
Re: Best way to "classify" a vector? ("averaging" subsampling)
Posted:
Mar 4, 2013 5:11 PM


On Tuesday, March 5, 2013 10:19:09 AM UTC+13, Luca wrote: > Hi everyone. > > Let's suppose to have these two vectors: > > > > t=0:0.01:1000; %timestamps > > val = rand(size(t)); %value associated with each timestamp > > > > Now let's suppose I want to calculate the mean value of val in each interval of "t" broad "1". > > What would be the best way to do it? > > The dumbest would be something _like_ (I'm sure somebody will find a couple of minor errors :). But try to get the point!): > > > > t2 = ceil (t); > > [t2,I]= unique (t2,'first'); > > [t2,J]=unique (t2,'last'); > > meanVal= zeros(max(t2(:),1); > > for i=1:numel(meanVal) > > meanVal(i) = mean(val(I(i):val(J(i)); > > end > > > > Now... I know that matlab always has some built in functions that does all of these basic operations better and faster. > > So.... what would be a smarter way to do this??
So, you're doing the equivalent of taking daily means (if the t were Matlab days). Why is that dumb?
The only thing I'd criticise about your method is the use of i as an index. By default i and j are sqrt(1). This may seem trivial, but one day this will jump up and bite you. Use something else, like it or jt, for the index.

