12 #include <Evergreen/evergreen.hpp> 
   14 typedef unsigned long int uiint;
 
   24   template <
typename Label>
 
   34     std::map<int, double> 
chgLLhoods = {{1, 0.7}, {2, 0.9}, {3, 0.7}, {4, 0.5}, {5, 0.5}};
 
   41       return std::pow(2., log2(1. - 
beta_) + summ * log2(1. - 
alpha_));
 
   49     evergreen::TableDependency<Label> 
createProteinFactor(Label 
id, 
double prior, 
int nrMissingPeps = 0);
 
   70     evergreen::TableDependency<Label> 
createSumFactor(
size_t nr_parents, Label nId);
 
   72     evergreen::TableDependency<Label> 
createChargeFactor(Label repId, Label chargeId, 
int chg);
 
   79     evergreen::PseudoAdditiveDependency<Label> 
createBFPeptideProbabilisticAdderFactor(
const std::set<Label> & parentProteinIDs, Label nId, 
const std::vector<evergreen::TableDependency <Label> > & deps);
 
   96                                      const std::vector<std::vector<Label>> & parentsOfPeps,
 
   97                                      const std::vector<double> & pepEvidences,
 
   98                                      evergreen::InferenceGraphBuilder<Label> & igb);
 
  108   template <
typename Label>
 
  110     assert(0. <= alpha && alpha <= 1.);
 
  111     assert(0. <= beta && beta <= 1.);
 
  112     assert(0. <= gamma && gamma <= 1.);
 
  115     assert(0. < pep_prior && pep_prior < 1.);
 
  120     pepPrior_ = pep_prior;
 
  123   template <
typename Label>
 
  125     double prior = gamma_;
 
  126     if (nrMissingPeps > 0)
 
  128       double powFactor = std::pow(1.0 - alpha_, -nrMissingPeps);
 
  129       prior = -prior/(prior * powFactor - prior - powFactor);
 
  131     double table[] = {1.0 - prior, prior};
 
  132     evergreen::LabeledPMF<Label> lpmf({
id}, evergreen::PMF({0L}, evergreen::Tensor<double>::from_array(table)));
 
  133     return evergreen::TableDependency<Label>(lpmf,p_);
 
  136   template <
typename Label>
 
  138     if (nrMissingPeps > 0)
 
  140       double powFactor = std::pow(1.0 - alpha_, -nrMissingPeps);
 
  141       prior = -prior/(prior * powFactor - prior - powFactor);
 
  143     double table[] = {1.0 - prior, prior};
 
  144     evergreen::LabeledPMF<Label> lpmf({
id}, evergreen::PMF({0L}, evergreen::Tensor<double>::from_array(table)));
 
  145     return evergreen::TableDependency<Label>(lpmf,p_);
 
  148   template <
typename Label>
 
  150     double table[] = {(1 - prob) * (1 - pepPrior_), prob * pepPrior_};
 
  151     evergreen::LabeledPMF<Label> lpmf({
id}, evergreen::PMF({0L}, evergreen::Tensor<double>::from_array(table)));
 
  152     return evergreen::TableDependency<Label>(lpmf,p_);
 
  156   template <
typename Label>
 
  158     evergreen::Tensor<double> table({
static_cast<unsigned long>(nrParents + 1) , 2});
 
  159     for (
unsigned long i=0; i <= nrParents; ++i) {
 
  160       double notConditional = notConditionalGivenSum(i);
 
  161       unsigned long indexArr[2] = {i,0ul};
 
  162       table[indexArr] = notConditional;
 
  163       unsigned long indexArr2[2] = {i,1ul};
 
  164       table[indexArr2] = 1.0 - notConditional;
 
  167     evergreen::LabeledPMF<Label> lpmf({nId, pepId}, evergreen::PMF({0L,0L}, table));
 
  169     return evergreen::TableDependency<Label>(lpmf,p_);
 
  172   template <
typename Label>
 
  174     evergreen::Tensor<double> table({
static_cast<unsigned long>(nrParents + 1) , 2});
 
  175     unsigned long z[2]{0ul,0ul};
 
  176     unsigned long z1[2]{0ul,1ul};
 
  177     table[z] = 1. - beta_;
 
  179     for (
unsigned long i=1; i <= nrParents; ++i) {
 
  180       double notConditional = notConditionalGivenSum(i);
 
  181       unsigned long indexArr[2] = {i,0ul};
 
  182       table[indexArr] = notConditional / i;
 
  183       unsigned long indexArr2[2] = {i,1ul};
 
  184       table[indexArr2] = (1.0 - notConditional) / i;
 
  187     evergreen::LabeledPMF<Label> lpmf({nId, pepId}, evergreen::PMF({0L,0L}, table));
 
  189     return evergreen::TableDependency<Label>(lpmf,p_);
 
  192   template <
typename Label>
 
  194     evergreen::Tensor<double> table({nrParents+1});
 
  195     for (
unsigned long i=0; i <= nrParents; ++i) {
 
  196       table[i] = 1.0/(nrParents+1.);
 
  199     evergreen::LabeledPMF<Label> lpmf({nId}, evergreen::PMF({0L}, table));
 
  201     return evergreen::TableDependency<Label>(lpmf,p_);
 
  204   template <
typename Label>
 
  206     using arr = 
unsigned long[2];
 
  207     evergreen::Tensor<double> table({2,2});
 
  208     table[arr{0,0}] = 0.999;
 
  209     table[arr{0,1}] = 0.001;
 
  210     table[arr{1,0}] = 0.1;
 
  211     table[arr{1,1}] = 0.9;
 
  213     evergreen::LabeledPMF<Label> lpmf({seqId,repId}, evergreen::PMF({0L,0L}, table));
 
  215     return evergreen::TableDependency<Label>(lpmf,p_);
 
  218   template <
typename Label>
 
  220     double chgPrior = chgLLhoods[chg];
 
  221     using arr = 
unsigned long[2];
 
  222     evergreen::Tensor<double> table({2,2});
 
  223     table[arr{0,0}] = 0.999;
 
  224     table[arr{0,1}] = 0.001;
 
  225     table[arr{1,0}] = 0.1;
 
  226     table[arr{1,1}] = chgPrior;
 
  228     evergreen::LabeledPMF<Label> lpmf({repId,chgId}, evergreen::PMF({0L,0L}, table));
 
  230     return evergreen::TableDependency<Label>(lpmf,p_);
 
  233   template <
typename Label>
 
  235     std::vector<std::vector<Label>> parents;
 
  236     std::transform(parentProteinIDs.begin(), parentProteinIDs.end(), std::back_inserter(parents), [](
const Label& l){return std::vector<Label>{l};});
 
  237     return evergreen::AdditiveDependency<Label>(parents, {nId}, p_);
 
  240   template <
typename Label>
 
  242     std::vector<std::vector<Label>> parents;
 
  243     std::transform(parentProteinIDs.begin(), parentProteinIDs.end(), std::back_inserter(parents), [](
const Label& l){return std::vector<Label>{l};});
 
  244     return evergreen::AdditiveDependency<Label>(parents, {nId}, p_);
 
  247   template <
typename Label>
 
  249     std::vector<std::vector<Label>> parents;
 
  250     std::transform(parentProteinIDs.begin(), parentProteinIDs.end(), std::back_inserter(parents), [](
const Label& l){return std::vector<Label>{l};});
 
  251     return evergreen::PseudoAdditiveDependency<Label>(parents, {nId}, deps, p_);
 
  256   template <
typename Label>
 
  258                                                             const std::vector<std::vector<Label>>& parentsOfPeps,
 
  259                                                             const std::vector<double>& pepEvidences,
 
  260                                                             evergreen::InferenceGraphBuilder<Label>& igb)
 
