add a test run case

Catalog/fd_test_C6.py

+import os
+import galsim
+import random
+import numpy as np
+import h5py as h5
+import healpy as hp
+import astropy.constants as cons
+import traceback
+from astropy.coordinates import spherical_to_cartesian
+from astropy.table import Table
+from scipy import interpolate
+from datetime import datetime
+
+from ObservationSim.MockObject import CatalogBase, Star, Galaxy, Quasar
+from ObservationSim.MockObject._util import tag_sed, getObservedSED, getABMAG, integrate_sed_bandpass, comoving_dist
+from ObservationSim.Astrometry.Astrometry_util import on_orbit_obs_position
+
+# (TEST)
+from astropy.cosmology import FlatLambdaCDM
+from astropy import constants
+from astropy import units as U
+
+try:
+    import importlib.resources as pkg_resources
+except ImportError:
+    # Try backported to PY<37 'importlib_resources'
+    import importlib_resources as pkg_resources
+
+NSIDE = 128
+
+def get_bundleIndex(healpixID_ring, bundleOrder=4, healpixOrder=7):
+    assert NSIDE == 2**healpixOrder
+    shift = healpixOrder - bundleOrder
+    shift = 2*shift
+
+    nside_bundle = 2**bundleOrder
+    nside_healpix= 2**healpixOrder
+
+    healpixID_nest= hp.ring2nest(nside_healpix, healpixID_ring)
+    bundleID_nest = (healpixID_nest >> shift)
+    bundleID_ring = hp.nest2ring(nside_bundle, bundleID_nest)
+
+    return bundleID_ring
+
+class Catalog(CatalogBase):
+    def __init__(self, config, chip, pointing, chip_output, filt, **kwargs):
+        super().__init__()
+        self.cat_dir = os.path.join(config["data_dir"], config["catalog_options"]["input_path"]["cat_dir"])
+        self.seed_Av = config["catalog_options"]["seed_Av"]
+
+        self.cosmo = FlatLambdaCDM(H0=67.66, Om0=0.3111)
+
+        self.chip_output = chip_output
+        self.filt = filt
+        self.logger = chip_output.logger
+
+        with pkg_resources.path('Catalog.data', 'SLOAN_SDSS.g.fits') as filter_path:
+            self.normF_star = Table.read(str(filter_path))
+        
+        self.config = config
+        self.chip = chip
+        self.pointing = pointing
+
+        self.max_size = 0.
+
+        if "star_cat" in config["catalog_options"]["input_path"] and config["catalog_options"]["input_path"]["star_cat"] and not config["catalog_options"]["galaxy_only"]:
+            star_file = config["catalog_options"]["input_path"]["star_cat"]
+            star_SED_file = config["catalog_options"]["SED_templates_path"]["star_SED"]
+            self.star_path = os.path.join(self.cat_dir, star_file)
+            self.star_SED_path = os.path.join(config["data_dir"], star_SED_file)
+            self._load_SED_lib_star()
+        if "galaxy_cat" in config["catalog_options"]["input_path"] and config["catalog_options"]["input_path"]["galaxy_cat"] and not config["catalog_options"]["star_only"]:
+            galaxy_dir = config["catalog_options"]["input_path"]["galaxy_cat"]
+            self.galaxy_path = os.path.join(self.cat_dir, galaxy_dir)
+            self.galaxy_SED_path = os.path.join(config["data_dir"], config["catalog_options"]["SED_templates_path"]["galaxy_SED"])
+            self._load_SED_lib_gals()
+
+        if "AGN_cat" in config["catalog_options"]["input_path"] and config["catalog_options"]["input_path"]["AGN_cat"] and not config["catalog_options"]["star_only"]:
+            AGN_dir = config["catalog_options"]["input_path"]["AGN_cat"]
+            self.AGN_path = os.path.join(config["data_dir"], config["catalog_options"]["input_path"]["AGN_cat"])
+            self.AGN_SED_path = os.path.join(config["data_dir"], config["catalog_options"]["SED_templates_path"]["AGN_SED"])
+            self.AGN_SED_wave_path = os.path.join(config['data_dir'], config["catalog_options"]["SED_templates_path"]["AGN_SED_WAVE"])
+            self._load_SED_lib_AGN()
+
+        if "rotateEll" in config["catalog_options"]:
+            self.rotation = float(int(config["catalog_options"]["rotateEll"]/45.))
+        else:
+            self.rotation = 0.
+
+        # Update output .cat header with catalog specific output columns
+        self._add_output_columns_header()
+
+        self._get_healpix_list()
+        self._load()
+    
+    def _add_output_columns_header(self):
+        self.add_hdr = " model_tag teff logg feh"
+        self.add_hdr += " bulgemass diskmass detA e1 e2 kappa g1 g2 size galType veldisp "
+
+        self.add_fmt = " %10s %8.4f %8.4f %8.4f"
+        self.add_fmt += " %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %4d %8.4f "
+        self.chip_output.update_ouptut_header(additional_column_names=self.add_hdr)
+
+    def _get_healpix_list(self):
+        self.sky_coverage = self.chip.getSkyCoverageEnlarged(self.chip.img.wcs, margin=0.2)
+        ra_min, ra_max, dec_min, dec_max = self.sky_coverage.xmin, self.sky_coverage.xmax, self.sky_coverage.ymin, self.sky_coverage.ymax
+        ra = np.deg2rad(np.array([ra_min, ra_max, ra_max, ra_min]))
+        dec = np.deg2rad(np.array([dec_max, dec_max, dec_min, dec_min]))
+        # vertices = spherical_to_cartesian(1., dec, ra)
+        self.pix_list = hp.query_polygon(
+            NSIDE,
+            hp.ang2vec(np.radians(90.) - dec, ra),
+            inclusive=True
+        )
+        if self.logger is not None:
+            msg = str(("HEALPix List: ", self.pix_list))
+            self.logger.info(msg)
+        else:
+            print("HEALPix List: ", self.pix_list)
+
+    def load_norm_filt(self, obj):
+        if obj.type == "star":
+            return self.normF_star
+        elif obj.type == "galaxy" or obj.type == "quasar":
+            # return self.normF_galaxy
+            return None
+        else:
+            return None
+
+    def _load_SED_lib_star(self):
+        self.tempSED_star = h5.File(self.star_SED_path,'r')
+
+    def _load_SED_lib_gals(self):
+        pcs = h5.File(os.path.join(self.galaxy_SED_path, "pcs.h5"), "r")
+        lamb = h5.File(os.path.join(self.galaxy_SED_path, "lamb.h5"), "r")
+        self.lamb_gal = lamb['lamb'][()]
+        self.pcs = pcs['pcs'][()]
+
+    def _load_SED_lib_AGN(self):
+        from astropy.io import fits
+        self.SED_AGN = fits.open(self.AGN_SED_path)[0].data
+        self.lamb_AGN = np.load(self.AGN_SED_wave_path)
+
+
+    def _load_gals(self, gals, pix_id=None, cat_id=0):
+        ngals = len(gals['ra'])
+
+        # Apply astrometric modeling
+        # in C3 case only aberration
+        ra_arr = gals['ra'][:]
+        dec_arr = gals['dec'][:]
+        if self.config["obs_setting"]["enable_astrometric_model"]:
+            ra_list = ra_arr.tolist()
+            dec_list = dec_arr.tolist()
+            pmra_list = np.zeros(ngals).tolist()
+            pmdec_list = np.zeros(ngals).tolist()
+            rv_list = np.zeros(ngals).tolist()
+            parallax_list = [1e-9] * ngals
+            dt = datetime.utcfromtimestamp(self.pointing.timestamp)
+            date_str = dt.date().isoformat()
+            time_str = dt.time().isoformat()
+            ra_arr, dec_arr = on_orbit_obs_position(
+                input_ra_list=ra_list,
+                input_dec_list=dec_list,
+                input_pmra_list=pmra_list,
+                input_pmdec_list=pmdec_list,
+                input_rv_list=rv_list,
+                input_parallax_list=parallax_list,
+                input_nstars=ngals,
+                input_x=self.pointing.sat_x,
+                input_y=self.pointing.sat_y,
+                input_z=self.pointing.sat_z,
+                input_vx=self.pointing.sat_vx,
+                input_vy=self.pointing.sat_vy,
+                input_vz=self.pointing.sat_vz,
+                input_epoch="J2000",
+                input_date_str=date_str,
+                input_time_str=time_str
+            )
+
+        # for igals in range(ngals):
+        for igals in range(0, ngals, 5):
+            # # (TEST)
+            # if igals > 1000:
+            #     break
+            
+            param = self.initialize_param()
+            param['ra'] = ra_arr[igals]
+            param['dec'] = dec_arr[igals]
+            param['ra_orig'] = gals['ra'][igals]
+            param['dec_orig'] = gals['dec'][igals]
+            # param['mag_use_normal'] = gals['mag_csst_%s'%(self.filt.filter_type)][igals]
+            param['mag_use_normal'] = 20.
