Traktor/myenv/Lib/site-packages/sympy/sets/handlers/intersection.py
2024-05-23 01:57:24 +02:00

515 lines
16 KiB
Python

from sympy.core.function import Lambda, expand_complex
from sympy.core.mul import Mul
from sympy.core.numbers import ilcm
from sympy.core.relational import Eq
from sympy.core.singleton import S
from sympy.core.symbol import (Dummy, symbols)
from sympy.core.sorting import ordered
from sympy.functions.elementary.complexes import sign
from sympy.functions.elementary.integers import floor, ceiling
from sympy.sets.fancysets import ComplexRegion
from sympy.sets.sets import (FiniteSet, Intersection, Interval, Set, Union)
from sympy.multipledispatch import Dispatcher
from sympy.sets.conditionset import ConditionSet
from sympy.sets.fancysets import (Integers, Naturals, Reals, Range,
ImageSet, Rationals)
from sympy.sets.sets import EmptySet, UniversalSet, imageset, ProductSet
from sympy.simplify.radsimp import numer
intersection_sets = Dispatcher('intersection_sets')
@intersection_sets.register(ConditionSet, ConditionSet)
def _(a, b):
return None
@intersection_sets.register(ConditionSet, Set)
def _(a, b):
return ConditionSet(a.sym, a.condition, Intersection(a.base_set, b))
@intersection_sets.register(Naturals, Integers)
def _(a, b):
return a
@intersection_sets.register(Naturals, Naturals)
def _(a, b):
return a if a is S.Naturals else b
@intersection_sets.register(Interval, Naturals)
def _(a, b):
return intersection_sets(b, a)
@intersection_sets.register(ComplexRegion, Set)
def _(self, other):
if other.is_ComplexRegion:
# self in rectangular form
if (not self.polar) and (not other.polar):
return ComplexRegion(Intersection(self.sets, other.sets))
# self in polar form
elif self.polar and other.polar:
r1, theta1 = self.a_interval, self.b_interval
r2, theta2 = other.a_interval, other.b_interval
new_r_interval = Intersection(r1, r2)
new_theta_interval = Intersection(theta1, theta2)
# 0 and 2*Pi means the same
if ((2*S.Pi in theta1 and S.Zero in theta2) or
(2*S.Pi in theta2 and S.Zero in theta1)):
new_theta_interval = Union(new_theta_interval,
FiniteSet(0))
return ComplexRegion(new_r_interval*new_theta_interval,
polar=True)
if other.is_subset(S.Reals):
new_interval = []
x = symbols("x", cls=Dummy, real=True)
# self in rectangular form
if not self.polar:
for element in self.psets:
if S.Zero in element.args[1]:
new_interval.append(element.args[0])
new_interval = Union(*new_interval)
return Intersection(new_interval, other)
# self in polar form
elif self.polar:
for element in self.psets:
if S.Zero in element.args[1]:
new_interval.append(element.args[0])
if S.Pi in element.args[1]:
new_interval.append(ImageSet(Lambda(x, -x), element.args[0]))
if S.Zero in element.args[0]:
new_interval.append(FiniteSet(0))
new_interval = Union(*new_interval)
return Intersection(new_interval, other)
@intersection_sets.register(Integers, Reals)
def _(a, b):
return a
@intersection_sets.register(Range, Interval)
def _(a, b):
# Check that there are no symbolic arguments
if not all(i.is_number for i in a.args + b.args[:2]):
return
# In case of null Range, return an EmptySet.
if a.size == 0:
return S.EmptySet
# trim down to self's size, and represent
# as a Range with step 1.
start = ceiling(max(b.inf, a.inf))
if start not in b:
start += 1
end = floor(min(b.sup, a.sup))
if end not in b:
end -= 1
return intersection_sets(a, Range(start, end + 1))
@intersection_sets.register(Range, Naturals)
def _(a, b):
return intersection_sets(a, Interval(b.inf, S.Infinity))
@intersection_sets.register(Range, Range)
def _(a, b):
# Check that there are no symbolic range arguments
if not all(all(v.is_number for v in r.args) for r in [a, b]):
return None
# non-overlap quick exits
if not b:
return S.EmptySet
if not a:
return S.EmptySet
if b.sup < a.inf:
return S.EmptySet
if b.inf > a.sup:
return S.EmptySet
# work with finite end at the start
r1 = a
if r1.start.is_infinite:
r1 = r1.reversed
r2 = b
if r2.start.is_infinite:
r2 = r2.reversed
# If both ends are infinite then it means that one Range is just the set
# of all integers (the step must be 1).
if r1.start.is_infinite:
return b
if r2.start.is_infinite:
return a
from sympy.solvers.diophantine.diophantine import diop_linear
# 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
va, vb = diop_linear(eq(r1, Dummy('a')) - eq(r2, Dummy('b')))
# check for no solution
no_solution = va is None and vb is None
if no_solution:
return S.EmptySet
# there is a solution
# -------------------
# find the coincident point, c
a0 = va.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(a, s1)
r2 = _updated_range(b, 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)
@intersection_sets.register(Range, Integers)
def _(a, b):
return a
@intersection_sets.register(Range, Rationals)
def _(a, b):
return a
@intersection_sets.register(ImageSet, Set)
def _(self, other):
from sympy.solvers.diophantine import diophantine
# Only handle the straight-forward univariate case
if (len(self.lamda.variables) > 1
or self.lamda.signature != self.lamda.variables):
return None
base_set = self.base_sets[0]
# Intersection between ImageSets with Integers as base set
# For {f(n) : n in Integers} & {g(m) : m in Integers} we solve the
# diophantine equations f(n)=g(m).
# If the solutions for n are {h(t) : t in Integers} then we return
# {f(h(t)) : t in integers}.
# If the solutions for n are {n_1, n_2, ..., n_k} then we return
# {f(n_i) : 1 <= i <= k}.
if base_set is S.Integers:
gm = None
if isinstance(other, ImageSet) and other.base_sets == (S.Integers,):
gm = other.lamda.expr
var = other.lamda.variables[0]
# Symbol of second ImageSet lambda must be distinct from first
m = Dummy('m')
gm = gm.subs(var, m)
elif other is S.Integers:
m = gm = Dummy('m')
if gm is not None:
fn = self.lamda.expr
n = self.lamda.variables[0]
try:
solns = list(diophantine(fn - gm, syms=(n, m), permute=True))
except (TypeError, NotImplementedError):
# TypeError if equation not polynomial with rational coeff.
# NotImplementedError if correct format but no solver.
return
# 3 cases are possible for solns:
# - empty set,
# - one or more parametric (infinite) solutions,
# - a finite number of (non-parametric) solution couples.
# Among those, there is one type of solution set that is
# not helpful here: multiple parametric solutions.
if len(solns) == 0:
return S.EmptySet
elif any(s.free_symbols for tupl in solns for s in tupl):
if len(solns) == 1:
soln, solm = solns[0]
(t,) = soln.free_symbols
expr = fn.subs(n, soln.subs(t, n)).expand()
return imageset(Lambda(n, expr), S.Integers)
else:
return
else:
return FiniteSet(*(fn.subs(n, s[0]) for s in solns))
if other == S.Reals:
from sympy.solvers.solvers import denoms, solve_linear
def _solution_union(exprs, sym):
# return a union of linear solutions to i in expr;
# if i cannot be solved, use a ConditionSet for solution
sols = []
for i in exprs:
x, xis = solve_linear(i, 0, [sym])
if x == sym:
sols.append(FiniteSet(xis))
else:
sols.append(ConditionSet(sym, Eq(i, 0)))
return Union(*sols)
f = self.lamda.expr
n = self.lamda.variables[0]
n_ = Dummy(n.name, real=True)
f_ = f.subs(n, n_)
re, im = f_.as_real_imag()
im = expand_complex(im)
re = re.subs(n_, n)
im = im.subs(n_, n)
ifree = im.free_symbols
lam = Lambda(n, re)
if im.is_zero:
# allow re-evaluation
# of self in this case to make
# the result canonical
pass
elif im.is_zero is False:
return S.EmptySet
elif ifree != {n}:
return None
else:
# univarite imaginary part in same variable;
# use numer instead of as_numer_denom to keep
# this as fast as possible while still handling
# simple cases
base_set &= _solution_union(
Mul.make_args(numer(im)), n)
# exclude values that make denominators 0
base_set -= _solution_union(denoms(f), n)
return imageset(lam, base_set)
elif isinstance(other, Interval):
from sympy.solvers.solveset import (invert_real, invert_complex,
solveset)
f = self.lamda.expr
n = self.lamda.variables[0]
new_inf, new_sup = None, None
new_lopen, new_ropen = other.left_open, other.right_open
if f.is_real:
inverter = invert_real
else:
inverter = invert_complex
g1, h1 = inverter(f, other.inf, n)
g2, h2 = inverter(f, other.sup, n)
if all(isinstance(i, FiniteSet) for i in (h1, h2)):
if g1 == n:
if len(h1) == 1:
new_inf = h1.args[0]
if g2 == n:
if len(h2) == 1:
new_sup = h2.args[0]
# TODO: Design a technique to handle multiple-inverse
# functions
# Any of the new boundary values cannot be determined
if any(i is None for i in (new_sup, new_inf)):
return
range_set = S.EmptySet
if all(i.is_real for i in (new_sup, new_inf)):
# this assumes continuity of underlying function
# however fixes the case when it is decreasing
if new_inf > new_sup:
new_inf, new_sup = new_sup, new_inf
new_interval = Interval(new_inf, new_sup, new_lopen, new_ropen)
range_set = base_set.intersect(new_interval)
else:
if other.is_subset(S.Reals):
solutions = solveset(f, n, S.Reals)
if not isinstance(range_set, (ImageSet, ConditionSet)):
range_set = solutions.intersect(other)
else:
return
if range_set is S.EmptySet:
return S.EmptySet
elif isinstance(range_set, Range) and range_set.size is not S.Infinity:
range_set = FiniteSet(*list(range_set))
if range_set is not None:
return imageset(Lambda(n, f), range_set)
return
else:
return
@intersection_sets.register(ProductSet, ProductSet)
def _(a, b):
if len(b.args) != len(a.args):
return S.EmptySet
return ProductSet(*(i.intersect(j) for i, j in zip(a.sets, b.sets)))
@intersection_sets.register(Interval, Interval)
def _(a, b):
# handle (-oo, oo)
infty = S.NegativeInfinity, S.Infinity
if a == Interval(*infty):
l, r = a.left, a.right
if l.is_real or l in infty or r.is_real or r in infty:
return b
# We can't intersect [0,3] with [x,6] -- we don't know if x>0 or x<0
if not a._is_comparable(b):
return None
empty = False
if a.start <= b.end and b.start <= a.end:
# Get topology right.
if a.start < b.start:
start = b.start
left_open = b.left_open
elif a.start > b.start:
start = a.start
left_open = a.left_open
else:
#this is to ensure that if Eq(a.start,b.start) but
#type(a.start) != type(b.start) the order of a and b
#does not matter for the result
start = list(ordered([a,b]))[0].start
left_open = a.left_open or b.left_open
if a.end < b.end:
end = a.end
right_open = a.right_open
elif a.end > b.end:
end = b.end
right_open = b.right_open
else:
end = list(ordered([a,b]))[0].end
right_open = a.right_open or b.right_open
if end - start == 0 and (left_open or right_open):
empty = True
else:
empty = True
if empty:
return S.EmptySet
return Interval(start, end, left_open, right_open)
@intersection_sets.register(EmptySet, Set)
def _(a, b):
return S.EmptySet
@intersection_sets.register(UniversalSet, Set)
def _(a, b):
return b
@intersection_sets.register(FiniteSet, FiniteSet)
def _(a, b):
return FiniteSet(*(a._elements & b._elements))
@intersection_sets.register(FiniteSet, Set)
def _(a, b):
try:
return FiniteSet(*[el for el in a if el in b])
except TypeError:
return None # could not evaluate `el in b` due to symbolic ranges.
@intersection_sets.register(Set, Set)
def _(a, b):
return None
@intersection_sets.register(Integers, Rationals)
def _(a, b):
return a
@intersection_sets.register(Naturals, Rationals)
def _(a, b):
return a
@intersection_sets.register(Rationals, Reals)
def _(a, b):
return a
def _intlike_interval(a, b):
try:
if b._inf is S.NegativeInfinity and b._sup is S.Infinity:
return a
s = Range(max(a.inf, ceiling(b.left)), floor(b.right) + 1)
return intersection_sets(s, b) # take out endpoints if open interval
except ValueError:
return None
@intersection_sets.register(Integers, Interval)
def _(a, b):
return _intlike_interval(a, b)
@intersection_sets.register(Naturals, Interval)
def _(a, b):
return _intlike_interval(a, b)