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

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

.. _sphx_glr__auto_examples_other_applications_plot_check_logging.py:


.. _useful-log-tips:

Checking AequilibraE's log
==========================

AequilibraE's log is a very useful tool to get more information about
what the software is doing under the hood.

Information such as Traffic Class and Traffic Assignment stats, and Traffic Assignment
outputs. If you have created your project's network from OSM, you will also find
information on the number of nodes, links, and the query performed to obtain the data.

In this example, we'll use Sioux Falls data to check the logs, but we strongly encourage
you to go ahead and download a place of your choice and perform a traffic assignment!

.. GENERATED FROM PYTHON SOURCE LINES 18-26

.. code-block:: Python


    # Imports
    from uuid import uuid4
    from tempfile import gettempdir
    from os.path import join
    from aequilibrae.utils.create_example import create_example
    from aequilibrae.paths import TrafficAssignment, TrafficClass








.. GENERATED FROM PYTHON SOURCE LINES 28-29

We create an empty project on an arbitrary folder

.. GENERATED FROM PYTHON SOURCE LINES 29-32

.. code-block:: Python

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








.. GENERATED FROM PYTHON SOURCE LINES 33-34

We build our graphs

.. GENERATED FROM PYTHON SOURCE LINES 34-41

.. code-block:: Python

    project.network.build_graphs()

    graph = project.network.graphs["c"]
    graph.set_graph("free_flow_time")
    graph.set_skimming(["free_flow_time", "distance"])
    graph.set_blocked_centroid_flows(False)





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

 .. code-block:: none

    /opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/aequilibrae/project/network/network.py:327: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
      df = pd.read_sql(sql, conn).fillna(value=np.nan)




.. GENERATED FROM PYTHON SOURCE LINES 42-43

We get our demand matrix from the project and create a computational view

.. GENERATED FROM PYTHON SOURCE LINES 43-47

.. code-block:: Python

    proj_matrices = project.matrices
    demand = proj_matrices.get_matrix("demand_omx")
    demand.computational_view(["matrix"])








.. GENERATED FROM PYTHON SOURCE LINES 48-49

Now let's perform our traffic assignment

.. GENERATED FROM PYTHON SOURCE LINES 49-64

.. code-block:: Python

    assig = TrafficAssignment()

    assigclass = TrafficClass(name="car", graph=graph, matrix=demand)

    assig.add_class(assigclass)
    assig.set_vdf("BPR")
    assig.set_vdf_parameters({"alpha": 0.15, "beta": 4.0})
    assig.set_capacity_field("capacity")
    assig.set_time_field("free_flow_time")
    assig.set_algorithm("bfw")
    assig.max_iter = 50
    assig.rgap_target = 0.001

    assig.execute()





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

 .. code-block:: none

                                Equilibrium Assignment:   0%|          | 0/50 [00:00<?, ?it/s]
                                        All-or-Nothing:   0%|          | 0/24 [00:00<?, ?it/s]
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.. GENERATED FROM PYTHON SOURCE LINES 66-70

.. code-block:: Python

    with open(join(fldr, "aequilibrae.log")) as file:
        for idx, line in enumerate(file):
            print(idx + 1, "-", line)





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

 .. code-block:: none

    1 - 2024-07-26 23:46:24,740;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations

    2 - 2024-07-26 23:46:24,768;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations

    3 - 2024-07-26 23:46:24,795;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations

    4 - 2024-07-26 23:46:24,823;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations

    5 - 2024-07-26 23:46:24,851;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations

    6 - 2024-07-26 23:46:24,878;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations

    7 - 2024-07-26 23:46:24,897;WARNING ; Cost field with wrong type. Converting to float64

