def rank2_GF(n=500, p=16411, system='sage'):
"""
Rank over GF(p): Given a (n + 10) x n matrix over GF(p) with
random entries, compute the rank.
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.rank2_GF(500)
sage: tm = b.rank2_GF(500, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n + 10, n)
t = cputime()
v = A.rank()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
K := Rank(A);
s := Cputime(t);
""" % (n, p)
if verbose: print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"' % system)
def invert_hilbert_QQ(n=40, system='sage'):
"""
Runs the benchmark for calculating the inverse of the hilbert
matrix over rationals of dimension n.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.invert_hilbert_QQ(30)
sage: tm = b.invert_hilbert_QQ(30, system='magma') # optional - magma
"""
if system == 'sage':
A = hilbert_matrix(n)
t = cputime()
d = A**(-1)
return cputime(t)
elif system == 'magma':
code = """
h := HilbertMatrix(%s);
tinit := Cputime();
d := h^(-1);
s := Cputime(tinit);
delete h;
""" % n
if verbose: print(code)
magma.eval(code)
return float(magma.eval('s'))
def charpoly_GF(n=100, p=16411, system='sage'):
"""
Given a n x n matrix over GF with random entries, compute the
charpoly.
INPUT:
- ``n`` - matrix dimension (default: 100)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.charpoly_GF(100)
sage: tm = b.charpoly_GF(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n)
t = cputime()
v = A.charpoly()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
K := CharacteristicPolynomial(A);
s := Cputime(t);
"""%(n,p)
if verbose: print code
magma.eval(code)
return magma.eval('s')
else:
raise ValueError('unknown system "%s"'%system)
def charpoly_GF(n=100, p=16411, system='sage'):
"""
Given a n x n matrix over GF with random entries, compute the
charpoly.
INPUT:
- ``n`` - matrix dimension (default: 100)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.charpoly_GF(100)
sage: tm = b.charpoly_GF(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n)
t = cputime()
v = A.charpoly()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
K := CharacteristicPolynomial(A);
s := Cputime(t);
""" % (n, p)
if verbose: print(code)
magma.eval(code)
return magma.eval('s')
else:
raise ValueError('unknown system "%s"' % system)
def nullspace_GF(n=300, p=16411, system='sage'):
"""
Given a n+1 x n matrix over GF(p) with random
entries, compute the nullspace.
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.nullspace_GF(300)
sage: tm = b.nullspace_GF(300, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n+1)
t = cputime()
v = A.kernel()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(RMatrixSpace(GF(%s), n, n+1));
t := Cputime();
K := Kernel(A);
s := Cputime(t);
"""%(n,p)
if verbose: print code
magma.eval(code)
return magma.eval('s')
else:
raise ValueError('unknown system "%s"'%system)
def nullspace_GF(n=300, p=16411, system='sage'):
"""
Given a n+1 x n matrix over GF(p) with random
entries, compute the nullspace.
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.nullspace_GF(300)
sage: tm = b.nullspace_GF(300, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n + 1)
t = cputime()
v = A.kernel()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(RMatrixSpace(GF(%s), n, n+1));
t := Cputime();
K := Kernel(A);
s := Cputime(t);
""" % (n, p)
if verbose: print(code)
magma.eval(code)
return magma.eval('s')
else:
raise ValueError('unknown system "%s"' % system)
def invert_hilbert_QQ(n=40, system='sage'):
"""
Runs the benchmark for calculating the inverse of the hilbert
matrix over rationals of dimension n.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.invert_hilbert_QQ(30)
sage: tm = b.invert_hilbert_QQ(30, system='magma') # optional - magma
"""
if system == 'sage':
A = hilbert_matrix(n)
t = cputime()
d = A**(-1)
return cputime(t)
elif system == 'magma':
code = """
h := HilbertMatrix(%s);
tinit := Cputime();
d := h^(-1);
s := Cputime(tinit);
delete h;
"""%n
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
def rank2_GF(n=500, p=16411, system='sage'):
"""
Rank over GF(p): Given a (n + 10) x n matrix over GF(p) with
random entries, compute the rank.
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.rank2_GF(500)
sage: tm = b.rank2_GF(500, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n+10, n)
t = cputime()
v = A.rank()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
K := Rank(A);
s := Cputime(t);
"""%(n,p)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def EllipticCurve_from_cubic(F, P):
r"""
Construct an elliptic curve from a ternary cubic with a rational point.
INPUT:
- ``F`` -- a homogeneous cubic in three variables with rational
coefficients (either as a polynomial ring element or as a
string) defining a smooth plane cubic curve.
- ``P`` -- a 3-tuple `(x,y,z)` defining a projective point on the
curve `F=0`.
OUTPUT:
(elliptic curve) An elliptic curve (in minimal Weierstrass form)
isomorphic to the curve `F=0`.
.. note::
USES MAGMA - This function will not work on computers that
do not have magma installed.
TO DO: implement this without using MAGMA.
For a more general version, see the function
``EllipticCurve_from_plane_curve()``.
EXAMPLES:
First we find that the Fermat cubic is isomorphic to the curve
with Cremona label 27a1::
sage: E = EllipticCurve_from_cubic('x^3 + y^3 + z^3', [1,-1,0]) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 + y = x^3 - 7 over Rational Field
sage: E.cremona_label() # optional - magma
'27a1'
Next we find the minimal model and conductor of the Jacobian of the
Selmer curve.
