Loading test_efficiency.m +131 −105 Original line number Diff line number Diff line Loading @@ -150,61 +150,27 @@ Omega_min = 2*pi/porb_max; % singah = zeros(4,1); nismin = zeros(4,1); nismax = zeros(4,1); % for s = 1:4 % singah(s) = max(sin(gam + s*pi/2),[],'all'); % singal(s) = min(sin(gam + s*pi/2),[],'all'); % end % % %% Tutto sto macello e poi ora mi viene da pensare che valori intermedi di % %% tasc possono portare a sin(gam) anche più alti o più bassi... % %% Guarda come ora avrei fatto molto prima a mettere semplicemente +1 e -1 % % Adding special case for s = 1 % s = 1; % if singal(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s) + f_max; % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s) + f_min; % elseif singah(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s) + f_max; % nismax(s) = -f_max*a_max*(Omega_max^s)*singal(s) + f_max; % else % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s) + f_max; % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s) + f_min; % end % for s = 2:4 % % This range is computed by finding the maximum span of Equation (15) after varying the search % % parameters over their respective ranges (given in Table 2). This % % is done with the exception of ν which is held fixed at its % % maximum value within sub-bands over the frequency search space. % %% RECHECK EVERY COMBINATION % if singal(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s); % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s); % elseif singah(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s); % nismax(s) = -f_max*a_max*(Omega_max^s)*singal(s); % else % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s); % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s); % end % end % Find the range in ν^s (i.e. the maximum span of Eq. (15) covered by % combining the search parameters over their respective ranges) % Sin(gamma) going from -1 to 1 % Adding special case for s = 1 % s = 1; % if a_max*Omega_max>1 % nismin(s) = -f_max*a_max*(Omega_max) + f_max; % if a_min*Omega_min>1 % nismax(s) = -f_min*a_min*(Omega_min) + f_min; % else % nismax(s) = -f_max*a_min*(Omega_min) + f_max; % end % else % nismin(s) = -f_min*a_max*(Omega_max) + f_min; % nismax(s) = -f_max*a_min*(Omega_min) + f_max; % end % Is (1-Ome*a) more than fmin-fmax? to ask myself s = 1; if a_max*Omega_max>1 nismin(s) = -f_max*a_max*(Omega_max) + f_max; if a_min*Omega_min>1 nismax(s) = -f_min*a_min*(Omega_min) + f_min; else nismax(s) = -f_max*a_min*(Omega_min) + f_max; end else nismin(s) = -f_min*a_max*(Omega_max) + f_min; nismax(s) = -f_max*a_min*(Omega_min) + f_max; end % The other s's are easier nismin(s) = f_max*(1 - a_max*Omega_max); nismax(s) = f_max*(1 + a_max*Omega_max); for s = 2:4 nismin(s) = -f_max*a_max*(Omega_max^s); nismax(s) = f_max*a_max*(Omega_max^s); Loading Loading @@ -253,7 +219,7 @@ for s = 1:s_s Nni(s) = Nni(s)+1; end franco=nismin(s):((nismax(s)-nismin(s))/(Nni(s))):nismax(s); nis{s}=franco; nis{s}=franco/f_max; end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Loading @@ -274,6 +240,12 @@ tic tm=gpuArray(tm); nibank = gpuArray(combinations(nis{:}).Variables); Lambda = zeros(length(nibank),length(f_gr),'gpuArray'); F1=gpuArray((0:N-1)./(N*dt_psd)).'; f_ind = zeros(1,length(f_gr),'uint32'); for n = 1:length(f_gr) [bles,f_ind(n)] = min(abs(F1-f_gr(n))); end clear bles % nibank = combinations(nis{:}).Variables; % Lambda = zeros(length(nibank),length(f_gr)); toc