Skip to content
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

Delay SVD of the transformation matrix in TauSampling and MatsubaraSampling #49

Closed
shinaoka opened this issue May 30, 2024 · 2 comments
Closed

Comments

@shinaoka
Copy link
Member

The SVD can be done when the fit is called first time.

@SamuelBadr
Copy link
Collaborator

I implemented this in the lazy-svd branch but had to make the *Sampling types mutable, so I'm a little hesitant to merge into main. If it degrades performance, maybe the current solution (specifying factorize = false via kwarg in the *Sampling constructors) is preferable. What do you think?

@shinaoka
Copy link
Member Author

shinaoka commented May 31, 2024

maybe the current solution (specifying factorize = false via kwarg in the *Sampling constructors) is preferable.

Sorry, I was not aware of this change!
OK, let us stick to your solution.

BTW, we should add some description on this point in the "sparse-ir-tutorial" since this is crucial when evaluating an object on a large number of frequencies and tau points.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants