update

csst_ifs_sim/__init__.py

+__version__ = "3.0.1"

csst_ifs_sim/csst_ifs_sim.py

@@ -356,7 +356,7 @@ class cosmicrays():
                         exposure time.
     """
 
-    def __init__(self, log, image, crInfo=None, information=None):
+    def __init__(self, log, image, exposuretime,crInfo=None, information=None):
         """
         Cosmic ray generation class. Can either draw events from distributions or
         set the energy of the events to a constant.
@@ -376,8 +376,7 @@ class cosmicrays():
 
         # set up the information dictionary, first with defaults and then overwrite with inputs if given
         self.information = (dict(cosmicraylengths='/home/yan/csst-master/data/cdf_cr_length.dat',
-                                 cosmicraydistance='/home/yan/csst-master/data/cdf_cr_total.dat',
-                                 exptime=565))
+                                 cosmicraydistance='/home/yan/csst-master/data/cdf_cr_total.dat',exptime=exposuretime))
         if information is not None:
             self.information.update(information)
 
@@ -520,12 +519,6 @@ class cosmicrays():
         :return: None
         """
 
-        if coveringFraction > 1 or coveringFraction < 0.1:
-            self.log.error(
-                'coveringFraction error, it shoub be in [0.1, 1]!')
-            raise ValueError(
-                'coveringFraction error, it shoub be in [0.1, 1]!')
-
         self.cosmicrayMap = np.zeros((self.ysize, self.xsize))
 
         # how many events to draw at once, too large number leads to exceeding the covering fraction
@@ -2164,74 +2157,76 @@ class IFSsimulator():
         return FlatMat
     ####################################################################
 
