Merge remote-tracking branch 'origin/develop' into develop

scenarios/metropole-ruhr-v2.0/input/metropole-ruhr-v2.0-3pct.config.xml

@@ -2,7 +2,7 @@
 <!DOCTYPE config SYSTEM "http://www.matsim.org/files/dtd/config_v2.dtd">
 <config>
 	<module name="timeAllocationMutator" >
-		<param name="mutationRange" value="7200.0" />
+		<param name="mutationRange" value="900.0" />
 	</module>
 	<module name="controller">
 		<param name="lastIteration" value="400"/>
@@ -69,22 +69,22 @@
 		<parameterset type="strategysettings">
 			<param name="strategyName" value="ChangeExpBeta"/>
 			<param name="subpopulation" value="person"/>
-			<param name="weight" value="0.85"/>
+			<param name="weight" value="1.0"/>
 		</parameterset>
 		<parameterset type="strategysettings">
 			<param name="strategyName" value="ReRoute"/>
 			<param name="subpopulation" value="person"/>
-			<param name="weight" value="0.10"/>
+			<param name="weight" value="0.15"/>
 		</parameterset>
 		<parameterset type="strategysettings">
 			<param name="strategyName" value="SubtourModeChoice"/>
 			<param name="subpopulation" value="person"/>
-			<param name="weight" value="0.10"/>
+			<param name="weight" value="0.15"/>
 		</parameterset>
 		<parameterset type="strategysettings" >
 			<param name="strategyName" value="TimeAllocationMutator" />
 			<param name="subpopulation" value="person"/>
-			<param name="weight" value="0.05" />
+			<param name="weight" value="0.15" />
 			<param name="disableAfterIteration" value="350" />
 		</parameterset>
 	</module>
@@ -106,7 +106,7 @@
 		<param name="vspDefaultsCheckingLevel" value="abort" />
 	</module>
 	<module name="scoring">
-		<param name="fractionOfIterationsToStartScoreMSA" value="1.0" />
+		<param name="fractionOfIterationsToStartScoreMSA" value="0.9" />
 		<parameterset type="scoringParameters" >
 			<param name="marginalUtilityOfMoney" value="1.0"/>
 			<!-- car prices 2012->2022: inflation (110.2-91.7)/91.7 = 0.2017448
@@ -237,4 +237,24 @@
 			<param name="ptModes" value="pt" />
 		</parameterset>
 	</module>
+
+	<module name="ReplanningAnnealer" >
+		<param name="activateAnnealingModule" value="false" />
+		<parameterset type="AnnealingVariable" >
+			<param name="annealParameter" value="globalInnovationRate" />
+			<param name="annealType" value="sigmoid" />
+			<param name="defaultSubpopulation" value="person" />
+			<!-- this parameter enters the exponential and sigmoid formulas. May be an iteration or a share, i.e. 0.5 for halfLife at 50% of iterations. Exponential: startValue / exp(it/halfLife) -->
+			<param name="halfLife" value="0.5" />
+			<!-- sigmoid: 1/(1+e^(shapeFactor*(it - halfLife))); geometric: startValue * shapeFactor^it; msa: startValue / it^shapeFactor -->
+			<param name="shapeFactor" value="0.01" />
+			<param name="startValue" value="0.6" />
+			<param name="endValue" value="0.01" />
+		</parameterset>
+	</module>
+	<module name="strategy">
+		<param name="fractionOfIterationsToDisableInnovation" value="0.8"/>
+		<!-- Strategies are added in code -->
+	</module>
+
 </config>

src/main/R/srv.R

@@ -34,8 +34,7 @@ tt <- 17728996
 
 persons <- read_delim("../../../../shared-svn/projects/rvr-metropole-ruhr/data/MID/MiD2017_Personen_RVR-Gebiet.csv", delim = ";", 
                       locale = locale(decimal_mark = ",")) %>%
-  filter(kernwo == 2) %>%
-  filter(anzwege3 >= 0 & anzwege3 < 100)
+  filter(ST_WOTAG >= 2 & ST_WOTAG <= 4)
 
 # Avg. number of trips per person per day
 per_day <- weighted.mean(persons$anzwege3, persons$gew_pers)
@@ -62,8 +61,9 @@ order_modes_im <- c("walk", "bike", "pt", "ride", "car", "pt_w_bike_used", "pt_w
 
