def sloanimage(img, survey='sloan', frames=[], show=False, force=False):
import sys
from lsc import readhdr, readkey3, deg2HMS, display_image
if show:
display_image(img, 1, True, '', '')
hdr = readhdr(img)
_ra = readkey3(hdr, 'RA')
_dec = readkey3(hdr, 'DEC')
_object = readkey3(hdr, 'object')
_instrume = readkey3(hdr, 'instrume')
_filter = readkey3(hdr, 'filter')
_radius = 1100
filt = {'up': 'u', 'gp': 'g', 'rp': 'r', 'ip': 'i', 'zs': 'z'}
if _filter in filt.keys():
_band = filt[_filter]
else:
_band = _filter
if 'fs' in _instrume:
_telescope = 'spectral'
elif 'fl' in _instrume:
_telescope = 'sinistro'
elif 'kb' in _instrume:
_telescope = 'sbig'
print _ra, _dec, _band, _radius
if survey == 'sloan':
frames = downloadsdss(_ra, _dec, _band, _radius, force)
elif survey == 'ps1':
if len(frames) == 0:
delta = 0.22
DR = delta / np.cos(_dec * np.pi / 180)
DD = delta
f = open(_object + '_' + _band + '_ps1request.txt', 'w')
f.write('%s %s %s\n' % (str(_ra), str(_dec), str(_band)))
f.write('%s %s %s\n' %
(str(_ra + DR), str(_dec + DD), str(_band)))
f.write('%s %s %s\n' %
(str(_ra - DR), str(_dec - DD), str(_band)))
f.write('%s %s %s\n' %
(str(_ra + DR), str(_dec - DD), str(_band)))
f.write('%s %s %s\n' %
(str(_ra - DR), str(_dec + DD), str(_band)))
f.close()
print '#' * 20
print "Please submit file:" + _object + '_' + _band + '_ps1request at this link (you need an account)\n'
print " http://psps.ifa.hawaii.edu/PSI/postage_stamp.php "
print " select:\n Survey ID: 3PI 3PI.PV3 \n "
print " Image Type: Total Stacked Image, 1 pixel 0.250 "
print " Method of Image Selection by: Coordinate- Images are selected based on supplied Ra and DEC "
print " Size of the Postage Stamp: (x) Arc-Second Width: 2000 Height: 2000 pixel"
print " Center Coordinate of Image - Input coordinate From: "
print " (x) Upload File "
print " Choose File: " + _object + '_' + _band + '_ps1request.txt'
print '#' * 20
answ = raw_input(
'Do you want to wait that the frames are downloded [y/n] [y] ? '
)
if not answ:
answ = 'y'
if answ in ['Yes', 'yes', 'Y', 'y']:
print 'Which is the last req_name at this page: '
answ1 = raw_input(
'http://psps.ifa.hawaii.edu/PSI/postage_stamp_results.php ? '
)
if not answ1:
sys.exit(
'no name provided, no PS1 images have been downloaded')
else:
print 'try download........'
