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
Showing with 1628 additions and 95 deletions
+1628 -95
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)
......
File deleted
File added
File deleted
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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