Hi Pankaj,
if I understand your question correctly, the quick way might be to utilize the methods provided by timeseries class. One possibility to reduce the number of data "columns" is shown below along with cropping the timeseries to a given start and end time:
% Create timeseries
time = 0:0.01:2;
for ik = 1:4
data(:,ik) = sin((2 * pi * 5 * time) + ((ik-1) * pi/2));
end
TS_initial = timeseries(data,time);
% Extract part of the timeseries
startTime = 0.5;
endTime = 1.5;
colsToExtract = [2 3 4];
if size(colsToExtract,1) > 0
% copy the original time series
TS_extract = TS_initial;
% select the data
TS_extract.Data = TS_extract.Data(:,colsToExtract);
% extract for a given time range
TS_extract = TS_extract.getsampleusingtime(startTime,endTime);
end
Kind regards,
Robert
