openbread

A python 3 implementation of OPENFPM based brownian reaction dynamics.

Container-based install

We recommend to use this package inside of the provided DOCKER container. This requires an installation of Docker (R) (Community edition sufficient) that is freely available here

See docker/ page for the setup and use of the container.

Source-based install

For a source based it is necessary to install OPENFPM with CXXFLAGS=-fPIC CFLAGS=-fPIC. We recommend to use our fork of the openfpm package that is using openmpi 3.0.0. If OPENFPM is compiled with openmpi 2.X.X openbread cannot be compiled due to a bug impacting shared libraries.

git clone https://github.com/weilandtd/openfpm_pdata.git
cd openfpm_pdata
./install -s -i "/installation/directory" \
             -c "--prefix=/dependency/directory  CXXFLAGS=-fPIC  CFLAGS=-fPIC"
make install

Note that correct include and library paths need to be added. Be aware to specify your python version 3.X for the PYTHON_INCLUDE environmental variable:

cp /path/to/openfpm/ ~/example.mk
source /openfpm_install_dir/openfpm_vars
export PYTHON_INCLUDE=$PYTHON_ROOT/include/python3.Xm

The package can then be installed using the distutils:

pip install -e /path/to/openbread

The source-based install of openbread was only tested in Linux based environments. Platform compatibility is achieved using the container-based install.

Requirements

This module was developed in Python 3.5, and it is recommended to run Python 3.5. The module also was tested in Python 3.6.

This module requires OPENFPM to work properly.

Further the following pip-python packages are required

• sympy >= 1.1.
• pytest
• scipy
• numpy
• dill

Quick start

from openbread.core import *


# Construct species in the model

A = Species(    name = 'A',
                diffusion_constant = 100e-12,
                collision_radius   = 2e-9,
                mass = 1 )

B = Species(    name = 'B',
                diffusion_constant = 100e-12,
                collision_radius   = 2e-9,
                mass = 1 )

C = Species(    name = 'C',
                diffusion_constant = 50e-12,
                collision_radius   = 4e-9,
                mass = 2 )


# Rate constant
k = 1e12
Keq = 50e-6

# Setup particle simulation environemnt
volume = 10e-18 # (0.1 mum)^3 in L

medium = ParticleModel.Medium(  viscosity=0.7e-3, # Pa s
                                temperatur=310.15)
volume_fraction = 0.0

crowding = ParticleModel.Crowding( volume_fraction = volume_fraction,
                                   mu = np.log(31.9),
                                   sigma = 0.825,
                                   max_size = 10e-3)

particle_model = ParticleModel(medium,
                               crowding,
                               volume)

particle_model.add_reaction(Reaction('A+B->C', {A:-1,B:-1,C:1},  k ))
particle_model.add_reaction(Reaction('C->A+B', {A:1,B:1,C:-1},   k*Keq ))

# Define initial conditions
particle_model.initial_conditions['A'] = 50e-6
particle_model.initial_conditions['B'] = 50e-6


result = particle_model.simulate(   dt=1e-9,
                                    max_time=1e-5,
                                    log_step=10,
                                    random_seed=1,
                                    is_hardsphere=False,
                                    is_constant_state=False,
                                    t_equlibriate=0.0)

License

The software in this repository is put under an APACHE-2.0 licensing scheme - please see the LICENSE file for more details