[HN Gopher] Augurs demo
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       Augurs demo
        
       Author : weinzierl
       Score  : 163 points
       Date   : 2025-02-18 12:28 UTC (4 days ago)
        
 (HTM) web link (demo.augu.rs)
 (TXT) w3m dump (demo.augu.rs)
        
       | whatevermom wrote:
       | Thanks for sharing
        
       | dang wrote:
       | Related:
       | 
       |  _Show HN: Augurs, a time series toolkit for Rust_ -
       | https://news.ycombinator.com/item?id=42184386 - Nov 2024 (1
       | comment)
        
       | atdt wrote:
       | 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?
        
         | ekianjo wrote:
         | entirely depends on the use case. If you want to do prediction,
         | decomposition, classification, you have many different choices
         | available.
        
         | sd2k wrote:
         | 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!
        
       | jan_Inkepa wrote:
       | Is there any way to zoom out of the graphs once you've zoomed in
       | by clicking and dragging?
        
         | dygd wrote:
         | Double-click will reset the zoom
        
       | zachwill wrote:
       | As someone coming from the Python data science / Jupyter side:
       | holy crap this is lightning fast. Kudos! Very impressive work.
        
       | mrshu wrote:
       | Some links:
       | 
       | - Repo: https://github.com/grafana/augurs
       | 
       | - Docs: https://docs.augu.rs/
       | 
       | - Python library: https://pypi.org/project/augurs/
       | 
       | - npm library: https://www.npmjs.com/package/@bsull/augurs
        
       | sammcgrail wrote:
       | Nice uplot
        
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       (page generated 2025-02-22 23:01 UTC)