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/*
* Errorscounter.cpp
*
* Created on: Oct 5, 2017
* Author: Quentin Marcou
*
* This source code is distributed as part of the IGoR software.
* IGoR (Inference and Generation of Repertoires) is a versatile software to analyze and model immune receptors
* generation, selection, mutation and all other processes.
* Copyright (C) 2017 Quentin Marcou
*
* This program 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.
*
* This program 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 this program. If not, see <https://www.gnu.org/licenses/>.
*/
#include "Errorscounter.h"
using namespace std;
Errors_counter::Errors_counter(size_t n_scenarios): Counter(), n_scenarios_counted(n_scenarios) , output_scenarios(n_scenarios_counted>0) ,
scenario_n_mismatches(0) , scenario_n_genomic(0) , sequence_average_error_freq(0) , sequence_average_n_genomic(0) , sequence_average_n_mismatches(0){
}
Errors_counter::Errors_counter(size_t n_scenarios , bool is_last_iter_only): Errors_counter(n_scenarios) {
this->last_iter_only = is_last_iter_only;
}
Errors_counter::Errors_counter(size_t n_scenarios , string path): Counter(path) , n_scenarios_counted(n_scenarios) , output_scenarios(n_scenarios_counted>0),
scenario_n_mismatches(0) , scenario_n_genomic(0) , sequence_average_error_freq(0) , sequence_average_n_genomic(0) , sequence_average_n_mismatches(0){
}
/**
* \param n_scenarios: number of scenarios to be recorded, if 0 only the average sequence mutation rate will be recorded.
*/
Errors_counter::Errors_counter( size_t n_scenarios , string path , bool is_last_iter_only) : Errors_counter(n_scenarios , path) {
this->last_iter_only = is_last_iter_only;
}
Errors_counter::Errors_counter():Errors_counter(0,true) {
// TODO Auto-generated constructor stub
}
Errors_counter::~Errors_counter() {
// TODO Auto-generated destructor stub
}
void Errors_counter::count_scenario(long double scenario_seq_joint_proba , double scenario_probability , const string& original_sequence , Seq_type_str_p_map& constructed_sequences , const Seq_offsets_map& seq_offsets , const unordered_map<tuple<Event_type,Gene_class,Seq_side>, shared_ptr<Rec_Event>>& events_map , Mismatch_vectors_map& mismatches_lists){
// Get the number of genomic nucleotides
if(constructed_sequences.exist(V_gene_seq)){
const vector<int>& v_seq = *constructed_sequences.at(V_gene_seq);
this->scenario_n_genomic+=v_seq.size();
}
if(constructed_sequences.exist(D_gene_seq)){
const vector<int>& d_seq = *constructed_sequences[D_gene_seq];
this->scenario_n_genomic+=d_seq.size();
}
if(constructed_sequences.exist(J_gene_seq)){
const vector<int>& j_seq = *constructed_sequences.at(J_gene_seq);
this->scenario_n_genomic+=j_seq.size();
}
// Get the number of mismatches and add them to the mismatch counter
if(mismatches_lists.exist(V_gene_seq)){
const vector<int>& v_mismatch_list = *mismatches_lists.at(V_gene_seq);
this->scenario_n_mismatches+=v_mismatch_list.size();
}
if(mismatches_lists.exist(D_gene_seq)){
const vector<int>& d_mismatch_list = *mismatches_lists[D_gene_seq];
this->scenario_n_mismatches+=d_mismatch_list.size();
}
if(mismatches_lists.exist(J_gene_seq)){
const vector<int>& j_mismatch_list = *mismatches_lists.at(J_gene_seq);
this->scenario_n_mismatches+=j_mismatch_list.size();
}
if(this->output_scenarios){
if(this->best_scenarios_vec.size()<this->n_scenarios_counted){
if(this->best_scenarios_vec.empty()){
this->best_scenarios_vec.emplace_back(scenario_seq_joint_proba,this->scenario_n_genomic,this->scenario_n_mismatches);
}
else{
vector<tuple<double,size_t,size_t>>::iterator jter = this->best_scenarios_vec.begin();
while( (scenario_seq_joint_proba>get<0>(*jter)) and (jter != this->best_scenarios_vec.end()) ){
++jter;
}
this->best_scenarios_vec.emplace(jter , scenario_seq_joint_proba,this->scenario_n_genomic,this->scenario_n_mismatches);
}
}
else{
if(scenario_seq_joint_proba > get<0>(this->best_scenarios_vec[0])){
auto jter = this->best_scenarios_vec.begin()+1;
while( (scenario_seq_joint_proba>get<0>(*jter)) and (jter != this->best_scenarios_vec.end()) ){
++jter;
}
this->best_scenarios_vec.emplace(jter , scenario_seq_joint_proba,this->scenario_n_genomic,this->scenario_n_mismatches);
this->best_scenarios_vec.erase(this->best_scenarios_vec.begin());
}
}
}
//Add the contributions to the average mutation/genomic counters
this->sequence_average_n_genomic+=scenario_seq_joint_proba*this->scenario_n_genomic;
this->sequence_average_n_mismatches+=scenario_seq_joint_proba*this->scenario_n_mismatches;
this->sequence_average_error_freq+=scenario_seq_joint_proba*((double)this->scenario_n_mismatches/(double)this->scenario_n_genomic);
//Reset dummy variables
this->scenario_n_genomic = 0;
this->scenario_n_mismatches = 0;
}
void Errors_counter::count_sequence(double seq_likelihood , const Model_marginals& single_seq_marginals , const Model_Parms& single_seq_model_parms){
for(vector<tuple<double,size_t,size_t>>::iterator iter = this->best_scenarios_vec.begin() ; iter!=this->best_scenarios_vec.end() ; ++iter){
get<0>(*iter)/=seq_likelihood;
//If an exception is thrown here there is a problem upstream
}
//Re normalize the mutation frequency
this->sequence_average_n_genomic/=seq_likelihood;
this->sequence_average_n_mismatches/=seq_likelihood;
this->sequence_average_error_freq/=seq_likelihood;
}
void Errors_counter::initialize_counter(const Model_Parms& parms , const Model_marginals& marginals){
if(not fstreams_created){
//Create the individual scenarios file
if(this->n_scenarios_counted>0){
output_scenario_errors_file_ptr = shared_ptr<ofstream>(new ofstream);
this->output_scenario_errors_file_ptr->open(path_to_file + "scenarios_background_and_errors.csv");
//Create the header
(*this->output_scenario_errors_file_ptr.get())<<"seq_index;scenario_rank;scenario_proba_cond_seq;n_genomic_nt;n_mismatches"<<endl;
}
//Create the average mutation rate scenario file
output_sequence_averaged_errors_file_ptr = shared_ptr<ofstream>(new ofstream);
this->output_sequence_averaged_errors_file_ptr->open(path_to_file + "sequence_mutation_frequency.csv");
//Create the header
(*this->output_sequence_averaged_errors_file_ptr.get())<<"seq_index;n_genomic_nt;n_mismatches;average_mutation_frequency"<<endl;
fstreams_created = true;
}
}
void Errors_counter::add_checked(shared_ptr<Counter> counter){
return ;
}
void Errors_counter::dump_sequence_data(int seq_index , int iteration_n){
//Output individual scenarios stats
if(this->output_scenarios){
size_t counter = 1;
for(vector<tuple<double,size_t,size_t>>::reverse_iterator iter = this->best_scenarios_vec.rbegin() ; iter!=this->best_scenarios_vec.rend() ; ++iter){
(*this->output_scenario_errors_file_ptr.get())<<seq_index<<";"<<counter<<";"<<get<0>(*iter)<<";"<<get<1>(*iter)<<";"<<get<2>(*iter)<<endl;
++counter;
}
}
//Output sequence stats
(*this->output_sequence_averaged_errors_file_ptr.get())<<seq_index<<";"<<this->sequence_average_n_genomic<<";"<<this->sequence_average_n_mismatches<<";"<<this->sequence_average_error_freq<<endl;
best_scenarios_vec.clear();
this->sequence_average_n_genomic = 0;
this->sequence_average_n_mismatches = 0;
this->sequence_average_error_freq = 0;
}
shared_ptr<Counter> Errors_counter::copy() const{
shared_ptr<Errors_counter> counter_copy_ptr (new Errors_counter(this->n_scenarios_counted));
counter_copy_ptr->fstreams_created = this->fstreams_created;
if(this->fstreams_created){
counter_copy_ptr->output_scenario_errors_file_ptr = this->output_scenario_errors_file_ptr;
counter_copy_ptr->output_sequence_averaged_errors_file_ptr = this->output_sequence_averaged_errors_file_ptr;
}
else{
throw runtime_error("Counters should not be copied before stream initalization in Errors_counter::copy()");
}
return counter_copy_ptr;
}
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