def usecase__get_linear_series__P1P1_DP6():
'''
Construct linear series of curves in P^1xP^1,
with a given tree of (infinitely near) base points.
'''
# construct ring over Gaussian rationals
#
ring = PolyRing('x,y,v,w', True)
ring.ext_num_field('t^2 + 1')
a0 = ring.root_gens()[0]
# setup base point tree for 2 simple complex conjugate base points.
#
bp_tree = BasePointTree(['xv', 'xw', 'yv', 'yw'])
bp = bp_tree.add('xv', (-a0, a0), 1)
bp = bp_tree.add('xv', (a0, -a0), 1)
LSTools.p(
'We consider linear series of curves in P^1xP^1 with the following base point tree:'
)
LSTools.p(bp_tree)
#
# Construct linear series is defined by a list of polynomials
# in (x:y)(v:w) of bi-degree (2,2) with base points as in "bp_tree".
# The defining polynomials of this linear series, correspond to a parametric map
# of an anticanonical model of a Del Pezzo surface of degree 6 in P^6.
#
# We expect that the linear series is defined by the following set of polynomials:
#
# [ 'x^2*v^2 - y^2*w^2', 'x^2*v*w + y^2*v*w', 'x^2*w^2 + y^2*w^2', 'x*y*v^2 - y^2*v*w',
# 'x*y*v*w - y^2*w^2', 'y^2*v*w + x*y*w^2', 'y^2*v^2 + y^2*w^2' ]
#
ls = LinearSeries.get([2, 2], bp_tree)
LSTools.p(
'The linear series of bi-degree (2,2) corresponding to this base point tree is as follows:'
)
LSTools.p(ls.get_bp_tree())
#
# construct corresponding linear series of bi-degree (1,1)
# and 2 simple complex conjugate base points
#
# We expect that the linear series is defined by the following set of polynomials:
#
# ['x * v - y * w', 'y * v + x * w' ]
#
#
ls = LinearSeries.get([1, 1], bp_tree)
LSTools.p(
'The linear series of bi-degree (1,1) corresponding to this base point tree is as follows:'
)
LSTools.p(ls.get_bp_tree())
def usecase__get_base_points__and__get_linear_series():
'''
We obtain (infinitely near) base points of a
linear series defined over QQ. The base points
are defined over a number field.
'''
ring = PolyRing('x,y,z', True)
ls = LinearSeries(['x^2+y^2', 'y^2+x*z'], ring)
bp_tree = ls.get_bp_tree()
LSTools.p(bp_tree)
ls = LinearSeries.get([2], bp_tree)
LSTools.p(ls)
LSTools.p(ls.get_bp_tree())
def usecase__get_base_points__P2():
'''
We obtain (infinitely near) base points of a
linear series defined over a number field.
'''
ring = PolyRing('x,y,z', True)
ring.ext_num_field('t^2 + 1')
ring.ext_num_field('t^3 + a0')
a0, a1 = ring.root_gens()
x, y, z = ring.gens()
pol_lst = [x**2 + a0 * y * z, y + a1 * z + x]
ls = LinearSeries(pol_lst, ring)
LSTools.p(ls)
bp_tree = ls.get_bp_tree()
LSTools.p(bp_tree)
def usecase__get_base_points__P1P1():
'''
We obtain (infinitely near) base points of a
linear series defined by bi-homogeneous polynomials.
Such polynomials are defined on P^1xP^1 (the fiber product
of the projective line with itself).
The coordinate functions of P^1xP^1 are (x:y)(v:w).
'''
pol_lst = [
'17/5*v^2*x^2 + 6/5*v*w*x^2 + w^2*x^2 + 17/5*v^2*y^2 + 6/5*v*w*y^2 + w^2*y^2',
'6/5*v^2*x^2 + 8/5*v*w*x^2 + 6/5*v^2*y^2 + 8/5*v*w*y^2',
'7/5*v^2*x^2 + 6/5*v*w*x^2 + w^2*x^2 + 7/5*v^2*y^2 + 6/5*v*w*y^2 + w^2*y^2',
'4*v^2*x*y', '-2*v^2*x^2 + 2*v^2*y^2',
'2/5*v^2*x^2 + 6/5*v*w*x^2 - 4*v^2*x*y - 2/5*v^2*y^2 - 6/5*v*w*y^2',
'2*v^2*x^2 + 4/5*v^2*x*y + 12/5*v*w*x*y - 2*v^2*y^2'
]
ls = LinearSeries(pol_lst, PolyRing('x,y,v,w'))
LSTools.p(ls)
bp_tree = ls.get_bp_tree()
LSTools.p(bp_tree)
def usecase__get_linear_series__P2():
'''
Construct linear series of curves in the plane P^2,
with a given tree of (infinitely near) base points.
