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Commit 1e880aca authored by niejuzi's avatar niejuzi
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updated combined_file

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csst/msc/calib_pos.py
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csst/msc/calib_pos.py~ 0 → 100644
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import os
import time
from functools import partial
from multiprocessing import Pool
from subprocess import Popen
import healpy as hp
import numpy as np
from astropy import table
from astropy import units as u
from astropy.coordinates import SkyCoord
from astropy.io import fits
from astropy.wcs import WCS
from .. import PACKAGE_PATH
from ..core.processor import CsstProcessor
from csst.msc.data_manager import CsstMscDataManager
CONFIG_PATH = PACKAGE_PATH + "/msc/pos_calib_config/"
class CsstProcMscPositionCalibration(CsstProcessor):
def join_data(self, img_list, wht_list, flg_list):
"""
Prepare data for running scamp; Combine all image data, weight files, flag files to their one frame.
Parameters
----------
img_list:
image files to join together, e.g.,MSC_210304093000_0000000_06_img.fits
wht_list:
weith files to join together, e.g.,MSC_210304093000_0000000_06_img.fits
flg_list:
flag files to join together, e.g.,e.g.,MSC_210304093000_0000000_06_flg.fits
Returns
-------
The joined multi-extension file(not stacked), weight, flag files.
e.g., combined_img.fits,combined_wht.fits, combined_flg.fits.
"""
output_imgnm = self.dm.pc_combined_file("img","fits")
hdul_img = fits.HDUList()
for i in range(0, len(img_list)):
h0 = fits.PrimaryHDU(header=img_list[i][0].header)
h1 = fits.ImageHDU(data=img_list[i][1].data, header=img_list[i][1].header)
hdul_img.append(h0)
hdul_img.append(h1)
hdul_img.writeto(output_imgnm, overwrite=True)
output_whtnm = self.dm.pc_combined_file("wht","fits")
hdul_wht = fits.HDUList()
for i in range(0, len(wht_list)):
h0 = fits.PrimaryHDU(header=wht_list[i][0].header)
h1 = fits.ImageHDU(data=wht_list[i][1].data, header=wht_list[i][1].header)
hdul_wht.append(h0)
hdul_wht.append(h1)
hdul_wht.writeto(output_whtnm, overwrite=True)
output_flgnm = self.dm.pc_combined_file("flg","fits")
hdul_flg = fits.HDUList()
for i in range(0, len(flg_list)):
h0 = fits.PrimaryHDU(header=flg_list[i][0].header)
h1 = fits.ImageHDU(data=flg_list[i][1].data, header=flg_list[i][1].header)
hdul_flg.append(h0)
hdul_flg.append(h1)
hdul_flg.writeto(output_flgnm, overwrite=True)
def run_sextractor(self,ccd_ids):
"""
Run sextractor
Parameters
----------
ccd_ids:
ccd list...
Returns
-------
The photometric catalog, with position and flux, e.g.,MSC_210304093000_0000000_06_img.cat
"""
cat_list = []
fn_list = []
for this_ccd_id in ccd_ids:
sex_cat = self.dm.l1_sci(ccd_id = this_ccd_id, suffix="img", ext="cat")
fn = self.dm.l1_sci(ccd_id=this_ccd_id, suffix="img", ext="fits")
cat_list.append(sex_cat)
fn_list.append(fn)
config_sextractor = CONFIG_PATH + "new_csst_realtime.no.weight.sex"
sex_comd1 = 'sex -c ' + config_sextractor + ' '
sex_comd2 = fn_list + ' -CATALOG_NAME ' + cat_list
sex_comd3 = ' -PARAMETERS_NAME ' + CONFIG_PATH + 'csst_realtime.param' + ' -FILTER_NAME ' + CONFIG_PATH + 'csst_realtime.conv' + ' -STARNNW_NAME ' + CONFIG_PATH + 'csst_realtime.nnw'
sex_comd = sex_comd1 + sex_comd2 + sex_comd3
print(sex_comd)
p = Popen(sex_comd, shell=True)
p.wait()
def combine_catalog(self, ccd_ids):
"""
Combine the sextractor catalog together
Parameters
-----------
ccd_ids: ccd list
Returns
-------
The combined catalog,e.g., combined_cat.fits
"""
fn = self.dm.pc_combined_file("cat","fits")
hdul = fits.HDUList()
for this_ccd_id in ccd_ids:
cat_nm = self.dm.l1_sci(ccd_id=this_ccd_id, suffix="img", ext="cat")
cat_i = fits.open(cat_nm)
data=cat_i[2].data
msk=(data['MAGERR_AUTO']<0.2)&(data['CLASS_STAR']>0.5)&(data['CLASS_STAR']<=1.0)
data=data[msk]
cat_i[2].data=data
hdul.append(cat_i[0])
hdul.append(cat_i[1])
hdul.append(cat_i[2])
hdul.writeto(fn, overwrite=True)
def run_scamp(self, wcs_refine=False):
"""
Run scamp
Returns
-------
Image header updated with WCS keywords, combined_cat.head.
"""
cb_fn = self.dm.pc_combined_file("cat","fits")
config_scamp = CONFIG_PATH + "csst.scamp"
scamp_comd = 'scamp ' + cb_fn + ' -ASTREFCAT_NAME= ' + 'ref.cat\
-MERGEDOUTCAT_NAME ' + 'merged.cat -FULLOUTCAT_NAME ' + 'full.cat\
-c ' + config_scamp
print(scamp_comd)
p = Popen(scamp_comd, shell=True)
p.wait()
if wcs_refine:
Popen('cp '+ self.dm.pc_combined_file("cat","head")+" "+self.dm.pc_combined_file("cat","ahead"),shell=True)
scamp_comd = 'scamp ' + cb_fn + ' -ASTREFCAT_NAME= ' + 'ref.cat\
-MERGEDOUTCAT_NAME ' + 'merged.cat -FULLOUTCAT_NAME ' + 'full.cat\
-c ' + config_scamp + '-AHEADER_SUFFIX '+ self.dm.pc_combined_file("cat","ahead")
print(scamp_comd)
p=Popen(scamp_comd,shell=True)
p.wait()
def convert_hdu_to_ldac(self, hdu):
"""
Convert an hdu table to a fits_ldac table (format used by astromatic suite)
Parameters
----------
hdu:
`astropy.io.fits.BinTableHDU` or `astropy.io.fits.TableHDU`
HDUList to convert to fits_ldac HDUList
Returns
-------
tbl1:
`astropy.io.fits.BinTableHDU`
Header info for fits table (LDAC_IMHEAD)
tbl2:
`astropy.io.fits.BinTableHDU`
Data table (LDAC_OBJECTS)
"""
tblhdr = np.array([hdu[1].header.tostring()])
col1 = fits.Column(name='Field Header Card', array=tblhdr, format='13200A')
cols = fits.ColDefs([col1])
tbl1 = fits.BinTableHDU.from_columns(cols)
tbl1.header['TDIM1'] = '(80, {0})'.format(len(hdu[1].header))
tbl1.header['EXTNAME'] = 'LDAC_IMHEAD'
dcol = fits.ColDefs(hdu[1].data)
tbl2 = fits.BinTableHDU.from_columns(dcol)
tbl2.header['EXTNAME'] = 'LDAC_OBJECTS'
return tbl1, tbl2
def get_refcat(self, img_list, path_gaia, search_radius, silent=True,pm_correct=True):
"""
Get reference catalog for scamp. The reference cat is GAIA EDR3.
