Samantha Huff asked . 2021-12-08

Simple for loop taking way longer than it should

I am running a for loop on 10 million lines of data and it has taken over a day and is still running. I have preallocated the array I am modifying according to suggestions provided by Matlab for optimizing runtime. This post says 100 million lines of data ran in a simple for loop in 0.2 seconds. I am testing my code both on my personal computer (Mac) and a remote server. Why is my code so slow??

%% read in file
cwaFileToRead = '6011549_0000000003.cwa';
ptID = '6011549_0000000003';
sampling_rate = 100;
Fs = sampling_rate;
output_dir = '';

rawData = CWA_readFile(cwaFileToRead, 'verbose', 0);

%% calculate vector magnitude
xRaw = rawData.AXES(:,2);
yRaw = rawData.AXES(:,3);
zRaw = rawData.AXES(:,4);
vmRaw = sqrt((xRaw.^2)+(yRaw.^2)+(zRaw.^2));
vmRaw = vmRaw.*(1000);

numrows=size(vmRaw); 
peak=zeros(numrows);%add empty rows for peak identification

time = datetime(rawData.AXES(:,1), 'ConvertFrom', 'datenum'); % convert mtime to datetime
timedata = timetable(time, xRaw, yRaw, zRaw, vmRaw, peak); % convert data to timetable

 %% CHECK FOR UNIFORM SAMPLING, RESAMPLE IF NOT UNIFORM
    % Check if sampling rate is uniform
    isUniform = isregular(timedata);
    % If sampling rate is non-uniform, resample at regular sampling intervals
    if isUniform == 0
        timeStep = seconds(1/Fs); % how long between each regular sample
        regularizedData = retime(timedata,'regular','linear','TimeStep',timeStep);
        fprintf('Sampling rate is non-uniform, resampling using linear interpolation\n')
    else
        regularizedData = timedata;
    end
    
%FOR LOOP THAT IS SO SLOW!! HELP!
tic
for row = 2:numrows-1 
    if regularizedData.vmRaw(row)>regularizedData.vmRaw(row-1)&& regularizedData.vmRaw(row)>regularizedData.vmRaw(row+1)
        regularizedData.peak(row)=1;
    else
        regularizedData.peak(row)=0;
    end
end
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signal processing , for loop , performance , matlab