"""Pure continuous mapping: mood[7] (V A D U G W I, 0-255) -> render params.
Hue flows smoothly with valence (red->orange->yellow->green); arousal sets
vividness and eye-openness; face is parametric (mouth curve, eye size, brow tilt)."""
from __future__ import annotations


def _lerp(x, x0, x1, y0, y1):
    if x1 == x0:
        return y0
    t = max(0.0, min(1.0, (x - x0) / (x1 - x0)))
    return y0 + (y1 - y0) * t


def _norm(x):  # 0..255 -> 0..1
    return max(0, min(255, x)) / 255.0


def _face(v: int, a: int) -> str:
    """Region string for voice/emoticon lookup (backward compatibility)."""
    POS, NEG = 150, 106
    if v >= POS:
        return "excited" if a >= 170 else "content"
    if v <= NEG:
        return "angry" if a >= 128 else "sad"
    return "neutral"


def mood_to_appearance(mood: list[int]) -> dict:
    v, a, d, u, g, w, i = mood
    return {
        "hue": round((_lerp(v, 0, 128, 8.0, 48.0) if v <= 128 else _lerp(v, 128, 255, 48.0, 125.0)), 1),
        "saturation": round(_lerp(a, 0, 255, 30.0, 95.0), 1),
        "lightness": round(_lerp(a, 0, 255, 52.0, 70.0), 1),
        "aura": round(_lerp(a, 0, 255, 0.12, 0.7), 2),
        "scale": round(_lerp(d, 0, 255, 0.85, 1.18), 3),
        "droop": round(_norm(g), 2),
        "lean": round((i - 128) / 128.0, 2),
        "face": {
            "mouth": round((v - 128) / 128.0, 2),          # +smile … -frown
            "eye": round(_lerp(a, 0, 255, 0.5, 1.4), 2),   # openness
            "brow": round(((128 - v) / 128.0) * _norm(a), 2),  # angry = low V + high A
        },
        "mood": mood,
    }