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

.. only:: html

    .. meta::
        :keywords: codex

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

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

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

.. _sphx_glr_gallery_event_handling_resample.py:


===============
Resampling Data
===============

Downsampling lowers the sample rate or sample size of a signal. In
this tutorial, the signal is downsampled when the plot is adjusted
through dragging and zooming.

.. note::
    This example exercises the interactive capabilities of Matplotlib, and this
    will not appear in the static documentation. Please run this code on your
    machine to see the interactivity.

    You can copy and paste individual parts, or download the entire example
    using the link at the bottom of the page.

.. GENERATED FROM PYTHON SOURCE LINES 18-78



.. image-sg:: /gallery/event_handling/images/sphx_glr_resample_001.png
   :alt: resample
   :srcset: /gallery/event_handling/images/sphx_glr_resample_001.png, /gallery/event_handling/images/sphx_glr_resample_001_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np


    # A class that will downsample the data and recompute when zoomed.
    class DataDisplayDownsampler:
        def __init__(self, xdata, ydata):
            self.origYData = ydata
            self.origXData = xdata
            self.max_points = 50
            self.delta = xdata[-1] - xdata[0]

        def downsample(self, xstart, xend):
            # get the points in the view range
            mask = (self.origXData > xstart) & (self.origXData < xend)
            # dilate the mask by one to catch the points just outside
            # of the view range to not truncate the line
            mask = np.convolve([1, 1, 1], mask, mode='same').astype(bool)
            # sort out how many points to drop
            ratio = max(np.sum(mask) // self.max_points, 1)

            # mask data
            xdata = self.origXData[mask]
            ydata = self.origYData[mask]

            # downsample data
            xdata = xdata[::ratio]
            ydata = ydata[::ratio]

            print(f"using {len(ydata)} of {np.sum(mask)} visible points")

            return xdata, ydata

        def update(self, ax):
            # Update the line
            lims = ax.viewLim
            if abs(lims.width - self.delta) > 1e-8:
                self.delta = lims.width
                xstart, xend = lims.intervalx
                self.line.set_data(*self.downsample(xstart, xend))
                ax.figure.canvas.draw_idle()


    # Create a signal
    xdata = np.linspace(16, 365, (365-16)*4)
    ydata = np.sin(2*np.pi*xdata/153) + np.cos(2*np.pi*xdata/127)

    d = DataDisplayDownsampler(xdata, ydata)

    fig, ax = plt.subplots()

    # Hook up the line
    d.line, = ax.plot(xdata, ydata, 'o-')
    ax.set_autoscale_on(False)  # Otherwise, infinite loop

    # Connect for changing the view limits
    ax.callbacks.connect('xlim_changed', d.update)
    ax.set_xlim(16, 365)
    plt.show()


.. _sphx_glr_download_gallery_event_handling_resample.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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