/* * Copyright © 2004 Ondra Kamenik * Copyright © 2019 Dynare Team * * This file is part of Dynare. * * Dynare is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * Dynare is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with Dynare. If not, see . */ #include "fs_tensor.hh" #include "gs_tensor.hh" #include "pascal_triangle.hh" #include "rfs_tensor.hh" #include "sparse_tensor.hh" #include "tl_exception.hh" /* This constructs a fully symmetric tensor as given by the contraction: [g_yⁿ]_α₁…αₙ = [t_yⁿ⁺¹]_α₁…αₙβ [x]^β We go through all columns of output tensor [g] and for each column we cycle through all variables, insert a variable to the column coordinates obtaining a column of tensor [t]. The column is multiplied by an appropriate item of x and added to the column of [g] tensor. */ FFSTensor::FFSTensor(const FFSTensor& t, const ConstVector& x) : FTensor(indor::along_col, IntSequence(t.dimen() - 1, t.nvar()), t.nrows(), calcMaxOffset(t.nvar(), t.dimen() - 1), t.dimen() - 1), nv(t.nvar()) { TL_RAISE_IF(t.dimen() < 1, "Wrong dimension for tensor contraction of FFSTensor"); TL_RAISE_IF(t.nvar() != x.length(), "Wrong number of variables for tensor contraction of FFSTensor"); zeros(); for (Tensor::index to = begin(); to != end(); ++to) for (int i = 0; i < nvar(); i++) { IntSequence from_ind(to.getCoor().insert(i)); Tensor::index from(t, from_ind); addColumn(x[i], t, *from, *to); } } /* This returns number of indices for folded tensor with full symmetry. Let n be a number of variables and d the ⎛n+d-1⎞ dimension dim. Then the number of indices is ⎝ d ⎠. */ int FFSTensor::calcMaxOffset(int nvar, int d) { if (nvar == 0 && d == 0) return 1; if (nvar == 0 && d > 0) return 0; return PascalTriangle::noverk(nvar + d - 1, d); } /* The conversion from sparse tensor is clear. We go through all the tensor and write to the dense what is found. */ FFSTensor::FFSTensor(const FSSparseTensor& t) : FTensor(indor::along_col, IntSequence(t.dimen(), t.nvar()), t.nrows(), calcMaxOffset(t.nvar(), t.dimen()), t.dimen()), nv(t.nvar()) { zeros(); for (const auto& it : t.getMap()) { index ind(*this, it.first); get(it.second.first, *ind) = it.second.second; } } /* The conversion from unfolded copies only columns of respective coordinates. So we go through all the columns in the folded tensor (this), make an index of the unfolded vector from coordinates, and copy the column. */ FFSTensor::FFSTensor(const UFSTensor& ut) : FTensor(indor::along_col, IntSequence(ut.dimen(), ut.nvar()), ut.nrows(), calcMaxOffset(ut.nvar(), ut.dimen()), ut.dimen()), nv(ut.nvar()) { for (index in = begin(); in != end(); ++in) { index src(ut, in.getCoor()); copyColumn(ut, *src, *in); } } /* Here just make a new instance and return the reference. */ std::unique_ptr FFSTensor::unfold() const { return std::make_unique(*this); } /* Incrementing is easy. We have to increment by calling static method UTensor::increment() first. In this way, we have coordinates of unfolded tensor. Then we have to skip to the closest folded index which corresponds to monotonizeing the integer sequence. */ void FFSTensor::increment(IntSequence& v) const { TL_RAISE_IF(v.size() != dimen(), "Wrong input/output vector size in FFSTensor::increment"); UTensor::increment(v, nv); v.monotone(); } /* Decrement calls static FTensor::decrement(). */ void FFSTensor::decrement(IntSequence& v) const { TL_RAISE_IF(v.size() != dimen(), "Wrong input/output vector size in FFSTensor::decrement"); FTensor::decrement(v, nv); } int FFSTensor::getOffset(const IntSequence& v) const { TL_RAISE_IF(v.size() != dimen(), "Wrong input vector size in FFSTensor::getOffset"); return FTensor::getOffset(v, nv); } /* Here we add a general symmetry tensor to the (part of) full symmetry tensor provided that the unique variable of the full symmetry tensor is a stack of variables from the general symmetry tensor. We check for the dimensions and number of variables. Then we calculate a shift of coordinates when going from the general symmetry tensor to full symmetry (it corresponds to shift of coordinates induces by stacking