Commit 716634ad authored by Fang Yuedong's avatar Fang Yuedong
Browse files

Merge remote-tracking branch 'origin/new_sim_sls' into new_sim

parents 14f5a535 8918310a
......@@ -270,7 +270,7 @@ class Chip(FocalPlane):
noise = self.dark_noise * exptime + self.read_noise**2
return noise
def addEffects(self, config, img, chip_output, filt, ra_cen, dec_cen, img_rot, exptime=150., pointing_ID=0, timestamp_obs=1621915200, pointing_type='SCI', sky_map=None, tel=None, logger=None):
def addEffects(self, config, img, chip_output, filt, ra_cen, dec_cen, img_rot, exptime=150., pointing_ID=0, timestamp_obs=1621915200, pointing_type='SCI', sky_map=None, post_flash_map=None, tel=None, logger=None):
# Set random seeds
SeedGainNonuni=int(config["random_seeds"]["seed_gainNonUniform"])
SeedBiasNonuni=int(config["random_seeds"]["seed_biasNonUniform"])
......@@ -309,6 +309,9 @@ class Chip(FocalPlane):
if config["output_setting"]["flat_output"] == False:
del flat_img
if post_flash_map is not None:
img = img + post_flash_map
# Apply Shutter-effect for one chip
if config["ins_effects"]["shutter_effect"] == True:
chip_utils.log_info(msg=" Apply shutter effect", logger=self.logger)
......@@ -320,7 +323,6 @@ class Chip(FocalPlane):
shutt_gsimg.write("%s/ShutterEffect_%s_1.fits" % (chip_output.subdir, self.chipID))
del shutt_gsimg
del shuttimg
# # Add Poisson noise to the resulting images
# # (NOTE): this can only applied to the slitless image
# # since it dose not use photon shooting to draw stamps
......
import galsim
import os, sys
import numpy as np
from astropy.io import fits
from scipy.interpolate import griddata
import math
import astropy.constants as cons
from astropy.table import Table
from ObservationSim.MockObject.SpecDisperser import SpecDisperser
import time
from scipy import interpolate
from ObservationSim.MockObject.MockObject import MockObject
# from ObservationSim.Straylight import calculateSkyMap_split_g
# flatDir = '/Volumes/EAGET/LED_FLAT/'
LED_name = ['LED1', 'LED2', 'LED3', 'LED4', 'LED5', 'LED6', 'LED7', 'LED8', 'LED9', 'LED10', 'LED11', 'LED12', 'LED13',
'LED14']
cwaves_name = {'LED1': '275', 'LED2': '310', 'LED3': '430', 'LED4': '505', 'LED5': '545', 'LED6': '590', 'LED7': '670',
'LED8': '760', 'LED9': '940', 'LED10': '940', 'LED11': '1050', 'LED12': '1050',
'LED13': '340', 'LED14': '365'}
cwaves = {'LED1': 2750, 'LED2': 3100, 'LED3': 4300, 'LED4': 5050, 'LED5': 5250, 'LED6': 5900, 'LED7': 6700,
'LED8': 7600, 'LED9': 8800, 'LED10': 9400, 'LED11': 10500, 'LED12': 15500, 'LED13': 3400, 'LED14': 3650}
cwaves_fwhm = {'LED1': 110, 'LED2': 120, 'LED3': 200, 'LED4': 300, 'LED5': 300, 'LED6': 130, 'LED7': 210,
