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import os
import gwcs
import numpy as np
from gwcs.coordinate_frames import CelestialFrame, Frame2D
from astropy import coordinates as coord
from astropy import units
from astropy import wcs as fits_wcs
from astropy.io import fits
from astropy.modeling.models import (
Mapping,
Pix2Sky_TAN,
Polynomial2D,
RotateNative2Celestial,
Shift,
)
from astropy.modeling.projections import AffineTransformation2D
__all__ = ["wcs_from_file"]
DATA_DIR = os.environ.get('DRIZZLE_TEST_DIR', '/usr/share/python-drizzle/test_data')
def wcs_from_file(filename, ext=None, return_data=False, crpix_shift=None,
wcs_type="fits"):
"""
Read the WCS from a ".fits" file.
Parameters
----------
filename : str
Name of the file to load WCS from.
ext : int, None, optional
Extension number to load the WCS from. When `None`, the WCS will be
loaded from the first extension containing a WCS.
return_data : bool, optional
When `True`, this function will return a tuple with first item
being the WCS and the second item being the image data array.
crpix_shift : tuple, None, optional
A tuple of two values to be added to header CRPIX values before
creating the WCS. This effectively introduces a constant shift
in the image coordinate system.
wcs_type : {"fits", "gwcs"}, optional
Return either a FITS WCS or a gwcs.
Returns
-------
WCS or tuple of WCS and image data
"""
full_file_name = os.path.join(DATA_DIR, filename)
path = os.path.join(DATA_DIR, full_file_name)
def get_shape(hdr):
naxis1 = hdr.get("WCSNAX1", hdr.get("NAXIS1"))
naxis2 = hdr.get("WCSNAX2", hdr.get("NAXIS2"))
if naxis1 is None or naxis2 is None:
return None
return (naxis2, naxis1)
def data_from_hdr(hdr, data=None, shape=None):
if data is not None:
return data
bitpix = hdr.get("BITPIX", -32)
dtype = fits.hdu.BITPIX2DTYPE[bitpix]
shape = get_shape(hdr) or shape
if shape is None:
return None
return np.zeros(shape, dtype=dtype)
if os.path.splitext(filename)[1] in [".hdr", ".txt"]:
hdul = None
hdr = fits.Header.fromfile(
path,
sep='\n',
endcard=False,
padding=False
)
else:
with fits.open(path) as fits_hdul:
hdul = fits.HDUList([hdu.copy() for hdu in fits_hdul])
if ext is None and hdul is not None:
for k, u in enumerate(hdul):
if "CTYPE1" in u.header:
ext = k
break
hdr = hdul[ext].header
if crpix_shift is not None and "CRPIX1" in hdr:
hdr["CRPIX1"] += crpix_shift[0]
hdr["CRPIX2"] += crpix_shift[1]
result = fits_wcs.WCS(hdr, hdul)
shape = get_shape(hdr)
result.array_shape = shape
if wcs_type == "gwcs":
result = _gwcs_from_hst_fits_wcs(result)
if return_data:
if hdul is None:
data = data_from_hdr(hdr, data=None, shape=shape)
return (result, data)
result = (result, )
if not isinstance(return_data, (list, tuple)):
return_data = [ext]
for ext in return_data:
data = data_from_hdr(
hdul[ext].header,
data=hdul[ext].data,
shape=shape
)
result = result + (data, )
return result
def _gwcs_from_hst_fits_wcs(w):
# NOTE: this function ignores table distortions
def coeffs_to_poly(mat, degree):
pol = Polynomial2D(degree=degree)
for i in range(mat.shape[0]):
for j in range(mat.shape[1]):
if 0 < i + j <= degree:
setattr(pol, f'c{i}_{j}', mat[i, j])
return pol
nx, ny = w.pixel_shape
x0, y0 = w.wcs.crpix - 1
cd = w.wcs.piximg_matrix
if w.sip is None:
# construct GWCS:
det2sky = (
(Shift(-x0) & Shift(-y0)) |
Pix2Sky_TAN() | RotateNative2Celestial(*w.wcs.crval, 180)
)
else:
cfx, cfy = np.dot(cd, [w.sip.a.ravel(), w.sip.b.ravel()])
a = np.reshape(cfx, w.sip.a.shape)
b = np.reshape(cfy, w.sip.b.shape)
a[1, 0] = cd[0, 0]
a[0, 1] = cd[0, 1]
b[1, 0] = cd[1, 0]
b[0, 1] = cd[1, 1]
polx = coeffs_to_poly(a, w.sip.a_order)
poly = coeffs_to_poly(b, w.sip.b_order)
sip = Mapping((0, 1, 0, 1)) | (polx & poly)
# construct GWCS:
det2sky = (
(Shift(-x0) & Shift(-y0)) | sip |
Pix2Sky_TAN() | RotateNative2Celestial(*w.wcs.crval, 180)
)
detector_frame = Frame2D(
name="detector",
axes_names=("x", "y"),
unit=(units.pix, units.pix)
)
sky_frame = CelestialFrame(
reference_frame=getattr(coord, w.wcs.radesys).__call__(),
name=w.wcs.radesys,
unit=(units.deg, units.deg)
)
pipeline = [(detector_frame, det2sky), (sky_frame, None)]
gw = gwcs.wcs.WCS(pipeline)
gw.array_shape = w.array_shape
gw.bounding_box = ((-0.5, nx - 0.5), (-0.5, ny - 0.5))
if w.sip is not None:
# compute inverse SIP and re-create output GWCS
# compute inverse SIP:
hdr = gw.to_fits_sip(
max_inv_pix_error=1e-5,
inv_degree=None,
npoints=64,
crpix=w.wcs.crpix,
projection='TAN',
verbose=False
)
winv = fits_wcs.WCS(hdr)
ap = winv.sip.ap.copy()
bp = winv.sip.bp.copy()
ap[1, 0] += 1
bp[0, 1] += 1
polx_inv = coeffs_to_poly(ap, winv.sip.ap_order)
poly_inv = coeffs_to_poly(bp, winv.sip.bp_order)
af = AffineTransformation2D(
matrix=np.linalg.inv(winv.wcs.piximg_matrix)
)
# set analytical inverses:
sip.inverse = af | Mapping((0, 1, 0, 1)) | (polx_inv & poly_inv)
# construct GWCS:
det2sky = (
(Shift(-x0) & Shift(-y0)) | sip |
Pix2Sky_TAN() | RotateNative2Celestial(*w.wcs.crval, 180)
)
pipeline = [(detector_frame, det2sky), (sky_frame, None)]
gw = gwcs.wcs.WCS(pipeline)
gw.array_shape = w.array_shape
gw.bounding_box = ((-0.5, nx - 0.5), (-0.5, ny - 0.5))
return gw
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