Skip to main content

A evolutionary computing framework

Project description

EVOKIT

A modular, permissively licensed, highly customisable evolutionary computing framework. This framework was developed further from my MEng report, produced with supervision and guidance from Dr. Stephen Kelly.

This framework is thoroughly documented and completely typed. Please see the [documentation] for instructions on how to install and use it.

Installation

Install from PyPI:

pip install evokit

Install from source:

pip install .

Please see documentation for detailed instructions, how the project is built, and how to perform a trial run after installation.

Components

The library have the following modules:

Component Description
core Interfaces for custom evolutionary operators
core.accelerator Performance-boosting utilities; parallelisation
accounting Observe and report algorithms at runtime
core.accelerator Custom evolutionary operators, including representations
tools.diversity Diversity maintenance
core.lineage Lineage tracing
save, load in core.population Saving and loading individuals and populations

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

evokit-0.5.0.tar.gz (39.1 kB view details)

Uploaded Source

Built Distribution

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

evokit-0.5.0-py3-none-any.whl (218.2 kB view details)

Uploaded Python 3

File details

Details for the file evokit-0.5.0.tar.gz.

File metadata

  • Download URL: evokit-0.5.0.tar.gz
  • Upload date:
  • Size: 39.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.10

File hashes

Hashes for evokit-0.5.0.tar.gz
Algorithm Hash digest
SHA256 92fcc8a7c1ea8c4e42d189090a0b1eed3a8c9de9c2c1d721ce31aa8acd441cbf
MD5 88fa2c66d54ac03dcc538eb73a37d653
BLAKE2b-256 0e907197bb660006b6b01a53b2d8c3209fe3c77618feb1c7fb1e0b66a0857f85

See more details on using hashes here.

File details

Details for the file evokit-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: evokit-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 218.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.10

File hashes

Hashes for evokit-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0b3bd67726f5dfa69048e06f9cea7dff94c85956ed77ef9141f615863329ab6a
MD5 043fec71d329bebcc4d1e339514dec0e
BLAKE2b-256 df41a0859c38b6b2c6a63167b7298c294a7ad485e5d19c9cb5830c4e32ddaee5

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