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from __future__ import division # confidence high
from astropy.io import fits as pyfits
from stsci.tools import fileutil
import utils
import numpy as np
import logging, time
logger = logging.getLogger('stwcs.updatewcs.npol')
class NPOLCorr(object):
"""
Defines a Lookup table prior distortion correction as per WCS paper IV.
It uses a reference file defined by the NPOLFILE (suffix 'NPL') keyword
in the primary header.
Notes
-----
- Using extensions in the reference file create a WCSDVARR extensions
and add them to the science file.
- Add record-valued keywords to the science extension header to describe
the lookup tables.
- Add a keyword 'NPOLEXT' to the science extension header to store
the name of the reference file used to create the WCSDVARR extensions.
If WCSDVARR extensions exist and `NPOLFILE` is different from `NPOLEXT`,
a subsequent update will overwrite the existing extensions.
If WCSDVARR extensions were not found in the science file, they will be added.
It is assumed that the NPL reference files were created to work with IDC tables
but will be applied with SIP coefficients. A transformation is applied to correct
for the fact that the lookup tables will be applied before the first order coefficients
which are in the CD matrix when the SIP convention is used.
"""
def updateWCS(cls, fobj):
"""
Parameters
----------
fobj: pyfits object
Science file, for which a distortion correction in a NPOLFILE is available
"""
logger.info("\n\tStarting NPOL: %s" %time.asctime())
try:
assert isinstance(fobj, pyfits.HDUList)
except AssertionError:
logger.exception('\n\tInput must be a pyfits.HDUList object')
raise
cls.applyNPOLCorr(fobj)
nplfile = fobj[0].header['NPOLFILE']
new_kw = {'NPOLEXT': nplfile}
return new_kw
updateWCS = classmethod(updateWCS)
def applyNPOLCorr(cls, fobj):
"""
For each science extension in a pyfits file object:
- create a WCSDVARR extension
- update science header
- add/update NPOLEXT keyword
"""
nplfile = fileutil.osfn(fobj[0].header['NPOLFILE'])
# Map WCSDVARR EXTVER numbers to extension numbers
wcsdvarr_ind = cls.getWCSIndex(fobj)
for ext in fobj:
try:
extname = ext.header['EXTNAME'].lower()
except KeyError:
continue
if extname == 'sci':
extversion = ext.header['EXTVER']
ccdchip = cls.get_ccdchip(fobj, extname='SCI', extver=extversion)
header = ext.header
# get the data arrays from the reference file and transform
# them for use with SIP
dx,dy = cls.getData(nplfile, ccdchip)
idccoeffs = cls.getIDCCoeffs(header)
if idccoeffs != None:
dx, dy = cls.transformData(dx,dy, idccoeffs)
# Determine EXTVER for the WCSDVARR extension from the
# NPL file (EXTNAME, EXTVER) kw.
# This is used to populate DPj.EXTVER kw
wcsdvarr_x_version = 2 * extversion -1
wcsdvarr_y_version = 2 * extversion
for ename in zip(['DX', 'DY'], [wcsdvarr_x_version,wcsdvarr_y_version],[dx, dy]):
error_val = ename[2].max()
cls.addSciExtKw(header, wdvarr_ver=ename[1], npol_extname=ename[0], error_val=error_val)
hdu = cls.createNpolHDU(header, npolfile=nplfile, \
wdvarr_ver=ename[1], npl_extname=ename[0], data=ename[2],ccdchip=ccdchip)
if wcsdvarr_ind:
fobj[wcsdvarr_ind[ename[1]]] = hdu
else:
fobj.append(hdu)
applyNPOLCorr = classmethod(applyNPOLCorr)
def getWCSIndex(cls, fobj):
"""
If fobj has WCSDVARR extensions:
returns a mapping of their EXTVER kw to file object extension numbers
if fobj does not have WCSDVARR extensions:
an empty dictionary is returned
"""
wcsd = {}
for e in range(len(fobj)):
try:
ename = fobj[e].header['EXTNAME']
except KeyError:
continue
if ename == 'WCSDVARR':
