LikelihoodCalculationSingleProcess.cpp

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// SPDX-FileCopyrightText: The Bio++ Development Group
//
// SPDX-License-Identifier: CECILL-2.1
 
#include <list>
#include <numeric>
#include <unordered_map>
 
#include "Bpp/Phyl/Model/MixedTransitionModel.h"
#include "Bpp/Phyl/Model/RateDistribution/ConstantRateDistribution.h"
#include "Bpp/Phyl/Likelihood/DataFlow/BackwardLikelihoodTree.h"
#include "Bpp/Phyl/Likelihood/DataFlow/ForwardLikelihoodTree.h"
#include "Bpp/Phyl/Likelihood/DataFlow/LikelihoodCalculationSingleProcess.h"
#include "Bpp/Phyl/Likelihood/SubstitutionProcessCollectionMember.h"
 
using namespace std;
using namespace bpp;
using namespace numeric;
using namespace Eigen;
 
LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess(
    Context& context,
    std::shared_ptr<const AlignmentDataInterface> sites,
    std::shared_ptr<const SubstitutionProcessInterface> process) :
  AlignedLikelihoodCalculation(context), process_(process), psites_(sites),
  rootPatternLinks_(), rootWeights_(), shrunkData_(),
  processNodes_(), rFreqs_(),
  vRateCatTrees_(), catProb_(), condLikelihoodTree_(0)
{
  if (!process_->getParametrizablePhyloTree())
    throw Exception("LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess: missing tree in SubstitutionProcess.");
  setPatterns_();
  makeProcessNodes_();
 
  // Default Derivate
  setNumericalDerivateConfiguration(0.0001, NumericalDerivativeType::ThreePoints);
}
 
LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess(
    Context& context,
    std::shared_ptr<const SubstitutionProcessInterface> process) :
  AlignedLikelihoodCalculation(context),
  process_(process), psites_(),
  rootPatternLinks_(), rootWeights_(), shrunkData_(),
  processNodes_(), rFreqs_(),
  vRateCatTrees_(), catProb_(), condLikelihoodTree_(0)
{
  if (!process_->getParametrizablePhyloTree())
    throw Exception("LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess: missing tree in SubstitutionProcess.");
 
  makeProcessNodes_();
 
  // Default Derivate
  setNumericalDerivateConfiguration(0.0001, NumericalDerivativeType::ThreePoints);
}
 
LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess(
    std::shared_ptr<CollectionNodes> collection,
    std::shared_ptr<const AlignmentDataInterface> sites,
    size_t nProcess) :
  AlignedLikelihoodCalculation(collection->context()),
  process_(collection->collection().getSubstitutionProcess(nProcess)),
  psites_(sites),
  rootPatternLinks_(), rootWeights_(), shrunkData_(),
  processNodes_(), rFreqs_(),
  vRateCatTrees_(), catProb_(), condLikelihoodTree_(0)
{
  if (!process_->getParametrizablePhyloTree())
    throw Exception("LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess: missing tree in SubstitutionProcess.");
 
  setPatterns_();
  makeProcessNodes_(*collection, nProcess);
 
  // Default Derivate
  setNumericalDerivateConfiguration(0.0001, NumericalDerivativeType::ThreePoints);
}
 
 
LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess(
    std::shared_ptr<CollectionNodes> collection,
    size_t nProcess) :
  AlignedLikelihoodCalculation(collection->context()),
  process_(collection->collection().getSubstitutionProcess(nProcess)),
  psites_(),
  rootPatternLinks_(), rootWeights_(), shrunkData_(),
  processNodes_(), rFreqs_(),
  vRateCatTrees_(), catProb_(), condLikelihoodTree_(0)
{
  makeProcessNodes_(*collection, nProcess);
 
  // Default Derivate
  setNumericalDerivateConfiguration(0.0001, NumericalDerivativeType::ThreePoints);
}
 
