def mask_create(images, no_unlearn=False):
output_files = []
# If the output file list doesn't exsist, create it.
if len(output_files) == 0:
output_files = [os.path.join(os.path.dirname(i), "mask_" + os.path.basename(i)) for i in images]
# Create a temporary file to hold the input image list
tfile = tempfile.mkstemp()
os.write(tfile[0], "\n".join(images) + "\n")
os.close(tfile[0])
# Create a temporary file to hold the input image list
tofile = tempfile.mkstemp()
os.write(tfile[0], "\n".join(output_files) + "\n")
os.close(tfile[0])
try:
# Set up to call the task
iraf.set(clobber="yes")
iraf.nproto()
if no_unlearn == False:
print "Objmasks is unlearning!!"
iraf.objmasks.unlearn()
# set parameters
iraf.objmasks.images = "@" + tfile[1]
iraf.objmasks.objmasks = "@" + tofile[1]
iraf.objmasks.omtype = "boolean"
iraf.objmasks()
except iraf.IrafError, e:
print "objmasks failed"
print "error #" + str(e.errno)
print "Msg: " + e.errmsg
print "Task: " + e.errtask
raise e
def mkobjmask(inlist,
inpref='',
outpref='m',
bpm='none',
minpix=250,
hsigma=3,
lsigma=10,
conv='block 3 3'):
# load IRAF package
iraf.nproto()
# open input list and check if it exists
inimg_arr = check_input(inlist, inpref)
if isinstance(inimg_arr, int):
return 1
# check output images
outimg_arr = check_outpref(outpref, inimg_arr)
if isinstance(outimg_arr, int):
return 1
# check optional parameters
if bpm.lower() != 'none':
if not os.access(bpm, os.R_OK):
print >> sys.stderr, 'cannot read bad pixel mask (%s)' % bpm
return 1
bpmex = 1
else:
bpmex = 0
if lsigma <= 0:
print >> sy.stderr, 'invalid lsigma value (%f)' % lsigma
return 1
if hsigma <= 0:
print >> sys.stderr, 'invalid hsigma value (%f)' % hsigma
return 1
# check convolution kernel name
ret = 1
param = conv.split()
if len(param) == 1:
if os.access(param[0], os.R_OK):
conv = '@' + conv
ret = 0
else:
print >> sys.stderr, 'convolution kernel file (%s) does not exist' % param[
0]
elif param[0] == 'block' and len(param) == 3:
if param[1].isdigit() and param[2].isdigit():
ret = 0
elif param[0] == 'bilinear' and len(param) == 3:
if param[1].isdigit() and param[2].isdigit() and int(
param[1]) > 0 and int(param[2]) > 0:
ret = 0
elif param[0] == 'gauss' and len(param) == 5:
if param[1].isdigit() and param[2].isdigit() and int(
param[1]) > 0 and int(param[2]) > 0:
if isfloat(param[3]) and isfloat(
param[4]) and float(param[3]) > 0 and float(param[4]) > 0:
ret = 0
if ret > 0:
print >> sys.stderr, 'invalid convolve parameter (%s)' % conv
return 1
# prefix for temoprary images
tmp = tempfile.NamedTemporaryFile(suffix='', prefix='', dir='/tmp')
tmp_prefix = tmp.name
tmp.close()
# check if input images exist and fix bad pixel if requested
for i in range(len(inimg_arr)):
tmp_inimg = tmp_prefix + os.path.basename(inimg_arr[i])
tmp_outimg = tmp_prefix + 'mask' + os.path.basename(outimg_arr[i])
iraf.unlearn('imcopy')
iraf.imcopy(inimg_arr[i], tmp_inimg, verbose='no')
if bpmex == 1:
iraf.unlearn('fixpix')
iraf.fixpix(tmp_inimg, bpm)
iraf.fixpix(tmp_inimg, bpm)
iraf.fixpix(tmp_inimg, bpm)
iraf.unlearn('objmasks')
iraf.objmasks(tmp_inimg,
tmp_outimg,
omtype='boolean',
masks='',
convolve=conv,
lsigma=lsigma,
hsigma=hsigma,
hdetect='yes',
ldetect='yes',
minpix=minpix)
ret = []
ret = iraf.objmasks(tmp_inimg,
outimg_arr[i],
omtype='boolean',
masks=tmp_outimg + '[pl]',
convolve=conv,
lsigma=lsigma,
hsigma=hsigma,
hdetect='yes',
ldetect='yes',
minpix=minpix,
Stdout=1)
if len(ret) != 0:
iraf.unlearn('hedit')
iraf.hedit(inimg_arr[i],
'objmask',
outimg_arr[i] + '[pl]',
add='yes',
verify='no')
os.remove(tmp_inimg)
os.remove(tmp_outimg)
if len(ret) == 0:
print >> sys.stderr, 'failed to execute iraf objmasks task for %s' % inimg_arr[
i]
return 1
return 0
def mkcombmask(combimg,
inlist,
sspref='sdfr',
outpref='mc',
minpix=250,
hsigma=3,
lsigma=10,
conv='block 3 3',
bpm='none',
sigmap='none'):
# load IRAF package
iraf.nproto()
# chceck combined image
if not os.access(combimg, os.R_OK):
