Commit 9c07d167 authored by Xie Zhou's avatar Xie Zhou
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补全仪器效应改正里的宇宙线去除功能

parent b0ca68fe

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 Diff line number Diff line 
from collections import OrderedDict

from abc import ABCMeta, abstractmethod

from enum import Enum

from pathlib import Path



from ccdproc import cosmicray_lacosmic

import numpy as np

from deepCR import deepCR

from ..core.processor import CsstProcStatus, CsstProcessor



from ..core.processor import CsstProcessor, CsstProcStatus





class CsstMscInstrumentProc(CsstProcessor):

    _status = CsstProcStatus.empty

    _switches = {'crosstalk': False, 'nonlinear': False,

                 'deepcr': False, 'cti': False, 'brighterfatter': False}

    _switches = {'deepcr': True, 'clean': False}



    def __init__(self):

        pass
@@ -73,19 +73,51 @@ class CsstMscInstrumentProc(CsstProcessor): 
        flg = raw == 65535

        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

        '''





        

        flg, _ = deepCR(self.__l1img)







        self.__flagimg = self.__flagimg | (flg * 16)

        if self._switches['deepcr']:

            clean_model = str(Path(__file__).parent /

                              'CSST_2021-12-30_CCD23_epoch20.pth')

            inpaint_model = 'ACS-WFC-F606W-2-32'

            model = deepCR(clean_model,

                           inpaint_model,

                           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):

        '''权重图
@@ -121,15 +153,17 @@ class CsstMscInstrumentProc(CsstProcessor): 
            flat = data.get_flat()

            bias = data.get_bias()

            dark = data.get_dark()



            print('Flat and bias correction')



            self._do_fix(raw, bias, dark, flat, exptime)

            self._do_badpix(flat)

            self._do_hot_and_warm_pix(dark, exptime, rdnoise)

            self._do_over_saturation(raw)

            # self._do_cray()

            self._do_cray(gain, rdnoise)

            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('weight', self.__weightimg)