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@@ -272,7 +272,7 @@ void MatrixExponential<MatrixType>::computeUV(float)
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} else {
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const float maxnorm = 3.925724783138660f;
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m_squarings = std::max(0, (int)ceil(log2(m_l1norm / maxnorm)));
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MatrixType A = *m_M / std::pow(Scalar(2), m_squarings);
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MatrixType A = *m_M / std::pow(Scalar(2), Scalar(m_squarings));
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pade7(A);
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}
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}
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@@ -291,7 +291,7 @@ void MatrixExponential<MatrixType>::computeUV(double)
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} else {
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const double maxnorm = 5.371920351148152;
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m_squarings = std::max(0, (int)ceil(log2(m_l1norm / maxnorm)));
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MatrixType A = *m_M / std::pow(Scalar(2), m_squarings);
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MatrixType A = *m_M / std::pow(Scalar(2), Scalar(m_squarings));
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pade13(A);
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}
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}
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@@ -46,7 +46,7 @@ public:
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* flags \a flags. */
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SkylineInplaceLU(MatrixType& matrix, int flags = 0)
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: /*m_matrix(matrix.rows(), matrix.cols()),*/ m_flags(flags), m_status(0), m_lu(matrix) {
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m_precision = RealScalar(0.1) * Eigen::precision<RealScalar > ();
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m_precision = RealScalar(0.1) * Eigen::dummy_precision<RealScalar > ();
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m_lu.IsRowMajor ? computeRowMajor() : compute();
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}
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@@ -589,7 +589,7 @@ public:
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m_data.squeeze();
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}
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void prune(Scalar reference, RealScalar epsilon = precision<RealScalar > ()) {
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void prune(Scalar reference, RealScalar epsilon = dummy_precision<RealScalar > ()) {
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//TODO
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}
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@@ -206,7 +206,7 @@ public:
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memset(m_lowerProfile, 0, m_diagSize * sizeof (int));
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}
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void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>()) {
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void prune(Scalar reference, RealScalar epsilon = dummy_precision<RealScalar>()) {
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//TODO
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}
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