def __new__(cls, f, index):
if isinstance(f, RootsOf):
f = f.poly
elif not isinstance(f, Poly):
raise PolynomialError("%s is not a polynomial" % f)
if f.is_multivariate:
raise ValueError('multivariate polynomial')
if index < 0 or index >= f.degree():
raise IndexError("Index must be in [0, %d] range" % (f.degree()-1))
else:
exact = _exact_roots(f)
if index < len(exact):
return exact[index]
else:
index = sympify(index)
return Expr.__new__(cls, f, index)
def solve_reduced_system(system, entry=False):
"""Recursively solves reduced polynomial systems. """
basis = poly_groebner(system)
if len(basis) == 1 and basis[0].is_one:
if not entry:
return []
else:
return None
univariate = filter(is_univariate, basis)
if len(univariate) == 1:
f = univariate.pop()
else:
raise PolynomialError("Not a zero-dimensional system")
zeros = roots(Poly(f, f.symbols[-1])).keys()
if not zeros:
return []
if len(basis) == 1:
return [[zero] for zero in zeros]
solutions = []
for zero in zeros:
new_system = []
for poly in basis[:-1]:
eq = poly.evaluate((poly.symbols[-1], zero))
if not eq.is_zero:
new_system.append(eq)
for solution in solve_reduced_system(new_system):
solutions.append(solution + [zero])
return solutions
def reduce_rational_inequalities(exprs, gen, relational=True):
"""Reduce a system of rational inequalities with rational coefficients.
Examples
========
>>> from sympy import Poly, Symbol
>>> from sympy.solvers.inequalities import reduce_rational_inequalities
>>> x = Symbol('x', real=True)
>>> reduce_rational_inequalities([[x**2 <= 0]], x)
Eq(x, 0)
>>> reduce_rational_inequalities([[x + 2 > 0]], x)
(-2 < x) & (x < oo)
>>> reduce_rational_inequalities([[(x + 2, ">")]], x)
(-2 < x) & (x < oo)
>>> reduce_rational_inequalities([[x + 2]], x)
Eq(x, -2)
"""
exact = True
eqs = []
solution = S.Reals if exprs else S.EmptySet
for _exprs in exprs:
_eqs = []
for expr in _exprs:
if isinstance(expr, tuple):
expr, rel = expr
else:
if expr.is_Relational:
expr, rel = expr.lhs - expr.rhs, expr.rel_op
else:
expr, rel = expr, '=='
if expr is S.true:
numer, denom, rel = S.Zero, S.One, '=='
elif expr is S.false:
numer, denom, rel = S.One, S.One, '=='
else:
numer, denom = expr.together().as_numer_denom()
try:
(numer, denom), opt = parallel_poly_from_expr((numer, denom),
gen)
except PolynomialError:
raise PolynomialError(
filldedent('''
only polynomials and rational functions are
supported in this context.
'''))
if not opt.domain.is_Exact:
numer, denom, exact = numer.to_exact(), denom.to_exact(), False
domain = opt.domain.get_exact()
if not (domain.is_ZZ or domain.is_QQ):
expr = numer / denom
expr = Relational(expr, 0, rel)
solution &= solve_univariate_inequality(expr,
gen,
relational=False)
else:
_eqs.append(((numer, denom), rel))
if _eqs:
eqs.append(_eqs)
if eqs:
solution &= solve_rational_inequalities(eqs)
exclude = solve_rational_inequalities([[((d, d.one), '==') for i in eqs
for ((n, d), _) in i
if d.has(gen)]])
solution -= exclude
if not exact and solution:
solution = solution.evalf()
if relational:
solution = solution.as_relational(gen)
return solution
def roots(f, *gens, **flags):
"""Computes symbolic roots of a univariate polynomial.
Given a univariate polynomial f with symbolic coefficients (or
a list of the polynomial's coefficients), returns a dictionary
with its roots and their multiplicities.
Only roots expressible via radicals will be returned. To get
a complete set of roots use RootOf class or numerical methods
instead. By default cubic and quartic formulas are used in
the algorithm. To disable them because of unreadable output
set `cubics=False` or `quartics=False` respectively.
To get roots from a specific domain set the `filter` flag with
one of the following specifiers: Z, Q, R, I, C. By default all
roots are returned (this is equivalent to setting `filter='C'`).
By default a dictionary is returned giving a compact result in
case of multiple roots. However to get a tuple containing all
those roots set the `multiple` flag to True.
