补全仪器效应改正里的宇宙线去除功能 (9c07d167) · Commits · Bo Zhang / csst

csst/msc/CSST_2021-12-30_CCD23_epoch20.pth

0 → 100644

+982 KiB

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csst/msc/instrument.py

+52 −18

Original line number	Original line	Diff line number	Diff line
	from collections import OrderedDict		from pathlib import Path
	from abc import ABCMeta, abstractmethod
	from enum import Enum		from ccdproc import cosmicray_lacosmic
	import numpy as np		import numpy as np
	from deepCR import deepCR		from deepCR import deepCR
	from ..core.processor import CsstProcStatus, CsstProcessor
			from ..core.processor import CsstProcessor, CsstProcStatus


	class CsstMscInstrumentProc(CsstProcessor):		class CsstMscInstrumentProc(CsstProcessor):
	_status = CsstProcStatus.empty		_status = CsstProcStatus.empty
	_switches = {'crosstalk': False, 'nonlinear': False,		_switches = {'deepcr': True, 'clean': False}
	'deepcr': False, 'cti': False, 'brighterfatter': False}

	def __init__(self):		def __init__(self):
	pass		pass
	@@ -73,19 +73,51 @@ class CsstMscInstrumentProc(CsstProcessor):
	flg = raw == 65535		flg = raw == 65535
	self.__flagimg = self.__flagimg \| (flg * 8)		self.__flagimg = self.__flagimg \| (flg * 8)

	def _do_cray(self):		def _do_cray(self, gain, rdnoise):
	'''宇宙线像元标记		'''宇宙线像元标记

	宇宙线污染的像元, 用deepCR进行标记		宇宙线污染的像元, 用deepCR或lacosmic进行标记
	'''		'''

			if self._switches['deepcr']:
			clean_model = str(Path(__file__).parent /
	flg, _ = deepCR(self.__l1img)		'CSST_2021-12-30_CCD23_epoch20.pth')
			inpaint_model = 'ACS-WFC-F606W-2-32'
			model = deepCR(clean_model,
			inpaint_model,
	self.__flagimg = self.__flagimg \| (flg * 16)		device='CPU',
			hidden=50)
			masked, cleaned = model.clean(self.__l1img,
			threshold=0.5,
			inpaint=True,
			segment=True,
			patch=256,
			parallel=True,
			n_jobs=2)
			else:
			cleaned, masked = cosmicray_lacosmic(ccd=self.__l1img,
			sigclip=3., # cr_threshold
			sigfrac=0.5, # neighbor_threshold
			objlim=5., # constrast
			gain=gain,
			readnoise=rdnoise,
			satlevel=65535.0,
			pssl=0.0,
			niter=4,
			sepmed=True,
			cleantype='meanmask',
			fsmode='median',
			psfmodel='gauss',
			psffwhm=2.5,
			psfsize=7,
			psfk=None,
			psfbeta=4.765,
			verbose=False,
			gain_apply=True)

			self.__flagimg = self.__flagimg \| (masked * 16)
			if self._switches['clean']:
			self.__l1img = cleaned

	def _do_weight(self, bias, gain, rdnoise, exptime):		def _do_weight(self, bias, gain, rdnoise, exptime):
	'''权重图		'''权重图
	@@ -121,15 +153,17 @@ class CsstMscInstrumentProc(CsstProcessor):
	flat = data.get_flat()		flat = data.get_flat()
	bias = data.get_bias()		bias = data.get_bias()
	dark = data.get_dark()		dark = data.get_dark()

	print('Flat and bias correction')		print('Flat and bias correction')

	self._do_fix(raw, bias, dark, flat, exptime)		self._do_fix(raw, bias, dark, flat, exptime)
	self._do_badpix(flat)		self._do_badpix(flat)
	self._do_hot_and_warm_pix(dark, exptime, rdnoise)		self._do_hot_and_warm_pix(dark, exptime, rdnoise)
	self._do_over_saturation(raw)		self._do_over_saturation(raw)
	# self._do_cray()		self._do_cray(gain, rdnoise)
	self._do_weight(bias, gain, rdnoise, exptime)		self._do_weight(bias, gain, rdnoise, exptime)

	print('fake to finish the run and save the results back to CsstData')		print('finish the run and save the results back to CsstData')

	data.set_l1data('sci', self.__l1img)		data.set_l1data('sci', self.__l1img)
	data.set_l1data('weight', self.__weightimg)		data.set_l1data('weight', self.__weightimg)