Commit 9f1aaa66 authored by Zhang Xin's avatar Zhang Xin
Browse files

Merge branch 'wcs_test' into 'develop'

starting point of the new version

See merge request csst_sim/csst-simulation!15
parents 10e28e08 a4832bdf
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 = np.radians(float(config["catalog_options"]["rotateEll"]))
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['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
# 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, 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
......@@ -83,7 +83,7 @@ class Catalog(CatalogBase):
self._load_SED_lib_AGN()
if "rotateEll" in config["catalog_options"]:
self.rotation = float(int(config["catalog_options"]["rotateEll"]/45.))
self.rotation = np.radians(float(config["catalog_options"]["rotateEll"]))
else:
self.rotation = 0.
......@@ -259,7 +259,7 @@ class Catalog(CatalogBase):
param['id'] = '%06d'%(int(pix_id)) + '%06d'%(cat_id) + '%08d'%(igals)
if param['star'] == 0:
obj = Galaxy(param, self.rotation, logger=self.logger)
obj = Galaxy(param, logger=self.logger)
# Need to deal with additional output columns
obj.additional_output_str = self.add_fmt%("n", 0., 0., 0.,
......
......@@ -94,7 +94,7 @@ class Catalog(CatalogBase):
###mock_stamp_END
if "rotateEll" in config["catalog_options"]:
self.rotation = float(int(config["catalog_options"]["rotateEll"]/45.))
self.rotation = np.radians(float(config["catalog_options"]["rotateEll"]))
else:
self.rotation = 0.
......@@ -272,7 +272,7 @@ class Catalog(CatalogBase):
param['id'] = '%06d'%(int(pix_id)) + '%06d'%(cat_id) + '%08d'%(igals)
if param['star'] == 0:
obj = Galaxy(param, self.rotation, logger=self.logger)
obj = Galaxy(param, logger=self.logger)
# Need to deal with additional output columns
obj.additional_output_str = self.add_fmt%("n", 0., 0., 0.,
......
......@@ -84,7 +84,7 @@ class Catalog(CatalogBase):
self._load_SED_lib_AGN()
if "rotateEll" in config["catalog_options"]:
self.rotation = float(int(config["catalog_options"]["rotateEll"]/45.))
self.rotation = np.radians(float(config["catalog_options"]["rotateEll"]))
else:
self.rotation = 0.
......@@ -260,7 +260,7 @@ class Catalog(CatalogBase):
param['id'] = '%06d'%(int(pix_id)) + '%06d'%(cat_id) + '%08d'%(igals)
if param['star'] == 0:
obj = Galaxy(param, self.rotation, logger=self.logger)
obj = Galaxy(param, logger=self.logger)
# Need to deal with additional output columns
obj.additional_output_str = self.add_fmt%("n", 0., 0., 0.,
......
......@@ -52,7 +52,7 @@ class Catalog(CatalogBase):
self.galaxy_SED_path = os.path.join(config["data_dir"], config["catalog_options"]["SED_templates_path"]["galaxy_SED"])
self._load_SED_lib_gals()
if "rotateEll" in config["catalog_options"]:
self.rotation = float(int(config["catalog_options"]["rotateEll"]/45.))
self.rotation = np.radians(float(config["catalog_options"]["rotateEll"]))
else:
self.rotation = 0.
......@@ -191,7 +191,7 @@ class Catalog(CatalogBase):
param['id'] = gals['galaxyID'][igals]
if param['star'] == 0:
obj = Galaxy(param, self.rotation, logger=self.logger)
obj = Galaxy(param, logger=self.logger)
if param['star'] == 2:
obj = Quasar(param, logger=self.logger)
......
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 = np.radians(float(config["catalog_options"]["rotateEll"]))
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, 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
......@@ -81,7 +81,7 @@ class Catalog(CatalogBase):
self._load_SED_lib_AGN()
if "rotateEll" in config["catalog_options"]:
self.rotation = float(int(config["catalog_options"]["rotateEll"]/45.))
self.rotation = np.radians(float(config["catalog_options"]["rotateEll"]))
else:
self.rotation = 0.
