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Commit 931e5956 authored by Fang Yuedong's avatar Fang Yuedong
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update output catalog, apply astrometry module to galaxy catalog, add new PSF tests

parent a5d541c9
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Catalog/C3Catalog.py
View file @ 931e5956
......@@ -84,10 +84,46 @@ class C3Catalog(CatalogBase):
self.rng_sedGal = random.Random()
self.rng_sedGal.seed(pix_id) # Use healpix index as the random seed
self.ud = galsim.UniformDeviate(pix_id)
# Apply astrometric modeling
# in C3 case only aberration
ra_arr = gals['ra_true'][:]
dec_arr = gals['dec_true'][:]
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.fromtimestamp(self.pointing.timestamp)
date_str = dt.date().isoformat()
time_str = dt.time().isoformat()
ra_arr, dec_arr = on_orbit_obs_position(
input_ra_list=ra_list,
input_dec_list=dec_list,
input_pmra_list=pmra_list,
input_pmdec_list=pmdec_list,
input_rv_list=rv_list,
input_parallax_list=parallax_list,
input_nstars=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="J2015.5",
input_date_str=date_str,
input_time_str=time_str
)
for igals in range(ngals):
param = self.initialize_param()
param['ra'] = gals['ra_true'][igals]
param['dec'] = gals['dec_true'][igals]
param['ra'] = ra_arr[igals]
param['dec'] = dec_arr[igals]
param['ra_orig'] = gals['ra_true'][igals]
param['dec_orig'] = gals['dec_true'][igals]
if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
continue
param['mag_use_normal'] = gals['mag_true_g_lsst'][igals]
......@@ -129,7 +165,8 @@ class C3Catalog(CatalogBase):
param['star'] = 2 # Quasar
self.ids += 1
param['id'] = self.ids
# param['id'] = self.ids
param['id'] = gals['galaxyID'][igals]
if param['star'] == 0:
obj = Galaxy(param, self.rotation)
......@@ -141,9 +178,9 @@ class C3Catalog(CatalogBase):
def _load_stars(self, stars, pix_id=None):
nstars = len(stars['sourceID'])
# Apply astrometric modeling
# in C3 case only aberration
ra_arr = stars["RA"][:]
dec_arr = stars["Dec"][:]
# if "astrometric_lib" in self.config["obs_setting"] and self.config["obs_setting"]["enable_astrometric_model"]:
if self.config["obs_setting"]["enable_astrometric_model"]:
ra_list = ra_arr.tolist()
dec_list = dec_arr.tolist()
......@@ -170,20 +207,22 @@ class C3Catalog(CatalogBase):
input_vz=self.pointing.sat_vz,
input_epoch="J2015.5",
input_date_str=date_str,
input_time_str=time_str,
# lib_path=lib_path
input_time_str=time_str
)
for istars in range(nstars):
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]
if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
continue
param['mag_use_normal'] = stars['app_sdss_g'][istars]
if param['mag_use_normal'] >= 26.5:
continue
self.ids += 1
param['id'] = self.ids
# param['id'] = self.ids
param['id'] = stars['sourceID'][istars]
param['sed_type'] = stars['sourceID'][istars]
param['model_tag'] = stars['model_tag'][istars]
param['teff'] = stars['teff'][istars]
......
ObservationSim/Config/ChipOutput.py
View file @ 931e5956
......@@ -23,73 +23,81 @@ class ChipOutput(object):
self.cat_name = 'MSC_' + config["obs_setting"]["date_obs"] + config["obs_setting"]["time_obs"] + "_" + str(pointing_ID).rjust(7, '0') + "_" + self.chipLabel.rjust(2,'0') + ".cat"
self.subdir = subdir
# hdr1 = "#ID ID_chip filter xImage yImage ra dec z mag flag SNR "
hdr1 = "#ID ID_chip filter xImage yImage ra dec z mag flag "
hdr2 = "thetaR bfrac hlr_disk hlr_bulge e1_disk e2_disk e1_bulge e2_bulge "
hdr3 = "e1PSF e2PSF e1 e2 g1 g2 e1OBS e2OBS "
hdr4 = "sed_type av redden "
hdr5 = "star_model teff logg feh\n"
# fmt1 = "%10d %4d %5s %10.3f %10.3f %15.6f %15.6f %7.4f %8.4f %2d %9.2f "
fmt1 = "%10d %4d %5s %10.3f %10.3f %15.6f %15.6f %7.4f %8.4f %2d "
fmt2 = "%8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f "
fmt3 = "%8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f "
fmt4 = "%2d %8.4f %8.4f "
fmt5 = "%10s %8.4f %8.4f %8.4f\n"
self.hdr = hdr1 + hdr2 + hdr3 + hdr4 + hdr5
self.fmt = fmt1 + fmt2 + fmt3 + fmt4 + fmt5
hdr1 = "obj_ID ID_chip filter xImage yImage ra dec ra_orig dec_orig z mag obj_type "
hdr2 = "thetaR bfrac hlr_disk hlr_bulge e1_disk e2_disk e1_bulge e2_bulge g1 g2 "
hdr3 = "sed_type av redden "
hdr4 = "pm_ra pm_dec RV parallax\n"
fmt1 = "%10d %4d %5s %10.3f %10.3f %15.8f %15.8f %15.8f %15.8f %7.4f %8.4f %15s "
fmt2 = "%8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f "
fmt3 = "%2d %8.4f %8.4f "
fmt4 = "%15.8f %15.8f %15.8f %15.8f\n"
self.hdr = hdr1 + hdr2 + hdr3 + hdr4
self.fmt = fmt1 + fmt2 + fmt3 + fmt4
print("pointing_type = %s\n"%(pointing_type))
if pointing_type == 'MS':
self.cat = open(os.path.join(self.subdir, self.cat_name), "w")
print("Creating catalog file %s ...\n"%(os.path.join(self.subdir, self.cat_name)))
self.cat.write(self.hdr)
def updateHDR(self, hdr):
hdrNew = [{"name":"RDNOISE", "value":self.chip.read_noise, "comment":"read noise in e-/pixel"},
{"name":"DARK", "value":self.chip.dark_noise, "comment":"Dark noise (e-/pixel/s)"},
{"name":"EXPTIME", "value":self.exptime, "comment":"exposure time in second"},
{"name":"GAIN", "value":self.chip.gain, "comment":"CCD gain in e-/ADU"},
{"name":"SATURATE","value":65535.0, "comment":"saturation level"},
{"name":"CCDCHIP", "value":int(self.chipLabel), "comment":"chip ID in the CCD mosaic"},
{"name":"FILTER", "value":self.filt.filter_type, "comment":"filter name"},
{"name":"MJD-OBS", "value":self.mjdTime, "comment":"Modified Julian Date (MJD) of observation"},
{"name":"DATE-OBS","value":self.imgKey1, "comment":"Date of observation"},
{"name":"EQUINOX", "value":2000.0},
{"name":"RADECSYS","value":"ICRS"},
{"name":"RA", "value":self.ra_cen, "comment":"telescope pointing center"},
{"name":"DEC", "value":self.dec_cen, "comment":"telescope pointing center"},
{"name":"OBJECT", "value":"CSS-OS"},
