Analyse light spectra for visual and non-visual (often called
 melanopic) needs, wrapped up in a Shiny App. 'Spectran' allows for the import
 of spectra in various CSV forms but also provides a wide range of example
 spectra and even the creation of own spectral power distributions. The goal of
 the app is to provide easy access and a visual overview of the spectral
 calculations underlying common parameters used in the field. It is thus ideal
 for educational purposes or the creation of presentation ready graphs in
 lighting research and application. 'Spectran' uses equations and action spectra
 described in CIE S026 (2018) <doi:10.25039/S026.2018>, DIN/TS 5031-100 (2021)
 <doi:10.31030/3287213>, and ISO/CIE 23539 (2023)
 <doi:10.25039/IS0.CIE.23539.2023>.

Spectra viewer, organizer, data preparation and property blocks
        from within R or stand-alone. Binary (application) part is 
        installed separately using spnInstallApp() from spectrino package.

Input/Output, processing and visualization of spectra taken with different spectrometers, including SVC (Spectra Vista), ASD and PSR (Spectral Evolution). Implements an S3 class spectra that other packages can build on. Provides methods to access, plot, manipulate, splice sensor overlap, vector normalize and smooth spectra.

A self-tuning spectral clustering method for single or multi-view data. 'Spectrum' uses a new type of adaptive density aware kernel that strengthens connections in the graph based on common nearest neighbours. It uses a tensor product graph data integration and diffusion procedure to integrate different data sources and reduce noise. 'Spectrum' uses either the eigengap or multimodality gap heuristics to determine the number of clusters. The method is sufficiently flexible so that a wide range of Gaussian and non-Gaussian structures can be clustered with automatic selection of K.

Do multi-gene descent probabilities
   (Thompson, 1983, <doi:10.1098/rspb.1983.0072>)
   and special cases thereof
   (Thompson, 1986, <doi:10.1002/zoo.1430050210>)
   including inbreeding and kinship coefficients.  But does much more:
   probabilities of any set of genes descending from any other
   set of genes.