"""
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.

"""  # noqa: D205, D212, D400

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()