{"name":"WCSDIM", "value":2.0, "comment":"WCS Dimensionality"},
{"name":"EXTNAME", "value":"IM1", "comment":"Extension name"},
{"name":"BSCALE", "value":1.0},
{"name":"BZERO", "value":0.0},
{"name":"OBSID", "value":self.imgKey0, "comment":"Observation ID"},
{"name":"CCDNAME", "value":"ccd"+self.chipLabel,"comment":"CCD name"},
{"name":"RSPEED", "value":10.0, "comment":"Read speed"},
{"name":"CHIPTEMP","value":-100.0, "comment":"Chip temperature"},
{"name":"DATASEC", "value":"1:%d,1:%d"%(self.chip.npix_x,self.chip.npix_y), "comment":"Data section"},
{"name":"CCDSUM", "value":self.chip.npix_x*self.chip.npix_y, "comment":"CCD pixel summing"},
{"name":"NSUM", "value":self.chip.npix_x*self.chip.npix_y, "comment":"CCD pixel summing"},
{"name":"AUTHOR", "value":"CSST-Sim Group"},
{"name":"GROUP", "value":"Weak Lensing Working Group for CSST"}]
for item in hdrNew:
hdr.add_record(item)
return hdr
# def updateHDR(self, hdr):
# hdrNew = [{"name":"RDNOISE", "value":self.chip.read_noise, "comment":"read noise in e-/pixel"},
# {"name":"DARK", "value":self.chip.dark_noise, "comment":"Dark noise (e-/pixel/s)"},
# {"name":"EXPTIME", "value":self.exptime, "comment":"exposure time in second"},
# {"name":"GAIN", "value":self.chip.gain, "comment":"CCD gain in e-/ADU"},
# {"name":"SATURATE","value":65535.0, "comment":"saturation level"},
# {"name":"CCDCHIP", "value":int(self.chipLabel), "comment":"chip ID in the CCD mosaic"},
# {"name":"FILTER", "value":self.filt.filter_type, "comment":"filter name"},
# {"name":"MJD-OBS", "value":self.mjdTime, "comment":"Modified Julian Date (MJD) of observation"},
# {"name":"DATE-OBS","value":self.imgKey1, "comment":"Date of observation"},
# {"name":"EQUINOX", "value":2000.0},
# {"name":"RADECSYS","value":"ICRS"},
# {"name":"RA", "value":self.ra_cen, "comment":"telescope pointing center"},
# {"name":"DEC", "value":self.dec_cen, "comment":"telescope pointing center"},
# {"name":"OBJECT", "value":"CSS-OS"},
# {"name":"WCSDIM", "value":2.0, "comment":"WCS Dimensionality"},
# {"name":"EXTNAME", "value":"IM1", "comment":"Extension name"},
# {"name":"BSCALE", "value":1.0},
# {"name":"BZERO", "value":0.0},
# {"name":"OBSID", "value":self.imgKey0, "comment":"Observation ID"},
# {"name":"CCDNAME", "value":"ccd"+self.chipLabel,"comment":"CCD name"},
# {"name":"RSPEED", "value":10.0, "comment":"Read speed"},
# {"name":"CHIPTEMP","value":-100.0, "comment":"Chip temperature"},
# {"name":"DATASEC", "value":"1:%d,1:%d"%(self.chip.npix_x,self.chip.npix_y), "comment":"Data section"},
# {"name":"CCDSUM", "value":self.chip.npix_x*self.chip.npix_y, "comment":"CCD pixel summing"},
# {"name":"NSUM", "value":self.chip.npix_x*self.chip.npix_y, "comment":"CCD pixel summing"},
# {"name":"AUTHOR", "value":"CSST-Sim Group"},
# {"name":"GROUP", "value":"Weak Lensing Working Group for CSST"}]
# for item in hdrNew:
# hdr.add_record(item)
# return hdr
# def cat_add_obj(self, obj, pos_img, snr, pos_shear, g1, g2):
def cat_add_obj(self, obj, pos_img, pos_shear, g1, g2):
def cat_add_obj(self, obj, pos_img, pos_shear):
ximg = pos_img.x - self.chip.bound.xmin + 1.0
yimg = pos_img.y - self.chip.bound.ymin + 1.0
e1, e2, g1, g2, e1OBS, e2OBS = obj.getObservedEll(g1, g2)
if obj.type == 'galaxy':
line = self.fmt%(obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.z, obj.getMagFilter(self.filt), obj.param["star"], obj.thetaR, obj.bfrac, obj.hlr_disk, obj.hlr_bulge,
obj.e1_disk, obj.e2_disk, obj.e1_bulge, obj.e2_bulge,
pos_shear.g1, pos_shear.g2, e1, e2, g1, g2, e1OBS, e2OBS, obj.sed_type, obj.param['av'], obj.param['redden'], 'n', 0, 0, 0)
elif obj.type == "quasar":
line = self.fmt % (obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.z,
obj.getMagFilter(self.filt), obj.param["star"], 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
pos_shear.g1, pos_shear.g2, e1, e2, g1, g2, e1OBS, e2OBS, obj.sed_type, obj.param['av'], obj.param['redden'], 'n', 0.0, 0.0, 0.0)
else:
line = self.fmt%(obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.z, obj.getMagFilter(self.filt), obj.param["star"], 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
pos_shear.g1, pos_shear.g2, e1, e2, g1, g2, e1OBS, e2OBS, 0, 0.0, 0.0, obj.param['model_tag'], obj.param['teff'], obj.param['logg'],obj.param['feh'])
# line = self.fmt%(obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.z, obj.getMagFilter(self.filt), obj.param["star"], pos_shear.g1, pos_shear.g2, e1, e2, g1, g2, e1OBS, e2OBS)
# if obj.type == 'galaxy':
# line = self.fmt%(obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.z, obj.getMagFilter(self.filt), obj.param["star"], obj.thetaR, obj.bfrac, obj.hlr_disk, obj.hlr_bulge,
# obj.e1_disk, obj.e2_disk, obj.e1_bulge, obj.e2_bulge,
# pos_shear.g1, pos_shear.g2, e1, e2, g1, g2, e1OBS, e2OBS, obj.sed_type, obj.param['av'], obj.param['redden'], 'n', 0, 0, 0)
# elif obj.type == "quasar":
# line = self.fmt % (obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.z,
# obj.getMagFilter(self.filt), obj.param["star"], 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# pos_shear.g1, pos_shear.g2, e1, e2, g1, g2, e1OBS, e2OBS, obj.sed_type, obj.param['av'], obj.param['redden'], 'n', 0.0, 0.0, 0.0)
# else:
# line = self.fmt%(obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.z, obj.getMagFilter(self.filt), obj.param["star"], 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# pos_shear.g1, pos_shear.g2, e1, e2, g1, g2, e1OBS, e2OBS, 0, 0.0, 0.0, obj.param['model_tag'], obj.param['teff'], obj.param['logg'],obj.param['feh'])
# print(
# obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.ra_orig, obj.dec_orig, obj.z, obj.getMagFilter(self.filt), obj.type,
# obj.thetaR, obj.bfrac, obj.hlr_disk, obj.hlr_bulge, obj.e1_disk, obj.e2_disk, obj.e1_bulge, obj.e2_bulge, obj.g1, obj.g2,
# obj.sed_type, obj.av, obj.redden,
# obj.pmra, obj.pmdec, obj.rv, obj.parallax)
line = self.fmt%(
