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* FullPivLU: replace "remaining==0" termination condition (from Golub) by a fuzzy compare
(fixes lu test failures when testing solve()) * LU test: set appropriate threshold and limit the number of times that a specially tricky test is run. (fixes lu test failures when testing rank()). * Tests: rename createRandomMatrixOfRank to createRandomProjectionOfRank
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@@ -404,6 +404,7 @@ FullPivLU<MatrixType>& FullPivLU<MatrixType>::compute(const MatrixType& matrix)
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m_nonzero_pivots = size; // the generic case is that in which all pivots are nonzero (invertible case)
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m_maxpivot = RealScalar(0);
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RealScalar cutoff(0);
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for(int k = 0; k < size; ++k)
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{
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@@ -418,8 +419,11 @@ FullPivLU<MatrixType>& FullPivLU<MatrixType>::compute(const MatrixType& matrix)
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row_of_biggest_in_corner += k; // correct the values! since they were computed in the corner,
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col_of_biggest_in_corner += k; // need to add k to them.
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// when k==0, biggest_in_corner is the biggest coeff absolute value in the original matrix
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if(k == 0) cutoff = biggest_in_corner * NumTraits<Scalar>::epsilon();
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// if the pivot (hence the corner) is exactly zero, terminate to avoid generating nan/inf values
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if(biggest_in_corner == RealScalar(0))
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if(ei_abs(biggest_in_corner) < cutoff)
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{
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// before exiting, make sure to initialize the still uninitialized transpositions
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// in a sane state without destroying what we already have.
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