Changeset 18027 for branches/3026_IntegrationIntoSymSpace/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs
- Timestamp:
- 07/20/21 18:13:55 (3 years ago)
- Location:
- branches/3026_IntegrationIntoSymSpace
- Files:
-
- 4 edited
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branches/3026_IntegrationIntoSymSpace
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branches/3026_IntegrationIntoSymSpace/HeuristicLab.Algorithms.DataAnalysis
- Property svn:mergeinfo changed
/trunk/HeuristicLab.Algorithms.DataAnalysis merged: 17931,17934,17942,17979
- Property svn:mergeinfo changed
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branches/3026_IntegrationIntoSymSpace/HeuristicLab.Algorithms.DataAnalysis/3.4
- Property svn:mergeinfo changed
/trunk/HeuristicLab.Algorithms.DataAnalysis/3.4 merged: 17931,17934,17942,17979
- Property svn:mergeinfo changed
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branches/3026_IntegrationIntoSymSpace/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs
r17180 r18027 20 20 #endregion 21 21 22 extern alias alglib_3_7; 22 23 using System; 23 24 using System.Collections.Generic; … … 32 33 /// Represents a neural network model for regression and classification 33 34 /// </summary> 34 [StorableType(" AEB9B960-FCA6-4A6D-BD5F-27BCE9CC5BEA")]35 [StorableType("DABDBD64-E93B-4F50-A343-C8A92C1C48A4")] 35 36 [Item("NeuralNetworkModel", "Represents a neural network for regression and classification.")] 36 37 public sealed class NeuralNetworkModel : ClassificationModel, INeuralNetworkModel { 37 38 38 39 private object mlpLocker = new object(); 40 41 42 39 43 private alglib.multilayerperceptron multiLayerPerceptron; 44 [Storable] 45 private string SerializedMultiLayerPerceptron { 46 get { alglib.mlpserialize(multiLayerPerceptron, out var ser); return ser; } 47 set { if (value != null) alglib.mlpunserialize(value, out multiLayerPerceptron); } 48 } 40 49 41 50 public override IEnumerable<string> VariablesUsedForPrediction { … … 48 57 private double[] classValues; 49 58 [StorableConstructor] 50 private NeuralNetworkModel(StorableConstructorFlag _) : base(_) { 51 multiLayerPerceptron = new alglib.multilayerperceptron(); 52 } 59 private NeuralNetworkModel(StorableConstructorFlag _) : base(_) { } 53 60 private NeuralNetworkModel(NeuralNetworkModel original, Cloner cloner) 54 61 : base(original, cloner) { 55 multiLayerPerceptron = new alglib.multilayerperceptron(); 56 multiLayerPerceptron.innerobj.chunks = (double[,])original.multiLayerPerceptron.innerobj.chunks.Clone(); 57 multiLayerPerceptron.innerobj.columnmeans = (double[])original.multiLayerPerceptron.innerobj.columnmeans.Clone(); 58 multiLayerPerceptron.innerobj.columnsigmas = (double[])original.multiLayerPerceptron.innerobj.columnsigmas.Clone(); 59 multiLayerPerceptron.innerobj.derror = (double[])original.multiLayerPerceptron.innerobj.derror.Clone(); 60 multiLayerPerceptron.innerobj.dfdnet = (double[])original.multiLayerPerceptron.innerobj.dfdnet.Clone(); 61 multiLayerPerceptron.innerobj.neurons = (double[])original.multiLayerPerceptron.innerobj.neurons.Clone(); 62 multiLayerPerceptron.innerobj.nwbuf = (double[])original.multiLayerPerceptron.innerobj.nwbuf.Clone(); 63 multiLayerPerceptron.innerobj.structinfo = (int[])original.multiLayerPerceptron.innerobj.structinfo.Clone(); 64 multiLayerPerceptron.innerobj.weights = (double[])original.multiLayerPerceptron.innerobj.weights.Clone(); 65 multiLayerPerceptron.innerobj.x = (double[])original.multiLayerPerceptron.innerobj.x.Clone(); 66 multiLayerPerceptron.innerobj.y = (double[])original.multiLayerPerceptron.innerobj.y.Clone(); 