def flatten(cls, seq):
"""Return commutative, noncommutative and order arguments by
combining related terms.
** Developer Notes **
* In an expression like ``a*b*c``, python process this through sympy
as ``Mul(Mul(a, b), c)``. This can have undesirable consequences.
- Sometimes terms are not combined as one would like:
{c.f. http://code.google.com/p/sympy/issues/detail?id=1497}
>>> from sympy import Mul, sqrt
>>> from sympy.abc import x, y, z
>>> 2*(x + 1) # this is the 2-arg Mul behavior
2*x + 2
>>> y*(x + 1)*2
2*y*(x + 1)
>>> 2*(x + 1)*y # 2-arg result will be obtained first
y*(2*x + 2)
>>> Mul(2, x + 1, y) # all 3 args simultaneously processed
2*y*(x + 1)
>>> 2*((x + 1)*y) # parentheses can control this behavior
2*y*(x + 1)
Powers with compound bases may not find a single base to
combine with unless all arguments are processed at once.
Post-processing may be necessary in such cases.
{c.f. http://code.google.com/p/sympy/issues/detail?id=2629}
>>> a = sqrt(x*sqrt(y))
>>> a**3
(x*sqrt(y))**(3/2)
>>> Mul(a,a,a)
(x*sqrt(y))**(3/2)
>>> a*a*a
x*sqrt(y)*sqrt(x*sqrt(y))
>>> _.subs(a.base, z).subs(z, a.base)
(x*sqrt(y))**(3/2)
- If more than two terms are being multiplied then all the
previous terms will be re-processed for each new argument.
So if each of ``a``, ``b`` and ``c`` were :class:`Mul`
expression, then ``a*b*c`` (or building up the product
with ``*=``) will process all the arguments of ``a`` and
``b`` twice: once when ``a*b`` is computed and again when
``c`` is multiplied.
Using ``Mul(a, b, c)`` will process all arguments once.
* The results of Mul are cached according to arguments, so flatten
will only be called once for ``Mul(a, b, c)``. If you can
structure a calculation so the arguments are most likely to be
repeats then this can save time in computing the answer. For
example, say you had a Mul, M, that you wished to divide by ``d[i]``
and multiply by ``n[i]`` and you suspect there are many repeats
in ``n``. It would be better to compute ``M*n[i]/d[i]`` rather
than ``M/d[i]*n[i]`` since every time n[i] is a repeat, the
product, ``M*n[i]`` will be returned without flattening -- the
cached value will be returned. If you divide by the ``d[i]``
first (and those are more unique than the ``n[i]``) then that will
create a new Mul, ``M/d[i]`` the args of which will be traversed
again when it is multiplied by ``n[i]``.
{c.f. http://code.google.com/p/sympy/issues/detail?id=2607}
This consideration is moot if the cache is turned off.
NB
The validity of the above notes depends on the implementation
details of Mul and flatten which may change at any time. Therefore,
you should only consider them when your code is highly performance
sensitive.
"""
# apply associativity, separate commutative part of seq
c_part = [] # out: commutative factors
nc_part = [] # out: non-commutative factors
nc_seq = []
coeff = S.One # standalone term
# e.g. 3 * ...
c_powers = [] # (base,exp) n
# e.g. (x,n) for x
num_exp = [] # (num-base, exp) y
# e.g. (3, y) for ... * 3 * ...
neg1e = 0 # exponent on -1 extracted from Number-based Pow
pnum_rat = {} # (num-base, Rat-exp) 1/2
# e.g. (3, 1/2) for ... * 3 * ...
order_symbols = None
# --- PART 1 ---
#
# "collect powers and coeff":
#
# o coeff
# o c_powers
# o num_exp
# o neg1e
# o pnum_rat
#
# NOTE: this is optimized for all-objects-are-commutative case
for o in seq:
# O(x)
if o.is_Order:
o, order_symbols = o.as_expr_variables(order_symbols)
# Mul([...])
if o.is_Mul:
if o.is_commutative:
seq.extend(o.args) # XXX zerocopy?
else:
# NCMul can have commutative parts as well
for q in o.args:
if q.is_commutative:
seq.append(q)
else:
nc_seq.append(q)
# append non-commutative marker, so we don't forget to
# process scheduled non-commutative objects
seq.append(NC_Marker)
continue
# 3
elif o.is_Number:
if o is S.NaN or coeff is S.ComplexInfinity and o is S.Zero:
# we know for sure the result will be nan
return [S.NaN], [], None
elif coeff.is_Number: # it could be zoo
coeff *= o
if coeff is S.NaN:
# we know for sure the result will be nan
return [S.NaN], [], None
continue
elif o is S.ComplexInfinity:
if not coeff or coeff is S.ComplexInfinity:
# we know for sure the result will be nan
return [S.NaN], [], None
coeff = S.ComplexInfinity
continue
elif o.is_commutative:
# e
# o = b
b, e = o.as_base_exp()
# y
# 3
if o.is_Pow and b.is_Number:
# get all the factors with numeric base so they can be
# combined below, but don't combine negatives unless
# the exponent is an integer
if e.is_Rational:
if e.is_Integer:
coeff *= Pow(b, e) # it is an unevaluated power
continue
elif e.is_negative: # also a sign of an unevaluated power
seq.append(Pow(b, e))
continue
elif b.is_negative:
neg1e += e
b = -b
if b is not S.One:
pnum_rat.setdefault(b, []).append(e)
continue
elif b.is_positive or e.is_integer:
num_exp.append((b, e))
continue
c_powers.append((b,e))
# NON-COMMUTATIVE
# TODO: Make non-commutative exponents not combine automatically
else:
if o is not NC_Marker:
nc_seq.append(o)
# process nc_seq (if any)
while nc_seq:
o = nc_seq.pop(0)
if not nc_part:
nc_part.append(o)
continue
# b c b+c
# try to combine last terms: a * a -> a
o1 = nc_part.pop()
b1,e1 = o1.as_base_exp()
b2,e2 = o.as_base_exp()
new_exp = e1 + e2
# Only allow powers to combine if the new exponent is
# not an Add. This allow things like a**2*b**3 == a**5
# if a.is_commutative == False, but prohibits
# a**x*a**y and x**a*x**b from combining (x,y commute).
if b1==b2 and (not new_exp.is_Add):
o12 = b1 ** new_exp
# now o12 could be a commutative object
if o12.is_commutative:
seq.append(o12)
continue
else:
nc_seq.insert(0, o12)
else:
nc_part.append(o1)
nc_part.append(o)
# We do want a combined exponent if it would not be an Add, such as
# y 2y 3y
# x * x -> x
# We determine this if two exponents have the same term in as_coeff_mul
#
# Unfortunately, this isn't smart enough to consider combining into
# exponents that might already be adds, so things like:
# z - y y
# x * x will be left alone. This is because checking every possible
# combination can slow things down.
# gather exponents of common bases...
# in c_powers
new_c_powers = []
common_b = {} # b:e
for b, e in c_powers:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_c_powers.append((b, c*Mul(*t)))
c_powers = new_c_powers
# and in num_exp
new_num_exp = []
common_b = {} # b:e
for b, e in num_exp:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_num_exp.append((b,c*Mul(*t)))
