.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/dataset/use_cases/plot_burgers.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_examples_dataset_use_cases_plot_burgers.py: Burgers dataset =============== Dataset consisting of solutions to Burgers' equation. .. GENERATED FROM PYTHON SOURCE LINES 27-35 .. code-block:: default from __future__ import annotations from gemseo import configure_logger from gemseo import create_benchmark_dataset from gemseo.post.dataset.curves import Curves configure_logger() .. rst-class:: sphx-glr-script-out .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 36-40 Load Burgers' dataset ----------------------- We can easily load this dataset by means of the high-level function :func:`~gemseo.create_benchmark_dataset`: .. GENERATED FROM PYTHON SOURCE LINES 40-43 .. code-block:: default dataset = create_benchmark_dataset("BurgersDataset") print(dataset) .. rst-class:: sphx-glr-script-out .. code-block:: none GROUP inputs outputs ... VARIABLE t u_t ... COMPONENT 0 0 1 ... 498 499 500 0 0.000000 -8.610583e-43 0.012566 ... -0.025133 -0.012566 8.610583e-43 1 0.068966 -2.580645e-01 -0.246309 ... -0.281576 -0.269820 -2.580645e-01 2 0.137931 -4.848485e-01 -0.473805 ... -0.506935 -0.495892 -4.848485e-01 3 0.206897 -6.857143e-01 -0.675302 ... -0.706539 -0.696126 -6.857143e-01 4 0.275862 -8.648649e-01 -0.855016 ... -0.884563 -0.874714 -8.648649e-01 5 0.344828 -1.025641e+00 -1.016297 ... -1.044329 -1.034985 -1.025641e+00 6 0.413793 -1.170732e+00 -1.161843 ... -1.188509 -1.179620 -1.170732e+00 7 0.482759 -1.302326e+00 -1.293851 ... -1.319276 -1.310801 -1.302326e+00 8 0.551724 -1.422222e+00 -1.414124 ... -1.438419 -1.430321 -1.422222e+00 9 0.620690 -1.531915e+00 -1.524161 ... -1.547404 -1.539655 -1.531904e+00 10 0.689655 -1.632653e+00 -1.625216 ... -1.642738 -1.636298 -1.629650e+00 11 0.758621 -1.725490e+00 -1.718345 ... -1.068848 -1.175574 -1.266034e+00 12 0.827586 -1.811321e+00 -1.804445 ... 1.494420 1.473941 1.447486e+00 13 0.896552 -1.890909e+00 -1.884283 ... 1.407409 1.413715 1.419947e+00 14 0.965517 -1.964912e+00 -1.958519 ... 1.218988 1.225377 1.231764e+00 15 1.034483 -2.033898e+00 -2.027722 ... 1.042093 1.048270 1.054446e+00 16 1.103448 -2.098361e+00 -2.092386 ... 0.876779 0.882753 8.887274e-01 17 1.172414 -2.158730e+00 -2.152946 ... 0.721961 0.727745 7.335297e-01 18 1.241379 -2.215385e+00 -2.209778 ... 0.576670 0.582276 5.878827e-01 19 1.310345 -2.268657e+00 -2.263218 ... 0.440053 0.445492 4.509310e-01 20 1.379310 -2.318841e+00 -2.313559 ... 0.311355 0.316637 3.219185e-01 21 1.448276 -2.366197e+00 -2.361064 ... 0.189909 0.195042 2.001743e-01 22 1.517241 -2.410959e+00 -2.405967 ... 