# Find closest value in array

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I have two vector(which are time stamps) like,

V N

1375471092848936 1375473384440853

1375473388165900 1375471277856598

1375471320476780 1375473388165900

1375473388947681 1375471322465961

1375473392527002 1375471335206288

.................. ..................

My goal is to find closest time in N with respect to V (i.e. find time in N which is nearly equal with V). My frame is W = 1e4, furthermore V should lies between N-W and N+W. So how do I get closest time through MATLAB? Any help would be appreciated.

Thanks

##### 0 Comments

### Accepted Answer

Joe S
on 10 Sep 2018

Edited: MathWorks Support Team
on 27 Nov 2018

To compute the closest value in a vector “N” for each element of “V”, try the following code with example vectors “N” and “V”:

V = randi(10,[5 1])

N = randi(10,[5 1])

A = repmat(N,[1 length(V)])

[minValue,closestIndex] = min(abs(A-V’))

closestValue = N(closestIndex)

Note that if there is a tie for the minimum value in each column, MATLAB chooses the first element in the column.

##### 6 Comments

David
on 5 Jul 2023

This just saved my night!

For anybody juse searching the index, faster variant:

[~,closestIndex] = min(abs(N-V));

### More Answers (4)

Andrew Reibold
on 25 Aug 2014

Edited: Andrew Reibold
on 25 Aug 2014

This finds the value in N which is closest to the V value I am calling.

N = [1990 1998 2001 2004 2001]

V = [2000 2011 2010 2001 1998]

[c index] = min(abs(N-V(1)))

In this case Im looking for the closest value to 'V(1)' which is 2000. It should return the 3rd or 5th value of N which is 2001.

Note: 'index' is the index of the closest value. If two are the same, like in this example with two different '2001's, it will return the index of the first one.

##### 4 Comments

reetu hooda
on 17 Feb 2018

Image Analyst
on 17 Feb 2018

reetu, if N is just a single number then you can do this

[minDistance, indexOfMin] = min(abs(V-N));

Image Analyst
on 25 Aug 2014

How about this:

clc;

% Sample data

numberOfRows = 5;

V = rand(numberOfRows, 1)

N = rand(numberOfRows, 1)

% Find min distance

minDistance = inf;

for ni = 1 : numberOfRows

for vi = 1 : numberOfRows

distances(vi, ni) = abs(N(ni) - V(vi));

if distances(vi, ni) < minDistance

minNRow = ni;

minVRow = vi;

minDistance = distances(vi, ni);

end

end

end

% Report to command window:

distances

fprintf('Closest distance is %f which occurs between row %d of N and row %d of V\n',...

minDistance, minNRow, minVRow);

In the command window:

V =

0.5309

0.6544

0.4076

0.8200

0.7184

N =

0.9686

0.5313

0.3251

0.1056

0.6110

distances =

0.4378 0.0005 0.2057 0.4252 0.0801

0.3142 0.1231 0.3293 0.5488 0.0435

0.5610 0.1237 0.0825 0.3020 0.2033

0.1487 0.2886 0.4948 0.7144 0.2090

0.2503 0.1870 0.3932 0.6127 0.1074

Closest distance is 0.000470 which occurs between row 2 of N and row 1 of V

##### 3 Comments

Image Analyst
on 2 Nov 2017

You can try this:

% Sample data

numberOfRows = 5;

V = rand(numberOfRows, 1)

N = rand(numberOfRows, 1)

% Find min distance

distances = pdist2(V, N)

[minDistance, index] = min(distances(:))

[minVRow, minNRow] = ind2sub(size(distances), index)

fprintf('The closest distance is %f which occurs between\nrow %d of V (%f) and\nrow %d of N (%f)\n',...

minDistance, minVRow, V(minVRow), minNRow, N(minNRow));

% Double-check / Prove it

V(minVRow) - N(minNRow)

John D'Errico
on 10 Jul 2024 at 18:36

Edited: John D'Errico
on 10 Jul 2024 at 18:40

To be honest, the easiest way is to use knnsearch. It works well in one dimension, as you have here, and it should be quite efficient.

V = [1375471092848936; 1375473388165900; 1375471320476780; 1375473388947681; 1375473392527002];

N = [1375473384440853; 1375471277856598; 1375473388165900; 1375471322465961; 1375471335206288];

help knnsearch

ids = knnsearch(N,V)

There is no need to look at differences, compute absolute values, etc. Just use the tool that is designed to solve your problem directly.

##### 0 Comments

Korosh Agha Mohammad Ghasemi
on 25 Jun 2024

Moved: Voss
on 25 Jun 2024

% Example V and N vectors

V = [1375471092848936; 1375473388165900; 1375471320476780; 1375473388947681; 1375473392527002];

N = [1375473384440853; 1375471277856598; 1375473388165900; 1375471322465961; 1375471335206288];

W = 1e4; % Window size

% Initialize the closest times array

closest_times = zeros(size(V));

% Find the closest time in N for each time in V within the window

for i = 1:length(V)

% Calculate the absolute differences

diffs = abs(N - V(i));

% Find the indices within the window

within_window = diffs <= W;

if any(within_window)

% Find the closest time

[~, closest_idx] = min(diffs(within_window));

% Get the actual index in N

closest_times(i) = N(find(within_window, closest_idx, 'first'));

else

% No times within the window

closest_times(i) = NaN;

end

end

% Display the closest times

disp('Closest times:');

disp(closest_times);

##### 0 Comments

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