I am new to MATLAB and trying to learn Bayesian Networks.
Running this code shows an error
Index exceeds matrix dimensions.
in line
( for r = 1:length(nodes(root(rr)).values))
Please help me out with this.
Thanks in Advance
function [nodes, edges] = bnMsgPassInitiate(nodes, edges, root)
N = numel(nodes);
for X = 1:N % for every node
nodes(X).lambda = ones(1, length(nodes(X).values)); % l(x) = 1
Z = nodes(X).parents;
for pa = 1:length(Z) % for each parent of X
edges(Z(pa),X).lambdaX = ones(1, length(nodes(Z(pa)).values)); % lX(z) = 1
end
Y = nodes(X).children;
for ch = 1:length(Y) % for each child of X
edges(X,Y(ch)).peyeX = ones(1, length(nodes(X).values)); % peyeY(x)
end
end
numRoots = length(root);
for rr = 1:numRoots
**for r = 1:length(nodes(root(rr)).values)**
nodes(root(rr)).peye(r) = nodes(root(rr)).CPT(r);
nodes(root(rr)).P(r) = nodes(root(rr)).CPT(r);
end
childrenR = nodes(root(rr)).children;
for cr = 1:length(childrenR)
[nodes, edges] = bnMsgPassSendPiMsg(root(rr), childrenR(cr), nodes, edges, []); %A = []
end
end
Matlab Index Exceeds Matrix Dimensions Error
In MATLAB, an ‘index exceeds matrix dimensions error’ is encountered when we try accessing an element in the array/matrix which is not in the index or not present in the array/matrix. The simple way to resolve this error is by ensuring that we are trying to access the element in the matrix or array. The array’s length should be greater than or equal to the index we call or attempt to access.
In the latest versions of MATLAB (Starting from R2018b), the error message is:
“Index exceeds the number of array elements.”
Syntax:
If A is an array, then we access any element of it using the below syntax:
E = A(n)Where ‘n’ is the element index we want to access.
If ‘n’ is greater than the number of elements in the array, then we get the index exceeds matrix dimensions’ error in the case of a matrix or the’ index exceeds the number of array elements’ error in the case of an array.
Examples of Matlab Index Exceeds Matrix Dimensions
Let us now understand how we get this error in MATLAB and how to resolve it.
Example #1
In the first example, we will create an array with five elements and try accessing the 7th element of this array (which does not exist). This will result in an index exceed dimensions error. The steps to be followed for this example are:
- Initialize the array
- Try accessing the element which is out of the index
Code:
A = [3, 5, 1, 7, 10][Creating the array with five elements]
E = A(7)
[Code to access the 7th element of the array A]
[Since the 7th element does not exist in array A, we will get the error message]
This is how our input and output will look in the Matlab command window:
Input:
A = [3, 5, 1, 7, 10]
E = A(7)Output:
As we can see in the output, we got the error message since we are trying to access an element that does not exist in the array. To overcome this error, we must try accessing an element in the range, i.e., for E = A(n), ‘n’ must be less than or equal to 5.
Example #2
In this example, we will create a matrix of size 3 X 3 and try accessing an element in the 4th row (which does not exist). This will result in an index exceed dimensions error. The steps to be followed for this example are:
- Initialize the matrix
- Try accessing the element which is out of the index
Code:
A = [3, 5, 1; 7, 10, 5; 3, 6, 9][Creating the matrix of the order 3 X 3]
E = A(4, 2)
[Code to access the 2nd element in the 4th row of the matrix A]
[Since the 4th row does not exist in matrix A, we will get the error message]
This is how our input and output will look in the Matlab command window:
Input:
A = [3, 5, 1; 7, 10, 5; 3, 6, 9]
E = A(4, 2)Output:
As we can see in the output, we got the error message since we are trying to access an element that does not exist in the matrix. To overcome this error, we must try accessing an element in the range, i.e., for E = A(m, n), ‘m’ and ‘n’ must be less than or equal to 3.
Example #3
In this example, we will create a matrix of size 4 X 4 and try accessing an element in the 5th column (which does not exist). This will result in an index exceed dimensions error. The steps to be followed for this example are:
- Initialize the matrix
- Try accessing the element which is out of the index
Code:
A = [3, 15, 10, 4; 4, 5, 8, 0; 13, 5, 7, 10; 3, 4, 1, 6][Creating the matrix of the order 4 X 4]
E = A(4, 5)
[Code to access the 4th element in the 5th column of the matrix A]
[Since the 5th column does not exist in the matrix M, we will get the error message]
This is how our input and output will look in the Matlab command window:
Input:
A = [3, 15, 10, 4; 4, 5, 8, 0; 13, 5, 7, 10; 3, 4, 1, 6]
E = A(4, 5)Output:
As we can see in the output, we got the error message since we are trying to access an element that does not exist in the matrix. To overcome this error, we must try accessing a part in the range, i.e., for E = A(m, n), ‘m’ and ‘n’ must be less than or equal to 4.