obj.id, int(self.chipLabel), self.filt.filter_type, ximg, yimg, obj.ra, obj.dec, obj.ra_orig, obj.dec_orig, obj.z, obj.getMagFilter(self.filt), obj.type,
obj.thetaR, obj.bfrac, obj.hlr_disk, obj.hlr_bulge, obj.e1_disk, obj.e2_disk, obj.e1_bulge, obj.e2_bulge, obj.g1, obj.g2,
obj.sed_type, obj.av, obj.redden,
obj.pmra, obj.pmdec, obj.rv, obj.parallax)
self.cat.write(line)
ObservationSim/MockObject/Catalog.py deleted 100644 → 0
View file @ a5d541c9
import os
import numpy as np
import random
import galsim
import h5py as h5
import healpy as hp
from astropy.table import Table
from astropy.coordinates import spherical_to_cartesian
from ObservationSim.MockObject.Star import Star
from ObservationSim.MockObject.Galaxy import Galaxy
from ObservationSim.MockObject.Quasar import Quasar
from ObservationSim.MockObject._util import seds, sed_assign, extAv
NSIDE = 128
class Catalog(object):
def __init__(self, config, chip, cat_dir=None, pRa=None, pDec=None, sed_dir=None, rotation=None):
if cat_dir is not None:
self.cat_dir = cat_dir
else:
self.cat_dir = os.path.join(config["data_dir"], config["input_path"]["cat_dir"])
self.sed_dir = sed_dir
self.chip = chip
self.seed_Av = config["random_seeds"]["seed_Av"]
if pRa is not None:
self.pRa = float('{:8.4f}'.format(pRa))
if pDec is not None:
self.pDec = float('{:8.4f}'.format(pDec))
# star_file = 'stars_ccd' + chip.getChipLabel(chip.chipID) + '_p_RA'+str(self.pRa) + '_DE' + str(self.pDec) + '.hdf5'
# galaxy_file = 'galaxies_ccd' + chip.getChipLabel(chip.chipID) + '_p_RA'+str(self.pRa) + '_DE' + str(self.pDec) + '.hdf5'
if "star_cat" in config["input_path"] and config["input_path"]["star_cat"]:
star_file = config["input_path"]["star_cat"]
star_SED_file = config["SED_templates_path"]["star_SED"]
self.star_path = os.path.join(self.cat_dir, star_file)
self.star_SED_path = os.path.join(config["data_dir"], star_SED_file)
self._load_SED_lib_star()
if "galaxy_cat" in config["input_path"] and config["input_path"]["galaxy_cat"]:
galaxy_file = config["input_path"]["galaxy_cat"]
self.galaxy_path = os.path.join(self.cat_dir, galaxy_file)
self.galaxy_SED_path = os.path.join(config["data_dir"], config["SED_templates_path"]["galaxy_SED"])
self._load_SED_lib_gals()
if "rotateEll" in config["shear_setting"]:
self.rotation = float(int(config["shear_setting"]["rotateEll"]/45.))
else:
self.rotation = 0.
# self._load_SED_info()
self._get_healpix_list()
self._load()
def _get_healpix_list(self):
self.sky_coverage = self.chip.getSkyCoverageEnlarged(self.chip.img.wcs, margin=0.2)
# self.sky_coverage_enlarged = self.chip.getSkyCoverageEnlarged(self.chip.img.wcs, margin=0.5)
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]))
# phi, theta = ra, np.pi/2. - dec
# vertices_pix = np.unique(hp.ang2pix(NSIDE, theta, phi))
# print(vertices_pix)
vertices = spherical_to_cartesian(1., dec, ra)
self.pix_list = hp.query_polygon(NSIDE, np.array(vertices).T, inclusive=True)
print("HEALPix List: ", self.pix_list)
def _load_SED_lib_star(self):
self.tempSED_star = h5.File(self.star_SED_path,'r')
def _load_SED_lib_gals(self):
# tempdir_gal = os.path.join(self.template_dir, "Galaxy/")
# tempdir_star = os.path.join(self.template_dir, "PicklesStars/")
# self.tempSed_star, self.tempRed_star = seds("star.list", seddir=tempdir_star)
self.tempSed_gal, self.tempRed_gal = seds("galaxy.list", seddir=self.galaxy_SED_path)
def _load_SED_info(self):
sed_info_file = os.path.join(self.sed_dir, "sed.info")
sed_info = Table.read(sed_info_file, format="ascii")
self.cosids = sed_info["IDCosmoDC2"]
self.objtypes = sed_info["objType"]
def _load_gals(self, gals, pix_id=None):
ngals = len(gals['galaxyID'])
self.rng_sedGal = random.Random()
self.rng_sedGal.seed(pix_id) # Use healpix index as the random seed
self.ud = galsim.UniformDeviate(pix_id)
for igals in range(ngals):
param = {}
param['ra'] = gals['ra_true'][igals]
param['dec'] = gals['dec_true'][igals]
param['z'] = gals['redshift_true'][igals]
param['model_tag'] = 'None'
param['gamma1'] = 0
param['gamma2'] = 0
param['kappa'] = 0
param['delta_ra'] = 0
param['delta_dec'] = 0
sersicB = gals['sersic_bulge'][igals]
hlrMajB = gals['size_bulge_true'][igals]
hlrMinB = gals['size_minor_bulge_true'][igals]
sersicD = gals['sersic_disk'][igals]
hlrMajD = gals['size_disk_true'][igals]
hlrMinD = gals['size_minor_disk_true'][igals]
aGal = gals['size_true'][igals]
bGal = gals['size_minor_true'][igals]
param['bfrac'] = gals['bulge_to_total_ratio_i'][igals]
param['theta'] = gals['position_angle_true'][igals]
param['hlr_bulge'] = np.sqrt(hlrMajB * hlrMinB)
param['hlr_disk'] = np.sqrt(hlrMajD * hlrMinD)
param['ell_bulge'] = (hlrMajB - hlrMinB)/(hlrMajB + hlrMinB)
param['ell_disk'] = (hlrMajD - hlrMinD)/(hlrMajD + hlrMinD)
param['ell_tot'] = (aGal - bGal) / (aGal + bGal)
# Assign each galaxy a template SED
param['sed_type'] = sed_assign(phz=param['z'], btt=param['bfrac'], rng=self.rng_sedGal)
param['redden'] = self.tempRed_gal[param['sed_type']]
param['av'] = self.avGal[int(self.ud()*self.nav)]
if param['sed_type'] <= 5:
param['av'] = 0.0
param['redden'] = 0
param['star'] = 0 # Galaxy
if param['sed_type'] >= 29:
param['av'] = 0.6 * param['av'] / 3.0 # for quasar, av=[0, 0.2], 3.0=av.max-av.im
param['star'] = 2 # Quasar
if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
continue
param['mag_use_normal'] = gals['mag_true_g_lsst'][igals]
if param['mag_use_normal'] >= 26.5:
continue
self.ids += 1
param['id'] = self.ids
if param['star'] == 0:
obj = Galaxy(param, self.rotation)
self.objs.append(obj)
if param['star'] == 2:
obj = Quasar(param)
self.objs.append(obj)
def _load_stars(self, stars, pix_id=None):
nstars = len(stars['sourceID'])
for istars in range(nstars):
param = {}
param['ra'] = stars['RA'][istars]
param['dec'] = stars['Dec'][istars]
