def getMdriztabParameters(files):
""" Gets entry in MDRIZTAB where task parameters live.
This method returns a record array mapping the selected
row.
"""
# Get the MDRIZTAB table file name from the primary header.
# It is gotten from the first file in the input list. No
# consistency checks are performed.
_fileName = files[0]
_header = fileutil.getHeader(_fileName)
if 'MDRIZTAB' in _header:
_tableName = _header['MDRIZTAB']
else:
raise KeyError("No MDRIZTAB found in file " + _fileName)
_tableName = fileutil.osfn(_tableName)
# Now get the filters from the primary header.
_filters = fileutil.getFilterNames(_header)
# Specifically check to see whether the MDRIZTAB file can be found
mtab_path = os.path.split(_tableName)[0] # protect against no path given for _tableName
if mtab_path and not os.path.exists(mtab_path): # check path first, if given
raise IOError("Directory for MDRIZTAB '%s' could not be accessed!"%mtab_path)
if not os.path.exists(_tableName): # then check for the table itself
raise IOError("MDRIZTAB table '%s' could not be found!"%_tableName)
# Open MDRIZTAB file.
try:
_mdriztab = fits.open(_tableName, memmap=False)
except:
raise IOError("MDRIZTAB table '%s' not valid!" % _tableName)
# Look for matching rows based on filter name. If no
# match, pick up rows for the default filter.
_rows = _getRowsByFilter(_mdriztab, _filters)
if _rows == []:
_rows = _getRowsByFilter(_mdriztab, 'ANY')
# Now look for the row that matches the number of images.
# The logic below assumes that rows for a given filter
# are arranged in ascending order of the 'numimage' field.
_nimages = len(files)
_row = 0
for i in _rows:
_numimages = _mdriztab[1].data.field('numimages')[i]
if _nimages >= _numimages:
_row = i
print('- MDRIZTAB: AstroDrizzle parameters read from row %s.'%(_row+1))
mpars = _mdriztab[1].data[_row]
_mdriztab.close()
interpreted = _interpretMdriztabPars(mpars)
if "staticfile" in interpreted:
interpreted.pop("staticfile")
return interpreted
def getMdriztabParameters(files):
""" Gets entry in MDRIZTAB where task parameters live.
This method returns a record array mapping the selected
row.
"""
# Get the MDRIZTAB table file name from the primary header.
# It is gotten from the first file in the input list. No
# consistency checks are performed.
_fileName = files[0]
_header = fileutil.getHeader(_fileName)
if 'MDRIZTAB' in _header:
_tableName = _header['MDRIZTAB']
else:
raise KeyError("No MDRIZTAB found in file " + _fileName)
_tableName = fileutil.osfn(_tableName)
# Now get the filters from the primary header.
_filters = fileutil.getFilterNames(_header)
# Specifically check to see whether the MDRIZTAB file can be found
mtab_path = os.path.split(_tableName)[0] # protect against no path given for _tableName
if mtab_path and not os.path.exists(mtab_path): # check path first, if given
raise IOError("Directory for MDRIZTAB '%s' could not be accessed!"%mtab_path)
if not os.path.exists(_tableName): # then check for the table itself
raise IOError("MDRIZTAB table '%s' could not be found!"%_tableName)
# Open MDRIZTAB file.
try:
_mdriztab = fits.open(_tableName)
except:
raise IOError("MDRIZTAB table '%s' not valid!" % _tableName)
# Look for matching rows based on filter name. If no
# match, pick up rows for the default filter.
_rows = _getRowsByFilter(_mdriztab, _filters)
if _rows == []:
_rows = _getRowsByFilter(_mdriztab, 'ANY')
# Now look for the row that matches the number of images.
# The logic below assumes that rows for a given filter
# are arranged in ascending order of the 'numimage' field.
_nimages = len(files)
_row = 0
for i in _rows:
_numimages = _mdriztab[1].data.field('numimages')[i]
if _nimages >= _numimages:
_row = i
print('- MDRIZTAB: AstroDrizzle parameters read from row %s.'%(_row+1))
mpars = _mdriztab[1].data[_row]
_mdriztab.close()
interpreted = _interpretMdriztabPars(mpars)
if "staticfile" in interpreted:
interpreted.pop("staticfile")
return interpreted
def getIDCFile(image,keyword="",directory=None):
