assign activity chains

Makefile

@@ -92,8 +92,9 @@ input/$V/$N-$V-facilities.xml.gz: input/$V/$N-$V-network.xml.gz input/facilities
 input/$V/$N-static-$V-10pct.plans.xml.gz: input/facilities.gpkg
 	$(sc) prepare kansai-population\
 		--input $(kyoto)/data/census_kansai_region.csv\
-		--shp $(kyoto)/data/kansai-region-epsg4612.gpkg --shp-crs $(CRS)\
-		--facilities $< --facilities-attr resident\
+		--shp $(kyoto)/data/kansai-region.gpkg\
+		--postal-shp $(kyoto)/data/postalcodes.gpkg\
+		--facilities $< --facilities-attr all\
 		--output $@
 
 
@@ -102,27 +103,11 @@ input/$V/$N-$V-10pct.plans-initial.xml.gz: input/$V/$N-static-$V-10pct.plans.xml
 	$(sc) prepare create-daily-plans --input $< --output $@\
 	 --persons src/main/python/table-persons.csv\
   	 --activities src/main/python/table-activities.csv\
-	 --shp $(kyoto)/data/kansai-region-epsg4612.gpkg --shp-crs $(CRS)\
+	 --shp $(kyoto)/data/postalcodes.gpkg\
 	 --facilities $(word 2,$^)\
 	 --network $(word 3,$^)\
 
 
-# Assigns locations to the activities
-$p/berlin-initial-$V-10pct.plans.xml.gz: $p/$N-activities-$V-25pct.plans.xml.gz input/$V/$N-$V-facilities.xml.gz input/$V/$N-$V-network.xml.gz
-	$(sc) prepare init-location-choice\
-	 --input $<\
-	 --output $@\
-	 --facilities $(word 2,$^)\
-	 --network $(word 3,$^)\
-	 --shp $(germany)/vg5000/vg5000_ebenen_0101/VG5000_GEM.shp\
-	 --commuter $(germany)/regionalstatistik/commuter.csv\
-
-	# For debugging and visualization
-	$(sc) prepare downsample-population $@\
-		 --sample-size 0.25\
-		 --samples 0.1 0.03 0.01\
-
-
 # Aggregated target for input plans to calibration
 prepare: input/$V/$N-$V-10pct.plans-initial.xml.gz input/$V/$N-$V-network-with-pt.xml.gz
 	echo "Done"

pom.xml

@@ -67,7 +67,8 @@
 		<dependency>
 			<groupId>com.github.matsim-scenarios</groupId>
 			<artifactId>matsim-berlin</artifactId>
-			<version>ce81ea226c</version>
+			<version>6.3-SNAPSHOT</version>
+<!--			<version>d9f763ffbc</version>-->
 		</dependency>
 
 
@@ -103,6 +104,13 @@
 	<build>
 		<plugins>
 
+			<plugin>
+				<artifactId>maven-enforcer-plugin</artifactId>
+				<configuration>
+					<skip>true</skip>
+				</configuration>
+			</plugin>
+
 			<plugin>
 				<groupId>org.apache.maven.plugins</groupId>
 				<artifactId>maven-compiler-plugin</artifactId>

src/main/java/org/matsim/prepare/population/CreateDailyPlans.java

@@ -1,18 +1,28 @@
 package org.matsim.prepare.population;
 
+import me.tongfei.progressbar.ProgressBar;
+import org.apache.commons.csv.CSVFormat;
+import org.apache.commons.csv.CSVParser;
+import org.apache.commons.csv.CSVRecord;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
+import org.matsim.api.core.v01.Coord;
 import org.matsim.api.core.v01.population.Person;
 import org.matsim.api.core.v01.population.Population;
 import org.matsim.application.MATSimAppCommand;
 import org.matsim.application.options.ShpOptions;
+import org.matsim.core.population.PersonUtils;
 import org.matsim.core.population.PopulationUtils;
 import org.matsim.core.population.algorithms.ParallelPersonAlgorithmUtils;
 import org.matsim.core.population.algorithms.PersonAlgorithm;
 import picocli.CommandLine;
 
