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OASIS: Fast online deconvolution of calcium imaging data

Tools for extracting the neural activity from fluorescence calcium imaging data  

The code can be readily run on neural temporal fluorescence calcium imaging data. Please have a look at the demo.

Requirements

The package is tested on Linux, macOS, and Windows with Python 3.8–3.14. Dependencies (numpy, scipy, matplotlib) are handled automatically by pip.

Optionally, to perform comparisons with interior point methods:

Installation

Package based

The easiest way to install OASIS is using either pip:

pip install oasis-deconv

or if you are using conda (or mamba):

conda install -c conda-forge oasis-deconv

However, you won't have the examples provided in the GitHub repo.

Compile from source

Alternatively you can clone the repo

git clone git@github.com:j-friedrich/OASIS.git
cd OASIS

and install using pip, which will automatically compile the Cython extensions:

pip install .

For development, use an editable install (Python files take effect immediately; Cython files still require a reinstall when changed):

pip install -e .

Examples

The scripts to produce the figures and table are in the subfolder 'examples' with names obvious from the PLoS Comput Biol paper. They can be run with python examples/fig[1-6].py.

The results of fig4 and table1 will be even better than in the paper, because the version in the master branch includes later improvements, in particular up to an order of magnitude less computing time. The specific points in history marking the time of the publications have been tagged.

To demonstrate how to use the methods on your own data, we included a demo jupyter notebook in the subfolder 'examples' as well.

Other implementations

Related packages

In order to deal not just with temporal, but with raw spatio-temporal fluorescence data, we added OASIS also to CaImAn, the computational toolbox for large scale Calcium Imaging Analysis.

References

The code accompanies a short NIPS paper and an extended journal version with full details. If you use our code in your research, please cite one of them:

Project links

Data verified by PyPI on Jul 15, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

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Credits

Author: Johannes Friedrich

GitHub Statistics

Data verified by PyPI on Jul 15, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

GPL-3.0

Requires

Python >=3.8

Provides Extra

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This release

0.3.2 This release

21 files

0.3.1

31 files

0.3.0

31 files

0.2.1

7 files

0.2.0

6 files

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