num_exp = new_num_exp
# --- PART 2 ---
#
# o process collected powers (x**0 -> 1; x**1 -> x; otherwise Pow)
# o combine collected powers (2**x * 3**x -> 6**x)
# with numeric base
# ................................
# now we have:
# - coeff:
# - c_powers: (b, e)
# - num_exp: (2, e)
# - pnum_rat: {(1/3, [1/3, 2/3, 1/4])}
# 0 1
# x -> 1 x -> x
for b, e in c_powers:
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif not e is S.Zero:
c_part.append(Pow(b, e))
# x x x
# 2 * 3 -> 6
inv_exp_dict = {} # exp:Mul(num-bases) x x
# e.g. x:6 for ... * 2 * 3 * ...
for b, e in num_exp:
inv_exp_dict.setdefault(e, []).append(b)
for e, b in inv_exp_dict.items():
inv_exp_dict[e] = Mul(*b)
c_part.extend([Pow(b, e) for e, b in inv_exp_dict.iteritems() if e])
# b, e -> e, b
# {(1/5, [1/3]), (1/2, [1/12, 1/4]} -> {(1/3, [1/5, 1/2])}
comb_e = {}
for b, e in pnum_rat.iteritems():
comb_e.setdefault(Add(*e), []).append(b)
del pnum_rat
# process them, reducing exponents to values less than 1
# and updating coeff if necessary else adding them to
# num_rat for further processing
num_rat = []
for e, b in comb_e.iteritems():
b = Mul(*b)
if e.q == 1:
coeff *= Pow(b, e)
continue
if e.p > e.q:
e_i, ep = divmod(e.p, e.q)
coeff *= Pow(b, e_i)
e = Rational(ep, e.q)
num_rat.append((b, e))
del comb_e
# extract gcd of bases in num_rat
# 2**(1/3)*6**(1/4) -> 2**(1/3+1/4)*3**(1/4)
pnew = {}
i = 0 # steps through num_rat which may grow
while i < len(num_rat):
bi, ei = num_rat[i]
grow = []
for j in range(i + 1, len(num_rat)):
bj, ej = num_rat[j]
g = igcd(bi, bj)
if g != 1:
# 4**r1*6**r2 -> 2**(r1+r2) * 2**r1 * 3**r2
# this might have a gcd with something else
e = ei + ej
if e.q == 1:
coeff *= Pow(g, e)
else:
if e.p > e.q:
e_i, ep = divmod(e.p, e.q) # change e in place
coeff *= Pow(g, e_i)
e = Rational(ep, e.q)
grow.append((g, e))
# update the jth item
num_rat[j] = (bj//g, ej)
# update bi that we are checking with
bi = bi//g
if bi is S.One:
break
if bi is not S.One:
obj = Pow(bi, ei)
if obj.is_Number:
coeff *= obj
else:
if obj.is_Mul: # sqrt(12) -> 2*sqrt(3)
c, obj = obj.args # expecting only 2 args
coeff *= c
assert obj.is_Pow
bi, ei = obj.args
pnew.setdefault(ei, []).append(bi)
num_rat.extend(grow)
i += 1
# combine bases of the new powers
for e, b in pnew.iteritems():
pnew[e] = Mul(*b)
# see if there is a base with matching coefficient
# that the -1 can be joined with
if neg1e:
p = Pow(S.NegativeOne, neg1e)
if p.is_Number:
coeff *= p
else:
if p.is_Mul:
c, p = p.args
coeff *= c
assert p.is_Pow and p.base is S.NegativeOne
neg1e = p.args[1]
for e, b in pnew.iteritems():
if e == neg1e and b.is_positive:
pnew[e] = -b
break
else:
c_part.append(p)
# add all the pnew powers
c_part.extend([Pow(b, e) for e, b in pnew.iteritems()])
# oo, -oo
if (coeff is S.Infinity) or (coeff is S.NegativeInfinity):
new_c_part = []
coeff_sign = 1
for t in c_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_c_part.append(t)
c_part = new_c_part
new_nc_part = []
for t in nc_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_nc_part.append(t)
nc_part = new_nc_part
coeff *= coeff_sign
# zoo
if coeff is S.ComplexInfinity:
# zoo might be
# unbounded_real + bounded_im
# bounded_real + unbounded_im
# unbounded_real + unbounded_im
# and non-zero real or imaginary will not change that status.
c_part = [c for c in c_part if not (c.is_nonzero and
c.is_real is not None)]
nc_part = [c for c in nc_part if not (c.is_nonzero and
c.is_real is not None)]
# 0
elif coeff is S.Zero:
# we know for sure the result will be 0
return [coeff], [], order_symbols
# order commutative part canonically
c_part.sort(key=cmp_to_key(Basic.compare))
# current code expects coeff to be always in slot-0
if coeff is not S.One:
c_part.insert(0, coeff)
# we are done
if len(c_part)==2 and c_part[0].is_Number and c_part[1].is_Add:
# 2*(1+a) -> 2 + 2 * a
coeff = c_part[0]
c_part = [Add(*[coeff*f for f in c_part[1].args])]
return c_part, nc_part, order_symbols
def flatten(cls, seq):
# apply associativity, separate commutative part of seq
c_part = [] # out: commutative factors
nc_part = [] # out: non-commutative factors
nc_seq = []
coeff = S.One # standalone term
# e.g. 3 * ...
c_powers = [] # (base,exp) n
# e.g. (x,n) for x
num_exp = [] # (num-base, exp) y
# e.g. (3, y) for ... * 3 * ...
neg1e = 0 # exponent on -1 extracted from Number-based Pow
pnum_rat = {} # (num-base, Rat-exp) 1/2
# e.g. (3, 1/2) for ... * 3 * ...
order_symbols = None
# --- PART 1 ---
#
# "collect powers and coeff":
#
# o coeff
# o c_powers
# o num_exp
# o neg1e
# o pnum_rat
#
# NOTE: this is optimized for all-objects-are-commutative case
for o in seq:
# O(x)
if o.is_Order:
o, order_symbols = o.as_expr_variables(order_symbols)
# Mul([...])
if o.is_Mul:
if o.is_commutative:
seq.extend(o.args) # XXX zerocopy?
else:
# NCMul can have commutative parts as well
for q in o.args:
if q.is_commutative:
seq.append(q)
else:
nc_seq.append(q)
# append non-commutative marker, so we don't forget to
# process scheduled non-commutative objects
seq.append(NC_Marker)
continue
# 3
elif o.is_Number:
if o is S.NaN or coeff is S.ComplexInfinity and o is S.Zero:
# we know for sure the result will be nan
return [S.NaN], [], None
elif coeff.is_Number: # it could be zoo
coeff *= o
if coeff is S.NaN:
# we know for sure the result will be nan
return [S.NaN], [], None
continue
elif o is S.ComplexInfinity:
if not coeff or coeff is S.ComplexInfinity:
# we know for sure the result will be nan
return [S.NaN], [], None
coeff = S.ComplexInfinity
continue
elif o.is_commutative:
# e
# o = b
b, e = o.as_base_exp()
# y
# 3
if o.is_Pow and b.is_Number:
# get all the factors with numeric base so they can be
# combined below, but don't combine negatives unless
# the exponent is an integer
if e.is_Rational:
if e.is_Integer:
coeff *= Pow(b, e) # it is an unevaluated power
continue
elif e.is_negative: # also a sign of an unevaluated power
seq.append(Pow(b, e))
continue
elif b.is_negative:
neg1e += e
b = -b
if b is not S.One:
pnum_rat.setdefault(b, []).append(e)
continue
elif b.is_positive or e.is_integer:
num_exp.append((b, e))
continue
c_powers.append((b,e))
# NON-COMMUTATIVE
# TODO: Make non-commutative exponents not combine automatically
else:
if o is not NC_Marker:
nc_seq.append(o)
# process nc_seq (if any)
while nc_seq:
o = nc_seq.pop(0)
if not nc_part:
nc_part.append(o)
continue
# b c b+c
# try to combine last terms: a * a -> a
o1 = nc_part.pop()
b1,e1 = o1.as_base_exp()
b2,e2 = o.as_base_exp()
new_exp = e1 + e2
# Only allow powers to combine if the new exponent is
# not an Add. This allow things like a**2*b**3 == a**5
# if a.is_commutative == False, but prohibits
# a**x*a**y and x**a*x**b from combining (x,y commute).
if b1==b2 and (not new_exp.is_Add):
o12 = b1 ** new_exp
# now o12 could be a commutative object
if o12.is_commutative:
seq.append(o12)
continue
else:
nc_seq.insert(0, o12)
else:
nc_part.append(o1)
nc_part.append(o)
