def determineCoordsFromImage(self, imageFileName):
configFolder = self.ppl["CONFIG_FOLDER"]
if configFolder == None:
configFolder = "$HOME/.pmlib"
SOLVE_ARGS = "-O --config " + configFolder + "/astrometry.cfg --use-sextractor --sextractor-path sextractor -r -y -p"
makedirs("temp", exist_ok = True)
invoke("cp " + imageFileName + " temp/src.fits")
astFolder = self.ppl["AST_BIN_FOLDER"]
if astFolder == None:
astFolder = "/usr/local/astrometry/bin"
astResult = invoke(astFolder + "/solve-field " + SOLVE_ARGS + " -D temp -N temp/ast.fits temp/src.fits")
r = astResult.split('\n')
coords = [0.0, 0.0]
sCoordsSexa = ["00:00:00", "+00:00:00"]
for line in r:
if line.startswith("Field center"):
if line.find("RA,Dec") > -1:
sCoords = self.getPair(line.split('(')[2].split(')')[0])
coords = [ float(sCoords[0]), float(sCoords[1]) ]
printInfo("Image center: %s %s" % (sCoords[0], sCoords[1]))
else:
sCoordsSexa = self.getPair(line.split('(')[2].split(')')[0])
coords = [ hexa2deg(sCoordSexa[0]) * 15.0, hexa2deg(sCoordSexa[1]) ]
printInfo("Image center: %s %s" % (sCoordsSexa[0], sCoordsSexa[1]))
elif line.startswith("Field size"):
sFieldSize = self.getPair(line.split(':')[1].split('a')[0], 'x')
printInfo("Image size: %s' x %s'" % (sFieldSize[0], sFieldSize[1]))
return coords
def makeMasterBias(self, biasFolder, color):
BIAS_PATTERN = "%s/%s*-%s.fits" % (
biasFolder, self.pplSetup['BIAS_FILE_PREFIX'], color)
BIASLIST = glob.glob(BIAS_PATTERN)
BIASLIST.sort()
masterBiasFile = "%s/%s-%s.fits" % (
biasFolder, self.pplSetup['MASTER_BIAS_FILE'], color)
if len(BIASLIST) == 0:
return 1
print("%s -> %s" % (BIAS_PATTERN, masterBiasFile))
# Calibrated images: all the images have the same name but put into a separate directory ($TARGET):
R_BIASLIST = list(
map(lambda x: self.TEMPDIR + '/' + basename(x), BIASLIST))
# The calibration of the individual bias frames, followed by their combination into a single master image:
invoke("ficalib -i %s %s %s -o %s" %
(' '.join(BIASLIST), self.COMMON_ARGS,
self.imSizeArg(BIASLIST[0]), ' '.join(R_BIASLIST)))
invoke("ficombine %s --mode median -o %s" %
(' '.join(R_BIASLIST), masterBiasFile))
# cleanup: remove temp files
for f in R_BIASLIST:
os.remove(f)
return 0
def cleanFolder(self, subfolder, filePattern='*'):
folderPattern = '*' + self.opt['baseFolder'] + '*/' + subfolder
removePattern = folderPattern + '/' + filePattern
fs = glob(removePattern)
if len(fs) > 0:
printInfo("Cleaning folders: %s" % (folderPattern))
for f in fs:
invoke("rm -f %s" % (f))
else:
print("No %s files in folders %s" % (filePattern, folderPattern))
def makeMasterDark(self, darkFolder, biasFolder, color):
# Names of the individual files storing the raw bias, dark, flat and object frames:
DARK_PATTERN = "%s/%s*-%s.fits" % (
darkFolder, self.pplSetup['DARK_FILE_PREFIX'], color)
DARKLIST = glob.glob(DARK_PATTERN)
DARKLIST.sort()
masterDarkFile = "%s/%s-%s.fits" % (
darkFolder, self.pplSetup['MASTER_DARK_FILE'], color)
masterBiasFile = "%s/%s-%s.fits" % (
biasFolder, self.pplSetup['MASTER_BIAS_FILE'], color)
if len(DARKLIST) == 0:
return 1
print("%s -> %s" % (DARK_PATTERN, masterDarkFile))
