def test_crpix_maps_to_crval():
twcs = wcs.WCS(naxis=2)
twcs.wcs.crval = [251.29, 57.58]
twcs.wcs.cdelt = [1, 1]
twcs.wcs.crpix = [507, 507]
twcs.wcs.pc = np.array([[7.7e-6, 3.3e-5], [3.7e-5, -6.8e-6]])
twcs._naxis = [1014, 1014]
twcs.wcs.ctype = ['RA---TAN-SIP', 'DEC--TAN-SIP']
a = np.array([[0, 0, 5.33092692e-08, 3.73753773e-11, -2.02111473e-13],
[0, 2.44084308e-05, 2.81394789e-11, 5.17856895e-13, 0.0],
[-2.41334657e-07, 1.29289255e-10, 2.35753629e-14, 0.0, 0.0],
[-2.37162007e-10, 5.43714947e-13, 0.0, 0.0, 0.0],
[-2.81029767e-13, 0.0, 0.0, 0.0, 0.0]])
b = np.array([[0, 0, 2.99270374e-05, -2.38136074e-10, 7.23205168e-13],
[0, -1.71073858e-07, 6.31243431e-11, -5.16744347e-14, 0.0],
[6.95458963e-06, -3.08278961e-10, -1.75800917e-13, 0.0, 0.0],
[3.51974159e-11, 5.60993016e-14, 0.0, 0.0, 0.0],
[-5.92438525e-13, 0.0, 0.0, 0.0, 0.0]])
twcs.sip = wcs.Sip(a, b, None, None, twcs.wcs.crpix)
twcs.wcs.set()
pscale = np.sqrt(wcs.utils.proj_plane_pixel_area(twcs))
# test that CRPIX maps to CRVAL:
assert_allclose(twcs.wcs_pix2world(*twcs.wcs.crpix, 1),
twcs.wcs.crval,
rtol=0.0,
atol=1e-6 * pscale)
# test that CRPIX maps to CRVAL:
assert_allclose(twcs.all_pix2world(*twcs.wcs.crpix, 1),
twcs.wcs.crval,
rtol=0.0,
atol=1e-6 * pscale)
def get_wcs_mcs(cent, rot):
"""Get WCS parameters For PFSC (MCS) file (WCS on PFI coordinates)
Parameters
----------
cent : `np.ndarray`, (2, 1)
The FoV center, i.e., telescope pointing center, (ra, dec) in unit
of degree.
rot : `float`
Telescope instrument rotator angle in unit of degree.
Returns
-------
w: `astropy.wcs.WCS`
registered wcs keywords
s: `astropy.wcs.Sip`
registered SIP keywords
"""
c = disco.Coeff('mcs_pfi')
rot *= np.pi / 180.
w = wcs.WCS(naxis=2)
# pixel -> intermediate pixel
w.wcs.crpix = [cent[0], cent[1]]
w.wcs.pc = [[np.cos(rot), -1. * np.sin(rot)], [np.sin(rot), np.cos(rot)]]
# intermediate pixel to intermediate worlds
w.wcs.cdelt = np.array([disco.mcspix * c.rsc[0], disco.mcspix * c.rsc[0]])
# Simple Imaging Polynomial (no inverse func is defined)
# Here, r~x~y is assumed
order = 7
a = np.zeros((order + 1, order + 1))
a[3][0] = c.rsc[1] / c.rsc[0]
a[5][0] = c.rsc[2] / c.rsc[0]
a[7][0] = c.rsc[3] / c.rsc[0]
ap = np.zeros((order + 1, order + 1))
b = np.swapaxes(a, 0, 1)
bp = np.swapaxes(ap, 0, 1)
s = wcs.Sip(a, b, ap, bp, w.wcs.crpix)
# intermeriate worlds to worlds
w.wcs.crval = [0., 0.]
