300 lines
8.7 KiB
C++
300 lines
8.7 KiB
C++
/*
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* Scheduler.h
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* @brief an example how inference can be used for scheduling qualifiers
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* @date Mar 26, 2011
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* @author Frank Dellaert
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*/
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#include <gtsam_unstable/discrete/Scheduler.h>
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#include <gtsam/discrete/DiscreteFactorGraph.h>
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#include <gtsam/discrete/DiscreteSequentialSolver.h>
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#include <gtsam/base/debug.h>
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#include <gtsam/base/timing.h>
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#include <boost/tokenizer.hpp>
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#include <boost/foreach.hpp>
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#include <fstream>
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#include <iomanip>
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#include <cmath>
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namespace gtsam {
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using namespace std;
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Scheduler::Scheduler(size_t maxNrStudents, const string& filename):
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maxNrStudents_(maxNrStudents)
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{
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typedef boost::tokenizer<boost::escaped_list_separator<char> > Tokenizer;
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// open file
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ifstream is(filename.c_str());
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if (!is) {
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cerr << "Scheduler: could not open file " << filename << endl;
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throw runtime_error("Scheduler: could not open file " + filename);
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}
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string line; // buffer
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// process first line with faculty
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if (getline(is, line, '\r')) {
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Tokenizer tok(line);
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Tokenizer::iterator it = tok.begin();
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for (++it; it != tok.end(); ++it)
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addFaculty(*it);
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}
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// for all remaining lines
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size_t count = 0;
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while (getline(is, line, '\r')) {
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if (count++ > 100) throw runtime_error("reached 100 lines, exiting");
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Tokenizer tok(line);
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Tokenizer::iterator it = tok.begin();
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addSlot(*it++); // add slot
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// add availability
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for (; it != tok.end(); ++it)
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available_ += (it->empty()) ? "0 " : "1 ";
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available_ += '\n';
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}
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} // constructor
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/** addStudent has to be called after adding slots and faculty */
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void Scheduler::addStudent(const string& studentName,
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const string& area1, const string& area2,
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const string& area3, const string& advisor) {
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assert(nrStudents()<maxNrStudents_);
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assert(facultyInArea_.count(area1));
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assert(facultyInArea_.count(area2));
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assert(facultyInArea_.count(area3));
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size_t advisorIndex = facultyIndex_[advisor];
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Student student(nrFaculty(), advisorIndex);
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student.name_ = studentName;
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// We fix the ordering by assigning a higher index to the student
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// and numbering the areas lower
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Index j = 3*maxNrStudents_ + nrStudents();
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student.key_ = DiscreteKey(j, nrTimeSlots());
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Index base = 3*nrStudents();
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student.keys_[0] = DiscreteKey(base+0, nrFaculty());
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student.keys_[1] = DiscreteKey(base+1, nrFaculty());
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student.keys_[2] = DiscreteKey(base+2, nrFaculty());
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student.areaName_[0] = area1;
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student.areaName_[1] = area2;
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student.areaName_[2] = area3;
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students_.push_back(student);
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}
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/** get key for student and area, 0 is time slot itself */
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const DiscreteKey& Scheduler::key(size_t s, boost::optional<size_t> area) const {
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return area ? students_[s].keys_[*area] : students_[s].key_;
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}
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const string& Scheduler::studentName(size_t i) const {
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assert(i<nrStudents());
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return students_[i].name_;
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}
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const DiscreteKey& Scheduler::studentKey(size_t i) const {
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assert(i<nrStudents());
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return students_[i].key_;
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}
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const string& Scheduler::studentArea(size_t i, size_t area) const {
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assert(i<nrStudents());
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return students_[i].areaName_[area];
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}
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/** Add student-specific constraints to the graph */
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void Scheduler::addStudentSpecificConstraints(size_t i, boost::optional<size_t> slot) {
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bool debug = ISDEBUG("Scheduler::buildGraph");
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assert(i<nrStudents());
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const Student& s = students_[i];
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if (!slot && !slotsAvailable_.empty()) {
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if (debug) cout << "Adding availability of slots" << endl;
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CSP::add(s.key_, slotsAvailable_);
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}
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// For all areas
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for (size_t area = 0; area < 3; area++) {
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DiscreteKey areaKey = s.keys_[area];
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const string& areaName = s.areaName_[area];
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if (debug) cout << "Area constraints " << areaName << endl;
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CSP::add(areaKey, facultyInArea_[areaName]);
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if (debug) cout << "Advisor constraint " << areaName << endl;
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CSP::add(areaKey, s.advisor_);
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if (debug) cout << "Availability of faculty " << areaName << endl;
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if (slot) {
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// get all constraints then specialize to slot
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DiscreteKey dummy(0, nrTimeSlots());
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Potentials::ADT p(dummy & areaKey, available_);
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Potentials::ADT q = p.choose(0, *slot);
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DiscreteFactor::shared_ptr f(new DecisionTreeFactor(areaKey, q));
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CSP::push_back(f);
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} else {
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CSP::add(s.key_, areaKey, available_);
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}
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}
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// add mutex
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if (debug) cout << "Mutex for faculty" << endl;
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addAllDiff(s.keys_[0] & s.keys_[1] & s.keys_[2]);
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}
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/** Main routine that builds factor graph */
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void Scheduler::buildGraph(size_t mutexBound) {
