def eliminate(polys, elim_variables, **kwds):
r"""
Compute a Groebner basis with respect to an elimination order defined by
the given variables.
INPUT:
- ``polys`` -- an ideal or a polynomial sequence.
- ``elim_variables`` -- the variables to eliminate.
- ``force_elim`` -- integer (default: `1`).
- ``kwds`` -- same as in :func:`groebner_basis`.
OUTPUT: a Groebner basis of the elimination ideal.
EXAMPLES::
sage: R.<x,y,t,s,z> = PolynomialRing(QQ,5)
sage: I = R * [x-t,y-t^2,z-t^3,s-x+y^3]
sage: import fgb_sage # optional - fgb_sage
sage: gb = fgb_sage.eliminate(I, [t,s], verbosity=0) # optional - fgb_sage, random
open simulation
sage: gb # optional - fgb_sage
[x^2 - y, x*y - z, y^2 - x*z]
sage: gb.is_groebner() # optional - fgb_sage
True
sage: gb.ideal() == I.elimination_ideal([t,s]) # optional - fgb_sage
True
.. NOTE::
In some cases, this function fails to set the correct elimination
order, see :trac:`24981`. This was fixed in Sage 8.7.
"""
kwds.setdefault('force_elim', 1)
polyseq = PolynomialSequence(polys)
ring = polyseq.ring()
elim_variables = set(elim_variables)
block1 = [x for x in ring.gens() if x in elim_variables]
block2 = [x for x in ring.gens() if x not in elim_variables]
from sage.rings.polynomial.term_order import TermOrder
if len(block1) == 0 or len(block2) == 0:
t = TermOrder("degrevlex", ring.ngens())
else:
t = TermOrder("degrevlex", len(block1)) + TermOrder(
"degrevlex", len(block2))
if t == ring.term_order() and set(
ring.gens()[:len(block1)]) == elim_variables:
return groebner_basis(polyseq, **kwds)
else:
block_ring = ring.change_ring(names=block1 + block2, order=t)
gb = groebner_basis(PolynomialSequence(block_ring, polyseq), **kwds)
return PolynomialSequence(ring, gb, immutable=True)
def __init__(self, base_ring, n, names, order):
from sage.rings.polynomial.polynomial_singular_interface import can_convert_to_singular
order = TermOrder(order, n)
MPolynomialRing_generic.__init__(self, base_ring, n, names, order)
# Construct the generators
v = [0 for _ in xrange(n)]
one = base_ring(1)
self._gens = []
C = self._poly_class()
for i in xrange(n):
v[i] = 1 # int's!
self._gens.append(C(self, {tuple(v): one}))
v[i] = 0
self._gens = tuple(self._gens)
self._zero_tuple = tuple(v)
self._has_singular = can_convert_to_singular(self)
# This polynomial ring should belong to Algebras(base_ring).
# Algebras(...).parent_class, which was called from MPolynomialRing_generic.__init__,
# tries to provide a conversion from the base ring, if it does not exist.
# This is for algebras that only do the generic stuff in their initialisation.
# But here, we want to use PolynomialBaseringInjection. Hence, we need to
# wipe the memory and construct the conversion from scratch.
if n:
from sage.rings.polynomial.polynomial_element import PolynomialBaseringInjection
base_inject = PolynomialBaseringInjection(base_ring, self)
self.register_coercion(base_inject)
def _multi_variate(base_ring, names, n, sparse, order, implementation):
# if not sparse:
# raise ValueError, "A dense representation of multivariate polynomials is not supported"
sparse = False
# "True" would be correct, since there is no dense implementation of
# multivariate polynomials. However, traditionally, "False" is used in the key,
# even though it is meaningless.
if implementation is not None:
raise ValueError(
"The %s implementation is not known for multivariate polynomial rings"
% implementation)
names = normalize_names(n, names)
n = len(names)
import sage.rings.polynomial.multi_polynomial_ring as m
from sage.rings.polynomial.term_order import TermOrder
order = TermOrder(order, n)
key = (base_ring, names, n, sparse, order)
R = _get_from_cache(key)
if not R is None:
return R
from sage.rings.polynomial.multi_polynomial_libsingular import MPolynomialRing_libsingular
if isinstance(base_ring, ring.IntegralDomain):
if n < 1:
R = m.MPolynomialRing_polydict_domain(base_ring, n, names, order)
else:
try:
R = MPolynomialRing_libsingular(base_ring, n, names, order)
except (TypeError, NotImplementedError):
R = m.MPolynomialRing_polydict_domain(base_ring, n, names,
order)
else:
if not base_ring.is_zero():
try:
R = MPolynomialRing_libsingular(base_ring, n, names, order)
except (TypeError, NotImplementedError):
R = m.MPolynomialRing_polydict(base_ring, n, names, order)
else:
R = m.MPolynomialRing_polydict(base_ring, n, names, order)
_save_in_cache(key, R)
return R
def polynomial_ring(self, names, gens=None):
r"""
Return a polynomial ring of which ``self`` is a quotient.
INPUT:
- ``names`` -- a list or tuple of names (strings), or a comma separated string
- ``gens`` (default: None) -- (list) a list of generator of ``self``. If ``gens`` is
``None`` then the generators returned by :meth:`~sage.modular.modform.find_generator.ModularFormsRing.gen_forms`
is used instead.
OUTPUT: A multivariate polynomial ring in the variable ``names``. Each variable of the
polynomial ring correspond to a generator given in gens (following the ordering of the list).
EXAMPLES::
sage: M = ModularFormsRing(1)
sage: gens = M.gen_forms()
sage: M.polynomial_ring('E4, E6', gens)
Multivariate Polynomial Ring in E4, E6 over Rational Field
sage: M = ModularFormsRing(Gamma0(8))
sage: gens = M.gen_forms()
sage: M.polynomial_ring('g', gens)
Multivariate Polynomial Ring in g0, g1, g2 over Rational Field
The degrees of the variables are the weights of the corresponding forms::
sage: M = ModularFormsRing(1)
sage: P.<E4, E6> = M.polynomial_ring()
sage: E4.degree()
4
sage: E6.degree()
6
sage: (E4*E6).degree()
10
"""
if gens is None:
gens = self.gen_forms()
degs = [f.weight() for f in gens]
return PolynomialRing(
self.base_ring(),
len(gens),
names,
order=TermOrder(
'wdeglex',
degs)) # Should we remove the deg lexicographic ordering here?
def __classcall__(cls, base_ring, num_gens, name_list,
order='negdeglex', default_prec=10, sparse=False):
"""
Preprocessing of arguments: The term order can be given as string
or as a :class:`~sage.rings.polynomial.term_order.TermOrder` instance.
TESTS::
sage: P1 = PowerSeriesRing(QQ, ['f0','f1','f2','f3'], order = TermOrder('degrevlex'))
sage: P2 = PowerSeriesRing(QQ,4,'f', order='degrevlex')
sage: P1 is P2 # indirect doctest
True
"""
order = TermOrder(order,num_gens)
return super(MPowerSeriesRing_generic,cls).__classcall__(cls, base_ring, num_gens, name_list,
order, default_prec, sparse)
def _multi_variate(base_ring,
names,
sparse=None,
order="degrevlex",
implementation=None):
# if not sparse:
# raise ValueError("a dense representation of multivariate polynomials is not supported")
sparse = False
if implementation is None:
force_singular = False
elif implementation == "singular":
force_singular = True
else:
raise ValueError(
"unknown implementation %r for multivariate polynomial rings" %
(implementation, ))
n = len(names)
from sage.rings.polynomial.term_order import TermOrder
order = TermOrder(order, n)
key = (base_ring, names, n, sparse, order)
R = _get_from_cache(key)
if not R is None:
return R
from sage.rings.polynomial.multi_polynomial_libsingular import MPolynomialRing_libsingular
try:
R = MPolynomialRing_libsingular(base_ring, n, names, order)
except (TypeError, NotImplementedError):
if force_singular:
raise
import sage.rings.polynomial.multi_polynomial_ring as m
if isinstance(base_ring, ring.IntegralDomain):
R = m.MPolynomialRing_polydict_domain(base_ring, n, names, order)
else:
R = m.MPolynomialRing_polydict(base_ring, n, names, order)
_save_in_cache(key, R)
return R
def __init__(self, base_ring, n, names, order):
from sage.rings.polynomial.polynomial_singular_interface import can_convert_to_singular
order = TermOrder(order, n)
# MPolynomialRing_base.__init__() normally initialises the base ring,
# but it also needs the generators to construct a coercion map from the
# base ring, and the base ring must be set to initialise the generators.
# We set the base ring manually to break this circular dependency.
self._base = base_ring
# Construct the generators
v = [0] * n
one = base_ring.one()
self._gens = []
for i in range(n):
v[i] = 1 # int's!
self._gens.append(self.Element_hidden(self, {tuple(v): one}))
v[i] = 0
self._gens = tuple(self._gens)
self._zero_tuple = tuple(v)
MPolynomialRing_base.__init__(self, base_ring, n, names, order)
self._has_singular = can_convert_to_singular(self)
def polynomial_ring(self, names='E2, E4, E6'):
r"""
Return a multivariate polynomial ring isomorphic to the given graded
quasimodular forms ring.
