def test_solve_biquadratic():
x0, y0, x1, y1, r = symbols('x0 y0 x1 y1 r')
f_1 = (x - 1)**2 + (y - 1)**2 - r**2
f_2 = (x - 2)**2 + (y - 2)**2 - r**2
s = sqrt(2*r**2 - 1)
a = (3 - s)/2
b = (3 + s)/2
assert solve_poly_system([f_1, f_2], x, y) == [(a, b), (b, a)]
f_1 = (x - 1)**2 + (y - 2)**2 - r**2
f_2 = (x - 1)**2 + (y - 1)**2 - r**2
assert solve_poly_system([f_1, f_2], x, y) == \
[(1 - sqrt(((2*r - 1)*(2*r + 1)))/2, S(3)/2),
(1 + sqrt(((2*r - 1)*(2*r + 1)))/2, S(3)/2)]
query = lambda expr: expr.is_Pow and expr.exp is S.Half
f_1 = (x - 1 )**2 + (y - 2)**2 - r**2
f_2 = (x - x1)**2 + (y - 1)**2 - r**2
result = solve_poly_system([f_1, f_2], x, y)
assert len(result) == 2 and all(len(r) == 2 for r in result)
assert all(r.count(query) == 1 for r in flatten(result))
f_1 = (x - x0)**2 + (y - y0)**2 - r**2
f_2 = (x - x1)**2 + (y - y1)**2 - r**2
result = solve_poly_system([f_1, f_2], x, y)
assert len(result) == 2 and all(len(r) == 2 for r in result)
assert all(len(r.find(query)) == 1 for r in flatten(result))
s1 = (x*y - y, x**2 - x)
assert solve(s1) == [{x: 1}, {x: 0, y: 0}]
s2 = (x*y - x, y**2 - y)
assert solve(s2) == [{y: 1}, {x: 0, y: 0}]
gens = (x, y)
for seq in (s1, s2):
(f, g), opt = parallel_poly_from_expr(seq, *gens)
raises(SolveFailed, lambda: solve_biquadratic(f, g, opt))
seq = (x**2 + y**2 - 2, y**2 - 1)
(f, g), opt = parallel_poly_from_expr(seq, *gens)
assert solve_biquadratic(f, g, opt) == [
(-1, -1), (-1, 1), (1, -1), (1, 1)]
ans = [(0, -1), (0, 1)]
seq = (x**2 + y**2 - 1, y**2 - 1)
(f, g), opt = parallel_poly_from_expr(seq, *gens)
assert solve_biquadratic(f, g, opt) == ans
seq = (x**2 + y**2 - 1, x**2 - x + y**2 - 1)
(f, g), opt = parallel_poly_from_expr(seq, *gens)
assert solve_biquadratic(f, g, opt) == ans
def test_solve_biquadratic():
x0, y0, x1, y1, r = symbols('x0 y0 x1 y1 r')
f_1 = (x - 1)**2 + (y - 1)**2 - r**2
f_2 = (x - 2)**2 + (y - 2)**2 - r**2
s = sqrt(2*r**2 - 1)
a = (3 - s)/2
b = (3 + s)/2
assert solve_poly_system([f_1, f_2], x, y) == [(a, b), (b, a)]
f_1 = (x - 1)**2 + (y - 2)**2 - r**2
f_2 = (x - 1)**2 + (y - 1)**2 - r**2
assert solve_poly_system([f_1, f_2], x, y) == \
[(1 - sqrt(((2*r - 1)*(2*r + 1)))/2, Rational(3, 2)),
(1 + sqrt(((2*r - 1)*(2*r + 1)))/2, Rational(3, 2))]
query = lambda expr: expr.is_Pow and expr.exp is S.Half
f_1 = (x - 1 )**2 + (y - 2)**2 - r**2
f_2 = (x - x1)**2 + (y - 1)**2 - r**2
result = solve_poly_system([f_1, f_2], x, y)
assert len(result) == 2 and all(len(r) == 2 for r in result)
assert all(r.count(query) == 1 for r in flatten(result))
f_1 = (x - x0)**2 + (y - y0)**2 - r**2
f_2 = (x - x1)**2 + (y - y1)**2 - r**2
result = solve_poly_system([f_1, f_2], x, y)
assert len(result) == 2 and all(len(r) == 2 for r in result)
assert all(len(r.find(query)) == 1 for r in flatten(result))
s1 = (x*y - y, x**2 - x)
assert solve(s1) == [{x: 1}, {x: 0, y: 0}]
s2 = (x*y - x, y**2 - y)
assert solve(s2) == [{y: 1}, {x: 0, y: 0}]
gens = (x, y)
for seq in (s1, s2):
(f, g), opt = parallel_poly_from_expr(seq, *gens)
raises(SolveFailed, lambda: solve_biquadratic(f, g, opt))
seq = (x**2 + y**2 - 2, y**2 - 1)
(f, g), opt = parallel_poly_from_expr(seq, *gens)
assert solve_biquadratic(f, g, opt) == [
(-1, -1), (-1, 1), (1, -1), (1, 1)]
ans = [(0, -1), (0, 1)]
seq = (x**2 + y**2 - 1, y**2 - 1)
(f, g), opt = parallel_poly_from_expr(seq, *gens)
assert solve_biquadratic(f, g, opt) == ans
seq = (x**2 + y**2 - 1, x**2 - x + y**2 - 1)
(f, g), opt = parallel_poly_from_expr(seq, *gens)
assert solve_biquadratic(f, g, opt) == ans
def solve_poly_system(seq, *gens, **args):
"""
Solve a system of polynomial equations.
Examples
========
>>> from sympy import solve_poly_system
>>> from sympy.abc import x, y
>>> solve_poly_system([x*y - 2*y, 2*y**2 - x**2], x, y)
[(0, 0), (2, -sqrt(2)), (2, sqrt(2))]
"""
try:
polys, opt = parallel_poly_from_expr(seq, *gens, **args)
except PolificationFailed as exc:
raise ComputationFailed('solve_poly_system', len(seq), exc)
if len(polys) == len(opt.gens) == 2:
f, g = polys
if all(i <= 2 for i in f.degree_list() + g.degree_list()):
try:
return solve_biquadratic(f, g, opt)
except SolveFailed:
pass
return solve_generic(polys, opt)
def solve_poly_system(seq, *gens, **args):
"""
Solve a system of polynomial equations.
Examples
========
>>> from sympy import solve_poly_system
>>> from sympy.abc import x, y
>>> solve_poly_system([x*y - 2*y, 2*y**2 - x**2], x, y)
[(0, 0), (2, -sqrt(2)), (2, sqrt(2))]
"""
try:
polys, opt = parallel_poly_from_expr(seq, *gens, **args)
except PolificationFailed as exc:
raise ComputationFailed('solve_poly_system', len(seq), exc)
if len(polys) == len(opt.gens) == 2:
f, g = polys
a, b = f.degree_list()
c, d = g.degree_list()
if a <= 2 and b <= 2 and c <= 2 and d <= 2:
try:
return solve_biquadratic(f, g, opt)
except SolveFailed:
pass
return solve_generic(polys, opt)
def solve_poly_system(seq, *gens, strict=False, **args):
"""
Solve a system of polynomial equations.
