/// <summary>
/// Checks the defaults.
/// </summary>
public void checkDefaults()
{
experimentSetup setup = experimentSetup.GetDefaultExperimentSetup();
if (folderForClassifierSets.findFile(NAMEFORDEFAULT).isNullOrEmpty())
{
setup = experimentSetup.GetDefaultExperimentSetup();
setup.name = "default";
setup.featureVectorExtractors_semantic.Clear();
objectSerialization.saveObjectToXML(setup, folderForClassifierSets.pathFor(NAMEFORDEFAULT, imbSCI.Data.enums.getWritableFileMode.overwrite, "Default set of classifiers"));
}
if (folderForFeatureVectorExtractors.findFile(NAMEFORDEFAULT).isNullOrEmpty())
{
setup = experimentSetup.GetDefaultExperimentSetup();
setup.name = "default";
setup.classifiers_settings.Clear();
objectSerialization.saveObjectToXML(setup.featureVectorExtractors_semantic.First(), folderForFeatureVectorExtractors.pathFor(NAMEFORDEFAULT, imbSCI.Data.enums.getWritableFileMode.overwrite, "Default FVE"));
}
setup = experimentSetup.GetDefaultExperimentSetup();
setup.classifiers.Clear();
setup.classifiers_settings.Clear();
setup.featureVectorExtractors_semantic.Clear();
if (folderForExperimentShells.findFile(NAMEFORDEFAULT).isNullOrEmpty())
{
objectSerialization.saveObjectToXML(setup, folderForExperimentShells.pathFor(NAMEFORDEFAULT, imbSCI.Data.enums.getWritableFileMode.overwrite, "Default setup schell"));
}
}
public semanticFVExtractor CreateExperiment(experimentSetup model, ILogBuilder output)
{
if (model == null)
{
model = blueprint;
}
semanticFVExtractor fve = model.models.First() as semanticFVExtractor;
String serializedModel = objectSerialization.ObjectToXML(model);
foreach (experimentTemplateVariable variable in replacements)
{
String newModelXML = serializedModel;
serializedModel = serializedModel.Replace(variable.needle, variable.replace);
semanticFVExtractor newModel = objectSerialization.ObjectFromXML <semanticFVExtractor>(newModelXML);
newModel.name = newModel.GetShortName(name);
newModel.description = newModel.GetShortDescription();
output.log("-- created model: " + newModel.name);
//experiment.featureVectorExtractors_semantic.Add(newModel);
}
//for (INt32 i = start; i < end; i++)
//{
// String newModelXML = serializedModel;
// newModelXML = newModelXML.Replace(needle, "<caseTermExpansionSteps>" + i + "</caseTermExpansionSteps>");
//}
return(fve);
}
public static experimentSetup GetDefaultExperimentSetup()
{
experimentSetup setup = new experimentSetup();
setup.classifiers_settings.Add(new WebPostClassifierSettings(WebPostClassifierType.kNearestNeighbors, "kNN"));
setup.classifiers_settings.Add(new WebPostClassifierSettings(WebPostClassifierType.multiClassSVM, "mSVM"));
setup.classifiers_settings.Add(new WebPostClassifierSettings(WebPostClassifierType.naiveBayes, "nBayes"));
setup.classifiers_settings.Add(new WebPostClassifierSettings(WebPostClassifierType.backPropagationActivationNeuralNetwork, "bpANN"));
//= new List<pos_type> { pos_type.A, pos_type.N };
var tfe = new semanticFVExtractor();
tfe.termTableConstructor.settings.allowedLemmaTypes.AddUnique(pos_type.A);
tfe.termTableConstructor.settings.allowedLemmaTypes.AddUnique(pos_type.N);
var sfe = new semanticFVExtractor();
sfe.termTableConstructor.settings.allowedLemmaTypes.AddUnique(pos_type.A);
sfe.termTableConstructor.settings.allowedLemmaTypes.AddUnique(pos_type.N);
setup.featureVectorExtractors_semantic.Add(tfe);
setup.featureVectorExtractors_semantic.Add(sfe);
setup.validationSetup.name = setup.name;
setup.validationSetup.k = 5;
setup.setClassifiers();
return(setup);
}
protected void DeployBlueprint(experimentSetup _blueprint)
{
blueprint = _blueprint;
if (blueprint.featureVectorExtractors_semantic.Any())
{
blueprint.featureVectorExtractors_semantic.RemoveRange(1, blueprint.featureVectorExtractors_semantic.Count - 1);
}
}
public experimentTemplate MakeTemplate([Description("Name of the experiment to process")] experimentSetup experiment,
[Description("Starting value for Stx")] Int32 start = 3,
[Description("Ending value for Sts")] Int32 end = 8,
[Description("3 or 4 letter code indicating how the settings are different then in other experiments")] String name = "",
[Description("Comment line for experiment header")] String comment = "",
experimentTemplateOption option = experimentTemplateOption.STX)
{
experimentTemplate output = new experimentTemplate();
output.DeriveBlueprint(experiment, name);
output.comment = comment;
semanticFVExtractor model = experiment.models.First() as semanticFVExtractor;
experiment.RemoveAllModelsExcept();
String currentValue = "";
String xmlElementName = "";
switch (option)
{
case experimentTemplateOption.LPF:
currentValue = model.settings.semanticCloudFilter.lowPassFilter.ToString();
xmlElementName = "lowPassFilter";
break;
case experimentTemplateOption.none:
break;
case experimentTemplateOption.REPEAT:
break;
case experimentTemplateOption.STX:
currentValue = model.settings.caseTermExpansionSteps.ToString();
xmlElementName = "caseTermExpansionSteps";
break;
case experimentTemplateOption.TC:
break;
}
for (int i = start; i < end; i++)
{
var exp = new experimentTemplateVariable();
exp.needle = "<" + xmlElementName + ">" + currentValue + "</" + xmlElementName + ">";
exp.replace = "<" + xmlElementName + ">" + i + "</" + xmlElementName + ">";
exp.i = i;
output.replacements.Add(exp);
}
return(output);
}
public void DeriveBlueprint(experimentSetup _blueprint, String _name)
{
DeployBlueprint(_blueprint);
DerivedFromName = blueprint.name;
DerivedFromType = derivedFromType.fromAnExperiment;
name = blueprint.name.getCleanFilepath();
UpdateDescription();
if (_name.isNullOrEmpty())
{
_name = blueprint.name.getCleanFilepath() + "_child";
}
name = _name;
}
/// <summary>
/// Sets the execution context.
/// </summary>
/// <param name="_manager">The manager.</param>
/// <param name="_setup">The setup.</param>
/// <param name="_tools">The tools.</param>
/// <param name="_classes">The classes.</param>
/// <param name="sufix">The sufix.</param>
/// <param name="chunker">The chunker.</param>
/// <param name="_masterExtractor">The master extractor.</param>
/// <param name="_logger">The logger.</param>
public void SetExecutionContext(experimentManager _manager, experimentSetup _setup, classifierTools _tools, DocumentSetClasses _classes, String sufix, chunkComposerBasic chunker, semanticFVExtractor _masterExtractor, ILogBuilder _logger = null)
{
if (_logger == null)
{
_logger = new builderForLog();
aceLog.consoleControl.setAsOutput(_logger, _setup.name);
}
logger = _logger;
chunkComposer = chunker;
setup = _setup;
tools = _tools;
tools.context = this;
classes = _classes;
// masterConstructor = _masterExtractor.termTableConstructor;
masterExtractor = _setup.featureVectorExtractors_semantic.First();
masterConstructor = masterExtractor.termTableConstructor;
manager = _manager;
String expContextName = "exp_" + setup.name.add(sufix, "_");
folder = manager.folder.Add(expContextName, "Experiment " + setup.name, "Directory with all information on the experiment [" + setup.name + "]");
errorNotesFolder = folder.Add("errors", "Error logs", "Directory with error reports produced if an exception occours. Normally, if everything was ok this folder should have only two files inside: directory_readme.txt and empty: note.txt).");
errorNotes = new experimentNotes(errorNotesFolder, "Notes (logs) about critical and non-critical errors that happen during experiment execution. If everything was ok - this file should remain empty");
notes = new experimentNotes(folder, "Notes on experiment setup and execution log");
aceLog.consoleControl.setAsOutput(notes, "Notes");
notes.log("Experiment [" + expContextName + "] initiated");
notes.AppendLine("About: " + setup.description);
notes.AppendHorizontalLine();
notes.SaveNote();
notes.AppendHeading("Feature extraction models");
var lnsc = chunkComposer.DescribeSelf();
lnsc.ForEach(x => notes.AppendLine(x));
notes.AppendLine(" - ");
List <String> mdn = new List <string>();
foreach (var md in setup.models)
{
if (mdn.Contains(md.name))
{
md.name += "_" + mdn.Count.ToString();
}
else
{
mdn.Add(md.name);
}
}
foreach (var md in setup.models)
{
String prefix = md.name;
md.classes = classes;
md.BuildFeatureVectorDefinition();
var lns = md.DescribeSelf();
lns.ForEach(x => notes.AppendLine(x));
kFoldValidationCollection validationCases = classes.BuildValidationCases(prefix, setup.validationSetup.k, tools.DoDebug, logger, folder, setup.validationSetup.randomize);
validationCases.pipelineCollection = pipelineCollection;
validationCases.connectContext(this, md);
validationCollections.Add(md.name, validationCases);
//md.postClassifiers = setup.classifiers;
}
}
