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Commit c99d5409 authored by BO ZHANG's avatar BO ZHANG 🏀
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inherit CsstData from HDUList

parent ca026c55
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csst/__init__.py
View file @ c99d5409
import os import os
__version__ = "0.0.4" __version__ = "0.0.5"
PACKAGE_PATH = os.path.dirname(__file__) PACKAGE_PATH = os.path.dirname(__file__)
csst/core/data.py
View file @ c99d5409
...@@ -5,43 +5,43 @@ from astropy.io.fits import HDUList, PrimaryHDU ...@@ -5,43 +5,43 @@ from astropy.io.fits import HDUList, PrimaryHDU
import numpy as np import numpy as np
from csst.core.exception import CsstException from csst.core.exception import CsstException
from astropy.io import fits
from copy import deepcopy
__all__ = ["CsstData", "INSTRUMENT_LIST"] __all__ = ["CsstData", "INSTRUMENT_LIST"]
INSTRUMENT_LIST = ["MSC", ] INSTRUMENT_LIST = ["MSC", ]
class CsstData: class CsstData(fits.HDUList):
""" General CSST data class """ """ General CSST raw class """
_primary_hdu = [] # hdu_pri = fits.PrimaryHDU()
_l0data = [] # HDUList # hdu_l0 = fits.ImageHDU(raw=None, name="raw")
_l1hdr_global = [] # hdu_l1 = fits.ImageHDU(raw=None, name="l1")
_l1data = OrderedDict() # dict object
_l2data = OrderedDict() # """
_auxdata = OrderedDict() header methods:
'add_blank', 'add_comment', 'add_history', 'append', 'cards', 'clear', 'comments', 'copy', 'count', 'extend',
'fromfile', 'fromkeys', 'fromstring', 'fromtextfile', 'get', 'index', 'insert', 'items', 'keys', 'pop', 'popitem',
'remove', 'rename_keyword', 'set', 'setdefault', 'strip', 'tofile', 'tostring', 'totextfile', 'update', 'values'
"""
def __init__(self, priHDU, imgHDU, instrument=None, detector=None): def __init__(self, hdus=None, file=None):
""" """
Parameters Parameters
---------- ----------
priHDU: hdus:
primary HDU a alist of HDUs
imgHDU: file:
image HDU open file object
instrument:
instrument
detector:
detector
""" """
self._primary_hdu = priHDU if hdus is None:
self._l0data = imgHDU hdus = []
self.instrument = instrument super(CsstData, self).__init__(hdus=hdus, file=file)
self.detector = detector
def get_l0data(self, copy=True): def get_data(self, copy=True, hdu=1):
""" get level 0 data from CsstData class """ get level 0 raw from CsstData class
Parameters Parameters
---------- ----------
...@@ -49,72 +49,79 @@ class CsstData: ...@@ -49,72 +49,79 @@ class CsstData:
if True, return a copy. if True, return a copy.
""" """
if copy: if copy:
return self._l0data.data.copy() return self[hdu].data.copy()
else: else:
return self._l0data.data return self[hdu].data
def get_l0keyword(self, ext="pri", key="INSTRUME"): def get_keyword(self, key="INSTRUME", hdu=0):
""" get a specific keyword from fits header of level 0 image data """ get keyword from fits header
Parameters Parameters
---------- ----------
ext: {"pri"| "img"}
the HDU extension
key: key:
the key the key
""" """
if ext == 'pri': return self[hdu].header.get(key)
try:
return self._primary_hdu.header.get(key)
except Exception as e:
print(e)
elif ext == 'img':
try:
return self._l0data.header.get(key)
except Exception as e:
print(e)
else:
raise CsstException
def set_l1keyword(self, key, value): def set_keyword(self, key, value, hdu=1):
""" set L1 keyword """ """ set keyword
raise NotImplementedError("Well, not implemented...")
