.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/XY/NCL_xy_12.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_gallery_XY_NCL_xy_12.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_XY_NCL_xy_12.py:


NCL_xy_12.py
===============
This script illustrates the following concepts:
   - Emphasizing part of a curve in an XY plot
   - Drawing longitude labels on the X axis

See following URLs to see the reproduced NCL plot & script:
    - Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/xy_12.ncl
    - Original NCL plots: https://www.ncl.ucar.edu/Applications/Images/xy_12_1_lg.png and https://www.ncl.ucar.edu/Applications/Images/xy_12_2_lg.png

.. GENERATED FROM PYTHON SOURCE LINES 14-15

Import packages:

.. GENERATED FROM PYTHON SOURCE LINES 15-23

.. code-block:: Python


    import numpy as np
    import xarray as xr
    import matplotlib.pyplot as plt

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








.. GENERATED FROM PYTHON SOURCE LINES 24-25

Read in data:

.. GENERATED FROM PYTHON SOURCE LINES 25-30

.. code-block:: Python


    # Open a netCDF data file using xarray default engine and load the data into
    # xarrays
    ds = xr.open_dataset(gdf.get("netcdf_files/uv300.nc"))








.. GENERATED FROM PYTHON SOURCE LINES 31-32

Method 1: Splitting the line into parts and coloring them differently

.. GENERATED FROM PYTHON SOURCE LINES 32-69

.. code-block:: Python

    U = ds.isel(time=0, lon=5, drop=True).U

    plt.figure(figsize=(7, 7))
    ax = plt.axes()

    bins = [0, 5, 20]
    # Slicing data in Python excludes the last value. To include the last value we
    # can increment it by 1. This ensures that the different colored line segments
    # touch
    start = U.data[bins[0] : bins[1] + 1]
    highlight = U.data[bins[1] : bins[2] + 1]
    end = U.data[bins[2] :]

    ax.plot(U.lat[bins[0] : bins[1] + 1], start, color='black', linewidth=0.5)
    ax.plot(U.lat[bins[1] : bins[2] + 1], highlight, color='red', linewidth=1)
    ax.plot(U.lat[bins[2] :], end, color='black', linewidth=0.5)

    # Use geocat.viz.util convenience function to set axes parameters
    gv.set_axes_limits_and_ticks(
        ax,
        ylim=(-10, 40),
        xlim=(-90, 90),
        xticks=np.arange(-90, 91, 30),
        yticks=np.arange(-10, 41, 10),
        xticklabels=['90S', '60S', '30S', '0', '30N', '60N', '90N'],
    )

    # Use geocat.viz.util convenience function to add minor and major tick lines
    gv.add_major_minor_ticks(ax, x_minor_per_major=3, y_minor_per_major=5, labelsize=14)

    # Use geocat.viz.util convenience function to set titles and labels
    gv.set_titles_and_labels(
        ax, maintitle="Highlight Part of a Line", ylabel=U.long_name + " " + U.units
    )

    plt.show()




.. image-sg:: /gallery/XY/images/sphx_glr_NCL_xy_12_001.png
   :alt: Highlight Part of a Line
   :srcset: /gallery/XY/images/sphx_glr_NCL_xy_12_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 70-71

Method 2: Drawing a polygon around the section of interest

.. GENERATED FROM PYTHON SOURCE LINES 71-119

.. code-block:: Python

    U = ds.isel(time=0, lon=84, drop=True).U

    plt.figure(figsize=(7, 7))
    ax = plt.axes()

    bins = [5, 24]
    # Slicing data in Python excludes the last value. To include the last value we
    # can increment it by 1. This ensures that the highlight extends through the
    # last bin value
    highlight = U.data[bins[0] : bins[1] + 1]

    # Define bounds for region centered on the data with a width of 4
    nlat = np.shape(highlight)[0]
    top = np.empty(nlat)
    bottom = np.empty(nlat)

    for k in range(0, nlat):
        top[k] = highlight[k] + 2
        bottom[k] = highlight[k] - 2

    # Plot curves that bound the region to be colored
    ax.plot(U.lat[bins[0] : bins[1] + 1], top, color='salmon')
    ax.plot(U.lat[bins[0] : bins[1] + 1], bottom, color='salmon')

    # Fill the area between the bounds
    ax.fill_between(U.lat[bins[0] : bins[1] + 1], top, bottom, color='salmon')

    ax.plot(U.lat, U.data, color='black', linewidth=0.5)

    # Use geocat.viz.util convenience function to set axes parameters
    gv.set_axes_limits_and_ticks(
        ax,
        ylim=(-10, 50),
        xlim=(-90, 90),
        xticks=np.arange(-90, 91, 30),
        yticks=np.arange(-10, 51, 10),
        xticklabels=['90S', '60S', '30S', '0', '30N', '60N', '90N'],
    )

    # Use geocat.viz.util convenience function to add minor and major tick lines
    gv.add_major_minor_ticks(ax, x_minor_per_major=3, y_minor_per_major=5, labelsize=14)

    # Use geocat.viz.util convenience function to set titles and labels
    gv.set_titles_and_labels(
        ax, maintitle="Highlight Part of a Line", ylabel=U.long_name + " " + U.units
    )

    plt.show()



.. image-sg:: /gallery/XY/images/sphx_glr_NCL_xy_12_002.png
   :alt: Highlight Part of a Line
   :srcset: /gallery/XY/images/sphx_glr_NCL_xy_12_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.164 seconds)


.. _sphx_glr_download_gallery_XY_NCL_xy_12.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: NCL_xy_12.ipynb <NCL_xy_12.ipynb>`

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

      :download:`Download Python source code: NCL_xy_12.py <NCL_xy_12.py>`

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

      :download:`Download zipped: NCL_xy_12.zip <NCL_xy_12.zip>`


.. only:: html

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

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