scipy.interpolate.

PPoly#

class scipy.interpolate.PPoly(c, x, extrapolate=None, axis=0)[source]#

Piecewise polynomial in terms of coefficients and breakpoints

The polynomial between x[i] and x[i + 1] is written in the local power basis:

S = sum(c[m, i] * (xp - x[i])**(k-m) for m in range(k+1))

where k is the degree of the polynomial.

Parameters:

cndarray, shape (k, m, …): Polynomial coefficients, order k and m intervals.
xndarray, shape (m+1,): Polynomial breakpoints. Must be sorted in either increasing or decreasing order.
extrapolatebool or ‘periodic’, optional: If bool, determines whether to extrapolate to out-of-bounds points based on first and last intervals, or to return NaNs. If ‘periodic’, periodic extrapolation is used. Default is True.
axisint, optional: Interpolation axis. Default is zero.

Attributes:

xndarray: Breakpoints.
cndarray: Coefficients of the polynomials. They are reshaped to a 3-D array with the last dimension representing the trailing dimensions of the original coefficient array.
axisint: Interpolation axis.

Methods

`__call__`(x[, nu, extrapolate])	Evaluate the piecewise polynomial or its derivative.
`derivative`([nu])	Construct a new piecewise polynomial representing the derivative.
`antiderivative`([nu])	Construct a new piecewise polynomial representing the antiderivative.
`integrate`(a, b[, extrapolate])	Compute a definite integral over a piecewise polynomial.
`solve`([y, discontinuity, extrapolate])	Find real solutions of the equation `pp(x) == y`.
`roots`([discontinuity, extrapolate])	Find real roots of the piecewise polynomial.
`extend`(c, x)	Add additional breakpoints and coefficients to the polynomial.
`from_spline`(tck[, extrapolate])	Construct a piecewise polynomial from a spline
`from_bernstein_basis`(bp[, extrapolate])	Construct a piecewise polynomial in the power basis from a polynomial in Bernstein basis.
`construct_fast`(c, x[, extrapolate, axis])	Construct the piecewise polynomial without making checks.