"""
归一化常量 - point9_v30
从 data/each-point-V30/point9_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point9_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    -0.12687032082273955,
    -0.036684748468658004,
    -0.1500179749581063,
    0.028206904805729877,
    0.6122692655357367,
    -0.023200515864581262,
    0.0,
    0.1998390246824548,
    1.0792388664919386,
    -0.7438378233066395,
    0.07516690328567417,
    0.7451424780750904,
    0.052306057294479034,
    0.05337745063575038
], dtype=np.float32)

STATE_STD = np.array([
    9.161563818354771e-05,
    6.565246521768482e-05,
    0.00014853381036188356,
    5.4935169942010397e-05,
    3.0314402184518994e-07,
    1.0696350790923684e-05,
    0.0,
    0.19334436439401964,
    0.7468203133843938,
    0.5563007852660695,
    0.12521193090174662,
    0.24714571181564915,
    0.09695591683097207,
    0.026807901657205098
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    -0.13086460573446723,
    -0.031905150499351484,
    -0.17714334448518482,
    0.03691164604161681,
    0.5106044783021237,
    -0.028782537914904698,
    -0.017799981057825084,
    0.20171889206832191,
    1.0678730896211122,
    -0.7625965521734605,
    0.08184901982010348,
    0.7020391768669159,
    0.0518838830544826,
    0.05827606569204759
], dtype=np.float32)

ACTION_STD = np.array([
    0.00025180691622196823,
    1.805365984284138e-09,
    0.00016874256698898044,
    2.0061900752572355e-08,
    2.8885855748546208e-08,
    8.40284854069312e-05,
    4.279058407581297e-05,
    0.19498184149591666,
    0.7326933248613593,
    0.5605629146731506,
    0.137227747479853,
    0.2816728522424186,
    0.0995232980010479,
    0.03193760938707793
], 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)