public boolean addNewStudent(
String admission_No,
String name,
String fullname,
String name_wt_initial,
Date dob,
String gender,
String address) {
Student student = YschoolDataPoolFactory.getStudent();
student.setAddress(admission_No);
student.setName(name);
student.setFullName(fullname);
student.setNameWtInitial(name_wt_initial);
student.setDob(dob);
student.setGender(gender);
student.setAddress(address);
// TODO: hage to get bytestream to send database.
// student.setPhoto(photo);
dataLayerYschool.save(student);
dataLayerYschool.flushSession();
// TODO: save method does not indicates/returns success/failure
return true;
}
public boolean preloadStudent() {
// this.student = analyticsService.getStudenById(39);
this.student = analyticsController.getStudent();
this.oLSubjects = new ListDataModel(analyticsService.getOLSubjects(student));
this.oLSubjectsEleven = new ListDataModel(analyticsService.getOLSubjectsEleven(student));
List<OLSubjectPrediction> olSubjectPredictions = new ArrayList<>();
double termMark = 0.0;
Iterator<ClassroomSubject> olsubjectIterator = oLSubjects.iterator();
Iterator<ClassroomSubject> olsubjectElevenIterator = oLSubjectsEleven.iterator();
OLSubjectPrediction olSubjectPrediction = null;
while (true) {
List<Double> termMarks = new ArrayList<Double>();
ClassroomSubject olSubject = null;
ClassroomSubject olsubjectEleven = null;
if (olsubjectIterator.hasNext() && olsubjectElevenIterator.hasNext()) {
olSubject = olsubjectIterator.next();
olsubjectEleven = olsubjectElevenIterator.next();
} else {
break;
}
ArrayList<Integer> previousTermMarks = new ArrayList<>();
ArrayList<Integer> predictedTermMarksLower = new ArrayList<>();
ArrayList<Integer> predictedTermMarksUpper = new ArrayList<>();
ArrayList<Integer> range = new ArrayList<>();
olSubjectPrediction = new OLSubjectPrediction();
boolean check = true;
for (int term = 1; term <= 3; term++) {
termMark = analyticsService.getTermMarksForOLSub(this.student, olSubject, term);
if (termMark >= 0 && termMark <= 100) {
termMarks.add(termMark);
int mark = (int) termMark;
if (check) {
previousTermMarks.add(mark);
try {
// range = predictNextTerm(null, 2008, 10, term,
// olSubject.getSubjectIdsubject().getName(), student.getId(), previousTermMarks);
if (term < 3) {
range =
predictNextTerm(
null,
2008,
10,
term + 1,
olSubject.getSubjectIdsubject().getName(),
student.getId(),
previousTermMarks);
}
if (term == 3) {
range =
predictNextTerm(
null,
2009,
11,
1,
olSubject.getSubjectIdsubject().getName(),
student.getId(),
previousTermMarks);
}
} catch (Exception e) {
}
}
}
// else if (termMark == -1) {
// termMarks.add(-0.1);
// } else if (termMark == -2) {
// termMarks.add(-0.2);
// } else if (termMark == -3) {
// termMarks.add(-0.3);
// }
else {
check = false;
termMark = -1.0;
termMarks.add(termMark);
range.add(-1);
range.add(-1);
olSubjectPrediction.setCheck(true);
// break;
}
predictedTermMarksLower.add(range.get(0));
predictedTermMarksUpper.add(range.get(1));
}
for (int term = 1; term <= 3; term++) {
termMark = analyticsService.getTermMarksForOLSub(this.student, olsubjectEleven, term);
if (termMark >= 0 && termMark <= 100) {
termMarks.add(termMark);
olSubjectPrediction.setCheckTermMarks(false);
int mark = (int) termMark;
if (check) {
previousTermMarks.add(mark);
try {
if (term < 3) {
range =
predictNextTerm(
null,
2008,
11,
term + 1,
olSubject.getSubjectIdsubject().getName(),
student.getId(),
previousTermMarks);
}
if (term == 3) {
// range = predictNextTerm(null, 2008, 11, 1,
// olSubject.getSubjectIdsubject().getName(), student.getId(), previousTermMarks);
}
} catch (Exception e) {
}
}
}
// else if (termMark == -1) {
// termMarks.add(-0.1);
