- Timestamp:
- 08/10/09 15:51:04 (15 years ago)
- Location:
- trunk/tools/CedmaImporter
- Files:
-
- 2 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/tools/CedmaImporter/Importer.cs
r2265 r2272 5 5 using System.IO; 6 6 using HeuristicLab.Modeling.Database; 7 using HeuristicLab.Modeling.Database.SQLServerCompact;8 7 using HeuristicLab.GP; 9 8 using HeuristicLab.GP.Interfaces; … … 19 18 private const int ALGORITHM_COLUMN = 3; 20 19 private const int RESULTS_IDX = 4; 21 private Result[] results; 20 private const int TRAINING_MSE = 4; 21 private const int VALIDATION_MSE = TRAINING_MSE + 1; 22 private const int TEST_MSE = TRAINING_MSE + 2; 23 24 private const int TRAINING_R2 = 7; 25 private const int VALIDATION_R2 = TRAINING_R2 + 1; 26 private const int TEST_R2 = TRAINING_R2 + 2; 27 28 private const int TRAINING_MAPE = 10; 29 private const int VALIDATION_MAPE = TRAINING_MAPE + 1; 30 private const int TEST_MAPE = TRAINING_MAPE + 2; 31 32 private const int TRAINING_MAPRE = 13; 33 private const int VALIDATION_MAPRE = TRAINING_MAPRE + 1; 34 private const int TEST_MAPRE = TRAINING_MAPRE + 2; 35 36 private const int TRAINING_VAF = 16; 37 private const int VALIDATION_VAF = TRAINING_VAF + 1; 38 private const int TEST_VAF = TRAINING_VAF + 2; 39 40 private const int VARIABLE_IMPACTS = 19; 41 private const string EVALUATION_IMPACT = "EvaluationImpact"; 42 private const string QUALITY_IMPACT = "QualityImpact"; 43 44 private string[] results; 22 45 private string[] inputVariables; 23 24 46 private HeuristicLab.CEDMA.Server.Problem problem; 25 47 … … 30 52 31 53 public void Import(string fileName, string dirName) { 32 string outputFileName = Path. GetFileNameWithoutExtension(fileName) + ".sdf";54 string outputFileName = Path.Combine(dirName, Path.GetFileNameWithoutExtension(fileName) + ".sdf"); 33 55 string connectionString = @"Data Source=" + outputFileName; 34 56 35 DatabaseService database = newDatabaseService(connectionString);36 Problem p = database.GetOrCreateProblem(problem.Dataset);57 var database = new HeuristicLab.Modeling.Database.SQLServerCompact.DatabaseService(connectionString); 58 IProblem p = database.GetOrCreateProblem(problem.Dataset); 37 59 using (StreamReader reader = File.OpenText(fileName)) { 38 ReadResultsAndInputVariables(reader );60 ReadResultsAndInputVariables(reader, database); 39 61 reader.ReadLine(); 40 62 ImportAllModels(dirName, reader, database); … … 42 64 } 43 65 44 private void ReadResultsAndInputVariables(StreamReader reader ) {45 string[] columns = reader.ReadLine().Split(';') ;46 results = Enumerable.Repeat<Result>(null, columns.Length).ToArray();47 inputVariables = Enumerable.Repeat<string>(null, columns.Length).ToArray();66 private void ReadResultsAndInputVariables(StreamReader reader, IModelingDatabase database) { 67 string[] columns = reader.ReadLine().Split(';').Select(x=>x.Trim()).ToArray(); 68 results = new string[columns.Length]; 69 inputVariables = new string[columns.Length]; 48 70 for (int i = RESULTS_IDX; i < columns.Length; i++) { 49 71 string resultColumn = columns[i].Trim(); 50 if (resultColumn.Contains(" :")) {51 string[] tokens = resultColumn.Split(' :');52 string variableName = tokens[1].Trim( );72 if (resultColumn.Contains(" ")) { 73 string[] tokens = resultColumn.Split(' '); 74 string variableName = tokens[1].Trim(' ','(',')'); 53 75 string variableResultName = tokens[0].Trim(); 54 76 inputVariables[i] = variableName; 55 results[i] = new Result(variableResultName);77 results[i] = variableResultName; 56 78 } else { 57 79 // normal result value 58 results[i] = new Result(resultColumn);80 results[i] = resultColumn; 59 81 } 60 82 } 61 83 } 62 84 63 private void ImportAllModels(string dirName, StreamReader reader, DatabaseService database) {85 private void ImportAllModels(string dirName, StreamReader reader, IModelingDatabase database) { 64 86 while (!reader.EndOfStream) { 65 string modelLine = reader.ReadLine(); 66 string[] modelData = modelLine.Split(';'); 87 string[] modelData = reader.ReadLine().Split(';').Select(x => x.Trim()).ToArray(); 67 88 int id = int.Parse(modelData[ID_COLUMN]); 68 89 string targetVariableName = modelData[TARGETVARIABLE_COLUMN].Trim(); 69 90 string algoName = modelData[ALGORITHM_COLUMN].Trim(); 70 91 try { 71 HeuristicLab.Core.IItem modelItem = ParseModel(dirName, modelData[FILENAME_COLUMN].Trim(), algoName); 