 
LikelihoodCalculationSingleProcess::LikelihoodCalculationSingleProcess(const LikelihoodCalculationSingleProcess& lik) :
  AlignedLikelihoodCalculation(lik),
  process_(lik.process_), psites_(lik.psites_),
  rootPatternLinks_(lik.rootPatternLinks_), rootWeights_(), shrunkData_(lik.shrunkData_),
  processNodes_(), rFreqs_(),
  vRateCatTrees_(), catProb_(), condLikelihoodTree_(0)
{
  setPatterns_();
  makeProcessNodes_();
 
  // Default Derivate
  setNumericalDerivateConfiguration(0.0001, NumericalDerivativeType::ThreePoints);
}
 
void LikelihoodCalculationSingleProcess::setPatterns_()
{
  SitePatterns patterns(*psites_, process_->getParametrizablePhyloTree()->getAllLeavesNames());
  shrunkData_       = patterns.getSites();
  rootPatternLinks_ = NumericConstant<PatternType>::create(getContext_(), patterns.getIndices());
  size_t nbSites    = shrunkData_->getNumberOfSites();
  Eigen::RowVectorXi weights(nbSites);
  for (std::size_t i = 0; i < nbSites; i++)
  {
    weights(Eigen::Index(i)) = int(patterns.getWeights()[i]);
  }
  rootWeights_ = SiteWeights::create(getContext_(), std::move(weights));
}
 
void LikelihoodCalculationSingleProcess::makeProcessNodes_()
{
#ifdef DEBUG
  cerr << "LikelihoodCalculationSingleProcess::makeProcessNodes_(){" << endl;
#endif
  // add Independent Parameters
  const auto& paramProc = process_->getIndependentParameters();
 
  for (size_t i = 0; i < paramProc.size(); ++i)
  {
    shareParameter_(ConfiguredParameter::create(getContext_(), paramProc[i]));
  }
 
  // Share dependencies with aliased parameters
  for (size_t i = 0; i < paramProc.size(); i++)
  {
    auto name = paramProc[i].getName();
    auto vs = process_->getAlias(name);
 
    auto dep = dynamic_cast<const ConfiguredParameter*>(&getParameters_()[i])->dependency(0);
    for (const auto& s:vs)
    {
      auto newacp = ConfiguredParameter::create(getContext_(), {dep}, process_->parameter(s));
      shareParameter_(newacp);
      aliasParameters(name, s);
    }
  }
 
  auto spcm = dynamic_pointer_cast<const SubstitutionProcessCollectionMember>(process_);
 
 
  auto& pl2(getParameters_());
 
  // rates node
  std::string suff = spcm ? ("_" + TextTools::toString(spcm->getRateDistributionNumber())) : "";
 
  auto rates = process_->getRateDistribution();
  if (rates && dynamic_pointer_cast<const ConstantRateDistribution>(rates) == nullptr)
    processNodes_.ratesNode_ = ConfiguredParametrizable::createConfigured<DiscreteDistributionInterface, ConfiguredDistribution>(getContext_(), *rates, pl2, suff);
 
  // tree node
  suff = spcm ? ("_" + TextTools::toString(spcm->getTreeNumber())) : "";
  processNodes_.treeNode_ = ProcessTree::makeProcessTree(getContext_(), process_, pl2, suff);
 
  // rootFrequencies node
 
  auto root = process_->getRootFrequencySet();
  if (root)
  {
    suff = spcm ? ("_" + TextTools::toString(spcm->getRootFrequenciesNumber())) : "";
    processNodes_.rootFreqsNode_ = ConfiguredParametrizable::createConfigured<FrequencySetInterface, ConfiguredFrequencySet>(getContext_(), *root, pl2, suff);
  }
 
  auto itE = processNodes_.treeNode_->allEdgesIterator();
  // get any modelNode from the map (only for StateMap)
  for (itE->start(); !itE->end(); itE->next())
  {
    if ((*(*itE))->getModel() != 0)
    {
      processNodes_.modelNode_ = (*(*itE))->getModel();
      break;
    }
  }
  if (!processNodes_.modelNode_)
    throw Exception("LikelihoodCalculationSingleProcess::makeProcessNodes_: null modelNode_");
 
#ifdef DEBUG
  cerr << "likelihoodcalculationsingleprocess::makeprocessnodes_()}" << endl;
#endif
}
 
void LikelihoodCalculationSingleProcess::makeProcessNodes_(CollectionNodes& collection, size_t nProc)
{
  auto& spcm = collection.collection().substitutionProcess(nProc);
 
