
.. index:: tutorial
.. index:: example
.. _example :
.. _examples :

Examples
========

This page describes the example models included with ActivitySim. There are three
basic types of example model:

* "production" examples are calibrated and validated by the relevant agency, and
  are intended to be replicas of an "official" travel model used by that agency,
  although generally we expect agencies to maintain independent repositories and
  not rely on the Consortium maintained version as a single source for the model.
  At this time there are no production examples in the consortium's collection,
  but we expect that to change soon.
* "prototype" examples are not representative of any "official" travel model
  used by the relevant agency, but they are viewed as "ok" models by the
  consortium: they are usually at least loosely calibrated and/or validated, and
  typically contain at least some components or parameters specialized for the
  relevant region. They may be in-development models that are not quite finished,
  or consortium maintained models that are derived from but now different from
  the official model of some region. They should not be used in place of
  "official" models for policy analysis in any given region, but could serve as
  a donor model for new users who want to implement ActivitySim somewhere new
  (subject to all the caveats that go along with transferring models).
* "placeholder" examples are computational testbeds that technically run but
  have not been calibrated nor validated in any meaningful way. These examples
  are early stage development models used for testing purposes, and users are
  strongly cautioned not to use them for any policy or planning purpose.

The current examples are:

+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| Example                         | Purpose                                                   | Zone Systems | Status               |
+=================================+===========================================================+==============+======================+
| :ref:`prototype_mtc`            | Original ActivitySim Example, derived from MTC TM1        | 1            | Mature               |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`prototype_mtc_extended`   | Prototype MTC example with additional optional models     | 1            | In development       |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`example_estimation`       | Estimation example with prototype_mtc                     | 1            | Mature               |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`placeholder_multiple_zone`| 2 or 3 zone system example using MTC data                 | 2 or 3       | Simple test example  |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`prototype_marin`          | 3 zone system example using Marin tour mode choice model  | 3            | Mature               |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`prototype_arc`            | ARC agency example                                        | 1            | In development       |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`prototype_semcog`         | SEMCOG agency example                                     | 1            | In development       |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`placeholder_psrc`         | PSRC agency example                                       | 2            | Future development   |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`placeholder_sandag`       | SANDAG agency example                                     | 3            | Future development   |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`prototype_sandag_xborder` | SANDAG agency example                                     | 3            | In development       |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+
| :ref:`prototype_mwcog`          | MWCOG agency example                                      | 2            | In development       |
+---------------------------------+-----------------------------------------------------------+--------------+----------------------+

.. note::
   The `example_manifest.yaml <https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_manifest.yaml>`_
   contains example commands to create and run several versions of the examples.  See also :ref:`adding_agency_examples` for more
   information on agency example models.

.. _prototype_mtc :

prototype_mtc
-------------

The initial example implemented in ActivitySim was prototype_mtc.  This section described the prototype_mtc
model design, how to setup and run the example, and how to review outputs. The default configuration of the
example is limited to a small sample of households and zones so that it can be run quickly and require
less than 1 GB of RAM.  The full scale example can be configured and run as well.

Model Design
~~~~~~~~~~~~

The prototype_mtc example is based on (but has evolved away from) the
`Bay Area Metro Travel Model One <https://github.com/BayAreaMetro/travel-model-one>`__ (TM1).
TM1 has its roots in a wide array of analytical approaches, including discrete
choice forms (multinomial and nested logit models), activity duration models, time-use models,
models of individual micro-simulation with constraints, entropy-maximization models, etc.
These tools are combined in the model design to realistically represent travel behavior,
adequately replicate observed activity-travel patterns, and ensure model sensitivity to
infrastructure and policies. The model is implemented in a micro-simulation framework. Microsimulation
methods capture aggregate outcomes through the representation of the behavior of
individual decision-makers.

Space
^^^^^

The prototype MTC model uses the 1454 TAZ zone system developed for the MTC trip-based model.  The zones are fairly large for the region,
which may somewhat distort the representation of transit access in mode choice. To ameliorate this problem, the
original model zones were further sub-divided into three categories of transit access: short walk, long walk, and not
walkable.  However, support for transit subzones is not included in the activitysim implementation since the latest generation
of activity-based models typically use an improved approach to spatial representation called multiple zone systems.  See
:ref:`multiple_zone_systems` for more information.

Decision-making units
^^^^^^^^^^^^^^^^^^^^^

Decision-makers in the model system are households and persons. These decision-makers are
created for each simulation year based on a population synthesis process such as
`PopulationSim <https://github.com/ActivitySim/PopulationSim>`__. The decision-makers are used in the
subsequent discrete-choice models to select a single alternative from a list of available
alternatives according to a probability distribution. The probability distribution is generated
from various logit-form models which take into account the attributes of the decision-maker and
the attributes of the various alternatives. The decision-making unit is an important element of
model estimation and implementation, and is explicitly identified for each model.

Person type segmentation
^^^^^^^^^^^^^^^^^^^^^^^^

TM1 is implemented in a micro-simulation framework. A key advantage of the
micro-simulation approach is that there are essentially no computational constraints on the
number of explanatory variables which can be included in a model specification. However, even
with this flexibility, the model system includes some segmentation of decision-makers.
Segmentation is a useful tool both to structure models and also as a way to characterize person
roles within a household.

The person types shown below are used for the example model. The person types are mutually exclusive
with respect to age, work status, and school status.

+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| Person Type Code | Person Type                                               | Age     | Work Status      | School Status |
+==================+===========================================================+=========+==================+===============+
| 1                | Full-time worker (30+ hours a week)                       | 18+     | Full-time        | None          |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| 2                | Part-time worker (<30 hours but works on a regular basis) | 18+     | Part-time        | None          |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| 3                | College student                                           | 18+     | Any              | College       |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| 4                | Non-working adult                                         | 18 - 64 | Unemployed       | None          |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| 5                | Retired person                                            | 65+     | Unemployed       | None          |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| 6                | Driving age student                                       | 16 - 17 | Any              | Pre-college   |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| 7                | Non-driving student                                       | 6 - 16  | None             | Pre-college   |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+
| 8                | Pre-school child                                          | 0 - 5   | None             | Preschool     |
+------------------+-----------------------------------------------------------+---------+------------------+---------------+

Household type segments are useful for pre-defining certain data items (such as destination
choice size terms) so that these data items can be pre-calculated for each segment. Precalculation
of these data items reduces model complexity and runtime. The segmentation is based on household income,
and includes four segments - low, medium, high, very high.

In the model, the persons in each household are assigned a simulated but fixed value of time
that modulates the relative weight the decision-maker places on time and cost. The probability
distribution from which the value of time is sampled was derived from a toll choice model
estimated using data from a stated preference survey performed for the SFCTA Mobility, Access, and
Pricing Study, and is a lognormal distribution with a mean that varies by income segment.

Activity type segmentation
^^^^^^^^^^^^^^^^^^^^^^^^^^

The activity types are used in most model system components, from developing daily activity patterns
and to predicting tour and trip destinations and modes by purpose.  The set of activity types is shown below.
The activity types are also grouped according to whether the activity is mandatory or non-mandatory and
eligibility requirements are assigned determining which person-types can be used for generating each
activity type. The classification scheme of each activity type reflects the relative importance or
natural hierarchy of the activity, where work and school activities are typically the most inflexible
in terms of generation, scheduling and location, and discretionary activities are typically the most
flexible on each of these dimensions. Each out-of-home location that a person travels to in the
simulation is assigned one of these activity types.

+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Purpose             | Description                                                              | Classification| Eligibility                           |
+=====================+==========================================================================+===============+=======================================+
| Work                | Working at regular workplace or work-related activities outside the home | Mandatory     | Workers and students                  |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| University          | College or university                                                    | Mandatory     | Age 18+                               |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| High School         | Grades 9-12                                                              | Mandatory     | Age 14-17                             |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Grade School        | Grades preschool, K-8                                                    | Mandatory     | Age 0-13                              |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Escorting           | Pick-up/drop-off passengers (auto trips only)                            | NonMandatory  | Age 16+                               |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Shopping            | Shopping away from home                                                  | NonMandatory  | Age 5+ (if joint travel, all persons) |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Other Maintenance   | Personal business/services and medical appointments                      | NonMandatory  | Age 5+ (if joint travel, all persons) |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Social/Recreational | Recreation, visiting friends/family                                      | NonMandatory  | Age 5+ (if joint travel, all persons) |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Eat Out             | Eating outside of home                                                   | NonMandatory  | Age 5+ (if joint travel, all persons) |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+
| Other Discretionary | Volunteer work, religious activities                                     | NonMandatory  | Age 5+ (if joint travel, all persons) |
+---------------------+--------------------------------------------------------------------------+---------------+---------------------------------------+

Treatment of time
^^^^^^^^^^^^^^^^^

The TM1 example model system functions at a temporal resolution of one hour. These one hour increments
begin with 3 AM and end with 3 AM the next day. Temporal integrity is ensured so that no
activities are scheduled with conflicting time windows, with the exception of short
activities/tours that are completed within a one hour increment. For example, a person may have
a short tour that begins and ends within the 8 AM to 9 AM period, as well as a second longer tour
that begins within this time period, but ends later in the day.

A critical aspect of the model system is the relationship between the temporal resolution used for
scheduling activities and the temporal resolution of the network assignment periods. Although
each activity generated by the model system is identified with a start time and end time in one hour
increments, LOS matrices are only created for five aggregate time periods. The trips occurring in each time period
reference the appropriate transport network depending on their trip mode and the mid-point trip
time. The definition of time periods for LOS matrices is given below.

+---------------+------------+
|  Time Period  | Start Hour |
+===============+============+
|  EA           |  3         |
+---------------+------------+
|  AM           |  5         |
+---------------+------------+
|  MD           |  9         |
+---------------+------------+
|  PM           |  14        |
+---------------+------------+
|  EV           |  18        |
+---------------+------------+

Trip modes
^^^^^^^^^^

The trip modes defined in the example model are below. The modes include auto by
occupancy and toll/non-toll choice, walk and bike, walk and drive access to five different
transit line-haul modes, and ride hail with taxi, single TNC (Transportation Network Company), and shared TNC.

  * Auto

    * SOV Free
    * SOV Pay
    * 2 Person Free
    * 2 Person Pay
    * 3+ Person Free
    * 3+ Person Pay

  * Nonmotorized

    * Walk
    * Bike

  * Transit

    * Walk

      * Walk to Local Bus
      * Walk to Light-Rail Transit
      * Walk to Express Bus
      * Walk to Bus Rapid Transit
      * Walk to Heavy Rail

    * Drive

      * Drive to Local Bus
      * Drive to Light-Rail Transit
      * Drive to Express Bus
      * Drive to Bus Rapid Transit
      * Drive to Heavy Rail

  * Ride Hail

    * Taxi
    * Single TNC
    * Shared TNC

Sub-models
^^^^^^^^^^

The general design of the prototype_mtc model is presented below.  Long-term choices that relate to
the usual workplace/university/school for each worker and student, household car ownership, and the
availability of free parking at workplaces are first.

The coordinated daily activity pattern type of each household member is the first travel-related
sub-model in the hierarchy. This model classifies daily patterns by three types:

  * Mandatory, which includes at least one out-of-home mandatory activity (work or school)
  * Non-mandatory, which includes at least one out-of-home non-mandatory activity, but does not include out-of-home mandatory activities
  * Home, which does not include any out-of-home activity or travel

The pattern type sub-model leaves open the frequency of tours for mandatory and nonmandatory
purposes since these sub-models are applied later in the model sequence. Daily
pattern-type choices of the household members are linked in such a way that decisions made by
members are reflected in the decisions made by the other members.

After the frequency and time-of-day for work and school tours are determined, the
next major model component relates to joint household travel. This component produces a
number of joint tours by travel purpose for the entire household, travel party composition
in terms of adults and children, and then defines the participation of each household
member in each joint household tour. It is followed by choice of destination and time-ofday.

The next stage relates to maintenance and discretionary tours that are modeled at the individual
person level. The models include tour frequency, choice of destination and time
of day. Next, a set of sub-models relate tour-level details on mode, exact number of
intermediate stops on each half-tour and stop location. It is followed by the last set of
sub-models that add details for each trip including trip departure time, trip mode details and parking
location for auto trips.

.. image:: images/abmexample.jpg

The output of the model is a disggregate table of trips with individual attributes for custom analysis.  The trips
can be aggregated into travel demand matrices for network loading.

Setup
~~~~~