 # Filter invalid modes and trip distances, also filter for weekdays
 relevant <- trips %>%
-  filter(kernwo == 2) %>%
-  filter(wegkm < 1000) %>%
+  filter(ST_WOTAG >= 2 & ST_WOTAG <= 4) %>%
+  filter(wegkm < 9994) %>%
+  filter(wegmin < 9994) %>%
   filter(hvm < 9) %>%
   mutate(dist=wegkm * 1000) %>%
   mutate(dist_group = cut(dist, breaks=breaks, labels=levels))

src/main/java/org/matsim/dashboard/MetropoleRuhrDashboardProvider.java

@@ -0,0 +1,25 @@
+package org.matsim.dashboard;
+
+import org.matsim.core.config.Config;
+import org.matsim.simwrapper.Dashboard;
+import org.matsim.simwrapper.DashboardProvider;
+import org.matsim.simwrapper.SimWrapper;
+import org.matsim.simwrapper.dashboard.TripDashboard;
+
+import java.util.List;
+
+/**
+ * Provider for default dashboards in the scenario.
+ * Declared in META-INF/services
+ */
+public class MetropoleRuhrDashboardProvider implements DashboardProvider {
+
+	@Override
+	public List<Dashboard> getDashboards(Config config, SimWrapper simWrapper) {
+
+		TripDashboard trips = new TripDashboard("mode_share_ref.csv", "mode_share_per_dist_ref.csv", "mode_users_ref.csv");
+
+		return List.of(trips);
+	}
+
+}

src/main/java/org/matsim/run/RunMetropoleRuhrScenario.java

@@ -77,7 +77,7 @@
 @MATSimApplication.Prepare({AdjustDemand.class})
 public class RunMetropoleRuhrScenario extends MATSimApplication {
 
-	public static final String VERSION = "v1.4";
+	public static final String VERSION = "v2.0";
 
 	private static final Logger log = LogManager.getLogger(RunMetropoleRuhrScenario.class);
 

src/main/python/calibrate.py

@@ -1,33 +1,9 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
-import os
-
-import pandas as pd
 import geopandas as gpd
-import numpy as np
-
-try:
-    # Use the matsim package if available
-    from matsim import calibration
-except:
-    # Alternatively, import calibration.py from same directory
-    import calibration
-
-# %%
-
-if os.path.exists("mid.csv"):
-    srv = pd.read_csv("mid.csv")
-    sim = pd.read_csv("sim.csv")
-
-    _, adj = calibration.calc_adjusted_mode_share(sim, srv)
-
-    print(srv.groupby("mode").sum())
-
-    print("Adjusted")
-    print(adj.groupby("mode").sum())
 
-    adj.to_csv("mid_adj.csv", index=False)
+from matsim.calibration import create_calibration, ASCCalibrator, utils
 
 # %%
 
@@ -44,11 +20,11 @@
 
 # Modal split target
 target = {
-    "walk": 0.205397,
-    "bike": 0.097191,
-    "pt":  0.120314,
-    "car": 0.456896,
-    "ride": 0.120203
+    "walk": 0.232118,
+    "bike": 0.098503,
+    "pt": 0.116146,
+    "car": 0.424297,
+    "ride": 0.128936
 }
 
 region = gpd.read_file("../scenarios/metropole-ruhr-v1.0/shape/dilutionArea.shp").set_crs("EPSG:25832")
@@ -70,13 +46,16 @@ def adjust_trips(df):
     return df
 
 
-study, obj = calibration.create_mode_share_study("calib", "matsim-metropole-ruhr-1.4.1-136d8aa.jar",
-                                                 "../scenarios/metropole-ruhr-v1.0/input/metropole-ruhr-v1.0-10pct.config.xml",
-                                                 modes, target,
-                                                 initial_asc=initial,
-                                                 args="--10pct",
-                                                 jvm_args="-Xmx68G -Xmx68G -XX:+AlwaysPreTouch",
-                                                 person_filter=f, map_trips=adjust_trips, chain_runs=True)
+study, obj = create_calibration(
+    "calib",
+    ASCCalibrator(modes, initial, target, lr=utils.linear_scheduler(start=0.3, interval=8)),
+    "matsim-metropole-ruhr-1.4.1-136d8aa.jar",
+    "../scenarios/metropole-ruhr-v1.0/input/metropole-ruhr-v1.0-10pct.config.xml",
+    args="--10pct",
+    jvm_args="-Xmx68G -Xmx68G -XX:+AlwaysPreTouch",
+    transform_persons=f, transform_trips=adjust_trips,
+    chain_runs=utils.default_chain_scheduler, debug=False
+)
 
 # %%
 

src/main/python/create_ref.py

@@ -1,26 +1,32 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
+import numpy as np
+
 from matsim.scenariogen.data import TripMode, run_create_ref_data
 
 
 def person_filter(df):
     """ Default person filter for reference data. """
-    return df[df.reporting_day <= 5]
+    # Tuesday to Thursday
+    return df[(df.reporting_day >= 2) & (df.reporting_day <= 4)]
 
 
 def trip_filter(df):
     # Motorcycles are counted as cars
     df.loc[df.main_mode == TripMode.MOTORCYCLE, "main_mode"] = TripMode.CAR
 
