Tags¶
12 tags across 121 page assignments. Tag chips at the top of a page link here.
Models¶
20 pages.
- 100 Fitting Functions — Catalog & Implementation Status
- A Wrong Model with a Good \(r^2\)
- Adding a Model
- Bounded Fitting with an Active-Bounds Solver
- Explanation
- Extending SpectraFit-Core
- Glossary
- Holding a Parameter Fixed
- How-to guides
- Model Composition — DAG IR
- Model Reference
- N-Dimensional (≥3-D) Fitting
- Parameter Confidence Intervals
- Parameter Model
- Python: shape factories
- Quickstart
- Shared Parameters Across Peaks
- Sigma-Weighted Fitting
- Single-Dataset Fitting
- SpectraFit-Core
Solvers¶
19 pages.
- Bounded Fitting with an Active-Bounds Solver
- Choosing a Solver
- Escaping Local Minima with the Global Solver
- Explanation
- Extending SpectraFit-Core
- Glossary
- Holding a Parameter Fixed
- How-to guides
- Multi-Dataset Joint Fitting
- N-Dimensional (≥3-D) Fitting
- Parameter Model
- Python: core API
- Robust Fitting Against Outliers
- Rust ↔ Python binding audit
- Shared Parameters Across Peaks
- Solver
- VarPro vs. Levenberg-Marquardt
- When a Fit Fails
- Why SpectraFit-Core
Benchmarking¶
15 pages.
- 100 Fitting Functions — Catalog & Implementation Status
pyproject.toml, explained- Benchmark engine
- Contributor Guide
- Limitations
- NIST StRD Validation
- Python: benchmark API
- Python: benchmark harness
- Significant digits & the uncertainty budget
- spectrafit vs. lmfit: a complex, 8-peak spectrum
- spectrafit vs. lmfit: a moderately complex spectrum
- SpectraFit-Core
- The self-auditing benchmark
- Web dashboard
- Why SpectraFit-Core
Rust¶
15 pages.
- Adding a Model
- CI pipeline & cache architecture
- Contributing to spectrafit-core
- Contributor Guide
- Extending SpectraFit-Core
- Getting Started
- Installation
- Model Composition — DAG IR
- Model Reference
- Reference
- Rust workspace overview
- Rust ↔ Python binding audit
- Solver
- SpectraFit-Core
- Why SpectraFit-Core
Python¶
13 pages.
pyproject.toml, explained- Benchmark engine
- Contributing to spectrafit-core
- Getting Started
- Installation
- Model Composition — DAG IR
- Python: benchmark API
- Python: benchmark harness
- Python: core API
- Python: shape factories
- Quickstart
- Reference
- Web dashboard
Validation¶
10 pages.
- A Wrong Model with a Good \(r^2\)
- Escaping Local Minima with the Global Solver
- Limitations
- NIST StRD Validation
- Significant digits & the uncertainty budget
- Single-Dataset Fitting
- spectrafit vs. lmfit: a complex, 8-peak spectrum
- spectrafit vs. lmfit: a moderately complex spectrum
- The self-auditing benchmark
- When a Fit Fails
CI¶
6 pages.
pyproject.toml, explained- CI pipeline & cache architecture
- Contributor Guide
- Cutting a release
- GitHub mirror workflow
- Release Notes
Governance¶
6 pages.
Uncertainty¶
6 pages.
- Multi-Dataset Joint Fitting
- Parameter Confidence Intervals
- Robust Fitting Against Outliers
- Sigma-Weighted Fitting
- Significant digits & the uncertainty budget
- Solver
NIST StRD¶
4 pages.
PyO3¶
4 pages.
VarPro¶
3 pages.