Renaming.

clouds.py

@@ -1,63 +0,0 @@
-import json
-from pathlib import Path
-from datetime import datetime
-
-WINDOW_DAYS = 14
-MIN_WINDOW_SIZE = 3
-THRESHOLDS = {"aggressive": {"threshold": 0.3, "delta": 0.15}, "nonaggressive": {"threshold": 0.2, "delta": 0.25}}
-
-
-def detect_clouds(season, site_name, cleaning_strategy="aggressive"):
-    output_file = Path(f"data/{site_name}/{season}/clouds_{cleaning_strategy}.json")
-    clouds = {"s2": [], "s3": []}
-    thresholds = THRESHOLDS[cleaning_strategy]
-
-    for source in ["s2", "s3"]:
-        timeseries_file = Path(
-            f"data/{site_name}/{season}/raw/ndvi/{source}/timeseries.json"
-        )
-        if not timeseries_file.exists():
-            print(f"[CLOUDS-{source.upper()}] No timeseries.json found")
-            continue
-
-        print(f"[CLOUDS-{source.upper()}] Processing {timeseries_file}...")
-
-        with open(timeseries_file) as f:
-            timeseries = json.load(f)
-
-        # Flag entries with ndvi: None as outliers (bad/invalid data)
-        for e in timeseries:
-            if e.get("ndvi") is None:
-                clouds[source].append(e["filename"])
-
-        entries = [
-            (e, datetime.fromisoformat(e["date"].replace("Z", "+00:00")))
-            for e in timeseries
-            if e.get("ndvi") is not None
-        ]
-
-        for entry, entry_date in entries:
-            window_ndvi = [
-                e["ndvi"]
-                for e, d in entries
-                if abs((d - entry_date).days) <= WINDOW_DAYS
-            ]
-
-            if len(window_ndvi) < MIN_WINDOW_SIZE:
-                continue
-
-            max_ndvi = max(window_ndvi)
-            threshold = max_ndvi - thresholds["delta"]
-
-            if entry["ndvi"] < threshold and entry["ndvi"] < thresholds["threshold"]:
-                clouds[source].append(entry["filename"])
-
-        print(
-            f"[CLOUDS-{source.upper()}] Found {len(clouds[source])} cloud-covered files"
-        )
-
-    output_file.parent.mkdir(parents=True, exist_ok=True)
-    with open(output_file, "w") as f:
-        json.dump(clouds, f, indent=2)
-
-    print(f"[CLOUDS] Saved: {output_file}")