bricegnichols · Nov 26, 2025 · Jul 8, 2024 · Jul 8, 2024 · Sep 13, 2024 · Sep 17, 2024
diff --git a/configs_dev/annotate_persons.csv b/configs_dev/annotate_persons.csv
@@ -38,6 +38,7 @@ school_segment university,school_segment,"np.where(is_university, SCHOOL_SEGMENT
 #,,
 is_worker,is_worker,"persons.pemploy.isin([PEMPLOY_FULL, PEMPLOY_PART])"
 ,is_out_of_home_worker,is_worker
+#,is_telecommuter,"np.where(persons.telework_time >= 3, True, False)"
 #,,
 home_zone_id,home_zone_id,"reindex(households.home_zone_id, persons.household_id)"
 ,_mean_work,distributed_time_factor_work_mean

diff --git a/configs_dev/cdap_coefficients.csv b/configs_dev/cdap_coefficients.csv
diff --git a/configs_dev/cdap_indiv_and_hhsize1.csv b/configs_dev/cdap_indiv_and_hhsize1.csv
diff --git a/configs_dev/disaggregate_accessibility.yaml b/configs_dev/disaggregate_accessibility.yaml
@@ -64,6 +64,7 @@ CREATE_TABLES:
             grade: 0                    # Not attending
             timeFactorWork: 1           # mean
             timeFactorNonWork: 1        # mean
+            telework_time: 0            # not teleworking
         mapped_fields:
             pnum:
                 age:

diff --git a/configs_dev/non_mandatory_tour_frequency.csv b/configs_dev/non_mandatory_tour_frequency.csv
diff --git a/configs_dev/non_mandatory_tour_frequency.yaml b/configs_dev/non_mandatory_tour_frequency.yaml
@@ -39,4 +39,5 @@ preprocessor:
   DF: persons
   TABLES:
     - tours
+    - households
 #    - accessibility
diff --git a/configs_dev/non_mandatory_tour_frequency_annotate_persons_preprocessor.csv b/configs_dev/non_mandatory_tour_frequency_annotate_persons_preprocessor.csv
@@ -2,9 +2,14 @@ Description,Target,Expression
 #,,
 ,max_window,person_max_window(persons)
 ,log_max_window,np.log1p(max_window)
-,medium_low_income,(persons.income_in_thousands > 20) & (persons.income_in_thousands <= 50)
-,medium_high_income,(persons.income_in_thousands > 50) & (persons.income_in_thousands <= 100)
-,high_income,(persons.income_in_thousands > 100)
+,total_hours_available_7am_to_10pm,"person_available_periods(persons, start_bin=7, end_bin=22, continuous=False) / 2"
+,max_consecutive_hours_available_7am_to_10pm,"person_available_periods(persons, start_bin=7, end_bin=22, continuous=True) / 2"
+,log_total_hours_available_7am_to_10pm,"np.log1p(total_hours_available_7am_to_10pm)"
+,log_max_consecutive_hours_available_7am_to_10pm,"np.log1p(max_consecutive_hours_available_7am_to_10pm)"
+,low_income,(persons.income_in_thousands <= 25)
+,medium_low_income,(persons.income_in_thousands > 25) & (persons.income_in_thousands <= 50)
+,medium_high_income,(persons.income_in_thousands > 100) & (persons.income_in_thousands <= 150)
+,high_income,(persons.income_in_thousands > 150)
 ,no_cars,(persons.auto_ownership == 0)
 ,car_sufficiency,persons.auto_ownership-persons.num_workers
 #,,

diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_DRIVING.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_DRIVING.csv
diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_FULL.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_FULL.csv
diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_NONWORK.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_NONWORK.csv
diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_PART.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_PART.csv
diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_PRESCHOOL.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_PRESCHOOL.csv
diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_RETIRED.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_RETIRED.csv
diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_SCHOOL.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_SCHOOL.csv
diff --git a/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_UNIVERSITY.csv b/configs_dev/non_mandatory_tour_frequency_coeffs_PTYPE_UNIVERSITY.csv
diff --git a/configs_dev/settings.yaml b/configs_dev/settings.yaml
@@ -6,8 +6,7 @@ expression_profile: True
 
 # number of households to simulate
 households_sample_size: 0
-
-
+disable_zarr: True
 #chunk_size: 
 #chunk_size: 123_000_000_000
 chunk_training_mode: explicit
@@ -131,6 +130,7 @@ models:
   - workplace_location
   - free_parking
   - telecommute_frequency
+  - telecommute_status
   - cdap_simulate
   - mandatory_tour_frequency
   - mandatory_tour_scheduling

diff --git a/configs_dev/telecommute_frequency.csv b/configs_dev/telecommute_frequency.csv
@@ -1,31 +1,32 @@
-Label,Description,Expression,No_Telecommute,1_day_week,2_3_days_week,4_days_week
-util_employment_density_at_work,log employment density work,@df.log_employment_density_at_work,0,coef_Emp_Density_At_Work_1day,coef_Emp_Density_At_Work_23day,coef_Emp_Density_At_Work_4day
-util_asc_KingCounty,King County constant,@df.county_id==1,0,coef_ASC_KingCounty_1day,coef_ASC_KingCounty_23day,coef_ASC_KingCounty_4day
-util_asc,asc constant,1,0,coef_ASC_1_day,coef_ASC_2_3_day,coef_ASC_4_day
-util_HasChildren0to5,Has children 0 to 5 years old,@df.has_young_children,0,coef_HasChildren0to5_1day,coef_HasChildren0to5_23day,coef_HasChildren0to5_4day
-util_HasChildren6to12,Has children 6 to 12 years old,@df.has_children_6_to_12,0,coef_HasChildren6to12_1day,coef_HasChildren6to12_23day,coef_HasChildren6to12_4day
-util_OneAdultInHH,One adult in hh,@df.num_adults==1,0,coef_OneAdultInHH_1day,coef_OneAdultInHH_23day,coef_OneAdultInHH_4day
-util_2plusAdultsInHH,2 or more adults in hh,@df.num_adults==2,0,coef_2plusAdultsInHH_1day,coef_2plusAdultsInHH_23day,coef_2plusAdultsInHH_4day
-util_Female,female,@df.sex==2,0,coef_Female_1day,coef_Female_23day,coef_Female_4day
-util_PartTimeWorker,Part-time worker,@df.pemploy==PEMPLOY_PART,0,coef_PartTimeWorker_1day,coef_PartTimeWorker_23day,coef_PartTimeWorker_4day
-util_CollegeStudent,College student,@df.ptype==PTYPE_UNIVERSITY,0,coef_CollegeStudent_1day,coef_CollegeStudent_23day,coef_CollegeStudent_4day
-util_PaysToPark,Pays to park,@df.pay_to_park_at_work,0,coef_PaysToPark_1day,coef_PaysToPark_23day,coef_PaysToPark_4day
-#util_PaysToPark,Pays to park,@~df.free_parking_at_work,0,coef_PaysToPark_1day,coef_PaysToPark_23day,coef_PaysToPark_4day
-util_missing_income,Missing Income,@df.income==-1,0,coef_MissingIncome_1day,coef_MissingIncome_23day,coef_MissingIncome_4day
