def check_kmeans_lost_cluster(self, level=1):
"""This will cause kmean to have a cluster with no points."""
data = N.fromfile(open(DATAFILE1), sep = ", ")
data = data.reshape((200, 2))
initk = N.array([[-1.8127404, -0.67128041],
[ 2.04621601, 0.07401111],
[-2.31149087,-0.05160469]])
res = kmeans(data, initk)
res = kmeans2(data, initk, missing = 'warn')
try :
res = kmeans2(data, initk, missing = 'raise')
raise AssertionError("Exception not raised ! Should not happen")
except ClusterError, e:
print "exception raised as expected: " + str(e)
def check_kmeans_simple(self, level=1):
initc = N.concatenate(([[X[0]], [X[1]], [X[2]]]))
code = initc.copy()
code1 = kmeans(X, code, iter = 1)[0]
assert_array_almost_equal(code1, CODET2)
