Asking for multi signal support about sequitur HOT 5 CLOSED

Glad I could help. And yes I'd be happy to accept that PR.

from sequitur.

Hi Sadra, thanks for the question. sequitur supports what you're asking for, and you'll probably want to use the LSTM autoencoder (LSTM_AE). If you want to use quick_train, you'll first have to create a training set. Do this by creating a list of tensors, each with shape [sequence_length, num_signals]. Then plug in your training set and the model into quick_train, like so:

from sequitur.models import LSTM_AE
from sequitur import quick_train

train_set = ... # List of tensors, each with shape [sequence_length, num_signals]
encoding_dim = ... # Whatever you want the vector encoding size to be
encoder, decoder, _, _ = quick_train(LSTM_AE, train_set, encoding_dim=encoding_dim)

Please let me know if you have any further questions!

from sequitur.

Oh and check out https://projector.tensorflow.org/ if you want to visualize the latent space produced by the autoencoder.

from sequitur.

@sadransh Please let me know if this solves your issue so I can close it. Thanks!

from sequitur.

Thanks a lot. tbh in the meanwhile, I switched to Keras. However, the web-based projector you mentioned was really helpful to me. ( due to buggy behavior embedded projector for my case. )

As I review your readme I think it is clear that your library is able to do such. However, it was not clear to me as I was a beginner at the time I saw your work.

Thanks a lot for your help.

I might be able to create a notebook based on the HAR dataset using your library as a tutorial.

Are you willing to accept such a pull request?

from sequitur.