/*
* Summary: Given an array and a specific range [0, size) where the "size"_th
* iteration is not inclusive, return the iteration of the first
* instance of the specified key, or -1 if it does not exist.
* Parameters: u32 array to search, u32 size of the array, and the u32 element
* to locate.
* Return: Iteration of the first location of the key, -1 if it doesn't
* exist.
*/
u32
linearSearch(u32 a[], u32 size, u32 key)
{
if (NULL == a) // null array pointer?
{
logNormal("linearSearch: NULL array pointer!\n");
API_ASSERT_NONNULL(a); // blinkcode!
}
if (size <= 0) // invalid size?
{
logNormal("linearSearch: Invalid size %d\n", size);
API_ASSERT_GREATER(size, 0); // blinkcode!
}
if (key < 0) // invalid key?
{
logNormal("linearSearch: Invalid size %d\n", size);
API_ASSERT_GREATER_EQUAL(size, 0); // blinkcode!
}
for (u32 i = 0; i < size; ++i)
if (a[i] == key) // If there is a match
return i; // say so
return INVALID; // Otherwise, return the signal that there is no match
}
/*
* Summary: Handles (r)esult packet reflex. Packet information is logged and
* result is logged for the specific calculation.
* Parameters: (r)esult packet.
* Return: None.
*/
void
r_handler(u8 * packet)
{
R_PKT PKT_R;
if (packetScanf(packet, "%Zr%z\n", R_ZScanner, &PKT_R) != 3)
{
logNormal("r_handler: Failed at %d\n", packetCursor(packet));
return; // No harm done so no blinkcoding necessary
}
u32 NODE_INDEX; // index holder for if log is valid
// only log properly formatted packets
if (INVALID == (NODE_INDEX = log(PKT_R.key.ID, PKT_R.key.TIME)))
return; // Don't continue if this packet has been received before
// Handle packet spammers
else if (PC_NODE_ARR[NODE_INDEX] > (PKT_R.key.TIME / 1000))
{
// Decrease the amount of pings recorded; "spammer amnesty" of sorts.
PC_NODE_ARR[NODE_INDEX] -= 2;
return; // Don't continue if this IXM is spamming packets right now.
}
else if (PKT_R.calc_ver < HOST_CALC_VER)
return; // Don't continue if this is an old calculation version
else if (0xffffffff == PKT_R.calc_ver)
logNormal("Calculation version overflow.\n");
if (PKT_R.neighbor)
{ // If this a neighboring node
PKT_R.neighbor = 0; // Reset the flag before forwarding
NEIGHBORS_ARR[packetSource(packet)] = PKT_R.key.ID; // And remember the ID
}
// If all the hoops have been jumped through
FWD_R_PKT(&PKT_R, packetSource(packet)); // Forward the packet
if (PKT_R.calc_ver == HOST_CALC_VER) // Same result?
// Update the results from packets with proper calculation versions
voteCount(NODE_INDEX, PKT_R.rslt);
else if (PKT_R.calc_ver > HOST_CALC_VER) // New calculation version?
{ // perform standard procedures
strikeCheck(); // evaluate the strikes for my neighbors
flush(); // clear out my records for the new voting session
voteCount(NODE_INDEX, PKT_R.rslt); // Remember the node's vote
HOST_CALC = PKT_R.calc; // Remember the new calculation
HOST_CALC_VER = PKT_R.calc_ver; // Remember the new calculation version
voteCount(0, calculate(HOST_CALC)); // calculation occurs here
}
return;
}
/*
* Summary: Adjusts the vote count based on a recent vote.
* Parameters: u32 index of the node that voted, u32 ballot of the node.
* Return: None.
*/
void
voteCount(u32 NODE_INDEX, u32 BALLOT)
{
if (NODE_INDEX < 0)
{
logNormal("voteCount: Invalid node index %d", NODE_INDEX);
API_ASSERT_GREATER_EQUAL(NODE_INDEX, 0); // blinkcode!
}
if (BALLOT < 0)
{
logNormal("voteCount: Invalid ballot %d", BALLOT);
API_ASSERT_GREATER_EQUAL(BALLOT, 0); // blinkcode!
}
if (0 == BALLOT) // 0 is never a correct answer
return; // But it's not worth blinkcoding over
else if (BALLOT == VOTE_NODE_ARR[NODE_INDEX])
return; // Ignore duplicate votes
// Invalid vote if I've already voted (didn't flush from a new calculation)
else if (0 != VOTE_NODE_ARR[NODE_INDEX])
return;
else if (0 == VOTE_NODE_ARR[NODE_INDEX]) // Haven't voted yet
++VOTE_COUNT; // This is the first vote received
if (VOTE_COUNT > NODE_COUNT) // Someone voted multiple times
{
flush(); // Clean out memory
voteCount(0, calculate(HOST_CALC)); // Recount our own vote
return;
}
// look to see if the ballot is for an existing candidate
u32 k = linearSearch(CANDIDATE_ARR, CANDIDATE_COUNT + 1, BALLOT);
if (INVALID != k) // if so, give him a vote
++CANDIDATE_VOTES_ARR[k];
else // otherwise the ballot is new to the candidate list
{ // so add it
k = CANDIDATE_COUNT++; // Give him a vote
CANDIDATE_ARR[k] = BALLOT; // Add the new candidate to the nominations list
++CANDIDATE_VOTES_ARR[k]; // Give the candidate a vote
}
VOTE_NODE_ARR[NODE_INDEX] = BALLOT; // record the node's ballot
evalMajority(); //Reevaluate the majority with every different ballot
return;
}
/*
* Summary: Logs the ID and time-stamp keys of a received packet.
* Parameters: u32 ID, u32 time-stamp (from a (r)esult packet)
* Return: Return index of the node if successful, otherwise INVALID.
*/
u32
log(u32 ID, u32 TIME)
{
if (TIME < 0)
{
logNormal("log: No time-traveling or overflow allowed!\n");
API_ASSERT_GREATER_EQUAL(TIME, 0); // blinkcode!
}
for (u32 i = 0; i < NODE_COUNT; ++i)
{ // Look for an existing match in the list of previous PING'ers
if (ID == ID_NODE_ARR[i])
{
if (TIME != TS_NODE_ARR[i])
{ // If there is a match and it is a new packet
if (PC_NODE_ARR[i] < 0xffff) // Make sure ping count won't overflow
++PC_NODE_ARR[i]; // So we can keep track of the valid packet
else
// Notify us if the ping count will overflow
logNormal("Limit of pings reached for IXM %t\n", ID);
TS_NODE_ARR[i] = TIME; // Update nodular time-stamp
TS_HOST_ARR[i] = millis(); // Update host-based time-stamp
return i; // Return the location of the existing node
}
else
// Don't forward the packet if it isn't new
return INVALID;
}
}
// Otherwise check to see if there is any free space left in the array
if (NODE_COUNT >= (sizeof(ID_NODE_ARR) / sizeof(u32)))
{
logNormal("Inadequate memory space in ID table.\n"
"Rebooting.\n");
reenterBootloader(); // Clear out memory for new boards
}
// Add the new IXM board to the phone-book.
