"""
归一化常量 - point3_v30
从 data/each-point-V30/point3_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point3_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    -0.21596119232660482,
    1.2207692969225374,
    -1.0096915239590631,
    0.06665300637731363,
    0.8658904797422844,
    -0.10243313168005087,
    0.06063812544194792,
    0.023706428706645966,
    -0.031137486115619922,
    -0.1523554427025122,
    -0.00582632172151972,
    0.5936174524881294,
    -0.050186213915922054,
    7.000005638347541e-05
], dtype=np.float32)

STATE_STD = np.array([
    0.22912212245489327,
    0.8531831383553732,
    0.5894133692031163,
    0.06660771562770082,
    0.19870830588697294,
    0.15119653380079995,
    0.030942214621278254,
    0.0,
    7.220514537896655e-05,
    0.0004696939228577277,
    1.6153864865645676e-09,
    0.0017753155458789874,
    0.00010829307026397923,
    4.550171910212743e-08
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    -0.21606439613876077,
    1.2051186572374768,
    -1.0383560313384674,
    0.07103687554190287,
    0.8088382380255467,
    -0.10317745810504365,
    0.061444765060923084,
    0.023654008747490077,
    -0.03171321288973903,
    -0.17187524861071532,
    -0.005878656783530805,
    0.5043942184018506,
    -0.051233122995382026,
    -0.021100035854290898
], dtype=np.float32)

ACTION_STD = np.array([
    0.23080246069430865,
    0.8366779817931731,
    0.5930560500708245,
    0.07621794983645165,
    0.23375717676174276,
    0.1546705690915461,
    0.03634931021459363,
    3.581398692335805e-05,
    2.7334416730016675e-05,
    0.00044864365745036176,
    1.5242100193644467e-09,
    2.576540317068765e-08,
    9.01566114957018e-09,
    9.312128726530881e-10
], 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)