Conclusion
‘Index exceeds matrix dimensions error’ is encountered when we try accessing an element in the array or matrix which is not in the index or not present in the array/matrix. In the latest versions of MATLAB (Starting from R2018b), the error message is: “Index exceeds the number of array elements (n)”. We can resolve this error by ensuring that the index we are trying to access is within the range of the array or matrix.
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Hi,
Im new to MATLAB and am trying to extract data from a sine wave. I’ve set the threshold to -1 SD and want all of the data below it to stack into one matrix. In other words, M has to be a stacked product of P. However, at the last part of the code it gives the error: Index Exceeds Matrix Dimensions. From what I understand, this means that length(P)+P(i)>length(noise). So the logical thing to do would be to make ‘noise’ bigger or P(i) smaller. However, I can’t seem to get rid of the error. I was told not to index so far into P, but i have no idea how to do that. Hopefully someone can help me with this!
clear all
hold off
srate=1000;
t=1:99/srate:10;
noiseAmplitude=2;
a=4;
f=4;
signal=a*sin(2*pi*f*t);
noise= signal + noiseAmplitude*randn(1,length(signal));
standdev=std(noise);
P=find(diff(noise<-standdev)==1);
for i=1:length(P)
M(i,:)=noise(P(i):P(i)+10); (<— ERROR: index exceeds matrix dimensions)
end
plot(M)
Accepted Answer
P =
2 27 32 34 37 50 52 60 65 68 70 75 90
P+10
ans =
12 37 42 44 47 60 62 70 75 78 80 85 100
Therefore P+10 exceeds the size of noise, and is giving you the error.
How you go about fixing it depends what you want to achieve in those cases. This one would fill in the rightmost part of array M:
for i=1:length(P)
offset = min(10, size(noise,2)-P(i));
M(i,(end-offset):end)=noise(P(i):P(i)+offset);
end
More Answers (11)
I don’t fully understand what you are trying to do here, but I can tell you how to examine the issue. With any kind of error, it’s often easiest to set a breakpoint at the line the error occurs. With an error in a loop, however, it could be many iterations before you actually hit the parameter combination that will cause the error. In that case, it’s probably easiest to just run this at the command line:
Now MATLAB will automatically go into debug mode as soon as it encounters an error. Once in debug mode, you can examine the variables and see where the issue is. Of course, in your particular code, the exact iteration may change every time because of the randomized noise.
I suspect that you don’t actually want to index into «P» using «10» as an offset to the next index value, when «P» already contains index values itself. But I don’t fully understand your workflow, so I can’t be sure.
-Cam
Hi , i have an error in line 18,
kindly need helps
Index exceeds matrix dimensions.
Error in guidedfilter_color (line 18)
mean_I_g = boxfilter(I(:, :, 2), r) ./ N;
function q = guidedfilter_color(I, p, r, eps)
I = double(imread(‘.img_smoothingcat.bmp’)) / 255;
p = I;
r = 4;
eps = 0.2^2;
[hei, wid] = size(p);
N = boxfilter(ones(hei, wid), r);
mean_I_r = boxfilter(I(:, :, 1), r) ./ N;
mean_I_g = boxfilter(I(:, :, 2), r) ./ N;
mean_I_b = boxfilter(I(:, :, 3), r) ./ N;
mean_p = boxfilter(p, r) ./ N;
mean_Ip_r = boxfilter(I(:, :, 1).*p, r) ./ N;
mean_Ip_g = boxfilter(I(:, :, 2).*p, r) ./ N;
mean_Ip_b = boxfilter(I(:, :, 3).*p, r) ./ N;
cov_Ip_r = mean_Ip_r — mean_I_r .* mean_p;
cov_Ip_g = mean_Ip_g — mean_I_g .* mean_p;
