def _separatevars_dict(expr, symbols): if symbols: if not all((t.is_Atom for t in symbols)): raise ValueError("symbols must be Atoms.") symbols = list(symbols) elif symbols is None: return {'coeff': expr} else: symbols = list(expr.free_symbols) if not symbols: return ret = {i: [] for i in symbols + ['coeff']} for i in Mul.make_args(expr): expsym = i.free_symbols intersection = set(symbols).intersection(expsym) if len(intersection) > 1: return if len(intersection) == 0: # There are no symbols, so it is part of the coefficient ret['coeff'].append(i) else: ret[intersection.pop()].append(i) # rebuild for k, v in ret.items(): ret[k] = Mul(*v) return ret
def product_simplify(s): """Main function for Product simplification""" from diofant.concrete.products import Product terms = Mul.make_args(s) p_t = [] # Product Terms o_t = [] # Other Terms for term in terms: if isinstance(term, Product): p_t.append(term) else: o_t.append(term) used = [False] * len(p_t) for method in range(2): for i, p_term1 in enumerate(p_t): if not used[i]: for j, p_term2 in enumerate(p_t): if not used[j] and i != j: if isinstance(product_mul(p_term1, p_term2, method), Product): p_t[i] = product_mul(p_term1, p_term2, method) used[j] = True result = Mul(*o_t) for i, p_term in enumerate(p_t): if not used[i]: result = Mul(result, p_term) return result
def _print_Mul(self, expr): prec = precedence(expr) c, e = expr.as_coeff_Mul() if c < 0: expr = _keep_coeff(-c, e) sign = "-" else: sign = "" a = [] # items in the numerator b = [] # items that are in the denominator (if any) if self.order != 'none': args = expr.as_ordered_factors() else: # use make_args in case expr was something like -x -> x args = Mul.make_args(expr) multiple_ones = len([x for x in args if x == S.One]) > 1 # Gather args for numerator/denominator for item in args: if item.is_commutative and item.is_Pow and item.exp.is_Rational and item.exp.is_negative: if item.exp != -1: b.append(Pow(item.base, -item.exp, evaluate=False)) else: b.append(Pow(item.base, -item.exp)) elif item.is_Rational and item is not S.Infinity: if item.p != 1 or multiple_ones: a.append(Rational(item.p)) if item.q != 1: b.append(Rational(item.q)) else: a.append(item) a = a or [S.One] a_str = [self.parenthesize(x, prec) for x in a] b_str = [self.parenthesize(x, prec) for x in b] if len(b) == 0: return sign + '*'.join(a_str) elif len(b) == 1: return sign + '*'.join(a_str) + "/" + b_str[0] else: return sign + '*'.join(a_str) + "/(%s)" % '*'.join(b_str)
def _parallel_dict_from_expr_if_gens(exprs, opt): """Transform expressions into a multinomial form given generators. """ k, indices = len(opt.gens), {} for i, g in enumerate(opt.gens): indices[g] = i polys = [] for expr in exprs: poly = {} if expr.is_Equality: expr = expr.lhs - expr.rhs for term in Add.make_args(expr): coeff, monom = [], [0] * k for factor in Mul.make_args(term): if not _not_a_coeff(factor) and factor.is_Number: coeff.append(factor) else: try: base, exp = decompose_power(factor) if exp < 0: exp, base = -exp, Pow(base, -S.One) monom[indices[base]] += exp except KeyError: if not factor.free_symbols.intersection(opt.gens): coeff.append(factor) else: raise PolynomialError( "%s contains an element of the generators set" % factor) monom = tuple(monom) if monom in poly: poly[monom] += Mul(*coeff) else: poly[monom] = Mul(*coeff) polys.append(poly) return polys, opt.gens
def update(b): '''Decide what to do with base, b. If its exponent is now an integer multiple of the Rational denominator, then remove it and put the factors of its base in the common_b dictionary or update the existing bases if necessary. If it has been zeroed out, simply remove the base. ''' newe, r = divmod(common_b[b], b[1]) if not r: common_b.pop(b) if newe: for m in Mul.make_args(b[0]**newe): b, e = bkey(m) if b not in common_b: common_b[b] = 0 common_b[b] += e if b[1] != 1: bases.append(b)
def mrv(e, x): """ Calculate the MRV set of expression. Examples ======== >>> from diofant import Symbol, exp, log >>> x = Symbol('x', real=True, positive=True) >>> mrv(log(x - log(x))/log(x), x) {x} >>> mrv(exp(x + exp(-x)), x) {E**(-x), E**(x + E**(-x))} """ if not e.has(x): return set() elif e == x: return {x} elif e.is_Mul or e.is_Add: a, b = e.as_two_terms() return mrv_max(mrv(a, x), mrv(b, x), x) elif e.is_Pow: if e.base is S.Exp1: if e.exp == x: return {e} elif any(a.is_infinite for a in Mul.make_args(limitinf(e.exp, x))): return mrv_max({e}, mrv(e.exp, x), x) else: return mrv(e.exp, x) else: assert not e.exp.has(x) return mrv(e.base, x) elif e.func is log: return mrv(e.args[0], x) elif e.is_Function: return reduce(lambda a, b: mrv_max(a, b, x), [mrv(a, x) for a in e.args]) else: raise NotImplementedError( "Don't know how to calculate the mrv of '%s'" % e)
def repl(nu, z): if factors.intersection(Mul.make_args(z)): return to(nu, z) return fro(nu, z)
