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

.. only:: html

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

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

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

.. _sphx_glr_generated_gallery_extraction_wedge_manifold.py:


Wedge Extraction
----------------

This example demonstrates how to extract a region using a geodesic wedge manifold.

📋 Summary
^^^^^^^^^^

This example uses an unstructured Met Office LFRic C48 cubed-sphere mesh of
surface altitude data.

Three separate geodesic wedge manifolds are constructed to extract the cells
of the mesh contained within the wedge. Each wedge uses a different enclosure
preference to extract the cells.

The regions extracted by each wedge are rendered along with the boundary where
the manifold intersects the surface of the mesh. A different colour is used
for each manifold boundary.

The **red boundary** contains only those cells where all points defining the
face of a cell are within the manifold.

The **purple boundary** contains only those cells where at least one point
that defines the face of the cell is within the manifold.

The **orange boundary** contains only those cells where the center of the
cell is within the manifold.

Each of the extracted mesh regions contain quad cells and are constructed from
CF UGRID unstructured cell points and connectivity. A Natural Earth base layer
is also rendered along with Natural Earth coastlines.

.. tags::

    component: coastlines, component: manifold, component: texture,
    domain: orography,
    sample: unstructured,
    version: 0.6.0

----

.. GENERATED FROM PYTHON SOURCE LINES 50-110







.. tab-set::



   .. tab-item:: Static Scene



            
     .. image-sg:: /generated/gallery/extraction/images/sphx_glr_wedge_manifold_001.png
        :alt: wedge manifold
        :srcset: /generated/gallery/extraction/images/sphx_glr_wedge_manifold_001.png
        :class: sphx-glr-single-img
     


   .. tab-item:: Interactive Scene



       .. offlineviewer:: /home/docs/checkouts/readthedocs.org/user_builds/geovista-ja/checkouts/latest/geovista/docs/src/generated/gallery/extraction/images/sphx_glr_wedge_manifold_001.vtksz






.. code-block:: Python


    from __future__ import annotations

    import geovista as gv
    from geovista.geodesic import wedge
    from geovista.pantry.meshes import lfric_orog


    def main() -> None:
        """Extract and plot 3 wedge regions, each using different enclosure methods.

        Notes
        -----
        .. versionadded:: 0.6.0

        """
        # Load the sample mesh.
        mesh = lfric_orog()

        # Calculate the sample data range.
        clim = mesh.get_data_range()

        # Create 3 different wedge geodesic bounding-box manifolds.
        bbox_1 = wedge(-25, 25)
        bbox_2 = wedge(65, 115)
        bbox_3 = wedge(155, 205)

        # Extract the underlying sample mesh within each manifold using a different
        # preference which defines the criterion of sample mesh cell enclosure.
        region_1 = bbox_1.enclosed(mesh, preference="cell")
        region_2 = bbox_2.enclosed(mesh, preference="point")
        region_3 = bbox_3.enclosed(mesh, preference="center")

        p = gv.GeoPlotter()

        # Add the 3 extracted regions.
        sargs = {"title": "Surface Altitude / m", "fmt": "%.0f"}
        p.add_mesh(region_1, clim=clim, scalar_bar_args=sargs)
        p.add_mesh(region_2, clim=clim, scalar_bar_args=sargs)
        p.add_mesh(region_3, clim=clim, scalar_bar_args=sargs)

        # Add the surface boundary of each wedge region.
        p.add_mesh(bbox_1.boundary(mesh), color="red", line_width=3)
        p.add_mesh(bbox_2.boundary(mesh), color="purple", line_width=3)
        p.add_mesh(bbox_3.boundary(mesh), color="orange", line_width=3)

        # Add coastlines and a texture mapped base layer.
        p.add_base_layer(texture=gv.natural_earth_hypsometric())
        p.add_coastlines(resolution="10m")

        # Define a specific camera position.
        p.view_vector(vector=(1, 1, 1))
        p.camera.zoom(1.2)

        p.add_axes()
        p.show()


    if __name__ == "__main__":
        main()


.. _sphx_glr_download_generated_gallery_extraction_wedge_manifold.py:

.. only:: html

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

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

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: wedge_manifold.zip <wedge_manifold.zip>`


.. only:: html

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

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