Using K-means Analysis to Classify Synthetic Spectral Profiles from Numerical Simulations of the Solar Atmosphere

Installation

Works on MacOS, Linux, and Windows.

1. Download the Python 3.6 version (can also download 2.7 version if necessary)

2. Clone the latest version of helita from Github: git clone https://github.com/jamiehuang00/K-Means-IRIS and download to desktop

3. Use Terminal to compile and run the code

Python libraries used: iPython, matplotlib, scipy, numpy

Requires Python 3.0 or higher.

Usage

In order to run the code, enter this on terminal or Jupyter Notebook:

python

---

ipython

import numpy as np

import matplotlib.pyplot as plt

from sklearn.cluster import KMeans

from sklearn.cluster import MiniBatchKMeans

import pickle

import imp

import helita

cd ~/k-means/K-Means-IRIS/k-means

from helita import kmeans as km

Contributing

If you would like to improve the code or report a bug, your help is welcomed. Here are the steps:

1. Fork the repository.
2. Develop and test code changes.
3. Verify that tests pass successfully.
4. Start discussion or give feedback
5. Look over your changes in the diffs on the Compare page, make sure they’re what you want to submit.
6. Push to your fork repository
7. Go to the right of the Branch menu
8. Select the master branch, and click New pull request.

Credits

Juan Martinez-Sykora, Alberto Sainz-Dalda