ID_NODE_ARR[NODE_COUNT] = ID;
TS_NODE_ARR[NODE_COUNT] = TIME;
TS_HOST_ARR[NODE_COUNT] = millis();
++PC_NODE_ARR[NODE_COUNT];
return NODE_COUNT++; // And pass it on
}
/*
* Summary: Custom (r)esult packet scanner.
* Parameters: The arguments are automatically handled within a parent
* header file.
* Return: Boolean confirming the packet was read correctly.
*/
bool
R_ZScanner(u8 * packet, void * arg, bool alt, int width)
{
/* (r)esult packet structure */
u32 ID; // hex ID (board key)
u32 TIME; // integer timestamp (packet key)
u32 CALC; // integer calculation
u32 CALC_VER; // integer calculation version
u32 VOTE; // integer vote
u32 NEIGHBOR; // neighbor flag
if (packetScanf(packet, "%t,%d,%d,%d,%d,%d", &ID, &TIME, &CALC, &CALC_VER,
&VOTE, &NEIGHBOR) != 11)
{
logNormal("Inconsistent packet format for (r)esult packet.\n");
return false;
}
if (arg)
{
R_PKT * PKT_R = (R_PKT*) arg;
PKT_R->key.ID = ID;
PKT_R->key.TIME = TIME;
PKT_R->calc = CALC;
PKT_R->calc_ver = CALC_VER;
PKT_R->rslt = VOTE;
PKT_R->neighbor = NEIGHBOR;
}
return true;
}
/*
* Summary: Handles (c)alculation packet reflex. Packet information is saved
* and converted into a R packet to be forwarded to neighboring nodes.
* Parameters: (c)alculation packet.
* Return: None.
*/
void
c_handler(u8 * packet)
{
C_PKT PKT_R;
if (packetScanf(packet, "%Zc%z\n", C_ZScanner, &PKT_R) != 3)
{
logNormal("c_handler: Failed at %d\n", packetCursor(packet));
return;
}
if (PKT_R.calc < 0)
{
logNormal("c_handler: Input %d must be a non-negative integer.\n",
PKT_R.calc);
return;
}
if (PKT_R.calc > PRIME_THRESHOLD)
{
logNormal("c_handler: Value %d is higher than the threshold %d (%d).\n",
PKT_R.calc, PRIME_THRESHOLD, PRIME_ARR_THRESHOLD - 1);
return;
}
strikeCheck(); // evaluate the strikes for my neighbors
flush(); // clear out my records for the new voting session
R_PKT PKT_T; // synthesize a new packet
++HOST_CALC_VER;
HOST_CALC = PKT_R.calc;
PKT_T.key.ID = ID_HOST;
PKT_T.key.TIME = millis();
PKT_T.calc = HOST_CALC;
PKT_T.calc_ver = HOST_CALC_VER;
PKT_T.rslt = VOTE_NODE_ARR[0];
// If all the hoops have been jumped through
FWD_R_PKT(&PKT_T, packetSource(packet)); // Forward the packet
voteCount(0, calculate(HOST_CALC)); // calculation occurs here
return;
}
/*
* Summary: Given an array and a specific range [first, size) where the
* "size"_th iteration is not inclusive, return the index of the
* greatest positive value in the array or INVALID if there is a
* tie.
* Parameters: u32 array to search, u32 size of the array.
* Return: Index of the highest value greater than or equal to 0;
* INVALID otherwise.
*/
u32
getMaxIndex(u32 a[], u32 size)
{
if (NULL == a) // null array pointer?
{
logNormal("getMaxIndex: NULL array pointer!\n");
API_ASSERT_NONNULL(a); // blinkcode!
}
if (size <= 0) // invalid size?
{
logNormal("getMaxIndex: Invalid size %d\n", size);
API_ASSERT_GREATER(size, 0); // blinkcode!
}
bool tiedetected = false; // flag to mark if there is a tie
u32 maxVotes = 0; // highest amount of ballots currently
u32 maxIndex = INVALID; // index of the highest candidate
for (u32 i = 0; i < size; ++i)
{ // iterate through the entire array
if (a[i] > maxVotes)
{ // record higher values
maxVotes = a[i];
maxIndex = i;
tiedetected = false; // disarm tie flag
}
// if there is ever candidate that ties with the highest candidate
else if (a[i] == maxVotes)
tiedetected = true; // set tie flag
}
if (tiedetected) // if the tie flag was set
return TIE; // there is no winning candidate
// It worked, there's a candidate greater than 0 votes and no ties
else if ((0 != maxVotes) && (INVALID != maxIndex))
return maxIndex;
else
return INVALID; // This should never happen.
}
/*
* Summary: Displays a table containing each IXM's ID, timestamp(ms), and
* pings. Note that there might exist a time-stamp inconsistency
* (boards may base their time based on when they started receiving
* power).
* Parameters: Time when function was called (handled automagically).
* Return: None.
*/
void
printTable(u32 when)
{
if (when < 0)
{
logNormal("log: No time-traveling or overflow allowed!\n");
API_ASSERT_GREATER_EQUAL(when, 0); // blinkcode!
}
u32 HOST_TIME = when;
facePrintf(
TERMINAL_FACE,
"\n\n\n\n\n\n\n\n\n\n\n\n\n+===============================================================+\n");
facePrintf(TERMINAL_FACE,
"|CALCULATION: %4d HOST TIME: %010d |\n",
HOST_CALC, HOST_TIME);
facePrintf(TERMINAL_FACE,
"+---------------------------------------------------------------+\n");
facePrintf(TERMINAL_FACE,
"|ID ACTIVE TIME-STAMP VOTE STRIKES PINGS|\n");
facePrintf(TERMINAL_FACE,
"+---- ------ ---------- ------ ------- -----+\n");
for (u32 i = 0; i < NODE_COUNT; ++i)
{
facePrintf(TERMINAL_FACE, "|%04t %c%15d%11d%12d%10d|\n",
ID_NODE_ARR[i], ACTIVE_NODE_ARR[i], TS_HOST_ARR[i], VOTE_NODE_ARR[i],
STRIKES_NODE_ARR[i], PC_NODE_ARR[i]);
}
facePrintf(TERMINAL_FACE,
"+---------------------------------------------------------------+\n");
if ((TIE == MAJORITY_RSLT) || (INVALID == MAJORITY_RSLT) || (0
== MAJORITY_RSLT))
facePrintf(TERMINAL_FACE,
"|MAJORITY: -- |\n");
else
facePrintf(TERMINAL_FACE,
"|MAJORITY: %4d |\n",
MAJORITY_RSLT);
facePrintf(TERMINAL_FACE,
"+===============================================================+\n");
// schedule the next table printout
Alarms.set(Alarms.currentAlarmNumber(), when + printTable_PERIOD);
return;
}
/*
* Summary: Custom (c)alculation packet scanner.
* Parameters: The arguments are automatically handled within a parent
* header file.
* Return: Boolean confirming the packet was read correctly.
*/
bool
C_ZScanner(u8 * packet, void * arg, bool alt, int width)
{
/* (c)alculation packet structure */
u32 CALC; // integer calculation
if (packetScanf(packet, "%d", &CALC) != 1)
{
logNormal("Inconsistent packet format for (c)alculation packet.\n");
return false;
}
if (arg)
{
C_PKT * PKT_R = (C_PKT*) arg;
PKT_R->calc = CALC;
}
return true;
}
/***********************************************************************//**
* @brief Generate the exposure cube(s).
*
* This method reads the task parameters from the parfile, sets up the
* observation container, loops over all CTA observations in the container
* and generates an exposure cube from the CTA observations.
***************************************************************************/
void ctexpcube::run(void)
{
// If we're in debug mode then all output is also dumped on the screen
if (logDebug()) {
log.cout(true);
}
// Get task parameters
get_parameters();
// Warn if there are not enough energy bins
log_string(TERSE, warn_too_few_energies(m_expcube.energies()));
// Write input observation container into logger
log_observations(NORMAL, m_obs, "Input observation");
// Initialise exposure cube
init_cube();
// Write header into logger
log_header1(TERSE, "Generate exposure cube");
// Set pointer to logger dependent on chattiness
GLog* logger = (logNormal()) ? &log : NULL;
// Fill exposure cube
m_expcube.fill(m_obs, logger);
// Write exposure cube into logger
log_string(EXPLICIT, m_expcube.print(m_chatter));
// Optionally publish exposure cube
if (m_publish) {
publish();
}
// Return
return;
}
/*
* Summary: Turns on a specific LED color depending on the status input.
* Parameters: u32 LED status denoting which LED to turn on.
* OFF = off, MINORITY = red, MAJORITY = green, PROCESSING = blue
* Return: None.
*/
void
setStatus(u32 STATUS)
{
if ((STATUS != OFF) && // if input is not "no LED"
(STATUS != MINORITY) && // or "red LED"
(STATUS != MAJORITY) && // or "green LED"
(STATUS != PROCESSING)) // or "blue LED"
{
logNormal("setStatus: Invalid input %d\n", STATUS);
// blinkcode!
API_ASSERT((OFF == STATUS) || (MINORITY == STATUS)
|| (MAJORITY == STATUS) || (PROCESSING == STATUS), E_API_EQUAL);
}
for (u8 i = 0; i < 3; ++i)
ledOff(LED_PIN[i]); // turn off the LEDs
if (STATUS == OFF) // and if the status to display is "off"
return; // keep the LEDs off
ledOn(LED_PIN[STATUS]); // otherwise, turn on the appropriate LED
return;
}
/***********************************************************************//**
* @brief Optimize model parameters using Levenberg-Marquardt method
***************************************************************************/
void ctlike::optimize_lm(void)
{
// Write Header for optimization and indent for optimizer logging
if (logTerse()) {
log << std::endl;
log.header1("Maximum likelihood optimisation");
log.indent(1);
}
// Compute number of fitted parameters
int nfit = 0;
for (int i = 0; i < m_obs.models().size(); ++i) {
const GModel* model = m_obs.models()[i];
for (int k = 0; k < model->size(); ++k) {
if ((*model)[k].is_free()) {
nfit++;
}
}
}
// Notify if all parameters are fixed
if (nfit == 0) {
if (logTerse()) {
log << "WARNING: All model parameters are fixed!";
log << std::endl;
log << " ctlike will proceed without fitting parameters.";
log << std::endl;
log << " All curvature matrix elements will be zero.";
log << std::endl;
}
}
// Perform LM optimization
m_obs.optimize(*m_opt);
// Optionally refit
if (m_refit) {
// Dump new header
log.indent(0);
if (logTerse()) {
log << std::endl;
log.header1("Maximum likelihood re-optimisation");
log.indent(1);
}
// Optimise again
m_obs.optimize(*m_opt);
}
// Optionally show curvature matrix
if (logNormal()) {
log << std::endl;
log.header1("Curvature matrix");
log.indent(1);
log << *(const_cast<GObservations::likelihood&>(m_obs.function()).curvature());
log << std::endl;
}
// Compute errors
m_obs.errors(*m_opt);
// Store maximum log likelihood value
m_logL = -(m_opt->value());
// Remove indent
log.indent(0);
// Return
return;
}
/***********************************************************************//**
* @brief Simulate source events from photon list
*
* @param[in] obs Pointer on CTA observation.
* @param[in] models Model list.
* @param[in] ran Random number generator.
* @param[in] wrklog Pointer to logger.
*
* Simulate source events from a photon list for a given CTA observation.
* The events are stored in as event list in the observation.
*
* This method does nothing if the observation pointer is NULL. It also
* verifies if the observation has a valid pointing and response.
***************************************************************************/
void ctobssim::simulate_source(GCTAObservation* obs, const GModels& models,
GRan& ran, GLog* wrklog)
{
// Continue only if observation pointer is valid
if (obs != NULL) {
// If no logger is specified then use the default logger
if (wrklog == NULL) {
wrklog = &log;
}
// Get CTA response
const GCTAResponseIrf* rsp =
dynamic_cast<const GCTAResponseIrf*>(obs->response());
if (rsp == NULL) {
std::string msg = "Response is not an IRF response.\n" +
obs->response()->print();
throw GException::invalid_value(G_SIMULATE_SOURCE, msg);
}
// Get pointer on event list (circumvent const correctness)
GCTAEventList* events =
static_cast<GCTAEventList*>(const_cast<GEvents*>(obs->events()));
// Extract simulation region.