# We do want a combined exponent if it would not be an Add, such as
# y 2y 3y
# x * x -> x
# We determine this if two exponents have the same term in as_coeff_mul
#
# Unfortunately, this isn't smart enough to consider combining into
# exponents that might already be adds, so things like:
# z - y y
# x * x will be left alone. This is because checking every possible
# combination can slow things down.
# gather exponents of common bases...
# in c_powers
new_c_powers = []
common_b = {} # b:e
for b, e in c_powers:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_c_powers.append((b,c*Mul(*t)))
c_powers = new_c_powers
# and in num_exp
new_num_exp = []
common_b = {} # b:e
for b, e in num_exp:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_num_exp.append((b,c*Mul(*t)))
num_exp = new_num_exp
# --- PART 2 ---
#
# o process collected powers (x**0 -> 1; x**1 -> x; otherwise Pow)
# o combine collected powers (2**x * 3**x -> 6**x)
# with numeric base
# ................................
# now we have:
# - coeff:
# - c_powers: (b, e)
# - num_exp: (2, e)
# - pnum_rat: {(1/3, [1/3, 2/3, 1/4])}
# 0 1
# x -> 1 x -> x
for b, e in c_powers:
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif not e is S.Zero:
c_part.append(Pow(b, e))
# x x x
# 2 * 3 -> 6
inv_exp_dict = {} # exp:Mul(num-bases) x x
# e.g. x:6 for ... * 2 * 3 * ...
for b, e in num_exp:
inv_exp_dict.setdefault(e, []).append(b)
for e, b in inv_exp_dict.items():
inv_exp_dict[e] = Mul(*b)
c_part.extend([Pow(b, e) for e, b in inv_exp_dict.iteritems() if e])
# b, e -> e, b
# {(1/5, [1/3]), (1/2, [1/12, 1/4]} -> {(1/3, [1/5, 1/2])}
comb_e = {}
for b, e in pnum_rat.iteritems():
comb_e.setdefault(Add(*e), []).append(b)
del pnum_rat
# process them, reducing exponents to values less than 1
# and updating coeff if necessary else adding them to
# num_rat for further processing
num_rat = []
for e, b in comb_e.iteritems():
b = Mul(*b)
if e.q == 1:
coeff *= Pow(b, e)
continue
if e.p > e.q:
e_i, ep = divmod(e.p, e.q)
coeff *= Pow(b, e_i)
e = Rational(ep, e.q)
num_rat.append((b, e))
del comb_e
# extract gcd of bases in num_rat
# 2**(1/3)*6**(1/4) -> 2**(1/3+1/4)*3**(1/4)
pnew = {}
i = 0 # steps through num_rat which may grow
while i < len(num_rat):
bi, ei = num_rat[i]
grow = []
for j in range(i + 1, len(num_rat)):
bj, ej = num_rat[j]
g = igcd(bi, bj)
if g != 1:
# 4**r1*6**r2 -> 2**(r1+r2) * 2**r1 * 3**r2
# this might have a gcd with something else
e = ei + ej
if e.q == 1:
coeff *= Pow(g, e)
else:
if e.p > e.q:
e_i, ep = divmod(e.p, e.q) # change e in place
coeff *= Pow(g, e_i)
e = Rational(ep, e.q)
grow.append((g, e))
# update the jth item
num_rat[j] = (bj//g, ej)
# update bi that we are checking with
bi = bi//g
if bi is S.One:
break
if bi is not S.One:
obj = Pow(bi, ei)
if obj.is_Number:
coeff *= obj
else:
if obj.is_Mul: # 12**(1/2) -> 2*sqrt(3)
c, obj = obj.args # expecting only 2 args
coeff *= c
assert obj.is_Pow
bi, ei = obj.args
pnew.setdefault(ei, []).append(bi)
num_rat.extend(grow)
i += 1
# combine bases of the new powers
for e, b in pnew.iteritems():
pnew[e] = Mul(*b)
# see if there is a base with matching coefficient
# that the -1 can be joined with
if neg1e:
p = Pow(S.NegativeOne, neg1e)
if p.is_Number:
coeff *= p
else:
if p.is_Mul:
c, p = p.args
coeff *= c
assert p.is_Pow and p.base is S.NegativeOne
neg1e = p.args[1]
for e, b in pnew.iteritems():
if e == neg1e and b.is_positive:
pnew[e] = -b
break
else:
c_part.append(p)
# add all the pnew powers
c_part.extend([Pow(b, e) for e, b in pnew.iteritems()])
# oo, -oo
if (coeff is S.Infinity) or (coeff is S.NegativeInfinity):
new_c_part = []
coeff_sign = 1
for t in c_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_c_part.append(t)
c_part = new_c_part
new_nc_part = []
for t in nc_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_nc_part.append(t)
nc_part = new_nc_part
coeff *= coeff_sign
# zoo
if coeff is S.ComplexInfinity:
# zoo might be
# unbounded_real + bounded_im
# bounded_real + unbounded_im
# unbounded_real + unbounded_im
# and non-zero real or imaginary will not change that status.
c_part = [c for c in c_part if not (c.is_nonzero and
c.is_real is not None)]
nc_part = [c for c in nc_part if not (c.is_nonzero and
c.is_real is not None)]
# 0
elif coeff is S.Zero:
# we know for sure the result will be 0
return [coeff], [], order_symbols
# order commutative part canonically
c_part.sort(key=cmp_to_key(Basic.compare))
# current code expects coeff to be always in slot-0
if coeff is not S.One:
c_part.insert(0, coeff)
# we are done
if len(c_part)==2 and c_part[0].is_Number and c_part[1].is_Add:
# 2*(1+a) -> 2 + 2 * a
coeff = c_part[0]
c_part = [Add(*[coeff*f for f in c_part[1].args])]
return c_part, nc_part, order_symbols
def flatten(cls, seq):
# apply associativity, separate commutative part of seq
c_part = [] # out: commutative factors
nc_part = [] # out: non-commutative factors
nc_seq = []
coeff = S.One # standalone term
# e.g. 3 * ...
c_powers = [] # (base,exp) n
# e.g. (x,n) for x
num_exp = [] # (num-base, exp) y
# e.g. (3, y) for ... * 3 * ...
neg1e = 0 # exponent on -1 extracted from Number-based Pow
pnum_rat = {} # (num-base, Rat-exp) 1/2
# e.g. (3, 1/2) for ... * 3 * ...
order_symbols = None
# --- PART 1 ---
#
# "collect powers and coeff":
#
# o coeff
# o c_powers
# o num_exp
# o neg1e
# o pnum_rat
#
# NOTE: this is optimized for all-objects-are-commutative case
for o in seq:
# O(x)
if o.is_Order:
o, order_symbols = o.as_expr_variables(order_symbols)
# Mul([...])
if o.is_Mul:
if o.is_commutative:
seq.extend(o.args) # XXX zerocopy?
else:
# NCMul can have commutative parts as well
for q in o.args:
if q.is_commutative:
seq.append(q)
else:
nc_seq.append(q)
# append non-commutative marker, so we don't forget to
# process scheduled non-commutative objects
seq.append(NC_Marker)
continue
# 3
elif o.is_Number:
if o is S.NaN or coeff is S.ComplexInfinity and o is S.Zero:
# we know for sure the result will be nan
return [S.NaN], [], None
elif coeff.is_Number: # it could be zoo
coeff *= o
if coeff is S.NaN:
# we know for sure the result will be nan
return [S.NaN], [], None
continue
elif o is S.ComplexInfinity:
if not coeff or coeff is S.ComplexInfinity:
# we know for sure the result will be nan
return [S.NaN], [], None
coeff = S.ComplexInfinity
continue
elif o.is_commutative:
# e
# o = b
b, e = o.as_base_exp()
# y
# 3
if o.is_Pow and b.is_Number:
# get all the factors with numeric base so they can be
# combined below, but don't combine negatives unless
# the exponent is an integer
if e.is_Rational:
if e.is_Integer:
coeff *= Pow(b, e) # it is an unevaluated power
continue
elif e.is_negative: # also a sign of an unevaluated power
seq.append(Pow(b, e))
continue
elif b.is_negative:
neg1e += e
b = -b
if b is not S.One:
pnum_rat.setdefault(b, []).append(e)
continue
elif b.is_positive or e.is_integer:
num_exp.append((b, e))
continue
c_powers.append((b, e))
# NON-COMMUTATIVE
# TODO: Make non-commutative exponents not combine automatically
else:
if o is not NC_Marker:
nc_seq.append(o)
# process nc_seq (if any)
while nc_seq:
o = nc_seq.pop(0)
if not nc_part:
nc_part.append(o)
continue
# b c b+c
# try to combine last terms: a * a -> a
o1 = nc_part.pop()
b1, e1 = o1.as_base_exp()
b2, e2 = o.as_base_exp()
new_exp = e1 + e2
# Only allow powers to combine if the new exponent is
# not an Add. This allow things like a**2*b**3 == a**5
# if a.is_commutative == False, but prohibits
# a**x*a**y and x**a*x**b from combining (x,y commute).
if b1 == b2 and (not new_exp.is_Add):
o12 = b1**new_exp
# now o12 could be a commutative object
if o12.is_commutative:
seq.append(o12)
continue
else:
nc_seq.insert(0, o12)
else:
nc_part.append(o1)
nc_part.append(o)
