0.6.3

🐛 Bug fixes

• Fix bug in Cavity transfer map bug. (see #129 and #135) (@cr-xu)

🐆 Other

• Add GPL 3 licence (see #131) (@jank324)

0.6.2

🚨 Breaking Changes

• The handling of device and dtype was overhauled. They might not behave as expected. Elements also no longer have a device attribute. (see #115) (@jank324)

🚀 Features

• Add charge to the ParameterBeam and ParticleBeam classes (see #86) (@cr-xu)
• Add opt-in speed optimisations (see #88) (@jank324)

🐛 Bug fixes

• Fix the transfer maps in Drift and Dipole; Add R56 in horizontal and vertical correctors modelling (see #90) (@cr-xu)
• Fix fringe_field_exit of Dipole is overwritten by fringe_field bug (see #99) (@cr-xu)
• Fix error caused by mismatched devices on machines with CUDA GPUs (see #97 and #115) (@jank324)
• Fix error raised when tracking a ParameterBeam through an active BPM (see #101) (@jank324)
• Fix error in ASTRA beam import where the energy was set to float64 instead of float32 (see #111) (@jank324)
• Fix missing passing of total_charge in ParameterBeam.transformed_to (see #112) (@jank324)
• Fix Cavitiy.__repr__ printing voltage value for phase property (see #121) (@jank324)

🐆 Other

• Add pull request template (see #97) (@jank324)
• Add Acknowledgements section to README (see #103) (@jank324)
• benchmark directory was moved to desy-ml/cheetah-demos repository (see #108) (@jank324)
• Update citations to new arXiv preprint (see #117) (@jank324)
• Improve the docstring with proper units for the phase space dimensions (see #122) (@cr-xu)
• Link to the new paper (on arXiv) in the documentation (see #125) (@jank324)

0.6.1

🐛 Bug fixes

• Fix issue where converters submodule was not installed properly (see 1562496) (@jank324)

0.6.0

🚨 Breaking Changes

• Cheetah elements are now subclasses of torch.nn.Module, where the parameters should always be torch.Tensor. This makes cheetah a fully differentiable simulation code. (see #11)
• The cell keyword argument of cheetah.Segment has been renamed to elements.
• Element and beam parameters must now always be passed to the constructor or set afterwards as a torch.Tensor. It is no longer possible to use float, int or np.ndarray. (see #11)

🚀 Features

• Convert from Bmad lattices files (see #65) (@jank324)
• Add proper transfer map for cavity (see #65) (@jank324, @cr-xu)
• Twiss parameter calculation and generate new beam from twiss parameter (see #62) (@jank324, @cr-xu)
• Saving and loading lattices from LatticeJSON (see #9) (@cr-xu)
• Nested Segments can now be flattened (@jank324)
• Ocelot converter adds support for Cavity, TDCavity, Marker, Monitor, RBend, SBend, Aperture and Solenoid (see #78) (@jank324)

🐛 Bug fixes

• Fix dependencies on readthedocs (see #54) (@jank324)
• Fix error when tracking ParameterBeam through segment on CPU (see #68) (@cr-xu)

🐆 Other

• Add CHANGELOG.md (see #74)
• Improved documentation on converting Marker object into cheetah (see #58) (#jank324)

0.5.19

🚀 Features

• Better error messages when beam and accelerator devices don't match (@FelixTheilen)

🐛 Bug fixes

• Fix BPM issue with ParameterBeam (@FelixTheilen)
• Fix wrong screen reading dimensions (@cr-xu)

🐆 Other

• Improve docstrings (@FelixTheilen)
• Implement better testing with pytest (@FelixTheilen)
• Setup formatting with black and isort as well as flake8 listing (@cr-xu)
• Add type annotations (@jank324)
• Setup Sphinx documentation on readthedocs (@jank324)

0.5.18

🐛 Bug Fixes

• Fix issue where multivariate_normal() crashes because cov is not positive-semidefinite.

0.5.17

🚀 New Features

• Faster screen reading simulation by using torch.histogramdd()

0.5.16

🐛 Bug Fixes

• Fix bug where some screens from the ARES Ocelot lattice were converted to Drift elements.

0.5.15

🚀 New Features

• Ocelot has been removed as a mandatory dependency and is now only needed when someone wants to convert from Ocelot objects.

🐛 Bug Fixes

• An error that only packages with all dependencies available on PyPI can be installed from PyPI has been fixed.

0.5.14

🚀 Features

• Introduce black for code formatting and isort for import organisation.
• Prepare release on PyPI as cheetah-accelerator.