v1.3.1
PyPi release: https://pypi.org/project/osl-dynamics/1.3.1/
Changes:
- Models:
- The efficiency of the model initialisation methods (
random_subset_initialization
,random_state_time_course_initialization
) was improved (minimised the number of shuffles). - Methods was updated to ensure a TensorFlow (TFRecord) Dataset can be passed.
- Improvements to H/DIVE:
- Modification to the calculation the KL term in the loss.
- Ability to pass multiple embeddings.
- The efficiency of the model initialisation methods (
- Data object:
- Option to pass arbitrary auxiliary inputs to models when creating datasets with the Data object.
- Option to save/load TFRecord datasets (useful for training on very large datasets).
- Simulation classes:
random_seed
argument was removed - this may cause old scripts to error due to the unexpected argument (can just be deleted in the script). The user can useosl_dynamics.utils.misc.set_random_seed
to ensure scripts are deterministic now.
- Plotting:
- Improved spatial map plotting to work with fMRI data (can now handle cifti files).