lys documentation

lys is a Python-based multi-dimensional data analysis and visualization platform based on several popular libraries such as numpy, dask, matplotlib, and Qt.

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To use lys, go to Installation and Tutorial. Source code of lys is opened in GitHub (https://github.com/lys-devel/lys).

What lys can do in visualization:

  • Publication-quality visualization of 1D and 2D data, which can be edited by GUI interface.

  • Interactive, intuitive, and flexible visualization of multi-dimensional (> 3D) data based on GUI.

  • Creating an animation based on the multi-dimensional data.

  • Saving graphics in editable format, or standard vector/raster format (png, eps, pdf, …).

What lys can do in analysis:

  • Applying pre-defined and user-defined processes (such as smoothing, interpolation, fast Fourier transform, and integration) to multi-dimensional data.

  • Exporting arbitrary data analysis as a file, which can be used to reproduce the scientific result.

  • Executing arbitrary Python command in CUI interface, supporting flexible analysis.

  • Standard fitting for 1D data.

Characteristics of lys:

  • Low code: Most of operation can be done without coding.

  • Intuitive: GUI-based visualization and analysis for users who are not familier with scientific Python libraries.

  • Parallelized: Automatic parallel computation using dask can be done in high-performance computers.

  • Extendable: Both CUI and GUI can be customized by users.

  • Open source: Free to use. You can confirm what is done in lys and change it.

How lys differs from other similar softwares:

  • It employs Python (numpy/dask) as a backend. Variety of scientific computing libraries such as scipy can be used. This cannot be achieved by similar softwares such as Igor Pro and Matlab.

  • It is open source software. Users can confirm what is done in lys and modify it. This cannot be realized in proprietary softwares.

  • lys offers interactive GUIs, which lacks in the scientific Python ecosystems.

  • lys can treat massive multi-dimensional array more than hundreds of gigabites through dask. Coexistence of intuitive GUI and fast parallel calculation also lacks in other similar software/libraries.

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