.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/post_process/algorithms/plot_variable_influence.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_post_process_algorithms_plot_variable_influence.py: Variables influence =================== In this example, we illustrate the use of the :class:`.VariableInfluence` plot on the Sobieski's SSBJ problem. The :class:`.VariableInfluence` post-processing performs first-order variable influence analysis. The method computes :math:`\frac{d f}{d x_i} \cdot \left(x_{i_*} - x_{initial_design}\right)`, where :math:`x_{initial_design}` is the initial value of the variable and :math:`x_{i_*}` is the optimal value of the variable. .. GENERATED FROM PYTHON SOURCE LINES 36-46 .. image-sg:: /examples/post_process/algorithms/images/sphx_glr_plot_variable_influence_001.png :alt: 9 variables explain 99% of -y_4, 5 variables explain 99% of g_1[0], 5 variables explain 99% of g_1[1], 5 variables explain 99% of g_1[2], 5 variables explain 99% of g_1[3], 5 variables explain 99% of g_1[4], 4 variables explain 99% of g_1[5], 4 variables explain 99% of g_1[6], 1 variables explain 99% of g_2, 7 variables explain 99% of g_3[0], 7 variables explain 99% of g_3[1], 3 variables explain 99% of g_3[2], 3 variables explain 99% of g_3[3] :srcset: /examples/post_process/algorithms/images/sphx_glr_plot_variable_influence_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none INFO - 16:25:55: Importing the optimization problem from the file sobieski_mdf_scenario.h5 INFO - 16:25:56: Output name; most influential variables to explain 0.99% of the output variation INFO - 16:25:56: -y_4; x_1[1], x_2, x_3, x_shared[0], x_shared[1], x_shared[2], x_shared[3], x_shared[4], x_shared[5] INFO - 16:25:56: g_1[0]; x_1[0], x_1[1], x_shared[0], x_shared[3], x_shared[5] INFO - 16:25:56: g_1[1]; x_1[0], x_1[1], x_shared[0], x_shared[3], x_shared[5] INFO - 16:25:56: g_1[2]; x_1[0], x_1[1], x_shared[0], x_shared[3], x_shared[5] INFO - 16:25:56: g_1[3]; x_1[0], x_1[1], x_shared[0], x_shared[3], x_shared[5] INFO - 16:25:56: g_1[4]; x_1[0], x_1[1], x_shared[0], x_shared[3], x_shared[5] INFO - 16:25:56: g_1[5]; x_1[0], x_1[1], x_shared[3], x_shared[5] INFO - 16:25:56: g_1[6]; x_1[0], x_1[1], x_shared[3], x_shared[5] INFO - 16:25:56: g_2; x_shared[0] INFO - 16:25:56: g_3[0]; x_2, x_3, x_shared[0], x_shared[1], x_shared[2], x_shared[4], x_shared[5] INFO - 16:25:56: g_3[1]; x_2, x_3, x_shared[0], x_shared[1], x_shared[2], x_shared[4], x_shared[5] INFO - 16:25:56: g_3[2]; x_3, x_shared[1], x_shared[2] INFO - 16:25:56: g_3[3]; x_3, x_shared[1], x_shared[2] | .. code-block:: Python from __future__ import annotations from gemseo import execute_post from gemseo.settings.post import VariableInfluence_Settings execute_post( "sobieski_mdf_scenario.h5", settings_model=VariableInfluence_Settings(save=False, show=True), ) .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.867 seconds) .. _sphx_glr_download_examples_post_process_algorithms_plot_variable_influence.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_variable_influence.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_variable_influence.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_variable_influence.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_