The following describes the prototype_mtc model setup.


Folder and File Setup

The prototype_mtc has the following root folder/file setup:

  * configs - settings, expressions files, etc.
  * configs_mp - override settings for the multiprocess configuration
  * data - input data such as land use, synthetic population files, and network LOS / skims
  * output - outputs folder

Inputs
^^^^^^
In order to run prototype_mtc, you first need the input files in the ``data`` folder as identified in the ``configs\settings.yaml`` file and the ``configs\network_los.yaml`` file:

* input_table_list: the input CSV tables for MTC (see below for column definitions):

    * households - Synthetic population household records for a subset of zones.
    * persons - Synthetic population person records for a subset of zones.
    * land_use - Zone-based land use data (population and employment for example) for a subset of zones.

* taz_skims: skims.omx - an OMX matrix file containing the MTC TM1 skim matrices for a subset of zones.  The time period for the matrix must be represented at the end of the matrix name and be seperated by a double_underscore (e.g. BUS_IVT__AM indicates base skim BUS_IVT with a time period of AM).

These files are used in the tests as well.  The full set
of MTC households, persons, and OMX skims are on the ActivitySim `resources repository <https://github.com/rsginc/activitysim_resources>`__.

Additional details on these files is available in the original `Travel Model 1 repository <https://github.com/BayAreaMetro/modeling-website/wiki/DataDictionary>`_,
although many of the files described there are not used in ActivitySim.

Households
^^^^^^^^^^
The households table contains the following synthetic population columns:

* household_id: numeric ID of this household, used in persons table to join with household characteristics
* TAZ: zone where this household lives
* income: Annual household income, in 2000 dollars
* hhsize: Household size
* HHT: Household type (see below)
* auto_ownership: number of cars owned by this household (0-6)
* num_workers: number of workers in the household
* sample_rate

Household types
"""""""""""""""

These are household types defined by the Census Bureau and used in `ACS table B11001 <https://censusreporter.org/tables/B11001/>`_.

+------+------------------------------------------+
| Code | Description                              |
+======+==========================================+
| 0    | None                                     |
+------+------------------------------------------+
| 1    | Married-couple family                    |
+------+------------------------------------------+
| 2    | Male householder, no spouse present      |
+------+------------------------------------------+
| 3    | Female householder, no spouse present    |
+------+------------------------------------------+
| 4    | Nonfamily household, male alone          |
+------+------------------------------------------+
| 5    | Nonfamily household, male not alone      |
+------+------------------------------------------+
| 6    | Nonfamily household, female alone        |
+------+------------------------------------------+
| 7    | Nonfamily household, female not alone    |
+------+------------------------------------------+


Persons
^^^^^^^

This table describes attributes of the persons that constitute each household. This file contains the following columns:

* person_id: Unique integer identifier for each person. This value is globally unique, i.e.
  no two individuals have the same person ID, even if they are in different households.
* household_id: Household identifier for this person, foreign key to households table
* age: Age in years
* PNUM: Person number in household, starting from 1.
* sex: Sex, 1 = Male, 2 = Female
* pemploy: Employment status (see below)
* pstudent: Student status (see below)
* ptype: Person type (see person type segmentation above)

Employment status
"""""""""""""""""

+------+------------------------------------------+
| Code | Description                              |
+======+==========================================+
| 1    | Full-time worker                         |
+------+------------------------------------------+
| 2    | Part-time worker                         |
+------+------------------------------------------+
| 3    | Not in labor force                       |
+------+------------------------------------------+
| 4    | Student under 16                         |
+------+------------------------------------------+

Student status
""""""""""""""

+------+------------------------------------------+
| Code | Description                              |
+======+==========================================+
| 1    | Preschool through Grade 12 student       |
+------+------------------------------------------+
| 2    | University/professional school student   |
+------+------------------------------------------+
| 3    | Not a student                            |
+------+------------------------------------------+

Land use
^^^^^^^^

All values are raw numbers and not proportions of the total.

