Using K-means Analysis to Classify Synthetic Spectral Profiles from Numerical Simulations of the Solar Atmosphere
Works on MacOS, Linux, and Windows.
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Download the Python 3.6 version (can also download 2.7 version if necessary)
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Clone the latest version of helita from Github: git clone https://github.com/jamiehuang00/K-Means-IRIS and download to desktop
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Use Terminal to compile and run the code
Python libraries used: iPython, matplotlib, scipy, numpy
Requires Python 3.0 or higher.
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
If you would like to improve the code or report a bug, your help is welcomed. Here are the steps:
- Fork the repository.
- Develop and test code changes.
- Verify that tests pass successfully.
- Start discussion or give feedback
- Look over your changes in the diffs on the Compare page, make sure they’re what you want to submit.
- Push to your fork repository
- Go to the right of the Branch menu
- Select the master branch, and click New pull request.
Juan Martinez-Sykora, Alberto Sainz-Dalda