Renaming.

fusion.py

@@ -0,0 +1,76 @@
+"""EFAST fusion: S2/S3 reflectance fusion for four scenarios."""
+from pathlib import Path
+from datetime import datetime, timedelta
+
+from preselection import detect_clouds
+from preparation import (
+    prepare_s2,
+    prepare_s3,
+    _get_base_dir,
+    RESOLUTION_RATIO,
+)
+
+
+def _import_efast():
+    """Lazy import of efast to avoid import errors when not using efast functions."""
+    try:
+        import efast
+        return efast
+    except ImportError:
+        raise ImportError(
+            "efast package not found. Install with: pip install git+https://github.com/DHI-GRAS/efast.git"
+        )
+
+
+def run_efast(season, site_position, site_name, cleaning_strategy="aggressive", sigma=None, date_range=None):
+    lat, lon = site_position
+    datetime_range = date_range or f"{season}-01-01/{season}-12-31"
+
+    efast_base_dir = _get_base_dir(season, site_name, cleaning_strategy)
+    s2_output_dir = efast_base_dir / "s2"
+    s3_output_dir = efast_base_dir / "s3"
+    fusion_output_dir = efast_base_dir / (f"fusion_sigma{sigma}" if sigma else "fusion")
+
+    fusion_output_dir.mkdir(parents=True, exist_ok=True)
+    print(f"[EFAST] Starting fusion: {site_name} ({lat:.6f}, {lon:.6f}), {season}")
+
+    efast = _import_efast()
+
+    start_str, end_str = datetime_range.split("/")
+    start_date = datetime.strptime(start_str, "%Y-%m-%d")
+    end_date = datetime.strptime(end_str, "%Y-%m-%d")
+
+    current_date = start_date
+    while current_date <= end_date:
+        date_str = current_date.strftime("%Y%m%d")
+        output_file = fusion_output_dir / f"REFL_{date_str}.tif"
+        try:
+            kwargs = {
+                "product": "REFL",
+                "max_days": 30,
+                "date_position": 2,
+                "minimum_acquisition_importance": 0.0,
+                "ratio": RESOLUTION_RATIO,
+            }
+            if sigma is not None:
+                kwargs["sigma"] = sigma
+            efast.fusion(current_date, s3_output_dir, s2_output_dir, fusion_output_dir, **kwargs)
+            print(
+                f"[EFAST] Saved: {output_file}"
+                if output_file.exists()
+                else f"[EFAST] No output for {date_str} (insufficient nearby data)"
+            )
+        except Exception as e:
+            print(f"[EFAST] Error processing {date_str}: {e}")
+        current_date += timedelta(days=1)
+
+    print("[EFAST] Completed")
+
+
+def run_all_efast_scenarios(season, site_position, site_name, sigma_value=30, date_range=None):
+    for strategy in ["aggressive", "nonaggressive"]:
+        detect_clouds(season, site_name, cleaning_strategy=strategy)
+        prepare_s2(season, site_position, site_name, cleaning_strategy=strategy, date_range=date_range)
+        prepare_s3(season, site_position, site_name, cleaning_strategy=strategy, date_range=date_range)
+        run_efast(season, site_position, site_name, cleaning_strategy=strategy, sigma=None, date_range=date_range)
+        run_efast(season, site_position, site_name, cleaning_strategy=strategy, sigma=sigma_value, date_range=date_range)