  // share process parameters with those of the collection
  const auto& paramProc = spcm.getIndependentParameters();
 
  for (size_t i = 0; i < paramProc.size(); i++)
  {
    auto name = paramProc[i].getName();
    if (!collection.hasParameter(name))
      throw Exception("LikelihoodCalculationSingleProcess::makeProcessNodes_ : CollectionNodes does not have parameter " + name);
 
    shareParameter_(collection.getParameter(name));
  }
 
  // share dependencies
 
  for (size_t i = 0; i < paramProc.size(); i++)
  {
    auto name = paramProc[i].getName();
    auto vs = spcm.getAlias(name);
 
    auto dep = dynamic_cast<const ConfiguredParameter*>(&getParameters_()[i])->dependency(0);
    for (const auto& s:vs)
    {
      auto newacp = ConfiguredParameter::create(getContext_(), {dep}, spcm.parameter(s));
      shareParameter_(newacp);
      aliasParameters(name, s);
    }
  }
 
  // rates node
 
  auto rates = spcm.getRateDistribution();
 
  if (dynamic_pointer_cast<const ConstantRateDistribution>(rates) == nullptr)
    processNodes_.ratesNode_ = collection.getRateDistribution(spcm.getRateDistributionNumber());
 
  // tree node
 
  processNodes_.treeNode_ = ProcessTree::makeProcessTree(collection, nProc);
 
  // rootFrequencies node
 
  if (!spcm.isStationary())
    processNodes_.rootFreqsNode_ = collection.getFrequencies(spcm.getRootFrequenciesNumber());
 
  // get any modelNode from the map (only for StateMap)
 
  auto itE = processNodes_.treeNode_->allEdgesIterator();
  for (itE->start(); !itE->end(); itE->next())
  {
    if ((*(*itE))->getModel() != 0)
    {
      processNodes_.modelNode_ = (*(*itE))->getModel();
      break;
    }
  }
  if (!processNodes_.modelNode_)
    throw Exception("LikelihoodCalculationSingleProcess::makeProcessNodes_: null modelNode_");
}
 
 
void LikelihoodCalculationSingleProcess::setNumericalDerivateConfiguration(double delta, const NumericalDerivativeType& config)
{
  auto deltaNode = NumericMutable<double>::create(getContext_(), delta);
 
  if (processNodes_.ratesNode_)
  {
    processNodes_.ratesNode_->config.delta = deltaNode;
    processNodes_.ratesNode_->config.type = config;
  }
 
  // model nodes
 
  vector<shared_ptr<ProcessEdge>> vpn = processNodes_.treeNode_->getAllEdges();
 
  for (auto& it: vpn)
  {
    auto mN = it->getModel();
    if (mN)
    {
      mN->config.delta = deltaNode;
      mN->config.type = config;
    }
 
    // auto pN=it->getProba();
    // {
    //   pN->config.delta = deltaNode;
    //   pN->config.type = config;
    // }
  }
 
  // rootFrequencies node
 
  if (processNodes_.rootFreqsNode_)
  {
    processNodes_.rootFreqsNode_->config.delta = deltaNode;
    processNodes_.rootFreqsNode_->config.type = config;
  }
}
 
void LikelihoodCalculationSingleProcess::setClockLike(double rate)
{
  Parameter pRate("BrLen_rate", rate, Parameter::R_PLUS_STAR);
 
  auto rateNode = ConfiguredParameter::create(getContext_(), pRate);
 
  auto rateRef = ValueFromConfiguredParameter::create(getContext_(), {rateNode});
 