print >> sys.stderr, 'cannot open combined image (%s)' % combimg
return 1
# open input list and check if it exists
inimg_arr = check_input(inlist, sspref)
if isinstance(inimg_arr, int):
return 1
# check output images
outimg_arr = check_outpref(outpref, inimg_arr)
if isinstance(outimg_arr, int):
return 1
if lsigma <= 0:
print >> sy.stderr, 'invalid lsigma value (%f)' % lsigma
return 1
if hsigma <= 0:
print >> sys.stderr, 'invalid hsigma value (%f)' % hsigma
return 1
# check convolution kernel name
ret = 1
param = conv.split()
if len(param) == 1:
if os.access(param[0], os.R_OK):
conv = '@' + conv
ret = 0
else:
print >> sys.stderr, 'convolution kernel file (%s) does not exist' % param[
0]
elif param[0] == 'block' and len(param) == 3:
if param[1].isdigit() and param[2].isdigit():
ret = 0
elif param[0] == 'bilinear' and len(param) == 3:
if param[1].isdigit() and param[2].isdigit() and int(
param[1]) > 0 and int(param[2]) > 0:
ret = 0
elif param[0] == 'gauss' and len(param) == 5:
if param[1].isdigit() and param[2].isdigit() and int(
param[1]) > 0 and int(param[2]) > 0:
if isfloat(param[3]) and isfloat(
param[4]) and float(param[3]) > 0 and float(param[4]) > 0:
ret = 0
if ret > 0:
print >> sys.stderr, 'invalid convolve parameter (%s)' % conv
return 1
# check bad pixel mask
if bpm.lower() != 'none':
bpmex = 1
if os.access(bpm, os.R_OK) == False:
print >> sys.stderr, 'cannot read bad pixel mask (%s)' % bpm
return 1
else:
bpmex = 0
# prefix for temoprary images
tmp = tempfile.NamedTemporaryFile(suffix='', prefix='', dir='/tmp')
tmp_prefix = tmp.name
tmp.close()
# check sigma map
if sigmap.lower() == 'none':
tmp_sigma = ''
tmp_mask = ''
else:
if os.access(sigmap, os.R_OK) == False:
print >> sys.stderr, 'cannot read sigma map image (%s)' % sigmap
return 1
else:
tmp_mask = tmp_prefix + 'mask' + os.path.basename(sigmap)
tmp_sigma = tmp_prefix + 'sigma' + os.path.basename(sigmap)
iraf.imcopy(sigmap, tmp_sigma, verbose='no')
ret = iraf.imstat(sigmap,
nclip=50,
field='mode',
format='no',
Stdout=1)
sigma_mode = float(ret[0])
iraf.imreplace(tmp_sigma, sigma_mode, upper=0)
iraf.imarith(sigmap, '*', -1, tmp_mask, verbose='no')
iraf.imreplace(tmp_mask, 1, lower=0)
iraf.imreplace(tmp_mask, 0, upper=0)
iraf.imarith(tmp_mask, '*', -1, tmp_mask)
iraf.imarith(tmp_mask, '+', 1, tmp_mask)
#
tmp_precombmask = tmp_prefix + 'premask' + os.path.basename(combimg)
tmp_combmask = tmp_prefix + 'mask' + os.path.basename(combimg)
iraf.unlearn('objmasks')
try:
iraf.objmasks(combimg,
tmp_precombmask,
omtype='boolean',
masks='',
convolve=conv,
lsigma=lsigma,
hsigma=hsigma,
hdetect='yes',
ldetect='yes',
minpix=minpix,
sigmas=tmp_sigma)
iraf.objmasks(combimg,
tmp_combmask,
omtype='boolean',
masks=tmp_precombmask + '[pl]',
convolve=conv,
lsigma=lsigma,
hsigma=hsigma,
hdetect='yes',
ldetect='yes',
minpix=minpix,
sigmas=tmp_sigma)
os.remove(tmp_precombmask)
except:
print >> sys.stderr, 'failed to execute iraf objmasks task for %s' % combimg
remove_temp_all(tmp_prefix)
return 1
# remove the area with no sigma value
tmp_combmask2 = tmp_prefix + 'mask2' + os.path.basename(combimg)
if sigmap.lower() == 'none':
iraf.imcopy(tmp_combmask + '[pl]', tmp_combmask2, verbose='no')
else:
iraf.imarith(tmp_combmask + '[pl]',
'*',
tmp_mask,
tmp_combmask2,
verbose='no')
os.remove(tmp_combmask)
# check if input images exist and fix bad pixel if requested
iraf.unlearn('imcopy')
iraf.unlearn('imshift')
for i in range(len(inimg_arr)):
# get offset values from header
im = pyfits.open(inimg_arr[i])
try:
dx = float(im[0].header['dx'])
dy = float(im[0].header['dy'])
dxc = float(im[0].header['dxc'])
dyc = float(im[0].header['dyc'])
nx = int(im[0].header['NAXIS1'])
ny = int(im[0].header['NAXIS2'])
except:
print >> sys.stderr, 'failed to get offset values from the header of %s' % inimg_arr[
i]
remove_temp_all(tmp_prefix)
return 1
im.close()
# shift combined mask
tmp_shiftimg = tmp_prefix + os.path.basename(outimg_arr[i])
iraf.imshift(tmp_combmask2,
tmp_shiftimg,
dxc,
dyc,
