY_IS_APPROX(m, refMat);
-
-  m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-  refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-
-  VERIFY_IS_APPROX(m, refMat);
-  /*
-  // test InnerIterators and Block expressions
-  for (int t=0; t<10; ++t)
-  {
-    int j = ei_random<int>(0,cols-1);
-    int i = ei_random<int>(0,rows-1);
-    int w = ei_random<int>(1,cols-j-1);
-    int h = ei_random<int>(1,rows-i-1);
-
-//     VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
-    for(int c=0; c<w; c++)
-    {
-      VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
-      for(int r=0; r<h; r++)
-      {
-//         VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
-      }
-    }
-//     for(int r=0; r<h; r++)
-//     {
-//       VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
-//       for(int c=0; c<w; c++)
-//       {
-//         VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
-//       }
-//     }
-  }
-
-  for(int c=0; c<cols; c++)
-  {
-    VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
-    VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
-  }
-
-  for(int r=0; r<rows; r++)
-  {
-    VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
-    VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
-  }
-  */
-
-  // test SparseSetters
-  // coherent setter
-  // TODO extend the MatrixSetter
-//   {
-//     m.setZero();
-//     VERIFY_IS_NOT_APPROX(m, refMat);
-//     SparseSetter<SparseMatrixType, FullyCoherentAccessPattern> w(m);
-//     for (int i=0; i<nonzeroCoords.size(); ++i)
-//     {
-//       w->coeffRef(nonzeroCoords[i].x(),nonzeroCoords[i].y()) = refMat.coeff(nonzeroCoords[i].x(),nonzeroCoords[i].y());
-//     }
-//   }
-//   VERIFY_IS_APPROX(m, refMat);
-
-  // random setter
-//   {
-//     m.setZero();
-//     VERIFY_IS_NOT_APPROX(m, refMat);
-//     SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
-//     std::vector<Vector2i> remaining = nonzeroCoords;
-//     while(!remaining.empty())
-//     {
-//       int i = ei_random<int>(0,remaining.size()-1);
-//       w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
-//       remaining[i] = remaining.back();
-//       remaining.pop_back();
-//     }
-//   }
-//   VERIFY_IS_APPROX(m, refMat);
-
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
-    #ifdef EIGEN_UNORDERED_MAP_SUPPORT
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-    #ifdef _DENSE_HASH_MAP_H_
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-    #ifdef _SPARSE_HASH_MAP_H_
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-
-    // test fillrand
-    {
-      DenseMatrix m1(rows,cols);
-      m1.setZero();
-      SparseMatrixType m2(rows,cols);
-      m2.startFill();
-      for (int j=0; j<cols; ++j)
-      {
-        for (int k=0; k<rows/2; ++k)
-        {
-          int i = ei_random<int>(0,rows-1);
-          if (m1.coeff(i,j)==Scalar(0))
-            m2.fillrand(i,j) = m1(i,j) = ei_random<Scalar>();
-        }
-      }
-      m2.endFill();
-      VERIFY_IS_APPROX(m2,m1);
-    }
-  
-  // test RandomSetter
-  /*{
-    SparseMatrixType m1(rows,cols), m2(rows,cols);
-    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-    initSparse<Scalar>(density, refM1, m1);
-    {
-      Eigen::RandomSetter<SparseMatrixType > setter(m2);
-      for (int j=0; j<m1.outerSize(); ++j)
-        for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
-          setter(i.index(), j) = i.value();
-    }
-    VERIFY_IS_APPROX(m1, m2);
-  }*/
-//   std::cerr << m.transpose() << "\n\n"  << refMat.transpose() << "\n\n";
-//   VERIFY_IS_APPROX(m, refMat);
-
-  // test basic computations
-  {
-    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM4 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m1(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    SparseMatrixType m4(rows, rows);
-    initSparse<Scalar>(density, refM1, m1);
-    initSparse<Scalar>(density, refM2, m2);
-    initSparse<Scalar>(density, refM3, m3);
-    initSparse<Scalar>(density, refM4, m4);
-
-    VERIFY_IS_APPROX(m1+m2, refM1+refM2);
-    VERIFY_IS_APPROX(m1+m2+m3, refM1+refM2+refM3);
-    VERIFY_IS_APPROX(m3.cwise()*(m1+m2), refM3.cwise()*(refM1+refM2));
-    VERIFY_IS_APPROX(m1*s1-m2, refM1*s1-refM2);
-
-    VERIFY_IS_APPROX(m1*=s1, refM1*=s1);
-    VERIFY_IS_APPROX(m1/=s1, refM1/=s1);
-    
-    VERIFY_IS_APPROX(m1+=m2, refM1+=refM2);
-    VERIFY_IS_APPROX(m1-=m2, refM1-=refM2);
-    
-    VERIFY_IS_APPROX(m1.col(0).eigen2_dot(refM2.row(0)), refM1.col(0).eigen2_dot(refM2.row(0)));
-    
-    refM4.setRandom();
-    // sparse cwise* dense
-    VERIFY_IS_APPROX(m3.cwise()*refM4, refM3.cwise()*refM4);
-//     VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
-  }
-
-  // test innerVector()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    int j0 = ei_random(0,rows-1);
-    int j1 = ei_random(0,rows-1);
-    VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0));
-    VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1));
-    //m2.innerVector(j0) = 2*m2.innerVector(j1);
-    //refMat2.col(j0) = 2*refMat2.col(j1);
-    //VERIFY_IS_APPROX(m2, refMat2);
-  }
-  
-  // test innerVectors()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    int j0 = ei_random(0,rows-2);
-    int j1 = ei_random(0,rows-2);
-    int n0 = ei_random<int>(1,rows-std::max(j0,j1));
-    VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
-    VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
-                     refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
-    //m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0);
-    //refMat2.block(0,j0,rows,n0) = refMat2.block(0,j0,rows,n0) + refMat2.block(0,j1,rows,n0);
-  }
-
-  // test transpose
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
-    VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
-  }
-  
-  // test prune
-  {
-    SparseMatrixType m2(rows, rows);
-    DenseMatrix refM2(rows, rows);
-    refM2.setZero();
-    int countFalseNonZero = 0;
-    int countTrueNonZero = 0;
-    m2.startFill();
-    for (int j=0; j<m2.outerSize(); ++j)
-      for (int i=0; i<m2.innerSize(); ++i)
-      {
-        float x = ei_random<float>(0,1);
-        if (x<0.1)
-        {
-          // do nothing
-        }
-        else if (x<0.5)
-        {
-          countFalseNonZero++;
-          m2.fill(i,j) = Scalar(0);
-        }
-        else
-        {
-          countTrueNonZero++;
-          m2.fill(i,j) = refM2(i,j) = Scalar(1);
-        }
-      }
-    m2.endFill();
-    VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
-    VERIFY_IS_APPROX(m2, refM2);
-    m2.prune(1);
-    VERIFY(countTrueNonZero==m2.nonZeros());
-    VERIFY_IS_APPROX(m2, refM2);
-  }
-}
-
-void test_eigen2_sparse_basic()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_basic(SparseMatrix<double>(8, 8)) );
-    CALL_SUBTEST_2( sparse_basic(SparseMatrix<std::complex<double> >(16, 16)) );
-    CALL_SUBTEST_1( sparse_basic(SparseMatrix<double>(33, 33)) );
-    
-    CALL_SUBTEST_3( sparse_basic(DynamicSparseMatrix<double>(8, 8)) );
-  }
-}