Examples with CompoundTheory com.sri.ai.grinder.theory.compound.CompoundTheory used on opensource projects

Example 31 with CompoundTheory

use of com.sri.ai.grinder.theory.compound.CompoundTheory in project aic-expresso by aic-sri-international.

the class IntensionalSetConditionSimplifierTest method setUp.

@Before
public void setUp() {
    context = new TrueContext(new CompoundTheory(new DifferenceArithmeticTheory(false, false), new TupleTheory()));
    IntegerInterval nType = new IntegerInterval(1, 10);
    context = (Context) GrinderUtil.extendRegistryWith(map("N", nType.toString()), Arrays.asList(nType), context);
    simplifier = new IntensionalSetConditionSimplifier();
}

Example 32 with CompoundTheory

use of com.sri.ai.grinder.theory.compound.CompoundTheory in project aic-expresso by aic-sri-international.

the class DistributeIntersectionOverUnionSimplifierTest method setUp.

@Before
public void setUp() {
    context = new TrueContext(new CompoundTheory(new DifferenceArithmeticTheory(false, false), new TupleTheory()));
    IntegerInterval intType = new IntegerInterval(1, 10);
    context = (Context) GrinderUtil.extendRegistryWith(map("M", intType.toString(), "N", intType.toString()), Arrays.asList(intType), context);
    simplifier = new DistributeIntersectionOverUnionSimplifier();
}

Example 33 with CompoundTheory

use of com.sri.ai.grinder.theory.compound.CompoundTheory in project aic-expresso by aic-sri-international.

the class Tests method main.

public static void main(String[] args) {
    // Theory initialization
    Theory theory = new CompoundTheory(new EqualityTheory(false, true), new DifferenceArithmeticTheory(false, false), new LinearRealArithmeticTheory(false, false), new TupleTheory(), new PropositionalTheory());
    Context context = new TrueContext(theory);
    context = context.extendWithSymbolsAndTypes("A", "Boolean");
    Model m;
    String modelName;
    modelName = "Ising Model";
    m = new Model(IsingModel(3, 2, context, parse("Boolean")), theory, true);
    testFunction(modelName, m, true);
    // modelName = "Line Model";
    // m = new Model(lineModel(10, context, parse("Boolean")),theory, true);
    // 
    // testFunction(modelName, m,true);
    // 
    // modelName = "Binary Tree Model";
    // m = new Model(nTreeModel(4, 2, context, parse("Boolean")),theory, true);
    // 
    // testFunction(modelName, m,true);
    // 
    // modelName = "Random Model";
    // m = new Model(ModelGenerator.randomModel(8, 10, context, parse("Boolean")),theory, true);
    // 
    // testFunction(modelName, m,true);
    modelName = "Ising Model";
    List<List<TupleOfData>> listOdModelsToPrintInFile = new ArrayList<>();
    // m = new Model(IsingModel(20, 4, context, parse("Boolean")),theory, true);
    // List<InferenceResult> IsingModel2X2 = testing("IsingModel",m,2,2);
    // listOdModelsToPrintInFile.add(IsingModel2X2);
    // println("ok");
    // 
    // m = new Model(IsingModel(3, 3, context, parse("Boolean")),theory, true);
    // List<InferenceResult> IsingModel3X3 = testing("IsingModel",m,3,3);
    // listOdModelsToPrintInFile.add(IsingModel3X3);
    // println("ok");
    // 
    // m = new Model(IsingModel(3, 4, context, parse("Boolean")),theory, true);
    // List<InferenceResult> IsingModel3X4 = testing("IsingModel",m,3,4);
    // listOdModelsToPrintInFile.add(IsingModel3X4);
    // println("ok");
    // 
    // m = new Model(IsingModel(4, 4, context, parse("Boolean")),theory, true);
    // List<InferenceResult> IsingModel4X4 = testing("IsingModel",m,4,4);
    // listOdModelsToPrintInFile.add(IsingModel4X4);
    // println("ok");
    // 
    // //		m = new Model(IsingModel(4, 5, context, parse("Boolean")),theory, true);
    // //		List<InferenceResult> IsingModel4X5 = testing("IsingModel",m,4,5);
    // //		listOdModelsToPrintInFile.add(IsingModel4X5);
    // //		println("ok");
    // 
    // modelName = "Line Model";
    // m = new Model(lineModel(20, context, parse("Boolean")),theory, true);
    // List<InferenceResult> line10 = testing(modelName,m,4,5);
    // listOdModelsToPrintInFile.add(line10);
    // println("ok");
    modelName = "Binary Tree Model";
    m = new Model(IsingModel(4, 4, context, parse("Boolean")), theory, true);
    List<TupleOfData> btree = testing(modelName, m, 4, 5);
    listOdModelsToPrintInFile.add(btree);
    println("ok");
    testingAndWritingToFile(modelName + ".csv", listOdModelsToPrintInFile);
}

Example 34 with CompoundTheory

use of com.sri.ai.grinder.theory.compound.CompoundTheory in project aic-expresso by aic-sri-international.

the class InversionPerformanceEvaluationTest method setUp.

@Before
public void setUp() {
    context = new TrueContext(new CompoundTheory(new DifferenceArithmeticTheory(false, false), new EqualityTheory(false, false), new PropositionalTheory(), new TupleTheory()));
    updateContextWithIndexAndType("R", GrinderUtil.INTEGER_TYPE);
    context.conjoin(parse("R = 1"), context);
}

Example 35 with CompoundTheory

use of com.sri.ai.grinder.theory.compound.CompoundTheory in project aic-expresso by aic-sri-international.

the class InversionSimplifierTest method setUp.

@Before
public void setUp() {
    context = new TrueContext(new CompoundTheory(new DifferenceArithmeticTheory(false, false), new TupleTheory()));
    FunctionType gFunctionType = new FunctionType(new IntegerInterval("1..10"), new IntegerInterval("1..10"));
    context = (Context) GrinderUtil.extendRegistryWith(map("g", gFunctionType.toString()), Arrays.asList(gFunctionType), context);
    simplifier = new InversionSimplifier();
}