/

Source code for sympy.core.numbers

from .core import C
from .sympify import converter, sympify, _sympify, SympifyError
from .basic import Basic
from .singleton import S, Singleton
from .expr import Expr, AtomicExpr
from .decorators import _sympifyit, deprecated
from .cache import cacheit, clear_cache
from sympy.core.compatibility import as_int
import sympy.mpmath as mpmath
import sympy.mpmath.libmp as mlib
from sympy.mpmath.libmp import mpf_pow, mpf_pi, mpf_e, phi_fixed
from sympy.mpmath.ctx_mp import mpnumeric
from sympy.mpmath.libmp.libmpf import fnan, _normalize as mpf_normalize

import decimal
import math
import re as regex
from collections import defaultdict

rnd = mlib.round_nearest

_LOG2 = math.log(2)

def mpf_norm(mpf, prec):
"""Return the mpf tuple normalized appropriately for the indicated
precision.

This also contains a portion of code to not return zero if
the mantissa is 0 since it is zero for mpf's +inf, -inf and
nan, too.
"""
sign, man, expt, bc = mpf
if not man:
# hack for mpf_normalize which does not do this;
# it assumes that if man is zero the result is 0
if not bc:
return mlib.fzero
else:
# don't change anything; this should already
# be a well formed mpf tuple
return mpf
rv = mpf_normalize(sign, man, expt, bc, prec, rnd)
return rv

# TODO: we should use the warnings module
_errdict = {"divide": False}
[docs]def seterr(divide=False):
"""
Should sympy raise an exception on 0/0 or return a nan?

divide == True .... raise an exception
divide == False ... return nan
"""
if _errdict["divide"] != divide:
clear_cache()
_errdict["divide"] = divide

def _decimal_to_Rational_prec(dec):
"""Convert an ordinary decimal instance to a Rational."""
# _is_special is needed for Python 2.5 support; is_finite for Python 3.3
# support
nonfinite = getattr(dec, '_is_special', None)
if nonfinite is None:
nonfinite = not dec.is_finite()
if nonfinite:
raise TypeError("dec must be finite, got %s." % dec)
s, d, e = dec.as_tuple()
prec = len(d)
if int(dec) == dec:
rv = Rational(int(dec))
else:
s = (-1)**s
d = sum([di*10**i for i, di in enumerate(reversed(d))])
rv = Rational(s*d, 10**-e)
return rv, prec

def _literal_float(f):
"""Return True if n can be interpreted as a floating point number."""
pat = r"[-+]?((\d*\.\d+)|(\d+\.?))(eE[-+]?\d+)?"
return bool(regex.match(pat, f))

# (a,b) -> gcd(a,b)
_gcdcache = {}

# TODO caching with decorator, but not to degrade performance
[docs]def igcd(a, b):
"""Computes positive, integer greatest common divisor of two numbers.

The algorithm is based on the well known Euclid's algorithm. To
improve speed, igcd() has its own caching mechanism implemented.
"""
try:
return _gcdcache[(a,b)]
except KeyError:
a, b = as_int(a), as_int(b)

if a and b:
if b < 0:
b = -b

while b:
a, b = b, a % b
else:
a = abs(a or b)

_gcdcache[(a,b)] = a
return a

[docs]def ilcm(a, b):
"""Computes integer least common multiple of two numbers. """
if a == 0 and b == 0:
return 0
else:
return a*b // igcd(a, b)

def igcdex(a, b):
"""Returns x, y, g such that g = x*a + y*b = gcd(a, b).

>>> from sympy.core.numbers import igcdex
>>> igcdex(2, 3)
(-1, 1, 1)
>>> igcdex(10, 12)
(-1, 1, 2)

>>> x, y, g = igcdex(100, 2004)
>>> x, y, g
(-20, 1, 4)
>>> x*100 + y*2004
4

"""
if (not a) and (not b):
return (0, 1, 0)

if not a:
return (0, b//abs(b), abs(b))
if not b:
return (a//abs(a), 0, abs(a))

if a < 0:
a, x_sign = -a, -1
else:
x_sign = 1

if b < 0:
b, y_sign = -b, -1
else:
y_sign = 1

x, y, r, s = 1, 0, 0, 1

while b:
(c, q) = (a % b, a // b)
(a, b, r, s, x, y) = (b, c, x-q*r, y-q*s, r, s)

return (x*x_sign, y*y_sign, a)

[docs]class Number(AtomicExpr):
"""
Represents any kind of number in sympy.

Floating point numbers are represented by the Float class.
Integer numbers (of any size), together with rational numbers (again,
there is no limit on their size) are represented by the Rational class.

If you want to represent, for example, 1+sqrt(2), then you need to do::

Rational(1) + sqrt(Rational(2))
"""
is_commutative = True
is_bounded = True
is_finite = True
is_number = True

__slots__ = []

# Used to make max(x._prec, y._prec) return x._prec when only x is a float
_prec = -1

is_Number = True

def __new__(cls, *obj):
if len(obj) == 1:
obj=obj

if isinstance(obj, Number):
return obj
if isinstance(obj, int):
return Integer(obj)
if isinstance(obj, tuple) and len(obj) == 2:
return Rational(*obj)
if isinstance(obj, (float, mpmath.mpf, decimal.Decimal)):
return Float(obj)
if isinstance(obj, str):
val = sympify(obj)
if isinstance(val, Number):
return val
else:
raise ValueError('String "%s" does not denote a Number'%obj)
if isinstance(obj, Number):
return obj
msg = "expected str|int|long|float|Decimal|Number object but got %r"
raise TypeError(msg % type(obj).__name__)

def __divmod__(self, other):
from .containers import Tuple
from sympy.functions.elementary.complexes import sign

try:
other = Number(other)
except TypeError:
msg = "unsupported operand type(s) for divmod(): '%s' and '%s'"
raise TypeError(msg % (type(self).__name__, type(other).__name__))
if not other:
raise ZeroDivisionError('modulo by zero')
if self.is_Integer and other.is_Integer:
return Tuple(*divmod(self.p, other.p))
else:
rat = self/other
w = sign(rat)*int(abs(rat)) # = rat.floor()
r = self - other*w
#w*other + r == self
return Tuple(w, r)

def __rdivmod__(self, other):
try:
other = Number(other)
except TypeError:
msg = "unsupported operand type(s) for divmod(): '%s' and '%s'"
raise TypeError(msg % (type(other).__name__, type(self).__name__))
return divmod(other, self)

def __round__(self, *args):
return round(float(self), *args)

def _as_mpf_val(self, prec):
"""Evaluation of mpf tuple accurate to at least prec bits."""
raise NotImplementedError('%s needs ._as_mpf_val() method' % \
(self.__class__.__name__))

def _eval_evalf(self, prec):
return Float._new(self._as_mpf_val(prec), prec)

def _as_mpf_op(self, prec):
prec = max(prec, self._prec)
return self._as_mpf_val(prec), prec

def __float__(self):
return mlib.to_float(self._as_mpf_val(53))

def _eval_conjugate(self):
return self

def _eval_order(self, *symbols):
# Order(5, x, y) -> Order(1,x,y)
return C.Order(S.One, *symbols)

def _eval_subs(self, old, new):
if old == -self:
return -new
return self # there is no other possibility

@classmethod
def class_key(cls):
return 1, 0, 'Number'

@cacheit
def sort_key(self, order=None):
return self.class_key(), (0, ()), (), self

@_sympifyit('other', NotImplemented)
if isinstance(other, Number):
if other is S.NaN:
return S.NaN
elif other is S.Infinity:
return S.Infinity
elif other is S.NegativeInfinity:
return S.NegativeInfinity

@_sympifyit('other', NotImplemented)
def __sub__(self, other):
if isinstance(other, Number):
if other is S.NaN:
return S.NaN
elif other is S.Infinity:
return S.NegativeInfinity
elif other is S.NegativeInfinity:
return S.Infinity
return AtomicExpr.__sub__(self, other)

@_sympifyit('other', NotImplemented)
def __mul__(self, other):
if isinstance(other, Number):
if other is S.NaN:
return S.NaN
elif other is S.Infinity:
if self == 0:
return S.NaN
elif self > 0:
return S.Infinity
else:
return S.NegativeInfinity
elif other is S.NegativeInfinity:
if self == 0:
return S.NaN
elif self > 0:
return S.NegativeInfinity
else:
return S.Infinity
return AtomicExpr.__mul__(self, other)