the variables). Then we add the appropriate columns by going through the columns in general symmetry, adding the shift and sorting. */ void FFSTensor::addSubTensor(const FGSTensor& t) { TL_RAISE_IF(dimen() != t.getDims().dimen(), "Wrong dimensions for FFSTensor::addSubTensor"); TL_RAISE_IF(nvar() != t.getDims().getNVS().sum(), "Wrong nvs for FFSTensor::addSubTensor"); // set shift for addSubTensor() /* Code shared with UFSTensor::addSubTensor() */ IntSequence shift_pre(t.getSym().num(), 0); for (int i = 1; i < t.getSym().num(); i++) shift_pre[i] = shift_pre[i - 1] + t.getDims().getNVS()[i - 1]; IntSequence shift(shift_pre.unfold(t.getSym())); for (Tensor::index ind = t.begin(); ind != t.end(); ++ind) { IntSequence c(ind.getCoor()); c.add(1, shift); c.sort(); Tensor::index tar(*this, c); addColumn(t, *ind, *tar); } } // UFSTensor contraction constructor /* This is a bit more straightforward than FFSTensor contraction constructor. We do not add column by column but we do it by submatrices due to regularity of the unfolded tensor. */ UFSTensor::UFSTensor(const UFSTensor& t, const ConstVector& x) : UTensor(indor::along_col, IntSequence(t.dimen() - 1, t.nvar()), t.nrows(), calcMaxOffset(t.nvar(), t.dimen() - 1), t.dimen() - 1), nv(t.nvar()) { TL_RAISE_IF(t.dimen() < 1, "Wrong dimension for tensor contraction of UFSTensor"); TL_RAISE_IF(t.nvar() != x.length(), "Wrong number of variables for tensor contraction of UFSTensor"); zeros(); for (int i = 0; i < ncols(); i++) { ConstTwoDMatrix tpart(t, i * nvar(), nvar()); Vector outcol {getCol(i)}; tpart.multaVec(outcol, x); } } /* Here we convert folded full symmetry tensor to unfolded. We copy all columns of folded tensor, and then call unfoldData(). */ UFSTensor::UFSTensor(const FFSTensor& ft) : UTensor(indor::along_col, IntSequence(ft.dimen(), ft.nvar()), ft.nrows(), calcMaxOffset(ft.nvar(), ft.dimen()), ft.dimen()), nv(ft.nvar()) { for (index src = ft.begin(); src != ft.end(); ++src) { index in(*this, src.getCoor()); copyColumn(ft, *src, *in); } unfoldData(); } std::unique_ptr UFSTensor::fold() const { return std::make_unique(*this); } // UFSTensor increment and decrement /* Here we just call UTensor respective static methods. */ void UFSTensor::increment(IntSequence& v) const { TL_RAISE_IF(v.size() != dimen(), "Wrong input/output vector size in UFSTensor::increment"); UTensor::increment(v, nv); } void UFSTensor::decrement(IntSequence& v) const { TL_RAISE_IF(v.size() != dimen(), "Wrong input/output vector size in UFSTensor::decrement"); UTensor::decrement(v, nv); } int UFSTensor::getOffset(const IntSequence& v) const { TL_RAISE_IF(v.size() != dimen(), "Wrong input vector size in UFSTensor::getOffset"); return UTensor::getOffset(v, nv); } /* This is very similar to FFSTensor::addSubTensor(). The only difference is the addition. We go through all columns in the full symmetry tensor and cancel the shift. If the coordinates after the cancellation are positive, we find the column in the general symmetry tensor, and add it. */ void UFSTensor::addSubTensor(const UGSTensor& t) { TL_RAISE_IF(dimen() != t.getDims().dimen(), "Wrong dimensions for UFSTensor::addSubTensor"); TL_RAISE_IF(nvar() != t.getDims().getNVS().sum(), "Wrong nvs for UFSTensor::addSubTensor"); // set shift for addSubTensor() /* Code shared with FFSTensor::addSubTensor() */ IntSequence shift_pre(t.getSym().num(), 0); for (int i = 1; i < t.getSym().num(); i++) shift_pre[i] = shift_pre[i - 1] + t.getDims().getNVS()[i - 1]; IntSequence shift(shift_pre.unfold(t.getSym())); for (Tensor::index tar = begin(); tar != end(); ++tar) { IntSequence c(tar.getCoor()); c.sort(); c.add(-1, shift); if (c.isPositive() && c.less(t.getDims().getNVX())) { Tensor::index from(t, c); addColumn(t, *from, *tar); } } } /* Here we go through all columns, find a column of folded index, and then copy the column data. Finding the index is done by sorting the integer sequence. */ void UFSTensor::unfoldData() { for (index in = begin(); in != end(); ++in) { IntSequence v(in.getCoor()); v.sort(); copyColumn(*index(*this, v), *in); } }