thuml / iTransformer

Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah
https://arxiv.org/abs/2310.06625
MIT License
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data_loader.py文件的疑问 #79

Closed Sunlandis closed 4 months ago

Sunlandis commented 4 months ago

您好,在这个文件这定义类有这么一个判断操作: if self.timeenc == 0: df_stamp['month'] = df_stamp.date.apply(lambda row: row.month, 1) df_stamp['day'] = df_stamp.date.apply(lambda row: row.day, 1) df_stamp['weekday'] = df_stamp.date.apply(lambda row: row.weekday(), 1) df_stamp['hour'] = df_stamp.date.apply(lambda row: row.hour, 1) df_stamp['minute'] = df_stamp.date.apply(lambda row: row.minute, 1) df_stamp['minute'] = df_stamp.minute.map(lambda x: x // 15) data_stamp = df_stamp.drop(['date'], 1).values elif self.timeenc == 1: data_stamp = time_features(pd.to_datetime(df_stamp['date'].values), freq=self.freq) data_stamp = data_stamp.transpose(1, 0) 这段判断条件中为什么没有else?不知道有没有具体的用意?

WenWeiTHU commented 4 months ago

您好,这快没有特殊用意,应该是一个历史遗留问题,详情可移步tslib

Sunlandis commented 4 months ago

感谢!