  // brlen nodes
 
  vector<shared_ptr<ProcessEdge>> vpn = processNodes_.treeNode_->getAllEdges();
 
  for (auto& it: vpn)
  {
    auto cp = it->getBrLen();
 
    if (cp)
    {
      auto mulref = CWiseMul<double, std::tuple<double, double>>::create (getContext_(), {cp->dependency(0), rateRef}, Dimension<double>());
 
      auto cp2 = ConfiguredParameter::resetDependencies(getContext_(), cp, {mulref});
 
      it->setBrLen(cp2);
    }
  }
 
  // Remove all BrLen parameters
  auto parNames = getParameters().getParameterNames();
 
  for (auto& name:parNames)
  {
    if (name.substr(0, 5) == "BrLen")
      deleteParameter_(name);
  }
 
  shareParameter_(rateNode);
}
 
RowLik LikelihoodCalculationSingleProcess::getSiteLikelihoodsForAClass(size_t nCat, bool shrunk)
{
  if (shrunk)
    return getSiteLikelihoodsTree_(nCat)->getRoot()->targetValue();
  else
    return expandVector(getSiteLikelihoodsTree_(nCat)->getRoot())->targetValue();
}
 
AllRatesSiteLikelihoods LikelihoodCalculationSingleProcess::getSiteLikelihoodsForAllClasses(bool shrunk)
{
  auto nbCat = vRateCatTrees_.size();
  auto allLk = std::make_shared<AllRatesSiteLikelihoods>(nbCat, shrunk ? getNumberOfDistinctSites() : getNumberOfSites());
 
  for (size_t nCat = 0; nCat < nbCat; nCat++)
  {
    allLk->row(Eigen::Index(nCat)) = getSiteLikelihoodsForAClass(nCat, shrunk);
  }
 
  return *allLk;
}
 
 
/****************************************
* Construction methods
****************************************/
void LikelihoodCalculationSingleProcess::makeRootFreqs_()
{
// Set root frequencies
 
  size_t nbState = stateMap().getNumberOfModelStates();
  rFreqs_ = processNodes_.rootFreqsNode_ ? ConfiguredParametrizable::createRowVector<ConfiguredFrequencySet, FrequenciesFromFrequencySet, Eigen::RowVectorXd>(
        getContext_(), {processNodes_.rootFreqsNode_}, RowVectorDimension (Eigen::Index (nbState))) :
      ConfiguredParametrizable::createRowVector<ConfiguredModel, EquilibriumFrequenciesFromModel, Eigen::RowVectorXd>(
        getContext_(), {processNodes_.modelNode_}, RowVectorDimension (Eigen::Index (nbState)));
}
 
 
void LikelihoodCalculationSingleProcess::makeForwardLikelihoodTree_()
{
  // Build conditional likelihoods up to root recursively.
  if (!processNodes_.treeNode_->isRooted ())
  {
    throw Exception ("LikelihoodCalculationSingleProcess::makeForwardLikelihoodTree_ : PhyloTree must be rooted");
  }
 
  if (processNodes_.ratesNode_)
  {
    uint nbCat = (uint)processNodes_.ratesNode_->targetValue()->getNumberOfCategories();
 
    vRateCatTrees_.resize(nbCat);
 
    for (uint nCat = 0; nCat < nbCat; nCat++)
    {
      ValueRef<double> catRef = CategoryFromDiscreteDistribution::create(getContext_(), {processNodes_.ratesNode_}, nCat);
 
      auto treeCat = std::make_shared<ProcessTree>(*processNodes_.treeNode_, catRef);
 
      vRateCatTrees_[nCat].phyloTree = treeCat;
 
      auto flt = std::make_shared<ForwardLikelihoodTree>(getContext_(), treeCat, stateMap());
 
      if (getShrunkData())
        flt->initialize(*getShrunkData());
      else
        flt->initialize(*psites_);
      vRateCatTrees_[nCat].flt = flt;
    }
  }
  else
  {
    vRateCatTrees_.resize(1);
    vRateCatTrees_[0].phyloTree = processNodes_.treeNode_;
 
    auto flt = std::make_shared<ForwardLikelihoodTree >(getContext_(), processNodes_.treeNode_, processNodes_.modelNode_->targetValue()->stateMap());
 
    if (getShrunkData())
      flt->initialize(*getShrunkData());
    else
      flt->initialize(*psites_);
    vRateCatTrees_[0].flt = flt;
  }
}
 
 
void LikelihoodCalculationSingleProcess::makeLikelihoodsAtRoot_()
{
  if (vRateCatTrees_.size() == 0)
    makeForwardLikelihoodTree_();
 
  size_t nbDistSite = getNumberOfDistinctSites();
  // Set root frequencies
  if (rFreqs_ == 0)
    makeRootFreqs_();
 
