Metadata-Version: 1.2
Name: tofu
Version: 1.3.2
Summary: A python library for Tomography for Fusion
Home-page: https://github.com/ToFuProject/tofu
Author: Didier VEZINET
Author-email: didier.vezinet@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: .. image:: https://img.shields.io/travis/ToFuProject/tofu.svg?label=Travis-CI
            :target: https://travis-ci.org/ToFuProject/tofu
        
        .. image:: https://anaconda.org/tofuproject/tofu/badges/version.svg
           :target: https://anaconda.org/tofuproject/tofu/badges/
        
        .. image:: https://anaconda.org/tofuproject/tofu/badges/downloads.svg
              :target: https://anaconda.org/tofuproject/tofu/badges/
        
        .. image:: https://codecov.io/gh/ToFuProject/tofu/branch/master/graph/badge.svg
                 :target: https://codecov.io/gh/ToFuProject/tofu
        
        
        ToFu
        ====
        
        -----
        
        **Warning**
        This Pypi package focuses on tomography for fusion research.
        It uses the same name as a previous package dedicated to a testing framework coupling fixtures and tests loosely, now renamed **reahl-tofu** and developped by Iwan Vosloo since 2006. If you ended up here looking for a web-oriented library, you should probably redirect to the more recent [**reahl-tofu**](https://pypi.python.org/pypi/reahl-tofu) page.
        
        -----
        
        ToFu stands for Tomography for Fusion, it is an open-source machine-independent python library
        with non-open source plugins containing all machine-dependent routines.
        
        It is distributed under the MIT license and aims at providing the fusion community with 
        a transparent and modular tool for creating / designing diagnostics and using them for 
        synthtic diagnostic (direct problem) and tomography (inverse problem).
        
        It was first created at the Max-Planck Institute for Plasma Physics (IPP) in Garching, Germany, 
        by Didier Vezinet, and is now maintained / debugged / updated by him and other contributors.
        
        A sphinx-generated documentation can be found at [the ToFu documentation page](https://ToFuProject.github.io/tofu/index.html),
        and the code itself is hosted on [GitHub](https://github.com/ToFuProject/tofu).
        
        
        ----
        
        ToFu provides the user with a series of python classes for creating, handling and visualizing a diagnostic geometry, meshes and basis functions, 
        geometry matrices, pre-treating experimental data and computing tomographic inversions.
        
        Each one of these main tasks is accomplished by a dedicated module in the larger ToFu package.
        
        In its current version, only the geometry and data-handling modules are released. 
        The others, while operational, are not user-friendly and documented yet, they will be available in future releases.
        
        
        The geometry module is sufficient for diagnostic designing and for a synthetic diagnostic approach (i.e.: computing the integrated signal from a simulated 2D or 3D emissivity).
        This geometry module allows in particular:
        
        * To handle linear and toroidal vaccum vessels
        * To define apertures and detectors as planar polygons of arbitrary shapes, or to define a spherical converging lens and a circular detector in its focal plane.
        * To assign an arbitrary number of apertures to each detector (and the apertures do not have to stand in parallel planes)
        * To automatically compute the full Volume of Sight (VOS) in 3D of each {detector+aperture(s)} set
        * To discretise the VOS for a numerical 3D integration of a simulated emissivity in order to compute the associated signal
        
        It is in this geometrical sense that ToFu enables a synthetic diagnostic approach, it does not provide the tools for simulating the emissivity (that should be an input, provided by another code).
        
        
        
        
        
        
        
Keywords: tomography geometry 3D inversion synthetic fusion
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
Classifier: Natural Language :: English
Requires-Python: >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*
