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acse-9-independent-research-project-wafflescore's Introduction

Machine Learning for Automatic Facies Classification from Tomography Models

Author:

Nitchakul Pipitvej

[email protected]

CID: 01592487

Project Information

This project is part of an independent research project for MSc in Applied Computational Science and Engineering, Module ACSE-9, at Imperial College London. The supervisor of this project is Dr Michele Paulatto.

Requirements and Dependencies

  • hdbscan==0.8.22
  • numpy==1.14.3
  • pandas==0.23.0
  • seaborn==0.8.1
  • scikit-learn==0.19.1
  • scikit-image==0.13.1
  • scipy==1.1.0

The listed version may not be the latest release of each libraries and may result in some error when compiling with different version.

User Guide

Installation

This package can be installed using the command

pip install acse-9-irp-wafflescore

or simply clone the Git repository on to you machine via web or using the command

git clone https://github.com/msc-acse/acse-9-independent-research-project-wafflescore.git

Implementation

The python code that were developed are located in build/lib.

Example

An example of a simple run of all the methods explored are located in example folder. Additional notes and run result are recorded in Notebooks.

Compatibility notes

This project is built and tested on Python 3.6.5

License

This package is licensed under MIT License

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