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

refactor sampling algorithms #1200

Closed
galpha opened this Issue Apr 1, 2019 · 0 comments

Comments

Projects
None yet
1 participant
@galpha
Copy link
Contributor

galpha commented Apr 1, 2019

refactor should contain the following changes:

  • generify sampling algorithms to run on base graphs
  • cleanup classes and tests for each sampling algorithm
  • introduce annotate function where the graph keeps preserved and each element gets a new sampled property. This function can be used for visualization of sampling results and demonstrations in general.

@galpha galpha self-assigned this Apr 1, 2019

galpha added a commit to galpha/gradoop that referenced this issue Apr 8, 2019

galpha added a commit to galpha/gradoop that referenced this issue Apr 8, 2019

[dbs-leipzig#1200]
- added random walk sampling to benchmark class
- moved all statistics of sampling eval to statistics package
- moved all runner of statistics of sampling eval to statistics runner package
- fixed typos
- removed string output in CSVDataSinkTest

galpha added a commit to galpha/gradoop that referenced this issue Apr 12, 2019

galpha added a commit to galpha/gradoop that referenced this issue Apr 12, 2019

@galpha galpha closed this in #1210 Apr 12, 2019

galpha added a commit that referenced this issue Apr 12, 2019

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
You can’t perform that action at this time.