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ctx_mp.py

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+"""
+This module defines the mpf, mpc classes, and standard functions for
+operating with them.
+"""
+__docformat__ = 'plaintext'
+
+import functools
+
+import re
+
+from .ctx_base import StandardBaseContext
+
+from .libmp.backend import basestring, BACKEND
+
+from . import libmp
+
+from .libmp import (MPZ, MPZ_ZERO, MPZ_ONE, int_types, repr_dps,
+    round_floor, round_ceiling, dps_to_prec, round_nearest, prec_to_dps,
+    ComplexResult, to_pickable, from_pickable, normalize,
+    from_int, from_float, from_str, to_int, to_float, to_str,
+    from_rational, from_man_exp,
+    fone, fzero, finf, fninf, fnan,
+    mpf_abs, mpf_pos, mpf_neg, mpf_add, mpf_sub, mpf_mul, mpf_mul_int,
+    mpf_div, mpf_rdiv_int, mpf_pow_int, mpf_mod,
+    mpf_eq, mpf_cmp, mpf_lt, mpf_gt, mpf_le, mpf_ge,
+    mpf_hash, mpf_rand,
+    mpf_sum,
+    bitcount, to_fixed,
+    mpc_to_str,
+    mpc_to_complex, mpc_hash, mpc_pos, mpc_is_nonzero, mpc_neg, mpc_conjugate,
+    mpc_abs, mpc_add, mpc_add_mpf, mpc_sub, mpc_sub_mpf, mpc_mul, mpc_mul_mpf,
+    mpc_mul_int, mpc_div, mpc_div_mpf, mpc_pow, mpc_pow_mpf, mpc_pow_int,
+    mpc_mpf_div,
+    mpf_pow,
+    mpf_pi, mpf_degree, mpf_e, mpf_phi, mpf_ln2, mpf_ln10,
+    mpf_euler, mpf_catalan, mpf_apery, mpf_khinchin,
+    mpf_glaisher, mpf_twinprime, mpf_mertens,
+    int_types)
+
+from . import function_docs
+from . import rational
+
+new = object.__new__
+
+get_complex = re.compile(r'^\(?(?P<re>[\+\-]?\d*(\.\d*)?(e[\+\-]?\d+)?)??'
+                         r'(?P<im>[\+\-]?\d*(\.\d*)?(e[\+\-]?\d+)?j)?\)?$')
+
+if BACKEND == 'sage':
+    from sage.libs.mpmath.ext_main import Context as BaseMPContext
+    # pickle hack
+    import sage.libs.mpmath.ext_main as _mpf_module
+else:
+    from .ctx_mp_python import PythonMPContext as BaseMPContext
+    from . import ctx_mp_python as _mpf_module
+
+from .ctx_mp_python import _mpf, _mpc, mpnumeric
+
+class MPContext(BaseMPContext, StandardBaseContext):
+    """
+    Context for multiprecision arithmetic with a global precision.
+    """
+
+    def __init__(ctx):
+        BaseMPContext.__init__(ctx)
+        ctx.trap_complex = False
+        ctx.pretty = False
+        ctx.types = [ctx.mpf, ctx.mpc, ctx.constant]
+        ctx._mpq = rational.mpq
+        ctx.default()
+        StandardBaseContext.__init__(ctx)
+
+        ctx.mpq = rational.mpq
+        ctx.init_builtins()
+
+        ctx.hyp_summators = {}
+
+        ctx._init_aliases()
+
+        # XXX: automate
+        try:
+            ctx.bernoulli.im_func.func_doc = function_docs.bernoulli
+            ctx.primepi.im_func.func_doc = function_docs.primepi
+            ctx.psi.im_func.func_doc = function_docs.psi
+            ctx.atan2.im_func.func_doc = function_docs.atan2
+        except AttributeError:
+            # python 3
+            ctx.bernoulli.__func__.func_doc = function_docs.bernoulli
+            ctx.primepi.__func__.func_doc = function_docs.primepi
+            ctx.psi.__func__.func_doc = function_docs.psi
+            ctx.atan2.__func__.func_doc = function_docs.atan2
+
+        ctx.digamma.func_doc = function_docs.digamma
+        ctx.cospi.func_doc = function_docs.cospi
+        ctx.sinpi.func_doc = function_docs.sinpi
+
+    def init_builtins(ctx):
+
+        mpf = ctx.mpf
+        mpc = ctx.mpc
+
+        # Exact constants
+        ctx.one = ctx.make_mpf(fone)
+        ctx.zero = ctx.make_mpf(fzero)
+        ctx.j = ctx.make_mpc((fzero,fone))
+        ctx.inf = ctx.make_mpf(finf)
+        ctx.ninf = ctx.make_mpf(fninf)
+        ctx.nan = ctx.make_mpf(fnan)
+
+        eps = ctx.constant(lambda prec, rnd: (0, MPZ_ONE, 1-prec, 1),
+            "epsilon of working precision", "eps")
+        ctx.eps = eps
+
+        # Approximate constants
+        ctx.pi = ctx.constant(mpf_pi, "pi", "pi")
+        ctx.ln2 = ctx.constant(mpf_ln2, "ln(2)", "ln2")
+        ctx.ln10 = ctx.constant(mpf_ln10, "ln(10)", "ln10")
+        ctx.phi = ctx.constant(mpf_phi, "Golden ratio phi", "phi")
+        ctx.e = ctx.constant(mpf_e, "e = exp(1)", "e")
+        ctx.euler = ctx.constant(mpf_euler, "Euler's constant", "euler")
+        ctx.catalan = ctx.constant(mpf_catalan, "Catalan's constant", "catalan")
+        ctx.khinchin = ctx.constant(mpf_khinchin, "Khinchin's constant", "khinchin")