cov_Ip_b = mean_Ip_b — mean_I_b .* mean_p;
var_I_rr = boxfilter(I(:, :, 1).*I(:, :, 1), r) ./ N — mean_I_r .* mean_I_r;
var_I_rg = boxfilter(I(:, :, 1).*I(:, :, 2), r) ./ N — mean_I_r .* mean_I_g;
var_I_rb = boxfilter(I(:, :, 1).*I(:, :, 3), r) ./ N — mean_I_r .* mean_I_b;
var_I_gg = boxfilter(I(:, :, 2).*I(:, :, 2), r) ./ N — mean_I_g .* mean_I_g;
var_I_gb = boxfilter(I(:, :, 2).*I(:, :, 3), r) ./ N — mean_I_g .* mean_I_b;
var_I_bb = boxfilter(I(:, :, 3).*I(:, :, 3), r) ./ N — mean_I_b .* mean_I_b;
a = zeros(hei, wid, 3);
for y=1:hei
for x=1:wid
Sigma = [var_I_rr(y, x), var_I_rg(y, x), var_I_rb(y, x);
var_I_rg(y, x), var_I_gg(y, x), var_I_gb(y, x);
var_I_rb(y, x), var_I_gb(y, x), var_I_bb(y, x)];
cov_Ip = [cov_Ip_r(y, x), cov_Ip_g(y, x), cov_Ip_b(y, x)];
a(y, x, 
= cov_Ip * inv(Sigma + eps * eye(3));
end
end
b = mean_p — a(:, :, 1) .* mean_I_r — a(:, :, 2) .* mean_I_g — a(:, :, 3) .* mean_I_b;
q = (boxfilter(a(:, :, 1), r).* I(:, :, 1)…
+ boxfilter(a(:, :, 2), r).* I(:, :, 2)…
+ boxfilter(a(:, :, 3), r).* I(:, :, 3)…
+ boxfilter(b, r)) ./ N;
figure();imshow(q)
end
Bmp files are not always rgb.
And when they are rgb then
is always wrong.
[hei, wid, panes] = size(p);
Index exceeds matrix dimensions.
Error in feasmbll (line 21)
kk(ii,jj)=kk(ii,jj)+k(i,j)
function [kk]=feasmbll(kk,k,index)
edof=length(index);
for i=1:edof
ii=index(i);
for j=1:edof
jj=index(j);
26. kk(ii,jj)=kk(ii,jj)+k(i,j)
end
end
end
could you help me
kindly
The issue is with the line:
M(i,:)=noise(P(i):P(i)+10);
You want to take the index P(i) and grab the next 10 elements after that point, then put them into a row in M. This works fine for the first several iterations where P is picking out relatively small indices. However, some of the elements of P are picking out array elements near the end of noise, so there aren’t 10 elements after those points to grab.
To put it more concretely, here is what P contains when I ran the code:
>> P
P =
2 12 14 20 27 30 32 40 55 65 70 75 78 80 88
So, when you get to the last element of P, 88, you will want to grab elements 88-98 from noise and put them into M. However, noise only has 91 elements:
So to fix this error you need to replace the +10 with something else. You can use min(diff(P)) to see the minimum distance between consecutive indices in P, or min(abs(P-length(noise))) to see how close the last element in P is to the end of noise, or maybe you could just loop to length(P)-1 or length(P)-2, avoiding the last few large indices in P.
for i=1:s/k sum=0; for j=1:k sum=m((i-1)*k+j)+sum; <—(ERROR: index exceeds matrix dimensions) end M(i)=sum/k;
what can be done here?
Rmin = 60;
Rmax = 100;
[center, radius] = imfindcircles(RGB,[Rmin Rmax],‘Sensitivity’,0.9);
viscircles(center,radius);
hold on;
plot(center(:,1),center(:,2),‘yx’,‘LineWidth’,2);
hold off;
This error is returned when MATLAB tries to access elements of an array that do not exist. In this case, since “noise” only has 91 elements, MATLAB errors when the loop reaches an element of “P” such that “P(i) + 10” exceeds 91. Starting in R2018b, you will see the following error instead:
Index exceeds the number of array elements (91).
To fix this error, you will need to replace the index “P(i)+10” with something that doesn’t exceed 91, or end your loop earlier. For example, you could stop the loop at “length(P)-2”, and concatenate the remaining elements of “M” outside of the loop.
kindly help me regarding this error..
