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BDCSVD: Streamline compute() and copyUV()
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@ -139,7 +139,7 @@ public:
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void setSwitchSize(int s)
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{
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eigen_assert(s>3 && "BDCSVD the size of the algo switch has to be greater than 4");
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eigen_assert(s>3 && "BDCSVD the size of the algo switch has to be greater than 3");
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algoswap = s;
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}
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@ -201,7 +201,7 @@ private:
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void deflation43(Index firstCol, Index shift, Index i, Index size);
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void deflation44(Index firstColu , Index firstColm, Index firstRowW, Index firstColW, Index i, Index j, Index size);
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void deflation(Index firstCol, Index lastCol, Index k, Index firstRowW, Index firstColW, Index shift);
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void copyUV(MatrixXr naiveU, MatrixXr naiveV, MatrixX householderU, MatrixX houseHolderV);
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void copyUV(MatrixX householderU, MatrixX houseHolderV);
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protected:
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MatrixXr m_naiveU, m_naiveV;
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@ -282,15 +282,8 @@ BDCSVD<MatrixType>::compute(const MatrixType& matrix, unsigned int computationOp
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internal::UpperBidiagonalization<MatrixX > bid(copy);
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//**** step 2 Divide
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// this is ugly and has to be redone (care of complex cast)
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MatrixXr temp;
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temp = bid.bidiagonal().toDenseMatrix().transpose();
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m_computed.setZero();
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for (int i=0; i<this->m_diagSize - 1; i++) {
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m_computed(i, i) = temp(i, i);
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m_computed(i + 1, i) = temp(i + 1, i);
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}
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m_computed(this->m_diagSize - 1, this->m_diagSize - 1) = temp(this->m_diagSize - 1, this->m_diagSize - 1);
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m_computed.topRows(this->m_diagSize) = bid.bidiagonal().toDenseMatrix().transpose();
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m_computed.template bottomRows<1>().setZero();
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divide(0, this->m_diagSize - 1, 0, 0, 0);
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//**** step 3 copy
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@ -307,45 +300,31 @@ BDCSVD<MatrixType>::compute(const MatrixType& matrix, unsigned int computationOp
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break;
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}
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}
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copyUV(m_naiveV, m_naiveU, bid.householderU(), bid.householderV());
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copyUV(bid.householderU(), bid.householderV());
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this->m_isInitialized = true;
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return *this;
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}// end compute
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// TODO: this function should accept householder sequences to save converting them to matrix
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template<typename MatrixType>
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void BDCSVD<MatrixType>::copyUV(MatrixXr naiveU, MatrixXr naiveV, MatrixX householderU, MatrixX householderV){
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void BDCSVD<MatrixType>::copyUV(MatrixX householderU, MatrixX householderV){
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// Note exchange of U and V: m_matrixU is set from m_naiveV and vice versa
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if (this->computeU()){
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MatrixX temp = MatrixX::Zero(naiveU.rows(), naiveU.cols());
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temp.real() = naiveU;
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if (this->m_computeThinU){
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this->m_matrixU = MatrixX::Identity(householderU.cols(), this->m_nonzeroSingularValues );
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this->m_matrixU.block(0, 0, this->m_diagSize, this->m_nonzeroSingularValues) =
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temp.block(0, 0, this->m_diagSize, this->m_nonzeroSingularValues);
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this->m_matrixU = householderU * this->m_matrixU ;
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}
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else
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{
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this->m_matrixU = MatrixX::Identity(householderU.cols(), householderU.cols());
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this->m_matrixU.block(0, 0, this->m_diagSize, this->m_diagSize) = temp.block(0, 0, this->m_diagSize, this->m_diagSize);
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this->m_matrixU = householderU * this->m_matrixU ;
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}
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Index Ucols = this->m_computeThinU ? this->m_nonzeroSingularValues : householderU.cols();
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this->m_matrixU = MatrixX::Identity(householderU.cols(), Ucols);
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Index blockCols = this->m_computeThinU ? this->m_nonzeroSingularValues : this->m_diagSize;
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this->m_matrixU.block(0, 0, this->m_diagSize, blockCols) =
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m_naiveV.template cast<Scalar>().block(0, 0, this->m_diagSize, blockCols);
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this->m_matrixU = householderU * this->m_matrixU;
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}
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if (this->computeV()){
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MatrixX temp = MatrixX::Zero(naiveV.rows(), naiveV.cols());
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temp.real() = naiveV;
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if (this->m_computeThinV){
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this->m_matrixV = MatrixX::Identity(householderV.cols(),this->m_nonzeroSingularValues );
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this->m_matrixV.block(0, 0, this->m_nonzeroSingularValues, this->m_nonzeroSingularValues) =
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temp.block(0, 0, this->m_nonzeroSingularValues, this->m_nonzeroSingularValues);
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this->m_matrixV = householderV * this->m_matrixV ;
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}
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else
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{
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this->m_matrixV = MatrixX::Identity(householderV.cols(), householderV.cols());
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this->m_matrixV.block(0, 0, this->m_diagSize, this->m_diagSize) = temp.block(0, 0, this->m_diagSize, this->m_diagSize);
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this->m_matrixV = householderV * this->m_matrixV;
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}
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Index Vcols = this->m_computeThinV ? this->m_nonzeroSingularValues : householderV.cols();
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this->m_matrixV = MatrixX::Identity(householderV.cols(), Vcols);
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Index blockCols = this->m_computeThinV ? this->m_nonzeroSingularValues : this->m_diagSize;
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this->m_matrixV.block(0, 0, this->m_diagSize, blockCols) =
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m_naiveU.template cast<Scalar>().block(0, 0, this->m_diagSize, blockCols);
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this->m_matrixV = householderV * this->m_matrixV;
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}
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}
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