Parameters
----------
image_prefix:
a image to get its reference catalog, e.g.,combined_img.fits.
Usually the center of the image is the wcs parameters CRVAL1,CRVAL1.
search_radius:
circle radius for searching, units: degree. e.g., 2 degree for a 1x1 deg^2 image.
For large ccd size, use larger radius. csst, r=3 deg.
path_gaia: directory of the reference catalog.
Returns
-------
outcat:
filename of the cross matched catalog: ref.cat
"""
outcat = self.dm.pc_ref_cat
fnmae = cb_fn = self.dm.pc_combined_file("img","fits")
hdu = fits.open(fname)
header1 = hdu[0].header
header2 = hdu[1].header
if (pm_correct):
oday=header1['DATE-OBS']
otime=header1['TIME-OBS']
exptime=header1['EXPTIME']
odaytime=header1['DATE-OBS']+'T'+header1['TIME-OBS']
t = Time(oday, format='isot', scale='utc')
t.format = 'decimalyear'
t1=Time(2016.0, format='decimalyear', scale='utc')
deltatime= t.value -2016.0
print('(Time - 2016.0) = deltatime =', deltatime)
else:
deltatime=0.00
ra = float(header2['CRVAL1'])
dec = float(header2['CRVAL2'])
c = SkyCoord(ra, dec, unit=(u.deg, u.deg))
print('ra, dec ra.deg dec.deg= ', ra, dec, c.ra.deg, c.dec.deg)
ra = c.ra.deg
dec = c.dec.deg
c = SkyCoord(ra, dec, unit=(u.deg, u.deg))
phi = c.ra.deg / (180. / np.pi)
theta = (90. - c.dec.deg) / (180 / np.pi)
vec = hp.ang2vec(theta, phi)
list1 = hp.query_disc(nside=32, vec=vec, radius=np.radians(search_radius))
if -1 in list1:
list1.remove(-1)
ipring = np.array(list1)
pix = np.unique(ipring)
npix = pix.size
print(ipring, 'ipring', pix, 'pix', npix, 'npix')
dt = np.dtype(
[('ra', '>f8'), ('dec', '>f8'), ('ra_error', '>f8'), ('dec_error', '>f8'), ('phot_g_mean_mag', '>f8'),
('pmra', '>f8'), ('pmra_error', '>f8'), ('pmdec', '>f8'), ('pmdec_error', '>f8')])
refcat = table.Table(dtype=dt)
for i in pix:
print('i= %5.5d' % i, path_gaia)
fname = path_gaia + 'healpix-' + '%5.5d' % i + '.fits'
print('fname=', fname)
if not silent: print('Reading ', fname)
d = table.Table.read(fname)
refcat = [refcat, d]
refcat = table.vstack(refcat, join_type='inner')
refcat.rename_column('ra', 'X_WORLD')
refcat.rename_column('dec', 'Y_WORLD')
mask = (refcat['pmdec'] != refcat['pmdec'])
refcat['pmdec'][mask] = 0
mask = (refcat['pmra'] != refcat['pmra'])
refcat['pmra'][mask] = 0
refcat['X_WORLD'] = refcat['X_WORLD'] + deltatime * refcat['pmra'] / np.cos(
refcat['Y_WORLD'] / 180. * np.pi) / 3600.0 / 1000.0
refcat['Y_WORLD'] = refcat['Y_WORLD'] + deltatime * refcat['pmdec'] / 3600.0 / 1000.0
refcat['ra_error'] = refcat['ra_error'] / 1000.0 / 3600.0
refcat['dec_error'] = refcat['dec_error'] / 1000.0 / 3600.0
refcat.rename_column('ra_error', 'ERRA_WORLD')
refcat.rename_column('dec_error', 'ERRB_WORLD')
refcat.rename_column('phot_g_mean_mag', 'MAG')
hdu = refcat
hdu1 = self.convert_hdu_to_ldac(hdu)
hdup = fits.PrimaryHDU()
hdu = hdu1[0]
tbhdu = hdu1[1]
thdulist = fits.HDUList([hdup, hdu, tbhdu])
thdulist.writeto(outcat)
print('##################### end #####################')
def rewrite_wcs_head(self, head):
"""
Rewrite the WCS head from Scamp to the standard fits header
Parameters
----------
head: scamp head file names
Returns
-------
wcshead: a new head file in fits format
"""
wcshead = head + '.fits'
f = open(head, 'r')
f1 = open(wcshead, 'w')
a = ''
i = 0
for v in f.readlines():
sp = ''
asp = ''
i += 1
if len(v) <= 81:
sp = ' ' * (81 - len(v))
if 'END' in v:
asp = ' ' * 80 * (36 - i % 36)
i = i + (36 - i % 36)
# print(i)
a = a + v + sp + asp
f1.write(a.replace('\n', ''))
f1.close()
f.close()
return wcshead
def check_astrometry(self, img_list):
"""
Check position calibration quality
Parameters
------------
img_list:
list of images, in table format
Returns
-------
ccdraoff:
ra difference between observed catalog and reference catalog
ccddecoff:
dec difference between observed catalog and reference catalog
ccdraoff_med,ccddecoff_med:
median of the ra or dec difference
ccdraoff_rms,ccddecoff_rms:
rms of the ra or dec difference
"""
print('############## check the astrometry quality and save files ################')
r1 = []
d1 = []
fn_head = self.dm.pc_combined_file("cat","head")
fn_scat = self.dm.pc_combined_file("cat","fits")
data_scat = fits.open(fn_scat)
wcshead = self.rewrite_wcs_head(fn_head)
scat = fits.open(fn_scat)
hdul = fits.HDUList()
for i in range(0, len(img_list)):
wcshdr = fits.getheader(wcshead, i, ignore_missing_simple=True) # read headers and change to RA---TPV,DEC--TPV for wcs_transfer package
wcshdr['CTYPE1'] = 'RA---TPV'
