egutierrez
dabc945eda
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>
68 lines
2.0 KiB
Python
68 lines
2.0 KiB
Python
"""alpha_shape_concave_hull — Concave hull via Delaunay alpha-shape filtering."""
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from __future__ import annotations
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def alpha_shape_concave_hull(
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points: list[tuple[float, float]],
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alpha: float,
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) -> "shapely.geometry.base.BaseGeometry | None":
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"""Compute the alpha-shape (concave hull) of a 2-D point set.
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Performs a Delaunay triangulation over the input points, then keeps only
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those triangles whose circumscribed circle radius is <= alpha. The
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remaining triangles are merged via unary_union.
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Args:
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points: List of (x, y) coordinate pairs. Must have >= 4 elements.
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alpha: Alpha parameter controlling concavity (smaller = more concave).
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Triangles with circumradius > alpha are discarded.
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Returns:
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A shapely geometry (Polygon, MultiPolygon, or GeometryCollection)
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representing the alpha-shape, or None if len(points) < 4 or no
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triangles survive the alpha filter (shapely is required).
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"""
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if len(points) < 4:
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return None
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try:
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import numpy as np
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from shapely.geometry import MultiPoint
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from shapely.ops import triangulate, unary_union
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except ImportError:
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return None
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mp = MultiPoint(points)
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triangles = triangulate(mp)
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valid = []
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for tri in triangles:
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coords = list(tri.exterior.coords)
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a_pt = np.array(coords[0])
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b_pt = np.array(coords[1])
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c_pt = np.array(coords[2])
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# Circumradius via the formula R = (abc) / (4 * Area)
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ab = np.linalg.norm(b_pt - a_pt)
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bc = np.linalg.norm(c_pt - b_pt)
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ca = np.linalg.norm(a_pt - c_pt)
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# Area via cross product
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area = abs(
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(b_pt[0] - a_pt[0]) * (c_pt[1] - a_pt[1])
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- (c_pt[0] - a_pt[0]) * (b_pt[1] - a_pt[1])
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) / 2.0
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if area == 0:
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continue
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circumradius = (ab * bc * ca) / (4.0 * area)
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if circumradius <= alpha:
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valid.append(tri)
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if not valid:
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return None
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return unary_union(valid)
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