NetworkX 到 GraphLab 连通分量转换

Question

与以下 NetworkX 代码等效的 GraphLab 是什么？
for nodeset in nx.connected_components(G):

在 GraphLab 中，我想为每个连接的组件获取一组顶点 ID。

Answer 1

这是从 NetworkX 移植到 GraphLab 的第一个剪辑。但是，迭代似乎很慢。
temp1 = cc['component_id']
temp1.remove_column('__id')
id_set = set()
id_set = temp1['component_id']
for item in id_set:
nodeset = cc_out[cc_out['component_id'] == item]['__id']

Answer 2

graphlab.graph_analytics.connected_components返回的组件 ID 采用 SFrame 的形式，因此获取给定组件 ID 的最简单方法是过滤 SFrame：

# Make a graph with two components.
import graphlab
G = graphlab.SGraph().add_edges(
    [graphlab.Edge(i, i+1) for i in range(3)])
G = G.add_edges([graphlab.Edge(i, i+1) for i in range(4, 6)])

# Get the connected components.
cc = graphlab.connected_components.create(G)

# Find the vertices for a given component (0, in this example).
nodes = cc.component_id.filter_by(0, 'component_id')
print nodes

+------+--------------+
| __id | component_id |
+------+--------------+
|  5   |      0       |
|  6   |      0       |
|  4   |      0       |
+------+--------------+
[3 rows x 2 columns]

NetworkX 到 GraphLab 连通分量转换

NetworkX to GraphLab Connected Component Conversion

python

networkx

graphlab