def test_roots_quadratic():
assert roots_quadratic(Poly(2*x**2, x)) == [0, 0]
assert roots_quadratic(Poly(2*x**2 + 3*x, x)) == [Rational(-3, 2), 0]
assert roots_quadratic(Poly(2*x**2 + 3, x)) == [-I*sqrt(6)/2, I*sqrt(6)/2]
assert roots_quadratic(Poly(2*x**2 + 4*x + 3, x)) == [-1 - I*sqrt(2)/2, -1 + I*sqrt(2)/2]
_check(Poly(2*x**2 + 4*x + 3, x).all_roots())
f = x**2 + (2*a*e + 2*c*e)/(a - c)*x + (d - b + a*e**2 - c*e**2)/(a - c)
assert roots_quadratic(Poly(f, x)) == \
[-e*(a + c)/(a - c) - sqrt((a*b + c*d - a*d - b*c + 4*a*c*e**2))/(a - c),
-e*(a + c)/(a - c) + sqrt((a*b + c*d - a*d - b*c + 4*a*c*e**2))/(a - c)]
# check for simplification
f = Poly(y*x**2 - 2*x - 2*y, x)
assert roots_quadratic(f) == \
[-sqrt(2*y**2 + 1)/y + 1/y, sqrt(2*y**2 + 1)/y + 1/y]
f = Poly(x**2 + (-y**2 - 2)*x + y**2 + 1, x)
assert roots_quadratic(f) == \
[1,y**2 + 1]
f = Poly(sqrt(2)*x**2 - 1, x)
r = roots_quadratic(f)
assert r == _nsort(r)
# issue 8255
f = Poly(-24*x**2 - 180*x + 264)
assert [w.n(2) for w in f.all_roots(radicals=True)] == \
[w.n(2) for w in f.all_roots(radicals=False)]
for _a, _b, _c in cartes((-2, 2), (-2, 2), (0, -1)):
f = Poly(_a*x**2 + _b*x + _c)
roots = roots_quadratic(f)
assert roots == _nsort(roots)
def test__nsort():
# issue 6137
r = S('''[3/2 + sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) - 4/sqrt(-7/3 +
61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3)) -
61/(18*(-415/216 + 13*I/12)**(1/3)))/2 - sqrt(-7/3 + 61/(18*(-415/216
+ 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3))/2, 3/2 - sqrt(-7/3
+ 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3))/2 - sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) -
4/sqrt(-7/3 + 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3)) - 61/(18*(-415/216 + 13*I/12)**(1/3)))/2, 3/2 +
sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) + 4/sqrt(-7/3 +
61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3)) -
61/(18*(-415/216 + 13*I/12)**(1/3)))/2 + sqrt(-7/3 + 61/(18*(-415/216
+ 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3))/2, 3/2 + sqrt(-7/3
+ 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3))/2 - sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) +
4/sqrt(-7/3 + 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3)) - 61/(18*(-415/216 + 13*I/12)**(1/3)))/2]''')
ans = [r[1], r[0], r[-1], r[-2]]
assert _nsort(r) == ans
assert len(_nsort(r, separated=True)[0]) == 0
b, c, a = exp(-1000), exp(-999), exp(-1001)
assert _nsort((b, c, a)) == [a, b, c]
# issue 12560
a = cos(1)**2 + sin(1)**2 - 1
assert _nsort([a]) == [a]
def test_roots_quadratic():
assert roots_quadratic(Poly(2*x**2, x)) == [0, 0]
assert roots_quadratic(Poly(2*x**2 + 3*x, x)) == [-Rational(3, 2), 0]
assert roots_quadratic(Poly(2*x**2 + 3, x)) == [-I*sqrt(6)/2, I*sqrt(6)/2]
assert roots_quadratic(Poly(2*x**2 + 4*x + 3, x)) == [-1 - I*sqrt(2)/2, -1 + I*sqrt(2)/2]
f = x**2 + (2*a*e + 2*c*e)/(a - c)*x + (d - b + a*e**2 - c*e**2)/(a - c)
assert roots_quadratic(Poly(f, x)) == \
[-e*(a + c)/(a - c) - sqrt((a*b + c*d - a*d - b*c + 4*a*c*e**2))/(a - c),
-e*(a + c)/(a - c) + sqrt((a*b + c*d - a*d - b*c + 4*a*c*e**2))/(a - c)]
# check for simplification
f = Poly(y*x**2 - 2*x - 2*y, x)
assert roots_quadratic(f) == \
[-sqrt(2*y**2 + 1)/y + 1/y, sqrt(2*y**2 + 1)/y + 1/y]
f = Poly(x**2 + (-y**2 - 2)*x + y**2 + 1, x)
assert roots_quadratic(f) == \
[1,y**2 + 1]
f = Poly(sqrt(2)*x**2 - 1, x)
r = roots_quadratic(f)
assert r == _nsort(r)
# issue 8255
f = Poly(-24*x**2 - 180*x + 264)
assert [w.n(2) for w in f.all_roots(radicals=True)] == \
[w.n(2) for w in f.all_roots(radicals=False)]
for _a, _b, _c in cartes((-2, 2), (-2, 2), (0, -1)):
f = Poly(_a*x**2 + _b*x + _c)
roots = roots_quadratic(f)
assert roots == _nsort(roots)
def test_issue_8289():
roots = (Poly(x**2 + 2)*Poly(x**4 + 2)).all_roots()
assert roots == _nsort(roots)
roots = Poly(x**6 + 3*x**3 + 2, x).all_roots()
assert roots == _nsort(roots)
roots = Poly(x**6 - x + 1).all_roots()
assert roots == _nsort(roots)
# all imaginary roots
roots = Poly(x**4 + 4*x**2 + 4, x).all_roots()
assert roots == _nsort(roots)
def test_issue_8285():
roots = (Poly(4*x**8 - 1, x)*Poly(x**2 + 1)).all_roots()
assert roots == _nsort(roots)
f = Poly(x**4 + 5*x**2 + 6, x)
ro = [RootOf(f, i) for i in range(4)]
roots = Poly(x**4 + 5*x**2 + 6, x).all_roots()
assert roots == ro
assert roots == _nsort(roots)
# more than 2 complex roots from which to identify the
# imaginary ones
roots = Poly(2*x**8 - 1).all_roots()
assert roots == _nsort(roots)
assert len(Poly(2*x**10 - 1).all_roots()) == 10 # doesn't fail
def test_roots_binomial():
assert roots_binomial(Poly(5 * x, x)) == [0]
assert roots_binomial(Poly(5 * x**4, x)) == [0, 0, 0, 0]