@_sympifyit('other', NotImplemented)
def __div__(self, other):
if isinstance(other, Number):
if other is S.NaN:
return S.NaN
elif other is S.Infinity or other is S.NegativeInfinity:
return S.Zero
return AtomicExpr.__div__(self, other)

__truediv__ = __div__

def __eq__(self, other):
raise NotImplementedError('%s needs .__eq__() method' %
(self.__class__.__name__))

def __ne__(self, other):
raise NotImplementedError('%s needs .__ne__() method' %
(self.__class__.__name__))

def __lt__(self, other):
raise NotImplementedError('%s needs .__lt__() method' %
(self.__class__.__name__))

def __le__(self, other):
raise NotImplementedError('%s needs .__le__() method' %
(self.__class__.__name__))

def __gt__(self, other):
return _sympify(other).__lt__(self)

def __ge__(self, other):
return _sympify(other).__le__(self)

def __hash__(self):
return super(Number, self).__hash__()

def is_constant(self, *wrt, **flags):
return True

@property
def is_number(self):
return True

def as_coeff_mul(self, *deps):
# a -> c*t
if self.is_Rational:
return self, tuple()
elif self.is_negative:
return S.NegativeOne, (-self,)
return S.One, (self,)

# a -> c + t
if self.is_Rational:
return self, tuple()
return S.Zero, (self,)

[docs]    def gcd(self, other):
"""Compute greatest common divisor of input arguments. """
return S.One

[docs]    def lcm(self, other):
"""Compute least common multiple of input arguments. """
other = _sympify(other)
return self*other

[docs]    def cofactors(self, other):
"""Compute GCD and cofactors of input arguments. """
other = _sympify(other)
return S.One, self, other

[docs]    def as_coeff_Mul(self, rational=False):
"""Efficiently extract the coefficient of a product. """
if rational and not self.is_Rational:
return S.One, self
return self, S.One

"""Efficiently extract the coefficient of a summation. """
return self, S.Zero

[docs]class Float(Number):
"""
Represents a floating point number. It is capable of representing
arbitrary-precision floating-point numbers.

Examples
========

>>> from sympy import Float
>>> Float(3.5) # convert from Python float or int
3.50000000000000
>>> Float(3) # reverts to Integer
3
>>> Float(3, '') # forced to Float
3.

Floats can be created from a string representations of Python floats
to force ints to Float or to enter high-precision (> 15 significant
digits) values:

>>> Float('.0010')
0.00100000000000000
>>> Float('1e-3')
0.00100000000000000
>>> Float('1e-3', 3)
0.00100

Float can automatically count significant figures if a null string
is sent for the precision; space are also allowed in the string. (Auto-
counting is only allowed for strings, ints and longs).

>>> Float('123 456 789 . 123 456', '')
123456789.123456
>>> Float('12e-3', '')
0.012

Notes
=====

Floats are inexact by their nature unless their value is a binary-exact
value.

>>> approx, exact = Float(.1, 1), Float(.125, 1)

For calculation purposes, evalf needs to be able to change the precision
but this will not increase the accuracy of the inexact value. The
following is the most accurate 5-digit approximation of a value of 0.1
that had only 1 digit of precision:

>>> approx.evalf(5)
0.099609

By contrast, 0.125 is exact in binary (as it is in base 10) and so it
can be passed to Float or evalf to obtain an arbitrary precision with
matching accuracy:

>>> Float(exact, 5)
0.12500
>>> exact.evalf(20)
0.12500000000000000000

Trying to make a high-precision Float from a float is not disallowed,
but one must keep in mind that the *underlying float* (not the apparent
decimal value) is being obtained with high precision. For example, 0.3
does not have a finite binary representation. The closest rational is
the fraction 5404319552844595/2**54. So if you try to obtain a Float of
0.3 to 20 digits of precision you will not see the same thing as 0.3
followed by 19 zeros:

>>> Float(0.3, 20)
0.29999999999999998890

If you want a 20-digit value of the decimal 0.3 (not the floating point
approximation of 0.3) you should send the 0.3 as a string. The underlying
representation is still binary but a higher precision than Python's float
is used:

>>> Float('0.3', 20)
0.30000000000000000000

Although you can increase the precision of an existing Float using Float
it will not increase the accuracy -- the underlying value is not changed:

>>> def show(f): # binary rep of Float
...     from sympy import Mul, Pow
...     s, m, e, b = f._mpf_
...     v = Mul(m, Pow(2, e, evaluate=False), evaluate=False)
...     print('%s at prec=%s' % (v, f._prec))
...
>>> t = Float('0.3', 3)
>>> show(t)
4915/2**14 at prec=13
>>> show(Float(t, 20)) # higher prec, not higher accuracy
4915/2**14 at prec=70
>>> show(Float(t, 2)) # lower prec
307/2**10 at prec=10

The same thing happens when evalf is used on a Float:

>>> show(t.evalf(20))
4915/2**14 at prec=70
>>> show(t.evalf(2))
307/2**10 at prec=10

Finally, Floats can be instantiated with an mpf tuple (n, c, p) to
produce the number (-1)**n*c*2**p:

>>> n, c, p = 1, 5, 0
>>> (-1)**n*c*2**p
-5
>>> Float((1, 5, 0))
-5.00000000000000

An actual mpf tuple also contains the number of bits in c as the last
element of the tuple, but this is not needed for instantiation:

>>> _._mpf_
(1, 5, 0, 3)

"""
__slots__ = ['_mpf_', '_prec']

is_real = True
is_irrational = False
is_integer = False

is_Float = True

def __new__(cls, num, prec=15):
if isinstance(num, str):
num = num.replace(' ', '')
if num.startswith('.') and len(num) > 1:
num = '0' + num
elif num.startswith('-.') and len(num) > 2:
num = '-0.' + num[2:]
elif not num:
return C.Zero()
if prec == '':
if isinstance(num, (int, Integer)):
# an int is unambiguous, but if someone enters
# .99999999999999999, Python automatically converts
# this to 1.0 and although 1.0 == 1, this is not
# really what the user typed, so we avoid guessing --
# even if num == int(num) -- because we don't know how
# it became that exact float.
num = str(num)
elif not isinstance(num, str):
raise ValueError('The null string can only be used when '
'the number to Float is passed as a string.')
ok = None
if _literal_float(num):
try:
Num = decimal.Decimal(num)
except decimal.InvalidOperation:
pass
else:
num, dps = _decimal_to_Rational_prec(Num)
ok = True
if num.is_Integer:
dps = len(str(num))
if ok is None:
raise ValueError('string-float not recognized: %s' % num)
else:
dps = prec

if prec != '' and isinstance(num, (int, Integer)):
# if this is changed here it has to be changed in _new, too
return Integer(num)

prec = mlib.libmpf.dps_to_prec(dps)
if isinstance(num, float):
_mpf_ = mlib.from_float(num, prec, rnd)
elif isinstance(num, (str, decimal.Decimal, Integer)):
_mpf_ = mlib.from_str(str(num), prec, rnd)
elif isinstance(num, Rational):
_mpf_ = mlib.from_rational(num.p, num.q, prec, rnd)
elif isinstance(num, tuple) and len(num) in (3, 4):
if type(num) is str:
# it's a hexadecimal (coming from a pickled object)
# assume that it is in standard form
num = list(num)
num = int(num, 16)
_mpf_ = tuple(num)
else:
if not num and len(num) == 4:
# handle normalization hack
return Float._new(num, prec)
else:
_mpf_ = mpmath.mpf(
S.NegativeOne**num*num*2**num)._mpf_
elif isinstance(num, Float):
_mpf_ = num._mpf_
if prec < num._prec:
_mpf_ = mpf_norm(_mpf_, prec)
else:
_mpf_ = mpmath.mpf(num)._mpf_

if not num:
return C.Zero()

obj = Expr.__new__(cls)
obj._mpf_ = _mpf_
obj._prec = prec
return obj

@classmethod
def _new(cls, _mpf_, _prec):
if _mpf_ == mlib.fzero:
return S.Zero

# the new Float should be normalized unless it is
# an integer because Float doesn't return Floats
# for Integers. If Integers can become Floats then
# all the following (up to the first 'obj =' line
# can be replaced with ok = mpf_norm(_mpf_, _prec)

sign, man, expt, bc = _mpf_
if not man:
# hack for mpf_normalize which does not do this
if not bc:
ok = mlib.fzero
else:
ok = (sign % 2, int(man), expt, bc)
elif expt < 0:
# this is the non-hack normalization
ok = mpf_normalize(sign, man, expt, bc, _prec, rnd)
else:
ok = _mpf_

obj = Expr.__new__(cls)
obj._mpf_ = ok
obj._prec = _prec
return obj

# mpz can't be pickled
def __getnewargs__(self):
return (mlib.to_pickable(self._mpf_),)

def __getstate__(self):
return {'_prec': self._prec}

def _hashable_content(self):
return (self._mpf_, self._prec)

def floor(self):
return C.Integer(int(mlib.to_int(
mlib.mpf_floor(self._mpf_, self._prec))))

def ceiling(self):
return C.Integer(int(mlib.to_int(
mlib.mpf_ceil(self._mpf_, self._prec))))

