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Add scaling in JacobiSVD to avoid overflows
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@ -832,6 +832,11 @@ JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsig
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if(m_computeThinV) m_matrixV.setIdentity(m_cols, m_diagSize);
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}
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// Scaling factor to reducover/under-flows
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RealScalar scale = m_workMatrix.cwiseAbs().maxCoeff();
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if(scale==RealScalar(0)) scale = RealScalar(1);
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m_workMatrix /= scale;
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/*** step 2. The main Jacobi SVD iteration. ***/
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bool finished = false;
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@ -880,6 +885,8 @@ JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsig
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if(computeU() && (a!=RealScalar(0))) m_matrixU.col(i) *= m_workMatrix.coeff(i,i)/a;
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}
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m_singularValues *= scale;
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/*** step 4. Sort singular values in descending order and compute the number of nonzero singular values ***/
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m_nonzeroSingularValues = m_diagSize;
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@ -285,7 +285,7 @@ void jacobisvd_inf_nan()
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// Regression test for bug 286: JacobiSVD loops indefinitely with some
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// matrices containing denormal numbers.
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void jacobisvd_bug286()
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void jacobisvd_underoverflow()
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{
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#if defined __INTEL_COMPILER
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// shut up warning #239: floating point underflow
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@ -300,6 +300,15 @@ void jacobisvd_bug286()
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#endif
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JacobiSVD<Matrix2d> svd;
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svd.compute(M); // just check we don't loop indefinitely
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// Check for overflow:
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Matrix3d M3;
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M3 << 4.4331978442502944e+307, -5.8585363752028680e+307, 6.4527017443412964e+307,
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3.7841695601406358e+307, 2.4331702789740617e+306, -3.5235707140272905e+307,
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-8.7190887618028355e+307, -7.3453213709232193e+307, -2.4367363684472105e+307;
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JacobiSVD<Matrix3d> svd3;
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svd3.compute(M3); // just check we don't loop indefinitely
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}
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void jacobisvd_preallocate()
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@ -398,5 +407,5 @@ void test_jacobisvd()
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CALL_SUBTEST_9( jacobisvd_preallocate() );
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// Regression check for bug 286
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CALL_SUBTEST_2( jacobisvd_bug286() );
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CALL_SUBTEST_2( jacobisvd_underoverflow() );
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}
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