update dark and hotpix (0efad3cf) · Commits · csst-sims / csst_msc_sim

config/config_overall.yaml

+2 −2

Original line number	Diff line number	Diff line
		@@ -11,8 +11,8 @@
		# 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/project/workplace/"
		run_name: "ext_on"
		data_set: "csst-msc-c11-1000sqdeg-wide-v1"
		run_name: "csst-msc-c11-test-wide-v1"
		data_set: "csst-msc-c11-test-wide-v1"

		# Project cycle and run counter are used to name the outputs
		project_cycle: 11

config/obs_config_SCI.yaml

+5 −5

Original line number	Diff line number	Diff line
		@@ -9,14 +9,13 @@
		###############################################

		# Observation type
		obs_type: "SCI"
		obs_type: null
		obs_type_code: "101"
		obs_id: "00000001" # this setting will only be used if pointing list file is not given

		# Define list of chips
		# run_chips: [6,7,8,9,11,12,13,14,15,16,17,18,19,20,22,23,24,25] # Photometric chips
		run_chips: [6,7,8,9,11,12,13,14,15,16,17,18,19,20,22,23,24,25] # Photometric chips
		# run_chips: [1,2,3,4,5,10,21,26,27,28,29,30] # Spectroscopic chips
		run_chips: [17, 22]

		# Define observation sequence
		call_sequence:
		@@ -55,11 +54,12 @@ call_sequence:
		# Set it here is you want to override the default
		# exptime: 150. # [s]
		add_dark: YES
		input_dark: YES
		# Simulate brighter fatter effects
		bright_fatter: {}
		# Add detector defects: hot/warm pixels, bad columns
		detector_defects:
		hot_pixels: YES
		# hot_pixels: NO
		dead_pixels: YES
		bad_columns: YES
		# Apply CCD Saturation & Blooming

observation_sim/instruments/chip/Chip.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -124,6 +124,7 @@ class Chip(FocalPlane):
		self.rotate_angle = 0.
		self.overscan = 1000
		self.badfraction = 5e-5
		self.chip_type = 'default'
		# Override default values
		# for key in ["gain", "bias_level, dark_exptime", "flat_exptime", "readout_time", "full_well", "read_noise", "dark_noise", "overscan"]:
		# if key in config["ins_effects"]:

observation_sim/instruments/chip/chip_utils.py

+53 −24

Original line number	Diff line number	Diff line
		@@ -214,14 +214,12 @@ def get_poisson(seed=0, sky_level=0.):
		return rng_poisson, poisson_noise


		def get_base_img(img, chip, read_noise, readout_time, dark_noise, exptime=150., InputDark=None):
		if InputDark is None:
		def get_base_img(img, chip, read_noise, readout_time, dark_noise, exptime=150., InputDark=False):
		if not InputDark:
		# base_level = read_noise*2 + dark_noise(exptime+0.5*readout_time)
		# base_level = dark_noise(exptime+0.5readout_time)
		base_level = dark_noise*(exptime)
		base_img1 = base_level * np.ones_like(img.array)
		else:
		base_img1 = np.zeros_like(img.array)

		ny = int(chip.npix_y/2)
		nx = chip.npix_x
		@@ -231,27 +229,58 @@ def get_base_img(img, chip, read_noise, readout_time, dark_noise, exptime=150.,
		base_img2[:ny, :] = arr
		base_img2[ny:, :] = arr[::-1, :]
		base_img2[:, :] = base_img2[:, :](readout_time/ny)dark_noise
		return base_img1+base_img2


		def add_poisson(img, chip, exptime=150., seed=0, sky_level=0., poisson_noise=None, dark_noise=None, InputDark=None):
		else:
		# base_img1 = np.zeros_like(img.array)
		histfile = 'hist_dark_{:}.npz'.format(chip.chip_type)
		try:
		with pkg_resources.files('observation_sim.instruments.data.ccd').joinpath(histfile) as dark_histogram:
		hist_dc = np.load(dark_histogram)
		except AttributeError:
		with pkg_resources.path('observation_sim.instruments.data.ccd', histfile) as dark_histogram:
		hist_dc = np.load(dark_histogram)
		hist = stats.rv_histogram((hist_dc['counts'], hist_dc['bins']), density=True)
		xsize= chip.npix_x
		ysize= chip.npix_y
		seed = chip.chipID
		samples= hist.rvs(size=xsize*ysize, random_state=seed)
		map_dc = np.reshape(samples, [ysize, xsize])
		base_img1 = map_dc*exptime

