Commit 07cee8ad authored by Fang Yuedong's avatar Fang Yuedong
Browse files

1. new C6_50sqdeg.py catalog added. 2. change 'nuv' to 'NUV'

Showing with 696 additions and 8 deletions
+696 -8
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
from astropy.coordinates import SkyCoord
from astropy.io import fits
try:
import importlib.resources as pkg_resources
except ImportError:
# Try backported to PY<37 'importlib_resources'
import importlib_resources as pkg_resources
NSIDE = 128
bundle_file_list = ['galaxies_C6_bundle000199.h5','galaxies_C6_bundle000200.h5','galaxies_C6_bundle000241.h5','galaxies_C6_bundle000242.h5','galaxies_C6_bundle000287.h5','galaxies_C6_bundle000288.h5','galaxies_C6_bundle000714.h5','galaxies_C6_bundle000715.h5','galaxies_C6_bundle000778.h5','galaxies_C6_bundle000779.h5','galaxies_C6_bundle000842.h5','galaxies_C6_bundle000843.h5','galaxies_C6_bundle002046.h5','galaxies_C6_bundle002110.h5','galaxies_C6_bundle002111.h5','galaxies_C6_bundle002173.h5','galaxies_C6_bundle002174.h5','galaxies_C6_bundle002238.h5','galaxies_C6_bundle002596.h5','galaxies_C6_bundle002597.h5','galaxies_C6_bundle002656.h5','galaxies_C6_bundle002657.h5','galaxies_C6_bundle002711.h5','galaxies_C6_bundle002712.h5','galaxies_C6_bundle002844.h5','galaxies_C6_bundle002845.h5','galaxies_C6_bundle002884.h5','galaxies_C6_bundle002885.h5','galaxies_C6_bundle002921.h5','galaxies_C6_bundle002922.h5']
qsosed_file_list = ['quickspeclib_interp1d_run1.fits','quickspeclib_interp1d_run2.fits','quickspeclib_interp1d_run3.fits','quickspeclib_interp1d_run4.fits','quickspeclib_interp1d_run5.fits','quickspeclib_interp1d_run6.fits','quickspeclib_interp1d_run7.fits','quickspeclib_interp1d_run8.fits','quickspeclib_interp1d_run9.fits','quickspeclib_interp1d_run10.fits','quickspeclib_interp1d_run11.fits','quickspeclib_interp1d_run12.fits','quickspeclib_interp1d_run13.fits','quickspeclib_interp1d_run14.fits','quickspeclib_interp1d_run15.fits','quickspeclib_interp1d_run16.fits','quickspeclib_interp1d_run17.fits','quickspeclib_interp1d_run18.fits','quickspeclib_interp1d_run19.fits','quickspeclib_interp1d_run20.fits','quickspeclib_interp1d_run21.fits','quickspeclib_interp1d_run22.fits','quickspeclib_interp1d_run23.fits','quickspeclib_interp1d_run24.fits','quickspeclib_interp1d_run25.fits','quickspeclib_interp1d_run26.fits','quickspeclib_interp1d_run27.fits','quickspeclib_interp1d_run28.fits','quickspeclib_interp1d_run29.fits','quickspeclib_interp1d_run30.fits']
star_file_list = ['C7_Gaia_Galaxia_RA170DECm23_healpix.hdf5', 'C7_Gaia_Galaxia_RA180DECp60_healpix.hdf5', 'C7_Gaia_Galaxia_RA240DECp30_healpix.hdf5', 'C7_Gaia_Galaxia_RA300DECm60_healpix.hdf5', 'C7_Gaia_Galaxia_RA30DECm48_healpix.hdf5']
star_center_list = [(170., -23.), (180., 60.), (240., 30.), (300., -60.), (30., -48.)]