* TAZ: Zone which this row describes
* DISTRICT: Superdistrict where this TAZ is (34 superdistricts in the Bay Area)
* SD: Duplicate of DISTRICT
* COUNTY: County within the Bay Area (see below)
* TOTHH: Total households in TAZ
* TOTPOP: Total population in TAZ
* TOTACRE: Area of TAZ, acres
* RESACRE: Residential area of TAZ, acres
* CIACRE: Commercial/industrial area of TAZ, acres
* TOTEMP: Total employment
* AGE0519: Persons age 5 to 19 (inclusive)
* RETEMPN: NAICS-based total retail employment
* FPSEMPN: NAICS-based financial and professional services employment
* HEREMPN: NAICS-based health, education, and recreational service employment
* AGREMPN: NAICS-based agricultural and natural resources employment
* MWTEMPN: NAICS-based manufacturing and wholesale trade employment
* OTHEMP: NAICS-based other employment
* PRKCST: Hourly cost paid by long-term (8+ hours) parkers, year 2000 cents
* OPRKCST: Hourly cost paid by short term parkers, year 2000 cents
* area_type: Area type designation (see below)
* HSENROLL: High school students enrolled at schools in this TAZ
* COLLFTE: College students enrolled full-time at colleges in this TAZ
* COLLPTE: College students enrolled part-time at colleges in this TAZ
* TERMINAL: Average time to travel from automobile storage location to origin/destination (floating-point minutes)

Counties
""""""""

+------+------------------------------------------+
| Code | Name                                     |
+======+==========================================+
| 1    | San Francisco                            |
+------+------------------------------------------+
| 2    | San Mateo                                |
+------+------------------------------------------+
| 3    | Santa Clara                              |
+------+------------------------------------------+
| 4    | Alameda                                  |
+------+------------------------------------------+
| 5    | Contra Costa                             |
+------+------------------------------------------+
| 6    | Solano                                   |
+------+------------------------------------------+
| 7    | Napa                                     |
+------+------------------------------------------+
| 8    | Sonoma                                   |
+------+------------------------------------------+
| 9    | Marin                                    |
+------+------------------------------------------+

Area types
""""""""""

+------+------------------------------------------+
| Code | Description                              |
+======+==========================================+
| 0    | Regional core                            |
+------+------------------------------------------+
| 1    | Central business district                |
+------+------------------------------------------+
| 2    | Urban business                           |
+------+------------------------------------------+
| 3    | Urban                                    |
+------+------------------------------------------+
| 4    | Suburban                                 |
+------+------------------------------------------+
| 5    | Rural                                    |
+------+------------------------------------------+

.. note::

  ActivitySim can optionally build an HDF5 file of the input CSV tables for use in subsequent runs since
  HDF5 is binary and therefore results in faster read times. see :ref:`configuration`

  OMX and HDF5 files can be viewed with the `OMX Viewer <https://github.com/osPlanning/omx/wiki/OMX-Viewer>`__ or
  `HDFView <https://www.hdfgroup.org/downloads/hdfview>`__.

  The ``other_resources\scripts\build_omx.py`` script will build one OMX file containing all the skims. The original MTC TM1 skims were converted for the prototype from
  Cube to OMX using the ``other_resources\scripts\mtc_tm1_omx_export.s`` script.

  The prototype_mtc_sf inputs were created by the ``other_resources\scripts\create_sf_example.py`` script, which creates the land use, synthetic population, and
  skim inputs for a subset of user-defined zones.

.. index:: configuration

Configuration
^^^^^^^^^^^^^

This section has been moved to :ref:`configuration`.

.. _sub-model-spec-files:

Sub-Model Specification Files
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Included in the ``configs`` folder are the model specification files that store the
Python/pandas/numpy expressions, alternatives, and other settings used by each model.  Some models includes an
alternatives file since the alternatives are not easily described as columns in the expressions file.  An example
of this is the ``non_mandatory_tour_frequency_alternatives.csv`` file, which lists each alternative as a row and each
columns indicates the number of non-mandatory tours by purpose.  The  set of files for the prototype_mtc are below.  The
:ref:`prototype_arc`, :ref:`prototype_semcog`, and :ref:`prototype_mtc_extended` examples added additional submodels.