Parameters
==========
seq: a list/tuple/set
Listing all the equations that are needed to be solved
gens: generators
generators of the equations in seq for which we want the
solutions
strict: a boolean (default is False)
if strict is True, NotImplementedError will be raised if
the solution is known to be incomplete (which can occur if
not all solutions are expressible in radicals)
args: Keyword arguments
Special options for solving the equations.
Returns
=======
List[Tuple]
A List of tuples. Solutions for symbols that satisfy the
equations listed in seq
Examples
========
>>> from sympy import solve_poly_system
>>> from sympy.abc import x, y
>>> solve_poly_system([x*y - 2*y, 2*y**2 - x**2], x, y)
[(0, 0), (2, -sqrt(2)), (2, sqrt(2))]
>>> solve_poly_system([x**5 - x + y**3, y**2 - 1], x, y, strict=True)
Traceback (most recent call last):
...
UnsolvableFactorError
"""
try:
polys, opt = parallel_poly_from_expr(seq, *gens, **args)
except PolificationFailed as exc:
raise ComputationFailed('solve_poly_system', len(seq), exc)
if len(polys) == len(opt.gens) == 2:
f, g = polys
if all(i <= 2 for i in f.degree_list() + g.degree_list()):
try:
return solve_biquadratic(f, g, opt)
except SolveFailed:
pass
return solve_generic(polys, opt, strict=strict)
def apart(f, x=None, full=False, **options):
"""
Compute partial fraction decomposition of a rational function.
Given a rational function ``f`` compute partial fraction decomposition
of ``f``. Two algorithms are available: one is based on undetermined
coefficients method and the other is Bronstein's full partial fraction
decomposition algorithm.
Examples
========
>>> from sympy.polys.partfrac import apart
>>> from sympy.abc import x, y
>>> apart(y/(x + 2)/(x + 1), x)
-y/(x + 2) + y/(x + 1)
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
options = set_defaults(options, extension=True)
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
if P.is_multivariate:
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
if Q.degree() <= 1:
partial = P / Q
else:
if not full:
partial = apart_undetermined_coeffs(P, Q)
else:
partial = apart_full_decomposition(P, Q)
terms = S.Zero
for term in Add.make_args(partial):
if term.has(RootSum):
terms += term
else:
terms += factor(term)
return common * (poly.as_expr() + terms)
def apart(f, x=None, full=False, **options):
"""
Compute partial fraction decomposition of a rational function.
Given a rational function ``f`` compute partial fraction decomposition
of ``f``. Two algorithms are available: one is based on undetermined
coefficients method and the other is Bronstein's full partial fraction
decomposition algorithm.
Examples
========
>>> from sympy.polys.partfrac import apart
>>> from sympy.abc import x, y
>>> apart(y/(x + 2)/(x + 1), x)
-y/(x + 2) + y/(x + 1)
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
options = set_defaults(options, extension=True)
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
if P.is_multivariate:
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
if Q.degree() <= 1:
partial = P/Q
else:
if not full:
partial = apart_undetermined_coeffs(P, Q)
else:
partial = apart_full_decomposition(P, Q)
terms = S.Zero
for term in Add.make_args(partial):
if term.has(RootSum):
terms += term
else:
terms += factor(term)
return common*(poly.as_expr() + terms)
def cancel(f):
try:
f = factor_terms(f, radical=True)
p, q = f.as_numer_denom()
# TODO accelerate parallel_poly_from_expr
(p, q), opt = parallel_poly_from_expr((p, q))
c, P, Q = p.cancel(q)
return c * (P.as_expr() / Q.as_expr())
except:
return f
def symmetrize(F, *gens, **args):
"""
Rewrite a polynomial in terms of elementary symmetric polynomials.
Examples
========
>>> from sympy.polys.polyfuncs import symmetrize
>>> from sympy.abc import x, y
>>> symmetrize(x**2 + y**2)
(-2*x*y + (x + y)**2, 0)
>>> symmetrize(x**2 + y**2, formal=True)
(s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)])
>>> symmetrize(x**2 - y**2)
(-2*x*y + (x + y)**2, -2*y**2)
>>> symmetrize(x**2 - y**2, formal=True)
(s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)])
"""
allowed_flags(args, ["formal", "symbols"])
iterable = True
if not hasattr(F, "__iter__"):
iterable = False
F = [F]
try:
F, opt = parallel_poly_from_expr(F, *gens, **args)
except PolificationFailed, exc:
result = []
for expr in exc.exprs:
if expr.is_Number:
result.append((expr, S.Zero))
else:
raise ComputationFailed("symmetrize", len(F), exc)
else:
if not iterable:
result, = result
if not exc.opt.formal:
return result
else:
if iterable:
return result, []
else:
return result + ([],)
def symmetrize(F, *gens, **args):
"""
Rewrite a polynomial in terms of elementary symmetric polynomials.
Examples
========
>>> from sympy.polys.polyfuncs import symmetrize
>>> from sympy.abc import x, y
>>> symmetrize(x**2 + y**2)
(-2*x*y + (x + y)**2, 0)
>>> symmetrize(x**2 + y**2, formal=True)
(s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)])
>>> symmetrize(x**2 - y**2)
(-2*x*y + (x + y)**2, -2*y**2)
>>> symmetrize(x**2 - y**2, formal=True)
(s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)])
"""
allowed_flags(args, ['formal', 'symbols'])
iterable = True
if not hasattr(F, '__iter__'):
iterable = False
F = [F]
try:
F, opt = parallel_poly_from_expr(F, *gens, **args)
except PolificationFailed, exc:
result = []
for expr in exc.exprs:
if expr.is_Number:
result.append((expr, S.Zero))
else:
raise ComputationFailed('symmetrize', len(F), exc)
else:
if not iterable:
result, = result
if not exc.opt.formal:
return result
else:
if iterable:
return result, []
else:
return result + ([],)
def solve_poly_system(seq, *gens, **args):
"""
Solve a system of polynomial equations.
Parameters
==========
seq: a list/tuple/set
Listing all the equations that are needed to be solved
gens: generators
generators of the equations in seq for which we want the
solutions
args: Keyword arguments
Special options for solving the equations
Returns
=======
List[Tuple]
A List of tuples. Solutions for symbols that satisfy the
equations listed in seq
Examples
========
>>> from sympy import solve_poly_system
>>> from sympy.abc import x, y
>>> solve_poly_system([x*y - 2*y, 2*y**2 - x**2], x, y)
[(0, 0), (2, -sqrt(2)), (2, sqrt(2))]
"""
try:
polys, opt = parallel_poly_from_expr(seq, *gens, **args)
except PolificationFailed as exc:
raise ComputationFailed('solve_poly_system', len(seq), exc)
if len(polys) == len(opt.gens) == 2:
f, g = polys
if all(i <= 2 for i in f.degree_list() + g.degree_list()):
try:
return solve_biquadratic(f, g, opt)
except SolveFailed:
pass
return solve_generic(polys, opt)
def solve_poly_system(seq, *gens, **args):
"""
Solve a system of polynomial equations.