wcshdr['CTYPE2'] = 'DEC--TPV'
w = WCS(wcshdr)
sexcat = data_scat[i*3+2].data
x = sexcat['XWIN_IMAGE']
y = sexcat['YWIN_IMAGE']
r, d = w.all_pix2world(x, y, 0) # convert xwin,ywin to ra,de
sexcat['ALPHA_J2000'] = r
sexcat['DELTA_J2000'] = d
r1 = np.hstack((r1, r))
d1 = np.hstack((d1, d))
obsc = SkyCoord(ra=r1 * u.degree, dec=d1 * u.degree)
tmp_cat = np.zeros((len(obsc), 2))
tmp_cat[:, 0] = obsc.ra
tmp_cat[:, 1] = obsc.dec
np.savetxt(dm.pc_scamp_coord, tmp_cat, fmt="%.10f %.10f", delimiter="\n")
gaia_cat=Table.read(self.dm.pc_ref_cat)
gaia_ra=gaia_cat['X_WORLD']
gaia_dec=gaia_cat['Y_WORLD']
refc=SkyCoord(ra=gaia_ra*u.degree,dec=gaia_dec*u.degree)
idx, d2d, d3d = obsc.match_to_catalog_sky(refc)
ref_uid=np.unique(idx)
obs_uid=np.full_like(ref_uid,-1)
tmpj=-1
ccdraoff_med=ccddecoff_med=ccdra_rms=ccddec_rms=-1
for i in ref_uid:
tmpj=tmpj+1
iid=(idx == i)
iiid = (d2d.deg[iid] == d2d.deg[iid].min())
obs_uid[tmpj]=iid.nonzero()[0][iiid.nonzero()[0]][0]
uidlim=d2d[obs_uid].arcsecond <1. # set match radius=1 arcsec
if uidlim.sum()>0:
obs_uidlim=obs_uid[uidlim]
ref_uidlim=ref_uid[uidlim]
ccdraoff=(obsc[obs_uidlim].ra- refc[ref_uidlim].ra).arcsec*np.cos(obsc[obs_uidlim].dec.deg*np.pi/180.)
ccdraoff_med=np.median(ccdraoff)
ccdra_rms=np.std(ccdraoff)
ccddecoff=(obsc[obs_uidlim].dec- refc[ref_uidlim].dec).arcsec
ccddec_rms=np.std(ccddecoff)
ccddecoff_med=np.median(ccddecoff)
match_num=len(ccdraoff)
print('################# astrometry result: ##############')
if (match_num<100):
print('### bad astrometry ###')
print('median ra_off, dec_off (mas) from scamp:',ccdraoff_med*1000.,ccddecoff_med*1000.)
print('rms ra_off, dec_off (mas) from scamp:',ccdra_rms*1000.,ccddec_rms*1000.)
print('############################################')
return ccdraoff,ccddecoff,ccdraoff_med,ccddecoff_med,ccdra_rms,ccddec_rms
def write_headers(self, ccd_ids):
"""
Wrtie history to header
"""
head_suffix = self.dm.pc_combined_head_fits
hdul2 = fits.open(head_suffix, ignore_missing_simple=True)
for this_ccd_id in ccd_ids:
fits_nm = self.dm.l1_sci(this_ccd_id, suffix="img", ext="head")
hdul1 = fits.open(fits_nm, mode='update', ignore_missing_simple=True)
hdr = hdul1[0].header
hdr2 = hdul2[i].header
hdr.extend(hdr2, unique=True, update=True)
WCS_S = 0
WCS_V = '2.0.4'
WCS_P = 'default.scamp'
WCS_TOL = time.strftime('%Y-%m-%d %H:%M:%S %p')
hdr.set('WCS_S', '0', '0=done')
hdr.set('WCS_V', WCS_V, 'Version of WCS calibration')
hdr.set('WCS_P', WCS_P, 'Configure file name of WCS')
hdr.set('WCS_TOL', WCS_TOL, 'Time of last wcs calibration')
hdul1.flush()
hdul1.close()
def make_plots(self, ccdoff):
print('##### Analyzing the scampe result, making some pltos.... ####')
plt.figure(figsize=(11,5))
ax1=plt.subplot(121)
bin=0.05
plt.grid(color='grey',ls='--')
plt.plot(ccdoff[0],ccdoff[1],'ko',markersize=3,alpha=0.3)
plt.xlabel(r'$\Delta$ RA (arcsec)',fontsize=12)
plt.ylabel(r'$\Delta$ Dec (arcsec)',fontsize=12)
ax2=plt.subplot(122)
plt.grid(color='grey',ls='--')
plt.hist(ccdoff[0],bins=np.arange(-1,1, bin),histtype="step",color="r",label=r'$\Delta$RA (arcsec)')
plt.hist(ccdoff[1],bins=np.arange(-1,1, bin),histtype="step",color="b",label=r'$\Delta$Dec (arcsec)')
plt.legend()
a=str(float(ccdoff[2]))
b=str(float(ccdoff[4]))
c=str(float(ccdoff[3]))
d=str(float(ccdoff[5]))
plt.text(-0.95,45,r'$\mu$='+a[0:6]+r', $\sigma$='+b[0:5]+' (arcsec)',color='red')
plt.text(-0.95,35,r'$\mu$='+c[0:6]+r', $\sigma$='+d[0:5]+' (arcsec)',color='blue')
plt.xlabel('coord_diff (arcsec)',fontsize=12)
plt.savefig(self.dm.pc_radecoff,dpi=300)
def prepare(self, dm):
self.dm = dm
def run(self, img_list, wht_list, flg_list, ccd_ids, path_gaia, search_radius, pm_correct=True, wcs_refine=False, plot=False):
print('preparing files for position calibration....')
self.join_data(img_list, wht_list, flg_list)
print('################## run sextractor ###################')
p = Pool()
prod_x = partial(self.run_sextractor)
result = p.map(prod_x, ccd_ids)
p.close()
p.join()
print('################## sextractor done ###################')
print('############### combine sextractor catalog ###############')
self.combine_catalog(ccd_ids)
print('############### get reference catalog ###############3')
self.get_refcat(img_list, path_gaia=path_gaia, search_radius=search_radius, silent=True,pm_correct=True)
print('############### run scamp ##################')
self.run_scamp(wcs_refine=wcs_refine)
print('################ scamp done #################')
print('Checking astrometry quality....')