::
sage: E = EllipticCurve_from_cubic('u^3 + v^3 + 60*w^3', [1,-1,0]) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 = x^3 - 24300 over Rational Field
sage: E.conductor() # optional - magma
24300
"""
from sage.interfaces.all import magma
cmd = "P<%s,%s,%s> := ProjectivePlane(RationalField());" % SR(
F).variables()
magma.eval(cmd)
cmd = 'aInvariants(MinimalModel(EllipticCurve(Curve(Scheme(P, %s)),P!%s)));' % (
F, P)
s = magma.eval(cmd)
return EllipticCurve(rings.RationalField(), eval(s))
def EllipticCurve_from_cubic(F, P):
r"""
Construct an elliptic curve from a ternary cubic with a rational point.
INPUT:
- ``F`` -- a homogeneous cubic in three variables with rational
coefficients (either as a polynomial ring element or as a
string) defining a smooth plane cubic curve.
- ``P`` -- a 3-tuple `(x,y,z)` defining a projective point on the
curve `F=0`.
OUTPUT:
(elliptic curve) An elliptic curve (in minimal Weierstrass form)
isomorphic to the curve `F=0`.
.. note::
USES MAGMA - This function will not work on computers that
do not have magma installed.
TO DO: implement this without using MAGMA.
For a more general version, see the function
``EllipticCurve_from_plane_curve()``.
EXAMPLES:
First we find that the Fermat cubic is isomorphic to the curve
with Cremona label 27a1::
sage: E = EllipticCurve_from_cubic('x^3 + y^3 + z^3', [1,-1,0]) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 + y = x^3 - 7 over Rational Field
sage: E.cremona_label() # optional - magma
'27a1'
Next we find the minimal model and conductor of the Jacobian of the
Selmer curve.
::
sage: E = EllipticCurve_from_cubic('u^3 + v^3 + 60*w^3', [1,-1,0]) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 = x^3 - 24300 over Rational Field
sage: E.conductor() # optional - magma
24300
"""
from sage.interfaces.all import magma
cmd = "P<%s,%s,%s> := ProjectivePlane(RationalField());" % SR(F).variables()
magma.eval(cmd)
cmd = "aInvariants(MinimalModel(EllipticCurve(Curve(Scheme(P, %s)),P!%s)));" % (F, P)
s = magma.eval(cmd)
return EllipticCurve(rings.RationalField(), eval(s))
def matrix_add_ZZ(n=200, min=-9, max=9, system='sage', times=50):
"""
Matrix addition over ZZ
Given an n x n matrix A and B over ZZ with random entries between
``min`` and ``max``, inclusive, compute A + B ``times`` times.
INPUT:
- ``n`` - matrix dimension (default: ``200``)
- ``min`` - minimal value for entries of matrix (default: ``-9``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of experiments (default: ``50``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_add_ZZ(200)
sage: tm = b.matrix_add_ZZ(200, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
B = random_matrix(ZZ, n, n, x=min, y=max+1)
t = cputime()
for z in range(times):
v = A + B
return cputime(t)/times
elif system == 'magma':
code = """
n := %s;
min := %s;
max := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(min,max) : i in [1..n^2]];
B := MatrixAlgebra(IntegerRing(), n)![Random(min,max) : i in [1..n^2]];
t := Cputime();
for z in [1..%s] do
K := A + B;
end for;
s := Cputime(t);
"""%(n,min,max,times)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def vecmat_ZZ(n=300, min=-9, max=9, system='sage', times=200):
"""
Vector matrix multiplication over ZZ.
Given an n x n matrix A over ZZ with random entries
between min and max, inclusive, and v the first row of A,
compute the product v * A.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``min`` - minimal value for entries of matrix (default: ``-9``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of runs (default: ``200``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.vecmat_ZZ(300) # long time
sage: tm = b.vecmat_ZZ(300, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
v = A.row(0)
t = cputime()
for z in range(times):
w = v * A
return cputime(t)/times
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(%s,%s) : i in [1..n^2]];
v := A[1];
t := Cputime();
for z in [1..%s] do
K := v * A;
end for;
s := Cputime(t);
"""%(n,min,max,times)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def MatrixVector_QQ(n=1000,h=100,system='sage',times=1):
"""
Compute product of square ``n`` matrix by random vector with num and
denom bounded by ``h`` the given number of ``times``.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``h`` - numerator and denominator bound (default: ``bnd``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of experiments (default: ``1``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.MatrixVector_QQ(500)
sage: tm = b.MatrixVector_QQ(500, system='magma') # optional - magma
"""
if system=='sage':
V=QQ**n
v=V.random_element(h)
M=random_matrix(QQ,n)
t=cputime()
for i in range(times):
w=M*v
return cputime(t)
elif system == 'magma':
code = """
n:=%s;
h:=%s;
times:=%s;
v:=VectorSpace(RationalField(),n)![Random(h)/(Random(h)+1) : i in [1..n]];
M:=MatrixAlgebra(RationalField(),n)![Random(h)/(Random(h)+1) : i in [1..n^2]];
t := Cputime();
for z in [1..times] do
W:=v*M;
end for;
s := Cputime(t);
"""%(n,h,times)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def matrix_add_ZZ(n=200, min=-9, max=9, system='sage', times=50):
"""
Matrix addition over ZZ
Given an n x n matrix A and B over ZZ with random entries between
``min`` and ``max``, inclusive, compute A + B ``times`` times.