boundary_typ='constant',
constant=0.0)
tmp_shiftimg_reg = '%s[1:%d,1:%d]' % (tmp_shiftimg, nx, ny)
#iraf.imcopy(tmp_shiftimg_reg, outimg_arr[i]+'[pl]',verbose='no')
iraf.imcopy(tmp_shiftimg_reg, outimg_arr[i], verbose='no')
if bpmex == 1:
iraf.imarith(outimg_arr[i], '+', bpm, outimg_arr[i], verbose='no')
convert_maskfits_int(outimg_arr[i], outimg_arr[i])
os.remove(tmp_shiftimg)
# remove all temporary files
remove_temp_all(tmp_prefix)
return 0
def mkskyflat_with_mask(inlist,
output,
inpref='',
mskpref='m',
bpm='none',
iternum=50,
nsigma=3):
# load IRAF package
iraf.proto()
iraf.nproto()
# open input list and check if it exists
inimg_arr = check_input(inlist, inpref)
if len(inimg_arr) == 1 and inimg_arr[0] == 1:
return 1
# check if output image is already exist
if os.access(output, os.R_OK):
print >> sys.stderr, 'operation would overwrite existing file (%s)' % output
return 1
# check mask images
if mskpref.lower() == 'none' or mskpref == '':
print >> sys.stderr, 'mask frames are required for this task'
return 1
else:
mskimg_arr = check_inpref(mskpref, inimg_arr)
if isinstance(mskimg_arr, int):
return 1
# check optional parameters
if bpm.lower() == 'none' or bpm == '':
bpmex = 0
else:
bpmex = 1
if not os.access(bpm, os.R_OK):
print >> sys.stderr, 'cannot read bad pixel mask (%s)' % bpm
return 1
if iternum <= 0:
print >> sys.stderr, 'invalid iternum value (%d)' % iternum
return 1
if nsigma <= 0:
print >> sys.stderr, 'invalid nsigma value (%f)' % nsigma
return 1
# prefix for temoprary images
tmp = tempfile.NamedTemporaryFile(suffix='', prefix='', dir='/tmp')
tmp_prefix = tmp.name
tmp.close()
# nomalize by object masked average
tmp_list = tmp_prefix + '.lst'
fout = open(tmp_list, 'w')
for i in range(len(inimg_arr)):
im = pyfits.open(inimg_arr[i], mode='update')
try:
pattern = im[0].header['PATTERN']
except KeyError:
pattern = 0
im.close()
if pattern == 0:
tmpimg = tmp_prefix + os.path.basename(inimg_arr[i])
maskimg = mskimg_arr[i]
tmpmask = tmp_prefix + maskimg
fout.write('%s\n' % tmpimg)
if os.access(tmpimg, os.R_OK):
os.remove(tmpimg)
if os.access(tmpmask, os.R_OK):
os.remove(tmpmask)
if bpmex == 1:
iraf.unlearn('imarith')
#iraf.imarith(maskimg+'[pl]','+',bpm,tmpmask,verbose='no')
iraf.imarith(maskimg, '+', bpm, tmpmask, verbose='no')
else:
iraf.unlearn('imcopy')
#iraf.imcopy(maskimg+'[pl]',tmpmask,verbose='no')
iraf.imcopy(maskimg, tmpmask, verbose='no')
iraf.unlearn('mimstat')
res = iraf.mimstat(inimg_arr[i],
imasks=tmpmask,
format='no',
fields='mean',
nclip=iternum,
lsigma=nsigma,
usigma=nsigma,
Stdout=1)
if len(res) == 1:
ave = float(res[0])
else:
print >> sys.stderr, 'failed to calculate masked avarage from the frame (%s)' % inimg_arr[
i]
remove_temp_all(tmp_prefix)
return 1
# normalize each frame by average
iraf.unlearn('imarith')
iraf.imarith(inimg_arr[i], '/', ave, tmpimg, verbose='no')
# add mask into header
iraf.unlearn('hedit')
if mskpref[0] != ':':
iraf.hedit(tmpimg, 'objmask', maskimg, add='yes', verify='no')
# close output file handler
fout.close()
# combine
ret = zcombine(tmp_list,
output,
combine='median',
reject='sigclip',
masktype='!objmask')
if ret != 0:
print >> sys.stderr, 'failed to combine normalized frames'
remove_temp_all(tmp_prefix)
return 1
# remove temoprary files
remove_temp_all(tmp_prefix)
return 0
def makefringingmask(listimg, _output, _interactive, _combine='average', _rejection='avsigclip'):
# print "LOGX:: Entering `makefringingmask` method/function in
# %(__file__)s" % globals()
import ntt
from ntt.util import readhdr, readkey3, delete, updateheader
import glob
import os
import sys
import re
import string
from pyraf import iraf
iraf.noao(_doprint=0)
iraf.immatch(_doprint=0)
iraf.imutil(_doprint=0)
iraf.nproto(_doprint=0)
iraf.proto(_doprint=0)
toforget = ['nproto.objmasks', 'proto.fixpix']
for t in toforget:
iraf.unlearn(t)
if _interactive == True:
listimg2 = []
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
if float(_exptime) >= 10:
