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| name: ROSS Test | ||
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| on: | ||
| push: | ||
| branches-ignore: | ||
| - master | ||
| pull_request: | ||
| branches: | ||
| - v2 | ||
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| jobs: | ||
| build-linux: | ||
| runs-on: ubuntu-latest | ||
| strategy: | ||
| max-parallel: 5 | ||
| steps: | ||
| - uses: actions/checkout@v3 | ||
| - name: Set up Python 3.9 | ||
| uses: actions/setup-python@v3 | ||
| with: | ||
| python-version: '3.9' | ||
| - name: Add conda to system path | ||
| run: | | ||
| # $CONDA is an environment variable pointing to the root of the miniconda directory | ||
| echo $CONDA/bin >> $GITHUB_PATH | ||
| - name: Install dependencies | ||
| run: | | ||
| conda env update --file environment.yml --name base | ||
| - name: Test with pytest | ||
| run: | | ||
| python -m pytest -q -rf --tb=short --cov-report term-missing --cov=./ |
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| # ROSS v2 | ||
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| ROSS v2 (beta) is the Python version of offline spike sorting software implemented based on the methods described in the paper entitled [An automatic spike sorting algorithm based on adaptive spike detection and a mixture of skew-t distributions](https://www.nature.com/articles/s41598-021-93088-w). (Official Python Implementation) | ||
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| ROSS v2 (alpha) is the Python version of offline spike sorting software implemented based on the methods described in the | ||
| paper | ||
| entitled [An automatic spike sorting algorithm based on adaptive spike detection and a mixture of skew-t distributions](https://www.nature.com/articles/s41598-021-93088-w). ( | ||
| Official Python Implementation) | ||
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| ### Important Note on ROSS v2 | ||
| ROSS v2 is implemented based on the client-server architecture. In the beta version, the GUI and processing units are completely separated and their connection is based on Restful APIs. However, at this moment, it only works on one machine and we try to find a good way to optimize the data transfer between the client and the server. In our final release, you would be able to run the light GUI on a simple machine while the data and algorithms would be executed on a separate server in your lab. | ||
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| ROSS v2 is implemented based on the client-server architecture. In the alpha version, the GUI and processing units are | ||
| completely separated and their connection is based on Restful APIs. Now, you are able to run the light GUI on a simple machine while the data and algorithms would be executed on a | ||
| separate server in your lab. Please carefully read the docs and check our tutorial videos. | ||
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| ## Requirements | ||
| - All the requirement packages are listed at enviroments.yml file in root path | ||
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| - All the requirement packages are listed at environment.yml file in root path | ||
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| ## How to install | ||
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| 1. Git Clone this repository to your local path ```git clone https://github.com/ramintoosi/ROSS``` | ||
| 2. Checkout to v2 ```git checkout v2``` | ||
| 2. Checkout to v2 ```git checkout v2``` | ||
| 3. Create a conda enviroment by command : ```conda env create -f environment.yml``` | ||
| 4. Activate conda environment ```conda activate ross``` | ||
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| ## How to run | ||
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| 1. Run the backend by typing ```python ./ross_backend/app.py``` in the terminal. | ||
| 2. Run the UI by typing ```python ./ross_ui/main.py``` in the terminal. | ||
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| **Note:** If you have a separate server, run ```step 1``` in your server and ```step 2``` in your personal computer. | ||
| 3. The first time you want to use the software, you must define a user as follows: | ||
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| - In opened window, click on ```Options``` ---> ```Sign In/Up``` , enter the desired username and password, click on ```Sign Up```. | ||
| - In opened window, click on ```Options``` ---> ```Sign In/Up``` , enter the desired username and password, click | ||
| on ```Sign Up```. | ||
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| 4. The next time you want to use the software, just click on ```Options``` ---> ```Sign In/Up``` and enter your username and password, click on ```Sign In``` . | ||
| 4. The next time you want to use the software, just click on ```Options``` ---> ```Sign In/Up``` and enter your username | ||
| and password, click on ```Sign In``` . | ||
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| 5. Import your "Raw Data" as follows : | ||
| 5. Import your "Raw Data" as follows : | ||
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| - In opened window, click on ```File``` ---> ```Import``` ---> ```Raw Data``` , select the data file from your system, then, select the variable containing raw-data ```(Spike)``` and click on ```OK```. | ||
| - In opened window, click on ```File``` ---> ```Import``` ---> ```Raw Data``` , select the data file from your system, | ||
| then, select the variable containing raw-data ```(Spike)``` and click on ```OK```. | ||
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| 6. Now you can Go on and enjoy the Software. | ||
| 6. Enjoy the Software! | ||
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| For more instructions and samples please visit ROSS documentation at (link), or demo video at (link). | ||
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| ## Usage | ||
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| ROSS v2, same as v1, provides useful tools for spike detection, automatic and manual sorting. | ||
| ROSS v2, same as v1, provides useful tools for spike detection, automatic and manual sorting. | ||
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| - Detection | ||
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| You can load raw extracellular data and adjust the provided settings for filtering and thresholding. Then by pushing **Start Detection** button the detection results appear in a PCA plot: | ||
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| You can load raw extracellular data and adjust the provided settings for filtering and thresholding. Then by pushing * | ||
| *Start Detection** button the detection results appear in a PCA plot: | ||
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| - Automatic Sorting | ||
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| Automatic sorting is implemented based on five different methods: skew-t and t distributions, GMM, k-means and template matching. Several options are provided for configurations in the algorithm. Automatic sorting results will appear in PCA and waveform plots: | ||
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| Automatic sorting is implemented based on five different methods: skew-t and t distributions, GMM, k-means and | ||
| template matching. Several options are provided for configurations in the algorithm. Automatic sorting results will | ||
| appear in PCA and waveform plots: | ||
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| - Manual Sorting | ||
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| Manual sorting tool is used for manual modifications on automatic results by the researcher. These tools include: Merge, Delete, Resort and Manual grouping or deleting samples in PCA domain: | ||
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| Manual sorting tool is used for manual modifications on automatic results by the researcher. These tools include: | ||
| Merge, Delete, Resort and Manual grouping or deleting samples in PCA domain: | ||
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| - Visualization | ||
| - Several visualization tools are provided such as: 3D plot | ||
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| - Several visualization tools are provided such as: 3D plot | ||
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| - Also, inter spike interval, neuron live time and Cluster Waveforms | ||
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| - Also, inter spike interval, neuron live time and Cluster Waveforms | ||
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| # Citation | ||
| If ROSS helps your research, please cite our paper in your publications. | ||
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| ``` | ||
| @article{Toosi_2021, | ||
| doi = {10.1038/s41598-021-93088-w}, | ||
| url = {https://doi.org/10.1038%2Fs41598-021-93088-w}, | ||
| year = 2021, | ||
| month = {jul}, | ||
| publisher = {Springer Science and Business Media {LLC}}, | ||
| volume = {11}, | ||
| number = {1}, | ||
| author = {Ramin Toosi and Mohammad Ali Akhaee and Mohammad-Reza A. Dehaqani}, | ||
| title = {An automatic spike sorting algorithm based on adaptive spike detection and a mixture of skew-t distributions}, | ||
| journal = {Scientific Reports} | ||
| } | ||
| ``` | ||
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