private void runTestAllFeatures(DenseIndicatorLogLinearFactor parametricFactor) {
SufficientStatistics parameters = parametricFactor.getNewSufficientStatistics();
Factor initial = parametricFactor.getModelFromParameters(parameters);
assertEquals(0.0, initial.getUnnormalizedLogProbability("A", "T"), TOLERANCE);
assertEquals(0.0, initial.getUnnormalizedLogProbability("B", "T"), TOLERANCE);
assertEquals(0.0, initial.getUnnormalizedLogProbability("C", "F"), TOLERANCE);
parametricFactor.incrementSufficientStatisticsFromAssignment(
parameters, parameters, vars.outcomeArrayToAssignment("B", "F"), 2.0);
parametricFactor.incrementSufficientStatisticsFromAssignment(
parameters, parameters, vars.outcomeArrayToAssignment("B", "F"), -3.0);
parametricFactor.incrementSufficientStatisticsFromAssignment(
parameters, parameters, vars.outcomeArrayToAssignment("A", "T"), 1.0);
parametricFactor.incrementSufficientStatisticsFromAssignment(
parameters, parameters, vars.outcomeArrayToAssignment("C", "T"), 2.0);
Factor factor = parametricFactor.getModelFromParameters(parameters);
assertEquals(-1.0, factor.getUnnormalizedLogProbability("B", "F"), TOLERANCE);
assertEquals(1.0, factor.getUnnormalizedLogProbability("A", "T"), TOLERANCE);
assertEquals(2.0, factor.getUnnormalizedLogProbability("C", "T"), TOLERANCE);
TableFactorBuilder incrementBuilder =
new TableFactorBuilder(vars, SparseTensorBuilder.getFactory());
incrementBuilder.setWeight(4.0, "A", "F");
incrementBuilder.setWeight(6.0, "C", "F");
Factor increment = incrementBuilder.build();
parametricFactor.incrementSufficientStatisticsFromMarginal(
parameters, parameters, increment, Assignment.EMPTY, 3.0, 2.0);
factor = parametricFactor.getModelFromParameters(parameters);
assertEquals(-1.0, factor.getUnnormalizedLogProbability("B", "F"), TOLERANCE);
assertEquals(1.0, factor.getUnnormalizedLogProbability("A", "T"), TOLERANCE);
assertEquals(2.0, factor.getUnnormalizedLogProbability("C", "T"), TOLERANCE);
assertEquals(6.0, factor.getUnnormalizedLogProbability("A", "F"), TOLERANCE);
assertEquals(9.0, factor.getUnnormalizedLogProbability("C", "F"), TOLERANCE);
TableFactor pointDist =
TableFactor.logPointDistribution(truthVar, truthVar.outcomeArrayToAssignment("T"));
parametricFactor.incrementSufficientStatisticsFromMarginal(
parameters, parameters, pointDist, alphabetVar.outcomeArrayToAssignment("B"), 3, 2.0);
factor = parametricFactor.getModelFromParameters(parameters);
assertEquals(1.5, factor.getUnnormalizedLogProbability("B", "T"), TOLERANCE);
}
