"""
归一化常量 - point4_v30
从 data/each-point-V30/point4_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point4_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    -0.21735365385481095,
    1.146649527479852,
    -0.8639224236397658,
    -0.0366343220295033,
    0.9104707563216103,
    -0.021397598130488894,
    0.059362471541857365,
    0.023706428706645966,
    -0.031137484798775067,
    -0.15235542476220895,
    -0.005826317618105161,
    0.5936171133118961,
    -0.05018620966114964,
    7.000005880953068e-05
], dtype=np.float32)

STATE_STD = np.array([
    0.2102253805949658,
    0.7658808333158452,
    0.5529057432367724,
    0.07265797427364623,
    0.23469697324617478,
    0.09436715707689124,
    0.03222894862077091,
    0.0,
    7.767954915336072e-05,
    0.0004781704950766074,
    5.168509104714842e-09,
    0.001913202964455008,
    0.00010597815677546606,
    3.859463417203669e-08
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    -0.21809362965479312,
    1.1355306549402504,
    -0.8904613166359503,
    -0.04333029593342418,
    0.8643201283589087,
    -0.023920130371530745,
    0.059623906544497396,
    0.02365400729111893,
    -0.03171323145067094,
    -0.17187523067041208,
    -0.005878658843141073,
    0.5043942354545788,
    -0.051233134417770415,
    -0.021100036475361048
], dtype=np.float32)

ACTION_STD = np.array([
    0.21219605932089225,
    0.75205568886306,
    0.5567277356808167,
    0.08035356119525855,
    0.26816162993954756,
    0.09766573132322597,
    0.03677641727915061,
    3.229803036732761e-05,
    1.9943653300040918e-05,
    0.0004333556851899771,
    2.4517295805128176e-09,
    3.0683424331473354e-08,
    1.388979743365584e-08,
    9.329212659536094e-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)