Parfoor loop with 3D matrix
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Hello,
I write you today because I have to treat 655Mo of data (matrix 16*512*10000 of double) and before the treatment I use a filtering to reduce noise and center my signals. The structure data contains the signals at the beginning, and also différent parameters like the length of each signals and the number of signals for each sensor. Moreover, the structure parametres contains different variables relative to these signals (sampling frequency, signal frequency, number of sensors). For this, I do:
% Hanning Window
g = ones(data.sig_length, data.nb_signals);
h = hann(31);
g(1:15,:) = repmat(h(1:15), 1, data.nb_signals);
g(data.sig_length-14:data.sig_length, :) = repmat(h(17:31), 1, data.nb_signals);
% Low pass filter coefficient
N = 3;
Fe = parametres.freq_ech; % 20 MHz
Fce = parametres.freq_central; % 2 MHz
Wn = (2*Fce)/(Fe/2);
[b, a] = butter(N, Wn, 'low');
% Variable Initialisations
signal_temp = zeros(data.sig_length, data.nb_signals);
moyenne_sig = zeros(data.sig_length, data.nb_signals);
signal_filt = zeros(data.sig_length, data.nb_signals, parametres.text_nb_sensors);
donnees = data.signal_init;
sig_length = data.sig_length;
for sensor = 1:parametres.text_nb_sensors
% DC Suppression
signal_temp = squeeze(donnees(:,:,sensor));
moyenne_sig = repmat(mean(squeeze(donnees(:,:,sensor))), sig_length, 1);
signal_filt(:,:,sensor) = signal_temp - moyenne_sig;
% Median filter on 5 points
for k = 1:1:data.sig_length
signal_filt(k,:,sensor) = medfilt1(squeeze(signal_filt(k,:,sensor)),5);
end
% Low pass filter with Hanning window
signal_filt(:,:,sensor) = filtfilt(b,a,g.*(signal_filt(:,:,sensor)));
end
Until here, no problem, I have the result I want and my treatments after are okay. But this take 19 seconds, so it is too much time for me. I have the toolbox to use the 4 cores of my computers, what I use in another place on my code. My wish is to do the same thing here but after several tries, I always have Matlab which informs me that a variable have not the good indices to be in a parfor loop. For example with the code above, it is the nested-for loop which is the problem.
Somebody could help me to begin somewhere?
I thank you a lot in advance. Best regards.
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采纳的回答
Edric Ellis
2015-12-2
I think the problem here is with the way you're using signal_filt. You're using multiple forms of indexing, and the parfor restrictions do not allow that, as described in the documentation. Here's what I think you need to do to fix this, something like this:
parfor sensor = 1:parametres.text_nb_sensors
% DC Suppression
signal_temp = squeeze(donnees(:,:,sensor));
moyenne_sig = repmat(mean(squeeze(donnees(:,:,sensor))), sig_length, 1);
tmp = signal_temp - moyenne_sig;
% Median filter on 5 points
for k = 1:1:data.sig_length
tmp(k) = medfilt1(squeeze(tmp(k)),5);
end
% Low pass filter with Hanning window
signal_filt(:,:,sensor) = filtfilt(b,a,g.*(tmp));
end
Note I'm using tmp to build up the value to be placed back into a slice of signal_filt. This is sufficient to convince parfor that you're not doing anything order-dependent.
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