[Scilab-users] ugly code improvement (with vectorization)

[Carrico, Paul]

Dear All,

Can I ask advice to correct this ugly/slow code (using vectorization)?

In the example here bellow, I want

-          to capture the non-null values of each line from the 5th column - each row can have different "length"

-          the 4th column indicates how many values there're i.e the length

-          Then to put this values in a vector previously initialized

If I can extract the values with ''Elements(k,[5: Elements (k,4)]'', I do not know how to put it the ''View'' matrix without using dynamic allocation ([View ; Elements (k,4) ... indeed I'm using block and not explicit index

Thanks for your time

Paul

########################################################

View = zeros(dim,2); // dim previously calculated

n = 1;
for k = 1 : size(Elements,1)
    for m = 1 : Elements (k,4)
        View(n,1) = Elements (k,4+m);
        n = n+1;
    end
end

with
Elements = [
    1.     1.    29.    8.    81.    82.     83.     124.    165.    164.    163.    122.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.     0.    0.    0.    0.
    2.     1.    29.    8.    83.    84.     85.     126.    167.    166.    165.    124.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.     0.    0.    0.    0.
    3.     1.    29.    8.    85.    86.     87.     128.    169.    168.    167.    126.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.     0.    0.    0.    0.
    4.     1.    29.    8.    87.    88.     89.     130.    171.    170.    169.    128.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.     0.    0.    0.    0.
    5.     1.    29.    8.    89.    90.     91.     132.    173.    172.    171.    130.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.     0.    0.    0.    0.
....
    797.    1.    8.    20.    2193.    2194.    2195.    2219.    2257.    2256.    2255.    2218.    3515.    3516.    3517.    3541.    3579.    3578.    3577.      3540.    2854.    2856.    2918.    2916.
    798.    1.    8.    20.    2195.    2196.    2197.    2220.    2259.    2258.    2257.    2219.    3517.    3518.    3519.    3542.    3581.    3580.    3579.      3541.    2856.    2858.    2920.    2918.
    799.    1.    8.    20.    2197.    2198.    2199.    2221.    2261.    2260.    2259.    2220.    3519.    3520.    3521.    3543.    3583.    3582.    3581.      3542.    2858.    2860.    2922.    2920.
    800.    1.    8.    20.    2199.    2200.    2201.    2222.    2263.    2262.    2261.    2221.    3521.    3522.    3523.    3544.    3585.    3584.    3583.      3543.    2860.    2862.    2924.    2922.
...
    1047.    999.    3.    2.    3587.    3582.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.
    1048.    999.    3.    2.    3587.    3583.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.
    1049.    999.    3.    2.    3587.    3584.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.
    1050.    999.    3.    2.    3587.    3585.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.];


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