'''
# Example from PhD thesis (page 159).
PolyRing.reset_base_field()
bp_tree = BasePointTree()
bp = bp_tree.add('z', (0, 0), 1)
bp = bp.add('t', (0, 0), 1)
bp = bp.add('t', (-1, 0), 1)
bp = bp.add('t', (0, 0), 1)
LSTools.p(bp_tree)
ls = LinearSeries.get([2], bp_tree)
LSTools.p(ls.get_bp_tree())
def usecase__get_base_points__examples():
'''
We obtain (infinitely near) base points of several
examples of linear series in order to test
"get_base_point_tree.get_bp_tree()".
'''
pol_lst_lst = []
# 0
pol_lst_lst += [['x^2*z + y^2*z', 'y^3 + z^3']]
# 1
pol_lst_lst += [['x^3*z^2 + y^5', 'x^5']]
# 2 (example from PhD thesis)
pol_lst_lst += [['x^2', 'x*z + y^2']]
# 3
pol_lst_lst += [['x^2 + y^2', 'x*z + y^2']]
# 4
pol_lst_lst += [['x*z', 'y^2', 'y*z', 'z^2']]
# 5
pol_lst_lst += [['x^5', 'y^2*z^3']]
# 6
pol_lst_lst += [['x^2*y', 'x*y^2', 'x*y*z', '( x^2 + y^2 + z^2 )*z']]
# 7 (weighted projective plane P(2:1:1))
pol_lst_lst += [[
'z^6', 'y*z^5', 'y^2*z^4', 'y^3*z^3', 'y^4*z^2', 'y^5*z', 'y^6',
'x^2*z^4', 'x^2*y*z^3', 'x^2*y^2*z^2', 'x^3*z^3'
]]
# 8 (provided by Martin Weimann)
pol_lst_lst += [[
'y^2*(x^3+x^2*z+2*x*z^2+z^3)+y*(2*x^3+2*x*z^2)*z+z^2*(x^3-x^2*z+x*z^2)',
'z^5'
]]
# 9
pol_lst_lst += [['x^3*y^4+x*y^4*z^2+3*x^2*y^3*z^2+3*x*y^2*z^4+y', 'z^7']]
# 10 (degree 6 del Pezzo in S^5, which is the orbital product of 2 circles)
pol_lst_lst += [[
'x^2*y^2 + 6/5*x^2*y*z + 17/5*x^2*z^2 + y^2*z^2 + 6/5*y*z^3 + 17/5*z^4',
'8/5*x^2*y*z + 6/5*x^2*z^2 + 8/5*y*z^3 + 6/5*z^4',
'x^2*y^2 + 6/5*x^2*y*z + 7/5*x^2*z^2 + y^2*z^2 + 6/5*y*z^3 + 7/5*z^4',
'4*x*z^3', '2*x^2*z^2 - 2*z^4',
'-6/5*x^2*y*z - 2/5*x^2*z^2 - 4*x*z^3 + 6/5*y*z^3 + 2/5*z^4',
'-2*x^2*z^2 + 12/5*x*y*z^2 + 4/5*x*z^3 + 2*z^4'
]]
BasePointTree.short = True
idx = 0
for pol_lst in pol_lst_lst:
ls = LinearSeries(pol_lst, PolyRing('x,y,z', True))
LSTools.p(3 * ('\n' + 50 * '='))
LSTools.p('index for example =', idx)
LSTools.p(ls)
bp_tree = ls.get_bp_tree()
LSTools.p(bp_tree)
idx += 1
def usecase__neron_severi_lattice():
'''
Compute NS-lattice of a linear series and
the dimension of complete linear with base points.
