

.. _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.




.. image:: /gallery/event_handling/images/sphx_glr_resample_001.png
    :align: center





.. code-block:: python


    import numpy as np
    import matplotlib.pyplot as plt


    # A class that will downsample the data and recompute when zoomed.
    class DataDisplayDownsampler(object):
        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], 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("using {} of {} visible points".format(
                len(ydata), np.sum(mask)))

            return xdata, ydata

        def update(self, ax):
            # Update the line
            lims = ax.viewLim
            if np.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()

**Total running time of the script:** ( 0 minutes  0.036 seconds)



.. container:: sphx-glr-footer


  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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

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

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