@property
def num(self):
return mpmath.mpf(self._mpf_)

def _as_mpf_val(self, prec):
rv = mpf_norm(self._mpf_, prec)
# uncomment to see failures
#if rv != was._mpf_ and self._prec == prec:
#    print was._mpf_, rv
return rv

def _as_mpf_op(self, prec):
return self._mpf_, max(prec, self._prec)

def _eval_is_positive(self):
return self.num > 0

def _eval_is_negative(self):
return self.num < 0

def __neg__(self):
return Float._new(mlib.mpf_neg(self._mpf_), self._prec)

@_sympifyit('other', NotImplemented)
if isinstance(other, Number):
rhs, prec = other._as_mpf_op(self._prec)
return Float._new(mlib.mpf_add(self._mpf_, rhs, prec, rnd), prec)

@_sympifyit('other', NotImplemented)
def __sub__(self, other):
if isinstance(other, Number):
rhs, prec = other._as_mpf_op(self._prec)
return Float._new(mlib.mpf_sub(self._mpf_, rhs, prec, rnd), prec)
return Number.__sub__(self, other)

@_sympifyit('other', NotImplemented)
def __mul__(self, other):
if isinstance(other, Number):
rhs, prec = other._as_mpf_op(self._prec)
return Float._new(mlib.mpf_mul(self._mpf_, rhs, prec, rnd), prec)
return Number.__mul__(self, other)

@_sympifyit('other', NotImplemented)
def __div__(self, other):
if isinstance(other, Number):
rhs, prec = other._as_mpf_op(self._prec)
return Float._new(mlib.mpf_div(self._mpf_, rhs, prec, rnd), prec)
return Number.__div__(self, other)

__truediv__ = __div__

@_sympifyit('other', NotImplemented)
def __mod__(self, other):
if isinstance(other, Number):
rhs, prec = other._as_mpf_op(self._prec)
return Float._new(mlib.mpf_mod(self._mpf_, rhs, prec, rnd), prec)
return Number.__mod__(self, other)

@_sympifyit('other', NotImplemented)
def __rmod__(self, other):
if isinstance(other, Number):
rhs, prec = other._as_mpf_op(self._prec)
return Float._new(mlib.mpf_mod(rhs, self._mpf_, prec, rnd), prec)
return Number.__rmod__(self, other)

def _eval_power(self, expt):
"""
expt is symbolic object but not equal to 0, 1

(-p)**r -> exp(r*log(-p)) -> exp(r*(log(p) + I*Pi)) ->
-> p**r*(sin(Pi*r) + cos(Pi*r)*I)
"""
if isinstance(expt, Number):
if isinstance(expt, Integer):
prec = self._prec
return Float._new(
mlib.mpf_pow_int(self._mpf_, expt.p, prec, rnd), prec)
expt, prec = expt._as_mpf_op(self._prec)
self = self._mpf_
try:
y = mpf_pow(self, expt, prec, rnd)
return Float._new(y, prec)
except mlib.ComplexResult:
re, im = mlib.mpc_pow(
(self, mlib.fzero), (expt, mlib.fzero), prec, rnd)
return Float._new(re, prec) + \
Float._new(im, prec)*S.ImaginaryUnit

def __abs__(self):
return Float._new(mlib.mpf_abs(self._mpf_), self._prec)

def __int__(self):
return int(mlib.to_int(self._mpf_)) # uses round_fast = round_down

def __eq__(self, other):
if isinstance(other, float):
# coerce to Float at same precision
o = Float(other)
try:
ompf = o._as_mpf_val(self._prec)
except ValueError:
return False
return bool(mlib.mpf_eq(self._mpf_, ompf))
try:
other = _sympify(other)
except SympifyError:
return False    # sympy != other  -->  not ==
if isinstance(other, NumberSymbol):
if other.is_irrational:
return False
return other.__eq__(self)
if isinstance(other, Float):
# hack for the nan == nan case which, to mpf_eq is not equal
# but to SymPy should be equal
if other._mpf_ == self._mpf_ == fnan:
return True
return bool(mlib.mpf_eq(self._mpf_, other._mpf_))
if isinstance(other, Number):
# numbers should compare at the same precision;
# all _as_mpf_val routines should be sure to abide
# by the request to change the prec if necessary; if
# they don't, the equality test will fail since it compares
# the mpf tuples
ompf = other._as_mpf_val(self._prec)
return bool(mlib.mpf_eq(self._mpf_, ompf))
return False    # Float != non-Number

def __ne__(self, other):
return not self.__eq__(other)

def __gt__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other
if isinstance(other, NumberSymbol):
return other.__le__(self)
if other.is_comparable:
other = other.evalf()
if isinstance(other, Number):
return bool(mlib.mpf_gt(self._mpf_, other._as_mpf_val(self._prec)))
return Expr.__gt__(self, other)

def __ge__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  -->  ! <=
if isinstance(other, NumberSymbol):
return other.__lt__(self)
if other.is_comparable:
other = other.evalf()
if isinstance(other, Number):
return bool(mlib.mpf_ge(self._mpf_, other._as_mpf_val(self._prec)))
return Expr.__ge__(self, other)

def __lt__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other
if isinstance(other, NumberSymbol):
return other.__ge__(self)
if other.is_real and other.is_number:
other = other.evalf()
if isinstance(other, Number):
return bool(mlib.mpf_lt(self._mpf_, other._as_mpf_val(self._prec)))
return Expr.__lt__(self, other)

def __le__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  -->  ! <=
if isinstance(other, NumberSymbol):
return other.__gt__(self)
if other.is_real and other.is_number:
other = other.evalf()
if isinstance(other, Number):
return bool(mlib.mpf_le(self._mpf_, other._as_mpf_val(self._prec)))
return Expr.__le__(self, other)

def __hash__(self):
return super(Float, self).__hash__()

def epsilon_eq(self, other, epsilon="10e-16"):
return abs(self - other) < Float(epsilon)

def _sage_(self):
import sage.all as sage
return sage.RealNumber(str(self))

converter[float] = converter[decimal.Decimal] = Float

# this is here to work nicely in Sage
RealNumber = Float

[docs]def Real(*args, **kwargs):  # pragma: no cover
"""Deprecated alias for the Float constructor."""
return Float(*args, **kwargs)

[docs]class Rational(Number):
"""Represents integers and rational numbers (p/q) of any size.

Examples
========

>>> from sympy import Rational
>>> from sympy.abc import x, y
>>> Rational(3)
3
>>> Rational(1,2)
1/2
>>> Rational(1.5)
1

Rational can also accept strings that are valid literals for reals:

>>> Rational("1.23")
123/100
>>> Rational('1e-2')
1/100
>>> Rational(".1")
1/10

Parsing needs for any other type of string for which a Rational is desired
can be handled with the rational=True option in sympify() which produces
rationals from strings like '.' (=1/3) and '3/10' (=3/10).

