Metadata-Version: 2.1
Name: fissa
Version: 0.6.1
Summary: A Python Library estimating somatic signals in 2-photon data
Home-page: https://github.com/rochefort-lab/fissa
Author: Sander Keemink & Scott Lowe
Author-email: swkeemink@scimail.eu
License: GNU
Description: |Gitter| |Travis| |Documentation| |Codecov| |Coveralls|
        
        
        FISSA
        =====
        
        FISSA (Fast Image Signal Separation Analysis) is a Python library for
        decontaminating somatic signals from two-photon calcium imaging data. It
        can read images in tiff format and ROIs in zips as exported by ImageJ;
        or operate with numpy arrays directly, which can be produced by
        importing files stored in other formats.
        
        For details of the algorithm, please see our `companion
        paper <https://www.doi.org/10.1038/s41598-018-21640-2>`__ published in
        Scientific Reports.
        
        FISSA is compatible with both Python 2.7 and Python 3.5+. Using Python 3
        is strongly encouraged, as Python 2 will no longer be `maintained
        starting January 2020 <https://python3statement.org/>`__.
        
        FISSA has been tested on Ubuntu 17.04 and on Windows Windows 10 with the
        `Anaconda <https://www.anaconda.com/download/#linux>`__ distribution.
        
        Documentation, including the full API, is available online at
        `<https://fissa.readthedocs.io>`_.
        
        If you encounter a specific problem please `open a new
        issue <https://github.com/rochefort-lab/fissa/issues/new>`__. For
        general discussion and help with installation or setup, please see the
        `Gitter chat <https://gitter.im/rochefort-lab/fissa>`__.
        
        Usage
        -----
        
        A general tutorial on the use of FISSA can be found at:
        https://rochefort-lab.github.io/fissa/examples/Basic%20usage.html
        
        An example workflow with another Python toolbox (SIMA):
        https://rochefort-lab.github.io/fissa/examples/SIMA%20example.html
        
        An example workflow importing data exported from a MATLAB toolbox
        (cNMF):
        https://rochefort-lab.github.io/fissa/examples/cNMF%20example.html
        
        These notebooks can also be run on your own machine. To do so, you will
        need to `download a copy of the
        repository <https://github.com/rochefort-lab/fissa/archive/master.zip>`__,
        unzip it and browse to the `examples <examples>`__ directory. Then,
        start up a jupyter notebook server to run our notebooks. If you're new
        to jupyter notebooks, an approachable tutorial can be found at
        https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook.
        
        Installation
        ------------
        
        Installation on Windows
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        Basic prerequisites
        ^^^^^^^^^^^^^^^^^^^
        
        Download and install, in the following order:
        
        -  (for Python 2.7 only) Microsoft Visual C++ Compiler for Python 2.7:
           https://www.microsoft.com/en-us/download/details.aspx?id=44266
        
        -  Python 2.7 or 3.5+ (recommended) Anaconda as the Python environment,
           available from https://www.anaconda.com/download/.
        
        Installing FISSA
        ^^^^^^^^^^^^^^^^
        
        Open ``Anaconda Prompt.exe``, which can be found through the Windows
        start menu or search, and type or copy-paste (by right clicking) the
        following:
        
        ::
        
            conda install -c conda-forge shapely tifffile
        
        Then, install FISSA by running the command
        
        ::
        
            pip install fissa
        
        To test if FISSA has been installed, enter the command
        
        ::
        
            python
        
        to go into the Python environment. Then type
        
        ::
        
            import fissa
        
        If no errors show up, FISSA is now installed. You can leave Python by
        typing ``exit()``.
        
        If you want to use the interactive plotting from the notebooks, you
        should also install the HoloViews plotting toolbox, as follows
        
        ::
        
            conda install -c ioam holoviews
        
        See `usage <#usage>`__ above for details on how to use FISSA.
        
        Installation on Linux
        ~~~~~~~~~~~~~~~~~~~~~
        
        Before installing FISSA, you will need to make sure you have all of its
        dependencies (and the dependencies of its dependencies) installed.
        
