use of com.sri.ai.praise.core.representation.interfacebased.factor.core.expression.api.ExpressionVariable in project aic-praise by aic-sri-international.
the class ExpressionFactorTest method testMax.
@Test
public void testMax() {
Context context = new TrueContext(new CommonTheory()).extendWithSymbolsAndTypes("U", "Boolean", "V", "Boolean");
ExpressionFactor factorUV = new DefaultExpressionFactor(parse("if U then if V then 4 else 2 else 3"), context);
ExpressionVariable u = new DefaultExpressionVariable(parse("U"));
List<ExpressionVariable> variablesToMaxOut = new ArrayList<>();
variablesToMaxOut.add(u);
Factor maxFactor = factorUV.max(variablesToMaxOut);
assertEquals("if V then 4 else 3", maxFactor.toString());
}
use of com.sri.ai.praise.core.representation.interfacebased.factor.core.expression.api.ExpressionVariable in project aic-praise by aic-sri-international.
the class UsefulExpressionOperations method main.
public static void main(String[] args) {
Theory theory = new CommonTheory();
Context context = new TrueContext(theory);
// Only one child and one parent, 2 parameters (Param1 and Param2)
Expression child = parse("Child");
Expression parent = parse("Parent");
Expression param1 = parse("Param1");
Expression param2 = parse("Param2");
Expression param3 = parse("Param3");
context = context.extendWithSymbolsAndTypes("Child", "1..5", "Parent", "1..5", "Param1", "Real", "Param2", "Real", "Param3", "Real", "A", "Boolean");
// Old way: making parameters become constants
// Predicate<Expression> isUniquelyNamedConstantPredicate = context.getIsUniquelyNamedConstantPredicate();
// Predicate<Expression> newIsUniquelyNamedConstantPredicate = s -> s.equals(param1) || s.equals(param2) || s.equals(param3) || isUniquelyNamedConstantPredicate.apply(s);
// context = context.setIsUniquelyNamedConstantPredicate(newIsUniquelyNamedConstantPredicate);
println("My context:");
println(context.getSymbolsAndTypes());
// Expression E = parse("if Child < 5 then Param1 else Param2");
Expression E = parse("if Parent != 5 then Param1 else Param2");
// Expression E = parse("if Parent != 5 then if Child < 5 then Param1 else Param2 else Param3");
// Expression E = parse("if Parent != 5 then if Child < Parent then Param1 else Param2 else Param3");
println("\nE = " + E + "\n");
// Gives you <Child in 1..5>
childIndexExpressionsSet = getIndexExpressionsForIndicesInListAndTypesInRegistry(list(child), context);
parametersIndexExpressionsSet = getIndexExpressionsForIndicesInListAndTypesInRegistry(list(param1, param2, param3), context);
Expression F1 = new DefaultExistentiallyQuantifiedFormula(childIndexExpressionsSet, forAllParametersValues(Equality.make(E, param1)));
println("F1 = " + F1);
println(context.evaluate(F1) + "\n");
// Old way of computing families (taking the parameters as constants):
// Expression F1 = new DefaultExistentiallyQuantifiedFormula(childIndexExpressionsSet, Equality.make(E, param1));
// println("F1 = " + F1);
// println(context.evaluate(F1) + "\n");
Expression F2 = new DefaultExistentiallyQuantifiedFormula(childIndexExpressionsSet, forAllParametersValues(Equality.make(E, param2)));
println("F2 = " + F2);
println(context.evaluate(F2) + "\n");
Expression F1intersectsF2 = verifyEquivalenceAndGetIntersectionCondition(F1, F2, context);
println("F1intersectsF2 = " + F1intersectsF2);
println(context.evaluate(F1intersectsF2));
// Normalization for Parame1_1
Expression multiset = new DefaultIntensionalMultiSet(childIndexExpressionsSet, child, forAllParametersValues(Equality.make(E, param1)));
Expression cardinality = apply(CARDINALITY, multiset);
println("\nCardinality = " + cardinality);
Expression cardinalityResult = context.evaluate(cardinality);
println("N for normalizing Param1_1: " + cardinalityResult);
// Draft for the Java syntax when shattering the families
LinkedList<Integer> initialFamilies = Util.list(1, 2, 3, 4, 5);
List<Integer> finalFamilies = Util.list();
while (!initialFamilies.isEmpty()) {
int family1 = initialFamilies.removeFirst();
for (Iterator<Integer> it = initialFamilies.iterator(); it.hasNext(); ) {
int family2 = it.next();
if (family2 == 4) {
it.remove();
}
}
if (family1 == 3)
initialFamilies.add(7);
finalFamilies.add(family1);
}
println("\n" + finalFamilies);
// Testing syntax for context (used for method convertToAnExpressionBasedModelAfterLearning in ExpressionBayesianModel)
ExpressionVariable expressionVariable = new DefaultExpressionVariable(parse("A"));
println("\nexpressionVariable.toString() = " + expressionVariable.toString());
Type type = context.getTypeOfRegisteredSymbol(expressionVariable);
println("type.toString() = " + type.toString());
println("child.toStringe() = " + child.toString());
type = context.getTypeOfRegisteredSymbol(child);
println("type.toString() = " + type.toString());
// TODO: Below I let 2 comments about Expresso edge case problems, to be studied and fixed later:
// 1]
// Comparison that we would like to be false, Expresso problem with constants - to be seen later (TODO)
// context.evaluate(Equality.make(parse("Param1"), parse("1-Param1"))); // we would like to have "false" as result here but it gives error, that is why we have to use OneMinusParam1 as other parameter
