DEC/processor/Settings.cpp

#include "Settings.h"
#include <vector>
#include <iostream>
#include <fstream>
#include <cstdio>
#include <boost/algorithm/string.hpp>
#include <boost/tokenizer.hpp>

#ifdef LINUX
#define sscanf_s sscanf
#endif

// Default parameters
bool		Settings::WRITE_FULL_STATISTICS_TO_FILE = false;

int			Settings::Iterations = 10;
long int	Settings::InitPopSize = 10;
float		Settings::InitRatioBetweenPops = 1.f;

double		Settings::BirthRate = 0.01;
double		Settings::NaturalDeathRate = 0.01;

long int	Settings::KMaxParameter = 10000;

int			Settings::OffspringsMean = 3;
float		Settings::CoadaptiveThreshold = 0;
float		Settings::CoadaptiveMinimumP = 0.2f;
float		Settings::CoadaptiveMaximumTrait = 15.f;

float		Settings::DiseaseThreshold = 1;
std::string Settings::CoadaptiveGenesInteraction = "onechromosome";
std::string Settings::DiseaseGenesInteraction = "add";


std::string Settings::BreedingStrategy = "default";
std::string Settings::GenToPhenStrategy = "default";
std::string Settings::PhenToFitStrategy = "default";
std::string Settings::RecombinationStrategy = "default";

double Settings::ProbMtDNARecomb = 0.0;
int Settings::PopulationHomoInitSize = 1000;
int Settings::PopulationAncientInitSize = 1000;
double Settings::migrationPartHomoToAncient = 0.1;
double Settings::migrationPartAncientToHomo = 0.1;
int Settings::generationsPerMigration = 100;
int Settings::locusLength = 60;
double Settings::percentDiffLoci = 0.1;
int Settings::numLoci = 50;
// (END) Default parameters

void Settings::initScript(std::string fileName){
	std::vector<std::string> script;
	std::ifstream file(fileName.c_str());
	std::string str;

	while(getline(file,str)){
		if(str.length() > 2)
			script.push_back(str);
	}
	file.close();

	// process Script
	unsigned int curLine;
	for(curLine = 0; curLine < script.size(); curLine++){
		if(script.at(curLine).at(0) == '/' || script.at(curLine).at(0) == '#')
			continue;

		std::vector<std::string > tokensVector; // Search for tokens
		boost::split(tokensVector, script.at(curLine), boost::is_any_of("=") );

		std::string instr = tokensVector.at(0);
		boost::to_lower(instr);
		boost::trim(instr);
		
		// <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
		if(instr == "fullstat"){
			int flag = 0;
			sscanf_s(tokensVector.at(1).c_str(),"%d", &flag);
			if(flag != 0)
				Settings::WRITE_FULL_STATISTICS_TO_FILE = true;
		}
		else if(instr == "generations" || instr == "iterations" ){
			int iter = Settings::Iterations;
			sscanf_s(tokensVector.at(1).c_str(),"%d", &iter);
			Settings::Iterations = iter;
		}
		else if(instr == "initpopsize" || instr == "init_pop_size" || instr == "popsize" ){
			long int size = Settings::InitPopSize;
			sscanf_s(tokensVector.at(1).c_str(),"%ld", &size);
			Settings::InitPopSize = size;
		}
		else if(instr == "initratio" || instr == "init_ratio" || instr == "init_ratio_between_pop_size" ){
			float size = Settings::InitRatioBetweenPops;
			sscanf_s(tokensVector.at(1).c_str(),"%f", &size);
			Settings::InitRatioBetweenPops = size;
		}
		else if(instr == "birth" || instr == "birthrate" || instr == "birth_rate" ){
			double rate = Settings::BirthRate;
			sscanf_s(tokensVector.at(1).c_str(),"%lg", &rate);
			Settings::BirthRate = rate;
		}
		else if(instr == "death" || instr == "deathrate" || instr == "death_rate" ){
			double rate = Settings::NaturalDeathRate;
			sscanf_s(tokensVector.at(1).c_str(),"%lg", &rate);
			Settings::NaturalDeathRate = rate;
		}
		else if(instr == "kmax"){
			long int kMax = Settings::KMaxParameter;
			sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
			Settings::KMaxParameter = kMax;
		}
		else if(instr == "offsprings" || instr == "offsprings_mean" ){
			int offsprings = Settings::OffspringsMean;
			sscanf_s(tokensVector.at(1).c_str(),"%d", &offsprings);
			Settings::OffspringsMean = offsprings;
		}
		else if(instr == "coadaptivet" || instr == "coadaptive_threshold" ){
			float coadaptive = Settings::CoadaptiveThreshold;
			sscanf_s(tokensVector.at(1).c_str(),"%f", &coadaptive);
			Settings::CoadaptiveThreshold = coadaptive;
		}
		else if(instr == "coadaptivemax" || instr == "coadaptive_maximum_trait" ){
			float coadaptive = Settings::CoadaptiveMaximumTrait;
			sscanf_s(tokensVector.at(1).c_str(),"%f", &coadaptive);
			Settings::CoadaptiveMaximumTrait = coadaptive;
		}
		else if(instr == "coadaptivemin" || instr == "coadaptive_minimum_p" ){
			float coadaptive = Settings::CoadaptiveMinimumP;
			sscanf_s(tokensVector.at(1).c_str(),"%f", &coadaptive);
			Settings::CoadaptiveMinimumP = coadaptive;
		}
		else if(instr == "diseaset" || instr == "disease_threshold" ){
			float disease = Settings::DiseaseThreshold;
			sscanf_s(tokensVector.at(1).c_str(),"%f", &disease);
			Settings::DiseaseThreshold = disease;
		}
		else if(instr == "coadaptivegenesinteract" || instr == "cgi"){
			//long int kMax = Settings::KMaxParameter;
			//sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
			std::string cgi = tokensVector.at(1);
			boost::to_lower(cgi);
			boost::trim(cgi);
			Settings::CoadaptiveGenesInteraction = cgi;
		}
		else if(instr == "diseasegenesinteract" || instr == "dgi"){
			//long int kMax = Settings::KMaxParameter;
			//sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
			std::string dgi = tokensVector.at(1);
			boost::to_lower(dgi);
			boost::trim(dgi);
			Settings::DiseaseGenesInteraction = dgi;
		}
		//*****************************
		else if(instr == "breedings"){
			//long int kMax = Settings::KMaxParameter;
			//sscanf_s(tokensVector.at(1).c_str(),"%ld", &kMax);
			std::string strategy = tokensVector.at(1);
			boost::to_lower(strategy);
			boost::trim(strategy);
			Settings::BreedingStrategy = strategy;
		}
	} // (END) for(curLine = 0; curLine < script.size(); curLine++)
}