`scipy.interpolate._interpolate:NdPPoly`

source: build-install/usr/lib/python3.14/site-packages/scipy/interpolate/_interpolate.py:2393

Signature

class NdPPoly(c, x, extrapolate = None)

Members

Summary

Piecewise tensor product polynomial.

Extended Summary

The value at point xp = (x', y', z', ...) is evaluated by first computing the interval indices i such that

x[0][i[0]] <= x' < x[0][i[0]+1]
x[1][i[1]] <= y' < x[1][i[1]+1]
...

and then computing

S = sum(c[k0-m0-1,...,kn-mn-1,i[0],...,i[n]]
        * (xp[0] - x[0][i[0]])**m0
        * ...
        * (xp[n] - x[n][i[n]])**mn
        for m0 in range(k[0]+1)
        ...
        for mn in range(k[n]+1))

where k[j] is the degree of the polynomial in dimension j. This representation is the piecewise multivariate power basis.

Parameters

c : ndarray, shape (k0, ..., kn, m0, ..., mn, ...): Polynomial coefficients, with polynomial order kj and mj+1 intervals for each dimension j.
x : ndim-tuple of ndarrays, shapes (mj+1,): Polynomial breakpoints for each dimension. These must be sorted in increasing order.
extrapolate : bool, optional: Whether to extrapolate to out-of-bounds points based on first and last intervals, or to return NaNs. Default: True.

Attributes

x : tuple of ndarrays: Breakpoints.
c : ndarray: Coefficients of the polynomials.

Methods

__call__
derivative
antiderivative
integrate
integrate_1d
construct_fast

Notes

High-order polynomials in the power basis can be numerically unstable.

Aliases

scipy.interpolate.NdPPoly

Referenced by

This package

release:0.18.0-notes