def test_DomainMatrix_init():
A = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
assert A.rep == DDM([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
assert A.shape == (2, 2)
assert A.domain == ZZ
raises(DDMBadInputError, lambda: DomainMatrix([[ZZ(1), ZZ(2)]], (2, 2), ZZ))
def test_DomainMatrix_from_Matrix():
sdm = SDM({0: {0: ZZ(1), 1: ZZ(2)}, 1: {0: ZZ(3), 1: ZZ(4)}}, (2, 2), ZZ)
A = DomainMatrix.from_Matrix(Matrix([[1, 2], [3, 4]]))
assert A.rep == sdm
assert A.shape == (2, 2)
assert A.domain == ZZ
K = QQ.algebraic_field(sqrt(2))
sdm = SDM(
{
0: {
0: K.convert(1 + sqrt(2)),
1: K.convert(2 + sqrt(2))
},
1: {
0: K.convert(3 + sqrt(2)),
1: K.convert(4 + sqrt(2))
}
}, (2, 2), K)
A = DomainMatrix.from_Matrix(Matrix([[1 + sqrt(2), 2 + sqrt(2)],
[3 + sqrt(2), 4 + sqrt(2)]]),
extension=True)
assert A.rep == sdm
assert A.shape == (2, 2)
assert A.domain == K
A = DomainMatrix.from_Matrix(Matrix([[QQ(1, 2), QQ(3, 4)],
[QQ(0, 1), QQ(0, 1)]]),
fmt='dense')
ddm = DDM([[QQ(1, 2), QQ(3, 4)], [QQ(0, 1), QQ(0, 1)]], (2, 2), QQ)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == QQ
def test_dom_eigenvects_algebraic():
# Algebraic eigenvalues
A = DomainMatrix([[QQ(1), QQ(2)], [QQ(3), QQ(4)]], (2, 2), QQ)
Avects = dom_eigenvects(A)
# Extract the dummy to build the expected result:
lamda = Avects[1][0][1].gens[0]
irreducible = Poly(lamda**2 - 5 * lamda - 2, lamda, domain=QQ)
K = FiniteExtension(irreducible)
KK = K.from_sympy
algebraic_eigenvects = [
(K, irreducible, 1,
DomainMatrix([[KK((lamda - 4) / 3), KK(1)]], (1, 2), K)),
]
assert Avects == ([], algebraic_eigenvects)
# Test converting to Expr:
sympy_eigenvects = [
(S(5) / 2 - sqrt(33) / 2, 1,
[Matrix([[-sqrt(33) / 6 - S(1) / 2], [1]])]),
(S(5) / 2 + sqrt(33) / 2, 1,
[Matrix([[-S(1) / 2 + sqrt(33) / 6], [1]])]),
]
assert dom_eigenvects_to_sympy([], algebraic_eigenvects,
Matrix) == sympy_eigenvects
def test_dom_eigenvects_rootof():
# Algebraic eigenvalues
A = DomainMatrix([[0, 0, 0, 0, -1], [1, 0, 0, 0, 1], [0, 1, 0, 0, 0],
[0, 0, 1, 0, 0], [0, 0, 0, 1, 0]], (5, 5), QQ)
Avects = dom_eigenvects(A)
# Extract the dummy to build the expected result:
lamda = Avects[1][0][1].gens[0]
irreducible = Poly(lamda**5 - lamda + 1, lamda, domain=QQ)
K = FiniteExtension(irreducible)
KK = K.from_sympy
algebraic_eigenvects = [
(K, irreducible, 1,
DomainMatrix(
[[KK(lamda**4 - 1),
KK(lamda**3),
KK(lamda**2),
KK(lamda),
KK(1)]], (1, 5), K)),
]
assert Avects == ([], algebraic_eigenvects)
# Test converting to Expr (slow):
l0, l1, l2, l3, l4 = [CRootOf(lamda**5 - lamda + 1, i) for i in range(5)]
sympy_eigenvects = [
(l0, 1, [Matrix([-1 + l0**4, l0**3, l0**2, l0, 1])]),
(l1, 1, [Matrix([-1 + l1**4, l1**3, l1**2, l1, 1])]),
(l2, 1, [Matrix([-1 + l2**4, l2**3, l2**2, l2, 1])]),
(l3, 1, [Matrix([-1 + l3**4, l3**3, l3**2, l3, 1])]),
(l4, 1, [Matrix([-1 + l4**4, l4**3, l4**2, l4, 1])]),
]
assert dom_eigenvects_to_sympy([], algebraic_eigenvects,
Matrix) == sympy_eigenvects
def test_DomainMatrix_eq():
A = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
assert A == A
B = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(1)]], (2, 2), ZZ)
assert A != B