# We do want a combined exponent if it would not be an Add, such as
# y 2y 3y
# x * x -> x
# We determine this if two exponents have the same term in as_coeff_mul
#
# Unfortunately, this isn't smart enough to consider combining into
# exponents that might already be adds, so things like:
# z - y y
# x * x will be left alone. This is because checking every possible
# combination can slow things down.
# gather exponents of common bases...
# in c_powers
new_c_powers = []
common_b = {} # b:e
for b, e in c_powers:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_c_powers.append((b, c * Mul(*t)))
c_powers = new_c_powers
# and in num_exp
new_num_exp = []
common_b = {} # b:e
for b, e in num_exp:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_num_exp.append((b, c * Mul(*t)))
num_exp = new_num_exp
# --- PART 2 ---
#
# o process collected powers (x**0 -> 1; x**1 -> x; otherwise Pow)
# o combine collected powers (2**x * 3**x -> 6**x)
# with numeric base
# ................................
# now we have:
# - coeff:
# - c_powers: (b, e)
# - num_exp: (2, e)
# - pnum_rat: {(1/3, [1/3, 2/3, 1/4])}
# 0 1
# x -> 1 x -> x
for b, e in c_powers:
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif not e is S.Zero:
c_part.append(Pow(b, e))
# x x x
# 2 * 3 -> 6
inv_exp_dict = {} # exp:Mul(num-bases) x x
# e.g. x:6 for ... * 2 * 3 * ...
for b, e in num_exp:
inv_exp_dict.setdefault(e, []).append(b)
for e, b in inv_exp_dict.items():
inv_exp_dict[e] = Mul(*b)
c_part.extend([Pow(b, e) for e, b in inv_exp_dict.iteritems() if e])
# b, e -> e, b
# {(1/5, [1/3]), (1/2, [1/12, 1/4]} -> {(1/3, [1/5, 1/2])}
comb_e = {}
for b, e in pnum_rat.iteritems():
comb_e.setdefault(Add(*e), []).append(b)
del pnum_rat
# process them, reducing exponents to values less than 1
# and updating coeff if necessary else adding them to
# num_rat for further processing
num_rat = []
for e, b in comb_e.iteritems():
b = Mul(*b)
if e.q == 1:
coeff *= Pow(b, e)
continue
if e.p > e.q:
e_i, ep = divmod(e.p, e.q)
coeff *= Pow(b, e_i)
e = Rational(ep, e.q)
num_rat.append((b, e))
del comb_e
# extract gcd of bases in num_rat
# 2**(1/3)*6**(1/4) -> 2**(1/3+1/4)*3**(1/4)
pnew = {}
i = 0 # steps through num_rat which may grow
while i < len(num_rat):
bi, ei = num_rat[i]
grow = []
for j in range(i + 1, len(num_rat)):
bj, ej = num_rat[j]
g = igcd(bi, bj)
if g != 1:
# 4**r1*6**r2 -> 2**(r1+r2) * 2**r1 * 3**r2
# this might have a gcd with something else
e = ei + ej
if e.q == 1:
coeff *= Pow(g, e)
else:
if e.p > e.q:
e_i, ep = divmod(e.p, e.q) # change e in place
coeff *= Pow(g, e_i)
e = Rational(ep, e.q)
grow.append((g, e))
# update the jth item
num_rat[j] = (bj // g, ej)
# update bi that we are checking with
bi = bi // g
if bi is S.One:
break
if bi is not S.One:
obj = Pow(bi, ei)
if obj.is_Number:
coeff *= obj
else:
if obj.is_Mul: # 12**(1/2) -> 2*sqrt(3)
c, obj = obj.args # expecting only 2 args
coeff *= c
assert obj.is_Pow
bi, ei = obj.args
pnew.setdefault(ei, []).append(bi)
num_rat.extend(grow)
i += 1
# combine bases of the new powers
for e, b in pnew.iteritems():
pnew[e] = Mul(*b)
# see if there is a base with matching coefficient
# that the -1 can be joined with
if neg1e:
p = Pow(S.NegativeOne, neg1e)
if p.is_Number:
coeff *= p
else:
if p.is_Mul:
c, p = p.args
coeff *= c
assert p.is_Pow and p.base is S.NegativeOne
neg1e = p.args[1]
for e, b in pnew.iteritems():
if e == neg1e and b.is_positive:
pnew[e] = -b
break
else:
c_part.append(p)
# add all the pnew powers
c_part.extend([Pow(b, e) for e, b in pnew.iteritems()])
# oo, -oo
if (coeff is S.Infinity) or (coeff is S.NegativeInfinity):
new_c_part = []
coeff_sign = 1
for t in c_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_c_part.append(t)
c_part = new_c_part
new_nc_part = []
for t in nc_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_nc_part.append(t)
nc_part = new_nc_part
coeff *= coeff_sign
# zoo
if coeff is S.ComplexInfinity:
# zoo might be
# unbounded_real + bounded_im
# bounded_real + unbounded_im
# unbounded_real + unbounded_im
# and non-zero real or imaginary will not change that status.
c_part = [
c for c in c_part
if not (c.is_nonzero and c.is_real is not None)
]
nc_part = [
c for c in nc_part
if not (c.is_nonzero and c.is_real is not None)
]
# 0
elif coeff is S.Zero:
# we know for sure the result will be 0
return [coeff], [], order_symbols
# order commutative part canonically
c_part.sort(key=cmp_to_key(Basic.compare))
# current code expects coeff to be always in slot-0
if coeff is not S.One:
c_part.insert(0, coeff)
# we are done
if len(c_part) == 2 and c_part[0].is_Number and c_part[1].is_Add:
# 2*(1+a) -> 2 + 2 * a
coeff = c_part[0]
c_part = [Add(*[coeff * f for f in c_part[1].args])]
return c_part, nc_part, order_symbols
class Mul(AssocOp):
__slots__ = []
is_Mul = True
#identity = S.One
# cyclic import, so defined in numbers.py
# Key for sorting commutative args in canonical order
_args_sortkey = cmp_to_key(Basic.compare)
@classmethod
def flatten(cls, seq):
"""Return commutative, noncommutative and order arguments by
combining related terms.
** Developer Notes **
* In an expression like ``a*b*c``, python process this through sympy
as ``Mul(Mul(a, b), c)``. This can have undesirable consequences.
- Sometimes terms are not combined as one would like:
{c.f. http://code.google.com/p/sympy/issues/detail?id=1497}
>>> from sympy import Mul, sqrt
>>> from sympy.abc import x, y, z
>>> 2*(x + 1) # this is the 2-arg Mul behavior
2*x + 2
>>> y*(x + 1)*2
2*y*(x + 1)
>>> 2*(x + 1)*y # 2-arg result will be obtained first
y*(2*x + 2)
>>> Mul(2, x + 1, y) # all 3 args simultaneously processed
2*y*(x + 1)
>>> 2*((x + 1)*y) # parentheses can control this behavior
2*y*(x + 1)
Powers with compound bases may not find a single base to
combine with unless all arguments are processed at once.
Post-processing may be necessary in such cases.
