Out of memory. The likely cause is an infinite recursion within the program.

% Bus Admittance Matrix
% Copyright (c) 1998 by H. Saadat.
function[Ybus] = ybus(zdata)
nl=zdata(:,1); nr=zdata(:,2); R=zdata(:,3); X=zdata(:,4);
nbr=length(zdata(:,1)); nbus = max(max(nl), max(nr));
Z = R + j*X; %branch impedance
y= ones(nbr,1)./Z; %branch admittance
Ybus=zeros(nbus,nbus); % initialize Ybus to zero
for k = 1:nbr; % formation of the off diagonal elements
    if nl(k) > 0 & nr(k) > 0
        Ybus(nl(k),nr(k)) = Ybus(nl(k),nr(k)) - y(k);
        Ybus(nr(k),nl(k)) = Ybus(nl(k),nr(k));
    end
end
for n = 1:nbus % formation of the diagonal elements
    for k = 1:nbr
        if nl(k) == n | nr(k) == n
            Ybus(n,n) = Ybus(n,n) + y(k);
        else, end
    end
end

i want to run this code but i get this error Out of memory. The likely cause is an infinite recursion within the program.

% From To R X
zdata = [ 0 1 0 1.0
    0 2 0 0.8
    1 2 0 0.4
    1 3 0 0.2
    2 3 0 0.2
    3 4 0 0.08];
[Ybus] = ybus(zdata) % bus admittance matrix
Ibus = [-j*1.1; -j*1.25; 0; 0]; % vector of injected bus currents
Zbus = inv(Ybus) % bus impedance matrix
Vbus = Zbus*Ibus
%Vbus = Ybus\Ibus

Answer 1

[essrra]

function [neighborIds, neighborDistances] = kNearestNeighbors(dataMatrix, queryMatrix, k)

%--------------------------------------------------------------------------

% Program to find the k - nearest neighbors (kNN) within a set of points.

% Distance metric used: Euclidean distance

%

% Usage:

% [neighbors distances] = kNearestNeighbors(dataMatrix, queryMatrix, k);

% dataMatrix (N x D) - N vectors with dimensionality D (within which we search for the nearest neighbors)

% queryMatrix (M x D) - M query vectors with dimensionality D

% k (1 x 1) - Number of nearest neighbors desired

%

% Example:

% a = [1 1; 2 2; 3 2; 4 4; 5 6];

% b = [1 1; 2 1; 6 2];

% [neighbors distances] = kNearestNeighbors(a,b,2);

%

% Output:

% neighbors =

% 1 2

% 1 2

% 4 3

%

% distances =

% 0 1.4142

% 1.0000 1.0000

% 2.8284 3.0000

%--------------------------------------------------------------------------

neighborIds = zeros(size(queryMatrix,1),k);

neighborDistances = neighborIds;

numDataVectors = size(dataMatrix,1);

numQueryVectors = size(queryMatrix,1);

for i=1:numQueryVectors

dist = sum((repmat(queryMatrix(i,:),numDataVectors,1)-dataMatrix).^2,2);

[sortval, sortpos] = sort(dist,'ascend');

neighborIds(i,:) = sortpos(1:k);

neighborDistances(i,:) = sqrt(sortval(1:k));

endfunction [neighborIds, neighborDistances] = kNearestNeighbors(dataMatrix, queryMatrix, k)

%--------------------------------------------------------------------------

% Program to find the k - nearest neighbors (kNN) within a set of points.

% Distance metric used: Euclidean distance

%

% Usage:

% [neighbors distances] = kNearestNeighbors(dataMatrix, queryMatrix, k);

% dataMatrix (N x D) - N vectors with dimensionality D (within which we search for the nearest neighbors)

% queryMatrix (M x D) - M query vectors with dimensionality D

% k (1 x 1) - Number of nearest neighbors desired

%

% Example:

% a = [1 1; 2 2; 3 2; 4 4; 5 6];

% b = [1 1; 2 1; 6 2];

% [neighbors distances] = kNearestNeighbors(a,b,2);

%

% Output:

% neighbors =

% 1 2

% 1 2

% 4 3

%

% distances =

% 0 1.4142

% 1.0000 1.0000

% 2.8284 3.0000

%--------------------------------------------------------------------------

neighborIds = zeros(size(queryMatrix,1),k);

neighborDistances = neighborIds;

numDataVectors = size(dataMatrix,1);

numQueryVectors = size(queryMatrix,1);

for i=1:numQueryVectors

dist = sum((repmat(queryMatrix(i,:),numDataVectors,1)-dataMatrix).^2,2);

[sortval, sortpos] = sort(dist,'ascend');

neighborIds(i,:) = sortpos(1:k);

neighborDistances(i,:) = sqrt(sortval(1:k));

endfunction [neighborIds, neighborDistances] = kNearestNeighbors(dataMatrix, queryMatrix, k)

%--------------------------------------------------------------------------

% Program to find the k - nearest neighbors (kNN) within a set of points.