**Low-level**

Access numerator and denominator as .p and .q:

>>> r = Rational(3,4)
>>> r
3/4
>>> r.p
3
>>> r.q
4

Note that p and q return integers (not sympy Integers) so some care
is needed when using them in expressions:

>>> r.p//r.q
0

"""
is_real = True
is_integer = False
is_rational = True

__slots__ = ['p', 'q']

is_Rational = True

@cacheit
def __new__(cls, p, q=None):
if q is None:
if isinstance(p, Rational):
return p
if isinstance(p, str):
p = p.replace(' ', '')
try:
# we might have a Float
neg_pow, digits, expt = decimal.Decimal(p).as_tuple()
p = [1, -1][neg_pow]*int("".join(str(x) for x in digits))
if expt > 0:
# TODO: this branch needs a test
return Rational(p*Pow(10, expt), 1)
return Rational(p, Pow(10, -expt))
except decimal.InvalidOperation:
f = regex.match('^([-+]?[0-9]+)/([0-9]+)\$', p)
if f:
n, d = f.groups()
return Rational(int(n), int(d))
raise ValueError('invalid literal: %s' % p)
elif not isinstance(p, Basic):
return Rational(S(p))
q = S.One
if isinstance(q, Rational):
p *= q.q
q = q.p
if isinstance(p, Rational):
q *= p.q
p = p.p
p = int(p)
q = int(q)
if q == 0:
if p == 0:
if _errdict["divide"]:
raise ValueError("Indeterminate 0/0")
else:
return S.NaN
if p < 0:
return S.NegativeInfinity
return S.Infinity
if q < 0:
q = -q
p = -p
n = igcd(abs(p), q)
if n > 1:
p //= n
q //= n
if q == 1:
return Integer(p)
if p == 1 and q == 2:
return S.Half
obj = Expr.__new__(cls)
obj.p = p
obj.q = q
#obj._args = (p, q)
return obj

[docs]    def limit_denominator(self, max_denominator=1000000):
"""Closest Rational to self with denominator at most max_denominator.

>>> from sympy import Rational
>>> Rational('3.141592653589793').limit_denominator(10)
22/7
>>> Rational('3.141592653589793').limit_denominator(100)
311/99

"""
# Algorithm notes: For any real number x, define a *best upper
# approximation* to x to be a rational number p/q such that:
#
#   (1) p/q >= x, and
#   (2) if p/q > r/s >= x then s > q, for any rational r/s.
#
# Define *best lower approximation* similarly.  Then it can be
# proved that a rational number is a best upper or lower
# approximation to x if, and only if, it is a convergent or
# semiconvergent of the (unique shortest) continued fraction
# associated to x.
#
# To find a best rational approximation with denominator <= M,
# we find the best upper and lower approximations with
# denominator <= M and take whichever of these is closer to x.
# In the event of a tie, the bound with smaller denominator is
# chosen.  If both denominators are equal (which can happen
# only when max_denominator == 1 and self is midway between
# two integers) the lower bound---i.e., the floor of self, is
# taken.

if max_denominator < 1:
raise ValueError("max_denominator should be at least 1")
if self.q <= max_denominator:
return self

p0, q0, p1, q1 = 0, 1, 1, 0
n, d = self.p, self.q
while True:
a = n//d
q2 = q0+a*q1
if q2 > max_denominator:
break
p0, q0, p1, q1 = p1, q1, p0+a*p1, q2
n, d = d, n-a*d

k = (max_denominator-q0)//q1
bound1 = Rational(p0+k*p1, q0+k*q1)
bound2 = Rational(p1, q1)
if abs(bound2 - self) <= abs(bound1-self):
return bound2
else:
return bound1

def __getnewargs__(self):
return (self.p, self.q)

def _hashable_content(self):
return (self.p, self.q)

def _eval_is_positive(self):
return self.p > 0

def _eval_is_zero(self):
return self.p == 0

def __neg__(self):
return Rational(-self.p, self.q)

@_sympifyit('other', NotImplemented)
if isinstance(other, Rational):
return Rational(self.p*other.q + self.q*other.p, self.q*other.q)
elif isinstance(other, Float):
return other + self
else:

@_sympifyit('other', NotImplemented)
def __sub__(self, other):
if isinstance(other, Rational):
return Rational(self.p*other.q - self.q*other.p, self.q*other.q)
elif isinstance(other, Float):
return -other + self
else:
return Number.__sub__(self, other)

@_sympifyit('other', NotImplemented)
def __mul__(self, other):
if isinstance(other, Rational):
return Rational(self.p*other.p, self.q*other.q)
elif isinstance(other, Float):
return other*self
else:
return Number.__mul__(self, other)

@_sympifyit('other', NotImplemented)
def __div__(self, other):
if isinstance(other, Rational):
return Rational(self.p*other.q, self.q*other.p)
elif isinstance(other, Float):
return self*(1/other)
else:
return Number.__div__(self, other)

__truediv__ = __div__

@_sympifyit('other', NotImplemented)
def __mod__(self, other):
if isinstance(other, Rational):
n = (self.p*other.q) // (other.p*self.q)
return Rational(self.p*other.q - n*other.p*self.q, self.q*other.q)
if isinstance(other, Float):
return self.evalf() % other
return Number.__mod__(self, other)

@_sympifyit('other', NotImplemented)
def __rmod__(self, other):
if isinstance(other, Rational):
return Rational.__mod__(other, self)
if isinstance(other, Float):
return other % self.evalf()
return Number.__rmod__(self, other)

def _eval_power(self, expt):
if isinstance(expt, Number):
if isinstance(expt, Float):
return self._eval_evalf(expt._prec)**expt
if expt.is_negative:
# (3/4)**-2 -> (4/3)**2
ne = -expt
if (ne is S.One):
return Rational(self.q, self.p)
if self < 0:
if expt.q != 1:
return -(S.NegativeOne)**((expt.p % expt.q) / \
S(expt.q))*Rational(self.q, -self.p)**ne
else:
return S.NegativeOne**ne*Rational(self.q, -self.p)**ne
else:
return Rational(self.q, self.p)**ne
if expt is S.Infinity: # -oo already caught by test for negative
if self.p > self.q:
# (3/2)**oo -> oo
return S.Infinity
if self.p < -self.q:
# (-3/2)**oo -> oo + I*oo
return S.Infinity + S.Infinity*S.ImaginaryUnit
return S.Zero
if isinstance(expt, Integer):
# (4/3)**2 -> 4**2 / 3**2
return Rational(self.p**expt.p, self.q**expt.p)
if isinstance(expt, Rational):
if self.p != 1:
# (4/3)**(5/6) -> 4**(5/6)*3**(-5/6)
return Integer(self.p)**expt*Integer(self.q)**(-expt)
# as the above caught negative self.p, now self is positive
return Integer(self.q)**Rational(expt.p*(expt.q-1), expt.q) / \
Integer(self.q)**Integer(expt.p)

if self.is_negative and expt.is_even:
return (-self)**expt

return

def _as_mpf_val(self, prec):
return mlib.from_rational(self.p, self.q, prec, rnd)

def _mpmath_(self, prec, rnd):
return mpmath.make_mpf(mlib.from_rational(self.p, self.q, prec, rnd))

def __abs__(self):
return Rational(abs(self.p), self.q)

def __int__(self):
p, q = self.p, self.q
if p < 0:
return -(-p//q)
return p//q

def __eq__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy != other  -->  not ==
if isinstance(other, NumberSymbol):
if other.is_irrational:
return False
return other.__eq__(self)
if isinstance(other, Number):
if isinstance(other, Float):
return mlib.mpf_eq(self._as_mpf_val(other._prec), other._mpf_)
elif isinstance(other, Rational):
return self.p == other.p and self.q == other.q
return False

def __ne__(self, other):
return not self.__eq__(other)

def __gt__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  --> not <
if isinstance(other, NumberSymbol):
return other.__le__(self)
if other.is_real and other.is_number and not isinstance(other, Rational):
other = other.evalf()
if isinstance(other, Number):
if isinstance(other, Float):
return bool(mlib.mpf_gt(
self._as_mpf_val(other._prec), other._mpf_))
return bool(self.p*other.q > self.q*other.p)
return Expr.__gt__(self, other)

def __ge__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  -->  not <=
if isinstance(other, NumberSymbol):
return other.__lt__(self)
if other.is_real and other.is_number and not isinstance(other, Rational):
other = other.evalf()
if isinstance(other, Number):
if isinstance(other, Float):
return bool(mlib.mpf_ge(
self._as_mpf_val(other._prec), other._mpf_))
return bool(self.p*other.q >= self.q*other.p)
return Expr.__ge__(self, other)

def __lt__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  --> not <
if isinstance(other, NumberSymbol):
return other.__ge__(self)
if other.is_real and other.is_number and not isinstance(other, Rational):
other = other.evalf()
if isinstance(other, Number):
if isinstance(other, Float):
return bool(mlib.mpf_lt(
self._as_mpf_val(other._prec), other._mpf_))
return bool(self.p*other.q < self.q*other.p)
return Expr.__lt__(self, other)

def __le__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  -->  not <=
if isinstance(other, NumberSymbol):
return other.__gt__(self)
if other.is_real and other.is_number and not isinstance(other, Rational):
other = other.evalf()
if isinstance(other, Number):
if isinstance(other, Float):
return bool(mlib.mpf_le(
self._as_mpf_val(other._prec), other._mpf_))
return bool(self.p*other.q <= self.q*other.p)
return Expr.__le__(self, other)

def __hash__(self):
return super(Rational, self).__hash__()

