SVGResource *SVGMarkerElement::canvasResource()
{
if (!m_marker) {
m_marker = SVGResourceMarker::create();
}
m_marker->setMarker(static_cast<RenderSVGViewportContainer *>(renderer()));
// Spec: If the attribute is not specified, the effect is as if a
// value of "0" were specified.
if (!m_orientType) {
setOrientToAngle(SVGSVGElement::createSVGAngle());
}
if (orientType() == SVG_MARKER_ORIENT_ANGLE) {
m_marker->setAngle(orientAngle()->value());
} else {
m_marker->setAutoAngle();
}
m_marker->setRef(refX().value(), refY().value());
m_marker->setUseStrokeWidth(markerUnits() == SVG_MARKERUNITS_STROKEWIDTH);
return m_marker.get();
}
KCanvasMarker *SVGMarkerElement::canvasResource()
{
if(!m_marker)
m_marker = static_cast<KCanvasMarker *>(renderingDevice()->createResource(RS_MARKER));
m_marker->setMarker(renderer());
// Spec: If the attribute is not specified, the effect is as if a
// value of "0" were specified.
if(!m_orientType)
{
SVGAngle *angle = SVGSVGElement::createSVGAngle();
angle->setValueAsString(String("0").impl());
setOrientToAngle(angle);
}
if(orientType()->baseVal() == SVG_MARKER_ORIENT_ANGLE)
m_marker->setAngle(orientAngle()->baseVal()->value());
else
m_marker->setAutoAngle();
m_marker->setRef(refX()->baseVal()->value(), refY()->baseVal()->value());
m_marker->setUseStrokeWidth(markerUnits()->baseVal() == SVG_MARKERUNITS_STROKEWIDTH);
double w = markerWidth()->baseVal()->value();
double h = markerHeight()->baseVal()->value();
RefPtr<SVGMatrix> viewBox = viewBoxToViewTransform(w, h);
m_marker->setScale(viewBox->matrix().m11(), viewBox->matrix().m22());
return m_marker;
}
void SVGMarkerElement::parseMappedAttribute(MappedAttribute *attr)
{
const AtomicString& value = attr->value();
if (attr->name() == SVGNames::markerUnitsAttr) {
if (value == "userSpaceOnUse")
markerUnits()->setBaseVal(SVG_MARKERUNITS_USERSPACEONUSE);
}
else if (attr->name() == SVGNames::refXAttr)
refX()->baseVal()->setValueAsString(value.impl());
else if (attr->name() == SVGNames::refYAttr)
refY()->baseVal()->setValueAsString(value.impl());
else if (attr->name() == SVGNames::markerWidthAttr)
markerWidth()->baseVal()->setValueAsString(value.impl());
else if (attr->name() == SVGNames::markerHeightAttr)
markerHeight()->baseVal()->setValueAsString(value.impl());
else if (attr->name() == SVGNames::orientAttr)
{
if (value == "auto")
setOrientToAuto();
else {
SVGAngle *angle = SVGSVGElement::createSVGAngle();
angle->setValueAsString(value.impl());
setOrientToAngle(angle);
}
}
else
{
if(SVGLangSpace::parseMappedAttribute(attr)) return;
if(SVGExternalResourcesRequired::parseMappedAttribute(attr)) return;
if(SVGFitToViewBox::parseMappedAttribute(attr)) return;
SVGStyledElement::parseMappedAttribute(attr);
}
}
bool SVGMarkerElement::selfHasRelativeLengths() const
{
return refX().isRelative()
|| refY().isRelative()
|| markerWidth().isRelative()
|| markerHeight().isRelative();
}
template<typename Scalar> void sparse_llt(int rows, int cols)
{
double density = std::max(8./(rows*cols), 0.01);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
// TODO fix the issue with complex (see SparseLLT::solveInPlace)
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, 0, 0);
for(int i=0; i<rows; ++i)
m2.coeffRef(i,i) = refMat2(i,i) = ei_abs(ei_real(refMat2(i,i)));
refX = refMat2.template selfadjointView<Lower>().llt().solve(b);
if (!NumTraits<Scalar>::IsComplex)
{
x = b;
