🚀 [feat] vehicle type model

activitysim/abm/models/__init__.py

@@ -36,3 +36,5 @@
 from . import trip_scheduling_choice
 from . import trip_matrices
 from . import summarize
+from . import vehicle_allocation
+from . import vehicle_type_choice

activitysim/abm/models/atwork_subtour_mode_choice.py

@@ -10,6 +10,7 @@
 from activitysim.core import inject
 from activitysim.core import pipeline
 from activitysim.core import simulate
+from activitysim.core import expressions
 
 from activitysim.core import los
 from activitysim.core.pathbuilder import TransitVirtualPathBuilder
@@ -166,6 +167,15 @@ def atwork_subtour_mode_choice(
     assign_in_place(tours, choices_df)
     pipeline.replace_table("tours", tours)
 
+    # - annotate tours table
+    if model_settings.get('annotate_tours'):
+        tours = inject.get_table('tours').to_frame()
+        expressions.assign_columns(
+            df=tours,
+            model_settings=model_settings.get('annotate_tours'),
+            trace_label=tracing.extend_trace_label(trace_label, 'annotate_tours'))
+        pipeline.replace_table("tours", tours)
+
     if trace_hh_id:
         tracing.trace_df(tours[tours.tour_category == 'atwork'],
                          label=tracing.extend_trace_label(trace_label, mode_column_name),

activitysim/abm/models/tour_mode_choice.py

@@ -10,6 +10,7 @@
 from activitysim.core import config
 from activitysim.core import inject
 from activitysim.core import pipeline
+from activitysim.core import expressions
 from activitysim.core import simulate
 from activitysim.core import logit
 from activitysim.core.util import assign_in_place, reindex
@@ -353,6 +354,15 @@ def tour_mode_choice_simulate(tours, persons_merged,
 
     pipeline.replace_table("tours", all_tours)
 
+    # - annotate tours table
+    if model_settings.get('annotate_tours'):
+        tours = inject.get_table('tours').to_frame()
+        expressions.assign_columns(
+            df=tours,
+            model_settings=model_settings.get('annotate_tours'),
+            trace_label=tracing.extend_trace_label(trace_label, 'annotate_tours'))
+        pipeline.replace_table("tours", tours)
+
     if trace_hh_id:
         tracing.trace_df(primary_tours,
                          label=tracing.extend_trace_label(trace_label, mode_column_name),

activitysim/abm/models/util/canonical_ids.py

@@ -10,16 +10,17 @@
 logger = logging.getLogger(__name__)
 
 
-RANDOM_CHANNELS = ['households', 'persons', 'tours', 'joint_tour_participants', 'trips']
-TRACEABLE_TABLES = ['households', 'persons', 'tours', 'joint_tour_participants', 'trips']
+RANDOM_CHANNELS = ['households', 'persons', 'tours', 'joint_tour_participants', 'trips', 'vehicles']
+TRACEABLE_TABLES = ['households', 'persons', 'tours', 'joint_tour_participants', 'trips', 'vehicles']
 
 CANONICAL_TABLE_INDEX_NAMES = {
     'households': 'household_id',
     'persons': 'person_id',
     'tours': 'tour_id',
     'joint_tour_participants': 'participant_id',
     'trips': 'trip_id',
-    'land_use': 'zone_id'
+    'land_use': 'zone_id',
+    'vehicles': 'vehicle_id'
 }
 
