public QsarAddin(Dictionary <string, string> Modelinfo, TbScale ScaleDeclaration, TbObjectId objectId)
{
this.Modelinfo = Modelinfo;
this.ScaleDeclaration = ScaleDeclaration;
this.objectId = objectId;
//CHANGED TO UNITNAME, not anymore log units
this.qsarUnit = new TbUnit(ScaleDeclaration.Name, Modelinfo["UnitName"]);
}
public static TbScalarData ConvertData(string stringvalue, TbScale ScaleDeclaration, Dictionary <string, string> Modelinfo)
{
//understand how to pass qualitative predictions
if (ScaleDeclaration is TbQualitativeScale scaleDeclaration)
{
// TbQualitativeScale scaleD = (TbQualitativeScale)this.ScaleDeclaration;
if (!scaleDeclaration.Labels.Any <string>((Func <string, bool>)(l => l.Equals(stringvalue, StringComparison.InvariantCultureIgnoreCase))))
{
throw new Exception(string.Format("\"{0}\" is not a prediction for the declared scale.", (object)stringvalue));
}
return((TbData) new TbData(new TbUnit(ScaleDeclaration.Name, stringvalue), new double?()));
}
if (Modelinfo["Unit"] == "a-dimensional")
{
//labda is read from csv, for this reason should follow different rules than other parsers
double lambda = DoubleParser(Modelinfo["Lambda"]);
double value = DoubleParser(stringvalue);
return((TbData) new TbData(new TbUnit(ScaleDeclaration.Name, "mmol/L"), BoxCox(lambda, value)));
//AFTER INTANTIATING ALL CLASSIFICATION MODELS RUN THIS
//}
//if (this.Modelinfo["Unit"] == "no unit")
//{
// return (TbData)new TbData(qsarUnit, runmodel(target, this.Modelinfo["tag"], "prediction"));
}
//workaroud for the lack of conversion for Log unitfamily
Regex regexloginv = new Regex(@"log\(1/.*");
//Doesn't work, don't ask why
if (regexloginv.IsMatch(Modelinfo["Unit"]))
{
double value = DoubleParser(stringvalue);
return((TbData) new TbData(new TbUnit(ScaleDeclaration.Name, Modelinfo["UnitName"]), Math.Pow(10, value * -1)));
}
Regex regex = new Regex(@"log\(.*");
//Doesn't work, don't ask why
if (regex.IsMatch(Modelinfo["Unit"]) & Modelinfo["Unit"] != "log(cm/h)")
{
double value = DoubleParser(stringvalue);
return((TbData) new TbData(new TbUnit(ScaleDeclaration.Name, Modelinfo["UnitName"]), Math.Pow(10, value)));
}
else
{
double value = DoubleParser(stringvalue);
return((TbData) new TbData(new TbUnit(ScaleDeclaration.Name, Modelinfo["UnitName"]), value));
}
}
public static IReadOnlyList <ChemicalWithData> getSet(Dictionary <string, string> Modelinfo, TbScale ScaleDeclaration, string set)
{
TbUnit qsarunit = new TbUnit(ScaleDeclaration.Name, Modelinfo["Unit"]);
List <ChemicalWithData> DataSet = new List <ChemicalWithData>();
List <Dictionary <string, string> > ChemicalsDict = CSVtoDict(Modelinfo);
foreach (Dictionary <string, string> ChemicalDict in ChemicalsDict)
{
int Cas = Convert.ToInt32(string.Join(null, System.Text.RegularExpressions.Regex.Split(ChemicalDict["CAS"], "[^\\d]")));
string name = ChemicalDict["ID"];
string smiles = ChemicalDict["SMILES"];
string SetInfo = ChemicalDict["Set"];
double Experimental = double.Parse(ChemicalDict["Exp"], CultureInfo.InvariantCulture);
if (SetInfo == set)
{
ChemicalWithData chemical = new ChemicalWithData(Cas, new[] { name }, smiles,
new[] { new TbDescribedData(new TbData(qsarunit, new double?()), null) },
new TbDescribedData(new TbData(qsarunit, Experimental), null));
DataSet.Add(chemical);
}
}
return(DataSet);
}
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);
}
