test_occult.py

import numpy as np
import sunpy.io
import matplotlib.pyplot as plt
import sunkit_image.enhance as enhance

aia = sunpy.io.fits.read("http://www.lmsal.com/~aschwand/software/tracing/EUVIA_20070430.fits")

# plt.imshow(aia[0].data, cmap='Reds_r')

# plt.show()

def test_image():
    ima = np.zeros((11, 11), dtype=float)
    ima[:,5] = 1.0
    ima[3,6] = 1.0
    ima[4,7] = 1.0
    ima[5,8] = 1.0
    ima[4,9] = 1.0
    ima[3,10] = 1.0
    return ima

# You can use any of the two settings to test

# image = aia[0].data
# base = 60
# qd = 0.7
# n1 = 5
# n2 = n1+2
# noise = 10

image = test_image()
base = 1
qd = 1
n1 = 1
n2 = n1+2
noise = 0

loops = enhance.occult2(image, base, noise_thresh=noise, qmed=qd, nsm1=n1, nsm2=n2, rmin=20, nmax=10000)

for loop in loops:
    for points in loop:
        image[points[1], points[0]] = 10000

fig4 = plt.figure()
plt.imshow(image)
fig4.canvas.set_window_title("loops") 
plt.show()
len(loops)