What problem does it solve?
This Skill addresses the challenge of analyzing mixed mineral Raman spectra, enabling users to preprocess noisy spectra, match residual peaks against a reference spectral library, unmix components with NNLS, diagnose reliability, write reports, and optionally generate/evaluate synthetic benchmark cases with hidden ground truth.
Core Features & Use Cases
- Preprocessing: Despike, denoise, baseline correction, and normalization of noisy Raman spectra.
- Spectral Library Matching: Iterative matching of residual peaks against a reference spectral library.
- Component Unmixing: Unmixing of components using NNLS.
- Reliability Diagnosis: Diagnosing the reliability of the analysis.
- Reporting: Writing detailed reports of the analysis.
- Synthetic Benchmarking: Optionally generating and evaluating synthetic benchmark cases with hidden ground truth.
- Use Case: A geologist may use this Skill to analyze a complex Raman spectrum of a rock sample and determine the types and proportions of minerals present.
Quick Start
To run the analysis on a given spectrum, execute the following command:
python -m mineral_spectra_analysis kernel.analyze_spectrum_file --spectrum_csv_path "path/to/spectrum.csv" --library "path/to/library" --output_dir "path/to/outputs"
