diff --git a/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Benchmark.java b/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Benchmark.java
index a1c0b7c3ac373d9908824b38bb070c3c793fd573..a22f1b7bb610895afbdfa7f589388129288761a5 100644
--- a/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Benchmark.java
+++ b/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Benchmark.java
@@ -7,8 +7,10 @@ import org.apache.http.entity.ContentType;
import org.apache.http.util.EntityUtils;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
+
import java.io.File;
import java.io.FileReader;
+import java.io.IOException;
import java.util.Arrays;
public class Benchmark {
@@ -38,15 +40,15 @@ public class Benchmark {
private static final Logger logger = LogManager.getLogger(Benchmark.class);
private static final String ERASER_ITEM_URI = "http://localhost:4567/model/items/";
//TODO ITEM_NAME HAS TO BE DISCUSSED
- private static String[] ACTIVITY_ITEM_NAME;
- private static String[] PREFERENCE_ITEM_NAME;
- private static boolean flag2 = true;
+ private String[] ACTIVITY_ITEM_NAME;
+ private String[] PREFERENCE_ITEM_NAME;
//csv_type is activity or preference
Benchmark(String a_csv_file_path, String p_csv_file_path) {
this.a_csv_file_path = a_csv_file_path;
this.p_csv_file_path = p_csv_file_path;
}
void start(){
+ int TIME_PERIOD = 1000;
String PREFERENCE_URL = "http://localhost:4567/model/items/iris1_item/state";
String ACTIVITY_URL = "http://localhost:4567/activity/current";
File a_file;
@@ -57,7 +59,6 @@ public class Benchmark {
CSVReader p_csv_reader;
String[] a_next_record;
String[] p_next_record;
- boolean flag1;
a_file=new File(a_csv_file_path);
p_file= new File(p_csv_file_path);
try {
@@ -66,45 +67,35 @@ public class Benchmark {
a_csv_reader = new CSVReader(a_file_reader);
p_csv_reader = new CSVReader(p_file_reader);
int i = 0;
- while ((((a_next_record = a_csv_reader.readNext())!= null) && flag2)){
+ while ((a_next_record = a_csv_reader.readNext())!= null){
if( i==0 ){
+
getCSVHeader(Arrays.copyOf(a_next_record,12),"a");
i++;
}
else{
String[] values = Arrays.copyOf(a_next_record,12);
setNewValue(values, ACTIVITY_ITEM_NAME,"activity");
- HttpResponse response= Request.Get(ACTIVITY_URL).execute().returnResponse();
- String status = response.getStatusLine().toString();
- if(status.contains("200")){
- flag1 = true;
- logger.info("activity should be (read direct from CSV): " + a_next_record[12]);
- logger.info(EntityUtils.toString(response.getEntity()));
- logger.info("get activity from web server: response 200 ok");
- }else{
- flag1 = false;
- flag2 = false;
- logger.info("can not get the activity from the web server");
- }
int j = 0;
- while((((p_next_record = p_csv_reader.readNext()) != null) && flag1)) {
- if( j==0 ){
+ while(((p_next_record = p_csv_reader.readNext()) != null)) {
+ if( j == 0 ){
getCSVHeader(Arrays.copyOf(p_next_record,2),"p");
j++;
}else{
String[] values1 = Arrays.copyOf(p_next_record,2);
setNewValue(values1, PREFERENCE_ITEM_NAME,"preference");
+ // wait for 1s
+ try{Thread.sleep(TIME_PERIOD);}catch (InterruptedException e){e.printStackTrace();}
+ HttpResponse response= Request.Get(ACTIVITY_URL).execute().returnResponse();
HttpResponse response1= Request.Get(PREFERENCE_URL).execute().returnResponse();
- String status1=response1.getStatusLine().toString();
- if(status1.contains("200")){
- flag2 = true;
- logger.info("get the iris1_item preference from web server: response 200 ok, value is: "+EntityUtils.toString(response1.getEntity()));
- }else {flag2 = false;
- logger.info("can not get the iris1_item from the web server");}
+ //check response
+ checkResult(response, a_next_record);
+ checkResult(response1, p_next_record);
break;
}
}
}
+
}
}
catch (Exception e){
@@ -113,7 +104,6 @@ public class Benchmark {
}
private void setNewValue(String[] values, String[] name, String file_typ){
- int TIME_PERIOD = 1000;
if(file_typ.equals("activity"))
{
int i = 0;
@@ -137,8 +127,6 @@ public class Benchmark {
}else{
String uri= ERASER_ITEM_URI + "w_brightness" +"/state";
try {
- logger.info("debug for w_brigntess");
- logger.info(values[1]);
HttpResponse httpResponse = Request.Put(uri)
.bodyString(values[1], ContentType.TEXT_PLAIN)
.execute().returnResponse();
@@ -150,7 +138,7 @@ public class Benchmark {
e.printStackTrace();
}
}
- try{Thread.sleep(TIME_PERIOD);}catch (InterruptedException e){e.printStackTrace();}
+
}
private void getCSVHeader(String[] a_values,String csv_typ){
@@ -160,4 +148,40 @@ public class Benchmark {
PREFERENCE_ITEM_NAME = a_values;
}
}
+ private void checkResult(HttpResponse response,String[] record){
+ int status = response.getStatusLine().getStatusCode();
