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)