public void AddSearchSpace_EmptyName_Failure()
{
SearchSpace oSearchSpace;
var res = SearchSpace.AddSearchSpace(_mockServer, out oSearchSpace, "");
Assert.IsFalse(res.Success, "Static method for add SearchSpace did not fail with empty name");
}
public void GetSearchSpaces_NullConnectionServer_Failure()
{
List <SearchSpace> oSpaces;
var res = SearchSpace.GetSearchSpaces(null, out oSpaces, 1, 10, "params");
Assert.IsFalse(res.Success, "Calling GetSearchSpaces member did not fail with null Connection server ");
}
public void AddSearchSpace_NullConnectionServer_Failure()
{
SearchSpace oSearchSpace;
var res = SearchSpace.AddSearchSpace(null, out oSearchSpace, "name");
Assert.IsFalse(res.Success, "Static method for add SearchSpace did not fail with null ConnectionServer");
}
public void SearchSpace_Constructor_DisplayNameNotFound_Success()
{
Reset();
SearchSpace oTest = new SearchSpace(_mockServer, "", "Name");
Console.WriteLine(oTest);
}
public void CFO_should_find_maximum_value_when_function_is_convex()
{
var searchSpace = new SearchSpace <LSE3DSearchSpace>();
var initValues = searchSpace.SampleFromFeatureSpace(searchSpace.Default);
var cfo = new CostFrugalTuner(searchSpace, Parameter.FromObject(initValues), false);
double bestMetric = 0;
for (int i = 0; i != 100; ++i)
{
var trialSettings = new TrialSettings()
{
TrialId = 0,
};
var param = cfo.Propose(trialSettings).AsType <LSE3DSearchSpace>();
var x = param.X;
var y = param.Y;
var z = param.Z;
var metric = LSE3D(x, y, z);
bestMetric = Math.Max(bestMetric, metric);
Output.WriteLine($"{i} x: {x} y: {y} z: {z}");
if (x == 10 && y == 10 && z == 10)
{
break;
}
cfo.Update(new TrialResult()
{
DurationInMilliseconds = 1 * 1000,
Metric = metric,
TrialSettings = trialSettings,
});
}
bestMetric.Should().BeGreaterThan(LSE3D(10, 10, 10) - 2);
}
/// <summary>
/// For each block, check whether all hidden dimensions in hiddenList are the same (except for 0).
/// If all hidden dimensions in one block are 0, it will be set to the last hidden dimension
/// (if exists) or the maximum hidden dimension (if not exist).
/// </summary>
/// <returns>The list of hidden dimensions in blocks.</returns>
private List <int> CheckBlockHiddenSize(int blockPerLayer)
{
var hiddenSizePerBlock = new List <int>();
for (var i = 0; i < DistillBlocks; ++i)
{
var hiddenSizesPerBlock = Enumerable.Range(i * blockPerLayer, blockPerLayer)
.Select(j => SearchSpace.ArchHiddenSize[DiscreteArches[j]]).ToArray();
var nextHiddenSize = SearchSpace.CheckHiddenDimensionsAndReturnMax(hiddenSizesPerBlock);
if (nextHiddenSize == 0)
{
if (hiddenSizePerBlock.Count == 0)
{
nextHiddenSize = SearchSpace.ArchHiddenSize[SearchSpace.ArchHiddenSize.Length - 1];
}
else
{
nextHiddenSize = hiddenSizePerBlock[hiddenSizePerBlock.Count - 1];
}
}
hiddenSizePerBlock.Add(nextHiddenSize);
}
return(hiddenSizePerBlock);
}
public void CFO_e2e_test()
{
var searchSpace = new SearchSpace <LbfgsOption>();
var initValues = searchSpace.SampleFromFeatureSpace(searchSpace.Default);
var cfo = new CostFrugalTuner(searchSpace, Parameter.FromObject(initValues));
for (int i = 0; i != 1000; ++i)
{
var trialSettings = new TrialSettings()
{
TrialId = i,
};
var param = cfo.Propose(trialSettings);
var option = param.AsType <CodeGen.LbfgsOption>();
option.L1Regularization.Should().BeInRange(0.03125f, 32768.0f);
option.L2Regularization.Should().BeInRange(0.03125f, 32768.0f);
cfo.Update(new TrialResult()
{
DurationInMilliseconds = i * 1000,
Metric = i,
TrialSettings = trialSettings,
});
}
}
public void SearchSpace_Constructor_ObjectId_Success()
{
Reset();
SearchSpace oTest = new SearchSpace(_mockServer, "ObjectId");
Console.WriteLine(oTest);
}
/// <summary>
/// Initializes the solver so that the optimization can be run.
