Augurs demo

 (demo.augu.rs)

183 points | by weinzierl5 天前

9 comments

  • zachwill1 天前
    As someone coming from the Python data science / Jupyter side: holy crap this is lightning fast. Kudos! Very impressive work.
  • dang1 天前
    Related:

    Show HN: Augurs, a time series toolkit for Rust - https://news.ycombinator.com/item?id=42184386 - Nov 2024 (1 comment)

  • atdt1 天前
    For someone new to time series analysis, how did you choose these particular algorithms? Are they standard in the field, or more of a personal selection?
    • sd2k1 天前
      Most of the algorithms in augurs were chosen to solve problems we've had at Grafana, which tend to require a solution that doesn't require tweaking too many parameters and deals with higher frequency series than many other time series algorithms are designed to deal with. For example, the DBSCAN clustering algorithm works without having to choose the number of clusters, and MSTL/Prophet work with multiple seasonalities and sub-daily data.

      The other criteria is that they needed to be fast and cheap, which ruled out many of the deep learning/neural net based models, although I'd still like to try some foundation models using Burn or some other Rust deep learning framework!

      • ayhanfuat1 天前
        Did you consider matrix profile as well?
    • ekianjo1 天前
      entirely depends on the use case. If you want to do prediction, decomposition, classification, you have many different choices available.
  • esafak1 天前
    Could this be used for outlier detection in Grafana or the like?
  • whatevermom1 天前
    Thanks for sharing
  • jan_Inkepa1 天前
    Is there any way to zoom out of the graphs once you've zoomed in by clicking and dragging?
    • dygd1 天前
      Double-click will reset the zoom
  • sammcgrail1 天前
    Nice uplot
  • 1 天前
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