C = [[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]]
assert A != C
def test_DomainMatrix_get_domain():
K, items = DomainMatrix.get_domain([1, 2, 3, 4])
assert items == [ZZ(1), ZZ(2), ZZ(3), ZZ(4)]
assert K == ZZ
K, items = DomainMatrix.get_domain([1, 2, 3, Rational(1, 2)])
assert items == [QQ(1), QQ(2), QQ(3), QQ(1, 2)]
assert K == QQ
def test_DomainMatrix_to_dok():
A = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
assert A.to_dok() == {
(0, 0): ZZ(1),
(0, 1): ZZ(2),
(1, 0): ZZ(3),
(1, 1): ZZ(4)
}
def test_DomainMatrix_setitem():
dM = DomainMatrix({2: {2: ZZ(1)}, 4: {4: ZZ(1)}}, (5, 5), ZZ)
dM[2, 2] = ZZ(2)
assert dM == DomainMatrix({2: {2: ZZ(2)}, 4: {4: ZZ(1)}}, (5, 5), ZZ)
def setitem(i, j, val):
dM[i, j] = val
raises(TypeError, lambda: setitem(2, 2, QQ(1, 2)))
raises(NotImplementedError, lambda: setitem(slice(1, 2), 2, ZZ(1)))
def test_DomainMatrix_scalarmul():
A = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
lamda = DomainScalar(QQ(3)/QQ(2), QQ)
assert A * lamda == DomainMatrix([[QQ(3, 2), QQ(3)], [QQ(9, 2), QQ(6)]], (2, 2), QQ)
assert A * 2 == DomainMatrix([[ZZ(2), ZZ(4)], [ZZ(6), ZZ(8)]], (2, 2), ZZ)
assert A * DomainScalar(ZZ(0), ZZ) == DomainMatrix([[ZZ(0)]*2]*2, (2, 2), ZZ)
assert A * DomainScalar(ZZ(1), ZZ) == A
raises(TypeError, lambda: A * 1.5)
def test_DomainMatrix_scc():
Ad = DomainMatrix(
[[ZZ(1), ZZ(2), ZZ(3)], [ZZ(0), ZZ(1), ZZ(0)],
[ZZ(2), ZZ(0), ZZ(4)]], (3, 3), ZZ)
As = Ad.to_sparse()
Addm = Ad.rep
Asdm = As.rep
for A in [Ad, As, Addm, Asdm]:
assert Ad.scc() == [[1], [0, 2]]
def test_DomainMatrix_init():
lol = [[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]]
dod = {0: {0: ZZ(1), 1: ZZ(2)}, 1: {0: ZZ(3), 1: ZZ(4)}}
ddm = DDM(lol, (2, 2), ZZ)
sdm = SDM(dod, (2, 2), ZZ)
A = DomainMatrix(lol, (2, 2), ZZ)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == ZZ
A = DomainMatrix(dod, (2, 2), ZZ)
assert A.rep == sdm
assert A.shape == (2, 2)
assert A.domain == ZZ
raises(TypeError, lambda: DomainMatrix(ddm, (2, 2), ZZ))
raises(TypeError, lambda: DomainMatrix(sdm, (2, 2), ZZ))
raises(TypeError, lambda: DomainMatrix(Matrix([[1]]), (1, 1), ZZ))
for fmt, rep in [('sparse', sdm), ('dense', ddm)]:
A = DomainMatrix(lol, (2, 2), ZZ, fmt=fmt)
assert A.rep == rep
A = DomainMatrix(dod, (2, 2), ZZ, fmt=fmt)
assert A.rep == rep
raises(ValueError, lambda: DomainMatrix(lol, (2, 2), ZZ, fmt='invalid'))
raises(DMBadInputError, lambda: DomainMatrix([[ZZ(1), ZZ(2)]], (2, 2), ZZ))
def test_DomainMatrix_truediv():
A = DomainMatrix.from_Matrix(Matrix([[1, 2], [3, 4]]))
lamda = DomainScalar(QQ(3) / QQ(2), QQ)
assert A / lamda == DomainMatrix(
{
0: {
0: QQ(2, 3),
1: QQ(4, 3)
},
1: {
0: QQ(2),
1: QQ(8, 3)
}
}, (2, 2), QQ)
b = DomainScalar(ZZ(1), ZZ)
assert A / b == DomainMatrix(
{
0: {
0: QQ(1),
1: QQ(2)
},
1: {
0: QQ(3),
1: QQ(4)
}
}, (2, 2), QQ)
assert A / 1 == DomainMatrix(
{
0: {
0: QQ(1),
1: QQ(2)
},
1: {
0: QQ(3),
1: QQ(4)
}
}, (2, 2), QQ)
assert A / 2 == DomainMatrix(
{
0: {
0: QQ(1, 2),
1: QQ(1)
},
1: {
0: QQ(3, 2),
1: QQ(2)
}
}, (2, 2), QQ)
raises(ZeroDivisionError, lambda: A / 0)
raises(TypeError, lambda: A / 1.5)
raises(ZeroDivisionError, lambda: A / DomainScalar(ZZ(0), ZZ))
def test_DomainMatrix_solve():