/// </summary>
/// <exception cref="InvalidOperationException">
/// If not all target nodes are connected to the start node.
/// </exception>
public void Initialize()
{
BuildSearchGraph();
_searchSpace =
_searchGraph.NodeDict.Values.Where(n => IncludeNode(n) && n != StartNodes && !TargetNodes.Contains(n))
.ToList();
var consideredNodes = SearchSpace.Concat(TargetNodes).ToList();
consideredNodes.Add(StartNodes);
Distances.CalculateFully(consideredNodes);
if (_targetNodes.Any(node => !Distances.AreConnected(StartNodes, node)))
{
throw new InvalidOperationException("The graph is disconnected.");
}
// Saving the leastSolution as initial solution. Makes sure there is always a
// solution even if the search space is empty or MaxGeneration is 0.
BestSolution = SpannedMstToSkillnodes(CreateLeastSolution());
var removedNodes = new List <GraphNode>();
var newSearchSpace = new List <GraphNode>();
foreach (var node in SearchSpace)
{
if (IncludeNodeUsingDistances(node))
{
newSearchSpace.Add(node);
}
else
{
removedNodes.Add(node);
}
}
_searchSpace = newSearchSpace;
var remainingNodes = SearchSpace.Concat(TargetNodes).ToList();
remainingNodes.Add(StartNodes);
Distances.RemoveNodes(removedNodes, remainingNodes);
if (_targetNodes.Count / (double)remainingNodes.Count >= PreFilledSpanThreshold)
{
var prioQueue = new LinkedListPriorityQueue <LinkedGraphEdge>(100);
for (var i = 0; i < remainingNodes.Count; i++)
{
for (var j = i + 1; j < remainingNodes.Count; j++)
{
prioQueue.Enqueue(new LinkedGraphEdge(i, j), Distances[i, j]);
}
}
_firstEdge = prioQueue.First;
}
InitializeGa();
_isInitialized = true;
}
public Parameter Propose(SearchSpace searchSpace)
{
var d = searchSpace.FeatureSpaceDim;
var featureVec = Enumerable.Repeat(0, d).Select(i => _rnd.NextDouble()).ToArray();
return(searchSpace.SampleFromFeatureSpace(featureVec));
}
public void DeleteSearchSpaceMember_EmptyClassData_Failure()
{
SearchSpace oSpace = new SearchSpace(_mockServer);
var res = oSpace.DeleteSearchSpaceMember("PartitionObjectId");
Assert.IsFalse(res.Success, "Calling DeleteSearchSpaceMember from empty class instance should fail");
}
public void GridSearchTuner_should_search_entire_naive_search_space()
{
// the behavior of a grid search tuner is it will exhaustively generate
// candidates from a grid of parameter value. And once exhausted, it will start
// over again.
// So we use the following way to test a grid search tuner: we go through the grid search
// twice, and check if all candidates are repeated twice. By doing so we know if grid search
// tuner either search grid of parameter value exhaustively or or generate candidates exactly one
// time in each search.
// default step is used when an option is continous, like double option or single option.
var defaultStep = 10;
var searchSpace = new SearchSpace <NaiveSearchSpace>();
var tuner = new GridSearchTuner(searchSpace, defaultStep);
var parameters = new List <Parameter>();
// calculate the total steps, which is the sum of all grid points.