{c.f. http://code.google.com/p/sympy/issues/detail?id=2629}
>>> a = sqrt(x*sqrt(y))
>>> a**3
(x*sqrt(y))**(3/2)
>>> Mul(a,a,a)
(x*sqrt(y))**(3/2)
>>> a*a*a
x*sqrt(y)*sqrt(x*sqrt(y))
>>> _.subs(a.base, z).subs(z, a.base)
(x*sqrt(y))**(3/2)
- If more than two terms are being multiplied then all the
previous terms will be re-processed for each new argument.
So if each of ``a``, ``b`` and ``c`` were :class:`Mul`
expression, then ``a*b*c`` (or building up the product
with ``*=``) will process all the arguments of ``a`` and
``b`` twice: once when ``a*b`` is computed and again when
``c`` is multiplied.
Using ``Mul(a, b, c)`` will process all arguments once.
* The results of Mul are cached according to arguments, so flatten
will only be called once for ``Mul(a, b, c)``. If you can
structure a calculation so the arguments are most likely to be
repeats then this can save time in computing the answer. For
example, say you had a Mul, M, that you wished to divide by ``d[i]``
and multiply by ``n[i]`` and you suspect there are many repeats
in ``n``. It would be better to compute ``M*n[i]/d[i]`` rather
than ``M/d[i]*n[i]`` since every time n[i] is a repeat, the
product, ``M*n[i]`` will be returned without flattening -- the
cached value will be returned. If you divide by the ``d[i]``
first (and those are more unique than the ``n[i]``) then that will
create a new Mul, ``M/d[i]`` the args of which will be traversed
again when it is multiplied by ``n[i]``.
{c.f. http://code.google.com/p/sympy/issues/detail?id=2607}
This consideration is moot if the cache is turned off.
NB
The validity of the above notes depends on the implementation
details of Mul and flatten which may change at any time. Therefore,
you should only consider them when your code is highly performance
sensitive.
"""
rv = None
if len(seq) == 2:
a, b = seq
if b.is_Rational:
a, b = b, a
assert not a is S.One
if a and a.is_Rational and a.q:
r, b = b.as_coeff_Mul()
a *= r
if b.is_Mul:
bargs, nc = b.args_cnc(clist=True)
rv = bargs, nc, None
if a is not S.One:
bargs.insert(0, a)
elif b.is_Add and b.is_commutative:
if a is S.One:
rv = [b], [], None
else:
r, b = b.as_coeff_Add()
bargs = [_keep_coeff(a, bi) for bi in Add.make_args(b)]
bargs.sort(key=hash)
ar = a * r
if ar:
bargs.insert(0, ar)
bargs = [Add._from_args(bargs)]
rv = bargs, [], None
if rv:
return rv
# apply associativity, separate commutative part of seq
c_part = [] # out: commutative factors
nc_part = [] # out: non-commutative factors
nc_seq = []
coeff = S.One # standalone term
# e.g. 3 * ...
c_powers = [] # (base,exp) n
# e.g. (x,n) for x
num_exp = [] # (num-base, exp) y
# e.g. (3, y) for ... * 3 * ...
neg1e = 0 # exponent on -1 extracted from Number-based Pow
pnum_rat = {} # (num-base, Rat-exp) 1/2
# e.g. (3, 1/2) for ... * 3 * ...
order_symbols = None
# --- PART 1 ---
#
# "collect powers and coeff":
#
# o coeff
# o c_powers
# o num_exp
# o neg1e
# o pnum_rat
#
# NOTE: this is optimized for all-objects-are-commutative case
for o in seq:
# O(x)
if o.is_Order:
o, order_symbols = o.as_expr_variables(order_symbols)
# Mul([...])
if o.is_Mul:
if o.is_commutative:
seq.extend(o.args) # XXX zerocopy?
else:
# NCMul can have commutative parts as well
for q in o.args:
if q.is_commutative:
seq.append(q)
else:
nc_seq.append(q)
# append non-commutative marker, so we don't forget to
# process scheduled non-commutative objects
seq.append(NC_Marker)
continue
# 3
elif o.is_Number:
if o is S.NaN or coeff is S.ComplexInfinity and o is S.Zero:
# we know for sure the result will be nan
return [S.NaN], [], None
elif coeff.is_Number: # it could be zoo
coeff *= o
if coeff is S.NaN:
# we know for sure the result will be nan
return [S.NaN], [], None
continue
elif o is S.ComplexInfinity:
if not coeff or coeff is S.ComplexInfinity:
# we know for sure the result will be nan
return [S.NaN], [], None
coeff = S.ComplexInfinity
continue
elif o.is_commutative:
# e
# o = b
b, e = o.as_base_exp()
# y
# 3
if o.is_Pow and b.is_Number:
# get all the factors with numeric base so they can be
# combined below, but don't combine negatives unless
# the exponent is an integer
if e.is_Rational:
if e.is_Integer:
coeff *= Pow(b, e) # it is an unevaluated power
continue
elif e.is_negative: # also a sign of an unevaluated power
seq.append(Pow(b, e))
continue
elif b.is_negative:
neg1e += e
b = -b
if b is not S.One:
pnum_rat.setdefault(b, []).append(e)
continue
elif b.is_positive or e.is_integer:
num_exp.append((b, e))
continue
c_powers.append((b, e))
# NON-COMMUTATIVE
# TODO: Make non-commutative exponents not combine automatically
else:
if o is not NC_Marker:
nc_seq.append(o)
# process nc_seq (if any)
while nc_seq:
o = nc_seq.pop(0)
if not nc_part:
nc_part.append(o)
continue
# b c b+c
# try to combine last terms: a * a -> a
o1 = nc_part.pop()
b1, e1 = o1.as_base_exp()
b2, e2 = o.as_base_exp()
new_exp = e1 + e2
# Only allow powers to combine if the new exponent is
# not an Add. This allow things like a**2*b**3 == a**5
# if a.is_commutative == False, but prohibits
# a**x*a**y and x**a*x**b from combining (x,y commute).
if b1 == b2 and (not new_exp.is_Add):
o12 = b1**new_exp
# now o12 could be a commutative object
if o12.is_commutative:
seq.append(o12)
continue
else:
nc_seq.insert(0, o12)
else:
nc_part.append(o1)
nc_part.append(o)
# We do want a combined exponent if it would not be an Add, such as
# y 2y 3y
# x * x -> x
# We determine this if two exponents have the same term in as_coeff_mul
#
# Unfortunately, this isn't smart enough to consider combining into
# exponents that might already be adds, so things like:
# z - y y
# x * x will be left alone. This is because checking every possible
# combination can slow things down.
# gather exponents of common bases...
# in c_powers
new_c_powers = []
common_b = {} # b:e
for b, e in c_powers:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_c_powers.append((b, c * Mul(*t)))
c_powers = new_c_powers
# and in num_exp
new_num_exp = []
common_b = {} # b:e
for b, e in num_exp:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_num_exp.append((b, c * Mul(*t)))
