Osl-dynamics

PyPi release: https://pypi.org/project/osl-dynamics/1.2.3/

Changes:
- Analysis:
- Added cycles analysis (TINDA).
- New feature to hierarchically cluster state time courses from different runs.
- Models: subject embedding model for the HMM (SE-HMM).
- Examples: added toolbox paper scripts.
- Docs: updated the Fisher kernel write up.

PyPi release: https://pypi.org/project/osl-dynamics/1.2.2/

**This version was used for the OSL workshop 2023.**

Changes (mainly patching bugs):
- The default learning rate of `config_api.wrappers.train_hmm` is higher (1e-3 -> 1e-2).
- `config_api.wrappers.train_dynemo` also saves a `free_energy` values to the `history` dict.
- Bug in the config API (finding custom functions) was fixed.
- New command line option for using the config API.
- Fixed issue re-initialising variables in Dense layers.

PyPi release: https://pypi.org/project/osl-dynamics/1.2.1/

Changes:
- Docs: 'Using BMRC' page removed from readthedocs, it is now a readme on the repo.
- Analysis:
- `analysis.statistics` module and examples for evoked response and comparing groups.
- Added Fisher kernel analysis code and example.
- Data: enforced `n_window` is odd; fixed bigs in `trim_time_series`.
- Simulation: new simulation class for soft mixtures with subject variability.
- Config API: more complete implementation for performing dynamic network analysis.

PyPi release: https://pypi.org/project/osl-dynamics/1.2.0/

Changes:
- Rewrote the implementation of learnable tensors:
- **This means models trained with previous versions of osl-dynamics are incompatible**.
- Data:
- Fixed ordering bug when loading prepared data.
- Can now load MNE Raw/Epochs fif files.
- SE-DyNeMo: developed a directional version.
- HMM:
- Modified the implementation of hmm.Model.random_state_time_course_initialization.
- Added new methods to calculate the variational free energy and exact model evidence.
- Interface: new simplified config based user interface for the HMM/DyNeMo.
- Logging:
- Replaced print statements with a logger.
- Removed `ncols=98` from tqdm progress bars.
- Post-hoc analysis:
- Updated the functions used to threshold alphas.
- Added the Glasser and AAL parcellation.
- Updated dependencies: now includes mne and seaborn.

PyPI release: https://pypi.org/project/osl-dynamics/1.1.7/.

Changes:
- Compatibility with TensorFlow v2.10+:
- The default behaviour of TensorFlow initialisers was changed in 2.10:
- https://blog.tensorflow.org/2022/09/whats-new-in-tensorflow-210.html.
- This osl-dynamics release ensures the correct behaviour of reseting the model with the latest TensorFlow versions (2.10 and 2.11).
- This release can be used with old TensorFlow versions (<2.10) without a problem.

PyPI release: https://pypi.org/project/osl-dynamics/1.1.6/.

Changes:
- Data: option to parallelise loading and data preparation.
- Models:
- Save method now records the version of osl-dynamics used in the config.yml file.
- HMM/DyNeMo/State-DyNeMo: option to learn diagonal covariances.
- Bugs fixes:
- Calculating static power spectra with one subject
- Power maps were not being saved as images.
- Documentation: major update to tutorials and description of models.