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backport: pooling ratio is now occupancy rate
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@tschlenther
tschlenther committed Jun 25, 2024
1 parent caa988b commit 94442ff
Showing 1 changed file with 1 addition and 190 deletions.
191 changes: 1 addition & 190 deletions src/main/java/org/matsim/analysis/postAnalysis/drt/DrtPostProcessingAverageAnalysis.java
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package org.matsim.analysis.postAnalysis.drt;

import org.apache.commons.csv.CSVFormat;
import org.apache.commons.csv.CSVPrinter;
import org.matsim.application.CommandSpec;
import org.matsim.application.MATSimAppCommand;
import org.matsim.application.options.CsvOptions;
import org.matsim.application.options.InputOptions;
import org.matsim.application.options.OutputOptions;
import org.matsim.core.utils.io.IOUtils;
import picocli.CommandLine;
import tech.tablesaw.api.ColumnType;
import tech.tablesaw.api.Row;
import tech.tablesaw.api.Table;
import tech.tablesaw.io.csv.CsvReadOptions;

import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.text.DecimalFormat;
import java.text.DecimalFormatSymbols;
import java.time.LocalTime;
import java.util.*;

import static org.matsim.application.ApplicationUtils.globFile;

@CommandLine.Command(name = "average-drt", description = "Calculates average drt stats based on several sim runs with different random seeds.")
@CommandSpec(
requires = {"runs", "mode"},
produces = {"avg_demand_stats.csv", "avg_supply_stats.csv"}
)
public class DrtPostProcessingAverageAnalysis implements MATSimAppCommand {

@CommandLine.Mixin
private InputOptions input = InputOptions.ofCommand(DrtPostProcessingAverageAnalysis.class);
@CommandLine.Mixin
private OutputOptions output = OutputOptions.ofCommand(DrtPostProcessingAverageAnalysis.class);
@CommandLine.Option(names = "--no-runs", defaultValue = "5", description = "Number of simulation runs to be averaged.")
private Integer noRuns;

private final Map<String, List<Double>> demandStats = new HashMap<>();
private final Map<String, List<Double>> supplyStats = new HashMap<>();
private final Map<String, Double[]> demandAvgs = new HashMap<>();
private final Map<String, Double[]> supplyAvgs = new HashMap<>();

private final CsvOptions csv = new CsvOptions();

String supplyInfo = "info[titleCase]";
String value = "value";

public static void main(String[] args) {
new DrtPostProcessingAverageAnalysis().execute(args);
}

@Override
public Integer call() throws Exception {

String runs = input.getPath("runs");

List<String> foldersSeeded = Arrays.stream(runs.split(",")).toList();

// add stats from every run to map
for (String folder : foldersSeeded) {

String demandKpiCsv = globFile(Path.of(folder + "/analysis/" + input.getPath("mode")), "*demand_kpi.csv*").toString();
String supplyKpiCsv = globFile(Path.of(folder + "/analysis/" + input.getPath("mode")), "*supply_kpi.csv*").toString();

Table demand = Table.read().csv(CsvReadOptions.builder(IOUtils.getBufferedReader(demandKpiCsv))
.sample(false)
.separator(CsvOptions.detectDelimiter(demandKpiCsv)).build());

Table supply = Table.read().csv(CsvReadOptions.builder(IOUtils.getBufferedReader(supplyKpiCsv))
.sample(false)
.separator(CsvOptions.detectDelimiter(supplyKpiCsv)).build());

// get all demand stats
for (int i = 0; i < demand.rowCount(); i++) {
Row row = demand.row(i);

if (!demandStats.containsKey(row.getString("Info"))) {
demandStats.put(row.getString("Info"), new ArrayList<>());
}

// some values are in format hh:mm:ss or empty
if (row.getString(value).isEmpty()) {
demandStats.get(row.getString("Info")).add(0.);
} else if (row.getString(value).contains(":")) {
demandStats.get(row.getString("Info")).add((double) LocalTime.parse(row.getString(value)).toSecondOfDay());
} else {
demandStats.get(row.getString("Info")).add(Double.parseDouble(row.getString(value)));
}
}

// get all supply stats
for (int i = 0; i < supply.rowCount(); i++) {
Row row = supply.row(i);

if (!supplyStats.containsKey(row.getString(supplyInfo))) {
supplyStats.put(row.getString(supplyInfo), new ArrayList<>());
}

if (row.getColumnType(value) == ColumnType.INTEGER) {
supplyStats.get(row.getString(supplyInfo)).add((double) row.getInt(value));
} else {
supplyStats.get(row.getString(supplyInfo)).add(row.getDouble(value));
}
}
}

fillAvgMap(demandStats, demandAvgs);
fillAvgMap(supplyStats, supplyAvgs);