answ = 'xxx'
while answ.lower() not in ['y', 'n', 's', 'a']:
iraf.display(img, frame=1, fill='yes')
answ = raw_input(
'use this image (yes,no,stop (not more images),all) [[y]/n/s/a] ? ')
if not answ:
answ = 'y'
if answ.lower() == 'y':
listimg2.append(img)
elif answ.lower() == 'a':
listimg2 = listimg[:]
if answ.lower() in ['a', 's']:
break
listimg = listimg2[:]
iraf.nproto.objmasks1.fitxord = 1
iraf.nproto.objmasks1.fityord = 1
hdr0 = readhdr(listimg[0])
_date = readkey3(hdr0, 'date-obs')
_filter = readkey3(hdr0, 'filter')
_exptime = readkey3(hdr0, 'exptime')
_instrume = readkey3(hdr0, 'instrume')
_ron = readkey3(hdr0, 'ron')
_gain = readkey3(hdr0, 'gain')
badpixelmask = 'bad_pixel_mask.pl'
if not os.path.isfile(badpixelmask):
os.system('cp ' + ntt.__path__[0] + '/archive/' + _instrume +
'/badpixels/badpixel_20100210.pl ' + badpixelmask)
ff = open('_listmask', 'w')
hh = open('_listobgz', 'w')
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
hh.write('z_' + img + '\n')
ff.write('mask_' + img + '\n')
delete('mask_' + img)
aaa = iraf.hedit(img, delete='yes', field='OBJMASK',
up='yes', verify='no', Stdout=1)
aaa = iraf.hedit(img, delete='yes', field='BPM',
up='yes', verify='no', Stdout=1)
delete('z_' + img)
iraf.imutil.imexpr(expr='(a - median(a))/' + str(_exptime),
a=img, output='z_' + img, verbose='no')
ntt.util.updateheader('z_' + img, 0, {'EXPTIME': [1, '']})
ff.close()
hh.close()
if not _output:
_output = 'fringing_' + str(_date) + '_' + str(_filter) + '.fits'
delete(_output)
print ' making mask for each frame .......'
ccc = iraf.nproto.objmasks(images='@_listobgz', objmasks='@_listmask', omtype='boolean',
blksize=-16, convolv='block 3 3', hsigma=5, lsigma=3, minpix=10, ngrow=2, agrow=4., Stdout=1)
print 'combining all frames, masking the objects .....'
iraf.imcombine('@_listobgz', output=_output, masktyp='!OBJMASK', maskval=0, combine=_combine, reject=_rejection,
scale='none', statsec='[100:800,100:800]', rdnoise='', gain='', nlow=1, nhigh=1, logfile='imcombinelog')
ntt.util.phase3header(_output)
ntt.util.updateheader(
_output, 0, {'BUNIT': ['ADU', 'pixel units(ADU,electrons)']})
ntt.util.updateheader(_output, 0, {'FILETYPE': [11231, 'fringing frame']})
return _output
def makefringing(listimg, _output, _xorder, _yorder, _interactive, combine='average', rejection='avsigclip'):
# print "LOGX:: Entering `makefringing` method/function in %(__file__)s" %
# globals()
import os
import string
import re
import ntt
from ntt.util import readhdr, readkey3, delete, updateheader
from pyraf import iraf
from pyfits import open as popen
from numpy import median, where, mean
iraf.noao(_doprint=0)
iraf.nproto(_doprint=0)
if _interactive == True:
listimg2 = []
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
if float(_exptime) >= 100:
answ = 'xxx'
while answ.lower() not in ['y', 'n', 's', 'a']:
iraf.display(img, frame=1, fill='yes')
answ = raw_input(
'use this image (yes,no,stop (not more images),all) [[y]/n/s/a] ? ')
if not answ:
answ = 'y'
if answ.lower() == 'y':
listimg2.append(img)
elif answ.lower() == 'a':
listimg2 = listimg[:]
if answ.lower() in ['a', 's']:
break
listimg = listimg2[:]
iraf.nproto.objmasks1.fitxord = 1
iraf.nproto.objmasks1.fityord = 1
listmask = []
ff = open('_listmask', 'w')
gg = open('_listobg', 'w')
hh = open('_listobgz', 'w')
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
gg.write(img + '\n')
hh.write('z_' + img + '\n')
ff.write('mask_' + img + '\n')
listmask.append('mask_' + img)
os.system('rm -rf mask_' + img)
os.system('rm -rf t_' + img)
os.system('rm -rf z_' + img)
iraf.imsurfit(img, 't_' + img, xorder=_xorder,
yorder=_yorder, type_ou='residual', regions='all')
iraf.imarith('t_' + img, '/', _exptime, 'z_' + img)
os.system('rm -rf t_' + img)
gg.close()
ff.close()
hh.close()
os.system('rm ' + _output)
iraf.objmasks(images='@_listobgz', objmasks='@_listmask', omtype='boolean',
blksize=-16, convolv='block 3 3', hsigma=5, lsigma=3, minpix=10, ngrow=2, agrow=4.)
