.. _sphx_glr_gallery_event_handling_pick_event_demo2.py:


================
Pick Event Demo2
================

compute the mean and standard deviation (stddev) of 100 data sets and plot
mean vs stddev.  When you click on one of the mu, sigma points, plot the raw
data from the dataset that generated the mean and stddev.




.. image:: /gallery/event_handling/images/sphx_glr_pick_event_demo2_001.png
    :align: center





.. code-block:: python

    import numpy as np
    import matplotlib.pyplot as plt


    X = np.random.rand(100, 1000)
    xs = np.mean(X, axis=1)
    ys = np.std(X, axis=1)

    fig, ax = plt.subplots()
    ax.set_title('click on point to plot time series')
    line, = ax.plot(xs, ys, 'o', picker=5)  # 5 points tolerance


    def onpick(event):

        if event.artist != line:
            return True

        N = len(event.ind)
        if not N:
            return True

        figi = plt.figure()
        for subplotnum, dataind in enumerate(event.ind):
            ax = figi.add_subplot(N, 1, subplotnum + 1)
            ax.plot(X[dataind])
            ax.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
                    transform=ax.transAxes, va='top')
            ax.set_ylim(-0.5, 1.5)
        figi.show()
        return True

    fig.canvas.mpl_connect('pick_event', onpick)

    plt.show()

**Total running time of the script:** ( 0 minutes  0.019 seconds)



.. only :: html

 .. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: pick_event_demo2.py <pick_event_demo2.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: pick_event_demo2.ipynb <pick_event_demo2.ipynb>`


.. only:: html

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

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