frames = downloadPS1('./', answ1)
else:
frames2 = []
for img in frames:
if '_' + _band + '_' in img:
frames2.append(img)
frames = frames2
if len(frames):
out, varimg = sdss_swarp(frames,
_telescope,
_ra,
_dec,
'',
_object,
survey,
show=show)
else:
sys.exit('exit, no PS1 images have been downloaded')
return out, varimg
def sloanimage(img,survey='sloan',frames=[], show=False, force=False):
import sys
from lsc import readhdr, readkey3,deg2HMS,display_image
if show:
display_image(img,1,True,'','')
hdr = readhdr(img)
_ra = readkey3(hdr,'RA')
_dec = readkey3(hdr,'DEC')
_object = readkey3(hdr,'object')
_instrume = readkey3(hdr,'instrume')
_filter = readkey3(hdr,'filter')
_radius = 1100
filt={'up':'u','gp':'g','rp':'r','ip':'i','zs':'z'}
if _filter in filt.keys():
_band = filt[_filter]
else:
_band = _filter
if 'fs' in _instrume:
_telescope = 'spectral'
elif 'fl' in _instrume:
_telescope = 'sinistro'
elif 'fa' in _instrume:
_telescope = 'sinistro'
elif 'kb' in _instrume:
_telescope = 'sbig'
print _ra, _dec, _band, _radius
if survey == 'sloan':
frames = downloadsdss(_ra, _dec, _band, _radius, force)
elif survey == 'ps1':
if len(frames) == 0:
delta= 0.22
DR = delta/np.cos(_dec*np.pi/180)
DD = delta
f=open(_object+'_'+_band+'_ps1request.txt','w')
f.write('%s %s %s\n' %(str(_ra),str(_dec),str(_band)))
f.write('%s %s %s\n' %(str(_ra+DR),str(_dec+DD),str(_band)))
f.write('%s %s %s\n' %(str(_ra-DR),str(_dec-DD),str(_band)))
f.write('%s %s %s\n' %(str(_ra+DR),str(_dec-DD),str(_band)))
f.write('%s %s %s\n' %(str(_ra-DR),str(_dec+DD),str(_band)))
f.close()
print '#'*20
print "Please submit file:"+_object+'_'+_band+'_ps1request at this link (you need an account)\n'
print " http://psps.ifa.hawaii.edu/PSI/postage_stamp.php "
print " select:\n Survey ID: 3PI 3PI.PV3 \n "
print " Image Type: Total Stacked Image, 1 pixel 0.250 "
print " Method of Image Selection by: Coordinate- Images are selected based on supplied Ra and DEC "
print " Size of the Postage Stamp: (x) Arc-Second Width: 2000 Height: 2000 pixel"
print " Center Coordinate of Image - Input coordinate From: "
print " (x) Upload File "
print " Choose File: "+_object+'_'+_band+'_ps1request.txt'
print '#'*20
answ = raw_input('Do you want to wait that the frames are downloded [y/n] [y] ? ')
if not answ:
answ= 'y'
if answ in ['Yes','yes','Y','y']:
print 'Which is the last req_name at this page: '
answ1 = raw_input('http://psps.ifa.hawaii.edu/PSI/postage_stamp_results.php ? ' )
if not answ1:
sys.exit('no name provided, no PS1 images have been downloaded')
else:
print 'try download........'
frames = downloadPS1('./',answ1)
else:
frames2 = []
for img in frames:
if '_'+_band+'_' in img:
frames2.append(img)
frames = frames2
if len(frames):
out, varimg = sdss_swarp(frames,_telescope,_ra,_dec,'',_object, survey, show=show)
else:
sys.exit('exit, no PS1 images have been downloaded')
return out, varimg
def sdss_swarp(imglist,
_telescope='spectral',
_ra='',
_dec='',
output='',
objname='',
survey='sloan',
combine_type='MEDIAN',
show=False):
import re
import datetime
import lsc
import time
import string
if _telescope == 'spectral':
pixelscale = 0.30104 # 2 meter
_imagesize = 2020
elif _telescope == 'sbig':