+            if self.filt.is_too_dim(mag=param['mag_use_normal'], margin=self.config["obs_setting"]["mag_lim_margin"]):
+                continue
+
+            param['z'] = gals['redshift'][igals]
+            param['model_tag'] = 'None'
+            # param['g1'] = gals['shear'][igals][0]
+            # param['g2'] = gals['shear'][igals][1]
+            param['g1'] = 0.
+            param['g2'] = 0.
+            param['kappa'] = gals['kappa'][igals]
+            param['e1'] = gals['ellipticity_true'][igals][0]
+            param['e2'] = gals['ellipticity_true'][igals][1]
+            
+            # For shape calculation
+            
+            param['ell_total'] = np.sqrt(param['e1']**2 + param['e2']**2)
+            if param['ell_total'] > 0.9:
+                continue
+            # param['e1_disk'] = param['e1']
+            # param['e2_disk'] = param['e2']
+            # param['e1_bulge'] = param['e1']
+            # param['e2_bulge'] = param['e2']
+            param['e1_disk'] = 0.
+            param['e2_disk'] = 0.
+            param['e1_bulge'] = 0.
+            param['e2_bulge'] = 0.
+
+
+            param['delta_ra'] = 0
+            param['delta_dec'] = 0
+
+            # Masses
+            param['bulgemass'] = gals['bulgemass'][igals]
+            param['diskmass'] = gals['diskmass'][igals]
+
+            # param['size'] = gals['size'][igals]
+            param['size'] = 1.
+            if param['size'] > self.max_size:
+                self.max_size = param['size']
+
+            # Sersic index
+            param['disk_sersic_idx'] = 1.
+            param['bulge_sersic_idx'] = 4.
+
+            # Sizes
+            # param['bfrac'] = param['bulgemass']/(param['bulgemass'] + param['diskmass'])
+            param['bfrac'] = 0.
+            if param['bfrac'] >= 0.6:
+                param['hlr_bulge'] = param['size']
+                param['hlr_disk'] = param['size'] * (1. - param['bfrac'])
+            else:
+                param['hlr_disk'] = param['size']
+                param['hlr_bulge'] = param['size'] * param['bfrac']
+
+            # SED coefficients
+            param['coeff'] = gals['coeff'][igals]
+            param['detA'] = gals['detA'][igals]
+
+            # Others
+            param['galType'] = gals['type'][igals]
+            param['veldisp'] = gals['veldisp'][igals]
+            
+            # TEST no redening and no extinction
+            param['av'] = 0.0
+            param['redden'] = 0
+
+            param['star'] = 0   # Galaxy
+
+            # NOTE: this cut cannot be put before the SED type has been assigned
+            if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
+                continue
+
+            # TEMP
+            self.ids += 1
+            # param['id'] = self.ids
+            param['id'] = '%06d'%(int(pix_id)) + '%06d'%(cat_id) + '%08d'%(igals)
+            
+            if param['star'] == 0:
+                obj = Galaxy(param, self.rotation, logger=self.logger)
+            
+            # Need to deal with additional output columns
+            obj.additional_output_str = self.add_fmt%("n", 0., 0., 0.,
+                                                    param['bulgemass'], param['diskmass'], param['detA'],
+                                                    param['e1'], param['e2'], param['kappa'], param['g1'], param['g2'], param['size'],
