diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 398ce9c49319e1b96243f2b4d8cb0949eca08938..8d218c5fa97e742f6b317fe7269ec38ab6446c1f 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -68,7 +68,7 @@ automated_test:
- python3 -m pip install ".[automated_test]"
- echo "Running automated test. This can take sometime to finish depending on the test data."
- echo "Given variables are REFERENCE=$REFERENCE, OUTPUT=$OUTPUT, DETECTOR=$DETECTORS, CALIBRATION=$CALIBRATION"
- - python3 -m pytest ./tests/test_reference_runs --color yes --verbose --release-test --reference-folder /gpfs/exfel/data/scratch/xcaltst/test/$REFERENCE --out-folder /gpfs/exfel/data/scratch/xcaltst/test/$OUTPUT --detectors $DETECTORS --calibration $CALIBRATION
+ - python3 -m pytest ./tests/test_reference_runs --color yes --verbose --release-test --reference-folder /gpfs/exfel/data/scratch/xcaltst/test/$REFERENCE --out-folder /gpfs/exfel/data/scratch/xcaltst/test/$OUTPUT --detectors $DETECTORS --calibration $CALIBRATION --find-difference
timeout: 24 hours
cython-editable-install-test:
diff --git a/notebooks/REMI/REMI_Digitize_and_Transform.ipynb b/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
index ddb1c0c17976f3aaa87928d0aa2d34728949bbd1..fc1ac99babe5143276436c865e383dc0b67237b4 100644
--- a/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
+++ b/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
@@ -412,32 +412,59 @@
" train_triggers['fel'] = [pos in fel_pos for pos in all_pos]\n",
" train_triggers['ppl'] = [pos in ppl_pos for pos in all_pos]\n",
"\n",
- "with timing('find_triggers'):\n",
- " psh.map(trigger_by_ppt, ppt_data)\n",
" \n",
- "if (np.unique(triggers['pulse'][1:] - triggers['pulse'][:-1]) > 0).sum() > 1:\n",
- " # There is more than one delta between pulse entries across all pulses. This is not\n",
- " # necessarily a problem, as the pattern could simply have changed in between trains\n",
- " # with each train being split properly.\n",
- " # If there's more than one delta in a single train, this likely points to a mismatch\n",
- " # of FEL and PPL repetition rate. This is most likely not intended.\n",
+ "if ignore_fel and ignore_ppl:\n",
+ " # Both FEL and PPL are ignored, use virtual full train triggers.\n",
+ " print('WARNING: Both FEL and PPL pulses are ignored, '\n",
+ " 'virtual trigger is inserted covering the entire train')\n",
" \n",
- " one = np.uint64(1) # Because np.uint64 + int = np.float64\n",
- " pulse_deltas = set()\n",
- "\n",
- " for pulse_id, (offset, count) in enumerate(zip(pulse_offsets, pulse_counts)):\n",
- " deltas = triggers['pulse'][offset+one:offset+count] - triggers['pulse'][offset:offset+count-one]\n",
- "\n",
- " if len(np.unique(deltas)) > 1:\n",
- " for delta in deltas:\n",
- " pulse_deltas.add(delta)\n",
- "\n",
- " if len(pulse_deltas) > 1:\n",
- " delta_str = ', '.join([str(x) for x in sorted(pulse_deltas)])\n",
- " warning(f'Different pulse lengths (PPT: {delta_str}) encountered within single trains, '\n",
- " f'separated pulse spectra may split up signals!')\n",
- " else:\n",
- " warning('Different pulse lengths encountered across trains, separation may be unstable!')"
+ " # Overwrite global pulse statistics computed before,\n",
+ " num_pulses = len(dc.train_ids)\n",
+ " pulse_counts[:] = 1\n",
+ " pulse_counts = pulse_counts.astype(np.int32)\n",
+ " pulse_offsets = np.arange(len(pulse_counts)).astype(np.int32)\n",
+ "\n",
+ " # Obtain minimal trace length.\n",
+ " min_trace_len = min([\n",
+ " dc[src, key].entry_shape[0]\n",
+ " for det_name in remi['detector'].keys()\n",
+ " for src, key in remi.get_detector_sourcekeys(det_name)\n",
+ " ])\n",
+ "\n",
+ " triggers['start'] = first_pulse_offset\n",
+ " triggers['stop'] = min_trace_len\n",
+ " triggers['offset'] = 0.0\n",
+ " triggers['pulse'] = -1\n",
+ " triggers['fel'] = False\n",
+ " triggers['ppl'] = False \n",
+ " \n",
+ "else:\n",
+ " with timing('find_triggers'):\n",
+ " psh.map(trigger_by_ppt, ppt_data)\n",
+ " \n",
+ " if (np.unique(triggers['pulse'][1:] - triggers['pulse'][:-1]) > 0).sum() > 1:\n",
+ " # There is more than one delta between pulse entries across all pulses. This is not\n",
+ " # necessarily a problem, as the pattern could simply have changed in between trains\n",
+ " # with each train being split properly.\n",
+ " # If there's more than one delta in a single train, this likely points to a mismatch\n",
+ " # of FEL and PPL repetition rate. This is most likely not intended.\n",
+ "\n",
+ " one = np.uint64(1) # Because np.uint64 + int = np.float64\n",
+ " pulse_deltas = set()\n",
+ "\n",
+ " for pulse_id, (offset, count) in enumerate(zip(pulse_offsets, pulse_counts)):\n",
+ " deltas = triggers['pulse'][offset+one:offset+count] - triggers['pulse'][offset:offset+count-one]\n",
+ "\n",
+ " if len(np.unique(deltas)) > 1:\n",
+ " for delta in deltas:\n",
+ " pulse_deltas.add(delta)\n",
+ "\n",
+ " if len(pulse_deltas) > 1:\n",
+ " delta_str = ', '.join([str(x) for x in sorted(pulse_deltas)])\n",
+ " warning(f'Different pulse lengths (PPT: {delta_str}) encountered within single trains, '\n",
+ " f'separated pulse spectra may split up signals!')\n",
+ " else:\n",
+ " warning('Different pulse lengths encountered across trains, separation may be unstable!')"
]
},
{
@@ -878,7 +905,7 @@
"max_num_hits = 0.0\n",
" \n",
"for det_name in remi['detector'].keys():\n",
- " agg_window = num_pulses // 1000\n",
+ " agg_window = num_pulses // min(1000, num_pulses)\n",
" \n",
" num_hits = np.isfinite(det_data[det_name]['hits']['x']).sum(axis=1)\n",
" num_hits = num_hits[:(len(num_hits) // agg_window) * agg_window]\n",
@@ -1127,6 +1154,7 @@
" \n",
" for det_name in remi['detector']:\n",
" cur_device_id = det_device_id.format(karabo_id=karabo_id, det_name=det_name.upper())\n",
+ " cur_max_hits = remi['detector'][det_name]['max_hits']\n",
" \n",
" cur_control_data = outp.create_control_source(cur_device_id)\n",
" # Manually manipulate the file here, still creates the index properly.\n",
@@ -1139,23 +1167,36 @@
" \n",
" if save_raw_triggers:\n",
" cur_fast_data.create_key('raw.triggers', triggers[pulse_mask],\n",
+ " maxshape=(None,) + triggers.shape[1:],\n",
" chunks=tuple(chunks_triggers), **dataset_kwargs)\n",
" \n",
" if save_raw_edges:\n",
" cur_fast_data.create_key('raw.edges', cur_data['edges'][pulse_mask],\n",
- " chunks=tuple(chunks_edges), **dataset_kwargs)\n",
+ " maxshape=(None,) + cur_data['edges'].shape[1:],\n",
+ " chunks=tuple(chunks_edges if chunks_edges[-1] <= cur_max_hits\n",
+ " else chunks_edges[:-1] + [cur_max_hits]),\n",
+ " **dataset_kwargs)\n",
" \n",
" if save_raw_amplitudes:\n",
" cur_fast_data.create_key('raw.amplitudes', cur_data['amplitudes'][pulse_mask],\n",
- " chunks=tuple(chunks_amplitudes), **dataset_kwargs)\n",
+ " maxshape=(None,) + cur_data['amplitudes'].shape[1:],\n",
+ " chunks=tuple(chunks_amplitudes if chunks_amplitudes[-1] <= cur_max_hits\n",
+ " else chunks_amplitudes[:-1] + [cur_max_hits]),\n",
+ " **dataset_kwargs)\n",
" \n",
" if save_rec_signals:\n",
" cur_fast_data.create_key('rec.signals', cur_data['signals'][pulse_mask],\n",
- " chunks=tuple(chunks_signals), **dataset_kwargs)\n",
+ " maxshape=(None,) + cur_data['signals'].shape[1:],\n",
+ " chunks=tuple(chunks_signals if chunks_signals[-1] <= cur_max_hits\n",
+ " else chunks_signals[:-1] + [cur_max_hits]),\n",
+ " **dataset_kwargs)\n",
" \n",
" if save_rec_hits:\n",
" cur_fast_data.create_key('rec.hits', cur_data['hits'][pulse_mask],\n",
- " chunks=tuple(chunks_hits), **dataset_kwargs)\n",
+ " maxshape=(None,) + hits.shape[1:],\n",
+ " chunks=tuple(chunks_hits if chunks_hits[-1] <= cur_max_hits\n",
+ " else chunks_hits[:-1] + [cur_max_hits]),\n",
+ " **dataset_kwargs)\n",
" \n",
" cur_fast_data.create_index(raw=pulse_counts[train_mask], rec=pulse_counts[train_mask])\n",
" \n",
diff --git a/notebooks/ePix100/Characterize_Darks_ePix100_NBC.ipynb b/notebooks/ePix100/Characterize_Darks_ePix100_NBC.ipynb
index 3d2da0b11e8dfbcd569c1a9385612fbdba185452..cfaf022060c1028f47fccfaa3c13931751f6aa77 100644
--- a/notebooks/ePix100/Characterize_Darks_ePix100_NBC.ipynb
+++ b/notebooks/ePix100/Characterize_Darks_ePix100_NBC.ipynb
@@ -27,14 +27,14 @@
"metadata": {},
"outputs": [],
"source": [
- "in_folder = '/gpfs/exfel/exp/HED/202330/p900338/raw' # input folder, required\n",
+ "in_folder = '/gpfs/exfel/exp/MID/202330/p900329/raw' # input folder, required\n",
"out_folder = '' # output folder, required\n",
"metadata_folder = '' # Directory containing calibration_metadata.yml when run by xfel-calibrate\n",
"sequence = 0 # sequence file to use\n",
- "run = 176 # which run to read data from, required\n",
+ "run = 106 # which run to read data from, required\n",
"\n",
"# Parameters for accessing the raw data.\n",
- "karabo_id = \"HED_IA1_EPX100-1\" # karabo karabo_id\n",
+ "karabo_id = \"MID_EXP_EPIX-1\" # karabo karabo_id\n",
"karabo_da = [\"EPIX01\"] # data aggregators\n",
"receiver_template = \"RECEIVER\" # detector receiver template for accessing raw data files\n",
"path_template = 'RAW-R{:04d}-{}-S{{:05d}}.h5' # the template to use to access data\n",
diff --git a/notebooks/ePix100/Correction_ePix100_NBC.ipynb b/notebooks/ePix100/Correction_ePix100_NBC.ipynb
index 9585d4eb66c9f7ff5d876bef40992ec95d9e3120..89fa139226537207b3b447893c3a26c57333ccb5 100644
--- a/notebooks/ePix100/Correction_ePix100_NBC.ipynb
+++ b/notebooks/ePix100/Correction_ePix100_NBC.ipynb
@@ -24,15 +24,15 @@
"metadata": {},
"outputs": [],
"source": [
- "in_folder = \"/gpfs/exfel/exp/MID/202301/p003346/raw\" # input folder, required\n",
+ "in_folder = \"/gpfs/exfel/exp/HED/202102/p002739/raw\" # input folder, required\n",
"out_folder = \"\" # output folder, required\n",
"metadata_folder = \"\" # Directory containing calibration_metadata.yml when run by xfel-calibrate\n",
"sequences = [-1] # sequences to correct, set to -1 for all, range allowed\n",
"sequences_per_node = 1 # number of sequence files per cluster node if run as slurm job, set to 0 to not run SLURM parallel\n",
- "run = 55 # which run to read data from, required\n",
+ "run = 38 # which run to read data from, required\n",
"\n",
"# Parameters for accessing the raw data.\n",
- "karabo_id = \"MID_EXP_EPIX-1\" # karabo karabo_id\n",
+ "karabo_id = \"HED_IA1_EPX100-1\" # karabo karabo_id\n",
"karabo_da = \"EPIX01\" # data aggregators\n",
"db_module = \"\" # module id in the database\n",
"receiver_template = \"RECEIVER\" # detector receiver template for accessing raw data files\n",
@@ -612,19 +612,6 @@
" # Create count/first datasets at INDEX source.\n",
" outp_source.create_index(data=image_counts)\n",
"\n",
- " # Store uncorrected RAW image datasets for the corrected trains.\n",
- "\n",
- " data_raw_fields = [ # /data/\n",
- " \"ambTemp\", \"analogCurr\", \"analogInputVolt\", \"backTemp\",\n",
- " \"digitalInputVolt\", \"guardCurr\", \"relHumidity\", \"digitalCurr\"\n",
- " ]\n",
- " for field in data_raw_fields:\n",
- " field_arr = seq_dc[instrument_src, f\"data.{field}\"].ndarray()\n",
- "\n",
- " outp_source.create_key(\n",
- " f\"data.{field}\", data=field_arr,\n",
- " chunks=(chunk_size_idim, *field_arr.shape[1:]))\n",
- "\n",
" image_raw_fields = [ # /data/image/\n",
" \"binning\", \"bitsPerPixel\", \"dimTypes\", \"dims\",\n",
" \"encoding\", \"flipX\", \"flipY\", \"roiOffsets\", \"rotation\",\n",
@@ -641,6 +628,11 @@
" \"data.image.pixels\", data=data, chunks=dataset_chunk)\n",
" outp_source.create_key(\n",
" \"data.trainId\", data=seq_dc.train_ids, chunks=min(50, len(seq_dc.train_ids)))\n",
+ " \n",
+ " if np.isin('data.pulseId', list(seq_dc[instrument_src].keys())): # some runs are missing 'data.pulseId'\n",
+ " outp_source.create_key(\n",
+ " \"data.pulseId\", data=list(seq_dc[instrument_src]['data.pulseId'].ndarray().squeeze()), chunks=min(50, len(seq_dc.train_ids)))\n",
+ " \n",
" if pattern_classification:\n",
" # Add main corrected `data.image.pixels` dataset and store corrected data.\n",
" outp_source.create_key(\n",
diff --git a/src/cal_tools/epix100/epix100lib.py b/src/cal_tools/epix100/epix100lib.py
index 9cea56634612b1cc3ab38e9a49ba6210ae05cb64..d2c71e1b912b5fe5137131f21b4ad38f3298edff 100644
--- a/src/cal_tools/epix100/epix100lib.py
+++ b/src/cal_tools/epix100/epix100lib.py
@@ -23,12 +23,24 @@ class epix100Ctrl():
def get_temprature(self):
"""Get temperature value from CONTROL.
- Temprature is stored in Celsius/100 units.
- Therefore, we are dividing by 100 and
- there is an absolute tolerance of 100.
- atol=100 is a 1 degree variation tolerance.
+ atol is degree variation tolerance.
"""
- # data.backTemp shape evolved from (n_trains,) to (n_trains, 1)
- return self.run_dc[
- self.instrument_src, 'data.backTemp'].as_single_value(
- reduce_by='mean', atol=100).item() / 100
+ # old receiver device configuration
+ # temperature was stored in:
+ # source: 'MID_EXP_EPIX-1/DET/RECEIVER:daqOutput'
+ # key: 'data.backTemp'
+ if 'data.backTemp' in self.run_dc[self.instrument_src]:
+ # using `item()` because data.backTemp shape evolved from (n_trains,) to (n_trains, 1)
+ # atol = 100 because temperature was in C/100
+ return self.run_dc[
+ self.instrument_src, 'data.backTemp'].as_single_value(
+ reduce_by='mean', atol=100).item() / 100
+
+ # new (2023) receiver device configuration
+ # temperature is stored in:
+ # source: 'MID_EXP_EPIX-1/DET/RECEIVER'
+ # key: 'slowdata.backTemp.value'
+ else:
+ return self.run_dc[
+ self.instrument_src.split(':daqOutput')[0], 'slowdata.backTemp.value'].as_single_value(
+ reduce_by='mean', atol=1)
\ No newline at end of file
diff --git a/webservice/templates/last_characterizations.html b/webservice/templates/last_characterizations.html
index 1a9b893740aabbe1a7ffe80f26668a9e9276e18e..d874bff9d53767358c729154335d0f2e5c92d396 100644
--- a/webservice/templates/last_characterizations.html
+++ b/webservice/templates/last_characterizations.html
@@ -4,7 +4,12 @@
<h3>{{ instrument }}</h3>
<dl>
<dt>Requested:</dt><dd>{{ data['requested'] }}</dd>
- <dt>Check in DB:</dt><dd><a href="https://in.xfel.eu/calibration/admin/calibration_constant_version?model_name=calibration_constant_version&utf8=%E2%9C%93&f%5Bphysical_device%5D%5B02524%5D%5Bo%5D=like&f%5Bphysical_device%5D%5B02524%5D%5Bv%5D={{ data['device_type'] }}&f%5Bcalibration_constant%5D%5B02697%5D%5Bo%5D=like&f%5Bcalibration_constant%5D%5B02697%5D%5Bv%5D=Offset&query=" target="_blank"> Open in calDB </a></dd>
+ <dt>Check in DB:</dt><dd>
+ {% for pdf in data['pdfs'] %}
+ <a href="https://in.xfel.eu/calibration/reports/by_file/{{ pdf[1] }}" target="_blank">Open in calDB</a>
+ {% endfor %}
+
+ </dd>
<dt>Output path:</dt><dd>{{ data['out_path'] }}</dd>
<dt>Input path:</dt><dd>{{ data['in_path'] }}</dd>
<dt>Input runs:</dt><dd>{{ data['runs'] }}</dd>