+        ctx.glaisher = ctx.constant(mpf_glaisher, "Glaisher's constant", "glaisher")
+        ctx.apery = ctx.constant(mpf_apery, "Apery's constant", "apery")
+        ctx.degree = ctx.constant(mpf_degree, "1 deg = pi / 180", "degree")
+        ctx.twinprime = ctx.constant(mpf_twinprime, "Twin prime constant", "twinprime")
+        ctx.mertens = ctx.constant(mpf_mertens, "Mertens' constant", "mertens")
+
+        # Standard functions
+        ctx.sqrt = ctx._wrap_libmp_function(libmp.mpf_sqrt, libmp.mpc_sqrt)
+        ctx.cbrt = ctx._wrap_libmp_function(libmp.mpf_cbrt, libmp.mpc_cbrt)
+        ctx.ln = ctx._wrap_libmp_function(libmp.mpf_log, libmp.mpc_log)
+        ctx.atan = ctx._wrap_libmp_function(libmp.mpf_atan, libmp.mpc_atan)
+        ctx.exp = ctx._wrap_libmp_function(libmp.mpf_exp, libmp.mpc_exp)
+        ctx.expj = ctx._wrap_libmp_function(libmp.mpf_expj, libmp.mpc_expj)
+        ctx.expjpi = ctx._wrap_libmp_function(libmp.mpf_expjpi, libmp.mpc_expjpi)
+        ctx.sin = ctx._wrap_libmp_function(libmp.mpf_sin, libmp.mpc_sin)
+        ctx.cos = ctx._wrap_libmp_function(libmp.mpf_cos, libmp.mpc_cos)
+        ctx.tan = ctx._wrap_libmp_function(libmp.mpf_tan, libmp.mpc_tan)
+        ctx.sinh = ctx._wrap_libmp_function(libmp.mpf_sinh, libmp.mpc_sinh)
+        ctx.cosh = ctx._wrap_libmp_function(libmp.mpf_cosh, libmp.mpc_cosh)
+        ctx.tanh = ctx._wrap_libmp_function(libmp.mpf_tanh, libmp.mpc_tanh)
+        ctx.asin = ctx._wrap_libmp_function(libmp.mpf_asin, libmp.mpc_asin)
+        ctx.acos = ctx._wrap_libmp_function(libmp.mpf_acos, libmp.mpc_acos)
+        ctx.atan = ctx._wrap_libmp_function(libmp.mpf_atan, libmp.mpc_atan)
+        ctx.asinh = ctx._wrap_libmp_function(libmp.mpf_asinh, libmp.mpc_asinh)
+        ctx.acosh = ctx._wrap_libmp_function(libmp.mpf_acosh, libmp.mpc_acosh)
+        ctx.atanh = ctx._wrap_libmp_function(libmp.mpf_atanh, libmp.mpc_atanh)
+        ctx.sinpi = ctx._wrap_libmp_function(libmp.mpf_sin_pi, libmp.mpc_sin_pi)
+        ctx.cospi = ctx._wrap_libmp_function(libmp.mpf_cos_pi, libmp.mpc_cos_pi)
+        ctx.floor = ctx._wrap_libmp_function(libmp.mpf_floor, libmp.mpc_floor)
+        ctx.ceil = ctx._wrap_libmp_function(libmp.mpf_ceil, libmp.mpc_ceil)
+        ctx.nint = ctx._wrap_libmp_function(libmp.mpf_nint, libmp.mpc_nint)
+        ctx.frac = ctx._wrap_libmp_function(libmp.mpf_frac, libmp.mpc_frac)
+        ctx.fib = ctx.fibonacci = ctx._wrap_libmp_function(libmp.mpf_fibonacci, libmp.mpc_fibonacci)
+
+        ctx.gamma = ctx._wrap_libmp_function(libmp.mpf_gamma, libmp.mpc_gamma)
+        ctx.rgamma = ctx._wrap_libmp_function(libmp.mpf_rgamma, libmp.mpc_rgamma)
+        ctx.loggamma = ctx._wrap_libmp_function(libmp.mpf_loggamma, libmp.mpc_loggamma)
+        ctx.fac = ctx.factorial = ctx._wrap_libmp_function(libmp.mpf_factorial, libmp.mpc_factorial)
+
+        ctx.digamma = ctx._wrap_libmp_function(libmp.mpf_psi0, libmp.mpc_psi0)
+        ctx.harmonic = ctx._wrap_libmp_function(libmp.mpf_harmonic, libmp.mpc_harmonic)
+        ctx.ei = ctx._wrap_libmp_function(libmp.mpf_ei, libmp.mpc_ei)
+        ctx.e1 = ctx._wrap_libmp_function(libmp.mpf_e1, libmp.mpc_e1)
+        ctx._ci = ctx._wrap_libmp_function(libmp.mpf_ci, libmp.mpc_ci)
+        ctx._si = ctx._wrap_libmp_function(libmp.mpf_si, libmp.mpc_si)
+        ctx.ellipk = ctx._wrap_libmp_function(libmp.mpf_ellipk, libmp.mpc_ellipk)
+        ctx._ellipe = ctx._wrap_libmp_function(libmp.mpf_ellipe, libmp.mpc_ellipe)
+        ctx.agm1 = ctx._wrap_libmp_function(libmp.mpf_agm1, libmp.mpc_agm1)
+        ctx._erf = ctx._wrap_libmp_function(libmp.mpf_erf, None)
+        ctx._erfc = ctx._wrap_libmp_function(libmp.mpf_erfc, None)
+        ctx._zeta = ctx._wrap_libmp_function(libmp.mpf_zeta, libmp.mpc_zeta)
+        ctx._altzeta = ctx._wrap_libmp_function(libmp.mpf_altzeta, libmp.mpc_altzeta)
+
+        # Faster versions
+        ctx.sqrt = getattr(ctx, "_sage_sqrt", ctx.sqrt)
+        ctx.exp = getattr(ctx, "_sage_exp", ctx.exp)
+        ctx.ln = getattr(ctx, "_sage_ln", ctx.ln)
+        ctx.cos = getattr(ctx, "_sage_cos", ctx.cos)
+        ctx.sin = getattr(ctx, "_sage_sin", ctx.sin)
+
+    def to_fixed(ctx, x, prec):
+        return x.to_fixed(prec)
+
+    def hypot(ctx, x, y):
+        r"""
+        Computes the Euclidean norm of the vector `(x, y)`, equal
+        to `\sqrt{x^2 + y^2}`. Both `x` and `y` must be real."""
