Fitbenchmarking
Tool for comparing the run time and accuracy of minimizers on fit benchmarking problems
Install / Use
/learn @fitbenchmarking/FitbenchmarkingREADME
FitBenchmarking
FitBenchmarking is an open source tool for comparing different minimizers/fitting frameworks. FitBenchmarking is cross platform and we support Windows, Linux and Mac OS. For questions, feature requests or any other inquiries, please open an issue on GitHub.
- Installation Instructions: https://fitbenchmarking.readthedocs.io/en/latest/users/install_instructions/index.html
- User Documentation & Example Usage: https://fitbenchmarking.readthedocs.io/en/latest/users/index.html
- Community Guidelines: https://fitbenchmarking.readthedocs.io/en/latest/contributors/guidelines.html
- Automated Tests: Run via GitHub Actions, https://github.com/fitbenchmarking/fitbenchmarking/actions, and tests are documented at https://fitbenchmarking.readthedocs.io/en/latest/users/tests.html
The package is the result of a collaboration between STFC’s Scientific Computing Department and ISIS Neutron and Muon Facility and the Diamond Light Source. We also would like to acknowledge support from:
- EU SINE2020 WP-10, which received funding from the European Union’s Horizon2020 research and innovation programme under grant agreement No 654000.
- EPSRC Grant EP/M025179/1 Least Squares: Fit for the Future.
- The Ada Lovelace Centre (ALC). ALC is an integrated, cross-disciplinary data intensive science centre, for better exploitation of research carried out at our large scale National Facilities including the Diamond Light Source (DLS), the ISIS Neutron and Muon Facility, the Central Laser Facility (CLF) and the Culham Centre for Fusion Energy (CCFE).
Related Skills
node-connect
352.2kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
frontend-design
111.1kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
openai-whisper-api
352.2kTranscribe audio via OpenAI Audio Transcriptions API (Whisper).
qqbot-media
352.2kQQBot 富媒体收发能力。使用 <qqmedia> 标签,系统根据文件扩展名自动识别类型(图片/语音/视频/文件)。
