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

Support overhang slow down and arachne at the same time. #854

Closed
SaltWei opened this issue Dec 16, 2022 · 4 comments
Closed

Support overhang slow down and arachne at the same time. #854

SaltWei opened this issue Dec 16, 2022 · 4 comments
Assignees
Labels
feature New feature or request

Comments

@SaltWei
Copy link
Collaborator

SaltWei commented Dec 16, 2022

See discussing in #466

@SaltWei SaltWei added the feature New feature or request label Dec 16, 2022
@SaltWei SaltWei self-assigned this Dec 16, 2022
@psiberfunk
Copy link

psiberfunk commented Dec 16, 2022

Thanks for forking this off the parent task ! I look forward finding an efficient way to compute the overhang %

@finsdotsurf
Copy link

I asked chatgpt and it came up with some ideas that could help solve this problem:

Pre-calculate and cache the serial of width values and expolygons based on a set of common line widths that are likely to be used in practice. This would allow you to avoid recalculating the serials and expolygons every time the line width is changed.

Another approach is to use approximation techniques to reduce the number of segments and width values that need to be calculated. For example, you could use a piecewise linear approximation to represent the relationship between the overhang degree and line width, which would allow you to perform the calculations more quickly by using fewer segments and width values.

Some potential approximation techniques:

Use a piecewise linear approximation to represent the relationship between the overhang degree and line width, allowing you to perform the calculations more quickly by using fewer segments and width values.

B-spline Approximation, a form of curve fitting that uses a series of polynomial functions to help reduce the number of calculations required and to achieve a more accurate representation of the relationship between the overhang degree and line width.

Simplification algorithms, such as the Ramer-Douglas-Peucker algorithm, to reduce the number of segments in the line.

Interpolation methods, such as linear or polynomial interpolation, to estimate the overhang degree and line width based on a smaller set of reference points.

@kvnper
Copy link

kvnper commented Apr 17, 2023

I'm curious, did Bambu Lab use the suggestions in the above chatgpt post?

@SaltWei SaltWei removed their assignment Apr 18, 2023
@QingZhangBambu
Copy link
Collaborator

We've supported that feature, and you can get that in version 1.6

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

No branches or pull requests

5 participants