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CaGraph

Graph theory analysis and visualization package for calcium imaging timeseries data. The package makes it simple for experimental researchers to generate graphs of functional networks and inspect their topology, using NetworkX to compute useful graph theory metrics. Bokeh is used to assist with interactive plotting of graph networks.
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Table of Contents

  1. About The Project
  2. Getting Started
  3. Usage
  4. License
  5. Contact
  6. Acknowledgements

About The Project

CaGraph Screen Shot

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

A list of software required for the CaGraph project and how to install the packages.

  • networkx
    pip install networkx
  • bokeh
    pip install bokeh
  • numpy
    pip install numpy
  • matplotlib
    pip install matplotlib
  • pynwb
    pip install pynwb
  • scipy
    pip install scipy
  • seaborn
    pip install seaborn
  • statsmodels
    pip install statsmodels

Installation

  1. Clone the repo
    git clone https://github.com/vporubsky/CaGraph.git
  2. Install via PyPI
    pip install cagraph

Usage

Examples of using the package will be added here. Additional screenshots, code examples and demos will be included formally in documentation.

Documentation to be added.

License

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

Contact

Veronica Porubksy - verosky@uw.edu

Project Link: https://github.com/vporubsky/CaGraph

Acknowledgements

About

Application of graph theory to summarize network behavior of neurons recorded using calcium fluorescence imaging.

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