"""
归一化常量 - point2_v30
从 data/each-point-V30/point2_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point2_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    -0.2105864585016499,
    1.3310560174962338,
    -1.1387206377712409,
    0.06850543825862183,
    0.7681250187706506,
    -0.08478798886625565,
    0.05835128650106446,
    0.02370642884928235,
    -0.031137483014934606,
    -0.15235544200127704,
    -0.006249059893535669,
    0.5941734570462274,
    -0.05018620472882003,
    7.000005561990393e-05
], dtype=np.float32)

STATE_STD = np.array([
    0.2400051179695121,
    0.9237869478542775,
    0.7118947011828334,
    0.08144195556664052,
    0.23071447286401414,
    0.179722397158341,
    0.03285219262761961,
    4.953138735344596e-10,
    8.388984945120932e-05,
    0.0004753077244397484,
    0.0008577420475323502,
    0.002150086383523521,
    0.00010284846023543875,
    3.132144638762018e-08
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    -0.2109139475252697,
    1.3108079862689859,
    -1.1673434242464766,
    0.07370919146763717,
    0.7044337684964903,
    -0.0844366189408058,
    0.057783793058325136,
    0.02365400559923624,
    -0.03171325462574329,
    -0.17187520877501722,
    -0.005509715998848856,
    0.5043942625478558,
    -0.05123314912850634,
    -0.02110003694254407
], dtype=np.float32)

ACTION_STD = np.array([
    0.24125223557585568,
    0.9046525674814566,
    0.7146504447920251,
    0.09142734038550057,
    0.25411883130066965,
    0.18318653299101498,
    0.037955622978664776,
    2.7160945227379783e-05,
    5.362838404012091e-06,
    0.0004134820247080275,
    0.001425757586551424,
    2.979843662272417e-08,
    9.064657920470249e-09,
    1.5702117327601945e-05
], 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)