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 //  Copyright John Maddock 2006-7, 2013-20.
 //  Copyright Paul A. Bristow 2007, 2013-14.
 //  Copyright Nikhar Agrawal 2013-14
 //  Copyright Christopher Kormanyos 2013-14, 2020
 
 //  Use, modification and distribution are subject to 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)
 
 #ifndef BOOST_MATH_SF_GAMMA_HPP
 #define BOOST_MATH_SF_GAMMA_HPP
 
 #ifdef _MSC_VER
 #pragma once
 #endif
 
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/fraction.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/promotion.hpp>
 #include <boost/math/tools/assert.hpp>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/special_functions/trunc.hpp>
 #include <boost/math/special_functions/powm1.hpp>
 #include <boost/math/special_functions/sqrt1pm1.hpp>
 #include <boost/math/special_functions/lanczos.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
 #include <boost/math/special_functions/detail/igamma_large.hpp>
 #include <boost/math/special_functions/detail/unchecked_factorial.hpp>
 #include <boost/math/special_functions/detail/lgamma_small.hpp>
 #include <boost/math/special_functions/bernoulli.hpp>
 #include <boost/math/special_functions/polygamma.hpp>
 
 #include <cmath>
 #include <algorithm>
 #include <type_traits>
 
 #ifdef _MSC_VER
 # pragma warning(push)
 # pragma warning(disable: 4702) // unreachable code (return after domain_error throw).
 # pragma warning(disable: 4127) // conditional expression is constant.
 # pragma warning(disable: 4100) // unreferenced formal parameter.
 # pragma warning(disable: 6326) // potential comparison of a constant with another constant
 // Several variables made comments,
 // but some difficulty as whether referenced on not may depend on macro values.
 // So to be safe, 4100 warnings suppressed.
 // TODO - revisit this?
 #endif
 
 namespace boost{ namespace math{
 
 namespace detail{
 
 template <class T>
 inline bool is_odd(T v, const std::true_type&)
 {
    int i = static_cast<int>(v);
    return i&1;
 }
 template <class T>
 inline bool is_odd(T v, const std::false_type&)
 {
    // Oh dear can't cast T to int!
    BOOST_MATH_STD_USING
    T modulus = v - 2 * floor(v/2);
    return static_cast<bool>(modulus != 0);
 }
 template <class T>
 inline bool is_odd(T v)
 {
    return is_odd(v, ::std::is_convertible<T, int>());
 }
 
 template <class T>
 T sinpx(T z)
 {
    // Ad hoc function calculates x * sin(pi * x),
    // taking extra care near when x is near a whole number.
    BOOST_MATH_STD_USING
    int sign = 1;
    if(z < 0)
    {
       z = -z;
    }
    T fl = floor(z);
    T dist;
    if(is_odd(fl))
    {
       fl += 1;
       dist = fl - z;
       sign = -sign;
    }
    else
    {
       dist = z - fl;
    }
    BOOST_MATH_ASSERT(fl >= 0);
    if(dist > T(0.5))
       dist = 1 - dist;
    T result = sin(dist*boost::math::constants::pi<T>());
    return sign*z*result;
 } // template <class T> T sinpx(T z)
 //
 // tgamma(z), with Lanczos support:
 //
 template <class T, class Policy, class Lanczos>
 T gamma_imp(T z, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
 
    T result = 1;
 
 #ifdef BOOST_MATH_INSTRUMENT
    static bool b = false;
    if(!b)
    {
       std::cout << "tgamma_imp called with " << typeid(z).name() << " " << typeid(l).name() << std::endl;
       b = true;
    }
 #endif
    static const char* function = "boost::math::tgamma<%1%>(%1%)";
 
    if(z <= 0)
    {
       if(floor(z) == z)
          return policies::raise_pole_error<T>(function, "Evaluation of tgamma at a negative integer %1%.", z, pol);
       if(z <= -20)
       {
          result = gamma_imp(T(-z), pol, l) * sinpx(z);
          BOOST_MATH_INSTRUMENT_VARIABLE(result);
          if((fabs(result) < 1) && (tools::max_value<T>() * fabs(result) < boost::math::constants::pi<T>()))
             return -boost::math::sign(result) * policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
          result = -boost::math::constants::pi<T>() / result;
          if(result == 0)
             return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
          if((boost::math::fpclassify)(result) == (int)FP_SUBNORMAL)
             return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", result, pol);
          BOOST_MATH_INSTRUMENT_VARIABLE(result);
          return result;
       }
 
       // shift z to > 1:
       while(z < 0)
       {
          result /= z;
          z += 1;
       }
    }
    BOOST_MATH_INSTRUMENT_VARIABLE(result);
    if((floor(z) == z) && (z < max_factorial<T>::value))
    {
       result *= unchecked_factorial<T>(itrunc(z, pol) - 1);
       BOOST_MATH_INSTRUMENT_VARIABLE(result);
    }
    else if (z < tools::root_epsilon<T>())
    {
       if (z < 1 / tools::max_value<T>())
          result = policies::raise_overflow_error<T>(function, nullptr, pol);
       result *= 1 / z - constants::euler<T>();
    }
    else
    {
       result *= Lanczos::lanczos_sum(z);
       T zgh = (z + static_cast<T>(Lanczos::g()) - boost::math::constants::half<T>());
       T lzgh = log(zgh);
       BOOST_MATH_INSTRUMENT_VARIABLE(result);
       BOOST_MATH_INSTRUMENT_VARIABLE(tools::log_max_value<T>());
       if(z * lzgh > tools::log_max_value<T>())
       {
          // we're going to overflow unless this is done with care:
          BOOST_MATH_INSTRUMENT_VARIABLE(zgh);
          if(lzgh * z / 2 > tools::log_max_value<T>())
             return boost::math::sign(result) * policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
          T hp = pow(zgh, T((z / 2) - T(0.25)));
          BOOST_MATH_INSTRUMENT_VARIABLE(hp);
          result *= hp / exp(zgh);
          BOOST_MATH_INSTRUMENT_VARIABLE(result);
          if(tools::max_value<T>() / hp < result)
             return boost::math::sign(result) * policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
          result *= hp;
          BOOST_MATH_INSTRUMENT_VARIABLE(result);
       }
       else
       {
          BOOST_MATH_INSTRUMENT_VARIABLE(zgh);
          BOOST_MATH_INSTRUMENT_VARIABLE(pow(zgh, T(z - boost::math::constants::half<T>())));
          BOOST_MATH_INSTRUMENT_VARIABLE(exp(zgh));
          result *= pow(zgh, T(z - boost::math::constants::half<T>())) / exp(zgh);
          BOOST_MATH_INSTRUMENT_VARIABLE(result);
       }
    }
    return result;
 }
 //
 // lgamma(z) with Lanczos support:
 //
 template <class T, class Policy, class Lanczos>
 T lgamma_imp(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
 {
 #ifdef BOOST_MATH_INSTRUMENT
    static bool b = false;
    if(!b)
    {
       std::cout << "lgamma_imp called with " << typeid(z).name() << " " << typeid(l).name() << std::endl;
       b = true;
    }
 #endif
 
    BOOST_MATH_STD_USING
 
    static const char* function = "boost::math::lgamma<%1%>(%1%)";
 
    T result = 0;
    int sresult = 1;
    if(z <= -tools::root_epsilon<T>())
    {
       // reflection formula:
       if(floor(z) == z)
          return policies::raise_pole_error<T>(function, "Evaluation of lgamma at a negative integer %1%.", z, pol);
 