		# base_img2
		map_temp = np.zeros((ysize//2, 2*xsize))
		map_temp[:, :xsize] = map_dc[:ysize//2, :]
		map_temp[:, xsize:] = map_dc[:ysize//2-1:-1, :]

		dt= readout_time/(ysize/2.)
		A = map_temp
		A_adjusted= np.vstack([np.zeros((1, A.shape[1])), A[:-1]])
		cumsum_A = np.cumsum(A_adjusted, axis=0)
		B = cumsum_A * dt
		base_img2 = np.vstack([B[:, :xsize], B[::-1, xsize:]])
		del hist_dc
		del hist
		del samples
		del map_temp
		del A
		del A_adjusted
		del cumsum_A
		del B
		return base_img1+base_img2, map_dc


		def add_poisson(img, chip, exptime=150., seed=0, sky_level=0., poisson_noise=None, dark_noise=None, InputDark=False):
		if poisson_noise is None:
		_, poisson_noise = get_poisson(seed=seed, sky_level=sky_level)
		read_noise = chip.read_noise
		if dark_noise is None:
		dark_noise = chip.dark_noise
		base_img = get_base_img(img=img, chip=chip, read_noise=read_noise, readout_time=chip.readout_time,
		base_img, map_dc = get_base_img(img=img, chip=chip, read_noise=read_noise, readout_time=chip.readout_time,
		dark_noise=dark_noise, exptime=exptime, InputDark=InputDark)
		img += base_img
		img.addNoise(poisson_noise)
		# img -= read_noise**2

		if InputDark is not None:
		# "Instrument/data/dark/dark_1000s_example_0.fits"
		hdu = fits.open(InputDark)
		img += hdu[0].data/hdu[0].header['exptime']*exptime
		hdu.close()
		return img, base_img
		del base_img
		return img, map_dc


		def add_brighter_fatter(img):

observation_sim/instruments/data/ccd/chip_definition.json

+42 −0

Original line number	Diff line number	Diff line
		{
		"31": {
		"chip_name": "FGS1A-D1",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -23,6 +24,7 @@
		},
		"32": {
		"chip_name": "FGS1A-D2",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -45,6 +47,7 @@
		},
		"33": {
		"chip_name": "FGS1B-D1",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -67,6 +70,7 @@
		},
		"34": {
		"chip_name": "FGS1B-D2",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -89,6 +93,7 @@
		},
		"35": {
		"chip_name": "FGS2A-D1",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -111,6 +116,7 @@
		},
		"36": {
		"chip_name": "FGS2A-D2",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -133,6 +139,7 @@
		},
		"37": {
		"chip_name": "FGS2B-D1",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -155,6 +162,7 @@
		},
		"38": {
		"chip_name": "FGS2B-D2",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -177,6 +185,7 @@
		},
		"39": {
		"chip_name": "FGS3-D1",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -199,6 +208,7 @@
		},
		"40": {
		"chip_name": "FGS3-D2",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -221,6 +231,7 @@
		},
		"41": {
		"chip_name": "FGS4-D1",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -243,6 +254,7 @@
		},
		"42": {
		"chip_name": "FGS4-D2",
		"chip_type": "default",
		"pix_size": 0.0075,
		"pix_scale": 0.0555,
		"npix_x": 11264,
		@@ -265,6 +277,7 @@
		},
		"1": {
		"chip_name": "GI-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -288,6 +301,7 @@
		},
		"2": {
		"chip_name": "GV-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -311,6 +325,7 @@
		},
		"3": {
		"chip_name": "GU-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -334,6 +349,7 @@
		},
		"4": {
		"chip_name": "GU-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -357,6 +373,7 @@
		},
		"5": {
		"chip_name": "GV-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -380,6 +397,7 @@
		},
		"6": {
		"chip_name": "y-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -403,6 +421,7 @@
		},
		"7": {
		"chip_name": "i-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -426,6 +445,7 @@
		},
		"8": {
		"chip_name": "g-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -449,6 +469,7 @@
		},
		"9": {
		"chip_name": "r-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -472,6 +493,7 @@
		},
		"10": {
		"chip_name": "GI-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -495,6 +517,7 @@
		},
		"11": {
		"chip_name": "z-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -518,6 +541,7 @@
		},
		"12": {
		"chip_name": "NUV-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -541,6 +565,7 @@
		},
		"13": {
		"chip_name": "NUV-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -564,6 +589,7 @@
		},
		"14": {
		"chip_name": "u-1",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -587,6 +613,7 @@
		},
		"15": {
		"chip_name": "y-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -610,6 +637,7 @@
		},
		"16": {
		"chip_name": "y-3",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -633,6 +661,7 @@
		},
		"17": {
		"chip_name": "u-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -656,6 +685,7 @@
		},
		"18": {
		"chip_name": "NUV-3",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -679,6 +709,7 @@
		},
		"19": {
		"chip_name": "NUV-4",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -702,6 +733,7 @@
		},
		"20": {
		"chip_name": "z-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -725,6 +757,7 @@
		},
		"21": {
		"chip_name": "GI-3",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -748,6 +781,7 @@
		},
		"22": {
		"chip_name": "r-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -771,6 +805,7 @@
		},
		"23": {
		"chip_name": "g-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -794,6 +829,7 @@
		},
		"24": {
		"chip_name": "i-2",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -817,6 +853,7 @@
		},
		"25": {
		"chip_name": "y-4",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -840,6 +877,7 @@
		},
		"26": {
		"chip_name": "GV-3",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -863,6 +901,7 @@
		},
		"27": {
		"chip_name": "GU-3",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -886,6 +925,7 @@
		},
		"28": {
		"chip_name": "GU-4",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -909,6 +949,7 @@
		},
		"29": {
		"chip_name": "GV-4",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,
		@@ -932,6 +973,7 @@
		},
		"30": {
		"chip_name": "GI-4",
		"chip_type": "default",
		"pix_size": 0.01,
		"pix_scale": 0.074,
		"npix_x": 9216,