// } else if (termMark == -2) {
// termMarks.add(-0.2);
// } else if (termMark == -3) {
// termMarks.add(-0.3);
// }
else {
check = false;
termMark = -1.0;
termMarks.add(termMark);
range.add(-1);
range.add(-1);
olSubjectPrediction.setCheck(true);
// break;
}
if (term < 3) {
predictedTermMarksLower.add(range.get(0));
predictedTermMarksUpper.add(range.get(1));
}
}
olSubjectPrediction.setOlSubject(olSubject);
olSubjectPrediction.setTermMarks(termMarks);
olSubjectPrediction.setTermMarksUpper(predictedTermMarksUpper);
olSubjectPrediction.setTermMarksLower(predictedTermMarksLower);
// createLinearModelTermMarks(olSubjectPrediction);
// olSubjectPrediction.setLinearModelTermMarks(linearModelTermMarks);
olSubjectPredictions.add(olSubjectPrediction);
}
this.olSubjectPredictions = new ListDataModel<OLSubjectPrediction>(olSubjectPredictions);
Iterator<OLSubjectPrediction> iterator = olSubjectPredictions.iterator();
while (iterator.hasNext()) {
OLSubjectPrediction olSubjectPrediction_tmp = iterator.next();
olSubjectPrediction_tmp.setLinearModelTermMarks(
createLinearModelTermMarksForOlSub(olSubjectPrediction_tmp));
}
Iterator<OLSubjectPrediction> iterator1 = olSubjectPredictions.iterator();
while (iterator1.hasNext()) {
OLSubjectPrediction olSubjectPrediction_tmp = iterator1.next();
// List<String> msgs = new ArrayList<>();
// String msg = olSubjectPrediction_tmp.getMsg();
if (olSubjectPrediction_tmp.isCheck()) {
olSubjectPrediction_tmp.setMsg(null);
olSubjectPrediction_tmp.setMsgWarning(null);
olSubjectPrediction_tmp.setMsgValidation(null);
continue;
}
// int index = 0;
// while (index < olSubjectPrediction_tmp.getTermMarksLower().size()-1) {
// msgs = new ArrayList<>();
int recentIndex = olSubjectPrediction_tmp.getTermMarks().size() - 1;
double termMarks1;
termMarks1 = olSubjectPrediction_tmp.getTermMarks().get(recentIndex - 1);
double lower = olSubjectPrediction_tmp.getTermMarksLower().get(recentIndex - 2);
double upper = olSubjectPrediction_tmp.getTermMarksUpper().get(recentIndex - 2);
double upper_prediction = olSubjectPrediction_tmp.getTermMarksUpper().get(recentIndex - 1);
double lower_prediction = olSubjectPrediction_tmp.getTermMarksUpper().get(recentIndex - 1);
if (upper < upper_prediction) {
olSubjectPrediction_tmp.setPrediction_msgValidation(MessageStudentHome.future_positive);
olSubjectPrediction_tmp.setPrediction_msgValidation_available(true);
} else if (lower > lower_prediction) {
olSubjectPrediction_tmp.setPrediction_msgWarning(MessageStudentHome.future_negative);
olSubjectPrediction_tmp.setPrediction_msgWarning_available(true);
} else if (lower <= lower_prediction || upper_prediction <= upper) {
olSubjectPrediction_tmp.setPrediction_msg(MessageStudentHome.future_information);
olSubjectPrediction_tmp.setPrediction_msg_available(true);
}
if (upper >= termMarks1 && termMarks1 >= lower) {
// index++;
olSubjectPrediction_tmp.setMsg(MessageStudentHome.info_consis);
olSubjectPrediction_tmp.setMsg_available(true);
continue;
}
if (upper < termMarks1) {
// msgs.add(MessageStudentHome.appreciation);
olSubjectPrediction_tmp.setMsgValidation(MessageStudentHome.appreciation);
olSubjectPrediction_tmp.setMsgValidation_available(true);
olSubjectPrediction_tmp.setMsg(null);
olSubjectPrediction_tmp.setMsgWarning(null);
continue;
}
if (lower > termMarks1) {
olSubjectPrediction_tmp.setMsgWarning(MessageStudentHome.warning);
olSubjectPrediction_tmp.setMsgWarning_available(true);
olSubjectPrediction_tmp.setMsg(null);
olSubjectPrediction_tmp.setMsgValidation(null);
continue;
} else {
olSubjectPrediction_tmp.setMsg_available(true);
}
// index++;
}
// olSubjectPrediction_tmp.setMsgs(msg);
// }
return true;
}