Metadata-Version: 2.1
Name: avtraj
Version: 0.0.8
Summary: A library to calculate FRET observables for MD trajectories by accessible volume (AV) simulations.In the AV simulations the sterically allowed conformation space of the labels is approximated the conformational space of flexible attached ellipsoids.
Home-page: https://github.com/Fluorescence-Tools/avtraj
Author: Thomas-Otavio Peulen
Author-email: thomas.otavio.peulen@gmail.com
License: LGPLv2.1
Description: AvTraj
        ======
        
        AvTraj is tool to calculate FRET observables from MD-trajectories. Read, write and analyze accessible volumes (AVs) 
        using MD trajectories as an input with only a few lines of Python code. By the use of LabelLib AvTraj provides
        programmatic access to latest developments in implicit dye models for FRET experiments [![DOI for Citing COSB](https://img.shields.io/badge/DOI-10.1016/j.sbi.2016.11.012-blue.svg)](https://doi.org/10.1016/j.sbi.2016.11.012). 
        
        AvTraj is a python library that allows users to perform simulations of accessible volumes for molecular
        dynamics (MD) trajectories. AvTraj serves as a high-level interface for the development of new methodologies
        for structure-based fluorescence spectroscopy.
        
        Features include:
        
                A wide support of diverse MD formats by the use of MDTraj. Extremely fast calculation of AVs by the
                use of LabelLib (e.g. xxxx the speed of yyyy). Extensive analysis functions including those that compute
                inter-dye distances, FRET-efficiencies, fluorescence decays, distance distributions, and an Pythonic API.
        
        AVTraj includes a command-line application, avana, for screening and analyzing structural models.
        
        
        Relation of other software and libraries
        ----------------------------------------
        
        LabelLib serves as core low-level library for the software Olga and the higher-level Python library AvTraj. The
        deprecated software FPS is independent of LabelLib.
        
        ![LabelLib and other software/libraries][3]
        
        [Olga](https://github.com/Fluorescence-Tools/Olga) is a software dedicated towards experimentalists. Olga provides a graphical user interface for the calculation of accessible volumes (AVs), screen a set of structural models against experimental observables, rigid-body docking, 
        and the optimal design of new FRET experiments. 
        
        [AvTraj](https://github.com/Fluorescence-Tools/avtraj)
        AvTraj is a Python library for the calculation of accessible volumes (AVs), screening. AvTraj facilitates the development of new analytical approaches for FRET-based structural models. Avtraj facilitates processing of 
        MD-simulations and the development of Python scripts handling FRET-based structural models. 
        
        [FPS](http://www.mpc.hhu.de/software/fps.html) is a software with a graphical user interface for the FRET-based structural modeling. FPS can calculate accessible volumes (AVs), screen a set of structural models against experimental observables, and can generate new structural 
        models by rigid-body docking using experimental FRET data.
        
        
        Installation
        ============
        
        Anaconda
        --------
        
        ```commandline
        conda --add channels tpeulen
        conda install avtraj
        ```
        
        
        Code Example
        ============
        
        ```python
        import mdtraj as md
        import avtraj as avt
        
        # First load an MD trajectory by mdtraj
        traj = md.load('./examples/hGBP1_out_3.h5')
        
        # Pass a trajectory to fps.AVTrajectory. This creates an object, which can be 
        # accessed as a list. The objects within the "list" are accessible volumes  
        av_traj = avt.AVTrajectory(traj, '18D', attachment_atom_selection='resSeq 7 and name CB')
        # These accessible volumes can be saved as xyz-file
        av_traj[0].save_xyz('test_344.xyz')
        
        # The dye parameters can either be passed explicitly on creation of the object
        av_traj = avt.AVTrajectory(traj, '18D', attachment_atom_selection='resSeq 7 and name CB', linker_length=25., linker_width=1.5, radius_1=6.0)
        
        # or they can be selected from a predefined set of parameters found in the JSON file dye_definition.json located within
        # the package directory 
        av_traj = avt.AVTrajectory(traj, '18D', attachment_atom_selection='resSeq 7 and name CB', dye_parameter_set='D3Alexa488')
        
        # To calculate a trajectory of distances and distance distributions first a labeling file and a "distance file" 
        # needs to be specified. The distance file contains a set of labeling positions and distances and should be compatible
        # to the labeling files used by the software "Olga". By default the 
        av_dist = avt.AvDistanceTrajectory(traj, './examples/hGBP1_distance.json')
        
        ```
        
        
        Citations 
        =========
        
        * MDTraj - [![DOI for Citing MDTraj](https://img.shields.io/badge/DOI-10.1016%2Fj.bpj.2015.08.015-blue.svg)](http://doi.org/10.1016/j.bpj.2015.08.015)
        * FPS - [![DOI for Citing FPS](https://img.shields.io/badge/DOI-10.1038/nmeth.2222-blue.svg)](http://doi.org/10.1038/nmeth.2222)
        
        
        License
        =======
        
        GNU LGPL version 2.1, or at your option a later version of the license.
        Various sub-portions of this library may be independently distributed under
        different licenses. See those files for their specific terms.
        
        [3]: doc/img/software_overview.svg "LabelLib and other software/libraries"
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
