/**
* Modify the current search temperature (defaults to 1.0). Higher temperatures increase the
* likelihood of a bad (i.e. high MML cost) model being accepted.
*/
public void setTemperature(double temperature) {
if (fixedTemperature) {
throw new RuntimeException("Temperature value unchangable");
}
this.temperature = temperature;
caseInfo.temperature = temperature;
updateMutationOperators(arcProb, temperature);
}
/**
* Modify the current arc probability. This effects structureCost and the TOM mutation operators
* (skeletalChange, temporalChange, doubleSkeletalChange, parentSwapChange)
*/
public void setArcProb(double arcProb) {
if (fixedArcProb) {
throw new RuntimeException("ArcProb value unchangable");
}
this.arcProb = arcProb;
caseInfo.arcProb = arcProb;
updateMutationOperators(arcProb, temperature);
}
/** Create new Mutation operators */
protected void updateMutationOperators(double arcProb, double temperature) {
skeletalChange = new SkeletalChange(rand, arcProb, caseInfo, temperature);
temporalChange = new TemporalChange(rand, arcProb, caseInfo, temperature);
doubleSkeletalChange = new DoubleSkeletalChange(rand, arcProb, caseInfo, temperature);
parentSwapChange = new ParentSwapChange(rand, arcProb, caseInfo, temperature);
// tomCoster = new TOMCoster.UniformTOMCoster( arcProb, caseInfo );
tomCoster.setArcProb(arcProb);
caseInfo.tomCoster = tomCoster;
}
/** Setter for TOMCoster. */
public void setTOMCoster(TOMCoster tc) {
this.tomCoster = tc;
caseInfo.tomCoster = tomCoster;
}
/**
* Set an option by name to a given value. Some options are search specific. <br>
* Return false if option name is unknown
*
* <p>General options include: <br>
* <b>arcProb</b> -- Fix the probability of arc existance at a value <br>
* <b>temperature</b> -- Fix temperature at a set value <br>
* <b>currentTOM</b> -- Set initial TOM to a given value <br>
* <b>clean</b> -- Should model cleaning be used? <br>
* <b>searchFactor</b>-- Multiplier to search/sample time. Default is 1.0. <br>
*
* <p>Metropolis only options <br>
* <b>joinDAGs</b> -- Join DAGs to form SECs. (default == true)<br>
* <b>joinSECs</b> -- Join SECs to form MMLECs. (defalut == true) <br>
* <b>allowMergeToModelWithMoreArcs</b> -- When joining SECs to MMLECs, allow the representative
* SEC to have more arcs than SEC it is being joined too. (default == false) <br>
* <b>sortTOMsBy</b> -- "weight"|"mml", What metric should we use to rank TOMs within a SEC?
* Default == "weight" <br>
* <b>regression</b> -- Sets options to the values used in oldCamml. Also makes an attempt to
* ensure random number generators line up, etc. Only useful for regressiont testing. <br>
* <b>TOMPrior</b> -- Use expert ellicited prior over network. String passed as option reflects
* the prior specified. For details see {@link ExpertElicitedTOMCoster} <b>maxNumSECs</b> --
* Maximum number of SECs retained post metropolis sampling. <b>minTotalPosterior</b> -- Minimal
* posterior retained post metropolis sampling. If more than 'maxSECs' SECs are required, this
* condition is ignored. <b>useNetica</b> -- Return BNetNetica instead of BNetStochastic models.
