Metadata-Version: 2.1
Name: pycellfit
Version: 0.2.3
Summary: Python implementation of the CellFIT method of inferring cellular forces
Home-page: https://github.com/NilaiVemula/PyCellFIT
Author: Nilai Vemula
Author-email: nilai.r.vemula@vanderbilt.edu
License: MIT
Description: =========
        pycellfit
        =========
        
        .. image:: https://travis-ci.com/NilaiVemula/pycellfit.svg?branch=master
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          :alt: Documentation Status
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        Project Description
        -------------------
        **pycellfit**: an open-source Python implementation of the CellFIT method of inferring cellular forces developed by Brodland et al.
        
        **Author**: Nilai Vemula, Vanderbilt University (working under Dr. Shane Hutson, Vanderbilt University)
        
        **Project Goal**: To develop an open-source version of CellFIT, a toolkit for inferring tensions along cell membranes and pressures inside cells based on cell geometries and their curvilinear boundaries. (See [1]_.)
        
        **Project Timeline**: Initial project started in August 2019 with work based off of XJ Xu. This repository was re-made in May 2020 in order to restart repository structure.
        
        **Project Status**: **Development**
        
        Getting Started
        ---------------
        This project is available on `PyPI <https://pypi.org/project/pycellfit/>`_ and can be installed using pip.
        
        It recommended that users make a `virtual environment <https://docs.python.org/3/tutorial/venv.html>`_ and then install
        the package as such:
        
        Install from PyPI:
        ^^^^^^^^^^^^^^^^^^
        .. code:: bash
        
           pip install pycellfit
        
        Or compile from source:
        ^^^^^^^^^^^^^^^^^^^^^^^
        .. code:: bash
        
           git clone https://github.com/NilaiVemula/pycellfit.git
           cd pycellfit
           python setup.py install
        
        Full documentation for this package can be found on `readthedocs <https://pycellfit.readthedocs.io/>`_.
        
        Dependencies
        ^^^^^^^^^^^^
        This project is written in Python and has been tested on Python 3.7 and 3.8 on Linux and Windows. This project
        primarily
        depends
        on numpy,
        scipy, matplotlib, and other common python packages common in scientific computing. Additionally, `Pillow
        <https://github.com/python-pillow/Pillow>`_ is required for reading in input image files. A full list of dependencies
        is available in the requirements.txt_ file. All dependencies should be automatically installed when running pip install.
        
        .. _requirements.txt: requirements.txt
        
        Development
        -----------
        This project is under active development and not ready for public use. The project is built using Travis CI, and all
        tests are run with every commit or merge.
        
        Features
        --------
        Currently, pycellfit supports the following features in the cellular force inference pipeline:
        
        - [ ] converting raw images into segmented images
        
          - see `SeedWaterSegmenter <https://github
            .com/davidmashburn/SeedWaterSegmenter>`_ or `neural_net_cell_segmenter <https://github
            .com/NilaiVemula/neural_net_cell_segmenter>`_ (work in progress).
        
        - [x] read in segmented images
        
        - [x] convert between watershed and skeleton segmented images
        
        - [x] identify triple junctions
        
        - [ ] identify quad junctions
        
        - [x] generate a mesh
        
        - [x] fit cell edges to circular arcs
        
        - [ ] calculate tangent vectors using circle fits, nearest segment, and chord methods
        
          - circle fit is incorrect, others have not been added
        
        - [x] calculate tensions
        
        - [ ] calculate pressures
        
        - [x] visualize all of the above steps
        
        Examples
        --------
        A example walk-through of how to use this module is found in quickstart_.
        
        .. _quickstart: tutorials/README.rst
        
        Future Goals
        ------------
        The final implementation of pycellfit will be as a web-app based on the Django framework. (See `pycellfit-web <https://github.com/NilaiVemula/pycellfit-web>`_)
        
        References
        ----------
        .. [1] Brodland GW, Veldhuis JH, Kim S, Perrone M, Mashburn D, et al. (2014) CellFIT: A Cellular Force-Inference Toolkit Using Curvilinear Cell Boundaries. PLOS ONE 9(6): e99116. https://doi.org/10.1371/journal.pone.0099116
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Description-Content-Type: text/x-rst
