diff --git a/notebooks/Gotthard2/Characterize_Darks_Gotthard2_NBC.ipynb b/notebooks/Gotthard2/Characterize_Darks_Gotthard2_NBC.ipynb
index e7dbfc9cd26bebd5e62d440c3971a9edfd3613fe..bf2384afb09c59108e739a9ab9493d8adaf8f7b8 100644
--- a/notebooks/Gotthard2/Characterize_Darks_Gotthard2_NBC.ipynb
+++ b/notebooks/Gotthard2/Characterize_Darks_Gotthard2_NBC.ipynb
@@ -52,7 +52,7 @@
"acquisition_rate = -1. # Detector acquisition rate (1.1/4.5), set to -1 to use value in raw file.\n",
"single_photon = -1 # Detector single photon mode (High/Low CDS), set to -1 to use value in raw file.\n",
"# This is used for the summary notebook\n",
- "gh2_detector = \"\" # Specifies the GH2 detector type ('50um' or '25um'). This parameter can be used to manually set the detector type if the code cannot automatically determine it from the control data.\n",
+ "sensor_type = \"\" # Specifies the GH2 sensor type: '50um', '25um', or \"\" to automatically decide from RUN data.\n",
"\n",
"# Parameters used for calculating calibration constants\n",
"bpix_noise_nitrs = 5 # number of maximum iterations to actively try to reach correct number of badpixels of NOISE_OUT_OF_THRESHOLD type. Leave -1 to keep iterating until finding maximum number of badpixels.\n",
@@ -208,9 +208,9 @@
"print(\"Single photon: \", single_photon)\n",
"acquisition_rate = conditions[\"acquisition_rate\"].pop()\n",
"print(\"Acquisition rate: \", acquisition_rate)\n",
- "if not gh2_detector:\n",
- " gh2_detector = g2ctrl.get_det_type()\n",
- "print(f\"Processing {gh2_detector} Gotthard2.\")"
+ "if not sensor_type:\n",
+ " sensor_type = g2ctrl.get_sensor_type()\n",
+ "print(f\"Processing {sensor_type} Gotthard2.\")"
]
},
{
diff --git a/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb b/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb
index 022c74bfff23567dda077fcf563400eada501c6d..478719287185de554a953965039c62d6550ee8b6 100644
--- a/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb
+++ b/notebooks/Gotthard2/Correction_Gotthard2_NBC.ipynb
@@ -84,7 +84,7 @@
"acquisition_rate = -1. # Detector acquisition rate (1.1/4.5), set to -1 to use value in raw file.\n",
"single_photon = -1 # Detector single photon mode (High/Low CDS), set to -1 to use value in raw file.\n",
"reverse_second_module = -1 # Reverse 25um GH2 second module before interleaving. set to -1 to use value in raw file to reverse based on `CTRL/reverseSlaveReadOutMode`'s value.\n",
- "gh2_detector = \"\" # Specifies the GH2 detector type ('50um' or '25um'). This parameter can be used to manually set the detector type if the code cannot automatically determine it from the control data.\n",
+ "sensor_type = \"\" # Specifies the GH2 sensor type: '50um', '25um', or \"\" to automatically decide from RUN data.\n",
"\n",
"# Parameters for plotting\n",
"skip_plots = False # exit after writing corrected files\n",
@@ -189,17 +189,17 @@
" acquisition_rate = g2ctrl.get_acquisition_rate()\n",
"if single_photon == -1:\n",
" single_photon = g2ctrl.get_single_photon()\n",
- "if not gh2_detector:\n",
- " gh2_detector = g2ctrl.get_det_type()\n",
+ "if not sensor_type:\n",
+ " sensor_type = g2ctrl.get_sensor_type()\n",
"\n",
"# Check if the GH2 detector type is \"50um\" and validate that only one data aggregator is provided\n",
- "if gh2_detector == \"50um\" and len(karabo_da) > 1:\n",
+ "if sensor_type == \"50um\" and len(karabo_da) > 1:\n",
" raise ValueError(\n",
" f\"karabo_da has more than one aggregator {karabo_da}, \"\n",
" \"but the GH2 detector type is specified as '50um', which expects only one aggregator.\"\n",
" )\n",
"\n",
- "if reverse_second_module == -1 and gh2_detector == \"25um\":\n",
+ "if reverse_second_module == -1 and sensor_type == \"25um\":\n",
" reverse_second_module = not g2ctrl.second_module_reversed()\n",
" if reverse_second_module:\n",
" warning(\n",
@@ -211,7 +211,7 @@
"print(\"Exposure Period:\", exposure_period)\n",
"print(\"Acquisition Rate:\", acquisition_rate)\n",
"print(\"Single Photon:\", single_photon)\n",
- "print(f\"Processing {gh2_detector} Gotthard2.\")"
+ "print(f\"Processing {sensor_type} Gotthard2.\")"
]
},
{
@@ -444,7 +444,7 @@
" print(f\"Correcting {n_trains} for {raw_file}.\")\n",
"\n",
" # Initialize GH2 data and gain arrays to store in corrected files.\n",
- " if gh2_detector == \"25um\":\n",
+ " if sensor_type == \"25um\":\n",
" dshape_stored = (dc[data_sources[0], \"data.adc\"].shape[:2] + (1280 * 2,))\n",
" data_stored = np.zeros(dshape_stored, dtype=np.float32)\n",
" gain_stored = np.zeros(dshape_stored, dtype=np.uint8)\n",
@@ -486,7 +486,7 @@
" # Create CORR files and add corrected data sections.\n",
" image_counts = dc[src, \"data.adc\"].data_counts(labelled=False)\n",
"\n",
- " if gh2_detector == \"25um\":\n",
+ " if sensor_type == \"25um\":\n",
" data_stored[..., i::2] = data_corr\n",
" gain_stored[..., i::2] = gain\n",
" mask_stored[..., i::2] = mask\n",
@@ -577,14 +577,14 @@
" )\n",
" mask = out_dc[corr_data_source, \"data.mask\"].train_from_id(tid)[1]\n",
"\n",
- "if gh2_detector == \"25um\":\n",
+ "if sensor_type == \"25um\":\n",
" mod_dcs[corr_data_source][\"train_raw_data\"] = np.zeros((data_corr.shape[1], 1280 * 2), dtype=np.float32)\n",
" mod_dcs[corr_data_source][\"train_raw_gain\"] = np.zeros((data_corr.shape[1], 1280 * 2), dtype=np.uint8)\n",
"\n",
"for i, src in enumerate(data_sources):\n",
" with H5File(first_seq_raw) as in_dc:\n",
" train_dict = in_dc.train_from_id(tid)[1][src]\n",
- " if gh2_detector == \"25um\":\n",
+ " if sensor_type == \"25um\":\n",
" if reverse_second_module and i == 1:\n",
" data = np.flip(train_dict[\"data.adc\"], axis=-1)\n",
" gain = np.flip(train_dict[\"data.gain\"], axis=-1)\n",
@@ -621,8 +621,8 @@
"display(Markdown(\"### Mean RAW and CORRECTED across pulses for one train:\"))\n",
"display(Markdown(f\"Train: {tid}\"))\n",
"\n",
- "# Set title format based on gh2_detector\n",
- "if gh2_detector == \"50um\":\n",
+ "# Set title format based on sensor_type\n",
+ "if sensor_type == \"50um\":\n",
" title_format = f\"{{}} data for {karabo_da} ({db_modules})\"\n",
"else:\n",
" title_format = f\"Interleaved {{}} data for {karabo_da} ({db_modules})\"\n",
diff --git a/notebooks/Gotthard2/Summary_Darks_Gotthard2_NBC.ipynb b/notebooks/Gotthard2/Summary_Darks_Gotthard2_NBC.ipynb
index b4f6df31e0331831a8248d7d93fc6935c7abb7ff..ecd41edee72cadf063920f14a6fb93432014b300 100644
--- a/notebooks/Gotthard2/Summary_Darks_Gotthard2_NBC.ipynb
+++ b/notebooks/Gotthard2/Summary_Darks_Gotthard2_NBC.ipynb
@@ -31,7 +31,7 @@
"ctrl_source_template = '{karabo_id}/DET/{control_template}' # template for control source name (filled with karabo_id_control)\n",
"karabo_id_control = \"\" # Control karabo ID. Set to empty string to use the karabo-id\n",
"\n",
- "gh2_detector = \"\" # Specifies the GH2 detector type ('50um' or '25um'). This parameter can be used to manually set the detector type if the code cannot automatically determine it from the control data.\n",
+ "sensor_type = \"\" # Specifies the GH2 sensor type: '50um', '25um', or \"\" to automatically decide from RUN data.\n",
"\n",
"# Parameters to be used for injecting dark calibration constants.\n",
"local_output = True # Boolean indicating that local constants were stored in the out_folder\n",
@@ -93,12 +93,9 @@
" karabo_id_control=karabo_id_control,\n",
" control_template=control_template\n",
" ))\n",
- "if not gh2_detector:\n",
- " # Unfortunately we can't check if we can't validate this value\n",
- " # as the notebook will have only one karabo_da anyway.\n",
- " # Dark processing split nodes over each karabo_da\n",
- " gh2_detector = g2ctrl.get_det_type()\n",
- "print(f\"Processing {gh2_detector} Gotthard2.\")"
+ "if not sensor_type:\n",
+ " sensor_type = g2ctrl.get_sensor_type()\n",
+ "print(f\"Processing {sensor_type} Gotthard2.\")"
]
},
{
diff --git a/src/cal_tools/gotthard2/gotthard2lib.py b/src/cal_tools/gotthard2/gotthard2lib.py
index e6a8267c86de2b567a1e613120f6cde3f16fd226..e13e5ad1e142c123a9dc387f2c91a0141d14574b 100644
--- a/src/cal_tools/gotthard2/gotthard2lib.py
+++ b/src/cal_tools/gotthard2/gotthard2lib.py
@@ -63,16 +63,31 @@ class Gotthard2Ctrl():
return bool(
self.run_dc[self.ctrl_src, "singlePhoton"].as_single_value())
- def get_det_type(self):
+ def get_sensor_type(self):
"""GH2 rxHostname is a vector of bytes objects.
GH2 25um has two host names unlike 50um which has one.
Returns:
str: return if its a 25um or 50um detector.
"""
-
- hostname = self.run_dc.get_run_value(self.ctrl_src, "rxHostname")
- return "25um" if hostname[1].decode("utf-8") else "50um"
+ import numpy as np
+
+ hostnames = self.run_dc.get_run_value(self.ctrl_src, "rxHostname")
+ num_hosts = np.count_nonzero(hostnames != b'')
+ if num_hosts == 0:
+ raise ValueError(
+ "No hosts are present in RUN/rxHostname. "
+ "Unable to determine the sensor type for this data. ")
+
+ if num_hosts == 1:
+ return "50um"
+ elif num_hosts == 2:
+ return "25um"
+ else:
+ raise ValueError(
+ f"RUN/rxHostname has more host names ({num_hosts}) than expected. "
+ "Expected either 1 hostname for 50um or 2 host names for 25um."
+ )
def second_module_reversed(self):
"""Check if reverseSlaveReadOutMode is True."""