From 41603db359bf2b6ad1d2e0efe800a89f60615187 Mon Sep 17 00:00:00 2001
From: Philipp Schmidt <philipp.schmidt@xfel.eu>
Date: Thu, 7 Oct 2021 14:45:43 +0200
Subject: [PATCH] Add support to only correct AGIPD trains picked by a PPU
device
---
.../AGIPD/AGIPD_Correct_and_Verify.ipynb | 32 +++++++++++++++++++
1 file changed, 32 insertions(+)
diff --git a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
index 613b264ad..147757da0 100644
--- a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
+++ b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
@@ -40,6 +40,9 @@
"cal_db_timeout = 30000 # in milli seconds\n",
"creation_date_offset = \"00:00:00\" # add an offset to creation date, e.g. to get different constants\n",
"\n",
+ "use_ppu_device = '' # Device ID for a pulse picker device to only process picked trains, empty string to disable\n",
+ "ppu_train_offset = 0 # When using the pulse picker, offset between the PPU's sequence start and actually picked train\n",
+ "\n",
"max_cells = 0 # number of memory cells used, set to 0 to automatically infer\n",
"bias_voltage = 300 # Bias voltage\n",
"acq_rate = 0. # the detector acquisition rate, use 0 to try to auto-determine\n",
@@ -381,6 +384,29 @@
"print(f\"• Photon Energy: {photon_energy}\")"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Obtain trains to process if using a pulse picker device.\n",
+ "if use_ppu_device:\n",
+ " run = RunDirectory(in_folder / f'r{run:04d}')\n",
+ "\n",
+ " # Will throw an uncaught exception if the device is wrong.\n",
+ " seq_start = run[use_ppu_device, 'trainTrigger.sequenceStart.value'].ndarray()\n",
+ "\n",
+ " # The trains picked are the unique values of trainTrigger.sequenceStart\n",
+ " # minus the first (previous trigger before this run).\n",
+ " train_ids = np.unique(seq_start)[1:] + ppu_train_offset\n",
+ "\n",
+ " print(f'PPU device {use_ppu_device} triggered for {len(train_ids)} trains')\n",
+ "\n",
+ "else:\n",
+ " train_ids = None"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -415,6 +441,7 @@
" corr_bools=corr_bools,\n",
" gain_mode=gain_mode,\n",
" comp_threads=os.cpu_count() // n_cores_files,\n",
+ " train_ids=train_ids\n",
")\n",
"\n",
"agipd_corr.baseline_corr_noise_threshold = -blc_noise_threshold\n",
@@ -558,6 +585,11 @@
" [not common_mode]*len(file_batch)))\n",
" step_timer.done_step(f'Loading data from files')\n",
"\n",
+ " if img_counts == 0:\n",
+ " # Skip any further processing and output if there are no images to\n",
+ " # correct in this file.\n",
+ " continue\n",
+ "\n",
" if mask_zero_std:\n",
" # Evaluate zero-data-std mask\n",
" pool.starmap(agipd_corr.mask_zero_std, itertools.product(\n",
--
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