Loading Loading @@ -304,7 +276,9 @@ for m=1:M ttemp = tm(m,:); ttempdif = (ttemp(:)-tmid(m)).'; ttempdifl = (ttemp(:)-tmid(m)-0.5*dt).'; xtemp = x(:,m).'; xtemp = gpuArray(x(:,m).'); sumx = sum(xtemp); % toc Loading @@ -312,54 +286,45 @@ for m=1:M % Dev'essere fatto per ciascun template, ergo mettiamo un bel ciclo % sulle possibili combinazioni di ni_s tic % for i = 1:length(nibank) for i = 1:1 for i = 1:length(nibank) % for i = 1:1 % Tento ricampionamento (Eq. 17 MP2015) % Ricampionamento (Eq. 17 MP2015) % Per prima cosa, generiamo la nuova coordinata temporale per % questa templ combini % Careful! ni_0 still needs to be defined (it's the spin freq. % currently being considered) for n = 1:length(f_gr) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% nizero = f_gr(n); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % tau = zeros(N,1); % tic % for j = 1:N % % ta(j) = ; No Tau_zero: indifferente per il calcolo della FFT % for s = 1:s_s % tau(j) = tau(j) + (nibank(i,s)/(nizero*factorial(s)))*(tm(m,j)-tmid(m))^s; % end % end % tic tau = tmid(m) + sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttempdif(1:N)).^((1:s_s).').'),2); taul(1:2) = tmid(m) + sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttempdifl(1:2)).^((1:s_s).').'),2); tau = tmid(m) + sum((nibank(i,1:s_s)./(factorial(1:s_s))).*((ttempdif(1:N)).^((1:s_s).').'),2); taul(1:2) = tmid(m) + sum((nibank(i,1:s_s)./(factorial(1:s_s))).*((ttempdifl(1:2)).^((1:s_s).').'),2); dtau = ((taul(2)-taul(1))); % inzo = (interp1(tau(:),(xtemp(:)./dtau),ttemp(:),'linear',0)).*dt; Y1 = fft((interp1(tau(:),(xtemp(:)./dtau),ttemp(:),'linear',0)).*dt).'; F1=((0:length(Y1)-1)./(length(Y1)*dt_psd)).'; [nnfreq,nnind] = min(abs(F1-nizero)); Y1=Y1(nnind); clear F1 Lambda(i,n) = 2*(abs(max(Y1)).^2)/sum(xtemp(:)); %CREDO (oppure prendono la potenza massima?) % toc % Careful! ni_0 still needs to be defined (it's the spin freq. % currently being considered) for n = 1:length(f_gr) Yenne=Y1(f_ind(n)); Lambda(i,n) = 2*(abs(Yenne)^2)/sumx; %CREDO (oppure prendono la potenza massima?) end % disp('1ni') end toc disp(length(f_gr)); disp(length(f_gr)*i); disp(m); lamfiname = sprintf('Lambda_seg_%d.mat', m); % save(lamfiname,"Lambda"); save([pathfi,lamfiname],"Lambda"); save([pathfi,lamfiname],"Lambda","-v7.3"); Lambda = zeros(length(nibank),length(f_gr)); disp(m); end %% tic % nisearcher = KDTreeSearcher(nibank,'BucketSize',100); nisearcher = KDTreeSearcher(gather(nibank),'BucketSize',100); Loading @@ -376,40 +341,101 @@ toc totlam = zeros(length(parbank),length(f_gr)); tic for n=1:length(f_gr) % for n=1:length(f_gr) % for i=1:length(parbank) % curpar = [f_gr(n),parbank(i,:)]; % % Move from ν,P,a,T_asc to ν,Ω,a,γ % curpar(2) = 2*pi/curpar(2); % for m = 1:M % curpar(4) = curpar(2)*(tmid(m) - parbank(i,3)); % curni=zeros(1,s_s); % for s=1:s_s % curni(s) = (curpar(2)^s)*sin(curpar(4)+0.5*s*pi); % end % curni = -curni.*curpar(3); % curni(1) = curni(1) + 1; % % lamfiname = sprintf('Lambda_seg_%d.mat', m); % % load(lamfiname); % load([pathfi,lamfiname]); % % [Idx,D] = knnsearch(nisearcher,curni); % totlam(i,n) = totlam(i,n)+Lambda(Idx,n); % % clear Lambda % % end % % % if (totlam > bestpar(1)) % % % bestpar = [totlam,f_gr(n),parbank(i,:)]; % % % end % end % end bles = cospi(1/2); for m = 1:M tic lamfiname = sprintf('Lambda_seg_%d.mat', m); % load(lamfiname); load([pathfi,lamfiname]); toc disp(m); tic for i=1:length(parbank) curpar = [f_gr(n),parbank(i,:)]; curpar = [bles,parbank(i,:)]; % Move from ν,P,a,T_asc to ν,Ω,a,γ curpar(2) = 2*pi/curpar(2); for m = 1:M curpar(4) = curpar(2)*(tmid(m) - parbank(i,3)); curni=zeros(1,s_s); for s=1:s_s curni(s) = (curpar(2)^s)*sin(curpar(4)+0.5*s*pi); end curni = -curni.