GSkyDir dir = events->roi().centre().dir();
double rad = events->roi().radius() + g_roi_margin;
// Dump simulation cone information
if (logNormal()) {
*wrklog << gammalib::parformat("Simulation area");
*wrklog << m_area << " cm2" << std::endl;
*wrklog << gammalib::parformat("Simulation cone");
*wrklog << "RA=" << dir.ra_deg() << " deg";
*wrklog << ", Dec=" << dir.dec_deg() << " deg";
*wrklog << ", r=" << rad << " deg" << std::endl;
}
// Initialise indentation for logging
int indent = 0;
// Loop over all Good Time Intervals
for (int it = 0; it < events->gti().size(); ++it) {
// Extract time interval
GTime tmin = events->gti().tstart(it);
GTime tmax = events->gti().tstop(it);
// Dump time interval
if (logNormal()) {
if (events->gti().size() > 1) {
indent++;
wrklog->indent(indent);
}
*wrklog << gammalib::parformat("Time interval", indent);
*wrklog << tmin.convert(m_cta_ref);
*wrklog << " - ";
*wrklog << tmax.convert(m_cta_ref);
*wrklog << " s" << std::endl;
}
// Loop over all energy boundaries
for (int ie = 0; ie < events->ebounds().size(); ++ie) {
// Extract energy boundaries
GEnergy emin = events->ebounds().emin(ie);
GEnergy emax = events->ebounds().emax(ie);
// Set true photon energy limits for simulation. If observation
// has energy dispersion then add margin
GEnergy e_true_min = emin;
GEnergy e_true_max = emax;
if (rsp->use_edisp()) {
e_true_min = rsp->ebounds(e_true_min).emin();
e_true_max = rsp->ebounds(e_true_max).emax();
}
// Dump energy range
if (logNormal()) {
if (events->ebounds().size() > 1) {
indent++;
wrklog->indent(indent);
}
*wrklog << gammalib::parformat("Photon energy range", indent);
*wrklog << e_true_min << " - " << e_true_max << std::endl;
*wrklog << gammalib::parformat("Event energy range", indent);
*wrklog << emin << " - " << emax << std::endl;
}
// Loop over all sky models
for (int i = 0; i < models.size(); ++i) {
// Get sky model (NULL if not a sky model)
const GModelSky* model =
dynamic_cast<const GModelSky*>(models[i]);
// If we have a sky model that applies to the present
// observation then simulate events
if (model != NULL &&
model->is_valid(obs->instrument(), obs->id())) {
// Determine duration of a time slice by limiting the
// number of simulated photons to m_max_photons.
// The photon rate is estimated from the model flux
// and used to set the duration of the time slice.
double flux = get_model_flux(model, emin, emax,
dir, rad);
double rate = flux * m_area;
double duration = 1800.0; // default: 1800 sec
if (rate > 0.0) {
duration = m_max_photons / rate;
if (duration < 1.0) { // not <1 sec
duration = 1.0;
}
else if (duration > 180000.0) { // not >50 hr
duration = 180000.0;
}
}
GTime tslice(duration, "sec");
// If photon rate exceeds the maximum photon rate
// then throw an exception
if (rate > m_max_rate) {
std::string modnam = (model->name().length() > 0) ?
model->name() : "Unknown";
std::string msg = "Photon rate "+
gammalib::str(rate)+
" photons/sec for model \""+
modnam+"\" exceeds maximum"
" allowed photon rate of "+
gammalib::str(m_max_rate)+
" photons/sec. Please check"
" the model parameters for"
" model \""+modnam+"\" or"
" increase the value of the"
" hidden \"maxrate\""
" parameter.";
throw GException::invalid_value(G_SIMULATE_SOURCE, msg);
}
// Dump length of time slice and rate
if (logExplicit()) {
*wrklog << gammalib::parformat("Photon rate", indent);
*wrklog << rate << " photons/sec";
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
}
// To reduce memory requirements we split long time
// intervals into several slices.
GTime tstart = tmin;
GTime tstop = tstart + tslice;
// Initialise cumulative photon counters
int nphotons = 0;
// Loop over time slices
while (tstart < tmax) {
// Make sure that tstop <= tmax
if (tstop > tmax) {
tstop = tmax;
}
// Dump time slice
if (logExplicit()) {
if (tmax - tmin > tslice) {
indent++;
wrklog->indent(indent);
}
*wrklog << gammalib::parformat("Time slice", indent);
*wrklog << tstart.convert(m_cta_ref);
*wrklog << " - ";
*wrklog << tstop.convert(m_cta_ref);
*wrklog << " s";
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
}
// Get photons
GPhotons photons = model->mc(m_area, dir, rad,
e_true_min, e_true_max,
tstart, tstop, ran);
// Dump number of simulated photons
if (logExplicit()) {
*wrklog << gammalib::parformat("MC source photons/slice", indent);
*wrklog << photons.size();
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
}
// Simulate events from photons
for (int i = 0; i < photons.size(); ++i) {
// Increment photon counter
nphotons++;
// Simulate event. Note that this method
// includes the deadtime correction.
GCTAEventAtom* event = rsp->mc(m_area,
photons[i],
*obs,
ran);
if (event != NULL) {
// Use event only if it falls within ROI
// energy boundary and time slice
if (events->roi().contains(*event) &&
event->energy() >= emin &&
event->energy() <= emax &&
event->time() >= tstart &&
event->time() <= tstop) {
event->event_id(m_event_id);
events->append(*event);
m_event_id++;
}
delete event;
}
} // endfor: looped over events
// Go to next time slice
tstart = tstop;
tstop = tstart + tslice;
// Reset indentation
if (logExplicit()) {
if (tmax - tmin > tslice) {
indent--;
wrklog->indent(indent);
}
}
} // endwhile: looped over time slices
// Dump simulation results
if (logNormal()) {
*wrklog << gammalib::parformat("MC source photons", indent);
*wrklog << nphotons;
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
*wrklog << gammalib::parformat("MC source events", indent);
*wrklog << events->size();
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
}
} // endif: model was a sky model
} // endfor: looped over models
// Dump simulation results
if (logNormal()) {
*wrklog << gammalib::parformat("MC source events", indent);
*wrklog << events->size();
*wrklog << " (all source models)";
*wrklog << std::endl;
}
// Reset indentation
if (logNormal()) {
if (events->ebounds().size() > 1) {
indent--;
wrklog->indent(indent);
}
}
} // endfor: looped over all energy boundaries
// Reset indentation
if (logNormal()) {
if (events->gti().size() > 1) {
indent--;
wrklog->indent(indent);
}
}
} // endfor: looped over all time intervals
// Reset indentation
wrklog->indent(0);
} // endif: observation pointer was valid
// Return
return;
}
/***********************************************************************//**
* @brief Simulate event data
*
* This method runs the simulation. Results are not saved by this method.
* Invoke "save" to save the results.