iraf.imcombine('@_listobgz', output=_output, masktyp='!OBJMASK', maskval=0, combine=_combine, reject=_rejection,
scale='none', statsec='[100:800,100:800]', offsets='', rdnoise='', gain='', nlow=1, nhigh=1, logfile='imcombinelog')
for img in listimg:
os.system('rm -rf mask_' + img)
os.system('rm -rf z_' + img)
os.system('rm _listmask')
os.system('rm _listobg')
iraf.display(_output, frame=2, fill='yes')
def makefringing(listimg,
_output,
_xorder,
_yorder,
_interactive,
combine='average',
rejection='avsigclip'):
# print "LOGX:: Entering `makefringing` method/function in %(__file__)s" %
# globals()
import os
import string
import re
import ntt
from ntt.util import readhdr, readkey3, delete, updateheader
from pyraf import iraf
from pyfits import open as popen
from numpy import median, where, mean
iraf.noao(_doprint=0)
iraf.nproto(_doprint=0)
if _interactive == True:
listimg2 = []
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
if float(_exptime) >= 100:
answ = 'xxx'
while answ.lower() not in ['y', 'n', 's', 'a']:
iraf.display(img, frame=1, fill='yes')
answ = raw_input(
'use this image (yes,no,stop (not more images),all) [[y]/n/s/a] ? '
)
if not answ:
answ = 'y'
if answ.lower() == 'y':
listimg2.append(img)
elif answ.lower() == 'a':
listimg2 = listimg[:]
if answ.lower() in ['a', 's']:
break
listimg = listimg2[:]
iraf.nproto.objmasks1.fitxord = 1
iraf.nproto.objmasks1.fityord = 1
listmask = []
ff = open('_listmask', 'w')
gg = open('_listobg', 'w')
hh = open('_listobgz', 'w')
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
gg.write(img + '\n')
hh.write('z_' + img + '\n')
ff.write('mask_' + img + '\n')
listmask.append('mask_' + img)
os.system('rm -rf mask_' + img)
os.system('rm -rf t_' + img)
os.system('rm -rf z_' + img)
iraf.imsurfit(img,
't_' + img,
xorder=_xorder,
yorder=_yorder,
type_ou='residual',
regions='all')
iraf.imarith('t_' + img, '/', _exptime, 'z_' + img)
os.system('rm -rf t_' + img)
gg.close()
ff.close()
hh.close()
os.system('rm ' + _output)
iraf.objmasks(images='@_listobgz',
objmasks='@_listmask',
omtype='boolean',
blksize=-16,
convolv='block 3 3',
hsigma=5,
lsigma=3,
minpix=10,
ngrow=2,
agrow=4.)
iraf.imcombine('@_listobgz',
output=_output,
masktyp='!OBJMASK',
maskval=0,
combine=_combine,
reject=_rejection,
scale='none',
statsec='[100:800,100:800]',
offsets='',
rdnoise='',
gain='',
nlow=1,
nhigh=1,
logfile='imcombinelog')
for img in listimg:
os.system('rm -rf mask_' + img)
os.system('rm -rf z_' + img)
os.system('rm _listmask')
os.system('rm _listobg')
iraf.display(_output, frame=2, fill='yes')
def makefringingmask(listimg,
_output,
_interactive,
_combine='average',
_rejection='avsigclip'):
# print "LOGX:: Entering `makefringingmask` method/function in
# %(__file__)s" % globals()
import ntt
from ntt.util import readhdr, readkey3, delete, updateheader
import glob
import os
import sys
import re
import string
from pyraf import iraf
iraf.noao(_doprint=0)
iraf.immatch(_doprint=0)
iraf.imutil(_doprint=0)
iraf.nproto(_doprint=0)
iraf.proto(_doprint=0)
toforget = ['nproto.objmasks', 'proto.fixpix']
for t in toforget:
iraf.unlearn(t)
if _interactive == True:
listimg2 = []
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
if float(_exptime) >= 10:
answ = 'xxx'
while answ.lower() not in ['y', 'n', 's', 'a']:
iraf.display(img, frame=1, fill='yes')
answ = raw_input(
'use this image (yes,no,stop (not more images),all) [[y]/n/s/a] ? '
)
if not answ:
answ = 'y'
if answ.lower() == 'y':
listimg2.append(img)
elif answ.lower() == 'a':
listimg2 = listimg[:]
if answ.lower() in ['a', 's']:
break
listimg = listimg2[:]
iraf.nproto.objmasks1.fitxord = 1
iraf.nproto.objmasks1.fityord = 1
hdr0 = readhdr(listimg[0])
_date = readkey3(hdr0, 'date-obs')
_filter = readkey3(hdr0, 'filter')
_exptime = readkey3(hdr0, 'exptime')
_instrume = readkey3(hdr0, 'instrume')
_ron = readkey3(hdr0, 'ron')
_gain = readkey3(hdr0, 'gain')
badpixelmask = 'bad_pixel_mask.pl'
if not os.path.isfile(badpixelmask):
os.system('cp ' + ntt.__path__[0] + '/archive/' + _instrume +
'/badpixels/badpixel_20100210.pl ' + badpixelmask)
ff = open('_listmask', 'w')
hh = open('_listobgz', 'w')
for img in listimg:
_exptime = readkey3(readhdr(img), 'exptime')
hh.write('z_' + img + '\n')
ff.write('mask_' + img + '\n')
delete('mask_' + img)
aaa = iraf.hedit(img,
delete='yes',
field='OBJMASK',
up='yes',
verify='no',
Stdout=1)
aaa = iraf.hedit(img,
delete='yes',
field='BPM',
up='yes',
verify='no',
Stdout=1)
delete('z_' + img)
iraf.imutil.imexpr(expr='(a - median(a))/' + str(_exptime),
a=img,
output='z_' + img,
verbose='no')
ntt.util.updateheader('z_' + img, 0, {'EXPTIME': [1, '']})
ff.close()
hh.close()
if not _output:
_output = 'fringing_' + str(_date) + '_' + str(_filter) + '.fits'
delete(_output)
print ' making mask for each frame .......'
