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import os
import galsim
import random
import numpy as np
import h5py as h5
import healpy as hp
import astropy.constants as cons
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 seds, sed_assign, extAv, tag_sed, getObservedSED
from ObservationSim.Astrometry.Astrometry_util import on_orbit_obs_position
try:
import importlib.resources as pkg_resources
except ImportError:
# Try backported to PY<37 'importlib_resources'
import importlib_resources as pkg_resources
NSIDE = 128
class C3Catalog(CatalogBase):
def __init__(self, config, chip, pointing, **kwargs):
super().__init__()
self.cat_dir = os.path.join(config["data_dir"], config["input_path"]["cat_dir"])
self.seed_Av = config["random_seeds"]["seed_Av"]
# self.normalize_dir = os.path.join(config["data_dir"], config["SLS_path"]["SLS_norm"])
# self.normF_star = Table.read(os.path.join(self.normalize_dir, 'SLOAN_SDSS.g.fits'))
# self.normF_galaxy = Table.read(os.path.join(self.normalize_dir, 'lsst_throuput_g.fits'))
with pkg_resources.path('Catalog.data', 'SLOAN_SDSS.g.fits') as filter_path:
self.normF_star = filter_path
with pkg_resources.path('Catalog.data', 'lsst_throuput_g.fits') as filter_path:
self.normF_star = filter_path
self.pointing = pointing
if "star_cat" in config["input_path"] and config["input_path"]["star_cat"] and not config["run_option"]["galaxy_only"]:
star_file = config["input_path"]["star_cat"]
star_SED_file = config["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["input_path"] and config["input_path"]["galaxy_cat"] and not config["run_option"]["star_only"]:
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galaxy_file = config["input_path"]["galaxy_cat"]
self.galaxy_path = os.path.join(self.cat_dir, galaxy_file)
self.galaxy_SED_path = os.path.join(config["data_dir"], config["SED_templates_path"]["galaxy_SED"])
self._load_SED_lib_gals()
if "rotateEll" in config["shear_setting"]:
self.rotation = float(int(config["shear_setting"]["rotateEll"]/45.))
else:
self.rotation = 0.
self._get_healpix_list()
self._load()
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, np.array(vertices).T, inclusive=True)
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
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):
self.tempSed_gal, self.tempRed_gal = seds("galaxy.list", seddir=self.galaxy_SED_path)
def _load_gals(self, gals, pix_id=None):
ngals = len(gals['galaxyID'])
self.rng_sedGal = random.Random()
self.rng_sedGal.seed(pix_id) # Use healpix index as the random seed
self.ud = galsim.UniformDeviate(pix_id)
for igals in range(ngals):
param = self.initialize_param()
param['ra'] = gals['ra_true'][igals]
param['dec'] = gals['dec_true'][igals]
if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
continue
param['mag_use_normal'] = gals['mag_true_g_lsst'][igals]
if param['mag_use_normal'] >= 26.5:
continue
param['z'] = gals['redshift_true'][igals]
param['model_tag'] = 'None'
param['gamma1'] = 0
param['gamma2'] = 0
param['kappa'] = 0
param['delta_ra'] = 0
param['delta_dec'] = 0
# sersicB = gals['sersic_bulge'][igals]
hlrMajB = gals['size_bulge_true'][igals]
hlrMinB = gals['size_minor_bulge_true'][igals]
# sersicD = gals['sersic_disk'][igals]
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hlrMajD = gals['size_disk_true'][igals]
hlrMinD = gals['size_minor_disk_true'][igals]
aGal = gals['size_true'][igals]
bGal = gals['size_minor_true'][igals]
param['bfrac'] = gals['bulge_to_total_ratio_i'][igals]
param['theta'] = gals['position_angle_true'][igals]
param['hlr_bulge'] = np.sqrt(hlrMajB * hlrMinB)
param['hlr_disk'] = np.sqrt(hlrMajD * hlrMinD)
param['ell_bulge'] = (hlrMajB - hlrMinB)/(hlrMajB + hlrMinB)
param['ell_disk'] = (hlrMajD - hlrMinD)/(hlrMajD + hlrMinD)
param['ell_tot'] = (aGal - bGal) / (aGal + bGal)
# Assign each galaxy a template SED
param['sed_type'] = sed_assign(phz=param['z'], btt=param['bfrac'], rng=self.rng_sedGal)
param['redden'] = self.tempRed_gal[param['sed_type']]
param['av'] = self.avGal[int(self.ud()*self.nav)]
if param['sed_type'] <= 5:
param['av'] = 0.0
param['redden'] = 0
param['star'] = 0 # Galaxy
if param['sed_type'] >= 29:
param['av'] = 0.6 * param['av'] / 3.0 # for quasar, av=[0, 0.2], 3.0=av.max-av.im
param['star'] = 2 # Quasar
self.ids += 1
param['id'] = self.ids
if param['star'] == 0:
obj = Galaxy(param, self.rotation)
self.objs.append(obj)
if param['star'] == 2:
obj = Quasar(param)
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"][:]
# if "astrometric_lib" in self.config["obs_setting"] and self.config["obs_setting"]["enable_astrometric_model"]:
if self.config["obs_setting"]["enable_astrometric_model"]:
ra_list = ra_arr.tolist()
dec_list = dec_arr.tolist()
pmra_list = np.zeros(nstars).tolist()
pmdec_list = np.zeros(nstars).tolist()
rv_list = np.zeros(nstars).tolist()
parallax_list = [1e-9] * nstars
# lib_path = os.path.join(self.config["data_dir"], self.config["obs_setting"]["astrometric_lib"])
dt = datetime.fromtimestamp(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="J2015.5",
input_date_str=date_str,
input_time_str=time_str,
for istars in range(nstars):
param = self.initialize_param()
param['ra'] = ra_arr[istars]
param['dec'] = dec_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'] = self.ids
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)
self.objs.append(obj)
def _load(self, **kwargs):
self.nav = 15005
self.avGal = extAv(self.nav, seed=self.seed_Av)
self.objs = []
self.ids = 0
if "star_cat" in self.config["input_path"] and self.config["input_path"]["star_cat"] and not self.config["run_option"]["galaxy_only"]:
star_cat = h5.File(self.star_path, 'r')['catalog']
for pix in self.pix_list:
stars = star_cat[str(pix)]
self._load_stars(stars, pix_id=pix)
del stars
if "galaxy_cat" in self.config["input_path"] and self.config["input_path"]["galaxy_cat"] and not self.config["run_option"]["star_only"]:
gals_cat = h5.File(self.galaxy_path, 'r')['galaxies']
for pix in self.pix_list:
gals = gals_cat[str(pix)]
self._load_gals(gals, pix_id=pix)
del gals
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print("number of objects in catalog: ", len(self.objs))
del self.avGal
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':
sed_data = getObservedSED(
sedCat=self.tempSed_gal[obj.sed_type],
redshift=obj.z,
av=obj.param["av"],
redden=obj.param["redden"]
)
wave, flux = sed_data[0], sed_data[1]
else:
raise ValueError("Object type not known")
speci = interpolate.interp1d(wave, flux)
# lamb = np.arange(2500, 10001 + 0.5, 0.5)
lamb = np.arange(2400, 11001 + 0.5, 0.5)
y = speci(lamb)
# erg/s/cm2/A --> photo/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'))
del wave
del flux