def test():
anp = np.random.randn(4, 5)
a = lg.array(anp)
assert np.array_equal(lg.argmin(a, axis=0), np.argmin(anp, axis=0))
assert np.array_equal(lg.argmin(a, axis=1), np.argmin(anp, axis=1))
return
def test():
np.random.seed(50)
datanp = np.random.randn(2000000, 3)
data = lg.array(datanp)
pointsnp = np.random.choice(lg.arange(len(data)), 4, False)
points = lg.array(pointsnp)
centroids = data[points]
centroidsnp = datanp[pointsnp]
sqdists = lg.zeros((4, len(data)))
sqdistsnp = np.zeros((4, len(datanp)))
for i in range(4):
vec = data - centroids[i]
vecnp = datanp - centroidsnp[i]
sqdists[i] = lg.linalg.norm(vec, axis=1)
sqdistsnp[i] = np.linalg.norm(vecnp, axis=1)
clusters = lg.argmin(sqdists, axis=0)
clustersnp = np.argmin(sqdistsnp, axis=0)
assert lg.array_equal(lg.where(clusters == 0), np.where(clustersnp == 0))
def relabel(pairwise_distances, data_index):
new_labels = np.argmin(pairwise_distances, axis=1)
distances = pairwise_distances[data_index, new_labels]
return new_labels, distances
def relabel(pairwise_distances):
return np.argmin(pairwise_distances, axis=1)