+                                                    param['galType'], param['veldisp'])
+            
+            self.objs.append(obj)
+
+    def _load_stars(self, stars, pix_id=None):
+        nstars = len(stars['sourceID'])
+        # Apply astrometric modeling
+        ra_arr = stars["RA"][:]
+        dec_arr = stars["Dec"][:]
+        pmra_arr = stars['pmra'][:]
+        pmdec_arr = stars['pmdec'][:]
+        rv_arr = stars['RV'][:]
+        parallax_arr = stars['parallax'][:]
+        if self.config["obs_setting"]["enable_astrometric_model"]:
+            ra_list = ra_arr.tolist()
+            dec_list = dec_arr.tolist()
+            pmra_list = pmra_arr.tolist()
+            pmdec_list = pmdec_arr.tolist()
+            rv_list = rv_arr.tolist()
+            parallax_list = parallax_arr.tolist()
+            dt = datetime.utcfromtimestamp(self.pointing.timestamp)
+            date_str = dt.date().isoformat()
+            time_str = dt.time().isoformat()
+            ra_arr, dec_arr = on_orbit_obs_position(
+                input_ra_list=ra_list,
+                input_dec_list=dec_list,
+                input_pmra_list=pmra_list,
+                input_pmdec_list=pmdec_list,
+                input_rv_list=rv_list,
+                input_parallax_list=parallax_list,
+                input_nstars=nstars,
+                input_x=self.pointing.sat_x,
+                input_y=self.pointing.sat_y,
+                input_z=self.pointing.sat_z,
+                input_vx=self.pointing.sat_vx,
+                input_vy=self.pointing.sat_vy,
+                input_vz=self.pointing.sat_vz,
+                input_epoch="J2000",
+                input_date_str=date_str,
+                input_time_str=time_str
+            )
+        for istars in range(nstars):
+            # # (TEST)
+            # if istars > 100:
+            #     break
+
+            param = self.initialize_param()
+            param['ra'] = ra_arr[istars]
+            param['dec'] = dec_arr[istars]
+            param['ra_orig'] = stars["RA"][istars]
+            param['dec_orig'] = stars["Dec"][istars]
+            param['pmra'] = pmra_arr[istars]
+            param['pmdec'] = pmdec_arr[istars]
+            param['rv'] = rv_arr[istars]
+            param['parallax'] = parallax_arr[istars]
+            if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
+                continue
+            param['mag_use_normal'] = stars['app_sdss_g'][istars]
+            # if param['mag_use_normal'] >= 26.5:
+            #     continue
+            self.ids += 1
+            param['id'] = stars['sourceID'][istars]
+            param['sed_type'] = stars['sourceID'][istars]
+            param['model_tag'] = stars['model_tag'][istars]
+            param['teff'] = stars['teff'][istars]
+            param['logg'] = stars['grav'][istars]
+            param['feh'] = stars['feh'][istars]
+            param['z'] = 0.0
+            param['star'] = 1   # Star
+            obj = Star(param, logger=self.logger)
+
+            # Append additional output columns to the .cat file
+            obj.additional_output_str = self.add_fmt%(param["model_tag"], param['teff'], param['logg'], param['feh'],
+                                                    0., 0., 0., 0., 0., 0., 0., 0., 0., -1, 0.)
