tvii: tests/test_kmeans.py comparison

add kmeans + dataset

comparison

equal deleted inserted replaced

-:b56d329c238d
+:9d5a5e9f5c3b
+#!/usr/bin/env python
+"""
+tests K means algorithm
+"""
+import unittest
+from tvii import kmeans
+from nettwerk.dataset.circle import CircularRandom
+class TestKMeans(unittest.TestCase):
+def test_dualing_gaussians(self):
+"""tests two gaussian distributions;  first, cut overlap"""
+# TODO
+def test_circles(self):
+"""test with two circles of points"""
+# generate two non-overlapping circles
+n_points = 10000   # per circle
+p1 = CircularRandom((-1.5, 0), 1)(n_points)
+p2 = CircularRandom((1.5, 0), 1)(n_points)
+# run kmeans
+classes, centroids = kmeans.kmeans(p1+p2, 2)
+# sanity
+assert len(centroids) == 2
+assert len(classes) == 2
+# the centroids should have opposite x values
+xprod = centroids[0][0] * centroids[1][0]
+assert xprod < 0.
+assert abs(xprod + 2.25) < 0.1
+# assert we're kinda close
+for c in centroids:
+c = [abs(i) for i in c]
+assert abs(c[0]-1.5) < 0.1
+assert abs(c[1]) < 0.1
+# its a pretty clean break; our points should be exact, most likely
+if centroids[0][0] < 0.:
+left = 0
+right = 1
+else:
+left = 1
+right = 0
+assert sorted(p1) == sorted(classes[left])
+assert sorted(p2) == sorted(classes[right])
+def test_help(self):
+"""smoketest for CLI"""
+try:
+kmeans.main(['--help'])
+except SystemExit:
+# this is expected
+pass
+if __name__ == '__main__':
+unittest.main()

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