![]() are equally spaced and monotonic, use the methods ' *linear', ' *cubic', or ' *nearest'. For faster interpolation when X1, X2, X3, etc. interpn(V,1) is the same as interpn(V).Īll the interpolation methods require that X1, X2, and X3 be monotonic and have the same format ("plaid") as if they were created using ndgrid. Interpolates as above, assuming X1 = 1:size(V,1), X2 = 1:size(V,2), X3 = 1:size(V,3), etc.Įxpands V by interleaving interpolates between each element, working recursively for ntimes iterations. ![]() interpn works for all N-D arrays with 2 or more dimensions. with both row and column vectors) are passed through ndgrid to create the Y1, Y2, Y3, etc. Vector arguments that are not the same size, and have mixed orientations (i.e. must be arrays of the same size, or vectors. xq 0:pi/16:2pi Interpolate the function at the query points and plot the result. x 0:pi/4:2pi v sin (x) Define the query points to be a finer sampling over the range of x. Define the sample points, x, and corresponding sample values, v. Out of range values are returned as NaNs. Interpolation of Coarsely Sampled Sine Function. By default, griddedInterpolant uses the 'linear' interpolation method. ![]() x sort (20rand (100,1)) v besselj (0,x) Create a gridded interpolant object for the data. The points are sampled at random 1-D locations between 0 and 20. Create a vector of scattered sample points v. specify the points at which the data V is given. Use griddedInterpolant to interpolate a 1-D data set. For an N-D V, interpn is called with 2*N+1 arguments. Interpolates to find VI, the values of the underlying multidimensional function V at the points in the arrays Y1, Y2, Y3, etc. Multidimensional data interpolation (table lookup) Interpn (MATLAB Functions) MATLAB Function Reference
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