       T t = sinpx(z);
       z = -z;
       if(t < 0)
       {
          t = -t;
       }
       else
       {
          sresult = -sresult;
       }
       result = log(boost::math::constants::pi<T>()) - lgamma_imp(z, pol, l) - log(t);
    }
    else if (z < tools::root_epsilon<T>())
    {
       if (0 == z)
          return policies::raise_pole_error<T>(function, "Evaluation of lgamma at %1%.", z, pol);
       if (4 * fabs(z) < tools::epsilon<T>())
          result = -log(fabs(z));
       else
          result = log(fabs(1 / z - constants::euler<T>()));
       if (z < 0)
          sresult = -1;
    }
    else if(z < 15)
    {
       typedef typename policies::precision<T, Policy>::type precision_type;
       typedef std::integral_constant<int,
          precision_type::value <= 0 ? 0 :
          precision_type::value <= 64 ? 64 :
          precision_type::value <= 113 ? 113 : 0
       > tag_type;
 
       result = lgamma_small_imp<T>(z, T(z - 1), T(z - 2), tag_type(), pol, l);
    }
    else if((z >= 3) && (z < 100) && (std::numeric_limits<T>::max_exponent >= 1024))
    {
       // taking the log of tgamma reduces the error, no danger of overflow here:
       result = log(gamma_imp(z, pol, l));
    }
    else
    {
       // regular evaluation:
       T zgh = static_cast<T>(z + T(Lanczos::g()) - boost::math::constants::half<T>());
       result = log(zgh) - 1;
       result *= z - 0.5f;
       //
       // Only add on the lanczos sum part if we're going to need it:
       //
       if(result * tools::epsilon<T>() < 20)
          result += log(Lanczos::lanczos_sum_expG_scaled(z));
    }
 
    if(sign)
       *sign = sresult;
    return result;
 }
 
 //
 // Incomplete gamma functions follow:
 //
 template <class T>
 struct upper_incomplete_gamma_fract
 {
 private:
    T z, a;
    int k;
 public:
    typedef std::pair<T,T> result_type;
 
    upper_incomplete_gamma_fract(T a1, T z1)
       : z(z1-a1+1), a(a1), k(0)
    {
    }
 
    result_type operator()()
    {
       ++k;
       z += 2;
       return result_type(k * (a - k), z);
    }
 };
 
 template <class T>
 inline T upper_gamma_fraction(T a, T z, T eps)
 {
    // Multiply result by z^a * e^-z to get the full
    // upper incomplete integral.  Divide by tgamma(z)
    // to normalise.
    upper_incomplete_gamma_fract<T> f(a, z);
    return 1 / (z - a + 1 + boost::math::tools::continued_fraction_a(f, eps));
 }
 
 template <class T>
 struct lower_incomplete_gamma_series
 {
 private:
    T a, z, result;
 public:
    typedef T result_type;
    lower_incomplete_gamma_series(T a1, T z1) : a(a1), z(z1), result(1){}
 
    T operator()()
    {
       T r = result;
       a += 1;
       result *= z/a;
       return r;
    }
 };
 
 template <class T, class Policy>
 inline T lower_gamma_series(T a, T z, const Policy& pol, T init_value = 0)
 {
    // Multiply result by ((z^a) * (e^-z) / a) to get the full
    // lower incomplete integral. Then divide by tgamma(a)
    // to get the normalised value.
    lower_incomplete_gamma_series<T> s(a, z);
    std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
    T factor = policies::get_epsilon<T, Policy>();
    T result = boost::math::tools::sum_series(s, factor, max_iter, init_value);
    policies::check_series_iterations<T>("boost::math::detail::lower_gamma_series<%1%>(%1%)", max_iter, pol);
    return result;
 }
 
 //
 // Fully generic tgamma and lgamma use Stirling's approximation
 // with Bernoulli numbers.
 //
 template<class T>
 std::size_t highest_bernoulli_index()
 {
    const float digits10_of_type = (std::numeric_limits<T>::is_specialized
                                       ? static_cast<float>(std::numeric_limits<T>::digits10)
                                       : static_cast<float>(boost::math::tools::digits<T>() * 0.301F));
 
    // Find the high index n for Bn to produce the desired precision in Stirling's calculation.
    return static_cast<std::size_t>(18.0F + (0.6F * digits10_of_type));
 }
 
 template<class T>
 int minimum_argument_for_bernoulli_recursion()
 {
    BOOST_MATH_STD_USING
 
    const float digits10_of_type = (std::numeric_limits<T>::is_specialized
                                     ? (float) std::numeric_limits<T>::digits10
                                     : (float) (boost::math::tools::digits<T>() * 0.301F));
 
    int min_arg = (int) (digits10_of_type * 1.7F);
 
    if(digits10_of_type < 50.0F)
    {
       // The following code sequence has been modified
       // within the context of issue 396.
 
       // The calculation of the test-variable limit has now
       // been protected against overflow/underflow dangers.
 
       // The previous line looked like this and did, in fact,
       // underflow ldexp when using certain multiprecision types.
 
       // const float limit = std::ceil(std::pow(1.0f / std::ldexp(1.0f, 1-boost::math::tools::digits<T>()), 1.0f / 20.0f));
 
       // The new safe version of the limit check is now here.
       const float d2_minus_one = ((digits10_of_type / 0.301F) - 1.0F);
       const float limit        = ceil(exp((d2_minus_one * log(2.0F)) / 20.0F));
 
       min_arg = (int) ((std::min)(digits10_of_type * 1.7F, limit));
    }
 
    return min_arg;
 }
 
 template <class T, class Policy>
 T scaled_tgamma_no_lanczos(const T& z, const Policy& pol, bool islog = false)
 {
    BOOST_MATH_STD_USING
    //
    // Calculates tgamma(z) / (z/e)^z
    // Requires that our argument is large enough for Sterling's approximation to hold.
    // Used internally when combining gamma's of similar magnitude without logarithms.
    //
    BOOST_MATH_ASSERT(minimum_argument_for_bernoulli_recursion<T>() <= z);
 
    // Perform the Bernoulli series expansion of Stirling's approximation.
 
    const std::size_t number_of_bernoullis_b2n = policies::get_max_series_iterations<Policy>();
 
    T one_over_x_pow_two_n_minus_one = 1 / z;
    const T one_over_x2 = one_over_x_pow_two_n_minus_one * one_over_x_pow_two_n_minus_one;
    T sum = (boost::math::bernoulli_b2n<T>(1) / 2) * one_over_x_pow_two_n_minus_one;
    const T target_epsilon_to_break_loop = sum * boost::math::tools::epsilon<T>();
    const T half_ln_two_pi_over_z = sqrt(boost::math::constants::two_pi<T>() / z);
    T last_term = 2 * sum;
 
    for (std::size_t n = 2U;; ++n)
    {
       one_over_x_pow_two_n_minus_one *= one_over_x2;
 
       const std::size_t n2 = static_cast<std::size_t>(n * 2U);
 
       const T term = (boost::math::bernoulli_b2n<T>(static_cast<int>(n)) * one_over_x_pow_two_n_minus_one) / (n2 * (n2 - 1U));
 
       if ((n >= 3U) && (abs(term) < target_epsilon_to_break_loop))
       {
          // We have reached the desired precision in Stirling's expansion.
          // Adding additional terms to the sum of this divergent asymptotic
          // expansion will not improve the result.
 
          // Break from the loop.
          break;
       }
       if (n > number_of_bernoullis_b2n)
          return policies::raise_evaluation_error("scaled_tgamma_no_lanczos<%1%>()", "Exceeded maximum series iterations without reaching convergence, best approximation was %1%", T(exp(sum) * half_ln_two_pi_over_z), pol);
 
       sum += term;
 
       // Sanity check for divergence:
       T fterm = fabs(term);
       if(fterm > last_term)
          return policies::raise_evaluation_error("scaled_tgamma_no_lanczos<%1%>()", "Series became divergent without reaching convergence, best approximation was %1%", T(exp(sum) * half_ln_two_pi_over_z), pol);
       last_term = fterm;
    }
 
    // Complete Stirling's approximation.
    T scaled_gamma_value = islog ? T(sum + log(half_ln_two_pi_over_z)) : T(exp(sum) * half_ln_two_pi_over_z);
    return scaled_gamma_value;
 }
 
 // Forward declaration of the lgamma_imp template specialization.
 template <class T, class Policy>
 T lgamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&, int* sign = nullptr);
 
 template <class T, class Policy>
 T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&)
 {
    BOOST_MATH_STD_USING
 
    static const char* function = "boost::math::tgamma<%1%>(%1%)";
 
    // Check if the argument of tgamma is identically zero.
    const bool is_at_zero = (z == 0);
 
    if((boost::math::isnan)(z) || (is_at_zero) || ((boost::math::isinf)(z) && (z < 0)))
       return policies::raise_domain_error<T>(function, "Evaluation of tgamma at %1%.", z, pol);
 
    const bool b_neg = (z < 0);
 
    const bool floor_of_z_is_equal_to_z = (floor(z) == z);
 
    // Special case handling of small factorials:
    if((!b_neg) && floor_of_z_is_equal_to_z && (z < boost::math::max_factorial<T>::value))
    {
       return boost::math::unchecked_factorial<T>(itrunc(z) - 1);
    }
 
    // Make a local, unsigned copy of the input argument.
    T zz((!b_neg) ? z : -z);
 
