From edea3987466fd5bdd50ec00e83031f481db5ea38 Mon Sep 17 00:00:00 2001
From: ahmedk <karim.ahmed@xfel.eu>
Date: Wed, 20 Nov 2024 18:00:18 +0100
Subject: [PATCH] feat: add new parameter to exclude first ntrains from dark
processing
---
.../Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb | 6 +++++-
1 file changed, 5 insertions(+), 1 deletion(-)
diff --git a/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb
index c4ffa097a..0d63bf4ec 100644
--- a/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb
@@ -44,6 +44,7 @@
"offset_abs_threshold_high = [8000, 15000, 15000] # absolute bad pixel threshold in terms of offset, upper values\n",
"max_trains = 1000 # Maximum trains to process darks. Set to 0 to process all available train images. 1000 trains is enough resolution to create the dark constants\n",
"min_trains = 100 # Minimum number of trains to process dark constants. Raise a warning if the run has fewer trains.\n",
+ "exclude_ntrains = 0 # Number of first number of trains to exclude from dark processing.\n",
"manual_slow_data = False # if true, use manually entered bias_voltage and integration_time values\n",
"time_limits = 0.025 # to find calibration constants later on, the integration time is allowed to vary by 0.5 us\n",
"creation_time = \"\" # To overwrite the measured creation_time. Required Format: YYYY-MM-DD HR:MN:SC e.g. \"2022-06-28 13:00:00\"\n",
@@ -378,8 +379,11 @@
" if n_trains < min_trains:\n",
" warning(f\"Less than {min_trains} trains are available in RAW data.\")\n",
"\n",
+ " if exclude_ntrains:\n",
+ " print(f\"Excluding first {exclude_ntrains} from processing as configured.\")\n",
+ "\n",
" # Select only requested number of images to process darks.\n",
- " instr_dc = instr_dc.select_trains(np.s_[:n_trains])\n",
+ " instr_dc = instr_dc.select_trains(np.s_[exclude_ntrains:n_trains])\n",
" images = np.transpose(\n",
" instr_dc[instrument_src, \"data.adc\"].ndarray(), (3, 2, 1, 0))\n",
" acelltable = np.transpose(instr_dc[instrument_src, \"data.memoryCell\"].ndarray())\n",
--
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