Scikit-xray provides simple functions useful for X-ray science, conveniently grouped by technique. It includes domain-specific functionality written for this package and also relevant functions from other scientific packages such as scikit-image. Thus, it is a complete solution, curating useful tools from the scientific Python community and presenting them in a context for X-ray science.
There are several ways to use scikit-image. Users comfortable with Python, IPython, or the IPython notebook can use it like any other package. Users who prefer drag-and-drop software can access all the tools in scikit-image through vistrails.
Scikit-xray functions accept and return standard Python and numpy datatypes, so they play nicely with other packages from the scientific Python community. Further, the modular design of scikit-xray allows its components to be easily reused in way not envisioned by the authors.
Scikit-xray is being developed to support X-ray techniques at the beamlines listed in the Supported Beamlines section.
Powder Diffraction
X-ray Fluorescence
Image Segmentation
Tomography
- Absorption
- Fluorescence
1-time correlation
Scikit-image is developed in collaboration with beamline scientists at the following beamlines.
NSLS-II
Scikit-xray is part of the Nikea software organization supported by the Brookhaven National Lab.