Resampling a Data Array for LSTM Training
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Hi,
I am preparing data for training an LSTM network with a sequenceInputLayer. The data is from ANSYS which uses a variable step solver. The time steps in the captured data varying from 1.0E-04 sec to 9.0E-09 sec (average of 5.4E-05 sec). The 4 data sets are imported as approx. 594x7 doubles. I have had help on another post regarding using the interp1 function to help resize the sequences lengths.
My questions is can I resample the data to say 5.0E-05 sec using the resample function? And can the resample function be used on the array as well as a single observation?
I have included the code below as to my progress in using the resample function.
Thanks in advance,
Patrick
%Data Resampling
%Import Chemkin Data from Folder Location - Data captured with Variable Step Solver - Average step size = 5.38E-05
dataraw_03 = xlsread('Data_Ethanol_Raw\export_Ethanol_20%_440t_0.3.csv'); % 574x7 double
dataraw_04 = xlsread('Data_Ethanol_Raw\export_Ethanol_20%_440t_0.4.csv'); % 594x7 double
dataraw_05 = xlsread('Data_Ethanol_Raw\export_Ethanol_20%_440t_0.5.csv'); % 595x7 double
dataraw_06 = xlsread('Data_Ethanol_Raw\export_Ethanol_20%_440t_0.6.csv'); % 596x7 double
%Extract Observations from Array for Resampling
time_03 = dataraw_03(:,1); % Column 1 all rows from first data set
volume_03 = dataraw_03(:,2); % Column 2 all rows from first data set
crankAngle_03 = dataraw_03(:,3); % Column 3 all rows from first data set
temperature_03 = dataraw_03(:,4); % Column 4 all rows from first data set
pressure_03 = dataraw_03(:,5); % Column 5 all rows from first data set
co2_03 = dataraw_03(:,6); % Column 6 all rows from first data set
no_03 = dataraw_03(:,7); % Column 7 all rows from first data set
%Resample Data for LSTM SequenceInputLayer with a target sample rate of 5.0E-05 sec or 20 KHz
timeInterval = 5.0e-5; % Target sample rate [s]
timeInterval_min = 9.0e-8; % Smallest sample rate captured from ANSYS variable rate solver [s]
fs = 1/timeInterval; % Target sample frequency of 20,000 [Hz]
f_down = 1/timeInterval_min; % Downsampling frequency [Hz]
resampledvolume_03 = resample(volume_03,fs,f_down); % Resampled the volume @ 5.0E-05 sec
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Accepted Answer
Ben
on 5 Sep 2022
Hi Patrick,
In principle I think you can use Signal Processing resample - however you may want to verify this resample behaves as you expect. For example I tried this following toy example that demonstrates this type of signal resampling may not always be appropriate:
% Get timeseries from a variable step solver.
[t,y] = ode45(@vdp1,[0,1],[1;0]);
% Resample to a fixed rate of 1e4
samplerate = 1e4;
[yresample,tresample] = resample(y,t,samplerate);
% For comparison compute a timeseries resample
% - this uses interpolation according to getinterpmethod(ts);
% - This was 'linear' for me, so should match interp1
ts = timeseries(y,t);
tsresample = resample(ts,0:samplerate:1);
% Plot everything to compare
plot(t,y(:,1));
hold on;
plot(tresample,yresample(:,1));
plot(tsresample.Time,tsresample.Data(:,1));
legend(["Original","Signal Resample","Linear Interplation"]);
In this example the signal processing resample introduces some error at the boundaries. Unfortunately I don't know enough about signal processing to say whether there are ways to avoid this behaviour, and perhaps for your problem this is actually more appropriate.
In the above I have used the syntax
[yresample,tresample] = resample(y,t,samplerate)
where y is my original data, t is the sample times of y, and samplerate is my desired new sampling rate. I think this syntax should work for your case, though if each of your variables are sampled at different times you may need to call resample independently on each with their given sampling times. Also it is worth getting the 2nd output tresample above as this call to resample actually includes samples at times tresample>max(t).
Hope that helps,
Ben
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