Merge branch 'new_skims' into dev_RSG

Author: bricegnichols

configs_dev/accessibility.csv

@@ -3,28 +3,28 @@ Description,Target,Expression
 #,, auto peak
 #,,
 #,, assume peak occurs in AM for outbound and PM for inbound
-peak round trip distance,_auPkTime,"skim_od[('SOVTOLL_TIME_M', 'AM')] + skim_do[('SOVTOLL_TIME_M', 'PM')]"
+peak round trip distance,_auPkTime,"skim_od[('sov_inc2t', 'AM')] + skim_do[('sov_inc2t', 'PM')]"
 decay function,_decayauPk, exp(_auPkTime * dispersion_parameter_automobile)
 auto peak retail,auPkRetail,df.RETEMPN * _decayauPk
 auto peak total,auPkTotal,df.TOTEMP * _decayauPk
 #,,
 #,, auto off-peak
 #,,
 #,, assume midday occurs entirely in the midday period
-off-peak round trip distance,_auOpTime,"skim_od[('SOVTOLL_TIME_M', 'MD')] + skim_do[('SOVTOLL_TIME_M', 'MD')]"
+off-peak round trip distance,_auOpTime,"skim_od[('sov_inc2t', 'MD')] + skim_do[('sov_inc2t', 'MD')]"
 decay function,_decayauOp, exp(_auOpTime * dispersion_parameter_automobile)
 auto off-peak retail,auOpRetail,df.RETEMPN * _decayauOp
 auto off-peak total,auOpTotal,df.TOTEMP * _decayauOp
 #,,
 #,, transit peak
 #,,
 #,, assume peak outbound transit occurs in AM
-o-d peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'AM')]"
-o-d peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_TWAIT', 'AM')] + skim_od[('WLK_TRN_WLK_WAUX', 'AM')] "
+o-d peak transit ivt,_inVehicleTime,"skim_od[('ivtwa', 'AM')]"
+o-d peak transit ovt,_outOfVehicleTime,"skim_od[('twtwa', 'AM')] + skim_od[('auxwa', 'AM')] "
 o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) 
 #,, assume peak inbound transit occurs in PM
-d-o peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'PM')]"
-d-o peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_TWAIT', 'PM')] + skim_do[('WLK_TRN_WLK_WAUX', 'PM')] "
+d-o peak transit ivt,_inVehicleTime,"skim_do[('ivtwa', 'PM')]"
+d-o peak transit ovt,_outOfVehicleTime,"skim_do[('twtwa', 'PM')] + skim_do[('auxwa', 'PM')] "
 d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) 
 peak transit time,_trPkTime,_trPkTime_od + _trPkTime_do
 round trip path is available,_rt_available,(_trPkTime_od > 0) & (_trPkTime_do > 0)
@@ -35,12 +35,12 @@ transit peak total,trPkTotal,df.TOTEMP * _decaytrPk
 #,, transit off-peak
 #,,
 #,, assume off-peak outbound transit occurs in the MD time period
-o-d off-peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'MD')]"
-o-d off-peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_TWAIT', 'MD')] + skim_od[('WLK_TRN_WLK_WAUX', 'MD')] "
+o-d off-peak transit ivt,_inVehicleTime,"skim_od[('ivtwa', 'MD')]"
+o-d off-peak transit ovt,_outOfVehicleTime,"skim_od[('twtwa', 'MD')] + skim_od[('auxwa', 'MD')] "
 o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) 
 #,, assume off-peak inbound transit occurs in the MD time period
-d-o off-peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'MD')]"
-d-o off-peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_TWAIT', 'MD')] + skim_do[('WLK_TRN_WLK_WAUX', 'MD')] "
+d-o off-peak transit ivt,_inVehicleTime,"skim_do[('ivtwa', 'MD')]"
+d-o off-peak transit ovt,_outOfVehicleTime,"skim_do[('twtwa', 'MD')] + skim_do[('auxwa', 'MD')] "
 d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) 
 off-peak transit time,_trOpTime,_trOpTime_od + _trOpTime_do
 round trip path is available,_rt_available,(_trOpTime_od > 0) & (_trOpTime_do > 0)

