facing issue in FFT : P1 = P2(1:L/2+1)

I am facing error to solve this code , kindly guide me

i am facing issue at:

    P1 = P2(1:L/2+1)

Kindly help me resove the issue: the error details screenshot has be uploaded

Below is the full code i am trying

%%
%Data Collection and Labeling
clc;
clear all;
labelPoints = {[2,50],[51,80]}; 
NoOfFailureModes = 2;
estimateRULFlags = [false, true]; 
path = 'Datasets/'; 
labels = {[categorical("OFF"),categorical("ON"),categorical("DUCT BLOCKAGE")],[categorical("OFF"),categorical("ON"),categorical("ROTOR IMBALANCE")]};

rawdata = cell(NoOfFailureModes);
data = cell(NoOfFailureModes);


for i = 1:NoOfFailureModes
    rawdata{i} = readtable([path 'Dataset' num2str(i) '.csv'],'Delimiter',','); %Read the downloaded csv file
    data{i} = dataParsing(rawdata{i},labelPoints{i},labels{i},i); %Parse the rawdata
end


%%
%Data Exploration
fs = 100; %Sampling Frequency
L = 100; %Length of each data sample is 100 sensor readings
f = fs*(0:(L/2))/L; % Frequency bins until Nyquist Frequency at which FFT is computed
convertToMinutes = (1/fs)/60; %Convert sample number to minutes 0.01/60
votype = 'VideoWriter'; %Record the Exploration to view it again
vo = VideoWriter('Data Exploration Video', 'MPEG-4');
set(vo, 'FrameRate', 5); 
open(vo);
for i = 1:NoOfFailureModes
    NoOfDataPoints = height(data{i});
    x = zeros(L*NoOfDataPoints,0);
    y = zeros(L*NoOfDataPoints,0);
    z = zeros(L*NoOfDataPoints,0);
    figure;
    set(gcf,'Visible','on')
    for j = 1:NoOfDataPoints
        data{i}.X_FFT(j,:) = computeFFT(data{i}.X(j,:)-mean(data{i}.X(j,:)),L);  
        data{i}.Y_FFT(j,:) = computeFFT(data{i}.Y(j,:)-mean(data{i}.Y(j,:)),L);
        data{i}.Z_FFT(j,:) = computeFFT(data{i}.Z(j,:)-mean(data{i}.Z(j,:)),L);
        x((j-1)*L+1 : j*L) = data{i}.X(j,:);
        y((j-1)*L+1 : j*L) = data{i}.Y(j,:);
        z((j-1)*L+1 : j*L) = data{i}.Z(j,:);
        t = (1:j*L)*convertToMinutes;
        
        subplot(3,2,1); 
        plot(t,x);  
        title({"Experiment: " + num2str(i) , "Time Domain"});
        xlabel("time (min.)",'FontWeight','bold');
        ylabel("X",'rotation',0,'FontWeight','bold'); 
        
        subplot(3,2,2); 
        bar(f,data{i}.X_FFT(j,:)); 
        title({"Sample: " + num2str(j) + "; Label: " + char(data{i}.Label(j)), "Frequency Domain"});
        xlabel("frequency (Hz)",'FontWeight','bold');
        ylabel("X",'rotation',0,'FontWeight','bold'); 
        
        subplot(3,2,3); 
        plot(t,y); 
        xlabel("time (min.)",'FontWeight','bold');
        ylabel("Y",'rotation',0,'FontWeight','bold');
        
        subplot(3,2,4); 
        bar(f,data{i}.Y_FFT(j,:)); 
        xlabel("frequency (Hz)",'FontWeight','bold');
        ylabel("Y",'rotation',0,'FontWeight','bold');
        
        subplot(3,2,5); 
        plot(t,z); 
        xlabel("time (min.)",'FontWeight','bold');
        ylabel("Z",'rotation',0,'FontWeight','bold'); 
        
        subplot(3,2,6); 
        bar(f,data{i}.Z_FFT(j,:)); 
        xlabel("frequency (Hz)",'FontWeight','bold');
        ylabel("Z",'rotation',0,'FontWeight','bold'); 
        
