mdaviz 1.2.2

Python Qt6 application to visualize multi-dimensional arrays (MDA) files from synchrotron beamlines.

mdaviz

Python Qt6 application to visualize mda data.

Status Badges

CI/CD	Code Quality	Documentation	Package

Coverage	License	Python	Pre-commit

Features

• Data Visualization: Visualize MDA data with support for 1-D and 2D plots (mesh scans) with matplotlib integration.
• Auto-Load Folders: Automatically loads the first valid folder from recent folders list (can be disabled in the preferences).
• Recent Folders: Remembers recently opened folders for quick access.
• Lazy Loading: Efficient folder scanning with progress indicators for large datasets.
• Curve Management: Add, remove, and style multiple data curves.
• Axis Selection: Select X-axis (positioners), Y-axis (detectors), I0 normalization, and curve unscaling using checkboxes. Axis selection is saved from one file to the next.
• Curve Unscaling: Rescale curves to match the range of other Y curves for better comparison.
• Data Analysis: Basic statistics, cursor measurements, and curve fitting.
• Metadata Search: Searchable metadata to quickly locate specific parameters and settings.
• Cross-Platform: Runs on macOS and Linux (Windows TBD).

Quickstart

Option 1: Install from PyPI (Recommended for users)

Mdaviz is available on PyPI. We recommend creating a dedicated environment:

# Create a simple conda environment
conda create -n mdaviz python=3.12
conda activate mdaviz
pip install PyQt6 Qt6

# Install mdaviz
pip install mdaviz

Once installed, you can run the application at any time using:

conda activate mdaviz
mdaviz

Note:

• PyQt6 and Qt6 are required dependencies that may need to be installed separately via pip as they are not available in conda-forge for all platforms.
• At the APS: PyQt6 requires to install the following library:

sudo yum install xcb-util-cursor

Option 2: Development setup with conda environment

For development and contributing, it is strongly recommended to use the provided conda environment. This ensures all dependencies (including PyQt6) are available and compatible.

# Clone the repo first
git clone https://github.com/BCDA-APS/mdaviz.git
cd mdaviz

# Create and activate conda environment
conda env create -f env.yml
conda activate mdaviz
pip install PyQt6 Qt6

# Install in development mode
pip install -e .

Once installed, you can run the application at any time using:

cd mdaviz
conda activate mdaviz
mdaviz

Always activate the environment before running, testing, or using pre-commit hooks.

Note:

• PyQt6 and Qt6 are required dependencies that may need to be installed separately via pip as they are not available in conda-forge for all platforms.
• At the APS: PyQt6 requires to install the following library:

sudo yum install xcb-util-cursor

Usage

Basic Operation

1. Load Data: Click "Open" (folder icon) and select an MDA file.
2. Select Axes: Use the checkboxes in the data table to select:
   • X: Positioner for the x-axis (only one can be selected)
   • Y: Detectors for the y-axis (multiple can be selected)
   • I0: Normalization detector (only one can be selected)
   • Un: Unscale curves to match the range of other Y curves (requires Y selection on same row)
3. Plot Data: Data will automatically plot based on your selection mode

Plotting Modes

• Auto-add: New curves are added to existing plots
• Auto-replace: New curves replace existing plots
• Auto-off: Manual plotting using buttons

Plot Controls

• Log Scale: Use the "LogX" and "LogY" checkboxes to switch between linear and logarithmic scales.
• Curve Styling: Select different line styles and markers for the selected curve.
• Data Manipulation: Apply offset and scaling factors to individual curves.
• Data Analysis: Basic statistics, cursor measurements, and curve fitting.

Development

Logging and Debugging

Default Behavior: By default, mdaviz logs at the WARNING level, showing only warnings, errors and critical messages (quiet mode).

Command Line Options: You can control the logging level using the --log argument:

# Show only errors and critical messages
mdaviz --log error

# Show warnings, errors, critical messages and info (progress messages, file loading status, and important application events).
mdaviz --log info

# Show all messages including debug information
mdaviz --log debug

Log Files: Log files are automatically created in ~/.mdaviz/logs/ with timestamps. Old log files (older than 1 day) are automatically cleaned up on startup.

Testing

Run all tests:

pytest src/tests

Current test status:

• 223 tests passing with 54% coverage
• 48 skipped tests (GUI tests in headless environment)
• 0 failed tests (all tests are now passing!)

Code Quality

The project uses pre-commit hooks for code quality. Run them before committing:

pre-commit run --all-files

Contributing

1. Fork and clone the repository.
2. Create a new branch for your feature or bugfix.
3. Make your changes and add tests.
4. Run pre-commit and pytest to ensure all checks pass.
5. Submit a pull request.

For a complete installation guide, see https://bcda-aps.github.io/mdaviz/.

Acknowledgements

"This product includes software produced by UChicago Argonne, LLC under Contract No. DE-AC02-06CH11357 with the Department of Energy."