num_exp = new_num_exp
# --- PART 2 ---
#
# o process collected powers (x**0 -> 1; x**1 -> x; otherwise Pow)
# o combine collected powers (2**x * 3**x -> 6**x)
# with numeric base
# ................................
# now we have:
# - coeff:
# - c_powers: (b, e)
# - num_exp: (2, e)
# - pnum_rat: {(1/3, [1/3, 2/3, 1/4])}
# 0 1
# x -> 1 x -> x
for b, e in c_powers:
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif e is not S.Zero:
c_part.append(Pow(b, e))
# x x x
# 2 * 3 -> 6
inv_exp_dict = {} # exp:Mul(num-bases) x x
# e.g. x:6 for ... * 2 * 3 * ...
for b, e in num_exp:
inv_exp_dict.setdefault(e, []).append(b)
for e, b in inv_exp_dict.items():
inv_exp_dict[e] = Mul(*b)
c_part.extend([Pow(b, e) for e, b in inv_exp_dict.iteritems() if e])
# b, e -> e' = sum(e), b
# {(1/5, [1/3]), (1/2, [1/12, 1/4]} -> {(1/3, [1/5, 1/2])}
comb_e = {}
for b, e in pnum_rat.iteritems():
comb_e.setdefault(Add(*e), []).append(b)
del pnum_rat
# process them, reducing exponents to values less than 1
# and updating coeff if necessary else adding them to
# num_rat for further processing
num_rat = []
for e, b in comb_e.iteritems():
b = Mul(*b)
if e.q == 1:
coeff *= Pow(b, e)
continue
if e.p > e.q:
e_i, ep = divmod(e.p, e.q)
coeff *= Pow(b, e_i)
e = Rational(ep, e.q)
num_rat.append((b, e))
del comb_e
# extract gcd of bases in num_rat
# 2**(1/3)*6**(1/4) -> 2**(1/3+1/4)*3**(1/4)
pnew = {}
i = 0 # steps through num_rat which may grow
while i < len(num_rat):
bi, ei = num_rat[i]
grow = []
for j in range(i + 1, len(num_rat)):
bj, ej = num_rat[j]
g = igcd(bi, bj)
if g != 1:
# 4**r1*6**r2 -> 2**(r1+r2) * 2**r1 * 3**r2
# this might have a gcd with something else
e = ei + ej
if e.q == 1:
coeff *= Pow(g, e)
else:
if e.p > e.q:
e_i, ep = divmod(e.p, e.q) # change e in place
coeff *= Pow(g, e_i)
e = Rational(ep, e.q)
grow.append((g, e))
# update the jth item
num_rat[j] = (bj // g, ej)
# update bi that we are checking with
bi = bi // g
if bi is S.One:
break
if bi is not S.One:
obj = Pow(bi, ei)
if obj.is_Number:
coeff *= obj
else:
if obj.is_Mul: # sqrt(12) -> 2*sqrt(3)
c, obj = obj.args # expecting only 2 args
coeff *= c
assert obj.is_Pow
bi, ei = obj.args
pnew.setdefault(ei, []).append(bi)
num_rat.extend(grow)
i += 1
# combine bases of the new powers
for e, b in pnew.iteritems():
pnew[e] = Mul(*b)
# see if there is a base with matching coefficient
# that the -1 can be joined with
if neg1e:
p = Pow(S.NegativeOne, neg1e)
if p.is_Number:
coeff *= p
else:
if p.is_Mul:
c, p = p.args
coeff *= c
assert p.is_Pow and p.base is S.NegativeOne
neg1e = p.args[1]
for e, b in pnew.iteritems():
if e == neg1e and b.is_positive:
pnew[e] = -b
break
else:
c_part.append(p)
# add all the pnew powers
c_part.extend([Pow(b, e) for e, b in pnew.iteritems()])
# oo, -oo
if (coeff is S.Infinity) or (coeff is S.NegativeInfinity):
new_c_part = []
coeff_sign = 1
for t in c_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_c_part.append(t)
c_part = new_c_part
new_nc_part = []
for t in nc_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_nc_part.append(t)
nc_part = new_nc_part
coeff *= coeff_sign
# zoo
if coeff is S.ComplexInfinity:
# zoo might be
# unbounded_real + bounded_im
# bounded_real + unbounded_im
# unbounded_real + unbounded_im
# and non-zero real or imaginary will not change that status.
c_part = [
c for c in c_part
if not (c.is_nonzero and c.is_real is not None)
]
nc_part = [
c for c in nc_part
if not (c.is_nonzero and c.is_real is not None)
]
# 0
elif coeff is S.Zero:
# we know for sure the result will be 0
return [coeff], [], order_symbols
# order commutative part canonically
c_part.sort(key=cls._args_sortkey)
# current code expects coeff to be always in slot-0
if coeff is not S.One:
c_part.insert(0, coeff)
# we are done
if len(c_part) == 2 and c_part[0].is_Number and c_part[1].is_Add:
# 2*(1+a) -> 2 + 2 * a
coeff = c_part[0]
c_part = [Add(*[coeff * f for f in c_part[1].args])]
return c_part, nc_part, order_symbols
def _eval_power(b, e):
if e.is_Number:
if b.is_commutative:
if e.is_Integer:
# (a*b)**2 -> a**2 * b**2
return Mul(*[s**e for s in b.args])
if e.is_rational:
coeff, rest = b.as_coeff_mul()
rest = list(rest)
unk = []
nonneg = []
neg = []
for bi in rest:
if bi.is_negative is not None: #then we know the sign
if bi.is_negative:
neg.append(bi)
else:
nonneg.append(bi)
elif bi.is_polar:
nonneg.append(bi)
else:
unk.append(bi)
if len(unk) == len(rest) or len(neg) == len(rest) == 1:
# if all terms were unknown there is nothing to pull
# out except maybe the coeff; if there is a single
# negative term, this is the base case which cannot
# be processed further
if coeff.is_negative:
coeff *= -1
rest[0] = -rest[0]
if coeff is S.One:
return None
return Mul(Pow(coeff, e), Pow(Mul(*rest), e))
# otherwise return the new expression expanding out the
# known terms; those that are not known can be expanded
# out with separate() but this will introduce a lot of
# "garbage" that is needed to keep one on the same branch
# as the unexpanded expression. The negatives are brought
# out with a negative sign added and a negative left behind
# in the unexpanded terms if there were an odd number of
# negatives.
if neg:
neg = [-w for w in neg]
if coeff.is_negative:
coeff = -coeff
unk.append(S.NegativeOne)
if len(neg) % 2:
unk.append(S.NegativeOne)
return Mul(*[Pow(s, e) for s in nonneg + neg + [coeff]])* \
Pow(Mul(*unk), e)
coeff, rest = b.as_coeff_mul()
if coeff is not S.One:
# (2*a)**3 -> 2**3 * a**3
return Mul(Pow(coeff, e), Mul(*[s**e for s in rest]))
elif e.is_Integer:
coeff, rest = b.as_coeff_mul()
if coeff == S.One:
return # the test below for even exponent needs coeff != 1
else:
return Mul(Pow(coeff, e), Pow(Mul(*rest), e))
c, t = b.as_coeff_mul()
if e.is_even and c.is_Number and c < 0:
return Pow((Mul(-c, Mul(*t))), e)
#if e.has(Wild):
# return Mul(*[t**e for t in b])
@classmethod
def class_key(cls):
return 3, 0, cls.__name__
def _eval_evalf(self, prec):
c, m = self.as_coeff_Mul()
if c is S.NegativeOne:
if m.is_Mul:
rv = -AssocOp._eval_evalf(m, prec)
else:
mnew = m._eval_evalf(prec)
if mnew is not None:
m = mnew
rv = -m
else:
rv = AssocOp._eval_evalf(self, prec)
if rv.is_number:
return rv.expand()
return rv
@cacheit
def as_two_terms(self):
"""Return head and tail of self.
This is the most efficient way to get the head and tail of an
expression.
- if you want only the head, use self.args[0];
- if you want to process the arguments of the tail then use
self.as_coef_mul() which gives the head and a tuple containing
the arguments of the tail when treated as a Mul.
- if you want the coefficient when self is treated as an Add
then use self.as_coeff_add()[0]
>>> from sympy.abc import x, y
>>> (3*x*y).as_two_terms()
(3, x*y)
"""
args = self.args
if len(args) == 1:
return S.One, self
elif len(args) == 2:
return args
else:
return args[0], self._new_rawargs(*args[1:])
@cacheit
def as_coeff_mul(self, *deps):
if deps:
l1 = []
l2 = []
for f in self.args:
if f.has(*deps):
l2.append(f)
else:
l1.append(f)
return self._new_rawargs(*l1), tuple(l2)
coeff, notrat = self.args[0].as_coeff_mul()
if coeff is not S.One:
return coeff, notrat + self.args[1:]
return S.One, self.args
def as_coeff_Mul(self):
"""Efficiently extract the coefficient of a product. """
coeff, args = self.args[0], self.args[1:]
if coeff.is_Number:
if len(args) == 1:
return coeff, args[0]
else:
return coeff, self._new_rawargs(*args)
else:
return S.One, self
def as_real_imag(self, deep=True):
other = []
coeff = S(1)
for a in self.args:
if a.is_real:
coeff *= a
else:
other.append(a)
m = Mul(*other)
return (coeff * C.re(m), coeff * C.im(m))
@staticmethod
def _expandsums(sums):
"""
Helper function for _eval_expand_mul.
sums must be a list of instances of Basic.
