why do i get this error as no enough input arguments

function [J,distinct_d]=jd(X,p)

% Computes the distances between all pairs of points in a sampling

% plan X using the p–norm, sorts them in ascending order and

% removes multiple occurrences.

%

% Inputs:

% X – sampling plan being evaluated

% p – distance norm (p=1 rectangular – default, p=2 Euclidean)

%

% Outputs:

% J – multiplicity array (that is, the number of pairs

% separated by each distance value).

% distinct_d – list of distinct distance values

if ~exist('p','var')

p=1;

end

% Number of points in the sampling plan

n=size(X,1);

% Compute the distances between all pairs of points

d=zeros(1,n*(n-1)/2);

for i=1:n-1

for j=i+1:n

% Distance metric: p–norm

d((i-1)*n-(i-1)*i/2+j-i)=norm(X(i,:)-X(j,:),p);

end

end

% Remove multiple occurrences

distinct_d=unique(d);

% Pre-allocate memory for J

J =zeros(size(distinct_d));

% Generate multiplicity array

for i=1:length(distinct_d)

% J(i) will contain the number of pairs separated

% by the distance distinct_d(i)

J(i)=sum(ismember(d,distinct_d(i)));

end

after this wheni am running this code i am gettimg a error as no enough arguments

this code i have taken from a book

Answer 1

[Image Analyst]

You can't just push the green run triangle because it won't know what you want for the input arguments. You have to either

1. call the function with a script or function in another m-file, or
2. call it in a script defined before the function in the same m-file. In this case the function will have to have "end" as the last line.

Answer 2

[Askic V]

You're probably executing this code as a Matlab script. You need to make a function call.

This code should be saved in a separate file called jd.m.

and in Matlab command windows make a coll of this function, like:

[j_out,d_out] = jd(X,1)

Answer 3

[Kevin Holly]

I just ran the code without getting an error.

x = 10*rand(4,2)

x = 4×2

9.1847 5.8076 4.9108 6.3358 3.5890 2.8121 4.7894 9.1143

[J,distinct_d] = jd(x,1)

J = 1×6

1 1 1 1 1 1

distinct_d = 1×6

2.8999 4.8020 4.8455 7.5026 7.7020 8.5911

function [J,distinct_d]=jd(X,p)
% Computes the distances between all pairs of points in a sampling
% plan X using the p–norm, sorts them in ascending order and
% removes multiple occurrences.
%
% Inputs:
% X – sampling plan being evaluated
% p – distance norm (p=1 rectangular – default, p=2 Euclidean)
%
% Outputs:
% J – multiplicity array (that is, the number of pairs
% separated by each distance value).
% distinct_d – list of distinct distance values
if ~exist('p','var')
p=1;
end
% Number of points in the sampling plan
n=size(X,1);
% Compute the distances between all pairs of points
d=zeros(1,n*(n-1)/2);
for i=1:n-1
    for j=i+1:n
    % Distance metric: p–norm
    d((i-1)*n-(i-1)*i/2+j-i)=norm(X(i,:)-X(j,:),p);
    end
end
% Remove multiple occurrences
distinct_d=unique(d);
% Pre-allocate memory for J
J =zeros(size(distinct_d));
% Generate multiplicity array
for i=1:length(distinct_d)
% J(i) will contain the number of pairs separated
% by the distance distinct_d(i)
J(i)=sum(ismember(d,distinct_d(i)));
end
end