Metadata-Version: 2.1
Name: qojpca
Version: 0.1.5
Summary: qojpca package
Home-page: https://github.com/florentjousse/qojpca/
Author: florentjousse
License: UNKNOWN
Description: # qojpca
        
        [![codecov](https://codecov.io/gh/cryckx/qojpca/branch/main/graph/badge.svg?token=qojpca_token_here)](https://codecov.io/gh/cryckx/qojpca)
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        QOJPCA (Quasi-orthogonal Joint Principal Component Analysis) package allows for improving the orthogonality between linear bases computed through Principal Component Analysis.  
        
        ## Install it from PyPI
        
        The package has been released on PyPip and can be installed through. 
        
        ```bash
        pip install qojpca
        ```
        
        ## Requirements
        
        Numpy, Scikit
        
        ## Usage
        
        The package can be used by importing the "base" module into your python script as:
        
        ```py
        from qojpca import base
        """ 
        QOJPCA can be computed using the qojpca static function
        l_p (resp. l_q): number of latent variables for P (resp. Q)
        l: regularization parameter. Note that it is multiplied by the largest eigenvalue of XX^T
        """
        P_vals,Q_vals,P,Q = base.qojpca(X,Y,l_p,l_q,l)
        ```
        
        Or by using the command line interface. For example 
        
        ```bash
        $ python -m qojpca X.npy Y.npy --l_x 10 --l_y 10 --output_directory output --regularization 100
        ```
        where:
        l_p (resp. l_q) are the number of latent variables for linear basis P (resp. Q).
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: gpu
Provides-Extra: test
