Reorganize bundled assets into checkpoints/ and data/ folders

.gitignore

@@ -9,9 +9,9 @@ build/
 
 # Model checkpoints are not stored in git — fetch from Hugging Face
 # (huggingface.co/maxxxzdn/mosaic) instead. On HF they live as LFS objects.
-*.pt
-*.pth
-*.ckpt
+checkpoints/*.pt
+checkpoints/*.pth
+checkpoints/*.ckpt
 
 # Generated forecast outputs (kept out of git but bundled .npz assets are tracked)
 verify_*.npz

README.md

@@ -112,7 +112,7 @@ pip install gcsfs
 
 ## Getting the weights
 
-If you installed via Hugging Face (`huggingface-cli download maxxxzdn/mosaic --local-dir .`), the checkpoints (`era5_best.pt`, `hres_best.pt`) and normalization stats are already bundled and `inference.py` finds them in the working directory.
+If you installed via Hugging Face (`huggingface-cli download maxxxzdn/mosaic --local-dir .`), the checkpoints (`checkpoints/era5_best.pt`, `checkpoints/hres_best.pt`) and normalization stats (`data/*.npz`) are already in place and `inference.py` finds them automatically.
 
 If you cloned this repo from GitHub instead, the weights are not in the git tree (they live on the [Hugging Face mirror](https://huggingface.co/maxxxzdn/mosaic) as LFS objects). Fetch them with:
 
@@ -208,11 +208,11 @@ gs://weatherbench2/datasets/hres_t0/2016-2022-6h-240x121_equiangular_with_poles_
 | `base.py` | `WeatherModel` wrapper |
 | `config.py` | Variable / level definitions |
 | `dataset.py` | Metadata dataclasses |
-| `norm_stats_era5.npz` | Normalization statistics for the `era5` variant |
-| `norm_stats_hres.npz` | Normalization statistics for the `hres` variant |
-| `static_vars.npz` | Static fields (orography, land–sea mask, soil type) — shared between variants |
-| `era5_best.pt` | Trained checkpoint, `era5` variant (~1.7 GB) |
-| `hres_best.pt` | Trained checkpoint, `hres` variant (~1.7 GB) |
+| `data/norm_stats_era5.npz` | Normalization statistics for the `era5` variant |
+| `data/norm_stats_hres.npz` | Normalization statistics for the `hres` variant |
+| `data/static_vars.npz` | Static fields (orography, land–sea mask, soil type) — shared between variants |
+| `checkpoints/era5_best.pt` | Trained checkpoint, `era5` variant (~1.7 GB) — Hugging Face only |
+| `checkpoints/hres_best.pt` | Trained checkpoint, `hres` variant (~1.7 GB) — Hugging Face only |
 | `figures_weather/` | Figures from the paper |
 
 ## Limitations

era5_best.pt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:187df31a0caef3e934e4eb8a11506c9fea518ff0e02ce6d1f804fc6c8a78a940
-size 1713557607

hres_best.pt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6e0bc244382fa1b0f09ecdbd527c601d352cc5989697149742e8983f38a25e5e
-size 1714571315

inference.py

@@ -102,15 +102,15 @@ class Preset:
 PRESETS = {
     "era5": Preset(
         step_stride=4, num_history_steps=2, k_neighbors=24,
-        default_checkpoint="era5_best.pt",
-        default_norm_stats="norm_stats_era5.npz",
+        default_checkpoint="checkpoints/era5_best.pt",
+        default_norm_stats="data/norm_stats_era5.npz",
         stage_cfgs=_STAGE_CFGS_COMMON,
         bottleneck_cfg=_BOTTLENECK_CFG_COMMON,
     ),
     "hres": Preset(
         step_stride=1, num_history_steps=4, k_neighbors=20,
-        default_checkpoint="hres_best.pt",
-        default_norm_stats="norm_stats_hres.npz",
+        default_checkpoint="checkpoints/hres_best.pt",
+        default_norm_stats="data/norm_stats_hres.npz",
         stage_cfgs=_STAGE_CFGS_COMMON,
         bottleneck_cfg=_BOTTLENECK_CFG_COMMON,
     ),
@@ -247,8 +247,8 @@ def build_model(
     longitude: np.ndarray,
     latitude: np.ndarray,
     preset: Preset,
-    norm_stats_path: str = "norm_stats.npz",
-    static_vars_path: str = "static_vars.npz",
+    norm_stats_path: str = "data/norm_stats_era5.npz",
+    static_vars_path: str = "data/static_vars.npz",
     device: str = "cuda",
 ):
     """Build and return the WeatherModel with loaded checkpoint and metadata."""
@@ -412,8 +412,8 @@ def main():
                         help="Output file path (default: forecast.npz)")
     parser.add_argument("--norm-stats", type=str, default=None,
                         help="Path to norm_stats .npz. Default: preset's default_norm_stats")
-    parser.add_argument("--static-vars", type=str, default="static_vars.npz",
-                        help="Path to static_vars.npz (default: static_vars.npz in current dir)")
+    parser.add_argument("--static-vars", type=str, default="data/static_vars.npz",
+                        help="Path to static_vars.npz (default: data/static_vars.npz)")
     parser.add_argument("--k-neighbors", type=int, default=None,
                         help="Override preset's k_neighbors (advanced — for ablation only)")
     parser.add_argument("--no-compile", action="store_true",