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PONearest neighbor 1 dimensional data with a specified range
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copied!<p>I have two nested lists A and B:</p> <p><code>A = [[50,140],[51,180],[54,500],......]</code></p> <p><code>B = [[50.1, 170], [51,200],[55,510].....]</code></p> <p>The 1st element in each inner list runs from 0 to around 1e5, the 0th element runs from around 50 up to around 700, these elements are unsorted. What i want to do, is run through each element in A[n][1] and find the closest element in B[n][1], but when searching for the nearest neighbor i want to only search within an interval defined by A[n][0] plus or minus 0.5.</p> <p>I have been using the function:</p> <pre><code>def find_nearest_vector(array, value): idx = np.array([np.linalg.norm(x+y) for (x,y) in array-value]).argmin() return array[idx] </code></pre> <p>Which finds the nearest neighbor between the coordinates <code>A[0][:]</code>and <code>B[0][:]</code>, for example. However, this I need to confine the search range to a rectangle around some small shift in the value A[0][0]. Also, I do not want to reuse elements - I want a unique bijection between each value A[n][1] to B[n][1] within the interval A[n][0] +/- 0.5.</p> <p>I have been trying to use Scipy's KDTree, but this reuses elements and I don't know how to confine the search range. Effectively, I want to do a one dimensional NNN search on a two dimensional nested list along a specific axis where the neighborhood in which the NNN search is within a hyper-rectangle defined by the 0th element in each inner list plus or minus some small shift.</p>

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