EasyScience is a Python/QML framework for data analysis being developed to speed-up the time from data collection to publication. Users will be able to both view and model their data using a variety of popular field dependent engines or calculators within a friendly graphical interface or through a Jupyter notebooks.
Current success stories are for the fields of powder neutron diffraction and reflectometry where profiles based on user defined models are simulated and refinement against experimental data.
Simulation of diffraction patterns based on structural models and refinement against experimental data.
Integrates such crystallographic data analysis libraries as CrysPy and CrysFML.
Visit easydiffraction.org
Simulation of reflectometry profiles based on layered structures and refinement against experimental data.
Integrates such reflectometry data analysis libraries such as refnx and refl1d.
Visit easyreflectometry.orgAnyone is free to use EasyScience-based applications and the source code is openly shared on GitHub.
EasyScience-based applications works across operating systems: macOS, Windows, or Linux.
EasyScience-based applications have intuitive tabbed interface with a clear workflow, built-in step-by-step user guides and video tutorials.
EasyScience-based applications are distributed as an all-in-one package that includes all the dependencies and can be installed with only a few clicks.
EasyScience-based applications integrate existing technique-specific libraries, to cover different functionality. Minimization can be done with multiple packages such as lmfit, bumps and DFO-LS.
In EasyScience-based applications, you can modify any parameter manually or with a sidebar slider, and the simulated model curve is automatically recalculated in real time.
For general questions or comments related to EasyScience framework, please contact us at contact@easyscience.software, or fill out the form.
For technique-specific, please use EasyDiffraction, or EasyReflectometry contact forms instead.
