| """Read one extracted NumPy RF episode; returned RSS values are float32 dBm.""" |
| import argparse |
| import json |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
|
|
| def load_rss(directory, frames=slice(None)): |
| directory = Path(directory) |
| metadata = json.loads((directory / "metadata.json").read_text()) |
| stored = np.load(directory / metadata["training_file"], mmap_mode="r", allow_pickle=False) |
| selected = stored[frames] |
| quantization_file = metadata.get("quantization_file") |
| if quantization_file: |
| encoding = json.loads((directory / quantization_file).read_text()) |
| if encoding["schema"] != "uint16_centi_dbm_v1" or stored.dtype != np.dtype("uint16"): |
| raise ValueError("Unsupported RSS encoding") |
| values = (selected.astype(np.int32) - encoding["integer_offset"]).astype(np.float32) |
| values *= np.float32(encoding["step_db"]) |
| values[selected == encoding["invalid_code"]] = np.nan |
| else: |
| if stored.dtype != np.dtype("float32"): |
| raise ValueError("Expected direct float32 RSS") |
| values = selected |
| return np.ascontiguousarray(values) |
|
|
|
|
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("directory", type=Path) |
| parser.add_argument("--frame", type=int, default=0) |
| args = parser.parse_args() |
| rss = load_rss(args.directory, args.frame) |
| valid = rss[np.isfinite(rss)] |
| print(json.dumps(dict(unit="dBm", shape=list(rss.shape), dtype=str(rss.dtype), |
| valid_voxels=int(valid.size), |
| min_dbm=float(valid.min()) if valid.size else None, |
| max_dbm=float(valid.max()) if valid.size else None))) |
|
|
