Initial import of eigen 3.1.1android-cts-4.4_r4android-cts-4.2_r2android-4.4_r1.2.0.1android-4.4_r1.2android-4.4_r1.1.0.1android-4.4_r1.1android-4.4_r1.0.1android-4.4_r1android-4.4_r0.9android-4.4_r0.8android-4.3_r2.3android-4.3_r2.2android-4.3_r2.1android-4.3_r2android-4.3_r1.1android-4.3_r1android-4.3_r0.9.1android-4.3_r0.9android-4.2.2_r1.2android-4.2.2_r1.1android-4.2.2_r1kitkat-releasekitkat-cts-releasejb-mr2.0-releasejb-mr2-releasejb-mr1.1-releasejb-mr1.1-dev

Added a README.android and a MODULE_LICENSE_MPL2 file.
Added empty Android.mk and CleanSpec.mk to optimize Android build.
Non MPL2 license code is disabled in ./Eigen/src/Core/util/NonMPL2.h.
Trying to include such files will lead to an error.

Change-Id: I0e148b7c3e83999bcc4dfaa5809d33bfac2aac32

1 files changed, 395 insertions, 0 deletions

diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp
new file mode 100644
index 000000000..8897a9dca
--- /dev/null
+++ b/test/sparse_basic.cpp
@@ -0,0 +1,395 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// 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 SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
+{
+  typedef typename SparseMatrixType::Index Index;
+
+  const Index rows = ref.rows();
+  const Index 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 = internal::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(internal::is_same<SparseMatrixType,SparseMatrix<Scalar,Flags> >::value)
+      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 = internal::random<int>(0,cols-1);
+    int i = internal::random<int>(0,rows-1);
+    int w = internal::random<int>(1,cols-j-1);
+    int h = internal::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 insert (inner random)
+    {
+      DenseMatrix m1(rows,cols);
+      m1.setZero();
+      SparseMatrixType m2(rows,cols);
+      if(internal::random<int>()%2)
+        m2.reserve(VectorXi::Constant(m2.outerSize(), 2));
+      for (int j=0; j<cols; ++j)
+      {
+        for (int k=0; k<rows/2; ++k)
+        {
+          int i = internal::random<int>(0,rows-1);
+          if (m1.coeff(i,j)==Scalar(0))
+            m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
+        }
+      }
+      m2.finalize();
+      VERIFY_IS_APPROX(m2,m1);
+    }
+
+    // test insert (fully random)
+    {
+      DenseMatrix m1(rows,cols);
+      m1.setZero();
+      SparseMatrixType m2(rows,cols);
+      if(internal::random<int>()%2)
+        m2.reserve(VectorXi::Constant(m2.outerSize(), 2));
+      for (int k=0; k<rows*cols; ++k)
+      {
+        int i = internal::random<int>(0,rows-1);
+        int j = internal::random<int>(0,cols-1);
+        if ((m1.coeff(i,j)==Scalar(0)) && (internal::random<int>()%2))
+          m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
+        else
+        {
+          Scalar v = internal::random<Scalar>();
+          m2.coeffRef(i,j) += v;
+          m1(i,j) += v;
+        }
+      }
+      VERIFY_IS_APPROX(m2,m1);
+    }
+    
+    // test insert (un-compressed)
+    for(int mode=0;mode<4;++mode)
+    {
+      DenseMatrix m1(rows,cols);
+      m1.setZero();
+      SparseMatrixType m2(rows,cols);
+      VectorXi r(VectorXi::Constant(m2.outerSize(), ((mode%2)==0) ? m2.innerSize() : std::max<int>(1,m2.innerSize()/8)));
+      m2.reserve(r);
+      for (int k=0; k<rows*cols; ++k)
+      {
+        int i = internal::random<int>(0,rows-1);
+        int j = internal::random<int>(0,cols-1);
+        if (m1.coeff(i,j)==Scalar(0))
+          m2.insert(i,j) = m1(i,j) = internal::random<Scalar>();
+        if(mode==3)
+          m2.reserve(r);
+      }
+      if(internal::random<int>()%2)
+        m2.makeCompressed();
+      VERIFY_IS_APPROX(m2,m1);
+    }
+
+  // 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.cwiseProduct(m1+m2), refM3.cwiseProduct(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);
+
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.row(0).dot(refM2.row(0)));
+    else
+      VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.col(0).dot(refM2.row(0)));
+
+    VERIFY_IS_APPROX(m1.conjugate(), refM1.conjugate());
+    VERIFY_IS_APPROX(m1.real(), refM1.real());
+
+    refM4.setRandom();
+    // sparse cwise* dense
+    VERIFY_IS_APPROX(m3.cwiseProduct(refM4), refM3.cwiseProduct(refM4));
+//     VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
+  }
+
+  // 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());
+
+    VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
+  }
+
+  // test innerVector()
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
+    SparseMatrixType m2(rows, rows);
+    initSparse<Scalar>(density, refMat2, m2);
+    int j0 = internal::random<int>(0,rows-1);
+    int j1 = internal::random<int>(0,rows-1);
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.row(j0));
+    else
+      VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0));
+
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.row(j0)+refMat2.row(j1));
+    else
+      VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1));
+
+    SparseMatrixType m3(rows,rows);