if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
continue
param['mag_use_normal'] = stars['app_sdss_g'][istars]
if param['mag_use_normal'] >= 26.5:
continue
self.ids += 1
param['id'] = self.ids
param['sed_type'] = stars['sourceID'][istars]
param['model_tag'] = stars['model_tag'][istars]
param['teff'] = stars['teff'][istars]
param['logg'] = stars['grav'][istars]
param['feh'] = stars['feh'][istars]
param['z'] = 0.0
param['star'] = 1 # Star
obj = Star(param)
self.objs.append(obj)
def _load(self):
self.nav = 15005
self.avGal = extAv(self.nav, seed=self.seed_Av)
gals_cat = h5.File(self.galaxy_path, 'r')['galaxies']
star_cat = h5.File(self.star_path, 'r')['catalog']
self.objs = []
self.ids = 0
for pix in self.pix_list:
gals = gals_cat[str(pix)]
stars = star_cat[str(pix)]
self._load_gals(gals, pix_id=pix)
self._load_stars(stars, pix_id=pix)
print("number of objects in catalog: ", len(self.objs))
del self.avGal
\ No newline at end of file
ObservationSim/MockObject/CatalogBase.py
View file @ 931e5956
......@@ -29,29 +29,33 @@ class CatalogBase(metaclass=ABCMeta):
"star":-1,
"id":-1,
"ra":0,
"dec":0,
"z":0,
"dec":0.,
"ra_orig":0.,
"dec_orig":0.,
"z":0.,
"sed_type":-1,
"model_tag":"unknown",
"mag_use_normal":100,
"theta":0,
"kappa":0,
"gamma1":0,
"gamma2":0,
"bfrac":0,
"hlr_bulge":0,
"hlr_disk":0,
"ell_bulge":0,
"ell_disk":0,
"ell_tot":0,
"teff":0,
"logg":0,
"feh":0,
"g1":0,
"g2":0,
"pmra":0,
"pmdec":0,
"rv":0,
"mag_use_normal":100.,
"theta":0.,
"kappa":0.,
"gamma1":0.,
"gamma2":0.,
"bfrac":0.,
"av":0.,
"redden":0.,
"hlr_bulge":0.,
"hlr_disk":0.,
"ell_bulge":0.,
"ell_disk":0.,
"ell_tot":0.,
"teff":0.,
"logg":0.,
"feh":0.,
"g1":0.,
"g2":0.,
"pmra":0.,
"pmdec":0.,
"rv":0.,
"parallax":1e-9
}
return param
......
ObservationSim/MockObject/Galaxy.py
View file @ 931e5956
......@@ -131,12 +131,12 @@ class Galaxy(MockObject):
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
# gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
# (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
# # (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)
......@@ -220,12 +220,12 @@ class Galaxy(MockObject):
bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
bulge = bulge.shear(bulge_shape)
# gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
# (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
# 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(tel.pupil_area * exptime)
gal_shear = galsim.Shear(g1=g1, g2=g2)
......
ObservationSim/MockObject/MockObject.py
View file @ 931e5956
......@@ -17,15 +17,34 @@ class MockObject(object):
self.type = "star"
elif self.param["star"] == 2:
self.type = "quasar"
self.id = self.param["id"]
self.ra = self.param["ra"]
self.dec = self.param["dec"]
self.ra_orig = self.param["ra_orig"]
self.dec_orig = self.param["dec_orig"]
self.z = self.param["z"]
self.sed_type = self.param["sed_type"]
self.model_tag = self.param["model_tag"]
self.mag_use_normal = self.param["mag_use_normal"]
self.sed = None
# Place holder for outputs
self.av = self.param["av"]
self.redden = self.param["redden"]
self.pmra = self.param["pmra"]
self.pmdec = self.param["pmdec"]
self.rv = self.param["rv"]
self.parallax = self.param["parallax"]
self.g1 = self.param["g1"]
self.g2 = self.param["g2"]
self.thetaR = self.param["theta"]
self.bfrac = self.param["bfrac"]
self.hlr_disk = self.param["hlr_disk"]
self.hlr_bulge = self.param["hlr_bulge"]
self.e1_disk, self.e2_disk = 0., 0.
self.e1_bulge, self.e2_bulge = 0., 0.
def getMagFilter(self, filt):
if filt.filter_type in ["GI", "GV", "GU"]:
return self.param["mag_use_normal"]
......@@ -304,5 +323,5 @@ class MockObject(object):
snr_obj = img_flux / sig_obj
return snr_obj
def getObservedEll(self, g1=0, g2=0):
return 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
# def getObservedEll(self, g1=0, g2=0):
# return 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
ObservationSim/MockObject/__init__.py
View file @ 931e5956
......@@ -3,6 +3,5 @@ from .Galaxy import Galaxy
from .CatalogBase import CatalogBase
from .Quasar import Quasar
from .Star import Star
from .Catalog import Catalog
from .SkybackgroundMap import *
# from .CosmicRay import CosmicRay
\ No newline at end of file
ObservationSim/ObservationSim.py
View file @ 931e5956
......@@ -19,10 +19,8 @@ class Observation(object):
def __init__(self, config, Catalog, work_dir=None, data_dir=None):
self.path_dict = config_dir(config=config, work_dir=work_dir, data_dir=data_dir)
self.config = config
# self.tel = Telescope(optEffCurve_path=self.path_dict["mirror_file"])
self.tel = Telescope()
self.focal_plane = FocalPlane(survey_type=self.config["obs_setting"]["survey_type"])
# self.filter_param = FilterParam(filter_dir=self.path_dict["filter_dir"])
self.filter_param = FilterParam()
self.chip_list = []
self.filter_list = []
......@@ -44,10 +42,6 @@ class Observation(object):
# Make Chip & Filter lists
chip = Chip(
chipID=chipID,
# ccdEffCurve_dir=self.path_dict["ccd_dir"],
# CRdata_dir=self.path_dict["CRdata_dir"],
# normalize_dir=self.path_dict["normalize_dir"],
# sls_dir=self.path_dict["sls_dir"],
config=self.config)
filter_id, filter_type = chip.getChipFilter()
filt = Filter(filter_id=filter_id,
......@@ -114,7 +108,6 @@ class Observation(object):
skyMap=flat_normal,
blueLimit=filt.blue_limit,
redLimit=filt.red_limit,
# skyfn=self.path_dict["sky_file"],
conf=chip.sls_conf,
pixelSize=chip.pix_scale,
isAlongY=0)
......@@ -130,7 +123,7 @@ class Observation(object):
bright_obj = 0
dim_obj = 0
for j in range(self.nobj):
# if j >= 100:
# if j >= 10:
# break
obj = self.cat.objs[j]
if obj.type == 'star' and self.config["run_option"]["galaxy_only"]:
......@@ -170,13 +163,13 @@ class Observation(object):
if self.config["shear_setting"]["shear_type"] == "constant":
if obj.type == 'star':
obj.param["g1"], obj.param["g2"] = 0, 0
obj.g1, obj.g2 = 0., 0.
else:
obj.param["g1"], obj.param["g2"] = self.g1_field, self.g2_field
obj.g1, obj.g2 = self.g1_field, self.g2_field
elif self.config["shear_setting"]["shear_type"] == "extra":
try:
# TODO: every object with individual shear from input catalog(s)
obj.param["g1"], obj.param["g2"] = self.g1_field[j], self.g2_field[j]
obj.g1, obj.g2 = self.g1_field[j], self.g2_field[j]
except:
print("failed to load external shear.")
pass
......@@ -205,8 +198,8 @@ class Observation(object):
bandpass_list=filt.bandpass_sub_list,
filt=filt,
chip=chip,
g1=obj.param["g1"],
g2=obj.param["g2"],
g1=obj.g1,
g2=obj.g2,
exptime=pointing.exp_time
)
elif chip.survey_type == "spectroscopic" and not self.config["run_option"]["out_cat_only"]:
......@@ -217,14 +210,15 @@ class Observation(object):
bandpass_list=filt.bandpass_sub_list,
filt=filt,
chip=chip,
g1=obj.param["g1"],
g2=obj.param["g2"],
g1=obj.g1,
g2=obj.g2,
exptime=pointing.exp_time,
normFilter=norm_filt,
)
if isUpdated:
# TODO: add up stats
chip_output.cat_add_obj(obj, pos_img, pos_shear, obj.param["g1"], obj.param["g2"])
# print("updating output catalog...")
chip_output.cat_add_obj(obj, pos_img, pos_shear)
pass
else:
# print("object omitted", flush=True)
......
config/config_C3.yaml
View file @ 931e5956
......@@ -67,7 +67,6 @@ obs_setting:
image_rot: -113.4333
# Number of calibration pointings
# Note: only valid when a pointing list is specified
np_cal: 0
# Run specific pointing(s):
......@@ -100,7 +99,6 @@ SED_templates_path:
star_SED: "Catalog_20210126/SpecLib.hdf5"
galaxy_SED: "Templates/Galaxy/"
###############################################
# PSF setting
###############################################
......
config/config_NGP.yaml 0 → 100644
View file @ 931e5956
---
###############################################
#
# Configuration file for CSST simulation
# CSST-Sim Group, 2021/10/07, version 0.3
#
###############################################
# Base diretories and naming setup
# Can add some of the command-line arguments here as well;
# OK to pass either way or both, as long as they are consistent
# work_dir: "/public/home/fangyuedong/sim_code_release/CSST/test/"
work_dir: "/public/home/fangyuedong/temp/CSST/workplace/"
data_dir: "/data/simudata/CSSOSDataProductsSims/data/"
run_name: "NGP_20220327"
# (Optional) a file of point list
# if you just want to run default pointing:
# - pointing_dir: null
# - pointing_file: null
pointing_dir: null
pointing_file: null
# Whether to use MPI
run_option:
use_mpi: YES
# NOTE: "n_threads" paramters is currently not used in the backend
# simulation codes. It should be implemented later in the web frontend
# in order to config the number of threads to request from NAOC cluster
n_threads: 80
# Output catalog only?
# If yes, no imaging simulation will run
out_cat_only: NO
# Only simulate stars?
star_only: NO
# Only simulate galaxies?
galaxy_only: NO
###############################################
# Observation setting
###############################################
obs_setting:
# Options for survey types:
# "Photometric": simulate photometric chips only
# "Spectroscopic": simulate slitless spectroscopic chips only
# "All": simulate full focal plane
survey_type: "All"
# Exposure time [seconds]
exp_time: 150.
# Observation starting date & time
# (Subject to change)
date_obs: "210525" # [yymmdd]
time_obs: "120000" # [hhmmss]
# Default Pointing [degrees]
# Note: NOT valid when a pointing list file is specified
ra_center: 192.8595
dec_center: 27.1283
# Image rotation [degree]
image_rot: -113.4333
# Number of calibration pointings
np_cal: 0
# Run specific pointing(s):
# - give a list of indexes of pointings: [ip_1, ip_2...]
# - run all pointings: null
# Note: only valid when a pointing list is specified
run_pointings: null
# Run specific chip(s):
# - give a list of indexes of chips: [ip_1, ip_2...]
# - run all chips: null
# Note: for all pointings
run_chips: null
# Whether to enable astrometric modeling
# astrometric_lib: "libshao.so"
enable_astrometric_model: True
###############################################
# Input path setting
###############################################
# Default path settings for WIDE survey simulation
input_path:
cat_dir: "OnOrbitCalibration/CTargets20211231"
star_cat: "CT-NGP_V2.2.hdf5"
galaxy_cat: "galaxyCats_r_10.0_healpix_shift_192.859500_27.128300.hdf5"
SED_templates_path:
star_SED: "Catalog_20210126/SpecLib.hdf5"
galaxy_SED: "Templates/Galaxy/"
###############################################
# PSF setting
###############################################
psf_setting:
# Which PSF model to use:
# "Gauss": simple gaussian profile
# "Interp": Interpolated PSF from sampled ray-tracing data
psf_model: "Interp"
# PSF size [arcseconds]
# radius of 80% energy encircled
# NOTE: only valid for "Gauss" PSF
psf_rcont: 0.15
# path to PSF data
# NOTE: only valid for "Interp" PSF
psf_dir: "/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/psfCube"
# path to field-distortion model
# Note: only valid when ins_effects: field_dist is "ON"
fd_path: "FieldDistModelGlobal_v1.0.pickle"
# sigma_spin: 0.0 # psf spin?
###############################################
# Shear setting
###############################################
shear_setting:
# Options to generate mock shear field:
# "constant": all galaxies are assigned a constant reduced shear
# "catalog": from catalog (not available yet)
# "extra": from seprate file
shear_type: "constant"
# For constant shear filed
reduced_g1: 0.026
reduced_g2: 0.015
# Representation of the shear vector?
reShear: "E"
# rotate galaxy ellipticity
rotateEll: 0. # [degree]
# Extra shear catalog
# (currently not used)
# shear_cat: "mockShear.cat"
###############################################
# Instrumental effects setting
###############################################
ins_effects:
# switches
field_dist: ON # Whether to add field distortions
add_back: ON # Whether to add sky background
add_dark: ON # Whether to add dark noise
add_readout: ON # Whether to add read-out (Gaussian) noise
add_bias: ON # Whether to add bias-level to images
shutter_effect: ON # Whether to add shutter effect
flat_fielding: ON # Whether to add flat-fielding effect
prnu_effect: ON # Whether to add PRNU effect
non_linear: ON # Whether to add non-linearity
cosmic_ray: ON # Whether to add cosmic-ray
cray_differ: ON # Whether to generate different cosmic ray maps CAL and MS output
cte_trail: OFF # Whether to simulate CTE trails
saturbloom: ON # Whether to simulate Saturation & Blooming
add_badcolumns: ON # Whether to add bad columns
add_hotpixels: ON # Whether to add hot pixels
add_deadpixels: ON # Whether to add dead(dark) pixels
bright_fatter: ON # Whether to simulate Brighter-Fatter (also diffusion) effect
# values
dark_exptime: 300 # Exposure time for dark current frames [seconds]
flat_exptime: 150 # Exposure time for flat-fielding frames [seconds]
readout_time: 40 # The read-out time for each channel [seconds]
df_strength: 2.3 # Sillicon sensor diffusion strength
bias_level: 500 # bias level [e-/pixel]
gain: 1.1 # Gain
full_well: 90000 # Full well depth [e-]
NBias: 1 # Number of bias frames to be exported for each exposure
NDark: 1 # Number of dark frames to be exported for each exposure
NFlat: 1 # Number of flat frames to be exported for each exposure
###############################################
# Output options
###############################################
output_setting:
readout16: OFF # Whether to export as 16 channels (subimages) with pre- and over-scan
shutter_output: OFF # Whether to export shutter effect 16-bit image
bias_output: ON # Whether to export bias frames
dark_output: ON # Whether to export the combined dark current files
flat_output: ON # Whether to export the combined flat-fielding files
prnu_output: OFF # Whether to export the PRNU (pixel-to-pixel flat-fielding) files
###############################################
# Random seeds
###############################################
random_seeds:
seed_Av: 121212 # Seed for generating random intrinsic extinction
seed_poisson: 20210601 # Seed for Poisson noise
seed_CR: 20210317 # Seed for generating random cosmic ray maps
seed_flat: 20210101 # Seed for generating random flat fields
seed_prnu: 20210102 # Seed for photo-response non-uniformity
seed_gainNonUniform: 20210202 # Seed for gain nonuniformity
seed_biasNonUniform: 20210203 # Seed for bias nonuniformity
seed_rnNonUniform: 20210204 # Seed for readout-noise nonuniformity
seed_badcolumns: 20240309 # Seed for bad columns
seed_defective: 20210304 # Seed for defective (bad) pixels
seed_readout: 20210601 # Seed for read-out gaussian noise
...
