def _add_splines(c, b1, d, b2, x):
"""Construct c*b1 + d*b2."""
if S.Zero in (b1, c):
rv = piecewise_fold(d * b2)
elif S.Zero in (b2, d):
rv = piecewise_fold(c * b1)
else:
new_args = []
# Just combining the Piecewise without any fancy optimization
p1 = piecewise_fold(c * b1)
p2 = piecewise_fold(d * b2)
# Search all Piecewise arguments except (0, True)
p2args = list(p2.args[:-1])
# This merging algorithm assumes the conditions in
# p1 and p2 are sorted
for arg in p1.args[:-1]:
expr = arg.expr
cond = arg.cond
lower = _ivl(cond, x)[0]
# Check p2 for matching conditions that can be merged
for i, arg2 in enumerate(p2args):
expr2 = arg2.expr
cond2 = arg2.cond
lower_2, upper_2 = _ivl(cond2, x)
if cond2 == cond:
# Conditions match, join expressions
expr += expr2
# Remove matching element
del p2args[i]
# No need to check the rest
break
elif lower_2 < lower and upper_2 <= lower:
# Check if arg2 condition smaller than arg1,
# add to new_args by itself (no match expected
# in p1)
new_args.append(arg2)
del p2args[i]
break
# Checked all, add expr and cond
new_args.append((expr, cond))
# Add remaining items from p2args
new_args.extend(p2args)
# Add final (0, True)
new_args.append((0, True))
rv = Piecewise(*new_args, evaluate=False)
return rv.expand()
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
return expand(piecewise_fold(d * b2))
if b2 == S.Zero or d == S.Zero:
return expand(piecewise_fold(c * b1))
new_args = []
n_intervals = len(b1.args)
assert n_intervals == len(b2.args)
new_args.append((expand(c * b1.args[0].expr), b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((expand(c * b1.args[i].expr + d * b2.args[i - 1].expr), b1.args[i].cond))
new_args.append((expand(d * b2.args[-2].expr), b2.args[-2].cond))
new_args.append(b2.args[-1])
return Piecewise(*new_args)
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
return expand(piecewise_fold(d * b2))
if b2 == S.Zero or d == S.Zero:
return expand(piecewise_fold(c * b1))
new_args = []
n_intervals = len(b1.args)
assert (n_intervals == len(b2.args))
new_args.append((expand(c * b1.args[0].expr), b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((expand(c * b1.args[i].expr + d * b2.args[i - 1].expr),
b1.args[i].cond))
new_args.append((expand(d * b2.args[-2].expr), b2.args[-2].cond))
new_args.append(b2.args[-1])
return Piecewise(*new_args)
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d * b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c * b1)
else:
new_args = []
n_intervals = len(b1.args)
if n_intervals != len(b2.args):
raise ValueError("Args of b1 and b2 are not equal")
new_args.append((c * b1.args[0].expr, b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((c * b1.args[i].expr + d * b2.args[i - 1].expr,
b1.args[i].cond))
new_args.append((d * b2.args[-2].expr, b2.args[-2].cond))
new_args.append(b2.args[-1])
rv = Piecewise(*new_args)
return rv.expand()
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d*b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c*b1)
else:
new_args = []
n_intervals = len(b1.args)
if n_intervals != len(b2.args):
raise ValueError("Args of b1 and b2 are not equal")
new_args.append((c*b1.args[0].expr, b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((
c*b1.args[i].expr + d*b2.args[i - 1].expr,
b1.args[i].cond
))
new_args.append((d*b2.args[-2].expr, b2.args[-2].cond))
new_args.append(b2.args[-1])
rv = Piecewise(*new_args)
return rv.expand()
def _simpsol(soleq):
lhs = soleq.lhs
sol = soleq.rhs
sol = powsimp(sol)
gens = list(sol.atoms(exp))
p = Poly(sol, *gens, expand=False)
gens = [factor_terms(g) for g in gens]
if not gens:
gens = p.gens
syms = [Symbol('C1'), Symbol('C2')]
terms = []
for coeff, monom in zip(p.coeffs(), p.monoms()):
coeff = piecewise_fold(coeff)
if type(coeff) is Piecewise:
coeff = Piecewise(*((ratsimp(coef).collect(syms), cond) for coef, cond in coeff.args))
else:
coeff = ratsimp(coeff).collect(syms)
monom = Mul(*(g ** i for g, i in zip(gens, monom)))
terms.append(coeff * monom)
return Eq(lhs, Add(*terms))
def test_deltasummation_mul_add_x_kd_add_y_kd():
assert ds((x + KD(i, k)) * (y + KD(i, j)), (j, 1, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= 3)), (0, True)) + 3 *
(KD(i, k) + x) * y)
assert ds((x + KD(i, k)) * (y + KD(i, j)), (j, 1, 1)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 1)), (0, True)) + (KD(i, k) + x) * y)
assert ds((x + KD(i, k)) * (y + KD(i, j)), (j, 2, 2)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 2)), (0, True)) + (KD(i, k) + x) * y)
assert ds((x + KD(i, k)) * (y + KD(i, j)), (j, 3, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 3)), (0, True)) + (KD(i, k) + x) * y)
assert ds((x + KD(i, k)) * (y + KD(i, j)), (j, 1, k)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= k)), (0, True)) + k *
(KD(i, k) + x) * y)
assert ds((x + KD(i, k)) * (y + KD(i, j)), (j, k, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= 3)), (0, True)) + (4 - k) *
(KD(i, k) + x) * y)
assert ds((x + KD(i, k)) * (y + KD(i, j)), (j, k, l)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= l)), (0, True)) +
(l - k + 1) * (KD(i, k) + x) * y)
def test_deltasummation_mul_add_x_kd_add_y_kd():
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= 3)), (0, True)) +
3*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 1)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 1)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 2, 2)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 2)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 3, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 3)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, k)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= k)), (0, True)) +
k*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= 3)), (0, True)) +
(4 - k)*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, l)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= l)), (0, True)) +
(l - k + 1)*(KD(i, k) + x)*y)
def test_deltasummation_mul_add_x_y_add_kd_kd():
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x + y, Eq(i, 1)), (0, True)) +
Piecewise((x + y, Eq(j, 1)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x + y, Eq(i, 2)), (0, True)) +
Piecewise((x + y, Eq(j, 2)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x + y, Eq(i, 3)), (0, True)) +
Piecewise((x + y, Eq(j, 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= l)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= m)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= m)), (0, True)))
def test_deltasummation_mul_add_x_y_add_kd_kd():
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= 3)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x + y, Eq(i, 1)), (0, True)) +
Piecewise((x + y, Eq(j, 1)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x + y, Eq(i, 2)), (0, True)) +
Piecewise((x + y, Eq(j, 2)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x + y, Eq(i, 3)), (0, True)) +
Piecewise((x + y, Eq(j, 3)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= l)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= 3)), (0, True)))
assert ds((x + y) * (KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= m)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= m)), (0, True)))
def test_deltasummation_add_mul_x_kd_kd():
assert ds(x * KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(1 <= i, i <= 3)), (0, True)) +
Piecewise((1, And(1 <= j, j <= 3)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(1 <= i, i <= l)), (0, True)) +
Piecewise((1, And(1 <= j, j <= l)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(x * KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
def _solveset(f, symbol, domain, _check=False):
"""Helper for solveset to return a result from an expression
that has already been sympify'ed and is known to contain the
given symbol."""