+        x = ctx.convert(x)
+        y = ctx.convert(y)
+        return ctx.make_mpf(libmp.mpf_hypot(x._mpf_, y._mpf_, *ctx._prec_rounding))
+
+    def _gamma_upper_int(ctx, n, z):
+        n = int(ctx._re(n))
+        if n == 0:
+            return ctx.e1(z)
+        if not hasattr(z, '_mpf_'):
+            raise NotImplementedError
+        prec, rounding = ctx._prec_rounding
+        real, imag = libmp.mpf_expint(n, z._mpf_, prec, rounding, gamma=True)
+        if imag is None:
+            return ctx.make_mpf(real)
+        else:
+            return ctx.make_mpc((real, imag))
+
+    def _expint_int(ctx, n, z):
+        n = int(n)
+        if n == 1:
+            return ctx.e1(z)
+        if not hasattr(z, '_mpf_'):
+            raise NotImplementedError
+        prec, rounding = ctx._prec_rounding
+        real, imag = libmp.mpf_expint(n, z._mpf_, prec, rounding)
+        if imag is None:
+            return ctx.make_mpf(real)
+        else:
+            return ctx.make_mpc((real, imag))
+
+    def _nthroot(ctx, x, n):
+        if hasattr(x, '_mpf_'):
+            try:
+                return ctx.make_mpf(libmp.mpf_nthroot(x._mpf_, n, *ctx._prec_rounding))
+            except ComplexResult:
+                if ctx.trap_complex:
+                    raise
+                x = (x._mpf_, libmp.fzero)
+        else:
+            x = x._mpc_
+        return ctx.make_mpc(libmp.mpc_nthroot(x, n, *ctx._prec_rounding))
+
+    def _besselj(ctx, n, z):
+        prec, rounding = ctx._prec_rounding
+        if hasattr(z, '_mpf_'):
+            return ctx.make_mpf(libmp.mpf_besseljn(n, z._mpf_, prec, rounding))
+        elif hasattr(z, '_mpc_'):
+            return ctx.make_mpc(libmp.mpc_besseljn(n, z._mpc_, prec, rounding))
+
+    def _agm(ctx, a, b=1):
+        prec, rounding = ctx._prec_rounding
+        if hasattr(a, '_mpf_') and hasattr(b, '_mpf_'):
+            try:
+                v = libmp.mpf_agm(a._mpf_, b._mpf_, prec, rounding)
+                return ctx.make_mpf(v)
+            except ComplexResult:
+                pass
+        if hasattr(a, '_mpf_'): a = (a._mpf_, libmp.fzero)
+        else: a = a._mpc_
+        if hasattr(b, '_mpf_'): b = (b._mpf_, libmp.fzero)
+        else: b = b._mpc_
+        return ctx.make_mpc(libmp.mpc_agm(a, b, prec, rounding))
+
+    def bernoulli(ctx, n):
+        return ctx.make_mpf(libmp.mpf_bernoulli(int(n), *ctx._prec_rounding))
+
+    def _zeta_int(ctx, n):
+        return ctx.make_mpf(libmp.mpf_zeta_int(int(n), *ctx._prec_rounding))
+
+    def atan2(ctx, y, x):
+        x = ctx.convert(x)
+        y = ctx.convert(y)
+        return ctx.make_mpf(libmp.mpf_atan2(y._mpf_, x._mpf_, *ctx._prec_rounding))
+
+    def psi(ctx, m, z):
+        z = ctx.convert(z)
+        m = int(m)
+        if ctx._is_real_type(z):
+            return ctx.make_mpf(libmp.mpf_psi(m, z._mpf_, *ctx._prec_rounding))
+        else:
+            return ctx.make_mpc(libmp.mpc_psi(m, z._mpc_, *ctx._prec_rounding))
+
+    def cos_sin(ctx, x, **kwargs):
+        if type(x) not in ctx.types:
+            x = ctx.convert(x)
+        prec, rounding = ctx._parse_prec(kwargs)
+        if hasattr(x, '_mpf_'):
+            c, s = libmp.mpf_cos_sin(x._mpf_, prec, rounding)
+            return ctx.make_mpf(c), ctx.make_mpf(s)
+        elif hasattr(x, '_mpc_'):
+            c, s = libmp.mpc_cos_sin(x._mpc_, prec, rounding)
+            return ctx.make_mpc(c), ctx.make_mpc(s)
+        else:
+            return ctx.cos(x, **kwargs), ctx.sin(x, **kwargs)
+
+    def cospi_sinpi(ctx, x, **kwargs):
+        if type(x) not in ctx.types:
+            x = ctx.convert(x)
+        prec, rounding = ctx._parse_prec(kwargs)
+        if hasattr(x, '_mpf_'):
+            c, s = libmp.mpf_cos_sin_pi(x._mpf_, prec, rounding)
+            return ctx.make_mpf(c), ctx.make_mpf(s)
+        elif hasattr(x, '_mpc_'):
+            c, s = libmp.mpc_cos_sin_pi(x._mpc_, prec, rounding)
+            return ctx.make_mpc(c), ctx.make_mpc(s)
+        else:
+            return ctx.cos(x, **kwargs), ctx.sin(x, **kwargs)
+
+    def clone(ctx):
+        """
+        Create a copy of the context, with the same working precision.
+        """
+        a = ctx.__class__()
+        a.prec = ctx.prec
+        return a
+
+    # Several helper methods
+    # TODO: add more of these, make consistent, write docstrings, ...
+
+    def _is_real_type(ctx, x):
+        if hasattr(x, '_mpc_') or type(x) is complex:
+            return False
+        return True
+
+    def _is_complex_type(ctx, x):
+        if hasattr(x, '_mpc_') or type(x) is complex:
+            return True
+        return False
+
+    def isnan(ctx, x):
+        """
+        Return *True* if *x* is a NaN (not-a-number), or for a complex
+        number, whether either the real or complex part is NaN;
+        otherwise return *False*::
+
+            >>> from mpmath import *
+            >>> isnan(3.14)
+            False
+            >>> isnan(nan)
+            True
+            >>> isnan(mpc(3.14,2.72))
+            False
+            >>> isnan(mpc(3.14,nan))
+            True
+
+        """
+        if hasattr(x, "_mpf_"):
+            return x._mpf_ == fnan
+        if hasattr(x, "_mpc_"):
+            return fnan in x._mpc_
+        if isinstance(x, int_types) or isinstance(x, rational.mpq):
+            return False
+        x = ctx.convert(x)
+        if hasattr(x, '_mpf_') or hasattr(x, '_mpc_'):
+            return ctx.isnan(x)
+        raise TypeError("isnan() needs a number as input")
+
+    def isfinite(ctx, x):
+        """
+        Return *True* if *x* is a finite number, i.e. neither
+        an infinity or a NaN.
+
+            >>> from mpmath import *
+            >>> isfinite(inf)
+            False
+            >>> isfinite(-inf)
+            False
+            >>> isfinite(3)
+            True
+            >>> isfinite(nan)
+            False
+            >>> isfinite(3+4j)
+            True
+            >>> isfinite(mpc(3,inf))
+            False
+            >>> isfinite(mpc(nan,3))
+            False
+
+        """
+        if ctx.isinf(x) or ctx.isnan(x):
+            return False
+        return True
+
+    def isnpint(ctx, x):
+        """
+        Determine if *x* is a nonpositive integer.
+        """
+        if not x:
+            return True
+        if hasattr(x, '_mpf_'):
+            sign, man, exp, bc = x._mpf_
+            return sign and exp >= 0
+        if hasattr(x, '_mpc_'):
+            return not x.imag and ctx.isnpint(x.real)
+        if type(x) in int_types:
+            return x <= 0
+        if isinstance(x, ctx.mpq):
+            p, q = x._mpq_
+            if not p:
+                return True
+            return q == 1 and p <= 0
+        return ctx.isnpint(ctx.convert(x))
+
+    def __str__(ctx):
+        lines = ["Mpmath settings:",
+            ("  mp.prec = %s" % ctx.prec).ljust(30) + "[default: 53]",
+            ("  mp.dps = %s" % ctx.dps).ljust(30) + "[default: 15]",
+            ("  mp.trap_complex = %s" % ctx.trap_complex).ljust(30) + "[default: False]",
+        ]
+        return "\n".join(lines)
+
+    @property
+    def _repr_digits(ctx):
+        return repr_dps(ctx._prec)
+
+    @property
+    def _str_digits(ctx):
+        return ctx._dps
+
+    def extraprec(ctx, n, normalize_output=False):
+        """
+        The block
+
+            with extraprec(n):
+                <code>
+
+        increases the precision n bits, executes <code>, and then
+        restores the precision.
