Branch sequential xtc pipeline

scripts/production/inference_xtc_serial_pipeline/bash_launcher.py

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+#!/usr/bin/env python3
+"""
+bash_launcher.py
+Launches routine_detection_v3.sh with specified arguments.
+Can be run from CDS to orchestrate the complete XTC workflow.
+
+USAGE:
+    python bash_launcher.py [OPTIONS]
+    python bash_launcher.py --help
+
+EXAMPLES:
+    # Run with defaults
+    python bash_launcher.py
+
+    # Run with custom parameters
+    python bash_launcher.py --run_number=61 --exp_number=mfx101346325 --max_events=80000
+
+    # Run with specific user
+    python bash_launcher.py --user=pmonteil --run_number=100
+"""
+
+import argparse
+import subprocess
+import sys
+from pathlib import Path
+
+
+def eprint(msg):
+    """Write message to stderr."""
+    sys.stderr.write(str(msg) + "\n")
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Launch coyote XTC detection routine via bash",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=__doc__
+    )
+
+    parser.add_argument(
+        "--user",
+        default="pmonteil",
+        help="Username for SSH to SDF (default: pmonteil)"
+    )
+    parser.add_argument(
+        "--run_number",
+        type=int,
+        default=61,
+        help="LCLS run number to process (default: 61)"
+    )
+    parser.add_argument(
+        "--exp_number",
+        default="mfx101346325",
+        help="Experiment identifier (default: mfx101346325)"
+    )
+    parser.add_argument(
+        "--save_normalized",
+        type=int,
+        choices=[0, 1],
+        default=1,
+        help="Save normalized images (1=yes, 0=no, default: 1)"
+    )
+    parser.add_argument(
+        "--max_events",
+        type=int,
+        default=10000,
+        help="Maximum events to process (default: 10000)"
+    )
+    parser.add_argument(
+        "--use_normalized",
+        type=int,
+        choices=[0, 1],
+        default=1,
+        help="Use normalized images for inference (1=yes, 0=no, default: 1)"
+    )
+    parser.add_argument(
+        "--camera_name",
+        default="inline_alvium",
+        help="Psana detector name for the inline camera (default: inline_alvium)"
+    )
+    parser.add_argument(
+        "--dry_run",
+        action="store_true",
+        help="Print command without executing"
+    )
+
+    args = parser.parse_args()
+
+    # Get the script path (should be in same directory)
+    script_path = Path(__file__).parent / "routine_detection_v3.sh"
+
+    if not script_path.exists():
+        eprint("[ERROR] Script not found: {}".format(script_path))
+        sys.exit(1)
+
+    # Build command
+    cmd = [
+        "bash",
+        str(script_path),
+        "--user={}".format(args.user),
+        "RUN_NUMBER={}".format(args.run_number),
+        "EXP_NUMBER={}".format(args.exp_number),
+        "SAVE_NORMALIZED={}".format(args.save_normalized),
+        "MAX_EVENTS={}".format(args.max_events),
+        "USE_NORMALIZED={}".format(args.use_normalized),
+        "CAMERA_NAME={}".format(args.camera_name),
+    ]
+
+    print("[INFO] ============================================")
+    print("[INFO] COYOTE XTC DETECTION LAUNCHER")
+    print("[INFO] ============================================")
+    print("[INFO] User: {}".format(args.user))
+    print("[INFO] Run Number: {}".format(args.run_number))
+    print("[INFO] Experiment: {}".format(args.exp_number))
+    print("[INFO] Save Normalized: {}".format(args.save_normalized))
+    print("[INFO] Max Events: {}".format(args.max_events))
+    print("[INFO] Use Normalized: {}".format(args.use_normalized))
+    print("[INFO] Camera Name: {}".format(args.camera_name))
+    print("[INFO] ============================================")
+    print()
+
+    print("[INFO] Command: {}".format(" ".join(cmd)))
+    print()
+
+    if args.dry_run:
+        print("[INFO] DRY RUN MODE - Command not executed")
+        return 0
+
+    try:
+        result = subprocess.run(cmd, check=False)
+        return result.returncode
+    except KeyboardInterrupt:
+        eprint("\n[INFO] Interrupted by user")
+        return 130
+    except Exception as e:
+        eprint("[ERROR] Failed to execute command: {}".format(e))
+        return 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/production/inference_xtc_serial_pipeline/export_xtc_normalized_args.py