+------------------------------------------------+--------------------------------------------------------------------+
|            Model                               |    Specification Files                                             |
+================================================+====================================================================+
|  :ref:`initialize_landuse`                     |  - initialize_landuse.yaml                                         |
|                                                |  - annotate_landuse.csv                                            |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`accessibility`                          |  - accessibility.yaml                                              |
|                                                |  - accessibility.csv                                               |
+------------------------------------------------+--------------------------------------------------------------------+
|                                                |  - initialize_households.yaml                                      |
|  :ref:`initialize_households`                  |  - annotate_persons.csv                                            |
|                                                |  - annotate_households.csv                                         |
|                                                |  - annotate_persons_after_hh.csv                                   |
+------------------------------------------------+--------------------------------------------------------------------+
|   :ref:`school_location`                       |  - school_location.yaml                                            |
|                                                |  - school_location_coeffs.csv                                      |
|                                                |  - annotate_persons_school.csv                                     |
|                                                |  - school_location_sample.csv                                      |
|                                                |  - tour_mode_choice.yaml (and related files)                       |
|                                                |  - school_location.csv                                             |
|                                                |  - destination_choice_size_terms.csv                               |
|                                                |  - shadow_pricing.yaml                                             |
+------------------------------------------------+--------------------------------------------------------------------+
|    :ref:`work_location`                        |  - workplace_location.yaml                                         |
|                                                |  - workplace_location_coeffs.csv                                   |
|                                                |  - annotate_persons_workplace.csv                                  |
|                                                |  - annotate_households_workplace.csv                               |
|                                                |  - workplace_location_sample.csv                                   |
|                                                |  - tour_mode_choice.yaml (and related files)                       |
|                                                |  - workplace_location.csv                                          |
|                                                |  - destination_choice_size_terms.csv                               |
|                                                |  - shadow_pricing.yaml                                             |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`auto_ownership`                          |  - auto_ownership.yaml                                             |
|                                                |  - auto_ownership_coeffs.csv                                       |
|                                                |  - auto_ownership.csv                                              |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`freeparking`                             |  - free_parking.yaml                                               |
|                                                |  - free_parking_coeffs.csv                                         |
|                                                |  - free_parking.csv                                                |
|                                                |  - free_parking_annotate_persons_preprocessor.csv                  |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`cdap`                                    |  - cdap.yaml                                                       |
|                                                |  - annotate_persons_cdap.csv                                       |
|                                                |  - annotate_households_cdap.csv                                    |
|                                                |  - cdap_indiv_and_hhsize1.csv                                      |
|                                                |  - cdap_interaction_coefficients.csv                               |
|                                                |  - cdap_fixed_relative_proportions.csv                             |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`mandatory_tour_frequency`               |  - mandatory_tour_frequency.yaml                                   |
|                                                |  - mandatory_tour_frequency_coeffs.csv                             |
|                                                |  - mandatory_tour_frequency.csv                                    |
|                                                |  - mandatory_tour_frequency_alternatives.csv                       |
|                                                |  - annotate_persons_mtf.csv                                        |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`mandatory_tour_scheduling`               |  - mandatory_tour_scheduling.yaml                                  |
|                                                |  - tour_scheduling_work_coeffs.csv                                 |
|                                                |  - tour_scheduling_work.csv                                        |
|                                                |  - tour_scheduling_school.csv                                      |
|                                                |  - tour_departure_and_duration_alternatives.csv                    |
|                                                |  - tour_departure_and_duration_segments.csv                        |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`joint_tour_frequency`                    |  - joint_tour_frequency.yaml                                       |
|                                                |  - joint_tour_frequency_coeffs.csv                                 |
|                                                |  - annotate_persons_jtf.csv                                        |
|                                                |  - joint_tour_frequency_annotate_households_preprocessor.csv       |
|                                                |  - joint_tour_frequency_alternatives.csv                           |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`joint_tour_composition`                  |  - joint_tour_composition.yaml                                     |
|                                                |  - joint_tour_composition_coefficients.csv                         |
|                                                |  - joint_tour_composition_annotate_households_preprocessor.csv     |
|                                                |  - joint_tour_composition.csv                                      |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`joint_tour_participation`                |  - joint_tour_participation.yaml                                   |
|                                                |  - joint_tour_participation_coefficients.csv                       |
|                                                |  - joint_tour_participation_annotate_participants_preprocessor.csv |
|                                                |  - joint_tour_participation.csv                                    |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`joint_tour_destination_choice`           |  - joint_tour_destination.yaml                                     |
|                                                |  - non_mandatory_tour_destination_coefficients.csv                 |
|                                                |  - non_mandatory_tour_destination_sample.csv                       |
|                                                |  - non_mandatory_tour_destination.csv                              |
|                                                |  - tour_mode_choice.yaml (and related files)                       |
|                                                |  - destination_choice_size_terms.csv                               |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`joint_tour_scheduling`                   |  - joint_tour_scheduling.yaml                                      |
|                                                |  - tour_scheduling_joint_coefficients.csv                          |
|                                                |  - joint_tour_scheduling_annotate_tours_preprocessor.csv           |
|                                                |  - tour_scheduling_joint.csv                                       |
|                                                |  - tour_departure_and_duration_alternatives.csv                    |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`non_mandatory_tour_frequency`            |  - non_mandatory_tour_frequency.yaml                               |
|                                                |  - non_mandatory_tour_frequency_coefficients_{ptype}.csv           |
|                                                |  - non_mandatory_tour_frequency.csv                                |
|                                                |  - non_mandatory_tour_frequency_alternatives.csv                   |
|                                                |  - non_mandatory_tour_frequency_annotate_persons_preprocessor.csv  |
|                                                |  - non_mandatory_tour_frequency_extension_probs.csv                |
|                                                |  - annotate_persons_nmtf.csv                                       |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`non_mandatory_tour_destination_choice`   |  - non_mandatory_tour_destination.yaml                             |
|                                                |  - non_mandatory_tour_destination_coefficients.csv                 |
|                                                |  - non_mandatory_tour_destination.csv                              |
|                                                |  - non_mandatory_tour_destination_sample.csv                       |
|                                                |  - tour_mode_choice.yaml (and related files)                       |
|                                                |  - destination_choice_size_terms.csv                               |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`non_mandatory_tour_scheduling`           |  - non_mandatory_tour_scheduling.yaml                              |
|                                                |  - tour_scheduling_nonmandatory_coefficients.csv                   |
|                                                |  - non_mandatory_tour_scheduling_annotate_tours_preprocessor.csv   |
|                                                |  - tour_scheduling_nonmandatory.csv                                |
|                                                |  - tour_departure_and_duration_alternatives.csv                    |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`tour_mode_choice`                        |  - tour_mode_choice.yaml                                           |
|                                                |  - tour_mode_choice_annotate_choosers_preprocessor.csv             |
|                                                |  - tour_mode_choice.csv                                            |
|                                                |  - tour_mode_choice_coefficients.csv                               |
|                                                |  - tour_mode_choice_coeffs_template.csv                            |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`atwork_subtour_frequency`               |  - atwork_subtour_frequency.yaml                                   |
|                                                |  - atwork_subtour_frequency_coefficients.csv                       |
|                                                |  - atwork_subtour_frequency.csv                                    |
|                                                |  - atwork_subtour_frequency_alternatives.csv                       |
|                                                |  - atwork_subtour_frequency_annotate_tours_preprocessor.csv        |
+------------------------------------------------+--------------------------------------------------------------------+
|   :ref:`atwork_subtour_destination`            |  - atwork_subtour_destination.yaml                                 |
|                                                |  - atwork_subtour_destination_coefficients.csv                     |
|                                                |  - atwork_subtour_destination_sample.csv                           |
|                                                |  - atwork_subtour_destination.csv                                  |
|                                                |  - tour_mode_choice.yaml (and related files)                       |
|                                                |  - destination_choice_size_terms.csv                               |
+------------------------------------------------+--------------------------------------------------------------------+
| :ref:`atwork_subtour_scheduling`               |  - tour_scheduling_atwork.yaml                                     |
|                                                |  - tour_scheduling_atwork_coefficients.csv                         |
|                                                |  - tour_scheduling_atwork.csv                                      |
|                                                |  - tour_scheduling_atwork_preprocessor.csv                         |
|                                                |  - tour_departure_and_duration_alternatives.csv                    |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`atwork_subtour_mode_choice`             |  - tour_mode_choice.yaml (and related files)                       |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`intermediate_stop_frequency`            |  - stop_frequency.yaml                                             |
|                                                |  - stop_frequency_annotate_tours_preprocessor.csv                  |
|                                                |  - stop_frequency_alternatives.csv                                 |
|                                                |  - stop_frequency_atwork.csv                                       |
|                                                |  - stop_frequency_eatout.csv                                       |
|                                                |  - stop_frequency_escort.csv                                       |
|                                                |  - stop_frequency_othdiscr.csv                                     |
|                                                |  - stop_frequency_othmaint.csv                                     |
|                                                |  - stop_frequency_school.csv                                       |
|                                                |  - stop_frequency_shopping.csv                                     |
|                                                |  - stop_frequency_social.csv                                       |
|                                                |  - stop_frequency_subtour.csv                                      |
|                                                |  - stop_frequency_univ.csv                                         |
|                                                |  - stop_frequency_work.csv                                         |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`trip_purpose`                           |  - trip_purpose.yaml (+ trip_purpose_and_destination.yaml)         |
|                                                |  - trip_purpose_annotate_trips_preprocessor.csv                    |
|                                                |  - trip_purpose_probs.csv                                          |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`trip_destination_choice`                |  - trip_destination.yaml (+ trip_purpose_and_destination.yaml)     |
|                                                |  - trip_destination.csv                                            |
|                                                |  - trip_destination_annotate_trips_preprocessor.csv                |
|                                                |  - trip_destination_sample.csv                                     |
|                                                |  - trip_mode_choice.yaml (and related files)                       |
|                                                |  - destination_choice_size_terms.csv                               |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`trip_scheduling`                        |  - trip_scheduling.yaml                                            |
|                                                |  - trip_scheduling_probs.csv                                       |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`trip_mode_choice`                       |  - trip_mode_choice.yaml                                           |
|                                                |  - trip_mode_choice_annotate_trips_preprocessor.csv                |
|                                                |  - trip_mode_choice_coefficients.csv                               |
|                                                |  - trip_mode_choice.csv                                            |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`parking_location_choice`                |  - parking_location_choice.yaml                                    |
|                                                |  - parking_location_choice_annotate_trips_preprocessor.csv         |
|                                                |  - parking_location_choice_coeffs.csv                              |
|                                                |  - parking_location_choice.csv                                     |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`write_trip_matrices`                    |  - write_trip_matrices.yaml                                        |
|                                                |  - write_trip_matrices_annotate_trips_preprocessor.csv             |
+------------------------------------------------+--------------------------------------------------------------------+

.. _model_steps :

Pipeline
^^^^^^^^

The ``models`` setting contains the specification of the data pipeline model steps, as shown below:

::

 models:
    - initialize_landuse
    - compute_accessibility
    - initialize_households
    - 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

These model steps must be registered Inject steps, as noted below.  If you provide a ``resume_after``
argument to :func:`activitysim.core.pipeline.run` the pipeliner will load checkpointed tables from the checkpoint store
and resume pipeline processing on the next model step after the specified checkpoint.

::

  resume_after = None
  #resume_after = 'school_location'

The model is run by calling the :func:`activitysim.core.pipeline.run` method.

