def eval_sum(f, limits):
from sympy.concrete.delta import deltasummation, _has_simple_delta
from sympy.functions import KroneckerDelta
(i, a, b) = limits
if f is S.Zero:
return S.Zero
if i not in f.free_symbols:
return f*(b - a + 1)
if a == b:
return f.subs(i, a)
if f.has(KroneckerDelta) and _has_simple_delta(f, limits[0]):
return deltasummation(f, limits)
dif = b - a
definite = dif.is_Integer
# Doing it directly may be faster if there are very few terms.
if definite and (dif < 100):
return eval_sum_direct(f, (i, a, b))
# Try to do it symbolically. Even when the number of terms is known,
# this can save time when b-a is big.
# We should try to transform to partial fractions
value = eval_sum_symbolic(f.expand(), (i, a, b))
if value is not None:
return value
# Do it directly
if definite:
return eval_sum_direct(f, (i, a, b))
def eval_sum(f, limits):
from sympy.concrete.delta import deltasummation, _has_simple_delta
from sympy.functions import KroneckerDelta
(i, a, b) = limits
if f is S.Zero:
return S.Zero
if i not in f.free_symbols:
return f * (b - a + 1)
if a == b:
return f.subs(i, a)
if f.has(KroneckerDelta) and _has_simple_delta(f, limits[0]):
return deltasummation(f, limits)
dif = b - a
definite = dif.is_Integer
# Doing it directly may be faster if there are very few terms.
if definite and (dif < 100):
return eval_sum_direct(f, (i, a, b))
# Try to do it symbolically. Even when the number of terms is known,
# this can save time when b-a is big.
# We should try to transform to partial fractions
value = eval_sum_symbolic(f.expand(), (i, a, b))
if value is not None:
return value
# Do it directly
if definite:
return eval_sum_direct(f, (i, a, b))
def _expand_delta(expr, idx):
"""Expand the first :class:`sympy.Add` containing a simple
:class:`sympy.KroneckerDelta`.
Auxiliary routine for :func:`_deltasummation`. Adapted from SymPy. The
input `expr` may be a :class:`.QuantumExpression` or a
`:class:`sympy.Basic` instance.
Returns a list of summands. The elements of the list may be
:class:`.QuantumExpression` or a `:class:`sympy.Basic` instances. There is
no guarantee of type stability: an input :class:`.QuantumExpression` may
result in a :class:`sympy.Basic` instance in the `summands`.
"""
found_first_delta = False
summands = None
for factor in _factors_for_expand_delta(expr):
need_to_expand = False
if not found_first_delta and isinstance(factor, sympy.Basic):
if factor.is_Add and _has_simple_delta(factor, idx):
need_to_expand = True
if need_to_expand:
found_first_delta = True
if summands is None:
summands = list(factor.args)
else:
summands = [summands[0] * t for t in factor.args]
else:
if summands is None:
summands = [
factor,
]
else:
summands = [t * factor for t in summands]
return summands
def eval_sum(f, limits):
from sympy.concrete.delta import deltasummation, _has_simple_delta
from sympy.functions import KroneckerDelta
(i, a, b) = limits
if f.is_zero:
return S.Zero
if i not in f.free_symbols:
return f*(b - a + 1)
if a == b:
return f.subs(i, a)
if isinstance(f, Piecewise):
if not any(i in arg.args[1].free_symbols for arg in f.args):
# Piecewise conditions do not depend on the dummy summation variable,
# therefore we can fold: Sum(Piecewise((e, c), ...), limits)
# --> Piecewise((Sum(e, limits), c), ...)
newargs = []
for arg in f.args:
newexpr = eval_sum(arg.expr, limits)
if newexpr is None:
return None
newargs.append((newexpr, arg.cond))
return f.func(*newargs)
if f.has(KroneckerDelta):
f = f.replace(
lambda x: isinstance(x, Sum),
lambda x: x.factor()
)
if _has_simple_delta(f, limits[0]):
return deltasummation(f, limits)
dif = b - a
definite = dif.is_Integer
# Doing it directly may be faster if there are very few terms.
if definite and (dif < 100):
return eval_sum_direct(f, (i, a, b))
if isinstance(f, Piecewise):
