void AdvancedScoreModel::learn_prm_normalizer_values(const FileManager& fm)
{
const float step = 0.5;
const float min_delta = -1.0;
const float max_delta = 7.0;
const float target_mid_ratio = 0.96;
const float target_side_ratio = 0.94;
config.set_use_spectrum_charge(1);
regional_prm_normalizers.resize(regional_breakage_score_models.size());
int c;
for (c=0; c<regional_breakage_score_models.size(); c++)
{
regional_prm_normalizers[c].resize(regional_breakage_score_models[c].size());
int s;
for (s=0; s<regional_breakage_score_models[c].size(); s++)
regional_prm_normalizers[c][s].resize(regional_breakage_score_models[c][s].size(),0);
}
const vector< vector<mass_t> >& mass_threshes = config.get_size_thresholds();
for (c=1; c<regional_prm_normalizers.size(); c++)
{
int s;
for (s=0; s<regional_prm_normalizers[c].size(); s++)
{
const mass_t min_mass = (s == 0 ? 0 : mass_threshes[c][s-1]);
const mass_t max_mass = mass_threshes[c][s];
const int num_regions = regional_prm_normalizers[c][s].size();
cout << "Finding normalizers for charge " << c << " size " << s << " (masses " << min_mass << " - " <<
max_mass << ")" << endl;
FileSet fs;
BasicSpecReader bsr;
fs.select_files_in_mz_range(fm,min_mass/c,max_mass/c,c);
fs.randomly_reduce_ssfs(2000);
vector< vector< NodeType > > all_prms;
const vector<SingleSpectrumFile *>& all_ssf = fs.get_ssf_pointers();
if (fs.get_total_spectra()<50)
{
cout << "Insufficient number of spectra... skipping" << endl;
continue;
}
int sc;
for (sc=0; sc<all_ssf.size(); sc++)
{
PrmGraph prm;
static vector<QCPeak> peaks;
SingleSpectrumFile *ssf = all_ssf[sc];
if (peaks.size()<ssf->num_peaks)
{
int new_size = ssf->num_peaks*2;
if (new_size<2500)
new_size=2500;
peaks.resize(new_size);
}
const int num_peaks = bsr.read_basic_spec(&config,fm,ssf,&peaks[0]);
if (num_peaks<5)
continue;
// convert peak list ot a spectrum with charge (if original charge ==0)
// the spectrum gets charge 2, but the true charge is computed from the data
Spectrum s;
s.init_from_QCPeaks(&config,&peaks[0],num_peaks,ssf);
vector<mass_t> pms_with_19;
vector<int> charges;
pms_with_19.clear();
charges.clear();
BasicSpectrum bs;
bs.ssf = ssf;
bs.peaks = &peaks[0];
bs.num_peaks = num_peaks;
// output m/z and prob values for the different charge states
select_pms_and_charges(&config,bs,pms_with_19,charges);
if (pms_with_19.size()<=0)
continue;
s.set_charge(charges[0]);
init_model_for_scoring_spectrum(&s);
prm.create_graph_from_spectrum(this,&s,pms_with_19[0]);
vector<NodeType> spec_prms;
vector<mass_t> exp_masses;
const mass_t true_mass_with_19 = s.get_true_mass_with_19();
s.get_peptide().calc_expected_breakage_masses(&config,exp_masses);
int i;
for (i=1; i<prm.get_num_nodes()-1; i++)
{
const Node& node = prm.get_node(i);
if (node.score == 0)
continue;
NodeType nt;
nt.type = 0;
int j;
for (j=0; j<exp_masses.size(); j++)
if (fabs(exp_masses[j]-node.mass)<config.get_tolerance())
{
nt.type=1;
break;
}
if (nt.type<=0)
{
int j;
for (j=0; j<exp_masses.size(); j++)
if (fabs(true_mass_with_19 - exp_masses[j] -node.mass-MASS_PROTON)<config.get_tolerance())
{
nt.type=2;
break;
}
}
nt.org_score = node.score;
nt.mod_score = node.score;
nt.region = node.breakage.region_idx;
spec_prms.push_back(nt);
}
all_prms.push_back(spec_prms);
}
vector< vector< double > > per_pre, per_suf, per_covered;
vector<float> deltas;
per_pre.resize(num_regions);
per_suf.resize(num_regions);
per_covered.resize(num_regions);
float delta;
for (delta = min_delta; delta<=max_delta; delta+=step )
{
// perform mods
int a;
for (a=0; a<all_prms.size(); a++)
{
int b;
for (b=0; b<all_prms[a].size(); b++)
{
NodeType& nt = all_prms[a][b];
if (nt.org_score< -delta)
{
nt.mod_score = NEG_INF;
continue;
}
/* if (nt.org_score>delta)