        Here we will outline how to do all of these steps, assuming you already
        have both Python and pip installed. It is highly likely that your Linux
        distribution ships with these.
        
        Dependencies of dependencies
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        -  `scipy <https://pypi.python.org/pypi/scipy/>`__ requires a `Fortran
           compiler and
           BLAS/LAPACK/ATLAS <http://www.scipy.org/scipylib/building/linux.html#installation-from-source>`__.
        
        -  `shapely <https://pypi.python.org/pypi/Shapely>`__ requires GEOS.
        
        -  `Pillow <https://pypi.org/project/Pillow/>`__>=3.0.0 effectively
           requires a JPEG library.
        
        These packages can be installed on *Debian/Ubuntu* with the following
        shell commands.
        
        .. code:: bash
        
            sudo apt-get update
            sudo apt-get install gfortran libopenblas-dev liblapack-dev libatlas-dev libatlas-base-dev
            sudo apt-get install libgeos-dev
            sudo apt-get install libjpeg-dev
        
        .. installing-fissa-1:
        
        Installing FISSA
        ^^^^^^^^^^^^^^^^
        
        For normal usage of FISSA, you can install the latest release version on
        PyPI using pip:
        
        ::
        
            pip install fissa
        
        To also install fissa along with the dependencies required to run our
        sample notebooks (which include plots rendered with holoviews) you
        should run the following command:
        
        ::
        
            pip install fissa['plotting']
        
        Afterwards, you can test to see if FISSA is install by running the
        command
        
        ::
        
            python
        
        to start an interactive python session. Then run
        
        ::
        
            import fissa
        
        at the python command prompt.
        
        If no errors show up, FISSA is now installed. You can leave the
        interactive python session with the ``exit()`` command, or CTRL+D.
        
        Folder Structure
        ----------------
        
        continuous_integration/
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        Contains files necessary for deploying tests on continuous integration
        servers. Users should ignore this directory.
        
        examples/
        ~~~~~~~~~
        
        Contains example code. You can load the notebooks as .ipynb directly in
        GitHub, or on your system if you know how to use jupyter notebooks.
        
        examples/exampleData/
        ~~~~~~~~~~~~~~~~~~~~~
        
        Contains example data. It a zipfile with region of interests from
        ImageJ. It also contains three tiff stacks, which have been downsampled
        and cropped from full data from the Rochefort lab.
        
        .. fissa-1:
        
        fissa/
        ~~~~~~
        
        Contains the toolbox.
        
        fissa/tests/
        ~~~~~~~~~~~~
        
        Contains tests for the toolbox, which are run to ensure it will work as
        expected.
        
        Citing FISSA
        ------------
        
        If you use FISSA for your research, please cite the following paper in
        any resulting publications:
        
        S. W. Keemink, S. C. Lowe, J. M. P. Pakan, E. Dylda, M. C. W. van
        Rossum, and N. L. Rochefort. FISSA: A neuropil decontamination toolbox
        for calcium imaging signals, *Scientific Reports*, **8**\ (1):3493,
        2018.
        `DOI:10.1038/s41598-018-21640-2 <https://www.doi.org/10.1038/s41598-018-21640-2>`__.
        
        For your convenience, the FISSA package ships with a copy of this
        citation in bibtex format, available at
        `citation.bib <https://raw.githubusercontent.com/rochefort-lab/fissa/master/citation.bib>`__.
        
        License
        -------
        
        Unless otherwise stated in individual files, all code is Copyright (c)
        2015, Sander Keemink, Scott Lowe, and Nathalie Rochefort. All rights
        reserved.
        
        This program is free software; you can redistribute it and/or modify it
        under the terms of the GNU General Public License as published by the
        Free Software Foundation; either version 2 of the License, or (at your
        option) any later version.
        
        This program is distributed in the hope that it will be useful, but
        WITHOUT ANY WARRANTY; without even the implied warranty of
        MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
        Public License for more details.
        
        You should have received a copy of the GNU General Public License along
        with this program. If not, see http://www.gnu.org/licenses/.
        
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Platform: UNKNOWN
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Provides-Extra: dev
Provides-Extra: docs
Provides-Extra: plotting
Provides-Extra: all