\ No newline at end of file
run_NGP.pbs 0 → 100755
View file @ 931e5956
#!/bin/bash
#PBS -N SIMS
##PBS -l walltime=70:00:00
##mpdallexit
##mpdboot -n 10 -f ./mpd.hosts
##PBS -j oe
#PBS -l nodes=comput110:ppn=80
#####PBS -q longq
#PBS -q batch
#PBS -u fangyuedong
NP=30
date
echo $NP
mpirun -np $NP python /public/home/fangyuedong/temp/CSST/run_sim.py config_NGP.yaml -c /public/home/fangyuedong/temp/CSST/config
tests/PSFInterpTest/PSFInterpModule_coverage.py 0 → 100644
View file @ 931e5956
import unittest
import sys,os,math
from itertools import islice
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.use('Agg')
import yaml
from ObservationSim.Config import Config
from ObservationSim.Config.Config import config_dir
from ObservationSim.Instrument import Chip
from ObservationSim.PSF.PSFInterp import PSFInterp
def defineCCD(iccd, config_file):
with open(config_file, "r") as stream:
try:
config = yaml.safe_load(stream)
#for key, value in config.items():
# print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
path_dict = config_dir(config=config, work_dir=config['work_dir'], data_dir=config['data_dir'])
chip = Chip(chipID=iccd, config=config)
#chip = Chip(chipID=iccd, ccdEffCurve_dir=path_dict["ccd_dir"], CRdata_dir=path_dict["CRdata_dir"], normalize_dir=path_dict["normalize_dir"], sls_dir=path_dict['sls_dir'], config=config)
return chip
def psfSecondMoments(psfMat, cenX, cenY, pixSize=1):
apr = 0.5 #arcsec, 0.5角秒内测量
fl = 28. #meters
pxs = 2.5 #microns
apr = np.deg2rad(apr/3600.)*fl*1e6
apr = apr/pxs
apr = np.int(np.ceil(apr))
I = psfMat
ncol = I.shape[1]
nrow = I.shape[0]
w = 0.0
w11 = 0.0
w12 = 0.0
w22 = 0.0
for icol in range(ncol):
for jrow in range(nrow):
x = icol*pixSize - cenX
y = jrow*pixSize - cenY
rr = np.sqrt(x*x + y*y)
wgt= 0.0
if rr <= apr:
wgt = 1.0
w += I[jrow, icol]*wgt
w11 += x*x*I[jrow, icol]*wgt
w12 += x*y*I[jrow, icol]*wgt
w22 += y*y*I[jrow, icol]*wgt
w11 /= w
w12 /= w
w22 /= w
sz = w11 + w22
e1 = (w11 - w22)/sz
e2 = 2.0*w12/sz
return sz, e1, e2
def test_psfEll(iccd, iwave, psfMat):
psfMat_iwave = psfMat.psfMat[iwave-1, :,:,:]
npsf = np.shape(psfMat_iwave)[0]
imx = np.zeros(npsf)
imy = np.zeros(npsf)
psf_e1 = np.zeros(npsf)
psf_e2 = np.zeros(npsf)
psf_sz = np.zeros(npsf)
for ipsf in range(1, npsf+1):
print('ipsf-{:}'.format(ipsf), end='\r')
imx[ipsf-1] = psfMat.cen_col[iwave-1, ipsf-1]
imy[ipsf-1] = psfMat.cen_row[iwave-1, ipsf-1]
psfMat_iwave_ipsf = psfMat_iwave[ipsf-1, :, :]
cenX = 256
cenY = 256
sz, e1, e2 = psfSecondMoments(psfMat_iwave_ipsf, cenX, cenY, pixSize=1)
psf_e1[ipsf-1] = e1
psf_e2[ipsf-1] = e2
psf_sz[ipsf-1] = sz
#print('ell======', ipsf, np.sqrt(e1**2 + e2**2))
#######
arr = [imx, imy, psf_e1, psf_e2, psf_sz]
np.save('data/psfEll{:}_{:}_{:}'.format(int(np.sqrt(npsf)),iccd, iwave), arr)
def test_psfEllPlot(OVERPLOT=False):
#if ThisTask == 0:
if True:
prefix = 'psfEll30'
iccd = 1
iwave= 1
data = np.load('data/'+prefix+'_1_1.npy')
imx= data[0]
imy= data[1]
psf_e1 = data[2]
psf_e2 = data[3]
print(np.shape(imx))
npsf = np.shape(imx)[0]
#######
plt.cla()
plt.close("all")
fig = plt.figure(figsize=(12, 12))
plt.subplots_adjust(wspace=0.1, hspace=0.1)
ax = plt.subplot(1, 1, 1)
for ipsf in range(npsf):
plt.plot(imx[ipsf], imy[ipsf], 'r.')
ang = np.arctan2(psf_e2[ipsf], psf_e1[ipsf])/2
ell = np.sqrt(psf_e1[ipsf]**2 + psf_e2[ipsf]**2)
ell *= 15
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
plt.plot([imx[ipsf]-lcos, imx[ipsf]+lcos],[imy[ipsf]-lsin, imy[ipsf]+lsin],'r', lw=2)
###########
ang = 0.
ell = 0.05
ell*= 15
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
plt.plot([imx[898]-lcos, imx[898]+lcos],[imy[898]+5.-lsin, imy[898]+5.+lsin],'k', lw=2)
plt.annotate('{:}'.format(ell/15), (imx[898]-2., imy[898]+6.), xycoords='data', fontsize=10)
plt.xlabel('CCD X (mm)')
plt.ylabel('CCD Y (mm)')
if OVERPLOT == True:
prefix = 'psfEll20'
data = np.load('data/'+prefix+'_1_1.npy')
imx= data[0]
imy= data[1]
psf_e1 = data[2]
psf_e2 = data[3]
npsf = np.shape(imx)[0]
for ipsf in range(npsf):
plt.plot(imx[ipsf], imy[ipsf], 'b.')
