- Added parallelization to batch processor
- Preprocess step now runs in parallel
- Filtering and standarization running in one step to avoid I/O overhead
- It is now possible to save results for every step to resume execution, see save_results option
- Fixed a bug that caused excessive logging when logger level was set to DEBUG
- General improvements to the sorting algorithm
- Fixes a bug that was causing and import error in the mfm module (thanks @neil-gallagher for reporting this issue)
- New CLI tool for training neural networks yass train
- New CLI tool for exporting results to phy yass export
- Separated logic in five steps: preprocess, detect, cluster templates and deconvolute
- Improved Neural Network detector speed
- Improved package organization
- Updated examples
- Added integration tests
- Increased testing coverage
- Some examples include links to Jupyter notebooks
- Errors in documentation building are now tested in Travis
- Improved batch processor
- Simplified configuration file
- Preprocessing speedups
- New stability metric
- New batch module
- Rewritten preprocessor
- A lot of functions were rewritten and documented
- More partial results are saved to improve debugging
- Removed a lot of legacy code
- Removed batching logic from old functions, they are now using the batch module
- Rewritten CLI interface yass command is now yass sort
- Improved logging
- Last release with old codebase
- Fixes bug in preprocessing (#38)
- Increased template size
- Updates deconvolution method
- Adds new neural network module
- Config module refactoring, configuration files are now much simpler
- Fixed bug that was causing spike times to be off due to the buffer
- Various bug fixes
- Updates to input/output structure
- Adds new module for augmented spikes
- Function names changes in score module
- Simplified parameters for score module functions
- Minor changes to setup.py for uploading to pypi
- First release