A GUI for electron diffraction data analysis
Project description
AutoLEI
Automated EffortLess MicroED Graphic User Interface (AutoLEI) is an XDS-based GUI designed for real-time and batch processing of MicroED/3DED datasets. It provides a user-friendly platform for rapid, automated data processing and merging of multiple MicroED datasets, with well-designed and significantly streamlining structure determination workflows.
Key Features
- User-Friendly Interface: Simplifies MicroED data processing, requiring minimal manual input.
- Batch Processing: Handles large numbers of datasets with automated workflows.
- Real-Time Data Processing: Provides live feedback during data collection.
- Versatility: Supports diverse samples, including small molecules and proteins workflow.
Installation
Requirements
- Operating Systems: Linux or Windows via WSL (versions 1/2).
- Software Dependencies:
Steps
- Install via pip:
pip install autolei
For historical versions, use:pip install autolei-[version_name].zip
- Manual installation: Follow the steps in the Tutorial for AutoLEI and our Wiki.
Usage
Command-line Usage
-
Launch the GUI:
autolei
Note: The first launch may take slightly longer as dependencies initialize.
-
Configure Settings:
autolei_setting
The opened .ini file includes settings on screen scaling, multi-thread and report format.
-
Import Instrument:
autolei_add_instrument [instrument_setting_file]
GUI pages
AutoLEI is organised into multiple working pages:
- Input: Configure experiment parameters and generate input files.
- XDSRunner: Automate initial processing and data quality inspection.
- CellCorr: Update unit cell information and refine settings.
- XDSRefine: Fine-tune processing parameters, including rotation axis and scaling.
- MergeData: Filter and merge datasets for downstream analysis.
- Cluster&Output: Perform clustering and generate outputs for structure determination.
- Expert: Miscellaneous tools for data reduction and PETS related function.
- RealTime: Live data processing with real-time feedback and automatic merging.
Documentation
Detailed guides and examples can be found in:
Authors and Acknowledgments
Developed by Lei Wang and Yinlin Chen. Contributions from Gerhard Hofer, Hongyi Xu, and Xiaodong Zou at Stockholm University. The project integrates valuable resources from edtools.
Supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 956099 (NanED − Electron Nanocrystallography−H2020-MSCAITN).
License
The software is licensed under the BSD 3-Clause License.
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