+
+        extraprec(n)(f) returns a decorated version of the function f
+        that increases the working precision by n bits before execution,
+        and restores the parent precision afterwards. With
+        normalize_output=True, it rounds the return value to the parent
+        precision.
+        """
+        return PrecisionManager(ctx, lambda p: p + n, None, normalize_output)
+
+    def extradps(ctx, n, normalize_output=False):
+        """
+        This function is analogous to extraprec (see documentation)
+        but changes the decimal precision instead of the number of bits.
+        """
+        return PrecisionManager(ctx, None, lambda d: d + n, normalize_output)
+
+    def workprec(ctx, n, normalize_output=False):
+        """
+        The block
+
+            with workprec(n):
+                <code>
+
+        sets the precision to n bits, executes <code>, and then restores
+        the precision.
+
+        workprec(n)(f) returns a decorated version of the function f
+        that sets the precision to n bits before execution,
+        and restores the precision afterwards. With normalize_output=True,
+        it rounds the return value to the parent precision.
+        """
+        return PrecisionManager(ctx, lambda p: n, None, normalize_output)
+
+    def workdps(ctx, n, normalize_output=False):
+        """
+        This function is analogous to workprec (see documentation)
+        but changes the decimal precision instead of the number of bits.
+        """
+        return PrecisionManager(ctx, None, lambda d: n, normalize_output)
+
+    def autoprec(ctx, f, maxprec=None, catch=(), verbose=False):
+        r"""
+        Return a wrapped copy of *f* that repeatedly evaluates *f*
+        with increasing precision until the result converges to the
+        full precision used at the point of the call.
+
+        This heuristically protects against rounding errors, at the cost of
+        roughly a 2x slowdown compared to manually setting the optimal
+        precision. This method can, however, easily be fooled if the results
+        from *f* depend "discontinuously" on the precision, for instance
+        if catastrophic cancellation can occur. Therefore, :func:`~mpmath.autoprec`
+        should be used judiciously.
+
+        **Examples**
+
+        Many functions are sensitive to perturbations of the input arguments.
+        If the arguments are decimal numbers, they may have to be converted
+        to binary at a much higher precision. If the amount of required
+        extra precision is unknown, :func:`~mpmath.autoprec` is convenient::
+
+            >>> from mpmath import *
+            >>> mp.dps = 15
+            >>> mp.pretty = True
+            >>> besselj(5, 125 * 10**28)    # Exact input
+            -8.03284785591801e-17
+            >>> besselj(5, '1.25e30')   # Bad
+            7.12954868316652e-16
+            >>> autoprec(besselj)(5, '1.25e30')   # Good
+            -8.03284785591801e-17
+
+        The following fails to converge because `\sin(\pi) = 0` whereas all
+        finite-precision approximations of `\pi` give nonzero values::
+
+            >>> autoprec(sin)(pi) # doctest: +IGNORE_EXCEPTION_DETAIL
+            Traceback (most recent call last):
+              ...
+            NoConvergence: autoprec: prec increased to 2910 without convergence
+
+        As the following example shows, :func:`~mpmath.autoprec` can protect against
+        cancellation, but is fooled by too severe cancellation::
+
+            >>> x = 1e-10
+            >>> exp(x)-1; expm1(x); autoprec(lambda t: exp(t)-1)(x)
+            1.00000008274037e-10
+            1.00000000005e-10
+            1.00000000005e-10
+            >>> x = 1e-50
+            >>> exp(x)-1; expm1(x); autoprec(lambda t: exp(t)-1)(x)
+            0.0
+            1.0e-50
+            0.0
+
+        With *catch*, an exception or list of exceptions to intercept
+        may be specified. The raised exception is interpreted
+        as signaling insufficient precision. This permits, for example,
+        evaluating a function where a too low precision results in a
+        division by zero::
+
+            >>> f = lambda x: 1/(exp(x)-1)
+            >>> f(1e-30)
+            Traceback (most recent call last):
+              ...
+            ZeroDivisionError
+            >>> autoprec(f, catch=ZeroDivisionError)(1e-30)
+            1.0e+30
+
+
+        """
+        def f_autoprec_wrapped(*args, **kwargs):
+            prec = ctx.prec
+            if maxprec is None:
+                maxprec2 = ctx._default_hyper_maxprec(prec)
+            else:
+                maxprec2 = maxprec
+            try:
+                ctx.prec = prec + 10
+                try:
+                    v1 = f(*args, **kwargs)
+                except catch:
+                    v1 = ctx.nan
+                prec2 = prec + 20
+                while 1:
+                    ctx.prec = prec2
+                    try:
+                        v2 = f(*args, **kwargs)
+                    except catch:
+                        v2 = ctx.nan
+                    if v1 == v2:
+                        break
+                    err = ctx.mag(v2-v1) - ctx.mag(v2)
+                    if err < (-prec):
+                        break
+                    if verbose:
+                        print("autoprec: target=%s, prec=%s, accuracy=%s" \
+                            % (prec, prec2, -err))
+                    v1 = v2
+                    if prec2 >= maxprec2:
+                        raise ctx.NoConvergence(\
+                        "autoprec: prec increased to %i without convergence"\
+                        % prec2)
+                    prec2 += int(prec2*2)
+                    prec2 = min(prec2, maxprec2)
+            finally:
+                ctx.prec = prec
+            return +v2
+        return f_autoprec_wrapped
+
+    def nstr(ctx, x, n=6, **kwargs):
+        """
+        Convert an ``mpf`` or ``mpc`` to a decimal string literal with *n*
+        significant digits. The small default value for *n* is chosen to
+        make this function useful for printing collections of numbers
+        (lists, matrices, etc).
+
+        If *x* is a list or tuple, :func:`~mpmath.nstr` is applied recursively
+        to each element. For unrecognized classes, :func:`~mpmath.nstr`
+        simply returns ``str(x)``.
+
+        The companion function :func:`~mpmath.nprint` prints the result
+        instead of returning it.
+
+        The keyword arguments *strip_zeros*, *min_fixed*, *max_fixed*
+        and *show_zero_exponent* are forwarded to :func:`~mpmath.libmp.to_str`.
+
+        The number will be printed in fixed-point format if the position
+        of the leading digit is strictly between min_fixed
+        (default = min(-dps/3,-5)) and max_fixed (default = dps).
+
+        To force fixed-point format always, set min_fixed = -inf,
+        max_fixed = +inf. To force floating-point format, set
+        min_fixed >= max_fixed.
+
+            >>> from mpmath import *
+            >>> nstr([+pi, ldexp(1,-500)])
+            '[3.14159, 3.05494e-151]'
+            >>> nprint([+pi, ldexp(1,-500)])
+            [3.14159, 3.05494e-151]
+            >>> nstr(mpf("5e-10"), 5)
+            '5.0e-10'
+            >>> nstr(mpf("5e-10"), 5, strip_zeros=False)
+            '5.0000e-10'
+            >>> nstr(mpf("5e-10"), 5, strip_zeros=False, min_fixed=-11)
+            '0.00000000050000'
+            >>> nstr(mpf(0), 5, show_zero_exponent=True)
+            '0.0e+0'
+
+        """
+        if isinstance(x, list):
+            return "[%s]" % (", ".join(ctx.nstr(c, n, **kwargs) for c in x))
+        if isinstance(x, tuple):
+            return "(%s)" % (", ".join(ctx.nstr(c, n, **kwargs) for c in x))
+        if hasattr(x, '_mpf_'):
+            return to_str(x._mpf_, n, **kwargs)
+        if hasattr(x, '_mpc_'):
+            return "(" + mpc_to_str(x._mpc_, n, **kwargs)  + ")"
+        if isinstance(x, basestring):
+            return repr(x)
+        if isinstance(x, ctx.matrix):
+            return x.__nstr__(n, **kwargs)
+        return str(x)
+
+    def _convert_fallback(ctx, x, strings):
+        if strings and isinstance(x, basestring):
+            if 'j' in x.lower():
+                x = x.lower().replace(' ', '')
+                match = get_complex.match(x)
+                re = match.group('re')
+                if not re:
+                    re = 0
+                im = match.group('im').rstrip('j')
+                return ctx.mpc(ctx.convert(re), ctx.convert(im))
+        if hasattr(x, "_mpi_"):
+            a, b = x._mpi_
+            if a == b:
+                return ctx.make_mpf(a)
+            else:
+                raise ValueError("can only create mpf from zero-width interval")
+        raise TypeError("cannot create mpf from " + repr(x))
+
+    def mpmathify(ctx, *args, **kwargs):
+        return ctx.convert(*args, **kwargs)
+
+    def _parse_prec(ctx, kwargs):
+        if kwargs:
+            if kwargs.get('exact'):
+                return 0, 'f'
+            prec, rounding = ctx._prec_rounding
+            if 'rounding' in kwargs:
+                rounding = kwargs['rounding']
+            if 'prec' in kwargs:
+                prec = kwargs['prec']
+                if prec == ctx.inf:
+                    return 0, 'f'
+                else:
+                    prec = int(prec)
+            elif 'dps' in kwargs:
+                dps = kwargs['dps']
+                if dps == ctx.inf:
+                    return 0, 'f'
+                prec = dps_to_prec(dps)
+            return prec, rounding
+        return ctx._prec_rounding
+
+    _exact_overflow_msg = "the exact result does not fit in memory"
+
+    _hypsum_msg = """hypsum() failed to converge to the requested %i bits of accuracy
+using a working precision of %i bits. Try with a higher maxprec,
+maxterms, or set zeroprec."""
+
+    def hypsum(ctx, p, q, flags, coeffs, z, accurate_small=True, **kwargs):
+        if hasattr(z, "_mpf_"):
+            key = p, q, flags, 'R'
+            v = z._mpf_
+        elif hasattr(z, "_mpc_"):
+            key = p, q, flags, 'C'
+            v = z._mpc_
+        if key not in ctx.hyp_summators:
+            ctx.hyp_summators[key] = libmp.make_hyp_summator(key)[1]
+        summator = ctx.hyp_summators[key]
+        prec = ctx.prec
+        maxprec = kwargs.get('maxprec', ctx._default_hyper_maxprec(prec))
+        extraprec = 50
+        epsshift = 25
+        # Jumps in magnitude occur when parameters are close to negative
+        # integers. We must ensure that these terms are included in
+        # the sum and added accurately
+        magnitude_check = {}
+        max_total_jump = 0
+        for i, c in enumerate(coeffs):
+            if flags[i] == 'Z':
+                if i >= p and c <= 0:
+                    ok = False
+                    for ii, cc in enumerate(coeffs[:p]):
+                        # Note: c <= cc or c < cc, depending on convention
+                        if flags[ii] == 'Z' and cc <= 0 and c <= cc:
+                            ok = True
+                    if not ok:
+                        raise ZeroDivisionError("pole in hypergeometric series")
+                continue
+            n, d = ctx.nint_distance(c)
+            n = -int(n)
+            d = -d
+            if i >= p and n >= 0 and d > 4:
+                if n in magnitude_check:
+                    magnitude_check[n] += d
+                else:
+                    magnitude_check[n] = d
+                extraprec = max(extraprec, d - prec + 60)
+            max_total_jump += abs(d)
+        while 1:
+            if extraprec > maxprec:
+                raise ValueError(ctx._hypsum_msg % (prec, prec+extraprec))
+            wp = prec + extraprec
+            if magnitude_check:
+                mag_dict = dict((n,None) for n in magnitude_check)
+            else:
+                mag_dict = {}
+            zv, have_complex, magnitude = summator(coeffs, v, prec, wp, \
+                epsshift, mag_dict, **kwargs)
+            cancel = -magnitude
+            jumps_resolved = True
+            if extraprec < max_total_jump:
+                for n in mag_dict.values():
+                    if (n is None) or (n < prec):
+                        jumps_resolved = False
+                        break
+            accurate = (cancel < extraprec-25-5 or not accurate_small)
+            if jumps_resolved:
+                if accurate:
+                    break
+                # zero?
+                zeroprec = kwargs.get('zeroprec')
+                if zeroprec is not None:
+                    if cancel > zeroprec:
+                        if have_complex:
+                            return ctx.mpc(0)
+                        else:
+                            return ctx.zero
+
+            # Some near-singularities were not included, so increase
+            # precision and repeat until they are
+            extraprec *= 2
+            # Possible workaround for bad roundoff in fixed-point arithmetic
+            epsshift += 5
+            extraprec += 5
+
+        if type(zv) is tuple:
+            if have_complex:
+                return ctx.make_mpc(zv)
+            else:
+                return ctx.make_mpf(zv)
+        else:
+            return zv
+
+    def ldexp(ctx, x, n):
+        r"""
+        Computes `x 2^n` efficiently. No rounding is performed.
+        The argument `x` must be a real floating-point number (or
+        possible to convert into one) and `n` must be a Python ``int``.
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> ldexp(1, 10)
+            mpf('1024.0')
+            >>> ldexp(1, -3)
+            mpf('0.125')
+
+        """
+        x = ctx.convert(x)
+        return ctx.make_mpf(libmp.mpf_shift(x._mpf_, n))
+
+    def frexp(ctx, x):
+        r"""
+        Given a real number `x`, returns `(y, n)` with `y \in [0.5, 1)`,
+        `n` a Python integer, and such that `x = y 2^n`. No rounding is
+        performed.
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> frexp(7.5)
+            (mpf('0.9375'), 3)
+
+        """
+        x = ctx.convert(x)
+        y, n = libmp.mpf_frexp(x._mpf_)
+        return ctx.make_mpf(y), n
+
+    def fneg(ctx, x, **kwargs):
+        """
+        Negates the number *x*, giving a floating-point result, optionally
+        using a custom precision and rounding mode.
