Published February 7, 2025
| Version v7.2.0
Software
Open
SciML/DataInterpolations.jl: v7.2.0
Authors/Creators
- Christopher Rackauckas1
- Sathvik Bhagavan
- Bart de Koning2
- Shubham Maddhashiya3
- Andreas Noack4
- Ashutosh Bharambe
- Avik Pal1
- Daniel González Arribas5
- Diogo Netto6
- Arno Strouwen
- Anshul Singhvi7
- Jonathan Stickel
- Glen Hertz8
- Isaac Wheeler
- David Widmann9
- Mike Boyle10
- Michael Hatherly11
- Tim Kim
- Venkateshprasad8
- Anant Thazhemadam8
- Pepijn de Vos
- Fredrik Bagge Carlson
- Yingbo Ma8
- contradict
- Mathieu Le Séac'h
- Zack Li
- Dilum Aluthge12
- Lucas Pacheco
- 1. Massachusetts Institute of Technology
- 2. Deltares
- 3. @PumasAI @KRSSG
- 4. @JuliaHub
- 5. ienai SPACE
- 6. @RelationalAI
- 7. Columbia University
- 8. @JuliaComputing
- 9. @PumasAI
- 10. Cornell University
- 11. PumasAI
- 12. Brown University; Pumas-AI
Description
DataInterpolations v7.2.0
Merged pull requests:
- Add Unitful tests for constant extrapolation (#381) (@Ickaser)
- Fix integrating over interval that is fully outside data range (#386) (@SouthEndMusic)
- Fix type inference and performance problems of
munge_data(#392) (@devmotion) - Improve
cumulative_integral(#393) (@devmotion) - Do not fall back to inplace interpolation method (#394) (@devmotion)
Closed issues:
- Broken extrapolation with integer interpolation (#378)
- AkimaInterpolation of Float32 data results in Float64 values when interpolating (#382)
- Integrals with incorrect dimensions for Unitful input (#385)
- Inconsistent output eltype when evaluating on vectors (#388)
- Regressions of
ConstantInterpolationreported byJET.@report_opt(#389)
Files
SciML/DataInterpolations.jl-v7.2.0.zip
Files
(110.8 kB)
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Additional details
Related works
- Is supplement to
- Software: https://github.com/SciML/DataInterpolations.jl/tree/v7.2.0 (URL)
Software
- Repository URL
- https://github.com/SciML/DataInterpolations.jl