  263     assert(parentsOfPeps.size() == pepEvidences.size());
 
  264     for (
const std::vector<uiint>& parents : parentsOfPeps)
 
  265       for (Label parent : parents)
 
  266         assert(std::find(protIDs.begin(), protIDs.end(), parent) != protIDs.end());
 
  268     for (
uiint pid : protIDs)
 
  269       igb.insert_dependency(createProteinFactor(pid));
 
  271     for (
uiint j = 0; j < parentsOfPeps.size(); j++)
 
  273       igb.insert_dependency(createPeptideEvidenceFactor(j,pepEvidences[j]));
 
  274       igb.insert_dependency(createSumEvidenceFactor(parentsOfPeps[j],j,j));
 
  275       igb.insert_dependency(createPeptideProbabilisticAdderFactor(parentsOfPeps[j],j));
 
unsigned long int uiint
Definition: MessagePasserFactory.h:14
 
Definition: MessagePasserFactory.h:25
 
evergreen::TableDependency< Label > createProteinFactor(Label id, int nrMissingPeps=0)
Protein Factor initialized with model prior (missing peps are experimental)
Definition: MessagePasserFactory.h:124
 
double notConditionalGivenSum(unsigned long summ)
Definition: MessagePasserFactory.h:39
 
evergreen::AdditiveDependency< Label > createPeptideProbabilisticAdderFactor(const std::set< Label > &parentProteinIDs, Label nId)
To sum up distributions for the number of parent proteins of a peptide with convolution trees.
Definition: MessagePasserFactory.h:234
 
double alpha_
the model parameters
Definition: MessagePasserFactory.h:30
 
evergreen::TableDependency< Label > createSumEvidenceFactor(size_t nr_parents, Label id, Label pep_id)
Definition: MessagePasserFactory.h:157
 
MessagePasserFactory(double alpha, double beta, double gamma, double p, double pep_prior)
Constructor.
Definition: MessagePasserFactory.h:109
 
double beta_
Definition: MessagePasserFactory.h:30
 
void fillVectorsOfMessagePassers(const std::vector< Label > &protIDs, const std::vector< std::vector< Label >> &parentsOfPeps, const std::vector< double > &pepEvidences, evergreen::InferenceGraphBuilder< Label > &igb)
Works on a vector of protein indices (potentially not consecutive)
Definition: MessagePasserFactory.h:257
 
evergreen::TableDependency< Label > createRegularizingSumEvidenceFactor(size_t nr_parents, Label id, Label pep_id)
Definition: MessagePasserFactory.h:173
 
evergreen::TableDependency< Label > createChargeFactor(Label repId, Label chargeId, int chg)
Definition: MessagePasserFactory.h:219
 
double gamma_
Definition: MessagePasserFactory.h:30
 
double pepPrior_
Definition: MessagePasserFactory.h:30
 
evergreen::TableDependency< Label > createReplicateFactor(Label seqId, Label repId)
Definition: MessagePasserFactory.h:205
 
evergreen::TableDependency< Label > createSumFactor(size_t nr_parents, Label nId)
Definition: MessagePasserFactory.h:193
 
evergreen::TableDependency< Label > createPeptideEvidenceFactor(Label id, double prob)
Definition: MessagePasserFactory.h:149
 
double p_
Definition: MessagePasserFactory.h:30
 
std::map< int, double > chgLLhoods
Definition: MessagePasserFactory.h:34
 
evergreen::PseudoAdditiveDependency< Label > createBFPeptideProbabilisticAdderFactor(const std::set< Label > &parentProteinIDs, Label nId, const std::vector< evergreen::TableDependency< Label > > &deps)
To sum up distributions for the number of parent proteins of a peptide brute-force.
Definition: MessagePasserFactory.h:248
 
Main OpenMS namespace.
Definition: openswathalgo/include/OpenMS/OPENSWATHALGO/DATAACCESS/ISpectrumAccess.h:19