# _check controls whether the answer is checked or not
from sympy.simplify.simplify import signsimp
orig_f = f
f = together(f)
if f.is_Mul:
_, f = f.as_independent(symbol, as_Add=False)
if f.is_Add:
a, h = f.as_independent(symbol)
m, h = h.as_independent(symbol, as_Add=False)
f = a/m + h # XXX condition `m != 0` should be added to soln
f = piecewise_fold(f)
# assign the solvers to use
solver = lambda f, x, domain=domain: _solveset(f, x, domain)
if domain.is_subset(S.Reals):
inverter_func = invert_real
else:
inverter_func = invert_complex
inverter = lambda f, rhs, symbol: inverter_func(f, rhs, symbol, domain)
result = EmptySet()
if f.expand().is_zero:
return domain
elif not f.has(symbol):
return EmptySet()
elif f.is_Mul and all(_is_finite_with_finite_vars(m, domain)
for m in f.args):
# if f(x) and g(x) are both finite we can say that the solution of
# f(x)*g(x) == 0 is same as Union(f(x) == 0, g(x) == 0) is not true in
# general. g(x) can grow to infinitely large for the values where
# f(x) == 0. To be sure that we are not silently allowing any
# wrong solutions we are using this technique only if both f and g are
# finite for a finite input.
result = Union(*[solver(m, symbol) for m in f.args])
elif _is_function_class_equation(TrigonometricFunction, f, symbol) or \
_is_function_class_equation(HyperbolicFunction, f, symbol):
result = _solve_trig(f, symbol, domain)
elif f.is_Piecewise:
dom = domain
result = EmptySet()
expr_set_pairs = f.as_expr_set_pairs()
for (expr, in_set) in expr_set_pairs:
if in_set.is_Relational:
in_set = in_set.as_set()
if in_set.is_Interval:
dom -= in_set
solns = solver(expr, symbol, in_set)
result += solns
else:
lhs, rhs_s = inverter(f, 0, symbol)
if lhs == symbol:
# do some very minimal simplification since
# repeated inversion may have left the result
# in a state that other solvers (e.g. poly)
# would have simplified; this is done here
# rather than in the inverter since here it
# is only done once whereas there it would
# be repeated for each step of the inversion
if isinstance(rhs_s, FiniteSet):
rhs_s = FiniteSet(*[Mul(*
signsimp(i).as_content_primitive())
for i in rhs_s])
result = rhs_s
elif isinstance(rhs_s, FiniteSet):
for equation in [lhs - rhs for rhs in rhs_s]:
if equation == f:
if any(_has_rational_power(g, symbol)[0]
for g in equation.args) or _has_rational_power(
equation, symbol)[0]:
result += _solve_radical(equation,
symbol,
solver)
elif equation.has(Abs):
result += _solve_abs(f, symbol, domain)
else:
result += _solve_as_rational(equation, symbol, domain)
else:
result += solver(equation, symbol)
else:
result = ConditionSet(symbol, Eq(f, 0), domain)
if _check:
if isinstance(result, ConditionSet):
# it wasn't solved or has enumerated all conditions
# -- leave it alone
return result
# whittle away all but the symbol-containing core
# to use this for testing
fx = orig_f.as_independent(symbol, as_Add=True)[1]
fx = fx.as_independent(symbol, as_Add=False)[1]
if isinstance(result, FiniteSet):
# check the result for invalid solutions
result = FiniteSet(*[s for s in result
if isinstance(s, RootOf)
or domain_check(fx, symbol, s)])
return result
def simplify(expr, ratio=1.7, measure=count_ops, fu=False):
"""
Simplifies the given expression.
Simplification is not a well defined term and the exact strategies
this function tries can change in the future versions of SymPy. If
your algorithm relies on "simplification" (whatever it is), try to
determine what you need exactly - is it powsimp()?, radsimp()?,
together()?, logcombine()?, or something else? And use this particular
function directly, because those are well defined and thus your algorithm
will be robust.
Nonetheless, especially for interactive use, or when you don't know
anything about the structure of the expression, simplify() tries to apply
intelligent heuristics to make the input expression "simpler". For
example:
>>> from sympy import simplify, cos, sin
>>> from sympy.abc import x, y
>>> a = (x + x**2)/(x*sin(y)**2 + x*cos(y)**2)
>>> a
(x**2 + x)/(x*sin(y)**2 + x*cos(y)**2)
>>> simplify(a)
x + 1
Note that we could have obtained the same result by using specific
simplification functions:
>>> from sympy import trigsimp, cancel
>>> trigsimp(a)
(x**2 + x)/x
>>> cancel(_)
x + 1
In some cases, applying :func:`simplify` may actually result in some more
complicated expression. The default ``ratio=1.7`` prevents more extreme
cases: if (result length)/(input length) > ratio, then input is returned
unmodified. The ``measure`` parameter lets you specify the function used
to determine how complex an expression is. The function should take a
single argument as an expression and return a number such that if
expression ``a`` is more complex than expression ``b``, then
``measure(a) > measure(b)``. The default measure function is
:func:`count_ops`, which returns the total number of operations in the
expression.
For example, if ``ratio=1``, ``simplify`` output can't be longer
than input.
::
>>> from sympy import sqrt, simplify, count_ops, oo
>>> root = 1/(sqrt(2)+3)
Since ``simplify(root)`` would result in a slightly longer expression,
root is returned unchanged instead::
>>> simplify(root, ratio=1) == root
True
If ``ratio=oo``, simplify will be applied anyway::
>>> count_ops(simplify(root, ratio=oo)) > count_ops(root)
True
Note that the shortest expression is not necessary the simplest, so
setting ``ratio`` to 1 may not be a good idea.
Heuristically, the default value ``ratio=1.7`` seems like a reasonable
choice.
You can easily define your own measure function based on what you feel
should represent the "size" or "complexity" of the input expression. Note
that some choices, such as ``lambda expr: len(str(expr))`` may appear to be
good metrics, but have other problems (in this case, the measure function
may slow down simplify too much for very large expressions). If you don't
know what a good metric would be, the default, ``count_ops``, is a good
one.
For example:
>>> from sympy import symbols, log
>>> a, b = symbols('a b', positive=True)
>>> g = log(a) + log(b) + log(a)*log(1/b)
>>> h = simplify(g)
>>> h
log(a*b**(-log(a) + 1))
>>> count_ops(g)
8
>>> count_ops(h)
5
So you can see that ``h`` is simpler than ``g`` using the count_ops metric.
However, we may not like how ``simplify`` (in this case, using
``logcombine``) has created the ``b**(log(1/a) + 1)`` term. A simple way
to reduce this would be to give more weight to powers as operations in
``count_ops``. We can do this by using the ``visual=True`` option:
>>> print(count_ops(g, visual=True))
2*ADD + DIV + 4*LOG + MUL
>>> print(count_ops(h, visual=True))
2*LOG + MUL + POW + SUB
>>> from sympy import Symbol, S
>>> def my_measure(expr):
... POW = Symbol('POW')
... # Discourage powers by giving POW a weight of 10
... count = count_ops(expr, visual=True).subs(POW, 10)
... # Every other operation gets a weight of 1 (the default)
... count = count.replace(Symbol, type(S.One))
... return count
>>> my_measure(g)
8
>>> my_measure(h)
14
>>> 15./8 > 1.7 # 1.7 is the default ratio
True
>>> simplify(g, measure=my_measure)
-log(a)*log(b) + log(a) + log(b)
Note that because ``simplify()`` internally tries many different
simplification strategies and then compares them using the measure
function, we get a completely different result that is still different
from the input expression by doing this.