[docs]    def factors(self, limit=None, use_trial=True,
use_rho=False,
use_pm1=False,
verbose=False,
visual=False):
"""A wrapper to factorint which return factors of self that are
smaller than limit (or cheap to compute). Special methods of
factoring are disabled by default so that only trial division is used.
"""
from sympy.ntheory import factorint

f = factorint(self.p, limit=limit,
use_trial=use_trial,
use_rho=use_rho,
use_pm1=use_pm1,
verbose=verbose).copy()
f = defaultdict(int, f)
for p, e in list(factorint(self.q, limit=limit,
use_trial=use_trial,
use_rho=use_rho,
use_pm1=use_pm1,
verbose=verbose).items()):
f[p] += -e

if len(f) > 1 and 1 in f:
del f
if not f:
f = {1: 1}
if not visual:
return dict(f)
else:
if -1 in f:
f.pop(-1)
args = [S.NegativeOne]
else:
args = []
args.extend([Pow(*i, **{'evaluate':False})
for i in sorted(f.items())])
return Mul(*args, **{'evaluate':False})

[docs]    def gcd(self, other):
"""Compute greatest common divisor of input arguments. """
if type(other) in (int, int):
p = igcd(self.p, other)

if self.is_Integer:
return Integer(p)
else:
return Rational(p, self.q)
else:
other = _sympify(other)

if other.is_Rational:
p = igcd(self.p, other.p)

if other.is_Integer:
if self.is_Integer:
return Integer(p)
else:
return Rational(p, self.q)
else:
if self.is_Integer:
return Rational(p, other.q)
else:
return Rational(p, ilcm(self.q, other.q))
elif other.is_Number:
return S.One
else:
raise TypeError("expected integer or rational, got %s" % other)

[docs]    def lcm(self, other):
"""Compute least common multiple of input arguments. """
if type(other) in (int, int):
return Integer(ilcm(self.p, other))
else:
other = _sympify(other)

if other.is_Rational:
p = ilcm(self.p, other.p)

if self.is_Integer or other.is_Integer:
return Integer(p)
else:
return Rational(p, igcd(self.q, other.q))
elif other.is_Number:
return self*other
else:
raise TypeError("expected integer or rational, got %s" % other)

[docs]    def cofactors(self, other):
"""Compute GCD and cofactors of input arguments. """
other = _sympify(other)
gcd = self.gcd(other)

if gcd is S.One:
return gcd, self, other
else:
return gcd, self/gcd, other/gcd

def as_numer_denom(self):
return Integer(self.p), Integer(self.q)

def _sage_(self):
import sage.all as sage
return sage.Integer(self.p)/sage.Integer(self.q)

"""Return the tuple (R, self/R) where R is the positive Rational
extracted from self.

Examples
========

>>> from sympy import S
>>> (S(-3)/2).as_content_primitive()
(3/2, -1)

See docstring of Expr.as_content_primitive for more examples.
"""

if self:
if self.is_positive:
return self, S.One
return -self, S.NegativeOne
return S.One, self

# int -> Integer
_intcache = {}

# TODO move this tracing facility to sympy/core/trace.py  ?
def _intcache_printinfo():
ints = sorted(_intcache.keys())
nhit = _intcache_hits
nmiss= _intcache_misses

if nhit == 0 and nmiss == 0:
print()
print('Integer cache statistic was not collected')
return

miss_ratio = float(nmiss) / (nhit+nmiss)

print()
print('Integer cache statistic')
print('-----------------------')
print()
print('#items: %i' % len(ints))
print()
print(' #hit   #miss               #total')
print()
print('%5i   %5i (%7.5f %%)   %5i' % (nhit, nmiss, miss_ratio*100, nhit + nmiss))
print()
print(ints)

_intcache_hits = 0
_intcache_misses = 0

def int_trace(f):
import os
if os.getenv('SYMPY_TRACE_INT', 'no').lower() != 'yes':
return f

def Integer_tracer(cls, i):
global _intcache_hits, _intcache_misses

try:
_intcache_hits += 1
return _intcache[i]
except KeyError:
_intcache_hits -= 1
_intcache_misses += 1

return f(cls, i)

# also we want to hook our _intcache_printinfo into sys.atexit
import atexit
atexit.register(_intcache_printinfo)

return Integer_tracer

[docs]class Integer(Rational):

q = 1
is_integer = True

is_Integer = True

__slots__ = ['p']

def _as_mpf_val(self, prec):
return mlib.from_int(self.p, prec)

def _mpmath_(self, prec, rnd):
return mpmath.make_mpf(self._as_mpf_val(prec))

# TODO caching with decorator, but not to degrade performance
@int_trace
def __new__(cls, i):
if isinstance(i, str):
i = i.replace(' ', '')
# whereas we cannot, in general, make a Rational from an
# arbitrary expression, we can make an Integer unambiguously
# (except when a non-integer expression happens to round to
# an integer). So we proceed by taking int() of the input and
# let the int routines determine whether the expression can
# be made into an int or whether an error should be raised.
ival = int(i)
try:
return _intcache[ival]
except KeyError:
# We only work with well-behaved integer types. This converts, for
# example, numpy.int32 instances.
obj = Expr.__new__(cls)
obj.p = ival

_intcache[ival] = obj
return obj

def __getnewargs__(self):
return (self.p,)

# Arithmetic operations are here for efficiency
def __int__(self):
return self.p

def __neg__(self):
return Integer(-self.p)

def __abs__(self):
if self.p >= 0:
return self
else:
return Integer(-self.p)

def __divmod__(self, other):
from .containers import Tuple
if isinstance(other, Integer):
return Tuple(*(divmod(self.p, other.p)))
else:
return Number.__divmod__(self, other)

def __rdivmod__(self, other):
from .containers import Tuple
if isinstance(other, int):
return Tuple(*(divmod(other, self.p)))
else:
try:
other = Number(other)
except TypeError:
msg = "unsupported operand type(s) for divmod(): '%s' and '%s'"
oname = type(other).__name__
sname = type(self).__name__
raise TypeError(msg % (oname, sname))
return Number.__divmod__(other, self)

