How to find the Laplacian Matrix with Network, please

Hi Dear

If we difine L_{ij} of the graph Laplacian are defined by L_{ij} = A_{ij}- k_i delta_{ij}, where A is the adjacency matrix, k_{i} is the degree of node i, delta_{ij} is the Kronecker delta, and where we do not sum over repeated indices.

N=200;L=100; coverage_range=20;

% random coordination

distinct_BOUND = 5;

P = zeros(N,2);

% rand(1,2)<0.05;

Q = rand(1,2)*L;

P(1,:) = Q;

for j = 2:N

u = true;

m = false;

while u || m

Q = rand(1,2)*L ;

% u is true if new added node is too far to all node

u = true;

for i = 1:j-1

if pdist([Q;P(i,:)],'euclidean') < coverage_range

%D = pdist(X) returns the Euclidean distance between pairs of observations in X.

u = false;

end

end

% m is true if new added node is too near to one node

m = false;

for i = 1:j-1

if pdist([Q;P(i,:)],'euclidean') < distinct_BOUND

m = true;

end

end

end

P(j,:) = Q;

end

figure;

OP=gscatter(P(:,1),P(:,2));

r = sprintf('N-%d,L-%d, cr-%d nodes', N, L, coverage_range);

could you help me to find Laplacian, I use Laplacian() but it didn't work, please