Loading scsearch.m +15 −15 Original line number Diff line number Diff line Loading @@ -113,13 +113,13 @@ end %CONTROLLARE SE CON LA FUNZIONE RESHAPE PUOI EVITARE IL CICLO FOR % Time series for each segment x = zeros(M,N); x = zeros(N,M); toc tic aux1 = M*N; aux2 = C(1:aux1); clear aux1 x = reshape(aux2,[M,N]); clear aux2 x = reshape(aux2,[N,M]); clear aux2 toc clear C % Loading Loading @@ -260,12 +260,11 @@ tic % Cercheremo un modo per combinare in tutti i possibili modi vettori di % vari ni1,ni2,...,nis_s %%%[kung,fu,fight] = ndgrid(nis{1},nino{2},nino{3}); % tm=gpuArray(tm); % nibank = gpuArray(combinations(nis{:}).Variables); % Lambda = zeros(length(nibank),length(f_gr),M,'gpuArray'); nibank = combinations(nis{:}).Variables; Lambda = zeros(length(nibank),length(f_gr),M); % Lambda = zeros(length(nibank),length(f_gr),M,'gpuArray'); tm=gpuArray(tm); nibank = gpuArray(combinations(nis{:}).Variables); Lambda = zeros(length(nibank),length(f_gr),M,'gpuArray'); % nibank = combinations(nis{:}).Variables; % Lambda = zeros(length(nibank),length(f_gr),M); toc %Fourier transform on original time-series -------------------------------- %per mantenere l'informazione di fase, non faccio il valore assoluto al quadrato della fft Loading @@ -286,10 +285,10 @@ for m=1:M % Y=Y(cond); % X=ifft(Y); %inverse-fourier transf. % ttemp = gpuArray(tm(m,:)-tmid(m)); % xtemp = gpuArray(x(m,:)); ttemp = tm(m,:)-tmid(m); xtemp = x(m,:); ttemp = gpuArray(tm(m,:)); xtemp = gpuArray(x(:,m).'); % ttemp = tm(m,:); % xtemp = x(:,m).'; % toc Loading Loading @@ -318,7 +317,7 @@ for m=1:M % end % tic tau = sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttemp(1:N)).^((1:s_s).').'),2); tau = tmid(m) + sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttemp(1:N)).^((1:s_s).').'),2); % toc % tic Loading Loading @@ -362,11 +361,12 @@ end tic % nisearcher = KDTreeSearcher(nibank,'BucketSize',100); nisearcher = KDTreeSearcher(gather(nibank),'BucketSize',100); %% The line above will have to be substituted with something along the lines %% of the ones below to account for the metric g_jj in the phase derivatives gdistance = @(a,b)sqrt(((a-b).^2)*(g_jj(1:s_s))); % gdistance = @(a,b)sqrt(((a-b).^2)*(g_jj(1:s_s))); % nisearcher = ExhaustiveSearcher(gather(nibank),'Distance',gdistance); nisearcher = ExhaustiveSearcher(nibank,'Distance',gdistance); % nisearcher = ExhaustiveSearcher(nibank,'Distance',gdistance); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% parbank = combinations(porb_gr,a_gr,tasc_gr).Variables; Loading Loading
scsearch.m +15 −15 Original line number Diff line number Diff line Loading @@ -113,13 +113,13 @@ end %CONTROLLARE SE CON LA FUNZIONE RESHAPE PUOI EVITARE IL CICLO FOR % Time series for each segment x = zeros(M,N); x = zeros(N,M); toc tic aux1 = M*N; aux2 = C(1:aux1); clear aux1 x = reshape(aux2,[M,N]); clear aux2 x = reshape(aux2,[N,M]); clear aux2 toc clear C % Loading Loading @@ -260,12 +260,11 @@ tic % Cercheremo un modo per combinare in tutti i possibili modi vettori di % vari ni1,ni2,...,nis_s %%%[kung,fu,fight] = ndgrid(nis{1},nino{2},nino{3}); % tm=gpuArray(tm); % nibank = gpuArray(combinations(nis{:}).Variables); % Lambda = zeros(length(nibank),length(f_gr),M,'gpuArray'); nibank = combinations(nis{:}).Variables; Lambda = zeros(length(nibank),length(f_gr),M); % Lambda = zeros(length(nibank),length(f_gr),M,'gpuArray'); tm=gpuArray(tm); nibank = gpuArray(combinations(nis{:}).Variables); Lambda = zeros(length(nibank),length(f_gr),M,'gpuArray'); % nibank = combinations(nis{:}).Variables; % Lambda = zeros(length(nibank),length(f_gr),M); toc %Fourier transform on original time-series -------------------------------- %per mantenere l'informazione di fase, non faccio il valore assoluto al quadrato della fft Loading @@ -286,10 +285,10 @@ for m=1:M % Y=Y(cond); % X=ifft(Y); %inverse-fourier transf. % ttemp = gpuArray(tm(m,:)-tmid(m)); % xtemp = gpuArray(x(m,:)); ttemp = tm(m,:)-tmid(m); xtemp = x(m,:); ttemp = gpuArray(tm(m,:)); xtemp = gpuArray(x(:,m).'); % ttemp = tm(m,:); % xtemp = x(:,m).'; % toc Loading Loading @@ -318,7 +317,7 @@ for m=1:M % end % tic tau = sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttemp(1:N)).^((1:s_s).').'),2); tau = tmid(m) + sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttemp(1:N)).^((1:s_s).').'),2); % toc % tic Loading Loading @@ -362,11 +361,12 @@ end tic % nisearcher = KDTreeSearcher(nibank,'BucketSize',100); nisearcher = KDTreeSearcher(gather(nibank),'BucketSize',100); %% The line above will have to be substituted with something along the lines %% of the ones below to account for the metric g_jj in the phase derivatives gdistance = @(a,b)sqrt(((a-b).^2)*(g_jj(1:s_s))); % gdistance = @(a,b)sqrt(((a-b).^2)*(g_jj(1:s_s))); % nisearcher = ExhaustiveSearcher(gather(nibank),'Distance',gdistance); nisearcher = ExhaustiveSearcher(nibank,'Distance',gdistance); % nisearcher = ExhaustiveSearcher(nibank,'Distance',gdistance); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% parbank = combinations(porb_gr,a_gr,tasc_gr).Variables; Loading