// ordered list of params to display them in same order as in single-run DrtDashboard
List<String> orderedDemandParams = List.of("Handled Requests", "Passengers (Pax)", "Avg Group Size", "Pax per veh", "Pax per veh-h", "Pax per veh-km",
"Rejections", "Rejection rate", "Avg. total travel time", "Avg. in-vehicle time", "Avg. wait time", "95th percentile wait time", "Avg. ride distance [km]",
"Avg. direct distance [km]", "Avg. fare [MoneyUnit]");
List<String> orderedSupplyParams = List.of("Number of stops", "Vehicles", "Total vehicle mileage [km]", "Empty ratio", "Total pax distance [km]",
"Occupancy rate [pax-km/v-km]", "Detour ratio", "Total service hours");

writeFile("avg_demand_stats.csv", demandAvgs, orderedDemandParams);
writeFile("avg_supply_stats.csv", supplyAvgs, orderedSupplyParams);

return 0;
}

private void writeFile(String fileName, Map<String, Double[]> values, List<String> orderedParams) throws IOException {
try (CSVPrinter printer = new CSVPrinter(Files.newBufferedWriter(output.getPath(fileName)), CSVFormat.DEFAULT)) {
DecimalFormat df = new DecimalFormat("#,###.##", new DecimalFormatSymbols(Locale.US));

// as of 19.06.24 min and max values are not printed anymore. they will still be calculated though.
// if one wants to include them to dashboard tables one just has to re-include them in this print method. -sme0624
printer.printRecord("parameter", "mean", "median", "standard deviation");


for (String param : orderedParams) {
printer.printRecord(param, df.format(values.get(param)[0]), df.format(values.get(param)[1]), df.format(values.get(param)[2]));
}
}
}

private void fillAvgMap(Map<String, List<Double>> source, Map<String, Double[]> destination) {
for (Map.Entry<String, List<Double>> e: source.entrySet()) {

String key = e.getKey();
Double[] values = new Double[5];

double sum = 0.;

for (double d : source.get(key)) {
sum += d;
}
double mean = sum / source.get(key).size();

values[0] = mean;
values[1] = calcMedian(source.get(key));
values[2] = calcStandardDeviation(source.get(key), mean);
values[3] = Collections.min(source.get(key));
values[4] = Collections.max(source.get(key));

destination.put(key, values);
}
}

private Double calcStandardDeviation(List<Double> values, double mean) {

double sumSquaredDiff = 0;
for (double num : values) {
sumSquaredDiff += Math.pow(num - mean, 2);
}

return Math.sqrt(sumSquaredDiff / values.size());
}

private Double calcMedian(List<Double> values) {
Collections.sort(values);

int length = values.size();
// Check if the length of the array is odd or even
if (length % 2 != 0) {
// If odd, return the middle element
return values.get(length / 2);
} else {
// If even, return the average of the two middle elements
int midIndex1 = length / 2 - 1;
int midIndex2 = length / 2;
return (values.get(midIndex1) + values.get(midIndex2)) / 2.0;
}
}
}

