import os

# Data Configuration
# 使用基于当前文件的绝对路径拼接，以防止你在不同目录下运行报错
DATA_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'downloads')
SEQ_LEN = 512 # 滑动窗口的长度 (时间序列步数)
STEP_SIZE = 20       # 滑动窗口的步长
BATCH_SIZE = 128

# Features Configuration
INPUT_SENSOR = 'WSMS00012'
OUTPUT_SENSORS = ['WSMS00007', 'WSMS00008', 'WSMS00009', 'WSMS00010', 'WSMS00011']
INPUT_AXIS = 'value1'   # 底部传感器输入轴（课程要求：X轴）
OUTPUT_AXIS = 'value3'  # 目标传感器输出轴

# Model Configuration
CHANNELS = [64, 64, 128, 128, 256, 256] # TCN 各层通道数
KERNEL_SIZE = 5
DROPOUT = 0.1

# Training Configuration
LEARNING_RATE = 3e-4
EPOCHS = 50
WEIGHT_DECAY = 1e-4
ENABLE_EARLY_STOP = False
EARLY_STOP_PATIENCE = 15
SPECTRAL_LOSS_WEIGHT = 0.25
CORR_LOSS_WEIGHT = 0.05
MSE_LOSS_WEIGHT = 0.5
STD_LOSS_WEIGHT = 0.3
PEAK_LOSS_WEIGHT = 0.2
CORR_LOSS_EPS = 1e-8

# Device
import torch
DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'