  ValueRef<RowLik> sL;
 
  if (processNodes_.ratesNode_)
  {
    std::vector<std::shared_ptr<Node_DF>> vLikRoot;
 
    auto zero = getContext_().getZero();
 
    for (auto& rateCat: vRateCatTrees_)
    {
      vLikRoot.push_back(LikelihoodFromRootConditionalAtRoot::create (
            getContext_(), {rFreqs_, rateCat.flt->getForwardLikelihoodArrayAtRoot()},
            RowVectorDimension (Eigen::Index (nbDistSite))));
    }
 
    // for (size_t nCat = 0; nCat < vRateCatTrees_.size(); nCat++)
    // {
    //   vLikRoot.push_back(ProbabilityFromDiscreteDistribution::create(getContext_(), {processNodes_.ratesNode_}, (uint)nCat));
    // }
 
 
//    sL = CWiseMean<RowLik, ReductionOf<RowLik>, ReductionOf<double> >::create(getContext_(), std::move(vLikRoot), RowVectorDimension (Eigen::Index(nbDistSite)));
 
    catProb_ = ProbabilitiesFromDiscreteDistribution::create(getContext_(), {processNodes_.ratesNode_});
    auto catProb = Convert<RowLik, Eigen::RowVectorXd>::create(getContext_(), {catProb_}, RowVectorDimension (Eigen::Index (vRateCatTrees_.size())));
    vLikRoot.push_back(catProb);
 
    sL = CWiseMean<RowLik, ReductionOf<RowLik>, RowLik>::create(getContext_(), std::move(vLikRoot), RowVectorDimension (Eigen::Index(nbDistSite)));
  }
  else
  {
    sL = LikelihoodFromRootConditionalAtRoot::create (
          getContext_(), {rFreqs_, vRateCatTrees_[0].flt->getForwardLikelihoodArrayAtRoot()}, RowVectorDimension (Eigen::Index (nbDistSite)));
  }
 
 
  // likelihoods per distinct site
  setSiteLikelihoods(sL, true);
 
  // likelihoods per site
  setSiteLikelihoods(expandVector(patternedSiteLikelihoods_), false);
 
  // global likelihood
  ValueRef<DataLik> val;
  if (rootPatternLinks_)
    val = SumOfLogarithms<RowLik>::create (getContext_(), {sL, rootWeights_}, RowVectorDimension (Eigen::Index (nbDistSite)));
  else
    val = SumOfLogarithms<RowLik>::create (getContext_(), {sL}, RowVectorDimension (Eigen::Index (nbDistSite)));
 
  setLikelihoodNode(val);
 
#ifdef DEBUG
  using bpp::DotOptions;
  writeGraphToDot(
      "debug_lik.dot", {likelihood_.get()}, DotOptions::DetailedNodeInfo);
#endif
}
 
 
void LikelihoodCalculationSingleProcess::makeLikelihoodsAtNode_(uint speciesId)
{
  // Already built
  if (condLikelihoodTree_ && condLikelihoodTree_->hasNode(speciesId))
    return;
 
  if (vRateCatTrees_.size() == 0)
    makeForwardLikelihoodTree_();
 
  if (rFreqs_ == 0)
    makeRootFreqs_();
 
  auto nbDistSite = Eigen::Index(getNumberOfDistinctSites());
  auto nbState = Eigen::Index(stateMap().getNumberOfModelStates());
  MatrixDimension likelihoodMatrixDim = conditionalLikelihoodDimension (nbState, nbDistSite);
 
  const auto phylotree = process_->getParametrizablePhyloTree();
 
  ValueRef<RowLik> siteLikelihoodsNode;
 
  std::shared_ptr<ConditionalLikelihood> cond(0);
 
  std::vector<NodeRef> vCondRate;
 
