From 08ef98851e5dfa5ffdeda189ccb7f15b2ea288e7 Mon Sep 17 00:00:00 2001 From: Vivek Yadav Date: Thu, 18 Apr 2024 12:06:27 -0400 Subject: [PATCH] moving clip expressions to preprocessor for sharrow --- configs/resident/trip_mode_choice.csv | 42 +++++++++---------- ...ode_choice_annotate_trips_preprocessor.csv | 24 ++++++++++- 2 files changed, 44 insertions(+), 22 deletions(-) diff --git a/configs/resident/trip_mode_choice.csv b/configs/resident/trip_mode_choice.csv index a3500b0..cedab0c 100644 --- a/configs/resident/trip_mode_choice.csv +++ b/configs/resident/trip_mode_choice.csv @@ -52,7 +52,7 @@ util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@(odt_skims['WALK util_WALK_LOC_Walk_access_time,WALK_LOC - Walk access time,@(df.origin_local_time)* df.time_factor,,,,,,coef_acctime,,,,,,,,,,,,,,,,, util_WALK_LOC_Walk_egress_time,WALK_LOC - Walk egress time,@(df.dest_local_time)* df.time_factor,,,,,,coef_acctime,,,,,,,,,,,,,,,,, util_WALK_LOC_transfer_walk_time,WALK_LOC - transfer walk time,@(odt_skims['WALK_LOC_XFERWALK'])* df.time_factor,,,,,,coef_xwalk,,,,,,,,,,,,,,,,, -util_WALK_LOC_transfers_penalty,WALK_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['WALK_LOC_XFERS'], a_min=None,a_max=4))) * df.time_factor",,,,,,coef_xfer,,,,,,,,,,,,,,,,, +util_WALK_LOC_transfers_penalty,WALK_LOC - number of transfers,"@(-23+23*np.exp(0.414*df.clip_WALK_LOC_XFERS)) * df.time_factor",,,,,,coef_xfer,,,,,,,,,,,,,,,,, util_WALK_LOC_Fare,WALK_LOC - Fare,"@df.transitSubsidyPassDiscount*(odt_skims['WALK_LOC_FARE'])*100/(np.maximum(df.income,1000)**df.income_exponent)",,,,,,coef_income,,,,,,,,,,,,,,,,, util_WALK_LOC - Female,WALK_LOC - Female,@(df.female),,,,,,coef_female_tran,,,,,,,,,,,,,,,,, util_WALK_LOC - Origin Mix,WALK_LOC - Origin Mix,oMGRAMix,,,,,,coef_oMix_wTran,,,,,,,,,,,,,,,,, @@ -68,7 +68,7 @@ util_WALK_PRM_In_vehicle_time_on_URB,WALK_PRM - In-vehicle time on BRT,@(ivt_brt util_WALK_PRM_wait_time,WALK_PRM - wait time,@(odt_skims['WALK_PRM_FIRSTWAIT']) * df.time_factor,,,,,,,coef_wait,,,,,,,,,,,,,,,, util_WALK_PRM_transfer_wait_time,WALK_PRM - transfer wait time,@(odt_skims['WALK_PRM_XFERWAIT'])* df.time_factor,,,,,,,coef_xwait,,,,,,,,,,,,,,,, util_WALK_PRM_transfer_waLK_time,WALK_PRM - transfer walk time,@(odt_skims['WALK_PRM_XFERWALK'])* df.time_factor,,,,,,,coef_xwalk,,,,,,,,,,,,,,,, -util_WALK_PRM_transfers_penalty,WALK_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['WALK_PRM_XFERS'] + df.outbound*df.mtnev_egr_xfer_out + ~df.outbound*df.mtnev_acc_xfer_in, a_min=None,a_max=4))) * df.time_factor",,,,,,,coef_xfer,,,,,,,,,,,,,,,, +util_WALK_PRM_transfers_penalty,WALK_PRM - number of transfers,"@(-23+23*np.exp(0.414*df.clip_WALK_PRM_XFERS)) * df.time_factor",,,,,,,coef_xfer,,,,,,,,,,,,,,,, util_WALK_PRM_Walk_access_time,WALK_PRM - Walk access time,"@np.where(df.nev_access_available_in & ~df.outbound, df.nev_access_time_in, np.where(df.microtransit_access_available_in & ~df.outbound, df.microtransit_access_time_in, df.origin_prm_time))* df.time_factor",,,,,,,coef_acctime,,,,,,,,,,,,,,,, util_WALK_PRM_Walk_egress_time,WALK_PRM - Walk egress time,"@np.where(df.nev_egress_available_out & df.outbound, df.nev_egress_time_out, np.where(df.microtransit_egress_available_out & df.outbound, df.microtransit_egress_time_out, df.dest_prm_time))* df.time_factor",,,,,,,coef_acctime,,,,,,,,,,,,,,,, util_WALK_PRM_Fare,WALK_PRM - Fare,"@df.transitSubsidyPassDiscount*odt_skims['WALK_PRM_FARE']*100/(np.maximum(df.income,1000)**df.income_exponent)",,,,,,,coef_income,,,,,,,,,,,,,,,, @@ -86,7 +86,7 @@ util_WALK_MIX_In_vehicle_time_on_LTD_EXP,WALK_MIX - In-vehicle time on LTD and E util_WALK_MIX_In_vehicle_time_on_URB,WALK_MIX - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['WALK_MIX_BRTIVTT'])* df.time_factor,,,,,,,,coef_ivt,,,,,,,,,,,,,,, util_WALK_MIX_FIRST_wait_time,WALK_MIX - First wait time,@(odt_skims['WALK_MIX_FIRSTWAIT'])* df.time_factor,,,,,,,,coef_wait,,,,,,,,,,,,,,, util_WALK_MIX_transfer_wait_time,WALK_MIX - transfer wait time,@(odt_skims['WALK_MIX_XFERWAIT'])* df.time_factor,,,,,,,,coef_xwait,,,,,,,,,,,,,,, -util_WALK_MIX_number_of_transfers,WALK_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['WALK_MIX_XFERS'], a_min=None,a_max=4))) * df.time_factor",,,,,,,,coef_xfer,,,,,,,,,,,,,,, +util_WALK_MIX_number_of_transfers,WALK_MIX - number of transfers,"@(-23+23*np.exp(0.414*df.clip_WALK_MIX_XFERS)) * df.time_factor",,,,,,,,coef_xfer,,,,,,,,,,,,,,, util_WALK_MIX_Walk_access_time,WALK_MIX - Walk access