package org.matsim.analysis.postAnalysis.drt;import org.apache.commons.csv.CSVFormat;import org.apache.commons.csv.CSVPrinter;import org.matsim.application.CommandSpec;import org.matsim.application.MATSimAppCommand;import org.matsim.application.options.CsvOptions;import org.matsim.application.options.InputOptions;import org.matsim.application.options.OutputOptions;import org.matsim.core.utils.io.IOUtils;import picocli.CommandLine;import tech.tablesaw.api.ColumnType;import tech.tablesaw.api.Row;import tech.tablesaw.api.Table;import tech.tablesaw.io.csv.CsvReadOptions;import java.io.IOException;import java.nio.file.Files;import java.nio.file.Path;import java.text.DecimalFormat;import java.text.DecimalFormatSymbols;import java.time.LocalTime;import java.util.*;import static org.matsim.application.ApplicationUtils.globFile;@CommandLine.Command(name = "average-drt", description = "Calculates average drt stats based on several sim runs with different random seeds.")@CommandSpec( requires = {"runs", "mode"}, produces = {"avg_demand_stats.csv", "avg_supply_stats.csv"})public class DrtPostProcessingAverageAnalysis implements MATSimAppCommand { @CommandLine.Mixin private InputOptions input = InputOptions.ofCommand(DrtPostProcessingAverageAnalysis.class); @CommandLine.Mixin private OutputOptions output = OutputOptions.ofCommand(DrtPostProcessingAverageAnalysis.class); @CommandLine.Option(names = "--no-runs", defaultValue = "5", description = "Number of simulation runs to be averaged.") private Integer noRuns; private final Map<String, List<Double>> demandStats = new HashMap<>(); private final Map<String, List<Double>> supplyStats = new HashMap<>(); private final Map<String, Double[]> demandAvgs = new HashMap<>(); private final Map<String, Double[]> supplyAvgs = new HashMap<>(); private final CsvOptions csv = new CsvOptions(); String supplyInfo = "info[titleCase]"; String value = "value"; public static void main(String[] args) { new DrtPostProcessingAverageAnalysis().execute(args); } @Override public Integer call() throws Exception { String runs = input.getPath("runs"); List<String> foldersSeeded = Arrays.stream(runs.split(",")).toList();// add stats from every run to map for (String folder : foldersSeeded) { String demandKpiCsv = globFile(Path.of(folder + "/analysis/" + input.getPath("mode")), "*demand_kpi.csv*").toString(); String supplyKpiCsv = globFile(Path.of(folder + "/analysis/" + input.getPath("mode")), "*supply_kpi.csv*").toString(); Table demand = Table.read().csv(CsvReadOptions.builder(IOUtils.getBufferedReader(demandKpiCsv)) .sample(false) .separator(CsvOptions.detectDelimiter(demandKpiCsv)).build()); Table supply = Table.read().csv(CsvReadOptions.builder(IOUtils.getBufferedReader(supplyKpiCsv)) .sample(false) .separator(CsvOptions.detectDelimiter(supplyKpiCsv)).build());// get all demand stats for (int i = 0; i < demand.rowCount(); i++) { Row row = demand.row(i); if (!demandStats.containsKey(row.getString("Info"))) { demandStats.put(row.getString("Info"), new ArrayList<>()); }// some values are in format hh:mm:ss or empty if (row.getString(value).isEmpty()) { demandStats.get(row.getString("Info")).add(0.); } else if (row.getString(value).contains(":")) { demandStats.get(row.getString("Info")).add((double) LocalTime.parse(row.getString(value)).toSecondOfDay()); } else { demandStats.get(row.getString("Info")).add(Double.parseDouble(row.getString(value))); } }// get all supply stats for (int i = 0; i < supply.rowCount(); i++) { Row row = supply.row(i); if (!supplyStats.containsKey(row.getString(supplyInfo))) { supplyStats.put(row.getString(supplyInfo), new ArrayList<>()); } if (row.getColumnType(value) == ColumnType.INTEGER) { supplyStats.get(row.getString(supplyInfo)).add((double) row.getInt(value)); } else { supplyStats.get(row.getString(supplyInfo)).add(row.getDouble(value)); } } } fillAvgMap(demandStats, demandAvgs); fillAvgMap(supplyStats, supplyAvgs);// ordered list of params to display them in same order as in single-run DrtDashboard List<String> orderedDemandParams = List.of("Requests", "Rides", "Rides per veh", "Rides per veh-h", "Rides per veh-km", "Rejections", "Rejection rate", "Avg. total travel time", "Avg. in-vehicle time", "Avg. wait time", "95th percentile wait time", "Avg. ride distance [km]", "Avg. direct distance [km]", "Avg. fare [MoneyUnit]"); List<String> orderedSupplyParams = List.of("Number of stops", "Vehicles", "Total vehicle mileage [km]", "Empty ratio", "Total pax distance [km]", "Pooling ratio", "Detour ratio", "Total service hours"); writeFile("avg_demand_stats.csv", demandAvgs, orderedDemandParams); writeFile("avg_supply_stats.csv", supplyAvgs, orderedSupplyParams); return 0; } private void writeFile(String fileName, Map<String, Double[]> values, List<String> orderedParams) throws IOException { try (CSVPrinter printer = new CSVPrinter(Files.newBufferedWriter(output.getPath(fileName)), CSVFormat.DEFAULT)) { DecimalFormat df = new DecimalFormat("#,###.##", new DecimalFormatSymbols(Locale.US));// as of 19.06.24 min and max values are not printed anymore. they will still be calculated though.// if one wants to include them to dashboard tables one just has to re-include them in this print method. -sme0624 printer.printRecord("parameter", "mean", "median", "standard deviation"); for (String param : orderedParams) { printer.printRecord(param, df.format(values.get(param)[0]), df.format(values.get(param)[1]), df.format(values.get(param)[2])); } } } private void fillAvgMap(Map<String, List<Double>> source, Map<String, Double[]> destination) { for (Map.Entry<String, List<Double>> e: source.entrySet()) { String key = e.getKey(); Double[] values = new Double[5]; double sum = 0.; for (double d : source.get(key)) { sum += d; } double mean = sum / source.get(key).size(); values[0] = mean; values[1] = calcMedian(source.get(key)); values[2] = calcStandardDeviation(source.get(key), mean); values[3] = Collections.min(source.get(key)); values[4] = Collections.max(source.get(key)); destination.put(key, values); } } private Double calcStandardDeviation(List<Double> values, double mean) { double sumSquaredDiff = 0; for (double num : values) { sumSquaredDiff += Math.pow(num - mean, 2); } return Math.sqrt(sumSquaredDiff / values.size()); } private Double calcMedian(List<Double> values) { Collections.sort(values); int length = values.size(); // Check if the length of the array is odd or even if (length % 2 != 0) { // If odd, return the middle element return values.get(length / 2); } else { // If even, return the average of the two middle elements int midIndex1 = length / 2 - 1; int midIndex2 = length / 2; return (values.get(midIndex1) + values.get(midIndex2)) / 2.0; } }}
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