    001package org.cpsolver.exam;
    002
    003import java.io.File;
    004import java.io.IOException;
    005import java.io.PrintWriter;
    006import java.util.ArrayList;
    007import java.util.HashMap;
    008import java.util.HashSet;
    009import java.util.List;
    010import java.util.Locale;
    011import java.util.Map;
    012import java.util.Set;
    013
    014
    015import org.cpsolver.exam.model.Exam;
    016import org.cpsolver.exam.model.ExamModel;
    017import org.cpsolver.exam.model.ExamPlacement;
    018import org.cpsolver.exam.model.ExamRoom;
    019import org.cpsolver.exam.model.ExamRoomPlacement;
    020import org.cpsolver.exam.model.ExamStudent;
    021import org.cpsolver.ifs.assignment.Assignment;
    022import org.cpsolver.ifs.assignment.DefaultSingleAssignment;
    023import org.cpsolver.ifs.util.DataProperties;
    024import org.cpsolver.ifs.util.Progress;
    025import org.cpsolver.ifs.util.ToolBox;
    026import org.dom4j.io.SAXReader;
    027
    028/**
    029 * A simple program that prints a few statistics about the given examination problem in the format of the MISTA 2013 paper
    030 * (entitled Real-life Examination Timetabling).
    031 * It outputs data for the Table 1 (characteristics of the data sets) and Table 2 (number of rooms and exams of a certain size).
    032 * <br>
    033 * Usage:
    034 * <pre><code>java -cp cpsolver-all-1.2.jar org.cpsolver.exam.MistaTables problem1.xml problem2.xml ...</code></pre>
    035 * <br>
    036 *
    037 * @version ExamTT 1.3 (Examination Timetabling)<br>
    038 *          Copyright (C) 2008 - 2014 Tomáš Müller<br>
    039 *          <a href="mailto:muller@unitime.org">muller@unitime.org</a><br>
    040 *          <a href="http://muller.unitime.org">http://muller.unitime.org</a><br>
    041 * <br>
    042 *          This library is free software; you can redistribute it and/or modify
    043 *          it under the terms of the GNU Lesser General Public License as
    044 *          published by the Free Software Foundation; either version 3 of the
    045 *          License, or (at your option) any later version. <br>
    046 * <br>
    047 *          This library is distributed in the hope that it will be useful, but
    048 *          WITHOUT ANY WARRANTY; without even the implied warranty of
    049 *          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
    050 *          Lesser General Public License for more details. <br>
    051 * <br>
    052 *          You should have received a copy of the GNU Lesser General Public
    053 *          License along with this library; if not see
    054 *          <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>.
    055 */
    056public class MistaTables {
    057    private static org.apache.log4j.Logger sLog = org.apache.log4j.Logger.getLogger(MistaTables.class);
    058    private static java.text.DecimalFormat sNF = new java.text.DecimalFormat("###,##0", new java.text.DecimalFormatSymbols(Locale.US));
    059    private static java.text.DecimalFormat sDF = new java.text.DecimalFormat("###,##0.000", new java.text.DecimalFormatSymbols(Locale.US));
    060
    061    public static void main(String[] args) {
    062        try {
    063            ToolBox.configureLogging();
    064            DataProperties config = new DataProperties();
    065
    066            Table[] tables = new Table[] { new Problems(), new Rooms() };
    067
    068            for (int i = 0; i < args.length; i++) {
    069                File file = new File(args[i]);
    070                sLog.info("Loading " + file);
    071                ExamModel model = new ExamModel(config);
    072                Assignment<Exam, ExamPlacement> assignment = new DefaultSingleAssignment<Exam, ExamPlacement>();
    073                model.load(new SAXReader().read(file), assignment);
    074
    075                String name = file.getName();
    076                if (name.contains("."))
