.. 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 ` 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 18-19 Imports .. GENERATED FROM PYTHON SOURCE LINES 19-25 .. code-block:: Python 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 26-27 We create an empty project on an arbitrary folder .. GENERATED FROM PYTHON SOURCE LINES 27-30 .. code-block:: Python fldr = join(gettempdir(), uuid4().hex) project = create_example(fldr) .. GENERATED FROM PYTHON SOURCE LINES 31-32 We build our graphs .. GENERATED FROM PYTHON SOURCE LINES 32-39 .. 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) .. GENERATED FROM PYTHON SOURCE LINES 40-41 We get our demand matrix from the project and create a computational view .. GENERATED FROM PYTHON SOURCE LINES 41-45 .. code-block:: Python proj_matrices = project.matrices demand = proj_matrices.get_matrix("demand_omx") demand.computational_view(["matrix"]) .. GENERATED FROM PYTHON SOURCE LINES 46-47 Now let's perform our traffic assignment .. GENERATED FROM PYTHON SOURCE LINES 47-62 .. 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() .. GENERATED FROM PYTHON SOURCE LINES 64-68 .. 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 - 2023-12-16 11:44:44,831;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations 2 - 2023-12-16 11:44:44,859;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations 3 - 2023-12-16 11:44:44,887;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations 4 - 2023-12-16 11:44:44,913;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations 5 - 2023-12-16 11:44:44,940;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations 6 - 2023-12-16 11:44:44,967;WARNING ; Field(s) name, lanes has(ve) at least one NaN value. Check your computations 7 - 2023-12-16 11:44:44,985;WARNING ; Cost field with wrong type. Converting to float64 8 - 2023-12-16 11:44:45,254;INFO ; Traffic Class specification 9 - 2023-12-16 11:44:45,254;INFO ; {'car': {'Graph': "{'Mode': 'c', 'Block through centroids': False, 'Number of centroids': 24, 'Links': 76, 'Nodes': 24}", 'Matrix': "{'Source': '/tmp/f0fcbf9ba7874a6daab274e0229f5917/matrices/demand.omx', 'Number of centroids': 24, 'Matrix cores': ['matrix'], 'Matrix totals': {'matrix': 360600.0}}"}} 10 - 2023-12-16 11:44:45,254;INFO ; Traffic Assignment specification 11 - 2023-12-16 11:44:45,254;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 - 2023-12-16 11:44:45,256;WARNING ; Cost field with wrong type. Converting to float64 13 - 2023-12-16 11:44:45,256;INFO ; bfw Assignment STATS 14 - 2023-12-16 11:44:45,256;INFO ; Iteration, RelativeGap, stepsize 15 - 2023-12-16 11:44:45,261;INFO ; 1,inf,1.0 16 - 2023-12-16 11:44:45,265;INFO ; 2,0.8550751349428284,0.32839952448634563 17 - 2023-12-16 11:44:45,270;INFO ; 3,0.4763455007221067,0.18660240547488702 18 - 2023-12-16 11:44:45,276;INFO ; 4,0.2355126365951965,0.2411477440291793 19 - 2023-12-16 11:44:45,281;INFO ; 5,0.10924072010481088,0.8185470737942447 20 - 2023-12-16 11:44:45,285;INFO ; 6,0.1980945227617506,0.14054330572978305 21 - 2023-12-16 11:44:45,293;INFO ; 7,0.0668172221544687,0.36171152718899235 22 - 2023-12-16 11:44:45,300;INFO ; 8,0.06792122267870576,0.9634685345644022 23 - 2023-12-16 11:44:45,313;INFO ; 9,0.10705582933092841,0.13757153109677167 24 - 2023-12-16 11:44:45,317;INFO ; 10,0.04038814432034633,0.16094034254279746 