pixelscale = 0.467 # 1 meter
_imagesize = 2030
elif _telescope == 'sinistro':
pixelscale = 0.387 # 1 meter
_imagesize = 4020
if survey == 'sloan':
out1 = 'SDSS'
hdr = fits.getheader(imglist[0])
_filter = hdr.get('filter')
_gain = hdr.get('gain')
_ron = hdr.get('rdnoise')
if not _ra:
_ra = hdr.get('CRVAL1')
if not _dec:
_dec = hdr.get('CRVAL2')
_saturate = hdr.get('SATURATE')
if not _saturate:
_saturate = 61000
if 'day-obs' in hdr:
_dayobs = hdr.get('day-obs')
elif 'date-obs' in hdr:
_dayobs = re.sub('-', '', hdr.get('date-obs'))
if '/' in _dayobs:
_dayobs = '19' + ''.join(string.split(_dayobs, '/')[::-1])
try:
_mjd = MJDnow(
datetime.datetime(int(str(_dayobs)[0:4]),
int(str(_dayobs)[4:6]),
int(str(_dayobs)[6:8])))
except:
print 'warning, no mjd'
_mjd = 0
_dayobs = '19991231'
elif survey == 'ps1':
out1 = 'PS1'
imglist2 = []
for i, img in enumerate(imglist):
print i, img
hdr = fits.open(img)
if os.path.isfile(re.sub('.fits', '_1.fits', img)):
os.system('rm ' + re.sub('.fits', '_1.fits', img))
fits.writeto(re.sub('.fits', '_1.fits', img), hdr[1].data,
hdr[1].header)
imglist2.append(re.sub('.fits', '_1.fits', img))
imglist = imglist2
hdr = fits.getheader(imglist[0])
_saturate = hdr.get('HIERARCH CELL.SATURATION')
_filter = string.split(hdr.get('HIERARCH FPA.FILTER'), '.')[0]
_gain = hdr.get('HIERARCH CELL.GAIN')
_ron = hdr.get('HIERARCH CELL.READNOISE')
_mjd = hdr.get('MJD-OBS')
_dayobs = jd2date(_mjd + 2400000.5).strftime('%Y%d%m')
if not _ra:
_ra = hdr.get('RA_DEG')
if not _dec:
_dec = hdr.get('DEC_DEG')
# airmass
if 'airmass' in hdr:
_airmass = hdr.get('airmass')
else:
_airmass = 1
# filters
filt = {
'U': 'U',
'B': 'B',
'V': 'V',
'R': 'R',
'I': 'I',
'u': 'up',
'g': 'gp',
'r': 'rp',
'i': 'ip',
'z': 'zs'
}
if _filter in filt.keys():
_filter = filt[_filter]
if 'date-obs' in hdr:
_dateobs = hdr.get('date-obs')
else:
_dateobs = jd2date(_mjd + 2400000.5).strftime('%Y-%d-%m')
print imglist[0]
print _dateobs, _dayobs, _mjd, _filter
if not output:
output = _telescope + '_' + str(out1) + '_' + str(_dayobs) + '_' + str(
_filter) + '_' + objname + '.fits'
imgmask = []
skylevel = []
# if the template is from sloan, use mask and weight image
if survey == 'sloan':
welist = [i for i in imglist if '.weight.' in i]
if len(welist):
# if weight images provided, use them in swarp
# and take out them from input list image
imglist = [j for j in imglist if j not in welist]
imgmask = welist
for jj in imglist:
img_data, img_header = fits.getdata(jj, header=True)
if 'SKYLEVEL' in img_header:
skylevel.append(img_header['SKYLEVEL'])
elif survey == 'ps1':
wtlist = [i for i in imglist if '.wt_' in i]
mklist = [i for i in imglist if '.mk_' in i]
if len(wtlist):
for i, name in enumerate(wtlist):
weightimg = re.sub('.wt_', '.weight.', name)
imgmask.append(weightimg)
if re.sub('.wt_', '.mk_', name) in mklist:
weight_data, weight_header = fits.getdata(name,
header=True)
mask_data, mask_header = fits.getdata(re.sub(
'.wt_', '.mk_', name),
header=True)
weight_data = 1 / weight_data
weight_fits = fits.PrimaryHDU(header=weight_header,
data=weight_data)
weight_fits.writeto(weightimg,
output_verify='fix',
clobber=True)
else:
os.system('cp ' + name + ' ' + weightimg)
imglist = [