ccc = iraf.nproto.objmasks(images='@_listobgz',
objmasks='@_listmask',
omtype='boolean',
blksize=-16,
convolv='block 3 3',
hsigma=5,
lsigma=3,
minpix=10,
ngrow=2,
agrow=4.,
Stdout=1)
print 'combining all frames, masking the objects .....'
iraf.imcombine('@_listobgz',
output=_output,
masktyp='!OBJMASK',
maskval=0,
combine=_combine,
reject=_rejection,
scale='none',
statsec='[100:800,100:800]',
rdnoise='',
gain='',
nlow=1,
nhigh=1,
logfile='imcombinelog')
ntt.util.phase3header(_output)
ntt.util.updateheader(_output, 0,
{'BUNIT': ['ADU', 'pixel units(ADU,electrons)']})
ntt.util.updateheader(_output, 0, {'FILETYPE': [11231, 'fringing frame']})
return _output
def mkskyflat(inlist, output, inpref='', mskpref='m', bpm='none', iternum=50, nsigma=3, minpix=250, hsigma=3, lsigma=10, conv='block 3 3'):
# load IRAF package
iraf.proto()
iraf.nproto()
# open input list and check if it exists
inimg_arr = check_input(inlist, inpref)
if len(inimg_arr) == 1 and inimg_arr[0] == 1:
return 1
# check if output image is already exist
if os.access(output, os.R_OK) :
print >> sys.stderr, 'operation would overwrite existing file (%s)' % output
return 1
# check optional parameters
if bpm.lower() == 'none' or bpm == '':
bpmex = 0
else:
bpmex = 1
if not os.access(bpm, os.R_OK):
print >> sys.stderr, 'cannot read bad pixel mask (%s)' % bpm
return 1
if iternum <= 0:
print >> sys.stderr, 'invalid iternum value (%d)' % iternum
return 1
if nsigma <= 0:
print >> sys.stderr, 'invalid nsigma value (%f)' % nsigma
return 1
# prefix for temoprary images
tmp = tempfile.NamedTemporaryFile(suffix='', prefix='', dir='/tmp')
tmp_prefix = tmp.name
tmp.close()
# temporary normalize raw frames by average
tmp_list = tmp_prefix+'.lst'
fout = open(tmp_list, 'w')
for i in range(len(inimg_arr)):
tmpimg = tmp_prefix+os.path.basename(inimg_arr[i])
fout.write('%s\n' % tmpimg)
# remove temporary files if it exists
if os.access(tmpimg, os.R_OK):
os.remove(tmpimg)
# calculate average counts in each frame
if bpmex == 0:
iraf.unlearn('imstat')
res = iraf.imstat(inimg_arr[i], format='no', fields='mean', nclip=iternum, lsigma=nsigma, usigma=nsigma, Stdout=1)
if len(res) == 1:
ave = float(res[0])
else:
print >> sys.stderr, 'failed to calculate avarage from the frame (%s)' % inimg
remove_temp_all(tmp_prefix)
fout.close()
return 1
else:
iraf.unlearn('mimstat')
res = iraf.mimstat(inimg_arr[i], imasks=bpm, format='no', fields='mean', nclip=iternum, lsigma=nsigma, usigma=nsigma, Stdout=1)
if len(res) == 1:
ave = float(res[0])
else:
print >> sys.stderr, 'failed to calculate masked avarage from the frame (%s)'% inimg
remove_temp_all(tmp_prefix)
fout.close()
return 1
# normalize each frame by average
iraf.unlearn('imarith')
iraf.imarith(inimg_arr[i], '/', ave, tmpimg, verbose='no')
# close output file handler
fout.close()
# make temporary sky flat frame
tmp_flat = tmp_prefix+'_sflat.fits'
ret = zcombine(tmp_list, tmp_flat, combine='median', reject='sigclip')
if ret != 0:
remove_temp_all(tmp_prefix)
return 1
# temporary flat field
iraf.unlearn('imarith')
tmpff_list = tmp_prefix+'_ff.lst'
fout = open(tmpff_list, 'w')
for i in range(len(inimg_arr)):
tmpimg = tmp_prefix+'_ff_'+os.path.basename(inimg_arr[i])
fout.write('%s\n' % tmpimg)
# remove temporary files if it exists
if os.access(tmpimg, os.R_OK):
os.remove(tmpimg)
# divided by temporary flat
iraf.imarith(inimg_arr[i], '/', tmp_flat, tmpimg, verbose='no')
# read image fits header
im = pyfits.open(inimg_arr[i])
exptime = float(im[0].header['EXP1TIME'])
coadds = int(im[0].header['COADDS'])
ndr = int(im[0].header['NDR'])
im.close()
# normalize by coadds, ndr, and exptime values
iraf.imarith(tmpimg, '/', (coadds*ndr*exptime), tmpimg, verbose='no')
# close output file handler
fout.close()
# remove temporary flat
os.remove(tmp_flat)
# calculate standard deviation of the temporary flat divided images
try:
iraf.unlearn('imstat')
stddev = iraf.imstat('@'+tmpff_list, format='no', fields='stddev', nclip=50, Stdout=1)
except:
remove_temp_all(tmp_prefix)
return 1