Examples
========
>>> from sympy import solve_poly_system
>>> from sympy.abc import x, y
>>> solve_poly_system([x*y - 2*y, 2*y**2 - x**2], x, y)
[(0, 0), (2, -sqrt(2)), (2, sqrt(2))]
"""
try:
polys, opt = parallel_poly_from_expr(seq, *gens, **args)
except PolificationFailed, exc:
raise ComputationFailed('solve_poly_system', len(seq), exc)
def solve_poly_system(seq, *gens, **args):
"""
Solve a system of polynomial equations.
Example
=======
>>> from sympy import solve_poly_system
>>> from sympy.abc import x, y
>>> solve_poly_system([x*y - 2*y, 2*y**2 - x**2], x, y)
[(0, 0), (2, -2**(1/2)), (2, 2**(1/2))]
"""
try:
polys, opt = parallel_poly_from_expr(seq, *gens, **args)
except PolificationFailed, exc:
raise ComputationFailed('solve_poly_system', len(seq), exc)
def from_list(cls, rows, cols, items, gens, ring):
# items can be Expr, Poly, or a mix of Expr and Poly
items = [_sympify(item) for item in items]
if items and all(isinstance(item, Poly) for item in items):
polys = True
else:
polys = False
# Identify the ring for the polys
if ring is not None:
# Parse a domain string like 'QQ[x]'
if isinstance(ring, str):
ring = Poly(0, Dummy(), domain=ring).domain
elif polys:
p = items[0]
for p2 in items[1:]:
p, _ = p.unify(p2)
ring = p.domain[p.gens]
else:
items, info = parallel_poly_from_expr(items, gens, field=True)
ring = info['domain'][info['gens']]
polys = True
# Efficiently convert when all elements are Poly
if polys:
p_ring = Poly(0, ring.symbols, domain=ring.domain)
to_ring = ring.ring.from_list
convert_poly = lambda p: to_ring(p.unify(p_ring)[0].rep.rep)
elements = [convert_poly(p) for p in items]
else:
convert_expr = ring.from_sympy
elements = [convert_expr(e.as_expr()) for e in items]
# Convert to domain elements and construct DomainMatrix
elements_lol = [[elements[i * cols + j] for j in range(cols)]
for i in range(rows)]
dm = DomainMatrix(elements_lol, (rows, cols), ring)
return cls.from_dm(dm)
def apart_list(f, x=None, dummies=None, **options):
"""
Compute partial fraction decomposition of a rational function
and return the result in structured form.
Given a rational function ``f`` compute the partial fraction decomposition
of ``f``. Only Bronstein's full partial fraction decomposition algorithm
is supported by this method. The return value is highly structured and
perfectly suited for further algorithmic treatment rather than being
human-readable. The function returns a tuple holding three elements:
* The first item is the common coefficient, free of the variable `x` used
for decomposition. (It is an element of the base field `K`.)
* The second item is the polynomial part of the decomposition. This can be
the zero polynomial. (It is an element of `K[x]`.)
* The third part itself is a list of quadruples. Each quadruple
has the following elements in this order:
- The (not necessarily irreducible) polynomial `D` whose roots `w_i` appear
in the linear denominator of a bunch of related fraction terms. (This item
can also be a list of explicit roots. However, at the moment ``apart_list``
never returns a result this way, but the related ``assemble_partfrac_list``
function accepts this format as input.)
- The numerator of the fraction, written as a function of the root `w`
- The linear denominator of the fraction *excluding its power exponent*,
written as a function of the root `w`.
- The power to which the denominator has to be raised.
On can always rebuild a plain expression by using the function ``assemble_partfrac_list``.
Examples
========
A first example:
>>> from sympy.polys.partfrac import apart_list, assemble_partfrac_list
>>> from sympy.abc import x, t
>>> f = (2*x**3 - 2*x) / (x**2 - 2*x + 1)
>>> pfd = apart_list(f)
>>> pfd
(1,
Poly(2*x + 4, x, domain='ZZ'),
[(Poly(_w - 1, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1)])
>>> assemble_partfrac_list(pfd)
2*x + 4 + 4/(x - 1)
Second example:
>>> f = (-2*x - 2*x**2) / (3*x**2 - 6*x)
>>> pfd = apart_list(f)
>>> pfd
(-1,
Poly(2/3, x, domain='QQ'),
[(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 2), Lambda(_a, -_a + x), 1)])
>>> assemble_partfrac_list(pfd)
-2/3 - 2/(x - 2)
Another example, showing symbolic parameters:
>>> pfd = apart_list(t/(x**2 + x + t), x)
>>> pfd
(1,
Poly(0, x, domain='ZZ[t]'),
[(Poly(_w**2 + _w + t, _w, domain='ZZ[t]'),
Lambda(_a, -2*_a*t/(4*t - 1) - t/(4*t - 1)),
Lambda(_a, -_a + x),
1)])
>>> assemble_partfrac_list(pfd)
RootSum(_w**2 + _w + t, Lambda(_a, (-2*_a*t/(4*t - 1) - t/(4*t - 1))/(-_a + x)))
This example is taken from Bronstein's original paper:
>>> f = 36 / (x**5 - 2*x**4 - 2*x**3 + 4*x**2 + x - 2)
>>> pfd = apart_list(f)
>>> pfd
(1,
Poly(0, x, domain='ZZ'),
[(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1),
(Poly(_w**2 - 1, _w, domain='ZZ'), Lambda(_a, -3*_a - 6), Lambda(_a, -_a + x), 2),
(Poly(_w + 1, _w, domain='ZZ'), Lambda(_a, -4), Lambda(_a, -_a + x), 1)])
>>> assemble_partfrac_list(pfd)
-4/(x + 1) - 3/(x + 1)**2 - 9/(x - 1)**2 + 4/(x - 2)
See also
========
apart, assemble_partfrac_list
References
==========
1. [Bronstein93]_
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
options = set_defaults(options, extension=True)
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
if P.is_multivariate:
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
polypart = poly
if dummies is None:
def dummies(name):
d = Dummy(name)
while True:
yield d
dummies = dummies("w")
rationalpart = apart_list_full_decomposition(P, Q, dummies)
return (common, polypart, rationalpart)
def apart(f, x=None, full=False, **options):
"""
Compute partial fraction decomposition of a rational function.
Given a rational function ``f`` compute partial fraction decomposition
of ``f``. Two algorithms are available: one is based on undetermined
coefficients method and the other is Bronstein's full partial fraction
decomposition algorithm.
