def random(self, vectors):
weights = np.zeros([4, 80])
for i in range(80):
row = np.array([random_normal_01() for _ in range(4)])
weights[0][i], weights[1][i], weights[2][i], weights[3][i] = row / sum(row)
centers = np.array([(np.random.rand(2) * 180 - 90) * random_normal_01() for _ in range(4)])
return MultiFuzzyClustering(weights, centers, vectors)
def random(self, vectors):
clusters = np.array([random.choice([0, 1, 2, 3]) for _ in range(80)])
centers = np.array([
(np.random.rand(2) * 180 - 90) * random_normal_01()
for _ in range(4)
])
return Clustering(clusters, centers, vectors)
def random(self, vectors, neighbors):
weights = np.zeros([4, 80])
for i in range(80):
row = np.array([random_normal_01() for _ in range(4)])
weights[0][i], weights[1][i], weights[2][i], weights[3][
i] = row / sum(row)
return FuzzyClusteringNeighbors(weights, vectors, neighbors)
