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Gridded and scattered data interpolation, data gridding, piecewise polynomials

Interpolation is a technique for adding new data points within a range of a set of known data points. You can use interpolation to fill-in missing data, smooth existing data, make predictions, and more. Interpolation in MATLAB® is divided into techniques for data points on a grid and scattered data points.


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interp11-D data interpolation (table lookup)
interp2Interpolation for 2-D gridded data in meshgrid format
interp3Interpolation for 3-D gridded data in meshgrid format
interpnInterpolation for 1-D, 2-D, 3-D, and N-D gridded data in ndgrid format
griddedInterpolantGridded data interpolation
pchipPiecewise Cubic Hermite Interpolating Polynomial (PCHIP)
makimaModified Akima piecewise cubic Hermite interpolation
splineCubic spline data interpolation
ppvalEvaluate piecewise polynomial
mkppMake piecewise polynomial
unmkppExtract piecewise polynomial details
padecoefPadé approximation of time delays
interpft1-D interpolation (FFT method)
ndgridRectangular grid in N-D space
meshgrid2-D and 3-D grids
griddataInterpolate 2-D or 3-D scattered data
griddatanInterpolate N-D scattered data
scatteredInterpolantInterpolate 2-D or 3-D scattered data


Gridded and Scattered Sample Data

Introduction to interpolating gridded and scattered data sets.

Interpolating Gridded Data

Interpolation of regularly spaced, axis-aligned data sets.

Interpolating Scattered Data

Interpolating scattered data using scatteredInterpolant.

Featured Examples