"""Generate normalized precipitation sequences at the paper's 288x288 resolution."""

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"]
    inputs, outputs = 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, inputs + outputs, height, width), np.float32)
    for sample in range(count):
        centers = rng.uniform(-0.45, 0.45, (2, 2))
        velocity = rng.uniform(-0.025, 0.025, (2, 2))
        amplitudes = rng.uniform(0.35, 1.0, 2)
        widths = rng.uniform(0.10, 0.28, 2)
        for step in range(inputs + outputs):
            field = np.zeros((height, width), np.float32)
            for storm in range(2):
                cy, cx = centers[storm] + velocity[storm] * step
                radius = ((x - cx) ** 2 + (y - cy) ** 2) / (2 * widths[storm] ** 2)
                field += amplitudes[storm] * np.exp(-radius)
            field += rng.normal(0, 0.01, field.shape)
            sequences[sample, step] = np.clip(field, 0, 1)
    np.savez_compressed(
        path,
        format_version=np.asarray(data["format_version"]),
        data_source=np.asarray("synthetic_knmi_like"),
        inputs=sequences[:, :inputs],
        targets=sequences[:, inputs:],
    )


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", int(config["data"]["train_samples"])),
        ("test.npz", int(config["data"]["test_samples"])),
    )):
        target = output / filename
        if not target.exists():
            make_split(target, count, config, int(config["seed"]) + offset)
        print(f"generated={target.relative_to(ROOT)} samples={count} shape=({config['data']['height']},{config['data']['width']})")


if __name__ == "__main__":
    main()