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Wei Chengliang authored4574f13f
import os
import galsim
import random
import copy
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 observation_sim.mock_objects import CatalogBase, Star, Galaxy, Quasar, ExtinctionMW
from observation_sim.mock_objects._util import tag_sed, getObservedSED, getABMAG, integrate_sed_bandpass, comoving_dist
from observation_sim.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
import astropy.constants as atcons
import ctypes
try:
import importlib.resources as pkg_resources
except ImportError:
# Try backported to PY<37 'importlib_resources'
import importlib_resources as pkg_resources
NSIDE = 128
pointing_file_list = ['pointing_C10_1000deg_lat80.dat', 'pointing_C10_1000deg_latm80_.dat', 'pointing_C10_1000deg_p180_m30.dat', 'pointing_C10_1000deg_p320_m40.dat']
star_file_list = ['CSST_C10_1000sqd_1.hdf5', 'CSST_C10_1000sqd_2_Fornax.hdf5', 'CSST_C10_1000sqd_3.hdf5', 'CSST_C10_1000sqd_4.hdf5']
def get_galaxy_qso_list(config):
cat_dir = config["catalog_options"]["input_path"]["cat_dir"]
with open(cat_dir+"galcat_C10/qsocat/gal_C10_file", 'r', encoding='utf-8') as fn1:
fn1_list = fn1.readlines()
bundle_file_list = [line.strip() for line in fn1_list]
with open(cat_dir+"galcat_C10/qsocat/qso_sed_C10_file", 'r', encoding='utf-8') as fn2:
fn2_list = fn2.readlines()
qsosed_file_list = [line.strip() for line in fn2_list]
return bundle_file_list, qsosed_file_list
class StarParm(ctypes.Structure):
_fields_ = [
('logte', ctypes.c_float),
('logg', ctypes.c_float),
('Mass', ctypes.c_float),
('Av', ctypes.c_float),
('mu0', ctypes.c_float),
('Z', ctypes.c_float)]
def get_star_cat(config):
idx = pointing_file_list.index(os.path.basename(config['obs_setting']['pointing_file']))
return_star_path = star_file_list[idx]
return return_star_path
def get_bundleIndex(healpixID_ring, bundleOrder=4, healpixOrder=7):
assert NSIDE == 2**healpixOrder
shift = healpixOrder - bundleOrder
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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, config):
bundle_file_list, qsosed_file_list = get_galaxy_qso_list(config)
return qsosed_file_list[bundle_file_list.index(bundle_file_name)]
class Catalog(CatalogBase):
def __init__(self, config, chip, pointing, chip_output, filt, **kwargs):
super().__init__()
self.cat_dir = config["catalog_options"]["input_path"]["cat_dir"]
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.
# [TODO] Milky Way extinction
if "enable_mw_ext_gal" in config["catalog_options"] and config["catalog_options"]["enable_mw_ext_gal"]:
if "planck_ebv_map" not in config["catalog_options"]:
raise ValueError(
"Planck dust map must be given to enable Milky Way extinction calculation for galaxies.")
self.mw_ext = ExtinctionMW()
self.mw_ext.init_ext_model(model_name="odonnell")
self.mw_ext.load_Planck_ext(
file_path=config["catalog_options"]["planck_ebv_map"])
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(self.config)
star_path = os.path.join(config["catalog_options"]["input_path"]["star_cat"], star_file_name)
self.star_path = os.path.join(self.cat_dir, star_path)
self.star_SED_path = config["catalog_options"]["SED_templates_path"]["star_SED"]
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 = 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 = config["catalog_options"]["SED_templates_path"]["AGN_SED"]
if "rotateEll" in config["catalog_options"]:
self.rotation = np.radians(
float(config["catalog_options"]["rotateEll"]))
else:
self.rotation = 0.
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# 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 = " av stellarmass dm teff logg feh"
self.add_hdr += " bulgemass diskmass detA e1 e2 kappa g1 g2 size galType veldisp "
self.add_fmt = "%8.4f %8.4f %8.4f %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_output_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_star(self):
# self.tempSED_star = h5.File(self.star_SED_path,'r')
with pkg_resources.path('catalog.data', 'starSpecInterp.so') as ddl_path:
self.starDDL = ctypes.CDLL(str(ddl_path))
self.starDDL.loadSpecLibs.argtypes = [ctypes.c_char_p, ctypes.c_char_p]
self.starDDL.loadExts.argtypes = [ctypes.c_char_p]
nwv = self.starDDL.loadSpecLibs(str.encode(os.path.join(
self.star_SED_path, 'file_BT-Settl_CSST_wl1000-24000_R1000.par')), str.encode(self.star_SED_path))
self.starDDL.loadExts(str.encode(os.path.join(
self.star_SED_path, "Ext_odonnell94_R3.1_CSST_wl1000-24000_R1000.fits")))
self.star_spec_len = nwv
def _interp_star_sed(self, obj):
spec = (ctypes.c_float*self.star_spec_len)()
wave = (ctypes.c_float*self.star_spec_len)()
self.starDDL.interpSingleStar.argtypes = [
ctypes.Structure, ctypes.POINTER(ctypes.c_float)]
# s=Star(obj.param['teff'], obj.param['grav''], obj.paramstar['mwmsc_mass'], obj.param['AV'], obj.param['DM'], obj.param['z_met'])
s = StarParm(obj.param['teff'], obj.param['logg'], obj.param['stellarMass'],
obj.param['av'], obj.param['DM'], obj.param['feh'])
self.starDDL.interpSingleStar(s, spec, wave)
rv_c = obj.param['rv']/(atcons.c.value/1000.)