var steps = 1;
foreach (var step in searchSpace.Step)
{
steps *= step ?? defaultStep;
}
foreach (var i in Enumerable.Range(0, steps * 2))
{
var settings = new TrialSettings();
parameters.Add(tuner.Propose(settings));
}
steps.Should().Be(600);
parameters.Distinct().Count().Should().Be(steps);
}
public void Update_EmptyClassData_Failure()
{
Reset();
SearchSpace oSpace = new SearchSpace(_mockServer);
var res = oSpace.Update("New Name", "New Description");
Assert.IsFalse(res.Success, "Calling Update from empty class instance should fail");
}
public void Delete_EmptyClassData_Failure()
{
Reset();
SearchSpace oSpace = new SearchSpace(_mockServer);
var res = oSpace.Delete();
Assert.IsFalse(res.Success, "Calling Delete from empty class instance should fail");
}
public void AddSearchSpace_InvalidLocationId_Failure()
{
SearchSpace oSearchSpace;
//invalid locaiton
var res = SearchSpace.AddSearchSpace(_connectionServer, out oSearchSpace, "name", "description", "boguslocation");
Assert.IsFalse(res.Success, "Static method for add SearchSpace did not fail with invalid Location");
}
public void SearchSpace_Test()
{
_errorString = "";
List <SearchSpace> oSearchSpaces;
var res = SearchSpace.GetSearchSpaces(_connectionServer, out oSearchSpaces, 1, 2);
Assert.IsTrue(res.Success & oSearchSpaces.Count > 0, "Failed to fetch SearchSpace:" + res);
Assert.IsTrue(string.IsNullOrEmpty(_errorString), _errorString);
}
public void SearchSpace_Constructor_EmptyObjectIdAndName_Success()
{
Reset();
SearchSpace oTest = new SearchSpace(_mockServer);
Console.WriteLine(oTest.ToString());
Console.WriteLine(oTest.DumpAllProps());
Console.WriteLine(oTest.UniqueIdentifier);
Console.WriteLine(oTest.SelectionDisplayString);
}
private void ResetSearch()
{
if (SearchResults != null)
{
SearchResults.Clear();
}
ImageGrid.Children.Clear();
SearchSpace.ScrollToTop();
ImageGrid.RowDefinitions.Clear();
}
/// <summary>
/// Create a list of <see cref="SweepableEstimator"/> for multiclass classification.
/// </summary>
/// <param name="labelColumnName">label column name.</param>
/// <param name="featureColumnName">feature column name.</param>
/// <param name="exampleWeightColumnName">example weight column name.</param>
/// <param name="useFastForest">true if use fast forest as available trainer.</param>
/// <param name="useLgbm">true if use lgbm as available trainer.</param>
/// <param name="useFastTree">true if use fast tree as available trainer.</param>
/// <param name="useLbfgs">true if use lbfgs as available trainer.</param>
/// <param name="useSdca">true if use sdca as available trainer.</param>
/// <param name="fastTreeOption">if provided, use it as initial option for fast tree, otherwise the default option will be used.</param>
/// <param name="lgbmOption">if provided, use it as initial option for lgbm, otherwise the default option will be used.</param>
/// <param name="fastForestOption">if provided, use it as initial option for fast forest, otherwise the default option will be used.</param>
/// <param name="lbfgsOption">if provided, use it as initial option for lbfgs, otherwise the default option will be used.</param>
/// <param name="sdcaOption">if provided, use it as initial option for sdca, otherwise the default option will be used.</param>
/// <param name="fastTreeSearchSpace">if provided, use it as search space for fast tree, otherwise the default search space will be used.</param>
/// <param name="lgbmSearchSpace">if provided, use it as search space for lgbm, otherwise the default search space will be used.</param>
/// <param name="fastForestSearchSpace">if provided, use it as search space for fast forest, otherwise the default search space will be used.</param>
