gtsam/gtsam_unstable/discrete/examples/schedulingQuals12.cpp

/*
 * schedulingExample.cpp
 * @brief hard scheduling example
 * @date March 25, 2011
 * @author Frank Dellaert
 */

#define ENABLE_TIMING
#define ADD_NO_CACHING
#define ADD_NO_PRUNING
#define ENABLE_OLD_TIMING
#include <gtsam_unstable/discrete/Scheduler.h>
#include <gtsam/base/debug.h>
#include <gtsam/base/timing.h>

#include <boost/assign/std/vector.hpp>
#include <boost/assign/std/map.hpp>
#include <boost/optional.hpp>
#include <boost/foreach.hpp>
#include <boost/format.hpp>

#include <algorithm>

using namespace boost::assign;
using namespace std;
using namespace gtsam;

size_t NRSTUDENTS = 9;

bool NonZero(size_t i) {
	return i > 0;
}

/* ************************************************************************* */
void addStudent(Scheduler& s, size_t i) {
	switch (i) {
	case 0:
		s.addStudent("Pan, Yunpeng", "Controls", "Perception", "Mechanics", "Eric Johnson");
		break;
	case 1:
		s.addStudent("Sawhney, Rahul", "Controls", "AI", "Perception", "Henrik Christensen");
		break;
	case 2:
		s.addStudent("Akgun, Baris", "Controls", "AI", "HRI", "Andrea Thomaz");
		break;
	case 3:
		s.addStudent("Jiang, Shu", "Controls", "AI", "Perception", "Ron Arkin");
		break;
	case 4:
		s.addStudent("Grice, Phillip", "Controls", "Perception", "HRI", "Charlie Kemp");
		break;
	case 5:
		s.addStudent("Huaman, Ana", "Controls", "AI", "Perception", "Mike Stilman");
		break;
	case 6:
		s.addStudent("Levihn, Martin", "AI", "Autonomy", "Perception", "Mike Stilman");
		break;
	case 7:
		s.addStudent("Nieto, Carlos", "AI", "Autonomy", "Perception", "Henrik Christensen");
		break;
	case 8:
		s.addStudent("Robinette, Paul", "Controls", "AI", "HRI", "Ayanna Howard");
		break;
	}
}

/* ************************************************************************* */
Scheduler largeExample(size_t nrStudents = NRSTUDENTS) {
	string path("../../../gtsam_unstable/discrete/examples/");
	Scheduler s(nrStudents, path + "Doodle2012.csv");

	s.addArea("Harvey Lipkin", "Mechanics");
	s.addArea("Jun Ueda", "Mechanics");

	s.addArea("Patricio Vela", "Controls");
	s.addArea("Magnus Egerstedt", "Controls");
	s.addArea("Jun Ueda", "Controls");
	s.addArea("Panos Tsiotras", "Controls");
	s.addArea("Fumin Zhang", "Controls");

	s.addArea("Henrik Christensen", "Perception");
	s.addArea("Aaron Bobick", "Perception");

	s.addArea("Mike Stilman", "AI");
//	s.addArea("Henrik Christensen", "AI");
	s.addArea("Ayanna Howard", "AI");
	s.addArea("Charles Isbell", "AI");
	s.addArea("Tucker Balch", "AI");

	s.addArea("Ayanna Howard", "Autonomy");
	s.addArea("Charlie Kemp", "Autonomy");
	s.addArea("Tucker Balch", "Autonomy");
	s.addArea("Ron Arkin", "Autonomy");

	s.addArea("Andrea Thomaz", "HRI");
	s.addArea("Karen Feigh", "HRI");
	s.addArea("Charlie Kemp", "HRI");

	// add students
	for (size_t i = 0; i < nrStudents; i++)
		addStudent(s, i);

	return s;
}

/* ************************************************************************* */
void runLargeExample() {

	Scheduler scheduler = largeExample();
	scheduler.print();

	// BUILD THE GRAPH !
	size_t addMutex = 3;
	// SETDEBUG("Scheduler::buildGraph", true);
	scheduler.buildGraph(addMutex);

	// Do brute force product and output that to file
	if (scheduler.nrStudents() == 1) { // otherwise too slow
		DecisionTreeFactor product = scheduler.product();
		product.dot("scheduling-large", false);
	}

	// Do exact inference
	//	SETDEBUG("timing-verbose", true);
	SETDEBUG("DiscreteConditional::DiscreteConditional", true);
#define SAMPLE
#ifdef SAMPLE
	tic(2, "large");
	DiscreteBayesNet::shared_ptr chordal = scheduler.eliminate();
	toc(2, "large");
	tictoc_finishedIteration();
	tictoc_print();
	for (size_t i=0;i<100;i++) {
		DiscreteFactor::sharedValues assignment = sample(*chordal);
		vector<size_t> stats(scheduler.nrFaculty());
		scheduler.accumulateStats(assignment, stats);
		size_t max = *max_element(stats.begin(), stats.end());
		size_t min = *min_element(stats.begin(), stats.end());
		size_t nz = count_if(stats.begin(), stats.end(), NonZero);
//		cout << min << ", " << max << ", "  << nz << endl;
		if (nz >= 13 && min >=1 && max <= 4) {
			cout << "======================================================\n";
			scheduler.printAssignment(assignment);
		}
	}
#else
	tic(2, "large");
	DiscreteFactor::sharedValues MPE = scheduler.optimalAssignment();
	toc(2, "large");
	tictoc_finishedIteration();
	tictoc_print();
	scheduler.printAssignment(MPE);
#endif
}