# Open the primary header of the file and read the name of
# the IDCTAB.
# Parameters:
# header - primary and extension header object to read IDCTAB info
#
# keyword(optional) - header keyword with name of IDCTAB
# --OR-- 'HEADER' if need to build IDCTAB name from scratch
# (default value: 'IDCTAB')
# directory(optional) - directory with default drizzle coeffs tables
# (default value: 'drizzle$coeffs')
#
# This function needs to be generalized to support
# keyword='HEADER', as would be the case for WFPC2 data.
#
if type(image) == type(''):
# We were provided an image name, so read in the header...
header = fileutil.getHeader(image)
else:
# otherwise, we were provided an image header we can work with directly
header = image
if keyword.lower() == 'header':
idcfile,idctype = __getIDCTAB(header)
if (idcfile == None):
idcfile,idctype = __buildIDCTAB(header,directory)
elif keyword.lower() == 'idctab':
# keyword specifies header keyword with IDCTAB name
idcfile,idctype = __getIDCTAB(header)
elif keyword == '':
idcfile = None
idctype = None
else:
# Need to build IDCTAB filename from scratch
idcfile,idctype = __buildIDCTAB(header,directory,kw = keyword)
# Account for possible absence of IDCTAB name in header
if idcfile == 'N/A':
idcfile = None
if idcfile != None and idcfile != '':
# Now we need to recursively expand any IRAF symbols to full paths...
#if directory:
idcfile = fileutil.osfn(idcfile)
if idcfile == None:
print('WARNING: No valid distortion coefficients available!')
print('Using default unshifted, unscaled, unrotated model.')
return idcfile,idctype
def getExptime(self):
header = fileutil.getHeader(self.name+'[sci,1]')
_exptime = float(header['EXPTIME'])
if _exptime == 0.: _exptime = 1.0
if 'EXPSTART' in header:
_expstart = float(header['EXPSTART'])
_expend = float(header['EXPEND'])
else:
_expstart = 0.
_expend = _exptime
return (_exptime,_expstart,_expend)
def check_exptime(filelist):
"""
Removes files with EXPTIME==0 from filelist.
"""
removed_files = []
for f in filelist:
try:
exptime = fileutil.getHeader(f+'[sci,1]')['EXPTIME']
except KeyError:
removed_files.append(f)
print("Warning: There are files without keyword EXPTIME")
continue
if exptime <= 0:
removed_files.append(f)
print("Warning: There are files with zero exposure time: keyword EXPTIME = 0.0")
if removed_files != []:
print("Warning: Removing the following files from input list")
for f in removed_files:
print('\t',f)
return removed_files
def check_exptime(filelist):
"""
Removes files with EXPTIME==0 from filelist.
"""
removed_files = []
for f in filelist:
try:
exptime = fileutil.getHeader(f + '[sci,1]')['EXPTIME']
except KeyError:
removed_files.append(f)
print("Warning: There are files without keyword EXPTIME")
continue
if exptime <= 0:
removed_files.append(f)
print(
"Warning: There are files with zero exposure time: keyword EXPTIME = 0.0"
)
if removed_files != []:
print("Warning: Removing the following files from input list")
for f in removed_files:
print('\t', f)
return removed_files
def _getInputImage (input,group=None):
""" Factory function to return appropriate imageObject class instance"""
# extract primary header and SCI,1 header from input image
sci_ext = 'SCI'
if group in [None,'']:
exten = '[sci,1]'
phdu = fits.getheader(input, memmap=False)
else:
# change to use fits more directly here?
if group.find(',') > 0:
grp = group.split(',')
if grp[0].isalpha():
grp = (grp[0],int(grp[1]))
else:
grp = int(grp[0])
else:
grp = int(group)
phdu = fits.getheader(input, memmap=False)
phdu.extend(fits.getheader(input, ext=grp, memmap=False))
# Extract the instrument name for the data that is being processed by Multidrizzle
_instrument = phdu['INSTRUME']
# Determine the instrument detector in use. NICMOS is a special case because it does
# not use the 'DETECTOR' keyword. It instead used 'CAMERA' to identify which of it's
# 3 camera's is in use. All other instruments support the 'DETECTOR' keyword.
if _instrument == 'NICMOS':
_detector = phdu['CAMERA']
else:
try:
_detector = phdu['DETECTOR']
except KeyError:
# using the phdu as set above (fits.getheader) is MUCH faster and
# works for the majority of data; but fileutil handles waivered fits
phdu = fileutil.getHeader(input+exten)
