from compas.datastructures import Network
HERE = os.path.dirname(__file__)
FILE = os.path.join(HERE, 'clusters.json')
network = Network()
network.update_default_node_attributes({'cluster': None, 'base': False})
cloud = Pointcloud.from_bounds(10, 5, 3, 100)
kmeans = KMeans(n_clusters=10, n_init=500, max_iter=100).fit(array(cloud, dtype=float))
clusters = {}
for i, point in zip(kmeans.labels_, cloud):
print(i)
if i not in clusters:
clusters[i] = []
clusters[i].append(point)
for index in clusters:
nodes = []
for point in clusters[index]:
node = network.add_node(x=point[0], y=point[1], z=point[2], cluster=index)
nodes.append(node)
x, y, z = centroid_points(clusters[index])
base = network.add_node(x=x, y=y, z=z, cluster=index, base=True)
for node in nodes:
network.add_edge(base, node)
network.to_json(FILE)
self.value = value or random.choice(range(20))
@property
def data(self):
return {'value': self.value}
@data.setter
def data(self, data):
self.value = data['value']
network = Network()
last_node = None
for i in range(12):
node = network.add_node(x=i // 3, y=i % 3, z=0)
network.node_attribute(node, 'weight', Weight())
if last_node:
network.add_edge(node, i - 1)
last_node = node
print(network.summary())
# print(network.to_data())
network.to_json(__file__ + '.json')
network2 = Network.from_json(__file__ + '.json')
print(network2.summary())
# print(network2.to_data())