"""
expr = sympify(expr)
try:
return expr._eval_simplify(ratio=ratio, measure=measure)
except AttributeError:
pass
original_expr = expr = signsimp(expr)
from sympy.simplify.hyperexpand import hyperexpand
from sympy.functions.special.bessel import BesselBase
from sympy import Sum, Product
if not isinstance(expr, Basic) or not expr.args: # XXX: temporary hack
return expr
if not isinstance(expr, (Add, Mul, Pow, ExpBase)):
if isinstance(expr, Function) and hasattr(expr, "inverse"):
if len(expr.args) == 1 and len(expr.args[0].args) == 1 and \
isinstance(expr.args[0], expr.inverse(argindex=1)):
return simplify(expr.args[0].args[0], ratio=ratio,
measure=measure, fu=fu)
return expr.func(*[simplify(x, ratio=ratio, measure=measure, fu=fu)
for x in expr.args])
# TODO: Apply different strategies, considering expression pattern:
# is it a purely rational function? Is there any trigonometric function?...
# See also https://github.com/sympy/sympy/pull/185.
def shorter(*choices):
'''Return the choice that has the fewest ops. In case of a tie,
the expression listed first is selected.'''
if not has_variety(choices):
return choices[0]
return min(choices, key=measure)
expr = bottom_up(expr, lambda w: w.normal())
expr = Mul(*powsimp(expr).as_content_primitive())
_e = cancel(expr)
expr1 = shorter(_e, _mexpand(_e).cancel()) # issue 6829
expr2 = shorter(together(expr, deep=True), together(expr1, deep=True))
if ratio is S.Infinity:
expr = expr2
else:
expr = shorter(expr2, expr1, expr)
if not isinstance(expr, Basic): # XXX: temporary hack
return expr
expr = factor_terms(expr, sign=False)
# hyperexpand automatically only works on hypergeometric terms
expr = hyperexpand(expr)
expr = piecewise_fold(expr)
if expr.has(BesselBase):
expr = besselsimp(expr)
if expr.has(TrigonometricFunction) and not fu or expr.has(
HyperbolicFunction):
expr = trigsimp(expr, deep=True)
if expr.has(log):
expr = shorter(expand_log(expr, deep=True), logcombine(expr))
if expr.has(CombinatorialFunction, gamma):
expr = combsimp(expr)
if expr.has(Sum):
expr = sum_simplify(expr)
if expr.has(Product):
expr = product_simplify(expr)
short = shorter(powsimp(expr, combine='exp', deep=True), powsimp(expr), expr)
short = shorter(short, factor_terms(short), expand_power_exp(expand_mul(short)))
if short.has(TrigonometricFunction, HyperbolicFunction, ExpBase):
short = exptrigsimp(short, simplify=False)
# get rid of hollow 2-arg Mul factorization
hollow_mul = Transform(
lambda x: Mul(*x.args),
lambda x:
x.is_Mul and
len(x.args) == 2 and
x.args[0].is_Number and
x.args[1].is_Add and
x.is_commutative)
expr = short.xreplace(hollow_mul)
numer, denom = expr.as_numer_denom()
if denom.is_Add:
n, d = fraction(radsimp(1/denom, symbolic=False, max_terms=1))
if n is not S.One:
expr = (numer*n).expand()/d
if expr.could_extract_minus_sign():
n, d = fraction(expr)
if d != 0:
expr = signsimp(-n/(-d))
if measure(expr) > ratio*measure(original_expr):
expr = original_expr
return expr
def solveset_real(f, symbol):
""" Solves a real valued equation.
Parameters
==========
f : Expr
The target equation
symbol : Symbol
The variable for which the equation is solved
Returns
=======
Set
A set of values for `symbol` for which `f` is equal to
zero. An `EmptySet` is returned if no solution is found.
A `ConditionSet` is returned as unsolved object if algorithms
to evaluate complete solutions are not yet implemented.
`solveset_real` claims to be complete in the set of the solution it
returns.
Raises
======
NotImplementedError
Algorithms to solve inequalities in complex domain are
not yet implemented.
ValueError
The input is not valid.
RuntimeError
It is a bug, please report to the github issue tracker.
See Also
=======
solveset_complex : solver for complex domain
Examples
========
>>> from sympy import Symbol, exp, sin, sqrt, I
>>> from sympy.solvers.solveset import solveset_real
>>> x = Symbol('x', real=True)
>>> a = Symbol('a', real=True, finite=True, positive=True)
>>> solveset_real(x**2 - 1, x)
{-1, 1}
>>> solveset_real(sqrt(5*x + 6) - 2 - x, x)
{-1, 2}
>>> solveset_real(x - I, x)
EmptySet()
>>> solveset_real(x - a, x)
{a}
>>> solveset_real(exp(x) - a, x)
{log(a)}
* In case the equation has infinitely many solutions an infinitely indexed
`ImageSet` is returned.
>>> solveset_real(sin(x) - 1, x)
ImageSet(Lambda(_n, 2*_n*pi + pi/2), Integers())
* If the equation is true for any arbitrary value of the symbol a `S.Reals`
set is returned.
>>> solveset_real(x - x, x)
(-oo, oo)
"""
if not symbol.is_Symbol:
raise ValueError(" %s is not a symbol" % (symbol))
f = sympify(f)
if not isinstance(f, (Expr, Number)):
raise ValueError(" %s is not a valid sympy expression" % (f))
original_eq = f
f = together(f)
# In this, unlike in solveset_complex, expression should only
# be expanded when fraction(f)[1] does not contain the symbol
# for which we are solving
if not symbol in fraction(f)[1].free_symbols and f.is_rational_function():
f = expand(f)
if f.has(Piecewise):
f = piecewise_fold(f)
result = EmptySet()
if f.expand().is_zero:
return S.Reals
elif not f.has(symbol):
return EmptySet()
elif f.is_Mul and all([_is_finite_with_finite_vars(m) for m in f.args]):
# if f(x) and g(x) are both finite we can say that the solution of
# f(x)*g(x) == 0 is same as Union(f(x) == 0, g(x) == 0) is not true in
# general. g(x) can grow to infinitely large for the values where
# f(x) == 0. To be sure that we are not silently allowing any
# wrong solutions we are using this technique only if both f and g are
# finite for a finite input.
result = Union(*[solveset_real(m, symbol) for m in f.args])
elif _is_function_class_equation(TrigonometricFunction, f, symbol) or \
_is_function_class_equation(HyperbolicFunction, f, symbol):
result = _solve_real_trig(f, symbol)
elif f.is_Piecewise:
result = EmptySet()
expr_set_pairs = f.as_expr_set_pairs()
for (expr, in_set) in expr_set_pairs:
solns = solveset_real(expr, symbol).intersect(in_set)
result = result + solns
else:
lhs, rhs_s = invert_real(f, 0, symbol)
if lhs == symbol:
result = rhs_s
elif isinstance(rhs_s, FiniteSet):
equations = [lhs - rhs for rhs in rhs_s]
for equation in equations:
if equation == f:
if any(
_has_rational_power(g, symbol)[0]
for g in equation.args):
result += _solve_radical(equation, symbol,
solveset_real)
elif equation.has(Abs):
result += _solve_abs(f, symbol)
else:
result += _solve_as_rational(
equation,
symbol,
solveset_solver=solveset_real,
as_poly_solver=_solve_as_poly_real)
else:
result += solveset_real(equation, symbol)
else:
result = ConditionSet(symbol, Eq(f, 0), S.Reals)
if isinstance(result, FiniteSet):
result = [
s for s in result
if isinstance(s, RootOf) or domain_check(original_eq, symbol, s)
]
return FiniteSet(*result).intersect(S.Reals)
else:
return result.intersect(S.Reals)
def solveset_real(f, symbol):
""" Solves a real valued equation.