wcsd[fobj[e].header['EXTVER']] = e
logger.debug("A map of WSCDVARR externsions %s" % wcsd)
return wcsd
getWCSIndex = classmethod(getWCSIndex)
def addSciExtKw(cls, hdr, wdvarr_ver=None, npol_extname=None, error_val=0.0):
"""
Adds kw to sci extension to define WCSDVARR lookup table extensions
"""
if npol_extname =='DX':
j=1
else:
j=2
cperror = 'CPERR%s' %j
cpdis = 'CPDIS%s' %j
dpext = 'DP%s.' %j + 'EXTVER'
dpnaxes = 'DP%s.' %j +'NAXES'
dpaxis1 = 'DP%s.' %j+'AXIS.1'
dpaxis2 = 'DP%s.' %j+'AXIS.2'
keys = [cperror, cpdis, dpext, dpnaxes, dpaxis1, dpaxis2]
values = {cperror: error_val,
cpdis: 'Lookup',
dpext: wdvarr_ver,
dpnaxes: 2,
dpaxis1: 1,
dpaxis2: 2}
comments = {cperror: 'Maximum error of NPOL correction for axis %s' % j,
cpdis: 'Prior distortion function type',
dpext: 'Version number of WCSDVARR extension containing lookup distortion table',
dpnaxes: 'Number of independent variables in distortion function',
dpaxis1: 'Axis number of the jth independent variable in a distortion function',
dpaxis2: 'Axis number of the jth independent variable in a distortion function'
}
# Look for HISTORY keywords. If present, insert new keywords before them
before_key = 'HISTORY'
if before_key not in hdr:
before_key = None
for key in keys:
hdr.set(key, value=values[key], comment=comments[key], before=before_key)
addSciExtKw = classmethod(addSciExtKw)
def getData(cls,nplfile, ccdchip):
"""
Get the data arrays from the reference NPOL files
Make sure 'CCDCHIP' in the npolfile matches "CCDCHIP' in the science file.
"""
npl = pyfits.open(nplfile)
for ext in npl:
nplextname = ext.header.get('EXTNAME',"")
nplccdchip = ext.header.get('CCDCHIP',1)
if nplextname == 'DX' and nplccdchip == ccdchip:
xdata = ext.data.copy()
continue
elif nplextname == 'DY' and nplccdchip == ccdchip:
ydata = ext.data.copy()
continue
else:
continue
npl.close()
return xdata, ydata
getData = classmethod(getData)
def transformData(cls, dx, dy, coeffs):
"""
Transform the NPOL data arrays for use with SIP
"""
ndx, ndy = np.dot(coeffs, [dx.ravel(), dy.ravel()]).astype(np.float32)
ndx.shape = dx.shape
ndy.shape=dy.shape
return ndx, ndy
transformData = classmethod(transformData)
def getIDCCoeffs(cls, header):
"""
Return a matrix of the scaled first order IDC coefficients.
"""
try:
ocx10 = header['OCX10']
ocx11 = header['OCX11']
ocy10 = header['OCY10']
ocy11 = header['OCY11']
coeffs = np.array([[ocx11, ocx10], [ocy11,ocy10]], dtype=np.float32)
except KeyError:
logger.exception('\n\tFirst order IDCTAB coefficients are not available. \n\
Cannot convert SIP to IDC coefficients.')
return None
try:
idcscale = header['IDCSCALE']
except KeyError:
logger.exception("IDCSCALE not found in header - setting it to 1.")
idcscale = 1
return np.linalg.inv(coeffs/idcscale)
getIDCCoeffs = classmethod(getIDCCoeffs)
def createNpolHDU(cls, sciheader, npolfile=None, wdvarr_ver=1, npl_extname=None,data = None, ccdchip=1):
"""
Creates an HDU to be added to the file object.
"""
hdr = cls.createNpolHdr(sciheader, npolfile=npolfile, wdvarr_ver=wdvarr_ver, npl_extname=npl_extname, ccdchip=ccdchip)
hdu=pyfits.ImageHDU(header=hdr, data=data)
return hdu
createNpolHDU = classmethod(createNpolHDU)
def createNpolHdr(cls, sciheader, npolfile, wdvarr_ver, npl_extname, ccdchip):
"""
Creates a header for the WCSDVARR extension based on the NPOL reference file
and sci extension header. The goal is to always work in image coordinates
(also for subarrays and binned images. The WCS for the WCSDVARR extension
i ssuch that a full size npol table is created and then shifted or scaled
if the science image is a subarray or binned image.
"""
npl = pyfits.open(npolfile)
npol_phdr = npl[0].header
for ext in npl:
try:
nplextname = ext.header['EXTNAME']
nplextver = ext.header['EXTVER']
except KeyError:
continue
nplccdchip = cls.get_ccdchip(npl, extname=nplextname, extver=nplextver)
if nplextname == npl_extname and nplccdchip == ccdchip:
npol_header = ext.header
break
else:
continue
npl.close()
naxis = npl[1].header['NAXIS']
ccdchip = nplextname #npol_header['CCDCHIP']
kw = { 'NAXIS': 'Size of the axis',
'CDELT': 'Coordinate increment along axis',
'CRPIX': 'Coordinate system reference pixel',
'CRVAL': 'Coordinate system value at reference pixel',
}
kw_comm1 = {}
kw_val1 = {}
for key in kw.keys():
for i in range(1, naxis+1):
si = str(i)
kw_comm1[key+si] = kw[key]
for i in range(1, naxis+1):
si = str(i)
kw_val1['NAXIS'+si] = npol_header.get('NAXIS'+si)
kw_val1['CDELT'+si] = npol_header.get('CDELT'+si, 1.0) * \
sciheader.get('LTM'+si+'_'+si, 1)
kw_val1['CRPIX'+si] = npol_header.get('CRPIX'+si, 0.0)
kw_val1['CRVAL'+si] = (npol_header.get('CRVAL'+si, 0.0) - \
sciheader.get('LTV'+str(i), 0))
kw_comm0 = {'XTENSION': 'Image extension',
'BITPIX': 'IEEE floating point',
'NAXIS': 'Number of axes',
'EXTNAME': 'WCS distortion array',
'EXTVER': 'Distortion array version number',
'PCOUNT': 'Special data area of size 0',
'GCOUNT': 'One data group',
}
kw_val0 = { 'XTENSION': 'IMAGE',
'BITPIX': -32,
'NAXIS': naxis,
'EXTNAME': 'WCSDVARR',
'EXTVER': wdvarr_ver,
'PCOUNT': 0,
'GCOUNT': 1,
'CCDCHIP': ccdchip,
}
cdl = []
for key in kw_comm0.keys():
cdl.append((key, kw_val0[key], kw_comm0[key]))
for key in kw_comm1.keys():
cdl.append((key, kw_val1[key], kw_comm1[key]))
# Now add keywords from NPOLFILE header to document source of calibration
# include all keywords after and including 'FILENAME' from header
start_indx = -1
end_indx = 0
for i, c in enumerate(npol_phdr):
if c == 'FILENAME':
start_indx = i
if c == '': # remove blanks from end of header
end_indx = i+1
break
if start_indx >= 0:
for card in npol_phdr.cards[start_indx:end_indx]:
cdl.append(card)
hdr = pyfits.Header(cards=cdl)
return hdr
createNpolHdr = classmethod(createNpolHdr)
def get_ccdchip(cls, fobj, extname, extver):
"""
Given a science file or npol file determine CCDCHIP
"""
ccdchip = 1
if fobj[0].header['INSTRUME'] == 'ACS' and fobj[0].header['DETECTOR'] == 'WFC':
ccdchip = fobj[extname, extver].header['CCDCHIP']
elif fobj[0].header['INSTRUME'] == 'WFC3' and fobj[0].header['DETECTOR'] == 'UVIS':
ccdchip = fobj[extname, extver].header['CCDCHIP']
elif fobj[0].header['INSTRUME'] == 'WFPC2':
ccdchip = fobj[extname, extver].header['DETECTOR']
elif fobj[0].header['INSTRUME'] == 'STIS':
ccdchip = fobj[extname, extver].header['DETECTOR']
elif fobj[0].header['INSTRUME'] == 'NICMOS':
ccdchip = fobj[extname, extver].header['CAMERA']
return ccdchip
get_ccdchip = classmethod(get_ccdchip)
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