'LED8': 260, 'LED9': 400, 'LED10': 370, 'LED11': 500, 'LED12': 1400, 'LED13': 90, 'LED14': 100}
# LED_QE = {'LED1': 0.3, 'LED2': 0.4, 'LED13': 0.5, 'LED14': 0.5, 'LED10': 0.4}
# e-/ms
fluxLED = {'LED1': 0.16478729, 'LED2': 0.084220931, 'LED3': 2.263360617, 'LED4': 2.190623489, 'LED5': 0.703504768,
'LED6': 0.446117963, 'LED7': 0.647122098, 'LED8': 0.922313442,
'LED9': 0.987278143, 'LED10': 2.043989167, 'LED11': 0.612571429, 'LED12': 1.228915663, 'LED13': 0.17029384,
'LED14': 0.27842925}
mirro_eff = {'GU':0.61, 'GV':0.8, 'GI':0.8}
class FlatLED(object):
def __init__(self, chip,filt, flatDir = '/Users/zhangxin/Work/SlitlessSim/csst_sls_calibration/flat_field_cube/models/', logger=None):
# self.led_type_list = led_type_list
self.flatDir = flatDir
self.filt = filt
self.chip = chip
self.logger = logger
###
### return LED flat, e/s
###
def getLEDImage(self, led_type='LED1'):
# cwave = cwaves[led_type]
flat = fits.open(self.flatDir + 'model_' + cwaves_name[led_type] + 'nm.fits')
xlen = flat[0].header['NAXIS1']
ylen = 601
x = np.linspace(0, self.chip.npix_x * 6, xlen)
y = np.linspace(0, self.chip.npix_y * 5, ylen)
xx, yy = np.meshgrid(x, y)
a1 = flat[0].data[0:ylen, 0:xlen]
# z = np.sin((xx+yy+xx**2+yy**2))
# fInterp = interp2d(xx, yy, z, kind='linear')
X_ = np.hstack((xx.flatten()[:, None], yy.flatten()[:, None]))
Z_ = a1.flatten()
n_x = np.arange(0, self.chip.npix_x * 6, 1)
n_y = np.arange(0, self.chip.npix_y * 5, 1)
M, N = np.meshgrid(n_x, n_y)
i = self.chip.rowID - 1
j = self.chip.colID - 1
U = griddata(X_, Z_, (
M[self.chip.npix_y * i:self.chip.npix_y * (i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)],
N[self.chip.npix_y * i:self.chip.npix_y * (i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)]),
method='cubic')
U = U/np.mean(U)
flatImage = U*fluxLED[led_type]*1000
return flatImage
def drawObj_LEDFlat_img(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if len(led_type_list) > len(exp_t_list):
return np.ones([self.chip.npix_y,self.chip.npix_x])
ledFlat = np.zeros([self.chip.npix_y,self.chip.npix_x])
for i in np.arange(len(led_type_list)):
led_type = led_type_list[i]
exp_t = exp_t_list[i]
unitFlatImg = self.getLEDImage(led_type=led_type)
led_wave = cwaves[led_type]
led_fwhm = cwaves_fwhm[led_type]
led_spec = self.gaussian1d_profile_led(led_wave, led_fwhm)
speci = interpolate.interp1d(led_spec['WAVELENGTH'], led_spec['FLUX'])
w_list = np.arange(self.filt.blue_limit, self.filt.red_limit, 0.5) #A
f_spec = speci(w_list)
ccd_bp = self.chip._getChipEffCurve(self.chip.filter_type)
ccd_eff = ccd_bp.__call__(w_list / 10.)
filt_bp = self.filt.filter_bandpass
fil_eff = filt_bp.__call__(w_list / 10.)
