SpectraFit Interface¶
Welcome to the interface documentation for SpectraFit, a comprehensive Python package for spectral analysis and curve fitting.
Overview¶
The interface of SpectraFit is designed to be flexible and user-friendly, accommodating both command-line usage and integration with Jupyter notebooks. This section covers everything you need to get started with SpectraFit and take advantage of its powerful features.
Quick Navigation
- Installation - Set up SpectraFit on your system
- Usage - Learn how to use SpectraFit with examples
- Features - Explore the capabilities and statistical methods
Key Interface Components¶
Complete installation instructions for pip, conda, and development environments.
Command-line interface usage, input file formats, and common workflows.
Statistical analysis, plotting capabilities, and output formats.
Command Line Interface¶
SpectraFit provides a powerful command-line interface that allows you to:
- Process spectral data files directly
- Apply various fitting models
- Generate publication-quality plots
- Export results in multiple formats
For detailed usage examples, see the Usage page.
Jupyter Notebook Integration¶
In addition to the command-line interface, SpectraFit seamlessly integrates with Jupyter notebooks, providing:
- Interactive plotting and visualization
- Real-time parameter adjustments
- Enhanced data exploration capabilities
- Export functionality for presentations and publications
To learn more about using SpectraFit in Jupyter notebooks, check out the notebook examples.
Next Steps¶
After familiarizing yourself with the interface, you may want to explore:
- Examples of real-world applications
- Documentation of available models and statistical methods
- API Reference for programmatic usage