Examples
========
>>> from sympy import Poly, roots
>>> from sympy.abc import x, y
>>> roots(x**2 - 1, x)
{1: 1, -1: 1}
>>> p = Poly(x**2-1, x)
>>> roots(p)
{1: 1, -1: 1}
>>> p = Poly(x**2-y, x, y)
>>> roots(Poly(p, x))
{y**(1/2): 1, -y**(1/2): 1}
>>> roots(x**2 - y, x)
{y**(1/2): 1, -y**(1/2): 1}
>>> roots([1, 0, -1])
{1: 1, -1: 1}
"""
multiple = flags.get('multiple', False)
if isinstance(f, list):
if gens:
raise ValueError('redundant generators given')
x = Dummy('x')
poly, i = {}, len(f)-1
for coeff in f:
poly[i], i = sympify(coeff), i-1
f = Poly(poly, x, field=True)
else:
try:
f = Poly(f, *gens, **flags)
except GeneratorsNeeded:
if multiple:
return []
else:
return {}
if f.is_multivariate:
raise PolynomialError('multivariate polynomials are not supported')
f, x = f.to_field(), f.gen
def _update_dict(result, root, k):
if root in result:
result[root] += k
else:
result[root] = k
def _try_decompose(f):
"""Find roots using functional decomposition. """
factors = f.decompose()
result, g = {}, factors[0]
for h, i in g.sqf_list()[1]:
for r in _try_heuristics(h):
_update_dict(result, r, i)
for factor in factors[1:]:
last, result = result.copy(), {}
for last_r, i in last.iteritems():
g = factor - Poly(last_r, x)
for h, j in g.sqf_list()[1]:
for r in _try_heuristics(h):
_update_dict(result, r, i*j)
return result
def _try_heuristics(f):
"""Find roots using formulas and some tricks. """
if f.is_ground:
return []
if f.is_monomial:
return [S(0)]*f.degree()
if f.length() == 2:
if f.degree() == 1:
return map(cancel, roots_linear(f))
else:
return roots_binomial(f)
result = []
for i in [S(-1), S(1)]:
if f.eval(i).expand().is_zero:
f = f.exquo(Poly(x-1, x))
result.append(i)
break
n = f.degree()
if n == 1:
result += map(cancel, roots_linear(f))
elif n == 2:
result += map(cancel, roots_quadratic(f))
elif n == 3 and flags.get('cubics', True):
result += roots_cubic(f)
elif n == 4 and flags.get('quartics', True):
result += roots_quartic(f)
return result
if f.is_monomial == 1:
if f.is_ground:
if multiple:
return []
else:
return {}
else:
result = { S(0) : f.degree() }
else:
(k,), f = f.terms_gcd()
if not k:
zeros = {}
else:
zeros = { S(0) : k }
result = {}
if f.length() == 2:
if f.degree() == 1:
result[cancel(roots_linear(f)[0])] = 1
else:
for r in roots_binomial(f):
_update_dict(result, r, 1)
elif f.degree() == 2:
for r in roots_quadratic(f):
_update_dict(result, cancel(r), 1)
else:
_, factors = Poly(f.as_basic()).factor_list()
if len(factors) == 1 and factors[0][1] == 1:
result = _try_decompose(f)
else:
for factor, k in factors:
for r in _try_heuristics(Poly(factor, x, field=True)):
_update_dict(result, r, k)
result.update(zeros)
filter = flags.get('filter', None)
if filter not in [None, 'C']:
handlers = {
'Z' : lambda r: r.is_Integer,
'Q' : lambda r: r.is_Rational,
'R' : lambda r: r.is_real,
'I' : lambda r: r.is_imaginary,
}
try:
query = handlers[filter]
except KeyError:
raise ValueError("Invalid filter: %s" % filter)
for zero in dict(result).iterkeys():
if not query(zero):
del result[zero]
predicate = flags.get('predicate', None)
if predicate is not None:
for zero in dict(result).iterkeys():
if not predicate(zero):
del result[zero]
if not multiple:
return result
else:
zeros = []
for zero, k in result.iteritems():
zeros.extend([zero]*k)
return zeros
def reduce_rational_inequalities(exprs, gen, assume=True, relational=True):
"""Reduce a system of rational inequalities with rational coefficients.
Examples
========
>>> from sympy import Poly, Symbol
>>> from sympy.solvers.inequalities import reduce_rational_inequalities
>>> x = Symbol('x', real=True)
>>> reduce_rational_inequalities([[x**2 <= 0]], x)
x == 0
>>> reduce_rational_inequalities([[x + 2 > 0]], x)
-2 < x
"""
exact = True
eqs = []
for _exprs in exprs:
_eqs = []
for expr in _exprs:
if isinstance(expr, tuple):
expr, rel = expr
else:
if expr.is_Relational:
expr, rel = expr.lhs - expr.rhs, expr.rel_op
else:
expr, rel = expr, '=='
try:
(numer, denom), opt = parallel_poly_from_expr(expr.together().as_numer_denom(), gen)
except PolynomialError:
raise PolynomialError("only polynomials and rational functions are supported in this context")
if not opt.domain.is_Exact:
numer, denom, exact = numer.to_exact(), denom.to_exact(), False
domain = opt.domain.get_exact()
if not (domain.is_ZZ or domain.is_QQ):
raise NotImplementedError("inequality solving is not supported over %s" % opt.domain)
_eqs.append(((numer, denom), rel))
eqs.append(_eqs)
solution = solve_rational_inequalities(eqs)
if not exact:
solution = solution.evalf()
if not relational:
return solution
real = ask(Q.real(gen), assumptions=assume)
if not real:
result = And(solution.as_relational(re(gen)), Eq(im(gen), 0))
else:
result = solution.as_relational(gen)
return result