***************************************************************************/
void ctobssim::run(void)
{
// Switch screen logging on in debug mode
if (logDebug()) {
log.cout(true);
}
// Get parameters
get_parameters();
// Write input parameters into logger
if (logTerse()) {
log_parameters();
log << std::endl;
}
// Special mode: if read ahead is specified we know that we called
// the execute() method, hence files are saved immediately and event
// lists are disposed afterwards.
if (read_ahead()) {
m_save_and_dispose = true;
}
// Determine the number of valid CTA observations, set energy dispersion flag
// for all CTA observations and save old values in save_edisp vector
int n_observations = 0;
std::vector<bool> save_edisp;
save_edisp.assign(m_obs.size(), false);
for (int i = 0; i < m_obs.size(); ++i) {
GCTAObservation* obs = dynamic_cast<GCTAObservation*>(m_obs[i]);
if (obs != NULL) {
save_edisp[i] = obs->response()->apply_edisp();
obs->response()->apply_edisp(m_apply_edisp);
n_observations++;
}
}
// If more than a single observation has been handled then make sure that
// an XML file will be used for storage
if (n_observations > 1) {
m_use_xml = true;
}
// Write execution mode into logger
if (logTerse()) {
log << std::endl;
log.header1("Execution mode");
log << gammalib::parformat("Event list management");
if (m_save_and_dispose) {
log << "Save and dispose (reduces memory needs)" << std::endl;
}
else {
log << "Keep events in memory" << std::endl;
}
log << gammalib::parformat("Output format");
if (m_use_xml) {
log << "Write Observation Definition XML file" << std::endl;
}
else {
log << "Write single event list FITS file" << std::endl;
}
}
// Write seed values into logger
if (logTerse()) {
log << std::endl;
log.header1("Seed values");
for (int i = 0; i < m_rans.size(); ++i) {
log << gammalib::parformat("Seed "+gammalib::str(i));
log << gammalib::str(m_rans[i].seed()) << std::endl;
}
}
// Write observation(s) into logger
if (logTerse()) {
log << std::endl;
if (m_obs.size() > 1) {
log.header1("Observations");
}
else {
log.header1("Observation");
}
log << m_obs << std::endl;
}
// Write header
if (logTerse()) {
log << std::endl;
if (m_obs.size() > 1) {
log.header1("Simulate observations");
}
else {
log.header1("Simulate observation");
}
}
// From here on the code can be parallelized if OpenMP support
// is enabled. The code in the following block corresponds to the
// code that will be executed in each thread
#pragma omp parallel
{
// Each thread will have it's own logger to avoid conflicts
GLog wrklog;
if (logDebug()) {
wrklog.cout(true);
}
// Allocate and initialize copies for multi-threading
GModels models(m_obs.models());
// Copy configuration from application logger to thread logger
wrklog.date(log.date());
wrklog.name(log.name());
// Set a big value to avoid flushing
wrklog.max_size(10000000);
// Loop over all observation in the container. If OpenMP support
// is enabled, this loop will be parallelized.
#pragma omp for
for (int i = 0; i < m_obs.size(); ++i) {
// Get pointer on CTA observation
GCTAObservation* obs = dynamic_cast<GCTAObservation*>(m_obs[i]);
// Continue only if observation is a CTA observation
if (obs != NULL) {
// Write header for observation
if (logTerse()) {
if (obs->name().length() > 1) {
wrklog.header3("Observation "+obs->name());
}
else {
wrklog.header3("Observation");
}
}
// Work on a clone of the CTA observation. This makes sure that
// any memory allocated for computing (for example a response
// cache) is properly de-allocated on exit of this run
GCTAObservation obs_clone = *obs;
// Save number of events before entering simulation
int events_before = obs_clone.events()->size();
// Simulate source events
simulate_source(&obs_clone, models, m_rans[i], &wrklog);
// Simulate source events
simulate_background(&obs_clone, models, m_rans[i], &wrklog);
// Dump simulation results
if (logNormal()) {
wrklog << gammalib::parformat("MC events");
wrklog << obs_clone.events()->size() - events_before;
wrklog << " (all models)";
wrklog << std::endl;
}
// Append the event list to the original observation
obs->events(*(obs_clone.events()));
// If requested, event lists are saved immediately
if (m_save_and_dispose) {
// Set event output file name. If multiple observations are
// handled, build the filename from prefix and observation
// index. Otherwise use the outfile parameter.
std::string outfile;
if (m_use_xml) {
m_prefix = (*this)["prefix"].string();
outfile = m_prefix + gammalib::str(i) + ".fits";
}
else {
outfile = (*this)["outevents"].filename();
}
// Store output file name in original observation
obs->eventfile(outfile);
// Save observation into FITS file. This is a critical zone
// to avoid multiple threads writing simultaneously
#pragma omp critical
{
obs_clone.save(outfile, clobber());
}
// Dispose events
obs->dispose_events();
}
// ... otherwise append the event list to the original observation
/*
else {
obs->events(*(obs_clone.events()));
}
*/
} // endif: CTA observation found
} // endfor: looped over observations
// At the end, the content of the thread logger is added to
// the application logger
#pragma omp critical (log)
{
log << wrklog;
}
} // end pragma omp parallel
// Restore energy dispersion flag for all CTA observations
for (int i = 0; i < m_obs.size(); ++i) {
GCTAObservation* obs = dynamic_cast<GCTAObservation*>(m_obs[i]);
if (obs != NULL) {
obs->response()->apply_edisp(save_edisp[i]);
}
}
// Return
return;
}
/***********************************************************************//**
* @brief Simulate background events from model
*
* @param[in] obs Pointer on CTA observation.
* @param[in] models Models.
* @param[in] ran Random number generator.
* @param[in] wrklog Pointer to logger.
*
* Simulate background events from models. The events are stored as event
* list in the observation.
*
* This method does nothing if the observation pointer is NULL.
***************************************************************************/
void ctobssim::simulate_background(GCTAObservation* obs,
const GModels& models,
GRan& ran,
GLog* wrklog)
{
// Continue only if observation pointer is valid
if (obs != NULL) {
// If no logger is specified then use the default logger
if (wrklog == NULL) {
wrklog = &log;
}
// Get pointer on event list (circumvent const correctness)
GCTAEventList* events =
static_cast<GCTAEventList*>(const_cast<GEvents*>(obs->events()));
// Loop over all models
for (int i = 0; i < models.size(); ++i) {
// Get data model (NULL if not a data model)
const GModelData* model =
dynamic_cast<const GModelData*>(models[i]);
// If we have a data model that applies to the present observation
// then simulate events
if (model != NULL &&
model->is_valid(obs->instrument(), obs->id())) {
// Get simulated CTA event list. Note that this method
// includes the deadtime correction.
GCTAEventList* list =
dynamic_cast<GCTAEventList*>(model->mc(*obs, ran));
// Continue only if we got a CTA event list
if (list != NULL) {
// Reserves space for events
events->reserve(list->size()+events->size());
// Append events
for (int k = 0; k < list->size(); k++) {
// Get event pointer
GCTAEventAtom* event = (*list)[k];
// Use event only if it falls within ROI
if (events->roi().contains(*event)) {
// Set event identifier
event->event_id(m_event_id);
m_event_id++;
// Append event
events->append(*event);
} // endif: event was within ROI
} // endfor: looped over all events
// Dump simulation results
if (logNormal()) {
*wrklog << gammalib::parformat("MC background events");
*wrklog << list->size() << std::endl;
}
// Free event list
delete list;
} // endif: we had a CTA event list
} // endif: model was valid
} // endfor: looped over all models
} // endif: observation pointer was valid
// Return
return;
}
/***********************************************************************//**
* @brief Simulate source events from photon list
*
* @param[in] obs Pointer on CTA observation.
