# 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.

"""
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.

"""

import matplotlib.pyplot as plt
import numpy as np
import iris
import cartopy.crs as ccrs
import iris.quickplot as qplt
import iris.plot as iplt

def main():
# 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()"
# 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')
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')