    // Special case for ultra-small z:
    if(zz < tools::cbrt_epsilon<T>())
    {
       const T a0(1);
       const T a1(boost::math::constants::euler<T>());
       const T six_euler_squared((boost::math::constants::euler<T>() * boost::math::constants::euler<T>()) * 6);
       const T a2((six_euler_squared -  boost::math::constants::pi_sqr<T>()) / 12);
 
       const T inverse_tgamma_series = z * ((a2 * z + a1) * z + a0);
 
       return 1 / inverse_tgamma_series;
    }
 
    // Scale the argument up for the calculation of lgamma,
    // and use downward recursion later for the final result.
    const int min_arg_for_recursion = minimum_argument_for_bernoulli_recursion<T>();
 
    int n_recur;
 
    if(zz < min_arg_for_recursion)
    {
       n_recur = boost::math::itrunc(min_arg_for_recursion - zz) + 1;
 
       zz += n_recur;
    }
    else
    {
       n_recur = 0;
    }
    if (!n_recur)
    {
       if (zz > tools::log_max_value<T>())
          return policies::raise_overflow_error<T>(function, nullptr, pol);
       if (log(zz) * zz / 2 > tools::log_max_value<T>())
          return policies::raise_overflow_error<T>(function, nullptr, pol);
    }
    T gamma_value = scaled_tgamma_no_lanczos(zz, pol);
    T power_term = pow(zz, zz / 2);
    T exp_term = exp(-zz);
    gamma_value *= (power_term * exp_term);
    if(!n_recur && (tools::max_value<T>() / power_term < gamma_value))
       return policies::raise_overflow_error<T>(function, nullptr, pol);
    gamma_value *= power_term;
 
    // Rescale the result using downward recursion if necessary.
    if(n_recur)
    {
       // The order of divides is important, if we keep subtracting 1 from zz
       // we DO NOT get back to z (cancellation error).  Further if z < epsilon
       // we would end up dividing by zero.  Also in order to prevent spurious
       // overflow with the first division, we must save dividing by |z| till last,
       // so the optimal order of divides is z+1, z+2, z+3...z+n_recur-1,z.
       zz = fabs(z) + 1;
       for(int k = 1; k < n_recur; ++k)
       {
          gamma_value /= zz;
          zz += 1;
       }
       gamma_value /= fabs(z);
    }
 
    // Return the result, accounting for possible negative arguments.
    if(b_neg)
    {
       // Provide special error analysis for:
       // * arguments in the neighborhood of a negative integer
       // * arguments exactly equal to a negative integer.
 
       // Check if the argument of tgamma is exactly equal to a negative integer.
       if(floor_of_z_is_equal_to_z)
          return policies::raise_pole_error<T>(function, "Evaluation of tgamma at a negative integer %1%.", z, pol);
 
       gamma_value *= sinpx(z);
 
       BOOST_MATH_INSTRUMENT_VARIABLE(gamma_value);
 
       const bool result_is_too_large_to_represent = (   (abs(gamma_value) < 1)
                                                      && ((tools::max_value<T>() * abs(gamma_value)) < boost::math::constants::pi<T>()));
 
       if(result_is_too_large_to_represent)
          return policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
 
       gamma_value = -boost::math::constants::pi<T>() / gamma_value;
       BOOST_MATH_INSTRUMENT_VARIABLE(gamma_value);
 
       if(gamma_value == 0)
          return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
 
       if((boost::math::fpclassify)(gamma_value) == static_cast<int>(FP_SUBNORMAL))
          return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", gamma_value, pol);
    }
 
    return gamma_value;
 }
 
 template <class T, class Policy>
 inline T log_gamma_near_1(const T& z, Policy const& pol)
 {
    //
    // This is for the multiprecision case where there is
    // no lanczos support, use a taylor series at z = 1,
    // see https://www.wolframalpha.com/input/?i=taylor+series+lgamma(x)+at+x+%3D+1
    //
    BOOST_MATH_STD_USING // ADL of std names
 
    BOOST_MATH_ASSERT(fabs(z) < 1);
 
    T result = -constants::euler<T>() * z;
 
    T power_term = z * z / 2;
    int n = 2;
    T term = 0;
 
    do
    {
       term = power_term * boost::math::polygamma(n - 1, T(1), pol);
       result += term;
       ++n;
       power_term *= z / n;
    } while (fabs(result) * tools::epsilon<T>() < fabs(term));
 
    return result;
 }
 
 template <class T, class Policy>
 T lgamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&, int* sign)
 {
    BOOST_MATH_STD_USING
 
    static const char* function = "boost::math::lgamma<%1%>(%1%)";
 
    // Check if the argument of lgamma is identically zero.
    const bool is_at_zero = (z == 0);
 
    if(is_at_zero)
       return policies::raise_domain_error<T>(function, "Evaluation of lgamma at zero %1%.", z, pol);
    if((boost::math::isnan)(z))
       return policies::raise_domain_error<T>(function, "Evaluation of lgamma at %1%.", z, pol);
    if((boost::math::isinf)(z))
       return policies::raise_overflow_error<T>(function, nullptr, pol);
 
    const bool b_neg = (z < 0);
 
    const bool floor_of_z_is_equal_to_z = (floor(z) == z);
 
    // Special case handling of small factorials:
    if((!b_neg) && floor_of_z_is_equal_to_z && (z < boost::math::max_factorial<T>::value))
    {
       if (sign)
          *sign = 1;
       return log(boost::math::unchecked_factorial<T>(itrunc(z) - 1));
    }
 
    // Make a local, unsigned copy of the input argument.
    T zz((!b_neg) ? z : -z);
 
    const int min_arg_for_recursion = minimum_argument_for_bernoulli_recursion<T>();
 
    T log_gamma_value;
 
    if (zz < min_arg_for_recursion)
    {
       // Here we simply take the logarithm of tgamma(). This is somewhat
       // inefficient, but simple. The rationale is that the argument here
       // is relatively small and overflow is not expected to be likely.
       if (sign)
          * sign = 1;
       if(fabs(z - 1) < 0.25)
       {
          log_gamma_value = log_gamma_near_1(T(zz - 1), pol);
       }
       else if(fabs(z - 2) < 0.25)
       {
          log_gamma_value = log_gamma_near_1(T(zz - 2), pol) + log(zz - 1);
       }
       else if (z > -tools::root_epsilon<T>())
       {
          // Reflection formula may fail if z is very close to zero, let the series
          // expansion for tgamma close to zero do the work:
          if (sign)
             *sign = z < 0 ? -1 : 1;
          return log(abs(gamma_imp(z, pol, lanczos::undefined_lanczos())));
       }
       else
       {
          // No issue with spurious overflow in reflection formula,
          // just fall through to regular code:
          T g = gamma_imp(zz, pol, lanczos::undefined_lanczos());
          if (sign)
          {
             *sign = g < 0 ? -1 : 1;
          }
          log_gamma_value = log(abs(g));
       }
    }
    else
    {
       // Perform the Bernoulli series expansion of Stirling's approximation.
       T sum = scaled_tgamma_no_lanczos(zz, pol, true);
       log_gamma_value = zz * (log(zz) - 1) + sum;
    }
 
    int sign_of_result = 1;
 
    if(b_neg)
    {
       // Provide special error analysis if the argument is exactly
       // equal to a negative integer.
 
       // Check if the argument of lgamma is exactly equal to a negative integer.
       if(floor_of_z_is_equal_to_z)
          return policies::raise_pole_error<T>(function, "Evaluation of lgamma at a negative integer %1%.", z, pol);
 
       T t = sinpx(z);
 
       if(t < 0)
       {
          t = -t;
       }
       else
       {
          sign_of_result = -sign_of_result;
       }
 
       log_gamma_value = - log_gamma_value
                         + log(boost::math::constants::pi<T>())
                         - log(t);
    }
 
    if(sign != static_cast<int*>(nullptr)) { *sign = sign_of_result; }
 
    return log_gamma_value;
 }
 
 //
 // This helper calculates tgamma(dz+1)-1 without cancellation errors,
 // used by the upper incomplete gamma with z < 1:
 //
 template <class T, class Policy, class Lanczos>
 T tgammap1m1_imp(T dz, Policy const& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
 
    typedef typename policies::precision<T,Policy>::type precision_type;
 
    typedef std::integral_constant<int,
       precision_type::value <= 0 ? 0 :
       precision_type::value <= 64 ? 64 :
       precision_type::value <= 113 ? 113 : 0
    > tag_type;
 
