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import os
import galsim
import numpy as np
from astropy.io import fits
from observation_sim.instruments.chip import chip_utils
from observation_sim.instruments.chip import effects
from astropy.time import Time
from datetime import datetime, timezone
def add_prescan_overscan(self, chip, filt, tel, pointing, catalog, obs_param):
self.chip_output.Log_info("Apply pre/over-scan")
chip.img = chip_utils.AddPreScan(GSImage=chip.img,
pre1=chip.prescan_x,
pre2=chip.prescan_y,
over1=chip.overscan_x,
over2=chip.overscan_y)
ny = int(chip.npix_y/2)
base_dark = (ny-1)*(chip.readout_time/ny)*chip.dark_noise
chip.img.array[(chip.prescan_y+ny):-(chip.prescan_y+ny), :] = base_dark
return chip, filt, tel, pointing
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def add_crosstalk(self, chip, filt, tel, pointing, catalog, obs_param):
crosstalk=np.zeros([16,16])
crosstalk[0,:] = np.array([1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[1,:] = np.array([1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[2,:] = np.array([0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[3,:] = np.array([0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[4,:] = np.array([0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[5,:] = np.array([0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[6,:] = np.array([0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[7,:] = np.array([0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0.])
crosstalk[8,:] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0.])
crosstalk[9,:] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0.])
crosstalk[10,:]= np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0.])
crosstalk[11,:]= np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0.])
crosstalk[12,:]= np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0.])
crosstalk[13,:]= np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0.])
crosstalk[14,:]= np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4])
crosstalk[15,:]= np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1.])
# 2*8 -> 1*16
img = formatOutput(chip.img)
ny, nx = img.array.shape
nsecy=1
nsecx=16
dy = int(ny/nsecy)
dx = int(nx/nsecx)
newimg = galsim.Image(nx, ny, init_value=0)
for i in range(16):
for j in range(16):
newimg.array[:, int(i*dx):int(i*dx+dx)] += crosstalk[i,j]*img.array[:, int(j*dx):int(j*dx+dx)]
# 1*16 -> 2*8
newimg = formatRevert(newimg)
chip.img.array[:, :] = newimg.array[:, :]
return chip, filt, tel, pointing
def add_readout_noise(self, chip, filt, tel, pointing, catalog, obs_param):
seed = int(self.overall_config["random_seeds"]
["seed_readout"]) + pointing.id*30 + chip.chipID
rng_readout = galsim.BaseDeviate(seed)
readout_noise = galsim.GaussianNoise(
rng=rng_readout, sigma=chip.read_noise)
chip.img.addNoise(readout_noise)
return chip, filt, tel, pointing
def apply_gain(self, chip, filt, tel, pointing, catalog, obs_param):
self.chip_output.Log_info(" Applying Gain")
chip.img, chip.gain_channel = effects.ApplyGainNonUniform16(chip.img,
gain=chip.gain,
nsecy=chip.nsecy,
nsecx=chip.nsecx,
seed=self.overall_config["random_seeds"]["seed_gainNonUniform"]+chip.chipID)
chip.gain_channel = np.ones(chip.nsecy*chip.nsecx)*chip.gain
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return chip, filt, tel, pointing
def quantization_and_output(self, chip, filt, tel, pointing, catalog, obs_param):
if not hasattr(self, 'h_ext'):
_, _ = self.prepare_headers(chip=chip, pointing=pointing)
self.updateHeaderInfo(header_flag='ext', keys=['SHTSTAT', 'SHTOPEN1', 'SHTCLOS0', 'SHTCLOS1', 'EXPTIME'], values=[
False, self.h_ext['SHTOPEN0'], self.h_ext['SHTOPEN0'], self.h_ext['SHTOPEN0'], 0.0])
# 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0.5s，开灯后等待0.5s,开始曝光
t_obs_renew = Time(t_obs.mjd - 2. / 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]])
gains1 = list(chip.gain_channel[0:8])
gains2 = list(chip.gain_channel[8:])
gains2.reverse()
gains = np.append(gains1, gains2)
self.updateHeaderInfo(header_flag='ext', keys=['GAIN01', 'GAIN02', 'GAIN03', 'GAIN04', 'GAIN05', 'GAIN06', 'GAIN07',
'GAIN08', 'GAIN09', 'GAIN10', 'GAIN11', 'GAIN12', 'GAIN13', 'GAIN14', 'GAIN15', 'GAIN16'], values=gains)
self.chip_output.Log_info(" Apply 1*16 format")
chip.img = chip_utils.formatOutput(GSImage=chip.img)
chip.nsecy = 1
chip.nsecx = 16
chip.img.array[chip.img.array > 65535] = 65535
chip.img.replaceNegative(replace_value=0)
chip.img.quantize()
chip.img = galsim.Image(chip.img.array, dtype=np.uint16)
fname = os.path.join(self.chip_output.subdir,
self.h_prim['FILENAME'] + '.fits')
# f_name_size = 68
# if (len(self.h_prim['FILENAME']) > f_name_size):
# self.updateHeaderInfo(header_flag='prim', keys=['FILENAME'], values=[
# self.h_prim['FILENAME'][0:f_name_size]])
hdu1 = fits.PrimaryHDU(header=self.h_prim)
self.updateHeaderInfo(header_flag='ext', keys=['DATASECT'], values=[
str(chip.img.array.shape[1]) + 'x' + str(chip.img.array.shape[0])])
hdu2 = fits.ImageHDU(chip.img.array, header=self.h_ext)
hdu2.header.comments["XTENSION"] = "image extension"
hdu = fits.HDUList([hdu1, hdu2])
hdu[0].add_datasum(when='data unit checksum')
hdu[0].add_checksum(when='HDU checksum', override_datasum=True)
hdu[1].add_datasum(when='data unit checksum')
hdu[1].add_checksum(when='HDU checksum', override_datasum=True)
hdu.writeto(fname, output_verify='ignore', overwrite=True)
return chip, filt, tel, pointing