HyperSpy: multidimensional data analysis toolbox

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multidimensional datasets that can be described as multidimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

HyperSpy aims at making it easy and natural to apply analytical procedures that operate on an individual signal to multidimensional arrays, as well as providing easy access to analytical tools that exploit the multidimensionality of the dataset.

Its modular structure makes it easy to add features to analyze different kinds of signals. Currently there are specialized tools for electron energy-loss spectroscopy (EELS) and energy dispersive X-rays (EDX) data analysis.


HyperSpy provides tools that operate on numpy arrays without subclassing them and therefore it is fully compatible with the scientific Python ecosystem. It provides, amongst others:

  • Named and scaled axes.
  • Axes indexing by name.
  • Non-equivalent axes: HyperSpy distinguishes between signal and navigation axes.
  • Iteration over the navigation axes.
  • Advanced data indexing capabilities including separate indexing for the signal and navigation axes and data indexing using using axis units.
  • Visualization tools for n-dimensional spectra and images based on matplotlib.
  • Curve fitting.
  • Easy access to machine learning e.g. PCA, ICA...
  • Reading and writing of multidimensional datasets in multiple file formats.
  • Modular design for easy extensibility.
  • Specialized classes for electron-energy loss spectroscopy (EELS) and energy-dispersive X-rays (EDX) data analysis.

HyperSpy is released under the GPL v3 license and is actively developed and used in research (see the Bibliography section of the User Guide)


Citing HyperSpy

Published on 2015-04-15

HyperSpy can now be cited using our brand new D.O.I. See how to cite HyperSpy or click on the DOI badge below for details.

HyperSpy 0.8 has been released!

Published on 2015-04-07

We are proud to announce a new release of Hyperspy.

Read more…

HyperSpy Workshop @ Cambridge (UK), 13th of April 2015

Published on 2015-03-18

Multi-dimensional data analysis with Python and HyperSpy Workshop. Registration and more information here.

Citing HyperSpy

All of the authors of HyperSpy are connected with academic and scientific research, so it is important to us to be able to show the impact of our work in other projects and fields.

If HyperSpy contributes to a project that leads to a scientific publication, please acknowledge this fact by citing the project. Please, read on how to cite HyperSpy here