Examples
========
>>> from sympy.polys.partfrac import apart
>>> from sympy.abc import x, y
By default, using the undetermined coefficients method:
>>> apart(y/(x + 2)/(x + 1), x)
-y/(x + 2) + y/(x + 1)
You can choose Bronstein's algorithm by setting ``full=True``:
>>> apart(y/(x**2 + x + 1), x)
y/(x**2 + x + 1)
>>> apart(y/(x**2 + x + 1), x, full=True)
RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x)))
See Also
========
apart_list, assemble_partfrac_list
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
_options = options.copy()
options = set_defaults(options, extension=True)
try:
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
except PolynomialError as msg:
if f.is_commutative:
raise PolynomialError(msg)
# non-commutative
if f.is_Mul:
c, nc = f.args_cnc(split_1=False)
nc = Mul(*[apart(i, x=x, full=full, **_options) for i in nc])
if c:
c = apart(Mul._from_args(c), x=x, full=full, **_options)
return c*nc
else:
return nc
elif f.is_Add:
c = []
nc = []
for i in f.args:
if i.is_commutative:
c.append(i)
else:
try:
nc.append(apart(i, x=x, full=full, **_options))
except NotImplementedError:
nc.append(i)
return apart(Add(*c), x=x, full=full, **_options) + Add(*nc)
else:
reps = []
pot = preorder_traversal(f)
pot.next()
for e in pot:
try:
reps.append((e, apart(e, x=x, full=full, **_options)))
pot.skip() # this was handled successfully
except NotImplementedError:
pass
return f.xreplace(dict(reps))
if P.is_multivariate:
fc = f.cancel()
if fc != f:
return apart(fc, x=x, full=full, **_options)
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
if Q.degree() <= 1:
partial = P/Q
else:
if not full:
partial = apart_undetermined_coeffs(P, Q)
else:
partial = apart_full_decomposition(P, Q)
terms = S.Zero
for term in Add.make_args(partial):
if term.has(RootSum):
terms += term
else:
terms += factor(term)
return common*(poly.as_expr() + terms)
def apart(f, x=None, full=False, **options):
"""
Compute partial fraction decomposition of a rational function.
Given a rational function ``f``, computes the partial fraction
decomposition of ``f``. Two algorithms are available: One is based on the
undertermined coefficients method, the other is Bronstein's full partial
fraction decomposition algorithm.
The undetermined coefficients method (selected by ``full=False``) uses
polynomial factorization (and therefore accepts the same options as
factor) for the denominator. Per default it works over the rational
numbers, therefore decomposition of denominators with non-rational roots
(e.g. irrational, complex roots) is not supported by default (see options
of factor).
Bronstein's algorithm can be selected by using ``full=True`` and allows a
decomposition of denominators with non-rational roots. A human-readable
result can be obtained via ``doit()`` (see examples below).
Examples
========
>>> from sympy.polys.partfrac import apart
>>> from sympy.abc import x, y
By default, using the undetermined coefficients method:
>>> apart(y/(x + 2)/(x + 1), x)
-y/(x + 2) + y/(x + 1)
The undetermined coefficients method does not provide a result when the
denominators roots are not rational:
>>> apart(y/(x**2 + x + 1), x)
y/(x**2 + x + 1)
You can choose Bronstein's algorithm by setting ``full=True``:
>>> apart(y/(x**2 + x + 1), x, full=True)
RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x)))
Calling ``doit()`` yields a human-readable result:
>>> apart(y/(x**2 + x + 1), x, full=True).doit()
(-y/3 - 2*y*(-1/2 - sqrt(3)*I/2)/3)/(x + 1/2 + sqrt(3)*I/2) + (-y/3 -
2*y*(-1/2 + sqrt(3)*I/2)/3)/(x + 1/2 - sqrt(3)*I/2)
See Also
========
apart_list, assemble_partfrac_list
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
_options = options.copy()
options = set_defaults(options, extension=True)
try:
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
except PolynomialError as msg:
if f.is_commutative:
raise PolynomialError(msg)
# non-commutative
if f.is_Mul:
c, nc = f.args_cnc(split_1=False)
nc = f.func(*nc)
if c:
c = apart(f.func._from_args(c), x=x, full=full, **_options)
return c*nc
else:
return nc
elif f.is_Add:
c = []
nc = []
for i in f.args:
if i.is_commutative:
c.append(i)
else:
try:
nc.append(apart(i, x=x, full=full, **_options))
except NotImplementedError:
nc.append(i)
return apart(f.func(*c), x=x, full=full, **_options) + f.func(*nc)
else:
reps = []
pot = preorder_traversal(f)
next(pot)
for e in pot:
try:
reps.append((e, apart(e, x=x, full=full, **_options)))
pot.skip() # this was handled successfully
except NotImplementedError:
pass
return f.xreplace(dict(reps))
if P.is_multivariate:
fc = f.cancel()
if fc != f:
return apart(fc, x=x, full=full, **_options)
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
if Q.degree() <= 1:
partial = P/Q
else:
if not full:
partial = apart_undetermined_coeffs(P, Q)
else:
partial = apart_full_decomposition(P, Q)
terms = S.Zero
for term in Add.make_args(partial):
if term.has(RootSum):
terms += term
else:
terms += factor(term)
return common*(poly.as_expr() + terms)
def _minpoly_op_algebraic_number(ex1, ex2, x, mp1=None, mp2=None, op=Add):
"""
return the minimal polinomial for ``op(ex1, ex2)``
Parameters
==========
ex1, ex2 : expressions for the algebraic numbers
x : indeterminate of the polynomials
mp1, mp2 : minimal polynomials for ``ex1`` and ``ex2`` or None
op : operation ``Add`` or ``Mul``
Examples
========
>>> from sympy import sqrt, Mul
>>> from sympy.polys.numberfields import _minpoly_op_algebraic_number
>>> from sympy.abc import x
>>> p1 = sqrt(sqrt(2) + 1)
>>> p2 = sqrt(sqrt(2) - 1)
>>> _minpoly_op_algebraic_number(p1, p2, x, op=Mul)
x - 1
References
==========
[1] http://en.wikipedia.org/wiki/Resultant
[2] I.M. Isaacs, Proc. Amer. Math. Soc. 25 (1970), 638
"Degrees of sums in a separable field extension".