+
+        See the documentation of :func:`~mpmath.fadd` for a detailed description
+        of how to specify precision and rounding.
+
+        **Examples**
+
+        An mpmath number is returned::
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> fneg(2.5)
+            mpf('-2.5')
+            >>> fneg(-5+2j)
+            mpc(real='5.0', imag='-2.0')
+
+        Precise control over rounding is possible::
+
+            >>> x = fadd(2, 1e-100, exact=True)
+            >>> fneg(x)
+            mpf('-2.0')
+            >>> fneg(x, rounding='f')
+            mpf('-2.0000000000000004')
+
+        Negating with and without roundoff::
+
+            >>> n = 200000000000000000000001
+            >>> print(int(-mpf(n)))
+            -200000000000000016777216
+            >>> print(int(fneg(n)))
+            -200000000000000016777216
+            >>> print(int(fneg(n, prec=log(n,2)+1)))
+            -200000000000000000000001
+            >>> print(int(fneg(n, dps=log(n,10)+1)))
+            -200000000000000000000001
+            >>> print(int(fneg(n, prec=inf)))
+            -200000000000000000000001
+            >>> print(int(fneg(n, dps=inf)))
+            -200000000000000000000001
+            >>> print(int(fneg(n, exact=True)))
+            -200000000000000000000001
+
+        """
+        prec, rounding = ctx._parse_prec(kwargs)
+        x = ctx.convert(x)
+        if hasattr(x, '_mpf_'):
+            return ctx.make_mpf(mpf_neg(x._mpf_, prec, rounding))
+        if hasattr(x, '_mpc_'):
+            return ctx.make_mpc(mpc_neg(x._mpc_, prec, rounding))
+        raise ValueError("Arguments need to be mpf or mpc compatible numbers")
+
+    def fadd(ctx, x, y, **kwargs):
+        """
+        Adds the numbers *x* and *y*, giving a floating-point result,
+        optionally using a custom precision and rounding mode.
+
+        The default precision is the working precision of the context.
+        You can specify a custom precision in bits by passing the *prec* keyword
+        argument, or by providing an equivalent decimal precision with the *dps*
+        keyword argument. If the precision is set to ``+inf``, or if the flag
+        *exact=True* is passed, an exact addition with no rounding is performed.
+
+        When the precision is finite, the optional *rounding* keyword argument
+        specifies the direction of rounding. Valid options are ``'n'`` for
+        nearest (default), ``'f'`` for floor, ``'c'`` for ceiling, ``'d'``
+        for down, ``'u'`` for up.
+
+        **Examples**
+
+        Using :func:`~mpmath.fadd` with precision and rounding control::
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> fadd(2, 1e-20)
+            mpf('2.0')
+            >>> fadd(2, 1e-20, rounding='u')
+            mpf('2.0000000000000004')
+            >>> nprint(fadd(2, 1e-20, prec=100), 25)
+            2.00000000000000000001
+            >>> nprint(fadd(2, 1e-20, dps=15), 25)
+            2.0
+            >>> nprint(fadd(2, 1e-20, dps=25), 25)
+            2.00000000000000000001
+            >>> nprint(fadd(2, 1e-20, exact=True), 25)
+            2.00000000000000000001
+
+        Exact addition avoids cancellation errors, enforcing familiar laws
+        of numbers such as `x+y-x = y`, which don't hold in floating-point
+        arithmetic with finite precision::
+
+            >>> x, y = mpf(2), mpf('1e-1000')
+            >>> print(x + y - x)
+            0.0
+            >>> print(fadd(x, y, prec=inf) - x)
+            1.0e-1000
+            >>> print(fadd(x, y, exact=True) - x)
+            1.0e-1000
+
+        Exact addition can be inefficient and may be impossible to perform
+        with large magnitude differences::
+
+            >>> fadd(1, '1e-100000000000000000000', prec=inf)
+            Traceback (most recent call last):
+              ...
+            OverflowError: the exact result does not fit in memory
+
+        """
+        prec, rounding = ctx._parse_prec(kwargs)
+        x = ctx.convert(x)
+        y = ctx.convert(y)
+        try:
+            if hasattr(x, '_mpf_'):
+                if hasattr(y, '_mpf_'):
+                    return ctx.make_mpf(mpf_add(x._mpf_, y._mpf_, prec, rounding))
+                if hasattr(y, '_mpc_'):
+                    return ctx.make_mpc(mpc_add_mpf(y._mpc_, x._mpf_, prec, rounding))
+            if hasattr(x, '_mpc_'):
+                if hasattr(y, '_mpf_'):
+                    return ctx.make_mpc(mpc_add_mpf(x._mpc_, y._mpf_, prec, rounding))
+                if hasattr(y, '_mpc_'):
+                    return ctx.make_mpc(mpc_add(x._mpc_, y._mpc_, prec, rounding))
+        except (ValueError, OverflowError):
+            raise OverflowError(ctx._exact_overflow_msg)
+        raise ValueError("Arguments need to be mpf or mpc compatible numbers")
+
+    def fsub(ctx, x, y, **kwargs):
+        """
+        Subtracts the numbers *x* and *y*, giving a floating-point result,
+        optionally using a custom precision and rounding mode.
+
+        See the documentation of :func:`~mpmath.fadd` for a detailed description
+        of how to specify precision and rounding.
+
+        **Examples**
+
+        Using :func:`~mpmath.fsub` with precision and rounding control::
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> fsub(2, 1e-20)
+            mpf('2.0')
+            >>> fsub(2, 1e-20, rounding='d')
+            mpf('1.9999999999999998')
+            >>> nprint(fsub(2, 1e-20, prec=100), 25)
+            1.99999999999999999999
+            >>> nprint(fsub(2, 1e-20, dps=15), 25)
+            2.0
+            >>> nprint(fsub(2, 1e-20, dps=25), 25)
+            1.99999999999999999999
+            >>> nprint(fsub(2, 1e-20, exact=True), 25)
+            1.99999999999999999999
+
+        Exact subtraction avoids cancellation errors, enforcing familiar laws
+        of numbers such as `x-y+y = x`, which don't hold in floating-point
+        arithmetic with finite precision::
+
+            >>> x, y = mpf(2), mpf('1e1000')
+            >>> print(x - y + y)
+            0.0
+            >>> print(fsub(x, y, prec=inf) + y)
+            2.0
+            >>> print(fsub(x, y, exact=True) + y)
+            2.0
+
+        Exact addition can be inefficient and may be impossible to perform
+        with large magnitude differences::
+
+            >>> fsub(1, '1e-100000000000000000000', prec=inf)
+            Traceback (most recent call last):
+              ...