-    def getFrameTransferImg(self):
-        """
-
-
-        Returns
-        -------
-        None.
-
-        """
-        """
-        get frame transfer image from original image of self.image_b and self.image_r
-        """
-        self.frame_b_4 = np.zeros((1024+320, 2048), dtype=float)
-        self.frame_b_3 = np.zeros((1024+320, 2048), dtype=float)
-        self.frame_b_2 = np.zeros((1024+320, 2048), dtype=float)
-        self.frame_b_1 = np.zeros((1024+320, 2048), dtype=float)
-
-        self.frame_r_4 = np.zeros((1536+320, 3072), dtype=float)
-        self.frame_r_3 = np.zeros((1536+320, 3072), dtype=float)
-        self.frame_r_2 = np.zeros((1536+320, 3072), dtype=float)
-        self.frame_r_1 = np.zeros((1536+320, 3072), dtype=float)
-
-        # blue channle
-        b_4 = np.sum(self.image_b[0:1024, 0:2048], axis=0)
-
-        # flip right to  left of part3 and part2
-        temp_b_3 = np.fliplr(self.image_b[0:1024, 2048:4096])  # left to right
-        b_3 = np.sum(temp_b_3, axis=0)
-
-        temp_b_2 = np.fliplr(
-            self.image_b[1024:1024+1024, 2048:2048+2048])      # left to right
-        b_2 = np.sum(temp_b_2, axis=0)
-
-        b_1 = np.sum(self.image_b[1024:1024+1024, 0:2048], axis=0)
-        ####
-
-        for k in range(1024+320):
-            # part
-            self.frame_b_4[k, :] += b_4*0.09216/self.information['exptime']
-            self.frame_b_3[k, :] += b_3*0.09216/self.information['exptime']
-            self.frame_b_2[k, :] += b_2*0.09216/self.information['exptime']
-            self.frame_b_1[k, :] += b_1*0.09216/self.information['exptime']
-
-        ###################
-        # red channle
-        r_4 = np.sum(self.image_r[0:1536, 0:3072], axis=0)
-
-        # flip right to  left of part3 and part2
-        temp_r_3 = np.fliplr(self.image_r[0:1536, 3072:6144])  # left to right
-        r_3 = np.sum(temp_r_3, axis=0)
-
-        temp_r_2 = np.fliplr(
-            self.image_r[1536:1536+1536, 3072:6144])  # left to right
-        r_2 = np.sum(temp_r_2, axis=0)
-
-        # r_3 = np.sum(self.image_r[0:1536, 3072:6144], axis=0)
-
-        # r_2 = np.sum(self.image_r[1536:1536+1536, 3072:6144], axis=0)
-
-        r_1 = np.sum(self.image_r[1536:1536+1536, 0:3072], axis=0)
-
-        for k in range(1536+320):
-            # part 4, OSH zone;
-            self.frame_r_4[k, :] += r_4*0.13824/self.information['exptime']
-            self.frame_r_3[k, :] += r_3*0.13824/self.information['exptime']
-            self.frame_r_2[k, :] += r_2*0.13824/self.information['exptime']
-            self.frame_r_1[k, :] += r_1*0.13824/self.information['exptime']
-            # end
+     def getFrameTransferImg(self):
+         """
+
+
+         Returns
+         -------
+         None.
+
+         """
+         """
+         get frame transfer image from original image of self.image_b and self.image_r
+         """
+         overscan=320
+         self.frame_b_4 = np.zeros((1024+overscan, 2048), dtype=float)
+         self.frame_b_3 = np.zeros((1024+overscan, 2048), dtype=float)
+         self.frame_b_2 = np.zeros((1024+overscan, 2048), dtype=float)
+         self.frame_b_1 = np.zeros((1024+overscan, 2048), dtype=float)
+
+         self.frame_r_4 = np.zeros((1536+overscan, 3072), dtype=float)
+         self.frame_r_3 = np.zeros((1536+overscan, 3072), dtype=float)
+         self.frame_r_2 = np.zeros((1536+overscan, 3072), dtype=float)
+         self.frame_r_1 = np.zeros((1536+overscan, 3072), dtype=float)
+
+         # OSH, part2 ,no change
+         b_2 = np.sum(self.image_b[0:1024, 0:2048], axis=0)
+
+         # flip right to  left of part1
+         temp_b_1 = np.fliplr(self.image_b[0:1024, 2048:4096])  # left to right
+         b_1 = np.sum(temp_b_1, axis=0)
+
+         # part 4, left to right  and up to down
+         temp_b_4 = np.fliplr(
+             self.image_b[1024:1024+1024, 2048:2048+2048])      # left to right
+         b_4 = np.sum(temp_b_4, axis=0)
+
+         # part 3,OSE, up to dwon
+         b_3 = np.sum(self.image_b[1024:1024+1024, 0:2048], axis=0)
+         ####
+
+         for k in range(1024+overscan):
+             # part
+             self.frame_b_4[k, :] += b_4*0.09216/self.information['exptime']
+             self.frame_b_3[k, :] += b_3*0.09216/self.information['exptime']
+             self.frame_b_2[k, :] += b_2*0.09216/self.information['exptime']
+             self.frame_b_1[k, :] += b_1*0.09216/self.information['exptime']
+
+         ###################
+         # red channle
+         # OSH, part2 ,no change
+         r_2 = np.sum(self.image_r[0:1536, 0:3072], axis=0)
+
+         # # flip right to  left of part1
+         temp_r_1 = np.fliplr(self.image_r[0:1536, 3072:6144])  # left to right
+         r_1 = np.sum(temp_r_1, axis=0)
+
+         # part 4, left to right  and up to down
+         temp_r_4 = np.fliplr(
+             self.image_r[1536:1536+1536, 3072:6144])  # left to right
+         r_4 = np.sum(temp_r_4, axis=0)
+
+         # part 3,OSE, up to dwon
+         r_3 = np.sum(self.image_r[1536:1536+1536, 0:3072], axis=0)
+
+         for k in range(1536+overscan):
+             # part 4, OSH zone;
+             self.frame_r_4[k, :] += r_4*0.13824/self.information['exptime']
+             self.frame_r_3[k, :] += r_3*0.13824/self.information['exptime']
+             self.frame_r_2[k, :] += r_2*0.13824/self.information['exptime']
+             self.frame_r_1[k, :] += r_1*0.13824/self.information['exptime']
+             # end
 
 ###############################################################################
     def applyflatfield(self, simnumber):
@@ -2294,6 +2289,12 @@ class IFSsimulator():
         support package.
         """
         self.readCosmicRayInformation()
+        #
+        if self.information['coveringfraction'] > 1 or self.information['coveringfraction'] < 0.1:
+            self.log.error(
+                'coveringFraction error, it shoub be in [0.1, 1]!')
+            raise ValueError(
+                'coveringFraction error, it shoub be in [0.1, 1]!')
         # to scale the number of cosmics with exposure time
         self.cr['exptime'] = self.information['exptime']
 
@@ -2303,8 +2304,8 @@ class IFSsimulator():
         crImage_r = np.zeros((3072, 6144), dtype=float)
 
         # cosmic ray instance
-        cosmics_b = cosmicrays(self.log, crImage_b, crInfo=self.cr)
-        cosmics_r = cosmicrays(self.log, crImage_r, crInfo=self.cr)
+        cosmics_b = cosmicrays(self.log, crImage_b,self.information['exptime'], crInfo=self.cr)
+        cosmics_r = cosmicrays(self.log, crImage_r,self.information['exptime'], crInfo=self.cr)
 
