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The Paul toolbox for python-based scientific data analysis.

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paul

Paul is a visual data navigation and analyis tool written on top of Python, Qt4, IPython, Numpy and Matplotlib (just to name the most prominent dependencies). It's basically a series of scripts for easier everyday handling of "normal" scientific data. '"normal" scientific data' in this context means what you would usually get out of spectral analysers, tunneling microscope images etc. In my case, it means data from angle-resolved photoelectron spectroscopy.

It allows point-and-view displaying of scientific spectra, integrates a Matplotlib viewer with an easy-to-use file navigator and offers powerful live data introspection and processing from an integrated IPython shell.

It features some useful ideas borrowed from a commercial data analysis tool called IgorPro(tm) made by Wavemetrics, a number of data reading/writing functions for various more or less obscure scientific data formats, and some new ideas.

Here's an incomplete feature list:

Supported data formats

  • Reading and writing if IgroPro(tm) IBW files (binary waves)

  • Reading and unpacking of IgorPro(tm) PXP and PXT files (packed experiment files)

  • Reading of Elmitec's proprietary LEED/LEEM image format (used in low electron energy microscopy)

  • Generating of IgorPro(tm) UXP (Unpacked Experiment Files) for easier exchange of data between Paul and Igor.

Data processing

  • Implementation of a Wave class, i.e. a numpy.ndarray subclass that can handle intrinsic scaling information as typically used in IgorPro(tm) -- arguably one if its most powerful features.

  • Implementation of indexing/slicing algorithms in Wave based not the coordinate system of the intrinsic scale (i.e. data slicing can be done not only like foo[x,y,z], but also like foo(p,q,r), where p,q,r are index objects specifying position information in the coordinate system intrinsic to the data.

  • Basic functions for common data analysis tasks (slicing of data, generating of waterfall diagrams etc) that take advantage of the Wave interface.

  • Ability to use plot specification scripts in order to define Matplotlib visualisation presets and data plots -- a good idea also borrowed from IgorPro(tm).

  • The ability to modularly "blend into" a Unix environment, manipulate IBW data files (...or possibly others; interface is easily extensible) without the need to load / write large, opaque, binary data files (think IgoroPro(tm)'s PXP files) which cannot be manipulated except by a single, monolithic system. Its integrability is arguably one of the most powerful features of Paul; in fact, Paul was extensively used in scientific day-to-day business within Unix Makefile setups to automatically generate graphs from data files and lot specifitation scripts.

Data visualization and interaction

  • paul-viewer: a scripting-based Matplotlib plotting application similarly to the GUI displayed by Pylab (in fact, it makes heavy use of the Matplotlib's FigureCanvas object :-) ) with the ability to load and automatically reload the plotting script when modified on disk.

  • paul-browser: a click-and-display data browser application, allowing to quickly skim through 1D or 2D data files on disk.

  • paul-shell: a module to expose as much functionality of paul-browser and paul-viewer to the IPython command line, making Paul integration with the Spyder toolset easier.

Project Status / Usability

Consider the status a "usable prototype". Most of the code that appears to be working does indeed work robustly and was used to analyze data and generate graphs for various high-ranking publications. Formal documentation is lacking, but many portions of the code, in particular the science-heavy parts, are very well explained & documented. Writing few examples of how to rapidly start using it would probably go a long way in helping to get a new user started.

Data exchange code, in particular reading / writing of IBW and UXP files has received a large amount of testing and can be considered fairly robust; writing of UXP could still be a little buggy. However, data exchange is probably out of date with regards to newer versions of the file formats. Code state is from around 2014, I assume IgorPro(tm) will have moved along with its formats during that time.

Architecture of the system is in principle validated, but largerly undocumented, and in an unfinished state.

On the plus side, the codebase is fairly small and still possible to understand and modify/refactor by a single person or a small group of developers.

The project is mostly orphaned, meaning that I don't actively work on it anymore, although I would love to see it continued. If you feel inclined, let me know, and I'll support to you the best of my abilities.

The Paul package is released under GPL-v3.

-- Florin Boariu <florin.p(at)rootshell.ro>

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The Paul toolbox for python-based scientific data analysis.

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