time,@(df.origin_mix_time)* df.time_factor,,,,,,,,coef_acctime,,,,,,,,,,,,,,, util_WALK_MIX_Walk_egress_time,WALK_MIX - Walk egress time,@(df.dest_mix_time)* df.time_factor,,,,,,,,coef_acctime,,,,,,,,,,,,,,, util_WALK_MIX_Walk_other_time,WALK_MIX - Walk other time,@(odt_skims['WALK_MIX_XFERWALK'])* df.time_factor,,,,,,,,coef_xwalk,,,,,,,,,,,,,,, @@ -101,7 +101,7 @@ util_PNR_LOC_Unavailable,PNR_LOC - Unavailable,(pnr_local_available == False)|(P util_PNR_LOC_In_vehicle_time,PNR_LOC - In-vehicle time,@(odt_skims['PNROUT_LOC_TOTALIVTT'])* df.time_factor * df.outbound,,,,,,,,,coef_ivt,,,,,,,,,,,,,, util_PNR_LOC_iwait_time,PNR_LOC - First iwait time,@(odt_skims['PNROUT_LOC_FIRSTWAIT'])* df.time_factor * df.outbound,,,,,,,,,coef_wait,,,,,,,,,,,,,, util_PNR_LOC_transfer_wait_time,PNR_LOC - transfer wait time,@(odt_skims['PNROUT_LOC_XFERWAIT'])* df.time_factor * df.outbound,,,,,,,,,coef_xwait,,,,,,,,,,,,,, -util_PNR_LOC_number_of_transfers,PNR_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['PNROUT_LOC_XFERS'], a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,coef_xferdrive,,,,,,,,,,,,,, +util_PNR_LOC_number_of_transfers,PNR_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['PNROUT_LOC_XFERS'],None,4))) * df.time_factor * df.outbound",,,,,,,,,coef_xferdrive,,,,,,,,,,,,,, util_PNR_LOC_PNR_time,PNR_LOC - PNR time,@odt_skims['PNROUT_LOC_ACC']* df.time_factor * df.outbound,,,,,,,,,coef_acctime,,,,,,,,,,,,,, util_PNR_LOC_PNR_cost,PNR_LOC - PNR cost,"@(df.auto_op_cost * (odt_skims['PNROUT_LOC_ACC']) *driveSpeed)* df.outbound/(np.maximum(df.income,1000)**df.income_exponent)",,,,,,,,,coef_income,,,,,,,,,,,,,, util_PNRIN_LOC_PNR_cost,PNR_LOC - PNR cost,"@(df.auto_op_cost * (dot_skims['PNRIN_LOC_ACC']) *driveSpeed) * ~df.outbound/(np.maximum(df.income,1000)**df.income_exponent)",,,,,,,,,coef_income,,,,,,,,,,,,,, @@ -111,7 +111,7 @@ util_PNR_LOC_Fare_and_operating_cost,PNR_LOC - Fare ,"@df.transitSubsidyPassDisc util_PNRIN_LOC_In_vehicle_time,PNRIN_LOC - In-vehicle time,@(odt_skims['PNRIN_LOC_TOTALIVTT'])* df.time_factor * ~df.outbound,,,,,,,,,coef_ivt,,,,,,,,,,,,,, util_PNRIN_LOC_iwait_time,PNRIN_LOC - First iwait time,@(odt_skims['PNRIN_LOC_FIRSTWAIT']) * df.time_factor* ~df.outbound,,,,,,,,,coef_wait,,,,,,,,,,,,,, util_PNRIN_LOC_transfer_wait_time,PNRIN_LOC - transfer wait time,@(odt_skims['PNRIN_LOC_XFERWAIT'])* ~df.outbound,,,,,,,,,coef_xwait,,,,,,,,,,,,,, -util_PNRIN_LOC_number_of_transfers,PNRIN_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['PNRIN_LOC_XFERS'], a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,coef_xferdrive,,,,,,,,,,,,,, +util_PNRIN_LOC_number_of_transfers,PNRIN_LOC - number of transfers,"@(-23+23*np.exp(0.414*df.clip_PNRIN_LOC_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,coef_xferdrive,,,,,,,,,,,,,, util_PNRIN_LOC_PNRIN_time,PNRIN_LOC - PNR time,@odt_skims['PNRIN_LOC_EGR'] * df.time_factor * ~df.outbound,,,,,,,,,coef_acctime,,,,,,,,,,,,,, util_PNRIN_LOC_Walk_access_time,PNRIN_LOC - Walk access time,@(df.origin_local_time)* df.time_factor * ~df.outbound,,,,,,,,,coef_acctime,,,,,,,,,,,,,, util_PNRIN_LOC_Walk_other_time,PNRIN_LOC - Walk other time,@odt_skims['PNRIN_LOC_XFERWALK']* df.time_factor * ~df.outbound,,,,,,,,,coef_xwalk,,,,,,,,,,,,,, @@ -128,7 +128,7 @@ util_PNR_PRM_In_vehicle_time_on_LTD_EXP,PNR_PRM - In-vehicle time on LTD and EXP util_PNR_PRM_In_vehicle_time_on_URB,PNR_PRM - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['PNROUT_PRM_BRTIVTT']) * df.time_factor * df.outbound,,,,,,,,,,coef_ivt,,,,,,,,,,,,, util_PNR_PRM_FIRST_iwait_time,PNR_PRM - First iwait time,@(odt_skims['PNROUT_PRM_FIRSTWAIT']) * df.time_factor * df.outbound,,,,,,,,,,coef_wait,,,,,,,,,,,,, util_PNR_PRM_transfer_wait_time,PNR_PRM - transfer wait time,@(odt_skims['PNROUT_PRM_XFERWAIT']) * df.time_factor * df.outbound,,,,,,,,,,coef_xwait,,,,,,,,,,,,, -util_PNR_PRM_number_of_transfers,PNR_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['PNROUT_PRM_XFERS'] + df.mtnev_egr_xfer_out, a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,coef_xferdrive,,,,,,,,,,,,, +util_PNR_PRM_number_of_transfers,PNR_PRM - number of transfers,"@(-23+23*np.exp(0.414*df.clip_PRNOUT_PRM_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,coef_xferdrive,,,,,,,,,,,,, util_PNR_PRM_PNR_time,PNR_PRM - PNR time,@(odt_skims['PNROUT_PRM_ACC']) * df.time_factor * df.outbound,,,,,,,,,,coef_acctime,,,,,,,,,,,,, util_PNR_PRM_Walk_egress_time_(at_attraction_end),PNR_PRM - Walk egress time (at attraction