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add a blueNorm() function implementing the Blues's stable norm

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algorithm. it is currently provided for experimentation
purpose only.
This commit is contained in:
Gael Guennebaud
2009-07-13 21:14:47 +02:00
parent ddbaaebf9e
commit f5d2317b12
4 changed files with 170 additions and 14 deletions
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33
test/adjoint.cpp
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@@ -76,6 +76,7 @@ template<typename MatrixType> void adjoint(const MatrixType& m)
{
VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(), static_cast<RealScalar>(1));
VERIFY_IS_APPROX(v1.norm(), v1.stableNorm());
VERIFY_IS_APPROX(v1.blueNorm(), v1.stableNorm());
}
// check compatibility of dot and adjoint
@@ -113,15 +114,29 @@ template<typename MatrixType> void adjoint(const MatrixType& m)
void test_adjoint()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( adjoint(Matrix<float, 1, 1>()) );
CALL_SUBTEST( adjoint(Matrix3d()) );
CALL_SUBTEST( adjoint(Matrix4f()) );
CALL_SUBTEST( adjoint(MatrixXcf(4, 4)) );
CALL_SUBTEST( adjoint(MatrixXi(8, 12)) );
CALL_SUBTEST( adjoint(MatrixXf(21, 21)) );
}
// for(int i = 0; i < g_repeat; i++) {
// CALL_SUBTEST( adjoint(Matrix<float, 1, 1>()) );
// CALL_SUBTEST( adjoint(Matrix3d()) );
// CALL_SUBTEST( adjoint(Matrix4f()) );
// CALL_SUBTEST( adjoint(MatrixXcf(4, 4)) );
// CALL_SUBTEST( adjoint(MatrixXi(8, 12)) );
// CALL_SUBTEST( adjoint(MatrixXf(21, 21)) );
// }
// test a large matrix only once
CALL_SUBTEST( adjoint(Matrix<float, 100, 100>()) );
// CALL_SUBTEST( adjoint(Matrix<float, 100, 100>()) );
for(int i = 0; i < g_repeat; i++)
{
std::cerr.precision(20);
int s = 1000000;
double y = 1.131242353467546478463457843445677435233e23 * ei_abs(ei_random<double>());
VectorXf v = VectorXf::Ones(s) * y;
// Vector4f x(v.segment(0,s/4).blueNorm(), v.segment(s/4+1,s/4).blueNorm(),
// v.segment((s/2)+1,s/4).blueNorm(), v.segment(3*s/4+1,s - 3*s/4-1).blueNorm());
// std::cerr << v.norm() << " == " << v.stableNorm() << " == " << v.blueNorm() << " == " << x.norm() << "\n";
std::cerr << v.norm() << "\n" << v.stableNorm() << "\n" << v.blueNorm() << "\n" << ei_sqrt(double(s)) * y << "\n\n\n";
// VectorXd d = VectorXd::Ones(s) * y;//v.cast<double>();
// std::cerr << d.norm() << "\n" << d.stableNorm() << "\n" << d.blueNorm() << "\n" << ei_sqrt(double(s)) * y << "\n\n\n";
}
}