uncertainties on parameter values on diagonal 1D histograms
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- Dominant language
- Python
- Stars
- 576
- Forks
- 234
- PR merge metrics
- No merged PRs in 30d
Description
I realise playing around with the displaying of the quantiles on the 1D histograms that the uncertainties are not updated accordingly to the extremes of the percentiles values provided (stay as a default 0.16 and 0.84, in the code, line 266 of the corner.py file, Version 2.0.1).
A small hack to recover the quantiles values provided in the quantiles keywords do the trick (provided that the array as an even number).
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Research direction
Start at line 266 of corner.py in version 2.0.1 and inspect how diagonal 1D histogram uncertainties use the default 0.16 and 0.84 values when quantiles are supplied. Verify that displayed uncertainties follow the supplied percentile extremes, including the even-length-array case described, using a focused histogram example.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-visualization
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100