end),"@np.where(df.nev_egress_available_out, df.nev_egress_time_out, np.where(df.microtransit_egress_available_out, df.microtransit_egress_time_out, df.dest_prm_time))* df.time_factor * df.outbound",,,,,,,,,,coef_acctime,,,,,,,,,,,,, util_PNR_PRM_Walk_other_time,PNR_PRM - Walk other time,@(odt_skims['PNROUT_PRM_XFERWALK']) * df.time_factor * df.outbound,,,,,,,,,,coef_xwalk,,,,,,,,,,,,, @@ -143,7 +143,7 @@ util_PNRIN_PRM_In_vehicle_time_on_LTD_EXP,PNRIN_PRM - In-vehicle time on LTD and util_PNRIN_PRM_In_vehicle_time_on_URB,PNRIN_PRM - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['PNRIN_PRM_BRTIVTT']) * df.time_factor * ~df.outbound,,,,,,,,,,coef_ivt,,,,,,,,,,,,, util_PNRIN_PRM_FIRST_iwait_time,PNRIN_PRM - First iwait time,@(odt_skims['PNRIN_PRM_FIRSTWAIT'])* df.time_factor * ~df.outbound,,,,,,,,,,coef_wait,,,,,,,,,,,,, util_PNRIN_PRM_transfer_wait_time,PNRIN_PRM - transfer wait time,@(odt_skims['PNRIN_PRM_XFERWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,coef_xwait,,,,,,,,,,,,, -util_PNRIN_PRM_number_of_transfers,PNRIN_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['PNRIN_PRM_XFERS'] + df.mtnev_acc_xfer_in, a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,coef_xferdrive,,,,,,,,,,,,, +util_PNRIN_PRM_number_of_transfers,PNRIN_PRM - number of transfers,"@(-23+23*np.exp(0.414*df.clip_PNRIN_PRM_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,coef_xferdrive,,,,,,,,,,,,, util_PNRIN_PRM_PNRIN_time,PNRIN_PRM - PNR time,@(odt_skims['PNRIN_PRM_EGR']) * df.time_factor * ~df.outbound,,,,,,,,,,coef_acctime,,,,,,,,,,,,, util_PNRIN_PRM_Walk_access_time_(at_attraction_end),PNRIN_PRM - Walk access time (at attraction end),"@np.where(df.nev_access_available_in, df.nev_access_time_in, np.where(df.microtransit_access_available_in, df.microtransit_access_time_in, df.origin_prm_time)) * df.time_factor * ~df.outbound",,,,,,,,,,coef_acctime,,,,,,,,,,,,, util_PNRIN_PRM_Walk_other_time,PNRIN_PRM - Walk other time,@(odt_skims['PNRIN_PRM_XFERWALK']) * df.time_factor * ~df.outbound,,,,,,,,,,coef_xwalk,,,,,,,,,,,,, @@ -160,7 +160,7 @@ util_PNR_MIX_In_vehicle_time_on_LTD_EXP,PNR_MIX - In-vehicle time on LTD and EXP util_PNR_MIX_In_vehicle_time_on_URB,PNR_MIX - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['PNROUT_MIX_BRTIVTT']) * df.time_factor * df.outbound,,,,,,,,,,,coef_ivt,,,,,,,,,,,, util_PNR_MIX_FIRST_iwait_time,PNR_MIX - First iwait time,@(odt_skims['PNROUT_MIX_FIRSTWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,coef_wait,,,,,,,,,,,, util_PNR_MIX_transfer_wait_time,PNR_MIX - transfer wait time,@(odt_skims['PNROUT_MIX_XFERWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,coef_xwait,,,,,,,,,,,, -util_PNR_MIX_number_of_transfers,PNR_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['PNROUT_MIX_XFERS'], a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,,coef_xferdrive,,,,,,,,,,,, +util_PNR_MIX_number_of_transfers,PNR_MIX - number of transfers,"@(-23+23*np.exp(0.414*df.clip_PNROUT_MIX_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,,coef_xferdrive,,,,,,,,,,,, util_PNR_MIX_PNR_time,PNR_MIX - PNR time,@odt_skims['PNROUT_MIX_ACC'] * df.time_factor * df.outbound,,,,,,,,,,,coef_acctime,,,,,,,,,,,, util_PNR_MIX_Walk_egress_time_(at_attraction_end),PNR_MIX - Walk egress time (at attraction end),@(df.dest_mix_time) * df.time_factor * df.outbound,,,,,,,,,,,coef_acctime,,,,,,,,,,,, util_PNR_MIX_Walk_other_time,PNR_MIX - Walk other time,@(odt_skims['PNROUT_MIX_XFERWALK']) * df.time_factor * df.outbound,,,,,,,,,,,coef_xwalk,,,,,,,,,,,, @@ -175,7 +175,7 @@ util_PNRIN_MIX_In_vehicle_time_on_LTD_EXP,PNRIN_MIX - In-vehicle time on LTD and util_PNRIN_MIX_In_vehicle_time_on_URB,PNRIN_MIX - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['PNRIN_MIX_BRTIVTT']) * df.time_factor * ~df.outbound,,,,,,,,,,,coef_ivt,,,,,,,,,,,, util_PNRIN_MIX_FIRST_iwait_time,PNRIN_MIX - First iwait time,@(odt_skims['PNRIN_MIX_FIRSTWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,coef_wait,,,,,,,,,,,, util_PNRIN_MIX_transfer_wait_time,PNRIN_MIX - transfer wait time,@(odt_skims['PNRIN_MIX_XFERWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,coef_xwait,,,,,,,,,,,, -util_PNRIN_MIX_number_of_transfers,PNRIN_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['PNRIN_MIX_XFERS'], a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,,coef_xferdrive,,,,,,,,,,,, +util_PNRIN_MIX_number_of_transfers,PNRIN_MIX - number of transfers,"@(-23+23*np.exp(0.414*df.clip_PNRIN_MIX_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,,coef_xferdrive,,,,,,,,,,,, util_PNRIN_MIX_PNRIN_time,PNRIN_MIX - PNR time,@odt_skims['PNRIN_MIX_EGR'] * df.time_factor * ~df.outbound,,,,,,,,,,,coef_acctime,,,,,,,,,,,, util_PNRIN_MIX_Walk_access_time_(at_attraction_end),PNRIN_MIX - Walk access time (at attraction end),@(df.origin_mix_time) * df.time_factor * ~df.outbound,,,,,,,,,,,coef_acctime,,,,,,,,,,,, util_PNRIN_MIX_Walk_other_time,PNRIN_MIX - Walk other time,@(odt_skims['PNRIN_MIX_XFERWALK']) * df.time_factor * ~df.outbound,,,,,,,,,,,coef_xwalk,,,,,,,,,,,, @@ -188,7 +188,7 @@ util_KNR_LOC_Unavailable,KNR_LOC - Unavailable,(knr_local_available == False)|(K util_KNR_LOC_In_vehicle_time,KNR_LOC - In-vehicle time,@(odt_skims['KNROUT_LOC_TOTALIVTT']) * df.time_factor * df.outbound,,,,,,,,,,,,coef_ivt,,,,,,,,,,, util_KNR_LOC_iwait_time,KNR_LOC - First iwait time,@(odt_skims['KNROUT_LOC_FIRSTWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,coef_wait,,,,,,,,,,, util_KNR_LOC_transfer_wait_time,KNR_LOC - transfer wait time,@(odt_skims['KNROUT_LOC_XFERWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,coef_xwait,,,,,,,,,,, -util_KNR_LOC_number_of_transfers,KNR_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['KNROUT_LOC_XFERS'], a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,,,coef_xferdrive,,,,,,,,,,, +util_KNR_LOC_number_of_transfers,KNR_LOC - number of transfers,"@(-23+23*np.exp(0.414*df.clip_KNROUT_LOC_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,,,coef_xferdrive,,,,,,,,,,, util_KNR_LOC_KNR_time,KNR_LOC - KNR time,@(odt_skims['KNROUT_LOC_ACC']) * df.time_factor * df.outbound,,,,,,,,,,,,coef_acctime,,,,,,,,,,, util_KNR_LOC_Walk_egress_time_(at_attraction_end),KNR_LOC - Walk egress time (at attraction end),@(df.dest_local_time) * df.time_factor * df.outbound,,,,,,,,,,,,coef_acctime,,,,,,,,,,, util_KNR_LOC_Walk_other_time,KNR_LOC - Walk other time,@(odt_skims['KNROUT_LOC_XFERWALK']) * df.time_factor * df.outbound,,,,,,,,,,,,coef_xwalk,,,,,,,,,,, @@ -198,7 +198,7 @@ util_KNRIN_LOC_KNR_cost,KNR_LOC - KNR cost,"@(df.auto_op_cost * df.autoCPMFactor util_KNRIN_LOC_In_vehicle_time,KNRIN_LOC - In-vehicle time,@(odt_skims['KNRIN_LOC_TOTALIVTT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,coef_ivt,,,,,,,,,,, util_KNRIN_LOC_iwait_time,KNRIN_LOC - First iwait time,@(odt_skims['KNRIN_LOC_FIRSTWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,coef_wait,,,,,,,,,,, util_KNRIN_LOC_transfer_wait_time,KNRIN_LOC - transfer wait time,@(odt_skims['KNRIN_LOC_XFERWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,coef_xwait,,,,,,,,,,, -util_KNRIN_LOC_number_of_transfers,KNRIN_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['KNRIN_LOC_XFERS'], a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,,,coef_xferdrive,,,,,,,,,,, +util_KNRIN_LOC_number_of_transfers,KNRIN_LOC - number of transfers,"@(-23+23*np.exp(0.414*df.clip_KNRIN_LOC_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,,,coef_xferdrive,,,,,,,,,,, util_KNRIN_LOC_KNRIN_time,KNRIN_LOC - KNR time,@odt_skims['KNRIN_LOC_EGR'] * df.time_factor * ~df.outbound,,,,,,,,,,,,coef_acctime,,,,,,,,,,, util_KNRIN_LOC_Walk_access_time,KNRIN_LOC - Walk access time,@df.origin_local_time * df.time_factor * ~df.outbound,,,,,,,,,,,,coef_acctime,,,,,,,,,,, util_KNRIN_LOC_Walk_other_time,KNRIN_LOC - Walk other time,@(odt_skims['KNRIN_LOC_XFERWALK']) * df.time_factor * ~df.outbound,,,,,,,,,,,,coef_xwalk,,,,,,,,,,, @@ -214,7 +214,7 @@ util_KNR_PRM_In_vehicle_time_on_LTD_EXP,KNR_PRM - In-vehicle time on LTD and EXP util_KNR_PRM_In_vehicle_time_on_URB,KNR_PRM - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['KNROUT_PRM_BRTIVTT']) * df.time_factor * df.outbound,,,,,,,,,,,,,coef_ivt,,,,,,,,,, util_KNR_PRM_FIRST_iwait_time,KNR_PRM - First iwait time,@(odt_skims['KNROUT_PRM_FIRSTWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,coef_wait,,,,,,,,,, util_KNR_PRM_transfer_wait_time,KNR_PRM - transfer wait time,@(odt_skims['KNROUT_PRM_XFERWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,coef_xwait,,,,,,,,,, -util_KNR_PRM_number_of_transfers,KNR_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['KNROUT_PRM_XFERS'] + df.mtnev_egr_xfer_out, a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,,,,coef_xferdrive,,,,,,,,,, +util_KNR_PRM_number_of_transfers,KNR_PRM - number of transfers,"@(-23+23*np.exp(0.414*df.clip_KNROUT_PRM_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,,,,coef_xferdrive,,,,,,,,,, util_KNR_PRM_KNR_time,KNR_PRM - KNR time,@(odt_skims['KNROUT_PRM_ACC']) * df.time_factor * df.outbound,,,,,,,,,,,,,coef_acctime,,,,,,,,,, util_KNR_PRM_Walk_egress_time_(at_attraction_end),KNR_PRM - Walk egress time (at attraction end),"@np.where(df.nev_egress_available_out, df.nev_egress_time_out, np.where(df.microtransit_egress_available_out, df.microtransit_egress_time_out, df.dest_prm_time)) * df.time_factor * df.outbound",,,,,,,,,,,,,coef_acctime,,,,,,,,,, util_KNR_PRM_Walk_other_time,KNR_PRM - Walk other time,@(odt_skims['KNROUT_PRM_XFERWALK']) * df.time_factor * df.outbound,,,,,,,,,,,,,coef_xwalk,,,,,,,,,, @@ -229,7 +229,7 @@ util_KNRIN_PRM_In_vehicle_time_on_LTD_EXP,KNRIN_PRM - In-vehicle time on LTD and util_KNRIN_PRM_In_vehicle_time_on_URB,KNRIN_PRM - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['KNRIN_PRM_BRTIVTT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,coef_ivt,,,,,,,,,, util_KNRIN_PRM_FIRST_iwait_time,KNRIN_PRM - First iwait time,@(odt_skims['KNRIN_PRM_FIRSTWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,coef_wait,,,,,,,,,, util_KNRIN_PRM_transfer_wait_time,KNRIN_PRM - transfer wait time,@(odt_skims['KNRIN_PRM_XFERWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,coef_xwait,,,,,,,,,, -util_KNRIN_PRM_number_of_transfers,KNRIN_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['KNRIN_PRM_XFERS'] + df.mtnev_acc_xfer_in, a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,,,,coef_xferdrive,,,,,,,,,, +util_KNRIN_PRM_number_of_transfers,KNRIN_PRM - number of transfers,"@(-23+23*np.exp(0.414*df.clip_KNRIN_PRM_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,,,,coef_xferdrive,,,,,,,,,, util_KNRIN_PRM_KNRIN_time,KNRIN_PRM - KNR time,@(odt_skims['KNRIN_PRM_EGR']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,coef_acctime,,,,,,,,,, util_KNRIN_PRM_Walk_access_time_(at_attraction_end),KNRIN_PRM - Walk access time (at attraction end),"@np.where(df.nev_access_available_in, df.nev_access_time_in, np.where(df.microtransit_access_available_in, df.microtransit_access_time_in, df.origin_prm_time)) * df.time_factor * ~df.outbound",,,,,,,,,,,,,coef_acctime,,,,,,,,,, util_KNRIN_PRM_Walk_other_time,KNRIN_PRM - Walk other time,@(odt_skims['KNRIN_PRM_XFERWALK']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,coef_xwalk,,,,,,,,,, @@ -246,7 +246,7 @@ util_KNR_MIX_In_vehicle_time_on_LTD_EXP,KNR_MIX - In-vehicle time on LTD and EXP util_KNR_MIX_In_vehicle_time_on_URB,KNR_MIX - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['KNROUT_MIX_BRTIVTT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,coef_ivt,,,,,,,,, util_KNR_MIX_FIRST_iwait_time,KNR_MIX - First iwait time,@(odt_skims['KNROUT_MIX_FIRSTWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,coef_wait,,,,,,,,, util_KNR_MIX_transfer_wait_time,KNR_MIX - transfer wait time,@(odt_skims['KNROUT_MIX_XFERWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,coef_xwait,,,,,,,,, -util_KNR_MIX_number_of_transfers,KNR_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['KNROUT_PRM_XFERS'], a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,,,,,coef_xferdrive,,,,,,,,, +util_KNR_MIX_number_of_transfers,KNR_MIX - number of transfers,"@(-23+23*np.exp(0.414*df.clip_KNROUT_MIX_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,,,,,coef_xferdrive,,,,,,,,, util_KNR_MIX_KNR_time,KNR_MIX - KNR time,@(odt_skims['KNROUT_MIX_ACC']) * df.time_factor * df.outbound,,,,,,,,,,,,,,coef_acctime,,,,,,,,, util_KNR_MIX_Walk_egress_time_(at_attraction_end),KNR_MIX - Walk egress time (at attraction end),@(df.dest_mix_time) * df.time_factor * df.outbound,,,,,,,,,,,,,,coef_acctime,,,,,,,,, util_KNR_MIX_Walk_other_time,KNR_MIX - Walk other time,@(odt_skims['KNROUT_MIX_XFERWALK']) * df.time_factor * df.outbound,,,,,,,,,,,,,,coef_xwalk,,,,,,,,, @@ -261,7 +261,7 @@ util_KNRIN_MIX_In_vehicle_time_on_LTD_EXP,KNRIN_MIX - In-vehicle time on LTD and util_KNRIN_MIX_In_vehicle_time_on_URB,KNRIN_MIX - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['KNRIN_MIX_BRTIVTT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,coef_ivt,,,,,,,,, util_KNRIN_MIX_FIRST_iwait_time,KNRIN_MIX - First iwait time,@(odt_skims['KNRIN_MIX_FIRSTWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,coef_wait,,,,,,,,, util_KNRIN_MIX_transfer_wait_time,KNRIN_MIX - transfer wait time,@(odt_skims['KNRIN_MIX_XFERWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,coef_xwait,,,,,,,,, -util_KNRIN_MIX_number_of_transfers,KNRIN_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['KNRIN_MIX_XFERS'], a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,coef_xferdrive,,,,,,,,, +util_KNRIN_MIX_number_of_transfers,KNRIN_MIX - number of transfers,"@(-23+23*np.exp(0.414*df.clip_KNRIN_MIX_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,coef_xferdrive,,,,,,,,, util_KNRIN_MIX_KNRIN_time,KNRIN_MIX - KNR time,@(odt_skims['KNRIN_MIX_EGR']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,coef_acctime,,,,,,,,, util_KNRIN_MIX_Walk_access_time_(at_attraction_end),KNRIN_MIX - Walk access time (at attraction end),@(df.origin_mix_time) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,coef_acctime,,,,,,,,, util_KNRIN_MIX_Walk_other_time,KNRIN_MIX - Walk other time,@(odt_skims['KNRIN_MIX_XFERWALK']) * ~df.outbound,,,,,,,,,,,,,,coef_xwalk,,,,,,,,, @@ -275,7 +275,7 @@ util_TNC_LOC_Unavailable_for_persons_less_than_16,TNC_LOC - Unavailable for pers util_TNC_LOC_In_vehicle_time,TNC_LOC - In-vehicle time,@(odt_skims['TNCOUT_LOC_TOTALIVTT'])* df.time_factor * df.outbound,,,,,,,,,,,,,,,coef_ivt,,,,,,,, util_TNC_LOC_iwait_time,TNC_LOC - First iwait time,@(odt_skims['TNCOUT_LOC_FIRSTWAIT'])* df.time_factor * df.outbound,,,,,,,,,,,,,,,coef_wait,,,,,,,, util_TNC_LOC_transfer_wait_time,TNC_LOC - transfer wait time,@odt_skims['TNCOUT_LOC_XFERWAIT']* df.time_factor * df.outbound,,,,,,,,,,,,,,,coef_xwait,,,,,,,, -util_TNC_LOC_number_of_transfers,TNC_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCOUT_LOC_XFERS'], a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,,,,,,coef_xferdrive,,,,,,,, +util_TNC_LOC_number_of_transfers,TNC_LOC - number of transfers,"@(-23+23*np.exp(0.414*df.clip_TNCOUT_LOC_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,,,,,,coef_xferdrive,,,,,,,, util_TNC_LOC_TNC_time,TNC_LOC - TNC time,@odt_skims['TNCOUT_LOC_ACC']* df.time_factor * df.outbound,,,,,,,,,,,,,,,coef_acctime,,,,,,,, util_TNC_LOC_Walk_egress_time_(at_attraction_end),TNC_LOC - Walk egress time (at attraction end),@df.dest_local_time* df.time_factor * df.outbound,,,,,,,,,,,,,,,coef_acctime,,,,,,,, util_TNC_LOC_Walk_other_time,TNC_LOC - Walk other time,@odt_skims['TNCOUT_LOC_XFERWALK']* df.time_factor * df.outbound,,,,,,,,,,,,,,,coef_xwalk,,,,,,,, @@ -283,7 +283,7 @@ util_TNC_LOC_Fare_and_operating_cost,TNC_LOC - Fare ,"@odt_skims['TNCOUT_LOC_FAR util_TNC_LOC_In_vehicle_time,TNC_LOC - In-vehicle time,@(odt_skims['TNCIN_LOC_TOTALIVTT'])* df.time_factor * ~df.outbound,,,,,,,,,,,,,,,coef_ivt,,,,,,,, util_TNC_LOC_iwait_time,TNC_LOC - First iwait time,@(odt_skims['TNCIN_LOC_FIRSTWAIT'])* df.time_factor * ~df.outbound,,,,,,,,,,,,,,,coef_wait,,,,,,,, util_TNC_LOC_transfer_wait_time,TNC_LOC - transfer wait time,@odt_skims['TNCIN_LOC_XFERWAIT']* df.time_factor * ~df.outbound,,,,,,,,,,,,,,,coef_xwait,,,,,,,, -util_TNC_LOC_number_of_transfers,TNC_LOC - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCIN_LOC_XFERS'], a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,coef_xferdrive,,,,,,,, +util_TNC_LOC_number_of_transfers,TNC_LOC - number of transfers,"@(-23+23*np.exp(0.414*df.clip_TNCIN_LOC_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,coef_xferdrive,,,,,,,, util_TNC_LOC_TNC_time,TNC_LOC - TNC time,@odt_skims['TNCIN_LOC_EGR']* df.time_factor * ~df.outbound,,,,,,,,,,,,,,,coef_acctime,,,,,,,, util_TNC_LOC_Walk_egress_time_(at_attraction_end),TNC_LOC - Walk egress time (at attraction end),@df.origin_local_time* df.time_factor * ~df.outbound,,,,,,,,,,,,,,,coef_acctime,,,,,,,, util_TNC_LOC_Walk_other_time,TNC_LOC - Walk other time,@odt_skims['TNCIN_LOC_XFERWALK']* df.time_factor * ~df.outbound,,,,,,,,,,,,,,,coef_xwalk,,,,,,,, @@ -300,7 +300,7 @@ util_TNC_PRM_In_vehicle_time_on_LTD_EXP,TNC_PRM - In-vehicle time on LTD and EXP util_TNC_PRM_In_vehicle_time_on_URB,TNC_PRM - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['TNCOUT_PRM_BRTIVTT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,coef_ivt,,,,,,, util_TNC_PRM_FIRST_iwait_time,TNC_PRM - First iwait time,@(odt_skims['TNCOUT_PRM_FIRSTWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,coef_wait,,,,,,, util_TNC_PRM_transfer_wait_time,TNC_PRM - transfer wait time,@(odt_skims['TNCOUT_PRM_XFERWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,coef_xwait,,,,,,, -util_TNC_PRM_number_of_transfers,TNC_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCOUT_PRM_XFERS'] + df.mtnev_acc_xfer_out + df.mtnev_egr_xfer_out, a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,,,,,,,coef_xferdrive,,,,,,, +util_TNC_PRM_number_of_transfers,TNC_PRM - number of transfers,"@(-23+23*np.exp(0.414*df.clip_TNCOUT_PRM_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,,,,,,,coef_xferdrive,,,,,,, util_TNC_PRM_TNC_time,TNC_PRM - TNC time,"@np.where(df.nev_access_available_out, df.nev_access_time_out, np.where(df.microtransit_access_available_out, df.microtransit_access_time_out, odt_skims['TNCOUT_PRM_ACC'])) * df.time_factor * df.outbound",,,,,,,,,,,,,,,,coef_acctime,,,,,,, util_TNC_PRM_Walk_egress_time_(at_attraction_end),TNC_PRM - Walk egress time (at attraction end),"@np.where(df.nev_egress_available_out, df.nev_egress_time_out, np.where(df.microtransit_egress_available_out, df.microtransit_egress_time_out, df.dest_prm_time)) * df.time_factor * df.outbound",,,,,,,,,,,,,,,,coef_acctime,,,,,,, util_TNC_PRM_Walk_other_time,TNC_PRM - Walk other time,@(odt_skims['TNCOUT_PRM_XFERWALK']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,coef_xwalk,,,,,,, @@ -313,7 +313,7 @@ util_TNCIN_PRM_In_vehicle_time_on_LTD_EXP,TNCIN_PRM - In-vehicle time on LTD and util_TNCIN_PRM_In_vehicle_time_on_URB,TNCIN_PRM - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['TNCIN_PRM_BRTIVTT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,coef_ivt,,,,,,, util_TNCIN_PRM_FIRST_iwait_time,TNCIN_PRM - First iwait time,@(odt_skims['TNCIN_PRM_FIRSTWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,coef_wait,,,,,,, util_TNCIN_PRM_transfer_wait_time,TNCIN_PRM - transfer wait time,@(odt_skims['TNCIN_PRM_XFERWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,coef_xwait,,,,,,, -util_TNCIN_PRM_number_of_transfers,TNCIN_PRM - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCIN_PRM_XFERS'] + df.mtnev_acc_xfer_in + df.mtnev_egr_xfer_in, a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,,coef_xferdrive,,,,,,, +util_TNCIN_PRM_number_of_transfers,TNCIN_PRM - number of transfers,"@(-23+23*np.exp(0.414*df.clip_TNCIN_PRM_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,,coef_xferdrive,,,,,,, util_TNCIN_PRM_TNCIN_time,TNCIN_PRM - TNC time,"@np.where(df.nev_egress_available_in, df.nev_egress_time_in, np.where(df.microtransit_egress_available_in, df.microtransit_egress_time_in, odt_skims['TNCIN_PRM_EGR'])) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,,coef_acctime,,,,,,, util_TNCIN_PRM_Walk_access_time_(at_attraction_end),TNCIN_PRM - Walk access time (at attraction end),"@np.where(df.nev_access_available_in, df.nev_access_time_in, np.where(df.microtransit_access_available_in, df.microtransit_access_time_in, df.origin_prm_time)) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,,coef_acctime,,,,,,, util_TNCIN_PRM_Walk_other_time,TNCIN_PRM - Walk other time,@(odt_skims['TNCOUT_PRM_XFERWALK']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,coef_xwalk,,,,,,, @@ -331,7 +331,7 @@ util_TNC_MIX_In_vehicle_time_on_LTD_EXP,TNC_MIX - In-vehicle time on LTD and EXP util_TNC_MIX_In_vehicle_time_on_URB,TNC_MIX - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['TNCOUT_MIX_BRTIVTT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,,coef_ivt,,,,,, util_TNC_MIX_FIRST_iwait_time,TNC_MIX - First iwait time,@(odt_skims['TNCOUT_MIX_FIRSTWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,,coef_wait,,,,,, util_TNC_MIX_transfer_wait_time,TNC_MIX - transfer wait time,@(odt_skims['TNCOUT_MIX_XFERWAIT']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,,coef_xwait,,,,,, -util_TNC_MIX_number_of_transfers,TNC_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCOUT_MIX_XFERS'], a_min=None,a_max=4))) * df.time_factor * df.outbound",,,,,,,,,,,,,,,,,coef_xferdrive,,,,,, +util_TNC_MIX_number_of_transfers,TNC_MIX - number of transfers,"@(-23+23*np.exp(0.414*df.clip_TNCOUT_MIX_XFERS)) * df.time_factor * df.outbound",,,,,,,,,,,,,,,,,coef_xferdrive,,,,,, util_TNC_MIX_TNC_time,TNC_MIX - TNC time,@(odt_skims['TNCOUT_MIX_ACC']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,,coef_acctime,,,,,, util_TNC_MIX_Walk_egress_time_(at_attraction_end),TNC_MIX - Walk egress time (at attraction end),@(df.dest_mix_time) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,,coef_acctime,,,,,, util_TNC_MIX_Walk_other_time,TNC_MIX - Walk other time,@(odt_skims['TNCOUT_MIX_XFERWALK']) * df.time_factor * df.outbound,,,,,,,,,,,,,,,,,coef_xwalk,,,,,, @@ -344,7 +344,7 @@ util_TNCIN_MIX_In_vehicle_time_on_LTD_EXP,TNCIN_MIX - In-vehicle time on LTD and util_TNCIN_MIX_In_vehicle_time_on_URB,TNCIN_MIX - In-vehicle time on BRT,@(ivt_brt_multiplier - 1) * (odt_skims['TNCIN_MIX_BRTIVTT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,,coef_ivt,,,,,, util_TNCIN_MIX_FIRST_iwait_time,TNCIN_MIX - First iwait