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+# Must source this env before running:
+# source /sdf/group/lcls/ds/ana/sw/conda2/manage/bin/psconda.sh
+
+import os
+import sys
+import csv
+from pathlib import Path
+import cv2
+import numpy as np
+from psana import DataSource
+
+
+def parse_bool(s: str) -> bool:
+    """Accept 1/0, true/false, yes/no (case-insensitive)."""
+    v = s.strip().lower()
+    if v in ("1", "true", "t", "yes", "y", "on"):
+        return True
+    if v in ("0", "false", "f", "no", "n", "off"):
+        return False
+    raise ValueError(f"Could not parse boolean from: {s!r}")
+
+
+# -------------------------
+# Argument parsing
+# -------------------------
+DEFAULT_RUN = 61
+DEFAULT_EXP = "mfx  "
+DEFAULT_SAVE_NORM = True
+DEFAULT_MAX_EVENTS = 10000
+DEFAULT_CAMERA = "inline_alvium"
+
+argc = len(sys.argv)
+
+if argc == 1:
+    run_number = DEFAULT_RUN
+    exp = DEFAULT_EXP
+    SAVE_NORMALIZED = DEFAULT_SAVE_NORM
+    max_events = DEFAULT_MAX_EVENTS
+    camera_name = DEFAULT_CAMERA
+elif argc in (2, 3, 4, 5, 6):
+    run_number = int(sys.argv[1])
+    exp = sys.argv[2] if argc >= 3 else DEFAULT_EXP
+    SAVE_NORMALIZED = parse_bool(sys.argv[3]) if argc >= 4 else DEFAULT_SAVE_NORM
+    max_events = int(sys.argv[4]) if argc >= 5 else DEFAULT_MAX_EVENTS
+    camera_name = sys.argv[5] if argc >= 6 else DEFAULT_CAMERA
+else:
+    print(
+        "Usage:\n"
+        "  python export_xtc_normalized.py\n"
+        "  python export_xtc_normalized.py <run_number>\n"
+        "  python export_xtc_normalized.py <run_number> <exp_number>\n"
+        "  python export_xtc_normalized.py <run_number> <exp_number> <save_normalized>\n"
+        "  python export_xtc_normalized.py <run_number> <exp_number> <save_normalized> <max_events>\n"
+        "  python export_xtc_normalized.py <run_number> <exp_number> <save_normalized> <max_events> <camera_name>\n"
+    )
+    sys.exit(1)
+
+print(f"[CONFIG] exp={exp} run={run_number} save_normalized={SAVE_NORMALIZED} max_events={max_events} camera_name={camera_name}")
+
+# -------------------------
+# psana setup
+# -------------------------
+#print(run_number, exp, max_events, SAVE_NORMALIZED)
+ds = DataSource(exp=exp, run=[run_number], max_events=max_events)
+
+myrun = next(ds.runs())
+
+cam = myrun.Detector(camera_name)
+xtraj = myrun.Detector("XTRAJ")
+ytraj = myrun.Detector("YTRAJ")
+
+# -------------------------
+# Output dirs
+# -------------------------
+out_dir = Path(f"run_{run_number}_png")
+out_dir.mkdir(exist_ok=True)
+
+norm_dir = Path(f"run_{run_number}_png_norm")
+if SAVE_NORMALIZED:
+    norm_dir.mkdir(exist_ok=True)
+
+# -------------------------
+# CSV (manual open/close — SAME as second script)
+# -------------------------
+out_dir_csv = Path("results_csv")
+out_dir_csv.mkdir(exist_ok=True)
+csv_path = out_dir_csv / "event_data.csv"
+csv_file = open(csv_path, "w", newline="")
+writer = csv.writer(csv_file)
+writer.writerow(["event_id", "png_file", "xtraj", "ytraj"])
+
+# -------------------------
+# Event loop
+# -------------------------
+eid = 0
+
+for evt in myrun.events():
+    if eid % 3 == 0 :
+        img = cam.raw.value(evt)
+        if img is None:
+            eid += 1
+            continue
+
+        x = xtraj(evt)
+        y = ytraj(evt)
+
+        # Save raw
+        fname = out_dir / f"event_{eid:06d}.png"
+        #cv2.imwrite(str(fname), img)
+
+        # Save normalized
+        if SAVE_NORMALIZED:
+            img8 = cv2.normalize(img, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)
+            fname_norm = norm_dir / f"event_{eid:06d}.png"
+            cv2.imwrite(str(fname_norm), img8)
+
+        # CSV entry (same as your second script)
+        writer.writerow([eid, fname.name, x[eid], y[eid]])
+
+        print(f"[EVENT {eid}] Saved {fname.name} | X={x[eid]}, Y={y[eid]}")
+
+    eid += 1
+
+csv_file.close()
+
+print(f"\n[INFO] Saved {eid} raw images → {out_dir}")
+if SAVE_NORMALIZED:
+    print(f"[INFO] Saved {eid} normalized images → {norm_dir}")
+print(f"[INFO] CSV saved → {csv_path}")