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#### mpfr_float

`#include <boost/multiprecision/mpfr.hpp>`

    namespace boost{ namespace multiprecision{

    enum mpfr_allocation_type
    {
       allocate_stack,
       allocate_dynamic
    };

    template <unsigned Digits10, mpfr_allocation_type AllocateType = allocate_dynamic>
    class mpfr_float_backend;

    typedef number<mpfr_float_backend<50> >    mpfr_float_50;
    typedef number<mpfr_float_backend<100> >   mpfr_float_100;
    typedef number<mpfr_float_backend<500> >   mpfr_float_500;
    typedef number<mpfr_float_backend<1000> >  mpfr_float_1000;
    typedef number<mpfr_float_backend<0> >     mpfr_float;

    typedef number<mpfr_float_backend<50, allocate_stack> >    static_mpfr_float_50;
    typedef number<mpfr_float_backend<100, allocate_stack> >   static_mpfr_float_100;

    }} // namespaces

The `mpfr_float_backend` type is used in conjunction with `number`: It acts as a thin wrapper around the MPFR `mpfr_t` to provide an real-number type that is a drop-in replacement for the native C++ floating-point types, but with much greater precision.

Type `mpfr_float_backend` can be used at fixed precision by specifying a non-zero `Digits10` template parameter, or at variable precision by setting the template argument to zero. The typedefs mpfr_float_50, mpfr_float_100, mpfr_float_500, mpfr_float_1000 provide arithmetic types at 50, 100, 500 and 1000 decimal digits precision respectively. The typedef mpfr_float provides a variable precision type whose precision can be controlled via the `number`s member functions.

In addition the second template parameter lets you choose between dynamic allocation (the default, and uses MPFR's normal allocation routines), or stack allocation (where all the memory required for the underlying data types is stored within `mpfr_float_backend`). The latter option can result in significantly faster code, at the expense of growing the size of `mpfr_float_backend`. It can only be used at fixed precision, and should only be used for lower digit counts. Note that we can not guarantee that using `allocate_stack` won't cause any calls to mpfr's allocation routines, as mpfr may call these inside it's own code. The following table gives an idea of the performance tradeoff's at 50 decimal digits precision[2]:

Type | Bessel function evaluation, relative times
--- | ---
`number<mpfr_float_backend<50, allocate_static>, et_on>` | 1.0 (5.5s)
`number<mpfr_float_backend<50, allocate_static>, et_off>` | 1.05 (5.8s)
`number<mpfr_float_backend<50, allocate_dynamic>, et_on>` | 1.05 (5.8s)
`number<mpfr_float_backend<50, allocate_dynamic>, et_off>` | 1.16 (6.4s)

| Note
This type only provides `numeric_limits` support when the precision is fixed at compile time.

As well as the usual conversions from arithmetic and string types, instances of `number<mpfr_float_backend<N> >` are copy constructible and assignable from:

- The GMP native types `mpf_t`, `mpz_t`, `mpq_t`.
- The MPFR native type `mpfr_t`.
- The `number` wrappers around those types: `number<mpfr_float_backend<M> >`, `number<mpf_float<M> >`, `number<gmp_int>`, `number<gmp_rational>`.

It's also possible to access the underlying `mpfr_t` via the data() member function of `mpfr_float_backend`.

Things you should know when using this type:

- A default constructed `mpfr_float_backend` is set to a NaN (this is the default MPFR behavior).
- All operations use round to nearest.
- No changes are made to GMP or MPFR global settings, so this type can coexist with existing MPFR or GMP code.
- The code can equally use MPIR in place of GMP - indeed that is the preferred option on Win32.
- This backend supports rvalue-references and is move-aware, making instantiations of `number` on this backend move aware.
- Conversion from a string results in a `std::runtime_error` being thrown if the string can not be interpreted as a valid floating-point number.
- Division by zero results in an infinity.

###### MPFR example:

    #include <boost/multiprecision/mpfr.hpp>
    #include <boost/math/special_functions/gamma.hpp>
    #include <iostream>

    int main()
    {
       using namespace boost::multiprecision;

       // Operations at variable precision and no numeric_limits support:
       mpfr_float a = 2;
       mpfr_float::default_precision(1000);
       std::cout << mpfr_float::default_precision() << std::endl;
       std::cout << sqrt(a) << std::endl; // print root-2

       // Operations at fixed precision and full numeric_limits support:
       mpfr_float_100 b = 2;
       std::cout << std::numeric_limits<mpfr_float_100>::digits << std::endl;
       // We can use any C++ std lib function:
       std::cout << log(b) << std::endl; // print log(2)
       // We can also use any function from Boost.Math:
       std::cout << boost::math::tgamma(b) << std::endl;
       // These even work when the argument is an expression template:
       std::cout << boost::math::tgamma(b * b) << std::endl;

       // Access the underlying data:
       mpfr_t r;
       mpfr_init(r);
       mpfr_set(r, b.backend().data(), GMP_RNDN);
       mpfr_clear(r);
       return 0;
    }

[2] Compiled with VC++10 and /Ox, with MPFR-3.0.0 and MPIR-2.3.0