+import java.math.BigInteger;
+import java.nio.charset.StandardCharsets;
 import java.nio.file.Path;
-import java.util.SplittableRandom;
+import java.util.*;
+import java.util.stream.IntStream;
+import java.util.stream.Stream;
 
 @CommandLine.Command(
 	name = "create-daily-plans",
@@ -21,37 +31,40 @@
 public class CreateDailyPlans implements MATSimAppCommand, PersonAlgorithm {
 
 	private static final Logger log = LogManager.getLogger(CreateDailyPlans.class);
-
+	private final Map<String, CSVRecord> persons = new HashMap<>();
+	private final Map<Key, List<String>> groups = new HashMap<>();
 	@CommandLine.Option(names = "--input", description = "Path to input population.")
 	private Path input;
-
 	@CommandLine.Option(names = "--output", description = "Path to output population", required = true)
 	private Path output;
-
 	@CommandLine.Option(names = "--persons", description = "Path to person table", required = true)
 	private Path personsPath;
-
 	@CommandLine.Option(names = "--activities", description = "Path to activity table", required = true)
 	private Path activityPath;
-
 	@CommandLine.Option(names = "--facilities", description = "Path to facilities file", required = true)
 	private Path facilityPath;
-
 	@CommandLine.Option(names = "--network", description = "Path to network file", required = true)
 	private Path networkPath;
-
 	@CommandLine.Option(names = "--seed", description = "Seed used to sample locations", defaultValue = "1")
 	private long seed;
-
 	@CommandLine.Mixin
 	private ShpOptions shp;
-
-	private ThreadLocal<SplittableRandom> rnd;
+	private Population population;
+	private Map<String, List<CSVRecord>> activities;
+	private ProgressBar pb;
 
 	public static void main(String[] args) {
 		new CreateDailyPlans().execute(args);
 	}
 
+	/**
+	 * Initializes random number generator with person specific seed.
+	 */
+	private SplittableRandom initRandomNumberGenerator(Person person) {
+		BigInteger i = new BigInteger(person.getId().toString().getBytes());
+		return new SplittableRandom(i.longValue() + seed);
+	}
+
 	@Override
 	public Integer call() throws Exception {
 
@@ -60,9 +73,25 @@ public Integer call() throws Exception {
 			return 2;
 		}
 
-		Population population = PopulationUtils.readPopulation(input.toString());
+		// TODO: map zones to shape file
+
+		activities = RunActivitySampling.readActivities(activityPath);
+
+		// Remove activities with missing leg duration
+		activities.values().removeIf(
+			rows -> rows.stream().anyMatch(act -> act.get("leg_duration").isBlank() || act.get("duration").isBlank())
+		);
+
+		log.info("Got {} persons after cleaning", activities.size());
+
+		try (CSVParser csv = CSVParser.parse(personsPath, StandardCharsets.UTF_8,
+			CSVFormat.DEFAULT.builder().setHeader().setSkipHeaderRecord(true).build())) {
+			readPersons(csv);
+		}
 
-		rnd = ThreadLocal.withInitial(() -> new SplittableRandom(seed));
+		population = PopulationUtils.readPopulation(input.toString());
+
+		pb = new ProgressBar("Creating daily plans", population.getPersons().size());
 
 		ParallelPersonAlgorithmUtils.run(population, 8, this);
 
@@ -74,7 +103,141 @@ public Integer call() throws Exception {
 	@Override
 	public void run(Person person) {
 
