How to find end of time series in plot

Hi!

This is kind of a basic question.

I have a file containing a number of keys/positions (x-pos, y-pox, etc..) that again contains data within arrays. There are some missing data in this file, and the missing data appears as a flat line in the plot. I only care for the missing data that last for more that 2 sec (2*mps). I have managed to find the index of the beginning of the missing data, I don't know how to find the end (or technically the whole missing data interval). The reason I want to find the end as well is that I want to plot figures that shows the interval of the missing data, and some time-buffer at both ends so I can see how the plot behaves right before the data goes missing, and right after. Is there some way to find the end of each interval (or the end of them)?

Thank you in advance!

My code so far:

data = load('x.mat');

figure(1) 
plot(data.Time,data.PITCH);     %The whole graph
N = length(data.XPOS);
mps = length(data.Time)/(data.Time(end));       %measurements per second (about 28 meas/sec)

M = [];
arr = [];
counter = 0;
nc = 0;
nnc=0;
intervall=[];
index = [];
%len = [];
for i=1:length(data.XPOS)-1       
    if data.XPOS(i) == data.XPOS(i+1)       %if the data repeats itself
        counter = counter+1;
        if counter > mps*2    % if tangent is repeated for more than 2 sec
            nc = nc+1;
            arr(nc) = data.XPOS(i);
            
            %%%% trying to find end of interval here  
            
            if not(ismember(data.XPOS(i),M))
                nnc=nnc+1;
                M(nnc) = data.XPOS(i);      % the x-pos that have missing data for more than 2 sec
                intervall(nnc) = data.Time(i);      % time of the critically missed data
                index(nnc) = i;
            end
        end
    else
        counter = 0;
    end  
end

%%%%%%      Plot critical points        %%%%%%


start=[];
endd =[];
for k=1:length(M)
    start(k)= index(k)- 28*20;
    endd(k) =index(k) + 28*70;      %   +28*70 is buffer after the first index of missing data
    figure(k+1)    
    plot(data.Time(start(k):endd(k)),data.XPOS(start(k):endd(k)));     
end

[KSSV]

How are the missing values? It got NaN's?

[Vilde Solberg]

For this file; 4 intervals of missing data that last for more than 2 sec, there are 5048 missing elements all toghether (of about 350 000).

The number of intervals of missing data is given by length(M).

And when the data goes missing, the last documented value repeats itself until the connection is back. There are no NaN.

Hope this helps!

[KSSV]

Attach your data.

[Vilde Solberg]

I can't do that, I'm sorry. But replacing data.XPOS with a general array as: pos = [0.11, 0.12, 0.12, 0.12, 0.12 0.12, 0.14, 0.14, 0.11, 0.16, 0.13, 0.13, 0.13, 0.13] and counter > 3, it should work the same. The general code:

M = [];
arr = [];
counter = 0;
nc = 0;
nnc=0;
interval=[];
index = [];
len = [];
pos = [0.11, 0.12, 0.12, 0.12, 0.12 0.12, 0.14, 0.14, 0.11, 0.16, 0.13, 0.13, 0.13, 0.13];
for i=1:length(pos)-1       
    if pos(i) == pos(i+1)
        counter = counter+1;
        if counter > 3    % if tangent is repeated for more than 2 sec
            nc = nc+1;
            arr(nc) = pos(i);
            %%%% trying to find end of interval here  
            
           
            if not(ismember(pos(i),M))
                nnc=nnc+1;
                M(nnc) = pos(i); % the x-pos that have missing data for more than 2 sec
                interval(nnc) = pos(i);  % time of the critically missed data
                index(nnc) = i;
            end
        end
    else
        counter = 0;
    end  
end

Answer 1

[Joseph Cheng]

to go with your example of pos where

pos = [0.11, 0.12, 0.12, 0.12, 0.12 0.12, 0.14, 0.14, 0.11, 0.16, 0.13, 0.13, 0.13, 0.13];

you can find sequences of consecutive numbers by doing something like this

dpos = diff(pos); %diff from next
stalepos = [find(dpos~=0)+1 numel(pos)+1]%find edges of consecutive index where the difference is 0

stalepos = 1×6

2 7 9 10 11 15

for ind = 1:numel(stalepos)-1
   disp(pos(stalepos(ind):stalepos(ind+1)-1))  %display the values between the sequences.  
end

    0.1200    0.1200    0.1200    0.1200    0.1200

    0.1400    0.1400

    0.1100

    0.1600

    0.1300    0.1300    0.1300    0.1300

now that last for loop we can see which ones have length > your minimum not missing/stale data threshold you can do whatever you need to.