# TODO make it decorator + bytecodehacks?
if isinstance(other, int):
return Integer(self.p + other)
elif isinstance(other, Integer):
return Integer(self.p + other.p)

if isinstance(other, int):
return Integer(other + self.p)

def __sub__(self, other):
if isinstance(other, int):
return Integer(self.p - other)
elif isinstance(other, Integer):
return Integer(self.p - other.p)
return Rational.__sub__(self, other)

def __rsub__(self, other):
if isinstance(other, int):
return Integer(other - self.p)
return Rational.__rsub__(self, other)

def __mul__(self, other):
if isinstance(other, int):
return Integer(self.p*other)
elif isinstance(other, Integer):
return Integer(self.p*other.p)
return Rational.__mul__(self, other)

def __rmul__(self, other):
if isinstance(other, int):
return Integer(other*self.p)
return Rational.__mul__(self, other)

def __mod__(self, other):
if isinstance(other, int):
return Integer(self.p % other)
elif isinstance(other, Integer):
return Integer(self.p % other.p)
return Rational.__mod__(self, other)

def __rmod__(self, other):
if isinstance(other, int):
return Integer(other % self.p)
elif isinstance(other, Integer):
return Integer(other.p % self.p)
return Rational.__rmod__(self, other)

def __eq__(self, other):
if isinstance(other, int):
return (self.p == other)
elif isinstance(other, Integer):
return (self.p == other.p)
return Rational.__eq__(self, other)

def __ne__(self, other):
return not self.__eq__(other)

def __gt__(self, other):
if isinstance(other, int):
return (self.p >  other)
elif isinstance(other, Integer):
return (self.p >  other.p)
return Rational.__gt__(self, other)

def __lt__(self, other):
if isinstance(other, int):
return (self.p <  other)
elif isinstance(other, Integer):
return (self.p <  other.p)
return Rational.__lt__(self, other)

def __ge__(self, other):
if isinstance(other, int):
return (self.p >= other)
elif isinstance(other, Integer):
return (self.p >= other.p)
return Rational.__ge__(self, other)

def __le__(self, other):
if isinstance(other, int):
return (self.p <= other)
elif isinstance(other, Integer):
return (self.p <= other.p)
return Rational.__le__(self, other)

def __hash__(self):
return super(Integer, self).__hash__()

def __index__(self):
return self.p

########################################

def _eval_is_odd(self):
return bool(self.p % 2)

def _eval_power(self, expt):
"""
Tries to do some simplifications on self**expt

Returns None if no further simplifications can be done

When exponent is a fraction (so we have for example a square root),
we try to find a simpler representation by factoring the argument
up to factors of 2**15, e.g.

- sqrt(4) becomes 2
- sqrt(-4) becomes 2*I
- (2**(3+7)*3**(6+7))**Rational(1,7) becomes 6*18**(3/7)

Further simplification would require a special call to factorint on
the argument which is not done here for sake of speed.

"""
from sympy import perfect_power

if expt is S.Infinity:
if self.p > S.One:
return S.Infinity
# cases -1, 0, 1 are done in their respective classes
return S.Infinity + S.ImaginaryUnit*S.Infinity
if expt is S.NegativeInfinity:
return Rational(1, self)**S.Infinity
if not isinstance(expt, Number):
# simplify when expt is even
# (-2)**k --> 2**k
if self.is_negative and expt.is_even:
return (-self)**expt
if not isinstance(expt, Rational):
return
if expt is S.Half and self < 0:
# we extract I for this special case since everyone is doing so
return S.ImaginaryUnit*Pow(-self, expt)
if expt < 0:
# invert base and change sign on exponent
ne = -expt
if self < 0:
if expt.q != 1:
return -(S.NegativeOne)**((expt.p % expt.q) / \
S(expt.q))*Rational(1, -self)**ne
else:
return (S.NegativeOne)**ne*Rational(1, -self)**ne
else:
return Rational(1, self.p)**ne
# see if base is a perfect root, sqrt(4) --> 2
x, xexact = integer_nthroot(abs(self.p), expt.q)
if xexact:
# if it's a perfect root we've finished
result = Integer(x**abs(expt.p))
if self < 0:
result*= (-1)**expt
return result

# The following is an algorithm where we collect perfect roots
# from the factors of base.

# if it's not an nth root, it still might be a perfect power
b_pos = int(abs(self.p))
p = perfect_power(b_pos)
if p is not False:
dict = {p: p}
else:
dict = Integer(self).factors(limit=2**15)

# now process the dict of factors
if self.is_negative:
dict[-1] = 1
out_int = 1 # integer part
sqr_int = 1
sqr_gcd = 0
sqr_dict = {}
for prime, exponent in list(dict.items()):
exponent *= expt.p
# remove multiples of expt.q: (2**12)**(1/10) -> 2*(2**2)**(1/10)
div_e, div_m = divmod(exponent, expt.q)
if div_e > 0:
out_int *= prime**div_e
if div_m > 0:
# see if the reduced exponent shares a gcd with e.q
# (2**2)**(1/10) -> 2**(1/5)
g = igcd(div_m, expt.q)
if g != 1:
else:
sqr_dict[prime] = div_m
# identify gcd of remaining powers
for p, ex in sqr_dict.items():
if sqr_gcd == 0:
sqr_gcd = ex
else:
sqr_gcd = igcd(sqr_gcd, ex)
if sqr_gcd == 1:
break
for k, v in sqr_dict.items():
sqr_int *= k**(v//sqr_gcd)
if sqr_int == self and out_int == 1 and out_rad == 1:
result = None
else:
return result

def _eval_is_prime(self):
from sympy.ntheory import isprime

return isprime(self)

def as_numer_denom(self):
return self, S.One

def __floordiv__(self, other):
return Integer(self.p // Integer(other).p)

def __rfloordiv__(self, other):
return Integer(Integer(other).p // self.p)

[docs]    def factorial(self):
"""Compute factorial of self. """
from sympy.functions.combinatorial.factorials import factorial
return Integer(factorial(int(self)))

[docs]    def isqrt(self):
"""Compute integer square root of self. """
return Integer(mlib.isqrt(int(self)))

[docs]    def half_gcdex(self, other):
"""Half Extended Euclidean Algorithm. """
s, _, h = self.gcdex(other)
return s, h

[docs]    def gcdex(self, other):
"""Extended Euclidean Algorithm. """
if isinstance(other, int):
return tuple(map(Integer, igcdex(int(self), other)))
b = _sympify(other)
if b.is_Integer:
return tuple(map(Integer, igcdex(int(self), int(b))))
else:
raise ValueError("expected an integer, got %s" % b)

[docs]    def invert(self, other):
"""Invert self modulo other, if possible. """
if isinstance(other, int):
a, b = int(self), other
else:
b = _sympify(other)

if b.is_Integer:
a, b = int(self), int(b)
else:
raise ValueError("expected an integer, got %s" % b)

s, _, h = igcdex(a, b)

if h == 1:
return Integer(s % b)
else:
raise ZeroDivisionError("zero divisor")

converter[int] = converter[int] = Integer

class RationalConstant(Rational):
"""
Abstract base class for rationals with specific behaviors

Derived classes must define class attributes p and q and should probably all
be singletons.
"""
__slots__ = []

def __new__(cls):
return AtomicExpr.__new__(cls)

class IntegerConstant(Integer):
__slots__ = []

def __new__(cls):
return AtomicExpr.__new__(cls)

class Zero(IntegerConstant, metaclass=Singleton):
p = 0
q = 1
is_positive = False
is_negative = False
is_finite = False
is_zero = True
is_composite = False

__slots__ = []

@staticmethod
def __abs__():
return S.Zero

@staticmethod
def __neg__():
return S.Zero

@_sympifyit('other', NotImplemented)
def __mul__(self, other):
if other is S.NaN or \
other is S.NegativeInfinity or \
other is S.Infinity or \
other is S.ComplexInfinity:
return S.NaN
return S.Zero

def _eval_power(self, expt):
if expt.is_positive:
return self
if expt.is_negative:
return S.Infinity
if expt.is_real is False:
return S.NaN
# infinities are already handled with pos and neg
# tests above; now throw away leading numbers on Mul
# exponent
coeff, terms = expt.as_coeff_Mul()
if coeff.is_negative:
return S.Infinity**terms
if coeff is not S.One: # there is a Number to discard
return self**terms

def _eval_order(self, *symbols):
# Order(0,x) -> 0
return self

def __bool__(self):
return False

class One(IntegerConstant, metaclass=Singleton):
p = 1
q = 1

__slots__ = []

@staticmethod
def __abs__():
return S.One

@staticmethod
def __neg__():
return S.NegativeOne

def _eval_power(self, expt):
return self

def _eval_order(self, *symbols):
return

@staticmethod
def factors(limit=None, use_trial=True,
use_rho=False,
use_pm1=False,
verbose=False,
visual=False):
if visual:
return S.One
return {1: 1}

class NegativeOne(IntegerConstant, metaclass=Singleton):
p = -1
q = 1

__slots__ = []

@staticmethod
def __abs__():
return S.One

@staticmethod
def __neg__():
return S.One

def _eval_power(self, expt):
if expt.is_odd:
return S.NegativeOne
if expt.is_even:
return S.One
if isinstance(expt, Number):
if isinstance(expt, Float):
return Float(-1.0)**expt
if expt is S.NaN:
return S.NaN
if expt is S.Infinity or expt is S.NegativeInfinity:
return S.NaN
if expt is S.Half:
return S.ImaginaryUnit
if isinstance(expt, Rational):
if expt.q == 2:
return S.ImaginaryUnit**Integer(expt.p)
i, r = divmod(expt.p, expt.q)
if i:
return self**i*self**Rational(r, expt.q)
return

class Half(RationalConstant, metaclass=Singleton):
p = 1
q = 2

__slots__ = []

@staticmethod
def __abs__():
return S.Half

class Infinity(Number, metaclass=Singleton):
is_commutative   = True
is_positive      = True
is_bounded       = False
is_finite        = False
is_infinitesimal = False
is_integer       = None
is_rational      = None
is_odd           = None

