Examples with Expression com.sri.ai.expresso.api.Expression used on opensource projects

Example 81 with Expression

use of com.sri.ai.expresso.api.Expression in project aic-praise by aic-sri-international.

the class HOGMQueryRunner method query.

public List<HOGMQueryResult> query() {
    List<HOGMQueryResult> result = new ArrayList<>();
    Expression queryExpr = null;
    //
    ParsedHOGModel parsedModel = null;
    for (String query : queries) {
        long startQuery = System.currentTimeMillis();
        List<HOGMQueryError> errors = new ArrayList<>();
        try {
            if (model == null || model.trim().equals("")) {
                errors.add(new HOGMQueryError(HOGMQueryError.Context.MODEL, "Model not specified", 0, 0, 0));
            }
            if (query == null || query.trim().equals("")) {
                errors.add(new HOGMQueryError(HOGMQueryError.Context.QUERY, "Query not specified", 0, 0, 0));
            }
            if (errors.size() == 0) {
                HOGMParserWrapper parser = new HOGMParserWrapper();
                if (parsedModel == null) {
                    parsedModel = parser.parseModel(model, new QueryErrorListener(HOGMQueryError.Context.MODEL, errors));
                }
                queryExpr = parser.parseTerm(query, new QueryErrorListener(HOGMQueryError.Context.QUERY, errors));
                if (errors.size() == 0) {
                    FactorsAndTypes factorsAndTypes = new ExpressionFactorsAndTypes(parsedModel);
                    if (!canceled) {
                        inferencer = new InferenceForFactorGraphAndEvidence(factorsAndTypes, false, null, true, getOptionalTheory());
                        startQuery = System.currentTimeMillis();
                        Expression marginal = inferencer.solve(queryExpr);
                        result.add(new HOGMQueryResult(query, queryExpr, parsedModel, marginal, System.currentTimeMillis() - startQuery));
                    }
                }
            }
        } catch (RecognitionException re) {
            errors.add(new HOGMQueryError(HOGMQueryError.Context.MODEL, re.getMessage(), re.getOffendingToken().getLine(), re.getOffendingToken().getStartIndex(), re.getOffendingToken().getStopIndex()));
        } catch (UnableToParseAllTheInputError utpai) {
            errors.add(new HOGMQueryError(utpai));
        } catch (HOGModelException me) {
            me.getErrors().forEach(modelError -> {
                String inStatement = modelError.getInStatementInfo().statement.toString();
                String inSource = modelError.getInStatementInfo().sourceText;
                String inSubStatement = modelError.getMessage();
                String inInfo = "";
                if (inSubStatement.equals("") || inSubStatement.equals(inSource)) {
                    inInfo = " in '" + inStatement + "'";
                } else {
                    inInfo = " ('" + inSubStatement + "') in '" + inStatement + "'";
                }
                if (!inSource.replaceAll(" ", "").replaceAll(";", "").equals(inStatement.replaceAll(" ", ""))) {
                    inInfo = inInfo + " derived from '" + inSource + "'";
                }
                errors.add(new HOGMQueryError(HOGMQueryError.Context.MODEL, modelError.getErrorType().formattedMessage() + inInfo, modelError.getInStatementInfo().line, modelError.getInStatementInfo().startIndex, modelError.getInStatementInfo().endIndex));
            });
        } catch (Throwable t) {
            // Unexpected
            errors.add(new HOGMQueryError(t));
        }
        if (errors.size() > 0) {
            result.add(new HOGMQueryResult(query, queryExpr, parsedModel, errors, System.currentTimeMillis() - startQuery));
        }
    }
    return result;
}

Example 82 with Expression

use of com.sri.ai.expresso.api.Expression in project aic-praise by aic-sri-international.

the class HOGModelGroundingTest method test.

