/**
* File ./src/main/java/de/lemo/dms/processing/questions/QPerformanceBoxPlot.java
* Lemo-Data-Management-Server for learning analytics.
* Copyright (C) 2015
* Leonard Kappe, Andreas Pursian, Sebastian Schwarzrock, Boris Wenzlaff
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
**/
/**
* File ./main/java/de/lemo/dms/processing/questions/QPerformanceBoxPlot.java
* Date 2013-01-24
* Project Lemo Learning Analytics
*/
package de.lemo.dms.processing.questions;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import javax.ws.rs.FormParam;
import javax.ws.rs.POST;
import javax.ws.rs.Path;
import org.hibernate.Criteria;
import org.hibernate.Session;
import org.hibernate.criterion.Restrictions;
import de.lemo.dms.core.config.ServerConfiguration;
import de.lemo.dms.db.IDBHandler;
import de.lemo.dms.db.mapping.Attribute;
import de.lemo.dms.db.mapping.LearningAttribute;
import de.lemo.dms.db.mapping.abstractions.ILearningUserAssociation;
import de.lemo.dms.processing.MetaParam;
import de.lemo.dms.processing.Question;
import de.lemo.dms.processing.StudentHelper;
import de.lemo.dms.processing.resulttype.BoxPlot;
import de.lemo.dms.processing.resulttype.ResultListBoxPlot;
import de.lemo.dms.processing.resulttype.ResultListStringObject;
import de.lemo.dms.service.ServiceRatedObjects;
/**
* Accumulates the performance (result of tests) of the users over a period
*
* @author Sebastian Schwarzrock
*/
@Path("performanceboxplot")
public class QPerformanceBoxPlot extends Question {
/**
* @param courses
* (optional) List of course-ids that shall be included
* @param users
* (optional) List of user-ids
* @param quizzes
* (mandatory) List of the tuples: every learning object has successive entries, first the prefix of the
* learning-object-type (11 for "assignment", 14 for "quiz", 17 for "scorm") and the objects id
* @param resolution
* (mandatory)
* @param startTime
* (mandatory)
* @param endTime
* (mandatory)
* @return
*/
@SuppressWarnings("unchecked")
@POST
public ResultListBoxPlot compute(
@FormParam(MetaParam.COURSE_IDS) final List<Long> courses,
@FormParam(MetaParam.USER_IDS) List<Long> users,
@FormParam(MetaParam.QUIZ_IDS) List<Long> quizzes,
@FormParam(MetaParam.RESOLUTION) final Long resolution,
@FormParam(MetaParam.START_TIME) final Long startTime,
@FormParam(MetaParam.END_TIME) final Long endTime,
@FormParam(MetaParam.GENDER) final List<Long> gender) {
validateTimestamps(startTime, endTime, resolution);
if(logger.isDebugEnabled()) {
if ((courses != null) && (courses.size() > 0))
{
StringBuffer buffer = new StringBuffer();
buffer.append("Parameter list: Courses: " + courses.get(0));
for (int i = 1; i < courses.size(); i++) {
buffer.append(", " + courses.get(i));
}
logger.debug(buffer.toString());
}
if ((users != null) && (users.size() > 0))
{
StringBuffer buffer = new StringBuffer();
buffer.append("Parameter list: Users: " + users.get(0));
for (int i = 1; i < users.size(); i++) {
buffer.append(", " + users.get(i));
}
logger.debug(buffer.toString());
}
logger.debug("Parameter list: Start time: : " + startTime);
logger.debug("Parameter list: End time: : " + endTime);
}
final Map<Long, Integer> obj = new HashMap<Long, Integer>();
if(quizzes.size() > 0)
{
for (int i = 0; i < quizzes.size(); i++)
{
obj.put(quizzes.get(i), i);
}
}
else
{
ServiceRatedObjects sro = new ServiceRatedObjects();
ResultListStringObject rso = sro.getRatedObjects(courses);
String s = new String();
int count = 0;
for(int i = 0; i < rso.getElements().size(); i++)
