-
Notifications
You must be signed in to change notification settings - Fork 38
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Obtaining confidence values from the model #26
Comments
Hi @yoavatsmonraz81 , Did you find a solution? I'm facing a similar issue and would appreciate any insights. Thanks! |
Hello @yoavatsmonraz81 , @YFeriel , |
None that i am aware of. I just moved on to other software.
…--------------------------------------
Dr. Yoav Atsmon Raz
Head of Computational Biology
DenovAI Biotech Ltd.
AION Labs, 4 Oppenheimer,
Rehovot, 7670104, Israel
https://denovai.com<https://denovai.com/>
***@***.***
From: Sue-Fwl ***@***.***>
Sent: Sunday, 20 October 2024 5:04
To: ketatam/DiffDock-PP ***@***.***>
Cc: Yoav Atsmon Raz ***@***.***>; Mention ***@***.***>
Subject: Re: [ketatam/DiffDock-PP] Obtaining confidence values from the model (Issue #26)
Hello @yoavatsmonraz81<https://github.com/yoavatsmonraz81> , @YFeriel<https://github.com/YFeriel> ,
Any news on the matter? It's October and sadly no one replied or updated README.
—
Reply to this email directly, view it on GitHub<#26 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/BD3F5JWO5IJPSADDZW7LRGTZ4MFRNAVCNFSM6AAAAABFG75OYKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDIMRUGQYDKMBUGE>.
You are receiving this because you were mentioned.Message ID: ***@***.******@***.***>>
|
Thank you! |
Hi there, thanks a lot for your work on this software, its quite impressive. However, I'm trying to understand if their is a way to obtain the confidence values of each predicted pose ?
I printed out the prediction pickle and got a list composed of this data structure (40 copies of it per number of sampled structures):
name='2Q3A',
center=[1, 3],
receptor={
pos=[117, 3],
x=[117, 1281],
},
ligand={
pos=[117, 3],
x=[117, 1281],
},
(receptor, contact, receptor)={ edge_index=[2, 2340] },
(ligand, contact, ligand)={ edge_index=[2, 2340] }
), -7.416438102722168)]]
I suspected the -7.41 to be the gradient value and not the confidence one, but I also couldn't find any clear way how to get a handle on this via main_inf.py
Could you please advise ?
Kindest regards,
Yoav
The text was updated successfully, but these errors were encountered: