Open 123456789qwerfds opened 2 months ago
Thank you for following our work.
We set breakpoints and ran the program on the SWaT dataset but did not find the above problems. Below is a screenshot of the running program under debugging. This code means randomly selecting several dimensions in a multi-dimensional time series to add trend items. We guess it is a Numpy version problem, our version is v1.24.3.
Sorry, we found the problem because we forgot to modify the WADI hyperparameters. According to the paper, it should be as follows:
self.features_len = 6
self.window_size = 32
self.time_step = 16
The source code has been updated.
Traceback (most recent call last): File "cutAddPaste.py", line 110, in
train_dl, val_dl, test_dl, test_anomaly_window_num = data_generator(train_data, test_data, train_labels,
File "/data/wxc/CutAddPaste-main/dataloader/dataset.py", line 83, in data_generator
train_aug_x = cut_add_paste_outlier(train_origin, configs)
File "/data/wxc/CutAddPaste-main/dataloader/generate_negative.py", line 162, in cut_add_paste_outlier
cut_data[:, item] += slope
ValueError: operands could not be broadcast together with shapes (8,) (16,) (8,)