::

  pipeline.run(models=_MODELS, resume_after=resume_after)


.. _example_run :

Running the example
~~~~~~~~~~~~~~~~~~~

To run the example, do the following:

* Activate the correct conda environment if needed
* View the list of available examples

::

  activitysim create --list

* Create a local copy of an example folder

::

  activitysim create --example prototype_mtc --destination my_test_example

* Run the example

::

  cd my_test_example
  activitysim run -c configs -d data -o output


* ActivitySim will log progress and write outputs to the output folder.

The example should run in a few minutes since it runs a small sample of households.

.. note::

  A customizable run script for power users can be found in the `Github repo <https://github.com/ActivitySim/activitysim/tree/main/other_resources/scripts>`__.
  This script takes many of the same arguments as the ``activitysim run`` command, including paths to
  ``--config``, ``--data``, and ``--output`` directories. The script looks for these folders in the current
  working directory by default.

  ::

    python simulation.py

Multiprocessing
^^^^^^^^^^^^^^^

The model system is parallelized via :ref:`multiprocessing`.  To setup and run the :ref:`example` using
multiprocessing, follow the same steps as the above :ref:`example_run`, but add an additional ``-c`` flag to
include the multiprocessing configuration settings via settings file inheritance (see :ref:`cli`) as well:

::

  activitysim run -c configs_mp -c configs -d data -o output

The multiprocessing example also writes outputs to the output folder.

The default multiprocessed example is configured to run with two processors and chunking training: ``num_processes: 2``,
``chunk_size: 0``, and ``chunk_training_mode: training``.  Additional more performant configurations are included and
commented out in the example settings file.  For example, the 100 percent sample full scale multiprocessing example
- ``prototype_mtc_full`` - was run on a Windows Server machine with 28 cores and 256GB RAM with the configuration below.
The default setup runs with ``chunk_training_mode: training`` since no chunk cache file is present. To run the example
significantly faster, try ``chunk_training_mode: disabled`` if the machine has sufficient RAM, or try
``chunk_training_mode: production``.  To configure ``chunk_training_mode: production``, first configure chunking as
discussed below. See :ref:`multiprocessing` and :ref:`chunk_size` for more information.

::

  households_sample_size: 0
  num_processes: 24
  chunk_size: 0
  chunk_training_mode: production


.. _configuring_chunking :

Configuring chunking
^^^^^^^^^^^^^^^^^^^^

To configure chunking, ActivitySim must first be trained to determine reasonable chunking settings given the
model setup and machine.  The steps to configure chunking are:

* Run the full scale model with ``chunk_training_mode: training``.
  Set ``num_processors`` to about 80% of the available physical processors
  and ``chunk_size`` to about 80% of the available RAM.  This will run the model
  and create the ``chunk_cache.csv`` file in the output\cache directory for reuse.
* The ``households_sample_size`` for training chunking should be at least 1 / num_processors
  to provide sufficient data for training and the ``chunk_method: hybrid_uss``
  typically performs best.
* Run the full scale model with ``chunk_training_mode: production``.  Experiment
  with different ``num_processors`` and ``chunk_size`` settings depending on desired
  runtimes and machine resources.

See :ref:`chunk_size` for more information.  Users can run ``chunk_training_mode: disabled`` if the machine has an abundance of RAM for the model setup.

Outputs
~~~~~~~

The key output of ActivitySim is the HDF5 data pipeline file ``outputs\pipeline.h5``.  By default, this datastore file
contains a copy of each data table after each model step in which the table was modified.

The example also writes the final tables to CSV files by using the ``write_tables`` step.  This step calls
:func:`activitysim.core.pipeline.get_table` to get a pandas DataFrame and write a CSV file for each table
specified in ``output_tables`` in the settings.yaml file.

::

  output_tables:
    h5_store: False
    action: include
    prefix: final_
    tables:
      - checkpoints
      - accessibility
      - land_use
      - households
      - persons
      - tours
      - trips
      - joint_tour_participants



The ``other_resources\scripts\make_pipeline_output.py`` script uses the information stored in the pipeline file to create
the table below for a small sample of households.  The table shows that for each table in the pipeline, the number of rows
and/or columns changes as a result of the relevant model step.  A ``checkpoints`` table is also stored in the
pipeline, which contains the crosswalk between model steps and table states in order to reload tables for
restarting the pipeline at any step.

+-----------------------------------+------------------------------------+------+------+
| Table                             | Creator                            | NRow | NCol |
+===================================+====================================+======+======+
| accessibility                     | compute_accessibility              | 1454 | 10   |
+-----------------------------------+------------------------------------+------+------+
| households                        | initialize                         | 100  | 65   |
+-----------------------------------+------------------------------------+------+------+
| households                        | workplace_location                 | 100  | 66   |
+-----------------------------------+------------------------------------+------+------+
| households                        | cdap_simulate                      | 100  | 73   |
+-----------------------------------+------------------------------------+------+------+
| households                        | joint_tour_frequency               | 100  | 75   |
+-----------------------------------+------------------------------------+------+------+
| joint_tour_participants           | joint_tour_participation           | 13   | 4    |
+-----------------------------------+------------------------------------+------+------+
| land_use                          | initialize_landuse                 | 1454 | 44   |
+-----------------------------------+------------------------------------+------+------+
| person_windows                    | initialize_households              | 271  | 21   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | initialize_households              | 271  | 42   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | school_location                    | 271  | 45   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | workplace_location                 | 271  | 52   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | free_parking                       | 271  | 53   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | cdap_simulate                      | 271  | 59   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | mandatory_tour_frequency           | 271  | 64   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | joint_tour_participation           | 271  | 65   |
+-----------------------------------+------------------------------------+------+------+
| persons                           | non_mandatory_tour_frequency       | 271  | 74   |
+-----------------------------------+------------------------------------+------+------+
| school_destination_size           | initialize_households              | 1454 | 3    |
+-----------------------------------+------------------------------------+------+------+
| school_modeled_size               | school_location                    | 1454 | 3    |
+-----------------------------------+------------------------------------+------+------+
| tours                             | mandatory_tour_frequency           | 153  | 11   |
+-----------------------------------+------------------------------------+------+------+
| tours                             | mandatory_tour_scheduling          | 153  | 15   |
+-----------------------------------+------------------------------------+------+------+
| tours                             | joint_tour_composition             | 159  | 16   |
+-----------------------------------+------------------------------------+------+------+
| tours                             | tour_mode_choice_simulate          | 319  | 17   |
+-----------------------------------+------------------------------------+------+------+
| tours                             | atwork_subtour_frequency           | 344  | 19   |
+-----------------------------------+------------------------------------+------+------+
| tours                             | stop_frequency                     | 344  | 21   |
+-----------------------------------+------------------------------------+------+------+
| trips                             | stop_frequency                     | 859  | 7    |
+-----------------------------------+------------------------------------+------+------+
| trips                             | trip_purpose                       | 859  | 8    |
+-----------------------------------+------------------------------------+------+------+
| trips                             | trip_destination                   | 859  | 11   |
+-----------------------------------+------------------------------------+------+------+
| trips                             | trip_scheduling                    | 859  | 11   |
+-----------------------------------+------------------------------------+------+------+
| trips                             | trip_mode_choice                   | 859  | 12   |
+-----------------------------------+------------------------------------+------+------+
| workplace_destination_size        | initialize_households              | 1454 | 4    |
+-----------------------------------+------------------------------------+------+------+
| workplace_modeled_size            | workplace_location                 | 1454 | 4    |
+-----------------------------------+------------------------------------+------+------+

.. index:: logs
.. _logs :

Logging
^^^^^^^

Included in the ``configs`` folder is the ``logging.yaml``, which configures Python logging
library.  The following key log files are created with a model run:

* ``activitysim.log`` - overall system log file
* ``timing_log.csv`` - submodel step runtimes
* ``omnibus_mem.csv`` - multiprocessed submodel memory usage

Refer to the :ref:`tracing` section for more detail on tracing.

Trip Matrices
^^^^^^^^^^^^^

The ``write_trip_matrices`` step processes the trips table to create open matrix (OMX) trip matrices for
assignment.  The matrices are configured and coded according to the expressions in the model step
trip annotation file.  See :ref:`write_trip_matrices` for more information.

.. _tracing :

Tracing
^^^^^^^

There are two types of tracing in ActivtiySim: household and origin-destination (OD) pair.  If a household trace ID
is specified, then ActivitySim will output a comprehensive set (i.e. hundreds) of trace files for all
calculations for all household members:

* ``Several CSV files`` - each input, intermediate, and output data table - chooser, expressions/utilities, probabilities, choices, etc. - for the trace household for each sub-model

If an OD pair trace is specified, then ActivitySim will output the acessibility calculations trace
file:

* ``accessibility.result.csv`` - accessibility expression results for the OD pair

With the set of output CSV files, the user can trace ActivitySim calculations in order to ensure they are correct and/or to
help debug data and/or logic errors.

.. _writing_logsums :

Writing Logsums
^^^^^^^^^^^^^^^

The tour and trip destination and mode choice models calculate logsums but do not persist them by default.
Mode and destination choice logsums are essential for re-estimating these models and can therefore be
saved to the pipeline if desired.  To save the tour and trip destination and mode choice model logsums, include
the following optional settings in the model settings file.  The data is saved to the pipeline for later use.

