def _intersect(self, other):
from sympy.functions.elementary.integers import ceiling, floor
from sympy.functions.elementary.complexes import sign
if other is S.Naturals:
return self._intersect(Interval(1, S.Infinity))
if other is S.Integers:
return self
if other.is_Interval:
if not all(i.is_number for i in other.args[:2]):
return
# trim down to self's size, and represent
# as a Range with step 1
start = ceiling(max(other.inf, self.inf))
if start not in other:
start += 1
end = floor(min(other.sup, self.sup))
if end not in other:
end -= 1
return self.intersect(Range(start, end + 1))
if isinstance(other, Range):
from sympy.solvers.diophantine import diop_linear
from sympy.core.numbers import ilcm
# non-overlap quick exits
if not other:
return S.EmptySet
if not self:
return S.EmptySet
if other.sup < self.inf:
return S.EmptySet
if other.inf > self.sup:
return S.EmptySet
# work with finite end at the start
r1 = self
if r1.start.is_infinite:
r1 = r1.reversed
r2 = other
if r2.start.is_infinite:
r2 = r2.reversed
# this equation represents the values of the Range;
# it's a linear equation
eq = lambda r, i: r.start + i*r.step
# we want to know when the two equations might
# have integer solutions so we use the diophantine
# solver
a, b = diop_linear(eq(r1, Dummy()) - eq(r2, Dummy()))
# check for no solution
no_solution = a is None and b is None
if no_solution:
return S.EmptySet
# there is a solution
# -------------------
# find the coincident point, c
a0 = a.as_coeff_Add()[0]
c = eq(r1, a0)
# find the first point, if possible, in each range
# since c may not be that point
def _first_finite_point(r1, c):
if c == r1.start:
return c
# st is the signed step we need to take to
# get from c to r1.start
st = sign(r1.start - c)*step
# use Range to calculate the first point:
# we want to get as close as possible to
# r1.start; the Range will not be null since
# it will at least contain c
s1 = Range(c, r1.start + st, st)[-1]
if s1 == r1.start:
pass
else:
# if we didn't hit r1.start then, if the
# sign of st didn't match the sign of r1.step
# we are off by one and s1 is not in r1
if sign(r1.step) != sign(st):
s1 -= st
if s1 not in r1:
return
return s1
# calculate the step size of the new Range
step = abs(ilcm(r1.step, r2.step))
s1 = _first_finite_point(r1, c)
if s1 is None:
return S.EmptySet
s2 = _first_finite_point(r2, c)
if s2 is None:
return S.EmptySet
# replace the corresponding start or stop in
# the original Ranges with these points; the
# result must have at least one point since
# we know that s1 and s2 are in the Ranges
def _updated_range(r, first):
st = sign(r.step)*step
if r.start.is_finite:
rv = Range(first, r.stop, st)
else:
rv = Range(r.start, first + st, st)
return rv
r1 = _updated_range(self, s1)
r2 = _updated_range(other, s2)
# work with them both in the increasing direction
if sign(r1.step) < 0:
r1 = r1.reversed
if sign(r2.step) < 0:
r2 = r2.reversed
# return clipped Range with positive step; it
# can't be empty at this point
start = max(r1.start, r2.start)
stop = min(r1.stop, r2.stop)
return Range(start, stop, step)
else:
return
def test_multivariate_relational_as_set():
assert (x*y >= 0).as_set() == Interval(0, oo)*Interval(0, oo) + \
Interval(-oo, 0)*Interval(-oo, 0)
