.. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_reliability_sensitivity_design_of_experiments_plot_mixed_design.py: Mixed deterministic and probabilistic design of experiments =========================================================== In this example we build a mixed deterministic and probabilistic design of experiments in which levels are defined from the probabilistic distribution of the input random vector. More precisely, we show how to create an `Axial` design of experiments whose points are updated so that they match the mean and variance of the distribution. The example here is an axial design of experiments where levels are proportional to the standard deviation of each component of the random input vector, and centered on the mean vector of the random input vector. .. code-block:: default from __future__ import print_function import openturns as ot import math as m import openturns.viewer as viewer from matplotlib import pylab as plt ot.Log.Show(ot.Log.NONE) Define the underlying random vector. .. code-block:: default dim = 2 R = ot.CorrelationMatrix(dim) distribution = ot.Normal([2.0, 3.0], [0.5, 2.0], R) rv = ot.RandomVector(distribution) Define the structure of the design of experiments. .. code-block:: default levels = [1.0, 2.0, 3.0] experiment = ot.Axial(dim, levels) sample = experiment.generate() Scale the design proportionnally to the standard deviation of each component. .. code-block:: default covariance = rv.getCovariance() scaling = [m.sqrt(covariance[i, i]) for i in range(dim)] print('scaling=', scaling) sample *= scaling .. rst-class:: sphx-glr-script-out Out: .. code-block:: none scaling= [0.5, 2.0] Center the design around the mean point of the distribution. .. code-block:: default center = rv.getMean() print('center=', center) sample += center .. rst-class:: sphx-glr-script-out Out: .. code-block:: none center= [2,3] Draw the design as well as the distribution iso-values. .. code-block:: default graph = distribution.drawPDF() doe = ot.Cloud(sample) doe.setColor('red') doe.setLegend('design') graph.add(doe) view = viewer.View(graph) plt.show() .. image:: /auto_reliability_sensitivity/design_of_experiments/images/sphx_glr_plot_mixed_design_001.png :alt: [X0,X1] iso-PDF :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.140 seconds) .. _sphx_glr_download_auto_reliability_sensitivity_design_of_experiments_plot_mixed_design.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_mixed_design.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_mixed_design.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_