- class scipy.interpolate.PPoly(c, x, extrapolate=None, axis=0)¶
Piecewise polynomial in terms of coefficients and breakpoints
The polynomial in the ith interval is x[i] <= xp < x[i+1]:
S = sum(c[m, i] * (xp - x[i])**(k-m) for m in range(k+1))
where k is the degree of the polynomial. This representation is the local power basis.
c : ndarray, shape (k, m, ...)
Polynomial coefficients, order k and m intervals
x : ndarray, shape (m+1,)
Polynomial breakpoints. 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.
axis : int, optional
Interpolation axis. Default is zero.
- piecewise polynomials in the Bernstein basis
High-order polynomials in the power basis can be numerically unstable. Precision problems can start to appear for orders larger than 20-30.
x (ndarray) Breakpoints. c (ndarray) Coefficients of the polynomials. They are reshaped to a 3-dimensional array with the last dimension representing the trailing dimensions of the original coefficient array. axis (int) Interpolation axis.
__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 the equation pp(x) == y. roots([discontinuity, extrapolate]) Find real roots of the the piecewise polynomial. extend(c, x[, right]) 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.