Releases: pycroscopy/sidpy
0.12.3
0.12.1
Small but important update:
- updates to some of the visualizers (spectrum visualizer for example)
- bug fix to Sidpy Fitter class that was preventing proper scaling with multiple workers
- changes on the backend regarding getting and setting dimensions
- additional tests
0.12.0
New version of sidpy has been released. The major change is that previous operations that would have resulted in return of numpy or dask arrays are now programmed to return sidpy dataset objects. This is particularly useful for instance when wishing to crop, slice, and perform standard arithmetic operations on sidpy datasets. The sidpy.fitter class has been updated to allow for complex datasets. An example notebook is provided here
In addition to this major change, there are minor bug fixes throughout to deal with changes/deprecations to numpy, matplotlib, etc. If you run into issues with the new version, please let us know. We expect that given this substantial change, not every workflow will operate as normal without any modification. If this occurs, most likely you simply have to convert the sidpy dataset to a numpy array when it fails in your codebase.
0.11.2
0.11.1
0.11
Small update to sidpy. Changes since last version:
- Added CHANNEL dimension type for sidpy dimensions (for example of usage see this link) . This is useful for multi-channel spectral datasets, which can now be plotted using the intrinsic .plot() method
- Added updated capability on spectral visualizer to enable plotting of multi-channel spectra
- Small changes with set_dimension() method to be more robust
- Minor bug fixes
- Updates to various tests
0.10
This release adds a few 'under the hood' changes to the sidpy dataset object, with respect to chunking and folding/unfolding. Some minor edits to some visualization functions were also made. A new method visualize_fit_results() to the SidFitter class was added to aid in visualization of functional fits.
