Merge pull request #19 from psrc/dev_RSG

Dev rsg
psrc · Mar 7, 2023 · 76b767d · 76b767d
2 parents 2cce800 + a7d0f20
commit 76b767d
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diff --git a/configs_dev/accessibility.csv b/configs_dev/accessibility.csv
@@ -3,15 +3,15 @@ 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', 'AM')] + skim_do[('SOVTOLL_TIME', 'PM')]"
+peak round trip distance,_auPkTime,"skim_od[('SOVTOLL_TIME_M', 'AM')] + skim_do[('SOVTOLL_TIME_M', 'PM')]"
 decay function,_decay, exp(_auPkTime * dispersion_parameter_automobile)
 auto peak retail,auPkRetail,df.RETEMPN * _decay
 auto peak total,auPkTotal,df.TOTEMP * _decay
 #,,
 #,, auto off-peak
 #,,
 #,, assume midday occurs entirely in the midday period
-off-peak round trip distance,_auOpTime,"skim_od[('SOVTOLL_TIME', 'MD')] + skim_do[('SOVTOLL_TIME', 'MD')]"
+off-peak round trip distance,_auOpTime,"skim_od[('SOVTOLL_TIME_M', 'MD')] + skim_do[('SOVTOLL_TIME_M', 'MD')]"
 decay function,_decay, exp(_auOpTime * dispersion_parameter_automobile)
 auto off-peak retail,auOpRetail,df.RETEMPN * _decay
 auto off-peak total,auOpTotal,df.TOTEMP * _decay

diff --git a/configs_dev/annotate_persons.csv b/configs_dev/annotate_persons.csv
@@ -36,3 +36,12 @@ school_segment university,school_segment,"np.where(is_university, SCHOOL_SEGMENT
 is_worker,is_worker,"persons.pemploy.isin([PEMPLOY_FULL, PEMPLOY_PART])"
 #,,
 home_zone_id,home_zone_id,"reindex(households.home_zone_id, persons.household_id)"
+,_mean_work,distributed_time_factor_work_mean
+,_stddev_work,distributed_time_factor_work_stddev
+,_mean_nonwork,distributed_time_factor_nonwork_mean
+,_stddev_nonwork,distributed_time_factor_nonwork_stddev
+,_min_time_factor,distributed_time_factor_min
+,_max_time_factor,distributed_time_factor_max
+#,,"Below expression was previously done using np.clip, but was producing a NotImplemented error for mixed DataFrame and Series Inputs.  Reimplemented using min & max"
+travel time sensitivity factor for work travel,time_factor_work,"np.minimum(_max_time_factor, np.maximum(rng.lognormal_for_df(persons, mu=_mean_work, sigma=_stddev_work), _min_time_factor))"
+travel time sensitivity factor for non-work travel,time_factor_nonwork,"np.minimum(_max_time_factor, np.maximum(rng.lognormal_for_df(persons, mu=_mean_nonwork, sigma=_stddev_nonwork), _min_time_factor))  "
diff --git a/configs_dev/annotate_persons_school.csv b/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', 'MD'))"
-temp auto_time_return,_auto_time_return,"skim_dict.lookup(persons.school_zone_id, persons.home_zone_id, ('SOV_TIME', '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'))"
 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)"
diff --git a/configs_dev/annotate_persons_workplace.csv b/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', 'MD'))"
-,_auto_time_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('SOV_TIME', 'MD'))"
+,_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'))"
 ,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

diff --git a/configs_dev/constants.yaml b/configs_dev/constants.yaml
@@ -61,3 +61,16 @@ PTYPE_NAME:
 CDAP_ACTIVITY_MANDATORY: M
 CDAP_ACTIVITY_NONMANDATORY: N
 CDAP_ACTIVITY_HOME: H
+
+# annotate persons: time_factor
+distributed_time_factor_work_mean: 1.0
+distributed_time_factor_work_stddev: 0.7
+distributed_time_factor_nonwork_mean: 1.0
+distributed_time_factor_nonwork_stddev: 0.6
+distributed_time_factor_min: 0.1
+distributed_time_factor_max: 10
+
+cost_share_s2: 2
+cost_share_s3: 3
+vot_threshold_low: 8.81
+vot_threshold_med: 18.00
diff --git a/configs_dev/joint_tour_scheduling_annotate_tours_preprocessor.csv b/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', 'MD'))"
-temp auto_time_return,_auto_time_return,"skim_dict.lookup(joint_tours.destination, joint_tours.origin, ('SOV_TIME', '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'))"
 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)"