ccdoff = self.check_astrometry(img_list)
print('################ updating headers.... #############')
self.write_headers(ccd_ids)
print('#### Position calibration process done ####')
if plot:
make_plot(ccdoff)
def cleanup(self):
pass
csst/msc/data_manager.py~ 0 → 100644
View file @ 1e880aca
import glob
import re
from astropy.io import fits
from .backbone import VER_SIMS, CCD_FILTER_MAPPING
class CsstMscDataManager:
""" this class defines the file format of the input & output of CSST MSC L1 pipeline
C3:
MSC_MS_210525220000_100000020_06_raw.fits
MSC_CRS_210525220000_100000020_06_raw.fits
MSC_210525120000_0000020_06.cat
C5.1:
CSST_MSC_MS_SCI_20270810081950_20270810082220_100000100_06_L0_1.fits
CSST_MSC_MS_CRS_20270810081950_20270810082220_100000100_06_L0_1.fits
MSC_10000100_chip_06_filt_y.cat
MSC_10000100_chip_06_filt_y.log
"""
def __init__(self, ver_sim="C5.1", dir_l0="", dir_l1="", dir_pcref="", path_aux="", force_all_ccds=False):
assert ver_sim in VER_SIMS
self.dir_l0 = dir_l0
self.dir_l1 = dir_l1
self.dir_pcref = dir_pcref
self.path_aux = path_aux
self.ver_sim = ver_sim
fps_img = self.glob_image(dir_l0, ver_sim=ver_sim)
fps_cat = self.glob_cat(dir_l0, ver_sim=ver_sim)
if force_all_ccds:
assert len(fps_img) == len(CCD_ID_LIST)
else:
assert len(fps_img) > 0
if ver_sim == "C3":
# get info
# print(re.split(r"[_.]", fps[0]))
self._instrument, self._survey, \
self._exp_start, self._exp_id, \
_ccd_id, self._l0_suffix, _ext = re.split(r"[_.]", fps_img[0])
self._cat_id = re.split(r"[_.]", fps_cat[0])[1]
self._exp_start = int(self._exp_start)
self._exp_id = int(self._exp_id)
# available CCD IDs
self.available_ccd_ids = [int(re.split(r"[_.]", fp)[4]) for fp in fps_img]
self.available_ccd_ids.sort()
elif ver_sim == "C5.1":
# get info
# print(re.split(r"[_.]", fps[0]))
self._telescope, self._instrument, self._survey, self._imagetype, \
self._exp_start, self._exp_stop, self._exp_id, \
_ccd_id, self._l0_suffix, self._version, _ext = re.split(r"[_.]", fps_img[0])
self._cat_id = re.split(r"[_.]", fps_cat[0])[1]
self._exp_start = int(self._exp_start)
self._exp_stop = int(self._exp_stop)
self._exp_id = int(self._exp_id)
# available CCD IDs
self.available_ccd_ids = [int(re.split(r"[_.]", fp)[7]) for fp in fps_img]
self.available_ccd_ids.sort()
@staticmethod
def glob_image(dir_l0, ver_sim="C5"):
""" glob files in L0 data directory """
if ver_sim == "C3":
pattern = os.path.join(dir_l0, "MSC_MS_*_raw.fits")
elif ver_sim == "C5.1":
pattern = os.path.join(dir_l0, "CSST_MSC_MS_SCI_*.fits")
fps = glob.glob(pattern)
fps = [os.path.basename(fp) for fp in fps]
fps.sort()
print("@DM.glob_dir: {} files found with pattern: {}".format(len(fps), pattern))
return fps
@staticmethod
def glob_cat(dir_l0, ver_sim="C5"):
""" glob input catalogs in L0 data directory """
if ver_sim == "C3":
pattern = os.path.join(dir_l0, "MSC_*.cat")
elif ver_sim == "C5.1":
pattern = os.path.join(dir_l0, "MSC_*.cat")
fps = glob.glob(pattern)
fps = [os.path.basename(fp) for fp in fps]
fps.sort()
print("@DM.glob_dir: {} files found with pattern: {}".format(len(fps), pattern))
return fps
def l0_cat(self, ccd_id=6):
""" the L0 cat file path"""
if self.ver_sim == "C3":
fn = "{}_{}_{:07d}_{:02d}.cat".format(
self._instrument, self._cat_id, self._exp_id - 100000000, ccd_id)
elif self.ver_sim == "C5.1":
fn = "{}_{}_chip_{:02d}_filt_{}.cat".format(
self._instrument, self._exp_id - 90000000, ccd_id, CCD_FILTER_MAPPING[ccd_id])
return os.path.join(self.dir_l0, fn)
def l0_log(self, ccd_id=6):
""" L0 log file path """
if self.ver_sim == "C5.1":
fn = "{}_{}_chip_{:02d}_filt_{}.log".format(
self._instrument, self._exp_id - 90000000, ccd_id, CCD_FILTER_MAPPING[ccd_id])
return os.path.join(self.dir_l0, fn)
def l0_sci(self, ccd_id=6):
""" L0 image file path """
if self.ver_sim == "C3":
fn = "{}_{}_{}_{}_{:02d}_raw.fits".format(
self._instrument, self._survey, self._exp_start, self._exp_id, ccd_id)
elif self.ver_sim == "C5.1":
fn = "{}_{}_{}_SCI_{}_{}_{}_{:02d}_L0_1.fits".format(
self._telescope, self._instrument, self._survey,
self._exp_start, self._exp_stop, self._exp_id, ccd_id)
return os.path.join(self.dir_l0, fn)
def l0_crs(self, ccd_id=6):
""" L0 cosmic ray file path """
if self.ver_sim == "C3":
fn = "{}_CRS_{}_{}_{:02d}_raw.fits".format(
self._instrument, self._exp_start, self._exp_id, ccd_id)
elif self.ver_sim == "C5.1":
fn = "{}_{}_{}_CRS_{}_{}_{}_{:02d}_L0_1.fits".format(
self._telescope, self._instrument, self._survey,
self._exp_start, self._exp_stop, self._exp_id, ccd_id)
return os.path.join(self.dir_l0, fn)
def l1_sci(self, ccd_id=6, suffix="img_whead", ext="fits"):
""" generate L1 file path
Parameters
----------
ccd_id:
CCD ID
suffix:
{"img", "wht", "flg", "img_L1", "wht_L1", "flg_L1", "whead"}
ext:
{"fits", "cat", "rcat"}
Returns
-------
L1 file path
"""
if self.ver_sim == "C3":
fn = "{}_{}_{}_{}_{:02d}_{}.{}".format(
self._instrument, self._survey,
self._exp_start, self._exp_id, ccd_id, suffix, ext)
elif self.ver_sim == "C5.1":
fn = "{}_{}_{}_SCI_{}_{}_{}_{:02d}_{}.{}".format(
self._telescope, self._instrument, self._survey,
self._exp_start, self._exp_stop, self._exp_id, ccd_id, suffix, ext)
return os.path.join(self.dir_l1, fn)
def pc_combined_file(self, suffix="img", ext="fits"):
