don't index Eigen

1 files changed, 0 insertions, 163 deletions

diff --git a/eigen/test/sparse_vector.cpp b/eigen/test/sparse_vector.cpp
deleted file mode 100644
index b3e1dda..0000000
--- a/eigen/test/sparse_vector.cpp
+++ /dev/null
@@ -1,163 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// 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 Scalar,typename StorageIndex> void sparse_vector(int rows, int cols)
-{
-  double densityMat = (std::max)(8./(rows*cols), 0.01);
-  double densityVec = (std::max)(8./(rows), 0.1);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  typedef SparseVector<Scalar,0,StorageIndex> SparseVectorType;
-  typedef SparseMatrix<Scalar,0,StorageIndex> SparseMatrixType;
-  Scalar eps = 1e-6;
-
-  SparseMatrixType m1(rows,rows);
-  SparseVectorType v1(rows), v2(rows), v3(rows);
-  DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-  DenseVector refV1 = DenseVector::Random(rows),
-              refV2 = DenseVector::Random(rows),
-              refV3 = DenseVector::Random(rows);
-
-  std::vector<int> zerocoords, nonzerocoords;
-  initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
-  initSparse<Scalar>(densityMat, refM1, m1);
-
-  initSparse<Scalar>(densityVec, refV2, v2);
-  initSparse<Scalar>(densityVec, refV3, v3);
-
-  Scalar s1 = internal::random<Scalar>();
-
-  // test coeff and coeffRef
-  for (unsigned int i=0; i<zerocoords.size(); ++i)
-  {
-    VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps );
-    //VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 );
-  }
-  {
-    VERIFY(int(nonzerocoords.size()) == v1.nonZeros());
-    int j=0;
-    for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j)
-    {
-      VERIFY(nonzerocoords[j]==it.index());
-      VERIFY(it.value()==v1.coeff(it.index()));
-      VERIFY(it.value()==refV1.coeff(it.index()));
-    }
-  }
-  VERIFY_IS_APPROX(v1, refV1);
-  
-  // test coeffRef with reallocation
-  {
-    SparseVectorType v4(rows);
-    DenseVector v5 = DenseVector::Zero(rows);
-    for(int k=0; k<rows; ++k)
-    {
-      int i = internal::random<int>(0,rows-1);
-      Scalar v = internal::random<Scalar>();
-      v4.coeffRef(i) += v;
-      v5.coeffRef(i) += v;
-    }
-    VERIFY_IS_APPROX(v4,v5);
-  }
-
-  v1.coeffRef(nonzerocoords[0]) = Scalar(5);
-  refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
-  VERIFY_IS_APPROX(v1, refV1);
-
-  VERIFY_IS_APPROX(v1+v2, refV1+refV2);
-  VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3);
-
-  VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2);
-
-  VERIFY_IS_APPROX(v1*=s1, refV1*=s1);
-  VERIFY_IS_APPROX(v1/=s1, refV1/=s1);
-
-  VERIFY_IS_APPROX(v1+=v2, refV1+=refV2);
-  VERIFY_IS_APPROX(v1-=v2, refV1-=refV2);
-
-  VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2));
-  VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2));
-
-  VERIFY_IS_APPROX(m1*v2, refM1*refV2);
-  VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2));
-  {
-    int i = internal::random<int>(0,rows-1);
-    VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i)));
-  }
-
-
-  VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm());
-  
-  VERIFY_IS_APPROX(v1.blueNorm(), refV1.blueNorm());
-
-  // test aliasing
-  VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1));
-  VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval()));
-  VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1));
-  
-  // sparse matrix to sparse vector
-  SparseMatrixType mv1;
-  VERIFY_IS_APPROX((mv1=v1),v1);
-  VERIFY_IS_APPROX(mv1,(v1=mv1));
-  VERIFY_IS_APPROX(mv1,(v1=mv1.transpose()));
-  
-  // check copy to dense vector with transpose
-  refV3.resize(0);
-  VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense()); 
-  VERIFY_IS_APPROX(DenseVector(v1),v1.toDense()); 
-
-  // test conservative resize
-  {
-    std::vector<StorageIndex> inc;
-    if(rows > 3)
-      inc.push_back(-3);
-    inc.push_back(0);
-    inc.push_back(3);
-    inc.push_back(1);
-    inc.push_back(10);
-
-    for(std::size_t i = 0; i< inc.size(); i++) {
-      StorageIndex incRows = inc[i];
-      SparseVectorType vec1(rows);
-      DenseVector refVec1 = DenseVector::Zero(rows);
-      initSparse<Scalar>(densityVec, refVec1, vec1);
-
-      vec1.conservativeResize(rows+incRows);
-      refVec1.conservativeResize(rows+incRows);
-      if (incRows > 0) refVec1.tail(incRows).setZero();
-
-      VERIFY_IS_APPROX(vec1, refVec1);
-
-      // Insert new values
-      if (incRows > 0)
-        vec1.insert(vec1.rows()-1) = refVec1(refVec1.rows()-1) = 1;
-
-      VERIFY_IS_APPROX(vec1, refVec1);
-    }
-  }
-
-}
-
-void test_sparse_vector()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    int r = Eigen::internal::random<int>(1,500), c = Eigen::internal::random<int>(1,500);
-    if(Eigen::internal::random<int>(0,4) == 0) {
-      r = c; // check square matrices in 25% of tries
-    }
-    EIGEN_UNUSED_VARIABLE(r+c);
-
-    CALL_SUBTEST_1(( sparse_vector<double,int>(8, 8) ));
-    CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(r, c) ));
-    CALL_SUBTEST_1(( sparse_vector<double,long int>(r, c) ));
-    CALL_SUBTEST_1(( sparse_vector<double,short>(r, c) ));
-  }
-}
-