Synopsis

#include <boost/math/interpolators/makima.hpp>

namespace boost::math::interpolators {

template <class RandomAccessContainer>
class makima
{
public:

    using Real = RandomAccessContainer::value_type;

    makima(RandomAccessContainer&& abscissas, RandomAccessContainer&& ordinates,
           Real left_endpoint_derivative = std::numeric_limits<Real>::quiet_NaN(),
           Real right_endpoint_derivative = std::numeric_limits<Real>::quiet_NaN());

    Real operator()(Real x) const;

    Real prime(Real x) const;

    void push_back(Real x, Real y);

    friend std::ostream& operator<<(std::ostream & os, const makima & m);
};

} // namespaces

Modified Akima Interpolation

The modified Akima interpolant takes non-equispaced data and interpolates between them via cubic Hermite polynomials whose slopes are chosen by a modification of a geometric construction proposed by Akima. The modification is given by Cosmin Ionita and agrees with Matlab's version. The interpolant is C¹ and evaluation has 𝑶(log(N)) complexity. This is faster than barycentric rational interpolation, but also less smooth. An example usage is as follows:

std::vector<double> x{1, 5, 9 , 12};
std::vector<double> y{8,17, 4, -3};
using boost::math::interpolators::makima;
auto spline = makima(std::move(x), std::move(y));
// evaluate at a point:
double z = spline(3.4);
// evaluate derivative at a point:
double zprime = spline.prime(3.4);

Periodically, it is helpful to see what data the interpolator has, and the slopes it has chosen. This can be achieved via

std::cout << spline << "\n";

Note that the interpolator is pimpl'd, so that copying the class is cheap, and hence it can be shared between threads. (The call operator and .prime() are threadsafe.)

One unique aspect of this interpolator is that it can be updated in constant time. Hence we can use boost::circular_buffer to do real-time interpolation:

#include <boost/circular_buffer.hpp>
...
boost::circular_buffer<double> initial_x{1,2,3,4};
boost::circular_buffer<double> initial_y{4,5,6,7};
auto circular_akima = makima(std::move(initial_x), std::move(initial_y));
// interpolate via call operation:
double y = circular_akima(3.5);
// add new data:
circular_akima.push_back(5, 8);
// interpolat at 4.5:
y = circular_akima(4.5);

The modified Akima spline compared to the cubic B-spline. The modified Akima spline oscillates less than the cubic spline, but has less smoothness and is not exact on quadratic polynomials.

Complexity and Performance

The complexity and performance is identical to that of the cubic Hermite interpolator, since this object simply constructs derivatives and forwards the data to cubic_hermite.hpp.