    077                    name = name.substring(0, name.indexOf('.'));
    078
    079                for (Table table: tables)
    080                    table.add(name, model);
    081
    082                Progress.removeInstance(model);
    083            }
    084
    085            sLog.info("Saving tables...");
    086            File output = new File("tables"); output.mkdir();
    087            for (Table table: tables)
    088                table.save(output);
    089
    090            sLog.info("All done.");
    091        } catch (Exception e) {
    092            sLog.error(e.getMessage(), e);
    093        }
    094    }
    095
    096    public static class Counter {
    097        private double iTotal = 0.0, iMin = 0.0, iMax = 0.0, iTotalSquare = 0.0;
    098        private int iCount = 0;
    099
    100        public Counter() {
    101        }
    102
    103        public void inc(double value) {
    104                if (iCount == 0) {
    105                        iTotal = value;
    106                        iMin = value;
    107                        iMax = value;
    108                        iTotalSquare = value * value;
    109                } else {
    110                        iTotal += value;
    111                        iMin = Math.min(iMin, value);
    112                        iMax = Math.max(iMax, value);
    113                        iTotalSquare += value * value;
    114                }
    115                iCount ++;
    116        }
    117
    118        public int count() { return iCount; }
    119        public double sum() { return iTotal; }
    120        public double min() { return iMin; }
    121        public double max() { return iMax; }
    122        public double rms() { return (iCount == 0 ? 0.0 : Math.sqrt(iTotalSquare / iCount) - Math.abs(avg())); }
    123        public double avg() { return (iCount == 0 ? 0.0 : iTotal / iCount); }
    124
    125        @Override
    126        public String toString() {
    127                return sDF.format(sum()) +
    128                " (min: " + sDF.format(min()) +
    129                ", max: " + sDF.format(max()) +
    130                ", avg: " + sDF.format(avg()) +
    131                ", rms: " + sDF.format(rms()) +
    132                ", cnt: " + count() + ")";
    133        }
    134    }
    135
    136    public static abstract class Table {
    137        private List<String> iProblems = new ArrayList<String>();
    138        private List<String> iProperties = new ArrayList<String>();
    139        private Map<String, Map<String, String>> iData = new HashMap<String, Map<String, String>>();
    140
    141        public abstract void add(String problem, ExamModel model);
    142
    143
    144        protected void add(String problem, String property, int value) {
    145            add(problem, property, sNF.format(value));
    146        }
    147
    148        protected void add(String problem, String property, double value) {
    149            add(problem, property, sDF.format(value));
    150        }
    151
    152        protected void add(String problem, String property, Counter value) {
    153            add(problem, property, sDF.format(value.avg()) + " ± " + sDF.format(value.rms()));
    154        }
    155
    156        protected void add(String problem, String property, String value) {
    157            if (!iProblems.contains(problem)) iProblems.add(problem);
    158            if (!iProperties.contains(property)) iProperties.add(property);
    159            Map<String, String> table = iData.get(problem);
    160            if (table == null) {
    161                table = new HashMap<String, String>();
    162                iData.put(problem, table);
    163            }
    164            table.put(property, value);
    165        }
    166
    167        public void save(File folder) throws IOException {
    168            PrintWriter pw = new PrintWriter(new File(folder, getClass().getSimpleName() + ".csv"));
    169
    170            pw.print("Problem");
    171            for (String problem: iProblems) pw.print(",\"" + problem + "\"");
    172            pw.println();
    173
    174            for (String property: iProperties) {
    175                pw.print("\"" + property + "\"");
    176                for (String problem: iProblems) {
    177                    String value = iData.get(problem).get(property);
    178                    pw.print("," + (value == null ? "" : "\"" + value + "\""));
    179                }
    180                pw.println();
    181            }
    182
    183            pw.flush(); pw.close();
    184        }
    185    }
    186
    187    public static class Problems extends Table {
    188        @Override
    189        public void add(String problem, ExamModel model) {
    190            int enrollments = 0;
    191            for (ExamStudent student: model.getStudents())
    192                enrollments += student.variables().size();
    193
    194            int examSeating = 0;
    195            int examsFixedInTime = 0, examsFixedInRoom = 0, examsLarge = 0, examsToSplit = 0, examsWithOriginalRoom = 0;
