Interpolating data from a look up table

Question

read the look up table

LUT = np.genfromtxt('test.out', delimiter=',', dtype=float)
LUT:
    12, 25, 136, 6743
    13, 26, 139, 6786
    14, 27, 142, 6791
    15, 28, 145, 6789

Values to be read from the LUT are as follows:

x1, x2, x3 = 12.5, 25.5, 137

Reading the neighboring two values in the LUT for each of the given values (3 columns), I have to linearly interpolate the results (4th column in LUT).

The given values (x1, x2, x3) belongs to between 1st and 2nd row of the LUT. Based on this how to read the results between 1st and 2nd row?

Answer 1

Given a list of coordinates coords where you want to interpolate, you can use scipy.spatial.cKDTree to obtain the 2 closest entries of your table that are necessary for the linear interpolation. The code below shows an usage example, already vectorized.

import numpy as np
from scipy.spatial import cKDTree

# inputs
LTU = np.genfromtxt('test.txt', delimiter=',')

coords = ((12.5, 25.5, 137),
          (13.5, 26.5, 141),
          (14.5, 25.5, 144))

# querying and interpolating
xyz = LTU[:, :3]
val = LTU[:, 3]

del LTU # attempt to clean up memory

tree = cKDTree(xyz)
dist, ind = tree.query(coords, k=2)

d1, d2 = dist.T
v1, v2 = val[ind].T
v = (d1)/(d1 + d2)*(v2 - v1) + v1

print(v)
#[ 6758.73909236  6789.16987298  6790.03575996]