INPUT:
- ``n`` - matrix dimension (default: ``200``)
- ``min`` - minimal value for entries of matrix (default: ``-9``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of experiments (default: ``50``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_add_ZZ(200)
sage: tm = b.matrix_add_ZZ(200, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
B = random_matrix(ZZ, n, n, x=min, y=max+1)
t = cputime()
for z in range(times):
v = A + B
return cputime(t)/times
elif system == 'magma':
code = """
n := %s;
min := %s;
max := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(min,max) : i in [1..n^2]];
B := MatrixAlgebra(IntegerRing(), n)![Random(min,max) : i in [1..n^2]];
t := Cputime();
for z in [1..%s] do
K := A + B;
end for;
s := Cputime(t);
"""%(n,min,max,times)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def vecmat_ZZ(n=300, min=-9, max=9, system='sage', times=200):
"""
Vector matrix multiplication over ZZ.
Given an n x n matrix A over ZZ with random entries
between min and max, inclusive, and v the first row of A,
compute the product v * A.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``min`` - minimal value for entries of matrix (default: ``-9``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of runs (default: ``200``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.vecmat_ZZ(300) # long time
sage: tm = b.vecmat_ZZ(300, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
v = A.row(0)
t = cputime()
for z in range(times):
w = v * A
return cputime(t)/times
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(%s,%s) : i in [1..n^2]];
v := A[1];
t := Cputime();
for z in [1..%s] do
K := v * A;
end for;
s := Cputime(t);
"""%(n,min,max,times)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def MatrixVector_QQ(n=1000,h=100,system='sage',times=1):
"""
Compute product of square ``n`` matrix by random vector with num and
denom bounded by ``h`` the given number of ``times``.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``h`` - numerator and denominator bound (default: ``bnd``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of experiments (default: ``1``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.MatrixVector_QQ(500)
sage: tm = b.MatrixVector_QQ(500, system='magma') # optional - magma
"""
if system=='sage':
V=QQ**n
v=V.random_element(h)
M=random_matrix(QQ,n)
t=cputime()
for i in range(times):
w=M*v
return cputime(t)
elif system == 'magma':
code = """
n:=%s;
h:=%s;
times:=%s;
v:=VectorSpace(RationalField(),n)![Random(h)/(Random(h)+1) : i in [1..n]];
M:=MatrixAlgebra(RationalField(),n)![Random(h)/(Random(h)+1) : i in [1..n^2]];
t := Cputime();
for z in [1..times] do
W:=v*M;
end for;
s := Cputime(t);
"""%(n,h,times)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def matrix_multiply_QQ(n=100, bnd=2, system='sage', times=1):
"""
Given an n x n matrix A over QQ with random entries
whose numerators and denominators are bounded by bnd,
compute A * (A+1).
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``bnd`` - numerator and denominator bound (default: ``bnd``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of experiments (default: ``1``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_multiply_QQ(100)
sage: tm = b.matrix_multiply_QQ(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(QQ, n, n, num_bound=bnd, den_bound=bnd)
B = A + 1
t = cputime()
for z in range(times):
v = A * B
return cputime(t)/times
elif system == 'magma':
A = magma(random_matrix(QQ, n, n, num_bound=bnd, den_bound=bnd))
code = """
n := %s;
A := %s;
B := A + 1;
t := Cputime();
for z in [1..%s] do
K := A * B;
end for;
s := Cputime(t);
"""%(n, A.name(), times)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def matrix_multiply_QQ(n=100, bnd=2, system='sage', times=1):
"""
Given an n x n matrix A over QQ with random entries
whose numerators and denominators are bounded by bnd,
compute A * (A+1).
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``bnd`` - numerator and denominator bound (default: ``bnd``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
- ``times`` - number of experiments (default: ``1``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_multiply_QQ(100)
sage: tm = b.matrix_multiply_QQ(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(QQ, n, n, num_bound=bnd, den_bound=bnd)
B = A + 1
t = cputime()
for z in range(times):
v = A * B
return cputime(t)/times
elif system == 'magma':
A = magma(random_matrix(QQ, n, n, num_bound=bnd, den_bound=bnd))
code = """
n := %s;
A := %s;
B := A + 1;
t := Cputime();
for z in [1..%s] do
K := A * B;
end for;
s := Cputime(t);
"""%(n, A.name(), times)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def matrix_multiply_GF(n=100, p=16411, system='sage', times=3):
"""
Given an n x n matrix A over GF(p) with random entries, compute
A * (A+1).
INPUT:
- ``n`` - matrix dimension (default: 100)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
- ``times`` - number of experiments (default: ``3``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_multiply_GF(100, p=19)
sage: tm = b.matrix_multiply_GF(100, p=19, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n)
B = A + 1
t = cputime()
for n in range(times):
v = A * B
return cputime(t) / times
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
B := A + 1;
t := Cputime();
for z in [1..%s] do
K := A * B;
end for;
s := Cputime(t);
"""%(n,p,times)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def matrix_multiply_GF(n=100, p=16411, system='sage', times=3):
"""
Given an n x n matrix A over GF(p) with random entries, compute
A * (A+1).
