https://github.com/stefanmeili/fastfd
A library for building finite difference simulations
https://github.com/stefanmeili/fastfd
cupy electromagnetic-simulation engineering-design engineering-tools finite-difference finite-difference-simulations fluid-dynamics heat-transfer mechanical-engineering partial-differential-equations pde pde-solver physics-simulation process-simulation python scipy simulation
Last synced: 10 months ago
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A library for building finite difference simulations
- Host: GitHub
- URL: https://github.com/stefanmeili/fastfd
- Owner: stefanmeili
- License: mit
- Created: 2021-03-07T23:32:30.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-04-22T21:43:51.000Z (almost 5 years ago)
- Last Synced: 2025-03-25T20:51:12.789Z (11 months ago)
- Topics: cupy, electromagnetic-simulation, engineering-design, engineering-tools, finite-difference, finite-difference-simulations, fluid-dynamics, heat-transfer, mechanical-engineering, partial-differential-equations, pde, pde-solver, physics-simulation, process-simulation, python, scipy, simulation
- Language: Python
- Homepage:
- Size: 60.2 MB
- Stars: 34
- Watchers: 3
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# FastFD
A finite differences simulation library.
This package lets you quickly build simple numerical simulations.
## Features
* Quickly build finite difference simulations with an arbitrary number of domains, scalars, dimensions and boundary conditions.
* Concise, clear syntax.
* Build models for CPU or GPU using Scipy or Cupy sparse libraries.
* Arbitrary derivative order and approximation accuracy.
* Partial model updates minimize overheads in iterative solutions.
* Implicit transient simulation.
## Installation
```
pip install fastfd
```
## Usage
```python
# Import fastfd and select the scipy sparse library (or cupy for GPU support)
import fastfd as ffd
ffd.sparse_lib('scipy')
import numpy as np
# Define axes
x = ffd.LinearAxis('x', start = 0, stop = 1, num = 201)
y = ffd.LinearAxis('y', start = 0, stop = 1, num = 201)
# Define scalars
T = ffd.Scalar('T', [x, y], accuracy = 4)
# Define the model
model = ffd.FDModel([T])
# Set model governing equations (thermal diffusion)
model.update_equations({
'Conductivity': ((T.d('x', 2) + T.d('y', 2)), 0),
})
# Set model boundary conditions
model.update_bocos({
'Tx=1 adiabatic': (T.i[-1, :], T.d('x')[-1, :], 0),
'Ty=1 adiabatic': (T.i[:, -1], T.d('y')[:, -1], 0),
'Tx=0 sinewave': (T.i[0, :], T.i[0, :], 100 * np.sin(x.coords * 2*np.pi)),
'Ty=0 sinewave': (T.i[:, 0], T.i[:, 0], -100 * np.sin(y.coords * 2*np.pi)),
})
# Solve the model
result = model.solve()
```
## GPU
FastFD can be set to use the Cupyx sparse libraries, though support is still a little rough around the edges. The current
version of Cupy (8.5) only supports a least squares solver ('lsqr') which is much slower than the default 'spsolve'.
However, spsolve will be implemented in the upcoming release of Cupy 9.0.
## Example Notebooks
See example notebooks here: ./docs/examples for a more detailed explanation of how to use.
