Interpolation (scipy.interpolate) — SciPy v1.16.0 Manual (original) (raw)

There are several general facilities available in SciPy for interpolation and smoothing for data in 1, 2, and higher dimensions. The choice of a specific interpolation routine depends on the data: whether it is one-dimensional, is given on a structured grid, or is unstructured. One other factor is the desired smoothness of the interpolator. In short, routines recommended for interpolation can be summarized as follows:

Smoothing and approximation of data#

Further details are given in the links below

• 1-D interpolation
  • Piecewise linear interpolation
  • Cubic splines
  • Monotone interpolants
  • Interpolation with B-splines
    * Non-cubic splines
  • Batches of y
  • Parametric spline curves
  • Missing data
  • Legacy interface for 1-D interpolation (interp1d)
    * Recommended replacements for interp1d modes
• Piecewise polynomials and splines
  • Manipulating PPoly objects
  • B-splines: knots and coefficients
    * B-spline basis elements
    * Design matrices in the B-spline basis
  • Bernstein polynomials, BPoly
  • Conversion between bases
• Smoothing splines
  • Spline smoothing in 1D
    * “Classic” smoothing splines and generalized cross-validation (GCV) criterion
    * Smoothing splines with automatic knot selection
    * Smoothing spline curves in \(d>1\)
    * Batching of y arrays
    * Legacy routines for spline smoothing in 1-D
  • 2-D smoothing splines
    * Bivariate spline fitting of scattered data
    * Bivariate spline fitting of data on a grid
    * Bivariate spline fitting of data in spherical coordinates
• Multivariate data interpolation on a regular grid (RegularGridInterpolator)
  • Batch dimensions of values
  • Uniformly spaced data
• Scattered data interpolation (griddata)
• Using radial basis functions for smoothing/interpolation
  • 1-D Example
  • 2-D Example
• Extrapolation tips and tricks
  • interp1d : replicate numpy.interp left and right fill values
  • CubicSpline extend the boundary conditions
  • Manually implement the asymptotics
    * The setup
    * Use the known asymptotics
  • Extrapolation in D > 1
• interp2d transition guide
  • 1. How to transition away from using interp2d
    * 1.1 interp2d on a regular grid
    * 1.2. interp2d with full coordinates of points (scattered interpolation)
  • 2. Alternative to interp2d: regular grid
  • 3. Scattered 2D linear interpolation: prefer LinearNDInterpolator to SmoothBivariateSpline or bisplrep