"""
归一化常量 - point10_v30
从 data/each-point-V30/point10_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point10_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    0.03945469130938774,
    -0.036684750175496716,
    -0.14420977835076654,
    0.07125858545528015,
    0.6045667835144658,
    -0.12207297297360067,
    0.0,
    0.14661628825205947,
    1.232220075192642,
    -1.0148434059932745,
    -0.016941798111343585,
    0.8241991666316403,
    0.14750699481995927,
    0.052436080354416915
], dtype=np.float32)

STATE_STD = np.array([
    0.007826673888420833,
    6.507213128181688e-05,
    7.196581945487117e-08,
    0.00016114506768798135,
    0.0010394814327028597,
    0.00014708015693177227,
    0.0,
    0.28313673258313937,
    0.8379319205720088,
    0.5981789470443272,
    0.08554423150673869,
    0.2096234444893565,
    0.11766143021209088,
    0.027404202199854993
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    0.04208625927977355,
    -0.02820690410301247,
    -0.17410934984246795,
    0.06721168250064102,
    0.507706056050683,
    -0.12866700771276113,
    -0.01789999194443226,
    0.1465567561548079,
    1.2142852250404639,
    -1.0358380725229281,
    -0.01806039941107697,
    0.7775173290968913,
    0.1473984532134141,
    0.056367664585025117
], dtype=np.float32)

ACTION_STD = np.array([
    0.009659401610150165,
    5.529512395654432e-05,
    7.415110423889358e-08,
    0.0001335096561950502,
    0.001149983840094768,
    6.045416662412333e-05,
    2.8176085110043344e-05,
    0.28605545404572474,
    0.8210758013481333,
    0.6011500108903852,
    0.0947890849009308,
    0.2400083578393412,
    0.1210455335794461,
    0.033073617445561386
], 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)