Parameters
==========
f : Expr
The target equation
symbol : Symbol
The variable for which the equation is solved
Returns
=======
Set
A set of values for `symbol` for which `f` is equal to
zero. An `EmptySet` is returned if no solution is found.
`solveset_real` claims to be complete in the set of the solution it
returns.
Raises
======
NotImplementedError
The algorithms for to find the solution of the given equation are
not yet implemented.
ValueError
The input is not valid.
RuntimeError
It is a bug, please report to the github issue tracker.
See Also
=======
solveset_complex : solver for complex domain
Examples
========
>>> from sympy import Symbol, exp, sin, sqrt, I
>>> from sympy.solvers.solveset import solveset_real
>>> x = Symbol('x', real=True)
>>> a = Symbol('a', real=True, finite=True, positive=True)
>>> solveset_real(x**2 - 1, x)
{-1, 1}
>>> solveset_real(sqrt(5*x + 6) - 2 - x, x)
{-1, 2}
>>> solveset_real(x - I, x)
EmptySet()
>>> solveset_real(x - a, x)
{a}
>>> solveset_real(exp(x) - a, x)
{log(a)}
In case the equation has infinitely many solutions an infinitely indexed
`ImageSet` is returned.
>>> solveset_real(sin(x) - 1, x)
ImageSet(Lambda(_n, 2*_n*pi + pi/2), Integers())
If the equation is true for any arbitrary value of the symbol a `S.Reals`
set is returned.
>>> solveset_real(x - x, x)
(-oo, oo)
"""
if not symbol.is_Symbol:
raise ValueError(" %s is not a symbol" % (symbol))
f = sympify(f)
if not isinstance(f, (Expr, Number)):
raise ValueError(" %s is not a valid sympy expression" % (f))
original_eq = f
f = together(f)
if f.has(Piecewise):
f = piecewise_fold(f)
result = EmptySet()
if f.expand().is_zero:
return S.Reals
elif not f.has(symbol):
return EmptySet()
elif f.is_Mul and all([_is_finite_with_finite_vars(m) for m in f.args]):
# if f(x) and g(x) are both finite we can say that the solution of
# f(x)*g(x) == 0 is same as Union(f(x) == 0, g(x) == 0) is not true in
# general. g(x) can grow to infinitely large for the values where
# f(x) == 0. To be sure that we not are silently allowing any
# wrong solutions we are using this technique only if both f and g and
# finite for a finite input.
result = Union(*[solveset_real(m, symbol) for m in f.args])
elif _is_function_class_equation(C.TrigonometricFunction, f, symbol) or \
_is_function_class_equation(C.HyperbolicFunction, f, symbol):
result = _solve_real_trig(f, symbol)
elif f.is_Piecewise:
result = EmptySet()
expr_set_pairs = f.as_expr_set_pairs()
for (expr, in_set) in expr_set_pairs:
solns = solveset_real(expr, symbol).intersect(in_set)
result = result + solns
else:
lhs, rhs_s = invert_real(f, 0, symbol)
if lhs == symbol:
result = rhs_s
elif isinstance(rhs_s, FiniteSet):
equations = [lhs - rhs for rhs in rhs_s]
for equation in equations:
if equation == f:
if any(_has_rational_power(g, symbol)[0]
for g in equation.args):
result += _solve_radical(equation,
symbol,
solveset_real)
elif equation.has(Abs):
result += _solve_abs(f, symbol)
else:
result += _solve_as_rational(equation, symbol,
solveset_solver=solveset_real,
as_poly_solver=_solve_as_poly_real)
else:
result += solveset_real(equation, symbol)
else:
raise NotImplementedError
if isinstance(result, FiniteSet):
result = [s for s in result
if isinstance(s, RootOf)
or domain_check(original_eq, symbol, s)]
return FiniteSet(*result).intersect(S.Reals)
else:
return result.intersect(S.Reals)
def deltasummation(f, limit, no_piecewise=False):
"""
Handle summations containing a KroneckerDelta.
The idea for summation is the following:
- If we are dealing with a KroneckerDelta expression, i.e. KroneckerDelta(g(x), j),
we try to simplify it.
If we could simplify it, then we sum the resulting expression.
We already know we can sum a simplified expression, because only
simple KroneckerDelta expressions are involved.
If we couldn't simplify it, there are two cases:
1) The expression is a simple expression: we return the summation,
taking care if we are dealing with a Derivative or with a proper
KroneckerDelta.
2) The expression is not simple (i.e. KroneckerDelta(cos(x))): we can do
nothing at all.
- If the expr is a multiplication expr having a KroneckerDelta term:
First we expand it.
If the expansion did work, then we try to sum the expansion.
If not, we try to extract a simple KroneckerDelta term, then we have two
cases:
1) We have a simple KroneckerDelta term, so we return the summation.
2) We didn't have a simple term, but we do have an expression with
simplified KroneckerDelta terms, so we sum this expression.
Examples
========
>>> from sympy import oo
>>> from sympy.abc import i, j, k
>>> from sympy.concrete.delta import deltasummation
>>> from sympy import KroneckerDelta, Piecewise
>>> deltasummation(KroneckerDelta(i, k), (k, -oo, oo))
1
>>> deltasummation(KroneckerDelta(i, k), (k, 0, oo))
Piecewise((1, i >= 0), (0, True))
>>> deltasummation(KroneckerDelta(i, k), (k, 1, 3))
Piecewise((1, And(1 <= i, i <= 3)), (0, True))
>>> deltasummation(k*KroneckerDelta(i, j)*KroneckerDelta(j, k), (k, -oo, oo))
j*KroneckerDelta(i, j)
>>> deltasummation(j*KroneckerDelta(i, j), (j, -oo, oo))
i
>>> deltasummation(i*KroneckerDelta(i, j), (i, -oo, oo))
j
See Also
========
deltaproduct
sympy.functions.special.tensor_functions.KroneckerDelta
sympy.concrete.sums.summation
"""
from sympy.concrete.summations import summation
from sympy.solvers import solve
if ((limit[2] - limit[1]) < 0) is True:
return S.Zero
if not f.has(KroneckerDelta):
return summation(f, limit)
x = limit[0]
g = _expand_delta(f, x)
if g.is_Add:
return piecewise_fold(
g.func(*[deltasummation(h, limit, no_piecewise) for h in g.args]))
# try to extract a simple KroneckerDelta term
delta, expr = _extract_delta(g, x)
if not delta:
return summation(f, limit)
solns = solve(delta.args[0] - delta.args[1], x)
if len(solns) == 0:
return S.Zero
elif len(solns) != 1:
return Sum(f, limit)
value = solns[0]
if no_piecewise:
return expr.subs(x, value)
return Piecewise(
(expr.subs(x, value), Interval(*limit[1:3]).as_relational(value)),
(S.Zero, True)
)
def test_deltasummation():
ds = deltasummation
assert ds(x, (j, 1, 0)) == 0
assert ds(x, (j, 1, 3)) == 3*x
assert ds(x + y, (j, 1, 3)) == 3*(x + y)
assert ds(x*y, (j, 1, 3)) == 3*x*y
assert ds(KD(i, j), (k, 1, 3)) == 3*KD(i, j)
assert ds(x*KD(i, j), (k, 1, 3)) == 3*x*KD(i, j)
assert ds(x*y*KD(i, j), (k, 1, 3)) == 3*x*y*KD(i, j)
# return unevaluated, until it gets implemented
assert ds(KD(i**2, j**2), (j, -oo, oo)) == \
Sum(KD(i**2, j**2), (j, -oo, oo))
assert Piecewise((KD(i, k), And(S(1) <= i, i <= 3)), (0, True)) == \
ds(KD(i, j)*KD(j, k), (j, 1, 3)) == \
ds(KD(j, k)*KD(i, j), (j, 1, 3))
assert ds(KD(i, k), (k, -oo, oo)) == 1
assert ds(KD(i, k), (k, 0, oo)) == Piecewise((1, i >= 0), (0, True))
assert ds(KD(i, k), (k, 1, 3)) == \
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True))
assert ds(k*KD(i, j)*KD(j, k), (k, -oo, oo)) == j*KD(i, j)
assert ds(j*KD(i, j), (j, -oo, oo)) == i
assert ds(i*KD(i, j), (i, -oo, oo)) == j
assert ds(x, (i, 1, 3)) == 3*x
assert ds((i + j)*KD(i, j), (j, -oo, oo)) == 2*i
assert ds(KD(i, j), (j, 1, 3)) == \
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True))
assert ds(KD(i, j), (j, 1, 1)) == Piecewise((1, Eq(i, 1)), (0, True))
assert ds(KD(i, j), (j, 2, 2)) == Piecewise((1, Eq(i, 2)), (0, True))
assert ds(KD(i, j), (j, 3, 3)) == Piecewise((1, Eq(i, 3)), (0, True))
