"""Generate 5-to-15 synthetic radar sequences at the paper's 100x100 size.""" from pathlib import Path import numpy as np import yaml ROOT = Path(__file__).resolve().parents[1] def make_split(path, count, config, seed): rng = np.random.default_rng(seed) data = config["data"] total = int(data["input_frames"]) + int(data["output_frames"]) height, width = int(data["height"]), int(data["width"]) y, x = np.mgrid[-1:1:complex(height), -1:1:complex(width)].astype(np.float32) sequences = np.empty((count, total, 1, height, width), np.float32) for sample in range(count): centers = rng.uniform(-0.55, 0.55, (3, 2)) velocities = rng.uniform(-0.035, 0.035, (3, 2)) amplitudes = rng.uniform(0.25, 0.95, 3) scales = rng.uniform(0.10, 0.28, 3) for step in range(total): field = np.zeros((height, width), np.float32) for storm in range(3): cy, cx = centers[storm] + velocities[storm] * step distance = ((x - cx) ** 2 + (y - cy) ** 2) / (2 * scales[storm] ** 2) field += amplitudes[storm] * np.exp(-distance) sequences[sample, step, 0] = np.clip(field + rng.normal(0, 0.01, field.shape), 0, 1) split = int(data["input_frames"]) np.savez_compressed(path, format_version=np.asarray(data["format_version"]), data_source=np.asarray("synthetic_hko_radar_like"), inputs=sequences[:, :split], targets=sequences[:, split:]) def main(): config = yaml.safe_load((ROOT / "conf/config.yaml").read_text()) output = ROOT / config["data"]["root"] output.mkdir(parents=True, exist_ok=True) for offset, (filename, count) in enumerate((("train.npz", config["data"]["train_samples"]), ("test.npz", config["data"]["test_samples"]))): target = output / filename if not target.exists(): make_split(target, int(count), config, int(config["seed"]) + offset) print(f"generated={target.relative_to(ROOT)} input=5x1x100x100 target=15x1x100x100") if __name__ == "__main__": main()