t_spec = np.trapz(f_spec*ccd_eff*fil_eff, w_list)
# print(i, np.mean(unitFlatImg), t_spec, exp_t)
unitFlatImg = unitFlatImg * t_spec
ledFlat = ledFlat+unitFlatImg*exp_t
return ledFlat
def drawObj_LEDFlat_slitless(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if len(led_type_list) != len(exp_t_list):
return np.ones([self.chip.npix_y,self.chip.npix_x])
ledFlat = np.zeros([self.chip.npix_y,self.chip.npix_x])
for i in np.arange(len(led_type_list)):
led_type = led_type_list[i]
exp_t = exp_t_list[i]
unitFlatImg = self.getLEDImage(led_type=led_type)
ledFlat_ = unitFlatImg*exp_t
ledFlat_ = ledFlat_ / mirro_eff[self.filt.filter_type]
ledFlat_.astype(np.float32)
led_wave = cwaves[led_type]
led_fwhm = cwaves_fwhm[led_type]
led_spec = self.gaussian1d_profile_led(led_wave, led_fwhm)
ledspec_map = self.calculateLEDSpec(
skyMap=ledFlat_,
blueLimit=self.filt.blue_limit,
redLimit=self.filt.red_limit,
conf=self.chip.sls_conf,
pixelSize=self.chip.pix_scale,
isAlongY=0,
flat_cube=self.chip.flat_cube, led_spec=led_spec)
ledFlat = ledFlat + ledspec_map
return ledFlat
def drawObj_LEDFlat(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if self.chip.survey_type == "photometric":
return self.drawObj_LEDFlat_img(led_type_list=led_type_list, exp_t_list=exp_t_list)
elif self.chip.survey_type == "spectroscopic":
return self.drawObj_LEDFlat_slitless(led_type_list=led_type_list, exp_t_list=exp_t_list)
def gaussian1d_profile_led(self, xc=5050, fwhm=300):
sigma = fwhm/2.355
x_radii = int(5*sigma + 1)
xlist = np.arange(xc-x_radii, xc+x_radii, 0.5)
xlist_ = np.zeros(len(xlist) + 2)
xlist_[1:-1] = xlist
xlist_[0] = 2550
xlist_[-1] = 10000
data = np.exp((-(xlist-xc)*(xlist-xc))/(2*sigma*sigma))/(np.sqrt(2*math.pi)*sigma)
data_ = np.zeros(len(xlist) + 2)
data_[1:-1] = data
return Table(np.array([xlist_.astype(np.float32), data_.astype(np.float32)]).T, names=('WAVELENGTH', 'FLUX'))
def calculateLEDSpec(self, skyMap=None, blueLimit=4200, redLimit=6500,
conf=[''], pixelSize=0.074, isAlongY=0,
split_pos=3685, flat_cube=None, led_spec=None):
conf1 = conf[0]
conf2 = conf[0]
if np.size(conf) == 2:
conf2 = conf[1]
skyImg = galsim.Image(skyMap, xmin=0, ymin=0)
tbstart = blueLimit
tbend = redLimit
fimg = np.zeros_like(skyMap)
fImg = galsim.Image(fimg)
spec = led_spec
if isAlongY == 0:
directParm = 0
if isAlongY == 1:
directParm = 1
if split_pos >= skyImg.array.shape[directParm]:
skyImg1 = galsim.Image(skyImg.array)
origin1 = [0, 0]
# sdp = specDisperser.specDisperser(orig_img=skyImg1, xcenter=skyImg1.center.x, ycenter=skyImg1.center.y,
# full_img=fimg, tar_spec=spec, band_start=tbstart, band_end=tbend,
# origin=origin1,
# conf=conf1)
# sdp.compute_spec_orders()
y_len = skyMap.shape[0]
x_len = skyMap.shape[1]
delt_x = 100
delt_y = 100
sub_y_start_arr = np.arange(0, y_len, delt_y)
sub_y_end_arr = sub_y_start_arr + delt_y
sub_y_end_arr[-1] = min(sub_y_end_arr[-1], y_len)
sub_x_start_arr = np.arange(0, x_len, delt_x)
sub_x_end_arr = sub_x_start_arr + delt_x
sub_x_end_arr[-1] = min(sub_x_end_arr[-1], x_len)
for i, k1 in enumerate(sub_y_start_arr):
sub_y_s = k1
sub_y_e = sub_y_end_arr[i]
sub_y_center = (sub_y_s + sub_y_e) / 2.
for j, k2 in enumerate(sub_x_start_arr):
sub_x_s = k2
sub_x_e = sub_x_end_arr[j]
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2.
