protected NullDataCollection(
NullDataGenerator nullDataGenerator,
RangeCollection nullIndexRange,
IEnumerable <Pair <string, Dictionary <string, SufficientStatistics> > > predictorNameAndCaseIdToNonMissingValueEnumeration,
IEnumerable <Pair <string, Dictionary <string, SufficientStatistics> > > targetNameAndCaseIdToNonMissingValueEnumeration
//Dictionary<string, Dictionary<string, SufficientStatistics>> predictorVariableToCaseIdToRealNonMissingValue,
//Dictionary<string, Dictionary<string, SufficientStatistics>> targetVariableToCaseIdToRealNonMissingValue
)
{
Console.WriteLine(nullDataGenerator);
Name = nullDataGenerator.Name;
_nullIndexToNullDataGenerator = new Dictionary <int, NullDataGenerator>();
foreach (int nullIndex in nullIndexRange.Elements)
{
int predCount = SpecialFunctions.Count(predictorNameAndCaseIdToNonMissingValueEnumeration);
int preseed = ~nullIndex.GetHashCode() ^ predCount.GetHashCode()
^ "NullDataCollection".GetHashCode();
NullDataGenerator newNullDataGenerator = (NullDataGenerator)nullDataGenerator.Clone();
newNullDataGenerator.SetPreseed(preseed);
newNullDataGenerator.SetPredictorNameAndCaseIdToNonMissingValueEnumeration(predictorNameAndCaseIdToNonMissingValueEnumeration);
newNullDataGenerator.SetTargetNameAndCaseIdToNonMissingValueEnumeration(targetNameAndCaseIdToNonMissingValueEnumeration);
//newNullDataGenerator.RealPredictorVariableToCaseIdToNonMissingValue = predictorVariableToCaseIdToRealNonMissingValue;
//newNullDataGenerator.RealTargetVariableToCaseIdToNonMissingValue = targetVariableToCaseIdToRealNonMissingValue;
_nullIndexToNullDataGenerator.Add(nullIndex, newNullDataGenerator);
}
}
private static Dictionary <string, int> SufficientStatisticsMapToIntDictionaryMap(Converter <Leaf, SufficientStatistics> leafToStatsMap, IEnumerable <Leaf> fullLeafCollection)
{
Dictionary <string, int> result = new Dictionary <string, int>(SpecialFunctions.Count(fullLeafCollection));
foreach (Leaf leaf in fullLeafCollection)
{
SufficientStatistics value = leafToStatsMap(leaf);
if (!value.IsMissing())
{
result.Add(leaf.CaseName, (int)(BooleanStatistics)value);
}
}
return(result);
}
public override Dictionary <string, SufficientStatistics> GenerateRandomMapping(Dictionary <string, SufficientStatistics> realCaseIdToNonMissingValue, ref Random random)
{
//!!!!put check in to make sure ISufficientSTatistics is reall BooleanStatistics
Converter <Leaf, SufficientStatistics> leafToDistnClassFunction = PhyloDDriver.CreateSufficientStatisticsMap(realCaseIdToNonMissingValue);
PhyloTree tree = _modelScorer.PhyloTree;
MessageInitializer messageInitializer = MessageInitializerDiscrete.GetInstance(leafToDistnClassFunction, _discreteDistribution, new int[] { 1, 1 }, tree.LeafCollection);
Score score = _modelScorer.MaximizeLikelihood(messageInitializer);
double percentNonMissing = (double)tree.CountOfNonMissingLeaves(realCaseIdToNonMissingValue) /
(double)SpecialFunctions.Count(tree.LeafCollection);
double equilibrium = score.OptimizationParameters[(int)DistributionDiscreteConditional.ParameterIndex.Equilibrium].Value;
double lambda = score.OptimizationParameters[(int)DistributionDiscreteConditional.ParameterIndex.Lambda].Value;
Dictionary <string, BooleanStatistics> randomCaseIdToNonMissingValue = tree.EvolveBinaryTree(equilibrium, lambda, 1 - percentNonMissing, ref random);
Dictionary <string, SufficientStatistics> converted;
SpecialFunctions.ConvertDictionaryToBaseClasses(randomCaseIdToNonMissingValue, out converted);
return(converted);
}
public void Run(
ModelScorer modelScorer,
PhyloTree phyloTree,
string predictorSparseFileName,
string targetSparseFileName,
string leafDistributionName,
string nullDataGeneratorName,
KeepTest <Dictionary <string, string> > keepTest,
RangeCollection skipRowIndexRangeCollectionOrNull,
string shortName,
string outputDirectoryName,
RangeCollection pieceIndexRangeCollection, int pieceCount,
RangeCollection nullIndexRangeCollection,
string optimizerName)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
Directory.CreateDirectory(outputDirectoryName);
string outputFileName = string.Format(@"{0}\{1}.{2}.{3}.{4}.{5}.{6}{7}.txt",
outputDirectoryName, shortName,
leafDistributionName, nullDataGeneratorName,
nullIndexRangeCollection,
pieceCount,
pieceIndexRangeCollection,
skipRowIndexRangeCollectionOrNull == null ? "" : ".Skip" + skipRowIndexRangeCollectionOrNull.Count().ToString()
);
#region from PhyloTree refactor
//Dictionary<string, Dictionary<string, bool>> predictorVariableToCaseIdToRealNonMissingValue = LoadSparseFileInMemory<bool>(predictorSparseFileName);
//IEnumerable<Pair<string, Dictionary<string, T>>> targetNameAndCaseIdToNonMissingValueEnumeration = LoadSparseFileEnumeration<T>(targetSparseFileName);
//NullDataCollection nullDataGenerator =
// NullDataCollection.GetInstance(this, modelTester, nullIndexRangeCollection, predictorVariableToCaseIdToRealNonMissingValue);
//UniversalWorkList<T> workList = UniversalWorkList<T>.GetInstance(
// predictorVariableToCaseIdToRealNonMissingValue,
// targetNameAndCaseIdToNonMissingValueEnumeration,
// nullDataGenerator, nullIndexRangeCollection, keepTest);
#endregion
bool speedOverMemory = true;
IEnumerable <Pair <string, Dictionary <string, SufficientStatistics> > >
predictorNameAndCaseIdToNonMissingValueEnumeration = CreateNameAndCaseIdToNonMissingValueEnumeration(predictorSparseFileName, speedOverMemory);
IEnumerable <Pair <string, Dictionary <string, SufficientStatistics> > >
targetNameAndCaseIdToNonMissingValueEnumeration = CreateNameAndCaseIdToNonMissingValueEnumeration(targetSparseFileName, speedOverMemory);
NullDataCollection nullDataGenerator =
CreateNullDataGenerator(nullDataGeneratorName, modelScorer, phyloTree, nullIndexRangeCollection,
predictorNameAndCaseIdToNonMissingValueEnumeration, targetNameAndCaseIdToNonMissingValueEnumeration);
UniversalWorkList workList = UniversalWorkList.GetInstance(
predictorNameAndCaseIdToNonMissingValueEnumeration,
targetNameAndCaseIdToNonMissingValueEnumeration,
nullDataGenerator, nullIndexRangeCollection, keepTest);
int workListCount = SpecialFunctions.Count(workList.List());
int effectiveWorkListCount;
if (skipRowIndexRangeCollectionOrNull == null)
{
effectiveWorkListCount = workListCount;
}
else
{
effectiveWorkListCount = 0;
for (int iRowIndex = 0; iRowIndex < workListCount; iRowIndex++)
{
if (!skipRowIndexRangeCollectionOrNull.Contains(iRowIndex))
{
effectiveWorkListCount++;
}
}
}
Console.WriteLine("{0} Total rows. Skipping {1} of them.", workListCount, workListCount - effectiveWorkListCount);
using (TextWriter textWriter = File.CreateText(outputFileName))
{
textWriter.WriteLine(Header);
int rowIndex = -1;
int effectiveRowIndex = -1;
foreach (RowData rowAndTargetData in workList.List())
{
//!!!make all these parameters and the calculation a class
++rowIndex;
Debug.Assert(rowIndex < workListCount); // real assert
if (skipRowIndexRangeCollectionOrNull == null || !skipRowIndexRangeCollectionOrNull.Contains(rowIndex))
{
++effectiveRowIndex;
int workIndex = ExtractWorkIndex(effectiveRowIndex, pieceCount, effectiveWorkListCount);
if (pieceIndexRangeCollection.Contains(workIndex))
{
Debug.WriteLine("WorkItemIndex " + rowIndex.ToString());
string reportLine;
try
{
reportLine =
CreateReportLine(modelScorer, phyloTree, rowAndTargetData, workList, rowIndex, workListCount, workIndex);
}
catch (OutOfMemoryException)
{
Console.WriteLine("OUT OF MEMORY!! Clearing cache and trying to recover where we left off.");
modelScorer.ClearCache();
reportLine =
CreateReportLine(modelScorer, phyloTree, rowAndTargetData, workList, rowIndex, workListCount, workIndex);
}
textWriter.WriteLine(reportLine);
textWriter.Flush();
}
}
}
}
stopwatch.Stop();
Console.WriteLine("Running time: " + stopwatch.Elapsed);
}