Doppler_factor = np.sqrt((1+rv_c)/(1-rv_c))
wave_RV = wave*Doppler_factor
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return wave_RV, np.power(10, spec[:])
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
)
# [TODO] get Milky Way extinction AVs
if "enable_mw_ext_gal" in self.config["catalog_options"] and self.config["catalog_options"]["enable_mw_ext_gal"]:
MW_Av_arr = self.mw_ext.Av_from_Planck(ra=ra_arr, dec=dec_arr)
else:
MW_Av_arr = np.zeros(len(ra_arr))
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]
# [TODO] get Milky Way extinction AVs
param['mw_Av'] = MW_Av_arr[igals]
if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
continue
# 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
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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['e1'], param['e2'], param['ell_total'] = self.rotate_ellipticity(
e1=gals['ellipticity_true'][igals][0],
e2=gals['ellipticity_true'][igals][1],
rotation=self.rotation,
unit='radians')
# param['ell_total'] = np.sqrt(param['e1']**2 + param['e2']**2)
if param['ell_total'] > 0.9:
continue
# phi_e = cmath.phase(complex(param['e1'], param['e2']))
# param['e1'] = param['ell_total'] * np.cos(phi_e + 2*self.rotation)
# param['e2'] = param['ell_total'] * np.sin(phi_e + 2*self.rotation)
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
# TEMP
self.ids += 1
param['id'] = '%06d' % (int(pix_id)) + \
'%06d' % (cat_id) + '%08d' % (igals)
# Is this an Quasar?
param['qsoindex'] = gals['qsoindex'][igals]
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if param['qsoindex'] == -1:
param['star'] = 0 # Galaxy
param['agnsed_file'] = ""
obj = Galaxy(param, logger=self.logger)
else:
param_qso = copy.deepcopy(param)
param_qso['star'] = 2 # Quasar
param_qso['agnsed_file'] = agnsed_file
# First add QSO model
obj = Quasar(param_qso, logger=self.logger)
# Need to deal with additional output columns
obj.additional_output_str = self.add_fmt % (0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0, 0.)
self.objs.append(obj)
# Then add host galaxy model
param['star'] = 0 # Galaxy
param['agnsed_file'] = ""
obj = Galaxy(param, logger=self.logger)
# Need to deal with additional output columns for (host) galaxy
obj.additional_output_str = self.add_fmt % (0., 0., 0., 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['RA'])
# 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()
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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'] = '%06d' % (int(pix_id)) + '%08d' % (istars)
# param['sed_type'] = istars
# param['model_tag'] = ''
param['teff'] = stars['teff'][istars]
param['logg'] = stars['grav'][istars]
param['feh'] = stars['z_met'][istars]
param['stellarMass'] = stars['mass'][istars]
param['av'] = stars['AV'][istars]
param['DM'] = stars['DM'][istars]
# param['z_met'] = stars['z_met'][istars]
param['z'] = 0.0
param['star'] = 1 # Star
try:
obj = Star(param, logger=self.logger)
except Exception as e:
print(e)
# Append additional output columns to the .cat file
obj.additional_output_str = self.add_fmt % (param["av"], param['stellarMass'], param['DM'], param['teff'], param['logg'], param['feh'],
0., 0., 0., 0., 0., 0., 0., 0., 0., -1, 0.)
self.objs.append(obj)
def free_mem(self, **kward):
self.starDDL.freeGlobeData()
del self.starDDL
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')['star_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_C10_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, self.config)
agnsed_path = os.path.join(self.AGN_SED_path, agnsed_file)
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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']
# )
wave, flux = self._interp_star_sed(obj)
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 * (1.0 + obj.z)
else:
raise ValueError("Object type not known")
speci = interpolate.interp1d(wave, flux, fill_value=0., bounds_error=False)
lamb = np.arange(2000, 11001+0.5, 0.5)
y = speci(lamb)
# [TODO] Apply Milky Way extinction
if obj.type != 'star' and ("enable_mw_ext_gal" in self.config["catalog_options"] and self.config["catalog_options"]["enable_mw_ext_gal"]):
y = self.mw_ext.apply_extinction(y, Av=obj.mw_Av)
# 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']))
# integrate to get the magnitudes
if obj.type == 'quasar' or obj.type == 'galaxy':
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