Added new test dataset.

pes_to_spec/test/offline_analysis.py

@@ -116,20 +116,26 @@ def main():
     """
     Main entry point. Reads some data, trains and predicts.
     """
-    run_dir = "/gpfs/exfel/exp/SA3/202121/p002935/raw"
-    run_id = "r0015"
+    run_dir = "/gpfs/exfel/exp/SA3/202121/p002935/raw/r0015"
+    run_dir = "/gpfs/exfel/exp/SQS/202201/p002828/raw/r0206"
     # get run
-    run = RunDirectory(f"{run_dir}/{run_id}")
+    run = RunDirectory(run_dir)
 
     # get train IDs and match them, so we are sure to have information from all needed sources
     # in this example, there is an offset of -2 in the SPEC train ID, so correct for it
     spec_offset = -2
-    spec_tid = spec_offset + run['SA3_XTD10_SPECT/MDL/FEL_BEAM_SPECTROMETER_SQS1:output',
-                                 "data.trainId"].ndarray()
-    pes_tid = run['SA3_XTD10_PES/ADC/1:network',
-                  "digitizers.trainId"].ndarray()
-    xgm_tid = run['SA3_XTD10_XGM/XGM/DOOCS:output',
-                  "data.trainId"].ndarray()
+    spec_name = 'SA3_XTD10_SPECT/MDL/FEL_BEAM_SPECTROMETER_SQS1:output'
+    pes_name = 'SA3_XTD10_PES/ADC/1:network'
+    xgm_name = 'SA3_XTD10_XGM/XGM/DOOCS:output'
+
+    spec_offset = 0
+    spec_name = 'SA3_XTD10_SPECT/MDL/SPECTROMETER_SQS_NAVITAR:output'
+    pes_name = 'SA3_XTD10_PES/ADC/1:network'
+    xgm_name = 'SA3_XTD10_XGM/XGM/DOOCS:output'
+
+    spec_tid = spec_offset + run[spec_name, "data.trainId"].ndarray()
+    pes_tid = run[pes_name, "digitizers.trainId"].ndarray()
+    xgm_tid = run[xgm_name, "data.trainId"].ndarray()
     # these are the train ID intersection
     # this could have been done by a select call in the RunDirectory, but it would not correct for the spec_offset
     tids = matching_ids(spec_tid, pes_tid, xgm_tid)
@@ -137,19 +143,15 @@ def main():
     test_tids = tids[-10:]
 
     # read the spec photon energy and intensity
-    spec_raw_pe = run['SA3_XTD10_SPECT/MDL/FEL_BEAM_SPECTROMETER_SQS1:output',
-                      "data.photonEnergy"].select_trains(by_id[tids - spec_offset]).ndarray()
-    spec_raw_int = run['SA3_XTD10_SPECT/MDL/FEL_BEAM_SPECTROMETER_SQS1:output',
-                       "data.intensityDistribution"].select_trains(by_id[tids - spec_offset]).ndarray()
+    spec_raw_pe = run[spec_name, "data.photonEnergy"].select_trains(by_id[tids - spec_offset]).ndarray()
+    spec_raw_int = run[spec_name, "data.intensityDistribution"].select_trains(by_id[tids - spec_offset]).ndarray()
 
     # read the PES data for each channel
     channels = [f"channel_{i}_{l}"
                 for i, l in product(range(1, 5), ["A", "B", "C", "D"])]
-    pes_raw = {ch: run['SA3_XTD10_PES/ADC/1:network',
-                   f"digitizers.{ch}.raw.samples"].select_trains(by_id[tids]).ndarray()
+    pes_raw = {ch: run[pes_name, f"digitizers.{ch}.raw.samples"].select_trains(by_id[tids]).ndarray()
                for ch in channels}
-    pes_raw_t = {ch: run['SA3_XTD10_PES/ADC/1:network',
-                   f"digitizers.{ch}.raw.samples"].select_trains(by_id[test_tids]).ndarray()
+    pes_raw_t = {ch: run[pes_name, f"digitizers.{ch}.raw.samples"].select_trains(by_id[test_tids]).ndarray()
                for ch in channels}
 
     # read the XGM information