time,@(odt_skims['TNCIN_MIX_FIRSTWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,,coef_wait,,,,,, util_TNCIN_MIX_transfer_wait_time,TNCIN_MIX - transfer wait time,@(odt_skims['TNCIN_MIX_XFERWAIT']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,,coef_xwait,,,,,, -util_TNCIN_MIX_number_of_transfers,TNCIN_MIX - number of transfers,"@(-23+23*np.exp(0.414*np.clip(odt_skims['TNCIN_MIX_XFERS'], a_min=None,a_max=4))) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,,,coef_xferdrive,,,,,, +util_TNCIN_MIX_number_of_transfers,TNCIN_MIX - number of transfers,"@(-23+23*np.exp(0.414*df.clip_TNCIN_MIX_XFERS)) * df.time_factor * ~df.outbound",,,,,,,,,,,,,,,,,coef_xferdrive,,,,,, util_TNCIN_MIX_TNCIN_time,TNCIN_MIX - TNC time,@(odt_skims['TNCIN_MIX_EGR']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,,coef_acctime,,,,,, util_TNCIN_MIX_Walk_access_time_(at_attraction_end),TNCIN_MIX - Walk access time (at attraction end),@(df.origin_mix_time) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,,coef_acctime,,,,,, util_TNCIN_MIX_Walk_other_time,TNCIN_MIX - Walk other time,@(odt_skims['TNCIN_MIX_XFERWALK']) * df.time_factor * ~df.outbound,,,,,,,,,,,,,,,,,coef_xwalk,,,,,, diff --git a/configs/resident/trip_mode_choice_annotate_trips_preprocessor.csv b/configs/resident/trip_mode_choice_annotate_trips_preprocessor.csv index 14dc62c..022c3ef 100644 --- a/configs/resident/trip_mode_choice_annotate_trips_preprocessor.csv +++ b/configs/resident/trip_mode_choice_annotate_trips_preprocessor.csv @@ -328,4 +328,26 @@ microtransit/nev access transfer,mtnev_acc_xfer_in,microtransit_access_available microtransit/nev egress transfer,mtnev_egr_xfer_out,microtransit_egress_available_out | nev_egress_available_out microtransit/nev egress transfer,mtnev_egr_xfer_in,microtransit_egress_available_in | nev_egress_available_in #,, -transit subsidi pass discount,transitSubsidyPassDiscount,"np.where(df.transit_pass_subsidy | df.transit_pass_ownership,0,1)" \ No newline at end of file +transit subsidi pass discount,transitSubsidyPassDiscount,"np.where(df.transit_pass_subsidy | df.transit_pass_ownership,0,1)" +#,, +clip_WALK_LOC_XFERS,clip_WALK_LOC_XFERS,"np.clip(odt_skims['WALK_LOC_XFERS'],a_min=None,a_max=4)" +clip_WALK_PRM_XFERS,clip_WALK_PRM_XFERS,"np.clip(odt_skims['WALK_PRM_XFERS'] + df.outbound*mtnev_egr_xfer_out + ~df.outbound*mtnev_acc_xfer_in, a_min=None,a_max=4)" +clip_WALK_MIX_XFERS,clip_WALK_MIX_XFERS,"np.clip(odt_skims['WALK_MIX_XFERS'], a_min=None,a_max=4)" +clip_PNROUT_LOC_XFERS,clip_PNROUT_LOC_XFERS,"np.clip(odt_skims['PNROUT_LOC_XFERS'], a_min=None,a_max=4)" +clip_PNRIN_LOC_XFERS,clip_PNRIN_LOC_XFERS,"np.clip(odt_skims['PNRIN_LOC_XFERS'], a_min=None,a_max=4)" +clip_PRNOUT_PRM_XFERS,clip_PRNOUT_PRM_XFERS,"np.clip(odt_skims['PNROUT_PRM_XFERS'] + mtnev_egr_xfer_out, a_min=None,a_max=4)" +clip_PNRIN_PRM_XFERS,clip_PNRIN_PRM_XFERS,"np.clip(odt_skims['PNRIN_PRM_XFERS'] + mtnev_acc_xfer_in, a_min=None,a_max=4)" +clip_PNROUT_MIX_XFERS,clip_PNROUT_MIX_XFERS,"np.clip(odt_skims['PNROUT_MIX_XFERS'], a_min=None,a_max=4)" +clip_PNRIN_MIX_XFERS,clip_PNRIN_MIX_XFERS,"np.clip(odt_skims['PNRIN_MIX_XFERS'], a_min=None,a_max=4)" +clip_KNROUT_LOC_XFERS,clip_KNROUT_LOC_XFERS,"np.clip(odt_skims['KNROUT_LOC_XFERS'], a_min=None,a_max=4)" +clip_KNRIN_LOC_XFERS,clip_KNRIN_LOC_XFERS,"np.clip(odt_skims['KNRIN_LOC_XFERS'], a_min=None,a_max=4)" +clip_KNROUT_PRM_XFERS,clip_KNROUT_PRM_XFERS,"np.clip(odt_skims['KNROUT_PRM_XFERS'] + mtnev_egr_xfer_out, a_min=None,a_max=4)" +clip_KNRIN_PRM_XFERS,clip_KNRIN_PRM_XFERS,"np.clip(odt_skims['KNRIN_PRM_XFERS'] + mtnev_acc_xfer_in, a_min=None,a_max=4)" +clip_KNROUT_MIX_XFERS,clip_KNROUT_MIX_XFERS,"np.clip(odt_skims['KNROUT_MIX_XFERS'], a_min=None,a_max=4)" +clip_KNRIN_MIX_XFERS,clip_KNRIN_MIX_XFERS,"np.clip(odt_skims['KNRIN_MIX_XFERS'], a_min=None,a_max=4)" +clip_TNCOUT_LOC_XFERS,clip_TNCOUT_LOC_XFERS,"np.clip(odt_skims['TNCOUT_LOC_XFERS'], a_min=None,a_max=4)" +clip_TNCIN_LOC_XFERS,clip_TNCIN_LOC_XFERS,"np.clip(odt_skims['TNCIN_LOC_XFERS'], a_min=None,a_max=4)" +clip_TNCOUT_PRM_XFERS,clip_TNCOUT_PRM_XFERS,"np.clip(odt_skims['TNCOUT_PRM_XFERS'] + mtnev_acc_xfer_out + mtnev_egr_xfer_out, a_min=None,a_max=4)" +clip_TNCIN_PRM_XFERS,clip_TNCIN_PRM_XFERS,"np.clip(odt_skims['TNCIN_PRM_XFERS'] + mtnev_acc_xfer_in + mtnev_egr_xfer_in, a_min=None,a_max=4)" +clip_TNCOUT_MIX_XFERS,clip_TNCOUT_MIX_XFERS,"np.clip(odt_skims['TNCOUT_MIX_XFERS'], a_min=None,a_max=4)" +clip_TNCIN_MIX_XFERS,clip_TNCIN_MIX_XFERS,"np.clip(odt_skims['TNCIN_MIX_XFERS'], a_min=None,a_max=4)" \ No newline at end of file