""" combined images
Parameters
----------
suffix:
{"img", "wht", "flg", "cat", "head"}
ext:
{"fits", "head", "ahead" }
Returns
-------
combined image path
"""
if self.ver_sim == "C3":
fn = "{}_{}_{}_{}_{}.{}".format(
self._instrument, self._survey,
self._exp_start, self._exp_id, suffix, ext)
elif self.ver_sim == "C5.1":
fn = "{}_{}_{}_SCI_{}_{}_{}_{}.{}".format(
self._telescope, self._instrument, self._survey,
self._exp_start, self._exp_stop, self._exp_id, suffix, ext)
return os.path.join(self.dir_l1, fn)
@property
def pc_ref_cat(self):
""" reference catalog """
return os.path.join(self.dir_l1, "ref.cat")
@property
def pc_radecoff(self):
""" plot coordinate diff between obs and ref """
return os.path.join(self.dir_l1, "radec_off.png")
@property
def pc_check_fits(self):
""" check fits """
return os.path.join(self.dir_l1, "check.fits")
@property
def pc_combined_head_fits(self):
""" combined head (converted to) fits """
return os.path.join(self.dir_l1, "combined_cat.head.fits")
@property
def pc_scamp_coord(self):
""" SCAMP coord """
return os.path.join(self.dir_l1, "scamp_coord.txt")
def get_ccd_ids(self, ccd_ids=None):
""" """
if ccd_ids is None:
# default ccd_ids
ccd_ids = self.available_ccd_ids
else:
try:
# assert ccd_ids is a subset of available ccd_ids
assert set(ccd_ids).issubset(set(self.available_ccd_ids))
except AssertionError as ae:
print("@DM: available CCD IDs are ", self.available_ccd_ids)
print("@DM: target CCD IDs are ", ccd_ids)
raise ae
return ccd_ids
def get_bias(self, ccd_id=6):
fp = glob.glob(self.path_aux.format("CLB", ccd_id))[0]
return fits.getdata(fp)
def get_dark(self, ccd_id=6):
fp = glob.glob(self.path_aux.format("CLD", ccd_id))[0]
return fits.getdata(fp)
def get_flat(self, ccd_id=6):
fp = glob.glob(self.path_aux.format("CLF", ccd_id))[0]
return fits.getdata(fp)
if __name__ == "__main__":
# test C3
import os
from csst.msc.data_manager import CsstMscDataManager
dm = CsstMscDataManager(
ver_sim="C3", dir_l0="/data/L1Pipeline/msc/MSC_0000020", dir_l1="/data/L1Pipeline/msc/work")
print("----- L0 images -----")
print(dm.l0_sci(ccd_id=6))
print(os.path.exists(dm.l0_sci(ccd_id=6)))
print("----- L0 crs -----")
print(dm.l0_crs(ccd_id=6))
print(os.path.exists(dm.l0_sci(ccd_id=8)))
print("----- L0 input cat -----")
print(dm.l0_cat(8))
print(os.path.exists(dm.l0_cat(ccd_id=8)))
print("----- available ccd_ids -----")
print(dm.available_ccd_ids)
print("----- L1 images -----")
print(dm.l1_sci(25, "img", "fits"))
# test C5.1
import os
from csst.msc.data_manager import CsstMscDataManager
from csst.msc.backbone import CCD_ID_LIST
dm = CsstMscDataManager(
ver_sim="C5.1", dir_l0="/data/sim_data/MSC_0000100", dir_l1="/home/user/L1Pipeline/msc/work")
print("----- available ccd_ids -----")
print(dm.available_ccd_ids)
for ccd_id in dm.available_ccd_ids[:2]:
print("----- L0 images -----")
print(dm.l0_sci(ccd_id=ccd_id))
print(os.path.exists(dm.l0_sci(ccd_id=ccd_id)))
print("----- L0 crs -----")
print(dm.l0_crs(ccd_id=ccd_id))
print(os.path.exists(dm.l0_sci(ccd_id=ccd_id)))
print("----- L0 input cat -----")
print(dm.l0_cat(ccd_id=ccd_id))
print(os.path.exists(dm.l0_cat(ccd_id=ccd_id)))
print("----- L0 input log -----")
print(dm.l0_log(ccd_id=ccd_id))
print(os.path.exists(dm.l0_log(ccd_id=ccd_id)))
print("----- L1 images -----")
print(dm.l1_sci(ccd_id, "img", "fits"))
csst/msc/pipeline.py
View file @ 1e880aca
......@@ -107,8 +107,24 @@ def do_one_exposure(ver_sim="C5.1", dir_l0="", dir_l1="", dir_pcref="", path_aux
# Step 2. Calibrate Position
pcProc = CsstProcMscPositionCalibration()
pcProc.run(img_list, wht_list, flg_list, fn_list, dir_pcref, dir_l1, 2.0)
pcProc.cleanup(img_list, dir_l1)
pcProc.prepare(dm)
if (img_list):
pcProc.run(img_list, wht_list, flg_list, ccd_ids, dir_pcref, 2.0, pm_correct=True, wcs_refine=True, plot=True)
else:
for this_ccd_id in ccd_ids:
fp_img = dm.l1_sci(ccd_id=this_ccd_id, suffix="img",ext="fits")
fp_wht = dm.l1_sci(ccd_id=this_ccd_id, suffix="wht",ext="fits")
fp_flg = dm.l1_sci(ccd_id=this_ccd_id, suffix="flg",ext="fits")
img = CsstMscImgData.read(fp_img)
wht = CsstMscImgData.read(fp_wht)
flg = CsstMscImgData.read(fp_flg)
img_list.append(img)
wht_list.append(wht)
flg_list.append(flg)
pcProc.run(img_list, wht_list, flg_list, ccd_ids, dir_pcref, 2.0, pm_correct=True, wcs_refine=True, plot=True)
pcProc.cleanup()
"""
pcProc = CsstProcMscPositionCalibration()
pcProc.prepare(dm)
......@@ -120,13 +136,13 @@ def do_one_exposure(ver_sim="C5.1", dir_l0="", dir_l1="", dir_pcref="", path_aux
img_list, dir_l1
"""
# Step 3. Calibrate Flux
fcProc = CsstProcFluxCalibration()
# fcProc.prepare()
fcProc.run(
fn_list, img_list, wht_list, flg_list, wcsdir=dir_l1, L1dir=dir_l1, workdir=dir_l1, refdir=dir_l0,
addhead=True, morehead=False, plot=False, nodel=False, update=False, upcat=True)
fcProc.cleanup(fn_list, dir_l1)
## Step 3. Calibrate Flux
#fcProc = CsstProcFluxCalibration()
## fcProc.prepare()
#fcProc.run(
#fn_list, img_list, wht_list, flg_list, wcsdir=dir_l1, L1dir=dir_l1, workdir=dir_l1, refdir=dir_l0,
#addhead=True, morehead=False, plot=False, nodel=False, update=False, upcat=True)
#fcProc.cleanup(fn_list, dir_l1)
"""
fcProc = CsstProcFluxCalibration()
......
