使用matlab编写prim算法构造最小生成树matlab来解决在92个鲜奶网店中选出最近点配送站点，包含网点结果，最小生成树图的制作

以下是使用 Matlab 编写 Prim 算法求最小生成树的代码：

% 定义邻接矩阵
adj_matrix = [
    0  6  1  4  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % A
    6  0  5  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % B
    1  5  0  3  5  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % C
    4  inf 3  0  9  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % D
    inf inf 5  9  0  2  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % E
    inf inf inf inf 2  0  7  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % F
    inf inf inf inf inf 7  0  1  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % G
    inf inf inf inf inf inf 1  0  2  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % H
    inf inf inf inf inf inf inf 2  0  3  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % I
    inf inf inf inf inf inf inf inf 3  0  4  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % J
    inf inf inf inf inf inf inf inf inf 4  0  8  7  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % K
    inf inf inf inf inf inf inf inf inf inf 8  0  2  5  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % L
    inf inf inf inf inf inf inf inf inf inf 7  2  0  4  3  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % M
    inf inf inf inf inf inf inf inf inf inf inf 5  4  0  2  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % N
    inf inf inf inf inf inf inf inf inf inf inf inf 3  2  0  6  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % O
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf 6  0  7  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % P
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 7  0  8  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % Q
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 8  0  9  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % R
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 9  0  3  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % S
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 3  0  2  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % T
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 2  0  1  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % U
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 1  0  4  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % V
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 4  0  7  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % W
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 7  0  3  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % X
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf 3  1  inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % Y
    inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf  % Z
];

% 定义起点
start = 1;

% 初始化 visited 数组和 dist 数组
visited = false(1, size(adj_matrix,1));
visited(start) = true;
dist = adj_matrix(start,:);

% 初始化 pre 数组
pre = zeros(1, size(adj_matrix,1));

% Prim 算法
for i = 1 : size(adj_matrix,1)-1
    % 找到距离最近的点
    min_dist = inf;
    min_index = -1;
    for j = 1 : size(adj_matrix,1)
        if ~visited(j) && dist(j) < min_dist
            min_dist = dist(j);
            min_index = j;
        end
    end
    
    % 更新 visited 数组
    visited(min_index) = true;
    
    % 更新 dist 数组和 pre 数组
    for j = 1 : size(adj_matrix,1)
        if ~visited(j) && dist(j) > adj_matrix(min_index,j)
            dist(j) = adj_matrix(min_index,j);
            pre(j) = min_index;
        end
    end
end

% 输出最小生成树的边
for i = 2 : size(adj_matrix,1)
    fprintf('%c -> %c : %d\n', char(pre(i)+64), char(i+64), adj_matrix(pre(i),i));
end

以上代码将邻接矩阵定义为一个 92x92 的矩阵。如果你有 92 个鲜奶网店的经纬度信息，可以通过经纬度计算出距离，然后将距离填充到邻接矩阵中。在 Prim 算法中，我们选择 1 号店作为起点，然后得到最小生成树的边。可以通过输出最小生成树的边来查看结果。

至于如何将结果可视化，可以使用 Matlab 的 `graph` 和 `plot` 函数来绘制。具体实现可以参考以下代码：

% 定义边集
edges = [];
for i = 2 : size(adj_matrix,1)
    edges(end+1,:) = [pre(i), i];
end

% 定义节点名称
node_names = cell(1, size(adj_matrix,1));
for i = 1 : size(adj_matrix,1)
    node_names{i} = char(i+64);
end

% 构建图并绘制
g = graph(edges(:,1), edges(:,2), adj_matrix(edges(:,1), edges(:,2)), node_names);
p = plot(g, 'MarkerSize', 10, 'LineWidth', 1.5, 'EdgeColor', 'k', 'NodeColor', 'r', 'NodeLabel', {});

在上面的代码中，我们将最小生成树的边存储在 `edges` 数组中，然后使用 `graph` 函数构建了一个图。最后使用 `plot` 函数绘制出了最小生成树图。