"""
归一化常量 - point8_v30
从 data/each-point-V30/point8_v30/meta/stats.json 自动生成
"""
import numpy as np

# ====== 归一化统计量（从 point8_v30 数据集提取）======

# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
    -0.029357308751252288,
    -0.0366847310865186,
    -0.15001806139603732,
    0.024403185585707872,
    0.6105986150778014,
    -0.023200513795018196,
    0.0,
    0.23261437138917695,
    1.2513207708462388,
    -1.0035357727626397,
    0.0422896649669971,
    0.8004358498373007,
    0.15402530226691927,
    0.05202593022954153
], dtype=np.float32)

STATE_STD = np.array([
    0.056398723491224996,
    7.066846822897336e-05,
    9.266925077044174e-05,
    0.002200102029912923,
    0.001417246040206404,
    1.817338469257692e-05,
    0.0,
    0.21625684351379432,
    0.8382930945615424,
    0.6238856616798877,
    0.12221667939835275,
    0.23559872175942428,
    0.11968134009988947,
    0.026852916257278012
], dtype=np.float32)

# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
    -0.032802904031301976,
    -0.03356522257857736,
    -0.17505277360891494,
    0.0226375190800306,
    0.5078454193109547,
    -0.03052101877777979,
    -0.017799990113854223,
    0.2339140563913664,
    1.2324637310191093,
    -1.0244116678096804,
    0.04829354306249781,
    0.7543031499447965,
    0.1541142653223035,
    0.05467545737713154
], dtype=np.float32)

ACTION_STD = np.array([
    0.0567161197940044,
    0.0009601377678417388,
    0.0012123247497686602,
    0.008255705685968628,
    0.001676565003332173,
    0.0010080220821494172,
    3.67239565324797e-05,
    0.21772973865643708,
    0.8222133937073368,
    0.6279180203706777,
    0.13550558296994406,
    0.2693235465469347,
    0.12234343218067656,
    0.03189278702391559
], 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)