+            OverflowError: the exact result does not fit in memory
+
+        """
+        prec, rounding = ctx._parse_prec(kwargs)
+        x = ctx.convert(x)
+        y = ctx.convert(y)
+        try:
+            if hasattr(x, '_mpf_'):
+                if hasattr(y, '_mpf_'):
+                    return ctx.make_mpf(mpf_sub(x._mpf_, y._mpf_, prec, rounding))
+                if hasattr(y, '_mpc_'):
+                    return ctx.make_mpc(mpc_sub((x._mpf_, fzero), y._mpc_, prec, rounding))
+            if hasattr(x, '_mpc_'):
+                if hasattr(y, '_mpf_'):
+                    return ctx.make_mpc(mpc_sub_mpf(x._mpc_, y._mpf_, prec, rounding))
+                if hasattr(y, '_mpc_'):
+                    return ctx.make_mpc(mpc_sub(x._mpc_, y._mpc_, prec, rounding))
+        except (ValueError, OverflowError):
+            raise OverflowError(ctx._exact_overflow_msg)
+        raise ValueError("Arguments need to be mpf or mpc compatible numbers")
+
+    def fmul(ctx, x, y, **kwargs):
+        """
+        Multiplies the numbers *x* and *y*, giving a floating-point result,
+        optionally using a custom precision and rounding mode.
+
+        See the documentation of :func:`~mpmath.fadd` for a detailed description
+        of how to specify precision and rounding.
+
+        **Examples**
+
+        The result is an mpmath number::
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> fmul(2, 5.0)
+            mpf('10.0')
+            >>> fmul(0.5j, 0.5)
+            mpc(real='0.0', imag='0.25')
+
+        Avoiding roundoff::
+
+            >>> x, y = 10**10+1, 10**15+1
+            >>> print(x*y)
+            10000000001000010000000001
+            >>> print(mpf(x) * mpf(y))
+            1.0000000001e+25
+            >>> print(int(mpf(x) * mpf(y)))
+            10000000001000011026399232
+            >>> print(int(fmul(x, y)))
+            10000000001000011026399232
+            >>> print(int(fmul(x, y, dps=25)))
+            10000000001000010000000001
+            >>> print(int(fmul(x, y, exact=True)))
+            10000000001000010000000001
+
+        Exact multiplication with complex numbers can be inefficient and may
+        be impossible to perform with large magnitude differences between
+        real and imaginary parts::
+
+            >>> x = 1+2j
+            >>> y = mpc(2, '1e-100000000000000000000')
+            >>> fmul(x, y)
+            mpc(real='2.0', imag='4.0')
+            >>> fmul(x, y, rounding='u')
+            mpc(real='2.0', imag='4.0000000000000009')
+            >>> fmul(x, y, exact=True)
+            Traceback (most recent call last):
+              ...
+            OverflowError: the exact result does not fit in memory
+
+        """
+        prec, rounding = ctx._parse_prec(kwargs)
+        x = ctx.convert(x)
+        y = ctx.convert(y)
+        try:
+            if hasattr(x, '_mpf_'):
+                if hasattr(y, '_mpf_'):
+                    return ctx.make_mpf(mpf_mul(x._mpf_, y._mpf_, prec, rounding))
+                if hasattr(y, '_mpc_'):
+                    return ctx.make_mpc(mpc_mul_mpf(y._mpc_, x._mpf_, prec, rounding))
+            if hasattr(x, '_mpc_'):
+                if hasattr(y, '_mpf_'):
+                    return ctx.make_mpc(mpc_mul_mpf(x._mpc_, y._mpf_, prec, rounding))
+                if hasattr(y, '_mpc_'):
+                    return ctx.make_mpc(mpc_mul(x._mpc_, y._mpc_, prec, rounding))
+        except (ValueError, OverflowError):
+            raise OverflowError(ctx._exact_overflow_msg)
+        raise ValueError("Arguments need to be mpf or mpc compatible numbers")
+
+    def fdiv(ctx, x, y, **kwargs):
+        """
+        Divides the numbers *x* and *y*, giving a floating-point result,
+        optionally using a custom precision and rounding mode.
+
+        See the documentation of :func:`~mpmath.fadd` for a detailed description
+        of how to specify precision and rounding.
+
+        **Examples**
+
+        The result is an mpmath number::
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> fdiv(3, 2)
+            mpf('1.5')
+            >>> fdiv(2, 3)
+            mpf('0.66666666666666663')
+            >>> fdiv(2+4j, 0.5)
+            mpc(real='4.0', imag='8.0')
+
+        The rounding direction and precision can be controlled::
+
+            >>> fdiv(2, 3, dps=3)    # Should be accurate to at least 3 digits
+            mpf('0.6666259765625')
+            >>> fdiv(2, 3, rounding='d')
+            mpf('0.66666666666666663')
+            >>> fdiv(2, 3, prec=60)
+            mpf('0.66666666666666667')
+            >>> fdiv(2, 3, rounding='u')
+            mpf('0.66666666666666674')
+
+        Checking the error of a division by performing it at higher precision::
+
+            >>> fdiv(2, 3) - fdiv(2, 3, prec=100)
+            mpf('-3.7007434154172148e-17')
+
+        Unlike :func:`~mpmath.fadd`, :func:`~mpmath.fmul`, etc., exact division is not
+        allowed since the quotient of two floating-point numbers generally
+        does not have an exact floating-point representation. (In the
+        future this might be changed to allow the case where the division
+        is actually exact.)
+
+            >>> fdiv(2, 3, exact=True)
+            Traceback (most recent call last):
+              ...
+            ValueError: division is not an exact operation
+
+        """
+        prec, rounding = ctx._parse_prec(kwargs)
+        if not prec:
+            raise ValueError("division is not an exact operation")
+        x = ctx.convert(x)
+        y = ctx.convert(y)
+        if hasattr(x, '_mpf_'):
+            if hasattr(y, '_mpf_'):
+                return ctx.make_mpf(mpf_div(x._mpf_, y._mpf_, prec, rounding))
+            if hasattr(y, '_mpc_'):
+                return ctx.make_mpc(mpc_div((x._mpf_, fzero), y._mpc_, prec, rounding))
+        if hasattr(x, '_mpc_'):
+            if hasattr(y, '_mpf_'):
+                return ctx.make_mpc(mpc_div_mpf(x._mpc_, y._mpf_, prec, rounding))
+            if hasattr(y, '_mpc_'):
+                return ctx.make_mpc(mpc_div(x._mpc_, y._mpc_, prec, rounding))
+        raise ValueError("Arguments need to be mpf or mpc compatible numbers")
+
+    def nint_distance(ctx, x):
+        r"""
+        Return `(n,d)` where `n` is the nearest integer to `x` and `d` is
+        an estimate of `\log_2(|x-n|)`. If `d < 0`, `-d` gives the precision
+        (measured in bits) lost to cancellation when computing `x-n`.
