Package: libscanR 0.1.0.9001

R. Heller

libscanR: Analysis and Visualization of Laser-Induced Breakdown Spectroscopy Data

Provides a vendor-agnostic pipeline for importing, preprocessing, calibrating, and visualizing Laser-Induced Breakdown Spectroscopy (LIBS) spectral data. Supports baseline correction, peak identification against user-supplied atomic emission line references, univariate and multivariate calibration, relative elemental amounts under an explicitly specified two-stage Saha-Boltzmann model, and calibration-based detection-limit estimates. Includes exploratory chemometric analysis (principal component analysis, partial least squares discriminant analysis, clustering), heuristic tissue classification, and spatial elemental mapping. Includes an interactive 'shiny' application for spectral exploration. Designed for biomedical tissue analysis, environmental monitoring, and materials characterization workflows.

Authors:R. Heller [aut, cre]

libscanR_0.1.0.9001.tar.gz
libscanR_0.1.0.9001.zip(r-4.7-any)libscanR_0.1.0.9001.zip(r-4.6-any)libscanR_0.1.0.9001.zip(r-4.5-any)
libscanR_0.1.0.9001.tgz(r-4.6-any)libscanR_0.1.0.9001.tgz(r-4.5-any)
libscanR_0.1.0.9001.tar.gz(r-4.7-any)libscanR_0.1.0.9001.tar.gz(r-4.6-any)
libscanR_0.1.0.9001.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
libscanR/json (API)

# Install 'libscanR' in R:
install.packages('libscanR', repos = c('https://cttir.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cttir/libscanr/issues

Pkgdown/docs site:https://cttir.github.io

On CRAN:

Conda:

4.35 score 7 scripts 56 exports 47 dependencies

Last updated from:eccbb3e50d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK267
source / vignettesOK311
linux-releaseOK216
macos-releaseOK173
macos-oldrelOK181
windows-develOK200
windows-releaseOK187
windows-oldrelOK198
wasm-releaseOK131

Exports:is_libs_calibrationis_libs_datasetis_libs_spectrumls_average_shotsls_baselinels_build_mapls_calibratels_calibrationls_classifyls_clusterls_cropls_datasetls_demo_peaksls_element_dbls_example_datals_export_spectrals_find_peaksls_gate_optimizels_identify_peaksls_lodls_loqls_map_elementsls_normalizels_pcals_peak_areals_plot_calibrationls_plot_element_mapls_plot_loadingsls_plot_mapls_plot_map_panells_plot_overlayls_plot_pcals_plot_plsdals_plot_regionls_plot_residualsls_plot_screels_plot_spectrumls_plsdals_quantifyls_read_aurorals_read_autols_read_csvls_read_dirls_read_sciapsls_read_spectrumls_run_appls_saha_boltzmannls_simulate_spectrumls_smoothls_spectrumls_tissue_classifyls_tissue_discriminatels_train_classifierls_write_csvscale_color_wavelengththeme_libs

Dependencies:base64encbslibcachemclicommonmarkcpp11digestfarverfastmapfontawesomefsggplot2gluegtablehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMatrixmemoisemimeotelpillarpkgconfigpromisesR6rappdirsRColorBrewerRcpprlangS7sassscalesshinysourcetoolstibbleutf8vctrsviridisLitewithrxtable

Calibration and Quantification
From peak area to concentration | Synthetic calibration dataset | Univariate calibration | Visualize | Residual diagnostics | Internal standard calibration | PLS calibration | Quantifying unknowns | LOD and LOQ | Relative elemental amounts under a two-stage LTE model
Rendered fromcalibration-quantification.Rmdusingknitr::rmarkdown

Last update: 2026-11-03
Started: 2026-05-04

Getting Started with libscanR
What is libscanR? | Core data structures | A 5-minute tour | Simulate a spectrum | Plot it | Preprocess: baseline, smooth, normalize | Detect peaks without an atomic reference | Read from a file | Use example datasets | Next steps
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-11-03
Started: 2026-05-04

Preprocessing Workflow
Baseline correction | Normalization | Smoothing | Averaging replicate shots with outlier removal | Cropping | Recommended pipeline
Rendered frompreprocessing-workflow.Rmdusingknitr::rmarkdown

Last update: 2026-11-03
Started: 2026-05-04

Spatial Elemental Mapping
Raster scan dataset | Build a single elemental map | Multi-element panel | Applying a calibration to the map | Hotspot detection
Rendered fromspatial-mapping.Rmdusingknitr::rmarkdown