return None
# Try to do it symbolically. Even when the number of terms is known,
# this can save time when b-a is big.
# We should try to transform to partial fractions
value = eval_sum_symbolic(f.expand(), (i, a, b))
if value is not None:
return value
# Do it directly
if definite:
return eval_sum_direct(f, (i, a, b))
def eval_sum(f, limits):
from sympy.concrete.delta import deltasummation, _has_simple_delta
from sympy.functions import KroneckerDelta
(i, a, b) = limits
if f is S.Zero:
return S.Zero
if i not in f.free_symbols:
return f*(b - a + 1)
if a == b:
return f.subs(i, a)
if isinstance(f, Piecewise):
if not any(i in arg.args[1].free_symbols for arg in f.args):
# Piecewise conditions do not depend on the dummy summation variable,
# therefore we can fold: Sum(Piecewise((e, c), ...), limits)
# --> Piecewise((Sum(e, limits), c), ...)
newargs = []
for arg in f.args:
newexpr = eval_sum(arg.expr, limits)
if newexpr is None:
return None
newargs.append((newexpr, arg.cond))
return f.func(*newargs)
if f.has(KroneckerDelta) and _has_simple_delta(f, limits[0]):
return deltasummation(f, limits)
dif = b - a
definite = dif.is_Integer
# Doing it directly may be faster if there are very few terms.
if definite and (dif < 100):
return eval_sum_direct(f, (i, a, b))
if isinstance(f, Piecewise):
return None
# Try to do it symbolically. Even when the number of terms is known,
# this can save time when b-a is big.
# We should try to transform to partial fractions
value = eval_sum_symbolic(f.expand(), (i, a, b))
if value is not None:
return value
# Do it directly
if definite:
return eval_sum_direct(f, (i, a, b))
def _eval_product(self, term, limits):
from sympy.concrete.delta import deltaproduct, _has_simple_delta
from sympy.concrete.summations import summation
from sympy.functions import KroneckerDelta, RisingFactorial
(k, a, n) = limits
if k not in term.free_symbols:
if (term - 1).is_zero:
return S.One
return term**(n - a + 1)
if a == n:
return term.subs(k, a)
if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
return deltaproduct(term, limits)
dif = n - a
if dif.is_Integer:
return Mul(*[term.subs(k, a + i) for i in range(dif + 1)])
elif term.is_polynomial(k):
poly = term.as_poly(k)
A = B = Q = S.One
all_roots = roots(poly)
M = 0
for r, m in all_roots.items():
M += m
A *= RisingFactorial(a - r, n - a + 1)**m
Q *= (n - r)**m
if M < poly.degree():
arg = quo(poly, Q.as_poly(k))
B = self.func(arg, (k, a, n)).doit()
return poly.LC()**(n - a + 1) * A * B
elif term.is_Add:
p, q = term.as_numer_denom()
p = self._eval_product(p, (k, a, n))
q = self._eval_product(q, (k, a, n))
return p / q
elif term.is_Mul:
exclude, include = [], []
for t in term.args:
p = self._eval_product(t, (k, a, n))
if p is not None:
exclude.append(p)
else:
include.append(t)
if not exclude:
return None
else:
arg = term._new_rawargs(*include)
A = Mul(*exclude)
B = self.func(arg, (k, a, n)).doit()
return A * B
elif term.is_Pow:
if not term.base.has(k):
s = summation(term.exp, (k, a, n))
return term.base**s
elif not term.exp.has(k):
p = self._eval_product(term.base, (k, a, n))
if p is not None:
return p**term.exp
elif isinstance(term, Product):
evaluated = term.doit()
f = self._eval_product(evaluated, limits)
if f is None:
return self.func(evaluated, limits)
else:
return f
def _eval_product(self, term, limits):
from sympy.concrete.delta import deltaproduct, _has_simple_delta
from sympy.concrete.summations import summation
from sympy.functions import KroneckerDelta, RisingFactorial
(k, a, n) = limits
if k not in term.free_symbols:
if (term - 1).is_zero:
return S.One
return term**(n - a + 1)
if a == n:
return term.subs(k, a)
if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
return deltaproduct(term, limits)
dif = n - a
if dif.is_Integer:
return Mul(*[term.subs(k, a + i) for i in range(dif + 1)])
elif term.is_polynomial(k):
poly = term.as_poly(k)
A = B = Q = S.One
all_roots = roots(poly)
M = 0
for r, m in all_roots.items():
M += m
A *= RisingFactorial(a - r, n - a + 1)**m
Q *= (n - r)**m
if M < poly.degree():
arg = quo(poly, Q.as_poly(k))
B = self.func(arg, (k, a, n)).doit()
return poly.LC()**(n - a + 1) * A * B
elif term.is_Add:
factored = factor_terms(term, fraction=True)
if factored.is_Mul:
return self._eval_product(factored, (k, a, n))
elif term.is_Mul:
exclude, include = [], []
for t in term.args:
p = self._eval_product(t, (k, a, n))
if p is not None:
exclude.append(p)
else:
include.append(t)
if not exclude:
return None
else:
arg = term._new_rawargs(*include)
A = Mul(*exclude)
B = self.func(arg, (k, a, n)).doit()
return A * B
elif term.is_Pow:
if not term.base.has(k):
s = summation(term.exp, (k, a, n))
return term.base**s
elif not term.exp.has(k):
p = self._eval_product(term.base, (k, a, n))
if p is not None:
return p**term.exp
elif isinstance(term, Product):
evaluated = term.doit()
f = self._eval_product(evaluated, limits)
if f is None:
return self.func(evaluated, limits)
else:
return f
def _eval_product(self, term, limits):
from sympy.concrete.delta import deltaproduct, _has_simple_delta
from sympy.concrete.summations import summation
from sympy.functions import KroneckerDelta
(k, a, n) = limits
if k not in term.free_symbols:
return term**(n - a + 1)
if a == n:
return term.subs(k, a)
if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
return deltaproduct(term, limits)
dif = n - a
if dif.is_Integer:
return Mul(*[term.subs(k, a + i) for i in xrange(dif + 1)])
elif term.is_polynomial(k):
poly = term.as_poly(k)
A = B = Q = S.One
all_roots = roots(poly, multiple=True)
for r in all_roots:
A *= C.RisingFactorial(a - r, n - a + 1)
Q *= n - r
if len(all_roots) < poly.degree():
arg = quo(poly, Q.as_poly(k))
B = self.func(arg, (k, a, n)).doit()
return poly.LC()**(n - a + 1) * A * B
elif term.is_Add:
p, q = term.as_numer_denom()
p = self._eval_product(p, (k, a, n))
q = self._eval_product(q, (k, a, n))
return p / q
elif term.is_Mul:
exclude, include = [], []
for t in term.args:
p = self._eval_product(t, (k, a, n))
if p is not None:
exclude.append(p)
else:
include.append(t)
if not exclude:
return None
else:
arg = term._new_rawargs(*include)
A = Mul(*exclude)
B = self.func(arg, (k, a, n)).doit()
return A * B
elif term.is_Pow:
if not term.base.has(k):
s = summation(term.exp, (k, a, n))
return term.base**s
elif not term.exp.has(k):
p = self._eval_product(term.base, (k, a, n))
if p is not None:
return p**term.exp
elif isinstance(term, Product):
evaluated = term.doit()
f = self._eval_product(evaluated, limits)
if f is None:
return self.func(evaluated, limits)
else:
return f
def _eval_product(self, term, limits):
from sympy.concrete.delta import deltaproduct, _has_simple_delta
from sympy.concrete.summations import summation
from sympy.functions import KroneckerDelta, RisingFactorial
(k, a, n) = limits
if k not in term.free_symbols:
if (term - 1).is_zero:
return S.One
return term**(n - a + 1)
if a == n:
return term.subs(k, a)
if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
return deltaproduct(term, limits)
dif = n - a
if dif.is_Integer:
return Mul(*[term.subs(k, a + i) for i in range(dif + 1)])
elif term.is_polynomial(k):
poly = term.as_poly(k)
A = B = Q = S.One
all_roots = roots(poly)
M = 0
for r, m in all_roots.items():
M += m
A *= RisingFactorial(a - r, n - a + 1)**m
Q *= (n - r)**m
if M < poly.degree():
arg = quo(poly, Q.as_poly(k))
B = self.func(arg, (k, a, n)).doit()
return poly.LC()**(n - a + 1) * A * B
elif term.is_Add:
p, q = term.as_numer_denom()
q = self._eval_product(q, (k, a, n))
if q.is_Number:
