Find mean of steps in broken signal

X Centre Y Mean ________ ______ 1618 28.811 1651 30.648 1691 26.499 1725 28.549 1789 35.506 1828 33.727 1841 33.103 1876 33.305 1939 39.992

figure

plot(x, y)

hold on

plot(x(Lv), y(Lv), '.r')

hold off

grid

ylim([min(ylim) 70])

text(xmean, ymean, compose('\\mu = %.2f \\rightarrow',ymean), 'Horiz','right', 'Vert','middle', 'Rotation',-80)

.

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Konvictus177 2023-8-15

编辑：Konvictus177 2023-8-15

在 MATLAB Online 中打开

y_bad.mat

Thanks, this looks very promosing but your method above finds more than 5 flat regions.

I want the code to find exactly 5 flat regions as indicated in my image above where the signal is mostly flat.

Is there any smart way to get there from your code above?

I am thinking about looking at the length and difference of consecutive points of a flat region. If its shorter than say x points than its not considered flat region, if its longer than x points than its a flat region. I think this works:

min_contiguous_samples = 30; % select regions only if they are at least this length
ind = length>min_contiguous_samples;
start2 = start(ind);
stop2 = stop(ind);

But I still have another problem. Let's say my signal looks a bit worse like the one below where the flat regions are not so proiment. The code would not find the two regions I highlighted. How can I adjust the code to find these regions where the signal is mostly flat? I attached the signal.

Star Strider 2023-8-15

在 MATLAB Online 中打开

This version uses the median value of the segment lengths to select the segments to be analysed.

LD1 = load('y.mat');

LD2 = load('y_bad.mat');

y{1} = LD1.y;

y{2} = LD2.y;

x{1} = 0:numel(y{1})-1;

x{2} = 0:numel(y{2})-1;

for k1 = 1:numel(y)

Lv = islocalmax(y{k1}>25, 'FlatSelection','all');

start = strfind(Lv, [0 1]);

stop = strfind(Lv, [1 0]);

ssmtx = [start; stop]

sslen = diff(ssmtx); % Segment Lengths

% sslen_sts = [min(sslen) median(sslen) max(sslen)] % Statistics

Lvss = sslen >= 0.9*median(sslen) % Select Columns Of 'ssmtx' Using The 'median' Of The Length Values As The Criterion

ssmtx = ssmtx(:,Lvss) % Selected 'ssmtx'

xmean = [];

ymean = [];

for k2 = 1:size(ssmtx,2)

ymean(k2,k1) = mean(y{k1}(ssmtx(1,k2) : ssmtx(2,k2)), 'omitnan');

xmean(k2,k1) = mean(x{k1}(ssmtx(1,k2) : ssmtx(2,k2)), 'omitnan');

end

Flat_Means = table(xmean(:,k1), ymean(:,k1), 'VariableNames',{'X Centre','Y Mean'})

figure

plot(x{k1}, y{k1})

hold on

plot(x{k1}(Lv), y{k1}(Lv), '.r')

hold off

grid

xlim([x{k1}(find(Lv,1)-100) max(xlim)]) % 'Zoom' X-Axis

ylim([min(ylim) 70])

text(xmean(:,k1), ymean(:,k1)+2, compose('\\mu = %.2f \\rightarrow',ymean(:,k1)), 'Horiz','right', 'Vert','middle', 'Rotation',-80)

xl1 = xline(ssmtx(1,:), '-g', 'DisplayName','Segment Start');

xl2 = xline(ssmtx(2,:), '-r', 'DisplayName','Segment Stop');

legend([xl1(1) xl2(1)], 'Location','SE')

end

ssmtx = 2×9

1613 1628 1690 1695 1761 1828 1834 1852 1906 1625 1676 1694 1757 1819 1830 1850 1902 1974

Lvss = 1×9 logical array

0 1 0 1 1 0 0 1 1

ssmtx = 2×5

1628 1695 1761 1852 1906 1676 1757 1819 1902 1974

Flat_Means = 5×2 table

X Centre Y Mean ________ ______ 1651 30.648 1725 28.549 1789 35.506 1876 33.305 1939 39.992

ssmtx = 2×4

1330 1334 1407 1636 1331 1403 1631 1709

Lvss = 1×4 logical array

0 1 1 1

ssmtx = 2×3

1334 1407 1636 1403 1631 1709

Flat_Means = 3×2 table

X Centre Y Mean ________ ______ 1367.5 31.885 1518 32.04 1671.5 38.432

The islocalmax function makes this relatively straightforward, however dealing with ‘real-world’ data inevitably involves some compromises. It may not be possible to ‘correctly’ detect all the flat segments you detect visually, because it may not be possible to code those criteria.

The data are noisy, and while there are various ways to deal with that, filtering the data could make it impossible to determine the segment start and stop points. If you want to filter them, I suggest experimenting with movmean or movmedian to start with. They are both essentially lowpass filters, and relatively easy to implement.

.

Konvictus177 2023-8-16

@Star Strider The updated code works perfect! Thank you very much!

Star Strider 2023-8-16

As always, my pleasure!

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