SparseLLT<SparseMatrix<Scalar> > (m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default");
}
#ifdef EIGEN_CHOLMOD_SUPPORT
x = b;
SparseLLT<SparseMatrix<Scalar> ,Cholmod>(m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod");
#endif
#ifdef EIGEN_TAUCS_SUPPORT
// TODO fix TAUCS with complexes
if (!NumTraits<Scalar>::IsComplex)
{
x = b;
// SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
x = b;
SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
x = b;
SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
}
#endif
}
template<typename Scalar> void sparse_lu(int rows, int cols)
{
double density = std::max(8./(rows*cols), 0.01);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
DenseVector vec1 = DenseVector::Random(rows);
std::vector<Vector2i> zeroCoords;
std::vector<Vector2i> nonzeroCoords;
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords);
FullPivLU<DenseMatrix> refLu(refMat2);
refX = refLu.solve(b);
#if defined(EIGEN_SUPERLU_SUPPORT) || defined(EIGEN_UMFPACK_SUPPORT)
Scalar refDet = refLu.determinant();
#endif
x.setZero();
// // SparseLU<SparseMatrix<Scalar> > (m2).solve(b,&x);
// // VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: default");
#ifdef EIGEN_UMFPACK_SUPPORT
{
// check solve
x.setZero();
SparseLU<SparseMatrix<Scalar>,UmfPack> lu(m2);
VERIFY(lu.succeeded() && "umfpack LU decomposition failed");
VERIFY(lu.solve(b,&x) && "umfpack LU solving failed");
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack");
VERIFY_IS_APPROX(refDet,lu.determinant());
// TODO check the extracted data
//std::cerr << slu.matrixL() << "\n";
}
#endif
#ifdef EIGEN_SUPERLU_SUPPORT
{
x.setZero();
SparseLU<SparseMatrix<Scalar>,SuperLU> slu(m2);
if (slu.succeeded())
{
if (slu.solve(b,&x)) {
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: SuperLU");
}
// std::cerr << refDet << " == " << slu.determinant() << "\n";
if (slu.solve(b, &x, SvTranspose)) {
VERIFY(b.isApprox(m2.transpose() * x, test_precision<Scalar>()));
}
if (slu.solve(b, &x, SvAdjoint)) {
VERIFY(b.isApprox(m2.adjoint() * x, test_precision<Scalar>()));
}
if (!NumTraits<Scalar>::IsComplex) {
VERIFY_IS_APPROX(refDet,slu.determinant()); // FIXME det is not very stable for complex
}
}
}
#endif
}
template<typename Scalar> void sparse_solvers(int rows, int cols)
{
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;
DenseVector vec1 = DenseVector::Random(rows);
std::vector<Vector2i> zeroCoords;
std::vector<Vector2i> nonzeroCoords;
// test triangular solver
{
DenseVector vec2 = vec1, vec3 = vec1;
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
// lower
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().solveTriangular(vec2),
m2.template marked<LowerTriangular>().solveTriangular(vec3));
// lower - transpose
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().transpose().solveTriangular(vec2),
m2.template marked<LowerTriangular>().transpose().solveTriangular(vec3));
// upper
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().solveTriangular(vec2),
m2.template marked<UpperTriangular>().solveTriangular(vec3));
// upper - transpose
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().transpose().solveTriangular(vec2),
m2.template marked<UpperTriangular>().transpose().solveTriangular(vec3));
}
// test LLT
{
// TODO fix the issue with complex (see SparseLLT::solveInPlace)
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSPD(density, refMat2, m2);
refMat2.llt().solve(b, &refX);
