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Code located ==Summary== The code is in <code> E:\McNairprojects\Projects\FastCircles\src<hca The python3 file is main.py The code uses the AgglomerativeClustering from sklearn.cluster, which doesn't have GPU support. The input is a tdt file named CoLevelForCircles.txt with 7 columns: city state year lat lon coname datefirstinv The output is a tdt file named Results.tsv with 8 columns: (city, state, year) layer cluster ('lat','long','coname','datefirstinv') ==Documentation== There's useful reference material here: https://stackabuse.com/hierarchical-clustering-with-python-and-scikit-learn/ Note that it should be possible to use [https://www.tensorflow.org/api_docs/python/tf/contrib/factorization/code>KMeansClustering Tensorflow's KMeansClustering] to achieve the same result. ==Old Code Notes==
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This code takes a CoLevel master file, clusters points using k (number of clusters) in the range [1, num points / 5), and creates a file output.tsv.
Output.tsv has columns place, statecode, year, layer, cluster, lat, long, coname, datefirstinv. Layer is k, and cluster is the id of the cluster that the point belongs to.
The original version by Kyran and Oliver is in:
E:\McNair\Projects\FastCircles\src
You can run this program with:
<code>python3 main.py</code>
