1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92
|
"""
===========================================
Drawing the AIA limb on a STEREO EUVI image
===========================================
In this example we use a STEREO-B and an SDO image to demonstrate how to
overplot the limb as seen by AIA on an EUVI-B image. Then we overplot the AIA
coordinate grid on the STEREO image.
"""
import matplotlib.pyplot as plt
import astropy.units as u
from astropy.coordinates import SkyCoord
import sunpy.coordinates.wcs_utils
import sunpy.map
from sunpy.data.sample import AIA_193_JUN2012, STEREO_B_195_JUN2012
##############################################################################
# Let's create a dictionary with the two maps, which we crop to full disk.
maps = {m.detector: m.submap(SkyCoord([-1100, 1100], [-1100, 1100],
unit=u.arcsec, frame=m.coordinate_frame))
for m in sunpy.map.Map([AIA_193_JUN2012, STEREO_B_195_JUN2012])}
maps['AIA'].plot_settings['vmin'] = 0 # set the minimum plotted pixel value
##############################################################################
# Now, let's plot both maps, and we draw the limb as seen by AIA onto the
# EUVI image. We remove the part of the limb that is hidden because it is on
# the far side of the Sun from STEREO's point of view.
fig = plt.figure(figsize=(10, 4))
ax1 = fig.add_subplot(121, projection=maps['AIA'])
maps['AIA'].plot(axes=ax1)
maps['AIA'].draw_limb(axes=ax1)
ax2 = fig.add_subplot(122, projection=maps['EUVI'])
maps['EUVI'].plot(axes=ax2)
visible, hidden = maps['AIA'].draw_limb(axes=ax2)
hidden.remove()
##############################################################################
# Let's plot the helioprojective coordinate grid as seen by SDO on the STEREO
# image in a cropped view. Note that only those grid lines that intersect the
# edge of the plot will have corresponding ticks and tick labels.
fig = plt.figure()
ax = fig.add_subplot(projection=maps['EUVI'])
maps['EUVI'].plot(axes=ax)
# Crop the view using pixel coordinates
ax.set_xlim(500, 1300)
ax.set_ylim(100, 900)
# Shrink the plot slightly and move the title up to make room for new labels.
ax.set_position([0.1, 0.1, 0.8, 0.7])
ax.set_title(ax.get_title(), pad=45)
# Change the default grid labels and line properties.
stereo_x, stereo_y = ax.coords
stereo_x.set_axislabel("Helioprojective Longitude (STEREO B) [arcsec]")
stereo_y.set_axislabel("Helioprojective Latitude (STEREO B) [arcsec]")
ax.coords.grid(color='white', linewidth=1)
# Add a new coordinate overlay in the SDO frame.
overlay = ax.get_coords_overlay(maps['AIA'].coordinate_frame)
overlay.grid()
# Configure the grid:
x, y = overlay
# Wrap the longitude at 180 deg rather than the default 360.
x.set_coord_type('longitude', 180.)
# Set the tick spacing
x.set_ticks(spacing=250*u.arcsec)
y.set_ticks(spacing=250*u.arcsec)
# Set the ticks to be on the top and left axes.
x.set_ticks_position('tr')
y.set_ticks_position('tr')
# Change the defaults to arcseconds
x.set_major_formatter('s.s')
y.set_major_formatter('s.s')
# Add axes labels
x.set_axislabel("Helioprojective Longitude (SDO) [arcsec]")
y.set_axislabel("Helioprojective Latitude (SDO) [arcsec]")
plt.show()
|