def mk_skyflats(file_list=None,file_path=None, bias_fil=None):
import xastropy.PH136.experiments.hrdiagram as hrd
from astropy.io.fits import getdata
# Frames
B_sky = 32 + np.arange(5)
V_sky = 37 + np.arange(5)
R_sky = 43 + np.arange(5)
all_sky = [B_sky, V_sky, R_sky]
# Outfiles
outfil = ['Sky_B.fits', 'Sky_V.fits', 'Sky_R.fits']
filters = ['B','V','R']
# Bias
if bias_fil == None:
bias_fil = 'Bias.fits'
bias_img,bias_head = getdata(bias_fil,0,header=True)
# Loop on Filters
for ff in filters:
# Index
idx = filters.index(ff)
# Generate file names
files= hrd.mk_file_list(all_sky[idx])
# Stack with scaling
img = hrd.stack_img(files, bias_img=bias_img, norm=True)
# Trim
trim_img = hrd.trimflip_img(img)
# Deal with zeros
zro = np.where( trim_img == 0.)
trim_img[zro] = 1.
# Write
print 'Sky Flats: Writing ', outfil[idx]
fits.writeto(outfil[idx], trim_img, clobber=True)
print 'Sky Flats: All done'
return
def proc_sa104(file_path=None,outdir=None, bias_fil=None):
from astropy.coordinates import ICRS
from astropy.io import ascii
from astropy import units as u
from astropy.io.fits import getdata
import xastropy.PH136.experiments.hrdiagram as hrd
# Defaults
if file_path == None:
file_path = 'Raw/'
if outdir == None:
outdir = 'Std/'
# Bias frame
if bias_fil == None:
bias_fil = 'Bias.fits'
bias_img,bias_head = getdata(bias_fil,0,header=True)
# Read Log
data = ascii.read('simple.log',delimiter='|')
nfil = len(data)
all_coord = ICRS(ra=data['RA'], dec=data['DEC'], unit=(u.hour,u.degree))
# M67 coords
sa104_rac = '12:43:44.3'
sa104_decc = '-00:29:40.0'
sa104_c = ICRS(sa104_rac, sa104_decc, unit=(u.hour,u.degree))
# Find all SA 104
sep = (sa104_c.separation(all_coord)).degree
isa104, = np.where( sep < 1. ) # 1 degree
sa104 = data[isa104]
# Filters
all_filt=np.array(sa104['Filter'])
filters,ifilt = np.unique(all_filt,return_index=True)
# Loop on Filterse
all_fil = []
for ff in filters:
# Load Sky frame
skyfil = 'Sky_'+ff+'.fits'
sky_img,head = getdata(skyfil,0,header=True)
# Images
idx = np.where(sa104['Filter'] == ff)
# Loop on images
for kk in np.concatenate(idx,axis=0):
# Read
img,head = getdata(sa104[kk]['File'],0,header=True)
# Bias subtract
img = img - bias_img
# Trim
timg = hrd.trimflip_img(img)
# Flat field
timg = timg / sky_img
# Normalize by exposure
timg = timg / sa104[kk]['Exp']
# Filename
outfil = outdir+'SA104_t'+str(int(sa104[kk]['Exp']))+'_'+ff+'.fits'
# Check for duplicate
flg_skip = 0
mt = [i for i in range(len(all_fil)) if all_fil[i] == outfil]
if len(mt) > 0:
print 'Duplicate image', outfil
print 'Skipping...'
continue
all_fil.append(outfil)
# Write
print 'Writing ', outfil
fits.writeto(outfil, timg, head, clobber=True)
return
def proc_m67(file_path=None,outdir=None, bias_fil=None):
from astropy.coordinates import ICRS
from astropy.io import ascii
from astropy import units as u
from astropy.io.fits import getdata
import xastropy.PH136.experiments.hrdiagram as hrd
# Defaults
if file_path == None:
file_path = 'Raw/'
if outdir == None:
outdir = 'Science/'
# Bias frame
if bias_fil == None:
bias_fil = 'Bias.fits'
bias_img,bias_head = getdata(bias_fil,0,header=True)
# Read Log
data = ascii.read('simple.log',delimiter='|')
nfil = len(data)
all_coord = ICRS(ra=data['RA'], dec=data['DEC'], unit=(u.hour,u.degree))
# M67 coords
m67_rac = '08:54:24'
m67_decc = '+11:49:00'
m67_c = ICRS(m67_rac, m67_decc, unit=(u.hour,u.degree))
# Find all M67
sep = (m67_c.separation(all_coord)).degree
im67, = np.where( sep < 1. ) # 1 degree
m67 = data[im67]
# 5 positions
m67_ra = ['08:52:02.2', '08:52:15.3', '08:51:49.9', '08:51:50.0', '08:52:16.2']
m67_dec = ['+11:52:41.0', '+11:55:51.0', '+11:55:53.0', '+11:49:38.0', '+11:49:40.0']
m67_pointings = ICRS(ra=m67_ra, dec=m67_dec, unit=(u.hour, u.degree))
# Filters
all_filt=np.array(m67['Filter'])
filters,ifilt = np.unique(all_filt,return_index=True)
# Loop on Filterse
all_fil = []
for ff in filters:
# Load Sky frame
skyfil = 'Sky_'+ff+'.fits'
sky_img,head = getdata(skyfil,0,header=True)
# Images
idx = np.where(m67['Filter'] == ff)
# Loop on images
for kk in np.concatenate(idx,axis=0):
# Read
img,head = getdata(m67[kk]['File'],0,header=True)
# Bias subtract
img = img - bias_img
# Trim
timg = hrd.trimflip_img(img)
# Flat field
timg = timg / sky_img
# Normalize by exposure
timg = timg / m67[kk]['Exp']
# Filename
coord = ICRS(head['RA'], head['DEC'], unit=(u.hour,u.degree))
sep = (coord.separation(m67_pointings)).degree
ipos = np.argmin(sep)
outfil = outdir+'M67_C'+str(ipos)+'_t'+str(int(m67[kk]['Exp']))+'_'+ff+'.fits'
# Check for duplicate
flg_skip = 0
mt = [i for i in range(len(all_fil)) if all_fil[i] == outfil]
if len(mt) > 0:
print 'Duplicate image', outfil
print 'Skipping...'
continue
all_fil.append(outfil)
# Write
print 'Writing ', outfil
fits.writeto(outfil, timg, clobber=True)
return
