add notebook for photometry evaluation (3b9f0e28) · Commits · Fang Yuedong / injection_pipeline

.gitignore

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		@@ -7,3 +7,4 @@
		*.so
		*.out
		*pnodes
		*-checkpoint.ipynb
		No newline at end of file

evaluation/photometry_evaluation.ipynb

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injection_pipeline/Catalog/C5_SimCat.py

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		import os
		import numpy as np
		import h5py as h5
		import random
		import galsim
		import astropy.constants as cons
		from astropy.table import Table
		from scipy import interpolate

		from ObservationSim.MockObject import CatalogBase, Star, Galaxy, Quasar
		from ObservationSim.MockObject._util import seds, sed_assign, extAv, tag_sed, getObservedSED

		try:
		import importlib.resources as pkg_resources
		except ImportError:
		# Try backported to PY<37 'importlib_resources'
		import importlib_resources as pkg_resources

		class SimCat(CatalogBase):
		def __init__(self, config, chip, nobjects=None):
		super().__init__()
		self.cat_dir = os.path.join(config["data_dir"], config["input_path"]["cat_dir"])
		self.config = config
		self.chip = chip
		self.seed_Av = config["random_seeds"]["seed_Av"]

		with pkg_resources.path('Catalog.data', 'SLOAN_SDSS.g.fits') as filter_path:
		self.normF_star = Table.read(str(filter_path))
		with pkg_resources.path('Catalog.data', 'lsst_throuput_g.fits') as filter_path:
		self.normF_galaxy = Table.read(str(filter_path))
		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()

		self._load(nobjects=nobjects)

		def _load_SED_lib_star(self):
		self.tempSED_star = h5.File(self.star_SED_path,'r')

		def _load_SED_lib_gals(self):
		self.tempSed_gal, self.tempRed_gal = seds("galaxy.list", seddir=self.galaxy_SED_path)

		def load_norm_filt(self, obj):
		if obj.type == "star":
		return self.normF_star
		elif obj.type == "galaxy" or obj.type == "quasar":
		return self.normF_galaxy
		else:
		return None

		def _load_gals(self, gals, pix_id=None, nobjects=None):
		# Load how mnay objects?
		max_ngals = len(gals)
		if nobjects is None:
		ngals = max_ngals
		else:
		ngals = nobjects
		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 i in range(ngals):
		param = self.initialize_param()
		igals = i % max_ngals
		param['ra'] = gals['ra_true'][igals]
		param['dec'] = gals['dec_true'][igals]

		param['mag_use_normal'] = gals['mag_true_g_lsst'][igals]
		# (TEST) use same magnitude
		# (there will be slight difference due to randomness in SED)
		# param['mag_use_normal'] = 21

		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

		hlrMajB = gals['size_bulge_true'][igals]
		hlrMinB = gals['size_minor_bulge_true'][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

		param['id'] = gals['galaxyID'][igals]

		if param['star'] == 0:
		obj = Galaxy(param)
		if param['star'] == 2:
		obj = Quasar(param)

		self.objs.append(obj)

		def _load(self, nobjects=None):
		# (TEST) use objects in healpix:
		pix = 48656
		self.nav = 15005
		self.avGal = extAv(self.nav, seed=self.seed_Av)
		self.objs = []

		gals_cat = h5.File(self.galaxy_path, 'r')['galaxies']
		gals = gals_cat[str(pix)]
		self._load_gals(gals, pix_id=pix, nobjects=nobjects)
		del gals

		def load_sed(self, obj, **kwargs):
		if obj.type == 'star':
		_, wave, flux = tag_sed(
		h5file=self.tempSED_star,
		model_tag=obj.param['model_tag'],
		teff=obj.param['teff'],
		logg=obj.param['logg'],
		feh=obj.param['feh']
		)
		elif obj.type == 'galaxy' or obj.type == 'quasar':
		sed_data = getObservedSED(
		sedCat=self.tempSed_gal[obj.sed_type],
		redshift=obj.z,
		av=obj.param["av"],
		redden=obj.param["redden"]
		)
		wave, flux = sed_data[0], sed_data[1]
		else:
		raise ValueError("Object type not known")
		speci = interpolate.interp1d(wave, flux)
		lamb = np.arange(2000, 18001 + 0.5, 0.5)
		y = speci(lamb)
		# erg/s/cm2/A --> photo/s/m2/A
		all_sed = y * lamb / (cons.h.value * cons.c.value) * 1e-13
		sed = Table(np.array([lamb, all_sed]).T, names=('WAVELENGTH', 'FLUX'))
		del wave
		del flux
		return sed
		No newline at end of file

measurement_pipeline/run_csst_msc_mbi_photometry.py

+25 −8

Original line number	Diff line number	Diff line
		@@ -9,6 +9,7 @@ from typing import Optional