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bool debug = ISDEBUG("Scheduler::buildGraph");
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if (debug) cout << "Adding student-specific constraints" << endl;
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for (size_t i = 0; i < nrStudents(); i++)
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addStudentSpecificConstraints(i);
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// special constraint for MN
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if (studentName(0) == "Michael N") CSP::add(studentKey(0),
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"0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1");
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if (!mutexBound) {
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DiscreteKeys dkeys;
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BOOST_FOREACH(const Student& s, students_)
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dkeys.push_back(s.key_);
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addAllDiff(dkeys);
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} else {
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if (debug) cout << "Mutex for Students" << endl;
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for (size_t i1 = 0; i1 < nrStudents(); i1++) {
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// if mutexBound=1, we only mutex with next student
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size_t bound = min((i1 + 1 + mutexBound), nrStudents());
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for (size_t i2 = i1 + 1; i2 < bound; i2++) {
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addAllDiff(studentKey(i1), studentKey(i2));
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}
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}
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}
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} // buildGraph
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/** print */
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void Scheduler::print(const string& s) const {
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cout << s << " Faculty:" << endl;
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BOOST_FOREACH(const string& name, facultyName_)
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cout << name << '\n';
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cout << endl;
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cout << s << " Slots:\n";
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size_t i = 0;
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BOOST_FOREACH(const string& name, slotName_)
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cout << i++ << " " << name << endl;
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cout << endl;
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cout << "Availability:\n" << available_ << '\n';
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cout << s << " Area constraints:\n";
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BOOST_FOREACH(const FacultyInArea::value_type& it, facultyInArea_)
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{
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cout << setw(12) << it.first << ": ";
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BOOST_FOREACH(double v, it.second)
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cout << v << " ";
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cout << '\n';
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}
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cout << endl;
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cout << s << " Students:\n";
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BOOST_FOREACH (const Student& student, students_)
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student.print();
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cout << endl;
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CSP::print(s + " Factor graph");
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cout << endl;
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} // print
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/** Print readable form of assignment */
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void Scheduler::printAssignment(sharedValues assignment) const {
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// Not intended to be general! Assumes very particular ordering !
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cout << endl;
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for (size_t s = 0; s < nrStudents(); s++) {
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Index j = 3*maxNrStudents_ + s;
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size_t slot = assignment->at(j);
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cout << studentName(s) << " slot: " << slotName_[slot] << endl;
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Index base = 3*s;
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for (size_t area = 0; area < 3; area++) {
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size_t faculty = assignment->at(base+area);
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cout << setw(12) << studentArea(s,area) << ": " << facultyName_[faculty]
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<< endl;
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}
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cout << endl;
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}
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}
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/** Special print for single-student case */
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void Scheduler::printSpecial(sharedValues assignment) const {
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Values::const_iterator it = assignment->begin();
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for (size_t area = 0; area < 3; area++, it++) {
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size_t f = it->second;
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cout << setw(12) << it->first << ": " << facultyName_[f] << endl;
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}
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cout << endl;
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}
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/** Accumulate faculty stats */
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void Scheduler::accumulateStats(sharedValues assignment, vector<
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size_t>& stats) const {
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for (size_t s = 0; s < nrStudents(); s++) {
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Index base = 3*s;
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for (size_t area = 0; area < 3; area++) {
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size_t f = assignment->at(base+area);
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assert(f<stats.size());
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stats[f]++;
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} // area
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} // s
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}
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/** Eliminate, return a Bayes net */
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DiscreteBayesNet::shared_ptr Scheduler::eliminate() const {
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tic(1, "my_solver");
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DiscreteSequentialSolver solver(*this);
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toc(1, "my_solver");
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tic(2, "my_eliminate");
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DiscreteBayesNet::shared_ptr chordal = solver.eliminate();
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toc(2, "my_eliminate");
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return chordal;
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}
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/** Find the best total assignment - can be expensive */
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Scheduler::sharedValues Scheduler::optimalAssignment() const {
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DiscreteBayesNet::shared_ptr chordal = eliminate();
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if (ISDEBUG("Scheduler::optimalAssignment")) {
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DiscreteBayesNet::const_reverse_iterator it = chordal->rbegin();
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const Student & student = students_.front();
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cout << endl;
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(*it)->print(student.name_);
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}
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tic(3, "my_optimize");
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sharedValues mpe = optimize(*chordal);
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toc(3, "my_optimize");
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return mpe;
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}
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/** find the assignment of students to slots with most possible committees */
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Scheduler::sharedValues Scheduler::bestSchedule() const {
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sharedValues best;
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throw runtime_error("bestSchedule not implemented");
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return best;
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}
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/** find the corresponding most desirable committee assignment */
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Scheduler::sharedValues Scheduler::bestAssignment(
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sharedValues bestSchedule) const {
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sharedValues best;
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throw runtime_error("bestAssignment not implemented");
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return best;
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}
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} // gtsam
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