_detector = phdu['DETECTOR'] # if this fails, let it throw
del phdu # just to keep clean
# Match up the instrument and detector with the right class
# only importing the instrument modules as needed.
try:
if _instrument == 'ACS':
from . import acsData
if _detector == 'HRC': return acsData.HRCInputImage(input,group=group)
if _detector == 'WFC': return acsData.WFCInputImage(input,group=group)
if _detector == 'SBC': return acsData.SBCInputImage(input,group=group)
if _instrument == 'NICMOS':
from . import nicmosData
if _detector == 1: return nicmosData.NIC1InputImage(input)
if _detector == 2: return nicmosData.NIC2InputImage(input)
if _detector == 3: return nicmosData.NIC3InputImage(input)
if _instrument == 'WFPC2':
from . import wfpc2Data
return wfpc2Data.WFPC2InputImage(input,group=group)
"""
if _detector == 1: return wfpc2Data.PCInputImage(input)
if _detector == 2: return wfpc2Data.WF2InputImage(input)
if _detector == 3: return wfpc2Data.WF3InputImage(input)
if _detector == 4: return wfpc2Data.WF4InputImage(input)
"""
if _instrument == 'STIS':
from . import stisData
if _detector == 'CCD': return stisData.CCDInputImage(input,group=group)
if _detector == 'FUV-MAMA': return stisData.FUVInputImage(input,group=group)
if _detector == 'NUV-MAMA': return stisData.NUVInputImage(input,group=group)
if _instrument == 'WFC3':
from . import wfc3Data
if _detector == 'UVIS': return wfc3Data.WFC3UVISInputImage(input,group=group)
if _detector == 'IR': return wfc3Data.WFC3IRInputImage(input,group=group)
except ImportError:
msg = 'No module implemented for '+str(_instrument)+'!'
raise ValueError(msg)
# If a supported instrument is not detected, print the following error message
# and raise an exception.
msg = 'Instrument: ' + str(_instrument) + '/' + str(_detector) + ' not yet supported!'
raise ValueError(msg)
def _getInputImage(input, output=None, group=None):
""" Factory function to return appropriate imageObject class instance"""
# extract primary header and SCI,1 header from input image
sci_ext = 'SCI'
if group in [None, '']:
exten = '[sci,1]'
phdu = fits.getheader(input, memmap=False)
else:
# change to use fits more directly here?
if group.find(',') > 0:
grp = group.split(',')
if grp[0].isalpha():
grp = (grp[0], int(grp[1]))
else:
grp = int(grp[0])
else:
grp = int(group)
phdu = fits.getheader(input, memmap=False)
phdu.extend(fits.getheader(input, ext=grp, memmap=False))
# Extract the instrument name for the data that is being processed by Multidrizzle
_instrument = phdu['INSTRUME']
# Determine the instrument detector in use. NICMOS is a special case because it does
# not use the 'DETECTOR' keyword. It instead used 'CAMERA' to identify which of it's
# 3 camera's is in use. All other instruments support the 'DETECTOR' keyword.
if _instrument == 'NICMOS':
_detector = phdu['CAMERA']
else:
try:
_detector = phdu['DETECTOR']
except KeyError:
# using the phdu as set above (fits.getheader) is MUCH faster and
# works for the majority of data; but fileutil handles waivered fits
phdu = fileutil.getHeader(input + exten)
_detector = phdu['DETECTOR'] # if this fails, let it throw
del phdu # just to keep clean
# Match up the instrument and detector with the right class
# only importing the instrument modules as needed.
try:
if _instrument == 'ACS':
from . import acsData
if _detector == 'HRC':
return acsData.HRCInputImage(input, output=output, group=group)
if _detector == 'WFC':
return acsData.WFCInputImage(input, output=output, group=group)
if _detector == 'SBC':
return acsData.SBCInputImage(input, output=output, group=group)
if _instrument == 'NICMOS':
from . import nicmosData
if _detector == 1:
return nicmosData.NIC1InputImage(input, output=output)
if _detector == 2:
return nicmosData.NIC2InputImage(input, output=output)
if _detector == 3:
return nicmosData.NIC3InputImage(input, output=output)
if _instrument == 'WFPC2':
from . import wfpc2Data
return wfpc2Data.WFPC2InputImage(input, output=output, group=group)
"""
if _detector == 1: return wfpc2Data.PCInputImage(input)
if _detector == 2: return wfpc2Data.WF2InputImage(input)
if _detector == 3: return wfpc2Data.WF3InputImage(input)
if _detector == 4: return wfpc2Data.WF4InputImage(input)
"""
if _instrument == 'STIS':
from . import stisData
if _detector == 'CCD':
return stisData.CCDInputImage(input,
output=output,
group=group)
if _detector == 'FUV-MAMA':
return stisData.FUVInputImage(input,
output=output,
group=group)
if _detector == 'NUV-MAMA':
return stisData.NUVInputImage(input,
output=output,
group=group)
if _instrument == 'WFC3':
from . import wfc3Data
if _detector == 'UVIS':
return wfc3Data.WFC3UVISInputImage(input,
output=output,
group=group)
if _detector == 'IR':
return wfc3Data.WFC3IRInputImage(input,
output=output,
group=group)
except ImportError:
msg = 'No module implemented for ' + str(_instrument) + '!'
raise ValueError(msg)
# If a supported instrument is not detected, print the following error message
# and raise an exception.
msg = 'Instrument: ' + str(_instrument) + '/' + str(
_detector) + ' not yet supported!'