    196            Counter avgPeriods = new Counter(), avgRooms = new Counter(), avgBigRooms = new Counter();
    197            double density = 0;
    198
    199            for (Exam exam: model.variables()) {
    200                if (exam.hasAltSeating()) examSeating ++;
    201
    202                if (exam.getPeriodPlacements().size() <= 2)
    203                    examsFixedInTime ++;
    204                if (exam.getRoomPlacements().size() <= 2)
    205                    examsFixedInRoom ++;
    206
    207                for (ExamRoomPlacement room: exam.getRoomPlacements()) {
    208                    if (room.getPenalty() < -2) { examsWithOriginalRoom ++; break; }
    209                }
    210
    211                int bigEnoughRooms = 0;
    212                for (ExamRoomPlacement room: exam.getRoomPlacements()) {
    213                    if (room.getSize(exam.hasAltSeating()) >= exam.getSize()) bigEnoughRooms ++;
    214                }
    215
    216                if (bigEnoughRooms == 0)
    217                    examsToSplit ++;
    218
    219                if (exam.getSize() >= 600)
    220                    examsLarge ++;
    221
    222                avgPeriods.inc(exam.getPeriodPlacements().size());
    223                avgRooms.inc(exam.getRoomPlacements().size());
    224                avgBigRooms.inc(bigEnoughRooms);
    225
    226                density += exam.nrStudentCorrelatedExams();
    227            }
    228
    229            add(problem, "Exams", model.variables().size());
    230            add(problem, "   with exam seating", examSeating);
    231            add(problem, "Students", model.getStudents().size());
    232            add(problem, "Enrollments", enrollments);
    233            add(problem, "Distribution constraints", model.getDistributionConstraints().size());
    234
    235            add(problem, "Exams fixed in time", examsFixedInTime);
    236            add(problem, "Exams fixed in room", examsFixedInRoom);
    237            add(problem, "Large exams (600+)", examsLarge);
    238            add(problem, "Exams needing a room split", examsToSplit);
    239            add(problem, "Exams with original room", examsWithOriginalRoom);
    240            add(problem, "Density", sDF.format(100.0 * density / (model.variables().size() * (model.variables().size() - 1))) + "%");
    241
    242            add(problem, "Average periods", avgPeriods);
    243            add(problem, "Average rooms", avgRooms);
    244            add(problem, "   that are big enough", avgBigRooms);
    245        }
    246    }
    247
    248    public static class Rooms extends Table {
    249        @Override
    250        public void add(String problem, ExamModel model) {
    251            int[] sizes = new int[] { 0, 100, 200, 400, 600 };
    252            int[] nrRooms = new int[] { 0, 0, 0, 0, 0 }, nrRoomsAlt = new int[] { 0, 0, 0, 0, 0 };
    253            int[] nrExams = new int[] { 0, 0, 0, 0, 0 }, nrExamsAlt = new int[] { 0, 0, 0, 0, 0 };
    254            double[] density = new double[] { 0, 0, 0, 0, 0 };
    255
    256            Set<ExamRoom> rooms = new HashSet<ExamRoom>();
    257            for (Exam exam: model.variables()) {
    258                for (ExamRoomPlacement room: exam.getRoomPlacements()) {
    259                    if (rooms.add(room.getRoom())) {
    260                        for (int i = 0; i < sizes.length; i++) {
    261                            if (room.getRoom().getSize() >= sizes[i])
    262                                nrRooms[i] ++;
    263                            if (room.getRoom().getAltSize() >= sizes[i])
    264                                nrRoomsAlt[i] ++;
    265                        }
    266                    }
    267                }
    268
    269                for (int i = 0; i < sizes.length; i++) {
    270                    if (exam.getSize() >= sizes[i]) {
    271                        nrExams[i] ++;
    272                        if (exam.hasAltSeating())
    273                            nrExamsAlt[i] ++;
    274                        for (Exam x: exam.getStudentCorrelatedExams())
    275                            if (x.getSize() >= sizes[i])
    276                                density[i] ++;
    277                    }
    278                }
    279            }
    280
    281            for (int i = 0; i < sizes.length; i++) {
    282                add(problem, "Rooms" + (sizes[i] == 0 ? "" : " (≥ " + sizes[i] + " seats)"), sNF.format(nrRooms[i]) + (sizes[i] == 0 ? "" : " (" + sNF.format(nrRoomsAlt[i]) + ")"));
    283            }
    284            for (int i = 0; i < sizes.length; i++) {
    285                add(problem, "Exams" + (sizes[i] == 0 ? "" : " (≥ " + sizes[i] + " seats)"), sNF.format(nrExams[i]) + (sizes[i] == 0 ? "" : " (" + sNF.format(nrExamsAlt[i]) + ")"));
    286            }
    287            for (int i = 0; i < sizes.length; i++) {
    288                add(problem, "Density" + (sizes[i] == 0 ? "" : " (≥ " + sizes[i] + " seats)"), sDF.format(100.0 * density[i] / (nrExams[i] * (nrExams[i] - 1))) + "%");
    289            }
    290        }
    291    }
    292
    293}