def _denest_pow(eq): """ Denest powers. This is a helper function for powdenest that performs the actual transformation. """ from diofant.simplify.simplify import logcombine b, e = eq.as_base_exp() if b.is_Pow and e != 1: new = b._eval_power(e) if new is not None: eq = new b, e = new.as_base_exp() # denest exp with log terms in exponent if b is S.Exp1 and e.is_Mul: logs = [] other = [] for ei in e.args: if any(ai.func is log for ai in Add.make_args(ei)): logs.append(ei) else: other.append(ei) logs = logcombine(Mul(*logs)) return Pow(exp(logs), Mul(*other)) _, be = b.as_base_exp() if be is S.One and not (b.is_Mul or b.is_Rational and b.q != 1 or b.is_positive): return eq # denest eq which is either pos**e or Pow**e or Mul**e or # Mul(b1**e1, b2**e2) # handle polar numbers specially polars, nonpolars = [], [] for bb in Mul.make_args(b): if bb.is_polar: polars.append(bb.as_base_exp()) else: nonpolars.append(bb) if len(polars) == 1 and not polars[0][0].is_Mul: return Pow(polars[0][0], polars[0][1] * e) * powdenest( Mul(*nonpolars)**e) elif polars: return Mul(*[powdenest(bb**(ee*e)) for (bb, ee) in polars]) \ * powdenest(Mul(*nonpolars)**e) if b.is_Integer: # use log to see if there is a power here logb = expand_log(log(b)) if logb.is_Mul: c, logb = logb.args e *= c base = logb.args[0] return Pow(base, e) # if b is not a Mul or any factor is an atom then there is nothing to do if not b.is_Mul or any(s.is_Atom for s in Mul.make_args(b)): return eq # let log handle the case of the base of the argument being a Mul, e.g. # sqrt(x**(2*i)*y**(6*i)) -> x**i*y**(3**i) if x and y are positive; we # will take the log, expand it, and then factor out the common powers that # now appear as coefficient. We do this manually since terms_gcd pulls out # fractions, terms_gcd(x+x*y/2) -> x*(y + 2)/2 and we don't want the 1/2; # gcd won't pull out numerators from a fraction: gcd(3*x, 9*x/2) -> x but # we want 3*x. Neither work with noncommutatives. def nc_gcd(aa, bb): a, b = [i.as_coeff_Mul() for i in [aa, bb]] c = gcd(a[0], b[0]).as_numer_denom()[0] g = Mul(*(a[1].args_cnc(cset=True)[0] & b[1].args_cnc(cset=True)[0])) return _keep_coeff(c, g) glogb = expand_log(log(b)) if glogb.is_Add: args = glogb.args g = reduce(nc_gcd, args) if g != 1: cg, rg = g.as_coeff_Mul() glogb = _keep_coeff(cg, rg * Add(*[a / g for a in args])) # now put the log back together again if glogb.func is log or not glogb.is_Mul: if glogb.args[0].is_Pow: glogb = _denest_pow(glogb.args[0]) if (abs(glogb.exp) < 1) is S.true: return Pow(glogb.base, glogb.exp * e) return eq # the log(b) was a Mul so join any adds with logcombine add = [] other = [] for a in glogb.args: if a.is_Add: add.append(a) else: other.append(a) return Pow(exp(logcombine(Mul(*add))), e * Mul(*other))
def powsimp(expr, deep=False, combine='all', force=False, measure=count_ops): """ reduces expression by combining powers with similar bases and exponents. Notes ===== If deep is True then powsimp() will also simplify arguments of functions. By default deep is set to False. If force is True then bases will be combined without checking for assumptions, e.g. sqrt(x)*sqrt(y) -> sqrt(x*y) which is not true if x and y are both negative. You can make powsimp() only combine bases or only combine exponents by changing combine='base' or combine='exp'. By default, combine='all', which does both. combine='base' will only combine:: a a a 2x x x * y => (x*y) as well as things like 2 => 4 and combine='exp' will only combine :: a b (a + b) x * x => x combine='exp' will strictly only combine exponents in the way that used to be automatic. Also use deep=True if you need the old behavior. When combine='all', 'exp' is evaluated first. Consider the first example below for when there could be an ambiguity relating to this. This is done so things like the second example can be completely combined. If you want 'base' combined first, do something like powsimp(powsimp(expr, combine='base'), combine='exp'). Examples ======== >>> from diofant import powsimp, exp, log, symbols >>> from diofant.abc import x, y, z, n >>> powsimp(x**y*x**z*y**z, combine='all') x**(y + z)*y**z >>> powsimp(x**y*x**z*y**z, combine='exp') x**(y + z)*y**z >>> powsimp(x**y*x**z*y**z, combine='base', force=True) x**y*(x*y)**z >>> powsimp(x**z*x**y*n**z*n**y, combine='all', force=True) (n*x)**(y + z) >>> powsimp(x**z*x**y*n**z*n**y, combine='exp') n**(y + z)*x**(y + z) >>> powsimp(x**z*x**y*n**z*n**y, combine='base', force=True) (n*x)**y*(n*x)**z >>> x, y = symbols('x y', positive=True) >>> powsimp(log(exp(x)*exp(y))) log(E**x*E**y) >>> powsimp(log(exp(x)*exp(y)), deep=True) x + y Radicals with Mul bases will be combined if combine='exp' >>> from diofant import sqrt, Mul >>> x, y = symbols('x y') Two radicals are automatically joined through Mul: >>> a=sqrt(x*sqrt(y)) >>> a*a**3 == a**4 True But if an integer power of that radical has been autoexpanded then Mul does not join the resulting factors: >>> a**4 # auto expands to a Mul, no longer a Pow x**2*y >>> _*a # so Mul doesn't combine them x**2*y*sqrt(x*sqrt(y)) >>> powsimp(_) # but powsimp will (x*sqrt(y))**(5/2) >>> powsimp(x*y*a) # but won't when doing so would violate assumptions x*y*sqrt(x*sqrt(y)) """ from diofant.matrices.expressions.matexpr import MatrixSymbol def recurse(arg, **kwargs): _deep = kwargs.get('deep', deep) _combine = kwargs.get('combine', combine) _force = kwargs.get('force', force) _measure = kwargs.get('measure', measure) return powsimp(arg, _deep, _combine, _force, _measure) expr = sympify(expr) if (not isinstance(expr, Basic) or isinstance(expr, MatrixSymbol) or (expr.is_Atom or expr in (exp_polar(0), exp_polar(1)))): return expr if deep or expr.is_Add or expr.is_Mul and _y not in expr.args: expr = expr.func(*[recurse(w) for w in expr.args]) if expr.is_Pow: return recurse(expr * _y, deep=False) / _y if not expr.is_Mul: return expr # handle the Mul if combine in ('exp', 'all'): # Collect base/exp data, while maintaining order in the # non-commutative parts of the product c_powers = defaultdict(list) nc_part = [] newexpr = [] coeff = S.One for term in expr.args: if term.is_Rational: coeff *= term continue if term.is_Pow: term = _denest_pow(term) if term.is_commutative: b, e = term.as_base_exp() if deep: b, e = [recurse(i) for i in [b, e]] if b.is_Pow: # don't let smthg like sqrt(x**a) split into x**a, 1/2 # or else it will be joined as x**(a/2) later b, e = b**e, S.One c_powers[b].append(e) else: # This is the logic that combines exponents for equal, # but non-commutative bases: A**x*A**y == A**(x+y). if nc_part: b1, e1 = nc_part[-1].as_base_exp() b2, e2 = term.as_base_exp() if (b1 == b2 and e1.is_commutative and e2.is_commutative): nc_part[-1] = Pow(b1, Add(e1, e2)) continue nc_part.append(term) # add up exponents of common bases for b, e in ordered(iter(c_powers.items())): # allow 2**x/4 -> 2**(x - 2); don't do this when b and e are # Numbers since autoevaluation will undo it, e.g. # 2**(1/3)/4 -> 2**(1/3 - 2) -> 2**(1/3)/4 if (b and b.is_Number and not all(ei.is_Number for ei in e) and coeff is not S.One and b not in (S.One, S.NegativeOne)): m = multiplicity(abs(b), abs(coeff)) if m: e.append(m) coeff /= b**m c_powers[b] = Add(*e) if coeff is not S.One: if coeff in c_powers: c_powers[coeff] += S.One else: c_powers[coeff] = S.One # convert to plain dictionary c_powers = dict(c_powers) # check for base and inverted base pairs be = list(c_powers.items()) skip = set() # skip if we already saw them for b, e in be: if b in skip: continue bpos = b.is_positive or b.is_polar if bpos: binv = 1 / b if b != binv and binv in c_powers: if b.as_numer_denom()[0] is S.One: c_powers.pop(b) c_powers[binv] -= e else: skip.add(binv) e = c_powers.pop(binv) c_powers[b] -= e # check for base and negated base pairs be = list(c_powers.items()) _n = S.NegativeOne for i, (b, e) in enumerate(be): if ((-b).is_Symbol or b.is_Add) and -b in c_powers: if (b.is_positive in (0, 1) or e.is_integer): c_powers[-b] += c_powers.pop(b) if _n in c_powers: c_powers[_n] += e else: c_powers[_n] = e # filter c_powers and convert to a list c_powers = [(b, e) for b, e in c_powers.items() if e] # ============================================================== # check for Mul bases of Rational powers that can be combined with # separated bases, e.g. x*sqrt(x*y)*sqrt(x*sqrt(x*y)) -> # (x*sqrt(x*y))**(3/2) # ---------------- helper functions def ratq(x): '''Return Rational part of x's exponent as it appears in the bkey. ''' return bkey(x)[0][1] def bkey(b, e=None): '''Return (b**s, c.q), c.p where e -> c*s. If e is not given then it will be taken by using as_base_exp() on the input b. e.g. x**3/2 -> (x, 2), 3 x**y -> (x**y, 1), 1 x**(2*y/3) -> (x**y, 3), 2 exp(x/2) -> (exp(a), 2), 1 ''' if e is not None: # coming from c_powers or from below if e.is_Integer: return (b, S.One), e elif e.is_Rational: return (b, Integer(e.q)), Integer(e.p) else: c, m = e.as_coeff_Mul(rational=True) if c is not S.One and b.is_positive: return (b**m, Integer(c.q)), Integer(c.p) else: return (b**e, S.One), S.One else: return bkey(*b.as_base_exp()) def update(b): '''Decide what to do with base, b. If its exponent is now an integer multiple of the Rational denominator, then remove it and put the factors of its base in the common_b dictionary or update the existing bases if necessary. If it has been zeroed out, simply remove the base. ''' newe, r = divmod(common_b[b], b[1]) if not r: common_b.pop(b) if newe: for m in Mul.make_args(b[0]**newe): b, e = bkey(m) if b not in common_b: common_b[b] = 0 common_b[b] += e if b[1] != 1: bases.append(b) # ---------------- end of helper functions # assemble a dictionary of the factors having a Rational power common_b = {} done = [] bases = [] for b, e in c_powers: b, e = bkey(b, e) if b in common_b.keys(): common_b[b] = common_b[b] + e else: common_b[b] = e if b[1] != 1 and b[0].is_Mul: bases.append(b) c_powers = [(b, e) for b, e in common_b.items() if e] bases.sort(key=default_sort_key) # this makes tie-breaking canonical bases.sort(key=measure, reverse=True) # handle longest first for base in bases: if base not in common_b: # it may have been removed already continue b, exponent = base last = False # True when no factor of base is a radical qlcm = 1 # the lcm of the radical denominators while True: bstart = b qstart = qlcm bb = [] # list of factors ee = [] # (factor's expo. and it's current value in common_b) for bi in Mul.make_args(b): bib, bie = bkey(bi) if bib not in common_b or common_b[bib] < bie: ee = bb = [] # failed break ee.append([bie, common_b[bib]]) bb.append(bib) if ee: # find the number of extractions possible # e.g. [(1, 2), (2, 2)] -> min(2/1, 