"""
from sympy import gcd
y = Dummy(str(x))
if mp1 is None:
mp1 = _minpoly1(ex1, x)
if mp2 is None:
mp2 = _minpoly1(ex2, y)
else:
mp2 = mp2.subs({x:y})
if op is Add:
# mp1a = mp1.subs({x:x - y})
(p1, p2), _ = parallel_poly_from_expr((mp1, x - y), x, y)
r = p1.compose(p2)
mp1a = r.as_expr()
elif op is Mul:
mp1a = _muly(mp1, x, y)
else:
raise NotImplementedError('option not available')
r = resultant(mp1a, mp2, gens=[y, x])
deg1 = degree(mp1, x)
deg2 = degree(mp2, y)
if op is Add and gcd(deg1, deg2) == 1:
# `r` is irreducible, see [2]
return r
if op is Mul and deg1 == 1 or deg2 == 1:
# if deg1 = 1, then mp1 = x - a; mp1a = x - y - a;
# r = mp2(x - a), so that `r` is irreducible
return r
_, factors = factor_list(r)
if op in [Add, Mul]:
ex = op(ex1, ex2)
res = _choose_factor(factors, x, ex)
return res
def _minpoly_op_algebraic_element(op, ex1, ex2, x, dom, mp1=None, mp2=None):
"""
return the minimal polynomial for ``op(ex1, ex2)``
Parameters
==========
op : operation ``Add`` or ``Mul``
ex1, ex2 : expressions for the algebraic elements
x : indeterminate of the polynomials
dom: ground domain
mp1, mp2 : minimal polynomials for ``ex1`` and ``ex2`` or None
Examples
========
>>> from sympy import sqrt, Add, Mul, QQ
>>> from sympy.polys.numberfields.minpoly import _minpoly_op_algebraic_element
>>> from sympy.abc import x, y
>>> p1 = sqrt(sqrt(2) + 1)
>>> p2 = sqrt(sqrt(2) - 1)
>>> _minpoly_op_algebraic_element(Mul, p1, p2, x, QQ)
x - 1
>>> q1 = sqrt(y)
>>> q2 = 1 / y
>>> _minpoly_op_algebraic_element(Add, q1, q2, x, QQ.frac_field(y))
x**2*y**2 - 2*x*y - y**3 + 1
References
==========
.. [1] https://en.wikipedia.org/wiki/Resultant
.. [2] I.M. Isaacs, Proc. Amer. Math. Soc. 25 (1970), 638
"Degrees of sums in a separable field extension".
"""
y = Dummy(str(x))
if mp1 is None:
mp1 = _minpoly_compose(ex1, x, dom)
if mp2 is None:
mp2 = _minpoly_compose(ex2, y, dom)
else:
mp2 = mp2.subs({x: y})
if op is Add:
# mp1a = mp1.subs({x: x - y})
if dom == QQ:
R, X = ring('X', QQ)
p1 = R(dict_from_expr(mp1)[0])
p2 = R(dict_from_expr(mp2)[0])
else:
(p1, p2), _ = parallel_poly_from_expr((mp1, x - y), x, y)
r = p1.compose(p2)
mp1a = r.as_expr()
elif op is Mul:
mp1a = _muly(mp1, x, y)
else:
raise NotImplementedError('option not available')
if op is Mul or dom != QQ:
r = resultant(mp1a, mp2, gens=[y, x])
else:
r = rs_compose_add(p1, p2)
r = expr_from_dict(r.as_expr_dict(), x)
deg1 = degree(mp1, x)
deg2 = degree(mp2, y)
if op is Mul and deg1 == 1 or deg2 == 1:
# if deg1 = 1, then mp1 = x - a; mp1a = x - y - a;
# r = mp2(x - a), so that `r` is irreducible
return r
r = Poly(r, x, domain=dom)
_, factors = r.factor_list()
res = _choose_factor(factors, x, op(ex1, ex2), dom)
return res.as_expr()
def _minpoly_op_algebraic_number(ex1, ex2, x, mp1=None, mp2=None, op=Add):
"""
return the minimal polinomial for ``op(ex1, ex2)``
Parameters
==========
ex1, ex2 : expressions for the algebraic numbers
x : indeterminate of the polynomials
mp1, mp2 : minimal polynomials for ``ex1`` and ``ex2`` or None
op : operation ``Add`` or ``Mul``
Examples
========
>>> from sympy import sqrt, Mul
>>> from sympy.polys.numberfields import _minpoly_op_algebraic_number
>>> from sympy.abc import x
>>> p1 = sqrt(sqrt(2) + 1)
>>> p2 = sqrt(sqrt(2) - 1)
>>> _minpoly_op_algebraic_number(p1, p2, x, op=Mul)
x - 1
References
==========
[1] http://en.wikipedia.org/wiki/Resultant
[2] I.M. Isaacs, Proc. Amer. Math. Soc. 25 (1970), 638
"Degrees of sums in a separable field extension".
"""
from sympy import gcd
y = Dummy(str(x))
if mp1 is None:
mp1 = _minpoly1(ex1, x)
if mp2 is None:
mp2 = _minpoly1(ex2, y)
else:
mp2 = mp2.subs({x: y})
if op is Add:
# mp1a = mp1.subs({x:x - y})
(p1, p2), _ = parallel_poly_from_expr((mp1, x - y), x, y)
r = p1.compose(p2)
mp1a = r.as_expr()
elif op is Mul:
mp1a = _muly(mp1, x, y)
else:
raise NotImplementedError('option not available')
r = resultant(mp1a, mp2, gens=[y, x])
deg1 = degree(mp1, x)
deg2 = degree(mp2, y)
if op is Add and gcd(deg1, deg2) == 1:
# `r` is irreducible, see [2]
return r
if op is Mul and deg1 == 1 or deg2 == 1:
# if deg1 = 1, then mp1 = x - a; mp1a = x - y - a;
# r = mp2(x - a), so that `r` is irreducible
return r
_, factors = factor_list(r)
if op in [Add, Mul]:
ex = op(ex1, ex2)
res = _choose_factor(factors, x, ex)
return res
def symmetrize(F, *gens, **args):
"""
Rewrite a polynomial in terms of elementary symmetric polynomials.
A symmetric polynomial is a multivariate polynomial that remains invariant
under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``,
then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where
``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an
element of the group ``S_n``).
Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that
``f = f1 + f2 + ... + fn``.
Examples
========
>>> from sympy.polys.polyfuncs import symmetrize
>>> from sympy.abc import x, y
>>> symmetrize(x**2 + y**2)
(-2*x*y + (x + y)**2, 0)
>>> symmetrize(x**2 + y**2, formal=True)
(s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)])
>>> symmetrize(x**2 - y**2)
(-2*x*y + (x + y)**2, -2*y**2)
>>> symmetrize(x**2 - y**2, formal=True)
(s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)])
"""
allowed_flags(args, ['formal', 'symbols'])
iterable = True
if not hasattr(F, '__iter__'):
iterable = False
F = [F]
try:
F, opt = parallel_poly_from_expr(F, *gens, **args)
except PolificationFailed as exc:
result = []
for expr in exc.exprs:
if expr.is_Number:
result.append((expr, S.Zero))
else:
raise ComputationFailed('symmetrize', len(F), exc)
else:
if not iterable:
result, = result
if not exc.opt.formal:
return result
else:
if iterable:
return result, []
else:
return result + ([],)
polys, symbols = [], opt.symbols
gens, dom = opt.gens, opt.domain
for i in xrange(0, len(gens)):
poly = symmetric_poly(i + 1, gens, polys=True)
polys.append((next(symbols), poly.set_domain(dom)))
indices = list(range(0, len(gens) - 1))
weights = list(range(len(gens), 0, -1))
result = []
for f in F:
symmetric = []
if not f.is_homogeneous:
symmetric.append(f.TC())
f -= f.TC()
while f:
_height, _monom, _coeff = -1, None, None
for i, (monom, coeff) in enumerate(f.terms()):
if all(monom[i] >= monom[i + 1] for i in indices):
height = max([ n*m for n, m in zip(weights, monom) ])
if height > _height:
_height, _monom, _coeff = height, monom, coeff
if _height != -1:
monom, coeff = _monom, _coeff
else:
break
exponents = []
for m1, m2 in zip(monom, monom[1:] + (0,)):
exponents.append(m1 - m2)
term = [ s**n for (s, _), n in zip(polys, exponents) ]
poly = [ p**n for (_, p), n in zip(polys, exponents) ]
symmetric.append(Mul(coeff, *term))
product = poly[0].mul(coeff)
for p in poly[1:]:
product = product.mul(p)
f -= product
result.append((Add(*symmetric), f.as_expr()))
polys = [ (s, p.as_expr()) for s, p in polys ]
if not opt.formal:
for i, (sym, non_sym) in enumerate(result):
result[i] = (sym.subs(polys), non_sym)
if not iterable:
result, = result
if not opt.formal:
return result
else:
if iterable:
return result, polys
else:
return result + (polys,)
def symmetrize(F, *gens, **args):
"""
Rewrite a polynomial in terms of elementary symmetric polynomials.
