`scipy.interpolate._cubic:CubicHermiteSpline`

source: /scipy/interpolate/_cubic.py :74

Signature

   class     CubicHermiteSpline (    x    ,    y    ,    dydx    ,    axis    =  0   ,    extrapolate    =  None     )

Members

__init__

Summary

Piecewise cubic interpolator to fit values and first derivatives (C1 smooth).

Extended Summary

The result is represented as a PPoly instance.

Parameters

x : array_like, shape (n,): 1-D array containing values of the independent variable. Values must be real, finite and in strictly increasing order.
y : array_like: Array containing values of the dependent variable. It can have arbitrary number of dimensions, but the length along axis (see below) must match the length of x. Values must be finite.
dydx : array_like: Array containing derivatives of the dependent variable. It can have arbitrary number of dimensions, but the length along axis (see below) must match the length of x. Values must be finite.
axis : int, optional: Axis along which y is assumed to be varying. Meaning that for x[i] the corresponding values are np.take(y, i, axis=axis). Default is 0.
extrapolate : {bool, 'periodic', None}, 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. If None (default), it is set to True.

Attributes

x : ndarray, shape (n,): Breakpoints. The same x which was passed to the constructor.
c : ndarray, shape (4, n-1, ...): Coefficients of the polynomials on each segment. The trailing dimensions match the dimensions of y, excluding axis. For example, if y is 1-D, then c[k, i] is a coefficient for (x-x[i])**(3-k) on the segment between x[i] and x[i+1].
axis : int: Interpolation axis. The same axis which was passed to the constructor.

Methods

__call__
derivative
antiderivative
integrate
solve
roots

Notes

If you want to create a higher-order spline matching higher-order derivatives, use BPoly.from_derivatives.

Array API Standard Support

CubicHermiteSpline has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ⛔                   
PyTorch               ✅                     ⛔                   
JAX                   ⚠️ no JIT             ⛔                   
Dask                  ⛔                     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

Aliases

scipy.interpolate.CubicHermiteSpline