assert roots_binomial(Poly(5 * x + 2, x)) == [Rational(-2, 5)]
A = 10**Rational(3, 4) / 10
assert roots_binomial(Poly(5*x**4 + 2, x)) == \
[-A - A*I, -A + A*I, A - A*I, A + A*I]
_check(roots_binomial(Poly(x**8 - 2)))
a1 = Symbol('a1', nonnegative=True)
b1 = Symbol('b1', nonnegative=True)
r0 = roots_quadratic(Poly(a1 * x**2 + b1, x))
r1 = roots_binomial(Poly(a1 * x**2 + b1, x))
assert powsimp(r0[0]) == powsimp(r1[0])
assert powsimp(r0[1]) == powsimp(r1[1])
for a, b, s, n in cartes((1, 2), (1, 2), (-1, 1), (2, 3, 4, 5)):
if a == b and a != 1: # a == b == 1 is sufficient
continue
p = Poly(a * x**n + s * b)
ans = roots_binomial(p)
assert ans == _nsort(ans)
# issue 8813
assert roots(Poly(2 * x**3 - 16 * y**3, x)) == {
2 * y * (Rational(-1, 2) - sqrt(3) * I / 2): 1,
2 * y: 1,
2 * y * (Rational(-1, 2) + sqrt(3) * I / 2): 1
}
def test_roots_binomial():
assert roots_binomial(Poly(5*x, x)) == [0]
assert roots_binomial(Poly(5*x**4, x)) == [0, 0, 0, 0]
assert roots_binomial(Poly(5*x + 2, x)) == [-Rational(2, 5)]
A = 10**Rational(3, 4)/10
assert roots_binomial(Poly(5*x**4 + 2, x)) == \
[-A - A*I, -A + A*I, A - A*I, A + A*I]
a1 = Symbol('a1', nonnegative=True)
b1 = Symbol('b1', nonnegative=True)
r0 = roots_quadratic(Poly(a1*x**2 + b1, x))
r1 = roots_binomial(Poly(a1*x**2 + b1, x))
assert powsimp(r0[0]) == powsimp(r1[0])
assert powsimp(r0[1]) == powsimp(r1[1])
for a, b, s, n in cartes((1, 2), (1, 2), (-1, 1), (2, 3, 4, 5)):
if a == b and a != 1: # a == b == 1 is sufficient
continue
p = Poly(a*x**n + s*b)
ans = roots_binomial(p)
assert ans == _nsort(ans)
# issue 8813
assert roots(Poly(2*x**3 - 16*y**3, x)) == {
2*y*(-S(1)/2 - sqrt(3)*I/2): 1,
2*y: 1,
2*y*(-S(1)/2 + sqrt(3)*I/2): 1}
def test__nsort():
# issue 6137
r = S('''[3/2 + sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) - 4/sqrt(-7/3 +
61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3)) -
61/(18*(-415/216 + 13*I/12)**(1/3)))/2 - sqrt(-7/3 + 61/(18*(-415/216
+ 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3))/2, 3/2 - sqrt(-7/3
+ 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3))/2 - sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) -
4/sqrt(-7/3 + 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3)) - 61/(18*(-415/216 + 13*I/12)**(1/3)))/2, 3/2 +
sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) + 4/sqrt(-7/3 +
61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3)) -
61/(18*(-415/216 + 13*I/12)**(1/3)))/2 + sqrt(-7/3 + 61/(18*(-415/216
+ 13*I/12)**(1/3)) + 2*(-415/216 + 13*I/12)**(1/3))/2, 3/2 + sqrt(-7/3
+ 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3))/2 - sqrt(-14/3 - 2*(-415/216 + 13*I/12)**(1/3) +
4/sqrt(-7/3 + 61/(18*(-415/216 + 13*I/12)**(1/3)) + 2*(-415/216 +
13*I/12)**(1/3)) - 61/(18*(-415/216 + 13*I/12)**(1/3)))/2]''')
ans = [r[1], r[0], r[-1], r[-2]]
assert _nsort(r) == ans
assert len(_nsort(r, separated=True)[0]) == 0
b, c, a = exp(-1000), exp(-999), exp(-1001)
assert _nsort((b, c, a)) == [a, b, c]
def test_roots_binomial():
assert roots_binomial(Poly(5 * x, x)) == [0]
assert roots_binomial(Poly(5 * x**4, x)) == [0, 0, 0, 0]
assert roots_binomial(Poly(5 * x + 2, x)) == [-Rational(2, 5)]
A = 10**Rational(3, 4) / 10
assert roots_binomial(Poly(5*x**4 + 2, x)) == \
[-A - A*I, -A + A*I, A - A*I, A + A*I]
a1 = Symbol('a1', nonnegative=True)
b1 = Symbol('b1', nonnegative=True)
r0 = roots_quadratic(Poly(a1 * x**2 + b1, x))
r1 = roots_binomial(Poly(a1 * x**2 + b1, x))
assert powsimp(r0[0]) == powsimp(r1[0])
assert powsimp(r0[1]) == powsimp(r1[1])
for a, b, s, n in cartes((1, 2), (1, 2), (-1, 1), (2, 3, 4, 5)):
if a == b and a != 1: # a == b == 1 is sufficient
continue
p = Poly(a * x**n + s * b)
roots = roots_binomial(p)
assert roots == _nsort(roots)
def normal_lines(self, p, prec=None):
"""Normal lines between `p` and the ellipse.
Parameters
==========
p : Point
Returns
=======
normal_lines : list with 1, 2 or 4 Lines
Examples
========
>>> from sympy import Line, Point, Ellipse
>>> e = Ellipse((0, 0), 2, 3)
>>> c = e.center
>>> e.normal_lines(c + Point(1, 0))
[Line2D(Point2D(0, 0), Point2D(1, 0))]
>>> e.normal_lines(c)
[Line2D(Point2D(0, 0), Point2D(0, 1)), Line2D(Point2D(0, 0), Point2D(1, 0))]
Off-axis points require the solution of a quartic equation. This
often leads to very large expressions that may be of little practical
use. An approximate solution of `prec` digits can be obtained by
passing in the desired value:
>>> e.normal_lines((3, 3), prec=2)
[Line2D(Point2D(-0.81, -2.7), Point2D(0.19, -1.2)),
Line2D(Point2D(1.5, -2.0), Point2D(2.5, -2.7))]
Whereas the above solution has an operation count of 12, the exact
solution has an operation count of 2020.