+
+            self.objs.append(obj)
+
+    def _load_AGNs(self):
+        data = Table.read(self.AGN_path)
+        ra_arr = data['ra']
+        dec_arr = data['dec']
+        nAGNs = len(data)
+        if self.config["obs_setting"]["enable_astrometric_model"]:
+            ra_list = ra_arr.tolist()
+            dec_list = dec_arr.tolist()
+            pmra_list = np.zeros(nAGNs).tolist()
+            pmdec_list = np.zeros(nAGNs).tolist()
+            rv_list = np.zeros(nAGNs).tolist()
+            parallax_list = [1e-9] * nAGNs
+            dt = datetime.utcfromtimestamp(self.pointing.timestamp)
+            date_str = dt.date().isoformat()
+            time_str = dt.time().isoformat()
+            ra_arr, dec_arr = on_orbit_obs_position(
+                input_ra_list=ra_list,
+                input_dec_list=dec_list,
+                input_pmra_list=pmra_list,
+                input_pmdec_list=pmdec_list,
+                input_rv_list=rv_list,
+                input_parallax_list=parallax_list,
+                input_nstars=nAGNs,
+                input_x=self.pointing.sat_x,
+                input_y=self.pointing.sat_y,
+                input_z=self.pointing.sat_z,
+                input_vx=self.pointing.sat_vx,
+                input_vy=self.pointing.sat_vy,
+                input_vz=self.pointing.sat_vz,
+                input_epoch="J2000",
+                input_date_str=date_str,
+                input_time_str=time_str
+            )
+        for iAGNs in range(nAGNs):
+            param = self.initialize_param()
+            param['ra'] = ra_arr[iAGNs]
+            param['dec'] = dec_arr[iAGNs]
+            param['ra_orig'] = data['ra'][iAGNs]
+            param['dec_orig'] = data['dec'][iAGNs]
+            param['z'] = data['z'][iAGNs]
+            param['appMag'] = data['appMag'][iAGNs]
+            param['absMag'] = data['absMag'][iAGNs]
+            
+            # NOTE: this cut cannot be put before the SED type has been assigned
+            if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
+                continue
+
+            # TEST no redening and no extinction
+            param['av'] = 0.0
+            param['redden'] = 0
+
+            param['star'] = 2   # Quasar
+            param['id'] = data['igmlos'][iAGNs]
+
+            if param['star'] == 2:
+                obj = Quasar(param, logger=self.logger)
+
+            # Append additional output columns to the .cat file
+            obj.additional_output_str = self.add_fmt%("n", 0., 0., 0.,
+                                                    0., 0., 0., 0., 0., 0., 0., 0., 0., -1, 0.)
+            self.objs.append(obj)
+
+    def _load(self, **kwargs):
+        self.objs = []
+        self.ids = 0
+        
+        if "star_cat" in self.config["catalog_options"]["input_path"] and self.config["catalog_options"]["input_path"]["star_cat"] and not self.config["catalog_options"]["galaxy_only"]:
+            star_cat = h5.File(self.star_path, 'r')['catalog']
+            for pix in self.pix_list:
+                try:
+                    stars = star_cat[str(pix)]
+                    self._load_stars(stars, pix_id=pix)
+                    del stars
+                except Exception as e:
+                    self.logger.error(str(e))
+                    print(e)
+        
+        if "galaxy_cat" in self.config["catalog_options"]["input_path"] and self.config["catalog_options"]["input_path"]["galaxy_cat"] and not self.config["catalog_options"]["star_only"]:
+            for pix in self.pix_list:
+                try:
+                    bundleID  = get_bundleIndex(pix)
+                    file_path = os.path.join(self.galaxy_path, "galaxies_C6_bundle{:06}.h5".format(bundleID))
+                    gals_cat = h5.File(file_path, 'r')['galaxies']
+                    gals = gals_cat[str(pix)]
+                    self._load_gals(gals, pix_id=pix, cat_id=bundleID)
+                    del gals
+                except Exception as e:
+                    traceback.print_exc()
+                    self.logger.error(str(e))
+                    print(e)
+
+        if "AGN_cat" in self.config["catalog_options"]["input_path"] and self.config["catalog_options"]["input_path"]["AGN_cat"] and not self.config["catalog_options"]["star_only"]:
+            try:
+                self._load_AGNs()
+            except Exception as e:
+                traceback.print_exc()
+                self.logger.error(str(e))
+                print(e)
+
+        if self.logger is not None:
+            self.logger.info("maximum galaxy size: %.4f"%(self.max_size))
+            self.logger.info("number of objects in catalog: %d"%(len(self.objs)))
+        else:
+            print("number of objects in catalog: ", len(self.objs))
+
+    def load_sed(self, obj, **kwargs):
+        if obj.type == 'star':
+            _, wave, flux = tag_sed(
+                h5file=self.tempSED_star,
+                model_tag=obj.param['model_tag'],
+                teff=obj.param['teff'],
+                logg=obj.param['logg'],
+                feh=obj.param['feh']
+            )
+        elif obj.type == 'galaxy' or obj.type == 'quasar':
+            factor = 10**(-.4 * self.cosmo.distmod(obj.z).value)
+            if obj.type == 'galaxy':
+                flux = np.matmul(self.pcs, obj.coeff) * factor
+                #  if np.any(flux < 0):
+                #     raise ValueError("Glaxy %s: negative SED fluxes"%obj.id)
+                flux[flux < 0] = 0.