2/2) -> 1 min1 = ee[0][1] / ee[0][0] for i in range(len(ee)): rat = ee[i][1] / ee[i][0] if rat < 1: break min1 = min(min1, rat) else: # update base factor counts # e.g. if ee = [(2, 5), (3, 6)] then min1 = 2 # and the new base counts will be 5-2*2 and 6-2*3 for i in range(len(bb)): common_b[bb[i]] -= min1 * ee[i][0] update(bb[i]) # update the count of the base # e.g. x**2*y*sqrt(x*sqrt(y)) the count of x*sqrt(y) # will increase by 4 to give bkey (x*sqrt(y), 2, 5) common_b[base] += min1 * qstart * exponent if (last # no more radicals in base or len(common_b) == 1 # nothing left to join with or all(k[1] == 1 for k in common_b) # no rad's in common_b ): break # see what we can exponentiate base by to remove any radicals # so we know what to search for # e.g. if base were x**(1/2)*y**(1/3) then we should # exponentiate by 6 and look for powers of x and y in the ratio # of 2 to 3 qlcm = lcm([ratq(bi) for bi in Mul.make_args(bstart)]) if qlcm == 1: break # we are done b = bstart**qlcm qlcm *= qstart if all(ratq(bi) == 1 for bi in Mul.make_args(b)): last = True # we are going to be done after this next pass # this base no longer can find anything to join with and # since it was longer than any other we are done with it b, q = base done.append((b, common_b.pop(base) * Rational(1, q))) # update c_powers and get ready to continue with powsimp c_powers = done # there may be terms still in common_b that were bases that were # identified as needing processing, so remove those, too for (b, q), e in common_b.items(): if b.is_Pow and q is not S.One and not b.exp.is_Rational: b, be = b.as_base_exp() b = b**(be / q) else: b = root(b, q) c_powers.append((b, e)) check = len(c_powers) c_powers = dict(c_powers) assert len(c_powers) == check # there should have been no duplicates # ============================================================== # rebuild the expression newexpr = expr.func(*(newexpr + [Pow(b, e) for b, e in c_powers.items()])) if combine == 'exp': return expr.func(newexpr, expr.func(*nc_part)) else: return recurse(expr.func(*nc_part), combine='base') * \ recurse(newexpr, combine='base') elif combine == 'base': # Build c_powers and nc_part. These must both be lists not # dicts because exp's are not combined. c_powers = [] nc_part = [] for term in expr.args: if term.is_commutative: c_powers.append(list(term.as_base_exp())) else: # This is the logic that combines bases that are # different and non-commutative, but with equal and # commutative exponents: A**x*B**x == (A*B)**x. if nc_part: b1, e1 = nc_part[-1].as_base_exp() b2, e2 = term.as_base_exp() if (e1 == e2 and e2.is_commutative): nc_part[-1] = Pow(b1 * b2, e1) continue nc_part.append(term) # Pull out numerical coefficients from exponent if assumptions allow # e.g., 2**(2*x) => 4**x for i in range(len(c_powers)): b, e = c_powers[i] if not (all(x.is_nonnegative for x in b.as_numer_denom()) or e.is_integer or force or b.is_polar): continue exp_c, exp_t = e.as_coeff_Mul(rational=True) if exp_c is not S.One and exp_t is not S.One: c_powers[i] = [Pow(b, exp_c), exp_t] # Combine bases whenever they have the same exponent and # assumptions allow # first gather the potential bases under the common exponent c_exp = defaultdict(list) for b, e in c_powers: if deep: e = recurse(e) c_exp[e].append(b) del c_powers # Merge back in the results of the above to form a new product c_powers = defaultdict(list) for e in c_exp: bases = c_exp[e] # calculate the new base for e if len(bases) == 1: new_base = bases[0] elif e.is_integer or force: new_base = expr.func(*bases) else: # see which ones can be joined unk = [] nonneg = [] neg = [] for bi in bases: if bi.is_negative: neg.append(bi) elif bi.is_nonnegative: nonneg.append(bi) elif bi.is_polar: nonneg.append( bi) # polar can be treated like non-negative else: unk.append(bi) if len(unk) == 1 and not neg or len(neg) == 1 and not unk: # a single neg or a single unk can join the rest nonneg.extend(unk + neg) unk = neg = [] elif neg: # their negative signs cancel in groups of 2*q if we know # that e = p/q else we have to treat them as unknown israt = False if e.is_Rational: israt = True else: p, d = e.as_numer_denom() if p.is_integer and d.is_integer: israt = True if israt: neg = [-w for w in neg] unk.extend([S.NegativeOne] * len(neg)) else: unk.extend(neg) neg = [] del israt # these shouldn't be joined for b in unk: c_powers[b].append(e) # here is a new joined base new_base = expr.func(*(nonneg + neg)) # if there are positive parts they will just get separated # again unless some change is made def _terms(e): # return the number of terms of this expression # when multiplied out -- assuming no joining of terms if e.is_Add: return sum(_terms(ai) for ai in e.args) if e.is_Mul: return prod([_terms(mi) for mi in e.args]) return 1 xnew_base = expand_mul(new_base, deep=False) if len(Add.make_args(xnew_base)) < _terms(new_base): new_base = factor_terms(xnew_base) c_powers[new_base].append(e) # break out the powers from c_powers now c_part = [Pow(b, ei) for b, e in c_powers.items() for ei in e] # we're done return expr.func(*(c_part + nc_part)) else: raise ValueError("combine must be one of ('all', 'exp', 'base').")