# calculate mean and sigma of the stddev of the image
y = map(float, stddev)
mean, sigma = meanclip(np.array(y, dtype=float))
#print mean, sigma
# flag bad frames
frame_flag = []
for i in range(len(stddev)):
im = pyfits.open(inimg_arr[i], mode='update')
if math.fabs(y[i] - mean) < nsigma * sigma:
frame_flag.append(0)
im[0].header['PATTERN'] = 0
else:
frame_flag.append(1)
im[0].header['PATTERN'] = 1
im.close()
# make object mask
ret = mkobjmask(tmpff_list, inpref='', outpref=mskpref, bpm=bpm, minpix=minpix, hsigma=hsigma, lsigma=lsigma, conv=conv)
# rename mask file
mskimg_arr = []
for i in range(len(inimg_arr)):
base = os.path.basename(inimg_arr[i])
tmpimg = tmp_prefix+'_ff_'+base
maskimg = mskpref+base
tmpmask = mskpref+os.path.basename(tmpimg)
move(tmpmask, maskimg)
mskimg_arr.append(maskimg)
# delete temporary flat fielded files
remove_temp_all(tmp_prefix)
# check mkobjmask result
if ret != 0:
return 1
# nomalize by object masked average
fout = open(tmp_list, 'w')
for i in range(len(inimg_arr)):
if frame_flag[i] == 0:
tmpimg = tmp_prefix+os.path.basename(inimg_arr[i])
maskimg = mskimg_arr[i]
tmpmask = tmp_prefix+maskimg
fout.write('%s\n' % tmpimg)
if os.access(tmpimg, os.R_OK):
os.remove(tmpimg)
if os.access(tmpmask, os.R_OK):
os.remove(tmpmask)
if bpmex == 1:
iraf.unlearn('imarith')
iraf.imarith(maskimg+'[pl]','+',bpm,tmpmask,verbose='no')
else :
iraf.unlearn('imcopy')
iraf.imcopy(maskimg+'[pl]',tmpmask,verbose='no')
iraf.unlearn('mimstat')
# calculate average of the raw images with mask
res = iraf.mimstat(inimg_arr[i], imasks=tmpmask, format='no', fields='mean', nclip=iternum, lsigma=nsigma, usigma=nsigma, Stdout=1)
if len(res) == 1:
ave = float(res[0])
else:
print >> sys.stderr, 'failed to calculate masked avarage from the frame (%s)' % inimg_arr[i]
remove_temp_all(tmp_prefix)
return 1
# normalize each frame by average
iraf.unlearn('imarith')
iraf.imarith(inimg_arr[i], '/', ave, tmpimg, verbose='no')
# add mask into header
iraf.unlearn('hedit')
iraf.hedit(tmpimg, 'objmask', maskimg+'[pl]', add='yes', verify='no')
# close output file handler
fout.close()
# combine
ret = zcombine(tmp_list, output, combine='median', reject='sigclip', masktype='!objmask')
if ret != 0:
print >> sys.stderr, 'failed to combine normalized frames'
remove_temp_all(tmp_prefix)
return 1
# remove temoprary files
remove_temp_all(tmp_prefix)
return 0
def fringing2(img, fmask, _interactive, _verbose=False):
# print "LOGX:: Entering `fringing2` method/function in %(__file__)s" %
# globals()
from ntt.util import delete, display_image, updateheader, readhdr, readkey3
from ntt.efoscphotredudef import searchfringe
import datetime
MJDtoday = 55927 + (datetime.date.today() - datetime.date(2012, 01, 01)).days
import ntt
import os
import string
import re
from numpy import median, where
from pyraf import iraf
iraf.nproto(_doprint=0)
iraf.unlearn('nproto.objmasks')
if _verbose:
ver = 'yes'
else:
ver = 'no'
hdr = readhdr(img)
_filter = readkey3(hdr, 'filter')
_exptime = readkey3(hdr, 'exptime')
_date = readkey3(hdr, 'date-night')
imgout = img
maskname = ''
if not readkey3(hdr, 'FRICOR'):
if fmask:
fmask = searchfringe(img, fmask)[0]
if fmask:
print '###### use fringing mask from user ' + fmask
else:
fmask = searchfringe(img, '')[0]
if fmask:
print '###### use fringing mask from archive ' + fmask
if fmask:
imgout = re.sub('.fits', '_fr.fits', img)
_trim = readkey3(hdr, 'TRIM')
_trimmask = readkey3(readhdr(fmask), 'TRIM')
maskname = 'fmask_' + str(_date) + '_' + \
_filter + '_' + str(MJDtoday) + '.fits'
delete(maskname)
if _trim and not _trimmask:
_trim = '[' + string.split(_trim, '[')[1]
iraf.ccdred.ccdproc(fmask, output=maskname, overscan="no", trim="yes", zerocor="no",
trimsec=_trim, flatcor="no", zero="", Stdout=1)
elif _trim and _trimmask:
if _trim == _trimmask:
os.system('cp ' + str(fmask) + ' ' + str(maskname))
else:
sys.exit('ERROR: fringing correction can be applied only to UNTRIMMED images or '
'images with this trim ' + str(_trimmask))
elif not _trim and _trimmask:
