extract more reference groups

src/main/java/org/matsim/run/scoring/AdvancedScoringConfigGroup.java

@@ -13,40 +13,34 @@
 public final class AdvancedScoringConfigGroup extends ReflectiveConfigGroup {
 
 	private static final String GROUP_NAME = "advancedScoring";
-
 	private final List<ScoringParameters> scoringParameters = new ArrayList<>();
 
-	/**
-	 * Different options for income dependent scoring.
-	 */
-	public enum IncomeDependentScoring {
-		none,
-		avg_by_personal_income
-	}
-
 	@Parameter
 	@Comment("The distance groups if marginal utility of distance is adjusted. In meters.")
 	public List<Integer> distGroups;
 
 	@Parameter
 	@Comment("Enable income dependent marginal utility of money.")
-	public IncomeDependentScoring incomeDependent = IncomeDependentScoring.avg_by_personal_income;
-
+	public IncomeDependentScoring incomeDependent = IncomeDependentScoring.avgByPersonalIncome;
 
-	// TODO: maybe option to re-assign variations or use them from attributes
-	// TODO: could load the random variations from a file, helper function to only generate the variations
+	@Parameter
+	@Comment("Define how to load existing preferences.")
+	public LoadPreferences loadPreferences = LoadPreferences.none;
 
 	public AdvancedScoringConfigGroup() {
 		super(GROUP_NAME);
 	}
 
 	/**
-	 *  Return the defined scoring parameters.
+	 * Return the defined scoring parameters.
 	 */
 	public List<ScoringParameters> getScoringParameters() {
 		return Collections.unmodifiableList(scoringParameters);
 	}
 
+	// TODO: maybe option to re-assign variations or use them from attributes
+	// TODO: could load the random variations from a file, helper function to only generate the variations
+
 	@Override
 	public ConfigGroup createParameterSet(String type) {
 		if (type.equals(ScoringParameters.GROUP_NAME)) {
@@ -66,6 +60,30 @@ public void addParameterSet(ConfigGroup set) {
 		}
 	}
 
+	/**
+	 * Different options for income dependent scoring.
+	 */
+	public enum IncomeDependentScoring {
+		none,
+		avgByPersonalIncome
+	}
+
+	/**
+	 * Define how existing preferences are loaded.
+	 */
+	public enum LoadPreferences {
+		none,
+		requireAttribute,
+		skipRefPersons
+	}
+
+	/**
+	 * Variate values with random draw from specific distribution.
+	 */
+	public enum VariationType {
+		fixed, normal, truncatedNormal
+	}
+
 	/**
 	 * Scoring parameters for a specific group of agents.
 	 * This group allows arbitrary attributes to be defined, which are matched against person attributes.
@@ -175,11 +193,4 @@ public ModeParams() {
 			super(GROUP_NAME);
 		}
 	}
-
-	/**
-	 * Variate values with random draw from specific distribution.
-	 */
-	public enum VariationType {
-		fixed, normal, truncatedNormal
-	}
 }

src/main/python/extract_ref_data.py

@@ -11,9 +11,10 @@ def person_filter(df):
     df = df[df.reporting_day <= 4]
     df = df[df.location == "Berlin"]
 
-    df["age"] = preparation.cut(df.age, [0, 18, 66, np.inf])
+    df["age"] = preparation.cut(df.age, [0, 12, 18, 25, 35, 66, np.inf])
 
     preparation.fill(df, "economic_status", EconomicStatus.UNKNOWN)
+    preparation.fill(df, "income", -1)
 
     return df
 
@@ -35,7 +36,7 @@ def trip_filter(df):
         d + "Berlin+Umland",
         person_filter, trip_filter,
         run_create_ref_data.InvalidHandling.REMOVE_TRIPS,
-        ref_groups=["age", "economic_status"]
+        ref_groups=["age", "income", "economic_status", "employment", "car_avail", "bike_avail", "pt_abo_avail"]
     )
 
     print(result.share)