{
nt.mod_score = nt.org_score ;
}
else
nt.mod_score = nt.org_score + (delta-nt.org_score)*0.5;*/
nt.mod_score = nt.org_score + delta;
}
}
// compute stats (if score is negative treat as 0)
vector<double> num_pre,num_suf;
vector<double> num_pre_wpos, num_suf_wpos;
vector<double> score_pre, score_suf, total_score;
num_pre.resize(num_regions,0);
num_suf.resize(num_regions,0);
num_pre_wpos.resize(num_regions,0);
num_suf_wpos.resize(num_regions,0);
score_pre.resize(num_regions,0);
score_suf.resize(num_regions,0);
total_score.resize(num_regions,0);
for (a=0; a<all_prms.size(); a++)
{
int b;
for (b=0; b<all_prms[a].size(); b++)
{
const int type = all_prms[a][b].type;
const float score = all_prms[a][b].mod_score;
const int region = all_prms[a][b].region;
if (type == 1)
{
num_pre[region]++;
if (score>0)
{
num_pre_wpos[region]++;
score_pre[region]+= score;
}
}
if (type == 2)
{
num_suf[region]++;
if (score>0)
{
num_suf_wpos[region]++;
score_suf[region]+=score;
}
}
if (score>0)
total_score[region]+=score;
}
}
deltas.push_back(delta);
int r;
for (r=0; r<num_regions; r++)
{
per_pre[r].push_back(num_pre_wpos[r]/num_pre[r]);
per_suf[r].push_back(num_suf_wpos[r]/num_suf[r]);
per_covered[r].push_back((score_pre[r]+score_suf[r])/total_score[r]);
}
}
// report
int r;
for (r=0; r<num_regions; r++)
{
cout << endl << "Region " << r << endl;
int d;
for (d=0; d<deltas.size(); d++)
cout << "\t" << deltas[d];
cout << endl << "% Pre";
for (d=0; d<per_pre[r].size(); d++)
cout << "\t" << per_pre[r][d];
cout << endl << "% Suf";
for (d=0; d<per_suf[r].size(); d++)
cout << "\t" << per_suf[r][d];
cout << endl << "% Cov";
for (d=0; d<per_covered[r].size(); d++)
cout << "\t" << per_covered[r][d];
cout << endl;
// select
float target_val = target_mid_ratio;
if (r==0 || r == num_regions-1)
target_val = target_side_ratio;
float best_val=POS_INF;
float best_delta=0;
for (d=0; d<deltas.size(); d++)
if (fabs(per_pre[r][d]-target_val)<best_val)
{
best_val = fabs(per_pre[r][d]-target_val);
best_delta = deltas[d];
}
cout << "Chose delta = " << best_delta << endl << endl;
regional_prm_normalizers[c][s][r]=best_delta;
}
}
}
}
void PrmNodeScoreModel::learnPrmNormalizerValue(void* allScoreModelsVoidPointer, const SpectraAggregator& sa)
{
AllScoreModels* allScoreModels = static_cast<AllScoreModels*>(allScoreModelsVoidPointer);
const float step = 0.5;
const float min_delta = -1.0;
const float max_delta = 7.0;
const float target_mid_ratio = 0.96;
const float target_side_ratio = 0.94;
config_->set_use_spectrum_charge(1);
regional_prm_normalizers.resize(RegionalPrmNodeScoreModels_.size());
int c;
for (c=0; c<RegionalPrmNodeScoreModels_.size(); c++)
{
regional_prm_normalizers[c].resize(RegionalPrmNodeScoreModels_[c].size());
int s;
for (s=0; s<RegionalPrmNodeScoreModels_[c].size(); s++)
regional_prm_normalizers[c][s].resize(RegionalPrmNodeScoreModels_[c][s].size(),0);
}
const vector< vector<mass_t> >& mass_threshes = config_->get_size_thresholds();
for (c=1; c<regional_prm_normalizers.size(); c++)
{
int s;
for (s=0; s<regional_prm_normalizers[c].size(); s++)
{
const mass_t min_mass = (s == 0 ? 0 : mass_threshes[c][s-1]);
const mass_t max_mass = mass_threshes[c][s];
const int num_regions = regional_prm_normalizers[c][s].size();
cout << "Finding normalizers for charge " << c << " size " << s << " (masses " << min_mass << " - " <<
max_mass << ")" << endl;
SpectraList sl(sa);
sl.selectHeaders(min_mass/c,max_mass/c,c,c);
sl.randomlyReduceListToSize(2000);
if (sl.getNumHeaders()<50)
{
cout << "Insufficient number of spectra... skipping" << endl;
continue;
}
vector< vector< NodeType > > all_prms;
int sc;
for (sc=0; sc<sl.getNumHeaders(); sc++)
{
const SingleSpectrumHeader* header = sl.getSpectrumHeader(sc);