def set_l1data(self, *args, **kwargs):
print('save image data to l2data')
raise NotImplementedError
def get_auxdata(self, name):
""" get aux data
Parameters Parameters
---------- ----------
""" key:
print('Parent class returns zero image.') key
# return np.zeros_like(self.get_l0data()) value:
raise NotImplementedError value
hdu:
def save_l1data(self, imgtype, filename): 0 for primary hdu, 1+ for raw hdu
""" save L1 image and auxilary data to file
Parameters
----------
imgtype: {}
image type
""" """
print("save L1 image to a fits file with name " + filename) self[hdu].header[key] = value
try: return
self._l1hdr_global.set('TYPE', imgtype, 'Type of Level 1 data')
hdulist = fits.HDUList( def set_data(self, data, hdu=1):
[ """ set image raw """
fits.PrimaryHDU(header=self._l1hdr_global), self[hdu].data = data
fits.ImageHDU(header=self._l1data[imgtype].header, data=self._l1data[imgtype].data), return
]
) # def writeto(self, fp, overwrite=False):
hdulist.writeto(filename, overwrite=True) # """ save L1 image and aux raw to file
except Exception as e: #
print(e) # Parameters
# ----------
def read(self, **kwargs): # fp: str
""" read data from fits file """ # image type
# overwrite : bool
# if True, overwrite file
# """
# self.writeto(fp, overwrite=overwrite)
def get_auxdata(self):
""" get aux raw
In future, this is to automatically get aux raw from database.
"""
raise NotImplementedError raise NotImplementedError
@classmethod
def read(cls, name, ignore_missing_simple=True):
""" read raw from fits file, should be implemented in child classes """
return cls.fromfile(name, ignore_missing_simple=ignore_missing_simple)
def deepcopy(self, name=None, data=None):
""" generate a deep copy of self """
cp = self.__class__(deepcopy(self))
if name is not None:
cp[1].name = name
if data is not None:
cp[1].data = data
return cp
@property
def data(self):
if len(self) == 1:
return self[1].data
return self[1].data
@property
def exptime(self):
return self[0].header["EXPTIME"]
csst/msc/__init__.py
View file @ c99d5409
from .data import CsstMscData, CsstMscImgData from .data import CsstMscImgData
\ No newline at end of file \ No newline at end of file
csst/msc/data.py
View file @ c99d5409
# from abc import ABC
from collections import OrderedDict from collections import OrderedDict
import astropy.io.fits as fits import astropy.io.fits as fits
from astropy.io.fits import HDUList, PrimaryHDU, ImageHDU from astropy.io.fits import HDUList, PrimaryHDU, ImageHDU
...@@ -6,143 +7,88 @@ from ..core.data import CsstData, INSTRUMENT_LIST ...@@ -6,143 +7,88 @@ from ..core.data import CsstData, INSTRUMENT_LIST
import numpy as np import numpy as np
__all__ = ["CsstMscData", "CsstMscImgData"] __all__ = ["CsstMscImgData", ]
class CsstMscData(CsstData): class CsstMscImgData(CsstData):
_l1img_types = {'sci': True, 'weight': True, 'flag': True} _l1img_types = {'sci': True, 'weight': True, 'flag': True}
def __init__(self, priHDU, imgHDU, **kwargs): def __init__(self, hdus=None, file=None):
super(CsstMscData, self).__init__(priHDU, imgHDU, **kwargs) """
self._l1hdr_global = priHDU.header.copy()
self._l1data['sci'] = ImageHDU()
self._l1data['weight'] = ImageHDU()
self._l1data['flag'] = ImageHDU()
def set_flat(self, flat):
""" set flat
Parameters Parameters
---------- ----------
flat: hdus:
flat image a list of HDUs
file:
Returns open file object
-------
""" """
self._auxdata['flat'] = flat if hdus is None:
hdus = []
def set_bias(self, biasimg): super(CsstMscImgData, self).__init__(hdus=hdus, file=file)
""" set bias """
self._auxdata['bias'] = biasimg
def set_dark(self, darkimg): # meta info
""" set dark """ self.instrument = self[0].header["INSTRUME"]
self._auxdata['dark'] = darkimg self.detector = self[0].header["DETECTOR"]
def set_badpixel(self, badpixelimg): # self._l1hdr_global = self[0].header.copy()
""" set badpixel """ # self._l1data = dict()
self._auxdata['badpixel'] = badpixelimg # self._l1data['sci'] = ImageHDU()
# self._l1data['weight'] = ImageHDU()
# self._l1data['flag'] = ImageHDU()
def get_flat(self): def get_flat(self, fp):
""" get flat """ """ get flat """
return self._auxdata['flat'] return fits.getdata(fp)
def get_bias(self): def get_bias(self, fp):
""" get bias """ """ get bias """
return self._auxdata['bias'] return fits.getdata(fp)
def get_dark(self): def get_dark(self, fp):
""" get dark """ """ get dark """
return self._auxdata['dark'] return fits.getdata(fp)
def get_badpixel(self): def get_l1data(self):
""" get badpixel """ """ get L1 raw """
return self._auxdata['badpixel'] imgdata = self.get_data(hdu=1)
exptime = self.get_keyword("EXPTIME", hdu=0)
def init_l0data(self): # image
""" initialize L0 data """ img = self.deepcopy(name="img", data=imgdata.astype(np.float32) / exptime)
pass img[1].header['BUNIT'] = 'e/s'
# weight
def set_l1keyword(self, key, value, comment=''): wht = self.deepcopy(name="wht", data=imgdata.astype(np.float32))
""" set L1 keyword """ wht[1].header.remove('BUNIT')
print('check out whether ' + key + " is a valid key and " + value + " is valid value") # flag
self._l1hdr_global.set(key, value, comment) flg = self.deepcopy(name="flg", data=imgdata.astype(np.uint16))
flg[1].header.remove('BUNIT')
def set_l1data(self, imgtype, img): return img, wht, flg
""" set L1 data """
try:
if imgtype == 'sci':
self._l1data[imgtype].header['EXTNAME'] = 'img'
self._l1data[imgtype].header['BUNIT'] = 'e/s'
self._l1data[imgtype].data = img.astype(np.float32) / self._l1hdr_global['exptime']
elif imgtype == 'weight':
self._l1data[imgtype].header['EXTNAME'] = 'wht'
self._l1data[imgtype].data = img.astype(np.float32)
elif imgtype == 'flag':
self._l1data[imgtype].header['EXTNAME'] = 'flg'
self._l1data[imgtype].data = img.astype(np.uint16)
else:
raise TypeError('unknow type image')
except Exception as e:
print(e)
print('save image data to l1data')
def save_l1data(self, imgtype, filename):
""" save L1 data """
print('check ' + imgtype + ' is validate')
try:
if self._l1img_types[imgtype]:
super().save_l1data(imgtype, filename)
except Exception as e:
print(e)
def get_l1data(self, imgtype):
assert imgtype in ["sci", "flag", "weight"]
return self._l1img_types[imgtype]
class CsstMscImgData(CsstMscData):
def __init__(self, priHDU, imgHDU, **kwargs):
# print('create CsstMscImgData')
super(CsstMscImgData, self).__init__(priHDU, imgHDU, **kwargs)
def __repr__(self): def __repr__(self):
return "<CsstMscImgData: {} {}>".format(self.instrument, self.detector) return "<CsstMscImgData: {} {}>".format(self.instrument, self.detector)
@staticmethod # @staticmethod
def read(fp): # def read(fp):
""" read data from fits file # """ read raw from fits file
#
Parameters # Parameters
---------- # ----------
fp: # fp:
the file path of fits file # the file path of fits file
#
Returns # Returns
------- # -------
CsstMscImgData # CsstMscImgData
#
Example # Example
------- # -------
#
>>> fp = "MSC_MS_210527171000_100000279_16_raw.fits" # >>> fp = "MSC_MS_210527171000_100000279_16_raw.fits"
>>> from csst.msc import CsstMscImgData # >>> from csst.msc import CsstMscImgData
>>> data = CsstMscImgData.read(fp) # >>> raw = CsstMscImgData.read(fp)
>>> # print some info # >>> # print some info
>>> print("data: ", data) # >>> print("raw: ", raw)
>>> print("instrument: ", data.get_l0keyword("pri", "INSTRUME")) # >>> print("instrument: ", raw.get_l0keyword("pri", "INSTRUME"))
>>> print("object: ", data.get_l0keyword("pri", "OBJECT")) # >>> print("object: ", raw.get_l0keyword("pri", "OBJECT"))
""" # """
with fits.open(fp) as hdulist: # return CsstMscImgData.fromfile(fp)
instrument = hdulist[0].header.get('INSTRUME') # strip or not?
detector = hdulist[0].header.get('DETECTOR') # strip or not?