csst/msc/pipeline.py~ 0 → 100644
View file @ 1e880aca
import glob
import os
from csst.msc.backbone import CCD_ID_LIST, VER_SIMS
from csst.msc.calib_flux import CsstProcFluxCalibration
from csst.msc.calib_pos import CsstProcMscPositionCalibration
from csst.msc.data import CsstMscImgData
from csst.msc.inst_corr import CsstMscInstrumentProc
from csst.msc.phot import CsstMscPhotometryProc
from csst.msc.data_manager import CsstMscDataManager
CONFIG_DANDELION = dict(
# test and working directory
dir_l0="/home/csstpipeline/L1Pipeline/msc/MSC_0000020",
dir_l1="/home/csstpipeline/L1Pipeline/msc/work/",
# on Dandelion
path_aux="/home/csstpipeline/L1Pipeline/msc/ref/MSC_{}_*_{:02d}_combine.fits",
# gaia catalog directory (for position calibration)
dir_pcref="/home/csstpipeline/L1Pipeline/msc/gaia_dr3/",
# version of simulation data
ver_sim="C3",
# only 18 cores available in cloud machine from PMO
n_jobs=18,
# shut down backend multithreading
backend_multithreading=False
)
CONFIG_PMO = dict(
# test and working directory
dir_l0="/share/simudata/CSSOSDataProductsSims/data/CSSTSimImage_C5/NGP_AstrometryON_shearOFF/MSC_0000100",
dir_l1="/home/user/L1Pipeline/msc/work/",
# on PMO
path_aux="/data/sim_data/MSC_0000100/ref/MSC_{}_*_{:02d}_combine.fits",
# gaia catalog directory (for position calibration)
dir_pcref="/home/user/L1Pipeline/msc/gaia_dr3/",
# version of simulation data
ver_sim="C5.1",
# only 18 cores available in cloud machine from PMO
n_jobs=18,
# shut down backend multithreading
backend_multithreading=False
)
def do_one_exposure(ver_sim="C5.1", dir_l0="", dir_l1="", dir_pcref="", path_aux="", ccd_ids=None,
n_jobs=18, backend_multithreading=False):
# currently C3 and C5.1 are tested
try:
assert ver_sim in VER_SIMS
except AssertionError as ae:
print("Available options for ver_sim: ", VER_SIMS)
raise ae
# shut down backend multi-threading
if not backend_multithreading:
# prohibit multi-threading in backend
os.environ["MKL_NUM_THREADS"] = '1'
os.environ["NUMEXPR_NUM_THREADS"] = '1'
os.environ["OMP_NUM_THREADS"] = '1'
# set paths
dm = CsstMscDataManager(ver_sim=ver_sim, dir_l0=dir_l0, dir_l1=dir_l1, dir_pcref=dir_pcref, path_aux=path_aux)
# request for ccd_ids
ccd_ids = dm.get_ccd_ids(ccd_ids)
# Step 1. Correct instrumental effect
os.chdir(dir_l1)
img_list = []
wht_list = []
flg_list = []
fn_list = []
for this_ccd_id in ccd_ids:
print("processing CCD {}".format(this_ccd_id))
fp_raw = dm.l0_sci(ccd_id=this_ccd_id)
# read data with CsstMscImgData.read
raw = CsstMscImgData.read(fp_raw)
# in the future, use get_* functions grab
bias = dm.get_bias(this_ccd_id)
dark = dm.get_dark(this_ccd_id)
flat = dm.get_flat(this_ccd_id)
# initialize Instrument Processor
instProc = CsstMscInstrumentProc()
instProc.prepare(n_jobs=n_jobs)
img, wht, flg = instProc.run(raw, bias, dark, flat, ver_sim)
instProc.cleanup()
fp_img = img[0].header["FILENAME"] + '.fits'
# save img, wht, flg to somewhere
img.writeto(dm.l1_sci(ccd_id=this_ccd_id, suffix="img", ext="fits"), overwrite=True)
wht.writeto(dm.l1_sci(ccd_id=this_ccd_id, suffix="wht", ext="fits"), overwrite=True)
flg.writeto(dm.l1_sci(ccd_id=this_ccd_id, suffix="flg", ext="fits"), overwrite=True)
# save header
img[1].header.tofile(dm.l1_sci(ccd_id=this_ccd_id, suffix="img", ext="head"), overwrite=True)
# append img, wht, flg list
img_list.append(img)
wht_list.append(wht)
flg_list.append(flg)
fn_list.append(fp_img)
# Step 2. Calibrate Position
pcProc = CsstProcMscPositionCalibration()
pcProc.prepare(dm)
if (img_list):
pcProc.run(img_list, wht_list, flg_list, ccd_ids, dir_pcref, 2.0, pm_correct=True, wcs_refine=True, plot=True)
else:
for this_ccd_id in ccd_ids:
fp_img = dm.l1_sci(ccd_id=this_ccd_id, suffix="img",ext="fits")
fp_wht = dm.l1_sci(ccd_id=this_ccd_id, suffix="wht",ext="fits")
fp_flg = dm.l1_sci(ccd_id=this_ccd_id, suffix="flg",ext="fits")
img = CsstMscImgData.read(fp_img)
wht = CsstMscImgData.read(fp_wht)
flg = CsstMscImgData.read(fp_flg)
img_list.append(img)
wht_list.append(wht)
flg_list.append(flg)
pcProc.run(img_list, wht_list, flg_list, ccd_ids, dir_pcref, 2.0, pm_correct=True, wcs_refine=True, plot=True)
pcProc.cleanup()
"""
pcProc = CsstProcMscPositionCalibration()
pcProc.prepare(dm)
pcProc.run(2.0)
pcProc.cleanup()
get these parameters from dm.l1_sci(*):
img_list, wht_list, flg_list, fn_list, dir_pcref, dir_l1
img_list, dir_l1
"""
## Step 3. Calibrate Flux
#fcProc = CsstProcFluxCalibration()
## fcProc.prepare()
#fcProc.run(
#fn_list, img_list, wht_list, flg_list, wcsdir=dir_l1, L1dir=dir_l1, workdir=dir_l1, refdir=dir_l0,
#addhead=True, morehead=False, plot=False, nodel=False, update=False, upcat=True)
#fcProc.cleanup(fn_list, dir_l1)
