Revize 0e7b6b11

Re #9049 Implementation of GetDataFileNames and Load methods

Server/ServerApp/Predictor/PredictionController.cs

@@ -9 +9 @@
 using Newtonsoft.Json;
 using ServerApp.WeatherPredictionParser;
 using ServerApp.Parser.OutputInfo;
-using System.Reflection;
 using log4net;
+using System.IO;
+using System.Text.RegularExpressions;
+using System.Linq;
 
 namespace ServerApp.Predictor
 {
@@ -21 +23 @@
     {
         private static readonly ILog _log = LogManager.GetLogger(typeof(PredictionController));
 
+        /// <summary>
+        /// ID of the current predictor instances.
+        /// </summary>
+        private string PredictorID;
+
         /// <summary>
         /// Configuration of the <c>Predictor</c>
         /// </summary>
-        private PredictorConfiguration Configuration;
+        public PredictorConfiguration Configuration { get; set; }
+
+        /// <summary>
+        /// Names of the files used to train the current predictor instances.
+        /// </summary>
+        private IEnumerable<string> DataFilenames;
 
-        private List<IPredictor> Predictors;
+        /// <summary>
+        /// Current predictor instances
+        /// </summary>
+        private IPredictor[] Predictors;
 
         /// <summary>
         /// A reference to a data parser.
@@ -49 +64 @@
         /// <param name="dataParser">A data parser used to get training data.</param>
         public PredictionController(IJsonParser weatherService, IDataParser dataParser, string pathToConfig = null)
         {
+            // TODO look for existing predictors
             _log.Info("Constructing a new PredictionController instance.");
             this.weatherService = weatherService;
             // load config or get the default one
@@ -58 +74 @@
             }
             try
             {
-                string json = System.IO.File.ReadAllText(pathToConfig);
+                string json = File.ReadAllText(pathToConfig);
                 this.Configuration = JsonConvert.DeserializeObject<PredictorConfiguration>(json);
             }
             catch (System.IO.IOException e)
@@ -69 +85 @@
             }
 
             this.DataParser = dataParser;
-            this.Predictors = new List<IPredictor>();
+            this.Predictors = new IPredictor[this.Configuration.PredictorCount];
             this.FeatureExtractor = new FeatureExtractor(this.DataParser, this.Configuration);
+            this.DataFilenames = dataParser.WeatherDataUsed.Concat(dataParser.ActivityDataUsed);
+            this.PredictorID = DateTime.Now.ToString();
 
             for (int i = 0; i < this.Configuration.PredictorCount; i++)
             {
-                Predictors.Add(new NaiveBayesClassifier());
+                Predictors[i] = new NaiveBayesClassifier();
             }
             PredictorConfiguration.SaveConfig(PredictorConfiguration.DEFAULT_CONFIG_PATH, Configuration);
         }
@@ -83 +101 @@
             return new List<string>(this.Configuration.BuildingsToAreas.Keys);
         }
 
-        public void Load(string locationKey = null, string path = null)
+        public void Load(string predictorID)
         {
-            if (locationKey is null)
-            {
-                throw new NotImplementedException();
-            }
-            else
+            DirectoryInfo di = new DirectoryInfo(Configuration.ModelDataPath);
+            FileInfo[] files = di.GetFiles($"{predictorID}_*.zip");
+            IPredictor[] newPredictors = new IPredictor[this.Configuration.PredictorCount];
+            for (int i = 0; i < this.Configuration.PredictorCount; i++)
             {
-                throw new NotImplementedException();
+                newPredictors[i] = new NaiveBayesClassifier(Array.Find(files, f => Regex.IsMatch(f.Name, $"{predictorID}_{i}.zip")).FullName);
             }
+            this.Predictors = newPredictors;
+            files = di.GetFiles($"{predictorID}.txt");
+            this.DataFilenames = File.ReadLines(files[0].FullName);
+            this.PredictorID = predictorID;
+        }
+
+        public void Rollback()
+        {
+
         }
 
         public Response Predict(Request request)
@@ -132 +158 @@
         private Prediction PredictSingle(Request request, DateTime predictionTime)
         {
             double[] predictedValues = new double[this.Configuration.BuildingsToAreas.Count];
-            string[] predictedLabels = new string[this.Predictors.Count];
-            for (int i = 0; i < this.Predictors.Count; i++)
+            string[] predictedLabels = new string[this.Predictors.Length];
+            for (int i = 0; i < this.Predictors.Length; i++)
             {
                 if (request.useWeather)
                 {
@@ -187 +213 @@
             return prediction;
         }
 
-        public void Train(string locationKey = null)
+        public void Train()
         {
-            if (locationKey is null)
-            // train all predictors
-            {
-                DataParser.Parse(DateTime.MinValue, DateTime.MaxValue, this.Configuration.TimeResolution, wholeDay: false);
-                for (int i = 0; i < this.Predictors.Count; i++)
+            DataParser.Parse(DateTime.MinValue, DateTime.MaxValue, this.Configuration.TimeResolution, wholeDay: false);
+                for (int i = 0; i < this.Predictors.Length; i++)
                 {
                     // train on all available data
                     List<ModelInput> data = FeatureExtractor.PrepareTrainingInput(i);
                     Console.WriteLine("Training predictor with {0} samples.", data.Count);
                     this.Predictors[i].Fit(data);
                 }
-            }
-            else
-            // train specified predictor only
-            {
-                throw new NotImplementedException();
-            }
         }
 
-
+        public IEnumerable<string> GetDataFileNames()
+        {
+            return this.DataFilenames;
+        }
     }
 }