// 2]
// Two Expressions that are equals, equality result should be true (from ExpressionBayesianModelTest, testChildParentModel4), but error with parent been canceled out, problem with Expresso - to be seen later
// also, TODO: see why it is not simplifying 1/Parent to 1/5 in learnedChild below
Expression expectedChild = parse("if Parent = 5 then 0.2 else if Child > Parent then (((5 - Parent) + 0) / (5 + 0)) / (5 - Parent) else ((Parent + 0) / (5 + 0)) / Parent");
Expression learnedChild = parse("if Parent < 5 then if Child > Parent then ((-Parent + 5) / ((-Parent + 5) + Parent)) / (-Parent + 5) else (Parent / ((-Parent + 5) + Parent)) / Parent else 1 / Parent");
// println(context.evaluate(Equality.make(expectedChild, learnedChild)));
// Problem when using "for all parameters in parametersValues" instead of handling them as constants - the problem was when adding "and (Parent != 5)" (family.condition) at the end of expression bellow
Expression expression = parse("(if Parent != 5 then if Child < 5 then Param1 else Param2 else Param3)");
println("\nexpression = " + expression);
multiset = new DefaultIntensionalMultiSet(childIndexExpressionsSet, child, forAllParametersValues(Equality.make(expression, param1)));
cardinality = apply(CARDINALITY, multiset);
Expression numberOfChildValues = cardinality;
println("numberOfChildValues = " + numberOfChildValues);
println(context.evaluate(numberOfChildValues));
}
use of com.sri.ai.praise.core.representation.interfacebased.factor.core.expression.api.ExpressionVariable in project aic-praise by aic-sri-international.
the class ExpressionBayesianNode method main.
public static void main(String[] args) {
Theory theory = new CommonTheory();
Context context = new TrueContext(theory);
// Only one child and one parent, 2 parameters (Param1 and Param2)
ExpressionVariable child = new DefaultExpressionVariable(parse("Child"));
ExpressionVariable parent = new DefaultExpressionVariable(parse("Parent"));
Expression param1 = parse("Param1");
Expression param2 = parse("Param2");
Expression param3 = parse("Param3");
context = context.extendWithSymbolsAndTypes("Child", "1..5", "Parent", "1..5", "Param1", "Real", "Param2", "Real", "Param3", "Real");
LinkedHashSet<Expression> parameters = Util.set(param1, param2);
parameters.add(param3);
// Expression E = parse("if Child < 5 then Param1 else Param2");
Expression E = parse("if Parent != 5 then Param1 else Param2");
// Expression E = parse("if Parent != 5 then if Child < 5 then Param1 else Param2 else Param3");
// Expression E = parse("if Parent != 5 then if Child < Parent then Param1 else Param2 else Param3"); // partial intersection
// Expression E = parse("if Child > 3 then Param1 else Param2");
println("E = " + E + "\n");
ExpressionBayesianNode parentNode = new ExpressionBayesianNode(E, context, parent, list(), parameters);
ExpressionBayesianNode childNode = new ExpressionBayesianNode(E, context, child, list(parent), parameters);
println("Families = " + childNode.getFamilies());
childNode.setInitialCountsForAllPossibleChildAndParentsAssignments();
// Incrementing from datapoints
LinkedList<Expression> childAndParentsValues = list(parse("1"), parse("1"));
int nIncrements = 0;
for (int i = 1; i <= nIncrements; i++) {
childNode.incrementCountForChildAndParentsAssignment(childAndParentsValues);
}
childNode.normalizeParameters();
println("\nnew E = " + childNode.getInnerExpression());
println("\nEnd of Program");
}
use of com.sri.ai.praise.core.representation.interfacebased.factor.core.expression.api.ExpressionVariable in project aic-praise by aic-sri-international.
the class ExpressionBayesianNode method replaceVariablesByTheirValuesInAnExpression.
private Expression replaceVariablesByTheirValuesInAnExpression(Expression originalExpression, List<ExpressionVariable> variables, List<Expression> variableValues) {
if (variables.size() != variableValues.size()) {
throw new Error("The list for variables and the one for their values must have the same size");
}
Expression newExpression = originalExpression;
ListIterator<ExpressionVariable> itVariable = variables.listIterator();
ListIterator<Expression> itValue = variableValues.listIterator();
while (itValue.hasNext() && itValue.hasNext()) {
ExpressionVariable variable = itVariable.next();
Expression variableValue = (Expression) itValue.next();
newExpression = newExpression.replaceAllOccurrences(variable, variableValue, context);
}
return newExpression;
}
use of com.sri.ai.praise.core.representation.interfacebased.factor.core.expression.api.ExpressionVariable in project aic-praise by aic-sri-international.
the class ProceduralAttachmentExpressionFactor method makeBooleanCondition.
private Expression makeBooleanCondition(Symbol valueExpression) {
boolean booleanValue = valueExpression.booleanValue();
Expression booleanCondition;
if (booleanValue) {
booleanCondition = (ExpressionVariable) proceduralAttachment.getVariable();
} else {
booleanCondition = Not.make((ExpressionVariable) proceduralAttachment.getVariable());
}
return booleanCondition;
}
Aggregations