fn_registry/python/functions/datascience/kde_density_levels.md

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 pendiente-usar				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.