ang = np.arctan2(psf_e2[ipsf], psf_e1[ipsf])/2
ell = np.sqrt(psf_e1[ipsf]**2 + psf_e2[ipsf]**2)
ell *= 15
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
plt.plot([imx[ipsf]-lcos, imx[ipsf]+lcos],[imy[ipsf]-lsin, imy[ipsf]+lsin],'b', lw=2)
plt.gca().set_aspect(1)
if OVERPLOT == True:
prefix = 'psfEllOP'
plt.savefig('figs/'+prefix+'_iccd{:}.pdf'.format(iccd))
def test_psfIDW(iccd, iwave, psfMatA, chip, psfMatB):
bandpass = iwave-1
class pos_img():
def __init__(self,x, y):
self.x = x*1e3/10. #in unit of pixels
self.y = y*1e3/10.
psfMat_iwave = psfMatA.psfMat[iwave-1, :,:,:]
npsf = np.shape(psfMat_iwave)[0]
psf_e1 = np.zeros(npsf)
psf_e2 = np.zeros(npsf)
psf_sz = np.zeros(npsf)
for ipsf in range(1, npsf+1):
print('ipsf:', ipsf, end='\r', flush=True)
tpos_img = pos_img(psfMatA.cen_col[iwave-1, ipsf-1], psfMatA.cen_row[iwave-1, ipsf-1])
psfIDW = psfMatB.get_PSF(chip, tpos_img, bandpass, galsimGSObject=False, findNeighMode='treeFind')
np.save('figs/psfIDW/psfIDW_{:}_{:}_{:}'.format(iccd, iwave, ipsf), psfIDW)
cenX = 256
cenY = 256
sz, e1, e2 = psfSecondMoments(psfIDW, cenX, cenY, pixSize=1)
psf_e1[ipsf-1] = e1
psf_e2[ipsf-1] = e2
psf_sz[ipsf-1] = sz
arr = [psf_e1, psf_e2, psf_sz]
np.save('data/psfEll20IDW_{:}_{:}'.format(iccd, iwave), arr)
def test_psfResidualPlot(iccd, iwave, ipsf, psfMatA):
psfMat_iwave = psfMatA.psfMat[iwave-1, :,:,:]
psfMatORG = psfMat_iwave[ipsf-1, :, :]
psfMatIDW = np.load('figs/psfIDW/psfIDW_{:}_{:}_{:}.npy'.format(iccd, iwave, ipsf))
npix = psfMatORG.shape[0]
pixCutEdge= int(npix/2-15)
img0 = psfMatORG[pixCutEdge:npix-pixCutEdge, pixCutEdge:npix-pixCutEdge]
img1 = psfMatIDW[pixCutEdge:npix-pixCutEdge, pixCutEdge:npix-pixCutEdge]
imgX = (img1 - img0)/img0
img0 = np.log10(img0)
img1 = np.log10(img1)
imgX = np.log10(np.abs(imgX))
fig = plt.figure(figsize=(18,4))
ax = plt.subplot(1,3,1)
plt.imshow(img0, origin='lower', vmin=-7, vmax=-1.3)
plt.plot([npix/2-pixCutEdge, npix/2-pixCutEdge],[0, (npix/2-pixCutEdge)*2-1],'w--')
plt.plot([0, (npix/2-pixCutEdge)*2-1],[npix/2-pixCutEdge, npix/2-pixCutEdge],'w--')
plt.annotate('ORG', [0,(npix/2-pixCutEdge)*2-5], c='w', size=15)
cticks=[-7, -6, -5, -4, -3, -2, -1]
cbar = plt.colorbar(ticks=cticks)
cbar.ax.set_yticklabels(['$10^{-7}$', '$10^{-6}$', '$10^{-5}$','$10^{-4}$','$10^{-3}$','$10^{-2}$', '$10^{-1}$'])
print(img0.min(), img0.max())
ax = plt.subplot(1,3,2)
plt.imshow(img1, origin='lower', vmin=-7, vmax=-1.3)
plt.plot([npix/2-pixCutEdge, npix/2-pixCutEdge],[0, (npix/2-pixCutEdge)*2-1],'w--')
plt.plot([0, (npix/2-pixCutEdge)*2-1],[npix/2-pixCutEdge, npix/2-pixCutEdge],'w--')
plt.annotate('IDW', [0,(npix/2-pixCutEdge)*2-5], c='w', size=15)
cticks=[-7, -6, -5, -4, -3, -2, -1]
cbar = plt.colorbar(ticks=cticks)
cbar.ax.set_yticklabels(['$10^{-7}$', '$10^{-6}$', '$10^{-5}$','$10^{-4}$','$10^{-3}$','$10^{-2}$', '$10^{-1}$'])
print(img1.min(), img1.max())
ax = plt.subplot(1,3,3)
plt.imshow(imgX, origin='lower', vmin =-3, vmax =np.log10(3e-1))
plt.plot([npix/2-pixCutEdge, npix/2-pixCutEdge],[0, (npix/2-pixCutEdge)*2-1],'w--')
plt.plot([0, (npix/2-pixCutEdge)*2-1],[npix/2-pixCutEdge, npix/2-pixCutEdge],'w--')
#plt.annotate('(IDW-ORG)/ORG', [0,(npix/2-pixCutEdge)*2-5], c='w', size=15)
cticks=[-5, -4, -3, -2, -1]
cbar = plt.colorbar(ticks=cticks)
cbar.ax.set_yticklabels(['$10^{-5}$','$10^{-4}$','$10^{-3}$','$10^{-2}$', '$10^{-1}$'])
print(np.max((psfMatORG-psfMatIDW)))
plt.savefig('figs/psfResidual_iccd{:}.pdf'.format(iccd))
def test_psfEllIDWPlot(OVERPLOT=False):
#if ThisTask == 0:
if True:
prefix = 'psfEll20'
iccd = 1
iwave= 1
data = np.load('data/'+prefix+'_1_1.npy')
imx= data[0]
imy= data[1]
psf_e1 = data[2]
psf_e2 = data[3]
print(np.shape(imx))
npsf = np.shape(imx)[0]
#######
plt.cla()
plt.close("all")
fig = plt.figure(figsize=(12, 12))
plt.subplots_adjust(wspace=0.1, hspace=0.1)
ax = plt.subplot(1, 1, 1)
for ipsf in range(npsf):
plt.plot(imx[ipsf], imy[ipsf], 'b.')
ang = np.arctan2(psf_e2[ipsf], psf_e1[ipsf])/2
ell = np.sqrt(psf_e1[ipsf]**2 + psf_e2[ipsf]**2)
ell *= 15
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
plt.plot([imx[ipsf]-lcos, imx[ipsf]+lcos],[imy[ipsf]-lsin, imy[ipsf]+lsin],'b', lw=2)
###########
ang = 0.