raise ValueError(msg)
def __init__(self,expname, handle=None, dqname=None, idckey=None,
new=no,wcs=None,mask=None,pa_key=None, parity=None,
idcdir=None, rot=None, extver=1, exptime=None,
ref_pscale=1.0, binned=1, mt_wcs=None, group_indx = None):
# This name should be formatted for use in image I/O
self.name = fileutil.osfn(expname)
# osfn() will expand '.' unnecessarily, potentially
# creating a string-length problem for 'drizzle', which
# is limited to strings of 80 chars.
_path,_name = os.path.split(self.name)
# if path for this filename is the same as the current dir,
# then there is no need to pass along the path.
if _path == os.getcwd(): self.name = _name
# Keep track of any associated mask file created for
# this exposure from its DQ file, or other mask file.
_fname,_extn = fileutil.parseFilename(expname)
_open = False
# Make sure we have an open file handle to use for getting the
# header and data arrays.
if not handle and not new:
handle = fileutil.openImage(expname)
_open = True
# If no extension was specified, try to interrogate the file
# to find whether the SCI array is in the Primary
# (as in Simple FITS) or first extension (as in MEF).
if handle and _extn == None:
if handle[0].data == None:
# Primary extension specified and no data present.
# Try looking for data in next extension.
if len(handle) > 1 and handle[1].data != None:
_extn = 1
expname += '[1]'
else:
raise IOError("No valid image data in %s.\n"%expname)
else:
_extn = 0
self.dgeoname = None
self.xgeoim = ""
self.ygeoim = ""
self.exptime = exptime
self.group_indx = group_indx
if not new:
# Read in a copy of the header for this exposure/group/extension
_header = fileutil.getHeader(expname,handle=handle)
_chip = drutil.getChipId(_header)
self.chip = str(_chip)
# Keep track of any distortion correction images provided
# for this chip
self.dgeoname = fileutil.getKeyword(expname,'DGEOFILE',handle=handle)
self.xgeoim,self.ygeoim = self.getDGEOExtn()
if self.exptime == None:
self.exptime = float(_header['EXPTIME'])
if self.exptime == 0.: self.exptime = 1.0
#
# Extract photometric transformation keywords
# If they do not exist, use default values of 0 and 1
#
self.plam = float(fileutil.getKeyword(expname,'PHOTPLAM',handle=handle)) / 10.
if self.plam == None:
# Setup a default value in case this keyword does not exist
self.plam = 555.
self.photzpt = float(fileutil.getKeyword(expname,'PHOTZPT',handle=handle))
if self.photzpt == None: self.photzpt = 0.0
self.photflam = float(fileutil.getKeyword(expname,'PHOTFLAM',handle=handle))
if self.photflam == None: self.photflam = 1.0
# Read in date-obs from primary header
if _header:
if 'date-obs' in _header:
self.dateobs = _header['date-obs']
elif 'date_obs' in _header:
self.dateobs = _header['date_obs']
else:
self.dateobs = None
else:
self.dateobs = None
# Initialize the value of BUNIT based on the header information, if
# the header has the keyword
if 'BUNIT' in _header and _header['BUNIT'].find('ergs') < 0:
self.bunit = _header['BUNIT']
else:
self.bunit = 'ELECTRONS'
else:
_chip = 1
_header = None
self.chip = str(_chip)
# Set a default value for pivot wavelength
self.plam = 555.
self.photzpt = 0.0
self.photflam = 1.0
self.dateobs = None
if self.exptime == None:
self.exptime = 1.
self.parity = parity
self.header = _header
self.extver = extver
# Create a pointer to the mask file's data array
# and the name of the original input DQ file
self.maskname = None
self.singlemaskname = None
self.masklist = None
if mask != None:
# Specifies filenames to be used if created.
self.maskname = mask[0]
self.singlemaskname = mask[1]
self.masklist = mask[2]
self.dqname = dqname
# Remember the name of the coeffs file generated for this chip
self.coeffs = self.buildCoeffsName()
# Read the name of idcfile from image header if not explicitly
# provided by user.
if idckey != None and idckey.lower() != 'wcs':
_indx = expname.find('[')
if _indx > -1:
_idc_fname = expname[:_indx]+'[0]'
else: _idc_fname = expname+'[0]'
idcfile, idctype = drutil.getIDCFile(self.header,keyword=idckey,
directory=idcdir)
else:
idcfile = None
idctype = None
if (idckey != None) and (idckey.lower() == 'header'):
idckey = idctype
# Get distortion model and WCS info.
self.geometry = ObsGeometry(expname, idcfile, idckey=idckey,
chip=_chip, new=new, header=self.header,
pa_key=pa_key, rot=rot, date=self.dateobs,
ref_pscale=ref_pscale, binned=binned, mt_wcs=mt_wcs)