+ if(status == 200 && record.length == 13){
+ logger.info("activity should be (read direct from CSV): " + record[12]);
+ try {
+ logger.info(EntityUtils.toString(response.getEntity()));
+ }catch (IOException e){
+ e.printStackTrace();
+ }
+ logger.info("get activity from web server: response 200 ok");
+
+ }else if(status ==200 && record.length == 4){
+ logger.info("preference should be (read direct from CSV): " + getPreference(record));
+ try {
+ logger.info("get the iris1_item preference from web server: response 200 ok, value is: " +
+ EntityUtils.toString(response.getEntity()));
+ }catch (IOException e){
+ e.printStackTrace();
+ }
+
+ }else if(status !=
+ 200 &&record.length == 13){
+ logger.info("can not get the activity from the web server");
+
+ }
+ else if(status != 200 && record.length == 4){
+ logger.info("can not get the iris1_item from the web server");
+ }else {
+ logger.info("unknown check");
+ }
+ }
+
+ private String getPreference(String[] record){
+ return "";
+
+ }
}
\ No newline at end of file
diff --git a/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Main.java b/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Main.java
index ac7536cae53749132be31ebe028e5ec0e55c30f4..640ef4e751e888f4e4ee13fe73868c794e3337a4 100644
--- a/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Main.java
+++ b/benchmark/src/main/java/de/tudresden/inf/st/eraser/benchmark/Main.java
@@ -5,7 +5,7 @@ public class Main {
public static void main(String[] args) {
String A_CSV_FILE_PATH = "../datasets/backup/activity_data.csv";
String P_CSV_FILE_PATH = "../datasets/backup/preference_data.csv";
- Benchmark benchmark=new Benchmark(A_CSV_FILE_PATH,P_CSV_FILE_PATH);
+ Benchmark benchmark = new Benchmark(A_CSV_FILE_PATH,P_CSV_FILE_PATH);
benchmark.start();
}
}
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 4adfd683365a749a1dbf667fe3e1b413acf06018..cdf3e9d03c99e48df645c8df8dfcbd6eac754a8d 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
@@ -168,11 +168,11 @@ public class EraserStarter {
newData.add(item10);
newData.add(item11);
newData.add(item12);
- handler.newData(newData);
+ handler.newData(newData);*/
List<ItemPreference> preference=handler.classify().getPreferences();
for(ItemPreference preference1 : preference){
preference1.apply();
- }*/
+ }
}
// initialize preference learning
@@ -197,11 +197,11 @@ public class EraserStarter {
ArrayList<Item> newData1 = new ArrayList<>();
newData1.add(activity_item);
newData1.add(brightness_item);
- handler.newData(newData1);
+ handler.newData(newData1);*/
List<ItemPreference> preference=handler.classify().getPreferences();
for(ItemPreference preference1 : preference){
preference1.apply();
- }*/
+ }
}
machineLearningRoot.getPreferenceLearning().connectItems(settings.preference.items);
diff --git a/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Learner.java b/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Learner.java
index d6c86be5a5e6bd64311066fb7225cfc66194558e..2519d4fdf16e26634e5b053d3870ca3baa579f5a 100644
--- a/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Learner.java
+++ b/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Learner.java
@@ -151,7 +151,7 @@ public class Learner {
String activity_predictor(String[] new_data){
logger.info("Activity predicting ... ...");
String activity_result;
- activityDataAnalyser("datasets/backup/activity_data.csv");
+ activityDataAnalyser("../datasets/backup/activity_data.csv");
BasicNetwork activity_method = (BasicNetwork) loadObject(save_activity_model_file);
MLData input = activity_helper.allocateInputVector();
activity_helper.normalizeInputVector(new_data,input.getData(),false);
@@ -166,7 +166,7 @@ public class Learner {
logger.info("Activity predicting ... ...");
String[] preference_result;
preference_result = new String[2];
- preferenceDataAnalyser("datasets/backup/preference_data.csv");
+ preferenceDataAnalyser("../datasets/backup/preference_data.csv");
BasicNetwork preference_method = (BasicNetwork)loadObject(save_preference_model_file);
MLData input = preference_helper.allocateInputVector();
preference_helper.normalizeInputVector(new_data, input.getData(),false);
@@ -187,5 +187,3 @@ public class Learner {
}
}
-
-
diff --git a/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/MachineLearningImpl.java b/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/MachineLearningImpl.java
index 90c1837d60e5d53325f9a4a30ca59f1096e8e778..f536026f95b47dab38c1acb695284bd31b5728ea 100644
--- a/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/MachineLearningImpl.java
+++ b/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/MachineLearningImpl.java