assert ds(KD(i, j), (j, 1, k)) == \
Piecewise((1, And(S(1) <= i, i <= k)), (0, True))
assert ds(KD(i, j), (j, k, 3)) == \
Piecewise((1, And(k <= i, i <= 3)), (0, True))
assert ds(KD(i, j), (j, k, l)) == \
Piecewise((1, And(k <= i, i <= l)), (0, True))
assert ds(x*KD(i, j), (j, 1, 3)) == \
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True))
assert ds(x*KD(i, j), (j, 1, 1)) == Piecewise((x, Eq(i, 1)), (0, True))
assert ds(x*KD(i, j), (j, 2, 2)) == Piecewise((x, Eq(i, 2)), (0, True))
assert ds(x*KD(i, j), (j, 3, 3)) == Piecewise((x, Eq(i, 3)), (0, True))
assert ds(x*KD(i, j), (j, 1, k)) == \
Piecewise((x, And(S(1) <= i, i <= k)), (0, True))
assert ds(x*KD(i, j), (j, k, 3)) == \
Piecewise((x, And(k <= i, i <= 3)), (0, True))
assert ds(x*KD(i, j), (j, k, l)) == \
Piecewise((x, And(k <= i, i <= l)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, 3)) == \
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, 1)) == \
Piecewise((x + y, Eq(i, 1)), (0, True))
assert ds((x + y)*KD(i, j), (j, 2, 2)) == \
Piecewise((x + y, Eq(i, 2)), (0, True))
assert ds((x + y)*KD(i, j), (j, 3, 3)) == \
Piecewise((x + y, Eq(i, 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, k)) == \
Piecewise((x + y, And(S(1) <= i, i <= k)), (0, True))
assert ds((x + y)*KD(i, j), (j, k, 3)) == \
Piecewise((x + y, And(k <= i, i <= 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, k, l)) == \
Piecewise((x + y, And(k <= i, i <= l)), (0, True))
assert ds(KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((1, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((1, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((1, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((1, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= l)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((1, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((1, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= l)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((x, Eq(j, 1)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((x, Eq(j, 2)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((x, Eq(j, 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x, And(S(1) <= j, j <= l)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x, And(l <= j, j <= 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((x, And(l <= j, j <= m)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x + y, Eq(i, 1)), (0, True)) +
Piecewise((x + y, Eq(j, 1)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x + y, Eq(i, 2)), (0, True)) +
Piecewise((x + y, Eq(j, 2)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x + y, Eq(i, 3)), (0, True)) +
Piecewise((x + y, Eq(j, 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= l)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= m)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= m)), (0, True)))
assert ds(x*y + x*KD(i, j), (j, 1, 3)) == \
Piecewise((3*x*y + x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*y + x*KD(i, j), (j, 1, 1)) == \
Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 2, 2)) == \
Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 3, 3)) == \
Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 1, k)) == \
Piecewise((k*x*y + x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*y + x*KD(i, j), (j, k, 3)) == \
Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*y + x*KD(i, j), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, 3)) == \
Piecewise((3*x*y + x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, 1)) == \
Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 2, 2)) == \
Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 3, 3)) == \
Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, k)) == \
Piecewise((k*x*y + x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*(y + KD(i, j)), (j, k, 3)) == \
Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*(y + KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, 3)) == \
Piecewise((3*x*y + 2*x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, 1)) == \
Piecewise((x*y + 2*x, Eq(i, 1)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 2, 2)) == \
Piecewise((x*y + 2*x, Eq(i, 2)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 3, 3)) == \
Piecewise((x*y + 2*x, Eq(i, 3)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, k)) == \
Piecewise((k*x*y + 2*x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, k, 3)) == Piecewise(
((4 - k)*x*y + 2*x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + 2*x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, 3)) == Piecewise(
(3*(x + y)*y + x + y, And(S(1) <= i, i <= 3)), (3*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, 1)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 1)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 2, 2)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 2)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 3, 3)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 3)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, k)) == Piecewise(
(k*(x + y)*y + x + y, And(S(1) <= i, i <= k)), (k*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, k, 3)) == Piecewise(
((4 - k)*(x + y)*y + x + y, And(k <= i, i <= 3)),
((4 - k)*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*(x + y)*y + x + y, And(k <= i, i <= l)),
((l - k + 1)*(x + y)*y, True))
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= 3)), (0, True)) +
3*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 1)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 1)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 2, 2)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 2)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 3, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 3)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, k)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= k)), (0, True)) +
k*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= 3)), (0, True)) +
(4 - k)*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, l)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= l)), (0, True)) +
(l - k + 1)*(KD(i, k) + x)*y)
def deltasummation(f, limit, no_piecewise=False):
"""
Handle summations containing a KroneckerDelta.
The idea for summation is the following:
- If we are dealing with a KroneckerDelta expression, i.e. KroneckerDelta(g(x), j),
we try to simplify it.
If we could simplify it, then we sum the resulting expression.
We already know we can sum a simplified expression, because only
simple KroneckerDelta expressions are involved.
If we couldn't simplify it, there are two cases:
1) The expression is a simple expression: we return the summation,
taking care if we are dealing with a Derivative or with a proper
KroneckerDelta.
2) The expression is not simple (i.e. KroneckerDelta(cos(x))): we can do
nothing at all.
- If the expr is a multiplication expr having a KroneckerDelta term:
First we expand it.
If the expansion did work, then we try to sum the expansion.
If not, we try to extract a simple KroneckerDelta term, then we have two
cases:
1) We have a simple KroneckerDelta term, so we return the summation.
2) We didn't have a simple term, but we do have an expression with
simplified KroneckerDelta terms, so we sum this expression.
