tensorflow / tensorflow/tensorboard
Make "Ignore outliers in chart scaling" compute bounds per time series
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- Dominant language
- TypeScript
- Stars
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- Avg merge
- 4d 22h
- Merged PRs (30d)
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Description
Currently, "Ignore outliers in chart scaling" computes the outliers across all time series and then clips so that n % of the data is inside the view.
When comparing a previous training run to a run that has just started (so it doesn't have many data points yet) but is somewhat different, this can lead to the entire new run to be clipped from view.
Instead, it would be better to compute and clip outliers separately for each time series. This ensures that no time series is ever completely hidden (which is confusing for users, see e.g. https://github.com/tensorflow/tensorboard/issues/214).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the chart-scaling entry point for the “Ignore outliers in chart scaling” option. Trace how outliers and bounds are computed across time series, then verify that clipping is performed separately for each series and that a short, different run is not completely hidden.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- typescript
- Domain
- data-visualization, frontend
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100