A symmetric polynomial is a multivariate polynomial that remains invariant
under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``,
then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where
``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an
element of the group ``S_n``).
Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that
``f = f1 + f2 + ... + fn``.
Examples
========
>>> from sympy.polys.polyfuncs import symmetrize
>>> from sympy.abc import x, y
>>> symmetrize(x**2 + y**2)
(-2*x*y + (x + y)**2, 0)
>>> symmetrize(x**2 + y**2, formal=True)
(s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)])
>>> symmetrize(x**2 - y**2)
(-2*x*y + (x + y)**2, -2*y**2)
>>> symmetrize(x**2 - y**2, formal=True)
(s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)])
"""
allowed_flags(args, ['formal', 'symbols'])
iterable = True
if not hasattr(F, '__iter__'):
iterable = False
F = [F]
try:
F, opt = parallel_poly_from_expr(F, *gens, **args)
except PolificationFailed as exc:
result = []
for expr in exc.exprs:
if expr.is_Number:
result.append((expr, S.Zero))
else:
raise ComputationFailed('symmetrize', len(F), exc)
else:
if not iterable:
result, = result
if not exc.opt.formal:
return result
else:
if iterable:
return result, []
else:
return result + ([], )
polys, symbols = [], opt.symbols
gens, dom = opt.gens, opt.domain
for i in xrange(0, len(gens)):
poly = symmetric_poly(i + 1, gens, polys=True)
polys.append((symbols.next(), poly.set_domain(dom)))
indices = range(0, len(gens) - 1)
weights = range(len(gens), 0, -1)
result = []
for f in F:
symmetric = []
if not f.is_homogeneous:
symmetric.append(f.TC())
f -= f.TC()
while f:
_height, _monom, _coeff = -1, None, None
for i, (monom, coeff) in enumerate(f.terms()):
if all(monom[i] >= monom[i + 1] for i in indices):
height = max([n * m for n, m in zip(weights, monom)])
if height > _height:
_height, _monom, _coeff = height, monom, coeff
if _height != -1:
monom, coeff = _monom, _coeff
else:
break
exponents = []
for m1, m2 in zip(monom, monom[1:] + (0, )):
exponents.append(m1 - m2)
term = [s**n for (s, _), n in zip(polys, exponents)]
poly = [p**n for (_, p), n in zip(polys, exponents)]
symmetric.append(Mul(coeff, *term))
product = poly[0].mul(coeff)
for p in poly[1:]:
product = product.mul(p)
f -= product
result.append((Add(*symmetric), f.as_expr()))
polys = [(s, p.as_expr()) for s, p in polys]
if not opt.formal:
for i, (sym, non_sym) in enumerate(result):
result[i] = (sym.subs(polys), non_sym)
if not iterable:
result, = result
if not opt.formal:
return result
else:
if iterable:
return result, polys
else:
return result + (polys, )
def apart(f, x=None, full=False, **options):
"""
Compute partial fraction decomposition of a rational function.
Given a rational function ``f`` compute partial fraction decomposition
of ``f``. Two algorithms are available: one is based on undetermined
coefficients method and the other is Bronstein's full partial fraction
decomposition algorithm.
Examples
========
>>> from sympy.polys.partfrac import apart
>>> from sympy.abc import x, y
By default, using the undetermined coefficients method:
>>> apart(y/(x + 2)/(x + 1), x)
-y/(x + 2) + y/(x + 1)
You can choose Bronstein's algorithm by setting ``full=True``:
>>> apart(y/(x**2 + x + 1), x)
y/(x**2 + x + 1)
>>> apart(y/(x**2 + x + 1), x, full=True)
RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x)))
See Also
========
apart_list, assemble_partfrac_list
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
_options = options.copy()
options = set_defaults(options, extension=True)
try:
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
except PolynomialError, msg:
if f.is_commutative:
raise PolynomialError(msg)
# non-commutative
if f.is_Mul:
c, nc = f.args_cnc(split_1=False)
nc = Mul(*[apart(i, x=x, full=full, **_options) for i in nc])
if c:
c = apart(Mul._from_args(c), x=x, full=full, **_options)
return c*nc
else:
return nc
elif f.is_Add:
c = []
nc = []
for i in f.args:
if i.is_commutative:
c.append(i)
else:
try:
nc.append(apart(i, x=x, full=full, **_options))
except NotImplementedError:
nc.append(i)
return apart(Add(*c), x=x, full=full, **_options) + Add(*nc)
else:
reps = []
pot = preorder_traversal(f)
pot.next()
for e in pot:
try:
reps.append((e, apart(e, x=x, full=full, **_options)))
pot.skip() # this was handled successfully
except NotImplementedError:
pass
return f.xreplace(dict(reps))
def symmetrize(F, *gens, **args):
"""
Rewrite a polynomial in terms of elementary symmetric polynomials.
A symmetric polynomial is a multivariate polynomial that remains invariant
under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``,
then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where
``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an
element of the group ``S_n``).
Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that
``f = f1 + f2 + ... + fn``.
Examples
========
>>> from sympy.polys.polyfuncs import symmetrize
>>> from sympy.abc import x, y
>>> symmetrize(x**2 + y**2)
(-2*x*y + (x + y)**2, 0)
>>> symmetrize(x**2 + y**2, formal=True)
(s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)])
>>> symmetrize(x**2 - y**2)
(-2*x*y + (x + y)**2, -2*y**2)
>>> symmetrize(x**2 - y**2, formal=True)
(s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)])
"""
allowed_flags(args, ['formal', 'symbols'])
iterable = True
if not hasattr(F, '__iter__'):
iterable = False
F = [F]
try:
F, opt = parallel_poly_from_expr(F, *gens, **args)
except PolificationFailed, exc:
result = []
for expr in exc.exprs:
if expr.is_Number:
result.append((expr, S.Zero))
else:
raise ComputationFailed('symmetrize', len(F), exc)
else:
if not iterable:
result, = result
if not exc.opt.formal:
return result
else:
if iterable:
return result, []
else:
return result + ([], )
def apart(f, x=None, full=False, **options):
"""
Compute partial fraction decomposition of a rational function.
