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

    Click :ref:`here <sphx_glr_download_intro_summary-exercises_auto_examples_plot_sprog_annual_maxima.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_intro_summary-exercises_auto_examples_plot_sprog_annual_maxima.py:


The Gumbell distribution, results
=================================

Generate the exercise results on the Gumbell distribution




.. image:: /intro/summary-exercises/auto_examples/images/sphx_glr_plot_sprog_annual_maxima_001.png
    :class: sphx-glr-single-img





.. code-block:: python

    import numpy as np
    import matplotlib.pyplot as plt

    years_nb = 21
    wspeeds = np.load('sprog-windspeeds.npy')
    max_speeds = np.array([arr.max() for arr in np.array_split(wspeeds, years_nb)])

    plt.figure()
    plt.bar(np.arange(years_nb) + 1, max_speeds)
    plt.axis('tight')
    plt.xlabel('Year')
    plt.ylabel('Annual wind speed maxima [$m/s$]')

**Total running time of the script:** ( 0 minutes  0.022 seconds)


.. _sphx_glr_download_intro_summary-exercises_auto_examples_plot_sprog_annual_maxima.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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