Finding nearest low match in array
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Hello, I’m trying to find the nearest match of a value in an array, with the condition that it never rounds up. To explain what I mean, imagine a vector of
f= [1:0.5:5]
where I want to find the nearest low match of 2.3. To simply find the nearest match, I would use
val = 2.3
tmp = abs(f-val)
[i i] = min(tmp)
nearest = f(idx)
How do I reformulate this so it gives me the index of 2 instead? Any tips?
Note, I want it to handle exact matches and negative values as well.
采纳的回答
Image Analyst
2016-4-4
There may be a more compact way of doing it but I'm doing it in explicit separate steps with a ton of comments so that you can easily understand it:
% Define target value.
targetValue = 2.3
% Define test values. This is just for demo, you'd use your actual values.
testValues = 5 * rand(1, 10)
% Find differences
diffValues = testValues - targetValue
% We only want values less than the target value
% so those diffValues will be negative.
% We want the max of those, so set the others to -inf
diffValues(diffValues > 0) = -inf;
% Now we can find the index of the greatest value that
% is still less than the reference value.
[~, indexOfMax] = max(diffValues)
% Get the value from the testValues array
maxValue = testValues(indexOfMax)
更多回答（3 个）
Kuifeng
2016-4-4
bigger_value_location = find((f-val)>0);
nearest = f(bigger_value_location(1)-1)
3 个评论
Kuifeng
2016-4-4
you are welcome. pls accept this answer if it's ok. Note (1) f values need to be sorted from small to big
This answer only works because the nearest value happens to be the first value above the search value. It would fail with
f = fliplr(1:0.5:5);
A simple way would be to set any value below 0 in your tmp to Inf, before calling min:
f = [1 1.5 2.5 3 2 4.5 5.5 5]; %shuffled values to show that ordering does not matter
val = 2.3;
tmp = val - f;
tmp(tmp < 0) = Inf;
[~, loc] = min(tmp)
Azzi Abdelmalek
2016-4-4
f= [1:0.5:5]
val = 2.3
[ii,jj]=sort(f)
ii1=find(ii>val,1)-1
idx=jj(ii1)
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