typedef SparseMatrix<Scalar,LowerTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
if (!NumTraits<Scalar>::IsComplex)
{
x = b;
SparseLLT<SparseSelfAdjointMatrix> (m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default");
}
#ifdef EIGEN_CHOLMOD_SUPPORT
x = b;
SparseLLT<SparseSelfAdjointMatrix,Cholmod>(m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod");
#endif
if (!NumTraits<Scalar>::IsComplex)
{
#ifdef EIGEN_TAUCS_SUPPORT
x = b;
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
x = b;
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
x = b;
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
#endif
}
}
// test LDLT
if (!NumTraits<Scalar>::IsComplex)
{
// TODO fix the issue with complex (see SparseLDLT::solveInPlace)
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
//initSPD(density, refMat2, m2);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
refMat2 += refMat2.adjoint();
refMat2.diagonal() *= 0.5;
refMat2.ldlt().solve(b, &refX);
typedef SparseMatrix<Scalar,UpperTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
x = b;
SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
if (ldlt.succeeded())
ldlt.solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
}
// test LU
{
static int count = 0;
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords);
LU<DenseMatrix> refLu(refMat2);
refLu.solve(b, &refX);
#if defined(EIGEN_SUPERLU_SUPPORT) || defined(EIGEN_UMFPACK_SUPPORT)
Scalar refDet = refLu.determinant();
#endif
x.setZero();
// // SparseLU<SparseMatrix<Scalar> > (m2).solve(b,&x);
// // VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: default");
#ifdef EIGEN_SUPERLU_SUPPORT
{
x.setZero();
SparseLU<SparseMatrix<Scalar>,SuperLU> slu(m2);
if (slu.succeeded())
{
if (slu.solve(b,&x)) {
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: SuperLU");
}
// std::cerr << refDet << " == " << slu.determinant() << "\n";
if (count==0) {
VERIFY_IS_APPROX(refDet,slu.determinant()); // FIXME det is not very stable for complex
}
}
}
#endif
#ifdef EIGEN_UMFPACK_SUPPORT
{
// check solve
x.setZero();
SparseLU<SparseMatrix<Scalar>,UmfPack> slu(m2);
if (slu.succeeded()) {
if (slu.solve(b,&x)) {
if (count==0) {
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack"); // FIXME solve is not very stable for complex
}
}
VERIFY_IS_APPROX(refDet,slu.determinant());
// TODO check the extracted data
//std::cerr << slu.matrixL() << "\n";
}
}
#endif
count++;
}
}
template<typename Scalar> void sparse_ldlt(int rows, int cols)
{
static bool odd = true;
odd = !odd;
double density = (std::max)(8./(rows*cols), 0.01);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
SparseMatrix<Scalar> m3 = m2 * m2.adjoint(), m3_lo(rows,rows), m3_up(rows,rows);
DenseMatrix refMat3 = refMat2 * refMat2.adjoint();
refX = refMat3.template selfadjointView<Upper>().ldlt().solve(b);
typedef SparseMatrix<Scalar,Upper|SelfAdjoint> SparseSelfAdjointMatrix;
x = b;
SparseLDLT<SparseSelfAdjointMatrix> ldlt(m3);
if (ldlt.succeeded())
ldlt.solveInPlace(x);
else
std::cerr << "warning LDLT failed\n";
VERIFY_IS_APPROX(refMat3.template selfadjointView<Upper>() * x, b);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
#ifdef EIGEN_CHOLMOD_SUPPORT
{
x = b;
SparseLDLT<SparseSelfAdjointMatrix, Cholmod> ldlt2(m3);
if (ldlt2.succeeded())
{
ldlt2.solveInPlace(x);
VERIFY_IS_APPROX(refMat3.template selfadjointView<Upper>() * x, b);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solveInPlace");