print("@CsstMscImgData: reading data {} ...".format(fp))
assert instrument in INSTRUMENT_LIST
if instrument == 'MSC' and 6 <= int(detector[3:5]) <= 25:
# multi-band imaging
hdu0 = hdulist[0].copy()
hdu1 = hdulist[1].copy()
data = CsstMscImgData(hdu0, hdu1, instrument=instrument, detector=detector)
return data
csst/msc/instrument.py
View file @ c99d5409
from pathlib import Path from pathlib import Path
from ccdproc import cosmicray_lacosmic
import numpy as np import numpy as np
from ccdproc import cosmicray_lacosmic
from deepCR import deepCR from deepCR import deepCR
from ..core.processor import CsstProcessor, CsstProcStatus from ..core.processor import CsstProcessor, CsstProcStatus
from ..msc import CsstMscImgData
from .. import PACKAGE_PATH
DEEPCR_MODEL_PATH = PACKAGE_PATH + "/msc/deepcr_model/CSST_2021-12-30_CCD23_epoch20.pth"
class CsstMscInstrumentProc(CsstProcessor): class CsstMscInstrumentProc(CsstProcessor):
...@@ -12,9 +17,9 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -12,9 +17,9 @@ class CsstMscInstrumentProc(CsstProcessor):
_switches = {'deepcr': True, 'clean': False} _switches = {'deepcr': True, 'clean': False}
def __init__(self): def __init__(self):
pass super(CsstMscInstrumentProc).__init__()
def _do_fix(self, raw, bias, dark, flat, exptime): def _do_fix(self, raw, bias, dark, flat):
'''仪器效应改正 '''仪器效应改正
将raw扣除本底, 暗场, 平场. 并且避免了除0 将raw扣除本底, 暗场, 平场. 并且避免了除0
...@@ -25,10 +30,10 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -25,10 +30,10 @@ class CsstMscInstrumentProc(CsstProcessor):
flat: 平场 flat: 平场
exptime: 曝光时长 exptime: 曝光时长
''' '''
self.__l1img = np.divide( self.__img = np.divide(
raw - bias - dark * exptime, flat, raw.data - bias.data - dark.data * raw.exptime, flat.data,
out=np.zeros_like(raw, float), out=np.zeros_like(raw.data, float),
where=(flat != 0), where=(flat.data != 0),
) )
def _do_badpix(self, flat): def _do_badpix(self, flat):
...@@ -39,9 +44,9 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -39,9 +44,9 @@ class CsstMscInstrumentProc(CsstProcessor):
Args: Args:
flat: 平场 flat: 平场
''' '''
med = np.median(flat) med = np.median(flat.data)
flg = (flat < 0.5 * med) | (1.5 * med < flat) flg = (flat.data < 0.5 * med) | (1.5 * med < flat.data)
self.__flagimg = self.__flagimg | (flg * 1) self.__flg = self.__flg | (flg * 1)
def _do_hot_and_warm_pix(self, dark, exptime, rdnoise): def _do_hot_and_warm_pix(self, dark, exptime, rdnoise):
'''热像元与暖像元标记 '''热像元与暖像元标记
...@@ -55,12 +60,12 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -55,12 +60,12 @@ class CsstMscInstrumentProc(CsstProcessor):
exptime: 曝光时长 exptime: 曝光时长
rdnoise: 读出噪声 rdnoise: 读出噪声
''' '''
tmp = dark * exptime tmp = dark.data * exptime
tmp[tmp < 0] = 0 tmp[tmp < 0] = 0
flg = 1 * rdnoise ** 2 <= tmp # 不确定是否包含 暂定包含 flg = 1 * rdnoise ** 2 <= tmp # 不确定是否包含 暂定包含
self.__flagimg = self.__flagimg | (flg * 2) self.__flg = self.__flg | (flg * 2)
flg = (0.5 * rdnoise ** 2 < tmp) & (tmp < 1 * rdnoise ** 2) flg = (0.5 * rdnoise ** 2 < tmp) & (tmp < 1 * rdnoise ** 2)
self.__flagimg = self.__flagimg | (flg * 4) self.__flg = self.__flg | (flg * 4)
def _do_over_saturation(self, raw): def _do_over_saturation(self, raw):
'''饱和溢出像元标记 '''饱和溢出像元标记
...@@ -70,8 +75,8 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -70,8 +75,8 @@ class CsstMscInstrumentProc(CsstProcessor):