def _parallel_dict_from_expr_no_gens(exprs, opt): """Transform expressions into a multinomial form and figure out generators. """ if opt.domain is not None: def _is_coeff(factor): return factor in opt.domain elif opt.extension is True: def _is_coeff(factor): return factor.is_algebraic elif opt.greedy is not False: def _is_coeff(factor): return False else: def _is_coeff(factor): return factor.is_number gens, reprs = set(), [] for expr in exprs: terms = [] if expr.is_Equality: expr = expr.lhs - expr.rhs for term in Add.make_args(expr): coeff, elements = [], defaultdict(int) for factor in Mul.make_args(term): if not _not_a_coeff(factor) and (factor.is_Number or _is_coeff(factor)): coeff.append(factor) else: base, exp = decompose_power(factor) if exp < 0: exp, base = -exp, Pow(base, -S.One) elements[base] += exp gens.add(base) terms.append((coeff, elements)) reprs.append(terms) if not gens: if len(exprs) == 1: arg = exprs[0] else: arg = (exprs, ) raise GeneratorsNeeded("specify generators to give %s a meaning" % arg) gens = _sort_gens(gens, opt=opt) k, indices = len(gens), {} for i, g in enumerate(gens): indices[g] = i polys = [] for terms in reprs: poly = {} for coeff, term in terms: monom = [0] * k for base, exp in term.items(): monom[indices[base]] = exp monom = tuple(monom) if monom in poly: poly[monom] += Mul(*coeff) else: poly[monom] = Mul(*coeff) polys.append(poly) return polys, tuple(gens)
def __new__(cls, expr, *args, **kwargs): expr = sympify(expr) if not args: if expr.is_Order: variables = expr.variables point = expr.point else: variables = list(expr.free_symbols) point = [S.Zero]*len(variables) else: args = list(args if is_sequence(args) else [args]) variables, point = [], [] if is_sequence(args[0]): for a in args: v, p = list(map(sympify, a)) variables.append(v) point.append(p) else: variables = list(map(sympify, args)) point = [S.Zero]*len(variables) if not all(isinstance(v, (Dummy, Symbol)) for v in variables): raise TypeError('Variables are not symbols, got %s' % variables) if len(list(uniq(variables))) != len(variables): raise ValueError('Variables are supposed to be unique symbols, got %s' % variables) if expr.is_Order: expr_vp = dict(expr.args[1:]) new_vp = dict(expr_vp) vp = dict(zip(variables, point)) for v, p in vp.items(): if v in new_vp.keys(): if p != new_vp[v]: raise NotImplementedError( "Mixing Order at different points is not supported.") else: new_vp[v] = p if set(expr_vp.keys()) == set(new_vp.keys()): return expr else: variables = list(new_vp.keys()) point = [new_vp[v] for v in variables] if expr is S.NaN: return S.NaN if any(x in p.free_symbols for x in variables for p in point): raise ValueError('Got %s as a point.' % point) if variables: if any(p != point[0] for p in point): raise NotImplementedError if point[0] in [S.Infinity, S.NegativeInfinity]: s = {k: 1/Dummy() for k in variables} rs = {1/v: 1/k for k, v in s.items()} elif point[0] is not S.Zero: s = {k: Dummy() + point[0] for k in variables} rs = {v - point[0]: k - point[0] for k, v in s.items()} else: s = () rs = () expr = expr.subs(s) if expr.is_Add: from diofant import expand_multinomial expr = expand_multinomial(expr) if s: args = tuple(r[0] for r in rs.items()) else: args = tuple(variables) if len(variables) > 1: # XXX: better way? We need this expand() to # workaround e.g: expr = x*(x + y). # (x*(x + y)).as_leading_term(x, y) currently returns # x*y (wrong order term!). That's why we want to deal with # expand()'ed expr (handled in "if expr.is_Add" branch below). expr = expr.expand() if expr.is_Add: lst = expr.extract_leading_order(args) expr = Add(*[f.expr for (e, f) in lst]) elif expr: expr = expr.as_leading_term(*args) expr = expr.as_independent(*args, as_Add=False)[1] expr = expand_power_base(expr) expr = expand_log(expr) if len(args) == 1: # The definition of O(f(x)) symbol explicitly stated that # the argument of f(x) is irrelevant. That's why we can # combine some power exponents (only "on top" of the # expression tree for f(x)), e.g.: # x**p * (-x)**q -> x**(p+q) for real p, q. x = args[0] margs = list(Mul.make_args( expr.as_independent(x, as_Add=False)[1])) for i, t in enumerate(margs): if t.is_Pow: b, q = t.args if b in (x, -x) and q.is_extended_real and not q.has(x): margs[i] = x**q elif b.is_Pow and not b.exp.has(x): b, r = b.args if b in (x, -x) and r.is_extended_real: margs[i] = x**(r*q) elif b.is_Mul and b.args[0] is S.NegativeOne: b = -b if b.is_Pow and not b.exp.has(x): b, r = b.args if b in (x, -x) and r.is_extended_real: margs[i] = x**(r*q) expr = Mul(*margs) expr = expr.subs(rs) if expr is S.Zero: return expr if expr.is_Order: expr = expr.expr if not expr.has(*variables): expr = S.One # create Order instance: vp = dict(zip(variables, point)) variables.sort(key=default_sort_key) point = [vp[v] for v in variables] args = (expr,) + Tuple(*zip(variables, point)) obj = Expr.__new__(cls, *args) return obj
def fraction(expr, exact=False): """Returns a pair with expression's numerator and denominator. If the given expression is not a fraction then this function will return the tuple (expr, 1). This function will not make any attempt to simplify nested fractions or to do any term rewriting at all. If only one of the numerator/denominator pair is needed then use numer(expr) or denom(expr) functions respectively. >>> from diofant import fraction, Rational, Symbol >>> from diofant.abc import x, y >>> fraction(x/y) (x, y) >>> fraction(x) (x, 1) >>> fraction(1/y**2) (1, y**2) >>> fraction(x*y/2) (x*y, 2) >>> fraction(Rational(1, 2)) (1, 2) This function will also work fine with assumptions: >>> k = Symbol('k', negative=True) >>> fraction(x * y**k) (x, y**(-k)) If we know nothing about sign of some exponent and 'exact' flag is unset, then structure this exponent's structure will be analyzed and pretty fraction will be returned: >>> from diofant import exp >>> fraction(2*x**(-y)) (2, x**y) >>> fraction(exp(-x)) (1, E**x) >>> fraction(exp(-x), exact=True) (E**(-x), 1) """ expr = sympify(expr) numer, denom = [], [] for term in Mul.make_args(expr): if term.is_commutative and term.is_Pow: b, ex = term.as_base_exp() if ex.is_negative: if ex is S.NegativeOne: denom.append(b) else: denom.append(Pow(b, -ex)) elif ex.is_positive: numer.append(term) elif not exact and ex.is_Mul: n, d = term.as_numer_denom() numer.append(n) denom.append(d) else: numer.append(term) elif term.is_Rational: n, d = term.as_numer_denom() numer.append(n) denom.append(d) else: numer.append(term) return Mul(*numer), Mul(*denom)