INPUT:
- ``n`` - matrix dimension (default: 100)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
- ``times`` - number of experiments (default: ``3``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_multiply_GF(100, p=19)
sage: tm = b.matrix_multiply_GF(100, p=19, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n)
B = A + 1
t = cputime()
for n in range(times):
v = A * B
return cputime(t) / times
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
B := A + 1;
t := Cputime();
for z in [1..%s] do
K := A * B;
end for;
s := Cputime(t);
"""%(n,p,times)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))/times
else:
raise ValueError('unknown system "%s"'%system)
def matrix_add_GF(n=1000, p=16411, system='sage',times=100):
"""
Given two n x n matrix over GF(p) with random entries, add them.
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
- ``times`` - number of experiments (default: ``100``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_add_GF(500, p=19)
sage: tm = b.matrix_add_GF(500, p=19, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n)
B = random_matrix(GF(p), n, n)
t = cputime()
for n in range(times):
v = A + B
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
B := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
for z in [1..%s] do
K := A + B;
end for;
s := Cputime(t);
"""%(n,p,p,times)
if verbose: print(code)
magma.eval(code)
return magma.eval('s')
else:
raise ValueError('unknown system "%s"'%system)
def matrix_add_GF(n=1000, p=16411, system='sage', times=100):
"""
Given two n x n matrix over GF(p) with random entries, add them.
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
- ``times`` - number of experiments (default: ``100``)
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.matrix_add_GF(500, p=19)
sage: tm = b.matrix_add_GF(500, p=19, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n)
B = random_matrix(GF(p), n, n)
t = cputime()
for n in range(times):
v = A + B
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
B := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
for z in [1..%s] do
K := A + B;
end for;
s := Cputime(t);
""" % (n, p, p, times)
if verbose: print code
magma.eval(code)
return magma.eval('s')
else:
raise ValueError('unknown system "%s"' % system)
def nullspace_RDF(n=300, min=0, max=10, system='sage'):
"""
Nullspace over RDF:
Given a n+1 x n matrix over RDF with random entries
between min and max, compute the nullspace.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``min`` - minimal value for entries of matrix (default: ``0``)
- ``max`` - maximal value for entries of matrix (default: `10``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.nullspace_RDF(100) # long time
sage: tm = b.nullspace_RDF(100, system='magma') # optional - magma
"""
if system == 'sage':
from sage.rings.real_double import RDF
A = random_matrix(ZZ, n+1, n, x=min, y=max+1).change_ring(RDF)
t = cputime()
v = A.kernel()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := RMatrixSpace(RealField(16), n+1,n)![Random(%s,%s) : i in [1..n*(n+1)]];
t := Cputime();
K := Kernel(A);
s := Cputime(t);
"""%(n,min,max)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def det_QQ(n=300, num_bound=10, den_bound=10, system='sage'):
"""
Dense rational determinant over QQ.
Given an n x n matrix A over QQ with random entries
with numerator bound and denominator bound, compute det(A).
INPUT:
- ``n`` - matrix dimension (default: ``200``)
- ``num_bound`` - numerator bound, inclusive (default: ``10``)
- ``den_bound`` - denominator bound, inclusive (default: ``10``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.det_QQ(200)
sage: ts = b.det_QQ(10, num_bound=100000, den_bound=10000)
sage: tm = b.det_QQ(200, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(QQ, n, n, num_bound=num_bound, den_bound=den_bound)
t = cputime()
d = A.determinant()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(RationalField(), n)![Random(%s,%s)/Random(1,%s) : i in [1..n^2]];
t := Cputime();
d := Determinant(A);
s := Cputime(t);
"""%(n,-num_bound, num_bound, den_bound)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def nullspace_RDF(n=300, min=0, max=10, system='sage'):
"""
Nullspace over RDF:
Given a n+1 x n matrix over RDF with random entries
between min and max, compute the nullspace.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``min`` - minimal value for entries of matrix (default: ``0``)
- ``max`` - maximal value for entries of matrix (default: `10``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.nullspace_RDF(100) # long time
sage: tm = b.nullspace_RDF(100, system='magma') # optional - magma
"""
if system == 'sage':
from sage.rings.real_double import RDF
A = random_matrix(ZZ, n+1, n, x=min, y=max+1).change_ring(RDF)
t = cputime()
v = A.kernel()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := RMatrixSpace(RealField(16), n+1,n)![Random(%s,%s) : i in [1..n*(n+1)]];
t := Cputime();
K := Kernel(A);
s := Cputime(t);
"""%(n,min,max)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def rank2_ZZ(n=400, min=0, max=2**64, system='sage'):
"""
Rank 2 over ZZ:
Given a (n + 10) x n matrix over ZZ with random entries
between min and max, compute the rank.
INPUT:
- ``n`` - matrix dimension (default: ``400``)
- ``min`` - minimal value for entries of matrix (default: ``0``)
- ``max`` - maximal value for entries of matrix (default: ``2**64``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.rank2_ZZ(300)
sage: tm = b.rank2_ZZ(300, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n+10, n, x=min, y=max+1)
t = cputime()
v = A.rank()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := RMatrixSpace(IntegerRing(), n+10, n)![Random(%s,%s) : i in [1..n*(n+10)]];
t := Cputime();
K := Rank(A);
s := Cputime(t);
"""%(n,min,max)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def smithform_ZZ(n=128, min=0, max=9, system='sage'):
"""
Smith Form over ZZ:
Given a n x n matrix over ZZ with random entries
between min and max, compute the Smith normal form.
INPUT:
- ``n`` - matrix dimension (default: ``128``)
- ``min`` - minimal value for entries of matrix (default: ``0``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.smithform_ZZ(100)
sage: tm = b.smithform_ZZ(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
t = cputime()
v = A.elementary_divisors()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(%s,%s) : i in [1..n^2]];
t := Cputime();
K := ElementaryDivisors(A);
s := Cputime(t);
"""%(n,min,max)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def det_ZZ(n=200, min=1, max=100, system='sage'):
"""
Dense integer determinant over ZZ.
Given an n x n matrix A over ZZ with random entries
between min and max, inclusive, compute det(A).
INPUT:
- ``n`` - matrix dimension (default: ``200``)
- ``min`` - minimal value for entries of matrix (default: ``1``)
- ``max`` - maximal value for entries of matrix (default: ``100``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.det_ZZ(200)
sage: tm = b.det_ZZ(200, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
t = cputime()
d = A.determinant()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(%s,%s) : i in [1..n^2]];
t := Cputime();
d := Determinant(A);
s := Cputime(t);
"""%(n,min,max)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def det_QQ(n=300, num_bound=10, den_bound=10, system='sage'):
"""
Dense rational determinant over QQ.
Given an n x n matrix A over QQ with random entries
with numerator bound and denominator bound, compute det(A).
INPUT:
- ``n`` - matrix dimension (default: ``200``)
- ``num_bound`` - numerator bound, inclusive (default: ``10``)
- ``den_bound`` - denominator bound, inclusive (default: ``10``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.det_QQ(200)
sage: ts = b.det_QQ(10, num_bound=100000, den_bound=10000)
sage: tm = b.det_QQ(200, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(QQ, n, n, num_bound=num_bound, den_bound=den_bound)
t = cputime()
d = A.determinant()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(RationalField(), n)![Random(%s,%s)/Random(1,%s) : i in [1..n^2]];
t := Cputime();
d := Determinant(A);
s := Cputime(t);
"""%(n,-num_bound, num_bound, den_bound)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def det_GF(n=400, p=16411 , system='sage'):
"""
Dense determinant over GF(p).
Given an n x n matrix A over GF with random entries compute
det(A).
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.det_GF(1000)
sage: tm = b.det_GF(1000, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n)
t = cputime()
d = A.determinant()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
d := Determinant(A);
s := Cputime(t);
"""%(n,p)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def inverse_QQ(n=100, min=0, max=9, system='sage'):
"""
Given a n x n matrix over QQ with random integer entries
between min and max, compute the reduced row echelon form.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``min`` - minimal value for entries of matrix (default: ``-9``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.inverse_QQ(100)
sage: tm = b.inverse_QQ(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1).change_ring(QQ)
t = cputime()
v = ~A
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(RationalField(), n)![Random(%s,%s) : i in [1..n*n]];
t := Cputime();
K := A^(-1);
s := Cputime(t);
"""%(n,min,max)
if verbose:
print(code)
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def rank2_ZZ(n=400, min=0, max=2**64, system='sage'):
"""
Rank 2 over ZZ:
Given a (n + 10) x n matrix over ZZ with random entries
between min and max, compute the rank.
INPUT:
- ``n`` - matrix dimension (default: ``400``)
- ``min`` - minimal value for entries of matrix (default: ``0``)
- ``max`` - maximal value for entries of matrix (default: ``2**64``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.rank2_ZZ(300)
sage: tm = b.rank2_ZZ(300, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n+10, n, x=min, y=max+1)
t = cputime()
v = A.rank()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := RMatrixSpace(IntegerRing(), n+10, n)![Random(%s,%s) : i in [1..n*(n+10)]];
t := Cputime();
K := Rank(A);
s := Cputime(t);
"""%(n,min,max)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def smithform_ZZ(n=128, min=0, max=9, system='sage'):
"""
Smith Form over ZZ:
Given a n x n matrix over ZZ with random entries
between min and max, compute the Smith normal form.
INPUT:
- ``n`` - matrix dimension (default: ``128``)
- ``min`` - minimal value for entries of matrix (default: ``0``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.smithform_ZZ(100)
sage: tm = b.smithform_ZZ(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
t = cputime()
v = A.elementary_divisors()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(%s,%s) : i in [1..n^2]];
t := Cputime();
K := ElementaryDivisors(A);
s := Cputime(t);
"""%(n,min,max)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def det_ZZ(n=200, min=1, max=100, system='sage'):
"""
Dense integer determinant over ZZ.
Given an n x n matrix A over ZZ with random entries
between min and max, inclusive, compute det(A).
