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@@ -33,9 +33,8 @@ For additional information, please visit our [Wiki](https://hz-b.github.io/rayx/
## Built with RAYX
### RAYX Python Bindings
-[](https://github.com/hz-b/rayx-python)
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To simplify the integration of RAYX into Python-based workflows, we provide Python bindings that allow direct simulation results. The figure above illustrates the simulated output at each element of a beamline using the *RAYX Python Bindings* and *Matplotlib*.
@@ -45,14 +44,14 @@ To add RAYX to your Python project simply install the package by typing: ```pip
[](https://github.com/hz-b/rayx-webapp)
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A lightweight Flask-based web application for visualizing RAYX beamline simulations.
The web app allows users to upload an `.rml` file, trace the beamline using the *RAYX Python bindings*, and interactively inspect the resulting ray distributions as 2D histograms with per-element breakdowns.
### RAYX-UI
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For users who prefer a more visual approach, _rayx-ui_ offers a graphical user interface (GUI) that includes a 3D viewport of the beamline, enabling interactive design and exploration. This GUI provides an intuitive interface to construct and modify beamlines, allowing users to visualize their designs in real-time. _rayx-ui_ not only enhances the design process but also allows users to iteratively optimize configurations based on immediate visual feedback.
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* Automated spectrometer alignment via machine learning
-* Inverse Surrogate Model of a Soft X-Ray Spectrometer using Domain Adaptation
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+* Inverse Surrogate Model of a Soft X-Ray Spectrometer using Domain Adaptation