Finding specific peaks and valleys

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Aram Zeytunyan 2025-1-30

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2173505-finding-specific-peaks-and-valleys

评论： Star Strider 2025-2-1

I have a periodic signal with 6 peaks and 6 valleys. I am able to find all 6 peaks and all 6 valleys using the code below:

% plot periodic signal
plot(angle,signal)
hold on;
% fit to avoid noisy oscillations and find 6 global peaks
f = fit(angle,signal,'sin9');
yfitted = feval(f,angle);
plot(angle,yfitted,'r')
% find peaks and corresponding angles
[ypk0,idx0] = findpeaks(yfitted);
peaks = signal(idx0);
max_angles = angle(idx0);
% invert fitted signal to find 6 global valleys and corresponding angles
yfittedinv = max(yfitted) - yfitted;
[ypk,idx] = findpeaks(yfittedinv);
valleys = signal(idx);
min_angles = angle(idx);

Furthermore, I am able to find the global minimum (i.e., the lowest valley) using this line:

% find the global minimum
minangle = min_angles(valleys == min(valleys));

Both the arrays "max_angles" and "min_angles" have 6 elements. The question is how to reduce the number of elements in the array "min_angles" from 6 to 3, where I will have only the global minimum and the 2 non-neighbor valleys. The attached pic should help. I am able to find the green circle, but I also need to find the 2 red circles. Note that the global valley (green circle) is not always in the middle. It can be the first element of the array "min_angles", or it can be the last one. In the picture below, it's number 4.

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Image Analyst 2025-1-30

在 MATLAB Online 中打开

Make it easy for us to help you, not hard. Attach your variables "angle" and "signal" in a .mat or text file. That way we'll have something to work with and won't have to try to create data on our own.

save('answers.mat', 'angle', 'signal');

If you have any more questions, then attach your data and code to read it in with the paperclip icon after you read this:

TUTORIAL: How to ask a question (on Answers) and get a fast answer

Aram Zeytunyan 2025-1-31

Please see attached. Thank you!

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Answer 1

Star Strider 2025-1-30

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链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2173505-finding-specific-peaks-and-valleys#answer_1558651

编辑：Star Strider 2025-1-30

在 MATLAB Online 中打开

To find specific valleys, one option might be to use the MinPeakProminence value. The prominences are the tthird output returned by findpeaks, so you can look at those to see iif that option would work.

Another option is to get the peak values and use the mink (or maxk) function to return thee three lowest values (since that appears to be what the green circle and the red circles represent). Return both outputs from mink beecausee the second will be the index values of the minima (or maxima, depending on you you have the results returned), and you can use those indices with the returned values for the peaks and their locations to isolate the ones you want.

This is based on the figure you posted.

.

EDIT — (30 Jan 2025 at 21:33)

Example —

a = linspace(0,360).';

s = sin(2*pi*a/360*6)-sin(2*pi*a/720);

[vlys,vlocs] = findpeaks(-s)

vlys = 6×1

1.3727 1.7946 1.9796 1.9212 1.6080 1.1255

vlocs = 6×1

14 30 46 63 79 96

[minpks, minpksidx] = mink(-vlys,3)

minpks = 3×1

-1.9796 -1.9212 -1.7946

minpksidx = 3×1

3 4 2

figure

plot(a, s)

hold on

plot(a(vlocs(minpksidx)), -vlys(minpksidx), 'rs')

hold off

grid

ylim([-2.5 1])

.

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Star Strider 2025-1-31

在 MATLAB Online 中打开

testdata1.csv

Considering the information in your original question, mink seems an appropriate approach.

I still don’t understand what your criteria are for identifying the peaks and valleys of interest, and your code doesn’t illuminate that.

clear

close all

% [fn,pn] = uigetfile('*.csv;*.mat;*.xlsx*','Select saved data file','MultiSelect', 'on');

% [fn,pn] = uigetfile('*.csv;*.mat;*.xlsx*','Select saved data file');

% cd(pn);

files = dir('*.csv')

files = struct with fields:

name: 'testdata1.csv' folder: '/users/mss.system.p2qdd' date: '31-Jan-2025 23:37:57' bytes: 25305 isdir: 0 datenum: 7.3965e+05

k = 1;

% for k = 1:numel(cellstr(fn))

% if numel(cellstr(fn))>=2

% loaddata = importdata([pn,char(fn(k))]);

% signal(:,k) = loaddata(:,2);

% else

% loaddata = importdata([pn,char(fn)]);

% signal = loaddata(:,2);

% end

% if numel(cellstr(fn))>=2

% for k = 1:numel(cellstr(fn))

% loaddata = importdata([pn,char(fn(k))]);

loaddata = readmatrix(files.name)

loaddata = 834×2

0.3530 133.2857 0.7844 134.3363 1.2157 136.3152 1.6471 137.6488 2.0785 139.0422 2.5099 141.3151 2.9412 142.2948 3.3726 144.7676 3.8040 146.6495 4.2354 147.9877

<mw-icon class=""></mw-icon>

signal(:,k) = loaddata(:,2);

angle(:,k) = loaddata(:,1);

plot(angle(:,k),signal(:,k),'LineWidth',1);

hold on;

% end

% else

% loaddata = importdata([pn,char(fn)]);

