"""Preference-conditioned metrics and utilities for two-property PolyEdit."""
from __future__ import annotations

import numpy as np


def preference_grid(n=11):
    return tuple((float(a), float(1.0 - a)) for a in np.linspace(0.0, 1.0, n))


def reward_vector(poly, directions, values, means, scales, clip=3.0):
    raw = [d * (values[poly][p] - means[p]) / (scales[p] + 1e-9)
           for p, d in zip(("Egc", "Egb"), directions)]
    return (np.clip(raw, -clip, clip) + clip) / (2.0 * clip)


def hypervolume_2d(points, reference=(0.0, 0.0)):
    """Area dominated by two-dimensional maximization points above a fixed reference."""
    rx, ry = reference
    pts = sorted(((max(float(x), rx), max(float(y), ry)) for x, y in points), reverse=True)
    area, top = 0.0, ry
    for x, y in pts:
        if y > top:
            area += (x - rx) * (y - top)
            top = y
    return area


def mip(weights, rewards):
    return float(np.mean([np.dot(w, r) for w, r in zip(weights, rewards)]))


def induced_graph(graph, nodes):
    nodes = set(nodes)
    return {p: [q for q in graph.get(p, ()) if q in nodes]
            for p in sorted(nodes) if any(q in nodes for q in graph.get(p, ())) }