"""
p = Point(p, dim=2)
# XXX change True to something like self.angle == 0 if the arbitrarily
# rotated ellipse is introduced.
# https://github.com/sympy/sympy/issues/2815)
if True:
rv = []
if p.x == self.center.x:
rv.append(Line(self.center, slope=oo))
if p.y == self.center.y:
rv.append(Line(self.center, slope=0))
if rv:
# at these special orientations of p either 1 or 2 normals
# exist and we are done
return rv
# find the 4 normal points and construct lines through them with
# the corresponding slope
x, y = Dummy('x', real=True), Dummy('y', real=True)
eq = self.equation(x, y)
dydx = idiff(eq, y, x)
norm = -1/dydx
slope = Line(p, (x, y)).slope
seq = slope - norm
# TODO: Replace solve with solveset, when this line is tested
yis = solve(seq, y)[0]
xeq = eq.subs(y, yis).as_numer_denom()[0].expand()
if len(xeq.free_symbols) == 1:
try:
# this is so much faster, it's worth a try
xsol = Poly(xeq, x).real_roots()
except (DomainError, PolynomialError, NotImplementedError):
# TODO: Replace solve with solveset, when these lines are tested
xsol = _nsort(solve(xeq, x), separated=True)[0]
points = [Point(i, solve(eq.subs(x, i), y)[0]) for i in xsol]
else:
raise NotImplementedError(
'intersections for the general ellipse are not supported')
slopes = [norm.subs(zip((x, y), pt.args)) for pt in points]
if prec is not None:
points = [pt.n(prec) for pt in points]
slopes = [i if _not_a_coeff(i) else i.n(prec) for i in slopes]
return [Line(pt, slope=s) for pt,s in zip(points, slopes)]
def solve_univariate_inequality(expr, gen, relational=True):
"""Solves a real univariate inequality.
Examples
========
>>> from sympy.solvers.inequalities import solve_univariate_inequality
>>> from sympy.core.symbol import Symbol
>>> x = Symbol('x')
>>> solve_univariate_inequality(x**2 >= 4, x)
Or(And(-oo < x, x <= -2), And(2 <= x, x < oo))
>>> solve_univariate_inequality(x**2 >= 4, x, relational=False)
(-oo, -2] U [2, oo)
"""
from sympy.solvers.solvers import solve, denoms
# This keeps the function independent of the assumptions about `gen`.
# `solveset` makes sure this function is called only when the domain is
# real.
d = Dummy(real=True)
expr = expr.subs(gen, d)
_gen = gen
gen = d
if expr is S.true:
rv = S.Reals
elif expr is S.false:
rv = S.EmptySet
else:
e = expr.lhs - expr.rhs
parts = n, d = e.as_numer_denom()
if all(i.is_polynomial(gen) for i in parts):
solns = solve(n, gen, check=False)
singularities = solve(d, gen, check=False)
else:
solns = solve(e, gen, check=False)
singularities = []
for d in denoms(e):
singularities.extend(solve(d, gen))
include_x = expr.func(0, 0)
def valid(x):
v = e.subs(gen, x)
try:
r = expr.func(v, 0)
except TypeError:
r = S.false
if r in (S.true, S.false):
return r
if v.is_real is False:
return S.false
else:
v = v.n(2)
if v.is_comparable:
return expr.func(v, 0)
return S.false
start = S.NegativeInfinity
sol_sets = [S.EmptySet]
try:
reals = _nsort(set(solns + singularities), separated=True)[0]
except NotImplementedError:
raise NotImplementedError('sorting of these roots is not supported')
for x in reals:
end = x
if end in [S.NegativeInfinity, S.Infinity]:
if valid(S(0)):
sol_sets.append(Interval(start, S.Infinity, True, True))
break
pt = ((start + end)/2 if start is not S.NegativeInfinity else
(end/2 if end.is_positive else
(2*end if end.is_negative else
end - 1)))
if valid(pt):
sol_sets.append(Interval(start, end, True, True))
if x in singularities:
singularities.remove(x)
elif include_x:
sol_sets.append(FiniteSet(x))
start = end
end = S.Infinity
# in case start == -oo then there were no solutions so we just
# check a point between -oo and oo (e.g. 0) else pick a point
# past the last solution (which is start after the end of the
# for-loop above
pt = (0 if start is S.NegativeInfinity else
(start/2 if start.is_negative else
(2*start if start.is_positive else
start + 1)))
if valid(pt):
sol_sets.append(Interval(start, end, True, True))
rv = Union(*sol_sets).subs(gen, _gen)
return rv if not relational else rv.as_relational(_gen)
def solve_univariate_inequality(expr, gen, relational=True):
"""Solves a real univariate inequality.
Examples
========
>>> from sympy.solvers.inequalities import solve_univariate_inequality
>>> from sympy.core.symbol import Symbol
>>> x = Symbol('x', real=True)
>>> solve_univariate_inequality(x**2 >= 4, x)
Or(And(-oo < x, x <= -2), And(2 <= x, x < oo))
>>> solve_univariate_inequality(x**2 >= 4, x, relational=False)
(-oo, -2] U [2, oo)
"""
from sympy.solvers.solvers import solve, denoms
e = expr.lhs - expr.rhs
parts = n, d = e.as_numer_denom()
if all(i.is_polynomial(gen) for i in parts):
solns = solve(n, gen, check=False)
singularities = solve(d, gen, check=False)
else:
solns = solve(e, gen, check=False)
singularities = []
for d in denoms(e):
singularities.extend(solve(d, gen))
include_x = expr.func(0, 0)
def valid(x):
v = e.subs(gen, x)
try:
r = expr.func(v, 0)
except TypeError:
r = S.false
if r in (S.true, S.false):
return r
if v.is_real is False:
return S.false
else:
v = v.n(2)
if v.is_comparable:
return expr.func(v, 0)
return S.false
start = S.NegativeInfinity
sol_sets = [S.EmptySet]
try:
reals = _nsort(set(solns + singularities), separated=True)[0]
except NotImplementedError:
raise NotImplementedError('sorting of these roots is not supported')
for x in reals:
end = x
if end in [S.NegativeInfinity, S.Infinity]:
if valid(S(0)):
sol_sets.append(Interval(start, S.Infinity, True, True))
break
if valid((start + end)/2 if start != S.NegativeInfinity else end - 1):
sol_sets.append(Interval(start, end, True, True))
if x in singularities:
singularities.remove(x)
elif include_x:
sol_sets.append(FiniteSet(x))
start = end
end = S.Infinity
if valid(start + 1):
sol_sets.append(Interval(start, end, True, True))
rv = Union(*sol_sets)
return rv if not relational else rv.as_relational(gen)
def solve_univariate_inequality(expr, gen, relational=True, domain=S.Reals, continuous=False):
"""Solves a real univariate inequality.