sdp = SpecDisperser(orig_img=skyImg_sub, xcenter=sub_x_center, ycenter=sub_y_center,
origin=origin_sub,
tar_spec=spec,
band_start=tbstart, band_end=tbend,
conf=conf2,
flat_cube=flat_cube, ignoreBeam=['D', 'E'])
spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items():
img_s = v[0]
origin_order_x = v[1]
origin_order_y = v[2]
ssImg = galsim.ImageF(img_s)
ssImg.setOrigin(origin_order_x, origin_order_y)
bounds = ssImg.bounds & fImg.bounds
if bounds.area() == 0:
continue
fImg[bounds] = fImg[bounds] + ssImg[bounds]
else:
# sdp.compute_spec_orders()
y_len = skyMap.shape[0]
x_len = skyMap.shape[1]
delt_x = 500
delt_y = y_len
sub_y_start_arr = np.arange(0, y_len, delt_y)
sub_y_end_arr = sub_y_start_arr + delt_y
sub_y_end_arr[-1] = min(sub_y_end_arr[-1], y_len)
delt_x = split_pos - 0
sub_x_start_arr = np.arange(0, split_pos, delt_x)
sub_x_end_arr = sub_x_start_arr + delt_x
sub_x_end_arr[-1] = min(sub_x_end_arr[-1], split_pos)
for i, k1 in enumerate(sub_y_start_arr):
sub_y_s = k1
sub_y_e = sub_y_end_arr[i]
sub_y_center = (sub_y_s + sub_y_e) / 2.
for j, k2 in enumerate(sub_x_start_arr):
sub_x_s = k2
sub_x_e = sub_x_end_arr[j]
# print(i,j,sub_y_s, sub_y_e,sub_x_s,sub_x_e)
T1 = time.time()
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2.
sdp = SpecDisperser(orig_img=skyImg_sub, xcenter=sub_x_center, ycenter=sub_y_center,
origin=origin_sub,
tar_spec=spec,
band_start=tbstart, band_end=tbend,
conf=conf1,
flat_cube=flat_cube)
spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items():
img_s = v[0]
origin_order_x = v[1]
origin_order_y = v[2]
ssImg = galsim.ImageF(img_s)
ssImg.setOrigin(origin_order_x, origin_order_y)
bounds = ssImg.bounds & fImg.bounds
if bounds.area() == 0:
continue
fImg[bounds] = fImg[bounds] + ssImg[bounds]
T2 = time.time()
print('time: %s ms' % ((T2 - T1) * 1000))
delt_x = x_len - split_pos
sub_x_start_arr = np.arange(split_pos, x_len, delt_x)
sub_x_end_arr = sub_x_start_arr + delt_x
sub_x_end_arr[-1] = min(sub_x_end_arr[-1], x_len)
for i, k1 in enumerate(sub_y_start_arr):
sub_y_s = k1
sub_y_e = sub_y_end_arr[i]
sub_y_center = (sub_y_s + sub_y_e) / 2.
for j, k2 in enumerate(sub_x_start_arr):
sub_x_s = k2
sub_x_e = sub_x_end_arr[j]
# print(i,j,sub_y_s, sub_y_e,sub_x_s,sub_x_e)
T1 = time.time()
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2.
sdp = SpecDisperser(orig_img=skyImg_sub, xcenter=sub_x_center, ycenter=sub_y_center,
origin=origin_sub,
tar_spec=spec,
band_start=tbstart, band_end=tbend,
conf=conf2,
flat_cube=flat_cube)
spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items():
img_s = v[0]
origin_order_x = v[1]
origin_order_y = v[2]
ssImg = galsim.ImageF(img_s)
ssImg.setOrigin(origin_order_x, origin_order_y)
bounds = ssImg.bounds & fImg.bounds
if bounds.area() == 0:
continue
fImg[bounds] = fImg[bounds] + ssImg[bounds]
T2 = time.time()
print('time: %s ms' % ((T2 - T1) * 1000))
if isAlongY == 1:
fimg, tmx, tmy = rotate90(array_orig=fImg.array, xc=0, yc=0, isClockwise=0)
else:
fimg = fImg.array
fimg = fimg * pixelSize * pixelSize
return fimg
......@@ -239,7 +239,7 @@ class SpecDisperser(object):
# else:
# beam_flat[k] = self.flat_cube[:, originOut_y + i, originOut_x + j]
status = disperse.disperse_grism_object(self.thumb_img,
status = disperse.disperse_grism_object(self.thumb_img.astype(np.float32),
flat_index[nonz], yfrac_beam[nonz],
sensitivity_beam[nonz],
modelf, x0,
......
......@@ -4,5 +4,6 @@ from .CatalogBase import CatalogBase
from .Quasar import Quasar
from .Star import Star
from .Stamp import Stamp
from .FlatLED import FlatLED
# from .SkybackgroundMap import *
# from .CosmicRay import CosmicRay
......@@ -18,6 +18,7 @@ from ObservationSim.Straylight import calculateSkyMap_split_g
from ObservationSim.PSF import PSFGauss, FieldDistortion, PSFInterp, PSFInterpSLS
from ObservationSim._util import get_shear_field, makeSubDir_PointingList
from ObservationSim.Astrometry.Astrometry_util import on_orbit_obs_position
from ObservationSim.MockObject import FlatLED
class Observation(object):
def __init__(self, config, Catalog, work_dir=None, data_dir=None):
......@@ -196,8 +197,8 @@ class Observation(object):
for j in range(self.nobj):
# (DEBUG)
# if j >= 10:
# break
if j >= 10:
break
obj = self.cat.objs[j]
......@@ -414,6 +415,139 @@ class Observation(object):
chip_output.Log_info("check running:2: 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) ))
def run_one_chip_calibration(self, chip, filt, pointing, chip_output, skyback_level = 20000, sky_level_filt = 'g', wcs_fp=None, psf_model=None, cat_dir=None, sed_dir=None):
# # Get WCS for the focal plane
# if wcs_fp == None:
# wcs_fp = self.focal_plane.getTanWCS(ra_cen, dec_cen, pointing.img_pa, chip.pix_scale)
# Create chip Image
chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
# chip.img.wcs = wcs_fp
pf_map = np.zeros_like(chip.img.array)
if self.config["obs_setting"]["LED_TYPE"] is not None:
if len(self.config["obs_setting"]["LED_TYPE"]) != 0:
print("LED OPEN--------")
led_obj = FlatLED(chip, filt)
led_flat = led_obj.drawObj_LEDFlat(led_type_list=self.config["obs_setting"]["LED_TYPE"], exp_t_list=self.config["obs_setting"]["LED_TIME"])
pf_map = led_flat
# whether to output zero, dark, flat calibration images.
expTime = self.config["obs_setting"]["exp_time"]
skybg_unit = self.filter_param.param[sky_level_filt][5]
norm_scaler = skyback_level/expTime/skybg_unit
if skyback_level == 0:
self.config["ins_effects"]["shutter_effect"] = False
if chip.survey_type == "photometric":
sky_map = np.ones_like(chip.img.array) * skybg_unit * norm_scaler / self.tel.pupil_area
elif chip.survey_type == "spectroscopic":
flat_normal = np.ones_like(chip.img.array)
if self.config["ins_effects"]["flat_fielding"] == True:
chip_output.Log_info("SLS flat preprocess,CHIP %d : Creating and applying Flat-Fielding" % chip.chipID)
msg = str(chip.img.bounds)
chip_output.Log_info(msg)
flat_img = Effects.MakeFlatSmooth(
chip.img.bounds,
int(self.config["random_seeds"]["seed_flat"]))
flat_normal = flat_normal * flat_img.array / np.mean(flat_img.array)
if self.config["ins_effects"]["shutter_effect"] == True:
chip_output.Log_info("SLS flat preprocess,CHIP %d : Apply shutter effect" % chip.chipID)
shuttimg = Effects.ShutterEffectArr(chip.img, t_shutter=1.3, dist_bearing=735,
dt=1E-3) # shutter effect normalized image for this chip
flat_normal = flat_normal * shuttimg
flat_normal = np.array(flat_normal, dtype='float32')
sky_map = calculateSkyMap_split_g(
skyMap=flat_normal,
blueLimit=filt.blue_limit,
redLimit=filt.red_limit,
conf=chip.sls_conf,
pixelSize=chip.pix_scale,
isAlongY=0,
flat_cube=chip.flat_cube)
sky_map = sky_map * norm_scaler