    T result;
    if(dz < 0)
    {
       if(dz < T(-0.5))
       {
          // Best method is simply to subtract 1 from tgamma:
          result = boost::math::tgamma(1+dz, pol) - 1;
          BOOST_MATH_INSTRUMENT_CODE(result);
       }
       else
       {
          // Use expm1 on lgamma:
          result = boost::math::expm1(-boost::math::log1p(dz, pol)
             + lgamma_small_imp<T>(dz+2, dz + 1, dz, tag_type(), pol, l), pol);
          BOOST_MATH_INSTRUMENT_CODE(result);
       }
    }
    else
    {
       if(dz < 2)
       {
          // Use expm1 on lgamma:
          result = boost::math::expm1(lgamma_small_imp<T>(dz+1, dz, dz-1, tag_type(), pol, l), pol);
          BOOST_MATH_INSTRUMENT_CODE(result);
       }
       else
       {
          // Best method is simply to subtract 1 from tgamma:
          result = boost::math::tgamma(1+dz, pol) - 1;
          BOOST_MATH_INSTRUMENT_CODE(result);
       }
    }
 
    return result;
 }
 
 template <class T, class Policy>
 inline T tgammap1m1_imp(T z, Policy const& pol,
                  const ::boost::math::lanczos::undefined_lanczos&)
 {
    BOOST_MATH_STD_USING // ADL of std names
 
    if(fabs(z) < T(0.55))
    {
       return boost::math::expm1(log_gamma_near_1(z, pol));
    }
    return boost::math::expm1(boost::math::lgamma(1 + z, pol));
 }
 
 //
 // Series representation for upper fraction when z is small:
 //
 template <class T>
 struct small_gamma2_series
 {
    typedef T result_type;
 
    small_gamma2_series(T a_, T x_) : result(-x_), x(-x_), apn(a_+1), n(1){}
 
    T operator()()
    {
       T r = result / (apn);
       result *= x;
       result /= ++n;
       apn += 1;
       return r;
    }
 
 private:
    T result, x, apn;
    int n;
 };
 //
 // calculate power term prefix (z^a)(e^-z) used in the non-normalised
 // incomplete gammas:
 //
 template <class T, class Policy>
 T full_igamma_prefix(T a, T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
    T prefix;
    if (z > tools::max_value<T>())
       return 0;
    T alz = a * log(z);
 
    if(z >= 1)
    {
       if((alz < tools::log_max_value<T>()) && (-z > tools::log_min_value<T>()))
       {
          prefix = pow(z, a) * exp(-z);
       }
       else if(a >= 1)
       {
          prefix = pow(T(z / exp(z/a)), a);
       }
       else
       {
          prefix = exp(alz - z);
       }
    }
    else
    {
       if(alz > tools::log_min_value<T>())
       {
          prefix = pow(z, a) * exp(-z);
       }
       else if(z/a < tools::log_max_value<T>())
       {
          prefix = pow(T(z / exp(z/a)), a);
       }
       else
       {
          prefix = exp(alz - z);
       }
    }
    //
    // This error handling isn't very good: it happens after the fact
    // rather than before it...
    //
    if((boost::math::fpclassify)(prefix) == (int)FP_INFINITE)
       return policies::raise_overflow_error<T>("boost::math::detail::full_igamma_prefix<%1%>(%1%, %1%)", "Result of incomplete gamma function is too large to represent.", pol);
 
    return prefix;
 }
 //
 // Compute (z^a)(e^-z)/tgamma(a)
 // most if the error occurs in this function:
 //
 template <class T, class Policy, class Lanczos>
 T regularised_gamma_prefix(T a, T z, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
    if (z >= tools::max_value<T>())
       return 0;
    T agh = a + static_cast<T>(Lanczos::g()) - T(0.5);
    T prefix;
    T d = ((z - a) - static_cast<T>(Lanczos::g()) + T(0.5)) / agh;
 
    if(a < 1)
    {
       //
       // We have to treat a < 1 as a special case because our Lanczos
       // approximations are optimised against the factorials with a > 1,
       // and for high precision types especially (128-bit reals for example)
       // very small values of a can give rather erroneous results for gamma
       // unless we do this:
       //
       // TODO: is this still required?  Lanczos approx should be better now?
       //
       if((z <= tools::log_min_value<T>()) || (a < 1 / tools::max_value<T>()))
       {
          // Oh dear, have to use logs, should be free of cancellation errors though:
          return exp(a * log(z) - z - lgamma_imp(a, pol, l));
       }
       else
       {
          // direct calculation, no danger of overflow as gamma(a) < 1/a
          // for small a.
          return pow(z, a) * exp(-z) / gamma_imp(a, pol, l);
       }
    }
    else if((fabs(d*d*a) <= 100) && (a > 150))
    {
       // special case for large a and a ~ z.
       prefix = a * boost::math::log1pmx(d, pol) + z * static_cast<T>(0.5 - Lanczos::g()) / agh;
       prefix = exp(prefix);
    }
    else
    {
       //
       // general case.
       // direct computation is most accurate, but use various fallbacks
       // for different parts of the problem domain:
       //
       T alz = a * log(z / agh);
       T amz = a - z;
       if(((std::min)(alz, amz) <= tools::log_min_value<T>()) || ((std::max)(alz, amz) >= tools::log_max_value<T>()))
       {
          T amza = amz / a;
          if(((std::min)(alz, amz)/2 > tools::log_min_value<T>()) && ((std::max)(alz, amz)/2 < tools::log_max_value<T>()))
          {
             // compute square root of the result and then square it:
             T sq = pow(z / agh, a / 2) * exp(amz / 2);
             prefix = sq * sq;
          }
          else if(((std::min)(alz, amz)/4 > tools::log_min_value<T>()) && ((std::max)(alz, amz)/4 < tools::log_max_value<T>()) && (z > a))
          {
             // compute the 4th root of the result then square it twice:
             T sq = pow(z / agh, a / 4) * exp(amz / 4);
             prefix = sq * sq;
             prefix *= prefix;
          }
          else if((amza > tools::log_min_value<T>()) && (amza < tools::log_max_value<T>()))
          {
             prefix = pow(T((z * exp(amza)) / agh), a);
          }
          else
          {
             prefix = exp(alz + amz);
          }
       }
       else
       {
          prefix = pow(T(z / agh), a) * exp(amz);
       }
    }
    prefix *= sqrt(agh / boost::math::constants::e<T>()) / Lanczos::lanczos_sum_expG_scaled(a);
    return prefix;
 }
 //
 // And again, without Lanczos support:
 //
 template <class T, class Policy>
 T regularised_gamma_prefix(T a, T z, const Policy& pol, const lanczos::undefined_lanczos& l)
 {
    BOOST_MATH_STD_USING
 
