Releases: flatironinstitute/CaImAn
Releases · flatironinstitute/CaImAn
1.9.1
1.9.0
- Added a CHANGELOG.txt to the repo noting changes that significantly change usage concerns
- Implemented a new (optional) way of managing storage that doesn't use the working directory (which is not well-defined for notebooks). You can enable this with an environment variable. Larger changes to storage are in the works.
- Clean up code around type() and isinstance() to better handle future changes to Python
- Smaller changes around string interpolation in some parts of the code
- Remove some more old python2 compatibility measures
- Progress bars (enable with an env var) thanks to EricThomson
- h5py pin for tensorflow
Please report any issues relating to storage paths, and please try the new env var.
1.8.9
This release moves us to python 3.7 and 3.8 being the supported python revisions for CaImAn, and also (because of upstream packaging changes in conda) marks a move to Tensorflow 2.2+ as our supported version. All diffs after this release may introduce dependencies on Python 3.7 and Tensorflow 2.2+.
Other changes:
- Made intro doc more focused on software installation
- Added reference to another volpy paper
- Updated setup.py to add current contact information
- Removed software pins that were no longer necessary
- update_temporal_components() - small improvements in docs
1.8.8
- Improved error handling for input
- Improvements to demo_dendritic
- VolPy paper datafiles
- Add exceptions to catch problems in background extraction
- small adjustments to perf guide
- other volpy improvements
- Remove obsolete demos
- Fix serialisation issues with motion correction init code
1.8.7
1.8.6
1.8.5
1.8.4
v1.8.3
1.8.2
- GUI: Fix some visualisations
- Motion correction: Improved validation for setup, to catch rare issues
- Fix some incorrect parameters in the memmap code
- CNMF: Some improved defaults
- Jupyter Demos: Fix some issues relating to tighter validation upstream in notebook formatting
- Packaging: Add psutil dependency explicitly in case conda environment does not provide it