*curpar(1).*curpar(3); curni(1) = curni(1) + curpar(1); lamfiname = sprintf('Lambda_seg_%d.mat', m); % load(lamfiname); load([pathfi,lamfiname]); curni = -curni.*curpar(3); curni(1) = curni(1) + 1; [Idx,D] = knnsearch(nisearcher,curni); totlam(i,n) = totlam(i,n)+Lambda(Idx,n); clear Lambda totlam(i,:) = totlam(i,:)+Lambda(Idx,:); end % % if (totlam > bestpar(1)) % % bestpar = [totlam,f_gr(n),parbank(i,:)]; % % end end toc disp(m); clear Lambda end % % for n=1:length(f_gr) % % for i=1:length(parbank) % % curpar = [f_gr(n),parbank(i,:)]; % % % Move from ν,P,a,T_asc to ν,Ω,a,γ % % curpar(2) = 2*pi/curpar(2); % % for m = 1:M % % curpar(4) = curpar(2)*(tmid(m) - parbank(i,3)); % % curni=zeros(1,s_s); % % for s=1:s_s % % curni(s) = (curpar(2)^s)*sin(curpar(4)+0.5*s*pi); % % end % % curni = -curni.*curpar(1).*curpar(3); % % curni(1) = curni(1) + curpar(1); % % % % lamfiname = sprintf('Lambda_seg_%d.mat', m); % % % load(lamfiname); % % load([pathfi,lamfiname]); % % % % [Idx,D] = knnsearch(nisearcher,curni); % % totlam(i,n) = totlam(i,n)+Lambda(Idx,n); % % % % clear Lambda % % % % end % % % % if (totlam > bestpar(1)) % % % % bestpar = [totlam,f_gr(n),parbank(i,:)]; % % % % end % % end % % end toc %% % disp(bestpar); % save('C:\Users\Filippo\Desktop\XMM_Jxxx\risultelli.mat'); save([pathfi,'risultelli_',num2str(Tseg),'s.mat']); save([pathfi,'risultelli_07_03_',num2str(Tseg),'s.mat'],"-v7.3"); %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Loading Loading
test_efficiency.m +131 −105 Original line number Diff line number Diff line Loading @@ -150,61 +150,27 @@ Omega_min = 2*pi/porb_max; % singah = zeros(4,1); nismin = zeros(4,1); nismax = zeros(4,1); % for s = 1:4 % singah(s) = max(sin(gam + s*pi/2),[],'all'); % singal(s) = min(sin(gam + s*pi/2),[],'all'); % end % % %% Tutto sto macello e poi ora mi viene da pensare che valori intermedi di % %% tasc possono portare a sin(gam) anche più alti o più bassi... % %% Guarda come ora avrei fatto molto prima a mettere semplicemente +1 e -1 % % Adding special case for s = 1 % s = 1; % if singal(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s) + f_max; % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s) + f_min; % elseif singah(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s) + f_max; % nismax(s) = -f_max*a_max*(Omega_max^s)*singal(s) + f_max; % else % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s) + f_max; % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s) + f_min; % end % for s = 2:4 % % This range is computed by finding the maximum span of Equation (15) after varying the search % % parameters over their respective ranges (given in Table 2). This % % is done with the exception of ν which is held fixed at its % % maximum value within sub-bands over the frequency search space. % %% RECHECK EVERY COMBINATION % if singal(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s); % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s); % elseif singah(s)>0 % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s); % nismax(s) = -f_max*a_max*(Omega_max^s)*singal(s); % else % nismin(s) = -f_max*a_max*(Omega_max^s)*singah(s); % nismax(s) = -f_min*a_min*(Omega_min^s)*singal(s); % end % end % Find the range in ν^s (i.e. the maximum span of Eq. (15) covered by % combining the search parameters over their respective ranges) % Sin(gamma) going from -1 to 1 % Adding special case for s = 1 % s = 1; % if a_max*Omega_max>1 % nismin(s) = -f_max*a_max*(Omega_max) + f_max; % if a_min*Omega_min>1 % nismax(s) = -f_min*a_min*(Omega_min) + f_min; % else % nismax(s) = -f_max*a_min*(Omega_min) + f_max; % end % else % nismin(s) = -f_min*a_max*(Omega_max) + f_min; % nismax(s) = -f_max*a_min*(Omega_min) + f_max; % end % Is (1-Ome*a) more than fmin-fmax? to ask myself s = 1; if a_max*Omega_max>1 nismin(s) = -f_max*a_max*(Omega_max) + f_max; if a_min*Omega_min>1 nismax(s) = -f_min*a_min*(Omega_min) + f_min; else nismax(s) = -f_max*a_min*(Omega_min) + f_max; end else nismin(s) = -f_min*a_max*(Omega_max) + f_min; nismax(s) = -f_max*a_min*(Omega_min) + f_max; end % The other s's are easier nismin(s) = f_max*(1 - a_max*Omega_max); nismax(s) = f_max*(1 + a_max*Omega_max); for s = 2:4 nismin(s) = -f_max*a_max*(Omega_max^s); nismax(s) = f_max*a_max*(Omega_max^s); Loading Loading @@ -253,7 +219,7 @@ for s = 1:s_s Nni(s) = Nni(s)+1; end franco=nismin(s):((nismax(s)-nismin(s))/(Nni(s))):nismax(s); nis{s}=franco; nis{s}=franco/f_max; end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Loading @@ -274,6 +240,12 @@ tic tm=gpuArray(tm); nibank = gpuArray(combinations(nis{:}).Variables); Lambda = zeros(length(nibank),length(f_gr),'gpuArray'); F1=gpuArray((0:N-1)./(N*dt_psd)).'; f_ind = zeros(1,length(f_gr),'uint32'); for n = 1:length(f_gr) [bles,f_ind(n)] = min(abs(F1-f_gr(n))); end clear bles % nibank = combinations(nis{:}).Variables; % Lambda = zeros(length(nibank),length(f_gr)); toc Loading Loading @@ -304,7 +276,9 @@ for m=1:M ttemp = tm(m,:); ttempdif = (ttemp(:)-tmid(m)).'; ttempdifl = (ttemp(:)-tmid(m)-0.5*dt).'; xtemp = x(:,m).'; xtemp = gpuArray(x(:,m).'); sumx = sum(xtemp); % toc Loading @@ -312,54 +286,45 @@ for m=1:M % Dev'essere fatto per ciascun template, ergo mettiamo un bel ciclo % sulle possibili combinazioni di ni_s tic % for i = 1:length(nibank) for i = 1:1 for i = 1:length(nibank) % for i = 1:1 % Tento ricampionamento (Eq. 17 MP2015) % Ricampionamento (Eq. 17 MP2015) % Per prima cosa, generiamo la nuova coordinata temporale per % questa templ combini % Careful! ni_0 still needs to be defined (it's the spin freq. % currently being considered) for n = 1:length(f_gr) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% nizero = f_gr(n); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % tau = zeros(N,1); % tic % for j = 1:N % % ta(j) = ; No Tau_zero: indifferente per il calcolo della FFT % for s = 1:s_s % tau(j) = tau(j) + (nibank(i,s)/(nizero*factorial(s)))*(tm(m,j)-tmid(m))^s; % end % end % tic tau = tmid(m) + sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttempdif(1:N)).^((1:s_s).').'),2); taul(1:2) = tmid(m) + sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((ttempdifl(1:2)).^((1:s_s).').'),2); tau = tmid(m) + sum((nibank(i,1:s_s)./(factorial(1:s_s))).*((ttempdif(1:N)).^((1:s_s).').'),2); taul(1:2) = tmid(m) + sum((nibank(i,1:s_s)./(factorial(1:s_s))).*((ttempdifl(1:2)).^((1:s_s).').'),2); dtau = ((taul(2)-taul(1))); % inzo = (interp1(tau(:),(xtemp(:)./dtau),ttemp(:),'linear',0)).*dt; Y1 = fft((interp1(tau(:),(xtemp(:)./dtau),ttemp(:),'linear',0)).*dt).'; F1=((0:length(Y1)-1)./(length(Y1)*dt_psd)).'; [nnfreq,nnind] = min(abs(F1-nizero)); Y1=Y1(nnind); clear F1 Lambda(i,n) = 2*(abs(max(Y1)).