 # unfortunately the two places this is needed (joint_tour_participation and estimation.infer

activitysim/abm/models/vehicle_allocation.py

@@ -0,0 +1,236 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import logging
+
+import pandas as pd
+import numpy as np
+import itertools
+import os
+
+from activitysim.core.interaction_simulate import interaction_simulate
+from activitysim.core import simulate
+from activitysim.core import tracing
+from activitysim.core import config
+from activitysim.core import inject
+from activitysim.core import pipeline
+from activitysim.core import expressions
+from activitysim.core import logit
+from activitysim.core import assign
+from activitysim.core import los
+
+from activitysim.core.util import assign_in_place
+
+from .util.mode import mode_choice_simulate
+from .util import estimation
+
+logger = logging.getLogger(__name__)
+
+
+def annotate_vehicle_allocation(model_settings, trace_label):
+    """
+    Add columns to the tours table in the pipeline according to spec.
+
+    Parameters
+    ----------
+    model_settings : dict
+    trace_label : str
+    """
+    tours = inject.get_table('tours').to_frame()
+    expressions.assign_columns(
+        df=tours,
+        model_settings=model_settings.get('annotate_tours'),
+        trace_label=tracing.extend_trace_label(trace_label, 'annotate_tours'))
+    pipeline.replace_table("tours", tours)
+
+
+def get_skim_dict(network_los, choosers):
+    """
+    Returns a dictionary of skim wrappers to use in expression writing.
+
+    Skims have origin as home_zone_id and destination as the tour destination.
+
+    Parameters
+    ----------
+    network_los : activitysim.core.los.Network_LOS object
+    choosers : pd.DataFrame
+
+    Returns
+    -------
+    skims : dict
+        index is skim wrapper name, value is the skim wrapper
+    """
+    skim_dict = network_los.get_default_skim_dict()
+    orig_col_name = 'home_zone_id'
+    dest_col_name = 'destination'
+
+    out_time_col_name = 'start'
+    in_time_col_name = 'end'
+    odt_skim_stack_wrapper = skim_dict.wrap_3d(orig_key=orig_col_name, dest_key=dest_col_name,
+                                               dim3_key='out_period')
+    dot_skim_stack_wrapper = skim_dict.wrap_3d(orig_key=dest_col_name, dest_key=orig_col_name,
+                                               dim3_key='in_period')
+
+    choosers['in_period'] = network_los.skim_time_period_label(choosers[in_time_col_name])
+    choosers['out_period'] = network_los.skim_time_period_label(choosers[out_time_col_name])
+
+    skims = {
+        "odt_skims": odt_skim_stack_wrapper.set_df(choosers),
+        "dot_skims": dot_skim_stack_wrapper.set_df(choosers),
+    }
+    return skims
+
+
+@inject.step()
+def vehicle_allocation(
+        persons,
+        households,
+        vehicles,
+        tours,
+        tours_merged,
+        network_los,
+        chunk_size,
+        trace_hh_id):
+    """Selects a vehicle for each occupancy level for each tour.
+
+    Alternatives consist of the up to the number of household vehicles plus one
+    option for non-household vehicles.
+
+    The model will be run once for each tour occupancy defined in the model yaml.
+    Output tour table will columns added for each occupancy level.
+
+    The user may also augment the `tours` tables with new vehicle
+    type-based fields specified via the annotate_tours option.
+
+    Parameters
+    ----------
+    persons : orca.DataFrameWrapper
+    households : orca.DataFrameWrapper
+    vehicles : orca.DataFrameWrapper
+    vehicles_merged : orca.DataFrameWrapper
+    tours : orca.DataFrameWrapper
+    tours_merged : orca.DataFrameWrapper
+    chunk_size : orca.injectable
+    trace_hh_id : orca.injectable
+    """
+    trace_label = 'vehicle_allocation'
+    model_settings_file_name = 'vehicle_allocation.yaml'
+    model_settings = config.read_model_settings(model_settings_file_name)
+
+    logsum_column_name = model_settings.get('MODE_CHOICE_LOGSUM_COLUMN_NAME')
+
+    estimator = estimation.manager.begin_estimation('vehicle_allocation')
+
+    model_spec_raw = simulate.read_model_spec(file_name=model_settings['SPEC'])
+    coefficients_df = simulate.read_model_coefficients(model_settings)
+    model_spec = simulate.eval_coefficients(model_spec_raw, coefficients_df, estimator)
+
+    nest_spec = config.get_logit_model_settings(model_settings)
