Metadata-Version: 1.2
Name: pyGDM2_retard
Version: 0.2
Summary: A python full-field electrodynamical solver, based on the Green dyadic method (volume integral technique in frequency domain).
Home-page: https://gitlab.com/wiechapeter/pyGDM2
Author: Gerard Colas des Francs, Peter R. Wiecha
Author-email: pwiecha@laas.fr
License: GPLv3+
Description: ***********************************
        Requirements / Installation
        ***********************************
        
        Retarded 3-layer Greens Tensors for pyGDM2 based on a fortran implementation by Gérard Colas des Francs.
        
        pyGDM2 is available on `pypi <https://pypi.python.org/pypi/pygdm2/>`_ and `gitlab <https://gitlab.com/wiechapeter/pyGDM2>`_. 
        
        Detailed documentation with many examples is can be found at the `pyGDM2 documentation website <https://wiechapeter.gitlab.io/pyGDM2-doc/>`_. See also the `documentation paper on arXiv (1802.04071) <https://arxiv.org/abs/1802.04071>`_ or a more `theoretical review about the GDM method <https://doi.org/10.1088/0034-4885/68/8/R05>`_.
        
        
        
        
        
        
        Requirements
        ================================
        
        Python
        ------------------
            - **python** (3.5+, `python <https://www.python.org/>`_)
            - **numpy** (`numpy <http://www.numpy.org/>`_)
            - **numba** (`numba <https://numba.pydata.org/>`_)
            - **python headers** (under linux install the package *python-dev* or *python-devel*)
        
        
        Fortran
        ------------------
            - *fortran* compiler (tested with **gfortran**. `gcc <https://gcc.gnu.org/fortran/>`_)
            - **f2py** (comes with **numpy**. `link <http://www.numpy.org/>`_)
        
        
        Optional Python packages
        -------------------------------------
            - **scipy** >= v0.17.0, lower versions supported with restrictions (*Strongly recommended*. Used for standard solver LU decomposition and several tools. `scipy <https://www.scipy.org/>`_)
        
        
        
        Installation under linux
        =============================================
        
        Via pip
        -------------------------------
        
        Install from pypi repository via
        
        .. code-block:: bash
            
            $ pip install pygdm2_retard
        
        
        
        Via setup script
        -------------------------------
        
        The easiest possibility to compile pyGDM2_retard is via the 
        setup-script, which uses the extended *distutils* from *numpy*. 
        
        To install the pyGDM2_retard module, run in the source directory:
        
        .. code-block:: bash
            
            $ pip3 install -U .
        
        or
        
        .. code-block:: bash
            
            $ python3 setup.py install
        
        To install as a user installation without administrator rights:
        
        .. code-block:: bash
            
            $ pip3 install -U . --user
        
        To install to a entirely free, user-defined location, use the *prefix* option:
        
        .. code-block:: bash
            
            $ python3 setup.py install --prefix=/some/specific/location
        
        
        To only compile without installation, use
        
        .. code-block:: bash
            
            $ python3 setup.py build
        
        
                
        
        
        Installation under windows
        =============================================
        
        For windows, we recommend `Anaconda <https://www.anaconda.com/download/#windows>`_ in which pyGDM can be installed easily via pip. On pip we provide python 3.5+ windows binaries of the pyGDM2_retard module 
        
        Via pip
        -------------------------------
        
        We provide a 64bit windows binary on the pypi repository (tested on Win7 and Win10). Install via
        
        .. code-block:: bash
            
            $ pip install pygdm2_retard
        
            
        Compile using the Anaconda distribution (tested with anaconda3)
        ------------------------------------------------------------------------------------------
            
        1. get the repo (e.g. download from gitlab)
        
        2. install gcc compiler:
        
           .. code-block:: bash
            
                $ conda install m2w64-toolchain libpython
        
        3. compile fortran parts:
        
           .. code-block:: bash
            
                $ python setupy.py build
        
        4. install:
        
           .. code-block:: bash
            
                $ python setupy.py install
        
        
        
        
        
        Installation under Mac OS X
        =============================================
        
        Should work under anaconda python as described above for compilation on windows.
        
        
        
        Authors
        =========================
        
        fortran implementation
        -------------------------
           - G\. Colas des Francs
        
        python interface
        ------------------------
           - P\. R. Wiecha
        
        
        
        
           
        
        
        
Keywords: coupled dipoles method,green dyadic method,electrodynamical simulations,nano optics,frequency-domain
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Environment :: Console
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.5
