How do i bin large data sets?

2 vues (au cours des 30 derniers jours)
Connor
Connor le 2 Mai 2016
I am trying to bin a large 2000hz data set into averge bins of 100ms for EMG data.
I have tried to reshape the data but Matlab keeps throwing up the problem that there are "not enough input arguments" currently the script reads
%reshape data by order 100
data_binned= mean(reshape(data,100,length,(data)/100,1));

Réponses (3)

Robert
Robert le 2 Mai 2016
It looks like you have an extra comma after length, which would cause the error you are seeing.

Connor
Connor le 2 Mai 2016
Modifié(e) : Connor le 2 Mai 2016
Thank you, that sorted out the issue however I am now getting the error message
"error in reshape: size arguments must be real integers"
Same code with the comma removed!

Walter Roberson
Walter Roberson le 2 Mai 2016
Fs = 2000;
t = 0.100;
blocksize = round(Fs*t);
numsamp = length(data);
num_blocks = floor(numsamp/blocksize);
blocks = blocksize * ones(1, num_blocks));
sampsused = num_blocks * blocksize;
if sampsused ~= numsamp
blocks(end+1) = numsamp - sampsused;
end
datacell = mat2cell(data(:), blocks, 1);
The above will break the data up into separate cell array entries.
But possibly for your purpose you just need
Fs = 2000;
t = 0.100;
blocksize = round(Fs*t);
data_binned = buffer(data(:), blocksize);

Catégories

En savoir plus sur Statistics and Machine Learning Toolbox dans Help Center et File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by