# input tables # # activitysim uses "well-known" index and foreign key names for imported tables (e.g. households, persons, land_use) # as well as for created tables (tours, joint_tour_participants, trips) # e.g. the households table must have an index column 'household_id' and the foreign key to households in the # persons table is also household_id. This naming convention allows activitysim to intuit the relationship # between tables - for instance, to ensure that multiprocess slicing includes all the persons, tours, and trips # in the same subprocess pipeline. The same strategy is also when chunking choosers, and to support tracing by # household_id. # # the input_table_list index_col directive instructs activitysim to set the imported table index to zone_id # you cannot change the well-known name of the index by modifying this directive. However, if your input file # has a different id column name, you can rename it to the required index name with the rename_columns directive. # In the settings below, the 'TAZ' column in the imported table is renamed 'zone_id' in the rename_columns settings. # input_table_list: # # households (table index 'household_id') # - tablename: households filename: households.csv index_col: household_id rename_columns: HHID: household_id # household_id is the required index column PERSONS: hhsize workers: num_workers VEHICL: auto_ownership TAZ: home_zone_id keep_columns: - home_zone_id - income - hhsize - HHT - auto_ownership - num_workers # # persons (table index 'person_id') # - tablename: persons filename: persons.csv index_col: person_id rename_columns: PERID: person_id # person_id is the required index column keep_columns: - household_id - age - PNUM - sex - pemploy - pstudent - ptype # # land_use (table index 'zone_id') # - tablename: land_use filename: land_use.csv index_col: zone_id rename_columns: TAZ: zone_id # person_id is the required index column COUNTY: county_id keep_columns: - DISTRICT - SD - county_id - TOTHH - TOTPOP - TOTACRE - RESACRE - CIACRE - TOTEMP - AGE0519 - RETEMPN - FPSEMPN - HEREMPN - OTHEMPN - AGREMPN - MWTEMPN - PRKCST - OPRKCST - area_type - HSENROLL - COLLFTE - COLLPTE - TOPOLOGY - TERMINAL # convert input CSVs to HDF5 format and save to outputs directory # create_input_store: True #input_store: ../output/input_data.h5 # number of households to simulate households_sample_size: 100 # simulate all households # households_sample_size: 0 # set false to disable variability check in simple_simulate and interaction_simulate check_for_variability: False # - shadow pricing global switches # turn shadow_pricing on and off for all models (e.g. school and work) # shadow pricing is deprecated for less than full samples # see shadow_pricing.yaml for additional settings use_shadow_pricing: False # turn writing of sample_tables on and off for all models # (if True, tables will be written if DEST_CHOICE_SAMPLE_TABLE_NAME is specified in individual model settings) want_dest_choice_sample_tables: False # log interaction simulate/sample expressions that return prohibitive utility values that exclude all alternatives log_alt_losers: False # alternate dir to read/write cache (defaults to output_dir) # used for skim cache, tvpb, and chunk_log caches #cache_dir: data/cache ############## # # chunking # # chooser chunk size in gigabytes # target top memory usage during activitysim run (including shared memory, loaded tables, and transient memory usage) #chunk_size: 12_000_000_000 chunk_size: 0 # minimum fraction of total chunk_size to reserve for adaptive chunking min_available_chunk_ratio: 0.05 # initial number of chooser rows for first chunk in training mode # when there is no pre-existing chunk_cache to set initial value # ordinarily bigger is better as long as it is not so big it causes memory issues (e.g. accessibility with lots of zones) default_initial_rows_per_chunk: 500 # method to calculate memory overhead when chunking is enabled (chunk_size > 0) chunk_method: hybrid_uss # chunk training mode # training to determine the chunking settings written to a cache file that is re-used for production runs # training # production chunk_training_mode: training # whether to preserve or delete subprocess chunk and mem logs when they are consolidated at end of multiprocess run keep_chunk_logs: True keep_mem_logs: True ############## # - tracing # trace household id; comment out or leave empty for no trace # households with all tour types # [ 728370 1234067 1402924 1594625 1595333 1747572 1896849 1931818 2222690 2344951 2677154] trace_hh_id: 982875 # trace origin, destination in accessibility calculation; comment out or leave empty for no trace # trace_od: [5, 11] trace_od: # to resume after last successful checkpoint, specify resume_after: _ #resume_after: trip_destination resume_after: checkpoints: True # if checkpoints is False, no intermediate checkpoints will be written before the end of run # (or if multiprocessing, at the end of each multiprocess_step) #checkpoints: False # explicit list of models to checkpoint #checkpoints: # - mandatory_tour_scheduling # - non_mandatory_tour_scheduling # - trip_mode_choice models: - initialize_landuse - initialize_households - compute_accessibility - school_location - workplace_location - auto_ownership_simulate - free_parking - cdap_simulate - mandatory_tour_frequency - mandatory_tour_scheduling - joint_tour_frequency - joint_tour_composition - joint_tour_participation - joint_tour_destination - joint_tour_scheduling - non_mandatory_tour_frequency - non_mandatory_tour_destination - non_mandatory_tour_scheduling - tour_mode_choice_simulate - atwork_subtour_frequency - atwork_subtour_destination - atwork_subtour_scheduling - atwork_subtour_mode_choice - stop_frequency - trip_purpose - trip_destination - trip_purpose_and_destination - trip_scheduling - trip_mode_choice - write_data_dictionary - track_skim_usage - write_trip_matrices - write_tables output_tables: h5_store: False action: include prefix: final_ tables: - checkpoints - accessibility - land_use - households - persons - tours - trips - joint_tour_participants # area_types less than this are considered urban urban_threshold: 4 cbd_threshold: 2 rural_threshold: 6 # - value of time min_value_of_time: 1 max_value_of_time: 50 distributed_vot_mu: 0.684 distributed_vot_sigma: 0.85 household_median_value_of_time: 1: 6.01 2: 8.81 3: 10.44 4: 12.86