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#### Polynomial and Rational Function Evaluation

##### synopsis

    #include <boost/math/tools/rational.hpp>

    // Polynomials:
    template <std::size_t N, class T, class V>
    V evaluate_polynomial(const T(&poly)[N], const V& val);

    template <std::size_t N, class T, class V>
    V evaluate_polynomial(const boost::array<T,N>& poly, const V& val);

    template <class T, class U>
    U evaluate_polynomial(const T* poly, U z, std::size_t count);

    // Even polynomials:
    template <std::size_t N, class T, class V>
    V evaluate_even_polynomial(const T(&poly)[N], const V& z);

    template <std::size_t N, class T, class V>
    V evaluate_even_polynomial(const boost::array<T,N>& poly, const V& z);

    template <class T, class U>
    U evaluate_even_polynomial(const T* poly, U z, std::size_t count);

    // Odd polynomials
    template <std::size_t N, class T, class V>
    V evaluate_odd_polynomial(const T(&a)[N], const V& z);

    template <std::size_t N, class T, class V>
    V evaluate_odd_polynomial(const boost::array<T,N>& a, const V& z);

    template <class T, class U>
    U evaluate_odd_polynomial(const T* poly, U z, std::size_t count);

    // Rational Functions:
    template <std::size_t N, class T, class V>
    V evaluate_rational(const T(&a)[N], const T(&b)[N], const V& z);

    template <std::size_t N, class T, class V>
    V evaluate_rational(const boost::array<T,N>& a, const boost::array<T,N>& b, const V& z);

    template <class T, class U, class V>
    V evaluate_rational(const T* num, const U* denom, V z, unsigned count);

##### Description

Each of the functions come in three variants: a pair of overloaded functions where the order of the polynomial or rational function is evaluated at compile time, and an overload that accepts a runtime variable for the size of the coefficient array. Generally speaking, compile time evaluation of the array size results in better type safety, is less prone to programmer errors, and may result in better optimised code. The polynomial evaluation functions in particular, are specialised for various array sizes, allowing for loop unrolling, and one hopes, optimal inline expansion.

    template <std::size_t N, class T, class V>
    V evaluate_polynomial(const T(&poly)[N], const V& val);

    template <std::size_t N, class T, class V>
    V evaluate_polynomial(const boost::array<T,N>& poly, const V& val);

    template <class T, class U>
    U evaluate_polynomial(const T* poly, U z, std::size_t count);

Evaluates the polynomial described by the coefficients stored in poly.

If the size of the array is specified at runtime, then the polynomial most have order count-1 with count coefficients. Otherwise it has order N-1 with N coefficients.

Coefficients should be stored such that the coefficients for the xi terms are in poly[i].

The types of the coefficients and of variable z may differ as long as *poly is convertible to type U. This allows, for example, for the coefficient table to be a table of integers if this is appropriate.

    template <std::size_t N, class T, class V>
    V evaluate_even_polynomial(const T(&poly)[N], const V& z);

    template <std::size_t N, class T, class V>
    V evaluate_even_polynomial(const boost::array<T,N>& poly, const V& z);

    template <class T, class U>
    U evaluate_even_polynomial(const T* poly, U z, std::size_t count);

As above, but evaluates an even polynomial: one where all the powers of z are even numbers. Equivalent to calling `evaluate_polynomial(poly, z*z, count)`.

    template <std::size_t N, class T, class V>
    V evaluate_odd_polynomial(const T(&a)[N], const V& z);

    template <std::size_t N, class T, class V>
    V evaluate_odd_polynomial(const boost::array<T,N>& a, const V& z);

    template <class T, class U>
    U evaluate_odd_polynomial(const T* poly, U z, std::size_t count);

As above but evaluates a polynomial where all the powers are odd numbers. Equivalent to `evaluate_polynomial(poly+1, z*z, count-1) * z + poly[0]`.

    template <std::size_t N, class T, class U, class V>
    V evaluate_rational(const T(&num)[N], const U(&denom)[N], const V& z);

    template <std::size_t N, class T, class U, class V>
    V evaluate_rational(const boost::array<T,N>& num, const boost::array<U,N>& denom, const V& z);

    template <class T, class U, class V>
    V evaluate_rational(const T* num, const U* denom, V z, unsigned count);

Evaluates the rational function (the ratio of two polynomials) described by the coefficients stored in num and demom.

If the size of the array is specified at runtime then both polynomials most have order count-1 with count coefficients. Otherwise both polynomials have order N-1 with N coefficients.

Array num describes the numerator, and demon the denominator.

Coefficients should be stored such that the coefficients for the xi terms are in num[i] and denom[i].

The types of the coefficients and of variable v may differ as long as *num and *denom are convertible to type V. This allows, for example, for one or both of the coefficient tables to be a table of integers if this is appropriate.

These functions are designed to safely evaluate the result, even when the value z is very large. As such they do not take advantage of compile time array sizes to make any optimisations. These functions are best reserved for situations where z may be large: if you can be sure that numerical overflow will not occur then polynomial evaluation with compile-time array sizes may offer slightly better performance.

##### Implementation

Polynomials are evaluated by Horners method. If the array size is known at compile time then the functions dispatch to size-specific implementations that unroll the evaluation loop.

Rational evaluation is by Horners method: with the two polynomials being evaluated in parallel to make the most of the processors floating-point pipeline. If v is greater than one, then the polynomials are evaluated in reverse order as polynomials in 1/v: this avoids unnecessary numerical overflow when the coefficients are large.

Both the polynomial and rational function evaluation algorithms can be tuned using various configuration macros to provide optimal performance for a particular combination of compiler and platform. This includes support for second-order Horner's methods. The various options are documented here. However, the performance benefits to be gained from these are marginal on most current hardware, consequently it's best to run the performance test application before changing the default settings.