-util_Income60to100k,Income 60-100k,@(df.income >= 60000) & (df.income < 100000),0,coef_Income60to100k_1day,coef_Income60to100k_23day,coef_Income60to100k_4day
-util_Income100to150k,Income 100-150k,@(df.income >= 100000) & (df.income < 150000),0,coef_Income100to150k_1day,coef_Income100to150k_23day,coef_Income100to150k_4day
-util_Income150to200k,Income 150-200k,@(df.income >= 150000) & (df.income < 200000),0,coef_Income150to200k_1day,coef_Income150to200k_23day,coef_Income150to200k_4day
-util_Income200kplus,Income 200k+,@df.income >=200000,0,coef_Income200kplus_1day,coef_Income200kplus_23day,coef_Income200kplus_4day
-util_0Autos,0 Autos,@df.auto_ownership==0,0,coef_0Autos_1day,coef_0Autos_23day,coef_0Autos_4day
-util_1Auto,1 Auto,@df.auto_ownership==1,0,coef_1Auto_1day,coef_1Auto_23day,coef_1Auto_4day
-util_3plusAutos,3+ Autos,@df.auto_ownership>=3,0,coef_3plusAutos_1day,coef_3plusAutos_23day,coef_3plusAutos_4day
-util_DistanceToWork,Distance to work,@np.log1p(df.distance_to_work),0,coef_DistanceToWork_1day,coef_DistanceToWork_23day,coef_DistanceToWork_4day
-util_workplace_AGREMPN_share,workplace AGR employment share,@df.workplace_AGREMPN_share,0,coef_WorkAGREMPNshare_1day,coef_WorkAGREMPNshare_23day,coef_WorkAGREMPNshare_4day
-util_workplace_FOOEMPN_share,workplace FOO employment share,@df.workplace_FOOEMPN_share,0,coef_WorkFOOEMPNshare_1day,coef_WorkFOOEMPNshare_23day,coef_WorkFOOEMPNshare_4day
-util_workplace_FPSEMPN_share,workplace FPS employment share,@df.workplace_FPSEMPN_share,0,coef_WorkFPSEMPNshare_1day,coef_WorkFPSEMPNshare_23day,coef_WorkFPSEMPNshare_4day
-util_workplace_HEREMPN_share,workplace HER employment share,@df.workplace_HEREMPN_share,0,coef_WorkHEREMPNshare_1day,coef_WorkHEREMPNshare_23day,coef_WorkHEREMPNshare_4day
-util_workplace_MWTEMPN_share,workplace MWT employment share,@df.workplace_MWTEMPN_share,0,coef_WorkMWTEMPNshare_1day,coef_WorkMWTEMPNshare_23day,coef_WorkMWTEMPNshare_4day
-util_workplace_OTHEMPN_share,workplace OTH employment share,@df.workplace_OTHEMPN_share,0,coef_WorkOTHEMPNshare_1day,coef_WorkOTHEMPNshare_23day,coef_WorkOTHEMPNshare_4day
-util_workplace_RETEMPN_share,workplace RET employment share,@df.workplace_RETEMPN_share,0,coef_WorkRETEMPNshare_1day,coef_WorkRETEMPNshare_23day,coef_WorkRETEMPNshare_4day
-util_Shopping_Maint_Accessibility,shopping accessiblity,@(df.shopping_accessibility + df.othdiscr_accessibility) / 2,0,coef_ShopMaintAcc_1day,coef_ShopMaint_23day,coef_ShopMaintAcc_4day
-#util_temp,temp_calibration,1,0,-4,-4.25,-6
+Label,Description,Expression,No_Telecommute,1_day_week,2_days_week,3_days_week,4_days_week
+util_employment_density_at_work,log employment density work,@df.log_employment_density_at_work,0,coef_Emp_Density_At_Work_1day,coef_Emp_Density_At_Work_23day,coef_Emp_Density_At_Work_23day,coef_Emp_Density_At_Work_4day
+util_asc_KingCounty,King County constant,@df.county_id==1,0,coef_ASC_KingCounty_1day,coef_ASC_KingCounty_23day,coef_ASC_KingCounty_23day,coef_ASC_KingCounty_4day
+util_asc,asc constant,1,0,coef_ASC_1_day,coef_ASC_2_3_day,coef_ASC_2_3_day,coef_ASC_4_day