__slots__ = []

def __new__(cls):
return AtomicExpr.__new__(cls)

@_sympifyit('other', NotImplemented)
if isinstance(other, Number):
if other is S.NegativeInfinity or other is S.NaN:
return S.NaN
elif other.is_Float:
if other == Float('-inf') or other._mpf_ == fnan:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
else:
return Float('inf')
else:
return S.Infinity
return NotImplemented

@_sympifyit('other', NotImplemented)
def __sub__(self, other):
if isinstance(other, Number):
if other is S.Infinity or other is S.NaN:
return S.NaN
elif other.is_Float:
if other == Float('inf') or other._mpf_ == fnan:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
else:
return Float('inf')
else:
return S.Infinity
return NotImplemented

@_sympifyit('other', NotImplemented)
def __mul__(self, other):
if isinstance(other, Number):
if other is S.Zero or other is S.NaN:
return S.NaN
elif other.is_Float:
if other._mpf_ == fnan or other == 0:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
if other > 0:
return Float('inf')
else:
return Float('-inf')
else:
if other > 0:
return S.Infinity
else:
return S.NegativeInfinity
return NotImplemented
__rmul__ = __mul__

@_sympifyit('other', NotImplemented)
def __div__(self, other):
if isinstance(other, Number):
if other is S.Infinity or \
other is S.NegativeInfinity or \
other is S.NaN:
return S.NaN
elif other.is_Float:
if other == Float('-inf') or \
other == Float('inf') or \
other._mpf_ == fnan:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
elif other >= 0:
return Float('inf')
else:
return Float('-inf')
else:
if other >= 0:
return S.Infinity
else:
return S.NegativeInfinity
return NotImplemented

__truediv__ = __div__

def __abs__(self):
return S.Infinity

def __neg__(self):
return S.NegativeInfinity

def _eval_power(self, expt):
"""
expt is symbolic object but not equal to 0 or 1.

================ ======= ==============================
Expression       Result  Notes
================ ======= ==============================
oo ** nan    nan
oo ** -p     0   p is number, oo
================ ======= ==============================

"""
if expt.is_positive:
return S.Infinity
if expt.is_negative:
return S.Zero
if expt is S.NaN:
return S.NaN

if expt.is_number:
return self**expt.evalf()

def _as_mpf_val(self, prec):
return mlib.finf

def _sage_(self):
import sage.all as sage
return sage.oo

def __hash__(self):
return super(Infinity, self).__hash__()

def __eq__(self, other):
return other is S.Infinity

def __ne__(self, other):
return other is not S.Infinity

def __lt__(self, other):
return False

def __le__(self, other):
return other is S.Infinity

def __gt__(self, other):
return other is not S.Infinity

def __ge__(self, other):
return True

def __mod__(self, other):
return S.NaN

__rmod__ = __mod__

oo = S.Infinity

class NegativeInfinity(Number, metaclass=Singleton):
is_commutative   = True
is_real          = True
is_positive      = False
is_bounded       = False
is_finite        = False
is_infinitesimal = False
is_integer       = None
is_rational      = None

__slots__ = []

def __new__(cls):
return AtomicExpr.__new__(cls)

@_sympifyit('other', NotImplemented)
if isinstance(other, Number):
if other is S.Infinity or other is S.NaN:
return S.NaN
elif other.is_Float:
if other == Float('inf') or other._mpf_ == fnan:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
else:
return Float('-inf')
else:
return S.NegativeInfinity
return NotImplemented

@_sympifyit('other', NotImplemented)
def __sub__(self, other):
if isinstance(other, Number):
if other is S.NegativeInfinity or other is S.NaN:
return S.NaN
elif other.is_Float:
if other == Float('-inf') or other._mpf_ == fnan:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
else:
return Float('-inf')
else:
return S.NegativeInfinity
return NotImplemented

@_sympifyit('other', NotImplemented)
def __mul__(self, other):
if isinstance(other, Number):
if other is S.Zero or other is S.NaN:
return S.NaN
elif other.is_Float:
if other._mpf_ == fnan or other == 0:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
elif other > 0:
return Float('-inf')
else:
return Float('inf')
else:
if other > 0:
return S.NegativeInfinity
else:
return S.Infinity
return NotImplemented
__rmul__ = __mul__

@_sympifyit('other', NotImplemented)
def __div__(self, other):
if isinstance(other, Number):
if other is S.Infinity or \
other is S.NegativeInfinity or \
other is S.NaN:
return S.NaN
elif other.is_Float:
if other == Float('-inf') or \
other == Float('inf') or \
other == Float('nan') or \
other._mpf_ == fnan:
#Used workaround because Float('nan') == Float('nan') return False
return Float('nan')
elif other >= 0:
return Float('-inf')
else:
return Float('inf')
else:
if other >= 0:
return S.NegativeInfinity
else:
return S.Infinity
return NotImplemented

__truediv__ = __div__

def __abs__(self):
return S.Infinity

def __neg__(self):
return S.Infinity

def _eval_power(self, expt):
"""
expt is symbolic object but not equal to 0 or 1.

================ ======= ==============================
Expression       Result  Notes
================ ======= ==============================
(-oo) ** nan nan
(-oo) ** oo  nan
(-oo) ** -oo nan
(-oo) ** e   oo  e is positive even integer
(-oo) ** o   -oo o is positive odd integer
================ ======= ==============================

"""
if isinstance(expt, Number):
if expt is S.NaN or \
expt is S.Infinity or \
expt is S.NegativeInfinity:
return S.NaN

if isinstance(expt, Integer) and expt.is_positive:
if expt.is_odd:
return S.NegativeInfinity
else:
return S.Infinity

return S.NegativeOne**expt*S.Infinity**expt

def _as_mpf_val(self, prec):
return mlib.fninf

def _sage_(self):
import sage.all as sage
return -(sage.oo)

def __hash__(self):
return super(NegativeInfinity, self).__hash__()

def __eq__(self, other):
return other is S.NegativeInfinity

def __ne__(self, other):
return other is not S.NegativeInfinity

def __lt__(self, other):
return other is not S.NegativeInfinity

def __le__(self, other):
return True

def __gt__(self, other):
return False

def __ge__(self, other):
return other is S.NegativeInfinity

class NaN(Number, metaclass=Singleton):
"""
Not a Number.

This represents the corresponding data type to floating point nan, which
is defined in the IEEE 754 floating point standard, and corresponds to the
Python float('nan').

NaN serves as a place holder for numeric values that are indeterminate,
but not infinite.  Most operations on nan, produce another nan.  Most
indeterminate forms, such as 0/0 or oo - oo produce nan.  Three
exceptions are 0**0, 1**oo, and oo**0, which all produce 1
(this is consistent with Python's float).

NaN is a singleton, and can be accessed by S.NaN, or can be imported
as nan.