def handle(expr): # Handle first reduces to the case # expr = 1/d, where d is an add, or d is base**p/2. # We do this by recursively calling handle on each piece. from diofant.simplify.simplify import nsimplify n, d = fraction(expr) if expr.is_Atom or (d.is_Atom and n.is_Atom): return expr elif not n.is_Atom: n = n.func(*[handle(a) for a in n.args]) return _unevaluated_Mul(n, handle(1 / d)) elif n is not S.One: return _unevaluated_Mul(n, handle(1 / d)) elif d.is_Mul: return _unevaluated_Mul(*[handle(1 / d) for d in d.args]) # By this step, expr is 1/d, and d is not a mul. if not symbolic and d.free_symbols: return expr if ispow2(d): d2 = sqrtdenest(sqrt(d.base))**fraction(d.exp)[0] if d2 != d: return handle(1 / d2) elif d.is_Pow and (d.exp.is_integer or d.base.is_positive): # (1/d**i) = (1/d)**i return handle(1 / d.base)**d.exp if not (d.is_Add or ispow2(d)): return 1 / d.func(*[handle(a) for a in d.args]) # handle 1/d treating d as an Add (though it may not be) keep = True # keep changes that are made # flatten it and collect radicals after checking for special # conditions d = _mexpand(d) # did it change? if d.is_Atom: return 1 / d # is it a number that might be handled easily? if d.is_number: _d = nsimplify(d) if _d.is_Number and _d.equals(d): return 1 / _d while True: # collect similar terms collected = defaultdict(list) for m in Add.make_args(d): # d might have become non-Add p2 = [] other = [] for i in Mul.make_args(m): if ispow2(i, log2=True): p2.append(i.base if i.exp is S.Half else i.base**( 2 * i.exp)) elif i is S.ImaginaryUnit: p2.append(S.NegativeOne) else: other.append(i) collected[tuple(ordered(p2))].append(Mul(*other)) rterms = list(ordered(list(collected.items()))) rterms = [(Mul(*i), Add(*j)) for i, j in rterms] nrad = len(rterms) - (1 if rterms[0][0] is S.One else 0) if nrad < 1: break elif nrad > max_terms: # there may have been invalid operations leading to this point # so don't keep changes, e.g. this expression is troublesome # in collecting terms so as not to raise the issue of 2834: # r = sqrt(sqrt(5) + 5) # eq = 1/(sqrt(5)*r + 2*sqrt(5)*sqrt(-sqrt(5) + 5) + 5*r) keep = False break if len(rterms) > 4: # in general, only 4 terms can be removed with repeated squaring # but other considerations can guide selection of radical terms # so that radicals are removed if all( [x.is_Integer and (y**2).is_Rational for x, y in rterms]): nd, d = rad_rationalize( S.One, Add._from_args([sqrt(x) * y for x, y in rterms])) n *= nd else: # is there anything else that might be attempted? keep = False break from diofant.simplify.powsimp import powsimp, powdenest num = powsimp(_num(rterms)) n *= num d *= num d = powdenest(_mexpand(d), force=symbolic) if d.is_Atom: break if not keep: return expr return _unevaluated_Mul(n, 1 / d)
def collect_const(expr, *vars, **kwargs): """A non-greedy collection of terms with similar number coefficients in an Add expr. If ``vars`` is given then only those constants will be targeted. Although any Number can also be targeted, if this is not desired set ``Numbers=False`` and no Float or Rational will be collected. Examples ======== >>> from diofant import sqrt >>> from diofant.abc import a, s, x, y, z >>> from diofant.simplify.radsimp import collect_const >>> collect_const(sqrt(3) + sqrt(3)*(1 + sqrt(2))) sqrt(3)*(sqrt(2) + 2) >>> collect_const(sqrt(3)*s + sqrt(7)*s + sqrt(3) + sqrt(7)) (sqrt(3) + sqrt(7))*(s + 1) >>> s = sqrt(2) + 2 >>> collect_const(sqrt(3)*s + sqrt(3) + sqrt(7)*s + sqrt(7)) (sqrt(2) + 3)*(sqrt(3) + sqrt(7)) >>> collect_const(sqrt(3)*s + sqrt(3) + sqrt(7)*s + sqrt(7), sqrt(3)) sqrt(7) + sqrt(3)*(sqrt(2) + 3) + sqrt(7)*(sqrt(2) + 2) The collection is sign-sensitive, giving higher precedence to the unsigned values: >>> collect_const(x - y - z) x - (y + z) >>> collect_const(-y - z) -(y + z) >>> collect_const(2*x - 2*y - 2*z, 2) 2*(x - y - z) >>> collect_const(2*x - 2*y - 2*z, -2) 2*x - 2*(y + z) See Also ======== collect, collect_sqrt, rcollect """ if not expr.is_Add: return expr recurse = False Numbers = kwargs.get('Numbers', True) if not vars: recurse = True vars = set() for a in expr.args: for m in Mul.make_args(a): if m.is_number: vars.add(m) else: vars = sympify(vars) if not Numbers: vars = [v for v in vars if not v.is_Number] vars = list(ordered(vars)) for v in vars: terms = defaultdict(list) Fv = Factors(v) for m in Add.make_args(expr): f = Factors(m) q, r = f.div(Fv) if r.is_one: # only accept this as a true factor if # it didn't change an exponent from an Integer # to a non-Integer, e.g. 2/sqrt(2) -> sqrt(2) # -- we aren't looking for this sort of change fwas = f.factors.copy() fnow = q.factors if not any(k in fwas and fwas[k].is_Integer and not fnow[k].is_Integer for k in fnow): terms[v].append(q.as_expr()) continue terms[S.One].append(m) args = [] hit = False uneval = False for k in ordered(terms): v = terms[k] if k is S.One: args.extend(v) continue if len(v) > 1: v = Add(*v) hit = True if recurse and v != expr: vars.append(v) else: v = v[0] # be careful not to let uneval become True unless # it must be because it's going to be more expensive # to rebuild the expression as an unevaluated one if Numbers and k.is_Number and v.is_Add: args.append(_keep_coeff(k, v, sign=True)) uneval = True else: args.append(k * v) if hit: if uneval: expr = _unevaluated_Add(*args) else: expr = Add(*args) if not expr.is_Add: break return expr