sys.exit(
'ERROR: image is not trimmed while selected fringing mask is trimmed: ' + str(_trimmask))
else:
os.system('cp ' + str(fmask) + ' ' + str(maskname))
iraf.nproto.objmasks1.fitxord = 1
iraf.nproto.objmasks1.fityord = 1
delete('mask_' + img)
imgcut = re.sub('.fits', '', img)
xxx = iraf.nproto.objmasks(images=imgcut, objmasks='mask_' + img, omtype='boolean',
blksize=-16, convolv='block 3 3', hsigma=5, lsigma=3, minpix=10, ngrow=2,
agrow=4., Stdout=1)
matimg = pyfits.open(img)[0].data
matmask = pyfits.open('mask_' + img)[1].data
matfrin = pyfits.open(maskname)[0].data
indices = where(matmask < 1)
scalevalue = median(
(matimg[indices] - median(matimg[indices])) / (matfrin[indices] - median(matfrin)))
delete(imgout)
iraf.imutil.imexpr(expr='a - (' + str(scalevalue) + '* (b - ' + str(median(matfrin)) + ') )', a=img,
b=maskname, output=imgout, verbose='no')
print '\n### fringing correction ..... done'
iraf.hedit(images=imgout, fields='OBJMASK', value='',
delete='yes', update='yes', verify='no')
ntt.util.updateheader(imgout, 0, {
'FRICOR': [str(scalevalue) + ' * (' + str(maskname) + ' - ' + str(median(matfrin)) + ')', '']})
ntt.util.updateheader(
imgout, 0, {'FILETYPE': [12205, 'pre-reduced image fringing corrected']})
ntt.util.updateheader(imgout, 0, {'PROV1': [readkey3(
readhdr(imgout), 'ARCFILE'), 'Originating file']})
ntt.util.updateheader(
imgout, 0, {'TRACE1': [img, 'Originating file']})
stringa = '%7.7s * (fmask_%8s.fits - %5.5s )' % (
str(scalevalue), _date, str(median(matfrin)))
else:
print '\n### fringing mask not available for this filter'
else:
print '\n### fringing correction already applyed to this image'
return imgout, maskname
def mkskyflat_quick(inlist,
output,
inpref='',
bpm='none',
iternum=50,
nsigma=3):
# load IRAF package
iraf.proto()
iraf.nproto()
# open input list and check if it exists
inimg_arr = check_input(inlist, inpref)
if len(inimg_arr) == 1 and inimg_arr[0] == 1:
return 1
# check if output image is already exist
if os.access(output, os.R_OK):
print >> sys.stderr, 'operation would overwrite existing file (%s)' % output
return 1
# check optional parameters
if bpm.lower() == 'none' or bpm == '':
bpmex = 0
else:
bpmex = 1
if not os.access(bpm, os.R_OK):
print >> sys.stderr, 'cannot read bad pixel mask (%s)' % bpm
return 1
if iternum <= 0:
print >> sys.stderr, 'invalid iternum value (%d)' % iternum
return 1
if nsigma <= 0:
print >> sys.stderr, 'invalid nsigma value (%f)' % nsigma
return 1
# prefix for temoprary images
tmp = tempfile.NamedTemporaryFile(suffix='', prefix='', dir='/tmp')
tmp_prefix = tmp.name
tmp.close()
# temporary normalize raw frames by average
tmp_list = tmp_prefix + '.lst'
fout = open(tmp_list, 'w')
for i in range(len(inimg_arr)):
tmpimg = tmp_prefix + os.path.basename(inimg_arr[i])
fout.write('%s\n' % tmpimg)
# remove temporary files if it exists
if os.access(tmpimg, os.R_OK):
os.remove(tmpimg)
# calculate average counts in each frame
if bpmex == 0:
iraf.unlearn('imstat')
res = iraf.imstat(inimg_arr[i],
format='no',
fields='mean',
nclip=iternum,
lsigma=nsigma,
usigma=nsigma,
Stdout=1)
if len(res) == 1:
ave = float(res[0])
else:
print >> sys.stderr, 'failed to calculate avarage from the frame (%s)' % inimg
remove_temp_all(tmp_prefix)
fout.close()
return 1
else:
iraf.unlearn('mimstat')
res = iraf.mimstat(inimg_arr[i],
imasks=bpm,
format='no',
fields='mean',
nclip=iternum,
lsigma=nsigma,
usigma=nsigma,
Stdout=1)
if len(res) == 1:
ave = float(res[0])
else:
print >> sys.stderr, 'failed to calculate masked avarage from the frame (%s)' % inimg
remove_temp_all(tmp_prefix)
fout.close()
return 1
# normalize each frame by average
iraf.unlearn('imarith')
iraf.imarith(inimg_arr[i], '/', ave, tmpimg, verbose='no')
# close output file handler
fout.close()
# make temporary sky flat frame
tmp_flat = tmp_prefix + '_sflat.fits'
ret = zcombine(tmp_list, output, combine='median', reject='sigclip')
if ret != 0:
remove_temp_all(tmp_prefix)
return 1
# remove temoprary files
remove_temp_all(tmp_prefix)
return 0