I have a set of signals that due to some unknown error have been acquired with millions of empty datapoints. Is there a way I can automatically detect the moment the signal ends so I can delete everything from that point onwards?
Thanks everyone.

4 Comments

Can you upload a copy of the raw data?
Ofcourse, I have modified a bit the original as it was too heavy, but it's the same concept.
There are no actual ‘missing’ values, just a very low amplitude signal after about element 40:
T1 = readtable('sampledata.csv');
figure
semilogy(abs(T1{:,1}))
grid
producing:
That would appear to be legitimate data.
.
This depends on how you define legitimate data, if you unplug a probe/sensor from an oscilloscope it will continue to display numbers and a waveform. If you're trying to measure a signal then it is fair to call recorded noise invalid data

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 Accepted Answer

Xavier
Xavier on 10 Sep 2020
Something like this may work for you
Raw data:
data = readmatrix('sampledata.csv');
avgdat = movmean(abs(data), 5);
threshold = 0.01;
data(avgdat < threshold) = [];
plot(data)

2 Comments

This worked perfectly!! thanks a lot.
No problem!

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More Answers (1)

If the empty data points are represented by NaN then find the 'last' 1 element of the vector that isfinite.
x = [1:10 NaN(1, 5)]
find(isfinite(x), 1, 'last')
If the vector has no missing data inside it, you could instead just rmmissing.
rmmissing(x)

1 Comment

Thanks for the reply! The missing values aren't really missing in the matlab file. They are missing in the original data collection software but as soon as you retrieve them, they turn into zeros so this code will not work :(
I'm in touch with the developers of the software but they still haven't been able to solve this.

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Release

R2020a

Asked:

on 9 Sep 2020

Commented:

on 10 Sep 2020

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