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

.. only:: html

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

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

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

.. _sphx_glr_gallery_transformations_reduction_to_pole.py:


Reduction to the pole of a magnetic anomaly grid
================================================

.. GENERATED FROM PYTHON SOURCE LINES 11-78



.. image-sg:: /gallery/transformations/images/sphx_glr_reduction_to_pole_001.png
   :alt: reduction to pole
   :srcset: /gallery/transformations/images/sphx_glr_reduction_to_pole_001.png
   :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none


    Reduced to the pole magnetic grid:
     <xarray.DataArray (northing: 370, easting: 346)>
    array([[  14.15556282,   10.38429905,   10.02003492, ..., -219.81018247,
            -210.93025635, -179.38408421],
           [  -3.21243279,   -9.37121782,  -10.96584477, ..., -165.15303656,
            -158.0958179 , -133.29352054],
           [  -2.3217145 ,   -9.44938578,  -11.35228505, ..., -170.79735965,
            -165.25667548, -141.046265  ],
           ...,
           [  45.45699147,  -24.80993602,  -51.27393817, ...,  -40.42604764,
             -64.12375288,  -75.97556361],
           [  36.91047424,  -37.13717168,  -58.40649469, ...,  -34.55576242,
             -55.65612416,  -71.01718934],
           [-102.42457874, -155.67864799, -165.96649111, ...,  -36.95819436,
             -35.04014832,  -40.15060688]])
    Coordinates:
      * northing  (northing) float64 7.576e+06 7.576e+06 ... 7.595e+06 7.595e+06
      * easting   (easting) float64 4.655e+05 4.656e+05 ... 4.827e+05 4.828e+05
    <IPython.core.display.Image object>






|

.. code-block:: default

    import ensaio
    import pygmt
    import verde as vd
    import xarray as xr
    import xrft

    import harmonica as hm

    # Fetch magnetic grid over the Lightning Creek Sill Complex, Australia using
    # Ensaio and load it with Xarray
    fname = ensaio.fetch_lightning_creek_magnetic(version=1)
    magnetic_grid = xr.load_dataarray(fname)

    # Pad the grid to increase accuracy of the FFT filter
    pad_width = {
        "easting": magnetic_grid.easting.size // 3,
        "northing": magnetic_grid.northing.size // 3,
    }
    # drop the extra height coordinate
    magnetic_grid_no_height = magnetic_grid.drop_vars("height")
    magnetic_grid_padded = xrft.pad(magnetic_grid_no_height, pad_width)

    # Define the inclination and declination of the region by the time of the data
    # acquisition (1990).
    inclination, declination = -52.98, 6.51

    # Apply a reduction to the pole over the magnetic anomaly grid. We will assume
    # that the sources share the same inclination and declination as the
    # geomagnetic field.
    rtp_grid = hm.reduction_to_pole(
        magnetic_grid_padded, inclination=inclination, declination=declination
    )

    # Unpad the reduced to the pole grid
    rtp_grid = xrft.unpad(rtp_grid, pad_width)

    # Show the reduced to the pole grid
    print("\nReduced to the pole magnetic grid:\n", rtp_grid)


    # Plot original magnetic anomaly and the reduced to the pole
    fig = pygmt.Figure()
    with fig.subplot(nrows=1, ncols=2, figsize=("28c", "15c"), sharey="l"):
        # Make colormap for both plots (saturate it a little bit)
        scale = 0.5 * vd.maxabs(magnetic_grid, rtp_grid)
        pygmt.makecpt(cmap="polar+h", series=[-scale, scale], background=True)
        with fig.set_panel(panel=0):
            # Plot magnetic anomaly grid
            fig.grdimage(
                grid=magnetic_grid,
                projection="X?",
                cmap=True,
            )
            # Add colorbar
            fig.colorbar(
                frame='af+l"Magnetic anomaly [nT]"',
                position="JBC+h+o0/1c+e",
            )
        with fig.set_panel(panel=1):
            # Plot upward reduced to the pole grid
            fig.grdimage(grid=rtp_grid, projection="X?", cmap=True)
            # Add colorbar
            fig.colorbar(
                frame='af+l"Reduced to the pole [nT]"',
                position="JBC+h+o0/1c+e",
            )
    fig.show()


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

   **Total running time of the script:** ( 0 minutes  6.581 seconds)


.. _sphx_glr_download_gallery_transformations_reduction_to_pole.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: reduction_to_pole.py <reduction_to_pole.py>`



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

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


.. only:: html

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

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