Finding the nearest value and return the index of array in Python
numpy, python, python-3.x
Solution
This is similar to using bisect_left, but it'll allow you to pass in an array of targets
def find_closest(A, target):
#A must be sorted
idx = A.searchsorted(target)
idx = np.clip(idx, 1, len(A)-1)
left = A[idx-1]
right = A[idx]
idx -= target - left < right - target
return idx
Some explanation:
First the general case: `idx = A.searchsorted(target)` returns an index for each `target` such that `target` is between `A[index - 1]` and `A[index]`. I call these `left` and `right` so we know that `left < target <= right`. `target - left < right - target` is `True` (or 1) when target is closer to `left` and `False` (or 0) when target is closer to `right`.
Now the special case: when `target` is less than all the elements of `A`, `idx = 0`. `idx = np.clip(idx, 1, len(A)-1)` replaces all values of `idx` < 1 with 1, so `idx=1`. In this case `left = A[0]`, `right = A[1]` and we know that `target <= left <= right`. Therefor we know that `target - left <= 0` and `right - target >= 0` so `target - left < right - target` is `True` unless `target == left == right` and `idx - True = 0`.
There is another special case if `target` is greater than all the elements of `A`, In that case `idx = A.searchsorted(target)` and `np.clip(idx, 1, len(A)-1) ` replaces `len(A)` with `len(A) - 1` so `idx=len(A) -1` and `target - left < right - target` ends up `False` so idx returns `len(A) -1`. I'll let you work though the logic on your own.
For example:
In [163]: A = np.arange(0, 20.)
In [164]: target = np.array([-2, 100., 2., 2.4, 2.5, 2.6])
In [165]: find_closest(A, target)
Out[165]: array([ 0, 19, 2, 2, 3, 3])
Problem
I found this post: Python: finding an element in an array and it's about returning the index of an array through matching the values. On the other hand, what I am thinking of doing is similar but different. I would like to find the nearest value for the target value. For example I am looking for 4.2 but I know in the array there is no 4.2 but I want to return the index of the value 4.1 instead of 4.4. What would be the fastest way of doing it? I am thinking of doing it the old way like how I used to do it with Matlab, which is using the array A where I want to get the index from to minus the target value and take the absolute of it, then select the min. Something like this:- ``` [~,idx] = min(abs(A - target)) ``` That is Matlab code but I am newbie in Python so I am thinking, is there a fast way of doing it in Python? Thank you so much for your help!