+    m3.reserve(VectorXi::Constant(rows,rows/2));
+    for(int j=0; j<rows; ++j)
+      for(int k=0; k<j; ++k)
+        m3.insertByOuterInner(j,k) = k+1;
+    for(int j=0; j<rows; ++j)
+    {
+      VERIFY(j==internal::real(m3.innerVector(j).nonZeros()));
+      if(j>0)
+        VERIFY(j==internal::real(m3.innerVector(j).lastCoeff()));
+    }
+    m3.makeCompressed();
+    for(int j=0; j<rows; ++j)
+    {
+      VERIFY(j==internal::real(m3.innerVector(j).nonZeros()));
+      if(j>0)
+        VERIFY(j==internal::real(m3.innerVector(j).lastCoeff()));
+    }
+
+    //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 = internal::random<int>(0,rows-2);
+    int j1 = internal::random<int>(0,rows-2);
+    int n0 = internal::random<int>(1,rows-(std::max)(j0,j1));
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols));
+    else
+      VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
+    if(SparseMatrixType::IsRowMajor)
+      VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
+                      refMat2.block(j0,0,n0,cols)+refMat2.block(j1,0,n0,cols));
+    else
+      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 prune
+  {
+    SparseMatrixType m2(rows, rows);
+    DenseMatrix refM2(rows, rows);
+    refM2.setZero();
+    int countFalseNonZero = 0;
+    int countTrueNonZero = 0;
+    for (int j=0; j<m2.outerSize(); ++j)
+    {
+      m2.startVec(j);
+      for (int i=0; i<m2.innerSize(); ++i)
+      {
+        float x = internal::random<float>(0,1);
+        if (x<0.1)
+        {
+          // do nothing
+        }
+        else if (x<0.5)
+        {
+          countFalseNonZero++;
+          m2.insertBackByOuterInner(j,i) = Scalar(0);
+        }
+        else
+        {
+          countTrueNonZero++;
+          m2.insertBackByOuterInner(j,i) = Scalar(1);
+          if(SparseMatrixType::IsRowMajor)
+            refM2(j,i) = Scalar(1);
+          else
+            refM2(i,j) = Scalar(1);
+        }
+      }
+    }
+    m2.finalize();
+    VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
+    VERIFY_IS_APPROX(m2, refM2);
+    m2.prune(Scalar(1));
+    VERIFY(countTrueNonZero==m2.nonZeros());
+    VERIFY_IS_APPROX(m2, refM2);
+  }
+
+  // test setFromTriplets
+  {
+    typedef Triplet<Scalar,Index> TripletType;
+    std::vector<TripletType> triplets;
+    int ntriplets = rows*cols;
+    triplets.reserve(ntriplets);
+    DenseMatrix refMat(rows,cols);
+    refMat.setZero();
+    for(int i=0;i<ntriplets;++i)
+    {
+      int r = internal::random<int>(0,rows-1);
+      int c = internal::random<int>(0,cols-1);
+      Scalar v = internal::random<Scalar>();
+      triplets.push_back(TripletType(r,c,v));
+      refMat(r,c) += v;
+    }
+    SparseMatrixType m(rows,cols);
+    m.setFromTriplets(triplets.begin(), triplets.end());
+    VERIFY_IS_APPROX(m, refMat);
+  }
+
+  // test triangularView
+  {
+    DenseMatrix refMat2(rows, rows), refMat3(rows, rows);
+    SparseMatrixType m2(rows, rows), m3(rows, rows);
+    initSparse<Scalar>(density, refMat2, m2);
+    refMat3 = refMat2.template triangularView<Lower>();
+    m3 = m2.template triangularView<Lower>();
+    VERIFY_IS_APPROX(m3, refMat3);
+
+    refMat3 = refMat2.template triangularView<Upper>();
+    m3 = m2.template triangularView<Upper>();
+    VERIFY_IS_APPROX(m3, refMat3);
+
+    refMat3 = refMat2.template triangularView<UnitUpper>();
+    m3 = m2.template triangularView<UnitUpper>();
+    VERIFY_IS_APPROX(m3, refMat3);
+
+    refMat3 = refMat2.template triangularView<UnitLower>();
+    m3 = m2.template triangularView<UnitLower>();
+    VERIFY_IS_APPROX(m3, refMat3);
+  }
+  
+  // test selfadjointView
+  if(!SparseMatrixType::IsRowMajor)
+  {
+    DenseMatrix refMat2(rows, rows), refMat3(rows, rows);
+    SparseMatrixType m2(rows, rows), m3(rows, rows);
+    initSparse<Scalar>(density, refMat2, m2);
+    refMat3 = refMat2.template selfadjointView<Lower>();
+    m3 = m2.template selfadjointView<Lower>();
+    VERIFY_IS_APPROX(m3, refMat3);
+  }
+  
+  // test sparseView
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
+    SparseMatrixType m2(rows, rows);
+    initSparse<Scalar>(density, refMat2, m2);
+    VERIFY_IS_APPROX(m2.eval(), refMat2.sparseView().eval());
+  }
+
+  // test diagonal
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
+    SparseMatrixType m2(rows, rows);
+    initSparse<Scalar>(density, refMat2, m2);
+    VERIFY_IS_APPROX(m2.diagonal(), refMat2.diagonal().eval());
+  }
+}
+
+void test_sparse_basic()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    int s = Eigen::internal::random<int>(1,50);
+    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(8, 8)) ));
+    CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, ColMajor>(s, s)) ));
+    CALL_SUBTEST_2(( sparse_basic(SparseMatrix<std::complex<double>, RowMajor>(s, s)) ));
+    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double>(s, s)) ));
+    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,ColMajor,long int>(s, s)) ));
+    CALL_SUBTEST_1(( sparse_basic(SparseMatrix<double,RowMajor,long int>(s, s)) ));
+  }
+}