x = ldlt2.solve(b);
VERIFY_IS_APPROX(refMat3.template selfadjointView<Upper>() * x, b);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solve");
}
else
std::cerr << "warning LDLT failed\n";
}
#endif
// new Simplicial LLT
// new API
{
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector ref_x(cols), x(cols);
DenseMatrix B = DenseMatrix::Random(rows,cols);
DenseMatrix ref_X(rows,cols), X(rows,cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, 0, 0);
for(int i=0; i<rows; ++i)
m2.coeffRef(i,i) = refMat2(i,i) = internal::abs(internal::real(refMat2(i,i)));
SparseMatrix<Scalar> m3 = m2 * m2.adjoint(), m3_lo(rows,rows), m3_up(rows,rows);
DenseMatrix refMat3 = refMat2 * refMat2.adjoint();
m3_lo.template selfadjointView<Lower>().rankUpdate(m2,0);
m3_up.template selfadjointView<Upper>().rankUpdate(m2,0);
// with a single vector as the rhs
ref_x = refMat3.template selfadjointView<Lower>().llt().solve(b);
x = SimplicialCholesky<SparseMatrix<Scalar>, Lower>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(b);
VERIFY(ref_x.isApprox(x,test_precision<Scalar>()) && "SimplicialCholesky: solve, full storage, lower, single dense rhs");
x = SimplicialCholesky<SparseMatrix<Scalar>, Upper>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(b);
VERIFY(ref_x.isApprox(x,test_precision<Scalar>()) && "SimplicialCholesky: solve, full storage, upper, single dense rhs");
x = SimplicialCholesky<SparseMatrix<Scalar>, Lower>(m3_lo).solve(b);
VERIFY(ref_x.isApprox(x,test_precision<Scalar>()) && "SimplicialCholesky: solve, lower only, single dense rhs");
x = SimplicialCholesky<SparseMatrix<Scalar>, Upper>(m3_up).solve(b);
VERIFY(ref_x.isApprox(x,test_precision<Scalar>()) && "SimplicialCholesky: solve, upper only, single dense rhs");
// with multiple rhs
ref_X = refMat3.template selfadjointView<Lower>().llt().solve(B);
X = SimplicialCholesky<SparseMatrix<Scalar>, Lower>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(B);
VERIFY(ref_X.isApprox(X,test_precision<Scalar>()) && "SimplicialCholesky: solve, full storage, lower, multiple dense rhs");
X = SimplicialCholesky<SparseMatrix<Scalar>, Upper>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(B);
VERIFY(ref_X.isApprox(X,test_precision<Scalar>()) && "SimplicialCholesky: solve, full storage, upper, multiple dense rhs");
// with a sparse rhs
// SparseMatrix<Scalar> spB(rows,cols), spX(rows,cols);
// B.diagonal().array() += 1;
// spB = B.sparseView(0.5,1);
//
// ref_X = refMat3.template selfadjointView<Lower>().llt().solve(DenseMatrix(spB));
//
// spX = SimplicialCholesky<SparseMatrix<Scalar>, Lower>(m3).solve(spB);
// VERIFY(ref_X.isApprox(spX.toDense(),test_precision<Scalar>()) && "LLT: cholmod solve, multiple sparse rhs");
//
// spX = SimplicialCholesky<SparseMatrix<Scalar>, Upper>(m3).solve(spB);
// VERIFY(ref_X.isApprox(spX.toDense(),test_precision<Scalar>()) && "LLT: cholmod solve, multiple sparse rhs");
}
// for(int i=0; i<rows; ++i)
// m2.coeffRef(i,i) = refMat2(i,i) = internal::abs(internal::real(refMat2(i,i)));
//
// refX = refMat2.template selfadjointView<Upper>().ldlt().solve(b);
// typedef SparseMatrix<Scalar,Upper|SelfAdjoint> SparseSelfAdjointMatrix;
// x = b;
// SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
// if (ldlt.succeeded())
// ldlt.solveInPlace(x);
// else
// std::cerr << "warning LDLT failed\n";
//
// VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
}