* @param[in] models Model list.
* @param[in] ran Random number generator.
* @param[in] wrklog Pointer to logger.
*
* Simulate source events from a photon list for a given CTA observation.
* The events are stored in as event list in the observation.
*
* This method does nothing if the observation pointer is NULL. It also
* verifies if the observation has a valid pointing and response.
***************************************************************************/
void ctobssim::simulate_source(GCTAObservation* obs, const GModels& models,
GRan& ran, GLog* wrklog)
{
// Continue only if observation pointer is valid
if (obs != NULL) {
// If no logger is specified then use the default logger
if (wrklog == NULL) {
wrklog = &log;
}
// Get pointer on CTA response. Throw an exception if the response
// is not defined.
const GCTAResponse& rsp = obs->response();
// Make sure that the observation holds a CTA event list. If this
// is not the case then allocate and attach a CTA event list now.
if (dynamic_cast<const GCTAEventList*>(obs->events()) == NULL) {
set_list(obs);
}
// Get pointer on event list (circumvent const correctness)
GCTAEventList* events = static_cast<GCTAEventList*>(const_cast<GEvents*>(obs->events()));
// Extract simulation region.
GSkyDir dir = events->roi().centre().dir();
double rad = events->roi().radius() + g_roi_margin;
// Dump simulation cone information
if (logNormal()) {
*wrklog << gammalib::parformat("Simulation area");
*wrklog << m_area << " cm2" << std::endl;
*wrklog << gammalib::parformat("Simulation cone");
*wrklog << "RA=" << dir.ra_deg() << " deg";
*wrklog << ", Dec=" << dir.dec_deg() << " deg";
*wrklog << ", r=" << rad << " deg" << std::endl;
}
// Initialise indentation for logging
int indent = 0;
// Loop over all Good Time Intervals
for (int it = 0; it < events->gti().size(); ++it) {
// Extract time interval
GTime tmin = events->gti().tstart(it);
GTime tmax = events->gti().tstop(it);
// Dump time interval
if (logNormal()) {
if (events->gti().size() > 1) {
indent++;
wrklog->indent(indent);
}
*wrklog << gammalib::parformat("Time interval", indent);
*wrklog << tmin.convert(m_cta_ref);
*wrklog << " - ";
*wrklog << tmax.convert(m_cta_ref);
*wrklog << " s" << std::endl;
}
// Loop over all energy boundaries
for (int ie = 0; ie < events->ebounds().size(); ++ie) {
// Extract energy boundaries
GEnergy emin = events->ebounds().emin(ie);
GEnergy emax = events->ebounds().emax(ie);
// Dump energy range
if (logNormal()) {
if (events->ebounds().size() > 1) {
indent++;
wrklog->indent(indent);
}
*wrklog << gammalib::parformat("Energy range", indent);
*wrklog << emin << " - " << emax << std::endl;
}
// Loop over all sky models
for (int i = 0; i < models.size(); ++i) {
// Get sky model (NULL if not a sky model)
const GModelSky* model =
dynamic_cast<const GModelSky*>(models[i]);
// If we have a sky model that applies to the present
// observation then simulate events
if (model != NULL &&
model->is_valid(obs->instrument(), obs->id())) {
// Determine duration of a time slice by limiting the
// number of simulated photons to m_max_photons.
// The photon rate is estimated from the model flux
// and used to set the duration of the time slice.
double flux = model->spectral()->flux(emin, emax);
double rate = flux * m_area;
double duration = 1800.0; // default: 1800 sec
if (rate > 0.0) {
duration = m_max_photons / rate;
if (duration < 1.0) { // not <1 sec
duration = 1.0;
}
else if (duration > 180000.0) { // not >50 hr
duration = 180000.0;
}
}
GTime tslice(duration, "sec");
// To reduce memory requirements we split long time
// intervals into several slices.
GTime tstart = tmin;
GTime tstop = tstart + tslice;
// Initialise cumulative photon counters
int nphotons = 0;
// Loop over time slices
while (tstart < tmax) {
// Make sure that tstop <= tmax
if (tstop > tmax) {
tstop = tmax;
}
// Dump time slice
if (logExplicit()) {
if (tmax - tmin > tslice) {
indent++;
wrklog->indent(indent);
}
*wrklog << gammalib::parformat("Time slice", indent);
*wrklog << tstart.convert(m_cta_ref);
*wrklog << " - ";
*wrklog << tstop.convert(m_cta_ref);
*wrklog << " s" << std::endl;
}
// Get photons
GPhotons photons = model->mc(m_area, dir, rad,
emin, emax,
tstart, tstop, ran);
// Dump number of simulated photons
if (logExplicit()) {
*wrklog << gammalib::parformat("MC source photons/slice", indent);
*wrklog << photons.size();
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
}
// Simulate events from photons
for (int i = 0; i < photons.size(); ++i) {
// Increment photon counter
nphotons++;
// Simulate event. Note that this method
// includes the deadtime correction.
GCTAEventAtom* event = rsp.mc(m_area,
photons[i],
*obs,
ran);
if (event != NULL) {
// Use event only if it falls within ROI
if (events->roi().contains(*event)) {
event->event_id(m_event_id);
events->append(*event);
m_event_id++;
}
delete event;
}
} // endfor: looped over events
// Go to next time slice
tstart = tstop;
tstop = tstart + tslice;
// Reset indentation
if (logExplicit()) {
if (tmax - tmin > tslice) {
indent--;
wrklog->indent(indent);
}
}
} // endwhile: looped over time slices
// Dump simulation results
if (logNormal()) {
*wrklog << gammalib::parformat("MC source photons", indent);
*wrklog << nphotons;
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
*wrklog << gammalib::parformat("MC source events", indent);
*wrklog << events->size();
if (model->name().length() > 0) {
*wrklog << " [" << model->name() << "]";
}
*wrklog << std::endl;
}
} // endif: model was a sky model
} // endfor: looped over models
// Dump simulation results
if (logNormal()) {
*wrklog << gammalib::parformat("MC source events", indent);
*wrklog << events->size();
*wrklog << " (all source models)";
*wrklog << std::endl;
}
// Reset indentation
if (logNormal()) {
if (events->ebounds().size() > 1) {
indent--;
wrklog->indent(indent);
}
}
} // endfor: looped over all energy boundaries
// Reset indentation
if (logNormal()) {
if (events->gti().size() > 1) {
indent--;
wrklog->indent(indent);
}
}
} // endfor: looped over all time intervals
// Reset indentation
wrklog->indent(0);
} // endif: observation pointer was valid
// Return
return;
}
/***********************************************************************//**
* @brief Simulate event data
*
* This method runs the simulation. Results are not saved by this method.
* Invoke "save" to save the results.