+
+            >>> from mpmath import *
+            >>> n, d = nint_distance(5)
+            >>> print(n); print(d)
+            5
+            -inf
+            >>> n, d = nint_distance(mpf(5))
+            >>> print(n); print(d)
+            5
+            -inf
+            >>> n, d = nint_distance(mpf(5.00000001))
+            >>> print(n); print(d)
+            5
+            -26
+            >>> n, d = nint_distance(mpf(4.99999999))
+            >>> print(n); print(d)
+            5
+            -26
+            >>> n, d = nint_distance(mpc(5,10))
+            >>> print(n); print(d)
+            5
+            4
+            >>> n, d = nint_distance(mpc(5,0.000001))
+            >>> print(n); print(d)
+            5
+            -19
+
+        """
+        typx = type(x)
+        if typx in int_types:
+            return int(x), ctx.ninf
+        elif typx is rational.mpq:
+            p, q = x._mpq_
+            n, r = divmod(p, q)
+            if 2*r >= q:
+                n += 1
+            elif not r:
+                return n, ctx.ninf
+            # log(p/q-n) = log((p-nq)/q) = log(p-nq) - log(q)
+            d = bitcount(abs(p-n*q)) - bitcount(q)
+            return n, d
+        if hasattr(x, "_mpf_"):
+            re = x._mpf_
+            im_dist = ctx.ninf
+        elif hasattr(x, "_mpc_"):
+            re, im = x._mpc_
+            isign, iman, iexp, ibc = im
+            if iman:
+                im_dist = iexp + ibc
+            elif im == fzero:
+                im_dist = ctx.ninf
+            else:
+                raise ValueError("requires a finite number")
+        else:
+            x = ctx.convert(x)
+            if hasattr(x, "_mpf_") or hasattr(x, "_mpc_"):
+                return ctx.nint_distance(x)
+            else:
+                raise TypeError("requires an mpf/mpc")
+        sign, man, exp, bc = re
+        mag = exp+bc
+        # |x| < 0.5
+        if mag < 0:
+            n = 0
+            re_dist = mag
+        elif man:
+            # exact integer
+            if exp >= 0:
+                n = man << exp
+                re_dist = ctx.ninf
+            # exact half-integer
+            elif exp == -1:
+                n = (man>>1)+1
+                re_dist = 0
+            else:
+                d = (-exp-1)
+                t = man >> d
+                if t & 1:
+                    t += 1
+                    man = (t<<d) - man
+                else:
+                    man -= (t<<d)
+                n = t>>1   # int(t)>>1
+                re_dist = exp+bitcount(man)
+            if sign:
+                n = -n
+        elif re == fzero:
+            re_dist = ctx.ninf
+            n = 0
+        else:
+            raise ValueError("requires a finite number")
+        return n, max(re_dist, im_dist)
+
+    def fprod(ctx, factors):
+        r"""
+        Calculates a product containing a finite number of factors (for
+        infinite products, see :func:`~mpmath.nprod`). The factors will be
+        converted to mpmath numbers.
+
+            >>> from mpmath import *
+            >>> mp.dps = 15; mp.pretty = False
+            >>> fprod([1, 2, 0.5, 7])
+            mpf('7.0')
+
+        """
+        orig = ctx.prec
+        try:
+            v = ctx.one
+            for p in factors:
+                v *= p
+        finally:
+            ctx.prec = orig
+        return +v
+
+    def rand(ctx):
+        """
+        Returns an ``mpf`` with value chosen randomly from `[0, 1)`.
+        The number of randomly generated bits in the mantissa is equal
+        to the working precision.
+        """
+        return ctx.make_mpf(mpf_rand(ctx._prec))
+
+    def fraction(ctx, p, q):
+        """
+        Given Python integers `(p, q)`, returns a lazy ``mpf`` representing
+        the fraction `p/q`. The value is updated with the precision.
+
+            >>> from mpmath import *
+            >>> mp.dps = 15
+            >>> a = fraction(1,100)
+            >>> b = mpf(1)/100
+            >>> print(a); print(b)
+            0.01
+            0.01
+            >>> mp.dps = 30
+            >>> print(a); print(b)      # a will be accurate
+            0.01
+            0.0100000000000000002081668171172
+            >>> mp.dps = 15
+        """
+        return ctx.constant(lambda prec, rnd: from_rational(p, q, prec, rnd),
+            '%s/%s' % (p, q))
+
+    def absmin(ctx, x):
+        return abs(ctx.convert(x))
+
+    def absmax(ctx, x):
+        return abs(ctx.convert(x))
+
+    def _as_points(ctx, x):
+        # XXX: remove this?
+        if hasattr(x, '_mpi_'):
+            a, b = x._mpi_
+            return [ctx.make_mpf(a), ctx.make_mpf(b)]
+        return x
+
+    '''
+    def _zetasum(ctx, s, a, b):
+        """
+        Computes sum of k^(-s) for k = a, a+1, ..., b with a, b both small
+        integers.
+        """
+        a = int(a)
+        b = int(b)
+        s = ctx.convert(s)
+        prec, rounding = ctx._prec_rounding
+        if hasattr(s, '_mpf_'):
+            v = ctx.make_mpf(libmp.mpf_zetasum(s._mpf_, a, b, prec))
+        elif hasattr(s, '_mpc_'):
+            v = ctx.make_mpc(libmp.mpc_zetasum(s._mpc_, a, b, prec))
+        return v
+    '''
+
+    def _zetasum_fast(ctx, s, a, n, derivatives=[0], reflect=False):
+        if not (ctx.isint(a) and hasattr(s, "_mpc_")):
+            raise NotImplementedError
+        a = int(a)
+        prec = ctx._prec
+        xs, ys = libmp.mpc_zetasum(s._mpc_, a, n, derivatives, reflect, prec)
+        xs = [ctx.make_mpc(x) for x in xs]
+        ys = [ctx.make_mpc(y) for y in ys]
+        return xs, ys
+
+class PrecisionManager:
+    def __init__(self, ctx, precfun, dpsfun, normalize_output=False):
+        self.ctx = ctx
+        self.precfun = precfun
+        self.dpsfun = dpsfun
+        self.normalize_output = normalize_output
+    def __call__(self, f):
+        @functools.wraps(f)
+        def g(*args, **kwargs):
+            orig = self.ctx.prec
+            try:
+                if self.precfun:
+                    self.ctx.prec = self.precfun(self.ctx.prec)
+                else:
+                    self.ctx.dps = self.dpsfun(self.ctx.dps)
+                if self.normalize_output:
+                    v = f(*args, **kwargs)
+                    if type(v) is tuple:
+                        return tuple([+a for a in v])
+                    return +v
+                else:
+                    return f(*args, **kwargs)
+            finally:
+                self.ctx.prec = orig
+        return g
+    def __enter__(self):
+        self.origp = self.ctx.prec
+        if self.precfun:
+            self.ctx.prec = self.precfun(self.ctx.prec)
+        else:
+            self.ctx.dps = self.dpsfun(self.ctx.dps)
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        self.ctx.prec = self.origp
+        return False
+
+
+if __name__ == '__main__':
+    import doctest
+    doctest.testmod()