j for j in imglist if (j not in wtlist) and (j not in mklist)
]
# measure skylevel in all ps1 images
for jj in imglist:
img_data, img_header = fits.getdata(jj, header=True)
skylevel.append(np.mean(img_data))
# elif len(welist):
# imglist = [j for j in imglist if j not in welist]
# imgmask = welist
print imgmask
print skylevel
sampling = 'BILINEAR' # LANCZOS3
line = 'swarp ' + ','.join(imglist) + ' -IMAGEOUT_NAME ' + str(output) + \
' -WEIGHTOUT_NAME ' + re.sub('.fits', '', output) + '.weight.fits' + \
' -RESAMPLE_DIR ./ -RESAMPLE_SUFFIX .swarptemp.fits -RESAMPLING_TYPE ' +sampling+ \
' -COMBINE Y -COMBINE_TYPE ' + str(combine_type)+ \
' -VERBOSE_TYPE NORMAL -SUBTRACT_BACK Y -INTERPOLATE Y' + \
' -PIXELSCALE_TYPE MANUAL,MANUAL -PIXEL_SCALE ' + str(pixelscale) + ',' + str(pixelscale) + \
' -IMAGE_SIZE ' + str(_imagesize) + ',' + str(_imagesize) + \
' -CENTER_TYPE MANUAL,MANUAL -CENTER ' + str(_ra) + ',' + str(_dec) + \
' -GAIN_DEFAULT ' + str(_gain)
if imgmask:
line += ' -WEIGHT_TYPE MAP_WEIGHT -WEIGHT_IMAGE ' + ','.join(imgmask)
print line
os.system(line)
# the output of swarp give the normalized weight
# we want to store the variance image
# we invert the normalized weight and we "de-normalized" this image
hd = fits.getheader(output)
ar = fits.getdata(output)
hd2 = fits.getheader(re.sub('.fits', '', output) + '.weight.fits')
ar2 = fits.getdata(re.sub('.fits', '', output) + '.weight.fits')
variance = 1 / ar2
# this is to take in account that the weight is normalized
variance *= (np.median(np.abs(ar - np.median(ar))) *
1.48)**2 / np.median(variance)
varimg = re.sub('.fits', '', output) + '.var.fits'
fits.writeto(varimg, variance, hd2, clobber=True)
# put the saturation all values where the weight is zero
ar = np.where(ar2 == 0, _saturate, ar)
if len(skylevel):
hd['SKYLEVEL'] = (np.mean(skylevel), 'average sky level')
hd['L1FWHM'] = (9999, 'FHWM (arcsec) - computed with sextractor')
hd['WCSERR'] = (0, 'error status of WCS fit. 0 for no error')
hd['MJD-OBS'] = (_mjd, 'MJD')
hd['RA'] = (_ra, 'RA')
hd['DEC'] = (_dec, 'DEC')
hd['RDNOISE'] = (_ron, 'read out noise')
hd['PIXSCALE'] = (pixelscale, '[arcsec/pixel] Nominal pixel scale on sky')
hd['FILTER'] = (_filter, 'filter used')
hd['DAY-OBS'] = (_dayobs, 'day of observation')
hd['AIRMASS'] = (_airmass, 'airmass')
hd['DATE-OBS'] = (_dateobs, 'date of observation')
hd['GAIN'] = (_gain, 'gain')
hd['SATURATE'] = (_saturate, 'saturation level ')
if objname:
hd['OBJECT'] = (objname, 'title of the data set')
if survey == 'sloan':
hd['TELESCOP'] = ('SDSS', 'name of the telescope')
hd['INSTRUME'] = ('SDSS', 'instrument used')
hd['SITEID'] = ('SDSS', 'ID code of the Observatory site')
elif survey == 'ps1':
hd['TELESCOP'] = ('PS1', 'name of the telescope')
hd['INSTRUME'] = ('PS1', 'instrument used')
hd['SITEID'] = ('PS1', 'ID code of the Observatory site')
ar, hdr = northupeastleft(data=ar, header=hd)
out_fits = fits.PrimaryHDU(header=hd, data=ar)
out_fits.writeto(output, clobber=True, output_verify='fix')
northupeastleft(filename=varimg)
if show:
lsc.display_image(output, 2, True, '', '')
return output, varimg
def sdss_swarp(imglist,_telescope='spectral',_ra='',_dec='',output='', objname='',survey='sloan',combine_type='MEDIAN', show=False):
