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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_gallery_blockreduce.py>`
        to download the full example code

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

.. _sphx_glr_gallery_blockreduce.py:


Blocked reduction operations
============================

When gridding data that has been highly oversampled in a direction (shipborne
and airborne data, for example), it is important to decimate the data before
interpolation to avoid aliasing. Class :func:`verde.BlockReduce` decimates
data by applying a reduction operation (mean, median, mode, max, etc) to the
data in blocks. For non-smooth data, like bathymetry, a blocked median filter
is a good choice.

.. GENERATED FROM PYTHON SOURCE LINES 18-47



.. image-sg:: /gallery/images/sphx_glr_blockreduce_001.png
   :alt: 10' Block Median Bathymetry
   :srcset: /gallery/images/sphx_glr_blockreduce_001.png
   :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    Original data size: 82970
    Decimated data size: 1801






|

.. code-block:: default

    import cartopy.crs as ccrs
    import matplotlib.pyplot as plt
    import numpy as np

    import verde as vd

    # We'll test this on the Baja California shipborne bathymetry data
    data = vd.datasets.fetch_baja_bathymetry()

    # Decimate the data using a blocked median with 10 arc-minute blocks
    reducer = vd.BlockReduce(reduction=np.median, spacing=10 / 60)
    coordinates, bathymetry = reducer.filter(
        (data.longitude, data.latitude), data.bathymetry_m
    )
    lon, lat = coordinates

    print("Original data size:", data.bathymetry_m.size)
    print("Decimated data size:", bathymetry.size)

    # Make a plot of the decimated data using Cartopy
    plt.figure(figsize=(7, 6))
    ax = plt.axes(projection=ccrs.Mercator())
    ax.set_title("10' Block Median Bathymetry")
    # Plot the bathymetry as colored circles.
    plt.scatter(lon, lat, c=bathymetry, s=5, transform=ccrs.PlateCarree())
    plt.colorbar().set_label("meters")
    # Use a utility function to setup the tick labels and land feature
    vd.datasets.setup_baja_bathymetry_map(ax)
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.293 seconds)


.. _sphx_glr_download_gallery_blockreduce.py:


.. only :: html

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



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

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



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

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


.. only:: html

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

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