PROGRAMMING:Importance calculation of nodes in social network graph
In social networks, individuals or units (nodes) are connected through certain relationships (edges). They are affected by these relationships, which can be understood as a kind of spreading interaction between interconnected nodes in the network, which can be enhanced or weakened. The importance of nodes in the network is different according to their location.
"Compactness Centrality" is used to measure the "speed" of a node arriving at other nodes. That is to say, a node with higher centrality can arrive at other nodes in the network faster (in the average sense) than a node with lower centrality, so it has more important value in the transmission process of the network. In a network with $$n $$nodes, node $$V_ Compactness centrality of I $$$CC (V)_ i) $$is mathematically defined as $$v_ I $$to all other nodes $$V_ The shortest distance of J $$($$J / ne I $$) $$d (V)_ i, v_ j) Reciprocal of the average of $$:
For unconnected graphs, the centrality of compactness of all nodes is 0.
Given an undirected graph with no right and a group of nodes, the compactness centrality of each node in the group is calculated.
###Input format:
Enter the first line to give two positive integers, $$n $$and $$M $$, where $$n $$($$Le 10 ^ 4 $$) is the number of nodes in the graph. By the way, assume that nodes are numbered from 1 to $$n $$$$ M $$($$Le 10 ^ 5 $$) is the number of edges. In the following $$M $$lines, each line gives the information of an edge, that is, the number of two nodes connected by the edge, separated by a space. The last line gives the number of $$k $$($$Le 100 $$) and the number of $$k $$nodes, separated by spaces.
###Output format:
Output the compactness centrality of $$k $$given nodes according to the format of 'CC (I) = x.xx'. Each output occupies one line, and the result is retained to 2 decimal places.
###Input example:
```in
9 14
1 2
1 3
1 4
2 3
3 4
4 5
4 6
5 6
5 7
5 8
6 7
6 8
7 8
7 9
3 3 4 9
```
###Output example:
```out
Cc(3)=0.47
Cc(4)=0.62
Cc(9)=0.35
```
answer：If there is no answer, please comment
"Compactness Centrality" is used to measure the "speed" of a node arriving at other nodes. That is to say, a node with higher centrality can arrive at other nodes in the network faster (in the average sense) than a node with lower centrality, so it has more important value in the transmission process of the network. In a network with $$n $$nodes, node $$V_ Compactness centrality of I $$$CC (V)_ i) $$is mathematically defined as $$v_ I $$to all other nodes $$V_ The shortest distance of J $$($$J / ne I $$) $$d (V)_ i, v_ j) Reciprocal of the average of $$:
For unconnected graphs, the centrality of compactness of all nodes is 0.
Given an undirected graph with no right and a group of nodes, the compactness centrality of each node in the group is calculated.
###Input format:
Enter the first line to give two positive integers, $$n $$and $$M $$, where $$n $$($$Le 10 ^ 4 $$) is the number of nodes in the graph. By the way, assume that nodes are numbered from 1 to $$n $$$$ M $$($$Le 10 ^ 5 $$) is the number of edges. In the following $$M $$lines, each line gives the information of an edge, that is, the number of two nodes connected by the edge, separated by a space. The last line gives the number of $$k $$($$Le 100 $$) and the number of $$k $$nodes, separated by spaces.
###Output format:
Output the compactness centrality of $$k $$given nodes according to the format of 'CC (I) = x.xx'. Each output occupies one line, and the result is retained to 2 decimal places.
###Input example:
```in
9 14
1 2
1 3
1 4
2 3
3 4
4 5
4 6
5 6
5 7
5 8
6 7
6 8
7 8
7 9
3 3 4 9
```
###Output example:
```out
Cc(3)=0.47
Cc(4)=0.62
Cc(9)=0.35
```
answer：If there is no answer, please comment