What is HyperSpy¶
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.
To us this program is a research tool, much like a screwdriver or a Green’s function. We believe that the better our tools are, the better our research will be. We also think that it is beneficial for the advancement of knowledge to share our research tools and to forge them in a collaborative way. This is because by collaborating we advance faster, mainly by avoiding reinventing the wheel. Idealistic as it may sound, many other people think like this and it is thanks to them that this project exists.
HyperSpy has been written by a subset of the people who use it, a particularity that sets its character:
The main way of interacting with the program is through the command line. This is because:
- Our command line interface is agreeable to use thanks to IPython.
- With a command line interface it is very easy to automate the data analysis, and therefore boost productivity. Of course the drawback is that the learning curve is steeper, but we have tried to keep it as gentle as possible.
That said, Graphical User Interface (GUI) elements are provided where there is a clear productivity advantage in doing so. See the jupyter widgets GUI and the traitsui GUI. If you need a full, standalone GUI, HyperSpyUI is for you.
We see HyperSpy as a collaborative project, and therefore we care about making it easy for others to contribute to it. In other words, we want to minimise the “user becomes developer” threshold. To achieve this goal we: