Files
fn_registry/python/functions/datascience/kde_density_levels.md
T
egutierrez faac610745 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>
2026-05-04 23:35:22 +02:00

2.3 KiB

id, name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, example, tested, tests, test_file_path, file_path, params, output, source_repo, source_license, source_file
id name kind lang domain version purity signature description tags uses_functions uses_types returns returns_optional error_type imports example tested tests test_file_path file_path params output source_repo source_license source_file
kde_density_levels_py_datascience kde_density_levels function py datascience 1.0.0 pure def kde_density_levels(xs: list[float], ys: list[float], bw_adjust: float = 0.6, abs_quantile: float = 0.1, dense_quantile: float = 0.85, bins: int = 80) -> dict | None Estimates 2-D density via KDE (scipy) or histogram fallback (numpy) and returns per-point density values plus absolute and dense quantile thresholds.
statistics
kde
density
spatial
geospatial
scipy
numpy
false
numpy
scipy
from kde_density_levels import kde_density_levels import numpy as np rng = np.random.default_rng(42) result = kde_density_levels(rng.normal(0,1,50).tolist(), rng.normal(0,1,50).tolist()) # {"method": "kde", "densities": array(...), "abs_level": ..., "dense_level": ...} true
test_kde_density_levels_returns_dict_for_50_points
test_kde_density_levels_none_for_few_points
test_kde_density_levels_none_for_4_points
test_kde_density_levels_levels_ordered
test_kde_density_levels_mismatched_lengths
python/functions/datascience/tests/test_kde_density_levels.py python/functions/datascience/kde_density_levels.py
name desc
xs X-coordinates of the 2-D point cloud.
name desc
ys Y-coordinates of the 2-D point cloud. Must have same length as xs.
name desc
bw_adjust Bandwidth adjustment factor for gaussian_kde. Default 0.6.
name desc
abs_quantile Quantile of density values used as the absolute (sparse) threshold. Default 0.1.
name desc
dense_quantile Quantile of density values used as the dense cluster threshold. Default 0.85.
name desc
bins Number of bins per axis for the histogram fallback. Default 80.
Dict with method (str), densities (np.ndarray of per-point density), abs_level (float), dense_level (float). Returns None if len(xs) < 5 or lengths differ. internal:footprint_aurgi internal-aurgi ponderacion_isochronas/src/recomendador_centros.py:305

Funcion pura que no escribe nada en disco. returns_optional=true porque devuelve None cuando hay menos de 5 puntos.