Scattered data 4D interpolation
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Dear Sir/Madam
I have following type of data
% X1 X2 X3 X4 V
XV = [
0 0 0 0 -1.5474
0 0 0 0.0010 -1.5392
0 0 0.5000 0.0010 -1.5360
0 0 0.5000 0 -1.5422
0 0 1.0000 0 -1.5501
0 0 1.0000 0.0010 -1.5503
0 0.5000 1.0000 0 -1.5393
0 0.5000 1.0000 0.0010 -1.5447
0 0.5000 0.5000 0.0010 -1.5518
0 0.5000 0.5000 0 -1.5481
0 0.5000 0 0 -1.5366
0 0.5000 0 0.0010 -1.5479
0 1.0000 0 0 -1.5561
0 1.0000 0 0.0010 -1.5362
0 1.0000 0.5000 0.0010 -1.5335
0 1.0000 0.5000 0 -1.5360
0 1.0000 1.0000 0 -1.5531
0 1.0000 1.0000 0.0010 -1.5531
0.5000 1.0000 0 0 -1.5620
0.5000 1.0000 0 0.0010 -1.5449
0.5000 1.0000 0.5000 0.0010 -1.5646
0.5000 1.0000 0.5000 0 -1.5419
0.5000 1.0000 1.0000 0 -1.5450
0.5000 1.0000 1.0000 0.0010 -1.5339
0.5000 0.5000 1.0000 0 -1.5477
0.5000 0.5000 1.0000 0.0010 -1.5280
0.5000 0.5000 0.5000 0.0010 -1.5421
0.5000 0.5000 0.5000 0 -1.5505
0.5000 0.5000 0 0 -1.5504
0.5000 0.5000 0 0.0010 -1.5418
0.5000 0 0 0 -1.5450
0.5000 0 0 0.0010 -1.5421
0.5000 0 0.5000 0.0010 -1.5503
0.5000 0 0.5000 0 -1.5447
0.5000 0 1.0000 0 -1.5448
0.5000 0 1.0000 0.0010 -1.5392
1.0000 0 0 0 -1.5534
1.0000 0 0 0.0010 -1.5334
1.0000 0 0.5000 0.0010 -1.5447
1.0000 0 0.5000 0 -1.5444
1.0000 0 1.0000 0 -1.5310
1.0000 0 1.0000 0.0010 -1.5564
1.0000 0.5000 1.0000 0 -1.5533
1.0000 0.5000 1.0000 0.0010 -1.5422
1.0000 0.5000 0.5000 0.0010 -1.5275
1.0000 0.5000 0.5000 0 -1.5445
1.0000 0.5000 0 0 -1.5558
1.0000 0.5000 0 0.0010 -1.5363
1.0000 1.0000 0 0 -1.5423
1.0000 1.0000 0 0.0010 -1.5563
1.0000 1.0000 0.5000 0.0010 -1.5506
1.0000 1.0000 0.5000 0 -1.5448
1.0000 1.0000 1.0000 0 -1.5501
1.0000 1.0000 1.0000 0.0010 -1.5563
];
X1,X2,X3, and X4 are independent variables, and V is dependent one. How can I interpolate the data?
Most of methods I saw for scattered data interpolation only work for 2D and 3D.
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Accepted Answer
More Answers (1)
Walter Roberson
on 13 Aug 2020
What interpolation do you need?
For example you could do knnsearch() asking for the 2 nearest neighbours of each query point, and do linear interpolation for each.
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