Interpolation of Multiple 1-D Value Sets

This example shows how to interpolate three 1-D data sets in a single pass using griddedInterpolant. This is a faster alternative to looping over your data sets.

Define the x-coordinates that are common to all value sets.

x = (1:5)';

Define the sets of sample points along the columns of matrix V.

V = [x, 2*x, 3*x]

V = 5×3

     1     2     3
     2     4     6
     3     6     9
     4     8    12
     5    10    15

Create a 2-D grid of sample points.

samplePoints = {x, 1:size(V,2)};

This compact notation specifies a full 2-D grid. The first element, samplePoints{1}, contains the x-coordinates for V, and samplePoints{2} contains the y-coordinates. The orientation of each coordinate vector does not matter.

Create the interpolant, F, by passing the sample points and sample values to griddedInterpolant.

F = griddedInterpolant(samplePoints,V);

Create a 2-D query grid with 0.5 spacing along x over all columns of V.

queryPoints = {(1:0.5:5),1:size(V,2)};

Evaluate the interpolant at the x-coordinates for each value set.

Vq = F(queryPoints)

Vq = 9×3

    1.0000    2.0000    3.0000
    1.5000    3.0000    4.5000
    2.0000    4.0000    6.0000
    2.5000    5.0000    7.5000
    3.0000    6.0000    9.0000
    3.5000    7.0000   10.5000
    4.0000    8.0000   12.0000
    4.5000    9.0000   13.5000
    5.0000   10.0000   15.0000