366 lines
11 KiB
C++
366 lines
11 KiB
C++
// Copyright 2004, Ondra Kamenik
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#include "kord_exception.hh"
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#include "korder.hh"
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PLUMatrix::PLUMatrix(const PLUMatrix &plu)
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: TwoDMatrix(plu), inv(plu.inv), ipiv(new lapack_int[nrows()])
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{
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memcpy(ipiv, plu.ipiv, nrows()*sizeof(lapack_int));
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}
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/* Here we set |ipiv| and |inv| members of the |PLUMatrix| depending on
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its content. It is assumed that subclasses will call this method at
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the end of their constructors. */
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void
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PLUMatrix::calcPLU()
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{
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lapack_int info;
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lapack_int rows = nrows(), lda = ld;
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inv = (const Vector &) getData();
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dgetrf(&rows, &rows, inv.base(), &lda, ipiv, &info);
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}
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/* Here we just call the LAPACK machinery to multiply by the inverse. */
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void
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PLUMatrix::multInv(TwoDMatrix &m) const
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{
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KORD_RAISE_IF(m.nrows() != ncols(),
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"The matrix is not square in PLUMatrix::multInv");
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lapack_int info;
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lapack_int lda = ld;
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lapack_int mcols = m.ncols();
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lapack_int mrows = m.nrows();
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lapack_int ldb = m.getLD();
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double *mbase = m.getData().base();
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dgetrs("N", &mrows, &mcols, inv.base(), &lda, ipiv,
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mbase, &ldb, &info);
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KORD_RAISE_IF(info != 0,
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"Info!=0 in PLUMatrix::multInv");
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}
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/* Here we construct the matrix $A$. Its dimension is |ny|, and it is
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$$A=\left[f_{y}\right]+
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\left[0 \left[f_{y^{**}_+}\right]\cdot\left[g^{**}_{y^*}\right] 0\right]$$,
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where the first zero spans |nstat| columns, and last zero spans
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|nforw| columns. */
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MatrixA::MatrixA(const FSSparseTensor &f, const IntSequence &ss,
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const TwoDMatrix &gy, const PartitionY &ypart)
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: PLUMatrix(ypart.ny())
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{
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zeros();
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IntSequence c{1};
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FGSTensor f_y(f, ss, c, TensorDimens(ss, c));
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add(1.0, f_y);
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ConstTwoDMatrix gss_ys(ypart.nstat+ypart.npred, ypart.nyss(), gy);
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c[0] = 0;
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FGSTensor f_yss(f, ss, c, TensorDimens(ss, c));
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TwoDMatrix sub(*this, ypart.nstat, ypart.nys());
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sub.multAndAdd(ConstTwoDMatrix(f_yss), gss_ys);
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calcPLU();
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}
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/* Here we construct the matrix $S$. Its dimension is |ny|, and it is
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$$S=\left[f_{y}\right]+
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\left[0\quad\left[f_{y^{**}_+}\right]\cdot\left[g^{**}_{y^*}\right]\quad
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0\right]+ \left[0\quad 0\quad\left[f_{y^{**}_+}\right]\right]$$
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It is, in fact, the matrix $A$ plus the third summand. The first zero
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in the summand spans |nstat| columns, the second zero spans |npred|
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columns. */
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MatrixS::MatrixS(const FSSparseTensor &f, const IntSequence &ss,
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const TwoDMatrix &gy, const PartitionY &ypart)
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: PLUMatrix(ypart.ny())
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{
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zeros();
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IntSequence c{1};
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FGSTensor f_y(f, ss, c, TensorDimens(ss, c));
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add(1.0, f_y);
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ConstTwoDMatrix gss_ys(ypart.nstat+ypart.npred, ypart.nyss(), gy);
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c[0] = 0;
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FGSTensor f_yss(f, ss, c, TensorDimens(ss, c));
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TwoDMatrix sub(*this, ypart.nstat, ypart.nys());
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sub.multAndAdd(ConstTwoDMatrix(f_yss), gss_ys);
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TwoDMatrix sub2(*this, ypart.nstat+ypart.npred, ypart.nyss());
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sub2.add(1.0, f_yss);
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calcPLU();
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}
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// |KOrder| member access method specializations
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/* These are the specializations of container access methods. Nothing
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interesting here. */
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template<>
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ctraits<KOrder::unfold>::Tg& KOrder::g<KOrder::unfold>()
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{
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return _ug;
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}
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template<>
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const ctraits<KOrder::unfold>::Tg& KOrder::g<KOrder::unfold>() const
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{ return _ug;}
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template<>
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ctraits<KOrder::fold>::Tg& KOrder::g<KOrder::fold>()
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{
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return _fg;
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}
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template<>
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const ctraits<KOrder::fold>::Tg& KOrder::g<KOrder::fold>() const
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{ return _fg;}
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template<>
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ctraits<KOrder::unfold>::Tgs& KOrder::gs<KOrder::unfold>()
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{
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return _ugs;
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}
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template<>
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const ctraits<KOrder::unfold>::Tgs& KOrder::gs<KOrder::unfold>() const
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{ return _ugs;}
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template<>
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ctraits<KOrder::fold>::Tgs& KOrder::gs<KOrder::fold>()
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{
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return _fgs;
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}
