File size: 2,809 Bytes
b20ca9c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | """Create structurally realistic full-grid samples with irregular HadEX-style masks."""
from pathlib import Path
import json
import numpy as np
INDICES = np.array(["TX90p", "TN90p", "TX10p", "TN10p"])
H, W = 144, 192
def europe_mask(lat, lon):
yy, xx = np.meshgrid(lat, lon, indexing="ij")
broad = (yy >= 30) & (yy <= 72) & (xx >= -25) & (xx <= 45)
# A coarse geographic silhouette keeps the scientific global-grid contract.
atlantic_cut = (xx < -10) & (yy < 44)
southeast_cut = (xx > 30) & (yy < 40)
north_cut = (yy > 68) & ((xx < 5) | (xx > 30))
return (broad & ~atlantic_cut & ~southeast_cut & ~north_cut).astype(np.float32)
def main():
rng = np.random.default_rng(42)
root = Path(__file__).resolve().parents[1]
output = root / "data"
output.mkdir(exist_ok=True)
lat = np.linspace(-89.375, 89.375, H, dtype=np.float32)
lon = np.linspace(-179.0625, 179.0625, W, dtype=np.float32)
land = europe_mask(lat, lon)
yy, xx = np.meshgrid(lat, lon, indexing="ij")
n = 8
target = np.zeros((n, 1, H, W), dtype=np.float32)
valid = np.zeros_like(target)
index_ids = np.arange(n, dtype=np.int64) % 4
for sample in range(n):
phase = 0.55 * sample
field = 50 + 21 * np.sin(np.deg2rad(2.3 * xx) + phase)
field += 16 * np.cos(np.deg2rad(3.2 * yy) - 0.4 * phase)
field += 5 * np.sin(np.deg2rad(xx + yy) * 4 + phase)
field += rng.normal(0, 1.2, (H, W))
if index_ids[sample] >= 2:
field = 100 - field
target[sample, 0] = np.clip(field, 0, 100) * land
observed = land.copy()
observed[rng.random((H, W)) < (0.35 + 0.04 * (sample % 3))] = 0
for _ in range(5):
cy, cx = rng.integers(45, 99), rng.integers(78, 121)
ry, rx = rng.integers(3, 11), rng.integers(4, 15)
hole = ((np.arange(H)[:, None] - cy) / ry) ** 2
hole = hole + ((np.arange(W)[None, :] - cx) / rx) ** 2
observed[hole < 1] = 0
valid[sample, 0] = observed
observed_values = target * valid
np.savez_compressed(
output / "crai_fake.npz", target=target, observed=observed_values,
valid_mask=valid, europe_mask=land, index_ids=index_ids,
index_names=INDICES, latitude=lat, longitude=lon,
)
metadata = {
"kind": "structured_synthetic",
"shape": [n, 1, H, W],
"grid_resolution": {"longitude_degrees": 1.875, "latitude_degrees": 1.25},
"indices": INDICES.tolist(),
"mask": "global grid with coarse Europe land support and irregular missing regions",
}
(output / "metadata.json").write_text(json.dumps(metadata, indent=2) + "\n")
print(f"wrote {output / 'crai_fake.npz'} with shape {target.shape}")
if __name__ == "__main__":
main()
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