Metadata-Version: 1.1
Name: scipion-em-pyseg
Version: 3.1.2
Summary: Scipion plugin for PySeg
Home-page: https://github.com/scipion-em/scipion-em-pyseg
Author: I2PC
Author-email: scipion@cnb.csic.es
License: UNKNOWN
Description: ========================
        Scipion plugin for PySeg
        ========================
        
        .. image:: https://img.shields.io/pypi/v/scipion-em-pyseg.svg
                :target: https://pypi.python.org/pypi/scipion-em-pyseg
                :alt: PyPI release
        
        .. image:: https://img.shields.io/pypi/l/scipion-em-pyseg.svg
                :target: https://pypi.python.org/pypi/scipion-em-pyseg
                :alt: License
        
        .. image:: https://img.shields.io/pypi/pyversions/scipion-em-pyseg.svg
                :target: https://pypi.python.org/pypi/scipion-em-pyseg
                :alt: Supported Python versions
        
        .. image:: https://img.shields.io/pypi/dm/scipion-em-pyseg
                :target: https://pypi.python.org/pypi/scipion-em-pyseg
                :alt: Downloads
        
        This plugin allows to use PySeg_ - De novo analysis for cryo-electron tomography - within the Scipion framework.
        
        =====
        Setup
        =====
        
        **System pre-requisites:**
        
            1. Cmake 2.6.3+. The intallation command in Ubuntu is:
        
            .. code-block::
        
                sudo apt-get install cmake
        
            2. GSL (GNU Scientific Library). In Ubuntu, the installation command is:
        
            .. code-block::
        
                sudo apt-get install libgsl-dev
        
            3. gcc/g++ version greater or equal to 5 (for DisPerSE_ compilation).
        
        ============
        Installation
        ============
        The plugin can be installed in user (stable) or developer (latest, may be unstable) mode:
        
        **1. User (stable) version:**:
        
        .. code-block::
        
            scipion3 installp -p scipion-em-pyseg
        
        **2. Developer (latest, may be unstable) version:**:
        
        * Clone the source code repository:
        
        .. code-block::
        
            git clone https://github.com/scipion-em/scipion-em-pyseg.git
            
        * Install:
        
        .. code-block::
        
            scipion3 installp -p local/path/to/scipion-em-pyseg --devel
            
        =========
        Protocols
        =========
        The integrated protocols are:
        
        1. pyseg - fils: Filters a MbGraphMCF (Mean Cumulative Function) object by extracting a filament network
        
        2. pyseg - graphs: Analyzes a GraphMCF (Mean Cumulative Function) from a segmented membrane
        
        3. pyseg - picking: Extracts particles from a filament network of a oriented single membrane graph
        
        4. pyseg - 2D classification: Unsupervised and deterministic classification of membrane-bound particles
        
        5. pyseg - posrec: post-process already reconstructed particles; rot angle randomization and membrane suppression
        
        6. pyseg - preseg membranes: Segment membranes into membranes, inner surroundings and outer surroundings
            
        =====
        Tests
        =====
        
        The installation can be checked out running some tests (Important: TestPosRec requires the plugins scipion-em-xmipp_
        and scipion-em-reliontomo_ to be installed:
        
        .. code-block::
        
             scipion3 tests pyseg.tests.test_preseg_graphs_fils_picking.TestFromPresegToPicking
        
        .. code-block::
        
            scipion3 tests pyseg.tests.test_pos_rec.TestPostRec
            
        ========
        Tutorial
        ========
        A tutorial about how to use PySeg within Scipion can be found here_.
        
        ==========
        References
        ==========
        
        * `Template-free detection and classification of heterogeneous membrane-bound complexes in cryo-electron tomograms. <http://doi.org/10.1038/s41592-019-0675-5>`_
          A. Martinez-Sanchez et al., Nature Methods, 2020.
        
        ===================
        Contact information
        ===================
        
        If you experiment any problem, please contact us here: scipion-users@lists.sourceforge.net or open an issue_.
        
        We'll be pleased to help.
        
        *Scipion Team*
        
        
        .. _PySeg: https://github.com/anmartinezs/pyseg_system
        .. _DisPerSE: http://www2.iap.fr/users/sousbie/web/html/indexd41d.html
        .. _scipion-em-xmipp: https://github.com/I2PC/scipion-em-xmipp
        .. _scipion-em-reliontomo: https://github.com/scipion-em/scipion-em-reliontomo
        .. _issue: https://github.com/scipion-em/scipion-em-pyseg/issues
        .. _here: https://scipion-em.github.io/docs/release-3.0.0/docs/user/denoising_mbSegmentation_pysegDirPicking/tomosegmemTV-pySeg-workflow.html#tomosegmemtv-pyseg-workflow
        
Keywords: scipion cryoem cryoet imageprocessing scipion-3.0
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