{
if((i + 1) % 3 != 0)
{
s += rso.getElements().get(i);
}
else
{
obj.put(Long.valueOf(s), count);
quizzes.add(Long.valueOf(s));
s= "";
count++;
}
}
}
final HashMap<Long, ArrayList<Double>> values = new HashMap<Long, ArrayList<Double>>();
final IDBHandler dbHandler = ServerConfiguration.getInstance().getMiningDbHandler();
final Session session = dbHandler.getMiningSession();
Criteria criteria;
if(users == null || users.size() == 0)
{
users = new ArrayList<Long>(StudentHelper.getCourseStudentsAliasKeys(courses, gender).values());
}
else
{
Map<Long, Long> userMap = StudentHelper.getCourseStudentsAliasKeys(courses, gender);
List<Long> tmp = new ArrayList<Long>();
for(int i = 0; i < users.size(); i++)
{
tmp.add(userMap.get(users.get(i)));
}
users = tmp;
}
criteria = session.createCriteria(ILearningUserAssociation.class, "log");
criteria.add(Restrictions.between("log.timemodified", startTime, endTime));
if ((courses != null) && (courses.size() > 0)) {
criteria.add(Restrictions.in("log.course.id", courses));
}
if ((users != null) && (users.size() > 0)) {
criteria.add(Restrictions.in("log.user.id", users));
}
final ArrayList<ILearningUserAssociation> list = (ArrayList<ILearningUserAssociation>) criteria.list();
criteria = session.createCriteria(Attribute.class, "attribute");
criteria.add(Restrictions.like("attribute.name", "MaxGrade"));
Long maxGradeId;
final Map<Long, Double> maxGrades = new HashMap<Long, Double>();
if(!criteria.list().isEmpty())
{
maxGradeId = ((Attribute)criteria.list().get(0)).getId();
criteria = session.createCriteria(LearningAttribute.class, "learningAttribute");
criteria.add(Restrictions.in("learningAttribute.learning.id", obj.keySet()));
criteria.add(Restrictions.eq("learningAttribute.attribute.id", maxGradeId));
for(LearningAttribute la : (List<LearningAttribute>)criteria.list())
{
maxGrades.put(la.getLearning().getId(), Double.valueOf(la.getValue()));
}
}
for (final ILearningUserAssociation aso : list)
{
final Long name = Long.valueOf(aso.getLearning().getId());
if (values.get(name) == null)
{
final ArrayList<Double> v = new ArrayList<Double>();
values.put(name, v);
}
values.get(name).add(aso.getFinalGrade() / ((maxGrades.get(aso.getLearning().getId()) / resolution)));
}
BoxPlot[] results = new BoxPlot[values.keySet().size()];
int i = 0;
for (final Entry<Long, ArrayList<Double>> e : values.entrySet())
{
final BoxPlot plotty = this.calcBox(e.getValue(), e.getKey());
results[i] = plotty;
i++;
}
session.close();
return new ResultListBoxPlot(Arrays.asList(results));
}
// berechnen der boxplot werte
private BoxPlot calcBox(final List<Double> list, final Long id) {
final BoxPlot result = new BoxPlot();
result.setName(id + "");
// ---SORTIEREN
Collections.sort(list);
// ---MEDIAN
// gerade oder ungerade
if ((list.size() % 2) == 0) {
// gerade
int uw, ow;
uw = (list.size() / 2) - 1;
ow = uw + 1;
Double m = (list.get(uw) + list.get(ow));
m = m / 2;
result.setMedian(m);
} else {
// ungerade
result.setMedian(list.get((list.size() / 2)));
}
// ---QUARTILE
// 1 & 2Quartile
long q1, q2;
if (list.size() == 1) {
q1 = 1;
q2 = 1;
} else {
q1 = Math.round(0.25 * ((list.size()) + 1));
q2 = Math.round(0.75 * ((list.size()) + 1));
}
final Long i1 = new Long(q1 - 1);
final Long i2 = new Long(q2 - 1);
result.setLowerQuartil(list.get(i1.intValue()));
result.setUpperQuartil(list.get(i2.intValue()));
result.setUpperWhisker(list.get(list.size() - 1));
result.setLowerWhisker(list.get(0));
return result;
}
}