effenberger_DA11_2017_script.m

effenberger_DA11_2017_script.m - Audrey Effenberger MCB 105...

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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Audrey Effenberger % MCB 105: Systems Neuroscience % DA 11: Big data analysis, aka PCA %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Housekeeping clear all; close all; i = 1; N = 9; X = 5; % Create matfile % fish1.Fish1 is a 741 x 512 x 480 x 9 matrix fish1 = matfile('fishvolume1.mat'); fish2 = matfile('fishvolume2.mat'); fish3 = matfile('fishvolume3.mat'); % Pre-allocating single planes % avgFish is a 741 x 512 x 9 x 480 matrix avgFish = cell(9,1); for i=1:N avgFish(i) = {zeros(741,512,1,480)}; end; % Define parallel pool delete(gcp('nocreate')); cluster = parcluster('local'); cluster.NumWorkers = X; parpool('local',X); % Run parfor to calculate average of each slice through time parfor i = 1:N avgFish(i) = {(int16(fish1.Fish1(:,:,:,i))+int16(fish2.Fish2(:,:,:,i)) +int16(fish3.Fish3(:,:,:,i)))/3 }; end; % Threshold and reshape each slice threshold = 10000;
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