In the case of the full modular group, this
ring is `R[E_2, E_4, E_6]` where `E_2`, `E_4` and `E_6` have degrees 2,
4 and 6 respectively.
INPUT:
- ``names`` (str, default: ``'E2, E4, E6'``) -- a list or tuple of names
(strings), or a comma separated string. Correspond to the names of the
variables.
OUTPUT: A multivariate polynomial ring in the variables ``names``
EXAMPLES:
sage: QM = QuasiModularForms(1)
sage: P.<E2, E4, E6> = QM.polynomial_ring(); P
Multivariate Polynomial Ring in E2, E4, E6 over Rational Field
sage: E2.degree()
2
sage: E4.degree()
4
sage: E6.degree()
6
sage: P.<x, y, z, w> = QQ[]
sage: QM.from_polynomial(x+y+z+w)
Traceback (most recent call last):
...
ValueError: the number of variables (4) of the given polynomial cannot exceed the number of generators (3) of the quasimodular forms ring
"""
return PolynomialRing(
self.base_ring(),
3,
names,
order=TermOrder('wdeglex', [ZZ(2), ZZ(4), ZZ(6)]))
def __init__(self,
base_ring,
num_gens,
name_list,
order='negdeglex',
default_prec=10,
sparse=False):
"""
Initializes a multivariate power series ring. See PowerSeriesRing
for complete documentation.
INPUT
- ``base_ring`` - a commutative ring
- ``num_gens`` - number of generators
- ``name_list`` - List of indeterminate names or a single name.
If a single name is given, indeterminates will be this name
followed by a number from 0 to num_gens - 1. If a list is
given, these will be the indeterminate names and the length
of the list must be equal to num_gens.
- ``order`` - ordering of variables; default is
negative degree lexicographic
- ``default_prec`` - The default total-degree precision for
elements. The default value of default_prec is 10.
- ``sparse`` - whether or not power series are sparse
EXAMPLES::
sage: R.<t,u,v> = PowerSeriesRing(QQ)
sage: g = 1 + v + 3*u*t^2 - 2*v^2*t^2
sage: g = g.add_bigoh(5); g
1 + v + 3*t^2*u - 2*t^2*v^2 + O(t, u, v)^5
sage: g in R
True
TESTS:
By :trac:`14084`, the multi-variate power series ring belongs to the
category of integral domains, if the base ring does::
sage: P = ZZ[['x','y']]
sage: P.category()
Category of integral domains
sage: TestSuite(P).run()
Otherwise, it belongs to the category of commutative rings::
sage: P = Integers(15)[['x','y']]
sage: P.category()
Category of commutative rings
sage: TestSuite(P).run()
"""
order = TermOrder(order, num_gens)
self._term_order = order
if not base_ring.is_commutative():
raise TypeError("Base ring must be a commutative ring.")
n = int(num_gens)
if n < 0:
raise ValueError(
"Multivariate Polynomial Rings must have more than 0 variables."