0.075117 0.080109 8.510101e-02 23 1.586207 -2.453333e+00 -2.448474 ... -0.033553 -0.028694 -2.383501e-02 24 1.655172 -2.493506e+00 -2.488774 ... -0.136578 -0.131845 -1.271120e-01 25 1.724138 -2.531646e+00 -2.527033 ... -0.234386 -0.229773 -2.251598e-01 26 1.793103 -2.567901e+00 -2.563402 ... -0.327364 -0.322865 -3.183658e-01 27 1.862069 -2.602410e+00 -2.598019 ... -0.415861 -0.411470 -4.070798e-01 28 1.931034 -2.635294e+00 -2.631007 ... -0.500194 -0.495906 -4.916191e-01 29 2.000000 -2.666667e+00 -2.662478 ... -0.580649 -0.576460 -5.722716e-01 [30 rows x 502 columns] .. GENERATED FROM PYTHON SOURCE LINES 44-46 Show the input and output data ------------------------------ .. GENERATED FROM PYTHON SOURCE LINES 46-49 .. code-block:: default print(dataset.input_dataset) print(dataset.output_dataset) .. rst-class:: sphx-glr-script-out .. code-block:: none GROUP inputs VARIABLE t COMPONENT 0 0 0.000000 1 0.068966 2 0.137931 3 0.206897 4 0.275862 5 0.344828 6 0.413793 7 0.482759 8 0.551724 9 0.620690 10 0.689655 11 0.758621 12 0.827586 13 0.896552 14 0.965517 15 1.034483 16 1.103448 17 1.172414 18 1.241379 19 1.310345 20 1.379310 21 1.448276 22 1.517241 23 1.586207 24 1.655172 25 1.724138 26 1.793103 27 1.862069 28 1.931034 29 2.000000 GROUP outputs ... VARIABLE u_t ... COMPONENT 0 1 2 ... 498 499 500 0 -8.610583e-43 0.012566 0.025133 ... -0.025133 -0.012566 8.610583e-43 1 -2.580645e-01 -0.246309 -0.234553 ... -0.281576 -0.269820 -2.580645e-01 2 -4.848485e-01 -0.473805 -0.462762 ... -0.506935 -0.495892 -4.848485e-01 3 -6.857143e-01 -0.675302 -0.664890 ... -0.706539 -0.696126 -6.857143e-01 4 -8.648649e-01 -0.855016 -0.845166 ... -0.884563 -0.874714 -8.648649e-01 5 -1.025641e+00 -1.016297 -1.006953 ... -1.044329 -1.034985 -1.025641e+00 6 -1.170732e+00 -1.161843 -1.152955 ... -1.188509 -1.179620 -1.170732e+00 7 -1.302326e+00 -1.293851 -1.285376 ... -1.319276 -1.310801 -1.302326e+00 8 -1.422222e+00 -1.414124 -1.406026 ... -1.438419 -1.430321 -1.422222e+00 9 -1.531915e+00 -1.524161 -1.516407 ... -1.547404 -1.539655 -1.531904e+00 10 -1.632653e+00 -1.625216 -1.617779 ... -1.642738 -1.636298 -1.629650e+00 11 -1.725490e+00 -1.718345 -1.711199 ... -1.068848 -1.175574 -1.266034e+00 12 -1.811321e+00 -1.804445 -1.797569 ... 1.494420 1.473941 1.447486e+00 13 -1.890909e+00 -1.884283 -1.877657 ... 1.407409 1.413715 1.419947e+00 14 -1.964912e+00 -1.958519 -1.952125 ... 1.218988 1.225377 1.231764e+00 15 -2.033898e+00 -2.027722 -2.021545 ... 1.042093 1.048270 1.054446e+00 16 -2.098361e+00 -2.092386 -2.086412 ... 0.876779 0.882753 8.887274e-01 17 -2.158730e+00 -2.152946 -2.147161 ... 0.721961 0.727745 7.335297e-01 18 -2.215385e+00 -2.209778 -2.204172 ... 0.576670 0.582276 5.878827e-01 19 -2.268657e+00 -2.263218 -2.257778 ... 0.440053 0.445492 4.509310e-01 20 -2.318841e+00 -2.313559 -2.308278 ... 0.311355 0.316637 3.219185e-01 21 -2.366197e+00 -2.361064 -2.355932 ... 0.189909 0.195042 2.001743e-01 22 -2.410959e+00 -2.405967 -2.400975 ... 