***************************************************************************/
void ctobssim::run(void)
{
// Switch screen logging on in debug mode
if (logDebug()) {
log.cout(true);
}
// Get parameters
get_parameters();
// Write input parameters into logger
if (logTerse()) {
log_parameters();
log << std::endl;
}
// Write seed values into logger
if (logTerse()) {
log << std::endl;
log.header1("Seed values");
for (int i = 0; i < m_rans.size(); ++i) {
log << gammalib::parformat("Seed "+gammalib::str(i));
log << gammalib::str(m_rans[i].seed()) << std::endl;
}
}
// Write observation(s) into logger
if (logTerse()) {
log << std::endl;
if (m_obs.size() > 1) {
log.header1("Observations");
}
else {
log.header1("Observation");
}
log << m_obs << std::endl;
}
// Write header
if (logTerse()) {
log << std::endl;
if (m_obs.size() > 1) {
log.header1("Simulate observations");
}
else {
log.header1("Simulate observation");
}
}
// Initialise counters
int n_observations = 0;
// From here on the code can be parallelized if OpenMP support
// is enabled. The code in the following block corresponds to the
// code that will be executed in each thread
#pragma omp parallel
{
// Each thread will have it's own logger to avoid conflicts
GLog wrklog;
if (logDebug()) {
wrklog.cout(true);
}
// Copy configuration from application logger to thread logger
wrklog.date(log.date());
wrklog.name(log.name());
// Set a big value to avoid flushing
wrklog.max_size(10000000);
// Loop over all observation in the container. If OpenMP support
// is enabled, this looped will be parallelized.
#pragma omp for
for (int i = 0; i < m_obs.size(); ++i) {
// Get CTA observation
GCTAObservation* obs = dynamic_cast<GCTAObservation*>(m_obs[i]);
// Continue only if observation is a CTA observation
if (obs != NULL) {
// Write header for observation
if (logTerse()) {
if (obs->name().length() > 1) {
wrklog.header3("Observation "+obs->name());
}
else {
wrklog.header3("Observation");
}
}
// Increment counter
n_observations++;
// Save number of events before entering simulation
int events_before = obs->events()->size();
// Simulate source events
simulate_source(obs, m_obs.models(), m_rans[i], &wrklog);
// Simulate source events
simulate_background(obs, m_obs.models(), m_rans[i], &wrklog);
// Dump simulation results
if (logNormal()) {
wrklog << gammalib::parformat("MC events");
wrklog << obs->events()->size() - events_before;
wrklog << " (all models)";
wrklog << std::endl;
}
} // endif: CTA observation found
} // endfor: looped over observations
// At the end, the content of the thread logger is added to
// the application logger
#pragma omp critical (log)
{
log << wrklog;
}
} // end pragma omp parallel
// If more than a single observation has been handled then make sure that
// an XML file will be used for storage
if (n_observations > 1) {
m_use_xml = true;
}
// Return
return;
}
T& Random< T, G, I, F >::logNormal(T &t, F m, F s) {
return const_cast< T& >(logNormal(const_cast< const T& >(t), m, s));
}
// Returns 0 iff no measurement taken, 1 if a valid measurement was found, -1 if observed to be empty
template <typename PointT, typename NormalT> int
cpu_tsdf::TSDFVolumeOctree::updateVoxel (
const cpu_tsdf::OctreeNode::Ptr &voxel,
const pcl::PointCloud<PointT> &cloud,
const pcl::PointCloud<NormalT> &normals,
const Eigen::Affine3f &trans_inv)
{
// assert (!voxel->hasChildren ());
if (voxel->hasChildren ())
{
std::vector<OctreeNode::Ptr>& children = voxel->getChildren ();
std::vector<bool> is_empty (children.size ());
//#pragma omp parallel for
for (size_t i = 0; i < children.size (); i++)
{
is_empty[i] = updateVoxel (children[i], cloud, normals, trans_inv) < 0;
}
bool all_are_empty = true;
for (size_t i = 0; i < is_empty.size (); i++)
all_are_empty &= is_empty[i];
if (all_are_empty)
{
children.clear (); // Remove empty voxels
}
else
{
return (1); // Say I am not empty
}
}
pcl::PointXYZ v_g_orig;
voxel->getCenter (v_g_orig.x, v_g_orig.y, v_g_orig.z);
pcl::PointXYZ v_g = pcl::transformPoint (v_g_orig, trans_inv);
if (v_g.z < min_sensor_dist_ || v_g.z > max_sensor_dist_)
return (0); // No observation
int u, v;
if (!reprojectPoint (v_g, u, v))
return (0); // No observation
const PointT &pt = cloud (u,v);
if (pcl_isnan (pt.z))
return (0); // No observation
// if (pt.z >= max_sensor_dist_) // We want to let empty points be empty, even at noisy readings
// return (0);
float d;
float w;
voxel->getData (d, w);
float d_new = (pt.z - v_g.z);
// Check if we can split
if (fabs (d_new) < 3*voxel->getMaxSize ()/4.)// || (fabs (d_new) < max_dist_))
{
float xsize, ysize, zsize;
voxel->getSize (xsize, ysize, zsize);
if (xsize > xsize_ / xres_ && ysize > ysize_ / yres_ && zsize > zsize_ / zres_)
{
std::vector<OctreeNode::Ptr>& children = voxel->split ();
std::vector<bool> is_empty (children.size ());
//#pragma omp parallel for
for (size_t i = 0; i < children.size (); i++)
{
// TODO Make the weight and distance match the parent's?