62 if (original.multiLayerPerceptron != null) 63 multiLayerPerceptron = (alglib.multilayerperceptron)original.multiLayerPerceptron.make_copy(); 67 64 allowedInputVariables = (string[])original.allowedInputVariables.Clone(); 68 65 if (original.classValues != null) … … 73 70 this.name = ItemName; 74 71 this.description = ItemDescription; 75 this.multiLayerPerceptron = multiLayerPerceptron;72 this.multiLayerPerceptron = (alglib.multilayerperceptron)multiLayerPerceptron.make_copy(); 76 73 this.allowedInputVariables = allowedInputVariables.ToArray(); 77 74 if (classValues != null) … … 95 92 x[column] = inputData[row, column]; 96 93 } 97 // NOTE: mlpprocess changes data in multiLayerPerceptron and is therefore not thread-sa ve!94 // NOTE: mlpprocess changes data in multiLayerPerceptron and is therefore not thread-safe! 98 95 lock (mlpLocker) { 99 96 alglib.mlpprocess(multiLayerPerceptron, x, ref y); … … 115 112 x[column] = inputData[row, column]; 116 113 } 117 // NOTE: mlpprocess changes data in multiLayerPerceptron and is therefore not thread-sa ve!114 // NOTE: mlpprocess changes data in multiLayerPerceptron and is therefore not thread-safe! 118 115 lock (mlpLocker) { 119 116 alglib.mlpprocess(multiLayerPerceptron, x, ref y); … … 156 153 return new NeuralNetworkClassificationSolution(this, new ClassificationProblemData(problemData)); 157 154 } 158 159 #region persistence160 [Storable]161 private double[,] MultiLayerPerceptronChunks {162 get {163 return multiLayerPerceptron.innerobj.chunks;164 }165 set {166 multiLayerPerceptron.innerobj.chunks = value;167 }168 }169 [Storable]170 private double[] MultiLayerPerceptronColumnMeans {171 get {172 return multiLayerPerceptron.innerobj.columnmeans;173 }174 set {175 multiLayerPerceptron.innerobj.columnmeans = value;176 }177 }178 [Storable]179 private double[] MultiLayerPerceptronColumnSigmas {180 get {181 return multiLayerPerceptron.innerobj.columnsigmas;182 }183 set {184 multiLayerPerceptron.innerobj.columnsigmas = value;185 }186 }187 [Storable]188 private double[] MultiLayerPerceptronDError {189 get {190 return multiLayerPerceptron.innerobj.derror;191 }192 set {193 multiLayerPerceptron.innerobj.derror = value;194 }195 }196 [Storable]197 private double[] MultiLayerPerceptronDfdnet {198 get {199 return multiLayerPerceptron.innerobj.dfdnet;200 }201 set {202 multiLayerPerceptron.innerobj.dfdnet = value;203 }204 }205 [Storable]206 private double[] MultiLayerPerceptronNeurons {207 get {208 return multiLayerPerceptron.innerobj.neurons;209 }210 set {211 multiLayerPerceptron.innerobj.neurons = value;212 }213 }214 [Storable]215 private double[] MultiLayerPerceptronNwbuf {216 get {217 return multiLayerPerceptron.innerobj.nwbuf;218 }219 set {220 multiLayerPerceptron.innerobj.nwbuf = value;221 }222 }223 [Storable]224 private int[] MultiLayerPerceptronStuctinfo {225 get {226 return multiLayerPerceptron.innerobj.structinfo;227 }228 set {229 multiLayerPerceptron.innerobj.structinfo = value;230 }231 }232 [Storable]233 private double[] MultiLayerPerceptronWeights {234 get {235 return multiLayerPerceptron.innerobj.weights;236 }237 set {238 multiLayerPerceptron.innerobj.weights = value;239 }240 }241 [Storable]242 private double[] MultiLayerPerceptronX {243 get {244 return multiLayerPerceptron.innerobj.x;245 }246 set {247 multiLayerPerceptron.innerobj.x = value;248 }249 }250 [Storable]251 private double[] MultiLayerPerceptronY {252 get {253 return multiLayerPerceptron.innerobj.y;254 }255 set {256 multiLayerPerceptron.innerobj.y = value;257 }258 }259 #endregion260 155 } 261 156 }
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