added script to extract population data

matsim-scenarios · Aug 6, 2024 · c9ca320 · c9ca320
1 parent 88357c9
commit c9ca320
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Showing 4 changed files with 126 additions and 13 deletions.
diff --git a/Makefile b/Makefile
@@ -7,6 +7,7 @@ MEMORY ?= 20G
 JAR := matsim-$(N)-*.jar
 
 kyoto := ../public-svn/matsim/scenarios/countries/jp/kyoto
+confidential := ../shared-svn/projects/matsim-kyoto
 
 osmosis := osmosis/bin/osmosis
 
@@ -24,43 +25,36 @@ input/kansai.osm.pbf:
 
 input/network.osm: input/kansai.osm.pbf
 
-	# FIXME: Adjust level of details and area
-
 	$(osmosis) --rb file=$<\
 	 --tf accept-ways bicycle=yes highway=motorway,motorway_link,trunk,trunk_link,primary,primary_link,secondary_link,secondary,tertiary,motorway_junction,residential,unclassified,living_street\
-	 --bounding-polygon file="../shared-svn/projects/$N/data/area.poly"\
+	 --bounding-polygon file="input/area.poly"\
 	 --used-node --wb input/network-detailed.osm.pbf
 
 	$(osmosis) --rb file=$<\
 	 --tf accept-ways highway=motorway,motorway_link,trunk,trunk_link,primary,primary_link,secondary_link,secondary,tertiary,motorway_junction\
-	 --bounding-box top=51.92 left=11.45 bottom=50.83 right=13.36\
 	 --used-node --wb input/network-coarse.osm.pbf
 
-	$(osmosis) --rb file=$<\
-	 --tf accept-ways highway=motorway,motorway_link,motorway_junction,trunk,trunk_link,primary,primary_link\
-	 --used-node --wb input/network-germany.osm.pbf
 
-	$(osmosis) --rb file=input/network-germany.osm.pbf --rb file=input/network-coarse.osm.pbf --rb file=input/network-detailed.osm.pbf\
-  	 --merge --merge\
+	$(osmosis) --rb file=input/network-coarse.osm.pbf --rb file=input/network-detailed.osm.pbf\
+  	 --merge\
   	 --tag-transform file=input/remove-railway.xml\
   	 --wx $@
 
 	rm input/network-detailed.osm.pbf
 	rm input/network-coarse.osm.pbf
-	rm input/network-germany.osm.pbf
-
 
 input/sumo.net.xml: input/network.osm
 
 	$(SUMO_HOME)/bin/netconvert --geometry.remove --ramps.guess --ramps.no-split\
-	 --type-files $(SUMO_HOME)/data/typemap/osmNetconvert.typ.xml,$(SUMO_HOME)/data/typemap/osmNetconvertUrbanDe.typ.xml\
+	 --type-files $(SUMO_HOME)/data/typemap/osmNetconvert.typ.xml\
 	 --tls.guess-signals true --tls.discard-simple --tls.join --tls.default-type actuated\
 	 --junctions.join --junctions.corner-detail 5\
 	 --roundabouts.guess --remove-edges.isolated\
 	 --no-internal-links --keep-edges.by-vclass passenger,bicycle\
 	 --remove-edges.by-vclass hov,tram,rail,rail_urban,rail_fast,pedestrian\
 	 --output.original-names --output.street-names\
-	 --proj "+proj=utm +zone=53 +ellps=WGS84 +datum=WGS84 +units=m +no_defs"\
+	 --proj "+proj=utm +zone=53 +datum=WGS84 +units=m +no_defs"\
+	 --lefthand true
 	 --osm-files $< -o=$@
 
