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

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

.. _sphx_glr__auto_examples_public_transport_plot_public_transit_assignment.py:


.. _example_transit_asssignment:

Public transport assignment with Optimal Strategies
===================================================

In this example, perform a Spiess & Florian assignment. `Click here <https://doi.org/10.1016/0191-2615(89)90034-9>`_
to check out the paper.

We use data from Coquimbo, a city in La Serena Metropolitan Area in Chile.

.. GENERATED FROM PYTHON SOURCE LINES 13-16

.. admonition:: References

  * :doc:`../../public_transport`

.. GENERATED FROM PYTHON SOURCE LINES 18-26

.. seealso::
    Several functions, methods, classes and modules are used in this example:

    * :func:`aequilibrae.transit.Transit`
    * :func:`aequilibrae.transit.TransitGraphBuilder`
    * :func:`aequilibrae.paths.TransitClass`
    * :func:`aequilibrae.paths.TransitAssignment`
    * :func:`aequilibrae.matrix.AequilibraeMatrix`

.. GENERATED FROM PYTHON SOURCE LINES 28-37

.. code-block:: Python


    # Imports for example construction
    from uuid import uuid4
    from os.path import join
    from tempfile import gettempdir

    from aequilibrae.transit import Transit
    from aequilibrae.utils.create_example import create_example








.. GENERATED FROM PYTHON SOURCE LINES 39-40

Let's create an empty project on an arbitrary folder.

.. GENERATED FROM PYTHON SOURCE LINES 40-44

.. code-block:: Python

    fldr = join(gettempdir(), uuid4().hex)

    project = create_example(fldr, "coquimbo")








.. GENERATED FROM PYTHON SOURCE LINES 45-46

Let's create our ``Transit`` object.

.. GENERATED FROM PYTHON SOURCE LINES 46-48

.. code-block:: Python

    data = Transit(project)








.. GENERATED FROM PYTHON SOURCE LINES 49-57

Graph building
--------------
Let's build the transit network. We'll disable ``outer_stop_transfers`` and ``walking_edges`` 
because Coquimbo doesn't have any parent stations.

For the OD connections we'll use the ``overlapping_regions`` method and create some accurate line geometry later.
Creating the graph should only take a moment. By default zoning information is pulled from the project network. 
If you have your own zoning information add it using ``graph.add_zones(zones)`` then ``graph.create_graph()``. 

.. GENERATED FROM PYTHON SOURCE LINES 59-64

.. code-block:: Python

    graph = data.create_graph(with_outer_stop_transfers=False, with_walking_edges=False, blocking_centroid_flows=False, connector_method="overlapping_regions")

    # We drop geometry here for the sake of display.
    graph.vertices.drop(columns="geometry")






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
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        .dataframe tbody tr th {
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            text-align: right;
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    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>node_id</th>
          <th>node_type</th>
          <th>stop_id</th>
          <th>line_id</th>
          <th>line_seg_idx</th>
          <th>taz_id</th>
        </tr>
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      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>od</td>
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        <tr>
          <th>1</th>
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        <tr>
          <th>3</th>
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          <td>od</td>
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        <tr>
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          <th>...</th>
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          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
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        <tr>
          <th>362</th>
          <td>363</td>
          <td>alighting</td>
          <td>10000000075</td>
          <td>1_10001003000</td>
          <td>31</td>
          <td>-1</td>
        </tr>
        <tr>
          <th>363</th>
          <td>364</td>
          <td>alighting</td>
          <td>10000000076</td>
          <td>1_10001003000</td>
          <td>32</td>
          <td>-1</td>
        </tr>
        <tr>
          <th>364</th>
          <td>365</td>
          <td>alighting</td>
          <td>10000000077</td>
          <td>1_10001003000</td>
          <td>33</td>
          <td>-1</td>
        </tr>
        <tr>
          <th>365</th>
          <td>366</td>
          <td>alighting</td>
          <td>10000000078</td>
          <td>1_10001003000</td>
          <td>34</td>
          <td>-1</td>
        </tr>
        <tr>
          <th>366</th>
          <td>367</td>
          <td>alighting</td>
          <td>10000000053</td>
          <td>1_10001003000</td>
          <td>35</td>
          <td>-1</td>
        </tr>
      </tbody>
    </table>
    <p>367 rows × 6 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 65-67