'''
# Blowup of projective plane in 3 colinear points
# and 2 infinitly near points. The image of the
# map associated to the linear series is a quartic
# del pezzo surface with 5 families of conics. Moreover
# the surface contains 8 straight lines.
#
ring = PolyRing('x,y,z', True)
p1 = (-1, 0)
p2 = (0, 0)
p3 = (1, 0)
p4 = (0, 1)
p5 = (2, 0)
bp_tree = BasePointTree()
bp_tree.add('z', p1, 1)
bp_tree.add('z', p2, 1)
bp_tree.add('z', p3, 1)
bp = bp_tree.add('z', p4, 1)
bp.add('t', p5, 1)
ls = LinearSeries.get([3], bp_tree)
LSTools.p('ls = ', ls)
LSTools.p(ls.get_bp_tree(), '\n\n ', ls.get_implicit_image())
# Detects that 3 base points lie on a line.
#
bp_tree = BasePointTree()
bp_tree.add('z', p1, 1)
bp_tree.add('z', p2, 1)
bp_tree.add('z', p3, 1)
ls123 = LinearSeries.get([1], bp_tree)
LSTools.p('ls123 =', ls123)
assert ls123.pol_lst == ring.coerce('[y]')
# example of infinitly near base points
# that is colinear with another simple base point.
#
bp_tree = BasePointTree()
bp_tree.add('z', p1, 1)
bp = bp_tree.add('z', p4, 1)
bp.add('t', (1, 0), 1)
ls1 = LinearSeries.get([1], bp_tree)
LSTools.p('ls1 =', ls1)
assert ls1.pol_lst == ring.coerce('[x-y+z]')
# Detects that an infinitly near base points
# is not colinear with other point.
#
for p in [p1, p2, p3]:
bp_tree = BasePointTree()
bp = bp_tree.add('z', p4, 1)
bp.add('t', p5, 1)
bp_tree.add('z', p, 1)
ls45i = LinearSeries.get([1], bp_tree)
assert ls45i.pol_lst == []
# line with predefined tangent
#
bp_tree = BasePointTree()
bp = bp_tree.add('z', p4, 1)
bp.add('t', p5, 1)
ls45 = LinearSeries.get([1], bp_tree)
LSTools.p('ls45 =', ls45)
assert ls45.pol_lst == ring.coerce('[x-2*y+2*z]')
# class of conics through 5 basepoints
#
bp_tree = BasePointTree()
bp_tree.add('z', p1, 1)
bp_tree.add('z', p2, 1)
bp_tree.add('z', p3, 1)
bp = bp_tree.add('z', p4, 1)
bp.add('t', p5, 1)
ls1234 = LinearSeries.get([2], bp_tree)
LSTools.p('ls1234 =', ls1234)
LSTools.p('\t\t', sage_factor(ls1234.pol_lst[0]))
assert ring.coerce('(x - 2*y + 2*z, 1)') in ring.aux_gcd(ls1234.pol_lst)[0]
assert ring.coerce('(y, 1)') in ring.aux_gcd(ls1234.pol_lst)[0]
# class of conics through 4 basepoints
# has a fixed component
#
bp_tree = BasePointTree()
bp_tree.add('z', p4, 1)
ls4 = LinearSeries.get([1], bp_tree)
LSTools.p('ls4 =', ls4)
bp_tree = BasePointTree()
bp_tree.add('z', p1, 1)
bp_tree.add('z', p2, 1)
bp_tree.add('z', p3, 1)
bp_tree.add('z', p4, 1)
ls1234 = LinearSeries.get([2], bp_tree)
LSTools.p('ls1234 =', ls1234)
# return
# Compose map associated to linear series "ls"
# with the inverse stereographic projection "Pinv".
#
R = sage_PolynomialRing(sage_QQ, 'y0,y1,y2,y3,y4,x,y,z')
y0, y1, y2, y3, y4, x, y, z = R.gens()
delta = y1**2 + y2**2 + y3**2 + y4**2
Pinv = [
y0**2 + delta, 2 * y0 * y1, 2 * y0 * y2, 2 * y0 * y3, 2 * y0 * y4,
-y0**2 + delta
]
H = sage__eval(str(ls.pol_lst), R.gens_dict())
PinvH = [
elt.subs({
y0: H[0],
y1: H[1],
y2: H[2],
y3: H[3],
y4: H[4]
}) for elt in Pinv
]
LSTools.p('Pinv =', Pinv)
LSTools.p('H =', H)
LSTools.p('Pinv o H =', PinvH)
