.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/tutorials/plot_b03_importing_specification.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_tutorials_plot_b03_importing_specification.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_tutorials_plot_b03_importing_specification.py:


Importing model specification
=============================

The Python language allows to organize your model specification in different files.

Michel Bierlaire, EPFL
Thu May 16 13:24:56 2024

.. GENERATED FROM PYTHON SOURCE LINES 12-17

.. code-block:: Python


    from biogeme.biogeme import BIOGEME
    from biogeme.models import loglogit
    from biogeme.results_processing import get_pandas_estimated_parameters








.. GENERATED FROM PYTHON SOURCE LINES 18-20

After having imported the necessary packages, the database and the choice variable are imported
from the file `tutorial_data.py`

.. GENERATED FROM PYTHON SOURCE LINES 20-22

.. code-block:: Python

    from tutorial_data import biogeme_database, choice








.. GENERATED FROM PYTHON SOURCE LINES 23-24

Similarly, the specification of the utility functions is imported from the file `tutorial_model.py`.

.. GENERATED FROM PYTHON SOURCE LINES 24-26

.. code-block:: Python

    from tutorial_model import utilities








.. GENERATED FROM PYTHON SOURCE LINES 27-28

Once the ingredients have been imported, the rest of the script is exactly the same.

.. GENERATED FROM PYTHON SOURCE LINES 28-35

.. code-block:: Python

    log_choice_probability = loglogit(utilities, None, choice)
    biogeme_object = BIOGEME(biogeme_database, log_choice_probability)
    biogeme_object.model_name = 'first_model'
    biogeme_object.calculate_null_loglikelihood(avail={0: 1, 1: 1})
    results = biogeme_object.estimate()
    print(results.short_summary())
    print(get_pandas_estimated_parameters(estimation_results=results))




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Results for model first_model
    Nbr of parameters:              2
    Sample size:                    21
    Excluded data:                  0
    Null log likelihood:            -14.55609
    Final log likelihood:           -6.166042
    Likelihood ratio test (null):           16.7801
    Rho square (null):                      0.576
    Rho bar square (null):                  0.439
    Akaike Information Criterion:   16.33208
    Bayesian Information Criterion: 18.42113

          Name     Value  Robust std err.  Robust t-stat.  Robust p-value
    0  asc_car -0.237573         0.805174       -0.295058        0.767950
    1   b_time -0.053110         0.021672       -2.450673        0.014259





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.744 seconds)


.. _sphx_glr_download_auto_examples_tutorials_plot_b03_importing_specification.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_b03_importing_specification.ipynb <plot_b03_importing_specification.ipynb>`

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

      :download:`Download Python source code: plot_b03_importing_specification.py <plot_b03_importing_specification.py>`

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

      :download:`Download zipped: plot_b03_importing_specification.zip <plot_b03_importing_specification.zip>`


.. only:: html

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

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