https://github.com/benmaier/ljhouses
C++-based Python package to efficiently simulate 2D Lennard-Jones spheres in an external potential
https://github.com/benmaier/ljhouses
Last synced: 3 months ago
JSON representation
C++-based Python package to efficiently simulate 2D Lennard-Jones spheres in an external potential
- Host: GitHub
- URL: https://github.com/benmaier/ljhouses
- Owner: benmaier
- License: bsd-3-clause
- Created: 2023-02-09T15:58:37.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-16T10:17:15.000Z (about 1 year ago)
- Last Synced: 2024-10-11T11:08:04.183Z (8 months ago)
- Language: Python
- Size: 2.79 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# 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 get_close_to_equilibrium_initial_conditions, simulate, StochasticBerendsenThermostat
from ljhouses.drawing import plot_configuration
# define system parameters
N = 1000 # number of particles
LJ_r = 10 # potential minimum for interaction energy
LJ_e = 20 # potential depth
LJ_Rmax = 3*LJ_r # 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 = get_close_to_equilibrium_initial_conditions(N, v0, LJ_r, g, dt)
plot_configuration(x, LJ_r/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
N_sampling_rounds = 10
N_steps_per_sample = 1000
max_samples = 10
# run the simulation
samples, t, K, V, Vij = simulate(dt,
N_sampling_rounds,
N_steps_per_sample,
max_samples,
LJ_r,
LJ_e,
LJ_Rmax,
g,
x,
v,
a,
thermostat)
# obtain the final configuration and display it
x1, v1, a1 = samples[-1]
plot_configuration(x1, LJ_r/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 simulate_collisions_until_no_collisions
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')
plot_configuration(x, R, ax[0])
xnew = simulate_collisions_until_no_collisions(x, D)
plot_configuration(xnew, R, ax[1])
ax[1].set_title('after running collision detection')
```
## Changelog
Changes are logged in a [separate file](https://github.com/benmaier/ljhouses/blob/main/CHANGELOG.md).
## License
Most of this project is licensed under the [BSD-3 License](https://github.com/benmaier/ljhouses/blob/main/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](https://github.com/benmaier/ljhouses/blob/main/CODE_OF_CONDUCT.md) and the [contributing guidelines](https://github.com/benmaier/ljhouses/blob/main/CONTRIBUTING.md). 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](https://github.com/benmaier/ljhouses/blob/main/OUTLOOK.md).
[](code-of-conduct.md)
## Dev notes
Fork this repository, clone it, and install it in dev mode.
```bash
git clone [email protected]: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
```