how velocize it? (it's possibile to vectorize it?)
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Ntradess =[2 99 1 8 15 67 74 51 58 40
3 80 7 14 16 73 55 57 64 41
3 80 7 20 22 54 56 63 70 47
3 81 7 21 3 60 62 69 71 28
3 81 9 2 9 61 68 75 52 34
4 82 9 83 90 42 49 26 33 65
4 82 9 89 91 48 30 32 39 66
5 85 10 95 97 29 31 38 45 72
6 85 11 96 78 35 37 44 46 53
7 85 12 77 84 36 43 50 27 58
8 86 13 80 84 38 45 51 30 58
8 86 13 82 84 38 45 51 31 58
8 86 13 83 84 38 45 51 31 58
9 87 13 84 84 38 45 51 31 58];
RP_bin=[0 0 1 0 0 1 0 0 1 0 0 1 0 0]';
period=2;
minTrades=2;
g=find(RP_bin>0);
Ntradess_=Ntradess(g,:);
[r,c]=size(Ntradess_);
MinNtrad=zeros(r,c);
for x=1:c %loop colonne
for i=period+1:r
a=Ntradess_(i,x); %n:trade del idx attuale
if a>minTrades
a=find(flip(Ntradess_(1:i-1,x))<=(a-minTrades),1);
if ~isempty(a)
MinNtrad(i,x)= i-a; %MEMORIZZO la posizione della schiera per avere in mintrades richiesti
end
end
end
end
4 Comments
Dyuman Joshi
on 30 Jul 2023
What is your motivation behind wanting to vectorize the code above?
Walter Roberson
on 30 Jul 2023
You could save some coding effort if you were to use
a = find(Ntradess_(1:i-1,x))<=(a-minTrades), 1, 'last');
if ~isempty(a)
MinNtrad(i,x) = a;
end
The change in logic might make it easier to figure out how to vectorize.
pipin
on 30 Jul 2023
Accepted Answer
Bruno Luong
on 30 Jul 2023
Edited: Bruno Luong
on 31 Jul 2023
I don't know the memory requirement would go up if I vectorize the outer loop in a non-toy case. So I leave it for now.
Ntradess =[2 99 1 8 15 67 74 51 58 40
3 80 7 14 16 73 55 57 64 41
3 80 7 20 22 54 56 63 70 47
3 81 7 21 3 60 62 69 71 28
3 81 9 2 9 61 68 75 52 34
4 82 9 83 90 42 49 26 33 65
4 82 9 89 91 48 30 32 39 66
5 85 10 95 97 29 31 38 45 72
6 85 11 96 78 35 37 44 46 53
7 85 12 77 84 36 43 50 27 58
8 86 13 80 84 38 45 51 30 58
8 86 13 82 84 38 45 51 31 58
8 86 13 83 84 38 45 51 31 58
9 87 13 84 84 38 45 51 31 58];
RP_bin=[0 0 1 0 0 1 0 0 1 0 0 1 0 0]';
period=2;
minTrades=2;
g=find(RP_bin>0);
Ntradess_=Ntradess(g,:);
[r,c]=size(Ntradess_);
MinNtrad=zeros(r,c);
for x=1:c %loop colonne
for i=period+1:r
a=Ntradess_(i,x); %n:trade del idx attuale
if a>minTrades
a=find(flip(Ntradess_(1:i-1,x))<=(a-minTrades),1);
if ~isempty(a)
MinNtrad(i,x)= i-a; %MEMORIZZO la posizione della schiera per avere in mintrades richiesti
end
end
end
end
MinNtrad
[r,c]=size(Ntradess_);
MinNtrad = zeros(r,c);
Mask = flip(triu(true(r),1),1);
for x = 1:c
nx = Ntradess_(:,x);
[v,j] = max(Mask .* (nx'-flip(nx,1) >= minTrades), [], 1);
j = r+1-j;
j(v(:)==0 | nx(:)<=minTrades) = 0;
MinNtrad(:,x) = j;
end
MinNtrad(1:period,:) = 0;
MinNtrad
2 Comments
Bruno Luong
on 30 Jul 2023
Edited: Bruno Luong
on 31 Jul 2023
Full vectorize
warning: potential runout of memory
[r,c] = size(Ntradess_);
Mask = (1:r)' > (r:-1:1); % flip(triu(true(r),1),1);
D = reshape(Ntradess_, [1 r c]) - reshape(flip(Ntradess_, 1), [r 1 c]);
B = Mask .* (D >= minTrades);
[V,J] = max(B, [], 1);
MinNtrad = r+1-reshape(J, [r c]);
V = reshape(V, [r c]);
MinNtrad(V==0 | Ntradess_<=minTrades) = 0;
MinNtrad(1:period,:) = 0;
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