72 HeuristicLab.Modeling.Database.SQLServerCompact.Variable targetVariable = new HeuristicLab.Modeling.Database.SQLServerCompact.Variable(targetVariableName); 73 Algorithm algorithm = new Algorithm(algoName); 74 Model model = new Model(targetVariable, algorithm); 92 HeuristicLab.Modeling.Model model = new HeuristicLab.Modeling.Model(); 93 model.TargetVariable = targetVariableName; 94 model.Dataset = problem.Dataset; 75 95 model.TrainingSamplesStart = problem.TrainingSamplesStart; 76 96 model.TrainingSamplesEnd = problem.TrainingSamplesEnd; … … 80 100 model.TestSamplesEnd = problem.TestSamplesEnd; 81 101 82 IEnumerable<ModelResult> qualityModelResults = GetModelResults(model, modelData);83 IEnumerable<InputVariableResult> inputVariableResults = GetInputVariableResults(model, modelData);84 102 85 // TODO86 //database.Persist(model); 87 //foreach (ModelResult modelResult in qualityModelResults)88 // database.Persist(modelResult);89 //foreach (InputVariableResult inputVariableResult in inputVariableResults) 90 // database.Persist(inputVariableResult);103 model.Data = ParseModel(dirName, modelData[FILENAME_COLUMN].Trim(), algoName); 104 105 SetModelResults(model, modelData); 106 SetInputVariableResults(model, modelData); 107 108 database.Persist(model, algoName, null); 91 109 } 92 110 catch (Exception ex) { … … 95 113 } 96 114 97 private IEnumerable<InputVariableResult> GetInputVariableResults(Model model, string[] modelData) { 98 double temp; 99 return from i in Enumerable.Range(0, inputVariables.Count()) 100 where inputVariables[i] != null && results[i] != null && double.TryParse(modelData[i], out temp) 101 select new InputVariableResult(new InputVariable(model, new HeuristicLab.Modeling.Database.SQLServerCompact.Variable(inputVariables[i])), results[i], double.Parse(modelData[i])); 115 private void SetInputVariableResults(HeuristicLab.Modeling.Model model, string[] modelData) { 116 for (int i = VARIABLE_IMPACTS; i < modelData.Length; i++) { 117 if (!string.IsNullOrEmpty(modelData[i])) { 118 model.AddInputVariables(inputVariables[i]); 119 if (results[i] == EVALUATION_IMPACT) { 120 model.SetVariableEvaluationImpact(inputVariables[i], double.Parse(modelData[i])); 121 } else if (results[i] == QUALITY_IMPACT) { 122 model.SetVariableQualityImpact(inputVariables[i], double.Parse(modelData[i])); 123 } else throw new FormatException(); 124 } 125 } 102 126 } 103 127 104 private IEnumerable<ModelResult> GetModelResults(Model model, string[] modelData) { 105 return from i in Enumerable.Range(0, results.Count()) 106 where results[i] != null 107 select new ModelResult(model, results[i], double.Parse(modelData[i])); 128 private void SetModelResults(HeuristicLab.Modeling.Model model, string[] modelData) { 129 model.TrainingMeanSquaredError = double.Parse(modelData[TRAINING_MSE]); 130 model.ValidationMeanSquaredError = double.Parse(modelData[VALIDATION_MSE]); 131 model.TestMeanSquaredError = double.Parse(modelData[TEST_MSE]); 132 133 model.TrainingCoefficientOfDetermination = double.Parse(modelData[TRAINING_R2]); 134 model.ValidationCoefficientOfDetermination = double.Parse(modelData[VALIDATION_R2]); 135 model.TestCoefficientOfDetermination = double.Parse(modelData[TEST_R2]); 136 137 model.TrainingMeanAbsolutePercentageError = double.Parse(modelData[TRAINING_MAPE]); 138 model.ValidationCoefficientOfDetermination = double.Parse(modelData[VALIDATION_MAPE]); 139 model.TestCoefficientOfDetermination = double.Parse(modelData[TEST_MAPE]); 140 141 model.TrainingMeanAbsolutePercentageOfRangeError = double.Parse(modelData[TRAINING_MAPRE]); 142 model.ValidationMeanAbsolutePercentageOfRangeError = double.Parse(modelData[VALIDATION_MAPRE]); 143 model.TestMeanAbsolutePercentageOfRangeError = double.Parse(modelData[TEST_MAPRE]); 144 145 model.TrainingVarianceAccountedFor = double.Parse(modelData[TRAINING_VAF]); 146 model.ValidationVarianceAccountedFor = double.Parse(modelData[VALIDATION_VAF]); 147 model.TestVarianceAccountedFor = double.Parse(modelData[TEST_VAF]); 108 148 } 109 149 -
trunk/tools/CedmaImporter/ImporterForm.cs
r2259 r2272 31 31 string directoryName = Path.GetDirectoryName(fileName); 32 32 importer.Import(fileName, directoryName); 33 result = dialog.ShowDialog(); 33 34 } 34 35 }
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