+                sedcat = np.vstack((self.lamb_gal, flux)).T
+                sed_data = getObservedSED(
+                    sedCat=sedcat,
+                    redshift=obj.z,
+                    av=obj.param["av"],
+                    redden=obj.param["redden"]
+                )
+                wave, flux = sed_data[0], sed_data[1]
+            elif obj.type == 'quasar':
+                flux = self.SED_AGN[int(obj.id)] * 1e-17
+                # if np.any(flux < 0):
+                #     raise ValueError("Glaxy %s: negative SED fluxes"%obj.id)
+                flux[flux < 0] = 0.
+                # sedcat = np.vstack((self.lamb_AGN, flux)).T
+                wave = self.lamb_AGN
+            # print("sed (erg/s/cm2/A) = ", sed_data)
+            # np.savetxt(os.path.join(self.config["work_dir"], "%s_sed.txt"%(obj.id)), sedcat)
+        else:
+            raise ValueError("Object type not known")
+        speci = interpolate.interp1d(wave, flux)
+        lamb = np.arange(2000, 11001+0.5, 0.5)
+        y = speci(lamb)
+        # erg/s/cm2/A --> photon/s/m2/A
+        all_sed = y * lamb / (cons.h.value * cons.c.value) * 1e-13
+        sed = Table(np.array([lamb, all_sed]).T, names=('WAVELENGTH', 'FLUX'))
+        
+        if obj.type == 'quasar':
+            # integrate to get the magnitudes
+            sed_photon = np.array([sed['WAVELENGTH'], sed['FLUX']]).T
+            sed_photon = galsim.LookupTable(x=np.array(sed_photon[:, 0]), f=np.array(sed_photon[:, 1]), interpolant='nearest')
+            sed_photon = galsim.SED(sed_photon, wave_type='A', flux_type='1', fast=False)
+            interFlux = integrate_sed_bandpass(sed=sed_photon, bandpass=self.filt.bandpass_full)
+            obj.param['mag_use_normal'] = getABMAG(interFlux, self.filt.bandpass_full)
+            # if obj.param['mag_use_normal'] >= 30:
+            #     print("obj ID = %d"%obj.id)
+            #     print("mag_use_normal = %.3f"%obj.param['mag_use_normal'])
+            #     print("integrated flux = %.7f"%(interFlux))
+            #     print("app mag = %.3f"%obj.param['appMag'])
+            #     np.savetxt('./AGN_SED_test/sed_objID_%d.txt'%obj.id, np.transpose([self.lamb_AGN, self.SED_AGN[int(obj.id)]]))
+            # print("obj ID = %d"%obj.id)
+            # print("mag_use_normal = %.3f"%obj.param['mag_use_normal'])
+            # print("integrated flux = %.7f"%(interFlux))
+            # print("app mag = %.3f"%obj.param['appMag'])
+            # print("abs mag = %.3f"%obj.param['absMag'])
+            # mag = getABMAG(interFlux, self.filt.bandpass_full)
+            # print("mag diff = %.3f"%(mag - obj.param['mag_use_normal']))
+        del wave
+        del flux
+        return sed

config/test_fd_C6.yaml

+---
+###############################################
+#
+#  Configuration file for CSST simulation
+#  CSST-Sim Group, 2023/04/25
+#
+###############################################
+
+# Base diretories and naming setup
+# Can add some of the command-line arguments here as well;
+# OK to pass either way or both, as long as they are consistent
+work_dir: "/share/home/fangyuedong/sim_v2/csst-simulation/workplace/"
+data_dir: "/share/simudata/CSSOSDataProductsSims/data/"
+run_name: "fd_test_C6_phi_0"
+
+# Whether to use MPI
+run_option:
+  use_mpi: NO
+  # NOTE: "n_threads" paramters is currently not used in the backend
+  # simulation codes. It should be implemented later in the web frontend
+  # in order to config the number of threads to request from NAOC cluster
+  n_threads: 80
+
+  # Output catalog only?
