dioptas-batch-gui 0.4.2

GUI app for automated batch processing of Lambda detector data with Dioptas

Dioptas Batch Processor GUI

Standalone GUI for automated batch processing of Lambda detector diffraction files using Dioptas.

Features

• Folder watch mode for automatic processing of incoming .nxs / .h5 files
• Manual batch mode for selected files
• CHI export (1D integration)
• NPY export (2D cake arrays: intensity, two-theta, azimuth)
• Optional mask support
• Background processing thread to keep GUI responsive

Project Structure

dioptas_batch_gui/
├── dioptas_batch_gui/
│   ├── __init__.py
│   ├── __main__.py
│   ├── version.py
│   ├── gui.py
│   ├── batch_processor.py
│   └── file_watcher.py
├── dbg/
│   ├── __init__.py
│   └── __main__.py
├── check_dependencies.py
├── pyproject.toml
├── requirements.txt
├── LICENSE
├── CHANGELOG.md
├── CONTRIBUTING.md
└── SECURITY.md

Requirements

• Python 3.10+
• conda (recommended for environment management)

Installation (Recommended)

Set up in this order:

1. Create and activate a conda environment named dioptas.

conda create -n dioptas python=3.10 -y

conda activate dioptas

2. Install Dioptas first inside that environment.

pip install dioptas

3. Install this package.

pip install dioptas-batch-gui

Update to the latest PyPI release

pip install --upgrade dioptas-batch-gui

Force reinstall from PyPI

pip install --upgrade --force-reinstall dioptas-batch-gui

Verify Dependencies

python check_dependencies.py

Usage

Installed CLI commands (work from any directory once your environment is active in terminal or console):

After:

conda activate dioptas

dbg

Compatibility aliases:

dbgui
dioptas_batch_gui
dioptas-batch-gui

For a local checkout, you can also launch the app directly:

python -m dbg

or:

python -m dioptas_batch_gui

Basic Workflow

1. Set Watch Directory or switch to Batch Mode and select files manually.
2. Set Output Directory.
3. Select the Calibration File (.poni).
4. Optionally select a Mask File.
5. Configure integration points and azimuth bins.
6. Choose the export options you want.
7. Click Start Watching for automatic mode or Process for manual batch mode.
8. Click Stop Watching when finished with auto-processing.

Output

For each processed dataset, the app exports:

• <base_name>.chi
• <base_name>-param/<base_name>.int.cake.npy
• <base_name>-param/<base_name>.tth.cake.npy
• <base_name>-param/<base_name>.azi.cake.npy

For HDF5/NXS files containing multiple snapshot images, outputs use a one-based snapshot suffix in the output stem and parameter directory name. When the input stem ends in a numeric scan/index segment, the snapshot suffix is inserted before that final segment:

• xxx_map_1_0001.h5 snapshot 1: xxx_map_1_001_0001.chi
• xxx_map_1_0001.h5 snapshot 2: xxx_map_1_002_0001.chi
• xxx_map_1_001_0001-param/xxx_map_1_001_0001.int.cake.npy

Output layout:

output_directory/
├── <base_name>.chi
└── <base_name>-param/
    ├── <base_name>.int.cake.npy
    ├── <base_name>.tth.cake.npy
    ├── <base_name>.azi.cake.npy
    └── <calibration>.poni

License

GPL-3.0-only. See LICENSE.