Skip to main content

Python library for finding the optimal transformation(s) that makes two matrices as close as possible to each other.

Project description

Procrustes Python Library

This project supports Python 3.9+ GPLv3 License CI Tox docs CI CodeCov Binder

The Procrustes library provides a set of functions for transforming a matrix to make it as similar as possible to a target matrix. For more information, visit Procrustes Documentation.

Citation

Please use the following citation in any publication using Procrustes library:

@article{Meng2022procrustes,
    title = {Procrustes: A python library to find transformations that maximize the similarity between matrices},
    author = {Fanwang Meng and Michael Richer and Alireza Tehrani and Jonathan La and Taewon David Kim and Paul W. Ayers and Farnaz Heidar-Zadeh},
    journal = {Computer Physics Communications},
    volume = {276},
    number = {108334},
    pages = {1--37},
    year = {2022},
    issn = {0010-4655},
    doi = {https://doi.org/10.1016/j.cpc.2022.108334},
    url = {https://www.sciencedirect.com/science/article/pii/S0010465522000522},
    keywords = {Procrustes analysis, Orthogonal, Symmetric, Rotational, Permutation, Softassign},
}

Dependencies

The following dependencies are required to run Procrustes properly,

To test Procrustes, the following dependencies are required,

Installation

It is recommended to install qc-procrustes within a virtual environment.To create a virtual environment, we can use the venv module (Python 3.3+, https://docs.python.org/3/tutorial/venv.html), miniconda (https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html), or pipenv (https://pipenv.pypa.io/en/latest/).

Installing from PyPI

To install procrustes with pip, we can install the latest stable release from the Python Package Index (PyPI) as follows:

    # install the stable release.
    pip install qc-procrustes

Installing from The Prebuild Wheel Files

To download the prebuilt wheel files, visit the PyPI page and GitHub releases.

    # download the wheel file first to your local machine
    # then install the wheel file
    pip install file_path/qc_procrustes-1.0.2a1-py3-none-any.whl

Installing from the Source Code

In addition, we can install the latest development version from the GitHub repository as follows:

    # install the latest development version
    pip install git+https://github.com/theochem/procrustes.git

We can also clone the repository to access the latest development version, test it and install it as follows:

    # clone the repository
    git clone git@github.com:theochem/procrustes.git

    # change into the working directory
    cd procrustes
    # run the tests
    python -m pytest .

    # install the package
    pip install .

More

See https://procrustes.qcdevs.org for full details.

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

qc_procrustes-1.0.3.tar.gz (1.6 MB view details)

Uploaded Source

Built Distribution

qc_procrustes-1.0.3-py3-none-any.whl (1.6 MB view details)

Uploaded Python 3

File details

Details for the file qc_procrustes-1.0.3.tar.gz.

File metadata

  • Download URL: qc_procrustes-1.0.3.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for qc_procrustes-1.0.3.tar.gz
Algorithm Hash digest
SHA256 7f74f983c9e403f67e7b02c5b749c2a79cb23077b8e80740439d459f8eaa3427
MD5 7a8ba5c06a46619aa95193fe278c557a
BLAKE2b-256 216d993a4bfe3998d166717019901ee2b1e445645e7de77788ad1b02ac2085a6

See more details on using hashes here.

Provenance

File details

Details for the file qc_procrustes-1.0.3-py3-none-any.whl.

File metadata

File hashes

Hashes for qc_procrustes-1.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 767508350cadf011b9570cfce2c0a740a8907158800539d23a0a13f8f2c2f3a1
MD5 0af98a4706ff00fcc4035ac94d47fb87
BLAKE2b-256 b6f3f384918eba100b825675bc76ee3f619e54524b63b82a057c90b04c8759f5

See more details on using hashes here.

Provenance

Supported by

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