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

.. only:: html

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

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

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

.. _sphx_glr_examples_plotting_plot_rhi_contours_differential_reflectivity.py:


====================================================================
Create an RHI plot with reflectivity contour lines from an MDV file
====================================================================

An example which creates an RHI plot of reflectivity using a RadarDisplay object
and adding differnential Reflectivity contours from the same MDV file.

.. GENERATED FROM PYTHON SOURCE LINES 10-99



.. image-sg:: /examples/plotting/images/sphx_glr_plot_rhi_contours_differential_reflectivity_001.png
   :alt: ARM SGP C-SAPR 189.0 Deg. 2011-05-24T22:06:11Z  Equivalent reflectivity factor
   :srcset: /examples/plotting/images/sphx_glr_plot_rhi_contours_differential_reflectivity_001.png
   :class: sphx-glr-single-img





.. code-block:: Python

    print(__doc__)

    # Author: Cory Weber (cweber@anl.gov)
    # License: BSD 3 clause
    import matplotlib.pyplot as plt
    import numpy as np
    import scipy.ndimage as ndimage

    import pyart
    from pyart.testing import get_test_data

    filename = get_test_data("220629.mdv")

    # create the plot using RadarDisplay
    sweep = 0
    # read file
    radar = pyart.io.read_mdv(filename)
    display = pyart.graph.RadarDisplay(radar)
    fig = plt.figure(figsize=[20, 5])
    ax = fig.add_subplot(111)

    # plot reflectivity
    # alpha=0.25 sets the transparency of the pcolormesh to 75% transparent against
    # the default white. matplolib overlaps the edges of the pcolormesh and creates
    # a visable border around the edge, even with the default of edgecolor set to
    # 'none' the transparancy is effected. the flowing paramters are designed to
    # compensate for that:
    # edgecolors=(1.0, 1.0, 1.0, 0.1) sets the lines between patches to nearly
    # transparent
    # linewidth=0.00015 makes lines between patches very small
    # antialiased=true removes moire patterns.

    display.plot(
        "reflectivity",
        sweep=sweep,
        vmin=-8,
        vmax=64.0,
        fig=fig,
        ax=ax,
        colorbar_label="Reflectivity (dB)",
        alpha=0.75,
        edgecolors=(0.5, 0.5, 0.5, 0.3),
        linewidth=0.001,
        antialiased=True,
    )

    # Normal no alpha
    # display.plot('reflectivity', sweep=sweep, vmin=-8, vmax=64.0, fig=fig,
    #             ax=ax, colorbar_label='Reflectivity (dB)', antialiased=True)

    # get data
    start = radar.get_start(sweep)
    end = radar.get_end(sweep) + 1
    data = radar.get_field(sweep, "differential_reflectivity")
    x, y, z = radar.get_gate_x_y_z(sweep, edges=False)

    x /= 1000.0
    y /= 1000.0
    z /= 1000.0

    # apply a gaussian blur to the data set for nice smooth lines:
    # sigma adjusts the distance effect of blending each cell,
    # 4 is arbirarly set for visual impact.
    data = ndimage.gaussian_filter(data, sigma=4)

    # calculate (R)ange
    R = np.sqrt(x**2 + y**2) * np.sign(y)
    R = -R
    display.set_limits(xlim=[0, 40], ylim=[0, 15])

    # add contours
    # creates steps 35 to 100 by 5
    levels = np.arange(-3, 4, 0.25)
    # levels_rain = np.arange(1, 4, 0.5)
    levels_ice = np.arange(-2, -0, 0.5)
    levels_rain = [0.75]

    # adds contours to plot
    contours = ax.contour(R, z, data, levels, linewidths=1, colors="k", antialiased=True)
    # adds more contours for ice and rain, matplotlib supports multiple sets of
    # contours ice
    contours_ice = ax.contour(R, z, data, levels_ice, linewidths=2, colors="blue")
    # contours heavy rain
    contours_rain = ax.contour(R, z, data, levels_rain, linewidths=2, colors="red")

    # adds contour labels (fmt= '%r' displays 10.0 vs 10.0000)
    plt.clabel(contours, levels, fmt="%r", inline=True, fontsize=10)

    plt.show()


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

   **Total running time of the script:** (0 minutes 1.650 seconds)


.. _sphx_glr_download_examples_plotting_plot_rhi_contours_differential_reflectivity.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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