		def run_csst_msc_mbi_photometry(image_path,
		output_dir,
		flag_weight_dir: str = None,
		weight_path: str = None,
		flag_path: str = None,
		psf_ccds_path: Optional[str] = None,
		@@ -18,11 +19,17 @@ def run_csst_msc_mbi_photometry(image_path,
		input_dir = os.path.dirname(image_path)
		img_filename = os.path.basename(image_path)

		if flag_weight_dir is None:
		flag_weight_dir = input_dir

		if weight_path is None:
		weight_file_name = img_filename.replace("_injected", "")
		weight_path = os.path.join(
		input_dir, img_filename.replace("img", "wht"))
		flag_weight_dir, weight_file_name.replace("img", "wht"))
		if flag_path is None:
		flag_path = os.path.join(input_dir, img_filename.replace("img", "flg"))
		flag_file_name = img_filename.replace("_injected", "")
		flag_path = os.path.join(
		flag_weight_dir, flag_file_name.replace("img", "flg"))

		psf_local_path = os.path.join(
		output_dir, img_filename.replace("img", "psf"))
		@@ -65,12 +72,12 @@ def genearte_path_list_for_one_pointing(input_dir,
		pointing_dir = os.path.join(input_dir, pointing_label)
		if chip_label_list is None:
		image_path_list = glob(
		pointing_dir + '/CSST_MSC_MS_SCIE__' + '_img_*')
		pointing_dir + '/CSST_MSC_MS_SCIE__' + '_img_*.fits')
		else:
		image_path_list = []
		for chip_label in chip_label_list:
		image_path = glob(pointing_dir + '/CSST_MSC_MS_SCIE_*_' +
		chip_label + '_img_*')[0]
		chip_label + '_img_*.fits')[0]
		image_path_list.append(image_path)

		return image_path_list
		@@ -79,9 +86,11 @@ def genearte_path_list_for_one_pointing(input_dir,
		def run_pointing_list(input_dir,
		pointing_label_list,
		output_dir,
		chip_label_list=None):
		chip_label_list=None,
		flag_weight_dir=None):
		image_path_list = []
		output_path_list = []
		fw_dir_list = []
		try:
		if not os.path.exists(output_dir):
		os.makedirs(output_dir)
		@@ -90,6 +99,7 @@ def run_pointing_list(input_dir,

		for pointing_label in pointing_label_list:
		output_pointing_dir = os.path.join(output_dir, pointing_label)
		fw_dir = os.path.join(flag_weight_dir, pointing_label)
		try:
		if not os.path.exists(output_pointing_dir):
		os.makedirs(output_pointing_dir)
		@@ -101,6 +111,7 @@ def run_pointing_list(input_dir,
		image_path_list = image_path_list + temp_img_path_list
		output_path_list = output_path_list + \
		[output_pointing_dir] * len(temp_img_path_list)
		fw_dir_list = fw_dir_list + [fw_dir] * len(temp_img_path_list)

		comm = MPI.COMM_WORLD
		ind_thread = comm.Get_rank()
		@@ -111,21 +122,27 @@ def run_pointing_list(input_dir,
		continue
		image_path = image_path_list[i]
		output_path = output_path_list[i]
		fw_dir = fw_dir_list[i]
		run_csst_msc_mbi_photometry(image_path=image_path,
		output_dir=output_path)
		output_dir=output_path,
		flag_weight_dir=fw_dir)


		if __name__ == "__main__":
		input_dir = "/public/home/fangyuedong/project/50sqDeg_L1_outputs"
		# input_dir = "/public/home/fangyuedong/project/50sqDeg_L1_outputs"
		input_dir = "/public/home/fangyuedong/project/injected_50sqDeg_L1_outputs"
		pointing_label_list = ["MSC_0000000", "MSC_0000001",
		"MSC_0000002", "MSC_0000003", "MSC_0000004", "MSC_0000005"]
		chip_label_list = None
		output_dir = "/public/home/fangyuedong/project/test_photometry"
		# output_dir = "/public/home/fangyuedong/project/test_photometry"
		output_dir = "/public/home/fangyuedong/project/processed_injected_50sqDeg_L1_outputs"
		flag_weight_dir = "/public/home/fangyuedong/project/50sqDeg_L1_outputs"

		# pointing_label_list = ["MSC_0000000"]
		# chip_label_list = ["08"]
		# output_dir = "/public/home/fangyuedong/project/test_photometry"
		run_pointing_list(input_dir=input_dir,
		flag_weight_dir=flag_weight_dir,
		pointing_label_list=pointing_label_list,
		output_dir=output_dir,
		chip_label_list=chip_label_list)