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"""
=========================================
Creating a Composite Plot with Three Maps
=========================================
In this example, a composite plot is created with three maps.
It demonstrates how to specify contour levels, transparency, and
ordering when overlaying multiple maps.
"""
import matplotlib.pyplot as plt
import astropy.units as u
from astropy.coordinates import SkyCoord
import sunpy.data.sample
from sunpy.coordinates import SphericalScreen
from sunpy.map import Map
###############################################################################
# First, we will import sample data from EIT, RHESSI, and AIA. The EIT data
# shows a hot region of the solar corona, while AIA shows the cooler upper
# region of the corona. RHESSI data is focused on a solar flare, and will be
# plotted using contours.
eit = Map(sunpy.data.sample.EIT_195_IMAGE)
rhessi = Map(sunpy.data.sample.RHESSI_IMAGE)
aia = Map(sunpy.data.sample.AIA_171_IMAGE)
###############################################################################
# Before we plot the image, let's reproject the off-disk AIA coordinates onto
# a spherical screen at the same distance as the EIT map, so they can be
# overlaid. Next, zoom in around the solar flare so the RHESSI contours are
# visible. Also, specify the RHESSI contour levels to be plotted.
with SphericalScreen(eit.observer_coordinate):
aia = aia.reproject_to(eit.wcs)
bottom_left = [200, -800] * u.arcsec
top_right = [1000, -200] * u.arcsec
eit_smap = eit.submap(SkyCoord(*bottom_left, frame=eit.coordinate_frame),
top_right=SkyCoord(*top_right, frame=eit.coordinate_frame))
aia_smap = aia.submap(SkyCoord(*bottom_left, frame=aia.coordinate_frame),
top_right=SkyCoord(*top_right, frame=aia.coordinate_frame))
levels = [5, 10, 20, 30, 40]*u.percent
###############################################################################
# When creating the plot, choose which Map will be used to create the WCS Axes
# that the other Maps will be plotted with. The EIT map is plotted first,
# followed by the AIA map, and lastly the RHESSI contours. Transparency is
# changed to 70% on the AIA map by specifying the parameter ``alpha``, and the
# image data is autoaligned to the EIT WCS Axes. The parameter ``zorder``
# specifies how each plot is layered (0 is plotted first and 1 is layered on
# top of 0, and so on).
fig = plt.figure()
ax = fig.add_subplot(projection=eit_smap)
eit_smap.plot(axes=ax, clip_interval=(1, 99.9)*u.percent, zorder=0)
aia_smap.plot(axes=ax, clip_interval=(1, 99.97)*u.percent, alpha=0.7, zorder=1)
rhessi.draw_contours(axes=ax, levels=levels, zorder=2)
ax.set_title("Three Map Composite")
plt.show()
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