w.wcs.ctype = ["PIXEL", "PIXEL"]
# w.wcs.set_pv([(2, 1, 45.0)])
# Others
w.wcs.cunit = ['mm', 'mm']
return w, s
def fit_wcs(x, y, ra, dec, x0, y0, ra0, dec0, order, projection="TAN"):
"""
Fit an astropy WCS object to given coordinates
Args:
x (array[float]): Pixel x coordinates
y (array[float]): Pixel y coordinates
ra (array[float]: RA coordinates in degrees
dec (array[float]: Dec coordinates in degrees
x0 (float): center pixel x
y0 (float): center pixel y
ra0 (float): center pixel RA in degrees
dec0 (float) center pixel DEC in degrees
order: order of imaging polynomials
Returns:
WCS instance
"""
dx, dy = x - x0, y - y0
ixs, iys = np.meshgrid(np.arange(order + 1), np.arange(order + 1))
c = ixs + iys <= order
ix, iy = ixs[c], iys[c]
a = np.array([dx**ix[i] * dy**iy[i] for i in range(len(iy))]).T
for k in range(5):
w = wcs.WCS(naxis=2)
w.wcs.ctype = ["RA---" + projection, "DEC--" + projection]
w.wcs.cd = [[1.0, 0.0], [0.0, 1.0]]
w.wcs.crval = [ra0, dec0]
w.wcs.crpix = [0.0, 0.0]
rx, ry = w.wcs_world2pix(np.stack((ra, dec), axis=-1), 1).T
ax = solve_linear_equation(a, rx)
ay = solve_linear_equation(a, ry)
ra0, dec0 = w.wcs_pix2world(([[ax[0], ay[0]]]), 1)[0]
cd = np.array([[ax[1], ax[order + 1]], [ay[1], ay[order + 1]]])
cdinv = np.linalg.inv(cd)
axm = np.zeros_like(ixs).astype("float32")
aym = np.zeros_like(ixs).astype("float32")
for i in range(len(ix)):
if ix[i] + iy[i] >= 2:
p = np.matmul(cdinv, np.array([ax[i], ay[i]]))
axm[iy[i], ix[i]] = p[0]
aym[iy[i], ix[i]] = p[1]
w = wcs.WCS(naxis=2)
w.wcs.ctype = ["RA---ZEA-SIP", "DEC--ZEA-SIP"]
w.wcs.cd = cd
w.wcs.crval = [ra0, dec0]
w.wcs.crpix = [x0, y0]
w.sip = wcs.Sip(axm.T, aym.T, None, None, w.wcs.crpix)
return w
def func(p):
w.wcs.crpix = [p[0], p[1]]
w.wcs.crval = [p[2], p[3]]
w.wcs.cdelt = [p[4], p[5]]
w.wcs.pc = [[p[6], p[7]], [p[8], p[9]]]
if wcstype == 'tan-sip':
a = np.zeros((order + 1, order + 1))
b = np.zeros((order + 1, order + 1))
ap = np.zeros(a.shape)
bp = np.zeros(b.shape)
n = 0
for i in range(order + 1):
for j in range(order + 1):
if i + j <= 1 or i + j > order:
continue
a[i, j] = p[n + 10]
b[i, j] = p[n + len(p) / 2 + 5]
n += 1
w.sip = wcs.Sip(a, b, ap, bp, w.wcs.crpix)
return (w)
if args.drizzled:
w.wcs.cd /= 2
# set up quadratic distortions [xy->uv and uv->xy]
m = 2
a = np.zeros((m + 1, m + 1), np.double)
a[0, 2] = a_02
a[1, 1] = a_11
a[2, 0] = a_20
b = np.zeros((m + 1, m + 1), np.double)
b[0, 2] = b_02
b[1, 1] = b_11
b[2, 0] = b_20
if args.drizzled:
a /= 2
b /= 2
ap = np.zeros((m + 1, m + 1), np.double)
bp = np.zeros((m + 1, m + 1), np.double)
w.sip = wcs.Sip(a, b, ap, bp, w.wcs.crpix)
# header['BLALA'] = 'LALA'
# turn WCS object into header
new_header = w.to_header(relax=True)
# merge with old header:
for key in header.keys():
new_header[key] = header[key]
export_fits(args.fits_in.replace('.fits', '.wcs.fits'),
img,
_header=new_header)