From 3af7df1887d770f47f845447c367b24196453644 Mon Sep 17 00:00:00 2001
From: David Hammer <dhammer@mailbox.org>
Date: Fri, 23 Apr 2021 15:40:13 +0200
Subject: [PATCH] Improving some variable names
---
.../AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb | 15 ++++++++-------
1 file changed, 8 insertions(+), 7 deletions(-)
diff --git a/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb b/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb
index 7cd2606ba..9201b66fd 100644
--- a/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb
+++ b/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb
@@ -306,10 +306,10 @@
"source": [
"# set everything up filewise\n",
"os.makedirs(out_folder, exist_ok=True)\n",
- "gain_mapped_files, total_sequences, total_file_size = map_gain_stages(\n",
+ "gain_mapped_files, total_files, total_file_size = map_gain_stages(\n",
" in_folder, offset_runs, path_template, karabo_da, sequences\n",
")\n",
- "print(f\"Will process a total of {total_sequences} files ({total_file_size:.02f} GB).\")\n",
+ "print(f\"Will process a total of {total_files} files ({total_file_size:.02f} GB).\")\n",
"\n",
"inp = []\n",
"inp_modules = []\n",
@@ -341,7 +341,8 @@
"metadata": {},
"outputs": [],
"source": [
- "parallel_num_procs = min(6, total_sequences)\n",
+ "# min() only relevant if running on multiple modules (i.e. within notebook)\n",
+ "parallel_num_procs = min(12, total_files)\n",
"parallel_num_threads = multiprocessing.cpu_count() // parallel_num_procs\n",
"print(f\"Will use {parallel_num_procs} processes with {parallel_num_threads} threads each\")\n",
"\n",
@@ -383,13 +384,13 @@
" last_index = int(last[status != 0][-1]) + 1\n",
" first_index = int(first[status != 0][0])\n",
" im = np.array(infile[f\"{h5path_f}/data\"][first_index:last_index,...])\n",
- " cellIds = np.squeeze(infile[f\"{h5path_f}/cellId\"][first_index:last_index,...])\n",
+ " cell_ids = np.squeeze(infile[f\"{h5path_f}/cellId\"][first_index:last_index,...])\n",
" \n",
" if interlaced:\n",
" if not fixed_gain_mode:\n",
" ga = im[1::2, 0, ...]\n",
" im = im[0::2, 0, ...].astype(np.float32)\n",
- " cellIds = cellIds[::2]\n",
+ " cell_ids = cell_ids[::2]\n",
" else:\n",
" if not fixed_gain_mode:\n",
" ga = im[:, 1, ...]\n",
@@ -411,7 +412,7 @@
" gains_std = context.alloc(like=offset)\n",
"\n",
" def process_cell(worker_id, array_index, cell_number):\n",
- " cell_slice_index = (cellIds == cell_number)\n",
+ " cell_slice_index = (cell_ids == cell_number)\n",
" im_slice = im[..., cell_slice_index]\n",
" offset[..., cell_number] = np.median(im_slice, axis=2)\n",
" noise[..., cell_number] = np.std(im_slice, axis=2)\n",
@@ -419,7 +420,7 @@
" ga_slice = ga[..., cell_slice_index]\n",
" gains[..., cell_number] = np.median(ga_slice, axis=2)\n",
" gains_std[..., cell_number] = np.std(ga_slice, axis=2)\n",
- " context.map(process_cell, np.unique(cellIds))\n",
+ " context.map(process_cell, np.unique(cell_ids))\n",
"\n",
" # bad pixels\n",
" bp = np.zeros_like(offset, dtype=np.uint32)\n",
--
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