INPUT:
- ``n`` - matrix dimension (default: ``200``)
- ``min`` - minimal value for entries of matrix (default: ``1``)
- ``max`` - maximal value for entries of matrix (default: ``100``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.det_ZZ(200)
sage: tm = b.det_ZZ(200, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1)
t = cputime()
d = A.determinant()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(IntegerRing(), n)![Random(%s,%s) : i in [1..n^2]];
t := Cputime();
d := Determinant(A);
s := Cputime(t);
"""%(n,min,max)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def det_GF(n=400, p=16411 , system='sage'):
"""
Dense determinant over GF(p).
Given an n x n matrix A over GF with random entries compute
det(A).
INPUT:
- ``n`` - matrix dimension (default: 300)
- ``p`` - prime number (default: ``16411``)
- ``system`` - either 'magma' or 'sage' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.det_GF(1000)
sage: tm = b.det_GF(1000, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(GF(p), n, n)
t = cputime()
d = A.determinant()
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := Random(MatrixAlgebra(GF(%s), n));
t := Cputime();
d := Determinant(A);
s := Cputime(t);
"""%(n,p)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def inverse_QQ(n=100, min=0, max=9, system='sage'):
"""
Given a n x n matrix over QQ with random integer entries
between min and max, compute the reduced row echelon form.
INPUT:
- ``n`` - matrix dimension (default: ``300``)
- ``min`` - minimal value for entries of matrix (default: ``-9``)
- ``max`` - maximal value for entries of matrix (default: ``9``)
- ``system`` - either 'sage' or 'magma' (default: 'sage')
EXAMPLES::
sage: import sage.matrix.benchmark as b
sage: ts = b.inverse_QQ(100)
sage: tm = b.inverse_QQ(100, system='magma') # optional - magma
"""
if system == 'sage':
A = random_matrix(ZZ, n, n, x=min, y=max+1).change_ring(QQ)
t = cputime()
v = ~A
return cputime(t)
elif system == 'magma':
code = """
n := %s;
A := MatrixAlgebra(RationalField(), n)![Random(%s,%s) : i in [1..n*n]];
t := Cputime();
K := A^(-1);
s := Cputime(t);
"""%(n,min,max)
if verbose: print code
magma.eval(code)
return float(magma.eval('s'))
else:
raise ValueError('unknown system "%s"'%system)
def hilbert_class_polynomial(D, algorithm=None):
r"""
Return the Hilbert class polynomial for discriminant `D`.
INPUT:
- ``D`` (int) -- a negative integer congruent to 0 or 1 modulo 4.
- ``algorithm`` (string, default None).
OUTPUT:
(integer polynomial) The Hilbert class polynomial for the
discriminant `D`.
ALGORITHM:
- If ``algorithm`` = "arb" (default): Use Arb's implementation which uses complex interval arithmetic.
- If ``algorithm`` = "sage": Use complex approximations to the roots.
- If ``algorithm`` = "magma": Call the appropriate Magma function (if available).
AUTHORS:
- Sage implementation originally by Eduardo Ocampo Alvarez and
AndreyTimofeev
- Sage implementation corrected by John Cremona (using corrected precision bounds from Andreas Enge)
- Magma implementation by David Kohel
EXAMPLES::
sage: hilbert_class_polynomial(-4)
x - 1728
sage: hilbert_class_polynomial(-7)
x + 3375
sage: hilbert_class_polynomial(-23)
x^3 + 3491750*x^2 - 5151296875*x + 12771880859375
sage: hilbert_class_polynomial(-37*4)
x^2 - 39660183801072000*x - 7898242515936467904000000
sage: hilbert_class_polynomial(-37*4, algorithm="magma") # optional - magma
x^2 - 39660183801072000*x - 7898242515936467904000000
sage: hilbert_class_polynomial(-163)
x + 262537412640768000
sage: hilbert_class_polynomial(-163, algorithm="sage")
x + 262537412640768000
sage: hilbert_class_polynomial(-163, algorithm="magma") # optional - magma
x + 262537412640768000
TESTS::
sage: all([hilbert_class_polynomial(d, algorithm="arb") == \
....: hilbert_class_polynomial(d, algorithm="sage") \
....: for d in range(-1,-100,-1) if d%4 in [0,1]])
True
"""
if algorithm is None:
algorithm = "arb"
D = Integer(D)
if D >= 0:
raise ValueError("D (=%s) must be negative" % D)
if not (D % 4 in [0, 1]):
raise ValueError("D (=%s) must be a discriminant" % D)
if algorithm == "arb":
import sage.libs.arb.arith
return sage.libs.arb.arith.hilbert_class_polynomial(D)
if algorithm == "magma":
magma.eval("R<x> := PolynomialRing(IntegerRing())")
f = str(magma.eval("HilbertClassPolynomial(%s)" % D))
return IntegerRing()['x'](f)
if algorithm != "sage":
raise ValueError("%s is not a valid algorithm" % algorithm)
from sage.quadratic_forms.binary_qf import BinaryQF_reduced_representatives
from sage.rings.all import RR, ComplexField
from sage.functions.all import elliptic_j
# get all primitive reduced quadratic forms, (necessary to exclude
# imprimitive forms when D is not a fundamental discriminant):
rqf = BinaryQF_reduced_representatives(D, primitive_only=True)
