interpax.interp1d

interpax.interp1d(xq: Real[Array, 'Nq'] | Real[ndarray, 'Nq'], x: Real[Array, 'Nx'] | Real[ndarray, 'Nx'], f: Num[Array, 'Nx ...'] | Num[ndarray, 'Nx ...'], method: str = 'cubic', derivative: int = 0, extrap: bool | float | tuple = False, period: None | float = None, **kwargs) → Inexact[Array, 'Nq ...']Source

Interpolate a 1d function.

Parameters:

• xq (ndarray, shape(Nq,)) – query points where interpolation is desired

• x (ndarray, shape(Nx,)) – coordinates of known function values (“knots”)

• f (ndarray, shape(Nx,...)) – function values to interpolate

• method (str) –

  method of interpolation

  • 'nearest': nearest neighbor interpolation

  • 'linear': linear interpolation

  • 'cubic': C1 cubic splines (aka local splines)

  • 'cubic2': C2 cubic splines (aka natural splines)

  • 'catmull-rom': C1 cubic centripetal “tension” splines

  • 'cardinal': C1 cubic general tension splines. If used, can also pass keyword parameter c in float[0,1] to specify tension

  • 'monotonic': C1 cubic splines that attempt to preserve monotonicity in the data, and will not introduce new extrema in the interpolated points

  • 'monotonic-0': same as 'monotonic' but with 0 first derivatives at both endpoints

  • 'akima': C1 cubic splines that appear smooth and natural

• derivative (int >= 0) – derivative order to calculate

• extrap (bool, float, array-like) – whether to extrapolate values beyond knots (True) or return nan (False), or a specified value to return for query points outside the bounds. Can also be passed as a 2 element array or tuple to specify different conditions for xq<x[0] and x[-1]<xq

• period (float > 0, None) – periodicity of the function. If given, function is assumed to be periodic on the interval [0,period]. None denotes no periodicity

Returns:

fq (ndarray, shape(Nq,…)) – function value at query points

Notes

For repeated interpolation given the same x, f data, recommend using Interpolator1D which caches the calculation of the derivatives and spline coefficients.