import re
import datetime
import lsc
import time
import string
if _telescope == 'spectral':
pixelscale = 0.30104 # 2 meter
_imagesize = 2020
elif _telescope == 'sbig':
pixelscale = 0.467 # 1 meter
_imagesize = 2030
elif _telescope == 'sinistro':
pixelscale = 0.387 # 1 meter
_imagesize = 4020
if survey =='sloan':
out1 = 'SDSS'
hdr = fits.getheader(imglist[0])
_filter = hdr.get('filter')
_gain = hdr.get('gain')
_ron = hdr.get('rdnoise')
if not _ra:
_ra = hdr.get('CRVAL1')
if not _dec:
_dec = hdr.get('CRVAL2')
_saturate = hdr.get('SATURATE')
if not _saturate:
_saturate = 61000
if 'day-obs' in hdr:
_dayobs = hdr.get('day-obs')
elif 'date-obs' in hdr:
_dayobs = re.sub('-','',hdr.get('date-obs'))
if '/' in _dayobs:
_dayobs = '19'+''.join(string.split(_dayobs,'/')[::-1])
try:
_mjd = MJDnow(datetime.datetime(int(str(_dayobs)[0:4]),int(str(_dayobs)[4:6]),int(str(_dayobs)[6:8])))
except:
print 'warning, no mjd'
_mjd = 0
_dayobs = '19991231'
elif survey =='ps1':
out1 = 'PS1'
imglist2=[]
for i,img in enumerate(imglist):
print i,img
hdr = fits.open(img)
if os.path.isfile(re.sub('.fits','_1.fits',img)):
os.system('rm '+re.sub('.fits','_1.fits',img))
fits.writeto(re.sub('.fits','_1.fits',img),hdr[1].data,hdr[1].header)
imglist2.append(re.sub('.fits','_1.fits',img))
imglist = imglist2
hdr = fits.getheader(imglist[0])
_saturate = hdr.get('HIERARCH CELL.SATURATION')
_filter = string.split(hdr.get('HIERARCH FPA.FILTER'),'.')[0]
_gain = hdr.get('HIERARCH CELL.GAIN')
_ron = hdr.get('HIERARCH CELL.READNOISE')
_mjd = hdr.get('MJD-OBS')
_dayobs = jd2date(_mjd+2400000.5).strftime('%Y%d%m')
if not _ra:
_ra = hdr.get('RA_DEG')
if not _dec:
_dec = hdr.get('DEC_DEG')
# airmass
if 'airmass' in hdr:
_airmass = hdr.get('airmass')
else:
_airmass = 1
# filters
filt={'U':'U','B':'B','V':'V','R':'R','I':'I','u':'up','g':'gp','r':'rp','i':'ip','z':'zs'}
if _filter in filt.keys():
_filter = filt[_filter]
if 'date-obs' in hdr:
_dateobs = hdr.get('date-obs')
else:
_dateobs = jd2date(_mjd+2400000.5).strftime('%Y-%d-%m')
print imglist[0]
print _dateobs, _dayobs, _mjd, _filter
if not output:
output = _telescope+'_'+str(out1)+'_'+str(_dayobs)+'_'+str(_filter)+'_'+objname +'.fits'
imgmask = []
skylevel = []
# if the template is from sloan, use mask and weight image
if survey =='sloan':
welist = [i for i in imglist if '.weight.' in i]
if len(welist):
# if weight images provided, use them in swarp
# and take out them from input list image
imglist = [j for j in imglist if j not in welist]
imgmask = welist
for jj in imglist:
img_data,img_header=fits.getdata(jj, header=True)
if 'SKYLEVEL' in img_header:
skylevel.append(img_header['SKYLEVEL'])
elif survey=='ps1':
wtlist = [i for i in imglist if '.wt_' in i]
mklist = [i for i in imglist if '.mk_' in i]
if len(wtlist):
for i,name in enumerate(wtlist):
weightimg = re.sub('.wt_','.weight.',name)
imgmask.append(weightimg)
if re.sub('.wt_','.mk_',name) in mklist:
weight_data, weight_header = fits.getdata(name, header=True)
mask_data, mask_header = fits.getdata(re.sub('.wt_','.mk_',name), header=True)
weight_data = 1/weight_data
weight_fits = fits.PrimaryHDU(header=weight_header, data=weight_data)
