Loading csst/msc/inst_corr.py +7 −2 Original line number Diff line number Diff line from pathlib import Path import torch import numpy as np from ccdproc import cosmicray_lacosmic from deepCR import deepCR Loading @@ -24,6 +25,9 @@ class CsstMscInstrumentProc(CsstProcessor): self.__wht = None self.__flg = None def set_num_threads(self, n_threads=1): torch.set_num_threads(n_threads) def _do_fix(self, raw, bias, dark, flat): '''仪器效应改正 Loading Loading @@ -100,7 +104,7 @@ class CsstMscInstrumentProc(CsstProcessor): n_jobs=self.n_jobs) else: masked, cleaned = model.clean( self.__img, threshold=0.5, inpaint=True, segment=False, patch=256, parallel=False, self.__img, threshold=0.5, inpaint=True, segment=True, patch=256, parallel=False, n_jobs=self.n_jobs) else: cleaned, masked = cosmicray_lacosmic(ccd=self.__img, Loading Loading @@ -144,8 +148,9 @@ class CsstMscInstrumentProc(CsstProcessor): weight[self.__flg > 0] = 0 self.__wht = weight def prepare(self, n_jobs=2, **kwargs): def prepare(self, n_jobs=2, n_threads=1, **kwargs): self.n_jobs = n_jobs self.set_num_threads(n_threads) for name in kwargs: self._switches[name] = kwargs[name] Loading Loading
csst/msc/inst_corr.py +7 −2 Original line number Diff line number Diff line from pathlib import Path import torch import numpy as np from ccdproc import cosmicray_lacosmic from deepCR import deepCR Loading @@ -24,6 +25,9 @@ class CsstMscInstrumentProc(CsstProcessor): self.__wht = None self.__flg = None def set_num_threads(self, n_threads=1): torch.set_num_threads(n_threads) def _do_fix(self, raw, bias, dark, flat): '''仪器效应改正 Loading Loading @@ -100,7 +104,7 @@ class CsstMscInstrumentProc(CsstProcessor): n_jobs=self.n_jobs) else: masked, cleaned = model.clean( self.__img, threshold=0.5, inpaint=True, segment=False, patch=256, parallel=False, self.__img, threshold=0.5, inpaint=True, segment=True, patch=256, parallel=False, n_jobs=self.n_jobs) else: cleaned, masked = cosmicray_lacosmic(ccd=self.__img, Loading Loading @@ -144,8 +148,9 @@ class CsstMscInstrumentProc(CsstProcessor): weight[self.__flg > 0] = 0 self.__wht = weight def prepare(self, n_jobs=2, **kwargs): def prepare(self, n_jobs=2, n_threads=1, **kwargs): self.n_jobs = n_jobs self.set_num_threads(n_threads) for name in kwargs: self._switches[name] = kwargs[name] Loading