.. code-block:: Python

    graph.edges






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

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            text-align: right;
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    <table border="1" class="dataframe">
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        <tr style="text-align: right;">
          <th></th>
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          <th>line_id</th>
          <th>stop_id</th>
          <th>line_seg_idx</th>
          <th>b_node</th>
          <th>a_node</th>
          <th>trav_time</th>
          <th>freq</th>
          <th>o_line_id</th>
          <th>d_line_id</th>
          <th>direction</th>
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          <td>1</td>
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          <td>90.000000</td>
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          <td>2</td>
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        <tr>
          <th>2</th>
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          <td>on-board</td>
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          <td>214</td>
          <td>292</td>
          <td>120.000000</td>
          <td>inf</td>
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          <td></td>
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        <tr>
          <th>3</th>
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          <td>on-board</td>
          <td>1_10001001000</td>
          <td></td>
          <td>3</td>
          <td>215</td>
          <td>293</td>
          <td>120.000000</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
        </tr>
        <tr>
          <th>4</th>
          <td>5</td>
          <td>on-board</td>
          <td>1_10001001000</td>
          <td></td>
          <td>4</td>
          <td>216</td>
          <td>294</td>
          <td>120.000000</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
        </tr>
        <tr>
          <th>...</th>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
        </tr>
        <tr>
          <th>641</th>
          <td>642</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>166</td>
          <td>112</td>
          <td>630.543431</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
        </tr>
        <tr>
          <th>642</th>
          <td>643</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>177</td>
          <td>112</td>
          <td>754.081137</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
        </tr>
        <tr>
          <th>643</th>
          <td>644</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>178</td>
          <td>112</td>
          <td>386.262027</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
        </tr>
        <tr>
          <th>644</th>
          <td>645</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>179</td>
          <td>112</td>
          <td>558.108038</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
        </tr>
        <tr>
          <th>645</th>
          <td>646</td>
          <td>egress_connector</td>
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          <td></td>
          <td>-1</td>
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          <td>113</td>
          <td>604.831967</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
        </tr>
      </tbody>
    </table>
    <p>646 rows × 12 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 68-71

The graphs also also stored in the ``Transit.graphs`` dictionary. They are keyed by the 'period_id' they 
were created for. A graph for a different 'period_id' can be created by providing ``period_id=`` in the 
``Transit.create_graph`` call. You can view previously created periods with the ``Periods`` object.

.. GENERATED FROM PYTHON SOURCE LINES 71-74

.. code-block:: Python

    periods = project.network.periods
    periods.data






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
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        <tr style="text-align: right;">
          <th></th>
          <th>period_id</th>
          <th>period_start</th>
          <th>period_end</th>
          <th>period_description</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>0</td>
          <td>86400</td>
          <td>Default time period, whole day</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 75-77

Connector project matching
--------------------------

.. GENERATED FROM PYTHON SOURCE LINES 77-79

.. code-block:: Python

    project.network.build_graphs()





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

 .. code-block:: none

    /home/runner/work/aequilibrae/aequilibrae/aequilibrae/paths/graph.py:248: UserWarning: Found centroids not present in the graph!
    [  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
      19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
      37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
      55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
      73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
      91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
     109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
     127 128 129 130 131 132 133]
      warnings.warn("Found centroids not present in the graph!\n" + str(centroids[~present_centroids]))
    /home/runner/work/aequilibrae/aequilibrae/aequilibrae/paths/graph.py:248: UserWarning: Found centroids not present in the graph!
    [  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
      19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
      37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
      55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
      73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
      91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
     109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
     127 128 129 130 131 132 133]
      warnings.warn("Found centroids not present in the graph!\n" + str(centroids[~present_centroids]))




.. GENERATED FROM PYTHON SOURCE LINES 80-84

Now we'll create the line strings for the access connectors, this step is optional but provides more accurate distance 
estimations and better looking geometry.

Because Coquimbo doesn't have many walking edges we'll match onto the ``"c"`` graph.

.. GENERATED FROM PYTHON SOURCE LINES 84-86

.. code-block:: Python

    graph.create_line_geometry(method="connector project match", graph="c")





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

 .. code-block:: none

    /home/runner/work/aequilibrae/aequilibrae/aequilibrae/transit/transit_graph_builder.py:1191: UserWarning: In its current implementation, the "connector project match" method may take a while for large networks.
      warnings.warn(




.. GENERATED FROM PYTHON SOURCE LINES 87-90

Saving and reloading
--------------------
Lets save all graphs to the 'public_transport.sqlite' database.

.. GENERATED FROM PYTHON SOURCE LINES 90-92

.. code-block:: Python

    data.save_graphs()








.. GENERATED FROM PYTHON SOURCE LINES 93-97

We can reload the saved graphs with ``data.load``. 
This will create new ``TransitGraphBuilder``\'s based on the 'period_id' of the saved graphs.
The graph configuration is stored in the 'transit_graph_config' table in 'project_database.sqlite' 
as serialised JSON.

.. GENERATED FROM PYTHON SOURCE LINES 97-99

.. code-block:: Python

    data.load()








.. GENERATED FROM PYTHON SOURCE LINES 100-101

We can also remove the previously saved graphs.

.. GENERATED FROM PYTHON SOURCE LINES 101-104

.. code-block:: Python


    # data.remove_graphs()








.. GENERATED FROM PYTHON SOURCE LINES 105-110

Links and nodes are stored in a similar manner to the 'project_database.sqlite' database.

Reading back into AequilibraE
-----------------------------
You can create back in a particular graph via it's 'period_id'.

.. GENERATED FROM PYTHON SOURCE LINES 110-113

.. code-block:: Python

    from aequilibrae.project.database_connection import database_connection
    from aequilibrae.transit.transit_graph_builder import TransitGraphBuilder








.. GENERATED FROM PYTHON SOURCE LINES 114-119

.. code-block:: Python

    pt_con = database_connection("transit")

    graph_db = TransitGraphBuilder.from_db(pt_con, periods.default_period.period_id)
    graph_db.vertices.drop(columns="geometry")






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
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          <th>3</th>
          <td>4</td>
          <td>od</td>
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          <td>-1</td>
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        <tr>
          <th>4</th>
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          <td>5</td>
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          <th>...</th>
          <td>...</td>
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          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
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          <td>363</td>
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          <td>1_10001003000</td>
          <td>31</td>
          <td>-1</td>
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        <tr>
          <th>363</th>
          <td>364</td>
          <td>alighting</td>
          <td>10000000076</td>
          <td>1_10001003000</td>
          <td>32</td>
          <td>-1</td>
        </tr>
        <tr>
          <th>364</th>
          <td>365</td>
          <td>alighting</td>
          <td>10000000077</td>
          <td>1_10001003000</td>
          <td>33</td>
          <td>-1</td>
        </tr>
        <tr>
          <th>365</th>
          <td>366</td>
          <td>alighting</td>
          <td>10000000078</td>
          <td>1_10001003000</td>
          <td>34</td>
          <td>-1</td>
        </tr>
        <tr>
          <th>366</th>
          <td>367</td>
          <td>alighting</td>
          <td>10000000053</td>
          <td>1_10001003000</td>
          <td>35</td>
          <td>-1</td>
        </tr>
      </tbody>
    </table>
    <p>367 rows × 6 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 120-122

.. code-block:: Python

    graph_db.edges






.. raw:: html

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    <div>
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        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