# Remember the name and type of the IDC file used...
self.idcfile = idcfile
self.idctype = idctype
# Remember the names of the filters used for the exposure
self.filters = self.geometry.filter1+','+self.geometry.filter2
# Define shape here...
# nx,ny,pixel scale
#
if wcs != None:
# We have been passed a WCS to use
self.geometry.wcs = wcs
self.geometry.model.pscale = wcs.pscale
if expname != None:
self.geometry.wcs.rootname = expname
self.naxis1 = self.geometry.wcs.naxis1
self.naxis2 = self.geometry.wcs.naxis2
self.pscale = self.geometry.wcs.pscale
self.shape = (self.naxis1,self.naxis2,self.pscale)
# Keep track of the positions of the corners of the exposure
# both for the RAW image and the
# distortion-corrected, unscaled, unrotated image
self.corners = {'raw':np.zeros((4,2),dtype=np.float64),'corrected':np.zeros((4,2),dtype=np.float64)}
self.setCorners()
# Generate BLOT output name specific to this Exposure
_blot_extn = '_sci'+repr(extver)+'_blt.fits'
self.outblot = fileutil.buildNewRootname(self.name,extn=_blot_extn)
# Keep track of undistorted frame's position relative to metachip
# Zero-point offset for chip relative to meta-chip product
# These values get computed using 'setSingleOffsets' from 'writeCoeffs'
# to insure that the final XDELTA/YDELTA values have been computed.
self.product_wcs = self.geometry.wcslin
self.xzero = 0.
self.yzero = 0.
self.chip_shape = (0.,0.)
self.xsh2 = 0.
self.ysh2 = 0.
if _open:
handle.close()
del handle
def _update(image,idctab,nimsets,apply_tdd=False,
quiet=None,instrument=None,prepend=None,nrchip=None, nrext=None):
tdd_xyref = {1: [2048, 3072], 2:[2048, 1024]}
_prepend = prepend
_dqname = None
# Make a copy of the header for keyword access
# This copy includes both Primary header and
# extension header
hdr = fileutil.getHeader(image)
# Try to get the instrument if we don't have it already
instrument = readKeyword(hdr,'INSTRUME')
binned = 1
# Read in any specified OFFTAB, if present (WFPC2)
offtab = readKeyword(hdr,'OFFTAB')
dateobs = readKeyword(hdr,'DATE-OBS')
if not quiet:
print("OFFTAB, DATE-OBS: ",offtab,dateobs)
print("-Updating image ",image)
if not quiet:
print("-Reading IDCTAB file ",idctab)
# Get telescope orientation from image header
# If PA_V# is not present of header, try to get it from the spt file
pvt = readKeyword(hdr,'PA_V3')
if pvt == None:
sptfile = fileutil.buildNewRootname(image, extn='_spt.fits')
if os.path.exists(sptfile):
spthdr = fileutil.getHeader(sptfile)
pvt = readKeyword(spthdr,'PA_V3')
if pvt != None:
pvt = float(pvt)
else:
print('PA_V3 keyword not found, WCS cannot be updated. Quitting ...')
raise ValueError
# Find out about instrument, detector & filters
detector = readKeyword(hdr,'DETECTOR')
Nrefchip=1
if instrument == 'WFPC2':
filter1 = readKeyword(hdr,'FILTNAM1')
filter2 = readKeyword(hdr,'FILTNAM2')
mode = readKeyword(hdr,'MODE')
if os.path.exists(fileutil.buildNewRootname(image, extn='_c1h.fits')):
_dqname = fileutil.buildNewRootname(image, extn='_c1h.fits')
dqhdr = pyfits.getheader(_dqname,1)
dqext = readKeyword(dqhdr, 'EXTNAME')
if mode == 'AREA':
binned = 2
Nrefchip=nrchip
elif instrument == 'NICMOS':
filter1 = readKeyword(hdr,'FILTER')
filter2 = None
elif instrument == 'WFC3':
filter1 = readKeyword(hdr,'FILTER')
filter2 = None
# use value of 'BINAXIS' keyword to set binning value for WFC3 data
binned = readKeyword(hdr,'BINAXIS1')
else:
filter1 = readKeyword(hdr,'FILTER1')
filter2 = readKeyword(hdr,'FILTER2')
if filter1 == None or filter1.strip() == '': filter1 = 'CLEAR'
else: filter1 = filter1.strip()
if filter2 == None or filter2.strip() == '': filter2 = 'CLEAR'
else: filter2 = filter2.strip()
if filter1.find('CLEAR') == 0: filter1 = 'CLEAR'
if filter2.find('CLEAR') == 0: filter2 = 'CLEAR'
# Set up parity matrix for chip
if instrument == 'WFPC2' or instrument =='STIS' or instrument == 'NICMOS':
parity = PARITY[instrument]
elif detector in PARITY:
parity = PARITY[detector]
else:
raise ValueError('Detector ',detector,
' Not supported at this time. Exiting...')
