MATLAB: How to resample the data

interp1interpolationresample

Hi,

I am looking for a method to standardise exercise duration. I measured core temperature during 60 minutes of exercise. However, due to exhaustion not all participants were able to complete the experiment. For those participants I want to resample the data, so that all participants have an equal sample number in the exercise phase. I have tried interp1, which works. However, I want to interpolate inbetween the temperatures I measured. So that the final temperature I measured, stays the final temperature measurement.

Does anyone have suggestions?

Cheers!

Best Answer

If the final time point in your query x (time) vector is the same, then the final temperature will be the same. If it's not, then attach your data and code to prove otherwise.

Related Solutions

MATLAB: Upsampling the data using interpolation gives NaN values.

Use the 'extrap' argument in interp1.

Example —

D = load('x.mat');
x = D.x;
v = 1:numel(x);
ve = 1:2225570;
x_extended = interp1(v, x, ve, 'linear','extrap');

This is dangerous, because you have no idea what ‘x’ actually would be beyond its current definition. I would definitely avoid that.

However you can completely avoid all those problems if you simply want more points in ‘x’:

vr = linspace(min(v), max(v), 2225570);
x_resampled = interp1(v, x, vr);

Experiment to get the result you want.

MATLAB: How to converter the hourly data interval to 15-minutes interval using interpolate function of matlab

%when interp1 is strictly required:
%assuming uniform times
way2 = interp1(HourlyTemperature, 1:0.25:length(HourlyTemperature)+0.75, 'spline', 'extrap');
%not assuming uniform times
OutTimes = InputTimes(1) + minutes(15)*(0:length(InputTimes)*4-1);
way4 = interp1(InputTimes, HourlyTemperature, OutTimes, 'spline', 'extrap');
%when interp1 is not strictly required
%assuming uniform times, and Signal Processing Toolbox
way1 = resample(HourlyTemperature, 4, 1);
%not assuming uniform times, but with Signal Processing Toolbox
way3 = resample(HourlyTemperature, InputTimes, 1/(15*60));   %1/(15*60) Hz -> 15 minutes apart
%timetable, does not need Signal Processing or uniform times
way5 = retime( timetable(InputTimes(:), HourlyTemperature(:))), minutes(15) );

Decisions have to be made about whether you need the 15, 30, and 45 after the final hour reading; if so then you need extrapolation, and you would need to recheck whether the resample() methods extrapolate.

Watch out for how resample() initializes the buffer, which can affect edge readings.

Best Answer

Related Solutions

MATLAB: Upsampling the data using interpolation gives NaN values.

MATLAB: How to converter the hourly data interval to 15-minutes interval using interpolate function of matlab

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