Examples
========
>>> from sympy import oo
>>> from sympy.abc import i, j, k
>>> from sympy.concrete.delta import deltasummation
>>> from sympy import KroneckerDelta, Piecewise
>>> deltasummation(KroneckerDelta(i, k), (k, -oo, oo))
1
>>> deltasummation(KroneckerDelta(i, k), (k, 0, oo))
Piecewise((1, i >= 0), (0, True))
>>> deltasummation(KroneckerDelta(i, k), (k, 1, 3))
Piecewise((1, And(1 <= i, i <= 3)), (0, True))
>>> deltasummation(k*KroneckerDelta(i, j)*KroneckerDelta(j, k), (k, -oo, oo))
j*KroneckerDelta(i, j)
>>> deltasummation(j*KroneckerDelta(i, j), (j, -oo, oo))
i
>>> deltasummation(i*KroneckerDelta(i, j), (i, -oo, oo))
j
See Also
========
deltaproduct
sympy.functions.special.tensor_functions.KroneckerDelta
sympy.concrete.sums.summation
"""
from sympy.concrete.summations import summation
from sympy.solvers import solve
if ((limit[2] - limit[1]) < 0) is True:
return S.Zero
if not f.has(KroneckerDelta):
return summation(f, limit)
x = limit[0]
g = _expand_delta(f, x)
if g.is_Add:
return piecewise_fold(
g.func(*[deltasummation(h, limit, no_piecewise) for h in g.args]))
# try to extract a simple KroneckerDelta term
delta, expr = _extract_delta(g, x)
if not delta:
return summation(f, limit)
solns = solve(delta.args[0] - delta.args[1], x)
if len(solns) == 0:
return S.Zero
elif len(solns) != 1:
return Sum(f, limit)
value = solns[0]
if no_piecewise:
return expr.subs(x, value)
return Piecewise(
(expr.subs(x, value), Interval(*limit[1:3]).as_relational(value)),
(S.Zero, True)
)
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d * b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c * b1)
else:
new_args = []
# Just combining the Piecewise without any fancy optimization
p1 = piecewise_fold(c * b1)
p2 = piecewise_fold(d * b2)
# Search all Piecewise arguments except (0, True)
p2args = list(p2.args[:-1])
# This merging algorithm assumes the conditions in
# p1 and p2 are sorted
for arg in p1.args[:-1]:
# Conditional of Piecewise are And objects
# the args of the And object is a tuple of two
# Relational objects the numerical value is in the .rhs
# of the Relational object
expr = arg.expr
cond = arg.cond
lower = cond.args[0].rhs
# Check p2 for matching conditions that can be merged
for i, arg2 in enumerate(p2args):
expr2 = arg2.expr
cond2 = arg2.cond
lower_2 = cond2.args[0].rhs
upper_2 = cond2.args[1].rhs
if cond2 == cond:
# Conditions match, join expressions
expr += expr2
# Remove matching element
del p2args[i]
# No need to check the rest
break
elif lower_2 < lower and upper_2 <= lower:
# Check if arg2 condition smaller than arg1,
# add to new_args by itself (no match expected
# in p1)
new_args.append(arg2)
del p2args[i]
break
# Checked all, add expr and cond
new_args.append((expr, cond))
# Add remaining items from p2args
new_args.extend(p2args)
# Add final (0, True)
new_args.append((0, True))
rv = Piecewise(*new_args)
return rv.expand()
def test_deltasummation():
ds = deltasummation
assert ds(x, (j, 1, 0)) == 0
assert ds(x, (j, 1, 3)) == 3*x
assert ds(x + y, (j, 1, 3)) == 3*(x + y)
assert ds(x*y, (j, 1, 3)) == 3*x*y
assert ds(KD(i, j), (k, 1, 3)) == 3*KD(i, j)
assert ds(x*KD(i, j), (k, 1, 3)) == 3*x*KD(i, j)
assert ds(x*y*KD(i, j), (k, 1, 3)) == 3*x*y*KD(i, j)
n = symbols('n', integer=True, nonzero=True)
assert ds(KD(n, 0), (n, 1, 3)) == 0
# return unevaluated, until it gets implemented
assert ds(KD(i**2, j**2), (j, -oo, oo)) == \
Sum(KD(i**2, j**2), (j, -oo, oo))
assert Piecewise((KD(i, k), And(S(1) <= i, i <= 3)), (0, True)) == \
ds(KD(i, j)*KD(j, k), (j, 1, 3)) == \
ds(KD(j, k)*KD(i, j), (j, 1, 3))
assert ds(KD(i, k), (k, -oo, oo)) == 1
assert ds(KD(i, k), (k, 0, oo)) == Piecewise((1, i >= 0), (0, True))
assert ds(KD(i, k), (k, 1, 3)) == \
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True))
assert ds(k*KD(i, j)*KD(j, k), (k, -oo, oo)) == j*KD(i, j)
assert ds(j*KD(i, j), (j, -oo, oo)) == i
assert ds(i*KD(i, j), (i, -oo, oo)) == j
assert ds(x, (i, 1, 3)) == 3*x
assert ds((i + j)*KD(i, j), (j, -oo, oo)) == 2*i
assert ds(KD(i, j), (j, 1, 3)) == \
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True))
assert ds(KD(i, j), (j, 1, 1)) == Piecewise((1, Eq(i, 1)), (0, True))
assert ds(KD(i, j), (j, 2, 2)) == Piecewise((1, Eq(i, 2)), (0, True))
assert ds(KD(i, j), (j, 3, 3)) == Piecewise((1, Eq(i, 3)), (0, True))
assert ds(KD(i, j), (j, 1, k)) == \
Piecewise((1, And(S(1) <= i, i <= k)), (0, True))
assert ds(KD(i, j), (j, k, 3)) == \
Piecewise((1, And(k <= i, i <= 3)), (0, True))
assert ds(KD(i, j), (j, k, l)) == \
Piecewise((1, And(k <= i, i <= l)), (0, True))
assert ds(x*KD(i, j), (j, 1, 3)) == \
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True))
assert ds(x*KD(i, j), (j, 1, 1)) == Piecewise((x, Eq(i, 1)), (0, True))
assert ds(x*KD(i, j), (j, 2, 2)) == Piecewise((x, Eq(i, 2)), (0, True))
assert ds(x*KD(i, j), (j, 3, 3)) == Piecewise((x, Eq(i, 3)), (0, True))
assert ds(x*KD(i, j), (j, 1, k)) == \
Piecewise((x, And(S(1) <= i, i <= k)), (0, True))
assert ds(x*KD(i, j), (j, k, 3)) == \
Piecewise((x, And(k <= i, i <= 3)), (0, True))
assert ds(x*KD(i, j), (j, k, l)) == \
Piecewise((x, And(k <= i, i <= l)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, 3)) == \
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, 1)) == \
Piecewise((x + y, Eq(i, 1)), (0, True))
assert ds((x + y)*KD(i, j), (j, 2, 2)) == \
Piecewise((x + y, Eq(i, 2)), (0, True))
assert ds((x + y)*KD(i, j), (j, 3, 3)) == \
Piecewise((x + y, Eq(i, 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, 1, k)) == \
Piecewise((x + y, And(S(1) <= i, i <= k)), (0, True))
assert ds((x + y)*KD(i, j), (j, k, 3)) == \
Piecewise((x + y, And(k <= i, i <= 3)), (0, True))
assert ds((x + y)*KD(i, j), (j, k, l)) == \
Piecewise((x + y, And(k <= i, i <= l)), (0, True))
assert ds(KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((1, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((1, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((1, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((1, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((1, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= l)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((1, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((1, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((1, Eq(j, 1)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((1, Eq(j, 2)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((1, Eq(j, 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((1, And(S(1) <= j, j <= l)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((1, And(l <= j, j <= 3)), (0, True)))
assert ds(x*KD(i, k) + KD(j, k), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((1, And(l <= j, j <= m)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x, And(S(1) <= j, j <= 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x, Eq(i, 1)), (0, True)) +
Piecewise((x, Eq(j, 1)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x, Eq(i, 2)), (0, True)) +
Piecewise((x, Eq(j, 2)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x, Eq(i, 3)), (0, True)) +
Piecewise((x, Eq(j, 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x, And(S(1) <= j, j <= l)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x, And(l <= j, j <= 3)), (0, True)))
assert ds(x*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x, And(l <= i, i <= m)), (0, True)) +
Piecewise((x, And(l <= j, j <= m)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 3)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, 1)) == piecewise_fold(
