def cached_zernike1(j,
shape,
pixelscale,
pupil_radius,
outside=np.nan,
noll_normalize=True):
"""Compute Zernike based on Noll index *j*, using an LRU cache
for efficiency. Refer to the `zernike1` docstring for details.
Note: all arguents should be plain ints, tuples, floats etc rather than
Astropy Quantities.
"""
y, x = Wavefront.pupil_coordinates(shape, pixelscale)
r = np.sqrt(x**2 + y**2)
rho = r / pupil_radius
theta = np.arctan2(y / pupil_radius, x / pupil_radius)
n, m = noll_indices(j)
result = zernike(n,
m,
rho=rho,
theta=theta,
outside=outside,
noll_normalize=noll_normalize)
result.flags.writeable = False # don't let caller modify cached copy in-place
return result
def cached_zernike1(j, shape, pixelscale, pupil_radius, outside=np.nan, noll_normalize=True):
"""Compute Zernike based on Noll index *j*, using an LRU cache
for efficiency. Refer to the `zernike1` docstring for details.
"""
y, x = Wavefront.pupil_coordinates(shape, pixelscale)
r = np.sqrt(x ** 2 + y ** 2)
rho = r / pupil_radius
theta = np.arctan2(y / pupil_radius, x / pupil_radius)
n, m = noll_indices(j)
result = zernike(n, m, rho=rho, theta=theta, outside=outside, noll_normalize=noll_normalize)
result.flags.writeable = False # don't let caller modify cached copy in-place
return result