Closed robinredX closed 2 years ago
Hi, Robin:
Thanks for trying TAPE and pointing out the problem. To solve your problem, I quickly tested it. I am not sure about the concrete bug, I propose some possible reasons and I put a reproducible notebook for your test.
I checked the code and noticed that the network structure in https://github.com/poseidonchan/TAPE/blob/main/TAPE/model.py has an extra CELU() function. I will fix it in further version.
On the other hand, I notice that you train it with four simulation datasets and 20 epochs. But in our paper, we only use data8k for training. Because, in my practice, I find that using data8k only is better.
Further issues may be related to the variance cutoff choice.
In this repository, I store the original file when I test the real bulk performance of TAPE (https://github.com/poseidonchan/TAPE/blob/main/Experiments/TAPE_realbulk.ipynb). You can check it. For your information, I also tested the performance in the following file a few minutes ago. (Sorry for the inconvenience, I will also email you the original notebook file.) You can run the code I attached to test it. TAPE_sdy67_response.pdf
In my test, the overall ccc is around 0.7 and the L1 error is around 0.065.
Though the manuscript is still under review, I must apologize for the immature public version and the inconvenience, I will fix it as soon as possible.
Good Evening, Yanshuo
Thank you for this quick response and sending the notebook. robin.
Hi, thanks for the nice tool. I was trying TAPE on SDY67 using Tape. I took following steps:
I am using following parameters in Deconvolution().
My results are as follows:
I don't know what I am doing wrong. Is there some step that I am missing?
Thanks. robin.