public void SaveRealDataOnDB()
{
using (var realDataRepository = new MongoRepository.RealDataRepository())
{
//We clear the collection
realDataRepository.removeAll();
//We stock the retrieved diseases in DB
realDataRepository.insert(RealData);
}
}
public void SaveRealDataOnDB()
{
using (var realDataRepository = new MongoRepository.RealDataRepository())
{
//We clear the collection
realDataRepository.removeAll();
//We stock the retrieved diseases in DB
//realDataRepository.insert(RealData);
Console.WriteLine("InsertRealDataInDB start...");
List <DiseaseData> listDiseaseData = RealData.DiseaseDataList;
if (listDiseaseData.Count != 0)
{
try
{
//Cut in listDiseaseData.Count parts
int numberOfDocument = listDiseaseData.Count;
for (int i = 0; i < numberOfDocument; i++)
{
realDataRepository.insert(
new DiseasesData(
type.Symptom,
listDiseaseData
.Skip(i)
.Take(1)
.ToList()
)
);
}
}
catch (Exception e)
{
Console.WriteLine(e);
Console.WriteLine("Error on insertion of RealData");
}
}
else
{
Console.WriteLine("0 realData to insert!");
}
Console.WriteLine("InsertRealDataInDB finished!");
}
}
static void Main(string[] args)
{
//Environnement variables
var path = Environment.GetEnvironmentVariable("RD_AGGREGATOR_SETTINGS");
ConfigurationManager.Instance.Init(path);
//TESTED AND DONE
//Update Orphanet (diseases/real datasets)
OrphaEngine orphaEngine = new OrphaEngine();
orphaEngine.Start();
//Retrieving diseases from DB
List <Disease> lst_diseases = new List <Disease>();
using (var db = new MongoRepository.DiseaseRepository())
{
lst_diseases = db.selectAll().Take(27).ToList();
//lst_diseases = db.selectAll();
}
//TESTED AND DONE
//Update Publications
PubmedEngine pubmedEngine = new PubmedEngine();
Console.WriteLine("Starting requests at PMC this can take some time...");
pubmedEngine.Start2(lst_diseases);
//Update number of publications per disease
Console.WriteLine("Update number of publications per disease.....");
using (var dbDisease = new MongoRepository.DiseaseRepository())
using (var dbPublication = new MongoRepository.PublicationRepository())
{
//Update all diseases
foreach (var disease in lst_diseases)
{
long numberPublications = dbPublication.countForOneDisease(disease.OrphaNumber);
disease.NumberOfPublications = (int)numberPublications;
dbDisease.updateDisease(disease);
}
}
Console.WriteLine("Update number of publications per disease finished");
//Retrieving related entities by disease AND TextMine
TextMiningEngine textMiningEngine = new TextMiningEngine();
RecupSymptomsAndTextMine(lst_diseases, textMiningEngine);
//RecupLinkedDiseasesAndTextMine(lst_diseases, textMiningEngine);
//RecupDrugsAndTextMine(lst_diseases, textMiningEngine);
//Retrieving PredictionData and RealData from DB (DiseasesData with type Symptom)
DiseasesData PredictionData = null;
DiseasesData RealData = null;
using (var dbPred = new MongoRepository.PredictionDataRepository())
using (var dbReal = new MongoRepository.RealDataRepository())
{
PredictionData = dbPred.selectByType(type.Symptom);
RealData = dbReal.selectByType(type.Symptom);
}
//Evaluation...
if (PredictionData != null && RealData != null)
{
Evaluator.Evaluate(PredictionData, RealData);
}
Console.WriteLine("Finished :)");
Console.ReadLine();
}
static void Main(string[] args)
{
//Environnement variables
//Environment.SetEnvironmentVariable("RD_AGGREGATOR_SETTINGS", @"C:\Users\Psycho\Source\Repos\RDSearch4\settings.json");
Environment.SetEnvironmentVariable("RD_AGGREGATOR_SETTINGS", @"C:\Users\CharlesCOUSYN\source\repos\Aggregator\settings.json");
var path = Environment.GetEnvironmentVariable("RD_AGGREGATOR_SETTINGS");
ConfigurationManager.Instance.Init(path);
//Obtain all symptoms/phenotypes
PhenotypeEngine phenotypeEngine = new PhenotypeEngine();
phenotypeEngine.GetSymptomsList();
/*
* //TESTED AND DONE
* //Update Orphanet (diseases/real datasets)
* OrphaEngine orphaEngine = new OrphaEngine(phenotypeEngine);
* orphaEngine.Start();*/
//Retrieving diseases from DB
List <Disease> lst_diseases = new List <Disease>();
using (var db = new MongoRepository.DiseaseRepository())
{
//lst_diseases = db.selectAll().Take(50).ToList();
lst_diseases = db.selectAll();
}
//TESTED AND DONE
/*
* //Update Publications
* PubmedEngine pubmedEngine = new PubmedEngine();
* Console.WriteLine("Starting requests at PMC this can take some time...");
* pubmedEngine.Start2(lst_diseases);
*/
/*
* //Update number of publications per disease
* Console.WriteLine("Update number of publications per disease.....");
* using (var dbDisease = new MongoRepository.DiseaseRepository())
* using (var dbPublication = new MongoRepository.PublicationRepository())
* {
* //Update all diseases
* foreach (var disease in lst_diseases)
* {
* long numberPublications = dbPublication.countForOneDisease(disease.OrphaNumber);
* disease.NumberOfPublications = (int)numberPublications;
* dbDisease.updateDisease(disease);
* }
* }
* Console.WriteLine("Update number of publications per disease finished");
*/
//Retrieving related entities by disease AND TextMine
/*
* TextMiningEngine textMiningEngine = new TextMiningEngine(phenotypeEngine);
* RecupSymptomsAndTextMine(lst_diseases, textMiningEngine);*/
//Retrieving PredictionData and RealData from DB (DiseasesData with type Symptom)
DiseasesData PredictionData = null;
DiseasesData RealData = null;
using (var dbPred = new MongoRepository.PredictionDataRepository())
using (var dbReal = new MongoRepository.RealDataRepository())
{
PredictionData = dbPred.selectByType(type.Symptom);
RealData = dbReal.selectByType(type.Symptom);
}
//Evaluation...
if (PredictionData != null && RealData != null)
{
Console.WriteLine("Evaluation....");
//Testing all combinaisons
MetaResults metaResults = Evaluator.MetaEvaluate(PredictionData, RealData, Evaluation.entities.Criterion.MeanRankRealPositives);
Evaluator.WriteMetaResultsJSONFile(metaResults);
//Having best combinaison and evaluate with it
Tuple <TFType, IDFType> tupleToTest = new Tuple <TFType, IDFType>(metaResults.bestInfos.TFType, metaResults.bestInfos.IDFType);
//Evaluate basically
Results resultsOfBestCombinaison = Evaluator.Evaluate(PredictionData, RealData, tupleToTest);
Evaluator.WriteResultsJSONFile(resultsOfBestCombinaison);
//Evaluate best combinaison with threshold search
MetaResultsWeight metaResultsWeight = Evaluator.MetaWeightEvaluate(PredictionData, RealData, tupleToTest, 0.0005, Evaluation.entities.Criterion.F_Score);
Evaluator.WriteMetaResultsWeightJSONFile(metaResultsWeight);
Console.WriteLine("Evaluation finished!");
}
Console.WriteLine("Finished :)");
Console.ReadLine();
}