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template<>
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const ctraits<KOrder::fold>::Tgs& KOrder::gs<KOrder::fold>() const
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{ return _fgs;}
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template<>
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ctraits<KOrder::unfold>::Tgss& KOrder::gss<KOrder::unfold>()
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{
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return _ugss;
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}
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template<>
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const ctraits<KOrder::unfold>::Tgss& KOrder::gss<KOrder::unfold>() const
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{ return _ugss;}
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template<>
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ctraits<KOrder::fold>::Tgss& KOrder::gss<KOrder::fold>()
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{
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return _fgss;
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}
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template<>
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const ctraits<KOrder::fold>::Tgss& KOrder::gss<KOrder::fold>() const
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{ return _fgss;}
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template<>
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ctraits<KOrder::unfold>::TG& KOrder::G<KOrder::unfold>()
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{
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return _uG;
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}
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template<>
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const ctraits<KOrder::unfold>::TG& KOrder::G<KOrder::unfold>() const
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{ return _uG;}
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template<>
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ctraits<KOrder::fold>::TG& KOrder::G<KOrder::fold>()
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{
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return _fG;
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}
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template<>
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const ctraits<KOrder::fold>::TG& KOrder::G<KOrder::fold>() const
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{ return _fG;}
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template<>
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ctraits<KOrder::unfold>::TZstack& KOrder::Zstack<KOrder::unfold>()
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{
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return _uZstack;
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}
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template<>
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const ctraits<KOrder::unfold>::TZstack& KOrder::Zstack<KOrder::unfold>() const
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{ return _uZstack;}
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template<>
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ctraits<KOrder::fold>::TZstack& KOrder::Zstack<KOrder::fold>()
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{
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return _fZstack;
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}
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template<>
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const ctraits<KOrder::fold>::TZstack& KOrder::Zstack<KOrder::fold>() const
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{ return _fZstack;}
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template<>
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ctraits<KOrder::unfold>::TGstack& KOrder::Gstack<KOrder::unfold>()
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{
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return _uGstack;
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}
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template<>
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const ctraits<KOrder::unfold>::TGstack& KOrder::Gstack<KOrder::unfold>() const
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{ return _uGstack;}
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template<>
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ctraits<KOrder::fold>::TGstack& KOrder::Gstack<KOrder::fold>()
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{
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return _fGstack;
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}
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template<>
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const ctraits<KOrder::fold>::TGstack& KOrder::Gstack<KOrder::fold>() const
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{ return _fGstack;}
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template<>
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ctraits<KOrder::unfold>::Tm& KOrder::m<KOrder::unfold>()
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{
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return _um;
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}
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template<>
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const ctraits<KOrder::unfold>::Tm& KOrder::m<KOrder::unfold>() const
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{ return _um;}
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template<>
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ctraits<KOrder::fold>::Tm& KOrder::m<KOrder::fold>()
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{
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return _fm;
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}
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template<>
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const ctraits<KOrder::fold>::Tm& KOrder::m<KOrder::fold>() const
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{ return _fm;}
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/* Here is the constructor of the |KOrder| class. We pass what we have
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to. The partitioning of the $y$ vector, a sparse container with model
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derivatives, then the first order approximation, these are $g_y$ and
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$g_u$ matrices, and covariance matrix of exogenous shocks |v|.
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We build the members, it is nothing difficult. Note that we do not make
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a physical copy of sparse tensors, so during running the class, the
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outer world must not change them.
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In the body, we have to set |nvs| array, and initialize $g$ and $G$
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containers to comply to preconditions of |performStep|. */
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KOrder::KOrder(int num_stat, int num_pred, int num_both, int num_forw,
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const TensorContainer<FSSparseTensor> &fcont,
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const TwoDMatrix &gy, const TwoDMatrix &gu, const TwoDMatrix &v,
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Journal &jr)
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: ypart(num_stat, num_pred, num_both, num_forw),
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ny(ypart.ny()), nu(gu.ncols()), maxk(fcont.getMaxDim()),
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nvs{ypart.nys(), nu, nu, 1},
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_ug(4), _fg(4), _ugs(4), _fgs(4), _ugss(4), _fgss(4),
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_uG(4), _fG(4),
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_uZstack(&_uG, ypart.nyss(), &_ug, ny, ypart.nys(), nu),
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_fZstack(&_fG, ypart.nyss(), &_fg, ny, ypart.nys(), nu),
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_uGstack(&_ugs, ypart.nys(), nu),
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_fGstack(&_fgs, ypart.nys(), nu),
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_um(maxk, v), _fm(_um), f(fcont),
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matA(f.get(Symmetry{1}), _uZstack.getStackSizes(), gy, ypart),
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matS(f.get(Symmetry{1}), _uZstack.getStackSizes(), gy, ypart),
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matB(f.get(Symmetry{1}), _uZstack.getStackSizes()),
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journal(jr)
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{
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KORD_RAISE_IF(gy.ncols() != ypart.nys(),
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"Wrong number of columns in gy in KOrder constructor");
