Ejemplo n.º 1
0
 /// <summary>
 /// Creates and trains the State Machine readout layer.
 /// </summary>
 /// <param name="regressionInput">
 /// RegressionInput object prepared by PrepareRegressionData function
 /// </param>
 /// <param name="regressionController">
 /// Optional. see Regression.RegressionCallbackDelegate
 /// </param>
 /// <param name="regressionControllerData">
 /// Optional custom object to be passed to regressionController together with other standard information
 /// </param>
 public ResultComparativeBundle BuildReadoutLayer(RegressionInput regressionInput,
                                                  ReadoutUnit.RegressionCallbackDelegate regressionController = null,
                                                  Object regressionControllerData = null
                                                  )
 {
     //Readout layer instance
     RL = new ReadoutLayer(_settings.ReadoutLayerConfig);
     //Optional mapper of predictors to readout units
     ReadoutLayer.PredictorsMapper mapper = null;
     if (_settings.MapperConfig != null)
     {
         //Create empty instance of the mapper
         mapper = new ReadoutLayer.PredictorsMapper(NP.NumOfPredictors);
         //Expand list of predicting neurons to array of predictor origin
         StateMachineSettings.MapperSettings.PoolRef[] neuronPoolRefCollection = new StateMachineSettings.MapperSettings.PoolRef[NP.NumOfPredictors];
         int idx = 0;
         foreach (Reservoir.PredictorNeuron pn in NP.PredictorNeuronCollection)
         {
             neuronPoolRefCollection[idx] = new StateMachineSettings.MapperSettings.PoolRef {
                 _reservoirInstanceIdx = pn.Neuron.Placement.ReservoirID, _poolIdx = pn.Neuron.Placement.PoolID
             };
             ++idx;
             if (pn.UseSecondaryPredictor)
             {
                 neuronPoolRefCollection[idx] = neuronPoolRefCollection[idx - 1];
                 ++idx;
             }
         }
         //Iterate readout units having specific predictors mapping
         foreach (string readoutUnitName in _settings.MapperConfig.Map.Keys)
         {
             bool[] switches = new bool[NP.NumOfPredictors];
             switches.Populate(false);
             foreach (StateMachineSettings.MapperSettings.PoolRef allowedPool in _settings.MapperConfig.Map[readoutUnitName])
             {
                 //Enable specific predictors from allowed pool (origin)
                 for (int i = 0; i < neuronPoolRefCollection.Length; i++)
                 {
                     if (neuronPoolRefCollection[i]._reservoirInstanceIdx == allowedPool._reservoirInstanceIdx && neuronPoolRefCollection[i]._poolIdx == allowedPool._poolIdx)
                     {
                         switches[i] = true;
                     }
                 }
             }
             //Add mapping to mapper
             mapper.Add(readoutUnitName, switches);
         }
     }
     //Training
     return(RL.Build(regressionInput.PreprocessedData,
                     regressionController,
                     regressionControllerData,
                     mapper
                     ));
 }
Ejemplo n.º 2
0
 /// <summary>
 /// Trains the State Machine readout layer.
 /// </summary>
 /// <param name="rsi">
 /// RegressionStageInput object prepared by PrepareRegressionStageInput function
 /// </param>
 /// <param name="regressionController">
 /// Optional. see Regression.RegressionCallbackDelegate
 /// </param>
 /// <param name="regressionControllerData">
 /// Optional custom object to be passed to regressionController together with other standard information
 /// </param>
 public ValidationBundle RegressionStage(RegressionStageInput rsi,
                                         ReadoutUnit.RegressionCallbackDelegate regressionController = null,
                                         Object regressionControllerData = null
                                         )
 {
     //Readout layer instance
     _readoutLayer = new ReadoutLayer(_settings.ReadoutLayerConfig, DataRange);
     //Training
     return(_readoutLayer.Build(rsi.PredictorsCollection,
                                rsi.IdealOutputsCollection,
                                regressionController,
                                regressionControllerData
                                ));
 }
Ejemplo n.º 3
0
 /// <summary>
 /// Creates and trains the State Machine readout layer.
 /// Function uses specific mapping of predictors to readout units, if available.
 /// Function also rejects unusable predictors having no reasonable fluctuation of values.
