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An atooms backend for simulating active matter

Reason this release was yanked:

Improper handling of equilibration times

Project description

active

pypi version license pipeline coverage report

active is a simulation backend for atooms, a high-level framework for particle-based simulations. This backend implements active matter systems, e.g. the Vicsek model as described in Vicsek et al. (1995) and in Grégoire and Chaté (2004).

Quick start

Here we have a simulation of an active matter system based on the Vicsek model. First of all, we need to setup a 2D atooms system.

import numpy
import atooms
from atooms.system import System

n = 200
dim = 2
system = System(N = n)
system.cell = [32. for i in range(dim)]
for p in system.particle:

	p.orientation = numpy.random.uniform(-numpy.pi,numpy.pi)
	p.position = [L*numpy.random.uniform() for i in range(dim)]
	p.fold(system.cell)

Having done so, we can run a simple Vicsek model simulation as follows. We need to provide the system size n, its noise amplitude eta, velocity v0, and density rho.

from atooms.active.vicsek import Vicsek
from atooms.active.neighbors import VicsekNeighbors
from atooms.simulation import Simulation

eta = 0.4
v0 = 0.5
rho = 0.5

backend = Vicsek(system, eta, v0, noise='vectorial')
neighbors = VicsekNeighbors(system, method='kdtree')
bck.neighbors = neighbors

Simulation(backend).run(10)

This simulation employs the so-called 'vectorial' noise implementation (discussed in Grégoire and Chaté) and the scipy-based kD-tree neighbor search algorithm.

A basic API is also available. We can run the same simulation as follows

from atooms.active.api import vm

vm('input.xyz', file_out='output.xyz', npart=2048, eta=0.4, rho=2.0, nsteps=1000, config_number=10)

or, from the command line

api.py input.xyz --file-out output.xyz --npart 2048 --eta 0.4 --rho 2.0 --nsteps 1000 --config-number 10

Features

  • Seamless integration with atooms framework
  • Various nearest neighbors algorithms available
  • Easy extension to new variations of the Vicsek model
  • Support for user-provided code

Dependencies

  • gfortran 11.3.0
  • python 3.10
    • argh 0.28.1
    • atooms 3.17.0
    • f2py-jit 0.9.2
    • numpy
    • scipy (optional)

Documentation

Check out the tutorial for more detailed examples and the public API for more detail.

Installation

From the Python Package Index

pip install atooms.active[full]

to get all optional dependencies (i.e. scipy). A lightweight installation can be performed as well

pip install atooms.active

From the code repository

git clone https://framagit.org/atooms/active.git
cd active
make install

Authors

Iacopo Ricci: https://iricci.frama.io/

Huge thanks to Prof. Daniele Coslovich for his careful supervision and for his profound insights.

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