# Get the VAFACTOR keyword if it exists, otherwise set to 1.0
# we also need the reference pointing position of the target
# as this is where
_va_key = readKeyword(hdr,'VAFACTOR')
if _va_key != None:
VA_fac = float(_va_key)
else:
VA_fac=1.0
if not quiet:
print('VA factor: ',VA_fac)
#ra_targ = float(readKeyword(hdr,'RA_TARG'))
#dec_targ = float(readKeyword(hdr,'DEC_TARG'))
# Get the chip number
_c = readKeyword(hdr,'CAMERA')
_s = readKeyword(hdr,'CCDCHIP')
_d = readKeyword(hdr,'DETECTOR')
if _c != None and str(_c).isdigit():
chip = int(_c)
elif _s == None and _d == None:
chip = 1
else:
if _s:
chip = int(_s)
elif str(_d).isdigit():
chip = int(_d)
else:
chip = 1
# For the ACS/WFC case the chip number doesn't match the image
# extension
nr = 1
if (instrument == 'ACS' and detector == 'WFC') or (instrument == 'WFC3' and detector == 'UVIS'):
if nimsets > 1:
Nrefchip = 2
else:
Nrefchip = chip
elif instrument == 'NICMOS':
Nrefchip = readKeyword(hdr,'CAMERA')
elif instrument == 'WFPC2':
nr = nrext
else:
if nimsets > 1:
nr = Nrefchip
if not quiet:
print("-PA_V3 : ",pvt," CHIP #",chip)
# Extract the appropriate information from the IDCTAB
#fx,fy,refpix,order=fileutil.readIDCtab(idctab,chip=chip,direction='forward',
# filter1=filter1,filter2=filter2,offtab=offtab,date=dateobs)
idcmodel = models.IDCModel(idctab,
chip=chip, direction='forward', date=dateobs,
filter1=filter1, filter2=filter2, offtab=offtab, binned=binned,
tddcorr=apply_tdd)
fx = idcmodel.cx
fy = idcmodel.cy
refpix = idcmodel.refpix
order = idcmodel.norder
# Determine whether to perform time-dependent correction
# Construct matrices neded to correct the zero points for TDD
if apply_tdd:
#alpha,beta = mutil.compute_wfc_tdd_coeffs(dateobs,skew_coeffs)
alpha = refpix['TDDALPHA']
beta = refpix['TDDBETA']
tdd = N.array([[beta, alpha], [alpha, -beta]])
mrotp = fileutil.buildRotMatrix(2.234529)/2048.
else:
alpha = 0.0
beta = 0.0
# Get the original image WCS
Old=wcsutil.WCSObject(image,prefix=_prepend)
# Reset the WCS keywords to original archived values.
Old.restore()
#
# Look for any subarray offset
#
ltv1,ltv2 = drutil.getLTVOffsets(image)
#
# If reference point is not centered on distortion model
# shift coefficients to be applied relative to observation
# reference position
#
offsetx = Old.crpix1 - ltv1 - refpix['XREF']
offsety = Old.crpix2 - ltv2 - refpix['YREF']
shiftx = refpix['XREF'] + ltv1
shifty = refpix['YREF'] + ltv2
if ltv1 != 0. or ltv2 != 0.:
ltvoffx = ltv1 + offsetx
ltvoffy = ltv2 + offsety
offshiftx = offsetx + shiftx
offshifty = offsety + shifty
else:
ltvoffx = 0.
ltvoffy = 0.
offshiftx = 0.
offshifty = 0.
if ltv1 != 0. or ltv2 != 0.:
fx,fy = idcmodel.shift(idcmodel.cx,idcmodel.cy,offsetx,offsety)
# Extract the appropriate information for reference chip
ridcmodel = models.IDCModel(idctab,
chip=Nrefchip, direction='forward', date=dateobs,
filter1=filter1, filter2=filter2, offtab=offtab, binned=binned,
tddcorr=apply_tdd)
rfx = ridcmodel.cx
rfy = ridcmodel.cy
rrefpix = ridcmodel.refpix
rorder = ridcmodel.norder
"""
rfx,rfy,rrefpix,rorder=mutil.readIDCtab(idctab,chip=Nrefchip,
direction='forward', filter1=filter1,filter2=filter2,offtab=offtab,
date=dateobs,tddcorr=apply_tdd)
"""
# Create the reference image name
rimage = image.split('[')[0]+"[sci,%d]" % nr
if not quiet:
print("Reference image: ",rimage)
# Create the tangent plane WCS on which the images are defined
# This is close to that of the reference chip
R=wcsutil.WCSObject(rimage)
R.write_archive(rimage)
R.restore()
# Reacd in declination of target (for computing orientation at aperture)
# Note that this is from the reference image
#dec = float(fileutil.getKeyword(rimage,'CRVAL2'))
#crval1 = float(fileutil.getKeyword(rimage,'CRVAL1'))
#crval1 = float(R.crval1)
#crval2 = dec
dec = float(R.crval2)
# Get an approximate reference position on the sky
rref = (rrefpix['XREF']+ltvoffx, rrefpix['YREF']+ltvoffy)
crval1,crval2=R.xy2rd(rref)
if apply_tdd:
# Correct zero points for TDD
tddscale = (R.pscale/fx[1][1])
rxy0 = N.array([[tdd_xyref[Nrefchip][0]-2048.],[ tdd_xyref[Nrefchip][1]-2048.]])