Examples
========

>>> from sympy import nan, S, oo
>>> nan is S.NaN
True
>>> oo - oo
nan
>>> nan + 1
nan

References
==========

- http://en.wikipedia.org/wiki/NaN

"""

is_commutative = True
is_real = None
is_rational = None
is_integer = None
is_comparable = False
is_finite = None
is_bounded = None
is_zero = None
is_prime = None
is_positive = None
is_negative = None

__slots__ = []

def __new__(cls):
return AtomicExpr.__new__(cls)

@_sympifyit('other', NotImplemented)
return self

@_sympifyit('other', NotImplemented)
def __sub__(self, other):
return self

@_sympifyit('other', NotImplemented)
def __mul__(self, other):
return self

@_sympifyit('other', NotImplemented)
def __div__(self, other):
return self

__truediv__ = __div__

def _as_mpf_val(self, prec):
return mlib.fnan

def _sage_(self):
import sage.all as sage
return sage.NaN

def __hash__(self):
return super(NaN, self).__hash__()

def __eq__(self, other):
return other is S.NaN

def __ne__(self, other):
return other is not S.NaN

def __gt__(self, other):
return False

def __ge__(self, other):
return False

def __lt__(self, other):
return False

def __le__(self, other):
return False

nan = S.NaN

class ComplexInfinity(AtomicExpr, metaclass=Singleton):
is_commutative = True
is_bounded = False
is_real = None
is_number = False

__slots__ = []

def __new__(cls):
return AtomicExpr.__new__(cls)

@staticmethod
def __abs__():
return S.Infinity

@staticmethod
def __neg__():
return S.ComplexInfinity

def _eval_power(self, expt):
if expt is S.ComplexInfinity:
return S.NaN

if isinstance(expt, Number):
if expt is S.Zero:
return S.NaN
else:
if expt.is_positive:
return S.ComplexInfinity
else:
return S.Zero

zoo = S.ComplexInfinity

[docs]class NumberSymbol(AtomicExpr, metaclass=Singleton):
is_commutative = True
is_bounded = True
is_finite = True
is_number = True

__slots__ = []

is_NumberSymbol = True

def __new__(cls):
return AtomicExpr.__new__(cls)

[docs]    def approximation(self, number_cls):
""" Return an interval with number_cls endpoints
that contains the value of NumberSymbol.
If not implemented, then return None.
"""

def _eval_evalf(self, prec):
return Float._new(self._as_mpf_val(prec), prec)

def __eq__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy != other  -->  not ==
if self is other:
return True
if isinstance(other, Number) and self.is_irrational:
return False

return False    # NumberSymbol != non-(Number|self)

def __ne__(self, other):
return not self.__eq__(other)

def __lt__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  --> not <
if self is other:
return False
if isinstance(other, Number):
approx = self.approximation_interval(other.__class__)
if approx is not None:
l,u = approx
if other < l:
return False
if other > u:
return True
return self.evalf() < other
if other.is_real and other.is_number:
other = other.evalf()
return self.evalf() < other
return Expr.__lt__(self, other)

def __le__(self, other):
try:
other = _sympify(other)
except SympifyError:
return False    # sympy > other  --> not <=
if self is other:
return True
if other.is_real and other.is_number:
other = other.evalf()
if isinstance(other, Number):
return self.evalf() <= other
return Expr.__le__(self, other)

def __gt__(self, other):
return (-self) < (-other)

def __ge__(self, other):
return (-self) <= (-other)

def __int__(self):
# subclass with appropriate return value
raise NotImplementedError

def __hash__(self):
return super(NumberSymbol, self).__hash__()

class Exp1(NumberSymbol, metaclass=Singleton):
is_real = True
is_positive = True
is_negative = False # XXX Forces is_negative/is_nonnegative
is_irrational = True

__slots__ = []

@staticmethod
def __abs__():
return S.Exp1

def __int__(self):
return 2

def _as_mpf_val(self, prec):
return mpf_e(prec)

def approximation_interval(self, number_cls):
if issubclass(number_cls,Integer):
return (Integer(2),Integer(3))
elif issubclass(number_cls,Rational):
pass

def _eval_power(self, expt):
return C.exp(expt)

def _sage_(self):
import sage.all as sage
return sage.e
E = S.Exp1

class Pi(NumberSymbol, metaclass=Singleton):
is_real = True
is_positive = True
is_negative = False
is_irrational = True

__slots__ = []

@staticmethod
def __abs__():
return S.Pi

def __int__(self):
return 3

def _as_mpf_val(self, prec):
return mpf_pi(prec)

def approximation_interval(self, number_cls):
if issubclass(number_cls, Integer):
return (Integer(3), Integer(4))
elif issubclass(number_cls, Rational):
return (Rational(223,71), Rational(22,7))

def _sage_(self):
import sage.all as sage
return sage.pi
pi = S.Pi

class GoldenRatio(NumberSymbol, metaclass=Singleton):
is_real = True
is_positive = True
is_negative = False
is_irrational = True

__slots__ = []

def __int__(self):
return 1

def _as_mpf_val(self, prec):
# XXX track down why this has to be increased
rv = mlib.from_man_exp(phi_fixed(prec+10), -prec-10)
return mpf_norm(rv, prec)

def _eval_expand_func(self, **hints):
from sympy import sqrt
return S.Half + S.Half*sqrt(5)

def approximation_interval(self, number_cls):
if issubclass(number_cls, Integer):
return (S.One, Rational(2))
elif issubclass(number_cls, Rational):
pass

def _sage_(self):
import sage.all as sage
return sage.golden_ratio

class EulerGamma(NumberSymbol, metaclass=Singleton):
is_real = True
is_positive = True
is_negative = False
is_irrational = None

__slots__ = []

def __int__(self):
return 0

def _as_mpf_val(self, prec):
# XXX track down why this has to be increased
v = mlib.libhyper.euler_fixed(prec+10)
rv = mlib.from_man_exp(v, -prec-10)
return mpf_norm(rv, prec)

def approximation_interval(self, number_cls):
if issubclass(number_cls, Integer):
return (S.Zero, S.One)
elif issubclass(number_cls, Rational):
return (S.Half, Rational(3, 5))

def _sage_(self):
import sage.all as sage
return sage.euler_gamma

class Catalan(NumberSymbol, metaclass=Singleton):
is_real = True
is_positive = True
is_negative = False
is_irrational = None

__slots__ = []

def __int__(self):
return 0

def _as_mpf_val(self, prec):
# XXX track down why this has to be increased
v = mlib.catalan_fixed(prec+10)
rv = mlib.from_man_exp(v, -prec-10)
return mpf_norm(rv, prec)

def approximation_interval(self, number_cls):
if issubclass(number_cls, Integer):
return (S.Zero, S.One)
elif issubclass(number_cls, Rational):
return (Rational(9, 10), S.One)

def _sage_(self):
import sage.all as sage
return sage.catalan

class ImaginaryUnit(AtomicExpr, metaclass=Singleton):
is_commutative = True
is_imaginary = True
is_bounded = True
is_finite = True
is_number = True

__slots__ = []

@staticmethod
def __abs__():
return S.One

def _eval_evalf(self, prec):
return self

def _eval_conjugate(self):
return -S.ImaginaryUnit

def _eval_power(self, expt):
"""
b is I = sqrt(-1)
e is symbolic object but not equal to 0, 1

I**r -> (-1)**(r/2) -> exp(r/2*Pi*I) -> sin(Pi*r/2) + cos(Pi*r/2)*I, r is decimal
I**0 mod 4 -> 1
I**1 mod 4 -> I
I**2 mod 4 -> -1
I**3 mod 4 -> -I
"""

if isinstance(expt, Number):
if isinstance(expt, Integer):
expt = expt.p % 4
if expt == 0:
return S.One
if expt == 1:
return S.ImaginaryUnit
if expt == 2:
return -S.One
return -S.ImaginaryUnit
return (S.NegativeOne)**(expt*S.Half)
return

def as_base_exp(self):
return S.NegativeOne, S.Half

def _sage_(self):
import sage.all as sage
return sage.I

I = S.ImaginaryUnit

try:
# fractions is only available for python 2.6+
import fractions

def sympify_fractions(f):
return Rational(f.numerator, f.denominator)

converter[fractions.Fraction] = sympify_fractions
except ImportError:
pass

try:
import gmpy

def sympify_mpz(x):
return Integer(int(x))

def sympify_mpq(x):
return Rational(int(x.numer()), int(x.denom()))

converter[type(gmpy.mpz(1))] = sympify_mpz
converter[type(gmpy.mpq(1, 2))] = sympify_mpq
except ImportError:
pass

def sympify_mpmath(x):
return Expr._from_mpmath(x, x.context.prec)

converter[mpnumeric] = sympify_mpmath

def sympify_complex(a):
real, imag = list(map(sympify, (a.real, a.imag)))
return real + S.ImaginaryUnit*imag

converter[complex] = sympify_complex

_intcache = S.Zero
_intcache = S.One
_intcache[-1]= S.NegativeOne

from .power import Pow, integer_nthroot
from .mul import Mul
Mul.identity = One()
`