Spectromicroscopy combines spectral data with microscopy,
where typical datasets consist of a stack of microscopic images
taken across an energy range. Due to the data complexity, manual analysis
can be time consuming and inefficient, whereas multivariate analysis tools
not only reduce the time needed but also can uncover hidden trends in the data.
MANTiS is Multivariate ANalysis Tool for Spectromicroscopy developed in Python by 2nd Look Consulting. It uses principal component analysis and cluster analysis to classify pixels according to spectral similarity.
Mantis package and binaries can be downloaded from
Mantis User Guide can be found on the project Wiki pages Home.
Please use the following reference when quoting Mantis
Lerotic M, Mak R, Wirick S, Meirer F, Jacobsen C. MANTiS: a program for the analysis of X-ray spectromicroscopy data. J. Synchrotron Rad. 2014 Sep; 21(5); 1206–1212 [http://dx.doi.org/10.1107/S1600577514013964]