diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java
index 5fa9ad6800b3964369d0a1f140db6a4c3e0d164f..75bbfe3c434e95adfe3474c3ad571db46403748a 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java
@@ -103,8 +103,7 @@ public class MqttReceiver implements AutoCloseable {
mqtt.setHost(this.host);
connection = mqtt.callbackConnection();
AtomicReference<Throwable> error = new AtomicReference<>();
- connection.listener(new Listener() {
- @Override
+ connection.listener(new ExtendedListener() {
public void onConnected() {
logger.debug("Connected");
}
@@ -115,12 +114,17 @@ public class MqttReceiver implements AutoCloseable {
}
@Override
- public void onPublish(UTF8Buffer topicBuffer, Buffer body, Runnable ack) {
- String topicString = topicBuffer.toString();
+ public void onPublish(UTF8Buffer topic, Buffer body, Callback<Callback<Void>> ack) {
+ String topicString = topic.toString();
String message = body.ascii().toString();
// logger.debug("{}: {}", topicString, message);
onMessageCallback.accept(topicString, message);
- ack.run(); // always acknowledge message
+ ack.onSuccess(null); // always acknowledge message
+ }
+
+ @Override
+ public void onPublish(UTF8Buffer topicBuffer, Buffer body, Runnable ack) {
+ logger.warn("onPublish should not be called");
}
@Override
diff --git a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java
index cdf3e9d03c99e48df645c8df8dfcbd6eac754a8d..3f990bc454289c519c7f41f1851a9f00a423c9eb 100644
--- a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java
+++ b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java
@@ -1,6 +1,7 @@
package de.tudresden.inf.st.eraser.starter;
import beaver.Parser;
+import com.fasterxml.jackson.databind.DeserializationFeature;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.dataformat.yaml.YAMLFactory;
import de.tudresden.inf.st.eraser.feedbackloop.analyze.AnalyzeImpl;
@@ -68,6 +69,7 @@ public class EraserStarter {
System.exit(1);
}
ObjectMapper mapper = new ObjectMapper(new YAMLFactory());
+ mapper.disable(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES);
File settingsFile = new File(commandLineOptions.configFile);
Setting settings;
try {
@@ -127,52 +129,6 @@ public class EraserStarter {
machineLearningModel.setEncoder(handler);
machineLearningModel.setDecoder(handler);
root.getMachineLearningRoot().setActivityRecognition(machineLearningModel);
- /**
- //Begin the Integration
- Item item1=model.resolveItem("m_accel_x").get();
- Item item2=model.resolveItem("m_accel_y").get();
- Item item3=model.resolveItem("m_accel_z").get();
- Item item4=model.resolveItem("m_rotation_x").get();
- Item item5=model.resolveItem("m_rotation_y").get();
- Item item6=model.resolveItem("m_rotation_z").get();
- Item item7=model.resolveItem("w_accel_x").get();
- Item item8=model.resolveItem("w_accel_y").get();
- Item item9=model.resolveItem("w_accel_z").get();
- Item item10=model.resolveItem("w_rotation_x").get();
- Item item11=model.resolveItem("w_rotation_y").get();
- Item item12=model.resolveItem("w_rotation_z").get();
- //0.2717419,8.698134,4.471172,0.043741,0.515962,0.854318,1.8818425,4.9320555,8.145074,0.2374878,-0.032836914,0.3381958,working
- item1.setStateFromString("0.2717419");
- item2.setStateFromString("8.698134");
- item3.setStateFromString("4.471172");
- item4.setStateFromString("0.043741");
- item5.setStateFromString("0.515962");
- item6.setStateFromString("0.854318");
- item7.setStateFromString("1.8818425");
- item8.setStateFromString("4.9320555");
- item9.setStateFromString("8.145074");
- item10.setStateFromString("0.2374878");
- item11.setStateFromString("-0.032836914");
- item12.setStateFromString("0.3381958");
-
- ArrayList<Item> newData=new ArrayList<>();
- newData.add(item1);
- newData.add(item2);
- newData.add(item3);
- newData.add(item4);
- newData.add(item5);
- newData.add(item6);
- newData.add(item7);
- newData.add(item8);
- newData.add(item9);
- newData.add(item10);
- newData.add(item11);
- newData.add(item12);
- handler.newData(newData);*/
- List<ItemPreference> preference=handler.classify().getPreferences();
- for(ItemPreference preference1 : preference){
- preference1.apply();
- }
}
// initialize preference learning
@@ -188,23 +144,9 @@ public class EraserStarter {
machineLearningModel.setEncoder(handler);
machineLearningModel.setDecoder(handler);
root.getMachineLearningRoot().setPreferenceLearning(machineLearningModel);
- //working,medium,240,70
- /**Item activity_item = model.resolveItem("activity").get();
- String activity=activity_item.getStateAsString();
- activity_item.setStateFromString(activity);
- Item brightness_item = model.resolveItem("w_brightness").get();
- brightness_item.setStateFromString("medium");
- ArrayList<Item> newData1 = new ArrayList<>();
- newData1.add(activity_item);
- newData1.add(brightness_item);
- handler.newData(newData1);*/
- List<ItemPreference> preference=handler.classify().getPreferences();
- for(ItemPreference preference1 : preference){
- preference1.apply();
- }
}
- machineLearningRoot.getPreferenceLearning().connectItems(settings.preference.items);
+// machineLearningRoot.getPreferenceLearning().connectItems(settings.preference.items);
if (!machineLearningRoot.getActivityRecognition().check()) {
logger.fatal("Invalid activity recognition!");
System.exit(1);
diff --git a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java
index 09af126b0a66f54aa2b6c88fb04bda9cb7218cb3..642438af01298f801af358dfa7dc5a0eae920326 100644
--- a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java
+++ b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java
@@ -6,7 +6,6 @@ import org.apache.logging.log4j.Logger;
import java.net.MalformedURLException;
import java.net.URL;
import java.nio.file.Paths;
-import java.util.List;
/**
* Setting bean.
@@ -47,10 +46,10 @@ class Setting {
public boolean dummy = false;
/** Model id. Default: 1.*/
public int id = 1;
- /** Items to connect to inputs */
- public List<String> items;
- /** Item to change with classification result */
- public String affectedItem;
+// /** Items to connect to inputs */
+// public List<String> items;
+// /** Item to change with classification result */
+// public String affectedItem;
}
public class OpenHabContainer {
/** The URL from which to import and at which openHAB is running */
diff --git a/eraser.starter/starter-setting.yaml b/eraser.starter/starter-setting.yaml
index e8f438cf3eeb22d71d44c675e7328e61ba612562..9bee9fd5220538612272edce35798a6b99629fe2 100644
--- a/eraser.starter/starter-setting.yaml
+++ b/eraser.starter/starter-setting.yaml
@@ -31,8 +31,8 @@ activity:
dummy: false
# Model id. Default: 1.
id: 1
- # Item to change with classification result
- affectedItem: activity
+# # Item to change with classification result
+# affectedItem: activity
# Model for preference learning. If dummy is true, then the file parameter is ignored.
preference:
@@ -43,12 +43,12 @@ preference:
dummy: false
# Model id. Default: 1.
id: 1
- # Items to connect to inputs
- items:
- - activity
- - w_brightness
- # Item to change with classification result
- affectedItem: iris1_item
+# # Items to connect to inputs
+# items:
+# - activity
+# - w_brightness
+# # Item to change with classification result
+# affectedItem: iris1_item
# Initialize the knowledge base by importing data from openHAB.
openhab: