public Trainer(
TrainerConfiguration configuration,
SkipPhaseRequest skipPhaseRequest,
IGuiLogger guiLogger)
{
NeuralNetwork = CreateNetworkToTeach(configuration);
_configuration = configuration;
_skipPhaseRequest = skipPhaseRequest;
GuiLogger = guiLogger;
}
private static DeepBeliefNetwork CreateNetworkToTeach(TrainerConfiguration configuration)
{
var inputs = configuration.InputsOutputsData.Inputs;
// Setup the deep belief network and initialize with random weights.
var network = new DeepBeliefNetwork(inputs.First().Length, configuration.Layers);
new GaussianWeights(network).Randomize();
network.UpdateVisibleWeights();
return(network);
}
/// <summary>
/// Constructor for creating TrainingParamters from resource file stream parameter file.
/// </summary>
/// <param name="resourceStream"></param>
/// <param name="config"></param>
public TrainingParameters(Stream resourceStream, TrainerConfiguration config = null)
{
_charges = new HashSet <int>();
_massSorter = new Dictionary <int, Histogram <double> >();
_rankTables = new Dictionary <int, List <RankTable> >();
_drankTables = new Dictionary <int, List <RankTable> >();
_ionProbabilities = new Dictionary <int, List <IonFrequencyTable> >();
_massErrors = new Dictionary <int, List <MassErrorTable> >();
_precursorOffsets = new Dictionary <int, List <PrecursorOffsets> >();
Config = config;
ReadFromResourceFile(resourceStream);
_computed = true;
}
/// <summary>
/// Constructor for creating empty TrainingParameters object.
/// </summary>
/// <param name="config">Configuration data read from configuration file.</param>
public TrainingParameters(TrainerConfiguration config)
{
Config = config;
_dataSet = new Queue <SpectrumMatch>();
_massBins = new Dictionary <int, int>();
_charges = new HashSet <int>();
_massSorter = new Dictionary <int, Histogram <double> >();
_rankTables = new Dictionary <int, List <RankTable> >();
_drankTables = new Dictionary <int, List <RankTable> >();
_ionProbabilities = new Dictionary <int, List <IonFrequencyTable> >();
_massErrors = new Dictionary <int, List <MassErrorTable> >();
_precursorOffsets = new Dictionary <int, List <PrecursorOffsets> >();
_computed = false;
}
public void RankProbability()
{
var methodName = MethodBase.GetCurrentMethod().Name;
Utils.ShowStarting(methodName);
const string configurationFile = @"\\protoapps\UserData\Wilkins\BottomUp\RankProbabilityConfig.ini";
if (!File.Exists(configurationFile))
{
Assert.Ignore(@"Skipping test {0} since file not found: {1}", methodName, configurationFile);
}
var config = new TrainerConfiguration(configurationFile);
var trainingParameters = new TrainingParameters(config);
foreach (var dataSet in config.DataSets)
{
var tsvName = config.TsvPath.Replace("@", dataSet);
var rawName = config.DataPath.Replace("@", dataSet);
var txtFiles = new List <string>();
var dataFiles = new List <string>();
if (config.DataFormat == DataFileFormat.Mgf)
{
dataFiles.Add(config.DataPath + dataSet + "." + config.DataFormat);
}
else
{
// Read directory
var txtFilesTemp = Directory.GetFiles(tsvName).ToList();
txtFiles = txtFilesTemp.Where(txtFile => Path.GetExtension(txtFile) == ".tsv").ToList();
var dataFilesTemp = Directory.GetFiles(rawName).ToList();
dataFiles =
dataFilesTemp.Where(dataFile => Path.GetExtension(dataFile) == ".raw").ToList();
Assert.True(dataFiles.Count == txtFiles.Count);
}
// Read Data files
for (int i = 0; i < dataFiles.Count; i++)
{
SpectrumMatchList targets;
if (config.DataFormat == DataFileFormat.Mgf)
{
Console.WriteLine(dataSet + ".mgf");
targets = new SpectrumMatchList(dataFiles[i], config.PrecursorCharge);
}
else
{
string textFile = txtFiles[i];
string rawFile = dataFiles[i];
Console.WriteLine("{0}\t{1}", textFile, rawFile);
var lcms = new LazyLcMsRun(rawFile, 0, 0);
targets = new SpectrumMatchList(lcms, txtFiles[i], config.DataFormat, config.PrecursorCharge);
}
// Add PSMs
trainingParameters.AddMatches(targets);
}
// Write output file
var outputFileName = config.OutputFileName.Replace("@", dataSet);
trainingParameters.WriteToFile(outputFileName);
}
}
