.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/Vectors/NCL_vector_4.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_gallery_Vectors_NCL_vector_4.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_Vectors_NCL_vector_4.py:


NCL_vector_4.py
===============
Plot U & V vectors globally, colored according to temperature

This script illustrates the following concepts:
  - Coloring vectors based on temperature data
  - Changing the scale of the vectors on the plot

See following URLs to see the reproduced NCL plot & script:
    - Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/vector_4.ncl
    - Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/vector_4_lg.png

.. GENERATED FROM PYTHON SOURCE LINES 16-17

Import packages:

.. GENERATED FROM PYTHON SOURCE LINES 17-27

.. code-block:: Python


    import xarray as xr
    from matplotlib import pyplot as plt
    import cartopy
    import cartopy.crs as ccrs
    import cmaps

    import geocat.datafiles as gdf
    import geocat.viz as gv








.. GENERATED FROM PYTHON SOURCE LINES 28-29

Read in data:

.. GENERATED FROM PYTHON SOURCE LINES 29-36

.. code-block:: Python


    # Open a netCDF data file using xarray default engine and load the data into xarrays
    file_in = xr.open_dataset(gdf.get("netcdf_files/83.nc"))

    # Extract slices of lon and lat for first timestamp and 13th lev
    ds = file_in.isel(time=0, lev=12, lon=slice(0, -1, 5), lat=slice(2, -1, 3))








.. GENERATED FROM PYTHON SOURCE LINES 37-38

Plot:

.. GENERATED FROM PYTHON SOURCE LINES 38-112

.. code-block:: Python


    # Because there is no equivalent to ``CurlyVector`` in ``geocat.viz`` yet,
    # this plot does not look as identical as the NCL version.

    # Generate figure (set its size (width, height) in inches)
    fig = plt.figure(figsize=(10, 7.25))

    # Generate axes using Cartopy projection
    ax = plt.axes(projection=ccrs.PlateCarree())

    # Import an NCL colormap and truncate it for a range and color levels
    cmap = gv.truncate_colormap(cmaps.BlAqGrYeOrReVi200, minval=0.03, maxval=0.95, n=16)

    # Draw vector plot
    # (there is no matplotlib equivalent to "CurlyVector" yet)
    Q = plt.quiver(
        ds['lon'],
        ds['lat'],
        ds['U'].data,
        ds['V'].data,
        ds['T'].data,
        cmap=cmap,
        zorder=1,
        pivot="middle",
        width=0.001,
    )
    plt.clim(228, 292)

    # Draw legend for vector plot
    ax.add_patch(
        plt.Rectangle(
            (150, -140), 30, 30, facecolor='white', edgecolor='black', clip_on=False
        )
    )
    qk = ax.quiverkey(
        Q, 0.93, 0.06, 10, r'10 $m/s$', labelpos='N', coordinates='figure', color='black'
    )

    # Use geocat.viz.util convenience function to add minor and major tick lines
    gv.add_major_minor_ticks(ax, labelsize=12)

    # Use geocat.viz.util convenience function to make plots look like NCL plots by using latitude, longitude tick labels
    gv.add_lat_lon_ticklabels(ax)

    # Set major and minor ticks
    plt.xticks(range(-180, 181, 30))
    plt.yticks(range(-90, 91, 30))

    # Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
    gv.set_titles_and_labels(
        ax,
        maintitle="Vectors colored by a scalar map",
        lefttitle="Temperature",
        righttitle=r"$^{\circ}$K",
    )

    cax = plt.axes((0.225, 0.075, 0.55, 0.025))
    cbar = fig.colorbar(
        Q,
        ax=ax,
        cax=cax,
        orientation='horizontal',
        ticks=range(232, 289, 8),
        drawedges=True,
    )

    # Turn on continent shading
    ax.add_feature(
        cartopy.feature.LAND, edgecolor='lightgray', facecolor='lightgray', zorder=0
    )

    # Generate plot!
    plt.tight_layout()
    plt.show()



.. image-sg:: /gallery/Vectors/images/sphx_glr_NCL_vector_4_001.png
   :alt: Temperature, Vectors colored by a scalar map, $^{\circ}$K
   :srcset: /gallery/Vectors/images/sphx_glr_NCL_vector_4_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    /home/docs/checkouts/readthedocs.org/user_builds/geocat-examples/checkouts/latest/Gallery/Vectors/NCL_vector_4.py:110: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
      plt.tight_layout()





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

   **Total running time of the script:** (0 minutes 0.183 seconds)


.. _sphx_glr_download_gallery_Vectors_NCL_vector_4.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: NCL_vector_4.ipynb <NCL_vector_4.ipynb>`

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

      :download:`Download Python source code: NCL_vector_4.py <NCL_vector_4.py>`

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

      :download:`Download zipped: NCL_vector_4.zip <NCL_vector_4.zip>`


.. only:: html

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

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