public static IReadOnlyList <ChemicalWithData> GetSet(Dictionary <string, string> Modelinfo, TbScale ScaleDeclaration, String Set)
{
List <ChemicalWithData> SetList = new List <ChemicalWithData>();
var setup = new BridgeSetup(false);
//setup.AddAllJarsClassPath(@"B:\ToolboxAddinExamples\lib");
setup.AddAllJarsClassPath(System.IO.Path.GetDirectoryName(System.Reflection.Assembly.GetExecutingAssembly().Location));
Bridge.CreateJVM(setup);
Bridge.RegisterAssembly(typeof(ChemicalinSet).Assembly);
java.util.List list = ChemicalinSet.getDataset(Modelinfo["tag"], Set);
if (list.size() == 0)
{
return(SetList);
}
for (int i = 0; i < list.size(); i++)
{
TbData Mockdescriptordata = new TbData(new TbUnit(TbScale.EmptyRatioScale.FamilyGroup, TbScale.EmptyRatioScale.BaseUnit), new double?());
ChemicalinSet cur_Chemical = (ChemicalinSet)list.get(i);
TbData cur_exp = (TbData)Utilities.ConvertData(cur_Chemical.getExperimental(), ScaleDeclaration, Modelinfo);
SetList.Add(new ChemicalWithData(cur_Chemical.getCAS(), new[] { "N.A." }, cur_Chemical.getSmiles(),
new TbDescribedData[] { new TbDescribedData(Mockdescriptordata, null) },
new TbDescribedData(cur_exp, null)));
}
return(SetList);
}
public PredictionAddin(TbData value, TbMetadata metadata, IReadOnlyDictionary <TbObjectId, TbData> xDescriptorsValues, IReadOnlyList <ISuportingChemicals> suportingChemicals)
{
Value = value;
Metadata = metadata;
XDescriptorsValues = xDescriptorsValues.ToDictionary(kvp => kvp.Key, kvp => kvp.Value);
SuportingChemicals = suportingChemicals;
}
public ITbPrediction Predict(ITbBasket target)
{
target.WorkTask.TbToken.ThrowIfCancellationRequested();
//understand how to pass scalar predictions
TbData predictedTbData = (TbData)Calculate(target);
// var predictedTbData = new TbData(predictedScalarData.Unit, predictedScalarData.Value);
//var targetLogKow =
// target.WorkTask.CalcService.CalculateParameter(_logKowDescriptor.Descriptor, null, target);
//mock descriptor
Dictionary <string, string> ModelPred = this.RetrieveModelPreD(target, Modelinfo);
TbData Mockdescriptordata = new TbData(new TbUnit(TbScale.EmptyRatioScale.FamilyGroup, TbScale.EmptyRatioScale.BaseUnit), new double?());
//TODO pack additional metadata into an unique object and then predicton probably will be faster
Dictionary <string, string> AdditionalMetadata = new Dictionary <string, string>()
{
{
"Guide name",
this.Modelinfo["GuideUrl"]
}
};
if (ModelPred.ContainsKey("assessment"))
{
AdditionalMetadata.Add("Assessment", ModelPred["assessment"]);
}
if (ModelPred.ContainsKey("assessment_verbose"))
{
AdditionalMetadata.Add("Brief Explanation", ModelPred["assessment_verbose"]);
}
if (ModelPred.ContainsKey("Similar_molecules_smiles"))
{
AdditionalMetadata.Add("Analogues' SMILES", ModelPred["Similar_molecules_smiles"]);
}
//if (Modelinfo.ContainsKey("QMRFlink"))
// AdditionalMetadata.Add("QMRF", Modelinfo["QMRFlink"]);
//if (Modelinfo.ContainsKey("Lambda"))
//{
// AdditionalMetadata.Add("Lambda", double.Parse(this.Modelinfo["Lambda"], CultureInfo.InvariantCulture).ToString());
//}
Dictionary <TbObjectId, TbData> matrixdescriptorvalues = new Dictionary <TbObjectId, TbData>()
{
{
this.objectId,
Mockdescriptordata
}
};
//run method Retrieve ADI, to retrieve all adi indexes
Dictionary <string, TbData> ADImetadata = this.RetrieveAdi(target, Modelinfo);
TbMetadata metadata = new TbMetadata((IReadOnlyDictionary <string, string>)AdditionalMetadata, (IReadOnlyDictionary <string, TbData>)ADImetadata);
//return new PredictionAddin(predictedTbData, predictionDescription, xData);
return(new PredictionAddin(predictedTbData, metadata, matrixdescriptorvalues, null));
}