clc;
clear
close all;
LB=[0 0 0];
UB=[10 10 10];
m=3;
n=500;
wmax=0.9;
wmin=0.4;
c1=2.05;
c2=2.05;
Maxiter=100;
for run=1:20
for i=1:n
for j=1:m
pos(i,j)=(LB(i,j)+rand()).*(UB(i,j)-LB(i,j)); <===Index exceeds matrix dimensions
Please some one help as at this point i see the error: Index exceeds matrix dimension
end
end
vel=(0.1).*pos;
for i=1:n
out(i,1)=fun(pos(i,:));
end
pbestval=out;
pbest=pos;
[fminval, index]=min(out);
gbest=pbest(index,:);
iter=1;
while iter<=Maxiter
w=wmax-(iter/Maxiter).*(wmax-wmin);
X=pos;
Out=fun(X);
Har=find(out<=pbestval);
pbest(Har,:)=X(Har,:);
pbestval=out(Har);
[fbestval, ind1]=min(pbestval);
if fbestval<=fminval
fminvalue=fbestval;
gbest=pbest(ind1,:);
end
for i=1:n
for j=1:m
vel(i,j)=w.*vel(i,j)+c1.*rand().*(pbest(i,j)-pos(i,j))…
+c2.*rand().*(gbeat(1,j)-pos(i,j));
pos(i,j)=vel(i,j)+pos(i,j);
if pos(i,j)<LB(j)
pos(i,j)=LB(j);
elseif pos(i,j)>UB(j)
pos(i,j)=UB(j);
end
end
end
iter=iter+1;
end
F_ans(run)=fun(gbest);
F_gbest(run,:)=gbest;
end
[bestFUN, bestRUN]=min(F_ans);
Best_X=F_gbest(bestRUN,:);
plot(F_ans)
function output = fun(X)
fx=10*(x1-1)^2+20.*x1.*x2+(x3-3)^2;
Con=[];
output=fx;
end
The program you will prepare must have an interface,
· Inputs (inputs.xlsx) and outputs (targets.xlsx) will be read from the files given to you in the program. The program will automatically determine the number of inputs and outputs according to the data read.
· There will be only one hidden layer in the program,
· The user will be able to determine the number of neurons in the hidden layer, the training rate, the number of epochs, and the data rates to be used for training and testing,
· Training and test data will be randomly selected according to the determined rate,
· The neurons in the hidden layer will use the sigmoid activation function, and the neuron in the output layer will use the linear activation (k=1) function,
· When the program starts, the initial weight values of the artificial neural network will be determined as random real numbers between -5 and 5.
· Backpropagation algorithm will be used for training.
· After the user-specified amount of training data and the desired epoch number are completed, the weights of the trained network should be displayed in the program.
· After the training is completed, the success of the test data will be graphically displayed using the trained network and test data. The metric to be used to determine success will be the Mean squared error.
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1 2 3 4 5 6 7 |
A = [1,1,1,1,1; 2,2,2,2,2; 5,3,3,3,3; 4,4,4,4,4; 5,5,5,5,5;] B = [3,3,3,3,3; 4,4,4,4,4; 5,5,5,5,5; 6,6,6,6,6;] C = [1,1,1,1,1; 4,4,4,4,4; 5,5,5,5,5;] [mA]=X(A); [mB]=X(B); [mC]=X(C); k=mA+mB-mC |
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- MATLAB Index Exceeds Matrix Dimensions
Ammar Ali
Apr 29, 2021
Apr 09, 2021
In this tutorial, we will discuss how to solve the index exceeds matrix dimensions problem in MATLAB.
Index Exceeds Matrix Dimensions Problem in MATLAB
In MATLAB, every array or matrix element is stored on a specific index which starts from 1 and increases as the number of elements increases in that array or matrix. To get an element or to replace an element in an array or matrix, we use the index of that element. If an array has ten elements in it, their indices range will vary from 1 to 10, respectively.
If we try to get or replace an element using an index that is 11 or larger, which is not in the range of the indices, then MATLAB will give us an error saying the index exceeds matrix dimensions. So make sure to use the index value which is inside the indices range. You can use the size() function to check the size of your array or matrix before using an index value. For example, see the below code.
myMatrix = [4 3 2 1]
myMatrix[5] = 10;
In the above code, we are saving a value of 10 at the index value of 5 in the matrix myMatrix . But as you can see, the number of indices present in the myMatrix is only four. That means we will get an error of index exceeding matrix dimensions. To solve this problem, we have to save the value at an index inside the indices range which is 1 to 4. See the corrected code below.
myMatrix = [4 3 2 1]
myMatrix[4] = 10;
In the above code, we are saving a value of 10 at the index value of 4 in the matrix myMatrix. As you can see, the index is inside the indices range, so the value 1 in the matrix myMatrix will be replaced with the value 10.
Hello! I am Ammar Ali, a programmer here to learn from experience, people, and docs, and create interesting and useful programming content. I mostly create content about Python, Matlab, and Microcontrollers like Arduino and PIC.
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