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do not stop the factorization if one pivot is exactly 0, and return the
index of the first zero pivot if any
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@ -225,7 +225,7 @@ PartialPivLU<MatrixType>::PartialPivLU(const MatrixType& matrix)
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namespace internal {
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/** \internal This is the blocked version of fullpivlu_unblocked() */
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template<typename Scalar, int StorageOrder>
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template<typename Scalar, int StorageOrder, typename PivIndex=DenseIndex>
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struct partial_lu_impl
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{
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// FIXME add a stride to Map, so that the following mapping becomes easier,
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@ -247,51 +247,50 @@ struct partial_lu_impl
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* of columns of the matrix \a lu, and an integer \a nb_transpositions
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* which returns the actual number of transpositions.
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*
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* \returns false if some pivot is exactly zero, in which case the matrix is left with
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* undefined coefficients (to avoid generating inf/nan values). Returns true
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* otherwise.
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* \returns The index of the first pivot which is exactly zero if any, or a negative number otherwise.
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*/
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static bool unblocked_lu(MatrixType& lu, Index* row_transpositions, Index& nb_transpositions)
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static Index unblocked_lu(MatrixType& lu, PivIndex* row_transpositions, PivIndex& nb_transpositions)
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{
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const Index rows = lu.rows();
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const Index size = std::min(lu.rows(),lu.cols());
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const Index cols = lu.cols();
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const Index size = std::min(rows,cols);
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nb_transpositions = 0;
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int first_zero_pivot = -1;
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for(Index k = 0; k < size; ++k)
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{
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Index rrows = rows-k-1;
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Index rcols = cols-k-1;
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Index row_of_biggest_in_col;
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RealScalar biggest_in_corner
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= lu.col(k).tail(rows-k).cwiseAbs().maxCoeff(&row_of_biggest_in_col);
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row_of_biggest_in_col += k;
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if(biggest_in_corner == 0) // the pivot is exactly zero: the matrix is singular
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{
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// end quickly, avoid generating inf/nan values. Although in this unblocked_lu case
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// the result is still valid, there's no need to boast about it because
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// the blocked_lu code can't guarantee the same.
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// before exiting, make sure to initialize the still uninitialized row_transpositions
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// in a sane state without destroying what we already have.
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for(Index i = k; i < size; i++)
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row_transpositions[i] = i;
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return false;
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}
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row_transpositions[k] = row_of_biggest_in_col;
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if(k != row_of_biggest_in_col)
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if(biggest_in_corner != 0)
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{
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lu.row(k).swap(lu.row(row_of_biggest_in_col));
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++nb_transpositions;
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if(k != row_of_biggest_in_col)
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{
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lu.row(k).swap(lu.row(row_of_biggest_in_col));
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++nb_transpositions;
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}
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// FIXME shall we introduce a safe quotient expression in cas 1/lu.coeff(k,k)
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// overflow but not the actual quotient?
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lu.col(k).tail(rrows) /= lu.coeff(k,k);
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}
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else if(first_zero_pivot==-1)
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{
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// the pivot is exactly zero, we record the index of the first pivot which is exactly 0,
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// and continue the factorization such we still have A = PLU
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first_zero_pivot = k;
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}
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if(k<rows-1)
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{
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Index rrows = rows-k-1;
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Index rsize = size-k-1;
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lu.col(k).tail(rrows) /= lu.coeff(k,k);
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lu.bottomRightCorner(rrows,rsize).noalias() -= lu.col(k).tail(rrows) * lu.row(k).tail(rsize);
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}
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lu.bottomRightCorner(rrows,rcols).noalias() -= lu.col(k).tail(rrows) * lu.row(k).tail(rcols);
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}
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return true;
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return first_zero_pivot;
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}
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/** \internal performs the LU decomposition in-place of the matrix represented
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@ -303,15 +302,13 @@ struct partial_lu_impl
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* of columns of the matrix \a lu, and an integer \a nb_transpositions
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* which returns the actual number of transpositions.
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*
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* \returns false if some pivot is exactly zero, in which case the matrix is left with
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* undefined coefficients (to avoid generating inf/nan values). Returns true
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* otherwise.
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* \returns The index of the first pivot which is exactly zero if any, or a negative number otherwise.
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*
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* \note This very low level interface using pointers, etc. is to:
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* 1 - reduce the number of instanciations to the strict minimum
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* 2 - avoid infinite recursion of the instanciations with Block<Block<Block<...> > >
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*/
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static bool blocked_lu(Index rows, Index cols, Scalar* lu_data, Index luStride, Index* row_transpositions, Index& nb_transpositions, Index maxBlockSize=256)
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static Index blocked_lu(Index rows, Index cols, Scalar* lu_data, Index luStride, PivIndex* row_transpositions, PivIndex& nb_transpositions, Index maxBlockSize=256)
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{
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MapLU lu1(lu_data,StorageOrder==RowMajor?rows:luStride,StorageOrder==RowMajor?luStride:cols);
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MatrixType lu(lu1,0,0,rows,cols);
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@ -334,6 +331,7 @@ struct partial_lu_impl
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}
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nb_transpositions = 0;
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int first_zero_pivot = -1;
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for(Index k = 0; k < size; k+=blockSize)
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{
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Index bs = std::min(size-k,blockSize); // actual size of the block
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@ -351,21 +349,15 @@ struct partial_lu_impl
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BlockType A21(lu,k+bs,k,trows,bs);
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BlockType A22(lu,k+bs,k+bs,trows,tsize);
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Index nb_transpositions_in_panel;
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PivIndex nb_transpositions_in_panel;
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// recursively call the blocked LU algorithm on [A11^T A21^T]^T
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// with a very small blocking size:
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if(!blocked_lu(trows+bs, bs, &lu.coeffRef(k,k), luStride,
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row_transpositions+k, nb_transpositions_in_panel, 16))
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{
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// end quickly with undefined coefficients, just avoid generating inf/nan values.
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// before exiting, make sure to initialize the still uninitialized row_transpositions
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// in a sane state without destroying what we already have.
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for(Index i=k; i<size; ++i)
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row_transpositions[i] = i;
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return false;
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}
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nb_transpositions += nb_transpositions_in_panel;
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Index ret = blocked_lu(trows+bs, bs, &lu.coeffRef(k,k), luStride,
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row_transpositions+k, nb_transpositions_in_panel, 16);
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if(ret>=0 && first_zero_pivot==-1)
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first_zero_pivot = k+ret;
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nb_transpositions += nb_transpositions_in_panel;
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// update permutations and apply them to A_0
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for(Index i=k; i<k+bs; ++i)
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{
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@ -385,7 +377,7 @@ struct partial_lu_impl
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A22.noalias() -= A21 * A12;
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}
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}
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return true;
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return first_zero_pivot;
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}
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};
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