# Calibrated images: all the images have the same name but put into a separate directory ($TARGET):
R_DARKLIST = list(
map(lambda x: self.TEMPDIR + '/' + basename(x), DARKLIST))
# The calibration of the individual bias frames, followed by their combination into a single master image:
invoke(
"ficalib -i %s %s %s -o %s --input-master-bias %s" %
(' '.join(DARKLIST), self.COMMON_ARGS, self.imSizeArg(
DARKLIST[0]), ' '.join(R_DARKLIST), masterBiasFile))
invoke("ficombine %s --mode median -o %s" %
(' '.join(R_DARKLIST), masterDarkFile))
# Calculate average ccd temperature from .cr2 files, and set it into the master dark
tsum = 0
count = 0
for f in DARKLIST:
hdr = getFitsHeader(f, 'CCD-TEMP')
if hdr:
ccdtemp = int()
tsum += ccdtemp
count += 1
if count > 0:
AVGTEMP = (tsum + (count / 2)) / count
print("average dark temperature: %d C" % (AVGTEMP))
setFitsHeaders(
masterDarkFile,
{'CCD-TEMP': ("%d." % (AVGTEMP), "CCD Temperature (Celsius)")})
# cleanup: remove temp files
for f in R_DARKLIST:
os.remove(f)
return 0
def invoked(self, cmd):
if self.opt['debug']:
printDebug(cmd)
result = invoke(cmd)
if result.startswith('ERROR:'):
printError(result[len('ERROR: '):])
elif self.opt['debug']:
printDebug(result)
return result
def makeMasterFlat(self, flatfolder, biasFolder, darkFolder, color):
# Names of the individual files storing the raw bias, dark, flat and object frames:
FLAT_PATTERN = "%s/%s*-%s.fits" % (
flatfolder, self.pplSetup['FLAT_FILE_PREFIX'], color)
FLATLIST = glob.glob(FLAT_PATTERN)
FLATLIST.sort()
masterFlatFile = "%s/%s-%s.fits" % (
flatfolder, self.pplSetup['MASTER_FLAT_FILE'], color)
masterDarkFile = "%s/%s-%s.fits" % (
darkFolder, self.pplSetup['MASTER_DARK_FILE'], color)
masterBiasFile = "%s/%s-%s.fits" % (
biasFolder, self.pplSetup['MASTER_BIAS_FILE'], color)
if len(FLATLIST) == 0:
return 1
print("%s -> %s" % (FLAT_PATTERN, masterFlatFile))
# Calibrated images: all the images have the same name but put into a separate directory ($TARGET):
R_FLATLIST = list(
map(lambda x: self.TEMPDIR + '/' + basename(x), FLATLIST))
# The calibration of the individual flat frames, followed by their combination into a single master image:
invoke(
"ficalib -i %s %s %s --post-scale 20000 -o %s --input-master-bias %s --input-master-dark %s"
%
(' '.join(FLATLIST), self.COMMON_ARGS, self.imSizeArg(FLATLIST[0]),
' '.join(R_FLATLIST), masterBiasFile, masterDarkFile))
invoke("ficombine %s --mode median -o %s" %
(' '.join(R_FLATLIST), masterFlatFile))
# remove temp files
for f in R_FLATLIST:
os.remove(f)
return 0
def raw2fitsFile(self, rawfile, color):
FITS_NAME = "%s-%s.fits" % (rawfile[:rawfile.rfind('.')], color)
if self.opt['overwrite'] and exists(FITS_NAME):
os.remove(FITS_NAME)
if not exists(FITS_NAME):
print("%s -> %s" % (rawfile, FITS_NAME))
# convert raw image to fits
# TODO: use invoke, parse options with ' or " correctly, or use preparsed options
os.system(
"rawtran -c %s -o %s -B 16 -C '-4 -D -t 0' -X '-q 3 -w' %s" %
(color, FITS_NAME, rawfile))
# read image temperature from raw file
exif = invoke("exiftool -s -g %s" % (rawfile))
IMAGETEMP = None
for line in exif.split('\n'):
if line.startswith('CameraTemperature'):
