Metadata-Version: 2.1
Name: mbpls
Version: 1.0.2a1
Summary: An implementation of the most common partial least squares algorithm as multi-block methods
Home-page: https://github.com/b0nsaii/MBPLS
Author: Andreas Baum, Laurent Vermue
Author-email: <andba@dtu.dk>, <lauve@dtu.dk>
License: new BSD
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Development Status :: 3 - Alpha
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.13.3)
Requires-Dist: matplotlib (>=2.1.1)
Requires-Dist: scipy (>=1.0.0)
Requires-Dist: scikit-learn (>=0.18.0)

## Partial Least Squares Package

Info text here.

### Installation

* `$ git clone https://github.com/b0nsaii/MBPLS.git`
* Install options 
    * Install as developing package
        * Move to /directory/to/MBPLS
        * `$ pip install -e .`
    * Add the directory to your systempath
        * `$ export PYTHONPATH="/directory/to/MBPLS:$PYTHONPATH"
* Now you can import the MBPLS class by typing\
`from mbpls.mbpls import MBPLS`