Args: Args:
raw: 科学图生图 raw: 科学图生图
''' '''
flg = raw == 65535 flg = raw.data == 65535
self.__flagimg = self.__flagimg | (flg * 8) self.__flg = self.__flg | (flg * 8)
def _do_cray(self, gain, rdnoise): def _do_cray(self, gain, rdnoise):
'''宇宙线像元标记 '''宇宙线像元标记
...@@ -80,25 +85,16 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -80,25 +85,16 @@ class CsstMscInstrumentProc(CsstProcessor):
''' '''
if self._switches['deepcr']: if self._switches['deepcr']:
clean_model = str(Path(__file__).parent / clean_model = DEEPCR_MODEL_PATH
'CSST_2021-12-30_CCD23_epoch20.pth')
inpaint_model = 'ACS-WFC-F606W-2-32' inpaint_model = 'ACS-WFC-F606W-2-32'
model = deepCR(clean_model, model = deepCR(clean_model, inpaint_model, device='CPU', hidden=50)
inpaint_model, masked, cleaned = model.clean(
device='CPU', self.__img, threshold=0.5, inpaint=True, segment=True, patch=256, parallel=True, n_jobs=2)
hidden=50)
masked, cleaned = model.clean(self.__l1img,
threshold=0.5,
inpaint=True,
segment=True,
patch=256,
parallel=True,
n_jobs=2)
else: else:
cleaned, masked = cosmicray_lacosmic(ccd=self.__l1img, cleaned, masked = cosmicray_lacosmic(ccd=self.__img,
sigclip=3., # cr_threshold sigclip=3., # cr_threshold
sigfrac=0.5, # neighbor_threshold sigfrac=0.5, # neighbor_threshold
objlim=5., # constrast objlim=5., # constrast
gain=gain, gain=gain,
readnoise=rdnoise, readnoise=rdnoise,
satlevel=65535.0, satlevel=65535.0,
...@@ -115,9 +111,9 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -115,9 +111,9 @@ class CsstMscInstrumentProc(CsstProcessor):
verbose=False, verbose=False,
gain_apply=True) gain_apply=True)
self.__flagimg = self.__flagimg | (masked * 16) self.__flg = self.__flg | (masked * 16)
if self._switches['clean']: if self._switches['clean']:
self.__l1img = cleaned self.__img = cleaned
def _do_weight(self, bias, gain, rdnoise, exptime): def _do_weight(self, bias, gain, rdnoise, exptime):
'''权重图 '''权重图
...@@ -128,55 +124,44 @@ class CsstMscInstrumentProc(CsstProcessor): ...@@ -128,55 +124,44 @@ class CsstMscInstrumentProc(CsstProcessor):
rdnoise: 读出噪声 rdnoise: 读出噪声
exptime: 曝光时长 exptime: 曝光时长
''' '''
data = self.__l1img.copy() data = self.__img.copy()
data[self.__l1img < 0] = 0 data[self.__img < 0] = 0
weight_raw = 1. / (gain * data + rdnoise ** 2) weight_raw = 1. / (gain * data + rdnoise ** 2)
bias_weight = np.std(bias) bias_weight = np.std(bias)
weight = 1. / (1. / weight_raw + 1. / bias_weight) * exptime ** 2 weight = 1. / (1. / weight_raw + 1. / bias_weight) * exptime ** 2
weight[self.__flagimg > 0] = 0 weight[self.__flg > 0] = 0
self.__weightimg = weight self.__wht = weight
def prepare(self, **kwargs): def prepare(self, **kwargs):
for name in kwargs: for name in kwargs:
self._switches[name] = kwargs[name] self._switches[name] = kwargs[name]
def run(self, data): def run(self, raw: CsstMscImgData, bias, dark, flat):
if type(data).__name__ == 'CsstMscImgData' or type(data).__name__ == 'CsstMscSlsData':
raw = data.get_l0data()
self.__l1img = raw.copy()
self.__weightimg = np.zeros_like(raw)
self.__flagimg = np.zeros_like(raw, dtype=np.uint16)
exptime = data.get_l0keyword('pri', 'EXPTIME')
gain = data.get_l0keyword('img', 'GAIN1')
rdnoise = data.get_l0keyword('img', 'RDNOISE1')
flat = data.get_flat()
bias = data.get_bias()
dark = data.get_dark()