Piecewise((x + y, Eq(i, 1)), (0, True)) +
Piecewise((x + y, Eq(j, 1)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 2, 2)) == piecewise_fold(
Piecewise((x + y, Eq(i, 2)), (0, True)) +
Piecewise((x + y, Eq(j, 2)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 3, 3)) == piecewise_fold(
Piecewise((x + y, Eq(i, 3)), (0, True)) +
Piecewise((x + y, Eq(j, 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, 1, l)) == piecewise_fold(
Piecewise((x + y, And(S(1) <= i, i <= l)), (0, True)) +
Piecewise((x + y, And(S(1) <= j, j <= l)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, 3)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= 3)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= 3)), (0, True)))
assert ds((x + y)*(KD(i, k) + KD(j, k)), (k, l, m)) == piecewise_fold(
Piecewise((x + y, And(l <= i, i <= m)), (0, True)) +
Piecewise((x + y, And(l <= j, j <= m)), (0, True)))
assert ds(x*y + x*KD(i, j), (j, 1, 3)) == \
Piecewise((3*x*y + x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*y + x*KD(i, j), (j, 1, 1)) == \
Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 2, 2)) == \
Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 3, 3)) == \
Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
assert ds(x*y + x*KD(i, j), (j, 1, k)) == \
Piecewise((k*x*y + x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*y + x*KD(i, j), (j, k, 3)) == \
Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*y + x*KD(i, j), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, 3)) == \
Piecewise((3*x*y + x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, 1)) == \
Piecewise((x*y + x, Eq(i, 1)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 2, 2)) == \
Piecewise((x*y + x, Eq(i, 2)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 3, 3)) == \
Piecewise((x*y + x, Eq(i, 3)), (x*y, True))
assert ds(x*(y + KD(i, j)), (j, 1, k)) == \
Piecewise((k*x*y + x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*(y + KD(i, j)), (j, k, 3)) == \
Piecewise(((4 - k)*x*y + x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*(y + KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, 3)) == \
Piecewise((3*x*y + 2*x, And(S(1) <= i, i <= 3)), (3*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, 1)) == \
Piecewise((x*y + 2*x, Eq(i, 1)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 2, 2)) == \
Piecewise((x*y + 2*x, Eq(i, 2)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 3, 3)) == \
Piecewise((x*y + 2*x, Eq(i, 3)), (x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, 1, k)) == \
Piecewise((k*x*y + 2*x, And(S(1) <= i, i <= k)), (k*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, k, 3)) == Piecewise(
((4 - k)*x*y + 2*x, And(k <= i, i <= 3)), ((4 - k)*x*y, True))
assert ds(x*(y + 2*KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*x*y + 2*x, And(k <= i, i <= l)), ((l - k + 1)*x*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, 3)) == Piecewise(
(3*(x + y)*y + x + y, And(S(1) <= i, i <= 3)), (3*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, 1)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 1)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 2, 2)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 2)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 3, 3)) == \
Piecewise(((x + y)*y + x + y, Eq(i, 3)), ((x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, 1, k)) == Piecewise(
(k*(x + y)*y + x + y, And(S(1) <= i, i <= k)), (k*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, k, 3)) == Piecewise(
((4 - k)*(x + y)*y + x + y, And(k <= i, i <= 3)),
((4 - k)*(x + y)*y, True))
assert ds((x + y)*(y + KD(i, j)), (j, k, l)) == Piecewise(
((l - k + 1)*(x + y)*y + x + y, And(k <= i, i <= l)),
((l - k + 1)*(x + y)*y, True))
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= 3)), (0, True)) +
3*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, 1)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 1)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 2, 2)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 2)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 3, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, Eq(i, 3)), (0, True)) +
(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, 1, k)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(S(1) <= i, i <= k)), (0, True)) +
k*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, 3)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= 3)), (0, True)) +
(4 - k)*(KD(i, k) + x)*y)
assert ds((x + KD(i, k))*(y + KD(i, j)), (j, k, l)) == piecewise_fold(
Piecewise((KD(i, k) + x, And(k <= i, i <= l)), (0, True)) +
(l - k + 1)*(KD(i, k) + x)*y)
def simplify(expr, ratio=1.7, measure=count_ops, rational=False):
# type: (object, object, object, object) -> object
"""
Simplifies the given expression.
Simplification is not a well defined term and the exact strategies
this function tries can change in the future versions of SymPy. If
your algorithm relies on "simplification" (whatever it is), try to
determine what you need exactly - is it powsimp()?, radsimp()?,
together()?, logcombine()?, or something else? And use this particular
function directly, because those are well defined and thus your algorithm
will be robust.
Nonetheless, especially for interactive use, or when you don't know
anything about the structure of the expression, simplify() tries to apply
intelligent heuristics to make the input expression "simpler". For
example:
>>> from sympy import simplify, cos, sin
>>> from sympy.abc import x, y
>>> a = (x + x**2)/(x*sin(y)**2 + x*cos(y)**2)
>>> a
(x**2 + x)/(x*sin(y)**2 + x*cos(y)**2)
>>> simplify(a)
x + 1
Note that we could have obtained the same result by using specific
simplification functions:
>>> from sympy import trigsimp, cancel
>>> trigsimp(a)
(x**2 + x)/x
>>> cancel(_)
x + 1
In some cases, applying :func:`simplify` may actually result in some more
complicated expression. The default ``ratio=1.7`` prevents more extreme
cases: if (result length)/(input length) > ratio, then input is returned
unmodified. The ``measure`` parameter lets you specify the function used
to determine how complex an expression is. The function should take a
single argument as an expression and return a number such that if
expression ``a`` is more complex than expression ``b``, then
``measure(a) > measure(b)``. The default measure function is
:func:`count_ops`, which returns the total number of operations in the
expression.
For example, if ``ratio=1``, ``simplify`` output can't be longer
than input.
::
>>> from sympy import sqrt, simplify, count_ops, oo
>>> root = 1/(sqrt(2)+3)
Since ``simplify(root)`` would result in a slightly longer expression,
root is returned unchanged instead::
>>> simplify(root, ratio=1) == root
True
If ``ratio=oo``, simplify will be applied anyway::
>>> count_ops(simplify(root, ratio=oo)) > count_ops(root)
True
Note that the shortest expression is not necessary the simplest, so
setting ``ratio`` to 1 may not be a good idea.
Heuristically, the default value ``ratio=1.7`` seems like a reasonable
choice.
You can easily define your own measure function based on what you feel
should represent the "size" or "complexity" of the input expression. Note
that some choices, such as ``lambda expr: len(str(expr))`` may appear to be
good metrics, but have other problems (in this case, the measure function
may slow down simplify too much for very large expressions). If you don't
know what a good metric would be, the default, ``count_ops``, is a good
one.
