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.md

@@ -0,0 +1,42 @@
+---
+id: alpha_shape_concave_hull_py_datascience
+name: alpha_shape_concave_hull
+kind: function
+lang: py
+domain: datascience
+version: "1.0.0"
+purity: pure
+signature: "def alpha_shape_concave_hull(points: list[tuple[float, float]], alpha: float) -> shapely.geometry.base.BaseGeometry | None"
+description: "Computes the alpha-shape (concave hull) of a 2-D point set via Delaunay triangulation, filtering triangles by circumradius <= alpha and merging survivors."
+tags: [geometry, spatial, concave-hull, alpha-shape, shapely, delaunay]
+uses_functions: []
+uses_types: []
+returns: []
+returns_optional: false
+error_type: ""
+imports: [numpy, shapely]
+example: |
+  from alpha_shape_concave_hull import alpha_shape_concave_hull
+  pts = [(0.0,0.0),(1.0,0.0),(1.0,1.0),(0.0,1.0)]
+  geom = alpha_shape_concave_hull(pts, alpha=10.0)
+  # shapely Polygon
+tested: true
+tests:
+  - "test_alpha_shape_square_large_alpha"
+  - "test_alpha_shape_too_few_points"
+  - "test_alpha_shape_very_small_alpha_returns_none"
+  - "test_alpha_shape_5_points_returns_geometry"
+test_file_path: "python/functions/datascience/tests/test_alpha_shape_concave_hull.py"
+file_path: "python/functions/datascience/alpha_shape_concave_hull.py"
+params:
+  - name: points
+    desc: "List of (x, y) coordinate pairs. Requires at least 4 points."
+  - name: alpha
+    desc: "Alpha radius parameter. Triangles with circumradius > alpha are discarded. Smaller alpha = more concave hull."
+output: "Shapely geometry (Polygon or MultiPolygon) of the alpha-shape, or None if fewer than 4 points or no triangles survive the alpha filter."
+source_repo: "internal:footprint_aurgi"
+source_license: "internal-aurgi"
+source_file: "ponderacion_isochronas/src/recomendador_centros.py:408"
+---
+
+Requiere shapely. Si shapely no esta instalado, retorna None en silencio. returns_optional=true porque puede no haber triangulos validos.