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// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
#include <BALL/FORMAT/commandlineParser.h>
#include <BALL/QSAR/registry.h>
#include <BALL/QSAR/featureSelection.h>
#include <BALL/QSAR/configIO.h>
#include <BALL/QSAR/registry.h>
#include <fstream>
using namespace BALL::QSAR;
using namespace BALL;
using namespace std;
void startModelCreation(ModelConfiguration& conf, QSARData* q, String* data_filename);
void startModelCreation(ifstream& in, QSARData* q, String* data_filename)
{
ModelConfiguration conf = ConfigIO::readModelConfiguration(&in);
if(conf.done) return; // stop processing this section
startModelCreation(conf, q, data_filename);
}
void startModelCreation(ModelConfiguration& conf, QSARData* q, String* data_filename)
{
bool created_data_object=0;
if(q==NULL || data_filename==NULL || conf.data_file!=*data_filename)
{
if(q==NULL)
{
q = new QSARData;
created_data_object=1;
}
q->readFromFile(conf.data_file);
if(data_filename) *data_filename = conf.data_file;
}
else
{
Log.level(2)<<"[ModelCreator debug-info:] QSARData object for file "<<conf.data_file<<" already in memory; not reading it again."<<endl;
}
Registry reg;
Model* model;
bool kernel=0;
RegistryEntry* entry = reg.getEntry(conf.model_no);
if(entry->create!=NULL)
{
model = (*entry->create)(*q);
}
else
{
if(conf.kernel_type==0 || conf.kernel_par1==0)
{
Log.error()<<"For kernel based model, kernel-type and kernel-parameter(s) must be specified!"<<endl;
return;
}
model = (*entry->createKernel1)(*q,conf.kernel_type,conf.kernel_par1, conf.kernel_par2);
kernel=1;
}
if(conf.model_parameters.size()>0)
{
model->setParameters(conf.model_parameters);
}
if(!conf.no_training && conf.optimize_model_parameters)
{
if(conf.k_fold==0)
{
Log.error()<<"'k_fold' must be set if model parameters are to be optimized!"<<endl;
return;
}
model->optimizeParameters(conf.k_fold);
}
if(!conf.no_training && kernel && conf.grid_search_steps>0)
{
if(conf.k_fold==0)
{
Log.error()<<"'k_fold' must be set if grid search is to be done!"<<endl;
return;
}
if(conf.grid_search_stepwidth==0 && conf.kernel_type!=2)
{
Log.error()<<"'grid_search_stepwidth' must be set if grid search is to be done!"<<endl;
return;
}
((KernelModel*)model)->kernel->gridSearch(conf.grid_search_stepwidth, conf.grid_search_steps, conf.grid_search_recursions, conf.k_fold);
}
model->readTrainingData();
if(!conf.no_training)
{
try
{
model->train();
}
catch(BALL::Exception::GeneralException e)
{
Log.error()<<e.getMessage();
}
}
model->saveToFile(conf.output);
if(created_data_object) delete q;
delete model;
}
#ifndef EXT_MAIN
int main(int argc, char* argv[])
{
CommandlineParser par("ModelCreator","create a QSAR model ","1.1",String(__DATE__), "QuEasy (QSAR)");
par.registerMandatoryInputFile("i", "input dat-file");
par.registerMandatoryOutputFile("o", "output model file");
par.registerMandatoryStringParameter("type", "model type");
par.registerOptionalStringParameter("kernel", "kernel type (in case of kernel-model)");
Registry reg;
list<String> restr;
for(RegistryEntryIterator it=reg.beginEntry(); it!=reg.endEntry(); it++)
{
restr.push_back(it->second.name_abreviation);
}
par.setParameterRestrictions("type", restr);
restr.clear();
restr.push_back("none");
restr.push_back("polynomial");
restr.push_back("rbf");
restr.push_back("sigmoidal");
par.setParameterRestrictions("kernel", restr);
String man = "ModelCreator creates a QSAR model using an input data set as generated by InputReader.\n\nThe type of QSAR model to be used can be specified by '-type', the type of kernel-function (if any) can be chosen by '-kernel'. Optimization of model- and kernel-parmeters will be done automatically using cross-validation.\n\nOutput of this tool is a model-file that can be used by other QuEasy tools (e.g. FeatureSelector).";
par.setToolManual(man);
par.setSupportedFormats("i","dat");
par.setSupportedFormats("o","mod");
par.parse(argc,argv);
ModelConfiguration conf;
conf.data_file = par.get("i");
conf.output = par.get("o");
conf.optimize_model_parameters = true;
conf.kernel_par1 = reg.default_kernel_par1;
conf.kernel_par1 = reg.default_kernel_par2;
conf.k_fold = reg.default_k;
conf.grid_search_recursions = reg.default_gridsearch_recursion;
conf.grid_search_stepwidth = reg.default_gridsearch_stepwidth;
conf.grid_search_steps = reg.default_gridsearch_steps;
try
{
conf.model_no = reg.getModelNo(par.get("type"));
}
catch(BALL::Exception::GeneralException e)
{
cerr << "A model-type '"<<par.get("type")<<"' does not exist; possible choices are:"<<endl;
for(RegistryEntryIterator it=reg.beginEntry(); it!=reg.endEntry(); it++)
{
cerr<<" "<<it->second.name_abreviation<<" : "<<it->second.name<<" ";
if(it->second.regression) cerr<<"(regression)"<<endl;
else cerr<<"(classification)"<<endl;
}
cerr<<endl;
exit(1);
}
String kernel = par.get("kernel");
if(kernel!=CommandlineParser::NOT_FOUND && kernel != "none")
{
if(!reg.getEntry(par.get("type"))->kernel)
{
cerr << "[Error:] The chosen model-type has no kernel but you specified a kernel-type!"<<endl;
exit(1);
}
if(kernel=="polynomial")
{
conf.kernel_type = 1;
}
else if(kernel=="rbf")
{
conf.kernel_type = 2;
}
else if(kernel=="sigmoidal")
{
conf.kernel_type = 3;
}
else
{
cerr << "Specified kernel-type '"<<kernel<<"' unknown; possible choices are: polynomial, rbf, sigmoidal"<<endl;
exit(1);
}
}
startModelCreation(conf,0,0);
}
#endif
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