scipy.interpolate.NdPPoly¶

class
scipy.interpolate.
NdPPoly
(c, x, extrapolate=None)[source]¶ Piecewise tensor product polynomial
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[k0m01,...,knmn1,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
 cndarray, shape (k0, …, kn, m0, …, mn, …)
Polynomial coefficients, with polynomial order kj and mj+1 intervals for each dimension j.
 xndimtuple of ndarrays, shapes (mj+1,)
Polynomial breakpoints for each dimension. These must be sorted in increasing order.
 extrapolatebool, optional
Whether to extrapolate to outofbounds points based on first and last intervals, or to return NaNs. Default: True.
See also
PPoly
piecewise polynomials in 1D
Notes
Highorder polynomials in the power basis can be numerically unstable.
 Attributes
 xtuple of ndarrays
Breakpoints.
 cndarray
Coefficients of the polynomials.
Methods
__call__
(self, x[, nu, extrapolate])Evaluate the piecewise polynomial or its derivative
construct_fast
(c, x[, extrapolate])Construct the piecewise polynomial without making checks.