.. _introduction: Introduction to scikit-xray --------------------------- 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. Targeted Techniques ^^^^^^^^^^^^^^^^^^^ Scikit-xray is being developed to support X-ray techniques at the beamlines listed in the Supported Beamlines section. Currently implemented ===================== * Differential Phase Contrast Under active development ======================== * Powder Diffraction * X-ray Fluorescence * Image Segmentation * Tomography * Absorption * Fluorescence * 1-time correlation Planned ======= * Ptychography * Inelastic Scattering * Coherent Diffractive Imaging * 2-time correlation * XANES (1-D, 2-D) Supported Beamlines ^^^^^^^^^^^^^^^^^^^ Scikit-image is developed in collaboration with beamline scientists at the following beamlines. **NSLS-II** * Inelastic X-ray Scattering (IXS) * X-ray Powder Diffraction (XPD) * Coherent Hard X-ray Scattering (CHX) * Coherent Soft X-ray Scattering (CSX) * Submicron Resolution X-ray Spectroscopy (SRX) * Hard X-ray Nanoprobe (HXN) Credit ^^^^^^ Scikit-xray is part of the `Nikea `__ software organization supported by the `Brookhaven National Lab `__.