     # Other modes are ignored in the total share
-    # Long distance mode are ignored as well
-    return df[(df.main_mode != "other") & (df.gis_length < 100)]
+    return df[df.main_mode != "other"]
 
 
 if __name__ == "__main__":
-    person, trips, share = run_create_ref_data.create("../../../../shared-svn/projects/NaMAV/data/SrV_2018",
-                                                      person_filter, trip_filter,
-                                                      run_create_ref_data.InvalidHandling.REMOVE_PERSONS)
+    result = run_create_ref_data.create("../../../../shared-svn/projects/rvr-metropole-ruhr/data/MID",
+                                        person_filter, trip_filter,
+                                        dist_groups=[0, 1000, 2000, 5000, 10000, 20000, 50000, np.inf],
+                                        invalid_trip_handling=run_create_ref_data.InvalidHandling.REMOVE_TRIPS)
+
+    print(result.persons)
+    print(result.trips)
 
-    print(share)
+    print(result.share)

src/main/resources/META-INF/services/org.matsim.simwrapper.DashboardProvider

@@ -0,0 +1 @@
+org.matsim.dashboard.MetropoleRuhrDashboardProvider

src/main/resources/mode_share_per_dist_ref.csv

@@ -0,0 +1,36 @@
+dist_group,main_mode,share
+0 - 1000,bike,0.08922756652897382
+0 - 1000,car,0.14920930393728898
+0 - 1000,pt,0.01141689518127269
+0 - 1000,ride,0.05266112251043193
+0 - 1000,walk,0.6974851118420325
+1000 - 2000,bike,0.1412980387219933
+1000 - 2000,car,0.2893394369807224
+1000 - 2000,pt,0.07355118760590791
+1000 - 2000,ride,0.14803247616603515
+1000 - 2000,walk,0.3477788605253412
+2000 - 5000,bike,0.17022654579538898
+2000 - 5000,car,0.4199284767872729
+2000 - 5000,pt,0.15407708873488477
+2000 - 5000,ride,0.1477080914190836
+2000 - 5000,walk,0.10805979726336983
+5000 - 10000,bike,0.051336571850878795
+5000 - 10000,car,0.5939631205574252
+5000 - 10000,pt,0.1551416574021224
+5000 - 10000,ride,0.16658004372932197
+5000 - 10000,walk,0.03297860646025174
+10000 - 20000,bike,0.020809262401952737
+10000 - 20000,car,0.6675803912060924
+10000 - 20000,pt,0.1356469565014502
+10000 - 20000,ride,0.159567475292094
+10000 - 20000,walk,0.016395914598410645
+20000 - 50000,bike,0.016706269387170403
+20000 - 50000,car,0.6492250405860016
+20000 - 50000,pt,0.22408126032827708
+20000 - 50000,ride,0.09851721323716982
+20000 - 50000,walk,0.011470216461381298
+50000+,bike,0.04024152153627648
+50000+,car,0.6660439494130431
+50000+,pt,0.16140958352218981
+50000+,ride,0.13230494552849048
+50000+,walk,0.0

src/main/resources/mode_share_ref.csv

@@ -0,0 +1,36 @@
+dist_group,main_mode,share
+0 - 1000,bike,0.018274383327818906
+0 - 1000,car,0.030559031499997773
+0 - 1000,pt,0.0023382540516596684
+0 - 1000,ride,0.010785338843869218
+0 - 1000,walk,0.14284946676326818
+1000 - 2000,bike,0.02105728428475822
+1000 - 2000,car,0.043119514144725465
+1000 - 2000,pt,0.010961144831928345
+1000 - 2000,ride,0.022060900223378015
+1000 - 2000,walk,0.051828591539901575
+2000 - 5000,bike,0.046015457211230064
+2000 - 5000,car,0.11351461527397798
+2000 - 5000,pt,0.04164995330653673
+2000 - 5000,ride,0.03992829278587998
+2000 - 5000,walk,0.02921060845118482
+5000 - 10000,bike,0.008688445624977822
+5000 - 10000,car,0.10052514396940579
+5000 - 10000,pt,0.026256912098118687
+5000 - 10000,ride,0.028192799011838694
+5000 - 10000,walk,0.0055814562345485996
+10000 - 20000,bike,0.0023225644244755732
+10000 - 20000,car,0.07451001564319057
+10000 - 20000,pt,0.015139834818416709
+10000 - 20000,ride,0.017809652944835996
+10000 - 20000,walk,0.0018299816311333934
+20000 - 50000,bike,0.0011909299394746936
+20000 - 50000,car,0.04628092127404028
+20000 - 50000,pt,0.015973948199656557
+20000 - 50000,ride,0.007022938280156049
+20000 - 50000,walk,0.0008176705331116503
+50000+,bike,0.0009538829674380032
+50000+,car,0.01578787169708562
+50000+,pt,0.0038260445088857597
+50000+,ride,0.00313614965909456
+50000+,walk,0.0

src/main/resources/mode_users_ref.csv

@@ -0,0 +1,6 @@
+main_mode,user
+pt,0.1630445040891789
+car,0.3870760553176311
+ride,0.16700096730641525
+walk,0.3177808474256387
+bike,0.11064980061817771