IMAGETEMP = line.split(':')[1].strip()
break
if IMAGETEMP:
# write image temperature to fits file
setFitsHeaders(
FITS_NAME,
{'CCD-TEMP': (IMAGETEMP, 'CCD Temperature (Celsius)')})
# convert observation time from local time to UT
if self.opt['imageTime'] == 'LT':
IMAGE_DATE = getFitsHeader(FITS_NAME, 'DATE-OBS')
IMAGE_DATE_UTC = self.lt2ut(IMAGE_DATE)
setFitsHeaders(
FITS_NAME, {
'DATE-OBS':
IMAGE_DATE_UTC,
'DATE-IMG':
(IMAGE_DATE, 'Original image date (in local time)')
})
else:
print("%s file already exists." % (FITS_NAME))
def matchCatalogsByGrmatchPoints(self, refCatFile, pmCatFile, outFile):
'''
Match reference catalog with sextractor's .cat file by frame xy points
'''
# 1. convert refCat to fits format
refFitsFile = refCatFile + '.fits'
table = Table.read(refCatFile, format='ascii')
if not exists(refFitsFile):
table.write(refFitsFile)
# 2. calculate ref objects' frame xy points
wcsFile = pmCatFile.replace('.cat', '.wcs')
axyFile = pmCatFile.replace('.cat', '.ref.axy')
invoke("wcs-rd2xy -w %s -i %s -o %s -R RA_DEG -D DEC_DEG" %
(wcsFile, refFitsFile, axyFile)) # -f option need argument
remove(refFitsFile)
# 3. merge frame xy point to refCat
tlen = len(table)
table['X'] = [0.0] * tlen
table['Y'] = [0.0] * tlen
table['ID'] = [0] * tlen
table['ROLE_'] = ['AA'] * tlen
f = fits.open(axyFile)
d = f[1].data
for j in range(tlen):
x, y = d[j]
table[j]['X'] = x
table[j]['Y'] = y
# 4. match refCat with sextractor's cat by frame xy points
idFile = pmCatFile + ".idmatch"
result = invoke(
"grmatch -r %s -i %s --match-coord --col-ref 4,6 --col-inp 14,15 --output-id %s --col-ref-id 1 --col-inp-id 1"
% (refCatFile, pmCatFile, idFile))
# get image size
astFile = pmCatFile.replace('.cat', '.ast.fits')
im_x, im_y = self.readFrameSize(astFile)
idTable = Table.read(idFile, format='ascii')
pmTable = Table.read(pmCatFile, format='ascii')
hmgs = self.hmg(pmTable)
print("Instumental HMG: HMG_ISOCORR = %8.4f, HMG_BEST = %8.4f" %
(hmgs[0], hmgs[1]))
for j in range(tlen):
onFrameStatus = self.determineOnFrameStatus(
table[j]['X'], table[j]['Y'], im_x, im_y)
matched = False
for k in range(len(idTable)):
if table[j]['AUID'] == idTable[k][0]:
table[j]['ID'] = int(idTable[k][1])
matched = True
break
pmid = int(table[j]['ID'])
d = -1.0
if id != 0:
pmrow = pmTable[pmid - 1]
dx = pmrow['XWIN_IMAGE'] - table[j]['X']
dy = pmrow['YWIN_IMAGE'] - table[j]['Y']
d = sqrt(dx * dx + dy * dy)
if onFrameStatus == '' and matched:
# print('AUID: %s, ID:%d, d:%f, OK, on-frame and mathed' % (table[j]['AUID'], pmid, d))
if d > 2.0:
print('AUID: %s, ID:%d, d:%f, OK, on-frame and mathed' %
(table[j]['AUID'], pmid, d))
print(' and too large distance')
table[j]['ROLE_'] = table[j]['ROLE'] + 'F'
if table[j]['ROLE'] == 'V' and float(
pmrow['MAG_BEST']) > hmgs[1]:
if d <= 2.0:
print('AUID: %s, ID:%d, OK, on-frame and mathed' %
(table[j]['AUID'], pmid))
print(' and under limit, mi:%7.3f, hmg:%7.3f' %
(float(pmrow['MAG_BEST']), hmgs[1]))
table[j]['ROLE_'] = table[j]['ROLE'] + 'F'
elif d <= 2.0:
table[j]['ROLE_'] = table[j]['ROLE']
elif onFrameStatus == 'B' and matched:
table[j]['ROLE_'] = table[j]['ROLE'] + 'B'
