# -*- coding: utf-8 -*-
"""
============================
Edge Enhancing Coronal Loops
============================

How to edge enhance coronal loops in an SDO/AIA image.
"""
import numpy as np
from scipy import ndimage
import matplotlib.pyplot as plt

import astropy.units as u
from astropy.coordinates import SkyCoord

import sunpy.map
from sunpy.data.sample import AIA_171_IMAGE

###############################################################################
# We start with the sample data and crop it down to a region featuring coronal
# loops.
aia = sunpy.map.Map(AIA_171_IMAGE)
bottom_left = SkyCoord(750 * u.arcsec, -200 * u.arcsec, frame=aia.coordinate_frame)
top_right = SkyCoord(1500 * u.arcsec, 550 * u.arcsec, frame=aia.coordinate_frame)
aia_smap = aia.submap(bottom_left, top_right)

###############################################################################
# Next we apply an edge enhance filter to the data in both x and y directions
# and combine the two images together.
sx = ndimage.sobel(aia_smap.data, axis=0, mode='constant')
sy = ndimage.sobel(aia_smap.data, axis=1, mode='constant')
edge_enhanced_im = np.hypot(sx, sy)

###############################################################################
# Finally we create a new map with the edge enhanced data.
edge_map = sunpy.map.Map(edge_enhanced_im, aia_smap.meta)

###############################################################################
# Let's plot the results.
fig = plt.figure()
ax = fig.add_subplot(111, projection=aia_smap)
edge_map.plot()
plt.show()

# -*- coding: utf-8 -*-
"""
============================
Edge Enhancing Coronal Loops
============================

How to edge enhance coronal loops in an SDO/AIA image.
"""
import numpy as np
from scipy import ndimage
import matplotlib.pyplot as plt

import astropy.units as u
from astropy.coordinates import SkyCoord

import sunpy.map
from sunpy.data.sample import AIA_171_IMAGE

###############################################################################
# We start with the sample data and crop it down to a region featuring coronal
# loops.
aia = sunpy.map.Map(AIA_171_IMAGE)
bottom_left = SkyCoord(750 * u.arcsec, -200 * u.arcsec, frame=aia.coordinate_frame)
top_right = SkyCoord(1500 * u.arcsec, 550 * u.arcsec, frame=aia.coordinate_frame)
aia_smap = aia.submap(bottom_left, top_right)

###############################################################################
# Next we apply an edge enhance filter to the data in both x and y directions
# and combine the two images together.
sx = ndimage.sobel(aia_smap.data, axis=0, mode='constant')
sy = ndimage.sobel(aia_smap.data, axis=1, mode='constant')
edge_enhanced_im = np.hypot(sx, sy)

###############################################################################
# Finally we create a new map with the edge enhanced data.
edge_map = sunpy.map.Map(edge_enhanced_im, aia_smap.meta)

###############################################################################
# Let's plot the results.
fig = plt.figure()
ax = plt.subplot(projection=aia_smap)
edge_map.plot()
plt.show()

Update examples/computer_vision_techniques/loop_edge_enhance.py