Parameters
==========
expr : Relational
The target inequality
gen : Symbol
The variable for which the inequality is solved
relational : bool
A Relational type output is expected or not
domain : Set
The domain over which the equation is solved
continuous: bool
True if expr is known to be continuous over the given domain
(and so continuous_domain() doesn't need to be called on it)
Raises
======
NotImplementedError
The solution of the inequality cannot be determined due to limitation
in `solvify`.
Notes
=====
Currently, we cannot solve all the inequalities due to limitations in
`solvify`. Also, the solution returned for trigonometric inequalities
are restricted in its periodic interval.
See Also
========
solvify: solver returning solveset solutions with solve's output API
Examples
========
>>> from sympy.solvers.inequalities import solve_univariate_inequality
>>> from sympy import Symbol, sin, Interval, S
>>> x = Symbol('x')
>>> solve_univariate_inequality(x**2 >= 4, x)
((2 <= x) & (x < oo)) | ((x <= -2) & (-oo < x))
>>> solve_univariate_inequality(x**2 >= 4, x, relational=False)
Union(Interval(-oo, -2), Interval(2, oo))
>>> domain = Interval(0, S.Infinity)
>>> solve_univariate_inequality(x**2 >= 4, x, False, domain)
Interval(2, oo)
>>> solve_univariate_inequality(sin(x) > 0, x, relational=False)
Interval.open(0, pi)
"""
from sympy import im
from sympy.calculus.util import (continuous_domain, periodicity,
function_range)
from sympy.solvers.solvers import denoms
from sympy.solvers.solveset import solveset_real, solvify, solveset
from sympy.solvers.solvers import solve
# This keeps the function independent of the assumptions about `gen`.
# `solveset` makes sure this function is called only when the domain is
# real.
_gen = gen
_domain = domain
if gen.is_real is False:
rv = S.EmptySet
return rv if not relational else rv.as_relational(_gen)
elif gen.is_real is None:
gen = Dummy('gen', real=True)
try:
expr = expr.xreplace({_gen: gen})
except TypeError:
raise TypeError(filldedent('''
When gen is real, the relational has a complex part
which leads to an invalid comparison like I < 0.
'''))
rv = None
if expr is S.true:
rv = domain
elif expr is S.false:
rv = S.EmptySet
else:
e = expr.lhs - expr.rhs
period = periodicity(e, gen)
if period is not None:
frange = function_range(e, gen, domain)
rel = expr.rel_op
if rel == '<' or rel == '<=':
if expr.func(frange.sup, 0):
rv = domain
elif not expr.func(frange.inf, 0):
rv = S.EmptySet
elif rel == '>' or rel == '>=':
if expr.func(frange.inf, 0):
rv = domain
elif not expr.func(frange.sup, 0):
rv = S.EmptySet
inf, sup = domain.inf, domain.sup
if sup - inf is S.Infinity:
domain = Interval(0, period, False, True)
if rv is None:
n, d = e.as_numer_denom()
try:
if gen not in n.free_symbols and len(e.free_symbols) > 1:
raise ValueError
# this might raise ValueError on its own
# or it might give None...
solns = solvify(e, gen, domain)
if solns is None:
# in which case we raise ValueError
raise ValueError
except (ValueError, NotImplementedError):
raise NotImplementedError(filldedent('''
The inequality cannot be solved using solve_univariate_inequality.
'''))
expanded_e = expand_mul(e)
def valid(x):
# this is used to see if gen=x satisfies the
# relational by substituting it into the
# expanded form and testing against 0, e.g.
# if expr = x*(x + 1) < 2 then e = x*(x + 1) - 2
# and expanded_e = x**2 + x - 2; the test is
# whether a given value of x satisfies
# x**2 + x - 2 < 0
#
# expanded_e, expr and gen used from enclosing scope
v = expanded_e.subs(gen, x)
try:
r = expr.func(v, 0)
except TypeError:
r = S.false
if r in (S.true, S.false):
return r
if v.is_real is False:
return S.false
else:
v = v.n(2)
if v.is_comparable:
return expr.func(v, 0)
# not comparable or couldn't be evaluated
raise NotImplementedError(
'relationship did not evaluate: %s' % r)
singularities = []
for d in denoms(expr, gen):
singularities.extend(solvify(d, gen, domain))
if not continuous:
domain = continuous_domain(e, gen, domain)
include_x = '=' in expr.rel_op and expr.rel_op != '!='
try:
discontinuities = set(domain.boundary -
FiniteSet(domain.inf, domain.sup))
# remove points that are not between inf and sup of domain
critical_points = FiniteSet(*(solns + singularities + list(
discontinuities))).intersection(
Interval(domain.inf, domain.sup,
domain.inf not in domain, domain.sup not in domain))
if all(r.is_number for r in critical_points):
reals = _nsort(critical_points, separated=True)[0]
else:
from sympy.utilities.iterables import sift
sifted = sift(critical_points, lambda x: x.is_real)
if sifted[None]:
# there were some roots that weren't known
# to be real
raise NotImplementedError
try:
reals = sifted[True]
if len(reals) > 1:
reals = list(sorted(reals))
except TypeError:
raise NotImplementedError
except NotImplementedError:
raise NotImplementedError('sorting of these roots is not supported')
#If expr contains imaginary coefficients
#Only real values of x for which the imaginary part is 0 are taken
make_real = S.Reals
if im(expanded_e) != S.Zero:
check = True
im_sol = FiniteSet()
try:
a = solveset(im(expanded_e), gen, domain)
if not isinstance(a, Interval):
for z in a:
if z not in singularities and valid(z) and z.is_real:
im_sol += FiniteSet(z)
else:
start, end = a.inf, a.sup
for z in _nsort(critical_points + FiniteSet(end)):
valid_start = valid(start)
if start != end:
valid_z = valid(z)
pt = _pt(start, z)
if pt not in singularities and pt.is_real and valid(pt):
if valid_start and valid_z:
im_sol += Interval(start, z)
elif valid_start:
im_sol += Interval.Ropen(start, z)
elif valid_z:
im_sol += Interval.Lopen(start, z)
else:
im_sol += Interval.open(start, z)
start = z
for s in singularities:
im_sol -= FiniteSet(s)
except (TypeError):
im_sol = S.Reals
check = False
if isinstance(im_sol, EmptySet):
raise ValueError(filldedent('''
%s contains imaginary parts which cannot be made 0 for any value of %s
satisfying the inequality, leading to relations like I < 0.
''' % (expr.subs(gen, _gen), _gen)))
make_real = make_real.intersect(im_sol)
empty = sol_sets = [S.EmptySet]
start = domain.inf
if valid(start) and start.is_finite:
sol_sets.append(FiniteSet(start))
for x in reals:
end = x
if valid(_pt(start, end)):
sol_sets.append(Interval(start, end, True, True))
if x in singularities:
singularities.remove(x)
else:
if x in discontinuities:
discontinuities.remove(x)
_valid = valid(x)
else: # it's a solution
_valid = include_x
if _valid:
sol_sets.append(FiniteSet(x))
start = end
end = domain.sup
if valid(end) and end.is_finite:
sol_sets.append(FiniteSet(end))
if valid(_pt(start, end)):
sol_sets.append(Interval.open(start, end))
if im(expanded_e) != S.Zero and check:
rv = (make_real).intersect(_domain)
else:
rv = Intersection(
(Union(*sol_sets)), make_real, _domain).subs(gen, _gen)
return rv if not relational else rv.as_relational(_gen)
def _set_function(f, x): # noqa:F811
from sympy.functions.elementary.miscellaneous import Min, Max
from sympy.solvers.solveset import solveset
from sympy.core.function import diff, Lambda
from sympy.series import limit
from sympy.calculus.singularities import singularities
from sympy.sets import Complement
# TODO: handle functions with infinitely many solutions (eg, sin, tan)
# TODO: handle multivariate functions
expr = f.expr
if len(expr.free_symbols) > 1 or len(f.variables) != 1:
return
var = f.variables[0]
if not var.is_real:
if expr.subs(var, Dummy(real=True)).is_real is False:
return
if expr.is_Piecewise:
result = S.EmptySet
domain_set = x
for (p_expr, p_cond) in expr.args:
if p_cond is true:
intrvl = domain_set
else:
intrvl = p_cond.as_set()
intrvl = Intersection(domain_set, intrvl)
if p_expr.is_Number:
image = FiniteSet(p_expr)
else:
image = imageset(Lambda(var, p_expr), intrvl)
result = Union(result, image)
# remove the part which has been `imaged`
domain_set = Complement(domain_set, intrvl)
if domain_set is S.EmptySet:
break
return result
if not x.start.is_comparable or not x.end.is_comparable:
return
try:
from sympy.polys.polyutils import _nsort
sing = list(singularities(expr, var, x))
if len(sing) > 1:
sing = _nsort(sing)
except NotImplementedError:
return
if x.left_open:
_start = limit(expr, var, x.start, dir="+")
elif x.start not in sing:
_start = f(x.start)
if x.right_open:
_end = limit(expr, var, x.end, dir="-")
elif x.end not in sing:
_end = f(x.end)
if len(sing) == 0:
soln_expr = solveset(diff(expr, var), var)
if not (isinstance(soln_expr, FiniteSet) or soln_expr is EmptySet):
return
solns = list(soln_expr)
extr = [_start, _end] + [f(i) for i in solns if i.is_real and i in x]
start, end = Min(*extr), Max(*extr)
left_open, right_open = False, False
if _start <= _end:
# the minimum or maximum value can occur simultaneously
# on both the edge of the interval and in some interior
# point
if start == _start and start not in solns:
left_open = x.left_open
if end == _end and end not in solns:
right_open = x.right_open
else:
if start == _end and start not in solns:
left_open = x.right_open
if end == _start and end not in solns:
right_open = x.left_open
return Interval(start, end, left_open, right_open)
else:
return imageset(f, Interval(x.start, sing[0],
x.left_open, True)) + \
Union(*[imageset(f, Interval(sing[i], sing[i + 1], True, True))
for i in range(0, len(sing) - 1)]) + \
imageset(f, Interval(sing[-1], x.end, True, x.right_open))
def solve_univariate_inequality(expr,
gen,
relational=True,
domain=S.Reals,
continuous=False):
"""Solves a real univariate inequality.
Parameters
==========
expr : Relational
The target inequality
gen : Symbol
The variable for which the inequality is solved
relational : bool
A Relational type output is expected or not
domain : Set
The domain over which the equation is solved
continuous: bool
True if expr is known to be continuous over the given domain
(and so continuous_domain() doesn't need to be called on it)
Raises
======
NotImplementedError
The solution of the inequality cannot be determined due to limitation
in `solvify`.
Notes
=====
Currently, we cannot solve all the inequalities due to limitations in
`solvify`. Also, the solution returned for trigonometric inequalities
are restricted in its periodic interval.
See Also
========
solvify: solver returning solveset solutions with solve's output API
Examples
========
>>> from sympy.solvers.inequalities import solve_univariate_inequality
>>> from sympy import Symbol, sin, Interval, S
>>> x = Symbol('x')
>>> solve_univariate_inequality(x**2 >= 4, x)
((2 <= x) & (x < oo)) | ((x <= -2) & (-oo < x))
>>> solve_univariate_inequality(x**2 >= 4, x, relational=False)
(-oo, -2] U [2, oo)
>>> domain = Interval(0, S.Infinity)
>>> solve_univariate_inequality(x**2 >= 4, x, False, domain)
[2, oo)
>>> solve_univariate_inequality(sin(x) > 0, x, relational=False)
(0, pi)
"""
from sympy.calculus.util import (continuous_domain, periodicity,
function_range)
from sympy.solvers.solvers import denoms
from sympy.solvers.solveset import solveset_real, solvify
# This keeps the function independent of the assumptions about `gen`.
# `solveset` makes sure this function is called only when the domain is
# real.
d = Dummy(real=True)
expr = expr.subs(gen, d)
_gen = gen
gen = d
rv = None
if expr is S.true:
rv = domain
elif expr is S.false:
rv = S.EmptySet
else:
e = expr.lhs - expr.rhs
period = periodicity(e, gen)
if period is not None:
frange = function_range(e, gen, domain)
rel = expr.rel_op
if rel == '<' or rel == '<=':
if expr.func(frange.sup, 0):
rv = domain
elif not expr.func(frange.inf, 0):
rv = S.EmptySet
elif rel == '>' or rel == '>=':
if expr.func(frange.inf, 0):
rv = domain
elif not expr.func(frange.sup, 0):
rv = S.EmptySet
inf, sup = domain.inf, domain.sup
if sup - inf is S.Infinity:
domain = Interval(0, period, False, True)
if rv is None:
singularities = []
for d in denoms(e):
singularities.extend(solvify(d, gen, domain))
if not continuous:
domain = continuous_domain(e, gen, domain)
solns = solvify(e, gen, domain)
if solns is None:
raise NotImplementedError(
filldedent('''The inequality cannot be
solved using solve_univariate_inequality.'''))
include_x = expr.func(0, 0)
def valid(x):
v = e.subs(gen, x)
try:
r = expr.func(v, 0)
except TypeError:
r = S.false
if r in (S.true, S.false):
return r
if v.is_real is False:
return S.false
else:
v = v.n(2)
if v.is_comparable:
return expr.func(v, 0)
return S.false
start = domain.inf
sol_sets = [S.EmptySet]
try:
discontinuities = domain.boundary - FiniteSet(
domain.inf, domain.sup)
critical_points = set(solns + singularities +
list(discontinuities))
reals = _nsort(critical_points, separated=True)[0]
except NotImplementedError:
raise NotImplementedError(
'sorting of these roots is not supported')
if valid(start) and start.is_finite:
sol_sets.append(FiniteSet(start))
for x in reals:
end = x
if end in [S.NegativeInfinity, S.Infinity]:
if valid(S(0)):
sol_sets.append(Interval(start, S.Infinity, True,
True))
break
pt = ((start + end) / 2 if start is not S.NegativeInfinity else
(end / 2 if end.is_positive else
(2 * end if end.is_negative else end - 1)))
if valid(pt):
sol_sets.append(Interval(start, end, True, True))
if x in singularities:
singularities.remove(x)
elif include_x:
sol_sets.append(FiniteSet(x))
start = end
end = domain.sup
# in case start == -oo then there were no solutions so we just
# check a point between -oo and oo (e.g. 0) else pick a point
# past the last solution (which is start after the end of the
# for-loop above
pt = (0 if start is S.NegativeInfinity else
(start / 2 if start.is_negative else
(2 * start if start.is_positive else start + 1)))
if pt >= end:
pt = (start + end) / 2
if valid(pt):
sol_sets.append(Interval(start, end, True, True))
rv = Union(*sol_sets).subs(gen, _gen)
return rv if not relational else rv.as_relational(_gen)
def normal_lines(self, p, prec=None):
"""Normal lines between `p` and the ellipse.
Parameters
==========
p : Point
Returns
=======
normal_lines : list with 1, 2 or 4 Lines
Examples
========
>>> from sympy import Line, Point, Ellipse
>>> e = Ellipse((0, 0), 2, 3)
>>> c = e.center
>>> e.normal_lines(c + Point(1, 0))
[Line(Point2D(0, 0), Point2D(1, 0))]
>>> e.normal_lines(c)
[Line(Point2D(0, 0), Point2D(0, 1)), Line(Point2D(0, 0), Point2D(1, 0))]
Off-axis points require the solution of a quartic equation. This
often leads to very large expressions that may be of little practical
use. An approximate solution of `prec` digits can be obtained by
passing in the desired value:
>>> e.normal_lines((3, 3), prec=2)
[Line(Point2D(-38/47, -85/31), Point2D(9/47, -21/17)),
Line(Point2D(19/13, -43/21), Point2D(32/13, -8/3))]
Whereas the above solution has an operation count of 12, the exact
solution has an operation count of 2020.
"""
p = Point(p)
# XXX change True to something like self.angle == 0 if the arbitrarily
# rotated ellipse is introduced.
# https://github.com/sympy/sympy/issues/2815)
if True:
rv = []
if p.x == self.center.x:
rv.append(Line(self.center, slope=oo))
if p.y == self.center.y:
rv.append(Line(self.center, slope=0))
if rv:
# at these special orientations of p either 1 or 2 normals
# exist and we are done
return rv
# find the 4 normal points and construct lines through them with
# the corresponding slope
x, y = Dummy('x', real=True), Dummy('y', real=True)
eq = self.equation(x, y)
dydx = idiff(eq, y, x)
norm = -1 / dydx
slope = Line(p, (x, y)).slope
seq = slope - norm
# TODO: Replace solve with solveset, when this line is tested
yis = solve(seq, y)[0]
xeq = eq.subs(y, yis).as_numer_denom()[0].expand()
if len(xeq.free_symbols) == 1:
try:
# this is so much faster, it's worth a try
xsol = Poly(xeq, x).real_roots()
except (DomainError, PolynomialError, NotImplementedError):
# TODO: Replace solve with solveset, when these lines are tested
xsol = _nsort(solve(xeq, x), separated=True)[0]
points = [Point(i, solve(eq.subs(x, i), y)[0]) for i in xsol]
else:
raise NotImplementedError(
'intersections for the general ellipse are not supported')
slopes = [norm.subs(zip((x, y), pt.args)) for pt in points]
if prec is not None:
points = [pt.n(prec) for pt in points]
slopes = [i if _not_a_coeff(i) else i.n(prec) for i in slopes]
return [Line(pt, slope=s) for pt, s in zip(points, slopes)]
def solve_univariate_inequality(expr,
gen,
relational=True,
domain=S.Reals,
continuous=False):
"""Solves a real univariate inequality.
