def testEquals(self):
a = clusters.bicluster([1, 2, 3])
b = clusters.bicluster([1, 2, 3])
self.assertEquals(a, b)
self.assertFalse(a != b)
self.assertEquals(clusters.bicluster([], left=a),
clusters.bicluster([], left=b))
self.assertEquals(clusters.bicluster([], right=a),
clusters.bicluster([], right=b))
self.assertEquals(clusters.bicluster([], distance=2.5),
clusters.bicluster([], distance=2.5))
self.assertEquals(clusters.bicluster([], id=5),
clusters.bicluster([], id=5))
def testEquals(self):
a = clusters.bicluster([1, 2, 3])
b = clusters.bicluster([1, 2, 3])
self.assertEquals(a, b)
self.assertFalse(a != b)
self.assertEquals(clusters.bicluster([], left=a),
clusters.bicluster([], left=b))
self.assertEquals(clusters.bicluster([], right=a),
clusters.bicluster([], right=b))
self.assertEquals(clusters.bicluster([], distance=2.5),
clusters.bicluster([], distance=2.5))
self.assertEquals(clusters.bicluster([], id=5),
clusters.bicluster([], id=5))
def testNormal(self):
rows = [[6, 4, 2],
[2, 4, 6],
[1, 2, 3],
[3, 2, 1.01]]
clust = [clusters.bicluster(rows[i], id=i) for i in range(len(rows))]
c0 = clusters.bicluster(clusters.mergevecs(rows[1], rows[2]),
left=clust[1], right=clust[2], id=-1, distance=0.0)
c1 = clusters.bicluster(clusters.mergevecs(rows[0], rows[3]),
left=clust[0], right=clust[3], id=-2,
distance=clusters.pearson_dist(rows[0], rows[3]))
c2 = clusters.bicluster(clusters.mergevecs(c0.vec, c1.vec),
left=c0, right=c1, id=-3,
distance=clusters.pearson_dist(c0.vec, c1.vec))
self.assertEquals(c2, clusters.hcluster(rows))
def testNormal(self):
rows = [[6, 4, 2], [2, 4, 6], [1, 2, 3], [3, 2, 1.01]]
clust = [clusters.bicluster(rows[i], id=i) for i in range(len(rows))]
c0 = clusters.bicluster(clusters.mergevecs(rows[1], rows[2]),
left=clust[1],
right=clust[2],
id=-1,
distance=0.0)
c1 = clusters.bicluster(clusters.mergevecs(rows[0], rows[3]),
left=clust[0],
right=clust[3],
id=-2,
distance=clusters.pearson_dist(
rows[0], rows[3]))
c2 = clusters.bicluster(clusters.mergevecs(c0.vec, c1.vec),
left=c0,
right=c1,
id=-3,
distance=clusters.pearson_dist(c0.vec, c1.vec))
self.assertEquals(c2, clusters.hcluster(rows))