v1.1.4
PyPI release: https://pypi.org/project/osl-dynamics/1.1.4/.
This release has a fully validated HMM.
Changes:
- Added the option to add an error to the diagonal of a matrix - can be specified in the config.
- Switched to a fully python based HMM and significantly reduced the training time - also validated against the c-library implementation.
- Added more features to the HMM: learning rate decay for the observation model; option to train on a subset of the full dataset in each epoch.
- Parallelised post-hoc calculation of power/coherence spectra.
- Added new initialisation methods to State-DyNeMo.
- Fixed an important bug in preparing amplitude envelope data.
- Added an option to specify a p-value to decide the threshold of a two-component GMM fit.
- Combined the Data object into one big class, which simplified the docs.