         CCD_cr_b = cosmics_b.addUpToFraction(
             self.information['coveringfraction']*self.information['exptime']/300.0, limit=None)
@@ -2729,49 +2730,49 @@ class IFSsimulator():
         apply frame transfer effect to the four part images
         """
         prescan = 50
-        overscan = 8
+        overscan = 0
 
-        # zone 4 ,  OSH ####  1024,  2048
+        # zone 1 ,  OSG ####  1024,  2048
         self.image_b[0:1024+overscan, prescan:2048 +
-                     prescan] += self.frame_b_4[0:1024+overscan, 0:2048]
+                     prescan] += self.frame_b_1[0:1024+overscan, 0:2048]
 
-        # ######### zone 3, OSG    #################
+        ########## zone 2, OSH    #################
 
         self.image_b[0:1024+overscan, prescan+2418:2418+2048 +
-                     prescan] += self.frame_b_3[0:1024+overscan, 0:2048]
+                     prescan] += self.frame_b_2[0:1024+overscan, 0:2048]
 
-        # ######### zone 1, OSE  ###################
+        ########## zone 3, OSE  ###################
 
         self.image_b[0:1024+overscan, prescan+2418*2:2418*2 +
-                     2048+prescan] += self.frame_b_1[0:1024+overscan, 0:2048]
+                     2048+prescan] += self.frame_b_3[0:1024+overscan, 0:2048]
 
-        # ######### zone 2, OSF ###############
+        ########## zone 4, OSF ###############
 
         self.image_b[0:1024+overscan, prescan+2418*3:2418*3 +
-                     2048+prescan] += self.frame_b_2[0:1024+overscan, 0:2048]
+                     2048+prescan] += self.frame_b_4[0:1024+overscan, 0:2048]
 
         # 3
 
         self.log.info('readnoise added in blue channel')
 
-        # red zone 4 , OSH### 1536* 3072
+        # red zone 1 , OSG### 1536* 3072
 
         self.image_r[0:1536+overscan, prescan+3442*0:3442*0 +
-                     3072+prescan] += self.frame_r_4[0:1536+overscan, 0:3072]
+                     3072+prescan] += self.frame_r_1[0:1536+overscan, 0:3072]
 
-        # ######### zone 3 ,OSG #################
+        ########## zone 2 ,OSh #################
 
         self.image_r[0:1536+overscan, prescan+3442*1:3442*1 +
-                     3072+prescan] += self.frame_r_3[0:1536+overscan, 0:3072]
+                     3072+prescan] += self.frame_r_2[0:1536+overscan, 0:3072]
 
-        # ######### zone 1 ,OSE ###################
+        ########## zone 1 ,OSE ###################
         self.image_r[0:1536+overscan, prescan+3442*2:3442*2 +
-                     3072+prescan] += self.frame_r_1[0:1536+overscan, 0:3072]
+                     3072+prescan] += self.frame_r_3[0:1536+overscan, 0:3072]
 
-        # ######### zone 2,OSF ###########
+        ########## zone 4,OSF ###########
 
         self.image_r[0:1536+overscan, prescan+3442*3:3442*3 +
-                     3072+prescan] += self.frame_r_2[0:1536+overscan, 0:3072]
+                     3072+prescan] += self.frame_r_4[0:1536+overscan, 0:3072]
 
     ##########################################################################
 
@@ -5932,7 +5933,7 @@ class IFSsimulator():
 
             if self.nonlinearity:
                 self.applyNonlinearity()
-                print('Applying  nonlinearity finished.......')
+                print('Applying nonlinearity finished.......')
 
             # cut original CCD image to four parts by four read out channels and zones
             self.CCDreadout()

requirements.txt

-numpy==1.23.5
-scipy==1.9.2
-setuptools==65.6.3
-pandas==1.5.3
-julian==0.14
-astropy==6.0.0
-tqdm==4.64.1
-galsim==2.4.9
+#numpy==1.23.5
+#scipy==1.9.2
+#setuptools==65.6.3
+#pandas==1.5.3
+#julian==0.14
+#astropy==6.0.0
+#tqdm==4.64.1
+#galsim==2.4.9

setup.py

@@ -16,7 +16,7 @@ with open("requirements.txt", "r") as f:
 setuptools.setup(
     
     name='csst_ifs_sim',  # 包名
-    version="3.0.0",  # 版本号
+    version="3.0.1",  # 版本号
     author="Zhaojun Yan",  # 作者
     author_email="zhaojunyan@shao.ac.cn",  # 邮箱
     description="The CSST IFS simulation - prototype",  # 短描述