Commit e0e28ece authored by Riccardo La Placa's avatar Riccardo La Placa
Browse files

Tseg 128s, perché farci del male con uno spazio di ni enorme?

parent 0b02de7d

scsearch.m

+28 −25
Original line number Diff line number Diff line
@@ -2,13 +2,13 @@ clear; 
close all;



% Define variables, M is segm. number

%pathfi = './';

pathfi = './';



%%%%%%%%%%%%%%%%

tic



% finame = 'J1023_B_2017_Bary.fits';

%finame = 'EPN_0744840201_bary.fits';

finame = 'EPN_0744840201_bary.fits';

% t_raw = fitsread([pathfi,finame],"binarytable");

t_raw = fitsread('C:\Users\Filippo\Desktop\EPN_0744840201_bary.fits','binarytable');

t_raw = t_raw{1};
@@ -43,20 +43,22 @@ a_tru = 0.0649905; %lt-s 
tasc_tru = (57231.437581-MJDREF)*86400; %in secondi



% f_gr = zeros(5,1);

porb_gr = zeros(5,1);

a_gr = zeros(5,1);

tasc_gr = zeros(5,1);

% porb_gr = zeros(5,1);

% a_gr = zeros(5,1);

% tasc_gr = zeros(5,1);



tic



f_gr=f_tru+(-2:2).';



for j = 1:5

    %f_gr(j) = f_tru*((j^2)/9);

    porb_gr(j) = porb_tru*((j^2)/9);

    a_gr(j) = a_tru*((j^2)/9);

    tasc_gr(j) = tasc_tru*((j^2)/9);

end

porb_gr = [porb_tru-10.0,porb_tru-5.0,porb_tru,porb_tru+5.0,porb_tru+10.0].';

a_gr = [0.01, 0.03, a_tru, 0.09, 0.12].';

tasc_gr = tasc_tru+[-500.0,-250.0,0.0,250.0,500.0].';

% for j = 1:5

%     %f_gr(j) = f_tru*((j^2)/9);

%     porb_gr(j) = porb_tru*((j^2)/9);

%     a_gr(j) = a_tru*((j^2)/9);

%     tasc_gr(j) = tasc_tru*((j^2)/9);

% end



f_min = min(f_gr);

f_max = max(f_gr);
@@ -91,7 +93,7 @@ t=(t(1:end-1)+(t(2)-t(1))/2).'; % vettore tempi rebinnato, prendo il centro del 


toc

tic

Tseg=256; %segments' length in seconds

Tseg=128; %segments' length in seconds

M=fix((t(end)-t(1))/Tseg); %number of segments

%con fix prendo la parte intera, scarto l'ultimo segmento che tanto non

%sarà mai di lunghezza Tseg (molto improbabile)
@@ -311,14 +313,14 @@ for m=1:M 
            %         tau(j) = tau(j) + (nibank(i,s)/(nizero*factorial(s)))*(tm(m,j)-tmid(m))^s;

            %     end

            % end

            tic

            % tic



            tau = sum((nibank(i,1:s_s)./(nizero*factorial(1:s_s))).*((tm(m,1:N)-tmid(m)).^((1:s_s).').'),2);

            toc

            % toc



            tic

            % tic

            X1 = interp1(tm(m,:),x(m,:),tau,'linear',0);

            toc

            % toc



            %X1 è la timeseries ricampionata (controllare che sia un vettore colonna)

            %zero-padding (metto gli zeri alla fine) -------------------------------
@@ -329,21 +331,21 @@ for m=1:M 
            %[Cm,edges]=(histcounts(X1,round((X1(end)-X1(1))/dt_psd)));

            %edges=edges(end)-edges(2); %mi dà il tempo preciso di tutta la TdF, che sarà leggermente diversa da length(C)*dt per come è definito histcounts

            % Y1=(2./sum(X1).*abs(fft(X1)).^2).'; %normalizzazione Leahy, giusto?????

            tic

            % tic

            Y1 = fft(X1).';

            clear X1

            F1=((0:length(Y1)-1)./(tm(m,end)-tm(m,1))).';

            % F1=F1(1:round(length(F1)/2));

            % Y1=Y1(1:round(length(Y1)/2));

            toc

            tic

            % toc

            % tic

            cond = F1>=f_min & F1<=f_max;

            F1=F1(cond);

            Y1=Y1(cond);



            %Calcolo della detection statistic

            Lambda(i,n,m)=sum(abs(Y1).^2)/sum(x(m,:)); %CREDO (oppure prendono la potenza massima?)

            toc

            % toc

        end

        disp('1ni')

    end
@@ -373,9 +375,10 @@ for n=1:length(f_gr) 
            curpar(4) = curpar(2)*(tmid(m) - curpar(4));

            curni=zeros(1,s_s);

            for s=1:s_s

                curni(s) = (curpar(2)^s)*sin(curpar(4)-0.5*s*pi);

                curni(s) = (curpar(2)^s)*sin(curpar(4)+0.5*s*pi);

            end

            curni=curni.*curpar(1).*curpar(2);

            curni = -curni.*curpar(1).*curpar(3);

            curni(1) = curni(1) + curpar(1);

            % curni(s_s+1) = curpar(1);



            [Idx,D] = knnsearch(nisearcher,curni);