For example:
>>> from sympy import symbols, log
>>> a, b = symbols('a b', positive=True)
>>> g = log(a) + log(b) + log(a)*log(1/b)
>>> h = simplify(g)
>>> h
log(a*b**(-log(a) + 1))
>>> count_ops(g)
8
>>> count_ops(h)
5
So you can see that ``h`` is simpler than ``g`` using the count_ops metric.
However, we may not like how ``simplify`` (in this case, using
``logcombine``) has created the ``b**(log(1/a) + 1)`` term. A simple way
to reduce this would be to give more weight to powers as operations in
``count_ops``. We can do this by using the ``visual=True`` option:
>>> print(count_ops(g, visual=True))
2*ADD + DIV + 4*LOG + MUL
>>> print(count_ops(h, visual=True))
2*LOG + MUL + POW + SUB
>>> from sympy import Symbol, S
>>> def my_measure(expr):
... POW = Symbol('POW')
... # Discourage powers by giving POW a weight of 10
... count = count_ops(expr, visual=True).subs(POW, 10)
... # Every other operation gets a weight of 1 (the default)
... count = count.replace(Symbol, type(S.One))
... return count
>>> my_measure(g)
8
>>> my_measure(h)
14
>>> 15./8 > 1.7 # 1.7 is the default ratio
True
>>> simplify(g, measure=my_measure)
-log(a)*log(b) + log(a) + log(b)
Note that because ``simplify()`` internally tries many different
simplification strategies and then compares them using the measure
function, we get a completely different result that is still different
from the input expression by doing this.
If rational=True, Floats will be recast as Rationals before simplification.
If rational=None, Floats will be recast as Rationals but the result will
be recast as Floats. If rational=False(default) then nothing will be done
to the Floats.
"""
expr = sympify(expr)
try:
return expr._eval_simplify(ratio=ratio, measure=measure)
except AttributeError:
pass
original_expr = expr = signsimp(expr)
from sympy.simplify.hyperexpand import hyperexpand
from sympy.functions.special.bessel import BesselBase
from sympy import Sum, Product
if not isinstance(expr, Basic) or not expr.args: # XXX: temporary hack
return expr
if not isinstance(expr, (Add, Mul, Pow, ExpBase)):
if isinstance(expr, Function) and hasattr(expr, "inverse"):
if len(expr.args) == 1 and len(expr.args[0].args) == 1 and \
isinstance(expr.args[0], expr.inverse(argindex=1)):
return simplify(expr.args[0].args[0], ratio=ratio,
measure=measure, rational=rational)
return expr.func(*[simplify(x, ratio=ratio, measure=measure, rational=rational)
for x in expr.args])
# TODO: Apply different strategies, considering expression pattern:
# is it a purely rational function? Is there any trigonometric function?...
# See also https://github.com/sympy/sympy/pull/185.
def shorter(*choices):
'''Return the choice that has the fewest ops. In case of a tie,
the expression listed first is selected.'''
if not has_variety(choices):
return choices[0]
return min(choices, key=measure)
# rationalize Floats
floats = False
if rational is not False and expr.has(Float):
floats = True
expr = nsimplify(expr, rational=True)
expr = bottom_up(expr, lambda w: w.normal())
expr = Mul(*powsimp(expr).as_content_primitive())
_e = cancel(expr)
expr1 = shorter(_e, _mexpand(_e).cancel()) # issue 6829
expr2 = shorter(together(expr, deep=True), together(expr1, deep=True))
if ratio is S.Infinity:
expr = expr2
else:
expr = shorter(expr2, expr1, expr)
if not isinstance(expr, Basic): # XXX: temporary hack
return expr
expr = factor_terms(expr, sign=False)
# hyperexpand automatically only works on hypergeometric terms
expr = hyperexpand(expr)
expr = piecewise_fold(expr)
if expr.has(BesselBase):
expr = besselsimp(expr)
if expr.has(TrigonometricFunction, HyperbolicFunction):
expr = trigsimp(expr, deep=True)
if expr.has(log):
expr = shorter(expand_log(expr, deep=True), logcombine(expr))
if expr.has(CombinatorialFunction, gamma):
# expression with gamma functions or non-integer arguments is
# automatically passed to gammasimp
expr = combsimp(expr)
if expr.has(Sum):
expr = sum_simplify(expr)
if expr.has(Product):
expr = product_simplify(expr)
short = shorter(powsimp(expr, combine='exp', deep=True), powsimp(expr), expr)
short = shorter(short, cancel(short))
short = shorter(short, factor_terms(short), expand_power_exp(expand_mul(short)))
if short.has(TrigonometricFunction, HyperbolicFunction, ExpBase):
short = exptrigsimp(short)
# get rid of hollow 2-arg Mul factorization
hollow_mul = Transform(
lambda x: Mul(*x.args),
lambda x:
x.is_Mul and
len(x.args) == 2 and
x.args[0].is_Number and
x.args[1].is_Add and
x.is_commutative)
expr = short.xreplace(hollow_mul)
numer, denom = expr.as_numer_denom()
if denom.is_Add:
n, d = fraction(radsimp(1/denom, symbolic=False, max_terms=1))
if n is not S.One:
expr = (numer*n).expand()/d
if expr.could_extract_minus_sign():
n, d = fraction(expr)
if d != 0:
expr = signsimp(-n/(-d))
if measure(expr) > ratio*measure(original_expr):
expr = original_expr
# restore floats
if floats and rational is None:
expr = nfloat(expr, exponent=False)
return expr
def _add_splines(c, b1, d, b2):
"""Construct c*b1 + d*b2."""
if b1 == S.Zero or c == S.Zero:
rv = piecewise_fold(d*b2)
elif b2 == S.Zero or d == S.Zero:
rv = piecewise_fold(c*b1)
else:
new_args = []
n_intervals = len(b1.args)
if n_intervals != len(b2.args):
# Args of b1 and b2 are not equal. Just combining the Piecewise without any fancy optimisation
p1 = piecewise_fold(c*b1)
p2 = piecewise_fold(d*b2)
# Search all Piecewise arguments except (0, True)
p2args = list(p2.args[:-1])
# This merging algorithm assume the conditions in p1 and p2 are sorted
for arg in p1.args[:-1]:
# Conditional of Piecewise are And objects
# the args of the And object is a tuple of two Relational objects
# the numerical value is in the .rhs of the Relational object
expr = arg.expr
cond = arg.cond
lower = cond.args[0].rhs
# Check p2 for matching conditions that can be merged
for i, arg2 in enumerate(p2args):
expr2 = arg2.expr
cond2 = arg2.cond
lower_2 = cond2.args[0].rhs
upper_2 = cond2.args[1].rhs
if cond2 == cond:
# Conditions match, join expressions
expr += expr2
# Remove matching element
del p2args[i]
# No need to check the rest
break
elif lower_2 < lower and upper_2 <= lower:
# Check if arg2 condition smaller than arg1, add to new_args by itself (no match expected in p1)
new_args.append(arg2)
del p2args[i]
break
# Checked all, add expr and cond
new_args.append((expr, cond))
# Add remaining items from p2args
new_args.extend(p2args)
# Add final (0, True)
new_args.append((0, True))
else:
new_args.append((c*b1.args[0].expr, b1.args[0].cond))
for i in range(1, n_intervals - 1):
new_args.append((
c*b1.args[i].expr + d*b2.args[i - 1].expr,
b1.args[i].cond
))
new_args.append((d*b2.args[-2].expr, b2.args[-2].cond))
new_args.append(b2.args[-1])
rv = Piecewise(*new_args)
return rv.expand()
