Skip to main content

Factory and registry primitives for selecting BEM solvers and excitation operators.

Project description

mnpbem-base

PyPI version Python versions

mnpbem-base provides registry and factory primitives for selecting solver classes from option constraints. The release notes are generated directly from this scientific README for traceable package documentation.

Implemented Formulation

Given a requirement set for a candidate class, the selection score is:

\hat{c}=\arg\max_c\sum_j\mathbf{1}[\text{need}_{c,j}\ \text{is satisfied}]

This mirrors rule-based class dispatch used in MNPBEM-style solver construction.

Implementation

  • Registry logic: src/mnpbem_base/registry.py
  • Factory entry points: src/mnpbem_base/factory.py

Dependencies

  • numpy>=1.24

Installation

pip install mnpbem-base

Example

Runnable example:

  • examples/basic_usage.py

Run:

python examples/basic_usage.py

Author

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

mnpbem_base-0.1.5.tar.gz (3.8 kB view details)

Uploaded Source

Built Distribution

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

mnpbem_base-0.1.5-py3-none-any.whl (4.2 kB view details)

Uploaded Python 3

File details

Details for the file mnpbem_base-0.1.5.tar.gz.

File metadata

  • Download URL: mnpbem_base-0.1.5.tar.gz
  • Upload date:
  • Size: 3.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for mnpbem_base-0.1.5.tar.gz
Algorithm Hash digest
SHA256 a0167337779843cb7a5453054266feaa85e64cee5be7d6e9041d7fcd3ced7693
MD5 e589bbc0a0b11c270c79b01111a997cd
BLAKE2b-256 49d642d291e932f4f0436264162f7e3db659cae689c2067e990a6e22444f4e85

See more details on using hashes here.

File details

Details for the file mnpbem_base-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: mnpbem_base-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 4.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for mnpbem_base-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 ad6efcb2119b364c4c0ac5222417328b82f9bce88363d57e380ad068916c4f56
MD5 09fab101bddab0db284853d6d2692a64
BLAKE2b-256 73c52655f3d09ef41d90d305ede508948bdeac08cb607faf7e389c12d4432e91

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