# compute needed precision
#
# NB: [https://arxiv.org/abs/0802.0979v1], quoting Enge (2006), is
# incorrect. Enge writes (2009-04-20 email to John Cremona) "The
# source is my paper on class polynomials
# [https://hal.inria.fr/inria-00001040] It was pointed out to me by
# the referee after ANTS that the constant given there was
# wrong. The final version contains a corrected constant on p.7
# which is consistent with your example. It says:
# "The logarithm of the absolute value of the coefficient in front
# of X^j is bounded above by
#
# log (2*k_2) * h + pi * sqrt(|D|) * sum (1/A_i)
#
# independently of j", where k_2 \approx 10.163.
h = len(rqf) # class number
c1 = 3.05682737291380 # log(2*10.63)
c2 = sum([1 / RR(qf[0]) for qf in rqf], RR(0))
prec = c2 * RR(3.142) * RR(D).abs().sqrt() + h * c1 # bound on log
prec = prec * 1.45 # bound on log_2 (1/log(2) = 1.44..)
prec = 10 + prec.ceil() # allow for rounding error
# set appropriate precision for further computing
Dsqrt = D.sqrt(prec=prec)
R = ComplexField(prec)['t']
t = R.gen()
pol = R(1)
for qf in rqf:
a, b, c = list(qf)
tau = (b + Dsqrt) / (a << 1)
pol *= (t - elliptic_j(tau))
coeffs = [cof.real().round() for cof in pol.coefficients(sparse=False)]
return IntegerRing()['x'](coeffs)
def hilbert_class_polynomial(D, algorithm=None):
r"""
Returns the Hilbert class polynomial for discriminant `D`.
INPUT:
- ``D`` (int) -- a negative integer congruent to 0 or 1 modulo 4.
- ``algorithm`` (string, default None).
OUTPUT:
(integer polynomial) The Hilbert class polynomial for the
discriminant `D`.
ALGORITHM:
- If ``algorithm`` = "arb" (default): Use Arb's implementation which uses complex interval arithmetic.
- If ``algorithm`` = "sage": Use complex approximations to the roots.
- If ``algorithm`` = "magma": Call the appropriate Magma function (if available).
AUTHORS:
- Sage implementation originally by Eduardo Ocampo Alvarez and
AndreyTimofeev
- Sage implementation corrected by John Cremona (using corrected precision bounds from Andreas Enge)
- Magma implementation by David Kohel
EXAMPLES::
sage: hilbert_class_polynomial(-4)
x - 1728
sage: hilbert_class_polynomial(-7)
x + 3375
sage: hilbert_class_polynomial(-23)
x^3 + 3491750*x^2 - 5151296875*x + 12771880859375
sage: hilbert_class_polynomial(-37*4)
x^2 - 39660183801072000*x - 7898242515936467904000000
sage: hilbert_class_polynomial(-37*4, algorithm="magma") # optional - magma
x^2 - 39660183801072000*x - 7898242515936467904000000
sage: hilbert_class_polynomial(-163)
x + 262537412640768000
sage: hilbert_class_polynomial(-163, algorithm="sage")
x + 262537412640768000
sage: hilbert_class_polynomial(-163, algorithm="magma") # optional - magma
x + 262537412640768000
TESTS::
sage: all([hilbert_class_polynomial(d, algorithm="arb") == \
....: hilbert_class_polynomial(d, algorithm="sage") \
....: for d in range(-1,-100,-1) if d%4 in [0,1]])
True
"""
if algorithm is None:
algorithm = "arb"
D = Integer(D)
if D >= 0:
raise ValueError("D (=%s) must be negative"%D)
if not (D%4 in [0,1]):
raise ValueError("D (=%s) must be a discriminant"%D)
if algorithm == "arb":
import sage.libs.arb.arith
return sage.libs.arb.arith.hilbert_class_polynomial(D)
if algorithm == "magma":
magma.eval("R<x> := PolynomialRing(IntegerRing())")
f = str(magma.eval("HilbertClassPolynomial(%s)"%D))
return IntegerRing()['x'](f)
if algorithm != "sage":
raise ValueError("%s is not a valid algorithm"%algorithm)
from sage.quadratic_forms.binary_qf import BinaryQF_reduced_representatives
from sage.rings.all import RR, ZZ, ComplexField
from sage.functions.all import elliptic_j
# get all primitive reduced quadratic forms, (necessary to exclude
# imprimitive forms when D is not a fundamental discriminant):
rqf = BinaryQF_reduced_representatives(D, primitive_only=True)
# compute needed precision
#
# NB: [http://arxiv.org/abs/0802.0979v1], quoting Enge (2006), is
# incorrect. Enge writes (2009-04-20 email to John Cremona) "The
# source is my paper on class polynomials
# [http://hal.inria.fr/inria-00001040] It was pointed out to me by
# the referee after ANTS that the constant given there was
# wrong. The final version contains a corrected constant on p.7
# which is consistent with your example. It says:
# "The logarithm of the absolute value of the coefficient in front
# of X^j is bounded above by
#
# log (2*k_2) * h + pi * sqrt(|D|) * sum (1/A_i)
#
# independently of j", where k_2 \approx 10.163.
h = len(rqf) # class number
c1 = 3.05682737291380 # log(2*10.63)
c2 = sum([1/RR(qf[0]) for qf in rqf], RR(0))
prec = c2*RR(3.142)*RR(D).abs().sqrt() + h*c1 # bound on log
prec = prec * 1.45 # bound on log_2 (1/log(2) = 1.44..)