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            text-align: right;
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          <th></th>
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          <th>stop_id</th>
          <th>line_seg_idx</th>
          <th>b_node</th>
          <th>a_node</th>
          <th>trav_time</th>
          <th>freq</th>
          <th>o_line_id</th>
          <th>d_line_id</th>
          <th>direction</th>
          <th>geometry</th>
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          <th>0</th>
          <td>1</td>
          <td>on-board</td>
          <td>1_10001001000</td>
          <td></td>
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          <td>212</td>
          <td>290</td>
          <td>90.000000</td>
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          <td>b'\x01\x02\x00\x00\x00\x02\x00\x00\x00\xb8Y\xf...</td>
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          <td>b'\x01\x02\x00\x00\x00\x02\x00\x00\x00U2\x00T\...</td>
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          <th>2</th>
          <td>3</td>
          <td>on-board</td>
          <td>1_10001001000</td>
          <td></td>
          <td>2</td>
          <td>214</td>
          <td>292</td>
          <td>120.000000</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b'\x01\x02\x00\x00\x00\x02\x00\x00\x00A\xb1\xf...</td>
        </tr>
        <tr>
          <th>3</th>
          <td>4</td>
          <td>on-board</td>
          <td>1_10001001000</td>
          <td></td>
          <td>3</td>
          <td>215</td>
          <td>293</td>
          <td>120.000000</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b'\x01\x02\x00\x00\x00\x02\x00\x00\x008\xde\xf...</td>
        </tr>
        <tr>
          <th>4</th>
          <td>5</td>
          <td>on-board</td>
          <td>1_10001001000</td>
          <td></td>
          <td>4</td>
          <td>216</td>
          <td>294</td>
          <td>120.000000</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b'\x01\x02\x00\x00\x00\x02\x00\x00\x00\xc8\xd5...</td>
        </tr>
        <tr>
          <th>...</th>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
        </tr>
        <tr>
          <th>641</th>
          <td>642</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>166</td>
          <td>112</td>
          <td>1039.945114</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b"\x01\x02\x00\x00\x00\x1b\x00\x00\x00\xa1\x92...</td>
        </tr>
        <tr>
          <th>642</th>
          <td>643</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>177</td>
          <td>112</td>
          <td>1149.832226</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b"\x01\x02\x00\x00\x00\x1e\x00\x00\x00\xa1\x92...</td>
        </tr>
        <tr>
          <th>643</th>
          <td>644</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>178</td>
          <td>112</td>
          <td>508.359402</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b"\x01\x02\x00\x00\x00\x13\x00\x00\x00\xa1\x92...</td>
        </tr>
        <tr>
          <th>644</th>
          <td>645</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>179</td>
          <td>112</td>
          <td>968.705083</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b'\x01\x02\x00\x00\x00\x1d\x00\x00\x00\xa1\x92...</td>
        </tr>
        <tr>
          <th>645</th>
          <td>646</td>
          <td>egress_connector</td>
          <td></td>
          <td></td>
          <td>-1</td>
          <td>166</td>
          <td>113</td>
          <td>1831.651685</td>
          <td>inf</td>
          <td></td>
          <td></td>
          <td>1</td>
          <td>b'\x01\x02\x00\x00\x00/\x00\x00\x00\x1ci\x91$\...</td>
        </tr>
      </tbody>
    </table>
    <p>646 rows × 13 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 123-126

Converting to a AequilibraE graph object
----------------------------------------
To perform an assignment we need to convert the graph builder into a graph.

.. GENERATED FROM PYTHON SOURCE LINES 126-128

.. code-block:: Python

    transit_graph = graph.to_transit_graph()





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

 .. code-block:: none

    /home/runner/work/aequilibrae/aequilibrae/aequilibrae/paths/graph.py:248: UserWarning: Found centroids not present in the graph!
    [  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
      21  22  23  24  25  26  30  31  32  34  35  36  38  41  42  43  44  45
      46  51  52  53  54  55  56  61  62  63  64  65  66  67  72  73  77  78
      79  80  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97
      98  99 100 101 102 103 104 105 109 110 111 114 115 116 117 118 119 120
     121 122 123 124 125 126 127 128 129 130 131 132 133]
      warnings.warn("Found centroids not present in the graph!\n" + str(centroids[~present_centroids]))
    /home/runner/work/aequilibrae/aequilibrae/aequilibrae/paths/graph.py:248: UserWarning: Found centroids not present in the graph!
    [  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
      21  22  23  24  25  26  30  31  32  34  35  36  38  41  42  43  44  45
      46  51  52  53  54  55  56  61  62  63  64  65  66  67  72  73  77  78
      79  80  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97
      98  99 100 101 102 103 104 105 109 110 111 114 115 116 117 118 119 120
     121 122 123 124 125 126 127 128 129 130 131 132 133]
      warnings.warn("Found centroids not present in the graph!\n" + str(centroids[~present_centroids]))




.. GENERATED FROM PYTHON SOURCE LINES 129-133

Mock demand matrix
------------------
We'll create a mock demand matrix with demand 1 for every zone.
We'll also need to convert from ``zone_id``\'s to ``node_id``\'s.