......@@ -253,7 +253,7 @@ class Catalog(CatalogBase):
param['id'] = '%06d'%(int(pix_id)) + '%06d'%(cat_id) + '%08d'%(igals)
if param['star'] == 0:
obj = Galaxy(param, self.rotation, logger=self.logger)
obj = Galaxy(param, logger=self.logger)
# Need to deal with additional output columns
obj.additional_output_str = self.add_fmt%("n", 0., 0., 0.,
......
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 = np.radians(float(config["catalog_options"]["rotateEll"]))
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):
# # (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]
# 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]
param['e1'] = 0.
param['e2'] = 0.
# 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
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, 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]
param['mag_use_normal'] = 20.
# 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
......@@ -291,7 +291,8 @@ def WCS_def(xlen = 9216, ylen = 9232, gapy = 898.0, gapx1 = 534, gapx2 = 1309, r
r_dat['CRPIX1'] = -x1
r_dat['CRPIX2'] = -y1
cd = np.array([[ pixel_scale, 0], [0, pixel_scale]])/3600.*flag_x[1]
# cd = np.array([[ pixel_scale, 0], [0, pixel_scale]])/3600.*flag_x[1]
cd = np.array([[ pixel_scale, 0], [0, -pixel_scale]])/3600.
cd_rot = rotate_CD_matrix(cd, pa_aper)
r_dat['CD1_1'] = cd_rot[0,0]
r_dat['CD1_2'] = cd_rot[0,1]
......
......@@ -77,7 +77,8 @@ class Chip(FocalPlane):
self.fdModel = None
else:
try:
with pkg_resources.files('ObservationSim.Instrument.data.field_distortion').joinpath("FieldDistModelGlobal_mainFP_v1.0.pickle") as field_distortion:
# with pkg_resources.files('ObservationSim.Instrument.data.field_distortion').joinpath("FieldDistModelGlobal_mainFP_v1.0.pickle") as field_distortion:
with pkg_resources.files('ObservationSim.Instrument.data.field_distortion').joinpath("FieldDistModel_v2.0.pickle") as field_distortion:
with open(field_distortion, "rb") as f:
self.fdModel = pickle.load(f)
except AttributeError:
......@@ -117,7 +118,7 @@ class Chip(FocalPlane):
self._getCRdata()
# Define the sensor model
if config["ins_effects"]["bright_fatter"] == True and self.survey_type == "photometric":
if "bright_fatter" in config["ins_effects"] and config["ins_effects"]["bright_fatter"] == True and self.survey_type == "photometric":
self.sensor = galsim.SiliconSensor(strength=self.df_strength, treering_func=treering_func)
else:
self.sensor = galsim.Sensor()
......@@ -146,18 +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
......@@ -184,7 +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:
......@@ -197,7 +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"
......@@ -514,21 +515,6 @@ class Chip(FocalPlane):
if config["ins_effects"]["add_badcolumns"] == True:
img = effects.BadColumns(img, seed=SeedBadColumns, chipid=self.chipID, logger=self.logger)
# Add Bias level
if config["ins_effects"]["add_bias"] == True:
if self.logger is not None:
self.logger.info(" Adding Bias level and 16-channel non-uniformity")
else:
print(" Adding Bias level and 16-channel non-uniformity")
if config["ins_effects"]["bias_16channel"] == True:
img = effects.AddBiasNonUniform16(img,
bias_level=float(self.bias_level),
nsecy = 2, nsecx=8,
seed=SeedBiasNonuni+self.chipID,
logger=self.logger)
elif config["ins_effects"]["bias_16channel"] == False:
img += self.bias_level
# Apply Nonlinearity on the chip image
if config["ins_effects"]["non_linear"] == True:
if self.logger is not None:
......@@ -552,6 +538,21 @@ class Chip(FocalPlane):
else:
print(" Apply CTE Effect")
img = effects.CTE_Effect(GSImage=img, threshold=27)
# Add Bias level
if config["ins_effects"]["add_bias"] == True:
if self.logger is not None:
self.logger.info(" Adding Bias level and 16-channel non-uniformity")
else:
print(" Adding Bias level and 16-channel non-uniformity")
if config["ins_effects"]["bias_16channel"] == True:
img = effects.AddBiasNonUniform16(img,
bias_level=float(self.bias_level),
nsecy = 2, nsecx=8,
seed=SeedBiasNonuni+self.chipID,
logger=self.logger)
elif config["ins_effects"]["bias_16channel"] == False:
img += self.bias_level
# Add Read-out Noise
if config["ins_effects"]["add_readout"] == True:
......
