"""
归一化常量 - point5_v30
从 data/each-point-V30/point5_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point5_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    -0.28005248155530416,
    1.3383875955120301,
    -1.1340355494467393,
    0.04400213425097945,
    0.6931494163132652,
    -0.013576608081085108,
    0.05974055656493036,
    0.018501200326071592,
    -0.03282953766787461,
    -0.15235542188725504,
    -0.002301428052642584,
    0.5936170996343659,
    -0.04125813545263295,
    0.0
], dtype=np.float32)

STATE_STD = np.array([
    0.21416834336270812,
    0.9030553839265362,
    0.6935661050312355,
    0.06133690093023171,
    0.19034198074473987,
    0.09296174655805599,
    0.0318032495403896,
    0.020133542034951886,
    3.9235387410912323e-05,
    0.0004789654057632508,
    0.002848207154696946,
    0.0019173978824850602,
    0.007214434067294394,
    0.0
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    -0.2807868087526399,
    1.3186104217237944,
    -1.1624275894222404,
    0.04484921323885086,
    0.6214815075819917,
    -0.01548597917326217,
    0.05852798315059126,
    0.018503104133437743,
    -0.03181775955729813,
    -0.17297348977113092,
    -0.00583117052590501,
    0.5048373769527363,
    -0.04608024321727365,
    -0.021100036575480336
], dtype=np.float32)

ACTION_STD = np.array([
    0.21595120233546664,
    0.8836377848472635,
    0.6972781236780935,
    0.06790456168072799,
    0.20456011389450912,
    0.0950634453821984,
    0.03626923789601678,
    0.018581566641577462,
    8.614682487762797e-05,
    0.0009287712234452638,
    0.0005459503451593117,
    0.0003580720599472833,
    0.00417338909340118,
    4.801666942775271e-06
], 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)