configs_dev/annotate_persons_school.csv

@@ -2,6 +2,6 @@ Description,Target,Expression
 #,, annotate persons table after school_location model has run
 ,distance_to_school,"np.where(persons.school_zone_id>=0,skim_dict.lookup(persons.home_zone_id, persons.school_zone_id, 'DIST'),np.nan)"
 #,, this uses the free flow travel time in both directions. MTC TM1 was MD and MD
-temp auto_time_to_school,_auto_time_to_school,"skim_dict.lookup(persons.home_zone_id, persons.school_zone_id, ('SOV_TIME_M', 'MD'))"
-temp auto_time_return,_auto_time_return,"skim_dict.lookup(persons.school_zone_id, persons.home_zone_id, ('SOV_TIME_M', 'MD'))"
+temp auto_time_to_school,_auto_time_to_school,"skim_dict.lookup(persons.home_zone_id, persons.school_zone_id, ('sov_inc2t', 'MD'))"
+temp auto_time_return,_auto_time_return,"skim_dict.lookup(persons.school_zone_id, persons.home_zone_id, ('sov_inc2t', 'MD'))"
 free flow roundtrip_auto_time_to_school,roundtrip_auto_time_to_school,"np.where(persons.school_zone_id>=0,_auto_time_to_school + _auto_time_return,0)"

configs_dev/annotate_persons_workplace.csv

@@ -5,8 +5,8 @@ workplace_in_cbd,workplace_in_cbd,"reindex(land_use.area_type, persons.workplace
 work_zone_area_type,work_zone_area_type,"reindex(land_use.area_type, persons.workplace_zone_id)"
 #,, auto time to work - free flow travel time in both directions. MTC TM1 was MD and MD
 #,,roundtrip_auto_time_to_work
-,_auto_time_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('SOV_TIME_M', 'MD'))"
-,_auto_time_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('SOV_TIME_M', 'MD'))"
+,_auto_time_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('sov_inc2t', 'MD'))"
+,_auto_time_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('sov_inc2t', 'MD'))"
 ,roundtrip_auto_time_to_work,"np.where(persons.workplace_zone_id>=0,_auto_time_home_to_work + _auto_time_work_to_home,0)"
 #,,_roundtrip_walk_time_to_work
 ,_MAX_TIME_TO_WORK,999
@@ -16,11 +16,11 @@ work_zone_area_type,work_zone_area_type,"reindex(land_use.area_type, persons.wor
 ,_work_walk_available,(_walk_time_home_to_work > 0) & (_walk_time_work_to_home > 0)
 ,_roundtrip_walk_time_to_work,"np.where(_work_walk_available, _walk_time_home_to_work + _walk_time_work_to_home, _MAX_TIME_TO_WORK)"
 #,,_roundtrip_transit_time_to_work
-,_transit_ivt_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))"
-,_transit_ivt_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))"
+,_transit_ivt_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('ivtwa', 'MD'))"
+,_transit_ivt_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('ivtwa', 'MD'))"
 ,_work_transit_available,(_transit_ivt_home_to_work > 0) & (_transit_ivt_work_to_home > 0)
-,_transit_total_wait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_TWAIT', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_TWAIT', 'MD'))"
-,_transit_total_walk,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WAUX', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))"
+,_transit_total_wait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('twtwa', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('twtwa', 'MD'))"
+,_transit_total_walk,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('auxwa', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('auxwa', 'MD'))"
 ,_roundtrip_transit_time_to_work,_transit_ivt_home_to_work + _transit_ivt_work_to_home + _transit_total_wait + _transit_total_walk
 #,,work_auto_savings_ratio
 ,_min_work_walk_transit,"np.where(_work_transit_available, np.minimum(_roundtrip_transit_time_to_work, _roundtrip_walk_time_to_work), _roundtrip_walk_time_to_work)"

configs_dev/constants.yaml

@@ -11,6 +11,13 @@
 #HHT_NONFAMILY_FEMALE_ALONE: 6
 #HHT_NONFAMILY_FEMALE_NOTALONE: 7
 
+# Occupancy
+OCC_SHARED2: 2
+OCC_SHARED3: 3.33
+OCC_TAXI: 1.1
+OCC_TNC_SINGLE: 1.2
+OCC_TNC_SHARED: 2.0
+
 # convenience for expression files
 HHT_NONFAMILY: [4, 5, 6, 7]
 HHT_FAMILY: [1, 2, 3]

