From d4fac2bbb0b1cc66a1e42231eee93e1c724a622e Mon Sep 17 00:00:00 2001
From: ahmedk <karim.ahmed@xfel.eu>
Date: Thu, 30 May 2024 19:52:17 +0200
Subject: [PATCH] fix: add Thomas' production hotfix
---
.../AGIPD/AGIPD_Correct_and_Verify.ipynb | 19 ++++++++-----------
1 file changed, 8 insertions(+), 11 deletions(-)
diff --git a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
index a7d9edcae..139fdd748 100644
--- a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
+++ b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
@@ -1044,29 +1044,26 @@
"display(Markdown(f'## Preview and statistics for {gains.shape[0]} images of the train {tid} ##\\n'))"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Signal vs. Analogue Gain ###"
- ]
- },
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
- "raw_float = raw.astype(np.float32)\n",
- "signal = raw[:, 0, ...]\n",
+ "# As part of data reduction efforts, the DAQ now has an option to discard AGIPD gain data\n",
+ "# when it is known that all data is in the same gain stage. In such cases, the gain data\n",
+ "# will be set to zeros. Consequently, the signal vs. analog gain 2D histogram can be skipped.\n",
"gain = raw[:, 1, ...]\n",
- "hist, bins_x, bins_y = calgs.histogram2d(\n",
+ "if gain.max() > 0:\n",
+ " signal = raw[:, 0, ...]\n",
+ " display(Markdown(\"### Signal vs. Analogue Gain\"))\n",
+ " hist, bins_x, bins_y = calgs.histogram2d(\n",
" signal.flatten().astype(np.float32),\n",
" gain.flatten().astype(np.float32),\n",
" bins=(100, 100),\n",
" range=[\n",
" np.percentile(signal, [0.02, 99.8]),\n",
- " [0, 3],\n",
+ " np.percentile(signal, [0.02, 99.8]),\n",
" ],\n",
" )\n",
"do_2d_plot(hist, (bins_x, bins_y), \"Signal (ADU)\", \"Analogue gain (ADU)\")"
--
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