 

diff --git a/input/area.gpkg b/input/area.gpkg
diff --git a/input/area.poly b/input/area.poly
@@ -0,0 +1,48 @@
+26101001001
+1
+    135.73306751966228     34.87073344970929
+    135.73136033233789     34.87075299638351
+    135.72974358990282     34.87120532106917
+    135.59762830922838     34.923964796171695
+    135.59625597408223     34.924804541820436
+    135.59511567458847     34.92575628050391
+    135.59436440996362     34.926941605825384
+    135.5940682681097     34.92825627406589
+    135.55374249771842     35.1360553509106
+    135.5537017047248     35.137798206491034
+    135.55507396099628     35.154786309421894
+    135.5551811918037     35.15600937780549
+    135.55568575318512     35.157163475622625
+    135.584450355535     35.220492859394284
+    135.58508235914425     35.221573285574834
+    135.5854822787441     35.222073257668065
+    135.58689642543368     35.22327641771856
+    135.63373787093332     35.25976016576515
+    135.63428707280005     35.260154583120915
+    135.63629113691238     35.26157299086489
+    135.63661612131972     35.26174798609984
+    135.79227684372395     35.32516809539943
+    135.79373704613968     35.32566494849434
+    135.79530938467258     35.32580087577925
+    135.79686394802118     35.32556464681516
+    135.7988485911786     35.32501195332199
+    135.8105242695204     35.321299774608505
+    135.81189106881797     35.32070288935732
+    135.86079475870204     35.293247205920665
+    135.8621412834626     35.292452461528406
+    135.86313733948296     35.29136458518591
+    135.86504228537342     35.28738939817372
+    135.86615870500023     35.28404059023343
+    135.86629592495538     35.282670565935724
+    135.8841505317859     34.94744801911249
+    135.8841462130628     34.94734667094723
+    135.8838632494947     34.94606591651803
+    135.88314767698824     34.944905119127014
+    135.8830855117753     34.94483258961723
+    135.881914550447     34.94383615747787
+    135.84888627371598     34.92639040728104
+    135.84754883545472     34.92569676588468
+    135.73469888281187     34.871148584446594
+    135.73306751966228     34.87073344970929
+END
+END
diff --git a/src/main/python/extract_population_data.py b/src/main/python/extract_population_data.py
@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+import argparse
+import os
+
+import numpy as np
+from matsim.scenariogen.data import TripMode, preparation, run_create_ref_data
+from matsim.scenariogen.data.preparation import join_person_with_household, remove_persons_with_invalid_trips, \
+    create_activities
+
+
+def transform_persons(df):
+
+    # Filter on the shape file for kyoto
+    # "PREF" = 26  AND "CITY" IN (101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111)
+
+    df = df[df.location.isin(("26101", "26102", "26103", "26104", "26105", "26106", "26107", "26108", "26109", "26110", "26111"))]
+
+    df.loc[:, "age"] = preparation.cut(df.age, [0, 12, 18, 25, 35, 66, np.inf])
+
+    return df
+
+
+def trip_filter(df):
+    # Motorcycles are counted as cars
+    df.loc[df.main_mode == TripMode.MOTORCYCLE, "main_mode"] = TripMode.CAR
+
+    # Other mode are ignored in the total share
+    df = df[df.main_mode != TripMode.OTHER]
+
+    return df
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Converter for survey data")
+
+    parser.add_argument("-d", "--directory",
+                        help="Directory with the kyoto survey data",
+                        default=os.path.expanduser(
+                            "~/Development/matsim-scenarios/shared-svn/projects/matsim-kyoto/data/survey_2010"))
+
+    parser.add_argument("--output", default="table", help="Output prefix")
+
+    args = parser.parse_args()
+
+    result = run_create_ref_data.create(
+        args.directory, transform_persons, trip_filter,
+        invalid_trip_handling=run_create_ref_data.InvalidHandling.REMOVE_TRIPS,
+        ref_groups=["age"]
+    )
+
+    print(result.share)
+
+    hh, persons, trips = (result.all_hh, result.all_persons, result.all_trips)
+
+    # Motorcycles are counted as cars
+    trips.loc[trips.main_mode == TripMode.MOTORCYCLE, "main_mode"] = TripMode.CAR
+
+    hh.to_csv(args.output + "-households.csv")
+    trips.to_csv(args.output + "-trips.csv")
+
+    df = join_person_with_household(persons, hh)
+    df = remove_persons_with_invalid_trips(df, trips)
+
+    df.to_csv(args.output + "-persons.csv")
+
+    print("Written survey csvs with %d persons" % len(df))
+
+    activities = create_activities(df, trips, include_person_context=False, cut_groups=False)
+    activities.to_csv(args.output + "-activities.csv", index=False)