+util_HasChildren0to5,Has children 0 to 5 years old,@df.has_young_children,0,coef_HasChildren0to5_1day,coef_HasChildren0to5_23day,coef_HasChildren0to5_23day,coef_HasChildren0to5_4day
+util_HasChildren6to12,Has children 6 to 12 years old,@df.has_children_6_to_12,0,coef_HasChildren6to12_1day,coef_HasChildren6to12_23day,coef_HasChildren6to12_23day,coef_HasChildren6to12_4day
+util_OneAdultInHH,One adult in hh,@df.num_adults==1,0,coef_OneAdultInHH_1day,coef_OneAdultInHH_23day,coef_OneAdultInHH_23day,coef_OneAdultInHH_4day
+util_2plusAdultsInHH,2 or more adults in hh,@df.num_adults==2,0,coef_2plusAdultsInHH_1day,coef_2plusAdultsInHH_23day,coef_2plusAdultsInHH_23day,coef_2plusAdultsInHH_4day
+util_Female,female,@df.sex==2,0,coef_Female_1day,coef_Female_23day,coef_Female_23day,coef_Female_4day
+util_PartTimeWorker,Part-time worker,@df.pemploy==PEMPLOY_PART,0,coef_PartTimeWorker_1day,coef_PartTimeWorker_23day,coef_PartTimeWorker_23day,coef_PartTimeWorker_4day
+util_CollegeStudent,College student,@df.ptype==PTYPE_UNIVERSITY,0,coef_CollegeStudent_1day,coef_CollegeStudent_23day,coef_CollegeStudent_23day,coef_CollegeStudent_4day
+util_PaysToPark,Pays to park,@df.pay_to_park_at_work,0,coef_PaysToPark_1day,coef_PaysToPark_23day,coef_PaysToPark_23day,coef_PaysToPark_4day
+#util_PaysToPark,Pays to park,@~df.free_parking_at_work,0,coef_PaysToPark_1day,coef_PaysToPark_23day,coef_PaysToPark_23day,coef_PaysToPark_4day
+util_missing_income,Missing Income,@df.income==-1,0,coef_MissingIncome_1day,coef_MissingIncome_23day,coef_MissingIncome_23day,coef_MissingIncome_4day
+util_Income60to100k,Income 60-100k,@(df.income >= 60000) & (df.income < 100000),0,coef_Income60to100k_1day,coef_Income60to100k_23day,coef_Income60to100k_23day,coef_Income60to100k_4day
+util_Income100to150k,Income 100-150k,@(df.income >= 100000) & (df.income < 150000),0,coef_Income100to150k_1day,coef_Income100to150k_23day,coef_Income100to150k_23day,coef_Income100to150k_4day
+util_Income150to200k,Income 150-200k,@(df.income >= 150000) & (df.income < 200000),0,coef_Income150to200k_1day,coef_Income150to200k_23day,coef_Income150to200k_23day,coef_Income150to200k_4day
+util_Income200kplus,Income 200k+,@df.income >=200000,0,coef_Income200kplus_1day,coef_Income200kplus_23day,coef_Income200kplus_23day,coef_Income200kplus_4day
+util_0Autos,0 Autos,@df.auto_ownership==0,0,coef_0Autos_1day,coef_0Autos_23day,coef_0Autos_23day,coef_0Autos_4day
+util_1Auto,1 Auto,@df.auto_ownership==1,0,coef_1Auto_1day,coef_1Auto_23day,coef_1Auto_23day,coef_1Auto_4day
+util_3plusAutos,3+ Autos,@df.auto_ownership>=3,0,coef_3plusAutos_1day,coef_3plusAutos_23day,coef_3plusAutos_23day,coef_3plusAutos_4day
+util_DistanceToWork,Distance to work,@np.log1p(df.distance_to_work),0,coef_DistanceToWork_1day,coef_DistanceToWork_23day,coef_DistanceToWork_23day,coef_DistanceToWork_4day
+util_workplace_AGREMPN_share,workplace AGR employment share,@df.workplace_AGREMPN_share,0,coef_WorkAGREMPNshare_1day,coef_WorkAGREMPNshare_23day,coef_WorkAGREMPNshare_23day,coef_WorkAGREMPNshare_4day
+util_workplace_FOOEMPN_share,workplace FOO employment share,@df.workplace_FOOEMPN_share,0,coef_WorkFOOEMPNshare_1day,coef_WorkFOOEMPNshare_23day,coef_WorkFOOEMPNshare_23day,coef_WorkFOOEMPNshare_4day
