from collections import defaultdict

def dfs(graph, u, visited, path):
    visited[u] = True
    path.append(u)
    if u in graph['W']:
        graph['WE'].append(path[:])
    else:
        for v in graph[u]:
            if not visited[v]:
                dfs(graph, v, visited, path)
    path.pop()
    visited[u] = False

def calculate_average_distance(graph, options):
    # calculate paths between western and eastern stations
    graph['WE'] = []
    visited = defaultdict(bool)
    for w in graph['W']:
        dfs(graph, w, visited, [])
    num_paths = len(graph['WE'])
    
    # calculate average distance for each option
    avg_distances = []
    for i, (w, e) in enumerate(options):
        # calculate number of paths and total distance in the complete graph
        num_paths_total = num_paths + 2  # add two for direct connections to the overpass
        total_distance = sum(len(path)-1 for path in graph['WE'])
        total_distance += min(len(graph[w])-1, len(graph[e])-1)  # add direct connection to the overpass
        for path in graph['WE']:
            if w in path and e in path:
                total_distance -= len(path)-1  # subtract paths that pass through the overpass
                num_paths_total -= 1
        # calculate average distance
        avg_distance = total_distance / num_paths_total
        avg_distances.append(avg_distance)
    
    return avg_distances

# read input
T = int(input())
for t in range(1, T+1):
    W, E, C = map(int, input().split())
    graph = defaultdict(list)
    for i in range(1, W):
        u, v = i, int(input())
        graph[u].append(v)
        graph[v].append(u)
    for j in range(1, E):
        u, v = j, int(input())
        graph['W'].append(u)  # add eastern stations to the graph
        graph['E'].append(v)
        graph[u].append(v)
        graph[v].append(u)
    options = [tuple(map(int, input().split())) for _ in range(C)]
    
    # calculate and print output
    avg_distances = calculate_average_distance(graph, options)
    print("Case #{}: {}".format(t, " ".join("{:.6f}".format(d) for d in avg_distances)))