Expose compressed image fields as parameters in AGIPD correct

notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb

@@ -33,7 +33,7 @@
     "ctrl_source_template = '{}/MDL/FPGA_COMP'  # path to control information\n",
     "karabo_id_control = \"SPB_IRU_AGIPD1M1\" # karabo-id for control device\n",
     "\n",
-    "slopes_ff_from_files = \"\" # Path to locally stored SlopesFF and BadPixelsFF constants\n",
+    "slopes_ff_from_files = \"\" # Path to locally stored SlopesFF and BadPixelsFF constants, loaded in precorrection notebook\n",
     "\n",
     "use_dir_creation_date = True # use the creation data of the input dir for database queries\n",
     "cal_db_interface = \"tcp://max-exfl016:8015#8045\" # the database interface to use\n",
@@ -88,11 +88,14 @@
     "use_litframe_device = '' # Device ID for a lit frame finder device to only process illuminated frames, empty string to disable\n",
     "energy_threshold = -1000 # The low limit for the energy (uJ) exposed by frames subject to processing. If -1000, selection by pulse energy is disabled\n",
     "\n",
+    "# Output parameters\n",
+    "compress_fields = ['gain', 'mask']  # Datasets in image group to compress.\n",
+    "\n",
     "# Plotting parameters\n",
     "skip_plots = False # exit after writing corrected files and metadata\n",
     "cell_id_preview = 1 # cell Id used for preview in single-shot plots\n",
     "\n",
-    "# Paralellization parameters\n",
+    "# Parallelization parameters\n",
     "chunk_size = 1000  # Size of chunk for image-wise correction\n",
     "n_cores_correct = 16 # Number of chunks to be processed in parallel\n",
     "n_cores_files = 4 # Number of files to be processed in parallel\n",
@@ -491,7 +494,9 @@
     "agipd_corr.cm_dark_fraction = cm_dark_fraction\n",
     "agipd_corr.cm_n_itr = cm_n_itr\n",
     "agipd_corr.noisy_adc_threshold = noisy_adc_threshold\n",
-    "agipd_corr.ff_gain = ff_gain"
+    "agipd_corr.ff_gain = ff_gain\n",
+    "\n",
+    "agipd_corr.compress_fields = compress_fields",
    ]
   },
   {
@@ -668,6 +673,7 @@
     "\n",
     "            img_counts = pool.map(agipd_corr.apply_selected_pulses, range(len(file_batch)))\n",
     "            step_timer.done_step(\"Applying selected cells after common mode correction\")\n",
+    "            \n",
     "        # Perform image-wise correction\"\n",
     "        pool.starmap(agipd_corr.gain_correction, imagewise_chunks(img_counts))\n",
     "        step_timer.done_step(\"Gain corrections\")\n",

src/cal_tools/agipdlib.py

@@ -343,6 +343,9 @@ class AgipdCorrections:
         self.noisy_adc_threshold = 0.25
         self.ff_gain = 1
 
+        # Output parameters
+        self.compress_fields = ['gain', 'mask']
+
         # Shared variables for data and constants
         self.shared_dict = []
         self.offset = {}
@@ -474,7 +477,6 @@ class AgipdCorrections:
         image_fields = [
             'trainId', 'pulseId', 'cellId', 'data', 'gain', 'mask', 'blShift',
         ]
-        compress_fields = ['gain', 'mask']
 
         n_img = data_dict['nImg'][0]
         if n_img == 0:
@@ -498,7 +500,7 @@ class AgipdCorrections:
             # so it's efficient to examine the file structure.
             for field in image_fields:
                 arr = data_dict[field][:n_img]
-                if field in compress_fields:
+                if field in self.compress_fields:
                     # gain/mask compressed with gzip level 1, but not
                     # checksummed as we would have to implement this.
                     kw = dict(
@@ -517,7 +519,7 @@ class AgipdCorrections:
 
             # Write the corrected data
             for field in image_fields:
-                if field in compress_fields:
+                if field in self.compress_fields:
                     self._write_compressed_frames(
                         image_grp[field], data_dict[field][:n_img],
                     )