Thème : Time series Analyses

Licence : Logiciel libre (freeware)

Système d’exploitation : Windows, Macintosh, Linux…


Welcome to the official Webpage of the DXM (Digital X Mapping) software.

DXM has been developed at INRA (Institut National de la Recherche Agronomique) in the AMAP laboratory (botAnique et bioinforMatique de l’Architecture des Plantes, France) since 2005, then in the ecology department at IFP (Institut Français de Pondicherry, India) since 2010.

DXM is a convenient tool dedicated to researchers of environmental sciences and for education purposes. DXM aims at analyzing and quantifying time series with the help of non stationary signal analysis methods. Starting from a loaded time series (whatever is its length and time resolution), the software is computing various maps and statistics related to its variability and non-stationnarity properties. Among others, it provides computations of Fourier and Autocorrelation spectra, SSA (Singular Spectrum Analysis), wavelet transform and DXM extended auto-correlations (cyclostationnarity).



Principle and software handling

The two main properties of the DXM software are: i) a set of signal processing analyses for any kind of time series; and ii) the simulation of neutral models (white and brown AR1 noises) for the same time series. DXM is manipulating time series (a data vector) to compute several classic and less used properties to quantify the variable variability: Among others, it provides a Fourier and Auto-correlation analysis, and time-frequency analyses such as SSA (Singular Spectrum Analysis), Wavelet transform and DXM decompositions. It allows to export all results in Jpeg and Ascii formats for further analyses.

As an input, DXM needs an Ascii file containing the time series (a column of the file can be selected for the computations). The user has then to decide in the main menu which property should be analyzed. DXM software then allows to compute neutral (noise) simulations (based on the observed time series and random or AR1 noises) to compute confidence levels on any previous property. The user then comes back to any computation to improve or constrain it by a new parameterization, and to finally save it in various formats for further analyses or for publication.


The DXM software is open-source (Cecill-C licence). Thanks to its flexible and optimized architecture, it is user-friendly to integrate additional properties (on time series) to be computed, with various questions in mind. These new properties will all benefit from the various noise simulations to estimate their associated confidence levels. Researchers and engineers in environmental sciences are welcome to use and develop the DXM software, and to kindly cite it in their documents.

DXM has first been developed with Matlab® routines by Cédric Gaucherel and Audrey Lustig, and has been recently transformed into a free, coherent and open source software with Java® by Bastien Rouy, helped by Romain Frelat (thanks to all!). Several case studies are illustrating the DXM methodology in the author’s publications.


Here, you may find DXM files.

Zip files also contain a sample of input data to be used with the Software.

Just click on Setup-DXM- file to instal the Windows version of the DXM Software. Any enquiry about the software should to be sent to C. Gaucherel.

Short DXM Bibliography

DXM References

  • Gaucherel, C., A study of the possible extended influence of the ENSO phenomenon. Comptes Rendus Geoscience, 2004. 336(3): p. 175-185.
  • Gaucherel, C., Use of wavelet transform for temporal characterization of remote watersheds. Journal of Hydrology, 2002. 269(3-4): p. 101-121.
  • Gaucherel, C., Analysis of ENSO interannual oscillations using non-stationary quasi-periodic statistics: a study of ENSO memory. International Journal of Climatology, DOI: 10.1002/joc.1937 (2010).

See also:



For any questions or remarks, please contact : Cédric Gaucherel