# There is expression, which couldn't change by
# as_numer_denom(). E.g. n**(2/3) + 1 --> (n**(2/3) + 1, 1).
# We have to catch this case.
p = sum([self._eval_product(i, (k, a, n)) for i in p.as_coeff_Add()])
else:
p = self._eval_product(p, (k, a, n))
return p / q
elif term.is_Mul:
exclude, include = [], []
for t in term.args:
p = self._eval_product(t, (k, a, n))
if p is not None:
exclude.append(p)
else:
include.append(t)
if not exclude:
return None
else:
arg = term._new_rawargs(*include)
A = Mul(*exclude)
B = self.func(arg, (k, a, n)).doit()
return A * B
elif term.is_Pow:
if not term.base.has(k):
s = summation(term.exp, (k, a, n))
return term.base**s
elif not term.exp.has(k):
p = self._eval_product(term.base, (k, a, n))
if p is not None:
return p**term.exp
elif isinstance(term, Product):
evaluated = term.doit()
f = self._eval_product(evaluated, limits)
if f is None:
return self.func(evaluated, limits)
else:
return f
def _eval_product(self, term, limits):
from sympy.concrete.delta import deltaproduct, _has_simple_delta
from sympy.concrete.summations import summation
from sympy.functions import KroneckerDelta, RisingFactorial
(k, a, n) = limits
if k not in term.free_symbols:
if (term - 1).is_zero:
return S.One
return term**(n - a + 1)
if a == n:
return term.subs(k, a)
if term.has(KroneckerDelta) and _has_simple_delta(term, limits[0]):
return deltaproduct(term, limits)
dif = n - a
definite = dif.is_Integer
if definite and (dif < 100):
return self._eval_product_direct(term, limits)
elif term.is_polynomial(k):
poly = term.as_poly(k)
A = B = Q = S.One
all_roots = roots(poly)
M = 0
for r, m in all_roots.items():
M += m
A *= RisingFactorial(a - r, n - a + 1)**m
Q *= (n - r)**m
if M < poly.degree():
arg = quo(poly, Q.as_poly(k))
B = self.func(arg, (k, a, n)).doit()
return poly.LC()**(n - a + 1) * A * B
elif term.is_Add:
factored = factor_terms(term, fraction=True)
if factored.is_Mul:
return self._eval_product(factored, (k, a, n))
elif term.is_Mul:
# Factor in part without the summation variable and part with
without_k, with_k = term.as_coeff_mul(k)
if len(with_k) >= 2:
# More than one term including k, so still a multiplication
exclude, include = [], []
for t in with_k:
p = self._eval_product(t, (k, a, n))
if p is not None:
exclude.append(p)
else:
include.append(t)
if not exclude:
return None
else:
arg = term._new_rawargs(*include)
A = Mul(*exclude)
B = self.func(arg, (k, a, n)).doit()
return without_k**(n - a + 1) * A * B
else:
# Just a single term
p = self._eval_product(with_k[0], (k, a, n))
if p is None:
p = self.func(with_k[0], (k, a, n)).doit()
return without_k**(n - a + 1) * p
elif term.is_Pow:
if not term.base.has(k):
s = summation(term.exp, (k, a, n))
return term.base**s
elif not term.exp.has(k):
p = self._eval_product(term.base, (k, a, n))
if p is not None:
return p**term.exp
elif isinstance(term, Product):
evaluated = term.doit()
f = self._eval_product(evaluated, limits)
if f is None:
return self.func(evaluated, limits)
else:
return f
if definite:
return self._eval_product_direct(term, limits)
