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

.. only:: html

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

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

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

.. _sphx_glr_examples_plots_Plotting_Surface_Analysis.py:


===============
Plotting Fronts
===============

This uses MetPy to decode text surface analysis bulletins from the Weather Prediction Center.
The features in this bulletin are then plotted on a map, making use of MetPy's various
path effects for matplotlib than can be used to represent a line as a traditional front.

.. GENERATED FROM PYTHON SOURCE LINES 13-23

.. code-block:: Python


    import cartopy.crs as ccrs
    import cartopy.feature as cfeature
    import matplotlib.pyplot as plt

    from metpy.cbook import get_test_data
    from metpy.io import parse_wpc_surface_bulletin
    from metpy.plots import (add_metpy_logo, ColdFront, OccludedFront, StationaryFront,
                             StationPlot, WarmFront)








.. GENERATED FROM PYTHON SOURCE LINES 24-28

Define a function that can be used to readily plot a bulletin that has been parsed into a
pandas `DataFrame`. This essentially encapsulates some appropriate plotting methods as well
as the necessary keyword arguments for giving the expected visual appearance for the
features.

.. GENERATED FROM PYTHON SOURCE LINES 28-59

.. code-block:: Python



    def plot_bulletin(ax, data):
        """Plot a dataframe of surface features on a map."""
        # Set some default visual styling
        size = 4
        fontsize = 9
        complete_style = {'HIGH': {'color': 'blue', 'fontsize': fontsize},
                          'LOW': {'color': 'red', 'fontsize': fontsize},
                          'WARM': {'linewidth': 1, 'path_effects': [WarmFront(size=size)]},
                          'COLD': {'linewidth': 1, 'path_effects': [ColdFront(size=size)]},
                          'OCFNT': {'linewidth': 1, 'path_effects': [OccludedFront(size=size)]},
                          'STNRY': {'linewidth': 1, 'path_effects': [StationaryFront(size=size)]},
                          'TROF': {'linewidth': 2, 'linestyle': 'dashed',
                                   'edgecolor': 'darkorange'}}

        # Handle H/L points using MetPy's StationPlot class
        for field in ('HIGH', 'LOW'):
            rows = data[data.feature == field]
            x, y = zip(*((pt.x, pt.y) for pt in rows.geometry))
            sp = StationPlot(ax, x, y, transform=ccrs.PlateCarree(), clip_on=True)
            sp.plot_text('C', [field[0]] * len(x), **complete_style[field])
            sp.plot_parameter('S', rows.strength, **complete_style[field])

        # Handle all the boundary types
        for field in ('WARM', 'COLD', 'STNRY', 'OCFNT', 'TROF'):
            rows = data[data.feature == field]
            ax.add_geometries(rows.geometry, crs=ccrs.PlateCarree(), **complete_style[field],
                              facecolor='none')









.. GENERATED FROM PYTHON SOURCE LINES 60-61

Set up the map for plotting, parse the bulletin, and plot it

.. GENERATED FROM PYTHON SOURCE LINES 61-79

.. code-block:: Python


    # Set up a default figure and map
    fig = plt.figure(figsize=(7, 7), dpi=150)
    ax = fig.add_subplot(1, 1, 1, projection=ccrs.LambertConformal(central_longitude=-100))
    ax.add_feature(cfeature.COASTLINE)
    ax.add_feature(cfeature.OCEAN)
    ax.add_feature(cfeature.LAND)
    ax.add_feature(cfeature.BORDERS)
    ax.add_feature(cfeature.STATES)
    ax.add_feature(cfeature.LAKES)

    # Parse the bulletin and plot it
    df = parse_wpc_surface_bulletin(get_test_data('WPC_sfc_fronts_20210628_1800.txt'))
    plot_bulletin(ax, df)

    ax.set_title(f'WPC Surface Analysis Valid {df.valid.dt.strftime("%HZ %d %b %Y")[0]}')
    add_metpy_logo(fig, 275, 295, size='large')
    plt.show()



.. image-sg:: /examples/plots/images/sphx_glr_Plotting_Surface_Analysis_001.png
   :alt: WPC Surface Analysis Valid 18Z 28 Jun 2021
   :srcset: /examples/plots/images/sphx_glr_Plotting_Surface_Analysis_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 6.516 seconds)


.. _sphx_glr_download_examples_plots_Plotting_Surface_Analysis.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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