from collections import defaultdict
from heapq import heappop, heappush

def dijkstra(adj_list, start):
    dist = {node: float('inf') for node in adj_list}
    dist[start] = 0
    heap = [(0, start)]
    while heap:
        curr_dist, curr_node = heappop(heap)
        if curr_dist > dist[curr_node]:
            continue
        for neighbor, weight in adj_list[curr_node]:
            new_dist = curr_dist + weight
            if new_dist < dist[neighbor]:
                dist[neighbor] = new_dist
                heappush(heap, (new_dist, neighbor))
    return dist

def avg_distance(W, E, connections):
    # build adjacency list for western and eastern stations
    adj_west = defaultdict(list)
    adj_east = defaultdict(list)
    for i in range(W-1):
        adj_west[i+1].append((i+2, 1))
        adj_west[i+2].append((i+1, 1))
    for i in range(E-1):
        adj_east[i+1].append((i+2, 1))
        adj_east[i+2].append((i+1, 1))
    
    # calculate shortest distances from each western and eastern station to all others
    dist_west = {}
    dist_east = {}
    for i in range(1, W+1):
        dist_west[i] = dijkstra(adj_west, i)
    for i in range(1, E+1):
        dist_east[i] = dijkstra(adj_east, i)
    
    # calculate average distance for each option
    avg_dist = []
    for c in connections:
        west, east = c
        dist = 0
        count = 0
        for i in range(1, W+1):
            for j in range(1, E+1):
                if (i,j) != c:
                    dist += dist_west[i][west] + dist_east[j][east] + 1
                    count += 1
        avg_dist.append(dist/count)
    
    return avg_dist

# read input
T = int(input())
for case in range(1, T+1):
    W, E, C = map(int, input().split())
    connections = [tuple(map(int, input().split())) for _ in range(C)]
    result = avg_distance(W, E, connections)
    print(f"Case #{case}: {' '.join(f'{x:.6f}' for x in result)}")
from collections import defaultdict
from heapq import heappop, heappush

def dijkstra(adj_list, start):
    dist = {node: float('inf') for node in adj_list}
    dist[start] = 0
    heap = [(0, start)]
    while heap:
        curr_dist, curr_node = heappop(heap)
        if curr_dist > dist[curr_node]:
            continue
        for neighbor, weight in adj_list[curr_node]:
            new_dist = curr_dist + weight
            if new_dist < dist[neighbor]:
                dist[neighbor] = new_dist
                heappush(heap, (new_dist, neighbor))
    return dist

def avg_distance(W, E, connections):
    # build adjacency list for western and eastern stations
    adj_west = defaultdict(list)
    adj_east = defaultdict(list)
    for i in range(W-1):
        adj_west[i+1].append((i+2, 1))
        adj_west[i+2].append((i+1, 1))
    for i in range(E-1):
        adj_east[i+1].append((i+2, 1))
        adj_east[i+2].append((i+1, 1))
    
    # calculate shortest distances from each western and eastern station to all others
    dist_west = {}
    dist_east = {}
    for i in range(1, W+1):
        dist_west[i] = dijkstra(adj_west, i)
    for i in range(1, E+1):
        dist_east[i] = dijkstra(adj_east, i)
    
    # calculate average distance for each option
    avg_dist = []
    for c in connections:
        west, east = c
        dist = 0
        count = 0
        for i in range(1, W+1):
            for j in range(1, E+1):
                if (i,j) != c:
                    dist += dist_west[i][west] + dist_east[j][east] + 1
                    count += 1
        avg_dist.append(dist/count)
    
    return avg_dist

# read input
T = int(input())
for case in range(1, T+1):
    W, E, C = map(int, input().split())
    connections = [tuple(map(int, input().split())) for _ in range(C)]
    result = avg_distance(W, E, connections)
    print(f"Case #{case}: {' '.join(f'{x:.6f}' for x in result)}")