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import os
import gc
import psutil
import traceback
import numpy as np
import galsim
from observation_sim._util import get_shear_field
from observation_sim.psf import PSFGauss, FieldDistortion, PSFInterp, PSFInterpSLS
from astropy.time import Time
from datetime import datetime, timezone
def _is_obj_valid(self, obj):
if obj.param['star'] == 4:
# Currently there's no parameter checks for 'calib' type
return True
pos_keys = ['ra', 'dec']
shape_keys = ['hlr_bulge', 'hlr_disk', 'e1_disk', 'e2_disk', 'e1_bulge', 'e2_bulge']
if any(obj.param[key] == -999. for key in pos_keys):
msg = 'One or more positional information (ra, dec) is missing'
self.chip_output.Log_error(msg)
return False
if obj.param['star'] == 0 and any(obj.param[key] == -999. for key in shape_keys):
msg = 'One or more shape information (hlr_bulge, hlr_disk, e1_disk, e2_disk, e1_bulge, e2_bulge) is missing'
self.chip_output.Log_error(msg)
return False
return True
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def add_objects(self, chip, filt, tel, pointing, catalog, obs_param):
# Get exposure time
if (obs_param) and ("exptime" in obs_param) and (obs_param["exptime"] is not None):
exptime = obs_param["exptime"]
else:
exptime = pointing.exp_time
# Load catalogues
if catalog is None:
self.chip_output.Log_error(
"Catalog interface class must be specified for SCIE-OBS")
raise ValueError(
"Catalog interface class must be specified for SCIE-OBS")
cat = catalog(config=self.overall_config, chip=chip,
pointing=pointing, chip_output=self.chip_output, filt=filt)
# Prepare output file(s) for this chip
# [NOTE] Headers of output .cat file may be updated by Catalog instance
# this should be called after the creation of Catalog instance
self.chip_output.create_output_file()
# Prepare the PSF model
if self.overall_config["psf_setting"]["psf_model"] == "Gauss":
psf_model = PSFGauss(
chip=chip, psfRa=self.overall_config["psf_setting"]["psf_rcont"])
elif self.overall_config["psf_setting"]["psf_model"] == "Interp":
if chip.survey_type == "spectroscopic":
psf_model = PSFInterpSLS(
chip, filt, PSF_data_prefix=self.overall_config["psf_setting"]["psf_sls_dir"])
else:
psf_model = PSFInterp(chip=chip, npsf=chip.n_psf_samples,
PSF_data_file=self.overall_config["psf_setting"]["psf_pho_dir"])
else:
self.chip_output.Log_error("unrecognized PSF model type!!", flush=True)
# Apply field distortion model
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fd_model = FieldDistortion(chip=chip, img_rot=pointing.img_pa.deg)
else:
fd_model = None
# Update limiting magnitudes for all filters based on the exposure time
# Get the filter which will be used for magnitude cut
for ifilt in range(len(self.all_filters)):
temp_filter = self.all_filters[ifilt]
temp_filter.update_limit_saturation_mags(
exptime=pointing.get_full_depth_exptime(temp_filter.filter_type), chip=chip)
if temp_filter.filter_type.lower() == self.overall_config["obs_setting"]["cut_in_band"].lower():
cut_filter = temp_filter
# Read in shear values from configuration file if the constant shear type is used
if self.overall_config["shear_setting"]["shear_type"] == "constant":
g1_field, g2_field, _ = get_shear_field(config=self.overall_config)
self.chip_output.Log_info(
"Use constant shear: g1=%.5f, g2=%.5f" % (g1_field, g2_field))
# Get chip WCS
if not hasattr(self, 'h_ext'):
_, _ = self.prepare_headers(chip=chip, pointing=pointing)
chip_wcs = galsim.FitsWCS(header=self.h_ext)
# Loop over objects
nobj = len(cat.objs)
missed_obj = 0
bright_obj = 0
dim_obj = 0
for j in range(nobj):
# # [DEBUG] [TODO]
# if j >= 10:
# break
obj = cat.objs[j]
if not self._is_obj_valid(obj):
continue
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# load and convert SED; also caculate object's magnitude in all CSST bands
try:
sed_data = cat.load_sed(obj)
norm_filt = cat.load_norm_filt(obj)
obj.sed, obj.param["mag_%s" % filt.filter_type.lower()], obj.param["flux_%s" % filt.filter_type.lower()] = cat.convert_sed(
mag=obj.param["mag_use_normal"],
sed=sed_data,
target_filt=filt,
norm_filt=norm_filt,
mu=obj.mu
)
_, obj.param["mag_%s" % cut_filter.filter_type.lower()], obj.param["flux_%s" % cut_filter.filter_type.lower()] = cat.convert_sed(
mag=obj.param["mag_use_normal"],
sed=sed_data,
target_filt=cut_filter,
norm_filt=norm_filt,
mu=obj.mu
)
except Exception as e:
traceback.print_exc()
self.chip_output.Log_error(e)
continue
# [TODO] Testing
# self.chip_output.Log_info("mag_%s = %.3f"%(filt.filter_type.lower(), obj.param["mag_%s"%filt.filter_type.lower()]))
# Exclude very bright/dim objects (for now)
if cut_filter.is_too_bright(
mag=obj.param["mag_%s" %
self.overall_config["obs_setting"]["cut_in_band"].lower()],
margin=self.overall_config["obs_setting"]["mag_sat_margin"]):
self.chip_output.Log_info("obj %s too birght!! mag_%s = %.3f" % (
obj.id, cut_filter.filter_type, obj.param["mag_%s" % self.overall_config["obs_setting"]["cut_in_band"].lower()]))
bright_obj += 1
obj.unload_SED()
continue
if filt.is_too_dim(
mag=obj.getMagFilter(filt),
margin=self.overall_config["obs_setting"]["mag_lim_margin"]):
self.chip_output.Log_info("obj %s too dim!! mag_%s = %.3f" % (
obj.id, filt.filter_type, obj.getMagFilter(filt)))
dim_obj += 1
obj.unload_SED()
continue
# Get corresponding shear values
if self.overall_config["shear_setting"]["shear_type"] == "constant":
if obj.type == 'star':
obj.g1, obj.g2 = 0., 0.
else:
# Figure out shear fields from overall configuration shear setting
obj.g1, obj.g2 = g1_field, g2_field
elif self.overall_config["shear_setting"]["shear_type"] == "catalog":
pass
else:
self.chip_output.Log_error("Unknown shear input")
raise ValueError("Unknown shear input")
# Get position of object on the focal plane
pos_img, _, _, _, fd_shear = obj.getPosImg_Offset_WCS(
img=chip.img, fdmodel=fd_model, chip=chip, verbose=False, chip_wcs=chip_wcs, img_header=self.h_ext, ra_offset=self.ra_offset, dec_offset=self.dec_offset)
# [TODO] For now, only consider objects which their centers (after field distortion) are projected within the focal plane
# Otherwise they will be considered missed objects
# if pos_img.x == -1 or pos_img.y == -1 or (not chip.isContainObj(x_image=pos_img.x, y_image=pos_img.y, margin=0.)):
if pos_img.x == -1 or pos_img.y == -1:
self.chip_output.Log_info('obj_ra = %.6f, obj_dec = %.6f, obj_ra_orig = %.6f, obj_dec_orig = %.6f' % (
obj.ra, obj.dec, obj.ra_orig, obj.dec_orig))
self.chip_output.Log_error("Object missed: %s" % (obj.id))
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missed_obj += 1
obj.unload_SED()
continue
# Draw object & update output catalog
try:
if self.overall_config["run_option"]["out_cat_only"]:
isUpdated = True
obj.real_pos = obj.getRealPos(
chip.img, global_x=obj.posImg.x, global_y=obj.posImg.y, img_real_wcs=obj.chip_wcs)
pos_shear = 0.
