why do i get this error as no enough input arguments

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sanket neharkar
sanket neharkar 2022-11-16
回答： Image Analyst 2022-11-17
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

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回答（3 个）

Image Analyst
Image Analyst 2022-11-17
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.
Askic V
Askic V 2022-11-16
编辑：Askic V 2022-11-16
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)
Kevin Holly
Kevin Holly 2022-11-16
Ran in:
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

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