xy0 = N.array([[tdd_xyref[chip][0]-2048.], [tdd_xyref[chip][1]-2048.]])
rv23_corr = N.dot(mrotp,N.dot(tdd,rxy0))*tddscale
v23_corr = N.dot(mrotp,N.dot(tdd,xy0))*tddscale
else:
rv23_corr = N.array([[0],[0]])
v23_corr = N.array([[0],[0]])
# Convert the PA_V3 orientation to the orientation at the aperture
# This is for the reference chip only - we use this for the
# reference tangent plane definition
# It has the same orientation as the reference chip
v2ref = rrefpix['V2REF'] + rv23_corr[0][0]*0.05
v3ref = rrefpix['V3REF'] - rv23_corr[1][0]*0.05
v2 = refpix['V2REF'] + v23_corr[0][0]*0.05
v3 = refpix['V3REF'] - v23_corr[1][0] *0.05
pv = wcsutil.troll(pvt,dec,v2ref,v3ref)
# Add the chip rotation angle
if rrefpix['THETA']:
pv += rrefpix['THETA']
# Set values for the rest of the reference WCS
R.crval1=crval1
R.crval2=crval2
R.crpix1=0.0 + offshiftx
R.crpix2=0.0 + offshifty
R_scale=rrefpix['PSCALE']/3600.0
R.cd11=parity[0][0] * cos(pv*pi/180.0)*R_scale
R.cd12=parity[0][0] * -sin(pv*pi/180.0)*R_scale
R.cd21=parity[1][1] * sin(pv*pi/180.0)*R_scale
R.cd22=parity[1][1] * cos(pv*pi/180.0)*R_scale
##print R
R_cdmat = N.array([[R.cd11,R.cd12],[R.cd21,R.cd22]])
if not quiet:
print(" Reference Chip Scale (arcsec/pix): ",rrefpix['PSCALE'])
# Offset and angle in V2/V3 from reference chip to
# new chip(s) - converted to reference image pixels
off = sqrt((v2-v2ref)**2 + (v3-v3ref)**2)/(R_scale*3600.0)
# Here we must include the PARITY
if v3 == v3ref:
theta=0.0
else:
theta = atan2(parity[0][0]*(v2-v2ref),parity[1][1]*(v3-v3ref))
if rrefpix['THETA']: theta += rrefpix['THETA']*pi/180.0
dX=(off*sin(theta)) + offshiftx
dY=(off*cos(theta)) + offshifty
# Check to see whether we are working with GEIS or FITS input
_fname,_iextn = fileutil.parseFilename(image)
if _fname.find('.fits') < 0:
# Input image is NOT a FITS file, so
# build a FITS name for it's copy.
_fitsname = fileutil.buildFITSName(_fname)
else:
_fitsname = None
# Create a new instance of a WCS
if _fitsname == None:
_new_name = image
else:
_new_name = _fitsname+'['+str(_iextn)+']'
#New=wcsutil.WCSObject(_new_name,new=yes)
New = Old.copy()
# Calculate new CRVALs and CRPIXs
New.crval1,New.crval2=R.xy2rd((dX,dY))
New.crpix1=refpix['XREF'] + ltvoffx
New.crpix2=refpix['YREF'] + ltvoffy
# Account for subarray offset
# Angle of chip relative to chip
if refpix['THETA']:
dtheta = refpix['THETA'] - rrefpix['THETA']
else:
dtheta = 0.0
# Create a small vector, in reference image pixel scale
# There is no parity effect here ???
delXX=fx[1,1]/R_scale/3600.
delYX=fy[1,1]/R_scale/3600.
delXY=fx[1,0]/R_scale/3600.
delYY=fy[1,0]/R_scale/3600.