Given a rational function ``f``, computes the partial fraction
decomposition of ``f``. Two algorithms are available: One is based on the
undertermined coefficients method, the other is Bronstein's full partial
fraction decomposition algorithm.
The undetermined coefficients method (selected by ``full=False``) uses
polynomial factorization (and therefore accepts the same options as
factor) for the denominator. Per default it works over the rational
numbers, therefore decomposition of denominators with non-rational roots
(e.g. irrational, complex roots) is not supported by default (see options
of factor).
Bronstein's algorithm can be selected by using ``full=True`` and allows a
decomposition of denominators with non-rational roots. A human-readable
result can be obtained via ``doit()`` (see examples below).
Examples
========
>>> from sympy.polys.partfrac import apart
>>> from sympy.abc import x, y
By default, using the undetermined coefficients method:
>>> apart(y/(x + 2)/(x + 1), x)
-y/(x + 2) + y/(x + 1)
The undetermined coefficients method does not provide a result when the
denominators roots are not rational:
>>> apart(y/(x**2 + x + 1), x)
y/(x**2 + x + 1)
You can choose Bronstein's algorithm by setting ``full=True``:
>>> apart(y/(x**2 + x + 1), x, full=True)
RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x)))
Calling ``doit()`` yields a human-readable result:
>>> apart(y/(x**2 + x + 1), x, full=True).doit()
(-y/3 - 2*y*(-1/2 - sqrt(3)*I/2)/3)/(x + 1/2 + sqrt(3)*I/2) + (-y/3 -
2*y*(-1/2 + sqrt(3)*I/2)/3)/(x + 1/2 - sqrt(3)*I/2)
See Also
========
apart_list, assemble_partfrac_list
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
_options = options.copy()
options = set_defaults(options, extension=True)
try:
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
except PolynomialError as msg:
if f.is_commutative:
raise PolynomialError(msg)
# non-commutative
if f.is_Mul:
c, nc = f.args_cnc(split_1=False)
nc = f.func(*nc)
if c:
c = apart(f.func._from_args(c), x=x, full=full, **_options)
return c*nc
else:
return nc
elif f.is_Add:
c = []
nc = []
for i in f.args:
if i.is_commutative:
c.append(i)
else:
try:
nc.append(apart(i, x=x, full=full, **_options))
except NotImplementedError:
nc.append(i)
return apart(f.func(*c), x=x, full=full, **_options) + f.func(*nc)
else:
reps = []
pot = preorder_traversal(f)
next(pot)
for e in pot:
try:
reps.append((e, apart(e, x=x, full=full, **_options)))
pot.skip() # this was handled successfully
except NotImplementedError:
pass
return f.xreplace(dict(reps))
if P.is_multivariate:
fc = f.cancel()
if fc != f:
return apart(fc, x=x, full=full, **_options)
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
if Q.degree() <= 1:
partial = P/Q
else:
if not full:
partial = apart_undetermined_coeffs(P, Q)
else:
partial = apart_full_decomposition(P, Q)
terms = S.Zero
for term in Add.make_args(partial):
if term.has(RootSum):
terms += term
else:
terms += factor(term)
return common*(poly.as_expr() + terms)
def symmetrize(F, *gens, **args):
"""
Rewrite a polynomial in terms of elementary symmetric polynomials.
A symmetric polynomial is a multivariate polynomial that remains invariant
under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``,
then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where
``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an
element of the group ``S_n``).
Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that
``f = f1 + f2 + ... + fn``.
Examples
========
>>> from sympy.polys.polyfuncs import symmetrize
>>> from sympy.abc import x, y
>>> symmetrize(x**2 + y**2)
(-2*x*y + (x + y)**2, 0)
>>> symmetrize(x**2 + y**2, formal=True)
(s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)])
>>> symmetrize(x**2 - y**2)
(-2*x*y + (x + y)**2, -2*y**2)
>>> symmetrize(x**2 - y**2, formal=True)
(s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)])
"""
allowed_flags(args, ["formal", "symbols"])
iterable = True
if not hasattr(F, "__iter__"):
iterable = False
F = [F]
try:
F, opt = parallel_poly_from_expr(F, *gens, **args)
except PolificationFailed, exc:
result = []
for expr in exc.exprs:
if expr.is_Number:
result.append((expr, S.Zero))
else:
raise ComputationFailed("symmetrize", len(F), exc)
else:
if not iterable:
result, = result
if not exc.opt.formal:
return result
else:
if iterable:
return result, []
else:
return result + ([],)
def _minpoly_op_algebraic_element(op, ex1, ex2, x, dom, mp1=None, mp2=None):
"""
return the minimal polynomial for ``op(ex1, ex2)``
Parameters
==========
op : operation ``Add`` or ``Mul``
ex1, ex2 : expressions for the algebraic elements
x : indeterminate of the polynomials
dom: ground domain
mp1, mp2 : minimal polynomials for ``ex1`` and ``ex2`` or None
Examples
========
>>> from sympy import sqrt, Add, Mul, QQ
>>> from sympy.polys.numberfields import _minpoly_op_algebraic_element
>>> from sympy.abc import x, y
>>> p1 = sqrt(sqrt(2) + 1)
>>> p2 = sqrt(sqrt(2) - 1)
>>> _minpoly_op_algebraic_element(Mul, p1, p2, x, QQ)
x - 1
>>> q1 = sqrt(y)
>>> q2 = 1 / y
>>> _minpoly_op_algebraic_element(Add, q1, q2, x, QQ.frac_field(y))
x**2*y**2 - 2*x*y - y**3 + 1
References
==========
[1] http://en.wikipedia.org/wiki/Resultant
[2] I.M. Isaacs, Proc. Amer. Math. Soc. 25 (1970), 638
"Degrees of sums in a separable field extension".
"""
from sympy import gcd
y = Dummy(str(x))
if mp1 is None:
mp1 = _minpoly_compose(ex1, x, dom)
if mp2 is None:
mp2 = _minpoly_compose(ex2, y, dom)
else:
mp2 = mp2.subs({x: y})
if op is Add:
# mp1a = mp1.subs({x: x - y})
(p1, p2), _ = parallel_poly_from_expr((mp1, x - y), x, y)
r = p1.compose(p2)
mp1a = r.as_expr()
elif op is Mul:
mp1a = _muly(mp1, x, y)
else:
raise NotImplementedError('option not available')
r = resultant(mp1a, mp2, gens=[y, x])
deg1 = degree(mp1, x)
deg2 = degree(mp2, y)
if op is Add and gcd(deg1, deg2) == 1:
# `r` is irreducible, see [2]
return r
if op is Mul and deg1 == 1 or deg2 == 1:
# if deg1 = 1, then mp1 = x - a; mp1a = x - y - a;
# r = mp2(x - a), so that `r` is irreducible
return r
r = Poly(r, x, domain=dom)
_, factors = r.factor_list()
res = _choose_factor(factors, x, op(ex1, ex2), dom)
return res.as_expr()
def apart_list(f, x=None, dummies=None, **options):
"""
Compute partial fraction decomposition of a rational function
and return the result in structured form.