::

  # in workplace_location.yaml for example
  DEST_CHOICE_LOGSUM_COLUMN_NAME: workplace_location_logsum
  DEST_CHOICE_SAMPLE_TABLE_NAME: workplace_location_sample

  # in tour_mode_choice.yaml for example
  MODE_CHOICE_LOGSUM_COLUMN_NAME: mode_choice_logsum

The `DEST_CHOICE_SAMPLE_TABLE_NAME` contains the fields in the table below.  Writing out the
destination choice sample table, which includes the mode choice logsum for each sampled
alternative destination, adds significant size to the pipeline.  Therefore, this feature should
only be activated when writing logsums for a small set of households for model estimation.

+-----------------------------------+---------------------------------------+
| Field                             | Description                           |
+===================================+=======================================+
| chooser_id                        | chooser id such as person or tour id  |
+-----------------------------------+---------------------------------------+
| alt_dest                          | destination alternative id            |
+-----------------------------------+---------------------------------------+
| prob                              | alternative probability               |
+-----------------------------------+---------------------------------------+
| pick_count                        | sampling with replacement pick count  |
+-----------------------------------+---------------------------------------+
| mode_choice_logsum                | mode choice logsum                    |
+-----------------------------------+---------------------------------------+

.. _prototype_mtc_extended :

prototype_mtc_extended
----------------------

prototype_mtc_extended contains additional models that were developed to enhance ActivitySim's modeling
capabilities. This example inherets
the data and configuration files from prototype_mtc. The current list of additional models included
in this example are:

* :ref:`vehicle_type_choice`: Selects a vehicle type for each household vehicle. Runs after auto_ownership.
* :ref:`vehicle_allocation`: Allocates a vehicle for each tour and each occupancy level.  Tour and trip mode choice
  auto operating costs are modified to reflect the allocated vehicle option.


.. _example_estimation :

example_estimation
------------------

ActivitySim includes the ability to re-estimate submodels using choice model estimation tools
such as `larch <https://larch.newman.me/>`__.  In order to do so, ActivitySim adopts the concept of an estimation
data bundle (EDB), which is a collection of the necessary data to re-estimate a submodel.  See :ref:`estimation`
for examples that illustrate running ActivitySim in estimation mode and using larch to re-restimate submodels.

.. index:: multiple_zone_systems
.. _multiple_zone_systems :
.. _placeholder_multiple_zone :

placeholder_multiple_zone
-------------------------

In a multiple zone system approach, households, land use, and trips are modeled at the microzone (MAZ) level.  MAZs are smaller
than traditional TAZs and therefore make for a more precise system.  However, when considering network level-of-service (LOS)
indicators (e.g. skims), the model uses different spatial resolutions for different travel modes in order to reduce the network
modeling burden and model runtimes.  The typical multiple zone system setup is a TAZ zone system for auto travel, a MAZ zone
system for non-motorized travel, and optionally a transit access points (TAPs) zone system for transit.

ActivitySim supports models with multiple zone systems.  The three versions of multiple zone systems are one-zone, two-zone, and three-zone.

  * **One-zone**: This version is based on TM1 and supports only TAZs. All origins and
    destinations are represented at the TAZ level, and all skims including auto, transit,
    and non-motorized times and costs are also represented at the TAZ level.
  * **Two-zone**: This version is similar to many DaySim models. It uses microzones (MAZs)
    for origins and destinations, and TAZs for specification of auto and transit times and
    costs. Impedance for walk or bike all-the-way from the origin to the destination can
    be specified at the MAZ level for close together origins and destinations, and at
    the TAZ level for further origins and destinations. Users can also override transit
    walk access and egress times with times specified in the MAZ file by transit mode.
    Careful pre-calculation of the assumed transit walk access and egress time by MAZ
    and transit mode is required depending on the network scenario.
  * **Three-zone**: This version is based on the SANDAG generation of CT-RAMP models.
    Origins and destinations are represented at the MAZ level. Impedance for walk or
    bike all-the-way from the origin to the destination can be specified at the MAZ
    level for close together origins and destinations, and at the TAZ level for further
    origins and destinations, just like the two-zone system. TAZs are used for auto
    times and costs. The difference between this system and the two-zone system is that
    transit times and costs are represented between Transit Access Points (TAPs), which
    are essentially dummy zones that represent transit stops or clusters of stops.
    Transit skims are built between TAPs, since there are typically too many MAZs to
    build skims between them. Often multiple sets of TAP to TAP skims (local bus only,
    all modes, etc.) are created and input to the demand model for consideration.  Walk
    access and egress times are also calculated between the MAZ and the TAP, and total
    transit path utilities are assembled from their respective components - from MAZ to
    first boarding TAP, from first boarding to final alighting TAP, and from alighting
    TAP to destination MAZ. This assembling is done via the
    :ref:`transit_virtual_path_builder` (TVPB), which considers all possible
    combinations of nearby boarding and alighting TAPs for each origin destination MAZ
    pair.

Regions that have an interest in more precise transit forecasts may wish to adopt the
three-zone approach, while other regions may adopt the one or two-zone approach.  The
microzone version requires coding households and land use at the microzone level.
Typically an all-streets network is used for representation of non-motorized impedances.
This requires a routable all-streets network, with centroids and connectors for
microzones.  If the three-zone system is adopted, procedures need to be developed to
code TAPs from transit stops and populate the all-street network with TAP centroids
and centroid connectors.  A model with transit virtual path building takes longer to
run than a traditional TAZ only model, but it provides a much richer framework for
transit modeling.

.. note::
   The two and three zone system test examples are simple test examples developed from the TM1 example.  To develop the two zone system
   example, TM1 TAZs were labeled MAZs, each MAZ was assigned a TAZ, and MAZ to MAZ impedance files were created from the
   TAZ to TAZ impedances.  To develop the three zone example system example, the TM1 TAZ model was further transformed
   so select TAZs also became TAPs and TAP to TAP skims and MAZ to TAP impedances files were created.  While sufficient for
   initial development, these examples were insufficient for validation and performance testing of the new software. As a result,
   the :ref:`prototype_marin` example was created.

Example simple test configurations and inputs for two and three-zone system models are described below.

Examples
~~~~~~~~

To run the two zone and three zone system examples, do the following:

* Activate the correct conda environment if needed
* Create a local copy of the example

::

  # simple two zone example
  activitysim create -e placeholder_2_zone -d test_placeholder_2_zone

  # simple three zone example
  activitysim create -e placeholder_3_zone -d test_placeholder_3_zone


* Change to the example directory
* Run the example

::

  # simple two zone example
  activitysim run -c configs_2_zone -c configs -d data_2 -o output_2

  # simple three zone example, single process and multiprocess (and makes use of settings file inheritance for running)
  activitysim run -c configs_3_zone -c configs -d data_3 -o output_3 -s settings_static.yaml
  activitysim run -c configs_3_zone -c configs -d data_3 -o output_3 -s settings_mp.yaml

Settings
~~~~~~~~

Additional settings for running ActivitySim with two or three zone systems are specified in the ``settings.yaml`` and
``network_los.yaml`` files.  The settings are:

Two Zone
^^^^^^^^

In ``settings.yaml``:

* ``want_dest_choice_presampling`` - enable presampling for multizone systems, which
  means first select a TAZ using the sampling model and then select a microzone within
  the TAZ based on the microzone share of TAZ size term.

In ``network_los.yaml``:

The additional two zone system settings and inputs are described and illustrated below.
No additional utility expression files or expression revisions are required beyond the
one zone approach.  The MAZ data is available as zone data and the MAZ to MAZ data is
available using the existing skim expressions.  Users can specify mode utilities using
MAZ data, MAZ to MAZ impedances, and TAZ to TAZ impedances.

* ``zone_system`` - set to 2 for two zone system
* ``maz`` -  MAZ data file, with MAZ ID, TAZ, and land use and other MAZ attributes
* ``maz_to_maz:tables`` - list of MAZ to MAZ impedance tables.  These tables are read
  as pandas DataFrames and the columns are exposed to expressions.
* ``maz_to_maz:max_blend_distance`` - in order to avoid cliff effects, the lookup of
  MAZ to MAZ impedance can be a blend of origin MAZ to destination MAZ impedance and
  origin TAZ to destination TAZ impedance up to a max distance.  The blending formula
  is below.  This requires specifying a distance TAZ skim and distance columns from
  the MAZ to MAZ files.  The TAZ skim name and MAZ to MAZ column name need to be the
  same so the blending can happen on-the-fly or else a value of 0 is returned.

