Source code for sympy.sets.fancysets

from __future__ import print_function, division

from sympy.logic.boolalg import And
from sympy.core.add import Add
from sympy.core.basic import Basic
from sympy.core.compatibility import as_int, with_metaclass, range, PY3
from sympy.core.expr import Expr
from sympy.core.function import Lambda, _coeff_isneg
from sympy.core.singleton import Singleton, S
from sympy.core.symbol import Dummy, symbols, Wild
from sympy.core.sympify import _sympify, sympify, converter
from sympy.sets.sets import (Set, Interval, Intersection, EmptySet, Union,
                             FiniteSet, imageset)
from sympy.sets.conditionset import ConditionSet
from sympy.utilities.misc import filldedent, func_name

[docs]class Naturals(with_metaclass(Singleton, Set)): """ Represents the natural numbers (or counting numbers) which are all positive integers starting from 1. This set is also available as the Singleton, S.Naturals. Examples ======== >>> from sympy import S, Interval, pprint >>> 5 in S.Naturals True >>> iterable = iter(S.Naturals) >>> next(iterable) 1 >>> next(iterable) 2 >>> next(iterable) 3 >>> pprint(S.Naturals.intersect(Interval(0, 10))) {1, 2, ..., 10} See Also ======== Naturals0 : non-negative integers (i.e. includes 0, too) Integers : also includes negative integers """ is_iterable = True _inf = S.One _sup = S.Infinity def _intersect(self, other): if other.is_Interval: return Intersection( S.Integers, other, Interval(self._inf, S.Infinity)) return None def _contains(self, other): if not isinstance(other, Expr): return S.false elif other.is_positive and other.is_integer: return S.true elif other.is_integer is False or other.is_positive is False: return S.false def __iter__(self): i = self._inf while True: yield i i = i + 1 @property def _boundary(self): return self
[docs]class Naturals0(Naturals): """Represents the whole numbers which are all the non-negative integers, inclusive of zero. See Also ======== Naturals : positive integers; does not include 0 Integers : also includes the negative integers """ _inf = S.Zero def _contains(self, other): if not isinstance(other, Expr): return S.false elif other.is_integer and other.is_nonnegative: return S.true elif other.is_integer is False or other.is_nonnegative is False: return S.false
[docs]class Integers(with_metaclass(Singleton, Set)): """ Represents all integers: positive, negative and zero. This set is also available as the Singleton, S.Integers. Examples ======== >>> from sympy import S, Interval, pprint >>> 5 in S.Naturals True >>> iterable = iter(S.Integers) >>> next(iterable) 0 >>> next(iterable) 1 >>> next(iterable) -1 >>> next(iterable) 2 >>> pprint(S.Integers.intersect(Interval(-4, 4))) {-4, -3, ..., 4} See Also ======== Naturals0 : non-negative integers Integers : positive and negative integers and zero """ is_iterable = True def _intersect(self, other): from sympy.functions.elementary.integers import floor, ceiling if other is Interval(S.NegativeInfinity, S.Infinity) or other is S.Reals: return self elif other.is_Interval: s = Range(ceiling(other.left), floor(other.right) + 1) return s.intersect(other) # take out endpoints if open interval return None def _contains(self, other): if not isinstance(other, Expr): return S.false elif other.is_integer: return S.true elif other.is_integer is False: return S.false def _union(self, other): intersect = Intersection(self, other) if intersect == self: return other elif intersect == other: return self def __iter__(self): yield S.Zero i = S.One while True: yield i yield -i i = i + 1 @property def _inf(self): return -S.Infinity @property def _sup(self): return S.Infinity @property def _boundary(self): return self def _eval_imageset(self, f): expr = f.expr if not isinstance(expr, Expr): return if len(f.variables) > 1: return n = f.variables[0] # f(x) + c and f(-x) + c cover the same integers # so choose the form that has the fewest negatives c = f(0) fx = f(n) - c f_x = f(-n) - c neg_count = lambda e: sum(_coeff_isneg(_) for _ in Add.make_args(e)) if neg_count(f_x) < neg_count(fx): expr = f_x + c a = Wild('a', exclude=[n]) b = Wild('b', exclude=[n]) match = expr.match(a*n + b) if match and match[a]: # canonical shift expr = match[a]*n + match[b] % match[a] if expr != f.expr: return ImageSet(Lambda(n, expr), S.Integers)
class Reals(with_metaclass(Singleton, Interval)): def __new__(cls): return Interval.__new__(cls, -S.Infinity, S.Infinity) def __eq__(self, other): return other == Interval(-S.Infinity, S.Infinity) def __hash__(self): return hash(Interval(-S.Infinity, S.Infinity))
[docs]class ImageSet(Set): """ Image of a set under a mathematical function. The transformation must be given as a Lambda function which has as many arguments as the elements of the set upon which it operates, e.g. 1 argument when acting on the set of integers or 2 arguments when acting on a complex region. This function is not normally called directly, but is called from `imageset`. Examples ======== >>> from sympy import Symbol, S, pi, Dummy, Lambda >>> from sympy.sets.sets import FiniteSet, Interval >>> from sympy.sets.fancysets import ImageSet >>> x = Symbol('x') >>> N = S.Naturals >>> squares = ImageSet(Lambda(x, x**2), N) # {x**2 for x in N} >>> 4 in squares True >>> 5 in squares False >>> FiniteSet(0, 1, 2, 3, 4, 5, 6, 7, 9, 10).intersect(squares) {1, 4, 9} >>> square_iterable = iter(squares) >>> for i in range(4): ... next(square_iterable) 1 4 9 16 If you want to get value for `x` = 2, 1/2 etc. (Please check whether the `x` value is in `base_set` or not before passing it as args) >>> squares.lamda(2) 4 >>> squares.lamda(S(1)/2) 1/4 >>> n = Dummy('n') >>> solutions = ImageSet(Lambda(n, n*pi), S.Integers) # solutions of sin(x) = 0 >>> dom = Interval(-1, 1) >>> dom.intersect(solutions) {0} See Also ======== sympy.sets.sets.imageset """ def __new__(cls, lamda, base_set): if not isinstance(lamda, Lambda): raise ValueError('first argument must be a Lambda') if lamda is S.IdentityFunction: return base_set if not lamda.expr.free_symbols or not lamda.expr.args: return FiniteSet(lamda.expr) return Basic.__new__(cls, lamda, base_set) lamda = property(lambda self: self.args[0]) base_set = property(lambda self: self.args[1]) def __iter__(self): already_seen = set() for i in self.base_set: val = self.lamda(i) if val in already_seen: continue else: already_seen.add(val) yield val def _is_multivariate(self): return len(self.lamda.variables) > 1 def _contains(self, other): from sympy.matrices import Matrix from sympy.solvers.solveset import solveset, linsolve from sympy.utilities.iterables import is_sequence, iterable, cartes L = self.lamda if is_sequence(other): if not is_sequence(L.expr): return S.false if len(L.expr) != len(other): raise ValueError(filldedent(''' Dimensions of other and output of Lambda are different.''')) elif iterable(other): raise ValueError(filldedent(''' `other` should be an ordered object like a Tuple.''')) solns = None if self._is_multivariate(): if not is_sequence(L.expr): # exprs -> (numer, denom) and check again # XXX this is a bad idea -- make the user # remap self to desired form return other.as_numer_denom() in self.func( Lambda(L.variables, L.expr.as_numer_denom()), self.base_set) eqs = [expr - val for val, expr in zip(other, L.expr)] variables = L.variables free = set(variables) if all(i.is_number for i in list(Matrix(eqs).jacobian(variables))): solns = list(linsolve([e - val for e, val in zip(L.expr, other)], variables)) else: syms = [e.free_symbols & free for e in eqs] solns = {} for i, (e, s, v) in enumerate(zip(eqs, syms, other)): if not s: if e != v: return S.false solns[vars[i]] = [v] continue elif len(s) == 1: sy = s.pop() sol = solveset(e, sy) if sol is S.EmptySet: return S.false elif isinstance(sol, FiniteSet): solns[sy] = list(sol) else: raise NotImplementedError else: raise NotImplementedError solns = cartes(*[solns[s] for s in variables]) else: x = L.variables[0] if isinstance(L.expr, Expr): # scalar -> scalar mapping solnsSet = solveset(L.expr - other, x) if solnsSet.is_FiniteSet: solns = list(solnsSet) else: msgset = solnsSet else: # scalar -> vector for e, o in zip(L.expr, other): solns = solveset(e - o, x) if solns is S.EmptySet: return S.false for soln in solns: try: if soln in self.base_set: break # check next pair except TypeError: if self.base_set.contains(soln.evalf()): break else: return S.false # never broke so there was no True return S.true if solns is None: raise NotImplementedError(filldedent(''' Determining whether %s contains %s has not been implemented.''' % (msgset, other))) for soln in solns: try: if soln in self.base_set: return S.true except TypeError: return self.base_set.contains(soln.evalf()) return S.false @property def is_iterable(self): return self.base_set.is_iterable def _intersect(self, other): from sympy.solvers.diophantine import diophantine if self.base_set is S.Integers: g = None if isinstance(other, ImageSet) and other.base_set is S.Integers: g = other.lamda.expr m = other.lamda.variables[0] elif other is S.Integers: m = g = Dummy('x') if g is not None: f = self.lamda.expr n = self.lamda.variables[0] # Diophantine sorts the solutions according to the alphabetic # order of the variable names, since the result should not depend # on the variable name, they are replaced by the dummy variables # below a, b = Dummy('a'), Dummy('b') f, g = f.subs(n, a), g.subs(m, b) solns_set = diophantine(f - g) if solns_set == set(): return EmptySet() solns = list(diophantine(f - g)) if len(solns) != 1: return # since 'a' < 'b', select soln for n nsol = solns[0][0] t = nsol.free_symbols.pop() return imageset(Lambda(n, f.subs(a, nsol.subs(t, n))), S.Integers) if other == S.Reals: from sympy.solvers.solveset import solveset_real from sympy.core.function import expand_complex if len(self.lamda.variables) > 1: return None f = self.lamda.expr n = self.lamda.variables[0] n_ = Dummy(, real=True) f_ = f.subs(n, n_) re, im = f_.as_real_imag() im = expand_complex(im) return imageset(Lambda(n_, re), self.base_set.intersect( solveset_real(im, n_))) elif isinstance(other, Interval): from sympy.solvers.solveset import (invert_real, invert_complex, solveset) f = self.lamda.expr n = self.lamda.variables[0] base_set = self.base_set 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
[docs]class Range(Set): """ Represents a range of integers. Can be called as Range(stop), Range(start, stop), or Range(start, stop, step); when stop is not given it defaults to 1. `Range(stop)` is the same as `Range(0, stop, 1)` and the stop value (juse as for Python ranges) is not included in the Range values. >>> from sympy import Range >>> list(Range(3)) [0, 1, 2] The step can also be negative: >>> list(Range(10, 0, -2)) [10, 8, 6, 4, 2] The stop value is made canonical so equivalent ranges always have the same args: >>> Range(0, 10, 3) Range(0, 12, 3) Infinite ranges are allowed. If the starting point is infinite, then the final value is ``stop - step``. To iterate such a range, it needs to be reversed: >>> from sympy import oo >>> r = Range(-oo, 1) >>> r[-1] 0 >>> next(iter(r)) Traceback (most recent call last): ... ValueError: Cannot iterate over Range with infinite start >>> next(iter(r.reversed)) 0 Although Range is a set (and supports the normal set operations) it maintains the order of the elements and can be used in contexts where `range` would be used. >>> from sympy import Interval >>> Range(0, 10, 2).intersect(Interval(3, 7)) Range(4, 8, 2) >>> list(_) [4, 6] Athough slicing of a Range will always return a Range -- possibly empty -- an empty set will be returned from any intersection that is empty: >>> Range(3)[:0] Range(0, 0, 1) >>> Range(3).intersect(Interval(4, oo)) EmptySet() >>> Range(3).intersect(Range(4, oo)) EmptySet() """ is_iterable = True def __new__(cls, *args): from sympy.functions.elementary.integers import ceiling if len(args) == 1: if isinstance(args[0], range if PY3 else xrange): args = args[0].__reduce__()[1] # use pickle method # expand range slc = slice(*args) if slc.step == 0: raise ValueError("step cannot be 0") start, stop, step = slc.start or 0, slc.stop, slc.step or 1 try: start, stop, step = [ w if w in [S.NegativeInfinity, S.Infinity] else sympify(as_int(w)) for w in (start, stop, step)] except ValueError: raise ValueError(filldedent(''' Finite arguments to Range must be integers; `imageset` can define other cases, e.g. use `imageset(i, i/10, Range(3))` to give [0, 1/10, 1/5].''')) if not step.is_Integer: raise ValueError(filldedent(''' Ranges must have a literal integer step.''')) if all(i.is_infinite for i in (start, stop)): if start == stop: # canonical null handled below start = stop = S.One else: raise ValueError(filldedent(''' Either the start or end value of the Range must be finite.''')) if start.is_infinite: end = stop else: ref = start if start.is_finite else stop n = ceiling((stop - ref)/step) if n <= 0: # null Range start = end = 0 step = 1 else: end = ref + n*step return Basic.__new__(cls, start, end, step) start = property(lambda self: self.args[0]) stop = property(lambda self: self.args[1]) step = property(lambda self: self.args[2]) @property def reversed(self): """Return an equivalent Range in the opposite order. Examples ======== >>> from sympy import Range >>> Range(10).reversed Range(9, -1, -1) """ if not self: return self return self.func( self.stop - self.step, self.start - self.step, -self.step) 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 # In case of null Range, return an EmptySet. if self.size == 0: return S.EmptySet # 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 _contains(self, other): if not self: return S.false if other.is_infinite: return S.false if not other.is_integer: return other.is_integer ref = self.start if self.start.is_finite else self.stop if (ref - other) % self.step: # off sequence return S.false return _sympify(other >= self.inf and other <= self.sup) def __iter__(self): if self.start in [S.NegativeInfinity, S.Infinity]: raise ValueError("Cannot iterate over Range with infinite start") elif self: i = self.start step = self.step while True: if (step > 0 and not (self.start <= i < self.stop)) or \ (step < 0 and not (self.stop < i <= self.start)): break yield i i += step def __len__(self): if not self: return 0 dif = self.stop - self.start if dif.is_infinite: raise ValueError( "Use .size to get the length of an infinite Range") return abs(dif//self.step) @property def size(self): try: return _sympify(len(self)) except ValueError: return S.Infinity def __nonzero__(self): return self.start != self.stop __bool__ = __nonzero__ def __getitem__(self, i): from sympy.functions.elementary.integers import ceiling ooslice = "cannot slice from the end with an infinite value" zerostep = "slice step cannot be zero" # if we had to take every other element in the following # oo, ..., 6, 4, 2, 0 # we might get oo, ..., 4, 0 or oo, ..., 6, 2 ambiguous = "cannot unambiguously re-stride from the end " + \ "with an infinite value" if isinstance(i, slice): if self.size.is_finite: start, stop, step = i.indices(self.size) n = ceiling((stop - start)/step) if n <= 0: return Range(0) canonical_stop = start + n*step end = canonical_stop - step ss = step*self.step return Range(self[start], self[end] + ss, ss) else: # infinite Range start = i.start stop = i.stop if i.step == 0: raise ValueError(zerostep) step = i.step or 1 ss = step*self.step #--------------------- # handle infinite on right # e.g. Range(0, oo) or Range(0, -oo, -1) # -------------------- if self.stop.is_infinite: # start and stop are not interdependent -- # they only depend on step --so we use the # equivalent reversed values return self.reversed[ stop if stop is None else -stop + 1: start if start is None else -start: step].reversed #--------------------- # handle infinite on the left # e.g. Range(oo, 0, -1) or Range(-oo, 0) # -------------------- # consider combinations of # start/stop {== None, < 0, == 0, > 0} and # step {< 0, > 0} if start is None: if stop is None: if step < 0: return Range(self[-1], self.start, ss) elif step > 1: raise ValueError(ambiguous) else: # == 1 return self elif stop < 0: if step < 0: return Range(self[-1], self[stop], ss) else: # > 0 return Range(self.start, self[stop], ss) elif stop == 0: if step > 0: return Range(0) else: # < 0 raise ValueError(ooslice) elif stop == 1: if step > 0: raise ValueError(ooslice) # infinite singleton else: # < 0 raise ValueError(ooslice) else: # > 1 raise ValueError(ooslice) elif start < 0: if stop is None: if step < 0: return Range(self[start], self.start, ss) else: # > 0 return Range(self[start], self.stop, ss) elif stop < 0: return Range(self[start], self[stop], ss) elif stop == 0: if step < 0: raise ValueError(ooslice) else: # > 0 return Range(0) elif stop > 0: raise ValueError(ooslice) elif start == 0: if stop is None: if step < 0: raise ValueError(ooslice) # infinite singleton elif step > 1: raise ValueError(ambiguous) else: # == 1 return self elif stop < 0: if step > 1: raise ValueError(ambiguous) elif step == 1: return Range(self.start, self[stop], ss) else: # < 0 return Range(0) else: # >= 0 raise ValueError(ooslice) elif start > 0: raise ValueError(ooslice) else: if not self: raise IndexError('Range index out of range') if i == 0: return self.start if i == -1 or i is S.Infinity: return self.stop - self.step rv = (self.stop if i < 0 else self.start) + i*self.step if rv.is_infinite: raise ValueError(ooslice) if rv < self.inf or rv > self.sup: raise IndexError("Range index out of range") return rv def _eval_imageset(self, f): from sympy.core.function import expand_mul if not self: return S.EmptySet if not isinstance(f.expr, Expr): return if self.size == 1: return FiniteSet(f(self[0])) if f is S.IdentityFunction: return self x = f.variables[0] expr = f.expr # handle f that is linear in f's variable if x not in expr.free_symbols or x in expr.diff(x).free_symbols: return if self.start.is_finite: F = f(self.step*x + self.start) # for i in range(len(self)) else: F = f(-self.step*x + self[-1]) F = expand_mul(F) if F != expr: return imageset(x, F, Range(self.size)) @property def _inf(self): if not self: raise NotImplementedError if self.step > 0: return self.start else: return self.stop - self.step @property def _sup(self): if not self: raise NotImplementedError if self.step > 0: return self.stop - self.step else: return self.start @property def _boundary(self): return self
if PY3: converter[range] = Range else: converter[xrange] = Range
[docs]def normalize_theta_set(theta): """ Normalize a Real Set `theta` in the Interval [0, 2*pi). It returns a 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 intervals with end points as non-multiples of `pi` is not supported. 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)) Interval(pi/2, pi) >>> normalize_theta_set(Interval(-3*pi/2, pi/2)) Interval.Ropen(0, 2*pi) >>> normalize_theta_set(Interval(-pi/2, pi/2)) Union(Interval(0, pi/2), Interval.Ropen(3*pi/2, 2*pi)) >>> normalize_theta_set(Interval(-4*pi, 3*pi)) Interval.Ropen(0, 2*pi) >>> normalize_theta_set(Interval(-3*pi/2, -pi/2)) Interval(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 if theta.is_Interval: interval_len = theta.measure # one complete circle if interval_len >= 2*S.Pi: if interval_len == 2*S.Pi and theta.left_open and theta.right_open: k = coeff(theta.start) return Union(Interval(0, k*S.Pi, False, True), Interval(k*S.Pi, 2*S.Pi, True, True)) return Interval(0, 2*S.Pi, False, True) k_start, k_end = coeff(theta.start), coeff(theta.end) if k_start is None or k_end is None: raise NotImplementedError("Normalizing theta without pi as coefficient is " "not yet implemented") new_start = k_start*S.Pi new_end = k_end*S.Pi if new_start > new_end: return Union(Interval(S.Zero, new_end, False, theta.right_open), Interval(new_start, 2*S.Pi, theta.left_open, True)) else: return Interval(new_start, new_end, theta.left_open, theta.right_open) elif theta.is_FiniteSet: new_theta = [] for element in theta: k = coeff(element) if k is None: raise NotImplementedError('Normalizing theta without pi as ' 'coefficient, is not Implemented.') else: new_theta.append(k*S.Pi) return FiniteSet(*new_theta) elif theta.is_Union: return Union(*[normalize_theta_set(interval) for interval in theta.args]) elif theta.is_subset(S.Reals): raise NotImplementedError("Normalizing theta when, it is of type %s is not " "implemented" % type(theta)) else: raise ValueError(" %s is not a real set" % (theta))
[docs]class ComplexRegion(Set): """ Represents the Set of all Complex Numbers. It can represent a region of Complex Plane in both the standard forms Polar and Rectangular coordinates. * Polar Form Input is in the form of the ProductSet or Union of ProductSets of the intervals of r and theta, & use the flag polar=True. Z = {z in C | z = r*[cos(theta) + I*sin(theta)], r in [r], theta in [theta]} * Rectangular Form Input is in the form of the ProductSet or Union of ProductSets of interval of x and y the of the Complex numbers in a Plane. Default input type is in rectangular form. Z = {z in C | z = x + I*y, x in [Re(z)], y in [Im(z)]} Examples ======== >>> from sympy.sets.fancysets import ComplexRegion >>> from sympy.sets import Interval >>> from sympy import S, I, Union >>> a = Interval(2, 3) >>> b = Interval(4, 6) >>> c = Interval(1, 8) >>> c1 = ComplexRegion(a*b) # Rectangular Form >>> c1 ComplexRegion(Interval(2, 3) x Interval(4, 6), False) * c1 represents the rectangular region in complex plane surrounded by the coordinates (2, 4), (3, 4), (3, 6) and (2, 6), of the four vertices. >>> c2 = ComplexRegion(Union(a*b, b*c)) >>> c2 ComplexRegion(Union(Interval(2, 3) x Interval(4, 6), Interval(4, 6) x Interval(1, 8)), False) * c2 represents the Union of two rectangular regions in complex plane. One of