    if((a < 1) && (z < 1))
    {
       // No overflow possible since the power terms tend to unity as a,z -> 0
       return pow(z, a) * exp(-z) / boost::math::tgamma(a, pol);
    }
    else if(a > minimum_argument_for_bernoulli_recursion<T>())
    {
       T scaled_gamma = scaled_tgamma_no_lanczos(a, pol);
       T power_term = pow(z / a, a / 2);
       T a_minus_z = a - z;
       if ((0 == power_term) || (fabs(a_minus_z) > tools::log_max_value<T>()))
       {
          // The result is probably zero, but we need to be sure:
          return exp(a * log(z / a) + a_minus_z - log(scaled_gamma));
       }
       return (power_term * exp(a_minus_z)) * (power_term / scaled_gamma);
    }
    else
    {
       //
       // Usual case is to calculate the prefix at a+shift and recurse down
       // to the value we want:
       //
       const int min_z = minimum_argument_for_bernoulli_recursion<T>();
       long shift = 1 + ltrunc(min_z - a);
       T result = regularised_gamma_prefix(T(a + shift), z, pol, l);
       if (result != 0)
       {
          for (long i = 0; i < shift; ++i)
          {
             result /= z;
             result *= a + i;
          }
          return result;
       }
       else
       {
          //
          // We failed, most probably we have z << 1, try again, this time
          // we calculate z^a e^-z / tgamma(a+shift), combining power terms
          // as we go.  And again recurse down to the result.
          //
          T scaled_gamma = scaled_tgamma_no_lanczos(T(a + shift), pol);
          T power_term_1 = pow(T(z / (a + shift)), a);
          T power_term_2 = pow(T(a + shift), T(-shift));
          T power_term_3 = exp(a + shift - z);
          if ((0 == power_term_1) || (0 == power_term_2) || (0 == power_term_3) || (fabs(a + shift - z) > tools::log_max_value<T>()))
          {
             // We have no test case that gets here, most likely the type T
             // has a high precision but low exponent range:
             return exp(a * log(z) - z - boost::math::lgamma(a, pol));
          }
          result = power_term_1 * power_term_2 * power_term_3 / scaled_gamma;
          for (long i = 0; i < shift; ++i)
          {
             result *= a + i;
          }
          return result;
       }
    }
 }
 //
 // Upper gamma fraction for very small a:
 //
 template <class T, class Policy>
 inline T tgamma_small_upper_part(T a, T x, const Policy& pol, T* pgam = 0, bool invert = false, T* pderivative = 0)
 {
    BOOST_MATH_STD_USING  // ADL of std functions.
    //
    // Compute the full upper fraction (Q) when a is very small:
    //
    T result;
    result = boost::math::tgamma1pm1(a, pol);
    if(pgam)
       *pgam = (result + 1) / a;
    T p = boost::math::powm1(x, a, pol);
    result -= p;
    result /= a;
    detail::small_gamma2_series<T> s(a, x);
    std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>() - 10;
    p += 1;
    if(pderivative)
       *pderivative = p / (*pgam * exp(x));
    T init_value = invert ? *pgam : 0;
    result = -p * tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter, (init_value - result) / p);
    policies::check_series_iterations<T>("boost::math::tgamma_small_upper_part<%1%>(%1%, %1%)", max_iter, pol);
    if(invert)
       result = -result;
    return result;
 }
 //
 // Upper gamma fraction for integer a:
 //
 template <class T, class Policy>
 inline T finite_gamma_q(T a, T x, Policy const& pol, T* pderivative = 0)
 {
    //
    // Calculates normalised Q when a is an integer:
    //
    BOOST_MATH_STD_USING
    T e = exp(-x);
    T sum = e;
    if(sum != 0)
    {
       T term = sum;
       for(unsigned n = 1; n < a; ++n)
       {
          term /= n;
          term *= x;
          sum += term;
       }
    }
    if(pderivative)
    {
       *pderivative = e * pow(x, a) / boost::math::unchecked_factorial<T>(itrunc(T(a - 1), pol));
    }
    return sum;
 }
 //
 // Upper gamma fraction for half integer a:
 //
 template <class T, class Policy>
 T finite_half_gamma_q(T a, T x, T* p_derivative, const Policy& pol)
 {
    //
    // Calculates normalised Q when a is a half-integer:
    //
    BOOST_MATH_STD_USING
    T e = boost::math::erfc(sqrt(x), pol);
    if((e != 0) && (a > 1))
    {
       T term = exp(-x) / sqrt(constants::pi<T>() * x);
       term *= x;
       static const T half = T(1) / 2;
       term /= half;
       T sum = term;
       for(unsigned n = 2; n < a; ++n)
       {
          term /= n - half;
          term *= x;
          sum += term;
       }
       e += sum;
       if(p_derivative)
       {
          *p_derivative = 0;
       }
    }
    else if(p_derivative)
    {
       // We'll be dividing by x later, so calculate derivative * x:
       *p_derivative = sqrt(x) * exp(-x) / constants::root_pi<T>();
    }
    return e;
 }
 //
 // Asymptotic approximation for large argument, see: https://dlmf.nist.gov/8.11#E2
 //
 template <class T>
 struct incomplete_tgamma_large_x_series
 {
    typedef T result_type;
    incomplete_tgamma_large_x_series(const T& a, const T& x)
       : a_poch(a - 1), z(x), term(1) {}
    T operator()()
    {
       T result = term;
       term *= a_poch / z;
       a_poch -= 1;
       return result;
    }
    T a_poch, z, term;
 };
 
 template <class T, class Policy>
 T incomplete_tgamma_large_x(const T& a, const T& x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    incomplete_tgamma_large_x_series<T> s(a, x);
    std::uintmax_t max_iter = boost::math::policies::get_max_series_iterations<Policy>();
    T result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter);
    boost::math::policies::check_series_iterations<T>("boost::math::tgamma<%1%>(%1%,%1%)", max_iter, pol);
    return result;
 }
 
 
 //
 // Main incomplete gamma entry point, handles all four incomplete gamma's:
 //
 template <class T, class Policy>
 T gamma_incomplete_imp(T a, T x, bool normalised, bool invert,
                        const Policy& pol, T* p_derivative)
 {
    static const char* function = "boost::math::gamma_p<%1%>(%1%, %1%)";
    if(a <= 0)
       return policies::raise_domain_error<T>(function, "Argument a to the incomplete gamma function must be greater than zero (got a=%1%).", a, pol);
    if(x < 0)
       return policies::raise_domain_error<T>(function, "Argument x to the incomplete gamma function must be >= 0 (got x=%1%).", x, pol);
 
    BOOST_MATH_STD_USING
 
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
 
    T result = 0; // Just to avoid warning C4701: potentially uninitialized local variable 'result' used
 
    if(a >= max_factorial<T>::value && !normalised)
    {
       //
       // When we're computing the non-normalized incomplete gamma
       // and a is large the result is rather hard to compute unless
       // we use logs.  There are really two options - if x is a long
       // way from a in value then we can reliably use methods 2 and 4
       // below in logarithmic form and go straight to the result.
       // Otherwise we let the regularized gamma take the strain
       // (the result is unlikely to underflow in the central region anyway)
       // and combine with lgamma in the hopes that we get a finite result.
       //
       if(invert && (a * 4 < x))
       {
          // This is method 4 below, done in logs:
          result = a * log(x) - x;
          if(p_derivative)
             *p_derivative = exp(result);
          result += log(upper_gamma_fraction(a, x, policies::get_epsilon<T, Policy>()));
       }
       else if(!invert && (a > 4 * x))
       {
          // This is method 2 below, done in logs:
          result = a * log(x) - x;
          if(p_derivative)
             *p_derivative = exp(result);
          T init_value = 0;
          result += log(detail::lower_gamma_series(a, x, pol, init_value) / a);
       }
       else
       {
          result = gamma_incomplete_imp(a, x, true, invert, pol, p_derivative);
          if(result == 0)
          {
             if(invert)
             {
                // Try http://functions.wolfram.com/06.06.06.0039.01
                result = 1 + 1 / (12 * a) + 1 / (288 * a * a);
                result = log(result) - a + (a - 0.5f) * log(a) + log(boost::math::constants::root_two_pi<T>());
                if(p_derivative)
                   *p_derivative = exp(a * log(x) - x);
             }
             else
             {
                // This is method 2 below, done in logs, we're really outside the
                // range of this method, but since the result is almost certainly
                // infinite, we should probably be OK:
                result = a * log(x) - x;
                if(p_derivative)
                   *p_derivative = exp(result);
                T init_value = 0;
                result += log(detail::lower_gamma_series(a, x, pol, init_value) / a);
             }
          }
          else
          {
             result = log(result) + boost::math::lgamma(a, pol);
          }
       }
       if(result > tools::log_max_value<T>())
          return policies::raise_overflow_error<T>(function, nullptr, pol);
       return exp(result);
    }
 
    BOOST_MATH_ASSERT((p_derivative == nullptr) || normalised);
 
    bool is_int, is_half_int;
    bool is_small_a = (a < 30) && (a <= x + 1) && (x < tools::log_max_value<T>());
    if(is_small_a)
    {
       T fa = floor(a);
       is_int = (fa == a);
       is_half_int = is_int ? false : (fabs(fa - a) == 0.5f);
    }
    else
    {
       is_int = is_half_int = false;
    }
 
    int eval_method;
 