prec = 10 + prec.ceil() # allow for rounding error
# set appropriate precision for further computing
Dsqrt = D.sqrt(prec=prec)
R = ComplexField(prec)['t']
t = R.gen()
pol = R(1)
for qf in rqf:
a, b, c = list(qf)
tau = (b+Dsqrt)/(a<<1)
pol *= (t - elliptic_j(tau))
coeffs = [cof.real().round() for cof in pol.coefficients(sparse=False)]
return IntegerRing()['x'](coeffs)
def EllipticCurve_from_plane_curve(C, P):
r"""
Construct an elliptic curve from a smooth plane cubic with a rational point.
INPUT:
- ``C`` -- a plane curve of genus one.
- ``P`` -- a 3-tuple `(x,y,z)` defining a projective point on the
curve ``C``.
OUTPUT:
(elliptic curve) An elliptic curve (in minimal Weierstrass form)
isomorphic to ``C``.
.. note::
USES MAGMA - This function will not work on computers that
do not have magma installed.
TO DO: implement this without using MAGMA.
EXAMPLES:
First we check that the Fermat cubic is isomorphic to the curve
with Cremona label '27a1'::
sage: x,y,z=PolynomialRing(QQ,3,'xyz').gens() # optional - magma
sage: C=Curve(x^3+y^3+z^3) # optional - magma
sage: P=C(1,-1,0) # optional - magma
sage: E=EllipticCurve_from_plane_curve(C,P) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 + y = x^3 - 7 over Rational Field
sage: E.label() # optional - magma
'27a1'
Now we try a quartic example::
sage: u,v,w=PolynomialRing(QQ,3,'uvw').gens() # optional - magma
sage: C=Curve(u^4+u^2*v^2-w^4) # optional - magma
sage: P=C(1,0,1) # optional - magma
sage: E=EllipticCurve_from_plane_curve(C,P) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 = x^3 + 4*x over Rational Field
sage: E.label() # optional - magma
'32a1'
"""
from sage.interfaces.all import magma
if C.genus()!=1:
raise TypeError, "The curve C must have genus 1"
elif P.parent()!=C.point_set(C.base_ring()):
raise TypeError, "The point P must be on the curve C"
dp=C.defining_polynomial()
x,y,z = dp.parent().variable_names()
cmd = "PR<%s,%s,%s>:=ProjectivePlane(RationalField());"%(x,y,z)
magma.eval(cmd)
cmd = 'CC:=Curve(PR, %s);'%(dp)
magma.eval(cmd)
cmd='aInvariants(MinimalModel(EllipticCurve(CC,CC!%s)));'%([P[0],P[1],P[2]])
s=magma.eval(cmd)
return EllipticCurve(rings.RationalField(), eval(s))
def EllipticCurve_from_plane_curve(C, P):
r"""
Construct an elliptic curve from a smooth plane cubic with a rational point.
INPUT:
- ``C`` -- a plane curve of genus one.
- ``P`` -- a 3-tuple `(x,y,z)` defining a projective point on the
curve ``C``.
OUTPUT:
(elliptic curve) An elliptic curve (in minimal Weierstrass form)
isomorphic to ``C``.
.. note::
USES MAGMA - This function will not work on computers that
do not have magma installed.
TO DO: implement this without using MAGMA.
EXAMPLES:
First we check that the Fermat cubic is isomorphic to the curve
with Cremona label '27a1'::
sage: x,y,z=PolynomialRing(QQ,3,'xyz').gens() # optional - magma
sage: C=Curve(x^3+y^3+z^3) # optional - magma
sage: P=C(1,-1,0) # optional - magma
sage: E=EllipticCurve_from_plane_curve(C,P) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 + y = x^3 - 7 over Rational Field
sage: E.label() # optional - magma
'27a1'
Now we try a quartic example::
sage: u,v,w=PolynomialRing(QQ,3,'uvw').gens() # optional - magma
sage: C=Curve(u^4+u^2*v^2-w^4) # optional - magma
sage: P=C(1,0,1) # optional - magma
sage: E=EllipticCurve_from_plane_curve(C,P) # optional - magma
sage: E # optional - magma
Elliptic Curve defined by y^2 = x^3 + 4*x over Rational Field
sage: E.label() # optional - magma
'32a1'
"""
from sage.interfaces.all import magma
if C.genus() != 1:
raise TypeError, "The curve C must have genus 1"
elif P.parent() != C.point_set(C.base_ring()):
raise TypeError, "The point P must be on the curve C"
dp = C.defining_polynomial()
x, y, z = dp.parent().variable_names()
cmd = "PR<%s,%s,%s>:=ProjectivePlane(RationalField());" % (x, y, z)
magma.eval(cmd)
cmd = 'CC:=Curve(PR, %s);' % (dp)
magma.eval(cmd)
cmd = 'aInvariants(MinimalModel(EllipticCurve(CC,CC!%s)));' % (
[P[0], P[1], P[2]])
s = magma.eval(cmd)
return EllipticCurve(rings.RationalField(), eval(s))