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A python full-field electrodynamical solver, based on the Green dyadic method (volume integral technique in frequency domain).

Project description

pyGDM2 is available on pypi and gitlab.

Detailed documentation with many examples is avaiable at the pyGDM2 documentation website. See also the documentation paper on arXiv (1802.04071)



  • python (2.7 or 3.5+, python)
  • numpy (numpy)
  • python headers (under ubuntu, install the package python-dev or python-devel)


  • fortran compiler (tested with gfortran. gcc)
  • openmp (usually comes with fortran. openmp)
  • f2py (comes with numpy. link)

Optional Python packages

  • scipy >= v0.17.0, lower versions supported with restrictions (Strongly recommended. Used for standard solver LU decomposition and several tools. scipy)
  • matplotlib (Strongly recommended. For all 2D visualization tools. matplotlib)
  • mpi4py (for MPI parallelized calculation of spectra. mpi4py)
  • mayavi (for all 3D visualization. mayavi)
  • PIL (image processing. PIL)
  • pathos (for multi-threaded generalized propagator operations. pathos)
  • pytables (v3.x recommended. For hdf5 saving/loading of simulations. pytables)
  • PaGMO / PyGMO (version 2.4+. Required for the EO submodule. pagmo)
  • pycuda (tested with version 2018.1, for GPU-based matrix inversion. pyCUDA, for problems during installation with pip, see solution proposed here)
  • scikit-cuda (tested with version 0.5, for GPU-based matrix inversion. scikit-cuda)
  • alternatively: cupy (version 7+, tested with version 7.0.0b4, alternative to pycuda for GPU-based matrix inversion. cupy)

(all available via pip)

Installation under linux

Via pip

Install from pypi repository via

$ pip install pygdm2

Via setup script

The easiest possibility to compile (and install) pyGDM is via the setup-script, which uses the extended distutils from numpy.

To install pyGDM, run in the source directory:

$ python install

To install to a user-defined location, use the prefix option:

$ python install --prefix=/some/specific/location

To only compile without installation, use

$ python build

Manual compilation

  1. clone git:

    $ git clone

2.a python 2.7: compile fortran parts:

$ cd fortranBase
$ make

2.b python 3.5+:

$ cd fortranBase
$ make python3
  1. optional, for system-wide usage add to path and pythonpath, e.g. add following lines to file “/home/USER/.profile”, where “path_of_pyGDM_folder” is the pyGDM installation directory:

    export PATH
    export PYTHONPATH

Installation under windows

For windows, we also recommend Anaconda in which pyGDM can be installed easily via pip. See also the MacOS X instructions, but you can skip all steps for installing the gcc compilers, since the windows version of pyGDM comes as pre-compiled binary package.

Via pip

We provide a 64bit windows binary on the pypi repository (tested on Win7 and Win10). Install via

$ pip install pygdm2

Compile using the Anaconda distribution (tested with anaconda3)

  1. get the repo (e.g. download from gitlab)

  2. install gcc compiler:

    $ conda install m2w64-toolchain libpython
  3. compile fortran parts:

    $ python build
  4. install:

    $ python install

Installation under Mac OS X

Using the Anaconda distribution

The default compiler on OSX uses a clang which does not support OpenMP. Hence compilation might fail. We therefore suggest using Anaconda (Mac) and install gcc from the conda repository in a virtualenv (Here the example of python2. python3 was not tested on OSX so far):

$ conda create -n python2 python=2.7 anaconda

“anaconda” at the end will copy the whole anaconda distribution to the virtial env. You can omit this option and create a “blank” virtual environment to install only selected packages.

Next activate the virtualenv and install the required software:

$ source activate python2
$ xcode-select --install
$ conda install pip
$ conda install gcc
$ pip install pygdm2

Also make sure you have the latest versions of numpy and scipy:

$ pip install numpy scipy --upgrade

Without Anaconda

Alternatively, you can download the latest version and compile it manually without OpenMP support, which should work with the default OSX compiler:

$ python install --no-openmp


Python code

  • P. R. Wiecha
  • contributions by C. Majorel

Fortran code

  • C. Girard
  • A. Arbouet
  • R. Marty
  • P. R. Wiecha

Project details

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