-		// TODO: map zones to shape file
+		SplittableRandom rnd = initRandomNumberGenerator(person);
+
+		Coord homeCoord = Attributes.getHomeCoord(person);
+
+		String personId = matchPerson(rnd, createKey(person, Zone.FULL));
+		if (personId == null) {
+			personId = matchPerson(rnd, createKey(person, Zone.CITY));
+		}
+		if (personId == null) {
+			personId = matchPerson(rnd, createKey(person, Zone.NONE));
+		}
+
+		if (personId == null) {
+			log.warn("No matching person found for {}", createKey(person, Zone.NONE));
+			return;
+		}
+
+		List<CSVRecord> activities = Objects.requireNonNull(this.activities.get(personId), "No activities found");
+
+		RunActivitySampling.createPlan(homeCoord, activities, rnd, population.getFactory());
+
+		// TODO: select locations
+
+		// TODO: add reference modes and weights for fully matched persons
+
+		pb.step();
+	}
+
+	/**
+	 * Create subpopulations for sampling.
+	 */
+	private void readPersons(CSVParser csv) {
+
+		int i = 0;
+		int skipped = 0;
 
+		for (CSVRecord r : csv) {
+
+			String idx = r.get("p_id");
+			String gender = r.get("gender");
+			int age = Integer.parseInt(r.get("age"));
+
+			if (!activities.containsKey(idx)) {
+				skipped++;
+				continue;
+			}
+
+			Stream<Key> keys = createKey(gender, age, r.get("location"), r.get("zone"));
+			keys.forEach(key -> {
+				groups.computeIfAbsent(key, (k) -> new ArrayList<>()).add(idx);
+
+				// Alternative keys with different zones
+				groups.computeIfAbsent(new Key(key.gender, key.age, r.get("location")), (k) -> new ArrayList<>()).add(idx);
+				groups.computeIfAbsent(new Key(key.gender, key.age, null), (k) -> new ArrayList<>()).add(idx);
+
+			});
+			persons.put(idx, r);
+			i++;
+		}
+
+		log.info("Read {} persons from csv. Skipped {} invalid persons", i, skipped);
 	}
+
+	/**
+	 * Match person attributes with person from survey data.
+	 *
+	 * @return daily activities
+	 */
+	private String matchPerson(SplittableRandom rnd, Key key) {
+		List<String> subgroup = groups.get(key);
+		if (subgroup == null) {
+			return null;
+		}
+
+		if (subgroup.size() < 5)
+			return null;
+
+		// TODO: needs to be weighted matching
+		// weights can be preprocessed after reading in
+
+		return subgroup.get(rnd.nextInt(subgroup.size()));
+	}
+
+	private Stream<Key> createKey(String gender, int age, String location, String zone) {
+
+		String homeZone;
+		if (zone.isBlank() || zone.equals(location))
+			homeZone = location;
+		else
+			// The last two digits of the postal code are not known
+			homeZone = location + "_" + zone.substring(0, zone.length() - 2);
+
+		if (age <= 10) {
+			return IntStream.rangeClosed(0, 10).mapToObj(i -> new Key(null, i, homeZone));
+		}
+		if (age < 18) {
+			return IntStream.rangeClosed(11, 18).mapToObj(i -> new Key(gender, i, homeZone));
+		}
+
+		int min = Math.max(18, age - 6);
+		int max = Math.min(65, age + 6);
+
+		// larger groups for older people
+		if (age > 65) {
+			min = Math.max(66, age - 10);
+			max = Math.min(105, age + 10);
+		}
+
+		return IntStream.rangeClosed(min, max).mapToObj(i -> new Key(gender, i, homeZone));
+	}
+
+	private Key createKey(Person person, Zone zone) {
+
+		Integer age = PersonUtils.getAge(person);
+		String gender = PersonUtils.getSex(person);
+		if (age <= 10)
+			gender = null;
+
+		String homeZone = switch (zone) {
+			case FULL -> person.getAttributes().getAttribute("city") + "_" + person.getAttributes().getAttribute("postal");
+			case CITY -> Objects.toString(person.getAttributes().getAttribute("city"));
+			case NONE -> null;
+		};
+
+		return new Key(gender, age, homeZone);
+	}
+
+	private enum Zone {
+		FULL, CITY, NONE
+	}
+
+	/**
+	 * Key used to match persons.
+	 */
+	public record Key(String gender, int age, String homeZone) {
+	}
+
 }