fix activity inputs

eraser.starter/src/main/resources/starter.eraser

@@ -18,7 +18,7 @@ String Item: id="w_accel_y" label="" state="4.9320555" topic="w_accel_y";
 String Item: id="w_accel_z" label="" state="8.145074" topic="w_accel_z";
 String Item: id="w_rotation_x" label="" state="0.2374878" topic="w_rotation_x";
 String Item: id="w_rotation_y" label="" state="-0.032836914" topic="w_rotation_y";
-String Item: id="w_rotation_z" label="" state="0.3381958" topic="w_rotation_y";
+String Item: id="w_rotation_z" label="" state="0.3381958" topic="w_rotation_z";
 String Item: id="w_brightness" label="" state="bright" topic="w_brightness";
 //String Item: id="activity" label="" state="lying" topic="activity";
 Activity Item: id="activity" topic="activity";

feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/MachineLearningImpl.java

@@ -25,6 +25,12 @@ public class MachineLearningImpl implements MachineLearningDecoder, MachineLearn
   private List<Item> relevant_item_list;
   private String[] preference_result;
 
+  private String[] a_new_data = new String[12];
+  private String[] p_new_data = new String[2];
+
+  private int a_length = 0;
+  boolean empty;
+
   private Root root;
   private String activity_result;
 
@@ -98,36 +104,52 @@ public class MachineLearningImpl implements MachineLearningDecoder, MachineLearn
              or let knowledge base pass all relevant items <- push model
     */
     if (this.goal == GOAL_ACTIVITY_PHONE_AND_WATCH) {
-      String[] new_data = new String[12];
-      for (int i = 0; i < new_data.length; i++) {
-        new_data[i] = "0";
-      }
+
       for (Item item : changedItems) {
+        if(item.getID().equals("m_accel_x"))
+        {
+          a_length = 0;
+        }
         int i = 0;
         for (Item item1 : relevant_item_list) {
           if (item.getTopic().toString().equals(item1.getTopic().toString())) {
-            new_data[i] = item.getStateAsString();
+            this.a_new_data[i] = item.getStateAsString();
           }
           i++;
         }
+        a_length++;
+      }
+      if(a_length == 12){
+        for (String value : a_new_data){
+          if(value == null){
+            empty = true;
+          }
+        }
+        if(!empty){
+          this.activity_result = learner.activity_predictor(a_new_data);
+        }
+        a_length = 0;
+        for (int j=0; j < this.a_new_data.length; j++){
+          this.a_new_data[j] = null;
+        }
       }
-      this.activity_result = learner.activity_predictor(new_data);
 
     } else if (this.goal == GOAL_PREFERENCE_BRIGHTNESS_IRIS) {
-      String[] new_data = new String[2];
       for (Item item : changedItems) {
         if (root.getSmartHomeEntityModel().getActivityItem().equals(item)) {
           String test = item.getStateAsString();
           int index = Math.round(Float.valueOf(test));
-          new_data[0] = root.getMachineLearningRoot().getActivity(index).getLabel();
+          this.p_new_data[0] = root.getMachineLearningRoot().getActivity(index).getLabel();
         }
         if (item.getID().equals("w_brightness")) {
-          new_data[1] = item.getStateAsString();
+          this.p_new_data[1] = item.getStateAsString();
         }
       }
-      this.preference_result = learner.preference_predictor(new_data);
+      logger.info("debug_preference_new_data");
+      logger.info(Arrays.toString(this.p_new_data));
+      this.preference_result = learner.preference_predictor(this.p_new_data);
       logger.info("debug for p");
-      logger.info(Arrays.toString(preference_result));
+      logger.info(Arrays.toString(this.preference_result));
     }
   }
 

feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Main.java

@@ -124,10 +124,10 @@ public class Main {
     //System.out.println("perference is: "+ result[1]);**/
   }
   public static void activity_validation_learner(){
-    ReadCSV csv = new ReadCSV("datasets/backup/activity_data.csv", true, CSVFormat.DECIMAL_POINT);
+    ReadCSV csv = new ReadCSV("../datasets/backup/activity_data.csv", true, CSVFormat.DECIMAL_POINT);
     String[] line = new String[11];
     Learner learner = new Learner();
-    learner.train("datasets/backup/activity_data.csv","datasets/backup/preference_data.csv");
+    learner.train("../datasets/backup/activity_data.csv","../datasets/backup/preference_data.csv");
     int wrong=0;
     int right=0;
     int i =0;