def build_pixel_transform(chip, output_wcs):
driz_pars = {}
driz_pars['pxg'] = np.zeros([2, 2], dtype=np.float32)
driz_pars['pyg'] = np.zeros([2, 2], dtype=np.float32)
# Use default C mapping function
_inwcs = np.zeros([8], dtype=np.float64)
driz_pars['inwcs'] = convertWCS(output_wcs.wcs, _inwcs)
indx = chip.outputNames['data'].find('.fits')
driz_pars['coeffs_name'] = chip.outputNames['data'][:indx] + '_coeffs' + str(chip.detnum) + '.dat'
#
# Need to compute and write out coeffs files for each chip as well.
#
xcoeffs, ycoeffs = coeff_converter.sip2idc(chip.wcs)
# account for the case where no IDCSCALE has been set, due to a
# lack of IDCTAB or to 'coeffs=False'.
idcscale = chip.wcs.idcscale
if idcscale is None: idcscale = chip.wcs.pscale
xcoeffs /= idcscale
ycoeffs /= idcscale
driz_pars['coeffs'] = [xcoeffs, ycoeffs]
abxt, cdyt = wcsfit(chip.wcs, output_wcs)
driz_pars['abxt'] = abxt
driz_pars['cdyt'] = cdyt
driz_pars['delta_rot'] = np.rad2deg(np.arctan2(abxt[1], cdyt[0]))
# Compute scale from fit to allow WFPC2 (and similar) data to be handled correctly
driz_pars['scale'] = 1. / np.sqrt(abxt[0]**2 + abxt[1]**2)
driz_pars['tddalpha'] = chip.header['tddalpha']
driz_pars['tddbeta'] = chip.header['tddbeta']
return driz_pars
def build_pixel_transform(chip,output_wcs):
driz_pars = {}
driz_pars['pxg'] = np.zeros([2,2],dtype=np.float32)
driz_pars['pyg'] = np.zeros([2,2],dtype=np.float32)
# Use default C mapping function
_inwcs = np.zeros([8],dtype=np.float64)
driz_pars['inwcs'] = convertWCS(output_wcs.wcs,_inwcs)
indx = chip.outputNames['data'].find('.fits')
driz_pars['coeffs_name'] = chip.outputNames['data'][:indx]+'_coeffs'+str(chip.detnum)+'.dat'
#
# Need to compute and write out coeffs files for each chip as well.
#
xcoeffs,ycoeffs = coeff_converter.sip2idc(chip.wcs)
# account for the case where no IDCSCALE has been set, due to a
# lack of IDCTAB or to 'coeffs=False'.
idcscale = chip.wcs.idcscale
if idcscale is None: idcscale = chip.wcs.pscale
xcoeffs /= idcscale
ycoeffs /= idcscale
driz_pars['coeffs'] = [xcoeffs,ycoeffs]
abxt,cdyt = wcsfit(chip.wcs,output_wcs)
#abxt[2] -= xzero
#cdyt[2] -= yzero
driz_pars['abxt'] = abxt
driz_pars['cdyt'] = cdyt
driz_pars['delta_rot'] = np.rad2deg(np.arctan2(abxt[1],cdyt[0]))
# Compute scale from fit to allow WFPC2 (and similar) data to be handled correctly
driz_pars['scale'] = 1./np.sqrt(abxt[0]**2 + abxt[1]**2)
driz_pars['tddalpha'] = chip.header['tddalpha']
driz_pars['tddbeta'] = chip.header['tddbeta']
return driz_pars
def _readModelFromHeader(self, header):
# Recreate idc model from SIP coefficients and header kw
print('Restoring IDC model from SIP coefficients\n')
model = models.GeometryModel()
cx, cy = coeff_converter.sip2idc(self)
model.cx = cx
model.cy = cy
model.name = "sip"
model.norder = header['A_ORDER']
refpix = {}
refpix['XREF'] = header['IDCXREF']
refpix['YREF'] = header['IDCYREF']
refpix['PSCALE'] = header['IDCSCALE']
refpix['V2REF'] = header['IDCV2REF']
refpix['V3REF'] = header['IDCV3REF']
refpix['THETA'] = header['IDCTHETA']
model.refpix = refpix
self.idcmodel = model
def wcsfit(img_wcs, ref_wcs):
"""
Perform a linear fit between 2 WCS for shift, rotation and scale.
Based on the WCSLIN function from 'drutil.f'(Drizzle V2.9) and modified to
allow for differences in reference positions assumed by PyDrizzle's
distortion model and the coeffs used by 'drizzle'.