# XXX: Maybe the _solve method should be changed...
A = DomainMatrix([[QQ(1), QQ(2)], [QQ(2), QQ(4)]], (2, 2), QQ)
b = DomainMatrix([[QQ(1)], [QQ(2)]], (2, 1), QQ)
particular = DomainMatrix([[1, 0]], (1, 2), QQ)
nullspace = DomainMatrix([[-2, 1]], (1, 2), QQ)
assert A._solve(b) == (particular, nullspace)
b3 = DomainMatrix([[QQ(1)], [QQ(1)], [QQ(1)]], (3, 1), QQ)
raises(DMShapeError, lambda: A._solve(b3))
bz = DomainMatrix([[ZZ(1)], [ZZ(1)]], (2, 1), ZZ)
raises(DMNotAField, lambda: A._solve(bz))
def test_DomainMatrix_from_rep():
ddm = DDM([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
A = DomainMatrix.from_rep(ddm)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == ZZ
sdm = SDM({0: {0: ZZ(1), 1: ZZ(2)}, 1: {0: ZZ(3), 1: ZZ(4)}}, (2, 2), ZZ)
A = DomainMatrix.from_rep(sdm)
assert A.rep == sdm
assert A.shape == (2, 2)
assert A.domain == ZZ
A = DomainMatrix([[ZZ(1)]], (1, 1), ZZ)
raises(TypeError, lambda: DomainMatrix.from_rep(A))
def test_DomainMatrix_from_rep():
# ddm = DDM([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
ddm = SDM({0: {0: ZZ(1), 1: ZZ(2)}, 1: {0: ZZ(3), 1: ZZ(4)}}, (2, 2), ZZ)
A = DomainMatrix.from_rep(ddm)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == ZZ
def test_dom_eigenvects_rational():
# Rational eigenvalues
A = DomainMatrix([[QQ(1), QQ(2)], [QQ(1), QQ(2)]], (2, 2), QQ)
rational_eigenvects = [
(QQ, QQ(3), 1, DomainMatrix([[QQ(1), QQ(1)]], (1, 2), QQ)),
(QQ, QQ(0), 1, DomainMatrix([[QQ(-2), QQ(1)]], (1, 2), QQ)),
]
assert dom_eigenvects(A) == (rational_eigenvects, [])
# Test converting to Expr:
sympy_eigenvects = [
(S(3), 1, [Matrix([1, 1])]),
(S(0), 1, [Matrix([-2, 1])]),
]
assert dom_eigenvects_to_sympy(rational_eigenvects, [],
Matrix) == sympy_eigenvects
def test_DomainMatrix_from_Matrix():
ddm = DDM([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
A = DomainMatrix.from_Matrix(Matrix([[1, 2], [3, 4]]))
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == ZZ
K = QQ.algebraic_field(sqrt(2))
ddm = DDM([[
K.convert(1 + sqrt(2)), K.convert(2 + sqrt(2))
], [K.convert(3 + sqrt(2)), K.convert(4 + sqrt(2))]], (2, 2), K)
A = DomainMatrix.from_Matrix(Matrix([[1 + sqrt(2), 2 + sqrt(2)],
[3 + sqrt(2), 4 + sqrt(2)]]),
extension=True)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == K
def test_DomainMatrix_rowspace():
A = DomainMatrix(
[[QQ(1), QQ(-1), QQ(1)], [QQ(2), QQ(-2), QQ(3)]], (2, 3), QQ)
assert A.rowspace() == A
Az = DomainMatrix(
[[ZZ(1), ZZ(-1), ZZ(1)], [ZZ(2), ZZ(-2), ZZ(3)]], (2, 3), ZZ)
raises(DMNotAField, lambda: Az.rowspace())
A = DomainMatrix(
[[QQ(1), QQ(-1), QQ(1)], [QQ(2), QQ(-2), QQ(3)]], (2, 3),
QQ,
fmt='sparse')
assert A.rowspace() == A
def test_DomainMatrix_nullspace():
A = DomainMatrix([[QQ(1), QQ(1)], [QQ(1), QQ(1)]], (2, 2), QQ)
Anull = DomainMatrix([[QQ(-1), QQ(1)]], (1, 2), QQ)