/**
	 * @throws AssertionError
	 */
@Test
public void test() throws AssertionError {
    long start = System.currentTimeMillis();
    StringJoiner sj = new StringJoiner("\n");
    sj.add("sort People : 10, Putin;");
    sj.add("sort Countries : 10, USA, Russia;");
    sj.add("random country : Countries;");
    sj.add("random president : People;");
    sj.add("random communism : Boolean;");
    sj.add("random democracy : Boolean;");
    sj.add("random votePutin : 1..15;");
    sj.add("if country = Russia then if president = Putin then communism else not communism else if democracy then not communism else communism;");
    sj.add("if country = Russia then if votePutin > 5 then president = Putin else not president = Putin;");
    HOGMParserWrapper parser = new HOGMParserWrapper();
    ParsedHOGModel parsedModel = parser.parseModel(sj.toString());
    FactorsAndTypes factorsAndTypes = new ExpressionFactorsAndTypes(parsedModel);
    List<Expression> evidence = new ArrayList<>();
    evidence.add(Expressions.parse("communism"));
    StringJoiner outputBuffer = new StringJoiner("");
    HOGModelGrounding.ground(factorsAndTypes, evidence, new // NOTE: an example listener that outputs in the UAI format
    HOGModelGrounding.Listener() {

        int numberVariables;

        StringJoiner preamble = new StringJoiner("");

        StringJoiner functionTables = new StringJoiner("");

        List<Pair<Integer, Integer>> evidence = new ArrayList<>();

        @Override
        public void numberGroundVariables(int number) {
            this.numberVariables = number;
            preamble.add("MARKOV\n");
            preamble.add("" + number + "\n");
        }

        @Override
        public void groundVariableCardinality(int variableIndex, int cardinality) {
            preamble.add("" + cardinality);
            if (variableIndex == (numberVariables - 1)) {
                preamble.add("\n");
            } else {
                preamble.add(" ");
            }
        }

        @Override
        public void numberFactors(int number) {
            preamble.add("" + number + "\n");
        }

        @Override
        public void factorParticipants(int factorIndex, int[] variableIndexes) {
            preamble.add("" + variableIndexes.length);
            for (int i = 0; i < variableIndexes.length; i++) {
                preamble.add(" " + variableIndexes[i]);
            }
            preamble.add("\n");
        }

        @Override
        public void factorValue(int numberFactorValues, boolean isFirstValue, boolean isLastValue, Rational value) {
            if (isFirstValue) {
                functionTables.add("\n" + numberFactorValues + "\n");
            } else {
                functionTables.add(" ");
            }
            functionTables.add("" + value.doubleValue());
            if (isLastValue) {
                functionTables.add("\n");
            }
        }

        @Override
        public void evidence(int variableIndex, int valueIndex) {
            evidence.add(new Pair<>(variableIndex, valueIndex));
        }

        @Override
        public void groundingComplete() {
            long end = System.currentTimeMillis() - start;
            outputBuffer.add("--- MODEL ---\n");
            outputBuffer.add(preamble.toString());
            outputBuffer.add(functionTables.toString());
            outputBuffer.add("--- EVIDENCE ---\n");
            outputBuffer.add("" + evidence.size());
            for (Pair<Integer, Integer> evidenceAssignment : evidence) {
                outputBuffer.add(" ");
                outputBuffer.add(evidenceAssignment.first.toString());
                outputBuffer.add(" ");
                outputBuffer.add(evidenceAssignment.second.toString());
            }
            System.out.println(outputBuffer.toString());
            System.out.println("\nTime taken for grounding (not printing): " + end + " ms.");
        }
    });
    String expected = "--- MODEL ---\n" + "MARKOV\n" + "5\n" + "10 10 2 2 15\n" + "2\n" + "4 0 1 2 3\n" + "3 0 4 1\n" + "\n" + "400\n" + "0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0 0.0 1.0 1.0 0.0\n" + "\n" + "1500\n" + "0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5\n" + "--- EVIDENCE ---\n" + "1 2 1";
    assertEquals(expected, outputBuffer.toString());
}

Example 83 with Expression

use of com.sri.ai.expresso.api.Expression in project aic-praise by aic-sri-international.

the class InferenceForFactorGraphAndEvidenceTest method testAPI.