% angle = loaddata(:,1);

% signal = loaddata(:,2);

% plot(angle,signal)

% hold on;

% end

% angle = loaddata(:,1);

% app.angle = angle;

% app.signal = signal;

%

% signal_test = app.signal;

% size(signal_test,2);

% numel(cellstr(fn));

% plot(angle,signal)

% hold on

% [globalmin,globalminidx] = min(signal)

% globalminangle = angle(signal == globalmin)

% globalminangle1 = angle(globalminidx)

% plot(angle,signal)

f = fit(angle,signal,'sin9');

yfitted = feval(f,angle);

plot(angle,yfitted,'r')

xlabel('angle (deg)')

ylabel('signal (mV)')

xlim([0 360])

hold on;

[ypk0,idx0] = findpeaks(yfitted);

peaks = signal(idx0);

max_angles = angle(idx0);

yfittedinv = max(yfitted) - yfitted;

% plot(app.UIAxes_2,angle,yfitted,'r','LineWidth',1);

[ypk,idx] = findpeaks(yfittedinv);

% [ypk1,idx1] = mink(ypk,3);

% valleys = yfitted(idx);

valleys = signal(idx);

min_angles = angle(idx);

minangle = min_angles(valleys == min(valleys));

minvalley = valleys(valleys == min(valleys));

idx2 = idx(valleys == min(valleys));

idx3 = find(idx == idx2);

if rem(idx3, 2) == 0 % global min index is even

idxv = [2 4 6];

if yfitted(2)-yfitted(1)>0 % curve is ascending

idxp = [2 3 4 5 6 1];

else % curve is descending

idxp = [1 2 3 4 5 6];

end

else % global min index is odd

idxv = [1 3 5];

if yfitted(2)-yfitted(1)>0 % curve is ascending

idxp = [1 2 3 4 5 6];

else % curve is descending

idxp = [6 1 2 3 4 5];

end

% plot(max_angles(idxp),peaks(idxp),'o','MarkerSize',12)

% hold on;

min3_angles = min_angles(idxv);

valleys3 = valleys(idxv);

plot(min3_angles,valleys3,'x','MarkerSize',12)

hold on

% plot(minangle,minvalley,'.r','MarkerSize',30)

% hold on

newpeaks = peaks(idxp);

newmax_angles = max_angles(idxp);

plot(newmax_angles(1:2),newpeaks(1:2),'.r','MarkerSize',15)

hold on;

plot(newmax_angles(3:4),newpeaks(3:4),'.g','MarkerSize',15)

hold on;

plot(newmax_angles(5:6),newpeaks(5:6),'.b','MarkerSize',15)

hold on;

newpeaks1 = (newpeaks(1:2:end) + newpeaks(2:2:end))/2;

delta = newpeaks1-valleys(idxv);

idx4 = find(delta == min(delta));

plot(minangle,minvalley,'.r','MarkerSize',30)

hold on

plot(min3_angles(idx4),valleys3(idx4),'.g','MarkerSize',30)

hold on

xline(min3_angles(idx4),'-g', LineWidth = 1.5);

hold on

yline(valleys3(idx4),'-g', LineWidth = 1.5);

●

.

If you describe the problem you want to solve, it would likely be straightforward to devise a more efficient solution.

Lackng that description, I’ll delete my Answer in a few days.

.

Aram Zeytunyan 2025-2-1

编辑：Aram Zeytunyan 2025-2-1

I need to find 3x valleys out of 6. The starting/reference point is the lowest valley (the large red dot in the plot, which is easy to find). The other two cannot be the neighboring valleys as that's forbidden by physics. mink will find valleys labeled 2, 4, and 5. I need to find valleys 2,4, and 6.

Star Strider 2025-2-1

在 MATLAB Online 中打开

testdata.csv

I am still not certain what you want, since I am still uncertain of the criteria.

See if this works —

loaddata = readmatrix('testdata.csv');

angle = loaddata(:,1);

signal = loaddata(:,2);

[pks,plocs,pprm] = findpeaks(signal, MinPeakProminence=10);

[vys,vlocs,vprm] = findpeaks(-signal, MinPeakProminence=10);

[minvly,minidx] = min(-vys); % Minimum Valley & Associated Valley Index

idxrng = [max(1,(minidx-2)) minidx min((minidx+2),numel(vlocs))] % Valley Indices ±2 Positions From Minimum

idxrng = 1×3

2 4 6

Results = table(angle(vlocs(idxrng)), signal(vlocs(idxrng)), VariableNames=["Angle","Value"])

Results = 3x2 table

Angle Value ______ ______ 102.16 83.776 226.39 77.624 343.3 81.332

figure

plot(angle, signal, DisplayName='Signal')

hold on

plot(angle(plocs), pks, 'vg', DisplayName='Peaks')

plot(angle(vlocs), -vys, '^r', DisplayName='Valleys')

plot(angle(vlocs(idxrng)), signal(vlocs(idxrng)), 'ms', MarkerSize=12, DisplayName='Selected')

hold off

grid

xlabel('Angle (°)')

ylabel('Signal (mV)')

legend(Location='best')

The ‘idxrng’ calculation contains a ‘fail safe’ to prevent finding indices outside the allotted range.

.

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