update

csst_ifs_sim/csst_ifs_sim.py

@@ -356,7 +356,7 @@ class cosmicrays():
                         exposure time.
     """
 
-    def __init__(self, log, image, exposuretime,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.
@@ -376,7 +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=exposuretime))
+                                 cosmicraydistance='/home/yan/csst-master/data/cdf_cr_total.dat', exptime=exposuretime))
         if information is not None:
             self.information.update(information)
 
@@ -2157,76 +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
-         """
-         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 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):