This library provides the adaptive MBA algorithm from [1] implemented in C++11. This is a fast algorithm for scattered N-dimensional data interpolation and approximation. Python bindings are also provided.
Example of 2D interpolation in C++:
#include <mba.hpp>
int main() {
// Coordinates of data points.
std::vector<mba::point<2>> coo = {
{0.0, 0.0},
{0.0, 1.0},
{1.0, 0.0},
{1.0, 1.0},
{0.4, 0.4},
{0.6, 0.6}
};
// Data values.
std::vector<double> val = {
0.2, 0.0, 0.0, -0.2, -1.0, 1.0
};
// Bounding box containing the data points.
mba::point<2> lo = {-0.1, -0.1};
mba::point<2> hi = { 1.1, 1.1};
// Initial grid size.
mba::index<2> grid = {3, 3};
// Algorithm setup.
mba::MBA<2> interp(lo, hi, grid, coo, val);
// Get interpolated value at arbitrary location.
double w = interp(mba::point<2>{0.3, 0.7});
}Same example in python:
from mba import *
interp = mba2(lo=[-0.1,-0.1], hi=[1.1,1.1], grid=[3,3],
coo=[ [0.0, 0.0], [0.0, 1.0], [1.0, 0.0],
[1.0, 1.0], [0.4, 0.4], [0.6, 0.6] ],
val=[0.2, 0.0, 0.0, -0.2, -1.0, 1.0]
)
w = interp([[0.3, 0.7]])Also see python/example.ipynb, python/layered.ipynb.
- S. Lee, G. Wolberg, and S. Y. Shin. Scattered data interpolation with multilevel B-Splines. IEEE Transactions on Visualization and Computer Graphics, 3:228–244, 1997, doi:10.1109/2945.620490.