weight_fits.writeto(weightimg, output_verify='fix', overwrite=True)
else:
os.system('cp '+name+' '+weightimg)
imglist = [j for j in imglist if (j not in wtlist) and (j not in mklist)]
# measure skylevel in all ps1 images
for jj in imglist:
img_data,img_header=fits.getdata(jj, header=True)
skylevel.append(np.mean(img_data))
# elif len(welist):
# imglist = [j for j in imglist if j not in welist]
# imgmask = welist
print imgmask
print skylevel
sampling = 'BILINEAR' # LANCZOS3
line = 'swarp ' + ','.join(imglist) + ' -IMAGEOUT_NAME ' + str(output) + \
' -WEIGHTOUT_NAME ' + re.sub('.fits', '', output) + '.weight.fits' + \
' -RESAMPLE_DIR ./ -RESAMPLE_SUFFIX .swarptemp.fits -RESAMPLING_TYPE ' +sampling+ \
' -COMBINE Y -COMBINE_TYPE ' + str(combine_type)+ \
' -VERBOSE_TYPE NORMAL -SUBTRACT_BACK Y -INTERPOLATE Y' + \
' -PIXELSCALE_TYPE MANUAL,MANUAL -PIXEL_SCALE ' + str(pixelscale) + ',' + str(pixelscale) + \
' -IMAGE_SIZE ' + str(_imagesize) + ',' + str(_imagesize) + \
' -CENTER_TYPE MANUAL,MANUAL -CENTER ' + str(_ra) + ',' + str(_dec) + \
' -GAIN_DEFAULT ' + str(_gain)
if imgmask:
line += ' -WEIGHT_TYPE MAP_WEIGHT -WEIGHT_IMAGE ' + ','.join(imgmask)
print line
os.system(line)
# the output of swarp give the normalized weight
# we want to store the variance image
# we invert the normalized weight and we "de-normalized" this image
hd = fits.getheader(output)
ar = fits.getdata(output)
hd2 = fits.getheader(re.sub('.fits', '', output) + '.weight.fits')
ar2 = fits.getdata(re.sub('.fits', '', output) + '.weight.fits')
variance = 1 / ar2
# this is to take in account that the weight is normalized
variance *= (np.median(np.abs(ar - np.median(ar)))*1.48)**2/np.median(variance)
varimg = re.sub('.fits', '', output) + '.var.fits'
fits.writeto(varimg, variance, hd2, overwrite=True)
# put the saturation all values where the weight is zero
ar = np.where(ar2 == 0, _saturate, ar)
if len(skylevel):
hd['SKYLEVEL'] = (np.mean(skylevel), 'average sky level')
hd['L1FWHM'] = (9999, 'FHWM (arcsec) - computed with sextractor')
hd['WCSERR'] = (0, 'error status of WCS fit. 0 for no error')
hd['MJD-OBS'] = (_mjd, 'MJD')
hd['RA'] = (_ra, 'RA')
hd['DEC'] = (_dec, 'DEC')
hd['RDNOISE'] = (_ron, 'read out noise')
hd['PIXSCALE'] = (pixelscale, '[arcsec/pixel] Nominal pixel scale on sky')
hd['FILTER'] = (_filter, 'filter used')
hd['DAY-OBS'] = (_dayobs, 'day of observation')
hd['AIRMASS'] = (_airmass, 'airmass')
hd['DATE-OBS'] = (_dateobs, 'date of observation')
hd['GAIN'] = (_gain, 'gain')
hd['SATURATE'] = (_saturate, 'saturation level ')
if objname:
hd['OBJECT'] = (objname, 'title of the data set')
if survey == 'sloan':
hd['TELESCOP'] = ('SDSS', 'name of the telescope')
hd['INSTRUME'] = ('SDSS', 'instrument used')
hd['SITEID'] = ('SDSS', 'ID code of the Observatory site')
elif survey == 'ps1':
hd['TELESCOP'] = ('PS1', 'name of the telescope')
hd['INSTRUME'] = ('PS1', 'instrument used')
hd['SITEID'] = ('PS1', 'ID code of the Observatory site')
ar, hdr = northupeastleft(data=ar, header=hd)
out_fits = fits.PrimaryHDU(header=hd, data=ar)
out_fits.writeto(output, overwrite=True, output_verify='fix')
northupeastleft(filename=varimg)
if show:
lsc.display_image(output,2,True,'','')
return output, varimg