"""
fcProc = CsstProcFluxCalibration()
fcProc.prepare(dm)
fcProc.run(addhead=True, morehead=False, plot=False, nodel=False, update=False, upcat=True)
fcProc.cleanup()
get these parameters from dm.l1_sci(*):
fn_list, img_list, wht_list, flg_list, wcsdir=dir_l1, L1dir=dir_l1, workdir=dir_l1, refdir=dir_l0,
fn_list, dir_l1
"""
# Step 4. Photometry
# ptProc = CsstMscPhotometryProc()
# ptProc.prepare()
# ptProc.run(fn_list, out_dir=dir_l1, n_jobs=n_jobs)
# ptProc.cleanup()
return
if __name__ == "__main__":
# identify where you are
HOSTNAME = os.uname()[1]
# you have to run this pipeline in some well-defined servers
assert HOSTNAME in ["ubuntu", "Dandelion"]
# get config parameters
if HOSTNAME == "ubuntu":
config = CONFIG_PMO
elif HOSTNAME == "Dandelion":
config = CONFIG_DANDELION
else:
raise ValueError("HOSTNAME {} not known!".format(HOSTNAME))
# process this exposure
do_one_exposure(**config)
for k, v in config.items():
eval("{}=config[\"{}\"]".format(k, k))
csst/msc/pos_calib_config/default2.scamp → csst/msc/pos_calib_config/csst.scamp
View file @ 1e880aca
......@@ -56,12 +56,12 @@ FIXFOCALPLANE_NMIN 1 # Min number of dets for FIX_FOCALPLANE
#---------------------------- Cross-identification ----------------------------
CROSSID_RADIUS 2.0 # Cross-id initial radius (arcsec)
CROSSID_RADIUS 1.0 # Cross-id initial radius (arcsec)
#---------------------------- Astrometric solution ----------------------------
SOLVE_ASTROM Y # Compute astrometric solution (Y/N) ?
PROJECTION_TYPE TAN # SAME, TPV or TAN
PROJECTION_TYPE TPV # SAME, TPV or TAN
ASTRINSTRU_KEY FILTER,QRUNID # FITS keyword(s) defining the astrom
STABILITY_TYPE EXPOSURE # EXPOSURE, PRE-DISTORTED or INSTRUMENT
CENTROID_KEYS XWIN_IMAGE,YWIN_IMAGE # Cat. parameters for centroiding
......@@ -69,8 +69,8 @@ CENTROIDERR_KEYS ERRAWIN_IMAGE,ERRBWIN_IMAGE,ERRTHETAWIN_IMAGE
# Cat. params for centroid err ellipse
DISTORT_KEYS XWIN_IMAGE,YWIN_IMAGE # Cat. parameters or FITS keywords
DISTORT_GROUPS 1,1 # Polynom group for each context key
DISTORT_DEGREES 2 # Polynom degree for each group
FOCDISTORT_DEGREE 1 # Polynom degree for focal plane coords
DISTORT_DEGREES 3 # Polynom degree for each group
FOCDISTORT_DEGREE 3 # Polynom degree for focal plane coords
ASTREF_WEIGHT 1000000.0 # Relative weight of ref.astrom.ca
ASTRACCURACY_TYPE SIGMA-PIXEL # SIGMA-PIXEL, SIGMA-ARCSEC,
# or TURBULENCE-ARCSEC
......
csst/msc/pos_calib_config/csst.scamp~ 0 → 100644
View file @ 1e880aca
# Default configuration file for SCAMP 2.0.4
# EB 2016-11-04
#
#----------------------------- Field grouping ---------------------------------
FGROUP_RADIUS 2.0 # Max dist (deg) between field groups
#---------------------------- Reference catalogs ------------------------------
REF_SERVER cocat1.u-strasbg.fr # Internet addresses of catalog servers
REF_PORT 80 # Ports to connect to catalog servers
CDSCLIENT_EXEC aclient_cgi # CDSclient executable
ASTREF_CATALOG FILE # NONE, FILE, USNO-A1,USNO-A2,USNO-B1,
# GSC-1.3,GSC-2.2,GSC-2.3,
# TYCHO-2, UCAC-1,UCAC-2,UCAC-3,UCAC-4,
# NOMAD-1, PPMX, CMC-14, 2MASS, DENIS-3,
# SDSS-R3,SDSS-R5,SDSS-R6,SDSS-R7,
# SDSS-R8, SDSS-R9
ASTREF_BAND DEFAULT # Photom. band for astr.ref.magnitudes
# or DEFAULT, BLUEST, or REDDEST
ASTREFCAT_NAME ref.cat # Local astrometric reference catalogs
ASTREFCENT_KEYS X_WORLD,Y_WORLD # Local ref.cat. centroid parameters
ASTREFERR_KEYS ERRA_WORLD, ERRB_WORLD , ERRTHETA_WORLD
# Local ref.cat. err. ellipse params
ASTREFMAG_KEY MAG # Local ref.cat. magnitude parameter
ASTREFMAGERR_KEY MAGERR # Local ref.cat. mag. error parameter
ASTREFOBSDATE_KEY OBSDATE # Local ref.cat. obs. date parameter
ASTREFMAG_LIMITS -99,99 # Select magnitude range in ASTREF_BAND
SAVE_REFCATALOG Y # Save ref catalogs in FITS-LDAC format?
REFOUT_CATPATH ./ # Save path for reference catalogs
#--------------------------- Merged output catalogs ---------------------------
MERGEDOUTCAT_TYPE FITS_LDAC # NONE, ASCII_HEAD, ASCII, FITS_LDAC
MERGEDOUTCAT_NAME merged.cat # Merged output catalog filename
#--------------------------- Full output catalogs ---------------------------
FULLOUTCAT_TYPE FITS_LDAC # NONE, ASCII_HEAD, ASCII, FITS_LDAC
FULLOUTCAT_NAME full.cat # Full output catalog filename
#----------------------------- Pattern matching -------------------------------
MATCH Y # Do pattern-matching (Y/N) ?
MATCH_NMAX 0 # Max.number of detections for MATCHing
# (0=auto)
PIXSCALE_MAXERR 2.0 # Max scale-factor uncertainty
POSANGLE_MAXERR 2.0 # Max position-angle uncertainty (deg)
POSITION_MAXERR 2.0 # Max positional uncertainty (arcmin)
MATCH_RESOL 0 # Matching resolution (arcsec); 0=auto
MATCH_FLIPPED Y # Allow matching with flipped axes?
