.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/bayesian_swissmetro/swissmetro_binary.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_bayesian_swissmetro_swissmetro_binary.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_bayesian_swissmetro_swissmetro_binary.py:


.. _swissmetro_binary:

Data preparation for Swissmetro (binary choice)
===============================================

Data preparation for Swissmetro, and definition of the variables. The
data is designed to estimate binary logit models. All observations
such that Swissmetro was chosen are removed.

:author: Michel Bierlaire, EPFL
:date: Mon Mar  6 15:17:03 2023

.. GENERATED FROM PYTHON SOURCE LINES 14-20

.. code-block:: Python


    import pandas as pd

    from biogeme.database import Database
    from biogeme.expressions import Variable


.. GENERATED FROM PYTHON SOURCE LINES 21-22

Read the data.

.. GENERATED FROM PYTHON SOURCE LINES 22-25

.. code-block:: Python

    df = pd.read_csv('swissmetro.dat', sep='\t')
    database = Database('swissmetro', df)


.. GENERATED FROM PYTHON SOURCE LINES 26-27

Definition of the variables.

.. GENERATED FROM PYTHON SOURCE LINES 27-48

.. code-block:: Python

    PURPOSE = Variable('PURPOSE')
    CHOICE = Variable('CHOICE')
    GA = Variable('GA')
    LUGGAGE = Variable('LUGGAGE')
    TRAIN_CO = Variable('TRAIN_CO')
    CAR_AV = Variable('CAR_AV')
    SP = Variable('SP')
    TRAIN_AV = Variable('TRAIN_AV')
    TRAIN_TT = Variable('TRAIN_TT')
    SM_TT = Variable('SM_TT')
    CAR_TT = Variable('CAR_TT')
    CAR_CO = Variable('CAR_CO')
    SM_CO = Variable('SM_CO')
    SM_AV = Variable('SM_AV')
    MALE = Variable('MALE')
    GROUP = Variable('GROUP')
    TRAIN_HE = Variable('TRAIN_HE')
    SM_HE = Variable('SM_HE')
    INCOME = Variable('INCOME')



.. GENERATED FROM PYTHON SOURCE LINES 49-50

Definition of new variables.

.. GENERATED FROM PYTHON SOURCE LINES 50-70

.. code-block:: Python

    SM_COST = database.define_variable('SM_COST', SM_CO * (GA == 0))
    TRAIN_COST = database.define_variable('TRAIN_COST', TRAIN_CO * (GA == 0))
    CAR_AV_SP = database.define_variable('CAR_AV_SP', CAR_AV * (SP != 0))
    TRAIN_AV_SP = database.define_variable('TRAIN_AV_SP', TRAIN_AV * (SP != 0))
    TRAIN_TT_SCALED = database.define_variable('TRAIN_TT_SCALED', TRAIN_TT / 100)
    TRAIN_COST_SCALED = database.define_variable('TRAIN_COST_SCALED', TRAIN_COST / 100)
    SM_TT_SCALED = database.define_variable('SM_TT_SCALED', SM_TT / 100)
    SM_COST_SCALED = database.define_variable('SM_COST_SCALED', SM_COST / 100)
    CAR_TT_SCALED = database.define_variable('CAR_TT_SCALED', CAR_TT / 100)
    CAR_CO_SCALED = database.define_variable('CAR_CO_SCALED', CAR_CO / 100)

    # Excluding observations. We keep only observations where either car or train has been chosen, and both are available.
    exclude = (
        (PURPOSE != 1) * (PURPOSE != 3)
        + (CHOICE == 0)
        + (CHOICE == 2)
        + (CAR_AV_SP == 0)
        + (TRAIN_AV_SP == 0)
    ) > 0
    database.remove(exclude)


.. _sphx_glr_download_auto_examples_bayesian_swissmetro_swissmetro_binary.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: swissmetro_binary.ipynb <swissmetro_binary.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: swissmetro_binary.py <swissmetro_binary.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: swissmetro_binary.zip <swissmetro_binary.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_