ljhouses

Simulate Lennard-Jones spheres and similar systems in the context of location of buildings.

Install

git clone https://github.com/benmaier/ljhouses/
pip install ./ljhouses

ljhouses was developed and tested for

• Python 3.10
• Python 3.11

So far, the package's functionality was tested on macOS X and Ubuntu only.

Dependencies

ljhouses directly depends on the following packages which will be installed by pip during the installation process

• numpy>=1.17

Examples

Thermalized LJ simulation

```python import numpy as np import matplotlib.pyplot as pl

from ljhouses.pythonsims import getclosetoequilibriuminitialconditions, simulate, StochasticBerendsenThermostat from ljhouses.drawing import plotconfiguration

define system parameters

N = 1000 # number of particles LJr = 10 # potential minimum for interaction energy LJe = 20 # potential depth LJRmax = 3*LJr # maximum distance to which to compute interaction forces g = 0.2 # gravitational pull to the center v0 = 6 # root mean squared velocity of the particles (~root temperature) dt = 0.01 # length of time step

create display figure

fig, ax = pl.subplots(1, 3, figsize=(10,4)) ax[0].sharex(ax[1]) ax[0].sharey(ax[1])

create initial conditions that should lie close to an equilibrium

configuration and display the configuration

x, v, a = getclosetoequilibriuminitialconditions(N, v0, LJr, g, dt) plotconfiguration(x, LJr/2, ax[0]) ax[0].set_title('initial configuration')

Define a thermostat that keeps the configuration at roughly the

same temperature

thermostat = StochasticBerendsenThermostat(v0, N)

define more simulation parameters

Nsamplingrounds = 10 Nstepspersample = 1000 maxsamples = 10

run the simulation

samples, t, K, V, Vij = simulate(dt, Nsamplingrounds, Nstepspersample, maxsamples, LJr, LJe, LJ_Rmax, g, x, v, a, thermostat)

obtain the final configuration and display it

x1, v1, a1 = samples[-1] plotconfiguration(x1, LJr/2, ax[1]) ax[1].set_title(f'after {int(np.round(t[-1]/dt)):d} steps')

plot the temporal evolution of the energies

ax[2].plot(t, K, label='K') ax[2].plot(t, V, label='V') ax[2].plot(t, Vij, label='Vij') ax[2].plot(t, np.sum((K, V, Vij),axis=0), label='E') ```

Collision simulation

```python import numpy as np import matplotlib.pyplot as pl

from ljhouses.pythonsims import simulatecollisionsuntilnocollisions from ljhouses.drawing import plot_configuration

N = 300 L = 1 R = L/np.sqrt(N)/np.pi D = 2*R x = np.random.rand(N,2) * L

fig, ax = pl.subplots(1,2,figsize=(10,5),sharex=True,sharey=True) ax[0].set_title('initial configuration')

plotconfiguration(x, R, ax[0]) xnew = simulatecollisionsuntilnocollisions(x, D) plotconfiguration(xnew, R, ax[1]) ax[1].set_title('after running collision detection') ```

Changelog

Changes are logged in a separate file.

License

Most of this project is licensed under the BSD-3 License. Note that this excludes any images/pictures/figures shown here or in the documentation.

Contributing

If you want to contribute to this project, please make sure to read the code of conduct and the contributing guidelines. In case you're wondering about what to contribute, we're always collecting ideas of what we want to implement next in the outlook notes.

Dev notes

Fork this repository, clone it, and install it in dev mode.

bash git clone git@github.com:YOURUSERNAME/ljhouses.git make

If you want to upload to PyPI, first convert the new README.md to README.rst

bash make readme

It will give you warnings about bad .rst-syntax. Fix those errors in README.rst. Then wrap the whole thing

bash make pypi

It will probably give you more warnings about .rst-syntax. Fix those until the warnings disappear. Then do

bash make upload