PSL basic-example using an existing database

BasicExampleReuse.groovy

import java.text.DecimalFormat

import edu.umd.cs.psl.application.inference.MPEInference
import edu.umd.cs.psl.config.*
import edu.umd.cs.psl.database.DataStore
import edu.umd.cs.psl.database.Database
import edu.umd.cs.psl.database.Partition
import edu.umd.cs.psl.database.rdbms.RDBMSDataStore
import edu.umd.cs.psl.database.rdbms.driver.H2DatabaseDriver
import edu.umd.cs.psl.database.rdbms.driver.H2DatabaseDriver.Type
import edu.umd.cs.psl.groovy.PSLModel
import edu.umd.cs.psl.model.atom.GroundAtom
import edu.umd.cs.psl.model.predicate.Predicate
import edu.umd.cs.psl.ui.functions.textsimilarity.*
import edu.umd.cs.psl.util.database.Queries

ConfigManager cm = ConfigManager.getManager()
ConfigBundle config = cm.getBundle("basic-example")

def defaultPath = System.getProperty("java.io.tmpdir")
String dbpath = config.getString("dbpath", defaultPath + File.separator + "basic-example")
DataStore data = new RDBMSDataStore(new H2DatabaseDriver(Type.Disk, dbpath, false), config)

PSLModel m = new PSLModel(this, data)
println m

Predicate samePerson = m.getPredicate("SamePerson")
Predicate network = m.getPredicate("Network")
Predicate name = m.getPredicate("Name")
Predicate knows = m.getPredicate("Knows")

def evidencePartition = new Partition(0);
def targetPartition = new Partition(1);
Database db = data.getDatabase(targetPartition, [network, name, knows] as Set, evidencePartition);

println m

MPEInference inferenceApp = new MPEInference(m, db, config);
inferenceApp.mpeInference();
inferenceApp.close();

println m

println "Inference results with hand-defined weights:"
DecimalFormat formatter = new DecimalFormat("#.##");
for (GroundAtom atom : Queries.getAllAtoms(db, samePerson))
    println atom.toString() + "\t" + formatter.format(atom.getValue());

db.close();