assert A.nullspace() == Anull
Az = DomainMatrix([[ZZ(1), ZZ(1)], [ZZ(1), ZZ(1)]], (2, 2), ZZ)
raises(DMNotAField, lambda: Az.nullspace())
def test_DomainScalar_mul():
A = DomainScalar(ZZ(1), ZZ)
B = DomainScalar(QQ(2), QQ)
dm = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
assert A * B == DomainScalar(QQ(2), QQ)
assert A * dm == dm
assert B * 2 == DomainScalar(QQ(4), QQ)
raises(TypeError, lambda: A * 1.5)
def test_DomainMatrix_unify_eq():
A = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
B1 = DomainMatrix([[QQ(1), QQ(2)], [QQ(3), QQ(4)]], (2, 2), QQ)
B2 = DomainMatrix([[QQ(1), QQ(3)], [QQ(3), QQ(4)]], (2, 2), QQ)
B3 = DomainMatrix([[ZZ(1)]], (1, 1), ZZ)
assert A.unify_eq(B1) is True
assert A.unify_eq(B2) is False
assert A.unify_eq(B3) is False
def test_DomainMatrix_from_list():
ddm = DDM([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
A = DomainMatrix.from_list([[1, 2], [3, 4]], ZZ)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == ZZ
dom = FF(7)
ddm = DDM([[dom(1), dom(2)], [dom(3), dom(4)]], (2, 2), dom)
A = DomainMatrix.from_list([[1, 2], [3, 4]], dom)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == dom
ddm = DDM([[QQ(1, 2), QQ(3, 1)], [QQ(1, 4), QQ(5, 1)]], (2, 2), QQ)
A = DomainMatrix.from_list([[(1, 2), (3, 1)], [(1, 4), (5, 1)]], QQ)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == QQ
def test_DomainMatrix_pow():
eye = DomainMatrix.eye(2, ZZ)
A = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
A2 = DomainMatrix([[ZZ(7), ZZ(10)], [ZZ(15), ZZ(22)]], (2, 2), ZZ)
A3 = DomainMatrix([[ZZ(37), ZZ(54)], [ZZ(81), ZZ(118)]], (2, 2), ZZ)
assert A**0 == A.pow(0) == eye
assert A**1 == A.pow(1) == A
assert A**2 == A.pow(2) == A2
assert A**3 == A.pow(3) == A3
raises(TypeError, lambda: A**Rational(1, 2))
raises(NotImplementedError, lambda: A**-1)
raises(NotImplementedError, lambda: A.pow(-1))
A = DomainMatrix.zeros((2, 1), ZZ)
raises(DMNonSquareMatrixError, lambda: A**1)
def test_DomainMatrix_from_list_sympy():
# ddm = DDM([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
ddm = SDM({0: {0: ZZ(1), 1: ZZ(2)}, 1: {0: ZZ(3), 1: ZZ(4)}}, (2, 2), ZZ)
A = DomainMatrix.from_list_sympy(2, 2, [[1, 2], [3, 4]])
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == ZZ
K = QQ.algebraic_field(sqrt(2))
ddm = DDM([[
K.convert(1 + sqrt(2)), K.convert(2 + sqrt(2))
], [K.convert(3 + sqrt(2)), K.convert(4 + sqrt(2))]], (2, 2), K)
ddm = SDM.from_ddm(ddm)
A = DomainMatrix.from_list_sympy(
2,
2, [[1 + sqrt(2), 2 + sqrt(2)], [3 + sqrt(2), 4 + sqrt(2)]],
extension=True)
assert A.rep == ddm
assert A.shape == (2, 2)
assert A.domain == K
def test_DomainMatrix_from_dict_sympy():
sdm = SDM({0: {0: QQ(1, 2)}, 1: {1: QQ(2, 3)}}, (2, 2), QQ)
sympy_dict = {0: {0: Rational(1, 2)}, 1: {1: Rational(2, 3)}}
A = DomainMatrix.from_dict_sympy(2, 2, sympy_dict)
