atwork_subtour_destination.py

# ActivitySim
# See full license in LICENSE.txt.

from __future__ import (absolute_import, division, print_function, )
from future.standard_library import install_aliases
install_aliases()  # noqa: E402

import logging

import pandas as pd

from activitysim.core import tracing
from activitysim.core import config
from activitysim.core import pipeline
from activitysim.core import simulate
from activitysim.core import inject

from activitysim.core.interaction_sample_simulate import interaction_sample_simulate
from activitysim.core.interaction_sample import interaction_sample
from activitysim.core.util import assign_in_place

from .util import logsums as logsum
from activitysim.abm.tables.size_terms import tour_destination_size_terms

logger = logging.getLogger(__name__)
DUMP = False


def atwork_subtour_destination_sample(
        tours,
        persons_merged,
        skim_dict,
        destination_size_terms,
        chunk_size, trace_hh_id):

    trace_label = 'atwork_subtour_location_sample'
    model_settings = config.read_model_settings('atwork_subtour_destination.yaml')
    model_spec = simulate.read_model_spec(file_name='atwork_subtour_destination_sample.csv')

    # merge persons into tours
    choosers = pd.merge(tours, persons_merged, left_on='person_id', right_index=True)
    # FIXME - MEMORY HACK - only include columns actually used in spec
    chooser_columns = model_settings['SIMULATE_CHOOSER_COLUMNS']
    choosers = choosers[chooser_columns]

    constants = config.get_model_constants(model_settings)

    sample_size = model_settings["SAMPLE_SIZE"]
    alt_dest_col_name = model_settings["ALT_DEST_COL_NAME"]

    logger.info("Running atwork_subtour_location_sample with %d tours", len(choosers))

    # create wrapper with keys for this lookup - in this case there is a workplace_taz
    # in the choosers and a TAZ in the alternatives which get merged during interaction
    # the skims will be available under the name "skims" for any @ expressions
    skims = skim_dict.wrap('workplace_taz', 'TAZ')

    locals_d = {
        'skims': skims
    }
    if constants is not None:
        locals_d.update(constants)

    choices = interaction_sample(
        choosers,
        alternatives=destination_size_terms,
        sample_size=sample_size,
        alt_col_name=alt_dest_col_name,
        spec=model_spec,
        skims=skims,
        locals_d=locals_d,
        chunk_size=chunk_size,
        trace_label=trace_label)

    # remember person_id in chosen alts so we can merge with persons in subsequent steps
    choices['person_id'] = choosers.person_id

    return choices


def atwork_subtour_destination_logsums(
        persons_merged,
        destination_sample,
        skim_dict, skim_stack,
        chunk_size, trace_hh_id):
    """
    add logsum column to existing atwork_subtour_destination_sample table

    logsum is calculated by running the mode_choice model for each sample (person, dest_taz) pair
    in atwork_subtour_destination_sample, and computing the logsum of all the utilities

    +-----------+--------------+----------------+------------+----------------+
    | person_id | dest_TAZ     | rand           | pick_count | logsum (added) |
    +===========+==============+================+============+================+
    | 23750     |  14          | 0.565502716034 | 4          |  1.85659498857 |
    +-----------+--------------+----------------+------------+----------------+
    + 23750     | 16           | 0.711135838871 | 6          | 1.92315598631  |
    +-----------+--------------+----------------+------------+----------------+
    + ...       |              |                |            |                |
    +-----------+--------------+----------------+------------+----------------+
    | 23751     | 12           | 0.408038878552 | 1          | 2.40612135416  |
    +-----------+--------------+----------------+------------+----------------+
    | 23751     | 14           | 0.972732479292 | 2          |  1.44009018355 |
    +-----------+--------------+----------------+------------+----------------+

    """

    trace_label = 'atwork_subtour_destination_logsums'

    model_settings = config.read_model_settings('atwork_subtour_destination.yaml')
    logsum_settings = config.read_model_settings(model_settings['LOGSUM_SETTINGS'])

    # FIXME - MEMORY HACK - only include columns actually used in spec
    persons_merged = logsum.filter_chooser_columns(persons_merged, logsum_settings, model_settings)

