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