+    constants = config.get_model_constants(model_settings)
+
+    locals_dict = {}
+    locals_dict.update(constants)
+    locals_dict.update(coefficients_df)
+
+    # ------ constructing alternatives from model spec and joining to choosers
+    vehicles_wide = vehicles.to_frame().pivot_table(
+        index='household_id', columns='vehicle_num',
+        values='vehicle_type', aggfunc=lambda x: ''.join(x))
+
+    alts_from_spec = model_spec.columns
+    # renaming vehicle numbers to alternative names in spec
+    vehicle_alt_columns_dict = {}
+    for veh_num in range(1, len(alts_from_spec)):
+        vehicle_alt_columns_dict[veh_num] = alts_from_spec[veh_num-1]
+    vehicles_wide.rename(columns=vehicle_alt_columns_dict, inplace=True)
+
+    # if the number of vehicles is less than the alternatives, fill with NA
+    # e.g. all households only have 1 or 2 vehicles because of small sample size,
+    #   still need columns for alternatives 3 and 4
+    for veh_num, col_name in vehicle_alt_columns_dict.items():
+        if col_name not in vehicles_wide.columns:
+            vehicles_wide[col_name] = ''
+
+    # last entry in spec is the non-hh-veh option
+    assert alts_from_spec[-1] == 'non_hh_veh', "Last option in spec needs to be non_hh_veh"
+    vehicles_wide[alts_from_spec[-1]] = ''
+
+    # merging vehicle alternatives to choosers
+    choosers = tours_merged.to_frame().reset_index()
+    choosers = pd.merge(choosers, vehicles_wide, how='left', on='household_id')
+    choosers.set_index('tour_id', inplace=True)
+
+    # ----- setup skim keys
+    skims = get_skim_dict(network_los, choosers)
+    locals_dict.update(skims)
+
+    # ------ preprocessor
+    preprocessor_settings = model_settings.get('preprocessor', None)
+    if preprocessor_settings:
+        expressions.assign_columns(
+            df=choosers,
+            model_settings=preprocessor_settings,
+            locals_dict=locals_dict,
+            trace_label=trace_label)
+
+    logger.info("Running %s with %d tours", trace_label, len(choosers))
+
+    if estimator:
+        estimator.write_model_settings(model_settings, model_settings_file_name)
+        estimator.write_spec(model_settings)
+        estimator.write_coefficients(coefficients_df, model_settings)
+        estimator.write_choosers(choosers)
+
+    tours = tours.to_frame()
+
+    # ------ running for each occupancy level selected
+    tours_veh_occup_cols = []
+    for occup in model_settings.get('OCCUPANCY_LEVELS', [1]):
+        logger.info("Running for occupancy = %d", occup)
+        # setting occup for access in spec expressions
+        locals_dict.update({'occup': occup})
+
+        choices = simulate.simple_simulate(
+            choosers=choosers,
+            spec=model_spec,
+            nest_spec=nest_spec,
+            skims=skims,
+            locals_d=locals_dict,
+            chunk_size=chunk_size,
+            trace_label=trace_label,
+            trace_choice_name='vehicle_allocation',
+            estimator=estimator)
+
+        # matching alt names to choices
+        choices = choices.map(dict(enumerate(alts_from_spec))).to_frame()
+        choices.columns = ['alt_choice']
+
+        # last alternative is the non-household vehicle option
+        for alt in alts_from_spec[:-1]:
+            choices.loc[choices['alt_choice'] == alt, 'choice'] = \
+                choosers.loc[choices['alt_choice'] == alt, alt]
+        choices.loc[choices['alt_choice'] == alts_from_spec[-1], 'choice'] = alts_from_spec[-1]
+
+        # creating a column for choice of each occupancy level
+        tours_veh_occup_col = f'vehicle_occup_{occup}'
+        tours[tours_veh_occup_col] = choices['choice']
+        tours_veh_occup_cols.append(tours_veh_occup_col)
+
+    if estimator:
+        estimator.write_choices(choices)
+        choices = estimator.get_survey_values(choices, 'households', 'vehicle_allocation')
+        estimator.write_override_choices(choices)
+        estimator.end_estimation()
+
+    pipeline.replace_table("tours", tours)
+
+    tracing.print_summary('vehicle_allocation', tours[tours_veh_occup_cols], value_counts=True)
+
+    annotate_settings = model_settings.get('annotate_tours', None)
+    if annotate_settings:
+        annotate_vehicle_allocation(model_settings, trace_label)
+
+    if trace_hh_id:
+        tracing.trace_df(tours,
+                         label='vehicle_allocation',
+                         warn_if_empty=True)