  SiteLikelihoodsRef distinctSiteLikelihoodsNode;
  ConditionalLikelihoodRef conditionalLikelihoodsNode;
 
  std::vector<std::shared_ptr<Node_DF>> vRoot; // if several rates
 
  if (!condLikelihoodTree_)
    condLikelihoodTree_ = std::make_shared<ConditionalLikelihoodTree>(phylotree->getGraph());
 
  auto one = ConstantOne<Eigen::RowVectorXd>::create(getContext_(), RowVectorDimension (nbState));
 
  for (auto& rateCat: vRateCatTrees_)
  {
    if (!rateCat.blt)
      rateCat.blt = std::make_shared<BackwardLikelihoodTree>(getContext_(), rateCat.flt, rateCat.phyloTree, rFreqs_, stateMap(), nbDistSite);
 
    if (!rateCat.clt)
      rateCat.clt = std::make_shared<ConditionalLikelihoodDAG>(rateCat.flt->getGraph());
 
    if (!rateCat.lt)
      rateCat.lt = std::make_shared<SiteLikelihoodsDAG>(rateCat.flt->getGraph());
 
 
    if (!rateCat.speciesLt)
      rateCat.speciesLt = std::make_shared<SiteLikelihoodsTree>(phylotree->getGraph());
 
    auto& dagIndexes = rateCat.flt->getDAGNodesIndexes(speciesId);
 
    std::vector<std::shared_ptr<Node_DF>> vCond;
 
    for (const auto& index : dagIndexes)
    {
      if (rateCat.clt->hasNode(index))
      {
        cond = rateCat.clt->getNode(index);
        if (dagIndexes.size() > 1) // for sum
          vCond.push_back(cond);
        continue;
      }
 
      auto condAbove = rateCat.blt->getBackwardLikelihoodArray(index);
      auto condBelow = rateCat.flt->getForwardLikelihoodArray(index);
 
      cond = BuildConditionalLikelihood::create (
            getContext_(), {condAbove, condBelow}, likelihoodMatrixDim);
 
      if (dagIndexes.size() > 1) // for sum
        vCond.push_back(cond);
 
      rateCat.clt->associateNode(cond, rateCat.flt->getNodeGraphid(rateCat.flt->getNode(index)));
      rateCat.clt->setNodeIndex(cond, index);
 
      // Site Likelihoods on this point
      auto lt = LikelihoodFromRootConditionalAtRoot::create (
            getContext_(), {one, cond}, RowVectorDimension (nbDistSite));
 
      rateCat.lt->associateNode(lt, rateCat.flt->getNodeGraphid(rateCat.flt->getNode(index)));
      rateCat.lt->setNodeIndex(lt, index);
    }
 
    /*
     * If several DAG nodes related with this species node, sum the
     * likelihoods of all (already multiplied by their probability).
     *
     */
 
    if (dagIndexes.size() > 1)
      cond = CWiseAdd<MatrixLik, ReductionOf<MatrixLik>>::create(getContext_(), std::move(vCond), likelihoodMatrixDim);
 
    // for Lik at Node
    auto siteLikelihoodsCat = LikelihoodFromRootConditionalAtRoot::create (
          getContext_(), {one, cond}, RowVectorDimension (nbDistSite));
 
    if (!rateCat.speciesLt->hasNode(speciesId))
    {
      rateCat.speciesLt->associateNode(siteLikelihoodsCat, phylotree->getNodeGraphid(phylotree->getNode(speciesId)));
      rateCat.speciesLt->setNodeIndex(siteLikelihoodsCat, speciesId);
    }
 
    if (!processNodes_.ratesNode_)
    {
      distinctSiteLikelihoodsNode = siteLikelihoodsCat;
      conditionalLikelihoodsNode = cond;
      break;
    }
    else
    {
      // For Conditional at Node
      vCondRate.push_back(cond);
      vRoot.push_back(siteLikelihoodsCat);
    }
  }
 
  if (catProb_) // Should have been computed before
  {
    auto catProb = Convert<RowLik, Eigen::RowVectorXd>::create(getContext_(), {catProb_}, RowVectorDimension (Eigen::Index (vRateCatTrees_.size())));
 
    vRoot.push_back(catProb);
    vCondRate.push_back(catProb);
 
    distinctSiteLikelihoodsNode = CWiseMean<RowLik, ReductionOf<RowLik>, RowLik>::create(getContext_(), std::move(vRoot), RowVectorDimension (nbDistSite));
 
    conditionalLikelihoodsNode = CWiseMean<MatrixLik, ReductionOf<MatrixLik>, RowLik>::create(getContext_(), std::move(vCondRate), MatrixDimension (nbState, nbDistSite));
  }
 
  condLikelihoodTree_->associateNode(conditionalLikelihoodsNode, phylotree->getNodeGraphid(phylotree->getNode(speciesId)));
  condLikelihoodTree_->setNodeIndex(conditionalLikelihoodsNode, speciesId);
 