def prove(Eq):
n = Symbol.n(domain=[2, oo], integer=True)
x = Symbol.x(shape=(oo, ), integer=True)
k = Symbol.k(integer=True)
j = Symbol.j(domain=[0, n - 1], integer=True, given=True)
Eq << apply(
Equality(x[:n].set_comprehension(k), Interval(0, n - 1, integer=True)),
j)
Eq << Eq[1].lhs.this.definition
Eq <<= Eq[-3].subs(Eq[-1]), Eq[-2].subs(Eq[-1])
Eq << Eq[-1].lhs.indices[0].this.expand()
Eq << Eq[-1].rhs.function.args[1].this.as_Piecewise()
Eq << Eq[-2].this.rhs.subs(Eq[-1])
Eq << Eq[-1].rhs.subs(1, 0).this.bisect({0})
assert Eq[-1].lhs.limits[0][1].args[-1][-1].step.is_zero == False
Eq << Eq[-2].subs(Eq[-1].reversed)
assert Eq[-1].rhs.limits[0][1].args[-1][-1].step.is_zero == False
sj = Symbol.s_j(definition=Eq[-1].rhs.limits[0][1])
Eq.sj_definition = sj.equality_defined()
assert Eq.sj_definition.rhs.limits[0][-1].step.is_zero == False
Eq.crossproduct = Eq[-1].subs(Eq.sj_definition.reversed)
Eq.sj_definition_reversed = Eq.sj_definition.this.rhs.limits[0][1].reversed
assert Eq.sj_definition_reversed.args[-1].args[-1][
-1].step.is_zero == False
Eq.sj_definition_reversed = Eq.sj_definition_reversed.reversed
assert Eq.sj_definition_reversed.lhs.args[-1][-1].step.is_zero == False
Eq << Eq[0].intersect({j})
Eq << Piecewise((x[k].set, Equality(x[k], j)),
(EmptySet(), True)).this.simplify()
Eq << Eq[-1].reversed.union_comprehension((k, 0, n - 1))
Eq.distribute = Eq[-1].subs(Eq[-3]).reversed
Eq << Eq.distribute.this.lhs.function.subs(
Eq.distribute.lhs.limits[0][1].args[1][1])
Eq << Eq[-1].as_Or()
Eq << Eq[-1].subs(Eq.sj_definition_reversed)
Eq.sj_greater_than_1 = greater_than.apply(Eq[-1])
Eq.distribute = Eq.distribute.subs(Eq.sj_definition_reversed)
Eq << Eq.sj_greater_than_1.lhs.assertion()
Eq.sj_less_than_1, Eq.inequality_ab = Eq[-1].split()
(a, *_), (b, *_) = Eq.inequality_ab.limits
Eq << sets.equality.imply.forall_equality.nonoverlapping.apply(
Eq[0].abs(), excludes=Eq.inequality_ab.variables_set)
Eq << Eq[-1].subs(k, a)
Eq << Eq[-1].subs(Eq[-1].variable, b)
Eq << (Eq.inequality_ab & Eq[-1])
Eq.distribute_ab = Eq[-1].this.function.distribute()
Eq.j_equality, _ = sj.assertion().split()
Eq.i_domain = ForAll[a:sj](Contains(a, Interval(0, n - 1, integer=True)),
plausible=True)
Eq << Eq.i_domain.simplify()
Eq.sj_element_contains = ForAll[b:sj](Contains(
b, Interval(0, n - 1, integer=True)),
plausible=True)
Eq << Eq.sj_element_contains.simplify()
Eq << Eq.i_domain.apply(sets.contains.imply.equality.union)
Eq << Eq.distribute_ab.subs(Eq[-1])
Eq << (Eq[-1] & Eq.sj_element_contains)
Eq << Eq.j_equality.limits_subs(k, a).reversed
Eq << Eq[-2].subs(Eq[-1])
Eq << Eq.j_equality.limits_subs(k, b).reversed
Eq << Eq[-1].subs(Eq[-2])
Eq << Eq.sj_less_than_1.subs(Eq.sj_greater_than_1)
Eq << sets.equality.imply.contains.apply(Eq[-1], var=k)
Eq.index_domain = Eq[-1].subs(Eq.crossproduct.reversed)
Eq << Eq.j_equality.subs(k, Eq.index_domain.lhs).split()
Eq <<= Eq[-2] & Eq.index_domain
Eq << Eq[-1].reversed
Eq << Subset(sj, Eq[1].rhs, plausible=True)
Eq <<= Eq[-1] & Eq.index_domain
def _intersect(self, other):
if other.is_Interval:
return Intersection(
S.Integers, other, Interval(self._inf, S.Infinity))
return None
def test_issue_10326():
assert Contains(oo, Interval(-oo, oo)) == False