configs_dev/destination_choice_size_terms.csv

@@ -9,15 +9,15 @@ gradeschool,school,0,0,0,0,0,0,0,0,1,0,0,0
 highschool,school,0,0,0,0,0,0,0,0,0,1,0,0
 escort,non_mandatory,0,0.225,0,0.144,0,0,0,0,0.465,0.166,0,0
 shopping,non_mandatory,0,1,0,0,0,0,0,0,0,0,0,0
-eatout,non_mandatory,0,0.742,0,0.258,0,0,0,0,0,0,0,0
+eatout,non_mandatory,0,0.22313016,0,0,0,0,0,1,0,0,0,0
 othmaint,non_mandatory,0,0.482,0,0.518,0,0,0,0,0,0,0,0
 social,non_mandatory,0,0.522,0,0.478,0,0,0,0,0,0,0,0
 othdiscr,non_mandatory,0.252252252,0.212212212,0,0.272272272,0.165165165,0,0,0,0,0.098098098,0,0
 atwork,atwork,0,0.742,0,0.258,0,0,0,0,0,0,0,0
 work,trip,0,0.166666667,0.166666667,0.166666667,0.166666667,0.166666667,0.166666667,0,0,0,0,0
 escort,trip,0.001,0.225,0,0.144,0,0,0,0,0.464,0.166,0,0
 shopping,trip,0.001,0.999,0,0,0,0,0,0,0,0,0,0
-eatout,trip,0,0.742,0,0.258,0,0,0,0,0,0,0,0
+eatout,trip,0,0.22313016,0,0,0,0,0,1,0,0,0,0
 othmaint,trip,0.001,0.481,0,0.518,0,0,0,0,0,0,0,0
 social,trip,0.001,0.521,0,0.478,0,0,0,0,0,0,0,0
 othdiscr,trip,0.252252252,0.212212212,0,0.272272272,0.165165165,0,0,0,0,0.098098098,0,0

configs_dev/joint_tour_scheduling_annotate_tours_preprocessor.csv

@@ -1,8 +1,8 @@
 Description,Target,Expression
 destination in central business district,destination_in_cbd,"(reindex(land_use.area_type, joint_tours.destination) < setting('cbd_threshold')) * 1"
 #,, this uses the free flow travel time in both directions. MTC TM1 was MD and MD
-temp auto_time_to_destination,_auto_time_to_destination,"skim_dict.lookup(joint_tours.origin, joint_tours.destination, ('SOV_TIME_M', 'MD'))"
-temp auto_time_return,_auto_time_return,"skim_dict.lookup(joint_tours.destination, joint_tours.origin, ('SOV_TIME_M', 'MD'))"
+temp auto_time_to_destination,_auto_time_to_destination,"skim_dict.lookup(joint_tours.origin, joint_tours.destination, ('sov_inc2t', 'MD'))"
+temp auto_time_return,_auto_time_return,"skim_dict.lookup(joint_tours.destination, joint_tours.origin, ('sov_inc2t', 'MD'))"
 free flow roundtrip_auto_time,roundtrip_auto_time,"_auto_time_to_destination + _auto_time_return"
 #"number of joint tours that this joint tours point_person participates in",,
 ,num_person_joint_tours,"reindex_i(joint_tour_participants.groupby('person_id').size(), joint_tours.person_id)"

configs_dev/network_los.yaml

@@ -9,8 +9,8 @@ zone_system: 2
 
 # glob 'skims*.omx' will match one or more files: skims.omx, skims1.omx, skims2.omx...
 taz_skims: 
-  omx: skims*.omx
-  zarr: skims.zarr
+  omx: Skims*.omx
+  #zarr: skims.zarr
 
 
 maz: maz.csv

configs_dev/settings.yaml

@@ -2,11 +2,9 @@
 #sharrow: require
 
 # activitysim run -c configs -d data -o output
-
+expression_profile: True
 
 # number of households to simulate
-#households_sample_size:  100
-# simulate all households
 households_sample_size: 0
 disable_zarr: True
 #chunk_size: 
@@ -30,7 +28,8 @@ want_dest_choice_sample_tables: False
 
 # trace household id; comment out or leave empty for no trace
 # households with all tour types
-#trace_hh_id: 251535
+trace_hh_id: 562656
+cleanup_trace_files_on_resume: True
 
 
 # trace origin, destination in accessibility calculation; comment out or leave empty for no trace
@@ -46,7 +45,6 @@ input_table_list:
       HHID: household_id
       PERSONS: hhsize
       workers: num_workers
-      VEHICL: auto_ownership
       MAZ: home_zone_id
     recode_columns:
       home_zone_id: land_use.zone_id
@@ -118,8 +116,7 @@ input_table_list:
     recode_columns:
       TAZ: zero-based
 # to resume after last successful checkpoint, specify resume_after: _
-#resume_after: trip_scheduling
-
+#resume_after: auto_ownership_simulate
 models:
   ## Disaggregate Accessibility steps
   - initialize_proto_population # Separate step so proto tables can be split for multiprocess.
@@ -158,7 +155,7 @@ models:
   - trip_mode_choice
   - write_data_dictionary
   - track_skim_usage
-#  - write_trip_matrices
+  - write_trip_matrices
   - write_tables