Changelog

Source: NEWS.md

libscanR 0.1.0

Initial release

Import & Export

• ls_read_spectrum(): Read individual LIBS spectra from CSV/TSV/TXT.
• ls_read_dir(): Batch-import spectra from a directory.
• ls_read_csv(): Convenience wrapper for CSV files.
• ls_read_sciaps(), ls_read_aurora(): Vendor-specific parsers.
• ls_read_auto(): Auto-detect format and dispatch to correct reader.
• ls_write_csv(), ls_export_spectra(): Export processed data.

Data Structures

• S3 classes: libs_spectrum, libs_dataset, libs_calibration.
• Print, summary, subset, plot, length, dim, and combine methods.
• Helper predicates: is_libs_spectrum(), is_libs_dataset(), is_libs_calibration().

Preprocessing

• ls_baseline(): SNIP, ALS, rolling ball, linear, polynomial.
• ls_normalize(): Total, max, SNV, internal standard, area.
• ls_smooth(): Savitzky-Golay, moving average, Gaussian, median.
• ls_average_shots(): Shot averaging with outlier removal.
• ls_crop(): Spectral range subsetting.
• ls_gate_optimize(): Optimize acquisition gate delay.

Peak Analysis

• ls_find_peaks(): Peak detection with SNR, prominence, distance filters.
• ls_identify_peaks(): Match detected peaks against the NIST database.
• ls_peak_area(): Integrate peak area with baseline subtraction.
• ls_element_db(): Curated NIST emission lines for 23 elements.

Calibration & Quantification

• ls_calibrate(): Univariate, internal standard, and PLS calibration.
• ls_saha_boltzmann(): Calibration-free LIBS (Boltzmann plot).
• ls_quantify(): Apply calibration to unknowns with LOD/LOQ flags.
• ls_lod(), ls_loq(): Figures of merit.

Chemometrics

• ls_pca(): Principal component analysis.
• ls_plsda(): PLS-DA classification with cross-validation.
• ls_cluster(): K-means and hierarchical clustering.
• ls_train_classifier(): SVM and Random Forest training.
• ls_classify(): Predict class for unknown spectra.

Spatial Mapping

• ls_build_map(): Build elemental distribution maps.
• ls_map_elements(): Multi-element map construction.

Tissue Analysis

• ls_tissue_classify(): Ratio-based and model-based tissue classification.
• ls_tissue_discriminate(): Identify discriminating emission lines.

Visualization

• ls_plot_spectrum(), ls_plot_overlay(), ls_plot_region(): Spectrum plots.
• ls_plot_calibration(), ls_plot_residuals(): Calibration diagnostics.
• ls_plot_map(), ls_plot_map_panel(), ls_plot_element_map(): Elemental maps.
• ls_plot_pca(), ls_plot_loadings(), ls_plot_scree(): PCA plots.
• ls_plot_plsda(): PLS-DA diagnostic plots.
• theme_libs(), scale_color_wavelength(): ggplot2 helpers.

Shiny Application

• ls_run_app(): Interactive spectral explorer with six tabs (Import, Preprocess, Peaks, Calibration, Chemometrics, Export).

Example Data

• ls_simulate_spectrum(): Realistic synthetic LIBS spectra.
• ls_example_data(): Tissue, calibration, and spatial scenarios.