print('AUID: %s, ID:%d, d:%f, OK, on-frame-border and mathed' %
(table[j]['AUID'], pmid, d))
if d > 2.0:
print(' and too large distance')
table[j]['ROLE_'] = table[j]['ROLE'] + 'F'
if table[j]['ROLE'] == 'VB' and float(
pmrow['MAG_BEST']) > hmgs[1]:
print(' and under limit, mi:%7.3f, hmg:%7.3f' %
(float(pmrow['MAG_BEST']), hmgs[1]))
table[j]['ROLE_'] = table[j]['ROLE'] + 'F'
elif onFrameStatus == 'O' and matched:
table[j]['ROLE_'] = table[j]['ROLE'] + 'O'
print(
'AUID: %s, ID:%d, d:%f, BAD-MATCH, out-of-frame and mathed'
% (table[j]['AUID'], pmid, d))
elif onFrameStatus == '' and not matched:
table[j]['ROLE_'] = table[j]['ROLE'] + 'F'
print('AUID: %s, FAINTER, on-frame and not mathed' %
(table[j]['AUID']))
print(' and under limit, hmg:%7.3f' % (hmgs[1]))
elif onFrameStatus == 'B' and not matched:
table[j]['ROLE_'] = table[j]['ROLE'] + 'O'
print(
'AUID: %s, FAINTER-ON-BORDER, on-frame-border and not mathed'
% (table[j]['AUID']))
elif onFrameStatus == 'O' and not matched:
table[j]['ROLE_'] = table[j]['ROLE'] + 'O'
print('AUID: %s, OK, out-of-frame and not mathed' %
(table[j]['AUID']))
# save result
self.dumpResult(table, pmTable, outFile, hmgs)
def photometry(self, seqFolder, photFolder, refcatFileName, color):
# Names of the sequence/combined files:
SEQLIST = glob(seqFolder + '/' + self.pplSetup['SEQ_FILE_PREFIX'] +
'*-' + color + '.fits')
SEQLIST.sort()
if len(SEQLIST) == 0:
SEQLIST = glob(seqFolder + '/Combined-' + color + '.fits')
if len(SEQLIST) == 0:
printWarning("No files for photometry in folder %s" %
(seqFolder))
return False
for f in SEQLIST:
print("photometry of %s" % (f))
AST_FILE = photFolder + '/' + basename(f).replace(
'.fits', '.ast.fits')
PMCAT_FILE = photFolder + '/' + basename(f).replace(
'.fits', '.cat')
printInfo("Make astrometry for %s" % (f))
if not exists(AST_FILE) or self.opt['overwrite']:
print("%s/solve-field %s -D %s -N %s %s" %
(self.pplSetup['AST_BIN_FOLDER'], self.SOLVE_ARGS,
photFolder, AST_FILE, f))
invoke("%s/solve-field %s -D %s -N %s %s" %
(self.pplSetup['AST_BIN_FOLDER'], self.SOLVE_ARGS,
photFolder, AST_FILE, f))
fsolved = PMCAT_FILE.replace('.cat', '.solved')
if not exists(fsolved):
printError("Astrometry of %s failed." % (fsolved))
break
else:
print("astrometry file %s already exists." % (AST_FILE))
printInfo("Make photometry for %s" % (f))
if not exists(PMCAT_FILE) or self.opt['overwrite']:
invoke(
"sextractor %s -c %s -CATALOG_NAME %s -CATALOG_TYPE ASCII_HEAD"
% (AST_FILE, self.SEX_CFG, PMCAT_FILE))
else:
print("photometry file %s already exists." % (PMCAT_FILE))
PMCAT_FILE_FLT = PMCAT_FILE + ".cat"
printInfo("Filtering result catalog to %s" % (PMCAT_FILE_FLT))
if not exists(PMCAT_FILE_FLT) or self.opt['overwrite']:
opt = {
'ref': refcatFileName,
'out': PMCAT_FILE_FLT,
'color': color,
'files': [PMCAT_FILE],
}
matcher = CatalogMatcher(opt)
matcher.process()
else:
print("filtered photometry file %s already exists." %
(PMCAT_FILE_FLT))
return True
def removeFolder(self, subfolder):
folderPattern = '*' + self.opt['baseFolder'] + '*/' + subfolder
fs = glob(folderPattern)
printInfo("Removing folders: %s" % (folderPattern))
for f in fs:
invoke("rmdir %s" % (f))