assert Contains(-oo, Interval(-oo, oo)) == False
def test_normalize_theta_set():
# Interval
assert normalize_theta_set(Interval(pi, 2*pi)) == \
Union(FiniteSet(0), Interval.Ropen(pi, 2*pi))
assert normalize_theta_set(Interval(9 * pi / 2,
5 * pi)) == Interval(pi / 2, pi)
assert normalize_theta_set(Interval(-3 * pi / 2,
pi / 2)) == Interval.Ropen(0, 2 * pi)
assert normalize_theta_set(Interval.open(-3*pi/2, pi/2)) == \
Union(Interval.Ropen(0, pi/2), Interval.open(pi/2, 2*pi))
assert normalize_theta_set(Interval.open(-7*pi/2, -3*pi/2)) == \
Union(Interval.Ropen(0, pi/2), Interval.open(pi/2, 2*pi))
assert normalize_theta_set(Interval(-pi/2, pi/2)) == \
Union(Interval(0, pi/2), Interval.Ropen(3*pi/2, 2*pi))
assert normalize_theta_set(Interval.open(-pi/2, pi/2)) == \
Union(Interval.Ropen(0, pi/2), Interval.open(3*pi/2, 2*pi))
assert normalize_theta_set(Interval(-4 * pi,
3 * pi)) == Interval.Ropen(0, 2 * pi)
assert normalize_theta_set(Interval(-3 * pi / 2, -pi / 2)) == Interval(
pi / 2, 3 * pi / 2)
assert normalize_theta_set(Interval.open(0, 2 * pi)) == Interval.open(
0, 2 * pi)
assert normalize_theta_set(Interval.Ropen(-pi/2, pi/2)) == \
Union(Interval.Ropen(0, pi/2), Interval.Ropen(3*pi/2, 2*pi))
assert normalize_theta_set(Interval.Lopen(-pi/2, pi/2)) == \
Union(Interval(0, pi/2), Interval.open(3*pi/2, 2*pi))
assert normalize_theta_set(Interval(-pi/2, pi/2)) == \
Union(Interval(0, pi/2), Interval.Ropen(3*pi/2, 2*pi))
assert normalize_theta_set(Interval.open(4 * pi,
9 * pi / 2)) == Interval.open(
0, pi / 2)
assert normalize_theta_set(Interval.Lopen(4 * pi,
9 * pi / 2)) == Interval.Lopen(
0, pi / 2)
assert normalize_theta_set(Interval.Ropen(4 * pi,
9 * pi / 2)) == Interval.Ropen(
0, pi / 2)
assert normalize_theta_set(Interval.open(3*pi, 5*pi)) == \
Union(Interval.Ropen(0, pi), Interval.open(pi, 2*pi))
# FiniteSet
assert normalize_theta_set(FiniteSet(0, pi, 3 * pi)) == FiniteSet(0, pi)
assert normalize_theta_set(FiniteSet(0, pi / 2, pi,
2 * pi)) == FiniteSet(0, pi / 2, pi)
assert normalize_theta_set(FiniteSet(0, -pi / 2, -pi,
-2 * pi)) == FiniteSet(
0, pi, 3 * pi / 2)
assert normalize_theta_set(FiniteSet(-3*pi/2, pi/2)) == \
FiniteSet(pi/2)
assert normalize_theta_set(FiniteSet(2 * pi)) == FiniteSet(0)
# Unions
assert normalize_theta_set(Union(Interval(0, pi/3), Interval(pi/2, pi))) == \
Union(Interval(0, pi/3), Interval(pi/2, pi))
assert normalize_theta_set(Union(Interval(0, pi), Interval(2*pi, 7*pi/3))) == \
Interval(0, pi)
# ValueError for non-real sets
raises(ValueError, lambda: normalize_theta_set(S.Complexes))
def test_multivariate_bool_as_set():
x, y = symbols('x,y')
assert And(x >= 0, y >= 0).as_set() == Interval(0, oo) * Interval(0, oo)
assert Or(x >= 0, y >= 0).as_set() == S.Reals*S.Reals - \
Interval(-oo, 0, True, True)*Interval(-oo, 0, True, True)
def __eq__(self, other):
return other == Interval(-S.Infinity, S.Infinity)
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 :func:`sympy.solvers.solveset.solvify`.
Notes
=====
Currently, we cannot solve all the inequalities due to limitations in
:func:`sympy.solvers.solveset.solvify`. Also, the solution returned for trigonometric inequalities
are restricted in its periodic interval.
