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Cubic polynomial splines are also used extensively in structural analysis applications, such as Euler–Bernoulli beam theory. Cubic polynomial splines have also been applied to mortality analysis [2] and mortality forecasting. [3] Cubic splines can be extended to functions of two or more parameters, in several ways. Bicubic splines (Bicubic ...
Example showing non-monotone cubic interpolation (in red) and monotone cubic interpolation (in blue) of a monotone data set. Monotone interpolation can be accomplished using cubic Hermite spline with the tangents m i {\displaystyle m_{i}} modified to ensure the monotonicity of the resulting Hermite spline.
Paper which explains step by step how cubic spline interpolation is done, but only for equidistant knots. Numerical Recipes in C, Go to Chapter 3 Section 3-3; A note on cubic splines; Information about spline interpolation (including code in Fortran 77) TinySpline:Open source C-library for splines which implements cubic spline interpolation
Example C++ code for several 1D, 2D and 3D spline interpolations (including Catmull-Rom splines). Multi-dimensional Hermite Interpolation and Approximation, Prof. Chandrajit Bajaja, Purdue University; Python library containing 3D and 4D spline interpolation methods.
SciPy: Python-library, contains a sub-library scipy.interpolate with spline functions based on FITPACK; TinySpline: C-library for splines with a C++ wrapper and bindings for C#, Java, Lua, PHP, Python, and Ruby; Einspline: C-library for splines in 1, 2, and 3 dimensions with Fortran wrappers
For example, to calculate for one of the points, find (,) for the points to the left and right of the target point and calculate their slope, and similarly for . To find the cross derivative f x y {\displaystyle f_{xy}} , take the derivative in both axes, one at a time.
A common spline is the natural cubic spline. A cubic spline has degree 3 with continuity C 2, i.e. the values and first and second derivatives are continuous. Natural means that the second derivatives of the spline polynomials are zero at the endpoints of the interval of interpolation.
In computer graphics, the centripetal Catmull–Rom spline is a variant form of the Catmull–Rom spline, originally formulated by Edwin Catmull and Raphael Rom, [1] which can be evaluated using a recursive algorithm proposed by Barry and Goldman. [2]