- Added explicit support for NumPy 2, in addition to NumPy 1.
- Made image autorange and histogram more robust (#28).
- Fixed an issue where migrating older datasets to add a diffraction center automatically could fail (#26).
- Added new Bragg peak functionality of processed datasets, as well as arbitrary mask loading and generation for pre-processing.
- Fixed an issue when computing azimuthal averages (#18).
- Fixed some issues with new versions of Python and PyQt5 (#16) and other maintenance (#17).
- Fixed an issue where iris would use up all available memory for datasets with a large number of time-delays (>500)
- Releases are now automatically performed using Github Actions
- Added the :meth:`DiffractionDataset.mask_apply` to modify the diffraction pattern mask.
- The center of diffraction is now calculated and updated as needed automatically.
- Better handling of write permissions.
- Added the :class:`MigrationWarning` and :class:`MigrationError` classes. Warnings/errors of these classes tell the user that migration should be performed. This is automatically done by opening a :class:`DiffractionDataset` with writing permission. The GUI does this automatically.
- Windows installers are now built with pynsist/NSIS instead of PyInstaller (#15).
- Support for Python 3.6 and NumPy<1.17 has been dropped
- Fixed an issue where creating the plug-in directory would rarely fail.
- Parallel operations on datasets (via HDF5 single-writer multiple-reader) is now possible on all platforms.
- Code snippets in documentation are now tested for correctness.
- Migration of test infrastructure to pytest.
- Tests are now included in source distributions.
- Added support for h5py 3.*.
- Re-licensing iris-ued to GPLv3.
- Changed the default colormap for processed datasets, to visually distinguish between raw and processed data viewers
- Added support for Python 3.9
- Fixed an issue where a broken plug-in would crash Iris. Instead, broken plug-ins will not be loaded.
- Added the DiffractionDataset.time_series_selection method, which allows to create time-series integrated across an arbitrary momentum-space selection mask. This allows to create time-series from shapes that are not rectangular, at the expense of performance.
- Added a few methods to create selection masks: DiffractionDataset.selection_rect, DiffractionDataset.selection_disk, and DiffractionDataset.selection_ring.
- Added the ability to show/hide dataset control bar;
- Added the ability to export time-series data in CSV format;
- Fixed an issue where calculations of time-series, relative to pre-time-zero, would raise an error.
- Symmetrization dialog is no longer in "beta".
- Official support for Linux.
- Plug-ins installed via the GUI can now be used right away. No restarts required.
- Added the iris.plugins.load_plugin function to load plug-ins without installing them. Useful for testing.
- Plug-ins can now have the
display_name
property which will be displayed in the GUI. This is optional and backwards-compatible. - Siwick Research Group-specific plugins were removed. They can be found here: https://github.com/Siwick-Research-Group/iris-ued-plugins
- Switched to Azure Pipelines for continuous integration builds;
- Added cursor information (position and image value) for processed data view;
- Fixed an issue where very large relative differences in datasets would crash the GUI displays;
- Fixed an issue where time-series fit would not display properly in fractional change mode;
- Added logging support for the GUI component. Logs can be reached via the help menu
- Added an update check. You can see whether an update is available via the help menu, as well as via the status bar.
- Added the ability to view time-series dynamics in absolute units AND relative change.
- Pinned dependency to scikit-ued, to prevent upgrade to scikit-ued 2.0 unless appropriate.
- Pinned dependency to npstreams, to prevent upgrade to npstreams 2.0 unless appropriate.
- Fixed an issue where the QDarkStyle internal imports were absolute.
- Fixed an issue where data reduction would freeze when using more than one CPU;
- Removed the auto-update mechanism. Update checks will run in the background only;
- Fixed an issue where the in-progress indicator would freeze;
- Moved tests outside of source repository;
- Updated GUI stylesheet to QDarkStyle 2.6.6;
- Added explicit support for Python 3.7;
- Usability tweaks, for example more visible mask controls;
- Added the ability to create standalone executables via PyInstaller;
- Added the ability to create Windows installers;
- Due to new forced image orientation, objects on screens were not properly registered (e.g. diffraction center finder).
- Added the ability to fit exponentials to time-series;
- Added region-of-interest text bounds for easier time-series exploration
- Enforced PyQtGraph to use row-major image orientation
- Datasets are now opened in read-only mode unless absolutely necessary. This should make it safer to handler multiple instances of iris at the same time.
- Better plug-in handling and command-line interface.
The major change in this version is the ability to guess raw dataset formats using the iris.open_raw function. This allows the possibility to start the GUI and open a dataset at the same time.
The package now only has dependencies that can be installed through conda
This is a minor bug-fix release that also includes user interface niceties (e.g. link to online documentation) and user experience niceties (e.g. confirmation message if you forget pixel masks).
This new version includes a completely rewritten library and GUI front-end. Earlier datasets will need to be re-processed. New features:
- Faster performance thanks to better data layout in HDF5;
- Plug-in architecture for various raw data formats;
- Faster performance thanks to npstreams package;
- Easier to extend GUI skeleton;
- Online documentation accessible from the GUI;
- Continuous integration.