chip.img = chip.addEffects(
config=self.config,
img=chip.img,
chip_output=chip_output,
filt=filt,
ra_cen=pointing.ra,
dec_cen=pointing.dec,
img_rot=pointing.img_pa,
exptime=self.config["obs_setting"]["exp_time"],
pointing_ID=pointing.id,
timestamp_obs=pointing.timestamp,
pointing_type=pointing.pointing_type,
sky_map=sky_map, tel=self.tel,
post_flash_map=pf_map,
logger=chip_output.logger)
datetime_obs = datetime.utcfromtimestamp(pointing.timestamp)
date_obs = datetime_obs.strftime("%y%m%d")
time_obs = datetime_obs.strftime("%H%M%S")
h_prim = generatePrimaryHeader(
xlen=chip.npix_x,
ylen=chip.npix_y,
pointNum=str(pointing.id),
ra=pointing.ra,
dec=pointing.dec,
pixel_scale=chip.pix_scale,
date=date_obs,
time_obs=time_obs,
exptime=self.config["obs_setting"]["exp_time"],
im_type='DARKPF',
sat_pos=[pointing.sat_x, pointing.sat_y, pointing.sat_z],
sat_vel=[pointing.sat_vx, pointing.sat_vy, pointing.sat_vz],
chip_name=str(chip.chipID).rjust(2, '0'))
h_ext = generateExtensionHeader(
chip=chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=pointing.ra,
dec=pointing.dec,
pa=pointing.img_pa.deg,
gain=chip.gain,
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
pixel_scale=chip.pix_scale,
pixel_size=chip.pix_size,
xcen=chip.x_cen,
ycen=chip.y_cen,
extName='SCI',
timestamp=pointing.timestamp,
exptime=self.config["obs_setting"]["exp_time"],
readoutTime=chip.readout_time)
chip.img = galsim.Image(chip.img.array, dtype=np.uint16)
hdu1 = fits.PrimaryHDU(header=h_prim)
hdu1.add_checksum()
hdu1.header.comments['CHECKSUM'] = 'HDU checksum'
hdu1.header.comments['DATASUM'] = 'data unit checksum'
hdu2 = fits.ImageHDU(chip.img.array, header=h_ext)
hdu2.add_checksum()
hdu2.header.comments['XTENSION'] = 'extension type'
hdu2.header.comments['CHECKSUM'] = 'HDU checksum'
hdu2.header.comments['DATASUM'] = 'data unit checksum'
hdu1 = fits.HDUList([hdu1, hdu2])
fname = os.path.join(chip_output.subdir, h_prim['FILENAME'] + '.fits')
hdu1.writeto(fname, output_verify='ignore', overwrite=True)
# chip_output.Log_info("# objects that are too bright %d out of %d" % (bright_obj, self.nobj))
# chip_output.Log_info("# objects that are too dim %d out of %d" % (dim_obj, self.nobj))
# chip_output.Log_info("# objects that are missed %d out of %d" % (missed_obj, self.nobj))
del chip.img
chip_output.Log_info("check running:2: 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)))
def runExposure_MPI_PointingList(self, pointing_list,chips=None, use_mpi=False):
if use_mpi:
comm = MPI.COMM_WORLD
......@@ -436,6 +570,7 @@ class Observation(object):
run_chips.append(chip)
run_filts.append(filt)
for ipoint in range(len(pointing_list)):
for ichip in range(nchips_per_fp):
i = ipoint*nchips_per_fp + ichip
......@@ -463,6 +598,14 @@ class Observation(object):
subdir=sub_img_dir,
prefix=prefix)
chip_output.Log_info("running pointing#%d, chip#%d, at PID#%d..."%(pointing_ID, chip.chipID, pid))
if self.config["obs_setting"]["survey_type"] == "CALIBRATION":
self.run_one_chip_calibration(chip=chip,
filt=filt,
chip_output=chip_output,
pointing=pointing,
skyback_level = self.config["obs_setting"]["FLAT_LEVEL"],
sky_level_filt = self.config["obs_setting"]["FLAT_LEVEL_FIL"])
else:
self.run_one_chip(
chip=chip,
filt=filt,
......
