corepytools 0.0.1

CorePy: XRF clustering tools to interpret and visualize geological core data

CorePy package

CorePy is designed to perform machine learning on data collected from geological samples of core.

CorePy bundles a wide range of data analytical tools to interpret multivariate datasets common to geological core characterization

The primary focus of CorePy is to classify high resolution X-ray fluoresence data into chemofacies using unsupervised and supervised clustering tools.

CorePy establishes a folder structure multiple users to work on the same datasets, and also provides visualizations that are useful to validate clustering results.

About the authors

CorePy is being developed by Toti Larson at the University of Texas at Austin, Bureau of Economic Geology, Mudrocks Systems Research Laboratory (MSRL) research consortium.

1. Toti E. Larson, Ph.D. - Research Associate at the University of Texas at Austin. PI MSRL research consortium

2. Esben Pedersen, M.S. - Graduate student (graduated 2020) at the University of Texas at Austin.

3. Priyanka Periwal, P.D. - Research Science Associate at the University of Texas at Austin.

4. Ana Letícia Batista - Undergraduate at Jackson State University (graduated 2020). 2020 Jackson School of Geosciences GeoForce Student

5. ** J. Evan Sivil** - Research Science Associate at the University of Texas at Austin.

Package Inventory

CorePy.py

Package Dependencies

os seaborn pickle pandas glob numpy natplotlib.pyplot seaborn as sns sklearn.preprocessing import StandardScaler sklearn.decomposition import PCA sklearn.cluster import KMeans matplotlib.patheffects

Notes

Folder structure

corepy-tools

|-LICENSE.txt         **MIT**

|-README.md           **edited in markdown**

|-setup.py            **name=corepy-tools, package=src, python module=CorePy**

|-src

    |-CorePy.py    **contains functions**

    |-__init__.py     ** empty**