% Distance metric used: Euclidean distance

%

% Usage:

% [neighbors distances] = kNearestNeighbors(dataMatrix, queryMatrix, k);

% dataMatrix (N x D) - N vectors with dimensionality D (within which we search for the nearest neighbors)

% queryMatrix (M x D) - M query vectors with dimensionality D

% k (1 x 1) - Number of nearest neighbors desired

%

% Example:

% a = [1 1; 2 2; 3 2; 4 4; 5 6];

% b = [1 1; 2 1; 6 2];

% [neighbors distances] = kNearestNeighbors(a,b,2);

%

% Output:

% neighbors =

% 1 2

% 1 2

% 4 3

%

% distances =

% 0 1.4142

% 1.0000 1.0000

% 2.8284 3.0000

%--------------------------------------------------------------------------

neighborIds = zeros(size(queryMatrix,1),k);

neighborDistances = neighborIds;

numDataVectors = size(dataMatrix,1);

numQueryVectors = size(queryMatrix,1);

for i=1:numQueryVectors

dist = sum((repmat(queryMatrix(i,:),numDataVectors,1)-dataMatrix).^2,2);

[sortval, sortpos] = sort(dist,'ascend');

neighborIds(i,:) = sortpos(1:k);

neighborDistances(i,:) = sqrt(sortval(1:k));

endV

i want to run this code but i get this error Out of memory. The likely cause is an infinite recursion within the program.

Answer 2

[Walter Roberson]

Put the function after the script.

% From To R X
zdata = [ 0 1 0 1.0
    0 2 0 0.8
    1 2 0 0.4
    1 3 0 0.2
    2 3 0 0.2
    3 4 0 0.08];
[Ybus] = ybus(zdata) % bus admittance matrix

Ybus = 
   0.0000 - 8.5000i   0.0000 + 2.5000i   0.0000 + 5.0000i   0.0000 + 0.0000i
   0.0000 + 2.5000i   0.0000 - 8.7500i   0.0000 + 5.0000i   0.0000 + 0.0000i
   0.0000 + 5.0000i   0.0000 + 5.0000i   0.0000 -22.5000i   0.0000 +12.5000i
   0.0000 + 0.0000i   0.0000 + 0.0000i   0.0000 +12.5000i   0.0000 -12.5000i

Ibus = [-j*1.1; -j*1.25; 0; 0]; % vector of injected bus currents
Zbus = inv(Ybus) % bus impedance matrix

Zbus = 
   0.0000 + 0.5000i   0.0000 + 0.4000i   0.0000 + 0.4500i   0.0000 + 0.4500i
   0.0000 + 0.4000i   0.0000 + 0.4800i   0.0000 + 0.4400i   0.0000 + 0.4400i
   0.0000 + 0.4500i   0.0000 + 0.4400i   0.0000 + 0.5450i   0.0000 + 0.5450i
   0.0000 + 0.4500i   0.0000 + 0.4400i   0.0000 + 0.5450i   0.0000 + 0.6250i

Vbus = Zbus*Ibus

Vbus = 4×1

1.0500 1.0400 1.0450 1.0450

%Vbus = Ybus\Ibus

% Bus Admittance Matrix
% Copyright (c) 1998 by H. Saadat.
function[Ybus] = ybus(zdata)
nl=zdata(:,1); nr=zdata(:,2); R=zdata(:,3); X=zdata(:,4);
nbr=length(zdata(:,1)); nbus = max(max(nl), max(nr));
Z = R + j*X; %branch impedance
y= ones(nbr,1)./Z; %branch admittance
Ybus=zeros(nbus,nbus); % initialize Ybus to zero
for k = 1:nbr; % formation of the off diagonal elements
    if nl(k) > 0 & nr(k) > 0
        Ybus(nl(k),nr(k)) = Ybus(nl(k),nr(k)) - y(k);
        Ybus(nr(k),nl(k)) = Ybus(nl(k),nr(k));
    end
end
for n = 1:nbus % formation of the diagonal elements
    for k = 1:nbr
        if nl(k) == n | nr(k) == n
            Ybus(n,n) = Ybus(n,n) + y(k);
        else, end
    end
end
end