)
self._ngens = n
self._has_singular = False #cannot convert to Singular by default
# Multivariate power series rings inherit from power series rings. But
# apparently we can not call their initialisation. Instead, initialise
# CommutativeRing and Nonexact:
CommutativeRing.__init__(self,
base_ring,
name_list,
category=_IntegralDomains if base_ring
in _IntegralDomains else _CommutativeRings)
Nonexact.__init__(self, default_prec)
# underlying polynomial ring in which to represent elements
self._poly_ring_ = PolynomialRing(base_ring,
self.variable_names(),
sparse=sparse,
order=order)
# because sometimes PowerSeriesRing_generic calls self.__poly_ring
self._PowerSeriesRing_generic__poly_ring = self._poly_ring()
# background univariate power series ring
self._bg_power_series_ring = PowerSeriesRing(self._poly_ring_,
'Tbg',
sparse=sparse,
default_prec=default_prec)
self._bg_indeterminate = self._bg_power_series_ring.gen()
self._is_sparse = sparse
self._params = (base_ring, num_gens, name_list, order, default_prec,
sparse)
self._populate_coercion_lists_()
def BooleanPolynomialRing_constructor(n=None, names=None, order="lex"):
"""
Construct a boolean polynomial ring with the following
parameters:
INPUT:
- ``n`` -- number of variables (an integer > 1)
- ``names`` -- names of ring variables, may be a string or list/tuple of strings
- ``order`` -- term order (default: lex)
EXAMPLES::
sage: R.<x, y, z> = BooleanPolynomialRing() # indirect doctest
sage: R
Boolean PolynomialRing in x, y, z
sage: p = x*y + x*z + y*z
sage: x*p
x*y*z + x*y + x*z
sage: R.term_order()
Lexicographic term order
sage: R = BooleanPolynomialRing(5,'x',order='deglex(3),deglex(2)')
sage: R.term_order()
Block term order with blocks:
(Degree lexicographic term order of length 3,
Degree lexicographic term order of length 2)
sage: R = BooleanPolynomialRing(3,'x',order='degneglex')
sage: R.term_order()
Degree negative lexicographic term order
sage: BooleanPolynomialRing(names=('x','y'))
Boolean PolynomialRing in x, y
sage: BooleanPolynomialRing(names='x,y')
Boolean PolynomialRing in x, y
TESTS::
sage: P.<x,y> = BooleanPolynomialRing(2,order='deglex')
sage: x > y
True
sage: P.<x0, x1, x2, x3> = BooleanPolynomialRing(4,order='deglex(2),deglex(2)')
sage: x0 > x1
True
sage: x2 > x3
True
"""
if isinstance(n, str):
names = n
n = -1
elif n is None:
n = -1
names = normalize_names(n, names)
n = len(names)
from sage.rings.polynomial.term_order import TermOrder
order = TermOrder(order, n)
key = ("pbori", names, n, order)
R = _get_from_cache(key)
if not R is None:
return R
from sage.rings.polynomial.pbori import BooleanPolynomialRing
R = BooleanPolynomialRing(n, names, order)
_save_in_cache(key, R)
return R
def create_key(self,
base,
prec=None,
log_radii=ZZ(0),
names=None,
order='degrevlex'):
"""
Create a key from the input paramaters.
INPUT:
- ``base`` -- a `p`-adic ring or field
- ``prec`` -- an integer or ``None`` (default: ``None``)
- ``log_radii`` -- an integer or a list or a tuple of integers
(default: ``0``)
- ``names`` -- names of the indeterminates
- ``order`` - a monomial ordering (default: ``degrevlex``)
EXAMPLES::
sage: TateAlgebra.create_key(Zp(2), names=['x','y'])
(2-adic Field with capped relative precision 20,
20,
(0, 0),
('x', 'y'),
Degree reverse lexicographic term order)
TESTS::
sage: TateAlgebra.create_key(Zp(2))
Traceback (most recent call last):
...
ValueError: you must specify the names of the variables
sage: TateAlgebra.create_key(ZZ)
Traceback (most recent call last):
...
TypeError: the base ring must be a p-adic ring or a p-adic field
sage: TateAlgebra.create_key(Zp(2), names=['x','y'], log_radii=[1])
Traceback (most recent call last):
...
ValueError: the number of radii does not match the number of variables
sage: TateAlgebra.create_key(Zp(2), names=['x','y'], log_radii=[0, 1/2])
Traceback (most recent call last):
...
NotImplementedError: only integral log_radii are implemented
sage: TateAlgebra.create_key(Zp(2), names=['x','y'], order='myorder')
Traceback (most recent call last):
...
