Storing the Y value of a known X value

Hello,

I have flipped this time series data using flipud and have found the value of 5% of the second to last peak. I want to flip this data back to its original position and figure out the x value that goes with the y value I found earlier. Does anyone know how I can do this?

for k = 1:15 % number of pages

clear pks locs indx threshv df Starts

df = (ButteryFilter(cutoff,samp_freq,abs(derivative(:,1,k))));

[pks,locs] = findpeaks(df,'minpeakprominence',0.01);

threshv = 0.05*abs(pks(end-1)); % 2nd to last peak is first movement

z = locs(end-1) % time of second to last peak

indx=find(df(z:10000)<threshv); % starting from 2nd to last pk, find 5 percent

Starts=indx(1,1) + z;

% find the y point of the index so i can flip and find right time

Start_RT(end+1)= Starts(1,1);

Sub_RT{end+1} = (Start_RT(:,k)) - (target_solutions{:,k}); % reaction time calculation

% RT_Unflipped = flipud(RT_FlipIt)

end

(I am interested in knowing at what time 5% of the value of the second to last peak occurs. I have to unflip this so that the time in ms is correct, the second to last peak is actually the second peak when unflipped)

Answer 1

[Satwik]

Hi @Aero32,

If the flipped data has length N and index Starts is found in the flipped data, the corresponding index in the original (unflipped) data is:

Starts_unflipped = N - Starts + 1;

With a time vector t, the associated time value is:

time_at_event = t(Starts_unflipped);

This provides the correct X (time) value for the identified Y after reversing the flip.