"""
归一化常量 - point6_v30
从 data/each-point-V30/point6_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point6_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    -0.007085140314847432,
    -0.03668476168522435,
    -0.15001790611264593,
    0.02313079016292914,
    0.6102600914863343,
    -0.0223078279476414,
    0.0,
    0.5099882148213464,
    1.1446939613341174,
    -0.8201013696834506,
    0.031126432575391345,
    0.5934614346440548,
    0.004724245610484785,
    0.05497666901780313
], dtype=np.float32)

STATE_STD = np.array([
    0.012557890494509377,
    6.053414836905151e-05,
    0.0002020044001694013,
    1.381821878530468e-08,
    0.0014517861158772052,
    0.001511308291785926,
    0.0,
    0.3652191086613024,
    0.7760467146669371,
    0.4718792864106299,
    0.07129632433162746,
    0.12295911007000543,
    0.08249436712990883,
    0.025471240915686186
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    -0.005136718748684256,
    -0.03412054045721903,
    -0.17435355442555325,
    0.017862677371012638,
    0.5062463928050912,
    -0.031102536014840948,
    -0.01779997369099908,
    0.5109146526894845,
    1.1305450997768085,
    -0.8409332029684848,
    0.03348627621020602,
    0.5344794620455249,
    0.0017850577796070354,
    0.05896427743418828
], dtype=np.float32)

ACTION_STD = np.array([
    0.013219498878056806,
    2.011524508279726e-09,
    7.470100902949707e-08,
    8.984777029888443e-09,
    0.0014530189885909569,
    8.441573803620589e-05,
    4.7111978829599714e-05,
    0.367917774188715,
    0.7618541379264655,
    0.47459581196510897,
    0.07797761403916502,
    0.12923715860023022,
    0.08473523241824801,
    0.030256989839921818
], dtype=np.float32)

# Image 归一化参数（ImageNet 标准）
IMAGE_MEAN = np.array([0.485, 0.456, 0.406], dtype=np.float32)
IMAGE_STD = np.array([0.229, 0.224, 0.225], dtype=np.float32)