# psl

**Repository Path**: bestwishesws/psl

## Basic Information

- **Project Name**: psl
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-04-09
- **Last Updated**: 2026-04-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# PSL: Python Systems Library v1.3.1
PSL is a minimalistic library for simulating dynamical systems in Python
using [SciPy](https://scipy.org/) library.

Authors: Jan Drgona, Aaron Tuor, Stefan Dernbach, 
James Koch, Soumya Vasisht, Wenceslao Shaw Cortez, Draguna Vrabie


## 1.3.1 release notes
+ Optional pytorch backend via torchdiffeq for all systems in autonomous.py
+ Faster numpy integration for systems in autonomous.py
+ Sampling of initial conditions and control inputs over dynamic range via get_U, and get_x0 functions for all systems.
+ Coupled dynamical systems in coupled_systems.py module

## Documentation

See online [Documentation](https://pnnl.github.io/psl/).

## Setup

```console
$ conda create -n psl python=3.8
$ conda activate psl
(psl) $ conda install numpy
(psl) $ conda install scipy
(psl) $ conda install matplotlib
(psl) $ pip install pyts
(psl) $ pip install tqdm
(psl) $ conda install torchdiffeq
```

## Syntax and Use
```python
import psl
# instantiate selected dynamical system model
model = psl.systems['Duffing'](ts=0.01)
# simulate the dynamical system over nsim steps
out = model.simulate(nsim=2000)
# plot time series and phase portrait 
psl.plot.pltOL(Y=out['Y'], X=out['X'])
psl.plot.pltPhase(X=out['Y'])
```

![Duffing_time_series](figs/Duffing_time_series.png)
![Duffing_phase](figs/Duffing_phase.png)

## Examples

See folder [tests](/tests).