修改： README.md (1a81229e) · Commits · Hu Yi / CSST-COMMOM-CRMASK

README.md

+1 −1

Original line number	Original line	Diff line number	Diff line
	@@ -60,4 +60,4 @@ If you would like use the native training model of deepCR, which are obtained fr

	# Bugs		# Bugs

	Please contact _HU Yi_ (huyi.naoc@gmail.com) to report bugs.		Bugs can be reported and filed at https://csst-tb.bao.ac.cn/code/huyi/csst-commom-crmask/-/issues. Alternatively, you can contact _HU Yi_ (huyi.naoc@gmail.com) to report bugs.

crmask.py

+74 −50

Original line number	Original line	Diff line number	Diff line
	@@ -23,22 +23,21 @@ from astropy.nddata import CCDData
	from pathlib import Path		from pathlib import Path
	import ccdproc		import ccdproc


	import datetime		import datetime
	import sys		import sys


	__all__ = ['CRMask']		__all__ = ['CRMask']

	class CRMask:		class CRMask:
	def __init__(self, obj, flag = None, mask = None, clean = None, sky = None, save_flag = True, update_flag = True, save_name = None, flag_suffix = 'flg', clean_suffix = 'crclean', append_flag = False, mask_suffix = 'crmask', model = 'deepCR', fill_flag = True, fill_method = 'inpainting', gpu_flag = False, config_path = 'crmask.ini', **kwargs):		def __init__(self, obj, flag = None, mask = None, clean = None, sky = None, save_flag = True, update_flag = True, save_name = None, flag_suffix = 'flg', clean_suffix = 'crclean', append_flag = False, mask_suffix = 'crmask', model = 'deepCR', fill_flag = True, fill_method = 'inpainting', gpu_flag = False, config_path = 'crmask.ini', **kwargs):
	"""		"""
	Instantiation of CRMask with specified model configuration.		Instantiation of CRMask with specified model configuration.

	Parameters		Parameters
	----------		__________

	obj : string, Path, astropy.io.fits.HDUList, numpy.ndarray, astropy.nddata.CCDData or list of string		obj : string, Path, astropy.io.fits.HDUList, numpy.ndarray, astropy.nddata.CCDData or list of string
	if model is ``deepCR``, ``lacosmic``, obj is input image to be cosmic-ray masked		if model is ``deepCR``, ``lacosmic``, obj is input image to be cosmic-ray masked, if model is ``deepCR_train``, obj is input training and validating images
	if model is ``deepCR_train``, obj is input training and validating images
	flag : (optional) string, Path, astropy.io.fits.HDUList, numpy.ndarray or astropy.nddata.CCDData		flag : (optional) string, Path, astropy.io.fits.HDUList, numpy.ndarray or astropy.nddata.CCDData
	flag image(s), default is None		flag image(s), default is None
	mask : (optional) string or list of string		mask : (optional) string or list of string
	@@ -68,6 +67,7 @@ class CRMask:
	config_path : (optional) string		config_path : (optional) string
	configuration file path, default is ``./crmask.ini``		configuration file path, default is ``./crmask.ini``
	"""		"""

	self.model = model		self.model = model
	if model == 'deepCR_train':		if model == 'deepCR_train':
	self.image_sets = obj		self.image_sets = obj
	@@ -450,8 +450,9 @@ class CRMask:
	Only returned if `fill_flag` is True		Only returned if `fill_flag` is True

	cosmic ray cleaned image.		cosmic ray cleaned image.

	Examples		Examples
	-------		--------
	>>> from crmask import CRMask		>>> from crmask import CRMask
	>>> crobj = CRMask('xxxx.fits', 'deepCR')		>>> crobj = CRMask('xxxx.fits', 'deepCR')
	>>> crobj.cr_mask()		>>> crobj.cr_mask()
	@@ -710,21 +711,44 @@ class CRMask:

	def cr_train(self):		def cr_train(self):
	"""		"""
	Training models, only support ``deepCR_train``. It will generate pytorch's *.pth file.		Training models, only support ``deepCR_train``. It will generate pytorch's \*.pth file. The train is very painful and time consuming, do NOT use it in pipelines.
	The train is very painful and time consuming, do NOT use it in pipelines.

