Integrated data converter.
Data preprocessing: alignment, normalization…
Principal component analysis (PCA).
Cluster analysis for classifying pixels according to spectral similarity.
SVD for composition map calculation.
Peak identifier and Xray peak fitting.
NNMA analysis.
Tomographic reconstruction with Compressed Sensing.


Code Repository

New Python 3 version of Mantis is available on Github.

Mantis on Github


MANTiS was developed by 2nd Look Consulting with the support from Argonne National Laboratory, The Advanced Photon Source, Diamond Light Source and McMaster University and contributions from Benjamin Watts (Paul Scherrer Institute) and Jan-David Förster (Max Planck Institute for Chemistry).


[1] 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
[2] Mak R, Lerotic M, Fleckenstein H, Vogt S, Wild SM, Leyffer S, Sheynkin Y, Jacobsen C. Non-Negative Matrix Analysis for Effective Feature Extraction in X-Ray Spectromicroscopy. Faraday Discussions. 2014 Apr; 171
[3] Lerotic M, Jacobsen C, Gillow JB, Francis AJ, Wirick S, Vogt S, Maser J. Cluster analysis in soft X-ray spectromicroscopy: Finding the patterns in complex specimens. Journal of Electron Spectroscopy and Related Phenomena. 2005 Jun; 144–147, p:1137-1143
[4] Lerotic M, Jacobsen C, Schäfer T, Vogt S. Cluster analysis of soft X-ray spectromicroscopy data. Ultramicroscopy. 2004 Jul; 100(1–2), p:35-57