See Also
========
sympy.solvers.solveset.solvify: solver returning solveset solutions with solve's output API
Examples
========
>>> from sympy import solve_univariate_inequality, Symbol, sin, Interval, S
>>> x = Symbol('x')
>>> solve_univariate_inequality(x**2 >= 4, x)
((2 <= x) & (x < oo)) | ((-oo < x) & (x <= -2))
>>> 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.solvers.solvers import denoms
if domain.is_subset(S.Reals) is False:
raise NotImplementedError(
filldedent('''
Inequalities in the complex domain are
not supported. Try the real domain by
setting domain=S.Reals'''))
elif domain is not S.Reals:
rv = solve_univariate_inequality(
expr, gen, relational=False,
continuous=continuous).intersection(domain)
if relational:
rv = rv.as_relational(gen)
return rv
else:
pass # continue with attempt to solve in Real domain
# 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_extended_real is False:
rv = S.EmptySet
return rv if not relational else rv.as_relational(_gen)
elif gen.is_extended_real is None:
gen = Dummy('gen', extended_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 == 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 in ('<', '<='):
if expr.func(frange.sup, 0):
rv = domain
elif not expr.func(frange.inf, 0):
rv = S.EmptySet
elif rel in ('>', '>='):
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).intersect(_domain)
_domain = domain
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_extended_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:
sifted = sift(critical_points,
lambda x: x.is_extended_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_extended_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_extended_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 im_sol is S.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)
sol_sets = [S.EmptySet]
start = domain.inf
if start in domain and 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 end in domain and 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 _eval_hilbert_space(cls, label):
return L2(Interval(S.NegativeInfinity, S.Infinity))
def solve_poly_inequality(poly, rel):
"""Solve a polynomial inequality with rational coefficients.
Examples
========
>>> from sympy import solve_poly_inequality, Poly
>>> from sympy.abc import x
>>> solve_poly_inequality(Poly(x, x, domain='ZZ'), '==')
[{0}]
>>> solve_poly_inequality(Poly(x**2 - 1, x, domain='ZZ'), '!=')
[Interval.open(-oo, -1), Interval.open(-1, 1), Interval.open(1, oo)]
>>> solve_poly_inequality(Poly(x**2 - 1, x, domain='ZZ'), '==')
[{-1}, {1}]
See Also
========
solve_poly_inequalities
"""
if not isinstance(poly, Poly):
raise ValueError(
'For efficiency reasons, `poly` should be a Poly instance')
if poly.as_expr().is_number:
t = Relational(poly.as_expr(), 0, rel)
if t is S.true:
return [S.Reals]
elif t is S.false:
return [S.EmptySet]
else:
raise NotImplementedError("could not determine truth value of %s" %
t)
reals, intervals = poly.real_roots(multiple=False), []
if rel == '==':
for root, _ in reals:
interval = Interval(root, root)
intervals.append(interval)
elif rel == '!=':
left = S.NegativeInfinity
for right, _ in reals + [(S.Infinity, 1)]:
interval = Interval(left, right, True, True)
intervals.append(interval)
left = right
else:
if poly.LC() > 0:
sign = +1
else:
sign = -1
eq_sign, equal = None, False
if rel == '>':
eq_sign = +1
elif rel == '<':
eq_sign = -1
elif rel == '>=':
eq_sign, equal = +1, True
elif rel == '<=':
eq_sign, equal = -1, True
else:
raise ValueError("'%s' is not a valid relation" % rel)
right, right_open = S.Infinity, True
for left, multiplicity in reversed(reals):
if multiplicity % 2:
if sign == eq_sign:
intervals.insert(
0, Interval(left, right, not equal, right_open))
sign, right, right_open = -sign, left, not equal
else:
if sign == eq_sign and not equal:
intervals.insert(0, Interval(left, right, True,
right_open))
right, right_open = left, True
elif sign != eq_sign and equal:
intervals.insert(0, Interval(left, left))
if sign == eq_sign:
intervals.insert(
0, Interval(S.NegativeInfinity, right, True, right_open))
return intervals
def solve_rational_inequalities(eqs):
"""Solve a system of rational inequalities with rational coefficients.