*/
public boolean setOption(final String option, Value v) {
if (option.equals("arcProb")) {
setArcProb(((Value.Scalar) v).getContinuous());
fixedArcProb = true;
System.out.println("Setting arcProb = " + v);
} else if (option.equals("temperature")) {
setTemperature(((Value.Scalar) v).getContinuous());
fixedTemperature = true;
System.out.println("Setting temperature = " + v);
} else if (option.equals("currentTOM")) {
setTOMStructure(tom, (Value.Vector) v);
} else if (option.equals("clean")) {
boolean clean = (((Value.Discrete) v).getDiscrete() == 0);
if (clean == false) {
caseInfo.tomCleaner = TOMCleaner.NoCleanTOMCleaner.tomCleaner;
}
System.out.println("Setting arc cleaning: " + clean);
} else if (option.equals("joinDAGs")) {
caseInfo.joinDAGs = (((Value.Discrete) v).getDiscrete() == 0);
System.out.println("Joining DAGs to form SECs: " + caseInfo.joinDAGs);
} else if (option.equals("joinSECs")) {
caseInfo.joinSECs = (((Value.Discrete) v).getDiscrete() == 0);
System.out.println("Joining SECs by KL distance: " + caseInfo.joinSECs);
} else if (option.equals("allowMergeToModelWithMoreArcs")) {
caseInfo.allowMergeToModelWithMoreArcs = (((Value.Discrete) v).getDiscrete() == 0);
System.out.println(
"Allow merge to model with more arcs: " + caseInfo.allowMergeToModelWithMoreArcs);
} else if (option.equals("sortTOMSBy")) {
String s = ((Value.Str) v).getString();
if (s.equals("weight")) {
caseInfo.tomComparator = SEC.tomWeightComparator;
} else if (s.equals("MML")) {
caseInfo.tomComparator = SEC.tomMMLComparator;
} else {
s = "Unknown option. Ignoring";
}
System.out.println("Sorting TOMs by : " + s);
} else if (option.equals("regression")) {
caseInfo.regression = (((Value.Discrete) v).getDiscrete() == 0);
System.out.println("Setting regression: " + caseInfo.regression);
} else if (option.equals("TOMCoster")) {
setTOMCoster((TOMCoster) ((Value.Obj) v).getObj());
System.out.println("Setting TOMCoster: " + tomCoster);
} else if (option.equals("TOMPrior")) {
String x = ((Value.Str) v).getString();
setTOMCoster(new ExpertElicitedTOMCoster(arcProb, new StringReader(x), tom.data));
System.out.println("Setting TOMCoster: " + tomCoster);
} else if (option.equals("searchFactor")) {
double d = ((Value.Scalar) v).getContinuous();
caseInfo.searchFactor = d;
} else if (option.equals("maxNumSECs")) {
int x = ((Value.Scalar) v).getDiscrete();
caseInfo.maxNumSECs = x;
} else if (option.equals("minTotalPosterior")) {
double d = ((Value.Scalar) v).getContinuous();
caseInfo.minTotalPosterior = d;
} else if (option.equals("useNetica")) {
caseInfo.useNetica = (((Value.Discrete) v).getDiscrete() == 0);
if (caseInfo.useNetica) {
caseInfo.bNet = new BNetNetica(caseInfo.bNet.getDataType());
} else {
caseInfo.bNet = new BNetStochastic(caseInfo.bNet.getDataType());
}
System.out.println("Using netica lib for inference: " + caseInfo.useNetica);
} else if (option.equals("printArcWeights")) {
caseInfo.printArcWeights = (((Value.Discrete) v).getDiscrete() != 0);
caseInfo.updateArcWeights = caseInfo.printArcWeights;
System.out.println("Printing Arc Weights: " + caseInfo.useNetica);
} else if (option.equals("cklJoinType")) {
caseInfo.cklJoinType = ((Value.Discrete) v).getDiscrete();
if (caseInfo.cklJoinType != 0 && caseInfo.cklJoinType != 3) {
throw new RuntimeException("Unknown join type. Should be 0 or 3");
}
System.out.println("Setting Model join type to CKL" + caseInfo.cklJoinType);
// caseInfo.joinDAGs = false;
// System.out.println( "Joining DAGs to form SECs: " + caseInfo.joinDAGs );
} else { // return false if an invalid option is passed.
return false;
}
return true;
}
