Interpolation and Approximation

CNLMath : Interpolation and Approximation

Functions

Cubic Spline Interpolation

Derivative end conditions, cub_spline_interp_e_cnd

Tension-Continuity-Bias Conditions, cub_spline_tcb

Cubic Spline Evaluation and Integration

Evaluation and differentiation, cub_spline_value

Spline Interpolation

One-dimensional interpolation, spline_interp

Knot sequence given interpolation data, spline_knots

Two-dimensional, tensor-product interpolation, spline_2d_interp

Spline Evaluation and Integration

One-dimensional evaluation and differentiation, spline_value

One-dimensional integration, spline_integral

Two-dimensional evaluation and differentiation, spline_2d_value

Two-dimensional integration, spline_2d_integral

Multi-dimensional

Multidimensional interpolation and differentiation, spline_nd_interp

Least-Squares Approximation and Smoothing

Splines with fixed knots, spline_least_squares

Tensor-product splines with fixed knots, spline_2d_least_squares

Cubic smoothing spline, cub_spline_smooth

Splines with constraints, spline_lsq_constrained

Smooth one-dimensional data by error detection, smooth_1d_data

Scattered Data Interpolation

Akima’s surface-fitting method, scattered_2d_interp

Scattered Data Least Squares

Fit using radial-basis functions, radial_scattered_fit

Evaluate radial-basis fit, radial_evaluate