@Test
public void testAPI() {
    // IMPORTANT: this test is reproduced in the User Guide as an example,
    // so it should be kept in sync with it.
    String modelString = "" + "random earthquake: Boolean;" + "random burglary: Boolean;" + "random alarm: Boolean;" + "" + "earthquake 0.01;" + "burglary 0.1;" + "" + "if earthquake" + "   then if burglary" + "      then alarm 0.95" + "      else alarm 0.6" + "   else if burglary" + "      then alarm 0.9" + "      else alarm 0.01;" + "     " + "not alarm;" + "";
    Expression evidence = parse("not alarm");
    // can be any boolean expression
    boolean isBayesianNetwork = true;
    // is a Bayesian network, that is, factors are normalized
    // and the sum of their product over all assignments to random variables is 1.
    boolean exploitFactorization = true;
    // exploit factorization (that is, employ Variable Elimination,
    // as opposed to summing over the entire joint probability distribution).
    InferenceForFactorGraphAndEvidence inferencer = new InferenceForFactorGraphAndEvidence(new ExpressionFactorsAndTypes(modelString), isBayesianNetwork, evidence, exploitFactorization, null);
    Expression queryExpression;
    Expression marginal;
    queryExpression = parse("not earthquake");
    // can be any boolean expression, or any random variable
    marginal = inferencer.solve(queryExpression);
    System.out.println("Marginal is " + marginal);
    queryExpression = parse("earthquake");
    marginal = inferencer.solve(queryExpression);
    System.out.println("Marginal is " + marginal);
}

Example 84 with Expression

use of com.sri.ai.expresso.api.Expression in project aic-expresso by aic-sri-international.

the class MaximumExpressionStepSolverTest method test.

@Test
public void test() {
    TheoryTestingSupport theoryTestingSupport = TheoryTestingSupport.make(makeRandom(), new DifferenceArithmeticTheory(true, true));
    Context context = theoryTestingSupport.makeContextWithTestingInformation();
    List<String> expressionStrings;
    String order;
    Expression orderMinimum;
    Expression orderMaximum;
    Expression expected;
    expressionStrings = list("I", "J");
    expected = parse("if I < J then J else I");
    order = LESS_THAN;
    orderMinimum = MINUS_INFINITY;
    orderMaximum = INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
    expressionStrings = list("I", "J");
    expected = parse("if I > J then J else I");
    order = GREATER_THAN;
    orderMinimum = INFINITY;
    orderMaximum = MINUS_INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
    expressionStrings = list("2", "3", "J");
    expected = parse("if 3 < J then J else 3");
    order = LESS_THAN;
    orderMinimum = MINUS_INFINITY;
    orderMaximum = INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
    expressionStrings = list("2", "I", "3", "J");
    expected = parse("if 2 < I then if I < J then J else I else if 3 < J then J else 3");
    order = LESS_THAN;
    orderMinimum = MINUS_INFINITY;
    orderMaximum = INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
    expressionStrings = list("1", "2");
    expected = parse("2");
    order = LESS_THAN;
    orderMinimum = MINUS_INFINITY;
    orderMaximum = INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
    expressionStrings = list("1", "2");
    expected = parse("1");
    order = GREATER_THAN;
    orderMinimum = INFINITY;
    orderMaximum = MINUS_INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
    expressionStrings = list("1", "-infinity");
    expected = parse("1");
    order = LESS_THAN;
    orderMinimum = MINUS_INFINITY;
    orderMaximum = INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
    expressionStrings = list("1", "infinity");
    expected = parse("infinity");
    order = LESS_THAN;
    orderMinimum = MINUS_INFINITY;
    orderMaximum = INFINITY;
    runTest(expressionStrings, order, orderMinimum, orderMaximum, expected, context);
}

Example 85 with Expression

use of com.sri.ai.expresso.api.Expression in project aic-expresso by aic-sri-international.

the class MaximumExpressionStepSolverTest method runTest.

private void runTest(List<String> expressions, String order, Expression orderMinimum, Expression orderMaximum, Expression expected, Context context) {
    MaximumExpressionStepSolver stepSolver = new MaximumExpressionStepSolver(mapIntoArrayList(expressions, Expressions::parse), makeSymbol(order), orderMinimum, orderMaximum);
    Expression solution = ContextDependentExpressionProblemSolver.staticSolve(stepSolver, context);
    System.out.println("Maximum of " + expressions + " for order " + order + ": " + solution);
    assertEquals(expected, solution);
}