106 lines
3.9 KiB
Python
106 lines
3.9 KiB
Python
import os, re, json, h5py
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from pathlib import Path
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from datetime import datetime, timedelta
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from tqdm import tqdm
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DATA_ROOTS = [Path("/mnt/kingston"), Path("/mnt/data_sdb1")]
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POSITIONS_CSV = Path("/mnt/kingston/Copie de SETE_AUV_DARFV4-Copier(1).csv")
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OUTPUT_INDEX = Path("/mnt/kingston/seismic_webapp/data/index.json")
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SAMPLE_RATE = 200
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def load_pos():
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positions = {}
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if not POSITIONS_CSV.exists(): return {}
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with open(POSITIONS_CSV, 'r', encoding='utf-8', errors='replace') as f:
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lines = f.readlines()
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if len(lines) < 5: return {}
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headers = lines[3].strip().split(',')
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try:
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ni = headers.index('NodeCode')
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ei = headers.index('Aslaid Easting') if 'Aslaid Easting' in headers else headers.index('Preplot Easting')
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oi = headers.index('Aslaid Northing') if 'Aslaid Northing' in headers else headers.index('Preplot Northing')
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except: return {}
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for line in lines[4:]:
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parts = line.strip().split(',')
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try:
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nid = parts[ni].strip()
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positions[nid] = {
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'easting': float(parts[ei]),
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'northing': float(parts[oi]),
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'depth': float(parts[headers.index('Aslaid Depth')]) if 'Aslaid Depth' in headers else 0.0
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}
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except: continue
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return positions
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def scan():
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pos = load_pos()
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nodes = {}
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all_dates = set()
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file_count = 0
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print("🔍 Scanning ONLY 'data' H5 files (ignoring 'aux')...")
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all_h5_files = []
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for root in DATA_ROOTS:
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all_h5_files.extend(list(root.rglob("*.h5")))
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for h5_path in tqdm(all_h5_files):
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# FILTRE : Uniquement les fichiers contenant "data"
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if "_data_" not in h5_path.name.lower():
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continue
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try:
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match = re.search(r'auto_(\d+)_(\d{6})_b(\d+)_.*?_(\d{10})\.h5$', h5_path.name)
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if not match: continue
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julian_day = int(match.group(1))
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time_str = match.group(2)
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node_id = match.group(3)
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date_ref = datetime(2020, 1, 1) + timedelta(days=julian_day - 1)
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date_str = date_ref.strftime('%Y-%m-%d')
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h, m, s = int(time_str[:2]), int(time_str[2:4]), int(time_str[4:6])
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actual_start_ts = int(datetime(2020, 1, 1).timestamp() + (julian_day - 1) * 86400 + h * 3600 + m * 60 + s)
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with h5py.File(h5_path, 'r') as f:
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if 'adc_values' not in f: continue
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duration = f['adc_values'].shape[0] / SAMPLE_RATE
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actual_end_ts = actual_start_ts + duration
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all_dates.add(date_str)
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if node_id not in nodes:
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nodes[node_id] = {
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'id': node_id,
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'position': pos.get(node_id),
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'files': []
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}
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# On extrait le canal du nom de fichier pour un matching plus précis
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channel_match = re.search(r'_ch(\d+)_', h5_path.name)
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channel = f"ch{channel_match.group(1)}" if channel_match else "ch0"
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nodes[node_id]['files'].append({
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'path': str(h5_path),
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'start': actual_start_ts,
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'end': actual_end_ts,
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'julian': julian_day,
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'channel': channel # Canal spécifique au fichier
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})
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file_count += 1
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except: continue
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result = {
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'generated_at': datetime.now().isoformat(),
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'sample_rate_hz': SAMPLE_RATE,
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'nodes': nodes,
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'dates': sorted(list(all_dates))
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}
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with open(OUTPUT_INDEX, 'w') as f:
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json.dump(result, f, indent=2)
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print(f"✅ Index updated: {file_count} 'data' files, {len(nodes)} nodes.")
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if __name__ == '__main__': scan()
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