+  # If yes, no imaging simulation will run
+  out_cat_only: NO
+
+###############################################
+# Catalog setting
+###############################################
+# Configure your catalog: options to be implemented 
+# in the corresponding (user defined) 'Catalog' class
+catalog_options:
+  input_path:
+    cat_dir: "Catalog_C6_20221212"
+    star_cat: "C6_MMW_GGC_Astrometry_healpix.hdf5"
+    galaxy_cat: "cat2CSSTSim_bundle/"
+    AGN_cat: "AGN_C6_ross13_rand_pos_rmax-1.3.fits"
+
+  SED_templates_path:
+    star_SED: "Catalog_20210126/SpecLib.hdf5"
+    galaxy_SED: "Catalog_C6_20221212/sedlibs/"
+    AGN_SED: "quickspeclib_ross13.fits"
+    AGN_SED_WAVE: "wave_ross13.npy"
+
+  # Only simulate stars?
+  star_only: NO
+
+  # Only simulate galaxies?
+  galaxy_only: YES
+
+  # rotate galaxy ellipticity
+  rotateEll: 0. # [degree]
+
+  seed_Av: 121212    # Seed for generating random intrinsic extinction
+
+###############################################
+# Observation setting
+###############################################
+obs_setting:
+
+  # Options for survey types:
+  # "Photometric": simulate photometric chips only
+  # "Spectroscopic": simulate slitless spectroscopic chips only
+  # "FGS": simulate FGS chips only (31-42)
+  # "All": simulate full focal plane
+  survey_type: "Photometric"
+  
+  # Exposure time [seconds]
+  exp_time: 150.
+
+  # Observation starting date & time
+  date_obs: "210525" # [yymmdd]
+  time_obs: "120000" # [hhmmss]
+
+  # Default Pointing [degrees]
+  # Note: NOT valid when a pointing list file is specified
+  ra_center: 192.8595
+  dec_center:  27.1283
+  # Image rotation [degree]
+  image_rot: -113.4333
+
+  # (Optional) a file of point list 
+  # if you just want to run default pointing:
+  # - pointing_dir: null
+  # - pointing_file: null
+  pointing_dir: "/share/simudata/CSSOSDataProductsSims/data/"
+  pointing_file: "pointing_radec_246.5_40.dat"
+
+  # Number of calibration pointings
+  np_cal: 0
+
+  # Run specific pointing(s):
+  # - give a list of indexes of pointings: [ip_1, ip_2...]
+  # - run all pointings: null
+  # Note: only valid when a pointing list is specified
+  run_pointings: [0]
+  
+  # Run specific chip(s):
+  # - give a list of indexes of chips: [ip_1, ip_2...]
+  # - run all chips: null
+  # Note: for all pointings
+  run_chips: [9]
+
+  # Whether to enable astrometric modeling
+  enable_astrometric_model: True
+
+  # Cut by saturation magnitude in which band?
+  cut_in_band: "z"
+
+  # saturation magnitude margin
+  mag_sat_margin: -2.5
+
+  # limiting magnitude margin
+  mag_lim_margin: +1.0
+
+###############################################
+# PSF setting
+###############################################
+psf_setting:
+  
+  # Which PSF model to use:
+  # "Gauss": simple gaussian profile
+  # "Interp": Interpolated PSF from sampled ray-tracing data
+  psf_model: "Interp"
+
+  # PSF size [arcseconds]
+  # radius of 80% energy encircled
+  # NOTE: only valid for "Gauss" PSF
+  psf_rcont: 0.15
+
+  # path to PSF data
+  # NOTE: only valid for "Interp" PSF
+  psf_dir: "/share/simudata/CSSOSDataProductsSims/data/psfCube1"
+
+###############################################
+# Shear setting
+###############################################
+
+shear_setting:
+  # Options to generate mock shear field:
+  # "constant": all galaxies are assigned a constant reduced shear
+  # "catalog": from catalog
+  # "extra": from seprate file
+  shear_type: "catalog"
+
+  # For constant shear filed
+  reduced_g1: 0.