+util_workplace_FPSEMPN_share,workplace FPS employment share,@df.workplace_FPSEMPN_share,0,coef_WorkFPSEMPNshare_1day,coef_WorkFPSEMPNshare_23day,coef_WorkFPSEMPNshare_23day,coef_WorkFPSEMPNshare_4day
+util_workplace_HEREMPN_share,workplace HER employment share,@df.workplace_HEREMPN_share,0,coef_WorkHEREMPNshare_1day,coef_WorkHEREMPNshare_23day,coef_WorkHEREMPNshare_23day,coef_WorkHEREMPNshare_4day
+util_workplace_MWTEMPN_share,workplace MWT employment share,@df.workplace_MWTEMPN_share,0,coef_WorkMWTEMPNshare_1day,coef_WorkMWTEMPNshare_23day,coef_WorkMWTEMPNshare_23day,coef_WorkMWTEMPNshare_4day
+util_workplace_OTHEMPN_share,workplace OTH employment share,@df.workplace_OTHEMPN_share,0,coef_WorkOTHEMPNshare_1day,coef_WorkOTHEMPNshare_23day,coef_WorkOTHEMPNshare_23day,coef_WorkOTHEMPNshare_4day
+util_workplace_RETEMPN_share,workplace RET employment share,@df.workplace_RETEMPN_share,0,coef_WorkRETEMPNshare_1day,coef_WorkRETEMPNshare_23day,coef_WorkRETEMPNshare_23day,coef_WorkRETEMPNshare_4day
+util_Shopping_Maint_Accessibility,shopping accessiblity,@(df.shopping_accessibility + df.othdiscr_accessibility) / 2,0,coef_ShopMaintAcc_1day,coef_ShopMaint_23day,coef_ShopMaint_23day,coef_ShopMaintAcc_4day
+#util_temp,temp_calibration,1,0,-4,-4.25,-4.25,-6
+util_split_2_3_days_constant, Constant for splitting 2_3_days telecommute frequency,@np.log(0.5),,,1,1,
diff --git a/configs_dev/telecommute_status.csv b/configs_dev/telecommute_status.csv
@@ -0,0 +1,11 @@
+Label,Description,Expression,telecommuting,commuting
+util_no_commute,commute 0 day a week,@df.work_from_home,,coef_unavailable
+util_no_telecommute,telecommute 0 day a week,@df.telecommute_frequency=='No_Telecommute',coef_unavailable,
+util_commute_1_day_a_week,commute to work 1 day a week,@(df.telecommute_frequency=='4_days_week') * np.log(1),,coef_one
+util_telecommute_4_days_a_week,telecommute 4 days a week,@(df.telecommute_frequency=='4_days_week') * np.log(4),coef_one,
+util_commute_2_days_a_week,commute to work 2 days a week,@(df.telecommute_frequency=='3_days_week') * np.log(2),,coef_one
+util_telecommute_3_days_a_week,telecommute 3 days a week,@(df.telecommute_frequency=='3_days_week') * np.log(3),coef_one,
+util_commute_3_days_a_week,commute to work 3 days a week,@(df.telecommute_frequency=='2_days_week') * np.log(3),,coef_one
+util_telecommute_2_days_a_week,telecommute 2 days a week,@(df.telecommute_frequency=='2_days_week') * np.log(2),coef_one,
+util_commute_4_days_a_week,commute to work 4 days a week,@(df.telecommute_frequency=='1_day_week') * np.log(4),,coef_one
+util_telecommute_1_day_a_week,telecommute 1 day a week,@(df.telecommute_frequency=='1_day_week') * np.log(1),coef_one,
diff --git a/configs_dev/telecommute_status.yaml b/configs_dev/telecommute_status.yaml
@@ -0,0 +1,6 @@
+SPEC: telecommute_status.csv
+COEFFICIENTS: telecommute_status_coeffs.csv
+
+LOGIT_TYPE: MNL
+
+TELECOMMUTE_ALT: 0
diff --git a/configs_dev/telecommute_status_coeffs.csv b/configs_dev/telecommute_status_coeffs.csv
@@ -0,0 +1,3 @@
+coefficient_name,value,constrain
+coef_unavailable,-999,F
+coef_one,1,F