Examples
========
>>> from sympy.abc import x
>>> from sympy import solve_rational_inequalities, Poly
>>> solve_rational_inequalities([[
... ((Poly(-x + 1), Poly(1, x)), '>='),
... ((Poly(-x + 1), Poly(1, x)), '<=')]])
{1}
>>> solve_rational_inequalities([[
... ((Poly(x), Poly(1, x)), '!='),
... ((Poly(-x + 1), Poly(1, x)), '>=')]])
Union(Interval.open(-oo, 0), Interval.Lopen(0, 1))
See Also
========
solve_poly_inequality
"""
result = S.EmptySet
for _eqs in eqs:
if not _eqs:
continue
global_intervals = [Interval(S.NegativeInfinity, S.Infinity)]
for (numer, denom), rel in _eqs:
numer_intervals = solve_poly_inequality(numer * denom, rel)
denom_intervals = solve_poly_inequality(denom, '==')
intervals = []
for numer_interval in numer_intervals:
for global_interval in global_intervals:
interval = numer_interval.intersect(global_interval)
if interval is not S.EmptySet:
intervals.append(interval)
global_intervals = intervals
intervals = []
for global_interval in global_intervals:
for denom_interval in denom_intervals:
global_interval -= denom_interval
if global_interval is not S.EmptySet:
intervals.append(global_interval)
global_intervals = intervals
if not global_intervals:
break
for interval in global_intervals:
result = result.union(interval)
return result
def normalize_theta_set(theta):
"""
Normalize a Real Set theta in the Interval [0, 2*pi). It currently
supports Interval and FiniteSet. It Returns a the normalized value
of theta in the Set. For Interval, a maximum of one cycle [0, 2*pi],
is returned i.e. for theta equal to [0, 10*pi], returned normalized
value would be [0, 2*pi). As of now it supports theta as FiniteSet
and Interval.
Raises
======
NotImplementedError
The algorithms for Normalizing theta Set are not yet
implemented.
ValueError
The input is not valid, i.e. the input is not a real set.
RuntimeError
It is a bug, please report to the github issue tracker.
Examples
========
>>> from sympy.sets.fancysets import normalize_theta_set
>>> from sympy import Interval, FiniteSet, pi
>>> normalize_theta_set(Interval(9*pi/2, 5*pi))
[pi/2, pi]
>>> normalize_theta_set(Interval(-3*pi/2, pi/2))
[0, 2*pi)
>>> normalize_theta_set(Interval(-pi/2, pi/2))
[0, pi/2] U [3*pi/2, 2*pi)
>>> normalize_theta_set(Interval(-4*pi, 3*pi))
[0, 2*pi)
>>> normalize_theta_set(Interval(-3*pi/2, -pi/2))
[pi/2, 3*pi/2]
>>> normalize_theta_set(FiniteSet(0, pi, 3*pi))
{0, pi}
"""
from sympy.functions.elementary.trigonometric import _pi_coeff as coeff
from sympy.functions.elementary.complexes import Abs
if theta.is_Interval:
# one complete circle
if Abs(theta.args[0] - theta.args[1]) >= 2*S.Pi:
return Interval(0, 2*S.Pi, False, True)
new_theta = []
for val in [theta.args[0], theta.args[1]]:
k = coeff(val)
if (not k) and (k != S.Zero):
raise NotImplementedError('Normalizing theta without pi as'
'coefficient, is not Implemented.')
elif k == S.Zero:
if val == S.Zero:
new_theta.append(S.Zero)
else:
# when theta is n*pi
new_theta.append(2*S.Pi)
else:
new_theta.append(k*S.Pi)
# for negative theta
if new_theta[0] > new_theta[1]:
return Union(Interval(S(0), new_theta[1]),
Interval(new_theta[0], 2*S.Pi, False, True))
else:
return Interval(*new_theta)
elif theta.is_FiniteSet:
new_theta = []
for element in theta:
k = coeff(element)
if (not k) and (k != S.Zero):
raise NotImplementedError('Normalizing theta without pi as'
'coefficient, is not Implemented.')