assert A.rep == sdm
assert A.shape == (2, 2)
assert A.domain == QQ
fds = DomainMatrix.from_dict_sympy
raises(DMBadInputError, lambda: fds(2, 2, {3: {0: Rational(1, 2)}}))
raises(DMBadInputError, lambda: fds(2, 2, {0: {3: Rational(1, 2)}}))
def test_DomainMatrix_vstack():
A = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
B = DomainMatrix([[ZZ(5), ZZ(6)], [ZZ(7), ZZ(8)]], (2, 2), ZZ)
C = DomainMatrix([[ZZ(9), ZZ(10)], [ZZ(11), ZZ(12)]], (2, 2), ZZ)
AB = DomainMatrix(
[[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)], [ZZ(5), ZZ(6)], [ZZ(7), ZZ(8)]],
(4, 2), ZZ)
ABC = DomainMatrix(
[[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)], [ZZ(5), ZZ(6)], [ZZ(7), ZZ(8)],
[ZZ(9), ZZ(10)], [ZZ(11), ZZ(12)]], (6, 2), ZZ)
assert A.vstack(B) == AB
assert A.vstack(B, C) == ABC
def test_DomainMatrix_unify():
Az = DomainMatrix([[ZZ(1), ZZ(2)], [ZZ(3), ZZ(4)]], (2, 2), ZZ)
Aq = DomainMatrix([[QQ(1), QQ(2)], [QQ(3), QQ(4)]], (2, 2), QQ)
assert Az.unify(Az) == (Az, Az)
assert Az.unify(Aq) == (Aq, Aq)
assert Aq.unify(Az) == (Aq, Aq)
assert Aq.unify(Aq) == (Aq, Aq)
def test_DomainMatrix_from_dict_sympy():
sdm = SDM({0: {0: QQ(1, 2)}, 1: {1: QQ(2, 3)}}, (2, 2), QQ)
A = DomainMatrix.from_dict_sympy(2, 2, {
0: {
0: QQ(1, 2)
},
1: {
1: QQ(2, 3)
}
})
assert A.rep == sdm
assert A.shape == (2, 2)
assert A.domain == QQ
def _compute_test_factor(p, gens, ZK):
r"""
Compute the test factor for a :py:class:`~.PrimeIdeal` $\mathfrak{p}$.
Parameters
==========
p : int
The rational prime $\mathfrak{p}$ divides
gens : list of :py:class:`PowerBasisElement`
A complete set of generators for $\mathfrak{p}$ over *ZK*, EXCEPT that
an element equivalent to rational *p* can and should be omitted (since
it has no effect except to waste time).
ZK : :py:class:`~.Submodule`
The maximal order where the prime ideal $\mathfrak{p}$ lives.
Returns
=======
:py:class:`~.PowerBasisElement`
References
==========
.. [1] Cohen, H. *A Course in Computational Algebraic Number Theory.*
(See Proposition 4.8.15.)
"""
_check_formal_conditions_for_maximal_order(ZK)
E = ZK.endomorphism_ring()
matrices = [E.inner_endomorphism(g).matrix(modulus=p) for g in gens]
B = DomainMatrix.zeros((0, ZK.n), FF(p)).vstack(*matrices)
# A nonzero element of the nullspace of B will represent a
# lin comb over the omegas which (i) is not a multiple of p
# (since it is nonzero over FF(p)), while (ii) is such that
# its product with each g in gens _is_ a multiple of p (since
# B represents multiplication by these generators). Theory
# predicts that such an element must exist, so nullspace should
# be non-trivial.
x = B.nullspace()[0, :].transpose()
beta = ZK.parent(ZK.matrix * x, denom=ZK.denom)
return beta
def _det_DOM(M):
DOM = DomainMatrix.from_Matrix(M, field=True, extension=True)
K = DOM.domain
return K.to_sympy(DOM.det())
