[section:tgamma Gamma] [h4 Synopsis] `` #include `` namespace boost{ namespace math{ template ``__sf_result`` tgamma(T z); template ``__sf_result`` tgamma(T z, const ``__Policy``&); template ``__sf_result`` tgamma1pm1(T dz); template ``__sf_result`` tgamma1pm1(T dz, const ``__Policy``&); }} // namespaces [h4 Description] template ``__sf_result`` tgamma(T z); template ``__sf_result`` tgamma(T z, const ``__Policy``&); Returns the "true gamma" (hence name tgamma) of value z: [equation gamm1] [graph tgamma] [optional_policy] The return type of this function is computed using the __arg_promotion_rules: the result is `double` when T is an integer type, and T otherwise. template ``__sf_result`` tgamma1pm1(T dz); template ``__sf_result`` tgamma1pm1(T dz, const ``__Policy``&); Returns `tgamma(dz + 1) - 1`. Internally the implementation does not make use of the addition and subtraction implied by the definition, leading to accurate results even for very small `dz`. The return type of this function is computed using the __arg_promotion_rules: the result is `double` when T is an integer type, and T otherwise. [optional_policy] [h4 Accuracy] The following table shows the peak errors (in units of epsilon) found on various platforms with various floating point types, along with comparisons to other common libraries. Unless otherwise specified any floating point type that is narrower than the one shown will have __zero_error. [table_tgamma] [table_tgamma1pm1] The following error plot are based on an exhaustive search of the functions domain, MSVC-15.5 at `double` precision, and GCC-7.1/Ubuntu for `long double` and `__float128`. [graph tgamma__double] [graph tgamma__80_bit_long_double] [graph tgamma____float128] [h4 Testing] The gamma is relatively easy to test: factorials and half-integer factorials can be calculated exactly by other means and compared with the gamma function. In addition, some accuracy tests in known tricky areas were computed at high precision using the generic version of this function. The function `tgamma1pm1` is tested against values calculated very naively using the formula `tgamma(1+dz)-1` with a lanczos approximation accurate to around 100 decimal digits. [h4 Implementation] The generic version of the `tgamma` function is implemented Sterling's approximation for `lgamma` for large z: [equation gamma6] Following exponentiation, downward recursion is then used for small values of z. For types of known precision the __lanczos is used, a traits class `boost::math::lanczos::lanczos_traits` maps type T to an appropriate approximation. For z in the range -20 < z < 1 then recursion is used to shift to z > 1 via: [equation gamm3] For very small z, this helps to preserve the identity: [equation gamm4] For z < -20 the reflection formula: [equation gamm5] is used. Particular care has to be taken to evaluate the [^ z * sin([pi] * z)] part: a special routine is used to reduce z prior to multiplying by [pi] to ensure that the result in is the range [0, [pi]/2]. Without this an excessive amount of error occurs in this region (which is hard enough already, as the rate of change near a negative pole is /exceptionally/ high). Finally if the argument is a small integer then table lookup of the factorial is used. The function `tgamma1pm1` is implemented using rational approximations [jm_rationals] in the region `-0.5 < dz < 2`. These are the same approximations (and internal routines) that are used for __lgamma, and so aren't detailed further here. The result of the approximation is `log(tgamma(dz+1))` which can fed into __expm1 to give the desired result. Outside the range `-0.5 < dz < 2` then the naive formula `tgamma1pm1(dz) = tgamma(dz+1)-1` can be used directly. [endsect] [/section:tgamma The Gamma Function] [/ Copyright 2006 John Maddock and Paul A. Bristow. Distributed under the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt). ]