print('Flat and bias correction') assert isinstance(raw, CsstMscImgData)
self.__img = np.copy(raw.data)
self.__wht = np.zeros_like(raw.data, dtype=float)
self.__flg = np.zeros_like(raw.data, dtype=np.uint16)
self._do_fix(raw, bias, dark, flat, exptime) exptime = raw.get_keyword('EXPTIME', hdu=0)
self._do_badpix(flat) gain = raw.get_keyword('GAIN1', hdu=1)
self._do_hot_and_warm_pix(dark, exptime, rdnoise) rdnoise = raw.get_keyword('RDNOISE1', hdu=1)
self._do_over_saturation(raw)
self._do_cray(gain, rdnoise)
self._do_weight(bias, gain, rdnoise, exptime)
print('finish the run and save the results back to CsstData') # Flat and bias correction
self._do_fix(raw, bias, dark, flat)
self._do_badpix(flat)
self._do_hot_and_warm_pix(dark, exptime, rdnoise)
self._do_over_saturation(raw)
self._do_cray(gain, rdnoise)
self._do_weight(bias, gain, rdnoise, exptime)
data.set_l1data('sci', self.__l1img) print('finish the run and save the results back to CsstData')
data.set_l1data('weight', self.__weightimg)
data.set_l1data('flag', self.__flagimg)
print('Update keywords') img = raw.deepcopy(name="SCI", data=self.__img)
data.set_l1keyword('SOMEKEY', 'some value', wht = raw.deepcopy(name="WHT", data=self.__wht)
'Test if I can append the header') flg = raw.deepcopy(name="FLG", data=self.__flg)
self._status = CsstProcStatus.normal return img, wht, flg
else:
self._status = CsstProcStatus.ioerror
return self._status
def cleanup(self): def cleanup(self):
pass pass
csst/msc/pipeline.py
View file @ c99d5409
...@@ -36,10 +36,10 @@ from csst.msc.data import CsstMscImgData ...@@ -36,10 +36,10 @@ from csst.msc.data import CsstMscImgData
from csst.msc.instrument import CsstMscInstrumentProc from csst.msc.instrument import CsstMscInstrumentProc
from astropy.io import fits from astropy.io import fits
# get aux data # get aux raw
bs = fits.getdata("/data/ref/MSC_CLB_210525190000_100000014_13_combine.fits") bs = fits.getdata("/raw/ref/MSC_CLB_210525190000_100000014_13_combine.fits")
dk = fits.getdata("/data/ref/MSC_CLD_210525192000_100000014_13_combine.fits") dk = fits.getdata("/raw/ref/MSC_CLD_210525192000_100000014_13_combine.fits")
ft = fits.getdata("/data/ref/MSC_CLF_210525191000_100000014_13_combine.fits") ft = fits.getdata("/raw/ref/MSC_CLF_210525191000_100000014_13_combine.fits")
fp_img_list = [] fp_img_list = []
fp_flg_list = [] fp_flg_list = []
...@@ -47,10 +47,10 @@ fp_wht_list = [] ...@@ -47,10 +47,10 @@ fp_wht_list = []
data_list = [] data_list = []
for fp in fp_list: for fp in fp_list:
# read image data # read image raw
data = CsstMscImgData.read(fp) data = CsstMscImgData.read(fp)
# set aux data # set aux raw
data.set_bias(bs) data.set_bias(bs)
data.set_dark(dk) data.set_dark(dk)
data.set_flat(ft) data.set_flat(ft)
...@@ -66,7 +66,7 @@ for fp in fp_list: ...@@ -66,7 +66,7 @@ for fp in fp_list:
fp_flg = fp.replace("raw.fits", "flg.fits") fp_flg = fp.replace("raw.fits", "flg.fits")
fp_wht = fp.replace("raw.fits", "wht.fits") fp_wht = fp.replace("raw.fits", "wht.fits")
# save l1 data # save l1 raw
data.save_l1data('sci', fp_img) data.save_l1data('sci', fp_img)
data.save_l1data('flag', fp_flg) data.save_l1data('flag', fp_flg)
data.save_l1data('weight', fp_wht) data.save_l1data('weight', fp_wht)
......
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