::

  (MAZ to MAZ distance) * (distance / max distance) * (TAZ to TAZ distance) * (1 - (distance / max distance))


* ``maz_to_maz:blend_distance_skim_name`` - Identify the distance skim for the blending calculation if different than the blend skim.

::

  zone_system: 2
  maz: maz.csv

  maz_to_maz:
    tables:
      - maz_to_maz_walk.csv
      - maz_to_maz_bike.csv

    max_blend_distance:
      DIST: 5
      DISTBIKE: 0
      DISTWALK: 1

    blend_distance_skim_name: DIST


Three Zone
^^^^^^^^^^

In addition to the extra two zone system settings and inputs above, the following additional settings and inputs are required for a three zone system model.  Examples values are illustrated below.

In ``settings.yaml``:

* ``models`` - add initialize_los and initialize_tvpb to load network LOS inputs / skims and pre-compute TAP to TAP utilities for TVPB.  See :ref:`initialize_los`.
* ``want_dest_choice_presampling`` - enable presampling for multizone systems, which means first select a TAZ using the sampling model and then select a microzone within the TAZ based on the microzone share of TAZ size term.

::

  models:
    - initialize_landuse
    - compute_accessibility
    - initialize_households
    # ---
    - initialize_los
    - initialize_tvpb
    # ---
    - school_location
    - workplace_location

In ``network_los.yaml``:

* ``zone_system`` - set to 3 for three zone system
* ``rebuild_tvpb_cache`` - rebuild and overwrite existing pre-computed TAP to TAP utilities cache
* ``trace_tvpb_cache_as_csv`` - write a CSV version of TVPB cache for tracing
* ``tap_skims`` - TAP to TAP skims OMX file name. The time period for the matrix must be represented at the end of the matrix name and be seperated by a double_underscore (e.g. BUS_IVT__AM indicates base skim BUS_IVT with a time period of AM).
* ``tap`` - TAPs table
* ``tap_lines`` - table of transit line names served for each TAP.  This file is used to trimmed the set of nearby TAP for each MAZ so only TAPs that are further away and serve new service are included in the TAP set for consideration.  It is a very important file to include as it can considerably reduce runtimes.
* ``maz_to_tap`` - list of MAZ to TAP access/egress impedance files by user defined mode.  Examples include walk and drive.  The file also includes MAZ to TAP impedances.
* ``maz_to_tap:{walk}:max_dist`` - max distance from MAZ to TAP to consider TAP
* ``maz_to_tap:{walk}:tap_line_distance_col`` - MAZ to TAP data field to use for TAP lines distance filter
* ``demographic_segments`` - list of user defined demographic_segments for pre-computed TVPB impedances.  Each chooser is coded with a user defined demographic segment.
* ``TVPB_SETTINGS:units`` - specify the units for calculations, e.g. utility or time.
* ``TVPB_SETTINGS:path_types`` - user defined set of TVPB path types to be calculated and available to the mode choice models.  Examples include walk transit walk (WTW), drive transit walk (DTW), and walk transit drive (WTD).
* ``TVPB_SETTINGS:path_types:{WTW}:access`` - access mode for the path type
* ``TVPB_SETTINGS:path_types:{WTW}:egress`` - egress mode for the path type
* ``TVPB_SETTINGS:path_types:{WTW}:max_paths_across_tap_sets`` - max paths to keep across all skim sets, for example, 3 TAP to TAP pairs per origin MAZ destination MAZ pair
* ``TVPB_SETTINGS:path_types:{WTW}:max_paths_per_tap_set`` - max paths to keep per skim set, for example 1 per skim set - all transit submodes, local bus only, etc.

Unlike the one and two zone system approach, the three zone system approach requires additional expression files for the TVPB.  The additional expression files for the TVPB are:

* ``TVPB_SETTINGS:tap_tap_settings:SPEC`` - TAP to TAP expressions, e.g. tvpb_utility_tap_tap.csv
* ``TVPB_SETTINGS:tap_tap_settings:PREPROCESSOR:SPEC`` - TAP to TAP chooser preprocessor, e.g. tvpb_utility_tap_tap_annotate_choosers_preprocessor.csv
* ``TVPB_SETTINGS:maz_tap_settings:walk:SPEC`` - MAZ to TAP {walk} expressions, e.g. tvpb_utility_walk_maz_tap.csv
* ``TVPB_SETTINGS:maz_tap_settings:drive:SPEC`` - MAZ to TAP {drive} expressions, e.g. tvpb_utility_drive_maz_tap.csv
* ``TVPB_SETTINGS:accessibility:tap_tap_settings:SPEC`` - TAP to TAP expressions for the accessibility calculator, e.g. tvpb_accessibility_tap_tap.csv
* ``TVPB_SETTINGS:accessibility:maz_tap_settings:walk:SPEC`` - MAz to TAP {walk} expressions for the accessibility calculator, e.g. tvpb_accessibility_walk_maz_tap.csv

Additional settings to configure the TVPB are:

* ``TVPB_SETTINGS:tap_tap_settings:attribute_segments:demographic_segment`` - TVPB pre-computes TAP to TAP total utilities for demographic segments.  These are defined using the attribute_segments keyword.  In the example below, the segments are demographic_segment (household income bin), tod (time-of-day), and access_mode (drive, walk).
* ``TVPB_SETTINGS:maz_tap_settings:{walk}:CHOOSER_COLUMNS`` - input impedance columns to expose for TVPB calculations.
* ``TVPB_SETTINGS:maz_tap_settings:{walk}:CONSTANTS`` - constants for TVPB calculations.
* ``accessibility:...`` - for the accessibility model step, the same basic set of TVPB configurations are available.

::

  zone_system: 3

  rebuild_tvpb_cache: False
  trace_tvpb_cache_as_csv: False
  tap_skims: tap_skims.omx
  tap: tap.csv
  maz_to_tap:
    walk:
      table: maz_to_tap_walk.csv
    drive:
      table: maz_to_tap_drive.csv

  demographic_segments: &demographic_segments
  - &low_income_segment_id 0
  - &high_income_segment_id 1

  TVPB_SETTINGS:
    tour_mode_choice:
      units: utility
      path_types:
        WTW:
          access: walk
          egress: walk
          max_paths_across_tap_sets: 3
          max_paths_per_tap_set: 1
        DTW:
          access: drive
          egress: walk
          max_paths_across_tap_sets: 3
          max_paths_per_tap_set: 1
        WTD:
          access: walk
          egress: drive
          max_paths_across_tap_sets: 3
          max_paths_per_tap_set: 1
      tap_tap_settings:
        SPEC: tvpb_utility_tap_tap.csv
        PREPROCESSOR:
          SPEC: tvpb_utility_tap_tap_annotate_choosers_preprocessor.csv
          DF: df
        attribute_segments:
          demographic_segment: *demographic_segments
          tod: *skim_time_period_labels
          access_mode: ['drive', 'walk']
        attributes_as_columns:
          - demographic_segment
          - tod
      maz_tap_settings:
        walk:
          SPEC: tvpb_utility_walk_maz_tap.csv
          CHOOSER_COLUMNS:
            - walk_time
        drive:
          SPEC: tvpb_utility_drive_maz_tap.csv
          CHOOSER_COLUMNS:
            - drive_time
            - DIST
      CONSTANTS:
        c_ivt_high_income: -0.028
        ...

    accessibility:
      units: time
      path_types:
        WTW:
          access: walk
          egress: walk
          max_paths_across_tap_sets: 1
          max_paths_per_tap_set: 1
      tap_tap_settings:
        SPEC: tvpb_accessibility_tap_tap_.csv
      maz_tap_settings:
          walk:
            SPEC: tvpb_accessibility_walk_maz_tap.csv
            CHOOSER_COLUMNS:
              - walk_time
      CONSTANTS:
          out_of_vehicle_walk_time_weight: 1.5
          out_of_vehicle_wait_time_weight: 2.0

Outputs
~~~~~~~

Essentially the same set of outputs is created for a two or three zone system
model as for a one zone system model.  However, the one key additional bit of
information for a three zone system model is the boarding TAP, alighting TAP, and
transit skim set is added to the relevant chooser table (e.g. tours and trips) when the
chosen mode is transit.  Logging and tracing also work for two and three zone models,
including tracing of the TVPB calculations. The :ref:`write_trip_matrices` step writes
both TAZ and TAP level matrices depending on the configured number of zone systems.

.. _presampling :

Presampling
~~~~~~~~~~~

In multiple zone systems models, destination choice presampling is activated by default.  Destination
choice presampling first aggregates microzone size terms to the TAZ level and then runs destination
choice sampling at the TAZ level using the destination choice sampling models.  After sampling X
number of TAZs based on impedance and size, the model selects a microzone for each TAZ based
on the microzone share of TAZ size.  Presampling significantly reduces runtime while producing
similar results.