Parameters
==========
expr : Relational
The target inequality
gen : Symbol
The variable for which the inequality is solved
relational : bool
A Relational type output is expected or not
domain : Set
The domain over which the equation is solved
continuous: bool
True if expr is known to be continuous over the given domain
(and so continuous_domain() doesn't need to be called on it)
Raises
======
NotImplementedError
The solution of the inequality cannot be determined due to limitation
in `solvify`.
Notes
=====
Currently, we cannot solve all the inequalities due to limitations in
`solvify`. Also, the solution returned for trigonometric inequalities
are restricted in its periodic interval.
See Also
========
solvify: solver returning solveset solutions with solve's output API
Examples
========
>>> from sympy.solvers.inequalities import solve_univariate_inequality
>>> from sympy import Symbol, sin, Interval, S
>>> x = Symbol('x')
>>> solve_univariate_inequality(x**2 >= 4, x)
((2 <= x) & (x < oo)) | ((x <= -2) & (-oo < x))
>>> solve_univariate_inequality(x**2 >= 4, x, relational=False)
Union(Interval(-oo, -2), Interval(2, oo))
>>> domain = Interval(0, S.Infinity)
>>> solve_univariate_inequality(x**2 >= 4, x, False, domain)
Interval(2, oo)
>>> solve_univariate_inequality(sin(x) > 0, x, relational=False)
Interval.open(0, pi)
"""
from sympy import im
from sympy.calculus.util import (continuous_domain, periodicity,
function_range)
from sympy.solvers.solvers import denoms
from sympy.solvers.solveset import solveset_real, solvify, solveset
from sympy.solvers.solvers import solve
# This keeps the function independent of the assumptions about `gen`.
# `solveset` makes sure this function is called only when the domain is
# real.
_gen = gen
_domain = domain
if gen.is_real is False:
rv = S.EmptySet
return rv if not relational else rv.as_relational(_gen)
elif gen.is_real is None:
gen = Dummy('gen', real=True)
try:
expr = expr.xreplace({_gen: gen})
except TypeError:
raise TypeError(
filldedent('''
When gen is real, the relational has a complex part
which leads to an invalid comparison like I < 0.
'''))
rv = None
if expr is S.true:
rv = domain
elif expr is S.false:
rv = S.EmptySet
else:
e = expr.lhs - expr.rhs
period = periodicity(e, gen)
if period is S.Zero:
e = expand_mul(e)
const = expr.func(e, 0)
if const is S.true:
rv = domain
elif const is S.false:
rv = S.EmptySet
elif period is not None:
frange = function_range(e, gen, domain)
rel = expr.rel_op
if rel == '<' or rel == '<=':
if expr.func(frange.sup, 0):
rv = domain
elif not expr.func(frange.inf, 0):
rv = S.EmptySet
elif rel == '>' or rel == '>=':
if expr.func(frange.inf, 0):
rv = domain
elif not expr.func(frange.sup, 0):
rv = S.EmptySet
inf, sup = domain.inf, domain.sup
if sup - inf is S.Infinity:
domain = Interval(0, period, False, True)
if rv is None:
n, d = e.as_numer_denom()
try:
if gen not in n.free_symbols and len(e.free_symbols) > 1:
raise ValueError
# this might raise ValueError on its own
# or it might give None...
solns = solvify(e, gen, domain)
if solns is None:
# in which case we raise ValueError
raise ValueError
except (ValueError, NotImplementedError):
# replace gen with generic x since it's
# univariate anyway
raise NotImplementedError(
filldedent('''
The inequality, %s, cannot be solved using
solve_univariate_inequality.
''' % expr.subs(gen, Symbol('x'))))
expanded_e = expand_mul(e)
def valid(x):
# this is used to see if gen=x satisfies the
# relational by substituting it into the
# expanded form and testing against 0, e.g.
# if expr = x*(x + 1) < 2 then e = x*(x + 1) - 2
# and expanded_e = x**2 + x - 2; the test is
# whether a given value of x satisfies
# x**2 + x - 2 < 0
#
# expanded_e, expr and gen used from enclosing scope
v = expanded_e.subs(gen, expand_mul(x))
try:
r = expr.func(v, 0)
except TypeError:
r = S.false
if r in (S.true, S.false):
return r
if v.is_real is False:
return S.false
else:
v = v.n(2)
if v.is_comparable:
return expr.func(v, 0)
# not comparable or couldn't be evaluated
raise NotImplementedError(
'relationship did not evaluate: %s' % r)
singularities = []
for d in denoms(expr, gen):
singularities.extend(solvify(d, gen, domain))
if not continuous:
domain = continuous_domain(expanded_e, gen, domain)
include_x = '=' in expr.rel_op and expr.rel_op != '!='
try:
discontinuities = set(domain.boundary -
FiniteSet(domain.inf, domain.sup))
# remove points that are not between inf and sup of domain
critical_points = FiniteSet(
*(solns + singularities +
list(discontinuities))).intersection(
Interval(domain.inf, domain.sup, domain.inf
not in domain, domain.sup not in domain))
if all(r.is_number for r in critical_points):
reals = _nsort(critical_points, separated=True)[0]
else:
from sympy.utilities.iterables import sift
sifted = sift(critical_points, lambda x: x.is_real)
if sifted[None]:
# there were some roots that weren't known
# to be real
raise NotImplementedError
try:
reals = sifted[True]
if len(reals) > 1:
reals = list(sorted(reals))
except TypeError:
raise NotImplementedError
except NotImplementedError:
raise NotImplementedError(
'sorting of these roots is not supported')
# If expr contains imaginary coefficients, only take real
# values of x for which the imaginary part is 0
make_real = S.Reals
if im(expanded_e) != S.Zero:
check = True
im_sol = FiniteSet()
try:
a = solveset(im(expanded_e), gen, domain)
if not isinstance(a, Interval):
for z in a:
if z not in singularities and valid(
z) and z.is_real:
im_sol += FiniteSet(z)
else:
start, end = a.inf, a.sup
for z in _nsort(critical_points + FiniteSet(end)):
valid_start = valid(start)
if start != end:
valid_z = valid(z)
pt = _pt(start, z)
if pt not in singularities and pt.is_real and valid(
pt):
if valid_start and valid_z:
im_sol += Interval(start, z)
elif valid_start:
im_sol += Interval.Ropen(start, z)
elif valid_z:
im_sol += Interval.Lopen(start, z)
else:
im_sol += Interval.open(start, z)
start = z
for s in singularities:
im_sol -= FiniteSet(s)
except (TypeError):
im_sol = S.Reals
check = False
if isinstance(im_sol, EmptySet):
raise ValueError(
filldedent('''
%s contains imaginary parts which cannot be
made 0 for any value of %s satisfying the
inequality, leading to relations like I < 0.
