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nnzhan / Graph-WaveNet

graph wavenet
MIT License
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Printing of results #33

Open annelorejp opened 2 years ago

annelorejp commented 2 years ago

Hi,

Currently I'm working on the Graph-WaveNet code with my own dataset (predicting the amount of patients occupying a bed in a hospital).

There is one thing I don't fully understand from the code.

In this line of code (test.py line 100-104):

afbeelding 
y12 = realy[:,99,11].cpu().detach().numpy()
yhat12 = scaler.inverse_transform(yhat[:,99,11]).cpu().detach().numpy()

y3 = realy[:,99,2].cpu().detach().numpy()
yhat3 = scaler.inverse_transform(yhat[:,99,2]).cpu().detach().numpy()

Can anyone explain to me what they are doing in this piece of code? And what the difference is between y12 and y3?

I really hope someone can help me! :)

Thanks in advance!

zowb commented 2 years ago

It is the prediction at time step 3 and 12 respectively.

annelorejp commented 2 years ago

Thanks for your reply! So there is predicted based on the time steps before AND the training model which uses the training data? OR Are the predictions only based on the couple of time steps before?

packer-c commented 1 year ago

Same question. What does 99 mean?

packer-c commented 1 year ago

oh, I knew that 99 represents 99th node.