    if(is_int && (x > 0.6))
    {
       // calculate Q via finite sum:
       invert = !invert;
       eval_method = 0;
    }
    else if(is_half_int && (x > 0.2))
    {
       // calculate Q via finite sum for half integer a:
       invert = !invert;
       eval_method = 1;
    }
    else if((x < tools::root_epsilon<T>()) && (a > 1))
    {
       eval_method = 6;
    }
    else if ((x > 1000) && ((a < x) || (fabs(a - 50) / x < 1)))
    {
       // calculate Q via asymptotic approximation:
       invert = !invert;
       eval_method = 7;
    }
    else if(x < T(0.5))
    {
       //
       // Changeover criterion chosen to give a changeover at Q ~ 0.33
       //
       if(T(-0.4) / log(x) < a)
       {
          eval_method = 2;
       }
       else
       {
          eval_method = 3;
       }
    }
    else if(x < T(1.1))
    {
       //
       // Changeover here occurs when P ~ 0.75 or Q ~ 0.25:
       //
       if(x * 0.75f < a)
       {
          eval_method = 2;
       }
       else
       {
          eval_method = 3;
       }
    }
    else
    {
       //
       // Begin by testing whether we're in the "bad" zone
       // where the result will be near 0.5 and the usual
       // series and continued fractions are slow to converge:
       //
       bool use_temme = false;
       if(normalised && std::numeric_limits<T>::is_specialized && (a > 20))
       {
          T sigma = fabs((x-a)/a);
          if((a > 200) && (policies::digits<T, Policy>() <= 113))
          {
             //
             // This limit is chosen so that we use Temme's expansion
             // only if the result would be larger than about 10^-6.
             // Below that the regular series and continued fractions
             // converge OK, and if we use Temme's method we get increasing
             // errors from the dominant erfc term as it's (inexact) argument
             // increases in magnitude.
             //
             if(20 / a > sigma * sigma)
                use_temme = true;
          }
          else if(policies::digits<T, Policy>() <= 64)
          {
             // Note in this zone we can't use Temme's expansion for
             // types longer than an 80-bit real:
             // it would require too many terms in the polynomials.
             if(sigma < 0.4)
                use_temme = true;
          }
       }
       if(use_temme)
       {
          eval_method = 5;
       }
       else
       {
          //
          // Regular case where the result will not be too close to 0.5.
          //
          // Changeover here occurs at P ~ Q ~ 0.5
          // Note that series computation of P is about x2 faster than continued fraction
          // calculation of Q, so try and use the CF only when really necessary, especially
          // for small x.
          //
          if(x - (1 / (3 * x)) < a)
          {
             eval_method = 2;
          }
          else
          {
             eval_method = 4;
             invert = !invert;
          }
       }
    }
 
    switch(eval_method)
    {
    case 0:
       {
          result = finite_gamma_q(a, x, pol, p_derivative);
          if(!normalised)
             result *= boost::math::tgamma(a, pol);
          break;
       }
    case 1:
       {
          result = finite_half_gamma_q(a, x, p_derivative, pol);
          if(!normalised)
             result *= boost::math::tgamma(a, pol);
          if(p_derivative && (*p_derivative == 0))
             *p_derivative = regularised_gamma_prefix(a, x, pol, lanczos_type());
          break;
       }
    case 2:
       {
          // Compute P:
          result = normalised ? regularised_gamma_prefix(a, x, pol, lanczos_type()) : full_igamma_prefix(a, x, pol);
          if(p_derivative)
             *p_derivative = result;
          if(result != 0)
          {
             //
             // If we're going to be inverting the result then we can
             // reduce the number of series evaluations by quite
             // a few iterations if we set an initial value for the
             // series sum based on what we'll end up subtracting it from
             // at the end.
             // Have to be careful though that this optimization doesn't
             // lead to spurious numeric overflow.  Note that the
             // scary/expensive overflow checks below are more often
             // than not bypassed in practice for "sensible" input
             // values:
             //
             T init_value = 0;
             bool optimised_invert = false;
             if(invert)
             {
                init_value = (normalised ? 1 : boost::math::tgamma(a, pol));
                if(normalised || (result >= 1) || (tools::max_value<T>() * result > init_value))
                {
                   init_value /= result;
                   if(normalised || (a < 1) || (tools::max_value<T>() / a > init_value))
                   {
                      init_value *= -a;
                      optimised_invert = true;
                   }
                   else
                      init_value = 0;
                }
                else
                   init_value = 0;
             }
             result *= detail::lower_gamma_series(a, x, pol, init_value) / a;
             if(optimised_invert)
             {
                invert = false;
                result = -result;
             }
          }
          break;
       }
    case 3:
       {
          // Compute Q:
          invert = !invert;
          T g;
          result = tgamma_small_upper_part(a, x, pol, &g, invert, p_derivative);
          invert = false;
          if(normalised)
             result /= g;
          break;
       }
    case 4:
       {
          // Compute Q:
          result = normalised ? regularised_gamma_prefix(a, x, pol, lanczos_type()) : full_igamma_prefix(a, x, pol);
          if(p_derivative)
             *p_derivative = result;
          if(result != 0)
             result *= upper_gamma_fraction(a, x, policies::get_epsilon<T, Policy>());
          break;
       }
    case 5:
       {
          //
          // Use compile time dispatch to the appropriate
          // Temme asymptotic expansion.  This may be dead code
          // if T does not have numeric limits support, or has
          // too many digits for the most precise version of
          // these expansions, in that case we'll be calling
          // an empty function.
          //
          typedef typename policies::precision<T, Policy>::type precision_type;
 
          typedef std::integral_constant<int,
             precision_type::value <= 0 ? 0 :
             precision_type::value <= 53 ? 53 :
             precision_type::value <= 64 ? 64 :
             precision_type::value <= 113 ? 113 : 0
          > tag_type;
 
          result = igamma_temme_large(a, x, pol, static_cast<tag_type const*>(nullptr));
          if(x >= a)
             invert = !invert;
          if(p_derivative)
             *p_derivative = regularised_gamma_prefix(a, x, pol, lanczos_type());
          break;
       }
    case 6:
       {
          // x is so small that P is necessarily very small too,
          // use http://functions.wolfram.com/GammaBetaErf/GammaRegularized/06/01/05/01/01/
          if(!normalised)
             result = pow(x, a) / (a);
          else
          {
 #ifndef BOOST_NO_EXCEPTIONS
             try
             {
 #endif
                result = pow(x, a) / boost::math::tgamma(a + 1, pol);
 #ifndef BOOST_NO_EXCEPTIONS
             }
             catch (const std::overflow_error&)
             {
                result = 0;
             }
 #endif
          }
          result *= 1 - a * x / (a + 1);
          if (p_derivative)
             *p_derivative = regularised_gamma_prefix(a, x, pol, lanczos_type());
          break;
       }
    case 7:
    {
       // x is large,
       // Compute Q:
       result = normalised ? regularised_gamma_prefix(a, x, pol, lanczos_type()) : full_igamma_prefix(a, x, pol);
       if (p_derivative)
          *p_derivative = result;
       result /= x;
       if (result != 0)
          result *= incomplete_tgamma_large_x(a, x, pol);
       break;
    }
    }
 
    if(normalised && (result > 1))
       result = 1;
    if(invert)
    {
       T gam = normalised ? 1 : boost::math::tgamma(a, pol);
       result = gam - result;
    }
    if(p_derivative)
    {
       //
       // Need to convert prefix term to derivative:
       //
       if((x < 1) && (tools::max_value<T>() * x < *p_derivative))
       {
          // overflow, just return an arbitrarily large value:
          *p_derivative = tools::max_value<T>() / 2;
       }
 
       *p_derivative /= x;
    }
 
    return result;
 }
 
 //
 // Ratios of two gamma functions:
 //
 template <class T, class Policy, class Lanczos>
 T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
    if(z < tools::epsilon<T>())
    {
       //
       // We get spurious numeric overflow unless we're very careful, this
       // can occur either inside Lanczos::lanczos_sum(z) or in the
       // final combination of terms, to avoid this, split the product up
       // into 2 (or 3) parts:
       //
       // G(z) / G(L) = 1 / (z * G(L)) ; z < eps, L = z + delta = delta
       //    z * G(L) = z * G(lim) * (G(L)/G(lim)) ; lim = largest factorial
       //
       if(boost::math::max_factorial<T>::value < delta)
       {
          T ratio = tgamma_delta_ratio_imp_lanczos(delta, T(boost::math::max_factorial<T>::value - delta), pol, l);
          ratio *= z;
          ratio *= boost::math::unchecked_factorial<T>(boost::math::max_factorial<T>::value - 1);
          return 1 / ratio;
       }
       else
       {
          return 1 / (z * boost::math::tgamma(z + delta, pol));
       }
    }
    T zgh = static_cast<T>(z + T(Lanczos::g()) - constants::half<T>());
    T result;
    if(z + delta == z)
    {
       if (fabs(delta / zgh) < boost::math::tools::epsilon<T>())
       {
          // We have:
          // result = exp((constants::half<T>() - z) * boost::math::log1p(delta / zgh, pol));
          // 0.5 - z == -z
          // log1p(delta / zgh) = delta / zgh = delta / z
          // multiplying we get -delta.
          result = exp(-delta);
       }
       else
          // from the pow formula below... but this may actually be wrong, we just can't really calculate it :(
          result = 1;
    }
    else
    {
       if(fabs(delta) < 10)
       {
          result = exp((constants::half<T>() - z) * boost::math::log1p(delta / zgh, pol));
       }
       else
       {
          result = pow(T(zgh / (zgh + delta)), T(z - constants::half<T>()));
       }
       // Split the calculation up to avoid spurious overflow:
       result *= Lanczos::lanczos_sum(z) / Lanczos::lanczos_sum(T(z + delta));
    }
    result *= pow(T(constants::e<T>() / (zgh + delta)), delta);
    return result;
 }
 //
 // And again without Lanczos support this time:
 //
 template <class T, class Policy>
 T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const lanczos::undefined_lanczos& l)
 {
    BOOST_MATH_STD_USING
 
    //
    // We adjust z and delta so that both z and z+delta are large enough for
    // Sterling's approximation to hold.  We can then calculate the ratio
    // for the adjusted values, and rescale back down to z and z+delta.
    //
    // Get the required shifts first:
    //
    long numerator_shift = 0;
    long denominator_shift = 0;
    const int min_z = minimum_argument_for_bernoulli_recursion<T>();
 
    if (min_z > z)
       numerator_shift = 1 + ltrunc(min_z - z);
    if (min_z > z + delta)
       denominator_shift = 1 + ltrunc(min_z - z - delta);
    //
    // If the shifts are zero, then we can just combine scaled tgamma's
    // and combine the remaining terms:
    //
    if (numerator_shift == 0 && denominator_shift == 0)
    {
       T scaled_tgamma_num = scaled_tgamma_no_lanczos(z, pol);
       T scaled_tgamma_denom = scaled_tgamma_no_lanczos(T(z + delta), pol);
       T result = scaled_tgamma_num / scaled_tgamma_denom;
       result *= exp(z * boost::math::log1p(-delta / (z + delta), pol)) * pow(T((delta + z) / constants::e<T>()), -delta);
       return result;
    }
    //
    // We're going to have to rescale first, get the adjusted z and delta values,
    // plus the ratio for the adjusted values:
    //
    T zz = z + numerator_shift;
    T dd = delta - (numerator_shift - denominator_shift);
    T ratio = tgamma_delta_ratio_imp_lanczos(zz, dd, pol, l);
    //
    // Use gamma recurrence relations to get back to the original
    // z and z+delta:
    //
    for (long long i = 0; i < numerator_shift; ++i)
    {
       ratio /= (z + i);
       if (i < denominator_shift)
          ratio *= (z + delta + i);
    }
    for (long long i = numerator_shift; i < denominator_shift; ++i)
    {
       ratio *= (z + delta + i);
    }
    return ratio;
 }
 
 template <class T, class Policy>
 T tgamma_delta_ratio_imp(T z, T delta, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
    if((z <= 0) || (z + delta <= 0))
    {
       // This isn't very sophisticated, or accurate, but it does work:
       return boost::math::tgamma(z, pol) / boost::math::tgamma(z + delta, pol);
    }
 
    if(floor(delta) == delta)
    {
       if(floor(z) == z)
       {
          //
          // Both z and delta are integers, see if we can just use table lookup
          // of the factorials to get the result:
          //
          if((z <= max_factorial<T>::value) && (z + delta <= max_factorial<T>::value))
          {
             return unchecked_factorial<T>((unsigned)itrunc(z, pol) - 1) / unchecked_factorial<T>((unsigned)itrunc(T(z + delta), pol) - 1);
          }
       }
       if(fabs(delta) < 20)
       {
          //
          // delta is a small integer, we can use a finite product:
          //
          if(delta == 0)
             return 1;
          if(delta < 0)
          {
             z -= 1;
             T result = z;
             while(0 != (delta += 1))
             {
                z -= 1;
                result *= z;
             }
             return result;
          }
          else
          {
             T result = 1 / z;
             while(0 != (delta -= 1))
             {
                z += 1;
                result /= z;
             }
             return result;
          }
       }
    }
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
    return tgamma_delta_ratio_imp_lanczos(z, delta, pol, lanczos_type());
 }
 
 template <class T, class Policy>
 T tgamma_ratio_imp(T x, T y, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
    if((x <= 0) || (boost::math::isinf)(x))
       return policies::raise_domain_error<T>("boost::math::tgamma_ratio<%1%>(%1%, %1%)", "Gamma function ratios only implemented for positive arguments (got a=%1%).", x, pol);
    if((y <= 0) || (boost::math::isinf)(y))
       return policies::raise_domain_error<T>("boost::math::tgamma_ratio<%1%>(%1%, %1%)", "Gamma function ratios only implemented for positive arguments (got b=%1%).", y, pol);
 
    if(x <= tools::min_value<T>())
    {
       // Special case for denorms...Ugh.
       T shift = ldexp(T(1), tools::digits<T>());
       return shift * tgamma_ratio_imp(T(x * shift), y, pol);
    }
 
    if((x < max_factorial<T>::value) && (y < max_factorial<T>::value))
    {
       // Rather than subtracting values, lets just call the gamma functions directly:
       return boost::math::tgamma(x, pol) / boost::math::tgamma(y, pol);
    }
    T prefix = 1;
    if(x < 1)
    {
       if(y < 2 * max_factorial<T>::value)
       {
          // We need to sidestep on x as well, otherwise we'll underflow
          // before we get to factor in the prefix term:
          prefix /= x;
          x += 1;
          while(y >=  max_factorial<T>::value)
          {
             y -= 1;
             prefix /= y;
          }
          return prefix * boost::math::tgamma(x, pol) / boost::math::tgamma(y, pol);
       }
       //
       // result is almost certainly going to underflow to zero, try logs just in case:
       //
       return exp(boost::math::lgamma(x, pol) - boost::math::lgamma(y, pol));
    }
    if(y < 1)
    {
       if(x < 2 * max_factorial<T>::value)
       {
          // We need to sidestep on y as well, otherwise we'll overflow
          // before we get to factor in the prefix term:
          prefix *= y;
          y += 1;
          while(x >= max_factorial<T>::value)
          {
             x -= 1;
             prefix *= x;
          }
          return prefix * boost::math::tgamma(x, pol) / boost::math::tgamma(y, pol);
       }
       //
       // Result will almost certainly overflow, try logs just in case:
       //
       return exp(boost::math::lgamma(x, pol) - boost::math::lgamma(y, pol));
    }
    //
    // Regular case, x and y both large and similar in magnitude:
    //
    return boost::math::tgamma_delta_ratio(x, y - x, pol);
 }
 
 template <class T, class Policy>
 T gamma_p_derivative_imp(T a, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    //
    // Usual error checks first:
    //
    if(a <= 0)
       return policies::raise_domain_error<T>("boost::math::gamma_p_derivative<%1%>(%1%, %1%)", "Argument a to the incomplete gamma function must be greater than zero (got a=%1%).", a, pol);
    if(x < 0)
       return policies::raise_domain_error<T>("boost::math::gamma_p_derivative<%1%>(%1%, %1%)", "Argument x to the incomplete gamma function must be >= 0 (got x=%1%).", x, pol);
    //
    // Now special cases:
    //
    if(x == 0)
    {
       return (a > 1) ? 0 :
          (a == 1) ? 1 : policies::raise_overflow_error<T>("boost::math::gamma_p_derivative<%1%>(%1%, %1%)", nullptr, pol);
    }
    //
    // Normal case:
    //
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
    T f1 = detail::regularised_gamma_prefix(a, x, pol, lanczos_type());
    if((x < 1) && (tools::max_value<T>() * x < f1))
    {
       // overflow:
       return policies::raise_overflow_error<T>("boost::math::gamma_p_derivative<%1%>(%1%, %1%)", nullptr, pol);
    }
    if(f1 == 0)
    {
       // Underflow in calculation, use logs instead:
       f1 = a * log(x) - x - lgamma(a, pol) - log(x);
       f1 = exp(f1);
    }
    else
       f1 /= x;
 
    return f1;
 }
 
 template <class T, class Policy>
 inline typename tools::promote_args<T>::type
    tgamma(T z, const Policy& /* pol */, const std::true_type)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::gamma_imp(static_cast<value_type>(z), forwarding_policy(), evaluation_type()), "boost::math::tgamma<%1%>(%1%)");
 }
 
 template <class T, class Policy>
 struct igamma_initializer
 {
    struct init
    {
       init()
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
 
          typedef std::integral_constant<int,
             precision_type::value <= 0 ? 0 :
             precision_type::value <= 53 ? 53 :
             precision_type::value <= 64 ? 64 :
             precision_type::value <= 113 ? 113 : 0
          > tag_type;
 