MOSAIC_TYPE FIX_FOCALPLANE # UNCHANGED, SAME_CRVAL, SHARE_PROJAXIS,
# FIX_FOCALPLANE or LOOSE
FIXFOCALPLANE_NMIN 1 # Min number of dets for FIX_FOCALPLANE
#---------------------------- Cross-identification ----------------------------
CROSSID_RADIUS 1.0 # Cross-id initial radius (arcsec)
#---------------------------- Astrometric solution ----------------------------
SOLVE_ASTROM Y # Compute astrometric solution (Y/N) ?
PROJECTION_TYPE TPV # SAME, TPV or TAN
ASTRINSTRU_KEY FILTER,QRUNID # FITS keyword(s) defining the astrom
STABILITY_TYPE EXPOSURE # EXPOSURE, PRE-DISTORTED or INSTRUMENT
CENTROID_KEYS XWIN_IMAGE,YWIN_IMAGE # Cat. parameters for centroiding
CENTROIDERR_KEYS ERRAWIN_IMAGE,ERRBWIN_IMAGE,ERRTHETAWIN_IMAGE
# Cat. params for centroid err ellipse
DISTORT_KEYS XWIN_IMAGE,YWIN_IMAGE # Cat. parameters or FITS keywords
DISTORT_GROUPS 1,1 # Polynom group for each context key
DISTORT_DEGREES 3 # Polynom degree for each group
FOCDISTORT_DEGREE 3 # Polynom degree for focal plane coords
ASTREF_WEIGHT 1000000.0 # Relative weight of ref.astrom.ca
ASTRACCURACY_TYPE SIGMA-PIXEL # SIGMA-PIXEL, SIGMA-ARCSEC,
# or TURBULENCE-ARCSEC
ASTRACCURACY_KEY ASTRACCU # FITS keyword for ASTR_ACCURACY param.
ASTR_ACCURACY 0.00000001 # Astrom. uncertainty floor parameter
ASTRCLIP_NSIGMA 3 # Astrom. clipping threshold in sigmas
COMPUTE_PARALLAXES N # Compute trigonom. parallaxes (Y/N)?
COMPUTE_PROPERMOTIONS N # Compute proper motions (Y/N)?
CORRECT_COLOURSHIFTS N # Correct for colour shifts (Y/N)?
INCLUDE_ASTREFCATALOG N # Include ref.cat in prop.motions (Y/N)?
ASTR_FLAGSMASK 0x00fc # Astrometry rejection mask on SEx FLAGS
ASTR_IMAFLAGSMASK 0x0 # Astrometry rejection mask on IMAFLAGS
#---------------------------- Photometric solution ----------------------------
SOLVE_PHOTOM Y # Compute photometric solution (Y/N) ?
MAGZERO_OUT 0.0 # Magnitude zero-point(s) in output
MAGZERO_INTERR 0.01 # Internal mag.zero-point accuracy
MAGZERO_REFERR 0.03 # Photom.field mag.zero-point accuracy
PHOTINSTRU_KEY FILTER # FITS keyword(s) defining the photom.
MAGZERO_KEY PHOT_C # FITS keyword for the mag zero-point
EXPOTIME_KEY EXPTIME # FITS keyword for the exposure time (s)
AIRMASS_KEY AIRMASS # FITS keyword for the airmass
EXTINCT_KEY PHOT_K # FITS keyword for the extinction coeff
PHOTOMFLAG_KEY PHOTFLAG # FITS keyword for the photometry flag
PHOTFLUX_KEY FLUX_AUTO # Catalog param. for the flux measurement
PHOTFLUXERR_KEY FLUXERR_AUTO # Catalog parameter for the flux error
PHOTCLIP_NSIGMA 3.0 # Photom.clipping threshold in sigmas
PHOT_ACCURACY 1e-3 # Photometric uncertainty floor (frac.)
PHOT_FLAGSMASK 0x00fc # Photometry rejection mask on SEx FLAGS
PHOT_IMAFLAGSMASK 0x0 # Photometry rejection mask on IMAFLAGS
#------------------------------- Check-plots ----------------------------------
CHECKPLOT_CKEY SCAMPCOL # FITS keyword for PLPLOT field colour
CHECKPLOT_DEV PS # NULL, XWIN, TK, PS, PSC, XFIG, PNG,
# JPEG, AQT, PDF or SVG
CHECKPLOT_RES 0 # Check-plot resolution (0 = default)
CHECKPLOT_ANTIALIAS Y # Anti-aliasing using convert (Y/N) ?
CHECKPLOT_TYPE FGROUPS,DISTORTION,ASTR_INTERROR2D,ASTR_INTERROR1D,ASTR_REFERROR2D,ASTR_REFERROR1D,ASTR_CHI2,PHOT_ERROR
CHECKPLOT_NAME fgroups,distort,astr_interror2d,astr_interror1d,astr_referror2d,astr_referror1d,astr_chi2,psphot_error # Check-plot filename(s)
#------------------------------- Check-images ---------------------------------
CHECKIMAGE_TYPE AS_PAIR # NONE, AS_PAIR, AS_REFPAIR, or AS_XCORR
CHECKIMAGE_NAME check.fits # Check-image filename(s)
#------------------------------ Miscellaneous ---------------------------------
SN_THRESHOLDS 10.0,100.0 # S/N thresholds (in sigmas) for all and
# high-SN sample
FWHM_THRESHOLDS 0.0,100.0 # FWHM thresholds (in pixels) for sources
ELLIPTICITY_MAX 0.5 # Max. source ellipticity
FLAGS_MASK 0x00f0 # Global rejection mask on SEx FLAGS
WEIGHTFLAGS_MASK 0x00ff # Global rejec. mask on SEx FLAGS_WEIGHT
IMAFLAGS_MASK 0x0 # Global rejec. mask on SEx IMAFLAGS_ISO
AHEADER_GLOBAL scamp.abcdhead # Filename of the global INPUT header
AHEADER_SUFFIX .ahead # Filename extension for additional
# INPUT headers
HEADER_SUFFIX .head # Filename extension for OUTPUT headers
HEADER_TYPE NORMAL # NORMAL or FOCAL_PLANE
VERBOSE_TYPE NORMAL # QUIET, NORMAL, LOG or FULL
WRITE_XML N # Write XML file (Y/N)?
XML_NAME scamp.xml # Filename for XML output
XSL_URL file:///usr/local/share/scamp/scamp.xsl
# Filename for XSL style-sheet
NTHREADS 0 # Number of simultaneous threads for
# the SMP version of SCAMP
# 0 = automatic
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