Parameters
----------
img : obj
ObsGeometry instance for input image
ref_wcs : obj
Undistorted WCSObject instance for output frame
"""
# Define objects that we need to use for the fit...
#in_refpix = img_geom.model.refpix
wmap = WCSMap(img_wcs,ref_wcs)
cx, cy = coeff_converter.sip2idc(img_wcs)
# Convert the RA/Dec positions back to X/Y in output product image
#_cpix_xyref = np.zeros((4,2),dtype=np.float64)
# Start by setting up an array of points +/-0.5 pixels around CRVAL1,2
# However, we must shift these positions by 1.0pix to match what
# drizzle will use as its reference position for 'align=center'.
_cpix = (img_wcs.wcs.crpix[0],img_wcs.wcs.crpix[1])
_cpix_arr = np.array([_cpix,(_cpix[0],_cpix[1]+1.),
(_cpix[0]+1.,_cpix[1]+1.),(_cpix[0]+1.,_cpix[1])], dtype=np.float64)
# Convert these positions to RA/Dec
_cpix_rd = wmap.xy2rd(img_wcs,_cpix_arr[:,0],_cpix_arr[:,1])
#for pix in xrange(len(_cpix_rd[0])):
_cpix_xref,_cpix_yref = wmap.rd2xy(ref_wcs,_cpix_rd[0],_cpix_rd[1])
_cpix_xyref = np.zeros((4,2),dtype=np.float64)
_cpix_xyref[:,0] = _cpix_xref
_cpix_xyref[:,1] = _cpix_yref
"""
# needed to handle correctly subarrays and wfpc2 data
if img_wcs.delta_refx == 0.0 and img_wcs.delta_refy == 0.0:
offx, offy = (0.0,0.0)
else:
offx, offy = (1.0, 1.0)
"""
offx, offy = (0.0,0.0)
# Now, apply distortion model to input image XY positions
#_cpix_xyc = np.zeros((4,2),dtype=np.float64)
_cpix_xyc = utils.apply_idc(_cpix_arr, cx, cy, img_wcs.wcs.crpix, img_wcs.pscale, order=1)
# Need to get the XDELTA,YDELTA values included here in order to get this
# to work with MDTng.
#if in_refpix:
# _cpix_xyc += (in_refpix['XDELTA'], in_refpix['YDELTA'])
# Perform a fit between:
# - undistorted, input positions: _cpix_xyc
# - X/Y positions in reference frame: _cpix_xyref
abxt,cdyt = fitlin(_cpix_xyc,_cpix_xyref)
# This correction affects the final fit when you are fitting
# a WCS to itself (no distortion coeffs), so it needs to be
# taken out in the coeffs file by modifying the zero-point value.
# WJH 17-Mar-2005
abxt[2] -= ref_wcs.wcs.crpix[0] + offx
cdyt[2] -= ref_wcs.wcs.crpix[1] + offy
return abxt,cdyt
def wcsfit(img_wcs, ref_wcs):
"""
Perform a linear fit between 2 WCS for shift, rotation and scale.
Based on the WCSLIN function from 'drutil.f'(Drizzle V2.9) and modified to
allow for differences in reference positions assumed by PyDrizzle's
distortion model and the coeffs used by 'drizzle'.
Parameters
----------
img : obj
ObsGeometry instance for input image
ref_wcs : obj
Undistorted WCSObject instance for output frame
"""
# Define objects that we need to use for the fit...
#in_refpix = img_geom.model.refpix
wmap = WCSMap(img_wcs,ref_wcs)
cx, cy = coeff_converter.sip2idc(img_wcs)
# Convert the RA/Dec positions back to X/Y in output product image
#_cpix_xyref = np.zeros((4,2),dtype=np.float64)
# Start by setting up an array of points +/-0.5 pixels around CRVAL1,2
# However, we must shift these positions by 1.0pix to match what
# drizzle will use as its reference position for 'align=center'.
_cpix = (img_wcs.wcs.crpix[0],img_wcs.wcs.crpix[1])
_cpix_arr = np.array([_cpix,(_cpix[0],_cpix[1]+1.),
(_cpix[0]+1.,_cpix[1]+1.),(_cpix[0]+1.,_cpix[1])], dtype=np.float64)
# Convert these positions to RA/Dec
_cpix_rd = wmap.xy2rd(img_wcs,_cpix_arr[:,0],_cpix_arr[:,1])
#for pix in xrange(len(_cpix_rd[0])):
_cpix_xref,_cpix_yref = wmap.rd2xy(ref_wcs,_cpix_rd[0],_cpix_rd[1])
_cpix_xyref = np.zeros((4,2),dtype=np.float64)
_cpix_xyref[:,0] = _cpix_xref
_cpix_xyref[:,1] = _cpix_yref
"""
# needed to handle correctly subarrays and wfpc2 data
if img_wcs.delta_refx == 0.0 and img_wcs.delta_refy == 0.0:
offx, offy = (0.0,0.0)
else:
offx, offy = (1.0, 1.0)
"""
offx, offy = (0.0,0.0)
# Now, apply distortion model to input image XY positions
#_cpix_xyc = np.zeros((4,2),dtype=np.float64)
_cpix_xyc = utils.apply_idc(_cpix_arr, cx, cy, img_wcs.wcs.crpix, img_wcs.pscale, order=1)
# Need to get the XDELTA,YDELTA values included here in order to get this
# to work with MDTng.
#if in_refpix:
# _cpix_xyc += (in_refpix['XDELTA'], in_refpix['YDELTA'])
# Perform a fit between:
# - undistorted, input positions: _cpix_xyc
# - X/Y positions in reference frame: _cpix_xyref
abxt,cdyt = fitlin(_cpix_xyc,_cpix_xyref)
# This correction affects the final fit when you are fitting
# a WCS to itself (no distortion coeffs), so it needs to be
# taken out in the coeffs file by modifying the zero-point value.
# WJH 17-Mar-2005
abxt[2] -= ref_wcs.wcs.crpix[0] + offx
cdyt[2] -= ref_wcs.wcs.crpix[1] + offy
return abxt,cdyt