        drawnow;
        writeVideo(vo, getframe(gcf));
    end
end
close(vo);
%%

%%
%Helper Functions
function P1 = computeFFT(X,L)
    Y = fft(X);
    P2 = abs(Y/L);%absolute value
    P1 = P2(1:L/2+1)
    P1(2:end-1) = 2*P1(2:end-1);
end


function data = dataParsing(rawdata,labelPoints,labels,dataset)
    bias = 44;
    noOfDataPoints = length(rawdata.entry_id);
    labelPoints = [0 labelPoints noOfDataPoints];

    for i = 1:length(labelPoints)-1 
        Label(labelPoints(i)+1:labelPoints(i+1),:) = labels(i); %Create Labels for the data points
    end
    j = 1;

    if(dataset == 2)
        offset = 0;
    else
        offset = 2000;
    end

    for i = 1:noOfDataPoints
        var1 = rawdata.field1(i);
        var2 = rawdata.field2(i);
        var3 = rawdata.field3(i);
        var4 = rawdata.field4(i);
        var5 = rawdata.field5(i);
        var6 = rawdata.field6(i);
        %Turning the device off and on will reset the first data set to all zeroes
        
        if var1 ~= 0 || var2 ~= 0 || var3 ~= 0
            var = [var1, var2, var3, var4, var5, var6] - bias;
            data.Label(j,:) = Label(i);
            data.sno(j,:) = rawdata.entry_id(i) + offset;
            data.X(j,:) = [var(1);var(4)];
            data.Y(j,:) = [var(2);var(5)];
            data.Z(j,:) = [var(3);var(6)];
            j = j+1;
        end
    end

    data = struct2table(data);

end

[KALYAN ACHARJYA]

Can you please provide?

>>whos L

[Aniket Manjare]

[Walter Roberson]

How does this differ from https://www.mathworks.com/matlabcentral/answers/698460-index-exceeds-the-number-of-array-elements-2?s_tid=srchtitle ?

Answer 1

[Mathieu NOE]

Hi

suggest this fft code that also allows averaging if needed :

  function  [freq_vector,fft_spectrum] = myfft_peak(signal, Fs, nfft, Overlap)
    %FFT peak spectrum of signal  (example sinus amplitude 1   = 0 dB after fft).
    %   signal - input signal, 
    %   Fs - Sampling frequency (Hz).
    %   nfft - FFT window size
    %   Overlap - buffer overlap % (between 0 and 0.95)

    samples = length(signal);
    % fill signal with zeros if its length is lower than nfft
    if samples<nfft
        s_tmp = zeros(nfft,1);
        s_tmp((1:samples)) = signal;
        signal = s_tmp;
    end

    % window : hanning
    window = hanning(nfft);
    window = window(:);

%    compute fft with overlap 
     offset = fix((1-Overlap)*nfft);
     spectnum = 1+ fix((samples-nfft)/offset); % Number of windows
%     % for info is equivalent to : 
%     noverlap = Overlap*nfft;
%     spectnum = fix((samples-noverlap)/(nfft-noverlap));	% Number of windows

        % main loop
        fft_spectrum = 0;
        for i=1:spectnum
            start = (i-1)*offset;
            sw = signal((1+start):(start+nfft)).*window;
            fft_spectrum = fft_spectrum + (abs(fft(sw))*4/nfft);     % X=fft(x.*hanning(N))*4/N; % hanning only 
        end
        fft_spectrum = fft_spectrum/spectnum; % to do linear averaging scaling

    % one sidded fft spectrum  % Select first half 
        if rem(nfft,2)    % nfft odd
            select = (1:(nfft+1)/2)';
        else
            select = (1:nfft/2+1)';
        end
    fft_spectrum = fft_spectrum(select);
    freq_vector = (select - 1)*Fs/nfft;
  end

   freq_vector = freq_vector(:);
  fft_spectrum = fft_spectrum(:);