/// <param name="lbfgsSearchSpace">if provided, use it as search space for lbfgs, otherwise the default search space will be used.</param>
/// <param name="sdcaSearchSpace">if provided, use it as search space for sdca, otherwise the default search space will be used.</param>
/// <returns></returns>
public SweepableEstimator[] MultiClassification(string labelColumnName = DefaultColumnNames.Label, string featureColumnName = DefaultColumnNames.Features, string exampleWeightColumnName = null, bool useFastForest = true, bool useLgbm = true, bool useFastTree = true, bool useLbfgs = true, bool useSdca = true,
FastTreeOption fastTreeOption = null, LgbmOption lgbmOption = null, FastForestOption fastForestOption = null, LbfgsOption lbfgsOption = null, SdcaOption sdcaOption = null,
SearchSpace <FastTreeOption> fastTreeSearchSpace = null, SearchSpace <LgbmOption> lgbmSearchSpace = null, SearchSpace <FastForestOption> fastForestSearchSpace = null, SearchSpace <LbfgsOption> lbfgsSearchSpace = null, SearchSpace <SdcaOption> sdcaSearchSpace = null)
{
var res = new List <SweepableEstimator>();
if (useFastTree)
{
fastTreeOption = fastTreeOption ?? new FastTreeOption();
fastTreeOption.LabelColumnName = labelColumnName;
fastTreeOption.FeatureColumnName = featureColumnName;
fastTreeOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateFastTreeOva(fastTreeOption, fastTreeSearchSpace ?? new SearchSpace <FastTreeOption>(fastTreeOption)));
}
if (useFastForest)
{
fastForestOption = fastForestOption ?? new FastForestOption();
fastForestOption.LabelColumnName = labelColumnName;
fastForestOption.FeatureColumnName = featureColumnName;
fastForestOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateFastForestOva(fastForestOption, fastForestSearchSpace ?? new SearchSpace <FastForestOption>(fastForestOption)));
}
if (useLgbm)
{
lgbmOption = lgbmOption ?? new LgbmOption();
lgbmOption.LabelColumnName = labelColumnName;
lgbmOption.FeatureColumnName = featureColumnName;
lgbmOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateLightGbmMulti(lgbmOption, lgbmSearchSpace ?? new SearchSpace <LgbmOption>(lgbmOption)));
}
if (useLbfgs)
{
lbfgsOption = lbfgsOption ?? new LbfgsOption();
lbfgsOption.LabelColumnName = labelColumnName;
lbfgsOption.FeatureColumnName = featureColumnName;
lbfgsOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateLbfgsLogisticRegressionOva(lbfgsOption, lbfgsSearchSpace ?? new SearchSpace <LbfgsOption>(lbfgsOption)));
res.Add(SweepableEstimatorFactory.CreateLbfgsMaximumEntropyMulti(lbfgsOption, lbfgsSearchSpace ?? new SearchSpace <LbfgsOption>(lbfgsOption)));
}
if (useSdca)
{
sdcaOption = sdcaOption ?? new SdcaOption();
sdcaOption.LabelColumnName = labelColumnName;
sdcaOption.FeatureColumnName = featureColumnName;
sdcaOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateSdcaMaximumEntropyMulti(sdcaOption, sdcaSearchSpace ?? new SearchSpace <SdcaOption>(sdcaOption)));
res.Add(SweepableEstimatorFactory.CreateSdcaLogisticRegressionOva(sdcaOption, sdcaSearchSpace ?? new SearchSpace <SdcaOption>(sdcaOption)));
}
return(res.ToArray());
}
internal SweepableEstimator[] Regression(string labelColumnName = DefaultColumnNames.Label, string featureColumnName = DefaultColumnNames.Features, string exampleWeightColumnName = null, bool useFastForest = true, bool useLgbm = true, bool useFastTree = true, bool useLbfgs = true, bool useSdca = true,
FastTreeOption fastTreeOption = null, LgbmOption lgbmOption = null, FastForestOption fastForestOption = null, LbfgsOption lbfgsOption = null, SdcaOption sdcaOption = null,
