def moon_mask(img):
"""Generate a masking array that covers the moon in a given image.
Parameters
---------
img : image.AllSkyImage
The image.
Returns
-------
numpy.ndarray
An array where pixels inside the moon are marked with False and those
outside the moon are marked with True.
"""
# Get the fraction visible for interpolation and find the
# location of the moon.
vis = moon_phase(img)
x, y, _ = find_moon(img)
# Creates the circle patch we use.
r = moon_circle(vis)
circ = Circle((x, y), r, fill=False)
# The following code converts the patch to a 512x512 mask array, with True
# for values outside the circle and False for those inside.
# This is the same syntax as np.ma.make_mask returns.
# This section of code generates an 262144x2 array of the
# 512x512 pixel locations. 262144 = 512^2
points = np.zeros((512**2, 2))
index = 0
for i in range(0, 512):
for j in range(0, 512):
# These are backwards as expected due to how reshape works later.
# Points is in x,y format, but reshape reshapes such that
# it needs to be in y,x format.
points[index, 0] = j
points[index, 1] = i
index += 1
# Checks all the points are inside the circle, then reshapes it to the
# 512x512 size.
mask = circ.contains_points(points)
mask = mask.reshape(512, 512)
return mask