    8 - 2024-07-26 23:46:25,144;INFO ; Traffic Class specification

    9 - 2024-07-26 23:46:25,144;INFO ; {'car': {'Graph': "{'Mode': 'c', 'Block through centroids': False, 'Number of centroids': 24, 'Links': 76, 'Nodes': 24}", 'Matrix': "{'Source': '/tmp/abbea16a4670431c851241f2ac4cb98c/matrices/demand.omx', 'Number of centroids': 24, 'Matrix cores': ['matrix'], 'Matrix totals': {'matrix': 360600.0}}"}}

    10 - 2024-07-26 23:46:25,144;INFO ; Traffic Assignment specification

    11 - 2024-07-26 23:46:25,144;INFO ; {'VDF parameters': {'alpha': 0.15, 'beta': 4.0}, 'VDF function': 'bpr', 'Number of cores': 4, 'Capacity field': 'capacity', 'Time field': 'free_flow_time', 'Algorithm': 'bfw', 'Maximum iterations': 250, 'Target RGAP': 0.0001}

    12 - 2024-07-26 23:46:25,146;WARNING ; Cost field with wrong type. Converting to float64

    13 - 2024-07-26 23:46:25,149;INFO ; bfw Assignment STATS

    14 - 2024-07-26 23:46:25,149;INFO ; Iteration, RelativeGap, stepsize

    15 - 2024-07-26 23:46:25,156;INFO ; 1,inf,1.0

    16 - 2024-07-26 23:46:25,164;INFO ; 2,0.8550751349428284,0.32839952448634563

    17 - 2024-07-26 23:46:25,174;INFO ; 3,0.4763455007221067,0.18660240547488702

    18 - 2024-07-26 23:46:25,183;INFO ; 4,0.2355126365951965,0.2411477440291793

    19 - 2024-07-26 23:46:25,191;INFO ; 5,0.10924072010481088,0.8185470737942447

    20 - 2024-07-26 23:46:25,202;INFO ; 6,0.1980945227617506,0.14054330572978305

    21 - 2024-07-26 23:46:25,214;INFO ; 7,0.0668172221544687,0.36171152718899235

    22 - 2024-07-26 23:46:25,223;INFO ; 8,0.06792122267870576,0.9634685345644022

    23 - 2024-07-26 23:46:25,231;INFO ; 9,0.10705582933092841,0.13757153109677167

    24 - 2024-07-26 23:46:25,239;INFO ; 10,0.04038814432034633,0.16094034254279746

    25 - 2024-07-26 23:46:25,248;INFO ; 11,0.027952481137756665,0.3408928228700516

    26 - 2024-07-26 23:46:25,256;INFO ; 12,0.03269999206552473,0.5467680533028664

    27 - 2024-07-26 23:46:25,266;INFO ; 13,0.024040970172177465,0.13812236751253093

    28 - 2024-07-26 23:46:25,274;INFO ; 14,0.02145103090950847,0.1970528150890548

    29 - 2024-07-26 23:46:25,286;INFO ; 15,0.01711663825927433,0.33993816583363684

    30 - 2024-07-26 23:46:25,298;INFO ; 16,0.01735082411129617,0.7287610532385379

    31 - 2024-07-26 23:46:25,308;INFO ; 17,0.02116470546437171,0.08183287977099409

    32 - 2024-07-26 23:46:25,318;INFO ; 18,0.012464530324248888,0.15115985804759452

    33 - 2024-07-26 23:46:25,326;INFO ; 19,0.01254978991985068,0.1683404948154042

    34 - 2024-07-26 23:46:25,338;INFO ; 20,0.011860719789715,0.5399903522726939

    35 - 2024-07-26 23:46:25,355;INFO ; 21,0.012859165521052455,0.05496659199654795

    36 - 2024-07-26 23:46:25,370;INFO ; 22,0.007671197552803449,0.061255615573591514

    37 - 2024-07-26 23:46:25,379;INFO ; 23,0.0055291789072302415,0.07401911120607103

    38 - 2024-07-26 23:46:25,389;INFO ; 24,0.005466797330664798,0.1917097792435685

    39 - 2024-07-26 23:46:25,398;INFO ; 25,0.007073668823305666,0.4228720696282328

    40 - 2024-07-26 23:46:25,410;INFO ; 26,0.009664731222549973,0.9410177051612054

    41 - 2024-07-26 23:46:25,419;INFO ; 27,0.008756083467128792,0.051726110618746685

    42 - 2024-07-26 23:46:25,430;INFO ; 28,0.005105221228052903,0.06397929882333767

    43 - 2024-07-26 23:46:25,438;INFO ; 29,0.0035319062476952537,0.05059090498822049

    44 - 2024-07-26 23:46:25,446;INFO ; 30,0.0031482926233629993,0.05843748781795877