# In order to compute the NS-lattice of the image
# of "PinvH" we do a base point analysis.
#
ls_PinvH = LinearSeries([str(elt) for elt in PinvH], ring)
LSTools.p('ls_PinvH =', ls_PinvH)
LSTools.p('\t\t', ls_PinvH.get_implicit_image())
if False: # takes a long time
LSTools.p(ls_PinvH.get_bp_tree())
def usecase__linear_normalization__and__adjoint():
'''
In this usecase are some applications of the
"linear_series" library. we show by example
how to compute a linear normalization X of a surface Y,
or equivalently, how to compute the completion of a
linear series. Also we contruct an example of a surface Z
such that X is its adjoint surface.
'''
#
# Linear series corresponding to the parametrization
# of a cubic surface X in P^4 that is the projection
# of the Veronese embedding of P^2 into P^5.
#
ring = PolyRing('x,y,z', True)
bp_tree = BasePointTree()
bp = bp_tree.add('z', (0, 0), 1)
ls = LinearSeries.get([2], bp_tree)
imp_lst = ls.get_implicit_image()
LSTools.p('linear series =', ls.get_bp_tree())
LSTools.p('implicit image =', imp_lst)
#
# compute Hilbert polynomial of X in QQ[x0,...,x6]
#
R = sage_PolynomialRing(sage_QQ,
['x' + str(i) for i in range(len(ls.pol_lst))])
x_lst = R.gens()
imp_lst = sage__eval(str(imp_lst), R.gens_dict())
hpol = R.ideal(imp_lst).hilbert_polynomial()
hdeg = hpol.diff().diff()
LSTools.p('Hilbert polynomial =', hpol)
LSTools.p('implicit degree =', hdeg)
#
# projection of X in P^4 to Y in P^3, where Y is singular.
#
ls = LinearSeries(['x^2-x*y', 'x*z', 'y^2', 'y*z'],
PolyRing('x,y,z', True))
bp_tree = ls.get_bp_tree()
LSTools.p('basepoint tree of projection =', bp_tree)
eqn = ls.get_implicit_image()
assert len(eqn) == 1
eqn = sage_SR(eqn[0])
x0, x1, x2, x3 = sage_var('x0,x1,x2,x3')
LSTools.p('eqn =', eqn)
LSTools.p('D(eqn,x0) =', sage_diff(eqn, x0))
LSTools.p('D(eqn,x1) =', sage_diff(eqn, x1))
LSTools.p('D(eqn,x2) =', sage_diff(eqn, x2))
LSTools.p('D(eqn,x3) =', sage_diff(eqn, x3))
#
# compute normalization X of Y
#
ls_norm = LinearSeries.get([2], bp_tree)
LSTools.p('normalization = ', ls_norm)
LSTools.p(' = ', ls_norm.get_implicit_image())
#
# define pre-adjoint surface Z
#
ring = PolyRing('x,y,z', True)
bp_tree = BasePointTree()
bp_tree.add('z', (0, 0), 2)
bp_tree.add('z', (0, 1), 1)
ls = LinearSeries.get([5], bp_tree)
LSTools.p(ls.get_bp_tree())
def usecase__get_implicit__DP6():
'''
Construct linear series of curves in P^1xP^1,
with a given tree of (infinitely near) base points.
The defining polynomials of this linear series, correspond to a parametric map
of an anticanonical model of a Del Pezzo surface of degree 6 in P^6.
Its ideal is generated by quadratic forms. We search for a quadratic form in
this ideal of signature (1,6). This quadratic form corresponds to a hyperquadric
in P^6, such that the sextic Del Pezzo surface is contained in this hyperquadric.
We construct a real projective isomorphism from this hyperquadric to the projectivization
of the unit 5-sphere in P^6.