"""
L = len(sums)
if L == 1:
return sums[0].args
terms = []
left = Mul._expandsums(sums[:L // 2])
right = Mul._expandsums(sums[L // 2:])
terms = [Mul(a, b) for a in left for b in right]
added = Add(*terms)
return Add.make_args(added) #it may have collapsed down to one term
def _eval_expand_basic(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_basic'):
newterm = term._eval_expand_basic(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_expand_power_exp(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_power_exp'):
newterm = term._eval_expand_power_exp(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_expand_power_base(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_power_base'):
newterm = term._eval_expand_power_base(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_expand_mul(self, deep=True, **hints):
from sympy import fraction
expr = self
n, d = fraction(expr)
if d is not S.One:
expr = n / d._eval_expand_mul(deep=deep, **hints)
if not expr.is_Mul:
return expr._eval_expand_mul(deep=deep, **hints)
plain, sums, rewrite = [], [], False
for factor in expr.args:
if deep:
term = factor.expand(deep=deep, **hints)
if term != factor:
factor = term
rewrite = True
if factor.is_Add:
sums.append(factor)
rewrite = True
else:
if factor.is_commutative:
plain.append(factor)
else:
Wrapper = Basic
sums.append(Wrapper(factor))
if not rewrite:
return expr
else:
plain = Mul(*plain)
if sums:
terms = Mul._expandsums(sums)
args = []
for term in terms:
t = Mul(plain, term)
if t.is_Mul and any(a.is_Add for a in t.args):
t = t._eval_expand_mul(deep=deep)
args.append(t)
return Add(*args)
else:
return plain
def _eval_expand_multinomial(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_multinomial'):
newterm = term._eval_expand_multinomial(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_expand_log(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_log'):
newterm = term._eval_expand_log(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_expand_complex(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_complex'):
newterm = term._eval_expand_complex(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_expand_trig(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_trig'):
newterm = term._eval_expand_trig(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_expand_func(self, deep=True, **hints):
sargs, terms = self.args, []
for term in sargs:
if hasattr(term, '_eval_expand_func'):
newterm = term._eval_expand_func(deep=deep, **hints)
else:
newterm = term
terms.append(newterm)
return self.func(*terms)
def _eval_derivative(self, s):
terms = list(self.args)
factors = []
for i in xrange(len(terms)):
t = terms[i].diff(s)
if t is S.Zero:
continue
factors.append(Mul(*(terms[:i] + [t] + terms[i + 1:])))
return Add(*factors)
def _matches_simple(self, expr, repl_dict):
# handle (w*3).matches('x*5') -> {w: x*5/3}
coeff, terms = self.as_coeff_mul()
if len(terms) == 1:
newexpr = self.__class__._combine_inverse(expr, coeff)
return terms[0].matches(newexpr, repl_dict)
return
def matches(self, expr, repl_dict={}):
expr = sympify(expr)
if self.is_commutative and expr.is_commutative:
return AssocOp._matches_commutative(self, expr, repl_dict)
# todo for commutative parts, until then use the default matches method for non-commutative products
return self._matches(expr, repl_dict)
def _matches(self, expr, repl_dict={}):
# weed out negative one prefixes
sign = 1
a, b = self.as_two_terms()
if a is S.NegativeOne:
if b.is_Mul:
sign = -sign
else:
# the remainder, b, is not a Mul anymore
return b.matches(-expr, repl_dict)
expr = sympify(expr)
if expr.is_Mul and expr.args[0] is S.NegativeOne:
expr = -expr
sign = -sign
if not expr.is_Mul:
# expr can only match if it matches b and a matches +/- 1
if len(self.args) == 2:
# quickly test for equality
if b == expr:
return a.matches(Rational(sign), repl_dict)
# do more expensive match
dd = b.matches(expr, repl_dict)
if dd == None:
return None
dd = a.matches(Rational(sign), dd)
return dd
return None
d = repl_dict.copy()
# weed out identical terms
pp = list(self.args)
ee = list(expr.args)
for p in self.args:
if p in expr.args:
ee.remove(p)
pp.remove(p)
# only one symbol left in pattern -> match the remaining expression
if len(pp) == 1 and isinstance(pp[0], C.Wild):
if len(ee) == 1:
d[pp[0]] = sign * ee[0]
else:
d[pp[0]] = sign * expr.func(*ee)
return d
if len(ee) != len(pp):
return None
for p, e in zip(pp, ee):
d = p.xreplace(d).matches(e, d)
if d is None:
return None
return d
@staticmethod
def _combine_inverse(lhs, rhs):
"""
Returns lhs/rhs, but treats arguments like symbols, so things like
oo/oo return 1, instead of a nan.
"""
if lhs == rhs:
return S.One
def check(l, r):
if l.is_Float and r.is_comparable:
# if both objects are added to 0 they will share the same "normalization"
# and are more likely to compare the same. Since Add(foo, 0) will not allow
# the 0 to pass, we use __add__ directly.
return l.__add__(0) == r.evalf().__add__(0)
return False
if check(lhs, rhs) or check(rhs, lhs):
return S.One
if lhs.is_Mul and rhs.is_Mul:
a = list(lhs.args)
b = [1]
for x in rhs.args:
if x in a:
a.remove(x)
else:
b.append(x)
return Mul(*a) / Mul(*b)
return lhs / rhs
def as_powers_dict(self):
d = defaultdict(list)
for term in self.args:
b, e = term.as_base_exp()
d[b].append(e)
for b, e in d.iteritems():
if len(e) == 1:
e = e[0]
else:
e = Add(*e)
d[b] = e
return d
def as_numer_denom(self):
# don't use _from_args to rebuild the numerators and denominators
# as the order is not guaranteed to be the same once they have
# been separated from each other
numers, denoms = zip(*[f.as_numer_denom() for f in self.args])
return Mul(*numers), Mul(*denoms)
def as_base_exp(self):
e1 = None
bases = []
nc = 0
for m in self.args:
b, e = m.as_base_exp()
if not b.is_commutative:
nc += 1
if e1 is None:
e1 = e
elif e != e1 or nc > 1:
return self, S.One
bases.append(b)
return Mul(*bases), e1
def _eval_is_polynomial(self, syms):
return all(term._eval_is_polynomial(syms) for term in self.args)
def _eval_is_rational_function(self, syms):
return all(term._eval_is_rational_function(syms) for term in self.args)
_eval_is_bounded = lambda self: self._eval_template_is_attr('is_bounded')
_eval_is_commutative = lambda self: self._eval_template_is_attr(
'is_commutative')
_eval_is_integer = lambda self: self._eval_template_is_attr('is_integer')
_eval_is_comparable = lambda self: self._eval_template_is_attr(
'is_comparable')
def _eval_is_polar(self):
has_polar = any(arg.is_polar for arg in self.args)
return has_polar and \
all(arg.is_polar or arg.is_positive for arg in self.args)
# I*I -> R, I*I*I -> -I
def _eval_is_real(self):
im_count = 0
is_neither = False
for t in self.args:
if t.is_imaginary:
im_count += 1
continue
t_real = t.is_real
if t_real:
continue
elif t_real is False:
if is_neither:
return None
else:
is_neither = True
else:
return None
if is_neither:
return False
return (im_count % 2 == 0)
def _eval_is_imaginary(self):
im_count = 0
is_neither = False
for t in self.args:
if t.is_imaginary:
im_count += 1
continue
t_real = t.is_real
if t_real:
continue
elif t_real is False:
if is_neither:
return None
else:
is_neither = True
else:
return None
if is_neither:
return False
return (im_count % 2 == 1)
def _eval_is_irrational(self):
for t in self.args:
a = t.is_irrational
if a:
others = list(self.args)
others.remove(t)
if all(x.is_rational is True for x in others):
return True
return None
if a is None:
return
return False
def _eval_is_positive(self):
terms = [t for t in self.args if not t.is_positive]
if not terms:
return True
c = terms[0]
if len(terms) == 1:
if c.is_nonpositive:
return False
return
r = self._new_rawargs(*terms[1:])
if c.is_negative and r.is_negative:
return True
if r.is_negative and c.is_negative:
return True
# check for nonpositivity, <=0
if c.is_negative and r.is_nonnegative:
return False
if r.is_negative and c.is_nonnegative:
return False
if c.is_nonnegative and r.is_nonpositive:
return False
if r.is_nonnegative and c.is_nonpositive:
return False
def _eval_is_negative(self):
terms = [t for t in self.args if not t.is_positive]
if not terms:
# all terms are either positive -- 2*Symbol('n', positive=T)
# or unknown -- 2*Symbol('x')
if self.is_positive:
return False
else:
return None
c = terms[0]
if len(terms) == 1:
return c.is_negative
r = self._new_rawargs(*terms[1:])
# check for nonnegativity, >=0
if c.is_negative and r.is_nonpositive:
return False
if r.is_negative and c.is_nonpositive:
return False
if c.is_nonpositive and r.is_nonpositive:
return False
if c.is_nonnegative and r.is_nonnegative:
return False
def _eval_is_odd(self):
is_integer = self.is_integer
if is_integer:
r = True
for t in self.args:
if t.is_even:
return False
if t.is_odd is None:
r = None
return r
# !integer -> !odd
elif is_integer == False:
return False
def _eval_is_even(self):
is_integer = self.is_integer
if is_integer:
return fuzzy_not(self._eval_is_odd())
elif is_integer == False:
return False
def _eval_subs(self, old, new):
from sympy import sign
from sympy.simplify.simplify import powdenest
if self == old:
return new
def fallback():
"""Return this value when partial subs has failed."""
