Finding Valley of Waveform (local minimum) without displacing wave

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Krispy Scripts 2016-11-18

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/312913-finding-valley-of-waveform-local-minimum-without-displacing-wave

评论： Greg Dionne 2016-12-5

采纳的回答： Star Strider

example.mat

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I am trying to find the peak and valley of a waveform. My data is attached in the matrix. It is a waveform repeated four times. I have written code based off of another thread. I am using findpeaks function, which worked well. I then used taking the max of the matrix and subtracting it to inverse the waveforms. However, it is displacing the waveform, which is a problem because I am trying to get the ratio of the peak to valley, so the displacing of the waveform is giving me inaccurate ratio. I will attach my code. Any ideas on how I might go about finding the valleys without displacing the waveform?

 if true
datain=example;
fs=4e4;
[pks,locs,w,p]=findpeaks(datain,fs,'NPeaks',4);
inverted=max(datain)-datain;
pksmean=mean(pks);
[valleys,locsvalley,wvalley,pvalley]=findpeaks(inverted,fs,'NPeaks',4,'WidthReference','halfheight');
valleysmean=mean(valleys);
peakvalleyratio=pksmean/valleysmean;
halfwidthaveragevalleys=mean(wvalley);
end

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采纳的回答

Star Strider 2016-11-18

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/312913-finding-valley-of-waveform-local-minimum-without-displacing-wave#answer_243838

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It’s easiest to use the subscripts rather than the times to get the valleys. Also, there appears to be a bug in findpeaks such that supplying the sampling frequency does not produce the correct times for the peak locations. An easy workaround is to provide a time vector instead and use that.

See if this does what you want:

D = load('Krispy Scripts example.mat');
datain=D.datain;
fs=4e4;
t = linspace(0, 1, length(datain))'/fs;                         % Time Vector
[pks,locs,w,p]=findpeaks(datain,t,'NPeaks',4);
inverted=max(datain)-datain;
pksmean=mean(pks);
[valleys,locsvalley,wvalley,pvalley]=findpeaks(inverted,'NPeaks',4,'WidthReference','halfheight');
valleysmean=mean(valleys);
peakvalleyratio=pksmean/valleysmean;
halfwidthaveragevalleys=mean(wvalley);
valleys_actual = datain(locsvalley);
valleys_time = t(locsvalley);
figure(1)
plot(t, datain)
hold on
plot(locs, pks, '^r', 'MarkerFaceColor','r')
plot(valleys_time, valleys_actual, 'vr', 'MarkerFaceColor','r')
hold off
grid