JoinOperator::JoinOperator(std::vector<std::string> expressionList, std::vector<Operator*> children): Operator(children){
this->type = "JOIN";
this->expressions = expressionList;
Schema *lsch = children[0]->getSchema(), *rsch = children[1]->getSchema();
ExpressionParser parser;
joinClause = parser.parse(expressions[0])[0];
updateExpression(joinClause, lsch->getColumnMap(), rsch->getColumnMap(), lsch->getTableName(), rsch->getTableName());
schema = mergeSchemas(lsch, rsch);
}
ProjectionOperator::ProjectionOperator(std::vector<std::string> expressionList, std::vector<Operator*> children) : Operator(children){
this->type = "PROJECT";
this->expressions = expressionList;
schema = children[0]->getSchema();
ExpressionParser parser;
bool allFound = false;
vector<string> attrs = schema->getAttributes();
for(int i = 0; i < expressions.size(); i++){
if(expressions[i] == "*"){
expressions.erase(expressions.begin()+i);
if(!allFound)
expressions.insert(expressions.begin()+i, attrs.begin(), attrs.end());
allFound = true;
}
}
for(int i = 0; i < expressions.size(); i++){
std::vector<Expression*> exps = parser.parse(expressions[i]);
projectionClauses.insert(projectionClauses.end(), exps.begin(), exps.end());
}
}
int main()
{
/**
* Seeding part 1443936225
*/
auto seed = time(NULL);
std::cout << "Hello, no seed was defined, so the program will use the default time(NULL) seed." << std::endl <<
"Your seed is : " + std::to_string(seed) << std::endl;
srand(seed);
/**
* File Opening and reading part
*/
std::string fileName = "/home/sergio/Copy/UFMG/Graduacao/2015_2/ComputacaoNatural/TP1/tests/SR_div.txt";
FileParser fileParser(fileName);
fileParser.getNumberOfVariables();
std::vector<std::string> file = fileParser.getVectorOfTextFile();
for (int generation = 0 ; generation < ExecutionParameters::getInstance().getMaxNumberOfGenerations(); generation++)
{
/**
* Individual creation
*/
std::vector<Individual> individualsList;
for (int i = 0; i < ExecutionParameters::getInstance().getMaxNumberOfIndividuals(); i++)
{
Individual individual;
individualsList.push_back(individual);
}
/**
* Evaluation part
*/
ExpressionParser expressionParser; //expressionParser
Individual bestIndividual, worstIndividual;
bool noBestIndividual = true;
std::vector<Individual> updatedIndividualList;
for (Individual individual : individualsList)
{
//std::cout << individual.getGenotype().getMathematicalExpression() << std::endl; debug cout
expressionParser.setExpression(individual.getGenotype().getMathematicalExpression());
for (auto line : file)
{
if (line == "")
continue;
double variableValues[ExecutionParameters::getInstance().getNumberOfVariables()];
double functionValue;
/**
* Transform into a function
*/
std::istringstream lineStream(line);
for (int i = 0; i < ExecutionParameters::getInstance().getNumberOfVariables(); i++)
{
lineStream >> variableValues[i];
expressionParser.defineVars(variableValues[i]);
}
lineStream >> functionValue;
/**
*
*/
double resultForIndividual = expressionParser.parse();
double individualFitnessScore;
//std::cout << "Results for A = " << variableValues[0] << " :\n\tind: " << resultForIndividual << "\nfun: " << functionValue << std::endl; debug cout
if (!std::isnan(resultForIndividual)) //check whether it has a valid result
{
/**
* The fitness score should be calculated here
*/
double differenceOfFunctionValueAndIndividual = std::fabs(resultForIndividual - functionValue);
individualFitnessScore = individual.getFitnessScore() + differenceOfFunctionValueAndIndividual;
individual.setFitnessScore(individualFitnessScore);
}
else
{
individualFitnessScore = std::nan("");
individual.setFitnessScore(
individualFitnessScore); //Setting individuals with invalid score to NaN so they won't appear in the worst individuals
//One case in which we don't want those individuals is for example the function x^x which can happen, and x can take negative values
expressionParser.clearVars();
updatedIndividualList.push_back(individual);
break;
}
expressionParser.clearVars();
}
if (noBestIndividual && std::isfinite(individual.getFitnessScore()))
{
bestIndividual.Copy(individual);
worstIndividual.Copy(individual);
noBestIndividual = false;
}
if (bestIndividual.getFitnessScore() > individual.getFitnessScore() &&
std::isfinite(individual.getFitnessScore()))
bestIndividual.Copy(individual);
if (worstIndividual.getFitnessScore() < individual.getFitnessScore() &&
std::isfinite(individual.getFitnessScore()))
worstIndividual.Copy(individual);
updatedIndividualList.push_back(individual);
}
individualsList.clear();
individualsList = updatedIndividualList;
IndividualsMetrics individualsMetrics(individualsList, 0.0);
std::cout << "#################\n\tGeneration " << generation << std::endl;
std::cout << "The best individual was : " << bestIndividual.getGenotype().getMathematicalExpression() <<
" with a fitness score of : " << bestIndividual.getFitnessScore() << std::endl;
std::cout << "The worst individual was : " << worstIndividual.getGenotype().getMathematicalExpression() <<
" with a fitness score of : " << worstIndividual.getFitnessScore() << std::endl;
std::cout << "The average fitness of this generation was : " << individualsMetrics.getAverageFitness() <<
std::endl;
std::cout << "The number of repeated individuals on this generation was : " <<
individualsMetrics.getRepeatedIndividuals() << std::endl;
std::cout << "There were " << individualsMetrics.getCrossoverIndividualsWithBetterFitnessThanParents() <<
" individuals generated by crossover better than parents" << std::endl;
}
return 0;
}
