First versions of 16M reduction scripts

2026-05-18 16:37:25 +02:00
parent 2b91c656f2
commit 7ff49899eb
3 changed files with 317 additions and 0 deletions
@@ -0,0 +1,87 @@
+import numpy as np
+import json, os, glob, yaml, time
+import argparse, pickle, h5py
+from pathlib import Path
+from sfdata import SFDataFile, SFDataFiles
+
+from alvra_tools.load_data import *
+from alvra_tools.channels import *
+from alvra_tools.utils import *
+
+
+#EventChan = 'SAR-CVME-TIFALL4:EvtSet'
+Detector  = 'JF06T32V07'
+chIzero110  = 'SAROP11-PBPS110:INTENSITY'
+chIzero122  = 'SAROP11-PBPS122:INTENSITY'
+chIzeroAPD  = 'SARES11-GES1:PR1_CH1_VAL_GET'
+
+#roi = [900, 1300, 850, 1250]    
+roi = [800, 1400, 750, 1350]    
+
+def get_acq_from_pth(path):
+    import re
+    return re.search(r"acq(\d+)", path).group(1).zfill(4)
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--input", "-i", required=True)
+args = parser.parse_args()
+
+filename = Path(args.input)
+output_file = Path(str(filename).replace("/raw/", "/res/processed/").replace(".h5",".corr_PROCESSED.h5") )
+output_file.parent.mkdir(parents=True, exist_ok=True, mode=0o775)
+
+acq = get_acq_from_pth(args.input)
+acq_meta_pth = Path(str(filename).replace("/data/ac", "/meta/ac")).parent
+acq_info_pth = acq_meta_pth.joinpath(f"acq{acq}.json")
+
+with open(acq_info_pth, "r") as f:
+    acq_parameters = json.load(f)
+    rbk_value = acq_parameters.get("scan_info", {}).get("scan_readbacks", 0)
+    #xlabel = acq_parameters.get("scan_info", {}).get("name", None)
+    #units = acq_parameters.get("scan_info", {}).get("units", None)
+
+file2load = args.input.replace('BSDATA', "*")
+#print ('sleeping 30 seconds, ROI = {}'.format(roi))
+#time.sleep(30) 
+
+#file2load = args.input.replace('JF06T32V07', "*")
+
+with SFDataFiles(file2load) as step:
+    subset = step[Detector, chIzero110, chIzero122, chIzeroAPD]
+    subset.drop_missing()
+
+    JF    = crop_roi(subset[Detector].data, roi)
+    JF_flat = JF.reshape(JF.shape[0], -1)
+    Izero110 = subset[chIzero110].data
+    Izero122 = subset[chIzero122].data
+    IzeroAPD = subset[chIzeroAPD].data
+
+    before = len(Izero110)
+
+    q_low  = np.percentile(Izero110, 5)
+    q_high = np.percentile(Izero110, 95)
+    outliers = (Izero110 < q_low) | (Izero110 > q_high)
+
+    JF_flat = JF_flat[~outliers]
+    Izero110 = Izero110[~outliers]
+    Izero122 = Izero122[~outliers]
+    IzeroAPD = IzeroAPD[~outliers]
+
+    print ("Survived {} out of {} shots".format(len(Izero110), before))
+
+    JF_int = np.sum(JF_flat, axis=1)
+
+with h5py.File(output_file, 'w') as f:
+    gr1 = f.create_group("data")
+    gr1['Izero110'] = Izero110
+    gr1['Izero122'] = Izero122
+    gr1['IzeroAPD'] = IzeroAPD
+    gr1['Int_JF'] = JF_int 
+    
+    gr2 = f.create_group("meta")
+    gr2["roi"] = roi
+
+
+
+
+