Given a rational function ``f`` compute the partial fraction decomposition
of ``f``. Only Bronstein's full partial fraction decomposition algorithm
is supported by this method. The return value is highly structured and
perfectly suited for further algorithmic treatment rather than being
human-readable. The function returns a tuple holding three elements:
* The first item is the common coefficient, free of the variable `x` used
for decomposition. (It is an element of the base field `K`.)
* The second item is the polynomial part of the decomposition. This can be
the zero polynomial. (It is an element of `K[x]`.)
* The third part itself is a list of quadruples. Each quadruple
has the following elements in this order:
- The (not necessarily irreducible) polynomial `D` whose roots `w_i` appear
in the linear denominator of a bunch of related fraction terms. (This item
can also be a list of explicit roots. However, at the moment ``apart_list``
never returns a result this way, but the related ``assemble_partfrac_list``
function accepts this format as input.)
- The numerator of the fraction, written as a function of the root `w`
- The linear denominator of the fraction *excluding its power exponent*,
written as a function of the root `w`.
- The power to which the denominator has to be raised.
On can always rebuild a plain expression by using the function ``assemble_partfrac_list``.
Examples
========
A first example:
>>> from sympy.polys.partfrac import apart_list, assemble_partfrac_list
>>> from sympy.abc import x, t
>>> f = (2*x**3 - 2*x) / (x**2 - 2*x + 1)
>>> pfd = apart_list(f)
>>> pfd
(1,
Poly(2*x + 4, x, domain='ZZ'),
[(Poly(_w - 1, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1)])
>>> assemble_partfrac_list(pfd)
2*x + 4 + 4/(x - 1)
Second example:
>>> f = (-2*x - 2*x**2) / (3*x**2 - 6*x)
>>> pfd = apart_list(f)
>>> pfd
(-1,
Poly(2/3, x, domain='QQ'),
[(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 2), Lambda(_a, -_a + x), 1)])
>>> assemble_partfrac_list(pfd)
-2/3 - 2/(x - 2)
Another example, showing symbolic parameters:
>>> pfd = apart_list(t/(x**2 + x + t), x)
>>> pfd
(1,
Poly(0, x, domain='ZZ[t]'),
[(Poly(_w**2 + _w + t, _w, domain='ZZ[t]'),
Lambda(_a, -2*_a*t/(4*t - 1) - t/(4*t - 1)),
Lambda(_a, -_a + x),
1)])
>>> assemble_partfrac_list(pfd)
RootSum(_w**2 + _w + t, Lambda(_a, (-2*_a*t/(4*t - 1) - t/(4*t - 1))/(-_a + x)))
This example is taken from Bronstein's original paper:
>>> f = 36 / (x**5 - 2*x**4 - 2*x**3 + 4*x**2 + x - 2)
>>> pfd = apart_list(f)
>>> pfd
(1,
Poly(0, x, domain='ZZ'),
[(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1),
(Poly(_w**2 - 1, _w, domain='ZZ'), Lambda(_a, -3*_a - 6), Lambda(_a, -_a + x), 2),
(Poly(_w + 1, _w, domain='ZZ'), Lambda(_a, -4), Lambda(_a, -_a + x), 1)])
>>> assemble_partfrac_list(pfd)
-4/(x + 1) - 3/(x + 1)**2 - 9/(x - 1)**2 + 4/(x - 2)
See also
========
apart, assemble_partfrac_list
References
==========
.. [1] [Bronstein93]_
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
options = set_defaults(options, extension=True)
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
if P.is_multivariate:
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
polypart = poly
if dummies is None:
def dummies(name):
d = Dummy(name)
while True:
yield d
dummies = dummies("w")
rationalpart = apart_list_full_decomposition(P, Q, dummies)
return (common, polypart, rationalpart)
def apart(f, x=None, full=False, **options):
"""
Compute partial fraction decomposition of a rational function.
Given a rational function ``f`` compute partial fraction decomposition
of ``f``. Two algorithms are available: one is based on undetermined
coefficients method and the other is Bronstein's full partial fraction
decomposition algorithm.
Examples
========
>>> from sympy.polys.partfrac import apart
>>> from sympy.abc import x, y
By default, using the undetermined coefficients method:
>>> apart(y/(x + 2)/(x + 1), x)
-y/(x + 2) + y/(x + 1)
You can choose Bronstein's algorithm by setting ``full=True``:
>>> apart(y/(x**2 + x + 1), x)
y/(x**2 + x + 1)
>>> apart(y/(x**2 + x + 1), x, full=True)
RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x)))
See Also
========
apart_list, assemble_partfrac_list
"""
allowed_flags(options, [])
f = sympify(f)
if f.is_Atom:
return f
else:
P, Q = f.as_numer_denom()
_options = options.copy()
options = set_defaults(options, extension=True)
try:
(P, Q), opt = parallel_poly_from_expr((P, Q), x, **options)
except PolynomialError as msg:
if f.is_commutative:
raise PolynomialError(msg)
# non-commutative
if f.is_Mul:
c, nc = f.args_cnc(split_1=False)
nc = f.func(*[apart(i, x=x, full=full, **_options) for i in nc])
if c:
c = apart(f.func._from_args(c), x=x, full=full, **_options)
return c*nc
else:
return nc
elif f.is_Add:
c = []
nc = []
for i in f.args:
if i.is_commutative:
c.append(i)
else:
try:
nc.append(apart(i, x=x, full=full, **_options))
except NotImplementedError:
nc.append(i)
return apart(f.func(*c), x=x, full=full, **_options) + f.func(*nc)
else:
reps = []
pot = preorder_traversal(f)
next(pot)
for e in pot:
try:
reps.append((e, apart(e, x=x, full=full, **_options)))
pot.skip() # this was handled successfully
except NotImplementedError:
pass
return f.xreplace(dict(reps))
if P.is_multivariate:
fc = f.cancel()
if fc != f:
return apart(fc, x=x, full=full, **_options)
raise NotImplementedError(
"multivariate partial fraction decomposition")
common, P, Q = P.cancel(Q)
poly, P = P.div(Q, auto=True)
P, Q = P.rat_clear_denoms(Q)
if Q.degree() <= 1:
partial = P/Q
else:
if not full:
partial = apart_undetermined_coeffs(P, Q)
else:
partial = apart_full_decomposition(P, Q)
terms = S.Zero
for term in Add.make_args(partial):
if term.has(RootSum):
terms += term
else:
terms += factor(term)
return common*(poly.as_expr() + terms)
