.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_probabilistic_modeling/distributions/plot_bayes_distribution.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_probabilistic_modeling_distributions_plot_bayes_distribution.py: Create a Bayes distribution =========================== .. GENERATED FROM PYTHON SOURCE LINES 6-16 In this example we are going to build the distribution of the random vector .. math:: ( \underline{X}|\underline{\Theta}, \underline{Y}) with X conditioned by the random variable Theta obtained with the random variable Y through a function f .. math:: \underline{\Theta}=f(\underline{Y}) .. GENERATED FROM PYTHON SOURCE LINES 18-24 .. code-block:: Python import openturns as ot import openturns.viewer as viewer from matplotlib import pylab as plt ot.Log.Show(ot.Log.NONE) .. GENERATED FROM PYTHON SOURCE LINES 25-26 create the Y distribution .. GENERATED FROM PYTHON SOURCE LINES 26-28 .. code-block:: Python YDist = ot.Uniform(-1.0, 1.0) .. GENERATED FROM PYTHON SOURCE LINES 29-30 create Theta=f(y) .. GENERATED FROM PYTHON SOURCE LINES 30-32 .. code-block:: Python f = ot.SymbolicFunction(["y"], ["y", "1 + y"]) .. GENERATED FROM PYTHON SOURCE LINES 33-34 create the X|Theta distribution .. GENERATED FROM PYTHON SOURCE LINES 34-36 .. code-block:: Python XgivenThetaDist = ot.Uniform() .. GENERATED FROM PYTHON SOURCE LINES 37-38 create the distribution .. GENERATED FROM PYTHON SOURCE LINES 38-42 .. code-block:: Python XDist = ot.BayesDistribution(XgivenThetaDist, YDist, f) XDist.setDescription(["X|Theta=f(y)", "y"]) XDist .. raw:: html
BayesDistribution


.. GENERATED FROM PYTHON SOURCE LINES 43-44 Get a sample .. GENERATED FROM PYTHON SOURCE LINES 44-46 .. code-block:: Python sample = XDist.getSample(100) .. GENERATED FROM PYTHON SOURCE LINES 47-48 draw PDF .. GENERATED FROM PYTHON SOURCE LINES 48-55 .. code-block:: Python graph = XDist.drawPDF() cloud = ot.Cloud(sample) cloud.setColor("red") cloud.setLegend("sample") graph.add(cloud) view = viewer.View(graph) plt.show() .. image-sg:: /auto_probabilistic_modeling/distributions/images/sphx_glr_plot_bayes_distribution_001.png :alt: [X|Theta=f(y),y] iso-PDF :srcset: /auto_probabilistic_modeling/distributions/images/sphx_glr_plot_bayes_distribution_001.png :class: sphx-glr-single-img .. _sphx_glr_download_auto_probabilistic_modeling_distributions_plot_bayes_distribution.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_bayes_distribution.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_bayes_distribution.py `