Delete hazards/hazards

hazards/hazards/flood.py

@@ -1,115 +0,0 @@
-from data.geometry import get_geometry, has_associated_features
-import math, os, rasterio, urllib.request
-from rasterio.merge import merge
-from rasterio.mask import mask
-from bs4 import BeautifulSoup
-from datetime import datetime
-import requests, tempfile
-
-def generate_flood_raster(iso: str, rp: int, gis_name: str = None):
-    iso = iso.upper()
-    base_url = "https://gis.unhcr.org/arcgis/rest/services/core_v2/wrl_polbnd_adm1_a_unhcr/MapServer/0/query"
-
-    has_features, _ = has_associated_features(iso, base_url)
-    if has_features:
-        gdf = get_geometry(iso, url=base_url)
-        # If a specific subdivision is selected, filter to it
-        if gis_name:
-            gdf = gdf[gdf['gis_name'] == gis_name]
-            if gdf.empty:
-                return None, f"❌ No geometry found for {gis_name} in {iso}."
-    else:
-        if not gis_name:
-            return None, f"❌ Subdivision required for {iso}."
-        gdf = get_geometry(iso, gis_name)
-        if gdf is None or gdf.empty:
-            return None, f"❌ No geometry found for {gis_name} in {iso}."
-
-    geoms = [feature["geometry"] for feature in gdf.__geo_interface__["features"]]
-    bounds = gdf.total_bounds  # left, bottom, right, top
-
-    # --- Determine tiles to download ---
-    top = math.ceil(bounds[3] / 10) * 10
-    left = (int(bounds[0]) // 10) * 10
-    right = math.ceil(bounds[2] / 10) * 10
-    bottom = (int(bounds[1]) // 10) * 10
-
-    url_base = f"https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/CEMS-GLOFAS/flood_hazard/RP{rp}/"
-    page = requests.get(url_base)
-    soup = BeautifulSoup(page.text, "html.parser")
-    all_links = [a['href'] for a in soup.find_all('a') if a['href'].endswith('.tif')]
-
-    tif_paths = []
-    col = left
-    while col < right:
-        row = top
-        while row > bottom:
-            prefix = f"{'N' if row >= 0 else 'S'}{abs(row)}_{'E' if col >= 0 else 'W'}{abs(col)}"
-            match = [l for l in all_links if prefix in l]
-            if match:
-                tif_paths.append(match[0])
-            row -= 10
-        col += 10
-
-    if not tif_paths:
-        return None, "❌ No tiles found for selected region."
-
-    # --- Create temporary working folder ---
-    workdir = tempfile.mkdtemp(dir=tempfile.gettempdir(), prefix="flood_")
-    cropped_files = []
-
-    # --- Download, crop, and write tiles one by one ---
-    for tif in tif_paths:
-        remote = url_base + tif
-        local = os.path.join(workdir, tif)
-        urllib.request.urlretrieve(remote, local)
-
-        # crop tile to geometry
-        with rasterio.open(local) as src:
-            out_image, out_transform = mask(src, geoms, crop=True, nodata=-9999)
-            out_meta = src.meta.copy()
-            out_meta.update({
-                "height": out_image.shape[1],
-                "width": out_image.shape[2],
-                "transform": out_transform,
-                "nodata": -9999
-            })
-
-            cropped_path = os.path.join(workdir, f"cropped_{tif}")
-            with rasterio.open(cropped_path, "w", **out_meta) as dst:
-                dst.write(out_image)
-
-            cropped_files.append(cropped_path)
-        os.remove(local)  # remove original tile to save disk
-
-    if not cropped_files:
-        return None, "❌ No cropped tiles available."
-
-    # --- Merge cropped tiles using generator to reduce memory ---
-    sources = [rasterio.open(f) for f in cropped_files]
-    mosaic, merge_transform = merge(sources)
-
-    # After merging, close sources to free RAM
-    for src in sources:
-        src.close()
-
-    timestamp = datetime.utcnow().strftime("%Y%m%d%H%M%S")
-    output_path = os.path.join(workdir, f"merged_raster_{iso}_{rp}_{timestamp}.tif")
-
-    out_meta = rasterio.open(cropped_files[0]).meta.copy()
-    out_meta.update({
-        "driver": "GTiff",
-        "height": mosaic.shape[1],
-        "width": mosaic.shape[2],
-        "transform": merge_transform,
-        "nodata": -9999
-    })
-
-    with rasterio.open(output_path, "w", **out_meta) as dest:
-        dest.write(mosaic)
-
-    # Cleanup
-    for f in cropped_files:
-        os.remove(f)
-
-    return output_path, f"✅ Raster generated for {iso} ({rp}-year return period). Click to download below."