/* ************************************************************************* */
// Solve a series of relaxed problems for maximum flexibility solution
void solveStaged(size_t addMutex = 2) {

	// super-hack! just count...
	bool debug = false;
	SETDEBUG("DiscreteConditional::COUNT", true);
	SETDEBUG("DiscreteConditional::DiscreteConditional", debug); // progress

	// make a vector with slot availability, initially all 1
	// Reads file to get count :-)
	vector<double> slotsAvailable(largeExample(0).nrTimeSlots(), 1.0);

	// now, find optimal value for each student, using relaxed mutex constraints
	for (size_t s = 0; s < NRSTUDENTS; s++) {
		// add all students first time, then drop last one second time, etc...
		Scheduler scheduler = largeExample(NRSTUDENTS - s);
		//scheduler.print(str(boost::format("Scheduler %d") % (NRSTUDENTS-s)));

		// only allow slots not yet taken
		scheduler.setSlotsAvailable(slotsAvailable);

		// BUILD THE GRAPH !
		scheduler.buildGraph(addMutex);

		// Do EXACT INFERENCE
		tic_("eliminate");
		DiscreteBayesNet::shared_ptr chordal = scheduler.eliminate();
		toc_("eliminate");

		// find root node
		DiscreteConditional::shared_ptr root = *(chordal->rbegin());
		if (debug)
			root->print(""/*scheduler.studentName(s)*/);

		// solve root node only
		Scheduler::Values values;
		size_t bestSlot = root->solve(values);

		// get corresponding count
		DiscreteKey dkey = scheduler.studentKey(NRSTUDENTS - 1 - s);
		values[dkey.first] = bestSlot;
		size_t count = (*root)(values);

		// remove this slot from consideration
		slotsAvailable[bestSlot] = 0.0;
		cout << boost::format("%s = %d (%d), count = %d") % scheduler.studentName(NRSTUDENTS-1-s)
				% scheduler.slotName(bestSlot) % bestSlot % count << endl;
	}
	tictoc_print_();
}

/* ************************************************************************* */
// Sample from solution found above and evaluate cost function
DiscreteBayesNet::shared_ptr createSampler(size_t i,
		size_t slot, vector<Scheduler>& schedulers) {
	Scheduler scheduler = largeExample(0); // todo: wrong nr students
	addStudent(scheduler, i);
	SETDEBUG("Scheduler::buildGraph", false);
	scheduler.addStudentSpecificConstraints(0, slot);
	DiscreteBayesNet::shared_ptr chordal = scheduler.eliminate();
	// chordal->print(scheduler[i].studentKey(0).name()); // large !
	schedulers.push_back(scheduler);
	return chordal;
}

void sampleSolutions() {

	vector<Scheduler> schedulers;
	vector<DiscreteBayesNet::shared_ptr> samplers(NRSTUDENTS);

	// Given the time-slots, we can create NRSTUDENTS independent samplers
	vector<size_t> slots;
	slots += 3, 20, 2, 6, 5, 11, 1, 4; // given slots
	for (size_t i = 0; i < NRSTUDENTS; i++)
		samplers[i] = createSampler(i, slots[i], schedulers);

	// now, sample schedules
	for (size_t n = 0; n < 500; n++) {
		vector<size_t> stats(19, 0);
		vector<Scheduler::sharedValues> samples;
		for (size_t i = 0; i < NRSTUDENTS; i++) {
			samples.push_back(sample(*samplers[i]));
			schedulers[i].accumulateStats(samples[i], stats);
		}
		size_t max = *max_element(stats.begin(), stats.end());
		size_t min = *min_element(stats.begin(), stats.end());
		size_t nz = count_if(stats.begin(), stats.end(), NonZero);
		if (nz >= 15 && max <= 2) {
			cout << boost::format(
					"Sampled schedule %d, min = %d, nz = %d, max = %d\n") % (n + 1) % min
					% nz % max;
			for (size_t i = 0; i < NRSTUDENTS; i++) {
				cout << schedulers[i].studentName(0) << " : " << schedulers[i].slotName(
						slots[i]) << endl;
				schedulers[i].printSpecial(samples[i]);
			}
		}
	}
}

/* ************************************************************************* */
int main() {
	runLargeExample();
//	solveStaged(3);
//	sampleSolutions();
	return 0;
}
/* ************************************************************************* */