ell = 0.05
ell*= 15
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
#plt.plot([imx[898]-lcos, imx[898]+lcos],[imy[898]+5.-lsin, imy[898]+5.+lsin],'k', lw=2)
#plt.annotate('{:}'.format(ell/15), (imx[898]-2., imy[898]+6.), xycoords='data', fontsize=10)
plt.xlabel('CCD X (mm)')
plt.ylabel('CCD Y (mm)')
if OVERPLOT == True:
prefix = 'psfEll20IDW'
data = np.load('data/'+prefix+'_1_1.npy')
#imx= data[0]
#imy= data[1]
psf_e1 = data[0]
psf_e2 = data[1]
npsf = np.shape(imx)[0]
for ipsf in range(npsf):
#plt.plot(imx[ipsf], imy[ipsf], 'r.')
ang = np.arctan2(psf_e2[ipsf], psf_e1[ipsf])/2
ell = np.sqrt(psf_e1[ipsf]**2 + psf_e2[ipsf]**2)
ell *= 15
lcos = ell*np.cos(ang)
lsin = ell*np.sin(ang)
plt.plot([imx[ipsf]-lcos, imx[ipsf]+lcos],[imy[ipsf]-lsin, imy[ipsf]+lsin],'r', lw=1)
plt.gca().set_aspect(1)
if OVERPLOT == True:
prefix = 'psfEllOPIDW'
plt.savefig('figs/'+prefix+'_iccd{:}.pdf'.format(iccd))
def test_psfdEllabsPlot(iccd):
#if ThisTask == 0:
if True:
prefix = 'psfEll20'
#iccd = 1
#iwave= 1
data = np.load('data/'+prefix+'_{:}_1.npy'.format(iccd))
imx= data[0]
imy= data[1]
psf_e1 = data[2]
psf_e2 = data[3]
psf_sz = data[4]
print(np.shape(imx))
npsf = np.shape(imx)[0]
ellX = np.sqrt(psf_e1**2 + psf_e2**2)
angX = np.arctan2(psf_e2, psf_e1)/2
angX = np.rad2deg(angX)
szX = psf_sz
##############################
prefix = 'psfEll20IDW'
data = np.load('data/'+prefix+'_{:}_1.npy'.format(iccd))
#imx= data[0]
#imy= data[1]
psf_e1 = data[0]
psf_e2 = data[1]
psf_sz = data[2]
ellY = np.sqrt(psf_e1**2 + psf_e2**2)
angY = np.arctan2(psf_e2, psf_e1)/2
angY = np.rad2deg(angY)
szY = psf_sz
##############################
fig=plt.figure(figsize=(6, 5))
grid = plt.GridSpec(3,1,left=0.15, right=0.95, wspace=None, hspace=0.02)
#plt.subplots_adjust(left=None,bottom=None,right=None,top=None,wspace=None,hspace=0.02)
ax = plt.subplot(grid[0:2,0])
plt.plot([0.01,0.1],[0.01,0.1], 'k--', lw=1. )
plt.scatter(ellX, ellY, color='b', alpha=1., s=3., edgecolors='None')
#plt.xlim([0.015, 0.085])
#plt.ylim([0.015, 0.085])
plt.ylabel('$\epsilon_{\\rm IDW}$')
plt.gca().axes.get_xaxis().set_visible(False)
ax = plt.subplot(grid[2,0])
plt.plot([0.015,0.085],[0.,0.], 'k--', lw=1. )
plt.scatter(ellX, (ellY-ellX), color='b', s=3., edgecolors='None')
#plt.xlim([0.015, 0.085])
#plt.ylim([-0.0018, 0.0018])
plt.xlabel('$\epsilon_{\\rm ORG}$')
plt.ylabel('$\Delta$')
plt.savefig('figs/psfEllOPIDWPDF_{:}.pdf'.format(iccd))
fig=plt.figure(figsize=(6, 6))
plt.hist((szY-szX)/szX, bins=20, color='r', alpha=0.5)
plt.xlabel('$(R_{\\rm IDW}-R_{\\rm ORG})/R_{\\rm ORG}$')
plt.ylabel('PDF')
plt.savefig('figs/psfEllOPIDWPDF_dsz_{:}.pdf'.format(iccd))
class PSFInterpModule_coverage(unittest.TestCase):
def test_psfEll_(self):
iccd = 1
iwave= 1
config_file = "/public/home/weichengliang/CSST_git/newVersion/CSST/config/config_C3.yaml"
chip = defineCCD(iccd, config_file)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
ipath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/psfCubeTest'
psfMatA = PSFInterp(chip, npsf=400, PSF_data_file=ipath, PSF_data_prefix="S20x20_")
psfMatB = PSFInterp(chip, npsf=900, PSF_data_file=ipath, PSF_data_prefix="S30x30_")
test_psfEll(iccd, iwave, psfMatA)
test_psfEll(iccd, iwave, psfMatB)
test_psfEllPlot(OVERPLOT=True)
test_psfIDW(iccd, iwave, psfMatA, chip, psfMatB)
ipsf = 1
test_psfResidualPlot(iccd, iwave, ipsf, psfMatA)
test_psfEllIDWPlot(OVERPLOT=True)
test_psfdEllabsPlot(iccd)
if __name__ == '__main__':
unittest.main()
print('#####haha#####')
tests/PSFInterpTest/loadPSFSet.py 0 → 100644
View file @ 931e5956
import unittest
import sys,os,math
from itertools import islice
import numpy as np
import yaml
from ObservationSim.Config import Config
from ObservationSim.Config.Config import config_dir
from ObservationSim.Instrument import Chip
from ObservationSim.PSF.PSFInterp import PSFInterp
def defineCCD(iccd, config_file):
with open(config_file, "r") as stream:
try:
config = yaml.safe_load(stream)
#for key, value in config.items():
# print (key + " : " + str(value))
except yaml.YAMLError as exc:
print(exc)
path_dict = config_dir(config=config, work_dir=config['work_dir'], data_dir=config['data_dir'])
chip = Chip(chipID=iccd, config=config)
#chip = Chip(chipID=iccd, ccdEffCurve_dir=path_dict["ccd_dir"], CRdata_dir=path_dict["CRdata_dir"], normalize_dir=path_dict["normalize_dir"], sls_dir=path_dict['sls_dir'], config=config)
return chip
def loadPSFSet(iccd):
config_file = "/public/home/weichengliang/CSST_git/newVersion/CSST/config/config_C3.yaml"
chip = defineCCD(iccd, config_file)
print(chip.chipID)
print(chip.cen_pix_x, chip.cen_pix_y)
ipath = '/data/simudata/CSSOSDataProductsSims/data/csstPSFdata/psfCube'
psfMat= PSFInterp(chip, npsf=900, PSF_data_file=ipath, PSF_data_prefix="")
psfSet= psfMat._loadPSF(iccd, ipath, PSF_data_prefix="")
twave = 0 #[0...3]
tpsf = 0 #[0...899]
field_x= psfSet[twave][tpsf]['field_x']
field_y= psfSet[twave][tpsf]['field_y']
image_x= psfSet[twave][tpsf]['image_x']
image_y= psfSet[twave][tpsf]['image_y']
centroid_x= psfSet[twave][tpsf]['centroid_x']
centroid_y= psfSet[twave][tpsf]['centroid_y']
print("pos_info:", field_x, field_y, image_x, image_y, centroid_x, centroid_y)
return psfSet
class PSFInterpModule_coverage(unittest.TestCase):
def test_psfEll_(self):
iccd = 1 #[1...30]
psfSet = loadPSFSet(iccd)
if __name__ == '__main__':
unittest.main()
print('#####haha#####')
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