.. _prototype_marin :

prototype_marin
---------------

To finalize development and verification of the multiple zone system and transit virtual path building components, the
`Transportation Authority of Marin County <https://www.tam.ca.gov/>`__ version of MTC travel model two (TM2) work
tour mode choice model was implemented.  This example was also developed to test multiprocessed runtime performance.
The complete runnable setup is available from the ActivitySim command line interface as `prototype_3_marin_full`.  This example
has essentially the same configuration as the simpler three zone example above.

Example
~~~~~~~

To run prototype_marin, do the following:

* Activate the correct conda environment if needed
* Create a local copy of the example

::

  # Marin TM2 work tour mode choice for the MTC region
  activitysim create -e prototype_3_marin_full -d test_prototype_3_marin_full

* Change to the example directory
* Run the example

::

  # Marin TM2 work tour mode choice for the MTC region
  activitysim run -c configs -d data -o output -s settings_mp.yaml

* For optimal performance, configure multiprocessing and chunk_size based on machine hardware.


Settings
~~~~~~~~

Additional settings for running the Marin TM2 tour mode choice example are in the ``network_los.yaml`` file.  The
only additional notable setting is the ``tap_lines`` setting, which identifies a table of transit line names
served for each TAP.  This file is used to trimmed the set of nearby TAP for each MAZ so only TAPs that are
further away and serve new service are included in the TAP set for consideration.  It is a very important
file to include as it can considerably reduce runtimes.

::

  tap_lines: tap_lines.csv


.. _prototype_arc :

prototype_arc
-------------

.. note::

  This example is in development


The prototype_arc added a :ref:`trip_scheduling_choice`, :ref:`trip_departure_choice`, and :ref:`parking_location_choice`
submodel.  These submodel specification files are below, and are in addition to the :ref:`prototype_mtc`
submodel :ref:`sub-model-spec-files`.

.. _arc-sub-model-spec-files:

Example ARC Sub-Model Specification Files
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

+------------------------------------------------+--------------------------------------------------------------------+
|            Model                               |    Specification Files                                             |
+================================================+====================================================================+
|  :ref:`trip_scheduling_choice`                 |  - trip_scheduling_choice.yaml                                     |
|                                                |  - trip_scheduling_choice_preprocessor.csv                         |
|                                                |  - trip_scheduling_choice.csv                                      |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`trip_departure_choice`                  |  - trip_departure_choice.yaml                                      |
|                                                |  - trip_departure_choice_preprocessor.csv                          |
|                                                |  - trip_departure_choice.csv                                       |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`parking_location_choice`                |  - parking_location_choice.yaml                                    |
|                                                |  - parking_location_choice_annotate_trips_preprocessor.csv         |
|                                                |  - parking_location_choice_coeffs.csv                              |
|                                                |  - parking_location_choice.csv                                     |
+------------------------------------------------+--------------------------------------------------------------------+

Example
~~~~~~~

See example commands in `example_manifest.yaml <https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_manifest.yaml>`_
for running prototype_arc.  For optimal performance, configure multiprocessing and chunk_size based on machine hardware.

.. _prototype_semcog :

prototype_semcog
----------------

.. note::

  This example is in development


The prototype_semcog added a :ref:`work_from_home`, :ref:`telecommute_frequency`, :ref:`transit_pass_subsidy`
and :ref:`transit_pass_ownership` submodel.  These submodel specification files are below, and are in addition to the :ref:`prototype_mtc`
submodel :ref:`sub-model-spec-files`.  These submodels were added to prototype_semcog as extensions, which is a way for users to add
submodels within their model setup as opposed to formally adding them to the activitysim package.  Extension submodels are run through 
the `models` settings.  However, the model must be run with the `simulation.py` script instead of the command line interface 
in order to load the extensions folder.

.. _semcog-sub-model-spec-files:

Example SEMCOG Sub-Model Specification Files
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

+------------------------------------------------+--------------------------------------------------------------------+
|            Model                               |    Specification Files                                             |
+================================================+====================================================================+
|  :ref:`work_from_home`                         |  - work_from_home.yaml                                             |
|                                                |  - work_from_home.csv                                              |
|                                                |  - work_from_home_coeffs.csv                                       |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`telecommute_frequency`                  |  - telecommute_frequency.yaml                                      |
|                                                |  - telecommute_frequency.csv                                       |
|                                                |  - telecommute_frequency_coeffs.csv                                |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`transit_pass_subsidy`                   |  - transit_pass_subsidy.yaml                                       |
|                                                |  - transit_pass_subsidy.csv                                        |
|                                                |  - transit_pass_subsidy_coeffs.csv                                 |
+------------------------------------------------+--------------------------------------------------------------------+
|  :ref:`transit_pass_ownership`                 |  - transit_pass_ownership.yaml                                     |
|                                                |  - transit_pass_ownership.csv                                      |
|                                                |  - transit_pass_ownership_coeffs.csv                               |
+------------------------------------------------+--------------------------------------------------------------------+

Example
~~~~~~~

See example commands in `example_manifest.yaml <https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_manifest.yaml>`_
for running prototype_semcog.  For optimal performance, configure multiprocessing and chunk_size based on machine hardware.


.. _placeholder_psrc :

placeholder_psrc
----------------

.. note::

  This example is a placeholder model used only for code development and debugging, and is not suitable for policy analysis


The placeholder_psrc is a two zone system (MAZs and TAZs) implementation of the
prototype_mtc model design.  It uses PSRC zones, land use, synthetic population, and network LOS (skims).

Example
~~~~~~~

See example commands in `example_manifest.yaml <https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_manifest.yaml>`_
for running placeholder_psrc.  For optimal performance, configure multiprocessing and chunk_size based on machine hardware.

.. _placeholder_sandag :

placeholder_sandag
------------------

.. note::

  This example is in development


The placeholder_sandag is a multi-part model, containing one-, two-, and three- zone system (MAZs, TAZs, and TAPs) implementation of the
prototype_mtc model design.  It uses SANDAG zones, land use, synthetic population, and network LOS (skims).

Example
~~~~~~~

See example commands in `example_manifest.yaml <https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_manifest.yaml>`_
for running placeholder_sandag.  For optimal performance, configure multiprocessing and chunk_size based on machine hardware.

.. _prototype_sandag_xborder :

prototype_sandag_xborder
------------------------

.. note::

  This example is in development


The prototype_sandag_xborder is a three zone system (MAZs, TAZs, and TAPs) that
generates cross-border activities for a tour-based population of Mexican residents.
In addition to the normal SANDAG zones, there are external MAZs and TAZs defined for
each border crossing station (Port of Entry). Because the model is tour-based, there
are no household or person-level attributes in the synthetic population. The
principal difference between this and the standard 3-zone implementation is that
since household do not have a default tour origin (home zones), a tour OD choice
model is required to assign tour origins and destinations simultaneously.

Example
~~~~~~~

See example commands in `example_manifest.yaml <https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_manifest.yaml>`_
for running prototype_sandag_xborder.  For optimal performance, configure multiprocessing and chunk_size based on machine hardware.

.. _prototype_mwcog :

prototype_mwcog
---------------

The prototype_mwcog is a one zone system (TAZs only).

Example
~~~~~~~

See example commands in `example_manifest.yaml <https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_manifest.yaml>`_
for running prototype_mwcog.  For optimal performance, configure multiprocessing and chunk_size based on machine hardware.