0.075117 0.080109 8.510101e-02 23 -2.453333e+00 -2.448474 -2.443615 ... -0.033553 -0.028694 -2.383501e-02 24 -2.493506e+00 -2.488774 -2.484041 ... -0.136578 -0.131845 -1.271120e-01 25 -2.531646e+00 -2.527033 -2.522420 ... -0.234386 -0.229773 -2.251598e-01 26 -2.567901e+00 -2.563402 -2.558903 ... -0.327364 -0.322865 -3.183658e-01 27 -2.602410e+00 -2.598019 -2.593628 ... -0.415861 -0.411470 -4.070798e-01 28 -2.635294e+00 -2.631007 -2.626719 ... -0.500194 -0.495906 -4.916191e-01 29 -2.666667e+00 -2.662478 -2.658289 ... -0.580649 -0.576460 -5.722716e-01 [30 rows x 501 columns] .. GENERATED FROM PYTHON SOURCE LINES 50-53 Load customized dataset ----------------------- Load the data with custom parameters and input-output naming. .. GENERATED FROM PYTHON SOURCE LINES 53-58 .. code-block:: default dataset = create_benchmark_dataset( "BurgersDataset", n_samples=20, n_x=700, fluid_viscosity=0.03 ) print(dataset) .. rst-class:: sphx-glr-script-out .. code-block:: none GROUP inputs outputs ... VARIABLE t u_t ... COMPONENT 0 0 1 ... 697 698 699 0 0.000000 -8.337238e-143 0.008989 ... -0.017978 -0.008989 8.337238e-143 1 0.105263 -3.809524e-01 -0.372820 ... -0.397218 -0.389085 -3.809524e-01 2 0.210526 -6.956522e-01 -0.688227 ... -0.710503 -0.703078 -6.956522e-01 3 0.315789 -9.600000e-01 -0.953168 ... -0.973663 -0.966832 -9.600000e-01 4 0.421053 -1.185185e+00 -1.178860 ... -1.197836 -1.191511 -1.185185e+00 5 0.526316 -1.379310e+00 -1.373421 ... -1.391089 -1.385200 -1.379310e+00 6 0.631579 -1.548387e+00 -1.542878 ... -1.559406 -1.553896 -1.548387e+00 7 0.736842 -1.696970e+00 -1.691794 ... -1.707233 -1.702094 -1.696940e+00 8 0.842105 -1.828571e+00 -1.823692 ... 1.572538 1.577416 1.582292e+00 9 0.947368 -1.945946e+00 -1.941330 ... 1.271323 1.275939 1.280555e+00 10 1.052632 -2.051282e+00 -2.046903 ... 1.000999 1.005378 1.009757e+00 11 1.157895 -2.146341e+00 -2.142176 ... 0.757047 0.761213 7.653786e-01 12 1.263158 -2.232558e+00 -2.228586 ... 0.535789 0.539761 5.437330e-01 13 1.368421 -2.311111e+00 -2.307316 ... 0.334199 0.337994 3.417894e-01 14 1.473684 -2.382979e+00 -2.379345 ... 0.149765 0.153399 1.570324e-01 15 1.578947 -2.448980e+00 -2.445494 ... -0.019613 -0.016128 -1.264243e-02 16 1.684211 -2.509804e+00 -2.506455 ... -0.175707 -0.172358 -1.690094e-01 17 1.789474 -2.566038e+00 -2.562815 ... -0.320020 -0.316797 -3.135751e-01 18 1.894737 -2.618182e+00 -2.615077 ... -0.453837 -0.450732 -4.476269e-01 19 2.000000 -2.666667e+00 -2.663670 ... -0.578264 -0.575268 -5.722716e-01 [20 rows x 701 columns] .. GENERATED FROM PYTHON SOURCE LINES 59-61 Plot the data ------------- .. GENERATED FROM PYTHON SOURCE LINES 61-62 .. code-block:: default Curves(dataset, "x", "u_t").execute(save=False, show=True) .. image-sg:: /examples/dataset/use_cases/images/sphx_glr_plot_burgers_001.png :alt: plot burgers :srcset: /examples/dataset/use_cases/images/sphx_glr_plot_burgers_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none [
] .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.615 seconds) .. _sphx_glr_download_examples_dataset_use_cases_plot_burgers.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_burgers.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_burgers.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_