def parse_expression(terms, pattern): """Parse terms searching for a pattern. terms is a list of tuples as returned by parse_terms; pattern is an expression treated as a product of factors """ pattern = Mul.make_args(pattern) if len(terms) < len(pattern): # pattern is longer than matched product # so no chance for positive parsing result return else: pattern = [parse_term(elem) for elem in pattern] terms = terms[:] # need a copy elems, common_expo, has_deriv = [], None, False for elem, e_rat, e_sym, e_ord in pattern: if elem.is_Number and e_rat == 1 and e_sym is None: # a constant is a match for everything continue for j in range(len(terms)): if terms[j] is None: continue term, t_rat, t_sym, t_ord = terms[j] # keeping track of whether one of the terms had # a derivative or not as this will require rebuilding # the expression later if t_ord is not None: has_deriv = True if (term.match(elem) is not None and (t_sym == e_sym or t_sym is not None and e_sym is not None and t_sym.match(e_sym) is not None)): if exact is False: # we don't have to be exact so find common exponent # for both expression's term and pattern's element expo = t_rat / e_rat if common_expo is None: # first time common_expo = expo else: # common exponent was negotiated before so # there is no chance for a pattern match unless # common and current exponents are equal if common_expo != expo: common_expo = 1 else: # we ought to be exact so all fields of # interest must match in every details if e_rat != t_rat or e_ord != t_ord: continue # found common term so remove it from the expression # and try to match next element in the pattern elems.append(terms[j]) terms[j] = None break else: # pattern element not found return return [_f for _f in terms if _f], elems, common_expo, has_deriv
def collect(expr, syms, func=None, evaluate=True, exact=False, distribute_order_term=True): """Collect additive terms of an expression. This function collects additive terms of an expression with respect to a list of expression up to powers with rational exponents. By the term symbol here are meant arbitrary expressions, which can contain powers, products, sums etc. In other words symbol is a pattern which will be searched for in the expression's terms. The input expression is not expanded by :func:`collect`, so user is expected to provide an expression is an appropriate form (for example, by using :func:`~diofant.core.function.expand` prior to calling this function). This makes :func:`collect` more predictable as there is no magic happening behind the scenes. However, it is important to note, that powers of products are converted to products of powers using the :func:`~diofant.core.function.expand_power_base` function. Parameters ========== expr : Expr an expression syms : iterable of Symbol's collected symbols evaluate : boolean First, if ``evaluate`` flag is set (by default), this function will return an expression with collected terms else it will return a dictionary with expressions up to rational powers as keys and collected coefficients as values. Examples ======== >>> from diofant import collect, expand, factor >>> from diofant.abc import a, b, c, x, y This function can collect symbolic coefficients in polynomials or rational expressions. It will manage to find all integer or rational powers of collection variable: >>> collect(a*x**2 + b*x**2 + a*x - b*x + c, x) c + x**2*(a + b) + x*(a - b) The same result can be achieved in dictionary form: >>> d = collect(a*x**2 + b*x**2 + a*x - b*x + c, x, evaluate=False) >>> d[x**2] a + b >>> d[x] a - b >>> d[1] c You can also work with multivariate polynomials. However, remember that this function is greedy so it will care only about a single symbol at time, in specification order: >>> collect(x**2 + y*x**2 + x*y + y + a*y, [x, y]) x**2*(y + 1) + x*y + y*(a + 1) Also more complicated expressions can be used as patterns: >>> from diofant import sin, log >>> collect(a*sin(2*x) + b*sin(2*x), sin(2*x)) (a + b)*sin(2*x) >>> collect(a*x*log(x) + b*(x*log(x)), x*log(x)) x*(a + b)*log(x) You can use wildcards in the pattern: >>> from diofant import Wild >>> w = Wild('w1') >>> collect(a*x**y - b*x**y, w**y) x**y*(a - b) It is also possible to work with symbolic powers, although it has more complicated behavior, because in this case power's base and symbolic part of the exponent are treated as a single symbol: >>> collect(a*x**c + b*x**c, x) a*x**c + b*x**c >>> collect(a*x**c + b*x**c, x**c) x**c*(a + b) However if you incorporate rationals to the exponents, then you will get well known behavior: >>> collect(a*x**(2*c) + b*x**(2*c), x**c) x**(2*c)*(a + b) Note also that all previously stated facts about :func:`collect` function apply to the exponential function, so you can get: >>> from diofant import exp >>> collect(a*exp(2*x) + b*exp(2*x), exp(x)) E**(2*x)*(a + b) If you are interested only in collecting specific powers of some symbols then set ``exact`` flag in arguments: >>> collect(a*x**7 + b*x**7, x, exact=True) a*x**7 + b*x**7 >>> collect(a*x**7 + b*x**7, x**7, exact=True) x**7*(a + b) You can also apply this function to differential equations, where derivatives of arbitrary order can be collected. Note that if you collect with respect to a function or a derivative of a function, all derivatives of that function will also be collected. Use ``exact=True`` to prevent this from happening: >>> from diofant import Derivative as D, Function >>> f = Function('f')(x) >>> collect(a*D(f,x) + b*D(f,x), D(f,x)) (a + b)*Derivative(f(x), x) >>> collect(a*D(D(f,x),x) + b*D(D(f,x),x), f) (a + b)*Derivative(f(x), x, x) >>> collect(a*D(D(f,x),x) + b*D(D(f,x),x), D(f,x), exact=True) a*Derivative(f(x), x, x) + b*Derivative(f(x), x, x) >>> collect(a*D(f,x) + b*D(f,x) + a*f + b*f, f) f(x)*(a + b) + (a + b)*Derivative(f(x), x) Or you can even match both derivative order and exponent at the same time: >>> collect(a*D(D(f,x),x)**2 + b*D(D(f,x),x)**2, D(f,x)) (a + b)*Derivative(f(x), x, x)**2 Finally, you can apply a function to each of the collected coefficients. For example you can factorize symbolic coefficients of polynomial: >>> f = expand((x + a + 1)**3) >>> collect(f, x, factor) x**3 + 3*x**2*(a + 1) + 3*x*(a + 1)**2 + (a + 1)**3 See Also ======== collect_const, collect_sqrt, rcollect """ def make_expression(terms): product = [] for term, rat, sym, deriv in terms: if deriv is not None: var, order = deriv while order > 0: term, order = Derivative(term, var), order - 1 if sym is None: if rat is S.One: product.append(term) else: product.append(Pow(term, rat)) else: product.append(Pow(term, rat * sym)) return Mul(*product) def parse_derivative(deriv): # scan derivatives tower in the input expression and return # underlying function and maximal differentiation order expr, sym, order = deriv.expr, deriv.variables[0], 1 for s in deriv.variables[1:]: if s == sym: order += 1 else: raise NotImplementedError( 'Improve MV Derivative support in collect') while isinstance(expr, Derivative): s0 = expr.variables[0] for s in expr.variables: if s != s0: raise NotImplementedError( 'Improve MV Derivative support in collect') if s0 == sym: expr, order = expr.expr, order + len(expr.variables) else: break return expr, (sym, Rational(order)) def parse_term(expr): """Parses expression expr and outputs tuple (sexpr, rat_expo, sym_expo, deriv) where: - sexpr is the base expression - rat_expo is the rational exponent that sexpr is raised to - sym_expo is the symbolic exponent that sexpr is raised to - deriv contains the derivatives the the expression for example, the output of x would be (x, 1, None, None) the output of 2**x would be (2, 1, x, None) """ rat_expo, sym_expo = S.One, None sexpr, deriv = expr, None if expr.is_Pow: if isinstance(expr.base, Derivative): sexpr, deriv = parse_derivative(expr.base) else: sexpr = expr.base if expr.exp.is_Number: rat_expo = expr.exp else: coeff, tail = expr.exp.as_coeff_Mul() if coeff.is_Number: rat_expo, sym_expo = coeff, tail else: sym_expo = expr.exp elif isinstance(expr, Derivative): sexpr, deriv = parse_derivative(expr) return sexpr, rat_expo, sym_expo, deriv def parse_expression(terms, pattern): """Parse terms searching for a pattern. terms is a list of tuples as returned by parse_terms; pattern is an expression treated as a product of factors """ pattern = Mul.make_args(pattern) if len(terms) < len(pattern): # pattern is longer than matched product # so no chance for positive parsing result return else: pattern = [parse_term(elem) for elem in pattern] terms = terms[:] # need a copy elems, common_expo, has_deriv = [], None, False for elem, e_rat, e_sym, e_ord in pattern: if elem.is_Number and e_rat == 1 and e_sym is None: # a constant is a match for everything continue for j in range(len(terms)): if terms[j] is None: continue term, t_rat, t_sym, t_ord = terms[j] # keeping track of whether one of the terms had # a derivative or not as this will require rebuilding # the expression later if t_ord is not None: has_deriv = True if (term.match(elem) is not None and (t_sym == e_sym or t_sym is not None and e_sym is not None and t_sym.match(e_sym) is not None)): if exact is False: # we don't have to be exact so find common exponent # for both expression's term and pattern's element expo = t_rat / e_rat if common_expo is None: # first time common_expo = expo else: # common exponent was negotiated before so # there is no chance for a pattern match unless # common and current exponents are equal if common_expo != expo: common_expo = 1 else: # we ought to be exact so all fields of # interest must match in every details if e_rat != t_rat or e_ord != t_ord: continue # found common term so remove it from the expression # and try to match next element in the pattern elems.append(terms[j]) terms[j] = None break else: # pattern element not found return return [_f for _f in terms if _f], elems, common_expo, has_deriv if evaluate: if expr.is_Mul: return expr.func(*[ collect(term, syms, func, True, exact, distribute_order_term) for term in expr.args ]) elif expr.is_Pow: b = collect(expr.base, syms, func, True, exact, distribute_order_term) return Pow(b, expr.exp) if iterable(syms): syms = [expand_power_base(i, deep=False) for i in syms] else: syms = [expand_power_base(syms, deep=False)] expr = sympify(expr) order_term = None if distribute_order_term: order_term = expr.getO() if order_term is not None: if order_term.has(*syms): order_term = None else: expr = expr.removeO() summa = [expand_power_base(i, deep=False) for i in Add.make_args(expr)] collected, disliked = defaultdict(list), S.Zero for product in summa: terms = [parse_term(i) for i in Mul.make_args(product)] for symbol in syms: if DIOFANT_DEBUG: print("DEBUG: parsing of expression %s with symbol %s " % (str(terms), str(symbol))) result = parse_expression(terms, symbol) if DIOFANT_DEBUG: print("DEBUG: returned %s" % str(result)) if result is not None: terms, elems, common_expo, has_deriv = result # when there was derivative in current pattern we # will need to rebuild its expression from scratch if not has_deriv: index = 1 for elem in elems: e = elem[1] if elem[2] is not None: e *= elem[2] index *= Pow(elem[0], e) else: index = make_expression(elems) terms = expand_power_base(make_expression(terms), deep=False) index = expand_power_base(index, deep=False) collected[index].append(terms) break else: # none of the patterns matched disliked += product # add terms now for each key collected = {k: Add(*v) for k, v in collected.items()} if disliked is not S.Zero: collected[S.One] = disliked if order_term is not None: for key, val in collected.items(): collected[key] = val + order_term if func is not None: collected = dict([(key, func(val)) for key, val in collected.items()]) if evaluate: return Add(*[key * val for key, val in collected.items()]) else: return collected