# Source code for sympy.core.mod

from __future__ import print_function, division

from sympy.core.numbers import nan
from .function import Function

[docs]class Mod(Function):
"""Represents a modulo operation on symbolic expressions.

Receives two arguments, dividend p and divisor q.

The convention used is the same as Python's: the remainder always has the
same sign as the divisor.

Examples
========

>>> from sympy.abc import x, y
>>> x**2 % y
Mod(x**2, y)
>>> _.subs({x: 5, y: 6})
1

"""

@classmethod
def eval(cls, p, q):
from sympy.core.mul import Mul
from sympy.core.singleton import S
from sympy.core.exprtools import gcd_terms
from sympy.polys.polytools import gcd

def doit(p, q):
"""Try to return p % q if both are numbers or +/-p is known
to be less than or equal q.
"""

if q == S.Zero:
raise ZeroDivisionError("Modulo by zero")
if p.is_infinite or q.is_infinite or p is nan or q is nan:
return nan
if p == S.Zero or p == q or p == -q or (p.is_integer and q == 1):
return S.Zero

if q.is_Number:
if p.is_Number:
return (p % q)
if q == 2:
if p.is_even:
return S.Zero
elif p.is_odd:
return S.One

if hasattr(p, '_eval_Mod'):
rv = getattr(p, '_eval_Mod')(q)
if rv is not None:
return rv

# by ratio
r = p/q
try:
d = int(r)
except TypeError:
pass
else:
if type(d) is int:
rv = p - d*q
if (rv*q < 0) == True:
rv += q
return rv

# by difference
# -2|q| < p < 2|q|
d = abs(p)
for _ in range(2):
d -= abs(q)
if d.is_negative:
if q.is_positive:
if p.is_positive:
return d + q
elif p.is_negative:
return -d
elif q.is_negative:
if p.is_positive:
return d
elif p.is_negative:
return -d + q
break

rv = doit(p, q)
if rv is not None:
return rv

# denest
if isinstance(p, cls):
qinner = p.args[1]
if qinner % q == 0:
return cls(p.args[0], q)
elif (qinner*(q - qinner)).is_nonnegative:
# |qinner| < |q| and have same sign
return p
elif isinstance(-p, cls):
qinner = (-p).args[1]
if qinner % q == 0:
return cls(-(-p).args[0], q)
elif (qinner*(q + qinner)).is_nonpositive:
# |qinner| < |q| and have different sign
return p
# separating into modulus and non modulus
both_l = non_mod_l, mod_l = [], []
for arg in p.args:
both_l[isinstance(arg, cls)].append(arg)
# if q same for all
if mod_l and all(inner.args[1] == q for inner in mod_l):
return cls(net, q)

elif isinstance(p, Mul):
# separating into modulus and non modulus
both_l = non_mod_l, mod_l = [], []
for arg in p.args:
both_l[isinstance(arg, cls)].append(arg)

if mod_l and all(inner.args[1] == q for inner in mod_l):
# finding distributive term
non_mod_l = [cls(x, q) for x in non_mod_l]
mod = []
non_mod = []
for j in non_mod_l:
if isinstance(j, cls):
mod.append(j.args[0])
else:
non_mod.append(j)
prod_mod = Mul(*mod)
prod_non_mod = Mul(*non_mod)
prod_mod1 = Mul(*[i.args[0] for i in mod_l])
net = prod_mod1*prod_mod
return prod_non_mod*cls(net, q)

# XXX other possibilities?

# extract gcd; any further simplification should be done by the user
G = gcd(p, q)
if G != 1:
p, q = [
gcd_terms(i/G, clear=False, fraction=False) for i in (p, q)]
pwas, qwas = p, q

# simplify terms
# (x + y + 2) % x -> Mod(y + 2, x)
args = []
for i in p.args:
a = cls(i, q)
if a.count(cls) > i.count(cls):
args.append(i)
else:
args.append(a)
if args != list(p.args):

else:
# handle coefficients if they are not Rational
# since those are not handled by factor_terms
# e.g. Mod(.6*x, .3*y) -> 0.3*Mod(2*x, y)
cp, p = p.as_coeff_Mul()
cq, q = q.as_coeff_Mul()
ok = False
if not cp.is_Rational or not cq.is_Rational:
r = cp % cq
if r == 0:
G *= cq
p *= int(cp/cq)
ok = True
if not ok:
p = cp*p
q = cq*q

# simple -1 extraction
if p.could_extract_minus_sign() and q.could_extract_minus_sign():
G, p, q = [-i for i in (G, p, q)]

# check again to see if p and q can now be handled as numbers
rv = doit(p, q)
if rv is not None:
return rv*G

# put 1.0 from G on inside
if G.is_Float and G == 1:
p *= G
return cls(p, q, evaluate=False)
elif G.is_Mul and G.args[0].is_Float and G.args[0] == 1:
p = G.args[0]*p
G = Mul._from_args(G.args[1:])
return G*cls(p, q, evaluate=(p, q) != (pwas, qwas))

def _eval_is_integer(self):
from sympy.core.logic import fuzzy_and, fuzzy_not
p, q = self.args
if fuzzy_and([p.is_integer, q.is_integer, fuzzy_not(q.is_zero)]):
return True

def _eval_is_nonnegative(self):
if self.args[1].is_positive:
return True

def _eval_is_nonpositive(self):
if self.args[1].is_negative:
return True