Last update: 2026-11-03
Started: 2026-05-04

Tissue Classification
Example: 5 simulated tissue types | Exploratory analysis with PCA | Identifying discriminating elements | PLS-DA classification | Rule-based classification with elemental ratios
Rendered fromtissue-classification.Rmdusingknitr::rmarkdown

Last update: 2026-11-03
Started: 2026-05-04

Readme and manuals

Help Manual

Help pageTopics
Subset a LIBS Dataset[.libs_dataset
Subset a LIBS Spectrum by Wavelength[.libs_spectrum
Combine Multiple LIBS Spectra by Stacking Shotsc.libs_spectrum
Dimensions of a Dataset (spectra x channels)dim.libs_dataset
Dimensions of a LIBS Spectrum (shots x channels)dim.libs_spectrum
Test whether an object is a libs_calibrationis_libs_calibration
Test whether an object is a libs_datasetis_libs_dataset
Test whether an object is a libs_spectrumis_libs_spectrum
Number of Spectra in a Datasetlength.libs_dataset
Number of Channels in a LIBS Spectrumlength.libs_spectrum
Average Replicate Shotsls_average_shots
Baseline Correctionls_baseline
Build a Spatial Elemental Mapls_build_map
Build Calibration Curvels_calibrate
Create a LIBS Calibration Modells_calibration
Classify Unknown Spectrals_classify
Cluster LIBS Spectrals_cluster
Crop Spectral Rangels_crop
Create a LIBS Datasetls_dataset
Fictional Peaks for Software Demonstrationsls_demo_peaks
Read a User-Supplied Atomic Line Referencels_element_db
Generate Example LIBS Datasetls_example_data
Export a LIBS Dataset to a Directoryls_export_spectra
Find Emission Peaksls_find_peaks
Gate Delay Optimizationls_gate_optimize
Identify Peaks Against the NIST Line Databasels_identify_peaks
Limit of Detection (3-sigma)ls_lod
Limit of Quantification (10-sigma)ls_loq
Build Maps for Multiple Elementsls_map_elements
Normalize Spectrals_normalize
Principal Component Analysis of LIBS Spectrals_pca
Calculate Peak Areals_peak_area
Plot a Calibration Curvels_plot_calibration
Plot an Element Map (alias)ls_plot_element_map
Plot PCA Loadingsls_plot_loadings
Plot an Elemental Mapls_plot_map
Plot Multi-Element Map Panells_plot_map_panel
Overlay Multiple Spectrals_plot_overlay
Plot PCA Scoresls_plot_pca
Plot PLS-DA Resultsls_plot_plsda
Plot a Spectral Region in Detaills_plot_region
Plot Calibration Residualsls_plot_residuals
Plot PCA Variance (Scree Plot)ls_plot_scree
Plot a LIBS Spectrumls_plot_spectrum
PLS-DA Classificationls_plsda
Quantify Element Concentrationls_quantify
Read Applied Spectra / Aurora Datals_read_aurora
Auto-Detect and Read LIBS Datals_read_auto
Read a LIBS Spectrum from CSV (Convenience Wrapper)ls_read_csv
Read All Spectra from a Directoryls_read_dir
Read SciAps LIBS Datals_read_sciaps
Read a LIBS Spectrum from Filels_read_spectrum
Launch the libscanR Shiny Applicationls_run_app
Relative Elemental Amounts under a Two-Stage LTE Modells_saha_boltzmann
Simulate a LIBS Spectrumls_simulate_spectrum
Smooth Spectrals_smooth
Create a LIBS Spectrum Objectls_spectrum
Tissue Classification via LIBSls_tissue_classify
Tissue Discrimination Analysisls_tissue_discriminate
Train a Classifierls_train_classifier
Write a LIBS Spectrum to CSVls_write_csv
Plot a LIBS Datasetplot.libs_dataset
Plot a LIBS Spectrumplot.libs_spectrum
Predict Concentrations from a Calibration Modelpredict.libs_calibration
Print a LIBS Calibrationprint.libs_calibration
Print a LIBS Datasetprint.libs_dataset
Print a LIBS Spectrumprint.libs_spectrum
Wavelength-Based Color Scalescale_color_wavelength
Summary of a LIBS Calibrationsummary.libs_calibration
Summary of a LIBS Datasetsummary.libs_dataset
Summary of a LIBS Spectrumsummary.libs_spectrum
LIBS Theme for ggplot2theme_libs