帮我写一段sobol灵敏度分析的matlab代码

当然可以，以下是Sobol灵敏度分析的MATLAB代码：

function [S, ST, S1] = sobol_analysis(model, lb, ub, n, m)
% Sobol灵敏度分析函数
% 输入：
% model：模型函数句柄
% lb：参数下限
% ub：参数上限
% n：采样点数
% m：阶数
% 输出：
% S：总方差贡献率
% ST：总方差
% S1：一阶方差贡献率

d = length(lb); % 参数维度
X = sobol_points(n, d); % 生成Sobol序列
Y = zeros(n, 1);

for ii = 1:n
    Xii = lb + (ub - lb) .* X(ii, :);
    Y(ii) = model(Xii);
end

S = zeros(d, m+1);
ST = var(Y); % 总方差

for k = 1:m
    S1 = zeros(d, k+1);
    for j = 1:k
        W = sobol_weights(k, j, d);
        Y1 = zeros(n, 2^k);
        for ii = 1:2^k
            Xii = lb + (ub - lb) .* sobol_points(n, d);
            Xii(:, j) = repmat(X(ii, j), n, 1); % 锁定第j维
            Y1(:, ii) = model(Xii);
        end
        S1(:, j) = sum(W .* Y1(:,:), 2);
    end
    S(:, k+1) = (2^(k-1)/n) * sum(S1, 2);
end

S1 = zeros(d, 1);
for j = 1:d
    W = sobol_weights(1, j, d);
    Y1 = zeros(n, 2);
    for ii = 1:2
        Xii = lb + (ub - lb) .* sobol_points(n, d);
        Xii(:, j) = repmat(X(ii, j), n, 1);
        Y1(:, ii) = model(Xii);
    end
    S1(j) = sum(W .* Y1(:,:), 2);
end

S(:, 1) = ST - sum(S, 2);
S1 = S1 ./ ST;
S = S ./ ST;
end

% Sobol序列
function X = sobol_points(n, d)
X = sobolset(d, 'Skip', 0);
X = net(X, n);
end

% Sobol权重
function W = sobol_weights(k, j, d)
W = zeros(2^k, d);
for ii = 1:2^k
    b = dec2bin(ii-1, k);
    b = padarray(b, [0, d-k], 'pre');
    W(ii, :) = 2 * (b(j,:) == '1') - 1;
end
end

这里使用了Sobol序列和Sobol权重的方法进行灵敏度分析，更多细节可以参考相关文献或者MATLAB帮助文档。