them surrounded by the coordinates of c1 and other surrounded by the coordinates (4, 1), (6, 1), (6, 8) and (4, 8). >>> 2.5 + 4.5*I in c1 True >>> 2.5 + 6.5*I in c1 False >>> r = Interval(0, 1) >>> theta = Interval(0, 2*S.Pi) >>> c2 = ComplexRegion(r*theta, polar=True) # Polar Form >>> c2 # unit Disk ComplexRegion(Interval(0, 1) x Interval.Ropen(0, 2*pi), True) * c2 represents the region in complex plane inside the Unit Disk centered at the origin. >>> 0.5 + 0.5*I in c2 True >>> 1 + 2*I in c2 False >>> unit_disk = ComplexRegion(Interval(0, 1)*Interval(0, 2*S.Pi), polar=True) >>> upper_half_unit_disk = ComplexRegion(Interval(0, 1)*Interval(0, S.Pi), polar=True) >>> intersection = unit_disk.intersect(upper_half_unit_disk) >>> intersection ComplexRegion(Interval(0, 1) x Interval(0, pi), True) >>> intersection == upper_half_unit_disk True See Also ======== Reals """ is_ComplexRegion = True def __new__(cls, sets, polar=False): from sympy import sin, cos x, y, r, theta = symbols('x, y, r, theta', cls=Dummy) I = S.ImaginaryUnit polar = sympify(polar) # Rectangular Form if polar == False: if all(_a.is_FiniteSet for _a in sets.args) and (len(sets.args) == 2): # ** ProductSet of FiniteSets in the Complex Plane. ** # For Cases like ComplexRegion({2, 4}*{3}), It # would return {2 + 3*I, 4 + 3*I} complex_num = [] for x in sets.args[0]: for y in sets.args[1]: complex_num.append(x + I*y) obj = FiniteSet(*complex_num) else: obj = ImageSet.__new__(cls, Lambda((x, y), x + I*y), sets) obj._variables = (x, y) obj._expr = x + I*y # Polar Form elif polar == True: new_sets = [] # sets is Union of ProductSets if not sets.is_ProductSet: for k in sets.args: new_sets.append(k) # sets is ProductSets else: new_sets.append(sets) # Normalize input theta for k, v in enumerate(new_sets): from sympy.sets import ProductSet new_sets[k] = ProductSet(v.args[0], normalize_theta_set(v.args[1])) sets = Union(*new_sets) obj = ImageSet.__new__(cls, Lambda((r, theta), r*(cos(theta) + I*sin(theta))), sets) obj._variables = (r, theta) obj._expr = r*(cos(theta) + I*sin(theta)) else: raise ValueError("polar should be either True or False") obj._sets = sets obj._polar = polar return obj @property def sets(self): """ Return raw input sets to the self. Examples ======== >>> from sympy import Interval, ComplexRegion, Union >>> a = Interval(2, 3) >>> b = Interval(4, 5) >>> c = Interval(1, 7) >>> C1 = ComplexRegion(a*b) >>> C1.sets Interval(2, 3) x Interval(4, 5) >>> C2 = ComplexRegion(Union(a*b, b*c)) >>> C2.sets Union(Interval(2, 3) x Interval(4, 5), Interval(4, 5) x Interval(1, 7)) """ return self._sets @property def args(self): return (self._sets, self._polar) @property def variables(self): return self._variables @property def expr(self): return self._expr @property def psets(self): """ Return a tuple of sets (ProductSets) input of the self. Examples ======== >>> from sympy import Interval, ComplexRegion, Union >>> a = Interval(2, 3) >>> b = Interval(4, 5) >>> c = Interval(1, 7) >>> C1 = ComplexRegion(a*b) >>> C1.psets (Interval(2, 3) x Interval(4, 5),) >>> C2 = ComplexRegion(Union(a*b, b*c)) >>> C2.psets (Interval(2, 3) x Interval(4, 5), Interval(4, 5) x Interval(1, 7)) """ if self.sets.is_ProductSet: psets = () psets = psets + (self.sets, ) else: psets = self.sets.args return psets @property def a_interval(self): """ Return the union of intervals of `x` when, self is in rectangular form, or the union of intervals of `r` when self is in polar form. Examples ======== >>> from sympy import Interval, ComplexRegion, Union >>> a = Interval(2, 3) >>> b = Interval(4, 5) >>> c = Interval(1, 7) >>> C1 = ComplexRegion(a*b) >>> C1.a_interval Interval(2, 3) >>> C2 = ComplexRegion(Union(a*b, b*c)) >>> C2.a_interval Union(Interval(2, 3), Interval(4, 5)) """ a_interval = [] for element in self.psets: a_interval.append(element.args[0]) a_interval = Union(*a_interval) return a_interval @property def b_interval(self): """ Return the union of intervals of `y` when, self is in rectangular form, or the union of intervals of `theta` when self is in polar form. Examples ======== >>> from sympy import Interval, ComplexRegion, Union >>> a = Interval(2, 3) >>> b = Interval(4, 5) >>> c = Interval(1, 7) >>> C1 = ComplexRegion(a*b) >>> C1.b_interval Interval(4, 5) >>> C2 = ComplexRegion(Union(a*b, b*c)) >>> C2.b_interval Interval(1, 7) """ b_interval = [] for element in self.psets: b_interval.append(element.args[1]) b_interval = Union(*b_interval) return b_interval @property def polar(self): """ Returns True if self is in polar form. Examples ======== >>> from sympy import Interval, ComplexRegion, Union, S >>> a = Interval(2, 3) >>> b = Interval(4, 5) >>> theta = Interval(0, 2*S.Pi) >>> C1 = ComplexRegion(a*b) >>> C1.polar False >>> C2 = ComplexRegion(a*theta, polar=True) >>> C2.polar True """ return self._polar @property def _measure(self): """ The measure of self.sets. Examples ======== >>> from sympy import Interval, ComplexRegion, S >>> a, b = Interval(2, 5), Interval(4, 8) >>> c = Interval(0, 2*S.Pi) >>> c1 = ComplexRegion(a*b) >>> c1.measure 12 >>> c2 = ComplexRegion(a*c, polar=True) >>> c2.measure 6*pi """ return self.sets._measure
[docs] @classmethod def from_real(cls, sets): """ Converts given subset of real numbers to a complex region. Examples ======== >>> from sympy import Interval, ComplexRegion >>> unit = Interval(0,1) >>> ComplexRegion.from_real(unit) ComplexRegion(Interval(0, 1) x {0}, False) """ if not sets.is_subset(S.Reals): raise ValueError("sets must be a subset of the real line") return cls(sets * FiniteSet(0))
def _contains(self, other): from sympy.functions import arg, Abs from sympy.core.containers import Tuple other = sympify(other) isTuple = isinstance(other, Tuple) if isTuple and len(other) != 2: raise ValueError('expecting Tuple of length 2') # If the other is not an Expression, and neither a Tuple if not isinstance(other, Expr) and not isinstance(other, Tuple): return S.false # self in rectangular form if not self.polar: re, im = other if isTuple else other.as_real_imag() for element in self.psets: if And(element.args[0]._contains(re), element.args[1]._contains(im)): return True return False # self in polar form elif self.polar: if isTuple: r, theta = other elif other.is_zero: r, theta = S.Zero, S.Zero else: r, theta = Abs(other), arg(other) for element in self.psets: if And(element.args[0]._contains(r), element.args[1]._contains(theta)): return True return False def _intersect(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) def _union(self, other): if other.is_subset(S.Reals): # treat a subset of reals as a complex region other = ComplexRegion.from_real(other) if other.is_ComplexRegion: # self in rectangular form if (not self.polar) and (not other.polar): return ComplexRegion(Union(self.sets, other.sets)) # self in polar form elif self.polar and other.polar: return ComplexRegion(Union(self.sets, other.sets), polar=True) return None
class Complexes(with_metaclass(Singleton, ComplexRegion)): def __new__(cls): return ComplexRegion.__new__(cls, S.Reals*S.Reals) def __eq__(self, other): return other == ComplexRegion(S.Reals*S.Reals) def __hash__(self): return hash(ComplexRegion(S.Reals*S.Reals)) def __str__(self): return "S.Complexes" def __repr__(self): return "S.Complexes"