.. GENERATED FROM PYTHON SOURCE LINES 133-136

.. code-block:: Python

    import numpy as np
    from aequilibrae.matrix import AequilibraeMatrix








.. GENERATED FROM PYTHON SOURCE LINES 137-149

.. code-block:: Python

    zones_in_the_model = len(transit_graph.centroids)

    names_list = ['pt']

    mat = AequilibraeMatrix()
    mat.create_empty(zones=zones_in_the_model,
                     matrix_names=names_list,
                     memory_only=True)
    mat.index = transit_graph.centroids[:]
    mat.matrices[:, :, 0] = np.full((zones_in_the_model, zones_in_the_model), 1.0)
    mat.computational_view()








.. GENERATED FROM PYTHON SOURCE LINES 150-153

Hyperpath generation/assignment
-------------------------------
We'll create a ``TransitAssignment`` object as well as a ``TransitClass``

.. GENERATED FROM PYTHON SOURCE LINES 153-155

.. code-block:: Python

    from aequilibrae.paths import TransitAssignment, TransitClass








.. GENERATED FROM PYTHON SOURCE LINES 156-157

Create the assignment class

.. GENERATED FROM PYTHON SOURCE LINES 157-170

.. code-block:: Python

    assigclass = TransitClass(name="pt", graph=transit_graph, matrix=mat)

    assig = TransitAssignment()

    assig.add_class(assigclass)

    # We need to tell AequilbraE where to find the appropriate fields we want to use,  
    # as well as the assignment algorithm to use.
    assig.set_time_field("trav_time")
    assig.set_frequency_field("freq")

    assig.set_algorithm("os")








.. GENERATED FROM PYTHON SOURCE LINES 171-173

When there's multiple matrix cores we'll also need to set the core to use for the demand as we can only assign one
at a time.

.. GENERATED FROM PYTHON SOURCE LINES 173-175

.. code-block:: Python

    assigclass.set_demand_matrix_core("pt")








.. GENERATED FROM PYTHON SOURCE LINES 176-177

Let's perform the assignment for the transit classes added

.. GENERATED FROM PYTHON SOURCE LINES 177-179

.. code-block:: Python

    assig.execute()








.. GENERATED FROM PYTHON SOURCE LINES 180-181

View the results

.. GENERATED FROM PYTHON SOURCE LINES 181-183

.. code-block:: Python

    assig.results()






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>pt_volume</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>479</th>
          <td>0.0</td>
        </tr>
        <tr>
          <th>480</th>
          <td>33.0</td>
        </tr>
        <tr>
          <th>481</th>
          <td>24.0</td>
        </tr>
        <tr>
          <th>482</th>
          <td>17.0</td>
        </tr>
        <tr>
          <th>483</th>
          <td>12.0</td>
        </tr>
        <tr>
          <th>...</th>
          <td>...</td>
        </tr>
        <tr>
          <th>74</th>
          <td>47.0</td>
        </tr>
        <tr>
          <th>75</th>
          <td>24.0</td>
        </tr>
        <tr>
          <th>76</th>
          <td>24.0</td>
        </tr>
        <tr>
          <th>77</th>
          <td>27.0</td>
        </tr>
        <tr>
          <th>78</th>
          <td>0.0</td>
        </tr>
      </tbody>
    </table>
    <p>646 rows × 1 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 184-189

Saving results
--------------
We'll be saving the results to another sqlite db called 'results_database.sqlite'. 
The 'results' table with 'project_database.sqlite' contains some metadata about each table in 
'results_database.sqlite'.

.. GENERATED FROM PYTHON SOURCE LINES 189-191

.. code-block:: Python

    assig.save_results(table_name='hyperpath example')








.. GENERATED FROM PYTHON SOURCE LINES 192-193

Wrapping up

.. GENERATED FROM PYTHON SOURCE LINES 193-194

.. code-block:: Python

    project.close()




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

 .. code-block:: none

    This project at /tmp/11e931f57c7d4f959c6ea14a0c841ebe is already closed





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

   **Total running time of the script:** (0 minutes 5.339 seconds)


.. _sphx_glr_download__auto_examples_public_transport_plot_public_transit_assignment.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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