# Convert to radians
rr=dtheta*pi/180.0
# Rotate the vectors
dXX= cos(rr)*delXX - sin(rr)*delYX
dYX= sin(rr)*delXX + cos(rr)*delYX
dXY= cos(rr)*delXY - sin(rr)*delYY
dYY= sin(rr)*delXY + cos(rr)*delYY
# Transform to sky coordinates
a,b=R.xy2rd((dX+dXX,dY+dYX))
c,d=R.xy2rd((dX+dXY,dY+dYY))
# Calculate the new CDs and convert to degrees
New.cd11=diff_angles(a,New.crval1)*cos(New.crval2*pi/180.0)
New.cd12=diff_angles(c,New.crval1)*cos(New.crval2*pi/180.0)
New.cd21=diff_angles(b,New.crval2)
New.cd22=diff_angles(d,New.crval2)
# Apply the velocity aberration effect if applicable
if VA_fac != 1.0:
# First shift the CRVALs apart
# New.crval1 = ra_targ + VA_fac*(New.crval1 - ra_targ)
# New.crval2 = dec_targ + VA_fac*(New.crval2 - dec_targ)
# First shift the CRVALs apart
# This is now relative to the reference chip, not the
# target position.
New.crval1 = R.crval1 + VA_fac*diff_angles(New.crval1, R.crval1)
New.crval2 = R.crval2 + VA_fac*diff_angles(New.crval2, R.crval2)
# and scale the CDs
New.cd11 = New.cd11*VA_fac
New.cd12 = New.cd12*VA_fac
New.cd21 = New.cd21*VA_fac
New.cd22 = New.cd22*VA_fac
New_cdmat = N.array([[New.cd11,New.cd12],[New.cd21,New.cd22]])
# Store new one
# archive=yes specifies to also write out archived WCS keywords
# overwrite=no specifies do not overwrite any pre-existing archived keywords
New.write(fitsname=_new_name,overwrite=no,quiet=quiet,archive=yes)
if _dqname:
_dq_iextn = _iextn.replace('sci', dqext.lower())
_new_dqname = _dqname +'['+_dq_iextn+']'
dqwcs = wcsutil.WCSObject(_new_dqname)
dqwcs.write(fitsname=_new_dqname, wcs=New,overwrite=no,quiet=quiet, archive=yes)
""" Convert distortion coefficients into SIP style
values and write out to image (assumed to be FITS).
"""
#First the CD matrix:
f = refpix['PSCALE']/3600.0
a = fx[1,1]/3600.0
b = fx[1,0]/3600.0
c = fy[1,1]/3600.0
d = fy[1,0]/3600.0
det = (a*d - b*c)*refpix['PSCALE']
# Write to header
fimg = fileutil.openImage(_new_name,mode='update')
_new_root,_nextn = fileutil.parseFilename(_new_name)
_new_extn = fileutil.getExtn(fimg,_nextn)
# Transform the higher-order coefficients
for n in range(order+1):
for m in range(order+1):
if n >= m and n>=2:
# Form SIP-style keyword names
Akey="A_%d_%d" % (m,n-m)
Bkey="B_%d_%d" % (m,n-m)
# Assign them values
Aval= f*(d*fx[n,m]-b*fy[n,m])/det
Bval= f*(a*fy[n,m]-c*fx[n,m])/det
_new_extn.header.update(Akey,Aval)
_new_extn.header.update(Bkey,Bval)
# Update the SIP flag keywords as well
#iraf.hedit(image,"CTYPE1","RA---TAN-SIP",verify=no,show=no)
#iraf.hedit(image,"CTYPE2","DEC--TAN-SIP",verify=no,show=no)
_new_extn.header.update("CTYPE1","RA---TAN-SIP")
_new_extn.header.update("CTYPE2","DEC--TAN-SIP")
# Finally we also need the order
#iraf.hedit(image,"A_ORDER","%d" % order,add=yes,verify=no,show=no)
#iraf.hedit(image,"B_ORDER","%d" % order,add=yes,verify=no,show=no)
_new_extn.header.update("A_ORDER",order)
_new_extn.header.update("B_ORDER",order)
# Update header with additional keywords required for proper
# interpretation of SIP coefficients by PyDrizzle.
_new_extn.header.update("IDCSCALE",refpix['PSCALE'])
_new_extn.header.update("IDCV2REF",refpix['V2REF'])
_new_extn.header.update("IDCV3REF",refpix['V3REF'])
_new_extn.header.update("IDCTHETA",refpix['THETA'])
_new_extn.header.update("OCX10",fx[1][0])
_new_extn.header.update("OCX11",fx[1][1])
_new_extn.header.update("OCY10",fy[1][0])
_new_extn.header.update("OCY11",fy[1][1])
#_new_extn.header.update("TDDXOFF",rv23_corr[0][0] - v23_corr[0][0])
#_new_extn.header.update("TDDYOFF",-(rv23_corr[1][0] - v23_corr[1][0]))
# Report time-dependent coeffs, if computed
if instrument == 'ACS' and detector == 'WFC':
_new_extn.header.update("TDDALPHA",alpha)
_new_extn.header.update("TDDBETA",beta)
# Close image now
fimg.close()
del fimg