return self.__class__(*[s._eval_subs(old, new) for s in self.args])
def breakup(eq):
"""break up powers assuming (not checking) that eq is a Mul:
b**(Rational*e) -> b**e, Rational
commutatives come back as a dictionary {b**e: Rational}
noncommutatives come back as a list [(b**e, Rational)]
"""
(c, nc) = (dict(), list())
for (i, a) in enumerate(Mul.make_args(eq)):
a = powdenest(a)
(b, e) = a.as_base_exp()
if e is not S.One:
(co, _) = e.as_coeff_mul()
b = Pow(b, e / co)
e = co
if a.is_commutative:
if b in c: # handle I and -1 like things where b, e for I is -1, 1/2
c[b] += e
else:
c[b] = e
else:
nc.append([b, e])
return (c, nc)
def rejoin(b, co):
"""
Put rational back with exponent; in general this is not ok, but
since we took it from the exponent for analysis, it's ok to put
it back.
"""
(b, e) = b.as_base_exp()
return Pow(b, e * co)
def ndiv(a, b):
"""if b divides a in an extractive way (like 1/4 divides 1/2
but not vice versa, and 2/5 does not divide 1/3) then return
the integer number of times it divides, else return 0.
"""
if not b.q % a.q or not a.q % b.q:
return int(a / b)
return 0
if not old.is_Mul:
return fallback()
# handle the leading coefficient and use it to decide if anything
# should even be started; we always know where to find the Rational
# so it's a quick test
co_self = self.args[0]
co_old = old.args[0]
if co_old.is_Rational and co_self.is_Rational:
co_xmul = co_self.extract_multiplicatively(co_old)
elif co_old.is_Rational:
co_xmul = None
else:
co_xmul = True
if not co_xmul:
return fallback()
(c, nc) = breakup(self)
(old_c, old_nc) = breakup(old)
# update the coefficients if we had an extraction
if getattr(co_xmul, 'is_Rational', False):
c.pop(co_self)
c[co_xmul] = S.One
old_c.pop(co_old)
# Do some quick tests to see whether we can succeed:
# 1) check for more non-commutative or 2) commutative terms
# 3) ... unmatched non-commutative bases
# 4) ... unmatched commutative terms
# 5) and finally differences in sign
if len(old_nc) > len(nc) or len(old_c) > len(c) or \
set(_[0] for _ in old_nc).difference(set(_[0] for _ in nc)) or \
set(old_c).difference(set(c)) or \
any(sign(c[b]) != sign(old_c[b]) for b in old_c):
return fallback()
if not old_c:
cdid = None
else:
rat = []
for (b, old_e) in old_c.items():
c_e = c[b]
rat.append(ndiv(c_e, old_e))
if not rat[-1]:
return fallback()
cdid = min(rat)
if not old_nc:
ncdid = None
for i in range(len(nc)):
nc[i] = rejoin(*nc[i])
else:
ncdid = 0 # number of nc replacements we did
take = len(old_nc) # how much to look at each time
limit = cdid or S.Infinity # max number that we can take
failed = [] # failed terms will need subs if other terms pass
i = 0
while limit and i + take <= len(nc):
hit = False
# the bases must be equivalent in succession, and
# the powers must be extractively compatible on the
# first and last factor but equal inbetween.
rat = []
for j in range(take):
if nc[i + j][0] != old_nc[j][0]:
break
elif j == 0:
rat.append(ndiv(nc[i + j][1], old_nc[j][1]))
elif j == take - 1:
rat.append(ndiv(nc[i + j][1], old_nc[j][1]))
elif nc[i + j][1] != old_nc[j][1]:
break
else:
rat.append(1)
j += 1
else:
ndo = min(rat)
if ndo:
if take == 1:
if cdid:
ndo = min(cdid, ndo)
nc[i] = Pow(new, ndo) * rejoin(
nc[i][0], nc[i][1] - ndo * old_nc[0][1])
else:
ndo = 1
# the left residual
l = rejoin(nc[i][0], nc[i][1] - ndo * old_nc[0][1])
# eliminate all middle terms
mid = new
# the right residual (which may be the same as the middle if take == 2)
ir = i + take - 1
r = (nc[ir][0], nc[ir][1] - ndo * old_nc[-1][1])
if r[1]:
if i + take < len(nc):
nc[i:i + take] = [l * mid, r]
else:
r = rejoin(*r)
nc[i:i + take] = [l * mid * r]
else:
# there was nothing left on the right
nc[i:i + take] = [l * mid]
limit -= ndo
ncdid += ndo
hit = True
if not hit:
# do the subs on this failing factor
failed.append(i)
i += 1
else:
if not ncdid:
return fallback()
# although we didn't fail, certain nc terms may have
# failed so we rebuild them after attempting a partial
# subs on them
failed.extend(range(i, len(nc)))
for i in failed:
nc[i] = rejoin(*nc[i]).subs(old, new)
# rebuild the expression
if cdid is None:
do = ncdid
elif ncdid is None:
do = cdid
else:
do = min(ncdid, cdid)
margs = []
for b in c:
if b in old_c:
# calculate the new exponent
e = c[b] - old_c[b] * do
margs.append(rejoin(b, e))
else:
margs.append(rejoin(b.subs(old, new), c[b]))
if cdid and not ncdid:
# in case we are replacing commutative with non-commutative,
# we want the new term to come at the front just like the
# rest of this routine
margs = [Pow(new, cdid)] + margs
return Mul(*margs) * Mul(*nc)
def _eval_nseries(self, x, n, logx):
from sympy import powsimp
terms = [t.nseries(x, n=n, logx=logx) for t in self.args]
return powsimp(Mul(*terms).expand(), combine='exp', deep=True)
def _eval_as_leading_term(self, x):
return Mul(*[t.as_leading_term(x) for t in self.args])
def _eval_conjugate(self):
return Mul(*[t.conjugate() for t in self.args])
def _sage_(self):
s = 1
for x in self.args:
s *= x._sage_()
return s
def as_content_primitive(self):
"""Return the tuple (R, self/R) where R is the positive Rational
extracted from self.
Examples
========
>>> from sympy import sqrt
>>> (-3*sqrt(2)*(2 - 2*sqrt(2))).as_content_primitive()
(6, -sqrt(2)*(-sqrt(2) + 1))
See docstring of Expr.as_content_primitive for more examples.
"""
coef = S.One
args = []
for i, a in enumerate(self.args):
c, p = a.as_content_primitive()
coef *= c
if p is not S.One:
args.append(p)
# don't use self._from_args here to reconstruct args
# since there may be identical args now that should be combined
# e.g. (2+2*x)*(3+3*x) should be (6, (1 + x)**2) not (6, (1+x)*(1+x))
return coef, Mul(*args)