SearchSpace <FastTreeOption> fastTreeSearchSpace = null, SearchSpace <LgbmOption> lgbmSearchSpace = null, SearchSpace <FastForestOption> fastForestSearchSpace = null, SearchSpace <LbfgsOption> lbfgsSearchSpace = null, SearchSpace <SdcaOption> sdcaSearchSpace = null)
{
var res = new List <SweepableEstimator>();
if (useFastTree)
{
fastTreeOption = fastTreeOption ?? new FastTreeOption();
fastTreeOption.LabelColumnName = labelColumnName;
fastTreeOption.FeatureColumnName = featureColumnName;
fastTreeOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateFastTreeRegression(fastTreeOption, fastTreeSearchSpace ?? new SearchSpace <FastTreeOption>()));
res.Add(SweepableEstimatorFactory.CreateFastTreeTweedieRegression(fastTreeOption, fastTreeSearchSpace ?? new SearchSpace <FastTreeOption>()));
}
if (useFastForest)
{
fastForestOption = fastForestOption ?? new FastForestOption();
fastForestOption.LabelColumnName = labelColumnName;
fastForestOption.FeatureColumnName = featureColumnName;
fastForestOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateFastForestRegression(fastForestOption, fastForestSearchSpace ?? new SearchSpace <FastForestOption>()));
}
if (useLgbm)
{
lgbmOption = lgbmOption ?? new LgbmOption();
lgbmOption.LabelColumnName = labelColumnName;
lgbmOption.FeatureColumnName = featureColumnName;
lgbmOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateLightGbmRegression(lgbmOption, lgbmSearchSpace ?? new SearchSpace <LgbmOption>()));
}
if (useLbfgs)
{
lbfgsOption = lbfgsOption ?? new LbfgsOption();
lbfgsOption.LabelColumnName = labelColumnName;
lbfgsOption.FeatureColumnName = featureColumnName;
lbfgsOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateLbfgsPoissonRegressionRegression(lbfgsOption, lbfgsSearchSpace ?? new SearchSpace <LbfgsOption>()));
}
if (useSdca)
{
sdcaOption = sdcaOption ?? new SdcaOption();
sdcaOption.LabelColumnName = labelColumnName;
sdcaOption.FeatureColumnName = featureColumnName;
sdcaOption.ExampleWeightColumnName = exampleWeightColumnName;
res.Add(SweepableEstimatorFactory.CreateSdcaRegression(sdcaOption, sdcaSearchSpace ?? new SearchSpace <SdcaOption>()));
}
return(res.ToArray());
}
public void Nest_search_space_mapping_to_feature_space_test()
{
var ss = new SearchSpace <NestSearchSpace>();
var param = ss.SampleFromFeatureSpace(new[] { 0.0, 0, 0, 0, 0, 0, 0, 0 });
var features = ss.MappingToFeatureSpace(param);
features.Should().Equal(0, 0, 0, 0, 0, 0, 0, 0);
param = ss.SampleFromFeatureSpace(new[] { 0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5 });
features = ss.MappingToFeatureSpace(param);
features.Should().Equal(0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5);
}
public new static void MyClassInitialize(TestContext testContext)
{
BaseIntegrationTests.MyClassInitialize(testContext);
string strName = "Temp_" + Guid.NewGuid().ToString();
WebCallResult res = SearchSpace.AddSearchSpace(_connectionServer, out _searchSpace, strName, "SearchSpace added by Unit Test");
Assert.IsTrue(res.Success, "Creation of new SearchSpace failed");
strName = "Temp_" + Guid.NewGuid().ToString();
res = Partition.AddPartition(_connectionServer, out _partition, strName, "Partition added by Unit Test");
Assert.IsTrue(res.Success, "Creation of new partition failed");
}
public void Search_space_add_option_test()
{
var ss = new SearchSpace();
ss.FeatureSpaceDim.Should().Be(0);
ss.Add("A", new UniformIntOption(-1000, 1000));
ss.FeatureSpaceDim.Should().Be(1);
var param = ss.SampleFromFeatureSpace(new[] { 0.5 });
param["A"].AsType <int>().Should().Be(0);
}
private void SetSearchSpace()
{
if (searchSpace == null || !searchSpace.enabled)
{
foreach (SearchSpace ss in GetComponents <SearchSpace>())
{