......@@ -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],
......
......@@ -86,15 +86,16 @@ class FocalPlane(object):
if (xcen == None) or (ycen == None):
xcen = self.cen_pix_x
ycen = self.cen_pix_y
# dudx = -np.cos(img_rot.rad) * pix_scale
# dudy = -np.sin(img_rot.rad) * pix_scale
# dvdx = -np.sin(img_rot.rad) * pix_scale
# dvdy = +np.cos(img_rot.rad) * pix_scale
dudx = -np.cos(img_rot.rad) * pix_scale
dudy = -np.sin(img_rot.rad) * pix_scale
dudy = +np.sin(img_rot.rad) * pix_scale
dvdx = -np.sin(img_rot.rad) * pix_scale
dvdy = +np.cos(img_rot.rad) * pix_scale
dvdy = -np.cos(img_rot.rad) * pix_scale
# dudx = +np.sin(img_rot.rad) * pix_scale
# dudy = +np.cos(img_rot.rad) * pix_scale
# dvdx = -np.cos(img_rot.rad) * pix_scale
# dvdy = +np.sin(img_rot.rad) * pix_scale
moscen = galsim.PositionD(x=xcen, y=ycen)
sky_center = galsim.CelestialCoord(ra=ra*galsim.degrees, dec=dec*galsim.degrees)
affine = galsim.AffineTransform(dudx, dudy, dvdx, dvdy, origin=moscen)
......
import numpy as np
import galsim
import copy
import cmath
from astropy.table import Table
from abc import abstractmethod, ABCMeta
......@@ -72,6 +73,16 @@ class CatalogBase(metaclass=ABCMeta):
"parallax":1e-9
}
return param
@staticmethod
def rotate_ellipticity(e1, e2, rotation=0., unit='radians'):
if unit == 'degree':
rotation = np.radians(rotation)
e_total = np.sqrt(e1**2 + e2**2)
phi = cmath.phase(complex(e1, e2))
e1 = e_total * np.cos(phi + 2*rotation)
e2 = e_total * np.sin(phi + 2*rotation)
return e1, e2, e_total
@staticmethod
def convert_sed(mag, sed, target_filt, norm_filt=None):
......
......@@ -12,7 +12,7 @@ from ObservationSim.MockObject.MockObject import MockObject
# import tracemalloc
class Galaxy(MockObject):
def __init__(self, param, rotation=None, logger=None):
def __init__(self, param, logger=None):
super().__init__(param, logger=logger)
# self.thetaR = self.param["theta"]
# self.bfrac = self.param["bfrac"]
......@@ -27,8 +27,6 @@ class Galaxy(MockObject):
# self.e1_bulge, self.e2_bulge = self.e_bulge.g1, self.e_bulge.g2
# self.e1_total, self.e2_total = self.e_total.g1, self.e_total.g2
if rotation is not None:
self.rotateEllipticity(rotation)
if not hasattr(self, "disk_sersic_idx"):
self.disk_sersic_idx = 1.
if not hasattr(self, "bulge_sersic_idx"):
......@@ -51,7 +49,8 @@ class Galaxy(MockObject):
full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full)
except Exception as e:
print(e)
self.logger.error(e)
if self.logger:
self.logger.error(e)
return -1
for i in range(len(bandpass_list)):
bandpass = bandpass_list[i]
......@@ -59,7 +58,8 @@ class Galaxy(MockObject):
sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
except Exception as e:
print(e)
self.logger.error(e)
if self.logger:
self.logger.error(e)
return -1
ratio = sub/full
......@@ -78,12 +78,13 @@ class Galaxy(MockObject):
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
gal = gal.withFlux(nphotons)
if fd_shear is not None:
g1 += fd_shear.g1
g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2)
gal = gal.shear(gal_shear)
gal = galsim.Convolve(psf, gal)
if fd_shear is not None:
gal = gal.shear(fd_shear)
objs.append(gal)
final = galsim.Sum(objs)
return final
......@@ -97,7 +98,8 @@ class Galaxy(MockObject):
full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full)
except Exception as e:
print(e)
self.logger.error(e)
if self.logger:
self.logger.error(e)
return 2, None
nphotons_sum = 0
......@@ -131,6 +133,18 @@ class Galaxy(MockObject):
real_wcs_local = self.real_wcs.local(self.real_pos)
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape)
bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
if fd_shear:
g1 += fd_shear.g1
g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2)
for i in range(len(bandpass_list)):
bandpass = bandpass_list[i]
......@@ -138,7 +152,8 @@ class Galaxy(MockObject):
sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
except Exception as e:
print(e)
self.logger.error(e)
if self.logger:
self.logger.error(e)
# return False
continue
......@@ -153,41 +168,24 @@ class Galaxy(MockObject):
# print("nphotons_sub-band_%d = %.2f"%(i, nphotons))
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
disk = galsim.Sersic(n=self.disk_sersic_idx, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
disk = disk.shear(disk_shape)
bulge = galsim.Sersic(n=self.bulge_sersic_idx, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
gal_temp = self.bfrac * bulge + (1.0 - self.bfrac) * disk
gal_temp = gal_temp.shear(gal_shear)
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
gal_temp = gal_temp.withFlux(nphotons)
if not big_galaxy: # Not apply PSF for very big galaxy
gal_temp = galsim.Convolve(psf, gal_temp)
if i == 0:
gal = gal_temp
else:
gal = gal + gal_temp
# (TEST) Random knots
# knots = galsim.RandomKnots(npoints=100, profile=disk)
# kfrac = np.random.random()*(1.0 - self.bfrac)
# gal = self.bfrac * bulge + (1.0 - self.bfrac - kfrac) * disk + kfrac * knots
gal = gal.withFlux(nphotons)
gal_shear = galsim.Shear(g1=g1, g2=g2)
gal = gal.shear(gal_shear)
if not big_galaxy: # Not apply PSF for very big galaxy
gal = galsim.Convolve(psf, gal)
if fd_shear is not None:
gal = gal.shear(fd_shear)
# Use (explicit) stamps to draw
stamp = gal.drawImage(wcs=real_wcs_local, method='phot', offset=offset, save_photons=True)
xmax = max(xmax, stamp.xmax - stamp.xmin)
ymax = max(ymax, stamp.ymax - stamp.ymin)
photons = stamp.photons
photons.x += x_nominal
photons.y += y_nominal
photons_list.append(photons)
del gal
# # [C6 TEST]
# print('xmax = %d, ymax = %d '%(xmax, ymax))
# # Output memory usage
......@@ -196,7 +194,12 @@ class Galaxy(MockObject):
# for stat in top_stats[:10]:
# print(stat)
stamp = galsim.ImageF(int(xmax * 1.1), int(ymax * 1.1))
stamp = gal.drawImage(wcs=real_wcs_local, method='phot', offset=offset, save_photons=True)
photons = stamp.photons
photons.x += x_nominal
photons.y += y_nominal
photons_list.append(photons)
stamp.wcs = real_wcs_local
stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1)
......@@ -226,7 +229,8 @@ class Galaxy(MockObject):
else:
# Return code 0: object photons missed this detector
print("obj %s missed"%(self.id))
self.logger.info("obj %s missed"%(self.id))
if self.logger:
self.logger.info("obj %s missed"%(self.id))
return 0, pos_shear
# # [C6 TEST]
......@@ -297,14 +301,17 @@ class Galaxy(MockObject):
# gal = self.bfrac * bulge + (1.0 - self.bfrac - kfrac) * disk + kfrac * knots
gal = gal.withFlux(tel.pupil_area * exptime)
if fd_shear:
g1 += fd_shear.g1
g2 += fd_shear.g2
gal_shear = galsim.Shear(g1=g1, g2=g2)
gal = gal.shear(gal_shear)
gal = galsim.Convolve(psf, gal)
if not big_galaxy: # Not apply PSF for very big galaxy
gal = galsim.Convolve(psf, gal)
if fd_shear is not None:
gal = gal.shear(fd_shear)
# if fd_shear is not None:
# gal = gal.shear(fd_shear)
starImg = gal.drawImage(wcs=real_wcs_local, offset=offset)
......@@ -397,14 +404,6 @@ class Galaxy(MockObject):
final = galsim.Convolve(psf, gal)
return final
def rotateEllipticity(self, rotation):
if rotation == 1:
self.e1_disk, self.e2_disk, self.e1_bulge, self.e2_bulge, self.e1_total, self.e2_total = -self.e2_disk, self.e1_disk, -self.e2_bulge, self.e1_bulge, -self.e2_total, self.e1_total
if rotation == 2:
self.e1_disk, self.e2_disk, self.e1_bulge, self.e2_bulge, self.e1_total, self.e2_total = -self.e1_disk, -self.e2_disk, -self.e1_bulge, -self.e2_bulge, -self.e1_total, -self.e2_total
if rotation == 3:
self.e1_disk, self.e2_disk, self.e1_bulge, self.e2_bulge, self.e1_total, self.e2_total = self.e2_disk, -self.e1_disk, self.e2_bulge, -self.e1_bulge, self.e2_total, -self.e1_total
def drawObject(self, img, final, noise_level=0.0, flux=None, filt=None, tel=None, exptime=150.):
""" Override the method in parent class
Need to constrain the size of image stamp for extended objects
......
......@@ -32,6 +32,7 @@ class MockObject(object):
# Place holder for outputs
self.additional_output_str = ""
self.fd_shear = None
self.logger = logger
......@@ -61,7 +62,7 @@ class MockObject(object):
dec = self.param["dec"]
return galsim.CelestialCoord(ra=ra * galsim.degrees, dec=dec * galsim.degrees)
def getPosImg_Offset_WCS(self, img, fdmodel=None, chip=None, verbose=True, img_header=None):
def getPosImg_Offset_WCS(self, img, fdmodel=None, chip=None, verbose=True, chip_wcs=None, img_header=None):
self.posImg = img.wcs.toImage(self.getPosWorld())
self.localWCS = img.wcs.local(self.posImg)
if (fdmodel is not None) and (chip is not None):
......@@ -79,8 +80,10 @@ class MockObject(object):
dx = x - self.x_nominal
dy = y - self.y_nominal
self.offset = galsim.PositionD(dx, dy)
if img_header is not None:
if chip_wcs is not None:
self.real_wcs = chip_wcs
elif img_header is not None:
self.real_wcs = galsim.FitsWCS(header=img_header)
else:
self.real_wcs = None
......@@ -132,7 +135,8 @@ class MockObject(object):
full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full)
except Exception as e:
print(e)
self.logger.error(e)
if self.logger:
self.logger.error(e)
return 2, None
nphotons_sum = 0
......@@ -164,7 +168,8 @@ class MockObject(object):
sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
except Exception as e:
print(e)
self.logger.error(e)
if self.logger:
self.logger.error(e)
# return False
continue
......@@ -214,7 +219,8 @@ class MockObject(object):
else:
# Return code 0: object photons missed this detector
print("obj %s missed"%(self.id))
self.logger.info("obj %s missed"%(self.id))
if self.logger:
self.logger.info("obj %s missed"%(self.id))
return 0, pos_shear
del photons_list
......
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