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
def get_agnsed_file(bundle_file_name):
return qsosed_file_list[bundle_file_list.index(bundle_file_name)]
def get_star_cat(ra_pointing, dec_pointing):
pointing_c = SkyCoord(ra=ra_pointing*U.deg, dec=dec_pointing*U.deg)
max_dist = 10
return_star_path = None
for star_file, center in zip(star_file_list, star_center_list):
center_c = SkyCoord(ra=center[0]*U.deg, dec=center[1]*U.deg)
dist = pointing_c.separation(center_c).to(U.deg).value
if dist < max_dist:
return_star_path = star_file
max_dist = dist
return return_star_path
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"]:
# Get the cloest star catalog file
star_file_name = get_star_cat(ra_pointing=self.pointing.ra, dec_pointing=self.pointing.dec)
star_path = os.path.join(config["catalog_options"]["input_path"]["star_cat"], star_file_name)
star_SED_file = config["catalog_options"]["SED_templates_path"]["star_SED"]
self.star_path = os.path.join(self.cat_dir, star_path)
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()
self.agn_seds = {}
if "AGN_SED" in config["catalog_options"]["SED_templates_path"] and not config["catalog_options"]["star_only"]:
self.AGN_SED_path = os.path.join(config["data_dir"], config["catalog_options"]["SED_templates_path"]["AGN_SED"])
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]))
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_gals(self, gals, pix_id=None, cat_id=0, agnsed_file=""):
ngals = len(gals['ra'])
# Apply astrometric modeling
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):
# # (TEST)
# if igals > 100:
# 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]
if self.filt.filter_type == 'NUV':
param['mag_use_normal'] = gals['mag_csst_nuv'][igals]
else:
param['mag_use_normal'] = gals['mag_csst_%s'%(self.filt.filter_type)][igals]
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['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['delta_ra'] = 0
param['delta_dec'] = 0
# Masses
param['bulgemass'] = gals['bulgemass'][igals]
param['diskmass'] = gals['diskmass'][igals]
param['size'] = gals['size'][igals]
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'])
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
# Is this an Quasar?
param['qsoindex'] = gals['qsoindex'][igals]
if param['qsoindex'] == -1:
param['star'] = 0 # Galaxy
param['agnsed_file'] = ""
else:
param['star'] = 2 # Quasar
param['agnsed_file'] = agnsed_file
# 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'] = '%06d'%(int(pix_id)) + '%06d'%(cat_id) + '%08d'%(igals)
if param['star'] == 0:
obj = Galaxy(param, self.rotation, logger=self.logger)
elif param['star'] == 2:
obj = Quasar(param, 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]
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(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)
bundle_file = "galaxies_C6_bundle{:06}.h5".format(bundleID)
file_path = os.path.join(self.galaxy_path, bundle_file)
gals_cat = h5.File(file_path, 'r')['galaxies']
gals = gals_cat[str(pix)]
# Get corresponding AGN SED file
agnsed_file = get_agnsed_file(bundle_file)
agnsed_path = os.path.join(self.AGN_SED_path, agnsed_file)
self.agn_seds[agnsed_file] = fits.open(agnsed_path)[0].data
self._load_gals(gals, pix_id=pix, cat_id=bundleID, agnsed_file=agnsed_file)
del gals
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.agn_seds[obj.agnsed_file][int(obj.qsoindex)] * 1e-17
flux[flux < 0] = 0.
wave = self.lamb_gal
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)
# mag = getABMAG(interFlux, self.filt.bandpass_full)
# print("mag diff = %.3f"%(mag - obj.param['mag_use_normal']))
del wave
del flux
return sed
......@@ -147,18 +147,18 @@ class Chip(FocalPlane):
def _getSurveyType(self):
if self.filter_type in ["GI", "GV", "GU"]:
return "spectroscopic"
elif self.filter_type in ["nuv", "u", "g", 'r', 'i', 'z', 'y', 'FGS']:
elif self.filter_type in ["NUV", "u", "g", 'r', 'i', 'z', 'y', 'FGS']:
return "photometric"
# elif self.filter_type in ["FGS"]:
# return "FGS"
def _getChipEffCurve(self, filter_type):
# CCD efficiency curves
if filter_type in ['nuv', 'u', 'GU']: filename = 'UV0.txt'
if filter_type in ['NUV', 'u', 'GU']: filename = 'UV0.txt'
if filter_type in ['g', 'r', 'GV', 'FGS']: filename = 'Astro_MB.txt' # TODO, need to switch to the right efficiency curvey for FGS CMOS
if filter_type in ['i', 'z', 'y', 'GI']: filename = 'Basic_NIR.txt'
# Mirror efficiency:
# if filter_type == 'nuv': mirror_eff = 0.54
# if filter_type == 'NUV': mirror_eff = 0.54
# if filter_type == 'u': mirror_eff = 0.68
# if filter_type in ['g', 'r', 'i', 'z', 'y']: mirror_eff = 0.8
# if filter_type in ['GU', 'GV', 'GI']: mirror_eff = 1. # Not sure if this is right
......@@ -185,7 +185,7 @@ class Chip(FocalPlane):
def getChipFilter(self, chipID=None, filter_layout=None):
"""Return the filter index and type for a given chip #(chipID)
"""
filter_type_list = ["nuv","u", "g", "r", "i","z","y","GU", "GV", "GI", "FGS"]
filter_type_list = ["NUV","u", "g", "r", "i","z","y","GU", "GV", "GI", "FGS"]
if filter_layout is not None:
return filter_layout[chipID][0], filter_layout[chipID][1]
if chipID == None:
......@@ -198,7 +198,7 @@ class Chip(FocalPlane):
if chipID in [7, 24]: filter_type = "i"
if chipID in [14, 17]: filter_type = "u"
if chipID in [9, 22]: filter_type = "r"
if chipID in [12, 13, 18, 19]: filter_type = "nuv"
if chipID in [12, 13, 18, 19]: filter_type = "NUV"
if chipID in [8, 23]: filter_type = "g"
if chipID in [1, 10, 21, 30]: filter_type = "GI"
if chipID in [2, 5, 26, 29]: filter_type = "GV"
......