// children[i]->setData (d, w);
is_empty[i] = updateVoxel (children[i], cloud, normals, trans_inv) < 0;
}
bool all_are_empty = true;
for (size_t i = 0; i < is_empty.size (); i++)
all_are_empty &= is_empty[i];
if (all_are_empty)
{
children.clear (); // Remove empty voxel
}
else
{
return (1); // Say I am not empty
}
}
}
if (d_new > max_dist_pos_)
{
d_new = max_dist_pos_;
}
else if (d_new < -max_dist_neg_)
{
return (0); // No observation, effectively
}
// Normalize s.t. -1 = unobserved
d_new /= max_dist_neg_;
float w_new = 1;
if (weight_by_depth_)
w_new *= (1 - std::min(pt.z / 10., 1.)); // Scales s.t. at 10m it's worthless
if (weight_by_variance_ && voxel->nsample_ > 5)
w_new *= std::exp (logNormal (d_new, voxel->d_, voxel->getVariance ()));
if (integrate_color_)
voxel->addObservation (d_new, w_new, max_weight_, pt.r, pt.g, pt.b);
else
voxel->addObservation (d_new, w_new, max_weight_);
if (voxel->d_ < -0.99)
return (0);
else if (voxel->d_ < 0.99* max_dist_pos_ / max_dist_neg_) //if I am not empty
return (1); // Say so
else
return (-1); // Otherwise say I'm empty
}
void Gui::SetArm(const char* text)
{
//Initialize a surface used to hide a part of the screen wich is used later
SDL_Surface* hide = NULL;
hide=LoadImage("Images/hide.png");
//The variables that the window is going to get
double mean =0;//the mean of the arm
double variance =0;//its variance
char armType ='A';//its type
//Initializing the texts
Texts arm(0,150,_font,text,_textColor);
Texts instructions(0,250,_font2,"Choose a type of arm then click in the boxes and type the parameters",_textColor);
//Initializing the buttons
//Ok button to skip to the next window
Buttons ok(361,500, "Images/ok1.png", "Images/ok2.png","Images/ok3.png");
//Type zones for the mean and the variance
TypeZone meanT(300,400,_font2,"Mean",_textColor);
TypeZone varianceT(600,400,_font2,"Variance",_textColor);
//Radiobuttons to choose the type of arm (exponential, uniform real, uniform int, poisson, logNormal)
RadioButtons exp(100,300,"Exponential",_font2,_textColor);
RadioButtons unifr(exp.GetBox().x+exp.GetBox().w+20,300,"Uniform real",_font2,_textColor);
RadioButtons unifi(unifr.GetBox().x+unifr.GetBox().w+20,300,"Uniform int",_font2,_textColor);
RadioButtons poisson(unifi.GetBox().x+unifi.GetBox().w+20,300,"Poisson",_font2,_textColor);
RadioButtons logNormal(poisson.GetBox().x+poisson.GetBox().w+20,300,"Log-normal",_font2,_textColor);
//Calculate the x for centering them (width of the screen minus the sum the width of the buttons)
int xCentered = ((*(_screen.GetScreen())).clip_rect.w-exp.GetBox().w-unifr.GetBox().w-unifi.GetBox().w-poisson.GetBox().w-logNormal.GetBox().w-80)/2;
//Relocate the buttons
exp.SetPosition(xCentered,exp.GetBox().y);
unifr.SetPosition(exp.GetBox().x+exp.GetBox().w+20,unifr.GetBox().y);
unifi.SetPosition(unifr.GetBox().x+unifr.GetBox().w+20,unifi.GetBox().y);
poisson.SetPosition(unifi.GetBox().x+unifi.GetBox().w+20,poisson.GetBox().y);
logNormal.SetPosition(poisson.GetBox().x+poisson.GetBox().w+20,logNormal.GetBox().y);
//Display them all
arm.DisplayCentered(_screen);
instructions.DisplayCentered(_screen);
//meanT.Display(_screen);
ok.Show(_screen);
exp.Show(_screen);
unifr.Show(_screen);
unifi.Show(_screen);
poisson.Show(_screen);
logNormal.Show(_screen);
meanT.DisplayLeft(_screen,mean,_font2,_textColor);
varianceT.DisplayRight(_screen,mean,_font2,_textColor);
//Initialize the event structure
SDL_Event event;
//Initialization of the loop
bool isChoiceCorrect= false;
bool skip=false;
while((skip==false)&&(_quit==false))
{ //While there's an event to handle
while( SDL_PollEvent( &event ) )
{
//the buttons react to the user's actions
ok.HandleEvents(event);
exp.HandleEvents(event);
unifr.HandleEvents(event);
unifi.HandleEvents(event);
poisson.HandleEvents(event);
logNormal.HandleEvents(event);
meanT.HandleEvents(event,mean);
//For some button we just need the mean to set the distribution so in this case we hide the variance
if((exp.IsActive()==false)&&(poisson.IsActive()==false))
{
varianceT.HandleEvents(event,variance);
}
//we check if one option was chosen
isChoiceCorrect = (exp.IsActive()|| unifr.IsActive()||unifi.IsActive()||poisson.IsActive()||logNormal.IsActive());
//If the user clicks on ok and made a choice
if((ok.HandleEvents(event)==false)&&(isChoiceCorrect))
{
//skip to the next window
skip=true;
}
//If he clicks on ok and hasn't made a choice then change color of the text
if((ok.HandleEvents(event)==false)&&(isChoiceCorrect==false))
{
SDL_Color red={240,0,0};
exp.SetColor(red);
unifr.SetColor(red);
unifi.SetColor(red);
poisson.SetColor(red);
logNormal.SetColor(red);
}
//If the user has Xed out the window
if( event.type == SDL_QUIT )
{
//Quit the program
_quit = true;
}
}
//Display all
ok.Show(_screen);
exp.Show(_screen);
unifr.Show(_screen);
unifi.Show(_screen);
poisson.Show(_screen);
logNormal.Show(_screen);
meanT.DisplayLeft(_screen,mean, _font2,_textColor);
//For some button we just need the mean to set the distribution so in this case we hide the variance
if((exp.IsActive()==false)&&(poisson.IsActive()==false))
{
varianceT.DisplayRight(_screen,variance, _font2,_textColor);
}
else
{
ApplySurface(400,398,hide,_screen.GetScreen());
}
_screen.Display();
}
_screen.Clean("Images/background.png");
//Then we save the parameters in the Gui's attributes
//First we get the type of arm:
if(exp.IsActive()){armType='A';}
if(unifr.IsActive()){armType='B';}
if(unifi.IsActive()){armType='C';}
if(poisson.IsActive()){armType='D';}
if(logNormal.IsActive()){armType='E';}
std::vector<double> parameter;
//Then acoording to the type of arms we calculate the parameters required
switch(armType)
{
case 'A'://Exponential: we need the lambda
_choices.push_back('A');//we save the type in _choices
parameter.push_back(1.0/(mean*1.0));
_parameters.push_back(parameter);//and the parameters calculated using the mean and the variance in _parameters
break;
case 'B'://uniform real on [a,b] we need a and b
_choices.push_back('B');
parameter.push_back((2.0*mean-sqrt(12.0*variance))/2.0);
parameter.push_back((2.0*mean+sqrt(12.0*variance))/2.0);
_parameters.push_back(parameter);
break;
case 'C':
_choices.push_back('C');//uniform integer on [a,b] we need a and b
parameter.push_back((2.0*mean -sqrt(12.0*variance+1.0)+1)/2.0);
parameter.push_back((2.0*mean+sqrt(12.0*variance+1)-1)/2.0);
_parameters.push_back(parameter);
break;
case 'D': //poisson we just need the mu wich equal to the mean
_choices.push_back('D');
parameter.push_back(mean);
_parameters.push_back(parameter);
break;
default:
_choices.push_back('E'); //log-normal we need mu and sigma square
parameter.push_back(log(mean*1.0)-0.5*log(1.0+((variance*1.0)/(mean*mean*1.0))));
parameter.push_back((2.0*mean+sqrt(12.0*variance+1.0)-1.0)/2.0);
_parameters.push_back(parameter);
break;
}
}
