.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/Distributions/plot_distributions.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_Distributions_plot_distributions.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_Distributions_plot_distributions.py:


Distribution Class
++++++++++++++++++

Handles the initialization of different statistical distribution

.. GENERATED FROM PYTHON SOURCE LINES 9-19

.. code-block:: Python

    from geobipy import Distribution
    from geobipy import plotting as cP
    import matplotlib.pyplot as plt
    import numpy as np

    from numpy.random import Generator
    from numpy.random import PCG64DXSM
    generator = PCG64DXSM(seed=0)
    prng = Generator(generator)








.. GENERATED FROM PYTHON SOURCE LINES 20-22

Univariate Normal Distribution
++++++++++++++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 22-37

.. code-block:: Python

    D = Distribution('Normal', 0.0, 1.0, prng=prng)

    # Get the bins of the Distribution from +- 4 standard deviations of the mean
    bins = D.bins()

    # Grab random samples from the distribution
    D.rng(10)

    # We can then get the Probability Density Function for those bins
    pdf = D.probability(bins, log=False)

    # And we can plot that PDF
    plt.figure()
    plt.plot(bins, pdf)




.. image-sg:: /examples/Distributions/images/sphx_glr_plot_distributions_001.png
   :alt: plot distributions
   :srcset: /examples/Distributions/images/sphx_glr_plot_distributions_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    [<matplotlib.lines.Line2D object at 0x14557e4b0>]



.. GENERATED FROM PYTHON SOURCE LINES 39-41

Multivariate Normal Distribution
++++++++++++++++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 41-45

.. code-block:: Python

    D = Distribution('MvNormal',[0.0,1.0,2.0],[1.0,1.0,1.0], prng=prng)
    D.rng()






.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    array([ 0.64050649,  1.77177243, -0.34500474])



.. GENERATED FROM PYTHON SOURCE LINES 46-47

Uniform Distribution

.. GENERATED FROM PYTHON SOURCE LINES 47-49

.. code-block:: Python

    D = Distribution('Uniform', 0.0, 1.0, prng=prng)
    D.bins()




.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    DataArray([0.        , 0.01010101, 0.02020202, 0.03030303, 0.04040404,
               0.05050505, 0.06060606, 0.07070707, 0.08080808, 0.09090909,
               0.1010101 , 0.11111111, 0.12121212, 0.13131313, 0.14141414,
               0.15151515, 0.16161616, 0.17171717, 0.18181818, 0.19191919,
               0.2020202 , 0.21212121, 0.22222222, 0.23232323, 0.24242424,
               0.25252525, 0.26262626, 0.27272727, 0.28282828, 0.29292929,
               0.3030303 , 0.31313131, 0.32323232, 0.33333333, 0.34343434,
               0.35353535, 0.36363636, 0.37373737, 0.38383838, 0.39393939,
               0.4040404 , 0.41414141, 0.42424242, 0.43434343, 0.44444444,
               0.45454545, 0.46464646, 0.47474747, 0.48484848, 0.49494949,
               0.50505051, 0.51515152, 0.52525253, 0.53535354, 0.54545455,
               0.55555556, 0.56565657, 0.57575758, 0.58585859, 0.5959596 ,
               0.60606061, 0.61616162, 0.62626263, 0.63636364, 0.64646465,
               0.65656566, 0.66666667, 0.67676768, 0.68686869, 0.6969697 ,
               0.70707071, 0.71717172, 0.72727273, 0.73737374, 0.74747475,
               0.75757576, 0.76767677, 0.77777778, 0.78787879, 0.7979798 ,
               0.80808081, 0.81818182, 0.82828283, 0.83838384, 0.84848485,
               0.85858586, 0.86868687, 0.87878788, 0.88888889, 0.8989899 ,
               0.90909091, 0.91919192, 0.92929293, 0.93939394, 0.94949495,
               0.95959596, 0.96969697, 0.97979798, 0.98989899, 1.        ])




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 3.202 seconds)


.. _sphx_glr_download_examples_Distributions_plot_distributions.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_distributions.ipynb <plot_distributions.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_distributions.py <plot_distributions.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_distributions.zip <plot_distributions.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_