  // We want -log(likelihood)
  // auto totalNegLogLikelihood =
  //   CWiseNegate<double>::create (getContext_(), {totalLogLikelihood}, Dimension<double> ());
  //  return totalNegLogLikelihood;
}
 
void LikelihoodCalculationSingleProcess::makeLikelihoodsAtDAGNode_(uint nodeId)
{
  if (vRateCatTrees_.size() == 0)
    makeForwardLikelihoodTree_();
 
  if (rFreqs_ == 0)
    makeRootFreqs_();
 
  auto nbDistSite = Eigen::Index(getNumberOfDistinctSites());
  auto nbState = Eigen::Index(stateMap().getNumberOfModelStates());
  MatrixDimension likelihoodMatrixDim = conditionalLikelihoodDimension (nbState, nbDistSite);
 
  ValueRef<RowLik> siteLikelihoodsNode;
 
  auto one = ConstantOne<Eigen::RowVectorXd>::create(getContext_(), RowVectorDimension (Eigen::Index (nbState)));
 
  for (auto& rateCat: vRateCatTrees_)
  {
    if (!rateCat.clt)
      rateCat.clt = std::make_shared<ConditionalLikelihoodDAG>(rateCat.flt->getGraph());
 
    if (rateCat.clt->hasNode(nodeId)) // already computed
      continue;
 
    if (!rateCat.blt)
      rateCat.blt = std::make_shared<BackwardLikelihoodTree>(getContext_(), rateCat.flt, rateCat.phyloTree, rFreqs_, stateMap(), nbDistSite);
 
    if (!rateCat.lt)
      rateCat.lt = std::make_shared<SiteLikelihoodsDAG>(rateCat.flt->getGraph());
 
    // Conditional Likelihoods on this node
 
    auto condAbove = rateCat.blt->getBackwardLikelihoodArray(nodeId);
    auto condBelow = rateCat.flt->getForwardLikelihoodArray(nodeId);
 
    auto cond = BuildConditionalLikelihood::create (
          getContext_(), {condAbove, condBelow}, likelihoodMatrixDim);
 
    rateCat.clt->associateNode(cond, rateCat.flt->getNodeGraphid(rateCat.flt->getNode(nodeId)));
    rateCat.clt->setNodeIndex(cond, nodeId);
 
    // Site Likelihoods on this node
    auto lt = LikelihoodFromRootConditionalAtRoot::create (
          getContext_(), {one, cond}, RowVectorDimension (Eigen::Index (nbDistSite)));
 
    rateCat.lt->associateNode(lt, rateCat.flt->getNodeGraphid(rateCat.flt->getNode(nodeId)));
    rateCat.lt->setNodeIndex(lt, nodeId);
  }
}
 
 
std::shared_ptr<SiteLikelihoodsTree> LikelihoodCalculationSingleProcess::getSiteLikelihoodsTree_(size_t nCat)
{
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getSiteLikelihoodsTree : Bad Class number " + TextTools::toString(nCat));
 
  if (!shrunkData_)
    throw Exception("LikelihoodCalculationSingleProcess::getSiteLikelihoodsTree : data not set.");
 
  if (!getLikelihoodNode_())
    makeLikelihoodsAtRoot_();
 
  if (vRateCatTrees_[nCat].speciesLt == 0)
    makeLikelihoodsAtNode_(getTreeNode(nCat)->getRoot()->getSpeciesIndex());
 
  return vRateCatTrees_[nCat].speciesLt;
}
 
 
ConditionalLikelihoodRef LikelihoodCalculationSingleProcess::getForwardLikelihoodsAtNodeForClass(uint nodeId, size_t nCat)
{
  // compute forward likelihoods for all nodes (not the quickest, but
  // in practice they are all needed)
 
  if (!getLikelihoodNode_())
    makeLikelihoods();
 
