The Daniel K. Inouye Solar Telescope (DKIST) continues to push the boundaries of solar observation, and its Diffraction-Limited Near-Infrared Spectropolarimeter (DLNIRSP) delivers some of the most detailed near-infrared solar data available today. To keep pace with new instrument capabilities and user feedback, the development team has rolled out dkist-processing-dlnirsp 1.6.3rc1, a release candidate for the official DLNIRSP data processing pipeline.
Release candidates (RCs) are pre-stable versions of software, designed for testing by instrument teams, early adopters, and power users before general release. This guide breaks down everything you need to know about dkist-processing-dlnirsp 1.6.3rc1, from new features to installation steps.
What’s New in dkist-processing-dlnirsp 1.6.3rc1?
This release focuses on improving processing accuracy, reducing runtime, and adding quality-of-life improvements for regular DLNIRSP users. Key updates include:
Core Feature Updates
- Enhanced Polarimetric Calibration: Improved correction algorithms for DLNIRSP’s 1.0–1.7 micron bandpasses, reducing systematic errors in full-Stokes spectropolarimetric data by up to 12% in internal tests.
- Optimized Memory Management: Reworked data loading routines cut memory usage by 30% when processing large DLNIRSP data cubes, making the pipeline more accessible to users with mid-range workstations.
- New Batch Processing CLI: A dedicated command-line tool for processing multiple DLNIRSP observation sets in sequence, with built-in error logging for failed calibration steps.
- Updated Wavelength Solution: Fixed edge-case errors in wavelength calibration for DLNIRSP’s multi-slit observing mode, ensuring consistent spectral alignment across all slits.
Bug Fixes
- Resolved a rare crash when processing dark frames with non-standard exposure times.
- Fixed incorrect flat field normalization for observations taken with DLNIRSP’s polarimetric modulation optics.
- Patched a permissions error when writing processed data to network-attached storage.
Who Should Upgrade to 1.6.3rc1?
Release candidates are not recommended for production pipelines or users processing data for published research. Instead, this version is best for:
- DLNIRSP instrument team members validating new calibration procedures.
- Early adopters testing new pipeline features for upcoming observation campaigns.
- Beginners learning DLNIRSP data processing, who can test the RC in an isolated virtual environment.
If you rely on stable, validated processing for critical work, stick to the current stable release (1.6.2) until 1.6.3 launches officially.
How to Install dkist-processing-dlnirsp 1.6.3rc1
Follow these steps to install the release candidate safely, without overwriting your existing stable pipeline installation:
- Create a dedicated virtual environment:
python -m venv dkist-dlnirsp-rc-test - Activate the environment:
- macOS/Linux:
source dkist-dlnirsp-rc-test/bin/activate - Windows:
dkist-dlnirsp-rc-test\Scripts\activate
- macOS/Linux:
- Install the release candidate via pip:
pip install dkist-processing-dlnirsp==1.6.3rc1 - Verify the installation:
python -c "import dkist_processing_dlnirsp; print(dkist_processing_dlnirsp.__version__)"– this should return1.6.3rc1.
Always back up your existing pipeline configuration and processed data before testing pre-release software.
Known Issues in 1.6.3rc1
The development team has flagged a few known limitations for this release candidate:
- Limited support for DLNIRSP data taken before 2023, with some legacy calibration files not yet compatible with the new wavelength solution routine.
- Rare segmentation faults when processing extremely large (>100 GB) DLNIRSP data cubes on systems with less than 32 GB of RAM.
- Documentation for the new batch processing CLI is still in draft form, with full guides coming in the stable release.
Report any additional bugs or unexpected behavior to the official DKIST processing GitLab repository.
When Will the Stable 1.6.3 Release Launch?
DKIST software release candidates typically have a 2–4 week testing window, depending on the volume of bug reports. If no critical issues are found, the stable 1.6.3 release is expected to launch in late Q2 2024, with full support for all DLNIRSP data formats and complete documentation.
Final Thoughts
The dkist-processing-dlnirsp 1.6.3rc1 release candidate brings meaningful improvements to DLNIRSP data processing, from better polarimetric accuracy to faster runtime for large datasets. While it’s not ready for production use yet, testing this RC helps the development team catch issues early and shape the stable release to better fit user needs.
Ready to get started? Head to the PyPI page for dkist-processing-dlnirsp 1.6.3rc1 to download the package, or check the DKIST data processing documentation for more guides.
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