 /// </summary>
 /// <param name="regressionInput">
 /// RegressionInput object prepared by PrepareRegressionData function
 /// </param>
 /// <param name="regressionController">
 /// Optional. see Regression.RegressionCallbackDelegate
 /// </param>
 /// <param name="regressionControllerData">
 /// Optional custom object to be passed to regressionController together with other standard information
 /// </param>
 public ResultBundle BuildReadoutLayer(RegressionInput regressionInput,
                                       ReadoutUnit.RegressionCallbackDelegate regressionController = null,
                                       Object regressionControllerData = null
                                       )
 {
     //Readout layer instance
     RL = new ReadoutLayer(_settings.ReadoutLayerConfig);
     //Create empty instance of the mapper
     ReadoutLayer.PredictorsMapper mapper = new ReadoutLayer.PredictorsMapper(PredictorGeneralSwitchCollection);
     if (_settings.MapperCfg != null)
     {
         //Expand list of predicting neurons to array of predictor origin
         StateMachineSettings.MapperSettings.AllowedPool[] neuronPoolRefCollection = new StateMachineSettings.MapperSettings.AllowedPool[NP.NumOfPredictors];
         int idx = 0;
         foreach (HiddenNeuron neuron in NP.PredictorNeuronCollection)
         {
             StateMachineSettings.MapperSettings.AllowedPool poolRef = new StateMachineSettings.MapperSettings.AllowedPool {
                 _reservoirInstanceIdx = neuron.Placement.ReservoirID, _poolIdx = neuron.Placement.PoolID
             };
             for (int i = 0; i < neuron.PredictorsCfg.NumOfEnabledPredictors; i++)
             {
                 neuronPoolRefCollection[idx] = poolRef;
                 ++idx;
             }
         }
         //Iterate all readout units
         foreach (string readoutUnitName in _settings.ReadoutLayerConfig.OutputFieldNameCollection)
         {
             bool[] switches = new bool[NP.NumOfPredictors];
             //Initially allow all valid predictors
             PredictorGeneralSwitchCollection.CopyTo(switches, 0);
             //Exists specific mapping?
             if (_settings.MapperCfg != null && (_settings.MapperCfg.PoolsMap.ContainsKey(readoutUnitName) || _settings.MapperCfg.RoutedInputFieldsMap.ContainsKey(readoutUnitName)))
             {
                 //Routed input fields
                 if (_settings.MapperCfg.RoutedInputFieldsMap.ContainsKey(readoutUnitName))
                 {
                     //Initially disable all routed input fields
                     for (int i = NP.PredictorNeuronCollection.Count; i < NP.NumOfPredictors; i++)
                     {
                         switches[i] = false;
                     }
                     //Enable enabled routed input fields
                     List <int> enabledRoutedFieldsIdxs = _settings.MapperCfg.RoutedInputFieldsMap[readoutUnitName];
                     for (int i = 0; i < enabledRoutedFieldsIdxs.Count; i++)
                     {
                         switches[NP.PredictorNeuronCollection.Count + enabledRoutedFieldsIdxs[i]] = PredictorGeneralSwitchCollection[NP.PredictorNeuronCollection.Count + enabledRoutedFieldsIdxs[i]];
                     }
                 }
                 //Neuron predictors
                 if (_settings.MapperCfg.PoolsMap.ContainsKey(readoutUnitName))
                 {
                     //Initially disable all neuron predictors
                     for (int i = 0; i < NP.PredictorNeuronCollection.Count; i++)
                     {
                         switches[i] = false;
                     }
                     //Enable allowed neuron predictors
                     foreach (StateMachineSettings.MapperSettings.AllowedPool allowedPool in _settings.MapperCfg.PoolsMap[readoutUnitName])
                     {
                         //Enable specific predictors from allowed pool (origin)
                         for (int i = 0; i < NP.PredictorNeuronCollection.Count; i++)
                         {
                             if (neuronPoolRefCollection[i]._reservoirInstanceIdx == allowedPool._reservoirInstanceIdx && neuronPoolRefCollection[i]._poolIdx == allowedPool._poolIdx)
                             {
                                 //Enable predictor if it is valid
                                 switches[i] = PredictorGeneralSwitchCollection[i];
                             }
                         }
                     }
                 }
             }
             //Add mapping to mapper
             mapper.Add(readoutUnitName, switches);
         }
     }
     //Training
     return(RL.Build(regressionInput.PreprocessedData,
                     regressionController,
                     regressionControllerData,
                     mapper
                     ));
 }