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IDL implementation of a Bisecting Clustering algorithm.

License: BSD 3-Clause "New" or "Revised" License

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bisectingclustering's Introduction

BisectingClustering

This is an implementation of a Divisive Bisecting Clustering algorithm.

This is the IDL implementation by Dr. Christiaan Boersma ([email protected]) and used in the publications:

--- Boersma, C., Bregman, J., Allamandola, L.J., "The Charge State of Polycyclic Aromatic Hydrocarbons Across Reflection Nebulae: PAH Charge Balance and Calibration", 2016, ApJ, 832, 51 https://doi.org/10.3847/0004-637X/832/1/51 ---

--- Boersma, C., Bregman, J., Allamandola, L.J., "Properties of Polycyclic Aromatic Hydrocarbons in the Northwest Photon Dominated Region of NGC 7023. II. Traditional PAH Analysis Using k-means as a Visualization Tool", 2014, ApJ, 795, 110 https://doi.org/10.1088/0004-637X/795/2/110 ---

When using this code, please refer to:

--- Boersma, C., Bregman, J., Allamandola, L.J., "The Charge State of Polycyclic Aromatic Hydrocarbons Across Reflection Nebulae: PAH Charge Balance and Calibration", 2016, ApJ, 832, 51 https://doi.org/10.3847/0004-637X/832/1/51 ---

Note that the sklearn package offers a similar, though not identical, Python implementation of a Bisecting K-Means algorithm in its cluster module (sklearn.cluster.BisectingKMeans).

Inputs

  1. data: the data to cluster (samples x features).
  2. img2: bisection_max: maximum number of bisections. The expected number of bins is 2 x bisection_max.
  3. min_samples: minimum number of samples needed to be considered a bin.

Outputs

  1. bin_labels: the label for each sample it belongs to (samples).

Basic Usage

Given 2 test data formatted as samples x features

 bin_labels = BISECTINGCLUSTERING(data, 2, 10)

Advanced Usage

A spectral cube (n, m, w). For example

bin_labels = REFORM( $
               BISECTINGCLUSTERING( $
                 REFORM(cube, n * m, w), 2, 10), n, m)

Authors

  • Christiaan Boersma - Initial work - PAHdb

License

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details

Acknowledgments

  • The NASA Ames PAH IR Spectroscopic Database Team
  • The Astrophysics & Astrochemistry Laboratory at NASA Ames Research Center - www.astrochemistry.org

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