          do_init(tag_type());
       }
       template <int N>
       static void do_init(const std::integral_constant<int, N>&)
       {
          // If std::numeric_limits<T>::digits is zero, we must not call
          // our initialization code here as the precision presumably
          // varies at runtime, and will not have been set yet.  Plus the
          // code requiring initialization isn't called when digits == 0.
          if(std::numeric_limits<T>::digits)
          {
             boost::math::gamma_p(static_cast<T>(400), static_cast<T>(400), Policy());
          }
       }
       static void do_init(const std::integral_constant<int, 53>&){}
       void force_instantiate()const{}
    };
    static const init initializer;
    static void force_instantiate()
    {
       initializer.force_instantiate();
    }
 };
 
 template <class T, class Policy>
 const typename igamma_initializer<T, Policy>::init igamma_initializer<T, Policy>::initializer;
 
 template <class T, class Policy>
 struct lgamma_initializer
 {
    struct init
    {
       init()
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
          typedef std::integral_constant<int,
             precision_type::value <= 0 ? 0 :
             precision_type::value <= 64 ? 64 :
             precision_type::value <= 113 ? 113 : 0
          > tag_type;
 
          do_init(tag_type());
       }
       static void do_init(const std::integral_constant<int, 64>&)
       {
          boost::math::lgamma(static_cast<T>(2.5), Policy());
          boost::math::lgamma(static_cast<T>(1.25), Policy());
          boost::math::lgamma(static_cast<T>(1.75), Policy());
       }
       static void do_init(const std::integral_constant<int, 113>&)
       {
          boost::math::lgamma(static_cast<T>(2.5), Policy());
          boost::math::lgamma(static_cast<T>(1.25), Policy());
          boost::math::lgamma(static_cast<T>(1.5), Policy());
          boost::math::lgamma(static_cast<T>(1.75), Policy());
       }
       static void do_init(const std::integral_constant<int, 0>&)
       {
       }
       void force_instantiate()const{}
    };
    static const init initializer;
    static void force_instantiate()
    {
       initializer.force_instantiate();
    }
 };
 
 template <class T, class Policy>
 const typename lgamma_initializer<T, Policy>::init lgamma_initializer<T, Policy>::initializer;
 
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z, const Policy&, const std::false_type)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef tools::promote_args_t<T1, T2> result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    // typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    igamma_initializer<value_type, forwarding_policy>::force_instantiate();
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(
       detail::gamma_incomplete_imp(static_cast<value_type>(a),
       static_cast<value_type>(z), false, true,
       forwarding_policy(), static_cast<value_type*>(nullptr)), "boost::math::tgamma<%1%>(%1%, %1%)");
 }
 
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z, const std::false_type& tag)
 {
    return tgamma(a, z, policies::policy<>(), tag);
 }
 
 
 } // namespace detail
 
 template <class T>
 inline typename tools::promote_args<T>::type
    tgamma(T z)
 {
    return tgamma(z, policies::policy<>());
 }
 
 template <class T, class Policy>
 inline typename tools::promote_args<T>::type
    lgamma(T z, int* sign, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    detail::lgamma_initializer<value_type, forwarding_policy>::force_instantiate();
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::lgamma_imp(static_cast<value_type>(z), forwarding_policy(), evaluation_type(), sign), "boost::math::lgamma<%1%>(%1%)");
 }
 
 template <class T>
 inline typename tools::promote_args<T>::type
    lgamma(T z, int* sign)
 {
    return lgamma(z, sign, policies::policy<>());
 }
 
 template <class T, class Policy>
 inline typename tools::promote_args<T>::type
    lgamma(T x, const Policy& pol)
 {
    return ::boost::math::lgamma(x, nullptr, pol);
 }
 
 template <class T>
 inline typename tools::promote_args<T>::type
    lgamma(T x)
 {
    return ::boost::math::lgamma(x, nullptr, policies::policy<>());
 }
 
 template <class T, class Policy>
 inline typename tools::promote_args<T>::type
    tgamma1pm1(T z, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    return policies::checked_narrowing_cast<typename std::remove_cv<result_type>::type, forwarding_policy>(detail::tgammap1m1_imp(static_cast<value_type>(z), forwarding_policy(), evaluation_type()), "boost::math::tgamma1pm1<%!%>(%1%)");
 }
 
 template <class T>
 inline typename tools::promote_args<T>::type
    tgamma1pm1(T z)
 {
    return tgamma1pm1(z, policies::policy<>());
 }
 
 //
 // Full upper incomplete gamma:
 //
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z)
 {
    //
    // Type T2 could be a policy object, or a value, select the
    // right overload based on T2:
    //
    using maybe_policy = typename policies::is_policy<T2>::type;
    using result_type = tools::promote_args_t<T1, T2>;
    return static_cast<result_type>(detail::tgamma(a, z, maybe_policy()));
 }
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z, const Policy& pol)
 {
    using result_type = tools::promote_args_t<T1, T2>;
    return static_cast<result_type>(detail::tgamma(a, z, pol, std::false_type()));
 }
 //
 // Full lower incomplete gamma:
 //
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    tgamma_lower(T1 a, T2 z, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef tools::promote_args_t<T1, T2> result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    // typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    detail::igamma_initializer<value_type, forwarding_policy>::force_instantiate();
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(
       detail::gamma_incomplete_imp(static_cast<value_type>(a),
       static_cast<value_type>(z), false, false,
       forwarding_policy(), static_cast<value_type*>(nullptr)), "tgamma_lower<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    tgamma_lower(T1 a, T2 z)
 {
    return tgamma_lower(a, z, policies::policy<>());
 }
 //
 // Regularised upper incomplete gamma:
 //
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    gamma_q(T1 a, T2 z, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef tools::promote_args_t<T1, T2> result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    // typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    detail::igamma_initializer<value_type, forwarding_policy>::force_instantiate();
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(
       detail::gamma_incomplete_imp(static_cast<value_type>(a),
       static_cast<value_type>(z), true, true,
       forwarding_policy(), static_cast<value_type*>(nullptr)), "gamma_q<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    gamma_q(T1 a, T2 z)
 {
    return gamma_q(a, z, policies::policy<>());
 }
 //
 // Regularised lower incomplete gamma:
 //
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    gamma_p(T1 a, T2 z, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef tools::promote_args_t<T1, T2> result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    // typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    detail::igamma_initializer<value_type, forwarding_policy>::force_instantiate();
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(
       detail::gamma_incomplete_imp(static_cast<value_type>(a),
       static_cast<value_type>(z), true, false,
       forwarding_policy(), static_cast<value_type*>(nullptr)), "gamma_p<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    gamma_p(T1 a, T2 z)
 {
    return gamma_p(a, z, policies::policy<>());
 }
 
 // ratios of gamma functions:
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    tgamma_delta_ratio(T1 z, T2 delta, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef tools::promote_args_t<T1, T2> result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::tgamma_delta_ratio_imp(static_cast<value_type>(z), static_cast<value_type>(delta), forwarding_policy()), "boost::math::tgamma_delta_ratio<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    tgamma_delta_ratio(T1 z, T2 delta)
 {
    return tgamma_delta_ratio(z, delta, policies::policy<>());
 }
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    tgamma_ratio(T1 a, T2 b, const Policy&)
 {
    typedef tools::promote_args_t<T1, T2> result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::tgamma_ratio_imp(static_cast<value_type>(a), static_cast<value_type>(b), forwarding_policy()), "boost::math::tgamma_delta_ratio<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    tgamma_ratio(T1 a, T2 b)
 {
    return tgamma_ratio(a, b, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
 inline tools::promote_args_t<T1, T2>
    gamma_p_derivative(T1 a, T2 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef tools::promote_args_t<T1, T2> result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::normalise<
       Policy,
       policies::promote_float<false>,
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::gamma_p_derivative_imp(static_cast<value_type>(a), static_cast<value_type>(x), forwarding_policy()), "boost::math::gamma_p_derivative<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
 inline tools::promote_args_t<T1, T2>
    gamma_p_derivative(T1 a, T2 x)
 {
    return gamma_p_derivative(a, x, policies::policy<>());
 }
 
 } // namespace math
 } // namespace boost
 
 #ifdef _MSC_VER
 # pragma warning(pop)
 #endif
 
 #include <boost/math/special_functions/detail/igamma_inverse.hpp>
 #include <boost/math/special_functions/detail/gamma_inva.hpp>
 #include <boost/math/special_functions/erf.hpp>
 
 #endif // BOOST_MATH_SF_GAMMA_HPP

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