.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "generated/gallery/vector_data/wind_arrows_uvw.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_vector_data_wind_arrows_uvw.py>`
        to download the full example code.

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

.. _sphx_glr_generated_gallery_vector_data_wind_arrows_uvw.py:


Wind Arrows 3D
--------------

This example demonstrates how to render 3D wind vectors.

📋 Summary
^^^^^^^^^^

The sample data contains a longitude and latitude point cloud, along with sample
winds provided in the form of three separate eastward (``U``), northward (``V``),
and upward (``W``) vector components.

The vector components are measured relative to each spatial sample point in the
point cloud.

No connectivity is provided within the sample data, so each point is a
separate location in a field of scattered points, and each point has an
associated wind vector independent of the others. We use the
:meth:`geovista.bridge.Transform.from_points` method, passing the winds with
the ``vectors`` keyword, along with the associated sample points to generate
a point cloud mesh with attached vectors.

The wind arrows are generated from this point cloud mesh via the
:meth:`pyvista.DataSetFilters.glyph` method, which scales each arrow in size and
colour relative to the magnitude of its associated wind vector.

Note that, we use all 3 wind components and amplify the upward (``W``) vector
component by a considerable factor for illustrative purposes. Vertical winds are
generally much smaller in magnitude, and tend not to be very visible otherwise.

.. tags::

    experimental 🧪,
    component: graticule, component: texture, component: vectors,
    domain: meteorology,
    filter: glyph,
    load: vectors,
    version: 0.6.0

----

.. GENERATED FROM PYTHON SOURCE LINES 50-111







.. tab-set::



   .. tab-item:: Static Scene



            
     .. image-sg:: /generated/gallery/vector_data/images/sphx_glr_wind_arrows_uvw_001.png
        :alt: wind arrows uvw
        :srcset: /generated/gallery/vector_data/images/sphx_glr_wind_arrows_uvw_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/vector_data/images/sphx_glr_wind_arrows_uvw_001.vtksz






.. code-block:: Python


    from __future__ import annotations

    import pyvista as pv

    import geovista as gv
    from geovista.pantry.data import lfric_winds


    def main() -> None:
        """Plot 3D wind arrows (UVW).

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

        """
        # Load the sample data.
        sample = lfric_winds()

        # Provide all three components, but with exaggerated upwards scaling bias.
        vectors = (sample.u, sample.v, sample.w * 1500.0)

        # Create the point cloud mesh with attached wind vectors from the
        # sample eastward (u), northward (v), and upward (w) components.
        mesh = gv.Transform.from_points(
            sample.lons,
            sample.lats,
            vectors=vectors,
            radius=1.1,
        )

        # Create a new mesh containing arrow glyphs, from the mesh vectors.
        # NOTE: choose an overall scaling factor to make the arrows a reasonable size.

        # Generate a mesh containing arrow glyphs from the wind vectors. Apply an
        # overall scaling factor to make the arrows a reasonable size, and colour
        # the arrows relative to their associated vector magnitude.
        arrows = mesh.glyph(factor=0.02, color_mode="vector")

        # Now render the plotter scene.
        p = gv.GeoPlotter()
        sargs = {"title": f"{sample.name} / {sample.units}"}
        p.add_mesh(arrows, cmap="inferno", scalar_bar_args=sargs)
        p.add_base_layer(texture=gv.natural_earth_hypsometric())
        p.add_graticule()

        # Define a specific camera position and orientation.
        cpos = pv.CameraPosition(
            position=(0.69178, -3.06569, 0.43180),
            focal_point=(0.41358, 0.07363, 0.50912),
            viewup=(0.80885, 0.05726, 0.58522),
        )
        p.camera.zoom(1.3)

        p.add_axes()
        p.show(cpos=cpos)


    if __name__ == "__main__":
        main()


.. _sphx_glr_download_generated_gallery_vector_data_wind_arrows_uvw.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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