''' % (expr.subs(gen, _gen), _gen)))
make_real = make_real.intersect(im_sol)
empty = sol_sets = [S.EmptySet]
start = domain.inf
if valid(start) and start.is_finite:
sol_sets.append(FiniteSet(start))
for x in reals:
end = x
if valid(_pt(start, end)):
sol_sets.append(Interval(start, end, True, True))
if x in singularities:
singularities.remove(x)
else:
if x in discontinuities:
discontinuities.remove(x)
_valid = valid(x)
else: # it's a solution
_valid = include_x
if _valid:
sol_sets.append(FiniteSet(x))
start = end
end = domain.sup
if valid(end) and end.is_finite:
sol_sets.append(FiniteSet(end))
if valid(_pt(start, end)):
sol_sets.append(Interval.open(start, end))
if im(expanded_e) != S.Zero and check:
rv = (make_real).intersect(_domain)
else:
rv = Intersection((Union(*sol_sets)), make_real,
_domain).subs(gen, _gen)
return rv if not relational else rv.as_relational(_gen)
def solve_univariate_inequality(expr, gen, relational=True, domain=S.Reals, continuous=False):
"""Solves a real univariate inequality.
Parameters
==========
expr : Relational
The target inequality
gen : Symbol
The variable for which the inequality is solved
relational : bool
A Relational type output is expected or not
domain : Set
The domain over which the equation is solved
continuous: bool
True if expr is known to be continuous over the given domain
(and so continuous_domain() doesn't need to be called on it)
Raises
======
NotImplementedError
The solution of the inequality cannot be determined due to limitation
in `solvify`.
Notes
=====
Currently, we cannot solve all the inequalities due to limitations in
`solvify`. Also, the solution returned for trigonometric inequalities
are restricted in its periodic interval.
See Also
========
solvify: solver returning solveset solutions with solve's output API
Examples
========
>>> from sympy.solvers.inequalities import solve_univariate_inequality
>>> from sympy import Symbol, sin, Interval, S
>>> x = Symbol('x')
>>> solve_univariate_inequality(x**2 >= 4, x)
((2 <= x) & (x < oo)) | ((x <= -2) & (-oo < x))
>>> solve_univariate_inequality(x**2 >= 4, x, relational=False)
(-oo, -2] U [2, oo)
>>> domain = Interval(0, S.Infinity)
>>> solve_univariate_inequality(x**2 >= 4, x, False, domain)
[2, oo)
>>> solve_univariate_inequality(sin(x) > 0, x, relational=False)
(0, pi)
"""
from sympy.calculus.util import (continuous_domain, periodicity,
function_range)
from sympy.solvers.solvers import denoms
from sympy.solvers.solveset import solveset_real, solvify
# This keeps the function independent of the assumptions about `gen`.
# `solveset` makes sure this function is called only when the domain is
# real.
d = Dummy(real=True)
expr = expr.subs(gen, d)
_gen = gen
gen = d
rv = None
if expr is S.true:
rv = domain
elif expr is S.false:
rv = S.EmptySet
else:
e = expr.lhs - expr.rhs
period = periodicity(e, gen)
if period is not None:
frange = function_range(e, gen, domain)
rel = expr.rel_op
if rel == '<' or rel == '<=':
if expr.func(frange.sup, 0):
rv = domain
elif not expr.func(frange.inf, 0):
rv = S.EmptySet
elif rel == '>' or rel == '>=':
if expr.func(frange.inf, 0):
rv = domain
elif not expr.func(frange.sup, 0):
rv = S.EmptySet
inf, sup = domain.inf, domain.sup
if sup - inf is S.Infinity:
domain = Interval(0, period, False, True)
if rv is None:
singularities = []
for d in denoms(e):
singularities.extend(solvify(d, gen, domain))
if not continuous:
domain = continuous_domain(e, gen, domain)
solns = solvify(e, gen, domain)
if solns is None:
raise NotImplementedError(filldedent('''The inequality cannot be
solved using solve_univariate_inequality.'''))
include_x = expr.func(0, 0)
def valid(x):
v = e.subs(gen, x)
try:
r = expr.func(v, 0)
except TypeError:
r = S.false
if r in (S.true, S.false):
return r
if v.is_real is False:
return S.false
else:
v = v.n(2)
if v.is_comparable:
return expr.func(v, 0)
return S.false
start = domain.inf
sol_sets = [S.EmptySet]
try:
discontinuities = domain.boundary - FiniteSet(domain.inf, domain.sup)
critical_points = set(solns + singularities + list(discontinuities))
reals = _nsort(critical_points, separated=True)[0]
except NotImplementedError:
raise NotImplementedError('sorting of these roots is not supported')
if valid(start) and start.is_finite:
sol_sets.append(FiniteSet(start))
for x in reals:
end = x
if end in [S.NegativeInfinity, S.Infinity]:
if valid(S(0)):
sol_sets.append(Interval(start, S.Infinity, True, True))
break
pt = ((start + end)/2 if start is not S.NegativeInfinity else
(end/2 if end.is_positive else
(2*end if end.is_negative else
end - 1)))
if valid(pt):
sol_sets.append(Interval(start, end, True, True))
if x in singularities:
singularities.remove(x)
elif include_x:
sol_sets.append(FiniteSet(x))
start = end
end = domain.sup
# in case start == -oo then there were no solutions so we just
# check a point between -oo and oo (e.g. 0) else pick a point
# past the last solution (which is start after the end of the
# for-loop above
pt = (0 if start is S.NegativeInfinity else
(start/2 if start.is_negative else
(2*start if start.is_positive else
start + 1)))
if pt >= end:
pt = (start + end)/2
if valid(pt):
sol_sets.append(Interval(start, end, True, True))
rv = Union(*sol_sets).subs(gen, _gen)
return rv if not relational else rv.as_relational(_gen)
