.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/Polygons/NCL_polyg_8.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_gallery_Polygons_NCL_polyg_8.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_Polygons_NCL_polyg_8.py:


NCL_polyg_8.py
==============
This script illustrates the following concepts:
   - Drawing a scatter plot on a map
   - Changing the marker color and size in a map plot
   - Plotting station locations using markers
   - Manually creating a legend using markers and text
   - Adding text to a plot
   - Generating dummy data using "random_uniform"
   - Binning data

See following URLs to see the reproduced NCL plot & script:
    - Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/polyg_8.ncl
    - Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/polyg_8_lg.png

.. GENERATED FROM PYTHON SOURCE LINES 19-20

Import packages:

.. GENERATED FROM PYTHON SOURCE LINES 20-29

.. code-block:: Python


    import numpy as np
    import cartopy.crs as ccrs
    import cartopy.feature as cfeature
    from cartopy.mpl.gridliner import LongitudeFormatter, LatitudeFormatter
    import matplotlib.pyplot as plt

    import geocat.viz as gv








.. GENERATED FROM PYTHON SOURCE LINES 30-31

Generate dummy data

.. GENERATED FROM PYTHON SOURCE LINES 31-53

.. code-block:: Python

    npts = 100
    random = np.random.default_rng(seed=1)
    # Create random coordinates to position the markers
    lat = random.uniform(low=25, high=50, size=npts)
    lon = random.uniform(low=-125, high=-70, size=npts)
    # Create random data which the color will be based off of
    r = random.uniform(low=-1.2, high=35, size=npts)

    bins = [0, 5, 10, 15, 20, 23, 26]
    colors = [
        'mediumpurple',
        'mediumblue',
        'blue',
        'green',
        'limegreen',
        'greenyellow',
        'gold',
        'orangered',
    ]
    # increasing sizes for the markers in each bin
    sizes = np.linspace(15, 25, len(bins))








.. GENERATED FROM PYTHON SOURCE LINES 54-55

Plot:

.. GENERATED FROM PYTHON SOURCE LINES 55-122

.. code-block:: Python

    plt.figure(figsize=(9, 6))
    projection = ccrs.PlateCarree()
    ax = plt.axes(projection=projection)
    ax.set_extent([-125, -70, 25, 50], crs=projection)

    # Draw land
    ax.add_feature(cfeature.LAND, color='silver', zorder=0)
    ax.add_feature(cfeature.LAKES, color='white', zorder=0)

    # Use geocat.viz.util convenience function to set axes tick values
    gv.set_axes_limits_and_ticks(
        ax, xticks=np.linspace(-120, -80, 3), yticks=np.linspace(30, 50, 3)
    )

    # Use geocat.viz.util convenience function to make latitude and longitude tick
    # labels
    gv.add_lat_lon_ticklabels(ax)
    # Removing degree symbol from tick labels to more closely resemble NCL example
    ax.yaxis.set_major_formatter(LatitudeFormatter(degree_symbol=''))
    ax.xaxis.set_major_formatter(LongitudeFormatter(degree_symbol=''))

    # Use geocat.viz.util convenience function to add minor and major tick lines
    gv.add_major_minor_ticks(ax, x_minor_per_major=4, y_minor_per_major=5, labelsize=12)

    # Use geocat.viz.util convenience function to add titles
    gv.set_titles_and_labels(
        ax,
        maintitlefontsize=16,
        maintitle="Dummy station data colored and\nsized according to range of values",
    )

    # Plot markers with values less than first bin value
    masked_lon = np.where(r < bins[0], lon, np.nan)
    masked_lat = np.where(r < bins[0], lat, np.nan)
    label = "x < " + str(bins[0])
    plt.scatter(masked_lon, masked_lat, label=label, s=sizes[0], color=colors[0], zorder=1)

    # Plot all other markers but those in the last bin
    label_format = "{} <= x < {}"
    for x in range(1, len(bins)):
        masked_lon = np.where(bins[x - 1] <= r, lon, np.nan)
        masked_lon = np.where(r < bins[x], masked_lon, np.nan)
        masked_lat = np.where(bins[x - 1] <= r, lat, np.nan)
        masked_lat = np.where(r < bins[x], masked_lat, np.nan)
        label = label_format.format(bins[x - 1], bins[x])
        plt.scatter(
            masked_lon, masked_lat, label=label, s=sizes[x], color=colors[x], zorder=1
        )

    # Plot markers with values greater than or equal to last bin value
    masked_lon = np.where(r >= bins[-1], lon, np.nan)
    masked_lat = np.where(r >= bins[-1], lat, np.nan)
    label = "x >= " + str(bins[-1])
    plt.scatter(
        masked_lon, masked_lat, label=label, s=sizes[-1], color=colors[-1], zorder=1
    )

    # `ncol` being equal to half of the number of labels makes the legend appear
    # horizontal with two rows
    legend = ax.legend(
        bbox_to_anchor=(-0.05, -0.3),
        ncol=4,
        loc='lower left',
        columnspacing=4.75,
        frameon=False,
    )
    plt.show()



.. image-sg:: /gallery/Polygons/images/sphx_glr_NCL_polyg_8_001.png
   :alt: Dummy station data colored and sized according to range of values
   :srcset: /gallery/Polygons/images/sphx_glr_NCL_polyg_8_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.130 seconds)


.. _sphx_glr_download_gallery_Polygons_NCL_polyg_8.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: NCL_polyg_8.ipynb <NCL_polyg_8.ipynb>`

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

      :download:`Download Python source code: NCL_polyg_8.py <NCL_polyg_8.py>`

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

      :download:`Download zipped: NCL_polyg_8.zip <NCL_polyg_8.zip>`


.. only:: html

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

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