cmlabs.interpolate.interpolate

cmlabs.interpolate.interpolate(xvals, x, yvals=None, coef=None, method='auto')[source]

Interpolate the value of a function at a given point.

Parameters:

  • xvals (array_like, 1-D) – The sorted x-coordinates of the data points.

  • x (float) – The x-coordinate at which to evaluate the polynomial.

  • yvals (array_like, 1-D, optional) – The y-coordinates of the data points, i.e., f(\(x\)). Only used if coef is not provided.

  • coef (array_like, 1-D or 2-D, optional) – The coefficients of the polynomial.

  • method (str, optional, default: 'auto') –

    The interpolation method to use. Can be one of:

    • ’auto’

    • ’lagrange’

    • ’newton’

    • ’newtonfd’

    • ’newtonbd’

    • ’gaussfd’

    • ’gaussbd’

    • ’stirling’

    • ’bessel’

Returns:

res – The value of the polynomial at \(x\).

Return type:

float

See also

divided_differences, finite_differences, lagrange, newton, newtonfd, newtonbd, gaussfd, gaussbd, stirling, bessel

Notes

The output is the value of the polynomial at \(x\) using the specified method or the most efficient method if method is ‘auto’.

Examples

>>> import numpy as np
>>> from cmlabs.interpolate import interpolate
>>> xvals = np.array([0, 1, 2, 3])
>>> yvals = np.array([1, 3, 2, 5])
>>> x = np.float32(1.15)
>>> interpolate(xvals, x, yvals=yvals)
>>> 2.8701875