feat: extraccion masiva footprint_aurgi (41 funcs + 4 types + stack Docker geo)

Extrae al registry funciones del proyecto interno footprint_aurgi:
- core (6): slugify_ascii, normalize_for_join, cp_provincia_es, infer_provincia_from_cp, safe_read_csv_fallback, csv_to_parquet_duckdb
- geo puras (7): haversine_km, point_in_ring, point_in_polygon, point_in_polygons_bbox, polygon_bbox, extent_with_padding, distance_bucket
- geo I/O (4): load_geojson_polygons, load_boundary_gdf, add_basemap_osm, add_basemap_with_timeout
- valhalla client (4): valhalla_route, valhalla_isochrone, valhalla_isochrones_async, valhalla_matrix_1_to_n
- datascience stats (7): trimmed_mean, geometric_mean, detect_distribution_type, best_central_tendency, summary_stats, kde_density_levels, alpha_shape_concave_hull
- datascience fuzzy (3): fuzzy_merge_adaptive (rapidfuzz), words_to_dataset, remove_words_from_column
- datascience viz (2): plot_kde_2d, plot_heatmap_log
- infra (4): compress_pdf_ghostscript, render_table_page_pdfpages, add_header_logo, osm2pgsql_ingest
- pipelines (4): setup_geo_stack_docker, compute_centers_reachability, generate_isochrones_by_zone, count_points_per_zone
- types geo (4): LonLat, BBox, IsochroneRequest, Centro

Incluye:
- apps/footprint_geo_stack/ (PostGIS + Martin + Valhalla via docker-compose)
- 131/132 tests pasan (1 skip esperado: osm2pgsql en PATH)
- Issue tracker dev/issues/0052-footprint-aurgi-extraction.md
- Atribucion uniforme: source_repo internal:footprint_aurgi, source_license internal-aurgi
- Build con 9 agentes en paralelo (8 wave 1 + 1 wave 2 pipelines)

Tambien commitea trabajo previo no commiteado: aggregate_extraction_results, chunk_with_overlap, clean_pdf_text, merge_entity_aliases, extract_graph_gliner2, extract_relations_mrebel, extract_triples_spacy_es, gliner2/mrebel/marianmt/rebel/spacy_es load_model, parse_rebel_output, translate_es_to_en, issue 0050/0051.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/functions/datascience/alpha_shape_concave_hull.py

@@ -0,0 +1,67 @@
+"""alpha_shape_concave_hull — Concave hull via Delaunay alpha-shape filtering."""
+
+from __future__ import annotations
+
+
+def alpha_shape_concave_hull(
+    points: list[tuple[float, float]],
+    alpha: float,
+) -> "shapely.geometry.base.BaseGeometry | None":
+    """Compute the alpha-shape (concave hull) of a 2-D point set.
+
+    Performs a Delaunay triangulation over the input points, then keeps only
+    those triangles whose circumscribed circle radius is <= alpha. The
+    remaining triangles are merged via unary_union.
+
+    Args:
+        points: List of (x, y) coordinate pairs. Must have >= 4 elements.
+        alpha: Alpha parameter controlling concavity (smaller = more concave).
+               Triangles with circumradius > alpha are discarded.
+
+    Returns:
+        A shapely geometry (Polygon, MultiPolygon, or GeometryCollection)
+        representing the alpha-shape, or None if len(points) < 4 or no
+        triangles survive the alpha filter (shapely is required).
+    """
+    if len(points) < 4:
+        return None
+
+    try:
+        import numpy as np
+        from shapely.geometry import MultiPoint
+        from shapely.ops import triangulate, unary_union
+    except ImportError:
+        return None
+
+    mp = MultiPoint(points)
+    triangles = triangulate(mp)
+
+    valid = []
+    for tri in triangles:
+        coords = list(tri.exterior.coords)
+        a_pt = np.array(coords[0])
+        b_pt = np.array(coords[1])
+        c_pt = np.array(coords[2])
+
+        # Circumradius via the formula R = (abc) / (4 * Area)
+        ab = np.linalg.norm(b_pt - a_pt)
+        bc = np.linalg.norm(c_pt - b_pt)
+        ca = np.linalg.norm(a_pt - c_pt)
+
+        # Area via cross product
+        area = abs(
+            (b_pt[0] - a_pt[0]) * (c_pt[1] - a_pt[1])
+            - (c_pt[0] - a_pt[0]) * (b_pt[1] - a_pt[1])
+        ) / 2.0
+
+        if area == 0:
+            continue
+
+        circumradius = (ab * bc * ca) / (4.0 * area)
+        if circumradius <= alpha:
+            valid.append(tri)
+
+    if not valid:
+        return None
+
+    return unary_union(valid)