traceH = hilbert(trace); clear trace traceH = traceH.*conj(traceH(:,1)); GAPL = 0.4; moveN = round(8/GAPL); [output] = moveVectorMean2(traceH,moveN); traceH=output; clear output amp = abs(traceH); [M,N] = size(amp); gapD = round(4/GAPL); [output] = spacephsed(traceH,gapD); clear traceH phaOutput = angle(output); clear output phaseUnw(:,:) = unwrap(squeeze(phaOutput(:,:))')'; clear phaOutput [~,axisTp,outputtp] = denoiseFunc(5,500,phaseUnw,fd,fs,GAPL); % 慢轴，快轴 clear phaseUnw [~,axisT,outputint] = denoiseFunc(5,490,amp,fd,fs,GAPL); % 慢轴，快轴 clear amp for i=1:1:floor(length(outputtp(:,1))/10) phase(i,:)=mean(outputtp((i-1)*10+1:i*10,:)); end clear outputtp for i=1:1:floor(length(outputint(:,1))/10) intensity(i,:)=mean(outputint((i-1)*10+1:i*10,:)); end clear outputint figure for i=1:1:22 plot(axisTp,phase(i,:)/10*10+i*4); hold on end hold off figure for i=1:1:22 plot(axisT,intensity(i,:)/10*10+i*4); hold on end hold off % for i=1:1:floor(length(intensity(1,:))/4000) % stdp(:,i)=var(phase(:,(i-1)*4000+1:i*4000),0,2); % stdt(:,i)=var(intensity(:,(i-1)*4000+1:i*4000),0,2); % end % for i=1:1:29 % positionp(i)=find(stdp(:,i)==max(stdp(:,i))); % positioni(i)=find(stdt(:,i)==max(stdt(:,i))); % end %%将数据切为不同帧 for i=1:1:10 trandatap(:,:,i)=phase(1:8,(i-1)*4000+1:(i)*4000); trandatai(:,:,i)=intensity(1:8,(i-1)*4000+1:(i)*4000); end %%删除信噪比较差的数据。（先把数据图像画图，然后筛选） trainphase=trandatap; traintensity=trandatai; trainphase(:,:,27:29)=[]; trainphase(:,:,1:2)=[]; trainphase(:,:,16)=[]; trainphase(:,:,14)=[]; trainphase(:,:,10)=[]; trainphase(:,:,7:8)=[]; trainphase(:,:,4)=[]; trainphase(:,:,1)=[]; traintensity(:,:,27:29)=[]; traintensity(:,:,1:2)=[]; traintensity(:,:,16)=[]; traintensity(:,:,14)=[]; traintensity(:,:,10)=[]; traintensity(:,:,7:8)=[]; traintensity(:,:,4)=[]; traintensity(:,:,1)=[];

traceH = hilbert(trace);
clear trace
traceH = traceH.*conj(traceH(:,1));

GAPL = 0.4;
moveN = round(8/GAPL);
[output] = moveVectorMean2(traceH,moveN);
traceH=output;
clear output
amp = abs(traceH);
[M,N] = size(amp);
gapD = round(4/GAPL);
[output] = spacephsed(traceH,gapD);
clear traceH
phaOutput = angle(output);
clear output
phaseUnw(:,:) = unwrap(squeeze(phaOutput(:,:))')';
clear phaOutput
[~,axisTp,outputtp] = denoiseFunc(5,500,phaseUnw,fd,fs,GAPL); % Slow axis, Fast axis
clear phaseUnw
[~,axisT,outputint] = denoiseFunc(5,490,amp,fd,fs,GAPL); % Slow axis, Fast axis
clear amp

for i=1:1:floor(length(outputtp(:,1))/10)
phase(i,:)=mean(outputtp((i-1)*10+1:i*10,:));
end
clear outputtp

for i=1:1:floor(length(outputint(:,1))/10)
intensity(i,:)=mean(outputint((i-1)*10+1:i*10,:));
end
clear outputint

figure
for i=1:1:22
plot(axisTp,phase(i,:)/10*10+i*4);
hold on
end
hold off

figure
for i=1:1:22
plot(axisT,intensity(i,:)/10*10+i*4);
hold on
end
hold off

% for i=1:1:floor(length(intensity(1,:))/4000)
% stdp(:,i)=var(phase(:,(i-1)*4000+1:i*4000),0,2);
% stdt(:,i)=var(intensity(:,(i-1)*4000+1:i*4000),0,2);
% end

% for i=1:1:29
% positionp(i)=find(stdp(:,i)==max(stdp(:,i)));
% positioni(i)=find(stdt(:,i)==max(stdt(:,i)));
% end

%% Split the data into different frames
for i=1:1:10
trandatap(:,:,i)=phase(1:8,(i-1)*4000+1:(i)*4000);
trandatai(:,:,i)=intensity(1:8,(i-1)*4000+1:(i)*4000);
end

%% Remove data with poor signal-to-noise ratio (plot the data and then select)
trainphase=trandatap;
traintensity=trandatai;
trainphase(:,:,27:29)=[];
trainphase(:,:,1:2)=[];
trainphase(:,:,16)=[];
trainphase(:,:,14)=[];
trainphase(:,:,10)=[];
trainphase(:,:,7:8)=[];
trainphase(:,:,4)=[];
trainphase(:,:,1)=[];
traintensity(:,:,27:29)=[];
traintensity(:,:,1:2)=[];
traintensity(:,:,16)=[];
traintensity(:,:,14)=[];
traintensity(:,:,10)=[];
traintensity(:,:,7:8)=[];
traintensity(:,:,4)=[];
traintensity(:,:,1)=[];