Skip to main content

Algorithms for inverse design

This project has been archived.

The maintainers of this project have marked this project as archived. No new releases are expected.

Project description

invrs-opt - Optimization algorithms for inverse design

Continuous integration PyPI version

Overview

The invrs-opt package defines an optimizer API intended for topology optimization, inverse design, or AI-guided design. It (currently) implements the L-BFGS-B optimization algorithm along with some variants. The API is intended to be general so that new algorithms can be accommodated, and is inspired by the functional optimizer approach used in jax. Example usage is as follows:

initial_params = ...

optimizer = invrs_opt.lbfgsb()
state = optimizer.init(initial_params)

for _ in range(steps):
    params = optimizer.params(state)
    value, grad = jax.value_and_grad(loss_fn)(params)
    state = optimizer.update(grad=grad, value=value, params=params, state=state)

Optimizers in invrs-opt are compatible with custom types defined in the totypes package. The basic lbfgsb optimizer enforces bounds for custom types, while the density_lbfgsb optimizer implements a filter-and-threshold operation for DensityArray2D types to ensure that solutions have the correct length scale.

Install

pip install invrs_opt

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

invrs_opt-0.10.5.tar.gz (46.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

invrs_opt-0.10.5-py3-none-any.whl (50.0 kB view details)

Uploaded Python 3

File details

Details for the file invrs_opt-0.10.5.tar.gz.

File metadata

  • Download URL: invrs_opt-0.10.5.tar.gz
  • Upload date:
  • Size: 46.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for invrs_opt-0.10.5.tar.gz
Algorithm Hash digest
SHA256 d14a25f0fbb9ace1658e1dc51e72ede4f977eab5f5978fde1f80d51923104ff0
MD5 e4faf5302176708a5bcd43f2b4fcaa73
BLAKE2b-256 411eb294fe68a269dffb390e71eaf66a1b76e7577fdc39167f2f1e28e5753e99

See more details on using hashes here.

File details

Details for the file invrs_opt-0.10.5-py3-none-any.whl.

File metadata

  • Download URL: invrs_opt-0.10.5-py3-none-any.whl
  • Upload date:
  • Size: 50.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for invrs_opt-0.10.5-py3-none-any.whl
Algorithm Hash digest
SHA256 b888d84f61697fdcf9e14526ffc497ff9875f0f5ec98b3c2236965f65ad797ae
MD5 7b97cd008a649f35f7feef5aab0b813f
BLAKE2b-256 13f8157ed7553ece85968329048ccc1f5d4394f5d570e2eb5c67389fc3ac3501

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page