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

.. only:: html

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

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

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

.. _sphx_glr_generated_gallery_general_plot_inset.py:


Test Data Showing Inset Plots
=============================

This example demonstrates the use of a single 3D data cube with time, latitude
and longitude dimensions to plot a temperature series for a single latitude
coordinate, with an inset plot of the data region.

.. GENERATED FROM PYTHON SOURCE LINES 10-70



.. image-sg:: /generated/gallery/general/images/sphx_glr_plot_inset_001.png
   :alt: Meridional Mean Temperature, Data Region
   :srcset: /generated/gallery/general/images/sphx_glr_plot_inset_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import cartopy.crs as ccrs
    import matplotlib.pyplot as plt
    import numpy as np

    import iris
    import iris.plot as iplt
    import iris.quickplot as qplt


    def main():
        cube1 = iris.load_cube(iris.sample_data_path("ostia_monthly.nc"))
        # Slice into cube to retrieve data for the inset map showing the
        # data region
        region = cube1[-1, :, :]
        # Average over latitude to reduce cube to 1 dimension
        plot_line = region.collapsed("latitude", iris.analysis.MEAN)

        # Open a window for plotting
        fig = plt.figure()
        # Add a single subplot (axes). Could also use "ax_main = plt.subplot()"
        ax_main = fig.add_subplot(1, 1, 1)
        # Produce a quick plot of the 1D cube
        qplt.plot(plot_line)

        # Set x limits to match the data
        ax_main.set_xlim(0, plot_line.coord("longitude").points.max())
        # Adjust the y limits so that the inset map won't clash with main plot
        ax_main.set_ylim(294, 310)
        ax_main.set_title("Meridional Mean Temperature")
        # Add grid lines
        ax_main.grid()

        # Add a second set of axes specifying the fractional coordinates within
        # the figure with bottom left corner at x=0.55, y=0.58 with width
        # 0.3 and height 0.25.
        # Also specify the projection
        ax_sub = fig.add_axes(
            [0.55, 0.58, 0.3, 0.25],
            projection=ccrs.Mollweide(central_longitude=180),
        )

        # Use iris.plot (iplt) here so colour bar properties can be specified
        # Also use a sequential colour scheme to reduce confusion for those with
        # colour-blindness
        iplt.pcolormesh(region, cmap="Blues")
        # Manually set the orientation and tick marks on your colour bar
        ticklist = np.linspace(np.min(region.data), np.max(region.data), 4)
        plt.colorbar(orientation="horizontal", ticks=ticklist)
        ax_sub.set_title("Data Region")
        # Add coastlines
        ax_sub.coastlines()
        # request to show entire map, using the colour mesh on the data region only
        ax_sub.set_global()

        qplt.show()


    if __name__ == "__main__":
        main()


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

   **Total running time of the script:** (0 minutes 0.445 seconds)


.. _sphx_glr_download_generated_gallery_general_plot_inset.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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