......@@ -26,7 +26,7 @@ class FilterParam(object):
# 8) dim end magnitude
if filter_param == None:
filtP = {
"nuv": [2867.7, 705.4, 2470.0, 3270.0, 0.1404, 0.004, 15.7, 25.4],
"NUV": [2867.7, 705.4, 2470.0, 3270.0, 0.1404, 0.004, 15.7, 25.4],
"u": [3601.1, 852.1, 3120.0, 4090.0, 0.2176, 0.021, 16.1, 25.4],
"g": [4754.5, 1569.8, 3900.0, 5620.0, 0.4640, 0.164, 17.2, 26.3],
"r": [6199.8, 1481.2, 5370.0, 7030.0, 0.5040, 0.207, 17.0, 26.0],
......
---
###############################################
#
# 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/csst-simulation/workplace/"
data_dir: "/share/simudata/CSSOSDataProductsSims/data/"
run_name: "50sqdeg_test"
# 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: ""
# star_cat: "C6_MMW_GGC_Astrometry_healpix.hdf5"
star_cat: "starcat/"
galaxy_cat: "qsocat/cat2CSSTSim_bundle-50sqDeg/"
# 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: "qsocat/qsosed/"
# AGN_SED_WAVE: "wave_ross13.npy"
# Only simulate stars?
star_only: NO
# Only simulate galaxies?
galaxy_only: NO
# 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/home/fangyuedong/50sqdeg_pointings/"
pointing_file: "pointing_50_combined.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: [8]
# Whether to enable astrometric modeling
enable_astrometric_model: True
# Whether to enable straylight model
enable_straylight_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
shear_type: "catalog"
# For constant shear filed
reduced_g1: 0.
reduced_g2: 0.
###############################################
# 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: ON # Whether to add sky background
add_dark: ON # Whether to add dark noise
add_readout: ON # Whether to add read-out (Gaussian) noise
add_bias: ON # Whether to add bias-level to images
bias_16channel: OFF # Whether to add different biases for 16 channels
gain_16channel: OFF # Whether to make different gains for 16 channels
shutter_effect: OFF # Whether to add shutter effect
flat_fielding: OFF # Whether to add flat-fielding effect
prnu_effect: OFF # Whether to add PRNU effect
non_linear: OFF # Whether to add non-linearity
cosmic_ray: OFF # Whether to add cosmic-ray
cray_differ: OFF # Whether to generate different cosmic ray maps CAL and MS output
cte_trail: OFF # Whether to simulate CTE trails
saturbloom: OFF # Whether to simulate Saturation & Blooming
add_badcolumns: OFF # Whether to add bad columns
add_hotpixels: OFF # Whether to add hot pixels
add_deadpixels: OFF # Whether to add dead(dark) pixels
bright_fatter: OFF # 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
......@@ -3,9 +3,14 @@
date
python -m cProfile -o C6_profiler_test.pstats /share/home/fangyuedong/csst-simulation/run_sim.py \
--config_file config_C6.yaml \
--catalog C6_Catalog \
--config_file config_50sqdeg.yaml \
--catalog C6_50sqdeg \
-c /share/home/fangyuedong/csst-simulation/config
# --config_file config_C6.yaml \
# --catalog C6_Catalog \
# -c /share/home/fangyuedong/csst-simulation/config
# --config_file test_fd_C6.yaml \
# --catalog fd_test_C6 \
# --config_file config_C6_test_wcs.yaml \
......
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