ValueError: unknown term order 'myorder'
"""
if not isinstance(base, pAdicGeneric):
raise TypeError(
"the base ring must be a p-adic ring or a p-adic field")
# TODO: allow for arbitrary CDVF
base = base.fraction_field()
if names is None:
raise ValueError("you must specify the names of the variables")
names = normalize_names(-1, names)
ngens = len(names)
if not isinstance(log_radii, (list, tuple)):
try:
log_radii = [ZZ(log_radii)] * ngens
except TypeError:
raise NotImplementedError(
"only integral log_radii are implemented")
elif len(log_radii) != ngens:
raise ValueError(
"the number of radii does not match the number of variables")
else:
try:
log_radii = [ZZ(r) for r in log_radii]
except TypeError:
raise NotImplementedError(
"only integral log_radii are implemented")
order = TermOrder(order, ngens)
if prec is None:
prec = base.precision_cap()
key = (base, prec, tuple(log_radii), names, order)
return key
def _multi_variate(base_ring,
names,
sparse=None,
order="degrevlex",
implementation=None):
if sparse is None:
sparse = True
if not sparse:
raise NotImplementedError(
"a dense representation of multivariate polynomials is not supported"
)
from sage.rings.polynomial.term_order import TermOrder
n = len(names)
order = TermOrder(order, n)
# "implementation" must be last
key = [base_ring, names, n, order, implementation]
R = _get_from_cache(key)
if R is not None:
return R
# Multiple arguments for the "implementation" keyword which actually
# yield the same implementation. We need this for caching.
implementation_names = set([implementation])
if implementation is None or implementation == "singular":
from sage.rings.polynomial.multi_polynomial_libsingular import MPolynomialRing_libsingular
try:
R = MPolynomialRing_libsingular(base_ring, n, names, order)
except (TypeError, NotImplementedError):
if implementation is not None:
raise
else:
implementation_names.update([None, "singular"])
if R is None and implementation is None:
# Interpret implementation=None as implementation="generic"
implementation = "generic"
implementation_names.add(implementation)
key[-1] = implementation
R = _get_from_cache(key)
if R is None and implementation == "generic":
from . import multi_polynomial_ring
if isinstance(base_ring, ring.IntegralDomain):
constructor = multi_polynomial_ring.MPolynomialRing_polydict_domain
else:
constructor = multi_polynomial_ring.MPolynomialRing_polydict
R = constructor(base_ring, n, names, order)
if R is None:
raise ValueError(
"unknown implementation %r for multivariate polynomial rings" %
(implementation, ))
for impl in implementation_names:
key[-1] = impl
_save_in_cache(key, R)
return R
def __init__(self, base_ring, n, names, order):
order = TermOrder(order, n)
MPolynomialRing_polydict.__init__(self, base_ring, n, names, order)
def __init__(self,
base_ring,
num_gens,
name_list,
order='negdeglex',
default_prec=10,
sparse=False):
"""
Initializes a multivariate power series ring. See PowerSeriesRing
for complete documentation.
INPUT
- ``base_ring`` - a commutative ring
- ``num_gens`` - number of generators
- ``name_list`` - List of indeterminate names or a single name.
If a single name is given, indeterminates will be this name
followed by a number from 0 to num_gens - 1. If a list is
given, these will be the indeterminate names and the length
of the list must be equal to num_gens.
- ``order`` - ordering of variables; default is
negative degree lexicographic
- ``default_prec`` - The default total-degree precision for
elements. The default value of default_prec is 10.
- ``sparse`` - whether or not power series are sparse
EXAMPLES::
sage: R.<t,u,v> = PowerSeriesRing(QQ)
sage: g = 1 + v + 3*u*t^2 - 2*v^2*t^2
sage: g = g.add_bigoh(5); g
1 + v + 3*t^2*u - 2*t^2*v^2 + O(t, u, v)^5
sage: g in R
True
"""
order = TermOrder(order, num_gens)
self._term_order = order
if not base_ring.is_commutative():
raise TypeError("Base ring must be a commutative ring.")
n = int(num_gens)
if n < 0:
raise ValueError(
"Multivariate Polynomial Rings must have more than 0 variables."
)
self._ngens = n
self._has_singular = False #cannot convert to Singular by default
ParentWithGens.__init__(self, base_ring, name_list)
Nonexact.__init__(self, default_prec)
# underlying polynomial ring in which to represent elements
self._poly_ring_ = PolynomialRing(base_ring,
self.variable_names(),
sparse=sparse,
order=order)
# because sometimes PowerSeriesRing_generic calls self.__poly_ring
self._PowerSeriesRing_generic__poly_ring = self._poly_ring()
# background univariate power series ring
self._bg_power_series_ring = PowerSeriesRing(self._poly_ring_,
'Tbg',
sparse=sparse,
default_prec=default_prec)
self._bg_indeterminate = self._bg_power_series_ring.gen()
## use the following in PowerSeriesRing_generic.__call__
self._PowerSeriesRing_generic__power_series_class = MPowerSeries
self._is_sparse = sparse
self._params = (base_ring, num_gens, name_list, order, default_prec,
sparse)
self._populate_coercion_lists_()