if (ss.enabled)
{
searchSpace = ss;
break;
}
}
}
}
public void Parameter_AsType_should_be_culture_invariant()
{
var originalCuture = Thread.CurrentThread.CurrentCulture;
var culture = new CultureInfo("ru", false);
Thread.CurrentThread.CurrentCulture = culture;
var ss = new SearchSpace();
ss.Add("_SampleSize", new UniformDoubleOption(10000, 20000));
var parameter = ss.SampleFromFeatureSpace(new[] { 0.5 });
parameter["_SampleSize"].AsType <double>().Should().Be(15000.0);
Thread.CurrentThread.CurrentCulture = originalCuture;
}
public void Search_space_default_value_test()
{
var ss = new SearchSpace <NestSearchSpace>();
var defaultTuner = new DefaultValueTuner(ss);
var param = defaultTuner.Propose().AsType <NestSearchSpace>();
param.UniformDouble.Should().Be(0);
param.UniformFloat.Should().Be(0);
param.BasicSS.UniformInt.Should().Be(0);
param.BasicSS.UniformDouble.Should().Be(0);
param.BasicSS.UniformFloat.Should().Be(0);
param.BasicSS.ChoiceStr.Should().Be("a");
param.BasicSS.ChoiceBoolean.Should().BeTrue();
param.BasicSS.JTokenType.Should().Be(JsonTokenType.Null);
}
public void AddSearchSpaceMember_ErrorResponse_Failure()
{
Reset();
_mockTransport.Setup(x => x.GetCupiResponse(It.IsAny <string>(), MethodType.POST, It.IsAny <ConnectionServerRest>(),
It.IsAny <string>(), It.IsAny <bool>())).Returns(new WebCallResult
{
Success = false,
ResponseText = "error text",
StatusCode = 404
});
var res = SearchSpace.AddSearchSpaceMember(_mockServer, "SSObjectId", "PartitionObjectID", 1);
Assert.IsFalse(res.Success, "Calling AddSearchSpaceMember with ErrorResponse did not fail");
}
public void UpdateSearchSpace_ErrorResponse_Failure()
{
Reset();
_mockTransport.Setup(x => x.GetCupiResponse(It.IsAny <string>(), MethodType.PUT, It.IsAny <ConnectionServerRest>(),
It.IsAny <string>(), It.IsAny <bool>())).Returns(new WebCallResult
{
Success = false,
ResponseText = "error text",
StatusCode = 404
});
var res = SearchSpace.UpdateSearchSpace(_mockServer, "ObjectId", "New Name", "New Description");
Assert.IsFalse(res.Success, "Calling UpdateSearchSpace with ErrorResponse did not fail");
}
public void GetSearchSpaces_EmptyResult_Failure()
{
Reset();
_mockTransport.Setup(x => x.GetCupiResponse(It.IsAny <string>(), It.IsAny <MethodType>(), It.IsAny <ConnectionServerRest>(),
It.IsAny <string>(), true)).Returns(new WebCallResult
{
Success = true,
ResponseText = ""
});
List <SearchSpace> oSpaces;
var res = SearchSpace.GetSearchSpaces(_mockServer, out oSpaces, 1, 5, null);
Assert.IsFalse(res.Success, "Calling GetSearchSpaces with EmptyResultText did not fail");
}
public void SearchSpace_sample_from_feature_space_test()
{
var ss = new SearchSpace <BasicSearchSpace>();
var param = ss.SampleFromFeatureSpace(new[] { 0.0, 0, 0, 0, 0, 0 });
param.ChoiceStr.Should().Be("a");
param.UniformDouble.Should().Be(-1000);
param.UniformFloat.Should().Be(-1000);
param.UniformInt.Should().Be(-1000);
param = ss.SampleFromFeatureSpace(new[] { 0.5, 0.5, 0.5, 0.5, 0.5, 0.5 });
param.ChoiceStr.Should().Be("c");
param.UniformDouble.Should().Be(0);
param.UniformFloat.Should().Be(0);
param.UniformInt.Should().Be(0);
}
// Use this for initialization
void Start()
{
SearchSpaceObj = GameObject.Find("SearchSpace");
searchScript = SearchSpaceObj.GetComponent("SearchSpace") as SearchSpace;
}
private void SetSearchSpace()
{
if (searchSpace == null || !searchSpace.enabled)
{
foreach (SearchSpace ss in GetComponents<SearchSpace>())
{
if (ss.enabled)
{
searchSpace = ss;
break;
}
}
}
}
void Start()
{
ssScript = GameObject.FindObjectOfType(typeof(SearchSpace)) as SearchSpace;
path = ssScript.getPathToSubDataFile();
pinching_ = false;
grabbed_ = null;
}