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getForwardLikelihoodsAtNodeForClass : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].flt->getNode(nodeId);
}
 
ConditionalLikelihoodRef LikelihoodCalculationSingleProcess::getConditionalLikelihoodsAtNodeForClass(uint nodeId, size_t nCat)
{
  // compute likelihoods for all edges with similar species index
  // (not the quickest, but in practice they are all needed)
 
  makeLikelihoodsAtDAGNode_(nodeId);
 
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getConditionalLikelihoodsAtNodeForClass : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].clt->getNode(nodeId);
}
 
SiteLikelihoodsRef LikelihoodCalculationSingleProcess::getLikelihoodsAtNodeForClass(uint nodeId, size_t nCat)
{
  // compute likelihoods for all edges with similar species index
  // (not the quickest, but in practice they are all needed)
 
  makeLikelihoodsAtDAGNode_(nodeId);
 
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getConditionalLikelihoodsAtNodeForClass : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].lt->getNode(nodeId);
}
 
 
ConditionalLikelihoodRef LikelihoodCalculationSingleProcess::getBackwardLikelihoodsAtEdgeForClass(uint edgeId, size_t nCat)
{
  // compute likelihoods for all edges with similar species index
  // (not the quickest, but in practice they are all needed)
 
  auto spId = getTreeNode(nCat)->getEdge(edgeId)->getSpeciesIndex();
 
  if (!(condLikelihoodTree_ && condLikelihoodTree_->hasNode(spId)))
    makeLikelihoodsAtNode_(spId);
 
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getForwardLikelihoodsAtNodeForClass : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].blt->getEdge(edgeId);
}
 
ConditionalLikelihoodRef LikelihoodCalculationSingleProcess::getBackwardLikelihoodsAtNodeForClass(uint nodeId, size_t nCat)
{
  // compute likelihoods for all nodes with similar species index
  // (not the quickest, but in practice they are all needed)
 
  makeLikelihoodsAtDAGNode_(nodeId);
 
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getForwardLikelihoodsAtNodeForClass : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].blt->getNode(nodeId);
}
 
 
const DAGindexes& LikelihoodCalculationSingleProcess::getNodesIds(uint speciesId) const
{
  if (vRateCatTrees_.size() == 0)
    throw Exception("LikelihoodCalculationSingleProcess::getNodeIds. ForwardLikelihoodTree not computed.");
 
  return vRateCatTrees_[0].flt->getDAGNodesIndexes(speciesId);
}
 
const DAGindexes& LikelihoodCalculationSingleProcess::getEdgesIds(uint speciesId, size_t nCat) const
{
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getEdgesIds : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].flt->getDAGEdgesIndexes(speciesId);
}
 
std::shared_ptr<ForwardLikelihoodTree> LikelihoodCalculationSingleProcess::getForwardLikelihoodTree(size_t nCat)
{
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getForwardTree : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].flt;
}
 
std::shared_ptr<BackwardLikelihoodTree> LikelihoodCalculationSingleProcess::getBackwardLikelihoodTree(size_t nCat)
{
  if (nCat >= vRateCatTrees_.size())
    throw Exception("LikelihoodCalculationSingleProcess::getBackwardTree : bad class number " + TextTools::toString(nCat));
 
  return vRateCatTrees_[nCat].blt;
}
 
void LikelihoodCalculationSingleProcess::cleanAllLikelihoods()
{
  psites_.reset();
  rootPatternLinks_.reset();
  rootWeights_.reset();
  shrunkData_.reset();
  condLikelihoodTree_.reset();
 
  vRateCatTrees_.clear();
 
  AlignedLikelihoodCalculation::cleanAllLikelihoods();
}
 
LikelihoodCalculationSingleProcess::RateCategoryTrees::~RateCategoryTrees()
{
  if (flt)
  {
    auto& c = flt->getContext();
    const auto& lroot = flt->getForwardLikelihoodArrayAtRoot();
    c.erase(lroot);
  }
 
  phyloTree.reset();
}