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fjxmlzn / DoppelGANger

[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
http://arxiv.org/abs/1909.13403
BSD 3-Clause Clear License
296 stars 75 forks source link

is_gen_flag #40

Closed Murmur0 closed 1 year ago

Murmur0 commented 1 year ago

Thanks for your great efforts and achievements in DGAN! And I do hope that you can answer my question below. "Note that is_gen_flag should always set to False (default). is_gen_flag=True is for internal use only (see comments in doppelganger.py for details)." Does it mean that I cannot set the "is_gen_flag" to True?And I must choose a apporpriate length of timesteps for my examples? Looking forward to your reply!

fjxmlzn commented 1 year ago

Yes. In the PKL files you provided to DoppelGANger, is_gen_flag should be False. The length of each time series is specified by data_gen_flag. The maximum length of all time series is specified by the second dimension of the shape of data_feature and data_gen_flag in data_train.npz.

Does that answer your questions?

Murmur0 commented 1 year ago

Oh,thanks for your prompt and elaborate reply!Does it mean that I can set the data_gen_flag to control which timestep of my example can be activated?

fjxmlzn commented 1 year ago

Yes

Murmur0 commented 1 year ago

Thanks!