elif k == S.Zero:
if element == S.Zero:
new_theta.append(S.Zero)
else:
new_theta.append(k*S.Pi)
return FiniteSet(*new_theta)
elif theta.is_subset(S.Reals):
raise NotImplementedError("Normalizing theta when, its %s is not"
"Implemented" % type(theta))
else:
raise ValueError(" %s is not a real set" % (theta))
def __eq__(self, other):
return other == Interval(S.NegativeInfinity, S.Infinity)
def test_issue_8777():
assert And(x > 2, x < oo).as_set() == Interval(2, oo, left_open=True)
assert And(x >= 1, x < oo).as_set() == Interval(1, oo)
assert (x < oo).as_set() == Interval(-oo, oo)
assert (x > -oo).as_set() == Interval(-oo, oo)
def __hash__(self):
return hash(Interval(S.NegativeInfinity, S.Infinity))
def test_issue_8975():
assert Or(And(-oo < x, x <= -2), And(2 <= x, x < oo)).as_set() == \
Interval(-oo, -2) + Interval(2, oo)
def __hash__(self):
return hash(Interval(-S.Infinity, S.Infinity))
def interval(self):
return Interval(self.args[1][1], self.args[1][2])
def test_imageset_intersect_interval():
from sympy.abc import n
f1 = ImageSet(Lambda(n, n * pi), S.Integers)
f2 = ImageSet(Lambda(n, 2 * n), Interval(0, pi))
f3 = ImageSet(Lambda(n, 2 * n * pi + pi / 2), S.Integers)
# complex expressions
f4 = ImageSet(Lambda(n, n * I * pi), S.Integers)
f5 = ImageSet(Lambda(n, 2 * I * n * pi + pi / 2), S.Integers)
# non-linear expressions
f6 = ImageSet(Lambda(n, log(n)), S.Integers)
f7 = ImageSet(Lambda(n, n**2), S.Integers)
f8 = ImageSet(Lambda(n, Abs(n)), S.Integers)
f9 = ImageSet(Lambda(n, exp(n)), S.Naturals0)
assert f1.intersect(Interval(-1, 1)) == FiniteSet(0)
assert f1.intersect(Interval(0, 2 * pi, False, True)) == FiniteSet(0, pi)
assert f2.intersect(Interval(1, 2)) == Interval(1, 2)
assert f3.intersect(Interval(-1, 1)) == S.EmptySet
assert f3.intersect(Interval(-5, 5)) == FiniteSet(pi * Rational(-3, 2),
pi / 2)
assert f4.intersect(Interval(-1, 1)) == FiniteSet(0)
assert f4.intersect(Interval(1, 2)) == S.EmptySet
assert f5.intersect(Interval(0, 1)) == S.EmptySet
assert f6.intersect(Interval(0, 1)) == FiniteSet(S.Zero, log(2))
assert f7.intersect(Interval(0, 10)) == Intersection(f7, Interval(0, 10))
assert f8.intersect(Interval(0, 2)) == Intersection(f8, Interval(0, 2))
assert f9.intersect(Interval(1, 2)) == Intersection(f9, Interval(1, 2))
def test_not_empty_in():
assert not_empty_in(FiniteSet(x, 2*x).intersect(Interval(1, 2, True, False)), x) == \
Interval(S(1)/2, 2, True, False)
assert not_empty_in(FiniteSet(x, x**2).intersect(Interval(1, 2)), x) == \
Union(Interval(-sqrt(2), -1), Interval(1, 2))
assert not_empty_in(FiniteSet(x**2 + x, x).intersect(Interval(2, 4)), x) == \
Union(Interval(-sqrt(17)/2 - S(1)/2, -2),
Interval(1, -S(1)/2 + sqrt(17)/2), Interval(2, 4))
assert not_empty_in(FiniteSet(x/(x - 1)).intersect(S.Reals), x) == \
Complement(S.Reals, FiniteSet(1))
assert not_empty_in(FiniteSet(a/(a - 1)).intersect(S.Reals), a) == \
Complement(S.Reals, FiniteSet(1))
assert not_empty_in(FiniteSet((x**2 - 3*x + 2)/(x - 1)).intersect(S.Reals), x) == \
Complement(S.Reals, FiniteSet(1))
assert not_empty_in(FiniteSet(3, 4, x/(x - 1)).intersect(Interval(2, 3)), x) == \
Union(Interval(S(3)/2, 2), FiniteSet(3))
assert not_empty_in(FiniteSet(x/(x**2 - 1)).intersect(S.Reals), x) == \
Complement(S.Reals, FiniteSet(-1, 1))
assert not_empty_in(FiniteSet(x, x**2).intersect(Union(Interval(1, 3, True, True),
Interval(4, 5))), x) == \
Union(Interval(-sqrt(5), -2), Interval(-sqrt(3), -1, True, True),
Interval(1, 3, True, True), Interval(4, 5))
assert not_empty_in(FiniteSet(1).intersect(Interval(3, 4)),
x) == S.EmptySet
assert not_empty_in(FiniteSet(x**2/(x + 2)).intersect(Interval(1, oo)), x) == \
Union(Interval(-2, -1, True, False), Interval(2, oo))