elif chip.survey_type == "photometric" and not self.overall_config["run_option"]["out_cat_only"]:
isUpdated, pos_shear = obj.drawObj_multiband(
tel=tel,
pos_img=pos_img,
psf_model=psf_model,
bandpass_list=filt.bandpass_sub_list,
filt=filt,
chip=chip,
g1=obj.g1,
g2=obj.g2,
exptime=exptime,
fd_shear=fd_shear)
elif chip.survey_type == "spectroscopic" and not self.overall_config["run_option"]["out_cat_only"]:
isUpdated, pos_shear = obj.drawObj_slitless(
tel=tel,
pos_img=pos_img,
psf_model=psf_model,
bandpass_list=filt.bandpass_sub_list,
filt=filt,
chip=chip,
g1=obj.g1,
g2=obj.g2,
exptime=exptime,
normFilter=norm_filt,
fd_shear=fd_shear)
if isUpdated == 1:
# TODO: add up stats
self.chip_output.cat_add_obj(
obj, pos_img, pos_shear, ra_offset=self.ra_offset, dec_offset=self.dec_offset)
self.chip_output.Log_error("Object missed: %s" % (obj.id))
else:
self.chip_output.Log_error(
"Draw error, object omitted: %s" % (obj.id))
continue
except Exception as e:
traceback.print_exc()
self.chip_output.Log_error(e)
self.chip_output.Log_error(
"pointing: #%d, chipID: %d" % (pointing.id, chip.chipID))
if obj.type == "galaxy":
self.chip_output.Log_error("obj id: %s" % (obj.param['id']))
self.chip_output.Log_error(" e1: %.5f\n e2: %.5f\n size: %f\n bfrac: %f\n detA: %f\n g1: %.5f\n g2: %.5f\n" % (
obj.param['e1'], obj.param['e2'], obj.param['size'], obj.param['bfrac'], obj.param['detA'], obj.param['g1'], obj.param['g2']))
# Unload SED:
obj.unload_SED()
del obj
if chip.survey_type == "spectroscopic" and not self.overall_config["run_option"]["out_cat_only"] and chip.slsPSFOptim:
# from observation_sim.instruments.chip import chip_utils as chip_utils
# gn = chip_utils.getChipSLSGratingID(chip.chipID)[0]
# img1 = np.zeros([2,chip.img.array.shape[0],chip.img.array.shape[1]])
# for id1 in np.arange(2):
# gn = chip_utils.getChipSLSGratingID(chip.chipID)[id1]
# img_i = 0
# for id2 in ['0','1']:
# o_n = "order"+id2
# for id3 in ['1','2','3','4']:
# w_n = "w"+id3
# img1[img_i] = img1[img_i] + chip.img_stack[gn][o_n][w_n].array
# img_i = img_i + 1
# from astropy.io import fits
# fits.writeto('order0.fits',img1[0],overwrite=True)
# fits.writeto('order1.fits',img1[1],overwrite=True)
psf_model.convolveFullImgWithPCAPSF(chip)
del psf_model
gc.collect()
self.chip_output.Log_info("Running checkpoint #1 (Object rendering finished): pointing-%d chip-%d pid-%d memory-%6.2fGB" %
(pointing.id, chip.chipID, os.getpid(), (psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024)))
self.chip_output.Log_info(
"# objects that are too bright %d out of %d" % (bright_obj, nobj))
self.chip_output.Log_info(
"# objects that are too dim %d out of %d" % (dim_obj, nobj))
self.chip_output.Log_info(
"# objects that are missed %d out of %d" % (missed_obj, nobj))
# Apply flat fielding (with shutter effects)
flat_normal = np.ones_like(chip.img.array)
flat_normal = flat_normal * chip.flat_img.array / \
np.mean(chip.flat_img.array)
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flat_normal = flat_normal * chip.shutter_img
flat_normal = np.array(flat_normal, dtype='float32')
self.updateHeaderInfo(header_flag='ext', keys=[
'SHTSTAT'], values=[True])
else:
self.updateHeaderInfo(header_flag='ext', keys=['SHTSTAT', 'SHTOPEN1', 'SHTCLOS0'], values=[
True, self.h_ext['SHTCLOS1'], self.h_ext['SHTOPEN0']])
chip.img *= flat_normal
del flat_normal
# renew header info
datetime_obs = datetime.utcfromtimestamp(pointing.timestamp)
datetime_obs = datetime_obs.replace(tzinfo=timezone.utc)
t_obs = Time(datetime_obs)
# ccd刷新2s,等待0.s，开始曝光
t_obs_renew = Time(t_obs.mjd - (2.+0.) / 86400., format="mjd")
t_obs_utc = datetime.utcfromtimestamp(np.round(datetime.utcfromtimestamp(
t_obs_renew.unix).replace(tzinfo=timezone.utc).timestamp(), 1))
self.updateHeaderInfo(header_flag='prim', keys=[
'DATE-OBS'], values=[t_obs_utc.strftime("%Y-%m-%dT%H:%M:%S.%f")[:-5]])
# dark time : 曝光时间+刷新后等带时间0.s+关快门后读出前等待0.s
self.updateHeaderInfo(header_flag='ext', keys=[
'DARKTIME'], values=[0.+0.+pointing.exp_time])
return chip, filt, tel, pointing