Skip to main content

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

Project description

CorePytools package

CorePytools (CorePy) is a machine learning python package applied to data collected from geological samples of core. 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 for input and output data. Visualizations are used to validate clustering results.

Corebox photographs can be cropped and used to visualized chemofacies results. Wireline log data can be upsampled and data integrated to chemofacies for upscaling

New line added

Installation

pip install corepytools

Examples and data

The authors Github account has examples and datapackages that apply corepytools. Corepytools builds a folder structure and looks for XRF data in the folder: ..\CorePy\CoreData\CoreXRF The .csv file Public_XRF.csv is provided in the authors github account to show the database format (required headings) that are called on with CorePy

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, Ph.D. - Research Science Associate at the University of Texas at Austin.

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

  5. Geoforce students - Ana Letícia Batista (2020) - Jackson State University

Package Inventory

corepytools.py

Package Dependencies

  1. os
  2. numpy
  3. pandas
  4. seaborn
  5. pickle
  6. glob
  7. matplotlib.pyplot
  8. seaborn as sns
  9. sklearn.preprocessing import StandardScaler
  10. sklearn.decomposition import PCA
  11. sklearn.cluster import KMeans
  12. matplotlib.patheffects

Notes

Install corepytools using pip install corepytools Follow over to the authors Github account to download example Python scripts that use corepytools

Folder structure

corepytools

|-LICENSE.txt         **MIT**

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

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

|-src

    |-corepytools    **contains functions**

    |-__init__.py     ** empty**

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

corepytools-0.0.7.tar.gz (5.2 kB view hashes)

Uploaded Source

Built Distribution

corepytools-0.0.7-py3-none-any.whl (5.4 kB view hashes)

Uploaded Python 3

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