^2)/sum(xtemp(:)); %CREDO (oppure prendono la potenza massima?) % toc % Careful! ni_0 still needs to be defined (it's the spin freq. % currently being considered) for n = 1:length(f_gr) Yenne=Y1(f_ind(n)); Lambda(i,n) = 2*(abs(Yenne)^2)/sumx; %CREDO (oppure prendono la potenza massima?) end % disp('1ni') end toc disp(length(f_gr)); disp(length(f_gr)*i); disp(m); lamfiname = sprintf('Lambda_seg_%d.mat', m); % save(lamfiname,"Lambda"); save([pathfi,lamfiname],"Lambda"); save([pathfi,lamfiname],"Lambda","-v7.3"); Lambda = zeros(length(nibank),length(f_gr)); disp(m); end %% tic % nisearcher = KDTreeSearcher(nibank,'BucketSize',100); nisearcher = KDTreeSearcher(gather(nibank),'BucketSize',100); Loading @@ -376,40 +341,101 @@ toc totlam = zeros(length(parbank),length(f_gr)); tic for n=1:length(f_gr) % for n=1:length(f_gr) % for i=1:length(parbank) % curpar = [f_gr(n),parbank(i,:)]; % % Move from ν,P,a,T_asc to ν,Ω,a,γ % curpar(2) = 2*pi/curpar(2); % for m = 1:M % curpar(4) = curpar(2)*(tmid(m) - parbank(i,3)); % curni=zeros(1,s_s); % for s=1:s_s % curni(s) = (curpar(2)^s)*sin(curpar(4)+0.5*s*pi); % end % curni = -curni.*curpar(3); % curni(1) = curni(1) + 1; % % lamfiname = sprintf('Lambda_seg_%d.mat', m); % % load(lamfiname); % load([pathfi,lamfiname]); % % [Idx,D] = knnsearch(nisearcher,curni); % totlam(i,n) = totlam(i,n)+Lambda(Idx,n); % % clear Lambda % % end % % % if (totlam > bestpar(1)) % % % bestpar = [totlam,f_gr(n),parbank(i,:)]; % % % end % end % end bles = cospi(1/2); for m = 1:M tic lamfiname = sprintf('Lambda_seg_%d.mat', m); % load(lamfiname); load([pathfi,lamfiname]); toc disp(m); tic for i=1:length(parbank) curpar = [f_gr(n),parbank(i,:)]; curpar = [bles,parbank(i,:)]; % Move from ν,P,a,T_asc to ν,Ω,a,γ curpar(2) = 2*pi/curpar(2); for m = 1:M curpar(4) = curpar(2)*(tmid(m) - parbank(i,3)); curni=zeros(1,s_s); for s=1:s_s curni(s) = (curpar(2)^s)*sin(curpar(4)+0.5*s*pi); end curni = -curni.*curpar(1).*curpar(3); curni(1) = curni(1) + curpar(1); lamfiname = sprintf('Lambda_seg_%d.mat', m); % load(lamfiname); load([pathfi,lamfiname]); curni = -curni.*curpar(3); curni(1) = curni(1) + 1; [Idx,D] = knnsearch(nisearcher,curni); totlam(i,n) = totlam(i,n)+Lambda(Idx,n); clear Lambda totlam(i,:) = totlam(i,:)+Lambda(Idx,:); end % % if (totlam > bestpar(1)) % % bestpar = [totlam,f_gr(n),parbank(i,:)]; % % end end toc disp(m); clear Lambda end % % for n=1:length(f_gr) % % for i=1:length(parbank) % % curpar = [f_gr(n),parbank(i,:)]; % % % Move from ν,P,a,T_asc to ν,Ω,a,γ % % curpar(2) = 2*pi/curpar(2); % % for m = 1:M % % curpar(4) = curpar(2)*(tmid(m) - parbank(i,3)); % % curni=zeros(1,s_s); % % for s=1:s_s % % curni(s) = (curpar(2)^s)*sin(curpar(4)+0.5*s*pi); % % end % % curni = -curni.*curpar(1).*curpar(3); % % curni(1) = curni(1) + curpar(1); % % % % lamfiname = sprintf('Lambda_seg_%d.mat', m); % % % load(lamfiname); % % load([pathfi,lamfiname]); % % % % [Idx,D] = knnsearch(nisearcher,curni); % % totlam(i,n) = totlam(i,n)+Lambda(Idx,n); % % % % clear Lambda % % % % end % % % % if (totlam > bestpar(1)) % % % % bestpar = [totlam,f_gr(n),parbank(i,:)]; % % % % end % % end % % end toc %% % disp(bestpar); % save('C:\Users\Filippo\Desktop\XMM_Jxxx\risultelli.mat'); save([pathfi,'risultelli_',num2str(Tseg),'s.mat']); save([pathfi,'risultelli_07_03_',num2str(Tseg),'s.mat'],"-v7.3"); %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Loading