25 - 2023-12-16 11:44:45,325;INFO ; 11,0.025801226183773198,0.7164350576171225 26 - 2023-12-16 11:44:45,329;INFO ; 12,0.042846437173171124,0.08581544277016764 27 - 2023-12-16 11:44:45,336;INFO ; 13,0.01697166233340716,0.16601579690331966 28 - 2023-12-16 11:44:45,341;INFO ; 14,0.020396548012132316,0.4461322062863093 29 - 2023-12-16 11:44:45,346;INFO ; 15,0.025887901335905326,0.08515995223661456 30 - 2023-12-16 11:44:45,353;INFO ; 16,0.015188959427662786,0.1988698342670054 31 - 2023-12-16 11:44:45,360;INFO ; 17,0.014751419643229704,0.3548856159715747 32 - 2023-12-16 11:44:45,368;INFO ; 18,0.015582407302127807,0.061454151540816244 33 - 2023-12-16 11:44:45,373;INFO ; 19,0.008935871473338668,0.08603462968532627 34 - 2023-12-16 11:44:45,377;INFO ; 20,0.00847704520821181,0.166891388604795 35 - 2023-12-16 11:44:45,385;INFO ; 21,0.00951758140998847,0.49170991560108357 36 - 2023-12-16 11:44:45,393;INFO ; 22,0.013060711845092839,0.06028430875522849 37 - 2023-12-16 11:44:45,401;INFO ; 23,0.006861821876764934,0.1095400978237806 38 - 2023-12-16 11:44:45,405;INFO ; 24,0.00620111331568848,0.1223071846428894 39 - 2023-12-16 11:44:45,412;INFO ; 25,0.007457404973803511,0.3080614235512719 40 - 2023-12-16 11:44:45,416;INFO ; 26,0.00690049778703863,0.328356663372252 41 - 2023-12-16 11:44:45,421;INFO ; 27,0.006963554132391644,0.7377893941138409 42 - 2023-12-16 11:44:45,425;INFO ; 28,0.0068177642798356785,0.04438707686992304 43 - 2023-12-16 11:44:45,430;INFO ; 29,0.004277860366532809,0.054318136217835634 44 - 2023-12-16 11:44:45,437;INFO ; 30,0.004136181096380939,0.05758294976347074 45 - 2023-12-16 11:44:45,444;INFO ; 31,0.003148392325029327,0.09180388535500701 46 - 2023-12-16 11:44:45,456;INFO ; 32,0.0034184967969866763,0.12279944254969805 47 - 2023-12-16 11:44:45,461;INFO ; 33,0.002738614050252826,0.08799214942481376 48 - 2023-12-16 11:44:45,465;INFO ; 34,0.002340378401630818,0.10982599850058662 49 - 2023-12-16 11:44:45,469;INFO ; 35,0.002318543550203436,0.1874192088468983 50 - 2023-12-16 11:44:45,476;INFO ; 36,0.0023838181828763254,0.14049673625006598 51 - 2023-12-16 11:44:45,480;INFO ; 37,0.0017801377860501193,0.25278698153033746 52 - 2023-12-16 11:44:45,488;INFO ; 38,0.001926434976140927,0.30768123024704397 53 - 2023-12-16 11:44:45,492;INFO ; 39,0.0018408894375050086,0.3982324050234211 54 - 2023-12-16 11:44:45,501;INFO ; 40,0.0018205742523342274,0.5255149131154504 55 - 2023-12-16 11:44:45,505;INFO ; 41,0.002022417110833193,0.012343794696316789 56 - 2023-12-16 11:44:45,513;INFO ; 42,0.0014238367784733673,0.030454026217358272 57 - 2023-12-16 11:44:45,520;INFO ; 43,0.0011877471305847959,0.022833087486041986 58 - 2023-12-16 11:44:45,525;INFO ; 44,0.001210668149459547,0.06969126002889173 59 - 2023-12-16 11:44:45,532;INFO ; 45,0.001133623256805662,0.03897096468594406 60 - 2023-12-16 11:44:45,541;INFO ; 46,0.0009780989052674482,0.02207199085154608 61 - 2023-12-16 11:44:45,541;INFO ; bfw Assignment finished. 46 iterations and 0.0009780989052674482 final gap .. GENERATED FROM PYTHON SOURCE LINES 69-103 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. .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.817 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 ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_check_logging.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_