input download progress tracking

Author: LTDakin

datalab/datalab_session/data_operations/median.py

@@ -48,7 +48,10 @@ def operate(self):
         comment = f'Datalab Median on {", ".join([image["basename"] for image in input_list])}'
         log.info(comment)
 
-        input_FITS_list = [FITSFileReader(input['basename'], input['source']) for input in input_list]
+        input_FITS_list = []
+        for index, input in enumerate(input_list, start=1):
+            input_FITS_list.append(FITSFileReader(input['basename'], input['source']))
+            self.set_operation_progress(0.5 * (index / len(input_list)))
 
         # Creating the Median array
         cropped_data = crop_arrays([image.sci_data for image in input_FITS_list])

datalab/datalab_session/data_operations/normalization.py

@@ -44,7 +44,10 @@ def operate(self):
         input_list = self.input_data.get('input_files', [])
         log.info(f'Normalization operation on {len(input_list)} file(s)')
 
-        input_FITS_list = [FITSFileReader(input['basename'], input['source']) for input in input_list]
+        input_FITS_list = []
+        for index, input in enumerate(input_list, start=1):
+            input_FITS_list.append(FITSFileReader(input['basename'], input['source']))
+            self.set_operation_progress(0.5 * (index / len(input_list)))
 
         output_files = []
         for index, image in enumerate(input_FITS_list, start=1):

datalab/datalab_session/data_operations/rgb_stack.py

@@ -63,8 +63,10 @@ def operate(self):
         rgb_comment = f'Datalab RGB Stack on files {", ".join([image["basename"] for image in rgb_input_list])}'
         log.info(rgb_comment)
 
-        input_FITS_list = [FITSFileReader(input['basename'], input['source']) for input in rgb_input_list]
-        self.set_operation_progress(0.4)
+        input_FITS_list = []
+        for index, input in enumerate(rgb_input_list, start=1):
+            input_FITS_list.append(FITSFileReader(input['basename'], input['source']))
+            self.set_operation_progress(0.4 * (index / len(rgb_input_list)))
 
         fits_file_list = [image.fits_file for image in input_FITS_list]
         large_jpg_path, small_jpg_path = create_jpgs(self.cache_key, fits_file_list, color=True)

datalab/datalab_session/data_operations/stacking.py

@@ -49,8 +49,10 @@ def operate(self):
         comment= f'Datalab Stacking on {", ".join([image["basename"] for image in input_files])}'
         log.info(comment)
 
-        input_FITS_list = [FITSFileReader(input['basename'], input['source']) for input in input_files]
-        self.set_operation_progress(0.4)
+        input_FITS_list = []
+        for index, input in enumerate(input_files, start=1):
+            input_FITS_list.append(FITSFileReader(input['basename'], input['source']))
+            self.set_operation_progress(0.5 * (index / len(input_files)))
 
         cropped_data = crop_arrays([image.sci_data for image in input_FITS_list])
         stacked_ndarray = np.stack(cropped_data, axis=2)

datalab/datalab_session/data_operations/subtraction.py

@@ -59,9 +59,12 @@ def operate(self):
 
         log.info(f'Subtraction operation on {len(input_files)} files')
 
-        input_FITS_list = [FITSFileReader(input['basename'], input['source']) for input in input_files]
         subtraction_FITS = FITSFileReader(subtraction_file_input[0]['basename'], subtraction_file_input[0]['source'])
-        self.set_operation_progress(0.5)
+        input_FITS_list = [FITSFileReader(input['basename'], input['source']) for input in input_files]
+        input_FITS_list = []
+        for index, input in enumerate(input_files, start=1):
+            input_FITS_list.append(FITSFileReader(input['basename'], input['source']))
+            self.set_operation_progress(0.5 * (index / len(input_files)))
 
         outputs = []
         for index, input_image in enumerate(input_FITS_list, start=1):