From 047b20c9ce644ae4d433afed26f497311cafc47e Mon Sep 17 00:00:00 2001
From: ahmedk <karim.ahmed@xfel.eu>
Date: Thu, 2 Mar 2023 16:38:25 +0100
Subject: [PATCH] update correction to use virtual karabo da
---
.../Gotthard2/Correction_Gotthard2_NBC.ipynb | 71 +++++++++----------
1 file changed, 32 insertions(+), 39 deletions(-)
diff --git a/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb b/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb
index b455ca34d..3f7d2368a 100644
--- a/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb
+++ b/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb
@@ -162,26 +162,12 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "7bf7fb32",
+ "id": "892172d8",
"metadata": {},
"outputs": [],
"source": [
"run_dc = RunDirectory(run_folder)\n",
"\n",
- "# Decide if we are processing 2 25um or 1 50um Gotthard-II\n",
- "\n",
- "receivers = list(run_dc.select(f'{karabo_id}/DET/{receiver_template}*').all_sources)\n",
- "\n",
- "corr_karabo_da = receivers[0].split(\"/\")[-1].split(\":\")[0][:-2]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "892172d8",
- "metadata": {},
- "outputs": [],
- "source": [
"# Read slow data\n",
"g2ctrl = gotthard2lib.Gotthard2Ctrl(run_dc=run_dc, ctrl_src=ctrl_src)\n",
"\n",
@@ -206,7 +192,18 @@
"gh2_hostname = run_dc.get_run_value(ctrl_src, \"rxHostname\")\n",
"# gh2_hostname is a vector of bytes objects.\n",
"# GH2 25um has two hostnames unlike 50um which has one.\n",
- "gh2_detector = \"25um\" if gh2_hostname[1].decode(\"utf-8\") else \"50um\""
+ "gh2_detector = \"25um\" if gh2_hostname[1].decode(\"utf-8\") else \"50um\"\n",
+ "\n",
+ "# Decide if we are processing 2 25um or 1 50um Gotthard-II\n",
+ "\n",
+ "receivers = sorted(list(run_dc.select(f'{karabo_id}/DET/{receiver_template}*').all_sources))\n",
+ "\n",
+ "if gh2_detector == \"25um\": # For 25um use virtual karabo_das for CALCAT data mapping.\n",
+ " karabo_da = [f\"{karabo_da[0]}/1\", f\"{karabo_da[0]}/2\"]\n",
+ " print(\"Processing 25um Gotthard2.\")\n",
+ " corr_karabo_da = receivers[0].split(\"/\")[-1].split(\":\")[0][:-2]\n",
+ "else:\n",
+ " corr_karabo_da = receivers[0].split(\"/\")[-1].split(\":\")[0]"
]
},
{
@@ -249,7 +246,7 @@
" db_modules = [None] * len(karabo_da)\n",
"\n",
"if constants_file:\n",
- " for mod in receivers:\n",
+ " for mod in karabo_da:\n",
" const_data[mod] = dict()\n",
" # load constants temporarily using defined local paths.\n",
" with h5py.File(constants_file, \"r\") as cfile:\n",
@@ -362,6 +359,8 @@
"metadata": {},
"outputs": [],
"source": [
+ "corr_data_source = f\"{karabo_id}/DET/{corr_karabo_da}:daqOutput\"\n",
+ "\n",
"for raw_file in seq_files:\n",
"\n",
" out_file = out_folder / raw_file.name.replace(\"RAW\", \"CORR\")\n",
@@ -378,12 +377,12 @@
" data_stored = None\n",
" gain_stored = None\n",
"\n",
- " for i, rec_mod in enumerate(receivers):\n",
+ " for i, (receiver, mod) in enumerate(zip(receivers, karabo_da)):\n",
" step_timer.start()\n",
- " print(f\"Correcting {rec_mod} for {raw_file}\")\n",
+ " print(f\"Correcting {receiver} for {raw_file}\")\n",
"\n",
- " data = dc[rec_mod, \"data.adc\"].ndarray()\n",
- " gain = dc[rec_mod, \"data.gain\"].ndarray()\n",
+ " data = dc[receiver, \"data.adc\"].ndarray()\n",
+ " gain = dc[receiver, \"data.gain\"].ndarray()\n",
" step_timer.done_step(\"Preparing raw data\")\n",
" dshape = data.shape\n",
"\n",
@@ -402,7 +401,7 @@
" data_corr[np.isinf(data_corr)] = np.nan\n",
"\n",
" # Create CORR files and add corrected data sections.\n",
- " image_counts = dc[rec_mod, \"data.adc\"].data_counts(labelled=False)\n",
+ " image_counts = dc[receiver, \"data.adc\"].data_counts(labelled=False)\n",
"\n",
" if gh2_detector == \"25um\":\n",
" data_stored[..., i::2] = data_corr.copy()\n",
@@ -421,7 +420,7 @@
" )\n",
"\n",
" # Create Instrument section to later add corrected datasets.\n",
- " outp_source = ofile.create_instrument_source(f\"{karabo_id}/DET/{corr_karabo_da}:daqOutput\")\n",
+ " outp_source = ofile.create_instrument_source(corr_data_source)\n",
"\n",
" # Create count/first datasets at INDEX source.\n",
" outp_source.create_index(data=image_counts)\n",
@@ -446,8 +445,8 @@
" # stored in the corrected file.\n",
" for field in [\"bunchId\", \"memoryCell\", \"frameNumber\", \"timestamp\"]:\n",
" outp_source.create_key(\n",
- " f\"data.{field}\", data=dc[instr_mod_src, f\"data.{field}\"].ndarray(),\n",
- " chunks=(chunks_data, data_corr.shape[1])\n",
+ " f\"data.{field}\", data=dc[receiver, f\"data.{field}\"].ndarray(),\n",
+ " chunks=(chunk_size_idim, data_corr.shape[1])\n",
" )\n",
" outp_source.create_compressed_key(f\"data.mask\", data=mask)\n",
" step_timer.done_step(\"Storing data\")\n",
@@ -465,16 +464,6 @@
"step_timer.print_summary()"
]
},
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "7f366352",
- "metadata": {},
- "outputs": [],
- "source": [
- "corr_data_source = f\"{karabo_id}/DET/{corr_karabo_da}:daqOutput\""
- ]
- },
{
"cell_type": "code",
"execution_count": null,
@@ -501,7 +490,6 @@
"first_seq_corr = out_folder / first_seq_raw.name.replace(\"RAW\", \"CORR\")\n",
"mod_dcs[corr_data_source] = {}\n",
"with H5File(first_seq_corr) as out_dc:\n",
- " print(out_dc.all_sources)\n",
" tid, mod_dcs[corr_data_source][\"train_corr_data\"] = next(\n",
" out_dc[corr_data_source, \"data.adc\"].trains()\n",
" )\n",
@@ -531,12 +519,17 @@
"display(Markdown(\"### Mean RAW and CORRECTED across pulses for one train:\"))\n",
"display(Markdown(f\"Train: {tid}\"))\n",
"\n",
+ "if gh2_detector == \"50um\":\n",
+ " title = f\"{{}} data for {karabo_da} ({db_modules})\"\n",
+ "else:\n",
+ " title = f\"Interleaved {{}} data for {karabo_da} ({db_modules})\"\n",
+ "\n",
"step_timer.start()\n",
"\n",
"fig, ax = plt.subplots(figsize=(20, 10))\n",
"raw_data = mod_dcs[corr_data_source][\"train_raw_data\"]\n",
"im = ax.plot(np.mean(raw_data, axis=0))\n",
- "ax.set_title(f\"RAW module {receivers} ({db_modules})\")\n",
+ "ax.set_title(title.format(\"RAW\"))\n",
"ax.set_xlabel(\"Strip #\", size=20)\n",
"ax.set_ylabel(\"12-bit ADC output\", size=20)\n",
"plt.xticks(fontsize=20)\n",
@@ -546,7 +539,7 @@
"fig, ax = plt.subplots(figsize=(20, 10))\n",
"corr_data = mod_dcs[corr_data_source][\"train_corr_data\"]\n",
"im = ax.plot(np.mean(corr_data, axis=0))\n",
- "ax.set_title(f\"CORRECTED module {receivers} ({db_modules})\")\n",
+ "ax.set_title(title.format(\"CORRECTED\"))\n",
"ax.set_xlabel(\"Strip #\", size=20)\n",
"ax.set_ylabel(\"10-bit KeV. output\", size=20)\n",
"plt.xticks(fontsize=20)\n",
@@ -575,7 +568,7 @@
" mod_dcs[corr_data_source][plt_data],\n",
" y_label=\"Pulses\",\n",
" x_label=\"Strips\",\n",
- " title=f\"{dname} module {receivers} ({db_modules})\",\n",
+ " title=title.format(dname),\n",
" use_axis=ax,\n",
" )\n",
" pass\n",
--
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