'''
#
# parametrization of degree 6 del Pezzo surface in projective 6-space.
# See ".usecase__get_linear_series__P1P1_DP6()" for the construction of
# this linear series.
#
pmz_lst = [
'x^2*v^2 - y^2*w^2', 'x^2*v*w + y^2*v*w', 'x^2*w^2 + y^2*w^2',
'x*y*v^2 - y^2*v*w', 'x*y*v*w - y^2*w^2', 'y^2*v*w + x*y*w^2',
'y^2*v^2 + y^2*w^2'
]
ls = LinearSeries(pmz_lst, PolyRing('x,y,v,w', True))
#
# base points of linear series
#
bp_tree = ls.get_bp_tree()
LSTools.p('parametrization =', ls.pol_lst)
LSTools.p('base points =' + str(bp_tree))
#
# implicit image in projective 6-space
# of map associated to linear series
#
imp_lst = ls.get_implicit_image()
LSTools.p('implicit equations =', imp_lst)
#
# compute Hilbert polynomial in QQ[x0,...,x6]
#
ring = sage_PolynomialRing(sage_QQ, ['x' + str(i) for i in range(7)])
x_lst = ring.gens()
imp_lst = sage__eval(str(imp_lst), ring.gens_dict())
hpol = ring.ideal(imp_lst).hilbert_polynomial()
hdeg = hpol.diff().diff()
LSTools.p('Hilbert polynomial =', hpol)
LSTools.p('implicit degree =', hdeg)
#
# equation of unit sphere is not in the ideal
#
s_pol = sum([-x_lst[0]**2] + [x**2 for x in x_lst[1:]])
LSTools.p('Inside sphere?: ', s_pol in ring.ideal(imp_lst))
#
# compute random quadrics containing del Pezzo surface
# until a quadric with signature (1,6) is found
# or set a precomputed quadric with given "c_lst"
#
LSTools.p(
'Look for quadric in ideal of signature (1,6)...(may take a while)...')
sig = []
while sorted(sig) != [0, 1, 6]:
# set coefficient list
c_lst = []
c_lst = [-1, -1, 0, 0, 0, -1, 1, 0, -1, -1,
-1] # uncomment to speed up execution
if c_lst == []:
lst = [-1, 0, 1]
for imp in imp_lst:
idx = int(sage_ZZ.random_element(0, len(lst)))
c_lst += [lst[idx]]
# obtain quadric in ideal from "c_lst"
i_lst = range(len(imp_lst))
M_pol = [
c_lst[i] * imp_lst[i] for i in i_lst
if imp_lst[i].total_degree() == 2
]
M_pol = sum(M_pol)
# eigendecomposition
M = sage_invariant_theory.quadratic_form(
M_pol, x_lst).as_QuadraticForm().matrix()
M = sage_matrix(sage_QQ, M)
vx = sage_vector(x_lst)
D, V = M.eigenmatrix_right()
# determine signature of quadric
num_pos = len([d for d in D.diagonal() if d > 0])
num_neg = len([d for d in D.diagonal() if d < 0])
num_zer = len([d for d in D.diagonal() if d == 0])
sig = [num_pos, num_neg, num_zer]
LSTools.p('\t sig =', sig, c_lst)
#
# output of M.eigenmatrix_right() ensures that
# D has signature either (--- --- +) or (- +++ +++)
#
if num_pos < num_neg: # (--- --- +) ---> (+ --- ---)
V.swap_columns(0, 6)
D.swap_columns(0, 6)
D.swap_rows(0, 6)
#
# diagonal orthonormalization
# note: M == W.T*D*W == W.T*L.T*J*L*W = U.T*J*U
#
W = sage_matrix([col / col.norm() for col in V.columns()])
J = []
for d in D.diagonal():
if d > 0:
J += [1]
elif d < 0:
J += [-1]
J = sage_diagonal_matrix(J)
L = sage_diagonal_matrix([d.abs().sqrt() for d in D.diagonal()])
U = L * W
#
# Do some tests
#
assert M_pol in ring.ideal(imp_lst)
assert vx * M * vx == M_pol
assert M * V == V * D
#
# output values
#
LSTools.p('quadratic form of signature (1,6) in ideal =', M_pol)
LSTools.p('matrix M associated to quadratic form =', list(M))
LSTools.p('M == U.T*J*U =',
list(U.T * J * U))
LSTools.p('U =', list(U))
LSTools.p('J =', list(J))