PrmGraph prm;
Spectrum s;
if (! s.readSpectrum(sa, header))
continue;
vector<mass_t> pms_with_19;
vector<int> charges;
// output m/z and prob values for the different charge states
allScoreModels->selectPrecursorMassesAndCharges(config_, s, pms_with_19, charges);
if (pms_with_19.size()<=0)
continue;
s.setCharge(charges[0]);
prm.create_graph_from_spectrum(allScoreModels, &s,pms_with_19[0]);
vector<NodeType> spec_prms;
vector<mass_t> exp_masses;
const mass_t true_mass_with_19 = s.get_true_mass_with_19();
s.getPeptide().calc_expected_breakage_masses(config_,exp_masses);
int i;
for (i=1; i<prm.get_num_nodes()-1; i++)
{
const Node& node = prm.get_node(i);
if (node.score == 0)
continue;
NodeType nt;
nt.type = 0;
int j;
for (j=0; j<exp_masses.size(); j++)
if (fabs(exp_masses[j]-node.mass)<config_->getTolerance())
{
nt.type=1;
break;
}
if (nt.type<=0)
{
int j;
for (j=0; j<exp_masses.size(); j++)
if (fabs(true_mass_with_19 - exp_masses[j] -node.mass-MASS_PROTON)<config_->getTolerance())
{
nt.type=2;
break;
}
}
nt.org_score = node.score;
nt.mod_score = node.score;
nt.region = node.breakage.region_idx;
spec_prms.push_back(nt);
}
all_prms.push_back(spec_prms);
}
vector< vector< double > > per_pre, per_suf, per_covered;
vector<float> deltas;
per_pre.resize(num_regions);
per_suf.resize(num_regions);
per_covered.resize(num_regions);
float delta;
for (delta = min_delta; delta<=max_delta; delta+=step )
{
// perform mods
int a;
for (a=0; a<all_prms.size(); a++)
{
int b;
for (b=0; b<all_prms[a].size(); b++)
{
NodeType& nt = all_prms[a][b];
if (nt.org_score< -delta)
{
nt.mod_score = NEG_INF;
continue;
}
nt.mod_score = nt.org_score + delta;
}
}
// compute stats (if score is negative treat as 0)
vector<double> num_pre,num_suf;
vector<double> num_pre_wpos, num_suf_wpos;
vector<double> score_pre, score_suf, total_score;
num_pre.resize(num_regions,0);
num_suf.resize(num_regions,0);
num_pre_wpos.resize(num_regions,0);
num_suf_wpos.resize(num_regions,0);
score_pre.resize(num_regions,0);
score_suf.resize(num_regions,0);
total_score.resize(num_regions,0);
for (a=0; a<all_prms.size(); a++)
{
int b;
for (b=0; b<all_prms[a].size(); b++)
{
const int type = all_prms[a][b].type;
const float score = all_prms[a][b].mod_score;
const int region = all_prms[a][b].region;
if (type == 1)
{
num_pre[region]++;
if (score>0)
{
num_pre_wpos[region]++;
score_pre[region]+= score;
}
}
if (type == 2)
{
num_suf[region]++;
if (score>0)
{
num_suf_wpos[region]++;
score_suf[region]+=score;
}
}
if (score>0)
total_score[region]+=score;
}
}
deltas.push_back(delta);
int r;
for (r=0; r<num_regions; r++)
{
per_pre[r].push_back(num_pre_wpos[r]/num_pre[r]);
per_suf[r].push_back(num_suf_wpos[r]/num_suf[r]);
per_covered[r].push_back((score_pre[r]+score_suf[r])/total_score[r]);
}
}
// report
int r;
for (r=0; r<num_regions; r++)
{
cout << endl << "Region " << r << endl;
int d;
for (d=0; d<deltas.size(); d++)
cout << "\t" << deltas[d];
cout << endl << "% Pre";
for (d=0; d<per_pre[r].size(); d++)
cout << "\t" << per_pre[r][d];
cout << endl << "% Suf";
for (d=0; d<per_suf[r].size(); d++)
cout << "\t" << per_suf[r][d];
cout << endl << "% Cov";
for (d=0; d<per_covered[r].size(); d++)
cout << "\t" << per_covered[r][d];
cout << endl;
// select
float target_val = target_mid_ratio;
if (r==0 || r == num_regions-1)
target_val = target_side_ratio;
float best_val=POS_INF;
float best_delta=0;
for (d=0; d<deltas.size(); d++)
if (fabs(per_pre[r][d]-target_val)<best_val)
{
best_val = fabs(per_pre[r][d]-target_val);
best_delta = deltas[d];
}
cout << "Chose delta = " << best_delta << endl << endl;
regional_prm_normalizers[c][s][r]=best_delta;
}
}
}
indNormzlizersInitialized_ = true;
write_prm_normalizer_values();
}