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/plot_kde_2d.py

@@ -0,0 +1,53 @@
+"""Plot a 2D KDE density overlay on a matplotlib Axes using seaborn."""
+
+from __future__ import annotations
+
+
+def plot_kde_2d(
+    ax: "Axes",
+    xs: "list[float] | np.ndarray",
+    ys: "list[float] | np.ndarray",
+    cmap: str = "magma",
+    alpha: float = 0.35,
+    thresh: float = 0.02,
+    levels: int = 30,
+    bw_adjust: float = 0.6,
+) -> None:
+    """Plot a 2D kernel density estimate as a filled contour overlay.
+
+    Uses seaborn.kdeplot to render a smooth density surface over the given
+    scatter of (x, y) points. If either array is empty the function returns
+    immediately without painting anything.
+
+    Args:
+        ax: matplotlib Axes to draw on.
+        xs: X coordinates (longitude or projected x).
+        ys: Y coordinates (latitude or projected y).
+        cmap: Matplotlib colormap name for the density fill. Default "magma".
+        alpha: Opacity of the density overlay (0–1). Default 0.35.
+        thresh: Density threshold below which contours are not drawn (0–1).
+            Default 0.02 removes very sparse outlier contours.
+        levels: Number of contour levels. Default 30.
+        bw_adjust: Bandwidth adjustment factor for the kernel. Values < 1
+            produce tighter, more detailed estimates. Default 0.6.
+    """
+    import numpy as np  # type: ignore
+    import seaborn as sns  # type: ignore
+
+    xs_arr = np.asarray(xs)
+    ys_arr = np.asarray(ys)
+
+    if xs_arr.size == 0 or ys_arr.size == 0:
+        return
+
+    sns.kdeplot(
+        x=xs_arr,
+        y=ys_arr,
+        ax=ax,
+        cmap=cmap,
+        fill=True,
+        alpha=alpha,
+        thresh=thresh,
+        levels=levels,
+        bw_adjust=bw_adjust,
+    )