    # merge persons into tours
    choosers = pd.merge(destination_sample,
                        persons_merged,
                        left_on='person_id',
                        right_index=True,
                        how="left")

    logger.info("Running %s with %s rows", trace_label, len(choosers))

    tracing.dump_df(DUMP, persons_merged, trace_label, 'persons_merged')
    tracing.dump_df(DUMP, choosers, trace_label, 'choosers')

    tour_purpose = 'atwork'
    logsums = logsum.compute_logsums(
        choosers,
        tour_purpose,
        logsum_settings, model_settings,
        skim_dict, skim_stack,
        chunk_size, trace_hh_id,
        trace_label)

    destination_sample['mode_choice_logsum'] = logsums

    return destination_sample


def atwork_subtour_destination_simulate(
        subtours,
        persons_merged,
        destination_sample,
        skim_dict,
        destination_size_terms,
        chunk_size, trace_hh_id):
    """
    atwork_subtour_destination model on atwork_subtour_destination_sample
    annotated with mode_choice logsum to select a destination from sample alternatives
    """

    trace_label = 'atwork_subtour_destination_simulate'

    model_settings = config.read_model_settings('atwork_subtour_destination.yaml')
    model_spec = simulate.read_model_spec(file_name='atwork_subtour_destination.csv')

    # interaction_sample_simulate insists choosers appear in same order as alts
    subtours = subtours.sort_index()

    # merge persons into tours
    choosers = pd.merge(subtours,
                        persons_merged,
                        left_on='person_id', right_index=True)
    # FIXME - MEMORY HACK - only include columns actually used in spec
    chooser_columns = model_settings['SIMULATE_CHOOSER_COLUMNS']
    choosers = choosers[chooser_columns]

    alt_dest_col_name = model_settings["ALT_DEST_COL_NAME"]
    chooser_col_name = 'workplace_taz'

    # alternatives are pre-sampled and annotated with logsums and pick_count
    # but we have to merge destination_size_terms columns into alt sample list
    alternatives = \
        pd.merge(destination_sample, destination_size_terms,
                 left_on=alt_dest_col_name, right_index=True, how="left")

    tracing.dump_df(DUMP, alternatives, trace_label, 'alternatives')

    constants = config.get_model_constants(model_settings)

    logger.info("Running atwork_subtour_destination_simulate with %d persons", len(choosers))

    # create wrapper with keys for this lookup - in this case there is a TAZ in the choosers
    # and a TAZ in the alternatives which get merged during interaction
    # the skims will be available under the name "skims" for any @ expressions
    skims = skim_dict.wrap(chooser_col_name, alt_dest_col_name)

    locals_d = {
        'skims': skims,
    }
    if constants is not None:
        locals_d.update(constants)

    tracing.dump_df(DUMP, choosers, trace_label, 'choosers')

    choices = interaction_sample_simulate(
        choosers,
        alternatives,
        spec=model_spec,
        choice_column=alt_dest_col_name,
        skims=skims,
        locals_d=locals_d,
        chunk_size=chunk_size,
        trace_label=trace_label,
        trace_choice_name='workplace_location')

    return choices


@inject.step()
def atwork_subtour_destination(
        tours,
        persons_merged,
        skim_dict,
        skim_stack,
        land_use, size_terms,
        chunk_size, trace_hh_id):

    persons_merged = persons_merged.to_frame()

    tours = tours.to_frame()
    subtours = tours[tours.tour_category == 'atwork']

    # - if no atwork subtours
    if tours.shape[0] == 0:
        tracing.no_results('atwork_subtour_destination')
        return

    destination_size_terms = tour_destination_size_terms(land_use, size_terms, 'atwork')

    destination_sample = atwork_subtour_destination_sample(
        subtours,
        persons_merged,
        skim_dict,
        destination_size_terms,
        chunk_size, trace_hh_id)

    destination_sample = atwork_subtour_destination_logsums(
        persons_merged,
        destination_sample,
        skim_dict, skim_stack,
        chunk_size, trace_hh_id)

    choices = atwork_subtour_destination_simulate(
        subtours,
        persons_merged,
        destination_sample,
        skim_dict,
        destination_size_terms,
        chunk_size, trace_hh_id)

    subtours['destination'] = choices

    assign_in_place(tours, subtours[['destination']])

    pipeline.replace_table("tours", tours)

    tracing.print_summary('subtour destination', subtours.destination, describe=True)

    if trace_hh_id:
        tracing.trace_df(tours,
                         label='atwork_subtour_destination',
                         columns=['destination'])