......@@ -9,14 +9,10 @@
# 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
##<<<<<<< HEAD
##work_dir: "/share/home/zhangxin/CSST_SIM/CSST_new_sim/csst-simulation/"
##=======
work_dir: "/share/home/weichengliang/CSST_git/test_new_sim/outputs/"
##>>>>>>> new_sim
data_dir: "/share/simudata/CSSOSDataProductsSims/data/"
run_name: "testRun2"
project_cycle: 8
work_dir: "/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_new_sim/csst-simulation/"
data_dir: "/Volumes/EAGET/C6_data/inputData/"
run_name: "C6_new_sim_2sq_run1"
project_cycle: 6
run_counter: 1
# Whether to use MPI
......@@ -70,7 +66,16 @@ obs_setting:
# "Spectroscopic": simulate slitless spectroscopic chips only
# "FGS": simulate FGS chips only (31-42)
# "All": simulate full focal plane
survey_type: "Photometric"
# "CALIBRATION": falt, bias, dark with or without postflash
survey_type: "CALIBRATION"
#"LED": ['LED1','LED2','LED3','LED4','LED5','LED6','LED7','LED8','LED9','LED10','LED11','LED12','LED13','LED14'] or null
#'LED1': '275', 'LED2': '310', 'LED3': '430', 'LED4': '505', 'LED5': '545', 'LED6': '590', 'LED7': '670',
#'LED8': '760', 'LED9': '940', 'LED10': '940', 'LED11': '1050', 'LED12': '1050','LED13': '340', 'LED14': '365'
LED_TYPE: ['LED5']
LED_TIME: [1.]
# unit e- ,flat level
FLAT_LEVEL: 20000
FLAT_LEVEL_FIL: 'g'
# Exposure time [seconds]
exp_time: 150.
......@@ -90,7 +95,7 @@ obs_setting:
# if you just want to run default pointing:
# - pointing_dir: null
# - pointing_file: null
pointing_dir: "/share/simudata/CSSOSDataProductsSims/data/"
pointing_dir: "/Volumes/EAGET/C6_data/inputData/"
pointing_file: "pointing_radec_246.5_40.dat"
# Number of calibration pointings
......@@ -106,10 +111,10 @@ obs_setting:
# - give a list of indexes of chips: [ip_1, ip_2...]
# - run all chips: null
# Note: for all pointings
run_chips: [8]
run_chips: [5]
# Whether to enable astrometric modeling
enable_astrometric_model: True
enable_astrometric_model: False
# Whether to enable straylight model
enable_straylight_model: True
......@@ -132,7 +137,7 @@ psf_setting:
# Which PSF model to use:
# "Gauss": simple gaussian profile
# "Interp": Interpolated PSF from sampled ray-tracing data
psf_model: "Interp"
psf_model: "Gauss"
# PSF size [arcseconds]
# radius of 80% energy encircled
......@@ -164,11 +169,12 @@ ins_effects:
# switches
# Note: bias_16channel, gain_16channel, and shutter_effect
# is currently not applicable to "FGS" observations
field_dist: YES # Whether to add field distortions
field_dist: NO # Whether to add field distortions
add_back: YES # Whether to add sky background
add_dark: YES # Whether to add dark noise
add_readout: YES # Whether to add read-out (Gaussian) noise
add_bias: YES # Whether to add bias-level to images
add_prescan: OFF
bias_16channel: YES # Whether to add different biases for 16 channels
gain_16channel: YES # Whether to make different gains for 16 channels
shutter_effect: YES # Whether to add shutter effect
......
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