def _xobjective_sip(params, u, v, x, y, crval, crpix, a_names, b_names, cd, ret):
"""
Objective function for fitting SIP coefficients
"""
from astropy.modeling import models, fitting
#u, v, x, y, crpix, a_names, b_names, cd = data
cdx = params[0:4].reshape((2, 2))
a_params = params[4:4+len(a_names)]
b_params = params[4+len(a_names):]
a_coeff = {}
for i in range(len(a_names)):
a_coeff[a_names[i]] = a_params[i]
b_coeff = {}
for i in range(len(b_names)):
b_coeff[b_names[i]] = b_params[i]
if ret == 1:
return cdx, a_coeff, b_coeff
off = 1
sip = models.SIP(crpix=crpix-off, a_order=4, b_order=4, a_coeff=a_coeff, b_coeff=b_coeff)
fuv, guv = sip(u, v)
xo, yo = np.dot(cdx, np.array([u+fuv-crpix[0], v+guv-crpix[1]]))
#dr = np.sqrt((x-xo)**2+(y-yo)**2)*3600.
dr = np.append(x-xo, y-yo)*3600./0.065
#print(params, np.abs(dr).max())
return dr
def setup_class(self):
hdr = fits.Header.fromtextfile(get_pkg_data_filename("data/acs.hdr"),
endcard=False)
#warnings.filterwarnings("ignore", message="^The WCS transformation has more axes (2)",
# module="astropy.wcs.wcs")
self.fitsw = astwcs.WCS(hdr)
a_coeff = hdr['A_*']
a_order = a_coeff.pop('A_ORDER')
b_coeff = hdr['B_*']
b_order = b_coeff.pop('B_ORDER')
crpix = [hdr['CRPIX1'], hdr['CRPIX2']]
distortion = models.SIP(
crpix, a_order, b_order, a_coeff, b_coeff,
name='sip_distorion') + models.Identity(2)
cdmat = np.array([[hdr['CD1_1'], hdr['CD1_2']],
[hdr['CD2_1'], hdr['CD2_2']]])
aff = models.AffineTransformation2D(matrix=cdmat, name='rotation')
offx = models.Shift(-hdr['CRPIX1'], name='x_translation')
offy = models.Shift(-hdr['CRPIX2'], name='y_translation')
wcslin = (offx & offy) | aff
phi = hdr['CRVAL1']
lon = hdr['CRVAL2']
theta = 180
n2c = models.RotateNative2Celestial(phi,
lon,
theta,
name='sky_rotation')
tan = models.Pix2Sky_TAN(name='tangent_projection')
sky_cs = cf.CelestialFrame(reference_frame=coord.ICRS(), name='sky')
det = cf.Frame2D('detector')
wcs_forward = wcslin | tan | n2c
pipeline = [('detector', distortion), ('focal', wcs_forward),
(sky_cs, None)]
self.wcs = wcs.WCS(input_frame=det,
output_frame=sky_cs,
forward_transform=pipeline)
nx, ny = (5, 2)
x = np.linspace(0, 1, nx)
y = np.linspace(0, 1, ny)
self.xv, self.yv = np.meshgrid(x, y)