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KORD_RAISE_IF(v.ncols() != nu,
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"Wrong number of columns of Vcov in KOrder constructor");
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KORD_RAISE_IF(nu != v.nrows(),
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"Wrong number of rows of Vcov in KOrder constructor");
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KORD_RAISE_IF(maxk < 2,
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"Order of approximation must be at least 2 in KOrder constructor");
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KORD_RAISE_IF(gy.nrows() != ypart.ny(),
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"Wrong number of rows in gy in KOrder constructor");
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KORD_RAISE_IF(gu.nrows() != ypart.ny(),
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"Wrong number of rows in gu in KOrder constructor");
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KORD_RAISE_IF(gu.ncols() != nu,
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"Wrong number of columns in gu in KOrder constructor");
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// put $g_y$ and $g_u$ to the container
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/* Note that $g_\sigma$ is zero by the nature and we do not insert it to
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the container. We insert a new physical copies. */
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auto tgy = std::make_unique<UGSTensor>(ny, TensorDimens(Symmetry{1, 0, 0, 0}, nvs));
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tgy->getData() = gy.getData();
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insertDerivative<unfold>(std::move(tgy));
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auto tgu = std::make_unique<UGSTensor>(ny, TensorDimens(Symmetry{0, 1, 0, 0}, nvs));
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tgu->getData() = gu.getData();
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insertDerivative<unfold>(std::move(tgu));
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// put $G_y$, $G_u$ and $G_{u'}$ to the container
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/* Also note that since $g_\sigma$ is zero, so $G_\sigma$. */
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auto tGy = faaDiBrunoG<unfold>(Symmetry{1, 0, 0, 0});
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G<unfold>().insert(std::move(tGy));
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auto tGu = faaDiBrunoG<unfold>(Symmetry{0, 1, 0, 0});
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G<unfold>().insert(std::move(tGu));
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auto tGup = faaDiBrunoG<unfold>(Symmetry{0, 0, 1, 0});
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G<unfold>().insert(std::move(tGup));
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}
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// |KOrder::sylvesterSolve| unfolded specialization
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/* Here we have an unfolded specialization of |sylvesterSolve|. We
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simply create the sylvester object and solve it. Note that the $g^*_y$
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is not continuous in memory as assumed by the sylvester code, so we
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make a temporary copy and pass it as matrix $C$.
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If the $B$ matrix is empty, in other words there are now forward
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looking variables, then the system becomes $AX=D$ which is solved by
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simple |matA.multInv()|.
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If one wants to display the diagnostic messages from the Sylvester
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module, then after the |sylv.solve()| one needs to call
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|sylv.getParams().print("")|. */
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template<>
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void
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KOrder::sylvesterSolve<KOrder::unfold>(ctraits<unfold>::Ttensor &der) const
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{
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JournalRecordPair pa(journal);
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pa << "Sylvester equation for dimension = " << der.getSym()[0] << endrec;
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if (ypart.nys() > 0 && ypart.nyss() > 0)
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{
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KORD_RAISE_IF(!der.isFinite(),
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"RHS of Sylverster is not finite");
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TwoDMatrix gs_y(gs<unfold>().get(Symmetry{1, 0, 0, 0}));
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GeneralSylvester sylv(der.getSym()[0], ny, ypart.nys(),
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ypart.nstat+ypart.npred,
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matA.getData(), matB.getData(),
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gs_y.getData(), der.getData());
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sylv.solve();
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}
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else if (ypart.nys() > 0 && ypart.nyss() == 0)
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{
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matA.multInv(der);
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}
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}
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// |KOrder::sylvesterSolve| folded specialization
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/* Here is the folded specialization of sylvester. We unfold the right
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hand side. Then we solve it by the unfolded version of
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|sylvesterSolve|, and fold it back and copy to output vector. */
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template<>
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void
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KOrder::sylvesterSolve<KOrder::fold>(ctraits<fold>::Ttensor &der) const
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{
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ctraits<unfold>::Ttensor tmp(der);
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sylvesterSolve<unfold>(tmp);
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ctraits<fold>::Ttensor ftmp(tmp);
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der.getData() = (const Vector &) (ftmp.getData());
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}
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void
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KOrder::switchToFolded()
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{
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JournalRecordPair pa(journal);
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pa << "Switching from unfolded to folded" << endrec;
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int maxdim = g<unfold>().getMaxDim();
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for (int dim = 1; dim <= maxdim; dim++)
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for (auto &si : SymmetrySet(dim, 4))
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{
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if (si[2] == 0 && g<unfold>().check(si))
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{
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auto ft = std::make_unique<FGSTensor>(g<unfold>().get(si));
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insertDerivative<fold>(std::move(ft));
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if (dim > 1)
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{
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gss<unfold>().remove(si);
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gs<unfold>().remove(si);
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g<unfold>().remove(si);
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}
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}
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if (G<unfold>().check(si))
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{
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auto ft = std::make_unique<FGSTensor>(G<unfold>().get(si));
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G<fold>().insert(std::move(ft));
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if (dim > 1)
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{
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G<fold>().remove(si);
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}
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}
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}
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}
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