Soft Potato

Soft Potato is an open-source electrochemical simulation and analysis toolkit in Python.

Full documentation: https://softpotato.readthedocs.io | Roadmap: ROADMAP.md | Changelog: CHANGELOG.md

Tutorials & Examples

Interactive Jupyter notebooks are available in the examples/ directory:

Installation

Clone the repository and install in development / editable mode:

git clone https://github.com/oliverrdz/softpotato.git
cd softpotato
pip install -e ".[dev,docs]"

Quick Start: Solving 1D Diffusion with scipy_ivp

Soft Potato makes it straightforward to simulate chemical diffusion:

$$\frac{\partial c}{\partial t} = D \frac{\partial^2 c}{\partial x^2}$$

Here is a minimal example setting boundary conditions to $0$ at the left boundary ($x=0$) and $1.0$ at the right boundary ($x=1.0$):

import numpy as np
from softpotato.solver import DiffusionProblem, DirichletBC, get_solver

# 1. Define grid and diffusion problem (c = 0 at left, c = 1.0 at right)
grid = np.linspace(0.0, 1.0, 50)
problem = DiffusionProblem(
    grid=grid,
    diffusivity={"c": 1e-4},
    boundary_conditions={"c": (DirichletBC(0.0), DirichletBC(1.0))},
    initial_conditions={"c": 1.0},
)

# 2. Solve using SciPy's Method of Lines solver
solver = get_solver("scipy_ivp")
result = solver.solve(problem, t_span=(0.0, 1.0))

# 3. Save the concentration profile to a variable
c_profile = result["c"]  # 2D array of shape (N_times, N_points)
print(f"Simulation success: {result.success}")
print(f"Concentration profile shape: {c_profile.shape}")

License

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.