@@ -132,9 +132,9 @@ public class MachineLearningImpl implements MachineLearningDecoder, MachineLearn
new_data[1]=item.getStateAsString();
}
}
+ this.preference_result=learner.preference_predictor(new_data);
logger.info("debug for p");
logger.info(Arrays.toString(preference_result));
- this.preference_result=learner.preference_predictor(new_data);
}
}
@@ -169,11 +169,12 @@ public class MachineLearningImpl implements MachineLearningDecoder, MachineLearn
for (int i=0; i< activites.length;i++){
if(activites[i].equals(activityStringValue)){
activityItem.setStateFromString(String.valueOf(i));
+ ItemPreference classifiedActivity = new ItemPreferenceDouble(activityItem,i);
+ return new MachineLearningResultImpl(classifiedActivity);
}
+ logger.debug("Classify would return activity: {}", activityStringValue);
}
- logger.debug("Classify would return activity: {}", activityStringValue);
- ItemPreference classifiedActivity = new ItemPreferenceDouble(activityItem, 0);
- return new MachineLearningResultImpl(classifiedActivity);
+
case GOAL_PREFERENCE_BRIGHTNESS_IRIS:
// String[] preference = {result[1], result[2]};
// FIXME what is the meaning of result[1] and result[2]
diff --git a/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Main.java b/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Main.java
index 7aa90f90c0c917d566661b648bf494b6116c6b1a..f6de59fbc7683e254b5108f0202fbfaa36f7ae99 100644
--- a/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Main.java
+++ b/feedbackloop.learner_backup/src/main/java/de/tudresden/inf/st/eraser/feedbackloop.learner_backup/Main.java
@@ -13,11 +13,12 @@ public class Main {
* */
//ReaderCSV reader = new ReaderCSV("datasets/backup/activity_data.csv","preference");
//reader.updater();
- Learner learner=new Learner();
+ //Learner learner=new Learner();
//learner.preference_train("../datasets/backup/preference_data.csv");
- learner.train("datasets/backup/activity_data.csv","datasets/backup/preference_data.csv");
+ //learner.train("datasets/backup/activity_data.csv","datasets/backup/preference_data.csv");
+ activity_validation_learner();
//0.5793968,1.2126632,-4.6244006,-0.030779,0.801127,0.590978,-3.1411927,-0.93373865,-0.31124622,-0.35992432,0.33746338,-0.79608154,dancing
- String[] new_data = new String[12];
+ /*String[] new_data = new String[12];
new_data[0]="0.5793968";
new_data[1]="1.2126632";
new_data[2]="-4.6244006";
@@ -123,45 +124,53 @@ 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", false, CSVFormat.DECIMAL_POINT);
- String[] line = new String[12];
- Learner learner=new Learner();
+ 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");
int wrong=0;
int right=0;
+ int i =0;
while(csv.next()) {
- StringBuilder result = new StringBuilder();
- line[0] = csv.get(0);
- line[1] = csv.get(1);
- line[2] = csv.get(2);
- line[3] = csv.get(3);
- line[4] = csv.get(4);
- line[5] = csv.get(5);
- line[6] = csv.get(6);
- line[7] = csv.get(7);
- line[8] = csv.get(8);
- line[9] = csv.get(9);
- line[10] = csv.get(10);
- line[11] = csv.get(11);
- String correct = csv.get(12);
- String irisChosen = learner.predictor(line)[0];
- result.append(Arrays.toString(line));
- result.append(" -> predicted: ");
- result.append(irisChosen);
- result.append("(correct: ");
- result.append(correct);
- result.append(")");
- if (irisChosen.equals(correct)!=true){
- System.out.println(correct);
- System.out.println(irisChosen);
- ++wrong;
- }else{
- ++right;
+ if(i==0){
+ i++;
+
+ }else {
+ StringBuilder result = new StringBuilder();
+ line[0] = csv.get(0);
+ line[1] = csv.get(1);
+ line[2] = csv.get(2);
+ line[3] = csv.get(3);
+ line[4] = csv.get(4);
+ line[5] = csv.get(5);
+ line[6] = csv.get(6);
+ line[7] = csv.get(7);
+ line[8] = csv.get(8);
+ line[9] = csv.get(9);
+ line[10] = csv.get(10);
+ //line[11] = csv.get(11);
+ String correct = csv.get(11);
+ String irisChosen = learner.predictor(line)[0];
+ result.append(Arrays.toString(line));
+ result.append(" -> predicted: ");
+ result.append(irisChosen);
+ result.append("(correct: ");
+ result.append(correct);
+ result.append(")");
+ if (irisChosen.equals(correct)!=true){
+ System.out.println(correct);
+ System.out.println(irisChosen);
+ ++wrong;
+ }else{
+ ++right;
+ }
+ System.out.println(result.toString());
}
- System.out.println(result.toString());
- }
- System.out.println("wrong number"+wrong);
- System.out.println("right number"+right);
- //double validation = (double(right))/(double(wrong+right));
- //System.out.println("%.2f"+validation);
+ System.out.println("wrong number"+wrong);
+ System.out.println("right number"+right);}
+
+
+ //double validation = (double(right))/(double(wrong+right));
+ //System.out.println("%.2f"+validation);
}
}