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Lean: update Semantics modules, add new numerics/physics data files Hardware: update FPGA bitstreams (tangnano9k_uart_loopback) Infra: k3s-flake tests, netcup-vps configuration, VCN compute substrate Docs: ARCHITECTURE, specs, citation updates
99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
#!/usr/bin/env python3
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"""
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bulk_process_hepdata.py — Process all downloaded HEPData through the RRC pipeline
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This script:
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1. Scans all CSV files in /tmp/hepdata-bulk
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2. Extracts numerical data points
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3. Builds event matrices for spectral analysis
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4. Outputs JSON for Lean pipeline ingestion
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Usage:
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python3 bulk_process_hepData.py > all_physics_data.json
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"""
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import csv
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import json
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import os
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import sys
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from pathlib import Path
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def extract_numerical_data(filepath):
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"""Extract all numerical values from a CSV file."""
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data_points = []
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try:
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with open(filepath, 'r') as f:
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for line in f:
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line = line.strip()
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if not line or line.startswith('#'):
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continue
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parts = line.split(',')
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values = []
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for p in parts:
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try:
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v = float(p)
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values.append(v)
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except:
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pass
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if len(values) >= 2:
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data_points.append(values)
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except:
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pass
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return data_points
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def process_record(record_dir):
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"""Process all CSV files in a record directory."""
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record_name = os.path.basename(record_dir)
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all_data = []
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for csv_file in sorted(Path(record_dir).glob("*.csv")):
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data = extract_numerical_data(str(csv_file))
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if data:
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all_data.append({
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"file": csv_file.name,
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"points": data[:100] # Limit to 100 points per file
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})
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return {
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"record": record_name,
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"tables": len(all_data),
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"data": all_data
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}
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def main():
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bulk_dir = Path("/tmp/hepdata-bulk")
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if not bulk_dir.exists():
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print("Error: /tmp/hepdata-bulk not found", file=sys.stderr)
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sys.exit(1)
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results = []
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total_points = 0
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for record_dir in sorted(bulk_dir.iterdir()):
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if record_dir.is_dir() and record_dir.name.startswith("HEPData-"):
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record_data = process_record(record_dir)
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results.append(record_data)
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# Count points
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for table in record_data["data"]:
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total_points += len(table["points"])
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output = {
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"source": "HEPData bulk download",
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"records": len(results),
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"total_data_points": total_points,
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"coverage": {
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"B_physics": sum(1 for r in results if any(x in r["record"] for x in ["ins14", "ins13", "ins15", "ins16", "ins17"])),
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"Z_Higgs": sum(1 for r in results if any(x in r["record"] for x in ["ins11", "ins12", "ins134", "ins178", "ins167"])),
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"Top_quark": sum(1 for r in results if any(x in r["record"] for x in ["ins160", "ins179", "ins136", "ins146", "ins315"])),
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"Diboson": sum(1 for r in results if any(x in r["record"] for x in ["ins89", "ins218", "ins292", "ins276", "ins185", "ins119"])),
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"eplus_eminus": sum(1 for r in results if any(x in r["record"] for x in ["ins21", "ins26", "ins177", "ins100", "ins99", "ins124"]))
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},
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"records": results[:50] # Limit output
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}
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print(json.dumps(output, indent=2))
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if __name__ == "__main__":
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main()
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