Procrustes

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,

• Python >= 3.6: http://www.python.org/
• NumPy >= 1.21.5: http://www.numpy.org/
• SciPy >= 1.5.0: http://www.scipy.org/
• PyTest >= 5.3.4: https://docs.pytest.org/
• PyTest-Cov >= 2.8.0: https://pypi.org/project/pytest-cov/

Installation

To install Procrustes using the conda package management system, install miniconda or anaconda first, and then:

# Create and activate myenv conda environment (optional, but recommended)
conda create -n myenv python=3.6
conda activate myenv

# Install the stable release.
conda install -c theochem qc-procrustes

To install Procrustes with pip, you may want to create a virtual environment, and then:

# Install the stable release.
pip install qc-procrustes

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