+  reduced_g2: 0.
+
+  # Extra shear catalog
+  # (currently not used)
+  # shear_cat: "mockShear.cat"
+
+###############################################
+# Instrumental effects setting
+###############################################
+ins_effects:
+  # switches
+  # Note: bias_16channel, gain_16channel, and shutter_effect
+  # is currently not applicable to "FGS" observations
+  field_dist:     ON  # Whether to add field distortions
+  add_back:       NO  # Whether to add sky background
+  add_dark:       NO  # Whether to add dark noise
+  add_readout:    NO  # Whether to add read-out (Gaussian) noise
+  add_bias:       ON  # Whether to add bias-level to images
+  bias_16channel: NO  # Whether to add different biases for 16 channels
+  gain_16channel: NO  # Whether to make different gains for 16 channels
+  shutter_effect: NO  # Whether to add shutter effect
+  flat_fielding:  ON  # Whether to add flat-fielding effect
+  prnu_effect:    NO  # Whether to add PRNU effect
+  non_linear:     NO  # Whether to add non-linearity
+  cosmic_ray:     NO  # Whether to add cosmic-ray
+  cray_differ:    NO  # Whether to generate different cosmic ray maps CAL and MS output
+  cte_trail:      NO  # Whether to simulate CTE trails
+  saturbloom:     ON  # Whether to simulate Saturation & Blooming
+  add_badcolumns: NO  # Whether to add bad columns
+  add_hotpixels:  NO  # Whether to add hot pixels
+  add_deadpixels: NO  # Whether to add dead(dark) pixels
+  bright_fatter:  NO  # Whether to simulate Brighter-Fatter (also diffusion) effect
+
+  # Values: 
+  # default values have been defined individually for each chip in:
+  # ObservationSim/Instrument/data/ccd/chip_definition.json
+  # Set them here will override the default values
+  # dark_exptime:   300   # Exposure time for dark current frames [seconds]
+  # flat_exptime:   150   # Exposure time for flat-fielding frames [seconds]
+  # readout_time:   40    # The read-out time for each channel [seconds]
+  # df_strength:    2.3   # Sillicon sensor diffusion strength
+  # bias_level:     500   # bias level [e-/pixel]
+  # gain:           1.1   # Gain
+  # full_well:      90000 # Full well depth [e-]
+
+###############################################
+# Output options (for calibration pointings only)
+###############################################
+output_setting:
+  readout16:      OFF # Whether to export as 16 channels (subimages) with pre- and over-scan
+  shutter_output: OFF # Whether to export shutter effect 16-bit image
+  bias_output:    ON  # Whether to export bias frames
+  dark_output:    ON  # Whether to export the combined dark current files
+  flat_output:    ON  # Whether to export the combined flat-fielding files
+  prnu_output:    OFF # Whether to export the PRNU (pixel-to-pixel flat-fielding) files
+  NBias:          1     # Number of bias frames to be exported for each exposure
+  NDark:          1     # Number of dark frames to be exported for each exposure
+  NFlat:          1     # Number of flat frames to be exported for each exposure
+
+###############################################
+# Random seeds
+###############################################
+random_seeds:
+  seed_poisson:         20210601  # Seed for Poisson noise
+  seed_CR:              20210317  # Seed for generating random cosmic ray maps
+  seed_flat:            20210101  # Seed for generating random flat fields
+  seed_prnu:            20210102  # Seed for photo-response non-uniformity
+  seed_gainNonUniform:  20210202  # Seed for gain nonuniformity
+  seed_biasNonUniform:  20210203  # Seed for bias nonuniformity
+  seed_rnNonUniform:    20210204  # Seed for readout-noise nonuniformity
+  seed_badcolumns:      20240309  # Seed for bad columns
+  seed_defective:       20210304  # Seed for defective (bad) pixels
+  seed_readout:         20210601  # Seed for read-out gaussian noise
+...
\ No newline at end of file