vectorization - Vectorize MATLAB code -

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let's have 3 m-by-n matrices of equal size: a, b, c.

every column in c represents time series.
a running maximum (over fixed window length) of each time series in c.
b running minimum (over fixed window length) of each time series in c.

is there way determine t in vectorized way?

[nrows, ncols] = size(a); t = zeros(nrows, ncols); row = 2:nrows                           %loop on rows (except row #1).     col = 1:ncols                       %loop on columns.         if     c(row, col) > a(row-1, col)             t(row, col) =  1;         elseif c(row, col) < b(row-1, col)             t(row, col) = -1;         else             t(row, col) = t(row-1, col);         end     end end

this i've come far:

t = zeros(m, n); t(c > circshift(a,1)) =  1; t(c < circshift(b,1)) = -1;

well, trouble dependency else part of conditional statement. so, after long mental work-out, here's way summed vectorize hell-outta everything.

now, approach based on mapping. column-wise runs or islands of 1s corresponding 2d mask else part , assign them same tags. then, go start-1 along each column of each such run , store value. finally, indexing each such start-1 tagged numbers, work mapping indices give elements set in new output.

here's implementation fulfill aspirations -

%// store sizes [m1,n1] = size(a);  %// masks corresponding 3 conditions mask1 = c(2:nrows,:) > a(1:nrows-1,:); mask2 = c(2:nrows,:) < b(1:nrows-1,:); mask3 = ~(mask1 | mask2);  %// mask3 set values output out = [zeros(1,n1) ; mask1 + (-1*(~mask1 & mask2))];  %// proceed if element in mask3 set if any(mask3(:))      %// row vectors appending onto matrices matching sizes     mask_appd = false(1,n1);     row_appd = zeros(1,n1);      %// 2d mapped indices     df = diff([mask_appd ; mask3],[],1)==1;     cdf = cumsum(df,1);      offset = cumsum([0 max(cdf(:,1:end-1),[],1)]);     map_idx = bsxfun(@plus,cdf,offset);     map_idx(map_idx==0) = 1;      %// extract values used setting new places     a1 = out([df ; false(1,n1)]);      %// map indices obtained earlier , set @ places mask3     newval = [row_appd ; a1(map_idx)];     mask3_appd = [mask_appd ; mask3];     out(mask3_appd) = newval(mask3_appd);  end

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