    45 - 2024-07-26 23:46:25,454;INFO ; 31,0.003063209044596168,0.0917313896798221

    46 - 2024-07-26 23:46:25,466;INFO ; 32,0.002664650770773266,0.07094979246384611

    47 - 2024-07-26 23:46:25,475;INFO ; 33,0.002302802037873827,0.12412864151961862

    48 - 2024-07-26 23:46:25,486;INFO ; 34,0.0027510302560621543,0.12799355702542464

    49 - 2024-07-26 23:46:25,494;INFO ; 35,0.0021256347783020885,0.1662038793394671

    50 - 2024-07-26 23:46:25,502;INFO ; 36,0.00209949122320099,0.10282963642093347

    51 - 2024-07-26 23:46:25,514;INFO ; 37,0.001440776365724902,0.14492101336881905

    52 - 2024-07-26 23:46:25,523;INFO ; 38,0.0014180447043991415,0.06529689866673664

    53 - 2024-07-26 23:46:25,534;INFO ; 39,0.0009714813735978865,0.0939925733525401

    54 - 2024-07-26 23:46:25,534;INFO ; bfw Assignment finished. 39 iterations and 0.0009714813735978865 final gap





.. GENERATED FROM PYTHON SOURCE LINES 71-106

In lines 1-7, we receive some warnings that our fields name and lane have ``NaN`` values.
As they are not relevant to our example, we can move on.

In lines 8-9 we get the Traffic Class specifications.
We can see that there is only one traffic class (car). Its **graph** key presents information
on blocked flow through centroids, number of centroids, links, and nodes.
In the **matrix** key, we find information on where in the disk the matrix file is located.
We also have information on the number of centroids and nodes, as well as on the matrix/matrices
used for computation. In our example, we only have one matrix named matrix, and the total
sum of this matrix element is equal to 360,600. If you have more than one matrix its data
will be also displayed in the *matrix_cores* and *matrix_totals* keys.

In lines 10-11 the log shows the Traffic Assignment specifications.
We can see that the VDF parameters, VDF function, capacity and time fields, algorithm,
maximum number of iterations, and target gap are just like the ones we set previously.
The only information that might be new to you is the number of cores used for computation.
If you haven't set any, AequilibraE is going to use the largest number of CPU threads
available.

Line 12 displays us a warning to indicate that AequilibraE is converting the data type
of the cost field.

Lines 13-61 indicate that we'll receive the outputs of a *bfw* algorithm.
In the log there are also the number of the iteration, its relative gap, and the stepsize.
The outputs in lines 15-60 are exactly the same as the ones provided by the function
``assig.report()``. Finally, the last line shows us that the *bfw* assignment has finished
after 46 iterations because its gap is smaller than the threshold we configured (0.001).

In case you execute a new traffic assignment using different classes or changing the
parameters values, these new specification values would be stored in the log file as well
so you can always keep a record of what you have been doing. One last reminder is that
if we had created our project from OSM, the lines on top of the log would have been
different to display information on the queries done to the server to obtain the data.

Log image by https://oldschool.runescape.wiki/index.php?curid=66905#


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

   **Total running time of the script:** (0 minutes 0.901 seconds)


.. _sphx_glr_download__auto_examples_other_applications_plot_check_logging.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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