Squalar Spectral Map is a simple package that takes a term-document matrix, calculates a term co-occurrence matrix, calculates its eigendecomposition with SVD, and finally maps terms to the visible spectrum by comparing a term's co-occurrence vector to the eigenvectors. Third-party work includes Svdlib by Adrian Kuhn and David Erni, and an image of the visible spectrum by Deborah S Krolls (http://commons.wikimedia.org/wiki/File:Spectrum4websiteEval.png). Two files are needed to create the document spectrum: 1) Libsvm-formatted sparse term-document matrix. 2) Ordered list of index terms. The class org.squalar.spectralmap.Decompose will perform the decomposition (see the javadoc for parameters). Based on the decomposition, the class org.squalar.spectralmap.TermSpectrum will create a png image of the spectrum of a given term (see the javadoc for parameters). For more details and publications, visit http://squalar.org.