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CaMOS

GUI for CMOS + Calcium imaging registration

License: MIT Build Status Python 3.6 Code style: black

CaMOS is an interactive application for CMOS and Calcium imaging registration. It's designed for browsing, detection, and easier signal processing across large datasets.

First Steps

Installing CaMOS

CaMOS can be installed on most macOS, Linux, and Windows systems with Python >=3.7. Currently, you can just install CaMOS from source. We are planning on adding pip in the future.

# Clone the repository locally
git clone https://github.com/danilexn/camos.git
# Navigate to the directory
cd camos
# Install using pip (make sure that pip is alias to pip for python >=3.7
pip install -e '.[all]'

Make sure you have an internet connection during the installation process, as pip will require it to automatically install all dependencies. Otherwise, dependencies listed under requirements.txt are expected to be installed beforehand.

Running CaMOS

To run CaMOS as a Python module, either having installed it with pip (or not), you can execute the following command

cd camos # or wherever the repo directory is
python -m camos

If you have installed it with pip, following the instructions above, you may execute CaMOS with the alias:

camos

Using CaMOS

To get detailed instructions on how to use CaMOS, please visit our Wiki page. You will find information about the core functionality and the built-in plugins.

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated. Follow the recipe below to contribute to this repository:

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Daniel León Periñán - @danilexn - daniel.leon-perinan@mailbox.tu-dresden.de

Josua Seidel - @jseidel5 - josua.seidel@mailbox.tu-dresden.de

Hani Al Hawasli - @HaniAlHawasli - hani.al-hawasli@mailbox.tu-dresden.de

About

CaMOS, a GUI for analysis of multimodal neuroscience datasets.

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