	Returns		Returns
	-------		-------
	No returns		No returns

	Examples		Examples
	-------		--------
	>>> from crmask import CRMask		>>> from crmask import CRMask
	>>> imglist = ['MSC_MS_210525170000_100000010_23_sci.fits', 'MSC_MS_210525171000_100000011_23_sci.fits', 'MSC_MS_210525172000_100000012_23_sci.fits', 'MSC_MS_210525173000_100000013_23_sci.fits', 'MSC_MS_210525174000_100000014_23_sci.fits', 'MSC_MS_210525175000_100000015_23_sci.fits', 'MSC_MS_210525180000_100000016_23_sci.fits', 'MSC_MS_210525181000_100000017_23_sci.fits', 'MSC_MS_210525182000_100000018_23_sci.fits', 'MSC_MS_210525183000_100000019_23_sci.fits']		>>> imglist = [
	>>> masklist = ['MSC_CRM_210525170000_100000010_23_raw.fits', 'MSC_CRM_210525171000_100000011_23_raw.fits', 'MSC_CRM_210525172000_100000012_23_raw.fits', 'MSC_CRM_210525173000_100000013_23_raw.fits', 'MSC_CRM_210525174000_100000014_23_raw.fits', 'MSC_CRM_210525175000_100000015_23_raw.fits', 'MSC_CRM_210525180000_100000016_23_raw.fits', 'MSC_CRM_210525181000_100000017_23_raw.fits', 'MSC_CRM_210525182000_100000018_23_raw.fits', 'MSC_CRM_210525183000_100000019_23_raw.fits']		>>> 'MSC_MS_210525170000_100000010_23_sci.fits',
	>>> trainobj = CRMask(imglist, mask = masklist, model = 'deepCR_train')		>>> 'MSC_MS_210525171000_100000011_23_sci.fits',
			>>> 'MSC_MS_210525172000_100000012_23_sci.fits',
			>>> 'MSC_MS_210525173000_100000013_23_sci.fits',
			>>> 'MSC_MS_210525174000_100000014_23_sci.fits',
			>>> 'MSC_MS_210525175000_100000015_23_sci.fits',
			>>> 'MSC_MS_210525180000_100000016_23_sci.fits',
			>>> 'MSC_MS_210525181000_100000017_23_sci.fits',
			>>> 'MSC_MS_210525182000_100000018_23_sci.fits',
			>>> 'MSC_MS_210525183000_100000019_23_sci.fits'
			>>> ]
			>>> masklist = [
			>>> 'MSC_CRM_210525170000_100000010_23_raw.fits',
			>>> 'MSC_CRM_210525171000_100000011_23_raw.fits',
			>>> 'MSC_CRM_210525172000_100000012_23_raw.fits',
			>>> 'MSC_CRM_210525173000_100000013_23_raw.fits',
			>>> 'MSC_CRM_210525174000_100000014_23_raw.fits',
			>>> 'MSC_CRM_210525175000_100000015_23_raw.fits',
			>>> 'MSC_CRM_210525180000_100000016_23_raw.fits',
			>>> 'MSC_CRM_210525181000_100000017_23_raw.fits',
			>>> 'MSC_CRM_210525182000_100000018_23_raw.fits',
			>>> 'MSC_CRM_210525183000_100000019_23_raw.fits'
			>>> ]
			>>> trainobj = CRMask(imglist, mask = masklist,
			>>> model = 'deepCR_train')
	>>> trainobj.cr_train()		>>> trainobj.cr_train()
	"""		"""

	if self.model == 'deepCR_train':		if self.model == 'deepCR_train':
	CRMask.cr_train_deepCR(self)		CRMask.cr_train_deepCR(self)
	else:		else: